diff --git a/.github/workflows/black.yml b/.github/workflows/black.yml
index 96aaea347..a022a6634 100644
--- a/.github/workflows/black.yml
+++ b/.github/workflows/black.yml
@@ -8,17 +8,27 @@ jobs:
 
     steps:
       - name: Check out code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
+
+      - name: Get changed Python files
+        id: changed-py-files
+        uses: tj-actions/changed-files@v47
+        with:
+          files: |
+            **.py
 
       - name: Set up Python
-        uses: actions/setup-python@v2
+        if: steps.changed-py-files.outputs.any_changed == 'true'
+        uses: actions/setup-python@v6
         with:
           python-version: "3.11"
 
       - name: Install Black
+        if: steps.changed-py-files.outputs.any_changed == 'true'
         run: |
           python -m pip install --upgrade pip
           pip install black
 
       - name: Check Black Formatting
-        run: black --check .
+        if: steps.changed-py-files.outputs.any_changed == 'true'
+        run: black --check ${{ steps.changed-py-files.outputs.all_changed_files }}
diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index ba7925a8f..7ca82b44d 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -1,4 +1,4 @@
-name: Py 3.10, 3.11, 3.12 | Windows Mac Linux
+name: Py 3.10, 3.11, 3.12, 3.13 | Windows Mac Linux
 
 on:
   pull_request:
@@ -10,7 +10,25 @@ on:
       - main
       - develop
 
+# Global configuration for all jobs. Can be overridden at the job level if needed.
+env:
+  # Conda channels: Set conda forge as only channel and disable defaults channel
+  CONDA_MINICONDA_VERSION: latest
+  CONDA_AUTO_UPDATE_CONDA: true
+  CONDA_CHANNELS: conda-forge
+  CONDA_REMOVE_DEFAULTS: true
+  CONDA_USE_ONLY_TAR_BZ2: false
+  CONDA_ENVIRONMENT_FILE: environment-dev.yml
+  CONDA_ENVIRONMENT_NAME: mhkit-dev-env
+  # Coveralls: Set to false to ignore upload failures during outages.
+  #   Check status: https://status.coveralls.io/
+  COVERALLS_FAIL_ON_ERROR: true
+
 jobs:
+  # Set the operating system matrix for the following jobs/tests
+  # conda-forge-build
+  # pip-build
+  # hindcast-calls
   set-os:
     runs-on: ubuntu-latest
     outputs:
@@ -24,6 +42,8 @@ jobs:
             echo "matrix_os=[\"windows-latest\", \"ubuntu-latest\", \"macos-latest\"]" >> $GITHUB_OUTPUT
           fi
 
+
+  # This job decides if the hindcast test suite should run.
   check-changes:
     runs-on: ubuntu-latest
     outputs:
@@ -31,11 +51,11 @@ jobs:
       should-run-hindcast: ${{ steps.hindcast-logic.outputs.should-run-hindcast }}
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Check for changes in wave/io/hindcast
         id: changes
-        uses: dorny/paths-filter@v3
+        uses: dorny/paths-filter@v4
         with:
           filters: |
             wave_io_hindcast:
@@ -56,45 +76,39 @@ jobs:
       PYTHON_VER: 3.11
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Setup Miniconda
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
-          miniconda-version: 'latest'
-          auto-update-conda: true
-          python-version: ${{ env.PYTHON_VER }}
-          activate-environment: TESTconda
-          use-only-tar-bz2: false
-
-      - name: Create MHKiT Conda environment
-        shell: bash -l {0}
-        run: |
-          conda env create -f environment.yml
-          conda activate mhkit-env
+          miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
+          auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
+          environment-file: ${{ env.CONDA_ENVIRONMENT_FILE }}
+          activate-environment: ${{ env.CONDA_ENVIRONMENT_NAME }}
+          python-version: ${{ matrix.python-version }}
+          use-only-tar-bz2: ${{ env.CONDA_USE_ONLY_TAR_BZ2 }}
+          channels: ${{ env.CONDA_CHANNELS }}
+          conda-remove-defaults: ${{ env.CONDA_REMOVE_DEFAULTS }}
 
       - name: Install testing dependencies
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          conda install -y pytest coverage coveralls
+          conda install -y pytest coverage
 
       - name: Install mhkit
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          pip install -e  ".[all,dev]" --no-deps
+          pip install -e ".[all,dev]" --no-deps
 
       - name: Prepare non-hindcast API data
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           pytest mhkit/tests/river/test_io_usgs.py
           pytest mhkit/tests/tidal/test_io.py
           pytest mhkit/tests/wave/io/test_cdip.py
 
       - name: Upload data as artifact
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v6
         with:
           name: data
           path: ~/.cache/mhkit
@@ -107,43 +121,37 @@ jobs:
     if: (needs.check-changes.outputs.should-run-hindcast == 'true')
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Setup Miniconda
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
-          miniconda-version: 'latest'
-          auto-update-conda: true
-          activate-environment: TEST
-          python-version: ${{ env.PYTHON_VER }}
-          use-only-tar-bz2: false
-
-      - name: Create MHKiT Conda environment
-        shell: bash -l {0}
-        run: |
-          conda env create -f environment.yml
-          conda activate mhkit-env
+          miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
+          auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
+          environment-file: ${{ env.CONDA_ENVIRONMENT_FILE }}
+          activate-environment: ${{ env.CONDA_ENVIRONMENT_NAME }}
+          python-version: ${{ matrix.python-version }}
+          use-only-tar-bz2: ${{ env.CONDA_USE_ONLY_TAR_BZ2 }}
+          channels: ${{ env.CONDA_CHANNELS }}
+          conda-remove-defaults: ${{ env.CONDA_REMOVE_DEFAULTS }}
 
       - name: Install testing dependencies
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          conda install -y pytest coverage coveralls
+          conda install -y pytest coverage
 
       - name: Install mhkit
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          pip install -e  ".[all,dev]" --no-deps
+          pip install -e ".[all,dev]" --no-deps
 
       - name: Prepare Wave Hindcast data
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           pytest mhkit/tests/wave/io/hindcast/test_hindcast.py
 
       - name: Upload Wave Hindcast data as artifact
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v6
         with:
           name: wave-hindcast-data
           path: ~/.cache/mhkit
@@ -156,104 +164,98 @@ jobs:
     if: (needs.check-changes.outputs.should-run-hindcast == 'true')
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Setup Miniconda
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
-          miniconda-version: 'latest'
-          auto-update-conda: true
-          activate-environment: TEST
-          python-version: ${{ env.PYTHON_VER }}
-          use-only-tar-bz2: false
-
-      - name: Create MHKiT Conda environment
-        shell: bash -l {0}
-        run: |
-          conda env create -f environment.yml
-          conda activate mhkit-env
+          miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
+          auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
+          environment-file: ${{ env.CONDA_ENVIRONMENT_FILE }}
+          activate-environment: ${{ env.CONDA_ENVIRONMENT_NAME }}
+          python-version: ${{ matrix.python-version }}
+          use-only-tar-bz2: ${{ env.CONDA_USE_ONLY_TAR_BZ2 }}
+          channels: ${{ env.CONDA_CHANNELS }}
+          conda-remove-defaults: ${{ env.CONDA_REMOVE_DEFAULTS }}
 
       - name: Install testing dependencies
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          conda install -y pytest coverage coveralls
+          conda install -y pytest coverage
 
       - name: Install mhkit
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          pip install -e  ".[all,dev]" --no-deps
+          pip install -e ".[all,dev]" --no-deps
 
       - name: Prepare Wind Hindcast data
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           pytest mhkit/tests/wave/io/hindcast/test_wind_toolkit.py
 
       - name: Upload Wind Hindcast data as artifact
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v6
         with:
           name: wind-hindcast-data
           path: ~/.cache/mhkit
 
-  conda-build:
-    name: conda-${{ matrix.os }}/${{ matrix.python-version }}
+  conda-forge-build:
+    name: conda-forge-${{ matrix.os }}/${{ matrix.python-version }}
     needs: [set-os, prepare-nonhindcast-cache]
     runs-on: ${{ matrix.os }}
     strategy:
       fail-fast: false
       matrix:
         os: ${{fromJson(needs.set-os.outputs.matrix_os)}}
-        python-version: ['3.10', '3.11', '3.12']
+        python-version: ['3.10', '3.11', '3.12', '3.13']
     env:
       PYTHON_VER: ${{ matrix.python-version }}
 
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
 
       - name: Setup Miniconda
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
-          miniconda-version: 'latest'
-          auto-update-conda: true
-          environment-file: environment.yml
-          activate-environment: TEST
+          miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
+          auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
+          environment-file: ${{ env.CONDA_ENVIRONMENT_FILE }}
+          activate-environment: ${{ env.CONDA_ENVIRONMENT_NAME }}
           python-version: ${{ matrix.python-version }}
-          use-only-tar-bz2: false
-
-      - name: Create MHKiT Conda environment
-        shell: bash -l {0}
-        run: |
-          conda env create -f environment.yml
-          conda activate mhkit-env
+          use-only-tar-bz2: ${{ env.CONDA_USE_ONLY_TAR_BZ2 }}
+          channels: ${{ env.CONDA_CHANNELS }}
+          conda-remove-defaults: ${{ env.CONDA_REMOVE_DEFAULTS }}
 
       - name: Install testing dependencies
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          conda install -y pytest coverage coveralls
+          conda install -y pytest coverage
 
       - name: Install mhkit
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          pip install -e . --no-deps
+          pip install -e ".[all,dev]" --no-deps
+
+      - name: Download data from artifact
+        uses: actions/download-artifact@v8
+        with:
+          name: data
+          path: ~/.cache/mhkit
 
       - name: Run pytest & generate coverage report
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           coverage run --rcfile=.github/workflows/.coveragerc --source=./mhkit/ -m pytest -c .github/workflows/pytest.ini
           coverage lcov
 
       - name: Upload coverage data to coveralls.io
-        uses: coverallsapp/github-action@master
+        uses: coverallsapp/github-action@v2
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
-          flag-name: conda-${{ runner.os }}-py${{ matrix.python-version }}
+          flag-name: conda-forge-${{ runner.os }}-py${{ matrix.python-version }}
           parallel: true
           path-to-lcov: ./coverage.lcov
+          fail-on-error: ${{ env.COVERALLS_FAIL_ON_ERROR }}
 
   pip-build:
     name: pip-${{ matrix.os }}/${{ matrix.python-version }}
@@ -263,56 +265,58 @@ jobs:
       fail-fast: false
       matrix:
         os: ${{fromJson(needs.set-os.outputs.matrix_os)}}
-        python-version: ['3.10', '3.11', '3.12']
+        python-version: ['3.10', '3.11', '3.12', '3.13']
 
     steps:
-      - uses: conda-incubator/setup-miniconda@v3
-
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v5
+        uses: actions/setup-python@v6
         with:
           python-version: ${{ matrix.python-version }}
 
+      - name: Setup Python Virtual Environment
+        shell: bash
+        # The second command puts the venv bin directory on the PATH for
+        # subsequent steps in the job, which ensures that the correct Python
+        # version and installed packages are used.
+        run: |
+          python -m venv venv
+          echo "$PWD/venv/bin" >> $GITHUB_PATH
+
       - name: Set up Git repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Download data from artifact
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         with:
           name: data
           path: ~/.cache/mhkit
 
-      - name: Install system dependencies
-        if: runner.os == 'Linux'
-        run: sudo apt-get install -y libhdf5-dev libnetcdf-dev
-
       - name: Update and install packages
-        shell: bash -l {0}
+        shell: bash
         run: |
           python -m pip install --upgrade pip wheel
-          pip install -e  ".[all,dev]"
-
-      - name: Reinstall h5py and netCDF4 with system libraries
-        if: runner.os == 'Linux'
-        run: "pip install --force-reinstall --no-binary=:all: h5py netCDF4"
+          pip install -e ".[all,dev]"
 
       - name: Install setuptools for Python 3.12
         if: matrix.python-version == '3.12'
-        run: pip install setuptools
+        shell: bash
+        run: |
+          pip install setuptools
 
       - name: Run pytest & generate coverage report
-        shell: bash -l {0}
+        shell: bash
         run: |
           coverage run --rcfile=.github/workflows/.coveragerc --source=./mhkit/ -m pytest -c .github/workflows/pytest.ini
           coverage lcov
 
       - name: Upload coverage data to coveralls.io
-        uses: coverallsapp/github-action@master
+        uses: coverallsapp/github-action@v2
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
           flag-name: pip-${{ runner.os }}-py${{ matrix.python-version }}
           parallel: true
           path-to-lcov: ./coverage.lcov
+          fail-on-error: ${{ env.COVERALLS_FAIL_ON_ERROR }}
 
   hindcast-calls:
     name: hindcast-${{ matrix.os }}/${{ matrix.python-version }}
@@ -331,47 +335,41 @@ jobs:
       fail-fast: false
       matrix:
         os: ${{fromJson(needs.set-os.outputs.matrix_os)}}
-        python-version: ['3.10', '3.11', '3.12']
+        python-version: ['3.10', '3.11', '3.12', '3.13']
 
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
 
       - name: Setup Miniconda
-        uses: conda-incubator/setup-miniconda@v3
+        uses: conda-incubator/setup-miniconda@v4
         with:
-          miniconda-version: 'latest'
-          auto-update-conda: true
-          environment-file: environment.yml
-          activate-environment: TEST
+          miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
+          auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
+          environment-file: ${{ env.CONDA_ENVIRONMENT_FILE }}
+          activate-environment: ${{ env.CONDA_ENVIRONMENT_NAME }}
           python-version: ${{ matrix.python-version }}
-          use-only-tar-bz2: false
-
-      - name: Create MHKiT Conda environment
-        shell: bash -l {0}
-        run: |
-          conda env create -f environment.yml
-          conda activate mhkit-env
+          use-only-tar-bz2: ${{ env.CONDA_USE_ONLY_TAR_BZ2 }}
+          channels: ${{ env.CONDA_CHANNELS }}
+          conda-remove-defaults: ${{ env.CONDA_REMOVE_DEFAULTS }}
 
       - name: Install testing dependencies
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          conda install -y pytest coverage coveralls
+          conda install -y pytest coverage
 
       - name: Install mhkit
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          pip install -e  ".[all,dev]" --no-deps
+          pip install -e ".[all,dev]" --no-deps
 
       - name: Download Wave Hindcast data from artifact
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         with:
           name: wave-hindcast-data
           path: ~/.cache/mhkit/wave-hindcast
 
       - name: Download Wind Hindcast data from artifact
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         with:
           name: wind-hindcast-data
           path: ~/.cache/mhkit/wind-hindcast
@@ -386,25 +384,25 @@ jobs:
       - name: Run hindcast pytest
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           coverage run --rcfile=.github/workflows/.coveragehindcastrc -m pytest -c .github/workflows/pytest-hindcast.ini
           coverage lcov
 
       - name: Upload coverage data to coveralls.io
-        uses: coverallsapp/github-action@master
+        uses: coverallsapp/github-action@v2
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
           flag-name: hindcast-${{ runner.os }}-py${{ matrix.python-version }}
           parallel: true
           path-to-lcov: ./coverage.lcov
+          fail-on-error: ${{ env.COVERALLS_FAIL_ON_ERROR }}
 
   test-wheel-packaging:
     name: Test Built Wheel
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
 
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
         with:
           python-version: '3.11'
 
@@ -462,25 +460,28 @@ jobs:
       matrix:
         module:
           [wave, tidal, river, dolfyn, power, loads, mooring, acoustics, utils]
-        python-version: ['3.12']
+        python-version: ['3.13']
 
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
 
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v5
+        uses: actions/setup-python@v6
         with:
           python-version: ${{ matrix.python-version }}
 
       - name: Download non-hindcast data
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         with:
           name: data
           path: ~/.cache/mhkit
 
       - name: Install system dependencies
         if: matrix.module != 'river' || matrix.module != 'power' || matrix.module != 'utils' || matrix.module != 'loads'
-        run: sudo apt-get install -y libhdf5-dev libnetcdf-dev
+        run: |
+          # Update apt-get cache
+          sudo apt-get update
+          sudo apt-get install -y libhdf5-dev libnetcdf-dev
 
       - name: Install MHKiT with optional dependency
         run: |
@@ -514,7 +515,7 @@ jobs:
           needs.prepare-nonhindcast-cache.result == 'success' &&
           needs.prepare-wave-hindcast-cache.result == 'skipped' &&
           needs.prepare-wind-hindcast-cache.result == 'skipped' &&
-          needs.check-changes.outputs.should-run-hindcast == 'false'    
+          needs.check-changes.outputs.should-run-hindcast == 'false'
         ) ||
         (
           needs.prepare-nonhindcast-cache.result == 'success' &&
@@ -527,10 +528,10 @@ jobs:
       matrix: ${{ steps.set-matrix.outputs.matrix }}
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Set up Python
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v6
         with:
           python-version: '3.11'
 
@@ -556,52 +557,46 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
-      - name: Set up Miniconda
-        uses: conda-incubator/setup-miniconda@v3
+      - name: Setup Miniconda
+        uses: conda-incubator/setup-miniconda@v4
         with:
-          miniconda-version: 'latest'
-          auto-update-conda: true
-          python-version: '3.12'
-          channels: conda-forge
-          activate-environment: TESTconda
-          use-only-tar-bz2: false
-
-      - name: Create MHKiT Conda environment
-        shell: bash -l {0}
-        run: |
-          conda env create -f environment.yml
-          conda activate mhkit-env
+          miniconda-version: ${{ env.CONDA_MINICONDA_VERSION }}
+          auto-update-conda: ${{ env.CONDA_AUTO_UPDATE_CONDA }}
+          environment-file: ${{ env.CONDA_ENVIRONMENT_FILE }}
+          activate-environment: ${{ env.CONDA_ENVIRONMENT_NAME }}
+          python-version: ${{ matrix.python-version }}
+          use-only-tar-bz2: ${{ env.CONDA_USE_ONLY_TAR_BZ2 }}
+          channels: ${{ env.CONDA_CHANNELS }}
+          conda-remove-defaults: ${{ env.CONDA_REMOVE_DEFAULTS }}
 
       - name: Install notebook testing dependencies
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          conda install -y pytest coverage coveralls nbval jupyter utm folium
+          conda install -y pytest coverage nbval jupyter utm folium
 
       - name: Install mhkit
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
-          pip install -e  ".[all,dev]" --no-deps
+          pip install -e ".[all,dev]" --no-deps
 
       - name: Download non-hindcast data
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         with:
           name: data
           path: ~/.cache/mhkit
 
       - name: Download Wave Hindcast data (if available)
         if: (needs.check-changes.outputs.should-run-hindcast == 'true')
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         with:
           name: wave-hindcast-data
           path: ~/.cache/mhkit/wave-hindcast
 
       - name: Download Wind Hindcast data (if available)
         if: (needs.check-changes.outputs.should-run-hindcast == 'true')
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v8
         with:
           name: wind-hindcast-data
           path: ~/.cache/mhkit/wind-hindcast
@@ -622,7 +617,6 @@ jobs:
       - name: Run notebook
         shell: bash -l {0}
         run: |
-          conda activate mhkit-env
           if [[ "${{ matrix.notebook }}" == "examples/metocean_example.ipynb" || "${{ matrix.notebook }}" == "examples/WPTO_hindcast_example.ipynb" ]]; then
             if [[ "${{ needs.check-changes.outputs.should-run-hindcast }}" == 'true' ]]; then
               jupyter nbconvert --to notebook --execute --inplace --ExecutePreprocessor.timeout=${{ matrix.timeout }} "${{ matrix.notebook }}"
@@ -639,7 +633,7 @@ jobs:
       [
         prepare-wave-hindcast-cache,
         prepare-wind-hindcast-cache,
-        conda-build,
+        conda-forge-build,
         pip-build,
         hindcast-calls,
       ]
@@ -647,14 +641,14 @@ jobs:
       always() &&
       (
         (
-          needs.conda-build.result == 'success' &&
+          needs.conda-forge-build.result == 'success' &&
           needs.pip-build.result == 'success' &&
           needs.prepare-wave-hindcast-cache.result == 'skipped' &&
           needs.prepare-wind-hindcast-cache.result == 'skipped' &&
           needs.hindcast-calls.result == 'skipped'
         ) ||
         (
-          needs.conda-build.result == 'success' &&
+          needs.conda-forge-build.result == 'success' &&
           needs.pip-build.result == 'success' &&
           needs.prepare-wave-hindcast-cache.result == 'success' &&
           needs.prepare-wind-hindcast-cache.result == 'success' &&
@@ -662,11 +656,10 @@ jobs:
         )
       )
     runs-on: ubuntu-latest
-    container: python:3-slim
     steps:
       - name: Coveralls Finished
-        uses: coverallsapp/github-action@master
+        uses: coverallsapp/github-action@v2
         with:
           parallel-finished: true
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          github-token: ${{ secrets.GITHUB_TOKEN }}
+          fail-on-error: ${{ env.COVERALLS_FAIL_ON_ERROR }}
diff --git a/.github/workflows/pylint.yml b/.github/workflows/pylint.yml
index 27d52e520..6c85b7c67 100644
--- a/.github/workflows/pylint.yml
+++ b/.github/workflows/pylint.yml
@@ -8,10 +8,10 @@ jobs:
 
     steps:
       - name: Check out code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Set up Python
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v6
         with:
           python-version: '3.11'
 
diff --git a/.github/workflows/pypi.yml b/.github/workflows/pypi.yml
index 9cc2d2e05..766251d91 100644
--- a/.github/workflows/pypi.yml
+++ b/.github/workflows/pypi.yml
@@ -19,11 +19,11 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
-      - uses: actions/setup-python@v5
+      - uses: actions/setup-python@v6
         with:
           python-version: '3.10'
 
diff --git a/.github/workflows/test-wheel-build.yml b/.github/workflows/test-wheel-build.yml
index 8186eff54..46ecbbe82 100644
--- a/.github/workflows/test-wheel-build.yml
+++ b/.github/workflows/test-wheel-build.yml
@@ -16,14 +16,14 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.11', '3.12']
+        python-version: ['3.10', '3.11', '3.12', '3.13']
 
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
-      - uses: actions/setup-python@v2
+      - uses: actions/setup-python@v6
         with:
           python-version: ${{ matrix.python-version }}
 
diff --git a/.gitignore b/.gitignore
index 9063f86c4..d24a4b879 100644
--- a/.gitignore
+++ b/.gitignore
@@ -10,6 +10,8 @@ $ cat .gitignore
 *.tws
 *~
 *.png
+*.index
+*.dolfyn.log
 
 # Directories
 **/__pycache__/
@@ -33,6 +35,8 @@ $ cat .gitignore
 # Exemptions
 !**/examples/data/wave/*.mat
 !**/tests/data/wave/*.mat
+!**/examples/data/dolfyn/test_data/*.dolfyn.log
 
 # Files created during tests
 mhkit/tests/wave/plots/
+**/examples/data/dolfyn/test_data/test_save.nc
diff --git a/LICENSE.md b/LICENSE.md
index 67b9ca56e..009012157 100644
--- a/LICENSE.md
+++ b/LICENSE.md
@@ -1,6 +1,6 @@
 BSD 3-Clause License
 
-Copyright (c) 2019, Alliance for Sustainable Energy, LLC under the terms of Contract DE-AC36-08GO28308, Battelle Memorial Institute under the terms of Contract DE-AC05-76RL01830, and National Technology & Engineering Solutions of Sandia, LLC under the terms of Contract DE-NA0003525. The U.S. Government retains certain rights in this software. 
+Copyright (c) 2026, Alliance for Energy Innovation, LLC under the terms of Contract DE-AC36-08GO28308, Battelle Memorial Institute under the terms of Contract DE-AC05-76RL01830, and National Technology & Engineering Solutions of Sandia, LLC under the terms of Contract DE-NA0003525. The U.S. Government retains certain rights in this software. 
 All rights reserved.
 
 Redistribution and use in source and binary forms, with or without
diff --git a/README.md b/README.md
index 85151bd56..ebe2960ab 100644
--- a/README.md
+++ b/README.md
@@ -15,7 +15,7 @@
     </a>
 </p>
 
-MHKiT-Python is a Python package designed for marine renewable energy applications to assist in
+MHKiT-Python is a Python package designed for marine energy applications to assist in
 data processing and visualization. The software package include functionality for:
 
 - Data processing
@@ -32,59 +32,238 @@ See the [MHKiT documentation](https://mhkit-software.github.io/MHKiT) for more i
 
 ## Installation
 
-[MHKiT-Python](https://github.com/MHKiT-Software/MHKiT-Python) requires [Python (3.10-3.12)](https://www.python.org/).
-It is recommended to use the [Anaconda Python Distribution](https://www.anaconda.com/distribution/) (a fully featured Python installer with a GUI) 
-or [Miniconda](https://docs.anaconda.com/miniconda/#quick-command-line-install) (a lightweight installer with the ``conda`` command line utility).  
-Both will include most of MHKiT-Python's package dependencies. 
-MHKiT can be installed several ways:
+[MHKiT-Python](https://github.com/MHKiT-Software/MHKiT-Python) requires [Python (3.10-3.13)](https://www.python.org/).
 
-### Option 1: Install from Python
+See [installation instructions](https://mhkit-software.github.io/MHKiT/installation.html) for more information.
+
+<details>
+
+<summary>Install with Anaconda/Miniconda (Recommended)</summary>
+
+### Install With Anaconda/Miniconda
 
-This option is recommended as a fast installation for MHKiT-Python users.
-To install MHKiT-Python using ``conda``, in an Anaconda Prompt:
+It is recommended to use the [Anaconda Python Distribution](https://www.anaconda.com/distribution/) (a fully featured Python installer with a GUI)
+or [Miniconda](https://docs.anaconda.com/miniconda/#quick-command-line-install) (a lightweight installer with the `conda` command line utility).  
+Both will include most of MHKiT-Python's package dependencies.
+
+This option is recommended for most MHKiT-Python users.
+To install MHKiT-Python using `conda`, in an Anaconda Prompt:
 
 ```bash
-	conda install -c conda-forge mhkit
+conda env create mhkit-env --python=3.11
 ```
 
-### Option 2: Clone Repository from GitHub
+```bash
+conda activate mhkit-env
+```
+
+```bash
+conda install -c conda-forge mhkit
+```
+
+Note: To use the above installed version of MHKiT-Python users must activate the `mhkit-env` environment each time, using `conda activate
+mhkit-env` in each new shell/terminal to use MHKiT.
+To avoid this, users can install MHKiT into their base conda environment, but this is not
+recommended as it may cause dependency conflicts with other software.
+
+Visual Studio Code has [instructions for using Python environments in VS Code](https://code.visualstudio.com/docs/python/environments) that support conda environment discovery.
+
+</details>
+
+<details>
+
+<summary>Clone Repository from GitHub</summary>
+
+### Clone Repository from GitHub
 
 This option is recommended for MHKiT-Python users who want access to example notebooks and developers.
+
+#### Step 1: Clone Repository
+
 Download and install your preferred version of [git](https://git-scm.com/).
 To clone MHKiT-Python:
 
 ```bash
-	git clone https://github.com/MHKiT-Software/MHKiT-Python
-	cd MHKiT-Python
+git clone https://github.com/MHKiT-Software/MHKiT-Python
+```
+
+```bash
+cd MHKiT-Python
 ```
 
+#### Step 2: Setup a Virtual Environment
+
+A virtual environment is a self-contained directory that contains a Python installation for a
+particular version of Python, plus a number of additional packages. Using a virtual environment
+allows you to manage dependencies for different projects separately, avoiding conflicts between
+packages and ensuring that your project has access to the specific versions of packages it needs.
+
+Use of a virtual environment is recommended to avoid dependency conflicts with other python
+packages (this environment must be activated in each new shell/terminal before using MHKiT).:
+
+##### Option A: Python `venv`
+
+Using Python venv (built into python) to create a virtual environment:
+
+###### Windows
+
+Note: A supported version of Python ([see installation for supported versions](#installation)) must be installed and added to the system PATH for venv to work in Git Bash or WSL. Use of Git Bash or WSL is recommended for Windows users to avoid issues with activating the virtual environment in Command Prompt or PowerShell.
+
+```sh
+python -m venv mhkit-env
+```
+
+```sh
+.\mhkit-env\Scripts\activate
+```
+
+Linux/MacOS:
+
+```bash
+python -m venv mhkit-env
+```
+
+```bash
+source mhkit-env/bin/activate
+```
+
+##### Option B: Conda (requires separate installation of Anaconda or Miniconda):
+
+```bash
+conda create -n mhkit-env python=3.11
+```
+
+```bash
+conda activate mhkit-env
+```
+
+#### Step 3: Install MHKiT-Python with pip
+
 To install a local, editable version of MHKiT-Python using [pip](https://pip.pypa.io/en/stable/):
 
 ```bash
-	pip install -e .["all"]
+pip install -e .["all,dev"]
 ```
 
-An [environment YAML file](https://github.com/MHKiT-Software/MHKiT-Python/blob/main/environment.yml) is also provided that can create the base environment required by MHKiT. 
+An [environment YAML file](https://github.com/MHKiT-Software/MHKiT-Python/blob/main/environment.yml) is also provided that can create the base environment required by MHKiT.
 MHKiT can then be installed into that environment using any of the provided methods.
 
-### Option 3: Module-specific Install from Python
+</details>
+
+<details>
+
+<summary>Module-specific Install using Pip</summary>
+
+### Module-specific Install using Pip
+
+A slim version of MHKiT-Python can be installed to reduce the number of dependencies and potential conflicts with other software.
+This installation utilizes pip's optional dependencies installation.
+
+Note: Use of a virtual environment is recommended to avoid dependency conflicts with other python.
+See Option 2 installation instructions for virtual environment setup.
 
-A slim version of MHKiT-Python can be installed to reduce the number of dependencies and potential conflicts with other software. 
-This installation utilizes pip's optional dependencies installation. 
 To install a single MHKiT module, e.g. the wave module, and its dependencies, use:
 
-	pip install mhkit["wave"]
+```bash
+pip install mhkit["wave"]
+```
+
+To install all MHKiT modules use:
+
+```bash
+pip install mhkit["all"]
+```
+
+Note: `pip install mhkit` does not install any MHKiT dependencies and will not work without installing dependencies separately.
+
+To install specific modules users must specify which module(s) they want to install with the optional dependencies installation syntax:
+
+```bash
+pip install mhkit "[<module>]"
+```
+
+Or multiple modules with:
+
+```bash
+pip install mhkit "[<module>,<module>]"
+```
+
+Supported modules are:
+
+- `dolfyn`
+- `wave`
+- `tidal`
+- `river`
+- `power`
+- `loads`
+- `mooring`
+- `acoustics`
+- `qc`
+- `all` (includes the above modules and their dependencies)
+- `dev` (includes development dependencies for contributing to MHKiT)
+- `examples` (includes dependencies for running MHKiT example notebooks)
 
-Note that ``pip install mhkit`` only installs the base MHKiT dependencies and not the entire software.
 To install all MHKiT dependencies use:
 
-	pip install mhkit["all"]
+```bash
+pip install mhkit["all"]
+```
 
 See [installation instructions](https://mhkit-software.github.io/MHKiT/installation.html) for more information.
 
+</details>
+
+<details>
+
+<summary>Development Installation</summary>
+
+### Development Installation
+
+For developers contributing to MHKiT, there are three development installation strategies after
+cloning the repository locally:
+
+Note: Use of a virtual environment is recommended to avoid dependency conflicts with other python.
+See Option 2 installation instructions for virtual environment setup.
+
+**Pip development** (no conda):
+
+Setup and activate virtual environment using Python venv using [the instructions above](#python-venv) and then:
+
+Note: Developers can create multiple virtual environments by changing the name, `python -m venv <name>`, install isolated versions of MHKiT, and switch between them by activating the desired environment. This allows developers to test different versions of MHKiT and its dependencies without conflicts.
+
+```bash
+pip install -e ".[all,dev]"
+```
+
+**Conda development** (minimal conda + pip resolves deps):
+
+```bash
+conda env create -f environment.yml
+```
+
+```bash
+conda activate mhkit-env
+```
+
+```bash
+pip install -e ".[all,dev]"
+```
+
+**Conda-forge development** (all deps from conda-forge, mirrors production deployment):
+
+```bash
+conda env create -f environment-dev.yml
+conda activate mhkit-env
+pip install -e ".[all,dev]" --no-deps
+```
+
+The conda-forge option mirrors how users install MHKiT via `conda install -c conda-forge mhkit`, ensuring all dependencies come from the conda-forge channel. The `--no-deps` flag prevents pip from resolving dependencies, relying entirely on the conda-forge packages for dependencies. The conda-forge build and deployment happens in separate repository: [https://github.com/conda-forge/mhkit-feedstock] which is updated with each MHKiT release.
+
+</details>
+
 ## Copyright and license
 
-MHKiT-Python is copyright through the National Renewable Energy Laboratory,
+MHKiT-Python is copyright through the National Laboratory of the Rockies,
 Pacific Northwest National Laboratory, and Sandia National Laboratories.
 The software is distributed under the Revised BSD License.
 See [copyright and license](LICENSE.md) for more information.
@@ -114,7 +293,7 @@ The GitHub platform has the Fork feature that facilitates code modification and
 
 ## Creating a branch
 
-The GitHub platform has the branch feature that facilitates code contributions and collaboration amongst developers. A branch isolates development work without affecting other branches in the repository. Each repository has one default branch, and can have multiple other branches. To create a branch of your forked MHKiT-Python repository, follow the steps below. More information about GitHub branches can be found [here](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/about-branches)
+The GitHub platform has the branch feature that facilitates code contributions and collaboration. A branch isolates development work without affecting other branches in the repository. Each repository has one default branch, and can have multiple other branches. To create a branch of your forked MHKiT-Python repository, follow the steps below. More information about GitHub branches can be found [here](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/about-branches)
 
 1. Navigate to your fork of MHKiT-Python (see instructions above)
 2. Above the list of files, click **Branches**.
@@ -128,13 +307,13 @@ The GitHub platform has the pull request feature that allows you to propose chan
 
 1. Navigate to the [MHKiT-Python main page](https://github.com/MHKiT-Software/MHKiT-Python)
 2. Above the list of files, click **Pull request**.
-3. On the compare page, click **Compare accross forks**.
+3. On the compare page, click **Compare across forks**.
 4. In the "base branch" drop-down menu, select the branch of the upstream repository you'd like to merge changes into.
 5. In the "head fork" drop-down menu, select your fork, then use the "compare branch" drop-down menu to select the branch you made your changes in.
 6. Type a title and description for your pull request.
 7. If you want to allow anyone with push access to the upstream repository to make changes to your pull request, select **Allow edits from maintainers**.
 8. To create a pull request that is ready for review, click **Create Pull Request**. To create a draft pull request, use the drop-down and select **Create Draft Pull Request**, then click **Draft Pull Request**. More information about draft pull requests can be found [here](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/about-pull-requests#draft-pull-requests)
-9. MHKiT-Python adminstrators will review your pull request and contact you if needed.
+9. MHKiT-Python administrators will review your pull request and contact you if needed.
 
 ## Code Formatting in MHKiT
 
diff --git a/environment-dev.yml b/environment-dev.yml
new file mode 100644
index 000000000..e624a7286
--- /dev/null
+++ b/environment-dev.yml
@@ -0,0 +1,30 @@
+name: mhkit-dev-env
+channels:
+  - conda-forge
+  - defaults
+dependencies:
+  - python>=3.10,<3.14
+  - pip
+  - numpy>=2.0.0
+  - pandas>=2.2.2
+  # Provides pyarrow storage for the default string dtype in pandas 3.0+
+  - pyarrow>=16.0.0
+  - scipy>=1.14.0
+  - xarray>=2024.6.0
+  - scikit-learn>=1.5.1
+  - h5py>=3.11.0
+  - h5pyd>=0.18.0
+  - netCDF4>=1.6.5
+  - hdf5>=1.14.3
+  - statsmodels>=0.14.2
+  - requests
+  - beautifulsoup4
+  - numexpr>=2.10.0
+  - lxml
+  - bottleneck
+  - pecos>=0.3.0
+  - notebook
+  - matplotlib>=3.9.1
+  - fatpack
+  - nrel-rex
+  - cartopy
diff --git a/environment.yml b/environment.yml
index 884a2e01d..d484f58a8 100644
--- a/environment.yml
+++ b/environment.yml
@@ -3,26 +3,5 @@ channels:
   - conda-forge
   - defaults
 dependencies:
-  - python>=3.10,<3.13
+  - python=3.11
   - pip
-  - numpy>=2.0.0
-  - pandas>=2.2.2
-  - scipy>=1.14.0
-  - xarray>=2024.6.0
-  - scikit-learn>=1.5.1
-  - h5py>=3.11.0
-  - h5pyd>=0.18.0
-  - netCDF4>=1.6.5
-  - hdf5>=1.14.3,<1.14.5.0a0
-  - statsmodels>=0.14.2
-  - requests
-  - beautifulsoup4
-  - numexpr>=2.10.0
-  - lxml
-  - bottleneck
-  - pecos>=0.3.0
-  - notebook
-  - matplotlib>=3.9.1
-  - fatpack
-  - nrel-rex
-  - cartopy
diff --git a/examples/Delft3D_example.ipynb b/examples/Delft3D_example.ipynb
index 8bb9e8702..c2342fb56 100644
--- a/examples/Delft3D_example.ipynb
+++ b/examples/Delft3D_example.ipynb
@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 18,
    "id": "030973b3",
    "metadata": {},
    "outputs": [],
@@ -47,7 +47,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 19,
    "id": "258b202f",
    "metadata": {},
    "outputs": [
@@ -138,7 +138,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 20,
    "id": "5e0dabc1",
    "metadata": {},
    "outputs": [
@@ -165,7 +165,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 32,
    "id": "ebbdc284",
    "metadata": {},
    "outputs": [
@@ -180,14 +180,14 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\sterl\\AppData\\Local\\Temp\\ipykernel_21668\\3610353735.py:2: UserWarning: Warning: seconds_run not found. Closest time stampfound 60.0\n",
-      "  time_index = d3d._convert_time(d3d_data, seconds_run=seconds_run)\n"
+      "c:\\Users\\ashly\\anaconda3\\envs\\Updated_MHKiT\\Lib\\site-packages\\mhkit\\river\\io\\d3d.py:87: UserWarning: Warning: seconds_run not found. Closest time stampfound 60.0\n",
+      "  time_index: int\n"
      ]
     }
    ],
    "source": [
     "seconds_run = 62\n",
-    "time_index = d3d._convert_time(d3d_data, seconds_run=seconds_run)\n",
+    "time_index = d3d.seconds_to_index(d3d_data, seconds_run=seconds_run)\n",
     "print(time_index)"
    ]
   },
@@ -204,7 +204,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 22,
    "id": "197ab8f9",
    "metadata": {},
    "outputs": [
@@ -252,7 +252,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 23,
    "id": "26e1daba",
    "metadata": {},
    "outputs": [
@@ -333,7 +333,7 @@
        "4      16.426020  3.0    1.000931"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -369,7 +369,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 24,
    "id": "199785ce",
    "metadata": {},
    "outputs": [
@@ -379,13 +379,13 @@
        "Text(0.5, 1.0, 'Centerline Velocity at: 240.0 s')"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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       "text/plain": [
        "<Figure size 1200x500 with 1 Axes>"
       ]
@@ -426,7 +426,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 25,
    "id": "26daf026",
    "metadata": {},
    "outputs": [
@@ -436,13 +436,13 @@
        "Text(0.5, 1.0, 'Velocity on Layer 2 at Time: 240.0 s')"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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9+/f7ZhOIRcHOae98DuWc17RXgc4RVeEPpRJ/KH/XUku/0wqQqqSvCwSaOcD/b6A/nf/qiaGq9t27dw97W94xS+59ec8ndYwzYv16/61bt3YXmfr37+9uqmR++eWXu547+v+mCzAAgNDQog2kkheu1SKs7one9EdffPFFwCm9vDCsD33/q5OQ7E1TZaW1QN1I01ObNm3cMVErmeafFX3tzUGesIU1q1KgV9dbhWxN7aWwrNCnbqIKwLpgoi74nkDTMKk1U2FC5+L777/vHtPXCt8SqOdAJM/bSHYb137dcccd7pzRenWhRkMnUkqtsQpZCtnqhr506VIXGnUu6tjqNmTIEPfa5Ka4ymq8c0Q9JkI5PxJOP5YWIVu9VX755Rd3cUdDH3ThMxANo9GQCLV0a/51XUzRcCD/m/fz1u+g95h3MUa8HhS6eJUU7/lwe1yk9frLli3rejl99dVX9uijj9qll17q3p96KmjIkaa30zEEAISGoA2kUtu2bV13XP9WbH3YV2uPWn68MasedZ0UtThGskVMLQ1egEmqS6v/c/4ti95+pVd3zoTU3de7aOF1adZxVMjRvqmlJVze+0uui6/3fKRbWtOqNVs/I/2sdTHn2muvTdRy5fVOSIo3XlXnrD5Me63barXVOO6E0uq8jURL9qeffuoL2V63+JTShR2tV3NKa71qzVOrXrjHNyvK6L8hCUO2hqNoznMvZHtDKgLRhRSFbf0uXH311e53KuFt69at7rUaluA95j9O3auLoW3rYmsgOre8uag1JCUc3vp1MShY/QP/bYe7ftGFBo2vHz58uBtKo55Ser8K4TpGGp5Bd3IACA1BG0gldXHWhw/54IMP4rUMXn/99b7xjAnHp+p1GscdKQoDGk8q6h4ZjLpGeh+o1Krp8bq3a4xuKN0+Q+E/DjKU1j+1WmsZFZnSh0kvcGssfDhF0DyXXXaZL0h7vQ0S0s9BXdZFoSrabdu2zd0XL148aJd472ecFJ2zGnusUKSiVMGKoKX1eZtS2g+9B9VG8EL2LbfcErHje/HFFwcdx5vU8fWWyYqt3d45onHyGVlQSz07FLL9W7JTEjrD5dW/ELUKB6LWYa9IWbjDG7z1a3mvpkZC/ttNzfAJjy4m6PfM6/miYxuoYCUAIDGCNhABXkusPlxqXJv3QSRht3GpUqWKb/xrnz594lX+DiScIlte0FCr3Jo1axI9r66OGv8sGuOrcaceVeFVYFEBKxXZigQFOY//eOJgND5cLbRei6uOY0qKoPl/MFWhsKSqjv/nP//xjS31qiFHM+9npg+8gcZK66LC66+/nux6ChQoYHfeeaf7+sUXX/RVIA/WRT8tz9uUtmSru7h6jajFLRIh2//46twLFJZ1kSGpitjeOR/K+Z7ZqKu9eveoN0/Pnj2TvNigluO0OEb+3cV1kVMX0UIJ2RrmkFxXd69+hXp8eI9p+IZ/zQ5VNJfXXnst0Rh28Srha11qOQ9HgwYNfPsQqKK+tqftivYjnJoWybVSq1iaJ9gFKABAAhGYIgyA39yl3lzUpUuXDjpXsOa41tzael316tXjJk+eHHfkyBHf89u3b4/74IMP3LzFCeeyTWqeXM1j681xq3mSZ8yY4eb7llWrVsXVrVvXN0fyypUrE+3XU0895Vv3vffeG7dhwwbfc/v27XPz0GoO2FD359ChQ3G5c+d2zw0cODDgvL0JTZs2zbc+3Zo3b56q8+uNN97wreuBBx6I++uvv3z7Nnz4cDfnuJ7r0KFDomW9ebSTmtM31LnCk5tHe/ny5W7e6mC3f/75xy2zd+/euAIFCrhlrr76ajf/uehc09zFlSpVijvrrLNCmp9b56H/sa5WrVqS+5ua8zY1x8mf3uctt9zi1pMzZ864zz77LC6SZs2a5dvPhx56yHfcDx48GPfOO++4Obq94xtoTuv33nvPPVe0aNG4tWvXRu082smdk0ltJ6nfi9GjR/u2ce2118YtXrzY9zdI97/88kvc4MGD3fnz4YcfRnQe7Z07d8bVqFHDLV+qVCm3rUhKbh5tWbBgQVyOHDnc6zSvtn4nROeRzifv2IwbNy7JbQR7/1ou0Pmp7XjzeGv7CxcuDOu96dy48MIL44YMGeKOm/cz099svSc95/1fCfZ/DQAQH0EbiBD/QKebQmtSvv/+e/dh0Hu9PhzpA3y+fPnirSecoO2FoXPOOcf3mrx588YVKlTI971C9vjx4wPukz5AdenSJd72FawUGrJly+a+L1y4cFj7o8DuPa+QUrZsWfdhslevXgH3QR/wvA+buk2YMCEutXr06OFbn96H3o9CmvdYo0aN3EWKjAzayd38j/vbb7+d6Gekn7O+LlasWNzUqVNDCtpy1VVX+V6rAJSclJ63kQra8+bN861HF0lKliyZ5E0Xh8LlBXnvVqRIEV94uvTSS32/64HC6L///htXvHhx37L6eeh1ui1atCjTB23v/PQusHl/c3SOeBe1vNvYsWMjGrSff/5537p1MSq5c2Pr1q0RD9rexRb/vy86f7y/n7rp+CW3jaTev3f8vb9nWr/3vbar7YfL/9zwfrf0M/N/H/o/Mn/+/LDXDQBZFf1/gAhRV1b/+acDdRtPOJ5R44YHDx7suhCqy6W6Uqr7tgoxqZKyusSqAm64BXNUAEhdpdWtUV1rjx07ZpUqVXLdsfVcsKrM2ramNtIYab0fFcBRd0RdlFMhIXWRnzhxYlj78+abb7p9ufDCC933KiikccHe9FMJqVuixglLSougJaQq0RqnqcJ16k6qLvQae6hxnCoGpnHp4U6Fk5H0c5w+fbrryq1pvVQFWeO1H3nkETc1j3esQ+3uK8GKoKXXeRsq/yrPOje9LvTBbqoeHS5v/1XzQMdFXdV1TF9++WU3xjbYnOpStGhRmz9/vuvKrp+JutjrfNctUrUPYuH8XL9+vavirbHuOoY6R3TcVDdB56l+5yI9VMP/3FDBvuTOjWAFxVKrc+fObg5qjW3WOaDptjRW/MYbb3T1M4INYwmVltd6tD6tV+vXdrQ9zTig7YdL9Sk0FOOhhx5y1cZVp0GzGeh/mv6PqOq46mbUr18/VfsOAFlJNqXtjN4JAPCnUKMx5r1797aXXnqJg5OGWrVq5aqXK/Ro/mkAABBdVGRSFyg15aRu3jR+4cY4XfRUTZZp06a5C3PebCNqTNHFuocffjhg8VnV8RkzZkzQ9b799tu+2UwSmjZtmrs4v2LFCve9CvE+/vjj1rJly6Dr8xqMVBNFjSOaXlCNPZp6MJbqROTM6B0AAH/6o6qQrT+kzJ2dtjZu3OgrgqaWLAAAEH1UaHfKlCmpXo8C74ABA1yhWfVWufLKK92UgOqtpQCvYrqaiSR//vwBl9f0f95Ujv6qVasW8PXDhg2zHj16uN6VTZs2daF+5syZblaeN954w7p27RpwGtMmTZq4HmlXXHGFK1apnmJaj2Zc0Gwj2v9YQNAGEDXUnbN79+7ua3Vv1x9XpA11C1W4Vndb/aOlSygAANGpTp06bjiThnnops9HGhYYLs04oqEgXbp0ccMDPb/++qsLwho6qJlIgvUmfOqpp3wzkCRn/f+GEClcawYIvQfR8DNNKavg3KJFC9da7T8kTEMXFbI17E+vEbVqa8rC8ePHu1lz1MIeC+g6DiDDaTyrrqb+9ddfbryxxktrrHE409MgNPqnp39UOtaa0kdXmb/77jurXbs2hxAAgBig+gkK2pEcAfzJJ5+47uMK8Zs2bQrYdVyBOdSg/fDDD7su5d26dUtUt2Xo0KFuGki1aKtl26NaER06dHD1PVauXBlvmeXLl7saEqpF5E2jG+1ip5M7gExLoU/zP+tKq66oqvs4ITttqAidCtLlzp3bXV3+6quvCNkAAGRxCrfy559/RmR906dPd/eBCvB6j2n8dqjLaGx3xYoV3fDCzZs3Wyyg6ziADKdgjfQxevRodwMAAPCv2yKBxmB7Jk2a5Gaf0awNahBRQdXq1asHLLq2detW93XNmjUTPX/uuee62Q00I4eGshUqVMg9rt6MXqgORI9rP1etWhUTwwsJ2gAAAACQhQ0fPtzd33DDDUFf49/NW5588klX70XLaiiaxwvZRYsWdb0VAylTpozrZaew7T8FrPdcsGVEy8SCLBO0VfBHXSE09jNWKtUBAAAAmZXGGB84cMDOPvvsmJq2SY4ePepqnaT0fSfMIyoapltGeOedd2zWrFlWpEgRV/AsIbVKa7hZ48aNXdjVkL8vv/zS+vbta2+99ZYbjqZx1x4VL5Ng1cvFC+D6+Ye6XKBlolmWCdoK2eqmAAAAACB6bNu2LWgrZrSG7LLlCtiunadTtHzBggV9odLz7LPPurmj05sKoqpgmYL/yJEj3UWPhPS8P3UbV7GzBg0auO7cI0aMcMXNyFpZNGirJVuaTuxouQrkzujdAYCwNThrA0cNAJBpHD140p5rtMD3OT1WqCVbIXv+0hJWsGB4PWUPHoyzq6/Y6S4ueGOTJSNas1VYTF3F9X5ef/11a9OmTVjL16hRw1q3bu3m3/722299027pQoIcPnzYgjl06JC79//Za7k9e/YEXS7QMtEsywRtr3uGQjZBG0CsaVxsXVb6kw0AyEJidVinQnbBM8Lt8v5/reAK2f5BO71pCi/NTa1gq5b0Rx55JEXrqVKlirvfsWOH7zFvju49e/a4cBxonLZmm5Fy5crFW07L6DnNGx7KMtEstgZDAAAAAABSTKG4WbNm7l7dwtVtPaUUjMU/TGusd9n/he0VK1YkWkat+SqEpsDsf7HBm2JMc2YH4j0eKIRHI4I2AMREazYAAEDqKBhfc8019vvvv9vdd98dr4hZuI4dO+ab+zrhlFwtW7Z09+pWnpD3mKYHC3UZBXZN7XXBBRfExNReQtAGgChGyAYAAOFQcTLNb927d+94j2vss8Ls6tWr7eabb7b33nsv2W7769atsw8//NCFan+7du2yW265xbVOqyW6Xr168Z7v1q2b5ciRw1U0X7x4se/xX3/91QYMGOCmA0tYZE1jxFVoTfNp+18AUPfzLl26uK979eoVMycDA/4AAAAAIEqp1bh///6+771pxWrXru17rF+/fr4WYXXLXr9+fbxx09KnTx9btGiRC8AKuvfee2/A7Y0ePdr3tabyuuuuu1wovuyyy6x48eJuNqdly5a5abZULf6zzz5LFNirVatmgwYNctXI69ev77qqaxqwmTNn2pEjR1zxtcqVK8dbJleuXDZ27Fhr2rSpW27cuHGue7kqo+u9tGvXzjp27GixgqANAFGK1mwAAKDW4yVLliQ6EP6P6TWhjqc+deqUffzxx0Ff5x+0q1atat27d3et0moJ/+eff1yFdD2urt8K4EWLFg24nh49ergwrcCtsCwK60888YRdf/31AZepW7eu/fDDD27c+Ny5c13rdqVKlezxxx/3TUMWK7LFacb0LGD//v1WuHBhu/ar+6g6DiAmELQBAJl9eq+nLp9n+/bty9AK3CnNFct/KRl21fGDB05brfP/jrn3jPAxRhsAohAhGwAAIHYRtAEAAAAAiCCCNgBEGVqzAQAAYhtBGwAAAACACCJoA0AUoTUbAAAg9hG0AQAAAACIIII2AEQJWrMBAAAyB4I2AAAAAAARRNAGgChAazYAAEDmQdAGAAAAACCCCNoAkMFozQYAAMhcCNoAkIEI2QAAAJkPQRsAMgghGwAAIHMiaANABiBkAwAAZF4EbQBIZ4RsAACAzI2gDQDpiJANAACQ+eXM6B0AgKyAgA0AAJB10KINAGmMkA0AAJC1ELQBIA0RsgEAQGosW7bMXnnlFbvpppusTJkyli1bNndLiXnz5tnzzz9vLVu2tOLFi7v1lC9fPqRlDx486Ja96KKLrGDBgla4cGG74IILrEuXLu65YCZPnmwtWrRw28ubN6+de+651qZNG/v+++/jvW706NG+95bU7YMPPrBYQNdxAEgjhGwAAJBa/fv3tylTpkTkQHbr1s1++umnsJfbtGmTNWnSxN1XrFjRrr32Wjt27JitX7/e3nrrLevdu7cL3/5Onz5t9913n40cOdIKFChgV111lRUpUsS2bt1qM2bMsEsvvdQ95qlcubJ17Ngx4Pb37dvnArv4LxPNCNoAkAYI2QAAIBLq1KnjWpEvv/xyd1MLtEJuSjRv3tzat2/v1qPW8Ro1aiS7jLalYK2A/M4779gDDzwQ7/k1a9bYmWeemWi5F154wYXsVq1audZq/9fs2bPHdu/eHe/1CtDBQvTbb7/tgna9evVc0I8FBG0AiDBCNgAAiJQnn3wyYusaOHCg7+u//vorpGWGDx/uWq4ff/zxRCFb1H08oe3bt9vLL79sZcuWtXHjxlm+fPniPV+0aFF3C9XYsWPd/Z133mmxgjHaABBBhGwAAJCZvPfee+7+kUceCXmZMWPG2PHjx61z586JQna41F194cKFljt3brv55pstVtCiDQARQsgGAACZybZt2+y3335z3cxVxGzBggU2depUN2a6QoUK1rZtWze2OqHZs2e7+7p169qOHTvso48+cutRAbVGjRrZNddcE3JBN681WwXcwmkFz2gEbQCIAEI2AAAI1f79++N9nydPHneLNr/88ou7P/vss111cRU+89e3b19XEb1Xr14Bl/vll19cGFcw9+++3rBhQ/v8889dcbTM2G1cCNoAkEqEbAAAsp6Zh6pb3mzhxamjh06a2d+uddjfs88+a88995xFGxUtk+XLl9uPP/7o9vHee++1nDlzumm2+vTpY4899phVr17dtTgnXK5nz56umJvGeavle+nSpa4S+dy5c939+PHjk9y+Xr9hwwZXSM1//bGAoA0AqUDIBgAAKemSXahQId/30dia7U3RJSdPnrSHHnrIXRDwPPHEE65y+KBBg+yll16KF4RP/285dfX+8ssv3fReoinC1PVcVdQnTJjgQnTVqlWTbc3W2GyN0Y4lFEMDAAAAgHSkkO1/i9ag7T839t13353oee+xJUuW2NGjRxMt1759e1/I9q9SrunFZP78+UG3rXCviuWx2G1cCNoAkEK0ZgMAgMysXLlyvq81f3dC3mOnTp2yf//9N9Fy5QMs4//4zp07g2575syZ7nnNm62iarGGoA0AAAAASERjr/PmzRtv3LU//3Dt3/pds2bNoMv4L+e/TLBu43fccUdM/mQI2gCQArRmAwCAzE5d2jUVl6iAWULz5s1z92p19h9z3rp163jP+zt48KArruYfyAO9ZsqUKe5rgjYAAAAAIEONGDHCtUT37t07IutT0TPp37+/K17m2bRpk/Xr1899/eCDD8ZbplWrVnbeeefZwoUL400Jpi7mqkSuFm2N1b7qqqsCbnPSpEl2+PBhq127tlWpUsViEVXHASAMtGQDAID0NH36dBdyPcePH3f3CqEeBV6v6rcqga9fv9527NiRaF3//e9/3U1OnDjh7vU6/3UpGNeqVcv3vcZHP/PMM/bCCy+4Fuh69epZjhw5bMGCBXbgwAG79tprXXj2lyNHDvv444+tQYMGbv7td999103vtWLFCtu4caOdddZZ7vls2bJlqrmz/RG0ASBEhGwAAJDedu3a5ap6J+T/mF4Tiu3btydal4K7/2P79+9PtNzzzz9vF198sQ0bNswWL17sKoJXq1bNOnbsaF27dnXBOqFLLrnEVq5c6ebeVmGzX375xUqWLGmdO3e2vn37xiu05k/Bf/bs2ZYrVy7r0KGDxapscXFxcZYF6IQpXLiwXfvVfZarQGzNwQYg4xGyAQCIrKMHT9pTl8+zffv2xRvfGyu54pUfGljegjmzxHtG+CiGBgDJIGQDAAAgHARtAEgCIRsAAADhImgDQBCEbAAAAKQEQRsAAiBkAwAAIKUI2gCQACEbAAAAqUHQBgA/hGwAAACkFkEbAP6HkA0AAIBIIGgDACEbAAAAEUTQBgAAAAAgggjaALI8uowDAAAgkgjaALI0QjYAAAAijaANAAAAAEAEEbQBZFm0ZgMAACAtELQBAAAAAIgggjaALInWbAAAAKQVgjYAAAAAABFE0AaQ5dCaDQAAgLRE0AYAAACAKLVs2TJ75ZVX7KabbrIyZcpYtmzZ3C2l9uzZY926dbNy5cpZnjx53H337t1t7969QZfZsGGD3X333e61uXPntjPOOMMuv/xyGzp0qB0/fjzR66dOnWodO3a0Cy+80IoVK2a5cuWyEiVK2HXXXWdffPFFwG2sWrXKunbtarVr17azzz7b7VvhwoWtTp069sYbb9iJEycslmSLi4uLsyxg//797gd17Vf3Wa4CuTN6dwBkEFqzAQCIDkcPnrSnLp9n+/bts0KFClms5YpXfmhgeQvmTPP3fOONN9qUKVMSPZ6SGLd7924XXH/77TerWLGiXXbZZfbzzz+7W9WqVW3RokV25plnxltm4cKF1qxZMzt8+LCdd955dsEFF7j9/+677+zIkSPWoEEDmzVrluXM+f+PRbt27WzSpElWo0YNK1u2rAvmmzdvtiVLlrjne/fubS+99FK87YwYMcIeeeQRF+YrV65sxYsXt127dtmCBQvs6NGjbjszZ850QT8W0KINAAAAAFFKwbhfv36ulXjHjh2upTel1HKtkK3W8fXr19u4ceNszZo1LuCq1bpnz56JllErs0L2yy+/bL/88ot99tln9vXXX/vC+rx58+zDDz+Mt0yfPn1cSF69erVNnz7dPv30U1u8eLG7FSxY0LXQ6zl/au3+/fffXSBXcP/kk0/cvb5XuNd23n33XYsVMRO0//nnH9fdQN0kdIUDAMJFazYAAOGZvbt6vBvS35NPPmkvvPCCtWrVykqVKpXi9SikK7yqRfitt96K1wI9aNAg14I8duxY27lzp+/xgwcP2ooVKyx//vz2xBNPxFufuncrhMsPP/wQ77maNWvaWWedlWgfrrzySuvQoYNrjZ8zZ0685xTadUuoZMmS7hjI7NmzLVbETNDu1auX6+oAAAAAIO1DdaBgTeCOXV999ZWdPn3a6tev78KrP7WSK8ifOnXKZsyY4XtcY6uzZ08+MgYK1cFonRJOF/CULJPRwhtUkEG+/fZbGzNmjN1///0x1V0AAAAAGY+W2LQ7pvQWix0//fSTu69Vq1bA5/X4yJEjXVEy/wB+9dVX29y5c23gwIH21FNP+Z77888/7c0333Qh+M477wxpH1avXu26q2sZjfsOtXjba6+95r5u2bKlxYqoD9oaYP/AAw/Y+eefb4899hhBG0CK8EEAQCwhGCIWz1X+14ZXUM2fAm1qxl6HYuvWre5elcsD8R7fsmVLvMffeecdF4pVwOyDDz5w46W1//Pnz7fSpUu7MdgqpBbItGnTbOLEia5iuLavwmoK2e+9955VqlQp4DK//vqrDRgwwLW+//33324ZdWF/8MEH7fbbb7dYEfVB+/nnn7eNGze6we9elwEAAADCKBDbv5MnDmlaqHkWq+b9U9VyHc2dovd87rnnxnv82Wefteeee87SksKqaLx1IAUKFHD3Bw4ciPd4tWrV7Pvvv7c2bdrY8uXLbe3ate5x1c5q1KiRqyyeVCv6mDFjfN/ny5fPhg8fnmQLuMK1/zLy6KOPWv/+/UPqxh4tojpoq9uCuglozjaNJVDFOQAIF1fYgfAQYAEgbW3bti3e9F5p3ZqdGipA1rZtW3dxQF9rSjAVqn7//ffdFF0a5rt06VJXTC2hvn37upum51KV8rffftsNB1YFdbV0BxpzfdVVV7liaRovrlbwzz//3DW+fvnll256r/Lly1ssiNqgra4CnTt3tiJFirjxAAAAZAWEXADI/BSy03vucE2rJZqqK5BDhw65e8157fn333+tffv2ruu3gu4555zje41amDWf9htvvGGDBw+2V199Nei28+bN67qca0x3jhw53DK6qeB1MHpdhQoV3JRjCtcK+5qGTN3RY0HUBm0deJWJHzVqVFhV7DzHjh1zt2DjIABkDbRmI1IIwACAWFa2bFl3v3379oDPe4+XK1fO95jGXytsN2nSxBey/SmEK7dpvHao7rzzTrfMlClTkgza/tRtXRcKVDn9+PHjMVF9PCqDtroIqItBgwYNrFOnTilahyZUVxcDAEDWQygGACC+iy++2N1rnHUg3uMXXXRRovBduHDhgMt4j6syeKiKFSvm7nft2hXyMhoPfuaZZ7qcqG0lnJ4sGkVl0O7SpYu7UqEKdymlqnjqZuDfop2w6ACAzI3W7MyB0AwAQOq1aNHCFRP77rvvbOfOnVaiRAnfc+oJrC7Z6q593XXX+R4vVaqUu1+xYoUbM63n/akHsoQzbnrevP8rgBes6nggKo7tjWv3gnq0i8qg/cUXX7ix2Srh7k+D6OWPP/6whg0buq8//fRT3wmQ3iXyAQDhIzgDAJB2RowY4W7qbq1evh5NxXXrrbfaRx99ZA8//LDLUTlz/l8cfOKJJ1wLc8eOHeMFcIVzZapNmzZZv3797MUXX/RV/l6/fr0988wz7ut27dr5ltF6Jk+e7KbiSljh/JtvvnHbEhW89qfu5OqKnjDbaTvaLxVIu+uuuxKF/WgVlUFb9u7d67vakZACt/ecF74BABmH8AwAQNrQOGkVHvOo56/Url3b95hCcMuWLd3Xu3fvduF0x44didY1bNgwW7x4sav4Xb16dVdB/Oeff7Y1a9ZYlSpVbMiQIfFer3CuQmeaXkuhfdy4cVazZk1XdXzRokWuJVwt4P7DfVVU7f7777fu3bvbpZde6ubn1mMbNmywdevWudf06NHDFTfzp9mmtIy6uFeuXNkFa83pvWzZMlco++qrr4534SDaRWXQ1kENRNN7qfKcuhmoPDwABEO38cggQAMAkLHUQrxkyZJEj/s/Fup4Z3W71lRcmrNbrc6aOkvjnRWkVd9KvYoT6tq1q6sYrvmvFdJVxEwt1QrcKmz2wAMPxGtlVov4wIEDbe7cuS7E//jjjy4oK7Tfcsst7vVe72R/AwYMsBkzZrjXf/3113bkyBE3LrtZs2auJV7biqV5tLPFBUu1USg1QVtjtDVY/9qv7rNcBaK/Sh2A1CFoh49QDQBITycOHbcvW7znpohK76muUiM1uSJW3zMySYs2AKQGITs+AjQAAED6ImgDQCZEuAYAAMg4MRW0VTY+hnq6A0C6IVgDAABEj5gK2gCQnKzUbZxwDQAAEJ0I2gAyXfjMjGGbUA0AABA7CNoAMnUojcbQTWgGAADI3AjaADK19AjdBGcAAAD4I2gDyDISBuJQgzdBGgAAAOEgaAPIsgjQAAAASAvZ02StAAAAAABkUQRtAAAAAAAiiKANAAAAAEAEEbQBAAAAAIgggjYAAAAAABFE0AYAAAAAIIII2gAAAAAARBBBGwAAAACACCJoAwAAAECUWrZsmb3yyit20003WZkyZSxbtmzullJ79uyxbt26Wbly5SxPnjzuvnv37rZ3796gy5w6dcqGDh1qF154oeXLl8+KFy9uN998s61duzbJbU2bNs0aNGhghQoVcreGDRva9OnTk1zm559/tvbt27ttaFva5rBhw+z06dMWSwjaAAAAABCl+vfvb71797bPP//c/vjjj1Sta/fu3XbFFVfY66+/bjlz5rQbb7zRzjjjDBs+fLhdeeWV9u+//yZaRgFXwbdnz562fft2a9mypdWoUcMmTJhgl112mS1dujTgtoYNG2atW7e2hQsXWr169axx48butddff72NGDEi4DKLFi2yyy+/3K27YsWKbnntc48ePeyWW26xuLg4ixUEbQAAAACIUnXq1LF+/frZ1KlTbceOHa4VOqXUcv3bb7+51vH169fbuHHjbM2aNfbII4/Yhg0bXJhOaOTIkS7kV6lSxdatW+dC8Ny5c238+PF2+PBhu/322+3kyZPxllm/fr099thjbl/nz59vX375pU2ePNlWrlxpZ511lgvO2g9/J06ccOs6cuSIDRkyxJYsWeL279dff3XHQNsbM2aMxQqCNgAAAABEqSeffNJeeOEFa9WqlZUqVSrF61FI/+STTyx37tz21ltvuRZtz6BBg1xX7bFjx9rOnTvjLafQKwMHDrSSJUv6Hm/btq1rcVZgnjJlSrxlhg8f7rqbP/jggy4ke6pWrWp9+vRxwVyv8acwv2nTJrv44otdEPcULFjQ1wL+2muvWawgaAMAAABAJvfVV1+5buD169ePF5hFLc8K8grHM2bM8D2u4Ktx2BorrS7jCbVr1843Ftvf9P+Nw/aeT+0ytWrVcl3J1fq+efNmiwUEbQAAAADI5H766SdfaA3Ee3zVqlWJlrngggssV65cIS2jompbt251X9esWTPRMueee64VK1bMtmzZYvv370/V/kUzgjYAAAAApCMFTP/bsWPH0nybXvhV5fJAvMcVgCOxTNGiRa1AgQJpuq1o9v875gMAAAAAQrL+7+KWI3/esI7WqcNHfa26/p599ll77rnn0vTIHzx40N3nz58/4PNeKD5w4ECaLhPJbUUzgjYAAAAApKNt27a5eaU9qakkjuhE0AYAAACAdKSQ7R+004Oqd4um5Ark0KFD7l7zaqflMkktt2fPnrC2Fc0Yow0AAAAAmVzZsmXd/fbt2wM+7z1erly5iCyzZ88eXzhOq21FM4I2AAAAAGRymp9ali9fHvB57/GLLroo0TKaVuvEiRMhLVOkSBFfaF6xYkXAbvO7d+92gdm/VT8l+xfNCNoAgJiz9q+SvhsAAEheixYtLHv27Pbdd9/Zzp074z2nquea1zpHjhx23XXX+R6vUKGCnXfeeXbkyBHfPNf+JkyY4O41B7e/lv+bc9t7PrXLKLBv3LjRTTNWvnz5mPhxM0YbADIJL3SeV+rvRI9lZlnhPSbF/+cNAMCIESPcrU2bNvbyyy/7Dkjp0qXt1ltvtY8++sgefvhh+/TTTy1nzv+Lg0888YTt2rXLOnbsaCVKlIh3EHv27Gn33Xefe03dunV9z0+aNMmmTp1qlStXthtuuCHeMt26dbN3333X3nnnHbvlllusdu3a7vFff/3VBgwY4Lar1/jT/irYaz7toUOHWo8ePdzj6n7epUsX93WvXr1i5gdM0AaATBYIs3rwzGqi6edN6AeAyFNLcv/+/X3fHz9+3N174VX69evnaxFWt+z169fbjh07Eq1r2LBhtnjxYps4caJVr17dLrvsMvv5559d1/AqVarYkCFDEi1zzz332IwZM+zzzz93yzRp0sRtY968eZYvXz4bO3asL7B7qlWrZoMGDXIhvX79+tasWTPLnTu3zZw507WOv/766y6g+8uVK5dbV9OmTd1y48aNc93L1QKv99KuXTt3ISBWELQBIIaDDZBVfjcI8QCyKrU0L1myJNHj/o/pNaEoVqyYLV261M3ZPXnyZBeeS5YsaY8++qg9//zzbnx1QupuPn78eBs+fLiNHDnSvvjiCzenddu2bd0y559/fsBt9ejRw4VpBW6FZVGwV8v49ddfH3AZtZj/8MMPbl7xuXPnutbtSpUq2eOPP+5awLNly2axIltcXFycZQH79++3woUL27Vf3We5CuTO6N0BEOUI00DWRagH0seJQ8ftyxbv2b59+9J9qqtI5IqKY562HPnzhrXsqcNHbWPHl2LuPSN8tGgDyHQIyQCi7W8I4R0AshaCNoBMhZANICv8bSK4A0B0I2gDyDQI2QCyCoI7ACTtgw8+sEi56667wl6GoA0gUyBkA0DG/Q2lhR1AtOnUqVPEiqcRtAFkSYRsAMgcf4cJ7AAi6eKLL040x3c4VJl91apVKVqWFm0AMY2QDQCZB4EdQCRdcsklbqqwlNq8eTNBG0DWQsAGAKTF/wha1YHMoVChQpY/f/5UrSNfvnwpnoaNFm0AMYeQDQCI1v8xBHUgOuzduzfV63jrrbfcLSUI2gBiCiEbABDNCOoAhKANICYQsAEAWUFK/9/Rkg5EF4I2AAAAEOPS84I0oR6x6O+//7b169dbtWrVrGTJ///78vvvv1ufPn1szZo1VrZsWXvmmWesdu3aqd4eQRsAAABAikM9wRux4JVXXrHXX3/d1q5d6wva+/fvt6uuusp27txpcXFx9ssvv9i8efNs5cqVVqVKlVRtL3uE9hsA0gzdxgEAiO7/00n9r/aeT3hb/3fxdN1PZG1z5861888/36pWrep7bPTo0a6l+9Zbb3Wt3UOGDLEjR47Ya6+9lurt0aININOF7JN//v+pHHKefThV2/fWldr1AACQ2XFhHNHsjz/+sDp16sR7bPr06ZYzZ04bNmyYFStWzLp3725jxoxxrdqpRdAGkKn4h+xA3/tTeE7q+VDXk5G4AAAAAJC8AwcOxJtX+9SpU7Zo0SK79NJLXcj2VK9e3b744gtLLYI2gCx7ZTxaw3N6vAcCOgAAyErOPvtsW7dune/777//3g4ePGgNGzaM97qTJ09a7ty5U709gjaATCMzBOdoPFaEcgAAEOvq1Kljn3zyiesm3qRJE+vbt69ly5bNWrVqFe91KpZ2zjnnpE/Qbty4sUWC3si3334bkXUByNwY5xVboZwwDgBA2lKRrpdfftk+/fRT27p1q5155pnWokUL69+/f9jBcPHixW5dCxYscK26mtaqffv29vTTT1uBAgUSvX7btm02bdo0W7p0qS1ZssQVDlOV7jlz5iRqEQ5k8uTJ9s4779iyZctcF+7ixYvbZZddZr169XJVv/2Lk919993Jrk/jqO+6666w3nPv3r1t0qRJbpui/W/UqJHVrVvX95rNmze7yuP33nuvpUvQVoW2SAVtAEgLtGZH5/EngAMAkHpHjx51jZ8KyKVLl7YbbrjBhcJRo0a58cR6vGLFiiGt66OPPrKOHTu6Mcq1atWycuXKuQD80ksvuXV99913VqhQoXjLTJw40Xr06BH2fp8+fdruu+8+GzlypAvwCtVFihRxFwpmzJjhxkf7B+3KlSu7fQtk3759LrCL/zKhqlGjhusuPnz4cNu9e7fb9uOPPx7vNV9//bVdfPHFduONN1q6dR1v166dDRo0KMUbeuyxx9wVBACIdGs2ITt6JfezIYgDAJC8F1980YVpdX+eOXOmFSxY0D2u6ajUQnvPPfeE1Di6fft269y5swvZ77//vltOjh8/bp06dXJdqxU+//Of/8RbTiFeFbkvv/xyd+vatavbj+S88MILLmSre7Zaq9UK79mzZ48LvP4UoIOF6LffftsF7Xr16oV8USEhXVhQa3gwDzzwgLtFQshBWz9MXe1IKe9kAAAg3IskBHIAQFalEDxixAj39ZtvvhkvV/Xs2dM3HZVapdVKmxSFXbWON2vWzBeyRcW/tA21aCsYq3X7rLPO8j3funVrdwunp/L27dtd93R1Sx83bpzly5cv3vNFixZ1t1CNHTvW3d95550hvV5hXPt8/fXXu+7tmsYrPWUP5UXdunWz5s2bp2pDWv7RRx9N1ToAICFas7POzznYDQCAzEzjqNVtulKlSlazZs2APY9FY6iTozAugcZVq7X5oosuclW3Nb90ao0ZM8ZdJFALesKQHa5NmzbZwoUL3QWBm2++OaRlFKxff/11u+aaa9z0Xbfccot9/PHHriU9PYQU64cOHZrqDd16663uBgCRQshCsPOAFnAAQGbx008/+bo9B+I9vmrVqmTXdejQIXcfrCXZa8X2tpkas2fPdvcqNrZjxw43Nvy3336zwoULuyJkCsCh1vDyWrNbtmwZciv4hg0bXNG2KVOmuIsQGmc+fvx4y5Ejh9sntXarS3uVKlUsLTC9FwAgS12EIYQDAGKJCodJmTJlAj7vPb5ly5Zk16Vq30m9Vi3Hoa4rOb/88ovvvm3btq5V3jNw4EDXqv7555+74miR7jbuqVatmj3xxBPu9s8//7iW+qlTp9o333xj8+fPd+PRFbRVXE5dzDU+PFIFvEPqOg4AsRSk8m/P7m5AsHOH7ucAgIy0f//+eLdjx44Ffa2m35L8+QN/9vGm49K0Wcm5+uqr3b2Knqlbt78ff/zRVq9eHfK6krPnf120NY5cXdKXL1/u3uusWbOsQoUKrnibKpInR1OKqXVaXdvVop1Saq3XlGATJkxwRdi+/PJLe+ihh9yYdRX9VvAvUaKEq3qu1m/vuGdIi7YG3eumrgDBTg5dEVBFOwBIr5Ad6OvDZU7zA0CKzikPLeEAAH+n/spvcXnzhnVQTh/9v88m5557brzHn332WXvuuefS/ADffvvtroK5WsnVdXrw4MGu4PWiRYtc6NW4Zo3Rzp499Q0Wp0//32cvdfVWqPUuCDRp0sS1Kit8K/QqRFetWjXZ1myNzdYY7UjIlSuX67qum4rAqdu9upirGJy29+GHH7ptvfHGGyFdDIhY0P7333+tTZs2bh4yTfSdFII2gGgQqIVb4TtYyzfBHAkxFhwAECnbtm2LN1d1njx5gr7WqzJ++PDhJMddn3HGGcluV+tSmFQ3ac0ZrZv/HNaaKuzVV18Nqxp4Utvas2ePtW/f3heyPRdccIGbJkyt1erCHSxoK/SrYnlKuo2HQ6Fft379+tlff/3lxnTr5t/dPV2CtiYr10TmmvT7/vvvd6XTmb4LQDS1Zociqdcn9RwhHMmdj7R+AwCSopDtH7SToumxvOmyAvEeD3Uq5osvvtgVCfvss89cd27Nqa2CaqrKrem4RDkvtcqVK+eCdvny5QM+r8cVtHfu3Bl0HZqrW88rb6qAWXooVaqUa8VOaUt2qoK20r0G3auLAQEbQFarMp4whBO8kRCt3wCASFEwFoXiQLzH1SIbKo337tSpk7v50xRawab/ClfNmjVt5cqVQafTUi9pSSpPet3G77jjDouUzZs3u1b05IY/q3U73YO2rnrUqVOHkA0gamRk8TNavxEKWr8BAClRr149NyXW77//7oLrJZdcEu95jXMWTVWVGhqnrPpbas3WNlOrdevWNmrUKLfOhFRozLtAEGhucO81GjcdqaCtomdqpdZc2pLUEOgMC9qXXnqp67sOALHYZTwaxoYDHlq/AQBJUVGurl272oABA6xLly6uO7U35nnIkCEuIDdo0MBlNI8KfOmmulped3CPwrrGSKvwmWft2rVuCi6FTxUAi4RWrVrZeeed51rJ33rrLXv44Yd9jbaqRK4Wbe2HptQKZNKkSW5ceu3atSMy1/WTTz7p5vJWZXEVhUvr4c8pCtp9+/a1Fi1a2FdffeXuAQChowAbkkPrNwAgYf7StFgKrQqd9evXd3NdL1myxM2NPXLkyHiv1/RVGoet7tEJde/e3c1trS7pWlaF2TQkWK24//nPf6xRo0aJltF6FNo969atc/cKz95Yc0295d8KnCNHDtd6rIsAukDw7rvvuoJrK1assI0bN7rptvR8sHmrUzp3djAqqlasWDF3oUHjsNNaioJ248aN3UHRPGTXXXedNWvWzM4555ygZeC9+doAAMkHcFq8kVwAp9gaAGQtefPmtTlz5rjWaeWwyZMnu3mlNca6f//+rn5WqNQNWyH2p59+sr1797qw3aFDB3v88ccTdUv3aCyzQn1Cagn3VK9ePdHzl1xyiQu2mrpMLfEK+CVLlrTOnTu7iwfBCrgp2M+ePdtNw6V9iwR1RVcjcXqEbMkWl9z8XEGMHj3a+vTpE1IXcnUPyGiaHF1jG6796j7LVSAy868BSBtr/yqZabqOpwRBG8khaAPIDE4dPmobO77kplAKtQJ3NPByRblXX7TsYc+jfdS2PNk35t5zZlC7dm13zBX400POlIbse++91/Xh1+D1tOjfrvEGmqd79erVrqS7Bq/r6oO6Huhqy4UXXhjR7QEAAAAAMqdevXq5sdnquh6sAFuGB+2BAwe6SdVnzJgRkdLvgbz00ktu8nWVqfdC9c8//2wffvihffrpp25wvCZaBwAAAAAgKe3bt3dzjmvYs4rLJTf82Zu/PF2DtuYeU8tyWoVsUSl3Vc7TeAR/qlinwfTq168D5V8tDwAAAACAQNSIq7HtGteuWzAq0Hby5ElLjRSlVCV/TXKeloLN3abKdupWrnnkNJg+nInZAQAAAABZzxdffGE33XSTC9CqPq5CbFE3vZeqjQ8dOtTNfaYrAulN1ee8OeUAAAAAAEjKs88+62qMjRo1yuXZYNOKRUqKSvU+/fTTbn413ebOnet2OL1ojLbmhNP8cZGYuBwAAAAAkLmtXbvWTTvdsWPHNA/ZKW7R9gKuJklv0qSJa2FWRfBAA8n1JtTNO6UGDRrkiqCpMJoOjr4+++yz7ZNPPnGToAMAAAAAkBR1F9ctvaS4GJq/48eP29atWy0tfP311/btt9/6vldf+g8++MAVSkuKJlXXzX++OwAAAABA1tOuXTvXWKtpoxMW3I6aruOnT58O65Yas2bNcl3T9+zZY/Pnz3et6ap4PmDAgCSXe/nll91E8t7t3HPPTdV+AAAAAABi04svvmjly5e31q1bp6rHdahiZm6sIkWKWP369d3c3XXq1LF+/fpZ8+bN7fLLLw/4+t69e1vPnj3jtWgTtgEAAAAg67n++uvd0GP1lq5evboL3cHm0dbwZ/9e1Zk6aHs0HrxDhw62bNkymzZtWtCgnSdPHncDAAAAAGRtc+fO9X196tQp16odrGU7EsXSQgramsZL/dhTM3f24cOHXX/4SEwH5g1i37VrV6rXBQAAAADI3DZt2pSu2wspaBcvXtw6depk77//foo31KVLFzc1lyYIT6158+a5+0qVKqV6XQAAAACAzK1cuXLpur2QiqGpGFkk5soOdR0LFiywr776KlEhtRMnTtgbb7zhAnu+fPlcF3IAAAAAAKJJyGO0v//+e7vnnntSvCEtH6pff/3V7r77btdFXNN4nXXWWbZ7925bvXq17dixw3VjHz16NMXNAAAAAABRN/w55KD922+/uVtqhDqoXNN3Pf30066L+KpVq1zIzp07t6sMp/nPHn30UatcuXKq9gUAAAAAkDkVz+DhzyEF7Tlz5lh6qlChQrLzZAMAAAAAEA3Dn1MUtNXCDAAAAADIGEeOHLGXX37ZPv30U9u6davrztyiRQvr37+/mw86HN98840NGzbMli5danv37rVChQq5IbsPPfSQtWnTJtHrhwwZ4oYCayjvzp07XXfqUqVKuZz4+OOP24UXXphomalTp9rEiRNt+fLlbvjvvn37rGjRonbZZZfZww8/7Oa1Tki9md9991378ccf3Xv8559/XPfv888/32677TZ78MEH3XTP0Tj8OaFscZGI+TFg//79VrhwYbv2q/ssV4HcGb07AJKw9q+SiR47+Wfw8TX5t4dU1zFqHS4Tv/Aj4C/n2Yc5IAAypVOHj9rGji+5AKagF2u5otyrL1r2vHnDWvb00aO25cm+Yb9nBdtGjRrZ4sWLrXTp0la/fn3bvHmzC8rqIq3HK1asGNK6FLB79OjhhvXWqVPH1b3atm2bLVq0yLXeaghvwt7Fqp116NAhu+iii3yh/ueff7YNGza44Dtp0qREwbldu3bu8Ro1aljZsmXtjDPOcPu8ZMkS93zv3r3tpZdeirfMiBEj7JFHHnEVwjVUWO9NUzqrWLaOgYL9zJkz3bDi5GTPHpnPhzpOmnc77OUI2gBiIWjHetgmTCM5BGoAWQ1BO/Sg3bdvXxd+FYwVNAsWLOhrae7Vq5cLoHPnzk12PQqtCtaa3Umt2v49l+fPn2/Nmze348ePu9pc/sFdQVct3mpd9vfWW2+5ccwlS5a07du3W86c/7/D9IoVK1zAVmFrfwraTZs2dcH9p59+itcavnHjRnef8KLB33//7ZZZs2aNm4Wqa9euIU8JHQkp6eFN0AYQlWK5VZtQjeQQqgGAoB1qi7aCb4kSJVwruLph16xZM97zF198setyre7WCsNJ+eKLL6xVq1Z2zTXXuOmUE7rhhhtcl+9x48bZzTffHNL+qeX5999/d6FZLd6h6Ny5sytSNnz4cFfoOhRjx461O++803VtV0t5tIueT6YAkIpwkpHhVtv2vwEJz9uENwAAQqXWZIXsSpUqJQrZXhdtmTZtWrLrypMnT0jbTNgKnRRvzHQo3bnTe5mMFPL0XgCA/0OYRsB/qARoAEAaUEux1KpVK+Dz3uNq1U7OFVdcYUWKFLHZs2e7rtUJu45//fXXVqVKFTcGPBSa+mr9+vVuGd1CsXr1atdiruDcrFmzkJbZs2ePvfbaa+7rli1bWiwgaAOIuTATrAu5AnByXcgJyUjt+QcAQHpS9W0pU6ZMwOe9x7ds2ZLsulTETV22VcFbxdXq1q3rltf46oULF1q9evXsgw8+CNpqPGjQIFcETeOr165d674+++yz7ZNPPrEcOXIEXGbatGmu+viJEyfce9F2FLLfe+8910ofyK+//urGpGssucZna5mDBw+6quO33367xQKCNoCodF6pv4MWRQs3bBOukRKEagBAWlYuT9ilO1i3bgVMyZ8/8GefAgUKuPsDBw6EtO2bbrrJvvzySzcGW93SPRozrmJoSU0Vphbvb7/91ve9qoMrmCc1Nvynn36yMWPG+L7Ply+fG5ut8dbBKFz7LyMay62pzCJVTTytpWgvn3/+eXfVAwCiEWOmES7GUQMAwpXvj+zu4n44Ny0jqvyt1mXvpvmx04u6YKuC99VXX+26myvI675x48b2zDPPuCAezKxZs9wUYOrKra7m6i6u7ucJpwNLWDFdy2gecHUbv/vuu+3+++93hddU6C2Qq666yi1z8uRJV4lc+zx69Gg3B7emCMvUQbtChQquYp2q0qlJHwDSE62NCPU8CeUGAEB60rzVKnDm3TSndDDeVF6HDwf+f6Vu3KJ5qpOjKcAee+wxu+SSS2z8+PFuai21iOt+woQJ7vHp06e7Fu+kaJy3xnHPmDHDtWb369fPfvjhhySXyZs3r11wwQX25ptvurmyVQFdU3UlRd3RlTt79uxpo0aNcl3KtWymDdovvviimxNNPwSVV9cVGR3cWLm6ACB2uo8nhYCEhOcDARoAEAvUTdv/llQ1cOUuCdaj2Htc3bhDKV4mynAJu2Ar1Hqt2WqtDoXGWnfo0MG1PodS9dzjdRufMmWKhUr7rIsOmpYsWEt4zAftp59+2s2VpsnS27dvb//884/rLqA51Fq0aOEGu6uZHwDSGmE766BVGgCQFWmebNEc2oF4j4cyh7UXytVdPRDvcXUND1WxYsXc/a5du9J0mWzZstmZZ57pcmY4+5ecjz76yNJCqkaSq2//p59+an/88YcNHjzYqlWr5sK3Btaret1TTz3lmvcBAAgHrdMAAPwfVQJXAFZD58qVKxMdFnX5Fg3rTU6pUqXc/Y8//hjwea/7d/ny5UM+/JomTIJVEI/UMhqrrS736gHgBfVIuOeee9w48mBCqeYeSERKtmlCc/WbV3n377//3m699VbbuXOnK/9evXp1a9KkiX3++eeR2BQAJEKrdmxhzDQAAKHTVFtdu3Z1X3fp0sU3JluGDBniCpmpIJl/5e8RI0a4HJZw7PeNN97oa8XVGGl/6sb98ccfuy7l6qbtUWVydddOWJdL03VpjLW6o6uSuLqQe3bt2uWm7wo0rvybb76xJ554wn2twmj+tL6//vor0TKaq1tTkqmL+l133RV0KrGUUEPxu+++a23bto23v7qwoRBetWrVjJ/eSzujvvn+Jd/Vsj1nzhw38F4/fHUr15huAEjtNF+IblwAAQAgMtTiqorfmk9alb5ViEwtrUuWLLHixYvbyJEj471+9+7dLpzu2LEjUdDW0F8VQlMLuKp4q9jYpk2bfK3cGhKsnsoe9VBWIFYrsvKcGlm1flUQ1/pV5EwVwf0z3qFDh1xl8e7du7tllAn12IYNG2zdunXuNT169HDh1p+qi2sZdZfXsGQFa73PZcuWuaCvSumRrtCuixQ6jjoeqnaufdDxVM9tHRsVb8uQoK0rGQrPumKhMK2D4bVwP/DAA+5EWLRokfuBqSqdrsaEM+gdAEKR1NzaiAyCMwAAGUNhVo2XCplqdZ48ebIbr9ypUyc3t7SCbKjjnMeNG+fqammearWGqzu6qohfd911rqK3nksYRFWjS9299XqFbLWyq3t5u3bt3PzWCsX+SpQoYQMHDnT5UL2eFeIVlEuXLm233HKLy4kNGzZMtH9eZtTrNWe3pgTT+2zWrJnrNa0iamkxj7YCtY6H3quGRyvDqtVf7y+l28sWp2ScAmvXrnXhWl0F/v33Xxew69ataw8++KC7ShKocl7t2rXdFYy9e/daRkwKr7EN1351n+UqkDvdtw8g5cJp0SZsh4fwDADIKKcOH7WNHV9y01tp3G2s8HJF9Udfshx58oa17KljR23d60/H3HvOzJYvX26vvPKKG+qs6cc0bly9B3RB4pprrknxelPUoq0mdbVSK1zrBHnooYdcwNaOJaVGjRrJzq8GAEgdwjMAAEBo1H1et0mTJvkKyr366qvWunVrF8DVxT3dgrbGBtSqVcuFaw1Kz58/tO6anTt3dv3qASCtxmkn1YU8lAAajS3iBGcAAIC0oa7qCbvLP/nkk3beeefZHXfc4caiJxwDn2ZBW63S/lXtQlWnTh13A4BoDaaEWgAAUndxXChkiliRMGR71KKtiuu6T4kUBe2UhGwAAAAAmTtgB/s+IYI4MmIstoY6q5BbqC688MIUD32O6PReAAAAALKG5MJ0csueOHTcNkZ0j4DgNA47Z86cbuoyTR92ySWXuHvdVCU9GE1rlhIEbQAAACCTS0koTtjqnJpgDWS0Nm3auKnMNN2YbpomTdOdScmSJX2h2wvgGqOdGgRtAAAAIAakd9AlWCMzmThxorvX1GorVqxwXcl1v3TpUvv111/tr7/+spkzZ7qZtTR39smTJ1O1PYI2gJjg/8+ecV0AgFhDaAWig+ZAb9iwobt51qxZY3369LEvvvjCVRr/559/Ur0dgjaATD3dFwAAkfz/AyDzueCCC2zKlCnWvXt3+/rrr11rd2oRtAHEJMI2ACCl/z8AIJBXX33Vjd0eNGiQPfPMM5YaBG0AMYuwDQBZBwEZQFrLkyePXXHFFfbpp58StAFkbYRtAIgNBGUAGUljsGvVqmU1a9a0ihUrBn3dnj17bMuWLaneHi3aAGIeYRsA0u7vKwBkBi+//LJvOq9ChQq5abwUunXTGG3Nl61iaIsWLUoyiIeKoA0gUyBsA0D8v4kAgP/vgw8+cPNoa0ov3c+bN8/dvPDt7/7777fUImgDyDQI2wBiHQEZANKGpu3SzbN161YXunVbvXq1bd++3YoXL25t2rSxe++9N9XbI2gDyFRS8yGVKcMApNffGwBAxipbtqy73XDDDWmyfoI2ACTzoZkADsQ2AjEAIL0RtAEgDT6kE86ByP0+AQAQawjaABDFYYLAjkgj6AJAbDpy5IirnK05njW++Mwzz7QWLVpY//797ZxzzglpHaNHj7a777472deNGTPG7rrrLt/3nTp1co8F8/bbb9uDDz4Y8Llp06bZ4MGD3Vho0RRbjz/+uLVs2TLo+n7++Wd77rnnbO7cuXbw4EGrXLmyGzf96KOPWvbs2S0WELQBIIpldChS0A+0D1wAiK6fEwAgczt69Kg1btzYFi9ebKVLl3bjijdv3myjRo1yU1Lp8VCmpFJg7dixY8Dn9u3bZ5MnT3ZfX3XVVQFfc80111ipUqUSPV6tWrWArx82bJj16NHDcubMaU2bNrU8efLYzJkz7frrr7c33njDunbtmmgZTa/VpEkTd2HhiiuusPLly9v8+fPdehYuXGjjxo0LWCk82hC0AQBhB0iCJQAA6efFF190YbpOnTouqBYsWNA9PmTIEOvVq5fdc889rvU3OQrQwUK0WqUVtOvVqxc0tD/11FPWsGHDkPZ5/fr19thjj7lwPWfOHLfvsmHDBqtbt64LzmqRV/j3nDhxwm6//XYXsvXe9BpRq3bz5s1t/Pjxdt1117kW9mgXG+3uAAAAAJAFHT9+3EaMGOG+fvPNN30hW3r27GkXXXSRmw962bJlqdrO2LFj3f2dd95pkTB8+HA7deqU61LuhWypWrWq9enTx06ePOle4+/zzz+3TZs22cUXX+wL2aL37B2D1157zWIBQRsAAAAAotSCBQtct+5KlSpZzZo1Ez3frl0731jolFK4Vbfs3Llz280332yRMH369Hj7F8o+J7WMxnarpX3NmjWu23y0o+s4AAAAAESpn376yRc0A/EeX7VqVapbs1WgrGjRokFfN2nSJJs4caJrqa5QoYK1atXKqlevnuh1e/fudQXbJNDFgXPPPdeKFStmW7Zssf3791uhQoVCfq8bN25071Vjt6MZQRsAAAAA0pHCpT+NY9YtEC+wlilTJuDz3uMKrWndbVwFzPw9+eST9tBDD7ku4Cp4lnCfixYtagUKFAi637t373b7feGFF6bbe00vBG0AAAAACFOBHactZ67TYS1z8sRpX4uuv2effdZNZxWICoFJ/vz5A+/H/4LsgQMHLCWWLl3qCpRpurBgU26pVVrjrFX5XGH3r7/+si+//NL69u1rb731lutyPnTo0JD3Odh+p/V7TU8EbQAAAABIR9u2bfN1l5ZgrdnpwWvN1thsBeZAunXrFu97dRt/+OGHrUGDBq47twqVqTBbwgsIWRnF0AAAAAAgHSlk+9+SCtpelfHDhw8HfP7QoUPu/owzzgh7P1T5W/NSp7TaeI0aNax169ZuPd9++23I+xxsv9PyvaY3gjYAAAAARKmyZcu6++3btwd83nu8XLlyYa9bc3Lv3LnTVfPW3NYpUaVKFXe/Y8eORPu8Z88eXzgOZb/T8r2mN4I2AAAAAEQpzSkty5cvD/i897jm005pt/E77rgjxfunMC3+Rc+KFCniC80rVqwI2HVehdAUmP270Kfle01vBG0AAAAAiFL16tWzwoUL2++//24rV65M9PyECRPcvabaCocKj02ZMiVVQfvYsWO+ua8TTsnV8n+F1bz9C2Wfk1pGgV1Te11wwQVRP7WXELQBAAAAIEqpQFnXrl3d1126dInXFXvIkCFuTmkVJbv00kt9j6s4mea37t27d5JzYmssdO3atX3dvwNZt26dffjhhy5U+9u1a5fdcsstrnVaLdG6IJCwgFqOHDnsnXfescWLF/se//XXX23AgAFuOrCERdbatGnjCq1pPm3/KuZ6z3rv0qtXL4sFVB0HAAAAgCimabRmzZplCxcudKG4fv36bi7pJUuWWPHixW3kyJHxXq9u2evXr483bjqlc2drKq+77rrLheLLLrvMbe/PP/+0ZcuWuWm2NN3XZ599ZtmyZYu3XLVq1WzQoEGuGrn2t1mzZu6igcaFHzlyxF5//XWrXLlyvGVy5crl9qtp06ZuORVqU/fy7777zr2Xdu3aWceOHS0W0KINAAAAAFEsb968NmfOHOvXr5+bY3ry5MkuaHfq1MmNW1Yxs3AotM6ePdsF2w4dOiT52qpVq1r37t1dcF69erWNHz/efvzxRxf4Nf+3WtT1mkB69OhhU6dOdXNwKyyrMrnC+rRp0+yRRx4JuIyKsv3www/Wtm1b++2339zymuNbrfcK3gkDfbTKFhcXF2dZwP79+93Yhmu/us9yFQg8PxwAAACA9HHi0HH7ssV7tm/fvngFsWIlV1za/kXLmStvWMuePHHUlo3vG3PvGeGjRRsAAAAAgAgiaAMAAAAAEEEEbQAAAAAAIoigDQAAAABABBG0AQAAAACIIII2AAAAAAARRNAGkOU0LrYuo3cBAAAAmVjOjN4BAMiIgB1u2J69u3oa7BEAAAAyI4I2gEwtUq3XBHMAAACEiqANIFPK6O7hKd0+LecAAACxj6ANIFPJ6ICdHvtPGAcAAIhuBG0AiPEwTvAGAACILlQdB5CpZMXQqeDt3QAAAJDxorJF+/DhwzZz5kybNm2aff/997ZlyxbLkSOHVa5c2dq2bWs9e/a0ggULZvRuAkDUobUbAAAg40Vli/bHH39sbdq0sZEjR7qA3bp1a6tfv75t2rTJnn32Wbv88stt586dGb2bAKJUVmzVDobWbgAAgPQXlS3auXLlsvvvv9+6d+9u5513nu/xHTt2WMuWLW3FihXuOQVyAEBowulazsUKAACATBa0O3bs6G4JlS5d2t58802rW7euTZo0yY4fP265c+fOkH0EEN0UFBmznHJUPwcAAMhkXceTcvHFF7v7Y8eO2T///JPRuwMAWZZ/t/SkbgAAIPWOHDlizzzzjFWtWtXy5s1rZ599tt1zzz32xx9/pGh9mzdvtgcffNAqVKhgefLksWLFilmdOnVs0KBBQZc5ceKEDRs2zK644gorVKiQq5ul/UluP+bNm+dqbZUqVcptS/t+7bXX2tSpU+O9bu7cuZYtW7Zkby+88IJFu6hs0U7Kxo0bfd3LzzzzzIzeHQBAMsIN23RbBwAgvqNHj1rjxo1t8eLFrpfvDTfc4ILyqFGj7IsvvnCPV6xYMeTD9uWXX1q7du1ceK9Vq5bVrl3bNWKuXr3a/vOf/9jjjz+eaJl///3XmjdvbsuWLXP70LRpU/f4b7/95vZDYfucc85JtNxzzz1nzz//vAvY9erVsxIlSrhQ/t1337nXqx6XR0E8UM9mOXXqlI0dO9Z9rfpd0S7mgvbw4cPdfYsWLdwPCwCCoft4bKLbOgAA8b344osuTKvFWbMzeTMwDRkyxHr16uVCrlqDQ7Fu3Tq76aab7IwzzrBvvvnGDcv1nD592pYvX55ombi4OBfMFbJVnLpv376WM2fOeI2hauFOaPTo0S5kX3nllTZhwgQrU6ZMvJmmvEZUT/Xq1d0ywS4OKGife+651rBhw6g/RWIqaM+YMcPef/9915rdv3//JF+rruW6efbv358OewgASA+R7JJOCzoAIJqpLtWIESPc16pX5T/NsaY9HjNmjOuarRB86aWXJrs+LaMW8okTJ8YL2ZI9e3a77LLLEi0zfvx4mzNnjrVv3961UCcUqDX9yJEj9thjj7lAP3nyZNda7S9//vx2wQUXWKi81uzbb7/ddR+PdjETtHXl5Y477nBXUzRuwBurHczLL7/srp4AyNpo1UZy0mscOYEeAJASCxYssH379lmlSpWsZs2aiZ5XS/OqVats2rRpyQbtbdu22ddff+2C8XXXXRfyPrz33nvu/pFHHgl5mUmTJrnu6GptTxiyw3Xo0CGbMmWK+/rOO++0WBATQVt9+NVVfM+ePe4KTLdu3ZJdpnfv3u61/i3a6mYAAEBGyKjCcAR8AIhtP/30k7vXWOpAvMcVtpOj7uXqHq6W7JMnT7owrCCv8c9qXe7QoYMVLVo0UQG077//3nUVVxE0bUct3Dt37nRjrDVePFAj6OzZs929trV371776KOPbM2aNZYvXz732I033hiv+3lStJ8K27rQcP7551ssiPqg7Q2637Jli9199902ePDgkJbT+G3GcAMQWrWRlUVT5XdCPwAEHtaaVHbZunWru/cf3+zPe1x5KTm//PKLu1f3cxUU07hvf3369HFjqRs1auR7TOOo1dW8ZMmSNnToUPcahXWPupKrIVTPBdrWrl27XDjesWOH7zm99sILL7Tp06eH1BjqdRuPldbsqA/aBw8edGXf9UPSgH11WYiF/vgAACC6Q39KcKEAiOzv+dG8J+3LGD6oZ2w+YjlzxoW1zMmTR919wnCpAmOBxj57mcgb0xxIgQIF3P2BAweS3b56CMt///tfF7Y//vhj13NYYVg1sBRo27RpYz///LOvgri3jLqBq9fwww8/7AqwFS5c2HXnVndyTflVuXJl69KlS6Jt9evXz6pVq2afffaZa/leu3atPfTQQ67omqb8WrJkSZIZTwH922+/tRw5ctitt95qsSJqg7YKmakbwtKlS+2aa66xTz75xB1cAACAjBDrFwoijQsP8PC7ET6Nlfav0p1ePXG9lmh1G9c0XjfffLP7Xt3FP/zwQ1u/fr398MMP9tZbb9mAAQMSLaNGUBVk82j8tVq7FbBVI8s/aJ/+33LKcKoY7l1cUPdzfa9x4trWrFmzrFmzZkH3WTlQXdt1QSC1Y70tqwdtHUhdrVC/fnVpUJ/83LlzZ/RuAYhhdB8HgMgiXGUeKb1owjmQcgrZgabDCsSrMq7psALR2GVRde9Q16V7VRBPSEN1FX5VxTzhMt7zCXXq1MkFbNXV0pzaatn2X65JkyaJWvA1l3bLli1dK7e2lVTQjsVu41EbtFW+/vPPP3dfFytWzHVPCETjtfU8AAAAAItYYE4qfBOw01fZsmXd/fbt2wM+7z1erly5ZNflvUbrDNRdu3z58u5ehc4SLuP/vD91aVdw1jK6eUG7XLlytmLFioDLBNtWQupmrnUotKt4WiyJyqDt9ecXL3AHonEMBG0AoaJVGwCA0BCmo4dX0VtjmgPxHr/ooouSXZc3PZh/3kpYiDphK7bGYleoUME2bdoUcDl1EVdV8YTL1axZ082fHc62ElJ3dlG9rmBj1KNVdotCCtCaLzu5W7CrIwAAAACQGdSrV8+F3d9//91WrlyZ6HlVCZdWrVoluy5Nq3XWWWfZX3/95cZjJ+R1GU84X3fr1q1904MlpMrlx48fd9N2qehZwmUWLlzopghLGM41ZVigbXmU91SsLRa7jUdt0AaAtELxHgAAEEtUq6pr167ua42F9sZky5AhQ9y81g0aNLBLL7003lDc6tWruyrh/jRvdc+ePV2I1br8pxlTUbLRo0e7LuUPPPBAvOW6d+/u9kPr9Z8SbPfu3e45b/y2f1G3Sy65xI291rRjffv2ddv0vPjii7Zu3TrX5Vyt1YF89913bllVP2/cuLHFmqjsOg4AAAAA+D8KqgrCah2uUqWKKxitEKqpsYoXL24jR46Md6gUgNVi7T93tefxxx+3OXPmuPVVrVrVateu7V6vAK2i1Ko2rsrg/tST+O2337bOnTvb1VdfbXXq1HGt7NofTftVq1Yte/XVVxNt6/3333evHThwoOtGrrmzNe5a0zerBfyjjz7yTU8WrAjabbfdZtmzx177cOztMQAAAABkIXnz5nXhWHNSa6yyQquCtip+a4y2psoKVa5cuWzGjBkuGKve1ddff22rV692reLTpk2zp59+OuBymspLs0KpdVmt6DNnznQt0hr2O3/+/IBjrc8991xXzEyt55oGbOrUqS7U33LLLW4a56ZNmwad6tnrEn/HHXdYLMoW59+Gn4mpW4Suulz71X2WqwBThQFZHUVeAADIWEcPnrSnLp9n+/btC3mqq2jKFQ0v72M5c+YNa9mTJ4/a3B8GxNx7Rvho0QYAAAAAIIII2gCyJIqiAQAAIK0QtAFkWYRtAAAApAWCNoAsjbANAACASCNoAwAAAAAQQQRtAFkerdoAAACIJII2ANCFHAAAABFE0AaA/6FlGwAAAJFA0AYAP4RtAAAApBZBGwASIGwDAAAgNQjaAAAAAABEEEEbAAKgVRsAAAApRdAGgCAI2wAAACBoA0CEEbYBAAAQLlq0ASAZhG0AAACEg6ANACEgbAMAACBUBG0ACBFhGwAAAKEgaANAGAjbAAAgIxw5csSeeeYZq1q1quXNm9fOPvtsu+eee+yPP/4Iaz3ly5e3bNmyBb2tW7cu4HIbNmywu+++28qVK2e5c+e2M844wy6//HIbOnSoHT9+PNHrp06dah07drQLL7zQihUrZrly5bISJUrYddddZ1988UXAbaxatcq6du1qtWvXdu8vT548VrhwYatTp4698cYbduLECYsVOTN6BwAgFsN242KB/wkBAABE2tGjR61x48a2ePFiK126tN1www22efNmGzVqlAuterxixYphrVMhOBAF24QWLlxozZo1s8OHD9t5551nN954o+3bt8++++4769mzp02ZMsVmzZplOXP+/3j5wQcf2KRJk6xGjRp25ZVXumCuff7yyy/drXfv3vbSSy/F2878+fPtzTffdGH+/PPPt+LFi9uuXbtswYIF7j1OnDjRZs6c6YJ+tMsWFxcXZ1nA/v373Ulz7Vf3Wa4C0f+DARD9CNsAAKTc0YMn7anL57nAVqhQoZjLFQ0v72M5c+YNa9mTJ4/a3B8GhP2e+/btawMGDHAtuwqaBQsWdI8PGTLEevXqZQ0aNLC5c+eG3KK9ZcsWCycG1qpVy1asWGEvv/yyPfXUU77H//zzT6tfv75t3LjRRo4c6Vq8PStWrLCyZcvaWWedFW9dS5YssaZNm9qhQ4fsp59+ci3eHq1HEl40+Pvvv90ya9ascS3bavWOdnQdB4AUohs5AABIa+qWPWLECPe1Wnu9kC1qTb7ooots3rx5tmzZsjTZ/sGDB11ozp8/vz3xxBPxnlP3bi/0/vDDD/Geq1mzZqKQLWrd7tChgwv6c+bMifecAnaglvmSJUvak08+6b6ePXu2xQKCNgAAAABEKXWbVgt4pUqVXHhNqF27du5+2rRpabJ9ja3Onj352BgoVCe1TgmnC3hKlslIBG0ASAVatQEAQFpS92qv+3Yg3uMqJBaOQYMG2YMPPmjdunWzd999142FDkQFya6++mo3PnvgwIHxnlPXcbWyKwTfeeedIW139erVNm7cOLeMxn2HYs+ePfbaa6+5r1u2bGmxgGJoAJBKFEcDAABpZevWre6+TJkyAZ/3Hte463Ak7Abeo0cPN/5ZlcwTeuedd1woVgEzFTm74IIL3Fh1FS9Tcbbp06e7auiBTJs2zRUxU8VwvRcVVlPIfu+991wrfSC//vqrG5N++vRpNz5by6gLuy4M3H777RYLCNoAAAAAkI4UUhO2GusWiAKmaIx0IAUKFHD3Bw4cCGnbrVu3tkaNGtmll17qqnp7hcyGDx9unTt3dl3AVdXcX7Vq1ez777+3Nm3a2PLly23t2rXucU0HpnWpsnhSLfJjxozxfZ8vXz63raRawBWu/ZeRRx991Pr37x9SN/ZoEBt7CQBRji7kAABkLTk37bCcv/8R3m3TDrfsueee6yqXezdV804vr7/+ugvMqgiu0KuQrG7Zb7/9titQ5hUd86cCZBdffLFrldbXulCwadMm69Onj5tirF69ekG7nvft29etV/OAq9u4KpPff//9LswHmn9brrrqKrfMyZMn3YUA7d/o0aPtsssuc1OExQKCNgBECGEbAACEYtu2ba7AmXdTl+xgvCrjGiMdiKbJEs1TnRr33nuvlShRwtavXx8vzP7777/Wvn17F7I1/7VasLUtTROmFuYuXbq41w8ePDjJ9efNm9d1OdeY7kceecTN/62u6knJkSOHVahQwVVXV6BXl3ItGwsI2gAAAACQjjSHtv8tWLdxUcuzbN++PeDz3uPlypVL1T6pS7Y3ZnrHjv9reReNv1bYrl27tp1zzjmJllMIF43XDtWd/+s2PmXKlJCXUSu8Ljp89dVXQVvCowlBGwAiiFZtAAAQSeqyLRobHYj3uObTTi1V9/Yf9+0f5NXFPRDvcW/ZUBQrVszdB+tuHojGg5955pmuO3k428ooBG0ASIOwTeAGAACRoPHPCrO///67rVy5MtHzEyZMcPetWrVK1XZ+/vln121cRdeqV6/ue7xUqVLufsWKFXbq1KlEy/3www/uXl3JQzVv3jx3H6zqeCAaq60u9+oB4AX1aEbQBoA0QtgGAACplTt3buvatav7WuOhvTHZMmTIEDd/doMGDVwVcc+IESNcWE449nvGjBmumFlCWoe6gKsAmSqPa5ueFi1auK7tKn7Wr18/N+WWR8H8mWeecV+3a9fO9/iuXbvc9F2BxpV/8803vqnFVBjNn8Zs//XXX4mW0XZuu+02t3933XWXG7sd7ZjeCwDSEHNsAwCA1FLl7lmzZrn5pKtUqWL169d382YvWbLETdGl6bn87d6924VT/7HWsnTpUnv++efdeG51SVfrtVqK1f1cXbIbNmxor7zySrxlNE+2Cp1pei1VRx83bpzVrFnT/vnnH1u0aJEdO3bMrrvuOuvUqZNvmUOHDrnK4t27d3cXADTXtx7bsGGDrVu3zjdvd9u2beNtS9XFtYz2rXLlyi5Y630uW7bMBfyrr746XSu0pwZBGwDSGGEbAACkhip2z5kzx4XMjz/+2CZPnuzGKyvcqvK3gmworrnmGtf9Wt29FyxY4Cqeqyu2ptO6/fbbXQtzoNZitairYrjmv168eLErYqaQrsCtwmYPPPBAvOVKlChhAwcOtLlz57ou6T/++KMLygrtt9xyi3u9Qn1CAwYMcK3uev3XX3/tpgTT+2zWrJndeuutbluxMo92tjhdJsgCNNebxjZc+9V9lqvA/+8KAQDppXGx/7uCCwAAzI4ePGlPXT7PF/ZiLVc0LXaP5cweXq44efq4zdo9MubeM8IXG5cDACATYMw2AABA1kDQBoB0RNgGAADI/AjaAJDOCNsAAACZG0EbADIAYRsAACDzImgDQAaGbQI3AABA5kPQBoAMRtgGAADIXAjaAAAAAABEEEEbAKIArdoAAACZB0EbAAAAAIAIImgDQJSgVRsAACBzIGgDAAAAABBBBG0AiCK0agMAAMQ+gjYAAAAAABFE0AaAKEOrNgAAQGwjaAMAAAAAEEEEbQCIQrRqAwAAxC6CNgAAAAAAEUTQBoAoRas2AADwHDlyxJ555hmrWrWq5c2b184++2y755577I8//gjrIJUvX96yZcsW9LZu3bqAy506dcqGDh1qF154oeXLl8+KFy9uN998s61duzbJ7U2bNs0aNGhghQoVcreGDRva9OnTk1zm559/tvbt27ttaFva5rBhw+z06dMxc0LkzOgdAAAAAAAEd/ToUWvcuLEtXrzYSpcubTfccINt3rzZRo0aZV988YV7vGLFimEdwo4dOwZ8vHDhwokeU8BV8P3888+tSJEi1rJlS9u9e7dNmDDBheY5c+bYFVdckWi5YcOGWY8ePSxnzpzWtGlTy5Mnj82cOdOuv/56e+ONN6xr166Jllm0aJE1adLEXVjQOnVhYP78+W49CxcutHHjxrkLAtGOoA0AUd6q3bhY4CvLAAAga3jxxRddmK5Tp44LqgULFnSPDxkyxHr16uVatufOnRvWOkePHh3ya0eOHOlCdpUqVey7776zkiVLuscnTpxo7dq1s9tvv921bCtQe9avX2+PPfaYC9cK4tp32bBhg9WtW9cF5xYtWljlypV9y5w4ccKtSyFb702vkYMHD1rz5s1t/Pjxdt1111mnTp0s2tF1HAAAAACi1PHjx23EiBHu6zfffNMXsqVnz5520UUX2bx582zZsmVptg8KvTJw4EBfyJa2bdta69at7bfffrMpU6bEW2b48OGuu/mDDz7oC9miru99+vSxkydPutf4U5jftGmTXXzxxb6QLXrP3jF47bXXLBYQtAEgyjFWGwCArGvBggW2b98+q1SpktWsWTPR82pR9sZCpwUFX7VWa6y0uoyHuv3p/xuH7T2f2mVq1arlusevWbPGdZuPdnQdBwAAAIAo9dNPP/mCZiDe46tWrQprvYMGDbLff//dde2uUaOGtWnTxhUfC7b9Cy64wHLlyhXS9vfu3Wtbt251Xwe6OHDuuedasWLFbMuWLbZ//35XJC3U97px40a3LY3djmYEbQCIoVZtxmsDAJC1eIG1TJkyAZ/3HldoDccTTzwR73t11VaBMo33Tu32t/5vmaJFi1qBAgWCLqeCalpOVcVTuq1olWWCdlxcnLs/ceh4Ru8KAKTY14cqWoOzNnAEAQAx7+jBk/E+p8eak3HHzU6nYBkz14rrT63KugWiQmCSP3/+gM97QfbAgQMh7YPGVDdq1MguvfRS14KtFmIVO9N46c6dO9tZZ53lqpqnZvsHk1kmpcuF+14zUpYJ2t4PY1bbMRm9KwCQKl9y/AAAmexzeqAppaJV7ty5rVSpUjb3r7EpWl6FvdR12t+zzz5rzz33nKWH119/Pd736jauAmPVq1e3+++/35588sl4QRspk2WCtiZ037Ztm51xxhkxMe9atNDVNv0h0LHzxk6A4xktOD85ntGKc5PjGc04Pzme0UIt2QrZ+pweS/LmzesKhKkaeErfd8I8Eqw1W7wq44cPHw74/KFDh9y9ck5q3Hvvvda3b183LZeKjXljoFOy/YLJLJPUcnv27Enz95oeskzQzp49e9C+/kieQjZBO3I4npHF8eR4RivOTY5nNOP85HhGg1hqyU4YtnVLD2XLlnX327dvD/i893i5cuVSnZdU2Xznzp22Y8cOX9BOyfbL/m8ZhWaF40DjtIMtp2X0nKYtS6v3mh6Y3gsAAAAAopTmlJbly5cHfN57PFAwDZdCrvgHY2/7mlbrxIkTIW2/SJEivrC9YsWKRMuot6wKoSkw+zfmped7TWsEbQAAAACIUvXq1XMt/5qKa+XKlYmenzBhgrtv1apVqrbz888/u27jKkSm8dqeChUq2HnnnWdHjhzxzXMdyvZb/m/Obe/51C6jwK7CbZpmLNqn9hKCNpKk8SIqzpDUuBGEjuMZWRxPjme04tzkeEYzzk+OJ2KLiq917drVfd2lSxffOGUZMmSIm1O6QYMGroq4Z8SIES4s9+7dO966ZsyYYbNnz060Da2jffv2bvy4Ko9rm/569uzpmxJMXcs9kyZNsqlTp1rlypUTFVDr1q2b5ciRw9555x1bvHix7/Fff/3VBgwYYDlz5nSv8ae5vBXsNZ/20KFDfY/rPeu9S69evSwWZIuL1Xr6AAAAAJAFHD161Bo2bGhLliyx0qVLW/369d1c0vpeU3QpyFasWNH3elUwf/75561jx442evToRI+ry7a6aav1Wq3E6pJ98uRJtw2F8Xz58sXb/unTp61du3b2+eefu7mxmzRp4rp+z5s3z41VnzNnjl155ZWJ9nvo0KEupCtUN2vWzAX4mTNnutZxVT9/5JFHEi2zcOFCa9q0qXuN1ql9/e6779y4ce3DZ599FhPFrWnRBgAAAIAo5oXZfv36uXA8efJkF7Q7derkQrJ/yE7KNddcY/fcc48bF71gwQLXRfu3336zq666yt577z2bNWtWopDtFUobP368mwZMVeK/+OILW716tbVt29Z+/PHHgCFbevTo4Vq869Sp48Lyt99+a5dddplNmzYtYMiWunXr2g8//ODWrX3T8meeeaZrvR83blxMhGyhRRsAAAAAgAiiRRsAAAAAgAgiaCMeTQ6vriiasL5atWqum4rK+2sMxwsvvGAHDx7kiKXCP//8YyVKlHBdXlQ0Aim3a9cue+yxx9x5qi5O6lJUq1Yte/zxxzmsYVDXrJtvvtl1A8uVK5ebjkPjvkaNGuUKoiCxZcuW2SuvvGI33XSTlSlTxv0+h9KNTWPkrrjiCitYsKA7X6+77jo3Di0rC+dYanyguh2qEI8K/pxxxhmuqJfmfH3wwQdt06ZNltWl9Nz0p3GR3nLB5szNKlJ6PDX90bBhw9zvu7rn6ne+atWqrrvuH3/8kS77DiDj0XUc8fz3v/+1++67z32tMv4qn79//373YfDAgQOueqGKHigsInwaR/PBBx+4AKMPhxp3gpR9+NEYI124qFGjhu88/eWXX9wHQxXzQPImTpxoHTp0sFOnTrmLFLr4owsYCjM6hrfddpt99NFHHMoEbrzxRpsyZUqi45LUhYnu3bvb8OHD3UWh5s2bu6I2GqemZTQ+TuvMisI5lvp7WaVKFfd1qVKlXIhRNdulS5e68KLgrQI+GmeYVaXk3Ex4Mejuu+92YVLLaJ5bBcysKiXH899//3W/4/o/pYJVtWvX9p2/Gs+qv69Z+RwFshRVHQc8o0ePjrv//vvjfvnll3gH5c8//4yrWbOm/rPE3XrrrRywFJg1a5Y7fjq+uq9UqRLHMQV27twZV6xYsbj8+fPHTZkyJdHzS5Ys4biG4MSJE3ElSpRw5+JHH30U7zn9/p955pnuudmzZ3M8E3jllVfi+vXrFzd16tS4HTt2xOXJk8cdq2C++eYb9/xZZ50Vt2HDBt/jCxcujMudO3dckSJF4vbs2ZMlj3M4x/K3336La9asWdy3334bd/r0ad/jR48ejevUqZNbrmzZsnHHjx+Py6rCPTcT/m3V733z5s3jypUr55bbtm1bXFYW7vHUedmoUSP3mmeffdb9nfX3+++/x+3atSsd9hxANCBoI2T6UKh/HvpHc+zYMY5cGA4fPuyC9fnnn+8+aBO0U+6hhx5yx+/NN9/kHEyF1atXu+NYrVq1gM8/+uij7vlXX32V45yM5D58X3vtte75oUOHBj3OgwcP5jiHcCyT+htbuHBht+zcuXM5liGem/5uu+22uLx587oLGgTtlB3PcePGuefbt2/POQggjjHaCJnGacuxY8dcl12ETvMVao7Cd955x42DRcpoPsWxY8e6ugHq3oiU09jWUJx11lkc5lSes7Nnz3Zfa+7PhLzHNM0JUk5d8jUGVv78808OZZi++uor+/jjj61Pnz5uWBNSRlMjSbApiwBkLTkzegcQOxQURUFRhXwQmlWrVrk5BxUMVWRq8+bNHLoU0jyNqhWg8W36YP3ll1/aN99848a76kO2V9QLydN8m/pAvX79evcBW+OxPWvXrnUXNIoWLWpt2rThcKaCjq8uThYvXjzgWFeNjff+TiDlVChN88l647cRukOHDtlDDz3karCo0BxSRgXQvv/+e8uZM6erH6Dfac05vHPnTjvnnHPshhtu8DVYAMgaCNoImQr5SIsWLUJuDcvq9OGvc+fOrpLzwIEDM3p3Yp6KnYmK8QUqUvP000/b+++/b7feemsG7WHsUBGpMWPG2PXXX2+33367uxikQlP6UKhiPeeff74rjMRFtdTZunWruw9WUEq9M/T3Yc+ePe4ikgp6IXyffPKJO3d1QaNu3bocwjA888wz7gLw3LlzLXfu3By7VDRG6KJvyZIlbejQoa53gD4DeJ577jnr1q2bew5A1kDXcYRElVwVYNSa3b9/f45aiN544w03fdKgQYPoghsBCiMydepU19XxzTffdB+u9SFRU32pm27Hjh1t5cqVnKMhqFevnptFQK3by5cvt3HjxtmcOXMse/bs1qxZM/c4UsebEjF//vxBX6OwLQraCJ8qY6uqu2gaSi4Eh06/97qIrr+bDRo04PSLwP8nDa3r3bu3m3Lu999/t927d7vPT+qFpSm/9H8LQNZA0Eay1q1bZ3fccYebzkKBka5Pobdk9e3b13140bReSD2vdUBTT+kD9cMPP+xasMqVK+fOzfbt27vue/oaobUCqovjueeea0uWLHGhcMOGDe58VQt348aNXbdnIJq7PWuOY4UZ9XJRuEFoNK2f1+Nq8ODBHLYI/n+69tprXaDWxUrVudD82d7/pZdffpljDWQRBG0kSXOTqqu4rtT27NnTdXtCaLp06WLHjx93BdAQGQULFvR9HagYmveYWmmRtF9//dW1YhUrVsy++OILF7jVsqru4//5z39cl3K1do0cOZJDGYFz9vDhw0mGRaHbeHh0UU0X11S7QXUbVGsAoVPr6ooVK9ywJv0dQNr+f/IuuOtzlebUBpD5MUYbQf3777/WvHlzV2BG/zS44h0ehRe1FCRsYdEYLu+fbcOGDd3Xn376KQV8QqCWa68brlqyEypfvry7V3dyJE3nnIKKLqT5f0D0qLCczuH58+e7QklImbJly7r77du3Bw3Ze/fudYXnCNrhtR7qQpEKIl5yySWuaru65iJ0OmbZsmVztRo++OCDeM/99ddf7l4XMtQV/6mnnnJ/K5D8/yf//0X+9H9L9UX0/0m3ypUrcziBTI6gjYDUhVRdn1R8St3yNGWF/iEjPPoAHax1VYHbe84L30hazZo13b3GYqtLc8KxmLo4JIGCI+Lzgl/hwoUDHhrvcW/cIVKmWrVq7jzdtWuXu7im6sP+1GtALrroIg5xGDR9koY+aLaBr7/+2l3URPg0JEwX04JZvHixu2f4U/L0N7NChQq2adOmgH83dXFInwmE/1FA1kDXcSSiAKNpKJYuXWrXXHON+zCjCsUI/wNMoJv+CYumVvIeC3T1G4FbB1UjQMcs0AUM7zEvkCM4bwokdbsNREX8hHMzddTKqrHuoql+EpowYYK7b9WqFadriFT74q233nJ/DzS9n1oJET5VGQ/2f8prnVWhOX1P0A5N69atfcc20EULDSfT3wRdgAOQ+RG0kag4iqZGmj17tpvzedKkSUz3gajizfOqKuM7duzwPa5K4yrgJRRESp4upolas95+++1EHwi9KWjatWsXwZ9e1qT6FvLiiy+6sfGeRYsWufHwao299957M3APY4fOywEDBrgLRbNmzfJ1zQeigarfa4q0ESNG+HoDiIr1eZXxNRSPyvhA1pAtTpcqgf/RNB/eP4M2bdpYoUKFAh4bjdemeErKaCoqdS9TizYFUVJGrSsaV6iAojlz1ZV84cKFrjfGfffdZ++++24K15y1PP74477aCzVq1HBzZ//5558uAKqb4/333++CIOKbPn16vGkO1ftH/0qvvPJK32P9+vWzli1b+r7X31X9fdU4TU2dppYttcZqObVqq2J2VhTOsdTFtFq1arnn69Sp47qNB6JK2iqOlhWl5NwMRD1ZVJ9FLdrB5oDPClJyPFVAUudgzpw53XmqLuX6/6Rpv3T+qucVXceBrIEx2ojHf1zR559/HvToPPfccwRtZJhRo0a5OaAVAtVFT/UD9AHmgQcecAWSEBpNN6MLFaqMv2zZMlu/fr0ryKUp6XTBQr1bkJjGW2s6tIT8H9NrElZ4VtEutXQpYKvVq2nTpu5Dun4GWVU4x1LjW722AV0M0i0QFZnMqkE7JecmIns8NZWXpvV65ZVX3Ot0IVjfq66AemJpdgcAWQMt2gAAAAAARBBjtAEAAAAAiCCCNgAAAAAAEUTQBgAAAAAgggjaAAAAAABEEEEbAAAAAIAIImgDAAAAABBBBG0AAAAAACKIoA0AAAAAQAQRtAEAAAAAiCCCNgAg6sydO9eyZcsW77Z79+403Wb37t3jba9hw4Zpuj0AAJB55czoHQAAIJhKlSrZVVdd5b7Omzdvmh6oK664wjp27GgHDx60iRMn8kMBAAApRtAGAEQthezRo0eny7Zuu+02d9u8eTNBGwAApApdxwEAAAAAiCCCNgAgIjp06ODGNj/xxBOJntuwYYMVLFjQ3X799deIbE/bKl++vJ08edL69+9vlStXtnz58tl5551no0aN8r1u9uzZ1qhRIytUqJAVLVrU7rrrLvvnn38isg8AAACBELQBABHxzjvvWJkyZey1116zOXPm+B4/ceKE3X777Xbo0CEbNmyYValSJaJH/Oabb3bbvPDCC+3qq6+2TZs22T333OPC9oQJE+yaa65xYVz3BQoUsA8//NBuvPFGi4uLi+h+AAAAeBijDQCICLUWf/DBB9a0aVPXarxq1Sr32HPPPWc//vijC7edO3eO6NHesmWLnXHGGa6VvHjx4u4xhfzGjRtbnz597Pjx4zZ58mRr2bKle27//v1Wt25d+/77711lc7V0AwAARBot2gCAiFFw7dWrl23fvt0efPBB++677+yVV16x0qVL23vvvZcmR1qt5F7I9vahZs2atmPHDrv22mt9IVvUffz+++93X8+bNy9N9gcAAICgDQCIqBdffNEuueQS++yzz+z66693XbTVjbtYsWIRP9K5cuUKON91xYoV3X3z5s2DPqcgDgAAkBYI2gCAiMqdO7eNGTPG11VbLdsaH50WSpUqZTly5Ej0uIquyTnnnBP0uWPHjqXJPgEAABC0AQARN27cON/XK1eutFOnTqXJUc6ePXuqngcAAEgLfAIBAESUCo29+uqrrrVZhdEWLVpkAwYM4CgDAIAsg6ANAIgYdRW/8847XQu2xmWPHTvWFSrTPNdLlizhSAMAgCyBoA0AiJiuXbva5s2b3X2LFi2sZMmS9t///tfNY33HHXe4ubQBAAAyO4I2ACAixo8fbx9++KGdf/75NnDgQN/jrVu3tvvuu89+++0369atG0cbAABkegRtAECq/fHHH/bAAw+4iuMfffSR5cuXL97zQ4cOtSpVqtj7779vn3/+OUccAABkajkzegcAALFP02j9+++/QZ8vUKCAbdiwIaLb1PzcwYwePdrdAtG820ktCwAAkFoEbQBAVFcw79Spk/t6xIgRvjmw08LHH39sM2fOtIMHD6bZNgAAQNZA0AYARK3ff//d3WTw4MFpGrSXLl1qY8aMSbP1AwCArCNbHP3nAAAAAACIGIqhAQAAAAAQQQRtAAAAAAAiiKANAAAAAEAEEbQBAAAAAIgggjYAAAAAABFE0AYAAAAAgKANAAAAAEB0okUbAAAAAIAIImgDAAAAAGCR8/8AkVkJ+fSAuNkAAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 1200x400 with 2 Axes>"
       ]
@@ -487,7 +487,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 26,
    "id": "baf1e542",
    "metadata": {},
    "outputs": [
@@ -613,7 +613,7 @@
        "[4000 rows x 3 columns]"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -638,7 +638,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 27,
    "id": "441f059a",
    "metadata": {},
    "outputs": [],
@@ -660,13 +660,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 28,
    "id": "d04fa7ad",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 1200x400 with 2 Axes>"
       ]
@@ -711,7 +711,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 29,
    "id": "857acdd2",
    "metadata": {},
    "outputs": [
@@ -923,13 +923,13 @@
        "[4000 rows x 8 columns]"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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0uZi4uDiXn2P79u3SsWNHE3ZHjx5tm4vqzMaNG2Xr1q2SP39+efTRRyWYRUxA1cqpql+wo0RHpd/dCgCASJNUtlhm7wKACJN0/aqs3DjG9jk9VGjlVMPp8rVFJE8e90ZmxsenSN17T5hQnjdvXtv17lRPjxw5Yob0nj17Vvr27Su9e/d2uXratm1btyu1gRYxAdUqo2s4JaACACCSVL5E5H0gABB0QnX6nYbTPDe5OzT5n6qrhlP7gOqqM2fOSOPGjU239K5du8qYMWMyfIyuRf3111+by1p1DXb8PQIAIAIDKQAgtMTHx5sGRzpUt3Xr1mZNU1fC/aJFi0zX3tKlS0udOnUk2IXWbGQAAOARwikAhK6rV69KixYtZO3atdKkSROzvnTWrFldeqw1vFerp6FQrSagAgAQ5ginABC6rl+/Lu3bt5fFixebCuiMGTMkJsa1njqXL1+WmTNnhkT3XgtDfAEACLGwGb3niFv3BwCEro8//tgWMmNjY6VXr14O76fzUfV2ez/++KMZGnzPPffIbbfdJqGAgAoAQIiwwmaq5kbphFXCKQCEvrNnz9ouW0HVEV2mJm1AtR/eGyoIqAAAhGFFlXAKAOEhLi7OrTVS7c2bN09CDXNQAQAIcWnDKOEUABCqqKACABAGCKUAgHBABRUAAAAAEBQIqAAAAACAoEBABQAAAAAEBQIqAAAhgDmmAIBIQEAFACDIEU4BAJGCgAoAQBAjnAIAIgnLzAAAkAkhM3rPEbcfAwBAuCOgAgDgJ+mFTL3NUUglmAIAIhkBFQCAdDgLjOlVQD0JmQRTAAAIqAAAeFwBdRRY3QmahFIAAFKjggoACElWuMtoLqc3z+3vxwAAgNQIqACAkOZOMKQxEQAAwY2ACgAIOZ5WK+0f58mQXAAA4F8EVABASPFVoCSYAgAQfKIyewcAAHAVoRIAgPBGBRUAEPQNjQimAABEBgIqAMCv7MOlXrYPqQRPAADSd/nyZVmwYIHMnj1bVq5cKQcOHJCsWbNKhQoV5PHHH5e+fftKnjx5MjyMDRs2lEWLFpnLhw4dkpIlSwbloSegAgD8xlEAJZQCAOC6adOmSY8ePczlypUry2OPPSYXLlyQVatWyZAhQ2T69OmybNkyKVKkiNPnmDRpkgmnWbJkkZSUlKA+/ARUAIDPED4BAPCtbNmySc+ePaVPnz4moFqOHTsmzZs3lz/++MPcpkHWkZMnT8rLL78sjRs3lh07dpgKbDCjSRIAwCfBlHAKAIDvde7cWcaPH58qnKpixYrJuHHjzOUZM2ZIYmKiw8dreNVhwp988klI/HoIqAAArxBMAQDIHHfddZc5v3r1qpw+ffqG23/55RdTWX3jjTekfPnyEgoIqAAAAAAQgvbu3WsbBlywYMFUt126dEmee+45qVSpkrz22msSKpiDCgAAAAABpE2O7GXPnt2c3PXhhx+a86ZNm97w+MGDB8v+/ftl6dKlEhMTI6GCgAoAAAAAblpwqZLkyOJenEq4lCQif0upUqVSXa/deOPi4tx6rnnz5smECRNM9XT48OGpbtu4caMJrzp/tV69ehJKCKgAAAAAEEC6DmnevHltP7tbPd2+fbt07NjRLBkzevRo21xUdf36denevbvkz59fxowZI6GGgAoAAAAAAaTh1D6guuPIkSNmSO/Zs2elb9++0rt371S3f/DBB2bpGa2uxsbGSqghoAIAvPtDsucInXwBAAiAM2fOmPVMdS3Trl27OqyQzp49W7JkySKTJ0+WKVOmpLrt+PHj5rxt27amatuvXz8TdoMJARUAAAAAglx8fLw0a9ZMtm7dKq1bt5bPPvvMBFFHdOjv8uXLnT7X6tWrzXmXLl0c3l6uXDmf7LPu3549e9x6DAEVAOAR1j8FACAwrl69Ki1atJC1a9dKkyZNZPr06ZI1a1aH99Wuvc6UKVPGVF91DmzJkiWd3k+7//qCswCdHtZBBQC4HUwJpwAABMb169elffv2snjxYqlTp47MmDEjIMvGaHU1OTnZ45N2EPYEFVQAiCBWsNR5o67czx5zTQEACLyPP/5YZs6caS5r06NevXo5vJ/ORw3FpkhpEVABIAKkDZyeVECpmgIAEHhnz561XbaCqiO6jqqvAur7778vVapU8eo5OnToINWqVXP7cVlSdAZtBLhw4YLky5dPGsZ2k+go/5fEASBYECwBAMEoKSlBlq4bIefPn/d4yZXMzBVvr6snOfK4V+9LiE+SfvcsC7nXHEjMQQWAMEY4BQAAoYQhvgAQpginAADAn3QJmW3btklUVJQZEqxdgr1FQAWAMEQ4BQAA/nLu3Dnp3r27bU6szhrVJWW02/D48eMld+7cHj83ARUAwgzhFAAA+NMzzzwj8+fPl8GDB8u9994rly5dkmnTppmThlMNqZ4ioAIAAAAAbBITE52utaprnP7444+m06/9kjdt2rSR++67T77//nuvAipNkgAgDCqm9icAAABv6HzSOXPmOLwtKSlJrl27JkWKFLnhNl3m5urVq15tm4AKACGKQAoAAPyhQoUK0qJFC3n00Udl7969qW7TyqoO6x0wYICsXLlSEhIS5MyZM/LRRx+ZYb8PPPCAV9smoAJAiCGYAgAAf/rll1/MUN3//e9/cvvtt5u5phpELf/5z38kPj5e6tWrZ+acFi5cWHr37i0lSpSQDz/80KttMwcVAEIEw3cBAECgtGrVSpo1ayYjR46U0aNHy5QpU8y8U72+evXqsnv3bpk6dars2LHD3F+DbIcOHSRHjhxebZeACgBBEDSj9xxx6/4AAAD+pmFz6NCh0qVLF1Mhffzxx6Vx48YyduxYufXWW6Vnz54+3yZDfAEgCDhqcsRQXgAAEAzKli0rP/30k8ydO9fMSb3zzjulX79+ZnkZXyOgAkAAuVINJZgCAIBgpEN+dV6qzkn9+OOPpVKlSvLNN9/4dBsEVAAIEIbqAgCAUHHw4EF58cUXpW7dulK1alVp3ry5aY6UJUsW08F327ZtUrNmTWnfvr00aNBAtm7d6pPtElABIAAIpwAAIFQsW7bMVEe1SnrixAnJkyePrF+/Xl544QUTSrWjb6lSpeS7776ThQsXyvHjx6VatWry8ssvy8WLF73aNgEVAAAAAGDzyiuvmPVOV6xYIdu3b5fff/9djh49Kv3795c//vhDvvjiC9t9H3roIdm8ebO89dZb8vnnn5tg6w0CKgD4GdVTAAAQSrZs2WKG7dauXdt2XdasWeW1116TlJQUE0jtRUdHm1CrYVYf5w0CKgAAAADApnjx4qZSmna4rg79VcWKFRNH9Povv/xSvME6qAAAAAAQpC5fviwLFiyQ2bNny8qVK+XAgQOmmlmhQgWzLmnfvn3NHFF7hw4dMvdfu3atrFmzRnbs2GEqn0uWLJH69etnuE19Tm2QpMN1W7RoIQUKFJCdO3fKnDlzJH/+/NKtWze/vV4CKgD4EcN7AQCAN6ZNmyY9evQwlytXriyPPfaYXLhwQVatWiVDhgyR6dOnm8pmkSJFbI/54Ycf5KWXXvJ4m9oMqVChQvLmm2/Kf//7X0lOTpYcOXLIww8/LCNGjDANkvyFIb4AAAAAEKSyZcsmPXv2NMu46Onbb7+VX375xVRFq1evbuZ99unTJ9VjypUrZ6776quvTOWzcePGbm9Xl4/RNU+1gvv333+bcw2+3jZBCpsK6unTp803BidPnpTy5cvL7t27M3uXACBdVE8BAIC3OnfubE6O5nuOGzdO7r//fpkxY4YkJiaazrtKq6x6sujapZ7S5yxcuLAESshUUHVNnVOnTmX2bgCASwinAADA3+666y5zfvXqVVPQCwchEVAXLVokkydPto29BoBgRjgFAACBsHfvXtsw4IIFC/rsebX6OnbsWK+e48MPP0xVxQ2bgHrlyhV55plnpEqVKmZtHQAI5mBKOAUAABnRJkf2J62AehoCVdOmTSV79uziK9qtd9OmTV49hz5+7ty54TcHdejQoeabAe1Mpd8MAEAwIpgCABBZlp2+VbIl/DPn01XXLiXqI2/ogqvdeOPi4tx6rnnz5smECRNMRho+fLj42vHjx2X58uVePd4TQR1QN2/eLO+++6507dpV6tSpI/v378/sXQKAGxBOAQCAO3Sd0rx589p+drf6uX37dunYsaNZ23T06NG2uai+NH/+fHPylO6bJ82Zgjag6lo73bt3NwvBjho1KrN3BwAcIpwCAAB3aTi1D6juOHLkiBnSe/bsWenbt6/07t3b578AR12DAyVoA+pHH30k69atk4kTJ5pFYt2l47jtx3Lr2G4A8CSARu854vQ2AACAQDlz5oxZ0/TAgQNmlOmYMWP8sh3NYJklKJskHTx4UAYOHCj16tWTLl26ePQcI0eOlHz58tlOacd5A4CrDY8IogAAILPFx8dLs2bNZOvWrdK6dWv57LPPvFrfNFgFZUB9/vnnzUKzn376qcfP0b9/fzl//rztpOO8AcAVjgIpIRUAAGSWq1evSosWLWTt2rXSpEkTmT59umTNmjUsfyFBOcRX2xrr3NNnn3021fUJCQm2cdf169c3l7/++mspWrToDc+hE4192WoZQPjLKISmN9wXAADAH65fvy7t27eXxYsXm8axM2bMkJgY97oHh5KgDKjq3LlzZmkZRzSoWrdZoRUAPOVOdZSQCgAAAunjjz+WmTNnmsuxsbHSq1cvh/fT+ah6uzp27Ji0atUqVddfpY+1mjM1b95cBg0aJMEmKAOqtiR2RJeZKVu2rJQvX152794d8P0CEH48GbpLSAUAAIFy9uxZ22UrqDqi66haAVWHBK9Zs+aG+2zbts12uVKlShKMgjKgAkAgeDOvlDmpAAAgEOLi4szJHWXKlHFa9At2QdkkCQD8jYAJAAAQfAioACJOMITTi2VzmhMAAECw279/f8C2FVJDfEO5VA0AFvtgal2+ad8Vrw5QemHX2+cGAACRrUKFCtKwYUPp0aOHWe4mOtp/MZIKKoCIEgzVU0c8raa6Uom17uPoflRyAQBARrRJ7YIFC6Rdu3ZSsmRJ6devn+zatUv8gYAKAAGUXph0Jyx6Giztw2raSi5hFQAAOLJjxw5ZsmSJWY/1woULMmrUKNMFuEGDBvL1119LYmKiROQQXwAIleqpN/NL9bE6LDez5qjab5fhwQAAQNWrV8+czp07J19++aV8/vnnsnTpUlm2bJkUKFBAOnXqZIYAV65cWbxBBRUAvJS2KumLYBksDZTsX4+vXyMAAAg9+fPnl3//+9/y559/yurVq6Vbt26mgvrhhx/KHXfcIXXq1DEBVtdi9QQVVAARwdPqKUGM4wAAABy79957JV++fJIlSxZTUVW//fabrFq1Sl555RUZNGiQvPDCC+IOKqgAwh7h1D+opAIAEJkSEhJMlbRu3bpSpUoVE06LFi0qAwYMkF9//VW6d+8u8fHx0rt3bxk+fLhbz01ABQB4haAKAEBk2Lx5sxneW7x4cenSpYuplj744IPy7bffysGDB+XNN980jZPGjx8vW7dulSJFish///tft7bBEF8AYStYl5QJV75a0xUAAAQXrZB+9tlnsn79eklJSZFChQrJSy+9JM8884xUrFjR4WNKly4tjRo1kq+++sqtbRFQAYQlwmnmIagCABBeevbsac7vv/9+efbZZ6Vt27aSPXv2DB935513yqFDh9zaFgEVQNghnAYHgioAAOHh+eefN9VS7dLrDm2UpCd3EFABwInMXIs0nDhbV9XZsWWIMAAAweXVV1+VPHnyZHi/s2fPysWLF+WWW27xeFs0SQIQVnxdPSUs+ZYr66g6WleWLwoAAMg8ZcuWNSE1I6+99pqUK1fOq20RUAEAIYGQCgBA5tDGSHpy9b7eYIgvgLDhy+opYSg4Ma8VAIDgderUKcmZ07vpUQRUABEdTAmioUl/bwy/BgBEgg0bNsjChQtl7dq15nTkyJEMK5VHjx6Vt956S3755RfTRTdr1qxSoUIFadWqlWladNNNN2W43eXLl6f6+fjx4zdcZ0lKSpIdO3bI/Pnz5fbbbxdvEFABRFSVlEAaPhz9LgmtAIBwM3z4cJk1a5bL99+1a5fUrl1bTp48KWXKlJFHHnlEEhISZNWqVTJs2DD5/vvvzeV8+fKl+zz169eXLFmy2H7W8KknZzQw6/1ffvll8QYBFUDIIJwiI3QGBgCEm1q1apn1RO+55x5z0tB59epVp/d//fXXTTjt1auXjB071lRP1fnz56Vp06ayevVqee+992To0KHpbrdTp062gDp58mQpX768Cb6OxMTESPHixeXRRx+VGjVqePV6CagAgLCXUeWcyisAIFi9/vrrbt3fGoY7aNAgWzhVWjHVLrutW7eWdevWZfg8kyZNsl3WgPrAAw/IF198If5GQAUARDyaLwEAwkX27NkzvE+hQoXces7k5GQJFJaZARCx4ktE3XBCZGPtVQBAqGvcuLFt7ur169dt1+sQ31GjRpnL3bp1k2BFBRVARHC1OZIVUvMcCdw3hQid9w1DgQEAvnDhwoUbqp6uVD5dMXLkSNP595NPPpF58+bJ3XffbZok/fbbb5IjRw6ZOnWqPPjgg+k+hzZT0vmnzz//vBQsWND87Cp9nA4v9lSWFG9XUg2hN4GOu24Y202io2Iye3cAZPJyMu5USwmrcISwCgDeSUpKkKXrRpjKXt68eUMuV5SbPECy5srh1mOvX06QvZ3fuuH6IUOGSFxcnEvPoSFTmySlF+POnDkj7du3lwULFqS6XuefjhgxQipVqpTuNqKiokzQ3LZtm9x66622n12Jjno/+8qtu6igAgh73oRT6/6EVDh7XxFUAQDu0rVJ7UO5r6qnavPmzdK8eXPTIEmXp6lbt65cunTJLC/Tv39/Wbp0qVlm5rbbbhNnJk6caM6LFSuW6udAIKACCHmBWNuUob9I7/1HSAUAuEPDqT+qxteuXZM2bdrI0aNHTadea8mX/PnzS+/evU1lU9cpHTx4sHzzzTdOn6dz587p/uxPdAQBEFHh1NtGSDRTgi/ehwAA+MPq1atl165dUrZsWYfrkbZt2zbVUjTBiAoqgIjhyy69DPtFWlRSAQCZ7fDhw+Zc58g6Yl1/9uxZn2wvKSlJPv/8c/nrr7+kVKlS0rNnTylQoIBXz0kFFUBEVK38sYQM1VSkRSUVAJCZihYtas537NghFy9evOF2HfarypQp49bzahdfndNqX3nVtVHr169vOv1qx+ABAwbIPffcI+fOnfPqNRBQAYSkYAoCrKOKYH1vAgAiS61ataRIkSKmKdILL7xguv1adF7qSy+9ZC7rPFV3LFy4UEqWLGkaLlm06ZI2W6pataqMHz9eWrRoIXv37pVx48Z59RoIqADCfokZf1RP09sWgRWEVACAr8ydO1dq1qxpOyUmJprr7a/T+1hL0GhYjI6OlilTpkj58uWlZcuW0qRJE7O0zJYtW8zc1H79+rm1Dxo8K1eunOq6GTNmmCVlpk+fLj169JAffvjBDPPV4OoN5qACCLlQav/h39vweblksjnPdTgqaLr/Mr81MkIqnX8BAK44efKkrFmz5obr7a/T+1g0kK5du1bGjBljhuTOmzdPYmJipGLFitKuXTvp06eP5Mzp3mif06dPS2xsbKrrli1bZp7TCq4aVnWI75IlS7z6xRJQAYRMldTb9UwzCqr+CqmuBNW0r8WV18barKGNdVQBAK7o0qWLObmjevXq8tVXX/nsAGs4PXLkiO3nrVu3yt9//22G9drTIGxVeD1FQAUQEnxZNU1bPQ1USPVHJ2FFUA2f9zZVVQBAMNIqqVZM//jjDxN+33vvPVMxffjhh1Pdb//+/VKsWDGvtkVABRBSQyP9PZ/U30N+/YGgGj6oqgIAgpE2V1q0aJEZwps/f36zTI2utdq0aVPbfc6fPy8bNmyQxx57zKtthc4nMAARL5DNjjSoWqdQwbI34RVU7U8AAGQmrZR+9NFHUqJECbly5YrUrl1bZs6caYb0WrQp07Vr1+Shhx7yaltUUAFEZCh1J3iGWlXV/pgx/Dc8eBpSGTIMAPAVXe9UT850795dOnXqJHny5PFqOwRUACEbTtOGTH8HSPvthVJYJaRGLoYMAwACRTsDu9sd2BECKoCQkVHVMxBNjlzZl2ALr4RUaFClmgoACAXB9SkKABzw9VxQf88rtZ+/GkpzWBHemM8KAPCGLi2jy92UK1fOVEqzZs3q8BQd7V0NlAoqAEQAqqiwUE0FALjr999/l4YNG5oGSapgwYJStGhR8QcCKoCwEshhvqG2TyxHAwshFQDgjv79+5tw2qdPHxk4cKAJqP5CQAWACAqpGTWfoqFS5CCkAgBctX79eqlWrZq899574m8EVAAIkFDoAswSNZGFLr8AAFfoeqeVKlWSQCCgAgg7wVStDOW1VZ1VWqmyhh+qqQCA9DzwwAOmSVIgBO8nIwDwQ8fdYOuqG2z7g8hldflNe0p7OwAg8rz11luye/duGTdunN+3RQUVQFgKhSpqKO6rYhhwZEkbSqm2AkDk2bhxo3Tt2lVefPFF+fbbb6VRo0ZSsmRJiYpy/PmlU6dOHm+LgAogKKXXyAfBg+VrIhNzVwEgsnTp0kWyZMkiKSkpsmLFCnPSn9PS2/V6AioAuIDhtP5BSI1c9tXVm/b9szYeACD8DB482GEg9QcqqACCmjX0lXAZ3AipYOgvAISvuLi4gG3L44C6f/9+WbZsmWzatElOnjwp586dk/z580vhwoXNGjn16tWTMmXK+HZvAUR0UHUUUqOLXzbnSUdzpTu3k4Drf4RUEFIBwPc2bNggCxculLVr15rTkSNHbMNpnYXJoUOHOn2+119/Xd5+++2g/VW5FVDPnj0rkydPls8++0y2b9/u9MBY5d/KlStLjx49zBjkAgUK+GqfAUSAtEuZaPhJG1KtcIrgmzvMUjSRi5AKAL41fPhwmTVrltuPq127tlSoUOGG6++++26v9ufPP/80QfnUqVNy++23y2OPPWauv3r1qjnlzZvX/wH18uXLMmrUKHn33Xfl0qVLkjNnTrMWzr333msWbC1YsKDZkfPnz5sQu23bNrPT69evl5deekkGDhwor7zyirz66quSK9eNVQ4AyIgGHkch1Vsach1VX+EdgmpkI6QCgO/UqlVL7rzzTrnnnnvMSUepahDMSPfu3U1zI1/ZsWOH6eS7Zs0a23WdO3e2BdRp06aZbc6dO1eaNm3q34Barlw5OXHihDRp0kQ6duwoLVu2lNy5c2f4OA2zM2bMkKlTp5oy8/jx4+Xo0aMe7yyAyOCo2Yp+4E0vpHoSNK0KLCHVfwiqkYuQCgC+8frrr2f6oTx06JDUrVvXTO3UQFqnTh1TfLTXrl076dWrl/zwww9eBdQoV1O7jn3++eef5cknn3QpnCq931NPPSXz58831dT77rvP4x0FENms0Go/dNSVQKpB1pWKa2YPFw73ObIsGxSZ0q6hCgAITcOGDTNDej///HP58ccf5eWXX3aY/bQXkX2F1W8V1JkzZ4q3atSo4ZPnARDZ0gs63lZCM7uSah9SreZO4YRqamSikgoAmWPx4sWmoW1CQoKULFlSmjVr5vH8019++cUMM+7WrVu699PhxwsWLBBvsMwMgJD5kGsFHCvIOap6uhoynVVMMzukRkJYJahGHtZLBYDA+/LLL1P9PGjQIHn88cdl0qRJkidPHreeS6d7atOljFy7ds30L/IGARVASAwJtA+n9uGyctG/bZe3Hb85LCqpzsJquAbVtOgAHN4IqwAgcuHChVSHIXv27ObkC9q5d8yYMaZiWrp0adPEdvny5fLaa6+Z+aHXr193e2RroUKF5ODBgxneb+fOnVKsWLHMC6i6Dqqejh075rSTlC45M2HCBG82AyDCOAsu6YVT62dXQqor802DLaSGe1U1vd8/gTV8uTNH1VHzNADITNeP55KUHDncekxywj9/40qVKpXq+iFDhpj1S31Bm9qmnRvaoUMHefDBB6Vq1apmDunq1aulZs2aLj+nVk/1cTpkWOeZOqK58K+//vK6c7BHAfXMmTPSqlUrWblypdMFYi0EVAC+YB9O7YNpg9h/1mRWi09VcjmkuiIYQ6r98QjnkOossBJWI5cVZgmqAMKBdsW1Xy/UV9XT9GhlU5eJ0eqqzil1J6DqkqFadW3RooV8+umn0rhx4xvmu2owjY6Olj59+kjAA6qubbpixQqzMGvPnj3NMjTujmMGAHcqhhmFU3v2IdXbTr3WY4IxqIbr0N/0MH8VBFUA4UDDqX1ADZSKFSuacx0B6w5djWXs2LHSu3dveeSRRyRXrlymEKlDhjW46pBl/fmTTz4xzZQCHlBnz55tOkH9/vvvBFMAfuVsSK99OH04z1aZF1/FXKdVVPuQ6qvlY+yfJ9jCaiRVU+2DKtXUyEZQBQD36XxU5eqyofZ0jVNdmeXtt982FVMdSXvx4kXJkSOHNGnSRN544w2XGin5JaDqxFpdG5WqKYBASS+cZhRSfc1RWHUWhAMVZiM1pCqCamQjqAKAazRQWs2RNGh6QocF61xUfS5dFzU5OVliY2Mla9as4isefZrR9XOOHz/us50AgFClwdRXVVpfDokGAACR5+TJkzJu3DhT2bQXHx8vzz33nKxZs0aKFi0qrVu3dut5tQuwdui16HDewoULy80335wqnO7atcvcN+ABdeDAgWZ4r06uBQAEj0gMqc66PiOyuNMRGABCydy5c03l0jolJiaa6+2v0/uoS5cuyQsvvCDFixeXBg0ayJNPPmkaGpUpU0bGjx8v+fPnl++//97MIXVH/fr15Z133snwfqNGjTLdggM+xFdf7LRp06RTp07y8MMPS6NGjaREiRISFeX4Q0LdunW92kkAkUuHyGqFUofqWsN8dQivNcxXh/Vaw3uDTWbPVU0bVsN5CDDDfQEA4VwVXbNmzQ3X21+n97HWK3399dfNMjJa8Vy1apWpcJYtW9Z02dVmt5rbPJHR6i2u3sdv66BqmThbtmzy5ZdfmlNGc1YBwFvphVREdhXVQlCNbFpFZRkaAOGmS5cuLq8tetNNN5kmRpnl6NGjXvcp8iigTpo0SZ5++mmTkKtXr+6XZWbee+89s87qli1b5MSJE5KQkGDGS9erV09effVVs8gsgPCmFT8NW1YVFQAAAIExZcqUVD/v3r37hussSUlJsmPHDvn111/dWl/VkSwpHtRhq1SpIvv375d58+aZ8cj+oN2gdAy1rqNjlaH/97//mVK1Vm5nzJhh1uBxla7Nky9fPmkY202io2L8ss8AvJNUvoRtHplVCXN3LVSrg6/FH118Q2F4ryPhPMQ3LTr7Ri4qqEDoSEpKkKXrRsj58+czZU1QT1m5ovQ7b0pUjhxuPTY5IUEOvD4wJF5zVFSUaYbkKo2VuuTMTz/9JA0bNgxsBVXDqVYy/RVO1axZs0y3YH2R9nTx1+eff166d+8uhw8fluhoj0cpAwjygKEh1aqiOhvq62049ddSNAAAAKFs8ODBJqBq8Bw2bJhUq1ZNWrRo4fC+MTExpjGTNmQqVqyYV9v1KN1pRdPdzk/ucrbIqy4Qq8N/9+zZI1u3bjUVVgDhVf1I240zvaG+1lzUtOHUHb4OqcFYPY00+uUGVdTIxDxUAPCNuLi4VFM8tSo6ZMgQ8TePxntp994lS5bImTNnJDPoEF8rqQMIX44ChhX+7AOlo3BKVRQAAMA3dAStLiETCB4F1AEDBpj1bfS0dOlSn7QTdpV2DNYJuBUrVjQnAAAAAEB48GiIrxUMDxw4IA899JCpaGqHXUfroOq4ZR2O66nRo0eb5kjaMGnbtm3mso5vnj59ulnTBwAAAADgX7qyivYDWr58uRw7dkyuXr3q8H7e5j+PmyTZS0xMlIMHD4o/zJ8/XxYtWmT7uXTp0qa9sTZQSo8eMPuDpt22AAAAAADu0UKhNsk9ffq030fPejTENzk52a2TN3QtHT0IZ8+eNWldq7d6cEaMGJHu40aOHGnaP1unUqVKebUfAAAAABCJXn31VTl16pS0bt1a1q9fb4p//sp/IbMoXv78+aVOnTpm7VWtng4aNEjWrVvn9P79+/c36wtZp0OHDgV0fwEAAAAgHKxYsUJuu+02+fbbb6VGjRqSJ08ev20rZAKqRee7PvHEE6aqOnv2bKf3y549u1n81v4EAAAAAHCPZi9dB1Xnl/qbSwFVGxP5gq+eJzY21pyfPHnSJ88HIHSkXQcVAAAA/vWvf/3LNMgNBJcC6p133int27eXzZs3e7SRP/74Q9q1ayd33XWX+MKyZcvMefny5X3yfACC2+WSN85lqFz0b9vlBrHbvXp+1kyNjDV0ERlu2ncls3cBAMJOXFycmV6Z3ghWX3Gpi++QIUNkzJgxZsxx1apVTVjVRkXVq1c3Q2nTSkhIMKFU10idNm2abN26VXLnzm2exxW//fabXLx4URo3bpxq6Zpr167Jp59+atZCzZkzpxnqCyDyqqeOwqmeLz5VKSjCqe5n0tFcPn9eAOkjnAKA//Tu3ds0SerQoYM0atRISpYs6XCZUVW3bl3/BtTBgwfLs88+azrn6hIv2oBIxx9HR0eb7rgFChSQm266yYTKM2fOmIZE169fN2OVtYOuvhh9TOHChV3aqV27dknXrl3NUF5tiFSoUCHTNWrLli1mzZ0cOXLIpEmT6MwLhLn4ElHpDu31tnKK8ET1NDIRTgHAf+rXr2/yn+Y7LRZOnTo13ftrFvT7OqhFihSRDz/8UN5++21TSZ0zZ46sXLlS9u7de8N9ixYtajruNm/e3Azt1UDpDq3ODhgwwAzl1WHFGk5jYmKkTJky0qZNG3nxxRelQoUKbj0ngPAY3mtfPU3L0yqqP1BFzRyEUwAAfK9Tp04BaZDkVkC16NDazp07m5PVqOjEiRNmKRetlmqQdbVS6kzZsmUzXOcUQORVT3057xThh3AKAIB/6OjVQHE7oKalYdTbQAoArjZHcuThPFtlXnyVVFVUDbOZ3fwos6qouQ6H3ApiXiOcAgDC1YYNG2ThwoWydu1aczpy5Ii5XofbppWcnGz6+Wgzo0WLFsnOnTslMTHRzBfVeaOvv/66KQYGM68DKgD40sWyOVP9nFH1VMNp2pAaySIxnAIAEM6GDx8us2bNcum+Ov3SalCk0y4bNGggWbNmNcF2/PjxpoHtvHnz5IEHHpBgRUAFENTDe70RiCqqVkiDZW3WSA2nVE8BAOGsVq1aZtnPe+65x5y0L8/Vq1cd3lfniWqltF+/fvLggw/a5o3q/bXprQ7VffLJJ2X37t2SLVs2p9scNmyYx/ur2xw0aJDnj09xVBsOQxcuXDBzZBvGdpPoqJjM3h0ADiSVL2GrompItYb4ulpFtSqoVqMkf4bTYFxGJhIDKuEUig6+QGhKSkqQpetGmF42efPmlVDLFaXfeVOi3GwGm5yQIAdeH+jVa86RI4cJnO7GuCtXrkixYsXMtnU5UG1M64wuH2N17XWVdX89D0gXXwDwt+g9R2wh9Z/g8U9ItaqUVuDUoGqFUA2q9kN7/R1OCabBgWAKRTAFAPea3d56662ybt06OXr0aLr3HTJkiGQWAiqAoAupN0kJU0VNG1LN7WmCqj1H4dT+ceEUSiO1akowhSKYAoD7tIHSgQMHbPNT00NABYAMQqpKG1RV2nVPHYVT67InITVYwynBFJGIYAoAnps+fbpZHlRXYLn//vslWFFBBRASIVXnpFqhzJqbqmHUvorqLJx6GlKDLZxGWihVVEzDH6ETQCTSeaz2smfPbk7+cujQIenTp4+tAZI/t5UpAXXo0KHy9NNPm/V0ACBwldR/OvxqULss/39eatpuvekFS1dDajCF00gIpgTRyEIoBRAOch6JkqzZ3fsbff3qP/cvVarUDUNq4+LixB8uXbokrVu3llOnTknLli1NN99g5nFAffPNN6Vp06bSo0cPeeSRR0ynJwDwV0hV9tVUlbZ5knVdRjIKqcESTsM9mBJKIwuhFABSVzTtu/j6q6J57do1adu2raxfv96sfarroAY7jz79aDi95ZZbZO7cudKqVSvzDYCudbN//37f7yGAiKchNe0HXEfhzZ1g6ey+wRBO9bWFczjVYEo4jRz675ZwCgCpaTi1P/kjoCYnJ0vnzp3l559/lmrVqsns2bNNJ99g59EnoAEDBsiePXtkwYIFJpGfPn1aRowYIRUqVDBV1R9++EGSkpJ8v7cAwpouMePsZL8+qv08VFe4GvYyO5wSTBFuCKYAkHn+/e9/m8ZIurTM/PnzJX/+/CHx6/DqK/qGDRvK119/LUeOHJExY8bIbbfdZkJru3btzPzUfv36ya5du3y3twAilqNw6spc0vTCaWYHUntUTBFuCKcAkHkGDhwon3zyiRn1unDhQilSpEjI/Dp8MoasUKFC0rdvX/nf//4nK1eulPbt25sWxqNHj5ZKlSrJQw89JDNnzvTFpgBESBhNe7I4q5x6Gjb1cdYps4RjOLWG8TKUNzIRTgEg87z//vtmdKuudfrrr7+akOqtKVOmyKpVqzK83+rVq819g2aZGR32q2ObFy1aZLtOK6lLliyRpUuXyt13322G/6btWgUAGdHqadpw6s6yMabzrxvDggNJ9ytcQiqBFIRTAPCtuXPnyvDhw20/JyYmmvOaNWvartN+QM2bN5dNmzbJyy+/bK4rW7asCaqOdO/e3TRNclWXLl3MKaP1UydMmCBffPGFdOrUSTItoGpnKA2dn332mQmhKSkptorqM888IxUrVpTff//dHJx58+bJCy+8ILNmzfJ2swDCnDWc15XKqTtrm8J/CKcgnAKA7508eVLWrFlzw/X21+l91Llz50weU5rB9ORI/fr13Qqo7jRmypIli1fP4XFA3bZtmwmlX375pZw5c8YcCE3Uuq6ONk6y70RVq1YtmTNnjkn5y5Yt82qHASAtZ8Nzw6UqGQoIpyCcAoB/dPl/1UtXaPC0Ampm2Lt3b6rlcwIWUDVtaxrXF6878Nxzz5lgescdd6T7uNtvv13WrVvn6b4CiEC+HJYbzMN8QxnhNLIRTAEgPA0bNizVzzp8OO11Fl3BZceOHbJ8+XJp1KhR4AOqTpCtUaOGCaUdOnSQXLlcay6iY53r1q3rySYBAEGIcBq5CKYAEN7i4uLMcF0tSuq5BlQ9pUe7Bb/11luBD6haBdWGR+7Sob56AgCENoJpZCOcAkD4mzhxojnXgNqtWzczivbpp592eN+YmBgpXry4mdJpP9UzYAHVk3AKAMEgGIf5htpcWcJpeAdPXdaJAAoA6Ny5s+0gTJ48WZo1a5bqOn/x6TIzABAJgTKSgql9GNXOyoTT8GWFUsIpACAtXTY0UAioAIKSBqG0S82EU/gL5v1zFkIJp+GJQAoACCbB+wkJAMKQBtPMDqeOgqZeZ50QOQinAABXbd261Sx3U65cOcmZM6dkzZrV4Sk62rsaKBVUAAiQzA6mygqgBFEQTgEArtIlRhs2bChXrvwzHaRgwYJStGhR8QcCKoCwEwxBMBj3iVAKRTAFALirf//+Jpz26dNHBg4caAKqvxBQAYRVo6RgCILBuD+EUyjCKQDAE+vXr5dq1arJe++9J/5GQAUQNKL3HJGk8iVsS13YN0pKL+i52+XXV52BgyV8ZoRwCoIpAMAbus5ppUqVJBAIqABCJqQGS1AMlWCqCKeRjWAKAPCFBx54wDRJCoTQ+ZQFIKJCqv2Ha/sOs5kZuIKhA68rguFYwT/034Sjk7P7AQDgC2+99Zbs3r1bxo0bJ/5GBRVAULMqqfas4OXtOqmhOq81PYTS8OJqyCSMAgD8aePGjdK1a1d58cUX5dtvv5VGjRpJyZIlJSrK8WekTp06ebwtAiqAoB7qmxkCHUhdGcbsynMgfBA4AQDBRNc/zZIli6SkpMiKFSvMSX9OS2/X6wmoAMJ+PqrFvprqi2CXGcHUUZj09LUQTMMP4RQAEGwGDx7sMJD6AxVUACFVSU075NebkGo/zDcQ4TSjMOnO0GWCafggkAIAgl1cXFzAtkVABRAWIdWeO4HV38HUkyBJ+Aw/hFAAAFxDQAUQdrwJrP7cD0QOAikAwNe2bdsmb775pixevFjOnDkjxYoVk0ceecRUN2NjYwN2wP/8809Zu3atnDp1Sm6//XZ57LHHzPVXr141p7x583r1/KHTmhIAQigoEk4jF+EUAOBrixcvln/9618ybdo0yZ8/vwmm2bNnN8u+VK9eXQ4fPuz3g75jxw65//77pUaNGvLss8/KwIED5ccff7TdrvtWoEAB+eWXX7zaDgEVQEQIVGBk/dHIRjgFAPja5cuXpUOHDuZcmxVpJfWHH36Q7du3yyuvvGLC6dNPP+3XA3/o0CGpW7eurF69Wh599FEZNWqU6dhrr127dhITE2P2zRsEVAARw1ch1Qqhjk6IXIRTAIA/zJgxQ/7++2+57bbbZMiQIbbrtavuW2+9JWXKlJEFCxaYobf+MmzYMDOk9/PPPzdV05dffvmG++TOnVuqVasma9as8WpbBFQAISkzwgAhFM4QTgEA/rJhwwZzrhXMqKjU8S1btmxSu3Ztc3nWrFl+2wcdtnvnnXdKt27d0r2fhuUjR454tS0CKoCQDgXOgoF1W9rbPa1yUh1Feu9DAAD85dKlS+Zc53c6UqhQIXPuzwrqiRMnTAU3I9euXTNDkb1BF18AYR8QvF07lXAKT997AAA4cuHChVQ/a8MjPTlSuHBhc37gwAGHt+/bty/d231BQ/DBgwczvN/OnTtNd2FvUEEFEDJrofqSq6GTcAp3q/cAgMiQ+5jznhTOTvoYVapUKcmXL5/tNHLkSKfbqVu3rjmfO3eumQdqT4fTLly40Fy+ePGi316rDiNet26dbNq0yel9li1bJn/99ZfUr1/fq20RUAFEREh1NUzQ9AiO3jtpTwAAeNsV9/z587ZT//79nd63cePGZmmX+Ph4adasmVmDVC///vvv5uekpCRzv7TzU31JuwVr194WLVrIzz//LNevX79hGZynnnpKoqOjpU+fPl5ti4AKIGIrqXThhTOEUQCAP+XNmzfVydnwXqtbr3byvf3222X9+vVy3333yU033WTWJNW5oXFxcenOUfUF3ebYsWPl6NGjZg1WXYtV90uXlNHtNmrUyNz28ccfm2ZK3mAOKoCQDKlJ5Utk9m4gzFAZBQAEq9KlS5vhtTNnzpRVq1bJlStXTGB98sknTXhV+rM/9erVy1Ry3377bVMx1YqqDivOkSOHNGnSRN544w1bR2FvEFABhCRCKrwNoFbjLIIpACAUREdHS9u2bc3JngZW5e3cT1fUrFnTrIOq4VTnwyYnJ0tsbKxkzZrVZ9sgoAIIWYRUZCS98EkwBQCEuuPHj8v3339vuuy2bt06YNvV4b1Wd2FfI6ACiJiQah9I7JedQWgjaAIAwt1ff/0lFSpUMMNpLYcPH5bHH3/cDLOdNGmS5MwZHp9tCKgAIrKSml6oIbwGP0IpACCSjBkzxsw/1Tmgus6oNkdauXKlXL16VQYNGiSdO3f26fYaNGjgVXV10aJFHj+egAogrLr7+qJ5EpXW4EY4BQBEmpYtW5rhvH/++af89ttvpnNu06ZNzZIu/ph7unTpUq8CqjcIqACAkEE4BQBEakBt2bJlwLa3b98+ySwEVABAUCOUAgAQ+GVtMgsBFUBY8WVnX+aiBg4hFAAAKAIqAIDgCQAAggIBFUDY8WXDJHiGiigAAOEja9asbjVJSkpK8nhbBFQAYcuboMrwXs8QTAEACD+lSpVy2J03OTnZdBe+du2az+auElABwEnQIqS6h3AKAEB42r9/v9PbNKQuXrxYevfuLVWrVpXp06d7ta0orx4NACFUSYXvA6n9CQAARJ6oqChp2LChzJkzR+bOnSvvvPOOV89HBRUAnHAldEVilZUwCgAA0ipbtqzUrFlTvvjiC+nXr594ioAKICL4cvmZ9MJauAdWwikAAHAmV65ccujQIfEGARUAAhjgnAVYV4NfZgZgwikAAHDmwIEDsnz5crn55pvFGwRUABHDX1VUb5svuRP87O/r67BqPbej5yWcAgAQuaZMmeL0tvj4eNm5c6dMnTpVLly4IL169fJqWwRUABElGEKqr4JfeoHSm+0QRgEAgL0uXbo4XGbGkpKSYs47deokQ4cOFW8QUAEgxJewSRtUrecnaAIAAF8YPHiw04AaExMjxYoVk7p160q5cuW83lZQBtTLly/LggULZPbs2bJy5Uoznjlr1qxSoUIFefzxx6Vv376SJ0+ezN5NACEqGKqo/giP9s9JOAUAAL4SFxcngRKU66BOmzZNWrVqZVoUazB97LHHpE6dOrJv3z4ZMmSI3HPPPXLixInM3k0AAAAAgA8FZQU1W7Zs0rNnT+nTp49UrlzZdv2xY8ekefPm8scff5jbNMgCQKRWYQEAAAJt1apVsmLFCjl69Kj5uXjx4vLAAw9I7dq1wzegdu7c2ZzS0rHN48aNk/vvv19mzJghiYmJZswzAAQyYOpjAQAAIsmWLVtMs6RNmzalaoxkzU296667ZNKkSXLnnXeGX0BNj75wdfXqVTl9+rQJrQDgbdB0NawSTgEAQGY5efKkvPPOO6ZXz8GDByVnzpxSpkwZeeihh2T06NF+2+6OHTukXr16cu7cOSlZsqS0adPGbFdpv6AffvjBBNf69eubCmulSpXCaw5qevbu3WsbBlywYMHM3h0AYcKV4Ek4BQAAmWXDhg1m+uO7775rslCLFi2kZs2acubMGXn//ff9uu0BAwaYcNqvXz+Tx9577z158cUXzUn3Z8+ePdK/f39znzfeeCOyKqgffvihOW/atKlkz549s3cHQBixAqijairhFAAAZGbltGnTpnLlyhWZNWuWaSJrb+3atX7d/pIlS+T222+Xt956y+Ht2th2xIgR8tNPP5n7RkxAnTdvnkyYMMF8YzB8+PB076tDgPVkuXDhQgD2EEA4BlXCKQAAyExDhgyRU6dOmX48acOpuvfee/26/WvXrrk0t1Tvs3//fq+2FTJDfLdv3y4dO3Y0k3F1fLU1F9WZkSNHSr58+WynUqVKBWxfAYQHDaaEUwAAkJmuXLkiU6dOldy5c0vXrl0zZR80e+kw3ozofTLKaWERUI8cOWJK2mfPnpW+fftK7969M3yMjoE+f/687XTo0KGA7CuAyEF4BQAA/rZ+/Xq5ePGiVK9e3TRF+vnnn00m6tWrl3zwwQe25V78SeeVrlu3Tr744gun95k4caK5j85XDeshvjrpt3HjxqY7lH5jMGbMGJcep/NTmaMKwN9YDxUAALgr7fTD9LLL1q1bzXmRIkWkZcuWZg6qPQ2EOg2yffv2PvtFLF++PNXPWr197rnnpEePHmYpmSeeeEJKly5tbtOc9u2338rKlSvNffLkyRO+ATU+Pl6aNWtmfimtW7eWzz77zLbODgAAAABklpv2X5Ho6H/WAnVVUlKCOU87/VDnmMbFxTl8jI4iVdqASJsR6TzUtm3byuXLl+Xjjz82BbzOnTubDr/VqlUTX9DlYhzlLp1uqUH0t99+u+F69Z///Mecrl+/Hn4BVRscaetk7UjVpEkTmT59uvmFAECwoYoKAADcodMP8+bNa/s5vZGfycnJ5jwpKcl0ytWhvRbtzaMVzO+++85c/uqrr3zyi+jUqVOmFQaDMqBq4tYS9eLFi6VOnToyY8YMiYmJyezdAgCnCKkAAMBVGk7tA2p68tgNmXXUJEmv04C6bNkyn/0CdBhvZgnKgKql6pkzZ5rLsbGxqb4lsKflbL0dAIKxaZKj9VQBAADcUfr/zfXMlSuXFC5c+Ibby5QpY85PnDjhtwM7duxYs/3u3btLRAZUa5y1soKqIzpOm4AKAAAAIFxVr17dttyMToNMOxxYm8oqb5sTpefll1+Whx9+OCABNSiXmdHgqRNtMzpZ3xYAQDBiGRoAAOCtW265xawtqvnH0TBe6zoryPpD0aJFJUeOHBIIQRlQASBcEFIBAIC3XnvtNXP+yiuvyLFjx2zXb9q0Sd59911z+dlnn/Xbgdamtdq9NzExUfyNgAoAAAAAQaxDhw5mKZktW7ZIlSpVpHnz5tKgQQOpWbOmGeKr65Pq0jP+ot2DdUWVJ598MlVAjpg5qAAQTujwCwAAvDVx4kSpXbu2jB8/XpYuXWqWgalRo4Y888wzJrz6U//+/c0wY11dZe7cuWa7OvTY0bBf3a8JEyZ4vK0sKdaqqmHuwoULki9fPmkY202io1iyBkBg0dEXAIA0fxuTEmTpuhFy/vx5l5dcCaZcUf+eNyQ6OkdEvOaoKNcH3mpA1WVDPUUFFQACgCoqAAAIVUuWLAnYtgioABCo/3D3HKGSCgAAQk69evUCti2aJAEAAAAAggIBFQACiGVnAAAAnGOILwAEcYCluRIAAMhsusSMO02SkpKSPN4WARUAMnEuakYVVet2gioAAMgspUqVMsEzreTkZDl+/Lhcu3bN/Fy6dGmvt0VABYAQGOpLUAUAAJll//79Tm/TkLp48WLp3bu3VK1aVaZPn+7VtpiDCgAhRIOqdQIAAAiGNVIbNmwoc+bMkblz58o777zj3fP5bM8AAAFFWAUAAMGibNmyUrNmTfniiy+8eh4CKgCEAaqqAAAgs+XKlUsOHTrk1XMQUAEgjBBUAQBAZjhw4IAsX75cbr75Zq+ehyZJAAAAAACnpkyZ4vS2+Ph42blzp0ydOlUuXLggvXr1Em8QUAEgzJeyAQAAcEe5cuWkbdu2toZHXbp0cbjMjCUlJcWcd+rUSYYOHSreIKACQJgipAIAAE+XlTl58qTt58GDBzsNqDExMVKsWDGpW7euCbbeIqACQBgjpAIAAG/FxcVJoNAkCQDCHGumAgCAUEFABYAIQHdfAAAQChjiCwARxN1qqtVoyXocjZcAAAi89957T1auXClbtmyREydOSEJCghQtWlTq1asnr776qlStWtXn29y0aZMMGzbMo8fqnFVPZUmxWi6FOW15nC9fPmkY202io2Iye3cAIKQRVAEAXv8tSUqQpetGyPnz5yVv3rwhlyvq3/OGREfnCMhrjo2NlUuXLsmdd94pJUr88+Xx//73P7O8S7Zs2WTGjBnyyCOPiK9ERUWl27XXGY2W+rjr1697vG0qqAAAryqxhFUAAPxr1qxZcvfdd0uOHKkD8SeffCLPP/+8dO/eXQ4fPizR0b6Ld+XLl5fatWtLoBFQAQDe/SFhzVUAAPyqtpOg2KtXLzP8d8+ePbJ161ZTYfWVBx54QL744gsJNJokAQAAAECIypYtm2090nBAQAUAAACAEPTll1/Kjh07pGLFiuYUDhjiCwAAAAAhYPTo0aY5kjZM2rZtm7lcvHhxmT59umTNmlXCAQEVAAAAAALcCdhe9uzZzSkj8+fPl0WLFtl+Ll26tEyZMsU0UAoXBFQAAAAAcDdI7Tvm/vKVyYnmrFSpUqmuHjJkiMTFxWX48F9//dWcnzt3zqyJquuU6lqob775przxxhvu7Ut6u5mcLJmFgAoAAAAAAXTo0KFU66C6Uj21lz9/fqlTp47MmzdPatWqJYMGDZLGjRvLPffcI6GOJkkAAAAAEEAaTu1P7gZU+w6+TzzxhKSkpMjs2bMlHBBQAQA+WQsVAAAEXmxsrDk/efJkWBx+AioAwCcIqQAABN6yZcvMefny5cPi8BNQAQA+DakEVQAAfOe3336TX3755YbGRdeuXZOPPvrIrIWaM2dOM9Q3HNAkCQDgtyG/SeVL+OX+AABEil27dknXrl3NUF5dTqZQoUJy6tQp08X32LFjkiNHDpk0adINnYFDFQEVAOC/PzIZBM+01daMqq8EWABApKlXr54MGDDADOXdvHmzCacxMTFSpkwZadOmjbz44otSoUIFCRcEVABAQIOqN0OA9bGEVABAJClbtqyMGDFCIgVzUAEAAeOL+am+nOPKfFkAAIILFVQAQMjxppLqbFgxlVkAADIfFVQAQEjydfWTDsQAAGQ+KqgAgLAPqVZ11JX7U1EFACDzEFABAGHPk2qrq0HV0XOzvA4AAJ4hoAIA4MZ8V3eqsGlltNwO82ABAJGOgAoAQIDmu9qHXUfP6U01FgCAcECTJAAAAsjdZkwshQMAiCQEVAAAAABAUCCgAgAQ5KiiAgAiBQEVAIAQQEgFAEQCAioAAAAAICgQUAEAAAAAQYGACgAAAAAICqyDCgBAGM5TZf1UAEAoooIKAEAYoIkSACAcEFABAAjxYOoonBJYAQChiIAKAECIIoQCQOS4cuWKDB48WG699VbJkSOHFC9eXLp16yZHjtz4JWUoYw4qAABhGkj1/sxFBYDQl5CQIA0aNJDVq1dLsWLFpEWLFrJ//36ZOHGizJkzx1xfrlw5CQdUUAEACGNUWQEg9L355psmhNaqVUt27twp33zzjaxZs0beffddOXnypKmkhgsCKgAAETpPFQAQ/BITE+Xjjz82l8eNGyd58uSx3da3b1+58847ZdmyZbJhwwYJBwRUAAAiBCEVAELPb7/9JufPn5fy5ctL9erVb7i9TZs25nz27NkSDpiDCgBABGGtVAAILX/++ac5r1GjhsPbres3b94s4YCACgBAhHJWUaWxEgAEj4MHD5rzkiVLOrzduv7AgQMSDiImoKakpJjzpOTEzN4VAACC2659qX5MKlss03YFQPhKun411ef0UJOUkiiS7MFjROTChQuprs+ePbs5ORIfH2/Oc+XK5fD23Llzm/OLFy9KOIiYgGr9wpaemZrZuwIAQGg5ldk7ACDcP6fny5dPQkVMTIwULVpUlh73LFdok6NSpUqlum7IkCESFxfnoz0MbRETUHUh20OHDslNN90kWbJkyezdCRn67Y7+A9Jjlzdv3szenZDH8eR4BjPenxzLYMV7k+MZzHh/ek4rpxpO9XN6KMmRI4fs27fPdNf19HWnzSPOqqfK6tp7+fJlceTSpUvmXHNOOIiYgBoVFeV03DYypuGUgOo7HE/f4nhyPIMV702OZzDj/cnxDAahVDlNG1L1FAi33HKLOT98+LDD263rS5cuLeGAZWYAAAAAIEjddddd5nzjxo0Ob7eu1/VQwwEBFQAAAACCVO3atU2lec+ePbJp06Ybbv/+++/N+aOPPirhgICKdOl4eJ20nd64eLiO4+lbHE+OZ7DivcnxDGa8PzmeCC0xMTHywgsvmMvPP/+8bc6peu+998z6p/Xq1ZO7775bwkGWlFDt6wwAAAAAESAhIUHq168va9askWLFikmdOnXMuqf6c+HChWX16tVSrlw5CQcEVAAAAAAIcleuXJGRI0fKtGnTzAobBQsWlKZNm8rw4cPDqhksARUAAAAAEBSYgwoAAAAACAoEVKSiCwD/+OOP8vTTT8ttt91m1nfKnTu3aW89bNgwiY+P54h54fTp01KkSBGzOHOFChU4ll44efKkvPLKK+Z9mjNnTjPMpUaNGvLqq69yXN2wbt06adeunVkkPVu2bJI/f34zr2XixIlmIXHcaMOGDfL2229L69atzZAq/fecdsF1RyZNmiT33nuvWXBd368PP/ywrFq1KqIPsTvHMjk5WVasWCGvvfaaaQSiC9Jrs5/y5cvLs88+K/v27ZNI5+l7017Dhg1tj3O25mKk8PR4Xrt2TT744APz713XmtV/87feeqt069ZNjhw5EpB9B0IZQ3yRyueffy49evQwlytXrix33HGHXLhwwXyIunjxolSqVEmWLVtmQhbc16VLF5kyZYr54K8fqnbv3s1h9PBDQ5MmTUzgv/32223v061bt5oPVElJSRxXF/zwww/yxBNPyPXr10241y9NNPhrCNBj2KFDB/nqq684lmm0bNlSZs2adcNxSS/Q9+nTRz788EPzZUrjxo1Ns4tFixaZx+jyAPqckcidY6n/X1asWNFcLlq0qPnwnzVrVlm7dq350K+Bdd68efLAAw9IpPLkvZn2S5SuXbuaEKaP0Tlu4TSvLRDH88yZM+bfuP6d0kY2NWvWtL1/t2zZYv5/jeT3KOAS7eILWCZNmpTSs2fPlK1bt6Y6KEePHk2pXr26/o+c0r59ew6YB3799Vdz/PT46nn58uU5jh44ceJESmxsbEquXLlSZs2adcPta9as4bi64Nq1aylFihQx78Wvvvoq1W36779gwYLmtsWLF3M803j77bdTBg0alPLTTz+lHDt2LCV79uzmWDmzcOFCc3uhQoVSdu7cabt+1apVKTExMSn58+dPOXv2bEQeZ3eO5e7du1MaNWqUsmjRopTk5GTb9QkJCSldunQxj7vllltSEhMTUyKVu+/NtP+36r/7xo0bp5QuXdo87tChQymRzN3jqe/LBx980NxnyJAh5v9Ze3v27Ek5efJkAPYcCG0EVLhMP0zpf7r6H/TVq1c5cm64fPmyCaRVqlQxH1AJqJ577rnnzPEbN24c70EvbNmyxRzH2267zeHtL774orn9nXfe4ThnIKMPrc2aNTO3v//++06P85gxYzjOLhzL9P6PzZcvn3ns0qVLOZYuvjftdejQISVHjhzmiwACqmfH85tvvjG3t23blvcg4AXmoMJlOg9VXb161QythOuGDh0qe/fulU8//dTM84Pn7dWnTp1q5kXrMDR4TufuuaJQoUIcZi/fs4sXLzaX27Rpc8Pt1nWzZ8/mOHtBh07rHD919OhRjqWbfvnlF7NsxRtvvGGmn8Azn332mTn/97//zSEEvBDtzYMRWTRgKQ1Y2uADrtm8ebO8++67JlBp85n9+/dz6Dy0fv16Mxda5+/oB9Kff/5ZFi5caObz6YdTq9kPMqaLeesH0R07dpgPpjrf1LJt2zbzRUCBAgWkVatWHE4v6PHVL/V0EXVHc/l07q/1/wQ8pw2UdMF6a34qXHfp0iV57rnnTI8JbUAFz2hjpJUrV0p0dLSZH63/pr/77js5ceKElChRQlq0aGH7oh9A+giocJk2+FC6ILCr1ZdIpx+aunfvbjqjjho1KrN3J+RpEySlTbocNa8YMGCATJgwQdq3b59Jexg6tLnM5MmT5ZFHHpEnn3zSfImiDWj0w5Q28ahSpYppmMKXUd45ePCgOXfWaEZHA+j/D2fPnjVfvmijH7hv+vTp5r2rXwTcf//9HEI3DB482HxxunTpUomJieHYefElvn5ZevPNN8v7779vqtH6GcASFxcnvXv3NrcBSB9DfOES7YyoH/y1ejp8+HCOmos++ugjs4zH6NGjGSrpA/ohXv30009mSNq4cePMh1L9cKVLzuhwys6dO8umTZt4j7qgdu3apiu3VlM3btwo33zzjSxZskSioqKkUaNG5np4x1qaK1euXE7voyFVaUCF+7TTrHZJVrocGl+guk7/3euXz/r/Zr169Xj7+eDvk06B6t+/v1n6aM+ePXLq1Cnz+UlH/ejSM/p3C0D6CKjI0Pbt26Vjx46mrboGLYaouF45GThwoPmjr8vLwHvWt9G6BIp+EO3Vq5epmJQuXdq8N9u2bWuGWelluFZ10qFopUqVkjVr1pgwtXPnTvN+1YpqgwYNzPBUIJiHp+oalRoCdFSFhgK4RpeXskb4jBkzhsPmw79PzZo1M0FUv+TTefy6/qn1d2nkyJEcayADBFSkS9eW0yG9+s1g3759zfAUuOb555+XxMRE0xgJvqGLnVscNUmyrtOqINK3a9cuUzWJjY2VOXPmmKCqlTwd5jt+/Hgz9FerK1988QWH0gfv2cuXL6cbshTDe92jX0bpl1I6N13npetcarhOq3l//PGHmX6i/w/Av3+frC+q9XMVa6AD6WMOKjJcbFobT+h/tnzD6h790K/fTKf9Rl/nqFh/pOrXr28uf/311zT2cIFWSq3hklo5TatMmTLmXIf9In36ntMP+PoFlP0HK4s2nNL38PLly00DFXjmlltuMeeHDx92Gk7PnTtnGlIRUN2rVukXLNoorVq1aqYLsg6hhOv0mGXJksXMRZ8yZUqq244fP27O9QsAHTLdr18/838FMv77ZP+3yJ7+3dL+Cfr3SU8VKlTgcAJOEFDhkA710yEq2pRGh09p63T9Qwb36AdPZ9U8DarWbVZoRfqqV69uznWuqQ49TTvXTL9UUY4CF1KzAlO+fPkcHhrremteFTxz2223mffpyZMnzZdS2s3Tnlap1Z133skhdoMu46FD1LV79/z5882XgXCfTt3RL6GcWb16tTlnmkrG9P/MsmXLyr59+xz+v6lfquhnAsXfKCB9DPHFDfSDv7ZDX7t2rTRp0sR8CNCOn3D/D7+jk/7xUrrEh3Wdo29b4bgapXOg9Zg5Cv7WdVaQhXPWUhw6PNIRbe6leG96R6t6OpdX6ZITaX3//ffm/NFHH+Xt6iKd2//JJ5+Y/w90mSmtSsF92rXX2d8pqxqoDaj0ZwKqax577DHbsXUU9nXaj/6foF9cAXCOgIobmiboEh26sLyu2TljxgzaziOoWOv0adfeY8eO2a7Xzr3a2EfRKCVj+iWU0urJf/7znxs+SFlLIbRp08aHv73IpPP31Ztvvmnm/lp+//13M99Xq39PP/10Ju5h6ND35YgRI8wXLL/++qttCDUQDLSbtC7V8/HHH9uqz0qbeFmdpnXKFJ2mgfRlSdGvxoD/R9vNW/+JtmrVSvLmzevw2Oh8VJoqeEaXRNFhQFpBpVGCZ/TbfJ03pR/sdc1DHfK7atUqU/3v0aOH/Pe///XwmSPLq6++aptbfvvtt5u1T48ePWqCkw5H69mzpwlQSG3u3LmpltvS0Sb6p/S+++6zXTdo0CBp3ry57Wf9f1X/f9V5aLqEj1ZStPqnj9MqqnagjUTuHEv9EqpGjRrm9lq1apnhvY5oZ1ptmhSJPHlvOqIjJ7T/hFZQna3hGwk8OZ7aWE7fg9HR0eZ9qkN/9e+TLj+j718d6cMQXyB9zEFFKvbzJmbOnOn06OiC0wRUZJaJEyeaNTw1POlQKp0frX/4n3nmGdM4Ba7RZQ804Gun6Q0bNsiOHTtMox5dGkmDvo6mwI10Pqkuy5OW/XV6n7QdU7WZj1ZWNJhqlaVhw4bmw63+DiKVO8dS5+9Z36nrlyh6ckSbz0VqQPXkvQnfHk9dUkaXl3n77bfN/fQLVP1Z503ryB9r3WMAzlFBBQAAAAAEBeagAgAAAACCAgEVAAAAABAUCKgAAAAAgKBAQAUAAAAABAUCKgAAAAAgKBBQAQAAAABBgYAKAAAAAAgKBFQAAAAAQFAgoAIAAAAAggIBFQAQ1IYNGyZRUVGyZcsWv26nZcuWcvPNN0t8fLxftwMAAJwjoAIAgtbff/8to0ePljZt2kjVqlX9uq3BgwfLiRMnZNSoUX7dDgAAcC5LSkpKSjq3AwCQaXr37i1jx46VjRs3SvXq1f2+vaZNm8qKFSvk4MGDUqhQIb9vDwAApEYFFQAQlC5fviyTJ0+WO+64IyDhVHXs2NG2XQAAEHgEVACATzzxxBOSJUsWee211264befOnZInTx5z2rVrl0vP991338n58+elffv2Dm/XbZUpU0aSkpJk+PDhUqFCBcmZM6dUrlxZJk6caLvf4sWL5cEHH5S8efNKgQIFpFOnTnL69Gmn81D1OT777DOXXzcAAPAdAioAwCc+/fRTKVmypLz77ruyZMkS2/XXrl2TJ598Ui5duiQffPCBVKxY0aXnmzNnjjmvX79+uvdr166d2abOUa1bt67s27dPunXrZkLq999/L02aNDEhVs9z584tX375pQmijma4aID+17/+Jdu3b5e9e/e6fQwAAIB3or18PAAAhlYnp0yZIg0bNjRVys2bN5vr4uLiZP369SYUdu/e3eWjpXNBo6Oj0x3ee+DAAbnppptMVbZw4cLmOg3HDRo0kDfeeEMSExPlxx9/lObNm5vbLly4IPfff7+sXLlSli5daiqrad17771m28uWLZNy5crx2wUAIICooAIAfEYD38svvyyHDx+WZ5991gS9t99+W4oVK+bWsFntpqsdfEuVKmWG3KZHq7JWOLX2QUPtsWPHpFmzZrZwqnSYb8+ePc1lDaCOVKpUyZxv2rTJ5f0FAAC+QUAFAPjUm2++KdWqVZNvv/1WHnnkETOUVofbxsbGuhVQlVZg05MtWzaHQ4Ctymfjxo2d3qYB1pGCBQua85MnT7q8vwAAwDcIqAAAn4qJibF1wdUhtVpJ1fmf7tDmSEqH76anaNGikjVrVodzSVWJEiWc3nb16lWHz6lVVnXu3Dm39hkAAHiPgAoA8LlvvvnGdlmHyl6/ft2tx+fLl8+cX7x4Md37RUVFeXV7euE4f/78bj8WAAB4h4AKAPApbUD0zjvvmOqmNkz6/fffZcSIEW49R5EiRcz5mTNnAv7bOXv2rDm3n9cKAAACg4AKAPAZHdL71FNPmYqpzjudOnWqCXq6TumaNWvcCqgacA8dOiSXL18O6G9o27Zt5lzn0QIAgMAioAIAfOaFF16Q/fv3m/OmTZvKzTffLJ9//rlZh7Rjx45mLVRX1alTxwTdP/74I6C/obVr15rzevXqBXS7AACAgAoA8JHvvvtOvvzyS6lSpYqMGjXKdv1jjz0mPXr0kN27d0vv3r1dfj5reRhdrzRQ4uPjzZqtutQMa6ACABB4VFABAF47cuSIPPPMM6aD71dffXXD2qXvv/++VKxYUSZMmCAzZ8506TnbtWtnmiVNmzYtYL8h3beEhAQTqAEAQOBlSdEF6gAACEIvvfSSfPDBB6aqeffdd/t9e7ocjjZ5OnjwoBQqVMjv2wMAAKlRQQUABK3+/fubdUtHjhzp921t3LhRFixYIC+//DLhFACATEIFFQAQ1IYNGyZxcXHy559/StWqVf22nZYtW5olcfbs2WNCMQAACDwCKgAAAAAgKDDEFwAAAAAQFAioAAAAAICgQEAFAAAAAAQFAioAAAAAICgQUAEAAAAAQYGACgAAAAAICgRUAAAAAEBQIKACAAAAAIICARUAAAAAIMHg/wIZRQD5QWG5XQAAAABJRU5ErkJggg==",
       "text/plain": [
        "<Figure size 1200x400 with 2 Axes>"
       ]
@@ -983,7 +983,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 30,
    "id": "941d76b7",
    "metadata": {},
    "outputs": [
@@ -1201,7 +1201,7 @@
        "[5760 rows x 9 columns]"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1256,7 +1256,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 31,
    "id": "75433d08",
    "metadata": {
     "scrolled": true
@@ -1271,7 +1271,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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GqnauZyQqdfLdPAAkL7pY/qAfogtFM0bcj+FSfmt9yhksmY/5d3EQaln3XwnJdqL2HQvJdgA7i751XZb8/W3sdZtVaMZIA6Nla2+XLFl8q0C6eDFGaj5wwgR+2bJli13uTdboyJEjpozuzJkzZgLYLl26eJw1atmypdcZqlAjOAohVwpTAyOCI8B30SXuCMkfr6i0GSRSXLzjn6AojTjD1aIiWY5EToAUFRUTmu3wwRsQMFYdAqGBUZasvn4Q9s/fTQ2M4gZHnvr777+lXr16pgtmhw4dZOjQoSm+RudW+9///me+1myT1Vn2I8YNGzbI+++/L82bNzcpTT1BfTlJx44dG/va5G7jx4+P97r27dsn+/zPP/88gO8WgDeBUShcKJYx4gIjp4mk9x2q8ylUvx8AnOfixYummYKWx+n1uc5Z5Mm1+cKFC013uiJFikiNGjXE6iybOdKBXTNnzvR7PSVLlpR27dq5fezcuXMyY8YM87VOkudO/fr1zUy+Cd15551+7xsAOCU4CPYxiKQsUkgyq3uOhHs3ANjItWvXpEmTJrJ27VpzbazzpaVJ41mtgqukTrNGVs3GRURwVLVqVSlbtqxUrlzZ3LQvuv5gvKVBT1KBz3//+18THFWrVk2KFy/u9jk9e/aU2rVre71dAIFH1uj/EBglPh5WD5A0e5R1X2jGHgFAoNy8eVNat24tixYtMpmfadOmSbp0no2dv3z5skyfPj0iutRZPjjq0aNH0LcRKS0FAVAuFBeBUeRmkUIVIJE9AhAoI0aMiA1wcufOLZ07d3b7PB1/pI/HpUkILcfTREekVF1ZNjgKtn379snKlStN5NuqVatw7w4Ai7DyWCOCIs+Pk5UDJACIJGfOnIn92hUkuaOtwBMGR3FL6iKFY4Mj1w+rYcOGkjNnziSfp6nDqVOnmpRisWLFTG/2MmXKhHBPAYDAyE4BEtkjAJGkX79+Xs2BlHCi2Ejj+OAopZK6zz77LFG530svvSTDhw+XqCjHHj4gpJw+1oiMkX/HzapBEgDAehzZ6kg7bezevVty5cplMkfuVKhQwbTr1ufpYLK9e/fKyJEjzcy+o0aNkjfeeCPF7WgDifPnz8e7AYA3CIzseQytGogDgNNZ7z9GCEvqdKxRUt02dLbfF154QUqVKiUZM2Y0JXU6AG358uXmNTo4TWcXTs7gwYMle/bssbdChQoF5f0Ads4YOTlrZMWLekSWUP4OAYAdOO4/b3R0tHz//fc+d6m75557pHHjxmY9OqlVcnr16mXmUnLdUgqmAITngo7AyP6sGGiG8rwjSAIAzzhu0My8efPkxIkTZl6jhx56yKd1aDZJ6Wy/yUmfPr25AUgan2pHxoW8HVixSUOo5z5K6feNyWMBOJ3jgqNAtBR0tTTMnDlzwPYLsDMrB0BWyxoRGDkvQLL67yoBEwAncdTHkzoJ1cyZM/0KjrTJwuzZs83XFStWDOj+AXZk5cDIagiMnHmcrRagA4CTWes/hB+0QYLOP6TjfJKbs0g7z1WpUiW2NM6dnTt3yoQJE0wgFNfJkyflX//6lxk7VK5cOalWrVpA3wNgN1YPjKx0UWq1C3a743jb5/cYABxRVqfZmQEDBsR+f/36dXOvgY3LO++8E9uK+9SpU7Jr165kxwG5SupSasRw/Phxadu2relYd//990uePHnk6NGjsmHDBrlw4YIULFhQJk+eLKlSpfL7fQJ2ZfULKisFRggPK5XYhXrskS+/z5TXAXACywZHmqVZs2ZNouVxl+lzPKVB06JFiyRt2rTy1FNPJfvc0qVLS9euXWX16tWydetWOX36tGmsoMsbNWpkgqacOXN6+Y4AwD2yGOFDgOQ5AiQATpAqJiYmJtw74RQ6CazOd1Qnd0eJSu1+fiXADsgaeY7AyBqskkGycvZIkT2CE0Tfui4LTo0207Bky5ZNrHYduXF7XsmS1bdS7IsXbknFu/+y3HuzEorcAQQUgZHnCIyswyo/C6uXe1r99xsA/GWN/wYA4DBWuRjH/+FnAgDgvzMAx3yqbJVP5bkIRyScp5H6ew4AtmzIAAB2ZMXA6HLB8I23yXQ4tSV/PuEeg0T3OgAID4IjAI74NNkKn8aHOjAKZ9AT6H0MdRBlpS52AIDQsdZHdgAQBARGkS8cgV64s3xWOG8BwGkIjgAgyMgYBS5ACnWQRIAUudliAPAFwREAWwvnp+96YR3Ki+twBA/h4LQACQAQOvzFB2DbT5DDFRiFOihSTgiKwh0ghStIorwOAEKH4AiALYUzMAo1pwVGTiyzI0ACgNAgOAKAAAlHtsipgZFTs0hWY9WsMYDAuXz5ssyYMUOeffZZufPOOyVDhgySOXNmKVeunPTv318uXrzo0Xrq1KkjqVKlMrfDhw9b9kfEX3cAtrs4CvWn7JTRhZ8TutmRPQIQDhMnTpRmzZrJ6NGjJU2aNNK4cWOpUaOG7Nu3T/r27SuVK1eWEydOJLuOsWPHysKFC01gZHUERwDgB8rorIMACQACL23atPL888/L9u3bzW3y5Mnyyy+/yK5du6RChQqyc+dO6dq1a5KvP3nypHTv3l3q1asnhQsXtvyPiOAIgK2E8tN1AiPrcdI4JKuwYvYYQOC0a9dOvvjiC7nrrrviLc+fP7+MHDnSfD1t2jS5fv2629dr4KSleaNGjYqIH4uz/6ID8IuTL4oYX2Rtdg6QKK8DYBXlypUz99euXZPTp08nelwzTFqW9/bbb0uJEiUkEhAcAbCNUF000qY7Mtg5QAIAK9i7d29s6V2uXLniPXbp0iV56aWXpEyZMvLmm29KpOAvOQBYGN3oIuv4OTVAcnIWGXCy4cOHm/sGDRpI+vTp4z3Wp08f2b9/v3z++eeSLl06iRRR4d4BAJHJqRdDobz4JTAK3HHMdDi17bKkWfddCfduAIhQ58+fj/e9BjYJg5uUzJkzR7755huTNRowYEC8xzZu3GgCJx2vVKtWLYkkBEcAbCEUJXUERpErlAGSnidZjjD/FIDgmHepjGRI5dsl/NVL0SLylxQqVCjecm3J3a9fP4/Xox3qnnnmGYmJiZEPP/wwduyRunnzpnTq1Ely5MghQ4cOlUhDcATAa07NGoUKGaPgHVcCpOD+XYjacySIWwAQKIcOHZJs2bLFfu9N1ujIkSOmjO7MmTPSrVs36dKlS7zHP/nkE/ntt99MVil37twR90MjOAIAC2WNCIyCf3ztUmJHaR0AX2lgFDc48tTff/9t5is6cOCAdOjQwW1maNasWWay13Hjxsn48ePjPXb8+HFz37JlSxOQ9ezZ0wRaVkJwBMArTswaERjZS6gCJCeW15E9Auzr4sWL8thjj5mJYJs3by5fffWVCYLc0XK7ZcuWJbmu1atXm/v27duL1RAcAYj4wMgO876QMQr98bZLBslqCJAA+7l27Zo0adJE1q5dK/Xr15dJkyZJmjRp3D53yZIlSa6naNGiJuukZX0FCxYUKyI4AhBx7BAMwRmCnT1y97tAFzsAgXTz5k1p3bq1LFq0SGrUqCHTpk2LqNbc3iI4AhBRCIwA6yN7BNjHiBEjZPr06eZrbbDQuXNnt8/T8UeR2IAhIYIjAIAjUVoHACk7c+ZM7NeuIMkdbQVuh+CIgmsAET3eyA7NGBhvBACwqn79+pkGCynddDxRSvbv32+ea9XxRorgCAAsMOkrwiMUgameR6E8lyg9BQDf8Z8fQMQI5UUf7bsRqecUAMB3/KUGgDB+yg9ncdK55dRSXACRzTl/pQHAYheujDWyhlD/HJwUIAFApOEvNIAU8QkwEFkBEuOOAMA3BEcAIkKwL/b4NN/ZwpHF45wDAOshOALgeOG4SKWkDk4IkMg6A4g0TAILwNHsfnEK504Kq9nWrPuuhHs3AMBrxYsXl0BIlSqV7Nmzx6vXEBwBsPwnv8EqqQtXYETWCAnPwyxHQl/WBwBWtX///oAFR96y7EdkGzZskPfff1+aN29uZtHVN+fLG1Q6Y6/r9e5uO3fudPu6mzdvyscffyz33XefZMyYUfLkySOtWrWSHTt2+PnuAIQbGSNYKXDlfASA+Nq3by+3bt3y+dauXTvxhWUzRwMGDJCZM2cGdJ1JHaTs2bMnWqYHtWXLljJ9+nTJkSOHNGzYUE6dOiVTpkyR2bNny+LFi+WBBx4I6P4BsD+yRkgKGSQACD/LBkdVq1aVsmXLSuXKlc1Nsz/Xrl3za51jx471+LmjR482gVGpUqVk+fLlkjdvXrN86tSp0qJFC2nTpo3JIEVFWfYQAkgCn9LDKaww7khLc6P2HAnrPgCILB9//LHcfffdfq3j6aeflvLly3v9Oste2ffo0SOs2x82bJi5HzJkSGxgpJ588klp3Lix/Pjjjyazpd8DdmXH8UbhDIzIGkWGcDZmIHsEACJdunTx+zDUrVvX3Gwz5iic9u3bZ7JCOs5Iy+kS0syRmjVrVhj2DgBgZ2Q2ASB8LJs5CoYPP/zQtPNLnz693HPPPdKsWTPTZCGhzZs3m/t7771X0qZNm+jxihUrmvstW7aEYK8B57JT1giRxU5tva1QWgcAwaDX9ZrQSJ06tSnD02E4/nJUcPTmm2/G+/7111+Xzz77TDp27Bhv+cGDB829dslzx7X8wIEDQdtXAPZCSR2cXF7HuCMAgXT27Fnp1KmT6Q+gYmJiTAfq1q1byxdffCGZM2f2ed32+FgsBTpGaNq0aSaYuXz5smzbtk26detmGjzogU3YFe/ixYvmPlOmTG7X5zrgFy5cSHa7uv7z58/HuwGRwgrjjYBwslNAG6y5wgAgHF544QWZO3eu9OnTR3766SeZPHmyNGnSRCZOnGiu8f3hiMzRp59+Gu97Lan76KOPpEyZMvL888+b5g96QANt8ODB8u677wZ8vYAT2Olizk4X2QAABNv169clXbp0bh/T6XZmzJhhOtp17tw5Xk+ABx980Ey7o9kjXzkic5SUZ599Vm6//XbZtWtXvJl4s2TJYu41y+TOpUuXzH3WrFmTXX+vXr3k3LlzsbdDhw4FdP8BeI7xRgAARIa7777bZITciY6Olhs3bphr+IRy587t99Q/jg6OdPBWiRIlzNfHjh2LXV64cGFzf/jwYbevcy0vUqRIsuvXxg/ZsmWLdwMQHuEav0HWKLLZ6ecX7mwspboAPFWyZElT1dWoUSPZu3dvvMc0o/TAAw/IW2+9Jb/++qtcvXpV/v77b9NHQEvtqlevLv5wdHCkzpw5Y+7jDtwqV66cudexSRqZJrRx40Zzr5PUAnYU7ouYcF/EAQCA8Pnll19Medzvv/9uhsPo2CINglz++9//mh4BtWrVMtfw2n1a50a64447ZPjw4X5t29HBkR5wLanTxgs6/silWLFictddd8mVK1dk9uzZiV6nPyyl0SwAOCHr4GT8HAE42eXLl80YHx2Ocuedd0qGDBlMQKLJhP79+8c2MotLh5KMGjVK2rdvb66ptVpLu8ktWbLE4+3qlDvbt2833aaHDh1qrtVd3ekqVKggf/75pwmSunbtam5ff/21ua7XffSHbYKjESNGmIOm43zimjNnjixatCjR83WOopYtW5rWf9qxLuGgL1enC/2BnDhxIna5dr378ccfY9N9AABECrKyALw1ceJEE6iMHj1a0qRJY7pA16hRQ/bt2yd9+/aVypUrx7tWVlOnTpWXX35Zxo0bJzt37jTX277QQEybm2lCQyu2nnzySWnQoIHs3r3bJDe0sZo2WdObTs2jz/eXZYMjzdhUqVIl9qZdK1TcZXGzOqdOnTLRYtyxQ2rt2rXy6KOPmkmhNJjR/ufayaJSpUpm0qjatWvL+++/n2j7eoD1RPjjjz9M0KWB1MMPP2w6YWTMmFG+/fZbiYpyRLM/IKTscvFGtsFe+Hnao2QXgPfSpk1rghDN4uhN22Zr2Zted2sGR4MfzdzEVbx4cbPsu+++M4FMvXr1/Dr0WtWlyQm99tcxSBoo9ezZM7ZJWiBZ9ur+5MmTsmbNmkTL4y7T56Skfv36JrW3bt06WbFihekap40RdLBWmzZtpEOHDiYKTkjTfz/88IOpW9RIWTtmaApRI1aNYLWLBmBHXLwA9v8AIuu+K+HeDQARol27duaWUP78+WXkyJHy0EMPmcqquO23NbukNxctqQuExx57TOrUqSMffvihvPfeeyb40pK7p556SgIlVYyveS54TSeBzZ49u9TJ3VGiUrvv3Q44OTgKdtYoVO28yTLYV6bDqW3RXTGcwVHUniNh2zbgiehb12XBqdGxH6hb7Try/XW1JEMW3/IbVy9GS8/KSwP23i5fvhzb1Ozo0aMmYHJHS+G0k9zixYtN1ZYnDh48aAKfTZs2mQZq2k36iSeekOeee85Ub2nyQ4fBaAmfrlOH2AQieWHZsjoAAKyGwBcA/o+rzbaW3uXKlUsCZenSpWZYiwY8Op5J5yBdv369vPLKK2ZojXauK1SokKnymj9/vhw/flzKly8v3bt3lwsXLvi1bYIjAAggLp4RCVnOcI7to3QXsEYWKu7N14lTh///ttmaGdL5PQPlP//5jynRW758uRnTtGrVKpOZ0sZrv/32mxny4qK9BbTRmpbZace6uB2obTXmCEDo2bmkDghkABzs8rpwTVoMwPqWni4taa/6NjzjxiVtcLbUZF3i0q5z/fr182pd2hH6m2++MVmjAQMGSCBt3bpVHn/8calWrVrsMu0RoF2kNQjSYCguLbPTgEr7Cehz/EFwBAABQtYIkYTGDIBz6XiduGOOvM367Ny5U5555hnTolubI+icR4FUoEABkyHSErmsWbPGK7dTSY1t0uUTJkzwa9sERwDCjqwRIk0oskcAECwaGPnakOHIkSOmjE6bJGhDhC5dugR8/3S9r732mimR06l4cubMaVqCa/foHDlymCl3goXgCAACgKwRAj3myM6ldVrCS9c6IPL8/fffZs6iAwcOmOlwtJtcMGjjhdtuu00GDhwoX375pdy6dctM8KqldoMGDUpUFhhIBEcAHDFIOpgD3AmMnMkO2SNK6wB46uLFi2aeIZ0Itnnz5vLVV18FbP4id1q3bm1uOn+Sth7PkydPSH5Ykf1XHUDEo6QOCO+8XACQkmvXrpnytrVr10r9+vVl0qRJpkFCKGjXulAFRoq/vABsj6wRgsUOWUM+oACQnJs3b5oMzqJFi6RGjRoybdo0E7DYFWV1AMKGizLYgR3K68KBcUdAZBgxYoRMnz7dfJ07d27p3Lmz2+fp+CN9XB07dkyaNWsWr7ud0te6GkE0bNhQ3nnnHbfraty4sdSpU8c0ZfCVzsG0cOFC+fHHH716HcERAFuPNyJrhEhm98YMAKzvzJkzsV+7giR3dJ4kV3CkZXhr1qxJ9JwdO3bEfp3cZK3alc61Ll9t2rRJZs+e7fXrCI4AhAVZI9hJMLNHoQiQaMwAILmgp5+XE8QWLVrUzIHkj+PHj8uyZcv8er0vCI4A2BZZI8DaKK0DkJS5c+eam680OPOlmx7BEeBwdi6pCxY7DMJH4JE9AoDAaNeunYQLwREAW5bU0QYZAIDINGbMmLBtm/Y6AOAFskYI1/kRioCfsYAAnI7gCEBIkTUCAABWRXAEAB4ia4RwnydkjwAguAiOAIQMWSM4BYG052gKA8BKCI4AB+OixHNc7MJJGHsEwKkIjgCHCnVgRNYIThOsgDpUnRhDGSDxQQ0AqyA4AhB0kf4pNFkjOBUBEgCnITgCHCiUn9JGemAEODl7BABWsH///pBti7+uAGwRGAXrYpGsEZyO7BGAcCtZsqQ0aNBApk6dKtHR0UHdFsER4DChyhqRMQKCK5TZI36fAYRTiRIlZN68edKqVSspWLCg9OzZU/7444+gbIvgCEDEI2sEK7NL9pEACUC47Nq1SxYvXiytW7eW8+fPy5AhQ6RMmTLyyCOPyP/+9z+5fv16wLZFcAQg4LiIAuArOtcBcKdWrVry7bffytGjR2X48OFy7733ypIlS6RNmzZSoEAB6datm+zYsUP8RXAEOEgoLjpCHRgxMB2RwC6NGfjgA0C45ciRQ1599VXZvHmzrF69Wjp27GgyR66AqUaNGjJhwgS5du2aT+snOAIAG5dCAQBgVw888ID85z//kX/9618SExNjbitWrJD27dtL4cKFZcSIEV6vk+AIQMDwqTKQNLJHABAYV69eNdmhmjVryt133y1ff/215MuXT9566y1ZsGCBdOrUSS5evChdunSRAQMGeLVugiMAEYtGDIA9Pwhh3BEAd7Zs2WJK6nSMkWaHNEv08MMPy+TJk+XgwYMycOBA06Thiy++kO3bt8vtt98uX375pXgjyqtnA4hYwb7YIGsEeJY9ynSYzyUBwBuaGfrqq69k/fr1pnTutttuk9dff11eeOEFKVWqlNvXFClSROrWrSvfffedV9siOAKAOBhrhEjNomY5EtpxcvqBSNZ9V0K6TQCht2HDBpk/f76sXbvW3I4cOWKWa5CSFO0o995778kvv/wihw4dkjRp0piJXJs1a2bGCGXNmtWrfXj++efN/UMPPSQvvviitGzZUtKnT5/i68qWLWu27w2CIwARmTWiSx0iFdkjAJFkwIABMnPmTI+fr5OzVqtWTU6ePClFixaVJ554wowRWrlypfTv31+mTJlivs6ePbvH63z55ZdNlki70XlDAzG9eYPcPgD8f2SNAOt8MMK4I8AaqlatKu+88478+OOPcuzYsRQzNj169DCBUefOneXPP/+UqVOnyuzZs2X//v1SpUoVMxZo2LBhXu3DG2+8YcYZpeTMmTNm7JE/CI4A+IWxRoA1AnGyqQCCoUePHibj06hRI9MRLiXLli0z9xpQaTmdi2aK3nzzTfP1unXrvNqHYsWKmQApJbr+4sWLiy2DI61vfP/996V58+ZSsGBBSZUqlbl56+zZszJx4kRp3bq1ObDp0qUzdY4PPvigmSzqxo0bbl+nHTBc23R3+/zzzwPwLoHQsNsnsMG4CCRrBACA/zwZC6QNFbzhmsPI0+f6I8ou9Y1JGTp0qAwaNMgENOXLlzdBkab6tPWfDirTuse5c+dKpkyZ3L6+fv36bqPkO++80+99AwAg0tGYAUBc9erVk7Fjx5pr+U8//TQ2e3Tu3DkZMmSI+bpjx44SDKdOnZKMGTPaMzjS+kbtMFG5cmVz0wFd165d83o9mTNnNik2HcilM+XGHSxWp04d+fXXX01PdO2o4U7Pnj2ldu3afr0XwK7sUlJH1gjhOu9o651y1jtqzz+dsQBEhsGDB5sKsFGjRsmcOXOkUqVKpiGDJiYyZMgg3377rZmbyNPyPJfjx48nWuYSHR0tu3btMgmPe+65x57BkdY3BkKvXr3cLtee6Fq29/TTT8ukSZOSDI6ASGa3cjoAzkOABATe+fPnE5XCeVIO5wmtuFqyZIkZ0jJv3jzTiMFFh8tosOQJTU7EHVKjgY/ekiun0+d3795dbBkchUK5cuVie7EDdkNg5BmyRggnu2SPKK0DQmfXX3kkTaYMPr325uWr5r5QoULxlvft21f69esXkP3bsmWLNGzY0JTT6RCZmjVryqVLl8xQFk1aaOCkrbxTGqLStm3b2OBo3LhxUqJECdMi3B3tKaDd7LRpRMWKFf3af0cHR3v37jX3yXXemDZtmmlBePPmTdPQQQ96mTJlQriXgDUDI7uU1AGIrL9plNkB/tOJUbNlyxb7faCyRjdu3JAWLVqYxIN2pHMFKjly5JAuXbqY62nN7PTp00e+//77ZNel45ZcNDiqXr26jB49WoLN0cGRdqtTTZo0SfI5n332WaJyv5deesm8NirK0YcPFkOmyHtkjWAFdskehQpldoD/NDCKGxwFyurVq824fs3yuMvgtGzZ0gRHSY0dSsqtW4Gf/iApjr2611bcCxYsMJGsNl1IqEKFCqYpxCOPPGJaiesgsJ9//ll69+5tBphp+u7jjz9OdhvaQCJuE4mE9Z1AIBAUAZGPAMm/v3tkkwBrOHz4cOycRu64lutkrVblyOBo+fLlJrWndYyannM3464+HpeW1OlMv7Vq1TKR8IgRI6Rbt26JajYTdut49913g/Ie4DwEQYFF1giwz7gjd38fCZiA0Mv3/4eqaOe4CxcumLlF43JN/qpdqJOjk87qdbp2m86VK5f53lP6Op2A1lepYvydKSlEtPWfZmH83d1t27aZgWEasWrv9VdffdXrdWhKUAeVjRkzxkwW603mSIOpOrk7SlTqdD6/BziP1QKjcI83CsQksARHsCJ/y+uyHAld6Yk74QqOkkKABF9E37ouC06NNvPyBKP0zFd6HamZl+Lj3vKrIcPedu/59d4yJHNNri27ixQpIidOnDANFb788svY8Uw6DqlBgwaydetWefvtt81UOklJnTq1CXJ27NghpUuXjv3ekzhAn6djm3zlqMzRvn37zMRUGhhpRw5fAiNXG3B17NixZJ8XyLaIcC6rBUZ2QGAEOAPjkwD/zZ4920zo6nL9+nVzX6VKldhlmqnRDnUaOH3xxRcmkTB+/HhZuHCh3H///XLlyhVZtWqVySZpBZa7IS1xaQJC5c+fP973oeCY4EgDmbp165p7LZnTloW+ctVJ6gSzAAAESqSPPaKlN2A/J0+elDVr1iRaHneZPseladOmsnbtWhk6dKhpvKATwepYfU0utGrVSrp27SoZMyZfgdKuXbtkvw8mRwRHGszUr19f9uzZIx06dEixkUJyNI2oEbTyt486EIlZo3CX1PmLrBHgLGSPAP+0b98+2WEk7mhjs++++y4iD33kfjyVgDZI0PmHdHKpuC5fvmzSfFrfqNHqV199FW+2XXd27twpEyZMiDdeyBUV/+tf/zK94XUC2aQmogIAwFcE8ADgmejoaNOB+pVXXpEPPvggIF3wouxQ36hOnTplOmMkHAekA760xlFn6dV5iZ599tkUJ5rStt06iEzL77ROMk+ePGYQ2YYNG0ytpLb2njx5copBFmA3ZI0AePJ3wmqNGcgeAZGtf//+pgP04sWLTWM119xHtWvXNtf52qhBr8s1CbJ+/XozVY/tgiNv6xuT4oogtWvFxIkTk3xe3OBIu2JoPaROZKUZp9OnT5vGCrq8UaNGJmjKmTOnD+8KiOySOgChEeljjwAgkObPn2+SE67ASGnn6JUrV0rZsmVNy2+dj3TGjBkycuRIkxyxfStvO3C1YKSVNyIxOLJS1siXVt6UKiHS+BIchbuVd1xWyx4pWnvDE7Tytp477rhD7rvvPvnll19il+lQlx9++MFM03PXXXeZ7JHOn6TzIv32228+b4uPpQALslpgBCD0Ij2gt9IHKgAi2+nTpyV37tzxli1dutR0wNPASGlZXeXKleXgwYN+bYvgCEDEXORoxoisERD43xEAsLLcuXPLkSNHYr/fvn27/PXXX2bMUVzaMtzVp8B2Y44Ap3Jq1ogLuuCIKnDZ3EcfzSSRuv+Ruu9W/32yUgleqNCYAYhMd911l8kUabmctgkfNmyYyRQ9/vjj8Z63f//+2IljfcXHSwBg88Ao4deRQPfXtc9xvwYAOM/rr79u2nZr2ZxmkcaMGSPFihWTBg0axD7n3LlzprO0TrfjD4IjAJbgxE+xg8ldMEGAARd+3wBEkscff1w+++wz05jhypUrZq7R6dOnmzI6l/Hjx8uNGzfk0Ucf9WtblNUBcETXr0gf3O6N5IKgSChTS2r/I2HfAQDBoe269ZaUTp06mXlKs2TJ4td2yBwBsAw+zQ4NK2eQUto3K+87ACB8MmbMaKbMSZMmjV/rITgCABvxNHiwYpBhxX0Kp2BNAsuHEACQNIIjAEBEBUYEUQDgPNu3b5f27dtL8eLFTZZIM0TublFR/o0aYswRAEvRT7Vp6+0bb4MGq4zhIdgBACRn1apVUqdOHdOMQeXKlUvy5csnwUBwBFhM1J4jjp3rCKEX7gCJwCi0KKkDEIl69eplAqOuXbtK7969TXAULARHAOBw4QqQCIwQ8nNuzxEOOhCB1q9fL+XLlzeTvwYbY44AWA6fbocegQoAwKp0PqMyZcqEZFsERwCAkAdI/m6LYA4AnKN69eqmIUMoEBwBcIRgtUW2ikgKFiJpX+2EjCyASPXee+/Jn3/+KSNHjgz6thhzBFgQTRlg1/FHBEYAAG9t3LhROnToIK+99ppMnjxZ6tatKwULFpTUqd1/8Nm2bVvxFcERAEuipbf9AiQCI4QTzRiAyNW+fXtJlSqVxMTEyPLly81Nv09IH9flBEcAAEsHSARG4S0DpaQOgK82bNgg8+fPl7Vr15rbkSNHYgMRd/r16yfvvvtukuvr0aOHvP/++17tQ58+fdwGQ8FA5ggAENQAicAIACLXgAEDZObMmV6/rlq1alKyZMlEyytVquT1ujTgChW/g6Nz587JyZMn5ezZs5IjRw7JkyePZM+ePTB7BwBw9CSxkbpvAGAXVatWlbJly0rlypXNrWjRonLt2rUUX9epUydTDhdpvA6OoqOjZfr06TJ79mxZunSpHDx4MNFzChcuLLVq1ZInnnhCmjZtKlFRJKgAr3859xyR6BJ3OPrAMe7IGqya+SEwAoDg69Gjh6UO8+bNm01536lTp+See+6Rxo0bm+UasOktW7Zsfq3f46hFM0MffPCBjB492uyM1hlqh4gCBQpIrly5zI5oFunMmTMmYBo/frxMmDBBcufOLc8++6y8+eabJrMEAEAgkDnyDOONaMYA2MGuXbtMx7o1a9bELmvXrl1scDRx4kSTrdIEToMGDXzejkcjPocOHSolSpQwwZGWzPXu3VsWLlxoAqFDhw6ZCE67RmzZssV8r4HUggUL5K233jJBkw660td/9NFHPu8oAPjL7nMdAQBgFYsWLZKuXbvKiy++KAMHDjSNHXyl8UXNmjVl9erV0qhRIxkyZEiihhCtWrWSdOnSydSpU4OfOdKsj0ZlvXr1kgcffDDF52fNmlUeeeQRc9NBXKtWrTIBkq6ne/fufu0w4CSU1gEAgEA7f/58vO/Tp09vboGkFWRxvfPOO/Lkk0/K2LFjJUuWLF6tq3///qZy7euvv5aOHTuaZW+88Ua852TOnFnKly8fL7MUtOBIJ17SjfkzkEu7XGzatMnndQBwJsYdRe6YIPiGDGdgMb8R7Obm8UwSkyGDT6+9dfWfCopChQrFW963b9+AdYQrWbKkqTp77LHHpEiRIqbSbNmyZSZJolmdmzdvmv4F3vjll19MUwhXYJQUbRYxb9684AdH/gRGwVgPAAAAAN/L1OI2Lghk1uiZZ55JlNF5+umn5eGHH5b77rtPZsyYYcrjqlSp4vE6T5w4YVqDp+TGjRty+bJ/HxhSgA9YHJ96BhafytsLWbPk0YwBgDsaGMW9Bbqkzp38+fObhgquTJA3brvtNrcdshPavXu32Y4//O6xrakxrQFMrt+5tvYGAAAIJT5cAqylVKlS5v7YsWNevU6zRppx0iE6SVWi6RRD27Zt83tuJZ8zR/PnzzfpMU2VaTvvYsWKub0VL17crx0EwD94JI3Mib2Q2QRgZ2fOnDH3Gj944z//+Y/pTtekSRP5+eefTXImYWe8f//732ZuVe2QF/LMkQ6meuqpp+TWrVtmHiMdbOVt1wkA3qFzHQB4/vcSgLXExMTENmKoWLGiV6/VbtmffvqpdOnSRZ544gnJlCmTpEqVysQkuk7tvqffjxo1yjRuCHlw5Opmoe30NHWlk8ECCD6nBkiB7linn85fLngrYOtDeDEZLABYw8mTJ2Xy5MnStm1bM7WPy8WLF032R9ts58uXT5o3b+71ujt37myCKp0eSDNFGmxduHBBMmTIIPXr15e3337bo6YNQQmO/vzzT6lVq1aK7fQAAIBnKKkLDLJGQGDNnj3bzFvqcv36dXMft9uczmHUsGFDuXTpkrzyyivSs2dPqVy5smmOoAGTTgt0+vRpyZEjh0yZMsVkfnyh29SxRxoYac8DVxVbmjRpJFB8Co404tMdAYBIZYfsEeONkBw61QEIhJMnT7qdWDXuMn2Oq6tcjx49TKtu7Ry3cuVKE7hoHwKtNnv99dfljju8r4DReZI0/ihdurT5Xkvo8uTJk+h5f/zxh2n2ULNmTQlpcNSyZUsz6+3Vq1dNKgtA6Di1tA6wM7JGAKyqffv2HneA01I6LXsLtNq1a5s24N98802yzxsyZIiMHj06UcMGb6T2dcyRzqzbqFEj2bNnj88bB4Bw4oIUsBdK6gD7iomJCchzgpI50jrBBQsWyEMPPSRlypSRokWLmhSZu8YMmvZauHCh3zsKAIAdEaQDQGAcPXrU7w7aPgVHR44ckTp16phaQo3QNHuUVAZJgyNfbNiwwcyltHbtWnPTbfoTEWpfdc146SCu48ePm7rFZs2amWU6OMwdTclp20BNz2kTCj3YOrfTu+++K3fddZdP+wHAWuww9ggAALsZP358vO/1WjzhMpfo6GjZtWuXSd7EbRQRsuCoW7duZgc0QHr11VfNRK+BnudIu2LMnDkzIOvSbhZVq1Y1B1X3tWnTpvL777/L8OHDzURSq1atkly5csV7jXa/0LFV2jtdgyftwKHr0Q4b2rVj8eLF8sADDwRk/wBvOXHcUaDbeQNWQNYIANzTcU6uJIver1ixwtySogkU7YXQp08fCXlwpFFZqVKlTGARyNZ5cWkwo5M4aRtAvWnp3rVr13xal86Uq4GR9lT//vvvzey56rXXXpPPPvvMBHtjx46N9xrNFmlgpO9z+fLlkjdvXrNcJ5tq0aKFtGnTRnbs2BG7LgCRi+xR5IvEuY6CGRg5sVMd440Ae+nTp48JijTo6d+/v5QvX16aNGni9rnp0qWTAgUKSL169Uz7cH+kivGhTi1nzpzSoEEDmTRpkoSKRoIaHHm7u9rOr2DBgiaIOXjwYGyQo3R92lji77//NjWKt99+e+xjd999twl+NEDSTFNc+oP58ccfTRbpySef9HhfdPbe7NmzS53cHSUqdTqv3geQUCgzRxeKZbTEDyDYmaNIK6+jlXd8kRQcBTtjZJXgKOu+KyHbFsERAiX61nVZcGq0nDt3TrJly2aZA+u6jizywUBJ7WO36FtXr8qBHr0t995SokmSVq1amW50webTX2et5YuULnW//PKLKZGrUaNGvMBIpU+f3nTc07FFc+bMiV2+b98+ExhlzJjRlNMlpJkjNWvWrBC8AwChQokTOM8AwHr2798fksDI5+Bo0KBBsnXrVvnqq6/E6jZv3mzuK1as6PZx1/ItW7Ykes29994radOm9eg1QKjxKamzAySyRpEpUs4vAHAqnwbMbNu2zUzE9OKLL8p3330ndevWTbKVt2rbtq2Ei5bSKS2tc8e1/MCBA369BoB9mjIwBgnBOq8QHHxYBNjfiRMnZNSoUbJs2TIzbCapXgQ6TsmfCrcof7pH6Pgf3UFtWOCOPq7PC2dwdPHixdi5mdzJnDmzub9w4YJfr3FHf2hxf3BaKwogMhAgIdDnU6hYZbwRAASKDnepVauWnD59OiATvQY8OHJ1j0DyBg8ebOZEAhCZCJAAAAi/N954w0ypo43QevXqJaVLlw74NEJ+BUc6cWqkcB24y5cvu3380qVL5j5r1qx+vcYd/eFpm/C4mSPtjgcEihPnOwo1AiT4e/4AAPyjVWp33nmnTJ48OegJGttP0lO4cGFzf/jwYbePu5YXKVLEr9e4o93w9AYgsieDdV3gWqnVt7atpimDdREUAUDgaCmdznMUiso123+kVa5cOXO/ceNGt4+7luuEswlfo40nbty44dFrADjjgpeLXmuy0hxH4TxHnDjeiGYMgP3df//9IWuE5tFf8KeeesoMhPLH77//biZvCjWdrFa76Gk6TrtcxKXNEnSuojRp0sjjjz8eu7xYsWJy1113yZUrV2T27NmJ1qmTvyqdIwlwglBO5BgJCJLAeZEy/m4ACBQd0rNu3bqQzDHqUXC0YMECue+++6R58+YyY8YMuX79ukcr1+dNnTpVmjRpYrIxixcvlmAZMWKElClTxozziSt//vzSunVrsy+dO3eW6Ojo2MfefPNNOXnypDzzzDNy++23x3uda6yQPiduUDVt2jT58ccfpWTJkuZ9AU660HHdws0qn46HO0iyUrbEqVznABnF/2OVvxMA7KVLly4mFmnXrp18++23smTJEtM1290t6GOO9u7dKwMHDjQByMyZM00jgipVqkjlypXN4KicOXOaZdra+u+//5Zdu3aZ6G7NmjVmmY676d69u7z11lse75hmbAYMGBD7vSsg0+26vPPOO9KwYUPztXaw0O1q3/OEPvnkE1m9erUJ1DSA0tScZrK0bK5UqVIybNiwRK/p2LGjzJkzR6ZPn25e8+ijj5ptLF26VDJmzGh+KFFRth+yBbilFz4XimXk6Fh4TJKThCNItGIwFO4PDQiIAARL7dq1Y6cRmjBhgrkOT87Nmzd93pZHV/fZs2eXDz/80AQ433zzjbnNmzfP3NwNjHL1H9fytB49ephAI2/evF7tmGZ0NLhKKO4yfY4ncufOLWvXrjUpOc18acCj+/Paa6+ZVts5cuRI9Botxfvhhx9k+PDhMnr0aPnpp5/M/EbaQlBfc/fdd3v1fgC7daxzXQgRJP0fgiT7s2JQZAUERgCCSedMDdU0QqlifJxJafv27WYcz5YtW0zZ2blz50wQpeVpWkJXo0YNM24HEq+Vtx6jOrk7SlTqdBwaBEy423mHK0AKddc6X4Qim+TkrnWhyhpFQlAUjsxRuIMimjEgGKJvXZcFp0aba9ts2bJZ7jqyyAcDJXWGDD6t49bVq3KgR2/LvTcr8bkuTDMnZE8AKMrsksY8SZEtEoIipwZGABAMkfFXH4DlcaEUvgtspzZmCPb7jpTAKBz4fQdgV3QUABCxGaRwTAjrKzJIsEvWiMAIcJYNGzbI/Pnzzfh9vR05csQsdzcy59atW7JixQrTcnvhwoWye/du01StYMGCUrduXdOLQHsSpKR///4+76+OTdKmbb4iOAIQUJTYhS+L4qSxR2SNwoPACHCeAQMGmG7Vnna4rlmzpvk6X7588sgjj5j5RDWo+uKLL2TixImmG3T16tWTXY82UXN1p/OU6/kERwDC1rHOCgES2SM4uZwu3O27Adhf1apVpWzZsmYKH70VLVpUrl275va5Gphohqhnz57y8MMPx3aY0+e/+OKLMnbsWGnTpo38+eefkjZt2iS32bdvXwkXn7vVwXt0q0MwWSk4cglliV2klNcFu4OdE7JHwcwaRVJgFOrgyGpZIzrVIVjoVpe8DBkymGDH2xDiypUrkj9/ftMpTydwrVWrllhRZP0XAAAbiLQLcFiTkwMjAJEnY8aMUrp0afP10aNHxar4Dw3AFhdUlBc5u3Od04JWAiMAkebWrVty4MCB2PFIVkVDBgBBxfijyO9e52/AFchSv2AFf5EUGIUSGSPAvkM94kqfPr25BdOkSZPkxIkTkidPHnnooYfEqnz6b5A6dWpJly6dDBs2LNnndejQQaKiiL+AUKD+PvJEwgV5IIIRq2ezIuHnEBdZUsDZMh5Jbf5u+XLT16pChQpJ9uzZY2+DBw8O6j4fOnRIunbtGtumO9iBmD98jlyio6PljTfekK1bt8qXX36ZZMcJ+j0ACMeFo5MzSIFo6x3ogMaqrcYJjAA4kQYr2bJli/0+mMHKpUuXpHnz5nLq1Clp2rSp6VpnZT5fPTRo0MC08xs3bpzUrl3bpMkAwB1KcyLnAl2DmGBlevxdt9UzUMFGxuj/kCkH/KOBUdxbsIKjGzduSMuWLWX9+vVmbiOd58jqfP6PrAOpli5danqVr1q1Sh544AHZtGlTYPcOAPy4kHTyxaS3gUQwg6KktuXN9oKxb1YKSlMSjnOZDzUA+NuAoV27dvLzzz9L+fLlZdasWaZjndX59Z9Bo8wJEyaYOsXDhw+biHDKlCmB2zsA8FOkBEjBuFBPKqCIG5yEMihKaV+Se45TAyOnB/kAIterr75qmjBo++65c+dKjhw5fF7X+PHjZeXKlSk+b/Xq1ea5/gjIf4cePXrIjBkzTKOGp556Svr16xeI1QKwkXB+Ch0pF5jBCpCsEgj5sq9OD4wAIBL17t1bRo0aJYULF5b58+fL7bff7tf62rdvL19//XWKz/vmm29MQzh/BOw/xBNPPGGitaJFi8qAAQPkySeflIsXLwZq9QDgiIvNSLlwj1SRcHytEMxTUgfAVx9//LEMGjTIDMFZsGCBCZBCWcqXKlUqv9YR0D7bd999t6xbt05atGgh06dP93vnAMCJ3ewiaQ4kBE64AyIAcGf27Nkm8eFy/fp1c1+lSpXYZe+88440bNjQ9B/o3r27WVasWDETJLnTqVMnMxwn0Pbu3RuvC1/IgiONAHPnzu32sVy5cpn0mdYZfv755wRIAMIyIawdgiQ4J2tkpcCIrBGAuE6ePClr1qyRhOIu0+eos2fPxk7jow3b9OaOdrpOKTjS+ZDi0sAr4bK4Uwzt2rVLli1bJnXr1hV/pIoJ4kRE2qTh5s2bUqRIkWBtIuJmI9aJturk7ihRqdOFe3dgQ9El7pBIYJUAycWqARLZI/sHRlYKiiIpMKKVN4Ip+tZ1WXBqtJw7d87vLEQwriPLvPaepEmfwad13Lx2VXZ++pbl3ps72stAq9A0VHHdp0THNs2ZM0cqVqwoliirS6hgwYLBXD0ANxcMkRAgWSmDZOUsEuV1gTuOVmO1oAgArGbMmDHmXoOijh07mkzTs88+6/a56dKlkwIFCphSP3/nbApqcAQAkcSKQRIBkv/Hz0qsHBRFStYIgDO0a9cu9utx48bJY489Fm9ZsBAcAQgLq2WPrBwkESBFPisHRYrACICVLV68OGTbIjgCEPYLMoIk2DVrRFAUeIw3AhBMBEcAws7KWaSkLnBDnVUie+T98Qo1qwdCCZEtAhBJtm/fLkOGDDEd6Y4dOxbbUjwhbd6g3et8RXAEwBKsnkWyQsBEgOT5cQq2SAuE4iIoAhBpVq1aJXXq1JErV67ETh2kk8wGA8ERAEuJtCDJkwvmQAZNBEgpH59Ai+RAKC6CIgCRqlevXiYw6tq1q/Tu3dsER8FCcATA8hdykRgoJby4JkAKPgKjxAiIANjB+vXrpXz58jJs2LCgb4vgCIDlRXI2KVjIIAVfJGeMCIoA2InOY1SmTJmQbCv8rXwABJSdOznpBV+kXvQF40LbCt3YrCLQxyJSA6NI/h0BgKToBLDakCEU+M8K2JCdA6RIvgCM1AtuqyMw+kck/k54+3fN7n/bALj33nvvyZ9//ikjR46UYKOsDrCpuBcR0SXuEDuyegtwdxh/FFgERvYOjAiGAKiNGzdKhw4d5LXXXpPJkydL3bp1pWDBgpI6tfs8T9u2bcVXBEeAA9g5UCJAcu74IwIjgiIAztC+fXszf1FMTIwsX77c3PT7hPRxXU5wBMDrQMluQVKkltj528XOiUFRwvceiCApEkse7ZYtIksEICl9+vRxGwwFA5kjAICjRWJgpLSk1E4Bkn5gQ4AEwJ1+/fpJqNCQAXAYvQAha2SfC3M61oX3+COw+NsEINzIHAEOwoUH7MbpwaHdskeKDBKA5GzevFnWrl0rp06dknvuuUcaN25sll+7ds3csmXLJv6w9H+VK1eumBrD0qVLS4YMGaRAgQLSsWNHOXLE81aeY8eONTWKKd3Gjx/vduBXUrfPP/88CO8YCB67BkaR1q0OQMrIcANIaNeuXfLQQw9JxYoV5cUXX5TevXvLjBkzYh+fOHGi5MyZU3755RexZebo6tWr8sgjj8jq1aslf/780qRJE9m/f7+MGTNGfvrpJ7O8ePHiKa6nZMmS0q5dO7ePnTt3Lvag6uRS7tSvX1/y5cuXaPmdd97p9XsCvGHXYAaBb+/t1G51sL9A/x1kTBMQmQ4dOiQ1a9aUkydPmkxRjRo15I033oj3nFatWknnzp1l6tSp0qBBA/sFRwMHDjQBUNWqVWXevHmSJUsWs3zYsGHSvXt3k0FasmRJiuvRoCepwOe///2vCY6qVauWZKDVs2dPqV27tp/vBkgZwRAQ2pI6xhs5T8K/swRLQGTo37+/KaP7+uuvTQygEgZHmTNnlvLly8uaNWvsV1Z3/fp1GTFihPlaZ8J1BUaqW7duUrZsWVm6dKls2LDBr+18++235v7f//63n3sM+F42QvkIAH9QWuo7/gYDntmxY4e0adPGVHOlT59eihYtKq+88ooJWEJBS+X0+t8VGCVF98ub4TcRExytWLHClLyVKFFCKlSokOjxFi1amPtZs2b5vI19+/bJypUrJV26dCYNBwQbwVDg2emikK51QHjxNxpwb9GiRXL//febMT05cuSQJ554wgRImsDQ6/TDhw8H/dCdOHHCoyEtN27ckMuXL/u1rSirdqFQOuDKHdfyLVu2+J01atiwoRm8lZRp06aZ2sWbN29KsWLFpFGjRlKmTBmftwvroZwNiDyU1MFO/xso74NVXb58WZ5++mlzr03S3n33XbM8JiZG3nzzTRk6dKg8++yzMnfu3KDux2233SYHDx5M8Xm7d+822S3bBUeuN1+wYEG3j7uWHzhwIOgldZ999lm873v06CEvvfSSDB8+XKKikj98rpaCLufPnzf30cXyi0Rl8HnfAdiTv40Z4Plxths7tvR2Ej6ks5bo6KsioakWs7xp06bJX3/9ZbI2ffv2jV2unZvfe+89mTJliukNoImNcuXKBW0/tD+A9gnYtGmTGVfkjg652bZtm+k47Q9L/he+ePGiuc+UKZPbx3XAlbpw4YJP69fe6BpZ5sqVy2SO3NE0obbr1udptLx3716TPtR04qhRoxINAnNn8ODBkj179thboUKFfNpfAPYuqQMAwIo2/P/x/dopLnXq+GFD2rRpTdCiZs6cGdT9+M9//mOyVdq9+ueffzYVXQlL/zThoYmLrl272i84CjZX1kjHGumYI3e6dOkiL7zwgpQqVUoyZsxoSuq0PeDy5cvNa7RhhLYVTE6vXr3M2CnXLaXnA4A/WQ2nT4jq1KwRAATLpUuXzH1SQ1C03C3ukJhgefDBB+XTTz+Vo0ePmjFPmqzQ7JUOfdF9q1u3rnlMr8+1cYM/LPmf1NWdLqkBVa4fVNasWb1ed3R0tHz//fc+d6lzzcSr61m4cGGyz9XBajpLb9wbAKSEC/jkEQQCQGjkyZMn2aEs2uAsuccDyZWk0PH/GhhpJkmryHQIi85LqmV1zz//vN/bseSYo8KFC5v7pLpfuJYXKVLE63VrXaR2vNB5jXSWXV9oNkkdO3bMp9cDAELP7kEn444AeMo1Dj7uB/p6S0jL6XRs0ezZs03b7ty5c8c+pi2z58+f79dQF29VqVLFjD3SwEj359atW2af0qRJE7BtWDJz5BrQtXHjRrePu5b7kjZzldQ988wzPu/fmTNn4o19AhBaThhv5OuFPFmVwB5PALCazMdumb9pvtz0tUrHwccdF6/j5N2pV6+e6RKt/QAee+wxM25fv161apX5XiupVMLxSMGmmSPNauXNmzeggZFlgyMd3KU/qD179piuFAlpZwylaTVv6A/TNWDM1+BIU3caPSfXahwAAoEL+sAEfxxHAIhPx8HHHRev4+STCkKmTZtmhpWsX7/ejP3RYS1afaWVWP369TPPS25anEhjybI6bXigs+4OGjRIXn75ZVMK58rSDBs2zMxvVKtWLalUqVLsa3QAlt6aNWuWZPSrP1wdx6QpOVdpnDs7d+6UdevWmYYNcVOMJ0+eNLWMekJpdsvVoQMAgoX23gCAQPNmLHyRIkVMsmL69OmycuVKuXLligmW2rRpY66tlX4fSI888ojPr9WALqW+ABEXHKnevXvLggULzA9BA5kaNWqYwV5r1qwxabTRo0fHe77WHe7atSvZcUCezm10/Phxadu2relYpzMC6/a0A4a2M9SaSp1nafLkyebgAwCsy2lZI8YdAQiGqKgoadmypbnFpdfpqnbt2gHd3pIlS3x+rb/X55YNjjJkyCCLFy82WaCJEyeawVc6L5FO7DRgwIAkJ4hNigZN2gNde7I/9dRTyT63dOnSpkf66tWrZevWrXL69GmTQdLlWsqnQZOd0odAJHHCeKNAlJ5dLuisoAAAEFrHjx83Q120nXfz5s0Dum5XF7xwSBWj7R4Qss4gOpaqduW3JSoqA0cd8IFTg6OLd3g31saOwRHjjTyTdd+VIP8kAHuLjr4qS9YNMmNxrDQNi+s6slLLgRKV1rfryOgbV2XDD729em/btm2TkiVLmsRF3M7RTz75pGnQMHbsWGnXrp3YhWUzRwAA+MNpJXUAEAxDhw414420EVn+/PlNI4Zff/3VNCl75513bBUYKYIjALAhSuuci3FHAAKpadOmpoRu8+bNsmLFCjO0pEGDBmYISqDHGlkBwRGAiOHUkjpF1zoAQLiCo6ZNm4b14Hszl5E2ZHDNv+QLgiMAgO3GG1FSBwD2UahQIbdd6G7dumWyWjdu3IhtO+4vgiMAAGyG0joAdrJ///4kH9MASTtSazfp++67TyZNmuTXtryfahwAEBbeZkN86e4GAEAkSZ06tdSpU0d++uknmT17tnzwwQf+rS9gewYAQeTk8UbwDiV1AOA8xYoVkypVqsjo0aP9Wg/BEQDA0siAAQA8kSlTJjl06JD4g+AIACIIWRF4imwrACc5cOCALFu2TPLmzevXemjIAMDyuMjzP+tyuWDkTYhKxggAoMaPHy9JuXjxouzevVu+/fZbOX/+vHTu3Fn8QXAEAA4QN9CwcqDkb0BEZi0+utYBsIP27du7beXtEhMTY+7btm0r7777rl/bIjgCYGlkjYIfgIQ7WCJDBABITp8+fZIMjtKlSyf58+eXmjVrSvHixcVfBEcALIvAyJ5ZJYKh0CJ7BCDS9evXL2TbIjgCYEkERvYKlAiIwosACQA8Q3AEwHIIjKyBgMZeCJAA2MHKlStl+fLlcvToUfN9gQIFpHr16lKtWrWArJ/gCIClEBgBwf39yrrvCocYQMTZunWracywadOmeE0YXGORypUrJ2PHjpWyZcv6tR2CIwCWQWAEhOb3jAAJQCTZtWuX1KpVS86ePSsFCxaUFi1aSNGiRWPnN5o6daoJmmrXrm0yS2XKlPF5WwRHACyBwAgI7e8bARKASPHWW2+ZwKhnz57Sv39/iYqKH8IMGTLEdLQbPHiwvP322yZY8pV/E0oAQAAQGAGhx+8dgEixePFiueeee+S9995LFBipNGnSyKBBg8xz9Ln+IDgCEFZcoAH8/gFAcm7cuOHRWCJ9jj7XHwRHAMKGwMg3WY6Ed9JW2Au/hwCsrly5crJnz54Un6fP0ef6g+AIQFhwQQZYB7+PAKzs7bfflnXr1sno0aOTfM6YMWPMc3R8kj9oyAAg5LgQA6yHJg0ArGLZsmXxvs+cObO89NJL8txzz5l23U899ZQUKVIktlvd5MmT5ddffzXPyZIli1/bJjgCEFIERoB1ESABsAJtye2avygundtIg6AVK1YkWq7++9//mtvNmzd93jbBEYCQITACrI8ACUBSTp48KR988IHMmjVLDh48KBkzZjTzDT366KPy4YcfSqC0bdvWbXAUCgRHAEKCwChwLt7BcFGE5veVuZAAuGzYsEHq168vp0+fNi2zmzRpIufPn5ft27fLxx9/HNDgSEvnwoXgCECyCGoA5wrE7z8BFmCPjFGDBg3kypUrMnPmTGncuHG8x9euXRvU7X/66aeSKVMm6dSpkwQbHz8CSBKBkTXRyhuRhL8jQOTr27evnDp1ymSHEgZG6oEHHgjq9rt3725K+UKB4AiAW1zQWBdldYjEvyf8TQEi05UrV+Tbb781HeM6dOgQln3Ily+fZMiQISTboqwOQDxcwAAIFpo9AJFn/fr1cuHCBalevbppwPDzzz/L/Pnz5erVq1K6dGlp1aqVFChQIKj7oGOddLvXr1+XdOnSBXVbBEcADIIiAKFAswcg/LSRQlzp06c3N3e04YK6/fbbpWnTpmbMUVw66eo333wjrVu3lmAZNGiQzJs3T9q0aWPGH+XPnz9o2yI4AkBgBCDkCJIA32Tdf0Wiov6Z18db0dFXzX2hQoUSjSnq16+f29ecOXPG3P/444+SJk0aGTlypLRs2VIuX74sI0aMkKFDh0q7du3krrvukvLly0sw9OrVS8qVKyfTpk2T2bNnS8WKFaVw4cJuS+20BbgGa74iOAIcikwRACsgSAJC79ChQ5ItW7bY75PKGqlbt26Z++joaJPB6dy5s7hog4YDBw7IDz/8YL7+7rvvJBjitvbWcr6VK1eamzsERwC8RmAEwGoIkoDQ0cAobnCUnCxZssR+7a4hgy7T4Gjp0qUSLIsXL5ZQIXMEOAQBEYBIQJAEWEuRIkXMvc4zlCdPnkSPFy1a1NyfOHEiaPtQq1YtCRWCozC4UDSjRKUNTTtCAAAiER/oIFyib6QSWcfxd6lQoUJsS+9r164lKsH7+++/E2WYIpml5znSH0KfPn1Mm0AdcKVtAjt27ChHjhzxaj0a0Wr9YVK3nTt3un3dzZs35eOPP5b77rvPtC7UaFnbFe7YsSNA7xAAAACwrsKFC5tmCDExMW5L51zLXEFUpLNs5kgHWz3yyCOyevVq066vSZMmsn//fhkzZoz89NNPZnnx4sW9Wqd20nAne/bsbgefaSeO6dOnS44cOaRhw4ZmZuApU6aYLhla+xjs2YABAACAcHvzzTdNG+3//Oc/Mnfu3NhW2ps2bZKPPvrIfP3iiy8GbfvaJc9TmvjQ5hG2C44GDhxoAqCqVauavuauVN2wYcOke/fuJoO0ZMkSnztdpGT06NEmMCpVqpQsX75c8ubNa5ZPnTpVWrRoYU4QzSBFRVn2EAIAAAB+e/rpp831+Lhx4+Tuu++Whx56yFR4acc4LbV77rnnTFIhWLT1uAY97pIZx48flxs3bsQbH2W7sjqd/Vb7pivtpR63hrFbt25StmxZk8LbsGFD0PZBgzA1ZMiQ2MBIPfnkk9K4cWP5888/E02CBQAAANjRmDFj5Msvv5QSJUqYBMXatWvNfEOafNDlwaTVY/v27Ut00zbiGqRp4KbzLD344IOyd+9e+wVHK1askHPnzpmD765+UTM3atasWUHZvh5szQrpOCMtpwv19gEAAAArSZUqlckQrV+/Xi5duiQXL140maOkhq2ESurUqaVOnTpm2I0Offnggw/8Wp8la8I2b95s7jUadce1fMuWLV6tVyen2rNnj+mycc8990izZs3ctiR0bf/ee++VtGnTBmz7AAAAAAKvWLFiUqVKFTM0pmfPnvYKjg4ePGjuCxYs6PZx13JNpXk7mCyu119/XT777DMzfikY29caTL25nD9/3qv9BQB45+IdqSXLkX9mcwcAOEumTJnk0KFD9iur0zSd6w26kzlzZnN/4cIFj9anY4SmTZtmgpnLly/Ltm3bzNglDVw6deqUaOxQoLY/ePBg0wnPddPBZAAAAAACS6/zly1bFq9XgG0yR4H26aefxvteS+q07WCZMmXk+eeflx49ephW4YHWq1cvE4TFzRwRIAHwNzMCAICTjB8/PsnHNKmxe/du+fbbb821dufOne0XHLm602mWxx0dBKayZs3q13aeffZZ6d27t+zatct0wdDJYgO5fR3blHAWYQAAAABJ07lMtTW4q7lC+/bt3bbydtEJalXbtm3l3XffFdsFRzoTrzp8+LDbx13L/e1lrt0ttCPeiRMn5NixY7HBUai2DwAAACA+TVqcPHky9vs+ffokGRylS5fOTEpbs2ZNE1T5y5LBUbly5cz9xo0b3T7uWq7zHfnrzJkz8cYRxd2+jk3SSaUSdqwL5PYBAIFFUwYAsJd+/fqFbFuWLF6vVq2aaWCgbbc3bdqU6PEpU6aY+0aNGvm1nd9//92U1GnjBR1/FLcVoE4kpZNKab/0YG0fALzBeCMAABwYHGl67JVXXjFfv/zyy7FjfNSwYcPM/EK1atWSSpUqxS4fMWKECXC0CUJcc+bMkUWLFiXahq5Daxm1RlE71uk243I1UtD231p256Jd73788UcpWbJkUJo4AAAAAAgPS5bVKW2UsGDBAjPzbqlSpaRGjRqmRd+aNWvMxK06wVNcp06dMlkgHTsU19q1a83ALB0fpOVymiXau3evKY2Ljo6W2rVry/vvv59o+zr3kQZW06dPN0HXo48+araxdOlSyZgxo+mIERVl2cMHAAAARKxNmzZJ//79fXqtjlHylWWv7jNkyCCLFy82cwVNnDhRZsyYIbly5TLdKgYMGJDkBK0J1a9f30wGtW7dOlmxYoWcO3dOsmXLJtWrV5c2bdpIhw4dJE2aNG6bNfzwww8yfPhwE4j99NNPZlzSk08+aYKtu+++OwjvGgAQCIw7AoDItnnzZnPzhlaEaeMGf4KjVDGu3ncIOu29rmOpKrUcKFFpM3DEAXiFMUfeyXLkFmcYAK9F37gqG37oHfuButWuI2tXfluiony7joyOvipL1g2y3Htzl6TQISzah8AXY8aMEdtljgAA/4fACADgJNWrV080jMaxDRkAAAAAINQIjgAAAACA4AgAYFeUIgIAvEXmCAAAAABoyAAA1kcGBADgJLduha/bKJkjAAAAACA4AgDYGVk3AIA3yBwBgIVxcQ8ACLdhw4ZJ8+bNpVSpUmYi2vTp00uRIkWkbdu2snXrVrETgiMAsCgCI44jAFjBe++9Jz///LPkypVLHn30UWnYsKFkyJBBJkyYIJUqVZKffvpJ7CIq3DsAAAAAwLpmzpxpgiANiOIaNWqUvPzyy9KpUyc5fPiwREVFfmhB5ggALIisEccTAKyiWrVqiQIj1blzZylRooT89ddfsn37drEDgiMAsBgCo+AdV44tAARW2rRpzX26dOlscWgJjgDAIrh4D91xBgD4b8KECbJr1y7TqEFvdhD5hYEAEOG4WA/fMc9yJHwTDQJApPnwww/l999/l0uXLsmOHTvM1wUKFJBJkyZJmjRpxA4IjgAgjAiMwosgCYATnT9/Pt732ppbbymZO3euLFy4MPZ7bec9fvx406zBLgiOACAMCIqs9/MgiwQgEkTtOyZRqX0c33PrurkrVKhQvMV9+/aVfv36pfjyBQsWmPuzZ8+a+Y369+8vtWrVkoEDB8rbb78tdkBwBAAhRFBkXWSRADjFoUOHJFu2bLHfe5I1iitHjhxSo0YNmTNnjlStWlXeeecdqVevnlSuXFkiHaNSASAEaLYQOfhZAbA7DYzi3rwNjuJ2qnvqqackJiZGZs2aJXZAcAQAQUa2KDIRJAFAynLnzm3uT548KXZAWR0ABAEBkT1/loxLAoD4li5dau51Mlg7IDgCgAAgGHIGAiUATrNixQq5cOGCGVOUOvX/fVh048YN+fzzz81cRxkzZjTldXZAcAQAPiIgcjYCJQBO8Mcff0iHDh1M+Zy27L7tttvk1KlTplvdsWPHJEOGDDJ27NhEHfAiFcERAHiBgAgpnReU3gGwk1q1aslbb71lyue2bNliAqN06dJJ0aJFpUWLFvLaa69JyZIlxS4IjgDYViACGb3QJSCCr+ddoM4fAi4A4VKsWDEZNGiQY34ABEcAbCXQgQyBEaxw/pCZAoDQIDgKg0v5U0ua9HRRDyQ+VXU2Ahg4+Xzn759z8bcvOG5e4xrNyQiOYAt2+AfBBY6zft5AoJBV8v+4AYALwRFgEZH6jzpUQV2kHh/A7oESv5sA7ITgCIBfuDACrInfTQDwHh/FAgAAAADBEQAAAAD8g8wRAAAAABAcAQAAAMA/yBwBAAAAgNWDoytXrkifPn2kdOnSkiFDBilQoIB07NhRjhw54vE6zp49KxMnTpTWrVtLsWLFJF26dJI1a1Z58MEHZfjw4XLjxg23r2vfvr2kSpUqydvnn38ewHcKAAAAINws28r76tWr8sgjj8jq1aslf/780qRJE9m/f7+MGTNGfvrpJ7O8ePHiKa5n6NChMmjQIBPQlC9f3gRFJ0+elBUrVsjatWtlypQpMnfuXMmUKZPb19evX1/y5cuXaPmdd94ZkPcJAAAAwBosGxwNHDjQBEBVq1aVefPmSZYsWczyYcOGSffu3U0GacmSJSmuJ3PmzPLmm2/Kyy+/LIULF45d/scff0idOnXk119/Ndt677333L6+Z8+eUrt27QC+MwAAAABWZMmyuuvXr8uIESPM1yNHjowNjFS3bt2kbNmysnTpUtmwYUOK6+rVq5d88MEH8QIjVapUKXn//ffN15MmTQr4ewAAAAAQWSwZHGnJ27lz56REiRJSoUKFRI+3aNHC3M+aNcuv7ZQrV87cHz161K/1AAAAAIh8liyr27x5s7mvWLGi28ddy7ds2eLXdvbu3Wvu3Y0pcpk2bZpMnTpVbt68aRo6NGrUSMqUKePXdgEAAABYjyWDo4MHD5r7ggULun3ctfzAgQN+bUe71Slt9pCUzz77LN73PXr0kJdeesm8NirKkocPAAAAgF3K6i5evGjuk+ogp00W1IULF3zehrbiXrBggeTIkcM0XUhIy/n0Obt375bLly+bLJOOf9Lnjxo1St54440Ut3Ht2jU5f/58vBsAAAAAa7JkcBRsy5cvly5dupj23qNHjzbzJyWkj7/wwgumcUPGjBlNSV3nzp3Na3WuJG0YcejQoWS3M3jwYMmePXvsrVChQkF8VwAAAABsFxy5utNpxsadS5cumXudzNVb27ZtM2V02hFPS+OaNWvm1evvueceady4sURHR8vChQtT7JSnjSVct5SCKQAAAADhY8lBM66224cPH3b7uGt5kSJFvFrvvn37pF69enLmzBnp16+fvPrqqz7tn2aT1LFjx5J9Xvr06c0NAAAAgPVZMnPkarG9ceNGt4+7lut8R57SQKZu3brmXkvm+vbt6/P+aXAVd+wTAAAAYFdXrlyRPn36SOnSpSVDhgxmSErHjh3lyJEjYjeWDI6qVatmxujs2bNHNm3alOjxKVOmmHttq+1pMFO/fn2zvg4dOsjHH3/s875pk4XZs2cn22ocAAAAsIOrV6/KI488IgMGDDBN03R4io6jHzNmjGlg5poaxy4sGRxpw4NXXnnFfP3yyy/HjjFSw4YNM/Mb1apVSypVqhS7XBsk6PxDOs4nLh231LBhQ9m6dau0atVKvvrqK9OIITk7d+6UCRMmmEAorpMnT8q//vUvM3ZIs1saxAEAAAB2NXDgQFm9erVUrVrVdHH+/vvvZc2aNfLRRx+Za2PNINmJJcccqd69e5tW2ytXrjRjfGrUqGHmNdIfRp48eUyXubhOnTolu3btSjQO6O2335ZVq1ZJmjRpzLxEzz77rNvtjR07Nvbr48ePS9u2bU353f3332+2d/ToUdmwYYNpH67zLE2ePDnFIAsAAACIVNevXzcJCKVT2riapqlu3brJuHHjZOnSpeYaOW7SIpJZNjjSesbFixebdtgTJ06UGTNmSK5cuaR9+/YmrZfUBLFJjQ+6efOmWU9S4gZHWk/ZtWtXEyVrxun06dOmsYIu11I+DZpy5swZgHcJAAAAWNOKFStMx+USJUqYErqEWrRoYSq6Zs2aRXAUCjq/UP/+/c0tJdp9Tm/ugp64gY8ndJCZP+OSAAAAgEi3efPmZMfZu5ZrgGQXlhxzBAAAACC8Dh48aO6TqthyLdehL3Zh2bI6O4qJiTH3N69dDfeuAAAAwA3XdZrrus1qomOui9zy47Uicv78eY/m5rx48aK5z5Qpk9v1uaa10TH5dkFwFEKuE+ePL1IuEwQAAEB4r9t0ahkrdXPOly+fLDn+rV/r0aYK2oo7Lp3/093wFCciOAohHcukbcCzZs3qqE53+umE/hLqe8+WLVu4dydicRw5llbEeclxtBrOSY6lvzRjpIGRXrdZrVnZvn37TAc5f99fwutQd1kj5epOp1PjuOOabkevbe2C4CiEUqdO7XGXPTvSwIjgiONoJZyTHEur4ZzkWFqRE89LK2WMEgZIeguVwoULm/vDhw+7fdy1vEiRImIXNGQAAAAAkEi5cuXM/caNGxM/GGd52bJlxS4IjgAAAAAkUq1aNZNF27Nnj2zatCnR41OmTDH3Og+oXRAcIei0jlUH+iVVzwqOY6hxTnIsrYZzkmNpRZyXSJcunbzyyivmQLz88suxY4zUsGHDzPxGtWrVss0EsCpVjFX7FAIAAAAIq6tXr0rt2rVlzZo1kj9/fqlRo4aZ10i/z5Mnj6xevVqKFy9um58SwREAAACAJF25ckUGDx4sEydONN2Hc+XKJQ0aNJABAwbYrtkYwREAAAAAMOYIAAAAAP5BQwZ4bMOGDfL+++9L8+bNTQpVJxDzdTLbokWLxr7e3W3nzp22/cnoRGozZsyQZ599Vu68804zX0HmzJlNu8z+/fvLxYsXvV7nmTNnpEuXLmaeAR1Aq/ddu3aVs2fPip0F+lg6+bx0Da7V3+9SpUqZ7kSuc6lt27aydetWr9fn1PMykMfR6edkXKdPn5bbb7/dvO+SJUv6tA6nnpOBPpacl7AzyurgsaZNm8rMmTMTLfelp4f+YdXBfO3atXP7uNa16qA/O/r666/lueeeM1/fddddcu+995oZ3VeuXGlm5C5TpowsXbrU/OPyxKlTp6Rq1ary559/mgGR999/v/z+++/mVrp0aVm1apWpDbajQB9LJ5+XKnfu3KYTkc5Xcccdd5hleh7t3r1b0qZNK9OmTZMnnnjCo3U5+bwM5HF0+jkZV/v27WX8+PHmf06JEiXMueUNJ5+TgT6WnJewNe1WB3ji/fffj3nnnXdifvzxx5hjx47FpE+fXqMinw5ekSJFfH5tpBs7dmzM888/H7N9+/Z4y48ePRpToUIFc1xat27t8fratGljXtO8efOYGzduxC5/9dVXzfJ27drF2FWgj6WTz0v166+/xly5ciXR8pEjR5rjkjdv3njnWHKcfF4G8jg6/Zx0WbBggTkO+vuu9yVKlPB6HU4+JwN9LDkvYWdkjuAzLWG6du2aX5kjOsnHp59cPvTQQ6bcQzMgOr9Aco4dO2ZKHKOiouTgwYOSN2/e2Mf0Z1OoUCH5+++/5ejRox5nT5x6LBXnZdK09EYnAdy8eXOKM6FzXgbmOHJO/l+XrPvuu8/8LmsZrWZ5vM12cE4G7lhyXsLuGHMEWIiOlXEFNloTnpJffvlFbt26ZeYciBsYKf3npzNW37x5U+bMmSNO4+2xRPK0HEx5EmRyXgbmOOIf7777ruzdu1c+//zz2OPnLc7JwB1LwO6iwr0DcLYPP/zQfIqqF/L33HOPNGvWzEwo5lT6T0vpPy1Pat/102dVsWJFt4/r8tGjR5sZrJ3G22MZF+dlfBMmTJBdu3aZBgN6SwnnZWCOI+ekmL9dH330kXTo0MF8CLR//36vjhvnZOCPJecl7I7gCGH15ptvxvv+9ddfl88++0w6duwoTjR8+HBzrxOracCYEi2lU0lNwOZariWMTuPtsYzL6eelBoc6SF2bCuzYscN8XaBAAZk0aZKkSZMmxddzXgbmODr9nNSseKdOnSRHjhwyZMgQv9bl9HMykMfS6ecl7I+yOoRF48aNTccm/Uek7Zi3bdsm3bp1MyVQ+gfcXVc8u9PSt2+++cZkOnTGaU+4WlVnypTJ7ePa1lpp5zYn8eVYKs7Lf8ydO1fGjRsnU6ZMMRf02u5YL+grVark0XHkvAzMcXT6OakX2evWrTNB5m233ebXupx+TgbyWDr9vIQDhLsjBCKXP93qkvLll1+add55550xTrJjx46YnDlzmvf+ySefePy6unXrmtd89dVXbh+fP3++eVyf5xS+HsvkOPW8PHPmTMyyZcti6tSpY97/wIEDPXod52VgjqOTz8kDBw7EZMmSJaZWrVrxlu/bt8+nDmtOPicDfSydfF7CGcgcwVJ0Mk/tqqZ1+YGoh44ER44cMaVfOjmhfvKmExR6KkuWLOZeP7lzR8t5VNasWcUJ/DmWyXHieam0BEfHJmgmTrMd77zzjvn0OSWcl4E5jk4+J19++WW5fv26aRwQCE4+JwN9LJ18XsIZGHMES0mdOrVpK3rixAnTelVbK9uZttmuV6+eKU3QQbJDhw716vWFCxc294cPH3b7uGu5lvPYnb/HMjlOOy8T0vLEp556SjZs2CCzZs2SypUrJ/t8zsvAHEcnn5M//fSTCSpffPHFeMuvXr0a+0FI7dq1zdf/+9//JF++fMmuz8nnZKCPpZPPSzgDwREsRz/1j1sDbldaA//YY4/J9u3bpXnz5vLVV19JqlSpfGpXvXHjRrePu5Z7Mp+K049lSpxyXiYld+7c5v7kyZMpPpfzMjDH0enn5NmzZ2Xp0qVuH9MLe9djrov85Dj9nAzksXT6eQn7o6wOlqKDljUdr4Nmy5QpI3alg1abNGkia9eulfr16/vUvUppCZl+Urd8+XLzSV3Cbein07rexx9/XOwqUMcyOU45L5PjunjST4VTwnkZmOPo5HNSJwh3d9u3b1/s8XMt8yQ74eRzMtDH0snnJZyB4AhBM2LECPPHsVevXvGWa939okWL3M7B0LJlS/MHWrvd2HWSRJ2UtXXr1uYY6DgE7fiT0ntN6ljmz5/frEvryTt37izR0dHxWqzqp9PPPPOMqQG3o0AeS6eflytWrIidKDOuGzdumE5XOkdPxowZTVmYC+dlcI+j089JX3BOBv9Ycl7C7iirg8dmz54dry2yXpCrKlWqxC7TgcYNGzY0X586dcp8gqR1x3HpJ/w6S7fWdmupg37CpBN2almDXtxr7fP7779v638406dPjy2x0aDGHR0z4yrBSepYqk8++URWr14tU6dONf/I7r//fvPpnbZW1Ykmhw0bJnYVyGPp9PPyjz/+MGO19Dhp0wBt96vHauvWreZYZciQQcaOHSuFChWKfQ3nZXCPo9PPSV9wTgb/WHJewu4IjuAxzUKsWbMm0fK4yzypo9fSp0OHDpluTfop67lz5yRbtmxSvXp1adOmjbmwCHRZlJW46rGV68LenX79+sVe0CdHn6P/rPT5M2bMMOvMmzevvPbaa+bCSgfi2lUgj6XTz8tatWrJW2+9Zcq+NDOhF0aakdAymxYtWpjzqWTJkh6vz6nnZSCPo9PPyUBz6jkZaJyXsLtU2s873DsBAAAAAOHGmCMAAAAAIDgCAAAAgH+QOQIAAAAAgiMAAAAA+AeZIwAAAAAgOAIAAACAf5A5AgAAAACCIwAAAAD4B5kjAIDH+vfvL6lTp5atW7cG9ag1bdpU8ubNKxcvXgzqdgAAiIvgCADgkb/++ks+/PBDadGihdx3331BPWp9+vSREydOyJAhQ/jpAABCJlVMTExM6DYHAIhUXbp0kU8//VQ2btwoFSpUCPr2GjRoIMuXL5eDBw/KbbfdFvTtAQBA5ggAkKLLly/LuHHj5N577w1JYKSeeeaZ2O0CABAKBEcAYDPr16+XVKlSyUMPPZTkc9577z3znL59+3q0zh9++EHOnTsnrVu3dvu4rqto0aISHR0tAwYMkJIlS0rGjBnlrrvukjFjxsQ+b9GiRfLwww9LtmzZJGfOnNK2bVs5ffp0kuOOdB1fffWVR/sIAIC/KKsDABuqVKmSKX/btm2b3HPPPfEe02pqDV72798v+/btk8KFC6e4vpYtW8qUKVNkxYoVboMuDY6KFCkiFStWjA2ANOuzdOlSuXbtmowePVqyZs1qgqsqVapIvnz5ZNWqVXLkyBGpXr26LFu2zKwjoZo1a5rSuj179kjx4sX9PCoAACSPzBEA2NCLL75o7t1lXRYuXCh79+6V+vXrexQYKQ1QoqKiki2pO3DggPzxxx/mNn36dJk7d678/PPP5rG3337b7NOMGTPMujQTtX37dhO4/frrr7JkyRK363zggQfMvQZZAAAEG8ERANjQ008/bUrXJkyYYDI3cX399dfm/rnnnvNoXdo1TjvVFSpUyJS5JeeTTz6RPHnyxH6vGSQNqI4dOyaPPfaYNGzYMPYx3b/nn38+2eCnTJky5n7Tpk0e7SsAAP4gOAIAG8qcObNpaPD333/L1KlTY5efOnXKZHW0rK1Ro0YeB0dKxwglJ23atFK7du1Ey13lcPXq1UvyMQ2e3MmVK5e5P3nypEf7CgCAPwiOAMBBpXXjx4+X69evS4cOHUyZnCe0EYPSMUPJ0YArTZo0iZZnyZLF3N9xxx1JPpYwuxU3u6TOnj3r0b4CAOAPgiMAsCmdqFWbJ+h4Hh0HpL755hvT+KBTp04eryd79uzm/sKFC8k+L3Xq1H49nlxgliNHDq9fCwCAtwiOAMAB2SMdZ6Sd5rQJwqOPPupV57fbb7/d3GuJXqidOXPG3McdxwQAQLAQHAGAjWkL7ttuu03Gjh0ro0aN8qoRQ9zgSEvmDh06ZNpzh9KOHTvMffny5UO6XQCAMxEcAYCNZciQQdq1a2eaKkycONFkYHRyVW/VqFFDbt68Kb/99puE0tq1a819rVq1QrpdAIAzERwBgM298MILsROsaqCULl06r9fhasGd1HxEwXDx4kVZv369aefNBLAAgFAgOAIAmytdurQULFjQfO1NI4a4WrVqZRozaPYpVLTl+NWrV70uAwQAwFepYmJiYnx+NQDA8latWmW61mlpmj+Zn9dff91M8qrZnEqVKkmw1a9fX3799Vc5ePCgGTcFAECwkTkCAJsbNGiQuX/llVf8Wk+vXr3MvESDBw+WYNu4caPMmzdPunfvTmAEAAgZMkcAYEMrV640cxpt27bNNDWoWLGirFu3zqe5huLq37+/9OvXTzZv3mzmUQoWbRqhGa89e/bEThQLAECwERwBgA1p6+4OHTpI1qxZpWbNmjJy5EgpUqRIuHcLAABLIzgCAAAAAMYcAQAAAMA/aMgAAAAAAARHAAAAAPAPMkcAAAAAQHAEAAAAAP8gcwQAAAAABEcAAAAA8A8yRwAAAABAcAQAAAAAYvw/fIlzjhhR1Y4AAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 1000x440 with 2 Axes>"
       ]
diff --git a/examples/adcp_example.ipynb b/examples/adcp_example.ipynb
index 8df4aa02b..d476e0d21 100644
--- a/examples/adcp_example.ipynb
+++ b/examples/adcp_example.ipynb
@@ -44,7 +44,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 33,
+      "execution_count": 1,
       "metadata": {
         "scrolled": true
       },
@@ -73,7 +73,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 34,
+      "execution_count": 2,
       "metadata": {
         "scrolled": true
       },
@@ -82,6 +82,7 @@
           "name": "stdout",
           "output_type": "stream",
           "text": [
+            "Indexing data/dolfyn/Sig1000_tidal.ad2cp... Done.\n",
             "Reading file data/dolfyn/Sig1000_tidal.ad2cp ...\n"
           ]
         }
@@ -100,7 +101,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 35,
+      "execution_count": 3,
       "metadata": {},
       "outputs": [
         {
@@ -520,33 +521,33 @@
               "    coord_sys:             earth\n",
               "    fs:                    1\n",
               "    has_imu:               1\n",
-              "    beam_angle:            25</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-3fd009a2-dae4-4635-8613-be7515d4baf3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3fd009a2-dae4-4635-8613-be7515d4baf3' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 55000</li><li><span class='xr-has-index'>time_b5</span>: 55000</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>range_b5</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-921732fd-d14b-455c-bd19-6708ed058630' class='xr-section-summary-in' type='checkbox'  checked><label for='section-921732fd-d14b-455c-bd19-6708ed058630' class='xr-section-summary' >Coordinates: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.500999927 .....</div><input id='attrs-24a35bc3-cfeb-4aef-9902-2fffc9e8a9d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24a35bc3-cfeb-4aef-9902-2fffc9e8a9d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc72a277-6552-4bf1-a7e4-a046a5dcdf2b' class='xr-var-data-in' type='checkbox'><label for='data-fc72a277-6552-4bf1-a7e4-a046a5dcdf2b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.500999927&#x27;, &#x27;2020-08-15T00:20:01.501100063&#x27;,\n",
+              "    beam_angle:            25</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-2bb93856-6493-4446-9b87-27cea014a081' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2bb93856-6493-4446-9b87-27cea014a081' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 55000</li><li><span class='xr-has-index'>time_b5</span>: 55000</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>range_b5</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-44ab80c1-468d-4c4c-bfd8-da385ad2911b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-44ab80c1-468d-4c4c-bfd8-da385ad2911b' class='xr-section-summary' >Coordinates: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.500999927 .....</div><input id='attrs-b1f3c94e-ecd6-47a7-9b10-f64197ef1000' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1f3c94e-ecd6-47a7-9b10-f64197ef1000' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0639fea1-589f-4696-98e4-db209d804809' class='xr-var-data-in' type='checkbox'><label for='data-0639fea1-589f-4696-98e4-db209d804809' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.500999927&#x27;, &#x27;2020-08-15T00:20:01.501100063&#x27;,\n",
               "       &#x27;2020-08-15T00:20:02.500999927&#x27;, ..., &#x27;2020-08-15T15:36:37.500999927&#x27;,\n",
               "       &#x27;2020-08-15T15:36:38.500999927&#x27;, &#x27;2020-08-15T15:36:39.500999927&#x27;],\n",
-              "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.438499927 .....</div><input id='attrs-36f73ccd-88a8-4e60-a351-8d1090fe2f24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36f73ccd-88a8-4e60-a351-8d1090fe2f24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5527781-2deb-4052-8b75-2b0148f43ec5' class='xr-var-data-in' type='checkbox'><label for='data-d5527781-2deb-4052-8b75-2b0148f43ec5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.438499927&#x27;, &#x27;2020-08-15T00:20:01.438499927&#x27;,\n",
+              "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.438499927 .....</div><input id='attrs-df1333fa-8090-4b73-90a1-370ef194f0d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df1333fa-8090-4b73-90a1-370ef194f0d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5bc8ccde-7a5f-478c-a30e-602041272b6a' class='xr-var-data-in' type='checkbox'><label for='data-5bc8ccde-7a5f-478c-a30e-602041272b6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time b5</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.438499927&#x27;, &#x27;2020-08-15T00:20:01.438499927&#x27;,\n",
               "       &#x27;2020-08-15T00:20:02.438499927&#x27;, ..., &#x27;2020-08-15T15:36:37.438499927&#x27;,\n",
               "       &#x27;2020-08-15T15:36:38.438499927&#x27;, &#x27;2020-08-15T15:36:39.438499927&#x27;],\n",
-              "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-ffb35e59-f730-42b0-a96f-916b97fb181b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ffb35e59-f730-42b0-a96f-916b97fb181b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-423e0438-a1ec-4677-b2b3-55547eb12915' class='xr-var-data-in' type='checkbox'><label for='data-423e0438-a1ec-4677-b2b3-55547eb12915' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
+              "      shape=(55000,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-f266a94c-6400-4611-b6cc-540c71e6f4f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f266a94c-6400-4611-b6cc-540c71e6f4f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3d7efda-a3b4-4fdf-a0ac-47fa75f7d90b' class='xr-var-data-in' type='checkbox'><label for='data-f3d7efda-a3b4-4fdf-a0ac-47fa75f7d90b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
               "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
-              "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-d67f323c-d7dd-4fb7-9273-81c2d697b95c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d67f323c-d7dd-4fb7-9273-81c2d697b95c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d92cd158-bd33-431a-8d70-0aa1b8faeb6a' class='xr-var-data-in' type='checkbox'><label for='data-d92cd158-bd33-431a-8d70-0aa1b8faeb6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
+              "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-390d0180-57eb-4119-b0c0-5b41d0402e28' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-390d0180-57eb-4119-b0c0-5b41d0402e28' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f61bff6-c013-498b-970d-d4673831eee5' class='xr-var-data-in' type='checkbox'><label for='data-5f61bff6-c013-498b-970d-d4673831eee5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range b5</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
               "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
-              "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-d337e183-6bf7-4e58-8ac9-62bd7673ccd6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d337e183-6bf7-4e58-8ac9-62bd7673ccd6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e34b5df1-f8f0-4a52-a78f-dd64a8c6064d' class='xr-var-data-in' type='checkbox'><label for='data-e34b5df1-f8f0-4a52-a78f-dd64a8c6064d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;</div><input id='attrs-0bd4fdac-1f06-49bd-a7bd-b1dfe7a0c17c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0bd4fdac-1f06-49bd-a7bd-b1dfe7a0c17c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-209efe02-47d0-4c33-b6e5-928fc97d8ba2' class='xr-var-data-in' type='checkbox'><label for='data-209efe02-47d0-4c33-b6e5-928fc97d8ba2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-39599054-9ed5-45da-b9c2-2319c4299e3a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39599054-9ed5-45da-b9c2-2319c4299e3a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6fc3ca8-a600-4562-969f-5c77b4104e89' class='xr-var-data-in' type='checkbox'><label for='data-a6fc3ca8-a600-4562-969f-5c77b4104e89' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-9ca1843a-3745-40cd-9a13-339c4a662068' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ca1843a-3745-40cd-9a13-339c4a662068' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ad95dab-9fe5-4bcf-8b8f-7cafa3d6cb62' class='xr-var-data-in' type='checkbox'><label for='data-1ad95dab-9fe5-4bcf-8b8f-7cafa3d6cb62' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-b983bce2-445c-4f3d-b8b3-215e7d526756' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b983bce2-445c-4f3d-b8b3-215e7d526756' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59be2b5c-034e-4b53-b036-f1b55d7f596b' class='xr-var-data-in' type='checkbox'><label for='data-59be2b5c-034e-4b53-b036-f1b55d7f596b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-e8503a65-310a-419a-80ea-9e4ff73ffdaa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8503a65-310a-419a-80ea-9e4ff73ffdaa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58ac4d63-9aa7-4f3f-8532-f30fbcee76f9' class='xr-var-data-in' type='checkbox'><label for='data-58ac4d63-9aa7-4f3f-8532-f30fbcee76f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Quaternion Vector Components</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-71113dee-e577-4768-a4ed-6e5b3d960fd4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-71113dee-e577-4768-a4ed-6e5b3d960fd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7795347a-aece-4c82-8f03-8c78f1e2373c' class='xr-var-data-in' type='checkbox'><label for='data-7795347a-aece-4c82-8f03-8c78f1e2373c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-e0a53bfb-e170-4057-9210-59d223ea2ce5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e0a53bfb-e170-4057-9210-59d223ea2ce5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69ac815c-6eb9-4a62-bfac-61cb466fc32f' class='xr-var-data-in' type='checkbox'><label for='data-69ac815c-6eb9-4a62-bfac-61cb466fc32f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-caafa3b9-e18d-4be9-9e0b-bf7328f40652' class='xr-section-summary-in' type='checkbox'  ><label for='section-caafa3b9-e18d-4be9-9e0b-bf7328f40652' class='xr-section-summary' >Data variables: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-1ff41122-0a03-4e45-9e58-c6de91bf0a07' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ff41122-0a03-4e45-9e58-c6de91bf0a07' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f03ef4b5-20c4-4a04-aa33-304a03d349c3' class='xr-var-data-in' type='checkbox'><label for='data-f03ef4b5-20c4-4a04-aa33-304a03d349c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.9, 1501.9, 1501.9, ..., 1498.4, 1498.3, 1498.3],\n",
-              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.55 14.55 14.55 ... 13.47 13.47</div><input id='attrs-ef92540a-208d-459e-b712-fcff908224a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef92540a-208d-459e-b712-fcff908224a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64c0628a-32f0-42e7-8c57-f5c973f25a80' class='xr-var-data-in' type='checkbox'><label for='data-64c0628a-32f0-42e7-8c57-f5c973f25a80' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.55, 14.55, 14.55, ..., 13.47, 13.47, 13.47],\n",
-              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.713 9.718 9.718 ... 9.594 9.596</div><input id='attrs-7399a93b-fc47-45fc-9873-1d6e168f20af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7399a93b-fc47-45fc-9873-1d6e168f20af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-816ce894-63f6-4355-8b1c-d87c7ad56e48' class='xr-var-data-in' type='checkbox'><label for='data-816ce894-63f6-4355-8b1c-d87c7ad56e48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.713, 9.718, 9.718, ..., 9.596, 9.594, 9.596],\n",
-              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.5 72.7 72.6 ... -197.2 -195.7</div><input id='attrs-46f7f794-acba-4a89-9ce8-f756fc524b25' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46f7f794-acba-4a89-9ce8-f756fc524b25' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a519738-2ec4-483c-adf7-ae38fd4ca1cc' class='xr-var-data-in' type='checkbox'><label for='data-0a519738-2ec4-483c-adf7-ae38fd4ca1cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.5,   72.7,   72.6, ...,   72.3,   72.8,   72.4],\n",
+              "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-7f44c1f4-69b3-4068-9911-0419633c6f89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f44c1f4-69b3-4068-9911-0419633c6f89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f6dd975-0fde-4e31-9eb0-bf06af4dc611' class='xr-var-data-in' type='checkbox'><label for='data-8f6dd975-0fde-4e31-9eb0-bf06af4dc611' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;</div><input id='attrs-94007066-9746-4038-8627-4e4cbdeebe51' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94007066-9746-4038-8627-4e4cbdeebe51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a776caf-27ad-490d-9198-a303fe3db364' class='xr-var-data-in' type='checkbox'><label for='data-6a776caf-27ad-490d-9198-a303fe3db364' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-e523f6b1-bdc3-4fbe-87ee-36a3c64207a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e523f6b1-bdc3-4fbe-87ee-36a3c64207a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d72a7f1b-9e73-4cda-884f-9df8be1c801b' class='xr-var-data-in' type='checkbox'><label for='data-d72a7f1b-9e73-4cda-884f-9df8be1c801b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-40c67b12-a0b6-47ed-afdc-dbec63068d92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-40c67b12-a0b6-47ed-afdc-dbec63068d92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-007855ee-909e-4285-9c39-c36252088294' class='xr-var-data-in' type='checkbox'><label for='data-007855ee-909e-4285-9c39-c36252088294' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-a13fb84b-25d1-48ff-838d-4c490f163ac5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a13fb84b-25d1-48ff-838d-4c490f163ac5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8e30837-ea9d-4cdf-86a0-be81d160c31b' class='xr-var-data-in' type='checkbox'><label for='data-b8e30837-ea9d-4cdf-86a0-be81d160c31b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-b065e21f-114d-46c5-b868-fe13351035e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b065e21f-114d-46c5-b868-fe13351035e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33f36f6d-3af7-4fc4-b563-86f1121a7203' class='xr-var-data-in' type='checkbox'><label for='data-33f36f6d-3af7-4fc4-b563-86f1121a7203' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Quaternion Vector Components</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-977e242d-bfc2-4800-9149-e7762c892688' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-977e242d-bfc2-4800-9149-e7762c892688' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a82d0ad-2e37-4d7c-adfe-d3b0cba5aa75' class='xr-var-data-in' type='checkbox'><label for='data-8a82d0ad-2e37-4d7c-adfe-d3b0cba5aa75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-c996444d-d6fd-4594-9a5f-9717e2605adb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c996444d-d6fd-4594-9a5f-9717e2605adb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ae7b00f-61dc-4a25-aaea-da2285f28319' class='xr-var-data-in' type='checkbox'><label for='data-5ae7b00f-61dc-4a25-aaea-da2285f28319' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aba501e5-2078-4cac-811c-1a57021b8eed' class='xr-section-summary-in' type='checkbox'  ><label for='section-aba501e5-2078-4cac-811c-1a57021b8eed' class='xr-section-summary' >Data variables: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-cd161dc4-2187-41ac-9b00-be6b10bc8bbf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd161dc4-2187-41ac-9b00-be6b10bc8bbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f2afe60-12d6-49fd-b1dd-14df2c4dab76' class='xr-var-data-in' type='checkbox'><label for='data-0f2afe60-12d6-49fd-b1dd-14df2c4dab76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.9, 1501.9, 1501.9, ..., 1498.4, 1498.3, 1498.3],\n",
+              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.55 14.55 14.55 ... 13.47 13.47</div><input id='attrs-c884fa59-ec0b-4529-8400-537d38bd77c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c884fa59-ec0b-4529-8400-537d38bd77c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd474941-9a8d-4e30-b7d3-7f958b6dc3a2' class='xr-var-data-in' type='checkbox'><label for='data-dd474941-9a8d-4e30-b7d3-7f958b6dc3a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.55, 14.55, 14.55, ..., 13.47, 13.47, 13.47],\n",
+              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.713 9.718 9.718 ... 9.594 9.596</div><input id='attrs-227176fc-19c4-40d5-8f74-df756d306f3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-227176fc-19c4-40d5-8f74-df756d306f3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3398794a-de4e-4e9b-bd3d-dee74335344a' class='xr-var-data-in' type='checkbox'><label for='data-3398794a-de4e-4e9b-bd3d-dee74335344a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.713, 9.718, 9.718, ..., 9.596, 9.594, 9.596],\n",
+              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.5 72.7 72.6 ... -197.2 -195.7</div><input id='attrs-c135a21c-5db2-487b-ad1f-1faff443d5db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c135a21c-5db2-487b-ad1f-1faff443d5db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c21e291-655d-4ff6-be10-951b9c9bc7a9' class='xr-var-data-in' type='checkbox'><label for='data-7c21e291-655d-4ff6-be10-951b9c9bc7a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.5,   72.7,   72.6, ...,   72.3,   72.8,   72.4],\n",
               "       [   9.3,    9.4,    8.9, ...,    5.9,    6.3,    6.4],\n",
               "       [-198. , -196.3, -198.1, ..., -197.4, -197.2, -195.7]],\n",
-              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.00479 -0.01437 ... 9.685 9.729</div><input id='attrs-183da95b-9157-46e7-83e9-b9f00a9b8f43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-183da95b-9157-46e7-83e9-b9f00a9b8f43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a927da27-ceac-46bd-9ccb-96a0ad212717' class='xr-var-data-in' type='checkbox'><label for='data-a927da27-ceac-46bd-9ccb-96a0ad212717' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-4.7900393e-03, -1.4370117e-02, -2.3950195e-02, ...,\n",
+              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.00479 -0.01437 ... 9.685 9.729</div><input id='attrs-b957bb42-48dc-425f-b414-290a166595ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b957bb42-48dc-425f-b414-290a166595ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5cf8d694-3813-4297-bae1-ed46db2b4ea8' class='xr-var-data-in' type='checkbox'><label for='data-5cf8d694-3813-4297-bae1-ed46db2b4ea8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-4.7900393e-03, -1.4370117e-02, -2.3950195e-02, ...,\n",
               "        -1.4370117e-02, -4.7900393e-03, -2.3950195e-02],\n",
               "       [-1.2933105e+00, -1.2549902e+00, -1.2645704e+00, ...,\n",
               "        -1.1017090e+00, -1.0873389e+00, -1.0969189e+00],\n",
               "       [ 9.7285690e+00,  9.7141991e+00,  9.7237797e+00, ...,\n",
               "         9.6710892e+00,  9.6854591e+00,  9.7285690e+00]],\n",
-              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.6 16.6 16.6 ... 16.4 16.4 15.2</div><input id='attrs-7cda3505-8b84-4725-9fef-f07bfbbc5ef0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7cda3505-8b84-4725-9fef-f07bfbbc5ef0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-473323e7-3b54-429d-886d-ea84227ffbd6' class='xr-var-data-in' type='checkbox'><label for='data-473323e7-3b54-429d-886d-ea84227ffbd6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.6, 16.6, 16.6, ..., 16.4, 16.4, 15.2],\n",
-              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-674e4a82-f528-4c4b-86b9-b0b3f39d9e8d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-674e4a82-f528-4c4b-86b9-b0b3f39d9e8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb878b99-2eaa-4918-84db-0162d2d02d9e' class='xr-var-data-in' type='checkbox'><label for='data-bb878b99-2eaa-4918-84db-0162d2d02d9e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20. , 20. , 20. , ..., 19.5, 19.5, 19.5],\n",
-              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-e78211e3-0ff7-4d94-991b-6dd58686c1f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e78211e3-0ff7-4d94-991b-6dd58686c1f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f38dc2c8-8599-4407-80d2-5f1c6a73fe00' class='xr-var-data-in' type='checkbox'><label for='data-f38dc2c8-8599-4407-80d2-5f1c6a73fe00' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-dcd7994a-e914-4f22-ac0f-2a1335906909' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dcd7994a-e914-4f22-ac0f-2a1335906909' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-174005cc-1f9d-4de7-a72b-7ded11d548f0' class='xr-var-data-in' type='checkbox'><label for='data-174005cc-1f9d-4de7-a72b-7ded11d548f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
-              "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-4fcc2627-b4a9-4eb9-8c15-86a869465daa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4fcc2627-b4a9-4eb9-8c15-86a869465daa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3d88ea9-e65d-4a58-9933-a7a6961d6087' class='xr-var-data-in' type='checkbox'><label for='data-c3d88ea9-e65d-4a58-9933-a7a6961d6087' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
-              "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.015 -0.048 ... -0.015 -0.012</div><input id='attrs-a54ee94f-e180-44f6-8b7a-f83765c77547' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a54ee94f-e180-44f6-8b7a-f83765c77547' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5da06787-6cf3-4c82-9495-184ccfaf6cbc' class='xr-var-data-in' type='checkbox'><label for='data-5da06787-6cf3-4c82-9495-184ccfaf6cbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.015, -0.048,  0.008, ..., -0.176, -0.071, -0.027],\n",
+              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.6 16.6 16.6 ... 16.4 16.4 15.2</div><input id='attrs-63d7dc22-a222-4368-8d64-edd3a7fb6ce9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63d7dc22-a222-4368-8d64-edd3a7fb6ce9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5fcd37e5-2bb0-44a4-87ab-07894fc1d27e' class='xr-var-data-in' type='checkbox'><label for='data-5fcd37e5-2bb0-44a4-87ab-07894fc1d27e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.6, 16.6, 16.6, ..., 16.4, 16.4, 15.2],\n",
+              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-7230bc27-e7dd-4a81-bc58-ec377dfba2f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7230bc27-e7dd-4a81-bc58-ec377dfba2f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-956e2170-d3fa-4b3f-91f8-b755c892f600' class='xr-var-data-in' type='checkbox'><label for='data-956e2170-d3fa-4b3f-91f8-b755c892f600' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20. , 20. , 20. , ..., 19.5, 19.5, 19.5],\n",
+              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-2b195a2d-ca32-41c9-bbc7-a257d1a55275' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b195a2d-ca32-41c9-bbc7-a257d1a55275' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43653780-016c-44e0-bb3f-c525c0c403cd' class='xr-var-data-in' type='checkbox'><label for='data-43653780-016c-44e0-bb3f-c525c0c403cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-0309ea33-451b-4d67-9839-d11061c65111' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0309ea33-451b-4d67-9839-d11061c65111' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8613093-89dc-48c6-b2a9-ee53b27f95b1' class='xr-var-data-in' type='checkbox'><label for='data-c8613093-89dc-48c6-b2a9-ee53b27f95b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
+              "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-608fbc04-d386-4fa1-8e43-de8db4cc6cb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-608fbc04-d386-4fa1-8e43-de8db4cc6cb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d316239-ef9e-4482-83b0-e7264fc944a8' class='xr-var-data-in' type='checkbox'><label for='data-8d316239-ef9e-4482-83b0-e7264fc944a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
+              "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.015 -0.048 ... -0.015 -0.012</div><input id='attrs-98644f44-ab34-4c0b-a749-8d40015b89b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98644f44-ab34-4c0b-a749-8d40015b89b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-199e8e9d-f69f-4bff-9f1d-881ed213794c' class='xr-var-data-in' type='checkbox'><label for='data-199e8e9d-f69f-4bff-9f1d-881ed213794c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.015, -0.048,  0.008, ..., -0.176, -0.071, -0.027],\n",
               "        [-0.093, -0.124, -0.031, ..., -0.175, -0.16 , -0.03 ],\n",
               "        [-0.163, -0.135, -0.105, ..., -0.129, -0.089, -0.116],\n",
               "        ...,\n",
@@ -577,7 +578,7 @@
               "        [-0.044,  0.015, -0.04 , ..., -0.015,  0.006,  0.012],\n",
               "        [-0.013,  0.014, -0.032, ...,  0.01 ,  0.   , -0.015],\n",
               "        [ 0.007,  0.016, -0.027, ..., -0.002, -0.015, -0.012]]],\n",
-              "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>81.0 80.0 80.5 ... 43.5 42.5 42.0</div><input id='attrs-277205bc-7d7e-494c-85b5-bd09c658f6d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-277205bc-7d7e-494c-85b5-bd09c658f6d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf0096df-72b6-46db-a3d7-03c26c74f57c' class='xr-var-data-in' type='checkbox'><label for='data-cf0096df-72b6-46db-a3d7-03c26c74f57c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[81. , 80. , 80.5, ..., 81.5, 81.5, 81.5],\n",
+              "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>81.0 80.0 80.5 ... 43.5 42.5 42.0</div><input id='attrs-c32c85ac-0276-4d5f-8f1d-cbd90cec0e3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c32c85ac-0276-4d5f-8f1d-cbd90cec0e3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9723746f-29e5-49fd-85c4-09b3642f16b6' class='xr-var-data-in' type='checkbox'><label for='data-9723746f-29e5-49fd-85c4-09b3642f16b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[81. , 80. , 80.5, ..., 81.5, 81.5, 81.5],\n",
               "        [75. , 74.5, 75. , ..., 79. , 77. , 77.5],\n",
               "        [73.5, 72. , 72. , ..., 75. , 74.5, 75. ],\n",
               "        ...,\n",
@@ -608,7 +609,7 @@
               "        [51.5, 51. , 51. , ..., 46. , 46. , 45. ],\n",
               "        [51. , 50. , 51. , ..., 45. , 44. , 43.5],\n",
               "        [50.5, 49.5, 50. , ..., 43.5, 42.5, 42. ]]],\n",
-              "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>100 91 91 97 99 ... 96 98 98 98 96</div><input id='attrs-98cf1824-4169-40fc-a1dc-56e164553766' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98cf1824-4169-40fc-a1dc-56e164553766' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39ca0db9-9fa6-4a96-bd45-3754d11d1eb1' class='xr-var-data-in' type='checkbox'><label for='data-39ca0db9-9fa6-4a96-bd45-3754d11d1eb1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[100,  91,  91, ...,  89,  90,  96],\n",
+              "      shape=(4, 28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>100 91 91 97 99 ... 96 98 98 98 96</div><input id='attrs-6cf257b5-82cd-4e7a-a64f-b3c347885ec8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6cf257b5-82cd-4e7a-a64f-b3c347885ec8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81ea19f2-bf29-4aa6-a618-9941b95035be' class='xr-var-data-in' type='checkbox'><label for='data-81ea19f2-bf29-4aa6-a618-9941b95035be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[100,  91,  91, ...,  89,  90,  96],\n",
               "        [ 74,  92,  96, ..., 100,  97, 100],\n",
               "        [100, 100,  99, ...,  99, 100, 100],\n",
               "        ...,\n",
@@ -639,7 +640,7 @@
               "        [100,  99,  96, ...,  98, 100, 100],\n",
               "        [100, 100, 100, ...,  94,  93,  95],\n",
               "        [100,  98,  99, ...,  98,  98,  96]]],\n",
-              "      shape=(4, 28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2164 ... 0.9937 0.9937</div><input id='attrs-e1503753-dd4d-4bb8-af92-ef879b7242fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e1503753-dd4d-4bb8-af92-ef879b7242fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecbe7724-d44e-4b94-b891-4ea51bf7fd55' class='xr-var-data-in' type='checkbox'><label for='data-ecbe7724-d44e-4b94-b891-4ea51bf7fd55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16688156e-01, -2.16397047e-01, -2.16593146e-01, ...,\n",
+              "      shape=(4, 28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2164 ... 0.9937 0.9937</div><input id='attrs-81e10eb9-2350-4e6c-8f48-13d67572014c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81e10eb9-2350-4e6c-8f48-13d67572014c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d233e24a-daa2-474f-ad1a-512b7641dc17' class='xr-var-data-in' type='checkbox'><label for='data-d233e24a-daa2-474f-ad1a-512b7641dc17' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16688156e-01, -2.16397047e-01, -2.16593146e-01, ...,\n",
               "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
               "        [ 9.76196468e-01,  9.76219118e-01,  9.76202846e-01, ...,\n",
               "          9.76315439e-01,  9.76210594e-01,  9.76245522e-01],\n",
@@ -659,52 +660,52 @@
               "         -2.31788009e-02, -2.33813375e-02, -2.34001204e-02],\n",
               "        [ 9.91607308e-01,  9.91618454e-01,  9.91612315e-01, ...,\n",
               "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
-              "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.00293</div><input id='attrs-bb6c5dd6-b6f9-45e2-a972-7bc38b3deb3b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb6c5dd6-b6f9-45e2-a972-7bc38b3deb3b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b06f35a-d6ba-4fbf-b789-cd8d63f2ead9' class='xr-var-data-in' type='checkbox'><label for='data-1b06f35a-d6ba-4fbf-b789-cd8d63f2ead9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00390625,\n",
+              "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.00293</div><input id='attrs-17f5fa72-a0bb-4b54-b694-f4903158ec8e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17f5fa72-a0bb-4b54-b694-f4903158ec8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3859ed97-6d64-4f02-b4cf-bfed1a1a9664' class='xr-var-data-in' type='checkbox'><label for='data-3859ed97-6d64-4f02-b4cf-bfed1a1a9664' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00390625,\n",
               "        -0.00292969, -0.00195312],\n",
               "       [ 0.00097656,  0.        ,  0.        , ...,  0.        ,\n",
               "         0.00097656,  0.00097656],\n",
               "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
-              "        -0.00195312, -0.00292969]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-d611b9eb-b7af-44da-82a3-454958c924f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d611b9eb-b7af-44da-82a3-454958c924f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0fa9809-826b-47ff-991f-1439c5b8b446' class='xr-var-data-in' type='checkbox'><label for='data-c0fa9809-826b-47ff-991f-1439c5b8b446' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6244812 , ...,  0.625     ,\n",
+              "        -0.00195312, -0.00292969]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-fd7a2f23-54b3-48d5-bf91-aee8beac0a22' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd7a2f23-54b3-48d5-bf91-aee8beac0a22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e6ffbf6-25c3-484d-b5e7-aef6638ab46e' class='xr-var-data-in' type='checkbox'><label for='data-2e6ffbf6-25c3-484d-b5e7-aef6638ab46e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6244812 , ...,  0.625     ,\n",
               "         0.6247864 ,  0.62490845],\n",
               "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
               "        -0.03564453, -0.03561401],\n",
               "       [-0.05014038, -0.05010986, -0.05014038, ..., -0.04354858,\n",
               "        -0.04360962, -0.04360962],\n",
               "       [ 0.77835083,  0.7782593 ,  0.7783203 , ...,  0.77856445,\n",
-              "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-6f4513ae-72ec-46ee-892f-94d1cc698516' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f4513ae-72ec-46ee-892f-94d1cc698516' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40c5de0a-222f-4935-b1b9-db2e3745c456' class='xr-var-data-in' type='checkbox'><label for='data-40c5de0a-222f-4935-b1b9-db2e3745c456' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.8, 12.8, 12.8, ..., 12. , 12. , 12. ],\n",
-              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>243 243 243 244 ... 246 246 246 246</div><input id='attrs-828857f0-560a-4847-8fae-97a9870c53e9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-828857f0-560a-4847-8fae-97a9870c53e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c3c11e8-de5e-4893-8301-92a783497502' class='xr-var-data-in' type='checkbox'><label for='data-5c3c11e8-de5e-4893-8301-92a783497502' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([243, 243, 243, ..., 246, 246, 246], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.9 72.8 72.4 ... -198.0 -195.7</div><input id='attrs-bf3c7d14-e904-4b67-ab3c-802a522946c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf3c7d14-e904-4b67-ab3c-802a522946c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7963343c-65d0-4f3f-a362-91c25d6ba372' class='xr-var-data-in' type='checkbox'><label for='data-7963343c-65d0-4f3f-a362-91c25d6ba372' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.9,   72.8,   72.4, ...,   73. ,   73. ,   72.7],\n",
+              "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-4ca0ab12-bd84-4097-b895-e57e3fc5de6b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ca0ab12-bd84-4097-b895-e57e3fc5de6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c2d82bb-5a17-4f7e-b60c-be48ad57a5e7' class='xr-var-data-in' type='checkbox'><label for='data-0c2d82bb-5a17-4f7e-b60c-be48ad57a5e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.8, 12.8, 12.8, ..., 12. , 12. , 12. ],\n",
+              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>243 243 243 244 ... 246 246 246 246</div><input id='attrs-baf3a83f-5067-483c-b593-c804797724f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-baf3a83f-5067-483c-b593-c804797724f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c853c46c-dd38-401f-91d9-dd5a664ea07a' class='xr-var-data-in' type='checkbox'><label for='data-c853c46c-dd38-401f-91d9-dd5a664ea07a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([243, 243, 243, ..., 246, 246, 246], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.9 72.8 72.4 ... -198.0 -195.7</div><input id='attrs-a3d36048-7a04-447f-bca2-3dc7664d54d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3d36048-7a04-447f-bca2-3dc7664d54d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c06619e-5cea-454c-a150-7d12c1a7adc2' class='xr-var-data-in' type='checkbox'><label for='data-5c06619e-5cea-454c-a150-7d12c1a7adc2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.9,   72.8,   72.4, ...,   73. ,   73. ,   72.7],\n",
               "       [   9.5,    9.5,    9.8, ...,    6. ,    6.4,    5.9],\n",
               "       [-197.1, -197.2, -197.7, ..., -197.4, -198. , -195.7]],\n",
-              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.01437 0.0 ... 9.709 9.724</div><input id='attrs-946bb2f4-847b-49e2-9f8a-692d51c7f1dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-946bb2f4-847b-49e2-9f8a-692d51c7f1dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a84be801-4ea5-4cea-b873-dd7e8a46d899' class='xr-var-data-in' type='checkbox'><label for='data-a84be801-4ea5-4cea-b873-dd7e8a46d899' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.4370117e-02,  0.0000000e+00, -1.4370117e-02, ...,\n",
+              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.01437 0.0 ... 9.709 9.724</div><input id='attrs-37b68fe2-0af0-480d-9d75-c671620f8b77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-37b68fe2-0af0-480d-9d75-c671620f8b77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02b2768b-9263-4783-ba00-4ba49ef9dae1' class='xr-var-data-in' type='checkbox'><label for='data-02b2768b-9263-4783-ba00-4ba49ef9dae1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.4370117e-02,  0.0000000e+00, -1.4370117e-02, ...,\n",
               "        -4.7900393e-03, -1.9160157e-02, -1.4370117e-02],\n",
               "       [-1.2693603e+00, -1.2885205e+00, -1.2837305e+00, ...,\n",
               "        -1.0825489e+00, -1.1017090e+00, -1.1064991e+00],\n",
               "       [ 9.7189894e+00,  9.7046194e+00,  9.7094088e+00, ...,\n",
               "         9.7141991e+00,  9.7094088e+00,  9.7237797e+00]],\n",
-              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-3c3930ab-6b97-4863-bf09-bb7f81c310fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c3930ab-6b97-4863-bf09-bb7f81c310fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca6930c4-b057-4d3d-a37b-5fa727c66eb6' class='xr-var-data-in' type='checkbox'><label for='data-ca6930c4-b057-4d3d-a37b-5fa727c66eb6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-1542f06f-2867-4ef6-aad7-c2c37f6f60a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1542f06f-2867-4ef6-aad7-c2c37f6f60a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1de580ae-abe2-49c1-b53b-d5bc0ae85126' class='xr-var-data-in' type='checkbox'><label for='data-1de580ae-abe2-49c1-b53b-d5bc0ae85126' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
-              "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-a9377d49-d4c3-4cbe-8a89-afce2dda7132' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a9377d49-d4c3-4cbe-8a89-afce2dda7132' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06b9d344-4506-400f-aa06-f747acffc709' class='xr-var-data-in' type='checkbox'><label for='data-06b9d344-4506-400f-aa06-f747acffc709' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
-              "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.003 0.021 0.018 ... -0.048 0.09</div><input id='attrs-5ab42a7d-2601-4861-b109-c16adb8d0917' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ab42a7d-2601-4861-b109-c16adb8d0917' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17f3ee0f-9dba-4c53-adee-d93c2d890eda' class='xr-var-data-in' type='checkbox'><label for='data-17f3ee0f-9dba-4c53-adee-d93c2d890eda' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.003,  0.021,  0.018, ...,  0.   , -0.044,  0.009],\n",
+              "      shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-e627ec10-d8cd-429d-b603-1d9a35e02e36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e627ec10-d8cd-429d-b603-1d9a35e02e36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-afdfad8b-d9e3-41af-9619-c2178b544fdb' class='xr-var-data-in' type='checkbox'><label for='data-afdfad8b-d9e3-41af-9619-c2178b544fdb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-437c65d8-caa7-4bc7-85ac-2e54a22e1402' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-437c65d8-caa7-4bc7-85ac-2e54a22e1402' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c857bb51-3bb7-4320-8d3a-493531d3d019' class='xr-var-data-in' type='checkbox'><label for='data-c857bb51-3bb7-4320-8d3a-493531d3d019' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
+              "       1053557762], shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-5c3f5314-b091-4990-8617-32819e546950' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c3f5314-b091-4990-8617-32819e546950' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0253f787-a52b-4f5c-b911-d1e23b9a3c36' class='xr-var-data-in' type='checkbox'><label for='data-0253f787-a52b-4f5c-b911-d1e23b9a3c36' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000],\n",
+              "      shape=(55000,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.003 0.021 0.018 ... -0.048 0.09</div><input id='attrs-8ba34c98-f026-466e-9c04-ca734c6dfd9c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ba34c98-f026-466e-9c04-ca734c6dfd9c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-505f74df-75de-4ab9-9b6f-e2c4b1c4a275' class='xr-var-data-in' type='checkbox'><label for='data-505f74df-75de-4ab9-9b6f-e2c4b1c4a275' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.003,  0.021,  0.018, ...,  0.   , -0.044,  0.009],\n",
               "       [ 0.057,  0.034,  0.017, ...,  0.01 ,  0.001, -0.002],\n",
               "       [ 0.039,  0.022,  0.02 , ...,  0.039, -0.008,  0.018],\n",
               "       ...,\n",
               "       [-0.036, -0.013,  0.058, ...,  0.058, -0.013,  0.028],\n",
               "       [-0.043, -0.009,  0.028, ...,  0.092, -0.021,  0.019],\n",
               "       [-0.073,  0.003,  0.   , ...,  0.049, -0.048,  0.09 ]],\n",
-              "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.5 80.5 80.0 ... 46.5 46.0 47.5</div><input id='attrs-acd08ed7-1663-4619-b563-42807a80e457' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acd08ed7-1663-4619-b563-42807a80e457' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e316ab20-5cb2-4df9-bfd0-ec434344eca4' class='xr-var-data-in' type='checkbox'><label for='data-e316ab20-5cb2-4df9-bfd0-ec434344eca4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[80.5, 80.5, 80. , ..., 82. , 81.5, 81. ],\n",
+              "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.5 80.5 80.0 ... 46.5 46.0 47.5</div><input id='attrs-e56774a7-c9e7-476f-97ad-72b4a06d9caf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e56774a7-c9e7-476f-97ad-72b4a06d9caf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5006da4b-9fac-45f3-93cf-093f338a4b03' class='xr-var-data-in' type='checkbox'><label for='data-5006da4b-9fac-45f3-93cf-093f338a4b03' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[80.5, 80.5, 80. , ..., 82. , 81.5, 81. ],\n",
               "       [75.5, 76.5, 76. , ..., 78.5, 78. , 77.5],\n",
               "       [72.5, 73.5, 73.5, ..., 75. , 76.5, 75.5],\n",
               "       ...,\n",
               "       [57.5, 57.5, 57. , ..., 49. , 49. , 48.5],\n",
               "       [56.5, 57. , 56. , ..., 47.5, 48. , 48. ],\n",
               "       [55.5, 55.5, 55. , ..., 46.5, 46. , 47.5]],\n",
-              "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>98 100 92 93 98 ... 100 99 94 100</div><input id='attrs-68eb1d8f-4197-4f91-8f66-f237585a132a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68eb1d8f-4197-4f91-8f66-f237585a132a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-160185be-6942-4cbe-a6b9-5ff02d66e55b' class='xr-var-data-in' type='checkbox'><label for='data-160185be-6942-4cbe-a6b9-5ff02d66e55b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[ 98, 100,  92, ...,  88,  90,  91],\n",
+              "      shape=(28, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>98 100 92 93 98 ... 100 99 94 100</div><input id='attrs-404c4618-f62e-4504-b6c3-1859e03b4f70' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-404c4618-f62e-4504-b6c3-1859e03b4f70' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfe891f4-9f91-4567-8f93-109fc59a7b74' class='xr-var-data-in' type='checkbox'><label for='data-bfe891f4-9f91-4567-8f93-109fc59a7b74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[ 98, 100,  92, ...,  88,  90,  91],\n",
               "       [ 97,  94,  98, ...,  97,  95,  97],\n",
               "       [100, 100, 100, ...,  93, 100,  96],\n",
               "       ...,\n",
               "       [100, 100, 100, ..., 100, 100,  98],\n",
               "       [100, 100, 100, ...,  99, 100,  98],\n",
               "       [100, 100, 100, ...,  99,  94, 100]],\n",
-              "      shape=(28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2165 ... 0.9937 0.9937</div><input id='attrs-38f987e4-4356-46e7-9bff-8731db8e8f2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-38f987e4-4356-46e7-9bff-8731db8e8f2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d50afe89-53f3-42b7-af50-55aabb08d039' class='xr-var-data-in' type='checkbox'><label for='data-d50afe89-53f3-42b7-af50-55aabb08d039' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16694236e-01, -2.16498137e-01, -2.16593146e-01, ...,\n",
+              "      shape=(28, 55000), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2165 ... 0.9937 0.9937</div><input id='attrs-1a470afd-e700-413c-b637-a244630e9ef8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a470afd-e700-413c-b637-a244630e9ef8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19fe9666-50f5-495e-8450-dc6b3f76616f' class='xr-var-data-in' type='checkbox'><label for='data-19fe9666-50f5-495e-8450-dc6b3f76616f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16694236e-01, -2.16498137e-01, -2.16593146e-01, ...,\n",
               "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
               "        [-9.67967808e-01, -9.68039632e-01, -9.68030274e-01, ...,\n",
               "         -9.70095694e-01, -9.69992876e-01, -9.70033050e-01],\n",
@@ -724,25 +725,25 @@
               "         -1.12442717e-01, -1.12462208e-01, -1.12422116e-01],\n",
               "        [ 9.91601229e-01,  9.91612315e-01,  9.91612315e-01, ...,\n",
               "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
-              "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.001953</div><input id='attrs-ae315607-cef3-4aaf-84d1-0876de12946a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae315607-cef3-4aaf-84d1-0876de12946a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdf5b386-e221-4f52-9e01-47befdc4dee1' class='xr-var-data-in' type='checkbox'><label for='data-fdf5b386-e221-4f52-9e01-47befdc4dee1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00097656,\n",
+              "      shape=(3, 3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.001953</div><input id='attrs-a74a7f13-0d52-4f16-82b1-ee206ae6d5bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a74a7f13-0d52-4f16-82b1-ee206ae6d5bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3f20d95-68d7-474a-8595-d5c5021028ea' class='xr-var-data-in' type='checkbox'><label for='data-b3f20d95-68d7-474a-8595-d5c5021028ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00097656,\n",
               "        -0.00195312, -0.00390625],\n",
               "       [ 0.        ,  0.        ,  0.00097656, ...,  0.00097656,\n",
               "         0.        ,  0.00097656],\n",
               "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
-              "        -0.00292969, -0.00195312]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-875ee1e5-47c6-4b02-b472-4175b7f4be87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-875ee1e5-47c6-4b02-b472-4175b7f4be87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3aed19f4-7103-4aa3-898c-26ba6cba838c' class='xr-var-data-in' type='checkbox'><label for='data-3aed19f4-7103-4aa3-898c-26ba6cba838c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6245117 , ...,  0.625     ,\n",
+              "        -0.00292969, -0.00195312]], shape=(3, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-26443951-1c72-4ee5-bfc4-bd88dbb72a68' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26443951-1c72-4ee5-bfc4-bd88dbb72a68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cd4a141-939b-4e48-927f-83fafb7cb2e4' class='xr-var-data-in' type='checkbox'><label for='data-7cd4a141-939b-4e48-927f-83fafb7cb2e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6245117 , ...,  0.625     ,\n",
               "         0.6247864 ,  0.62490845],\n",
               "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
               "        -0.03564453, -0.03561401],\n",
               "       [-0.0501709 , -0.05014038, -0.05014038, ..., -0.04354858,\n",
               "        -0.04360962, -0.04360962],\n",
               "       [ 0.77835083,  0.7782898 ,  0.7783203 , ...,  0.77856445,\n",
-              "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>65 65 65 65 65 ... 65 65 65 65 65</div><input id='attrs-3f9d4ba3-c1b4-47a4-a0fb-631e35298959' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f9d4ba3-c1b4-47a4-a0fb-631e35298959' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a46ee7f-0227-409b-8d72-e36ac1a5a64f' class='xr-var-data-in' type='checkbox'><label for='data-9a46ee7f-0227-409b-8d72-e36ac1a5a64f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65, 65, 65, ..., 65, 65, 65], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-7659606b-e0c0-4a3e-bc18-468c50df6b2c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7659606b-e0c0-4a3e-bc18-468c50df6b2c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38f98260-caf7-448d-a712-54ece9cd4846' class='xr-var-data-in' type='checkbox'><label for='data-38f98260-caf7-448d-a712-54ece9cd4846' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-f6fe8972-1dc7-470f-bc3b-360c6a6c6fe5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f6fe8972-1dc7-470f-bc3b-360c6a6c6fe5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eaedf31d-e0b9-440e-9786-84509474dbe6' class='xr-var-data-in' type='checkbox'><label for='data-eaedf31d-e0b9-440e-9786-84509474dbe6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-3a7ba2f6-caf9-4d89-bcee-d82a175fafea' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3a7ba2f6-caf9-4d89-bcee-d82a175fafea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ece9b1b-7a0a-49d6-baa6-4c2edea2fc78' class='xr-var-data-in' type='checkbox'><label for='data-6ece9b1b-7a0a-49d6-baa6-4c2edea2fc78' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 1 0 0 0 0 0 0 1</div><input id='attrs-6ba859bf-b58e-4a25-b954-8078fba21d2a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6ba859bf-b58e-4a25-b954-8078fba21d2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b91f3bf1-aad4-4288-8142-4946e7271f35' class='xr-var-data-in' type='checkbox'><label for='data-b91f3bf1-aad4-4288-8142-4946e7271f35' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 1], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-12.52 -12.51 ... -12.52 -12.5</div><input id='attrs-ee281545-54d1-482f-997d-a2bf800023d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee281545-54d1-482f-997d-a2bf800023d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad1aca52-6c9b-464a-86b0-6bc7f1cd6f41' class='xr-var-data-in' type='checkbox'><label for='data-ad1aca52-6c9b-464a-86b0-6bc7f1cd6f41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([-12.52    , -12.505001, -12.51    , ..., -12.490002, -12.52    ,\n",
-              "       -12.500001], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.065 -0.06 -0.06 ... -0.05 -0.05</div><input id='attrs-afd497d7-75be-45e6-969d-63d51ae43d6b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-afd497d7-75be-45e6-969d-63d51ae43d6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cad3d08f-a2eb-43f0-b323-1542d3e231ea' class='xr-var-data-in' type='checkbox'><label for='data-cad3d08f-a2eb-43f0-b323-1542d3e231ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.065, -0.06 , -0.06 , ..., -0.06 , -0.05 , -0.05 ],\n",
-              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.425 -7.42 -7.42 ... -6.45 -6.45</div><input id='attrs-b40b0456-4d12-49be-bf18-9990c6ba5287' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b40b0456-4d12-49be-bf18-9990c6ba5287' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-479207f2-58d9-44da-80ec-60d985c7461d' class='xr-var-data-in' type='checkbox'><label for='data-479207f2-58d9-44da-80ec-60d985c7461d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.4250007, -7.42     , -7.42     , ..., -6.45     , -6.45     ,\n",
-              "       -6.45     ], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.183 0.0 -1.183 ... 0.0 0.5518</div><input id='attrs-4af26767-d155-4c08-ba9d-b9cdb39f72fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4af26767-d155-4c08-ba9d-b9cdb39f72fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4c83551-5532-4483-9d8e-6dafb7c04249' class='xr-var-data-in' type='checkbox'><label for='data-a4c83551-5532-4483-9d8e-6dafb7c04249' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.1831,  0.    , -1.1831,  0.    ],\n",
+              "         0.77874756,  0.7786255 ]], shape=(4, 55000), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>65 65 65 65 65 ... 65 65 65 65 65</div><input id='attrs-7ec6af9a-2255-46c2-850c-93e145634ac2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ec6af9a-2255-46c2-850c-93e145634ac2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-61005fbb-7dfb-4d0b-9523-6eb3492ca550' class='xr-var-data-in' type='checkbox'><label for='data-61005fbb-7dfb-4d0b-9523-6eb3492ca550' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65, 65, 65, ..., 65, 65, 65], shape=(55000,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-4e977b39-1909-48dd-8c7e-e02ad7a96c22' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4e977b39-1909-48dd-8c7e-e02ad7a96c22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-baa95071-3866-471b-b363-0ef3d4385487' class='xr-var-data-in' type='checkbox'><label for='data-baa95071-3866-471b-b363-0ef3d4385487' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-93757c98-db60-44da-bdfb-1318145581a7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-93757c98-db60-44da-bdfb-1318145581a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d6e07b5-4397-4172-8c7b-25483bd9111e' class='xr-var-data-in' type='checkbox'><label for='data-2d6e07b5-4397-4172-8c7b-25483bd9111e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-318ea917-1899-4a34-abc4-5c37c5c15fc5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-318ea917-1899-4a34-abc4-5c37c5c15fc5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b729943f-bf76-445a-ba63-1bf020bd6fb8' class='xr-var-data-in' type='checkbox'><label for='data-b729943f-bf76-445a-ba63-1bf020bd6fb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 1 0 0 0 0 0 0 1</div><input id='attrs-e6c5b282-4fac-44ca-8c0f-2b06b9941da7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e6c5b282-4fac-44ca-8c0f-2b06b9941da7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45c11eaf-5ea8-491f-a07a-6202abbd36f5' class='xr-var-data-in' type='checkbox'><label for='data-45c11eaf-5ea8-491f-a07a-6202abbd36f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 1], shape=(55000,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-12.52 -12.51 ... -12.52 -12.5</div><input id='attrs-eba533fc-3add-4203-8fe9-58c745d4a428' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eba533fc-3add-4203-8fe9-58c745d4a428' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66aeb13a-c38a-492a-af64-001423f96b88' class='xr-var-data-in' type='checkbox'><label for='data-66aeb13a-c38a-492a-af64-001423f96b88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([-12.52    , -12.505001, -12.51    , ..., -12.490002, -12.52    ,\n",
+              "       -12.500001], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.065 -0.06 -0.06 ... -0.05 -0.05</div><input id='attrs-a4b40bd9-d7cb-4510-8ce3-3b2a91e29acc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a4b40bd9-d7cb-4510-8ce3-3b2a91e29acc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e4a129a-fc0f-42eb-9338-20dbed6475ad' class='xr-var-data-in' type='checkbox'><label for='data-9e4a129a-fc0f-42eb-9338-20dbed6475ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.065, -0.06 , -0.06 , ..., -0.06 , -0.05 , -0.05 ],\n",
+              "      shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.425 -7.42 -7.42 ... -6.45 -6.45</div><input id='attrs-f7999b95-d36b-45ad-b566-08589acee982' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7999b95-d36b-45ad-b566-08589acee982' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-042bdbd3-5f68-4ce3-8795-e9b64b6ae1c1' class='xr-var-data-in' type='checkbox'><label for='data-042bdbd3-5f68-4ce3-8795-e9b64b6ae1c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.4250007, -7.42     , -7.42     , ..., -6.45     , -6.45     ,\n",
+              "       -6.45     ], shape=(55000,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.183 0.0 -1.183 ... 0.0 0.5518</div><input id='attrs-36b40b6e-6419-46de-bbb3-b61ce161e810' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36b40b6e-6419-46de-bbb3-b61ce161e810' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-699e6c95-2bd9-4c71-8390-2bda2c0a5771' class='xr-var-data-in' type='checkbox'><label for='data-699e6c95-2bd9-4c71-8390-2bda2c0a5771' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.1831,  0.    , -1.1831,  0.    ],\n",
               "       [ 0.    , -1.1831,  0.    ,  1.1831],\n",
               "       [ 0.5518,  0.    ,  0.5518,  0.    ],\n",
-              "       [ 0.    ,  0.5518,  0.    ,  0.5518]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fe7b8cee-76fb-424c-bac6-1240e8c25e87' class='xr-section-summary-in' type='checkbox'  ><label for='section-fe7b8cee-76fb-424c-bac6-1240e8c25e87' class='xr-section-summary' >Indexes: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-f7b5f078-ca86-466e-90f1-ba08e1090bb7' class='xr-index-data-in' type='checkbox'/><label for='index-f7b5f078-ca86-466e-90f1-ba08e1090bb7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:20:00.500999927&#x27;,\n",
+              "       [ 0.    ,  0.5518,  0.    ,  0.5518]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-85c4917d-66c8-479f-b4e2-15d04b2bf964' class='xr-section-summary-in' type='checkbox'  ><label for='section-85c4917d-66c8-479f-b4e2-15d04b2bf964' class='xr-section-summary' >Indexes: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-2de81dd7-2cb8-44e4-904b-7daf8ca0d950' class='xr-index-data-in' type='checkbox'/><label for='index-2de81dd7-2cb8-44e4-904b-7daf8ca0d950' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:20:00.500999927&#x27;,\n",
               "               &#x27;2020-08-15 00:20:01.501100063&#x27;,\n",
               "               &#x27;2020-08-15 00:20:02.500999927&#x27;,\n",
               "               &#x27;2020-08-15 00:20:03.501100063&#x27;,\n",
@@ -763,7 +764,7 @@
               "               &#x27;2020-08-15 15:36:37.500999927&#x27;,\n",
               "               &#x27;2020-08-15 15:36:38.500999927&#x27;,\n",
               "               &#x27;2020-08-15 15:36:39.500999927&#x27;],\n",
-              "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=55000, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_b5</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-d29f11f7-0b8f-4d2e-b8e2-2847d3aa18e5' class='xr-index-data-in' type='checkbox'/><label for='index-d29f11f7-0b8f-4d2e-b8e2-2847d3aa18e5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:20:00.438499927&#x27;,\n",
+              "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=55000, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_b5</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-2afce65d-6462-4849-aa74-76741c2965b9' class='xr-index-data-in' type='checkbox'/><label for='index-2afce65d-6462-4849-aa74-76741c2965b9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:20:00.438499927&#x27;,\n",
               "               &#x27;2020-08-15 00:20:01.438499927&#x27;,\n",
               "               &#x27;2020-08-15 00:20:02.438499927&#x27;,\n",
               "               &#x27;2020-08-15 00:20:03.438499927&#x27;,\n",
@@ -784,13 +785,13 @@
               "               &#x27;2020-08-15 15:36:37.438499927&#x27;,\n",
               "               &#x27;2020-08-15 15:36:38.438499927&#x27;,\n",
               "               &#x27;2020-08-15 15:36:39.438499927&#x27;],\n",
-              "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_b5&#x27;, length=55000, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e6ed0073-a583-471c-963f-071dbff6aeab' class='xr-index-data-in' type='checkbox'/><label for='index-e6ed0073-a583-471c-963f-071dbff6aeab' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
+              "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_b5&#x27;, length=55000, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-f033e9d7-d4fd-4979-8ac4-bfb33ff92fd8' class='xr-index-data-in' type='checkbox'/><label for='index-f033e9d7-d4fd-4979-8ac4-bfb33ff92fd8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
               "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
               "       12.6, 13.1, 13.6, 14.1],\n",
-              "      dtype=&#x27;float64&#x27;, name=&#x27;range&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range_b5</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-275e03c2-59ed-4d76-ba28-abc3149c9aec' class='xr-index-data-in' type='checkbox'/><label for='index-275e03c2-59ed-4d76-ba28-abc3149c9aec' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
+              "      dtype=&#x27;float64&#x27;, name=&#x27;range&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range_b5</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-de7c4065-0bf4-4f6d-b14f-69449fc8b193' class='xr-index-data-in' type='checkbox'/><label for='index-de7c4065-0bf4-4f6d-b14f-69449fc8b193' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
               "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
               "       12.6, 13.1, 13.6, 14.1],\n",
-              "      dtype=&#x27;float64&#x27;, name=&#x27;range_b5&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>beam</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-aae3364f-a7bb-473c-8cb8-47ab99fe09f6' class='xr-index-data-in' type='checkbox'/><label for='index-aae3364f-a7bb-473c-8cb8-47ab99fe09f6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;beam&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dir</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-9b13b25f-9026-4ada-8a3a-2896c6cbfeb5' class='xr-index-data-in' type='checkbox'/><label for='index-9b13b25f-9026-4ada-8a3a-2896c6cbfeb5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dir&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dirIMU</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-cebacc15-1a43-4374-91de-1163db703022' class='xr-index-data-in' type='checkbox'/><label for='index-cebacc15-1a43-4374-91de-1163db703022' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dirIMU&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>earth</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-78c8fda9-c04e-40c7-a227-76cb5d12b040' class='xr-index-data-in' type='checkbox'/><label for='index-78c8fda9-c04e-40c7-a227-76cb5d12b040' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;earth&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>inst</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-143e1025-bf20-4509-92d2-3f2b545d8180' class='xr-index-data-in' type='checkbox'/><label for='index-143e1025-bf20-4509-92d2-3f2b545d8180' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;inst&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>q</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-3fc3581a-d096-4092-8e6c-bcc7c4c76a1f' class='xr-index-data-in' type='checkbox'/><label for='index-3fc3581a-d096-4092-8e6c-bcc7c4c76a1f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;q&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x1</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-41c20b41-c58a-4d32-b392-0b85c7cc9965' class='xr-index-data-in' type='checkbox'/><label for='index-41c20b41-c58a-4d32-b392-0b85c7cc9965' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;x1&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x2</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e341b0e7-18cb-4935-ba0f-c8336922d729' class='xr-index-data-in' type='checkbox'/><label for='index-e341b0e7-18cb-4935-ba0f-c8336922d729' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;x2&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cd03c791-b422-4adb-a0d5-8fa0645392f3' class='xr-section-summary-in' type='checkbox'  ><label for='section-cd03c791-b422-4adb-a0d5-8fa0645392f3' class='xr-section-summary' >Attributes: <span>(34)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>earth</dd><dt><span>fs :</span></dt><dd>1</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd></dl></div></li></ul></div></div>"
+              "      dtype=&#x27;float64&#x27;, name=&#x27;range_b5&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>beam</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-9137ad8f-4782-432a-8947-4b73692e8655' class='xr-index-data-in' type='checkbox'/><label for='index-9137ad8f-4782-432a-8947-4b73692e8655' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;beam&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dir</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-0263034c-e555-4e21-b001-f590f8e161ea' class='xr-index-data-in' type='checkbox'/><label for='index-0263034c-e555-4e21-b001-f590f8e161ea' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dir&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dirIMU</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-92be0ebb-9e9c-46f7-85f7-7ccca83a0541' class='xr-index-data-in' type='checkbox'/><label for='index-92be0ebb-9e9c-46f7-85f7-7ccca83a0541' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dirIMU&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>earth</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-cb6b149f-ce38-46e6-9fae-b4424b15f76d' class='xr-index-data-in' type='checkbox'/><label for='index-cb6b149f-ce38-46e6-9fae-b4424b15f76d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;earth&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>inst</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-c06b0f97-0474-48a9-bd9d-0ed657f86896' class='xr-index-data-in' type='checkbox'/><label for='index-c06b0f97-0474-48a9-bd9d-0ed657f86896' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;inst&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>q</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-36cb7aef-fbb6-4ed0-9ce5-1363e63f39ec' class='xr-index-data-in' type='checkbox'/><label for='index-36cb7aef-fbb6-4ed0-9ce5-1363e63f39ec' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;q&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x1</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-4602e62a-bc1a-49ec-bfd7-afd8f4f8498a' class='xr-index-data-in' type='checkbox'/><label for='index-4602e62a-bc1a-49ec-bfd7-afd8f4f8498a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;x1&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x2</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-dea9ba20-680e-4e92-8a42-2918492d10cb' class='xr-index-data-in' type='checkbox'/><label for='index-dea9ba20-680e-4e92-8a42-2918492d10cb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;x2&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e4c8d97d-a580-46d6-8a37-d465412da7bf' class='xr-section-summary-in' type='checkbox'  ><label for='section-e4c8d97d-a580-46d6-8a37-d465412da7bf' class='xr-section-summary' >Attributes: <span>(34)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>earth</dd><dt><span>fs :</span></dt><dd>1</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd></dl></div></li></ul></div></div>"
             ],
             "text/plain": [
               "<xarray.Dataset> Size: 83MB\n",
@@ -840,7 +841,7 @@
               "    beam_angle:            25"
             ]
           },
-          "execution_count": 35,
+          "execution_count": 3,
           "metadata": {},
           "output_type": "execute_result"
         }
@@ -860,7 +861,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 36,
+      "execution_count": 4,
       "metadata": {},
       "outputs": [
         {
@@ -892,7 +893,7 @@
               "  ... and others (see `<obj>.variables`)"
             ]
           },
-          "execution_count": 36,
+          "execution_count": 4,
           "metadata": {},
           "output_type": "execute_result"
         }
@@ -925,22 +926,22 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 37,
+      "execution_count": 5,
       "metadata": {},
       "outputs": [
         {
           "data": {
             "text/plain": [
-              "<matplotlib.collections.QuadMesh at 0x112d98e1190>"
+              "<matplotlib.collections.QuadMesh at 0x25a2a9fdc10>"
             ]
           },
-          "execution_count": 37,
+          "execution_count": 5,
           "metadata": {},
           "output_type": "execute_result"
         },
         {
           "data": {
-            "image/png": 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WJeimImFziWpTgeZcRGupibC55AdOpSK55hLGlAmaS1TTbRI2l/oHTiW/brS0+IETff0Dp1KRqKUESmOaW/y6Flv94FxplLM4HRJ2lLDpH2gVh7iwgDJVTGsrWlcxLa0EQewHTtG7B06KgD5MawuqGuJyRVxUTAdONjtWa8ftoIFTEGNLrf3zar8vixk45ZYwcIqWMHDS6cApN+AfqGgxAycVW1ryAwZO1tGcCyiEim4dU0gHTsZCmA6cmiNNazEkiRJi6wgT3ycbGVpaI3r04IFTcz7A5QzN6cCpRIXmptyggVOYWKIBAydVtVSMIR8EVIyhSVUpteRpzoWE6cCpyZYp5fzAqRLGlPIhzfmQahhTKoS4qqE578s3EVFqylHKBSRRQnNLgSTyv4daKZqoEGhFc0uBpiQi0IrW1laamv3+K7XkaYoCmpIIWzU0FUKaogCVDpxKxYgeXUUrRaQVobE0tzTRlEQUbURzi9/v3apKNUr7mguJo5ggsZSKIbaSDpyiINvWLS15knTb9+mqX6fmPMY5YuMHrCr2yzUXI7+9BwyconcNnFryAeUwpqka0tzSglJQSQdOLYWAqrFU0oFTa1OAq1jCxA92CuHCAydVtQSqf+DUnNOUFzFwaqkkVJpaCWJLIT1ugwEDp+x3YQRu7SiqgJxa+oFT4BTInc7DMuqeqps2bRqf+MQn+NKXvsSjjz46rGXPPfdcHn/88WXUMyGEEEJ80I26gdOWW27Jgw8+yPrrrz+s5Z599ll+8YtfLKNeCSGEECNPK3+2a2k/Wp53GrZRN3BaZ511yOfzbL755kNeplKpsN9++/GjH/1oGfZMCCGEGFmBUnV/xPCMuoFTzXBuYvve977Hdtttx84777wMeySEEEKID7pRe3P4UG+6e/jhh5k+fTp/+9vfeOedd5Zxr4QQQoiRU7vkttTLN64rK4xRO3Aaip6eHg4++GCuvvpqisXikJerVCpUKpXs587OzmXRPSGEEKIu9V5uC5BLdcM1ai/VDcVxxx3H17/+dbbaaqthLXfuuefS1taWfeTll0IIIYSAD/DA6U9/+hPPPvss3/3ud4e97CmnnEJHR0f2mTFjxjLooRBCCFGfep6oq/cy34rqA3mprr29naOPPpo77riDMBz+KubzefL5/DLomRBCCNE4cqlu5H0gzzgdccQRHHPMMXzoQx9a3l0RQgghxAfIB+6M05tvvsnvf/97fv/733P00Ucvssx///vf7Km81157jbXWWmtolTu7cIyKUqi4kkWooDQ4m0ViAKik7CNSTBVlqr5MGrOSldehj7hQGpWUfXNpO8pZnLOgQ5wOcUEOXe0GYyBI8+7S8iqpQhqJgjU+QiXM+X5bg8oXfXZdGIE1/qMDXFKFPlAtYwZNz2id/azCHGiNq5azdoK28bg000zlfeyJbir4CJYwAh2g8j4DTbeNR+kAtEZFOR9rogNcEhPkCtgkxlXKuCTO6gdQpVZfHnzcCqDyBVQYZX0izPm6rUFpjQo0aE04fhXMnJm+zzrA9fWg2sbjrEXnQkiqJOUKub4eiCL0ymuQzHoNVSih0nRzW+4laBlD35z5NE9cDRKfSm465oE1rPLxjVH5AranCxVGmHmzcJPWwlXL2K4Ffl9Yi+mYhy6WsF3tPgalWka99iyupxOTxt7oiWvgyj1UX34OgHDVtSCJCfPpeje14Xo7iN96HTd+FdTMF9GlFkzHPIK28diuBQQ2wc16hdy4VXxuXfubuLZVUNU+X4ep4qKiPy4rPT4H0VR9VmFUQPe248ICrtACzvrj0iT+eAxz2OKYLIIlO67T/eWiKMtcTH9NMvPLhkKg6IktxjkqCfQljra8Rikfx2Kdj1ipGkekob1sGFsIqBpHZ9VSDDW5AMoWEuswrhZ3An2JJdSKjopJ/yduaAk1iYFO44+lXOD/lx5bx6xuf5wZB4kF4xxpzBqVxMezGO0ItKI3NhgbEFuLxaFRRIEithZjwTqHVoruqmFswce7xImju5pgnCMfBGk2nd8gXdWEllyY9d866K4mVIxl5UgTW0tvbIgCRUc5JtIKrRSxcZQTH2NSMZbOSpK1H1tLX2zQWlFO+r/vqBhi66NNZnVVWKOtiHUO6xzG+vpqX5tzId2VhOZ8CChiY7M4kZ40EsXi29JK+fW0NutTRzkhCjSxsem28fVWjN+eftv66b2xIZ9G0wTpurXk/XaK0yiUqnH96xwoipHfn0AWC2NxaOf7Eqbbd2CSiHF++ygFgfb7Xil/9qAW/WOcoxhqfwziMxTBH5+1fWYdEITZ9qjFrcS2PyZoJCnqOwMi55uG7wM3cFJKLfZMUxzHvPrqq4RhyLrrrgtAlGaGCSGEEKONXKobeR+4gdNqq63Giy++uMh5r7/+OmuvvfYSywghhBCjhbzHaeSN2nucksQntpv01LsQQgghxLI2KgdOfX19PPecv/fjscceW869EUIIIZYPf8apnqy65b0Go8+oGzhNnTqVCRMm8PzzzwNw6aWXMn78eC666KLl3DMhhBBiZMl7nEbeqLvH6frrr1/qZddaay2cc+9dUAghhBBiEUbdwEkIIYQQnjxVN/Jk4CSEEEKMUrrOy22j7n6d9wHZZkIIIYQQQyRnnIQQQohRSi7VjTwZOAkhhBCjlLwAc+TJpTohhBBCiCGSgdNwKO0DaSEN/E1fbaBUFnaKsz7cV2mwCU5pH/4LWUCvC6Ksvizot1Yn+DaSOAsJzubZpL+8TQOHa0G47+5n6MNwXVRERXlwFtvT1R/eaw3O2iws11XL2N7OLATX9nb56cagolwW3DuomTCHyhWy4F0A3TJ2wPdjULkCtq8n+x4d+BBeQBdL6OYx2J5OdKkFXSz5vmmNCgJcuSf9OUA3taCbWny7UQ5dakUVS+hcwQcKl1r8tDDyn0Ip3RQ661Nt3UzXguxnpTVKa1wcE/eUCcZO9H2MIghz2TK1+rCGpLeMyhdwceyDi9NQ4qRcwfV0YrvacUmMCnO4ShqEnAYvqzDCVctZvbUAY1cLVrYGV+6F3gU+gDgNXXbVMrZaxrTP8SHFSqNyBT8/7RdBhErDktEByiS4JMYumJNtC5wl6J6D7utAdc1FxX3+ODRVlE3QfR3o3gVpqG8VlZTRPfP8z5UeHyjtLLrcRdA9x7frXPqx2e+Dc2BRuDRIty+2GOezJHOBItQK5xzO+XBUpXxYaiWxxNYRKP99Yh09scM46K5aqsZRSRy1HFWXhrYClBMfNBtbH1pbTXz4rwMSfOBuNfFtdlcsQfprp5WiO7Yo5QNsq4kjsb6u7qoPlfVt+fLG+aDaxECg4Z3uKr2x8WG2aWiuVj5QtruaML8vTsOMLRVjeGluD92VhED5MNxy0v973hsbYmPpriR0VQyR1vTFhtj45YF0HS1xmpbbGxu6q4ZA++87yjHGQZwG4xrn17EWUhtby+yeKh0Vn77QVU0ItKKSmHRfGdrLMTor79uuGksUaEpRgFKk+8JSSdN2e2OThgy7NKDX96+SWKxzRFphrC/XVUkwDpqiAK2UX874DRwFit7YEmmdhfLGNq0jUHRVDM75Yyax/a+X0SjKxmbHg3Fu0EUo63zor0aRWJf94xdq/7NKy8S1P+XO9R+vA07paAUuLLzrmPDlrUtv1h7BoF95j9PIk0t1QgghxCgl9ziNPBk4CSGEEKNUQJ33OMk7oYdNLtUJIYQQQgyRnHESQgghRild56U6XceyKyoZOAkhhBCjVN2vI5Bx07DJpTohhBBCiCGSM05CCCHEKFX3U3VyqW7YZOAkhBBCjFJyqW7kyaU6IYQQQoghkjNOQgghxCgll+pGngychBBCiFFKK1XXKwXkdQTDJ5fqhBBCCCGGSAZOSyEL2k3DalG6P9wX/Pc2gSCXlRkY5quqPVldLiz0h/1aH7rpghDlLE6H6XQfGqySKi6u+DqSSn+dJvZljV8eE/tAVx2gbOKX0SEqjLKQX1ct43o6fd3WoMIcWIvr831zcRWXVH3gLPjpSTWbD+CSqg+VrfRhq2VcuRfX14Pr6fTBuUkMWvu2yr24co8P1g0jVKEJVyljyz0+RDjM4YwPs8VaXKXPhw2Xe3z/8gUfqKu1D/vVGp2rTQsgzKHbxvt1LpZ8+UIJ3TLWt1cLG25qwVaTLFBYlVpRaaivrSZZ+K4zxgcYhxGu4vusw4i4vZ2wqeDDe63xQb+FpizEV7eNx/Z24ZIq4SprYDrmYebMRAVBNo+k6rdvLeg3jLLtqnIFnDFQbM3qd9biyr0+0NikIc19nf37MA1CdhW/r9ABLqmCc7i+HlQxDSgO82ATbNcCv+65Iiqu4Kp9qKQKSmfHlw/+jbNwaX/8pf1Nj3cbFfuPd1P1AcAAadAt+BBW53zQLPgA1CgNQC0bH4pq0rLGOixgLFl5Y31grlZg8SHBFh8k25f4r1XjP86ly1roS3wgrEbxanuZ3thmYbNKQcWYLKC1YgzlxBIolYX1xsb5EN5KjE3DiG0a7gtk62cs9MWG3tgvHxuXhfZ2VZM01NbSG1vyoaY3tqw1pkhsHXN7q2korqW9L8ZYR1MUpNvGhxXH1tIbGyrGUjaW+X0xlaQ/ABfAptso0joLSq6tR0s+oJIYuquJDy42vo2Z7X30xoamKKAQaN9GYgmUPwORDzTWOnpjH+Abp8t2lGNi67JcZ60UUdD/z0hsfB1RoLMP+P1pnQ9dru3v2nbsTUOMB277WkiyVmkgr1JZ2HKgoZz4QOWq8cdaxfjQZmNdFuJbCwC2Diz+e5WuS+3ylE6PUUUaADzg5IsZEEWiqd2E7Qv0kCNQPiC4Fg6slMqCfkfyhmsVqLo/YnjkUp0QQggxSulAobVcqhtJMnASQgghRqtA+ysMS0tJyu9wyaU6IYQQQoghkjNOQgghxCildH33Kfm7tMRwyMBJCCGEGKV0oNB1DJy0DJyGTS7VCSGEEEIMkZxxEkIIIUYppeu7OVw5uTl8uGTgJIQQQoxScqlu5MmlOiGEEEKIIZIzTkIIIcQoVe/bv+WpuuGTgZMQQggxSvmBUx33OGEb2JsVgwychBBCiFFK7nEaeXKP03CkQb4uDTkFfBCqNT7Q19ksyBfA6dAnYdamKZWVcekHm0CtzjTUt9aGSkN/szq0RkV5X0etnjCCIELFfb5oHPuvSTy46zrEVsv9P9fCYsGH6OYKPnjW+lBPlS+gwhy2z4fsugHLqihCBX5ZW+6BMAdpoK8t9/g6dODDcaMcrlrGdrX7UN++nixkmDR02Pb4wFozbxbOmrQfPujXVcq4vh5M1wK/bjrwIbrlXpw1mI552Tq4vh5UEPQH5kY5VK6QBRurXAFnLWFTEd08BnSALqSBwLkCYdGHMiutsb1dPpi3ZayvX/uQXmctxYnj/DYrlnzd1kISExby2K4Ffn3i2Pc/ibOAYVULfM4VfNivDnDlHnSu4KeXWnHlXt+fuM/XnVR9OHMYoYolbOc8XKUvCx/WbePTYGTTv55R3tdjquhSKy6u+k3UNX/AAeF8uK+ppuuns+1IEPhA6VootbOouOyPz6QCJj220jDq7PhOqv641AGhIgthrVnU33aXltFAbP2hXjU+kLdqHOU0NFfhA1wBymmgbmfV0Bv7abVA3Nha+mIf+BoohVLQGxs6q36ecY5ybGmKAuK0vnwQ0FFOqBqLVopC6AN0a6GyxvaH+rYVQuJ0nWpBs6R9i63/mxBoH7QbG5f2w69rbbk3OsoY54gCjVaK9r6YrqpJQ4T99EApOsvxoMDjtnxIbB1dVZO1VQvh7a4auqpJuiv9OgRK8cr8XmLrsLZ/P8TG8YWNVqKchQG7LHi5FoRcSdOM4zREtzc29MaGjkrit6Gx/QHAxocYW1fbD76+3tiHJ8fWUUlMVl8tKDdOt3d/+K/PTYutD8qtMTZdTvsQ5XwQoJWiHNvs+LK2P4BZKf+p/VyLcTPO4dL9U9v3/eHTvt3aIWoc9MSWSPswauP8tFogcCHUVIwj0oODgUPtg36DOrLjxPufnHESQgghRimlFKqOgZqyMsgbrlF7xmn69OlsvfXWXHHFFYst88orr7D33nszceJE8vk8G220Eeeccw6VSmXkOiqEEEIsIzrQdX/E8Iy6LTZt2jQ+8YlP8KUvfYlHH310seX++c9/stVWW3HdddexYMECqtUqL774Iqeddho77bQTfX19I9hrIYQQQnwQjLqB05ZbbsmDDz7I+uuvv8RyBx54IDvuuCP//Oc/qVarvPnmm+y7774APPzww5x99tkj0V0hhBBimam9jqCejxieUTdwWmeddcjn82y++eaLLfP3v/+dtdZai2nTprHxxhujlGK11Vbjyiuv5DOf+QwA11xzzUh1WQghhFgmZOA08kbdwKmmUCgsdt6bb77Jj3/8Y5QafEAopTj++OMBmDNnzjLtnxBCCCE+eEbtU3XvHhQN9MUvfnGx82qX+NZcc82G90kIIYQYSfXe4K3dqD1/styM2oHT0po7dy4Au+2223LuiRBCCFGnei+3OblUN1wr3MDp3nvvpVAocPTRRy+2TKVSGfTKgs7OzpHomhBCCCHe51aoc3SVSoXf/va3nHbaaUyePHmx5c4991za2tqyz+qrrz6CvRRCCCGGRiuF1nV8lnDbi1i0FWrg9KMf/Yj11luPk08+eYnlTjnlFDo6OrLPjBkzRqiHQgghxNCpQNf9EcOzwlyqe/LJJ7n++ut54IEHCNKctcXJ5/Pk8/kR6pkQQgixdOoO+ZXIlWFbIYaab7/9NkcccQS33norK6200vLujhBCCCFGqQ/8wKmrq4upU6dyySWXsMEGGzSkTmUTnwhvYrAJylRxOvTJ8C6N5DbVwT+DT553FvSAE33vKqPiMhiDivv8dJv0l7EWp0OfaK80OIsySVpNLQpcgw4G1w+opIxuaoEwh9Jp6n0U+SLG4KplVJTz03MFVJjDlnuwnfNABzhrfL06QOUKvp5cAaz19WiNCnOoMMJVy76ewJd3lbJfNoz611MHkMS+y6VWXFL15ZPYb6ekisoXsz5iDSrv393l4qrfxO1zcH09fnZPZ/+6JDFYi+3pxJV7sL1daZ0xyZyZmEoF29uFyhWw5R508xjQAS1rTsJ2Lejvcxj5bZEv4KplXNm3RW0ddYBpn51t86CQQ0U5XLZNAt/vdDu52veAbmpBhRGmpwuVL/jtbA26eQw6V/B9MAZnLbplDEoHqDCtM4n9fiiW/Has0QFojQv8fnRBzu/XIO1HlEMlse+vUn5fxRVcpc8vk1RQ+SYwpraTUM4fcy7wx7fToW/HWX8Mgo+irx17gFOaxIECFvV/2b7YH5MuTabPBSpLnq+x9KfRuwHLOuf8PR0KEtPfdDXxpSKt6Y0Nzvl5gYZ1xzZRSRyx6a9JK4VGZcs1Rf3b0Vg/v6vit0PFGIyF2DgqiSW2lnJiyYW+8Tjtd2wcsbXExlFOLNb5r7XvAcqJpSkKCJSiNzZ0VxN6Y0MlMXRUEqxzGOvoriTE1mGdy6bVfg4UBOmKG5d+rO9boKA3Nuk8x+yeKsY5jAPrGFAfRNpv96qxWV2xdURaEaWhsTbd3k1RQDnx6xak264pCuioJHRXDbGxRFpha9vC+nWvnQjJhwFRoLHObyNjoS82xNb3LdKaOO2Hdc7XFyhia7HpEeCc35+xtSjl91Hta00wIOxWKXDp/nTOf1WATo9KNWAbZofwgLq08vNq21opvw0Drfr3uYWqcRjn0Mov44+hgUftsiUvwBx5H+iBU09PD3vssQff//73+djHPrbQ/Ndee2059EoIIYRoDLnHaeSN2i2WJP5Mi6n97/hdenp6mDJlCscdd1wWs1LjnOPOO+/M3iIuhBBCCDEUo/Lm8L6+Pp577jkAHnvsMQ466KBB8xcsWMAXvvAFnnrqKZ588slB86y1dHd3E8cxv/3tb0esz0IIIUSj+Tso6rk5vIGdWUGMujNOU6dOZcKECTz//PMAXHrppYwfP56LLrooK/O5z32ORx99lGq1yrx58wZ92tvbieOYfD7PlClTltdqCCGEEHVTWtX9EcMz6s44XX/99e9Z5vHHHx+BngghhBBiRTPqzjgJIYQQwtNaZ0G/S/XRSzcMcM5x8cUX85GPfIRCocC4cePYbbfd+Nvf/tbgNXz/kYGTEEIIMUotr9cRHHbYYRx++OE899xzJElCe3s7t912G1tvvTU33XRTg9fy/WXUXaoTQgghxPLzxz/+kZtvvpkrr7ySr371qxSLRaZPn84hhxzCnDlzOOCAA/jMZz7DhAkTGtrugw8+2ND6Bnr30/dLIgMnIYQQYpSq911MS7PsFVdcwT333MNHP/rRbNpuu+1Gc3MzO+20E52dndx2220ceOCBS92vRfnsZz+bvbi0kZRS2SuOhkIGTkIIIcQopbTO0iCWdvnh2nbbbQcNmmp23HFHNt98c5555hnmzJmz1H1anJaWFr72ta81tE7nHLfccsuwlpGBkxBCCDFK1W7yrmf54TrqqKMWO2/99dfnmWeeYc0111zqPi3OyiuvzOWXX97weocbxyY3hwshhBCiIebOnUs+n2fXXXdd3l1ZZmTgNFxpuGkt6NcFOR+2a5PBZQDlbBbI62rL6NB/7yyqFu6rtA9fBVyYS9NJBwTi1kJ+a6moxvSHDNeWzxX754MPqU2qgwOFrfXBrlkgcJBNrwW0qjAH1vhQX2vQreN9qK710TYq8gG3SmtUvogzxi8PA8JofQCwD7ftj8RR+aIP6rUG29uFLfdkZXVTK6qp1bdVW15rX3c4IDA37bOr9Pl+JrFfz7QPtnuBb1fr/lDcWjhxvoCtJjhj0c1jcL2dkMQ+wDeJUbWw4VwBXSzhKmVM++wsSNgZg45CVBD4IN8wIlxpsu+TNZhy1ZcpNGXb1pV7IMwRjF+lPwTZWr9drEHnCti+HlShhO3pwvZ2+mWV3766WMLFcRayHIxfxdebxLiK77ezpj9AOYlRVd9fZapZqDDO+m2rFCpf9GHAA/YjzkIQ4Sq9uFwxO4adDgeE+Wp/LKfTnA7759c+6fEaaEViffCpdRBpH9gbKIXFh6/Wgm9rf4TsgOM3UIpA+WBWmwbZOnz4by5UGOvojQ1VY6kaRy5UxMYH2EaBD391zgcBgw/XNWnAbTmx5EMfsttejqkY44NnHVQSv96xtVnArbFkwb7lxPpQXmPR9Ie9dlSSLAQXIAo0xkFvbLPg2VpAby3Etjc2vv4B7ZYTS19syIU67YcPkK0YSyWxacCxD+GtpOHBtQ/47WStoxgFRFozthgRKB+WG2lFPtSUE0vF+H4FyofW5sP+kGOdlgsDTT7Ufj84R6AVUeDbt/jQ5O5qQj7UxOn+CAONVoruakJiLNGAsxnGOl/WOAINxTRYubY9a/u9ORcMWE+dhUKDD2OuJJaeqiHQafCvUmitMG5wsG5SC0bGZYHPtSDjWlk1IJRXA+GAl0H67ebLDnzwrBaoXMvxNQ5yuhb47I/XkYv4BerNqUv3UWdn56BPpVIZdld6e3t59NFHOfjggxkzZkyDV9RfVlsWhluvDJyEEEKIUUrpOkN+0/80r7766rS1tWWfc889d9h9ufTSS2lpaeH73/9+o1cTgLvvvvt9Ua/c4ySEEEKs4GbMmEFra2v2cz6fH9by8+bN45xzzuHKK69k3Lhxje4eAGuvvfb7ol4ZOAkhhBCjVKOeqmttbR00cBquQw45hBNPPPEDfW9TjQychBBCiFHKX3IL3rvgYpc3713oPfzwhz9kjTXW4IQTTqi7rtFA7nESQgghxFK55ppreOmll/jFL36xvLvynnbeeeeG1CNnnIQQQohRanm8Obzmpptu4pZbbuH6669f6I3exhjeeustVl999aWuv5Hmz5/PI4880pC6ZOAkhBBCjFJaa3Qd9zgt7bK33HILV155JdOmTSMMBw8l3n77bU488UQOPvjghg6cPv/5zy/VaxKMMfznP/9ZqmUXRQZOQgghhBiya6+9lv3335/m5mZWW221QfOq1SpdXV2svvrqXHXVVQ1td8011+SSSy5Z6uUblXMnAychhBBilBrpS3XTp09n3333xTnHggULFlvu61//esMDeU866SR+97vfceqpp/LJT36SQqEwpDaSJOHRRx/ljDPOaEg/ZOAkhBBCjFIjPXD64he/iLX2vQsuA2uvvTbf/OY3OeOMM4Y9KNtxxx05//zzG9IPeapOCCGEGKWU0tm7nJbqo0bXMOCEE05g5syZS7XshRde2JA+yBknIYQQQowKH/rQh5Z62a997WsN6cPoGmq+HyjtA1MHBJ+6INf/sxtwCrMWzmuT/sDfNBDY1cJ30/pQypeziQ/cTUNUa0HAyiQ+oNVU+wOFgwicG1BXeurSGlQUQZiDpAJJ1YfhDgx2DQIf+qo1aI3t6fKBvWm9OldAN4/pX+00sFeFOWxPl5+WBsvqphYfDqwDbLWc1hlk81WU6w/pDSNstezb0gEuqfpNVS3jquX+vtc2oTHoUiuuUkY3+RBeXSwNCip2Jg0lpj/81wcX+z6oMPL15go4a4nGjvWhvoUSrtKXhe7qQhM2Tnw/wG+jJPZlwwgV5bLT2ipdR9vXkwXtBoVc9iI619eDmfc2KlfALpjtQ4DbZ2d9suVeXBL7YORcIQ1I1tl2tgvm+HUJI2z3AnRTCyjtt3W+4PuTL2RhzK5azrY3YT47/pw1OGP8MWMtKvFPlai4gso3ZceLC3L+eAsj/zWpZEHWyqT7KD3OsmMyKfsy6THugpwvl/4uWNcfeGod5IL+IFYFFCMfhGvpD/j1oaq+bDUNaQUf5modVBJHpH1QcDnxQbXO+fm1IN5AKRLj51scsfWBupHWRFrTGxty2ofI1milmNsbY5zLAn5j67LQXpsG7QYaIq3Jp8eBsS4L3Y3T/vbGht7YH4/BgBDZ2vyuqv/9rS1jnV8mUIoo8P3rLif0xoaOcpz1L9JpuG8aEFyMAmLjw4sriaW9L05DjjV9sUnDhH1IrUnDamvrUwssBigEOlvHWpnYOJI0eNc46EpDjAsD1tuHFqtsPaPABwLX1rnWP50GNlvnw3Z7Y+P3TRpOXAg1cdqWVore2GahxuBDiHtjk/15q21bSP9s4rJ96ZwP99UoHw5d+zOBP0608p+cVjjnqJr+AN+q8ft4YDiwTveTcf0Z6lXryAUqC4atHaM1Jg0eHil15dTVeZlvRSVnnIQQQohRanm+x2lFJVtMCCGEEB8Y06ZNa/irEAaSM05CCCHEKKUDja7jrFE9y75f/b//9/9ob29nv/32Wyb1y8BJCCGEGKWUVv6eyzqW/yCq3YO2LAx54HTggQcukw4opbjsssuWSd1CCCGEEI005IHTFVdcsUw6IAMnIYQQYunIzeEjb8gDp0mTJnHttdc2tHHnHPvuu29D6xRCCCFWFDJwGnlDHjg1NTWx3XbbNbwDxWKx4XUKIYQQYsW0+uqr09LSsszqH/LAaVndaLUsb+ASQgghPshqkSv1LP9B8/TTTy/T+oc8cNp8882XSQeWVb1CCCHEB50KAnSaWLC0y39Q9fb28q9//YvVVluNVVddtWH1DnngNG3atLoaeumllxaZMVNvvUIIIcSKakW/x+lXv/pV9r1SiqOPPhqAm2++mYMPPpgFCxYAcPjhh3PBBRc0pM0R2WLWWrbeeuuRaEoIIYQQK4hvf/vbnHrqqXR2drL77rsD8K9//YupU6fS3t7OlltuybHHHstdd93Fb3/724a0WfcLMLu6uvjjH//IG2+8QV9f30L3LMVxzKOPPpqN+kY7F4SouP9nZaq4MO/DemuhqJUeXK7og3rz/gY1Xe5AxRVcPhwUnJqFAteuUVvrw3iVzoJZndI+uBayIFXAB7E62x/QmlSgFjIbx+hcwX9vDJi+tB0fXJutT7WMCtNw2lpIrIl9gGzsv0Ia8psKxk5Mg3EtKvKhvVmQbtgf0JstF0boYgnTPhtXKaOKpSyo1iWgCk2+rjSElziGMIfCn0ZWLWNwcZxtI9XUiiv3oAqlNBQ4l4bTBlm4r9+WPgA3+1kHhE0FbF8POsyhiyVsT2ca2JuG9g4I+UVr3066DiqMSHrK6EITJH772nKvDyi2lmpnD/kB25WBQcBpgDHWQJhDN7Vge7t827U+hzlcuRcKTdiuBZDEuJ5O3366z2qBya5axsVVv95VH4Rsm8bgOubhorzfpkr7/ZHEPlw6itLj1GTHV+1Y0JVuPw/6j880pNopnYZMa1wQ+WOuFiydHvO17atMjNNhFqgKEA/IvcY6CoHCAUkasGrxQcCBUiTWh/j2JdaHtDqXhab6sFqoGh/k21FJaMkHOAWVxBIbRzmxRAPChAHiNLy1KdLZ/GoazGrSr7FxNEUBYLLA4Vr/K8aCgdhYysr3pWIsSpGF5hZC7QOKrSOKAgqhzoJvjbP0GkPkFPkwoCUXpvX399M4aNKK7mpCbB25UJMPNe19MYFSdJZjjIMw0IwtRHRXkkG/ZwODZsuJpSUX0FU1vg9aU00SjIWxxYje2NAUaSqJ/5tSNrY/ZNk4AuXDd7VWNEUBgYIxBb+ccaTbiWwdrHXoQPsQ4sBvY50GFsfWZYHIsXWUY0tsHc1a+/nGkg+DLNy41g8frOv78U53NdsXxkI+9GULocY5vw8LoU5DpR1BWjixjqZIk2YFUzU+1Le2vWtr8VZ3zIRimIVKKw2FQNGTuKxcbF0aNO0oaU172dCcC9Dp8eDSY0kpH/5rR/De3RX9jBPAtddey2677Zb9fPzxxxPHMbvssgt33nknWmu+/e1v8+Uvf5lDDjmk7vbqGjg99thjfPnLX2bevHnZtHcPnGoHkhrBtGghhBBiRaB0nTeH17Hs+8GYMWMGDZoef/xx7rrrLvL5PBdddBE6Xb/JkyfT3t7ekDbrGjgdeeSRzJ07l8mTJ/M///M/TJgwIetkjXOORx55hPvuu6+ujr7b9OnTOeecczj00EPZf//9F1vu6aef5nvf+x7/+te/CIKA3XffnTPPPFNegyCEEEKMcqusssqgkzMnn3wySikOPvhg1lprrazc3LlzmTFjRkParGvg9NJLLxGGIY899hiTJk1abLkkSVhppZXqaSozbdo0fvazn/HEE08AcOihhy627O23384ee+zBD3/4Q6ZPn05HRwdf/OIX2XHHHbnnnnsolUoN6ZMQQgixPKzol+o+/vGPc/LJJ/PNb36TCy64gAceeIAxY8Zw+umnDyp3wgknNOz1R3VtsY9+9KNMmjRpiYMmgDAMueGGG+ppKrPlllvy4IMPsv766y+x3IwZM9h7773ZYYcdOO644wBoa2vjsssu47HHHuPEE09sSH+EEEKI5UVplQ2eluozykN+f/rTn3L//fez6aab8pvf/IZCocAVV1zBxIkTAbjnnnvYddddueqqqxrWZl0Dp3POOYd33nmHmTNnvmfZhx9+uJ6mMuussw75fP493/901lln0dXVxQEHHDBo+oc+9CG22morLrroIl544YWG9EkIIYQQI2/ChAk8+uijPPDAA/zhD3/glVde4ctf/nI2v7Ozk0MOOYQbbrihYa8/qmvg9NnPfpb/+7//44QTTlhiuXnz5vHjH/+4nqYWUigUFjsvjuPsDNeiXoPwyU9+Euccl156aUP7JIQQQoyk2s3h9XxGuyAI+PSnP83Xvva1hV50ufvuuw/6NELdryOYNGkSc+bMYauttlpkNowxhpdffplKpVJvU4Ms6Sm9hx56iM7OTvL5PKutttpC8zfddFMA7r///ob2SQghhBhJSgcoXcebw+tYdkVV18Dpyiuv5OCDD8Za+543XY3k6wieeeYZgEUOmsA/vgjw/PPPY4wheNcr5yuVyqCBXmdn57LpqBBCCCFGlboGTmeccQbGGD71qU9x5JFHMmnSpIVeR2Ct5f777+ecc86pq6PDMWfOHKB/gPRubW1tgH/ar6Ojg3Hjxg2af+6553LWWWct0z4KIYQQddNB/0t+l3Z5MSx1DZza29spFovcc889NDU1Lbbc9ttv37BXnQ9F7YWci+vTwMFduVxeaP4pp5ySPYkH/ozT6quv3uBeCiGEEHWqJR/Us7wYlroGTl/72te49957lzhoqvnPf/5TT1PDksv5WJLFXT6sVqvZ9+8+2wSQz+fJ5/MLTRdCCCHeT1QQ+MisOpYXw1PXUPNnP/sZbW1tPProo+9Zdq+99qqnqWFZZZVVAOjp6Vnk/FpuXqlUWuLTeUIIIYT4YFjcmGC46ho4jRs3joceeojrrruO3t7eRZax1vLYY49xzz331NPUsGy22WYAvPXWW4uc/8477wD+BZ7DZm1/0G4adqpMDGm4KaaKi/rPVqm4D5VUcGEBm0tjXkwVbIIyVZSzPjRVaR+iGub6Q1+d9XUPCFElLYfSEPp2lKn6UFblQ2WdtehSCwQRzlpUvuj/VxLlfMBrXw+mw1/ODNrGY8s9BBNXw1XKJHNm+naax4PWhCuvmYb5+nVWuYIPBtZpgGx6fVy3jMVVyuhiyT/lkYYDozRByxgIIx/UC/2BtenTICrvt4tfVvu+5guoUqsvF+Z8QG0S++1f7gEdELSN9+VyBV8mX8jadZW+AduiNQsCVrkCNk6yR3BdtezDdZMYVy0TFHK4vh6cNT7kOFfoDy4Oc4SlQv//0MIcJFW/bsZm7ap8ERVGhCtN9sG3A+4hcNWyX14HaUBv2fc5DQB2cTXdnmNQpVb/yRX8/nLWf7UGVynjyr39dVvjg3hrx2gSY/Mlfyylx6qfl/h1Sn/O1s05SB/gUDbxx7jx4cDo0H+vlA8+DgafqFZJOQ0GTvdrWnegFdZBoPzZ3zRfNftq0+8jrQiUwjqHwoexOudDWnuqhkD50F+Xhv7WAnWDNGQ3No58qGmKAirGUkl8AG8UKKpJf5hvObEE2ofeRlpRMYZAK4yF2FoqxhANuGxhHQTaLxtp5QNtna9Xp4HEcbp9a+thnQ+KjdKXChrr6CzHA5Z3FKMAnW7rQIGtBQ1bvy5aKaqJDzLuiQ1VY7Nw3bZ86EOH0+2bhewqRT7UdJQTCqEmDPz2yIc+pDeXbrPYWGLr664kflv1VQ0mnWddf98jreiu+NBhk07vjX0wcC2gOBjwzE9tvWuBw4VQ+20X+FDk2Pjw33Li29FK0ZwLCRR0lGPa0iDhQqjT7e9ozoU05wICpSjHPqC5FqyslcLi6xlbiJjTU0UrxfzemHd6Kljn+91TtRjnmNVd5Z3uKkpBJXH0JZbe2GIsdFb9Np3dHVMxjvaK8UHDaXBzYn1AcFfVDjhu/f51zmVh0S4NGe4blGy9jNXucarns4JYZ511GlJPXZfqxo4dmz1xduGFFzakQ42w/fbbk8vlmD17NnPnzmXChAmD5r/88ssAfP7zn18e3RNCCCEaQ+s6bw4f/fc4Oed48skneeONN+jr61voNp04jnn44YeZO3duQ9qra+B07LHHcuaZZw6p7Ei+jqC1tZW99tqLq6++mgcffJCvfe1rg+Y/+uijaK3Zc889R6xPQgghhGisf//733zlK1/hpZdeWmK5gUHA9ap74HTllVcyffp01llnneym7IGSJOHBBx9k1113raepRdYL/gWbi3LGGWdw0003cdVVVw0aOP3jH//g6aef5tBDD33PvDshhBDi/azet3+P9jeHH3zwwbz44os0Nzez7bbbMmHChIVei1Q7I/Xiiy82pM26Bk4tLS2ccsopix00gQ/43WGHHdh3333raWqQvr4+nnvuOQAee+wxDjrooIXKrLvuulx88cXsv//+XHPNNeyzzz688cYb7LPPPmyzzTb84he/aFh/hBBCiOVC1Xmfkhrd9zg99dRTaK15/PHH2WijjRZbrq+vj5VXXrkhbdY91Dz44IMXO2ga6LLLLqu3KQCmTp3KhAkTeP755wG49NJLGT9+PBdddNFCZffee2/uvPNOLrzwQtZZZx2+8IUvsO+++3LfffcN6RUKQgghhHj/Wn/99Zk8efISB00AxWKRX//61w1pc8hnnD75yU/y2GOPNaTReuq9/vrrh1X/zjvvzM477zzcbgkhhBDvfyv4m8O/973v8Y1vfIP29nbGjh27xLK1W3zqNeQzTrW3cTfasqpXCCGE+KCr3eNUz2c023333fnZz37GySefvMRyfX19HHvssQ1pc8hnnJbVU3Ej+bSdEEIIIT5Y/ud//oc//elP7L777lkW7UDGGP7+97837AWYQx44dXZ2cvXVVy82xmRpdXV1NbQ+IYQQYoWxgl+q++Mf/8iee+5Jb2/ve45PRvx1BLNnz2b//fdvSKM1jXyvghBCCLHCWcFfgHncccfR09PDeuutxze/+U0mTZq00OsIrLX85S9/4ZprrmlIm0MeOJ1xxhkNaVAIIYQQjbGih/zOmDGDXC7HI488wsSJExdbbv/99+fOO+9sSJsycBJCCCHEqLTLLrvw1FNPLXHQBP4y3UMPPdSQNkf3OTohhBBiRaZ1/Z9R7Be/+AXGGF544YX3LPvLX/6yIW2O7i02wpRN0HEfOIsL8+nE/k2onMVFTaDDbL6q9qGSMk5pCNIXher+E31OaT8vm5CmamvdX3cQ+O+dQ9n0PRRK+eWU9kn2gNMhKoz846VBhIsrqDACm8bS6AAXV1HFEsHYlVD5IugAXShh2mej8gXC8avgkhjKXehSK67c3f+LFeb892EOZy0uidFNLb6NpIrKF3Bx7JvKFXDWYOa/jYtj3698AVUsYXs6IYl9f5IqrqcT29uJbmrBWYvt6/F9TmJUWo8Kc9jermw9dLGELfegwhwqV/DT0/5gjb/mbw0qjHDGEIz1/xvRxRJBqdm3Xenzy6XlsAadK6BbxuB6fHi1S2JUsZRtQ11oQhVKqEIJkmq2vpUFXdk2yR7vTR/1ddb4crXtlsYEqTBCNbXi4qr/OV9ARX59dK3N2qcmXTdVLOGSajotPWZqN0Y65+seuP1M4r+vlnFREdLjyFnr63QWF4TZvRLKVHG5EsoMeO+Jc6ikCkr3H+tKZ8dz7Th26c/WgQOiQGVp8rlAY6xDAYl1WOdQCozrT7xXCmLrMBYKoR60arV6AfKhxjhHbC2VxGKcI9KKKFBUE0clsQQaYtufVK/Teyqt89/Xyg+cF6X7rzkXYNJFa/0rJ35CbCyx8X1sijRpFVkdTVFAObEEWhFbh1YK6xzGuqxsxVh6Y0s8YFpHJSZQkEvXLdCKQhhk26FiLLGxGOf70l6Oia2jkpis7d7Y0BcbuqsJ3dWEfBgwc34fnZWE2Dr6qoZZ3RW/PsbS0evraM6HNEUBvbGhq2qoJP3brRBo3u6uUE4MsbW8Mr+Xub0xxoFO13F2dyXti8U6l61/JbFopWjJh1SMIdK+n4VQY53fNsaBHnC7az7U2foESvl9lW6kKFBEWqMURFoRakVbwR9zoVY05/x61I6bQqgJ0rryoc72qUZhHVm9gVIEGpSCXNDfmdhCMd0f+VAN+kdTKUWgFXbg9wPqHBG1m8Pr+Yxia665Jg8//DC/+tWvFhvBBvDGG29w1VVXNaTNuiJXhBBCCCGWl4033phyuUxvby+33norhUJhoTJJkjB79mzi9D+69ZKBkxBCCDFKKR2g6jhrVM+y7we77rrrkC/BjfjrCIQQQgjxPqPqvE9Jje47dk4++WSuueYarrzyStZdd13y+fxCZeI45sEHH+TQQw9tSJsycBJCCCHEqLTSSitx/PHHs+OOO5LL5RZbbr311uP//u//GtKmDJyEEEKIUWpFv1QHcNJJJw2p3D333NOQ9hpyjq6rq4sbb7yRCy64IJv2xBNP8NhjjzWieiGEEEIsSu3N4Uv9GT2X6nbffff3Rb11b7GrrrqK1VdfnT333JOzzjorm77ZZptx11138alPfYpXXnml3maEEEIIsQJ7/vnn3xf11nWp7o477uCAAw5YZLBeoVDgjDPOoLe3l49//OM8/vjjrLfeevU0J4QQQoiB6n2J5Sg64/R+UdfA6Qc/+AFrrLEG5513Hptuuim77bbbQmW++c1vct5553Hqqacybdq0epoTQgghxAArUlZdX18fDz300CJP1tRb73DUNXD6xz/+wZNPPslGG20EsFAiMUBraysA9957bz1NCSGEEOLd6n379yi6OXzmzJl89rOfXd7dqG/gtMYaa2SDpsWpheo16o2dQgghhFjx7Lfffg17iWU96ho4rbfeerz00kt86EMfWuT8+fPn873vfQ+lFFtssUU9TQkhhBDi3VagM05XXHHF8u4CUOdTdaeccgq77747f/vb3xaad++997LNNtvw6quvAv7tnqOe0j68VweopIJKA3lr4aYqKfeH9DqH0yGmdSVMcawPRk3K/qupQpDzYag69N9HTT58Ncjhck24sIALcthcERfkcGGEyxUxTWN9wG9UwOWKuDCPi/LYfAmCAJcrgQ6w+RIqyvsA4GIrlMZix0zy4bEt47ET18F2taMKzbDKugRt433Y7bhVfXhtTycuLPjg22LJr1MaNlsLsVVR3l9fr/3iveurCnOoWjAwPvhXhZEPyU2DeYO28VlZdIDKFfpDe8PIB9kmcfYzgKuW/deeTlwagmvLPT60VwfYcm9/0C+gogjTtcAH41qLbhnr28kXUYWSD+ZtaqUyayYqX/D9yBf99tA6C9FVWmchvD7UuOjLA2EhT1jI+wDjNMwXQOWLWZCuitIA5lpob5hDF0t+fQYE0aogwPb4QGNdKGXbyQU5dFOrryOpogslbG8XwcTVUMWW/u1Y267p/8xcEmePLLu4ikoqYI0/NpIqqqnNH8tpaDQ2wUZNuCiPC0J/XOogq88HS0f+WK8FDSdVX78OcWmgLUCgfKBu7atxjlygqFpHTqtBQa6O/jDdvsRiceQCTWJ9ELB1PrTVODcovLWSWGJr+8Nga8ebUgNCfR2R1sTGhwJXjaOQBrda57IQ2Fo4bTmxRFr7UF3rsI5sncqJ5e3uCtY5Ksam7ft5TVFASy6gIw3UfaOjD60UFWP574I+2ssx/13Qx9tdZborCfP7quRDTRRoZndXmNNZYW5Ple5ywpvt/r6L9t4qkVa83VVmdneFub0x73SWebOjjwV9McY52vtirHP0xoaZ7X10VRO6Kz6g+Y32XtqaIub2+t+jYm7wP5TFXIB1jtjUQpI1fbGhtRBhnA80rm3PljQIuCUfUgh1GriraMv3/x+8FtAbKMgHmglN/piMtCIfBNl2b4r8vEAr1h3blAUvN+eCbHtb5yjlAlryAV0Vkwb76iz02KbhwIFSTGrJY5yjNR8woSkiF+i0P37fTm7JsWpzjkKoaMlrWvKasYWAlUohzTkfOLxmW4FiqGnNBQTKh/dG2rfTlg9oyweEWjG24PuYCxS5wAf/1o7xSDcu2mMoVBomXs9HDE9dZ5w+9alPccIJJ/DpT3+alVdemXnz5vGpT32Kl19+mfnz5+OcQ2vNeeedx6677tqoPgshhBBCLBd1DzX3339/nn32Wb70pS+xxhpr8Pzzz9PV1cUaa6zBvvvuy+OPP86xxx7biL4KIYQQYiBVz8svA7+8GJaGRK5suOGGg94aLoQQQogRoFR9Qb3vg5utR5u6zjj94Ac/GHLZWbNm8Zvf/IZf/epXvPTSS/U0K4QQQgixXNQ1cLr66quz7+fOncuCBQsWWe5vf/sbG264If/3f/9HGIYcfvjhnHjiifU0LYQQQojaQx31fMSw1LXF5s2bx1e+8hWKxSIrr7wy48ePZ8011+Tss8+mWq1m5U499VS6u7u5+OKLOfLII7n33nt56aWXOO644+peASGEEGJF5ZSu+zOaJUky4m3WtcXmz5/P7bffTqVSwTmHc44ZM2ZwxhlnsN1229Hb2wvAk08+CcA666wDQBAEnHvuufzv//4vjz/+eJ2rIIQQQogVUUtLC/Pnzx/RNuseara2tvK9732P5557jo6ODhYsWMADDzwAwI9+9CMAurr8O2ny+Xy23Ic//GHGjBkjN5ULIYQQS2sFv1RXqVTYcsst+eUvf8ncuXNHpM26t9i9997LWWedxSabbEJLSwutra1su+223Hzzzdx6660457DWLjLHbvz48Tz44IP1dkEIIYRYMSlV/2cU01qz++67c//997P22mszZcoU/vjHPzY8CHhQm/UsPGnSpMVGqYwdO5aenp6s8wPPNtVUKhXeeeederoghBBCrLi0rv8zip188smcd9553Hrrrbz++ut8+tOf5qSTTmKNNdbgtNNO45VXXml4m3Vtsba2Nv76178uNN1ay3e/+13WXXfd7Mat1tbWQWXK5TJvvfUWuVyuni4IIYQQYgU18LVI48eP59vf/jbPPfccN954I3PnzmWrrbZi++2355prrqFcLjekzbpegLnvvvuyyy67sM8++7DJJpsA8N///pcbb7yRJEkoFAr85S9/Afwga6A77rgDYwwf/vCH6+mCEEIIscKq98m40f5U3eJ8/OMfZ5VVVsFay6WXXsqDDz7IUUcdxdSpUznooIPYaqutlrruugZOJ554Ig8++CCXXHJJFmronGODDTbgiSee4LTTTssy6tZYYw323HNPjj/+eIIg4MQTT0QpxR577FFPF0aW8SGZysT9wb42wSmNchYX5HxYqk1QNsluulOm6oN6dQhpOUz/6xqwCar21SZ+PoBSvl5nUUmMy4Xo2D+pqOIyLgh9YGwQopxFVfv6lx1IB+AcesFbEOWhZwE6iXGrrgvVPuzrzxG0jScYvyr0dULzeFQzuHwJckWIy7jmArrcBUWNaZ5A0D4DF1d82RYFzqFsgh0ziaDzbWzzBHS5C5sr+mBjZ9GVHgCCcavgckVUXIGkgsoVSN6ZgW4Zgy61+NBgHeCqZVyt/1qjAKcNKlfAmf4QX3TQH+qrA3ShCcKcDyhuGYOLY1QEWOvnpcs4k4b4hhEqXyC/2hqoMMIlMbp5DNVX/+HDddO2XBL7gOIoh0tiXKUPF1exHfMorLEWyby3fTgw+D729aCKJYK28ZiOebhyT39/k6oP/80VfIhxGmBceeVf5MOIoGUMqlDCpoHGtXVT+QLOWlwc+/7kCiitcTpE2QTVMobsyn4tlDmMIEnLB0H/zaDp9nM6hCDwxyz4Y0gHYH05V7uBNAizEOAstDoIfduB9Qm8gEkDb7Xyx7CxDuMgl95KUYw0PbEl0AprHZr0VgsHifXfFwJN2VgCDX2x9YG9aberiSM34C9XObEYpzC6P4i3vRyzcnOOauLojS35UNNdTcin4bBV0x/kCzCuKaKaOCr0hy3P7CrTlg+ZXY4pNPtbDQIFlaQ/9BZgbNGH4RoH5cTQGxu6q4buakJHX8zYphzEfrvExhFoRS4N9s2l04zrnw7QXAipJj64uBbKmws1xkFLLqCnEFKMAqrGUgg0JnRUEot1jtXGFsmHmtVaCvTFhu5KwkrNeXpjQ0suoCnyvwOVxKC1YuOVW+iuGpoiTW9sac4FxNZRSQwrlXJUjCUfBoxvyqXbMCDSitg6mtMdEWhFMQrQSjGuGNEbG/KhxjroSMOGY+vorvrw48hBPgjorvp5FWOItA9Dtk4RG0uUDzHO0VM1xNZm+7Yp8qHE1cQBjlLOhwZX0+xsiyNAUTWWYqRxzk8zTlE1PjDaOagaf+wFWuHSgGEz4L4YlYYHx5Zs/xgLRqVh1VqRpMe6xe9/f2uK8sf+SKn3Bu9RPnAql8sUCoVB055//nl+8pOfMG3aNJIkQSnFl7/8ZY444giefPJJvv71r9PS0sKZZ57JbrvtNuw26xo4BUHAHXfcwZVXXsn06dOpVqt86lOf4sgjj6StrY2LLrqI7bffnpdffpkTTzyRf//730ydOpUXXngB5xwbbbQRRx55ZD1dEEIIIcQKau2112bWrFkA3HfffZx33nncfffdOOfI5/McfPDBHH/88WywwQYA7LLLLnz3u9/lD3/4A4cccgi33norl1566SIfYFucurPqtNYccMABHHDAAYucv9dee2Xfb7LJJjzzzDNcdtllvPbaaxx77LGLvGm8kR5++GF++MMf8vTTTxNFEU1NTUydOpVTTjlloVGqEEIIMaqs4Gec3nnnHbbeemvmzp3LK6+8gnOOcePGccQRR3D00Uez0korLXK5KVOmMGfOHI466ijWW289Tj311CG3OWJb7LLLLgMgiiIOP/xwfvzjH7PKKqss0zZvuOEGtttuOz7xiU8wY8YMZsyYwfXXX8/ll1/OjjvuOOjt5kIIIcSos4K/xwng8ccf5+WXX2bNNdfkf//3f3njjTc4++yzFztoqnnyySdxzvGb3/xmWO2NyBabN28exxxzzEg0lalUKhxxxBHstNNOnHHGGUSRv4dk880355xzzuGvf/1rNpgTQgghxOg0fvx4Lr30Ul5++WWOPvpompqahrTcP/7xD4BhP91f96W6hx9+mOuuu4433niDvr6+hV46FccxL774In19ffU2NSzPPfcc8+bN46Mf/ehC8z72sY8B/gYyIYQQYrRyStX5VN3ofwHmI488wvrrrz/sZX/2s58xbdo0Dj744GEtV9fA6Te/+Q1HHXUUwHu+pVON8M4plUoAPPbYYwvNq0XALGpQJYQQQowaK/g9Tj//+c+HNGi69tpr2XvvvQdN23bbbdl2222H3WZdW+ycc84BYIcdduCqq67innvu4f7771/oc95559XTzFLZaKONWH/99XnwwQcXuiR38803s+mmm/LNb35zxPslhBBCiMY4//zzh1Ruyy23HHLZ91LXGadyuUxbWxt33XXXEh/l22677fjf//3fepoaNqUUl1xyCZ/73Oc44ogjKBQK7L333jzyyCM89dRT/PnPf17sE32VSoVKpZL93NnZOVLdFkIIIYau3ry5UX6pbqiZdCuvvDIXXXRRdpWsHnUNnKZOncoNN9wwpPcfvPTSS/U0tVQ++9nPcuONN7Lnnnuy77778uSTTxKGIXfddRdBECx2uXPPPZezzjprBHsqhBBCLIUV7FLdQw89xDnnnJM9Ff/WW2+xww47LHGZcrnMCy+8kD0kVq+6Bk4//vGPefzxx5k+fTpf/OIXl1h2iy224F//+lc9zS2VL33pS/zkJz/h5Zdf5le/+hWFQoEtt9ySqVOnLnaZU045heOOOy77ubOzk9VXX30kuiuEEEIM2YoWubLtttty2WWXcfDBB3PXXXehlMqi3ZYkiiIuuuiihvShroHTvHnz+N3vfsepp57KpEmTGD9+/EJlkiThkUce4d///nc9TS21n/zkJ6y//vocddRRbL311uyzzz584xvfYO7cuYs9ZZfP55f5izmFEEIIMXyrrbYa06dP59BDD+Wuu+7immuuWWxZpRTFYpENNthgoczcpVXXwOkTn/gEs2fPBuDOO+9sSIca6ac//Sk33XRT9mTdnnvuSS6XY8qUKXzrW99i8803Z5tttlnOvRRCCCGWktIwjLiQRS4/Cmmtufjii5k6dSrbbbfdiLZdd8jvCSecQC6XY/z48URRtNBrB8rlMnPmzBnyDVyN8t///pfTTjuN7373u4Omf+UrX+FHP/oRJ554ImeddRZ333330CtVOg3pjVBp4G92mtNZ/7EJ6DArq2ziw3tr89PpA+e7sOCXS+tzQQ6VlFFxHxjjA4DTEF9cfwipTiq+HpOANbhKLypPunyMq/hAYEpjodwF1mC7F+CqZXRSRemApGMeJDG2pxNVC7KNq+hSK/QuQBWacdU+dNyHK/fgKmWY/Qau1OLDbyv+/VwqCHA6QFf7fF1JjI2rqHwR2zGPYOLktH9NuLjiw4vDAoqK709TCyrfhGpb2YcJp9vb5oppcLL1fxw6ZhNM/hB0zcWNWQVd6cGFeT/PWpSJsR1zUWNWgkoPKsr7MOKkiotjaB0H1mLaZxOutBqmawFBroAt9/hw31Kr70/rOFTkX4qm8oX+kNycj+lRaTCw6l7gp+mAoG08JFXIFVBRhANUmPMhu4BuGYuLqz5oNyr50OK+HnTbeGxvJ+iAaJXVUTrAdMxDF/0rNVy5B1ctw/xZvt6+HlSpFdM+24cat42HnnYo+PKq6ssrHeAAXWr12ztfygKBidIA6qY2bJTHhQV0tdsH/KbHtAty/vjVGmWSQaf0baEVFff2/9F1FpWUcVGRUPl3wyTWYR1YB2GaeqoAhw9PraYBv+ADcB0QaB++CqBRJMaHr1rnMFYRG5d+76fXgnaD9Gs+1JQTy4RaaK8x5ANNxfig4GDAMrXQ2HJiyQeO2PrfrUD71rUa8LumfHsTmnK0l2NWSUN/a2GukVZEgSLIBf5rb0xTpH1IbuJDhscWIxJjKYSa1nxIoBVrjSkyq7tCbGHtsU1UjCVKK9VK0VlJaM6FGAcrN+eJtKI3tkxqLRBpRVMUMLunysr5kEpiaYoCWvMhnZUkW781xzYRKMiHAXN74yzwuDkX0hubtB5NJbHE1qJVALgslDcfBrT3xTTnAiqJ347v9PjA4Epi6I0tY4tpSHViiI0P5A1UmH1vnSM2FmP9usXG0hsbH7QcpOG5zqHTAN1aGLN1LlsvsKRR39ky4MODlfJBvpH2x0wuglzgA35R/liKrSPQ/hgMlA/ltQpqd7vW/uky1tcTpMdwLvAhwMb6Y8M5lx5HpKHBatDj6Uop7Ej+c7eC3eM0UBAE3HDDDUMuP3v27Pd8m/hQ1LXFjjjiCDbaaCPmz5/PzJkzef3113nttdcGfWbNmtXQm7KGavr06VQqlUVupG9/+9tMnDiRJ554YkT7JIQQQojlY7PNNmtIPXWdcSoWi5x++ulLfF15uVxm/fXX5+STT66nqWGr3XH/5ptvLjQvDEPWWmstXn/99RHtkxBCCNFQK8gZp3vvvZfbbruNgw46iI985CPZ9Kuuuuo9l43jmL/85S/MmTOnIX2pO3Jlr732WuL8P//5z9x55538+te/rrepYfnSl77ECSecwB/+8AfOOOMMwrB/VTs6OnjxxRcXeouoEEIIMaqsIAOnPffck46ODp566ikeeeSRbPo555zDyy+//J7LO+calmBS98AJfIRJR0cH1tpB0621rLTSSlx//fVorUd08LTeeutx3nnncdxxx3HAAQdw/vnn09bWxttvv80BBxzAmmuuyQ9/+MMR648QQgghls63v/1tpk2bxuGHHz5o+mGHHcaJJ57IDjvswMorr7zI24Kq1SqPP/44r732WkP6UtfA6Z133mHKlCn89a9/XWI55xxXX331iJ91OvbYY/nQhz7Ez372M9Zee21aWlooFApMmTKFadOm0dLSMqL9EUIIIRppRQn5Pf300zn99NMXmn7AAQfw17/+lT/84Q9LXL63t5dJkyY1pC91DZxOPfVUHnnkEXK5HCuttBJz585l5ZVXHlRm1qxZbLjhhhx44IF1dXRpfeELX+ALX/jCcmlbCCGEWKaW46W6arXKz3/+cy6//HKSJGHy5MmcffbZfOYzn1n6/gzT2LFjOfbYY9+zXFNTE9dee21D2qxr4HT33Xdz9tln853vfIcoijj66KM55phjWG+99bIyp512GpMmTeLII4+su7NCCCGEWP4qlQqf//zneeedd7jnnntYY401uOGGG9hpp5249tpr2WOPPUasL0N9H+N7JZwMVV13hSVJwne/+93smuLBBx/Mb3/720FlTjjhBL7zne9w//3319OUEEIIId6tFvJbz2cpnHTSSdx///1cfvnlrLHGGgDsscceTJkyhf33379h9xMNxQsvvMC3v/3thcYZl19+OccccwwvvvhiQ9ura+C00korkSRJ9vNHPvIR/vWvf2VvEwcYM2YMY8aM4fjjj6+nKSGEEEK8W+1SXT2fYXr99de54IIL2Hjjjfn4xz8+aN6+++5Lb28vp5xySqPWcIn+/e9/86lPfYpf//rXCz3wdcABB3DggQeyyy67NCynDuocOG222WbstddeXHnllTz11FMAHH300UydOpUFCxYAcNlll/HWW2/xn//8p+7OCiGEEKJfLeS3ns9w/f73vydJErbeeuuF5n3iE58A4Oabb2bevHl1r997Oe200+jq6mKDDTbgkEMOWWj+Rz7yEX7yk59w1FFHcc899zSkzbrucTrzzDPZYostuOWWW4iiiJ6eHnbZZReuuuoqVl11VUqlEu3t7UD/xhRCCCHE6DV9+nQA1llnnYXmjRs3jtVWW42ZM2fyyCOP8OUvf3mZ9uXRRx/lscceY6uttlpsmS996UtYa/n+97/PzjvvXHebdQ2c1l13XZ544gkuuugi1ltvPYLAp/5ceumlKKW47rrrcM7xyU9+cqF7n4QQQghRpwY9VdfZ2Tlocj6fJ5/PL3KRZ555BoDJkycvcv6YMWOYOXMmzz777DIfOBUKhSUOmqA/SaR2Zaxedb8Ac4MNNuDnP//5oGmFQoGrr76aCy+8EICWlpYhvdnzfa8WsOucD0oFH4LqLE6H/nvwgb1Kgw5xSqPSA7tWFmtxuSZUtTer14UFH+zrrH+vRi1oNYxQJgEdgHO+HlMd1B8X5tCVHgij/gDhGmt8fyt9/aG1OsAZgy6UcJUyKopQYQ6s8YG1SeyDh5MYbILr64F8ARfHPgw3jnHWELSMwVXKuCTGJlXQASqMcEkMvV2oQhMqX8R0+NO1Lqmim1qxvZ24SplwlTVI2mf78F3AtM9GFUskXQt8MG6Y9jcIcLFfZ9u9AN06HlfuQc2eibEGlS+C1uimVkxvp1+v+bOw5R50oeS/NrXikioqV0AVS6hyCdvXg+vphKYWkrffIP/hT6SBxKvhKr3kNtgc8iW/Pctd6L4ev2wY+eDdOCbYcFXIl1BxH7ZrgQ/dLbXg8s24Be9AEhOMXQldaiGZPZNorY19CHH6QIUBH+CbhgQHY1fC9XTikqrfR7kCeuxKvt/5gg8JLpZQUR5VLKX7yKAKJR9CnAYKuzQcWuULfppNIMjhBr6k1jkfWJ0GUTsd+mVsMji8Wun0OLLZcQ344F/wP+v+PyUqqeCiAtb5wFQgDW8F5WohqYN/tQKtMNaR5vtm96wa5wNcNYpcoLAoqglEWkPog3Bb8kEW/mudD2Jtywe82VllXDEi0D5o+K2uCgAt+QBjITaOpiggcopCqOntM2kYb0jVOCaWIt7qqvCxSa0YC2HgQ11Xb8tjbJ5SpJnbW2W11gJvdJSzevNBQFNkifIh5cQCPijXOkd3GuJbCDW9seGNjrJff6WoGOuDdpUittavIz6QNraO3tiH3fbGhoLTxEr58mmAcS2wt7OSoJXCOCgbCyZdri+mu5pgnd9eNR2VhLGFiDjdV7F1/cHKzrcfpTtMax+W60ONNZF1ROlytVDh2vyOSkKUlq8FMtfaMM6Xj63fb1FOE2ndH7Q84IZlrXyAclfV0pIfnJ5b245RoIi0pmoc+VBlgdFuwPEUKEgshAP+POoB86rW+QBg7UN6XXrsxbY/1Le/T7V6VfZGaq3Akh7HI5jy69/jtPTvYqotu/rqqw+afsYZZ3DmmWcuVL5cLtPd3Q34AdKitLW1ATB37tyl7tdQjR07ljlz5jBx4sTFljn//POzso3QkDeHL07tBZNxHLPpppvS19e3LJsTQgghxFKYMWMGra2t2c+LO9s08L6lpqamRZbR6aC/XC43sIeLdtBBB7HHHntwzTXXLHQGbP78+Zx33nmcd955KKWYMmVKQ9pcpgOnmjvvvDM7VSaEEEKIxnCu/8za0i4P0NraOmjgtDi5XG7AsotuuPbv/bhx45a+Y0N0yCGHcMcdd7D++uuzyy67sN5662GM4ZVXXuG+++6jXC7jnGPDDTfk+9//fkPaXOYDp7lz53LiiScu62aEEEKIFY6/RL30I6fhLjtu3DhyuRzVapWenp5Flqk9VT9hwoSl7tdQaa25+eabOfXUU/n1r3/N7bffvtD8KVOmcMEFF2SXEOs17IHTSy+9xA033MDcuXPZdNNN2WeffRZ7Su+FF17gK1/5Ci+//HLDUomFEEIIsXwEQcDGG2/Ms88+y1tvvbXIMu+88w4AH/3oR0ekT2EY8pOf/ISTTjqJ++67j9dffx1rLZMnT+Yzn/nMQvdv1d3ecApfcsklHH300YNeennuuedy5513ssEGGwwqe+mll/Ltb3+b3l5/A7RErgghhBCN5dJPPcsP1+c+9zmeffZZ/vnPfy40b+7cuXR0dFAqldh2223r6NnwjR8/fkSiXoY8cHr66ac58sgjsQOfygFeffVV9tprr+zxxI6ODg455BBuvPFGnHOsuuqq/O53v+Nzn/tcY3suhBBCrOCs8596lh+ugw46iPPOO48HH3xwoXmPPvooALvvvvtir0YtC845brnlFqZPn84bb7xBa2srm222GXvssQcbbbRRQ9sa8ssffv3rX2OtZccdd+SOO+7ghRde4LbbbmOLLbbgueee49577+Wvf/0rH/3oR7NB0+67787zzz8vgyYhhBDiA2L99dfn0EMP5fnnn+fZZ58dNO/KK6+kWCxyxhlnjFh/Xn/9dbbaaiumTJnC5Zdfzr333stNN93EmWeeySabbMJ+++2XvYy7EYZ8xumJJ57gq1/9KjfeeGM27UMf+hA77bQT22yzDccccwz/+c9/SJKE1tZWfvWrX7Hffvs1rKNCCCGEGMw5t9in24a6/NL46U9/ypNPPsnhhx/OnXfeydixYzn//PO5/fbbufbaaxf5VvFlob29ne22244ZM2aQz+fZeuut2WijjRg7dixJkjBjxgzuvfdevvCFL3D//fdTKBTqbnPIA6dZs2Yxbdq0haYXCgXOPPNMdtttNwC22247rrzyyiwtWQghhBDLxvK4VAdQKpW4//77+d73vseWW26J1ppNNtmEJ598ks0222zpOzRMZ599Nm+//Tann346xx577CKfnKtUKhx44IH86le/4jvf+U7dbQ75Ul1fXx8bbrjhIudtv/32hGHIeeedx3333bfIQdOee+659L0UQgghxCK5Oj71aGlp4Ze//CWvvvoqL7/8MrfccsuIDpoAbr31Vq644grOPPPMxb5uIJ/Pc8kll/D73/++IW0OeeBUrVYHPU03UHNzM2ussQbHH3/8Il87UKlU+NOf/rT0vRRCCCGEeJdKpcLXv/719yxXKpXo6OhoSJtDvlTnnOPnP/85K6+88iLn9/X18dvf/nah66W9vb3ceeedi31RlhBCCCGWzvK6VPd+MWHCBKy1WczL4tx///10dXU1pM1hvcfptNNOW+L8ww8/fJHTayGIQgghhGic5XVz+PvFtttuy09/+tPF3rvknOOGG27gyCOPZMcdd2xIm8MaOIVhyEorrUQYDn2x3t5e5syZM+yOvS/pwKfEq8EjW6dDVFL26fM6RJn+XD5lE58cb6q4sIBKyrgwB2kZF+ZQpooL87ioCNUen3ZvqtioCeX635ulTBVXS6FX2rdlE1RcwSmNSqcr6y+pulqfARUEqDACa3DWooIB03MFv15hhAoCXMWAs7hKH6o2irfGL9vXg24bj0tinDG+HWvAWtABLol9OWMgiX35Ysm3lSvgkiq6UMJUyrhKGXSAigBrMZ1dBKVWdKkVM28WqqkVpTWOXNYHVSjhyuk2inLYnk5c1QdJujjGdi+ANovKFTDz3sY1tfhpKwe4Shk3723fj3IPhDlsxzxsbxe23Ev8+gtgDbanC11qwXYtQLeN99tHB7jeTmxPF8HYidhyL7qpBfPqbHSpFVUoZds0mfUaqqkVV+5B5QqoKEfS1+P7aRNUFPntUSihK2VMxzxUvoCrlFFjVsJ1tUO6j1QY4cpVXLWMyhf6t3NfF0HLGAhzUGjBdsxG5YvYnk5UlPPlrPH7P4jAWVTc5/eVsyhnsbkiqtqHC0Lfr/S4UZUeyBWzYwyTgLNgElwuPSaVwuWaIC73H+/psWmjwU+tOHz6fGx9qrxxta8O58Di87ICrcA6nFLE6X+DozSpPkmT6guBpqcak/NHO7Hp/6OfDzXaOLRSdFQMY4ohxjmwCoujORdk8RLW+XJx+l66cuK/BkrRXbFUjMFYiLTmra5K1kYlsUSBzvpWMZa5vVViY+koJ/31aEVzLqBifPnuakKkFVorYuPoqhr6YuP7h28nNo5I9697rY9lY4nS30ObzotNrR+K2ibQStETG8aFAZXEEAW+rSgY/J9W4xxNUUCg/PqWE9u/PUz/97X1bcuHad98Q4mxJAaiQJMPNLGxxMailaIvNmitCNL+aqXQqrb/fTRIpH2fa+uuld+OkVYESmGcw2T98WWMhUKoMdYR6P79VUjvNgm038exceRDle3LxDlC3X8c1sTW+eMtPfaUUoQaX79SOOcwDpTy97OkhyZBevxiHTbdRsZBqKC2lbWcIxhRJ510EltssQV/+tOf+OpXv8paa62FUoqZM2fy0ksvMW3aNGbNmkU+n2/YKxKGPAL66Ec/ykMPPUSpVBp2I3/+85/ZZZddhr2cEEIIIRbPpp96lh/NJk+ezJ133snUqVM55phjFrq65ZxjzJgxXH/99Wy88cYNaXPIN4fvtttuSzVoAthxxx1ZddVVl2pZIYQQQiyac/V/RrstttiC559/nvPPP5+tt96aMWPGkMvl2GijjTjppJN48cUXG3ryZshnnA488MC6GrrpppvqWl4IIYQQYlEKhQJHHnnkiOTiDvmMU73pwh//+MfrWl4IIYQQg9Weqqvns6L4wQ9+0JB6hjxwEkIIIcT7S+2puno+K4LZs2dz7rnnNqSuYT1VJ4QQQggx0nbeeWdM+iT3cMVxzAsvvEC5XG5IX2TgJIQQQoxSK8pTdYVCgenTp9dVR6PeJykDJyGEEGKUctT3ZNxouVD3//7f/+Of//wn5557LhMmTBjW+yTjOObBBx/knHPOaUhfZOAkhBBCjFLWuezFrku7/Giw66678qUvfYm99tprqZbfaaedGpaZ25Cbw51zPPXUU9x2223ZtH//+9/MmjWrEdULIYQQYgX3y1/+sq7ln3jiiYb0o+6B05///GfWX399Pv7xj3PwwQdn01taWjjttNPYa6+9mD9/fr3NCCGEEOJdXAM+o8WSgnxH8gROXQOnv/71r3zxi1/k1VdfXeiRxlVXXZXLLruMUqnEFltswTvvvFNXR4UQQggxmLzHaeRP4NQ1cPre975HqVTiJz/5CX/84x9pa2tbqMy3vvUt/vvf/3LqqafW09T7ggtyPjTVWf/RAdjEh6GGhSw8FcgCTwFf5t31KJ3d0TfwZzWwjtri+eb+cOG0fRdEKJv4EFZn/fdJ7PsF/V/TkF8Xxz4c1hjQaT3vCitW+aKfHkbpuvk6aiG6tlpG5Ys+4DcNrXVJ7BcOI0hidFNLtlwWDBxXfZvWYrsW+DqTGFvuwfX1+J+NL6tzBZwxPpC3txNnLbpY8m2l9aowwvZ04YzxwcW1PlqDq/T55a1BN7X4vsa+v7Z7gS+vAwhzPoC3WMLFVYJSi+9vbR/V1j1Jt1u6rjbtR9A2HlUsQRpqXAs2dpW+/tDhsl8329WOmTcLl8TEr7+AaZ+DaZ9D/Ma/Sea9ne0f272A+D/PYLsW4Cp9fpvVjoGeTr/NkyrJmy9juhbgKmXMnJmYWa/4QkkV29s1aN+4Sh+YGFfuyQKY/fbqQ7W/5bdnEqOSKhjjP+mTJ05pdKW7/wDRGl3uRJW70qwGizJx/++Ds6B8EKtyblDYae2Ps8I/2RJohcbfX5EMCOqthcvWlq0aH/iqFPQldlDgbWxcfxBuGlQbW/+1FgJbSSy9sWF+b5y1ERtfrmJ8GWOhYgwVY4mt/xg7+N6RSmKzdfCBtv773tgQpCG1Jg0qroXHWgdNkf/9i7QiHwZEafhvoPyy4Mv0xsavi+4PL/aBvzaty2+H2DoCBVqrbB1ja7PlC2Hgw47TMOFavq9NlzPO0Rv7AOABmz0L4AXIBxrrXPbVOr9sJbFpMLJL669tc0cU6Gy9o3SeVioL9dVKZSG9/WHCPjTXpsdKbP06+un96z4wpLi2zlnocXq+xKXL1MoOPG5q/Qprob5pXYFS/ok0589W1H7btEqP0bRZpXzQtM5+ru372vHjsvBqv48QI2h5nMCpa+D0xBNPcPvtt3PCCSfwuc99jihNfR9opZVWAuD222+vpykhhBBCvFu9OXWj/IzT8jiBU9dTdZMmTWLrrbdeYpmnn34agO7u7iWWW9aSJOH3v/89d9xxB2EYMnnyZA499FDWXnvt5dovIYQQYmlZXHbmbWmXH82eeOIJ7rrrrmwsMhIncOoaOK2++urMmjWLVVdddZHzy+Uyp59+OkopNtlkk3qaqsvTTz/NPvvsw4YbbsgvfvEL1lxzzeXWFyGEEEI0xvI4gVPXpbpjjz2WKVOmMHPmzIXm/ec//2GXXXbh2WefBfypsuXh1ltvZZtttmGvvfbipptukkGTEEKID4x6LtNll+tGsdoJnMVZFidw6ho4ffGLX2TXXXdlgw02YLvttmPWrFl8/etfZ4sttmCjjTbi4YcfBuDoo49mn332aUiHh+OBBx5gr7324qCDDuKMM84Y8faFEEKIZWlFf6pueZzAqfvN4d/73vf49Kc/zc9+9rPsPiLw1xm32WYbjj32WL7yla/U28ywvfPOO3z1q19l1VVX5ac//emIty+EEEKIxnn44Yf59Kc/PWjaF7/4RZ5++mk22GADttxyy+wEzr///W/+/ve/Y9OnMxt5AqchkSvbb78922+/PdZa5s+fT5IkjB8/fpE3aY2Uk08+mfb2dn74wx9SKBSWWz+EEEKIZaXey22j6VLdMcccw9/+9reFwnpH+gROQyJXssq0ZsKECayyyioLDZquvPLKRja1RG+++SZXXnkl+Xye9ddfn8MOO4ztttuO1VdfnZ122on77rtvictXKhU6OzsHfYQQQoj3m9pTdfV8RotnnnmGHXfckX/+858Lzdt+++2544476OjoYPbs2bz11lt0d3fzwAMPNPyqV0MHTovT29s7ojeH/+EPf8A5Ry6X47HHHuOcc87hgQce4JJLLuFvf/sbO++8M9ddd91ilz/33HNpa2vLPquvvvqI9V0IIYQYqhXt5vBnnnmGzTffnF122YVbbrkluxRXs6QTOI0ypEt1Bx100EJv5ByqOI554oknRvQ9Tg888AAABx54IN/97nez6Z///Of56U9/yiGHHMKhhx7KzjvvzMSJExda/pRTTuG4447Lfu7s7JTBkxBCCLEcfeQjH+GJJ56go6OD66+/njPOOIOjjjqKgw8+mEMOOYTVVlttRPoxpIHTK6+8wkMPPbTUgydgoWuSy9Kbb74JsMiNuPfee3PCCSfQ0dHBtGnT+H//7/8tVCafz5PP55d5P4UQQoh6DIwGWtrlR4vTTjuNKIqYMGECRx11FEcddRSPPPIIl1xyCRtuuCE77bQTRx55JDvvvPMy7ceQBk5HHnkkL7zwAscddxwTJkwgDId+T3kcxzz44INce+21S93J4ardk9Ta2rrQvGKxyPbbb88tt9zCCy+8MGJ9EkIIIRrNWP+pZ/nRYvfdd19o2jbbbMM222zDL3/5Sy6//HK+9a1vkSQJhx56KAceeCDjx49veD+GNALafffduffeeznppJOWqpGDDz6Ye++9d6mWXRoTJ07k3//+92Jv6p48eTLAQtdG31MtOFdpH6rrrA/zHRjKa6q4sIBKyhDk/LRaGZvglE4DfdPAWptgo6asfqc0TmkGnp9TpuqDhLMJ/tY0p0NULWQ4yIGu+Pm1UGFrULmCXy4NxVRRzgfrBoEPfzUGkhjVVEBp34YKAtAal1R9sG1PJ7pljF+VphYfMFstp8G6FlVo8j/H1Szo13QtQOXSpxl1kAUD294uwpXSM4FJjEtidKkVVymjm8fgrPH16sAvbw0uqfqfa+HEOiAYOxEVBNhq/7Z3SeyDivFBwEn7nKzftfBba30wsMoVCFrGYDvn+WWs8W2EEfT1hw+TVH0fyj1gDUHbeL+uYeTDdK3BWYvrXoBuHY/t9uG7rtzjQ3+TGNu1gLi7h9z4AJdE6Lbx2I55/f0u9/h1jUp+f5V70vUNspBiFeV8yHK6/q6nE9Ltq8LI7zPw65jEaaiy8dODCFVIg4rjGG0T3+84RqfHq69IoUzsA6TjMkQFHzxtk/R4jvwNEUr5YzKp+rImwYW57LgOtT+uAx1RHXDjqVZQMY5y4mjLayz9ob6BIg1cdYQasCr7n7Bzfnou0FRNLeRVYQIfHttR9sd7cy6kN64SG0dzLqCauCz0NbKKSGt6Y0M5SbLwXa0UvcbQHASMLUQ+ADdUVJzFOEewiDPl5cSSDzXlxNKWD4nTF+FEWgEqC8w1tj+EuJJYH46rfMjvvN4qxvUvZ9Pw3WIUpEG6ljCIiBxUEkMU6qx8bB1tUYC1hkD1B+I2RQE27cvAaeUB/zIWAo1xPkQYfBBubTmtfBBxoBWYweurs+BiRzEKfPBvGt5bC/DtKMeUjaU5H9JdSWgrRGjlw3BrAb+FcPBttSYN+q0F5jZFmthYIt2/f2LjyAc+2Ld2vNh03xjr93GgFM75IF9jIUib0fgwaYO/oVcpHzQdaZVtT5MGEftNl+63dBtq53DODTpWa2uQD9Pw4EBRNbXtvtDhIkbI2LFjOe644zjuuOO47777uPjii/nBD37AbrvtxmGHHcY222zTsLaGdHN4EAScd955dTVUu3w2ErbcckuARd55D2SvJ9hggw1GrE9CCCFEo9Uu1dXz+aDZYYcd+L//+z/OPfdcfv/73/OZz3yGzTbbjAsvvLAh9Q/5qbpFJQ4Px/Tp0+tafjimTp0KwD333EOSJAvNf+2119BaL5cXcwohhBCNYp0/c7i0nw/awGnBggWcd955rLvuuhx99NHEcYxzju7ubiqVSkPaGJHXEfT19bHvvvuORFMAfPKTn+SrX/0qb731Ftdcc82gebNnz+ZPf/oThx56KGuttdaI9UkIIYQQy8a//vUvDj/8cCZPnszJJ5/Mf//7X5xzbLfddtx00028/PLLHHvssQ1pa0j3OP3gBz9g2rRpnHTSSey9997Z9KG8piCOY5588km6urrq6+kwXX755fznP//hW9/6Fuuuuy7bbrst8+fPZ7/99mPzzTfnF7/4xYj2RwghhGg06+p7Mm40ZdVdd911fOMb3xg07Y477uB///d/sxdbO+fI5/N84xvf4JhjjmGzzTZreD+GNHD6+c9/zoIFC7jwwgsHDZyG85qCkXwdAfhLiw899BDf/e532XPPPcnn84wZM4Y999yTE044gVwuN6L9EUIIIRptRXqq7tJLL+Ub3/gGc+fO5eqrr+bCCy/k1VdfBfyAadKkSRxxxBEcdthhTJgwYZn1Y0gDp+uvv57DDz98oXuCDj/8cJ5//nmOO+44Vl555UW+pbNarXL//fdn2TEjacyYMVxwwQVccMEFI962EEIIIRrnL3/5CxMnTqS9vR2XPvEI8PGPf5xjjjmGPfbYY1ivS1paQ2qhs7OT119/nZ/85CeceOKJ2fTdd9+du+66a9DbuRflkEMOec98OCGEEEIMz4r0AkyA+fPn45wjDEOmTJnCMcccwyc+8YkR7cOQBk4/+tGPCIKA73//+4OmR1HEj370oyE1tLhXAwghhBBi6dSejqtn+dGkra2NI488kiOPPJJJkyYtlz4MaeD04osvcuutt/KFL3xh0PTjjjuOn//850Nq6KmnnmKXXXYZfg+FEEIIsUj+xbH1LT9aTJw4kaeffnrEMukWZ0ivI9hkk00WGjSBv5t9qI488sih90oIIYQQYoB99913uQ+aYIgDp89+9rP89a9/XepGXnrpJd54442lXl4IIYQQCzPW1f0ZLX74wx8u7y4AQ7xUd9JJJ/GJT3wCrTXjx48nl8uhlGLmzJnssMMOS1y2q6uLf/7znxhjllhOCCGEEMPj6rw5fCivE3q/eL+8RmhIA6exY8fywAMPcOyxx3LLLbdQrVazeX/5y1+G1NBIv8dpmVAap/0mc0Hkg37TwF2CyAfkpt/XAntrIbw4iwtyKGezgF8XRllgL+DnpVxY6P9Z6TSd0ofv+vrcoLBgnPUBtTr0Ib9paC34wFWHD8GtTXdx7INk8wVcTycqDcMFcMagjPEhs3EVVy37INkwwpZ7UFGEqwZZ4K4ulkh6ulD5QtoVHy7rkhiVC1CBD891+BBaZ3xorho7EVXpw/Z0oqIcpmMeqlhCaY3KF1C5AqZjXn8Ab8sYbNcCdEsJl1SxfT0+uLbSB4BO++jKPVAsZcHGtlombBuP6ZiH6+slHDMOQv8L6GJ/LNtyL+HYibiqQeWLmI556DDKtiGA6ekiHDsR27UACz50OP3qEh96W503j6i55PcF+KDdfAHV24czBp0roMJcti9cEqMKJZy1KGt9+TBC5Yu4ShlVavHrH0X+52KpPzTZGt//0M/zIccFXKXs29aBDyvWga8D/Py+Lh/uXAsvbvZhvuCDo7EGlyv64ygIUCbuD6rWgT/Wqr39vwu1Y9jZwfXUfh+AJA1OLYaaQPtA2TTLF/DBtYmFUIPDh7RaILH+0M/p/t+TQPt7OsqJD4+NAgWxn9cUaXpjm4XrGgsVY8gHAbG16RNIPuQ2SoNrtfI/B8oR6DTUVvkQ2ChQmKQ/jNdYRRRoX14rgnQNa0G9tSDY2FiacwG9sW9Hax/0G2lFxdg03NYHD/s+KKLAlwE/ry826Y2/ZNOMc+TToNwo0Og0rNZYR6Q1MTaL4KgklkLQv9209n3Xrj98eF5PlZWa874vgQ9MbiuExMbRFKk0cNhhrW+3N7a0FQLKic22U2075sOAKLbkA02v7v97Xws8jq2jKdJYBy35/n96YuvIB3rQP/7GOWLjiK3fx3EayO5vZNZpMK/OQoBLke/nwGBmjd82sYVAqzSo1+8rpRTG2DTs1x9j/eG9mkpiSawjl6b2BvgAX+N8YHAuUCjnBx39AcFiRTHkFx6suuqqXH/99fT09PDqq68yf/589t57b6699trFLlPLh7nxxhu56qqrGtJhIYQQQnjGkQ2ul3Z5MTzDflNUqVRi0003BaBYLLLddtu95zK77rorN9988/B7J4QQQojFWtHe4/R+UFfI75lnnjmkcmEYct1119XTlBBCCCHEQl577bURba+ugdPA3Lr3sqjXGQghhBBi6a1IT9UtypQpU1hvvfUGpZosaw0JdXHOccsttzB9+nTeeOMNWltb2XTTTdlzzz3ZaKONGtGEEEIIId5lRb9U9+c//xmAcePGjVibdZ1xAnj99dfZaqutmDJlCpdffjn33nsvN910E2eddRabbLIJ++23H+3t7Y3oqxBCCCFE5rDDDqOtrY3vfOc771n2oIMOakibdZ1xam9vZ7vttmPGjBnk83m23nprNtpoI8aOHUuSJMyYMYN7772XL3zhC9x///0UCoWGdFoIIYQQ8lTdj370I9ra2jjzzDM5/fTTiaJokeWeeeYZrrrqKi677LK626xr4HT22Wfz9ttvc/rpp3PsscfS1ta2UJlKpcKBBx7Ir371qyGNCIUQQggxNCv6pbpddtklO1Fz9dVXs8466yxUpre3l+eeew5rG5PMV9fA6dZbb+WKK67g61//+mLL5PN5LrnkEj7zmc/IwEkIIYRoIJu+oLSe5UezsWPH8oc//CF7A/qS4t0a9SLuugZOlUpliYOmmlKpREdHRz1NCSGEEEIMcsIJJ3DzzTdzwQUXsM466xCGCw9rrLXcd999Dcu6q2vgNGHCBKy1aL3ke8zvv/9+urq66mlKCCGEEO9i67zHaZSfcGKrrbbiK1/5CocccsgSy22//fb89re/bUibdT1Vt+222/LTn/50sfOdc0ybNo099tiDz372s/U0JYQQQoh3qd3jVM9ntLv66quHVO7tt99uSHt1nXE66aST2GKLLfjTn/7EV7/6VdZaay2UUsycOZOXXnqJadOmMWvWLPL5PGeccUZDOrxc6RDlLC4IUSYN0q0F7aYhqijdH6jqLCqp4kL6w3jTMioNAR40vbY8aUiqsxDk0rocLldExWU/XSlcmPMhwvQHBGfhw0nsA2+TGBVpH9QbBGlAbI9fplhCN7VgkzQhVQcw8OY5HUCtHmt9oG4co9MgXgCSGNvTBUkVZw1WB+hcAWsMGIO1BpUroNJAYJUv4Ko+hNZ2zMNZiy6WsF0LsjZrfVelVmif4/ue638i0/V0ZiG5unkMpqcTVSxly9meTnSpFVvuReWL6DBCt4xBt8+m2tNFmAb3mq4Ffv1KrVDu9f2qzStX0a2F/rBka3yYb7VM0ttHmIYWKx34IOK077Xt4qxF5Yt+WqGEznWholxWly61Ytpn+/qt8ds2jPy6FnxAsQ8PjvvXu9wDpRa/78LIb1Prw5htbxe6qQUVRiQ9XX4f1YKVK2Vs9wI/vxYS3NOVbdPaMYSzYOK0j+96MiUNlnZa+1hba3wfk6oPv3bWl6mFIjuLRWfB1xYfUpuk/701zof++qzq/umk5V06LxwQxGvSsFZjHZ2VhEhrIq0pY4mC/pBdrSAKVBYAWwvQjW1/MHAtODYe8F/13tik5eyg8F3wwa/NuZDYxkSBygJ3fWCwHVS2FgZrnf++EPow2vFNOXpjkwbnWvKhpqMSEwW5NMw2zAJ8Oyo+VLej7PdNFCi6KyYLCwZ/b0prPqQQaIz2ZcC3VQg0vbHJAnpj5WgONbFSxMYSpe3kwjQwF7+9an1tijTlLHAYglDTFAV0VJLshYmJsdiw///eA/8RriQ2C+719QW0l2OaooDZPVXa8iFNUUBsqhRCf8wUtO+LHhB+7Ms4Ymez/vmQZ0UuVFQTH8yslA/erST+2MopX5dKQ30t/ixB7Q4Xk4bzBloRJxbnlA/6re1XajdNKwLlj993n9VJrMuOT+ccSvmyDh9cLEaOtZazzjqLP/zhD3R1dfH6668D8Je//IXf/e53fP3rX+fzn/98w9qra+A0efJk7rzzTqZOncoxxxyz0I1XzjnGjBnD9ddfz8Ybb1xXR4UQQggxmHEOU8dZo3qWfT9ob2/ns5/9LP/4xz9wzjFhwoRs3mc/+1k+/OEPs8MOO/DHP/6RX/3qVw1ps+4XYG6xxRY8//zznH/++Wy99daMGTOGXC7HRhttxEknncSLL77ILrvs0oi+CiGEEGKA2lN19XxGs9NOO43nn3+ejTfemKlTpy70vsiJEyfywx/+kAsuuIDzzz+/IW3WNXDq6+vj/vvvR2vNkUceyUMPPcS8efPo6+vjH//4B+eeey4rrbRSQzoqhBBCCDHQzTffzKmnnsrzzz/PddddR3Nz80JlNt98c5xz/OY3v2lIm3UNnHbddVd22mknjjrqqIZ0RgghhBBDZ+h/e/hSfZb3CtSpdn/TksyZMweAV155pSFt1nWP0z//+U/AX64TQgghxMha0d8cPnny5Pd8seUll1wCwMorr9yQNus643T66afT2trKoYce+p5ld9ppp3qaEkIIIYQYZLfdduMHP/jBYudfcMEFXHzxxSil2H333RvSZl1nnL71rW8xceJEjj76aM466yzGjx+/yHJ33nkn999/fz1NCSGEEOJdVvSn6k444QS23XZbHn/8caZMmUJvby9333139kqkv/71rwCsv/76nH766Q1ps66B00YbbUSlUqGnp4errrpq0GOANb29vdn1RSGEEEI0jrUue7fW0i4/mhWLRf785z/zrW99i0MPPRRjTPbOplp+3Ze//GUuueQSxowZ05A26xo4ffrTn+ayyy7Lfu7u7l5s2UaF6wkhhBDCM3UOnOpZ9v2ira2NK6+8kh//+Mc8+OCDvPHGGyRJwqqrrsq2227LOuus09D26ho4HX/88Vx33XXccsst7xmuN5T7oIQQQgghhur222/nf/7nfwBYZZVV2HPPPRdZ7tprr2XvvfduSJt1DZw23HBD9tlnH3beeeclljvooIMaFq4nhBBCCG9FP+N0/PHHZwOnJdlyyy05//zzG/L6pLrfHH7xxRcPqdxjjz1Wb1NCCCGEGMDY/sHT0n2W9xqMjJVXXpmLLrqoIXUN+4zThRdeyIUXXshrr73Gqquuyj777MMpp5xCPp9vSIeEEEIIIRbloYce4pxzzqFarQIwc+ZMdthhhyUuUy6XeeGFF4iiaInlhmpYA6fDDjuMSy+9FPB3q7/66qucffbZPPzww9x9991oXfcJrPc1lZTB6jQp3g/TXRBl6fLKJDgd+nIpF4Q+PT4soIxPklemigsLWR0qKWNzxf/f3n3HR1HmfwD/PNN2k02nd0JVBISfSvfEcgeIyllBFGyIYjlsdwr2wmHBhu04UYpwR1HgPEHFgqcCYsOKDVBQkSqQZJNt83x/fzwzk12ygU0hBb7v12tfkNmZp8xMZp/MzM4HIlqiynbrIwnS4jYRSUDTnPKs0jY4ywg3wT6mEu5JSm85oekg2wZsG8Kw1ORwCbS0AChUDAqHICw/IG0I0wIZJigWgTAsCF8aEIuASoIQaQHIYAEoFvWSxuFsd2GqcmGYED5VFpUEIbL9IKmeT0vRiFrWMAFNByIhUDikpmkaNMsPqemgUNCrD9KGlpkLKgk63ZGQwQIIXxo0XYeMRaGFQ9DSM1XbIyHVN8OEsPyQhbuBWBRaZg6wt1CVa5iqrz6/V6/wB0CREOC0VcvMAUVCED4/yLZhhyLQcxtDswoBKSF8ftihYmiWH3ZJMTRNh5GRAYpFVNmWKlukBSB2b1d9DwUhfX7IYIHqi21DaLqzHp1/pQ0tvQHsXb8BhuWtV4qEQKFita59Th6TYan1r2mQkRCEYUILZAJSAoYPMEzIoj0g24aMhKBpOrRAJoQ/HYhFASOg9iOhgaJh1XdNAqZ0/q+r90mq/VFX6w0kIWIRkJXu7YcAADsK0k1odgya7gNAMHUBTainFEsCiOClygPqWGI4uz0B8Oma922YUIxApH4thABMIWBLgqlp0J1l/IaGcEzC1DTYGqALCU2otHv3/d0lUWRYhvewv1BMIiol0k0dgAZTFwAEJBF0IaBrQFQC4ZjqW6ZlwNQFfLqGqPN7pQuBqPPnerqpw9QFJAE6BHRhw5YETQhoQiDT0qE5DTI14bVFd6bpQiDLp6ZpQiASkzA1AV0APkOHqQmYuqbKMAC/rqFY2jCdlZBu6sj2GdhdEoXf0BAVah5NCPgMHZIIPkNHUcRGlt9EQSiKLL8JS9dgxh23NaHWQcN0C4URG7oAsv0mfi+Jeu1U7QbglB+S0lsPaaburWNdA0yhIepcCvI5daWbOnLTTIRjElFJMHU4/RPQpAAgURSJwdQ1SFLTzbjjoq6JhLMkoZiE39AgBGDoQMRO/Iq9EAIaEdxFfIaG4qiE0NQ+omtqu5kC0IXaP9U+ptZ/VAKmBkQJ3j5Xur7UvxKARgQSqqyadLhdqjv++OPx3HPPYcyYMXj99dchhMA777xzwOVM06z5M05vvvmmd5+Sz+dD165dsXv3bvz4449YsWIFZsyYgcsuu6xaGsUYY4yxAzvcBk4A0KJFCyxduhRjx47F66+/jjlz5pQ7rxACaWlp6NSpE7Kzs6ul/pQHTjNnzgQAjBgxAk8++STy8vIAACtXrsS5556LBQsW1PmB0yuvvILTTz8dM2bMwMUXX1zbzWGMMcZYJWiahmnTpmHEiBE44YQTarbuVGf88MMP0blzZ7zwwgveoAkA+vfvj2eeeQbff//9QWlgddm1axcuv/zy2m4GY4wxVm1klW4Mp3r9AExd17Fw4cIDzrd48WKsXLmy2upNeeC0Y8cOnHXWWdB1vcx7p5566gGXnzFjRsVaVs2uvPLK/T6gkzHGGKtvbKrawKm+R66k4owzzsC5556LpUuXVkt5KV+qKywsROPGjZO+Z5omWrVqtd/lJ06ciEsuuaRirasmc+fOxbZt23DmmWfihRdeqJU2MMYYY6z6Pffcc1i2bBn27t0LKROfryClxM6dO7F161ZcffXVGDp0aJXrS3ngJKXEli1byjQKAHbv3o1WrVqBiLxvw7iKioowd+5cbN++vcqNrYxff/0VEydOxDvvvIO77767VtrAGGOMHQyH483h8aZOnYrrrrsupXlbtGhRLXVW6HEEU6ZMwZQpU8p9f968eVVuUHW77LLLcOeddyI/P7+2m8IYY4xVq8N94PT888/juOOOw9VXX40WLVpg0qRJuPHGG5GRkQFAPe7k3nvvxeWXX15uHEtFVWjgtO/ZpIqojZDfZ555Bn6/H5deemmFlguHwwiHw97PBQUF1d00xhhjrMpikqBXYfATq+cDp02bNmHjxo3Izc0FoL4Itm3btoRLctnZ2TjnnHPwpz/9KeHLbZVVoYHT2LFjMWzYMKSnp6e8TFFRERYuXFjj9xZt2LABDz30UKWiXiZPnsyX9RhjjLE6rlWrVt6gCQDOOussnHbaaQknTHr27IlIJIJrrrkG//rXv6pcZ8oDp+zs7Eo/dXPIkCFYvHhxpZatDCklRo8ejUcffbTcG9r3Z8KECbjhhhu8nwsKCg548ztjjDFW0w73S3XZ2dl46aWXcPbZZwMADMPASSedhIceegh//etfAQA///wzduzYgVdeeaVa6kx54HTVVVdVuhJN06olkThVDz74II444ggMGzasUsv7fD7O3mOMMVbnySoOnOrzc5wA4LrrrsO5554LIQR69OiBTz75BNdeey26d++Ojz76CK1bt8a8efMQjUbRsmXLaqkz5ec4TZo0qUoVVXX5VH3xxReYOXMmHnvssRqpjzHGGGMHn5tgEu/ss8/GpEmTkJWVBcNQ54LS0tKwYMECvPPOO3jkkUewZcsWaJqGe+65p1raccil8j7++OP47rvvkJWVBSFEwmvWrFkAgEsuuQRCiMrFrrg3uRMBmg7hBu1qRmIgr9C8F+lW6TQnuJfc96HCfIUdU/NqhhcarAqWEDIGMpww4VgU0kpTbxn+0uWdoFaQVAG2PhWOKwxTBej6/Cqw1rRUeG9aAJCyNHB3327GoiooVtpOiKyuAmUBNU2qcFoKl0ALZKkgYMN0wnMlKFgAikZV4LCUKvDW51f1h1UIshtU67aBnPYgFgFFo7B3/KqWs/yw9+6CLC50gm6DQCwKCpcAmgY7FIFdUgx77y5QuESFADthuFpaADJauj6Fm9IpbVVeNFoa7KvpKog3HFLBv4Es2IV71M+mBd1veWHEXhCw0y87FAFiqh0AYO/ervrhPL6DpARFQpB7d4HCIRXyq8U9TFbaELrutUOYJkQgS71VElRhy4YJOCG+wrBK15XTV6+Plh8wTBVAreugaNTZ/UrLhxMELQyzNGxa07xgYgAqjNr0eyG/pBnOfia8/V5EQxDREBC37wtSSb6SyAuCdgN+Y5Ig40JUJREizv/dv3sjtlS/s1C/ZkLAC94F4AW8akJAgqBrAummDiHgBczCWdbUVSCsCvMFTF3zAnl1IWBqmreMJBUerAkBn65DdwJ6TU0F+6pAWBUabOoqfFaVpSE3zXSWTbz0EbYlsv2G03/VTwBe6G+GpSNqE9JNHbomEJWEqFR9yrDUchlW6X6S7TdUu5zQXwDQ4gKTM3wGQk4wcYbPUGG8UCG6fkNTYbrOstk+A9nOPCFbem1zQ4h1oUKOfbqmgoOd0GLb6Z67rArCVRNLojZCMRWyHLXJC0KWpPrkBj7rQsAm1W9NqOBdNwAYKC3P3RYuv6n6bBkCRKXbQxcCGlTf0gwNGkrDkwHA0EXCdtFF6U3RGkrDen2GBklwQqIFJJyAX3efc5aXVNpvSWq64YQCq8fyoMbYRFV+1RdjxozBli1bykyfMGECdu/ejTVr1njTevbsiS+//BJPPPEEHn/8cXz++ecYOXJktbSjQjeH1weNGzdG586dk77322+/oaCgAE2bNkV2djaaNWtWw61jjDHGqs/hdI+TlBInnHAC7r77bpx11lnw+/37nb9Jkya4+uqrq70dh9wZp8mTJ+Pbb79N+jrzzDMT5pk8eXItt5YxxhhjqTIMA4888giaNWuGiy66CK+99lrSB3MfTIfcwIkxxhg7XFQpp66KZ6tqWlpaGj755BN8/PHH+O6779CrVy/ce++9aN68Oa655hqsWrWqRtrBAyfGGGOsnjqcBk733nuv9xzJxo0b4+qrr8bKlSuxZs0atGjRAldeeSXatWuHiRMn4quvvjpo7eCBE2OMMVZP2SRhyyq8qGYvc7344ovo06cP0tPTkZWVhVNOOQVvvPFGSsvGP18xXps2bTBhwgR88cUXWLJkCYgIp59+Orp3744HHngAmzZtqs4uHF4Dp5kzZ4KIKvdtOsYYY4xV2t///nece+65WLNmDaLRKAoLC/HWW29h0KBBmDp1arXU0b17d0yePBmvvfYamjRpgokTJ6Jdu3YYMGAAnn766Wqp47AaODHGGGOHElnFy3Q19QDMr7/+GpMnT8Zjjz2G33//HZFIBCtWrED79u1BRLjhhhuwbt26KtWxY8cOPPHEE+jduze6dOmCt99+23k8BCESiVTbTeSH3OMIGGOMscOFLQlaPXgcwfTp0zFv3ryE8N2BAwfiv//9L3r06IFIJIJ58+bt9yGVV111VZmzRiUlJViyZAnmzJmDN954A7Ztg5xnU7Vt2xYjR47EqFGjyn1MUWXwwIkxxhhjB1X79u0TBk2uI488EkOHDsXixYuxY8eO/ZYxa9Ys3HHHHcjJycFbb72F+fPnY8mSJQgGg95gKScnB+eccw5GjRqF448//qD0hQdOjDHGWD0Vk4CowlmjWA3dG76/vNqOHTsCUDd5709JSQlat24NIvIuuxERLMvCkCFDcOGFF+L000+HZVnV1/AkeODEGGOM1VPVdamuoKAgYXpNht3v3LkTADBs2LADzht/Ke7YY49F06ZNsWLFCmiaBl3XIYQ4QAlVxzeHM8YYY4e5Vq1aITs723vVVLIGEeGtt97C0KFDceSRRx5wfp/Ph+uvvx7ffPMNPvzwQ7z88svYvHkz/vSnP+GRRx5B8+bNcdVVV2H16tUHrc08cKogMp1gWt1UobxOMC+A0mBf52fSrdKAX5KAjKl5nXBfkFTzGH7AVkGsbvCrkDG1jF4awEvx5QsNgqSq320DSRXMqlsq+Nfyq/qdQFpIqUJsY07oq2mCohH1/7SACqJ1Q25lTIX7wgmNdUNoAS/sl2KqLOHPUPPEoqBQMWQoqPohbdUGaYNCxdAsvwqW9flBsagTdlsI4YQDC0sFEcNQQcRqlWqgWBSycLf3s1p1tgohBuBr1kIF+UoJaDr0QCbsvbsgAlmgaAR6WjpkSRAwLGimAWGa6mcA0DSQbUPGoqBQEFpaANB0aJYBGCZkJAYKBb2wYSoJgqRErLjEW3fQdJiZ6SDbCf4NZKlwX2cdULgEMqKChqNFQVWeLw2IRSB0HVpaAMIfUOvePf1s29Azc1TYr7teNB2a5QeFiiH86WodGBbItr0QYBXkK0sDfQEIXa1zaBpgmM4+pIKE3X3B3dfIcLaRHQUZ/tJ92w34JQnh7KteWDUAOPurkDGQEBB2BIbzh19JtPRagCR4fy0KoQJlBVRYquUkrdoEL3jUZ6hwX8sJ5QVUsKuuwQuR1eCG8Zb+penO7wbzuqG8Pl0F9AYsHRmW4dRXGiirCeGF+NpE8BsqeNaW6i/zqK1eAGBqmirbCdB1w2b1uABeAF7QrSaEFzJcHLW9sN10J7jW1FT9AJCXZkE6IbjxbXOXc9sQjqltbDppvpoQCMck0k0d4ZhEg3QLpi6QZpYG5UYlecHBWX5TBdVKFcps6k4duqovzdS9PppOSK/bLlMX8Bmq7fHtdLnrt7T9wN5QDJIACVWfJoBMy/CClN2gZbe+nDQDYdv2prvbNRSVKlRXE16osaEBlla6H2gQ8DvbUXe2qyYEyAkcNjR3fxJOm9y2OoG9mtp20plmamrf1OP6SKTeU/ssvADkGjjp4amuB2D+/PPP2Lt3r/eaMGFC0vpuueUWFcJdgdf+HgH03//+F9u3b8djjz2WUn/ffPNNPPzwwwk3e+fm5uKKK67Au+++i48//hitW7fG2LFj0bFjR9xzzz3YsGFDyuszFTxwYowxxuqp6ho4ZWVlJbzKu0x3//33e1/xT/U1c+bMpGWFw2H87W9/w2OPPYYOHTocsK9nnXUW+vXrt9952rRpg1tuuQWzZ89G27Ztcffdd6NTp07o378//vGPfxywjlTwPU6MMcYYq3G33HILTj75ZIwdOzal+V988cX9vr9582bMnTsXc+fOxTfffANAneEWQsA0zWq7Z4sHTowxxlg9JePOGlV2+drwr3/9C5s3b8aCBQtSXubJJ58s8+28vXv3YsGCBZgzZw5WrlzpneUCgE6dOmHUqFEYNWoUWrduXW1t54ETY4wxVk/Zkqr0OILaCPl9++23MWfOHCxevBi6rh94Acctt9yC888/HxkZGVi6dCnmzp2LZcuWIRKJeIOlBg0aYPjw4Rg9ejR69ep1UNrPAyfGGGOsniIiUBUGP+6Ao6asWrUKkydPxuLFi5NeOvvpp5/Qtm3bpMsWFxejXbt2iEajCIfDAEqf4zR06FCMHj0ap556KkzTTLp8deGBE2OMMcYOutWrV+O2227DokWLkJGRkfDenj17MGnSJHTt2rXcgRMAFBUVeYO9Pn36YPTo0Rg+fDhyc3MPZtMT8MCJMcYYq6dkFYN6a+oep7feegvDhg2DpmllvkEXi8VQUFAAv9+Pbdu27becvLw8jBs3DqNHj07pm3gHAw+cGGOMsXoq/mboyi5/sK1duxZDhw71Lq+V5/TTT0dmZma57+u6jvfeew9HHHFEdTexQnjgxBhjjLGDpmfPngiFQlUuZ/z48bU+aAJ44MQYY4zVWySreHN4LT2OoDKmTJlS200AwAMnxhhjrN6qL/c4HUo4coUxxhhjLEU8cKqAhIBeTYXrQlfhp24AKoQAGerZFELGSucHVFBqLKTmgwoBVqGoWsJ8pFtOWZoK/yUJsgIqdNUw1c9OqC+ZPhU2bJggw6eWdYJ/PdJWQbCWH8K0VFBsuES10bRU4G40AmH6SoN8ZcwLlhWGpQJrnSBeYZqAYalgWcsPWfi7CuXVNFC4RAXhhoIqZFbaoJIgZLBALW+o52u4wcEyElLzSAlhmE5grQlhWNCyG6hA4VgEwrBAJUEIf0Atr+mApsHetbU0GNkND45GEQuGVDCwtKHnNlJ9AaD7fN78iEUgfGnee3bhHgh/AMI0ofnTQeEQdL8KSaZYVIXlmibILg2t1QKZoHAJhGEhVlAAoWsqrNeWXnixLNqjqisOedsDACgadV4qLJliUfVeLAKKhFRosBPW64Yc24V7QLYNLTMPiEXVtpC2t15lKAjhT1eBvsHdIFuFDGvOetPSAmr/dPcJzQmNtqNquhClIdW+gNo/nX1KBfmSF/wrpAou9vZdoYEMH4QbKk3SC4IVgBOuqkJVgdKwVJsA929ewwlpjdjkTYsP71XBwBpsCViGCnAVQoXcWvo+Ib+aCmE1nWBowwnjNTUVxts620LYtuE3NAQs3WuPG1SrC9V2v6FBEnnht+mmDlPTUBy14dNV2K0tS4N4TU0g22cg3dTh0zXYTihucVStFzck129oiNoSGZYBU1N1ZVp6XMiw6osbGqwLFZzbIN2Cz3DqN1RYsZSEveEY0k0VGqw5bY9Kgk/XkOkzoAkV8BtzAod1TUAXgM/QYOqaV06xE6Cb6dPRLNOnAo5JzSed8kIxCV0IZPtM+AzVTwBIN1VZKlhYtdEN+9WdkGKXqanAY7cvblBwuqkj228gKgka1LrNsAwVPIzSbeSG96abOoQAYhKIOGHF7r4ioT7k3OBeIYCoLH3oIxGgOwG+lCSgl4hgSzWPdN6znXBiXSvd5wxNhRjbUsV7xAcBH2zuR09VXqxi+FIdY4wxVk/Vh2/VHWr4jBNjjDHGWIr4jBNjjDFWT/HN4TWPB06MMcZYPXU4PY6gruCBE2OMMVZfVXHgBB44VRjf48QYY4wxliI+48QYY4zVU5IIogrfjJP8rboK44ETY4wxVk8RVfEeJx44VRhfqmOMMcYYSxGfcWKMMcbqKf5WXc3jgRNjjDFWT0kJiCo9x6kaG3OY4Et1jDHGGGMp4oFTBQg7ohIRdQPCjqlgX1uF9JJueOG+bogrABXSKkRp8K770k013Q3zFUKFp0rbC/ElwwfhBfqSKssNXHXplgr+BUC6E0JMUgWwSluFtNo2hC8tsS+mVRqYa5gQug6KhkHRqBdqq9qvqWDbaAQUDnl90gKZIGc+WVxYGpyr6apsyw+RFgBJqQJsIyH1p40T/OvOr1l+FeQLqDpjEdXutAC0zBxVphv4q2nesiKQBS0t4AXpmjk50HMbw971m2qzriFaWOyVS8ECpywTsT2/Q5hOneESmG2PhGb5UbJ9N4RPtUfoOoTPDzsUAUmp2uVuUtMJufWlQfgD0AJZKog3GoMeyAQAlGzf7c1vBwtV1el+yEjMW7fC54eMhErXl2GqvvnSnHXhtFvakIV7AE0HFReo7SE0yJIgZLBQzevsA167DAuyJKjCgt36NB1kqv2ApO0FPINk6fYDQKZP7dNCg7Ajaj9XBah9y46AdBNk+kv3O+d9EQtD2FFvH7UlIbbPX8NCqFBfTajwWE2oAFjhhf6qEFUBFfCrC+EFsJqagAQhKqUT0KrCVYsiMWc5FW4bH7Kqa6XBvZpQQa8q/Ff9nOkzoAsBv6khKlUwsXDCbyWRVy4AhGLSq8MNr3XriDp/uttEMHXh/SyJ0DzLh3RTRzhmI9tvQHPCad1gW5/hrC8CfLrmhQKbukCGE/zbIN1CXpoKu1XBtAKSCJmWjgyfgWyfAVNTAb+S1NOkdQGYTgCvCjgWyPAZ0DWBdNMN5tWRm2YiKglppo50U4OuqRDegKXaF47ZKlyZVLhtkwzL65vfCUL26RoaB3zI9hnIsAyURNW6ykszvT7mpZnI9Zsgghd+7Ib/um13g5TjA5KFUMHNUekG7KqfbSL4nLBnZxXCdMJ83XXkMzTY0tmOzrbSNQEignT6I4SAdPZFNxRYFwISqh4hVNiwWz6g9k9bEqLOenbL0kTN3nDtZtVV5cUqhi/VMcYYY/UUSfWqyvKsYg7pM05EhGnTpuHoo4+G3+9HXl4ehg0bho8//ri2m8YYY4yxeuiQHjhdccUVuPLKK/HFF18gFoth9+7dePnll9GvXz8sWrSotpvHGGOMVYkb8luVF6uYQ3bg9Oqrr2Lx4sWYNWsWCgoKEAqFsGTJEjRq1AjRaBSXXHIJdu7cWdvNZIwxxirNfRxBVV6sYg7ZgdPMmTPxxhtvYPTo0cjMzIRhGBg2bBj+/e9/AwAKCgrw8ssv13IrGWOMscrjgVPNO2QHTscffzx69OhRZvrJJ5+Mnj17AgB27NhRw61ijDHGWH12yA6crrnmmnLf69ixIwCgTZs2NdUcxhhjrNpJoiq/WMUclo8j2LlzJ3w+HwYPHlzbTWGMMcYqjSNXat5hN3AqLi7G6tWrMWbMGOTk5CSdJxwOIxwOez8XFBTUUOsYY4wxVpcdspfqyjN9+nRkZmbinnvuKXeeyZMnIzs723u1atWqBlvIGGOMpYaoijeH86W6CjusBk67du3CpEmTMGvWLOTl5ZU734QJE7B3717v9fPPP9dgKxljjLHUUBWf4cSX6irusLpUd/nll+Ovf/3rAe9t8vl88Pl8NdQqxhhjjNUXh83A6e9//ztat26Nm266qbabwhhjjFWLqgb18qW6ijssLtXNmTMH3333HR599NEqlUO6SgSHHXMmSEDT1MtJQifNAIQAaQbISZMHoCLhheYlzMOOAtJWafMyBjf+XZBULxkDSKqEeje9nkgt6yTPe3XoFqAZpen1MgYKF4OsAGBHIXxpqi5NgzBMwDDVz9KG8KWDYlFVXknQ66ss3K36JCUoGgVFQqp9mkpLh6ar5Z2yqCQICodAsSgoXAIYVuk8mqbqAwDDAkWjEJoGEchS6w4ApA0tM0ctZzjrWUpveT27AbTMXJCU0PzpqkzDgvAHoGXmQksLgMIl0NICEKYFMyOAaLAEJNW6s8NhaIFM6LmNIaMxCH8AMCw1v2FCmCasrIDXFgqr/up+C8LyI7p7N2RJEFpGDrS0AIyMDAjDVOtF2tByG3v9g5SqLGcdyIjaX/Tcxqo8fwCaPx3QdGjO9hCW31v3wp+u1rNhApoOkRZQ86ap9gnDgrAjEIYJLZCp6k8LQBbuAaRU6wbwtis0XW17n9/ZlzRVhl/1AbYzH1Hpvuzsq6Spv61ELOTs21rpvM6+LexYYtKos/8LGUNUAoYmoDuJ8u6iwaiE7VwiEM6vh66p96KSIICEZWwimJpKqLclQRcCli5ApFLsfbqOqFOeqWmQRIjYBEsX8OkChqbm1zWVdi9B+D1kI2DpMJ33TE3AdNadX9cQtQm6JqALgbAtoQn1vqmrdrlf4/bpuvezJEJemum0AUg3dRSGbVi6QLqp5rN0DVFJ0IRAVKo6TF2DLgSyfQYyfTp8uoaYLZHtM+A3NGRYOjJ9OkxNzeczdJi6Bk0ItMjyo3HAQrqpw9QFWmenISoJaaYOn6EhL83w1nVumokMS0e2z4AtgQzLgM8pJ93U0CTDgiZU/wKWDl0I7CyOqPZpQLbfQMN0E9k+E5oQCMUkTE31zd1e6aaOdNNZj4bmTQtYOnL8BixDqO0t1HaRIGd5IMune+vV1J3t4mxnWwIxSfA561+DgF8v/QjTNQFJgB03DkgzBIgIQgjEbPUvvP1NvedeqdI1QBIghGofoOokIsTtit66JKh9WwOgCXjz1PSVL34AZs075AdOixYtwpIlS/Dcc895vzQu27b5/iXGGGOMpeyQHjgtWbIEs2bNwty5c2EYiVclt27diosvvhgbN26spdYxxhhjVcMhvzXvkL3Hae7cubj44ouRkZGBFi1aJLwXiURQWFiIVq1aYfbs2bXUQsYYY6xqSNog91aISi7PKuaQHDgtXboUo0aNAhFhz5495c53/vnnl7l8xxhjjNUXPHCqeYfkwGno0KGQzs3ajDHGGGPV5ZAcODHGGGOHA5Kyimec+CRDRfHAiTHGGKunyLZBdhUGTlVY9nB1SH+rjjHGGGOsOvEZJ8YYY6yeIqrizeHEZ5wqigdOjDHGWD3F36qreXypjjHGGGMsRXzGiTHGGKun+IxTzeMzThXhBpxqmgrXdX4WsQiEHYWQMQg7qsJ3rTQVqOos54alemV44b3OdDecVzdL53XCLkloXiAwRFzdbuAunADi+LINUwUFazqE6YOw/CoINxaFMJ0QXU0H7Kj6xdF0CNNUZcWipSGzbhiwYZUG9bohuJoO4fOXBhzHoiqs1rBUWU7IrAwVQ/gDEDmNvcBfvUEzCE33Aoi9sOBICFRcoMJ00zNVUK1hgeLmEWkq2BcAKBJSffUHQJEQjGb5KvQ2uwF8OZmgUBDC8kNPS1fBtj4/rCbNvMBcrwx/AGZGAMKwQNEIRFpAtc/yA9JWywSyYO/eAb1JaxWY69QJw1IhxGbp3yG+5i284GIjPQ1Gepr6f1aWFzasZzdQffE74b1u4LBhqX+d8FgtI8cJQDahN2oBLTMH0p8JPbsBKByCFsiCLAkmbFd3WwrLD8QiENmNvX2JdMvZbmr/IDMN0AwIOwJppqttlp6TGChtOCHEQkBapesu/neBdKs0CNtZ1tRUKKodF+ugCyAcIy9MlaDm0aCCci1NwG9o0Jx53dBXmwg+QwXt+k0Nll768FpTF9AgkOHTkOXTQQB8hhMGKwQ0oZZXwa5qGcv5vxCA6YT5SiKVxy2ATJ+uAoU1INtnIN3UvdBaSQTbKcgyVIix7fy62xIIxSRy/SaiUsLUBcIxVY7P0BGxJTKt0jBbW5IX0GvqAhmWqivN1JHtN+DTVdguoIJ3bSJkWjpy00yEYzaEUNN9Ttuy/W67VfiuT9fRJMNCps9AbpqJvDQTGZaBqJRIN1U4shtOnG7qyPQZiNkqDFkTKqBXE6p/jQMWMiwDoZiErgFRqcKPbSJvHVnONtI1te4tXSDN1OB3goLdPrvt1YVqZ2kQs3BCh3VIJ8RZCMDQ4a2HDEuHEKqNfl2DBrX9bGf7+Z06bSoN83VDnjWoQ6uhCQih3iNnW+hOWK9bj+aEAZdEpQryBZxtTdCFCh3WNYGoFz6NhEDgmuAOnKryYhXDAyfGGGOMsRTxpTrGGGOsnuIHYNY8Hjgxxhhj9ZR0bqeo0vKsQnjgxBhjjNVTfHN4zeN7nBhjjDHGUsRnnBhjjLF6is841TweODHGGGP1lW2DtCoMfjjkt8L4Uh1jjDHGWIr4jBNjjDFWTxFV7Vt1HPJbcTxwYowxxuopkrJqAyd+jlOF8aU6xhhjjLEU8RknxhhjrJ6iKj4Ak79VV3E8cKoIkXiCjnQDIhYBGRZELOK874b1+lX4KRFI0wDdAGJhNU3T1XTdCdHVdBVwKzRVVjTsVKCCUoUdARk+ABpI01WQMAAIXdUVHyCs6SDoKrQ1FlKBrtESFZYbHwps214IrzBMUElQBb8CgKbKEYYJ6YboAhCmE7Zr+aGlZ3nhuABg790F4XyzQ0tzw29NFcyr6SrAlqTXBmGqvmt+FSobH3YLKaFl5KggXcsPioSgZzdALBxSQcKGBYpFIDQNFItAhlTALcVUYLGWowJtzdxcaBk50LMbqPXrtF1omhfeC8uvQnUtv2qbpqn5nXbq2Q1UEDEAWbjbW074AxCm6p8bGGzm5qr+mib0Bk29kGARyILQNOgNmsHetRVaepZa1gkuFj4/tEAmIKW3PkUgCxQucYKU05x1numtW0ESZJhqvVl+CF2HntsIMliogqMNC5o/AOFLg96gGaDrEGmZIE1X+5W7z5kqjJo0Q4VCu9sfcEKgnf2aJAQAaaQ528hJMtUtQIcXGAySKJAmsjQAduk+F5OEiK2CVoUQiNgSlk4w44J2bVJhu7YTwiuhfo5IQpqhISpJBfGCvFDedFMt5wbEFkUIPkMF+OpCeAG2TmYr/LoKB47Yqh5LF6oOp1JNlIYA+w0NwYiEcIJudQ2wnODlUIyQ5TMQjNiwpQqdDRkaolLCMgTCzmdRw3QVeiyJoAmBTEuHqWnIsAzoGpBhGd57USm9EOFMnw5ds5DtMyGcMFmTVNisqWnI9KlQ4G1FEewpiSHd1JHlMxCThJgTGqxrKmzX1FVIrgYVnKvWhRNqq6l+FoZjCMVU2Y0DlhNgrNap39CQbWiQRMi0DGc9R1Q7nbBgQxMwLF21U1NhunlpBn4viUFCBRwbTuivCn0GLFOFCKuQYg2aAEK2RJqhwSa1vxCpcGbDSc41dGcfsVWgrpvzrGvOy9nQNgEWAEkAOeHOkgAQIWQT/LpATBI0Aa/smCS4UdSaU7a7L/gMDbqzj7oZvtLZf4TTJxKl6b56DSb9qkt1lb/cxpfqKo4v1THGGGOMpYjPODHGGGP1FF+qq3k8cGKMMcbqKR441TweODHGGGP1lJQ2BA+cahTf48QYY4wxliI+48QYY4zVU2RLQFThjJPN36qrKB44McYYY/UUR67UPL5UxxhjjDGWIj7jxBhjjNVTJO2qXarjm8MrjAdOjDHGWD3FA6eax5fqGGOMMcZSxGecUkBOYFFhYaHK+XJfbo6cbkHEZXoBABlRiEgQEJrKpNMM9TPgZdVBiISsOgAgMwYRC6s8Ok136oiCjIi3jLBjKhdJ01VWnjuftCEixW6jIWJhkB5RmXVuVp1bTzQCEVVtlUXFKlctaoOiUScPTv1LdhRCNyE0HbKkGMKJMxNGFBQNQ0RUeXawWGXfGTFoUnhZdRQsAUkJTbNgFBYhGiwBABhFQVA4DDvo5LHFJLSYgAwXq6w6mBBRG7FgMSgShlkURCxYDFlcAiNYDIpFQCUloGgImqGWkSUl0DQLFA6pfhWHoOkl0M0g7GAJhBQQugm7uAS6vxix4hCErUE3iiGDJbCLQzCL1P+h6dBgQAZLIGLklFcCCB2aZkEGS6BBhywugab5IKLSK4/CIehBZ53GCNHiEghNg1kURKQ4BLMoCGGakCXFsItLYBYFIYPFAEnIkmLouh/CBihcAjtYDKMoiFiwBLovCM2GWrdaEagoCFlSDC0iIaK208Zi6P4iUDSk8gdtQAaLoRUWQURKQEZU5SEWBVXWn2EnZNXZtgEtWgIZcbZzNKSy75z9XYbVPuPu99BVFhtkDGTZAEkUShPQooC0UaJFIAmw98mqKwrbIFP93RaRBAEng0wSbKisuaiTe1ZiS8T00qy6onAMpiYQc/LTbAKiNkGaKlsuYghENQEbcJZR/wIqr83UBYIRCbI0lc+mCy/qqyhsw9QFbFODLQnBiAQiGmK2ykJzhWISlq4hGFHzk6WjqCSGmCSIiI5g2EZUVzlxgMqqC8ckwjGC3zYRiknoGmDL0hy7mJSIGRo0ISCJUBKV0COGl1UnSWW8lUQlRERDSVSiOBhB0LYgTQ22qSEm1ToOFoVVVl3USMiqs53cPlsSgiUxWDEDwZIYisMxBBGGoZW22TZVflywMIKYobLe9IjKqgsWq5xLQ1OZb0ZUfZR49ZfEUIgwikIx2M52NjUBTQg1TZaWL5xMONPLj1P9j9jktdlw8u8AQOoaQs52NZ18uAgRbENDUVTC0gQIQMzZ1+Kz6twMvKhemokYdvsrKSFjThNqv3KX1QS8f915VfvVfusuI8n5rIj77DiYKBqq2lkjO1p9jTlM8MApBe4vQbuuPWu5JYwxxuqLwsJCZGdnH5SyLctC06ZNsXXdgiqX1bRpU1iWVQ2tOjwIqokhcT0npcSWLVuQmZkJIWou9bqyCgoK0KpVK/z888/Iysqq7eZU2aHUn0OpLwD3p67j/tQOIkJhYSGaN28OTTt4d8SEQiFEIpEql2NZFvx+fzW06PDAZ5xSoGkaWrZsWdvNqLCsrKw6fXCpqEOpP4dSXwDuT13H/al5B+tMUzy/388DnlrAN4czxhhjjKWIB06MMcYYYynigdMhyOfz4c4774TP56vtplSLQ6k/h1JfAO5PXcf9Yaz68c3hjDHGGGMp4jNOjDHGGGMp4oETY4wxxliKeODEGGOMMZYiHjgxxhhjjKWIB06MMcYYYynigVMtiEQiuP/++9G5c2e0b98eJ5xwAt59992k827YsAEXXHABGjVqBJ/PhyOPPBKTJk1COBw+6HW7Pv30UwwdOhT5+fno0KEDbr75ZpSUlFSpTJdt2+jTpw/atm17SPTnhx9+wIQJE3DGGWdg/PjxeP755+tVf4qLi3H77bejc+fOaNmyJZo2bYqhQ4di1apVFerHweyPa+nSpejXrx9mzpxZLeXVh/7Uh+NBRfqzr7p4PGCsDGI1KhQK0YknnkhdunShTZs2ERHRggULyDRNWrBgQcK8X331FeXm5hIAMgyDAHivAQMGUHFx8UGr2/Xyyy+Tz+ejhx9+mIiI9uzZQ/3796e+fftSUVFRpcqMd++99xIAatOmTYX6Utf6E4lE6JZbbqHGjRvT7NmzybbtetefkpIS6tWrF3Xu3Jm++OILIiIKh8N0ww03kK7rtGTJklrvDxHR/PnzqVevXt7vwowZM8ptQyrl1Zf+1IfjQUX6k0xdOx4wlgwPnGrY+PHjCQCtWbMmYfr5559P6enptHHjRm9ar1696JxzzqGvv/6apJT0yy+/0KhRo7wD0oQJEw5a3UREmzdvpszMTBoyZEjC9G+//ZaEEDRu3LgKlxlv7dq1lJeXV+kDZV3pTzAYpJNPPpny8/P329+63p8pU6YQAFq1alXCvLZtU4cOHahZs2YVGhAejP4QEW3YsIFCoRB17Nhxvx/MqZZXX/pTH44HFenPvuri8YCxZHjgVIN+/PFHMgyDunTpUua9ZcuWEQAaPnw4ERF99tlndN5555GUMmE+KSX94Q9/IADUqlWrg1K367LLLiMASf9ac/+irGiZrlAoRN26daN//vOflTpQ1pX+xGIxOu200ygrK4vWr19foT7Utf6ceuqpBCDpmYtzzjmHANC2bdtqrT9CCFq3bp037bzzztvvB3NFy6vL/akPx4OKbp94dfF4UJH9gx1e+B6nGjR//nzEYjH069evzHu9e/cGACxevBi7du3CL7/8ggceeABCiIT5hBC48cYbAQA7duw4KHUDQDQaxcKFCwEg6TJ9+vQBgAqVGe/222/HCSecgD/+8Y8p96Eu9uf222/HK6+8ggceeADt27evVF/qSn8CgQAA4IMPPigzf2FhIZo3b45GjRrVWn+ICNOnT/em7S8VvjLl1eX+1IfjQUX6s6+6eDyoyP7BDi88cKpBS5cuBQC0a9euzHt5eXlo0aIFIpEIVq5ciaFDh5Z7g2THjh0BAG3atCnz3pQpU5CZmYmHHnqo0nUDwHvvvYeCggL4fD60aNGizDLdunXz/p9qma73338fS5cuxYMPPpi0f/WlPz/88AMefvhhtGzZEpdddtkB+1LX+3PGGWcAAMaNG4dgMOjNu2vXLrz33nt46KGHynxw13R/VqxY4U3bty3xKlNeXe5PfTkepNqfeHX5eLDv/sEYwAOnGrV27VoAQMuWLZO+n5OTAwD47LPP9lvOzp07AQDDhg0r896sWbNQVFSE2bNnV6lud/5kB5X4+QGgefPmKZUJAMFgEGPGjMHMmTORlpaWdLl4dbk/Dz74ICKRCP785z9j+vTpGDZsGDp27IgjjjgCN998M4qKiupVf0aOHInBgwfju+++w+DBg7F7925IKXHVVVfhqaeewsiRI2u9P19++SVs2046T7L6K1peXe3P/tSl40FF+1PXjwfVsX3YoYcHTjUkFAp5H6TxH2rxsrOzAZQeCMvz5ptvwu/349prry3z3q233opjjjkGt956a5Xqdk/7lzd//EHONM2UygSAG264Aeeffz6OO+64pMvsq672JxaLYfHixQCAzz//HF27dsWiRYuwZs0a9OzZEw8++CAGDhyI4uLietEfANA0DS+99BIGDRqE999/H/3798cVV1yB2267DRdffHHSMmqqP+78sVgMe/fuTTpPvMqWV1f7sz914XhQ2f7U1eNBdW4fdugxarsBh4v4+2LS09OTzqNpahwbCoXKLSccDuPZZ5/FbbfdlvSvqxEjRmDEiBFVrttdprz548+m6LqeUpmvvfYaPvvsMzz11FNJ50+mrvbn66+/9sp8+eWXvQNwXl4eZs6ciQ8//BCffPIJ7rrrroRLEHW1P/H1//vf/8att96K9957D9OnT8ePP/6IhQsXIjc3t0wZNdUfd/5921ueypZXV/tTnrpyPKhMf+ry8aC6tg87NPEZpxpiWZb3fyJKOk8kEgGgPnzLc//996NDhw645ZZbDmrd7jLlzR8/PTMz84Bl7t69G9deey1mz54Nw6jaeL0u9OeXX34BoA68+/7V6vP5vHueUnn4X13oj2vTpk34y1/+gscffxzvv/8+/vCHP+Ctt97CgAEDsH379gP25WD1x51/3/YeqA3VUV5d6E956srxoKL9qevHg+raPuzQxAOnGpKXl+f9ssbfeBtvz549AICGDRsmff+jjz7CvHnz8OKLL5Z7FqG66m7atOl+54+/7h+NRg9Y5rhx4zB+/Hh07tw55XaXpy70p6CgAACQlZWVdN6hQ4cCUJcEDnTptS70B1CXMQYOHIgLLrgApmkiOzsbr776Ko4//nisW7cOo0aN2m8/DmZ/3PkDgUBK39aqzvLqQn+SqUvHg4r2p64fD6pj+7BDFw+caoiu6+jSpQsAYMuWLUnn2bZtGwCgR48eZd7bunUrxo0bh//85z9o3LjxQa+7e/fu+50//qvPByqzadOmmD9/Pq699loIIRJe+fn5ANSZDnfaTz/9VKf706NHD+9r+e4Aal/xl02klEnncdWF/gDAbbfdhi1btuCUU07x5klPT8eSJUvQqlUrLF++PKXolYPRn/39biRTneXVhf7sq64dDyrSn19++aXOHw+qun3YoY0HTjVo0KBBAICvv/66zHs7d+7E3r17EQgEcPzxxye8V1hYiBEjRuCf//wnOnXqVCN1n3jiibAsC9u3b096xmT9+vXe/1Mps3Pnzklf7teHDcPwppV3M3Nd6s///d//Qdd1FBcXJz2wu3+l5ubmpvTso9ruDwAsWrQIeXl5ZS6d5OXlec8K+vDDDw/Yl4PZnyFDhqRUf3WXV9v9iVeXjwep9EcIUW+OB5XZPuwwUHPP2mTff/89aZpG3bp1K/Peyy+/TABo9OjRCdOLiopo0KBB9L///S9pmalGfFSmbjfO4aWXXiqzzP/93/+REKLCZe7rxx9/rNSTgutCfwYNGkQA6Kmnnioz/5dffkkA6JJLLqk3/cnOziZN0ygcDpeZf+nSpeX2tab6o2kaff/99960iy66aL9Ppq5oeXW9P0R1+3hQmf7sqy4dDyqyf7DDCw+catiVV15JAGjt2rUJ088++2xKS0ujDRs2eNOKiopo8ODB9Prrr5cpR0pJS5cupTPPPDNh+rx58+jYY49NGiNQkbqJiNavX0+BQICGDRuWMN0dFIwdO7bCZe7rQAfKutyfTz75hAzDoE6dOlEoFEqY/8Ybb0yaj1WX++N+0L3wwgtl2nb77beTZVleeGpt9SfeBRdcQABo+vTpZequTHl1vT/14XhQkf4kU9eOB4wlwwOnGlZUVETHHHMM9e7dm3bt2kVSSpo6dSpZlkULFy705tu9ezf17duXLMuiBg0aJLxyc3PJNE0CQM8++2xC+UcddRQBoK5du1a67nhz5swhwzC8D9NNmzbR0UcfTf3796dgMFipMuMd6EBZ1/szffp0AkAjR46kYDBIREQvvfQSZWRk0KJFi+pVf7Zv304dO3akhg0b0uuvv05SSpJS0rx58yg9PZ3+8Y9/1Hp/XMXFxdStWzcCQGPGjElaVkXKq+v9qS/Hg1T7U566djxgLBkeONWCgoICGj9+POXn51P79u1p2LBh9PnnnyfM44a07u/l8/lo9+7dCcv9/e9/p0AgQPfff3+l697X8uXLqW/fvpSfn09HHXUUTZkyJeFyTmXKdB3oQFkf+vPKK69Qnz59KCcnh4488kg644wz6KOPPqqX/dm1axfdcMMNlJ+fT40aNaIWLVrQ4MGD6e23364z/Rk+fDilp6cn/C7k5eXRM888U6ny6kN/6tPxoKLbJ15dPB4wti9BVM6DLBhjjDHGWAL+Vh1jjDHGWIp44MQYY4wxliIeODHGGGOMpYgHTowxxhhjKeKBE2OMMcZYinjgxBhjjDGWIh44McYYY4yliAdOjDHGGGMp4oETY4wxxliKeODEGGOMMZYiHjgdpoqLi9GzZ0/07NkTxcXFtd0cVgU7duzApEmT0LJlS7zzzju10oZ77rkHubm5WL58ea3UXxcQEaZNm4ajjz4afr8feXl5GDZsGD7++ONyl/n0008xdOhQ5Ofno0OHDrj55ptRUlJSbeVXtI7KWrNmDUaPHl2tZdakbdu24eabb0b37t1Tmn/x4sUQQpR5DR8+/CC3lNUJtRuVxyprz549CQGa7dq1o/bt21Nubi4BIL/fT+3bt6f27dtT8+bNSQhBAGjq1KlERPThhx96y5cXSFuXtGnThgB4fWrfvj1Nnjy5tptV65YtW0Z/+tOfvG25YsWKWmlHly5dCABdffXVtVJ/dSkpKaGnnnqK2rRpQz/++ON+5920aRNdcskllJ+fT02bNqWcnBxvO+i67v3fNE2aP38+NWzY8IBBvb169aK+fftSUVGRV8/ChQvp2GOPpczMzHLLf+mll5K28eWXXyafz0cPP/wwEanjRr9+/ah169bUoUMHateuHf3hD3+g//3vfwdcN1u3bqW//e1v1K1btzLvDR8+nHw+H23btu2A5ezbr/z8fOrWrRs9++yzB1ymItsnFT///DNdf/31lJaWtt9w4X0dd9xxSbffBx98UOU2sbqPB0711C+//ELp6en0+uuvJ0y/8847CQD1798/YfrGjRvpmGOOoUmTJhERUTQapREjRtCIESMoGo3WWLsryx04seTat29fqwOnWbNmUZ8+fejTTz+tlfqrKhgM0pQpU6hVq1beh+D+Ppg/+eQTysnJoZtuuonC4TAtW7aMMjMzSdd1+vOf/0zhcJiWLFlCjRo1IgDeB/P+Xr1796Zvv/2WhBA0btw4IiKaMGECZWRk0AMPPEANGzakyZMnU4MGDejqq69OKD8rK4t27NiR0MbNmzdTZmYmDRkyxJsWCoWod+/eBIAuvPBCIiJasGABmaZJCxYsSNrXAw0ufvnlFzIMgwDQvffem9L6dvv1zjvvEBHRN998Q40aNaJrr7026fwV3T6p+vXXX6mkpISef/75lAdOb7zxBg0YMIC++eabhNd3331X5faw+oE/ieqpb775hm6++eYy08sbOBERffXVV3TLLbfURPOqHQ+c9q9fv361OnCq7woKCmj79u20fv160jRtvx/MwWCQ2rRpQ7169fKmnXfeebR27Vq67777CAA99NBDRET05ptveh/0p5xyCn3++ee0detWuuCCCwgATZ8+nbZs2UKZmZk0ZcoUIiLq1asXCSFo6tSpBIAeeOABr3wiomnTphEAmj9/fkL5zz33XEI7L7vsMgKQMCAaP348AaCjjjqKhBC0bt06IiI6//zzKT09nTZu3FimvwcaXNxyyy3e2bAWLVoc8A+xxYsXe/2KF9+vfVVk+1TGunXrUh44nXTSSfTqq69WW92s/uFPonrqu+++o1WrVpWZvr+BExGVObjWFzxw2r8TTjiBB07VpHHjxvv9YHY/4O+66y5v2hNPPEFERLt37ybTNCknJ4cKCwuJiOioo44iAHT//fcTEVEkEqGsrCwCQL/88gstW7aMANCmTZuIiOgvf/kLAaCcnBwSQtC2bdu88omICgsLSdd1atGiBcViMerZs2dC+cnqICL68ccfyTAM6tKli1fHDTfcQETktWH48OHlrpdkg4vi4mJq2LAhvf7662SaZrkDH5dt29SxY0evX/H27Vd5DrR9KmPjxo0pDZzWrFlDfr+f/vGPf9A333xTbfWz+oVvDq+nOnXqhL59+1Z4uUsvvfQgtIaxQ4ff79/v+2+99RYAoHnz5t60a665BgCQk5ODY445Bnv27MFrr70GADjyyCMBAG3atAEAvPfeeygoKIDP50OLFi2wcOFC9O7dG61btwYAdOvWDQCwZ88etG/fHo0bN/bKB4CMjAwcddRR+PXXX7Fs2TJ07NgxofxkdQDA/PnzEYvF0K9fP6+OFStWAAB69+4NQN30vGvXrpTXywsvvIBjjjkGf/rTn3DOOecAAJ544oly193IkSPxww8/gIjQpEmThC8z9OnTB7Zt49dff01Yt/GeffZZ7N69GwDQrl0776bs7OxsdOzYEVdccUW5de+PECKl+f7+978jFArhyiuvxJFHHonjjjsOr7/+eqXqZPUXD5wOU2vXrsXYsWORkZFR5r333nsPAwcOxF133QUAWLRoEbp27YqMjAycccYZ2LZtGwD1zbybbroJTZo0QW5uLq677jrEYrEy5cViMUydOhW9e/dGy5Yt0bBhQ1x44YX4+eefq60/RUVFuO6669ClSxc0atTIO6Bed911ZeZdt24dzj//fK9P3bt3x/PPP5+03L1792LChAk46qij0LZtW7Rv3x433HCDd/COZ9s2nn76afTt2xedO3dG48aNcfrpp+P9998vM+/u3btxxx13IDs7GwCwfft2XHjhhcjOzkb79u3x0ksvldvXGTNm4Nhjj0WHDh3QqlUrTJw4Mel6B9QHY79+/dC+fXuYpumtlz179pRbfkWX//333/HII4+gU6dOmDlzZsLy33//PUaPHo1TTjkFAPDJJ59g4MCBCAQC6NOnD7766quk9W7duhVXX301OnfujFatWuGII47Afffdl/TbYD///DMuv/xydO/eHVlZWejUqRMeeughSClT6uO+DvQh+vvvvwNQ+0Yy7gDmo48+8ub3+XwYPHgwAPW7BwAtWrRANBrFf/7zH5x33nne8jk5Od7/8/Pzk9YRP/DZuXNnQvn71uFaunQpADXgcOv48ssvYds28vLy0KJFC0QiEaxcuTJpncnWy9SpU3HjjTcCAK6//noAwPvvv4/PPvssaRmdOnUCAJimWea9r776Cv369QMAhEKhMu+PHTsWY8eO9X5nVqxY4Q0227Ztix9++AHTpk1LWm912LVrF3bu3InOnTtD13UAwMcff4zBgwfj+uuvBxEdtLpZHVPbp7xY9TrQpToiosmTJ1OPHj28eyNcP/74o3fvBQC688476ZlnnqG0tDRq1qyZN33IkCFUXFxMAwYMoJycnIRvC913330JdUUiERo0aBCNGTOGiouLSUpJTz75JAGg5s2b05YtW1Lq14Eu1f35z3+mESNGUElJCRERvfvuu9SoUSMaP358wnyvvfYatW3blt577z0iUje+uusi/tILkfrWVMeOHemaa66hUChEREQPPPCAd49IMBj05g2FQjR48GDq168f/fbbb0RE9MMPP1DXrl1JCEH/+Mc/vHmfeOIJatmypbfONm/eTPn5+dSsWTNKT08nAGQYBq1fv75MPy+77DLKzc2ld999l4iItmzZQn379k36rbqPP/6YsrKyvEu6RUVFNGbMGAJAu3fv3t/qTnn59957j8466yzvW5szZswgIqJwOEx/+ctfyO/3EwA64YQTaPny5ZSRkUGtWrXyvhXWsWPHMpdlPvvsM2rcuDHdf//9FI1GSUpJV199NQGgk046iaSU3ryffvoptW7dmpYsWUJERLt27fK+ZXjxxRcfsI/JuPtaeZeCLrroIgJA5513XtL3zzvvPAJAl156KQWDQUpLS0v4tuHNN99MAOj//u//6NVXXyUhhHeZjoho+fLl3va84IILktbhro8//OEPZcrftw5XRkYGAaDZs2cn1LFr1y4iKr2kePfddyet88cff0y4nLV8+fIy37Bz77W79NJLk5Zx2mmnEQBq0qRJ0kvLF154IQHqW8Hx3n77be8+sfjt89xzz3n9cC9JVsa+fTuQ3bt30/PPP59wXLz99tsrXT+rX3jgdIhJZeBEpAYM+w6c3MHBueeeSwBowIABdOedd3r3arz44osEgIQQNGLECJo9e7b3oXfXXXcRAOrcuXNCPXfccQd17dq1zIfjqaeeSgBo9OjRKfVrfwOnzZs3EwD673//mzB91qxZCQOnnTt3Ul5eHs2bNy9hPvfRDJqm0Q8//EBERFJK6tWrF3Xp0oVs2/bm/e2337z1Fv8V8AkTJpAQgjZs2JBQ9rfffkumaZKu6/Thhx8SkRpUfPfdd145I0aMoPfff5+I1H0e7gfYvo9bePrppwkAvfDCCwnT169f7w1c4j+ILr30UjrmmGMS5o1Go9SxY8eUBk4VWf7kk09OGDi5/XTvB2rXrh2df/759NNPPxGR+nKDZVkEgFavXu0tEwwGqW3btjRo0KCE8levXu2tr08++YSI1KC8Q4cOCff2EKmvzbs3EL/99tsH7Oe+DjRw+s9//uN9uMcPeFz9+/cnAHTllVfS448/To0bN/YGJ0TkDT4HDBhAl156KfXp0ydh+fgbvseOHZu0DRMnTiQA1KxZszLl71sHkfoav1vmyy+/nFDHr7/+SkSlg57yvtm27+Bi6NChCdubSH1Dz103O3fuLFOG+40+9w+HfQdOV111FQHqEQvxbrjhBgJA119/fcL2KSgo8PqxZs2apO1ORUUHTq69e/d629s0zaQ317NDD1+qO0w1adKkzDSfzwcAaN++PQCgV69euOuuu7zLeWeffTbat28PIsKIESMwatQo75T1uHHjAACbN2/2yotEIpg6dSr+/Oc/e/O53AfNLV68uNKXVFzbt28HAEybNi3hktXw4cORmZnp/fz888+jsLAQw4YNS9oWKSUWL14MQF3W+PDDD3HJJZdA00p/TZo2bYpbb70VQ4YMQa9evQCoy26PPPIIjj76aLRr1y6h7M6dO+PMM8+Ebdu45557AACWZaFt27bePE888QT69+8PQN2/4j5EL35dlpSU4Pbbb0deXh5GjBiRUEf79u3RtWvXpOvls88+S7j0YhgGLr744jLzJlOR5ZPtT/H9zMjIwAsvvOBdxjriiCMwYMCAMv18/vnn8dNPP2HMmDEJZR133HEYO3YszjzzTO+eniVLlmD9+vXevTXxbWncuDEA4MUXX0yprxVxxhlnYNSoUQiFQjjttNPw9ddfAwB++ukn3Hzzzd4luoYNG2LSpEmYNWsW8vLyvOUtywKg9rclS5bg3HPPTSg/Eol4/49fLp67T27fvr1M+fF1kHP5KP6+pfT09KR1uGUmu0y2rx9++AFr167FyJEjE6afddZZaN26NUKhEKZPn15mObcd8b9TyfpF+1z2im9vvMzMTOTm5gJQ+2ZNy8rKwrJly9CmTRtEo9H9XmJnhw4eOB2mkt1j4HIHUPGDDpd706Z7n4GrYcOGAJBwD8ratWuxZ88eTJ8+HUcccUTCa+7cuWjQoAEsyyr3ZtRUdenSBU2aNMErr7yCY4891rsp1+fz4d577/Xme/vtt0FE6NGjR0Jbjj76aDRo0AANGjTwBmHLli0DAO9DOt59992HZcuWoWXLlgCAl156CeFwOGEwFG/o0KEAgDfeeMP7AIhf/+66czVr1gxA4rp85ZVXsGvXLvTs2TPpB0SyD9gTTzwRtm3jpJNOwl//+lfs3LkTADBx4sSE+2jKU5Hly9uf3Om5ubllBs/J+lneetd1HdOmTcOiRYu8/fLtt98GoNbvvvuXlBINGjSo8r5VnlmzZuHpp5+G3+/HoEGDcNJJJ+GZZ57BkUce6W3j//3vf/jrX/+acO8RoAbfgHpa9e7du8sMnOLvH9t3nbncOlq0aFGm/Pg6gsEggNKBFKAGJW4dgUDAu+n7gw8+AADMmTMHDRs29F7J7nl6/PHHEYlE0L1794T1ftRRR3nb8+mnn4Zt2wnLxbcjmWg0CqDswMr9IsymTZvKLENEsCwLRxxxhDdt2LBhCX1wXw8++OB+66+MrKws3HbbbQCADRs2VHv5rO6p+SE6q9cO9JdiPPdMwh133OGdkToY0tLS8NJLL+G8887D559/7p0NevTRR72bTd325OXl4dtvvz1gmT/99BMAlDnwJ7Nu3ToA5d9U7H6rKhwOY/v27WjZsuV+b0B2B0bxf3XHn8VI1V/+8hesW7cOzz33HKZMmYJnnnkG1113HSZOnIj09PSDvjyw/xutk/WzIuvd3b/Wrl2LtLS0lNpTXYQQGDduXJn9evz48QDUHx09e/bETTfdVGZZ9wznr7/+it69e6NVq1YJ77tfvgBKBz77cr8N594kvnLlyoQzqe7A6vPPPwegBtaWZSESiSAYDHp19OjRw1vGPVtbUlKSMJh1BzMuKSXmzZuHb775Bo0aNUp4r2HDht4Z5M2bNyMnJwc+nw//+c9/0L9/fzRt2hTr1q0rd/sWFBQAKDtgPPfcc/HUU09h+fLl3hkmQH0xYM+ePbjooosS9sm9e/cmHTQfrHgp98sPyb5sww49fMaJHTTugfj7778/6HX1798f33zzDW699VZkZGTgww8/xIABAxK+Gh2LxbBjx46UvlHmHvxT+QvSPRj/+uuvSd+PP9BnZWUdsLxk3G/x7fshtj+GYWD69OlYsWIF+vTpg2AwiEmTJuG4447zzqwdzOUroyLrvSb3r1Ts3LkTs2fPBqAu0T722GNJ5zvxxBNhWRZCoRBOPfXUMu+vX7/e+/+WLVvKvD9nzhxs3boVQOnAJxqNYteuXd6rsLAQgBqU7ty5E7quo0uXLl6Zbh1DhgzxynXPIr/xxhsgdf8riAgDBw5MqL+oqAhDhgwpM2gC1KW4+G+cFhUVYdeuXd5+6w4ay7v05p7V3PfMlGmaWL58OTp16uQNiAoKCnD11VejXbt2eOihhxLmf+eddxL64L7cbwpXN/fsaZ8+fQ5K+axu4YETO2jcg8miRYvK/br8qlWrEA6Hq6W+rKws3HfffVi/fj1GjhwJIsINN9zgncVo1qwZiAgLFixIujwRec+VcS/DlTevlNL76r17T9iGDRuS/iXt9r1169aVHji5l+KSXao4kIEDB2L16tV48cUX0bhxY6xbtw4TJ06sseUr4kDrvaioyHvP3b/mz59fbnnu5byacNttt2HPnj3IysrCu+++W+Zsm23b+Pnnn5GVlYXjjz8eQPJ7w1avXu2dwXXvn3ItWrQIS5Ys8S5XugOfgQMHIhaLYfPmzd4gYdSoUQCAd999FwAwaNAgr0y3DvcxCDt37sTevXsRCAS8tpWnoKCg3DPIbt1vvvmmN+2LL77wBl9uG9wzWu6jHVwbN24EkPx+pSeeeAK//vqrd4bSvZ9q9erVSQdxNemrr75Cfn4+TjvttFptB6sZPHBiB82xxx6LtLQ0bN68GTfffHOZ94uLi/Hggw9691RV1scff4x//vOf3s9NmjTB3LlzcdZZZyEWi+HDDz8EAPzhD38AANx6663eATrerFmzvL/w3QP9xx9/jFdffbXMvNOmTfPaffrppwNQf20vX768zLzu86rin9VTUe49Hp9//jl27NhR7nzxl73GjRuXcOP92WefjTfeeAOAGrAeSFWXrwx3vS9evDjpM57uvfde79KWuz0fffRRbxvHe+edd7BmzZqD0s59LV26FNOmTYNpmli1alWZS4dbt27FxRdf7O13DRo0gKZp3j1drq+++gqffvopLr30UuTn5+Obb77xtveSJUswa9YsPPXUU/j222+Rn5/vneHYt3wAuPPOOxEIBLyzYJdddhk0TcPy5cvx6aefYsyYMd69ZKtXrwagtnEqv4/xl8CTOfHEE73B/uTJk73pp5xyCvLz81FUVARAPZPMvRn9xRdf9M40FhQUYOfOnd7+/MEHH2DixIm45557vEHS8uXL8eSTT3pfBKgK94+b/V0illImfX4bANx///14/vnnq3wsY/VEDX17j9WQG2+8kQBQz5499ztfOBz2vsYbiUQS3nO/6nzrrbeWWe74448nAPTmm28mTJdSJi3PjXYAQOeccw6tXLmSfvnlF3rzzTepX79+9OSTT6bUr/09juCjjz6ibt26ec9wcrlZX+5X/X/++WcKBAIEgBo3bkzPPPMMbdy4kb777jt64IEHqFOnTt6jF0pKSqh169YEgHJzc+lf//oXFRcX02+//Ub33nsvde7c2Xt8AxHRiBEjCECZr9ETEV1//fWUm5ubEDER//XwfbO9ZsyYQQBo5MiR3rRIJEL5+fkEoMyzqYhKI1eWLl3qTRs6dCjNmTOnzLx5eXl0yimnJF2X8Sqy/Pnnn08A6J///GfC9FdffbXcx2O4z0OKX+a3337zokJatWpFr776KoXDYfrpp59o/PjxCeUEg0HvOTpuEO73339PGzZsoGnTplGbNm0q9WyfFi1aEICkz9FK5o033iCfz0cAKDMzkxo0aJDwcnPcWrVqRVJKikaj1LBhQ7rgggvIMAzv8RKbNm2io48+mvr370/BYJDmzZtHAOjRRx+lOXPmkGEYlJOT4+3DGRkZScuP5y7n1uE+p61Hjx4JzyE7++yzKS0trczjNOK9/vrrBIB0XU/6qIF4v//+uxdAjH0eU+H2y31lZmZSkyZNqHnz5gnT27RpQ9OnTyciohdeeCHhPfclhKCMjAzq169flfLj3PItyyp3HZx++umk6zqNHz/ee/zD9u3b6frrr6fXXnut0nWz+ocHToeQPXv2ULdu3bznqOwvS8k9CAKg5cuXe9Nt26aBAwd6g4D4A/HWrVu9h13um4L+zjvveOW99dZb3vRgMEh9+vRJetAbOnRomQN9eQ40cAJAgwcP9p698/vvv1Pv3r1p8ODBCXXMnz/fS3KPf/l8Pu+hkq5Vq1Z5Dw2Mf2VkZNAHH3yQMO+ePXvo6KOPJgD0t7/9jUKhEEkp6d///jfl5eXRsmXLEuZ/6623vPL+97//Jbx37bXXEgDq1KkTFRcXe9M/+OADrz2TJk2iSCRCUkqaMWOGl1w/ZswYWrVqFcViMRo6dCgFAgGaOXOm9xytuXPnkmVZXir9/qS6fDAYpPbt25cZ7BER3X777QSAGjVqlPBhG41GvYy1UaNGJSyzaNGipNuoadOmZQYz7777rjeQ2PcDdd/ndaVi48aNXuZaskFjvLVr19KVV17pPTPqQK+//e1vRKQeHCmEoM2bN9Py5cupb9++lJ+fT0cddRRNmTKFwuGwV8cVV1xBmZmZ3nO6Uil/X/F1HHnkkdSyZUs67rjjaNeuXSSlpKlTp5JlWbRw4cJy+zpp0qSENliWVeahm65HH33Ue/Bp/Cs3N9fr2xVXXEGBQIAaNWpEWVlZNHjwYMrMzKRLL72UGjZsSPfeey/t2bPHK1NKSRdffDG1atUqYRvHl6/ruveMr1R98MEHCQ+xBNTDZzt27Fhm3hUrVtBxxx1HgUCAcnJy6PTTT6f777+/zDO02KGPB06HiFNOOcV7oKD70jSNWrdu7T3J2jV69Gjvyc3uAWfkyJH05ZdfUl5eXkIZeXl5tHz5crr77ru9v6rdV5MmTej333+nwYMHJ3x4aJpGY8aM8eorLi6mO++8k9q1a0eWZVHbtm3pjjvuSPiAOJBUBk7uq3nz5tS1a1e67777Es4KuVatWkWDBg2izMxMCgQC9Mc//rHch+d9/fXXNGzYMMrKyqLMzEw688wzyx2QBoNBuv3226lDhw7UoEED6tatG40ePZq+/vrrhPkuueSSMuv/j3/8I33//ffUtGnTMn+Nxw+6vvrqKzr99NMpIyODmjZtSmeeeSYtXLiQBg4cSN27d6cbb7yRXnvtNW/g5Jbj9/upU6dONHjw4JQ/XFJZ/r///a93hsh9NWrUiH777Tfq2LFjwvT09HS64447aPbs2ZSdnV1mmd9//90rd+XKlXTyySdTeno65eXl0UUXXeQ9qHFf69ato3POOYdyc3PJ7/dT3759K3UGoHXr1mUGbM2aNaO1a9cmzDdz5kzKzMykli1b0vDhw+n111+vUD2XX3459e3bN6V5pZT0xBNP0JFHHknt2rWjvn37ek9Jr6yCggIaP3485efnU/v27WnYsGH0+eeflzt/RQYXqapov7Zs2UJ+vz/h98bdPmvWrKEffviBzjrrLLrpppsq3SbGUiWIOGCH1X1t27bFpk2bOA+KscPQH//4R1xyySVlHrgZb+nSpXjjjTfK/TYjY9WFbw5njDFWZ7322mt48803D/hk8H/9618Jj1dg7GDhgRNjjLE6y/2m4FVXXYXnnnsOe/fuTXj/p59+wqWXXoqSkhLvcQeMHUx8qY7VC3ypjrHDk/vAzffffx+Aemp7s2bNkJ6ejr1792LHjh0499xzMXv2bC8+hrGDic84McYYq7MyMjLwzjvv4Nlnn8UJJ5yArKws7NixA0VFRRgwYABeeeUVLFiwgAdNrMbwGSdWL7hnnNyndAPAmDFjcMstt9RiqxhjjB1ueODEGGOMMZYivlTHGGOMMZYiHjgxxhhjjKWIB06MMcYYYynigRNjjDHGWIp44MRYHRKJRHD//fejc+fOaN++PU444QS8++675c7/6aefYujQocjPz0eHDh1w8803o6SkpEbqri/1RyIRdOjQwXvl5eVBCIGZM2dWqp2MscNcbYXkMcYShUIhOvHEE6lLly60adMmIiJasGABmaZJCxYsKDP/yy+/TD6fjx5++GEiItqzZw/179+f+vbtS0VFRQe17vpc/5133kkAaMaMGRVqI2OMERHxwImxOmL8+PEEgNasWZMw/fzzz6f09HTauHGjN23z5s2UmZlJQ4YMSZj322+/JSEEjRs37qDVXd/r54ETY6wqeODEWB3w448/kmEY1KVLlzLvLVu2jADQ8OHDvWmXXXYZAUh6NqZXr14khKB169YdlLrre/08cGKMVQXf48RYHTB//nzEYjH069evzHu9e/cGACxevBi7du1CNBrFwoULASDp/H369AERYfr06dVeN4BDrn7GGKsIHjgxVgcsXboUANCuXbsy7+Xl5aFFixaIRCJYuXIl3nvvPRQUFMDn86FFixZl5u/WrRsAYMWKFQnTp0yZgszMTDz00EOVrhtAva2fMcaqAw+cGKsD1q5dCwBo2bJl0vdzcnIAAJ999pk3b7JBQ/y8X375JWzb9qbPmjULRUVFmD17dqXrjp+/vtXPGGPVgQdOjNWyUCiEoqIiAKUf+vvKzs4GAOzcuRM7duxIad5YLIa9e/d602+99VYcc8wxuPXWWytdN4B6Wz9jjFUHo7YbwNjhzr13BwDS09OTzqNp6m+cUCjkPafoQPO687tGjBiBESNGVKnu+GXqW/2MMVYd+IwTY7XMsizv/0SUdJ5IJAJA3fPjzn+ged35q7Pu+GUOhfoZY6yieODEWC2LHwwFg8Gk8+zZswcA0LBhQzRt2jSleQOBAPx+f7XWDeCQqp8xxiqKB06M1TJd19GlSxcAwJYtW5LOs23bNgBAjx490L1795Tnre66ARxS9TPGWEXxwImxOmDQoEEAgK+//rrMezt37sTevXsRCARw/PHH48QTT4RlWdi+fbt3w3S89evXAwCGDBlS7XUDOOTqZ4yxiuCBE2N1wGWXXQZN05KG2q5evRoAcPbZZ8Pn8yErKwvDhw8HgHLn1zQN5513XrXXDeCQq58xxiqk1p5ZzhhLcOWVVxIAWrt2bcL0s88+m9LS0mjDhg3etPXr11MgEKBhw4YlzPvll18SABo7dmyZ8ufNm0fHHnts0piSitRdX+t3ceQKY6wqeODEWB1RVFRExxxzDPXu3Zt27dpFUkqaOnUqWZZFCxcuLDP/nDlzyDAMeuGFF4iIaNOmTXT00UdT//79KRgMlpn/qKOOIgDUtWvXKtddH+t38cCJMVYVfKmOsToiEAhgxYoV6NOnD4499lh07NgRb731Fj766COcc845Zea/4IILsGzZMjz99NNo164dTj31VIwaNQpvv/120mccXXDBBQgEArjwwgurXHd9rJ8xxqqDICrnYSiMMXYIuuuuu3D33XdjxowZuPjii2u7OYyxeobPODHGGGOMpYgHTowxxhhjKeKBE2OMMcZYinjgxBhjjDGWIqO2G8AYYwdTJBLxYl0A4Pfff6/F1jDG6jv+Vh1jjDHGWIr4Uh1jjDHGWIp44MQYY4wxliIeODHGGGOMpYgHTowxxhhjKeKBE2OMMcZYinjgxBhjjDGWIh44McYYY4yliAdOjDHGGGMp+n+qcFmczgu9rgAAAABJRU5ErkJggg==",
+            "image/png": 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",
             "text/plain": [
               "<Figure size 640x480 with 2 Axes>"
             ]
@@ -955,7 +956,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 38,
+      "execution_count": 6,
       "metadata": {},
       "outputs": [],
       "source": [
@@ -973,7 +974,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 39,
+      "execution_count": 7,
       "metadata": {},
       "outputs": [
         {
@@ -1359,11 +1360,11 @@
               "    coverage_content_type:  coordinate\n",
               "    units:                  m\n",
               "    long_name:              Profile Range\n",
-              "    description:            Distance to the center of each depth bin</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'range'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>range</span>: 28</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-659c59d0-8c33-46d3-b3e2-c2de7a41df9b' class='xr-array-in' type='checkbox' checked><label for='section-659c59d0-8c33-46d3-b3e2-c2de7a41df9b' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.2 1.7 2.2 2.7 3.2 3.7 4.2 4.7 ... 11.7 12.2 12.7 13.2 13.7 14.2 14.7</span></div><div class='xr-array-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+              "    description:            Distance to the center of each depth bin</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'range'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>range</span>: 28</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-27183307-48d8-4334-9d4f-9e05d7a24cc7' class='xr-array-in' type='checkbox' checked><label for='section-27183307-48d8-4334-9d4f-9e05d7a24cc7' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.2 1.7 2.2 2.7 3.2 3.7 4.2 4.7 ... 11.7 12.2 12.7 13.2 13.7 14.2 14.7</span></div><div class='xr-array-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
               "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-              "       13.2, 13.7, 14.2, 14.7])</pre></div></div></li><li class='xr-section-item'><input id='section-df55617f-6d69-4336-9190-b5d4fced1165' class='xr-section-summary-in' type='checkbox'  checked><label for='section-df55617f-6d69-4336-9190-b5d4fced1165' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-a0492840-a7e8-45bf-9adc-2921795ad182' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0492840-a7e8-45bf-9adc-2921795ad182' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5296d03-5d36-4a6a-9850-8fdd6389762b' class='xr-var-data-in' type='checkbox'><label for='data-a5296d03-5d36-4a6a-9850-8fdd6389762b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+              "       13.2, 13.7, 14.2, 14.7])</pre></div></div></li><li class='xr-section-item'><input id='section-0182f8e5-1c9b-476b-af6c-5e3eaa33364e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0182f8e5-1c9b-476b-af6c-5e3eaa33364e' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-8ce42991-ade4-4c8c-b8e4-ef266c967ef8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ce42991-ade4-4c8c-b8e4-ef266c967ef8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-127f377e-0b3a-46b3-9028-0af3c4ab733e' class='xr-var-data-in' type='checkbox'><label for='data-127f377e-0b3a-46b3-9028-0af3c4ab733e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
               "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-              "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b1d0b5c0-8ae8-4f1f-8fa0-4fa9b227fd1a' class='xr-section-summary-in' type='checkbox'  ><label for='section-b1d0b5c0-8ae8-4f1f-8fa0-4fa9b227fd1a' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-c6b563ca-ca92-4e50-b099-0c5743f93b02' class='xr-index-data-in' type='checkbox'/><label for='index-c6b563ca-ca92-4e50-b099-0c5743f93b02' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               1.2, 1.7000000000000002,                2.2,\n",
+              "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8e8bb7c5-5914-419d-a3aa-7e595f1cc63d' class='xr-section-summary-in' type='checkbox'  ><label for='section-8e8bb7c5-5914-419d-a3aa-7e595f1cc63d' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-eeb0489d-3509-4e51-8c17-c60ea011f3f3' class='xr-index-data-in' type='checkbox'/><label for='index-eeb0489d-3509-4e51-8c17-c60ea011f3f3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               1.2, 1.7000000000000002,                2.2,\n",
               "                      2.7,                3.2,                3.7,\n",
               "                      4.2,  4.699999999999999,  5.199999999999999,\n",
               "        5.699999999999999,  6.199999999999999,  6.699999999999999,\n",
@@ -1373,7 +1374,7 @@
               "                     11.7,               12.2,               12.7,\n",
               "                     13.2,               13.7,               14.2,\n",
               "                     14.7],\n",
-              "      dtype=&#x27;float64&#x27;, name=&#x27;range&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-23141fce-2350-4970-af07-1aa47e3ab02e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-23141fce-2350-4970-af07-1aa47e3ab02e' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div></li></ul></div></div>"
+              "      dtype=&#x27;float64&#x27;, name=&#x27;range&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5c09138d-d003-4599-bca4-cd197af81125' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5c09138d-d003-4599-bca4-cd197af81125' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div></li></ul></div></div>"
             ],
             "text/plain": [
               "<xarray.DataArray 'range' (range: 28)> Size: 224B\n",
@@ -1389,7 +1390,7 @@
               "    description:            Distance to the center of each depth bin"
             ]
           },
-          "execution_count": 39,
+          "execution_count": 7,
           "metadata": {},
           "output_type": "execute_result"
         }
@@ -1414,7 +1415,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 40,
+      "execution_count": 8,
       "metadata": {},
       "outputs": [],
       "source": [
@@ -1424,22 +1425,22 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 41,
+      "execution_count": 9,
       "metadata": {},
       "outputs": [
         {
           "data": {
             "text/plain": [
-              "<matplotlib.collections.QuadMesh at 0x112d90785d0>"
+              "<matplotlib.collections.QuadMesh at 0x25a2aba1090>"
             ]
           },
-          "execution_count": 41,
+          "execution_count": 9,
           "metadata": {},
           "output_type": "execute_result"
         },
         {
           "data": {
-            "image/png": 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",
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7M4lJOSiEEEKISUtGdIQQQogWUFqhmnhgYDP77kik0BFCCCFaQOsmQz1DuSgzHPItCSGEEGLSammhc++993Lssccyffp0lFLccccdjfd83+fjH/84e++9N5lMhunTp3Pqqafy3HPPta7DQgghxBgZfI5OM4t4bS0tdEqlEm984xu56qqrtnqvXC7zyCOP8JnPfIZHHnmE2267jT//+c/84z/+Ywt6KoQQQoytwdvLm1nEa2vpHJ3FixezePHibb5XKBRYvnz5kHX/8R//wZvf/GZWr17NrFmzJqKLQgghxLhQWqN0E8/RaWLfHcnrajJyX18fSina2tpecZtarUatVmu87u/vn4CeCSGEEGJ79LopB6vVKp/4xCd473vfSz6ff8Xtli5dSqFQaCwzZ86cwF4KIYQQw6MN3fQiXtvr4lvyfZ+TTz6ZKIr45je/+arbXnzxxfT19TWWNWvWTFAvhRBCiBFodn6OFDrDst1fuvJ9n3e/+92sWrWKX/3qV686mgPgOA6O40xQ74QQQgixPduuC53BIucvf/kLd999N52dna3ukhBCCDEmlG4y1FMmIw9LSwudYrHI008/3Xi9atUqVq5cSUdHB9OnT+ef/umfeOSRR/jJT35CGIasX78egI6ODmzbblW3hRBCiKbJXVcTo6WFzkMPPcSiRYsary+44AIATjvtNJYsWcKPfvQjAPbdd98h+919990cdthhE9VNIYQQQrxOtbTQOeyww4jj+BXff7X3hBBCiNezZFKx0cT+4Rj2ZvLarufoCCGEEJNVs083licjD498S0IIIYSYtGRERwghhGgBrTW6iQnFzey7I5FCRwghhGgBuXQ1MeRbEkIIIVpgotPL7733Xo499limT5+OUoo77rjjNfe555572G+//XBdl3nz5nHNNdeM8tO2jhQ6QgghxA6gVCrxxje+kauuumpY269atYpjjjmGgw8+mEcffZRPfvKTnHvuudx6663j3NOxJZeuhBBCiBZQqskHBqqR7bt48WIWL1487O2vueYaZs2axZVXXgnA7rvvzkMPPcRXvvIVTjzxxBEdu5Wk0BFCCCFaYKzm6PT39w9ZP1aZj/fffz9HHnnkkHVHHXUU1113Hb7vY1lW08eYCHLpSgghhHgdmzlzJoVCobEsXbp0TNpdv3493d3dQ9Z1d3cTBAGbNm0ak2NMBBnREUIIIVpgrEZ01qxZQz6fb6wfi9GcxjGUGvJ6MLHg5eu3Z1LoCCGEEC2gDY1uotAZ3Defzw8pdMbKtGnTGmHagzZs2IBpmnR2do758caLXLoSQgghxFYWLlzI8uXLh6z7xS9+wf777/+6mZ8DUugIIYQQLaG0QmndxDKyy0fFYpGVK1eycuVKILl9fOXKlaxevRqAiy++mFNPPbWx/VlnncWzzz7LBRdcwJNPPsn111/Pddddx4UXXjhm38FEkEtXQgghRAtM9JORH3roIRYtWtR4fcEFFwBw2mmnsWzZMtatW9coegDmzp3LnXfeyfnnn883vvENpk+fzte//vXX1a3lIIWOEEIIsUM47LDDGpOJt2XZsmVbrTv00EN55JFHxrFX408KHSGEEKIFJOtqYkihI4QQQrTARD8ZeUclhY4QQgjRAsow0IbR1P7itUk5KIQQQohJS0Z0hBBCiBaQOToTQwodIYQQogWk0JkY8i0JIYQQYtKSER0hhBCiBQafcNzM/uK1SaEjhBBCtIBcupoYUugIIYQQoiX6+/tHvM9Ik9ql0BFCCCFaQGnV3IjOCEM9t0dtbW0oNfzPoZTiz3/+M/PmzRv2PlLoCCGEEC0gc3QS//M//0NHR8drbhfHMcccc8yI25dCRwghhBAtMXv2bA455BA6OzuHtf28efOwLGtEx5BCRwghhGgBpQ2UbiICool9txerVq0a0faPP/74iI8hhY4QQgjRCtpIlmb2F69pclzgE0IIIV5vtG5+2QE8//zzXHbZZaPef8f4loQQQgjxurR+/XouvfTSUe8vl66EEEKIFlCGgTKamKPTxL7bk8cee+xV33/qqaeaal8KHSGEEKIVZI4OAPvuuy9KKeI43uq9wfUjedbOy0mhI4QQQoiW6ezs5Etf+hKHH374Nt9/4oknOPbYY0fdvhQ6QgghRCto3eSIzuSYZrvffvvx3HPPMXv27G2+39vbu83RnuGSQkcIIYRoAXkycuLMM8+kVCq94vuzZs3ihhtuGHX7UugIIYQQomXe9a53ver77e3tnHbaaaNuf3KUg0IIIcTrjTJenJA8mkVNjsnI2/Kb3/yGWq02Jm1JoSOEEEK0QjNFTrN3bG3nFi9ezNq1a8ekLSl0hBBCCLFdaWby8cvJHB0hhBCiBWQy8sQYVqHzpje9aUSNKqX40Y9+xIwZM151u3vvvZd/+7d/4+GHH2bdunXcfvvtHH/88Y334zjm0ksv5dprr2XLli285S1v4Rvf+AZ77rnniPojhBBCbHfkgYGv6Fvf+hbd3d1j0tawCp2VK1fyr//6r2Sz2dfcNo5jvvjFLw5rElGpVOKNb3wjp59+OieeeOJW73/5y1/miiuuYNmyZcyfP5/LL7+cI444gqeeeopcLjecrgshhBDbJ3mOzit673vfS39/P3fccQe77roru++++6jbGvalq4997GN0dXUNa9uvfvWrw9pu8eLFLF68eJvvxXHMlVdeyac+9SlOOOEEAG688Ua6u7u5+eabOfPMM4fXcSGEEEJs99797ndzyCGHcM4551CpVNh///155plniOOYH/zgB9scEBmOYZWDq1atYurUqcNu9I9//OMrPuFwuFatWsX69es58sgjG+scx+HQQw/lt7/97SvuV6vV6O/vH7IIIYQQ25vBUM9mlsnk3nvv5eCDDwbg9ttvJ45jent7+frXv87ll18+6naHVejMnj17RIFaM2fOxGjyB7B+/XqAra7RdXd3N97blqVLl1IoFBrLzJkzm+qHEEIIMS60bn6ZRPr6+ujo6ADgrrvu4sQTTySdTvPOd76Tv/zlL6Nud1R3XVWrVR577DE2bNhAFEVD3vvHf/zHUXdmW15eYL1WiunFF1/MBRdc0Hjd398vxY4QQgixnZs5cyb3338/HR0d3HXXXfzgBz8AYMuWLbiuO+p2R1zo3HXXXZx66qls2rRpq/eUUoRhOOrOvNS0adOAZGSnp6ensX7Dhg2vOhPbcRwcxxmTPgghhBDjRu66GuKjH/0o73vf+8hms8yePZvDDjsMSC5p7b333qNud8TjXueccw4nnXQS69atI4qiIctYFTkAc+fOZdq0aSxfvryxzvM87rnnHg488MAxO44QQgjRCkobTS+Tydlnn80DDzzA9ddfz3333YeuX5qbN2/e+M/ReakNGzZwwQUXjMn97cVikZUrV7Jy5UogmYC8cuVKVq9ejVKKj370o3zhC1/g9ttv5/HHH+f9738/6XSa9773vU0fWwghhNgRffOb32Tu3Lm4rst+++3Hr3/961fcdsWKFSiltlr+9Kc/jUvf9ttvP971rncNeZzNO9/5Tg466KBRtzniS1f/9E//xIoVK9h5551HfdBBDz30EIsWLWq8Hpxbc9ppp7Fs2TIuuugiKpUKZ599duOBgb/4xS/kGTpCCCFe/1STE4rVyPe95ZZb+OhHP8o3v/lNDjroIL71rW+xePFi/vjHPzJr1qxX3O+pp54in883Xo/kTuxWU/EIAyXK5TInnXQSU6dOZe+998ayrCHvn3vuuWPawWb19/dTKBTo6+sb8kMSQgghXm4ifmcMHmPziv8in02Pvp1imc7D3j2ivr7lLW/hTW96E1dffXVj3e67787xxx/P0qVLt9p+xYoVLFq0iC1bttDW1jbqvrbSiEd0br75Zn7+85+TSqUaQ1qDlFLbXaEjhBBCTGYvf17cK92U43keDz/8MJ/4xCeGrD/yyCNf9fl0AAsWLKBarbLHHnvw6U9/esjVmO3diMe9Pv3pT3PZZZfR19fHM888w6pVqxrL3/72t/HooxBCCDH5DEZAjHpJfoXPnDlzyPPjtjUyA7Bp0ybCMBzR8+l6enq49tprufXWW7ntttvYddddOfzww7n33nvH9rsYRyMe0fE8j/e85z2N2dBCCCGEGIVmH/pX33fNmjVDLl291iNWRvJ8ul133ZVdd9218XrhwoWsWbOGr3zlKxxyyCGj7fkrGo/n9I240DnttNO45ZZb+OQnPzmqAwohhBCCpmMcBvfN5/PDmqMzZcoUDMPYavTmtZ5P93Jvfetbuemmm0bW2WEYr+f0jbjQCcOQL3/5y/z85z9nn3322Woy8hVXXDGqjgghhBBi/Ni2zX777cfy5ct517ve1Vi/fPlyjjvuuGG38+ijjw55kO9YGXxO32c/+9kxeYTNoBEXOn/4wx9YsGABAI8//viQ90aShyWEEELs0FrwZOQLLriAU045hf3335+FCxdy7bXXsnr1as466ywgiVFau3Yt3/nOdwC48sormTNnDnvuuSee53HTTTdx6623cuutt46+369gLJ/T91IjLnTuvvvuMe2AEEIIsUNqQaHznve8h82bN3PZZZexbt069tprL+68805mz54NwLp161i9enVje8/zuPDCC1m7di2pVIo999yTn/70pxxzzDGj7/crGMvn9L3UiJ+j83ojz9ERQggxXBP5HJ0XHvwZ+Wxm9O0US3QcsHjS/H4br+f0DWtE54QTTmDZsmXD/iLf97738bWvfY2urq5RdUoIIYSY7JTWqCbuumpm3+3ReD2nb1iFzg9/+EM2btw4rAbjOObHP/4xn/vc56TQEUIIIV6JavLSlZpcoZ6Dz+n7xCc+MaaPsBlWoRPHMfPnzx+zgwohhBBCvNR4PadvWIXOaCYgz5gxY8T7CCGEEDsMpUYVzDlk/0lkvJ7TN6xC59BDDx3TgwohhBA7PKWbLHQm1xyd8XpO34hvLxdCCCGEGGvj9Zw+KXSEEEKIFoiVJm5iVKaZfbdH4/WcPil0hBBCiFaQS1cTQr4lIYQQohWUan55nTvhhBPo7+8f9vbve9/72LBhw4iOMapCJwgC/vd//5dvfetbDAwMAPDcc89RLBZH05wQQgghdkCDz+nr7+9/zaWvr48f//jHI641Rnzp6tlnn+Xoo49m9erV1Go1jjjiCHK5HF/+8pepVqtcc801I21SCCGE2PFonSzN7P86NxHP6RtxoXPeeeex//778/vf/57Ozs7G+ne961188IMfHNPOCSGEEJOVTEaemOf0jbjQue+++/jNb36DbdtD1s+ePZu1a9eOtLkJEz77GFHKhCgkjiKU5RAVe1GWDVEI2U4o9yZ/NuufLQpRtkvsVYkrJTAtYq+K0d5FNNBLVO7H6OxpbBv2bcZeeGLLPqMQQuyI/rCujzCKyTsGfhRja0UYQ1jPrE6ZSUEQRjGWTua1+FHMYKK1oRRKgW0oSv2lVnyEHdZEPKdvxIVOFEWEYbjV+r///e/kcrkx6ZQQQggx6cldVxNixN/SEUccwZVXXtl4rZSiWCxyySWXcMwxx4xl34QQQojJa7DQaWYRr2nEIzpf+9rXWLRoEXvssQfVapX3vve9/OUvf2HKlCl8//vfH48+CiGEEEKMyogLnenTp7Ny5Uq+//3v88gjjxBFER/4wAd43/veRyqVGo8+CiGEEJOPXLqaEKN6MnIqleKMM87gjDPOGOv+CCGEEDuEWKkm77p6/T8w8KWWLFnC6aefzuzZs8e03REXOj/60Y+2uV4pheu67LLLLsydO7fpjgkhhBBix/HjH/+Yyy+/nEMPPZQPfOADnHDCCbiu23S7Iy50jj/+eJRSxHE8ZP3gOqUUb3vb27jjjjtob29vuoNCCCHEpCSXroZ4+OGHeeyxx7jhhhs4//zz+fCHP8zJJ5/MGWecwQEHHDDqdkf8LS1fvpwDDjiA5cuX09fXR19fH8uXL+fNb34zP/nJT7j33nvZvHkzF1544ag7JYQQQkx6knW1lX322Yevfe1rrF27luuvv561a9dy0EEHsffee/Pv//7v9PX1jbjNERc65513HldccQWHH344uVyOXC7H4Ycfzle+8hU+9rGPcdBBB3HllVeyfPnyEXdGCCGE2GHI7eWvKIoiPM+jVqsRxzEdHR1cffXVzJw5k1tuuWVEbY34W/rrX/9KPp/fan0+n+dvf/sbAG94wxvYtGnTSJsWQgghxA7s4Ycf5pxzzqGnp4fzzz+fBQsW8OSTT3LPPffwpz/9iUsuuYRzzz13RG2OuNDZb7/9+NjHPsbGjRsb6zZu3MhFF13UuIb2l7/8hZ122mmkTQshhBA7jMGsq2aWyWSfffbhrW99K6tWreK6665jzZo1fPGLX2SXXXZpbHPqqacOqT+GY8STka+77jqOO+44dtppJ2bOnIlSitWrVzNv3jx++MMfAlAsFvnMZz4z0qaFEEKIHYdqMr18khU6J510EmecccarhnZOnTqVKIpG1O6IC51dd92VJ598kp///Of8+c9/Jo5jdtttN4444gh0/Qd2/PHHj7RZIYQQQuzA4jje5t3alUqFf/u3f+Ozn/3sqNpV8cvvE59k+vv7KRQKbHn0l+TaOqDcizKt5E1tJGnmVgoVBcR+LVkfhaANlJ0i9iqNtpTlEKx/BrN7FlHfZsItGzCmzkjSzatllJuu7x+h3DRR/wvJ+6V+gudXo3PtxL4H2iDq34xO51CpTJKEPtCLzuSIKiV0rp1oYAsAYalIHEZY7e3UNmxEWybeQImw6uF2Fiit24xhmzhtOULPJyhXsXMZ3J5u0AalZ57F7SwQVj20ZVLrHQBgyrlfnbCfgRBi+3LstffTmXWoeAEAKdukt+wxvzvH42v76Mza9JZ9OrMOb5nXwZ2PraOnLUXFC5g3NUsYxfx9S4WunEPKNugt++zUkeKFokfZC5nXlcELIrwgYkrWwTJevDuo7IfkbJMZeZdNZY+0ZbCl4pOyDAwFWyo+C3oKbCjVKLhmfZ+IgpP8OW0ZjbYiYgylCOOYqh/hmJqUqQnjGFMn6+MYHEOhlcKPYga7YhvJdhoI4yS5PIxiKqUB5s+aTl9f3zbno46Fwd9LG5/5M/n86MOw+/sHmDpn/rj2dSIZhsG6devo6uoasn7z5s10dXVtM1B8OEb1ZORf/vKX/PKXv2TDhg1bDSFdf/31o+qIEEIIsUOR5+gMMfgsvpf7/e9/T0dHx6jbHXGhc+mll3LZZZex//7709PTs81OCSGEEEIMR3t7O0oplFLMnz9/SF0RhiHFYpGzzjpr1O2PuNC55pprWLZsGaeccsqoDyqEEELs8GREB4Arr7ySOI4544wzuPTSSykUCo33bNtmzpw5LFy4cNTtj7jQ8TyPAw88cNQHFEIIIYSEeg467bTTAJg7dy4HHngglmWNafsj/oY/+MEPcvPNN49pJ4QQQgix4+nv72/8ecGCBVQqFfr7+7e5jNaIR3Sq1SrXXnst//u//8s+++yzVeV1xRVXjLozQgghxA5DLl3R3t7euNOqra1tm/N+BycpT9hdV4899hj77rsvAI8//viQ98Z6YnIQBCxZsoTvfe97rF+/np6eHt7//vfz6U9/uvHMHiGEEOJ1qdlgzklw6epXv/pV446qX/3qV+Nyg9OIC5277757zDvxSr70pS9xzTXXcOONN7Lnnnvy0EMPcfrpp1MoFDjvvPMmrB9CCCHEmJMRHQ499NDGnw877LBxOcZ2/S3df//9HHfccbzzne9kzpw5/NM//RNHHnkkDz30UKu7JoQQQrwuffOb32Tu3Lm4rst+++3Hr3/961fd/p577mG//fbDdV3mzZvHNddcMy79uuGGG/jv//7vrdb/93//NzfeeOOo2x1VofPggw9y0UUXcfLJJ3PCCScMWcbS2972Nn75y1/y5z//GUgeGnTfffdxzDHHvOI+tVptzCYwCSGEEOOlFaGet9xyCx/96Ef51Kc+xaOPPsrBBx/M4sWLWb169Ta3X7VqFccccwwHH3wwjz76KJ/85Cc599xzufXWW5v9+Fv54he/yJQpU7Za39XVxRe+8IVRtzvib+kHP/gBBx10EH/84x+5/fbb8X2fP/7xj/zqV78acu/7WPj4xz/OP//zP7PbbrthWRYLFizgox/9KP/8z//8ivssXbqUQqHQWGbOnDmmfRJCCCHGxOClq2aWEbriiiv4wAc+wAc/+EF23313rrzySmbOnMnVV1+9ze2vueYaZs2axZVXXsnuu+/OBz/4Qc444wy+8pWvNPvpt/Lss88yd+7crdbPnj37FQux4Rjxt/SFL3yBr33ta/zkJz/Btm3+/d//nSeffJJ3v/vdzJo1a9Qd2ZZbbrmFm266iZtvvplHHnmEG2+8ka985SuvOoR18cUX09fX11jWrFkzpn0SQgghticvv4pRq9W2uZ3neTz88MMceeSRQ9YfeeSR/Pa3v93mPvfff/9W2x911FE89NBD+L4/Nh+grquri8cee2yr9b///e/p7Owcdbsjnoz817/+lXe+850AOI5DqVRCKcX555/P29/+di699NJRd+blPvaxj/GJT3yCk08+GYC9996bZ599lqVLlzYeMPRyjuPgOM5W62PDRkUB2C5ok1hpVJgEbCq/HtwZhSjbJfZCCDywnCTgs/5eDGg3QxzUf7jagHrWl7LdJIyzbzNx4KGtthf3i0IwbXQ6R1QtoUybuFpCOalkk4Fe0Jo4ioiqZXSuHZ3KEPZtRhmaOIzwt2zByqXxeouYrkNY9TBcm8gPiMMIt1Nj2BZh1SOo1oh9H5WyUVqjtMZqa8Pv7cWwLKq9AxS/dxnldZuJo4jU1HYiP8AvVbAyKaxcmud/90cKO88g8gNqvUX8UpXsjCmYroM3UEJpjdtZYGD184RVDwC3M09p/Qu0z5/Jlj+vIT9nGkG5SlDxeOFPa5iyz1x6/7wGbZl07jVXgkXFDueob/6GTesG2PUNnazdWEJpRa0SkMk7lPprxFGM5RjYjsnm9QO0Tc2Qy9hsWF/Eckz8WkBnV4aBgRpxBJmcTRBE7DwtR1/ZoxZEbOmrMrcnz6p1/WQyNrap2ak9TbEW8OyGIsW+KlO7s4RRxEA1IGUbVLyAXD1Asy1tkbJNNhc9egouXhiRtg3aUhZhFJN1TYrVAC8IqQURhbSFY2peKCb/DqRtA9vQeEGEbWr8KCJtWfTVfNKWQbEakLYMqkGEpYfeYWMZL/6/dzWIsPyItKWx6gGdbr09QysMpSAGQ0OlFhPGMbUgImVqlAJLK+IQIhUTk9ygFMfg1XOsLR3jhXESAhpFhPXYxomMuU4eGDj6u4wG9335lYtLLrmEJUuWbLX9pk2bCMOQ7u7uIeu7u7tZv379No+xfv36bW4fBAGbNm2ip6dn1P1/uZNPPplzzz2XXC7HIYccAiTzg84777xGHTAaIy50Ojo6GBhIErBnzJjB448/zt57701vby/lcnnUHdmWcrm81W3khmFsFSQqhBBCvN7EcXOF1eC+a9asGZJevq3/2X+pl9/C/Uphmq+2/bbWN+vyyy/n2Wef5fDDD8c0k/IkiiJOPfXUpubojLjQOfjgg1m+fDl777037373uznvvPP41a9+xfLlyzn88MNH3ZFtOfbYY/n85z/PrFmz2HPPPXn00Ue54oorOOOMM8b0OEIIIcTrVT6fH1LovJIpU6ZgGMZWozcbNmzYatRm0LRp07a5vWmaTV1O2hbbtrnlllv43Oc+x+9//3tSqRR77703s2fPbqrdERc6V111FdVqFUjmw1iWxX333ccJJ5zAZz7zmaY683L/8R//wWc+8xnOPvtsNmzYwPTp0znzzDP57Gc/O6bHEUIIISZaFMdETQzpjHRf27bZb7/9WL58Oe9617sa65cvX85xxx23zX0WLlzIj3/84yHrfvGLX7D//vuPeSbVoPnz5/OGN7wBGJtRoxFPRu7o6GD69OnJzlpz0UUX8aMf/YgrrrjiNYfLRiqXy3HllVfy7LPPUqlU+Otf/8rll1+ObdtjehwhhBBiosVjsIzUBRdcwH/+539y/fXX8+STT3L++eezevVqzjrrLCAZwDj11FMb25911lk8++yzXHDBBTz55JNcf/31XHfddVx44YWj/NSv7jvf+Q577703qVSKVCrFPvvsw3e/+92m2hzxiM62VKtVvvnNb/LlL3/5FSc0CSGEEOJFUZwszew/Uu95z3vYvHkzl112GevWrWOvvfbizjvvbFweWrdu3ZBbuefOncudd97J+eefzze+8Q2mT5/O17/+dU488cTRd/wVXHHFFXzmM5/hnHPO4aCDDiKOY37zm99w1llnsWnTJs4///xRtTvsQsfzPC699FJ+8YtfYFkWF110Eccffzw33HADn/rUp1BKSSyDEEIIsZ07++yzOfvss7f53rJly7Zad+ihh/LII4+Mc6+S6SpXX331kBGl4447jj333JMlS5aMf6GzZMkSvvGNb3DEEUfwm9/8hpNOOokzzjiDFStWsHTpUt773veO2/U6IYQQYrKJ47hxB9No959M1q1bx4EHHrjV+gMPPJB169aNut1hz9H5r//6L5YtW8b//M//cNdddxGGIf39/TzxxBOcdtppUuQIIYQQIzB46aqZZTLZZZdd+K//+q+t1t9yyy2NycmjMewRnTVr1nDAAQcA8MY3vhHbtvn4xz/euNddCCGEEGK0Lr30Ut7znvdw7733ctBBB6GU4r777uOXv/zlNgug4Rp2leL7/pC7nSzLGvNsKyGEEGJHMskGZZpy4okn8n//93987Wtf44477iCOY/bYYw9+97vfsWDBglG3O6LhmM9+9rOk02kgmZx8+eWXb1XsXHHFFaPujBBCCLGjaMVdV9u7/fbbj5tuumlM2xx2oXPIIYfw1FNPNV4feOCB/O1vfxuyzVg/DloIIYQQk1d/f/+wtx3O05+3ZdiFzooVK0Z1gO1KHDVCOmM3h/IrhH2bMdq7iL0qyklGq9AGse/RKNuikKg0gM61JSGgloMqdBL2ba4HbxrodC7ZNZMjDkOUaaHTOeJa9cU2qqUkCBTQuTZi38fId6AcN+lXFKK0Jty8Dp3JE9czvbRt4veXMdMplKExMy4Afv+L2WJ2ZycDTz+DX6qS7mpHWRZxpYSdzxCUqxj1tkrrN+N25lH1ENHBdanOAkHVI/IDQs/HdB20YeANlMnP6aGycQvVzf1kZ0wFwBsoY+czAIR+gGElp1IchtjtbUT+33A7C/Ru7qfWO4CVsQlKVex8Gr9UxS9VefL0f8R0bUobBijM7SLyfbz+MqEXYtgG+Tk9eANlglKFoOpR668xZa9Z/O2uJ8jvlMN0TQbWFSnslMcreQSVgOkHzscbKPP8I6uZc8RebHj0r6S78mz64/N0v2kWm//4HOkpKYJqwJR95tJz8TfG9hwT25Uv3v0XNvTXcEzNQDUJrvzbxiJZ1yLrmHhhRF/ZoyPjYGjFC6UaWddiXW8Fx9TUgoiethR/21AkZSeBlACl/hrTp2V59tleTMsg8EN2mllgS18VN2XR31vFSZkopSj2Vcm3pwjDCMPQaFOzob9GuehR6ExTGfAI/OTfpTCMMCODMIzIFlIY9XBMbWriOCYMI7wgIgpjtKEIo5haJcALIoL6/95HUUwYRViOSVfeZUN/lbRt8PctZQxT47gWhlZ4QRKO2Za2KVb9esBn8l9DK2peiG1qitUA29RMzTv0VnwqXkjFC8m6Fp1Zm76yz+aSR2c9QLTshej6//T2lX3CKKbgWFS85DMaWhFFMUUvqP+UIvwwYkbeZaAW4JhGI7gzbWn8MAnsBBrtAgRRzOBL19RYsSKKk6DOnKOpBTF+lOxr6eS7MjSoWNX3VWgV49XTPMM4Cf70JnCYRO66gra2ttccJBnM4grDcFTHkJnEQgghRAtE9aWZ/V/v7r777nE/hhQ6QgghhGiJQw89dNyPMeKsKyGEEEI0L46bXyabX//61/zLv/wLBx54IGvXrgXgu9/9Lvfdd9+o25RCRwghhGgBeWDgULfeeitHHXUUqVSKRx55hFqtBsDAwABf+MIXRt2uFDpCCCFECwxORm5mmUwuv/xyrrnmGr797W8PSVs48MADm8raGlWhMzi0tHDhwjEbWhJCCCHEjuupp57ikEMO2Wp9Pp+nt7d31O2OuNB56dDSo48+OmZDS0IIIcSOJBqDZTLp6enh6aef3mr9fffdx7x580bd7ogLnfEaWhJCCCF2JDFNTkZu9QcYY2eeeSbnnXce//d//4dSiueee47vfe97XHjhhZx99tmjbnfEt5eP19CSEEIIIXZcF110EX19fSxatIhqtcohhxyC4zhceOGFnHPOOaNud8QjOuM1tCSEEELsSKI4bnqZDPbdd1+uuuoqtmzZwuc//3k2bdrE7373Ox544AE2btzI5z73uabaH3GhM15DS0IIIcSOJB6DZTJ4y1vewqc//WmmT5/Oe9/7Xu6//372339/3vzmN5PNZptuf8SFzkUXXcTxxx/PokWLKBaLHHLIIXzwgx/kzDPPbGpoSQghhBA7nm9961usX7+ea6+9lvXr13PkkUcyZ84cLrvsMlavXt10+6OKgPj85z/Ppz71Kf74xz8SRRF77LHHmFRd4ym2HCAmtlKoOEIFPpgORqETlE5CPG2X2HShMoBOZYgNG3RyV5my3Xqgp0Xs11Bav/i6ViUqD2A4LlFpAOWmk/BO0yLqfwGjfSqRaaFMG53JEfZtJvZ9Yq8KUZSEf0YR0cCW5Li1KlGpH227eFt6sTs7MMMITIs4jAirHrXeAVJT28nOmEqtd4CoUsJwbYprN5Kf20Ps+4SVMkGpijJ00l9AWyZ+qUpqKiitsTJJUGhx7UYy0zoZWP08Smuc9ix2W5bi2o2Y6RTaGsAvVQiqNfxSlaDqMbD6eYprN2Ln0yhD4w2UqfUWCYpF/FIVZbuYKZu+vw5gZRwM18bwA4KKl/xMwrjx3zhMAk2rW6pYGYvQCymu3Ui1t4KdsbAyLgPrisT1AL7BfbWhsTIOtf4aVtYm8gNqWwao9dfwXhJ6aliaoFQh053BsEzKmyoAPHTM4XS/aQ6hH7DuwWdon9eO0priuoEkNNELmXbAPLz+EpEfoAxN5AXk5/ZQXLsRr79MdsZUDNdGGRq/v0zoB0S+j7Ys3M48hmVS6y3iduapbOilsMsM/FKF/lXryPR0kp3ZTXVzH4Zt4XRNpfz350hN7aD2Qh/OlA50ro1g83rMzmko00pCZ73qi5+tcxrRQC8qlYEoRGfbUIaBcjOgNFG6HVUdILZTSbCtNpNz3rDQtQFiwybMdYM2CLWFF0ZEMVSCmCCKMXUSuGcbijCOqQUxlSDCj2Kylub5kp/0Qyn8KKKvGhDGUPZDil5Au2uRc0w2FGv01QJ2nZKh7EesH6jyzOYyZS+kp83lhaLHgpltbCglf+e8IOKFokdH1gag4oX0FFw2DCTv22YSeBlGMSnboOKFhFFMb9mnM2tT8cLGvmEUk7YNCmmLIIpJWQYvlGp0ZBxSdvLPoKEVm4setmkQRjFZ16L3hTJh/alshlakbIP+gRqmpekr+2TbXCoDXqN/2tBUKz5excdJmVTLPrZjYpqawA8JiTAtg6xrUjQ0tqmJ4ph0ysKvhRiGxrQ1tUpAJu9Qq/gEviKOYrSlMQxNyjboqwVkCy62qSmFEWEUUfFCDK0wLYOyF5J1TXrLHinbYF1fhZxrknNNVteCRvhmWzq5oSRlmwxUq4RRTM598deCF0R0ZG1Sttn4viteSCFt0VtJfu5BFOMFIWUvbJwvfhSRdUwq9WDQsp/8bFxDE5oxJT8k71oEYUQtimlPWaztr2LVzzVLaxxDY2mNVi9eoqkFEa6l8YIY19SYBnj1fwtsQ+FHYNT/9z0ixjYUZT/G1oowphHwOUiRBIIWvQh0jKlUI0B0IjT70L/J9MBA13U55ZRTOOWUU1i1ahXXX3891113HZdddhmHH344H/jAB3j3u989qrZH/cDAdDo9pkNLQgghxA6l2fiHSVTovNTcuXP53Oc+xzPPPMMPfvADHnroIf75n/951O0Na0TnhBNOGHaDt91226g7I4QQQghx9913c8MNN3DbbbdhmiYf+tCHRt3WsAqdQqEw6gMIIYQQYmsRMVETwzLN7Ls9Wr16NcuWLWPZsmU888wzHHzwwXzzm9/kpJNOIpVKjbrdYRU6N9xww6gPIIQQQoitNZtAPknuLufmm2/mhhtu4O6776a7u5tTTz2VD3zgA+yyyy5j0v6oJiMLIYQQojkyGTnx/ve/n3e+853ccccdHHPMMWg9tnnjwyp03vSmN/HLX/6S9vZ2FixYgFLqFbeVGAghhBBCDNff//53urq6xq39YRU6xx13HI7jAHD88cePW2eEEEKIHYVcukqMZ5EDwyx02tvbG0NJp59+OjvttNOYDy0JIYQQOxKZjDwxhlWtXHDBBfT39wPJ/e2bNm0a104JIYQQQoyFYY3oTJ8+nVtvvZVjjjmGOI75+9//TrVa3ea2s2bNGtMOCiGEEJORXLp6URiG3Hfffeyzzz60t7ePadvDKnQ+/elP85GPfIRzzjkHpRQHHHDAVtvEcYxSijAMx7SDQgghxGTUbAL5ZEkvBzAMg6OOOoonn3yyNYXO//f//X/88z//M88++yz77LMP//u//0tnZ+eYdkQIIYQQO669996bv/3tb8ydO3dM2x32jOJcLsdee+3FDTfcwEEHHcQb3/jGbS7bK+XXkkBDlXxkFXoQBWA6jW2iUjIPSdkusZUiNi0IPJRpoazkz1GllGxsWJhTphHXqijLTgI3fT8J7PSqSciiYUA9/FMXXiwM41qV2KsmAZ6BB6ZNtGUDOpVBpfMY3bNQtouyLLRlojN5wqoHgY+ZcbHyecy0m/S1nmAXVj3sfIY4iqhs2EJQLBKUqngDJbz+EmHVo7xhC6ZrE4cRQbmKN1CmtH4zdiGH4dpo2ySKIryBMi88+SwApfWb6fvb3ymtf4E4ivBLVaxMcmy/VCH0QuIwIg4jSus2E1QDqpv78Ese5bXriMIIK+OgbZPq5j4qG7Zg2GbyeQDDtan21/AGypiug5N3cNszBNWA3lVbKD1fovR8ieqWEpZr4pcq7Hrifjh5h6AakOlKE/oBAHbGorq5j7DqY1gG5Q1b8Io+lU0DGLaBmUmhtEYZGsPWBKUq5c0VgnpfgkpAHEaYKZtaf40ojBuBqMowSE1NAj+jMMJwbYKKVw8kTT5/ef1m/HKFoFRBWxZhtUatt4i2TXQ92NMvV4jDiNqWIlAPWR0oow0j+U63bMHtLBDWaihDExSLRH2bCateEuSpDcKNa4kDn6jUT9S3GWXaEIVJoGc6j7Lsxnka18qoWgmURkUBKgwgjoiVRoU+cT3gc5AfxURxEtQ4GI6oVRKGmAQkJqGqYZQEZVaCGEtrakFEV8bC0ppqEOGHEVEcU/ZDojhO1kUxXhixqexTC0KqYYRtapx6WGTZC+lIWbxQ9DCUwgsiCmmLjG2Ssgy8IKIWRHhBRF/ZxzY1YRRj6GTbjoxN1jXxgqSPKdtofK7NJY8giql4IY6ZhGkOVAMcU1NIJcGWplb0tKXozNgYWpF1kv8P9IKoEWg52LaTskjZBnEUY9oGTsoiCCIK9RBRVQ+ONAyNaSX9dFMW6fqxKl5IHMWEUUwURKRsA6UUqaxNZcAjjmIKaYs4giiKqVV8DFNj1sNL8+2pxrFsx2Bz0Wv0LwqToNPB7ybnWpS9kM1Fj5RtEr00qLUeYDoYWAovhpt2t7l0ZG1sQ9OWslj7QoUwihio1v++Gcl3knNNUrZJxQ+3+t6zrskLRY8oToJXwxjaXItiNcA1NWEMeddCK4Vjasz6SWdoyDkGWqkkLDZMziU/iih5IbapUCq5dGPUH3cSRsnrKIaBWoRG0VcNUSo5r8M4Obf9lzx8xtCKahA1gjw1E/tsmuTvUXPLZPL5z3+eCy+8kJ/85CesW7eO/v7+IctojfiBgaeddhoADz/8ME8++SRKKXbffXfe9KY3jboTQgghxI5GLl0NdfTRRwPwj//4j0Oe19fs1JgRFzobNmzg5JNPZsWKFbS1tRHHMX19fSxatIgf/OAHTJ06dVQdEUIIIcSO6+677x6Xdkf8MJyPfOQj9Pf388QTT/DCCy+wZcsWHn/8cfr7+zn33HPHo49CCCHEpBPFySW10S7jOaKzZcsWTjnlFAqFAoVCgVNOOYXe3t5X3ef9738/Sqkhy1vf+tZhH/PQQw991WW0Rlzo3HXXXVx99dXsvvvujXV77LEH3/jGN/jZz3426o4IIYQQO5Ik6ypuYhm/vr33ve9l5cqV3HXXXdx1112sXLmSU0455TX3O/roo1m3bl1jufPOO0d03F//+tf8y7/8CwceeCBr164F4Lvf/S733XffqD4HjKLQiaIIy7K2Wm9ZFlE0yWZGCSGEEONke52M/OSTT3LXXXfxn//5nyxcuJCFCxfy7W9/m5/85Cc89dRTr7qv4zhMmzatsXR0dAz7uLfeeitHHXUUqVSKRx55hFqtBsDAwABf+MIXRv15RlzovP3tb+e8887jueeea6xbu3Yt559/PocffvioOyKEEEKIkXv53UmDBcJo3X///RQKBd7ylrc01r31rW+lUCjw29/+9lX3XbFiBV1dXcyfP58PfehDbNiwYdjHvfzyy7nmmmv49re/PWRA5cADD2wqMHzEhc5VV13FwMAAc+bMYeedd2aXXXZh7ty5DAwM8B//8R+j7ogQQgixI2nustWLc3RmzpzZmEtTKBRYunRpU/1av379NoM2u7q6WL9+/Svut3jxYr73ve/xq1/9iq9+9as8+OCDvP3tbx924fXUU09xyCGHbLU+n8+/5vygVzPiu65mzpzJI488wvLly/nTn/5EHMfssccevOMd7xh1J17N2rVr+fjHP87PfvYzKpUK8+fP57rrrmO//fYbl+MJIYQQE2FwUnEz+wOsWbOGfD7fWO84zja3X7JkCZdeeumrtvnggw8CDLm9e9Dgbd6v5D3veU/jz3vttRf7778/s2fP5qc//SknnHDCqx4XoKenh6effpo5c+YMWX/fffcxb96819z/lYyo0AmCANd1WblyJUcccQRHHHHEqA88HFu2bOGggw5i0aJF/OxnP6Orq4u//vWvtLW1jetxhRBCiNeLfD4/pNB5Jeeccw4nn3zyq24zZ84cHnvsMZ5//vmt3tu4cSPd3d3D7ldPTw+zZ8/mL3/5y7C2P/PMMznvvPO4/vrrUUrx3HPPcf/993PhhRfy2c9+dtjHfbkRFTqmaTJ79uwJy7P60pe+xMyZM7nhhhsa615e6QkhhBCvRxHNPYl5pHORp0yZwpQpU15zu4ULF9LX18fvfvc73vzmNwPwf//3f/T19XHggQcO+3ibN29mzZo19PT0DGv7iy66qPFcvmq1yiGHHILjOFx44YWcc845wz7uy414js6nP/1pLr74Yl544YVRH3S4fvSjH7H//vtz0kkn0dXVxYIFC/j2t7/9qvvUarUxe2y0EEIIMV4GozqaWcbD7rvvztFHH82HPvQhHnjgAR544AE+9KEP8Q//8A/suuuuje122203br/9dgCKxSIXXngh999/P8888wwrVqzg2GOPZcqUKbzrXe8a9rE///nPs2nTJn73u9/xwAMPsHHjRj73uc819XlGXOh8/etf59e//jXTp09n11135U1vetOQZSz97W9/4+qrr+YNb3gDP//5zznrrLM499xz+c53vvOK+yxdunTIpKyZM2eOaZ+EEEKIye573/see++9N0ceeSRHHnkk++yzD9/97neHbPPUU0/R19cHJOnjf/jDHzjuuOOYP38+p512GvPnz+f+++8nl8sN65hnnHEGAwMDpNNp9t9/f9785jeTzWYplUqcccYZo/4sI56MfNxxx73qZKSxFEUR+++/f+P++QULFvDEE09w9dVXc+qpp25zn4svvpgLLrig8bq/v1+KHSGEENuduMmnG8fj+GTkjo4ObrrppmEfP5VK8fOf/7ypY95444188Ytf3KowqlQqfOc73+H6668fVbsjLnSWLFkyqgONRk9PD3vssceQdbvvvju33nrrK+7jOM62Z5wbRiPBOTYsVOgnaeZBjdjJAiQp5ADaAG0kSc/aeDGxPPABiAa2YHRMS7ZJZdDp+g8lijA7pxF5VYgilONCFEEUokybcMuGJM0cMNqnEntJinlcfklqeuATe1WMQifh5vVUN/fhzN2VOEzaU4EPUUhUT+zWlknoBShDY+YLGK6Dnc8QVj2iMCQKI+y0i5nPY/YOJMnlpWpj38gPUKkMhmVS2zJAZcOWRiJ65AcYlklQqibH15rKxi24HQW01mBbGPWkYq+/1OhTaf0LuG1pwqqH31/GzKSwc2mKazeiLbPRllfycDtBGxor41LeuAXDtShtGCAOY5ShSLW7VLYk/VWGZtOT61GGgTJUo5+VTWWUoYjDmKDq4VcD3HaXTE8nm5/ahGFrrHqyeWVTmdSUNIZt4JcqRGHyF3XVL/6E6Zr0/32Anv07CaoB6SkpTNckjiLCao044xJWPaq9Faqb+4mjCMO1MFybWu9AcopUvCQ93bWTlHTLbCSVx/Wne3n9yflU6y1i5zP17Swqm/swXRsrkwKSdPg4jEjbJkprdLatcX76G5/H6pxSP9dC4sCHWhVV6CSuVYmr5eRcqlXRbpCklAOxYaICD+qv0SaxNlFBFbRJqA1ikjsuLAWVOAKSBOlaEDVSryOS723w3znH1CgFba5JX81k3UCNtKWT5OkoZvBvpG1o+qs+WcfE0kmqd0fW5tlN5aQ7Cgrp5PkZWdek4iWJ1V494XtmIcXGgRoD1YCcbTaSzFO2wfq+KlnXJG0bbOiv0Zm1qXghYRSTsgx62tzkz7aJY2o6sw5lLyRtG5i2Qbm+ba2eyO2FEUEQ4QVbz0m0TU3FC5nSnmLTlgpeLSTtmhj6xf8JbMs5bK6/l8nYpGyDDZvLGIZubJeyDaJ6qnoYRuRdB68aYFpJ/zb3Jee+YSbnehhEGFrR1ebSW09wL9X7M5jmXvQjitUgSQuPYnrLXuO1oRWmZTBvapbH1/a9JP09xAsi1vVWmDc1y0A1wDYN2lMWacvANjW9ZZ+UbRLGMcVq0Dhmb9mnLWXRW/HprCeqe0GSoJ51TLKuiaUVxVpET85tfH9py8Cv/50Y/GXvmsn5sansU/ZDerLJ5/ajGKv+nVlaY+nkvIpjRcpSFL0YpYE4OSdNI7kjKetoNIowTs4trZI5MbahiOOYIIobD90LI/CJcfXE/I88QBgnSzP7Twb9/f3EcUwcxwwMDOC6buO9MAy58847t3m7+3ANu9Apl8t87GMf44477sD3fd7xjnfw9a9/fVgTm0broIMO2uopjH/+85+ZPXv2uB1TCCGEEBOnra2tkY01f/78rd5XSr3mbfGvZtiFziWXXMKyZct43/veh+u6fP/73+f//b//x3//93+P+uCv5fzzz+fAAw/kC1/4Au9+97v53e9+x7XXXsu11147bscUQgghJkLU5KWr8Qz1nEh33303cRzz9re/nVtvvXVIbIRt28yePZvp06ePuv1hFzq33XYb1113XeMe/H/5l3/hoIMOIgxDDMMYdQdezQEHHMDtt9/OxRdfzGWXXcbcuXO58sored/73jcuxxNCCCEmSrN3To3XXVcTbTCZfNWqVcycOTOZGjGGhl3orFmzhoMPPrjx+s1vfjOmafLcc8+N62Tff/iHf+Af/uEfxq19IYQQohVkRGeowWkp5XKZ1atX43nekPf32WefUbU77EInDENs2x66s2kSBMGoDiyEEEIIMWjjxo2cfvrp/OxnP9vm+6N9WPGwC504jnn/+98/5I6marXKWWedRSaTaay77bbbRtURIYQQYkcid10N9dGPfpQtW7bwwAMPsGjRIm6//Xaef/55Lr/8cr761a+Out1hFzqnnXbaVuv+5V/+ZdQHFkIIIXZkculqqF/96lf88Ic/5IADDkBrzezZszniiCPI5/MsXbqUd77znaNqd9iFzkvzpoQQQgghxlKpVGo8L6ejo4ONGzcyf/589t57bx555JFRtzu2U5uFEEIIMSxRFDe9TCa77rpr49l5++67L9/61rdYu3Yt11xzzbCDQbdlxE9GFkIIIUTzoibn6EyyOoePfvSjrFu3Dkie3XfUUUfxve99D9u2WbZs2ajblUJHCCGEEC3z9NNPs8suuwx5Rt6CBQt45pln+NOf/sSsWbOaSmGQQkcIIYRoAZmMnJg/fz4zZsxg0aJFvP3tb+ewww5jzpw5pNNp3vSmNzXd/g4zRydWmth0IKhBHCevrRRRuu3FjbSRBH1GISqoEZs2se+hnBTKMMC0IIqIvSooTVTqR9suUbEXAh9lWehcG0Z7FzrXhnKzxL4Hpk0ceKhUhjjwMQqdEEVEA73Evo9K54nrwYyDoZ4qlUnW1Y+nbZM4DNF2EnY2GMgZVr1GuCWmjZ1LY2aSbSobe8nOmJps46SI/IDyxl4qm/saIZxKa/r/9Be0beLXwz6Dio/TliWsejhtOUI/IKzWiPwAr79Mef1mrHwa07UJvRC/VMXOJ48YsDJJwGXoB0RhRBRFRL6PmbIxbBNtaIKqh5VxMV0Tpy2HV/TQlkVQSbarbqniVwOCSkDohShDUd5cIfRDUu0ua379V1Jd7dT6a8l6L8Qr+Y0fo+WaeCUPpTXlTRU2/nETAP1/76e8qYKdS6O0anxeZWjSU9IE1YDKlirK0HhFn9Lz5UZ//VKV0rrN+KUaxeeKGK6NlXkxeC6OIoJK8nArr5RsX1zXh51P43bmk5+VHzSCPc1Usn9QTfpp5dON15XNfQTVGpUNvdj5DNpMgkNjr4pyXOLAo9Y7gKqfC41zx6sS+8n3ENcqKMtBWRaxVX8kRBQlYZ5ao7wysdLJ+Q6owCPWJmkj+YfT0lDyI2xD40dJ+GElSN4LopiMpXFNTVj/hzaKY2pBjFJQcEzSlkYrhWNqsrbZCGRMWwaOmTxJ3VBJcGdX1qGtHuRZC5JjemH0ksDJCNvUbOiv4YdJqOXg9l6QBH7Ci8GWhbSFUw/BzNaDNg2tsE1NyjbozNiNJ8p25R1qQURvxadYS54J5tTDMQ2V9HkwPHOwPcsxCaMYvxaQcy0CPyIKIoplH1Mroigm8EOK1YAojHHTFrapcUyNaRmYtqYtbTXa6ZqRb7RX80JMS+OmLGxDM70zjeOYOCkLpRSBH2Kbmo6MgxdEDJSTn3eu/jltU+PVAsL69xJGMV4QNfb7+wtlOvJO4/vKOsn/66ZsE9tM+tWZtRvfuf+SayO2qenM2NiGbgSvGlphakXZC8k6SR9StkHFC+kr+41A0GqYtGcoCOo/Qz+MmJK26UiZOKaBpVXjPNFq8FxJzjGn/m+cpTWGBqVAkwR6RjEYSjXORaWS10qBF8Z4YYxtKMIIVP28G/zFF8XJ9qZWmBpiYHRPahmdMI6bXiaDe+65hzPPPJPnnnuOD3/4w+y8887MnTuXD3zgA9x0002sXbu2qfZlREcIIYQQLXPwwQdz8MEH8+lPfxrf97n//vtZsWIFK1as4Pvf/z61Wo1ddtllq5Dv4ZJCRwghhGiBZu+cmmx3XQFYlsUhhxzCAQccwMKFC/n5z3/Ot7/9bZ5++ulRtymFjhBCCNECIU0+GXnMetJ61WqV3/72t9x9992sWLGCBx98kLlz53LooYdy9dVXN4I/R0MKHSGEEKIFZDJy4tBDD+XBBx9k55135pBDDuEjH/kIhx56KN3d3WPSvhQ6QgghhGiZ3/72t/T09LBo0SIOO+wwDjnkkKZuJ3+5HeauKyGEEGJ7InddJXp7e7n22mtJp9N86UtfYsaMGey9996cc845/M///A8bN25sqn0Z0RFCCCFaIIrixqMORrv/ZJDJZDj66KM5+uijARgYGOC+++7j7rvv5stf/jLve9/7eMMb3sDjjz8+qvZlREcIIYQQ241MJkNHRwcdHR20t7djmiZPPvnkqNuTER0hhBCiBcImR3Sa2Xd7EkURDz30ECtWrODuu+/mN7/5DaVSqfG05G984xssWrRo1O1LoSOEEEK0gBQ6iba2NkqlEj09PRx22GFcccUVLFq0iJ133nlM2pdCRwghhBAt82//9m8sWrSI+fPnj0v7UugIIYQQLRBGzY3K1KPzXvfOPPPMcW1/x5qMHMdgOsSmhYqSAD8V+MSmjc62gZtDhV4SpOnXUFGAclLJrmGYhHkONqU0OpNHFzpfEqRYJSoNQOChnDREQRIUGoUQRSjTQmkD5bigNTrXluznVdGpJBQzrpRQZj0wr70Lpy0HUYhfqkCQHCcKfOIownBtlKEbQZFEIXEYobRG2yZKa8Kqh53PEJf6qW0pEocRVsZF1cMqw2oSRBl5AX65ShzGuO2ZJKSyWkMZGq11/TuIsPNpav0V/P4ykRcQVOtLqdIIFzXdJFy0vH4zQamCtix6n16L4ToEVS8J49zYizY0kR+Qm54FQNc/S+n5EqEXEnohhm1Q3VLFbXeTsM6ij5N3iMOI6pbk5xFFMYZlYLhW8pn9kMiL8AbKyfdoJSGSQSXArwZEfoCZstj81CYiL0yCUF0TwzaIw4ig6qENhVdK+jqweiMD64pUNpdw2jOkp6QwLJP8nB4iPyCOIiIvIKz6+KUacRg3wj9rW4pEfoDTlk3CRA2NlUnOKTuXwXTt5HwLkzbiMEIbyc/NGyglP0/HRZk2Ud9mlGmjTBu/VCUOfHQmT7DumeRnH/igdXK+AcQRca2K8msor0RsmMTaRHmV5PuuFZNzFIhNO/n7EEeYg8GKQBzHuEbyOoqTME8AP0rCEst+SBTHDNRCqmFELYipBhFZOwl4nJK2KfshBdek7IeNdqIophpGZB0TrZIgyLRt0FcLsLTCNQ1yjkmxGjSCKTuzNivX9jWCPv16UGQhbVFIWYRRjGsajRDPYjUgYxmN0M+XBoBC8gtmMKxz8M+GVvRWfFK2+eK5pRV9ZZ8wiknbBp1Zm5RtYFoGA1WfVNZG1b+zWhDR1ZnGtAy68g6BF5KqB24mf0VfPH5cvzU465rM68qSytqEYYSbsmhLW7xQqjG7M4NtasIgolr2yeQdcu5gEKfBlLzDrO4sXhCRtg2K1YB01kbXg0+9IAnQjKOYnGs1tqsFETnXoqfNTT67kYSOTs25DFSTc8LQikr9ZzZQDci5JmUvZF5X8m/VYJBoR9ZuBK0OBovapibrJj9bux6SahuaMIaskwSIVoMIy1B0pCwKjklfLSCMoTNtY2mNpRVRHCd/NhRpy0Arha6HrZoGjcBZ0wC3/u9PxY8I45ggBEsrbENhKIVjKgZ//F69uLANRRDFaAVaJcGfE/kQvsFLV80s4rXtWIWOEEIIIXYoculKCCGEaAGZjDwxpNARQgghWkAeGDgxpNARQgghWiCMmxzRmSQREONN5ugIIYQQYtKSER0hhBCiBWSOzsSQQkcIIYRoASl0JoZcuhJCCCHEpCWFjhBCCNECQf2Bh80s4+Xzn/88Bx54IOl0mra2tmHtE8cxS5YsYfr06aRSKQ477DCeeOKJcevjcEmhI4QQQrTA9vxkZM/zOOmkk/h//+//DXufL3/5y1xxxRVcddVVPPjgg0ybNo0jjjiCgYGBcevncEihI4QQQoghLr30Us4//3z23nvvYW0fxzFXXnkln/rUpzjhhBPYa6+9uPHGGymXy9x8883j3NtXJ4WOEEII0QJRk6M5gw8M7O/vH7LUarUJ/yyrVq1i/fr1HHnkkY11juNw6KGH8tvf/nbC+/NSO06hozSxaRFbDioMiA27vl4RG3by2jCIDRtlOclbfo241A+ATmWSEM9MDmW7qNADbRA7GXQqkwQvZvIoyyIOQwh94sCvB3gajW7oTI44DJNwT9OGKExCPE07Cf18SbhnVD92HPjYuQx+sQRAbcsAViaFMjR+qUIcRhipNHEtCbkcDJlUhib0kiBQv1jCcG1M10YZBn6pSuT5WPk0oRc0XmvbQFsm2rIort2EmXEByM3qJqh62Lmkf6EfEEURpmti51zczgJKa4KKT1D1MF2H4ro+Qi/AyrgY9ZBEbZnEYUxU71etdwC3PUWtd4DihhLPPfh3lKEwbIP0lDR+NSDXk8XOWFgZi9APye+UI/J9ojBGa4WdsTBTJpEf4A1UqfXVcNtd4jAk051GGYrqlip2xsIvDYaYJqGhbrub7FdfX+v36F+9idAPk3DOakDoJcGG0xfuhl+qYqZM/FKVWm+R/JweAAzXroeAekRhXG+rRlCtUd3cj53PJIGe6RTaNgkqHto2cdqyVDf3YzgOoR+Q6ekkCiOiMCIzYyqh7yehsVEI2iCqlPD76+dFrYJO5wgHelGmRVyrEBV76yeaQdS3GUwL4ghMB+1VkiBPILbTL/7VCKoQRyi/TKw0XhjjR+CYGqUUYZyEJ2qlGBwpDyNQCnK2iWtpco5B1Y+IiDF0EghZcJKfedEL8MOYbP0c8MMIpx70OBjc2J1zMLSi7IekLQNDQcExSdkGKdugLZUE3Q4GbwJJcGXKGnKstGU0fglMa3MJ46QvOdds7JuyDeZOTcIyB0NDB0NBAeZNzbChP/m7ZNT7OdgPQ2sKabvRhzCKk/BOPwnvLFYDTK1wUhY7tadRWlHzQnKuRS2IsBwTx0nCMe16n8IoJmUZdLanmD+jgOeFdGQdUrbJjI4UadvASZmkszbtBTcJNQ0jZndm6Mg6hFFM1rWwzaSPlmNi1oM1B/sY+BE9BZeufNKuY2oqXkBHxibrmFT8kJRtNoJL29IWxaqPF0SsL9boyjt4QUTFD2lzk+9qZnuKKRmbrGuyU0eqcT4Nfv+GVjimJm0lAa1py6AjZZG1DVxD1wNfI7wwpuCatLsWllZY9XDOtGU0gj9ztkkYx1j1gM4wAs1g2CwEIXhhjFLgmroR4gmQMpPvC8DUSdCnY2gikjkyg6GfYZzsP5H3MYVx3PQCMHPmTAqFQmNZunTpBH6KxPr16wHo7u4esr67u7vxXqvsOIWOEEIIMQmtWbOGvr6+xnLxxRdvc7slS5aglHrV5aGHHmqqL6qeLj8ojuOt1k00eY6OEEII0QJj9RydfD5PPp9/ze3POeccTj755FfdZs6cOaPqy7Rp04BkZKenp6exfsOGDVuN8kw0KXSEEEKIFpjoBwZOmTKFKVOmjPp4r2bu3LlMmzaN5cuXs2DBAiC5c+uee+7hS1/60rgcc7jk0pUQQgjRAtvz7eWrV69m5cqVrF69mjAMWblyJStXrqRYLDa22W233bj99tuB5JLVRz/6Ub7whS9w++238/jjj/P+97+fdDrNe9/73nHr53DIiI4QQgghhvjsZz/LjTfe2Hg9OEpz9913c9hhhwHw1FNP0dfX19jmoosuolKpcPbZZ7Nlyxbe8pa38Itf/IJcLjehfX85KXSEEEKIFgjjiDCKmtp/vCxbtoxly5a96jZxPHRESSnFkiVLWLJkybj1azSk0BFCCCFaIGry8lM0jpeuJpPX1RydpUuXNq4DCiGEEEK8ltfNiM6DDz7Itddeyz777NPqrgghhBBNC6MYPYF3Xe2oXhcjOsVikfe97318+9vfpr29vdXdEUIIIZoWRM0mmLf6E7w+vC4KnQ9/+MO8853v5B3veMdrblur1bbK/RBCCCHEjmm7v3T1gx/8gEceeYQHH3xwWNsvXbqUSy+9dJx7JYQQQjRHLl1NjO16RGfNmjWcd9553HTTTbiuO6x9Lr744iGZH2vWrAEgNh0wbGJtEhsv1ncq9JPQTaUg8FFRkAQcmkmIoHLqxzWdRrCiTmUgCokGtkCptxHKCQwJ8FSmhdIGOEkQps7kUW4G1dHTCGgE0Lm2+rFSKK2JSv1JuGcUJaGcgYfh2mjLJCgWsTIpIi8gDiOU1pgpm6BYBK2x6iGcURhi2EnQZRxG9D29Fm2baMskO2MKfn+ZyA8Iqx5h1aPWO4A3UMbKuFQ3D6AMjekmn8kvVwAabZc2lAmrtcb7cf32SDNlk5qSw8q4hH6ANhTa0GjLJPSCRhtmyiTT04lX8ihtGEBpTXVLBa0Vj/1pM6ZrEnohhq0pzGqjMLsd0zWpbqmHloYx2RlTsVyT0E+CRbWh8Eo+hmUQ+hFxGGG6DrmeLKZrUtlSRRmaoBIQegHKUGS7M8RhTBxGRF6EYRkElQC/6GG6JvmdcuR3ymO6JoZlYOczRF5IZlry89KW2QhQ9UtVSs+XCf2QTHcGJ59C28m5UN6whfKGLfj9ZUI/qH+nVYKqhzI0cRgRRyGma1Pd3EfkBRiWSaqzQGpqO0b71OQciZJwUa+/RLqrnbBUBNNGu+kkFNayUaaNSmVQlk3kVVGGQVxLwjpjq34OKw2h9+J5GgWgTSK3gIojbEMRxzFeGGPpJNBzMDywFkQokuH2MIqJiPGCGMeoBzBqRdmPcAyNVgo/jLC0puyHdGVsUpZBGEPWNpmatnFMg96qT2fappC2yNomYZwEdlqGpq/s80LRwzU0Kdsg65p0Zmx27soSRTGuocm7LwZ+pi3dCO80tGJK2iJtG9imxjWTwM+BasALJY+UZQwJ57RNTcpKgjHTtkHONfFrQRKiGUR0Zh26cg6dGZuuvPuS/QzcdLLO0IoZ7Wk6OlJJH0yNUz++qRW79eQbYaIdeQfH1GzeUsGs9/cN3Vm0VlS8kIoX1ANFTdyURVvWbvzMNvRXG/0aDBndXKyRc81GcGm5HkZrm5ppXRmyrklHxmGn9hQzOlLYpqbgmMzrypCyknO14odJSGrapiOThBtnbJNC2sI2NW0piwEvoJC2sAxdD2BVzMi7pGwDL4joySXfTbEaNMJZLZ2cD5AEwTpmcjzH0CgFfhjjmkk4rKGgI2WRtgzSloFSyT/P6XofDQ1xTBIgW2/T0GAbCttQRPVYzsFztugn/z4ZSpGykjDPShBRCSLCKAmoNVTyvlYwkalM2/MDAyeT7XpE5+GHH2bDhg3st99+jXVhGHLvvfdy1VVXUavVMAxjyD6O4+A4zkR3VQghhBDboe260Dn88MP5wx/+MGTd6aefzm677cbHP/7xrYocIYQQ4vVCLl1NjO260Mnlcuy1115D1mUyGTo7O7daL4QQQryeyAMDJ8Z2XegIIYQQk1UYxSgZ0Rl3r7tCZ8WKFa3ughBCCCFeJ153hY4QQggxGcRxTNzEqMzLQzXFtkmhI4QQQrRAFMVNzbOROTrDs10/R0cIIYQQohkyoiOEEEK0QBzHTV1+kktXwyOFjhBCCNECcdTkHB25dDUsculKCCGEEJOWjOgIIYQQLSCTkSeGFDpCCCFEC8RRsjSzv3htO86lK6WGnlVxBHFMbDkor5TE4WqDWJtJurN+ScJ5PcmcbCdEISpdqK+3UZaTpEXr+leZbkNn2xqJ3jrXhooCdCHZN3YyqFqSWq4Mo5GObk6dAaaFcjPoVIa4ViUOPOx8Jkk8N23iMCKseljt7YS+j7ZMUj3dmGkXM50CIKh6RF5AUE6SvrVl4g2UiKII07WJ/ABtmTjtWeIwws6l8UsVtG2htMbrL6MMRVit1VO9A7Rl4fWXcdpySfthRFD10JaJ255JUtQNTWpqOwBuR/L9BJUkqTusejjtOZShqfUWsXMuhms3UscjP0gSwm2DA948HTtrU9gpT+hFWBkXt7OANjSGbRB6IeVNZYKKh19N2q9uqZLqTD5P8r0q3HYXb6CEX/LJz8wn33HKJDUlnfzZtdG2gVfy8AZKZKdnMVMmhdl5rKyNYRt4JR87l8bKOKSnpJKE95KHti3iKMLOp/FLVYJqDW3oRn+iemq0k0++70GDKfBefwnDMhvp805bFqUNvP4y2jLRtomdzxBUa1hzdieqlom9Kmij3ncnSU4PI6LeDcReFaU1ynZRbjo5j30vOd98H1J5VOhB4CcdCWqowIc4RoUBsdIQR6gwed8LY3KOgVYQAZZWaFQjDdo2kjRySBKfDQ1+FBHFMSUvIm1pCq5JwU2SyNOWbiRPR3GcJF5rhWloojimWA2I4pisa1ILIvwoSlLMo5hpbS5ZN/m7OC3r0OZa+GFMT84hXU9Cj+KYF6p+kjpebzvrmrimgWMmyeG2qZN2naTd7pxD2jYopC2KtSBJK3dMdupI4ZpJG7apmdWdpSvv4nkhYRTTUU8QL1Z9Zk7JMG9qNklJ70zhBSFd+SRQuC1t0VvxyeYd2tIWhlYsmN1OZ9ZOUtDryeWFtI1pJUnjjql5oehhmrqRTr6xv0ZPwWVeV5ZNWypU6ueWqVXS/5SFF0RsLtZoS9vs1J6mK+8wb2q2kdruBRFtaZuegktX3iFlG41U9LIfMjXjYJuandpTFFIWYRTTlXPwwogZhRTVICRtGczuTNNb8ZmStjGUohpEVMMIrRR516Ir62BoRdELGj8DrZI0+1oQYhlJmr1jagyVnDOWkWSF+1FEwTUp+8n7fhQRxjFRnEQkdKQMHFPhmIowSpLKLa1w6/81tcKsp5prknWD621DEUTJxN1akLSnFdg6OXcjYvwoph6ETiiDJJOOjOgIIYQQLSB3XU0MKXSEEEKIFpA5OhNDCh0hhBCiBeT28omx48zREUIIIcQOR0Z0hBBCiFZockQHGdEZFil0hBBCiBaI4hjVxITiSCYjD4tcuhJCCCHEpCUjOkIIIUQLxHGTk5FlRGdYpNARQgghWkDuupoYculKCCGEEJOWjOgIIYQQLRBFoJp6YOAYdmYSk0JHCCGEaAGJgJgYO9alqzhCxRGxlQQfYhgQ+MRWGhXVwxfrAYex0sReBUyb2LAhCpJgRNMmrhaJowhl1cM+tdEIVsQwkuNYTiMYNPZrSdNuBuVVQGlUWxc6nUuCGLVBHIVJX6ol0AZRsRdlu8RhlASCAmY2i+HaxL6P05ZDmXb98PX9gTiM8EtJeKRfqhJHEWY6CQ4Nqh52Pk1Y9QgqHsrQSTinbWFYJt5AldAL0ZZJbUsJbdX7H4Z4AyXiMAkGzXZnMF2boFTFcB2CakB2xlTCeqColXGJw5D87A4M1yb0A+xcGtO1Md2kz4Zl4eRT5GZNpbypgl/yMVMmbXPbyXSl0baBYWviKEJbJoZrYaZM2ue141cD4ijCydsUZhcwbANlaJSRnM5BJSCOYrRlEnph8h0amqAS4ORtdH27TFeOoBpgpVM4eYdMV5rc9CyGpZnx1lkYtkEcRXgDVYJ6YKcyNGG1Rq13gMqG3uT7ty2cthyRF2K59b5mUrj1gMdUZwHDNrFzmUY/Qz9AGRpvoIwyNHEUEvkBdj5DZlpn8pktC53OEdcqRJUSOpMjrpYwM0koalj1knMkipLzWRsoyyaulBqv0To5p1XymVU91Da2U8m5OvhXw7C3+uti1IMPvTAJPDSUolpPPExbBlopvHqoI9AIaExbBkolwZOWVmRtE0PTCPYsuCaOoelIWWwuexTSFmEMu03J4pgaS2v6qz6GVnS4Frap6UzbTMs5aKVIW0l4p2Nq0pZu7JOxDDaVfdpSFh0ZG0Mln6Eja5OyDboyDpZWOKamPWUxqzNNZ9qmI2M3gkPDKAkdfUN3DkMryl7IvKkZsmmLlJWEZCaBlRZZx6Qza7NbT47OrMNuPUl4rGNqCimbrpzDvK4sszszzO5M05N3sc3k51D2QmpBRBjFvGF6noof0pFxWNdX5U2z27FNzezODCnboCNrk3NM8rkkfHPe1Cz7zGzDNjU516RY9XFMzW49OTqyNj2FFF4Q4QURb+jOAbBbTw5DqcbxM5ZByjJ4fqBGV8YmrI8qtKUtUvUw0FT9O85YBjNyLlnbJGUZFByTvzxfJG0Z+GHyfRW9gJRl8LeNJQqOybSci6EVq7aU6z8jA0srCq6JoRQpy8BQiqIXYtfPmzCCrG3gmhqtFEqBpTXVIGqEdQYhmEYS6mnqZD9DQ6r+uWxDYRpJhnMYUQ8PTc7fMIYwjpPA1vq5aSiFayQ/08E26t0Rk4iM6AghhBAtEEfJ0sz+4rXtWCM6QgghxHZiMNSzmWW8fP7zn+fAAw8knU7T1tY2rH3e//73o5Qasrz1rW8dtz4Ol4zoCCGEEC2wPd9e7nkeJ510EgsXLuS6664b9n5HH300N9xwQ+O1bW99WXyiSaEjhBBCiCEuvfRSAJYtWzai/RzHYdq0aePQo9GTS1dCCCFECwyO6DSzAPT39w9ZarVayz7TihUr6OrqYv78+XzoQx9iw4YNLevLICl0hBBCiBaI4rjpBWDmzJkUCoXGsnTp0pZ8nsWLF/O9732PX/3qV3z1q1/lwQcf5O1vf3tLCy+QS1dCCCHE69qaNWvI5/ON147jbHO7JUuWNC5JvZIHH3yQ/ffff1T9eM973tP481577cX+++/P7Nmz+elPf8oJJ5wwqjbHghQ6QgghRAuM1WTkfD4/pNB5Jeeccw4nn3zyq24zZ86cUffn5Xp6epg9ezZ/+ctfxqzN0ZBCRwghhGiBiU4vnzJlClOmTBn18UZq8+bNrFmzhp6engk75rbIHB0hhBBCDLF69WpWrlzJ6tWrCcOQlStXsnLlSorFYmOb3Xbbjdtvvx2AYrHIhRdeyP33388zzzzDihUrOPbYY5kyZQrvete7WvUxABnREUIIIVoibvKhf+P5HJ3Pfvaz3HjjjY3XCxYsAODuu+/msMMOA+Cpp56ir68PAMMw+MMf/sB3vvMdent76enpYdGiRdxyyy3kcrlx6+dwSKEjhBBCtMD2HOq5bNmy13yGzkuPn0ql+PnPfz5u/WnGDnPpSteKSVin6aKCKmhNbNioOHox0DOOiU0LtPniuihERQFxtURsOijTgkx78p5pJ2EjTgZyyXVP5deIvWoSkhhHRKX+ZJ/B0M3KALE2UaFH5FUx2ruIA59ooDfZ380k4YymBYGfBD6W+hsBomHVA8DrLyWfK5NH22ayPoowUzZxFBFUPAzXRukkGNOwTAzLJKh4WJkUdj6N4TqNoM7BQEwAv1SjsqWKMjRuZx7TdYi8AG2b2Pk0qh6mF0URU/bZGaVVIwA0qHqEfvLduR0FIj+g9+n1SV8tEyufAcBwbQzXxmnLYmcttG2QmdaGNjTVLVUMyyTVmUHpJPjSL9WIwpjicwPU+pPwUMM2iMMIJ++gdBLamepqI9OdIdWZxS9VgSS8Mz8zR6Y7g2EblDeXCP2AoOrhtrmU1m8m8kJCP8Ir+dT6PVJT2zFdE6U16a48URjjl6oYlkZbFpVNA4R+gGGZVDf3UesdwMoknyPVWcCwTLI9+UaQ5+DPw3TtegCon5wPYYSVSaFz7ZgZN/mOpnYTVj2cjgLhxrWEpSJh1SPs24xyMxiOg9dbTIJWowhtWhid01C2+2KQJyTnj5OEd8Z+LQmf1SaxlUrCZaOI2HKT870euqOCGpaGWhARkQQhQhKGWPIjwjgmjGOytsZQCktrojgJdgzruTu2odEowjimI2U1wh9dU+OHMVopLCMJVcw7Jq6hCcKIrJ0ERs4quORdi66MTd61KDgWrqkpeiF+FDXCQ8t+xKxCioKTnHtW/Ry2tKZYC2hPJX9ndsq7dGeTu1D8KCbrmo1QUj+MSNsGO0/JNAI7B4NAwyjmjTPb8ILkg6VtA0MrNgzUsA1NV95hflcWQysqXkAYxXRkHAppi3ldGaYVXLwgopC26v0NMbRip/YUO7Wnmd+d46/rB5JAySGBoSZ7zSiQsg1StkGxGjCtzWX3njzzpmaZVnCZ25Hm71sqTCu47DmjgG0aFFIWXVmncbzesk9n1mZ2/bP5YUTetRrLG6ZlCaOYgmvSVt9nas5hVnuaQtpij54cFT+kVO93R8rCMTVlP6RYC+jJOURxTNY2GoGtADt3pOnJOeQdk7xjNgJYtVIUHAtDg6EV7SmL7qyNRhHFMYYGP4yxdHJuaRR+FGEoRfSS81CjqIZJ0OdgyGwYx8SAF8akTE0QxdiGQqskuDOOk6BPWyd/hiR81TYUtpFs44UxZj3oU0wuMqIjhBBCtMD2HAExmUihI4QQQrRAFMXQRLEynqGek4kUOkIIIUQLxFFIXJ/WMNr9xWvbYeboCCGEEGLHIyM6QgghRAvIiM7EkEJHCCGEaIE4iposdKIx7M3kJZeuhBBCCDFpbdeFztKlSznggAPI5XJ0dXVx/PHH89RTT7W6W0IIIUTT4jBsehGvbbsudO655x4+/OEP88ADD7B8+XKCIODII4+kVCq1umtCCCFEU+I4bMzTGdUSS6EzHNv1HJ277rpryOsbbriBrq4uHn74YQ455JAW9UoIIYQQrxfbdaHzcoPhYR0dHa+4Ta1Wo1arNV739/ePe7+EEEKIkZK7ribGdn3p6qXiOOaCCy7gbW97G3vttdcrbrd06VIKhUJjmTlz5gT2UgghhBiepi5bNVkk7UheN4XOOeecw2OPPcb3v//9V93u4osvpq+vr7GsWbMGgFjpJLgQQJvJ69AjslMARG4SI69rJWKdDHQpOwWpPCgN2c6knWoJFSaBjAQecbWUvB+FSWii0kmwIkDoEwc+sZVK1imNst0kJDTw0elcEjJqJ4vOdxB71aQt0wZtYDhOvc8GceDhDZRQjoudzzSCPs20S+QHBMUiQcXDL1UxUzba0JipJJDTzLj4pWoS+FmtEYcR6a62ZDvLxOsvYedc3PYM2tCkp6SIwygJjbRNUl3tWBkXt7OQfA9hROT5DKx+nnRXEt6ZntZBblY3AE5bjlrvAGYmRaozg2GbZHo6SXXmcdpzlNZvJtWVhKMqrYi8ECuTory5hGEbaNsk8gMiP8DrL+HkUxiWJj0ljWFprHyaXE+WVFc7oR9S3tCHYWviMEQbiqDqYeczOAUHw7VJd+XxSx6Wa1LeVE5+fBWfzjd0YLo2dj6Fk3fQWtE2r5M4jNCGIo4iCjvPQBuqESTqtGXpWrBL0ka1RnpqO0HVo/MNL440KkPjtOXQtkkcRoRVDyvjElQ9lKExXQc7lwaSgFOiEDuXJqx6aDdZH0chyklR6x1A2yaqfl6pVIagWkNbSehoUK4kp0gqQ9S3mdirolOZJLi2VoEwROn6ORpHxG4uCfo07eTcBfCrYFjESmMbSbikBlJmEnBoqCT80DU0cQw528Csn+aDwZ45x8A1NWE9oNHSCj+K6UxbjSDOgmvSnbFxTU3WNplZSJF3k7BIgNltLo6p6c7Y9dBQRcE1mZqxsbRiStpmStombWnaU0m7YQyGgpRl0JWxydpJxyxDE8aQtZNgyZ3yDgXHpDvvkraSIMqSH+IFEY6h6cja2KYm65hMTSd/nppzyLomtqmZ353FNY1GgGfKTsJK//5ChY5Mst1uPTkK9TDR9pRFT8El65p4QYSlFWEU4wURs6ek6cjadLe5tKUsuvIObWmLzoxNd/2YWddkY3+tEQ66704FZk9J49XTU21DJ99P2kqCRf0Qx9T8fUuFF0o1UvUQ0lQ9cFPXA0sBOlIWrqGZ35WlFkRkXZNC2qI9lSyuoXlDZ4ZpWYc212LdQI20lXxHZT+iM2MD0JWxqfgh7a5FwTHZb3Y7uh6KObOQYq/uHFoperIOrqkxDQgjaHctNpU9XENTDSMsrSk4yc/TMhTVIMI0IGVpXEtTC5NAWernZByDbSiCKAniHGS+JLRTqeS8GNxPQz2oNgn8jOOYlyYwxHGM5nX0S1EM2+vi0tVHPvIRfvSjH3Hvvfey0047veq2juPgDBYHQgghxHZKLl1NjO260InjmI985CPcfvvtrFixgrlz57a6S0IIIcSYkAcGToztutD58Ic/zM0338wPf/hDcrkc69evB6BQKJBKpVrcOyGEEGL0oihMLik3s794Tdv15cirr76avr4+DjvsMHp6ehrLLbfc0uquCSGEEOJ1YLse0YkHZ5UJIYQQk4zM0ZkY23WhI4QQQkxWUuhMjO360pUQQgghRDNkREcIIYRohTAk1k2Mykio57BIoSOEEEK0QBw3d9eVhHoOj1y6EkIIIcSkJSM6QgghRAvEUdTciI48MHBYpNARQgghWiBu8oGBctfV8Owwl65iO01kZ4kNi9h0QOkkUDMMIPSScEOliJwMKgrqO0VJAKfSybo4RqVyEAUQeKANlJtBhV6yuZUithyUnUrWaQOjvSvZz7SSYzpZYsNGaY1yUkm7WmO0T0Xlp6AzeXSurR4SqjFnzUelMijTIo6iJABSG3j9JdAG0UBv4zOGVQ87nybd1Y7TliP0ks+hDJ2sa88mIZBVj9BP3ovCCMM2Case+bk9OG05CjtPx2nLEkcRfqmKnUtTXLsRM+1ipl0Kc6dR2HkGyjAa4ZVef4nU1I6kf0CmpxOnLUd6ahu5Wd24nQWU1lQ299Ox22zCqke6qx1taAzbINuTR1smuRntpLuy5GZ247RlcdpypDoLmJkUbbtMp/vNu5FqdwHo3HMuuZld5GZNxcmnyM/qxO0sYLomhmViZVzsnJu0MbUdr+iTmpKm54A5tM+fiTY0xQ0lgqpHYecZOG05rKxNdsZU/HKVKIyx0ilM18GwkqDRoBpgZVy0bWLn0sRRRGbGFDp2n42Vccj2FJIQ0WkdtO8+G79UJTNjCto2sTIpqpv70G4aM+OS6iyQ7mrHzBeIKyW0YWBmXGKviuHaKNMm9pOQVu2mUY6LclzCgV4iP8DKpFBuBsO10Zl88vOslDA6pyf/LXQSlQfAMMB0iC2HKFVA1UrERvJzirVJrE1UUGucR4ZfxlAKpZLQxOglz7NSKglODF+2ztAqCfckxqqHLPZWA9JWEjzpGAZaKaakk8BLP0z2787azCq4TEnb+GEStril4tORtuirBUm4aD3csz1l0ZN1cAxNGCXBotUgImcbaK3I2QYdqSTgsj1lEUYxm8vJ382sbZBzTPworgd/mvhRhKEVs6akSVsGs9tSzG5LnrhuGpqFs9uxtMI2Nbv35HHMJLR0zxkFDK2Y3Z4mimPe0J2lp80lXw+2dExNsRpgacWu3Tl6sg69ZZ+0ZZCyDXbrydGVTfL49p/bwYyOFB1Zm6xrYmiFYxqEUUzGMrBNTbEW0JVzyLtW/TtzKPvJL7gZeZcwijG0anxXPQWXt+/WhaEVXTknCUnNOnRlHOa0p2l/SehoV8am7IekbIPpebf+s7DIOiYvVHy6s8l54pgaP4zpybtEccyCmW1kbQPLSEJQDQ1+FJO2kqDTgVrAlHQSzFpwTcp+SE/OYUPRR6kkVDRnm6QtTclLPouhoStjJYGvjkaThMiGUUza0tiGIm1pvCgma2lSpqLgGNhGEkBr1MNETa1QJL/cTENhKIWpQSnV+IVn1M/ROI6J6yG0ybmsMI0XQ0LF5CAjOkIIIUQLJJeuRn/5SS5dDY8UOkIIIUQLyKWriSGFjhBCCNECUuhMjB1mjo4QQgghdjwyoiOEEEK0QBSFKBnRGXdS6AghhBAtEIcRqCYKnVAmIw+HXLoSQgghxKQlIzpCCCFEC0jW1cSQER0hhBCiBeIobHoZD8888wwf+MAHmDt3LqlUip133plLLrkEz/Ne/fPEMUuWLGH69OmkUikOO+wwnnjiiXHp40hIoSOEEEKIhj/96U9EUcS3vvUtnnjiCb72ta9xzTXX8MlPfvJV9/vyl7/MFVdcwVVXXcWDDz7ItGnTOOKIIxgYGJignm+bXLoSQgghWiCOwuYmI4/TiM7RRx/N0Ucf3Xg9b948nnrqKa6++mq+8pWvbLsvccyVV17Jpz71KU444QQAbrzxRrq7u7n55ps588wzx6WvwyEjOkIIIUQLjNWlq/7+/iFLrVZ7jSOPXF9fHx0dHa/4/qpVq1i/fj1HHnlkY53jOBx66KH89re/HfP+jMSkH9GJ6+GDAwNFiOMkgVBplFcGbaK8MrFhgmE3/qy9CsQv3rYXaxMVR8l/Qw/imLiWhGoqKwSliLUJ2hi6fxwThz74KglN1AaxYSUhn36ZOIpQVkhULAGglEtYKoPWRKUKUbmKWSpDFBKVKwTlKrVqjbBcoVKpEZSrxLUqceDhV2rEYURYq2FZJnEYUal6hJUafjVZF1Rr1Koeup6Pog1NFEZJuKXnE1c9gpqHDiNqNR+75mEARhhS9HzcSg2vXGWg5uFVa5RqHn7VI/ICLEMRlasMVJNruH6lRrnqYRmKoOoTVmoorRmoeZiVGgM1j7iS9Kfo+UlQZNWjVvMJPB+zWqNY87FMI/lcfoBlaoJKjaIfMFD1MMIQI44ZqHkEno9WCv8l7QU1j3L9cylDU/QDYs/Hr3kE9e2KQYDyfJxqjWLNa7Rdqf/ZrXlQqVH0fFTNo+j7DFRrKEPjVT0qNR+jUmu0p+IYv5r8PCzLZKDmoSo1KjWPqN5Of/178itJO07951ir1LBMjelU8Co1TG1iuBUGqh6qXEUZBkapjFeuUq561Co1/FJyXvgDJcJSmahSxhoo4pfKmG6yzhgoovwakR0Smz66WiS2Q4gjYtNvnOtR7ELoAxBaAWU/wtQwUAupZ3Bi6yQk0dBQ9EKC5PQnjGM0akioZ6kaEMWQCi2KteQfZC+MMOvv63o7tSCiFsRopRhQFuVihaL2KJWSvtSCiKIdUKokP+NaENf7GxOYinI1oFKsUcajGFqUS17yOrKp1AJKeFhakYosKsUBTN+kqH0qxQEqQdKvkh1RrofgWoamGkSUQotKsUw1CKmVPSrF5JjVUo1auUq5aFP1QypBSLXkU1EehmdQCyOqpSrlIlT8CCxNrVykXDSolmpUQgtDKaqlGoZWhGby/5t+ENWPo6iWKlSUR61UxQwNKrFNOfaoloqUtU+lFuCVi5SLaaqlIl65SLWkKCufaqlIxfDxKyUqxQFq5RLlokbbJqGpKVd8nNCiXPWxAwsvjKiUypQjm5L20QrKxSqhoSmaPpVikdgyKEU2lWIl+TfRMihpj3I5+RmVQiv5OVR8im5EuVilqH2iOAmFLdVCirFFqRbhhCZxDGU/ZCC2KQ3U0EqhPAPLUPhhjFKgUViGolgNGIgsykFEFINWYCtFZGuqQbJtEMaEJMGigaHxogirHtBZ9CMMBbbWxHGMF8foWhKc6tVPbNNQBGGMUopKaWDI745xFfo0dZT639eZM2cOWX3JJZewZMmSZloe4q9//Sv/8R//wVe/+tVX3Gb9+vUAdHd3D1nf3d3Ns88+O2Z9GZV4kluzZk0MyCKLLLLIIsuwlzVr1ozb76VKpRJPmzZtTPo5bdr/3969x0VV5n8A/4wwMwwII0QwDBhKJIgiKqZiIlgq6HpLW6+RVJqkiLiaudouaKtiKauZeGFRt9bSLcB1UxEsLiqoyGUFQUQFL1xEDVBSbs7394c/Th4YLpbKxe/79ZrXi/Oc5zzn+R5mnvnOmfPMUdGNGzeovLxceFRWVmrdb0BAQLPtJScni7YpKCggW1tbev/995uM6cSJEwSACgsLReWzZ88mDw+P33fAfqcOf0ZHrVbj2rVrMDQ0hEQiae3uNOnOnTvo2rUrrl27BiMjo9buzu/G8bRtHE/bxvG0DiLC3bt3oVarn9o+9PT0kJeX1+wsppaQyWTQ09NrUV1fX19MmzatyTrdunUT/i4sLMTw4cPh4uKCHTt2NLmdSqUC8PDMjoWFhVBeUlLS4CzPs9bhE51OnTrBysqqtbvxWIyMjNr0QPC4OJ62jeNp2zieZ0+pVD71fejp6bU4QXlSTE1NYWpq2qK6BQUFGD58OJydnbFr1y506tT0Jb3du3eHSqVCTEwM+vXrBwCorq5GfHw81q1b97v7/nvwxciMMcYYExQWFsLd3R1du3bF+vXrcfPmTRQXFwvX4dSxt7dHZGQkAEAikcDf3x9r1qxBZGQkMjMz4e3tDX19fcyYMaM1whB0+DM6jDHGGGu56OhoXLx4ERcvXmzwjQg9cpF2Tk4OysvLheWlS5fi/v37mDdvHkpLSzFo0CBER0fD0NDwmfVdG0502hC5XI6AgADI5fLW7soTwfG0bRxP28bxsNbi7e0Nb2/vZutRvZlpEokEgYGBT3TG15Mgofo9ZYwxxhjrIPgaHcYYY4x1WJzoMMYYY6zD4kSHMcYYYx0WJzqMMcYY67A40XmCQkJC0L17d+jp6cHZ2RnHjh0DANTU1ODjjz+Go6MjDAwMoFar8c4776CwsLDZNjMyMuDm5gaFQgFLS0usWrWqwZXu8fHxcHZ2hp6eHmxsbLBt27anGk99c+fOhUQiwcaNG5ttsy3Hk52djfHjx0OpVMLQ0BCDBw/G1atX22U8FRUV8PX1hZWVFRQKBXr27ImtW7c222ZrxZOQkIBx48ZBrVZDIpFg//79ovVEhMDAQKjVaigUCri7u+PcuXPtMp72Nh409795VHsZC9hzplVuPNEB7d27l6RSKYWGhlJWVhYtXLiQDAwM6MqVK1RWVkYjRoygffv20fnz5ykpKYkGDRpEzs7OTbZZXl5O5ubmNG3aNMrIyKDw8HAyNDSk9evXC3UuX75M+vr6tHDhQsrKyqLQ0FCSSqX0/fffP7V4HhUZGUlOTk6kVqvp73//e7uN5+LFi2RiYkIfffQRpaam0qVLl+iHH36gGzdutMt4Zs+eTS+//DLFxsZSXl4ebd++nXR0dGj//v1tMp5Dhw7RihUrKDw8nABQZGSkaH1QUBAZGhpSeHg4ZWRk0NSpU8nCwoLu3LnT7uJpb+NBc/+bOu1lLGDPH050npCBAweSj4+PqMze3p6WLVumtf7p06cJQIPE4VEhISGkVCpFN2hbu3YtqdVq0mg0RES0dOlSsre3F203d+5cGjx48G8NhYhaFs/169fJ0tKSMjMzydrautnBrS3HM3XqVHr77bcfq822HE+vXr1o1apVovX9+/enTz75pE3G86j6b6YajYZUKhUFBQUJZZWVlaRUKmnbtm2NttNW49GmrY8HdRqLpT2NBez5w19dPQHV1dVISUnBqFGjROWjRo1CYmKi1m3Ky8shkUjQpUsXoczb2xvu7u7CclJSEtzc3EQ/sOXh4YHCwkLk5+cLderv18PDA2fOnEFNTc1Ti0ej0cDLywsfffQRevXqpbWd9hKPRqPBwYMH0aNHD3h4eMDMzAyDBg1qcIq+vcQDAEOHDsWBAwdQUFAAIkJsbCwuXLgADw+PNhdPc/Ly8lBcXCzar1wuh5ubm+j11V7i0aYtjwfNaU9jAXs+caLzBNy6dQsPHjxocIdWc3PzBvcGAYDKykosW7YMM2bMEN3czsLCAi+99JKwXFxcrLXNunVN1amtrcWtW7eeWjzr1q2Drq4u/Pz8Gm2nvcRTUlKCiooKBAUFwdPTE9HR0XjzzTcxadIkxMfHt7t4AOCLL76Ag4MDrKysIJPJ4OnpiZCQEAwdOrTNxdOcun039/pqL/HU19bHg+a0p7GAPZ/4FhBPkEQiES0TUYOympoaTJs2DRqNBiEhIaJ1a9eubVGb9ctbUue3aCyelJQUbNq0CampqU3uo73Eo9FoAAATJkzAokWLAAB9+/ZFYmIitm3bBjc3NwDtJx7gYaJz8uRJHDhwANbW1khISMC8efNgYWGBESNGtMl4mtPc66u9xQO0r/FAm/Y6FrDnC5/ReQJMTU2ho6PT4OxNSUmJ6BNJTU0NpkyZgry8PMTExIg+vWmjUqm0tgn8+umnsTq6urp44YUXnko8x44dQ0lJCV566SXo6upCV1cXV65cweLFi9GtW7d2F4+pqSl0dXXh4OAgWt+zZ88mZ1211Xju37+P5cuXIzg4GOPGjUOfPn3g6+uLqVOnYv369W0unuaoVCoAaPb1pW27thhPnfYyHjSlvY0F7PnEic4TIJPJ4OzsjJiYGFF5TEwMhgwZAuDXQS03NxdHjx5t0QvVxcUFCQkJqK6uFsqio6OhVquFQcTFxaXBfqOjozFgwABIpdKnEo+XlxfOnj2L9PR04aFWq/HRRx/hyJEj7S4emUyGV199FTk5OaL1Fy5cgLW1dbuLp6amBjU1NejUSfzy1tHREc5etaV4mtO9e3eoVCrRfqurqxEfHy+8vrRpq/EA7Ws8aEp7GwvYc+rZXvvccdVN9w0LC6OsrCzy9/cnAwMDys/Pp5qaGho/fjxZWVlReno6FRUVCY+qqiqhjWXLlpGXl5ewXFZWRubm5jR9+nTKyMigiIgIMjIy0joFc9GiRZSVlUVhYWFPdPqytni00TbToj3FExERQVKplHbs2EG5ubm0efNm0tHRoWPHjrXLeNzc3KhXr14UGxtLly9fpl27dpGenh6FhIS0yXju3r1LaWlplJaWRgAoODiY0tLShFlIQUFBpFQqKSIigjIyMmj69OkNppe3l3ja23jQ3P+mvrY+FrDnDyc6T9CWLVvI2tqaZDIZ9e/fn+Lj44mIKC8vjwBofcTGxgrbz5o1i9zc3ERtnj17llxdXUkul5NKpaLAwEBh+mWduLg46tevH8lkMurWrRtt3br1qcajjbbBrb3FExYWRra2tqSnp0dOTk4NfnOmPcVTVFRE3t7epFarSU9Pj+zs7GjDhg2ivrWleGJjY7W+PmbNmkVED6eYBwQEkEqlIrlcTsOGDaOMjAxRG+0lnvY2HjT3v6mvPYwF7PkiIar3U5SMMcYYYx0EX6PDGGOMsQ6LEx3GGGOMdVic6DDGGGOsw+JEhzHGGGMdFic6jDHGGOuwONFhjDHGWIfFiQ5jjDHGOixOdNhTExgYiL59+z7z/cbFxUEikUAikWDixInPfP9PUl0sZWVlT7xtd3d3+Pv7P/F22dO1du1avPrqqzA0NISZmRkmTpzY4PYlRITAwECo1WooFAq4u7vj3Llzwvqff/4ZCxYsgJ2dHfT19fHSSy/Bz88P5eXlonZKS0vh5eUFpVIJpVIJLy+vFj8Xr1+/DplMBnt7+98d8+M4d+4cJk+ejG7dukEikWDjxo0N6gQGBgpjRN2j7p5qrOPhRIf9JvUHifoPb29vLFmyBD/++GOr9TEnJwe7d+9utf23dREREfj0009btQ8teVO6e/cu/P39YW1tDYVCgSFDhiA5OVlUp7Hn4eeffy7UqaqqwoIFC2BqagoDAwOMHz8e169fb7aPV69exbhx42BgYABTU1P4+fmJ7tFUWVkJb29vODo6QldX97GS6/DwcDg4OEAul8PBwQGRkZGi9QkJCRg3bhzUajUkEgn279+P+Ph4zJ8/HydPnkRMTAxqa2sxatQo/PLLL8J2n332GYKDg/Hll18iOTkZKpUKI0eOxN27dwEAhYWFKCwsxPr165GRkYHdu3cjKioK77//vmj/M2bMQHp6OqKiohAVFYX09HR4eXm1KLbdu3djypQpuHfvHk6cONHiY/J73bt3DzY2NggKCmoyeenVqxeKioqER0ZGxjPrI3vGWvmXmVk79ej9eTZu3EhGRkaisrKyslbrW91P1peWlrZaH56UjhSLNqdPn6YlS5bQt99+SyqVqsGtA4iIpkyZQg4ODhQfH0+5ubkUEBBARkZGdP36daHOo8+9oqIi2rlzJ0kkErp06ZJQx8fHhywtLSkmJoZSU1Np+PDh5OTkRLW1tY32r7a2lnr37k3Dhw+n1NRUiomJIbVaTb6+vkKdiooK8vHxoR07dpCHhwdNmDChRbEnJiaSjo4OrVmzhrKzs2nNmjWkq6tLJ0+eFOocOnSIVqxYQeHh4QSAIiMjG7RTUlJCAIRbgGg0GlKpVBQUFCTUqaysJKVSSdu2bWu0P//+979JJpNRTU0NERFlZWURAFF/kpKSCACdP3++ydg0Gg3Z2NhQVFQUffzxx/Tuu++K1mt7XtfdSysvL08o27FjB1lZWZFCoaCJEyfShg0bSKlUNrnvR2m7HQURUUBAADk5ObW4Hda+caLDfrddu3ZpHXzqDyazZs2iCRMm0OrVq8nMzIyUSiUFBgZSTU0NLVmyhIyNjcnS0pLCwsJE7Vy/fp2mTJlCXbp0IRMTExo/frxoMKyvseTgu+++o969e5Oenh6ZmJjQG2+8QRUVFcL6nTt3kr29PcnlcrKzs6MtW7aItr927RpNnTqVjI2NSV9fn5ydnUVvAiEhIWRjY0NSqZR69OhBX331lWh7ABQaGkoTJ04khUJBtra29J///EdU5+DBg/TKK6+Qnp4eubu7065du0Sx5Ofn09ixY6lLly6kr69PDg4OdPDgwUaPxZYtW8jW1pbkcjmZmZnR5MmThXVubm60cOFCYdna2ppWr15N7777LnXu3Jm6du1K27dvf6xjcODAAerfvz/J5XLq3r278P9tCW1vSvfu3SMdHR364YcfROVOTk60YsWKRtuaMGECvf7668JyWVkZSaVS2rt3r1BWUFBAnTp1oqioqEbbOXToEHXq1IkKCgqEsm+//ZbkcjmVl5c3qF/3HG+JKVOmkKenp6jMw8ODpk2bprV+Y4lObm4uARDu/XXp0iUCQKmpqaJ648ePp3feeafR/oSGhpKpqamwHBYWpvV1rVQqaefOnY22Q0T0448/kkqlotraWsrMzCQDAwPRDVhbkugcP36cOnXqRJ9//jnl5OTQli1byMTE5IklOvr6+mRhYUHdunWjqVOnipJi1rHwV1fsmfrpp59QWFiIhIQEBAcHIzAwEGPHjoWxsTFOnToFHx8f+Pj44Nq1awAenoYePnw4OnfujISEBBw/fhydO3eGp6en6OuD5hQVFWH69Ol47733kJ2djbi4OEyaNAn0/7d6Cw0NxYoVK7B69WpkZ2djzZo1+Mtf/oJ//vOfAICKigq4ubmhsLAQBw4cwP/+9z8sXboUGo0GABAZGYmFCxdi8eLFyMzMxNy5c/Huu+8iNjZW1I+VK1diypQpOHv2LMaMGYOZM2fi559/BgBcu3YNkyZNwpgxY5Ceno7Zs2dj2bJlou3nz5+PqqoqJCQkICMjA+vWrUPnzp21xnzmzBn4+flh1apVyMnJQVRUFIYNG9bkcdqwYQMGDBiAtLQ0zJs3Dx9++CHOnz/fomNw5MgRvP322/Dz80NWVha2b9+O3bt3Y/Xq1S3+P9VXW1uLBw8eQE9PT1SuUChw/PhxrdvcuHEDBw8eFH0Nk5KSgpqaGowaNUooU6vV6N27NxITExvdf1JSEnr37g21Wi2UeXh4oKqqCikpKb81LKHtR/tT13ZT/amPiPCnP/0JQ4cORe/evQEAxcXFAABzc3NRXXNzc2Fdfbdv38ann36KuXPnCmXFxcUwMzNrUNfMzKzRduqEhYVh2rRp0NHRQa9evWBra4t9+/a1OC4A2Lx5M0aPHo0lS5agR48emDdvHkaPHv1YbTRm0KBB+Oqrr3DkyBGEhoaiuLgYQ4YMwe3bt59I+6yNae1Mi7V/j3NGx9ramh48eCCU2dnZkaurq7BcW1tLBgYG9O233xLRw0+VdnZ2orsaV1VVkUKhoCNHjmjtj7ZPiykpKQSA8vPztW7TtWtX+uabb0Rln376Kbm4uBAR0fbt28nQ0JBu376tdfshQ4bQnDlzRGV//OMfacyYMcIyAPrkk0+E5YqKCpJIJHT48GEiIvrzn/9MPXv2FMX68ccfi2JxdHSkwMBArX2oLzw8nIyMjESfpB+l7YzO22+/LSxrNBoyMzMT7hjd3DFwdXWlNWvWiMq+/vprsrCwaFF/G/v07eLiQm5ublRQUEC1tbX09ddfk0QioR49emhtZ926dWRsbEz3798Xyvbs2UMymaxB3ZEjR9IHH3zQaJ/mzJlDI0eObFAuk8kaPF+IHu+MjlQqpT179ojKGusnkfYzOvPmzSNra2u6du2aUHbixAkCQIWFhaK6s2fPJg8PjwbtlpeX06BBg8jT05Oqq6uF8tWrV2s9xra2trR27VoiInJwcCADAwMyMDAQzk6VlpaSnp4enTlzRtjm888/F15LRC07o9O3b19auXKlaN+bNm0SxporV64I+zYwMKDVq1c36Gtjz6n6KioqyNzcnDZs2NBsXdb+6LZeisWeR7169UKnTr+eSDQ3Nxc+iQKAjo4OXnjhBZSUlAB4+En84sWLMDQ0FLVTWVmJS5cutXi/Tk5OeOONN+Do6AgPDw+MGjUKb731FoyNjXHz5k1cu3YN77//PubMmSNsU1tbC6VSCQBIT09Hv379YGJiorX97OxsfPDBB6Ky1157DZs2bRKV9enTR/jbwMAAhoaGQqzZ2dkYPHgwJBKJUMfFxUW0vZ+fHz788ENER0djxIgRmDx5sqjNR40cORLW1tawsbGBp6cnPD098eabb0JfX7/R4/RoW3UzUer619wxSElJQXJysugMzoMHD1BZWYl79+41ud+mfP3113jvvfdgaWkJHR0d9O/fHzNmzEBqaqrW+jt37sTMmTMbnAXShoiE4z169GgcO3YMAGBtbS3MUnr0/6Ftu+ZcvXoVDg4OwvLy5cuxfPlyrW0/TrsLFizAgQMHkJCQACsrK6G87gLc4uJiWFhYCOUlJSUNzvLcvXsXnp6e6Ny5MyIjIyGVSkXt3Lhxo8F+b968KbRz6NAh1NTUAHh4lg0AvvnmG1RWVmLQoEGiuDQaDbKysuDg4CCMAfT/Z1QBCO00dSwera9Wq5Geni4sN/a8bAkDAwM4OjoiNzf3N7fB2i5OdNgz9ehACjwc6LWV1X0dotFo4OzsjD179jRo68UXX2zxfnV0dBATE4PExERER0dj8+bNWLFiBU6dOiW8AYeGhooG57rtgF8H8aa05E2rqVgfHcQbM3v2bHh4eODgwYOIjo7G2rVrsWHDBixYsKBBXUNDQ6SmpiIuLg7R0dH461//isDAQCQnJ6NLly5a22+qf80dA41Gg5UrV2LSpEkN1rUk6WjMyy+/jPj4ePzyyy+4c+cOLCwsMHXqVHTv3r1B3WPHjiEnJ6fB1yQqlQrV1dUoLS2FsbGxUF5SUoIhQ4YAAP7xj3/g/v37AH49DiqVCqdOnRK1VVpaipqamgZJQ2Mae0NWqVQNvgLSlozUR0RYsGABIiMjERcX1+A4dO/eHSqVCjExMejXrx8AoLq6GvHx8Vi3bp1Q786dO/Dw8IBcLseBAwca/I9cXFxQXl6O06dPY+DAgQCAU6dOoby8XDhm1tbWDfoXFhaGxYsXw9vbW1Tu5+eHnTt3Yv369cJrt6ioSPh/PHqMAMDe3h6nT58WlZ05c0b4W1dXF7a2tk0eq5aqqqpCdnY2XF1dn0h7rG3ha3RYm9a/f3/k5ubCzMwMtra2okfd2ZaWkkgkeO2117By5UqkpaVBJpMhMjIS5ubmsLS0xOXLlxvso+5NpE+fPkhPTxeup6mvZ8+eDa4ZSUxMRM+ePVvcPwcHB5w8eVJUVn8ZALp27QofHx9ERERg8eLFCA0NbbRNXV1djBgxAp999hnOnj2L/Px8/PTTTy3u06OaOwb9+/dHTk5Og2Noa2srOov3WxkYGMDCwgKlpaU4cuQIJkyY0KBOWFgYnJ2d4eTkJCp3dnaGVCpFTEyMUFZUVITMzEzhTdvS0lLob90buIuLCzIzM1FUVCRsFx0dDblcDmdn5xb1u+4Nue5Rl+i4uLiI+lPXdl1/GjN//nz861//wjfffANDQ0MUFxejuLhYSNIkEgn8/f2xZs0aREZGIjMzE97e3tDX18eMGTMAPDyTUzclPSwsDHfu3BHaefDgAYCHz2lPT0/MmTMHJ0+exMmTJzFnzhyMHTsWdnZ2WvuWnp6O1NRUzJ49G7179xY9pk+fjq+++go1NTWwtbVF165dERgYiAsXLuDgwYPYsGGDqK0FCxbg0KFDCA4ORm5uLrZv347Dhw83e8aruroa6enpSE9PR3V1NQoKCpCeno6LFy8KdZYsWYL4+Hjk5eXh1KlTeOutt3Dnzh3MmjWrybZZO9Va35mxjuNxZ109qv51IkTi79V/+eUXeuWVV8jd3Z0SEhLo8uXLFBcXR35+fqLrEh6l7fv/kydP0urVqyk5OZmuXLkiTKU9dOgQET2ccaJQKGjjxo2Uk5NDZ8+epZ07dwrf2VdVVVGPHj3I1dWVjh8/TpcuXaLvv/+eEhMTiYgoMjKSpFIpbd26lS5cuEAbNmwgHR0dio2NFfoALddYKJVK2rVrFxE9vOZAJpPRokWL6Pz587Rnzx5SqVSiWBYuXEhRUVF0+fJlSklJoYEDB9KUKVO0Hof//ve/tGnTJkpLS6P8/HwKCQmhTp06UWZmptZjr+16BicnJwoICGjRMYiKiiJdXV0KCAigzMxMysrKor179zY5O6qqqorS0tIoLS2NLCwsaMmSJZSWlka5ublCnaioKDp8+DBdvnyZoqOjycnJiQYOHCi6noTo4bUm+vr6wjVF9fn4+JCVlRUdPXqUUlNT6fXXX2/x9PI33niDUlNT6ejRo2RlZSWaXk5EdO7cOUpLS6Nx48aRu7u7EFNTTpw4QTo6OhQUFETZ2dkUFBTUYHr53bt3hbYAUHBwMAHQ+qh7HhE9vL4qICCAVCoVyeVyGjZsmDAri+jX14i2x6MzGm/fvk0zZ84kQ0NDMjQ0pJkzZzb5Uwe+vr7k4OCgdV1JSQnp6OhQeHg4ET2cVeXo6Eh6enrk6upK3333ndbp5ZaWlsL08r/97W+kUqmaPK55eXla43JzcxPqTJ06lSwsLEgqlZJaraZJkybRuXPnmmyXtV+c6LDf7WkmOkQPfyPlnXfeIVNTU5LL5WRjY0Nz5szROr2XSHuik5WVRR4eHvTiiy+SXC6nHj160ObNm0Xb7dmzh/r27UsymYyMjY1p2LBhFBERIazPz8+nyZMnk5GREenr69OAAQPo1KlTwvqWTC9vKtEhepic1E0Hd3V1pZ07d4pi8fX1pZdffpnkcjm9+OKL5OXlRbdu3dJ6HI4dO0Zubm5kbGxMCoWC+vTpQ/v27RPWP26i05JjEBUVRUOGDCGFQkFGRkY0cOBA2rFjh9b+EbXsTWnfvn1kY2NDMpmMVCoVzZ8/X+vvNG3fvp0UCkWjv+F0//598vX1JRMTE1IoFDR27Fi6evVqo32rc+XKFfrDH/5ACoWCTExMyNfXlyorK0V1rK2ttcbRnO+++47s7OxIKpWSvb29kATUaSwhmTVrVrNtd0SzZ8+moUOHtnY3WDsjIWrBhQGMtSNxcXEYPnw4SktLG70WhTHW9q1fvx4jR46EgYEBDh8+jMWLFyMkJASzZ89u7a6xdoSv0WEdlpWVFaZPn97a3WCM/UanT5/GyJEj4ejoiG3btuGLL77gJIc9Nj6jwzqc+/fvo6CgAADQuXNnvlkfY4w9xzjRYYwxxliHxV9dMcYYY6zD4kSHMcYYYx0WJzqMsWcmPz8fEokEEokEffv2be3uMMaeA5zoMNaKQkJC0L17d+jp6cHZ2Vm41xLw8Kf+AwMDoVaroVAo4O7uLtx/qSkZGRlwc3ODQqGApaUlVq1a1eD2EvHx8XB2doaenh5sbGywbdu2ZtutqqrCggULYGpqCgMDA4wfPx7Xr18X1SktLYWXlxeUSiWUSiW8vLxQVlYmrO/atSuKioqwePHiZvfHGGNPAic6jLWSffv2wd/fHytWrEBaWhpcXV0xevRoXL16FQDw2WefITg4GF9++SWSk5OhUqkwcuRI3L17t9E279y5g5EjR0KtViM5ORmbN2/G+vXrERwcLNTJy8vDmDFj4OrqirS0NCxfvhx+fn4IDw9vsr/+/v6IjIzE3r17cfz4cVRUVGDs2LHCLQMAYMaMGUhPT0dUVBSioqKQnp4OLy8vYb2Ojg5UKhU6d+78Ww8bY4w9ntb7rULGnm8DBw4kHx8fUZm9vT0tW7aMNBoNqVQqCgoKEtZVVlaSUqmkbdu2NdpmSEgIKZVK0S/3rl27ltRqNWk0GiIiWrp0Kdnb24u2mzt3Lg0ePLjRdsvKykgqldLevXuFsoKCAurUqRNFRUUR0cNfnwYguoVBUlISAaDz58+L2qv/q9mMMfa08BkdxlpBdXU1UlJSMGrUKFH5qFGjkJiYiLy8PBQXF4vWy+VyuLm5ITExUSjz9vaGu7u7sJyUlAQ3NzfI5XKhzMPDA4WFhcjPzxfq1N+vh4cHzpw5g5qaGgAPf11aIpEI26SkpKCmpka0nVqtRu/evYX+JCUlQalUiu4AP3jwYCiVSlGfGWPsWeJEh7FWcOvWLTx48ADm5uaicnNzc+Eu0nXL2tbXsbCwwEsvvSQsFxcXa92mbl1TdWpra3Hr1i0AgL6+Puzs7CCVSoVtZDIZjI2NG+1PcXExzMzMGsRqZmYm6jNjjD1Luq3dAcaeZxKJRLRMRKKy5tavXbu2RW3WL2+uzsCBA3H+/Plm+99cf7XVYYyxZ4nP6DDWCkxNTaGjo9PgTEdJSQnMzc2F21Y0tr4xKpVK6zbAr2d2Gqujq6uLF154odF2q6urUVpa2mh/VCoVbty40WDbmzdvNtlnxhh7mjjRYawVyGQyODs7IyYmRlQeExODIUOGoHv37lCpVKL11dXViI+Px5AhQxpt18XFBQkJCaiurhbKoqOjoVar0a1bN6FO/f1GR0djwIABwldV9Tk7O0MqlYq2KyoqQmZmptAfFxcXlJeX4/Tp00KdU6dOoby8vMk+M8bYU9WaV0Iz9jzbu3cvSaVSCgsLo6ysLPL39ycDAwPKz88nIqKgoCBSKpUUERFBGRkZNH36dLKwsKA7d+4IbSxbtoy8vLyE5bKyMjI3N6fp06dTRkYGRUREkJGREa1fv16oc/nyZdLX16dFixZRVlYWhYWFkVQqpe+//16oc+rUKbKzs6Pr168LZT4+PmRlZUVHjx6l1NRUev3118nJyYlqa2uFOp6entSnTx9KSkqipKQkcnR0pLFjxzaInWddMcaeFU50GGtFW7ZsIWtra5LJZNS/f3+Kj48X1mk0GgoICCCVSkVyuZyGDRtGGRkZou1nzZpFbm5uorKzZ8+Sq6sryeVyUqlUFBgYKEwtrxMXF0f9+vUjmUxG3bp1o61bt4rWx8bGEgDKy8sTyu7fv0++vr5kYmJCCoWCxo4dS1evXhVtd/v2bZo5cyYZGhqSoaEhzZw5k0pLSxvEzYkOY+xZ4buXM8aeucDAQOzfvx/p6emt3RXGWAfHs64YY8/M1atX4eDggOrqajg4OLR2dxhjzwE+o8MYe2Zqa2uFHyGUy+Xo2rVr63aIMdbhcaLDGGOMsQ6Lp5czxhhjrMPiRIcxxhhjHRYnOowxxhjrsDjRYYwxxliHxYkOY4wxxjosTnQYY4wx1mFxosMYY4yxDosTHcYYY4x1WP8HzUNNu8TZILcAAAAASUVORK5CYII=",
             "text/plain": [
               "<Figure size 640x480 with 2 Axes>"
             ]
@@ -1468,22 +1469,22 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 42,
+      "execution_count": 10,
       "metadata": {},
       "outputs": [
         {
           "data": {
             "text/plain": [
-              "<matplotlib.collections.QuadMesh at 0x112d975e410>"
+              "<matplotlib.collections.QuadMesh at 0x25a7fe4a9d0>"
             ]
           },
-          "execution_count": 42,
+          "execution_count": 10,
           "metadata": {},
           "output_type": "execute_result"
         },
         {
           "data": {
-            "image/png": 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",
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",
             "text/plain": [
               "<Figure size 640x480 with 2 Axes>"
             ]
@@ -1509,7 +1510,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 43,
+      "execution_count": 11,
       "metadata": {},
       "outputs": [],
       "source": [
@@ -1518,22 +1519,22 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 44,
+      "execution_count": 12,
       "metadata": {},
       "outputs": [
         {
           "data": {
             "text/plain": [
-              "<matplotlib.collections.QuadMesh at 0x112d83afe10>"
+              "<matplotlib.collections.QuadMesh at 0x25a2abaa990>"
             ]
           },
-          "execution_count": 44,
+          "execution_count": 12,
           "metadata": {},
           "output_type": "execute_result"
         },
         {
           "data": {
-            "image/png": 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",
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",
             "text/plain": [
               "<Figure size 640x480 with 2 Axes>"
             ]
@@ -1564,7 +1565,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 45,
+      "execution_count": 13,
       "metadata": {},
       "outputs": [
         {
@@ -1590,7 +1591,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 46,
+      "execution_count": 14,
       "metadata": {},
       "outputs": [],
       "source": [
@@ -1614,7 +1615,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 47,
+      "execution_count": 15,
       "metadata": {
         "scrolled": true
       },
@@ -1626,7 +1627,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 48,
+      "execution_count": 16,
       "metadata": {},
       "outputs": [
         {
@@ -2003,13 +2004,13 @@
               "  fill: currentColor;\n",
               "}\n",
               "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 379kB\n",
-              "Dimensions:         (time: 183, range: 28, dirIMU: 3, dir: 4, beam: 4,\n",
+              "Dimensions:         (time: 183, dirIMU: 3, dir: 4, range: 28, beam: 4,\n",
               "                     earth: 3, inst: 3, q: 4, time_b5: 183, range_b5: 28)\n",
               "Coordinates:\n",
               "  * time            (time) datetime64[ns] 1kB 2020-08-15T00:22:30.001030683 ....\n",
               "  * dirIMU          (dirIMU) &lt;U10 120B &#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert&#x27;\n",
-              "  * range           (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
               "  * dir             (dir) &lt;U10 160B &#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert1&#x27; &#x27;vert2&#x27;\n",
+              "  * range           (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
               "  * beam            (beam) int32 16B 1 2 3 4\n",
               "  * earth           (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
               "  * inst            (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
@@ -2018,18 +2019,18 @@
               "  * range_b5        (range_b5) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
               "Data variables: (12/38)\n",
               "    c_sound         (time) float32 732B 1.502e+03 1.502e+03 ... 1.498e+03\n",
-              "    U_std           (range, time) float32 20kB 0.04232 0.04293 ... nan nan\n",
               "    temp            (time) float32 732B 14.49 14.59 14.54 ... 13.62 13.56 13.5\n",
               "    pressure        (time) float32 732B 9.712 9.699 9.685 ... 9.58 9.584 9.591\n",
               "    mag             (dirIMU, time) float32 2kB 3.534 3.565 ... -197.1 -197.1\n",
               "    accel           (dirIMU, time) float32 2kB -1.261 -1.263 ... 9.714 9.712\n",
+              "    batt            (time) float32 732B 16.48 16.48 16.48 ... 16.25 16.26 16.26\n",
               "    ...              ...\n",
-              "    boost_running   (time) float32 732B 0.1267 0.1333 0.13 ... 0.2267 0.22 0.22\n",
               "    heading         (time) float32 732B 3.287 3.261 3.337 ... 3.331 3.352 3.352\n",
               "    pitch           (time) float32 732B -0.05523 -0.07217 ... -0.04288 -0.0429\n",
               "    roll            (time) float32 732B -7.414 -7.424 -7.404 ... -6.433 -6.436\n",
               "    water_density   (time) float32 732B 1.023e+03 1.023e+03 ... 1.023e+03\n",
               "    depth           (time) float32 732B 10.28 10.26 10.25 ... 10.14 10.15 10.15\n",
+              "    U_std           (range, time) float32 20kB 0.04232 0.04293 ... nan nan\n",
               "Attributes: (12/41)\n",
               "    fs:                        1\n",
               "    n_bin:                     300\n",
@@ -2043,7 +2044,7 @@
               "    range_offset:              0.6\n",
               "    declination:               15.8\n",
               "    declination_in_orientmat:  1\n",
-              "    principal_heading:         11.1898</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a24dc7b0-bc1d-4c64-b526-53e9bb42a57d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a24dc7b0-bc1d-4c64-b526-53e9bb42a57d' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 183</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>time_b5</span>: 183</li><li><span class='xr-has-index'>range_b5</span>: 28</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-409759b6-3e17-452e-b728-d80cbe8faf36' class='xr-section-summary-in' type='checkbox'  checked><label for='section-409759b6-3e17-452e-b728-d80cbe8faf36' class='xr-section-summary' >Coordinates: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:30.001030683 .....</div><input id='attrs-4ceed203-e8ac-40ac-ae60-0d3c55fbd71e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4ceed203-e8ac-40ac-ae60-0d3c55fbd71e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-812c8dc0-8d51-469a-b1cd-918c067293ad' class='xr-var-data-in' type='checkbox'><label for='data-812c8dc0-8d51-469a-b1cd-918c067293ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:22:30.001030683&#x27;, &#x27;2020-08-15T00:27:30.001019239&#x27;,\n",
+              "    principal_heading:         11.1898</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-40afcbec-82fa-4ea2-8864-207bc81a7a2f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-40afcbec-82fa-4ea2-8864-207bc81a7a2f' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 183</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>time_b5</span>: 183</li><li><span class='xr-has-index'>range_b5</span>: 28</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6a2d51fd-0c35-44ba-9e74-4c2f260aa17a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6a2d51fd-0c35-44ba-9e74-4c2f260aa17a' class='xr-section-summary' >Coordinates: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:30.001030683 .....</div><input id='attrs-8c6cc862-7bbd-406d-95d2-977701a314a4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8c6cc862-7bbd-406d-95d2-977701a314a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3388b96d-e832-465d-ba2d-8a2ee5e60b51' class='xr-var-data-in' type='checkbox'><label for='data-3388b96d-e832-465d-ba2d-8a2ee5e60b51' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:22:30.001030683&#x27;, &#x27;2020-08-15T00:27:30.001019239&#x27;,\n",
               "       &#x27;2020-08-15T00:32:30.001010656&#x27;, &#x27;2020-08-15T00:37:30.001015901&#x27;,\n",
               "       &#x27;2020-08-15T00:42:30.001019954&#x27;, &#x27;2020-08-15T00:47:30.001018524&#x27;,\n",
               "       &#x27;2020-08-15T00:52:30.001013994&#x27;, &#x27;2020-08-15T00:57:30.001026630&#x27;,\n",
@@ -2134,9 +2135,9 @@
               "       &#x27;2020-08-15T15:02:30.001021146&#x27;, &#x27;2020-08-15T15:07:30.001027345&#x27;,\n",
               "       &#x27;2020-08-15T15:12:30.001029014&#x27;, &#x27;2020-08-15T15:17:30.001026630&#x27;,\n",
               "       &#x27;2020-08-15T15:22:30.001026153&#x27;, &#x27;2020-08-15T15:27:30.001022577&#x27;,\n",
-              "       &#x27;2020-08-15T15:32:30.001030683&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert&#x27;</div><input id='attrs-df549f4c-2cd8-4198-b092-ace098b447c8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-df549f4c-2cd8-4198-b092-ace098b447c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b100f99a-5eaa-45d5-ac2b-0b1df66acc49' class='xr-var-data-in' type='checkbox'><label for='data-b100f99a-5eaa-45d5-ac2b-0b1df66acc49' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-2a3dd00e-9b6b-425e-8de8-f7ab20eec33b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a3dd00e-9b6b-425e-8de8-f7ab20eec33b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eca80e66-5d00-4f66-970f-146ea6673f68' class='xr-var-data-in' type='checkbox'><label for='data-eca80e66-5d00-4f66-970f-146ea6673f68' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+              "       &#x27;2020-08-15T15:32:30.001030683&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert&#x27;</div><input id='attrs-d4114ee4-4fd2-4656-a755-e1677ad95cbf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d4114ee4-4fd2-4656-a755-e1677ad95cbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07f9c86c-b27f-44bc-a342-95d51837989d' class='xr-var-data-in' type='checkbox'><label for='data-07f9c86c-b27f-44bc-a342-95d51837989d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;streamwise&#x27; &#x27;x-stream&#x27; ... &#x27;vert2&#x27;</div><input id='attrs-3ff426e7-7498-47ac-b74d-288024071044' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3ff426e7-7498-47ac-b74d-288024071044' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea33e978-7438-4f80-9375-612b056787b0' class='xr-var-data-in' type='checkbox'><label for='data-ea33e978-7438-4f80-9375-612b056787b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert1&#x27;, &#x27;vert2&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-358893ed-0b0c-41bf-8c7c-493855cc2ee4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-358893ed-0b0c-41bf-8c7c-493855cc2ee4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da36c9fa-4417-4a9b-8660-d95c849a25e7' class='xr-var-data-in' type='checkbox'><label for='data-da36c9fa-4417-4a9b-8660-d95c849a25e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
               "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-              "       13.2, 13.7, 14.2, 14.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;streamwise&#x27; &#x27;x-stream&#x27; ... &#x27;vert2&#x27;</div><input id='attrs-d6c84da7-01ea-43e4-bb44-365b7cf933d6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d6c84da7-01ea-43e4-bb44-365b7cf933d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05879cee-ce15-4012-8f63-564c7678ae25' class='xr-var-data-in' type='checkbox'><label for='data-05879cee-ce15-4012-8f63-564c7678ae25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert1&#x27;, &#x27;vert2&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-dbe17493-21e6-4f1e-b70a-07915b34d71e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dbe17493-21e6-4f1e-b70a-07915b34d71e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-709f73c5-2649-4256-a034-a1e0689265c5' class='xr-var-data-in' type='checkbox'><label for='data-709f73c5-2649-4256-a034-a1e0689265c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-f292a0ea-d970-4f2a-8ea4-dce6816c8450' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f292a0ea-d970-4f2a-8ea4-dce6816c8450' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ab082ca-188f-4065-944c-81669cade959' class='xr-var-data-in' type='checkbox'><label for='data-6ab082ca-188f-4065-944c-81669cade959' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-2d57035c-a6e8-4b45-a4ee-ed2d85f3a7f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2d57035c-a6e8-4b45-a4ee-ed2d85f3a7f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89a72885-cd5d-4826-9261-e9f848d45b8d' class='xr-var-data-in' type='checkbox'><label for='data-89a72885-cd5d-4826-9261-e9f848d45b8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-d8cca98d-6cb0-4889-aaa7-3a1baa97e10f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d8cca98d-6cb0-4889-aaa7-3a1baa97e10f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1fa56711-ac84-4ef3-9aeb-edd05d2af165' class='xr-var-data-in' type='checkbox'><label for='data-1fa56711-ac84-4ef3-9aeb-edd05d2af165' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:29.938495159 .....</div><input id='attrs-8a1153d5-ea1b-449d-83dd-3908186caaa7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8a1153d5-ea1b-449d-83dd-3908186caaa7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dfcb84d2-b340-473a-bd32-d56006d5eca3' class='xr-var-data-in' type='checkbox'><label for='data-dfcb84d2-b340-473a-bd32-d56006d5eca3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:22:29.938495159&#x27;, &#x27;2020-08-15T00:27:29.938490867&#x27;,\n",
+              "       13.2, 13.7, 14.2, 14.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-3e6e203d-6844-430c-817a-055331cd2e13' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e6e203d-6844-430c-817a-055331cd2e13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-834b2c68-401c-4879-bae7-bfd0f58002ba' class='xr-var-data-in' type='checkbox'><label for='data-834b2c68-401c-4879-bae7-bfd0f58002ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-24652350-689b-4f90-91ca-12b788f20e20' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24652350-689b-4f90-91ca-12b788f20e20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5585fda-1e78-4e83-a0e6-3c5a5eda53be' class='xr-var-data-in' type='checkbox'><label for='data-c5585fda-1e78-4e83-a0e6-3c5a5eda53be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-f0203aca-7838-436a-88d3-fe64978fe082' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f0203aca-7838-436a-88d3-fe64978fe082' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d33f4c6b-3f93-4b82-97ce-4cd4e91aebd8' class='xr-var-data-in' type='checkbox'><label for='data-d33f4c6b-3f93-4b82-97ce-4cd4e91aebd8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-9a254a54-000c-4a40-8c99-d7d9d1ebf2a8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9a254a54-000c-4a40-8c99-d7d9d1ebf2a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed47564f-b71a-4934-b7ae-18f156b1af82' class='xr-var-data-in' type='checkbox'><label for='data-ed47564f-b71a-4934-b7ae-18f156b1af82' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:29.938495159 .....</div><input id='attrs-0f8d92ee-d75c-4067-96be-8ccf57a9b599' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0f8d92ee-d75c-4067-96be-8ccf57a9b599' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8ee951d-8ed4-4b8a-8d8d-cdc25ea61095' class='xr-var-data-in' type='checkbox'><label for='data-d8ee951d-8ed4-4b8a-8d8d-cdc25ea61095' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:22:29.938495159&#x27;, &#x27;2020-08-15T00:27:29.938490867&#x27;,\n",
               "       &#x27;2020-08-15T00:32:29.938487529&#x27;, &#x27;2020-08-15T00:37:29.938496828&#x27;,\n",
               "       &#x27;2020-08-15T00:42:29.938495397&#x27;, &#x27;2020-08-15T00:47:29.938496589&#x27;,\n",
               "       &#x27;2020-08-15T00:52:29.938497781&#x27;, &#x27;2020-08-15T00:57:29.938495397&#x27;,\n",
@@ -2227,9 +2228,9 @@
               "       &#x27;2020-08-15T15:02:29.938493013&#x27;, &#x27;2020-08-15T15:07:29.938493967&#x27;,\n",
               "       &#x27;2020-08-15T15:12:29.938494920&#x27;, &#x27;2020-08-15T15:17:29.938493251&#x27;,\n",
               "       &#x27;2020-08-15T15:22:29.938486099&#x27;, &#x27;2020-08-15T15:27:29.938484191&#x27;,\n",
-              "       &#x27;2020-08-15T15:32:29.938490390&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-d4e41c20-ea47-4e65-9079-0602edb1e99d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d4e41c20-ea47-4e65-9079-0602edb1e99d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31247f07-f109-4151-a19a-3aff3b713fa2' class='xr-var-data-in' type='checkbox'><label for='data-31247f07-f109-4151-a19a-3aff3b713fa2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+              "       &#x27;2020-08-15T15:32:29.938490390&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-d5375742-8ba6-436b-b6d3-12a79f5c02df' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d5375742-8ba6-436b-b6d3-12a79f5c02df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5dcd2ea-cf12-4db4-bf1d-7f1fc9630097' class='xr-var-data-in' type='checkbox'><label for='data-d5dcd2ea-cf12-4db4-bf1d-7f1fc9630097' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
               "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-              "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0e80683a-8f7f-4804-93ff-ac0907983776' class='xr-section-summary-in' type='checkbox'  ><label for='section-0e80683a-8f7f-4804-93ff-ac0907983776' class='xr-section-summary' >Data variables: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-4246abc6-57bf-4b4f-9d91-f92c077b36fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4246abc6-57bf-4b4f-9d91-f92c077b36fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9145f922-7811-4f7a-b406-a1eb5a60daf4' class='xr-var-data-in' type='checkbox'><label for='data-9145f922-7811-4f7a-b406-a1eb5a60daf4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.6843, 1502.032 , 1501.8505, 1501.5714, 1501.8607, 1502.4133,\n",
+              "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a932f57a-5d21-4646-bc9d-3c6f245535a4' class='xr-section-summary-in' type='checkbox'  ><label for='section-a932f57a-5d21-4646-bc9d-3c6f245535a4' class='xr-section-summary' >Data variables: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-0e9bf684-5b1f-4b1f-b9bd-c62e5914a05e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e9bf684-5b1f-4b1f-b9bd-c62e5914a05e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a887c99f-97d9-4fcf-a09d-d5a3c45c3342' class='xr-var-data-in' type='checkbox'><label for='data-a887c99f-97d9-4fcf-a09d-d5a3c45c3342' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.6843, 1502.032 , 1501.8505, 1501.5714, 1501.8607, 1502.4133,\n",
               "       1502.8121, 1502.7344, 1502.8704, 1502.9467, 1502.883 , 1502.7606,\n",
               "       1502.6915, 1502.8214, 1502.8864, 1502.7937, 1502.6268, 1502.6473,\n",
               "       1502.4198, 1502.3577, 1501.9543, 1501.729 , 1501.32  , 1500.9684,\n",
@@ -2259,19 +2260,7 @@
               "       1499.5286, 1499.5846, 1499.6293, 1499.6262, 1499.6666, 1499.6971,\n",
               "       1499.6998, 1499.7269, 1499.7843, 1499.6895, 1499.7037, 1499.6376,\n",
               "       1499.4894, 1499.0636, 1499.0073, 1498.8967, 1498.8627, 1498.961 ,\n",
-              "       1498.8287, 1498.6285, 1498.472 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U_std</span></div><div class='xr-var-dims'>(range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.04232 0.04293 0.04402 ... nan nan</div><input id='attrs-ed8cb1b7-2535-4f89-9fd1-7486c4e0d36e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ed8cb1b7-2535-4f89-9fd1-7486c4e0d36e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3bdbac96-d7ec-4ab6-9c9c-db1032f098a0' class='xr-var-data-in' type='checkbox'><label for='data-3bdbac96-d7ec-4ab6-9c9c-db1032f098a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([[0.04231985, 0.04293143, 0.04401674, ..., 0.04380286, 0.04201568,\n",
-              "        0.04634431],\n",
-              "       [0.04002878, 0.04084466, 0.03949426, ..., 0.04000184, 0.04028782,\n",
-              "        0.03873245],\n",
-              "       [0.04025545, 0.03514179, 0.04270846, ..., 0.0391249 , 0.03997382,\n",
-              "        0.04237254],\n",
-              "       ...,\n",
-              "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
-              "               nan],\n",
-              "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
-              "               nan],\n",
-              "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
-              "               nan]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.49 14.59 14.54 ... 13.56 13.5</div><input id='attrs-08415c2b-8d95-425b-8279-724b2a346b95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-08415c2b-8d95-425b-8279-724b2a346b95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c91a5655-acb7-4fb1-ae61-b2260d83c1b7' class='xr-var-data-in' type='checkbox'><label for='data-c91a5655-acb7-4fb1-ae61-b2260d83c1b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.4871   , 14.592732 , 14.5369   , 14.450967 , 14.540566 ,\n",
+              "       1498.8287, 1498.6285, 1498.472 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.49 14.59 14.54 ... 13.56 13.5</div><input id='attrs-e389d35a-f683-44a6-99bd-93380cd821b6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e389d35a-f683-44a6-99bd-93380cd821b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a25e171-6518-412c-9a9c-35b718000676' class='xr-var-data-in' type='checkbox'><label for='data-9a25e171-6518-412c-9a9c-35b718000676' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.4871   , 14.592732 , 14.5369   , 14.450967 , 14.540566 ,\n",
               "       14.712167 , 14.838034 , 14.812099 , 14.855833 , 14.879432 ,\n",
               "       14.860366 , 14.821934 , 14.799266 , 14.840433 , 14.8621   ,\n",
               "       14.833766 , 14.782434 , 14.788966 , 14.716966 , 14.695799 ,\n",
@@ -2307,7 +2296,7 @@
               "       13.860667 , 13.870465 , 13.876833 , 13.878232 , 13.884268 ,\n",
               "       13.907367 , 13.875599 , 13.875534 , 13.861733 , 13.8139   ,\n",
               "       13.689401 , 13.665034 , 13.632333 , 13.6227665, 13.651935 ,\n",
-              "       13.6164665, 13.5551   , 13.503766 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.712 9.699 9.685 ... 9.584 9.591</div><input id='attrs-309660b2-41be-4ffa-a839-573acf7f3d62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-309660b2-41be-4ffa-a839-573acf7f3d62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16c8db5f-08fc-40c3-abe9-04fda660a3fb' class='xr-var-data-in' type='checkbox'><label for='data-16c8db5f-08fc-40c3-abe9-04fda660a3fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.712007 , 9.699074 , 9.685317 , 9.670219 , 9.65324  , 9.640334 ,\n",
+              "       13.6164665, 13.5551   , 13.503766 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.712 9.699 9.685 ... 9.584 9.591</div><input id='attrs-2a458a4b-e91c-4f24-9662-4a6f05dc33e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a458a4b-e91c-4f24-9662-4a6f05dc33e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-455ce3f4-c117-4153-b79f-fd02f0721f52' class='xr-var-data-in' type='checkbox'><label for='data-455ce3f4-c117-4153-b79f-fd02f0721f52' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.712007 , 9.699074 , 9.685317 , 9.670219 , 9.65324  , 9.640334 ,\n",
               "       9.62429  , 9.608537 , 9.594397 , 9.576526 , 9.56048  , 9.541069 ,\n",
               "       9.524289 , 9.505187 , 9.486143 , 9.464264 , 9.44223  , 9.416344 ,\n",
               "       9.393453 , 9.367396 , 9.339387 , 9.305754 , 9.278394 , 9.245257 ,\n",
@@ -2337,7 +2326,7 @@
               "       9.35049  , 9.37106  , 9.393917 , 9.40948  , 9.428807 , 9.441616 ,\n",
               "       9.459889 , 9.474596 , 9.488944 , 9.495657 , 9.510249 , 9.520061 ,\n",
               "       9.530423 , 9.537613 , 9.546494 , 9.554764 , 9.561024 , 9.57158  ,\n",
-              "       9.579874 , 9.583782 , 9.591404 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.534 3.565 3.547 ... -197.1 -197.1</div><input id='attrs-e2c0d628-a4b0-4cb7-988b-1de10e3bc149' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2c0d628-a4b0-4cb7-988b-1de10e3bc149' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e6c5d00-5de3-427f-b948-0c75d3da0ad2' class='xr-var-data-in' type='checkbox'><label for='data-6e6c5d00-5de3-427f-b948-0c75d3da0ad2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[ 3.53383756e+00,  3.56493616e+00,  3.54652500e+00,\n",
+              "       9.579874 , 9.583782 , 9.591404 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.534 3.565 3.547 ... -197.1 -197.1</div><input id='attrs-6675907a-764b-4c6d-9b2b-1bfce60030a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6675907a-764b-4c6d-9b2b-1bfce60030a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f35fda8-28ce-4760-a49c-abf3e3fe2445' class='xr-var-data-in' type='checkbox'><label for='data-7f35fda8-28ce-4760-a49c-abf3e3fe2445' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[ 3.53383756e+00,  3.56493616e+00,  3.54652500e+00,\n",
               "         3.60746217e+00,  3.56795740e+00,  3.58543777e+00,\n",
               "         3.56357908e+00,  3.57667398e+00,  3.60632110e+00,\n",
               "         3.56949067e+00,  3.57479167e+00,  3.59876704e+00,\n",
@@ -2377,7 +2366,7 @@
               "        -1.97044174e+02, -1.97063873e+02, -1.97090515e+02,\n",
               "        -1.97129501e+02, -1.97007523e+02, -1.97017838e+02,\n",
               "        -1.97019165e+02, -1.97129166e+02, -1.97051849e+02,\n",
-              "        -1.97113190e+02, -1.97104507e+02, -1.97053848e+02]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.261 -1.263 -1.26 ... 9.714 9.712</div><input id='attrs-bfa2fa40-388a-458f-8a67-8948ade22edd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfa2fa40-388a-458f-8a67-8948ade22edd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4515de1f-2a05-4616-868e-5c8ad284f0dc' class='xr-var-data-in' type='checkbox'><label for='data-4515de1f-2a05-4616-868e-5c8ad284f0dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.2608225 , -1.2632061 , -1.2602278 , -1.2620431 , -1.2610018 ,\n",
+              "        -1.97113190e+02, -1.97104507e+02, -1.97053848e+02]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.261 -1.263 -1.26 ... 9.714 9.712</div><input id='attrs-5660f62f-4bc7-4437-9336-fc2125a12873' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5660f62f-4bc7-4437-9336-fc2125a12873' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae198a49-8e0c-43e2-84cf-05b46db4c47b' class='xr-var-data-in' type='checkbox'><label for='data-ae198a49-8e0c-43e2-84cf-05b46db4c47b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.2608225 , -1.2632061 , -1.2602278 , -1.2620431 , -1.2610018 ,\n",
               "        -1.2613868 , -1.2610568 , -1.2621608 , -1.2631991 , -1.2639122 ,\n",
               "        -1.2618904 , -1.258823  , -1.2596216 , -1.258702  , -1.2583325 ,\n",
               "        -1.2578007 , -1.2583394 , -1.2576339 , -1.2579147 , -1.2534361 ,\n",
@@ -2417,7 +2406,7 @@
               "         9.714537  ,  9.714841  ,  9.714376  ,  9.71848   ,  9.7165    ,\n",
               "         9.715717  ,  9.711741  ,  9.710465  ,  9.712621  ,  9.71337   ,\n",
               "         9.715622  ,  9.715989  ,  9.711598  ,  9.71219   ,  9.71021   ,\n",
-              "         9.712366  ,  9.7141695 ,  9.711616  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.48 16.48 16.48 ... 16.26 16.26</div><input id='attrs-9c7282f7-38ba-4b1a-89ef-39c0abd8ca9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c7282f7-38ba-4b1a-89ef-39c0abd8ca9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17cc7d9d-2b53-4d12-a30e-3fd4bb52e6fd' class='xr-var-data-in' type='checkbox'><label for='data-17cc7d9d-2b53-4d12-a30e-3fd4bb52e6fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.481167, 16.478   , 16.478   , 16.477167, 16.481   , 16.484167,\n",
+              "         9.712366  ,  9.7141695 ,  9.711616  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.48 16.48 16.48 ... 16.26 16.26</div><input id='attrs-cc0755d1-eac2-491e-928f-87d0c37109ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc0755d1-eac2-491e-928f-87d0c37109ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-567a13b3-7eb6-4554-92ac-a39a2c00f691' class='xr-var-data-in' type='checkbox'><label for='data-567a13b3-7eb6-4554-92ac-a39a2c00f691' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.481167, 16.478   , 16.478   , 16.477167, 16.481   , 16.484167,\n",
               "       16.477167, 16.479834, 16.479166, 16.482666, 16.478167, 16.481668,\n",
               "       16.479668, 16.475334, 16.479668, 16.479   , 16.474   , 16.475334,\n",
               "       16.477667, 16.473167, 16.472168, 16.468334, 16.472334, 16.471169,\n",
@@ -2447,7 +2436,7 @@
               "       16.258333, 16.262335, 16.262169, 16.2575  , 16.261   , 16.260332,\n",
               "       16.25633 , 16.257998, 16.258333, 16.253334, 16.257998, 16.257332,\n",
               "       16.253166, 16.256998, 16.256998, 16.252666, 16.256998, 16.256998,\n",
-              "       16.252666, 16.256998, 16.256998], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-c9e1c8f9-b359-4e6e-9e24-a8872069a962' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c9e1c8f9-b359-4e6e-9e24-a8872069a962' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcb3ef16-1bf9-4232-a6fa-1afbf26a9a76' class='xr-var-data-in' type='checkbox'><label for='data-fcb3ef16-1bf9-4232-a6fa-1afbf26a9a76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20.      , 20.      , 20.      , 20.043333, 20.25    , 20.25    ,\n",
+              "       16.252666, 16.256998, 16.256998], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-0ea2a008-c7ed-404d-82e3-22b0a9cf1efd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ea2a008-c7ed-404d-82e3-22b0a9cf1efd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7bbdbfa5-d964-49a4-9ac2-26a5234ec875' class='xr-var-data-in' type='checkbox'><label for='data-7bbdbfa5-d964-49a4-9ac2-26a5234ec875' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20.      , 20.      , 20.      , 20.043333, 20.25    , 20.25    ,\n",
               "       20.25    , 20.25    , 20.263334, 20.446667, 20.5     , 20.5     ,\n",
               "       20.5     , 20.5     , 20.5     , 20.5     , 20.5     , 20.5     ,\n",
               "       20.5     , 20.5     , 20.5     , 20.5     , 20.5     , 20.31    ,\n",
@@ -2477,7 +2466,7 @@
               "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.53    ,\n",
               "       19.696667, 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
               "       19.75    , 19.75    , 19.71    , 19.5     , 19.5     , 19.5     ,\n",
-              "       19.5     , 19.5     , 19.5     ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-ab03e4c4-2c85-4a8d-a516-121216653cbd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ab03e4c4-2c85-4a8d-a516-121216653cbd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-546fe20c-d8bd-4566-bc66-9b1b01b181eb' class='xr-var-data-in' type='checkbox'><label for='data-546fe20c-d8bd-4566-bc66-9b1b01b181eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       19.5     , 19.5     , 19.5     ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-404cc268-b828-4be2-9f0e-f5ea092a8e62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-404cc268-b828-4be2-9f0e-f5ea092a8e62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae2d2613-dfc7-49eb-90ec-4cc77daf5d9c' class='xr-var-data-in' type='checkbox'><label for='data-ae2d2613-dfc7-49eb-90ec-4cc77daf5d9c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
@@ -2487,7 +2476,7 @@
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-01af1ccd-c3a4-419e-aed4-56b23e926757' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01af1ccd-c3a4-419e-aed4-56b23e926757' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0e5413a-be8e-496f-af35-fb662daba530' class='xr-var-data-in' type='checkbox'><label for='data-d0e5413a-be8e-496f-af35-fb662daba530' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-07b270e1-76b1-4d7a-bb68-bd0976704d2c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07b270e1-76b1-4d7a-bb68-bd0976704d2c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f5c59a0-1323-4827-b779-7dc9bc5a7064' class='xr-var-data-in' type='checkbox'><label for='data-9f5c59a0-1323-4827-b779-7dc9bc5a7064' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
               "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
               "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
               "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
@@ -2527,7 +2516,7 @@
               "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
               "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
               "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
-              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.2358 0.266 0.3007 ... nan nan nan</div><input id='attrs-665ebe14-ba24-40f5-9226-a118f6761f9d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-665ebe14-ba24-40f5-9226-a118f6761f9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3a5d9f8-a1cb-42be-ab63-663907c9dd0b' class='xr-var-data-in' type='checkbox'><label for='data-f3a5d9f8-a1cb-42be-ab63-663907c9dd0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.23582192,  0.2660148 ,  0.30069652, ..., -0.179669  ,\n",
+              "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.2358 0.266 0.3007 ... nan nan nan</div><input id='attrs-80f9429f-e37d-463a-b260-bc3dce95522f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80f9429f-e37d-463a-b260-bc3dce95522f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc2060a2-f49a-4655-9ed5-6966a6b9a0c8' class='xr-var-data-in' type='checkbox'><label for='data-dc2060a2-f49a-4655-9ed5-6966a6b9a0c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.23582192,  0.2660148 ,  0.30069652, ..., -0.179669  ,\n",
               "         -0.18383324, -0.17606331],\n",
               "        [ 0.25633767,  0.28601688,  0.3117814 , ..., -0.19580415,\n",
               "         -0.19696543, -0.20011853],\n",
@@ -2567,7 +2556,7 @@
               "        [        nan,         nan,         nan, ...,         nan,\n",
               "                 nan,         nan],\n",
               "        [        nan,         nan,         nan, ...,         nan,\n",
-              "                 nan,         nan]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>79.95 80.28 80.69 ... nan nan nan</div><input id='attrs-607b4830-7e21-4da6-8d8b-1f65eaf5f39c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-607b4830-7e21-4da6-8d8b-1f65eaf5f39c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5adc8999-e82a-423c-88e9-4af1054160d1' class='xr-var-data-in' type='checkbox'><label for='data-5adc8999-e82a-423c-88e9-4af1054160d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[79.94666 , 80.28167 , 80.68667 , ..., 81.721664, 81.80334 ,\n",
+              "                 nan,         nan]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>79.95 80.28 80.69 ... nan nan nan</div><input id='attrs-835a0dc2-bd02-46dc-b855-d47c12c9c279' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-835a0dc2-bd02-46dc-b855-d47c12c9c279' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d2b5c66-6ad4-4add-af31-56e1b8ffedc7' class='xr-var-data-in' type='checkbox'><label for='data-1d2b5c66-6ad4-4add-af31-56e1b8ffedc7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[79.94666 , 80.28167 , 80.68667 , ..., 81.721664, 81.80334 ,\n",
               "         81.68667 ],\n",
               "        [75.535   , 76.043335, 76.66167 , ..., 77.62666 , 77.73    ,\n",
               "         77.528336],\n",
@@ -2607,7 +2596,7 @@
               "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
               "               nan],\n",
               "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-              "               nan]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>92.59 92.61 92.47 ... 0.0 0.0 0.0</div><input id='attrs-99e9ecb5-0096-4877-b309-9fa45c5b5f25' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-99e9ecb5-0096-4877-b309-9fa45c5b5f25' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e29c093-c2c3-40d5-aab8-ff4fcf2f60f9' class='xr-var-data-in' type='checkbox'><label for='data-2e29c093-c2c3-40d5-aab8-ff4fcf2f60f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[92.58667 , 92.613335, 92.47    , ..., 91.933334, 91.96667 ,\n",
+              "               nan]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>92.59 92.61 92.47 ... 0.0 0.0 0.0</div><input id='attrs-286a83dd-1148-46cb-9de7-e2ae8ece0f95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-286a83dd-1148-46cb-9de7-e2ae8ece0f95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3d168c9-4293-4ab6-a0b1-2e9f011125be' class='xr-var-data-in' type='checkbox'><label for='data-d3d168c9-4293-4ab6-a0b1-2e9f011125be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[92.58667 , 92.613335, 92.47    , ..., 91.933334, 91.96667 ,\n",
               "         92.06333 ],\n",
               "        [96.236664, 96.526665, 96.206665, ..., 96.00667 , 96.3     ,\n",
               "         96.03333 ],\n",
@@ -2647,7 +2636,7 @@
               "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
               "          0.      ],\n",
               "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-              "          0.      ]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.05743 0.05697 ... 0.9937 0.9937</div><input id='attrs-241d0ed9-b027-414e-83dc-a606034fb4af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-241d0ed9-b027-414e-83dc-a606034fb4af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21ad0c23-83d5-48f5-9708-af9142aa6a71' class='xr-var-data-in' type='checkbox'><label for='data-21ad0c23-83d5-48f5-9708-af9142aa6a71' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[ 5.74317947e-02,  5.69723397e-02,  5.82992062e-02, ...,\n",
+              "          0.      ]]], shape=(4, 28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.05743 0.05697 ... 0.9937 0.9937</div><input id='attrs-f571b318-e797-496a-b128-02af5fbd8d46' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f571b318-e797-496a-b128-02af5fbd8d46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cb3b78f-ae14-4dba-b173-83f31056980d' class='xr-var-data-in' type='checkbox'><label for='data-2cb3b78f-ae14-4dba-b173-83f31056980d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[ 5.74317947e-02,  5.69723397e-02,  5.82992062e-02, ...,\n",
               "          5.81927113e-02,  5.85613623e-02,  5.85512854e-02],\n",
               "        [ 9.98300374e-01,  9.98323679e-01,  9.98248577e-01, ...,\n",
               "          9.98254061e-01,  9.98234987e-01,  9.98234689e-01],\n",
@@ -2667,7 +2656,7 @@
               "          7.35414820e-03,  7.39390310e-03,  7.38611678e-03],\n",
               "        [ 9.91627276e-01,  9.91604209e-01,  9.91649806e-01, ...,\n",
               "          9.93667483e-01,  9.93692815e-01,  9.93687749e-01]]],\n",
-              "      shape=(3, 3, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.000807 0.0008203 ... -0.002598</div><input id='attrs-12507aeb-982c-485c-b80b-ef6a2e6e4e1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12507aeb-982c-485c-b80b-ef6a2e6e4e1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-050e9f71-3258-44b4-8690-2f92378ece16' class='xr-var-data-in' type='checkbox'><label for='data-050e9f71-3258-44b4-8690-2f92378ece16' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00080699,  0.00082028,  0.00085015,  0.0008093 ,  0.00077764,\n",
+              "      shape=(3, 3, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.000807 0.0008203 ... -0.002598</div><input id='attrs-f5f72cc0-816a-4bd5-91a4-3554e0011ccd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f5f72cc0-816a-4bd5-91a4-3554e0011ccd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53b865f0-230e-4714-ba59-680e4cf00b61' class='xr-var-data-in' type='checkbox'><label for='data-53b865f0-230e-4714-ba59-680e4cf00b61' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00080699,  0.00082028,  0.00085015,  0.0008093 ,  0.00077764,\n",
               "         0.00076247,  0.00084005,  0.00080013,  0.00073725,  0.00069978,\n",
               "         0.00068869,  0.000708  ,  0.00070397,  0.00064101,  0.0007507 ,\n",
               "         0.00071757,  0.00060209,  0.00062077,  0.00062501,  0.0005675 ,\n",
@@ -2707,7 +2696,7 @@
               "        -0.00263345, -0.00258136, -0.00250975, -0.00261717, -0.00264321,\n",
               "        -0.00260741, -0.00261066, -0.00250649, -0.00248371, -0.0026074 ,\n",
               "        -0.00260415, -0.00260415, -0.00250324, -0.00259764, -0.002513  ,\n",
-              "        -0.00256509, -0.00253904, -0.00259764]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-16ed46ae-7d4d-4c4e-bcc1-329f5d24ac12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16ed46ae-7d4d-4c4e-bcc1-329f5d24ac12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b1d7b13-8be4-4d86-a16c-860579014f57' class='xr-var-data-in' type='checkbox'><label for='data-2b1d7b13-8be4-4d86-a16c-860579014f57' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245074 ,  0.624316  ,  0.6248463 ,  0.6245108 ,  0.6247046 ,\n",
+              "        -0.00256509, -0.00253904, -0.00259764]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-45a6a8d5-3fef-4a8f-866f-3a995f2a7b59' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45a6a8d5-3fef-4a8f-866f-3a995f2a7b59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0994d618-54bb-41b5-a0d3-170b89de0800' class='xr-var-data-in' type='checkbox'><label for='data-0994d618-54bb-41b5-a0d3-170b89de0800' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245074 ,  0.624316  ,  0.6248463 ,  0.6245108 ,  0.6247046 ,\n",
               "         0.62467265,  0.62460417,  0.62476116,  0.6245991 ,  0.6246464 ,\n",
               "         0.624686  ,  0.6249721 ,  0.6249648 ,  0.6250649 ,  0.62494904,\n",
               "         0.62500936,  0.6250884 ,  0.6250855 ,  0.6253171 ,  0.6254035 ,\n",
@@ -2747,7 +2736,7 @@
               "         0.7785521 ,  0.77869254,  0.77849793,  0.7787016 ,  0.77872854,\n",
               "         0.77860415,  0.7784391 ,  0.7783881 ,  0.7785563 ,  0.77852774,\n",
               "         0.77856874,  0.77847373,  0.7784385 ,  0.7782882 ,  0.778279  ,\n",
-              "         0.778462  ,  0.77835196,  0.77835387]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-a09fcfb0-cde6-413d-ad34-9add349bacff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a09fcfb0-cde6-413d-ad34-9add349bacff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a7e2d2c-f10e-4baa-85f6-0ace6279d138' class='xr-var-data-in' type='checkbox'><label for='data-0a7e2d2c-f10e-4baa-85f6-0ace6279d138' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.800002 , 12.800002 , 12.800002 , 12.800002 , 12.800002 ,\n",
+              "         0.778462  ,  0.77835196,  0.77835387]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-80807e6c-4ad1-4cb5-a7b4-432d16d0cb72' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80807e6c-4ad1-4cb5-a7b4-432d16d0cb72' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d10a642e-69bf-4c03-a5c3-06929c1a6332' class='xr-var-data-in' type='checkbox'><label for='data-d10a642e-69bf-4c03-a5c3-06929c1a6332' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.800002 , 12.800002 , 12.800002 , 12.800002 , 12.800002 ,\n",
               "       12.966666 , 13.       , 13.050666 , 13.199998 , 13.199998 ,\n",
               "       13.199998 , 13.199998 , 13.199998 , 13.199998 , 13.199998 ,\n",
               "       13.199998 , 13.199998 , 13.199998 , 13.176665 , 13.       ,\n",
@@ -2783,7 +2772,7 @@
               "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
               "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
               "       12.1119995, 12.       , 12.       , 12.       , 12.       ,\n",
-              "       12.       , 12.       , 12.       ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>244.0 244.0 244.0 ... 246.0 246.0</div><input id='attrs-75efebf3-f8be-4e5c-a22d-905b3bbad4fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75efebf3-f8be-4e5c-a22d-905b3bbad4fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c0ebbd6-078d-4f32-b25a-55eeb5f93919' class='xr-var-data-in' type='checkbox'><label for='data-8c0ebbd6-078d-4f32-b25a-55eeb5f93919' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([244.04333, 243.96   , 244.04666, 244.12334, 244.30667, 244.32   ,\n",
+              "       12.       , 12.       , 12.       ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>244.0 244.0 244.0 ... 246.0 246.0</div><input id='attrs-da38a2c5-c0d7-45bf-ace1-9a9ae7cc141c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da38a2c5-c0d7-45bf-ace1-9a9ae7cc141c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90901631-17a9-41e8-b887-81a76cadf770' class='xr-var-data-in' type='checkbox'><label for='data-90901631-17a9-41e8-b887-81a76cadf770' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([244.04333, 243.96   , 244.04666, 244.12334, 244.30667, 244.32   ,\n",
               "       244.04   , 243.95667, 243.72   , 243.45334, 243.46   , 243.49333,\n",
               "       243.49667, 243.69667, 243.80333, 243.78334, 243.81667, 244.     ,\n",
               "       244.27333, 244.39667, 244.58333, 244.73334, 244.95334, 245.     ,\n",
@@ -2813,7 +2802,7 @@
               "       245.95667, 245.94   , 245.93   , 245.95667, 245.95   , 245.95334,\n",
               "       245.94667, 245.96   , 245.96333, 245.97333, 245.96666, 245.96   ,\n",
               "       245.97667, 245.99   , 245.98   , 245.98666, 245.98666, 245.98334,\n",
-              "       245.99   , 245.98334, 245.99   ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.589 3.576 3.611 ... -197.1 -197.1</div><input id='attrs-fd489df3-8b21-4d7f-8332-54532a8591f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd489df3-8b21-4d7f-8332-54532a8591f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8aef5a18-22ef-4bad-8ed8-98dd5d4c9dac' class='xr-var-data-in' type='checkbox'><label for='data-8aef5a18-22ef-4bad-8ed8-98dd5d4c9dac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[ 3.5890043e+00,  3.5764265e+00,  3.6108000e+00,  3.5779481e+00,\n",
+              "       245.99   , 245.98334, 245.99   ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.589 3.576 3.611 ... -197.1 -197.1</div><input id='attrs-2aa34c31-3361-49b7-a9c5-8ab6c267b27f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2aa34c31-3361-49b7-a9c5-8ab6c267b27f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-731bdd99-c0c2-4995-8df5-99a7b6b8cba5' class='xr-var-data-in' type='checkbox'><label for='data-731bdd99-c0c2-4995-8df5-99a7b6b8cba5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[ 3.5890043e+00,  3.5764265e+00,  3.6108000e+00,  3.5779481e+00,\n",
               "         3.6116719e+00,  3.5757926e+00,  3.5947008e+00,  3.6243417e+00,\n",
               "         3.6057498e+00,  3.5963907e+00,  3.5682683e+00,  3.5830538e+00,\n",
               "         3.6165168e+00,  3.5789921e+00,  3.5747981e+00,  3.5690453e+00,\n",
@@ -2853,7 +2842,7 @@
               "        -1.9710718e+02, -1.9718983e+02, -1.9715218e+02, -1.9712483e+02,\n",
               "        -1.9706255e+02, -1.9714519e+02, -1.9712418e+02, -1.9705786e+02,\n",
               "        -1.9708685e+02, -1.9711749e+02, -1.9707716e+02, -1.9707919e+02,\n",
-              "        -1.9719186e+02, -1.9713850e+02, -1.9714883e+02]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.262 -1.263 -1.26 ... 9.714 9.713</div><input id='attrs-c72fb572-a5c8-4c91-8da0-efa35e435329' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c72fb572-a5c8-4c91-8da0-efa35e435329' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88c02d03-b496-43f8-a086-59776e5b79b2' class='xr-var-data-in' type='checkbox'><label for='data-88c02d03-b496-43f8-a086-59776e5b79b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.2623771 , -1.2625197 , -1.2600151 , -1.2631888 , -1.2615377 ,\n",
+              "        -1.9719186e+02, -1.9713850e+02, -1.9714883e+02]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.262 -1.263 -1.26 ... 9.714 9.713</div><input id='attrs-8a8419d8-2c69-41fe-8e75-29534c04e382' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a8419d8-2c69-41fe-8e75-29534c04e382' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26ead8e4-f4aa-4e9f-9c2b-b791e066a12a' class='xr-var-data-in' type='checkbox'><label for='data-26ead8e4-f4aa-4e9f-9c2b-b791e066a12a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.2623771 , -1.2625197 , -1.2600151 , -1.2631888 , -1.2615377 ,\n",
               "        -1.2616537 , -1.262574  , -1.2627327 , -1.2632962 , -1.2634871 ,\n",
               "        -1.2617764 , -1.2599101 , -1.2592376 , -1.2577692 , -1.259011  ,\n",
               "        -1.2584039 , -1.2585176 , -1.2577502 , -1.2569212 , -1.2552022 ,\n",
@@ -2893,7 +2882,7 @@
               "         9.714553  ,  9.715957  ,  9.7148075 ,  9.717874  ,  9.716309  ,\n",
               "         9.715032  ,  9.7090435 ,  9.711168  ,  9.7130995 ,  9.713355  ,\n",
               "         9.715256  ,  9.714936  ,  9.7148075 ,  9.711726  ,  9.711886  ,\n",
-              "         9.713675  ,  9.714042  ,  9.712781  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-173e0f05-5aad-4109-aef4-292f0d07423f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-173e0f05-5aad-4109-aef4-292f0d07423f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcca7d45-de13-4bfc-a608-bd7afacf7458' class='xr-var-data-in' type='checkbox'><label for='data-fcca7d45-de13-4bfc-a608-bd7afacf7458' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "         9.713675  ,  9.714042  ,  9.712781  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-c1489d78-e4f8-4ed9-a39b-16d34eef0607' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1489d78-e4f8-4ed9-a39b-16d34eef0607' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-979eb0b5-c11d-4941-91e7-eaed1428ac1b' class='xr-var-data-in' type='checkbox'><label for='data-979eb0b5-c11d-4941-91e7-eaed1428ac1b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
@@ -2903,7 +2892,7 @@
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-cb79631d-b8cd-4f38-be3c-d31808c5ce3d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb79631d-b8cd-4f38-be3c-d31808c5ce3d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6622e78-2817-4caf-a5b2-5a12ee985f2b' class='xr-var-data-in' type='checkbox'><label for='data-c6622e78-2817-4caf-a5b2-5a12ee985f2b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-52723004-2e23-4fbc-95bf-e29b29e5059f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52723004-2e23-4fbc-95bf-e29b29e5059f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4dabc074-db2c-43f3-a21f-ba8e89d48e8c' class='xr-var-data-in' type='checkbox'><label for='data-4dabc074-db2c-43f3-a21f-ba8e89d48e8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
               "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
               "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
               "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
@@ -2943,7 +2932,7 @@
               "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
               "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
               "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0006333 -0.004143 ... nan nan</div><input id='attrs-8cdda550-3fce-4d0b-91b9-172fdfaf973f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8cdda550-3fce-4d0b-91b9-172fdfaf973f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfd612d6-b3a1-49b1-9e09-51eaa5d47905' class='xr-var-data-in' type='checkbox'><label for='data-bfd612d6-b3a1-49b1-9e09-51eaa5d47905' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00063333, -0.00414333, -0.00776667, ..., -0.01952   ,\n",
+              "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0006333 -0.004143 ... nan nan</div><input id='attrs-ac1abc66-620f-46c9-9a93-3075662d1ab6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac1abc66-620f-46c9-9a93-3075662d1ab6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7234876-f33b-4775-8583-4d0c8554cecb' class='xr-var-data-in' type='checkbox'><label for='data-f7234876-f33b-4775-8583-4d0c8554cecb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00063333, -0.00414333, -0.00776667, ..., -0.01952   ,\n",
               "        -0.02035667, -0.01573333],\n",
               "       [ 0.02268667,  0.01564333,  0.01504   , ..., -0.00309667,\n",
               "        -0.00658667, -0.00238   ],\n",
@@ -2955,7 +2944,7 @@
               "       [        nan,         nan,         nan, ...,         nan,\n",
               "                nan,         nan],\n",
               "       [        nan,         nan,         nan, ...,         nan,\n",
-              "                nan,         nan]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.08 80.44 80.75 ... nan nan nan</div><input id='attrs-4674d53d-23f4-4ca3-a6c0-6716ceb13fad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4674d53d-23f4-4ca3-a6c0-6716ceb13fad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b30d7f25-c68f-4ad0-a6dc-3f864b9ddb81' class='xr-var-data-in' type='checkbox'><label for='data-b30d7f25-c68f-4ad0-a6dc-3f864b9ddb81' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[80.085   , 80.43833 , 80.75166 , ..., 81.761665, 81.86    ,\n",
+              "                nan,         nan]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.08 80.44 80.75 ... nan nan nan</div><input id='attrs-1207ec72-09c2-4b85-ac67-d272dcc3b499' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1207ec72-09c2-4b85-ac67-d272dcc3b499' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3d3b874-816d-4bc9-b9c1-cac5234ab087' class='xr-var-data-in' type='checkbox'><label for='data-d3d3b874-816d-4bc9-b9c1-cac5234ab087' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[80.085   , 80.43833 , 80.75166 , ..., 81.761665, 81.86    ,\n",
               "        81.745   ],\n",
               "       [76.05    , 76.60333 , 77.066666, ..., 78.23    , 78.21667 ,\n",
               "        78.045   ],\n",
@@ -2967,7 +2956,7 @@
               "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
               "              nan],\n",
               "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
-              "              nan]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>93.52 94.19 93.97 ... 0.0 0.0 0.0</div><input id='attrs-245f98b9-d7d1-48e6-b010-4aa5f61c9093' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-245f98b9-d7d1-48e6-b010-4aa5f61c9093' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f71b4578-897e-4a9c-97cd-d126fcc44f3f' class='xr-var-data-in' type='checkbox'><label for='data-f71b4578-897e-4a9c-97cd-d126fcc44f3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[93.51667 , 94.18667 , 93.97    , ..., 92.276665, 92.09    ,\n",
+              "              nan]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>93.52 94.19 93.97 ... 0.0 0.0 0.0</div><input id='attrs-03ad1167-0875-4cf7-975a-6bbb0d2a724a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-03ad1167-0875-4cf7-975a-6bbb0d2a724a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ed62442-4022-403a-b87a-5c6c1de5cf10' class='xr-var-data-in' type='checkbox'><label for='data-8ed62442-4022-403a-b87a-5c6c1de5cf10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[93.51667 , 94.18667 , 93.97    , ..., 92.276665, 92.09    ,\n",
               "        92.61667 ],\n",
               "       [96.75    , 96.403336, 96.32    , ..., 96.433334, 96.89    ,\n",
               "        96.57667 ],\n",
@@ -2979,7 +2968,7 @@
               "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
               "         0.      ],\n",
               "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-              "         0.      ]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2166 -0.217 ... 0.9937 0.9937</div><input id='attrs-40f80246-0761-48d4-bb1b-2d605298003b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-40f80246-0761-48d4-bb1b-2d605298003b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8b94896-a91d-47e1-a3cf-e2ce087e3fd7' class='xr-var-data-in' type='checkbox'><label for='data-c8b94896-a91d-47e1-a3cf-e2ce087e3fd7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16565624e-01, -2.17020363e-01, -2.15714216e-01, ...,\n",
+              "         0.      ]], shape=(28, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2166 -0.217 ... 0.9937 0.9937</div><input id='attrs-5e4433c1-a5c9-42b2-9362-7d86df0c9815' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e4433c1-a5c9-42b2-9362-7d86df0c9815' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83522526-79fc-4223-8c0c-267c8e027356' class='xr-var-data-in' type='checkbox'><label for='data-83522526-79fc-4223-8c0c-267c8e027356' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16565624e-01, -2.17020363e-01, -2.15714216e-01, ...,\n",
               "         -2.15817824e-01, -2.15457186e-01, -2.15469748e-01],\n",
               "        [-9.68014121e-01, -9.67880666e-01, -9.68221545e-01, ...,\n",
               "         -9.70180333e-01, -9.70283389e-01, -9.70276892e-01],\n",
@@ -2999,7 +2988,7 @@
               "         -1.12357967e-01, -1.12130813e-01, -1.12177916e-01],\n",
               "        [ 9.91627216e-01,  9.91603792e-01,  9.91649806e-01, ...,\n",
               "          9.93667185e-01,  9.93692756e-01,  9.93687451e-01]]],\n",
-              "      shape=(3, 3, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0008123 0.0008472 ... -0.002637</div><input id='attrs-a88a404b-46d4-4219-ad86-282168e89591' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a88a404b-46d4-4219-ad86-282168e89591' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6bf3922-5af0-410c-ba31-ebe6a624b783' class='xr-var-data-in' type='checkbox'><label for='data-e6bf3922-5af0-410c-ba31-ebe6a624b783' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00081228,  0.00084717,  0.00085335,  0.00075436,  0.00084513,\n",
+              "      shape=(3, 3, 183), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0008123 0.0008472 ... -0.002637</div><input id='attrs-d7173144-8398-40be-bd9d-dde1b7389737' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7173144-8398-40be-bd9d-dde1b7389737' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb4b2283-0ff2-44f1-b251-ed0b82c4cbce' class='xr-var-data-in' type='checkbox'><label for='data-bb4b2283-0ff2-44f1-b251-ed0b82c4cbce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00081228,  0.00084717,  0.00085335,  0.00075436,  0.00084513,\n",
               "         0.00085451,  0.00073719,  0.00067843,  0.00075248,  0.00074199,\n",
               "         0.00070569,  0.00065896,  0.0006914 ,  0.00069842,  0.00074138,\n",
               "         0.0006676 ,  0.00060215,  0.00059847,  0.0006675 ,  0.0006136 ,\n",
@@ -3039,7 +3028,7 @@
               "        -0.00265949, -0.00270831, -0.00258787, -0.0025423 , -0.00262368,\n",
               "        -0.00264647, -0.00268879, -0.00251626, -0.00256183, -0.00255207,\n",
               "        -0.00251626, -0.00251626, -0.00249998, -0.00248371, -0.0024479 ,\n",
-              "        -0.00254881, -0.00254881, -0.0026367 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-79342d36-54df-4ac7-b7a6-8ade131b8aa8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79342d36-54df-4ac7-b7a6-8ade131b8aa8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb4aa0ce-a72a-4cb6-87b0-f837b7a85472' class='xr-var-data-in' type='checkbox'><label for='data-cb4aa0ce-a72a-4cb6-87b0-f837b7a85472' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245025 ,  0.62430865,  0.62484366,  0.62450564,  0.624701  ,\n",
+              "        -0.00254881, -0.00254881, -0.0026367 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-b39bd1a7-c5aa-4350-abf6-a52d0d9b0342' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b39bd1a7-c5aa-4350-abf6-a52d0d9b0342' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2805d9de-f37e-4513-91bb-60faa10fcdd8' class='xr-var-data-in' type='checkbox'><label for='data-2805d9de-f37e-4513-91bb-60faa10fcdd8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245025 ,  0.62430865,  0.62484366,  0.62450564,  0.624701  ,\n",
               "         0.62466866,  0.62460196,  0.6247584 ,  0.62459546,  0.62464297,\n",
               "         0.6246826 ,  0.62496835,  0.6249581 ,  0.6250585 ,  0.62494546,\n",
               "         0.6250052 ,  0.62508506,  0.62507963,  0.6253132 ,  0.6254015 ,\n",
@@ -3079,7 +3068,7 @@
               "         0.77855694,  0.778695  ,  0.77849764,  0.7787041 ,  0.77873075,\n",
               "         0.7786052 ,  0.7784392 ,  0.7783923 ,  0.77855927,  0.77852917,\n",
               "         0.7785722 ,  0.77847767,  0.77844226,  0.77829295,  0.7782816 ,\n",
-              "         0.77846414,  0.778354  ,  0.77835685]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>65.0 65.0 65.0 ... 65.0 65.0 65.0</div><input id='attrs-90a82423-bd66-438b-b1eb-ba055085ce88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90a82423-bd66-438b-b1eb-ba055085ce88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5030b7a-9072-4086-8bca-0d9385aea495' class='xr-var-data-in' type='checkbox'><label for='data-a5030b7a-9072-4086-8bca-0d9385aea495' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+              "         0.77846414,  0.778354  ,  0.77835685]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>65.0 65.0 65.0 ... 65.0 65.0 65.0</div><input id='attrs-ac9904c0-7c54-436e-ae3f-01105ec4b6ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac9904c0-7c54-436e-ae3f-01105ec4b6ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0044892b-bf52-4cea-a990-44d519ed1609' class='xr-var-data-in' type='checkbox'><label for='data-0044892b-bf52-4cea-a990-44d519ed1609' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
               "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
               "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
               "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
@@ -3093,7 +3082,7 @@
               "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
               "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
               "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-              "       65.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-46bd7f90-904c-4bb4-885d-5966426d4586' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-46bd7f90-904c-4bb4-885d-5966426d4586' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea7fe455-de57-49f8-a767-2e3999b861ff' class='xr-var-data-in' type='checkbox'><label for='data-ea7fe455-de57-49f8-a767-2e3999b861ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       65.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-530600cd-d334-468f-b609-aa2995780efd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-530600cd-d334-468f-b609-aa2995780efd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4201c682-780a-4c9b-bcdb-91bea8d76fa6' class='xr-var-data-in' type='checkbox'><label for='data-4201c682-780a-4c9b-bcdb-91bea8d76fa6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
@@ -3103,7 +3092,7 @@
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-76e19f02-9be1-425f-98ce-a8b8b3158a17' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-76e19f02-9be1-425f-98ce-a8b8b3158a17' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5171da35-a4b5-4683-b9c2-81947203191c' class='xr-var-data-in' type='checkbox'><label for='data-5171da35-a4b5-4683-b9c2-81947203191c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-e880d741-352f-4824-8fdf-574661b1157a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e880d741-352f-4824-8fdf-574661b1157a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97f17196-9934-41d3-84eb-09808b171b41' class='xr-var-data-in' type='checkbox'><label for='data-97f17196-9934-41d3-84eb-09808b171b41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
@@ -3113,7 +3102,7 @@
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-462cefba-0bfb-4f65-a7d0-84ba279bddeb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-462cefba-0bfb-4f65-a7d0-84ba279bddeb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4aa0bf2-4dee-41c1-82fd-70af1445586e' class='xr-var-data-in' type='checkbox'><label for='data-b4aa0bf2-4dee-41c1-82fd-70af1445586e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-5421ce6b-1e96-439f-8a08-d278b40a3c44' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5421ce6b-1e96-439f-8a08-d278b40a3c44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc9df836-e7c1-47d7-a6dc-665c75d077b6' class='xr-var-data-in' type='checkbox'><label for='data-cc9df836-e7c1-47d7-a6dc-665c75d077b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
@@ -3123,7 +3112,7 @@
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
               "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.1267 0.1333 0.13 ... 0.22 0.22</div><input id='attrs-0c5481a4-18a4-42ff-9ca0-26f6c143daf8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c5481a4-18a4-42ff-9ca0-26f6c143daf8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f63b6680-7fcf-4cda-8783-43fce0c4ad63' class='xr-var-data-in' type='checkbox'><label for='data-f63b6680-7fcf-4cda-8783-43fce0c4ad63' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.12666667, 0.13333334, 0.13      , 0.13333334, 0.13      ,\n",
+              "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.1267 0.1333 0.13 ... 0.22 0.22</div><input id='attrs-e6d26a7e-dbf1-4e8b-b5c5-e7e625fbf25b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e6d26a7e-dbf1-4e8b-b5c5-e7e625fbf25b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-49a0c93a-7544-4e43-a887-660a21e44663' class='xr-var-data-in' type='checkbox'><label for='data-49a0c93a-7544-4e43-a887-660a21e44663' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.12666667, 0.13333334, 0.13      , 0.13333334, 0.13      ,\n",
               "       0.13      , 0.13      , 0.11666667, 0.12333333, 0.11666667,\n",
               "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11666667,\n",
               "       0.11      , 0.11333334, 0.11333334, 0.11333334, 0.12333333,\n",
@@ -3159,7 +3148,7 @@
               "       0.22666667, 0.22      , 0.22      , 0.22666667, 0.22      ,\n",
               "       0.22      , 0.22666667, 0.22      , 0.22      , 0.22666667,\n",
               "       0.22      , 0.22      , 0.22666667, 0.22      , 0.22      ,\n",
-              "       0.22666667, 0.22      , 0.22      ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.287 3.261 3.337 ... 3.352 3.352</div><input id='attrs-89c1f95c-d6a4-4603-a322-ce27aff150b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89c1f95c-d6a4-4603-a322-ce27aff150b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec191042-2bc1-4fbe-baf9-a5bbfa9dc4cd' class='xr-var-data-in' type='checkbox'><label for='data-ec191042-2bc1-4fbe-baf9-a5bbfa9dc4cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([3.287083 , 3.2605155, 3.3369133, 3.2892823, 3.3165808, 3.3119812,\n",
+              "       0.22666667, 0.22      , 0.22      ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.287 3.261 3.337 ... 3.352 3.352</div><input id='attrs-ee6c7c13-5318-4806-ad24-22ffe79846c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee6c7c13-5318-4806-ad24-22ffe79846c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d46d7a3-9016-4cc3-aaa6-71f6a1560d55' class='xr-var-data-in' type='checkbox'><label for='data-1d46d7a3-9016-4cc3-aaa6-71f6a1560d55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([3.287083 , 3.2605155, 3.3369133, 3.2892823, 3.3165808, 3.3119812,\n",
               "       3.3027983, 3.3258302, 3.3029814, 3.3100154, 3.3152144, 3.3549793,\n",
               "       3.3538957, 3.3682969, 3.3522127, 3.3599124, 3.3716784, 3.370829 ,\n",
               "       3.404896 , 3.4170458, 3.4101129, 3.4259632, 3.3813803, 3.352863 ,\n",
@@ -3189,7 +3178,7 @@
               "       3.2660322, 3.2617817, 3.3116815, 3.314548 , 3.289132 , 3.3249977,\n",
               "       3.287216 , 3.282166 , 3.306248 , 3.3363798, 3.3452635, 3.314365 ,\n",
               "       3.3198478, 3.3122149, 3.3298814, 3.3361466, 3.3632295, 3.3652124,\n",
-              "       3.331114 , 3.352297 , 3.351696 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.05523 -0.07217 ... -0.0429</div><input id='attrs-6ddbe7fd-0d4a-43de-a61e-a765e89b45b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ddbe7fd-0d4a-43de-a61e-a765e89b45b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9d7de0b-9402-405f-b436-f1b1629cd297' class='xr-var-data-in' type='checkbox'><label for='data-f9d7de0b-9402-405f-b436-f1b1629cd297' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.05523333, -0.07216667, -0.05975001, -0.0719    , -0.06111666,\n",
+              "       3.331114 , 3.352297 , 3.351696 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.05523 -0.07217 ... -0.0429</div><input id='attrs-c5a9fc28-31a5-4b78-bf31-d79210ec1dd4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5a9fc28-31a5-4b78-bf31-d79210ec1dd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-549b7c47-68e6-4efb-a142-3cdbc96f31c2' class='xr-var-data-in' type='checkbox'><label for='data-549b7c47-68e6-4efb-a142-3cdbc96f31c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.05523333, -0.07216667, -0.05975001, -0.0719    , -0.06111666,\n",
               "       -0.05995   , -0.07213333, -0.07148333, -0.07696667, -0.08181667,\n",
               "       -0.0731    , -0.0579    , -0.05488333, -0.05605   , -0.05533333,\n",
               "       -0.05278333, -0.047     , -0.0521    , -0.05088333, -0.04305   ,\n",
@@ -3225,7 +3214,7 @@
               "       -0.04428333, -0.05206667, -0.04676667, -0.05188334, -0.0574    ,\n",
               "       -0.06316667, -0.0484    , -0.04308333, -0.04601667, -0.0499    ,\n",
               "       -0.05471666, -0.05536667, -0.04616667, -0.02825   , -0.03388334,\n",
-              "       -0.0423    , -0.04288333, -0.0429    ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.414 -7.424 ... -6.433 -6.436</div><input id='attrs-0d7d1c1f-4856-47c2-8ee3-cac17108f21c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d7d1c1f-4856-47c2-8ee3-cac17108f21c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd7fe75f-ea11-41f2-8671-9eb4066199b5' class='xr-var-data-in' type='checkbox'><label for='data-dd7fe75f-ea11-41f2-8671-9eb4066199b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.414066 , -7.424116 , -7.4041324, -7.422417 , -7.4120665,\n",
+              "       -0.0423    , -0.04288333, -0.0429    ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.414 -7.424 ... -6.433 -6.436</div><input id='attrs-6c2edf8f-5c91-42ea-89ad-21b62c2beb53' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c2edf8f-5c91-42ea-89ad-21b62c2beb53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c567dd3-4ec1-4bd5-ac93-c615acab80af' class='xr-var-data-in' type='checkbox'><label for='data-0c567dd3-4ec1-4bd5-ac93-c615acab80af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.414066 , -7.424116 , -7.4041324, -7.422417 , -7.4120665,\n",
               "       -7.4167333, -7.4193   , -7.4148664, -7.4301662, -7.419133 ,\n",
               "       -7.4179006, -7.402567 , -7.4040666, -7.394583 , -7.403933 ,\n",
               "       -7.394567 , -7.39615  , -7.3910007, -7.386317 , -7.3802505,\n",
@@ -3261,7 +3250,7 @@
               "       -6.4438   , -6.450166 , -6.4428334, -6.45625  , -6.455867 ,\n",
               "       -6.44465  , -6.436783 , -6.430967 , -6.4454665, -6.441799 ,\n",
               "       -6.4480996, -6.4399   , -6.4372997, -6.4309335, -6.4305167,\n",
-              "       -6.4460497, -6.4332495, -6.4359174], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_density</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.023e+03</div><input id='attrs-20ca3cf4-a5e7-421f-b8f7-6af5213aed7c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-20ca3cf4-a5e7-421f-b8f7-6af5213aed7c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ff21534-9173-4595-b780-e6ba70ff82a6' class='xr-var-data-in' type='checkbox'><label for='data-8ff21534-9173-4595-b780-e6ba70ff82a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>kg m-3</dd><dt><span>long_name :</span></dt><dd>Water Density</dd><dt><span>standard_name :</span></dt><dd>sea_water_density</dd><dt><span>description :</span></dt><dd>Water density from linear approximation of sea water equation of state</dd></dl></div><div class='xr-var-data'><pre>array([1023.2506 , 1023.2348 , 1023.2431 , 1023.2559 , 1023.2423 ,\n",
+              "       -6.4460497, -6.4332495, -6.4359174], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_density</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.023e+03</div><input id='attrs-6950b35b-71bd-4e77-af5a-edfa6d09ff1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6950b35b-71bd-4e77-af5a-edfa6d09ff1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b5fb35a-3179-4627-941c-9092dcc52a7d' class='xr-var-data-in' type='checkbox'><label for='data-9b5fb35a-3179-4627-941c-9092dcc52a7d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>kg m-3</dd><dt><span>long_name :</span></dt><dd>Water Density</dd><dt><span>standard_name :</span></dt><dd>sea_water_density</dd><dt><span>description :</span></dt><dd>Water density from linear approximation of sea water equation of state</dd></dl></div><div class='xr-var-data'><pre>array([1023.2506 , 1023.2348 , 1023.2431 , 1023.2559 , 1023.2423 ,\n",
               "       1023.21655, 1023.1977 , 1023.2015 , 1023.19476, 1023.19116,\n",
               "       1023.194  , 1023.1996 , 1023.20294, 1023.19666, 1023.19336,\n",
               "       1023.19763, 1023.205  , 1023.20404, 1023.2148 , 1023.2179 ,\n",
@@ -3297,7 +3286,7 @@
               "       1023.3432 , 1023.34186, 1023.34094, 1023.3408 , 1023.34   ,\n",
               "       1023.33655, 1023.34143, 1023.34155, 1023.34357, 1023.3508 ,\n",
               "       1023.3694 , 1023.37335, 1023.3781 , 1023.3796 , 1023.3752 ,\n",
-              "       1023.3806 , 1023.3899 , 1023.3975 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>10.28 10.26 10.25 ... 10.15 10.15</div><input id='attrs-62dc49db-3c51-4954-b4cb-390df3c41304' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62dc49db-3c51-4954-b4cb-390df3c41304' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0840afc8-a014-497a-9e16-c27c3a759f9f' class='xr-var-data-in' type='checkbox'><label for='data-0840afc8-a014-497a-9e16-c27c3a759f9f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Water Depth</dd><dt><span>standard_name :</span></dt><dd>depth</dd></dl></div><div class='xr-var-data'><pre>array([10.275155 , 10.262421 , 10.248638 , 10.233478 , 10.216689 ,\n",
+              "       1023.3806 , 1023.3899 , 1023.3975 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>10.28 10.26 10.25 ... 10.15 10.15</div><input id='attrs-69c71a5f-e445-4ea7-8f0c-4ea2adeba256' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69c71a5f-e445-4ea7-8f0c-4ea2adeba256' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c304da2-da73-4cf8-8348-f522cbcc6fc6' class='xr-var-data-in' type='checkbox'><label for='data-1c304da2-da73-4cf8-8348-f522cbcc6fc6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Water Depth</dd><dt><span>standard_name :</span></dt><dd>depth</dd></dl></div><div class='xr-var-data'><pre>array([10.275155 , 10.262421 , 10.248638 , 10.233478 , 10.216689 ,\n",
               "       10.204074 , 10.188269 , 10.172538 , 10.158512 , 10.140744 ,\n",
               "       10.124731 , 10.10534  , 10.088593 , 10.069619 , 10.050677 ,\n",
               "       10.028841 , 10.00682  ,  9.981041 ,  9.958139 ,  9.932152 ,\n",
@@ -3333,7 +3322,19 @@
               "        9.972928 ,  9.992192 , 10.00496  , 10.023165 , 10.037822 ,\n",
               "       10.052144 , 10.058786 , 10.073322 , 10.083076 , 10.093331 ,\n",
               "       10.100321 , 10.109131 , 10.117323 , 10.123545 , 10.1341   ,\n",
-              "       10.142311 , 10.14612  , 10.153638 ], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-34d41744-573a-4081-a409-9fee3bf6593e' class='xr-section-summary-in' type='checkbox'  ><label for='section-34d41744-573a-4081-a409-9fee3bf6593e' class='xr-section-summary' >Indexes: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-c7659f11-a202-45a0-a263-7fa50ecf74a6' class='xr-index-data-in' type='checkbox'/><label for='index-c7659f11-a202-45a0-a263-7fa50ecf74a6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:22:30.001030683&#x27;,\n",
+              "       10.142311 , 10.14612  , 10.153638 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U_std</span></div><div class='xr-var-dims'>(range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.04232 0.04293 0.04402 ... nan nan</div><input id='attrs-6f8b823e-8ebc-4098-ac88-ef9e421e2501' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f8b823e-8ebc-4098-ac88-ef9e421e2501' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aee946c4-df3b-4a9d-9731-0c3b3e11590c' class='xr-var-data-in' type='checkbox'><label for='data-aee946c4-df3b-4a9d-9731-0c3b3e11590c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([[0.04231985, 0.04293143, 0.04401674, ..., 0.04380286, 0.04201568,\n",
+              "        0.04634431],\n",
+              "       [0.04002878, 0.04084466, 0.03949426, ..., 0.04000184, 0.04028782,\n",
+              "        0.03873245],\n",
+              "       [0.04025545, 0.03514179, 0.04270846, ..., 0.0391249 , 0.03997382,\n",
+              "        0.04237254],\n",
+              "       ...,\n",
+              "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
+              "               nan],\n",
+              "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
+              "               nan],\n",
+              "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
+              "               nan]], shape=(28, 183), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-39822272-7344-4f67-9029-9ac3bdaf315f' class='xr-section-summary-in' type='checkbox'  ><label for='section-39822272-7344-4f67-9029-9ac3bdaf315f' class='xr-section-summary' >Indexes: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-22f50f61-d724-40f0-ba78-70482d1b5863' class='xr-index-data-in' type='checkbox'/><label for='index-22f50f61-d724-40f0-ba78-70482d1b5863' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:22:30.001030683&#x27;,\n",
               "               &#x27;2020-08-15 00:27:30.001019239&#x27;,\n",
               "               &#x27;2020-08-15 00:32:30.001010656&#x27;,\n",
               "               &#x27;2020-08-15 00:37:30.001015901&#x27;,\n",
@@ -3354,7 +3355,7 @@
               "               &#x27;2020-08-15 15:22:30.001026153&#x27;,\n",
               "               &#x27;2020-08-15 15:27:30.001022577&#x27;,\n",
               "               &#x27;2020-08-15 15:32:30.001030683&#x27;],\n",
-              "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=183, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dirIMU</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-79d0022c-bb73-4025-b16c-0e69f1a07b55' class='xr-index-data-in' type='checkbox'/><label for='index-79d0022c-bb73-4025-b16c-0e69f1a07b55' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dirIMU&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-d1b99d26-7067-489a-b9b9-c458bcb33e66' class='xr-index-data-in' type='checkbox'/><label for='index-d1b99d26-7067-489a-b9b9-c458bcb33e66' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               1.2, 1.7000000000000002,                2.2,\n",
+              "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=183, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dirIMU</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-68d0fa06-2aea-4d10-accd-011823a35690' class='xr-index-data-in' type='checkbox'/><label for='index-68d0fa06-2aea-4d10-accd-011823a35690' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dirIMU&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dir</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e234f08d-8c57-434a-a27b-ceaea3df8e75' class='xr-index-data-in' type='checkbox'/><label for='index-e234f08d-8c57-434a-a27b-ceaea3df8e75' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert1&#x27;, &#x27;vert2&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dir&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-9f63e293-4cea-4995-829a-d6f2ce67b99d' class='xr-index-data-in' type='checkbox'/><label for='index-9f63e293-4cea-4995-829a-d6f2ce67b99d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               1.2, 1.7000000000000002,                2.2,\n",
               "                      2.7,                3.2,                3.7,\n",
               "                      4.2,  4.699999999999999,  5.199999999999999,\n",
               "        5.699999999999999,  6.199999999999999,  6.699999999999999,\n",
@@ -3364,7 +3365,7 @@
               "                     11.7,               12.2,               12.7,\n",
               "                     13.2,               13.7,               14.2,\n",
               "                     14.7],\n",
-              "      dtype=&#x27;float64&#x27;, name=&#x27;range&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dir</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-8becd749-8b7d-416c-9dc2-346d1af1c6b7' class='xr-index-data-in' type='checkbox'/><label for='index-8becd749-8b7d-416c-9dc2-346d1af1c6b7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert1&#x27;, &#x27;vert2&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dir&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>beam</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-3289eea6-61af-495a-b255-47ab10d76a15' class='xr-index-data-in' type='checkbox'/><label for='index-3289eea6-61af-495a-b255-47ab10d76a15' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;beam&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>earth</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-8ec3b2b4-3c32-4d5c-82d6-af39928e5524' class='xr-index-data-in' type='checkbox'/><label for='index-8ec3b2b4-3c32-4d5c-82d6-af39928e5524' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;earth&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>inst</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-5c4e62f4-cadd-4802-9306-b513f788b78d' class='xr-index-data-in' type='checkbox'/><label for='index-5c4e62f4-cadd-4802-9306-b513f788b78d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;inst&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>q</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-328767fe-c918-4658-9d10-ab092faff002' class='xr-index-data-in' type='checkbox'/><label for='index-328767fe-c918-4658-9d10-ab092faff002' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;q&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_b5</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-dec06c77-a6b4-4695-8d3a-28eac47621be' class='xr-index-data-in' type='checkbox'/><label for='index-dec06c77-a6b4-4695-8d3a-28eac47621be' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:22:29.938495159&#x27;,\n",
+              "      dtype=&#x27;float64&#x27;, name=&#x27;range&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>beam</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-34366b69-9c8f-4bf6-989d-1da3a72d15ab' class='xr-index-data-in' type='checkbox'/><label for='index-34366b69-9c8f-4bf6-989d-1da3a72d15ab' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;beam&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>earth</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-36fbb1ab-b6cc-4322-b1c4-be9a69d327bd' class='xr-index-data-in' type='checkbox'/><label for='index-36fbb1ab-b6cc-4322-b1c4-be9a69d327bd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;earth&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>inst</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-235eb738-3773-4f61-a25e-957043df7788' class='xr-index-data-in' type='checkbox'/><label for='index-235eb738-3773-4f61-a25e-957043df7788' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;inst&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>q</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-77db153b-8d36-4e42-8aa1-a218f8b28f07' class='xr-index-data-in' type='checkbox'/><label for='index-77db153b-8d36-4e42-8aa1-a218f8b28f07' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;q&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_b5</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-42bff68f-07ca-47ad-82d7-da6c885d3a03' class='xr-index-data-in' type='checkbox'/><label for='index-42bff68f-07ca-47ad-82d7-da6c885d3a03' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:22:29.938495159&#x27;,\n",
               "               &#x27;2020-08-15 00:27:29.938490867&#x27;,\n",
               "               &#x27;2020-08-15 00:32:29.938487529&#x27;,\n",
               "               &#x27;2020-08-15 00:37:29.938496828&#x27;,\n",
@@ -3385,7 +3386,7 @@
               "               &#x27;2020-08-15 15:22:29.938486099&#x27;,\n",
               "               &#x27;2020-08-15 15:27:29.938484191&#x27;,\n",
               "               &#x27;2020-08-15 15:32:29.938490390&#x27;],\n",
-              "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_b5&#x27;, length=183, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range_b5</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-9f2781bd-a200-4094-ad9e-4a2c07c32bbb' class='xr-index-data-in' type='checkbox'/><label for='index-9f2781bd-a200-4094-ad9e-4a2c07c32bbb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               1.2, 1.7000000000000002,                2.2,\n",
+              "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_b5&#x27;, length=183, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range_b5</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-2a0b257d-1e4d-415d-9dca-9988fdbf08bb' class='xr-index-data-in' type='checkbox'/><label for='index-2a0b257d-1e4d-415d-9dca-9988fdbf08bb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               1.2, 1.7000000000000002,                2.2,\n",
               "                      2.7,                3.2,                3.7,\n",
               "                      4.2,  4.699999999999999,  5.199999999999999,\n",
               "        5.699999999999999,  6.199999999999999,  6.699999999999999,\n",
@@ -3395,17 +3396,17 @@
               "                     11.7,               12.2,               12.7,\n",
               "                     13.2,               13.7,               14.2,\n",
               "                     14.7],\n",
-              "      dtype=&#x27;float64&#x27;, name=&#x27;range_b5&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8405663f-d2d0-4c79-b5d8-3988c9cad12a' class='xr-section-summary-in' type='checkbox'  ><label for='section-8405663f-d2d0-4c79-b5d8-3988c9cad12a' class='xr-section-summary' >Attributes: <span>(41)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>fs :</span></dt><dd>1</dd><dt><span>n_bin :</span></dt><dd>300</dd><dt><span>n_fft :</span></dt><dd>300</dd><dt><span>description :</span></dt><dd>Binned averages calculated from ensembles of size &quot;n_bin&quot;</dd><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>principal</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd><dt><span>range_offset :</span></dt><dd>0.6</dd><dt><span>declination :</span></dt><dd>15.8</dd><dt><span>declination_in_orientmat :</span></dt><dd>1</dd><dt><span>principal_heading :</span></dt><dd>11.1898</dd></dl></div></li></ul></div></div>"
+              "      dtype=&#x27;float64&#x27;, name=&#x27;range_b5&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cea8b836-b914-44c4-b99f-da6161f6f2c3' class='xr-section-summary-in' type='checkbox'  ><label for='section-cea8b836-b914-44c4-b99f-da6161f6f2c3' class='xr-section-summary' >Attributes: <span>(41)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>fs :</span></dt><dd>1</dd><dt><span>n_bin :</span></dt><dd>300</dd><dt><span>n_fft :</span></dt><dd>300</dd><dt><span>description :</span></dt><dd>Binned averages calculated from ensembles of size &quot;n_bin&quot;</dd><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>principal</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd><dt><span>range_offset :</span></dt><dd>0.6</dd><dt><span>declination :</span></dt><dd>15.8</dd><dt><span>declination_in_orientmat :</span></dt><dd>1</dd><dt><span>principal_heading :</span></dt><dd>11.1898</dd></dl></div></li></ul></div></div>"
             ],
             "text/plain": [
               "<xarray.Dataset> Size: 379kB\n",
-              "Dimensions:         (time: 183, range: 28, dirIMU: 3, dir: 4, beam: 4,\n",
+              "Dimensions:         (time: 183, dirIMU: 3, dir: 4, range: 28, beam: 4,\n",
               "                     earth: 3, inst: 3, q: 4, time_b5: 183, range_b5: 28)\n",
               "Coordinates:\n",
               "  * time            (time) datetime64[ns] 1kB 2020-08-15T00:22:30.001030683 ....\n",
               "  * dirIMU          (dirIMU) <U10 120B 'streamwise' 'x-stream' 'vert'\n",
-              "  * range           (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
               "  * dir             (dir) <U10 160B 'streamwise' 'x-stream' 'vert1' 'vert2'\n",
+              "  * range           (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
               "  * beam            (beam) int32 16B 1 2 3 4\n",
               "  * earth           (earth) <U1 12B 'E' 'N' 'U'\n",
               "  * inst            (inst) <U1 12B 'X' 'Y' 'Z'\n",
@@ -3414,18 +3415,18 @@
               "  * range_b5        (range_b5) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
               "Data variables: (12/38)\n",
               "    c_sound         (time) float32 732B 1.502e+03 1.502e+03 ... 1.498e+03\n",
-              "    U_std           (range, time) float32 20kB 0.04232 0.04293 ... nan nan\n",
               "    temp            (time) float32 732B 14.49 14.59 14.54 ... 13.62 13.56 13.5\n",
               "    pressure        (time) float32 732B 9.712 9.699 9.685 ... 9.58 9.584 9.591\n",
               "    mag             (dirIMU, time) float32 2kB 3.534 3.565 ... -197.1 -197.1\n",
               "    accel           (dirIMU, time) float32 2kB -1.261 -1.263 ... 9.714 9.712\n",
+              "    batt            (time) float32 732B 16.48 16.48 16.48 ... 16.25 16.26 16.26\n",
               "    ...              ...\n",
-              "    boost_running   (time) float32 732B 0.1267 0.1333 0.13 ... 0.2267 0.22 0.22\n",
               "    heading         (time) float32 732B 3.287 3.261 3.337 ... 3.331 3.352 3.352\n",
               "    pitch           (time) float32 732B -0.05523 -0.07217 ... -0.04288 -0.0429\n",
               "    roll            (time) float32 732B -7.414 -7.424 -7.404 ... -6.433 -6.436\n",
               "    water_density   (time) float32 732B 1.023e+03 1.023e+03 ... 1.023e+03\n",
               "    depth           (time) float32 732B 10.28 10.26 10.25 ... 10.14 10.15 10.15\n",
+              "    U_std           (range, time) float32 20kB 0.04232 0.04293 ... nan nan\n",
               "Attributes: (12/41)\n",
               "    fs:                        1\n",
               "    n_bin:                     300\n",
@@ -3442,7 +3443,7 @@
               "    principal_heading:         11.1898"
             ]
           },
-          "execution_count": 48,
+          "execution_count": 16,
           "metadata": {},
           "output_type": "execute_result"
         }
@@ -3465,7 +3466,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 49,
+      "execution_count": 17,
       "metadata": {
         "scrolled": true
       },
@@ -3493,22 +3494,22 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 50,
+      "execution_count": 18,
       "metadata": {},
       "outputs": [
         {
           "data": {
             "text/plain": [
-              "<matplotlib.colorbar.Colorbar at 0x112d84c8410>"
+              "<matplotlib.colorbar.Colorbar at 0x25a2de98c50>"
             ]
           },
-          "execution_count": 50,
+          "execution_count": 18,
           "metadata": {},
           "output_type": "execute_result"
         },
         {
           "data": {
-            "image/png": 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",
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",
             "text/plain": [
               "<Figure size 1000x600 with 2 Axes>"
             ]
@@ -3540,14 +3541,14 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 51,
+      "execution_count": 19,
       "metadata": {
         "scrolled": false
       },
       "outputs": [
         {
           "data": {
-            "image/png": 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",
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",
             "text/plain": [
               "<Figure size 1000x600 with 2 Axes>"
             ]
@@ -3585,7 +3586,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 52,
+      "execution_count": 20,
       "metadata": {},
       "outputs": [],
       "source": [
@@ -3614,22 +3615,22 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 53,
+      "execution_count": 21,
       "metadata": {},
       "outputs": [
         {
           "data": {
             "text/plain": [
-              "<matplotlib.collections.QuadMesh at 0x112d5652650>"
+              "<matplotlib.collections.QuadMesh at 0x25a3bd609d0>"
             ]
           },
-          "execution_count": 53,
+          "execution_count": 21,
           "metadata": {},
           "output_type": "execute_result"
         },
         {
           "data": {
-            "image/png": 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",
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ffoq7774bdrsds2fPDnXxiIiIAsYPZ7acVt252bdvHyZOnIhf/OIXAIDevXtj8+bN+PTTT0NcMiIiImqtWvVlqcsuuwzvvfce/v3vfwMADhw4gD179uDnP/95g2lqa2tRVlZmmIiIiFobOXITzET+teqRm4cffhilpaUYMGAAzGYznE4n/vCHP+DWW29tMM2yZcuwePHic1hKIiKipuOj4C2nVY/cbNmyBX/+85/x8ssv47PPPsNLL72EJ554Ai+99FKDabKzs1FaWqpPx44dO4clJiIiolBr1SM3Dz74IObPn49bbrkFADBkyBD85z//wbJly3DnnXf6TWO1WmG1Wn3ClUgLILSnrMxm94LaauPcGq3OhdcTWY4aj8zU3rKQYTVVxjQWm28eLqdxLgmhzqor1awjLO5lJm3zOOvVeZ1DC1fLL2S4Z+/dez16HK0fW1+rzjt0dBeh+BtjHFe9MW2kVh9nHXzIdetpveoX6bEt6mqNabTfSq/BvvkShaOKn9S597ErzxXexzzgPqbkeavez3EI6OcFA898/MXx/K0fu4pWNO08Z9KObe1c5fe9uHKZIvyvx+O8oJ+3IIxxZL6xndS553na6XVe8R6x0Nfv59/rWtsqcZ3Vn/Xa+mM6qHPPc3tMLKCcu/8t8obiltOqOzdVVVUwmYw7q9ls5qPgRETU5vGyVMtp1Z2ba6+9Fn/4wx/Qq1cvDBo0CPn5+Vi5ciV+/etfh7poREREFIB58+Y1Oc0jjzyCzp07Nzp+q+7cPPXUU3j00UcxY8YMlJSUIDExEdOmTcPvfve7UBeNiIgoKO31slROTg4yMjJgsVjOHhnAnj17MHPmzPDp3MTGxiInJwc5OTmhLgoREVGzMikKTEH0UIJJG2pbt25F9+7dGxU3Nja2yfm36s4NERFRuGqvIzcbN26E3W5vdPxnn30W8fHxTVoHOzdERER0zjT0tHNDJk+e3OR1sHNDREQUAgqCfFrK32P5BKCVv8SPiIgoXCmm4KdwdeDAAZjNft7d1Ehh3DRERETUVgnh/aLHxuNlKSIiolAI8iV+bfaOYgA33njjGZeXlpYG1Tbs3BAREYVAe31aCgDefvttjBs3rsGnoJzen9xoInZuiIiI2pG1a9fi8ccfR1FREQYNGoScnByMHj3ab9w9e/bg4YcfxpdffomqqiokJydj2rRpmDt3rh4nNzcXd999t0/a6upq2Gw2v/kOHDgQv/zlLzFlyhS/ywsKCvDXv/41gNqp2LkhIiIKAXXkJphvSzU9zZYtWzBnzhysXbsWo0aNwrPPPosJEybg8OHD6NWrl0/8mJgYzJw5ExdeeCFiYmKwZ88eTJs2DTExMbjnnnv0eHFxcfjqq68MaRvq2ABAWloaPvvsswY7N1ar1W95GoudGyIiohAIxWWplStXYsqUKZg6dSoA9VMI27dvx7p167Bs2TKf+EOHDsXQoUP1371798brr7+O3bt3Gzo3iqIgISGh0eVYv379GS89DRw4EEePHm10ft74tBQREVEbVlZWZphqa2v9xnM4HNi/fz8yMzMN4ZmZmdi7d2+j1pWfn4+9e/di7NixhvCKigokJyejZ8+euOaaa5Cfn3/GfKxWK6Kjoxu1zkC0q5EbUVUBAFDMke4w7VEzxVmvBjjr1LlZaxqHtpP46yJraYWjxhCseC0HAJi05/VlT1W4tPzVtEqkxXc99VpZ6h2GZUKWVebhcvmWrV6LE2Ex5iHrhTp3XJdWTpNct2JM44/+ggVhLIPLaayH02M9ento8zo1f1F0RFufFjfS6meFwpiH9/ZQ/LwPQWsfRctPOKqNac3uj7Yp3QIf/qRWqqpUnddpx7B+vGr7Qb37fwCKzevbNTKutj8r1igtose/B11e/+o0NeKdHN77rTwfmLR8XV7HtkdZ9J/asabI9cm4nvFkOb3XJ1wN/la8yyBp9RT6mc1jPTJ9A0MI8lxreKRXTyPXZzxnKLYYLdyjrPp5RDs3yHOgTCvTRLjP7ZDnVLluGbdzF3Uu2y8mzp2mvBSoD+5G1qZorm9LJSUlGcIXLlyIRYsW+cQ/ceIEnE6nz0288fHxKC4uPuO6evbsiR9//BH19fVYtGiRPvIDAAMGDEBubi6GDBmCsrIyrF69GqNGjcKBAwfQr18/n7zKysoQFxfnE96Q8vLyJn9fql11boiIiFqL5rosdezYMUNnwWr19w9Ez3TGlQohznrvz+7du1FRUYGPPvoI8+fPx/nnn49bb70VAJCeno709HQ97qhRo3DJJZfgqaeewpo1a3zy6tSpE4qKihr94czzzjsPBQUF6NOnT6PiA+zcEBERhYQS5HtuZNq4uLhGjYR07doVZrPZZ5SmpKTkrB+mTElJAQAMGTIEP/zwAxYtWqR3bryZTCYMHz4cR44c8btcCIHnn38eHTp0OGuZAaCuru7skbywc0NERNQOWCwWpKWlIS8vDzfccIMenpeXh4kTJzY6HyFEg/f1yOUFBQUYMmSI3+W9evXCc8891+j1JSQkIDIy8uwRPbBzQ0REFAKheFpq3rx5yMrKwrBhw5CRkYENGzagsLAQ06dPBwBkZ2fj+PHj2LRpEwDgmWeeQa9evTBgwAAA6ntvnnjiCcyaNUvPc/HixUhPT0e/fv1QVlaGNWvWoKCgAM8884zfMnz33XdNL3gTsXNDREQUAqHo3EyaNAknT57EkiVLUFRUhMGDB2Pbtm1ITk4GABQVFaGwsFCP73K5kJ2djaNHjyIiIgJ9+/bF8uXLMW3aND3O6dOncc8996C4uBh2ux1Dhw7Frl27cOmllwZeuSCxc0NERNSOzJgxAzNmzPC7LDc31/B71qxZhlEaf1atWoVVq1Y1V/GaBTs3REREIaCYFCimIG4oFm3441ItjJ0bIiKiEGjPH85saXxDMREREYUVdm6IiIhCQL6hOJiprevduzeWLFliuIm5ObBzQ0REFALyslQwU1t3//33480330SfPn0wbtw4vPLKK2d8h05jsXNDREREITFr1izs378f+/fvR2pqKu677z706NEDM2fOxGeffRZwvuzcEBERhYD8/EIwU7i46KKLsHr1ahw/fhwLFy7E888/j+HDh+Oiiy7Ciy++aPz4aiPwaSkiIqIQUBDk01LNVpLQq6urw9atW7Fx40bk5eUhPT0dU6ZMwffff48FCxbg3Xffxcsvv9zo/Ni5ISIiCoHm+nBmW/bZZ59h48aN2Lx5M8xmM7KysrBq1Sr9cw8AkJmZiTFjxjQpX3ZuiIiIKCSGDx+OcePGYd26dbj++uv9fiAzNTUVt9xyS5PybTedG1FfB6VTZ/VvR417gcuphplcAABFqHNEaZ9id/r51LridatSbbU6t1jVeYRFnddUuuNYo9R5dYU6j7Tp5QIAxaptUJfLYz1ar9xkVuPqy7Rrj7KsTqdvGS1q/qh3qPM6h7FeLs/rl9rfMnv5xkyZJsLqm7/eLlpcs9euJK+P1tf71kfWw2Qyll+2Y6TFnUbGlflp20u2ib5ez+0kl8ltK9tAtpfexO40ovhrY1kitO3hlOXX1m/2OPC8l0kyjlxfvUfZZD1kGWUcWQ8Z17M99fRaWof2JEGE7+ErSk8Y8hf78tTffbV/BRV+q86Lv3enqaoCAHyeuxsAMPi2dACA0rGjuvrDRwAANd/96FEktdwdH7lPXV3aleqC8p/UuS1GK6O7vcRPxVq+3dUA+Y/OilJ1LvdNT2atnSLV40fR9hn9uNHyF073fqbIttP3A+P+pshwS7R7PXI7aIUS2r6j/8tYbjfhsT/70OLIfUimNfzrWjHG9U6rH5eK7zKZr0srg6yHvi955CmcxjDtnKXXy3v/g+f5RSOPtaZc/PDOw6ee8D1/yjIo2naLVvcD4Xn+1PZ5Re5X2rnJXR+TV5kBJSpWjVNVZlxfpy7qXJ4jPY+j+nrjOaulBfvEU9sfuMG3336rf9eqITExMdi4cWOT8uUNxURERCHAG4qBK664AidPnvQJP336NPr06RNwvuzcEBERUUh89913cPq5+lBbW4vjx48HnG+7uSxFRETUmigm36t0TU3fVr311lv639u3b4fdbtd/O51OvPfee+jdu3fA+bNzQ0REFALt+Wmp66+/HoBahzvvvNOwLDIyEr1798aTTz4ZcP7s3BAREdE55dJuPk9JScEnn3yCrl27Nmv+7NwQERGFgklxP50aaPo27ujRoy2SLzs3REREoRDs1y/b6GWpNWvW4J577oHNZsOaNWvOGPe+++4LaB3s3BAREYVAe73nZtWqVbjttttgs9mwatWqBuMpisLODREREbV+npeiWuqyVBt+kIyIiKgNk/fcBDOFGafTiYKCApw6dSqofNi5ISIiCgV5z00wUxs3Z84cvPDCCwDUjs2YMWNwySWXICkpCR988EHA+bJzQ0RERCHxl7/8BRdddBEA4O2338Z3332HL7/8EnPmzMGCBQsCzpedGyIiohBQTErQU1t34sQJJCQkAAC2bduGX/3qV+jfvz+mTJmCQ4cOBZwvOzdEREShwMtSiI+Px+HDh+F0OvHOO+/gqquuAgBUVVXBbDYHnC+fliIiIqKQuPvuu3HzzTejR48eUBQF48aNAwB8/PHHGDBgQMD5snNDREQUAooS3KWltvqeG0+LFi3C4MGDcezYMfzqV7+C1WoFAJjNZsyfPz/gfNtV50a4nPIPd6DXziG0T6/LUFFfp/5h9mgqpxomyrVH1SzqxlCiYtXwmkotb4+rfiaTcd1RcercUWMMr61yp7FGqXOX1+fgtW9y6Glc9e7y19VqZelgTBMRafztrw1kmFC81q/lb/IYIjRp7VGnlV+vn/Baj0fZZfp6hzqXn7mPFMZyyDYHAGe9Vxm1uNo2gClaK6PHerzbR65Xrk9uS6e73fR89TaIMOYrt6XnejzTe8ZBnVc9PPYxWe4Ii3F9Pss9tpeMU6e2m6guV3O1xRjL7lEGUfaT+ruyQg3u2F0NP1mihl+Q6k7zyUcAAItFTes6oe7X5s6d1aIM6KuGf1OiJzFpJ2SlUzc1oPRHNf8qbX2yTJ77oXd7ae2i77ORWpt4bn+ZXmt3/RiWx0lER/jw2gdlGkW2o1ltW1Ff6xFJq4/XcSq0fUmJtGrhHhnLssj9S65X7t9yf4jwPHd47et6uDw3+Vmu75tOw3r1esn92XBMa/uBFub7P0GZp0eFZHrv84G+XPEpm749ZJjLuI2Fy+RbH2/yHGhVj2W5XwsZDgDy8oTXecCnXp77mCxbZZk6j9b2Jbm9tOMJHdxfoz7nj1e30zcUe7vpppt8wrw/ptlU7apzQ0RERK3Le++9h/feew8lJSX6BzWlF198MaA82bkhIiIKBROC/HBms5UkZBYvXowlS5Zg2LBh+n03zSEMmoaIiKjtkd+WCmYKxNq1a5GSkgKbzYa0tDTs3r27wbh79uzBqFGj0KVLF0RFRWHAgAF+vwf12muvITU1FVarFampqdi6dWujyrJ+/Xrk5ubi448/xhtvvIGtW7capkCxc0NERBQKIfj8wpYtW/QX5OXn52P06NGYMGECCgsL/caPiYnBzJkzsWvXLvzrX//CI488gkceeQQbNmzQ4+zbtw+TJk1CVlYWDhw4gKysLNx88834+OOPz1oeh8OBkSNHNrkeZ8PODRERUTuxcuVKTJkyBVOnTsXAgQORk5ODpKQkrFu3zm/8oUOH4tZbb8WgQYPQu3dv3H777Rg/frxhtCcnJwfjxo1DdnY2BgwYgOzsbFx55ZXIyck5a3mmTp2Kl19+ubmqp+M9N0RERKHQTE9LlZWVGYKtVqv+SLUnh8OB/fv3+zxinZmZib179zZqlfn5+di7dy8ee+wxPWzfvn2YO3euId748eMb1bmpqanBhg0b8O677+LCCy9EZKTxyd6VK1c2qlze2LkhIiIKAcVkfGNIIOkBICkpyRC+cOFCLFq0yCf+iRMn4HQ6ER8fbwiPj49HcXHxGdfVs2dP/Pjjj6ivr8eiRYswdepUfVlxcXFAeQLAwYMHcfHFFwMAPv/8c8OyYG4uZueGiIioDTt27Bji4uL03/5GbTx5dxqEEGftSOzevRsVFRX46KOPMH/+fJx//vm49dZbg8oTAN5///2zxgkEOzdERESh0EyXpeLi4gydm4Z07doVZrPZZ0SlpKTEZ+TFW0pKCgBgyJAh+OGHH7Bo0SK9c5OQkBBQnp6+/vprfPPNNxgzZgyioqIa3TlqCG8oJiIiCoFz/VVwi8WCtLQ05OXlGcLz8vKa9MSSEAK1te43fGdkZPjkuWPHjkblefLkSVx55ZXo378/fv7zn6OoqAiAeqPx/fff3+gyeWPnhoiIqJ2YN28enn/+ebz44ov417/+hblz56KwsBDTp08HAGRnZ+OOO+7Q4z/zzDN4++23ceTIERw5cgQbN27EE088gdtvv12PM3v2bOzYsQMrVqzAl19+iRUrVuDdd9/FnDlzzlqeuXPnIjIyEoWFhYiOjtbDJ02ahHfeeSfgerb6y1LHjx/Hww8/jL///e+orq5G//798cILLyAtLS3URSMiIgpcCL4tNWnSJJw8eRJLlixBUVERBg8ejG3btiE5ORkAUFRUZHjnjcvlQnZ2No4ePYqIiAj07dsXy5cvx7Rp0/Q4I0eOxCuvvIJHHnkEjz76KPr27YstW7ZgxIgRZy3Pjh07sH37dvTs2dMQ3q9fP/znP/9pcv2kVt25OXXqFEaNGoUrrrgCf//739G9e3d888036NixY6iLRkREFJxgP9QZYNoZM2ZgxowZfpfl5uYafs+aNQuzZs06a5433XST3w9gnk1lZaVhxEY6ceLEWW+MPpNW3blZsWIFkpKSsHHjRj2sd+/eZ0xTW1truBbo/fw/ERERtQ5jxozBpk2b8Pvf/x6A+tSVy+XC448/jiuuuCLgfFv1PTdvvfUWhg0bhl/96lfo3r07hg4diueee+6MaZYtWwa73a5P3s//ExERtQah+rZUa/L444/j2WefxYQJE+BwOPDQQw9h8ODB2LVrF1asWBFwvgF3bnbv3o3bb78dGRkZOH78OADgT3/6E/bs2RNwYbx9++23WLduHfr164ft27dj+vTpuO+++7Bp06YG02RnZ6O0tFSfjh071mzlISIiajYh+LZUa5OamoqDBw/i0ksvxbhx41BZWYkbb7wR+fn56Nu3b8D5BnRZ6rXXXkNWVhZuu+025Ofn65eBysvLsXTpUmzbti3gAnlyuVwYNmwYli5dCkD9xsUXX3yBdevWGe7m9tTQa6chBFBfp/5tMuvBSoT6qmfhqFEDtN9wqHVSLDZ1ubPencaspZe95kibllZrTvnayDqHO020+g4CIZe5XMY8hPApmx4mueqNv2V9HO7LcPq6hcuYn0dZfMiy1Gn5RMUY1y/LKON55utZXs/1miONaQHAWWeMK3/XVmtpZF4eaWR62f7e21DWS3iUzWx8fbe+TNZH5mV4Nai2rN7hVRa52CutIa62PuGUBVBnLqfvevT61BnLb1WvOYuaKjWa3KcAd129X5Il09ZUeuTvtf3lPinL0rGLOvfYZ5QOHQAAPRLU7W6K9br+rb0OvbrGXff6OjV/e6R6rAltG4ryk4b6KdYo93pi7MayKWZDWeTeLo9JQ7n1fUeLVau2E7TjytAGMkzuR1oewqS2jaLvK+72VBraj+X21vZ9UVfjm0Y/PmRSud3VAMXp539AsrLafiVcxvUYjythXKYY6yV/i3qP8422XWS76WcSWQ/52+lxXjBbjGFOY/4eqTwoxvK6vI41/XzndCeR21KGyX3REmXMS54XPOPK/Uxuf62einfbeOajncPh0soU10lbr7otlQ52PYmornC3wzkR5A3FaPudm8LCQiQlJWHx4sV+l/Xq1SugfAMauXnsscewfv16PPfcc4bvQIwcORKfffZZQAXxp0ePHkhNTTWEDRw4sMGvlxIREVHbkZKSgh9//NEn/OTJk/qLAwMR0MjNV199hTFjxviEx8XF4fTp0wEXxtuoUaPw1VdfGcL+/e9/64+sERERtVXB3jcTDvfcNPQm4oqKCthsNj8pGiegzk2PHj3w9ddf+zy5tGfPHvTp0yfgwnibO3cuRo4ciaVLl+Lmm2/GP//5T2zYsAEbNmxotnUQERGFRIgeBW8N5s2bB0DtoD366KOGx8GdTic+/vhj/YOagQioczNt2jTMnj0bL774IhRFwffff499+/bhgQcewO9+97uAC+Nt+PDh2Lp1K7Kzs7FkyRKkpKQgJycHt912W7Otg4iIiM6t/Px8AOrIzaFDh2CxuO91slgsuOiii/DAAw8EnH9AnZuHHnoIpaWluOKKK1BTU4MxY8bAarXigQcewMyZMwMujD/XXHMNrrnmmmbNk4iIKNTa82Up+TXwu+++G6tXr27Uhz+bIuCX+P3hD3/AggULcPjwYbhcLqSmpqKD9tQFERERnUU7viwleb6ktzkF9Ybi6OhoDBs2rLnKQkRERO1IZWUlli9fjvfeew8lJSVweb5yBOr77gIRUOfmhhtu8DscpigKbDYbzj//fEyePBkXXHBBQIUiIiIKeyH4cGZrM3XqVOzcuRNZWVno0aNHs11qC6hzY7fb8cYbb6Bjx45IS0uDEAL5+fk4ffo0MjMzsWXLFqxYsQLvvfceRo0a1SwFJSIiCieKSYESxKWlYNK2Fn//+9/xt7/9rdn7CgF1bhISEjB58mQ8/fTTMGlv/XS5XJg9ezZiY2PxyiuvYPr06Xj44Yeb9XMMREREFD46deqEzp07N3u+Ab2h+IUXXsCcOXP0jg0AmEwmzJo1Cxs2bICiKJg5cyY+//zzZisoERFRWJGXpYKZ2rjf//73+N3vfoeqqqpmzTegkZv6+np8+eWX6N+/vyH8yy+/hFP7HonNZmvTj6kRERG1KBOCfFqq2UoSMk8++SS++eYbxMfHo3fv3oZPOgEI+JNOAXVusrKyMGXKFPz2t7/F8OHDoSgK/vnPf2Lp0qX6By137tyJQYMGBVQoIiKicNee33MjXX/99S2Sb0Cdm1WrViE+Ph5//OMf8cMPPwAA4uPjMXfuXDz88MMAgMzMTFx99dXNV1IiIiIKKwsXLmyRfAPq3JjNZixYsAALFixAWVkZAPi8XTDQz5QTERG1C3yJX4sJ6iV+gG+nhoiIiBqhHb/nplOnTo26rPbTTz8FlH9AnZsffvgBDzzwgP5GQSGEYbm8qbhVES7AWQcAUKLcn4kQtdVqmEX7tLrW2KJWvXNbsapfKlVMZneaejUfyDRm7QYoR63xd53DvX6b9sXTE1pYlLa6qFj1D5fTXU7JMz0AyHZ21RvTmN1lUyItxriKdsdZhLxJS9uZhOc20sIirVq+wqss8q41j+0sFGMc4ZVGltGj3fTyyjA5l2nlfqPUoUF6Ownjb2uUO069th1M2u4tt5d8us+plU3xrI/LGFfmp7ej1/o9yyvJA1Xbz9z18TiAZX5yO8ntoreby/gbAOrV/UDUVBrXp4Xrc8C978lyduuhpq1UR1hhizKuHwCi1DBzVKSx3F27q/Nqdb3R0e7TRUSslo/WTqL0hPq7pEid94pRwytOw5tii9HqKLe71l5KlE89Fe99pbpCjaMdG+6WdW9LoW1/Pa1sS6c2j9SO27paj9TCmEa2n9we+jZ175vCa59XIryOPe0YEJ5vXPUqk2KOMJZF/nZ6bFOv86u+fbSo+qFc71E27/3AO608FjzS6MeLd53lOQRa2R017jSyzt71kGlkHtp5Vo2rlU2ea7V9U+nQ0VjWWvfTM/p5ulO8sV5yfXKfsVjd6eV2l22unxu18CptX/I8rlwud/2pReXk5LRo/gF1bu666y4UFhbi0UcfbdY3ChIREbUb7Xjk5s4772zR/APq3OzZswe7d+/GxRdf3MzFISIiai+CfVdN2+3ctLSAnpJPSkryuRRFRERE1BoE1LnJycnB/Pnz8d133zVzcYiIiNoJkyn4ifwK6LLUpEmTUFVVhb59+yI6OtrnjYKB3t1MRETUbrTje25aWkCdm5a+y5mIiIjaD4fDgaNHj6Jv376IiAj6LTWBdW5a+i5nIiKisMeRG1RVVWHWrFl46aWXAAD//ve/0adPH9x3331ITEzE/PnzA8o36At21dXVKCsrM0xERER0FvwqOLKzs3HgwAF88MEHsNlsevhVV12FLVu2BJxvQCM3lZWVePjhh/Hqq6/i5MmTPstb5Uv8iIiIWpNgbwoOgxuK33jjDWzZsgXp6emGd+alpqbim2++CTjfgFrmoYcewj/+8Q+sXbsWVqsVzz//PBYvXozExERs2rQp4MIQERFR+/Hjjz+ie/fuPuGVlZVBvSA4oM7N22+/jbVr1+Kmm25CREQERo8ejUceeQRLly7F//7v/wZcGCIionYjRJel1q5di5SUFNhsNqSlpWH37t0Nxn399dcxbtw4dOvWDXFxccjIyMD27dsNcXJzc6Eois9UU1PTQK5uw4cPx9/+9jePJlHr9NxzzyEjIyOg+gEBXpb66aefkJKSAkD9cKZ89Puyyy7D//zP/wRcGCIionYjBDcUb9myBXPmzMHatWsxatQoPPvss5gwYQIOHz6MXr16+cTftWsXxo0bh6VLl6Jjx47YuHEjrr32Wnz88ccYOnSoHi8uLg5fffWVIa3nPTQNWbZsGa6++mocPnwY9fX1WL16Nb744gvs27cPO3fubHL9pIBGbvr06aO/wC81NRWvvvoqAHVEp2PHjgEXhoiIiJrG+6Ge2traBuOuXLkSU6ZMwdSpUzFw4EDk5OQgKSkJ69at8xs/JycHDz30EIYPH45+/fph6dKl6NevH95++21DPEVRkJCQYJgaY+TIkfjwww/1d+ft2LED8fHx2LdvH9LS0hrfCF4C6tzcfffdOHDgAAD1Tmd5783cuXPx4IMPBlwYIiKidqOZLkslJSXBbrfr07Jly/yuzuFwYP/+/cjMzDSEZ2ZmYu/evY0qssvlQnl5OTp37mwIr6ioQHJyMnr27IlrrrkG+fn5jW6GIUOG4KWXXsLnn3+Ow4cP489//jOGDBnS6PT+NPmyVF1dHd566y08++yzAIArrrgCX375JT799FP07dsXF110UVAFIiIiahea6WmpY8eOIS4uTg+2Wq1+o584cQJOpxPx8fGG8Pj4eBQXFzdqlU8++SQqKytx880362EDBgxAbm4uhgwZgrKyMqxevRqjRo3CgQMH0K9fvzPmt23bNpjNZowfP94Qvn37drhcLkyYMKFR5fLW5M5NZGQkPv/8c8NdzL169fJ7ra41UWwdgErtsxAxHd0LaioBACLSov6WHwS1qNcKhbYcwuVOI+Mo2k5ZW22Iq1i0HcvkcT3UWa/GqVeHC5XqCjU8KkadyzcyanmpZdA+a2HW5rLN5e/6CkNZDWQcV71X+YWhPIa4+kHmVb/6Oi2e2Z1GaGWpc2hptWXCK/8Ij09zyFcERFiN+ct8zVobyLYBgKhYmdi4HsXrhOBZH1kms5ZG37Zeyz3bTdbRpaVxaZHrtbgRFp/1CG2Zomj10euu5iXO8EoERdZZrlceiXL9Hm0g5DprqrS4XoetZ1vUanG0dlL6DFDzcKg39inWaPV3+Sl3mi7dAADlJ9W00dqlZXH4czVNrLoNykod7iRd1DAlqoMxv8py9Xel+r4rJdKjjeW+3am7se5a2dChoxbusS299idx+kdD1YXcr10ebe3QhuTlfqYv89qmLs/1mDxjAC4tX31b1hvKYYgjjxtThDHfOlkOj2NAGI8TvfyyLeQx7vI433jT89fiyP0bHh8zrqv2qofWBnIbyHOU3KcAINJqTOPwurQhz4mV7neZKTbt/CXPY7I+cpvKenrsb4qMo+23okJdpnTrqZVVa3PP9ZedVsPKtFePyG2o7V+i/Lj6u7PHpRCXV/to69X32Wqt7p5t0Ea/1xQXF2fo3JyN91NIQohGPZm0efNmLFq0CG+++abhCaf09HSkp6frv0eNGoVLLrkETz31FNasWXPGPOfPn4/ly5f7hAshMH/+/IA7NwFtxTvuuAMvvPBCQCskIiIinPOnpbp27Qqz2ewzSlNSUuIzmuNty5YtmDJlCl599VVcddVVZ4xrMpkwfPhwHDly5KxlOnLkCFJTU33CBwwYgK+//vqs6RsS0NNSDocDzz//PPLy8jBs2DDExMQYlq9cuTLgAhEREbULCoJ8Wqpp0S0WC9LS0pCXl4cbbrhBD8/Ly8PEiRMbTLd582b8+te/xubNm/GLX/zirOsRQqCgoKBR983Y7XZ8++236N27tyH866+/9ulbNEVAnZvPP/8cl1xyCQD1OxCegnnpDhEREbWcefPmISsrC8OGDUNGRgY2bNiAwsJCTJ8+HYD6kNDx48f1F/Ju3rwZd9xxB1avXo309HR91CcqKgp2ux0AsHjxYqSnp6Nfv34oKyvDmjVrUFBQgGeeeeas5bnuuuswZ84cbN26FX379gWgdmzuv/9+XHfddQHXM6DOzfvvvx/wComIiAghec/NpEmTcPLkSSxZsgRFRUUYPHgwtm3bhuTkZABAUVERCgsL9fjPPvss6uvrce+99+Lee+/Vw++8807k5uYCAE6fPo177rkHxcXFsNvtGDp0KHbt2oVLL730rOV5/PHHcfXVV2PAgAHo2VO97+q///0vRo8ejSeeeKLJ9ZOC/644ERERNZliMkEJ4gbmQNPOmDEDM2bM8LtMdlikDz744Kz5rVq1CqtWrQqoLHa7HXv37kVeXh4OHDiAqKgoXHjhhRgzZkxA+Uns3BAREYVEsF/2Do/bQBRFQWZmps/7d4LBzg0RERGFzHvvvYf33nsPJSUlcHm9BuHFF18MKE92boiIiEIhBPfctDaLFy/GkiVLMGzYMPTo0aPZHkpi54aIiCgU2LnB+vXrkZubi6ysrGbNt+29ipGIiIjCgsPhwMiRI5s9X3ZuiIiIQkF+7iGYqY2bOnUqXn755WbPl5eliIiIQoGXpVBTU4MNGzbg3XffxYUXXojIyEjD8kC/eMDODREREYXEwYMHcfHFFwNQv37gKZibi9m5ISIiCgWO3LTYFw/a/gU7IiKitugcfxW8Nfv666+xfft2VFdXA1A/vhkMdm6IiIgoJE6ePIkrr7wS/fv3x89//nMUFRUBUG80vv/++wPOt31dljJp1TWb3WGK1r+rrTZEVaI6AAD0vmN1pXthhJaPScvHYlXTuOq1tLFqWpdHz9NRo87LT2vLnGrcbucZyxHh9CiE1iuPkDdYefXSnXXqXFjcYWbjzVioc2hltBnDzR6bXt5xL+dOrQyyfpGKMS9/69Hqg3qtTLI+nm2g18OrRy7T+ONsYJnchrJMwv1WS1FXqxZBtl91hbZ+izFPz3bTyi+0/UCJjtPiyrbQlnvuBzIf2U7aXMgyebcJAFijjOuRZZL7hyxHjcd6ZL5amBLbyZBGyLSeaqrUudxOVVobaPsmyk55xFXLUlqmljt23xcAgOhLzlfzr1f365gY9za3dI8zrM7UPUktfslxNaCiVJ3HddHjiKoytfzyDaRONV/5LzSlXCuTML6hFACE1zL5W5F19/xXnnYcinqv7SDXJ88Dhv3Z65iWaWUcc60xL3UFhrTymIa2/8GhzRWPf0N6/2NUtoWss5/9WV+nti1FVbmWrdzv7FoaP+cbk/E40fchbd8VHm2gaO2Deq3cMo7cPvKY09bvd5m2Xwttn1e0Y15Uu9PIY0Avm9wX62oMafVtAADVVVrdtX1I7teKw1gOz2NBHv9yO0Rqx1qMtu/+WKSt12M9Tqf7mD8Xgn3iKQyelpo7dy4iIyNRWFiIgQMH6uGTJk3C3Llz8eSTTwaUb/vq3BAREbUWvOcGO3bswPbt2/Uvgkv9+vXDf/7zn4DzZeeGiIgoFNi5QWVlJaKjo33CT5w4AavVGnC+bX9Mi4iIiNqkMWPGYNOmTfpvRVHgcrnw+OOP44orrgg4X47cEBERhQLvucHjjz+Oyy+/HJ9++ikcDgceeughfPHFF/jpp5/w4YcfBpxv228ZIiKitkhBkI+Ch7oCwUtNTcXBgwdx6aWXYty4caisrMSNN96I/Px89O3bN+B8OXJDREREIZOQkIDFixc3a57s3BAREYVCO72h+ODBg42Oe+GFFwa0DnZuiIiIQqGddm4uvvhiKIpy1rcQK4oCZ4DvHWLnhoiIiM6Zo0ePtvg62LkhIiIKBSXIp6WUtvlMUHJycouvg50bIiKiUGinl6U8eb7jxp877rgjoHzbVOdm2bJl+O1vf4vZs2cjJycn1MUhIiKiIMyePdvwu66uDlVVVbBYLIiOjg7/zs0nn3yCDRs2BHznNBERUavCkRucOnXKJ+zIkSP4n//5Hzz44IMB59smLthVVFTgtttuw3PPPYdOnTqdMW5tbS3KysoMExERUaujmIKfwlC/fv2wfPlyn1GdpmgTLXPvvffiF7/4Ba666qqzxl22bBnsdrs+JSUlnYMSEhERNZFJCX4KU2azGd9//33A6Vv9ZalXXnkFn332GT755JNGxc/Ozsa8efP032VlZezgEBERtUJvvfWW4bcQAkVFRXj66acxatSogPNt1Z2bY8eOYfbs2dixYwdsNluj0lit1oY/kx5pUed1DneY2azOnXUAAFFbrf2uN6aV8fyF1WkvGerQUZ3L66AR7uYVNZXqHw5t3Wav9dhi1Hm9R9lMXptH5ltfq86tUdp6LO44wmWMG+mxDHAPYxrG7LS48n1K+nVcuT6Hb16y7pYGtotc7vJoR6/rw8JRo5XFpC02GctoKKJiSKNERBp/x8S541ZXaCtQKyTq6zxrA5jkdvNoay0/PUy2oyS3n+f28Yoj5DJtX9Lr4e9FVXK7m9VtLPc7UXZSq09Hd1xXrTGtbDctX8Vju+htqr34SpT9pP62WI1ls3d251euXrqNjFTLW/TdaQBAovlbAEDU0PMBANFJ7kvCzmq1rhGuBl6wVauWWVR5XBaWZZPtVGdsL1Gj5aVtLwBQ7F3VP7RtKsq16/OlPxnz8ti3REWpGhSh1dmlbSe5vWQ55DYFgOhYLY62z1SWGfJXtP1ZVHukkfutPO6dsj7qttX3TXiQx4s8LuQ+4tUWnseVXhZ9H9Xatl7NQ4nqYKwX3O2uRGn1kttJaxshzx2eZBxHraH80NYj6y6qy/Uksm5Ctq3c17VtKLzPowAgt6E8R5wsUeNq+747Xqn7b7m9O3VR4zZQduGxPyqRWhtGdzCUSW9z2daRHdz51Ff6HvstKdhLS2FwWer66683/FYUBd26dcPPfvYzPPnkkwHn26o7N/v370dJSQnS0tL0MKfTiV27duHpp59GbW0tzP46HURERK0dbyiGy9UynclW3e278sorcejQIRQUFOjTsGHDcNttt6GgoIAdGyIioiZau3YtUlJSYLPZkJaWht27dzcY9/XXX8e4cePQrVs3xMXFISMjA9u3b/eJ99prryE1NRVWqxWpqanYunVrk8slhDjrJxkaq1V3bmJjYzF48GDDFBMTgy5dumDw4MGhLh4REVHgTKbgpybasmUL5syZgwULFiA/Px+jR4/GhAkTUFhY6Df+rl27MG7cOGzbtg379+/HFVdcgWuvvRb5+fl6nH379mHSpEnIysrCgQMHkJWVhZtvvhkff/xxo8r0wgsvYPDgwbDZbLDZbBg8eDCef/75JtfNU6u+LEVERBS2QnBZauXKlZgyZQqmTp0KAMjJycH27duxbt06LFu2zCe+9wtzly5dijfffBNvv/02hg4dqscZN24csrOzAagP9uzcuRM5OTnYvHnzGcvz6KOPYtWqVZg1axYyMjIAqJ2luXPn4rvvvsNjjz3W5DoCbbBz88EHH4S6CERERK2G9/vcGnqwxuFwYP/+/Zg/f74hPDMzE3v37m3UulwuF8rLy9G5s/uhBNkZ8TR+/PhGfUlg3bp1eO6553DrrbfqYddddx0uvPBCzJo1K+DOTau+LEVERBS2muklfklJSYb3u/kbgQGAEydOwOl0Ij4+3hAeHx+P4uLiRhX5ySefRGVlJW6++WY9rLi4OOA8nU4nhg0b5hOelpaG+no/T9s1UpsbuSEiIgoLCoK8LKXOjh07hrg49+swGnwdikzm/VoOIXzC/Nm8eTMWLVqEN998E927d2+WPG+//XasW7cOK1euNIRv2LABt91221nTN4SdGyIiojYsLi7O0LlpSNeuXWE2m31GVEpKSnxGXrxt2bIFU6ZMwf/93//5fC0gISGhSXl6vmhXURQ8//zz2LFjB9LT0wEAH330EY4dOxbwRzMBdm6IiIhCI8Anngzpm8BisSAtLQ15eXm44YYb9PC8vDxMnDixwXSbN2/Gr3/9a2zevBm/+MUvfJZnZGQgLy/PcN/Njh07MHLkSL/5eT5pBUB/l90333wDAOjWrRu6deuGL774ovGV88LODRERUSiE4GmpefPmISsrC8OGDUNGRgY2bNiAwsJCTJ8+HYD6pNPx48exadMmAGrH5o477sDq1auRnp6uj9BERUXBbrcDAGbPno0xY8ZgxYoVmDhxIt588028++672LNnj98yvP/++4HUtkl4QzEREVEohOCr4JMmTUJOTg6WLFmCiy++GLt27cK2bduQnJwMACgqKjK88+bZZ59FfX097r33XvTo0UOfPL/YPXLkSLzyyivYuHEjLrzwQuTm5mLLli0YMWLEGctSX1+PiIgIfP75502ux9lw5IaIiKgdmTFjBmbMmOF3WW5uruF3Y1+/ctNNN+Gmm25qUjkiIiKQnJwMp7OBb9QFgSM3REREoaAogCmIKQy+LfXII48gOzsbP/30U7Pmy5EbIiKiUOBXwbFmzRp8/fXXSExMRHJyMmJiYgzLP/vss4DyZeeGiIiIQuL6669vkXzZuSEiIgqFEDwt1dosXLiwRfJtN50b4awDzGb170r3dziUDuqjbK7yU+pvi82QTonqoKZx1Hhkpn2Svb7OuBKT2bg80uMtkXW1xrhVFWrUn35Q19M9SQ03e2ySCO1vuQMLlzGPSGNZtchaWbThSmE2hsu8FLM7ictpLL9cjayHvNkr0s9bL2V+Tu012XKY1GT2jSvjyGVOtf2USOMwpN+03uT2qHMY52fKxxwJABA1ldp6LR7LzMZ8Hdr20tpGeG9rAKitVpdp+er09tLyjPDYprKt5dym1V1u25oqdR7t8UIuWaZqbZ/R2k2vn8fQtKKFCVk3bT/T6yfrIcM96mGzquX8w8HvAQAresQY0kYmdNKTVH+lxrFobYkIbX2duqnzY99qESvd65GvUtfaVpSeUH+75H7mcYxp5LbSyy3zqK4ylN1w3Mj2qjytzuUxLfOQm8vzeJL7JmqM+dar+5WQ+dd77GeyzpWlxt/1xn3R89yhaOsUWv6Ktv1lHCUi0lgHj79leyly35Dr0fYHUeZxz4Jcj+u0+ltrL+GoMqTxpLjUF66J6nItwGRYj6jV0jrc5zIh42jLFGu0lqbOkFbWEwBElXr+Vcwxxvzk8STrXnbaXbiT2r7Ss7chrr7vdIhV84xwH9NC2/6KSTtHyXO5bKdSLf/oDu711NYCtX7OJS2Fl6VaTLvp3BAREVHrYjKZzviZhkCfpGLnhoiIKBTkU0/BpG/jtm7davhdV1eH/Px8vPTSS1i8eHHA+bJzQ0REFAq858bvZx9uuukmDBo0SP+eVSB4wY6IiIhalREjRuDdd98NOD1HboiIiEKBNxT7VV1djaeeego9e/YMOA92boiIiEKhHd9z8+tf/xo5OTlITk423FAshEB5eTmio6Px5z//OeD82bkhIiIKBUUJcuSm7XZuXnrpJSxfvhyrVq0ydG5MJhO6deuGESNGoFOnTmfI4czYuSEiIqJzSmjvUbvrrrtaJH92boiIiEKhnT8tdab32wSLnRsiIqJQaOc3FPfv3/+sHZxAvxbOzg0RERGdc4sXL4bdbm+RvNm5ISIiCoV2/LQUANxyyy3o3r17i+TNzg0REVEotOPLUi15vw3ANxQTERHROSaflmopHLkhIiIKhXb8tJTL5WrR/Nm5ISIiCgWTSZ2CSU9+tZ/OTXUl0Lmz+rfHdUpRekILMqsB9XXqvLZKXS5/y+UAUFWmLnPUqGmt0Wq4y2lMU1fjTuPShuBitTvDZY9baL3X6gp13qGjO43ccWV5TdrmctZ5LffovcvesAyTcbzDPdPoB4hcpsWVo4a2GC2en38leF/z9f6XhLPe/XedQ52btXpo7YVIizqvrfbNU7aPbH9tKFNvY2253BbqOp3GMsjhT6dxW3oOi8rrv0KWQebnvQ0885ZhsoyyPjJfR62x7ADgqDKWTaaprpIFgTchyy3bz6btbzW+aYR3mWQ9Oti1YK829/i7rl5Nk2xTt09Zqbq+mBptP+/SRU9isv6olV+rq2y38lPG/G1R7vVocURNpTqXcWX7VJT7pBEnvjfGkfXRtoOo1tJ47jPaPqfvI/q21PKQ7eh5fGrbTIm0amU7qf6W+77clvUOdxotHyHrqmhtEKH9ltugstS9mg7aG1e1uuvbQ+5/2rnFk5DnhsoyQ1xERGpl1fKqOOVOpNVVMUcal8n91xrlUx99PXI71XnUFQAqtHp4trUsk5afqNeOd1kvWY7oDu40si0t2n4cpc21suLUMWM9AYjTp9WgUq0esmw1Wptr20B4blNZFllXuY/qx5EWbrG505irADM7DOGg/XRuiIiIWpUgL0uh7V6Wamns3BAREYVCO35aqqWxc0NERBQK7fiG4pbGbh8RERGFFY7cEBERhQKflmox7NwQERGFAi9LtRh2+4iIiCiscOSGiIgoFBQlyKelOHLTEI7cEBERhYK8LBXMFIC1a9ciJSUFNpsNaWlp2L17d4Nxi4qKMHnyZFxwwQUwmUyYM2eOT5zc3FwoiuIz1dTU+GZ4jrBzQ0RE1E5s2bIFc+bMwYIFC5Cfn4/Ro0djwoQJKCws9Bu/trYW3bp1w4IFC3DRRRc1mG9cXByKiooMk81mazB+S2PnhoiIKBTkS/yCmZpo5cqVmDJlCqZOnYqBAwciJycHSUlJWLdund/4vXv3xurVq3HHHXfAbrc3XBVFQUJCgmEKJXZuiIiIQsGkBD8BKCsrM0y1tbV+V+dwOLB//35kZmYawjMzM7F3796gqlJRUYHk5GT07NkT11xzDfLz84PKL1js3BAREbVhSUlJsNvt+rRs2TK/8U6cOAGn04n4+HhDeHx8PIqLiwNe/4ABA5Cbm4u33noLmzdvhs1mw6hRo3DkyJGA8wwWn5YiIiIKhWb6ttSxY8cQFxenB1ut1jMn87oRWQjhE9YU6enpSE9P13+PGjUKl1xyCZ566imsWbMm4HyDwc4NERFRKDTTS/zi4uIMnZuGdO3aFWaz2WeUpqSkxGc0JxgmkwnDhw/nyM25IKrLAXN39UdlmXtBpEWdm8zq3Gz2SuhS5y6nO8waBcDjY/MWrZdcW63lEWH8DQAR6nqUqA5qtvUOdV6llaW+Xl1u7+an8GoZlIhI9aezzrjccHBo5dX/NaD9lvWTcyHcSeq1/LT89bQmLa1Tq7vL418YsgyyfbzVObQ83buY0NpQL61LGJIIWQ6zx27p1NrFFmPMXws/4796PLcZ1H+dGNR7tKNsf7ktte0Di00W3jgHIBzqY46KLK9sPy1cVFdoeXj8K+r0STVNF/VmO1FRqpW13lAOPS3gbssabX/S9iFUV8KHvbM6P1mizmO0E57cXrJeDo9r8lq+XbpHqz+/VtupqKQKAJDYpYtWJvf+bIrRjht5vNRr7VKplamrdqw5PbaBrIc8Lsq1ust9pOy08TcAVHm1oWzj3v28lrufyhA1ahnkv0SFtj4ltpNWVq0tPPYdPW5lqbGs2nGr76sm97EmKtRjV5FtbI401k871oTMC4CiLZPr0XPTzin6+cDkcR6S6U+fUuPINvA+z3iebyrVdhFxHbVlNca85DnjxA/uNN3OU9OcLPYtAwBUlKvzmA7uMLkPymPLJc83JmO9ajz2Va3dhIzr0Mrk9DoPff9fd5o6uSzCkAfKtO3VSd1HUfqTO42878Su7sei8rT6WzvGEK3Vw/P/B04n4GzgnNYSzvFXwS0WC9LS0pCXl4cbbrhBD8/Ly8PEiRMDL4cXIQQKCgowZMiQZsuzqdpN54aIiKi9mzdvHrKysjBs2DBkZGRgw4YNKCwsxPTp0wEA2dnZOH78ODZt2qSnKSgoAKDeNPzjjz+ioKAAFosFqampAIDFixcjPT0d/fr1Q1lZGdasWYOCggI888wz57x+Ejs3REREISBfdhdM+qaaNGkSTp48iSVLlqCoqAiDBw/Gtm3bkJycDEB9aZ/3O2+GDh2q/71//368/PLLSE5OxnfffQcAOH36NO655x4UFxfDbrdj6NCh2LVrFy699NKA6xYsdm6IiIhC4RxflpJmzJiBGTNm+F2Wm5vrE+ZzSd/LqlWrsGrVqoDK0lL4KDgRERGFFY7cEBERhUKIRm7aA3ZuiIiIQkFRDE/gBZSe/GK3j4iIiMIKR26IiIhCgZelWgw7N0RERKHQTG8oJl/s9hEREVFY4cgNERFRKChKkJelOHLTkFY9crNs2TIMHz4csbGx6N69O66//np89dVXoS4WERFR8ORlqWAm8qtVd2527tyJe++9Fx999BHy8vJQX1+PzMxMVFb6+WAgERFRWyJvKA5mIr9a9WWpd955x/B748aN6N69O/bv348xY8aEqFRERETUmrXqzo230lL18/adO3duME5tbS1q5afuAZSVlTUYl4iIKGRMQb7EL5i0Ya7NjGkJITBv3jxcdtllGDx4cIPxli1bBrvdrk9JSUnnsJRERESNxMtSLabNjNzMnDkTBw8exJ49e84YLzs7G/PmzdN/l5WVqR2cOgdQdlINjOrgTlBfb8ygzgEAUGI7AQCEo0YNt0a741SVq8tq1Ht/lEiblledMS+n0/23SfvbGqWmMZvVPLT1CUeVGi7caZQIq/qHOVILULRwi5rG5ZG/D8VvWsivu3p2+CO0OCazVg8tX5O2e1Rr9zhFWjzqo8WtdWjr0X47643LPdtAto/DPbIGAKJGrTu0+igWm3tZXa2h3HKZqK0yrtezLeS/ZmQZNIpZrY9wVGhp3bu/np8tRgtwaWWtMeThWXZFtq1ctznKf1rPdtPaQFRXGOsj85V5VXqMOMo2ralW51payHvPOnZyxz0l93Ftf43Q6ij387JTWlk92qa6ylDFRIu6TD9tyraPjdXjmKyRxvpUyHy1VD8WG8vhsR5ResJY19JyrT5ana1WdxpZbu/9VzuOBLQ2rq12p/npB3VZ53hDXUW5WkZF28ai8pQ7jdxmMh9tewi5/mj1nKFo6zWUX+7jcv+W5wqn9ls7xgFAnPxe/eP0T+pvLa0iyyr3A88bRWX+Vdp2P61t005d1HmlVmbP/d3pdayd1vYL/Xygbacad7vJ9tHrcbpEncv9q1LbTp7bVLZPZYWxjHEd1bnLZUwL+OxvelvLtv/pR3Ue4T4+XeVqGrNc32mtrHJfkfu9Z94/qfuZ6KDtt2Wn1bl+7tLW59lBiIp278PUprWJzs2sWbPw1ltvYdeuXejZs+cZ41qtVlg9T45EREStEV/i12JadedGCIFZs2Zh69at+OCDD5CSkhLqIhERETUPfn6hxbTqzs29996Ll19+GW+++SZiY2NRXKwOddvtdkRFRZ0lNREREbVHrbrbt27dOpSWluLyyy9Hjx499GnLli2hLhoREVFw+BK/FtOqR26EvHmQiIgo3PCyVIthyxAREVFYadUjN0RERGHLZFKnYNKTX+zcEBERhYCiKFCCuG8mmLThjp0bIiKiUFCUIO+5YeemIRzTIiIiorDCkRsiIqJQ4BuKWww7N0RERCER7McvefGlIWwZIiIiCiscuSEiIgoFXpZqMezcEBERhQLfc9Ni2DJEREQUVtrPyM2pHyGsWnXrHHqwYosBAIiTRervDnZ1gcmshv94XA3vnqSnEdUVapglWg2oqdQWuNS5tlzUe6zHqn3FvLZaXabN9TSyTGU/udcT10X7QxjzkEOR/m5E05d5xZHrcdapc7PHppfLtBnqtTgyillri4pS92oiIrV6VGlxIo3FiJBZO32KKBw16h+RFuP6ZFllOABocYVsYz0T7btjsh1jO7mX1dUa1yPJssi8tG1syE/mU1mmziMijGWTbeVRN0Urr94mMm50B3Ve7VH2bonq/PQJdW7z2ofkdvP8F5nJYiyDbJ8qdT9DTIw7bpSWn6NWK3+ksdw/aeuNT3SniYzUqqym+XmfrmoRS7V2rFHbUYmN1ZM4K9SwCLm/nvpRnZeeUudy/5LlAQC5/1Zq5f6xWJ130vbzWq3MHsenXleZr13bPiXq8YpE7bjUjjn1b22flNvfYlPnWnvp+7EsD6C3lzy29W3WsSs8iSqP9Wj7jL6Pa22syH229ISxDgBQU22so2wfbZ+FS9tOcr8G3Ns9rqM6r6835uHU1h/hcQxWauV3CWMcmZdsG8+2LtW25elThvroZa71k0Yui9XOm9q5Qq+z3A9rPOojt788/k5q7VSmrff4MXUe7d53ar4tUYPiD2pptXoUa/uQ1apWzyONKFHTKBaLsWynZP20tvE4fsTJkxC1HvVrabws1WI4ckNERBQK8sOZwUwBWLt2LVJSUmCz2ZCWlobdu3c3GLeoqAiTJ0/GBRdcAJPJhDlz5viN99prryE1NRVWqxWpqanYunVrQGVrLuzcEBERtRNbtmzBnDlzsGDBAuTn52P06NGYMGECCgsL/cavra1Ft27dsGDBAlx00UV+4+zbtw+TJk1CVlYWDhw4gKysLNx88834+OOPW7IqZ8TODRERUSjIy1LBTADKysoMU628xOvHypUrMWXKFEydOhUDBw5ETk4OkpKSsG7dOr/xe/fujdWrV+OOO+6A3W73GycnJwfjxo1DdnY2BgwYgOzsbFx55ZXIyckJuokCxc4NERFRSCjNMAFJSUmw2+36tGzZMr9rczgc2L9/PzIzMw3hmZmZ2Lt3b8C12Ldvn0+e48ePDyrPYLWfG4qJiIhak2a6ofjYsWOIi4vTg63aDdbeTpw4AafTifj4eEN4fHw8iuXN2QEoLi5u9jyDxc4NERFRGxYXF2fo3JyN4tWhEkL4hDVVS+QZDHZuiIiIQuEcPwretWtXmM1mnxGVkpISn5GXpkhISGj2PIPFe26IiIhConnuuWksi8WCtLQ05OXlGcLz8vIwcuTIgGuRkZHhk+eOHTuCyjNYHLkhIiJqJ+bNm4esrCwMGzYMGRkZ2LBhAwoLCzF9+nQAQHZ2No4fP45NmzbpaQoKCgAAFRUV+PHHH1FQUACLxYLU1FQAwOzZszFmzBisWLECEydOxJtvvol3330Xe/bsOef1k9i5ISIiCoUQvKF40qRJOHnyJJYsWYKioiIMHjwY27ZtQ3JyMgD1pX3e77wZOnSo/vf+/fvx8ssvIzk5Gd999x0AYOTIkXjllVfwyCOP4NFHH0Xfvn2xZcsWjBgxIvC6BYmdGyIiolBo+pUl3/QBmDFjBmbMmOF3WW5urk+YkJ+qOIObbroJN910U2AFagG854aIiIjCCkduiIiIQiJEQzftADs3REREocCvgrcYXpYiIiKisMKRGyIiolBQEOTITbOVJOwoojG3QbdhZWVlsNvtKC0tbdLrqYmIqP05F//PkOs4/e98xMXGBp5PeTk69h/K/7/5wZEbIiKiUOA9Ny2G99wQERFRWOHIDRERUUjwUfCWws4NERFRKPCyVIvhZSkiIiIKKxy5ISIiCgWO3LQYdm6IiIhCgvfctBReliIiIqKwwpEbIiKiEFAUBUoQl5aCSRvu2LkhIiIKBd5z02J4WYqIiIjCCkduiIiIQoI3FLcUdm6IiIhCIsjLUuzcNIidGyIiolDgPTcthvfcEBERUVjhyA0REVFI8J6blsLODRERUSjwslSL4WUpIiIiCiscuSEiIgoFXpVqMezcEBERhQR7Ny2Fl6WIiIgorHDkhoiIKBR4Q3GLYeeGiIgoFNi5aTG8LEVERERhhZ0bIiKikFCaYWq6tWvXIiUlBTabDWlpadi9e/cZ4+/cuRNpaWmw2Wzo06cP1q9fb1iem5sLRVF8ppqamoDK1xzYuSEiIgoFBe5LUwFNTV/lli1bMGfOHCxYsAD5+fkYPXo0JkyYgMLCQr/xjx49ip///OcYPXo08vPz8dvf/hb33XcfXnvtNUO8uLg4FBUVGSabzRZAozQP3nNDREQUCiG452blypWYMmUKpk6dCgDIycnB9u3bsW7dOixbtswn/vr169GrVy/k5OQAAAYOHIhPP/0UTzzxBH75y196FEVBQkJCYPVoAW1i5KapQ2hERETtRVlZmWGqra31G8/hcGD//v3IzMw0hGdmZmLv3r1+0+zbt88n/vjx4/Hpp5+irq5OD6uoqEBycjJ69uyJa665Bvn5+UHWKjitvnPT1CE0IiKitqF57rlJSkqC3W7XJ38jMABw4sQJOJ1OxMfHG8Lj4+NRXFzsN01xcbHf+PX19Thx4gQAYMCAAcjNzcVbb72FzZs3w2azYdSoUThy5EhTG6TZtPrLUk0dQiMiImoTmumy1LFjxxAXF6cHW63WsyQzrlMI4RN2tvie4enp6UhPT9eXjxo1CpdccgmeeuoprFmzphEVaX6tunMjh9Dmz59vCD/TEFptba1hSK60tBSAOmxHRER0JvL/FfJ/4C26rvLyZkkfFxdn6Nw0pGvXrjCbzT6jNCUlJT6jM1JCQoLf+BEREejSpYvfNCaTCcOHD+fITUMCGUJbtmwZFi9e7BOelJTUImUkIqLwU15eDrvd3iJ5WywWJCQkIKn/oKDzSkhIgMViafR609LSkJeXhxtuuEEPz8vLw8SJE/2mycjIwNtvv20I27FjB4YNG4bIyEi/aYQQKCgowJAhQxpZi+bXqjs3UlOG0LKzszFv3jz9t8vlwk8//YQuXbqccditNSgrK0NSUpLPEGNbxfq0fuFWJ9andWsL9RFCoLy8HImJiS22DpvNhqNHj8LhcASdl8ViadIj1/PmzUNWVhaGDRuGjIwMbNiwAYWFhZg+fToA9f+hx48fx6ZNmwAA06dPx9NPP4158+bhN7/5Dfbt24cXXngBmzdv1vNcvHgx0tPT0a9fP5SVlWHNmjUoKCjAM888E3T9AtWqOzeBDKFZrVaf640dO3ZsqSK2iMYOMbYVrE/rF251Yn1at9Zen5YasfFks9lC8h6YSZMm4eTJk1iyZAmKioowePBgbNu2DcnJyQCAoqIiwwM7KSkp2LZtG+bOnYtnnnkGiYmJWLNmjeEx8NOnT+Oee+5BcXEx7HY7hg4dil27duHSSy895/WTFHEuLiwGYcSIEUhLS8PatWv1sNTUVEycODHsbiguKyuD3W5HaWlpqz7wG4v1af3CrU6sT+sWbvWh1qtVj9wAZx9CIyIiIvLU6js3ZxtCCydWqxULFy4862N8bQXr0/qFW51Yn9Yt3OpDrVervyxFRERE1BSt/g3FRERERE3Bzg0RERGFFXZuiIiIKKywc0NERERhhZ2bZrR27VqkpKTAZrMhLS0Nu3fvBgDU1dXh4YcfxpAhQxATE4PExETccccd+P7778+a56FDhzB27FhERUXhvPPOw5IlS3y+ebJz506kpaXBZrOhT58+WL9+fYvWx9u0adOgKApycnLOmmdrrs+//vUvXHfddbDb7YiNjUV6evpZvz7fWutTUVGBmTNnomfPnoiKisLAgQOxbt26s+YZqvrs2rUL1157LRITE6EoCt544w3DciEEFi1ahMTERERFReHyyy/HF1980Sbr0xbPB2fbPp7ayvmAwpygZvHKK6+IyMhI8dxzz4nDhw+L2bNni5iYGPGf//xHnD59Wlx11VViy5Yt4ssvvxT79u0TI0aMEGlpaWfMs7S0VMTHx4tbbrlFHDp0SLz22msiNjZWPPHEE3qcb7/9VkRHR4vZs2eLw4cPi+eee05ERkaKv/zlLy1WH09bt24VF110kUhMTBSrVq1qs/X5+uuvRefOncWDDz4oPvvsM/HNN9+Iv/71r+KHH35ok/WZOnWq6Nu3r3j//ffF0aNHxbPPPivMZrN44403WmV9tm3bJhYsWCBee+01AUBs3brVsHz58uUiNjZWvPbaa+LQoUNi0qRJokePHqKsrKzN1actng/Otn2ktnI+oPDHzk0zufTSS8X06dMNYQMGDBDz58/3G/+f//ynAODTWfC0du1aYbfbRU1NjR62bNkykZiYKFwulxBCiIceekgMGDDAkG7atGkiPT090KoIIRpXn//+97/ivPPOE59//rlITk4+68msNddn0qRJ4vbbb29Snq25PoMGDRJLliwxLL/kkkvEI4880irr48n7f54ul0skJCSI5cuX62E1NTXCbreL9evXN5hPa62PP639fOCpofq0pfMBhT9elmoGDocD+/fvR2ZmpiE8MzMTe/fu9ZumtLQUiqIYvnt111134fLLL9d/79u3D2PHjjW88Gr8+PH4/vvv8d133+lxvNc7fvx4fPrpp6irq2ux+rhcLmRlZeHBBx/EoEH+v2zbVurjcrnwt7/9Df3798f48ePRvXt3jBgxwmfova3UBwAuu+wyvPXWWzh+/DiEEHj//ffx73//G+PHj2919Tmbo0ePori42LBeq9WKsWPHGo6vtlIff1rz+aAx2tL5gNoHdm6awYkTJ+B0On0+5hkfH+/z0U8AqKmpwfz58zF58mTD91V69OiBXr166b+Li4v95imXnSlOfX09Tpw40WL1WbFiBSIiInDfffc1mE9bqU9JSQkqKiqwfPlyXH311dixYwduuOEG3Hjjjdi5c2ebqw8ArFmzBqmpqejZsycsFguuvvpqrF27Fpdddlmrq8/ZyHWf7fhqK/Xx1trPB43Rls4H1D60+s8vtCWKohh+CyF8wurq6nDLLbfA5XIZPgYKwO+HQP3l6R3emDiBaKg++/fvx+rVq/HZZ5+dcR1tpT4ulwsAMHHiRMydOxcAcPHFF2Pv3r1Yv349xo4dC6Dt1AdQOzcfffQR3nrrLSQnJ2PXrl2YMWMGevTogauuuqpV1udsznZ8tbX6AG3rfNCQtno+oPDGkZtm0LVrV5jNZp9RmpKSEsO/Ourq6nDzzTfj6NGjyMvLO+tXcRMSEvzmCbj/hdNQnIiICHTp0qVF6rN7926UlJSgV69eiIiIQEREBP7zn//g/vvvR+/evdtcfbp27YqIiAikpqYalg8cOPCMT0u11vpUV1fjt7/9LVauXIlrr70WF154IWbOnIlJkybhiSeeaHX1OZuEhAQAOOvx5S9da6yP1FbOB2fT1s4H1D6wc9MMLBYL0tLSkJeXZwjPy8vDyJEjAbhPZEeOHMG7777bqAMzIyMDu3btgsPh0MN27NiBxMRE/aSRkZHhs94dO3Zg2LBhiIyMbJH6ZGVl4eDBgygoKNCnxMREPPjgg9i+fXubq4/FYsHw4cPx1VdfGZb/+9//PuMHWltrferq6lBXVweTyXh4m81mfZSqNdXnbFJSUpCQkGBYr8PhwM6dO/Xjy5/WWh+gbZ0PzqatnQ+onTi39y+HL/lo7gsvvCAOHz4s5syZI2JiYsR3330n6urqxHXXXSd69uwpCgoKRFFRkT7V1tbqecyfP19kZWXpv0+fPi3i4+PFrbfeKg4dOiRef/11ERcX5/dRyblz54rDhw+LF154oVkfNfZXH3/8PR3Rlurz+uuvi8jISLFhwwZx5MgR8dRTTwmz2Sx2797dJuszduxYMWjQIPH++++Lb7/9VmzcuFHYbDaxdu3aVlmf8vJykZ+fL/Lz8wUAsXLlSpGfn68/PbR8+XJht9vF66+/Lg4dOiRuvfVWn0fB20p92uL54Gzbx1trPx9Q+GPnphk988wzIjk5WVgsFnHJJZeInTt3CiGEOHr0qADgd3r//ff19HfeeacYO3asIc+DBw+K0aNHC6vVKhISEsSiRYv0xySlDz74QAwdOlRYLBbRu3dvsW7duhatjz/+TmZtrT4vvPCCOP/884XNZhMXXXSRzzth2lJ9ioqKxF133SUSExOFzWYTF1xwgXjyyScNZWtN9Xn//ff9Hh933nmnEEJ9HHzhwoUiISFBWK1WMWbMGHHo0CFDHm2lPm3xfHC27eOtLZwPKLwpQni9DpKIiIioDeM9N0RERBRW2LkhIiKisMLODREREYUVdm6IiIgorLBzQ0RERGGFnRsiIiIKK+zcEBERUVhh54aIqA1ZtmwZhg8fjtjYWHTv3h3XX3+9z6dDhBBYtGgREhMTERUVhcsvvxxffPGFvvynn37CrFmzcMEFFyA6Ohq9evXCfffdh9LSUkM+p06dQlZWFux2O+x2O7KysnD69OlGlfO///0vLBYLBgwYEHSdm+KLL77AL3/5S/Tu3RuKoiAnJ8cnzqJFi6AoimGS3zCj8MDODVGY+eCDD6AoSqP/J0Rty86dO3Hvvffio48+Ql5eHurr65GZmYnKyko9zh//+EesXLkSTz/9ND755BMkJCRg3LhxKC8vBwB8//33+P777/HEE0/g0KFDyM3NxTvvvIMpU6YY1jV58mQUFBTgnXfewTvvvIOCggJkZWU1qpy5ubm4+eabUVVVhQ8//LD5GuAsqqqq0KdPHyxfvvyMHZZBgwahqKhInw4dOnTOykjnQIjfkExEQRo7dqyYPXu2/ru2tlYUFRX5vMaewlNJSYkAoH9+w+VyiYSEBLF8+XI9Tk1NjbDb7WL9+vUN5vPqq68Ki8Ui6urqhBBCHD58WAAQH330kR5n3759AoD48ssvz1gml8sl+vTpI9555x3x8MMPi7vvvtuwXH7O4dSpU3qY/G7V0aNH9bANGzaInj17iqioKHH99deLJ598Utjt9rM1ic7fZyCEEGLhwoXioosuanQ+1PZw5IYozFgsFiQkJEBRlFAXhc4BeSmpc+fOAICjR4+iuLgYmZmZehyr1YqxY8di7969Z8wnLi4OERERAIB9+/bBbrdjxIgRepz09HTY7fYz5gMA77//PqqqqnDVVVchKysLr776qj5q1Fgffvghpk+fjtmzZ6OgoADjxo3DH/7whyblcSZHjhxBYmIiUlJScMstt+Dbb79ttrwp9Ni5IWrD7rrrLuzcuROrV6/W7x3Izc01XJbKzc1Fx44d8de//lW/x+Kmm25CZWUlXnrpJfTu3RudOnXCrFmz4HQ69bwdDgceeughnHfeeYiJicGIESPwwQcfhKai5JcQAvPmzcNll12GwYMHAwCKi4sBAPHx8Ya48fHx+jJvJ0+exO9//3tMmzZNDysuLkb37t194nbv3r3BfKQXXngBt9xyC8xmMwYNGoTzzz8fW7ZsaVLdnnrqKUyYMAEPPPAA+vfvjxkzZmDChAlNyqMhI0aMwKZNm7B9+3Y899xzKC4uxsiRI3Hy5MlmyZ9Cj50bojZs9erVyMjIwG9+8xv93oGkpCSfeFVVVVizZg1eeeUVvPPOO/jggw9w4403Ytu2bdi2bRv+9Kc/YcOGDfjLX/6ip7n77rvx4Ycf4pVXXsHBgwfxq1/9CldffTWOHDlyLqtIZzBz5kwcPHgQmzdv9lnmPXInhPA7mldWVoZf/OIXSE1NxcKFC8+Yh3c+gwYNQocOHdChQwe943H69Gm8/vrruP322/U0t99+O1588cUm1e2rr77CpZdeagjz/F1YWKivu0OHDli6dGmj854wYQJ++ctfYsiQIbjqqqvwt7/9DQDw0ksvNamM1HpFhLoARBQ4u90Oi8WC6Oho/ebJL7/80ideXV0d1q1bh759+wIAbrrpJvzpT3/CDz/8gA4dOiA1NRVXXHEF3n//fUyaNAnffPMNNm/ejP/+979ITEwEADzwwAN45513sHHjxib9j4RaxqxZs/DWW29h165d6Nmzpx4u94Pi4mL06NFDDy8pKfEZzSkvL8fVV1+NDh06YOvWrYiMjDTk88MPP/is98cff9Tz2bZtG+rq6gAAUVFRAICXX34ZNTU1hstZQgi4XC4cPnwYqampMJlMergk8/FM46+DJiUmJqKgoED/LS/LBSImJgZDhgxhxz2MsHND1A5ER0frHRtAvUTRu3dvdOjQwRBWUlICAPjss88ghED//v0N+dTW1qJLly7nptDklxACs2bNwtatW/HBBx8gJSXFsDwlJQUJCQnIy8vD0KFDAaiXGHfu3IkVK1bo8crKyjB+/HhYrVa89dZbsNlshnwyMjJQWlqKf/7zn/qIyccff4zS0lKMHDkSAJCcnOxTvhdeeAH3338/7rrrLkP4fffdhxdffBFPPPEEunXrBgAoKipCp06dAMDQUQGAAQMG4J///Kch7NNPP9X/joiIwPnnn3/Gtmqs2tpa/Otf/8Lo0aObJT8KPXZuiNoBz3+RA+rlBn9hLpcLAOByuWA2m7F//36YzWZDPM8OEZ179957L15++WW8+eabiI2N1e9/sdvtiIqKgqIomDNnDpYuXYp+/fqhX79+WLp0KaKjozF58mQA6ohNZmYmqqqq8Oc//xllZWUoKysDAHTr1g1msxkDBw7E1Vdfjd/85jd49tlnAQD33HMPrrnmGlxwwQV+y1ZQUIDPPvsM//u//+vzfptbb70VCxYswLJly3D++ecjKSkJixYtwmOPPYYjR47gySefNMSfNWsWxowZg5UrV+Laa6/FP/7xD/z9738/643yDocDhw8f1v8+fvw4CgoK0KFDB70z9MADD+Daa69Fr169UFJSgsceewxlZWW48847m7IpqDUL2XNaRNQsxo0bJ2bOnKn/9n7MduPGjT6Pz/p7FPbOO+8UEydOFEII8dVXXwkAYteuXS1YcgoEAL/Txo0b9Tgul0ssXLhQJCQkCKvVKsaMGSMOHTqkL5f7iL/J81HskydPittuu03ExsaK2NhYcdtttxke3/Y2c+ZMkZqa6ndZSUmJMJvN4rXXXhNCCLFnzx4xZMgQYbPZxOjRo8X//d//+X0U/LzzztMfBX/sscdEQkLCGdvn6NGjfus1duxYPc6kSZNEjx49RGRkpEhMTBQ33nij+OKLL86YL7UtihAeFzGJqM255557UFBQgFdffRUdOnTAwYMHceWVV+LUqVPo2LEjcnNzMWfOHMNL/RYtWoQ33njDcCngrrvuwunTp/HGG28AUG8C/fDDD/Hkk09i6NChOHHiBP7xj39gyJAh+PnPf35uK0kE4De/+Q2+/PJL7N69O9RFoVaOT0sRtXEPPPAAzGYzUlNT0a1bNxQWFjZLvhs3bsQdd9yB+++/HxdccAGuu+46fPzxx36fxiJqCU888QQOHDiAr7/+Gk899RReeuklXjqiRuHIDRERtUo333wzPvjgA5SXl6NPnz6YNWsWpk+fHupiURvAzg0RERGFFV6WIiIiorDCzg0RERGFFXZuiIiIKKywc0NERERhhZ0bIiIiCivs3BAREVFYYeeGiIiIwgo7N0RERBRW2LkhIiKisMLODREREYWV/wfnan3u26eNJQAAAABJRU5ErkJggg==",
             "text/plain": [
               "<Figure size 640x480 with 2 Axes>"
             ]
@@ -3660,7 +3661,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 54,
+      "execution_count": 22,
       "metadata": {},
       "outputs": [],
       "source": [
@@ -3687,7 +3688,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 55,
+      "execution_count": 33,
       "metadata": {},
       "outputs": [
         {
@@ -3699,15 +3700,15 @@
               " (0.0005, 0.1)]"
             ]
           },
-          "execution_count": 55,
+          "execution_count": 33,
           "metadata": {},
           "output_type": "execute_result"
         },
         {
           "data": {
-            "image/png": 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",
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",
             "text/plain": [
-              "<Figure size 500x500 with 2 Axes>"
+              "<Figure size 600x500 with 2 Axes>"
             ]
           },
           "metadata": {},
@@ -3771,7 +3772,7 @@
         "\n",
         "\n",
         "# Set up figure\n",
-        "fig, ax = plt.subplots(1, 1, figsize=(5, 5))\n",
+        "fig, ax = plt.subplots(1, 1, figsize=(6, 5))\n",
         "fig.subplots_adjust(left=0.2, right=0.75, top=0.95, bottom=0.1)\n",
         "\n",
         "# Plot spectra by color\n",
@@ -3806,7 +3807,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 56,
+      "execution_count": 24,
       "metadata": {},
       "outputs": [],
       "source": [
@@ -3824,7 +3825,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 57,
+      "execution_count": 25,
       "metadata": {},
       "outputs": [],
       "source": [
@@ -3845,7 +3846,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 58,
+      "execution_count": 26,
       "metadata": {},
       "outputs": [],
       "source": [
@@ -3888,7 +3889,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 59,
+      "execution_count": 27,
       "metadata": {},
       "outputs": [],
       "source": [
@@ -3915,22 +3916,22 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 60,
+      "execution_count": 28,
       "metadata": {},
       "outputs": [
         {
           "data": {
             "text/plain": [
-              "<matplotlib.collections.QuadMesh at 0x112d7649190>"
+              "<matplotlib.collections.QuadMesh at 0x25a30084250>"
             ]
           },
-          "execution_count": 60,
+          "execution_count": 28,
           "metadata": {},
           "output_type": "execute_result"
         },
         {
           "data": {
-            "image/png": 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",
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",
             "text/plain": [
               "<Figure size 640x480 with 2 Axes>"
             ]
@@ -3956,7 +3957,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 61,
+      "execution_count": 29,
       "metadata": {},
       "outputs": [
         {
@@ -3965,13 +3966,13 @@
               "Text(0.5, 1.0, 'TI Difference')"
             ]
           },
-          "execution_count": 61,
+          "execution_count": 29,
           "metadata": {},
           "output_type": "execute_result"
         },
         {
           "data": {
-            "image/png": 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",
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",
             "text/plain": [
               "<Figure size 640x480 with 2 Axes>"
             ]
@@ -4018,14 +4019,14 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 62,
+      "execution_count": 30,
       "metadata": {},
       "outputs": [
         {
           "name": "stderr",
           "output_type": "stream",
           "text": [
-            "c:\\Users\\mcve343\\anaconda3\\envs\\work\\Lib\\site-packages\\mhkit\\dolfyn\\adp\\turbulence.py:407: UserWarning:     The beam-variance algorithms assume the instrument's (XYZ) coordinate system is aligned with the principal flow directions.\n",
+            "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\dolfyn\\adp\\turbulence.py:422: UserWarning:     The beam-variance algorithms assume the instrument's (XYZ) coordinate system is aligned with the principal flow directions.\n",
             "  warnings.warn(\n"
           ]
         }
@@ -4065,14 +4066,14 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 63,
+      "execution_count": 31,
       "metadata": {},
       "outputs": [
         {
           "name": "stderr",
           "output_type": "stream",
           "text": [
-            "c:\\Users\\mcve343\\anaconda3\\envs\\work\\Lib\\site-packages\\mhkit\\dolfyn\\rotate\\api.py:72: UserWarning: You are attempting to rotate into the 'principal' coordinate system, but the dataset is in the inst coordinate system. Be sure that 'principal_heading' is defined based on the earth coordinate system.\n",
+            "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\dolfyn\\rotate\\api.py:72: UserWarning: You are attempting to rotate into the 'principal' coordinate system, but the dataset is in the inst coordinate system. Be sure that 'principal_heading' is defined based on the earth coordinate system.\n",
             "  warnings.warn(\n"
           ]
         }
@@ -4104,7 +4105,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 64,
+      "execution_count": 32,
       "metadata": {},
       "outputs": [
         {
@@ -4113,13 +4114,13 @@
               "Text(0.5, 1.0, 'TKE Balance')"
             ]
           },
-          "execution_count": 64,
+          "execution_count": 32,
           "metadata": {},
           "output_type": "execute_result"
         },
         {
           "data": {
-            "image/png": 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",
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",
             "text/plain": [
               "<Figure size 640x480 with 2 Axes>"
             ]
@@ -4129,7 +4130,7 @@
         },
         {
           "data": {
-            "image/png": 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",
+            "image/png": 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             "text/plain": [
               "<Figure size 640x480 with 2 Axes>"
             ]
diff --git a/examples/adcp_waves_example.ipynb b/examples/adcp_waves_example.ipynb
new file mode 100644
index 000000000..8b8dda1b7
--- /dev/null
+++ b/examples/adcp_waves_example.ipynb
@@ -0,0 +1,1529 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "7dcd8659",
+   "metadata": {},
+   "source": [
+    "## Analyzing Wave Statistics from ADCP Altimeter Data\n",
+    "\n",
+    "The following notebook illustrates how to process and compute wave statistics from acoustic Doppler current profilers (ADCPs) with the ability to measure waves (Nortek AWAC, Signature and RDI SentinelV). This example assumes the user is familiar with the basic workflow for processing ADCP data.\n",
+    "\n",
+    "Firstly, the ADCP must have been configured in wave measurement mode for deployment. This mode is only available for ADCPs with a vertically-oriented center transducer, which is used to located the water surface. The other four beams are utilized to measure water velocity at and around the water surface in order to track wave orbitals. The following basic workflow runs through the following:\n",
+    "\n",
+    "1. Import Data\n",
+    "2. Review and QC altimeter measurements\n",
+    "3. Create energy spectra from surface height\n",
+    "4. Compute wave height and period\n",
+    "5. Review and QC surface velocity measurements\n",
+    "6. Use \"SUV\" method to compute wave direction and spread\n",
+    "\n",
+    "We'll begin analysis by importing the DOLfYN and wave modules from MHKiT. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "cfc84a0d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from mhkit import dolfyn\n",
+    "from mhkit import wave"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "49d7332e",
+   "metadata": {},
+   "source": [
+    "### 1. Import Raw Datafile\n",
+    "\n",
+    "We'll start by using DOLfYN to read the binary file into python. This particular file is a clip from a Nortek Signature250 deployed at PacWave South, Oregon. In this case, the instrument was configured on a duty cycle to measure both waves and water velocity. Because two different profiling methods were used, DOLfYN will output two individual datasets.\n",
+    "\n",
+    "In this notebook, we'll focus on the waves dataset. A workflow for the water velocity dataset, which is the traditional ADCP measurement scheme, can be found in the ADCP example notebook."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "3667665a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\dolfyn\\io\\nortek2_lib.py:304: UserWarning: Dual Profile detected... Two datasets will be returned.\n",
+      "  warnings.warn(msg)\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reading file data/dolfyn/Sig250_PacWave.ad2cp ...\n"
+     ]
+    }
+   ],
+   "source": [
+    "ds_waves, ds_avg = dolfyn.read(\"data/dolfyn/Sig250_PacWave.ad2cp\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6a9ce962",
+   "metadata": {},
+   "source": [
+    "If we print the dataset, we can see all of the data variables that the ADCP collects for wave measurements. ADCPs measure basic wave information by using an altimeter pulse to detect where the surface is. \n",
+    "\n",
+    "The ADCP first (and periodically thereafter) sends out a series of sample pulses to calibrate the altimeter. These are saved in the dataset with the tag \"_altraw\". The ADCP then sends out altimeter pings at the user-defined sampling rate, which are saved in the dataset with the \"_alt\" tag.\n",
+    "\n",
+    "The altimeter pings are interpreted by the instrument using two different algorithms, called \"acoustic surface tracking\" (AST) and the \"leading edge\" (LE) method. These variables have either an \"ast_\" or \"le_\" prefix to their names. AST is typically used for measuring the air-water interface, while LE is better for detecting boundaries between water and other dense mediums, such as sea ice or seafloor."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "84dd5f7a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1f1f1f;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 11MB\n",
+       "Dimensions:                 (time: 18073, time_altraw: 35, range: 13, beam: 4,\n",
+       "                             dir: 4, dirIMU: 3, n_altraw: 2583, x1: 4, x2: 4,\n",
+       "                             earth: 3, inst: 3)\n",
+       "Coordinates:\n",
+       "  * time                    (time) datetime64[ns] 145kB 2024-10-22T19:29:36.3...\n",
+       "  * time_altraw             (time_altraw) datetime64[ns] 280B 2024-10-22T19:2...\n",
+       "  * range                   (range) float64 104B 38.7 42.2 45.7 ... 77.2 80.7\n",
+       "  * beam                    (beam) int32 16B 1 2 3 4\n",
+       "  * dir                     (dir) int32 16B 1 2 3 4\n",
+       "  * dirIMU                  (dirIMU) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
+       "  * x1                      (x1) int32 16B 1 2 3 4\n",
+       "  * x2                      (x2) int32 16B 1 2 3 4\n",
+       "  * earth                   (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
+       "  * inst                    (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
+       "Dimensions without coordinates: n_altraw\n",
+       "Data variables: (12/39)\n",
+       "    c_sound                 (time) float32 72kB 1.503e+03 ... 1.485e+03\n",
+       "    temp                    (time) float32 72kB 13.93 13.92 13.92 ... 8.23 8.23\n",
+       "    pressure                (time) float32 72kB 0.768 0.765 ... 74.71 74.71\n",
+       "    heading                 (time) float32 72kB 216.1 215.8 ... 212.7 212.9\n",
+       "    pitch                   (time) float32 72kB -27.59 -28.03 ... 2.21 2.22\n",
+       "    roll                    (time) float32 72kB 73.04 71.68 67.74 ... -0.36 -0.4\n",
+       "    ...                      ...\n",
+       "    low_volt_skip           (time) uint8 18kB 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0\n",
+       "    active_config           (time) uint8 18kB 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0\n",
+       "    telemetry_data          (time) uint8 18kB 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0\n",
+       "    boost_running           (time) uint8 18kB 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0\n",
+       "    beam2inst_orientmat     (x1, x2) float32 64B 1.462 0.0 -1.462 ... 0.0 0.532\n",
+       "    orientmat               (earth, inst, time) float32 651kB -0.5221 ... 0.9992\n",
+       "Attributes: (12/39)\n",
+       "    filehead_config:       {&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2024-10-22 19:29:32\\&quot;&quot;}, ...\n",
+       "    inst_model:            Signature250\n",
+       "    inst_make:             Nortek\n",
+       "    inst_type:             ADCP\n",
+       "    burst_config:          {&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass...\n",
+       "    n_cells:               13\n",
+       "    ...                    ...\n",
+       "    rotate_vars:           [&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;mag&#x27;]\n",
+       "    coord_sys:             beam\n",
+       "    fs:                    1\n",
+       "    bandwidth:             &quot;BROAD&quot;\n",
+       "    has_imu:               0\n",
+       "    beam_angle:            20</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-73387bb8-ff17-4a70-ae1e-d28a835b009f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-73387bb8-ff17-4a70-ae1e-d28a835b009f' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 18073</li><li><span class='xr-has-index'>time_altraw</span>: 35</li><li><span class='xr-has-index'>range</span>: 13</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span>n_altraw</span>: 2583</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-27c70c72-cbfa-4901-8a76-d6732546a6f3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-27c70c72-cbfa-4901-8a76-d6732546a6f3' class='xr-section-summary' >Coordinates: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2024-10-22T19:29:36.334399938 .....</div><input id='attrs-350fc6a3-4a51-4516-852d-72c058e09c1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-350fc6a3-4a51-4516-852d-72c058e09c1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0454cb8e-de6e-4294-92e8-71f7c12e30bb' class='xr-var-data-in' type='checkbox'><label for='data-0454cb8e-de6e-4294-92e8-71f7c12e30bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-10-22T19:29:36.334399938&#x27;, &#x27;2024-10-22T19:29:37.334399938&#x27;,\n",
+       "       &#x27;2024-10-22T19:29:38.334399938&#x27;, ..., &#x27;2024-10-23T04:10:38.334399938&#x27;,\n",
+       "       &#x27;2024-10-23T04:10:39.334199905&#x27;, &#x27;2024-10-23T04:10:40.334399938&#x27;],\n",
+       "      shape=(18073,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2024-10-22T19:29:36.000999927 .....</div><input id='attrs-a83feb10-8d6d-4ad1-ac67-586f62800524' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a83feb10-8d6d-4ad1-ac67-586f62800524' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5dc11762-06c3-4059-8f71-42ce8da479da' class='xr-var-data-in' type='checkbox'><label for='data-5dc11762-06c3-4059-8f71-42ce8da479da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time altraw</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2024-10-22T19:29:36.000999927&#x27;, &#x27;2024-10-22T19:46:39.000999927&#x27;,\n",
+       "       &#x27;2024-10-22T19:59:36.000999927&#x27;, &#x27;2024-10-22T20:16:39.000999927&#x27;,\n",
+       "       &#x27;2024-10-22T20:29:36.000999927&#x27;, &#x27;2024-10-22T20:46:39.000999927&#x27;,\n",
+       "       &#x27;2024-10-22T20:59:36.000999927&#x27;, &#x27;2024-10-22T21:16:39.000999927&#x27;,\n",
+       "       &#x27;2024-10-22T21:29:36.000999927&#x27;, &#x27;2024-10-22T21:46:39.001100063&#x27;,\n",
+       "       &#x27;2024-10-22T21:59:36.000999927&#x27;, &#x27;2024-10-22T22:16:39.001100063&#x27;,\n",
+       "       &#x27;2024-10-22T22:29:36.000999927&#x27;, &#x27;2024-10-22T22:46:39.001100063&#x27;,\n",
+       "       &#x27;2024-10-22T22:59:36.000999927&#x27;, &#x27;2024-10-22T23:16:39.001100063&#x27;,\n",
+       "       &#x27;2024-10-22T23:29:36.000900030&#x27;, &#x27;2024-10-22T23:46:39.000999927&#x27;,\n",
+       "       &#x27;2024-10-22T23:59:36.000999927&#x27;, &#x27;2024-10-23T00:16:39.000999927&#x27;,\n",
+       "       &#x27;2024-10-23T00:29:36.000999927&#x27;, &#x27;2024-10-23T00:46:39.000999927&#x27;,\n",
+       "       &#x27;2024-10-23T00:59:36.000999927&#x27;, &#x27;2024-10-23T01:16:39.000999927&#x27;,\n",
+       "       &#x27;2024-10-23T01:29:36.000999927&#x27;, &#x27;2024-10-23T01:46:39.000999927&#x27;,\n",
+       "       &#x27;2024-10-23T01:59:36.000999927&#x27;, &#x27;2024-10-23T02:16:39.000999927&#x27;,\n",
+       "       &#x27;2024-10-23T02:29:36.000999927&#x27;, &#x27;2024-10-23T02:46:39.000999927&#x27;,\n",
+       "       &#x27;2024-10-23T02:59:36.000999927&#x27;, &#x27;2024-10-23T03:16:39.000999927&#x27;,\n",
+       "       &#x27;2024-10-23T03:29:36.000999927&#x27;, &#x27;2024-10-23T03:46:39.000999927&#x27;,\n",
+       "       &#x27;2024-10-23T03:59:36.000999927&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>38.7 42.2 45.7 ... 73.7 77.2 80.7</div><input id='attrs-53fed162-6709-4959-a5d8-201416b8999f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-53fed162-6709-4959-a5d8-201416b8999f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7330cf07-c451-4027-a6ed-e43f3d8e2f2d' class='xr-var-data-in' type='checkbox'><label for='data-7330cf07-c451-4027-a6ed-e43f3d8e2f2d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([38.7, 42.2, 45.7, 49.2, 52.7, 56.2, 59.7, 63.2, 66.7, 70.2, 73.7, 77.2,\n",
+       "       80.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-ef7db9ae-55b6-4a12-9776-70aaae2e400c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef7db9ae-55b6-4a12-9776-70aaae2e400c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6232025-af30-4bb2-80a8-3a057008a4c2' class='xr-var-data-in' type='checkbox'><label for='data-a6232025-af30-4bb2-80a8-3a057008a4c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-3a01b450-c477-4353-8e47-db9fe814c450' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a01b450-c477-4353-8e47-db9fe814c450' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fac65951-3380-4519-8ee1-506ead0d5c7e' class='xr-var-data-in' type='checkbox'><label for='data-fac65951-3380-4519-8ee1-506ead0d5c7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>beam</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-21a9de9c-0c8a-4c32-8cc6-2093c588b3e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21a9de9c-0c8a-4c32-8cc6-2093c588b3e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7148f06d-250c-48ea-af49-bc641a440ab7' class='xr-var-data-in' type='checkbox'><label for='data-7148f06d-250c-48ea-af49-bc641a440ab7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>beam</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-fe5abe59-7bfe-4c4c-a098-56b744a76e91' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fe5abe59-7bfe-4c4c-a098-56b744a76e91' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9dda39fb-7e49-4532-82d4-879deeb89bf6' class='xr-var-data-in' type='checkbox'><label for='data-9dda39fb-7e49-4532-82d4-879deeb89bf6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-d4fa9332-8b4c-4c7e-8b61-810c37b99b9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d4fa9332-8b4c-4c7e-8b61-810c37b99b9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97718d04-c918-4c2c-aebe-1894d35366fc' class='xr-var-data-in' type='checkbox'><label for='data-97718d04-c918-4c2c-aebe-1894d35366fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-eafcd6d5-996d-4074-a5ed-f31aa2267539' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eafcd6d5-996d-4074-a5ed-f31aa2267539' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-966715da-7d57-49d8-9f64-d8a6c9c88221' class='xr-var-data-in' type='checkbox'><label for='data-966715da-7d57-49d8-9f64-d8a6c9c88221' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-4c1da1c1-472d-4c5d-a982-999437fd7b63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c1da1c1-472d-4c5d-a982-999437fd7b63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b541531-af2c-45cd-be99-47e20225ff94' class='xr-var-data-in' type='checkbox'><label for='data-4b541531-af2c-45cd-be99-47e20225ff94' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-23a85adb-4f1f-4474-9918-711e537d8c41' class='xr-section-summary-in' type='checkbox'  ><label for='section-23a85adb-4f1f-4474-9918-711e537d8c41' class='xr-section-summary' >Data variables: <span>(39)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.503e+03 1.503e+03 ... 1.485e+03</div><input id='attrs-9a1b7651-c756-4536-ac7d-e6035a7d1292' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a1b7651-c756-4536-ac7d-e6035a7d1292' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a50ef2ee-0433-4e59-95bd-7532c123e2fc' class='xr-var-data-in' type='checkbox'><label for='data-a50ef2ee-0433-4e59-95bd-7532c123e2fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1503.2, 1503.2, 1503.2, ..., 1484.6, 1484.5, 1484.6],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>13.93 13.92 13.92 ... 8.23 8.23</div><input id='attrs-58234fe8-4d64-4dbd-99ff-08ceeb89ccc8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58234fe8-4d64-4dbd-99ff-08ceeb89ccc8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e458078-e7e7-4df7-9f70-c59564dbedf7' class='xr-var-data-in' type='checkbox'><label for='data-0e458078-e7e7-4df7-9f70-c59564dbedf7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([13.93, 13.92, 13.92, ...,  8.23,  8.23,  8.23],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.768 0.765 0.762 ... 74.71 74.71</div><input id='attrs-c662c573-491e-44ce-aa86-4f9e6c511913' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c662c573-491e-44ce-aa86-4f9e6c511913' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-113b1785-2e28-41d7-b802-f20174c725bd' class='xr-var-data-in' type='checkbox'><label for='data-113b1785-2e28-41d7-b802-f20174c725bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([ 0.768,  0.765,  0.762, ..., 74.694, 74.706, 74.711],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>216.1 215.8 216.7 ... 212.7 212.9</div><input id='attrs-4d728563-cd12-4b75-92cf-2f5e003c40a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d728563-cd12-4b75-92cf-2f5e003c40a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78383fa9-b0e4-4d41-b9e0-24b5b44bfd30' class='xr-var-data-in' type='checkbox'><label for='data-78383fa9-b0e4-4d41-b9e0-24b5b44bfd30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([216.09, 215.8 , 216.7 , ..., 212.88, 212.72, 212.95],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-27.59 -28.03 -29.35 ... 2.21 2.22</div><input id='attrs-bf52dbc0-c274-4968-b0ad-1250476ba1f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf52dbc0-c274-4968-b0ad-1250476ba1f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84a8dc43-d59c-4d39-b557-94b9859e0b82' class='xr-var-data-in' type='checkbox'><label for='data-84a8dc43-d59c-4d39-b557-94b9859e0b82' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-27.59, -28.03, -29.35, ...,   2.19,   2.21,   2.22],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>73.04 71.68 67.74 ... -0.36 -0.4</div><input id='attrs-a2ba103c-550c-4c48-a191-ae4284dd20e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2ba103c-550c-4c48-a191-ae4284dd20e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b8e8b50-6351-43ae-ad5f-68f98c39442b' class='xr-var-data-in' type='checkbox'><label for='data-0b8e8b50-6351-43ae-ad5f-68f98c39442b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([73.04, 71.68, 67.74, ..., -0.38, -0.36, -0.4 ],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>5.9 8.8 8.4 ... -60.9 -60.8 -60.9</div><input id='attrs-31c0002c-0d0b-489f-b6f1-974696770951' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31c0002c-0d0b-489f-b6f1-974696770951' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee0b1dcf-c40e-46fd-a282-1362f210328b' class='xr-var-data-in' type='checkbox'><label for='data-ee0b1dcf-c40e-46fd-a282-1362f210328b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  5.9,   8.8,   8.4, ..., -21.7, -21.8, -21.7],\n",
+       "       [-57.6, -56.9, -56.9, ..., -12.1, -12.1, -12.1],\n",
+       "       [ -1.9,  -4.9,  -7.3, ..., -60.9, -60.8, -60.9]],\n",
+       "      shape=(3, 18073), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-4.489 -4.6 -4.715 ... 9.773 9.777</div><input id='attrs-d26746c4-67d4-4f14-a377-4519ffd73bd0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d26746c4-67d4-4f14-a377-4519ffd73bd0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86efcf88-f7ff-4b64-9bea-6c588e5a2b79' class='xr-var-data-in' type='checkbox'><label for='data-86efcf88-f7ff-4b64-9bea-6c588e5a2b79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-4.4888654 , -4.6002336 , -4.714596  , ...,  0.37541932,\n",
+       "         0.37781432,  0.38020936],\n",
+       "       [ 8.21312   ,  8.201145  ,  7.7568693 , ..., -0.06586304,\n",
+       "        -0.06346802, -0.06825805],\n",
+       "       [ 2.503993  ,  2.7147546 ,  3.1745985 , ...,  9.772877  ,\n",
+       "         9.772877  ,  9.777068  ]], shape=(3, 18073), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>23.4 23.4 23.4 ... 18.5 18.5 18.5</div><input id='attrs-6e108b4b-c6ea-43e1-af15-516e824500b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e108b4b-c6ea-43e1-af15-516e824500b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-091ff0a7-b374-407b-9409-bf1eed6d19e7' class='xr-var-data-in' type='checkbox'><label for='data-091ff0a7-b374-407b-9409-bf1eed6d19e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([23.4, 23.4, 23.4, ..., 18.5, 18.5, 18.5],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>19.75 19.75 19.75 ... 9.75 9.75</div><input id='attrs-77f41760-8bbb-4917-939f-0a355b82901b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77f41760-8bbb-4917-939f-0a355b82901b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-214e9e4b-9e26-43ed-a3ac-63a70dd39317' class='xr-var-data-in' type='checkbox'><label for='data-214e9e4b-9e26-43ed-a3ac-63a70dd39317' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([19.75, 19.75, 19.75, ...,  9.75,  9.75,  9.75],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-f68cecff-ef50-4eba-92a0-9633402adf22' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f68cecff-ef50-4eba-92a0-9633402adf22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-183c312e-2364-45a9-961e-547ec67eead6' class='xr-var-data-in' type='checkbox'><label for='data-183c312e-2364-45a9-961e-547ec67eead6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(18073,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>675807234 675807234 ... 944504834</div><input id='attrs-1e4bf90a-0b05-4c18-b072-21533f2b3eca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e4bf90a-0b05-4c18-b072-21533f2b3eca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8f9e70a-eebd-474f-8535-a5cca8fb0662' class='xr-var-data-in' type='checkbox'><label for='data-b8f9e70a-eebd-474f-8535-a5cca8fb0662' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([675807234, 675807234, 675807234, ..., 944504834, 944504834,\n",
+       "       944504834], shape=(18073,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 24285 24287 24289 24291</div><input id='attrs-f2725916-7755-4c32-8d36-b22ba1239c2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2725916-7755-4c32-8d36-b22ba1239c2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26f9b5d1-c9e4-4896-b699-dfc29c58a7e4' class='xr-var-data-in' type='checkbox'><label for='data-26f9b5d1-c9e4-4896-b699-dfc29c58a7e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 24287, 24289, 24291],\n",
+       "      shape=(18073,), dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.231 -2.796 0.219 ... -0.264 0.694</div><input id='attrs-c423276c-a8fe-466b-a156-d7243e75df98' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c423276c-a8fe-466b-a156-d7243e75df98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81675a96-bab9-4be0-8ca3-f4de51cab812' class='xr-var-data-in' type='checkbox'><label for='data-81675a96-bab9-4be0-8ca3-f4de51cab812' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[[ 1.231e+00, -2.796e+00,  2.190e-01, ...,  1.280e-01,\n",
+       "          6.200e-02,  6.400e-02],\n",
+       "        [-4.220e+00, -1.316e+00,  1.423e+00, ...,  8.900e-02,\n",
+       "          3.900e-02,  8.000e-03],\n",
+       "        [ 3.722e+00,  2.967e+00, -3.881e+00, ...,  1.280e-01,\n",
+       "          8.000e-02,  4.100e-02],\n",
+       "        ...,\n",
+       "        [ 3.608e+00, -4.118e+00,  9.000e-02, ...,  5.770e-01,\n",
+       "          5.840e-01,  1.810e-01],\n",
+       "        [-2.383e+00,  3.820e+00, -1.982e+00, ...,  9.310e-01,\n",
+       "          7.980e-01, -6.210e-01],\n",
+       "        [-1.288e+00, -5.273e+00,  4.996e+00, ...,  8.020e-01,\n",
+       "          6.680e-01,  1.020e-01]],\n",
+       "\n",
+       "       [[ 1.096e+00, -2.937e+00,  3.400e-01, ...,  7.100e-02,\n",
+       "         -8.000e-03,  1.000e-02],\n",
+       "        [-4.220e+00, -1.478e+00,  1.309e+00, ...,  1.150e-01,\n",
+       "         -5.000e-03, -9.600e-02],\n",
+       "        [ 3.097e+00,  2.886e+00, -4.042e+00, ...,  4.800e-02,\n",
+       "         -4.800e-02, -9.000e-02],\n",
+       "...\n",
+       "        [ 3.524e+00, -3.629e+00,  1.000e-02, ..., -2.840e-01,\n",
+       "         -2.460e-01,  7.240e-01],\n",
+       "        [-2.416e+00,  3.327e+00, -2.317e+00, ..., -2.630e-01,\n",
+       "         -2.010e-01,  6.630e-01],\n",
+       "        [-2.929e+00,  4.419e+00,  4.493e+00, ..., -1.730e-01,\n",
+       "         -4.800e-02, -4.700e-02]],\n",
+       "\n",
+       "       [[ 1.081e+00, -2.931e+00,  6.330e-01, ..., -3.400e-02,\n",
+       "         -1.800e-02,  6.400e-02],\n",
+       "        [-3.349e+00, -1.862e+00,  1.275e+00, ...,  9.000e-03,\n",
+       "          1.100e-02,  1.700e-02],\n",
+       "        [ 3.056e+00,  2.772e+00, -3.975e+00, ...,  7.100e-02,\n",
+       "          2.800e-02,  6.500e-02],\n",
+       "        ...,\n",
+       "        [ 3.464e+00, -3.135e+00, -4.500e-02, ..., -3.730e-01,\n",
+       "         -1.370e-01,  6.630e-01],\n",
+       "        [-1.834e+00,  3.931e+00, -2.047e+00, ..., -2.470e-01,\n",
+       "         -5.820e-01,  3.050e-01],\n",
+       "        [-2.065e+00,  5.129e+00,  4.794e+00, ..., -6.620e-01,\n",
+       "         -2.640e-01,  6.940e-01]]], shape=(4, 13, 18073), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>38.5 39.5 36.5 ... 48.0 43.0 46.5</div><input id='attrs-cfd8139d-1961-4ebe-9c3d-92b0c5977e83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfd8139d-1961-4ebe-9c3d-92b0c5977e83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0991d93-62c5-4eb3-9569-402c2d9f4b8a' class='xr-var-data-in' type='checkbox'><label for='data-e0991d93-62c5-4eb3-9569-402c2d9f4b8a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[ 38.5,  39.5,  36.5, ...,  45. ,  43. ,  42. ],\n",
+       "        [ 34.5,  38.5,  37. , ...,  42.5,  41. ,  42. ],\n",
+       "        [ 38.5,  36. ,  38.5, ...,  42.5,  41. ,  42. ],\n",
+       "        ...,\n",
+       "        [ 36.5,  37.5,  38. , ...,  95. ,  96.5, 100. ],\n",
+       "        [ 35. ,  37.5,  37. , ...,  60.5,  73. ,  75.5],\n",
+       "        [ 35.5,  33.5,  36.5, ...,  43.5,  41.5,  43.5]],\n",
+       "\n",
+       "       [[ 41.5,  41.5,  38.5, ...,  43.5,  44.5,  45.5],\n",
+       "        [ 37. ,  40. ,  38.5, ...,  43. ,  41.5,  42.5],\n",
+       "        [ 41.5,  37.5,  40.5, ...,  41. ,  41. ,  41.5],\n",
+       "        ...,\n",
+       "        [ 38.5,  40. ,  41.5, ...,  89. ,  96. ,  96. ],\n",
+       "        [ 36.5,  41. ,  40.5, ...,  86. ,  87.5,  87. ],\n",
+       "        [ 38. ,  37. ,  40.5, ...,  49. ,  46.5,  46. ]],\n",
+       "\n",
+       "       [[ 32.5,  31.5,  30. , ...,  43. ,  45.5,  44.5],\n",
+       "        [ 29.5,  31. ,  29.5, ...,  43.5,  43.5,  43.5],\n",
+       "        [ 33. ,  29.5,  31. , ...,  43.5,  42. ,  42.5],\n",
+       "        ...,\n",
+       "        [ 29.5,  31. ,  33. , ...,  99.5,  95. ,  86. ],\n",
+       "        [ 29. ,  33.5,  33.5, ...,  94.5,  88.5,  87.5],\n",
+       "        [ 29.5,  31. ,  35. , ...,  41.5,  44. ,  50. ]],\n",
+       "\n",
+       "       [[ 33. ,  31.5,  30.5, ...,  43. ,  44. ,  42.5],\n",
+       "        [ 29.5,  30.5,  30. , ...,  43.5,  44.5,  43.5],\n",
+       "        [ 33. ,  29. ,  31. , ...,  41.5,  42. ,  41.5],\n",
+       "        ...,\n",
+       "        [ 29.5,  31.5,  33.5, ...,  91. ,  89.5,  96. ],\n",
+       "        [ 28.5,  33.5,  33.5, ...,  81. ,  71.5,  80. ],\n",
+       "        [ 30. ,  31. ,  34.5, ...,  48. ,  43. ,  46.5]]],\n",
+       "      shape=(4, 13, 18073), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>26 65 32 45 32 1 ... 91 87 86 84 88</div><input id='attrs-74f69510-5da1-4e88-a1e7-01735d537de8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74f69510-5da1-4e88-a1e7-01735d537de8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95bf7d72-9d9f-49f8-8428-74653b70379e' class='xr-var-data-in' type='checkbox'><label for='data-95bf7d72-9d9f-49f8-8428-74653b70379e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[ 26,  65,  32, ..., 100,  99,  95],\n",
+       "        [ 21,  58,  34, ...,  98,  96,  98],\n",
+       "        [ 20,  61,  50, ...,  98,  97,  97],\n",
+       "        ...,\n",
+       "        [ 46,  22,  64, ..., 100, 100, 100],\n",
+       "        [  7,   8,  29, ...,  57,  31,  36],\n",
+       "        [  9,  19,  35, ...,  96,  87,  89]],\n",
+       "\n",
+       "       [[ 31,  62,  32, ...,  94, 100, 100],\n",
+       "        [ 12,  56,  32, ...,  99,  98,  96],\n",
+       "        [ 23,  53,  46, ...,  95,  98,  97],\n",
+       "        ...,\n",
+       "        [ 42,  20,  70, ...,  99, 100, 100],\n",
+       "        [  7,   7,  30, ...,  97,  83,  85],\n",
+       "        [ 11,  21,  36, ...,  80,  72,  93]],\n",
+       "\n",
+       "       [[ 33,  45,  25, ...,  94, 100,  98],\n",
+       "        [  8,  38,  24, ...,  99, 100,  99],\n",
+       "        [ 11,  26,  36, ...,  97,  94,  97],\n",
+       "        ...,\n",
+       "        [ 24,  14,  64, ..., 100, 100,  98],\n",
+       "        [  3,   7,  23, ...,  94,  90,  97],\n",
+       "        [  8,  18,  28, ...,  80,  73,  69]],\n",
+       "\n",
+       "       [[ 42,  46,  22, ...,  96,  99,  97],\n",
+       "        [  5,  48,  22, ..., 100, 100, 100],\n",
+       "        [ 19,  32,  33, ...,  97,  96,  95],\n",
+       "        ...,\n",
+       "        [ 27,  13,  64, ..., 100, 100, 100],\n",
+       "        [  7,   5,  24, ...,  76,  50,  62],\n",
+       "        [ 13,  20,  31, ...,  86,  84,  88]]],\n",
+       "      shape=(4, 13, 18073), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.766 0.76 0.766 ... 74.7 74.71</div><input id='attrs-a55ec02e-d476-4301-8a55-2fb4ecbbd7a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a55ec02e-d476-4301-8a55-2fb4ecbbd7a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd70aedd-1080-4963-a4bb-b91f7ada2d69' class='xr-var-data-in' type='checkbox'><label for='data-dd70aedd-1080-4963-a4bb-b91f7ada2d69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure measured during AST ping</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([ 0.766,  0.76 ,  0.766, ..., 74.672, 74.703, 74.707],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>le_dist_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>42.22 42.22 42.22 ... 73.36 73.73</div><input id='attrs-7f3c0de6-4375-47e0-82c1-2632fb2f41f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f3c0de6-4375-47e0-82c1-2632fb2f41f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7539dee0-96d7-413e-afbd-5be9ae33d328' class='xr-var-data-in' type='checkbox'><label for='data-7539dee0-96d7-413e-afbd-5be9ae33d328' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Altimeter Range Leading Edge Algorithm</dd><dt><span>standard_name :</span></dt><dd>altimeter_range</dd></dl></div><div class='xr-var-data'><pre>array([42.22273 , 42.222515, 42.222153, ..., 73.09078 , 73.35817 ,\n",
+       "       73.73138 ], shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>le_quality_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 168.8 150.8 171.1</div><input id='attrs-68f066e2-66c7-49db-8a10-c14a1aa7fab2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68f066e2-66c7-49db-8a10-c14a1aa7fab2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ace59c6d-9b22-4368-8846-07366617a7c0' class='xr-var-data-in' type='checkbox'><label for='data-ace59c6d-9b22-4368-8846-07366617a7c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Altimeter Quality Indicator Leading Edge Algorithm</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   0.  ,   0.  , ..., 168.79, 150.79, 171.05],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_dist_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 73.21 73.48 73.87</div><input id='attrs-b3e4dce1-876a-4e92-bf55-b6a63b1265a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3e4dce1-876a-4e92-bf55-b6a63b1265a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad0962f4-0c82-44da-aea9-22de34da1fc4' class='xr-var-data-in' type='checkbox'><label for='data-ad0962f4-0c82-44da-aea9-22de34da1fc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Altimeter Range Acoustic Surface Tracking</dd><dt><span>standard_name :</span></dt><dd>altimeter_range</dd></dl></div><div class='xr-var-data'><pre>array([ 0.      ,  0.      ,  0.      , ..., 73.210526, 73.476036,\n",
+       "       73.86819 ], shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_quality_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 58.44 58.52 61.61</div><input id='attrs-043e8363-cbf8-4e3a-bc47-c8d20be06070' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-043e8363-cbf8-4e3a-bc47-c8d20be06070' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-550717ee-26bb-4f02-917b-877dea03a7da' class='xr-var-data-in' type='checkbox'><label for='data-550717ee-26bb-4f02-917b-877dea03a7da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Altimeter Quality Indicator Acoustic Surface Tracking</dd></dl></div><div class='xr-var-data'><pre>array([ 0.  ,  0.  ,  0.  , ..., 58.44, 58.52, 61.61],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_offset_time_alt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.3334 -0.3333 ... -0.3331 -0.3333</div><input id='attrs-8c7eb74e-d75b-4cd4-81e3-8c3923ca04e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c7eb74e-d75b-4cd4-81e3-8c3923ca04e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64927e71-1cd2-4937-ba97-52191fcf8ef6' class='xr-var-data-in' type='checkbox'><label for='data-64927e71-1cd2-4937-ba97-52191fcf8ef6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Acoustic Surface Tracking Time Offset to Velocity Ping</dd></dl></div><div class='xr-var-data'><pre>array([-0.3334, -0.3333, -0.3332, ..., -0.3333, -0.3331, -0.3333],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.4 12.4 12.4 12.4 ... 7.0 7.0 7.0</div><input id='attrs-2a316ee4-6443-43f2-a28b-6112a316f9ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a316ee4-6443-43f2-a28b-6112a316f9ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd6922c9-c0b0-4331-a132-820cc43d410d' class='xr-var-data-in' type='checkbox'><label for='data-fd6922c9-c0b0-4331-a132-820cc43d410d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.4, 12.4, 12.4, ...,  7. ,  7. ,  7. ],\n",
+       "      shape=(18073,), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>170 169 169 169 ... 194 194 194 194</div><input id='attrs-cada8132-eada-463a-a522-f666fad7741d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cada8132-eada-463a-a522-f666fad7741d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35aa781a-198c-4874-8580-d41e70e08c32' class='xr-var-data-in' type='checkbox'><label for='data-35aa781a-198c-4874-8580-d41e70e08c32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([170, 169, 169, ..., 194, 194, 194], shape=(18073,), dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.766 0.773 0.769 ... 74.83 74.74</div><input id='attrs-62243207-4af1-4be0-8280-6b5d74a4c0d9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62243207-4af1-4be0-8280-6b5d74a4c0d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2265ce8a-96d0-4d62-ab9a-0d4b2c8f5c85' class='xr-var-data-in' type='checkbox'><label for='data-2265ce8a-96d0-4d62-ab9a-0d4b2c8f5c85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([ 0.766,  0.773,  0.769, 25.605, 61.209,  0.777, 34.85 , 62.615,\n",
+       "       76.575, 76.654, 76.721, 76.75 , 76.721, 76.793, 76.756, 76.727,\n",
+       "       76.724, 76.687, 76.631, 76.559, 76.467, 76.287, 76.343, 76.16 ,\n",
+       "       76.039, 75.903, 75.822, 75.618, 75.482, 75.335, 75.275, 75.104,\n",
+       "       74.998, 74.829, 74.743], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>le_dist_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>42.22 42.22 42.25 ... 72.77 73.4</div><input id='attrs-e65bc53b-7e50-44a5-8d43-ffc3c3af4eb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e65bc53b-7e50-44a5-8d43-ffc3c3af4eb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ab0f174-5fe2-420c-a30f-be54c4a854a7' class='xr-var-data-in' type='checkbox'><label for='data-8ab0f174-5fe2-420c-a30f-be54c4a854a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Altimeter Range Leading Edge Algorithm</dd><dt><span>standard_name :</span></dt><dd>altimeter_range</dd></dl></div><div class='xr-var-data'><pre>array([42.22273 , 42.22245 , 42.248127, 53.838898, 60.334473, 42.095585,\n",
+       "       41.693676, 60.747128, 74.52789 , 75.47511 , 75.798546, 75.46673 ,\n",
+       "       75.08749 , 75.53308 , 75.00033 , 75.2663  , 75.62667 , 75.66341 ,\n",
+       "       75.13237 , 75.59258 , 75.48645 , 74.45196 , 75.09751 , 74.65656 ,\n",
+       "       74.63918 , 74.48755 , 74.70199 , 74.48076 , 74.06819 , 73.60065 ,\n",
+       "       73.40783 , 73.81639 , 74.335014, 72.76904 , 73.397766],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>le_quality_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 67.05 206.4 146.7</div><input id='attrs-28dc13a1-c8d1-4d28-b48a-1e066bf78b1f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28dc13a1-c8d1-4d28-b48a-1e066bf78b1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1f3939d-8e78-4087-9f40-cc8241ee0cce' class='xr-var-data-in' type='checkbox'><label for='data-b1f3939d-8e78-4087-9f40-cc8241ee0cce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Altimeter Quality Indicator Leading Edge Algorithm</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   0.  ,   0.  , 108.67, 135.71,   0.  ,   0.  , 189.97,\n",
+       "       119.84, 127.84, 119.72, 184.63, 123.2 , 213.47, 154.79, 235.96,\n",
+       "       135.53, 126.95, 159.85, 207.4 ,  66.16, 212.89, 127.26, 196.62,\n",
+       "       125.15, 113.1 , 150.91, 219.6 , 130.77, 113.49, 104.92, 227.87,\n",
+       "        67.05, 206.42, 146.73], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_dist_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 74.34 72.9 73.52</div><input id='attrs-8ab06b4f-d423-414d-a34c-54b3335244fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ab06b4f-d423-414d-a34c-54b3335244fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ac71329-61c4-40f5-89fe-c081b3e90a79' class='xr-var-data-in' type='checkbox'><label for='data-7ac71329-61c4-40f5-89fe-c081b3e90a79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Altimeter Range Acoustic Surface Tracking</dd><dt><span>standard_name :</span></dt><dd>altimeter_range</dd></dl></div><div class='xr-var-data'><pre>array([ 0.      ,  0.      ,  0.      ,  0.      , 60.475662,  0.      ,\n",
+       "       41.92075 , 61.05163 , 74.65894 , 75.74271 , 76.07448 , 75.692055,\n",
+       "       75.19689 , 75.82613 , 75.08403 , 75.32452 , 75.729965, 76.012314,\n",
+       "       75.22676 , 75.71552 , 75.81318 , 74.594826, 75.21046 , 74.7399  ,\n",
+       "       75.11347 , 74.77125 , 74.823235, 74.63242 , 74.20987 , 73.8131  ,\n",
+       "       73.52494 , 73.96451 , 74.34137 , 72.897064, 73.523224],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_quality_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 53.5 65.63 61.81</div><input id='attrs-e79fa286-bc6e-40ea-9cea-2846549b3dfb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e79fa286-bc6e-40ea-9cea-2846549b3dfb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b4c1612-fd31-4410-b834-323e531daf2b' class='xr-var-data-in' type='checkbox'><label for='data-4b4c1612-fd31-4410-b834-323e531daf2b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>long_name :</span></dt><dd>Altimeter Quality Indicator Acoustic Surface Tracking</dd></dl></div><div class='xr-var-data'><pre>array([ 0.  ,  0.  ,  0.  ,  0.  , 52.53,  0.  , 23.02, 68.83, 57.15,\n",
+       "       67.61, 54.94, 74.65, 53.76, 73.48, 61.66, 73.67, 56.12, 64.72,\n",
+       "       65.88, 67.59, 49.72, 65.22, 54.34, 65.64, 50.62, 63.58, 60.39,\n",
+       "       68.26, 58.79, 66.06, 56.41, 66.77, 53.5 , 65.63, 61.81],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ast_offset_time_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-4669a56d-c4b5-4b96-bec9-f3503c81a85f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4669a56d-c4b5-4b96-bec9-f3503c81a85f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-650076c8-e23e-4751-8cba-8cb4ab824210' class='xr-var-data-in' type='checkbox'><label for='data-650076c8-e23e-4751-8cba-8cb4ab824210' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Acoustic Surface Tracking Time Offset to Velocity Ping</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nsamp_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>2583 2583 2583 ... 2583 2583 2583</div><input id='attrs-bd232f89-61fd-4b08-b886-884b1e9eddec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd232f89-61fd-4b08-b886-884b1e9eddec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d874b6e6-09ea-4331-b20d-b20a4b994fe7' class='xr-var-data-in' type='checkbox'><label for='data-d874b6e6-09ea-4331-b20d-b20a4b994fe7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Number of Altimeter Samples</dd></dl></div><div class='xr-var-data'><pre>array([2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583,\n",
+       "       2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583,\n",
+       "       2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583, 2583,\n",
+       "       2583, 2583], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dsamp_altraw</span></div><div class='xr-var-dims'>(time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.024 0.024 0.024 ... 0.024 0.024</div><input id='attrs-72072e2c-baa1-4ae1-8d49-839c9f13580e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-72072e2c-baa1-4ae1-8d49-839c9f13580e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef658323-3cc0-47ac-87cf-a987a54a5c69' class='xr-var-data-in' type='checkbox'><label for='data-ef658323-3cc0-47ac-87cf-a987a54a5c69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Altimeter Distance between Samples</dd></dl></div><div class='xr-var-data'><pre>array([0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024,\n",
+       "       0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024,\n",
+       "       0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024,\n",
+       "       0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024, 0.024],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>samp_altraw</span></div><div class='xr-var-dims'>(n_altraw, time_altraw)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>13.98 9.539 14.62 ... 11.14 15.56</div><input id='attrs-111f42b3-668f-431d-bd58-507c396a476e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-111f42b3-668f-431d-bd58-507c396a476e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26b27615-b591-4d06-bbf0-84dc0d373766' class='xr-var-data-in' type='checkbox'><label for='data-26b27615-b591-4d06-bbf0-84dc0d373766' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Altimeter Samples</dd></dl></div><div class='xr-var-data'><pre>array([[1.39804688e+01, 9.53906250e+00, 1.46250000e+01, ...,\n",
+       "        1.00000000e+01, 1.39804688e+01, 2.00468750e+01],\n",
+       "       [0.00000000e+00, 1.81328125e+01, 2.25078125e+01, ...,\n",
+       "        1.71601562e+01, 1.78515625e+01, 1.39804688e+01],\n",
+       "       [1.00000000e+01, 1.91406250e+01, 3.01562500e+00, ...,\n",
+       "        6.02343750e+00, 1.69921875e+01, 1.92968750e+01],\n",
+       "       ...,\n",
+       "       [3.01562500e+00, 3.90625000e-03, 1.41484375e+01, ...,\n",
+       "        6.99218750e+00, 1.30078125e+01, 3.90625000e-03],\n",
+       "       [3.01562500e+00, 1.30078125e+01, 1.23046875e+01, ...,\n",
+       "        1.81328125e+01, 1.61250000e+01, 1.39804688e+01],\n",
+       "       [1.50546875e+01, 1.61250000e+01, 1.78515625e+01, ...,\n",
+       "        6.99218750e+00, 1.11406250e+01, 1.55625000e+01]],\n",
+       "      shape=(2583, 35), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-a19a017f-4537-476c-81e2-5db05586ce87' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a19a017f-4537-476c-81e2-5db05586ce87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b179e896-c912-4d66-8427-42b203554fea' class='xr-var-data-in' type='checkbox'><label for='data-b179e896-c912-4d66-8427-42b203554fea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(18073,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-28428c19-d5bd-4372-a913-28a77fa60127' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28428c19-d5bd-4372-a913-28a77fa60127' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-150a8de7-bd79-4c6a-9a3b-f781d4daa1c6' class='xr-var-data-in' type='checkbox'><label for='data-150a8de7-bd79-4c6a-9a3b-f781d4daa1c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(18073,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-6d305b4d-d4c2-42d5-b8ac-663a59d6ef53' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6d305b4d-d4c2-42d5-b8ac-663a59d6ef53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-877d4613-bd9d-440b-af1b-1cb901921e6f' class='xr-var-data-in' type='checkbox'><label for='data-877d4613-bd9d-440b-af1b-1cb901921e6f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(18073,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0</div><input id='attrs-3b765d2c-9f89-434c-be62-8478b3e5900f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3b765d2c-9f89-434c-be62-8478b3e5900f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e90cd8f-c7af-472d-94af-e913f025c104' class='xr-var-data-in' type='checkbox'><label for='data-9e90cd8f-c7af-472d-94af-e913f025c104' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], shape=(18073,), dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.462 0.0 -1.462 ... 0.0 0.532</div><input id='attrs-3f3f20fa-e5fc-4603-af02-b4c1b8c63b3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f3f20fa-e5fc-4603-af02-b4c1b8c63b3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0e015c2-ad24-4295-bd56-b42e6d4dc508' class='xr-var-data-in' type='checkbox'><label for='data-f0e015c2-ad24-4295-bd56-b42e6d4dc508' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.4619,  0.    , -1.4619,  0.    ],\n",
+       "       [ 0.    , -1.4619,  0.    ,  1.4619],\n",
+       "       [ 0.532 ,  0.    ,  0.532 ,  0.    ],\n",
+       "       [ 0.    ,  0.532 ,  0.    ,  0.532 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.5221 -0.5163 ... 0.9992 0.9992</div><input id='attrs-2cf23729-32c9-485e-b9ec-d880bc87892e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2cf23729-32c9-485e-b9ec-d880bc87892e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ef3281d-b14a-429d-83a8-6d4c91dce910' class='xr-var-data-in' type='checkbox'><label for='data-8ef3281d-b14a-429d-83a8-6d4c91dce910' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.52207047, -0.51634324, -0.5209149 , ..., -0.54248476,\n",
+       "         -0.54013205, -0.5434986 ],\n",
+       "        [-0.71620005, -0.71592724, -0.69886136, ..., -0.8391961 ,\n",
+       "         -0.84069633, -0.83851576],\n",
+       "        [-0.46314135, -0.4699338 , -0.49014327, ...,  0.03821341,\n",
+       "          0.03856222,  0.03873662]],\n",
+       "\n",
+       "       [[-0.02522682, -0.00602216,  0.03262919, ...,  0.83965343,\n",
+       "          0.8411746 ,  0.83897805],\n",
+       "        [-0.5298138 , -0.54569435, -0.59008396, ..., -0.5430822 ,\n",
+       "         -0.54072726, -0.5441205 ],\n",
+       "        [ 0.8477387 ,  0.8379626 ,  0.8066822 , ..., -0.00662736,\n",
+       "         -0.00627847, -0.00697602]],\n",
+       "\n",
+       "       [[-0.8525292 , -0.85636055, -0.8529848 , ...,  0.02631467,\n",
+       "          0.02612993,  0.02692689],\n",
+       "        [ 0.45426297,  0.4355064 ,  0.4042198 , ...,  0.02849078,\n",
+       "          0.02904635,  0.02870771],\n",
+       "        [ 0.2585327 ,  0.27745417,  0.3301868 , ...,  0.9992476 ,\n",
+       "          0.99923646,  0.9992251 ]]], shape=(3, 3, 18073), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-650c496b-7f37-49e0-be28-fb2630ad357b' class='xr-section-summary-in' type='checkbox'  ><label for='section-650c496b-7f37-49e0-be28-fb2630ad357b' class='xr-section-summary' >Indexes: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-9e883d52-e0f6-48b3-8a5a-a9d0bd489dab' class='xr-index-data-in' type='checkbox'/><label for='index-9e883d52-e0f6-48b3-8a5a-a9d0bd489dab' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2024-10-22 19:29:36.334399938&#x27;,\n",
+       "               &#x27;2024-10-22 19:29:37.334399938&#x27;,\n",
+       "               &#x27;2024-10-22 19:29:38.334399938&#x27;,\n",
+       "               &#x27;2024-10-22 19:29:39.334399938&#x27;,\n",
+       "               &#x27;2024-10-22 19:29:40.334399938&#x27;,\n",
+       "               &#x27;2024-10-22 19:29:41.334399938&#x27;,\n",
+       "               &#x27;2024-10-22 19:29:42.334399938&#x27;,\n",
+       "               &#x27;2024-10-22 19:29:43.334399938&#x27;,\n",
+       "               &#x27;2024-10-22 19:29:44.334399938&#x27;,\n",
+       "               &#x27;2024-10-22 19:29:45.334399938&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2024-10-23 04:10:31.334399938&#x27;,\n",
+       "               &#x27;2024-10-23 04:10:32.334399938&#x27;,\n",
+       "               &#x27;2024-10-23 04:10:33.334399938&#x27;,\n",
+       "               &#x27;2024-10-23 04:10:34.334500074&#x27;,\n",
+       "               &#x27;2024-10-23 04:10:35.334399938&#x27;,\n",
+       "               &#x27;2024-10-23 04:10:36.334399938&#x27;,\n",
+       "               &#x27;2024-10-23 04:10:37.334399938&#x27;,\n",
+       "               &#x27;2024-10-23 04:10:38.334399938&#x27;,\n",
+       "               &#x27;2024-10-23 04:10:39.334199905&#x27;,\n",
+       "               &#x27;2024-10-23 04:10:40.334399938&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=18073, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_altraw</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-46d4f296-97f9-46b3-a2f5-06c419429b35' class='xr-index-data-in' type='checkbox'/><label for='index-46d4f296-97f9-46b3-a2f5-06c419429b35' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2024-10-22 19:29:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-22 19:46:39.000999927&#x27;,\n",
+       "               &#x27;2024-10-22 19:59:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-22 20:16:39.000999927&#x27;,\n",
+       "               &#x27;2024-10-22 20:29:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-22 20:46:39.000999927&#x27;,\n",
+       "               &#x27;2024-10-22 20:59:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-22 21:16:39.000999927&#x27;,\n",
+       "               &#x27;2024-10-22 21:29:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-22 21:46:39.001100063&#x27;,\n",
+       "               &#x27;2024-10-22 21:59:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-22 22:16:39.001100063&#x27;,\n",
+       "               &#x27;2024-10-22 22:29:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-22 22:46:39.001100063&#x27;,\n",
+       "               &#x27;2024-10-22 22:59:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-22 23:16:39.001100063&#x27;,\n",
+       "               &#x27;2024-10-22 23:29:36.000900030&#x27;,\n",
+       "               &#x27;2024-10-22 23:46:39.000999927&#x27;,\n",
+       "               &#x27;2024-10-22 23:59:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 00:16:39.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 00:29:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 00:46:39.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 00:59:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 01:16:39.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 01:29:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 01:46:39.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 01:59:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 02:16:39.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 02:29:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 02:46:39.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 02:59:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 03:16:39.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 03:29:36.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 03:46:39.000999927&#x27;,\n",
+       "               &#x27;2024-10-23 03:59:36.000999927&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_altraw&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e4fcb6f5-a6f6-407e-992e-d0c83ec17643' class='xr-index-data-in' type='checkbox'/><label for='index-e4fcb6f5-a6f6-407e-992e-d0c83ec17643' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([38.7, 42.2, 45.7, 49.2, 52.7, 56.2, 59.7, 63.2, 66.7, 70.2, 73.7, 77.2,\n",
+       "       80.7],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;range&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>beam</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b0583c1e-7301-4de4-b940-5df1c71c574a' class='xr-index-data-in' type='checkbox'/><label for='index-b0583c1e-7301-4de4-b940-5df1c71c574a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;beam&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dir</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-97d2bc5f-5040-4bef-accb-984b31cbe1da' class='xr-index-data-in' type='checkbox'/><label for='index-97d2bc5f-5040-4bef-accb-984b31cbe1da' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;dir&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dirIMU</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-3d8b080c-dcd5-4909-88de-4e2aba2e6644' class='xr-index-data-in' type='checkbox'/><label for='index-3d8b080c-dcd5-4909-88de-4e2aba2e6644' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dirIMU&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x1</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-5fe2f197-9e3c-4a27-893b-d05d20fa45fb' class='xr-index-data-in' type='checkbox'/><label for='index-5fe2f197-9e3c-4a27-893b-d05d20fa45fb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;x1&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x2</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-be361aad-4461-4a2a-acb5-e6fee66f1068' class='xr-index-data-in' type='checkbox'/><label for='index-be361aad-4461-4a2a-acb5-e6fee66f1068' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;x2&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>earth</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-fec6f7f8-b5c7-474c-b73c-fdeb1cebf483' class='xr-index-data-in' type='checkbox'/><label for='index-fec6f7f8-b5c7-474c-b73c-fdeb1cebf483' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;earth&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>inst</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-e5d69dd7-6678-4b81-be6e-ebbb72fb8b3c' class='xr-index-data-in' type='checkbox'/><label for='index-e5d69dd7-6678-4b81-be6e-ebbb72fb8b3c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;inst&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-91509bc0-29a8-4fb5-8cb7-835ecfdb2ae4' class='xr-section-summary-in' type='checkbox'  ><label for='section-91509bc0-29a8-4fb5-8cb7-835ecfdb2ae4' class='xr-section-summary' >Attributes: <span>(39)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2024-10-22 19:29:32\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature250\\&quot;,SN=104922&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2215, &quot;FPGA&quot;: 186, &quot;DIGITAL&quot;: &quot;\\&quot;I-5\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-1\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;C-1(High-Power 4 Channel)\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;I-0\\&quot;&quot;, &quot;BOOT&quot;: 25, &quot;FWMINOR&quot;: 15}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=250,TTR=2.4444,TTRB5=2.0000,TTRB5AUX=0.0000,AUXRS=0&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 471.15, &quot;BURST&quot;: 384.15, &quot;AVG&quot;: 90.34, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 471.15}, &quot;MEM&quot;: {&quot;PLAN&quot;: 1.141, &quot;BURST&quot;: 0.649, &quot;AVG&quot;: 0.492, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1.141}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: 1.15, &quot;BURSTHORZ&quot;: 6.98, &quot;BEAM5&quot;: -9.99, &quot;AVGBEAM&quot;: 0.56, &quot;BURSTBEAM&quot;: 3.37}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 1, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 35.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1800, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S104922A004_PWS_SITE_02.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 250, &quot;NSTT&quot;: 0}, &quot;AVG&quot;: {&quot;NC&quot;: 39, &quot;CS&quot;: 2.0, &quot;BD&quot;: 0.5, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: -15.0, &quot;AI&quot;: 120, &quot;VP&quot;: 0.0, &quot;VR&quot;: 5.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 120, &quot;NB&quot;: 4, &quot;CH&quot;: 0, &quot;MUX&quot;: 0, &quot;BW&quot;: &quot;\\&quot;BROAD\\&quot;&quot;, &quot;ALTI&quot;: 0, &quot;BT&quot;: 0, &quot;ICE&quot;: 0, &quot;ALTISTART&quot;: 0.5, &quot;ALTIEND&quot;: 150.0, &quot;RAWALTI&quot;: 1}, &quot;XFAVG&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.4619, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.4619, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.4619, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.4619, &quot;M31&quot;: 0.532, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.532, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.532, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.532}, &quot;BURST&quot;: {&quot;NC&quot;: 13, &quot;NB&quot;: 4, &quot;CS&quot;: 3.5, &quot;BD&quot;: 35.2, &quot;CY&quot;: &quot;\\&quot;BEAM\\&quot;&quot;, &quot;PL&quot;: -15.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1024, &quot;VR&quot;: 5.0, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 1, &quot;CH&quot;: 0, &quot;ALTI&quot;: 1, &quot;VR5&quot;: 5.0, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 1, &quot;ALTISTART&quot;: 42.0, &quot;ALTIEND&quot;: 104.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.4619, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.4619, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.4619, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.4619, &quot;M31&quot;: 0.532, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.532, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.532, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.532}, &quot;READALTIBURST&quot;: &quot;EN=1,START=42.00,END=104.00,SAMPSIZE=0.024,NB=1,NSAMP=2583,RAW=1&quot;, &quot;USER&quot;: {&quot;POFF&quot;: 9.5, &quot;DECL&quot;: 0.0, &quot;HX&quot;: 0, &quot;HY&quot;: 0, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;ON24H\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AUTOZUPDOWN\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 72, &quot;DY&quot;: 163, &quot;DZ&quot;: -42, &quot;M11&quot;: 32767, &quot;M12&quot;: 477, &quot;M13&quot;: -250, &quot;M21&quot;: -118, &quot;M22&quot;: 31551, &quot;M23&quot;: -399, &quot;M31&quot;: 838, &quot;M32&quot;: 376, &quot;M33&quot;: 32316}, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=61991026688,TC=62260248576,VS=62260248576,FF=4092,TF=4095&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=20.00,PHI=0.00,FREQ=250,BW=25,BRD=1,HWBEAM=1,ZNOM=100.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=20.00,PHI=-90.00,FREQ=250,BW=25,BRD=1,HWBEAM=2,ZNOM=100.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=20.00,PHI=180.00,FREQ=250,BW=25,BRD=1,HWBEAM=3,ZNOM=100.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=20.00,PHI=90.00,FREQ=250,BW=25,BRD=1,HWBEAM=4,ZNOM=100.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=500,BW=25,BRD=1,HWBEAM=5,ZNOM=100.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.95754e+01,P1=-6.89010e-02,P2=3.07926e-03,P3=8.38340e-05,P4=6.24624e-06,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.84575e+01,P1=-4.85768e-02,P2=3.40215e-03,P3=4.97871e-05,P4=5.28907e-06,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=2.03578e+01,P1=2.87348e-02,P2=1.24284e-03,P3=9.11659e-06,P4=9.46557e-06,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.98482e+01,P1=9.94687e-03,P2=3.95698e-03,P3=1.23846e-05,P4=5.44124e-06,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=5.14952e+00,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;639HSK16KKMKB\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;WULC7672JKMKB\\&quot;,DESC=\\&quot;Wave Mode\\&quot;,TYPE=6&quot;, &quot;KEY=\\&quot;8MTRYSYPJKMKB\\&quot;,DESC=\\&quot;64GB Recorder\\&quot;,TYPE=10&quot;], &quot;CALCOMPGET&quot;: &quot;DX=72,DY=163,DZ=-42,M11=32767,M12=477,M13=-250,M21=-118,M22=31551,M23=-399,M31=838,M32=376,M33=32316&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99836&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=-4.726771E-03,B1X=-2.648151E-04,B2X=-2.372674E-06,B3X=4.496909E-08,A1X=-1.020020E-04,A2X=1.769976E-06,A3X=-1.568007E-09&quot;, &quot;AY=1.000000E+00,B0Y=1.559532E-02,B1Y=-1.851641E-04,B2Y=-1.864571E-06,B3Y=-1.016134E-07,A1Y=-1.244390E-04,A2Y=2.423802E-06,A3Y=1.712951E-07&quot;, &quot;AZ=1.000000E+00,B0Z=-9.057428E-03,B1Z=1.972058E-04,B2Z=5.130616E-06,B3Z=-3.403830E-08,A1Z=1.938282E-04,A2Z=1.197075E-06,A3Z=-4.228993E-07&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5291115000e+02,RB0=3.7937528130e-01,RB1=-2.1489579690e-01,RB2=4.4181650000e-04,RB3=6.5130350000e-09,T0=-3.1473080000e+03,T1=2.4586100000e+00,T2=-6.5718281250e-04,T3=6.1275925000e-08,ID=\\&quot;P059353\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=1.4675400000e-01,A1=3.9377600000e-04,A2=-1.2027480470e-07,A3=1.1867438750e-11,B0=-6.2100006250e-01,B1=6.3748125000e-04,B2=-1.8018650000e-07,B3=1.6830001560e-11&quot;, &quot;C0=7.9542968750e-04,C1=-6.7488718750e-07,C2=1.9400940630e-10,C3=-1.8681940630e-14,D0=-3.0979950000e-06,D1=2.6566440630e-09,D2=-7.6620243750e-13,D3=7.3948556250e-17&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.98619,M12=0.01139,M13=0.01828,M21=-0.01080,M22=1.00513,M23=-0.00519,M31=-0.01061,M32=-0.00616,M33=0.96537&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.66,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature250</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: true, &quot;altraw&quot;: false, &quot;ast&quot;: true, &quot;echo&quot;: false, &quot;ahrs&quot;: false, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>13</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>10.31</dd><dt><span>SerialNum :</span></dt><dd>104922</dd><dt><span>nominal_corr :</span></dt><dd>89</dd><dt><span>cell_size :</span></dt><dd>3.5</dd><dt><span>blank_dist :</span></dt><dd>35.2</dd><dt><span>power_level_dB :</span></dt><dd>-15.0</dd><dt><span>tilt_over_5deg :</span></dt><dd>0</dd><dt><span>tilt_over_10deg :</span></dt><dd>0</dd><dt><span>multibeam_alt :</span></dt><dd>0</dd><dt><span>n_beams_alt :</span></dt><dd>1</dd><dt><span>power_level_alt :</span></dt><dd>high</dd><dt><span>burst_config_alt :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: false, &quot;amp&quot;: false, &quot;corr&quot;: false, &quot;le&quot;: true, &quot;altraw&quot;: true, &quot;ast&quot;: true, &quot;echo&quot;: false, &quot;ahrs&quot;: false, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_alt :</span></dt><dd>0</dd><dt><span>coord_sys_axes_alt :</span></dt><dd>beam</dd><dt><span>ambig_vel_alt :</span></dt><dd>0.0</dd><dt><span>SerialNum_alt :</span></dt><dd>104922</dd><dt><span>nominal_corr_alt :</span></dt><dd>0</dd><dt><span>cell_size_alt :</span></dt><dd>0.0</dd><dt><span>blank_dist_alt :</span></dt><dd>42.0</dd><dt><span>power_level_dB_alt :</span></dt><dd>-26.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>up</dd><dt><span>orient_status :</span></dt><dd>auto_UD</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;mag&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>beam</dd><dt><span>fs :</span></dt><dd>1</dd><dt><span>bandwidth :</span></dt><dd>&quot;BROAD&quot;</dd><dt><span>has_imu :</span></dt><dd>0</dd><dt><span>beam_angle :</span></dt><dd>20</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 11MB\n",
+       "Dimensions:                 (time: 18073, time_altraw: 35, range: 13, beam: 4,\n",
+       "                             dir: 4, dirIMU: 3, n_altraw: 2583, x1: 4, x2: 4,\n",
+       "                             earth: 3, inst: 3)\n",
+       "Coordinates:\n",
+       "  * time                    (time) datetime64[ns] 145kB 2024-10-22T19:29:36.3...\n",
+       "  * time_altraw             (time_altraw) datetime64[ns] 280B 2024-10-22T19:2...\n",
+       "  * range                   (range) float64 104B 38.7 42.2 45.7 ... 77.2 80.7\n",
+       "  * beam                    (beam) int32 16B 1 2 3 4\n",
+       "  * dir                     (dir) int32 16B 1 2 3 4\n",
+       "  * dirIMU                  (dirIMU) <U1 12B 'X' 'Y' 'Z'\n",
+       "  * x1                      (x1) int32 16B 1 2 3 4\n",
+       "  * x2                      (x2) int32 16B 1 2 3 4\n",
+       "  * earth                   (earth) <U1 12B 'E' 'N' 'U'\n",
+       "  * inst                    (inst) <U1 12B 'X' 'Y' 'Z'\n",
+       "Dimensions without coordinates: n_altraw\n",
+       "Data variables: (12/39)\n",
+       "    c_sound                 (time) float32 72kB 1.503e+03 ... 1.485e+03\n",
+       "    temp                    (time) float32 72kB 13.93 13.92 13.92 ... 8.23 8.23\n",
+       "    pressure                (time) float32 72kB 0.768 0.765 ... 74.71 74.71\n",
+       "    heading                 (time) float32 72kB 216.1 215.8 ... 212.7 212.9\n",
+       "    pitch                   (time) float32 72kB -27.59 -28.03 ... 2.21 2.22\n",
+       "    roll                    (time) float32 72kB 73.04 71.68 67.74 ... -0.36 -0.4\n",
+       "    ...                      ...\n",
+       "    low_volt_skip           (time) uint8 18kB 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0\n",
+       "    active_config           (time) uint8 18kB 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0\n",
+       "    telemetry_data          (time) uint8 18kB 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0\n",
+       "    boost_running           (time) uint8 18kB 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0\n",
+       "    beam2inst_orientmat     (x1, x2) float32 64B 1.462 0.0 -1.462 ... 0.0 0.532\n",
+       "    orientmat               (earth, inst, time) float32 651kB -0.5221 ... 0.9992\n",
+       "Attributes: (12/39)\n",
+       "    filehead_config:       {\"CLOCKSTR\": {\"TIME\": \"\\\"2024-10-22 19:29:32\\\"\"}, ...\n",
+       "    inst_model:            Signature250\n",
+       "    inst_make:             Nortek\n",
+       "    inst_type:             ADCP\n",
+       "    burst_config:          {\"press_valid\": true, \"temp_valid\": true, \"compass...\n",
+       "    n_cells:               13\n",
+       "    ...                    ...\n",
+       "    rotate_vars:           ['vel', 'accel', 'mag']\n",
+       "    coord_sys:             beam\n",
+       "    fs:                    1\n",
+       "    bandwidth:             \"BROAD\"\n",
+       "    has_imu:               0\n",
+       "    beam_angle:            20"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_waves"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "05097477",
+   "metadata": {},
+   "source": [
+    "### 2. Review and QC Altimeter Measurements\n",
+    "\n",
+    "Now that we've read in our data, our next step is to check the quality of the water surface measurements. We can do this by plotting the 'pressure_alt', 'ast_dist_alt' and 'le_dist_alt' variables.\n",
+    "\n",
+    "Since this dataset is a clip of the very start of a deployment, we can see that the instrument began recording before it was on the seafloor. Our next move will be to trim those measurements off."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "91ae222f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x20f3d5e2f90>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "ds_waves[\"ast_dist_alt\"].plot(label=\"Altimeter AST\")\n",
+    "ds_waves[\"le_dist_alt\"].plot(label=\"Altimeter LE\")\n",
+    "ds_waves[\"pressure_alt\"].plot(label=\"Pressure Sensor\")\n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "5beaac54",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Range [m]')"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "# Trim time to after Oct 22, 2024 21:30\n",
+    "time_slc = slice(np.datetime64(\"2024-10-22T21:30\"), None)\n",
+    "# Trim time for every time variable\n",
+    "ds_waves = ds_waves.sel(time=time_slc, time_altraw=time_slc)\n",
+    "\n",
+    "ds_waves[\"ast_dist_alt\"].plot(label=\"Altimeter AST\")\n",
+    "ds_waves[\"le_dist_alt\"].plot(label=\"Altimeter LE\")\n",
+    "ds_waves[\"pressure_alt\"].plot(label=\"Pressure\")\n",
+    "plt.legend()\n",
+    "plt.ylabel(\"Range [m]\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b16888a6",
+   "metadata": {},
+   "source": [
+    "In the plot above we can see a couple things. One, our altimeter is operating in pulses of approximately 20 minutes, and two, our pressure sensor appears like it was not zeroed perfectly before deployment. This can be due to multiple reasons, and it is always a good thing to verify in post. We can calculate water depth from the pressure reading next and verify it against the altimeter measurements.\n",
+    "\n",
+    "To do so, we can check that the pressure sensor was zeroed properly by looking at the pressure data immediately before deployment, where it is reading ~0.7 dBar. Adjusting the pressure measurement by -0.7 dBar appears to then correct the depth measurement when comparing it to the altimeter readings."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "e65471e1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Range [m]')"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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3GTNmDBEREUyYMAGZTMaxY8eIiooqzz6KjIxk06ZN9O/fH7Vajb+/v0nzzCElJYUjR45UOVaWtQSQkZFBYmJilfPe3t42s/xYg9OzmQQCV0MkZgsEDZd58+YxZMgQgxmy48eP58iRIxw6dKjGuX79+vHoo49y5513EhQUxEcffWQzmYYPH87q1avZsGEDvXr1ok+fPnz22We0aNGifMynn37Khg0biIiIoFu3bibPM4fffvuNbt26VXl899135eenTp1KaGholcdXX31l3S9vIySdsVy0BkJWVha+vr5kZmaK1gaNhGOXM7h1zk4AYmYZriptkLf1X27HVZ3p+Op2e4gmEDQYCgoKiI6OpmXLli5Ta0RQ/6jtfWTO9VtYZgSNlpTsQlYeiadQU9UPLYrmCQQCQf1CKDOCRsttX+/k6cVH+HLTOWeLIhAIBAIrEMqMwCEkZxUw5qvtLN4X62xRyonPyAfg3xNJTpZEIBAIBNYglBmBQ5i17jTH47N4eXmUs0UB4Hh8prNFEAgEAoGNEMqMwCHkFdqnPoOljPlqh7NFEAgEAoGNEMqMoMHRsPPzBAKBQFAdocwIBAKBQCCo1whlRtAgaSfFEiFZGNjrRMtOak4hv+2NJadQ4zwhBAKBoJ4h2hkIGhzygjTWq18ufWV923tHMvnHvZxOzGZf9FVm39XN2eIIBAJBvUBYZgQNDlV2nFXzdZLzumafTswGYO3xxDpGCgSC+kpMTAySJNXogySwHKHMuAANvKMEoO8/54y94tLy+PNAHJoSbfmx2Kt5AHSRzvOB4gf8tBlV57tABeBCjbbuQQKBwCLuv/9+JElCkiSUSiVNmzZl6NChzJ8/H63Wtp+9+++/n9tuu82mawpqIpQZJ3M0LoOu72zgt72uU0yuIXHDR1t4YekxFu6KKT+2N/oqXuSxUv0mdyu2ML3gW4fKpNPpygv2CQQC5zBixAgSEhKIiYlh7dq1DB48mKeffpoxY8ag0YiYtfqGUGaczNOLD5OZX8yrf7lGMbmGyp6LaVVe/6yaVf48QnvZobLMWnua/rM28+P2iw7dVyAQVKBWqwkJCaFZs2Z0796dV199lZUrV7J27VoWLlwIQGZmJg8//DDBwcH4+Phw0003cfTo0fI13n77bbp27crcuXOJiIjAw8ODCRMmkJGRUX7+p59+YuXKleWWoK1bt5bPv3jxIoMHD8bDw4MuXbqwe/duB/4FGhZCmWnEJGYWcPs3O1l5JN7ue7maJ6277LxD99PpdGTmFwMwd5teifnfmlMOlcGZxGfk88gvB9gXnVb3YEG9RafTkVec55SHLdz1N910E126dGH58uXodDpGjx5NYmIi//zzDwcPHqR79+7cfPPNpKVVvI/Pnz/PkiVLWLVqFevWrePIkSM88cQTADz//PNMnDix3AqUkJBAv379yue+9tprPP/88xw5coS2bdty9913C6uQhYhspkbMO6tPcCg2g0OxRxjbtZmzxbEdVn6pZRfY/svk7b9P8NPuSyyY2svma9cHnltyhD0X01h/IomYWaOdLY7ATuRr8un9W2+n7L130l48lB5Wr9O+fXuOHTvGli1biIqKIjk5GbVaDcAnn3zCihUrWLp0KQ8//DAABQUF/PTTT4SHhwPw1VdfMXr0aD799FNCQkJwd3ensLCQkJCQGns9//zzjB6t/zzMnDmTDh06cP78edq3b2/179HYEJaZRkxWvrgDcBQ/7b4EwMfrzjhZEudwOV3ECAnqBzqdDkmSOHjwIDk5OQQGBuLl5VX+iI6O5sKFC+XjmzdvXq7IAPTt2xetVsuZM3V/1jt37lz+PDQ0FIDk5GQb/jaNB2GZETQSXMzPJRA0QNwV7uydtNdpe9uCU6dO0bJlS7RaLaGhoVViXMrw8/MzOl8qTaeUTEjhVCqVNebZOpuqsSCUmUZAQmY+gZ5qVArnGeKcWLqlBqZ8yQgEAvORJMkmrh5nsXnzZqKionj22WcJDw8nMTERhUJBZGSk0TmxsbFcuXKFsLAwAHbv3o1MJqNt27YAqFQqSkpcq9FuQ0S4mRo4J65k0veDzYz5artd99lxLpXHfz1Iak5h+bErGfk8+stBo0Gf28+lMP33w6TnFtlVNoCUHPvvYYj8ohKOxmVUOdZfFsVa1ct0kRwbhCwQCCooLCwkMTGR+Ph4Dh06xPvvv8/YsWMZM2YM9913H0OGDKFv377cdtttrF+/npiYGHbt2sXrr7/OgQMHytdxc3NjypQpHD16lO3btzN9+nQmTpxYHiMTGRnJsWPHOHPmDKmpqRQXFzvrV27QCMtMA+fvo1cAOJuUU+u4pQcvc0eP8FrH1MbkeXrTskIm48u79WX4n//zKLsuXGXdiURGdqwZ/HbvvH0AuCvlfHiH3necnlvEqYQs+rYOtNiCYsihVFmh8My9ZNG6lnDXD3uq7K0DflV9AMAvqg+Apx0mi0AgqGDdunWEhoaiUCjw9/enS5cufPnll0yZMgWZTH+f/88///Daa68xbdo0UlJSCAkJ4cYbb6Rp06bl67Rp04bbb7+dUaNGkZaWxqhRo/jmm2/Kzz/00ENs3bqVnj17kpOTw5YtW2q19AgsQygzNubH7ReJDPRkyHVN6x5sB9Jyi9h0KolRnULxVCuY+5/xWiaVdYXn/zzKjdc0IdjHzar9EzIrAj2rB326U0A+6hpzDsamlz8f+vl/pOYU8cVdXS3KsNJqdXy6/jRzaxkTkHa02hGp2ivbxddUt8pUxkfKJymrgKZW/s0FAoF5LFy4sLyWTG14e3vz5Zdf8uWXX9Y67rHHHuOxxx4zeC4oKIh///23xvHqqeR+fn6Nohq8vRBuJhty8FI6/1tzigd/PlD34FJsHb8xZf4+Xlh6jDdWHq91XExqLtvPpVY5dv37mzh4Kd3IDOuIKDjLKbdpfKj4oca588kVVqPUUnfQvyct63h94FI6SVmFtY6RdK7jv+79/iZni+AQxHe0QCCwJ0KZsSHJWQVmz7G1Jh4VnwnAP1EJtY6783vDlSbv+G6XVfsb+3VGpv+q31ex1ar166JQY72iosM5AcLirkwgEAgsQygzDsLVLlTGrBcuJqZNmfvfBdJzi1wqs6qMQ7HpXN9IrDQCQUPh7bffFp2vXQShzFjJlYx8ftx+kewC4xHqn6w/Q+/3N1lkuanPVO5U7Qp8sPY0z/xxpIbdpVCjZd3x2i1Z5jJvRzQbDbjKjCm1t3+zi5Ts2t1j9iIhM583Vhyv4u4TCASC+oRQZqzktq938r81p3hr5QmjY+ZsOU9ydiFfb3FcKq7kJFdJbFoe3269wOpjV7iS6RzlrbK60Ea6zDT5WpToqx3/dzbFoBvp0UWHbLb/4dh03l190qzYKWfy6KJD/LLnEuO+3ll+LDmrQP+3asimOoFA0GAQ2UxWklx6N739fCpDnZTB5EokZxfy4brTFs39ZY9tUqYrqyob1S8C4EYh35TcZtJ8OSVsP5eCTJLoZ0GKeF0ByK5G1OUMALILK9pb9J21mRKtju8md2dEx1AnSSaoDwiFV2ANtnr/CMuMAzkcl8Gdc3dzvDRI157kF9cMhM3IK0Krdc4XT0mlN+yjvxzkdGJWjTFvrKjIwLK1Xamb7EKlV1X/BtVTsXvJznLvvH3c8+Ne1p+wLKuqvlNS+j6pnvEmEJRRVoo/Ly/PyZII6jNl75/KrR0sQVhmHMixy3olZtIPezj29nCH79/1nQ3c2DaIn6dd7/C9k7OLQK5/vu5EIrsupDJUdoBJ8k28UPyozfYx5l5TYFlTzW3nUhhhoOCfQNDYkcvl+Pn5lTdG9PDwEK1CBCaj0+nIy8sjOTkZPz8/5HK5VesJZcYJZBVUXFiDtKm8qPyehZrhwGi7773tbIrd9zCFrAINP7h9BsCr/MqI2VWrD1tqP9IZmTlYfhTKY7SrfuE6KxUbwIuad7U+5JCFlxOksS9uFFJgoGiioP5SVrJfdHoWWIqfn1/5+8gahDJjR77adI6zdWSIvFT0FT3lRxkl3wc8b/We7hRwvewMu7QdrF7LUTQhk9OJ2Q7br8iFsqy2qGcAE8pfP6NYyjOK5cwoehRbKbc6nY6Lqbm0auLptDvnPiUH+dTtf3yhuR1HKO0CxyBJEqGhoQQHB4ueQwKzUSqVVltkyhDKjB35dMPZOseEaG17R/Ot8gsGyY8yXzMCGGtwzMUU+6TgSmjROTkMS1NSt01n+cF4+qtMW8/Wl/7TidlQqXtBkFQ1dugZxXIAPlN9B3xokz1nbzzHF5vO8eCAlrw+5jqz5qbn2aZB53Oa7wF4WrGcrILv8XGzzj8ucC3kcrnNLkoCgSWIAOAGQE6hhid+PcQ/UQkMkuv7Dk2SGy/AtuzQZQDukm/mM+U3yLG+au5D8tVEqR/kWulS6Xq1B9nag4OX0pm6cL9D9qodw/urcU7n7i82nQPgxx3RZs89EpthY2mg89v/klNoWQyTQCAQGEIoM1bSQkrkGcVSfHSOc5NU56N1p1kTlcDjv5pXK2WW8kdul+/gVpl1LQwAXlP+hpdUwCzlD+xSP8XvyvesWs8Si8hrf0UB8L3qM6v2riKHjUwzzyv+4Izb/fSRnbTNghZiqJChM1xPZxzoVhQIBA0focxYyRrVqzyjWM6rJd9ZNL/YyviNZxYf5ufd5tVn+XrLhSqvfSTbpVZ2kV2kqZRBX3nVi3ZtQbaGzu04b3lKcJBUe+q7/e02NX+fJxUrAXhD8YvJq0S+vMZmEpXR9vW1/LDNeCf16jjbxiUQCASmIJQZK/GS9FVuu+hOU1BYyC/K93lJ8bvD9l9x5IrRc0v2xzlMDluTkWdZMKFE3cphY04e1ergvX9OAbDn4lWmzN9XXlNG4FoUl2gZ/+0u3v7beHVxgUCgRygzNuTIlqXcID/OY4pVzhYFN6mYF5cdY6p8LTvU0wmXGkfq5PXSGZuuZ1lbCPOUg90Xrho9Z63lrjbu+n4P/7lIqr6zuZpTyKHYdGeLUYX/zqRw8FI6C3fFOFsUgcDlEcqMjdDqICnd9eIA3lL+QriUymuKX42OcXbAbGuZceuSORSXaFFK5geWOrPODMDGU8arDC85UH+ta5WRXLzkfZ8PNnH7N7vYc9G4YuloNMJiJhCYjFBmGgmKWtwvbyt/5hG586xJ4ZJtSuZfSMk1aZwpl4jrpVOAzmYBwLUxb0c0/mTRVarZiDQ91z4ZUEsPXjZpnD10kG+Us+2zsBUUl5S1bxCWKoGgPiKUGTvTSzrN24qFeJLvbFFq5RWl4+J87EmoZP6dtRIN3tUq8S5Rv8sw2QELbTbGZxk7s0f9FCvUb1q0W114k8cE+VZ8qagv9PyfR02YqSMxq4AijW1dXaPk+/C4GmXTNQUCQeNGKDN25k/1O9yv+JdnFMscvvdw2f5aztr/zriVdIUVqjcYJDtS525PyFdYXYdllGwPHyu/r3PcOPmOKq9byxKIcnuwxribZYctlMT8v61asl/11E+V3/Kx8nu+U842eD5cSmaO8ks6SRerzPlH9SpKNHaJJZG0hn/fY5czuOmTrWw42TgbfAoEAssQyoydOJVQtbJrpFTzy3n1MdvEihhjrupzg8f9ySLG7R677g2wWf08XWUXWKj6qM6xLyiX8Hhp+rKlPKVYUeeYDlI0N8iP1zmujIbQOG+Y/CBAjXT5Mr5VzmaMfA+r1K+XHxsv3851sksMkDnWgvLATwe4mJrLQz8fcOi+AoGgfiOUGTsx8ovtdY558jdL7/zNZ2jpBQ1gqmKdTdcuKK67grApKkEPqe72D9YSIdWvmAh7h5aoKKatFG/fTcwgT1QGFggEFiCUmUaIzMYupuwC21yABsgbSj0N21hzfMjl0w1nWXHYdsrGWNkOmqAvKqhAwwH1o7W6uHrLTqPT6Sv2ino0AoHAVRHKjIMYKj+IzISCbvURnQ3NBz8rP+BaybyKxqYyXb6c71Sz7bJ2VYz/PQKqNZasjdnKrwF45o8j1gpUzheqb/hLpQ80DpOu4iNVDUzPLqiq2EyUb+HH7RcZPnubiUHDhqmp3rmm+87FkqwEAoGJCGXGgUyUb61xzFatBPTZOLV/E89RfsFMxQLaSaal5ZqKLb//b5RHsVj1roVy1H6BnKFcatG61qKgwnIVIpkeTHuT/Ej5c62FVpGoyzVbO0TIjLvatpypeW7TaX3Bxb+ssBCVCC1BIBDYEYWzBWhMtJdiy5+XVXYNlKwvtNdeimWd+mX+LelR67gx8r21nu8rO8FubQer5THEKPk+k8f62rBXlDVYevlddzyRQbIjJOn8OaVrwQCZ6QHHxijQlOChMv/jevcPezhuhhHElla2KutWP+CahhmBQFBPEZYZB+JOEYNkR1BTxJT5pl/c62KKfD1QkbViKd8ov7CFOHWiwpQ0ZNe4k7ckmen40X0sVH3EWvUrAE51L+YYCajtIEXztIFyAVo7KTM10u5d49/r0jSARDqBwGEIZcZGmNIS4E7FVhaqPmKmYiG7aunHYyr7otOsXsMWmPude9ZtCm8qfq51zEiZ7ZQ9S7lLsRV1iflWotZSQpXXzm4XYYg16tcYX63ejiFscT39YuM5gqrFCumMXKlzi+rOjGss2Nszdyg2nff/OUWuyCATNACcqsxERkYiSVKNxxNPPFE+5tSpU9x66634+vri7e1Nnz59iI2NrWVV5xAk1YxNMMZdiq1W71dQXMLLy44BoLKgH5EtseQ7d1od6eGj63CJOYr+SYusmu9FHvNUn1o1X4bWwoaXrsHnG01Luc8uKEaBhr6yE7hRWOWcTqdj+7kUkrML7CFi2S52XNv1uP2bXXy/7SKzTfz/CASujFNjZvbv309JScWd2PHjxxk6dCgTJkwA4MKFCwwYMIAHHniAmTNn4uvry6lTp3Bzc3OWyC7DF5vOcTFV34vI0YXNqtOQYzs9is2vflv5z3GHfJtV+x93e5DD2jbAKKvWcWU+33CWTaeT6N0ykOcUf/KYYhWbS7oCt5ePWXs8kcd/PYRKLuPseyNtLsPLit+5Vb6T5RpXauvhmA/W+eScugcJBC6OU5WZoKCgKq9nzZpF69atGThwIACvvfYao0aN4qOPKirItmrVyqEyWsosxfe8oZlml7WPx2fy/baK0vNNpQy77GMq+2PSuMWpErguptT0mSTfVOv5brLzFDjJMOOIy+kXm84BcDw+i+PqDUDVTC6ArWf0GVVFJfaJP3pUoW+02iPhd6CPXfYwl1VHE+oeJBAIABeKmSkqKmLRokVMmzYNSZLQarWsWbOGtm3bMnz4cIKDg+nduzcrVqxwtqjlFNfyxXqXYit3yrfYZc8Xlx6jRKujYzMfm67tL1l2h5aSYX1Gli3ws0FmWHWs1SFMiZd5XzmvzjF7nRQfVVe6u+XUva4plaVtQeXPcXJWYS0jHcs20cFbIDAZl1FmVqxYQUZGBvfffz8AycnJ5OTkMGvWLEaMGMG///7LuHHjuP322/nvv/+MrlNYWEhWVlaVh734cXt0redfVCy2+Z7fb7vIyYQs/DyUvDH6OpuvL1mQeaPSuIYyo8I1Ahnb2KE9wEobVgGuDa+cmCqv7RW8/PKyYxRqaldWbv7U+OfcllQOxo9Ld42yAAKBwDxcRpmZN28eI0eOJCwsDACtVn9RHTt2LM8++yxdu3bl5ZdfZsyYMXz33XdG1/nggw/w9fUtf0RERNhN5roaRVavrloV8y8S55Nzyk3yb465Dg+Vgi+Uc8xepzZcJcx0jHyPs0UA4EJpXJI5vKhcUumVbZSBbedS7VYDpjK+maftvkcZf+yPq/V3is/Id0imjb3S0Wtj1dErzN9R+82QQCAwHZdQZi5dusTGjRt58MEHy481adIEhULBdddVtT5ce+21tWYzvfLKK2RmZpY/4uLi7Cb3iSuWW33+Vb1oliKi1ep4edkxijRaBrYNYly3ZpTodIyV77JYBlvRkAOAi+uwHtSFrZTD1JxCYq7a32pQUKytUpvGnsptdoGGjaeSax0z4bvdpXJUSLL3ovVlDZzNU78f5p3VJzmf7BpWTYGgvuMSFYAXLFhAcHAwo0ePLj+mUqno1asXZ86cqTL27NmztGjRwuhaarUatVptN1ltRVtZPG0x3XWwaO8lDlxKx1Ml571xHfVxRQ1Zi2gg2NJNs/1cCi2beNpsPUMs3h/HfXvXE+OAhMGP15+pc8zJhJo3DHf9sIfoD0YbGG0/iku0KGT60hG2JCPPlAKSAoGgLpxumdFqtSxYsIApU6agUFTVrV544QX++OMPfvjhB86fP8+cOXNYtWoVjz/+uJOkdQ6X0/P4cK3e/P/SyPaE+3s4WSKBqYyT77TZWtvOmh8Q2k6yriaTHC1/qt7mPUXdQcqOwtE6fFZBMd3f3cBDPx+w+dqFmobZfFYgcDROV2Y2btxIbGws06bVTGMeN24c3333HR999BGdOnXixx9/ZNmyZQwYMMAJklbFkC+/t+yUzffR6XS89tdxcotK6NnCn8m9jVulbEFLSaSDVsba+/DrZLbrAL77wlWKzLz4WduiwkfKo5fsLPcoak8ftxXGsqdUJXl8rvyaYbL9Nt+zrv/xuuOJJrnELGHBTuNxM3q57K+5CfuuoCHgdGVm2LBh6HQ62rZta/D8tGnTOHfuHPn5+Rw5coSxY8c6WELDGLqoWFsgzRB/HY7nv7MpqBQyPryjMzKZfUN0f1e9Z8Gshnt3ebfC9un1lpJbVMLhWNOL+Ol0Ojwk81KN7ZeKbR2DUn9jnHwn36s+t+s+EjpGzN5GXpFjMuOSqqWC/74vlj7vb+JsUjZNSCfG7R5i3CY5RBaBoD7jdGVGYJyU7ELeWX0SgKdvvobWQV5VztvjshPs5AJ8AsMoStPOt59LNXnO/J0xLtkXCkxTml5R/EonSV8c0kdj+u9tLacTs1l28LLD9qvMK8ujSMwq4IU/j/ILrztFBoGgPiKUGQsxFAfoXWsqdt1Ud129veoEGXnFXBfqw8M31qx8bOtgxPqOa162bUP3cL0iu92MQmrvlirC5uBKlplHFGtYpXbsBb2vTP83K9E6991UotPhjfllAczBhxz6yE4i0zVcy6qg8SCUGRcit5Jpe/2JRNYcS0Auk/jojs4o5eJf1Zjp3yoQgGPxmaTnFpk8zw3Tx4ILK4Q2FEyr1fHhutOsO55Y41x32XnbbeTi/KN+lcWq/9Evd4OzRREIrEZcIV0IWamlJTO/mDdWHAfg4Rtb0bGZr8HxjiiiZgrZ+a5ReTdIsl+1Z2cT7K2ifYg3Oh3svGC6y8VPMvfu3vGWmSflf/G84g+j5/OKNMSk2c5Ksf5EIt9uvcCjiw4Chi2cb68ybNV6++8T/HnAfrWrHEm4pH8ftUreyPv/2D55QSBwJEKZsZDErAKbr1n2lfrBP6dIzi6kVRNPnr75GuMTtI7pXVMX83fGOFuERsEN1zQBYPtZ+8WP9JCdNdrS4hXFrzbbp8ydpaaI55V/8qRiJUEYDm6e+99FtDb0hCRV++xWvyn4QfkJSjQGe0Mt3BXDC0uP2UyW6nqULzkMlh1GpnPsZ7ty41qBoD4ilBkLORCTTrCRL19LkUkSO8+nsni//s5v1vjOuCnlRscrizJsur+lyLHPF6/WyXELroROkrjhGn2X+W3nUuq0yllqtXtYsYaH5GsMnntEYfh4bRyNyzB4fJX6dbzIQ1ZJcTLWW+uLTecc6v4aKj/EbfIdVY51li4Qgv0rDy9XvcUC1ceMK/jL7nsJBA0JocxYiCTBX+o3bbrm+ZQcXlkeBcC9fVpwfcuA2mWw6e6Wc7P8sF3WPX4l0y7r1leubxmASiEjIbOACymWdTg3hVeVv1s1X6vVselUEhPn7mbs18aLBk6SO6Z2jSV4UJEy7ZN9gb/Vb7DH7Smb71P9M9xapq/zdEPh9irH08yIkxIIGiNCmbEQZXE2zSTb3qlN+G43sWl5hPm68dLI9nWODzn4iU33txRzg0xNZctp8yveNlRir+bhppTTu1TB3WZHV5OlFBSXsHhfLEM//48HfjrAvui0WscrqrmzZioX2lE6PVGXM43Gw1TmFcVv5ValgAzbuZWqY6rFKdqChqcCQWNCKDMWEptqvwZx793eCS91HW2zrl4g8Ix1d9C2wl61TLacsX3F1fpKfIa+yWR53EwdKdqOjA1Pzy3iq03nGPDhZl5eHsWFlFy81QoeubEVr44yrpTfJD/MH6p3y18PkR+2urxBXdzxXdXGrNXjZ8pwk4q573vjRTCNzTMXU/urjf92V4NosCkQ2AuXaDRZH1m05xLP27gZnyf5DO/WhsHtgmsfqC2BFa7Tn8peyszRyxlczSkk0Mv1G4c6Cn3czGn2XEyjUFOCWmE8psreXLqay7wd0Sw5EEdBsd7KEubrxrQBLbmzVwTebkr+PnrF6PyesrMm72Wr+jfVeyH1fn8Tvu5KjtYyx1Ds1p8H4njyplqC803keLzpGXiz1p3mr8f7W71nddQUV4ldEgjqI0KZsRB7FBfzoIA3xlxX98C9cyFuj833txR7KTM6Hfx3NoXbu4fbZf36RNn7rX2IN0281KTmFHLwUjr9WjcxMt4+FGm0nLiSyQ/bL7LueCJl1/nrQn14ZGArRnUKtUtNpBCpdpeVNWTmF0MtNyaGspoaEv3lJ1gjvQrc4mxRBAKLEcqMi+Hvqap9wNULsOkd/dN2dxF4ZrEDpKode5bM33JGKDOVkSSJG69pwvLD8Ww/l2pUmbEXE+fu5kilDKWBbYN45MZW9G0daLBeS56BhqyWMFhem+3EfsSk5pKZV1zjuDVuvEd/OWiFRPbhWpl13dUFAmcjYmbqE1otrHwCNPnQahDp7ezTgM7ctN7b5LvqHmQh286moCmpPybwneftH5h7Y1t9inZtcTP2Kqh4JC4DpVzijh7hrH/mRn6adj392jQx2lpjqZN6HBli5qoTBo9fKxnvbD7ok63sqFSkUIkG0BGfYXlsz7oTNSsPCwQC6xDKjIW0lZzwJb1vLsTuBpUX3PqV4QZRNsDcvjTXyYxfDKzBz0NJZn4xh43UKnE1dDodH607bafFK572b6O3xhyPzyI1x7yu2NYyqXdzdrx0E59M6EK7EO86x5sa4OoIFhgp7thUMr1e1DH1g/ysnFVeC8qWiPRrgcByhDJjIe1kDi5pfvUCbJypfz7sXfBrbretziTZL1PLHG4sLRK35XT9yGpafyKRo5ftXxsnyFvNdaE+gGMsQZW5r28LmvqYHvne0JqhuktF3CiPsnqdJmTSXaoaAP3gT/urvK7NffvCn0d5fYX1cggEDQWhzNQHtFpY+aTevdTyRugx1a7bLXSR9gSD25cqM2dcv96MpkTLx+vP2G39loVVe+fc0FZvnTFWb8Z17CGuh5oi/MgudRk5ljL33wG3x1iufptBssOcStBnNB2KzagYVy3BwJ+KrKcrGfn8efAyi/bEkl/UsIOTBQJTEcqMhdgj6LWlZMSXvu97iN1V6l6aYzf3Uhl/HY4nI8/5Ju8brwlCkuBUQhaJmbbvhWVLlh+K50JKLn4eSrusf2v6wiqvy6xW22tpbXCDzH7F3uor42XbOON2P0fcHmG96kWH7386sarVc4ZiKWO+2mFwbGWFJqSSK6yyG1gn1FaBABDKjMUMlNk+u6K9oYyCqxdg49v650PfAf8WNt+3Ohqtjt/3Ob8zcKCXmq4RfgBsdeECegXFJczeqHcZPDGojV32uKbgOJW7LfZo4Y+bUkZydiFnk2q2NtDp4BfVLLvIYi4qamYDmUMHKdpGksCnqu/Kn7eSmRaIa8sblxwD2V0lWh1v/204OFkgEJiGUGYsZIgd+hHVqF2j1cLfTxl3L9nNQqPj590xFLtAFlFZAcHNLhw3s2jPJa5kFhDq68a9fewXy8TFLeVP9a0NAoG6qwHbEkvieSfKt1q15zC5c1OZ/bBdH6xlBy8zWFbzu2Phrhib7SEQNEaEMuNC1FBm9v8Al3aC0lOfvSRzzL9LLulIyCxgvQukkJYpMzvPp1Kocb34gOyCYr7ech6AZ4Zcg9t58ztLm8yB+VVelrU22HbO9fo0VcYf6wLKu0nnqrzuIMWYvYa5GXr2Ijo1lwWqj+scV1yitWvgk8icEjQ0hDLjqqRdrHAvDXsH/CMdtvVtXcMA46msjqRDmA9NvNTkFpVwIMb0FFpH8cP2aNLzimkV5Mn4jv6w7lX7bXZmLWQllL8sqzez9+LVGlVq7RVLoUo/b5d1a6N69tAi1ftmr7HskOFSCs0wbtXyRd/c0ZD9s6tk+7+DolJAssaA8mVLS2n3dzfUen77uRRunbODk1dMb7cgEDgTocy4IlotrHwKivMg8gboMc2h20+6vjlKucTBS+nlnYOdhUwmMbida6Zop+YU8uP2iwC8MKwdil2fQ5Yd6w/pSuDwL+Uvrwn2IsTHjUKNlv0x9iv3X5lWS26CpQ9Asun1dGzd+sNfMt/t89E6w5lmW9UzjM75WvWF0XMr1G+SXWBdLFB13lfMK3+uj9OpqtCUufjOOqB0wr3z9nHsciYPVEsXFwhcFaHMuCL7f4RLO/TupbFzHOZeKiPYS8WYzmXWGdsFX1rK4PalcTMuFgQ8Z/N58opK6Bzuy4jQXNj1lf03PbgQSvR38JIkVeqiXdXVZK9adRI6OL4UvukDS6ZAUu2Bq65SZcZYcUGlZNx12au0EaaxP2XlVGpLqazoTVT8Z3SchI4zpZlQD/x0oPx4fLp9u4xnGGjlIBC4IkKZcTXSomHjW/rnQ2c61L1UmWn9WwKwJiqB5CznpkUPuKYJcpnExZRcLl3NdaosZcSl5fHrXn3l4xeHtUNa9xKUFEGbIXbZ76hHH3APgKx4OF/hIrih1NW07axjgoAv3/QVXHsLoIOTK+DbfvDHZEgwngZuj6asjuQW+W67rV27zln176bR6nh5WdW/82ELFKosG1uUbIFOpzPYnVwgMBWhzLgaf1dyL/V8oNahkszyi8QRtYp7QptyVK1ioY83292rVnXtFO5Lzxb+FJfoWLTHtHYFeaXZVUfUKi4qFWxzd+PtJgEUGMm6Ki4dWwQMbN6MPi3CyZTJSJTLq4zzcVPSs4U/AFtNLKCXLUkUVtq2CIhT2K6v6uyN5ygu0dG/TSADSvbC+Y0gV8HIj2y2R2WKJDV0u0f/olIg8IA2TZAkff0SRyidBU06wp2L4LFd0GEcIMGpVTD3Bvj9brhSNVOnIRQA7iSLsdlae6OrugO7yi4aHFddAewt0xdNtEUbhcJi52cpVueJ3w5xw0dbRBFAgcUIZcaF+J9yAcRsNyN7yfIrxb1hIRxzUzM5LIRPA/15PCS4xpippdaZX/fG1ggwrc4X/r70joxgmZcn94aFMDY8jCdCglnm7cXPPhU9fLJkElvd3QHo3rI594aFMLR5M9LkcnJlMga0CGdo82akymRQUNEa4KZSV9MWE1xNJ1Qq+kVG0DOyOVkyiTiFnFERYYyKCONbPx9m+/vSLTKClV6eBu+MtcDPPt4cVxnuYH4mMZvlh/WxMS/dHAnrXtGf6PcUBLauUz6LKUvNP7cBMvQ1iQI8VXQM8wVghwNaG0glpXf1TTvAhIXw+G7oeAcgwZl/4PtB8OtEuKxPp84ucHyVXXOZpfzB6LkPFd8bPefIwpLXy+zU88tF+CcqkfiMfJeuJyVwbYQy44oMnQkBLR2+bV75bbT+Ej+8Q1PCfN24mlvE30ev1Dr3Rz/9BfXtoMAa5+b4+6IFdrm70b9FBE+FBDEptGn5+bRqlhiAld6ecGxJ+euyuJndF67Weve2w92Nu5qFlL/u3yKCURHNSCq1ynzj78c8P180ksTrQYGMDg9lv5uaKJWK1Z4edGrZnPcD/fk40J+7K61TmU/+PYNOByM7htA5Zj5kxoJPONzwXPmYGIWCTCssZ9XRIekVpZYDAR0c/Kn8nLG4GXsgK6lm/Qm+Fu6YB0/sg853gSSDc+vhx5vgl9vxSHJujRhTCKml0eSdiq1Gz7241DYVlvvKTtBLql1Zqe+uOoHA3ghlxtVoMaBO91IFdfuYi4HvfX2IUqkoAZ4JbsJrTQIMjl3g61PltUIu475+kfpzO2OMls2vU0pJYqWXJ49Usv5EualrnTM7wJ9zB3+kpDTY9ZpgL5r5uVOo0bL7ouGL9h43NY8ZsDDVRpxSybTQpkxqFsIrwXql4A8f492gD15KZ8PJJGQSvNRbDTtm608Mfw9UngBcUii4JSKMQc3DzZLFJHqWZrYd/gVKrSQ3lLc2SC2PO7BXALDRZYPawu1z4ckD0PUekORwYRPL1W/zgnKJsVn1mkKNbdw1v6ve40/1OzZZSyBorAhlxtUwI3tJQh8X8lxQILMC/BnXLITngwJJqzR/sY83XwX4MalZCCMjwtjk6cHf3l4G1/vO35e5flUVmrt6ReCmlHEqIauGv7+MQhNuGt80YLGpi9s98uj3ex+mrZ/G54c+p22raCRFJptPGTZFT28aZPYedVH5cqXT6fhwnf4OekKPCCL3vwslhdBqEFw3tnzcPne9oqaRJNZ5ehCrUPCXlycvBwWyo1JsUrRSwUF1hVJnkkOm/Wjwago5SXq3DvrWBh4qOak5hTV6/zicwNZw2zfw1EHodi/FuppWN0H9Ib+4pE4Xs0DgCtguIlJgG8xyL0n84e3Nv16e5UfOq1Ss9/Lk2sIiOhUWsrLSuQQTAmDn+PtxS04CBPkB4Oeh4vbu4fy2N5YFO6Pp06qmUnJOaTi2xFo8tFryKGR/4n72J+rrXXhdA3+n+5C1uQedmnSiU1AnOgR2wFvlTb4dUtifCW7Cl6XP/zubwr7oNFQKGS+2ioa/14FMCSM/rhLpelFZ0WzyhVJrTxlrvDxpVVTMs2kZPBWiV77uyspmWG4e00KbMjErm9eupnNMraJtUTEepSYWXdl9h1wJ3SbD9k/1gcDXjUWlkNG3VSCbTiez/VwK14X5oNPaJ2PFZHdHQEsYO4dX97nzsdJ43IkjuUu+2dkimIkJ5jULvU9Pyv8yeDwuLQ8ft6rNUru+8y8nZ45AZkO3qcB8tFodP2y/SPcW/vSKNGxdb8wIZaYeo0MiQ274An5KreKU2jIlw3fX+9Cyojjb1H6R/LY3ln9PJhGXlkdEgEeV8Su9PasvYRN2XbpMtJsnUbd8RFTWRY6lRHE67SzIs9gSt4UtcRW9ilr62ifGaIun/nfVanXlhdem9Q4hcPv9+gF9H9e7WCqxqJq7rjoXVcpyRQb01rPFpa6tJT7erPf0IFMuR6nT4V9SwpPpmYTqKl1Iuk+B7Z/Bxa36RqSBrbnhmiZsOp3MtnMpPDKwdbkLytkU6uyj6JpLEOnMUv7obDEsxmizSwvdic8r/6xxLCmrgBs+2lLjeEGxlqISLW4y17GypWQXsvN8KiM7haBWuI5c9mRNVAIfrNVbhmNmjXayNK6HUGbqOT+UBt7akueyduOz7kE8fMJxV7jjofSgbdurRKcU8/bmS9zZsw0eSg88FB54KD04q1LWvagFyJt2pE3ScdpkZzOu75sATJ6/nd1xxxjWvQhvnwSOpR4jPiee6Ez7FvdbE5XAyYQsvNUKnnZbC+kx4B0GN75o870ySwOiiyWJZIWCN4MCmVvZs+bfAq4ZCuf+hYMLYNj/yuvN7I9OrxEgvd7DnT99vJmVnEoTreul5TqC95Tz6x7kclQosCPl+5EVa9HaMTLAmdW+g0knQMoGups0/ravdxKfkc+55Na8MLy9TWT480AcPu5KhncwHPjvbKJTXaPGlqsilBknkSiX81pQINFKBc+mZTAoLx9vM6M27VXDY6eHOyTt1T/KkINbCOzLhX3VC5W6uWEXetwP/zwPBxZA70dBkri5XTg7zmaRkRDIt7f0ASCtII3jqcd5YtMTdhFj4fGf+XbHaVRN8rm+uYw5Z1ZQFOhPcavrKdr3PkXaIopKiijSFlFsJ4tISfX/dc9pemXm8K9w0xu0auJJMz934jPy2Rt9lV7N3MuHPl8aS/RZgD/vp161Sg6dZN5dsKuUQQuVrPu9bUVTTGs7YcidN1f5OQ8VP1fl2ObTyUzsFWGeEPaKDreCfW76z+7WnB5AaJ3j4zP0lY83nky2iTITn5HPC6XZacLqUT8RyowD0ADf+PvSJ7+A6wsKiSnNdinj1dK4iqjo2DrXSs1PZX/ifvYm7GVn7Da7yPt6ahrFkkRep/HkBbQkT5NHbnEe605eIq84jxZBCnzcdeRp8sgrziMvN4lce7Rc6HwnbHgLUs/ApV0Q2Z/B7YKZueok+2PSyC4oxttNSYBbADeG38jonFzWeNne5fXpwY/BC9ResC8f9nmXutlSD+kfDkBTXS1oMxR8mukrAp/8G6nzBG64pgmL98ex/Vwqrf2a4klVZWKLpzu4doPtBs8Uxb8Wzx0qP6hPT6zEOks62+e5bi0Xn8yTwPUO3zdddBGv9whlxo7EKBR46rRs8fDgBz9ffvDz5dm0dD4P8Dc4vhio7rDJLMzkQOIB9ibuZV/CPi5kXrC73GPCR+J56k84sRme2A9KveWlnTyGN1eeoDDfk8UzBlYEBL7ty0ovT14PCiRQU8JVW/mw3Xyg03g49LPenRLZn8gmnrRq4snF1Fx2nk9lRMeKu7hH0zPtoszI87pTUCRxY3AJrVK2o0JC2f0+VN5hqOQqVHIVSplS/1ym4qXtL9lchs3uGQyuIpRCHzuz9X19IHDnCdxwTVCpMpPC7Z0C0QGdWzYvn5Ijk5UrN44K5RT1URoGOh1sPJnEtWE+NPNzr3uCQOBghDJjAw6rVSTL5QzP05s+4xVy5DrKrS+3Z1d0+TWmyADkySQUxbkcTDrIvoR97Evcx+m00+iq3ZW3D2jP9SHXE5CnYHaMbWMBOhUUkt3vMTwv79RXmd3zDdyg7yw8vns4H68/Q3RqLv+dTSkvZAcwNieXsTm5aIFPAvwA+KWOQNjaeCS9tPpvz2l6ZebkShjxIXgGMqhdMBdTo9l8OrmKMhOp0fBP3BVGVbJ6WUugpoSYSxNp6afgu+SXkaWnQ98nYcBMo3P+t/UFso0EZlvKCq9UOp1ZQvfg7rTya4VMkkH3e+G/DyF2FySfon+b1kgSnE3KITmrAKWyZixT/+bhdC8sZE5SCveENuWYm5otly6bHktTT/sT1E+pHUteLcUo1x5PYMaSo4BwwwhcE6HMWEmSXM59YfqAsVV5+UQUF9fIZllupK5LdW5vFsrV3/tToqv6pdLKtxXXh1xP79De9GzaEz83PwAuRO22qTKzKTaeoJISEhXuMOQt+OsRfdZM13vAuymeagV39ozgxx3RzN8ZXUWZKUMGvJiWAdRUZsbk5LLPTU2yQoFPSQlZBir/AnhptTyZUarMhHWD0K6QcASO/Ar9pzO4fRDzd0az5UwKOp0OqdIFNkKjYV9MHAfd1ASVlPCrjzd/Vfv7/3IlkXvDTAvy+zopmdHAnMidyE5f1Nd4GVi75WVuYjKTjFQPtoZ397wLgK/al+7B3enRtAc9rhlI+7ObURxciN/ID+kc7sfRuAx2nE9lSXjN2INsuYz/PNz5x9ODY6WFC7/38+XVNONVcK1BWGYsw2j2kk3WNvw/ef7Po0bn7LrgGjFHAoExhDJjBRs93Hm2UqG2/zzcActNsMkKBehKCPcKp3dob3qF9OL6kOsJ8jBcDE6SJKKiY+lUyZVgCt8lJqPQ6XiwUksBgOCSkrKFodNE2PudvnHglv/pe0UBU/pFMn9nNNvPpXI+OZs2wcar5R6KjuV3H29kwFG1iheuplMsSex0d2N0bi49I/VyX1dYiEIHx9zUzElMZmB+tZL5PafCqqfh4ELo+yTXtwzAQyUnJbuQE1ey6NisakaXu07HgNI13klN453UNOb7epdbxboWVvjHB+Xm8XxaBs01Gm4JD+VSNWtGh6JiBgTlc9350lopw/6nd3/VgqfO9hlDcp2OnqF9OJpylMzCzCqp6e4twukSt5Ieh8K5pnkYRy/L2XHxMjQxvt5Llerf/O7rzSE3Nb9dSaTORGoXDB5tiNhTmTGGphF3rc4tdP0eYnJtIT8qP2aLthsgrGPVEcqMhZxQqaooMrage0EB79+zlWZezcya90NCEn95exGlVhFnwLXwUEYmzYs1/ObjzQ15+fQvvdC/mXqVOf5+NXojSZKkr0I8YhbMHw6HfoHrH4aQTkQEeDD0uqasP5HEgp0xvDeuk1G5lMB9WfqKtJMrHb89R59i+NOVJBb5evPi1XRCSkookCTcDF0sO94B61+HtAsQsw11q0H0b9OEDSeT2HomuYYyY4hpmdn0zS+gmUb/pSXpdOgkiTeuppcrcQsSktjo4YGnTsdrlSoWf+r7J1J2PrToD50m1LmXKdyYl882D9MV30cyMnns/h8pLinmZNpJDiUd4lDSIQ4mHyS7KJs9ahl7ovQKl1c7OZcLmpqVxHtGraJHy+asuHyFlsUao3PN1WVkNM5UcGuxZaduc3CngHzslJ1oITqdjkKNFjelferJbD6dxLSFB+yyti3pmPAXA+WHGSI/DHzubHFcDtHOwEI+CvSz+ZrDcvPMVGT05uI+BYV8mHKVNZcTeLDMPVPKn/EJTE/P5LacXJZcSeSpSucnZOeyITaeSZnZzE2oyHAo78HUvA90GAfoYP2r5Veysm7ayw5dtqpzcPfCQj5LTiWkVJkwqMiAPo2o80T98wMLABjcTu/i2nza9MyMa4uK8Sm9+9x16TIbYuMrrFFAUImWu7Nz6FlQ1TLU9PI6fa+hkR+ZFDNSecSdWdnsjYlj56W4KmOmZGbxbFo6o3KM1474LrHid7sjSz9OKVfSJagLUztO5aubv2LHXTtYFn4br6WmMaJETZB7EJJUgsy99sagxrgtPIyXShW5q5UChi3lJeViK1ewDR4U1D2okTNBvpVTbtOYLN9Qfuxx+QoekK/hSmkqtDO4b/4+2r+xjuRs+/wP31l10i7r2hpVSU7dgxoxQpmxkEN2qK0yIcu8N2v166oE3JZdcXGMio6lfVHtdU9UwCtp6fQrMPJFMWQmyNUQvQ3OrAWgd8sArg31oaBYy+L9cYbn2ZqeU/U/T6+GnGQGtdNbxQ7HZZBmQVqll05XrkRVJ0xTwvLLCWyKja84eP1DENLRpLUjizUMyMtnZE4ur19Nx0OnK1eiANRaLT0KCpmWmc2HKVc5ZiQlv39+AVHRsRyKjiXQiAtAJslo23s6d+UW8nHsOTYN+IyufEjJlbEGx5vCOi9P/vVwZ1CLcDq3bE6OJJFmoWITLrlGLrg93Datpfi6B1XDevVQzyfK73hPMc8ma5VR1nbif0r9DUMQGbyoXMIbyl85cMGCFHAbUdYNfvXRBKfJIHB9hDLjAvTIL+DJ9Iy64xVMoIVGw+L4RP6NNf+LtozKAbX4t9CX7Af49zXQFCFJElP7RwLw864Yy4U1h5BOEN4LtBo4/Athfu60D/FGp4Pt51Jsvt01xcUVVhvPIBj0islzJeDbpBQ+SqkaNLk3Jo6Vl69w4NJl5NXG746J4/6MLIPrKamj+JxXEFx7i36tgwsZ1vY6dJndTJbXEM9VcqH2jYxgYItwng6uJQinETJQdszsOZ2ki1bvG8pV7pBv4x7FJtwotHo9Y6ilipsEJRoek/9NF+m83fZzNt7kubQFT4TS145QZlyAeYnJPGLkQmYJHYqKCDVidbCIATPAMxjSLsL+HwC4tUsYgZ4qrmQ68MPfo9Q6c3AhaLXl2VRbzHA1WcTQd8Ddz+plPHQ6WhUbDjT00ul4Lj2Dn64kEV5czDeJVX8nXV0f1Z7T9D+j/uTGFu5IwN+XLXM1GWOLpwdaOwQ3OwJ7XAjeVP5S96BqKCTrP5cKqeI95KhA4bvlm3lJuZiVan1bEU2Jli82nuO7/y5QpLHde0JyUoC5miKi3B7kpNs0EeReTxHKjIU8nJ5Z96BSPk5O5Y/4BB5Oz2Tp5QQORsdyMDqW7Zcus/NSHC7fJs3NB256Xf/8vw8hLw03pZx7epuXRWU1HcaBm6++/s2FzeVxM/+dTaHEnpkYne+y39rV6F5YyNrLCdxQLaOrzhTnyAEQeA0U5dA8fg2eKjktizWsjbPcQmeIBVf+JC7bQa5FgUHukFtX+bt63SpDhJHKE/KV5a/bSpernP9tXyyfbzzLrLWnmbnqhFXyuALNKrtD66nC3tgRyoyFuBvR3vvn5bMhNp6j0bFsuXSZ5ZcTGJGbx3VFxTyVkUm74mJU6GNV/LTaKrEULk23ydC0ExRkwtYPAJjcpwVKuQONnyoP6HK3/vnBBXRv7oe3m4L0vGKO2LNJnj1aNZhJne8SSSqPK5IOzKdv6wAAwjUltKojbsoc1qRuYfTy0Tyx6Qm2X95ebyw1rvIps0XdnacVf9lAktr5Uz2TuxU1O2iXcSYxu/z5r3vrbsNiKmeSRZCrMQqKK6x6dr15q6eY9C0dEBBg1iMwMJBLly7ZW3an0ry4mEG5ebx8NY0jlQI4H87IIqSkBBnQRKvlmmL7NB50ODI5DH9P/3z/PEg+TbCPG6M71d0UzqaUuZrOrEWRm8iNpd2it55x3X4ztkAnmfBR7XK3Plg7KYpbAytcTEvjE9hxKY5wG7wX/RQ+6NCx7fI2Ht/0OLf8dQs/nfiJzMK6LZVb3d15rUkAefW0irAr0lN21i7rNnNSY85d56s24sypVP+lsV++K1do1gpXWA1MqjOTkZHB7Nmz8fWtu56HTqfj8ccfp8SWMRsuyLC8fIblVaQrPpWWQbxSQbdC+wXkOQ4jF5tWA6HdaDizBv59HSYvZdqAlnDagaIFt4fm/fQl/A/9wk3t7mHNsQS2nEnmubpn11tMuqP3CICOt8PR3+mZWnH3rgR8tTp+uZLE7AA/VppYkdoQb7SaTtvrevPHmT9YeX4lsdmxfHLgE+YcnsPoVqO5q/1dtA+o2cV4g4c7M0qDisM0JTyRYbqbtiGh09lWkQuRTOvCXV9Zd7xmFpW2klWi2NQ2HIIGj8lF8+666y6Cg2uWrzfEU089ZbFA9ZWHM20XwOvSDHsXzv0L5zfAuY10vmaI42XoObVUmfmJgQ8+CcDx+CxcrNaXTTHZPdFjKhz9Hb+YdTVONdFqeSs1zSplRoZEpG8kL13/Ek91e4o10WtYfHoxZ9PPsuzcMpadW0a34G7c1e4uhrYYihJ4OrgJmz09ytf4zt+XRzMyy2PFCiQJla7OEGercBVbUHNZklXznZVNVDnQOMeO1XINGe3CpRQipGTgOv3+RRX7p2Rbf/MoSVKV32/diUQGtQ+xW5E+gX0w6ftDq9WarMgAZGdn06pVK4uFEpiKfb6ia101sLW+GjDoU7VLnFAG/NpbwT0AsuJpkrCNLuF1WwzrPyb+ryOuh+AORk8rgWPRsURFx3IkOpa9MXF8n1Bxgd0QG8/2S5eNzg9TV3wPeCg9mNB2AktvWcpPI35iROQIFJKCw8mHeWn7SwxdOpQv/X2rKDJldG3ZHB2QIZPRKzKCqaGmf7+YS2JmQenF0PlY674pyyayBmO9mWqdU2nKWysdG/C7Q/00v6veIyjT/FR4U7im5AKb1C+Uv37810N88M8pu+wlsB/Oj2wUWIGT/KYDX9ArEymn4eACx++vdIOuk/TPDyxgUDv7XQhdBxMvQJUCgetaSY4+XbxvQWF5cb6QkhJ8tFq8jJjvlbKaxlxJkujetDsfD/yYf+/4l8e7Pk6QexBXC67yg59xRbNzy+a80UQfqGyPIpRlrD52BbkkYgxsxbZzKU6pCBycGVX+vL0Uy6uKX/Ehh0JNCYUay8MaXi/4tMax5YdsmwVoLrsupPL4rwdJzqrIahTv4NqxqDdTfHw8O3fuJDk5GW21L73p06fbRDCB8/BQ1/G2cPeHwa/CP8/DlvfJ1HngK+U5RrgyekyF3XPg3L8M7/YmXzh2d4djVqhF5zv1/xszKevqJQO2xl7myaZB7Hdzo8SMgN0gjyAe6/IYD3Z6kM2xm/lo0zP6BqpG2FrJatMtMoIRuXn8L+VqjXIFSXI5iQo5XQrNr/a88sgVHjR7lsAYKdmFbDlj+0KV5rBO/TIAIboser7rBRIcemMoCplUteinCbhi/7BJP+wFoLhExw/39XSyNPUDs5WZBQsW8Oijj6JSqQgMDKzyxpEkSSgzDQBvt5rNKmvQYyrs+wFSz+DrjICEJm2g5Y0QvY1rE/4i0LMPNOCYc7MiStx8yG8zGvfzayzeT62D7xNT0ABJCjkjI5oRYEZQv1KmZHjkcC5m5/CNv59JczSSxGovT/0j7gotNBpS5DIOurnxQmn14cXxCXQwI9X8YkoOUfGZDTqeqjHTVhdDdmkMTbvX13JT+2B+nNLLrnvqdDqzFSZLSch0Xk+s+obZbqY333yTN998k8zMTGJiYoiOji5/XLxofalugTnY6QNlStqfXFGRqu0sStO0pcOLGNzW37my2BmF3LyPqnvv2l1NpiCht9aEa0rYGBvPujjzKwq3sbDGzZiIMEaFh3JT8/ByRQbgDx9vs9b5+6htqyA3BEwpmldjTh1T7HXRNcedpdXBxlP2jY3KLdRw82f/8fIy+8Tv1IarBLG7KmYrM3l5edx1113IXKCQmMDJXDMU2jghm6mM9mP0fZNyErnT+7jz5HAAcrmZmRXeITbdv2lJSWmhSPMuhEPyLL/IxSlrWgj/8vYipha3VWV0Op1LKTP2KnQWk2q887qtqMsQ0feDzbbZp9r767MNNevoOPOivvxwPBdTclm8P45jlzOcKImgOmZrJA888AB//vmnPWQRuArmmFCHOdE6o1DpKxMDXZNXOE8Oh1A/78skwM/GNaduiQgzadyJK1lcTMlFrXCNG68lB+zTBuKDtfbPvHFUD6jKfLO1ehq680NgdZVMVHM2OyZNPjGzQO/aqiKHQ7auV5gdM/PBBx8wZswY1q1bR6dOnVBWu3v67LPPbCacoA5coZJqcM0CaQ6l+xTY8TnKGOOl1xsErvC/tpD1cVf4yt+XRb4+Dt23zCpzc/sgcHKz56yCYj5Zf4a77bD25fSGE1dR+ZL90bozRsYYft4QOR6fRZ8PNvH4oNZ0crYwLo7Zysz777/P+vXradeuHUCNAGCBwKEEtITWN8OFTc6WxK6Y1M7ARfHQ6XggM8uhyoxWq2NVqTJzT2Q2nId8ScJNZ4vuSObz1aZzXM0tEoHIZnJNpQaX5daI4grlzV+yvpdT9XfEMtXbvM1jVq9rS77ZeoFvwitei0ttTcz+hvzss8+YP38+p06dYuvWrWzZsqX8sXmzeX7TyMhIffXFao8nnngCgPvvv7/GuT59+pgrcsNF2Br11FFXpSGgkyyqomBzLL1haVKipUVpb6gHHdDKYH9MGgmZBXirFfTO20ayXM71kRE81jSIVJmMZ4KbsNPdMZrFxZQcFuyMscvazlDN/LFftfNCjRZNSUWqdGepIqlkw8kkBn68haJKLWPcsX37mG6y83zFR2bN0el0XEjJEQ0gnYjZyoxaraZ///422Xz//v0kJCSUPzZs2ADAhAkTyseMGDGiyph//vnHJnsLGhBtR4CXbQNeXQ5Z/S+tvuJyAnti4pieXqHMjMrRB6++kWrbHkMrj14BdPS/tpjFF5dzc/NmAOz0cGdwi3A2eXrwaIhjii2+t+YUGq2Owe2CbL62rXs9mcJHyh/sWptl+WHjBesuXc3j4/VVm8HdLd/E3XLbWmb9yOKmT7ay83xq1RM6HXfJN9NdOktlvWXx/jhu/vQ/pv9+2KZyCEzH7Nu9p59+mq+++oovv/zS6s2Dgqp+uGfNmkXr1q0ZOHBg+TG1Wk1ISAO/ULkc9cyGKVdC9/tgm3l3U/UJnYHKu87AGvO2AlCUWhPXxF2hUJJoU1zM0+kZhGlK0AKrvDwZkJ9vcm2a6iTnJbMzfjerr/yFZ5uz7CzMZqe75TJby39nU9h0OhmFTOL1MdfB17Zd/wnFCp5ijG0XrYOh8oNEyR5gSckgZmqm2Hz9qzmGCyOWBSH/E5XIh6VGNS/y+UA5D4C/S/qRi+3+2RdTc7nnx718fEdnXl4exdR+kXQvOcIs5Y8ARJ76rXzst1svALAmKsHW/+Jy8q/aJ4C8oWD2N+S+ffvYvHkzq1evpkOHDjUCgJcvX26RIEVFRSxatIgZM2ZUMWVv3bqV4OBg/Pz8GDhwIO+9916tfaIKCwsprGSGzMqqRw0gzYyLEDFKlRDKjEOwpK+PIZprKnp6hZWWor8rO4e7svUxEL0KCpka2rTOdfKK8ziQdIDdV3azJ2EP5zNKI3299GZnNTJ65OWyy8PwRU6L/Xq6FJdoeXf1SQCm9IukdZDlDT6N0UqWSMuSaOAGk+fY4n/oKRUyVbHeLsqMOVRuU6HEPn3iXliqrynz445o7pXvZZQJNUXtgZsmk7LS2KcTsunUKHrSmY7Z35B+fn7cfvvtNhdkxYoVZGRkcP/995cfGzlyJBMmTKBFixZER0fzxhtvcNNNN3Hw4EHUarXBdT744ANmzpxpc/kcQtOOzpag/uIX4WwJ7ItkppvJv6V95HBQnFbPgkJ2xcTRL7Lm/9VLq+W7o9+x+8pujqUcQ6OruIhJSHhJLUhNiWRIi/58fuVD1GkpdGrZ3OA+XUqPf5ycyo++PsxLTMbXSF8qc1m05xLnk3MI8FQx/eZrbLKmIbx12XZbuwLnxII0ldKdsq+rcyktVygz1bConYE9mDdvHiNHjiQsrKKGxJ133ln+vGPHjvTs2ZMWLVqwZs0aowrVK6+8wowZM8pfZ2VlERFRTy50foa/cAUCswOA1ba3AoBjsyi8dTr+ibuCUqejaUkJK7w8eTMokByZjK+PVBjzm3k1o09oH/qG9aVzYE9u/ng/RUUlPHWTL+rjF0FRd6BvWZXhAS3CmZ2Uwk15+VbZL9Jzi5i98RwAzw1ri6+7k27nDWBJBeDx8h12kKRuXlT+Uf68LNjZGTVvBK6PS9iuL126xMaNG+t0UYWGhtKiRQvOnTtndIxarTZqtXF51OaVag/2sVM2hnBfuRyF/tfYMBrAChz81oio5I4amZvHfF8frsrl9Gk1XK/AhPYlwqfiZmXV0SvkFZUQEeBO+6ul2ZVthkCh6eXnn2laEct3LDrWol/5841nycwvpn2IN3f1arg3KUo0LFK9z2FtG2C01etJ6MjMt6wFRkPCh1y6ys6zQ9sJrQFHqEhkrYlJ7uLu3buTnm66uW/AgAHEx5veQn3BggUEBwczenTtH4arV68SFxdHaGioyWvXK/o+adZwD2X9z3ARmEZOswHOFgGwXcyMJbjpdPwdn8CO2Mt8NugzJrabWEWRgYpCebd2DkU6uUJ/sMM4i/d8vUkAoI+tMdX5dCYxm0V7LgHw1i0dkMsa7s3Bc4ol9Jad5lHFaput+d1/FwweV6JxyQ7X9uBP1Ux+Vn3IA3KRvWsqJllmjhw5wtGjRwkICDBp0SNHjlQJwq0NrVbLggULmDJlCopKPVdycnJ4++23GT9+PKGhocTExPDqq6/SpEkTxo2z/MvJpQlxkZgZ94bdtLF+4hoXRGcb7SSM/yUy84rZekbfaHBCeCbsuaB3MbUdAYcsi6P729uLKLWaaJXeTbQq7govBQdyS04ek7NqxqrodDreWX0CrQ5Gdgyhb+tAi/Y1CyfepdtSiamLV5S/c5t8B3cWvemwPc2hCZmkYpvCkO1k+mKBt8p38UOJY7PV6ismu5luvvnmKn0pasOcLJuNGzcSGxvLtGnTqhyXy+VERUXx888/k5GRQWhoKIMHD+aPP/7A29s8d4zATFSezpZAUB1naxGluIYUhll3IoHiEh3tmnoTmfSv/mCbIaD2okVxMZcMNK40hTJFBir6Qp1Uqw0qMxtOJrHz/FVUChmvjrrWov3MxpX/KWZSFhfz8M8HDJ6/VhZntFDg04rlfKmxzY2uOX/S5OwCOmdsYo7bVyzS3Ax2SpVvLSXYZd2GgknKTHR0tNkLh4eH1z0IGDZsmEElyd3dnfXr15u9r0DQEHFOEf6auHLw5cojpS6mLqFwfIX+YKmL6cn0zPIgX3tRqCnhvX/0TR8fuqElEQEedt2vjIIi2zbydCZNJH1BxX9PJhkdY+w9OFWxnkgpEezSAcs4t83Zye8KfaDyZMUmkrMLCPa2fTxje5moM1MbJikzLVq0sLcc9Y+e0+DAfGdLIahEuiIYf02ys8WwC8VezZwtgkuTnFXA7otXARjfLB22VXIxATfn5nFNURHhxRq2erijs4Ola8HOGC5dzSPYW83jg9rYfH1jeGZfrHtQPeF/ygXs1HYkWmdZXGRf2UkbS1Q3VzILQFXxeuJ3u9n6wmC77vnU74cZ3D4YL7VL5PC4BPW3e52z8RMKnqtx3rObs0WwHy7iZjK73o2DWHUsAZ0Oujf3I+TyOv3BUhcTgBJYFp/Il8mpVWxcj1RqrWAu3/pVxEekZBcyZ7O+YN9LI9rj6cCLzF3y+t0xvrplfrhsv5MkqRtTLKQxV/McIAl8byRQurEilBmLcQFzu6tc4AQOwEX+1y76nqucxcSJFfqD1bKYyiSfm5iMd4mWD5NTeTIjk6joWL5ONN+i942/X/mF+JP1Z8gp1NAlwo9x3RqnFe18svkdrNNzi+j6zgY7SGMdpn67l2Wt2ZLUHNOSZ7IK7FPxuL4ilBmBoB7gKnUlXFGViUnN5WhcBjIJbg1Ng7SqLqbq9CkoZEfsZUblVtxB35hfQFR0LK+lpnFLdq7Jez/070OsOrWfJQf18QxvjrkOmYNTsV3krUFGnuGeSrXx6YYzZteVqS0929GxZa+vOG7zNXv+b2OdY5qRQnxGPgXFJVy6avr7tSEjlJn6jKtc4VyGBvz3cBGLiCRzva+MVaVWmf5tmhAQU1qXo5KLyRDGfou7snN4P/WqyXvvTdzLq3sfQB2yhBFd3OjRwrXLGuQWajgcm2GftS0IRF60J7bGMR+pdjfNTTLndaZW2an/U128pfipyuuesjNsOJnEqC+2M/DjrRy8ZNuu8/URi76ZMjIy+PHHH3nllVdIS9P/EQ8dOmRWobx6TwNVJNK82zlbBIFL4xpKVRk6nY6VJriYzOVYdCyfJqUA4FlLr6bOfoNA0qH0O8SBkpf46vBX5BY79k65NmtERl4RG08m8f4/pxj79U46z/yXV5fb3poA2Kxy7+OKv2s9r5acVyH4TeUv5c8VDlRspioMZ/ZeTNW/1/4uzeRzNNkFrlOt2ewotWPHjjFkyBB8fX2JiYnhoYceIiAggL/++otLly7x888/20NOgYPwaz/Q2SIIDBBkh1RPS1DIzbz/UXlDkf0aIZ5KyOZ8cg4qhYyRwal1uphMRQKG5eUTFR1LtFLBreFhNcbckJfP0YRx5BZcR6t2m0kqOs33x75n2dllPNntSW5rcxsKA93Oy9YbmZPLRymmW4GM4UV++fPkrAL2xaSxL1r/OJ1Y828f6KXCSQYGs+ghnTF7jiPdTHOUX/Fo8bMO28/V+GlXDG/9fYJ3b+vIvX2cnxBjtjIzY8YM7r//fj766KMqxetGjhzJpEmTbCqcoA7s4HqQqSzoACRTgtYVNHTXshrYEh93Vd2DHEBTc/uBKd3tqsysPKq3Bt/ULhiv86XVaOtwMZlLy2INr6am8X6TqhXQZyel0LYgn2Z+7Vg1/iF2Jmzl84OfE5sdy8zdM/n11K881/M5BlRrRVGmGK318uTezGw6FZkfa1KZVrJEXlp6jH0xaUSn1rQKtQ7y5PqWAVzfMoBekQEESZkw26ot7Y4MLYtV/zN4rjaFxVZ1kEz5Jhkh3w+u8LXnJN76+wQAb6w4Xj+Vmf379zN37twax5s1a0ZiYqJNhKoXmNCJt9Ew+hNY9bSzpWjYuEjMjCspjFqtjtVH9VVRb+0SCltX6E9Y6WIyxB3ZOex3d2ODZ0UhvDL18pVR7XFXKRjSYggDwwfyx5k/+Pbot5zPOM9jGx+jX1g/ZvSYQbuAdjUutZOahXAwOrZ8LR16o0lZzeFMmQxvraFWg1X544A+AFmS4NoQH65vGUDvlgH0jAwgyLtq493CDMvT0R3FZPkGlFL9KQboysUkGwtmKzNubm5kZWXVOH7mzBmCgoIMzGig9H0c1r/ibCkqCGgFaTYonuXV1Pw5/pHW7yuwPdP+hfnDbLumuUqVHZWwQ7HpxGfk46VWcLN/ss1cTIZQAp8lp5IrSdwf2pSHShWC6yMDGN2posCbUq5k8nWTuaX1LXx/7Ht+O/0bu67sYk/CHm5rcxvHmoXUWLtHS31X7Tuzstnh7k68UsGPCUmcUKv4PEAfUPxUWgYPZ9b83i3jkYGt6N0ygB4tAvB1t6xtg6MpKDaurIyW7zV6rp1kvBKuu2SdlcsWuFPgbBEaJWYHAI8dO5Z33nmH4mK9fU2SJGJjY3n55ZcZP368zQUUmMi4ufBA3Sl9tdLtXuj1oG3kcQoN+e7IAqWgeW87iGHmV0ak/bp9l7UvGNahKeqzpUGjNnYxVcdTp+PPK4kMy9PHqbx5y3UGe9H5qn15odcL/D32b4a1GIZWp2X5ueWcVxl3F/7h4028Un9/+WBo03JFBuCrAL9aPRqvjLyWm9o3rTeKDMCKw5YljBgLhnUVflB+6mwRGiVmKzOffPIJKSkpBAcHk5+fz8CBA2nTpg3e3t6899579pBRYCoRvaybP3YOKNR1jxM0YsxUqlreaBcpiku0/BOldzGN7RJmsywmc+nYzLfW8xE+EXw66FN+GfkLnYM6W7XXTncL4tlcmKIS16kXY0sGyE84W4RGidnKjI+PDzt27GDZsmXMmjWLJ598kn/++Yf//vsPT0/RbdmhNGnrbAlcDDt8ATbrafaUi7cut70c9fe73S7sPJ/K1dwiAj1V9PdKsKuLyRZ0De7KopGLrFrjqZAglnpXfMdeVCoorMfvC1cRXWuFQfcVxa80bItw/cHiBiI33XQTN910ky1lEZiLTG74eSMl1NcNbB3bOPGnusdUQ6twTLdkp2BuDEy7UXYJDi9rXzC6cyiK06XKo51dTNYiSRIeWi15VhQenNkkkBE5eex3d2N60yA6FxTya4LxDtOGkJ1zLTeNyoADTadznKqj0epqva0fJ9vOk4oVPFT8XI1zjyjWsL7ESou4BVT/6wh1ygJl5ssvvzR4XJIk3NzcaNOmDTfeeCNyubi4OoTrH4aMWAhtwE0WTaSZvzvULChqHb7hNl7QUlzlPtZMObyC7SLFvyf0F/BbO4fCqhX6gw52MVnCP3FXGNTCuvdU38iI8ufH3Mx0Cx/9A+UaF8k8lCSekK/gBeWSGqdkknEXlCOorBx8rvoWgI+VNbN4QV+x2F5uMQ9q79PUV3aCG2XHSNbWVLSsoVBTwrmkHDqE+RiMCXNFzFZmPv/8c1JSUsjLy8Pf3x+dTkdGRgYeHh54eXmRnJxMq1at2LJlCxEREXUvKLCOUR87WwKXqYYsucwF3w74ushnyZIvtqcOwVfdbSpGTqGGZn7udFdfdq6LKeUMeASCu79J1lHvWqoJ252jf8CKR+22vCWfPkOKDEBv2WnrhLEDbjg+U6q1LIGXFL8bPf+7Sh+nuja1JWC7G9qHfj7ItrMpvDu2A/f2jbTZuvbEbHvn+++/T69evTh37hxXr14lLS2Ns2fP0rt3b7744gtiY2MJCQnh2Wcbb2VEl+fWOc6WoIFjY+Xu4f/Ay7KyB7k6F6iHFNjaLsve0iUM2amV+hfOcjF9fT183BrebQIftYI5vWD+SPhjst69tuld2PMtHFsC5zdhj9KHJ1UmZDAd/QP+egR0Wko6u0ZxU1e+9XCGbBdScrh3Xs2U9McUq+qc619o21ZC287qW3ks3BVj03XtidmWmddff51ly5bRunXFF1SbNm345JNPGD9+PBcvXuSjjz4SadqujLnptQLnEtbV4qkKuUQtTYbNx9N1akmN7RIKS1foXzjLxeTmCwWZoNNC3lX9g7O1TjkaHUuiQs7wiGY2EeF/gQH8VuuGi+GvRwEd9JhKydD3kR+rdYZFaJxpdWoAPPTzAS6miA7YlmK2MpOQkIBGU7Oxh0ajKa8AHBYWRna2/UqYC6xE5aJZZ4FtICcZCo0XBxOYh0ous60y4+Zjw8Us55pgL9pLMc7PYno5FkqKIS8N8lL1ykxuaoViU/48FXKvQvIJZECYpoRgjYZkhcU5GOUkKWpxbx35HVY8Rpkiw+jPoNg+7pI/9scxrpvp8UD1JBTDJGxRATghw/Rie21ll/HQOq44X3JWAa/+FcXkPi0Y1M4+cXDWYvYnafDgwTzyyCP8+OOPdOum99EdPnyYxx57rDy7KSoqipYtW9pWUldEkunvyOob7cc4betcnRpPqTSo7Z6lcH6TPtZg9xwY/j4sq89F+1yPBnS9qMLYrmFIJ0tjCZydxSRXgndT/aMu3q6oS7MwIZkl3l7cm5VNUEkJWTKJ25qFkVqbcmKAZIWCuKw4InyqxVUd+Q1WPA7ooOc0GPUpWJFJVRd7LqZRqClBbaL88hLnV+s1hxApzdkilPO44m9ule9y2H5v/X2CjaeS2XgqmZhZox22rzmY/c6eN28eAQEB9OjRA7VajVqtpmfPngQEBDBv3jwAvLy8+PTTRlAF8THHvZkspnnfmsfk1t8N2oRrhsLIWTD8PXjlMrQdDj2m6M+1bCDdu8NElpk9uKVzqNMK5dmKCI2G59IzCC4pQQJ8tTo2x8Wz/HKC2WuN+msUj2x4hE2XNqHRauDwr5UUmQfsrsgAKNGweJ/xVgPVaXlltR2lsT2BkjFvg3MSIMKl1CqvN55M4pnFh9l0KokijW1usnMK9V6YxCzXb9Fg9lUtJCSEDRs2cPr0ac6ePYtOp6N9+/a0a9eufMzgwYNtKqTLEnytsyWomz6PQ+xuZ0tRN+rSDuw3vQmtBkFEH/PX8K7Z98YpVM7u6vcULJ3mPFncfKG44fnhWxRfdL6LyQ5IwDXFxayPi6cYiYnNQkyqSyMhsevKLnZd2UWwwovbU+IZL5cR0u1+GP2pUZ9OMRVNLa2lCZl8veU8d/aKwE1Zt3VGrnVdy4y3lO/wPa11uz348wEAVhy5wr19WvDubR2tlikpq5D4DMf/LSzBYlW9ffv23HrrrYwdO7aKIiNwIZ6JgtaupVjW+XlVqCx3G9zwHFx7S8VrSxQiW3Pdbc7df9Jis4bnNOlqHzlszckV+p/OdjHZiTBNCS00GvZeulzn2F+uJLLm9jU80PEBAuQeJGty+M7fl+HNm/GUexHb4rdToq3a1FEL3BnWlO4tm3NWabt+TsnZhSzac8lm6wlMIzYtr8rrX2z4P5gyf5+rVN+oFbMtMyUlJSxcuJBNmzaRnJyMtloE++bNm20mnMBK/JpDoWsFYqsUEhhvlmsdam+4c1FFXIKhWx21LxTaukxwbdShvrUbDWfW2G/70C7mja8vUZn13MVkDkvjE9jt5sY9Wdl0L+2wXZmuhUXgHcEzUiBPnD/DJk93/mzWln3FaWy9/B9bL/9HmGcYd7S9g3HXjMNH5k3XyAh0pf/r8eGh3JGVzVtX062S08tNDgXw3X8XmNS7OR6q2i8vOhd/r02XLydSluhsMUwir6jml2pekabO/4EpnE/OsXoNR2C2Zebpp5/m6aefpqSkhI4dO9KlS5cqD0El/COdLQHIKr2Zez8KTx60735tR0L3KRBguLaIwgXaLujc/ese5CjumOdsCeonDdDFZIx2RcXcn5WNEvg3Np4PklM5GB3L/IQk9seUxqgc+gX+fgolOkZcdw/z7t7KyttWcu919+Kj8uFK7hW+PPwlQ/8cyos7X6qhSCz18Sa/0rFYhYJv/XzIkpmucIzqFELzAA9Sc4r4ZXfdloFiG8V12IsZyqXcLt/hsP2sUe0MZVN1fvtfi9drKSXwpPwvvMire7CLYLbatnjxYpYsWcKoUaPsIU/95qbXYfP/9M+fPAA+zeD90FqnFHi3wC3bjmZZpTsM+x9oCuHG5+20SaUPkkwOt34J2z6u+Fu4GFKznnB+g7PFcEkUchlMXg6Lbne2KHXTQF1MtRFaUsKYXP0FpldBpVL3fz8F6PTtTUZ+BJJEK99WvNjrRaZ3m86GSxtYcmYJR1KOsCluk8G1R4aH8VVSCh2KihgdEQZAtFLJRylXTZJNIUlMv/kanv/zKN/9d4F7+rTAS238EuPihhkzkGguS3G2EDXQWNFBc6PqeeSSjnAphZc1D9tQKvthtmVGpVLRpk0be8hS/6lcjK7JNaCqo+Hgkwdxa+qAztf9nrKjIuPCyA3UWzXnC9RSF4Ytv6VHOrZdhVvXidDmZofuaTGNwMVkOjq4/pFyRaYybgo3bml9C7+M+oWltyxlfGvDiupVhZxJzULoUsmVtdbLkxnBTUwTQZJxW9cwWjbxJD2vmJ/qqB5rr35G5hIoWVfXyttG1gtX6oEkl/SKUE9Z7QUgXQmzlZnnnnuOL774Al19iAhydZo0RqXQAe+bW7+CgFYw5nPL1xjzOdyxwLK55nw2ZMbvXIs9gqG3g++KQjo5dj9LaSQuJpPp/SiM/LBORbpdQDue625eU8INnh4kyeUm1V5UyGU8ffM1AHy/7SJZBTU7YpdRYoXlwJb4SdZl+8lsWpVSYClmu5l27NjBli1bWLt2LR06dEBZLRJ++fLlNhNOUI+Rm9nN15Z0v0//MIgEChNk62mjdOq67rbkSrhvJWiKILI/vB9WfkqpckBfpaD2kOJ6Tf3qpBG6mGplxCyTLYIKyfyg0CHNmzE4N48vk1ONjmmZtR8YxC1dwpiz5Tznk3OYvyOaZ4YYtj7nGAhaFQgsxWzLjJ+fH+PGjWPgwIE0adIEX1/fKg+BmbiQadGm2EoZsAfD37Pr8mYbLVsNgrbD9G0mXrhoD5EM88R+6Fith1p9eT8KF1NVzPi/KeSWBeFv8fTgVC1NLQdd/gZ0OuQyiWeG6K0z87ZHk5ln2DpTT95pDqPs7+GL62UPtZQS2Kp6lgnyrc4WxShmq+gLFlhoehcYwUU+0h4m+sVNxVXvmiXJ8VlmoV0g4ahpYz0D7StLZYIcEK9lL4SLySlMbBbK4ehYgxcOr+I0OL0Grh3DqI6htA85z+nEbH7ccZHnholaZHVRdg901M0617IXeXyv/IxV2r6Ada0H2siu8ID8H4bJDxApS+Jj2feAY+P4TEW0T7YlLQeZNq7NULjL9l1rAWhqZtVHn2bw8FZ4yoqU7eb9LJ/rcJygPN63Eib+4vh9TcGVLWi14arKciOgW8vmHFcZCK4H2PIeaEuQyaRy99L8HdGk5das9usqAcDW4mq/xcOK1fSTn+QDpW3KPryhXERvmeu7oi1SZpYuXcrEiRPp06cP3bt3r/Jo1IT3gIe2wPPnax83eSm0L9WYbW3Wn7wMBr4Ez540fU5YN3D3s3xPZaXYjrrW6XSH/mezHpbvZw5+1YqMOaPrs7s/XHer6eMHPKv/OWKWfeSpjGd1i5yrfTULbI4kMTcx2aol7m4WQhGQWb0OTfJJOL4MgOEdmtIhzIfcohK+31bTfdpQ3mldZBdsso6t/h7e1I/2A7bGbGXmyy+/ZOrUqQQHB3P48GGuv/56AgMDuXjxIiNHjrSHjPWLZt3BK8j08QGtbLu/dwgMfhV8m9l23bq4Y4E+9mPITONjBr8GIz6E23/Ud8x2BI/vgQcq1ZQZ+7UDNjUxaKa6olXGkLfh5bgKhVcgsDH98gs4FB1LoEYfhNszv4DF8eY1uOzRsjkDWkTwbHATdECCZ3v9iS3vQ0kxkiTxbKl15qddMaTmFFZdoL7EZ9XBVMX6Gse0FmRqBZDJq4pfbSGSVVgiuytgtjLzzTff8P333zNnzhxUKhUvvvgiGzZsYPr06WRmOrJMfANh0Cv6rrb3/+NsSayj4+16d0qNO/1KDHxRX3un8wTwCHCMXCrPqp2rm/V0wKaVvgxq+8KuJS3bKRYkI1z17aB/4u6g/5nAISiBrXHxREXHsiAxmVCNZdlFGz09OKJWcaDpRPAMgvRoOLwIgJuvDaZLuC/5xSV8t7WqBaOB6DIGeWe1GZbxUt7lGx5W2LG1iYmsPBpf6/nYq65ZFdhsZSY2NpZ+/fQxEu7u7mRn63v/3Hvvvfz++++2la4x4OYDYz7Tp+U6krJskP7POHZfZyBXwnNnYMapqi4xR9P/GfBr4bz9AR7aDMHXwYOGq8Aawr33NH2W1YxTdhRM4GxUVtQOy5PJKJTc9c1eAf77CIoL9NaZoXrrzC97LpGcVWALUV2ehXUUDDREB+oIT3AQl+pQVm78eIuDJDEPs5WZkJAQrl7Vl7du0aIFe/bsASA6OloU0qtPjJ8HT+yD6x+y3x61WR4cjXcI+IQZPHXIezD0f7rigMzaLsJGbjmHzoSnTcxqshfNesDjuyHciIXKv6ay5aFW6LOsnKkICuyOl07HS1fTeelqOuOyzUsPfjQkmFA/d+gxFXzCIfsKHNAHoA5sG0T35n4UarR8U8k64650fp82QcPBbGXmpptuYtWqVQA88MADPPvsswwdOpQ777yTceNE7Yd6g0wOQe3sa+ttVz9iqHSSDIa+U3HAiNJjE1zdtm7P313g8kzOymZyVjbvpKYxq5YCeYaQSZJe4R34ov7A9s+gMBtJkspTs3/bG0tCpj5A1ZXK97sCgVK21WsEkEVLyTGdvpuQycPyVQTiGuElZisz33//Pa+99hoAjz76KAsXLuTaa69l5syZfPvttzYXUNBAcCUrjTHuWQahXW2QNl9fLZTi4iKoYFhuHoNy85iRls6x6FjG12GtiS4pDSDuOgkCWkNeKuz5DoB+rQO5vmUARSVavt6id6cIZaaCk/EZNlnnkNujDJI7xvr7o+oTXlX+zreq2Q7Zry7MVmZkMhkKRcWFaeLEiXz55ZdMnz6dlBTX6xzqMCRRsqdWrKljY2ea+Zc2BL1mCDzyH4SYWaunoWDs4uLj4Mw4gUugBL5KTmVqZjYS8FZqWq3j/807gEar0ceoDX5Vf3DXV5CXhiRJzCiNnfljfxyX010ziNQZ6HQ6ViyzLovJg8K6B5mIZOJNTdfSlPTrZWdstrc12OQKnJiYyFNPPdU4u2lPWa0PqJy6tvZxEX3gtu9g+mHHyOUKVM4ccnTVXTMI8RGxILXSZoizJaiKZ7CzJWiU1HWJO1h0lnv/uZcLGRegw+0Q3AEKM2HXlwD0aRVI/zaBFJfomLPZNYJd7UVvyfRg+X9PJtEzZZlV+01QbLNqfmUiMvbWOebFpU6O/TOAycpMRkYG99xzD0FBQYSFhfHll1+i1Wp58803adWqFXv27GH+/Pn2lNU1aXmDPqCyeR/D5ycshJDOcNs30PVu29eVcWX6PK4v/PZ43R8OgR1ReVs33+XcAfXVjecaWPPf/CfuCoNzDVtVVCg4fvU4E1ZN4McT89EMfkV/Yu9cyE4CKK878+fBy6TlGu+oXd/5Q/2uSeMKNSX8uHobN8sO2Vki0wnLqltRWXLgsgMkMQ+TlZlXX32Vbdu2MWXKFAICAnj22WcZM2YMO3bsYO3atezfv5+7777bnrLWTzqMg0e3Q2BrZ0vieBQq6PMYBLd3tiSuxWB9zBmjP3PMft3vNX/OsPf0nc/NSOF2GAGN8LNkUyxXZyI0Gr5MTmXLpZoXs/f8p3JDsxso1hbzxaEvuO/ib1xo1hWK82D7pwD0jAzgxrZBlGh17Lxwtcp8DZAua1zu+p92xXBj9hrkkvUK+gBZlA0kqr+Y/M5Zs2YNCxYs4JNPPuHvv/9Gp9PRtm1bNm/ezMCBA+0po0DQsBj4IryWBK0HO1sS4/R7El5LMJ7C7UzusE3PGYHlNNFqiYqO5ePkVFoWFfNbfCKBCm++vvlr3u3/Lt5Kb6JSjzNBncU8X280BxdARhxAeexMIFkUSBIxCgU/+XjTrWVzbmwRTpyiHiQL2IDUnEK+3XSau+SbbbLeItUHNlmnvmKyMnPlyhWuu+46AFq1aoWbmxsPPvig3QQTCBxGF9taFE0qt+TImi2tb9b/lIzU9RhU6g4Y83nV4zLn1gGJ8+hg+IRvuGMFERhlRG4ef8cn0KmoCNAhSRK3tbmNv8b+xYBmAyjWaZgd4M99wf5c3PwmAF0j/Li5fTCgpVdkBLdEhPFJoH/5mv96ujvnl3Ewn/57lhuKdxEkZaHzDnW2OPUek5UZrVaLUllRTEwul+Pp6WkXoQQCh9LmZmdLYF/a3Az3rzFewXfQy/oKvz3ud6hYdaE1pnwJXBJJpy1/3tSzKd/c/A3v9HsHb4U7UW5qJmTtZ97ej9BoNTw7tC1p6sbZEBHg5JUs/tgfy2SFvm+c5FKfvdrdkHfKtzBR7npVgE225+l0Ou6//37UajUABQUFPProozUUmuXLl9tWQoFAYB2SBJEDah/jGegYWQSNBkmSGHfNOPqG9WXmsnHsIIfZp39hc+pR3h3wLukqw8rM7AB/Zgf4cyw6tkFWPtLpdLy7+iRtidWnNcsU0H0KbLW9myi3UIOn2rZuuw+VP9h0PVthsmVmypQpBAcH4+vri6+vL5MnTyYsLKz8ddlDIBAIBI0Rw/7VEM8Qvhk6l3dSruKl1XIs9RgT/p7A2aArta42NaRqCv52dzeOqFU2k9ZZbDiZxO6LV7lPuVF/oP0Y8LGPm+mzDWftsq4rYrLKtmDBAnvKIRAIBNUQKdj1CamWYDEptDPjWgyn7+mVvN2iHTu1OaQqimpd76C7G397edKzoAC5Dh4vVW6iomNtKrcjKdSU8N4/p/AijzsUO0EL9LJf7Omh2HSz56Tl1f5/cVUaVx6cQOAAmnhZ26iyETBghgmDXNvJkC2JmMHKVI6ZMcjg1wjRwrcXT/JO+6kmrflaUCDDI5qxyqvq33qJtxe/+nhZKqrT+HnXJS5dzeM+j92otPnQpF3dLmArOBybYfac0wnm94hKcoFu6EKZEQhsTIBH/TeF252I6+sc4up2mWRZU2eL4FLU2WupSRvoejcSMO70FnoVNDd57S8C/Mqf50sS7zYJYFZgAGeV9efGITWnkC83nQN0POpRGkDb60GXK0ppyefu+T+dXxFYKDMCgcAlkVxenamn2OniqTNl3YEvgVwF0dvolW9Zt+WoSnEzU0ODeTAkmE4tm/NhgJ9Lv2M+23CW7EINdwdfwifnIig9octdzhbLJpxJtL7jt7UIZUYgENif1tXT3yV4ZDvZbW8vP1Iy4wxnle0cK5fAsfg1hx56F9OjGZZVrH0gtMIiliWXs9ddX7Npka8PP/j6WC+jHTiVkMXiffpYn+f9d+gPdrkT3FxT3vqIUGYEAlvjYmZjl2D0JzWPhXYmvcf0itceTdBSUVvGpOKDTiTIW+1sESyiTneQpeuaOvCG50DpgQQsiU+wqQxfVXJHuQo6nY7/rTmJVgeTrlUSGPev/kTPB5wrmA1xha88ocwIBAL7IzMS21D5W1CS8HWvGGfT70eV7YNFfdwaR9l90zHxP+bdFHo/AsC1RcXsj4njuavp3JqdY0fZnMfGU8nsPH8VlULGS8F7QauB5n0hpKOzRTOIzsUD740hlBmBwNa4uknBhWnqa/82D7tD7qnyOqfvC3bfU1CNfhUWOTedjvuzsnkvNc2JAtmHQk0J7605CcAj/SPwPfmr/oQd07GdQVJWobNFEMqMQCBwAqUWGaWs6l2gzF53hWNm63+W9aGqsqnj2iaUSPUn+8ZszPE1eASQLfOucfiRdH1QcFONxlZSOZWfd10i5moeQd5qHg87C9kJ4BkE197qkP1bS/EO2ccVcKoyExkZiSRJNR5PPPFEjbGPPPIIkiQxe/ZsxwsqEAisxLC1KtS3oqmgvNrF0Kb2rc4T4KVL+j5UlRn4svEGnHbgROQUm695rM0jNl/TEcQqW9c49khGJt8kJvPX5QQmZTo/Q8YarpanYsMLw9vhfqS08Gz3KaBwTPmGtxQ/O2QfJc5XPp2qzOzfv5+EhITyx4YN+qZbEyZMqDJuxYoV7N27l7CwMGeIKRAIbI3Sw8DBqupLusrGJd7d/WoeG/wKBe3H2XafWigxFjtkBbnuDaeLuBK4Ib8Ab52OhzItS90uKnGNCrZlqdgdwny4IyIXoreBJHNoQ9dWMtsGWBvjOcUSh+xTG05VZoKCgggJCSl/rF69mtatWzNw4MDyMfHx8Tz55JP8+uuvVbp2CwSCekxZ1dPqrolKrzWSSm9NeeUyDLdhE77qFiCFu5GB9YOIAEOKoeOxtYOwSYmWvTFxzE1MJqK42OR5Nyy+gRlbZ7DqwioyCjJMnpckl2NLNej30lTsN8dch+zgfP3BtiPBL8KGu9ROuJTqkH3GyXc4ZJ/acJlw/KKiIhYtWsSMGTPKUwe1Wi333nsvL7zwAh06dDBpncLCQgoLK4KRsrKy7CKvQCCwjNQB79DE1PiKMmuKA+NaTMagdal27BERFO7vGsqMufm5pmTNeOh09MsvYGFCMjc3b0b3ggIezMgq79NkiDxNHhsubWDDpQ3IJBndgrsxKHwQgyIGEekbaXDOCZWSu5rpLYG26tat1cGoTiH0bqaGP37XH+zVcNKxXQ2XUWZWrFhBRkYG999/f/mxDz/8EIVCwfTp041PrMYHH3zAzJkz7SChQGAqIpupNpp42z9jySGM/cbsKTrJFXIu7FQB2I4pvcElJeyNicNNp9+lqUZDkkJ/+XoiPYOv/f0A+OVKIsqHtrIlbgtb47ZyJv0MB5MOcjDpIJ8e/JRIn0gGRwxmUMQgugR1QV6qJE9vGlS+lwa9u8taVAoZr4y8FqL+gMIsCGgNrQbbYGXXwxXSuV1GmZk3bx4jR44sj4s5ePAgX3zxBYcOHTKryNMrr7zCjBkVTeyysrKIiHCcWU8gEBjAu1L8i6IWZabbZIjdXfrCxZXCJm3MnlKkFBVfLcWjUsmDf+Ou8GpQIK2LihmfncPX/n4odDq6FhZBkw50aNKBJ7s9yZWcK2yN28rWuK3sT9pPTFYMC04sYMGJBfir/bkh/AYGebiTrKi4FI4LD+Wvywko0b8Ds2QyPLRa9ru50a2wEHcTSy88OKAlEf7usP9H/YFeD4DMFZTZholLKDOXLl1i48aNLF++vPzY9u3bSU5OpnnzimZkJSUlPPfcc8yePZuYmBiDa6nVatTq+lmZU+BA2o+B06uhg+OCPxs18kr3urVZJ7reAytrZjPaEsmZdYAacA0ic+/NrbmblwGzUq6Wv95y6XIVZaeMMK8wJl07iUnXTiK7KJudV3byX9x/bLu8jfTCdP6+8Dd/V7LKAFxSKhkREcbLV9P5w8ebve5utCoq5qJKyU25eXyRbFocyuOD20DcPkg6Dgp36DrJ4t/XkVjyfwmR0u0giXm4hDKzYMECgoODGT16dPmxe++9lyFDhlQZN3z4cO69916mTjWtfbxAYJRxc+HCJmgzpO6xAvuh8qz62hXqogsswqRGk3aiiVZb5xhvlTcjIkcwInIEGq2Gw8mH2Rq3lZ9P1kxfTlYomFFJybmo0ivjmz1Nj0/yUitg/w/6F53Gg7u/yXMF5uN0ZUar1bJgwQKmTJmCopKpLzAwkMDAwCpjlUolISEhtGsnmtEJrETtBdeNdbYUAp8wGPaeXqmpFuTrqItj9cJ99Q/z5K/vv60tUMgU9ArpRa+QXgaVmdrQYmIacE4KnFihf97AKv4aIi23iABPx9TPMYTTlZmNGzcSGxvLtGnTnC2KQGAb5M77QNdL+j3p2P2qXc39PMz4f7UYAJecn4bqijQWJalLy4rQhy2xlwks0Rr+3Q//DNpiaNYTwro5TD5r6Ss7YdG81JzCxq3MDBs2DJ2JfmRjcTICgUvRtKM+FsdbFHk0iIkWl8rVgW2JxbEaHcZBi/6up8wI15zTGNw8HDetlmfTMpiYnVP1gnqgtOJvPbPKDJBbpswciEmnbdOaLSochdOVGYGgwSFJMGGhs6Wo94T7VVJmglzAtTxhIez7wdlSuCxyMzN1nBljUxlPrZZcK7KMCmQyPmgSgLtOx7ic3IoTmXH6OJlGkmRwKS237kF2ROSJCQQCl6TKta7VILjtW3hosx12qucZRq6g6AHtQ827K3cNVQbmJKXYZJ03gwJZ4u1V9WC3e0HZQOoq1cHc/y46dX+hzAgEgvpB10nQrIfVy7QPsaLWi7XWBBtbI9Kuf978eAw7WURk9bSGSs+CQj42Md26Lt5tEsDLQWWJKxL0FLGgjqJ+vvsEAkH9RV5HHSh1qbLRdoRdtvf3qFbftXLMXj0L3s5tOczZIpQjmWlrcYWqsfZgjVdpuYFrhkJAS+cK04gQyoxAIHAMg16FlgPrTomffgSmroV2o+wjR20JBw9uNHw8qL1NtnZqwb5SnC+BHleRozp/XU7gWHQsPfMLLF5jnadHvQv8re+IAGCBQOAYBr1k2jjPQPDsZ19ZqlDpsurV1PCQuxfbeiebEOxSfa7M/e3sY5lJzy3C38wUYWUlJbNNaYfu+YnJnFcquT081Ng0o7wQ3IQw36Z0NnumwFKEZUYgEAjKMNRqYdzcCndBpwl6hafL3Raub9sLuFohvsKr8/yfR00u91HGjXn59MovYFpGZvkxCbimVLGxhHvW3cv0zdM5l37O4jUEpiMsMwKBoHFRXaGo3PhS6a6vSFyYrW96eeUQtL+l4rybL8w47ToNA13AbVWBa8TAbDqdzI/bo3noxlYmz1Git8QYolNBIVFu5vf7k0my8u7do1uN5vGujxPhXXvTYx36v+JVmQytBEEldbdpEOgRyoxAIGjcuPvBLV/orTJq76oVif0MXHxcRZGxEHupHJKZVid7BgB/uO40PSL96d7c+n5I3ySlsM3DnSG5eXzl70tEsYZV3p50KCziDx/j6eh/jf2LOYfnsOHSBlZfXM266HWMbzuehzs/TLBHcI3x+93UTAut6uacm5BMvwLLY3caE/X7UykQCAS2oMf90P0+p2x9tWl/jngOqHrQjllVsnrfi6p2RncORaPV8dRvh8nIK7J6PT+tlltzcvHQ6XgpLYNJ2Tn8fiWJ168a7xS9JyaOVr6t+GzQZywes5j+Yf3R6DT8ceYPRi8fzWcHPyOzMLPKnOqKDMAjocGMDg/lR18ftMAnAX584+dr9e9kD1RY7pKzBUKZEQgEAodRU5GIazulppWiPnZYdpGKvrNu70SLQA/iM/J5/s9jZsfPmEPrIsPKkmelPTsEduC7od8xf/h8ugZ1paCkgAXHFzBi2QjmHp1LXnFerXvEKpV8EeDHuGah/OTrw7f+vk5WGwzztfJLp+4vlBmBQCBwKoYutq6hGNgX+/yO3m5Kvp7UHZVcxsZTSczfGWOXfQCWxSdyTTWFpl9evsGxvUJ68fPIn/n65q9p59+OnOIc5hyZw8jlI1l0clGde11UVdRHSlS4XoRIJ5moACwQCASNAyPX7zB/j2pHTLUmuFIAsOvQsZkvr42+FoBZa09xNC7DLvvIgXkJVQOHv62lPYIkSdwYfiNLblnCRzd+RHPv5qQVpPHh/g/N2ndURBinVMq6BzqQEMm4280RCGVGIBAIHIUB3UOSINjb9GyZTP9ONhTIhrS+yazh9lbD7uvbghEdQigu0fHEb4fIzLePc8Zfq+W50viZgJISky6qMknGyJYjWXHbCt7q+5bBgOC6eCY4SKiylRDKjEAgaFxE3uBsCWpQw2BTS5zHxfYP21UWS5EU7nUPciCSJPHhHZ2JCHDncno+Ly21X/zM5KxsPklKYVl8glnzlDIld7S9g39u/8fsPa8oFaz08uSJpkE80lQoNkKZEQgEjYs2Q2DyMnj2hOP3NhYmYmnwbHAHi0VpDPi6K5lzd3eUcol1JxL5aVeMXfZRAMPz8mliYV0YdV39yozwRlAg2zzc2eXhzrPBTXgquAl5LhKI7WiEMiMQCBoXkqRXaHzDHb51RI3YmFKuN93aUiXzSe56gaCuRpcIP14ZqY+fef+f00RdzqxjRv1kk6cHWz096B0ZQWEj1GeEMiMQCAQOIszXSC+lyAHw3BnHCtOImNo/kmHXNaWoRMsTvx0iq8D1kpvDijU2W+uusBC+8/MhvxFZaYQyIxAIBK6Ad4izJbAOF75wSpLEx3d0oZmfO7FpebyyLMqu9WcsYURurs3WOq9S8bW/H9/7+Zg1z9X+JuYglBmBQCBwFAYu+IavH8YvKlIDCfXU2Uv5KTFsdfH1UDJnUjcUMok1UQks2htrn/0t5JGMLB5Nz+TZNNulOJ9Q26+StKshlBmBQCAQOBxfNzvVSfntTijMMXiqW3N/XhrRHoB3V5/kxBXXiZ/x0Ol4IiOTiVmGZbcEc9XeemyYEcqMQCAQ1Bv8I1E0kN5KdvNKXdgEC0dDjuEu2A/e0JKb2wdTpNHy5G+H7SSE5XjpdCyJT+DtlKtMy7BO2VI7UDnR6pz7vhTKjEAgELgKt84BlRdM/Nnw+Ye2cF2YazYaNP+23k4XP49ASDgC84bB1Qs1d5UkPpnQhTBfN6JTbRenYkuuLSpmfE4uPQoKrVrnlEpZr+NgzEEoMwKBQOAoWvSvcaiKhaL7vfByHLTox+mQW2vO9whA7qqWGZl5lxO7XWKn/Qt+LSA9Wq/QxB+qMcTfU8VXk7q57t+ylBvyC1CUKiPjs813PyUrFExcPZE/z/5ZZ0NL0P9PioELSgU73I1k3rkoQpkRCAQCRxF8LYnDvq19TKlSUCJrPMGbNqVJG3hgA4R0hrxUWDgGzm+sMaxHiwBeGN7OCQKajgTsi4lj0ZVEXk9NY0ROLl0KCjkSHUtUdCzT0zLqXON02mne2f0ON/15E+/teY9z6edqHT8iIozbwsN4LCSY3W6mF/OTSc61AAllRiAQCBxIUeC11i3QYNwGdrSKeDeF+9dAq0FQnKsPCj7ye41hD9/Qyn4y2Agl0KWwCAXwccpVFiUkIS8916SkpM75z/d8nhY+LcgtzmXxmcXc/vftTFk7hTUX11BUUrXj99XcQpIrdeTe6eFeb3LnhDIjEAgEDiTC37IeRpl42VgSG9J9ivlz7O3hcfOBSX9Cpwmg1cCKR2HH51WUQZmLu5nq4pac2mN+JmdmMaXDFP6+7W++H/o9Q5oPQS7JOZR8iJe3v8zQpUP5/ODnXM6+DMC6qKq9pX7y9aFzy+a82iSQb/18eLJpELYr7WdbRC1sgUAgcCCStWk8rlicbvCrZk/JVjW1gyDVUKhg3Pfg1RR2z4GNb0NWAoz4AGTyOqe7Ogrg+4QkHg7V/y0fSc8kQSHnb28vfEpKeLHUDSWTZPQN60vfsL4k5Sax/Pxylp5dSnJeMvOPz2fB8QX0b9af6IudwYBnaZW3Z/nzLR7uDM3Ld8BvZx5CmREIBAJXxFXcSe3HwOnVtY+RzDfyFyj9LJPHXGQyGP4e+ITB+ldh31zISdQrOcr6FeRqiL4Fhay4fIU97m5MzMpBCcxMTTN6cW/q2ZTHujzGQ50e4r/L/7HkzBJ2XdnFjvgdoN5R534zmgYxLSOTG/MK6FFoXbaVLRFuJoFAIBDUTvf7aj/vKopXbfR9AsbPA5kSTq6EReMhP8PZUtmE1sUa7ilVZMA0K4VCpuDm5jczd+hc1oxbQ3ff29BpTHOBzvfz5f6wpnSLjGB6cBOXiKsRyoxAIBDUA5x6wRj9mb6z9/h5hs97BTtWHkvpdAdMXgoqb7i0AxaMcrZELkFzn+akXx5O7vmXzZqnkSS2eHpwxAXaJghlRiAQCFwRe8bGTF5u3ni5EkZ9rFcGquMTbqGsTor9aTUIpv6jj6NJPuEcGVyMmNRcjl3ORCFZppTcFxbidIVGKDMCgUDgRCIDTctSKr/0B7S2ftM2N9c8NnWdZWtZqHQFeNqpN5MphHbW16IJbOM8GVyI1ceuANC3VYDFa2z1sCxLz1YIZUYgEAgcStWLv6+7mRf1ptfBXb/Dw1ttJxJAi77wdiY8vgfu/NW2axvgmmAnp5r7t9BXCxaw6qg+JfuWziH0zC+waI14hXPziYQyIxAIBI6kyTUQeUOdw/JUTYyfbD8KwrrZUKhKBF8L144xfv6276q+tjD4V7IgA8rmeAY6WwKncyYxmzNJ2SjlEiN9YxmeW3fbA0Psc3L7Axd4NwkEAkEjQpLg/jpSnTHUzsCOIcAKAy6ClgP1P3s9UPV417vhqZr9jgT1kzIX08C2wXidW8kEC3pAuQKizoxAIBA0ZtoMhQkLah6fvFxfj8U3vOa5QBvE7Qicjk6nY9VRvTJza6cg2LgSORAVHUuuJHFreGiV9ga1kSZ3bhFCYZkRCASCeoDOXtk/fhGg9q55XK4wrMgIGgzH47OIuZqHm1LGMPezkHe1/JynTseS+ES+SkyhlwlxNO5arT1FrRNhmREIBAKBFbhCyTSBJawqdTHdfG1T3M7WrCEUqNUyKD+fQfn56IBjahWTw0IMrrU5Nt6eotaJsMwIBAKBM1H7GDwsVASBPdFqdawuczF1aAKnVtU6XkLfvXt+QlKNc/dnZOHl5CrQQpkRCAQCZ3DLF9D3SWjex6Thbor63xhR4Docik3nSmYBXmoFgxVRUJAJ3qF1zutVUMiUzKzy14GaEh7JyLSnqCYh3EwCgUDgDHrcb9ZwtVLcewpsR1ng77AOTVGd/lp/sMM42PNNnXOfSs+gY2ERffIL8HNyrEwZ4tMhEAgE9QCpfS21X6whcoBl83o/pv859B3L5tuzXYOgVjQlWtZE6Qvlje0QAGf+0Z/ocLtJ89U6GJGb5zKKDAjLjEAgELg+t86BjqZdaEzmmShIOAbtR1s2f8QHcOPz4FlLcT+BS7I3Oo3UnCL8PJT01x2CohzwbQ7hPZ0tmsUIZUYgEAhcne732n5Nv+b6h6VIklBk6illLqaRHUNRnPxYf7Dj7fXaWibcTAKBQCBwPJZahARWUaTRsvZ4IgBjr/OGs+v1J2xt+XMwQpkRCAQCgeNp2oHTXV52thSNjp3nU8nMLybIW831hftAU6DvHh7S2dmiWYVQZgQCgcAFqb8Gf9PJ92jmbBEaHWUuptGdQpGdWK4/2KF+u5hAKDMCgUAgcEU63uFsCRocBcUl/HtSX/TutvaecH6j/kTH8U6UyjYIZUYgEAhckMZQAbjWflND3naYHI2FrWeSySnU0MzPnS4520FbDMEdILi9s0WzGqHMCAQCgcD1UHk6W4IGx6qj+toyY7qEIpW5mDqOc6JEtkMoMwKBQCAQNHByCjVsOl3qYrpGDRf/058wsVCeqyOUGYFAIBA4BZvEnIZ1L396VtHWBgs2TDadSqKgWEurJp60T98CuhII7QqBrZ0tmk0QyoxAIBAI6i8Pb3G2BPWCsiymMZ1DkY6XuZjqf+BvGUKZEQgEAkH9osdUg4drDShuxGTmFfPf2RQAbmsjg0s79Sc6NIx4GRDKjEAgEAichM4VUrYiejtbAruz/kQixSU62od40yp5I6DT/95+Ec4WzWYIZUYgEAgETkGqLQG9toAaWxZ4m7rWdmu5KKuO6V1Mt3QJg+PL9AcbkIsJnKzMREZGIklSjccTTzwBwNtvv0379u3x9PTE39+fIUOGsHfvXmeKLBAIBIKGhEzubAnsSmpOITvPpwIwNlIDl/cDElw31rmC2RinKjP79+8nISGh/LFhwwYAJkyYAEDbtm2ZM2cOUVFR7Nixg8jISIYNG0ZKSoozxRYIBAKBI2jaseax9mOg75P6510mOVaeesjaqAS0OugS7kt4/Dr9wcgB4B3iXMFsjMKZmwcFBVV5PWvWLFq3bs3AgQMBmDSp6hv1s88+Y968eRw7doybb77ZYXIKBAKBwPbUGrCr9IDRn8H8YVWPD35Nn078WhIo3Wwih1YnIZNcIYDH9pQVyrulSxicaHhZTGU4VZmpTFFREYsWLWLGjBlIBvyhRUVFfP/99/j6+tKlSxej6xQWFlJYWFj+Oisryy7yCgQCgT2J8Hd3tgjOo0V/UKhBMuA8UKj1P22kyDRkktUt2BeTBsCtEXmw6Sj/b+/e42M68z+AfyaXmUxuIwnJZJKIREhcUiVYoZGoSoIQ1RW3prQorbiUUl37W6kt0S61vVCqQdfasiVaiyIWQaUpIRUi6pK4JZEiEXHJxXx/f9g5cmRuiSSTSb7v12tecp7znOc855lj5jvPec5zILEEOgw1cc3qXqMZAPz999+juLgY48ePF6Xv2LED9vb2sLGxwfLly5GcnIyWLVvqLCchIQEKhUJ4eXk1ndHajLHmw7M5BzPKwP/90TC9JWb+wGidvisPBgD0bOMM18u7Hie27QfYuZiwVvWj0QQziYmJGDhwIFQqlSi9X79+yMjIwNGjRxEZGYmYmBgUFhbqLOf999/HnTt3hNfVq1fru+qMMVYPmug3bD3ieWbE7pU/DgaHdHEHNBPlNZHHFzytUQQzly9fxr59+zBx4sRq6+zs7ODn54devXohMTERVlZWSExM1FmWTCaDo6Oj6MUYY6zxsbWu26+g2oYyem8RN3MWEiBKWQz8fhawlAIBg01dpXrRKIKZdevWwdXVFYMHG25kIhKNiWGMMWae/JUOpq4CgKbdo9PHryWccnY8XvAbAMhbmLQ+9cXkA4DVajXWrVuHcePGwcrqSXXu3buHRYsWYejQoXB3d8etW7ewcuVKXLt2Tbh1mzHGmq6m21ugoe1mD4NsnfWsbPptVlNDAt2BnzUT5TXNS0xAIwhm9u3bhytXruCNN94QpVtaWiI7OxvffPMNbt68CRcXF/To0QOHDx9Gp06dTFRbxhhjJjHpAFBZBsidTF0TEbJ1geT+LVNXQ6eBLW8Aty8BVnKgfWS97afY72W0qLfSDTN5MBMeHg7S8oAOGxsbJCUlmaBGjDHGTCpofPU0j271uEMJatur07gvUBEcLmx//Gf7CEBmX297eujcod7KNobJgxnGGGPNlHcf8XK/+UDPN81rXEejeFqmdlYWEuDMtscLTXCivKoaxQBgxhhjzZCtM/D+NaDHRMDB/fG/5hTINHLPS84Dd64CUgeg3YD63ZmJJ+vhYIYxxpjpyByAwcuAWWcNDO41zMvJtlbb5ateqt0OR2+u3XYN5EWLE4//CBgEWNfzJIwczDDGGGv2tH0ZWtRsJIStrHYjJ/JV4YYzPSXNPRbwr78BtXWqAS4xSUx8uY3HzDDGGGucVF0fPyVb4Vm/+9HWqeDaEXhYApRce7xsKQUelVfPJ3MAHtwWpzWmp3nbtAB8+9X/fkw8Epp7ZhhjjDVOEgkwaiMw8KOG3/fbqYBH1yfLb6VqzxcyW7w85jsganmNd1fp6F3jbYzSYQhgJa2fsqsw9V1dHMwwxhhr5nR8FbeoEmC09BOtEi6qdH1VvE378Fo90Zvqa8xJg93FZNpwhi8zMcYYY9qEvgc8LNYfEFhY1tHO6ikYaBNSP+U+pVazOdchDmYYY4wxbWwcgegVDbIriaSeBtBaNszXfL31LBmJLzMxxlhj1Mim7Wf1y8rGscbbqGUKvevLyLq21akxU9/NxMEMY4w1Rl3GAIEjGqxnwKxJ//f07Ya4a6e+RC6p+TaSxvMVbuKOGb7MxBhjjZKVFHjla1PXwjxM/Rm4uB94bqSpa1J7Cg9T18CscTDDGGPMvCk8gW6vmboWDa8R9cyYumumEbUEY4wxZr6KrV1rv3EtApPyzqPECe+eFy025CgWnmeGMcYYawLOOfau/cYKL8CvZg+DJJmDOMFeHEw17O3S3DPDGGOMNR49Jjb8PiUS4NUtdVqktVVdzYFjmH3Hen4qtwEczDDGGGvW7Ks+oHLSfiDS8OMTSMtFHEl9XNgZtFTnqoo2L+rd1KIBe2ZksprPelyXeAAwY4yxZq29W5XLNR5BpquINpa6n6ukbmHoeU58mYkxxhhrFkw9R0pt1Uu9Dd3ePrZuL4XVFQ5mGGOMsRrycbEzdRXqh5VM//p2ph0bowsHM4wxxpgx/AcJfyoV1ceIkMlvUK4D1uYZpHEwwxhjjBnDxU/vaoW8Hp6F1NDXwPrOadj91REOZhhjjLE60M7NvoH3WA+Bjp1L7bbjGYAZY4wxM2DgC9uyjr/Qr8gDAAvdvT2SpnBZq45wMMMYY4w1Eo+cn1zKKpD5Ap1eBlTdDG530mcyAKCymc64wsEMY4yx5s3Z19Q1EFgOfjJJngQArG2ANw8AHYbo3a6zdysAwG/SgHqsXePVPEM4xhhjTEPVFRj+NeBkaBI6HdwCgRuZQJfRz14Xa7nwZ03mE7bW1jXRkONYFJ4Nty8tOJhhjDHGnhtRs/zdJzz5e9J+oPQG0MKrTqtkKBQhrcGKicbRGJqfpp7xZSbGGGOspqr24lhJ6zyQMYajDfdHaHAwwxhjjDVCFgY6WQxeRer5Zp3VpbHjYIYxxhhrhDqqHJ8sGHFHUzX95tddZQBA6mA4j4lwMMMYY4w1QnLrKpeRguOA8EXiDLIqwY620cKWdXAZSmrERIBBrz/7fp4RBzOMMcaYMTq9/Pjf+ryVu2qAUvUykpUU6B0nzmthCfR6G3D0AHpoBiTX5B4oA2xdgBmnqtRH8iS9qqjldbfPWuJghjHGGDOGquvjL/e3UutvH24da5Y/MgF45wxg61z3dfHqpf3xBm+miJdN/CgDgG/NZowxxoxX27lo6lNDBxMmuHPLEO6ZYYwxxpqMOgxsGkGPi7E4mGGMMcaYWeNghjHGGGtMrO0e/+s3wLT1MEbL9qauAQAeM8MYY4w1LjN+BQrPAD6hpq6JYY4epq4BAO6ZYYwxxhoX+1aAb1jjHrMybgcQEAVErzB1TQBwMMMYY4w1Ge4Km7ovNGLx439fXv0kzScEGLURUHDPDGOMMcZq4tUkvaudbKXPvo+O0Y//Df7fJH3BU4E/FwIBg5697HrCY2YYY4wxc+HXH5j9G2DXqv72MeIb4EGReCI+K1n97a8OcDDDGGOMmRMHN93rFHUwoZ1EUj8zCtcjDmYYY4yxpiJiMaCuBLrFmromDYqDGcYYY6ypsHMB/pho6lo0OB4AzBhjjDGzxsEMY4wxxswaBzOMMcYYM2sczDDGGGPMrHEwwxhjjDGzxsEMY4wxxswaBzOMMcYYM2sczDDGGGPMrHEwwxhjjDGzxsEMY4wxxswaBzOMMcYYM2sczDDGGGPMrHEwwxhjjDGzxsEMY4wxxsyalakrUN+ICABQUlJi4powxhhjzFia723N97g+TT6YuXv3LgDAy8vLxDVhjDHGWE3dvXsXCoVCbx4JGRPymDG1Wo28vDw4ODhAIpGYujp1rqSkBF5eXrh69SocHR1NXR2T4/Z4gttCjNvjCW4LMW6PJxpTWxAR7t69C5VKBQsL/aNimnzPjIWFBTw9PU1djXrn6Oho8hOvMeH2eILbQozb4wluCzFujycaS1sY6pHR4AHAjDHGGDNrHMwwxhhjzKxxMGPmZDIZFixYAJlMZuqqNArcHk9wW4hxezzBbSHG7fGEubZFkx8AzBhjjLGmjXtmGGOMMWbWOJhhjDHGmFnjYIYxxhhjZo2DGRNJSEhAjx494ODgAFdXVwwbNgznzp0T1ldUVOC9995DYGAg7OzsoFKp8NprryEvL89g2ZmZmQgNDYVcLoeHhwcWLlxYbTrolJQUBAUFwcbGBr6+vli1alWdH2NNGGoPAIiPj0dAQADs7Ozg5OSEl156CWlpaQbLNqf2uHr1KiZMmACVSgWpVApvb2/MmDEDt27dMmr7gwcPQiKRoLi4WG8+Y8+vyZMno23btpDL5WjVqhWio6ORnZ1d28N7JitXroSPjw9sbGwQFBSEw4cPC+uSkpIQERGBli1bQiKRICMjw6gyzencqEpXWzS3zw0NfedGc/jcqEpfW1Q1efJkSCQS/P3vfzdYplm0BTGTiIiIoHXr1tHp06cpIyODBg8eTK1bt6bS0lIiIiouLqaXXnqJNm/eTNnZ2ZSamkp/+MMfKCgoSG+5d+7cITc3Nxo1ahRlZmbS1q1bycHBgZYuXSrkuXTpEtna2tKMGTMoKyuL1qxZQ9bW1rRly5Z6PWZ9DLUHEdHGjRspOTmZLl68SKdPn6YJEyaQo6MjFRYW6izXnNrj4sWL5OrqSi+88AIdPHiQLl++TLt27aJOnTpRu3bt6NatWwbLOHDgAAGgoqIivfmMPb9Wr15NKSkplJOTQ+np6TRkyBDy8vKiysrKZznUGtu0aRNZW1vTmjVrKCsri2bMmEF2dnZ0+fJlIiL6xz/+QR988AGtWbOGANDJkycNlmlO50ZV+tqiuX1uEBk+N5r650ZVhtpCY9u2bdSlSxdSqVS0fPlyvWWaS1twMNNIFBYWEgBKSUnRmeeXX34hANVOzKpWrlxJCoWCHj58KKQlJCSQSqUitVpNRERz586lgIAA0XaTJ0+mXr16PeNR1B1j2uPOnTsEgPbt26czjzm1R2RkJHl6etL9+/dF6fn5+WRra0tTpkwhIqKHDx/SnDlzyNPTk6RSKfn5+dHXX39NOTk5BED0GjdunNH7N+b8+vXXXwkAXbhwoVbHWFs9e/YUjl8jICCA5s2bJ0rTtIExwYw5nRtVGdsWGk39c6Om7dHUPjeqMqYtrl27Rh4eHnT69Gny9vY2GMyYS1vwZaZG4s6dOwAAZ2dnvXkkEglatGghpI0fPx5hYWHCcmpqKkJDQ0VzBERERCAvLw+5ublCnvDwcFHZEREROH78OCoqKp79YOqAofYoLy/HV199BYVCgS5dugjp5toet2/fxp49e/D2229DLpeL1imVSowdOxabN28GEeG1117Dpk2b8Nlnn+Hs2bNYtWoV7O3t4eXlha1btwIAzp07h/z8fHz66adG10Hb+VXVvXv3sG7dOvj4+DTog1vLy8uRnp5e7T0KDw/H0aNHjS7HXM+NqmrTFk35c6Om7dHUPjeqMqYt1Go1YmNjMWfOHHTq1ElrOebaFhzMNAJEhFmzZuGFF15A586dteZ5+PAh5s2bhzFjxoiel+Hu7o7WrVsLywUFBXBzcxNtq1kuKCjQm6eyshI3b96sk2N6FvraY8eOHbC3t4eNjQ2WL1+O5ORktGzZUlhvru1x/vx5EBE6dOigdX2HDh1QVFSEY8eO4d///jfWrl2Ll19+Gb6+vujfvz9GjhwJS0tLIfhzdXWFUqk0+rkmus4v4PE1eHt7e9jb22P37t1ITk6GVCp9tgOugZs3b+LRo0da3yPNe2gMcz03qqppWzT1zw1j26Opfm5UZUxbfPTRR7CyssL06dN1lmOubdHkHzRpDuLi4nDq1CkcOXJE6/qKigqMGjUKarUaK1euFK1LSEiolv/pp4PT/wZqVU03Jo+p6GuPfv36ISMjAzdv3sSaNWsQExODtLQ0uLq6Amia7QE8qU9OTg4sLS0RGhpq9LYbN27E5MmTheUff/wRISEhwrK+8wsAxo4diwEDBiA/Px9Lly5FTEwMfvrpJ9jY2DzDEdWctveoJu9PUzo3jGmL5vS5Yag9mtPnhq62SE9Px6effooTJ07orZ+5tgX3zJjYtGnTsH37dhw4cEDr070rKioQExODnJwcJCcnG3yKqVKprPYLrbCwEMCTaFpXHisrK7i4uDzL4TwzQ+1hZ2cHPz8/9OrVC4mJibCyskJiYqLO8sylPfz8/CCRSJCVlaV1fXZ2NpycnGBra1vjsocOHYqMjAzh1b17d2GdMeeXQqFAu3bt0LdvX2zZsgXZ2dnYtm1bjetRWy1btoSlpaXW9+jpX4M1YS7nRlXGtkVz+dwwtj2a6udGVYba4vDhwygsLETr1q1hZWUFKysrXL58GbNnz0abNm10lmsubcHBjIkQEeLi4pCUlIT9+/fDx8enWh7NB9L58+exb98+o06K4OBgHDp0COXl5ULa3r17oVKphBM2ODgYycnJou327t2L7t27w9ra+tkOrJaMaQ9d25WVlelcby7t4eLiggEDBmDlypV48OCBaF1BQQE2btyIkSNHIjAwEGq1GikpKVrL0Vz+efTokZDm4OAAPz8/4aUZk1Ob8wsw3OZ1TSqVIigoqNp7lJycjN69e9e6XHM5N6oypi2a0+dGbc+NpvK5UZWhtoiNjcWpU6dEP2xUKhXmzJmDPXv26CzXbNqioUYaM7G33nqLFAoFHTx4kPLz84WX5k6WiooKGjp0KHl6elJGRoYoT1lZmVDOvHnzKDY2VlguLi4mNzc3Gj16NGVmZlJSUhI5OjpqvY3unXfeoaysLEpMTDT5LYWG2qO0tJTef/99Sk1NpdzcXEpPT6cJEyaQTCaj06dPC+WYc3v89ttv1LJlSwoJCaGUlBS6cuUK/fjjj9S5c2fRrdnjx48nLy8v2rZtG126dIkOHDhAmzdvJqLHdypIJBJav349FRYW0t27d7Xuy5jz6+LFi7R48WI6fvw4Xb58mY4ePUrR0dHk7OxMN27caJhG+R/NLaeJiYmUlZVFM2fOJDs7O8rNzSUiolu3btHJkydp586dBIA2bdpEJ0+epPz8fKEMcz43qtLXFs3tc4NIf3s0h8+Nqgz9P3matruZzLUtOJgxETx1C63mtW7dOiIirbfZal4HDhwQyhk3bhyFhoaKyj516hSFhISQTCYjpVJJ8fHxwi10GgcPHqSuXbuSVCqlNm3a0JdfflnPR6yfofZ48OABvfzyy6RSqUgqlZK7uzsNHTqUfvnlF1E55t4eubm5NH78eFIqlWRtbU1eXl40bdo0unnzppDnwYMH9M4775C7u7twa/batWuF9QsXLiSlUkkSiUTnrdnGnF/Xr1+ngQMHkqurK1lbW5OnpyeNGTOGsrOz67MJdFqxYgV5e3uTVCqlbt26iW7bX7dundZjWbBggZDH3M+NqnS1RXP73NDQ1R7N5XOjKn3/T56mLZgx17bgp2YzxhhjzKzxmBnGGGOMmTUOZhhjjDFm1jiYYYwxxphZ42CGMcYYY2aNgxnGGGOMmTUOZhhjjDFm1jiYYYwxxphZ42CGMcYYe0YJCQno0aMHHBwc4OrqimHDhuHcuXOiPESE+Ph4qFQqyOVyhIWF4cyZM8L627dvY9q0afD394etrS1at26N6dOn486dO1r3WVZWhueffx4SiQQZGRlG1fPo0aMYNGgQnJycYGNjg8DAQCxbtkz0CBRD4uPj8fzzzxvMl5ubiwkTJsDHxwdyuRxt27bFggULRI9GuHXrFiIjI6FSqSCTyeDl5YW4uDiUlJQYXR+AgxnGDDL2P25dO3jwICQSCSQSCYYNG9bg+69LmmMpLi6u87LDwsIwc+bMOi+XsZpISUnB1KlT8fPPPyM5ORmVlZUIDw/HvXv3hDwff/wxPvnkE3zxxRc4duwYlEolBgwYgLt37wIA8vLykJeXh6VLlyIzMxPr16/H7t27MWHCBK37nDt3LlQqldF13LZtG0JDQ+Hp6YkDBw4gOzsbM2bMwKJFizBq1CjU9Ry62dnZUKvVWL16Nc6cOYPly5dj1apV+NOf/iTksbCwQHR0NLZv347ffvsN69evx759+zBlypSa7axB5xtmrJGBjqnfNa9x48bR3bt3RY8TaCgHDhwgAHTu3DkqKipq8P3XJc2x1Mdx3Lp1i0pKSuq83Jo4ffo0DR8+nLy9vQlAtSniiYhKSkpoxowZ1Lp1a7KxsaHg4OBq0+rrOg8//vhjIc/Dhw8pLi6OXFxcyNbWloYMGUJXr141WMfLly9TVFQU2drakouLC02bNk30vKYHDx7QuHHjqHPnzmRpaUnR0dFGH/+WLVuoQ4cOJJVKqUOHDpSUlCRan5KSQlFRUeTu7k4AaNu2bUaXba4KCwsJgPA4AbVaTUqlkpYsWSLkefjwISkUClq1apXOcv7973+TVCqliooKUfquXbsoICCAzpw5QwDo5MmTeutTWlpKLi4uNHz48Grrtm/fLjzTTOPq1as0cuRIcnJyIltbWwoKCqKff/5Z66NDNI+dMcbHH39MPj4+evN8+umn5OnpaXSZRETcM8Oatfz8fOH197//HY6OjqK0Tz/9FPb29g32GHttXF1d0aJFC5Ptv7FzdnaGg4ODSetw//59+Pr6YsmSJVAqlVrzTJw4EcnJydiwYQMyMzMRHh6Ol156CdevXxfyVD338vPzsXbtWkgkErzyyitCnpkzZ2Lbtm3YtGkTjhw5gtLSUkRFRem9TPDo0SMMHjwY9+7dw5EjR7Bp0yZs3boVs2fPFuWRy+WYPn06XnrpJaOPPTU1FSNHjkRsbCx+/fVXxMbGIiYmBmlpaUKee/fuoUuXLvjiiy+MLtfcaS4NOTs7AwBycnJQUFCA8PBwIY9MJkNoaCiOHj2qtxxHR0dYWVkJaTdu3MCkSZOwYcMG2NraGlWfvXv34tatW3j33XerrRsyZAjat2+Pb7/9FgBQWlqK0NBQ5OXlYfv27fj1118xd+5cqNVqjBw5ErNnz0anTp2E83TkyJFG1UFzPJo20SYvLw9JSUkIDQ01ukwA3DPDmMa6detIoVBUS1+wYAF16dJFWB43bhxFR0fTokWLyNXVlRQKBcXHx1NFRQW9++675OTkRB4eHpSYmCgq59q1axQTE0MtWrQgZ2dnGjp0KOXk5Oisj67ejO+++446d+5MNjY25OzsTP3796fS0lJh/dq1aykgIIBkMhn5+/vTihUrRNvr+sWlsXLlSvL19SVra2tq3749/eMf/xBtD4DWrFlDw4YNI7lcTn5+fvTDDz+I8uzcuZPatWtHNjY2FBYWJvya0xxLbm4uRUVFUYsWLcjW1pY6duxIO3fu1NkWK1asID8/P5LJZOTq6kqvvPKKsC40NJRmzJghLHt7e9OiRYvo9ddfJ3t7e/Ly8qLVq1fXqA22b99O3bp1I5lMRj4+PsL7awxtD++7f/8+WVpa0o4dO0TpXbp0ofnz5+ssKzo6ml588UVhubi4mKytrUW/oK9fv04WFha0e/duneXs2rWLLCws6Pr160Lat99+SzKZjO7cuVMtv+YcN0ZMTAxFRkaK0iIiImjUqFFa86MZ9Myo1WoaMmQIvfDCC0LaTz/9RABE7wER0aRJkyg8PFxrOTdv3qTWrVuLzhG1Wk2RkZH017/+lYiePFzUUM/MkiVL9PaODh06lDp06EBERKtXryYHBwe6deuW1rxPfyYa68KFC+To6Ehr1qyptm7UqFEkl8sJAA0ZMoQePHhQo7K5Z4axWti/fz/y8vJw6NAhfPLJJ4iPj0dUVBScnJyQlpaGKVOmYMqUKbh69SqAx7/c+/XrB3t7exw6dAhHjhyBvb09IiMjRYPhDMnPz8fo0aPxxhtv4OzZszh48CCGDx8uXOtes2YN5s+fj0WLFuHs2bNYvHgx/u///g/ffPMNAP2/uIDH19RnzJiB2bNn4/Tp05g8eTJef/11HDhwQFSPDz74ADExMTh16hQGDRqEsWPH4vbt2wCAq1evYvjw4Rg0aBAyMjIwceJEzJs3T7T91KlTUVZWhkOHDiEzMxMfffQR7O3ttR7z8ePHMX36dCxcuBDnzp3D7t270bdvX73ttGzZMnTv3h0nT57E22+/jbfeegvZ2dlGtcGePXvw6quvYvr06cjKysLq1auxfv16LFq0yOj36WmVlZV49OgRbGxsROlyuRxHjhzRus2NGzewc+dO0XiJ9PR0VFRUiH7dq1QqdO7cWe+v+9TUVHTu3Fk0viIiIgJlZWVIT0+v7WEJZVetj6ZsffVp6uLi4nDq1Cmhp6MqiUQiWiaiamkAUFJSgsGDB6Njx45YsGCBkP7555+jpKQE77//vs79d+rUCfb29rC3t8fAgQOr7U+bqvXIyMhA165d9fagPG3KlCnCPrX9X87Ly0NkZCRGjBiBiRMnVlu/fPlynDhxAt9//z0uXryIWbNmGb1vzQEwxqhmPTPe3t706NEjIc3f359CQkKE5crKSrKzs6Nvv/2WiIgSExPJ39+f1Gq1kKesrIzkcjnt2bNHa3209cykp6cTAMrNzdW6jZeXF/3rX/8Spf31r3+l4OBgIjL8i6t37940adIkUdqIESNo0KBBwjIA+vOf/ywsl5aWkkQioR9//JGIiN5//33q0KGD6Fjfe+890bEEBgZSfHy81jo8bevWreTo6KhzXIy2nplXX31VWFar1eTq6kpffvklERlug5CQEFq8eLEobcOGDeTu7m5UfbX1zBARBQcHU2hoKF2/fp0qKytpw4YNJJFIqH379lrL+eijj8jJyUn0C3Xjxo0klUqr5R0wYAC9+eabOus0adIkGjBgQLV0qVRa7XwhqlnPjLW1NW3cuFGUpqueRE2/ZyYuLo48PT3p0qVLovSLFy8SADpx4oQofejQofTaa6+J0kpKSig4OJj69+9frYciOjqaLCwsyNLSUngBIEtLS6Gc3NxcOn/+PJ0/f56uXbtGRERJSUkEgH766Set9W7Xrp3wns+aNYv69u2r8xi19czcuHFD2Of58+dF665fv07t27en2NhY0eemLocPHyYAlJeXZzCvBvfMMFYLnTp1goXFk/8+bm5uCAwMFJYtLS3h4uKCwsJCAI9/UV+4cAEODg7CLxdnZ2c8fPgQFy9eNHq/Xbp0Qf/+/REYGIgRI0ZgzZo1KCoqAgD8/vvvuHr1KiZMmCD6hfThhx8K+zD0i+vs2bPo06ePKK1Pnz44e/asKO25554T/razs4ODg4NwrGfPnkWvXr1EvzaDg4NF20+fPh0ffvgh+vTpgwULFuDUqVM6j3nAgAHw9vaGr68vYmNjsXHjRty/f19vO1Wtn0QigVKpFOpnqA3S09OxcOFCURtOmjQJ+fn5Bverz4YNG0BE8PDwgEwmw2effYYxY8bA0tJSa/61a9di7Nix1XpztKEqv6oHDhwo1LtTp05CHm2//klHr4A2V65cEbXJ4sWLdZZdk3KbCiJCXFwckpKSsH//fvj4+IjW+/j4QKlUIjk5WUgrLy9HSkoKevfuLaSVlJQgPDwcUqkU27dvr/b+f/bZZ/j111+RkZGBjIwM7Nq1CwCwefNmoffQ29sbfn5+8PPzg4eHBwAgPDwczs7OWLZsWbW6b9++HefPn8fo0aMBPP7/k5GRIfS2Pk0qlVYbo+Xq6irs08/PT0i/fv06wsLC0K1bN6xbt070uakL/a/3qKyszGBeDSvDWRhjT7O2thYtSyQSrWmaSxdqtRpBQUHYuHFjtbJatWpl9H4tLS2RnJyMo0ePYu/evfj8888xf/58pKWlCQMB16xZgz/84Q/VtgMeX9YwxJgvJn3HSkbc3jlx4kRERERg586d2Lt3LxISErBs2TJMmzatWl4HBwecOHECBw8exN69e/GXv/wF8fHxOHbsmM6B0frqZ6gN1Go1PvjgAwwfPrzaOmMCC13atm2LlJQU3Lt3DyUlJXB3d8fIkSOrfekBwOHDh3Hu3Dls3rxZlK5UKlFeXo6ioiI4OTkJ6YWFhcIX4tdff40HDx4AeNIOSqVSNCAXAIqKilBRUQE3Nzej6q9SqURzmWiCQaVSiYKCAlHewsJCo8ttKqZOnYp//etf+OGHH+Dg4CC0iUKhgFwuh0QiwcyZM7F48WK0a9cO7dq1w+LFi2Fra4sxY8YAAO7evYvw8HDcv38f//znP1FSUiLMt9KqVStYWlqidevWov1qLum0bdsWnp6eOutnZ2eH1atXY9SoUXjzzTcRFxcHR0dH/Pe//8WcOXPwxz/+ETExMQCA0aNHY/HixRg2bBgSEhLg7u6OkydPQqVSITg4GG3atEFOTg4yMjLg6ekJBwcHyGSyavvMy8tDWFgYWrdujaVLl+L3338X1mkGyu/atQs3btxAjx49YG9vj6ysLMydOxd9+vRBmzZtjH8DjO7DYayJq+kA4KqevtRBJL7c8NVXX5GTk5PWwZa6GHM7c2VlJXl4eNCyZcuIiMjDw4MWLlyoM//69evJ0dGxxpeZBg8eLCxDy2UChUIh3J6pucxU1bx58/Qey7x58ygwMFBnvasqLS0lKysr2rp1KxFpv8z09GWeLl260IIFC4jIuDZ44403jKqLNrouMz3t9u3bpFAoqg1OJnp8jgUFBVVL1wwA3rx5s5CWl5dn9ADgqt32mzZtqrMBwAMHDhSlRUZGNrsBwNBxW33V25bVajUtWLCAlEolyWQy6tu3L2VmZgrrNf/ntb103Sxg7ABgjUOHDlFkZCQpFAqSSqXUsWNHWrp0KVVWVory5ebm0iuvvEKOjo5ka2tL3bt3p7S0NCJ6fEv5K6+8Qi1atNB7a7a227g1L439+/dTcHAwKRQKsrGxoXbt2tF7771X42kcuGeGsQYwduxY/O1vf0N0dDQWLlwIT09PXLlyBUlJSZgzZ47eX1RVpaWl4b///S/Cw8Ph6uqKtLQ0/P777+jQoQOAxxP8TZ8+HY6Ojhg4cCDKyspw/PhxFBUVYdasWQZ/cc2ZMwcxMTHo1q0b+vfvj//85z9ISkrCvn37jD7WKVOmYNmyZZg1axYmT56M9PR0rF+/XpRn5syZGDhwINq3b4+ioiLs379fOIan7dixA5cuXULfvn3h5OSEXbt2Qa1Ww9/f3+g6VWWoDf7yl78gKioKXl5eGDFiBCwsLHDq1ClkZmbiww8/1FpmeXk5srKyhL+vX7+OjIwM2NvbC13ue/bsARHB398fFy5cwJw5c+Dv74/XX39dVFZJSQm+++47rZcDFAoFJkyYgNmzZ8PFxQXOzs549913ERgYqPd26vDwcHTs2BGxsbH429/+htu3b+Pdd9/FpEmT4OjoKOTLyspCeXk5bt++jbt37wo9MfomjZwxYwb69u2Ljz76CNHR0fjhhx+wb98+0cDm0tJSXLhwQVjW/Kp3dnau1tNgrsiIHkmJRIL4+HjEx8drXR8WFlbjievatGlTo21CQkLw448/Gszn7e2NLVu2aF0nk8l0rqtq/PjxGD9+vN48/fr1q5vB4jUKfRhrwuqzZ4aIKD8/n1577TVq2bIlyWQy8vX1pUmTJunsrdHWM5OVlUURERHUqlUrkslk1L59e/r8889F223cuJGef/55kkql5OTkRH379hVNYqbvFxeRcbdm6+uZISL6z3/+I9xKHRISQmvXrhUdS1xcHLVt25ZkMhm1atWKYmNjdU5MePjwYQoNDSUnJyeSy+X03HPPiXomatozY0wb7N69m3r37k1yuZwcHR2pZ8+e9NVXX2mtH9GTX8dPv0JDQ4U8mzdvJl9fX5JKpaRUKmnq1KlUXFxcrazVq1eTXC7Xuo7o8eR2cXFx5OzsTHK5nKKioujKlSs666Zx+fJlGjx4MMnlcnJ2dqa4uDh6+PChKI9m0r+nX4Z899135O/vT9bW1hQQECD0mmno6nEYN26cwbIZM4aEqI7nL2aM1YmDBw+iX79+KCoq4knzGGNMD76bibFGztPTU7jLgDHGWHXcM8NYI/XgwQNhqnt7e3ud0+Qzxlhzx8EMY4wxxswaX2ZijDHGmFnjYIYxxmooNzcXEokEEolE723LjLGGwcEMY+yZrVy5Ej4+PrCxsUFQUBAOHz4srCMixMfHQ6VSQS6XIywsDGfOnDFYZmZmJkJDQyGXy+Hh4YGFCxdWm08jJSUFQUFBsLGxga+vL1atWmWw3LKyMkybNg0tW7aEnZ0dhg4dimvXronyFBUVITY2FgqFAgqFArGxsSguLhbWe3l5IT8/H7Nnzza4P8ZY/eNghjH2TDZv3oyZM2di/vz5OHnyJEJCQjBw4EBcuXIFAPDxxx/jk08+wRdffIFjx45BqVRiwIABuHv3rs4yS0pKMGDAAKhUKhw7dgyff/45li5dik8++UTIk5OTg0GDBiEkJAQnT57En/70J0yfPh1bt27VW9+ZM2di27Zt2LRpE44cOYLS0lJERUWJnjUzZswYZGRkYPfu3di9ezcyMjIQGxsrrLe0tIRSqdT5pG/GWAMz3RQ3jLGmoGfPnjRlyhRRWkBAAM2bN4/UajUplUpasmSJsO7hw4ekUCho1apVOstcuXIlKRQK0aRuCQkJpFKphKdxz507lwICAkTbTZ48mXr16qWzXM3jADZt2iSkXb9+XfQ4gKysLAJAP//8s5AnNTWVAFB2draoPG1PD2aMNTzumWGM1Vp5eTnS09MRHh4uSg8PD8fRo0eRk5ODgoIC0XqZTIbQ0FDRFObjx49HWFiYsJyamorQ0FDRw+siIiKQl5eH3NxcIc/T+42IiMDx48dRUVEB4PHEgxKJRNgmPT0dFRUVou1UKhU6d+4s1Cc1NRUKhUL0sM5evXpBoVDUzbTrjLE6x8EMY6zWbt68iUePHlV7QrKbmxsKCgqEJwfrWq/h7u4uekZPQUGB1m006/TlqaysxM2bNwEAtra28Pf3F54eXVBQAKlUKnri9NP1KSgogKura7VjdXV1rfZ0aMZY48APmmSMPTOJRCJaJiJRmqH1CQkJRpX5dLqhPD179kR2drbB+huqr7Y8jLHGg3tmGGO11rJlS1haWlbrsSgsLISbm5swa7Gu9boolUqt2wBPemh05bGysoKLi4vOcsvLy1FUVKSzPkqlEjdu3Ki27e+//663zowx0+FghjFWa1KpFEFBQUhOThalJycno3fv3vDx8YFSqRStLy8vR0pKCnr37q2z3ODgYBw6dAjl5eVC2t69e6FSqdCmTRshz9P73bt3L7p37y5cVnpaUFAQrK2tRdvl5+fj9OnTQn2Cg4Nx584d/PLLL0KetLQ03LlzR2+dGWMmZMrRx4wx87dp0yaytramxMREysrKopkzZ5KdnR3l5uYSEdGSJUtIoVBQUlISZWZm0ujRo8nd3Z1KSkqEMubNm0exsbHCcnFxMbm5udHo0aMpMzOTkpKSyNHRkZYuXSrkuXTpEtna2tI777xDWVlZlJiYSNbW1rRlyxYhT1paGvn7+9O1a9eEtClTppCnpyft27ePTpw4QS+++CJ16dKFKisrhTyRkZH03HPPUWpqKqWmplJgYCBFRUVVO3a+m4mxxoGDGcbYM1uxYgV5e3uTVCqlbt26UUpKirBOrVbTggULSKlUkkwmo759+1JmZqZo+3HjxlFoaKgo7dSpUxQSEkIymYyUSiXFx8cLt2VrHDx4kLp27UpSqZTatGlDX375pWj9gQMHCADl5OQIaQ8ePKC4uDhydnYmuVxOUVFRdOXKFdF2t27dorFjx5KDgwM5ODjQ2LFjqaioqNpxczDDWOPAD5pkjLFaio+Px/fff4+MjAxTV4WxZo3vZmKMsRq6cuUKOnbsiPLycnTs2NHU1WGs2eOeGcYYq6HKykphIj6ZTAYvLy/TVoixZo6DGcYYY4yZNb41mzHGGGNmjYMZxhhjjJk1DmYYY4wxZtY4mGGMMcaYWeNghjHGGGNmjYMZxhhjjJk1DmYYY4wxZtY4mGGMMcaYWeNghjHGGGNm7f8Bx/fv0PEINYUAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ds_waves[\"pressure\"] -= 0.7  # Adjust pressure sensor by 0.7 dBar\n",
+    "\n",
+    "# Calculate water depth\n",
+    "dolfyn.adp.clean.water_depth_from_pressure(ds_waves, salinity=35)\n",
+    "\n",
+    "ds_waves[\"ast_dist_alt\"].plot(label=\"Altimeter AST\")\n",
+    "ds_waves[\"le_dist_alt\"].plot(label=\"Altimeter LE\")\n",
+    "ds_waves[\"depth\"].plot(label=\"Depth\")\n",
+    "plt.legend()\n",
+    "plt.ylabel(\"Range [m]\")\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5cb4ebc5",
+   "metadata": {},
+   "source": [
+    "The ADCP records a quality indicator that corresponds with each altimeter measurement algorithm, ranging from 0 to 100. These indicators are saved in the dataset as variables called \"ast_quality_alt\" and \"le_quality_alt\". We can use these variables to remove poor altimeter measurements.\n",
+    "\n",
+    "If values are removed, it is worthwhile to replace these values using the method of your choice. The FFT algorithm is unable to handle NaNs, and any windows that contain one with result in a spectrum filled with NaN."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "db398852",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Remove datapoints where quality is below 40\n",
+    "ds_waves[\"ast_dist_alt\"] = ds_waves[\"ast_dist_alt\"].where(ds_waves[\"ast_quality_alt\"] > 40)\n",
+    "ds_waves[\"le_dist_alt\"] = ds_waves[\"le_dist_alt\"].where(ds_waves[\"le_quality_alt\"] > 40)\n",
+    "\n",
+    "# Interpolate gaps smaller than 5 seconds\n",
+    "ds_waves[\"ast_dist_alt\"] = ds_waves[\"ast_dist_alt\"].interpolate_na(dim=\"time\", max_gap=np.timedelta64(5, \"s\"), method=\"linear\")\n",
+    "ds_waves[\"le_dist_alt\"] = ds_waves[\"le_dist_alt\"].interpolate_na(dim=\"time\", max_gap=np.timedelta64(5, \"s\"), method=\"linear\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0c3beeb2",
+   "metadata": {},
+   "source": [
+    "### 3. Create Energy Spectra\n",
+    "\n",
+    "We'll start wave processing by first spinning up DOLfYN's binning tools to compute wave height and period. A comprehensive overview of wave measurement and analysis can be found [here](https://essopenarchive.org/doi/full/10.22541/essoar.175130482.28547248).\n",
+    "\n",
+    "Wave stats are typically computing windows of 30 minutes to an hour. Shorter windows can be used but they have lower statistical certainty. We'll use a bin size equal to 30 minutes of data, and an FFT length of half the bin size.\n",
+    "\n",
+    "Now, we can calculate the energy spectrum for the surface using `power_spectral_density`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "140ac43a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "window = 20*60\n",
+    "fft_tool = dolfyn.VelBinner(\n",
+    "        n_bin=window * ds_waves.fs, fs=ds_waves.fs, n_fft=ds_waves.fs * window // 2\n",
+    "    )\n",
+    "\n",
+    "Szz_ast = fft_tool.power_spectral_density(ds_waves[\"ast_dist_alt\"], freq_units=\"Hz\")\n",
+    "Szz_le = fft_tool.power_spectral_density(ds_waves[\"le_dist_alt\"], freq_units=\"Hz\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "53d82c21",
+   "metadata": {},
+   "source": [
+    "We will also go ahead and set the bounds for the wave frequencies that we want to analyze with the instrument. Langrangian drifters like buoys are unabled to measure wave periods less than 22 seconds, but ADCPs do not have this same limitation. ADCPs are limited in their waves analysis by their ability to measure orbital velocities. Because of this, we'll set the frequency bounds for waves between 5 seconds at the high end and 30 seconds at the low end, typically the largest gravity swells. \n",
+    "\n",
+    "Further discussion of acoustic limitations are discussed in Section 3.2.3 [here](https://essopenarchive.org/doi/full/10.22541/essoar.175130482.28547248)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "da0f401b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Trim frequency vector to 0.2 > f > 0.05 Hz (wave periods between 5 and 30 s)\n",
+    "slc_freq = slice(0.05, 0.2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "73dcb9f0",
+   "metadata": {},
+   "source": [
+    "If we plot the energy spectra we just calculated, we can see the differences between the two methods. The methods begin to diverge at high frequencies (wave periods < 5 s), where each spectrum becomes noiser. This could be due to wind waves, which populate this region of the spectrum, starting to break. Linear wave theory cannot account for breaking waves, so these spectra will not be accurate at quantifying their estimation.\n",
+    "\n",
+    "The spectra also begin to drift at low frequencies, which may only be due to the short length of time we are analyzing here.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "bc8f103b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x20f3fef6a90>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1100x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1, 2, figsize=(11, 5))\n",
+    "ax[0].loglog(Szz_ast[\"freq\"], Szz_ast.mean(\"time\"), label=\"Altimeter AST\")\n",
+    "ax[0].loglog(Szz_le[\"freq\"], Szz_le.mean(\"time\"), label=\"Altimeter LE\")\n",
+    "ax[0].set(xlabel=\"Frequency [Hz]\", ylabel=\"Energy Density [m$^2$/Hz]\", title =\"Full frequency range\", xlim=(5e-3, 0.5), ylim=(5e-3, 5))\n",
+    "ax[1].loglog(Szz_ast[\"freq\"].sel(freq=slc_freq), Szz_ast.sel(freq=slc_freq).mean(\"time\"), label=\"Altimeter AST\")\n",
+    "ax[1].loglog(Szz_le[\"freq\"].sel(freq=slc_freq), Szz_le.sel(freq=slc_freq).mean(\"time\"), label=\"Altimeter LE\")\n",
+    "ax[1].set(xlabel=\"Frequency [Hz]\", title=\"Frequency limits of 1/22 to 1/3 Hz\", xlim=(5e-3, 0.5), ylim=(5e-3, 5))\n",
+    "ax[1].legend()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b26a34c6",
+   "metadata": {},
+   "source": [
+    "### 4. Compute Basic Wave Statistics\n",
+    "\n",
+    "To calculate some basic wave statistics, like significant wave height and peak wave period, we will use functions from the MHKiT Wave module."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "4d3d0e77",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "# Select frequency range for wave calculations\n",
+    "Szz_ast = Szz_ast.sel(freq=slc_freq)\n",
+    "Szz_le = Szz_le.sel(freq=slc_freq)\n",
+    "\n",
+    "# Convert to pandas DataFrame for MHKiT wave resource functions\n",
+    "Szz_ast = Szz_ast.T.to_pandas()\n",
+    "# Calculate wave parameters\n",
+    "Hs_ast = wave.resource.significant_wave_height(Szz_ast)\n",
+    "Tm_ast = wave.resource.average_wave_period(Szz_ast)\n",
+    "Tp_ast = wave.resource.peak_period(Szz_ast)\n",
+    "\n",
+    "Szz_le = Szz_le.T.to_pandas()\n",
+    "Hs_le = wave.resource.significant_wave_height(Szz_le)\n",
+    "Tm_le = wave.resource.average_wave_period(Szz_le)\n",
+    "Tp_le = wave.resource.peak_period(Szz_le)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3b9c4a6f",
+   "metadata": {},
+   "source": [
+    "Next we'll create create a bin-averaged dataset using DOLfYN's tools to save these stats in."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "c304d50b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create averaged dataset\n",
+    "ds_waves_avg = fft_tool.bin_average(ds_waves)\n",
+    "# Convert wave parameters to xarray and add to averaged dataset\n",
+    "ds_waves_avg[\"wave_height_ast\"] = Hs_ast.to_xarray().astype(\"float32\")\n",
+    "ds_waves_avg[\"mean_period_ast\"] = Tm_ast.to_xarray().astype(\"float32\")\n",
+    "ds_waves_avg[\"peak_period_ast\"] = Tp_ast.to_xarray().astype(\"float32\")\n",
+    "\n",
+    "ds_waves_avg[\"wave_height_le\"] = Hs_le.to_xarray().astype(\"float32\")\n",
+    "ds_waves_avg[\"mean_period_le\"] = Tm_le.to_xarray().astype(\"float32\")\n",
+    "ds_waves_avg[\"peak_period_le\"] = Tp_le.to_xarray().astype(\"float32\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "af09e51b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f86c69d7",
+   "metadata": {},
+   "source": [
+    "And plot. We can see a significant wave height between 1-2 m, mean wave period around 3 s, and a peak period around 9 s. There are some small differences between wave height and period below due to small differences between the AST and LE spectra. Both methods have the same spectral peak, so the peak period is equivalent. Again, the LE method determines the surface as the rising edge of the return acoustic signal, while AST determines the surface as the maximum point of the return acoustic signal."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "da81435e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[Text(0, 0.5, 'Peak Period [s]'), Text(0.5, 0, 'Time')]"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x700 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(3, 1, figsize=(10, 7), constrained_layout=True)\n",
+    "ax[0].plot(\n",
+    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"wave_height_ast\"],\n",
+    "    \".-\",\n",
+    "    label=\"Altimeter AST\",\n",
+    ")\n",
+    "ax[0].plot(\n",
+    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"wave_height_le\"],\n",
+    "    \".-\",\n",
+    "    label=\"Altimeter LE\",\n",
+    ")\n",
+    "ax[0].legend()\n",
+    "ax[0].set(ylabel=\"Significant Wave Height [m]\")\n",
+    "\n",
+    "ax[1].plot(\n",
+    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"mean_period_ast\"],\n",
+    "    \".-\",\n",
+    "    label=\"Altimeter AST\",\n",
+    ")\n",
+    "ax[1].plot(\n",
+    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"mean_period_le\"],\n",
+    "    \".-\",\n",
+    "    label=\"Altimeter LE\",\n",
+    ")\n",
+    "ax[1].legend()\n",
+    "ax[1].set(ylabel=\"Mean Period [s]\")\n",
+    "ax[2].plot(\n",
+    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"peak_period_ast\"],\n",
+    "    \".-\",\n",
+    "    label=\"Altimeter AST\",\n",
+    ")\n",
+    "ax[2].plot(\n",
+    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"peak_period_le\"],\n",
+    "    \".-\",\n",
+    "    label=\"Altimeter LE\",\n",
+    ")\n",
+    "ax[2].legend()\n",
+    "ax[2].set(ylabel=\"Peak Period [s]\", xlabel=\"Time\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7f250b8f",
+   "metadata": {},
+   "source": [
+    "### 5. Review and QC Surface Velocity Measurements\n",
+    "\n",
+    "ADCPs can be used to measure directional wave statistics, albeit to a lower degree of accuracy than one can get using a surface buoy. This can be done using the so-called the \"SUV\" method (short for \"Surface\" - \"U velocity\" - \"V velocity\"), which uses surface height and the horizontal velocity vector to estimate wave orbital speed and direction. \n",
+    "\n",
+    "First, it is useful to see what velocity data the ADCP is measuring while in wave mode. We'll start by doing some basic processing and plot the velocity data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "c477be85",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data is already in the earth coordinate system\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\dolfyn\\adp\\clean.py:90: UserWarning: The 'range_offset' is either already known or can be calculated from 'bin1_dist_m': 0.5 m. If you would like to override this value with 0.5 m, ignore this warning. If you do not want to override this value, you do not need to use this function.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "# The ADCP transducers were measured to be 0.5 m from the feet of the lander\n",
+    "dolfyn.adp.clean.set_range_offset(ds_waves, 0.5)\n",
+    "# Remove surface sidelobe interference and low correlation values\n",
+    "ds_waves = dolfyn.adp.clean.remove_surface_interference(ds_waves)\n",
+    "ds_waves = dolfyn.adp.clean.correlation_filter(ds_waves, thresh=30)\n",
+    "# Correct magnetic declination\n",
+    "dolfyn.set_declination(ds_waves, 14.8, inplace=True)  # 14.8 deg Eastz\n",
+    "dolfyn.rotate2(ds_waves, \"earth\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "59afeff9",
+   "metadata": {},
+   "source": [
+    "In the plot below, one can see that the ADCP is only measuring the top half of the water column. In order to measure wave direction, the ADCP needs to be able to capture the wave orbital velocity created by the waves. Because we still need to remove depth bins at the surface that are corrupted by sidelobe interference, the ADCP will generally only be able to measure the direction of long-period gravity waves (i.e., the \"peak\" or \"dominant\" wave direction)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "e9cfbf3b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_5016\\212097317.py:10: MatplotlibDeprecationWarning: Getting the array from a PolyQuadMesh will return the full array in the future (uncompressed). To get this behavior now set the PolyQuadMesh with a 2D array .set_array(data2d).\n",
+      "  fig.colorbar(h1, ax=ax[0], label=label, fraction=0.05, pad=0.02)\n",
+      "C:\\Users\\mcve343\\AppData\\Local\\Temp\\ipykernel_5016\\212097317.py:21: MatplotlibDeprecationWarning: Getting the array from a PolyQuadMesh will return the full array in the future (uncompressed). To get this behavior now set the PolyQuadMesh with a 2D array .set_array(data2d).\n",
+      "  fig.colorbar(h2, ax=ax[1], label=label, fraction=0.05, pad=0.02)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[Text(0.5, 0, 'Time'), Text(0, 0.5, 'Depth [m]'), (0.0, 78.0)]"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(2, figsize=(10, 6), constrained_layout=True)\n",
+    "h1 = ax[0].pcolor(\n",
+    "    ds_waves[\"time\"].values,\n",
+    "    ds_waves[\"range\"].values,\n",
+    "    ds_waves[\"vel\"][0],\n",
+    "    cmap=\"coolwarm_r\",\n",
+    ")\n",
+    "ax[0].plot(ds_waves[\"time\"], ds_waves[\"depth\"], \"k-\")\n",
+    "label = \"Velocity East [m/s]\"\n",
+    "fig.colorbar(h1, ax=ax[0], label=label, fraction=0.05, pad=0.02)\n",
+    "ax[0].set(xlabel=\"Time\", ylabel=\"Depth [m]\", ylim=(0, 78))\n",
+    "\n",
+    "h2 = ax[1].pcolor(\n",
+    "    ds_waves[\"time\"].values,\n",
+    "    ds_waves[\"range\"].values,\n",
+    "    ds_waves[\"vel\"][1],\n",
+    "    cmap=\"coolwarm_r\",\n",
+    ")\n",
+    "ax[1].plot(ds_waves[\"time\"], ds_waves[\"depth\"], \"k-\")\n",
+    "label = \"Velocity North [m/s]\"\n",
+    "fig.colorbar(h2, ax=ax[1], label=label, fraction=0.05, pad=0.02)\n",
+    "ax[1].set(xlabel=\"Time\", ylabel=\"Depth [m]\", ylim=(0, 78))\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "10c4437e",
+   "metadata": {},
+   "source": [
+    "### 6. Compute Directional Wave Statistics\n",
+    "\n",
+    "The following codeblock runs through the computational steps to estimate peak wave direction and spread. We start by creating a 3x matrix with the highest depth bin for the east and north velocity vectors, plus the surface vector. We next calculate the auto-spectra of each of those vectors, along with their cross-spectra. The auto- and cross-spectra are used to then compute the Fourier coefficients (a1, b1, a2, b2), which define the peak wave direction and spread.\n",
+    "\n",
+    "To follow this process using DOLfYN's tools, we'll need to use the `cross_spectral_density` function, which is located in the ADV's API.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "317a1faa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "\n",
+    "## \"SUV\" method - AST, u velocity, v velocity\n",
+    "fft_tool = dolfyn.adv.api.ADVBinner(\n",
+    "    n_bin=window * ds_waves.fs, fs=ds_waves.fs, n_fft=ds_waves.fs * window // 2\n",
+    ")\n",
+    "# Create 2D tensor for spectral analysis\n",
+    "disp = xr.DataArray(\n",
+    "    data=np.array(\n",
+    "        [\n",
+    "            ds_waves[\"vel\"][0, 7].values,  # first bin continuously below water surface\n",
+    "            ds_waves[\"vel\"][1, 7].values,\n",
+    "            ds_waves[\"ast_dist_alt\"].values,\n",
+    "        ]\n",
+    "    ),\n",
+    "    coords={\"dir\": [\"u\", \"v\", \"z\"], \"time\": ds_waves[\"time\"]},\n",
+    ")\n",
+    "# Auto-spectra\n",
+    "psd = fft_tool.power_spectral_density(disp, freq_units=\"Hz\")\n",
+    "psd = psd.sel(freq=slc_freq)\n",
+    "Sxx = psd.sel(S=\"Sxx\")\n",
+    "Syy = psd.sel(S=\"Syy\")\n",
+    "Szz = psd.sel(S=\"Szz\")\n",
+    "\n",
+    "# Cross-spectra\n",
+    "csd = fft_tool.cross_spectral_density(disp, freq_units=\"Hz\")\n",
+    "csd = csd.sel(coh_freq=slc_freq)\n",
+    "Cxz = csd.sel(C=\"Cxz\").real\n",
+    "Cxy = csd.sel(C=\"Cxy\").real\n",
+    "Cyz = csd.sel(C=\"Cyz\").real\n",
+    "\n",
+    "# Calculate peak wave direction and spread\n",
+    "a1 = Cxz.values / np.sqrt((Sxx + Syy) * Szz)\n",
+    "b1 = Cyz.values / np.sqrt((Sxx + Syy) * Szz)\n",
+    "a2 = (Sxx - Syy) / (Sxx + Syy)\n",
+    "b2 = 2 * Cxy.values / (Sxx + Syy)\n",
+    "theta = np.rad2deg(np.arctan2(b1, a1))  # degrees CCW from East, \"to\" convention\n",
+    "phi = np.rad2deg(np.sqrt(2 * (1 - np.sqrt(a1**2 + b1**2))))\n",
+    "\n",
+    "# Get peak frequency - fill nan slices with 0\n",
+    "peak_idx = Szz.fillna(0).argmax(\"freq\")\n",
+    "# degrees CW from North (\"from\" convention)\n",
+    "direction = (270 - theta[:, peak_idx]) % 360\n",
+    "# Set direction from -180 to 180\n",
+    "direction[direction > 180] -= 360\n",
+    "spread = phi[:, peak_idx]\n",
+    "\n",
+    "ds_waves_avg[\"wave_a1_value\"] = a1\n",
+    "ds_waves_avg[\"wave_b1_value\"] = b1\n",
+    "ds_waves_avg[\"wave_a2_value\"] = a2\n",
+    "ds_waves_avg[\"wave_b2_value\"] = b2\n",
+    "ds_waves_avg[\"peak_wave_direction\"] = direction\n",
+    "ds_waves_avg[\"peak_wave_spread\"] = spread"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7b9ee95d",
+   "metadata": {},
+   "source": [
+    "And plot. Some datapoints may be missing for velocity data that was quality controlled out, but we can see that the highest energy waves are coming from -80 degees (10 degrees north of due West), with a spread of approximately 20 degrees."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "aa7c5d49",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[Text(0, 0.5, 'Peak Wave Spread [deg]')]"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(2, 1, figsize=(10, 5), constrained_layout=True)\n",
+    "ax[0].plot(\n",
+    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"peak_wave_direction\"],\n",
+    "    \".-\",\n",
+    ")\n",
+    "ax[0].set(ylabel=\"Peak Wave Direction\\n[deg CW from N]\")\n",
+    "\n",
+    "ax[1].plot(\n",
+    "    ds_waves_avg[\"time\"],\n",
+    "    ds_waves_avg[\"peak_wave_spread\"],\n",
+    "    \".-\",\n",
+    ")\n",
+    "ax[1].set(ylabel=\"Peak Wave Spread [deg]\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1d05b8b5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "work",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/examples/data/dolfyn/AQD_HR.prf b/examples/data/dolfyn/AQD_HR.prf
new file mode 100644
index 000000000..1819ac847
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diff --git a/examples/data/dolfyn/AQD_test01.prf b/examples/data/dolfyn/AQD_test01.prf
new file mode 100644
index 000000000..a87e8c62c
Binary files /dev/null and b/examples/data/dolfyn/AQD_test01.prf differ
diff --git a/examples/data/dolfyn/Sig250_PacWave.ad2cp b/examples/data/dolfyn/Sig250_PacWave.ad2cp
new file mode 100644
index 000000000..eb9ac3c53
Binary files /dev/null and b/examples/data/dolfyn/Sig250_PacWave.ad2cp differ
diff --git a/examples/data/dolfyn/test_data/AQD_HR.nc b/examples/data/dolfyn/test_data/AQD_HR.nc
new file mode 100644
index 000000000..cd7c35ce1
Binary files /dev/null and b/examples/data/dolfyn/test_data/AQD_HR.nc differ
diff --git a/examples/data/dolfyn/test_data/AQD_test01.nc b/examples/data/dolfyn/test_data/AQD_test01.nc
new file mode 100644
index 000000000..6981b3c46
Binary files /dev/null and b/examples/data/dolfyn/test_data/AQD_test01.nc differ
diff --git a/examples/data/dolfyn/test_data/AWAC_test01.dolfyn.log b/examples/data/dolfyn/test_data/AWAC_test01.dolfyn.log
index b881b58da..e4bc50ae1 100644
--- a/examples/data/dolfyn/test_data/AWAC_test01.dolfyn.log
+++ b/examples/data/dolfyn/test_data/AWAC_test01.dolfyn.log
@@ -4,98 +4,98 @@ root - INFO - Position: 50, codes: (165, 4)
 root - INFO - Reading header configuration (0x04) ping #0 @ 50...
 root - INFO - Position: 274, codes: (165, 0)
 root - INFO - Reading user configuration (0x00) ping #0 @ 274...
+root - INFO - Init completed
 root - INFO - Position: 786, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #0 @ 786...
 root - INFO - Position: 1086, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #1 @ 1086...
 root - INFO - Position: 1386, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #2 @ 1386...
 root - INFO - Position: 1686, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #3 @ 1686...
 root - INFO - Position: 1986, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #4 @ 1986...
 root - INFO - Position: 2286, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #5 @ 2286...
 root - INFO - Position: 2586, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #6 @ 2586...
 root - INFO - Position: 2886, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #7 @ 2886...
 root - INFO - Position: 3186, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #8 @ 3186...
 root - INFO - Position: 3486, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #9 @ 3486...
 root - INFO - Position: 3786, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #10 @ 3786...
 root - INFO - Position: 4086, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #11 @ 4086...
 root - INFO - Position: 4386, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #12 @ 4386...
 root - INFO - Position: 4686, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #13 @ 4686...
 root - INFO - Position: 4986, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #14 @ 4986...
 root - INFO - Position: 5286, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #15 @ 5286...
 root - INFO - Position: 5586, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #16 @ 5586...
 root - INFO - Position: 5886, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #17 @ 5886...
 root - INFO - Position: 6186, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #18 @ 6186...
 root - INFO - Position: 6486, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #19 @ 6486...
 root - INFO - Position: 6786, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #20 @ 6786...
 root - INFO - Position: 7086, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #21 @ 7086...
 root - INFO - Position: 7386, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #22 @ 7386...
 root - INFO - Position: 7686, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #23 @ 7686...
 root - INFO - Position: 7986, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #24 @ 7986...
 root - INFO - Position: 8286, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #25 @ 8286...
 root - INFO - Position: 8586, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #26 @ 8586...
 root - INFO - Position: 8886, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #27 @ 8886...
 root - INFO - Position: 9186, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #28 @ 9186...
 root - INFO - Position: 9486, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #29 @ 9486...
 root - INFO - Position: 9786, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #30 @ 9786...
 root - INFO - Position: 10086, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #31 @ 10086...
 root - INFO - Position: 10386, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #32 @ 10386...
 root - INFO - Position: 10686, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #33 @ 10686...
 root - INFO - Position: 10986, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #34 @ 10986...
 root - INFO - Position: 11286, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #35 @ 11286...
 root - INFO - Position: 11586, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #36 @ 11586...
 root - INFO - Position: 11886, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #37 @ 11886...
 root - INFO - Position: 12186, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #38 @ 12186...
 root - INFO - Position: 12486, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #39 @ 12486...
 root - INFO - Position: 12786, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #40 @ 12786...
 root - INFO - Position: 13086, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #41 @ 13086...
 root - INFO - Position: 13386, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #42 @ 13386...
 root - INFO - Position: 13686, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #43 @ 13686...
 root - INFO - Position: 13986, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #44 @ 13986...
 root - INFO - Position: 14286, codes: (165, 32)
+root - INFO - Reading AWAC velocity data (0x20) ping #45 @ 14286...
 root - INFO - Position: 14586, codes: (165, 32)
-root - INFO - Position: 14886, codes: (165, 32)
-root - INFO - Position: 15186, codes: (165, 32)
-root - INFO - Position: 15486, codes: (165, 32)
-root - INFO - Position: 15786, codes: (165, 32)
-root - INFO - p0=1084, pos=16084, i=49
-root - INFO - Init completed
-root - INFO - Position: 786, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #0 @ 786...
-root - INFO - Position: 1086, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #1 @ 1086...
-root - INFO - Position: 1386, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #2 @ 1386...
-root - INFO - Position: 1686, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #3 @ 1686...
-root - INFO - Position: 1986, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #4 @ 1986...
-root - INFO - Position: 2286, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #5 @ 2286...
-root - INFO - Position: 2586, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #6 @ 2586...
-root - INFO - Position: 2886, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #7 @ 2886...
-root - INFO - Position: 3186, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #8 @ 3186...
-root - INFO - Position: 3486, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #9 @ 3486...
-root - INFO - Position: 3786, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #10 @ 3786...
-root - INFO - Position: 4086, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #11 @ 4086...
-root - INFO - Position: 4386, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #12 @ 4386...
-root - INFO - Position: 4686, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #13 @ 4686...
-root - INFO - Position: 4986, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #14 @ 4986...
-root - INFO - Position: 5286, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #15 @ 5286...
-root - INFO - Position: 5586, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #16 @ 5586...
-root - INFO - Position: 5886, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #17 @ 5886...
-root - INFO - Position: 6186, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #18 @ 6186...
-root - INFO - Position: 6486, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #19 @ 6486...
-root - INFO - Position: 6786, codes: (165, 32)
-root - INFO - Reading AWAC velocity data (0x20) ping #20 @ 6786...
+root - INFO - Reading AWAC velocity data (0x20) ping #46 @ 14586...
diff --git a/examples/data/dolfyn/test_data/AWAC_test01.nc b/examples/data/dolfyn/test_data/AWAC_test01.nc
index bcb760986..6665617f1 100644
Binary files a/examples/data/dolfyn/test_data/AWAC_test01.nc and b/examples/data/dolfyn/test_data/AWAC_test01.nc differ
diff --git a/examples/data/dolfyn/test_data/AWAC_test01_clean.nc b/examples/data/dolfyn/test_data/AWAC_test01_clean.nc
index 886468e8c..91058ffe5 100644
Binary files a/examples/data/dolfyn/test_data/AWAC_test01_clean.nc and b/examples/data/dolfyn/test_data/AWAC_test01_clean.nc differ
diff --git a/examples/data/dolfyn/test_data/AWAC_test01_earth2inst.nc b/examples/data/dolfyn/test_data/AWAC_test01_earth2inst.nc
index 6d2946c83..bde739af3 100644
Binary files a/examples/data/dolfyn/test_data/AWAC_test01_earth2inst.nc and b/examples/data/dolfyn/test_data/AWAC_test01_earth2inst.nc differ
diff --git a/examples/data/dolfyn/test_data/AWAC_test01_earth2principal.nc b/examples/data/dolfyn/test_data/AWAC_test01_earth2principal.nc
index f5b5c3256..f215b80ed 100644
Binary files a/examples/data/dolfyn/test_data/AWAC_test01_earth2principal.nc and b/examples/data/dolfyn/test_data/AWAC_test01_earth2principal.nc differ
diff --git a/examples/data/dolfyn/test_data/AWAC_test01_inst2beam.nc b/examples/data/dolfyn/test_data/AWAC_test01_inst2beam.nc
index 3ccd55d68..3109eed25 100644
Binary files a/examples/data/dolfyn/test_data/AWAC_test01_inst2beam.nc and b/examples/data/dolfyn/test_data/AWAC_test01_inst2beam.nc differ
diff --git a/examples/data/dolfyn/test_data/AWAC_test01_ud.nc b/examples/data/dolfyn/test_data/AWAC_test01_ud.nc
index e7dfa248f..821d011e3 100644
Binary files a/examples/data/dolfyn/test_data/AWAC_test01_ud.nc and b/examples/data/dolfyn/test_data/AWAC_test01_ud.nc differ
diff --git a/examples/data/dolfyn/test_data/H-AWAC_test01.nc b/examples/data/dolfyn/test_data/H-AWAC_test01.nc
index 880168335..ebf3d3c1a 100644
Binary files a/examples/data/dolfyn/test_data/H-AWAC_test01.nc and b/examples/data/dolfyn/test_data/H-AWAC_test01.nc differ
diff --git a/examples/data/dolfyn/test_data/dat_vec.mat b/examples/data/dolfyn/test_data/dat_vec.mat
index 85285e561..f4edad78d 100644
Binary files a/examples/data/dolfyn/test_data/dat_vec.mat and b/examples/data/dolfyn/test_data/dat_vec.mat differ
diff --git a/examples/data/dolfyn/test_data/vector_burst_mode01.nc b/examples/data/dolfyn/test_data/vector_burst_mode01.nc
index dfadef40b..37181bd36 100644
Binary files a/examples/data/dolfyn/test_data/vector_burst_mode01.nc and b/examples/data/dolfyn/test_data/vector_burst_mode01.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data01.nc b/examples/data/dolfyn/test_data/vector_data01.nc
index 6deb0dc39..ac71f82a2 100644
Binary files a/examples/data/dolfyn/test_data/vector_data01.nc and b/examples/data/dolfyn/test_data/vector_data01.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data01_GN.nc b/examples/data/dolfyn/test_data/vector_data01_GN.nc
index 83052cc27..edec45b1f 100644
Binary files a/examples/data/dolfyn/test_data/vector_data01_GN.nc and b/examples/data/dolfyn/test_data/vector_data01_GN.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data01_avg.nc b/examples/data/dolfyn/test_data/vector_data01_avg.nc
index d1a540e49..be54fff88 100644
Binary files a/examples/data/dolfyn/test_data/vector_data01_avg.nc and b/examples/data/dolfyn/test_data/vector_data01_avg.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data01_bin.nc b/examples/data/dolfyn/test_data/vector_data01_bin.nc
index f7c60a59d..bfb6875cc 100644
Binary files a/examples/data/dolfyn/test_data/vector_data01_bin.nc and b/examples/data/dolfyn/test_data/vector_data01_bin.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data01_rclean.nc b/examples/data/dolfyn/test_data/vector_data01_rclean.nc
index 7ff94f7be..f75191ab9 100644
Binary files a/examples/data/dolfyn/test_data/vector_data01_rclean.nc and b/examples/data/dolfyn/test_data/vector_data01_rclean.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data01_rotate_earth2principal.nc b/examples/data/dolfyn/test_data/vector_data01_rotate_earth2principal.nc
index 8c31401d2..3664c9ed9 100644
Binary files a/examples/data/dolfyn/test_data/vector_data01_rotate_earth2principal.nc and b/examples/data/dolfyn/test_data/vector_data01_rotate_earth2principal.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data01_rotate_inst2beam.nc b/examples/data/dolfyn/test_data/vector_data01_rotate_inst2beam.nc
index 461eb8674..8a784ec7c 100644
Binary files a/examples/data/dolfyn/test_data/vector_data01_rotate_inst2beam.nc and b/examples/data/dolfyn/test_data/vector_data01_rotate_inst2beam.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data01_rotate_inst2earth.nc b/examples/data/dolfyn/test_data/vector_data01_rotate_inst2earth.nc
index 7177e79b9..8c7852c17 100644
Binary files a/examples/data/dolfyn/test_data/vector_data01_rotate_inst2earth.nc and b/examples/data/dolfyn/test_data/vector_data01_rotate_inst2earth.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data01_sclean.nc b/examples/data/dolfyn/test_data/vector_data01_sclean.nc
index 7ff94f7be..f75191ab9 100644
Binary files a/examples/data/dolfyn/test_data/vector_data01_sclean.nc and b/examples/data/dolfyn/test_data/vector_data01_sclean.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data_imu01-json.nc b/examples/data/dolfyn/test_data/vector_data_imu01-json.nc
index 2ac6b8186..2d06e12bf 100644
Binary files a/examples/data/dolfyn/test_data/vector_data_imu01-json.nc and b/examples/data/dolfyn/test_data/vector_data_imu01-json.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data_imu01-json_mc.nc b/examples/data/dolfyn/test_data/vector_data_imu01-json_mc.nc
index 0e1fa430d..946ddd84d 100644
Binary files a/examples/data/dolfyn/test_data/vector_data_imu01-json_mc.nc and b/examples/data/dolfyn/test_data/vector_data_imu01-json_mc.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data_imu01.dolfyn.log b/examples/data/dolfyn/test_data/vector_data_imu01.dolfyn.log
index 649692018..58c4e2332 100644
--- a/examples/data/dolfyn/test_data/vector_data_imu01.dolfyn.log
+++ b/examples/data/dolfyn/test_data/vector_data_imu01.dolfyn.log
@@ -4,98 +4,98 @@ root - INFO - Position: 50, codes: (165, 4)
 root - INFO - Reading header configuration (0x04) ping #0 @ 50...
 root - INFO - Position: 274, codes: (165, 0)
 root - INFO - Reading user configuration (0x00) ping #0 @ 274...
+root - INFO - Init completed
 root - INFO - Position: 786, codes: (165, 18)
+root - INFO - Reading Vector header data (0x12) ping #0 @ 786...
 root - INFO - Position: 828, codes: (165, 7)
+root - INFO - Reading Vector check data (0x07) ping #0 @ 828...
 root - INFO - Position: 1738, codes: (165, 17)
+root - INFO - Reading Vector system data (0x11) ping #0 @ 1738...
 root - INFO - Position: 1766, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #0 @ 1766...
 root - INFO - Position: 1790, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #0 @ 1790...
 root - INFO - Position: 1876, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #1 @ 1876...
 root - INFO - Position: 1900, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #1 @ 1900...
 root - INFO - Position: 1986, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #2 @ 1986...
 root - INFO - Position: 2010, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #2 @ 2010...
 root - INFO - Position: 2096, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #3 @ 2096...
 root - INFO - Position: 2120, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #3 @ 2120...
 root - INFO - Position: 2206, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #4 @ 2206...
 root - INFO - Position: 2230, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #4 @ 2230...
 root - INFO - Position: 2316, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #5 @ 2316...
 root - INFO - Position: 2340, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #5 @ 2340...
 root - INFO - Position: 2426, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #6 @ 2426...
 root - INFO - Position: 2450, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #6 @ 2450...
 root - INFO - Position: 2536, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #7 @ 2536...
 root - INFO - Position: 2560, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #7 @ 2560...
 root - INFO - Position: 2646, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #8 @ 2646...
 root - INFO - Position: 2670, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #8 @ 2670...
 root - INFO - Position: 2756, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #9 @ 2756...
 root - INFO - Position: 2780, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #9 @ 2780...
 root - INFO - Position: 2866, codes: (165, 17)
+root - INFO - Reading Vector system data (0x11) ping #10 @ 2866...
 root - INFO - Position: 2894, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #10 @ 2894...
 root - INFO - Position: 2918, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #10 @ 2918...
 root - INFO - Position: 3004, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #11 @ 3004...
 root - INFO - Position: 3028, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #11 @ 3028...
 root - INFO - Position: 3114, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #12 @ 3114...
 root - INFO - Position: 3138, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #12 @ 3138...
 root - INFO - Position: 3224, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #13 @ 3224...
 root - INFO - Position: 3248, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #13 @ 3248...
 root - INFO - Position: 3334, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #14 @ 3334...
 root - INFO - Position: 3358, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #14 @ 3358...
 root - INFO - Position: 3444, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #15 @ 3444...
 root - INFO - Position: 3468, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #15 @ 3468...
 root - INFO - Position: 3554, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #16 @ 3554...
 root - INFO - Position: 3578, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #16 @ 3578...
 root - INFO - Position: 3664, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #17 @ 3664...
 root - INFO - Position: 3688, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #17 @ 3688...
 root - INFO - Position: 3774, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #18 @ 3774...
 root - INFO - Position: 3798, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #18 @ 3798...
 root - INFO - Position: 3884, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #19 @ 3884...
 root - INFO - Position: 3908, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #19 @ 3908...
 root - INFO - Position: 3994, codes: (165, 16)
+root - INFO - Reading Vector measurements (0x10) ping #20 @ 3994...
 root - INFO - Position: 4018, codes: (165, 113)
+root - INFO - Reading Vector IMU data (0x71) ping #20 @ 4018...
 root - INFO - Position: 4104, codes: (165, 16)
-root - INFO - Position: 4128, codes: (165, 113)
-root - INFO - Position: 4214, codes: (165, 16)
-root - INFO - Position: 4238, codes: (165, 113)
-root - INFO - Position: 4324, codes: (165, 16)
-root - INFO - Position: 4348, codes: (165, 113)
-root - INFO - Position: 4434, codes: (165, 16)
-root - INFO - Position: 4458, codes: (165, 113)
-root - INFO - Position: 4544, codes: (165, 16)
-root - INFO - Position: 4568, codes: (165, 113)
-root - INFO - Position: 4654, codes: (165, 16)
-root - INFO - Position: 4678, codes: (165, 113)
-root - INFO - Position: 4764, codes: (165, 16)
-root - INFO - Position: 4788, codes: (165, 113)
-root - INFO - Position: 4874, codes: (165, 16)
-root - INFO - Position: 4898, codes: (165, 113)
-root - INFO - Position: 4984, codes: (165, 16)
-root - INFO - Position: 5008, codes: (165, 113)
-root - INFO - Position: 5094, codes: (165, 16)
-root - INFO - Position: 5118, codes: (165, 113)
-root - INFO - Position: 5204, codes: (165, 16)
-root - INFO - Position: 5228, codes: (165, 113)
-root - INFO - Position: 5314, codes: (165, 16)
-root - INFO - Position: 5338, codes: (165, 113)
-root - INFO - Position: 5424, codes: (165, 16)
-root - INFO - Position: 5448, codes: (165, 113)
-root - INFO - Position: 5534, codes: (165, 16)
-root - INFO - Position: 5558, codes: (165, 113)
-root - INFO - Position: 5644, codes: (165, 16)
-root - INFO - Position: 5668, codes: (165, 113)
-root - INFO - Position: 5754, codes: (165, 16)
-root - INFO - Position: 5778, codes: (165, 113)
-root - INFO - Position: 5864, codes: (165, 16)
-root - INFO - Position: 5888, codes: (165, 113)
-root - INFO - Position: 5974, codes: (165, 16)
-root - INFO - Position: 5998, codes: (165, 113)
-root - INFO - Position: 6084, codes: (165, 16)
-root - INFO - Position: 6108, codes: (165, 113)
-root - INFO - Position: 6194, codes: (165, 16)
-root - INFO - Position: 6218, codes: (165, 113)
-root - INFO - Position: 6304, codes: (165, 16)
-root - INFO - Position: 6328, codes: (165, 113)
-root - INFO - Position: 6414, codes: (165, 16)
-root - INFO - Position: 6438, codes: (165, 17)
-root - INFO - Position: 6466, codes: (165, 113)
-root - INFO - Position: 6552, codes: (165, 16)
-root - INFO - Position: 6576, codes: (165, 113)
-root - INFO - Position: 6662, codes: (165, 16)
-root - INFO - Position: 6686, codes: (165, 113)
+root - INFO - Reading Vector measurements (0x10) ping #21 @ 4104...
diff --git a/examples/data/dolfyn/test_data/vector_data_imu01.nc b/examples/data/dolfyn/test_data/vector_data_imu01.nc
index 7a92bf125..f75191ab9 100644
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diff --git a/examples/data/dolfyn/test_data/vector_data_imu01_GN.nc b/examples/data/dolfyn/test_data/vector_data_imu01_GN.nc
index c3a9fa523..3d23a834c 100644
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diff --git a/examples/data/dolfyn/test_data/vector_data_imu01_head_pitch_roll.nc b/examples/data/dolfyn/test_data/vector_data_imu01_head_pitch_roll.nc
index 76e1026dd..a5086d7f3 100644
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diff --git a/examples/data/dolfyn/test_data/vector_data_imu01_mc.nc b/examples/data/dolfyn/test_data/vector_data_imu01_mc.nc
index 65b2af058..b6d87e54f 100644
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diff --git a/examples/data/dolfyn/test_data/vector_data_imu01_mcDeclin10.nc b/examples/data/dolfyn/test_data/vector_data_imu01_mcDeclin10.nc
index 9ec17832b..036164501 100644
Binary files a/examples/data/dolfyn/test_data/vector_data_imu01_mcDeclin10.nc and b/examples/data/dolfyn/test_data/vector_data_imu01_mcDeclin10.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data_imu01_mcsp.nc b/examples/data/dolfyn/test_data/vector_data_imu01_mcsp.nc
index 90ab1cf5e..7129c668e 100644
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diff --git a/examples/data/dolfyn/test_data/vector_data_imu01_rotate_earth2principal.nc b/examples/data/dolfyn/test_data/vector_data_imu01_rotate_earth2principal.nc
index 41949b3ae..9d2136cda 100644
Binary files a/examples/data/dolfyn/test_data/vector_data_imu01_rotate_earth2principal.nc and b/examples/data/dolfyn/test_data/vector_data_imu01_rotate_earth2principal.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data_imu01_rotate_inst2beam.nc b/examples/data/dolfyn/test_data/vector_data_imu01_rotate_inst2beam.nc
index f46d85900..52ec19ef8 100644
Binary files a/examples/data/dolfyn/test_data/vector_data_imu01_rotate_inst2beam.nc and b/examples/data/dolfyn/test_data/vector_data_imu01_rotate_inst2beam.nc differ
diff --git a/examples/data/dolfyn/test_data/vector_data_imu01_rotate_inst2earth.nc b/examples/data/dolfyn/test_data/vector_data_imu01_rotate_inst2earth.nc
index 72e71eb3b..37e9c113f 100644
Binary files a/examples/data/dolfyn/test_data/vector_data_imu01_rotate_inst2earth.nc and b/examples/data/dolfyn/test_data/vector_data_imu01_rotate_inst2earth.nc differ
diff --git a/examples/directional_waves.ipynb b/examples/directional_waves.ipynb
index 99d87dd75..7bc584b9b 100644
--- a/examples/directional_waves.ipynb
+++ b/examples/directional_waves.ipynb
@@ -41,7 +41,7 @@
    "metadata": {},
    "source": [
     "## Request Data\n",
-    "First, we will check if the buoy we're interested in–42012—has directional data. To do this we use the `wave.io.ndbc.available_data` function with any one of the 4 parameters used for the spread function. \n",
+    "First, we will check if the buoy we're interested in–42012, a buoy located in the Gulf south of Alabama—has directional data. To do this we use the `wave.io.ndbc.available_data` function with any one of the 4 parameters used for the spread function. \n",
     "We can see that this buoy does have directional data for the years 2009-2021."
    ]
   },
@@ -78,116 +78,130 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>346</th>\n",
+       "      <th>378</th>\n",
        "      <td>42012</td>\n",
        "      <td>2009</td>\n",
        "      <td>42012d2009.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>347</th>\n",
+       "      <th>379</th>\n",
        "      <td>42012</td>\n",
        "      <td>2010</td>\n",
        "      <td>42012d2010.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>348</th>\n",
+       "      <th>380</th>\n",
        "      <td>42012</td>\n",
        "      <td>2011</td>\n",
        "      <td>42012d2011.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>349</th>\n",
+       "      <th>381</th>\n",
        "      <td>42012</td>\n",
        "      <td>2012</td>\n",
        "      <td>42012d2012.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>350</th>\n",
+       "      <th>382</th>\n",
        "      <td>42012</td>\n",
        "      <td>2013</td>\n",
        "      <td>42012d2013.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>351</th>\n",
+       "      <th>383</th>\n",
        "      <td>42012</td>\n",
        "      <td>2014</td>\n",
        "      <td>42012d2014.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>352</th>\n",
+       "      <th>384</th>\n",
        "      <td>42012</td>\n",
        "      <td>2015</td>\n",
        "      <td>42012d2015.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>353</th>\n",
+       "      <th>385</th>\n",
        "      <td>42012</td>\n",
        "      <td>2016</td>\n",
        "      <td>42012d2016.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>354</th>\n",
+       "      <th>386</th>\n",
        "      <td>42012</td>\n",
        "      <td>2017</td>\n",
        "      <td>42012d2017.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>355</th>\n",
+       "      <th>387</th>\n",
        "      <td>42012</td>\n",
        "      <td>2018</td>\n",
        "      <td>42012d2018.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>356</th>\n",
+       "      <th>388</th>\n",
        "      <td>42012</td>\n",
        "      <td>2019</td>\n",
        "      <td>42012d2019.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>357</th>\n",
+       "      <th>389</th>\n",
        "      <td>42012</td>\n",
        "      <td>2020</td>\n",
        "      <td>42012d2020.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>358</th>\n",
+       "      <th>390</th>\n",
        "      <td>42012</td>\n",
        "      <td>2021</td>\n",
        "      <td>42012d2021.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>359</th>\n",
+       "      <th>391</th>\n",
        "      <td>42012</td>\n",
        "      <td>2022</td>\n",
        "      <td>42012d2022.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>360</th>\n",
+       "      <th>392</th>\n",
        "      <td>42012</td>\n",
        "      <td>2023</td>\n",
        "      <td>42012d2023.txt.gz</td>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>393</th>\n",
+       "      <td>42012</td>\n",
+       "      <td>2024</td>\n",
+       "      <td>42012d2024.txt.gz</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>394</th>\n",
+       "      <td>42012</td>\n",
+       "      <td>2025</td>\n",
+       "      <td>42012d2025.txt.gz</td>\n",
+       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
        "        id  year           filename\n",
-       "346  42012  2009  42012d2009.txt.gz\n",
-       "347  42012  2010  42012d2010.txt.gz\n",
-       "348  42012  2011  42012d2011.txt.gz\n",
-       "349  42012  2012  42012d2012.txt.gz\n",
-       "350  42012  2013  42012d2013.txt.gz\n",
-       "351  42012  2014  42012d2014.txt.gz\n",
-       "352  42012  2015  42012d2015.txt.gz\n",
-       "353  42012  2016  42012d2016.txt.gz\n",
-       "354  42012  2017  42012d2017.txt.gz\n",
-       "355  42012  2018  42012d2018.txt.gz\n",
-       "356  42012  2019  42012d2019.txt.gz\n",
-       "357  42012  2020  42012d2020.txt.gz\n",
-       "358  42012  2021  42012d2021.txt.gz\n",
-       "359  42012  2022  42012d2022.txt.gz\n",
-       "360  42012  2023  42012d2023.txt.gz"
+       "378  42012  2009  42012d2009.txt.gz\n",
+       "379  42012  2010  42012d2010.txt.gz\n",
+       "380  42012  2011  42012d2011.txt.gz\n",
+       "381  42012  2012  42012d2012.txt.gz\n",
+       "382  42012  2013  42012d2013.txt.gz\n",
+       "383  42012  2014  42012d2014.txt.gz\n",
+       "384  42012  2015  42012d2015.txt.gz\n",
+       "385  42012  2016  42012d2016.txt.gz\n",
+       "386  42012  2017  42012d2017.txt.gz\n",
+       "387  42012  2018  42012d2018.txt.gz\n",
+       "388  42012  2019  42012d2019.txt.gz\n",
+       "389  42012  2020  42012d2020.txt.gz\n",
+       "390  42012  2021  42012d2021.txt.gz\n",
+       "391  42012  2022  42012d2022.txt.gz\n",
+       "392  42012  2023  42012d2023.txt.gz\n",
+       "393  42012  2024  42012d2024.txt.gz\n",
+       "394  42012  2025  42012d2025.txt.gz"
       ]
      },
      "execution_count": 2,
@@ -204,7 +218,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We will ask for the data for 2021. To do this we use the `wave.io.ndbc.request_directional_data` function. We see that the spectrum is calculated over ~1hour which results in 8572 different timestamps. We also see there are 47 frequency bins."
+    "We will ask for the data for 2021. To do this we use the `wave.io.ndbc.request_directional_data` function. We see that the spectrum is calculated over ~1 hour which results in 8572 different timestamps. We also see there are 47 frequency bins."
    ]
   },
   {
@@ -230,39 +244,86 @@
        "</symbol>\n",
        "</defs>\n",
        "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
-       " *\n",
-       " */\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
        "\n",
        ":root {\n",
-       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
-       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
-       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
-       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
-       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
-       "  --xr-background-color: var(--jp-layout-color0, white);\n",
-       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
-       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
-       "}\n",
-       "\n",
-       "html[theme=dark],\n",
-       "html[data-theme=dark],\n",
-       "body[data-theme=dark],\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
        "body.vscode-dark {\n",
-       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
-       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
-       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
-       "  --xr-border-color: #1F1F1F;\n",
-       "  --xr-disabled-color: #515151;\n",
-       "  --xr-background-color: #111111;\n",
-       "  --xr-background-color-row-even: #111111;\n",
-       "  --xr-background-color-row-odd: #313131;\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
        "}\n",
        "\n",
        ".xr-wrap {\n",
        "  display: block !important;\n",
        "  min-width: 300px;\n",
        "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
        "}\n",
        "\n",
        ".xr-text-repr-fallback {\n",
@@ -285,11 +346,18 @@
        "}\n",
        "\n",
        ".xr-obj-type,\n",
-       ".xr-array-name {\n",
+       ".xr-obj-name,\n",
+       ".xr-group-name {\n",
        "  margin-left: 2px;\n",
        "  margin-right: 10px;\n",
        "}\n",
        "\n",
+       ".xr-group-name::before {\n",
+       "  content: \"📁\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-name,\n",
        ".xr-obj-type {\n",
        "  color: var(--xr-font-color2);\n",
        "}\n",
@@ -297,7 +365,9 @@
        ".xr-sections {\n",
        "  padding-left: 0 !important;\n",
        "  display: grid;\n",
-       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
        "}\n",
        "\n",
        ".xr-section-item {\n",
@@ -305,11 +375,15 @@
        "}\n",
        "\n",
        ".xr-section-item input {\n",
-       "  display: none;\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
        "}\n",
        "\n",
        ".xr-section-item input + label {\n",
        "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
        "}\n",
        "\n",
        ".xr-section-item input:enabled + label {\n",
@@ -317,6 +391,10 @@
        "  color: var(--xr-font-color2);\n",
        "}\n",
        "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
        ".xr-section-item input:enabled + label:hover {\n",
        "  color: var(--xr-font-color0);\n",
        "}\n",
@@ -338,7 +416,7 @@
        "\n",
        ".xr-section-summary-in + label:before {\n",
        "  display: inline-block;\n",
-       "  content: '►';\n",
+       "  content: \"►\";\n",
        "  font-size: 11px;\n",
        "  width: 15px;\n",
        "  text-align: center;\n",
@@ -349,7 +427,7 @@
        "}\n",
        "\n",
        ".xr-section-summary-in:checked + label:before {\n",
-       "  content: '▼';\n",
+       "  content: \"▼\";\n",
        "}\n",
        "\n",
        ".xr-section-summary-in:checked + label > span {\n",
@@ -359,7 +437,6 @@
        ".xr-section-summary,\n",
        ".xr-section-inline-details {\n",
        "  padding-top: 4px;\n",
-       "  padding-bottom: 4px;\n",
        "}\n",
        "\n",
        ".xr-section-inline-details {\n",
@@ -369,6 +446,7 @@
        ".xr-section-details {\n",
        "  display: none;\n",
        "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
        "  margin-bottom: 5px;\n",
        "}\n",
        "\n",
@@ -376,6 +454,32 @@
        "  display: contents;\n",
        "}\n",
        "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 20px auto;\n",
+       "  width: 100%;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 20px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "}\n",
+       "\n",
        ".xr-array-wrap {\n",
        "  grid-column: 1 / -1;\n",
        "  display: grid;\n",
@@ -421,15 +525,15 @@
        "}\n",
        "\n",
        ".xr-dim-list:before {\n",
-       "  content: '(';\n",
+       "  content: \"(\";\n",
        "}\n",
        "\n",
        ".xr-dim-list:after {\n",
-       "  content: ')';\n",
+       "  content: \")\";\n",
        "}\n",
        "\n",
        ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: ',';\n",
+       "  content: \",\";\n",
        "  padding-right: 5px;\n",
        "}\n",
        "\n",
@@ -446,7 +550,9 @@
        ".xr-var-item label,\n",
        ".xr-var-item > .xr-var-name span {\n",
        "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
        "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
        "}\n",
        "\n",
        ".xr-var-item > .xr-var-name:hover span {\n",
@@ -457,6 +563,7 @@
        ".xr-var-list > li:nth-child(odd) > label,\n",
        ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
        "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
        "}\n",
        "\n",
        ".xr-var-name {\n",
@@ -506,8 +613,15 @@
        ".xr-var-data,\n",
        ".xr-index-data {\n",
        "  display: none;\n",
-       "  background-color: var(--xr-background-color) !important;\n",
-       "  padding-bottom: 5px !important;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
        "}\n",
        "\n",
        ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
@@ -520,6 +634,12 @@
        "  float: right;\n",
        "}\n",
        "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
        ".xr-index-name div,\n",
@@ -579,78 +699,69 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 16MB\n",
        "Dimensions:    (date: 8572, frequency: 47)\n",
        "Coordinates:\n",
-       "  * date       (date) datetime64[ns] 69kB 2021-01-01T00:40:00 ... 2021-12-31T...\n",
+       "  * date       (date) datetime64[us] 69kB 2021-01-01T00:40:00 ... 2021-12-31T...\n",
        "  * frequency  (frequency) float64 376B 0.02 0.0325 0.0375 ... 0.445 0.465 0.485\n",
        "Data variables:\n",
        "    swden      (date, frequency) float64 3MB 0.0 0.0 0.0 0.0 ... 0.01 0.02 0.0\n",
        "    swdir      (date, frequency) float64 3MB 194.0 13.0 6.0 ... 167.0 159.0\n",
        "    swdir2     (date, frequency) float64 3MB 191.0 11.0 9.0 ... 169.0 106.0\n",
        "    swr1       (date, frequency) float64 3MB 0.16 0.26 0.21 ... 0.76 0.87 0.63\n",
-       "    swr2       (date, frequency) float64 3MB 0.99 0.93 0.9 ... 0.28 0.67 0.1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a570ad58-2fe6-4c75-9054-8b4e5179aa77' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a570ad58-2fe6-4c75-9054-8b4e5179aa77' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>date</span>: 8572</li><li><span class='xr-has-index'>frequency</span>: 47</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9a5d80a8-3471-434e-8b89-0ef65c32ebda' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9a5d80a8-3471-434e-8b89-0ef65c32ebda' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>date</span></div><div class='xr-var-dims'>(date)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01T00:40:00 ... 2021-12-...</div><input id='attrs-313cb012-7088-4776-b6b4-6087799bb91c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-313cb012-7088-4776-b6b4-6087799bb91c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec2ff83b-baef-43de-9f45-011bc4dcc930' class='xr-var-data-in' type='checkbox'><label for='data-ec2ff83b-baef-43de-9f45-011bc4dcc930' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>datetime</dd><dt><span>standard_name :</span></dt><dd>t</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:40:00.000000000&#x27;, &#x27;2021-01-01T01:40:00.000000000&#x27;,\n",
-       "       &#x27;2021-01-01T02:40:00.000000000&#x27;, ..., &#x27;2021-12-31T21:40:00.000000000&#x27;,\n",
-       "       &#x27;2021-12-31T22:40:00.000000000&#x27;, &#x27;2021-12-31T23:40:00.000000000&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02 0.0325 0.0375 ... 0.465 0.485</div><input id='attrs-113d9e44-9203-40de-a87a-ce9b96db0295' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-113d9e44-9203-40de-a87a-ce9b96db0295' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b38a32a2-2487-46a8-bac8-44dd586859d2' class='xr-var-data-in' type='checkbox'><label for='data-b38a32a2-2487-46a8-bac8-44dd586859d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>frequency</dd><dt><span>standard_name :</span></dt><dd>f</dd></dl></div><div class='xr-var-data'><pre>array([0.02  , 0.0325, 0.0375, 0.0425, 0.0475, 0.0525, 0.0575, 0.0625, 0.0675,\n",
+       "    swr2       (date, frequency) float64 3MB 0.99 0.93 0.9 ... 0.28 0.67 0.1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9c031c50-7cfd-453b-a761-a1ddd3da4ff7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9c031c50-7cfd-453b-a761-a1ddd3da4ff7' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>date</span>: 8572</li><li><span class='xr-has-index'>frequency</span>: 47</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e0ddc0a6-3f38-4425-b433-d3b5c73bbe9c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e0ddc0a6-3f38-4425-b433-d3b5c73bbe9c' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>date</span></div><div class='xr-var-dims'>(date)</div><div class='xr-var-dtype'>datetime64[us]</div><div class='xr-var-preview xr-preview'>2021-01-01T00:40:00 ... 2021-12-...</div><input id='attrs-60559a62-de99-415f-84ec-10868e9d0bc4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60559a62-de99-415f-84ec-10868e9d0bc4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2111a76e-dd0c-473c-b5dd-d330e4d17c69' class='xr-var-data-in' type='checkbox'><label for='data-2111a76e-dd0c-473c-b5dd-d330e4d17c69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>datetime</dd><dt><span>standard_name :</span></dt><dd>t</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:40:00.000000&#x27;, &#x27;2021-01-01T01:40:00.000000&#x27;,\n",
+       "       &#x27;2021-01-01T02:40:00.000000&#x27;, ..., &#x27;2021-12-31T21:40:00.000000&#x27;,\n",
+       "       &#x27;2021-12-31T22:40:00.000000&#x27;, &#x27;2021-12-31T23:40:00.000000&#x27;],\n",
+       "      shape=(8572,), dtype=&#x27;datetime64[us]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02 0.0325 0.0375 ... 0.465 0.485</div><input id='attrs-0e80c0c8-2121-4469-98bc-bf4213bdb57d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e80c0c8-2121-4469-98bc-bf4213bdb57d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-61e77607-a84c-4ce8-95b3-cf311831e31b' class='xr-var-data-in' type='checkbox'><label for='data-61e77607-a84c-4ce8-95b3-cf311831e31b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>frequency</dd><dt><span>standard_name :</span></dt><dd>f</dd></dl></div><div class='xr-var-data'><pre>array([0.02  , 0.0325, 0.0375, 0.0425, 0.0475, 0.0525, 0.0575, 0.0625, 0.0675,\n",
        "       0.0725, 0.0775, 0.0825, 0.0875, 0.0925, 0.1   , 0.11  , 0.12  , 0.13  ,\n",
        "       0.14  , 0.15  , 0.16  , 0.17  , 0.18  , 0.19  , 0.2   , 0.21  , 0.22  ,\n",
        "       0.23  , 0.24  , 0.25  , 0.26  , 0.27  , 0.28  , 0.29  , 0.3   , 0.31  ,\n",
        "       0.32  , 0.33  , 0.34  , 0.35  , 0.365 , 0.385 , 0.405 , 0.425 , 0.445 ,\n",
-       "       0.465 , 0.485 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f5ed5387-ddaa-483c-926e-bad809afd09b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f5ed5387-ddaa-483c-926e-bad809afd09b' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>swden</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.01 0.02 0.0</div><input id='attrs-18ec67a8-483c-47c7-a495-f3a124169895' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18ec67a8-483c-47c7-a495-f3a124169895' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1cd658d3-400a-4135-8196-3865ad6f61d2' class='xr-var-data-in' type='checkbox'><label for='data-1cd658d3-400a-4135-8196-3865ad6f61d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m^2/Hz</dd><dt><span>long_name :</span></dt><dd>omnidirecational spectrum</dd><dt><span>standard_name :</span></dt><dd>S</dd><dt><span>description :</span></dt><dd>Omnidirectional *sea surface elevation variance (m^2)* spectrum (/Hz).</dd></dl></div><div class='xr-var-data'><pre>array([[0.  , 0.  , 0.  , ..., 0.03, 0.02, 0.02],\n",
+       "       0.465 , 0.485 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f2eea650-229b-439b-bb1c-282a8ff4ad2f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f2eea650-229b-439b-bb1c-282a8ff4ad2f' class='xr-section-summary' >Data variables: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>swden</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.01 0.02 0.0</div><input id='attrs-acb6f8a6-3d12-4562-812e-39488f482e89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acb6f8a6-3d12-4562-812e-39488f482e89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a248ab18-28e7-419f-a14e-e48d3da2c0d8' class='xr-var-data-in' type='checkbox'><label for='data-a248ab18-28e7-419f-a14e-e48d3da2c0d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m^2/Hz</dd><dt><span>long_name :</span></dt><dd>omnidirectional spectrum</dd><dt><span>standard_name :</span></dt><dd>S</dd><dt><span>description :</span></dt><dd>Omnidirectional *sea surface elevation variance (m^2)* spectrum (/Hz).</dd></dl></div><div class='xr-var-data'><pre>array([[0.  , 0.  , 0.  , ..., 0.03, 0.02, 0.02],\n",
        "       [0.  , 0.  , 0.  , ..., 0.03, 0.02, 0.01],\n",
        "       [0.  , 0.  , 0.  , ..., 0.02, 0.02, 0.01],\n",
        "       ...,\n",
        "       [0.  , 0.  , 0.  , ..., 0.01, 0.01, 0.02],\n",
        "       [0.  , 0.  , 0.  , ..., 0.01, 0.01, 0.01],\n",
-       "       [0.  , 0.  , 0.  , ..., 0.01, 0.02, 0.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swdir</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>194.0 13.0 6.0 ... 167.0 159.0</div><input id='attrs-f3871019-520c-4696-827d-8487b1f723ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f3871019-520c-4696-827d-8487b1f723ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b7070e3-81a5-40b8-acf1-ee1fdbb1a268' class='xr-var-data-in' type='checkbox'><label for='data-8b7070e3-81a5-40b8-acf1-ee1fdbb1a268' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>long_name :</span></dt><dd>mean wave direction</dd><dt><span>standard_name :</span></dt><dd>α1</dd><dt><span>description :</span></dt><dd>Mean wave direction.</dd></dl></div><div class='xr-var-data'><pre>array([[194.,  13.,   6., ..., 127., 125., 129.],\n",
+       "       [0.  , 0.  , 0.  , ..., 0.01, 0.02, 0.  ]], shape=(8572, 47))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swdir</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>194.0 13.0 6.0 ... 167.0 159.0</div><input id='attrs-14d3cda6-53f7-4b54-8e0c-f67d14163cec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14d3cda6-53f7-4b54-8e0c-f67d14163cec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22588ac6-535f-46a7-9dbb-cdabc93a224e' class='xr-var-data-in' type='checkbox'><label for='data-22588ac6-535f-46a7-9dbb-cdabc93a224e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>mean wave direction</dd><dt><span>standard_name :</span></dt><dd>α1</dd><dt><span>description :</span></dt><dd>Mean wave direction.</dd></dl></div><div class='xr-var-data'><pre>array([[194.,  13.,   6., ..., 127., 125., 129.],\n",
        "       [179., 192., 205., ..., 134., 122., 138.],\n",
        "       [193., 356., 177., ..., 141., 128., 123.],\n",
        "       ...,\n",
        "       [ 26., 213.,  21., ..., 177., 179., 181.],\n",
        "       [194.,   7., 345., ..., 150., 176., 181.],\n",
-       "       [198., 199.,  29., ..., 173., 167., 159.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swdir2</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>191.0 11.0 9.0 ... 169.0 106.0</div><input id='attrs-96dcc3af-fcaf-4ed8-ad71-fd9375426a5b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96dcc3af-fcaf-4ed8-ad71-fd9375426a5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42fbc38a-2e11-43a1-870e-69a07eceae29' class='xr-var-data-in' type='checkbox'><label for='data-42fbc38a-2e11-43a1-870e-69a07eceae29' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>long_name :</span></dt><dd>principal wave direction</dd><dt><span>standard_name :</span></dt><dd>α2</dd><dt><span>description :</span></dt><dd>Principal wave direction.</dd></dl></div><div class='xr-var-data'><pre>array([[191.,  11.,   9., ..., 132., 118., 120.],\n",
+       "       [198., 199.,  29., ..., 173., 167., 159.]], shape=(8572, 47))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swdir2</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>191.0 11.0 9.0 ... 169.0 106.0</div><input id='attrs-a539b62a-ac22-4f33-aaf8-09d39153808d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a539b62a-ac22-4f33-aaf8-09d39153808d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1fdd91a-3b11-4d90-96a6-205257b6406f' class='xr-var-data-in' type='checkbox'><label for='data-f1fdd91a-3b11-4d90-96a6-205257b6406f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>principal wave direction</dd><dt><span>standard_name :</span></dt><dd>α2</dd><dt><span>description :</span></dt><dd>Principal wave direction.</dd></dl></div><div class='xr-var-data'><pre>array([[191.,  11.,   9., ..., 132., 118., 120.],\n",
        "       [197., 200., 197., ..., 106., 106., 117.],\n",
        "       [187.,   7., 188., ..., 147.,  75.,  53.],\n",
        "       ...,\n",
        "       [ 26., 200.,  22., ..., 179., 201., 184.],\n",
        "       [202.,  25.,  24., ..., 129., 178., 184.],\n",
-       "       [207., 204.,  26., ..., 178., 169., 106.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swr1</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.16 0.26 0.21 ... 0.76 0.87 0.63</div><input id='attrs-74bb48ff-8fe0-4f87-8df9-5a1a99541fe6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74bb48ff-8fe0-4f87-8df9-5a1a99541fe6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-258e0fa1-c211-46f6-9202-a318bf0792be' class='xr-var-data-in' type='checkbox'><label for='data-258e0fa1-c211-46f6-9202-a318bf0792be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>coordinate r1</dd><dt><span>standard_name :</span></dt><dd>r1</dd><dt><span>description :</span></dt><dd>First normalized polar coordinate of the Fourier coefficients (nondimensional).</dd></dl></div><div class='xr-var-data'><pre>array([[0.16, 0.26, 0.21, ..., 0.74, 0.72, 0.72],\n",
+       "       [207., 204.,  26., ..., 178., 169., 106.]], shape=(8572, 47))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swr1</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.16 0.26 0.21 ... 0.76 0.87 0.63</div><input id='attrs-f09f27f9-fe17-47de-ba6e-48fd3b25a8e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f09f27f9-fe17-47de-ba6e-48fd3b25a8e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4299d7ff-0489-4511-b4f3-6b56b512cd67' class='xr-var-data-in' type='checkbox'><label for='data-4299d7ff-0489-4511-b4f3-6b56b512cd67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>coordinate r1</dd><dt><span>standard_name :</span></dt><dd>r1</dd><dt><span>description :</span></dt><dd>First normalized polar coordinate of the Fourier coefficients (nondimensional).</dd></dl></div><div class='xr-var-data'><pre>array([[0.16, 0.26, 0.21, ..., 0.74, 0.72, 0.72],\n",
        "       [0.07, 0.41, 0.08, ..., 0.67, 0.71, 0.68],\n",
        "       [0.23, 0.27, 0.34, ..., 0.65, 0.6 , 0.41],\n",
        "       ...,\n",
        "       [0.34, 0.18, 0.25, ..., 0.69, 0.7 , 0.84],\n",
        "       [0.17, 0.36, 0.29, ..., 0.69, 0.87, 0.82],\n",
-       "       [0.34, 0.44, 0.69, ..., 0.76, 0.87, 0.63]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swr2</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.99 0.93 0.9 ... 0.28 0.67 0.1</div><input id='attrs-8079fd66-9243-4863-b45e-9643d7e24e0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8079fd66-9243-4863-b45e-9643d7e24e0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ea5b4ed-9f0a-4b61-bfdb-b6670c13a075' class='xr-var-data-in' type='checkbox'><label for='data-3ea5b4ed-9f0a-4b61-bfdb-b6670c13a075' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>coordinate r2</dd><dt><span>standard_name :</span></dt><dd>r2</dd><dt><span>description :</span></dt><dd>Second normalized polar coordinate of the Fourier coefficients (nondimensional).</dd></dl></div><div class='xr-var-data'><pre>array([[0.99, 0.93, 0.9 , ..., 0.21, 0.21, 0.29],\n",
+       "       [0.34, 0.44, 0.69, ..., 0.76, 0.87, 0.63]], shape=(8572, 47))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swr2</span></div><div class='xr-var-dims'>(date, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.99 0.93 0.9 ... 0.28 0.67 0.1</div><input id='attrs-fdc5d48c-9afb-49fc-bab0-b98f9761f711' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fdc5d48c-9afb-49fc-bab0-b98f9761f711' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-daf35db4-f4a6-4b1e-997e-6ddb6639be61' class='xr-var-data-in' type='checkbox'><label for='data-daf35db4-f4a6-4b1e-997e-6ddb6639be61' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>coordinate r2</dd><dt><span>standard_name :</span></dt><dd>r2</dd><dt><span>description :</span></dt><dd>Second normalized polar coordinate of the Fourier coefficients (nondimensional).</dd></dl></div><div class='xr-var-data'><pre>array([[0.99, 0.93, 0.9 , ..., 0.21, 0.21, 0.29],\n",
        "       [0.98, 0.93, 0.88, ..., 0.12, 0.27, 0.13],\n",
        "       [0.99, 0.9 , 0.87, ..., 0.1 , 0.17, 0.32],\n",
        "       ...,\n",
        "       [0.94, 0.94, 0.92, ..., 0.19, 0.2 , 0.51],\n",
        "       [0.91, 0.87, 0.85, ..., 0.3 , 0.65, 0.5 ],\n",
-       "       [0.92, 0.91, 0.83, ..., 0.28, 0.67, 0.1 ]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ea045dee-7b8b-4aae-9060-f4acccdec2e1' class='xr-section-summary-in' type='checkbox'  ><label for='section-ea045dee-7b8b-4aae-9060-f4acccdec2e1' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>date</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1c14c4d2-8726-40da-9d7b-a0526c5a2744' class='xr-index-data-in' type='checkbox'/><label for='index-1c14c4d2-8726-40da-9d7b-a0526c5a2744' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2021-01-01 00:40:00&#x27;, &#x27;2021-01-01 01:40:00&#x27;,\n",
-       "               &#x27;2021-01-01 02:40:00&#x27;, &#x27;2021-01-01 03:40:00&#x27;,\n",
-       "               &#x27;2021-01-01 04:40:00&#x27;, &#x27;2021-01-01 05:40:00&#x27;,\n",
-       "               &#x27;2021-01-01 06:40:00&#x27;, &#x27;2021-01-01 07:40:00&#x27;,\n",
-       "               &#x27;2021-01-01 08:40:00&#x27;, &#x27;2021-01-01 09:40:00&#x27;,\n",
-       "               ...\n",
-       "               &#x27;2021-12-31 14:40:00&#x27;, &#x27;2021-12-31 15:40:00&#x27;,\n",
-       "               &#x27;2021-12-31 16:40:00&#x27;, &#x27;2021-12-31 17:40:00&#x27;,\n",
-       "               &#x27;2021-12-31 18:40:00&#x27;, &#x27;2021-12-31 19:40:00&#x27;,\n",
-       "               &#x27;2021-12-31 20:40:00&#x27;, &#x27;2021-12-31 21:40:00&#x27;,\n",
-       "               &#x27;2021-12-31 22:40:00&#x27;, &#x27;2021-12-31 23:40:00&#x27;],\n",
-       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;date&#x27;, length=8572, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>frequency</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3a8c8ea4-7c2d-4f15-ac86-3b6f3af6ae28' class='xr-index-data-in' type='checkbox'/><label for='index-3a8c8ea4-7c2d-4f15-ac86-3b6f3af6ae28' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.02, 0.0325, 0.0375, 0.0425, 0.0475, 0.0525, 0.0575, 0.0625, 0.0675,\n",
-       "       0.0725, 0.0775, 0.0825, 0.0875, 0.0925,    0.1,   0.11,   0.12,   0.13,\n",
-       "         0.14,   0.15,   0.16,   0.17,   0.18,   0.19,    0.2,   0.21,   0.22,\n",
-       "         0.23,   0.24,   0.25,   0.26,   0.27,   0.28,   0.29,    0.3,   0.31,\n",
-       "         0.32,   0.33,   0.34,   0.35,  0.365,  0.385,  0.405,  0.425,  0.445,\n",
-       "        0.465,  0.485],\n",
-       "      dtype=&#x27;float64&#x27;, name=&#x27;frequency&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bbf14af5-cc5d-4b71-abb7-f95a7015f03a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bbf14af5-cc5d-4b71-abb7-f95a7015f03a' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "       [0.92, 0.91, 0.83, ..., 0.28, 0.67, 0.1 ]], shape=(8572, 47))</pre></div></li></ul></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 16MB\n",
        "Dimensions:    (date: 8572, frequency: 47)\n",
        "Coordinates:\n",
-       "  * date       (date) datetime64[ns] 69kB 2021-01-01T00:40:00 ... 2021-12-31T...\n",
+       "  * date       (date) datetime64[us] 69kB 2021-01-01T00:40:00 ... 2021-12-31T...\n",
        "  * frequency  (frequency) float64 376B 0.02 0.0325 0.0375 ... 0.445 0.465 0.485\n",
        "Data variables:\n",
        "    swden      (date, frequency) float64 3MB 0.0 0.0 0.0 0.0 ... 0.01 0.02 0.0\n",
@@ -705,39 +816,86 @@
        "</symbol>\n",
        "</defs>\n",
        "</svg>\n",
-       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
-       " *\n",
-       " */\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
        "\n",
        ":root {\n",
-       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
-       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
-       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
-       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
-       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
-       "  --xr-background-color: var(--jp-layout-color0, white);\n",
-       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
-       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
-       "}\n",
-       "\n",
-       "html[theme=dark],\n",
-       "html[data-theme=dark],\n",
-       "body[data-theme=dark],\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
        "body.vscode-dark {\n",
-       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
-       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
-       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
-       "  --xr-border-color: #1F1F1F;\n",
-       "  --xr-disabled-color: #515151;\n",
-       "  --xr-background-color: #111111;\n",
-       "  --xr-background-color-row-even: #111111;\n",
-       "  --xr-background-color-row-odd: #313131;\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
        "}\n",
        "\n",
        ".xr-wrap {\n",
        "  display: block !important;\n",
        "  min-width: 300px;\n",
        "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
        "}\n",
        "\n",
        ".xr-text-repr-fallback {\n",
@@ -760,11 +918,18 @@
        "}\n",
        "\n",
        ".xr-obj-type,\n",
-       ".xr-array-name {\n",
+       ".xr-obj-name,\n",
+       ".xr-group-name {\n",
        "  margin-left: 2px;\n",
        "  margin-right: 10px;\n",
        "}\n",
        "\n",
+       ".xr-group-name::before {\n",
+       "  content: \"📁\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-name,\n",
        ".xr-obj-type {\n",
        "  color: var(--xr-font-color2);\n",
        "}\n",
@@ -772,7 +937,9 @@
        ".xr-sections {\n",
        "  padding-left: 0 !important;\n",
        "  display: grid;\n",
-       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
        "}\n",
        "\n",
        ".xr-section-item {\n",
@@ -780,11 +947,15 @@
        "}\n",
        "\n",
        ".xr-section-item input {\n",
-       "  display: none;\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
        "}\n",
        "\n",
        ".xr-section-item input + label {\n",
        "  color: var(--xr-disabled-color);\n",
+       "  border: 2px solid transparent !important;\n",
        "}\n",
        "\n",
        ".xr-section-item input:enabled + label {\n",
@@ -792,6 +963,10 @@
        "  color: var(--xr-font-color2);\n",
        "}\n",
        "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0) !important;\n",
+       "}\n",
+       "\n",
        ".xr-section-item input:enabled + label:hover {\n",
        "  color: var(--xr-font-color0);\n",
        "}\n",
@@ -813,7 +988,7 @@
        "\n",
        ".xr-section-summary-in + label:before {\n",
        "  display: inline-block;\n",
-       "  content: '►';\n",
+       "  content: \"►\";\n",
        "  font-size: 11px;\n",
        "  width: 15px;\n",
        "  text-align: center;\n",
@@ -824,7 +999,7 @@
        "}\n",
        "\n",
        ".xr-section-summary-in:checked + label:before {\n",
-       "  content: '▼';\n",
+       "  content: \"▼\";\n",
        "}\n",
        "\n",
        ".xr-section-summary-in:checked + label > span {\n",
@@ -834,7 +1009,6 @@
        ".xr-section-summary,\n",
        ".xr-section-inline-details {\n",
        "  padding-top: 4px;\n",
-       "  padding-bottom: 4px;\n",
        "}\n",
        "\n",
        ".xr-section-inline-details {\n",
@@ -844,6 +1018,7 @@
        ".xr-section-details {\n",
        "  display: none;\n",
        "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
        "  margin-bottom: 5px;\n",
        "}\n",
        "\n",
@@ -851,6 +1026,32 @@
        "  display: contents;\n",
        "}\n",
        "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 20px auto;\n",
+       "  width: 100%;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 20px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "}\n",
+       "\n",
        ".xr-array-wrap {\n",
        "  grid-column: 1 / -1;\n",
        "  display: grid;\n",
@@ -896,15 +1097,15 @@
        "}\n",
        "\n",
        ".xr-dim-list:before {\n",
-       "  content: '(';\n",
+       "  content: \"(\";\n",
        "}\n",
        "\n",
        ".xr-dim-list:after {\n",
-       "  content: ')';\n",
+       "  content: \")\";\n",
        "}\n",
        "\n",
        ".xr-dim-list li:not(:last-child):after {\n",
-       "  content: ',';\n",
+       "  content: \",\";\n",
        "  padding-right: 5px;\n",
        "}\n",
        "\n",
@@ -921,7 +1122,9 @@
        ".xr-var-item label,\n",
        ".xr-var-item > .xr-var-name span {\n",
        "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
        "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
        "}\n",
        "\n",
        ".xr-var-item > .xr-var-name:hover span {\n",
@@ -932,6 +1135,7 @@
        ".xr-var-list > li:nth-child(odd) > label,\n",
        ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
        "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
        "}\n",
        "\n",
        ".xr-var-name {\n",
@@ -981,8 +1185,15 @@
        ".xr-var-data,\n",
        ".xr-index-data {\n",
        "  display: none;\n",
-       "  background-color: var(--xr-background-color) !important;\n",
-       "  padding-bottom: 5px !important;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
        "}\n",
        "\n",
        ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
@@ -995,6 +1206,12 @@
        "  float: right;\n",
        "}\n",
        "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
        ".xr-index-name div,\n",
@@ -1054,45 +1271,53 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (frequency: 47, direction: 180)&gt; Size: 68kB\n",
-       "array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
-       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
-       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "array([[0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
+       "       [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
+       "       [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
        "       ...,\n",
-       "       [2.21512935e-04, 3.00007246e-04, 3.89537948e-04, ...,\n",
-       "        4.78972678e-05, 9.59294370e-05, 1.53638415e-04],\n",
-       "       [5.05171904e-04, 5.68137407e-04, 6.34119449e-04, ...,\n",
-       "        3.34637188e-04, 3.88407564e-04, 4.45255232e-04],\n",
-       "       [2.26590428e-04, 2.84552135e-04, 3.45964024e-04, ...,\n",
-       "        7.35307830e-05, 1.21080223e-04, 1.72097824e-04]])\n",
+       "       [0.01269176, 0.01718915, 0.02231888, ..., 0.00274431, 0.00549635,\n",
+       "        0.00880283],\n",
+       "       [0.02894422, 0.03255188, 0.03633237, ..., 0.0191733 , 0.02225411,\n",
+       "        0.02551125],\n",
+       "       [0.01298268, 0.01630364, 0.01982228, ..., 0.004213  , 0.00693739,\n",
+       "        0.00986048]], shape=(47, 180))\n",
        "Coordinates:\n",
        "  * frequency  (frequency) float64 376B 0.02 0.0325 0.0375 ... 0.445 0.465 0.485\n",
        "  * direction  (direction) float64 1kB 0.0 2.0 4.0 6.0 ... 354.0 356.0 358.0\n",
        "Attributes:\n",
-       "    units:          m^2/Hz/deg\n",
+       "    units:          m^2/Hz/degree\n",
        "    long_name:      Elevation variance spectrum\n",
        "    standard_name:  spectrum\n",
-       "    description:    *Elevation variance (m^2)* spectrum (/Hz/deg).</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>frequency</span>: 47</li><li><span class='xr-has-index'>direction</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-93cccdeb-4324-42c0-b7ff-0e8989f778ee' class='xr-array-in' type='checkbox' checked><label for='section-93cccdeb-4324-42c0-b7ff-0e8989f778ee' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.0 0.0 0.0 ... 2.943e-05 7.353e-05 0.0001211 0.0001721</span></div><div class='xr-array-data'><pre>array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
-       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
-       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "    description:    *Elevation variance (m^2)* spectrum (/Hz/degree).</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-obj-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>frequency</span>: 47</li><li><span class='xr-has-index'>direction</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e8366115-b53c-411d-a541-f27c68d5ecc3' class='xr-array-in' type='checkbox' checked><label for='section-e8366115-b53c-411d-a541-f27c68d5ecc3' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.0 0.0 0.0 ... -0.0006447 0.001686 0.004213 0.006937 0.00986</span></div><div class='xr-array-data'><pre>array([[0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
+       "       [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
+       "       [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
        "       ...,\n",
-       "       [2.21512935e-04, 3.00007246e-04, 3.89537948e-04, ...,\n",
-       "        4.78972678e-05, 9.59294370e-05, 1.53638415e-04],\n",
-       "       [5.05171904e-04, 5.68137407e-04, 6.34119449e-04, ...,\n",
-       "        3.34637188e-04, 3.88407564e-04, 4.45255232e-04],\n",
-       "       [2.26590428e-04, 2.84552135e-04, 3.45964024e-04, ...,\n",
-       "        7.35307830e-05, 1.21080223e-04, 1.72097824e-04]])</pre></div></div></li><li class='xr-section-item'><input id='section-941b7b31-c0db-4199-a45a-ee03a450b677' class='xr-section-summary-in' type='checkbox'  checked><label for='section-941b7b31-c0db-4199-a45a-ee03a450b677' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02 0.0325 0.0375 ... 0.465 0.485</div><input id='attrs-fb644fc7-7c8b-494e-ac1a-9d6ff4cd9b8d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb644fc7-7c8b-494e-ac1a-9d6ff4cd9b8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c6f6461-9147-47f9-b233-fa073ea29238' class='xr-var-data-in' type='checkbox'><label for='data-5c6f6461-9147-47f9-b233-fa073ea29238' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>frequency</dd><dt><span>standard_name :</span></dt><dd>f</dd></dl></div><div class='xr-var-data'><pre>array([0.02  , 0.0325, 0.0375, 0.0425, 0.0475, 0.0525, 0.0575, 0.0625, 0.0675,\n",
+       "       [0.01269176, 0.01718915, 0.02231888, ..., 0.00274431, 0.00549635,\n",
+       "        0.00880283],\n",
+       "       [0.02894422, 0.03255188, 0.03633237, ..., 0.0191733 , 0.02225411,\n",
+       "        0.02551125],\n",
+       "       [0.01298268, 0.01630364, 0.01982228, ..., 0.004213  , 0.00693739,\n",
+       "        0.00986048]], shape=(47, 180))</pre></div></div></li><li class='xr-section-item'><input id='section-64ee2d6a-6ec4-4f71-a1b4-d7d573421c11' class='xr-section-summary-in' type='checkbox'  checked><label for='section-64ee2d6a-6ec4-4f71-a1b4-d7d573421c11' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02 0.0325 0.0375 ... 0.465 0.485</div><input id='attrs-03018c68-6e9e-4ab5-a71e-fec0312698dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-03018c68-6e9e-4ab5-a71e-fec0312698dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f902533d-6eb2-46d7-9653-db0ec2bbb5d2' class='xr-var-data-in' type='checkbox'><label for='data-f902533d-6eb2-46d7-9653-db0ec2bbb5d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>frequency</dd><dt><span>standard_name :</span></dt><dd>f</dd></dl></div><div class='xr-var-data'><pre>array([0.02  , 0.0325, 0.0375, 0.0425, 0.0475, 0.0525, 0.0575, 0.0625, 0.0675,\n",
        "       0.0725, 0.0775, 0.0825, 0.0875, 0.0925, 0.1   , 0.11  , 0.12  , 0.13  ,\n",
        "       0.14  , 0.15  , 0.16  , 0.17  , 0.18  , 0.19  , 0.2   , 0.21  , 0.22  ,\n",
        "       0.23  , 0.24  , 0.25  , 0.26  , 0.27  , 0.28  , 0.29  , 0.3   , 0.31  ,\n",
        "       0.32  , 0.33  , 0.34  , 0.35  , 0.365 , 0.385 , 0.405 , 0.425 , 0.445 ,\n",
-       "       0.465 , 0.485 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>direction</span></div><div class='xr-var-dims'>(direction)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-bc44332d-cc02-4629-aaa7-411b4c52cc1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc44332d-cc02-4629-aaa7-411b4c52cc1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8d7f712-ec94-409c-8820-6a1bd3bd12d5' class='xr-var-data-in' type='checkbox'><label for='data-f8d7f712-ec94-409c-8820-6a1bd3bd12d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>long_name :</span></dt><dd>wave direction</dd><dt><span>standard_name :</span></dt><dd>direction</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
+       "       0.465 , 0.485 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>direction</span></div><div class='xr-var-dims'>(direction)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-ac269564-9ec0-45f3-a169-f26200eb4f51' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac269564-9ec0-45f3-a169-f26200eb4f51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b84ae8e1-6373-461d-bae4-ab18524bbf2f' class='xr-var-data-in' type='checkbox'><label for='data-b84ae8e1-6373-461d-bae4-ab18524bbf2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>wave direction</dd><dt><span>standard_name :</span></dt><dd>direction</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
        "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
        "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
        "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
@@ -1106,40 +1331,31 @@
        "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
        "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
        "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
-       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-36041b6d-0acb-4ce7-8ceb-ef6debbe4390' class='xr-section-summary-in' type='checkbox'  ><label for='section-36041b6d-0acb-4ce7-8ceb-ef6debbe4390' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>frequency</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7c2fa4e1-9918-44c7-a18e-d54ef083e985' class='xr-index-data-in' type='checkbox'/><label for='index-7c2fa4e1-9918-44c7-a18e-d54ef083e985' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.02, 0.0325, 0.0375, 0.0425, 0.0475, 0.0525, 0.0575, 0.0625, 0.0675,\n",
-       "       0.0725, 0.0775, 0.0825, 0.0875, 0.0925,    0.1,   0.11,   0.12,   0.13,\n",
-       "         0.14,   0.15,   0.16,   0.17,   0.18,   0.19,    0.2,   0.21,   0.22,\n",
-       "         0.23,   0.24,   0.25,   0.26,   0.27,   0.28,   0.29,    0.3,   0.31,\n",
-       "         0.32,   0.33,   0.34,   0.35,  0.365,  0.385,  0.405,  0.425,  0.445,\n",
-       "        0.465,  0.485],\n",
-       "      dtype=&#x27;float64&#x27;, name=&#x27;frequency&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>direction</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cadb9cab-db81-48e5-96b4-c61d50695c25' class='xr-index-data-in' type='checkbox'/><label for='index-cadb9cab-db81-48e5-96b4-c61d50695c25' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,  18.0,\n",
-       "       ...\n",
-       "       340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0, 358.0],\n",
-       "      dtype=&#x27;float64&#x27;, name=&#x27;direction&#x27;, length=180))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5113910b-fbd9-468d-a599-890266222daa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5113910b-fbd9-468d-a599-890266222daa' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m^2/Hz/deg</dd><dt><span>long_name :</span></dt><dd>Elevation variance spectrum</dd><dt><span>standard_name :</span></dt><dd>spectrum</dd><dt><span>description :</span></dt><dd>*Elevation variance (m^2)* spectrum (/Hz/deg).</dd></dl></div></li></ul></div></div>"
+       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9be16afe-ef39-4f66-80ec-eaecda9855d6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9be16afe-ef39-4f66-80ec-eaecda9855d6' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m^2/Hz/degree</dd><dt><span>long_name :</span></dt><dd>Elevation variance spectrum</dd><dt><span>standard_name :</span></dt><dd>spectrum</dd><dt><span>description :</span></dt><dd>*Elevation variance (m^2)* spectrum (/Hz/degree).</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray (frequency: 47, direction: 180)> Size: 68kB\n",
-       "array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
-       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
-       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
-       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
+       "array([[0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
+       "       [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
+       "       [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
+       "        0.        ],\n",
        "       ...,\n",
-       "       [2.21512935e-04, 3.00007246e-04, 3.89537948e-04, ...,\n",
-       "        4.78972678e-05, 9.59294370e-05, 1.53638415e-04],\n",
-       "       [5.05171904e-04, 5.68137407e-04, 6.34119449e-04, ...,\n",
-       "        3.34637188e-04, 3.88407564e-04, 4.45255232e-04],\n",
-       "       [2.26590428e-04, 2.84552135e-04, 3.45964024e-04, ...,\n",
-       "        7.35307830e-05, 1.21080223e-04, 1.72097824e-04]])\n",
+       "       [0.01269176, 0.01718915, 0.02231888, ..., 0.00274431, 0.00549635,\n",
+       "        0.00880283],\n",
+       "       [0.02894422, 0.03255188, 0.03633237, ..., 0.0191733 , 0.02225411,\n",
+       "        0.02551125],\n",
+       "       [0.01298268, 0.01630364, 0.01982228, ..., 0.004213  , 0.00693739,\n",
+       "        0.00986048]], shape=(47, 180))\n",
        "Coordinates:\n",
        "  * frequency  (frequency) float64 376B 0.02 0.0325 0.0375 ... 0.445 0.465 0.485\n",
        "  * direction  (direction) float64 1kB 0.0 2.0 4.0 6.0 ... 354.0 356.0 358.0\n",
        "Attributes:\n",
-       "    units:          m^2/Hz/deg\n",
+       "    units:          m^2/Hz/degree\n",
        "    long_name:      Elevation variance spectrum\n",
        "    standard_name:  spectrum\n",
-       "    description:    *Elevation variance (m^2)* spectrum (/Hz/deg)."
+       "    description:    *Elevation variance (m^2)* spectrum (/Hz/degree)."
       ]
      },
      "execution_count": 4,
@@ -1180,7 +1396,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1198,7 +1414,7 @@
    "metadata": {},
    "source": [
     "We now show a few other ways of plotting this directional spectra. \n",
-    "In the first plot below we set a minimum value of $0.3m^2/Hz$. \n",
+    "In the first plot below we set a minimum value of 0.3 $m^2/Hz$. \n",
     "In the second plot, we plot 3 contour lines with no fill. "
    ]
   },
@@ -1219,7 +1435,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1249,7 +1465,7 @@
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1280,7 +1496,7 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x28112345fd0>]"
+       "[<matplotlib.lines.Line2D at 0x2c438c21b10>]"
       ]
      },
      "execution_count": 8,
@@ -1289,7 +1505,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1299,7 +1515,7 @@
     }
    ],
    "source": [
-    "data[\"swden\"].plot()"
+    "data[\"swden\"].plot(xscale=\"log\")"
    ]
   },
   {
@@ -1319,7 +1535,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1330,7 +1546,7 @@
    ],
    "source": [
     "spread = wave.io.ndbc.create_spread_function(data, directions)\n",
-    "wave.graphics.plot_directional_spectrum(spread, name=\"Spread\", units=\"1\")"
+    "wave.graphics.plot_directional_spectrum(spread, name=\"Spread\", units=\"1\", color_level_min=0.0)"
    ]
   },
   {
@@ -1359,7 +1575,7 @@
     },
     {
      "data": {
-      "image/png": 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8eJD8/Hzi4uI4deoUpaWldOjQQdf7JyUlpco+KSkpoi+QQCC46xAiRSAwEkqlEg8PD7Kysti5cydTp04lICAAd3d39u7dq9suNzeXkydPMnjwYCNaKxAIBK2PmN0jELQyO3fuRKvV0rlzZyIjI/nHP/6BhYUFhw8fxtTUlI8//piPPvqI77//noCAAN566y0uXrzI1atXayTcCgQCQXvGxNgGCAR3Gzk5ObzxxhvEx8fj6OjIjBkzeP/99zE1NQXg1VdfRaVSMX/+fLKzsxk2bBg7duwQAkUgENx1CE+KQCAQCAQCSSJyUgQCgUAgEEgSIVIEAoFAIBBIEiFSBAKBQCAQSBIhUgQCgUAgEEgSIVIEAoFAIBBIEiFSBAKBQCAQSBIhUgQCgUAgEEgSIVIEAoFAIBBIEiFSBAKBQCAQSBIhUgQCgUAgEEgSIVIEAoFAIGhGDh06xOTJk/H09EQmk7Fp06Yq6x977DFkMlmV1/jx46ts4+/vX2Objz76qMo2Fy9eZPjw4VhYWODj48PSpUtr2PL555/TuXNnLC0t8fHxYeHChRQVFTX7ObcUosGgQCAQCATNiEqlolevXsybN4/p06fr3Wb8+PGsWrVK997c3LzGNu+88w5PPfWU7r2NjY3u/7m5uYSFhREaGsqyZcu4dOkS8+bNw97envnz5wOwbt06Xn/9dVauXMmQIUO4ceOGTiB9+umnzXW6LYoQKQKBQCAQNCMTJkxgwoQJdW5jbm6Ou7t7ndvY2NjUus3atWspKSlh5cqVmJmZ0b17d8LDw/n00091IuXYsWMMHTqUWbNmAeXemYcffpiTJ0824qyMgxApAkELUlhYSGpqKrm5ueTn55OXl6f7t/L/8/PzUavVaDQaNBoNZWVlyOXyKi+FQoG1tTU2Nja6f6v/38bGBldXVywtLY196gKBJCgqKqKkpKTJ42i1WmQyWZVl5ubmej0gDeHAgQO4urri4ODAmDFjeO+993BycqqyzUcffcS7776Lr68vs2bNYuHChZiYlN+2jx8/zogRIzAzM9NtP27cOD7++GOysrJwcHBgyJAhrFmzhlOnTjFgwABu3brFn3/+yZw5cxplszEQIkUgaARarZaEhASioqJITEwkKSmJxMRE3SspKYnk5GRyc3ORy+VYWVlhZWWFUqnEysoKS0tL3f8r/jUxMakiSrKzs7G3t9eJl7KyMhITE1GpVBQUFFR5VV6m0Wiws7PDzc0NDw8PPD098fT0xMvLS/c+MDBQFy8XCNorRUVF+PopSUvVNHksa2tr8vPzqyxbvHgxS5YsMXis8ePHM336dAICAoiKimLRokVMmDCB48ePo1AoAHj++efp27cvjo6OHDt2jDfeeIOkpCRdmCY5OZmAgIAq47q5uenWOTg4MGvWLNLT0xk2bBharZaysjL+9re/sWjRokZ8AsZBiBSBoA6ysrK4ceMGN27c4Pr160RERHD9+nWioqIoKirCzc0NV1dXXF1dcXFxwd3dnT59+uDr64u3tzd+fn54eHjoLjwNpbS0lD///JN7770XU1PTBu+nVqtJSkoiJiaGuLg44uPjdQLq/PnzpKenk5qaSkpKCpaWlgQGBtK5c2e6dOlCp06ddC8HBwdDPyqBQHKUlJSQlqrh2CkXrK0bL8jz87UMGZBGXFwctra2uuWN9aI89NBDuv/37NmT4OBgAgMDOXDgAGPHjgXgpZde0m0THByMmZkZCxYs4MMPP2zwcQ8cOMAHH3zAV199xcCBA4mMjOSFF17g3Xff5a233mqU7a2NECkCAeWekVu3bnH27FnOnDnDmTNnuHDhApmZmTg5OeHr64u/vz9BQUHce++99OjRgx49emBlZWVs06ugUCjw9vbG29u7zu1UKhVXrlzh8uXLREREcOXKFbZt20ZsbCwZGRk4OjrSq1cv+vfvT79+/QgJCSEgIEB4XgRtEmtrGTY2TZnMWu6JsbW1rSJSmosOHTrg7OxMZGSkTqRUZ+DAgZSVlRETE0Pnzp1xd3cnJSWlyjYV7yvyWN566y3mzJnDk08+CZQLIpVKxfz58/nnP/+JXC79Cb5CpAjuOrRaLVFRUZw5c4azZ89y+vRpwsPDUalUBAUF0b17d0JDQ1m0aBG9e/fG2dnZ2CY3O0qlkgEDBjBgwIAa69LT0zl37hynTp3i/PnzbNmyhcjISJRKJb1799YJl379+tGhQwchXASCJhIfH09GRgYeHh61bhMeHo5cLsfV1RWAwYMH889//pPS0lKdt3X37t107txZ5wktKCioIUQqvLparbYlTqXZESJF0O7RarXcvHmTAwcOsG/fPg4cOEBGRgYdO3akW7duhIWFsWTJEgYMGCA5z4gxcHZ2JiwsjLCwMN2ygoICTp06xbFjxzh37hzbtm3j5s2bODs7M2rUKMaMGcOoUaMICgoSokVw15Ofn09kZKTufXR0NOHh4Tg6OuLo6Mjbb7/NjBkzcHd3JyoqildffZWgoCDGjRsHlCfFnjx5ktGjR2NjY8Px48dZuHAhs2fP1gmQWbNm8fbbb/PEE0/w2muvcfnyZf773//y2Wef6Y47efJkPv30U/r06aML97z11ltMnjzZ4BC0sZBp24qcEggaiFarJTIysoYoCQ4OZtCgQdxzzz2MHTsWa2tro9g3rv/b9W5jaibnqVeDWb70IqUldSf97Ty9uLlMM4j8/Hx2797Nnj17OHHiBJcuXaohWgIDA4VoERiN3Nxc7OzsuHjVtUnhnrw8DcHdUsnJyWlQuOfAgQOMHj26xvK5c+fy9ddfc99993H+/Hmys7Px9PQkLCyMd999V5f4eu7cOf7+978TERFBcXExAQEBzJkzh5deeqlKPsrFixd55plnOH36NM7Ozjz33HO89tpruvVlZWW8//77/PjjjyQkJODi4sLkyZN5//33sbe3b/Tn0ZoIkSJoFxQVFbF//342b97M1q1bSUtLo2fPngwaNIiwsLAWFSUNER2GYohIMZSWEjUVomX37t060eLm5saUKVOYMmUKo0ePbnSioUDQGIwlUgTNhwj3CNosaWlpbNu2jU2bNrF7925sbW0ZNWoUn376KRMnTmxWUdISQsRY1HUuTREw1tbWTJs2jWnTpgHlN4ht27axefNmHnvsMfLz8wkLC2Pq1KlMnDixXeb6CASC5kV4UgRtisjISH777Tc2btzImTNn6NKlC6Ghodx///0MGTKkWbLVpSBIWtKTYijN4XnRaDQcPXqUX3/9lT179nD9+nUGDBjAfffdx4wZMwgMDGwGSwWCqghPSttHeFIEkic1NZUNGzbw/fffc/HiRQYOHMjUqVP56aefahQzMhQpCBKpo+8zMlS4yOVyhg8fzvDhwwGIiopiw4YNbNmyhTfffJPevXvz6KOP8uCDD+Li4tIsdgsEgraP8KQIJIlKpWLz5s388MMP7N27l+DgYGbMmMG8efPq7XdRG21JkEjJk9JQGutxSU5OZuXKlfzyyy9cuXKFsWPH8uijjzJ16lQx20rQJIQnpe0jRIpAMqjVavbs2cMPP/zApk2bcHd3Z9q0aTz55JN06dKlUWO2JWFSmbYoUirTWMFy7do1li9fzqZNm0hJSWHatGk8+uijjB07ts1MmRRIByFS2j5CpAiMTlJSEitWrOCbb76hqKiISZMmMW/ePIYOHWpwjklbFSXVaesipTqGihaNRsORI0dYuXIl27Ztw8rKivnz5/PEE0802pMmuPsQIqXtI3JSBEZBq9Wyf/9+vvjiC/744w/69evHkiVLmD17tsHTVNuLMGnPVP4bNUSwyOVyRowYwYgRIyguLubHH3/ku+++4+2332by5Mk899xzjBw5UtRgEQjaOUKkCFqV/Px8fvzxR/73v/+RnJzMjBkzOHfuHD169DBoHCFM2i6GChZzc3OefPJJnnzySS5cuMB///tf7rvvPry8vHj++eeZPXs2SqWyJU0WCARGQoR7BK1CYmIin376Kd9++y1eXl48+eSTLFiwwKBaJneTMGlv4Z6GYEhIKD8/n6+//prvvvuO5ORk5s+fz0svvVRn7xPB3YcI97R9hCdF0KJERUXx8ccf88MPPzBo0CB+/vlnwsLCGpxrcjcJk7sdQzws1tbW/OMf/+Dll19m+/btLF26lICAAB577DFeffVVOnTo0NLmCgSCVkCIFEGLcOHCBT744AM2bdpEWFgYBw8eZODAgQ3aVwgTQUMFi1wuZ+LEiUycOJHjx4/z3nvv0bVrV6ZPn86iRYvo2bNna5grEAhaiKaX5xQIKnHkyBEmTJjAoEGDkMlkhIeHs3Xr1gYJlHH93xYCRVCDhn4vBg8ezLZt2zh79iwajYb+/fszceJEjh071gpWCgSClkCIFEGzcOLECUaOHMmECRPw9vYmIiKC9evX07Vr13r3FeJE0BAa+j3p0aMHGzZsICIiAnd3d8LCwhg1ahSnTp1qBSsFAkFzIkSKoElcu3aNqVOnMmbMGLp168atW7dYvnw5fn5+de5XccMR4kRgKA397vj7+7NixQqioqLo3Lkzo0aNYvr06URERLSSpQKBoKkIkSJoFHFxccybN48+ffpgaWnJ1atX+frrr+vtuyKEiaA5acj3yc3NjW+++YYrV65gYmJCr169ePLJJ0lISGglKwUCQWMRIkVgEBkZGbzyyit06tSJxMRETp48yfr16/H3969zPyFOBC1JQ75fAQEB/Pzzz5w8eZLY2FiCgoJ49dVXycrKaiUrBQKBoQiRImgQJSUlfPzxx3To0IGjR4+yY8cOduzYQa9evercT4gTQWvSkO9b79692bVrF9u3b+fgwYMEBASwdOlSSkpKWslKgUDQUIRIEdTLrl276N69O9999x0rV67k+PHjjBw5ss59hDgRGJOGfP9GjRrFyZMnWb58Od988w09e/Zk7969rWShQCBoCEKkCGolNjaW6dOnM2PGDB566CGuXLnCjBkz6txHiBOBlGjI93HmzJlcvXqV+++/n6lTpzJz5kzi4+NbyUKBQFAXQqQIalBcXMwHH3xA165dKS0t5dKlS7z77ruYmZnVuo8QJwIpU9/309zcnPfff59Lly5RUFBAly5d+Pjjj0UISCAwMkKkCKqwa9cuevTowapVq9iwYQNbt26tMylWiBNBW6K+72tAQADbtm1j7dq1LF++nJ49e7Jnz55WtFAgEFRGiBQBUD5r56GHHmLGjBk8/PDDXLlyhUmTJtW6vRAngrZMfd/fqVOncuXKFWbOnMm0adOYNWsWmZmZrWihQCAAIVIEwMaNG+nSpQuJiYlcvHiRd955p97QjkDQHqgvBPTee+8RHh5OfHw8Xbt2ZcuWLa1onUAgECLlLiYjI4OHH36Yxx57jDfffJMDBw4QEBBQ6/bCeyJoj9T3vQ4MDOTAgQO8/vrrzJ49m0ceeUR4VQSCVkKIlLuUzZs307VrVxITEwkPD+eFF15ALtf/dRDiRHA3UNf3XC6Xs3DhQs6dO0dsbCzdunVj69atrWyhQHD3IUTKXUZmZiazZs1izpw5LFq0iP3799frPREI7ibq+s4HBQVx8OBB/vGPf+h+R6JirUDQcgiRchexb98+unXrRnx8POfPn+fFF18U3hOBQA/1eVVefvllzp8/T3R0NN26dePAgQOta6BAcJcgRMpdQFlZGW+99RaTJk3i+eef58CBAwQGBurdVogTgeAOdf0egoKCOHToEM888wz33nsvS5YsQa1Wt7KFAkH7RoiUOjh06BCTJ0/G09MTmUzGpk2bqqxfsmQJXbp0QalU4uDgQGhoKCdPnqyyjb+/PzKZrMrro48+qrLN8uXL8fPzo0+fPjX2byoJCQmMHj2atWvXsnfvXhYtWlSn90QgENSkLq/Km2++ya5du1i9ejVjx44lMTGx1ez66KOPkMlkvPjii7plo0aNqnHN+dvf/lZlvy1bttCpUyc6d+7MH3/80Wr2CgSGIkRKHahUKnr16sWXX36pd32nTp344osvuHTpEkeOHMHf35+wsDDS0tKqbPfOO++QlJSkez333HO6dbGxsSxdupT169fzz3/+k8cff7zZ7P/zzz8JDg7GycmJ8+fPM3jwYL3bCe+JQFA/df1Ohg0bRnh4ODY2NgQHB7Nz584Wt+f06dN88803BAcH11j31FNPVbnmLF26VLeuuLiYZ555hq+++oovvviCp59+WlTWFUgWE2MbIGUmTJjAhAkTal0/a9asKu8//fRTVqxYwcWLFxk7dqxuuY2NDe7u7nrHyM3Nxd7enuDgYNzd3SksLGyy3aWlpSxatIivvvqK999/v8pTVnWEODE+MhnI5DLkuheYWSgAMLdUIJPJ0Gi0aDRatBotWq2RDb7LGdf/bXaeXlxjub29PVu3buXTTz9l+vTpPPfcc7z77ruYmpo2uw35+fk88sgjLF++nPfee6/Geisrq1qvOcXFxSgUCnr37g2AiYkJxcXFddZGauscKOyApaLxt7vCwjIgtfkMEjQYIVKaiZKSEr799lvs7Ozo1atXlXUfffQR7777Lr6+vsyaNYuFCxdiYlL+0ffo0YPg4GDs7OwwMzNj+fLlTbIjLi6O+++/n8zMTA4fPkzfvn1r3VYIlJbD3EKBlbUpShsTlNamWP31UtqYlP9rbYqVtQmmZoo6x3n0ue56l5eWqCnIL0OVX0pBXimq/DIK8kspyC9FlV+KKq/8fXGRyJFoCWoTKgAvvfQSI0aM4KGHHuLgwYP88ssveHt7N+vxn3nmGSZOnEhoaKhekbJ27VrWrFmDu7s7kydP5q233sLKygoAW1tbHn/8cTw8PJDJZLz33nvY2Ng0q30CQXMhREoT+eOPP3jooYcoKCjAw8OD3bt34+zsrFv//PPP07dvXxwdHTl27BhvvPEGSUlJfPrpp7ptVqxYwdKlS7GyssLS0rLRthw7doypU6cyYsQI9u3bh1Kp1LudECdNRy4HBxdLXD0scXK1RGljitKmQoyYYGIip6RY/ZdoKBcMqrxSUhML7oiL/FJKSzSVvCTo/q8wkfHkK8Gs/PQS6jItcrkMmRydt8XUTF5F7FhZm+LsbomVtS3Kv96bmSsoK9OUi5e8sr/ESykZqYWkJhWSlVaIRmPsT7LtUvE70idW+vXrR3h4OHPmzCEkJITNmzczaNCgZjnu+vXrOXfuHKdPn9a7ftasWfj5+eHp6cnFixd57bXXuH79Or///rtum8WLF+tm9wmBIpAyQqQ0kdGjRxMeHk56ejrLly/ngQce4OTJk7i6ugLlT1UVBAcHY2ZmxoIFC/jwww8xNzfXrXNycmqSHStXruTZZ5/l9ddf58033xTJsc2IXC7D0dUCFw9LXN2tcPGwwsnVgrIyLenJBaSnFJIUp9J5MSo8G2WljVcAcrkMAHWZltIS/eNkpRfXOcYdIWOi8+TY2JnSqacjQ++xRK6QkZFSSFpyIWlJBaQlFZKZVoRGI+JJhlCbV8Xa2prffvuNt99+mzFjxvD1118zd+7cJh0rLi6OF154gd27d2NhYaF3m/nz5+v+37NnTzw8PBg7dixRUVFVZvXZ2dk1yRaBoDUQIqWJKJVKgoKCCAoKYtCgQXTs2JEVK1bwxhtv6N1+4MCBlJWVERMTQ+fOnZt8/LKyMl555RVWr17NmjVrmD59eq3bCoFSP3KFDCcXC1w8rHDxsMTF/Y4gSUsuv5GHn0glLamAnCxpJxuWlmjIySwmJ1O/mLFzNNcJr049HBgS6oWJiYyM1CLSkgpI/et8M1OFcKmP2oSKXC7n7bffpkePHjz55JNcvHiRpUuXolDUHearjbNnz5KamloljKtWqzl06BBffPGFLt+kMgMHDgQgMjKy1tIDAoFUESKlmdFoNBQX1/6EGx4ejlwu13lamkJWVhYzZ84kOjqaI0eO0KNHD73bCXFSN66eVvh3ssW3gy1ObhaUlmhI/8u7EH4ildSkAnIlLkgaQ4WAibySrVtm52D2l0CzomN3B4aM9cLEVEZGShGxUbnE3MghNanpyd3tkbrCPzNnzqRjx45Mnz6dy5cvs2HDBuzt7Q0+xtixY7l06VKVZY8//jhdunThtdde0yt+wsPDAfDw8DD4eAKBsREipQ7y8/OJjIzUvY+OjiY8PBxHR0ecnJx4//33mTJlCh4eHqSnp/Pll1+SkJDAzJkzATh+/DgnT55k9OjR2NjYcPz4cRYuXMjs2bNxcHBokm3Xrl1j0qRJeHl5cerUqVrDRUKg1MTERIZ3gA3+nezw72iLXCEjNiqXC6fSSElQtUtB0lByskrIySoh8mq2bpmtgxluXkr8gmyZ/EgQZaUaYm7mEHMzl4ToPMrKhJelMrV5VXr37s2pU6e477776N+/P3/88YfB3lQbG5saDyNKpRInJyd69OhBVFQU69at495778XJyYmLFy+ycOFCRowYoXeqskAgdYRIqYMzZ84wevRo3fuK/JK5c+eybNkyIiIi+P7770lPT8fJyYn+/ftz+PBhuncvn5Fhbm7O+vXrWbJkCcXFxQQEBLBw4cIqeSqNYc+ePcyYMYOHHnqIr776qlbXsRAod7CyNsGvoy0BHe3wDrBBlVdK9I0cdm28TXJcvkggrYPcrBJys0q4eTkLuRw8fK3x72jLsDAvrKxNib+VpxMthaoyY5srCWoTKs7Ozhw4cIAFCxYwcOBANm7cWOUa01TMzMzYs2cPn3/+OSqVCh8fH2bMmMGbb77ZbMcQCFoTmVYrqi60JdavX8+8efN4//33Wbhwod5thDgpx8nVQuctcfGwIiVBRcyNXGJu5tSbdGpsTM3kPPVqMMuXXqw1cVYKODhb4N+pXPy5elmRllRAzI1com/kkJlWZGzzJEFtU5X/85//8NZbb/H999/rvK+C5iU3Nxc7Ozv+d3YQltZNqJOSX8bzISfIycnB1ta2GS0U1IfwpLQh/vvf/7Jo0SJWrFjBww8/rHebu12gOLla0KWXEx262GFhqSDuVh6Xz2YQGxlNYYF4ym9ustKLyEov4vyxVCytyr1V/h1t6TvUlcICNdHXs7kWnnlXC5bavCovv/wybm5uPPbYY6SmpvLMM88YwTqBQNoIkdIG0Gq1LFq0iGXLlrFx40bCwsL0bne3ChQTUzkdu9vTrY8Tjq6WRF3N5uCfcSTE5KNWC0dha1FYUEbEhUwiLmSiUMjw8remY3cH7p/XifSUQq6ezyDyanaTpma3VWoTKrNnz8bFxYUHH3yQ5ORk3nnnHWQymREsFAikiRApEqesrIz58+ezfft29u7dW2sF2btRoLh4WNKtjxMduzuQk1XM1fMZ3LycTUmxqLJqbNRqLbFRecRG5XFkVwIdezgQPMCFYWFe3LycxdXzGaQl312zhGoTKuPGjWPXrl1MnjyZ5ORkvv76a11FaoHgbkf8EiRMQUEBDzzwABERERw+fJigoCC9291NAkWukBHUzZ7g/i7YO5lz80oWm9dEktYGpsWqfPVXANaHmWl5Mb4CHyUlf3kelLGqFrGrpSkuUnP5TDqXz6Tj6mlFtz5O3PdoEFnpxVw8lUbk1ey7pg5LbUJlwIABHDlyhHHjxjFjxgzWr1/fpOrTAkF7QYgUiZKTk8OECRMoKiri6NGjuLm56d3ubhEolkoTuvd1okeIM8XFai6dSuf6pUxJJJUaIj5a4zhSFjOpiQWkJhZwdHcCnYMd6TfcjcFjPbl8Np2r5zLuiryh2oRKx44dOXbsGOPGjeOee+7hzz//FEmagrseIVIkSHZ2NqGhoZibm3Po0CGsra1rbHO3iBNnd0uCB7gQ1M2exNv57NsaS2xUnlFsaS0x0lRqs1NK4qW0RKPzrvgG2hA8wIWQoW7cvJrFxVPpZKRI3zPWFGor/Obu7s7hw4cZN24coaGh7N69W5SvF9zVCJEiMTIzMwkNDcXa2podO3boOpdW5m4QKI4uFgwc7YG3vzXXL2bx8/LrZGe03rThtiJIDKH6OUlFtFTkrjg4m9OzvwvT5wYRF53Pyf2Jkp8q3lT0eVVsbW3Zs2cPYWFhjB07lt27dze5+KNA0FbR34VOYBQyMjIYNWoUdnZ27Nq1664UKNZ2poyZ7Mv98zqRl13Cmi+ucWhHfIsLFJWvssrrbkBq55yVXsyh7fGs+fIa+bklzHyiM6Mn+WBta2ps01oUfb9ppVLJ7t27sbKyYvTo0WRmZhrBMoHA+AiRIhEyMzN15fM/++yzKh2SK2jPAsXCUsHQezyZ9beuyOTw0zcRHNmV0KI5ClK6QUsBqXwehaoyjuxMYP03EShMZDz8dFeGjPXE3LJxTfnaAvp+25aWlvz3v//F0tKSsWPHkpWVZQTLBALjIkSKBKjIQXF0dGTTpk0kJydz7do1KhcDbq8CxcRUTsgwN2Y/2w17R3N+W3WDvZtjyctumf45UrkRSx0pfE652SXs2RTL76tv4uBiwexnuhEy1A0T0/Z52ar8G9dqtVy9epXU1FS2bt2KjY0N99xzDzk5OUa0UCBofdrnr70NkZOTwz333KPLQXFxcWHo0KHExsbqhEp7FChyuYweIc7MfqYrfkG2bNtwi20boslIbf7KpFK44bZljP35ZaQUsm39Lbb/Eo1/J1se+XtXuvd1Qt4Or17j+r+tEyjx8fEMHToUZ2dnduzYgbm5OWFhYeTm5hrbTIGg1RCJs0akqKiISZMmYWZmxo4dO7CwsADKO50OHTqUo0ePsn71ESNb2fx07G7PgFEeqMu0HPwznugbzf90KARJ+yPxdj6/rbpJh852DBztQa9Brpw6kFSlY3N74O3XlzN4jB9Dhw7VzeyzsrJi165djB07lilTprBz5069IWGBoL0hRIqRUKvVPPTQQ2RnZ3PkyJEaSbI2Njas+iycqXPKC7id3J9kDDObFe8AawaP9cTC0oTTh5K5fjGT5mxvKYRJ8yGVmT/6uHU9h+gbOXTp5ciQUE96D3bl+N5EEmLyjW1akxk8xoOOPRxY8Z9zjBs3rso6pVLJjh07GDp0KLNmzeLnn3+utQO6QNBeaIcOU+mj1Wp5+umnuXDhArt27dJbB2Fc/7fJzixm84+RdAl2ZOBoDyNY2jyYmSsYPdmHcTMCuHEpi3VfXSPiQvMJFBHKaR6UsSrdS+potXAtPJO1X10j8koWE2YGMGqiD2bmbfeSViFQNv8YSU5Wid4wr729PTt37uTMmTM8//zziCb2gvZO2/1Ft2GWLFnC5s2b2bFjBx4eNcVH5YtTWxcqvoE2PLSgM0prUzZ8G8GFk2nN1vRPiJPmoa0IE32oy7SEn0hj/bcR2NiZ8dCCLvh0sDG2WQZTXaBUoE+oeHt7s2PHDn7++Wfee++91jRTIGh1RLinlfn666/5/PPP2bVrF507d66xXt9FqUKotKXQj5m5nKH3eNGhiz3H9iRwLbz56jwIYdJ02qooqY38nFK2rouiW18nxs3wJ/JqNkd3J0iibUJ91CZQKtBX8K1r165s2rSJCRMm4O7uzlNPPdVa5goErYoQKa3Ib7/9xssvv8zvv//OwIEDa6yvaxZPWxIqPh1sGD3Jh6z0IjZ8G0F+bmmzjCvEiWG0NyHSEK6eyyAuKo9Rk3x4aEEX9v8RS3y0dHNV6hMoFegTKkOHDmXdunU88MADuLq6MnXq1JY2VyBodUS4p5U4dOgQjz76KMuWLWP8+PE11jdkmrHUQz9m5nJGTfRh3Ax/Th9OZuu6W80iUERYp3FUryh7t3yGeTklbF0bxbmjKYy/P4CR93pjaia9S11DBUoF+q4RkyZN4osvvmDWrFkcOdL+ZgIKBNL75bZDbt26xX333cebb77Jo48+WmO9IXVQpCpUfDrY8NCCLtjYmbH+mwiunW96eOduurG2FneTaLlyLoMN317HzsGchxZ0wTugZqNOY2GoQKlA37Vi3rx5vPHGG0ydOpXbt283p5kCgdER4Z4WJi8vj8mTJzNx4kTeeOONZhlTSqEfU7Py3JOgbvYc25PI1fMZTR6zvd88pUTlz7o9hofyckrYsjaK7n2dGH9/ADevZHFsT6JRc1UaK1Dq4s033+TKlStMmjSJ48eP6+2cLhC0RYQnpQXRaDQ88sgjWFtbs2LFCr3bNLaarBQ8Kl7+1uXeE3sz1n8b0WSBcjc83UuZ9uxhuXIugw3Lr2PnWO5V8fQzzk28OQRKbdeM1atXY2FhwZw5c9BopJ8wLBA0BCFSWpC33nqL8PBwNm/ejJmZWY31TS13b0yh0mugC/c+EMC5oylsXRtFfk7Tck/a442xLdMeBUtedglb1kRx/lgqEx8MIHiAS6sevzk9KPquHebm5mzZsoVTp07x9tvtr5WG4O5EiJQWYsOGDfzvf//j999/x93dvcb65urH09pCRaGQMWaKL70GurD5x0iunBPek/ZOe/sbXT6bzuY1UfQZ7MroST7IFbIWP2ZLhHj0XUM8PDz47bff+M9//sOvv/7aLMcRCIyJECktwNmzZ5k3bx5ff/01/fr1q7G+uRsGtpZQsbI2YeqcIOwdzfl15Q1SkwobPVZ7u/HdDbQn70pqYgG/rryBk6sl980OwlLZcul5LSFQKtB3LRk0aBBffPEFjz32GOHh4c16PIGgtREipZlJSUlhypQpPPPMM8yePbvG+pbqaNzSQsXVw5L753Ui56/jFOSXNXqs9nCTu9tpD2JFlVfKxh9ukptTzMwnOuHsbtnsx2hJgVKBvmvKY489xvz585k8eTJpaWktclxB7Rw6dIjJkyfj6emJTCZj06ZNVdb//vvvhIWF4eTkhEwmqyEmY2JikMlkel+//PKLbrvnn3+ekJAQzM3N6d27dw07lixZoncMpbLt/HaFSGlGNBoNs2bNokePHnz00Uc11reUQKmgpYRKx+72TJ0TxIWTaezdEtvosvbt4cYmqEpb/5uqy7Ts2RTLpdPpTHs0iKBu9s02dmsIlAr0XVs++eQTunTpwuzZs0UibSujUqno1asXX375Za3rhw0bxscff6x3vY+PD0lJSVVeb7/9NtbW1kyYMKHKtvPmzePBBx/UO84rr7xSY5xu3boxc+bMpp1gKyKmIDcjH374ITdv3uT8+fPI5cbRf805PVkmg4GjPOge4szO32KIjcpr9Fht+UYmqJ+Kv29bncZ8/ngqmWlFhN7nh6OrBacOJDdpvNYUKLUhl8v56aef6NWrF//+97957bXXjGLH3ciECRNqiInKzJkzByj3mOhDoVDUyGXcuHEjDzzwQJXp5f/73/8ASEtL4+LFizXGsba2rrL9hQsXuHr1KsuWLWvwuRgb4UlpJg4fPsz777/Pjz/+iJOTU431Le1FqUxzeFRMzeRMmBlAhy52/LbqhhAoggbRlj0rtyNz+X31DTp2c2D8zIBGV6k1lkDRd41xdnbmhx9+4O233+bYsWOtZkt7JTc3t8qruLi4VY579uxZwsPDeeKJJ5o0znfffUenTp0YPnx4M1nW8ghPSjOQnp7Ogw8+yKuvvsrIkSNrrG9NgVJBUzwqtg5m3PtAB1R5Jfy26ibFRepG2dBWb1aCpqPyVbZJr0pWejG/rrxB2Ax/pj/Wke0/R5Ob3XChYWwPir4eP2PHjuWll17iwQcf5MKFCzg6Ora6XcbmWHYQZmU1y0A0lJL8EuAEPj4+VZYvXryYJUuWNM24BrBixQq6du3KkCFDGj1GUVERa9eu5fXXX29Gy1oe4UlpIlqtlrlz59KlSxf+9a9/1VhvDIFSQWM8Kl7+1tw/rxOxUbn88dMtIVDaOS0pJNqqV6W4SM22n6JIiMnn/nmdGlz4zdgCpQJ915x33nmHwMBAHn/8cbTaxuWUCSAuLo6cnBzdq7mqiNdFYWEh69ata7IXZePGjeTl5TF37txmsqx1EJ6UJvLZZ59x/vx5o+ah1IUhHpWAznaETvXl8M4EIi40vvdOW7wxtRYyGSgtFCitTLC2NMHaUoHS0gSFQoZCLkMmA7lchqlJee2OUSHOlJZp0GpBrdFSptaiKixDVagmv7AMVUEZqiI1jb3vVP9bVYiW5vwbtkWvikYDR3YlkJFayMQHA9i96TYxN3Jr3V4qAqU2KvJT+vTpw//93//x/PPPG9ukNomtrS22tratesxff/2VgoICvX3fDOG7775j0qRJuLm5NZNlrYMQKU3g1KlTvPnmm2zcuFHvH96YXpTKNESoBHWzZ/QkH3ZvvE3MzdovxnUhxEm5CHGwNcXd0QJHOzOUlgqsLU1QWpX/a2WhQCaT6YRGxb+lZRo0Wi0aDZSWaShTl4uUCoEil4OJQo61pRwvFwuUliZYWymwsjBBq9VSUFQhWsr/zS8sIzOnlJSMIjIN6ERdVy+fpvx926JQAbgWnklRoZp77vNj39ZYoq7l1NhGigJFX9jHw8ODFStWMHPmTIYOHUpISIiRrBMYwooVK5gyZQouLo2vkBwdHc3+/fvZsmVLM1rWOgiR0kgKCgp4+OGHeeaZZxg3blyN9VIRKBXUJVQ6BzswYrw3O36NIe5W4xJk70aBIpOBo60Zbk7muDma4+5kgaujOTIZpGUVk55dQn5BGSkZxeXCoeAvYVJURn0zQs1M5Qzo7sDRC5mUlNa+sVwOSotywaK0LPfOKC0VWFuZ4O9hhYuDK1otpGQWk5JRREpGMcmZRWTlltbrfakuWCqLjMb8vduqUIm+nsOu328TNt0PhSKeG5ezdOukKFAq0CdUJk6cyN/+9jcefvhhLly4gKVl89eGEUB+fj6RkZG699HR0YSHh+Po6Iivry+ZmZnExsaSmJgIwPXr1wFwd3evMqsnMjKSQ4cO8eeff+o9TmRkJPn5+SQnJ1NYWKirt9KtW7cqrVhWrlyJh4dHnTOOpIpMKwKUjeKFF17g4MGDnDlzBhOTqlpPagKlMvaO5kydE0TExUxO7k+iWx8nhoR6sv2XaBJi8hs15t0iUMzN5AR4WuHpYoGbkwWuDuWCJDWzmJTMYpIzikjNKCY9p6TR4ZcKzEzlvPBwIP/9KapOkVIfchk42Znh5mSBm5M57k7muDiYo9VW2F1EYloR0QkFFDfwOPqEhiHfgbYoVAC8A6wZf38AR3cncC08U9ICpTLVhUpZWRl9+vQhLCyM//znP0ayqnXIzc3Fzs6Oh/bOxsy6aYmz68euIScnp0HhngMHDjB69Ogay+fOncvq1atZvXo1jz/+eI311RNxFy1axJo1a4iJidGbTjBq1CgOHjxYY3l0dDT+/v5Aef0uPz8/Hn30Ud5///16bZcaQqQ0gsOHDzNu3DiOHj1Knz59aqyXskiBO0IlI60QN08l2zbcIjmucTeO9i5Q7G1MCfRWEuSjxMvVkozsEuJSCsu9EpnFZDSDINFHc4kUfch0wqXc++PjZomjnRnxKYVExauIilORnV9/iKg2sdGQ70RbFSoevkomPtiBlAQVDs4WkhcoUFOkQPmU1uHDh7Nnz54mzRiROsYSKYLmQ4R7DESlUjF37lwWLlzYJgUKlId+rp3PIGS4GxEXM4VAqYRMBh7OFgT5KAn0VuJgY0ZsSgE3buez/WgKuarGtwOQClotpGeXkJ5dwpW/6t/YKk0I9FES5K1kZF9nsvJKiIwrFyxJGUV6hVht+SstkXwrFZJiVURfz6FTTwdOH0yWvEAB/WGfkJAQnnvuOebOncvFixdF2EcgWYQnxUCef/55Dh061ObCPJXp2seRIWO9OPBHLMPGeetCP4bQnm5Achl08FYS5GNNoLcVMpmMW/EqIuNUxCQVNLsnoyG0pCelIcf297QiyFtJB28lGo2WWwkqbsaqiE5QoanjimGId6UtelMqQjxHdycwepIvR3Y1bSZca6Iv7NO3b19CQ0P59NNPjWRVyyI8KW0f4UkxgEOHDvHdd99x7NixGgKlrdCppwNDQ73Ytv4WSXEqMlKLDC741l4Eir2NKcEdbekRaEuZWsv12/lsOpBEYpp+z8HdQkmphhu387lxOx+ZDLxcLAjysWbsABcUclcuR+Vy8WYOOXqaTNZWHl+fd6WtJdJWz0EpLIhm4oMBqMs03LySbWzzDMbExIRVq1YxfPhwZsyYwdChQ41tkkBQg7Z5pzUCFWGel156SW+3ybbgRQnsas/ICd78+XM0SX+FeAypo9IexIlcBh39rOnV0Q4vVwui4lT8eSSFmKQCY5smSbRaiE8tIj61iIPn0vHzsKJXRzvmTfUjIbWI8Bs5RMbm1/Cu1CdWKrZpK0JFX5Js4u18dvwaw/j7/VGrtdyKqDk9WUrUFvZ5/vnndWEfKysrI1knEOhHhHsayAsvvKAL8ygUiirr2oJA8e9kyz33+dXaKLD6rJ/qtHWBYmkuJ7ijHX0626HWaLlwI5fLUbkUNLKibktjzHBPQ7CyUNAj0JZeneyQy+H89Rwu3syhqFi/rW1BiNRGfbN4/IJsCZvux66Nt7ndyBpDrcndFPYR4Z62j/CkNIDw8HC++eYbjh07VkOgtAXcva245z4/9myKrbVRYF0elbYsUJzszOjXzZ6uATYkphWx+2QatxJUd3U4pzkoKFJz6koWp69mEeitJKSrPUOCHbkanceZq1lk5lSdHdRWPCbVacg049uRuezdEkvYND+2rI0iJaFteeVMTEz47rvvGDFiBI8//jg9e/Y0tkkCgQ7p1XGXGBqNhqeffppHH32Uvn371lgvdS+Kta0p4+8P4PjeJKJv1O2O1tfrp60KFFulCROGujFnYnlDsDV/xvHz7gSi4oVAaU60WoiMU7FhVwJrt8chAx6d6Mv4IW7YKKs+A7W1Xj6G1EG5FZHDyf1JjL8/AKWNaStZ2Dj0XbMGDBjArFmzePrpp0VvH4GkECKlHn744Qeio6P597//XWOd1AWKiYmMCTMDiL6Rw+Wz6Q3apzFNCaWEpbmc0f2cmTfVDxmwasttdh5PJd2ATraCxpGWVcLO46ms2nIbhRyemOrHqBBnLMyrXmbaglhpTKG2i6fTiY3KZcLMABR/9V6SKvquXZ988gk3btxg7dq1RrBIINCPECl1kJ2dzSuvvMI777yDnZ2dsc0xmDGTfSkt1XB4R4JB+1UIlc59nBjex6mFrGteTE1kDO7pyFPT/HGwNWPtn3H8eTRF7wwUQcuSk1/GtiMprNseh5O9GfOn+TOop4OuaWIFUhUqTakke3B7PGq1htGTfFvIupbD0dGRxYsX8/LLL5OTI+0kYMHdgxApdfDmm28SFBTEk08+WWOd1L0oIUPdcPVSsuPXaDR1FbaohQRrE9bviqdHoK2khYpcDn062/HUNH86eFvx+75Eft+XSJrwnBid1KwSftubyMb9SQR6W/PUNH96d7ZDXkmrSM2r0tRS9xq1lh2/xuDpq6TPENcWsLD50HcNe/rpp/H19WXx4ppVagUCYyBESi2Eh4fz3Xff8dVXX9XomSB1geLfyZY+Q1zZ/vMtigoMn71ScdPIyi2VtFDp4m/NE1P96N3Zjl0nUlm7PZ741CJjmyWoRlxKIWu3x7H7ZCp9u9gzb6ofnf2tq2wjBaHSXL14ClVl/PlzNP2GueHXUdozQapfy+RyOV9++SXLli3j0qVLRrJKILiDECl6qEiWnTNnjt5kWSnj6GJB6NTytvIZjbhhV79ZSFGoWFuZMGOsJ6P7uXD8Yhart8YS2cjS/oLW42asilVbbnPychZj+rkwfYwn1pZ3ZssZU6g0d7PA9ORC9m2N4577/HBwtmgGC1sPkUQrkBJCpOhh3bp1REdH88knn9RYJ2UvioWlgnsfDCD8RGqjCkvVdpNobaFS11TVHoG2PD7Fl4JCNSu33OZyVK6YrdOG0GrhUmQuq7bcpqhYzeNT/OjewUa33hhCpaW6GUddy+biqTTufTAAc0vpli6oK4l2w4YNRrBIILiDECnVKC4uZtGiRbz22mttKllWLodx9weQllTImcMpBu9f382hNYWKPlusLRVMH+PJ8D5ObDucwvZjKRSXSK/ImaBhFJVo+PNoCn8eTWFEX2emjfZA+deNvDXzVFpKoFRw6mAyGalFjJvuj7wNXW0dHR35xz/+wRtvvEFJicjvEhiPNvSzaR2+/vprzMzMeO6552qsk7IXZViYN+bmCvZuiTV434beEFpSqNTlPekeaMPjU/0oKi73ntxKEKGd9kJUfHkIqKRUw7wpfnRrRa9KSwuUCvZuvo2l0oQhoV4tdoymou/a9sILLyCTyVi+fLkRLBIIyhEipRK5ubm8++67/Otf/2pTHY6793WiQ1c7/vzlFmUtXEK9JYSKMlZVp/dkRB9n/jxS/tQtvCftj6ISDduOlHvHRoXU9Kq0BK0lUABKSzT8+XM0HXs40LWPY4seqylUv8aZmZnx5ptvsmTJEvLz841kleBuR4iUSvznP//Bx8eH2bNnG9uUBuPiYcmQUE92/hpDfrVS5A2hMTeB5hQqtQmUrgE2PD6l3HuyasttouKF96S9ExmnYuVfXpXHp/jR5a8ZQM0tVFpToFSQl13Czt9iGHaPF87ulq1yzObgsccew8PDg88++8zYpgjuUoRI+YvU1FT+85//8MEHH7SZKcdyhYwxk305dyxV19XYEJpy8W+qUKkI71S3QSaD0f2cGTvARZezUCS8J3cNRcXlXpWdx1IIHejKqBBnZLLmEyrGECgVJN7OJ/xEGmMn+yKXS7Mirb4pye+99x7//ve/SU9vWNVqgaA5ESLlL959911CQkK49957jW1Kg+k/wh21Wsv5Y82fKNsQGitUavOemJvJuX+sJ/6eVqzZFie8J3cxN+NUrPkzjg5eSqaP8cTctOmXKmMKlArOHklBq4V+w92McvzGMGXKFIKDg3n//feNbYrgLkSIFODWrVssX76cjz/+uMY6qXpRXD0sCR7gwr4tsWiM6GgwVKjUJlAc7UyZc68PZWota7fHk51veOiqLZPvqajyUrmLn2Z2Xilrtseh1cLse30w62Hf6LGkIFAANBote7fG0muQKy4SDfvou+Z9/PHHfP3119y+fdsIFgnuZkzq36T9s3jxYu655x4GDRpkbFMahEIhY8wUX84dSSEzrekF25pKhVB5KMwbgMPnM2psU1t4ByDAy4pJw905H5HDkfCa+7Zl8j2bVh9D5S6nWF1/aMA60fDKwm2BklING/cnMryPE7Mn+LDV2pS0E2kGjSEVgVJBRkoh54+lMGaKL7+suIFGLf1CP0OHDiU0NJQlS5awatUqY5sjuIu46x/XYmJi2LBhA++9916NdVL1ovQf4U5ZqZZzRgrz6KMuj0pdAqV/d3umjPBg94nUNi9QqntDmipQ2sqxWxqtFg6dy2DPqTSmjvSg67iGT+WVmkCp4NzRFDQarWTDPvqufe+88w7r1q0jLi6uzn2//PJL/P39sbCwYODAgZw6darWbVevXo1MJqvysrCoWqF31KhRvPjii3r3tbe3b9D5CNoud71I+fe//83o0aPp1auXsU1pEK6eVvQc4MK+rbGSq7SqT6jUJlAUchn3DnUjpIs963fGExHT9qY4Sl0USN0+Q7kWnceGXfH06+7AiIc6oFDU7WGSqkAB0Ghg35ZYeg10xcVDmmGf6vTt25cRI0borcRdwYYNG3jppZdYvHgx586do1evXowbN47U1NRa97G1tSUpKUn3EiElQWXuapGSkpLCypUrefPNN2usk6IXRfHXbJ6zR5IlEebRR2WhMibQVu9xLczlPDTOCwdbU37cFkdKZnGL29VctOWbflu2vYLkjGJ+3BaLo50ZU2cHYW6h/1ykLFAqyEgtKg/7TPZFXo/gMgb6roFvvvkmy5cvJy1Nf8jt008/5amnnuLxxx+nW7duLFu2DCsrK1auXFnrcWQyGe7u7rqXm1vjvEv+/v41vDJtqWq4QD93tUj5/PPPCQkJYfjw4cY2pUGUh3k0nD9W+1NJbbRmT5Ss3FK2rL5Jl2BH+k71rbLOykLBQ2He5BeoWb8zAVWR9HMp2sPNvTpt+ZxUhWrW74wnT6tlyuxALKyqnkNbECgVnDuagkatpb9Ewz7VGTlyJL169eK///1vjXUlJSWcPXuW0NBQ3TK5XE5oaCjHjx+vdcz8/Hz8/Pzw8fFh6tSpXLlypVG2nT59WueNiY+PZ9CgQQwePLhRYwmkw10rUnJycvjyyy954403aqyTohelIsyzd4v0wjzVUcaqyM4s5qe9CVVDP5blAiUtq5gth5JQa6R7Iq1xEy9wr+P11z2rwK3muuamLYoVtUbLloNJZBSpuW9OEJbK8jkAbUmgwF9hn62xBEs07KPvWvj666/zxRdfkJubW2V5eno6arW6hifEzc2N5ORkveN37tyZlStXsnnzZtasWYNGo2HIkCHEx8dX2e6rr77C2tq6yutvf/tblW1cXFx03pilS5eSlJTEmjVrGnPaAglx187u+eqrrwgMDGTixInGNqVeFAoZY6f4cvZwMlnp0gzzVFA5B0VVadaPmamcAE8r4lML2Xk8VbJCqyVu1s0tLGobz0r/faDBVJx7W5kppNHCH4eTmTDEjfseDSIhOg//TnZtRqBUkJFaxLmj5WGftjDbZ/Lkyfj6+rJs2TJeffXVJo01ePDgKt6OIUOG0LVrV7755hveffdd3fJHHnmEf/7zn1X2/f333/nggw9qjPntt9+yYsUKjh07hrOzc5PsExifu9KTUlhYyKeffsorr7xSY50UvSj9R7pTUqzm/HHphnmUsSq9SbJZuaVsPZxE7052lJRq2HFMmgKlOb0JLe35aOhxG3vstuRZ0Wrhz6MplMqgW19ndv0e06YESgXnj6WgVmvpP6IVvzANRF8V2pdeeon//Oc/FBXdeWhydnZGoVCQklJ11mFKSgru7g07L1NTU/r06UNkZGSV5XZ2dgQFBVV5ubq61th///79PPfcc/zwww8EBwc39BQFEuauFCmrV6/GwcGBhx9+2Nim1IujiwU9+0tzNk8FlTsYVxdFSksF4wa7cf12PkpLk2bvntxUWkKcSImmCJa2IlZG9nXC0sKEWxHZjJ7kqwv9tCV0s30GuODgbFH/DkZmzpw52NjY8P333+uWmZmZERISwt69e3XLNBoNe/fubXBuiFqt5tKlS3h4eBhsU2RkJPfffz+LFi1i+vTpBu8vkCZ3nUjRarV89tln/P3vf28TPXoGjfHg6rkMstINnwHTGl6UugSKlYWCB+7xIjG1iD8OJzd79+Sm0Fw34IaKgGL3UoNeJW5lAJS4ldVY11RbDUUKYqXy96wyI/s60bWDLet3xrPpbDppSQVMeSQQC0vpi6vqZKYVcS08g4GjDb9BtzTVr40KhYIFCxbw+eefo6309PTSSy+xfPlyvv/+e65du8bTTz+NSqXi8ccfB+DRRx+tkgf4zjvvsGvXLm7dusW5c+eYPXs2t2/f5sknnzTIvsLCQiZPnkyfPn2YP38+ycnJJCcn1/DqCNoebe+Ro4ns2bOH9PR05s+fb2xT6sXDR4mnrzX7tl41til6qUugWJjJmRnqRVpWCTuOl18oGlKZtjVoLnFSG00REg2h+vjmyaYG7V/ZdkPyWIyZs6LyVdZoqVBZoGTnlX8mW8IzuC/EhcmzAtmyNoriNjB7rDJnjqQw+5muuHtbkRxfYGxz6uTpp5/mgw8+YP/+/YwZMwaABx98kLS0NP71r3+RnJxM79692bFjhy6ZNjY2tsrDYVZWFk899RTJyck4ODgQEhLCsWPH6Natm0G2pKSkEBERQUREBJ6enjXWX87wQFFo3uhzVRe0nTIJ7Q2ZVivVIELLMHnyZLy8vFi2bFmV5VL0okyf25HYW7mcOSydyrKVqU2kyOXwQKgXRSUathxMovokHgdbUx4K8+ZyVG6rCpWmipPahElDRImDe55BxzLXylmk7ssHinMUy2o2Z8pKtql9XwNFS2MSbo2VXFshVPQJlAps4lWMvz8AEzM5f6yLMmpvq8bQf6Q7Xn7WbPohsv6NW5GdpxfXWPbkk0+Snp7Opk2bWt+gBpCbm4udnR09fv4HCqumiZTLD/ybnJwcbG1tm9FCQX3cVZ6UmJgYdu7c2eh5+K2JfydbbB3MCDewT0lrUZcXZWx/F8zM5Py2L7GGQIHW96i0hDipS5joEyS9XBINOqaJxgRSoIdzMmXyMt3yC2metR6jQrhUtq0hgqXi/NqKVyU0yJaOvtb8pEegAOR5K9m18TbTH+vIkHu8OLIzodVtbArhx1Pp0dcZvyBbbkfm1r9DKzGu/9s1hMorr7xCcHAwt2/fxs/Pz0iWCdozd5VIWbZsGcOHD6djx47GNqVOZDIYNNqDM0dSKCs1/DGwpb0odQmU3p3s6OhrzY9/xlFaVruTrrWESlMESkPFSXXBoE+QDLe/Uf8BNQpkWhPQypGpy5/6hlrHo1UUcyQ3AI1Mo3dsfcKlMYKlwN1wr0q+p6JVhUq/+3zp6GvN5h8jKc0qgVq+62WlGrb/HM398zqRmVrEVSOFFhtDaYmGs0dTGDTaQ1IiRR9dunRh6NChfPvtt7z//vvGNkfQDrlrREpJSQkrVqzgq6++qrFOaqGeTj0dUZjIuXpOehfWugSKj5slI0Oc+XVvAnmqsuq71qClhUpjBUp1cVKfMKkuHPQJkrGWkZSUOFFY4EtJsTNlpbaUltpRWmpH2V//ajQ1i3k5RZXnTt0HaOTFaEzy0ZioSNHIKVQUUSQvxtO6gGzTHAoUBVxIr1+w1CVWpCxUKkI8P+2MLxcoUCNPpQKVrxJiVez4LZpJD3UgK6OIpFqSb6XI5bPpBA9woVMPB25czjK2OTr0eVPmz5/Piy++yJIlSzA1NSzUKBDUx10jUjZt2oSFhYXkp6YpFDIGjHTnxL5ENI2oyNoYL0ptF3p929V2HDtrE6aM9GDf6TQSUhtecK4lhEpLiZPahEl1UVIuSJwpLPClQOVLYYEfVwp8UastsLBMxNw8DVPTbCwsE7CxvcYljRUaExUakwKQlaKVaZFpTHC++SzpQV+CvIyT2Z0x15hjobHAQm2BhcYcS7UFTqUO+BZ6Y1tmQ6msjKGmOWSbZpNtms2xPHOyKdHZbYhYMZSWDv/UyEH5K5EW6u6ynRSr4ujuRMbPCODXlTfIy2kbNVQ0ai2nDyYxYJQ7kdeyJV3g7YEHHuCVV15hy5YtzJgxw9jmCNoZd41I+eqrr5g1axYKRdUbmNS8KD36OVNcqObmlexWOV5tUzsN2c7URMa00Z5ci87lUiPc080pVBojUBoqTmoTJqFWkWg0JqjyO5KT3Ytr2fMoK7PFwjIBS6tY7BzO4eG1CQvLBPYV+dc4/uHsTlBmDjjqlploTJgCHMsLKM9JUZRQrCghF/0JuHKtHLtSW+xL7bAvtadzfkdC1LbkU8p1WTYRshxuu+WhlmnrFSuN8aZU0BJelbqSZCtTXWxXzAi6ej4DJ1cLJjwQwO+rbzYqhGoMblzOovdgV7r3deLS6fRat4tNPUVM8lFKSvOxtnKnq88E7Ky96x0/KfMSl279hot9Z/oE3akZdTpiFTZW7nTxnVBl+4T081yP28G4/lWTaBUKBQ899BBff/21ECkCSkpKyM/Px9HRscpytVpNfn6+wU0f7wqRcuvWLY4ePSr5Pg5m5nJChrqxZ3PjWpW3VC5KdYFS/TgTh7mjKlSz/0ztF9L6aA6h0lSBUp84qS5MysqU5Ob0ICZpNHm53VAoCrG1v4S33xqsbW4gl5expyDorz1Moci/XJDooSKvpAJzrZwpwOV0d72ze2qnFEgD0jBRyPDX2tBFa899Gn/MURApy+G6azan09QUaDW685aiUFHGquh3n2+tAkVVyZtSeR99v4OjuxOYNCuQ0Km+7Pg1psm2tQZaLZzYn8ToST5EXMiktKTm9yA58zLX43bSzW8Sdkovbqec4OzNNQzt8Szmpta1jl1YnMWNuF3YW/vWuo0hPPfcc3Ts2FEk0Ap4++23OXHiRJWifhs3bmTu3Lnk5+czbNgwfv/99wa3LLgrRMratWsZMmQI3t71P10Yk96DXclIKyI2yrDpqo2lPi+KvvXVbwBDezvibG/Gmj/jmlwRtylCxVCBUpf3pDZxEmoViVYrIz+vCzFR88nNCcbCMgFbu4u4euzA0jIOmYxyYfKXx0SfKKkuSCpT4eWwkMnBCbJTbSjSNv7JPw0tke6xoI3FAys6a+wZrHFjqpMll4rzOVaUw43SAr1eFWMLlcFjPOqcxQP1C5WK9RoN7PwthvvndaL/CHdOH2pio6NW4vbNXHIyi+k9yFWvzTEpx/F27ouXcx8AuvlNIj3nJonp5wnw0N/dXavVcOnW7wR6jiY7/zalasP7gQH4+/tz+/adByo/Pz/8/f25y6paCKqxa9cuXnzxRd37kpISnnrqKZ566inuu+8+XnvtNd566y2+/vrrBo3X7kWKVqvlxx9/ZOHChTXWSSnUY6k0odcAF7asjWrU/s3lRWlo+AcgwMuKkC72rNkeR5Gep7zG0Bih0hSB0lBxUlZmRWryPWSkjUSjMcXR+Tidvd7G3KJ8iviegiAoLPeaVBcm+kRJXXVO6qOuXBJ9Sb4Vx8oCrpIH5OEiN2WQhR1zbDwo0Wo4XJTNiaIcCqt5VRozPbmCpgiVkX2dCOpgy+ZVNyjNKkGJYd9xfXkqxYVqtv8czfTHOpIcryLuVus8DDSV43uTmPRwBy6fSaew4E5CukZTRp4qkQ7uw3TLZDI5jrYdyFbF6xsKgKjEg5iZKvF26Ut2fuO8tuP6v83p06dRq8v/vmq1mkceeYSsrCy0Wi0ymaxR4wraPlFRUVX6Jh0+fJiCggI+/PBDzMzM+Oijj5gzZ06Dx2v3IuXcuXMkJibyyCOPGNuUOuk33I24W3mkJLROlUl9T5/1UfmCb24mZ9xgN/adSSczp3krrBoiVAwRKPV5T/SJk5JiR+JjHyYrYxCWVrF4eP+OnX04MpmmXJgUlMdXKwuT1hQlhm5bcc5pmlK2FqSzrSCdYDNrRlo6cK+VM6eKctjjmUlBYvPcZBojVKrkoNiYomzATJ7avr/Vl2emFXFsTyKjJ/mw/psISoqln5+SHK8i4XY+IcPcOLLrTs2XkrICtGgxqxbWMTdRoirSH3rNyrtNQvo5Bnf7W53HjEs7TUL6uSrLtFoNcvmdW4aLi4vu/y+88ALx8fGUlpZy8eJFevXq1eDzE7QvSktLsbG5c707ceIEffv2xczMDICAgACD2hW0e5Hy448/MmbMmBpVAqXmRena24lfvmtALQ09GOpFMcRbUtsxxvR3IS2zmMstVMehIUKlsQKlNu9JVc+JkoS4mWSkDcfOIZzAzp9gZRUHUCnPpOXEiVmKCTiV/1tM87nP9YmYcPd8wkvy8VGYM8bKkX86BHDUMpsDMbkUqMtv4q0V+qkvSbYxQqU6V89nENjVjqH3eLH/j7gG7WNsTh1IYsbjnThzOJmiwsZ5p8rUxVyK3kg3/ymYmdZ9zfBwDKZDtXBRStY1opMP695XTEf+9ttvWbFiBceOHeONN97gxx9/FCLlLsbHx4fTp0/j7+8PwPbt2xk5cqRufUpKCg4ODg0er12LlLKyMn766Se++OILY5tSJ937OpF4O5+s9MbFhlubQG8lQT5KVm2JbdHj1CVUmipQ9IV2Qq0iUavNSUm6l9Tke1Da3KRjl4+xtCp/eq0QJ/UJEzBcnNQQD83c+rOywKjuUao4dioa1pPOIYtcxrs58nonew6mZ3MoPYdSrbbFhUptAqW6AKlrynFD2f9HHA8t6ELUtexWywFrChmpRSTHq+jW14lzR1MBMDOxQoaMktL8KtsWl6n0Js0WFGdSVJJN+M11umXavwTw7jNvM7THc1hZlM/IMFGYY2VRtRGoPmGzf/9+nnvuOX766SeCg4OZPXs2L7/8Mh9//HGNmZSCu4MHHniA559/nri4OK5du8bJkyer5J/s3buX3r17N3i8di1S9u3bh0ajYdq0acY2pVbkChnd+zqz/4/G3fBb24tibiYnbJAr+0+nk19Qf8G2pqJPqDSnQKnwnoy1vEV66ihSku7FzDyNgKAvsbaJ/Cuk0zBxYogwac4aJdWpT0hUX19dtCQWlbDydjIdrCy4192RoY627E7L5mRmbosJlfo8KA2ZyWOINyU/t5SjexIYNdGH9d9cp6RY+o0IL5xKY+QEb8KPp6LRgFxugo3Sk4y8aFwdugLlIZnM3Fv4ug6osb/SwpnB3Z+usiwyYR9qdQmdfcdjYWZYT5qCogzuv/9+Fi1apKs/NWPGDJ599lkOHjyoazoouLt44403SExM5KOPPkKpVLJixQp69uypW9+9e3dGjBjR4PHatUj58ccfmThxIiYmVU9TSqGeoG72lJSoW+VprjnCPGP7u5CSWczlqNYr111ZqJRYy9gb1bAKnBU337pyT0KtIiks9ORmxGtoNGZ4+63B1u7inVk63BEnTfGa1CVK9N30zRVAN7BKAUUL3z9rEy23Cor44lYi3W2suNfdkX721mxISCOf5s1BamgdFH00tBChPq6dzySwiz1D7/FsE2Gf2zdzUd+jpUNXeyL/qqPk7zaYy9EbsbXyxE7pRWzKCdSaUjz/mu1zKfp3LExt6egdikJuio2lW5UxTRUWADWW14daU8r5yJ8wN7Vj/vz5JCff+RJNmDCBNWvWCJFyl2Jubs63337Lt99+q3f9pEmTDBqv3YqUwsJCNm7cyLZt24xtSp0E93fh0qnG1RdpjU7HlQn0VhLoo2RVI+u4NIWs3FJWhifxWIgHQJ1CxRDvSUrSeFKS7sXFbS9uHtuq1DZpqjjRJ0wa64VoTarbeIUCrucXEubqwAuBXuy2yeLMlRy9zSPro7o3xRCBUpunRN+U44ZyYFscD85vO2GfS6fTCO7vohMp7o49KClTEZW4n+LSfGys3OnbcbYu3FNUnIOM5p9pU1Kaj6ooHVVROp6eVX8fe/bsYdq0aXz11VdYWFg0+7EFdxftVqTs3bsXBwcHhg/XXytACrh7K7FzNCfiYmaLH6upXhSLv8I8+06nkd/IxL2mkO+pIL+glNVn6xYqDRUow2Qqbka8ikZjTlDnT7FSxjQ456QucVJdmNQlSurK0TAzLU9KUSZrMDWwQmpTuz5Xp/wctBxIyiTSVsV93V3o1U/JxitppBcY7lWpECpN8aBUp7EelfzcUo61obDPtQuZDBjlgaunFamJ5TMBfV0H4us6UO/2/bs8Xud4PQJqhsJr28fLuY+uHouluQNh/ZYA1Ojlo9FoUCqVHDhwgPHjx9d5fEH7QKFQNLg+jkZj2PWs3YqUzZs3M2rUKOTyqhmIUgr1BPd35lp4hiQ7HVdnzF9hnitGftrMqEOo1CZQKod3xlpGkZZyDzcSJ+Hsug93zz/KS9U3wHtSmzhpiDBpzU7BtR2rOcRLfG4xy04mMKaDAwsGerE/KotjsTkGjzN4hAtdXa0NFiiGTDduKNfCMwnsas/QME/2b5V22Ke0REPEhUyCBzizZ1PLJq43lOpNB+VyOaNGjWLz5s1CpNwlbNy4Uff/xMREFi9ezMyZMxk0aBBQPg35559/5p133jF47HYpUjQaDVu3btXb8VgqWFqZENDZjvXfRLT4sZrqRfFytSDIR8lKI4R5oObNVZ9QaYhAGW0ey+1bT1JY4Edgp89QWkc3KLTTWHHSmsKkIVS3pzbRos/uytuWabTsiszkapqKmT1c8bQ1Z/PVNEr/iv9U3l/fMe4JciTY3Zr125vuQWkuDmyL4+G/deHa+QyS41unVlFjuXw2nQee6oyFZUKjpyO3NNOmTWPhwoV89dVXorDbXcCUKVN0/x83bhwfffQRjz9+xyM3e/ZsQkJC+OWXX/jb3+qu0VOdZp7oKA3Onj2LSqVi4sSJxjalVjoHO5AUryInS/pdWUf2deb01WyjhXn0USFUenvaMDbwzpz72gTKCEUmkdf/QVmZDR27fshxuYI9BUEczu5ksEAxTzbVCRSr5DsvKL9BV7ykTmVb67Nb37r4nGK+PZWArbmCef08sTWv+beqvl+FQFl1NpF4m8YVUmsJL2J+binhJ9MYNKb2lgVSITujmNTEAjr1dKx/YyMxadIkcnJyCA8PN7Ypglbm8OHDDBs2rMby4cOHc+DAAYPHa5ciZfPmzQwdOhRzc/Mqy6UU6unax4mrjez225jy4I0dP8hHib2NKWeuNmxGTWtSIVR6edsw3s2hVoEySKPlZsTrKJW3COz0OQdKyj0wlcVJdYGSlWxTQ6DoEyfQtoRJU6l+rqpSDd+fSyIpr5j5A7zwsTOvdb+J7vY6gZJZWD59vbnzZ5pC+PFUHJws8AuqeypubOopDl38jD1n3+XEteXk5Ndegj4l6yonrn7DvvMfsufc+xy/8jWJGReqbHM6YhURsdtr7JuQfp595z/UO+7V8xl06+Okd50xqH5ttbKyYvDgwWzevNlIFgmMhYeHh95mvj/88AMeHh4Gj9cuwz2bN29mwYIFxjajVjx9lVhamhAdYXgsvzWRyWB4HyeOX8yktKz1m4Y15AYWZ1vKN9FJLAj0QF2s4ahNdBWB0qfAjei4B/Dw/o1wZSIRhR2A2sM7tXlOKqgc0mkNUWIVp8K0AX2RWjtHCaqe/76EFJIHOPBoXw/2lqbVqESsS5LdHk9JXilISJxUUFqi4ezRFAaN9iA2Kldvw0xDuw6bKiwJ8BiB0sIZuUxBWs4NrkRvwsxEibNdUM0DNJCoa9kMC/PC3VtJcnzjcnFamokTJ7J69WqWLFlibFMErcjSpUt56KGH2L17ty4n5fjx45w5c4b169cbPF67Eym3b98mIiKCmTNnGtuUWunWx4nrlzJRqw2/8bemF6VbBxtMFDIu3Gx9MdUQgVKRh5JWUsr/5cbyvIM3fha2XNEmMtzhBj1zOpKUMpaAoC85oSi/0TcmtAMtJ05q+xuZmhnm5GxIx+qW5uqpLPJji5gy0gOlhYKTl8u9b/pm8VgnqnV/4+bomNxcXD6bTvAAFzr2cODGpZreQ0O7DjvaBlR572cxiMSMcLLzYw0WKYcufkZRyZ3fonfPp7D3tSQ5XpphnwcffJBXXnmF+Ph4yXegFzQfM2bM4NKlS3zxxRdcuFDuNQwJCWH16tV07tzZ4PHanUj5448/6N27N25uhhUnai3MLRR06GLPLyuuG9uUOlHIZQzr7cShcxkYOGOsVaieKFvqkscJh2iGZwzFxzwT/ywT0tOHEdj5U45qrYCme0+a40ba2BkozXGs1hAtscmFbNgVzwP3eGGikGGikNU6zbiyUJEKGrWW0weTGDDSg8ir2WgqPUg0tutwBVqtlsy8aFRFGXTy8jPYtkFd56NFoxvr+OEjvPX2K9w6K82p0x4eHgQHB/PHH38YnCwpaNt06dKl2drRtDuRsnXrVu65554ay6WSjxLUzZ70lEKy0otb9DhN9aL06WxHUbGGa9GtP+W4vhtXdYFSUQcl30RFod9anG4/QjoQ1OVDjmrLBUhjBEpziZPWFCZ10VqiJS2rhPU7E5h9rw9a4Ic/YmudxdOYz7alP88bl7PoPdiVHn2duHj6TqHFxnQdBigtK+LQxf+g0aqRIaOr30Sc7AKrbNOQrsOVe+dExG4nNfs6WWnFBHa141p4y9daqo/qU5EBQkND2bp1qxApdxmFhYWsXbuWc+fOYW1tTXBwMA899FCN6u8NoV2JlNLSUo4cOcKbb75pbFNqxb+THbcishu1b2u5781M5QwKdmTbYWmXR61c7r6iUJt52lDk8lJKtHLCUyZw2DQVZI0TJ9B4gSIVYVIXlW1s7u9Wj0AbSso0yGUyugbYcLwVChY2F1otnNifxJhJvly7kElpA3KC6sJEYcbgbn+jTFNCZm401+N2YmnmUCUU1JCuwxXEp50hIf0cA7o8QfSNPPw7SUOk6OPee+9l2bJlqNVq0XDwLiE1NZURI0aQnp5Ox44dOXPmDB07duTDDz9k586dBof+2tXsnnPnzmFiYsLgwYONbYpeTEzlePtbE32jZfveNNWLMqC7A2lZxUQntn69iIZ6UarP5BlufwPL9AFYZvUizfdXcvzWI8vqTfe8LlxIbZz3pLFP+W1BoFSnwu7msL0iB+WnHfFs2BVP3y72DOje8Nbs9dEaYv32zVyyM4voPchVt8zQrsMVyGRyrCycsLXywN99CG4O3YhOPlJlm4quw5Vf+roOZ+ZGcy12Oz0CpmFj5U7MjRx8AmwwMZFmLZJhw4ah1WrFVOS7iNdeew0vLy9iYmJYt24dFhYWXL16laFDh/Lyyy8bPF67EikHDhwgJCSkhmKXSqjHp4MNudkl5GS2bKinKViYywnpas+hc42bHt1c6JvWW71bb+WpxuY5XbDKGEC27y+ozTM4UOjCYaejeKj8GavxAm3DphVXHNsQmvMGLwUqn4+h5xQaZFslByU9u4Rf9iQwqKcDnf1rv5FLkeN7k+g10AVzi/LrSeWuwxVUdB22Vzb86VCr1aLRGN5BvKAogwtRP9PBYzhuDt0AyEovRpVXildAwztwtyTVr7UmJib07duX/fv3G8kiQWvz559/8vbbb2NtbV2lVP6LL77Irl27DB6vXYmUvXv3MnToUGObUSv+nWyJudk4L0pLPj1WHrtXRzuS0otISi9qsePVRXVhos+zUjkPBWC0eQ42SWHkeW1DbZGmyz85mmXHasV1emudGJoXUGOc2mqeGEJ7ESZ10dBzDA2ypWMPB7asukHplWydyFGFZ7LtSArjB7vh6qi/joqhtIY3JTleRXpKIV0r1SPxdxtMQtpZEtLDyS9M49rtbTW6Dt+M36Pb/lbSYTJyoigoziS/MI2Y5GMkZV7EwynYIFsqug7bWLnj7RxCcWme7hVzM4eATnbNc9ItwNChQ9m3b5+xzRC0Enl5eXpDOgqFokabmobQbnJSSktLOXbsGIsXL65/YyMgk4F/kB07fo2uf+Mm0JSbplxWnjC751RaM1rUPFQP80B5HspIZQK2MbNRuRyjxDq6RoJshqyY/2XF85ytLwB/FJQnODaH9+Ruoq78FWWsisFjPOjYw4HNP0bqraKcfCyVs8CMEe78suIG6U5NFyuGdjxuDBdPpTH0Hi8unEhFqzW867BaU8K12G0UleQil5ugtHCmZ8B03B17GGRH5a7DBy/+p8q6gKBPCJtm+Gyh1mLcuHF88cUXlJWVNSpxUtC2qAj1+Pv765aVlJTw3nvvNarhb7v5xpw9exYTExNd8Rip4eZlBTIkW3gJoKOfNWoNREnExtryUyrCPHKtHNv4qZQqYyl0PFNDoNwJ7ZTXUakQKrtvldeaaIxAudvEiT6qfwb1CZQKzh9LxcnVkvH3+7N5TRQatdYoRegMIfp6DkPv8SKgsx23/iq+aEjX4Y5eY+noNbbOYxjadbg6yXH5yBWyKp2RpcTQoUN1eSn9+vUztjmCFmbs2LFs3LiRUaNGAeUzfRwcHPD19WXHjh0Gj9duwj1Sz0fx72hHbKT+Kpb10dALeVMTZkO62HMuIrtRNjY3lQVKZS+KLsyjhfGF/oCMPPddHM6pTaCUk6ouFyoDTe0Y7+YgBEoz0VCBUsH+P2JRKOSMnFDuDpb6Z6rVwqXTaQQPcDG2KbWi0UBsVB7+neou599a1JaX0pi+LYK2xyeffMJrr70GgIuLC19++SWbN2/m0qVL+PkZ7vFrNyJF+vkodkTfkG4ZfDdHc1wczLkU2bIzjxpL9TDPPZhjqvIn13sTh3PLa07UJlAqyEmAb6KT6G9b3pSwoQKlPSXFNieGChQAdZmW7b9E4xdkS+fg8kqpTfl8W8MTcy08Exd3S5xcLVr8WI0l5kYOAR1FXorA+FhbW+PpWX4tlslkTJ8+ndDQ0EaH+tqFSNFoNJw4cYLQ0FBjm6IXWwcz7BzMiLvV+oXRGkpwRzuuRedRUmr88rL6vChwJ8xjqbZEmTqKfI+dHFR5AfULlIocFFVseVPCvm42DG9AgzYhTvTTGIFSgSqvlP1/xDEszAulzZ3KvlL9rIuL1ERezZZUQ7/qxEblYe9sgY2dmbFN0UtoaCjHjh2rMtujPePv749MJqvxeuaZZwCIiopi2rRpuLi4YGtrywMPPEBKSopu/5iYGJ544gkCAgKwtLQkMDCQxYsXU1JSUmUbfcc4ceJEq59vdX744Qc6dOiAra0tbm5ueHt78/XXXzdqrHYhUm7evElJSQkDB+qPExsb/452JNzOb3JRqLpoSqjH1ERG1wBrLhqhR09DqOxFQQt9s3sRa57M3rLyG1xDBUpFiKc4soj1u+LpEWhbp1CR6k3T2DRFoFRwOzKX6Bs5jJroU2V5U0OWLcXV8xl06uko2XokJcVqkmLz8e8ojZBPdQYNGoRKpeLWrVvGNqVVOH36NElJSbrX7t27AZg5cyYqlYqwsDBkMhn79u3j6NGjlJSUMHnyZDR/9SCJiIhAo9HwzTffcOXKFT777DOWLVvGokWLahxrz549VY4VEhLSqudaneXLl/P0008ze/Zs9u/fz/79+3niiSd4+eWXWblypcHjtYvE2bNnz9KxY0fMzZtnemNz49/JllvXGicAWuMC3MXfhpz8MpIzjF+/pT4vin+BHzZlNpx0OAMYLlAqQjxZuaWs3xXPQ2HluRGHz9+pCyPESe00h0Cp4OiuBB6c35kuvRyJuFB3xdSkqKMk3DxISVEeSjsPOvS6DxtHX73bxqedJTHjAvmFqQDYWnnQ0WssdtZ3pkWejliFjZU7XXwnVNk3If081+N2MKbPG1WWpyQUkJ9bQmA3e65frNl4UArE3MjBv5Mtl87UXqLfWFhZWREUFMTZs2cJDAysf4c2jotL1Rymjz76iMDAQEaOHMnu3buJiYnh/Pnz2NqWi8rvv/8eBwcH9u3bR2hoKOPHj2f8+PG6/Tt06MD169f5+uuv+eSTT6qM7eTkhLt7tSJSRuSzzz7jo48+4rnnntMtGzlyJC4uLnz66afMmzfPoPHahSfl7NmzdOvWrcZyKSTNmlso8PCxJiay5bwUTb2pBne0bRNeFMsyS3rmduOcfThl8rJGC5QKKoRKZY+KECi105wCBcrDKAe2xTH0Hi+sbWsP+6TFhxN9aSs+Xe6h95gXUdp5cuXod5QU5VcfEoDMvBjcHXvQr/NcBnZ5AgszO87e/JGikqblW107nyHpkE/MzVw8/awxMzf+ZV3ftbdbt26cPXvWCNY0H7m5uVVexcX1P9iVlJSwZs0a5s2bh0wmo7i4GJlMVuWh2sLCArlczpEjR2odJycnB0fHmh2vp0yZgqurK8OGDWPLli2NO7Fm5NatW0yYMKHG8vHjxxMZGWnweMb/NjcDp0+fNrqLqzZ8A23ISisiP0d/gzVjUeGhcbAxxdXRnKsSyJepy4uCFvrm9CbBIpFU87QmC5QKKguVMYHSdJVLgeYWKBXERuVx63o2I++tPeyTePMQbv4DcfPvj5WtG4F9pqNQmJJ6+5Rum8oex+AOM/B1HYCtlQdKSxe6+08p70Cca3io4dDFz9h1Zgm7zixh2Y+v4+xuzsX4ZY0405YnN7uE7IxifDpI83vcp08fTp8+bZRjZ6dY6ypON+aVnVJeB8fHxwc7Ozvd68MPP6z32Js2bSI7O5vHHnsMKA99KZVKXnvtNQoKClCpVLzyyiuo1WqSkpL0jhEZGcn//d//sWDBAt0ya2tr/vOf//DLL7+wbds2hg0bxn333Wd0oeLs7Exubs0HgpycHJycDBf5bV6kaDQawsPDJduvx8vfhthb0pwxAxDko+R2UiHFEkiYrU5lL8p4Ww12ZbZctL1So1lgdSoESkPJyi1ly+qbdAl2ZOBoj0bZ2p5pKYFSwdFdibh6WOEXVPXmqoxVodGUkZ+dgL1rR91ymUyOnWtH8jJvN2h8taYUrVaDqYmlwbYN6jqfkb1eZmSvl+nbYT4R1yIZMTTM4HFai7ioPLwl2n5g8ODBnDt3rk0nz8bFxZGTk6N7vfHGG/Xus2LFCiZMmKCb8eLi4sIvv/zC1q1bsba2xs7OjuzsbPr27au3ImtCQgLjx49n5syZPPXUU7rlzs7OvPTSSwwcOJD+/fvz0UcfMXv2bP7973833wk3gvvvv59jx47VWH706FFmzJhh8HhtPiclKiqKoqIiBgwYYGxT9OLiYcnZIyn1b6iHhuSjNDU8EehjzbVo43tRKlPdiyLTQve8LkRYX+dsxp2Gb7V5USpoaC0UZayKbGDzj5FMnRMEwMn9+p9o7jZaWqBAedLn2SPJDBrtQWxU1VpCprfSQKvB1LzqjdfM3JqcvNQGjX8jfjfmZjY42naosjwu7TQJ6eeqLNNqNcjldy6LlZv8RcRu58xpb0JHT2br7ZgGnl3rkppUUKUpopSoSJ6NiYkhIKBmm4q2gK2trS6PpCHcvn2bPXv28Pvvv1dZHhYWRlRUFOnp6ZiYmGBvb4+7uzsdOlT9jiYmJjJ69GiGDBnCt99+W+/xBg4cqEvSNRaff/653uXPP/98o8Zr856UiqRZCwvp1TBQKGQ4uliSllxobFOqUCF+LMzleLlYSKLCbF3djydbK5BrFURb3XlybmqYp4LKIi87s5jNP0YKj8pftIZAqeDK75cwlWvp2KPx3ZL1ifropMMkZ16md+CDKORVPWwejsEM7va3Kq9Az9F6x45PO0NC+jmKMnzw9LPTNR2UGmlJBTi5WiCXS28WklKpJDAwsM3npRjCqlWrcHV1ZeLEiXrXOzs7Y29vz759+0hNTWXKlCm6dQkJCYwaNYqQkBBWrVrVoL434eHheHhI89qVnp7eKHHa5kXKmTNnJJs06+RqQWmJmrzslr3AN5YOXkpSM4vJLzC8I2tLUxHqMdHK6JrXmas2EYSnl//49AmUxnQz1ueFEkKlnNYUKACaMg2nN99gwFAX5Io7N1gzEytkyCgtrpokW1Kcj5lF3Z60mOSjRCcfIaTTHGysas5+MFGYY2XhVOVV2XNSQWZuNNdit9MjYBraEnuy0orwCZRG1+Hq5GSVUFamxdHF+A9ttSXPnjlzxgjWtD4ajYZVq1Yxd+7cGoXMVq1axYkTJ4iKimLNmjXMnDmThQsX0rlzZ+COQPH19eWTTz4hLS2N5ORkkpOTdWN8//33/PTTT0RERBAREcEHH3zAypUrq8yqMQZ//PEHnTt3xtzcHLlcrnu5uroSGxure99Q2ny45+LFi41qWtQauHhYkZYkLS9KZYK8lZLwolSmeqhngMaNHA38macFWe0CpQKr5Bqr9VJXmKxCqLRW6MfERIaTmyUu7lYobUxQmMgxMy9/Uh802oOSYjWqvDLSkgvISCmkrKxlY/qtLVAquHkigd7jO9DD34SLUeUiVS43wUbpierWNZw8y5vyabUaclIj8QgcUutY0UlHiE4+TN+Os7FTejXapoKiDC5E/UwHj+G4OZQ/DFV0HY68kt3ocVuS9OQCXDwsSU+R3rWnZ8+eRkuebW327NlDbGys3im3169f54033iAzMxN/f3/++c9/snDhQt363bt3ExkZSWRkZI2OwpVzet59911u376NiYkJXbp0YcOGDdx///0td1IN4OWXX+aee+5h7NixVdrU5OTkMHfuXDZt2mTQeG1epNy4cYO//e1vxjZDL+UipeUafjUlH0UhlxHgpeTEZePXfKge6qnwophrFQzXePCb/BbaWrzXtSXJGtrVuDotKVTsnczx6WCDi7sVLh6WODhbUFRYRlpSIfk5JZSVaSgp/st+GVhYmuDsbkW/EW5YWJqQlV5EWlIhaUkFxN3KIzuz+erbGEugQHmfnJO/XWf0vGCufX1dV/zQ320wl6M3YnE7AGsHHxIjD6NWl+Dq1x+AG2d+wszCDv8e9wLlAiUycT/BHWZgaW5PcWl5zpVCboaJouG1lNSaUs5H/oSNlTveziG6cW5c1TJjbjByuQyNRnpJoGlJhbh4WHEtvO7aM8age/furF271thmtAphYWG1Jgl/9NFHfPTRR7Xu+9hjj+lmA9XG3LlzmTt3blNMbBGio6N56623cHNzq7I8NbU8h6xySKshtGmRUlxcTFxcHD179jS2KXpxcbfk3LGWS5ptCj7ulhSVqEltxhtccxOidSadIiJl5bOjqntRqguUpoR59NGcQsXUTE6nHg50DnbE2d2ShJh80pIKiL6eQ1pyAfm5pTW27z3IlRP7kqpUKra2NdWJG98gWwaHepKeXEjExUxuXs5qUlVjYwqUCm5fTCU3tYBuPgouRJWfi7tjD0rKVMRc2kFxWT5KO0+6D31SF+4pLshGRrmKVfkqibt4Gq1WzYWon6uM3cFjJEFe+nNO9FFSmo+qKB1VUToHL/5Ht1x2UcbUWT/j4askIUZ/rRZjkppcQC+JNkTs2bMnt2/fprS0FFNTw2bhCdoG3t7eegurKhQK/P39DR6vTYuUqKgozMzMamRESwG5Qoajq4Vkk2YDJR7qcXLLY4Dan13y+BphHkOnGFfGUO9TU4WK0saU4P7OdOvrTE5mMdfCM9i2PpviosZ5evJzS8nPzdE1qzS3UBDUzZ5uvZ0YPMaTK2fTuXg6jYJ8w/KMjC1QtAFeyKITALi4J5oB0zpzae8BNP7loRpf14H4ug7UK957jni6yvsRwQtrbFOd/l0e17vcy7kPXs59ALA0dyCs3xK928XczClvdyFBkZKWVIiTmyVyeXmHZCnRsWNH5HI50dHRdOrUydjmCFqA2lofODk5NaotQpsWKTdu3MDX17dK3EsqlCfNashtoQt+U6ceB/ko2Xm8YVM4W5LaZvV01tojAyJkWQ0SKA3xojT2M2uMUJHLoc8QN0KGuhEblcu29bdIbgFRWFyk5sq5DK6cy8DdR0mfQa7MfqYbZ4+kcO5YCg0pSWFsgVKdW2eTGTyzK37BrkRXKzGkjFW1SquI+oi5kcuwcV4c3Z1gbFNqkJNZjEatxcHFkgyJ5aWYmJjg4+PDjRs3hEhpp7z9du2TVrRaLUuWLDFovDYvUvz8/Gosl8LMHhcPK9Il5kWpwMnODAszBXEStK8iH6W/1pXT8jQ0lXJRmiJQmoohQsXRxYIxU3xRKGRs/OFmqyVPJ8ep2B4XjaunFWMm+xLQ2Y69W2LJSi+qdR+pCRQAjVrLlQOxdB/tR8znp9EGND7xtaWIj8lDaW2KvaN5s+YENRdpyYW4ehhfpIzr/zY7Ty+usszPz48bN24YySJBS7N58+Yq71UqFbdv38bU1JSgoKC7S6Rcv35dkqEeKM9Hacmk2abg7mxOamYxagkl/VUO9TjLTfHTWvOb/Fa9BdsaSnP05KlPqFR4T/oOdePiyVROH05Bo279zzg1sYBfvrtO/xHu3P9EJ84eTub88dQaXhUpCpQKIo7E0W9KR2ycLKler1kK3hR1mZb0lEJcPa2kKVKSCnBxt+Ia0kueDQgI4Pr168Y2Q9BCnDt3rsayzMxM5syZw/Tp0w0er03XSYmIiNDNK5caLh5WkstHqcDdyYLkjNqfro3NYAs7rsuyiU+5U8bcGGEefdRWR8Xa1pTpj3WiY3d7Nv1wk5MHko0iUCpQq7Wc2J/E5h8j6RzsyPTHOqK0ufMZSlmgABTkFBN7KZUuw310uSpSIy2pfKqvFJGybZ07dyYiIsLYZghaEUdHRz744APef/99g/dt0yLl5s2begu5GRu5XIaTqwWpLeRJaepN183RnBQJPv1V0N/clkPZdz67piTKtgTVhYqdoznT5nYkPaWQn7+7IanaOKmJBfy8/DqZaUVMmxuErYNZgwRKbOopDl38jD1n3+XEteXk5MfXeoz8wlTCIzfomvHdTjleY5vL0Rs5H/lTjeWZudHsOrOE0rKan9m1w3F0HqI/1COFbtVpyeVTfaVI5eRZqdG9e3du3rxpbDMErYxCoSA2NpbSUsOa7UrwK9wwCgsLSUtLo0uXLsY2pQaOrhaUlWobnTTbUq5sla8SmQxcHc1JyTC+SNGXNOujMMdCJudGaf03odb2olSmQqh07e3IA0924uaVLA5sizOq96Q21Got+/+I41ZEDg8+1ZnOwY51CpTkzMtcj9tJoOcoBnVbgI2lG2dvrqG4VP9MFrWmFEtzBzp6h2Jm2vjmdtVzT+KvpGOhNMPJ20aS3pS0pAKc3aTprciuSJ51Nn7l2ep07tyZpKQkSkqk58ETtBw9evSgrKzM4KnnbTYnJSkpCYVCUaManxRwdLYgM006T9OVcbIzQ6uFzFzpXSCK3UvpYe7E1VIVFbJDal6Uymi0WmTI0Gpp0CwaY6PVaMvtlNVtb0zKcbyd++qm4nbzm0R6zk0S088T4FGzurOd0ktX1fVm/J4m2Xgq5w+yyu7k+vQ8b09ppzgKbyuofrs1dm5KZloRcrkMeydzsiUg+quTmVqEg4sFGanSCu36+Pggk8lITk7G19fX2OYImpm8vDw+/PBD9u3bR1paGppq8+Cjo6MNGq9NixQnJydJTj+2sjFFlWuYS6u1cHM0JzWrWLI31R5m1uwvLK+CW5dAMaYXBcDK2oQpjwRy/VImV89lSL57ckWI55fvrtOzvwuTHwlk4/c3a9RT0WjKyFMl0sF9mG6ZTCbH0bYD2araQz7NRW+bULTcuahFnItmRNhgtu+9hCw6QVIzfbRaSE8pD/lIUaSo8ktRWktP5JuZmeHk5ERSUpIQKe2QBQsWcPDgQebMmYOHhwcyWdOaXbZpkeLs7FxjuRSmHyutTVEZWEyrtXBzsiBFYkmzFTN77OUmeCrMuVoivQJZ1Rk7xY/kOBXH9iQCtGqvH0OpnoNyZFcClkoTxkz25Y+fqhZXKikrQIu2RtjG3ESJqii9SXakZ99g77mqiXPVy4abye/4S2IKL3Hx1E3m/u0hbBxuUZAtPSGQllyAi7slNyXQXqI6UhEp+qYhOzs7k5Qkrd+JoHnYvn07W7duZdiwYfVv3ADabE5KbSJFCiitTVDlt4wnpaneAXcnaeSj6KOHmTW3ygop0Goa5EWpi5b0onTr64S9kzkHt9/xLEi1e3JtSbIH/4zH0cWCrr0dW80WB5sABnf7W5VXd3/9fTzSSuK4UXCKAM0AUm5l4xfsqne76n/n1k6oreiTI0UK8kuxspHmc6gQKe0XOzs77Ozsmm28Ni1SXFyk2Z/CysaUghYSKU1BJgMXB+nO7OlupuRycX6D81BasnhbbdjYmTFkrCcHtsXV6JMjNaFS1yyekmI1B7bFMSTUC2vbO5+3mYkVMmSUVEuSLS5TYd6EpFgAhcIUKwunKi9z06p1cLQBXuSXZXExfy+drAbgbOZNTHgK/r3Km5VJLYE2LbkQF3dpJs+q8sqwkoAnRR8uLi5CpLRT3n33XRYvXkxubvUKR42jzYqUhIQEPDyMfyPQh5W1NEWKo60ZMhlk5EgvaRYgwMSSmOTabbNKNr4XZfQkH25eySLuVp7e9VIRKg2aZhyVx62IbEZP8tEtk8tNsFF6kpF3J7lNq9WQmXsLe2XLJ6mXlKo4l7cTN7MA/C3LG4cmRGTgHuRQ6z4Vf29jTEvOSitErpBh79jw7sqtRYFEwj36cHd3JzEx0dhmCFqAzz77jL179+Lh4UGPHj3o06dPlZehSNMX2AASEhIkW8hNaW2CKk96IsXexpTsvFJJJs06mZlghpyUYv031OrixBhelO59nbBzNGf7L3Vnpzdn9+TGYEihtqO7E3loQWe69nHk2vny6qT+boO5HL0RWytP7JRexKacQK0pxfOv2T6Xon/HwtSWjt6hQHmybX5RGgBarZqikjxyC5IwkZthZeFkkO0Xon5GITMh0DKEYk15rZyk2CJMLUywcbIkL0Nas+Y0GsjNKsHWwUxylWcL8ksl60nx8PDg6NGjxjZD0ALcd999zTpemxUpSUlJkpx+bGomx9RMYXAX2tZAaakgv1B6dgF4W5iTVFRM9TIjDfGcVKalnqZNTGQMGOnBvq2xNcI8+jCWUDG0kmxJsZpDO+IZda8PNy5moVZrcXfsQUmZiqjE/RSX5mNj5U7fjrN14Z6i4hxk3MnYLy7N48TVb3Tvb6cc43bKMRys/WrtNlwbWfm3ATiUXbXw24MJY3DxtyMvo1DvLB9jFneTqhhQ5ZdibqHAxERGWZm0nky8vLxEuKed8q9//atZx2uzIiUjIwM3Nzdjm1EDpbUpZWUaiota/0m/PqwtTVAV3LHL2HUmKuNtaU5CUdWbqqECpSXpHOyIKq+U25ENj7O2tlBpbKn7mBu5FI4qo1NPB66Fl3tTfF0H4us6UO/21YWHpbkDYf2W1HmMHgHT9C53tA2osm9YvyV6804yYvNx8bPj1lkJfSn+QqphlaICNWq1Bisb0xbrxt5Y3N3dSU9v2mwxwd1Bm81Jyc/Px97e3thm1KAlk2ab+rSotDSRrCfFy9Kc+MI77vK6BEptoZ6WfJruNdCF8BOpBu/XWjkqTe3FE34ijd6D9M+gaW301UJJu52Ds1/zzRhoTlR5pVhZS/N5ryBfmsmzdnZ2qFTGb20gaH4UCgVyubzWl6FI85dVDxqNhoKCgmad5tRcWEk0HwXA2kpBek65EJBC75PKeFuasS1ZWjH9Cjz9rDGzUBB5tXG1MFrao9IczQJvXsliSKgnHr5KkiT23QBIi8lhwH2djG2GXlT5ZXhKxCNZnXIvj/Qu8xUiRavVNrnYl0BabNy4scr70tJSLl26xMqVK3nzzTcNHk96394GUFBQgFarlaQnRWltKsl8FCj3pKgK1JITKA6mJpjJ5ST/lTQrpTAPQNdejty4lIWm/lSUWmkpodJc3Yw1ai03L2fRJdhRkiIlIz4XMytTlA4WqLIkVoxQojkpUC6gpBiKsre3p6ysjOLiYiwspNdfSNB4pkypWftoxowZ9OzZk9WrVzN//nyDxmuT4Z78/PIaDlIVKS1VyK2pWFsqUEkw3OOWZ0JemRq1tn6B0tqhHhNTOR262HH9YmaTx2ru0E9zCZQKIi5mEtTNHoWJ9J5s1aUaCnOLsXYsv6FJqV6KlEWKVG1zcCifUl5xLRe0f3r16sW+ffsM3q9NelLy8vIwNTWVpAK3sjEhU2INvSpQWpqgjtJf38OY2JgpyC0tk5wHBcDF3ZKSYk2zNWlrLo9KcwsUgPTkQkpLNTi7WZKSUNAsYzYWbYBXDSFSkF2MlZ30fvOqPGmGVKDcNjsJ1nCxtLREoVCQl5cn2crhgsZx+/btKu+1Wi0pKSksXboUPz8/g8eT5i+rHvLy8lAqpRkDtlSaUqCS3tOBpdIEuVxGQbV8GSnM8LExV6DKl95sKAAXDyvSkpr3ht1UodISAqWCijLvxhYp+lDlFGFlJ70briq/DIWJHHNLBcWF0voeF6rK8PCR3rVSLpdjZWVFXp70HpoETaNDhw66XKPKvbn8/f1Zt26dweO1SZGSn5+PpaU0S1ErFDLUZU1IXmghrKxNKSosQ129EEkttKZ4sTY3Ib9EWhf3ClzcLUlLbv4CYo0VKi0pUOBOwzwpUpBTjNJeeiKlrFRDSbEapbWp5ESKukyDQiG98B2AlZWVCPe0Q86fP1/lfWlpKZcvX2bNmjWNamXTJkWKlD0pcrmsSQmWLYWllYLCAunlo0B5uCezsP48HmNUmXXxsCTqWnaLjG2oUGlpgQKQnlSI/wjpzZoDKMguQukgTQFVqCrDUmkCaca2pCpqjRaZXLoiRXhS2h/BwcE1loWEhODl5cWTTz7J/v37DRrP4MTZQ4cOMXnyZDw9PZHJZGzatKnK+vz8fJ599lm8vb2xtLSkW7duLFu2rMo2RUVFPPPMMzg5OWFtbc2MGTNISUmpss2WLVvo1KkTnTt35o8//qiyrrCwEHNz6T1RQYVIaf7qjk1NDFUo5KglVnWyQnRYmyvIK268AGnJpFl7J4sW8aRU0NBk2tYQKACpyQU4ulhIInm2er0UVXaxJMM9AGq1BrkExYBWo5WkXQAWFhYUFDQurPjll1/i7++PhYUFAwcO5NSpU7p1169fZ+jQoXh7e7N06dLmMlfQRHx8fDh9+rTB+xnsSVGpVPTq1Yt58+Yxffr0Gutfeukl9u3bx5o1a/D392fXrl38/e9/x9PTUzc1aeHChWzbto1ffvkFOzs7nn32WaZPn67r5VBcXMwzzzzDqlWr0Gq1zJs3j7CwMMzMzIDyOimNKQrTGsjktIhIaSqG2NXcN/36QkdWpgpUpdJykwM4uVpQVFDW4nVv6vOotJZAAcjPKaW4SI2TiwWpSdLqk1OUX4KljZmxzdCLRoMkxYBU7YLyvBRtIxqJbdiwgZdeeolly5YxcOBAPv/8c8aNG8f169dxdXXl2WefZfbs2QwYMICnnnqqBSwX1MXBgwervK9InP3vf/9Lr169DB7PYJEyYcIEJkyYUOv6Y8eOMXfuXEaNGgXA/Pnz+eabbzh16hRTpkwhJyeHFStWsG7dOsaMGQPAqlWr6Nq1KydOnGDQoEEUFxejUCjo3bt3uZEmJhQXF9crUsb1f9vQ02l25HIZWgmKFKnaBaCQy1DXY5sxQj0WliatFiKrLlTOHS33LA4Y6U5gV/tWESgVFBWUYW4pvUiwukyDXKL5FRqJeiykaheUixS12vDf9aeffspTTz3F44+Xt2dYtmwZ27ZtY+XKlbz++utkZWUREhJCcHAw7u7uzW22oB7GjBlTo0ifhYUFo0aN4osvvjB4vGZ3RwwZMoQtW7aQkJCAVqtl//793Lhxg7CwMADOnj1LaWkpoaGhun26dOmCr68vx48fB8DW1pbHH38cDw8PPD09efrpp7GxsdFtL2VPSkuFe5pKXXa1RnG3uo4hl4EEPzIUJjLKSlsvwahy6Kff8PKLa2sLFChPBJVCuKc6WrUWuUKav3uNWotMgqZJxS59D5AymQyNgQl8JSUlnD17tsr9Qy6XExoaqrt/vPPOO4SGhmJlZSXZ+0R7Jisri+zsbLKyssjKyiInJweVSsW2bdsICAgweLxmf1z6v//7P+bPn4+3tzcmJibI5XKWL1/OiBEjAEhOTsbMzKxGITY3NzeSk+8Uyli8eDEvvvgicrm8ikCBcpEik8koLa3qhjc1M/4XUq6QoVDImmSLmWnNfZt6biZ/7V/bOBXHtIpTwV/b6LOjMZjWMZ5jmhaFTIaJDMwVMpTJtVy06rClpf7uZhYKtJrW/V6p8kvZtv4W98/rCMDO32MoUJW1qg0uHlYEdrUnIUYCMy86+yC7XR7+cg20x9HLBlOL8suWVgK/9wrcvZV06GxH3C1pJYK6e1vh5GopiWtj9ev1xYsX+fPPP3nwwQcbPEZ6ejpqtbpGc1k3NzciIiIAuPfee0lLSyM3Nxdzc3NJtk9pz9ja2jbreC0iUk6cOMGWLVvw8/Pj0KFDPPPMM3h6elZRvw2hti+XTCajpKSEP//8s8ryp16tmVVsDCY+FGhsE2pFKp9RdR7p03LN95qKMT+zGY8Zp19N556OdO7paJRj16Tq5//kl+OMZEfddOrpSCfJfGZVkcLvvvr1GqBnz54tcixzc3NcXFzIzS3vWm6WYorCovGVd9US7Gp/t9CsIqWwsJBFixaxceNGJk6cCJRPRwoPD+eTTz4hNDQUd3d3SkpKyM7OruJNSUlJaXD8UC6XY2Jiwr333ltl+bRRHzXbuTSW++d14sS+ROKb8BRaoKf4klVc00IyAZ3t6NnPmS1ro+o8ZvXj6LPFECqPV9tYs+/14dC5dGIbOYumqZ9NbfgF2dJ3qBsbv7/ZIuPrY8BId4K6ObDjt2hmPNaJgvxSrl/K4szh1ivHO/2xjpw+lCwJr8DGA6/r/p+amsr169cZPny4ES3Sz9GjRwkMDJRcDoSUP7OePXvi6+tr0D7Ozs4oFIoas0ENuX8I2hbNKlJKS0spLS2tEQdUKBS62GNISAimpqbs3buXGTNmAOVTxmJjYxk8eHCDjiOXy9FoNJiaVlXGfxx9y+jJs2q1Fo0GSksan8tQoicPwrQJ40G5PTKZrFa7Ko5Z/Tj6bDGEyuOZRuXpneVT/plpG32spn42tVFcpEZhUvtn1twMGuNBYFd7Nv1wkwJVecLuH+tvMfHBDmg02mbvnlwbJiZyiovUrXbedTFpyAe68vj+vd3oN6UjSx94Bqg5Rbk52Hl6caP3NTExqXFNMjZyuRy5XC45u6B81odCoTBoHzMzM0JCQti7dy/33XcfUB7+37t3L88++2wLWCkwNgaLlPz8fCIjI3Xvo6OjCQ8Px9Hx/9u77/Am6/3/488kTffeAzppC5RVdgHZG2QLAoIgB/Xg5qu/I86jHhX3OHpQUUFFREERHIBg2atlFMpsoZvume6R5PdHbW1pCh1pcrf9PK4rlza5c+fd0t555TMd8fb2ZtSoUTz11FNYWFjg4+PDwYMH+frrr3n33XeB6i6cFStWsHr1ahwdHbG1teWRRx4hLCyMoUOHNqmGmpAiRRqNNAaq3ex2dRlzZ+QqtUZv41/0qSC3HFt7U+QKGZomrtTbUkPHehBUZ5pxzRiCgjbaPbkxChMZNvamFOSWt+nrtITSTEFVK9bTaYqWfshZcH8w335yhqQW7I3VmmB0OzfPspCSlk6AWL16Nffeey8DBw5k8ODBvP/++xQXF9fO9hE6lmaHlFOnTjFmzJjar1evXg3Avffey8aNG9myZQtr1qxh8eLF5Obm4uPjw6uvvsqDDz5Y+5z33nsPuVzO3LlzKS8vZ9KkSfzvf/9retEmJlRVSXP1VKkuniSVunStmVJUosZKglNeVfkVVFZocHI1J6sN1wy5OaDcTF+bEjaFs5sF5aVqilTS28nb0t6c4gJpbt7Zmll9bdn6262nPb0HOfPak/Vfoy2DUVNVVVVhYtL8v/sFCxaQlZXFCy+8QHp6Ov369WP37t0NBtMKhqNWq0lJSWn285qy4WCzf0NGjx59ywV43N3d2bBhwy3PYW5uzscff8zHH3/c3JcHwNramtJSaS00VUMf6xK0xb45lRUaTM2a17TaVrXcfM7i0iqsLZpfmyFkpZfi4m7ZZiHldgGlhqGCirO7BVnp0ttcEMDK3oySAum18ACYmikk0T12s8a26TB0t7iuUFRaWoq1tXWLzvfwww+L7h0JSUxMJDAwsMmL89VsPtiUHhHpfXxtAhsbmxYvp9zWNBokueBUcVEllnrcTr6me0gfAaaotApHW2muJJqdVoKLhwWcvf2xzdXUgFLDEEHF1cOyTbcBaA1LOzNyko0/mPdmMln1LuPFRdJrfZJJeBHH4uLiBstLCO2XhYUFx44da9Kxubm5tYu53k67DCnW1taSDSkV5eoWtVi0tZLCShQKOeYWCsr0uFNrS1ta6j6vuFSNt3vLfhXbeixNVnop/Ya66v28zQ0oNdo6qLi4W3LqiOFmEjWHpZ05yRcktoMfYG5pglwuo6RIel3QZuYKKtp4HE9LlZSUtLglRZAWMzMz+vXrp3NzQV3y8vJqV5S/HemNVmyCmpYUKQ6eLSmqxMpGeiPpq6q0lJep26S2xoLC7QJEzeNFJVVYSbS7JzOtBCc3c0z0OLC3pQGlRlM3JWwupakcB5e2HX/TGlb2ZhTnV3f3tMXMnpayslFSVlLV5oOrW8LKWpotPFVVVZSVlYmWlA7inXfeYffu3U0+3sHBgTNnzjTp2HYbUrRarSS3+S4u1G+3ij6VFFViad02AaqlLRpWScWo44uwtpTmz0yVV0F+Tjn+3fWzamVrA0qNtggqAT3syc0qpbDAcEvwN4elvTklEhw4a2WtlGQQALC0UVJSKL0WnoKCAgARUjqIzZs3Nzl0NJc03xluo6aJMC8vT3JLHpcUVeHeRb8DTfWluIUhpaldOnWDSnO6gFR55Zgp5VhZKCjWY1eUvlw5l0v3Po7EROe16jz6Cig19N31E9zHkavncltdV1uwcjDHxFSBKkt6rTyW1iaUSDWkWCulsb3BTfLyqv+WrKykea0UmmfOnDncddddzJkzB1dX1yZNLX/xxabNMGuXIcXU1BRTU1Py8/ONXUoDxUWVWOmhtaItZtVUd0W1/p+8Ka0mzWlZqazQkJ9Tjo8aLrWmsDYScyGPoWM8sHUwRdXCcKHvgFJDX0HF3tEMdy9L9vwYr7fa9EXr54WLfRX5aUVUVagl1dUD1d09xRIcjwLV3T1SDFAFBQVYWFg0ezE3QZref/99evTowd69ezl9+vRtlwjRarUdO6RAdQKv2ZdBStqyS6W1SgqrJFtbVnr1LBqrwxl6D2etVVpcxbXL+fQd4sLh3Tea/fy2Cig19BFU+g51IfZiPmUl0mvJAnDxsSMrocDYZehkaa2kpFB6QQCqa5NigCooKBCDZjsQU1NTHnnkER555BG9n7tdjkmB6r7MnJwcY5fRQElRFRZWJpJYOO1mrWnlaetZNJmp1euRGOK1WiLqRBbd+zph3swBvm0dUGq0ZoyKhaUJwb0diTqR2UbVtZ6Ljx2ZUg4pEmytUJjIMLeQZktKTk6OGI/SwXz++ec89thj/Pnnn6jV+vuw025Diru7OzduNP9TbVsrKapEq9VKcvBsiZ7XStGnmpaUGlILKjkZpaQmFjF4dNMDgKECSo2WBpUhYzxIiS8kN0t6g1JruPjYkpVYILmuHqiZQSO91gpLayUajZbSYunVlpqaKjYE7GDCwsJQq9Xcd999uLi4sHjxYn744YdWT3BptyHFy8tLkiFFq63uHpBit0pxYSXWUl00Lb0UKxslFlZ/hyipBZVDu1MI6uWAl+/tm6kNHVBqNDeodPW3oVtPew7taf6S1oZiZaPE3MaMnGRptqRY25pKcnaPVMejANy4cQMvL+kFTqHlQkJC+Oijj0hMTCQ8PJzg4GDeeOMNXFxcare+acnS+e02pHh6epKWZphdYZtLn4Nn9SknqwwbO1PMzFs2WM0qqbjNgkPN4Fk3T0uDvWZzFeZXcDw8lTHTvWs3ANTFWAGlRlODiqmZnDHTu3JsXypFBdJ8MwNw87QkP62ISi/9rQmjLxaWJljZKMnNlOKsI6UkF5gDSEtLw9PT09hlCG2kX79+vPDCC5w+fZrr168za9YsfvnlFwIDAxkwYAAvv/xyk8/VrkNKZqY0+9BLiqok2a1SXqpGlV9er1tFSpLjCvHpZqvzsZuDirHCy8XTOajyyxk2TvcF1tgBpUZTgsqw8V7kZZdx6az0xnbV5d3NlqRk6YUAqN7rKD+3nIpy6S0sKeX1W7KyskRI6SS8vLz45z//ya5du8jOzuaZZ57h2rVrTX5+uw0pHh4eZGVJb4lsqO5WkeKqswBZaX8PUJWa+JgCfAJ1hxT4O5gYu2Vl/6/JBPZyoItf/W4fqQSUGrcKKl39bQjoYc/+X5ONVF3T+QbakhAjza4eVw9LstKkuUVH9UJu0g0pHh7SaxkT2paVlRVz587l66+/bvJzpPdxv4k8PDzIzs5ucP+eyBcNvsPnzaQ8DTkrrUSyLSlpScUoTRW4eFhIdml2qO72ObrvBhNm+bL961jyc8olF1Bq6Jqe7OBszvhZPhzde4MilTTfxGq4eVkiV8hIS5ZGl9/NXDwsSE+RZm2W1iYU5hv/d1HXDsgipHRc/v7+TdoNOT6+aWsytduQ4unpqTOkSEFxUSUu7voJAvpe1C0rvZQeoU56O58+aTRakq6r8A20k3RIAbh8NhcbO1NmLA4gIbYA30A7yQWUGnWDiqmZAv9gOy6cyuaKRFeXrcs30JakayqauAO8wbl4WBJ9SprXIStrJRkp0mzlyc7OFt09HdTjjz9e7+vs7Gzeeust3njjjRadr92GFA8PD4qKilCpVNjaNt5FYAxFBZXYOpjp9ZzF3lZ66ebITCvBzsEMM3MF5WXSW7grIaaAfmGuRB6S5k68dUUcSMc7wJaeoc7s3CTNgFIjP7ecP3ckMn1RAFnppe3i5wvgG2THqcMZxi5DJ3MLBTZ2ppIN1Lb2ppLchyk3N5fS0lLRktJBPfroo/W+jouL47333mtwf1O12zEpTk5OmJqacv36dWOX0kBWegn2Tma3nAFiLNWDZytw1lNLj74lXS/E0cUCa1tpdpfVNXSsB5ZWJsRE5zJhti8OzubGLqlRji7mjJvpw9XzuVjbKPW6e3JbsbE3xd7JjOQ46a0sDdWtKAW55VSUSy/sm5rJsXcyJztdegEqLi4Oc3Nz7O3tjV2K0A5I7120ieRyOX5+fly8eNHYpTRQUlRFSVEVzm766/LRp+pxKdIcPFtepubG5WwCezkYu5RbqjsGJfyXZC6dzWH2vd3oFmJv7NIaCOrlwKyl3bhwOpv9vybrfffkthLUy4GU+CJJzpwB/ho7Jc3uFGd3S4pUFZSWSG8K8oULFwgICEAmk96q3IL0tNuQAhAcHMzly5eNXYZO1Suo6i8I6DOoZKWX4CrRlhSAy4eT6NlLWrtb16VrkGzkoXQO/JbMiIleTJ7nW29ROmOxsDJhyl1+DBvvyf5fkjl9pLrbpDVL6BtSj36Okp4e7eJuSaYEWyoAXNwtyJRoN9SVK1cIDg42dhlCO2H8K2krBAcHExsba+wydMpKK5XsLJqstFJ69JPm4FmAhLMZjFzciy7mZaSUSasL5VazeOKuFJCaVMTISV24+4HuHN6dwrVL+UapM7CXA3dM8iLpeiHffXqF8tL6XRL62j25rXT1t8HERE5irDSnHkN1d8+F09IcNOsi4anR165dEyGlA3vppfqza3Nzc6moqODf//53vdazDr8LMlSHlAMHDhi7DJ2y0koI6GFv7DJ0yrhRjLWtKTb2ppKYongzjVrLlaMp9BrjQ8ou6QyabMo047ISNX9sT8S/ux0jp3ShW097Ig+lk5NpmH1xnFzNGTzKAzcvSw78mkzc1cbf5KUcVEIGOHP5XC4aafb0YOdgipW1CZmp0gwCLh4WxERLc/ZWQkICd955p7HLENrIjh07GtwXEhLCzp07a7/WarWdI6QEBQWRlJTU4H4prJWSlV6Kg7MZJko5VZXSutJWlGtITSrCN9CW6EjpfRLU+nlxYX8ii14dhc33lym0dTR2Sc1eB6WmVWXwKA/mLA8iLamIcyezSIkv1Pt0WpmsuuWh7xAX3Ltac/VcLls+vUJZ6e0HdEoxqNjam+ITYMMRCe8n5Btkx43EIiorpPW3DaA0lWPvaEaWBLqidK2RkpSURFBQkBGqEQzhzJkzej1fuw8pGRkZFBQUYGcnrTEMxYWVlBZXD56V4mJPCTEF+AbZSTKkABTllJJ4PpNeY3w4se2KUXe/belCbWUlag7tSiHiYBq9B7ow9k5vtFotV8/nEne1gJzMMjTqliUWuUKGs6s5/t3tCertgEwm4+KZbPZuT2xSOKlLakGl10Bn4q8WSHqhOd8gO65dyjN2GTq5uFvUXn+kJjc3l6ysLBFSOrCDBw/SvXt33Nzc9HK+dh1SXF1dsbGxITo6mhEjRhi7nAZqVneVZEiJVTFsvBemZnLJzp4490c8Ux8bxNld1ymPv2GUoKKPlWTLStREHkrn1OF0uvrb0L2vE3cuckZpKic3s4ys9FKy0krISiuhsKCSqioNsr+GtCtN5ZiYyLGxU+LiYVl9c7fA0dWcygoNKfGFHPgtmeS41rXQSCWomFso6BnqxC+bpbe0QA0zcwUeXa34c0eisUvRqXo8ivFbUXSJjo7G3t4eJyfpjokTWmfs2LG4uLiwfft2wsLCau/PzMzE3d0dTTP7cNt1SJHJZHTr1o1Lly5JMqRkppdKdqpvYX4F+TlleAfYGm1w561o/bxIv3aDjLh8+k8N4PjWKwavQd9L3Wu11evAJF0vBMDWwRQXdwtc3C3x727PkDEemFvU/5Nc9ngvAMpKqshKLyErrZQzxzLISitFpefxRFIIKgNGuJGWVETGDWmO9YDqDQ9zMksl29Lj4mFBVro0f34XLlwgMDDQ2GUIbWzq1KmMHTuW9evXc88999Te35Jp5+06pAD06NGD6OhoY5ehU1ZaCf7B0uqGqqu6y0eaIaXGyR+vMOvpYZzfl0CxAVtTDLEXjyqvAlVeBdcv/z24Va6QYWIix9xSwT0P9eSrDy5QWqJucbdQcxkzqFjbKQnp78yPG2IM9pot4RdoS0KMNBeYg+qp0bEX8o1dhk4XL16ke/fuxi5DaGOvv/46Y8eO5f777+fixYu8/vrrAE3a0+dm7XqdFIABAwZIOKSU4uBsjolSmj/mhFgV3gG2yKVZHgDZSSoSotIZNLO6D1sWf6PNX9OYmwVq1FoqytW14wkqyjUGCyg12mIdlWJvq3o3XQaP9OD6lXyDzYRqCblcRtcAWxIkOjVaaSrH3smMTIlOP46OjmbgwIHGLkMwgHvuuYeDBw/y9ddfM2fOHIqKilrUkiLht6emGTBggM4F3XSNKje04sJKykqqcHaT1lofNTJulKBRa3Hvam3sUnSqaTWJ+DmGwCGeOHi0fZ1S3c3Y0PQVVBoLJTcHFkcXc7r1tCfioLT3FPL0saKyQi3ZMR/OEho0e/M1WKPRcPnyZQYMGGCkioxj7dq1yGSyehvvffbZZ4wePRpbW1tkMhn5+fkNnjdjxgy8vb0xNzfHw8ODJUuWkJqaqvM1rl27ho2NjSS2GqjbWjJo0CBOnz5NSkoKkydP7pwtKaGhoWRlZZGYKM1BbFnppbi4S3NcClS3pvgGSmuDxpupMku4ciSZwbOrF4Bqq9YUEVDqa21Qac7u3UNGe3DpbI4k1+2pyzfQjsRYaXf1SGHqsS5xcXHk5eXRr18/Y5diMJGRkXz66af06dOn3v0lJSVMnjyZZ555ptHnjhkzhh9++IGrV6/y448/cv36debNm9fguMrKShYuXMgdd9yh9/pbwtfXF4VCUfu1u7s7hw8fZvjw4fj6+jb7fO0+pNja2uLv78+RI0eMXYpOGTeK8eja9Iu1oSXEFuAXJN1xMzWtKad+uUaXnk506ekM6D+oiICiW0uDSnMCistQFzx9rGuX7Zcy3yBbEiQcUjy6WpEp0UHHR44cITAwECsr6V4P9amoqIjFixezfv16HBzq70X2+OOP8/TTTzN06NBGn//EE08wdOhQfHx8GDZsGE8//TQnTpygsrL+gO3nnnuO7t27M3/+/Db5PpoqMjKSs2fPEhcXh7Ozc73HzMzM2LBhA3Fxcc0+b7sPKQADBw4kIiLC2GXolHhNRdcAW+RyaW6mlRJXiLmlCW5e0m3tAShVlXN86xVGL+uD0rx6vLe+gooIKLfW3KDSnIBippQzOcyVY/tuSHIzvLrcu1phaqYgJb7Q2KXoJFfI6OpvQ8I1aYaoyMjIdj8eRaVS1buVl5c3euxDDz3EtGnTGD9+fKtfNzc3l2+//ZZhw4ahVP69Q3x4eDhbt27l448/bvVrtFZMTAzjxo3Dx8eHRx55hL179zYIVC3RIULKoEGDJD14trJCjUczLtyGVFWlJfZCHj1DpbtuQU1ryqWDSRRkFDNsQY/ax1obVERAaZqmBJVbDYptzJhBzmTnV3A5SppLuNfVM9SJmOg81AYeyNxUXj7WlJepycmQZndPdHQ0gwYNMsprW2aCZXorbpnV5+natSt2dna1t5pZKzfbsmULZ86cafTxpvrXv/6FlZUVTk5OJCUl1VtyPicnh2XLlrFx40ZsbY3fZb948WKysrLYsGEDCoWCBx54ABcXF+6++26+++47CgpaNti8Q4SU/v37S3bwLEBirErSXSqXzubQrac9SlPp/zrs33ieboM86Bryd3NiS4OKCCjNc6ug0txwAuDnZUmQtzV7jmfqq8Q2Y2qmIKCHvaR3ZfYNsiUhRhqzjnRdey9fvkz//v2NUI3+JCcnU1BQUHtbs2aNzmMee+wxvv32W8zNWzdp4qmnnuLs2bP88ccfKBQKli5dWjv4dOXKlSxatIiRI0e26jX0SaFQMHbsWN5//33i4uI4fPgwvXv35v3338fNzY3x48fz3//+V+d2No2R/rtSE/Tv35/09HRSUqS510dCrArfIOMn3cZkZ5SSl11OYC+H2x9sJDWtKUU5pbXdPqZ1Fj5rblARAaVldAWVlgQUM6WcSWFu7D+VTaHEu3kAgno5kJNRSm6WdKdH+wbaSXa8THx8PDk5OYSGhhq7lFaxtbWtdzMzM2twzOnTp8nMzKR///6YmJhgYmLCwYMH+fDDDzExMUGtbvq2Fc7OzgQFBTFhwgS2bNnC77//zokTJ4Dqrp6333679jVWrFhBQUEBJiYmfPnll3r7nlujd+/ePPvss5w8eZKEhATmz5/Pnj17mrVWTocIKXZ2dnTr1o19+/YZuxSdUhIKsbA0wdFFmlORAS5F5dCzn3S7fKB+t09eWhHD7u5Z7/GmBhURUFqnblDpP9O7RecYO9iFrLxyoiU6fuJmPUOduBwl3VYUJzcLzMwV3EgsMnYpOoWHhxMUFIS1tTSXO9CncePGER0dTVRUVO1t4MCBLF68mKioqHozX5qjZjn5mnEwx48fr/caL7/8MjY2NkRFRTF79my9fT+tUTN2B6pn+dx///38+uuvZGc3fc+4DhFSoHq61oEDB4xdhk7qKi3J8UWSbk2JvZCHvZOZ5AfQ1jiw8Ty+fV3pMbJrvftvF1REQNGP/NxyvvvzBr0CbLmjmeOZ+gXZ4edp2S66eaB6wKyNvSmxF/ONXUqj/IJsSY4rNPjCf021f/9+xo4da+wyDMLGxoZevXrVu9WMK+nVq3qbi/T0dKKiorh27RpAbajJza0em3Xy5Ek++ugjoqKiSExMJDw8nIULFxIQEFC7H06PHj3qvYaXlxdyuZxevXo1mE1kSGq1mjfffBMvLy/s7e2xt7fHy8uLN998szZoWVo2/X2mw4SUsWPHcvLkyQb3S2VcSkJMAb6B0h2XUlmh4XJULn0Guxi7lFuq7fbJLWPP/84w/O6eeAQ51jumsaAiAor+FHtbkaeqZMsfKc0KKl3dLBg1wJkdB9Mo+qubxypJehtw1tVnkAuXz+ZQVSnNjTjhr64eCY9HiYiIYMyYMUaoRpo++eQTQkNDWblyJQAjR44kNDSUnTt3AtVv4j/99BPjxo0jODiYFStW0KdPHw4ePKizi0lKnnrqKd566y1Wr17NoUOHOHToEP/3f//Hm2++yZNPPtns88m0LVkCToLS0tLo0qUL6enpuLjUf6OdNOglI1X1NwsrE+59LISvPrgoidUgdbF1MGXhA93Z9PFliguluXlajZog0nOUN4NnB7HtlaMU5dSf1VB3n5/2FlCUpnJW/r8+rH/zPJUV0npzvHkMioOtkrsnduHCdRWHbzGw1M7ahHumenPoTHa9bh4phxRrWyWLV/Vg87orFBZI8/fGykbJkkd6svG9C5SVNn28Q1u5OaSkpaXh5eVFeno6rq6uBq1FpVJhZ2dHr/tfQ2Ha8u52dUUZFz57hoKCAknMpJEyBwcHNm7cyMyZM+vdv2PHDpYtW0ZeXl6zztdhWlI8PDzw9/dn165dxi5Fp9LiKjJTSyS9uqsqr4KkuEJ6DZD22BSoPz7lemQaUx4ZiIlZ/b7emiDT3gKKlOkaJNuUFhWliYzZYzy5HF/YbgIKQK+BziReU0k2oAD4BNqSnlIsiYCiy++//05wcLDBA4pgHHK5XOfA2O7du2Ni0vw9jTtMSIHqLp8///zT2GU0SupdPgDnI7Lo2d9Zspsi6nJ0yyXKiyoYe19fuGnNvLABNiKg6MHt1kC5XVCZNsKdkjI1+09ltWWZemWilNMz1InzEdKuuXpXZml09egSHh7eacajCHDffffx7rvv1pvFpFarefvtt7nvvvuafb72807UBGPGjJH2uJRYFV38bVCYSHP1WYAbCUWo8srpM9j59gcbWU1rikatZc+6Mzh3tWXEwpDax4fO607gUC92vn5UBJRWaOoU48aCyoQhrjjZm7LzYBp1O5el3orSb6gL+TnlpEq4ThOlHC8/G8lMPRbjUYTs7Gy2bNmCv78/c+bMYc6cOfj5+fHDDz+QkZHB8uXLa29N0fy2FwkbPXo0sbGxZGRk4ObmZuxyGsjNKqOkqJIuvjYkSnjq5fHwNKbc5cfFMzmUS7QJuYbWzwtZ/A3KiyvZ+c5JZv1rKOoqDVqNtjqgvHmcgswSZJTUG6Mi3F5L1j+pCSp3T+wCgIlChp+XJd/tSaFMYmNrbsXcUkG/oa789n3z9xoxpK5+NhQVVJCf0/jy7MZ048YNrl+/LqkFx4S2VVBQwLhx4+rdV7MdQs105OboUCHF3d2dgIAAfv/99yanNENLiKle2E3KISU1sYiMG8X0H+bG8T91bw0uJTVBpSinlJ1vn2T+i3egBba9dJiCzL83W5PF3xBBpYlaElBq1ASVpdO80QJf/ZJI4U2DxaXeijJguBtpSUWkSbzO6lVmpXst2bVrlxiP0sn89NNPej1fh+ruAZg4caJkB88CXL+ST0APexQK6Xb5AJwIT6PXQGesbZW3P1gCasJHz5HeVJSrqSpXEzLGp8Fx+t49uaNpyf47uoQG21NRqaGqSkOfm8ZhST2gWNspCenvzIn9acYu5ZZMTGT4d7fn+pV8Y5fSqF27djFx4kRjlyEYQVFREREREVy6dImKipZ3t3e4kDJz5kwOHjxYu2hMDamMS0lPLqa0uAr/HvbGLuWWsjNKib9awKCR7sYupcmGrBhI4FAvdqw9xvbXj+HX352R9/RCdlMeFEFFN32EE5kMJg51JaCLFZt3J/PdnuatoyIFg0d5cP1KPjmZ0l0CHyCgpz1FqgoybpTc/mADuPkaq1arOXToUIOpqELH9/zzz+Pi4sLQoUPp1asXjo6OvPrqq7RkxZMOF1JGjRpFSUkJhw8fNnYpjbp0NkfSuw7XiDiYRmCIAw7O0l48COpMM94cR0FmCaqsEna8cRzPYCemPDqo3j4/IIJKXfpqPTEzlTN3nCderuZs2ZNCQVFVg8G0Um9FcXQxp1sPeyIOphu7lNvqGeok6Q0P9+/fT0VFBXfccYexSxEM6L///S+ffvopn3/+OYcOHcLa2po///yTzZs3s3bt2mafr8OFFFNTUyZNmsS2bduMXUqjrp7Pxc3LEntHab/5q/IquHwuhyGjPW5/sBHdvA5K3VVpf3rtKABznh2OnVv9N+LOHlT0FU4AHG2V3DO1K2q1lm93pdTbNLAmqPT2tWmwe7LUDB3jwaWzORTmS3s2mIOzOS7ulsREN29hLEP68ccfmTx5Mkpl++gyFvRj3bp1vP322yxevBhPT0+0Wi1Dhgzhgw8+YP369c0+X4cLKVDd5aNrs0GpdPmUlaqJv1pAj3bQmnLqcAZd/W0ku6dPYwu1af280Pp5UVFaxa4PI0mIymDus8PpGlJ/anVnDCr6DCcA7r2tWTStKxdyivn5QBoVOpaPz1NVNtg9WWrcu1rh6WPN6SMZxi7ltnqGOhJ3JZ/yMmnMvtN1bf3zzz+ZNWuW4YsRjCouLo4RI0Y0uL9bt26kpze/hbJDhpSpU6cSGxtLbGyssUtp1KWzOQT3cUAul/YA2tLiKs6dzGLoWE9jl9JAU1aS1fp5odXCiW1XOLz5IpNWDaDPBL96x3SGoFITTPQZToo8FfQZ6sj83m78eiWbk4ezaazL2SqpuN7uyVIMKmFjPTh3MovSEmluW1FDoZAR3NtR0l09V65cIT4+nsmTJxu7FMHA7O3tKShouLjgoUOHCA4Obvb5OmRIcXJyYsiQIXz//ffGLqVRNxKKqCzX4Bcs7RVoAaJOZOLgZEZwb+PtrHmz5ix1X9P9E3viBjvfPkHfSf5MfngAlnZ/d7d11KCi72AC1eFE5mvKor5uDPW2Y+PpVBLONj4Ntu44FKkGle59HbG1NyPqhPR3ZvbvbkdpaZWkF5nbsmULw4YNM+puvIJx9O/fn6NHj9Z+XVlZycqVK3nwwQd57rnnmn2+DhlSAGbPns2ePXsa3C+VLh+AC6ez28XKrhXlGg7+nsLwiV5YWht/aZ2W7MVT0/2TGV/ADy8eoqpczYJXRhI45O8Woo4SVNqi1QSqw0mRp4K+HtY8FNaFsioN606koLpa2uhzdA2UlVpQsbZVMnyCFwd+S5bcZo669B7kwsVT2cYuo5aua+qePXuYPXu2EaoRjO2ZZ57Bzq76w7eZmRn9+/entLSUPXv2MHfu3Gafz/jvOG1kxowZPPvss+Tm5uLo6GjscnS6HJXL4FHuuLhbkJXe+IVeCuJjCgi4ZsfoaV35/ft4o9XR2s0CtX5elMffYN/6KPxC3Ri5pDcBgzw4+PUFSlXltUGlvS36pu9AUleRZ/XGjTamCu7s4YynrRnbL2ZxNbsE69TGx0TcaiZPTVCZuaQbACeNuCbJ6Gldib9aIOkFFmu4elri6GLO5XO5xi6lUdnZ2Zw6dYpNmzYZuxTBCEaMGFE7JsXLy4tjx4616nwdtiUlKCiIoKAgvvrqK2OX0qiKcjVXzufSZ7CLsUtpksN7buDibklwH+M04eprN+OaVpX4sxl8/8JBqirU3P2fkQSFedVuUNgeWlXaqsWkRk3LiQzqtZ58fDyFG+cLWxxQakihRaVHP0ccXcw58of0/70B+gx24cq5XEm3+GzYsIFevXoREBBg7FIEI0lISGDNmjW1e/c8/fTTxMe37MNthw0pAEuXLtU5LkVKXT7REdkE9LTHwkr6jVrlZWoO/p7MiIldsLIx7LRCfQWUurR+XpS6uLLvsygObIxmyNzuzH1uOF49qmddSTWotGUwgb/DCUCAowX3D/ZiXIAjP1/K4qeLWSiSKm/5/OashWLMoGJtq2TY+OpunopyacySuRUrGyUB3e04HymdXZl1XUt/+OEHli5daoRqBGNZvXo169atA+DXX3+le/fu7Nq1C0dHRxwdHdm1axfdu3dn586dzT53hw4pCxcu5PTp0y1OcIaQn1vOjYQieg2Q/tgUqN7JOSG2gNFTuxjsNdsioNSl9fMiLk/Bd8/s5/qpNCb9cwDTVw/G2cdWMkGlrVtNoH448bQ1497+Hszr7cqFjCI+PJbMlaxbd+9Ay5a8N1ZQGT2tK3FX80m6Xmiw12yNkAFOJMcVopLwjt6xsbFERUVx9913G7sUwYC+//57Bg0aBMD//d//8fjjjxMVFcXnn3/O559/zrlz53jiiSd48sknm33uDh1SunTpwvDhw/n888+NXcotnY/IIqS/E3KJ7+dT48ieGzi7WxLcp+3H+rR1QKmr0suDs1fK2fR0ONlJKmb9axgTHgjFviS/TV/3dtoymED9cOJkqWR+b1eWD/DgRkEZHxxN5mhiAeYpVW0SUGoYOqjUdPMc/UP6G2hC9bTjkFBnSbWi6PL5558zatQoPDyMPyBaMJy8vDycnKpboJOTk1mxYkWDY1asWEFycnKzz92hQwpUd/ls3769wf1S6vJJjiukrLSKHn2lOcD3ZuVlag78nsyIiV5t2u1jyIBSV7mbG8dPF7L5kytUlFax4KU7mDLNHU8fa4PVUKOkq2FaTvwczFnY141VQ7tQWqnhw6PJ7Lueh0lS5W3DCehn00BDBZX21s0D0CPUiZKiSlLii4xdSi1d19Cff/5ZdPV0Qt7e3hw5cgSAsLAwzp492+CYs2fPMmzYsGafW/oDIVpp7ty5/POf/+TUqVMMHDjQ2OU0KuJAOndM7sLV6DyqdKzYKTWJsSoSYgoYPa0rv22J0/v5jRVQ6iourOTA4VxOnSuk1wBnJs/zpVhVycUzOcRcyGuzN7hibytMlW33+aEmmJibyOnjbs3ALrZYmyo4fUPFb1eyUf31fRkqnNRliFk/Y6Z3Je5K++nmMVHKGTjCjQO/Nf9TqCEdP36cpKQkMfW4E1q6dCmPPvooSUlJLFiwgCeffJLo6GgGDx4MQEREBBs3buTVV19t9rk7fEixs7Nj+vTpfP7555IOKXFXCwgd5kqfwc6cOSr9BaUAjvxxg3krghg00p3IQ/rbkE0KAaWuIlUlJ/ancepwOoG9HOjRz4mw8Z5cv5TPtUt53EgoQq1u/u6eurT1mBMTuYwgRwtC3KwIcbUivbCC40kFRKcXUaXRYp2qpqntRW21WWBbBpUho92xsTdjz4+JejtnW+s31IWCvHISYqU9RfqLL75gxowZ2NjYGLsUwcCefvppysvL+eyzz0hJSQHgtddea3DcsmXLmt3SJtO2ZO/kdmbHjh2sWrWK5ORk5PL6n1AnDXrJSFU15OljzZS7/Nj08SXKS9tHM7SDszlzlwey/9ckrl9uuBRyc0ktoDTGydWc7n0d8Qu2w8LShOS4QhJiVSTGqlq0rPrN4cRUKeexhQF88N11nXvhNFWRpwIrUwVBzpYEO1sS4GRBcYWaK1klnLmhIrO4eqZOU1pN6jLEbsb2jmbMXNKNK+dz9RJUuoXYM2pKV37aEENeTrkeKmx75pYK7nmoJ79tiSMtWTorzN7c1aNWq/Hy8uKLL75g2rRpRqqqIZVKhZ2dHb3ufw2FqXmLz6OuKOPCZ89QUFCAra2tHivseCoqKigvL6exaNHcn1+Hb0kBmDJlCqWlpezYsUPSTZGpiUVk3Cim/zA3jv/ZPgb05WWXsffnRCbM8qEg9xrZGS1flK69BBSAnMwyju5N5ejeVBxdzPELsqNnqBOjp3Ul80YJSXEqstJKyUwrobS48dDSFi0nVhYK7AIt8bQ1o5ujBZ62ZqSqyrmaXUL49dx6waS5o2wMEU5q6LNFxcXdgjHTurLnx4R2E1AABgx3IzWpSFIBRZeffvqJqqoqJk6caOxSBCMzNTXF1NRUb+frFCHF1NSU++67j08++aRBSNkT+aKkWlNOhKcxe1kg0ZFZFKluvR6FVCTGqjhzNIMp8/3Y9mXMLd+UG9OeAsrNcrPKyM0q4/TRDCysTPANtMXLx5rAEAfsncwoKaoiK62ErPTq0KLKKyfLzpTyVo49MjOVY21hgr2NEncnM1wdzXB1NcfaVEFOSSWpqnLOpBay5XwGRRXq2taSlgz/NWQ4qUsfQcXCyoQp8/2IPJTebsahAFjbKQnp78y2L2OMXUo9ugbMfvrpp6xYsQKl0rDrJwnSUF5eTmRkpM7dj3Wpqqri6NGjjBo16rbHdoqQAvDAAw8QEhJCcnIyXbt2NXY5jcrOKCX+agGDRrqz/1dpD5Sr68yxTJzcLJg8z5cd31xHo2l6L2J7Dig3Ky2u4nJULpejqpctV5rKcXazwMXDEhcPCwJ62GPjYIrSRE5llYbiUjVFpVUUl1RRXKamSq1Fo9Ei+2s2+rC+jmi1YKKQYWWuwNrSBCsLE6wsFChN5FRUalAVV5KRU05SeikRF/PIzC2nsqr+z78185KMFVBqtCaoyBUyptzlx43EIqJOSHv67s0Gj/Lg+uV8crPKjF3KLcXHx3Po0CE+++wzY5ciGMmNGzeYMmUKhYVN+xCQm5vLmDFj0Ghu/0Gt04SUwMBARowYwYcffshbb71l7HJuKeJgGnff352oE5nkZbefpun9vyQxa2kgI6d0afJMhI4UUHSprNCQllxcr7m+ZvaOtYUCKwuTv4JH9f8r5KBUyDExqR47ZWoip0qtoapKQ2p2ZXWoKamiuLSKolJ1q8ar3I6xw0ldLQ0qo6Z2QSaDA+0o8AM4upjTrYc9331yxdil3NaHH37IqFGj8Pf3N3YpghFVVFSwfPnyJh1bWtr0YQGdJqQArFq1iscff5zXX38dE5O/v3Wpdfmo8iq4fC6HIaM92L0twdjlNFlVlZZdW+O5a0UQvQc6E32bnVo7ekC5Wd3xJxWVGnIrNeQ20qVnqpTTu5stB05nt2kQ0UVK4aSu5gaVPoNd8Pa3ZesXV/U2+8pQho7x4NLZHAoLpPV3cXNXT0VFBVu2bOHjjz82UkWCFFhbWzNt2jQKCpo+eWLWrFlNOq5ThZSZM2fy6KOP8t1337FkyRJjl3NLpw5ncM9DPXDzsiTjRomxy2my4sJKdm2NZ8biAPJyyhpdfKozBxSpkmo4qaupQaWrvw1DRruzY9N1SoqaP0bKmNy7WuHpY83+Xy8bu5Tb2rRpEwqFghkzZhi7FMGIXF1d+emnn9rk3B1+xdm6lEol//znP/nf//7X4DEprUAL1WMbzp3MYuhYT2OX0mwZN0o4uCuFyfP8cPOybPB4Zwoobb3fTmtZJRXX3tqL261M697Viklzfdn/WzKZqe0n4NcIG+tB1InMFk1lb0u6rpGffPIJq1atqtcyLQj61KlCCsD999/PmTNnOHPmjLFLua2zxzNxdDHHO6D9LY4UE53H8fBUpi8MwMXDovb+jhRQ6m7619hNqtpbMLlZY0HF1dOSaQv8ObYvlWsX841XYAv5Btpi52jGuZPSH+QbERHBuXPnWLlypbFLETqwThd/3dzcmDdvHm+99RbfffddvcekNjalskLD6SMZDB3rSXLcVdrbsnsXT+egUMi5c2EAOzZdI7CXQ4cJKPB394iUw0iN9hxIGnNz18/1S/lMX+hPxME0Lp3NMXJ1zSeTwZAxHpw+nEFlhbS2xtDVivL222+zYMECXFxcjFBR81ilqTFRtnyBzKrK9rG4ZkfU6UIKwFNPPUVYWJjkpyMDXDydTUh/J/oOdSXqePtYLr+u8xFZmJjImLM8iMpyNdu/iu0QAaWuugFASoGlIwaTm9UElVn3dqPPYBciD6YRHXnrAdtSFTrMFZlMxsUz0g9YCQkJ7Ny5k8jISGOXInRwna67B6Bfv36MGjWK//znPw0ek9rYFLVaS/gvSQy6ww0HJzNjl9MipuYKNGoNcoUME1OFsctpU3XHeBg6JBjztY3JxFSOXC5Dq9FiZtE+P3c5upgzYIQ74b8kNWuNIUPQdU185ZVXGDduHL179zZCRUJn0ilDCsCzzz7L5s2bycmR/qeWjBslXDidw9gZ3rWLfLUXNWNQtn0Rw9ljmcy8JwDXOmNUOrqbg4O+wkNbnbe9cfOyZMbiAE4fyWDbFzGNDqaVMrkcxt7pTXREVrsY6JuVlcX333/Ps88+a+xShE6g04aUO+64g969e7N27Vpjl9IkEQfTMDVT0G+oq7FLabKbB8mePZ7JqUPp3Lm4G+5dpNMtYmi6AsbNN8u/Fn+zTNb9uAAeXa24c1EAEQfSOXcy67azfqQqNMwNE6WMCD3uJN6WXnvtNUJDQxk2bJixSxE6gU4bUqC6NeXLL7+kqKj+Wh5S6/IBUFdVd/sMvMMNB2fpd/s0NovnfGQ2J8JTmb7QH99AsZuo0DJ+QXZMu9ufo3tvcOH032NQ2ltQcXQxp/8IN8J3JqGR4IJzN18LVSoVGzduFK0ogsF06pAydepUPD09effdd41dSpNk3Cjhwqlsxt4p7W6f200zvngmh/Bfkhg/y4f+w9pPy5AgDQNGuDFupjfhO5Nq90iqq70EFbkcxs7w5nxEFplpLd89vK3o+rD2zjvv4OPjw6RJk4xQkdAZdeqQIpPJeOaZZ/j000+pqKj/ZirF1hSAiIPp1d0+YdJ8c2/qOihxVwrY/vU1QgY4M2G2DyYmEk5dgiSYKOVMnONDj35ObP8qlrirjS/B3R6CSugwNxQKGZHtpJunvLyczz77jGeffRaZlD8lCR1Kpw4pAHfddRempqY6956QYlBRq7X8uTOJgXe44+Bsbuxy6mnuQm05GaVs+yIGa1sls5YGYmUjtnkXdLO2VTJ7aTcsrJRs+/IqOZm33xlYykHFydWc/sPdqmfztINuHoCPPvoIa2tr5syZY4SKhM6q04cUExMTXnjhBd555x3KyqS9JXqNzNQSoiOzGCeh2T4tXUm2tKSKHd9cJzujlLtWBOlcRl/o3Ny7WDHvviAyU0v45dvrlJU0fWEtKQaVmtk8509mkiXBbh5dSkpKeOedd3jhhRdQKDr2MgKCtHT6kAKwdOlSbGxsdM70kWJrCkDkwXRMlHJCJdDt09ql7jUaLQd+S+b0kQxmLA4guI9DG1QptEfd+zpy5yJ/Ig+lc3BXSovWEJFaUAkd5oZcISPycIaxS9FJ1zXv9ddfx9HRkUWLFhmhIqEzEyEFUCgUrF27lv/+97/k5+cbu5wmqVnkbcAd7ji6GK/bR5978USfymbX1niGT/Bi2HhPybQSCYYnk8HwCV6EjfPkt+/jW70Kq1SCSm03j0Rn8+iSk5PDRx99xBtvvCFaUQSDEyHlLzNmzCAwMJAXXnihwWNSbU3JTC0hOiKLsTO8kSsM/47eFpsFpsQXse3LGLwDbJh9byD27XSVXaHlHJzNmLMskC5+1vz4ZQypiUW3f1ITGDuoKBQyxs7w5tzJTLLSpdnNo+ta98ILL9CzZ0+mTp1qhIqEzk6ElL/IZDLefPNNvvzyS1JSUoxdTpNFHkoHLYya0sWgr9uWuxmr8irY+kUM6cnF3LUiiH5DXUSrSicgk1XvXzNvRTCpiUVs+yIGVb5+f7eMGVRGT+uKukrLKYl28+iSmJjIxo0beeutt8SMHsEoREipY+TIkdxxxx0888wzDR6TamuKWq1l19Z4vANs6TPI2SCv2ZYBpYa6SsuxP1P5ZXMcPUOdRKtKB1fTetK9jyM7N13jeHga6jbqDjFGUOk7xAUvX2t2b4uXbDePrmvcmjVrGDt2rFhdVjAaEVJu8sYbb/DDDz9w5coVY5fSZMWFlezaGs+QMR509bdp09cyRECpKz2lmB/WXyU9RbSqdEQyGYSG/dV6klTMD59fJeNG2+9fY8ig4h1gw+BR7uzeGk9JUVWbvpY+XbhwgZ9++qndbB0idEwipNykT58+zJ07lyeffLLBY1JtTYHq8SmHdqUwYbYPdg6mbfIahg4oNaqqtBzbV6dVZWkg9o6iVaW9c3D6q/Wk31+tJ3+moq4yXCuDIYKKvZMZE2b7cuC3ZEmuKltD17XtqaeeYsGCBYSEhBihIkGoJkKKDq+//jrh4eHs3r3b2KU0y9XoPC5H5TJ1gT+mZvr9pzVWQKmrtlXlRjF3/aO6VUUufoPbHbkc+oW5Mm9FEGlJ1f+mhmg90aUtg4qZuYKp8/24eDqb2Iv5ej23PukKKDt37uTQoUO8+uqrRqhIEP4mLvE6eHt788wzz/DYY4+1m+Xya5wIT0WVX8GE2b566xaRQkCpUduq8l0cPfo5cfcD3QnoYW/UmoSm6xZiz8IHe9C9jyO/bL7OMQO3nujSFkFFJoOJc3zIzynn5IE0vZzTUMrLy1m9ejXPP/88XboYdkC+INxMhJRGPPXUU1RVVfHaa681eEzKQUWrhb3bE7G1N2WoHi64UgoodaUnF7Pl0yucPZHJ8AmezLsviC5+1sYuS2hEV38b7loRxLBxnpw5lsH3n10hPcU4rSe66DuohI3zxMrGlL0/J6KV5jhZQPe17JVXXkEul7N69WojVCQI9ZkYuwCpMjMz4+OPP+auu+5ixYoVdO3a1dglNVlFuZrff4hn7vJAcrLKiInOa9F5pBpQami1cPlsLrHRefQe5MLEOb5kpZdyIjy13Sw33tG5eloydKwHzm4WnDmaQfSpbKO3nDSmJqjMXNINgJP7W9YC0r2vI937OrLtyxgqKzT6LLHNxcfH88EHH7B9+3ZMTdtmbJsgNIdoSbmFyZMnM27cOB5++OEGj0m5NQWgILecvdsTGTWlC66ezd8PR+oBpa6qKi1nj2fy7ceXyUotYdaSbkyc44OdGFxrNPaOZkya68vMewLIuFHCpo8uE3UiS7IBpUZrW1Tcu1hyxyQv9vyYgErifze6rmGPPPIIkyZNYvz48UaoSBAaEiHlNj744AP27t2rcxCt1INKclwhJw+kM+Uuv2btMNyeAkpd5WVqTuxPY/O6K5SXqVmwMphRU7pgbSt2VzYUazslo6Z2Yf7KYEpLqvj2f5c5uT+NivKmbwpobC0NKta2SibP8+NEeBo3EvSzSm5baWyw7P79+3nvvfeMUJEg6CZCym34+PjUDqKtqmo/axzUOB+RRdJ1FZPn+WKivP0/d3sNKHUVF1Zy8PcUflh/FTNzBYtX9WDiHB/cu1gZu7QOy6OrFZPm+rL4nz0wNVPw/WdXOLQrpV2tC1JXc4OKiVLO5Lv8SIhVEX0q2wAV6ldFRQX/93//x/PPP9+uuraFjk+ElCaoGUT70ksvNXhM6q0pAAd3pVBVqWHKfD8UJo1P+ekIAaWu/Nxy/tieyOZPrlCkqmTa3f7Muy+IoN4ORtnrqKNRKGQE93HgrhVBTJnvhyq/gs3rrrB3e2KH+f1pSlAxMZExbYEfFWVqDu2S/pYauq5ZL774IjKZTAyWFSRHptVKeey5dBw4cICpU6dy/Phx+vbt2+DxSYMaBhgpMVHKuXORPxVlanZtS2iwNHdHCyi6mCjldO/jSO9BzphbmnD1fC6Xz+aQl1Nu7NIaUJrKWfn/+rD+zfOSG3zp4GxOz1Angns7UFpSxfmILK5G51FVKa069cXe0YyZS7px5Xxug8G0CoWMKfP9MFHK+fW7OMn/DHQFlDNnzjBixAj27NnDHXfcYYSq2o5KpcLOzo4hd76CibLlu8VXVZZx8pfnKSgowNbWVo8VCrcjZvc00ejRo1m+fDnLly8nMjKy3W1ZXlWp4bctccxY3I2Js33446cENH9dTztDQIHqn8GF09lcOJ2Np481PUMduWtlMFlpJVw6m0P81QIqyqX9JmMspmZy/ILt6RnqiIu7Jdev5LNrWzxpScXGLq3NNTbrRy6XMXGuL6ZmCn7ZfF3yAUWXqqoqli1bxsqVKztcQBE6BtGS0gxFRUX07t2be+65h1deeaXB41JvTYHqVTBn3tONvJwy9v2cyJAxnSOgNMbMXEFwbwe693PCwdmM1MRiEmILSIhVUajnHXibQwotKTb2pvgG2uIbZIentzV5WWVcjsoh5kIe5WXtZyCsvtRtUYk4kMbEOb7Y2puy89vr7eLn0dgGgj/88APR0dFYWjZ/FqDUiZaU9k+ElGY6ePAgU6ZM4dixY/Tr16/B4+0hqJhbKpi1pBtabfWbdGcNKDez/etN2eevN+X87DISYguIj1GRmWrYhceMFVLcvCzxDbLDN9AWe6e/QlvMX6GtQPyO1ASVstLqAcE7vrlGWWn7DCg13Tx79+5l+PDhRqiq7YmQ0v6J7p5mGjVqFCtWrGD58uWcOnWq3XX7AJSVqElJKKJXf2cSrxWgMmKLgZSo8is4H5nN+chsTM0UeAfY4Btky/SF/mjUWhJiVSTEFJCWXNwuPjk3hZm5Ag9vK/yC7PDpZotcISPpmopThzNIjlOJ7q+bqPLLyUorwTvAlujT2e0ioOhS083zwAMPdNiAInQMIqS0wNq1a+nduzcvvvgi//nPf+o9tifyRcm3pgwd64F/sB3bv45h9DRvJsz2Yd/PibVjVITqVXuvXcrn2qV85HJw72qNb6AtwyZ4Ye9oRkFe9ZtVVlopWenV/5V6cDEzV+DiYYGLhyUu7pa4eFhg52BGfk4ZCbEq/tieSHpykfg9aIRcLmPCbB9s7EzZ/nUsk+f5UVWpafHKtIaiqxXlueeeo6SkRGwgKEieCCktYGVlxcaNG5k8eTJz584lNDS03uNSDio3D5Ld8c017lwcwMS5ftWDadWi9+9mGg2kJhaRmljEsX2pmFso/nqjt8DV05KQAU7Y2pv99Sm7tDq8pJeSk1lKaXGVwfdukcnAwsoEJ1cLXNz/CiUeFtja14Sr6mB16Ww2WemllLfT1gBDUihkTJrni6WVkp83XaO8VK2XJfTbmq6Acvr0aT788EP27t3bIcehCB2LCCktNHLkSB544AEWLVrE6dOn28Ufu65ZPGWlanZuus70hf5MucuP3dviJb90ubGVlapJjiskOa6w9j4zC8XfgcDdkh6hTtg5mKHRaCktrqK4qJKSokpKiv76/8LKv+6roqSokspKDVqNFo0GNBpt7Q7WcoUME6UcuRxkchlKpRxLayWW1iZYWSuxtFFiZa3Eytrkr/uVWFiZIJfLalt7MlNLuHgmu1209kiRiUn1NGOlUsHOb6/Xrp6rr71+DKm4uJhFixaxatUq0c0jtAti4GwrlJeXM3ToUHr16sU333zT4HEptabcbpqx0lTO9IX+qNVadv0QL7m1OdojuUL2d5iwVv4VKv7+uuYxCysTZLKmLS6n1dYNPdUBp7iokuLC+l+XFFWJVjE9UJrKmbrAH4Dfv4/T+Xdxq3VUjElXK8rChQu5du0aR48e7RQbCBpr4Oy6detYt24dCQkJAISEhPDCCy8wZcqUesdptVqmTp3K7t272b59O7NmzQLg3LlzrF27liNHjpCdnY2vry8PPvggjz32WIu/h/ZKtKS0gpmZGVu3bqV///5s3LiRZcuW1XtcKt0+TVkHpbJCwy+b45hyly9z7g3k963xRp2C2xFo1FqKCiopKqi85XEyWXWgkcurbzI5fy3n35Nv/nuRinINGo22+qbWGrz7qLOydTBlyl1+FBdWsntrPFWNtDBKsUVFV0D5/PPP+f3334mKiuoUAcWYunTpwtq1awkMDESr1fLVV18xc+ZMzp49S0hISO1x77//vs4PKKdPn8bV1ZVNmzbRtWtXjh07xv33349CodC54W1HJlpS9GDLli088MADREREEBwc3OBxYwaV5i7UJpfDsPFeBPZyYM+PCaQmSnujtI5KCuukdGZevtZMmuPL1ehcju1LbVIwlEqLiq6AcvHiRcLCwvjyyy+ZN2+eEaoyDilNQXZ0dOStt95ixYoVAERFRTF9+nROnTqFh4dHvZYUXR566CEuX75MeHh4i16/vRJ79+jB3XffzYIFC5g/fz7l5dJZYr0lK8lqNHDkjxuc2J/KtAV+hPR3auMqBUFaeg1wZup8P479mcrRvU0LKNDy3ZPbWllZGQsWLOCee+7pVAGlLahUqnq3plzv1Wo1W7Zsobi4mLCwMABKSkpYtGgRH3/8Me7u7k167YKCAhwdHVtVf3skunv05IMPPmDgwIE8/PDDrF+/vt5jxuj2ae1S95fP5pKfXc7keX44uVpw5I8UMTVV6NDkchl3TPbCL8iOXzbHkZ7S/CX/jd31o6sVZdWqVcjlct59912D1iIlVinFmChaPmi8Sl0G0GCH6BdffJF///vfOp8THR1NWFgYZWVlWFtbs337dnr27AnAE088wbBhw5g5c2aTXv/YsWN8//33/Pbbby3+HtorEVL0xMLCgm3btjFo0CDGjx/PggUL6j1uyKCir7140pKL2frlVabO9+fORQHs+TGh3S5eJQi3Ym6pYPI8P5RKOdu+jKFIdetxRLdirKCiK6Bs2rSJrVu3cvr0aczNW97dIVRLTk6u191jZmbW6LHBwcFERUVRUFDAtm3buPfeezl48CDXrl0jPDycs2fPNuk1L1y4wMyZM3nxxReZOHFiq7+H9kZ09+hRjx49+Pjjj3nwwQe5fPlyg8d1XUT0Td+bBRYVVPLTxljKStXMWxGEo4u40Akdi5OrOfPuC6aksJLtX8W2KqDUMHTXj65ry4ULF3j44YdZt24dQUFBbV5DZ2Bra1vvdquQYmpqSrdu3RgwYACvv/46ffv25YMPPiA8PJzr169jb2+PiYkJJibVbQVz585l9OjR9c5x6dIlxo0bx/33389zzz3Xlt+aZImQomf33nsvixcvZsaMGeTn5zd4vC2DSlvtZlxVqWHPjwlcOZfLnGWB+AXZ6e3cgmBM/t3tmH1vIJfP5vDH9sRGZ/C0hKGCiq5rSm5uLjNnzmTZsmXcc889bfbaQtNpNBrKy8t5+umnOX/+PFFRUbU3gPfee48NGzbUHn/x4kXGjBnDvffe26lXBhbdPW3gvffeY+LEicyZM4e9e/caZH+ftgoodZ06nEFuVhnjZnpz9ngmp49ktMnrCIIhDLzDjX5DXflzRxLxMQVt8hpt3fWjK6Co1WrmzJmDn58fb7/9tl5fT2iaNWvWMGXKFLy9vSksLGTz5s0cOHCAPXv24O7urnOwrLe3N35+fkB1K9jYsWOZNGkSq1evJj09HQCFQoGLi4tBvxdjEy0pbUCpVLJt2zbi4+N59NFHGzyu79YUQwSUGnFXCtj+VSw9Q52YONsHE6X4FRLaFxOlnElzfene15GfNsa2WUCpYeiun1WrVpGcnMzWrVtruxIEw8rMzGTp0qUEBwczbtw4IiMj2bNnDxMmTGjS87dt20ZWVhabNm3Cw8Oj9jZo0KA2rlx6xDopbejixYsMHTqUt99+mwceeKDB4/oYSGvIgFKXhaUJE+f6Ym2jJPyXJNKSmz8TQmicWCelbXh6WzHmTm8KCyr4w8ADwfW9joquDzsfffQRzz77LCdOnKBHjx6tfo32rmadlLGhT2OiaMU6Keoyws+ubdU6KULLiI/BbSgkJITNmzezevVqDh061ODx1raoGCugAJSWVLFz0zUunM5m+kJ/hk/wxMSkaUu7C4KhmSjljJjoxbS7/YmOyGLnpusGn6mmzxYVXdeOAwcO8P/+3//ju+++EwFF6DBESGljd955J88++yzz588nMTGxweMtDSrGDCg1tFo4dzKLrZ/H4OZpxfyVwbh3sTJKLYLQGA9vKxasDMbZ3YIf1l/lfGS20WrRR1DRdc1ISEhgwYIF/Pvf/2bq1KmtLVMQJEOEFANYs2YNY8aMYfr06RQUNOz/bm5QkUJAqSs/t5ztX8dy8UwOdy7yZ9h40aoiGF9N68n0u/2JPpUtqb+XlgYVXdeK/Px8pk6dyvjx43nqqaf0VaYgSIIIKQYgk8nYsGEDjo6OTJ06VedSyk0NKlILKDXqtqq4e9W0qlgauyyhk/LoWt164uLxV+tJRJakNmZsSVDRdY0oKytjypQpuLu78+WXXzZ5N21BaC9ESDEQc3Nzdu7cSWFhIfPmzUOtbtgffrugItWAUldNq8qlszncuSiAYeM9UYhWFcFATExkDJ/gyfSF1a0nP38t7b+VpgaVW001Lisr4+eff77lwmKC0F6JkGJAdnZ27Nmzh+joaFauXKnzmMaCSnsIKDW0Wog6kcXWL2Jw7yJaVQTDcO9qxfz7u+PqackPn8dIrvVEl6YEFV3XBI1Gw/Lly7ly5Qq7d+8WM06EDkuEFAPz8PBg79697Ny5kzVr1ug85uaLUnsKKHXl55Sz/atYLte0qozzFOuqCHpnopQzbLwndy705+Lpv1pPcqWzG/nt3CqoNPah5emnn2b37t3s3bsXNzc3Q5QpCEYh3jGMIDAwkD179vDRRx/xwQcf6Dym5uLUXgNKjbqtKm5dLFm8qgch/Z2Qi988oZXkcggZ4MQ9D/XAzcuSrZ/HcO6k9FtPdNEVVBoLKO+88w6ffPIJe/bsISAgwJBlCoLBieUIjWTAgAH89NNPzJw5E1dXVxYuXFjvca1Wy7sb5xF15lK7DSh1VbeqXMO/ux1DRnvQd4gLJw+kc/1yvrFLE9qhbiH2DBnlgUaj5eCuFOKvtu2qsYZQdwn9u5eNQKvVNhgIu2nTJp5//nl+/fVXQkNDjVSpIBiOCClGNGHCBDZs2MDy5csxMzNjzpw5QHVAuXTpEikpKcycPYWvP3zHyJXqT9yVAuKvFtC9ryPDJ3gSGubKif2ppMQXGbs0oR3o6m/D0DEeWFiZEHEwnavnc9tly0lj8nPLuXPmJI4ePQpU76xeE1S2bt3K/fffz9dff83YsWONWaYgGIwIKUa2YMECysvLWbJkCQqFghkzZtQGlOHDh2Ntbc2eyBf1soS+VGi1cDkql5gLefQe5MLEOb5kpZdyIjyVrLRSY5cnSJCrpyVDx3rg7GbBmaMZRJ/KRq3HHYuloqaLZ/jw4fWCyvbt27n33ntZv3498+bNM2aJgmBQIqRIwNKlS1Gr1SxatIj3338fb2/v2oBSo6MFFQB1lZao45lcPptDaJgrs5Z0I/GaipMH0tvVwEeh7dg7mjFkjAfeATacj8xm99YEKsoNu5y9odQdg2JjY1MbVA4fPszq1atZt24dixcvNmKFgmB4YviiRCxfvpx3332Xxx9/nMLCwnoBpYa+d0+WivIyNSf2p7F53RXKy9QsWBnMqCldsLQWGbqzsrJRMmpqF+avDKa0pIpv/3eZk/vTOkVAqWFjY0NBQQFPPPEE77//Pvfee68RKhME4xLvAhLywAMPIJPJuPfee1EqlcycObPBMR2xRaVGcWElB39P4dyJLAaP9mDxqh5ER2ZzPjKLkqIqY5cnGICltQl9B7vQa5ALiTEFfP/ZlXY/aPx2Gvvw8eOPP3Lffffx0Ucfcd999xm4KkGQBhFSJOb+++9HqVSycOFCvvnmG+bOndvgmI4cVKB68OAfPyXg6mHBwJHuLHm4J9ev5HM+IpvM1BJjlye0ATcvS3oPciGgux1JcYX8/FUsWekdf3xSYwHlhx9+YNmyZXzyyScsXbrUwFUJgnSIkCJBy5cvx8TEhCVLllBcXKzzItXRgwpAZlopv38fj52DKb0HuTBjcQC5WWWcj8gi7ko+Go2xKxRaQy4H/x729B3sgoOzOZejcvnu0yuoOnjLSY3GAsqXX37Jww8/zPr168UYFKHTEyFFopYsWYKlpSVLliwhIyND5+6mnSGoABTkVXDkjxtEHEyje18nhozxYNh4Ty6eyeHKuVyKCyuNXaLQDFY2Snr0c6RnqBPqKi3RkVlcPpdLZUXnSZ2NBZTXX3+d//znP3z77bfMnj3bwFUJgvSIkCJhc+fOxcnJiZkzZ5Kens5bb72F/KalWjtLUAGoKNdwPiKL6MgsfLrZEjLAmYF3uJF0vZBLZ3NIuqbqUGtmdCQyGfgE2tIz1Imu/jakxBVycFdKp/w3a2wvntWrV7Nx40Z27drFyJEjjVCZIEiPCCkSN3r0aA4dOsTEiRPJyMjgq6++QqFQ1DumMwUVqF5nJSFWRUKsCms7JT36OjFqShcArpzL5XJULoUFnaPLQOps7E3p0c+RHn2d0Gi0XI7K4dCuFIpUnbP1S1dAqaqqYsmSJezfv5/Dhw/Tu3dvI1QmCNIkQko70LdvX06cOMH48eOZNm0aP//8M+bm5vWOqbn4daawAlBUUEnkoXROHU7HO8CWHqFOLFrVnay0UhJiCkiIVZGbVWbsMjsVRxdz/ILs8Am0xcXDgsRYFft/TSI5rrDTtZrUaKx7p6SkhFmzZhEfH8+JEyfw9fU1bGGCIHEipLQTfn5+HD9+nMmTJzNq1Ch27dqFo6Njg+M6W6tKDa0WEq+pSLymwsLKBN9AW3wC7RhwhzslRZUkxKhIiC0gLalIDLjVM7lchqePFb6BdvgG2WJhaUJyXHUXXOIPKkpLOvf08cYCSk5ODpMnTwbg+PHjODs7G7IsQWgXxGJut/D6668zaNAgbGxscHV1ZdasWVy9erX28dzcXB555BGCg4OxsLDA29ubRx99lIKC+pudyWSyBrctW7bUO+all16iS5cujBgxgpiYGJ31uLq6cvDgQWxsbBg2bBixsbE6j+uoi741VWlxFZejctm9NZ4v34nmyJ4bmChljJ/pw/LVvZkw24fAEHvMzBW3P5mgk5m5gsBeDkyc7cPy1b0Ye6c3CoWMw7tv8OW7F9i9LYEr53JFQGnkb/Hq1asMGzYMBwcH9u/f32hAWbduHX369MHW1hZbW1vCwsLYtWtX7eOfffYZo0ePxtbWFplMRn5+foNz+Pr6Nrj+rF27tt4x69evx8fHh9DQUE6ePNnyb1gQ9Ey0pNzCwYMHeeihhxg0aBBVVVU888wzTJw4kUuXLmFlZUVqaiqpqam8/fbb9OzZk8TERB588EFSU1PZtm1bvXNt2LCh9lMTgL29fe3/Hz16lN9++40dO3Zw8uRJHn74Yf744w+dNdnY2PD777+zatUqwsLC+Pbbb5k0aVKD4zpri8rN1FXa2haWg6Tg4mGBb5AdoWFujJ3hQ3pyEfF/tbJ0lqmvLWXnYIpvkB2+QXa4d7EiN6uUhBgVZ49f6xRrmjRXYwHl999/Z8mSJcybN4+PPvoIpVLZ6Dm6dOnC2rVrCQwMRKvV8tVXXzFz5kzOnj1LSEgIJSUlTJ48mcmTJ7NmzZpGz/Pyyy+zcuXK2q9tbGxq/z8pKYk333yTLVu2cOPGDZYvX86lS5da8B0Lgv6JkHILu3fvrvf1xo0bcXV15fTp04wcOZJevXrx448/1j4eEBDAq6++yj333ENVVRUmJn//eO3t7XF3d9f5Onl5eXh6etKnTx+qqqrYuHHjLesyNTVl/fr19OnTh9mzZ/Of//yH1atXNzius45TuZWstFKy0kqJPJiOtZ0S327VXRRh4zxQ5VWQkVpCVloJWWmlZGeUUlXZOfuGTJRynN0tcHW3wMXDElcvS2ztTElJKOLapTz+3JHYaQe/3s6tWjLfeustXnzxRd5++21WrVp123Pdeeed9b5+9dVXWbduHSdOnCAkJITHH38cgAMHDtzyPDY2No1ef1QqFfb29vTp0wd3d3dKS0XgFKRDhJRmqOnG0TUWpO4xtra29QIKwEMPPcQ//vEP/P39efDBB1m+fHntFuyTJk3io48+wtLSEmtr6watMLrIZDIeffRRevbsyV133cX58+f57LPPMDU1bXCsaFXRraigkguns7lwOhulqRwvH2tcPC3x9rdhwHA3zC1NyM8pIyu99K9wU0JWescLLkrT6kDi4m6Ji0f1fx2czSgpqiIrvfp7vn45nxuJRZ1qLZOWaCygVFRUsGLFCn777Td+++03xowZ0+xzq9Vqtm7dSnFxMWFhYc167tq1a3nllVfw9vZm0aJFPPHEE7XXqF69etGnTx/s7OxqPwAJglSIkNJEGo2Gxx9/nOHDh9OrVy+dx2RnZ/PKK69w//3317v/5ZdfZuzYsVhaWvLHH3+watUqioqKePTRRwFQKpXs3r2bzMxM7O3tdQaNxowfP57IyEimT5/O6NGj2bFjBy4uLg2OE0Hl1iorNLXTmmtY2Shx+asloYufNaFhrlham5CfU05WWgmZaaVkpZeQnV7abt68laby2u+pJpDYO/0VSP4KYdcu5ZOVViL2S2qmxgJKeno6M2fOpKioiFOnTuHv79+s80ZHRxMWFkZZWRnW1tZs376dnj17Nvn5jz76KP3798fR0ZFjx46xZs0a0tLSePfdd2uP+eKLL3jzzTextLTEwsKiWfUJQluSabWddVJg8/zzn/9k165dHDlyhC5dujR4XKVSMWHCBBwdHdm5c+ct+5lfeOEFNmzYQHJyst7qU6lU3H333Vy8eJHt27fTv39/nceJoNI6ltYm1W/wNW/07hZY25pSXqamuLCSkqLqW3FRVf2vC6vva2orjNJUzsr/14f1b55vUgBSmsqxtFZiZW1S/V8b5d9f2yixsq7+2sxcQZGq4q/Woepurax0EUha41bdO6dOnWLOnDn07duXzZs31xsL0lQVFRUkJSVRUFDAtm3b+Pzzzzl48GC9oHLgwAHGjBlDXl5evfFuunz55Zc88MADFBUVYWZm1ux62hOVSoWdnR1jQ5/GRGF++yc0okpdRvjZtbUt5YLhiJaUJnj44Yf59ddfOXTokM6AUlhYyOTJk7GxsWH79u23DCgAQ4YM4ZVXXqG8vFxvFwlbW1t++eUXnnnmGUaNGsVbb73Fgw8+2OA4MU6ldUqKqkiMVZFYp8XF3EKBlU3dYKDE0toEj65W9cKCwkRORbm6NsSUFFVSWaFBq9Gi1mjRarRoNKDVaKG6J5BBI93Raqv3uZHJZSjkMmRyWYNQYmqmQF2lqT5vYSXFf4WjvOxyUhKKagNTcWElZaVqI/30Op5bBZSPPvqINWvW8Mgjj/Cf//ynwWrRTWVqakq3bt0AGDBgAJGRkXzwwQd8+umnLTrfkCFDqKqqIiEhgeDg4BadQxAMRYSUW9BqtTzyyCNs376dAwcO4Ofn1+AYlUrFpEmTMDMzY+fOnQ0WWdMlKioKBwcHvX+KUSgUvPHGG4SFhbFs2TLCw8P58ssvsba2bnCs6P7Rn7JSNWWlanIyb71onJm54q/QYlLbsmGilNcGELlchkIhQ6aUYaKsfkNTmspRV2nRaLSoKzVU/hVkqio1lBSpKC6qpLiwOvCUl4nwYUiNBRSVSsXy5csJDw9n8+bNDQa/tpZGo6G8vLzFz4+KikIul+Pq6qrHqgShbYiQcgsPPfQQmzdvZseOHdjY2JCeng6AnZ0dFhYWqFQqJk6cSElJCZs2bUKlUqFSVX/CdnFxQaFQ8Msvv5CRkcHQoUMxNzdn7969vPbaazz55JNtVvesWbM4d+4cCxYsIDQ0lC1btjBgwIAGx4lWFcMqL1NTXqYmN+v2xypN5fTo68SxfantZrxLZ3Gr1pOIiAgWLlyIm5sb58+fp2vXrq16rTVr1jBlyhS8vb0pLCxk8+bNHDhwgD179gDV413S09O5du0aUD1+xcbGBm9vbxwdHTl+/DgnT55kzJgx2NjYcPz4cZ544gnuueceHBwcWlWbIBiCCCm3sG7dOqB6/5y6NmzYwLJlyzhz5kztwkc1zbE14uPj8fX1RalU8vHHH/PEE0+g1Wrp1q0b7777br01C9qCj48Phw8f5rnnnmPkyJG88sorOqcpg2hVEYSmaiygaDQa3nnnHV588UUef/xxXn755QYz/FoiMzOTpUuXkpaWhp2dHX369GHPnj1MmDABgE8++YSXXvr7b7dmY8Kaa5SZmRlbtmzh3//+N+Xl5fj5+fHEE080ei3oqGQJacjkTZ+Q0OD5GrGGkrGIgbOdwO7du7nnnnsICwvjm2++ueXAOhFWpKG5A2eFtnWr1pPc3FyWLFlCREQE3377LRMnTjRgZcKt1AycHedwLyatCClVmgr+zPtKDJw1ArEsficwefJkzp8/j0qlol+/fvz555+NHtvZl9QXhJvd6m/ijz/+IDQ0lJKSEqKjo0VAEQQ9EyGlk/D09CQ8PJyVK1cyffp07r//fkpKSnQeuyfyRRFWhE7vVn8HxcXFrFixgpkzZ/Lggw+yb9++Rld0FQSh5URI6UQUCgXPPvssERERREZG0rt3b8LDwxs9XgQVobO61e/+vn376N27N1FRUZw6dYo1a9agUIjNKgWhLYiQ0gn17t2biIgIli1bxrRp03jggQdEq4ogcOvf95KSElauXMmdd97JihUrOHnyJCEhIQauUBA6FxFSOimlUsnzzz/PyZMnOXnyJH369LnlJmUirAgd2e1+v//880969erF6dOniYyM5Nlnn9XL7B1BEG5NhJROrk+fPkRGRrJkyRKmTJnCypUrazdS1EUEFaGjudXvdEFBAStWrGD69Oncd999nDx5stG9uwRB0D8RUgSUSiUvvvgiJ06cIDo6muDgYNavX49Go3vqq2hVETqCW/0eazQaPv30U4KDg7l8+TIRERE899xzt93yQhAE/RLtlUKtvn37cuzYMb766iueeuopvvzyS/73v/8RGhqq83ixYq3QHt0uYJ8+fZpVq1YRFxfHO++8w5IlS5DJZAaqThCEukRLilCPXC5n+fLlxMbG0r9/f8LCwrj//vtv2wUkWlYEqbvd72l+fj4rV65k+PDhDBkyhNjYWJYuXSoCiiAYkQgpgk4ODg58/PHHHD9+nPPnz9+2CwhEWBGk6Xa/lzVdO927d+fixYucPHmSDz/88JYrMwuCYBgipAi3FBoayrFjx1i7di1r1qxh0KBBtZubNUaEFUEKmvJ7uGfPHgYOHMhzzz3Hm2++ydGjR+nbt6+BKhQE4XZESBFuSy6Xs2zZMq5fv87kyZOZM2cOY8eO5dSpU7d8nggrgjE05fcuIiKC0aNHM2fOHKZNm8a1a9dE144gSJAIKUKT2dnZ8eqrr3Lt2jWCg4MZPnw4c+bMITY29pbPE2FFMISm/J5dvXqVmTNncscddxASEkJcXByvvPIKdnZ2BqpSEITmECFFaDYPDw/WrVvHxYsXMTExoU+fPtx3332kp6ff8nkirAhtoSm/V2lpaSxbtoy+fftiYWHBpUuX+Pjjj3FzczNQlYIgtIQIKUKLdevWjR9++IEjR46QlJREYGAgjzzyiAgrgkE0NZw89NBDBAUFkZqayvHjx9myZQsBAQEGqlIQhNYQ66QIrTZgwAD27dtHeHg4L7/8Mv7+/syfP5/nn3/+lm8Gdd9gxForQlM0Ndxeu3aNV155ha1btzJ06FB++eUXRo8e3bbFCYKgd6IlRdCbsWPHcuDAAfbv309ubi4hISHMmzePc+fO3fa5onVFuJWm/n5ERUUxZ84cQkJCKCgo4ODBg4SHh4uAIgjtlAgpgt4NGTKEnTt3cvr0aczNzRk8eDCTJ0/myJEjt31uzZuRCCxCc34XDh06xKRJkxgyZAjW1tZERUXx888/M2jQIANUKghCWxEhRWgzISEhbNq0iatXrxIQEMCECRMYNmwYmzZtQq1W3/b5Iqx0Tk39d6+qquKbb74hLCyMSZMmERQURExMDF9//TU9evQwQKWCILQ1mVar1Rq7CKFzyMzM5JNPPuF///sfJiYmLF26lMcee6xZMyw6y9gVpamclf+vD+vfPE9lReOr/HYUzQmjGRkZvP/++3zzzTeo1WpWrVrFgw8+iIuLSxtWKLRHKpUKOzs7xjnci4nctMXnqdJU8GfeVxQUFGBra6vHCoXbESFFMLjKykq2b9/OBx98wJkzZ5g0aRIPP/wwY8eORS5veuNeRw4snSGkNCeYaDQa9u7dy//+9z/++OMPBg4cyKOPPsqsWbPEzsRCo0RIaf/E7B7B4JRKJfPnz2f+/PmcP3+eTz75hNmzZ+Pp6cmSJUtYuXJlk1pXxOyg9qe53XcZGRl89tlnbNq0ibS0NJYsWUJERAS9e/duowoFQZAS0ZIiSEJRURFbtmxh3bp1REdHc8cdd7Bw4UIWLVqEpaVls8/X3kNLR2lJacmYouLiYjZv3sx3333HkSNH6Nu3Lw8++CB33303VlZWbVCl0FGJlpT2T4QUQXJiYmLYtGkT33zzDTk5OUyYMIGlS5cyffp0FApFs8/XHgNLew4pLQkmarWanTt38s0337B3715cXFxYunQpixcvJjAwsA2qFDoDEVLaP9HdI0hOUFAQL7/8Mi+99BInT57km2++4b777kOpVDJ9+nSWLl3KiBEjmjx+RdebZnsMLlLUmtlXGo2Gw4cP8/XXX/Pbb79RVVXFwoUL2bdvH4MHDxab/QmCIEKKIF0ymYyhQ4cydOhQ3n//ff744w+++eYbpk6dio2NDaNGjWLmzJnMnDmz2V1CN7+5itDSNK2dEl5cXMyOHTv4+eefOXToEMXFxUyfPp0NGzYwfvx4MQhWEIR6RHeP0O6Ul5dz4MABdu7cyY4dO8jLy2Po0KFMmzaN+fPn06VLF728jjGDixS6e/S1Rk1KSgrff/89v/32GydOnMDJyak2XI4aNQpT05Y3wwvCrYjunvZPhBShXdNqtZw/f54dO3awY8cOzp07R69evbjjjjsYP34848eP1/tgS0OEF0OGFH0vmFdcXMy+ffvYu3cvR44c4cKFC/Tr1682mPTu3Vt05QgGIUJK+ydCitChpKam8vvvv7Nv3z72799PQUEBvXv3JiwsrDa0tGS2UHO1NsjoK6QYYsXemlCyb98+Tpw4wfnz53FwcGDMmDGMGzeOadOm4eHh0eZ1CMLNREhp/0RIETosrVZLTEwMBw4cIDw8nP3796NSqejdu3ftWJcRI0bg4+Nj7FIbqKys5Pfff2fq1KmSG6eRmJjIkSNHOH78OCdOnCA6Ohp7e3vGjBnD2LFjGT16NIGBgaK1RDA6EVLaPzFwVuiwZDIZwcHBBAcH88ADD6DVarl69SoHDhzgwIEDvPDCC8TFxeHq6kqPHj3o06cPgwcPZsSIEfj6+hq7fEmIj4/nyJEjREREcP78eS5fvkxWVhYBAQEMGjSIlStXMnr0aIKCgkQoEQRB70RLitCpqVQqzp49y+nTp4mMjOTUqVNcv34dZ2dngoODCQgIICgoiJCQEHr16oWfn1+zlu5vKUO2pGg0GuLi4oiOjuby5cvExMQQFxfH5cuXycnJoVu3bgwcOJBBgwbRv39/QkNDxadJoV1oDy0pM2bMICoqiszMTBwcHBg/fjxvvPEGnp6eDY69du0aoaGhKBQK8vPzdZ5vy5YtLFy4kJkzZ/Lzzz/X3p+RkcG//vUv/vjjD/Lz8xk5ciT//e9/Jb8OkQgpgnCTwsJCoqKiiIqK4urVq1y5coWYmBhSUlIwNzfHx8cHb29vAgIC6NatG127dsXb2xsfHx9cXV31EmL0GVI0Gg0ZGRkkJiaSnJxMcnIysbGxxMXFkZiYSFJSEmVlZXTp0oWgoCC6d+9OcHAw/fr1o1+/ftjY2LT6+xEEY2gPIeW9994jLCwMDw8Pbty4wZNPPgnAsWPH6h1XWVnJsGHDcHFx4dixYzpDSkJCAiNGjMDf3x9HR8fakKLVahk2bBhKpZJ33nkHW1tb3n33XXbv3s2lS5ckvZKzCCmC0ERlZWVcu3aNmJgYYmJiuHr1KrGxsaSmppKRkUFJSQmmpqY4OTnh4uKCs7Mzrq6uuLq6Ymtri42NDba2trU3Ozs7bG1tsbe3x87ODqVSiUKhQC6Xo9Fo2LVrFxMnTkShUKBWq6msrKSgoID8/HxUKhUFBQWoVKraW2FhISqViszMTDIzM8nKyiI7O5ucnBwqKiqwsrLCzc0NDw8PgoKCCA4OJigoiKCgIAICAjA3Nzf2j1gQ9Ko9hJSb7dy5k1mzZlFeXl7vA8q//vUvUlNTGTduHI8//niDkKJWqxk5ciT33Xcfhw8fJj8/vzakxMTEEBwczIULFwgJCQGqP7y4u7vz2muv8Y9//KNNv6fWEGNSBKGJzM3N6dWrF7169dL5eGFhIWlpabW31NRUUlNTSU9PJyEhgcLCQgoLCykqKqr9b3FxMVVVVc2qw8TEBCsrK6ytrbGxsan9r62tLdbW1nh5eTF48GA8PDzq3USLiNBZVWkroBUz+au0FUB16KnLzMwMMzOz1pRWT25uLt9++21tq0eN8PBwtm7dSlRUFD/99JPO57788su4urqyYsUKDh8+XO+x8vJygHofRORyOWZmZhw5ckSEFEHoDGxsbLCxsSEoKKhZzysvL6e4uBi1Wo1Go0Gj0aBWq5HJZMjl8tqbQqHAyspKrxdFQejITE1NcXd352D6d60+l7W1NV27dq1334svvsi///3vVp/7X//6Fx999BElJSUMHTqUX3/9tfaxnJwcli1bxqZNmxptxTly5AhffPEFUVFROh/v3r073t7erFmzhk8//RQrKyvee+89UlJSSEtLa3X9bUmEFEEwMn1/GhMEoZq5uTnx8fFUVFS0+lxarbbBDLbG/m6ffvpp3njjjVue7/Lly3Tv3h2Ap556ihUrVpCYmMhLL73E0qVL+fXXX5HJZKxcuZJFixYxcuRInecpLCxkyZIlrF+/HmdnZ53HKJVKfvrpJ1asWIGjoyMKhYLx48czZcoUpD7iQ4xJEQRBEAQ9ysrKIicn55bH+Pv769wSIiUlha5du3Ls2DHCwsKwt7enqKio9nGtVotGo0GhUPDZZ5/Vzriru0O8RlPdtyWXy7l69SoBAQG1jxUUFFBRUYGLiwtDhgxh4MCBfPzxx639ltuMaEkRBEEQBD1ycXHBxcWlRc+tCRg140iOHz+OWq2ufXzHjh288cYbHDt2DC8vLywsLIiOjq53jueee47CwkI++OCDBl1UdnZ2AMTGxnLq1CleeeWVFtVpKCKkCIIgCIIRnDx5ksjISEaMGIGDgwPXr1/n+eefJyAggLCwMAB69OhR7zmnTp1CLpfXG8B/82B+e3v7Bvdv3boVFxcXvL29iY6O5rHHHmPWrFlMnDixjb47/Wj7VakEQRAEQWjA0tKSn376iXHjxhEcHMyKFSvo06cPBw8e1Ps4tbS0NJYsWUL37t159NFHWbJkCd991/oBxW1NjEkRBEEQBEGSREuKIAiCIAiSJEKKIAiCIAiSJEKKIAiCIAiSJEKKIAiCIAiSJEKKIAiCIAiSJEKKIAiCIAiSJEKKIAiCIAiSJEKKILSR119/nUGDBmFjY4OrqyuzZs3i6tWrtY8nJCQgk8l03rZu3Vp7XFJSEtOmTcPS0hJXV1eeeuopqqqq6r3WSy+9RJcuXRgxYgQxMTEG+x4FQRDakggpgtBGDh48yEMPPcSJEyfYu3cvlZWVTJw4keLiYgC6du1KWlpavdtLL72EtbU1U6ZMAUCtVjNt2jQqKio4duwYX331FRs3buSFF16ofZ2jR4/y22+/sWPHDhYtWsTDDz9slO9XEARB38SKs4JgIFlZWbi6unLw4MFGt10PDQ2lf//+fPHFFwDs2rWL6dOnk5qaipubGwCffPIJ//rXv8jKysLU1JRff/2Vzz//nK1bt3LmzBkeeeQRIiIiDPZ9CYIgtBXRkiIIBlJQUACAo6OjzsdPnz5NVFQUK1asqL3v+PHj9O7duzagAEyaNAmVSsXFixdrvy4rK8PS0pLJkyfz+uuvt+F3IQiCYDhiF2RBMACNRsPjjz/O8OHDG+xYWuOLL76gR48eDBs2rPa+9PT0egEFqP06PT0dAKVSye7du8nMzMTe3h5TU9M2+i4EQRAMS4QUQTCAhx56iAsXLnDkyBGdj5eWlrJ582aef/75Fr+Gq6tri58rCIIgRaK7RxDa2MMPP8yvv/7K/v376dKli85jtm3bRklJCUuXLq13v7u7OxkZGfXuq/na3d29bQoWBEGQCBFSBKGNaLVaHn74YbZv3054eDh+fn6NHvvFF18wY8YMXFxc6t0fFhZGdHQ0mZmZtfft3bsXW1tbevbs2Wa1C4IgSIGY3SMIbWTVqlVs3ryZHTt2EBwcXHu/nZ0dFhYWtV9fu3aNoKAgfv/9dyZPnlzvHGq1mn79+uHp6cmbb75Jeno6S5Ys4R//+Aevvfaawb4XQRAEYxAhRRDaiEwm03n/hg0bWLZsWe3XzzzzDJs2bSIhIQG5vGHjZmJiIv/85z85cOAAVlZW3HvvvaxduxYTEzGkTBCEjk2EFEEQBEEQJEmMSREEQRAEQZJESBEEQRAEQZJESBEEQRAEQZJESBEEQRAEQZJESBEEQRAEQZJESBEEQRAEQZJESBEEQRAEQZJESBEEQRAEQZJESBEEQRAEQZJESBEEQRAEQZJESBEEQRAEQZL+Pz7YABij7NFJAAAAAElFTkSuQmCC",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1371,7 +1587,7 @@
    "source": [
     "rho = 1025  # kg/m^3\n",
     "g = 9.81  # m/s^2\n",
-    "wave.graphics.plot_directional_spectrum(spectrum * rho * g, name=\"Energy\", units=\"J\")"
+    "wave.graphics.plot_directional_spectrum(spectrum * rho * g, name=\"Energy\", units=\"J\", color_level_min=0.0)"
    ]
   },
   {
@@ -1384,7 +1600,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "work",
    "language": "python",
    "name": "python3"
   },
@@ -1398,12 +1614,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.7"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "15fd306e44580d8cf431083454c399b84f9cc4f7f2c761501397671836835f49"
-   }
+   "version": "3.11.10"
   }
  },
  "nbformat": 4,
diff --git a/examples/environmental_contours_example.ipynb b/examples/environmental_contours_example.ipynb
index c97f2a634..524309692 100644
--- a/examples/environmental_contours_example.ipynb
+++ b/examples/environmental_contours_example.ipynb
@@ -83,31 +83,31 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1658</th>\n",
+       "      <th>1768</th>\n",
        "      <td>46022</td>\n",
        "      <td>1996</td>\n",
        "      <td>46022w1996.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1659</th>\n",
+       "      <th>1769</th>\n",
        "      <td>46022</td>\n",
        "      <td>1997</td>\n",
        "      <td>46022w1997.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1660</th>\n",
+       "      <th>1770</th>\n",
        "      <td>46022</td>\n",
        "      <td>1998</td>\n",
        "      <td>46022w1998.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1661</th>\n",
+       "      <th>1771</th>\n",
        "      <td>46022</td>\n",
        "      <td>1999</td>\n",
        "      <td>46022w1999.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1662</th>\n",
+       "      <th>1772</th>\n",
        "      <td>46022</td>\n",
        "      <td>2000</td>\n",
        "      <td>46022w2000.txt.gz</td>\n",
@@ -118,11 +118,11 @@
       ],
       "text/plain": [
        "         id  year           filename\n",
-       "1658  46022  1996  46022w1996.txt.gz\n",
-       "1659  46022  1997  46022w1997.txt.gz\n",
-       "1660  46022  1998  46022w1998.txt.gz\n",
-       "1661  46022  1999  46022w1999.txt.gz\n",
-       "1662  46022  2000  46022w2000.txt.gz"
+       "1768  46022  1996  46022w1996.txt.gz\n",
+       "1769  46022  1997  46022w1997.txt.gz\n",
+       "1770  46022  1998  46022w1998.txt.gz\n",
+       "1771  46022  1999  46022w1999.txt.gz\n",
+       "1772  46022  2000  46022w2000.txt.gz"
       ]
      },
      "execution_count": 2,
@@ -182,31 +182,31 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1658</th>\n",
+       "      <th>1768</th>\n",
        "      <td>46022</td>\n",
        "      <td>1996</td>\n",
        "      <td>46022w1996.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1659</th>\n",
+       "      <th>1769</th>\n",
        "      <td>46022</td>\n",
        "      <td>1997</td>\n",
        "      <td>46022w1997.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1660</th>\n",
+       "      <th>1770</th>\n",
        "      <td>46022</td>\n",
        "      <td>1998</td>\n",
        "      <td>46022w1998.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1661</th>\n",
+       "      <th>1771</th>\n",
        "      <td>46022</td>\n",
        "      <td>1999</td>\n",
        "      <td>46022w1999.txt.gz</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1662</th>\n",
+       "      <th>1772</th>\n",
        "      <td>46022</td>\n",
        "      <td>2000</td>\n",
        "      <td>46022w2000.txt.gz</td>\n",
@@ -217,11 +217,11 @@
       ],
       "text/plain": [
        "         id  year           filename\n",
-       "1658  46022  1996  46022w1996.txt.gz\n",
-       "1659  46022  1997  46022w1997.txt.gz\n",
-       "1660  46022  1998  46022w1998.txt.gz\n",
-       "1661  46022  1999  46022w1999.txt.gz\n",
-       "1662  46022  2000  46022w2000.txt.gz"
+       "1768  46022  1996  46022w1996.txt.gz\n",
+       "1769  46022  1997  46022w1997.txt.gz\n",
+       "1770  46022  1998  46022w1998.txt.gz\n",
+       "1771  46022  1999  46022w1999.txt.gz\n",
+       "1772  46022  2000  46022w2000.txt.gz"
       ]
      },
      "execution_count": 3,
@@ -547,7 +547,7 @@
        "      <th>Te</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>index</th>\n",
+       "      <th>date</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
@@ -615,7 +615,7 @@
       ],
       "text/plain": [
        "                          Hm0         Te\n",
-       "index                                   \n",
+       "date                                    \n",
        "1996-01-01 00:00:00  4.819627  14.856398\n",
        "1996-01-01 01:00:00  5.004158  14.961679\n",
        "1996-01-01 02:00:00  5.091169  14.244618\n",
@@ -719,7 +719,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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2+JzJuRNGCrmnBGZLSxj/99+9eG6zSneqLbLhoyfU4uJjauCxkRD7cPeK3FPCaDBZ7qsKpwkPXr4Ybyyvwf/+Yxt2dsbw9b9swu/e3Itvf3ABlkzzjPUQpwwT5Z4azPh02jhV8Oh0OvzlL3/BRRdddNB7mUwGF198MZqamvDKK68c0rG48847cddddx30+hNPPAG73T6SQxYEQRAGSV4DtgZ1eLlFhx1hldY0x53HymoNC7waZBJVEEaHXB54rV2H5/frkcjpoIOGFZUazp+eh0Wa0QsHiMfjuOqqqxAKhQ5pcwMT0LHIZDK47LLLsHv3bvz73/9GSUnJIbfTV8SitrYWPp/vsCdHOJhMJoOXXnoJZ511lpRxFEYEuaemJqlMDs9saMUjb+zDrs4YAMCg1+H8oyvxiVNmYGH10L+f5Z4SRoPJfF91RVP43vPb8cyGVgBUtvmuD87HyrllYzyyyc1EuafC4TBKS0sH5FhMqFQodip27NiBl19++bBOBQBYLBZYLAfXHTSZTOP6Io535PwJI43cU1ODYDyN367eh9+s3gtfNA2Acr+vOmE6Pn5yHaq9thHbl9xTwmgwGe+ryiITHrjyGHzk2E584y+b0BRI4FO/XYcLl1TjWxcuQKl07x5Vxvs9NZixjSvHIhqNYufOnd3P9+zZg/Xr16O4uBhVVVW45JJLsHbtWvz9739HLpdDW1sbAKC4uBhms1Q0EARBGK90hJP41Wu78fiaRsTTVA+22mPFdafU4/Lja+G2jt8fVUGYKrxvbhlevGkF7n1xOx757x78bUMLXtvRiW9duAAXLa2BTid5icKhGVeOxTvvvIPTTz+9+/nNN98MALj22mtx55134tlnnwUALF26tMd6L7/8MlauXHmkhikIgiAMkMauOH756i788Z0mpHN5AMD8Kjc+876ZOG9RlXQBFoRxht1sxDcvWIAPLq3G157ehPdaw7jpqQ146b12fOeiRSh2yESu0D/jyrFYuXLlIbtBjlM5iCAIgtCL7e0R/OKVXXh2Q0t3hadjZxThC6fPxsp5ZTLzKQjjnMXTvHjmC6fgoVd24YFVO/Dcpja8tSeAH16yCGccVTHWwxPGKePKsRAEQRAmNhv2B/Gzl3fixffau19bMbcMn185C8fXF4tDIQgTCJNBjxvOnIOV88px0x/WY2dHFJ947B1ceXwtvnn+AjgsYkYKPZE7QhAEQRg27+4L4P5/bcdrO3wAAJ0O+MDCSnxu5Wwskrr4gjChWTTNg7/fcCrueaEB//f6Hvz+rf34784u3Hf5Ehw7o3ishyeMI8SxEARBEIZMb4fCoNfhoqU1+OzKmZhd7hrj0QmCMFJYTQbcfsECnDm/HLf+cSMa/XFc9ss38eWz5+IzK2ZBLw1nBIhjIQiCIAyBd/cF8MCqHXh1eycAwKjX4ZJjp+Hzp89GbbE0HxWEycrJs0rxzy+dhm/+ZTOe3dCCHz7fgDd3+3HvZUukLK0gjoUgCIIwcMShEATBbTXhgSuW4pTZJbjjmS14dXsnznvgNTx45TKcOPPwPcaEyYs4FoIgCMJhWdcYwH3/6ulQXHwMORTTS8ShEISphk6nw+XHTcfS2iJ8/om12NkRxVW/ehM3njkXXzhjNgySGjUlEcdCEARB6JeGtgjueaEB/9pKVZ4Meh0uEYdCEIQDzKt04dkvnIJvPbMFf3y3Cff9azve2efHT65cBq9del5MNcSxEARBEA6isSuO+/61HX9d3wxNA/Q64OJjpuGGM+aIQyEIQg/sZiPuuXQJTppVgm/8ZTNe2+HDhT99HQ9fsxzzq9xjPTzhCCKOhSAIgtBNeziJn/x7B558az+yBxrbnb+oCjedNRezy51jPDpBEMYzHzlmGuZXufHp376D/f4EPvLzN/DDSxbjwiXVYz004QghjoUgCIKAYDyNX/xnF37zxl4kM3kA1Nju1rPnSR8KQRAGzPwqN/72hVNxw+/X4bUdPtzw+3XY3BzCVz5wlOgupgDiWAiCIExhYqksHv3vHvzy1d2IJLMAgGNnFOHWc+ZJdRdBEIaE127GY9cdjx++sA2//M9u/PLV3XivNSy6iymAOBaCIAhTkHQ2jyfW7MNPX94JXzQNADiq0oWvfGAeTp9XDp1OZhYFQRg6Br0Ot507H0dXe/CVP23Eazt8+Mgv3sCjHz8OM0ocYz08YZQQx0IQBGEKoWkantvUhh++sA37uuIAgLoSO246ay4uXFwt3XMFQRhRLlxSjdnlTnzysbexuzOGD//8DfzqY8fi2BnFYz00YRQQx0IQBGGK8O4+P777j61Y2xgEAJS5LPjS++fgsuW1MBn0Yzs4QRAmLfOr3Pjr50/BJ3/zDjY1h3Dlr9bgx5cuEVH3JEQcC0EQhEnOHl8MP/jnNjy/pQ0AYDMZ8D/vm4lPnTYTDov8DAiCMPqUu6146n9OxI1PrsdL77Xjht+vQ6M/js+tnCWpl5MI+UURBEGYpHRFU3hw1Q48vqYR2bwGvQ64/Lha3PT+uSh3W8d6eIIgTDHsZiMe+uix+N5zW/Hr1/fgnhcasNcXw90fWSRR00mCOBaCIAiTjGQmh0f+uwe/eHkXIimq9HT6vDLcdt58zK1wjfHoxo5UCsjnAb0esFjGejSCMDUx6HX45gULMKPEjm89S926/bE0fnb1MbCaDGM9PGGYiGMhCIIwScjnNfx1fTN+9EIDWkJJAMCCKje+cf58nDK7dIxHN3Ykk4DfD0QiQC4HGAyAywUUFwNWCdwIwphwzUl1qPba8LnH12LVtg587P/ewq+uXQ6PzTTWQxOGgcSdBEEQJgHv7gvgwz//L27+wwa0hJKo9lhx72VL8PcbTp3yTkVzMxAIUJTC46HHQIBeTybHeoSCMHU5c34FfvvJE+CyGvHWXj+uePhNdETkQzmREcdCEARhAtMaSuDGJ9fh4l+8gQ1NITjMBtx6zjz8+5aV+Mgx06Z8+Vi/n5yHoiLAbAZ0OnosKlKRDEEQxo7j64vx1KdPQqnTgq2tYVz60Go0HiiFLUw8xLEQBEGYgCTSOTzwrx0440f/wTPrW6DTAZctn4aXb12Jz58+W3KVQZqKSARw9NOLy+Gg91OpIzsuQRB6sqDajac/exJqi23Y1xXHxQ+9gW1t4bEeljAEBqWxePbZZwe9g7POOgs2m23Q6wmCIAgHo2ka/r6xFd//5zY0BxMAgOPqinDHBQuxaJpnjEc3vsjnSVNh6idl22QC4nFaThCEsWVGiQNPf+ZkfOyRt7CtLYIrH34Tv7v+BCyslu+1icSgHIuLLrpoUBvX6XTYsWMHZs6cOaj1BEEQhIPZ1BTCt/++BW/vDQAAqj1W3HbefFywuErqwPeBXk9C7UyG0p96k8nQ+3qJ3QvCuKDcbcVTnz4JH3tkDTY0hXD1r9fgd588AUfXiHMxURj012lbWxvy+fyA/ux2+2iMWRAEYUrREUniK3/agA/+7HW8vTcAq0mPm94/F6u+vBIXLqkWp6IfLBaq/hSL9f1+LEbvS+lZQRg/eOwm/Pb6E7BsuhfBeAZX/epNbGwKjvWwhAEyKMfi2muvHVRa00c/+lG43e5BD0oQBEEAMrk8fv3abpzxo//gD+80QdOAi5ZW4+VbVuLG98+BzSw6isPBJWUDASCdBjSNHgMBer24eKxHKAhCb9xWE/7fJ47HsTOKEE5mcfWv12D9/uBYD0sYAINKhXr00UcHtfFf/OIXg1peEARBIFbv6sK3nt2M7e1RAMCSaR7cceFCHDujaIxHNrGwWoGaGtXHIh6n9KeiIuljIQjjGZfVhN984nhc9+hbeHtvANf8eg0eO+BsCOMXaZAnCIIwjmgLJfHd57bibxtaAABFdhO++oGjcNny2ilfOnaoWK1AdbV03haEiYbTYsRj1x2PTzz2Ntbs8ePjj7yFJz51ohSqGMcMy7FIJpPYuHEjOjo6kO9VVuODH/zgsAYmCIIwlUhn83j0v3vw4KodiKVz0OmAj54wA18+ey689j6Ux8KgEWdCECYeDosRj153HK57lJyLjz2yBk/9z0mYW+Ea66EJfTBkx+L555/Hxz72Mfh8voPe0+l0yOVywxqYIAjCVOG/O32445nN2NVJKuNjpnvx7Q8dLZVQBEEQANjNRvzfx4/D1b9egw37g/jor9fgj585CTNK+mlSI4wZQy6yd8MNN+DSSy9Fa2vrQdWgxKkQBEE4PC3BBD7/+Fpc/es12NUZQ4nDjHsuWYw/feZkcSoEQRAKcFqM+M11x+GoShc6Iilc9as1aDnQy0cYPwzZsWhvb8fNN9+MioqKkRyPIAjCpCeTy+Oh/+zCmT/+D/6xqRV6HfDxk+vw71tW4lLRUgiCIPSJ127Gbz95AupLHWgOJvDRX6+BL5oa62EJBQzZsbjkkkvwyiuvjOBQBEEQJj9v7/Xj/Adfw/f/uQ2JTA7H1RXh7zechjs/uBAeWz8tooVxTyoFJBL0KAjC6FHmsuB315+AGq8Nu30xXPN/byGczIz1sIQDDFlj8dOf/hSXXnopXnvtNSxatAgmU88fxC9+8YvDHpwgCMJkIRBL4/v/3Ian3tkPACh2mPH18+bj4mNqpMHdBCaZVKVsczkqZetySSlbQRhNarw2PH79Cbj0l6uxtTWMz/z2XTx23fEwG4c8Xy6MEEN2LH7/+9/jxRdfhNVqxSuvvNLjh1Gn0w3JsXj11Vdxzz334N1330Vrayv+8pe/4KKLLup+X9M0fOtb38KvfvUrBINBnHLKKfjFL36BOXPmDPUwBEEQRhVN0/D02mbc/dxW+GNpAMAVx9Xia+ceJdWeJjjJJNDcTI8OB2AyAZkMNd9LJKh/hjgXgjA61JU68Nh1x+Gyh1bjjV1duPVPG3DfZUsllXSMGbJr941vfAN33XUXQqEQ9u7diz179nT/7d69e0jbjMViWLJkCX72s5/1+f4Pf/hDPPjgg3jooYewZs0aOBwOnHPOOUgmk0M9DEEQhFFjZ0cUVzz8Jm754wb4Y2nMq3DhT585Cd+/eLE4FZMAv5+ciqIiwGwGdDp6LCpSkQxBEEaPhdUePHTNsTDqdXhmfQt+8MK2sR7SlGfIEYt0Oo3LL78cev3IhZ3OPfdcnHvuuX2+p2ka7r//fnzzm9/Ehz70IQDA//t//w8VFRX461//iiuuuGLExiEIgjAckpkcfvbyTjz0n13I5DRYTXp86f1z8clT62EySKh+MpBKUfqTo59qlw4HvZ9KSf8MQRhNTptThh9cvBhf/uMG/PI/u1HtseHak+vGelhTliH/wl177bV46qmnRnIsh2TPnj1oa2vD+9///u7XPB4PTjjhBKxevfqIjUMQBOFQvLq9E+fc/yp+8u+dyOQ0nHFUOV666X34zPtmiVMxicjnSVNh6kdvbzLR+716xwqCMApcfOw03HrOPADAnX/bguc3t47xiKYuQ45Y5HI5/PCHP8QLL7yAxYsXHyTevvfee4c9uELa2toA4KDythUVFd3v9UUqlUKqoExHOBwGAGQyGWQyUkVgsPA5k3MnjBST5Z7qiKRw93MN+MfmA99VbgtuP+8onL2gHDqdbsIf30TiSNxT7DTE45T+1Jt0WjkfcuknB5Plu2qy8qlTpqPJH8Pv327CjU+ux+OfNGHJtPHdD2ii3FODGd+QHYtNmzZh2bJlAIDNmzf3eG88VTj53ve+h7vuuuug11988UXY7fYxGNHk4KWXXhrrIQiTjIl6T+U14I12Hf7WqEcyp4MOGlZUajhvegy5fe/in/vGeoRTl9G+p7q6LIjFzHA6D/7RjUZNcDjS2LVL6s9ONibqd9VU4DgDsMGrx3tB4BOPvIkvL8rBOwFSEcf7PRWPxwe87JAdi5dffnmoqw6JyspKANSYr6qqqvv19vZ2LF26tN/1brvtNtx8883dz8PhMGpra3H22WfD7XaP2ngnK5lMBi+99BLOOuusg6JUgjAUJvI9tbszhm88swXv7AsCABbVuPG/H1yAhdXy3TKWHKl7iqtCpVKA3a6qQsXjpKsYalWoVIqiHXq96DPGExP5u2oqsfLMLC7/1Rrs6IjhT+3FePwTx8FmNoz1sPpkotxTnO0zEAblWGzcuBFHH330gAXbW7Zswbx582A0Dtl/6aa+vh6VlZVYtWpVtyMRDoexZs0afPazn+13PYvFAksf38wmk2lcX8Txjpw/YaSZSPdUOpvHw6/uwoOrdiKdy8NuNuCWs+fh2pPrYJBSh+OG0b6nTCagrk71sYjHqY9FWdnQ+lhIT4yJwUT6rpqKFJtM+L9rj8eHfvY6NjWH8fVn3sNPrlw2rrJpejPe76nBjG1QFv+yZcvQ1taGsrKyAS1/0kknYf369Zg5c+aAlo9Go9i5c2f38z179mD9+vUoLi7G9OnT8aUvfQnf+c53MGfOHNTX1+P2229HdXV1j14XgiAIo8m6xgC+9vQmNLRHAADvm1uG7374aEwrktTKqYjVClRXDz/KID0xBGHkmF5ix0MfPRZX/3oN/r6xFXMrXPjimdLz7EgwKMdC0zTcfvvtA9YmpNPpQQ3mnXfewemnn979nFOYrr32Wjz22GP4yle+glgshk9/+tMIBoM49dRT8fzzz8Mq37aCIIwysVQWP3qxAY+9sReaRp2zv3XhAnxwSfW4ngkTjgzDTVkq7InBmM30FwjQ+9XVw9uHIEwlTphZgu9cdDS+9udNuPel7ZhT7sS5i6oOv6IwLAblWKxYsQINDQ0DXv6kk06CzWYb8PIrV66Epmn9vq/T6fDtb38b3/72twe8TUEQhOHySkMHvvGXzWgOJgAAH1lWg29esADFDmlydySY7JoD6YkhCKPDFcdPR0N7BI/+dy++/McNmF3uxJwK11gPa1IzKMfilVdeGaVhCIIgjD/8sTS+/bct+Ov6FgBAjdeGuz+yCO+bO7B0UGF4TBXNwUB6YsTj0hNDEIbCN86bj4a2CN7Y1YXP/O5dPPOFU+G0DF/7K/SNdGsSBEHohaZp+Ou6Zrz/3v/gr+tboNcBnzy1Hi/etEKciiMEaw4CAZql93joMRBQWoTJgl5PTlN/peIzGXp/gHVTBEEowGjQ48Erl6HSbcWuzhi++vTGQ2bHCMNDvqYEQRAKaAkmcN1jb+NLT62HP5bGUZUu/Plzp+D2CxbAIbNcgyaVIvFxapDtHAo1B2YzoNPRY1GRimRMFiwWisTEYn2/H4vR+5IGJQhDo9Rpwc+uPgZGvQ7/2NiKR/67d6yHNGmRX0lBEARQlOLJt/fj7n9sRSSVhdmgxxfPnI1Pr5gFs1HmYAoZiOZhOGlMU1FzUFxMDlgg0LMqVCxG56u4eKxHKAgTm2NnFOGb58/HnX97D997bisWT/PguDr5YI004lgIgjDl2e+P47Y/b8LrO30AgGXTvbjnksWYXS4iv0IG6iwMt3TqVNQcWK10Xnr3xCgqmnyaEkEYK649uQ7vNgbxtw0t+Pzja/GPL56GMtckmZ0YJ4hjIQjClCWf1/D4W434/nNbEUvnYDHqces583DdKfXS6K4XA3UWUimgpQUIh4GKCrX+YEqnFmoOzH0U3pqsmoOR6okhCELf6HQ6fP8ji7C1NYydHVHc/If1+M11x0Mv3/cjxpAcC5/Ph0ceeQSrV69GW1sbAKCyshInn3wyPv7xjw+4gZ4gCMJY0dgVx1ee3oA3d1Oy/nF1RfjBxYsxs8w5xiMbnxyuz0JLCxnGXV1AYyP9r2mA19tztn0gaUysOQgE+nYsYjEax2Q1uifrcQnCeMBhMeIXVx+DC3/6Ol7b4cOvX9+NT6+YNdbDmjQMer7n7bffxty5c/Hggw/C4/FgxYoVWLFiBTweDx588EEcddRReOedd0ZjrIIgCMMmn9fw6H/34Jz7X8Wbu/2wmQy488IFeOrTJ4lT0Q+H0zwYDMDOnUB7O0Uy7HZaNhQiJyMYVOJtk4nSnA6XxsTpP4EAkE6Tk5JO03PRHAiCMBzmVLhwxwULAQD3vNCATU2hMR7R5GHQEYsbbrgBl156KR566KGDus1qmobPfOYzuOGGG7B69eoRG6QgCMJIsMcXw1f+tAFv7w0AAE6cWYwfXrwE00vsfS4vKSnE4TQPsRilQ7ndKo0pnabz194O+HxAeTngdJLDMZA0JtEcCIIwmlx5fC1e3d6J57e04YtPrsPfbzhVKv+NAIM+gxs2bMBjjz12kFMBUO7aTTfdhGXLlo3I4ARBEEaCXF7DI6/vwY9ebEAqm4fDbMDXzpuPq4+f3mdu7VRpzDZQDqV5SKUoIuF0KgfMZAJ27aJz5XaTY6LTUQSjvR2YN29gjlqh5iBBTc9hs01tJ08QhJFBp9Ph+xcvwsamIPb4YvjWs1vwo0uXjPWwJjyDToWqrKzEW2+91e/7b731FioKFXuCIAhjyM6OCC556A1897mtSGXzOHV2KV64aQWuOXFGv07FUBuzDbVnw1hzuHEfqs9CPk+ve70HG/yaBhiNtAynPvUxJ3VIkknSbbS3k45j7156PFyDvExGPyGvRV9M1PtKEMY7XrsZ91+xDHod8Kd3m/DM+uaxHtKEZ9ARi1tuuQWf/vSn8e677+LMM8/sdiLa29uxatUq/OpXv8KPfvSjER+oIAjCYMjlNfzqtd2496XtSGfzcFmM+Mb583H5cbV9RlyZw4mU+6poNFEjHIcbd2EqWH99FsJhWtZ5QJ6SStHr06fT8qyvyGbpnNrt9P5AelAMpWxtMklOSEeHDXv3KqdovF+Lvpio95UgTCSOry/GF86YgwdX7cA3/7oZx9cXo8pjG+thTVgG7Vh8/vOfR2lpKe677z78/Oc/Ry6XAwAYDAYce+yxeOyxx3DZZZeN+EAFQRAGyh5fDF/+w3qsbQwCAFbOK8PdH16Eau+hfyyG0phtuD0bxopDjTsQoJSjTKanQVtSQlqHQs1DRQVFdThViaMTLhc5GzodPVZV0TnTNEqJGkgPisE6eXxM0ShgMuXhdtPr4/1a9MVEva8EYSLyxTNm49XtnVi/P4ivPr0Jv7nuuENOQAn9MySVyuWXX47LL78cmUwGPh81lCotLYWpP2WfIAjCESCf1/D/Vu/F95/fhmQmD6fFiDsuWIBLl08b0I/EUBqzDSXCMR7ob9z5PLB9OzkB9fV9G7QlJT1F7YXpY0YjRSeCQXp0uYDKSuWIDbQHxVCcPD4mrxcwGjXodDT+8X4t+mKi3leCMBExGvT40aVLcP6Dr+HV7Z148u39uPL46WM9rAnJsNoLmUwmVFVVoaqqSpwKQRDGlKZAHFf/eg3u/Nt7SGbyOHlWCV64aQUuO0zqUyGZDP1Fo/2/X2gUD8b4HU8catzBoBJraxpFHMxmMnA5NcdioYgGQM6GTkcOh82mtBANDaS96H3qYzFyNg6XBjUQJ6+wbO1EvRZ9MZmORRAmCrPLnbj1nHkAgO/8/T3s98fHeEQTkyHX1QqHw3j00UfR1taG+vp6LFmyBIsWLYLd3nfZRkEQhNFA0zT84Z39+N+/b0U0lYXNZMBt5x2Fj57Qtzi7Lwpz2QMBciyqqw9u7ta7MdtQIhzjgf7GnUrRsbvddE56j5sN2lCIzkVh7r/JRE6GywUsXkznMZOhZfJ5oLSUIhgD7UEx2O7bhceUzR68/Hi9Fn2Rz9O5ZOeutxM2kY5FECYS151Sjxe2tOHtvQF89emN+N0nT5Cu3INkyI7FRz7yEWzYsAHHHXcc/va3v6GhoQEAMGvWLCxZsgRPPfXUiA1SEAShL9rDSXzt6Y14uaETAHDsjCL86NIlqC/tZ6q3D3rnstfWAk1NwP79ZBRPm0YGXix2sFE8WON3vNDfuAurN+n1B4/bZCKHYf9+ikQU5v7v2UOOydy5qsxsMEiOSlcXGf2zZ9M6mnZ48fZgu28XHlNfAarxei16k0wCbW30ZzDQ8TmdPZ3ciXIsgjDRMOh1uOeSJTj3gdfwxq4u/G7NPnzspLqxHtaEYsiOxerVq/HKK6/guOOOAwCkUils2rQJ69evx4YNG0ZsgIIgCL3RNA3PbmjBHc9sQSiRgdmgx5fPnovrT5sJQz+zS/01u+srl722lozalhYyoquq+m7MNljjd7zQ37jZmQiHKcLQe9wcgXC5SLTNaJoydINB0lRYrfSYSgFlZeRgcIrPQCsc9VWJKhqlP5utp5NXeEzOPhqoj9drUUihk1tURGO2WChClEyq8zoRjkUQJip1pQ587dyj8K1nt+B7z23D6fPKUVss2TgDZciOxeLFi2E0qtUtFguWL1+O5cuXj8jABEEQ+qIrmsLtz2zGc5vaAABH17hx72VLMbfC1efyhyrZqdP1ncvORrHDQetXVaG7wlBv+ivD2leEYzzR17h1OjpHuRzNkPcmQA3LezhhgIp0uN3KgWCj12Kh9/x+VXLWaiUn5HAVjgq7b/t8ygm0WmmbLS3kRLhcPUviknBcB02jDuAjeS1Gsxt7oZNrs9F1iMepRG8sBnR20vGO5/tKECYD15w4A89tasWaPX7c/sxmPPpxqRI1UIbsWPzwhz/EHXfcgT/96U+wyLSJIAhHgBe3tOHrf9kEXzQNo16HL5wxG58/fTZMhr5zQg5XsrO4+NAaCafz0O8DPY3fwjKsfUU4hsvhjNrBGL39jXvGDDpfiQRtJ59X73NUoPf5KEybKkynYpqbVWpPKkXLcnpPInHoCkdsRAeDyiHMZICODmDzZtpXbS05gqWlVLHKaKQGeeEwjXkkrsVo95ToLdhm55bTyXI5um/Ly8nRlVKzgjB66PU6fPfDi3DeA6/hlYZO/GNTKy5YLGXYBsKQHYu6ujqEw2EsWLAAl19+OU488UQsW7YMtbW1Izk+QRAEhJMZ3PnsFvx5LXVFnVvhxI8vXYpF0zyHXO9wJTuDwZHRSFitZBiP1mz24aIu8TgdSzo9OKO3v3EnkxQN2LEDaG0l499mo4iEyUTbLy1V22EdgM+nohFMOEwVohwOGhOXo+X0npKSg8vG9sbvp3SroiJyUNjRcTppG8EgrZvNUk+N8nKgvDyBqioar802vOtxJHpK9CWoL0wny+XIweB0KEEQRpfZ5U58duUsPLBqB+7623s4bU4ZPDapgHo4huxYXHzxxWhvb8f73vc+vPHGG/jFL36BcDiM4uJiLFu2DC+++OJIjlMQhCnK6l1d+PIf1qMllIROB3x6xUzc9P65sJoMh1xvICU7UylyKGKxkdFIjEbwtj+jtq0N2LuXnnd1kVFdVkYGv8EwOKO3r3EnEvRXVEQz5MkkRQna2oCdO4Fly0jYztv2eqnUbC5Hzo6m0Tj37SOjua5OGc0mEzkAoZDSS/RX4ajwOvr99FzT6M/tpnXTaXrd5aJxtrYC4bAJ7e1K1D2c6MKR6ClxqEIAFgsdo80mgm1BOJJ87vRZ+NvGFuzujOEHz2/D3R9eNNZDGvcM2bHYvHkzVq9ejSVLlnS/tnfvXqxbtw4bN24ckcEJgjB1SWZy+PGLDfj163ugacD0YjvuvWwJltcNLLl8oKVgvV5adrxqJPoyavN5eq2zk4xRu53ej8fJuK+spOdDNXr9fnIiXC46Bx0d5AAYjXR+uLv1vHnAggW0/0SC0qisVjLy43E6/0YjMH06jbM3djtFG8zm/g1mvo58jbhzNzuMRqPSXfAYGxuBYNACi4X2MZzowkAc1K4u2s9wIiMTtRCAIExmLEYD7v7wIlzx8Jt4Yk0jPrKsZsC/QVOVITsWxx13HGKxWI/X6urqUFdXhw9/+MPDHpggCFOXra1h3PTUemxriwAArjiuFt+8YAGcloF/ZQ20FCwbhEdCIzFY+jNqg0F6r7iYIgIeT88oAFdmGorRm0rROvk8pRpxX490ms5ZSQltx2AgByOVAhYtokgJny9OrUqlaLlEglKiPL0y14xG2nZdXf9j0+spGtPURPszGCjlqrRUibb1ejp+Pl8U3cnCbFYN/oYaXTiUg5pM0jbb2ujccLrXUO+biVoIQBAmMyfOLMFly6fhD+804bY/b8JzN57Wr65PGIZjceONN+LOO+/EH/7wB3j7Kh8iCIIwSHJ5Db9+bTd+/OJ2pHN5lDjM+P7Fi3HWgorDr9yLwc4Aj6ZGYqj0ZdSGw2T4s5Yhm+0522+3k7EeDtMxDtbozedpeRZux+O0j0yGHA1No+cuF6VehcN0fguNdYtFdYXO5VTaWShE4yvUWdhsPfUaQM/roGl0PB0dtF2TiR59PnIibDZyovR62henjOl02kHHxg3+wmHazkCuc38OKvebiEbpfHq9A6t0dSiOZCEAQRAGzm3nzse/tnZgR0cUv3ljL64/beZYD2ncMmTH4pJLLgEAzJkzBx/+8IdxwgknYNmyZTj66KNh7utXXBAE4RA0BxP4yp+34K09fgDA++eX4/sXL0apc+gW/mBngMeDM1FIoVGbz1MkwucjYbXLRbPxvaswGY1ksLe0qE7XgzF6efY/n1fahXRanZtslt4zGFS/iFRKia97C80DAXqsrKR9R6P0mMuR0zBjhopk9CVSj8XoOKur6ZiiURpDVxct7/GQ4R0Mkuais5N6bJhMBzsWuRzpL5JJJUIvFMH35VT256By1IgjRXw+hxoZKXSmxqOTKwhTmSKHGbeeMw+3/XkTHvjXDly0rGZYv02TmSE7Frt378bGjRu7G+Ldfffd2Lt3L4xGI+bNmyc6C0EQBoSmaXirU4dv/HQ1oqks7GYD7rhgAS4/rnbYdcMn8gwwG5Zms9JZpFI0Q88pQMEgLRuPq3SpbJaMb6dzaEavxULpTj4f7VOnI8fGfqA/VDJJ+2ZnxWIhB4F1H72F5gYDsHs3pWzV1dH4OzooamCz0Vh37aLxRqM9141GlRNVXq6WjUTIgXK76ZhaW2kZm42OldKidEinVbQnmaR0qmiUxOhOZ08RvNNJ2+xL6N3bQWW9Ry6nyuYWwpGRw3UX53H1V/HLZhvw7SIIwihz2fJaPL5mHzY3h/GjFxrw/YsXj/WQxiXDKjdbV1eHD37wg92vRSIRrF+/XpwKQRAGRCCWxtee3oAXdhoAZHHMdC/uu3wpZpT0o5QdAqNdCnak6W1oZrPU/TuToX4NRiONv7OTjE+9ntbhNKNgkJYFaLlCo5c1D11dSivRF8XFZMjv36+E2GazKmfLDQO5eRtXK+IoQqHQ3OUikfe+fbQ9TrXifhOhEDkjsRi9NmeOigwYjWS4JxK0fjxO23O5VPWpWEw1jTOZ6K+xEejqsmH/fjp+r5fOSzCouqoDB4vgp03rW+jd20GNxchBKSvr20HlwgD9VboqvNajXcZWEISRwaDX4c4LF+KSh1bjqXf24+oTZhy25PlUZNCOhcvlwrJly3DsscfimGOOwTHHHIMFCxZAp9PB5XLhtNNOw2mnnTYaYxUEYRLxSkMHvvKnjeiIpKDXabjxjDn4/BlzYBwlUdx4diaYvgxNbo4GqJl6TuOyWmm5eJxe7+ykZc1mMtK5yzX3euBtcYSjurr/jtezZpHDYDBQhGHvXjK8a2pou8mk0jywod5f9SSrFaivpzK1bjcZ+oEAOS1OJzkn771Hhntbm+rVoNeToR0MqvS12lpyKFhgXlVFlak4+uB20zbzeR10Olq3q4vGVlLS09EqFMGHQhTd4SgIR3ZKSnqmKLEjxE5NNquqi/G5HGj/kyNRxlYQhJFjeV0xLlpajb+ub8G3nt2Mpz97snTk7sWgHYsf/OAHePfdd/Hvf/8bP/3pT5HP52Gz2bB48eIezkZhGVpBEAQmkc7h7ue24rdv7gMAzCx14CNVIfzPypmj5lRMFPoyNI1GMnzzeTLAy8qUqDkYVFWQKirI8LfZyMFwuchAZZFxKkXrc9pSKET/954V58hOJkNGe2kpRRG2baNZdE6J4vKx7OQUloXlrt2FzhxXiZo2jQzxVKqntqLQkeroUMfJjhCnBeXzZNCzI5HJ0P64W/isWXT+Nm7MQNOUtkTTevbdSKV6pphFIuQssPNhNJIj1NVFx2ow0PiSSdpWRQWNw2JRzf7YIRpIadiBlLEdaDqVIAhHjq+dOx8vvteOtY1B/HV9Mz68bNpYD2lcMWjH4nOf+1z3/4lEAg6HAzfccAP8fj/efPNN/PrXv0Y6nUaOp9gEQRAOsGF/EDc9tR67fVSq+uMn1+HL75+Ff7/0whiPbOzpz9DkcqpGI6UiFRrsXFLW66WIgNtNr7MGwGxWs/JsxIdCZPRWVNAyra20nXSaDGKfTxnc7DSUlgInnkjLd3bSNpNJNbvu96sysLGYcgi8XtqXx6OqRHGVJ7ud9pnP06w/OxWapjQYrCMxmZSzwuJtgI7BZiMdRiCgnBGrFSgqSmPaNBpXSQlFGXg9gLbX3q7Sp7hnRyiknC5Od3K7yYHZs4eOe9482i87PXY7HXdnp0rLOlxp2N4Vv3qn6g00nUoQhCNLpceKz58+G/e80IAf/LMBH1hYBZv50A1bpxJD1lgAgO3AFNKVV16JxYtJxJLNZvHee+8Nf2SCIEwacnkND/1nF+57aTuyeQ0VbgvuuWQJVswtQ4YFAVOc/volWCxkrAaDqgRsIdxxm50KQImN29uV4DiTIUOVdRfJJBnO+/eTIc/GtE6ntA3pNK2fzZJzUFJC48jnVdnXUIhm9VMpcgaiURpDIkHb44iHTqcqWSWTZIgnEsqY5qZ8dXXkDDgctF/eTlkZvc9Vn2w2JcB2OMjoLy2lMRVqTPJ5pQGJRlXaVjisjiuZpG05HHTMO3fStaivJyeBO4lz5IL7hFRW9kwxCwRIm1JVdXhtBFf8ikaVZoPPBY+F06kmij5IEKYKnzy1Hk+saURzMIHH3tiLz66cNdZDGjcMy7Hoc4NGY7eTIQiC0BxM4KYn1+OtvVRG9vzFVfjuRUfDa5ey1IUcqqGf10vRjEiEjGFNO3TZXBYbAzSbz9v2eJTGoK2NDGqDQc3kh8NkxM6ahe6u1Z2d5ETodMoB4fe4H8XOnVT5qbKSnrN2gqMPySQwezY5Jo2NJMS2WGjcvA2/n9bjErmsr+Cxeb00DoeDtut2q7SuQICch0yGtkHr6tHerlKdkkmV7sR9Nbg8LetVOBrT3k4OTXExpU8Bqqyv201OQCpF61RW0v+5HL3O6VCHg6MSDQ20fO/+Hu3t5GSxPqR3xSgRdQvC2GE1GXDzWXPx5T9uwM9f2Ykrj6+V37QDjLhjIQiCwPxtQwu+/pdNiCSzcJgNuOtDR+PiY2pE7NYHh2roZ7WqakgAGZ6HK5trtSo9Awu+ebabNRecx59IkGHOJVS5s3UoRM5GezsZ9vv2kcNSXq72o2m0jUyG0qqqqmhMhWk8PJvf0UGRBa7WNGeOihi4XOR4sCicu3rn87SP5mZaZsYMVZmpq0tFRWw2KidbWkpOjd9vQShEjkA2y70tVFSlq4uW41Szri4lkgdUWVkWk/NywMG9QywWinQYDMqx6R1Z6C/q0N9HIZ2m857PS8UoQRiPXLSsBr96bTe2tUXws5d34hvnLxjrIY0LBu1YXH/99Tj22GOxfPny7sjEkTIScrkc7rzzTvzud79DW1sbqqur8fGPfxzf/OY3xVARhHFENJXFHc9sxp/XNgMAltZ68cAVI1tGdriMx/SSQzX083jImOyvkVtfcE+KQEAtm0opjQPrA9jQbmujfba30+sWCzkvRiPtr6ODxsiC4lSKHIXNm8koZ+O8vl6t53LRMhw1yOdpTO3tFCGYNYv++HizWdVTorycHltayGmIxWh7Xi+dF27+V15ODgOXpdXpgHjcAJuNjtFqJQeDz62m0ThtNqoy1dhIEROHQ3UKdzrJGUkkVOqT00lOF0dUmGSS9supUoWRBaDvPhWcnlZXR2PkxoF6PV1rg4GOacYM5WhKxShBGD8Y9Dp89dyjcN2jb+M3b+zDtSfXYVqRfayHNeYM2rHYsWMH/vjHPyISicBopNXvuusurFy5EscccwyWLl0Ku310TuwPfvAD/OIXv8BvfvMbLFy4EO+88w6uu+46eDwefPGLXxyVfQqCMDjWNgbwpSfXo9Efh14HfOH02bjhzDkwjZOKT6EQGYfcLG88pZf019DPaCQjOJ3uqaU4FOw4ORxkGLe2kmHMs+qccuRwkFGcyZDhm0iQoZ3NKmE4942wWlWqjsdDxv7+/fQeOyi5HL1eVkbRi1RKlYYFyCGZMYPeb26ma1FVpZwQjpqUliqDmh2JYJBSrmbNUo6H202vt7XReHU6Ss3y+82IRJR4nB2ZdJqOwWCg5RIJ+r++XjlQej1tx2ymR0598nrJueIeGizw3r2bntfV0TFwZCEQUMv1jjoEAjQWPoZCRxeg688akd5IxShBGB+snFuGE2cW483dftz30g78+DKpiDpox+I///kPAHIw3n33XaxduxZr167FHXfcgWAwCIPBgLlz52LLli0jPtg33ngDH/rQh3D++ecDoCZ9v//97/HWW2+N+L4EQRgcubyGn728Ew+s2oFcXkON14b7Ll+K4+sPUx7nCJFM0sw3G5PcMdnpPHR6yZGObBQ29PP7yegPBskINZvJEJ05kxyNvsZV2GAvHlcGqKaRYc0N9SoqyLhnMTanPLW00P+lpbQO6xfCYdo+923IZGg/Tict6/Opc5rP03YtFnI8olHV2C+RoPW5K3hXF/3V1yuxOQu82ciPRsmYrqmhZcJhld7F43W7yUFh8XgwaOleb8cOlfrkdtM5cblozA0NNOb581WVp9JS2kYopKo/cbSltpZe48aBHMGYMaNnh3OzmbYNUBUpht9rb0e342M297yGiQRdb4ul714Y/VWMGo9ROEGYzOh0Onzt3Pm46Gf/xZ/XNeFTK+pxVOUAZ38mKUPWWMyZMwdz5szBFVdc0f3anj178M4772DdunUjMrjenHzyyXj44Yexfft2zJ07Fxs2bMDrr7+Oe++9t991UqkUUlznEED4wK9jJpORajRDgM+ZnDuhkKZAArc+vQnv7AsCAC5YVIm7LpwPt8102HvlSNxT3Hhu/34yjFlk7PdTek1FBRmk7e0qvaTQQGdj7UhGNsJhYNMm2n9xMRm/iQQZq9u2kSHucPQcF6C0CZxKE6PKvnA4yKhOp8lw1+noHHR2kgPR1kbHy7oKs5mMV26GxyVqQyHahtFIzgVnoWYyaox2Oy23YwdtnyMENhsdT0sLpUNxad2GBnIokknantNJyzU307mfM4ecIC7Jm07T/kwmGkdFherQ7fcDZnMWOp0O+XwWuRyNQ9NUj49QSFXg4jKybjedR6ezZ2neYFBpUIqKaNxcPpf7Z7hcSnjPpNPqXEejBxv67NB2dvbUrACqVwdXs+r90eAyvbkcvTfW9+pUQX7/hL5YWOnABxZW4Pkt7bjvxQb89MqlA153otxTgxmfTtM0bRTHMqLk83l8/etfxw9/+EMYDAbkcjl897vfxW233dbvOnfeeSfuuuuug15/4oknRi1lSxCmEu/6dPjDbj2SOR0sBg2X1uexvFTrV5Q6FnR1WRAKmZFIGGEyaTAY1NdePG6E3Z6By5VBJqNHUVEKuRwQDFqhaTpYrVkYDBpyOR2SSSNMphxKSpIwm0e3wcCuXS74fHaUlia7X8tk9AiFzOjstKKiIoaZM6M9xqXTaUinjXA6MwgEzIjHTbDbs8hmdYhGTXA40igvT6GlxYZkUg+bLQefz4Z4XI/mZhdCITNiMSPyeR2Mxhz0esBuz2LOnBDM5jwcjjQ6O23Q64F0Wodk0gS9XkMup0c2q4fZnEU2q0c6bUAyaTiQdqRHPq+H15uCyZSHTqeDyaQhkTBC0zTodBoyGT3s9iyczjTCYTOyWcOBFCIdDAYNdnsKbncONlsGZnMeFksO4bAJ8bgBBgNgt9NYYzHDgSiHhnjchJKSJFyuFBobXdA0HTRNd6DsbRoeTxr5vA7xuBEdHRbMmhVBTU0MJlPPn8SODis0TYPNlofBoEGv12C1ZuFyZQ5UvbJ3n2M26k0mDamUDj4flWQvKzv4ftE0IBQyw2Cgc9L7PotGDbBYNBQVpdAbvpYlJSmk03p0dVmRyRgO2gaQR3FxChZLHiaTNMQQhNGiJQ78cIMBGnT4yuIsasaPnHBEiMfjuOqqqxAKheA+TD7uhKoK9Yc//AGPP/44nnjiCSxcuBDr16/Hl770JVRXV+Paa6/tc53bbrsNN998c/fzcDiM2tpanH322Yc9OcLBZDIZvPTSSzjrrLNg6l1wX5hSRJJZ3PX3rXhmRysAYFmtBz+6ZBGmFw/OYR/teyqVAvbuJUOuvV31UlD7p2VKSyl/3uulWWqnk6IXXm/P2eZgkF4bDeEsp7JEo2SgLlumeivk86pxncFAM9rLl6tKUR0dNGNdW0vH2tREj9wzIp2mSEQup0TiBoOqQlVWBixcSGPIZGhZi0UJx1lXoNfTDHsySZGI0lJKQdLpVMO9fJ7eT6dpxpxF4Tx7brXSe1y6Vq+nCAz3rWDtgMejKjax/mTOHDr/DQ0UadA0VYbW7+dZ/iz279+KOXMWobjYCLOZthmLURpZZaXSb6TTtJ1586iKlt3eUwtRU6Ma/fHr3A+ktJRS1bikbWEfCrudIi6svegdsUinaZ3KShpX72iD3a76gxSOiffNaXstLeqeZJJJOretrXReKislgjESyO+fcCg25Tbguc3t2JirwafOG5jWYqLcU5ztMxAmlGNx66234mtf+1p3+tWiRYuwb98+fO973+vXsbBYLLD0kWxqMpnG9UUc78j5m9q8u8+PLz21Hvv9Ceh1wA1nzMENZ8yGcRgC7dG6p7JZ1Y2ZjUljwTcfG+ltbSqv3WwmozEWU6lTbJBxedR8fvh57GyMctdrrhwUiVDuPhvL8Tgt6/NRyo7XS86HTqca6jmd5FwYDGRsF2oh7HZatqWF3i8vp7+iImDXLtrHjBn0PBSi7en15JBxOpXdrlKB7HYaj9Go9A7sTOTzND5No22UlNB54spQdjuda9ZdlJWRQV9bC2zdSvtOp2mspaWq+7bHo0ruWq10ngpTmnI5GguLng2GLAAjAgET/H4y0lkoXRisDodp/xUVKlWsUDRfWkrXnzGb6boEAqrvh89Hy3AfCr5vABqb03nwtY9GVVdzl0ulX9ls6r5yuQ4W8peVKQeBK215POo+SCaVQ1JSos4PdyyXMrXDR37/hL648f3z8Nzmdjy/pR27uhKD0lqM93tqMGObUI5FPB6HvpeSzWAwIN9X2QxBEEacbC6Pn768Ez/5907k8hqmFdlw/+VLsbxufAi0+4Kbw/FMMlc0YrJZMtw0jWazeabY4VBaAS43CvQUzg5VLNtbYM1N6KqqVHQgGgU2blTGMB8Hi9Ct1p4OEu+fnSOuZMTai507ycmYPZv2mUjQMdXUkIEcDtMxWyxK78DHx9u3Wml87PBwfn86Tfvp6KBtc1laroQ0fTqdxz17VLfteJy2VVZGyzQ20msul2o4V+gkaRqNkXUYPF6ucBWN0p/BQNtpaSnCMccAc+fScu+8Q9vw+Wh/XNo2lyOnym5X/SryedWXo7/r6nDQmDnaw6V7jUblPLnd5LD0VT6Ym+K1tPTfAK9QyN/XfdZXt/ZgkJb3eFSPkcKKW1KmVhBGh3mVLpy/qAr/2NSKB1ftwM+vPnashzQmTCjH4sILL8R3v/tdTJ8+HQsXLsS6detw77334hOf+MRYD00QJj37/XF86an1eHdfAABw0dJqfPuio+G2jt9ZFqBn4zmvV6WJsBHY2UkGaV0dvc/pPtksGWxcRpXTc7gbNEc4BtsRmYXkySQZm1zFCGDhMc00FxcDW7Yow1vT6D2TiUTo9fUqDQpQKTSJBI2zUD0Xi5GxX15O2wiFVD8Mp5P2l0jQctQDgo7XZlMlacvKaDm9ns6Z16sqLcXj5DS0tdH7lZX0PkdNkkkyZrmPhNmsIhrsKLS20v7zedovoK4RO1GRCJ0jviYVFexEKEeQHYJQyNx9fbxeeo/Pvd+vHKS6OjouPoeFhjsb7X0Z9vk8jWfWLDqeYLBnL4rKSjqOmhoVjeKoQ1GRcmD5PjhUA7z+nJve3doLe5QAKlrH83FSplYQRpcvnjkH/9jUiuc2taGhLYJ5la7DrzTJmFCOxU9+8hPcfvvt+NznPoeOjg5UV1fjf/7nf3DHHXeM9dAEYVLzzPpmfPMvmxFJZeGyGPG/Fx2Ni5bVjPWwBgxrChIJ+j8WI0OQDemqKkqHYUOuMLJhNKpZdqCnzmEoHZF5/aIilffPqSwcHSkqUlWY9u2j9RwO5dBwzn9hozq/nxwHk4n+t1ppjH4/jY0dJa6Mxf+Hw+Qg+f3kPLABrmlqOxaL6qmQTNJ6RUWkWXE4aNxcNMRqpaiATkeGtddLfR4AGnsiQcty+lc4rAzjxkZVgpWrWnEvCXZa1q+nCAinonFjO67UlEyys5dHU5PqixGJ0HbcbrqmxcV0nc1mGkdlZU9jm53LpqaD9RNeL70G0PpWK61fuBw7cGazGluhc9LSou4DZrAN8Hp3a+eO4EYjnV/WXvBx9VemVhCEkaEwavGTf+/AT686ZqyHdMQZFcdCr9dj5cqVuOeee3DssSMXCnK5XLj//vtx//33j9g2BUHon94dtI+dUYT7L1+K2kEKtMea3o3nbDaVK89lPw0GtXxhZMNkUqVZOUXIaj3YIGRDnIXIfcHlUrnMaqEhCKiZeJuN/j/qKGDDBnIuNE0Z65WVykjs6KAIgtFIr5nNtK7BQMZlNEqGM5eR5Q7eHAHg8qs6nUqj0TRKD4rHaazs6FgstGwoROuGw+REcNSFZ82NRkq9ymbJCQiHaT+plGoGp9PRGKNRGid3tg4GVTpROk374WiKy0XHr2lkmHd0KD0M6w/sdnJ48nldt+aDj4Fn+DntzOslJwkgx5KjDRaL0ip0dZH+g/UToZDqseFy9ewzUeiYpNMqBa/3e73vg94URhb4Pukv3a6wWzuXAG5sVNoXg0E5o4VpgYIgjA5fOGP2gahFKxq74pheMrF+L4fLqDgWjzzyCPbu3YvPf/7zePPNN0djF4IgjDKbmkL44pPrsMcXg15HId4vnD48gfaRpPcM8aHy1dlpYHE3z0AHg2TAsvjWbqfZ78KCcsmkSoNJpciABshw7R256J0Tz2kqHEHg6EjhmCoqKBLB6U3c9M7nU2lEZWXKuOb8/aoqEl9XVqoGds3NZLQ2NalGdiUltJ/KStKYdHRQWlM2q1K/HA4al9VKjw4HpRt1dfUUHvt8av9sHHPEJRwmp8BkonUiEXrdZFJRC5erZ4TIbFbnq6KCnhuNdK45ClNbq4TMmQytazIBJSUJlJSo6AiPHaDnbW001mSSBOyRCF1Xh4POY1cXXddslpyP8nKVbtXWpkTnsZi6bwrvu3CYxtyXM9CXNqIQk4mOr7lZdUQvTLfjNDYuSsBOs89H1y8YJMewuJjWY2eI72tJgxKE0WN+lRsr5pbh1e2d+L/Xd+OuDx091kM6ogzZsWhsbERtbS10vYrVa5qGM844A9OnT8edd9453PEJgnCEyec1PPLfPfjB89uQyWmo9lhx/xXLxk0H7cNRKIzuS/9wuFlfTm9ix2PmTDLS7XYy5thw5X21talqR3a7SmPJ53umRaVSSpTMqT8WS8+0q8IKVrkcOSlz5pBRy9WHWC9hsdAs/IwZPcXonEoTj9PzUIjGUlamRM7cGbusjAx11pc4HLRv6glBjhh3/7bZVLdtTqfh2W+rlQzxTEYJn/l9jvxoGi0Xj6tu3cEgrefxkFHPnbXjcXVN7HY6Vq5wxJGJoiIy+FMpchQ4lYyrIQWDWve55pQhi4XOaVERHZ/BoIx0h0MJ4wHaV2Wl6lje0qLuIdZPlJTQNeGIV2GKHQvd2aAvpLc2ojfRqHJQC8vctrWRs+h0qmgE39vsNNfX0/nQNFXZqtAZKp4YH2NBmND8z4qZeHV7J/7wThO+9P65KHL08UGfpAzZsaivr0drayvKe7UM9fv9qK+vRy6XG/bgBEE4sviiKdzyxw14pYGsmnMWVuAHFy+G1z4xvhR7C6MPpX8ojFz0TpUqFNkWCrK5ozUbhIUVeABlxBYX0zb8fvq/0NEJBMgYnTGDtluYdsWdrjl9iWfcW1spysDVq/R6mhGPx2l7HJFhjEbaHvfAYIO8tpbGHAjQLL3VSlWTuOJVJkPrzppFzoteT45NezsZpj6fii4AqjIWp1TxeeM0LGpeR8tyKhNHEOx2Ms5ZLM6Rj1SK9sFOlsulUrpYTxIIkLNVXKwcRRZ8+/10LffsoTFNn07nLJ1W2pH2djLQy8roOfcu4Y7XTied80iE9mOz0bpmM53DQv1ETQ05HTt30j3mdNJr7DDG47ROofPHJY27unoeA9PSoqI0DOtbOjvpvE6b1vPeLi2lY6yuVo5jX2Ly8dS4UhAmKyfPKsHCaje2tITx2zf34YtnzhnrIR0xhuxYUMfUg7+hotEorFIkWxAmHK/v8OGmP6xHZyQFi1GP2y9YgKtPmN7n53y80DutqVAYzfQWxPY29Pua9e0vp71QLKtpPSvwAKqEqsVCBpzPRwaepilHx2AgMfPmzWT0cvrNnj2qDwMbsiUlNNYtW2hflZUqvWb3bjIsIxE1i85wyVWnk/bBs/qZDL1msdDYXC46Zj4/HR1kWLOuhFOLamrU8RQXK4H4zp1Ku5FI0DJsvCeTtB+jUfWOcLuVIxEKKY0CO4IsOOZme6wTsNvJcPZ4lJaAy+rW1vasmsXi8GjUhFxORW7icdpuLqeuMTscgYBqIMhOGwu9bTY17tZWOs+sDylMsysrU2WBNU0Z9sEgnavZs1W0gO8/n4+2WZjKFgjQ+KdP73nvdXTQuFi0X9hzhZ1VTq/S6foXk/cl3B5q2WRBEPpGp9Ph0ytm4sYn1+M3b+zFp1fMhNVkOPyKk4BBOxbcxVqn0+H222+HveBXNZfLYc2aNVi6dOmIDVAQhNElk8vj3pe246H/7IKmAXMrnPjJlceM6zJ5faU7mc0qT74vHI6+Df2+IhpsaPVVlpNTdNrayNBjY5E7InMHZDa+LRaa9WbxNZew3b6dZp+dThqX2UwpVw4HjSkYVNoAFlyzUWgwqNl9MqJ7jpXPCUcg8nmKAHR1kWHq8dCYYjElDE8kyFnhErNlZeTEdHWpCliBAL2+axdFhrgJXDBI+2QnTtPoj9OiXC56nsvReDweZfAbjXTOeAafu3nbbPScU5A4lYsNYL2etRTA/Pl0rvfsoW1GIoDZnO02uvn4k0k63+m06pfBvTK44zn3zOByubGYuu5+vypVy2J2jtgUFdEx9E6P4/O8fz+9ztfE6SRno6WFolHt7ZSSxvcvlxJOJsmp2LlTOYz5PJ0jvt6sZwF6plcdSkze3+dIOnQLwshw/qIqfPkPG9AVS+PqX6/B0589eayHdEQYtGOxbt06ABSx2LRpE8wFCaJmsxlLlizBLbfcMnIjFARh1Njvj+OG36/D+v1BAMBVJ0zH7ecvgM089JmV0Z797C/dqbWVDLC5cw/OW2dtQ1sbGaJVVT3HarerfghWqzK0crmes+WMTkfGYnMz7dPrpW1WVCiDrKuLDMbSUtoPN17jlCGbjbbR2qqqIpWXk3HX2Iju2XauzOR2qwgFaxD0ejKGNY3e5whANktjaW2l96mvgzp3LIzu6gLefFNVlGpvJwOZnRmPh7a3f78SEodCNN5UipaLRlUzPbdbXXOLhaIh8Tjtn9N6sllaNpFQx82CZLOZ0rBaWui9qioaYyhEY9Drab3CKIbZTPvN5Wg8s2bRmJxO8no4QpFI0HXiiAAfG1fgamtTRjs7Cek0jauw/0Z7O22HHUrW3bCD0js9LplUjuv27bTN2bNV5S425vm6zphB54h1KuzAskPGjkxHh2qix5Ewq/VgMTkTiyln6FCfo4GWTRYE4dAYDXpML7Fjd2cM7+4LIJfXYNCP3wyAkWLQjsXLL78MALjuuuvwwAMPwN3f9KAgCOOaZze04Bt/3oRIKgu31YgfXLwY5y6qGvL2jtTsZ+90J67KxIZ+Mkm6AK9Xpblwk7aWFjIkQyEynljIzLO44TAZVHY7vd/RQcdjtwMLFtCxcFOz2bPJIGtpIaOPS4PymPbsIUPN6yWjLRYDNm2ifRR2+A6FyABPJuk9r1dFJPx+1YSOezTEYkp7EInQ/u12cljsdjIquTxsOAy8+66KiLDGQdPovLBTw6k9kQg9nzaNzk1HhxJtsybD7abxslCZK1rpdKosL/evsFhoOTaG2eA1GNQyFRUq5UivV835olHlUHV20v49HjoGjjpVVtIy4TCdB7OZtkHnnHR+PPMfDitnhFPYOD0oHFb9PXw+KvNrMtG2uSJWSwtdt6IiVfGLoxNtbUoIHgpRdAWg42htpXPNkTBOd2pvVxEXLg7AlbvYQWDBv9dL54XF6Jzm1NZG6/L1KxST99Xpu1C4PZC0QenQLQjD48lPnYjj714FAHhjlw+nzSkb4xGNPkPWWDz66KMjOQ5BEI4Q8XQW33pmC/74bhMAYPmMIjxw5TLUeG1D3uaRmv3sXf+/MO3E5aJ8+44OGsuuXWoGmjsys6Hb2kpGqter+hPs20cGK4txfT6VvtTergSyHg8ZdskkjYFz8zs76bW6Otq+TkfjYYO7s5OMtVxOpRz5fKraEUco2GDlVKxolJwLgAy98nLaJ++Pox/ptBIP53I0JqdTGet6Pe2fHQjWIuj1KmJhsdA144Z3bW1UZYgNzpISFd1hZ4edCqNR9QUBaH2OzhQXkwGbz9Py2axalo1vm410BV4v/XGfDK6qZLfTNjRN3QcNDXTcrLlob1fRlHDYiooKVVUqmVRlbB0OGjNXsgqHaR2HQxnW3BTQalVN8GbNUnqRUIgiUul0zypTHF3gKlX8nCM9uZyK2tTVqQ7epaX0Opf11enonnS7lX6EU+fYyeQKWgaDqg7GWqPDFSEYaB8N0VwIwtApd1vxsZNm4P+t3offvblPHIvDsWrVKqxatQodHR3I91KEPfLII8MamCAII8+WlhBu+P067O6k3hRfOGMOvnjG8HtTHKnZz971/3unnfCMbWenMsKmTyfjnI3oeJyMQLdbbUfT6JGF1Wzc2WxkFBqNZIR2dgJHH93Toampoe0FArQuO1dz5yqRssFAM+JcqpYrM3F6Uk2NatzGAmZNUzPs3JAtk1FpWBYLGZZs0EejPQXWJSV0THPn0nnz+3s2qANUY77SUtof90zI5WisoZDq3WGxkOGbTqsyrzYb7VuvV8373G7lQGWzSv/idiutQyajNBZWK72eTpNTWFlJTiJXymJHoKJClVktKqLtRCL0vL1diZurq2l5iyWHdJoiR0VFKvWorEydD9aIJBJKW1JfT+fCYlERL+6VwQ5DVxdpHgIBVQ5Wp1O6ilhMpTBx93M+31zdCSCHatYsWt5uV529OZLGzhVrc8xmpQNxONR1MpnokZ2wwxUhGEgfjSPVoVuE48Jk56MnkmPx0nvtaAkmUD2MSbyJwJAdi7vuugvf/va3sXz5clRVVY3ryjGCMNXRNA2PvbEX33tuG9K5PCrdVtx/xVKcOLNk2NsejdnP/oyNTEaJldnIKqzKxHX7ucQmz+izYHn7djL+a2vp9XSatsNlRouKKNrBKTc8+81lU1lIyx2m2aFxOmmWPRxW43W5lJh3925VKjYaVd21TaaeDc3q62l5g0EZijYbRSm4YdqOHbQd7pztctH77EgEAqTRiMVUEzyAjsXtVj0lHA5aJpNRaTydnUr7wZWeWPBrt9M+W1pUJ2w2QNk54PKmHI0wm8l45pQpj4de44pT3OW7qIiM73CYtrVvn9KK8Pncu5fGduyx9BiJ0P7nzAHWraP1i4pUadpk0oBUSmkOZs2iMTqdZPTv3KmqSLHj4fUqR7Gjgwx0r1elGvH15IhORYWqcsXXPBpVkRabjdbL52k7nZ1q3IURq5IS2md5OS3LzhB3SAdUqhxA54QN/7IyWi+R6OnAH+qzdrg+GnxPjGaHbhGOC1OFuRUunDizGG/u9uOJNY245Zx5Yz2kUWXIjsVDDz2Exx57DNdcc81IjkcQhBHGH0vj1j9uwKptHQCAsxZU4IcXLx6xhj0jOfvZn7HB6TeRCBnO0SgZIBwdAMhI3bOHjFiPR5UO5cZ14bAScLNhXVREhiGXeGVnhSMfnDrDfw4HzVbbbDTLXwgLgdk5iUaVocSGflOTmnF2u1XDPq7IxBEfTaOogMFAy8XjtM3WVnqvvFwdE2sluAGdzUb/d3UpBysep+vA0RyAtp1K0Vg44sQ9JgA1m28yUcpOOk0GdTartAQsGOcUM07hYvF3YUdxjoSEQnS+9XoaYy5HzkE+T8exZw+tzxWpLBaKYvBxbNtGUSOrlY6TKypxyVV2JFlbwIJr7jnR0UFOCgvA2cjmhnOZDI3Z46Hr7feTMzJjBp2PREI5aBypsNnovrPZSIvT0qL0KewMNDbSPkpL1XnM51VVLq5StWOH0tVks/RXVkbngYsPcHNBr1eVpdXrB+7AF5ZNHojQe6QR4bgw1fjYSXV4c7cfT77diBvOnA2LcfKWnh2yY5FOp3HyyVOjdJYgTFTe2OXDl55cj45ICmajHt88fz6uOXHGiEYYR2r2k6MBvY2NtjZlRBUXU7ShqUnNnHPPiMZGNXtuMvVstMYlXt1uMtJYb7BvHxkxhYYbN2BjzQHnx3MefzhMBqGx17cn97AoLiYDuatLRUNSKdUsjcdYXExj49enT6ftb9lCRt/MmbT+pk1kGLOI1+mkbXZ00PlhTQZ3W2ahMFddKi5WqVMAGfKRCB0/H4PPR+fQ5aLtsnbC4VDpOyUlZCjv368cqFyOzh2nNrEDmc0qATFHQ1gYzQ5CIqFS0IJBFW1goTmfI+49wY3rQiEySlk3EQrRtQdoGyzUj0Qs3el4AB0Pl7/lcrY2mzovsZjq9eFw0LkoK6Nlliyha7t3L73HTQpjMXXcPPbZs+lcGY2qj0UuR+vU1dHxNDXRvebxqBQ2s5nurWiU7nGnk9YNhWh8rPXgaJ3bTQ4mM9j0pb66zfcn9B5pRDguTDXOWlCBCrcF7eEUnt/chg8trRnrIY0aQw50Xn/99XjiiSdGciyCIIwQ2Vwe977YgKt/vQYdkRRmlzvxzOdPwcdOqhsxp4JLeAJkhHG9/95wx+XDzX4WGhucLsNGIdfoN5vJ0KutJcM7n6eZ/pYW2g9XfNqxg4w81gdwyg9HDlgsyw4IV1vq7KT1mppUBIbTlioryTg2m5XIlnUJoRAdn81G6yaTtJ1164CNG8kYz+XoPPAsfzRK2+dIR3m5MvDmzAEWLiTjlKsncWpRJkPbbmykc8ZpS52dtG4uR0YuG9HsPPj9qmKSxaJ0KKwPicXoPLLYuLiYjrmsTBm4xcX0XkcH7YO1BCYTHRdXd2IjkXta8Hns6CCHKxJRKV+cSsSz7x4PXTerVYm1YzF1nJEIXd+dO1VvjvZ2FeWqrOTGdwYkk7Qf7urNTtf8+Sq1jcc8bRpFSUpK6FrMmkX32cKFKkWJI3MWCz3u2kXXAqDtGwx0rlpaaHuLFtH5Mxho2yze9nrV/VdRodbjqFNJCb1XVtazq3s6rYTzlZU9Z/XZgeemhoVVyvqCu81zw71QiB45BWu0IgaDSZ0UhMmCyaDHVcdT2PP3bzWO8WhGl0FFLLg5HgDk83k8/PDD+Ne//oXFixfD1CsP4t577x2ZEQqCMCjaQkl88cl1eGsPKUavOK4Wd1y4AHbzsGo1dNNXuhKnhAx19jOT0SMSURWFGK6KVFLSswkcd5o2GoGtW1X/Ba+XDD1O09E0MkZNJlq/pYX2wcZeWxt1wObGdMXFZBC2tpLRWFFBr3ElJYuFdBDFxbSfbJaMdY+HjNNAgIz1ykoyHLduJaciGFQ5+fG40kcYjbRvp5OWr6yk/z0e1ZnZ46HjY+eBZ5o571+no+vBURSnk857LqdE3eEwLcMz1Dwrz7P4HFFIJlUKFIvE29qUsxKP0/aMRjqHVquasdfplIbBYKDtcG8Iq1VpFFi3woJth4POXUeHSk0ClNjcaqVtcq8SjhYU9onI5egcAcpBaGvTuqMz9fV0flnrwI3murrU9lg4HwioEq5ms9LwcGQuGqX9ceUwLp3LmhnW9rS307VyOJSomp0Ds5mcFq48tm8fja2yku5jQ0GWhNdL56Gigs47j6+3o84C8dbWgWsWBiL0HmnGk3BcEI4klyyfhvtXbcebu/3Y74+jtth++JUmIIOyNLg5HsMdtjdv3tzjdRFyC8LY8PK2Dtz8h/UIxDNwWoy4+yOL8MElI5dT0F9uNEcrbDYyUvorc9kfrGHobWzw63a7qpRTCKfnWCxkrPn9ZLhVVND4OEWlq4sMLquVjCdOOwkE6JGNUU75KS5WqUYsSOamavk85du73aq8q8lEEQSfjwy1sjIyTN1uyrnnVBizWUUQTCY6jzyTzQY1z7jv3696P/BsO1cUSqdVPwZNU+Jhm005JlyWtLFRzQCHQkrrkEyqGXFNo/OTz9M2olFlAPMMezKptAklJXQ+2Jnbvl3pITRNjY2jFmz8G42q1wTPSLvdqudGPK6cD3aa3G61z8ZGpW/hhn6FJXr5GPi+zOdpTAYD3aOJhKroFIkowTlHnQDqYVFTo/bR1aV6UPj9dF3icXKaOPqTTFKkimf7AVqvuJhSo4JB1aW9tFSlQ9XUqPSzujo6znCYludeGFyMwGikc2E2K0eOj9PvV+mCHE0ZjGbhSFZjGg/CcUEYC2q8NpwyqxSv7/ThT+824aaz5o71kEaFQTkW3BxPEITxRSaXxz0vNODhV3cDAI6uceOnVx6DutJ+8g2GyOFyozm9YrCzn3q9KqdaaGzo9UrwyzPLDKdUxGLkRLAhyeVIeQY9HidjraqKjH7uEZDL0fa4IR6LqFmc7fGo2V/uzmw0kkHodJIBGo/Tc7+fHC52gNJpFQ1wOsl5YHF0S4vqPZHJ0PoWC+2vuZnGWFWlIgFcQchup23Z7cqB4hKu3OfBYKA0oZISSitirQeXveXyp5wuE4mo61VcrITb3KSuqIjG3dWlokeAqtbk9/dsesfrcTO3WEyVhWXBvM2mBOBcXpWrfbG2ZNcuVXUqn1dVlsrK1Mx9c7MSgXOUJZ0mgx8AEgkLiospjYm1J+m06mrOs/4lJeSgcEO+mTPJGeR7t61NNUoMh+mcJpM0Nk6Fs9uVk5tMqs8Ep7LNnk3Xme/FXI7enzaNli8pUeWP02mlHbHbaR/cl8TjofFxIQN24AFyKior+/5cjifNwlgLxwVhLLl0+bRux+LGM+eM9XBGhZHJjRAEYczY74/jht+vw/r9QQDAx0+uw23nHTXiVScGmhvNBtZAtqfSIvLdugMu5ZpIkDHFYt3qajJGbDbVNbuxUUUiOOWK12Vjb+tWMs6Ki5VomMuh7t1Lr3d20n5Yz8CpK3o9jdFspplmdjJCIdpuebkyIBMJ+mttpfdmzVL6iZISMiwNBjJoWbCtaWqsTicZlbt2UeO35mY10+5y0Z+m0Xi4EdvMmWSgs/Ygn6dz5PWqhmrNzcop42AyR094Vruyks7Dnj1k3LKxmkio5To7VfSCy9BydahgUHUDd7nIkOXjMxrJII7HlePI6UUcwchm6XyXlal7TKej8+H3qzK9gIpAALQe6SmUs8hOLTt1XC6W7zfuwB0K0bXgaAU7pm1t5GiwMJo1HUVFND52tLq6VHNFk4nOITe1q6pSDg+Xs9U0Vb0qm6Ux7N2rihKw+J/LFnP0j3tlcFqe1arSo1hH09ravyE+HpvdjaVwXBDGknMWVsJlNaI5mMCbu7tw3AzPWA9pxBmyY1GotyhEp9PBarVi9uzZ+NCHPoRi+YYQhFHj+c2tuPVPGxFJZuG2GnHPpUtwzsLKw684BEYqN7q3RiOfB7q6LN2z/Q0NPWfJOQJhsSiRNndIZm1ALEZGW2urynnPZskY1uvJKWHDkTtpswHK2+DqUry9zk41q88GIleVstmo7Gk0Ssarz0fHwukmXAK1ooKMp/Jy2n40Sv+Xl1M6DkcFeKadqxo1N6vjZONSr6f9d3SoDtpmMxnyXGKWe0LMnas6SvPr3KHablcVs7hbNaA0FlxulQ17bt5WmIfPVamqqlQPhWSS1rFaVQ8P7lPB22dno6iIjiWd7nl+ObLBx8TaB9YwcPNA1ivwulzOlsdGOgdTd5Qmk6FxctoUNx3s6qJrl8lQepvFopwo1oA0N6sKX6wzqaujcUYiqrQxO7h8HDZbz/uMnQDW1rDjyueZO3VzU0aPR0Uzpk1TmhKm0EmYaJoFjmwerkO4IEw2rCYDLlxSjSfWNOJP7zaJY1HIunXrsHbtWuRyOcybR80+tm/fDoPBgKOOOgo///nP8eUvfxmvv/46FixYMGIDFgQBSGZy+N5zW/Gb1fsAAMume/GTK5dhWtHoicEKc6N55rww3WkgudF9aTSoC7UZ27crIysSUakxnGfvdpPxxo3LXC4yKrlXABso7Kxwc7JZs8j455Qju10JhTntpqiItpfJ0Pj8ftXvoryc9svRAc7F5xQtFhnn87QtnpFnQ5JTUTweEuy2tND2IhFaLhCgvx07VBSgrIz2zU3RCjuNc8SipobOSWcnnYeqKlqnokIZuGyYc6pZLEZjZZ0DL9PRocrTcnoKa0F45t1gUA6QpinxeGUlzaCzMc2VqHI52hfrR7hrOBvnHFXhTtws1PZ4VISD1+XyqizW55Q8i0WlXgH0nO/LTEbf7WwUFdH91tlJy5aX0z3U3KxE7tx0jkXPfj9FxLjkMOtr2tvpXtLpaAysseHu7Pv301imT1frZrOqHDI7JezsJZM0rrIy+uN+INlszyjFQD6XE0mzMBbCcUEYD1xy7DQ8saYRz21uxTfPmzfWwxlxhuxYcDTi0UcfhdvtBgCEQiFcf/31OPXUU/GpT30KV111FW666Sa88MILIzZgQZjq7PHF8IUn1mJLSxgA8D/vm4lbzp4Hk2F0LQcWhe7Zo7oJc448p8f0lRtdaDgUajS4ck5HB9DebsfLL5OhPW+eMugdDmUk63Rk3B34uoGmqa7YgYBK0/F6yXD3+WgbnI5UV6cMbL9flT3lCEBzs5oV5zKkPOvPKTdclpZngDlv32hUM/NcHpWNds6zZyOU9RBcUUnTlDaDIyDxuDJ0ARW90OlUXwlOGwuHyRDO5+nR6+0p5uZeFrkcHQdXPuIIAxu47NSwfoBLlrIAmo8xn1fH2tFB+6qsVOks7AzwNmIxum41NcpR6uykZd1ularjcKjIDh9HPk/Xxu+nKAOnxplMSrDM6VZmsxJS53IAoHUb1SyY5lQ5QPXKAFSvknRadVz3++ke4hK4XGnJ66UUJquVnDmTicbPqWjc54LF13xPsPHPXcdZiK7X0/5276Ztut10r06bdmhDu/BzNZE1C+N1XIIwWiyr9WJmmQO7O2NYta0DfXxsJzRDdizuuecevPTSS91OBQB4PB7ceeedOPvss3HjjTfijjvuwNlnnz0iAxUEAXhmfTO+/udNiKVzKHaYce9lS7ByXvmo7rOwNCgbm5yWA5Dx1d5OqSSFmY+c8tTVpdKQQiFK7eDyp11dZBwmEkZUVtI+9u2j1+x2MuJsNlXhyWSifXD/Bs6ZLymhfQaD9FhRoToWc+Udi4Wch/37yahjQ27GDFo2laLx8Pomk0qt4vU5ktLeTttm3YHFQstyKdVwWPWFqK8nZ4kdjdJSOp62NlquslI1qHM66fiCQdoW5/kbDDS76/erjuKplOo0zVWaUikak06nUnySSTpmjkDY7TQWFlBzuhlHFThth685P3L/Bn5fpbEpjQTnyXM6WjqtNAHsILIDw8uxqJurY8VitI9C54W3U5gexl2+eaabIzDs+KRShu5+GXw9WHfR2ak0DHz8+/apfhmhEJ2/YFA5E9wYkPU9XMFK01Q/FINBRZs6O2k9o1FV5Coqom0Wir+5opnPR+l1ixbRPdufwd1fuWdANAuCMBHQ6XS4cHE1Hli1A//Y1IYPl4z1iEaWITsWoVAIHR0dB6U5dXZ2IhymmVSv14s0lxkRBGHIJNI53PnsFjz1DuVZnFBfjAevXIYK9+glI/c2YFhHMGOGMq64IhHrC3gGOJmktKCODlomkSBjnBuHGQz0Wi7HgmoT2tvJ4GxpURV6KirIEGdxcHU1bRtQ6SSpFBnWLFDmmeJwmLbBYvOmJjXOXI5mobnJWDBI++bUDNZTuN10/DqdMmhZ+5HJKGPTZlN57l1dKprAY9yxQzkAXBqVZ5LTaTI6DQb645nzSESda+7HEImoNCjucB0KqdKnzc20j5oalR7G1yOTIWOV06H0elUhi1ObOIWJdQlckYjL5XJakstF28hmlXPH9wI7Ldzvgs8/RRGUcDuVUlEYbjDIlab8ftX7go9z586ezoTJpHQKhSJzo5ErTuWRzdL9FAjQfcTi6K4u1WODnSY+L/v20X3Lzua6dXQ+y8uVroWvcy5Hr9fU0Hk3GOga8LljPUU2q6Jtzc3q3otEVAoaRyvY4evvM9lfuWfWtwyl3PNoIClO4xu5PmPLBYur8MCqHfjvri6cM8lkFsNKhfrEJz6BH//4xzjuuOMAAG+//TZuueUWXHTRRQCAt956C3PnTs46vYJwpNjeHsEXnliL7e1R6HTAF8+Ygy+eOQcG/ej1i+ltwLBeIJdTVYSKinoKoHn2l0XW+/erpnmsKYhGaVYWIAMzmyXDLJnUdzdus9lUhZ9IRM22hsMqTYhn8jkFhnPSPR4VWeAcfv7hZAeCZ65rakjkzBoGTuPhRnder0oxSibptWiUxs3LA2SgcppNPK5mo3lmntO5wmFg/Xo6Br0e3Q0BC0uQskHOuobdu5VBzqVbKypoGTYGODrB5UltNmD1ajJYeTyc9sQOBne95nPIla+4+lIqpRrEseiXoxhscLMAmYXXbEwXVmzi1DPWgbjdlD7Ejkg6rUTzXDqYH51O+uO0Lx4ToLQU6bSKbLBQnNPPLBatu3wrlx1mIXRREZ2zjg5V1cvtpv1ZLBTRCgaVM9nZScsYDErgDZATu3Sp6h/C1Zd8PiX0N5uVVmLPHjr3tbXKkWLH0uOh5bu66Hz2ZeyNVrnnkaSviMrhGvUJRw65PuODORUuzKtwoaE9go1+HS4Z6wGNIEN2LH75y1/ipptuwhVXXIHsgSLiRqMR1157Le677z4AwFFHHYVf//rXIzNSQZhiaJqGP77ThDue3YxkJo8ylwUPXL4UJ88uHbV98ixWW1tPA4ZTWLgUZjDYs2Y+N2nL52kbTU1kHIbDZKRxc7l0mhyLdJpSPoJB1hno4HarvPOyMjKM2BHQNPoxDIUo551TaDIZ1Wlap1PiYE0jA5IF1i4XOzBqtri0VIm/OcWmqUnNsPt8ZBA6nWS0NTXR69yYrLA/QUcHjZ1TT9jY5cZvqZQSWvPsNKfTsPHPjg2X9WXtgMWinA42mktKVE79jBl03vfuVc4bN8Jjslm1fqGjwIYFN9pj8XVhZS2DQaU9AcqRzOVUihugIlg8q8+vsxHOFbk4hY4dUZdLNYZzuZQTxtWZOOWIDXcWZBuNdL5YHwKocsBut9LGGI0qwpJI0HWaObNnqWDuWs3nlTU1Op1K0YrH6b1p09T9qdfTZ8Vq7dkckqticWUsLhnL55w/M+ykuVx0Px7uszmS5Z5Hg/4iKgNt1CeMLnJ9xhcXLK5Cw0sRrPON3iThWDBkx8LpdOJXv/oV7rvvPuzevRsAMHPmTDidzu5luDO3IAiDI5rK4ht/2YRn1rcAAE6bU4r7Ll+KUufoTEEWzmIlEqr0qc2m0k14Fp2FxoV18QsrzyQSSj/BKS6c4sEGYzxORjhrE8Jhc3cVHZ6NLyoio2/DBpXGY7GosqAskI5EVOO0eJz2y0Ytly6NRlXDvKoqlYbDqVic6sNNxLhnQiRC2yssu8rZnZpGRhxXJ9q1i46FZ59Zk8AdvDmCwhGP4mLqWM3VfLxe2i/rAgwGdSwGA20zGKRluIoQi8G9XtWzgscGKMObU5pYu2AwqLQnpUmgdQpLlxoMPcu5snjb66Vxc1oYG8mF0QNA7Y/PNc/6R6OqxG8goJxE1rBwWhN30Wbng6NTnBLFx8KN9LjCFKVj6bob57EjxPqXfftUlSmHg5yyZJLW6+xU9008rgywkhL6PxpVepLWVpWS5ffTGGbOpNfCYXIW3G51nmbPpjFyF3UufsCRNp9PldrtTX/lnnkyoLCPx1hxuIjKeGrUNxWR6zO+OH9xFX780nZsD+ngj6VR4e2nZvQEY9gN8pxOJxYvXjwSYxEEAcDm5hBu+P067PHFYNDr8OWz5+IzK2ZBP0qpT8kkpdwkEir9hBuz5XJKh+B0ktHsdiuRLFNYeYa7V4dCZIAGAqqWPhvBgNofGZx5mEz0A8dVf3hGP5+n1JGiItJpNDaS0TZ7NjkZsRgtu2OHqnbEYystVaLkGTNUtIIrUvGxcU+MVIqMc65oxF2WOa2JDVsuTZtOK6eqpITGwbN/gEoxam8ng5X7VFitylnh5ywyTiRo/5wKxhESo1GdR943O2zBoEohMpvpOTsC2az6n/UEDDsUrLPglCl2wtgw5xQj3i8b4XxueD+ASlfi6kccUeC+FSzGBsjJ4nPAkRFOJeP1eLyc7sZpTWyYM5zSxfodTdN19zLhFDu+1m1t1C/FZKIO6lw6t7OTrl9Jier5wR3Ey8qUiJt1IjwWXoYrU5WXq/2yLsZgIKfD4wE2b6ZlHQ6VEhgK0fb6qwbVu6xsMqkczUKno6ZmbCIWA42ojKdGfVMJuT7jj5llTsyvdGFrWwQvvteBa06uH+shjQiDcixuvvlm/O///i8cDke/DfKYe++9d1gDE4SphqZp+O2b+/Cdv29FOpdHtceKB69chuV1o1fSJZkE3nuPNBGcUsQlK7kSE6c9cUfqri5laLNxXFh5pjBVhqsN8Swzly0tLiYjm2ejUymtu1szl/HkJmVsgHV00PJ1dSo/vrpaldvk8rG8D27UlkrR8fl8tHwspgS83NuiuFg12WNRMpeSNZnIKOYoSyZDxltxMW3X7aaZPi47azarNBteXtNUBSc2HHlZNui7upShzqVd+TkbjuwAcHnUXbuUM8LN4EwmVXKVjX5u7sZi8t6z2zzzzw5IJtOzLwIb5LGY0gQcqNHRvT/eBkc1gJ46EC49m073TDkqLiZDmEvIsoi5tVVpTjgdip0qjr7w/vg+Y0eDKmDlu+9Fi0U1Pty/X10Pg0FVbDKZlB6GtR8mk2oWyM5EPE73J/e14MfyctpvIED3XX29Sn9ifYvZTPdgIqEcLHaW9HpyoPvr7cDVo7q6aJzcP8VuVz009Ho6LtYUHUlGqoGmMDrI9RmffGBhBba2RbBq2xR1LNatW4fMgYTZdevW9bucrr+SFoIg9EkokcFX/7QRz29pAwC8f34FfnTpYnjto1fhmiMVLS2qrCt3R+YfGE7P4eZllZWURmIwKOPVbqfIABsyJpOaseUSsdwhmQ0lTqnKZOgxFDJ1N6/jbfN+WZhstVKzu1BIVQkyGGj2mUu4VlYqA9PppLFyOk00Ssu2tJDhZ7fT+EIhVRWqrk5FNOrqgLffViVYOYoD0LGx9oIrUgGUjsV6CJ1Odb72+VR0gNOlvF7ahk6nyufydWHjn41SNjT5HPN4fD7VmI7PF1dlYgOfZ+OZQo0Fb4sf+ThYB5DPq0gJV9Pi6lGso+AZe06XYueE1+excflgt1s5NR0dKgLE5VdtNi5BrEr0skaE989jzedpuzodrWe3qygPC6DdbqV94HuPRdt8D3BqFkfiHA7VgNHnI+eHK0lxJMXjUcfJ4nWbje6N6dPpWNkp4HX4/p81i5wOLsXMqVZ2e9/CWh5nJELj4YjHjBm0fS5sUFmpUhGPdErLSDbqk4pFI89EbaQ42TnjqDLct2onVu/2I5HOwWY2HH6lcc6gHIuXX365z/8FQRg6G/YH8fkn1qIpkIDJoMNt587HdafUjbqD7verdCSuxGQyKZE1N/zimS7uYzF9uopu+P1KM1FSQgaYXk/LhMMUEeCymyyiLi4mAy0YBObMoRn8hoZ8t7PBM9ednSpVJB5XXaojEaWb2LuXKu1YLORc1NaqcqVbt9K43W5VRYhFytwcbdo0GhenulRUUEoVHzfrOjIZ1Z05HCaDUNPU+eMqSYEAHR/rVFhUzkYtG/6cssXRFDYkeTaxcNaQZ+fZqOZZdr4urJ9gzQmnGfFMe18zkHxrcQSDDWR2yrhpG0cDAFUxi3UGhSVo2aHgiEohnJrGvUC4KhVHGRIJlcbEx8GlXwvPQSpF59poVGl6fL8WRkt4DIXpWYUpWexEejwqMsOi9lRKpWPlcqpR3/TpZNDzteGoCzus3MgvmaT7tLy8Z8Sgd5M67jpdUqIMaE3rmZLI4+PPitdL9xZHqyIRuve54hT3CuGKY4NNaRmuMc+NDYfTqE8qFo0eI3F9hJFnXoUTRWYNgXQer+/04awFFWM9pGEzLI3Fa6+9hl/+8pfYvXs3/vjHP6Kmpga//e1vUV9fj1NPPXWkxigIkxJN0/DYG3tx93NbkclpmF5sx0+vWobF07yjvm/Ot2UHIZtVRi33aOAUG85550pKdjvpELhHBRtl3Ol61izartlM221tJUMum1XGdEkJMH8+rdfaCgB6LFjQUxPAzeQyGSXK5XSPri4ypDi9iKs2cfMxnY4MPu4T0d5OxzNzpkq14lz8eJyOhY3kPXuUgJcjN1xpiJfjBmgAPdrtqqmZ00nj8PlU9Sg2ktlwLXTceIadHZC+YKFyIqG2x6LqZFKJtAudCJ6BBHo6AYWds3nbvDzrEHqnRHFJWItFnRcWV7N+oDA9iSMebNizA8GRimyWrk1VFfcxUQ4G0LOqFDs6XIXKaFQicJeLzrfJROe8sFM4N9Hj+4g1H9EoOZGs4+AeJDzrz4J4/t/jUWWLq6pU5/LWVuVkp1K0HY7QRaN0v3CUq78mdWzE9ZWSyMUC2Nhm8T/3zqitVWVwCw3Cwaa0jKQxz071UBr1ScWi0Wc410cYHXQ6HY4u0vBauw7/3tY+tR2Lp59+Gtdccw2uvvpqrF27FqkDv5yhUAh33303nnvuuREbpCBMNsJJSn3652ZKffrAwkr88NLFcFtHtyoEG15s4Ho8qtOwx0PGRXu7MjI5XYebfDkcZNTv369y0NmQzOXodTYiw2HaZnGx6gXQ1kbrLFtGr+/bR0aYy5XuLuvJhmxZGf0AsriVy5YajTROjgJw7nlHB6WI8EwtG+But/oRZQN13z41k86z+vv3U3pVKETnIJejMQYCPRvgcSlW7hnBBi87BY2NqlQuG9qAqnjEEQZOl+LZdjbC+4NTqbgELM/Os+PFf4VRg8KSs4ByYHpHFQr3weej0IDnKk3RqNofbw/oeQ+wrqF3ZSc+Zv7jtCMWSbODwY4PGz1cWpaNe3YceFzssLDzxqVfc7ksXC7lQBsMdH+5XHRPcGdydmIMBhqHw0EOA2s9uHxvVRUJveNx0rbs3686jqfTtJ2SEvrjKFh1NTk1xcUqPat3RKCvlMRYjF5jjY7dTg6v3a6iPqxJ8vloHE6ncmb4fBwu+jDSxjz30WBHZTCN+qRi0egznOsjjB4LizW81g6s2tqBfF4btUItR4ohOxbf+c538NBDD+FjH/sYnnzyye7XTznlFHznO98ZkcEJwmRkc3MIn3t8LRr9cZgMOnz9vPn4+Mmjm/rUe1YyFCIHobKSflBYCNzVpQx27hFhNKqeAoEALcsGaDCoZs69Xvr/vfdovZoaMrhYZOpyKdHq+vVK9EpC7RR8PtWRmvfd3k7rc0dmNkQBMjhsNhV54Bl/vZ6WZcOYRblFRSplafduOhbuxMy9BrhjNhtnoRC9Fo2qfXAUgkvishEXDCrjtLNTOS6chtP7f9YK9BVFOBS8bmFFJ05/Ag6/nUM5FuwgsRNWGBEprArFsEPUOwLCjiigKlrxeuxosRieIyE8NtZrcOSKl+fjLTx3HGXjhnscZSBDP4eyMqXvYS0GO6GxmCosEAjQflpa6JqWlalStFytbN48Gk9pKW2/pYXuT+5E7nZTat+MGUo3wzP/h4oI9E5J5IgIR8ZyOXqvq4v2WVxMTk1rK9278bjSL/H1KC5Wx3yo6MNoGPOc5jWY1CqpWHTkGMr1EUaXOW4NDrMBHZEUNreEjkjWwmgyZMeioaEBK1asOOh1j8eDYDA4nDEJwqRE0zT87s19+N8DVZ9qvDb87OpjsLTWO6r7LZyV5NSk9nYyTgBKSTKZlHDbYlEVnMJh1WOhvJzW27OHfozYAGdDtbVVlYudNUuJtlta1Gx+SYlK2+H0EypPa4XBQNtm8TenOLHhylV1jjpKGf7t7aokKAuluSlZNKqiFry/jg5ajiMSDofSggQCJNhmbUIqpXL4ebaey6ay6JtL6brddKzpNHXz1ukocsEGazarKgCxwciVn1KpnulDh6Ow9OtA12F4edZqFKYqsVHPWgm+rvm8SlPifRZWYeLX+9oPVyfilCoeO8AlYdV2uD8Kj6FQ22M09tw2d8DmsXo8ZEDnckq87nZnUVystDmczsWCcaNRpWCl08qo5YgWn5fSUrV9bmZYVERjb2lRUZBFi0jvwAZ8SYm6vzlVijUQHBEoLT04JTEcVqWEDQb67PL6fj9pgHQ6+oxwqWVNo21zxaiSkp66pL6iD6NtzA9mHalYdOQRZ2L8YNQDp8wuwYvvdWDV1o6p61hUVlZi586dqKur6/H666+/jpkzZw53XP3S3NyMr371q/jnP/+JeDyO2bNn49FHH8Xy5ctHbZ+CMFwiyQxu+/Mm/H1jKwCq+vTjS5fAYx/9hjitrTSbbjRS7X4W6Xm91KBtzRoycJYsUaknFRWqtCUb5YWdrf1+mtXlCkptbZSSEQiobtuVlfS8q0sJXIuLVapTMqkq3SSThu6ULHYiWDDNlanYgGJjnJuZsfCcK5pw+g5HKuJxMs541jcSUWk63CsiHlfpWsXFqswsRxN4pt5sVs32WEvR2anExpkMHTvPjBc2oSvUObDBzkb2YB0ENtKHCoulmd4GG5dX5WgFpx4VOkcsiOcGeYUUPuf0No5AsHC00BlhsXjhOPg5ny+jsWekwmpVZXvtdjVjz4E/LlXMYm+LpWdqWiBAj263ch41jbZlNqt9xGKqkpjHQ9tob1fnxeGgzwuXlOUIjMlEnwt2YEMhVa3M66X71+frmZLo89Ej96Hg49q1iz6jsRjdX0cdRZ9hv5+Ox+GgKFw+T8fDzfv0eoqg9BV9GE/GvFQsEqY675tTihff68B/d/pw01lzx3o4w2LIjsWnPvUp3HjjjXjkkUeg0+nQ0tKC1atX45ZbbsHtt98+kmPsJhAI4JRTTsHpp5+Of/7znygrK8OOHTtQVBjHFYRxxnstYXz+ibXY44vBqNfha+cehU+eWj/qVZ+SSTIuGhroR3nvXjKiZ89Ws1W1taq067ZtqgpOaSkZU/k8rReNqllyNqz1evq/qYm2yzPAbW1kyGzbpqorsQCc06Jqa1VZUWr2Zeg2irhhGhuvvG02xjo6VGUiFntzrns+r3olAGq2mCtCBQLKODGZVC8BNhK5LGkspnpsFBrGnKJTWBmKdQ9c4YcNZjbMw+GeGhF2Kno3eBsMw3EqgIMjDL3h9K7CiAY7bazx4CgEcHDEhZcrdBYK07cKO4Cz9oL7dbDByw4EnzsuAOB00va4kSBfL7eb3ispofU5dY8jVgaDSplix5aPjY1rjsK53aoJnclE22XdEDu/nLrEKX3ccK+8nJzTXI4+G+XlygHiRnjJpIoq8PXwelWKYnGxihSFQsoZYmeJO7RbLOQscId7jopoGp2THTtou31FH8bamO+dijOcikWS1iNMdE6aRcr59fuDiKWycFiGVVtpTBnyyL/2ta8hn8/jzDPPRDwex4oVK2CxWHDLLbfghhtuGMkxdvODH/wAtbW1ePTRR7tfq6+fHA1FhMmHpml48u39uPPZLUhlqeHdT646BsfOGBlH+FA/ppz+xHn/nJbEjbRKSlSaSqFI1elU1YpaWpSGgcW1hWJcNtR5+c5OMnA4vaSri8ZSWqqiCuk0GWcdHcowjceBzk5rd5UeFuFySlIwqFJIjEbViyCRIIOJRbE8M8yVg3gZTpHhXgWFaU4ciSkpUVGHaFSdE71epZiwcJt1Gtxcj6Mo3HiPzx032GPHqi9x9limdhSWnO1NKtWz3Cv3WijsIVHonPSOuHCaV+HrHE0obPjHIm12KAob7PFzToNiXQ87BNwfIxZTehpNo3uAtEFad7Ssrk5tk50HvpdZhF/YdZwrRLE2J5GgiIDXS/vweGib771HaVM2m3IUkkn6HOzeTcdYVaXONafWsXaHHQGOUrDmY+9eOp5gkO7DhQuVM8t9RHisvG2PR+2bzzNXT1u4sGdDRGDsyo/2V4XKbh98xSIpTytMFmqL7KgttmG/P4G39vhx+lHlYz2kITNkx0Kn0+Eb3/gGbr31VuzcuRPRaBQLFiyAk6eTRoFnn30W55xzDi699FL85z//QU1NDT73uc/hU5/6VL/rpFKp7opVABA+0C42k8l0N/sTBg6fMzl3hyaWyuKOZ7fi2QOpT++bW4p7Lj4aRXbzsM9d4Y8pOxa9f0zb27naEhkaHAFgfUAwqKrX+HxkQHB1kGiUekBEoxRZAMio4bSkvXvpBz8SUWlO4TA9j0ToOafOcNlMTp/hRy5XW1MDlJdnEQqlYTRm0dpK43M4VBMygP6PROj/mTPp+AEyRDjNig1Wdjw4xzwapWXZIeptXHFfBc7tz2QozaukhMbY1UWvc8MzbkrHjg6L1gurNKVSPftKDDbV6UgwmKgHR20Gug6XeS2EZ8g5DY0dlEIRO6eecXSj0Enk2XN25DiVjR3sYFB16Aay0OnyyOez3VE2o5GuKWsL2LG1Wul+42pM4TBtx+ul5Z1Oeh4O0+eJy/4GAiqSEQyqHizhsNJ6cMGC3oa72UzRxOJiSlWKRMhJ0eupt0ogoPQTVquqpgZQiiFXj9qzR1Vw42heVRU9Z6eptVVFUvj+ZlwuGi+XTGZjnrVWLpe6n0ciIsATHtwxnD9/nZ30f0mJqvrW+7uNncGBbCscHp3ytPL7J4w0hffUSfXF2O9vxmvbO3DqrPGViTOYe16nacMNqh85rAe+JW6++WZceumlePvtt3HjjTfioYcewrXXXtvnOnfeeSfuuuuug15/4oknYLfbR3W8wtSkJQ48tt2A9oQOemi4YHoep1drGIkKcum0Hl1dVmQyBlitWRgMGnI5HaJRIwwGDaWlSZjNeXR02GAy5WE0aggEzOjqsqCjww6LJQeDQUMyqYfFkkNHhx3BoKnbYJw5MwSzGejstCEcNkGnA6ZPj8LrTcFqzSKf16GhwYvOThv0+hyam51IJg0wGmkDkYgJyaQJBkMOiYQBuZwOJhN/xehgNGahaXpomoZ02gCXKw2vNwOnM4No1IiODhsyGf2Bkq5ZTJ8eg06XRzBoQzarQacDKiricDjIUg+HTYhETIjFjEinjQB0MJvTSCbN0OtzsNmyiEQsyOV0MJtzADQABgDagTQbDbmcHgYDeRs6nQarNQOzOYd83oBg0AxAD4Mhh3xeB0CHXI4uZDJpPODQaLDZMtDrczAY9NDrNeh0eYTDFoTDJuRyhuFf+EmATqdB03TQ6fIwGvMHnAS6FwwGDTqdDvl8HqlU76T/PADyUvR62obJlANA62azetjtaRiNGvR6WtZmy6KyMo543IBUyginMwubLYtcTo9MRo9YzIhIxIhEwgSjMQ+bLXdgbBrM5gyyWT2KitKYMSMKvV6HZFIPjycFhyOPQMAMkymP2towdDoD9Po84nEjbLbcAcdSh5KSBNJpI1IpPWy2HDwe9aOcSOgRi5nQ0WFDTU0UFRVJ+P0mxOMGWK0a8nk9gkEzgkEjslnars2WhcmkIRQywWTKwemk+9/vNyGTMcLrTWHPHheyWR3mzAnDaNSQTBpgNudgseSRz2uoqopj1qzIQdclndYf+Nwakc/roNdrsFqzcLlozP29ZzYPPtzW1WVBLGaG03mwkRKNmuBwpFFSkkImo+92LEymvvcz0G0JwkRhrU+H3+wwoMau4StLxtdsVDwex1VXXYVQKAS3233IZYflWKxatQqrVq1CR0cH8r1i+o888shQN9svZrMZy5cvxxtvvNH92he/+EW8/fbbWL16dZ/r9BWxqK2thc/nO+zJEQ4mk8ngpZdewllnnQVTf6q/Kcyf1jbjrr9vRTKTR4XLgvsvX4zlw0x9Kpwt7OpSXXj5vWCQZjb59ZoamrErK1OpI+3t1OMhHKZZQa7B39ZGs5N79tCM4FFH0R+n9vj9FCHgak5NTSQkbW2lMbW10bI2m4oSAEqYXSim5dQjbqjG6R86XRapVAJFRTZEIsbuVCOjkY6B0zHCYdoWl8gFVGWgjg4aG6ce8QxyKtVTNMvC2kRCvQ+oWWVOveHxc+8OTaPtZLMqlx1Qs+vcuIx1A7yd5uae5VmnGlxtymRS17+wElRhpajCHh+F63M0il/nNCBAnW+nUwmpqSt3Fl5vAEVFRcjljHA66XqzDsjno3skEFCpcCxO54pn5eWUQlRXB2zaRJ+DBQvoPkskqPIZp17FYj2b8NXW0meD0504NSkYpIgfF05cuJDG1Nqq9Boej6o6xjoenY4iG2433VMAHU9Hh+rHoWn0WeHoCEdiUimKYpSXU8nc/iIOrAUyGmk/vSMCvaMZhRGBgUQ0Uik6du470xtOg6yrG1h52pHa1mCQ3z9hpCm8p8KpPE78wX8AAGu+thLFjj5u7jEiHA6jtLR0QI7FkFOh7rrrLnz729/G8uXLUVVVNepCVACoqqrCggULerw2f/58PP300/2uY7FYYOnjm8VkMskXwzCQ89eTeDqL2/+6BU+vbQIArJhbhvsuW4IS59B/1XrnD+dyZAhVVNCPfDJJRkUqRQaE3U4GTjBIRgnX1mejLp8H1q0jUTVXMGpro+24XGRcdXaS0VRVRUa9pikDyedTWgY2dsxmMkgKRbG8bS6jymlRnMPO6SxsdFKKgx7JpBFGI91TrG3IZOhYKitpjFwtinUXvIzFopqQNTUpQ5W1DfxnMtE5YsE65+/zWFh8XfjHaTgAjTudVgYtO1WcG895/pwqNnHiwaND4VcEi6RZ28DnsVBv0TtljOeruIoVL8P3EV8/1oDo9WRcUwd2A5JJI9xuGgQLlzm1ye+n+4dTswo7iXMPk2CQ/rhqE6cXFfbdyGZV7wdOv+PtGgzUbC8QIEOYU/24QtZbb6k+FUVFqvFdJEJGscNBnzmDgT4DvF2fj/Y9Zw4t19FBY7NalXPPeqPqalqOP4+9v7b70ilw1/Jcjr4HGLOZtsvaKi7IMBCNA/fa4H4iveGyxX2NsTf9bYsdHE6bG8i2hoL8/gkjjclkQqXdhKMqXdjWFsG7+8M4b1HVWA+rm8Hc70N2LB566CE89thjuOaaa4a6iUFzyimnoKGhocdr27dvx4wZM47YGAShNzs7Ivjs79ZiR0cUeh1w81lz8bmVs4fVPbOvjrjhcE8xdjBIP6SsQ2Bjt7SUjIvWVnIsAPqRnzuXtvXyyyQ47ehQpS4rKsi4iUbJuWhvp22wMNrnIweDG7JxTjfP1hbm37Njkc/3bJ7GQl3ug8DOBlXtoS8tdoK4AZ3RqErNlpYqB4iF1Owo7N6togZsXLABByjDlMcG9Nw+Ozis5SgcNx8HGzCF/R34dRaKs66Ay9NOdccCUBoJbmDIs+JcDQpQjkIhbByyk8qiZW4ix8/ZaWQdCFdxyuU0VFUp45d1H9GoagLIWoR0WkUMuHoUV0qzWsno7+igzuzc1yIUov00NdHnjEszcyQhm6VtctNGFoO3tys9k6bR/bZnD32e6+vJEQkG6TPH2oLCMr/ssNTW0vJ6PX1XNDTQOLhTPYueKyuVzqf3Oe6v83Z7O30PTJ/e9zV1OFTUh6M2h+vaPZJVqHpvK5lUkdvCMro1NSq6KAgTgePqismx2BcYV47FYBiyY5FOp3HyySeP5FgOy0033YSTTz4Zd999Ny677DK89dZbePjhh/Hwww8f0XEIAvPntU34xl82I5HJocxlwYNXLMNJs0qGvd2+OuJarZTqFAgo4WphrQSexdPraZZy3z4yEIqK1I++Xk/lZsNhMtaKiriPhErZYXH3/v09ewQEAmQwWa09RazcxKww5YcNQJ6ZZcNSr6f/2Sjn1CV+n1OnuGdESYlyKFwu1Y+Dm7txR2weSzZLx8LiXI6ssIHP+3E6VSlTdii4alAspvomcKSosLEcz6KzgcznjI8VkEZeDEci2NHjqEXvPhqF0QqOHnHDPoavEd9nHJECVOSK7xuqCpXC0qWUuhcK0T65hC6XJ+5dEpedGIDu+0iEChksXaoiFZzSxFGPjg56jwX/nLbHn1eO6HH/C4uFnAIeEzfY4+7vnPLE0TNNI+cAUJGBoiJKxeJJBS6f29KijHN+r6NDpUlyKVs2+PvrvO12U78MLuPbG3bWXC6Kbhau21/X7pGsQlW4LU7J5JQtrnyn15Pzw9XvBGEicMwML3775j6sbQyM9VCGzJAdi+uvvx5PPPHEqPWs6IvjjjsOf/nLX3Dbbbfh29/+Nurr63H//ffj6quvPmJjEAQASGZy+NYzW/DUO/sBUNfM+y9fhjLX8BN6++uIy8Zzezv9kOp0NCPn8dCPZzyu/jebydCxWlXdfS4bq9eToWGzqVQmn08Zx6yVYMPZ51Mz8tyXobUVBwTWZOiwMcCGnk6n6ulzSgXQsx5/KqVKYOp0um4HgPsTcOpLUZGKLOj19D73rGC48zXP7vJ2WQPB5PNKQ8GOGM8Cs66k0BDuDRvAfDzsVPXu1SAQvUvssvaksGxxf8VG2Onjc8pOCtCzFC6npLHjwY6jxxNHVRVFFDi6xc4koO4P7i6fzZJByk4POynBIEUqTj5ZpR21tJBzUF1Ns/p+v0pZyuXIweCKRpw+5/XS/isr1T7YeXA4VO8NTm3krvIWC63D92gqRRFGdhwA+jwsWECP/PmJRFRPF67oVhhN0On677zNEZZgkByR3sZ+NEqfoap+JlT769pdXDz4krL9wdvat4+2UVKiesw4nXTOEomDHRxBGM8cM528/C3NYaSyOViME6/4x6Aci5tvvrn7/3w+j4cffhj/+te/sHjx4oPyr+69996RGWEvLrjgAlxwwQWjsm1BGAi7OqP4/ONrsa0tAp0OuPHMObjhjDkwjETZJ/TdEZe7WwNkUPj9ataQy8ryzBz3IOC+FewMsEi1q4v+uLGX1arypGMxeuSUDhaSBgKqURkLanlcnI5iNisxNf9pGm2fDcTCPPbCUqOZjK47hYmjMSYTHQeXd62sJOOJZ7ybm8nBSSZVQ7tkUpU05f2bzWrfgNJNAMoxYrEnp0oN1DkoNJwLnSahb3pHfwx9/Gb2Pn/s/PH/hZEN7q3BJWi5Zwjl+2sIBOgePvpocggAclRTKfoMcPoa/3GUhO9TQDVNDIXISTEaSQTNs+BlZSqFLpmke4rv4b17KQLB2+Ju5XzfczSP+8Ww48znih1wHnsqRQZ1XwUNrVZVinnnTlqn0HEOBsngTqVof0VF/XfetljIEWlu7vt+5jK4/VWX769rt9VKTg1/33CBh6KiwfeesFopmslj5BLQHg+NnXvf9OXgjDbSsE8YKtOL7ShxmNEVS2Nzc3jE+l4dSQblWKxbt67H86VLlwIANm/e3OP1IyHkFoSx4Jn1zfj6nzchls6h1GnGA1cswymzS0d0H33lIrOeoqxMiYXjcSUQTiZpFpMbz7W307IVFeRUFFZ5CgbJkN64UdWN53Qiq1XVkE+n6XWeWQXU/+wUpNOqghNHIFiDwdoDNt7ZWGNDkB0UTjnhHHI28NhoZ20GO0ldXbRNn49mK3kdk4nGG48r8Wlhs7VCI4edDzaA2GkaTrSBjVthYHBfk0PRu5s3G+PsLBb2xGCnAmAtkhk7dtA9XajN4D4TuRwtx+vz/cC9Lbhho9FIjntnJ9179fW0LdYhsRictQ+zZinngnUI7DAUFam0Q01T4nCKsNAjR93Ky1VqX2kpvcfFGLq6VPGCQqxW+ky3tNCymkZGdmHXbxa987760zw4nbS9cFhFfDi6YLOp532tG40qQXxvjYPVShGEkTC+zWY6Nxwd7b2t/hyc0UIa9gnDRafTYdn0IvxrazvWNQYmv2Px8ssvj9Y4BGFck8zk8L9/fw+Pr2kEAJxQX4yfXLkM5e6R/7XonYvM3aB5lpJLpXIFmPZ2+rGvqKDXWltp+bIyMjA4j3rvXsoX9/tVuVd2TDSN9huNKqEsp1XwDzM7BTzzz1EH1i0UNogDlP6AjRL+cWfjkJ0BMgYy0DRjt9PCM8iA0lLs3aucHo5SsPCaIy/5PI25MFWmL+OVy8cmEmp2ebhIpGL04UiUqiam0na4mzqnRLW22rsrhk2bRu91dirD2OEgI5wLFHAqYWkprcPN8srL6bXiYlUpKpVS92k0Sp9Bm41Sg3h8Op3qhs2pidy8LZcjDVNbG+3b66Xt1taqlKBcjmbjq6qUM8NGc3s7PU6bdrBRns+rimdclhpQXb+DQfoOmDPn0JqHbJb0WDzZ0Du64PcfvC6LqFtalGMSjfZtWI/ETD5PwrBj2JvBCMKHS39C+P7E7ILQH8fM8B5wLIJjPZQhMWSNhSBMFRq74vjs4+9iS0sYOh3w+ZWz8aX3z4HRMHq/VoW5yGyIp1JkUEQiZOiUlKhZQb+fKiPxa0VFZLj4fGQMxWKqy3YqpQTYwaAScvMsMOeJh8MqasFRhEIxNIuwAeVk8P+sO+D8bXaKTCZlbHCkgJvMAcrZAGg8LLDllCg2ZDi1IxZTM8WD6XBdmMoljH+4FwZXiWLBfz6vrr/dTn+axhEGHfx+1V/C7aZ7hnVEfF/PnEkRgM5OpcdJp+ne0utpPZuNDHWLRXWOLytTJZ7ZSc9kyBFhATdHGLjvQzpN1ZuamuizsWQJrbttm6oK5XDQX1MTzew7nXSfer3KcA8EyHgPBOi7oqREaS5Y1N5fmpLZrCIKh9M8VFer9Mre0YXe6+ZyNGYWik+bRtdlJA3r3uMYSUH4cOlPCN+fmF0Q+oN1FusmqIBbHAtBOAQvvdeOm/+wHpFkFkV2E+6/YhneN7fs8CsOk8Jc5OZmchJYC8Czb8mkEjJbrWQYsQjb66Uf09271ax8aysZAJy2xGlOrIFg54BLW7LmgEP6vN/C/HCGy39yTndhOVYWk7rdKsWJjTHVGI02zukugJqNLux14HCoaAtrKBIJlaPOrxeKgrm3xEhEJYSxobBaGDsWXLUrnVZ9Wzg9isT8WnfkKxSie4ejG4V6iGRSGah83xfqN1io7HbTOPbsoeXb21XFJLud7sNolHrFBIOqB0VZGS1nNpPxP3MmfeY4qmGzAcuWqdl3jiIajeQw2Gy03VCIDFRuIBmPKyG51UrRhepq5byzTqo36bRK9Rqo5qEvw7z3uhwpra1VGgdgZAzrQ6UYjaQgfKj0V3CDKRSzA6OrvxB9x8RnQTV9sbSEkgjG0/Dax0+jvIEgjoUg9EE2l8c9Lzbgl//ZDQBYNt2Ln111DKq9o18UvfCHobiYjJTycpXrzB24NY2Mm0yGDJSiInIuQiHV+2HdOvpxyWbRLWRlA4rzu9ngSiSUeLWw9wSgctLZGAIOTv1hB6CwrCwbQbwud+6NRnvuI5czdv/PTcA4P5rF1iYTjTWZpD/efy6nehRw2lNhpSGuwCOOxcSFHVk2Kh0O5QAXiqz1epoppzQ8rbtXSSSiqpqxUw1QNIM1D6WldN+xw8vdvNnB5vuWdQWsr+AIgV5PTkBbGzkEtbVq9rqrC9ixg9L5EglKW+SO4VariiS2tNAkAn9G02nVy4InBKxWWi4cpu1zyWjWG3HaViBA3wVcgpWrvXGZatY/DEfzwOuGw6pKlMt18HL9VYkaCANJMRopQfhQ6avgRiEmE423qUmVpR5p/YXoOyYPbqsJ04psaAoksLU1MiIl7I8k4lgIQi86wkl84ffr8NYePwDgulPqcNu582E2jm6ibl8/DLGYMia2bSPDhHs6sLFUUaHElD6fSutgsTb/0Ofz9JwNJ9YocMM6dhioYd3Bgmfg0ALlwlQpTl3hCAiXteWKPTyzzAZPLpfvnl1mR6lwBpm7BnPjMq7exOscymngfHhh4sKfBy5xzAUDCnunsOPKvSpiMRNKS8nY5SaPwaBqoMflhjl6EImQEVZZqYxWo1FFAbhDvYqyqSZ9rP1wuZTjAygBeCCg7vV0WjnH3HyPNRPci8HtJmO6rU1ts7qa/lpaqDcHdxjncrk6Hf1vs5FzwU4293phg5YrqHGEgQ3P4cxucynfwVaJGggDTTEaKUH4UDhc879IhL6TgZ59hYabJsbHm07T/S36jsnD/Cr3AcciLI6FIExkVu/qwg2/XwdfNAWH2YAfXrIE5y8e/e6Xfc3KsWA5FKJlOKyfz1MKRFeXSuFwuaih1f79qlcF6w8CATWrzxGFwgZ1vUvCAqrs60Ap7JzMxj47IVySlt8vNMi42pNeTxYHNznj8Rcuy+lWyaRKhyl0fvpzHsSpmPiwY8ERNXYiuFxtYZpeKKTux6IiMrS5U7zfT2k6nPbHGgiulGYwUHSwvFx9bjjNjqOCLhd9zioq6P9cTqUCJZNKeJ1K0Wcyl6Pt5XLKsfd6VffuxkZVQIB7x3AvhmSSvgcsFppYaGoiZ8Nmo/2wWJ3L4ZaX0/cC97DhrtjZLDkkySRFUwarfzicwT6SXbV773egKUasuRgLDqf1aG2la1VRoV4bjv6i9ySUz0ePM2ao/Yu+Y2Izv8qNl95rx9bW8FgPZdAMy7F47bXX8Mtf/hK7du3Cn/70J9TU1OC3v/0t6uvrceqpp47UGAVh1MnnNTz06i786IUG5DVgXoULP//oMZhV1s8U3AjT16wcp/C0t6u0KE2jmS/uPp1IkPPR3Ex/gYAqxcrGDZe7ZEehsFxsYXdpLjvLBkRhs7fC3hUMi7wBlQZVaMSzroEjEwYDGUmFY1AN7GjFbFYZB2zoFea98zK8fuH+pCrTxITLn2raoZ1Z1lNwrxKuymS3q9n4QofWbs/A61VljI1GMua5keK0aXTPdHYq59fppNfr6+m+9PnoM8GRMpeLDHu+b2Mx+nzxmDi60NxM92xVFT2WlpLxz6WXC6N2fMz79qk+MFarOi7uQROJqF4xs2YpR6WkhJZta6NtsIGvooG0XCo1eP3DQNNrRktEPZAUoyNZTvZQ9Kf1CAToccaMvtcbbJpY70mowt4/bW0UcSu8NsNJQxPGjgVVlGqwtW0KORZPP/00rrnmGlx99dVYt24dUgdUSaFQCHfffTeee+65ERukIIwmoXgGN/9hPVZtoy5UHzmmBt+9aBFs5j66d40Cfc3KcQOvpiZVGYqNDO6mm0ioxm6JhJo57epSOd/xuIpCmExKP8FGGNAzOsERDDb0mL6alvEMJKcuFeoxOG2FnRdNU/npDNf+p+M1dW+Xx8tC7ML+ElzaVpg8cNSJ76e+jMTeKW9sbPL9w/caR+PsdiCfz6CoSFUQY0eEHxsb6XPD2+ASy9Goasg4fToZa6kURSk4bz8SIYeex8KOut2ulmH9QipFy7rd5BD4/bTNTEZFJtNp+qupUeeguZnG5vUqzURXl4rWeL00DtYrcefu6mp6j6N+mQyNa7D6h8GWTx0NEfVoRkJGOmWqPyE8V+saqTSx3pNQ3PHd66Xfh2CQ7t2hbl8YH8yvIgH39vYosrn8qFahHGmG7Fh85zvfwUMPPYSPfexjePLJJ7tfP+WUU/Cd73xnRAYnCKPNxqYgPvf4WjQFEjAb9fj2Bxfi8uNqj2iTx8JZuWSSIhRcSnLrVnp0OlVKxPTplPbw1lv0o1JcrASk3IOisNcEV5CxWFQEoHDWFFDGO//4HC4NimeFCyMWhWSzqgmdwaDG1nsbvV8rdHL4x7/3+311axYmNlwCtj/6i2ZwVC+bJcPdbiej1uMB0uksli2j1xoa6LPCFdKKi+kz4XCoxnlckrmkhD5zAH3uioro/ZISSjWqqiIjsqGBli8rU45LIkHRjvJy+mzxPvbvV44H96Bpa6P9cFGFmTPJ8eAqVOyUhMNkKJaWqjTIlhZax2gkZ4L7crAgmz+fRUWUhhMM0jH3NWvdn+E52PKpI9lVmxnpSMhoC5z7EsIDqiz4cJ2jviah2OnOZuneYg0an5Mj2ctDGDlqi+ywmw2Ip3PY2xXH7PIjkz0xEgzZsWhoaMCKFSsOet3j8SAYDA5nTIIw6miahsfXNOLbf3sP6Vwe04vt+PnVx+DoGs8RH0thmcnWVpol5IoxDgfNdra0oFuIyrP/3IGbm0N1dqpZ3cIyrzyjygLoQgOtd1+KgcKGHs8S93YseBaanZdCp+VwHM7IlOpOUwuzWaUzFcLONGt1APpMcCfskpI0ampUxAIgY5wNS4tFdZ8OBpXuYNcu2m4oRAa9TkfLLlmi0k3sdmD5cupez/vlKAWLwvV6JdyOxWjb27bR57i0lByS5mZlPPN9zQ5JPk8RilhMLccTED4fTTqUl6s0Qy66EI+TI8Mlc2MxSpHissxuN63HhnRfhudgtQ3MSHbVZkYqEjLQCMxIjL33eiPlHPWVGsb3cShE15bTWQE6Fr+fzpGkQU0s9Hod6koceK81jL2+2NRwLCorK7Fz507U1dX1eP3111/HzJkzhzsuQRg14uksvv7nTfjr+hYAwFkLKvCjS5fAY+snkXeUYcOioYEMBq7QwrNq3AOCy0VyQzyHg9ZjMXM6rRwJThkqNMgKK+gUMhxx8+HWlfC7MBw4takwRYq1A4zVqmbpubt0KASkUga0tpJglqMQs2ap7vTcqTseV5V6QiHaFxvper3qczF9Or323nsqva+oiMY1fTo9lpaqhpTxODkGBgONIRym9KtgUOXCFxXRPvx+MjqdTvoOaG5WqVQcaWFHpaqKPvvs3PNnPpVSzfKMRhrDrl3K2Whvp++L1lb6f+5cOld9GbbD1TYM1og9lDE/UpGQw0VguB/IaEQzDqW/4DLaA6G/1DBunsj3G1eJ6uxUFbtaWqT07ESjvvSAY9EVG+uhDIohOxaf+tSncOONN+KRRx6BTqdDS0sLVq9ejVtuuQW33377SI5REEaMnR1RfPZ372JHRxQGvQ5fOWcePr1i5pBTn0ZqZs7hoB94zqHOZsm46OigbTsc9IPK5TG5c7XdrirasGGSTKplubzrYKIRgjBeKIyksf6GZ9bNZjK+LRaVBsS9J+rqgGnT/NDpZiIcJsOrulpFA8JhFfFgQ6upiR75s2g00ufPYFCf7WnTaF1OJ+QqZXPnktPAzopeT84DOy1mMzkXrElqa6P1KyspusDGJXeP5yZ23G/CYKDJBY5O6PUkBu7sJOM3FqPHmTOVM8D6qlCIxsv793joe2bLFlre4zl41n+0tA29GWhq0nAjIYeLwBgMwM6dFEUayXKwheMvdI4CAXoEVEGAWOzwhn9/qWFWK91L+/bRtebHsjJydke6A7pwZKgrpQ6XU8ax+NrXvoZ8Po8zzzwT8XgcK1asgMViwS233IIbbrhhJMcoCCPCsxta8LWnNyKezqHMZcFPr1yGE2YOrT70SOfq8sxZZ6fq9+Dz0Y8Npxwkk6oMZVsbPdfp1IxmPk/LFnYn5lzrvrplC8JEoVB0zal/bKTH4yq9Raejz+Ds2QCQgctFnxnuIM89TXh9rirl89F+LBZy1NmZCIfpc819H4qKlH6Cy7x2dirHobGRPptcWMHppM9hLEaRhpkz6b22NhWhLC5WFalSKWUMxuP0efZ4lLNQVUWvOZ00Nu6g7XLR8RdWVONmeNksjbuqis5TLKYqx02b1tPQLDTczWZyQPpKoxlqladCBisO5+szFA4XgYnFaJ/cIR0Y+XKt7ByFQuTEulxDc2L6i34kEhQ54zSx3tdNSs9OPGaUkCe81xcf45EMjiE7FjqdDt/4xjdw6623YufOnYhGo1iwYAGc/ZU+EIQxIpXN4e5/bMVvVu8DAJw4sxgPXrkM5a6hTdsM5QfxoDH1mnlLp1WlGLdb1evP5VSVGhYu+3xkNLADwQ3kgIP7T3AgplBoLQjjnd7VoVicyn0eWHDN97TDQUbajBkUrTAYgI4OK/x++rw0NtJyZWXkGPBsvk5HUQmunMS9XXiWt6NDNa1LJMg4d7vJOHQ46L26OtpOOk1GWzRK3wFcjpmd/lCI/i8rU30NSkspPSscJgfFalXfAQBtt6yMIi7c8FLTaBwlJapRJkD74k7b/L3R1UWOCX9PuVz0PJcjB8pmU1GXwlQjnsyIx2msbrdKseJqbr2r2A02klAoKh/t3gt9RWB4zNksjcPp7DsCU6gnGQkBdOzA5PNQe1ocKjXM4VCd3/uKNEnp2YlFfSl9yPb4pkjE4vrrr8dHP/pRrFy5EgsWLBjJMQnCiNEUiOPzT6zDhv1BAMDnVs7CzWfNHVbptsFWSymkv0iHz6f6NiQSKseb00Cok7AyVrhuOW8TUD+ShUhzOGEiwn0i+P7N51UzOK4EBagUopoaMr41jWaDi4uBbFaPtjYyYAMBeo21FaxV4tx6Tj/M5VRzuVSKPnPhMBnrABniJ55IBubu3WScsWHe2EiGvc1Gy3Z20n44ihmJUJQiEFBi7EiEPvsOBxmDzc00RrudvkPcbjJ6zWbVCJP1HuwImUyqxG42Sw5FOKzSIUtKDk4hy2RoW5pGy/F3GjsO/J3CaZdbt9K2bTZyTGpqyIDt6qLl+PtoIJHbZJKOsaGBlo/FyKgv7K/hcNC27XaV7tYXA3VoClOI8nk6p9GomohpagLmzet7G4V6kuE6FkMVxfemv9QwLjs+Efp+CIdnRgl98bSEEkhlc7AYJ0ZJxCE7Fp2dnfjABz6AsrIyXHHFFfjoRz+KJUuWjOTYBGFYvNLQgS89tR7BeAZuqxH3Xb4UZ86vOPyKh2A4Pwz9ddfetAnYs0dFIdrbVSoFN9riiAX/kORyKiebG8ZJOUFhssCpRoAqRMA5/WYz3f8ejxIvWyxkgIZC9JmiNB4L/n975x0eV3H9/e/2vlpp1WXZllxxwxiMqYaAsak/WkixE0ooAUxoARJS6KE4QAi8AUIglACBEEJNQiCAIRBjCC40415kq7ftfe/7x/HZ2ZUlW73Y5/M8eqTdO3fu3NXdmXPmtHic3kskVA2Yxsbc4nTRqBJqdToSQFtaqD+jkc4Ph0mY3rEDWLWKrh2JKGsH18DwelUhyJYW+t56PEo45srZySQVq8vLU0pMtjXGbidLhtFImaQiERIkOcNbWxsJ53V1JJRzLIbXq1y9OP6qoYGulb2DzfFZNpsq8JefT2Nji00sRsHfXJBv61YaD2ewikZp3tI0FauxJ8stz4Hsbpafrywt0aiqv9DWpiy4nKQiW1npjSsq1wJZt46eI7YKcX2d7DS/2fQlnqSj4N/fBf86rjGDFRsjDA5FTgtsJgMiiRRq26MZC8Zwp9eKxSuvvIK2tja88MILePbZZ3Hvvfdi8uTJWLRoERYuXLhLtihBGCxSaQ2//fc6PPDuBmgaML0iDw8umoXKAnuf++7LwsC7guyqEInQol9fr/y0zWZVXbumhhZgzoHOKSW5uB1bNvhasgsl7C1wzAFAzzmgvnsGg8p0YzJRu2RSuSfp9SRwNzY6M8o7p4Jl1568PHJF4aBWvZ7iDdhtymhUdR/Y1dHno+/ljh3A5MkkyNrtJNwFg3RONErjYcuH2UzKBAuyySQJw4WFytrCVsr16+keuTp3Q4Ny1+J5orCQlASTiZSadJquz2NcvZoE46oqcgtraaHz8vNVdXB2A2MlJR5Xbl3BoLLO+P2q0GUkou6VrS+trep/xMHje7Lc8hxYUKAKYGZn8mpoUOm0rVZSyhIJ5TbFCSe764qaLdhz9jCu58NFRMvLSSFrbNy1uBzfG8eT7Km+D9OV4sP/74ES/AeqArowNOh0OpTmWbG5OYQG/z6gWABAfn4+LrroIlx00UXYvn07/vznP+OPf/wjbrjhBiQlDY0wBDQHY7jiuZX4cAPZ6L93yGj84qQpsJr6x4TY0x0hXtgSCRJaIhFVGXvFChIm4nFa0Px+5fpRV0evbTZaODkom5WHVIqOC8LeCLv1cWwQu0CxdYIVCf5+cPxFW5vKoNTYaIHFohIfZMcssbvP5MkkVPr9KhaivV2lh02nVe2LtWvptdWqCut5PCRwjx5NLlUc98HWlooKEpabm6kPgATZeFxtEmzfTgIfp8sF6Brr1tE9sTDf1kZjCgRyd/jdbuqH092GQqQAFRcDs2bR3w0N1K/Xq6p8OxzK9amyUn3uRqMqGMiFOTnrXHOzsq7U11OQvNebW5SNYxFaWugYC7HZ1l7OYOfzqcrUdjt9Fk4nHbdac12W6uqUdWlPrqgFBbsK9mYz9VVVperqsCUhGqV73LpVKQFcubynVcP3FIPHtUUGSvAfiArowtBR4rZkFIuRQp8UCyaRSOB///sfli9fji1btqAkOypJEAaJT7e2YvEzK1Hvj8JmMuCOM6bjtAMq+vUa3d0R0jQSNHhhCwZJiXC7acFatQp4/31abF0uWmB37KD2vEPLdSvsdqXQACodpSDsraRS9F3Q61VMhdFIghErHawI+P2qSJjTqTIzJZM22O20O9/SohQVvZ6EK52OhG4W3INBJTi3t9P3zmhUArHbrWrMhMM0B3BaWK6CnZ+vlBbOOGW3Ux+RiBIauVL311+rYG0WyCdNUsHqXHE7GqXXhYU05q1baf7ZtImER84std9+qhhmSQnNLZWVKnaDCwNWVFBfySTt1G/fTooIX5cLXAL0OfFnEA6TJUanU+l09XpSsliYDQbpb44Jq65W/7dsay8rCNkB5z6fUhJYIeT/g9FI911by1m/dsXhoP8hf77ZgnVLi4pn4TiYbHgDZ9MmFdMyahQpgj3J9LenGDyuTzJQgr/VSv9bdsVjq1NfKqALQ0eJm/5h+4xi8e677+LZZ5/Fiy++iHQ6jTPOOAOvv/46jjnmmP4anyDsEU3T8OR/t+C2v69BMq1hXJEDD3/vQEwocQ3I9fa0I2S30+IUiZCgY7VS9eyNG5Xf88cf08TvdtPOZFNTbqA279Ry8TveXeQsUIKwL8ACLgtjnEGNi9fpdEpQZUHWZOJaEwZEIsrCwcI5t7Hb6fvEmZFaWuh7Z7Eodxm/n4TdwkISvFtb6TvrdFL7cJhecy0Nu53Oq62l7zmnmuX4jXBY7e6HQqqoZXaQeDxOf5eV0Xh4vBYLWR54N3zCBKUQbd5M88WYMTRWVsQAasNpbh0OEpTZsmA0UnsunsdWBJuNPt9gUFkt2tvpXLs9d64Lh1WmqFhMzYWhEFl52tuBKVOoz2xrL9deYKsE1xYpLKRxR6PKmgGo2BMuQMgxEtmYTPQ/crno82PMZhW839ysLDR8nfp6lc2rooI+92i058kvuhODF4vRfXMq8d4W/OuMji5YAP2vCwtzP0th5MCKRb1v5Cz8vVYsKioq0NraiuOPPx6PPPIITjnlFFjEcU8YZMLxJK7/2+d4ZWcV7ZNmlOGuM2fAaekXY1yn7C7dHysVtbW0mK1fTwtWbS0tmuvXk0DCu511daRUcApCzuzCrg1AriIhSoWwr8GKtsGgFG7OGMXWQE7TGolQO/oO6RGJUDurVQnxnAihspK+s9mZlTi2govcMX4/fYdTKWVxYKE6maSNAw4y1unUrj3HgLCVgysisyVDp1NxBA6HKs7H8QzhsBJWYzESqjVN1bZgJQggS01NDfXHNToYdicqLKTzWZBm608iQffAloDmZjrOVhcuGMjCfDrNmbdU//y5cg2d8nIVEP7VV+SW1dHay8qF30+f7ejR1G9Dg4r1yH4O2E2J09R2FDk4ADtbqWAsFrK2sJsYn9vermJp8vLUPebl9TztbXdj8Mxm6r+/CqwCXbtghUL0/2TLnDCyyFgsAvuAxeKmm27CWWedBY/H04/DEYTus7k5hIv/9CnWNgRg0Otw/QmTcf4RVb2uot0TstP9seuSTkcTe20tLYDbtyv/Zr+fBJlAgASAUEiZ530+lfWGF2cgd7csmZRMHsK+C8dQsCBmMOTuyme75LAAqmnpTD2MdJqEOW6nafS9ZbcV3jF3OpVQz/2wD35zMwnB6TS1Z6UmElE70BxnYDTS9dxu5R7FVbM5CxHXpmAhE6Dx19XRtTk7XCBA84PfT+95PLsGErMbVn09jYWtEgwrX0YjteHaHEaj+mxranItpZyNq6mJ+mbrCEDn5uWpOh9cfDCRoD75uMlE42lqovsqK8u19qZS9Lk2Nalg/C1b6Lodd/05dW8sRnNrWVnnigVXLO+MwkKlLHi99L9sa6NxcMrbbHpa96GnMXj9uRfblzTowvClxE0PSYNvH1AsLrzwwv4chyD0iDe/rMeP/7IagVgSRS4LfrdwFg6uGtyotI5mZ66UDZDbU20tLZS86LJC4fMpiwX7iQO7L2CXbcEQhH0NVihYqeCsRqw4xOPKLSqZZNcj2k6PRlWNhmxlpK2Nvo8mk7KAJJMkYI4ZQ+d88YXalWc3xGyBMRZTMQgmE8UA6PXKdVGvJ4WAhWadTgn0kQj9DgRoB52LztXXk8C+bRsJv+PG0fFolITulhYKOmfLiU5HfxcX02uOy9I0tWPNQe4cQ5LtFpNO0zmcaraqijZBHA4S1NkKoNfTcU1T2ZWqq3NdnlwuUqbYPQyge+Qq5uXlytrb3ExzZDKpqo0nkxR3whmvXK7c+jxstWlvp2uWl6tihtn32ZVgbzDQOS6XckfjIHhWnrLpTfrXocjK1F/1MYThR6GT/mGt4ZETWNlnf5GvvvoK27ZtQ7xDNOn//d//9bVrQdiFZCqNe95ah4eWbgQAzB6bj98tnIVi9+DYeFnAYZcGNjuzCwBne9qxQ6VfZNcFDpLk4lyRSM+sEFLsTthXYaGfFQAOwmaBlxUMVhQo2DedSY2aSqnvYnaqVRb0o1mbgW63EpztdjqfXaMiERL2k0n6/gcCFD9QXk7X553+VEpZAzj+orlZuU5xFWyuuq3TKQGfXVYKCykA22xWY7BY1L1ypiNABZmPGUNKh05HAni2735dHSkrRUXqXmMxmpe2bKH7LisjxYrjC0pLldXEZFKBxdnuOw0NpIyk07lZoJhkUn32HC/D1t6iol1dmiZOJCVn1Sq6PrtgcRu9Hpg6le6tqYmEeFYwOBvU7gT7wsJcazP/L/or/etQZGXq7/oYwvDBZSUxPRAdOZlWe61YbNq0Caeffjo+//xz6HQ6aDulHnZDSe1u+1UQekFLMIbLs1LJ/uDwKlx/4mSY+lBFu7t0Zp2IRGhnj1NZRiLKhSEapd08DsTkHPcNDUq44AragiDsGa7ZwAI7C6uRiHIlZFce+m3I7HqzUMvV7Vlx0Otp9zseV/ViOLWz1UpCeShE333uo6mJrseBxqNGKVcqr5f6bmqiPjh1a1MT3QMXwPP5SNB3uZT7DWdBcrmUYsH3yKlmOTic40yKiqh9NErjnDGDgrq5cGC2777HQ9cPhZRFpaWF5iSrlSwebNHhIG6OZWBFKRymczmmpa1NKWIbNnQugGcX48tOwx2P0+eVLdBHo9RnRYVSZJxOla63rIzut7RUjZmDtdnNp7uCPcencIav/rIw7C4Gb6CyMklhvL0Xt5W0RX9k5AgLvVYsrrjiClRVVeHtt99GVVUVPv74Y7S0tODHP/4x7r777v4coyBgVU07Lnn6U9T5KJXsXd+cgf/bv28Oo7sLnMs+pmm5QXHsNtDaCqxZoyr0NjcrYQKgBZsr627apDJFRSIqp74gCN2DU8+yAAXQ95a/T5qmXGeoLgEpFuy6w65QXJsCULFLnNLV56PvdTpNgnh7uxLy+bqRiMoyNHZsbsyFyaRiK9rbSbCMRqmN3a6KznEdmqYmUkzGjVNpcLmqN1tIDAZ6j8fZ2Kh23oNBem0ykZJhMFCGqOxK1IzdTsI3F9ZkxcHrVS4yiYQSPu126p/jVljx6ExYBuhz4xgPVv7YAsNWAZ5nu9ph50DqsjJV64LT9/J8yUoF//95/HwPPRXsB8LCkB2D11/B2btDCuPtvbht9CWJJdOIJVOwGPunJtdA0mvFYtmyZXjnnXdQWFgIvV4PvV6PI444AnfccQcuv/xyrFy5sj/HKeyjaJqGZ5Zvwy2vfYV4Ko3qQgce/v6BmNiHVLJdVUXNXiCzj3FayKIiZXWoraVFl4MOYzGKq+DCV1wgyuEgAWLbNuqXi0tJ/UhB6D5skeA4Crb2sULBlZU5hSxlOtJldmpZ4fd66bjTSQIfV7/mwG+u48AVtq1WUhJGj1bZk3w++m63tKgU0GwhYEuI0UhCMltDNE2ls2WrAGc9isdJ+E2lVHwC7/CzcB4M0vsTJ5KlY8MGVecjlSLFY9w4mqO6qkTNaUfb2khJ4CxVDgcpJ1yhnAXTVEq9z8X7vF4S7M3mXYXlKVMo+xPXBjGb6T4421K2gN7ZDnt25W+OkykrU0oFp+ztmJujMzefngj2fbUw7O4agynIS2G8vROXxZhxAQ1Ek7A492LFIpVKweUi4a6wsBC1tbWYNGkSxowZg7Vr1/bbAIV9l2gihZ+/9AVeXLEdALBgagnuPmt/uKxdOJJ2p88uUvK1tdEPf4H5WEsL8PnnKitLSwvtym3ciEwqy7Y2WpC2blVxFlYr7UQ2NqoAbRZ4JFZCEHoGx1hwkchEQgmZ6bT6u7VV7YTze2xBjMVIoXC7lVXDYFDfT84cxfEL7KoTCqlMRayMGI303eZx8M55ezu9b7OpFKzRqBKuHQ51HyUlJLzm55P7UlOTsmwAdL7LpTI52e0qPWtVFV0jnaZ75sxULKRzil2/X8U0ALnCZyiklJ/mZhXYzJ9VXZ0KiOa+6+rodXX1rkKzx0MpZevq6LpsKeJNm2wBvbMddv4fGI10fl6euobNRu3Y+pPN7tx8uivY98bCsLsNqqFI6zoULljCwKPX6+A0GxGIJeGPJDLB3MOZXisW06ZNw+rVq1FVVYU5c+ZgyZIlMJvNeOSRR1BdXd2fYxT2Qba1hHHx05/iqzo/9DrguuMn44dzq/ucSnZ3KflYH540iX5zikn27WbXBXZF0OloYdyyRe2qsUmefYjZF5orBXOaTEEQegbHT2THJrEyYDarnWuOXzKZ0pkd83SavpOtrbRrz/EC7B7F1bHTaRW8zBW48/KUiw4XOGMFg6/J8QypFM0RHg9tLBQWqpo2VVWqDQd1s7WF74PdsUpLVaYfQLkB+XwkvBYXk6AYi6nK46wsccE5djfibEHslun1ktXV51OxX6NH0+uaGrp2MEjKTHGxKtrX0EB91tXROePG7Wq5sFrpPrsjoHfcYeeg+paW3NSvXFW9uZn676hA9KebT3f7iEZpHehsgyrbSjTYDLYLljA4uG0mUixGSAB3rxWLX/ziFwjtzK15yy234OSTT8aRRx4Jr9eL559/vt8GKOx7vPt1I654biX80SS8DjMe+O4BOGx8YZ/73V1KPp6I+W+LhRaOpiblbsEKBe+0NTTQ4stCCPsus4mf86OzciHB2oLQN3h3muMU+LvFsRc2m3qP3aY4NoMDvTlugAV8gL7DZjMJs2az2gAIh+k4p7O12WgOaWujNuxixLUfuLo1C/Qs2HGwM++L6HQ0n3Cwd329qvbd3k7CfVGRilvQ6aiv7MBlQAWkc0XytrbcGhWhEF1n40ZyVbJa6Z7y8lRNicZGFZ+ycSOwciX1Y7cr1zFA9ZlKkRW3tpYEaLt915367gizHXfY2dKk1+feI0D/l4aG3OKIQ+nmM9xrRogysXdhMZI2HU+OjF3JXisWCxYsyPw9fvx4fP3112htbUV+fv6gFCgT9j5SaQ2/fXs97n97PQBgZqUHD31vFsrybP3S/+5S8vHuDkCL7YYNwPLlKo87m7pLS1VmGc4Zn0wqiwUvvPE4/Yh1QhD6D1YWuBI3xzTpdMoFkVLNAu3t+kyxO7Z26PUq21AkQt9hFtjz8qgNBwtz1qhkUhXP0zQVMJ6XR4JkMEi77JGIqqrMcQLjxtHfDQ0qqJrHyulZOdNTMEi/i4tJaNY0ctsqLKTrh0K7FoXT6+n+3W61scEVnZublaVl61ZqP26c2lwxm5XS09BAlldWVJxOGkd9PW2uzJihYsm4iCfHi1gsne/Udze+IXuHvaKCxu3zqdgUgD6vMWOUlWZ3bj4DvVufSOgRCHRdhE9qRgj9jdFAMnUyNTIEil4rFmeffTa+8Y1vYO7cuRg3bhwAoECig4Re0h6O44rnVuG9dZSX8fuHjMEvTt6vXzMgdJWSj92WYjF6vXEj8OWXauewoIDeq6mhBYNdFlpalADAu6e8c5m9KAqC0DfM5tygaw7c5oBerkmRXf05kdBnLAiMx6N2t1mY532wSIR24TnwmF2fuFBcOk1zArslcf0JvjZnp2JhPj9fKTsGAwnfRqOK//B6qf3WrSQ0cxXosWPJjSo7XWx9vcqQxMpVIqGqUWuaCnzm2hS8sVFcTOfW1qp7zRaK+R7MZhoTKzQcCB8MUka7yZPpnlmp4srhBQV0r7xTz7UkehJ7wAI4W5pqa5XLFdfXGDeOlBCOdemoOAxWzAPHgkjNCGGwMO7c9UykR4ZQ0WvFwmw244477sD555+PiooKHHXUUTj66KNx1FFHYcKECf05xi658847cf311+OKK67AfffdNyjXFPqfL3b4cPHTn2J7WwRWkx63nz4dZ8wa1e/X6Rgw2NEfuaFB5bBPp1XaRE7l6PfTcbtdLWyRiMp9z65OolAIQv/C9VfZLUevV+5BJpNSEvi7R8dTSCZp91vTVA0JrjfDQdRsQeD4B7ZscJVtTsjAQd42GwnWbW2qDw4u51S2TicJs/X1KiC5pERtQuh0KnZDpyPlxemknw0b6PWECSoWJC+PAqbD4V0DcysqKCHFhg10DZ9PxY/Y7cqywpbVRILOY0WptZUE+VCIxuf10vW5wF5REbWrq1P/D7tdFQ9kAZqLALa35ybA6G7sQTRKCgxn0EunqQ/+fLnfigr6H3Q8t6ukHL2xpOwOLsgoNSOEwcK0r1gsHn30UQDAjh078P777+O9997DPffcgx/+8IcoKyvD9u3b+22QnfHJJ5/g97//PWbMmDGg1xEGlr9+uh0/e+lzxJNpjC6w4+HvHYgp5e4Bux67QNTX51bk5bSQW7bQbt/o0XSMBQnO4hIIqBSTeXm57gayQyUIA0s0mlsMD1DxC4ASOCkmQp9xYwLo+8rKB1eWZr94roYdDNL8wJmkWHBm1yZWOrLjpthlSqej9gYDuS+xayRnbeIsR7zj3dZG57Fb0pgxdHzrVuDjj0nYHzWKfioqyELg8ai5JrsI3qhRZEFtbKQfjjvgitVcn6KgQMWGcUA7u5aFQvRjNKrg8ZYWda3t2+neRo2ie+EaIKyEpVLUr9dLFgamu7EHtbV079ljSCTof9nYmBvsXlWVe27HmAf+jOx2UrJ6a0npDJMpDZeLnhWpGSEMBsadRYATqZGxa9lrxYLJz8+H1+tFfn4+PB4PjEYjioqK+mNsXRIMBrFo0SL84Q9/wG233Tag1xIGhkQqjdte/wpPLiPn32MnF+Peb81Enr33qWS7AwcM+nzKrWnHDlpAAWWNiETodSSi8swHArS4+nxqd45rXIhSIQiDA7seAcpayDvQLPzvbJkJwmbh2G6n87mPZFL95iQNXGtmZzZ1JJMqtatOp9wcuQYGj4V3wDklLqA2Mrj6NM8TXHyuqIgEaK6evWWLml/a2oDKSnrNNTWs1twU1ywgZ2eoYgtJtuWUrR7sTsXn5+dTDMX69XQNl0spWRUVZD347DO1O+/1KleycJjG09amUuvW1tJnxS5g2TgcNM9yjY5swTsWo7mVA+rjcZpb02l63dZGysWkSaqKeVmZirnguJGOVmj+n4TDvbekdEZBgRqX1IwQBpqMxWKECBq9Vix+9rOfYenSpVi5ciX2228/HHXUUfjpT3+KuXPnIj87VcIAsHjxYpx00kmYN2+eKBYjkKZADIufWYGPt7QCAK6cNwGXHzMBev3gBP2z60FJCQVUNjbSguZ0qkJbySTtOoZCqnZFOKyEhJYWpVhIsTtBGFw4KxT7ubMLIu9oUwpXQ8Zdil2Vsl9zMDK7WbFLFaeu1evVMbNZWTeZVIosm5pGc4FeTxYFm00J3ImEcucBaI5xueh9VnY2bCBB1GhUgjnv1E+dSufV1Kh6FB1dfgIBYN06uhdWUAwGej8UUtfkjFbptKqPsXkzuThxpfHiYvqc1q5VArzNRgpFfj71u3Ej9cMWhWiUlAW+ViKhKnCzsM41gJqalKXF4aB+udI4b/Q0N6tig8mkSpIRDALjx9PnzRaXiorcGLeGhtysWMkkjauujqwcY8eq/19fsjhJzQhhMDHslI1Se3uMxZ133omioiLceOONOOOMMzBx4sT+HFeXPPfcc1ixYgU++eSTbrWPxWKIcVQuAP9Ou3gikUBCcn/2GP7MevvZfbbdh8V/XoV6fwwOiwH3nDkdx+5XjFQqmbXTOLBw7vetW2mx4x0/ztSSTNLuGQsRDQ3UvrGRFhLemeIdQ6GvJDv8FgSCazx0hAO0s49nKxYGQxI6XRp6fTKTbtZoVBmkksncCtMOR667E1shWCHhWAoWeEtLaT7gHXjOFMfxCeEwCepuNwnEXGti1Cjqi62knFHJ7ydh1OFQmecaGkjpOPhgusctW1TWKg7STiToXINBFdADVJE+Tnlrs5Fw7fMp6wvXsPB6yTJSW0vHPR4a28aNZFEZN46uwxXFGxrIwhEIUFuvV2XDYhegUIgUBE4Tu2ULvZdIkBJhNtNnbLVS/waDOs6KAUDXSCbpc9yyhRSewkKVjSuZJAE/nVabP3l56v/KweA+n4ov6YjZTPM6u43tjuz1j2PvuOBidsyGiBZCd+mOTMVpZnVaesjk1p5cV6dpvQs1Xb16Nd577z0sXboU//nPf2A2mzMB3EcfffSAKBo1NTU46KCD8NZbb2ViK44++mjMnDmzy+Dtm266CTfffPMu7z/77LOw8+wlDAofNerwwiY9kpoOJTYN509KoaR/Msn2iERCjy+/9GDHDgeSSR3q6x1IpfRIJvXQNA0tLWbE4wYUFkZht6fQ2GjB9u0OhMNm6PVpmExphMMGxGID67YlCMLuMRhS0DQd0mnyQdbrAbM5CUCPeFwPvT6NZFIPkykJqzW183gKkYgRiYQeOp0OBkMaFksKqZQemqaDpmnQ6dSy6HCkYLfHAeig12uwWlNIpw3QtBRiMRNMpiTicQP0eh2s1iSSST0sljQKCiJIJAyIRvUIh40wGjWYTGlYLBp8PiN8PhP0eg02W2pnpicNHk8cHk8csZgBiYQO+fkxTJ7cjry8BNrazHC7E9Dr00il6P6SSR0iESMKCmI73bR08HjiCAZNCATMO+vrGOFyJXa6aaVgMKSxdasLLS1WaJoOLlcCLlcSen0agYAJkYgRPp95ZyB3DKWlYTgcKZjNCQSDZkQiBoTDBsTjRuTnx2AwAA5HAuXlIcTjBoTDJlgsKYTDBhgMafj9FkSjekQiJgSDhp1W4RSKiyM709bqYDan0NxsRSBghtWa2lmTJAmfzwJAQ3u7ZadVJY6KigDy8xOIRIwANEyY4EMgYERNjQt5eQkYDLkijc9nRjBoREFBFEVFUZhMucc1DQiHjSguDsNiGRmuJsK+xb2fG7A1qMMFk1KYXjA0VotwOIyFCxfC5/PB7d59HGyvFYuOrF69Gr/5zW/wzDPPIJ1OIzUAW7kvv/wyTj/9dBiynFhTqRR0Oh30ej1isVjOMaBzi0VlZSWam5v3+OEIu5JIJPDWW2/huOOOg6mrfHsdiCfTuOONtXh6eQ0A4NjJRfj1mdPhsvY5xKdX+HzAK68An35Ku2cNDbRT6HaT2b2hgQUU2uWqq6MdLQ7QTKVol3CEuDuOALItFUPzTAgjGw625grWmpaEmvaNmYxL0aiqNZNMqqBmdnXiTEQuF+2cx2K0I56Xp1yneAdc05TLTTBIVzIYyPe/okKlpDabqT0XyOMaEADNK16vsoawFcZiIZcak4ncf/bbj9oaDHQfyaSq57B5M425qEilim1uJqsIZ1iqrKTgcHbTaWoi9ymHQ7lhsStYWxvNg8kkWVgmTcrNiud0Up/t7ZSC1m5Xwel5eTR/cmVqu53Oq6+nz8jtVpmrOM7FYiErTShEFhqOi2ErRjRK55aXkwVk6lTqR9PoHqdOJUvJxx/TZ+1wKDcoTs+bTFL76upd3ZQ41fjYsd2zWPR0/ROE3dGdZ+rUB5fhq7oAHjt7FuZO6Hux4N7g9/tRWFjYLcWi16u4pmlYuXIlli5diqVLl+KDDz6A3+/HjBkzcNRRR/W2291y7LHH4vPPP89577zzzsPkyZPxk5/8ZBelAgAsFgssncwWJpNJJoY+0N3PrykQw6XPfIpPtrQBAK6aNxE/Omb8oMVTALnpBdk/l90TWlpUwN+OHbQI2e3Kv5rdn9ifOxpVLlNCf5IETUfynRQ6h91aOvvu8TFOqUrQM2UymXKEVKtVVePm2hfsnsPfe04H6/OpKttcUI4zw8Vi1BenkbVYVLwVF44rLqa5g2tMBAKkYLhc9Lq1lY4VF9M1QyE63+UiYTkep7HV1Kjif5zRimM3TCYVJ1ZcTC6eO3bQ+04njYOre6dSdF9cnI8DmrNdPK1WOpcz4nm9Sqni+hdcVNBmo/vgubGoiJSR7dtp3CYTKTesVPFnYbPRtdNpup7HQ/dWUUGfUWMjjYXrZnAl8oICGkN2Zr54nPoYPVoVCWSF0eulvpua6IfjZ7IJBlW/3aU38sNAF+4TRja7e6aSO2MrbOahk1t7ct1eKxYFBQUIBoPYf//9cdRRR+HCCy/EkUceCY/H09su94jL5cK0adNy3nM4HPB6vbu8Lww9K7e14ZKnV6DeH4XLYsR935mJY/crGbTrd1YwKRTKfY99rVtaSIhIJlXwdnaF3GyhRfxnBWHw4RgKhnelAbXD3RFWCKJREuxYIAVUDQyu4m2x0E44zwss9EajJOBy2ulYTNWw8fvpfM5QxBaB8nI6FgzSDj7XveAaGICqNcGVs00mujZnTAoGSdg1GFSxToeDBGQONPb7VbYmv19lrCorU8klJkyg89avJ4Gdk1ewYrFxo8p85/GQwsDB8bEYtWFlxGikudNioVgH/vyNxtw6HxwrwjEvxcUqDoOtO5wViy1LDgcpJevW0efhctF9tLVRX6kUKTEcG8PjZeWqsJDaFhfvKsBztfWOBQYHI4vTYBXuE/ZeOM2syTgyiqP0WrF4+umnceSRR4o7kdApf/mkBr94+QvEU2mMK3LgkbMPwriiHmwJ9ZHOCiYFg7Sb5/fTAmQy0cLT1KSCsINBWkjZLYBTUMbjKpOLIAhDT7a3bXZhu+zvKAdfcxYoFt4BdplSgh67KHHWJs5exPMEbzbw7jvXwwgGlcDu9ZK7Dbv5cNpYDugOh2ku0euVJYSVIpuNBGpOB9vaStYQh4ME6O3bVeA2B2WHQqqeDlteCwuVFYYC2VVK7JYWmv9GjVJpeAFldSgpoT5cLhL6s60hqRTNlXo9KTalpTTOpial1HEKVs6MxVYMDm7X6UhZam6m8el0SlHgjHycWSmVot+bNiHLrU1VHLdYVLpfrtHBWft4zo/HaTwWC1lDUqnBzeLUk8J9gtAVHLxtMuzlisVJJ53Un+PoNUuXLh3qIQhZxJNp3PL6l3j6o20AgPlTSnDPt/aHyzq45ruOBZPY37m1lbKLsL8w+wMHg7RIcyaReFwpFYBYKQRhuMGF6rLpqPin02qXmHeqWSlg10iHg35zxiLOEsU1H9iCwIU12V2SBXZ2r0qnSWDOdjHiCs0sQLMywC6YHg+NqaWF+udYkESC+uAUtokEzVtbtpBQX1GRa9XwepUQG4vR+PV6mv+iUVUbgq0KgQDFjhmNlJWpoYHacKxEaamyirBCwbUxRo+m/tnliK0yTifd46hRNJ7mZmqTl0fzLStVbBVi16C8PGW1icepf7+f7t9sJguEz0efeXs7XTs/nz6XSCS3GF12Cliu1QGQosQKU2mp+l8MtEtSx3UI6FuaW2HfJBQn06DD3IlZdhgikZJCv9EYiOLSp1fgf1vboNMBV8+biMXfGNx4CiC3YBJAEztX2jabaQFrbKSFjyvx8m4noKwTgiAMX7rKD2KxKHcmQO3Mc4VoFvizYzZYyOXaCbyxEAqpgGlNo/mipEQpIRz4y5YEvV6loK2ooPYeD8032cXabDaai9jFiHezbTba4U8mlXsVx0uwBaCpic4ZN44EeIuF2uj1ylWIXbUsFjonHFZWDA5Mt1qVBcbjoZ17i4X+ZquHy0WKQnMzXXP9euB//1MWHRbUq6tpvGz14VoZBgNd32Kh+9qxg+JFuI4QW2ucTjUvu1z02RcW0jmVlUpJSCToOlw3o6MbE7uh+Xx0HY5V6cxSMNBKRcd1qCMOBx2PxSTmQuiadFqDL0ICyUAXEO4vRLEQ+oVVNe344Z/+hwZ/DC6rEb/9zkwcM3nw4imy4V1KjjVqb6fJu6iIFvrWVlp02tpocWJLBQsKgiCMXNgiwbAVg4Vetl5kB4JzUT3OFBWLkZDP/bS00G+DITfWg12M+FwWqFOpXHdLTvoA0HtcM4OtHQUFqgJ3ZSW5bLKlIB4nIbuigl6z+5HTSULztm3UxuEgAb+9XSkhHGgej9O8ByhrAbsSNTaSgmO1knDv9apMVxxb5veroHG3m8YQDquigTx2LgzY3k73yMrW1q00v2a7YLEy5nbT/XNmrpYWurfiYuqPLUYGg6oplEqpKuCduRKFQjT2kqwlaLAtBR3XoY5kV0oXhK4IxJKZ+SbPJoqFsI/w0srt+MmLnyOeTGNCsROPnH0Qqgq72KYZBNivmKvCtrTQ4hMI0N9btiiXgVBILZBipRCEkQ8L+53BVg52Y2JLJQvAPp9SQJJJep8tGppG8wgH/XKqVC70xnFZ7PPPmZ5aW1UmqlSKrptMkmDsclFfbjellK2ro5iC9nZ6n60TiQS1YWVk+3ZqM2YMCdpGIwn3paUU/FxXR2NPpaionMVC16uoIOE6EqF+WPDljFNcfI6VK5dLuWkByqphMKhCfkYjteFga3aTMptpbh0zhqwgrIwYjfR3SQlZXTjuIRpVFc+zq3YzrIhwTAZbYPj/wAwXS0H2OpRdsZ1JJOg4W8oFoTN8YRJMbCYDLEZxhRL2clJpDUv+9TV+/94mAMC8/Upw33dmwmkZ2sfKYqEFavNmmrw3bKD3W1ro74YGWqxDIZWhhN0mBEEY2expBzjbOpkdc5FdbZsVCY6hYEtFMKhiNlhZAFR7jicIhVSsBWckisVUalmrVWUo8nrpWFMTXctsJuG7ro4UCI7d4DoOHOjNVbhtNhLqa2tJaLbZSGjnbFYcyzF+PF3b41EuVuxOBOQGP7e10b1wrAdbd/i6XOlbp6Nx+3w0v1ZU0P243So7EwevcxVy/gyya0qwK1pFhQrs5qxdwSApWzod1ZowmajN1q30OZWXk0LE1ovhYimwWOj/0tbWuWIRCuXGhwhCZ7RHyI3CM0LcoABRLIReEogmcc2Lq/DO140AgMXfGIcfHzdp0OMpsuHFiQP3WlpUfQqfD1izhhZqdltgIWEAajkKgjCM0OlUYTwWKA0Geo9rQ5jNyjoAKMG0Y1E9dktIJpUVgoPAXS4SWgsL6XdrKwn0RqOKc/D5VA0HnU7VcNi2jfqaPJk2QL7+mgRsh0PFfbH1w2ZT4+NinZxOt6CABHeuO1FURMJ+VZVyfwJIIN+0ScWdGQwksHOgtk5H8yUHaadSdD67jYXDNNe2t6vd90CAPguO2cgOpuZMTGVlu7owsXDNbk/Z5zQ3U9sxY6hNdrG9SIR+smMnhpOlgJU1Vq4GM82tsHeQia8YIW5QwAAoFvPmzcOmTZuwadOm/u5aGCY0RYCzHlmOjU0hWIx6LPnmDJw6s2LIxsPVsZuaaJFrbKQFSa8n68S2bZSrffNmWoR5UWEXKEEQ9g10uty/OY0puz/xLnm2AsGuQdnxGFzojc8xm6mv2loSFuNxEoA5/qK5WVW5ZkWluZnmI6+XBOqGBnp/xQoKkuZ6GfE49V9bS9dlod3lor+3bKE2Hg8pLaNG0T1EIjQv5ufTvPjJJ3SspISul22J4XgMkwmYOTO32F8oRP0Hg9Sez9++nc7hdLMVFeTCFAySIL18OTB/PikwPSkOxwHY7OqUStG9ms2q+J/BoGItQiFyI+N6EeXlw8dSYLV2rlwNdJpbYe+hNSQWC5x++ulobm7u726FYcKyTS2493MDwqkQStwWPPL9g7B/pWfIxtPeDnz1FS3iLS20ALIPczhMC+vWrbTgshDAx0WpEIR9A04nmw0rCmzFiEZJ2eCaDNmJHDg2ggOAAVUsk/vR6Uio5qKbZjNZDDhYORCgXXZA1Taw20kITibpp6AA+PBDmq+sVlVXhwv9xWIqSJxdqQBSWlpbab5jwTkaJeWFlYGmJrKCNDaqbFJ6PTBxIikUnDWPPwcuusdFRfV6UiaMRpUytq6OxjR2rEqLy5mk6uroeoccooT47PoaexLsLRaVNcpkorFs2ULHbDZV7LC5meb/8nIVOzGcLAXZipJU3hZ6Sp2Psj6U5dmGeCTdp98Vi8WLF/d3l8IwQNM0/Omjrbj5ta+QSuswY5Qbj549G8XuodtyiUZJqaitVfESkYiKrdDpKJCRC1Gx0pFI5GaNEQRh34KtDtmuT0zHDQcOXAZyNySyq31z8gejUbnYpNM0J23ZQu4/NTWqSF5NDQmaHg/NU/n5KjCca00kEspqwLUo2I2TM0VxMDfX5NA0ul5NjUplyylzZ80i620iQYqNxQIcfDBloWpsJPcpTSMh3eWifuNxskKw4tXcTMHgEyYoNySnk+7bbKbzuJ5FXp7K4mQ29676dLZbU1sbjaGsTClUOh1dhy0qNpuKBRlulgJRJoTeUNdOE1BZ3sgxb0mMhbBH4sk0bnrtSzy7nIreHVSYxhM/mA2nfWgf9Lo6WgQTCVIuEgmyWoRCKgCwtZUWX15gJEhbEITeBu5yjQZ2p0ynSajmgGFNo9c819hsykXKYlHB1KwM6HQq7bXDoYrUseLDGas41avZrILNk0m6TiCgMmHF4+p4IKBiFmpryQJRWEhuoRzo3dJCigLHPnCmpOZmVXiP6/yYTCTEr11LVmC9nuI3JkygdqxQADQXW63KZYyzUPW0+jQHQDc0qKxQyWRu/IvTSQoaF9RjxU4sBcLewI52sliUe/YBi8XVV1/d6fs6nQ5WqxXjx4/HqaeeigKJThrRtIbiuOTpT7F8cyt0OuCa4yagwr8GFtPQpj2LxWiRDgbJxL9jB/2t19Pi1dxM7gR+Py1eoZAoFYIgdE7H2hddwW24HgYHOQMk1GoazTcct5BKKUXCbFYB3vn5qhgfp8NmCwGgrBZcA8NoVHETTH29ErQ5Za3ZTH1FIipBBcdRbN1K7fx+sk7k5dH5LLSzEA+QUuL10t/JpBLSS0pUcblIBPj0UxozK0ceT+6YbTYVC9Hb6tMFBdQmFKLxsoLB6Wnz8lTdjbFjd1UeRJkQRjJ1PvrSl3v2AYvFypUrsWLFCqRSKUyaNAkAsG7dOhgMBkyePBkPPvggfvzjH+ODDz7AlClT+m3AwuDxdb0fFzz5P2xvi8BpMeL+787EkeMK8I9/rBnqoWVSMG7dSrtvbW3KFSEapd0rXrS4MJUgCEJn9NQ1kq0W2TUvsoO8OZ6rtVUpLZpGQm5xMQnbiQQJyRwoznFhnIGJFQK2bHCcB+/6GwxKceEUuXY7/TaZ1LlNTTRmn4/GWFSkqm5brfT6yy8pQ9Ts2XQu9wHQWDmTVCpF7QMBUiJcLspg5XQq5cTrJeuH2azclvpSU8JqJXctVi7YMs0F8rjauc1GFhlB2JuozbhC7QMWC7ZGPP7443DvjEjz+Xy44IILcMQRR+DCCy/EwoULcdVVV+Ff//pXvw1YGBze/boRlz27AqF4CmO8djx69kGYUOJCYhhUkYtGabduzRpg9WqV3SkYVAF9bK0QpUIQhIEgmVRKg3HnSsoWB65FwSla43ESntvbSTBPp2mOiseVgsIWBra6xmLqOMd22O0U85BIUL92OykO2YpFIkF9sBsWB2UnkyToc0Y8dpMCyAqxfTtZfjluobZWFaArKKCxezx0jVCIzh09miwezc2q2J/BQD9s4YhE+l5TIi+P0vY2NKiigBwzx5m8xoyhdoKwtxCJp9C2s0Be+b6gWPz617/GW2+9lVEqACAvLw833XQT5s+fjyuuuAI33HAD5s+f3y8DFQaPp5ZtwU2vfom0BhxSXYCHFh2IfEcnefuGgGiUFr+mJgo45KBF3v3jXb2GBlX8ThAEobdwDAULv+z+lO0+xRWjOZibBXm9PteC4PerdKk6nUr7Go+TYM4F3rhPjqtgrFYS7LODxg0GUkSCQeXCVF5O8yMrIw6HSn/LiS04QJv/5krd7Ka0bh317fFQu8JCer15s4q9yM8HZswg6zBbjeNxUijGj6cxcvA1x6dkxzr0pKYEZ3qKRlVAeSxGr93u3btTCcJIZGMTCTH5dhPctpETEt3rkfp8PjQ2Nu7i5tTU1AS/3w8A8Hg8iGfn7BOGNam0htv+/hUe/3ALAOCsA0fhV6dPh9k4CJWEugm7NrF/bX4+mcFNJnovFKLFlX2UBUEQegsrD7yBodcr60R2/QpApYFll6hkUrlmciG+VEpZEOx26pOrfxsMJDC3t9MmiclEiofXS0pDPK6K0lVXU1ufj66dStFufTJJ71sspIRkW06sVuWSxO5KVqvq12ikfrOLCDocuUUAOUCc3U7b2kjhKCtTcWzBIFlAuJ6HppEywpYZvV4FXEci3a8p0bEmBCtVJSVSE0LYO2HFYkKxC7rsIjzDnD65Qv3gBz/APffcg9mzZwMAPvnkE1xzzTU47bTTAAAff/wxJk6c2C8DFQaWUCyJy/+8Em/vrKR97YJJuPToccPiYebc57EYKRFmszKfp9PKHSCZpDbdMa0LgiB0B86KBKi4B65yzbERHAcBqErVvFPPgno8rlw1ObYilVJWAlZeuH4DH0ulaEdep1P1JNrbqS+LhYT65maVnIIVnlGjlIJhs9E57L5kNpPi4vVS+5oasjAUFpK11+NRgn8opFLnFhRQv62t6r5Y0XI41H1zcHsgoGp4sIuV2UzjZbemnuR3kUxPwr7E+gZSLMaXOId4JD2j14rF73//e1x11VX4zne+g+TOGc1oNOKcc87Bb37zGwDA5MmT8eijj/bPSIUBo84XwflP/A9f1flhNupx77f2x8kzBt6uvKfFIRolP1+u8BqP0++SEnInqKmhH6uVFjq/XwU/Sp0KQRD6SvY8wi5JPGexK47ZrOrkcHsO4GYrB7suZaeK5fSoFgsJ9DYbCe/Z1opkUu3KBwKqZgML61z3wu1WKWwrKsiSkEzSeRMmKEtLWxuNma0skQhd0+sFqqpoTFYrWUK4JgXXw2Crhaap9N5cV4NjKCIRGjenmm1uVnUlfD6qo2G1Up9Wq/rpKaJMCPsC6xsDAIAJxfuIYuF0OvGHP/wBv/nNb7Bp0yYAQHV1NZxO9QHMnDmzzwMUBpYvdvhw/pOfoMEfg9dhxh/OOQizRufv+cQ+EI12XizJ4VALs05HysOGDWqnS9Nol2vZMlqwYjGVeYV9eznVoyAIQn/AVgTekWchmwV5LlIH5MZddFQyOBUsWzcMBpWdiXf9TSZlbS0upr65YnQ4TO/zJgsXnWNLyKhRNE9ytiSOPeD6EsXFNGdu2EBF9CwWckOqrCQXKItFpb7NVhhYoeLaGGzN4OrgnAI3ElGWEKeTlJjmZhqP201jCofpXkwmsrQkErvPCCUI+zLrG3daLPYVxYJxOp2YMWNGf4xFGGT+/VUDLn9uJcLxFMYXO/H4ubNRWWAf0Gty8HV2saRAAPj8c5Uy0Gym95qa6LXHQwuU3U4L3ubN9DqVosVs+3a109exaq4gCEJ3YKUgWzng2hTsnpRO05yVPc9ku12yCxAf56BkTkfLigIrG6GQcnFyOEggLy2l+Y8rVrM7VSJBFgW2PrDrld1Of5eUUHXtpiaaD7kIXUMDMGkSXY9jNcaMofc8HlIsbDsTznAgtdNJikN2liV2+dI04IADqO/6erqHUIjasusVoLJBeb1qrA4H/fh8uZWyBUHIJZ5MY2sL7SZMKHYN8Wh6Ro8Ui6uvvhq33norHA5HlwXymHvvvbdPAxMGluzMT4eP9+LBRQciz9ZFTsB+hIOvuVhSNEoVtJuaaCFyuWgB+/RTWnwmTaL0jAYDZSn54ANyf8r2XQ4GaZETpUIQhN7S0dIA5LpVWiy5WYzY/adjBm62wvJvFqp1OpWOlt2pOCA6FKJjPh8pCGyh8HqVcB+Pk8DP2aR4o8VopOtwdimbjRSHQICUCrebNnOyMzaNG0d/b9tG829ZGbljmUyq0F00SuOx2+kaPh8dd7vJ3aqqSs3d7e10H1Yrze0ul5qfs12lGLt910rZgiAo1tYHkEpryLOZUOIeWSa9HikWK1euzNQxWLlyZZfthkPAr9A5mqbh1/9aiweXbgQAfPugStx2+jSYDAM/u3NO9exiSe3tZH2wWmnx+uILWqy2baOFLxRS+dk/+ghYv165FfAOHisZgiAI/QEL7Fy8jlO0ptPKMro7l0udLje2Ijt4m+MzspUUrlmRTitFxGZTu/6plHKZ4mDq4mJ1rUSC3JtKSkjg93pJuOfK1Js20XUOPJBec6xFURH1F4nQe9xfJEKuS6EQzbGhEM3RpaX0vk5HilZVFQVT8/1w2t10mvrQ68ny0rG+xO4qZQuCAKyqoS/k/pWeESdT90ixePfddzv9WxgZJFJp/PTFz/Hiiu0AgKuPm4gfHTN+0B5a9k3m3atYjCwYHMy4YQNV0jYYaMELBun4++8rtwGTiRasQED5AbOPryAIQn/AlgROkQooV6juuO6wS1S2csLVs2MxlcGJLRcAKRIOh6pgbTDQhko8TtaD7AJ6bP2IRmljJhymzRabjc7j4ndVVapoHrtLNTSQsO/x0HzKxfiKi6kfDqhuaaFzPB5SHrh2R12diovLTvPK7lQA9cf1NWKxXMtHMkmvpVK2IHTNypp2AMDMSs+QjqM39HibetmyZXj99ddz3nvqqadQVVWF4uJiXHTRRYhxyglh2BCKJXHBk//Diyu2w6DX4a4zp+PyYycMqibMO3jsOsCKhk5Hi2NTEy0+Hg+Z/BMJWkg3bAA++4x25LZsoRiL+noqANXSotwLBEEQ+gPe7MhWIjq+7gqdjuYvq1XFU3RUTgAVsM3vsdLBx9jKwcf4NRfOa2yk7EycES8Uovmwro5cSWtrab41mVSQ+NatNJ+2tdHxpibVdzqtCu1lL+GaRu1Z4eFYirY2FS/XEYtFuUOVltI5bLHmgoHjx0ulbEHoitUZxWLkfUl6HLx9yy234Oijj8bJJ58MAPj8889x/vnn49xzz8V+++2HX//61ygvL8dNN93U32MVeklzMIYfPPEJPtvug9Wkx4OLZuGYySUDft2O6WR5sWlrU761BgMtZA0NtHDb7bRAciXXHTtodysSocU2HqfFKhQa8OELgrCPk0opi0JHpSI7yDu7TXaqWI6jyHal0uuVZSH7GAv4breKh2CXKxbqCwqU0M/ZogwGsjawZWLbNhLmzWYS3MvLSfFgK4XRSO+nUvReMEivuRBeXR314/XSvWzfTgpIUZFy1eLq3G1tpNh0VvWaK2WzW5XHMzSVsqXmhTDS8EUS2NhEQs7+ozxDO5he0GPFYtWqVbj11lszr5977jnMmTMHf/jDHwAAlZWVuPHGG0WxGCZsaQ7hnMc/xtaWMAocZjx2zkE4YIjSyRYU0E97O+2c2e20QxYKkRUimaRzamtVQTzeieNsKjqdciMQBEEYaPT63AJ4AM1N2UpFdhu3m4ToeJzaORy0ccIxByaTco/iInepFFk5OFuUyUTzJsdo5OfnpqjlDFOcpnvUKDUurrbNsRJ+PykbZjPVtOCYNJOJfmpr6doWi0qMUVCgqorHYqSohMM0d5eWqs/B4VBWiI5C+1BXyt7dOiRVuoXhzOfbfQCAygIbvM6Rpw33WLFoa2tDSYna7X7vvfdwwgknZF7Pnj0bNTU1/TM6oU98scOHc/74MVpCcVQW2PDkeQejumhg8yF3lk42O+0hQDtizc004SeTtOg1N9OxdJp2x1palKVC0hEKgjBUJJMkNHNANm9scMwB/3CaVk5N63KRgsGWC70+N8sUZ0yy2agt98OxFk4nzZGRCPWZHa+RTO4aV8HxEZx+Nhymc7nehtutak1k155wu1WVbLZMsJLALlJGI/XLblJ83GSi63Q1Rw9VpezdrUORCCk8olwIw5WPN7cAAA6oHNhN4IGix4pFSUkJNm/ejMrKSsTjcaxYsQI333xz5nggEICpY245YdD535ZWnPfEJwhEk5ha7sbj581GsWvgZ9KO6WQBWlD8fmDlSvqdn68Wyq1bydQei9Gi5vOpoMRwWIrdCYIw9MTjynUpO0OT2ZwbN6HXKxcmk0nVjcgWzJNJZVFgYZvTbLMAzsHbDgedZ7fT3Oh0qpSwbJkwGlXxPLdbWTNY4He7KftStouWz6fS2ebn098tLdRXdkA1K0Q85o4bPdmZrbLpzA12MOlsHeqO+5YgDAc+2EA7rUeMH5nZDXqsWJx44on46U9/irvuugsvv/wy7HY7jjzyyMzxzz77DOPGjevXQQo94z/rm3DRU58ikkjh4LEFeOzcg+CyDryy11k62WiULBLbt9PfnN+9sVG5BiSTNNGzhSIapR9RKgRBGA5omsoUxa9ZqM6GLQIul1IeXC5lrTCbaXOF4yxsNpoPudp1NJprHRk3jhSC5mbqz2Qiyy9nrIpEqF+uhq1pqsioywVMnkwF8GpqVHrZkhLasff7Selhy0ZxMZ2XfU8WiyqWx3UzspWIUEhtFAHDw/2os3Uom925bwnCUOOPJrB6pyvU4RP2EcXi1ltvxRlnnIGjjjoKTqcTTz75JMxmc+b4H//4R8yfP79fByl0nze+qMflf16JeCqNoyYW4eHvHQib2bDnE/uBjulko1EqardjB/nmsuJQVEQLZ3s7WSm4kjYv3rz7JgiCMBRkB2Zz2lie38xmlYmOg7s5lapORzv+nJSCXXA69sEZpmw2lTrW7SYlIBolhcJup/OjUVUXgtPOcsG6dJoCrzWN+jCb6f38fIqnGDVKWQxYoQHodUkJ9cfxbiYTnbt5MxXYY0WAi+XV16ugcK4xZLWS0gAMH/ejjutQR/bkviUIQ8nyTa1IpTVUFTpQ4bHt+YRhSI8Vi8LCQrz//vvw+XxwOp0wdNiyeeGFF+B0Dqwfv9A5L63cjmte+AyptIYTppXit985AGbj4JU1zU4nm06TpaKhgRYZv592iTi+IpFQikddHS2WvHsmCIIwlGRXxeb0rhwDoWnKqqBpKq4BUBYDVkry80kA9/tVMLbNptyljEZq43QCEydSX2y1cLlU9jueFw0Gal9ZSX22tqoselwZ3OEApkwBpk5VgjwHiq9bp4r0RaPk/uRyUb0Lp5P637SJ2o0dq6wtVittCNlspHzwOLItEcPF/Sh7Hcra88zQlfuWIAwHPtzpBnX4eO8Qj6T39FixYPK6SEBdwNsXwqDyp4+24pcvfwEA+OaBo3DnGdNhHIRq2tlkp5PltIIOBy3AgQBZKDizSjBI7lD19fS+ZHoSBGEo6FhfB1AuMuymxDUkNE25MXGWOj43W3Gw2Wj+i8eVIsFtODharyeBnvfm7HaaJzmYm91BWblxOEiQN5lo999sJmF92zZSMkaPVgHj06YpF6qWFlI+YjGad202snIEAspSYjIpt61Jk8iK0dioXK6yK253FoQ9nNyPOqY170hH9y1BGE6M9PgKoA+KhTB8ePzDzbj5ta8AAOceNhY3nDwFev3gloCPxVTMRChEPr2cnaS9XZmmo1H6e/t2SnPo94tSIQjC0MGKBaCUhWyLBAc8Mzpd7q43Z2nS6WiOM5tJCPf5qJ3bTfMj/z1qFL3mzE06HVBdTRaGZBL4/HPacCksJAWA28ViKrtTKkVjLCtTrj0zZpBAnUjQ3Lp1K829nP7Wbqdrt7fTfTgcdH4oRErE6NH0vtVKCk8gQBYGruK9u8xOw839iGtotLXlumV1dN8ShOHEtpYwNjQGYdDrcEj1PmixEIYHT/53S0apuPiocfjJ8ZMGtZp2NEqL2PbtqgIs5073eul4YyOZ2TnN4bp11L69XapmC4IwtLBiwBYHdpGx20mojkRU8TqbTQnXnDrWaFTCql5Pc192kHdzM819+fnUtr1dKQ1tbeTWNGUKveaMT1u2kGVjv/1obO3ttFnj81FfiQRZH6xWVQdjyxZSLIqK6Hc6TWOy22kMFRXUf1ERzb91dTSORIKsGgAFcFutqo6GxUL3sHkz3RcrWh0Dsoeb+1HHGhrhcOfuW4IwnHjjyzoAwJyqAnjsnXyRRgiiWIxgnlq2BTe++iWAoVMqNm6kBS+ZVEGF7JPMhZhaWshc39REC1xNDS2U2a4HgiAI/YtKK8fWB4Oh8yKbPH9xATubjTZGWLDmWAcWuLlPi4WEVKdTxZIFg9Se07y2tVHf7Baan0+WgkCAftts1J7nw2CQ4i3YVYmVFJOJ2nM62nCYjnOaWh6Dy6WyR/GGTjRK13A6qS3HZeTnk0Lj89GcnE6T2xMrCn4/zfGtrSoInM/PDsgeju5HQ1VDQxB6yxtf1AMAjp9WuoeWw5sRpVjccccd+Nvf/oavv/4aNpsNhx12GO666y5MmjRpqIc26Pzpo6244RVSKn54VPWgKxUALTaNjcptIBKhxRigRW/DBjq2eTNlC+HFi1MkCoIg9BXOyhSP04/K6ETzYXaGp+yUsdlYrSRIsyuT1apqQqTTJOxz7YrsQnYFBSTMx2IqS5PFQv2wwlFQQK5IBQWUiSk/n9p++aWaLznt7KZNJITbbMr1yWoFxo9XsRpGI/XDVopwmCwNlZVkjQgEqM/ssXP8Rn6+CiTPz1dB5GYzjTESoTma62h89RVtDFVWqgJ94bAS0G02FZA9XN2PRJkQRgIN/ihWbGsHAMyfIorFoPHee+9h8eLFmD17NpLJJH72s59h/vz5+Oqrr+DoKmpsL+TZ5dsygdoXza3GT4+fPOhKRSxGpnTO286LYShEC1U8Tn7CjY0qE1QwqBY9QRCE/oArWBsMKjtTIrFrxWv+mwOQORDbaCQFwOlUx3mjhNPCcqE6h4OUgUSC5sB4nNrF4yTAFhVRe6+XdvCLi5W1Ij+fYhxSKRV3pmnKRbS1lYRxu10J7+EwWR44RfeWLTSPchVtgNqNHk3XsFppHuZsUTxWm40UBLZcmExkqTAaVbVtk4nGumWLUhI2b6Y+OFbDYlEWDq7WzQHZ4n4kCL3n32saAQAHjPagNG9kf1lGlGLxxhtv5Lx+4oknUFxcjE8//RRz584dolENLq9/Voufv/w5AOCCI6pw/QkDp1R0ZUKOx/XYsYOCA30+WjBqamgBa22lxamuTgVn19crdwBBEIT+hoOnHQ4SlkMhQNO0TO0IFpq5WjWfY7GQwMx1HAwGpQgAKo6iooIEak5QwYJ9IKCsGek0vTabSai221VKWVZE2tpobOk0Cdy1taQUsLDPwdWbNlFmJ72e4iEiEbq+16syQ4VCNK5YjCwKoRCN3WRSqWojERob3zcXxdPrVRVvk4k+B3a9CoeVdSE/n+7D7yelpLiY2trtKmFHtgVI3I8EoXe8+RUpFsdPHdnWCmCEKRYd8fmoOuG+kuL2/XVNuOr5VdA04HuHjMbPT9pvQJSK3VVPpUA/K/x+Wlza28kH9z//oYXMaKSFuL6edsKiUbWzJgiC0N9wXYZUiuYafm00JpFKmTJWCE7xyoJwdixAKqUsEsEgBTUXFJACsWGDUjpKS1WcBlsAWHBn4d1mI0FcpyPB3+kkhcLvJ8HcbqfzvF6VHYotCKkUvccB2j4fnc9uXvn51IfbTfOrzUZzLVtq/H7qi5Wn+nr6TNhqkEyS9djppPe8XnKBYsWotpZel5TQZpHZTMfcburb7yfrBispXCG8I6JMCEL3aY8Byza3AgBOmFY2xKPpOyNWsUin07jyyitx+OGHY9q0aV22i8ViiMVimdd+vx8AkEgkkBhBjv6ratrxwz/9D4mUhpOmleIXJ0xCcgBMAFw9NRajxYqLLnHgdSKRQDhshN2exPbtwJo1wBdfkLmefZ2DQXq9U+8ThD2Q7PBbEPYMKwkclJ39W69PIhYzQa9PZqpec0ByOq2UAE1TmZ3y80mwZ+WC6z3Y7aQYcPpsi4WOs9uT30/CuNmsavVw2u2NG0lJcblUmlmTiY6PGkV9+P1k4Q2HqY+iIhoLp3k1GOj6FRV0jKtvm0y0+eN00nvsilpfT+/X1qqNIS5+p9fTeLxeqq6drQCwxZkrhxuNqoI4B4T7fCoIPRyma7Kr2b4AywwjSXYQhjeJRAIfN+mgacBBYzwoc5uG5fPVkzHpNI3D2kYWl1xyCf75z3/igw8+wKhRo7psd9NNN+Hmm2/e5f1nn30Wdt7mGebUh4HffmlAOKnDpLw0LpqcxkAV1G5psSAUMsPpVA9RIqFHMGhEY6MNkYgBTmcC8bge4bAR27c7sG6dB+m0DqmUDj6fGcmkHu3tIzdVmiAIwxtWEnS6FDRND00DUikd9HoNJlMSyaQOgAE6nQadjmsspGEyadC09M5zdQA0WK0puFxxOJ1x+P0WGI0puFxJ2GwpWCxJbN/uQjyuR3l5GAaDhlDIgGTSCIMhjXgcCIWMsFpT0OsNiMd1MJtTsNtTSCb1SKc1pFJ67L9/M6qrgzCZ0vB44giHDYjHjdDp0mhstCIYNMFoTMNmS+20sGgoLY1C04BIxIDWVgvy8+Ow25NIJHRoazMjEjEindajsDCKVEoHkykNvV5DU5MVNTVOaBpQWhpBQUEURqMGiyWFgoIYYjE94nEDHI4UrNYkDAYNqZQOfr8ZPp8J5eUhWCwa2trM8PstiMf1SCb1MJlSSCT0yMuLIRQyw+2OYdw4P8zmQSpOIQh7IZoG3LbKgOaoDt8dl8IhxcNTJA+Hw1i4cCF8Ph/cbvdu245IxeKyyy7DK6+8gvfffx9VVVW7bduZxaKyshLNzc17/HCGA02BGM78/XLU+aKYMcqNp849CA5L/xua2F+2poZ2p9hNIBol6wMf//rrJNat+xolJZORTBoRDFLmEIOBdsjq6lRbQege2ZaKEWtEFQYJrjfBO+dc1C6VUm456XQSqVQKFosB4bAxUy2b4wlSKdrdd7lUpWyzWcVcAGSFYKtAPK5iG3bsoLaBgEoTazQqqwfHefj9dNxgAM48E5g9W8VyJBIUo7ZuHbVzOlXRO85MNXEixSz4fCo4urVVWSTGj1cxIZzdKRAgy3I8TnEXZWXqfnw+ssBwZiiXS6Wz1evVPXE2LJ77uYhpOKzSxhYXU40Nj2conoChI5FI4K233sJxxx0HU1fVAAWhB3y0sQnff2IlbCYDlv3kqAGR7/oDv9+PwsLCbikWw/MOukDTNPzoRz/CSy+9hKVLl+5RqQAAi8UCSycOnyaTadhPDNFECpf+eTXqfFFUFTrwxHlz4HH0ryUgO54iFCLFQNNo8bBayY84laKFr72dsz7pUFJixMaNpkzuc52O+kinpeid0BuSoOloeH8nhYGHszdl/wA0t8RiSojnNNesULDiwBmaAoE4dDoLjEZTpj1Acx7HTHDBN85kN348Cd87dpAAzzEILFjn5dF5TU0qCxW7CHERPSA3MNxmo/ciEbp2Ok2KxY4d1KfbrVLQptMk8EejNPd6PKSolJbSfMwZsCorqVq3ptG8HAxSBj5Nowrc8TgpFdkheG439Wsw0JgqK5U7GQdZ19bmpos1mVT/qRS5SU2YQH3vy1meRoL8IIwMXvmMgrZPnF4Cj9M2xKPpmp487yNKsVi8eDGeffZZvPLKK3C5XKivp2IieXl5sNmG7z+kN2iahuv++hlW1bQjz2bCH8+djYIBUCp27KDfvJC0tdGCFovRYsc50NvbaeEzGoHmZhtqamgR2rGDfji9YJZxSBAEoUdwrQi2SuTlqRSw8bjKNsRxA/G4ytDEKWWNRhLI9foY4nE78vJoftI0pVCw0Gw0qorX7e00l+l01Ka9nX5cLhKiORaDLSSscESjqjhdMEjHR4+m4zQOmittNlJcXC5K6drURHPr6NEkqCcSdB8NDfR3QwO9z9WwOb0tV/FmRam0lI653dRvZSX1zXEYjNFI/cdiKt6i455bx1oUFgu9p9ORkjVqFH1egiD0nWAsiX/uLIp35gEVQzya/mNEKRYPPfQQAODoo4/Oef/xxx/HueeeO/gDGkD+3zsb8OrqWhj1Ojy0aBaqCvu/TkdrKy2K+fnqPYeDFlM2/8di9PdXX9EOXmsrUFvrQDqtdtXa2qQ+hSAIPYd31Ll+AxeWSyRIgOZMTckkzT+A2mX3+5Vw7HJRm5IS5R5kNJKXr9VK/aZS1I6zLoVCym2Tj2/bRhsk+fkq+5NOpxQGtqCMGaPch0IhshZwMLPRSEHWHPhts9H5yaTK2hQO5yo5Viv9uFxqDua0tImEqnjd1kZWg44uSGwdMZlovE6ncn1iuK5HNEqfU2eZm7qqRVFSIrUoBKG/+csnNQjFUyi2ajhojGeoh9NvjCjFYgSGg/SK99Y14d5/rwMA3HLqNBw2vrDfrxGLkVJgNNLfbFJvbaW86a2tKkCyvp7aFhTQgpuXF0VtLe2K+f20+AiCIHQku+p1NtkuTnq92t1nywBneOIK183N6j2uDeHxkHAcjVI/7OJjtdJclkjoMxmaLBb6SSbpPKNRpYq12+k9riURj1M7t1tZTgA6v7RUuUFxLQqvF5mNFo77sFqpT6+X+q2upvPb2+k+4nE6npenYiQ4rs1gULEZwSDNsVzFm6/XmYCv15NiEolQ39EoKRd2O92vz0f353bvvgq21KIYWFKp1LDM+iMMLqm0hr+v2ooKlwELRqURi8WQzi4KM8iYTCYYeLLrIyNKsdgXqPNFMrUqFs0ZjYVzRvf7NdgFats2WnSSSVrw4nFa9NraaBGKxVRhJ7dbLTSBgAlNTbTAZi/2giAIDO/GJ5OqyjSgXI14DeMaDmYzCbEOhyoyx+mu02maqzSNBN9USsVGZNej8PtVwTqdTsuc43arWAy9XrkEeb1kXbDbSXA3GpUFtqCAxpBOq+vH49Q3WwO4andFBf3NaWqrqsiFic8tK6N74XSyNhvNw9n9AzSm2lra2Jk+nRSSYFD1y65KnREKkasSZZKiewsGVYyEzUaWlvLy7lkeRJnoXzRNQ319Pdrb24d6KMIwIJJI4eJZbhh0brjNGmpqagas2HF38Xg8KC0t7fM4RLEYRiRSaVz+55VoDcUxtdyNX548pd+vwUoF74KxRWLtWlp4OPja4aDFtbVVBQ5++SWdV1NjRyCgqt2KUiEIAqBcmyj9q1IeWKBPpVQchdms4h7SaZp/OtaD4BgBu53O1zSam/LylKuQ0UgCusOhBH8OcmaFprWVBHqnkzZU2ttJ8C8rU/Uj0mllMfH7lSuT1apcQ7madSql3KH0eqWgrF1LMROjRtF5ZjPdF7tnsSVD05Tlg92kNI0sw3V11EdFBd2Ly0U/bW30WVituQHWiQSNiy0NgHJl4mxXY8eSC5XERwwdrFQUFxfDbrcPuRApDC3bWkMwuFPId5hh1eJwOp3Qd1ZtchDQNA3hcBiNjRRIXlbWtyJ9olgMI3777/X4ZEsbnBYjfrdwFqym/jFLZcNxFXl5FBy4bh0thn4/7ZZx4SYWAFpalAl90yZSQnw+2u4aQqudIAjDEE2jnW62fmZniOPq1hxbYLWS4MvpWb1eEvyDQdrM4ErZOh2lZuXYA04iwYXZ2KLBKWFZsQgEEnA6c2M3OL0qWzw4SJsVBw7MtttJ6eACcJpGx7g/vm44TNc0m+kao0eTtWLcOOVCRHMmfQZ5efQeuyoFAnTfmkbtduwg5YBTzWbjcNAcXVpKikR2DARX1uZzxJVpeJFKpTJKhdfrHerhCENMJJ5ENG2A3mhEab4T4WAAVqt1yBQLAJkESI2NjSguLu6TW5QoFsOE1TXteHDpBgDAnWdOx9gBCNbmQGyjkRax9nbKIrJpEy2KnFklFKIF1W6nRauujhbicJgXVHlsBEFQmEwqNoJdjjqzZLLrEisNbClgwd/lojmmtJR+R6OqSjbHHSQSNHdxnADHJ5SVkYDNrj8Wi7J05OVRe86IkbIozgAAQ9NJREFUZLGo/jjzFLsN8VicTnVfHM/BAvq4cXQvvFFjt1M2poIC6sPvp7FoGh3jVLDl5VwZXFkYnE5lLTGZqO/Okhxy0LfZTGPek+IgysTwgWMqRkpRXmFgaQxQ+sw8uwlG/fCxXPHzmUgkRLEY6UQTKVzzwmqkNeCU/ctx8ozyAbkO79S1twObNwMbNpCCEQqpQMb6etoZc7s5tSy9l+0rLQiCwLCgrmk0j7BykY1Op7I8cYyFzUZKAW9iWCzkrhOPk6tPKkXCPkBzV0uLUhiMRpqPON4gFlMZl8xmEtYDgVQmS1IgQIJ7Xh4pLxaLcv8sLKQ5r6VFuRaxgsMxtiUl9DcXkKuspPGVlJBLVUUF9cOuXSz4s0Vh4kTqJ5Eg64XBQMpTtoUlkaBNnK7Wc85MlUjQuEVxGHmI+5MQSaTgi9DEUuQaXl/i/no+RbEYBjy4dCPWNwZR6DTj5v+bOmDX0etpodu4kSps19XRAsw+xJxBJRKhRTuZpMUsFMpd/ARB2Ldh5YCtDWyhyA7Q5jWKC9rZ7ST0p1LKNcjpJCGdrRLxuIohsNnoOG9uUHFOOo8VGVYyOAWtyURzFr2nZVLEcsraujpqU16u5jx2zSouVtaNkhJlEYhE6H23W1XIrq0lpWDiRGrLLkiJBN1nxc6U9B0tCruzMnBa2ra23ID0aJQ2g2pr1XwdDEr6V0EYiTT6KY1dns0Em8kwpJmgBoqhc+gSAAA1rWH8/r2NAICb/29avxfBy4aq0ZJi0dhIi3tzswpIbGmhdrEYLeRct4J33qJRsVgIgqCqTns8JOxyalgW8jlNLMcUcPAyZ0ICVEHNaJQUCpOJ5qDWVpqbgkGVLcrlIteiykpyeeJU2G43Cdf5+coi4XbTOfG4HokEtTMaqY9sYfzAA4Fp00gJKC6m+IgZM4CZM6m69NSpwLHHAscdR4XtOPudTqfi1DoqB6GQsohYLLtaFjp7LxseX1sbfSaRCG0C1dRQv5WVdG5bmypuKggDxfvvv49TTjkF5eXl0Ol0ePnll3dpo2kabrjhBpSVlcFms2HevHlYv359TpvW1lYsWrQIbrcbHo8H559/PoJsjuxAc3MzSktLcfvtt+9y7Fvf+hYOOeQQpAZZEHnxxRdx9NFHIy8vD06nEzNmzMAtt9yC1tbWHvUTiStrRYk7d1dg6dKl0Ol0e0XWMFEshpg7//k1Ysk0Dq324sTppQN6LZ+PftJpUija2ii+gtPLckCgz6cW/WRSgrQFYV/EuNOezbvrNhsJ7Xl5pEwUFZE7D8cSmM0qiNlmU/EJbL1gpSKZpHZc/bmujt7n9K2cPYmTR6RSdH1OQ8vuVByXkJen4r/iceo3Hs+tlcHjAkhA53FNmAAcdhj9zJxJysbYsSq+A1AbKmYzpX899FBSRBoaKKi8ro7mzbY2Gk9XNSK4GF8s1vVnzgXq8vOpXU0N9V1ZST+c5Sk/n8bVQ7lGEHpEKBTC/vvvj9/97nddtlmyZAnuv/9+PPzww1i+fDkcDgcWLFiAaJbWu2jRInz55Zd466238Prrr+P999/HRRdd1Gl/hYWFeOSRR3DzzTfj888/z7z/wgsv4PXXX8eTTz7Zb/UWmFQq1aXl4Oc//zm+/e1vY/bs2fjnP/+JL774Avfccw9Wr16NP/3pTz26TmOAPhOPzTQgyXm6Szw7q8YAIIrFELJyWxv+/nkd9DrghlOmDLj/ZUsLLbSVlbQobtlCVolgUGU9aW+nxS8aVTEZgiDsO3A8BFeDZhcmh4ME2vJyVYiNsyyZzcpikV3pOp1WSgCgApdZEYlE6LjFQgJ6KERCe1WVUhA4ToKVk0hE9afXkyISClGMRX19ttumHh6PGmsspuI58vJUv2xdSKVIKRg/nhQmj4fG1NhIbceOBSZPVp9JMEjFRNetIwUgP5+Ugo7uSdEouTFt2UKxbVu20OuurA0c1M3B6BMmqJTf2XBK8N0pKoLQF0444QTcdtttOP300zs9rmka7rvvPvziF7/AqaeeihkzZuCpp55CbW1txrqxZs0avPHGG3j00UcxZ84cHHHEEXjggQfw3HPPoba2ttN+/+///g8LFy7EOeecg0QigaamJixevBh33nknJk2ahFdeeQWzZs2C1WpFdXU1br75ZiSTycz59957L6ZPnw6Hw4HKykpceumlORaSJ554Ah6PB6+++iqmTJkCi8WCbdu27TKOjz/+GLfffjvuuece/PrXv8Zhhx2GsWPH4rjjjsOLL76Ic845J9P2oYcewrhx42A2mzFp0qRdlA6dTofH//gYrrzge5hcWYQJEybg1VdfBQBs27YNxx57LAAgPz8fOp0O5557LgAgFovh8ssvR3FxMaxWK4444gh88sknu9xLNi+//HKOPHnTTTdh5syZePTRR1FVVQXrAPtQSozFEPK7dykL1OkHjMJ+Ze5+67czP16/X7k61dVRDnVeoHl3LhjMjaOQeApB2Pvh+AQg151J0+hvjr3KjqHIyyOhlmtV2O1qRz47zSzHQMRiql92leI0sF4vHYtEqF+vV1WM5iQ6nGCCU75ardTe76f+jEayoBQUUFueu4qL1Tnl5dQfWyB4bly/nu7f4VDC+/jxpJBs3UqvfT5ShNhFyekkgZ/rAcViueczXDeIq3JzcHhbG42/M0WEMZnox+ns+jgX2BNGHpqmIZIY/J07m8nQb5uYmzdvRn19PebNm5d5Ly8vD3PmzMGyZcvwne98B8uWLYPH48FBBx2UaTNv3jzo9XosX768S6Xlt7/9LaZPn45bb70Va9aswbRp0/CjH/0I//nPf3D22Wfj/vvvx5FHHomNGzdmrB833ngjAECv1+P+++9HVVUVNm3ahEsvvRTXXXcdHnzwwUz/4XAYd911Fx599FF4vV4UFxfvMoZnnnkGTqcTl156aadjZIH+pZdewhVXXIH77rsP8+bNw+uvv47zzjsPo0aNwje+8Q1oOyfOh39zF35x86/wyP+7Dw888AAWLVqEzZs3o6KiAi+88ALOOussrF27Fm63O5P+9brrrsOLL76IJ598EmPGjMGSJUuwYMECbNiwAQVdmUc7YcOGDXjxxRfxt7/9rd8tPh0RxWKIWFPnx7/XNEKnAy79xrh+6ZNN49kLPpv/AwHaVdu4Efj4Y7VbptPRQhkO02+jPBGCsE+Q7SrEGxHZwj9bDFiZyC7GxvUcWChmAddsJuG+oUFtXHBmJJOJ+s9O58rns/tTLEZWgMJCOiccprmLA7NZGeB5rb5exR7YbCrTFAAYDGlYLBQ7UVlJfer15AbKNSD4HLa0+P30d3V1rvtVKKTmSPfOPSAOHi8tpT6bm3ctQMfpaPPz1XvsMtbWRse5qF1n/x9Or5sdzM1w/MgQpr4X+kAkkcKUG/416Nf96pYFsJv7Z6Gvr68HAJSUlOS8X1JSkjlWX1+/i9BuNBpRUFCQadMZbrcbjz/+OObPnw+Hw4HPPvsMOp0ON998M376059mrAXV1dW49dZbcd1112UUiyuvvDLTz9ixY3Hbbbfh4osvzlEsEokEHnzwQey///5djmH9+vWorq6GiSecLrj77rtx7rnnZhSQq6++Gh999BHuvvtufOMb38jEVZz6rYW46LyzYTbqcfvtt+P+++/Hxx9/jMMOOyyjJBQXF2cUllAohIceeghPPPEETjjhBADAH/7wB7z11lt47LHHcO211+52XNnE43E89dRTKCoq6vY5vUXEyCHiqWW0FXbitDKMK+piS6oHdLYzFgiQmZ5303w+2oGrqSHrhNtNC5PPp4QHsVIIwr6BppFAD+RWyNbpVOrYZFJldzIYVHAyoIKuLRYSyh0OFZvF1aW5pgX3mV0fIp2meYhjMbj6djBISks6rVw1efMjP58Ef4OBlACDQcVLcP0dj4frUiShaaRYFBWpGA9WiNxuYMqUXZWrcFgpHRywnUwqq0U0qu6JrT1Op7r37AxQgQB9Lp2R7crUVR0KrrjdmWIRCtHnIWlnhb2VY445BocccghmzpyJMWPGAABWr16NDz/8EL/61a8y7VKpFKLRKMLhMOx2O/7973/jjjvuwNdffw2/349kMplzHADMZjNmzJix2+uzpWFPrFmzZpeYkcMPPxy//e1vkU5rqPfRTu5BB8yE2UgTjsPhgNvtzlS77oyNGzcikUjg8MMPz7xnMplw8MEHY82aNd0aGzNmzJhBUSoAUSyGhEg8hddXk2/hojmj+6XP7EJN7LIQDqsc7pzGMRRSO2ac4SQWU8WtBEHYN8j+vnMsFVssE4lcpSBbiI7HSagHcgvIcQ2JhgaV+IEtINEoCeoclM3zT0uLCsC22ah/v18Vr+P0scmkqm/Brld6PblNWa0kXPt8yKSXLSsDWluTmQxKDocKNueU2mPGdF6IjudMr1cJ9kYjsG2bUhJ4/GVlNDaPR6XfZThGravNzu64MhUU0Fj5HrKtRrsLFBeGPzaTAV/dsmBIrttflJZSwpmGhgaUlZVl3m9oaMDMmTMzbToKz8lkEq2trZnzd4fRaIQxy5UiGAzi5ptvxhlnnLFLW6vVii1btuDkk0/GJZdcgl/96lcoKCjABx98gPPPPx/xeDyjWNhstj26hE2cOBEffPABEonEHq0WXdEUjCGeoi+515VbIFGn0/U53axer99FAUp0skPs6GqHYwAQI+oQ8O81DQjEkhiVb8Mh1d4+9xeLkRk+GFSpCTdupEBBXqDZZM4FrBwOWqg5rgJQO5OCIOybcPpXVjTSaWXVAFRtm0BA/fb5SOjesYMEYK5r4XKRAmA0qqKbJpOyPrDFQacjYdlqpbmJYydCIRXn4XCQEsBJJTi4nM/neY7Pb2kB0mldJjtUOk3XLy0llyiXa/cCPweec7XudesoNq2mhubahga6b45b45S72W5J2a5MndEdV6aOWaJ8PvrdVaC4MHLQ6XSwm42D/tOfSWKqqqpQWlqKt99+O/Oe3+/H8uXLceihhwIADj30ULS3t+PTTz/NtHnnnXeQTqcxZ86cHl9z1qxZWLt2LcaPH7/Lj16vx6effop0Oo177rkHhxxyCCZOnNhlkPieWLhwIYLBYI4LVTacGna//fbDhx9+mHPsww8/xOT99kNTQGVX0O+myrZ5p1kyO5UuB4Nn951IJPDJJ59gypQpAICioiIEAgGEQqFMm1WrVnXvBgcIsVgMAUvXNgEATppettsHrbuEw5RlhDO3GI206NfXK/eB+npaLCMRWtC4NgXvBGb7UguCIGTDFZ+zC9/ZbCQUx+NKIeEsS4CycnCgdiym6lkkEvQ7P58sCQAJ6TYbzWF+P/UbjdIPWynY2sEF8nw+pcSUltL5kQjPc/pMVe1EghQKnY7mxtZWNTd6PLkCerbAz9cwGilTVXOzskRw/IXVqu6lY82K/nBl4ixRuyuuJwgDQTAYxIYNGzKvN2/ejFWrVqGgoACjR4+GTqfDlVdeidtuuw0TJkxAVVUVfvnLX6K8vBynnXYaABK6jz/+eFx44YV4+OGHkUgkcNlll+E73/kOyrsKMNoNN9xwA04++WSMHj0a3/zmN6HX67F69Wp88cUXuO222zB+/HgkEgk88MADOOWUU/Dhhx/i4Ycf7tX9z5kzB9dddx1+/OMfY8eOHTj99NNRXl6ODRs24OGHH8YRRxyBK664Atdeey2+9a1v4YADDsC8efPw2muv4W9/+xuefvE1pDUNjm7EtIwZMwY6nQ6vv/46TjzxRNhsNjidTlxyySW49tprM5/5kiVLEA6Hcf7552fGaLfb8bOf/QyXX345li9fjieeeKJX99tfiMVikNE0DR9sIMXiyAn94+/W3k4LG5vKg0HaPdyxA/j8c+Cddyhge9s2tYuYSNDCyv7LYq0QBGFPcCxEdgaoVIpe+/1qs8LhoPdZKTCZSIDnCtusqLDFga0E7LLEhfE0TbkMJRIqxoKDrxMJVbGbU8/ytfV6DXY7WR0CAWDDBjqHlRCuAF5fn5v6NbvIHafAnTqViudNnUoKxowZNE67nRQina5zt6SOBe84Y9aeal50xp6K6wlCf/O///0PBxxwAA444AAAFJR8wAEH4IYbbsi0ue666/CjH/0IF110EWbPno1gMIg33ngjJ6XpM888g8mTJ+PYY4/FiSeeiCOOOAKPPPJIr8a0YMECvP7663jzzTcxe/ZsHHLIIfjNb36TicHYf//9ce+99+Kuu+7CtGnT8Mwzz+COO+7o9Wdw11134dlnn8Xy5cuxYMECTJ06FVdffTVmzJiRCSA/7bTT8Nvf/hZ33303pk6dit///vf4fw//AVMOPBQ6nQ4V+Z34XHagoqIiE5heUlKCyy67DABw55134swzz8T3v/99zJo1Cxs2bMC//vUv5O/MCFFQUICnn34a//jHPzB9+nT8+c9/xk033dTr++0PdFp3o1P2Evx+P/Ly8uDz+eDm9B6DSKM/ioNvfxt6HfDlzcfDZu6bv2MsRnnR29vpJxYjF6iGBlq8tm6lBd9iUf7Q4TCd09xMixwv4N2zWiQAJEHGrt75HApCLvJMjTQ4GJutB5xOlhUIi0XFRhQW0msW3tkN0+8nF6L8fFXsLj+fFAS/X1ktOMjb5VJWEi6oFwiQi1MoREI+u1tZrQkEg+tx8METUFlpQns7UFICzJqlxlJfT+NOJCiewutVsQsVFXSPX39NdSwKClQ8GhcQjcfp3JISYPbs3MxP2XSWra9jFXBhZJBIJPCPf/wDJ554Yo987qPRKDZv3jwoNQSEoSeZSmNdQxDJdBolbusuVbazSafT8Pv9cLvd0A9xirfdPac9kZ3FFWqQWd9IRVpGF9j7rFQAyixvsVBtitpatcgnk7QoBgK0+AEqy0k6netewDt/2ZliBEEQOsNmozkjnVZWBQ7U5jS1RqNyz2SXS5uNBHCTiTY30mllAeFUsFxJ22BQdTD0ehL2IxESyLk2hs1GCkFtrXJdAjgrVSqT0YmL/XE8mdVKVov2dtqAqa+nsXq9SuBni4zFQn1wutviYrqXVAoZhYXrbXSGuDIJwr5FnS+KZDoNq8mAIte+92UXxWKQ4bRjlQW7WYl6QDxOi3F9vXJFaGujnbdIhBZBzuRiMtF7BgMtvAC1B1QGF6OR3pOK24IgdIVOp4KpWejmWhBsHY3FVLVsg4GsCckkzS2cdpYDsSMR6pcz1TFOJykwrJywi5TJRP0WFJBgb7WqGI9Uii0paXi9KsbC6cwNlGblwuMhBaGyUs2LALW12VQ8WnaNCrOZ+tQ0uq/uKAqiTAjC3o8/kkBbOA4dgFH5Nuj3QT9zUSwGmWCMzAFua99dPqJRUioiEbJK8E5aUxMtevy6vJx+sz+w2UyLocdDblOBgCosxQGagiAIncHVuDlQm1O8Ggy5QcqsLLDlYdQoEvo5eQTHXPB8w7v5eXl0TiBAykQ6Ta5DOh29Nhiob5eLrB/JJDBpEm2sxGIU+0DF9RJwu8kK0dqqlJ6O6PUq61Q2HHwdCql0tpzlKpmkzZyiIko5KwiCkEilsb2NJj6v09JvhQhHGvvmXQ8h6X4MaeHaFZWVpDBwjAS7BMRitBByQLfdriwTnAbR5VIpJXk3jzOisE+xIAj7Huw2yQoEWzHZYsBxETxf5OWRoM91FriNptE8w21bW1UxPE4Kw3NQIEDXy89XygSnsOdjJhP1MXo0MHEiHfN6qV19Pc2FVO9CQ3ExbaLwmDtjd9mZuI4Efx4cpM4KzJQpEichCAIl5tneFsm4QJXuJq5ib0cUi0GGLRX+aN9KXGdXddU0sk5EoyqAG6D3vV5VSbatjRZvLobHgYqcCjIQUHniTSZaSNn6IQjC3g8HZQMqGJvf5/SqnMmJ4yjcblICsrMzlZSoVLTJJO3qc7yExaJcjoqKaL4ZO1YpJe3tlNHObKZ5jauAR6N0fksLzVn770+KBaeYDQbJKsKB41ZrGCUlpBywtbanheY4kNtmo/kxEqF7d7vpnkSpEAQBAJqDcQSiCeh1OowusPdLKYGRiigWg0yZh1airS3hPvWTXdWVUx36fLTQBoPA9u3K/SkapYW8vl75BY8ZQ4tsbS0txCwAWK3KV7qpSV1Pp1MFqCT+QhBGFizQswsTuyRlKw6A2ngwm1WWpWSSBHC9nuIUPB46lk6reIqSEhWLwAX2XC5qz3ER0SjNOWVlZG3ggO6CAnrNaWDjceCLL2i+GjVKWWItFpXRyeWifjkpRV6eCo4uKqLrrlzpx9ix9DdAcxpnZ+Lg8Pz8PWdnkuBrQRB2RySeRL2f4mfL8qyw9mN185GIKBaDzJQyStO1rTWM9nAcHnsnlZO6QXZVV7OZFvtolBa/8eNJUNi+nXbpOMCwuJh23OJxSgFZVUWLfFMTLbRGIy3QNhsJAK2tJEDwwq6Cu9MZxWbfSlYsCP0PC/ucqY2VeIaFWW7DLovptMrolm1lBNT8YDSS1bK0lDYcEgmaA1gpYHcnrk+RSJCgXV1N80A4TO/b7XQ+uwVZrTR3GI00T7hctLPPmZrYDdNup2vrdBQPFo0C48bR9bZsoblr7FhSBrhQndVK1+cK2U6nqtgdiSATN9HRAsGB4jzXWSzpHAWgrwqCKBOCIHQklU5jW2sEmqYhz2ZCgaN3Mt3ehCgWg4zHbsbEEifWNQTxzteNOGPWqF7107Gqa3b6xFSKFATe1UulyLUgkaCdwZIS5XPc3g6sW0d9Wq0kPHAaxeJiWoSbmuh1IkFtmpsj0OvNiEaVWxUXyWJXKr1eCUOMuFQJ+zqcOtVmo++f00l/s6sOJ1Dg2IZoVKVadTpJiAdU6lRWFAAlxIfDZGFIp2nzYN48Zbmsr1e1IZxOZaGMRmmOyM9Xgn9Jidrdr6ykuWT9eqqNE42SQM/W0LFjyQra2KiCoINBlca1qIgUllRKuUVNmaICvzkFbTxOY8/LI+UiHFYumgYDMq5NrIB0ZYEw7GbDUBQEQRD6A03TUNMaQSyZgsmgR4XHBp1kvxHFYig4fmop1jVswEsrd/RasQBUYCHv2lksqpBTfj69p9ORUsAVaIuLVfVWrp7LeeDz82mhDoVIkODsUW++SVW7OV1tKhWD3a6yqXA2mGSSxrJjB7W12ZSQwUHjPh9diwUoQLlpcDsu1icIA4lOpxRgrkNgNqsd/GRSJTXgStG7s9BxTILZTIK70ahqNHBRtOJiZXFwOGhXfscO2kmfOpWU+O3b6Xuk06kd+1Gj6DzaiafvpdVK4+GqzoCqPh2L0bnHHUeKgsuVW8V6+3Zqy+mlo1GKWZgwgfoPheg8nQ7YuJG+s5pGrpbTpinXoW3bqI3XqzI9RSL0vff7qY8pU5T1g5UfthZkF4/rzD3J4+nawrA7C4RsYgiCMNA0BGLwRxPQ6XQY47XDaBjaAnfDBVEshoBvHliJ//fuBvxnfTO+rPVhannenk/qBA4s7LgwZ+/qsfJgt5NwkZ0Okn2WDQa1a8ouE+wTHY8Dp50GfPwx7UaSkBRBeTkt+iUlwOTJKj5Drwe+/JIEE4AEmcJCSmvr85EQ5PEo9yq/X2WnApTFhTPBsMtVtsKRSilBymRSO52soJjNKmYklVIFAc1mlSqSBUTevRX2frhKNKcpLS0loZ0zp1VU0POxcSM9h4EAfTcMBvouNDaqYN9Egp5d9v3PzyfhmnfmW1vphzOreb303LvdKpVqWZkqUjlhAvVhtZLlorGRflh5Ly2lH07F2t5OrkWaBhx+OPVhMND4+LtTVsaF4uj7zdWeAeqztlZtHrDSY7WqOAgOsObMR5EIfV5cWyJb+WCLQjJJ42pspLlhyhQaG39uHQOeu+OetCcLg1ggBEEYbHyROBp3xlWM8tj22dSynSGfxBAw2mvHSTPK8drqWvzq72vwzAVzem0+29PCzMoDZ4XKViyYZJLiMrzeXB/ucBioqyPBpLKS3CDIpSqC2bOB6dNJqXC7lQsDuy00NtI57Oqx337A2rXAmjX0fjpNglkkQn0Gg9R2wgSVb97tJlcK9u1OJOg6HBzqcNC92+20A9veTn1YLPR3JEJ9xeNK6eKdZP5JJukY58dnIZLdMwwGun44rNzB+HNlVxRh8GFrQLZSyNYHtqBxbIDLRc8SxxBVVNDOe2kpuQq1ttKzmF2ozecjIXz6dHo2amvJBWjbNuXyxxYNu50sCpMnkxJdXU3PTCxGz8e2bdSuqIj6ra+n53b0aPrOHHggjSmdpuesulqleI3FqM9Ro3ILvEUi1FdLi7JQciFMjkOoqMiNy8ieF7pSFtrads2SxDEPvIHh8+VaFgB1zGKhz5g/e4DuYU9B0qIcCEL3GMwkAueeey6efPJJ3HHHHfjpT3+aef/ll1/G6aefDm3nDt3SpUvxjW98AwCg0+ngcrlQXV2N4447DldddRXKsoq93HTTTbj55pszr91uN2bMmIHbbrsNRx11VM71X3zxRTzwwANYuXIlUqkUqqur8c1vfhOXXXYZCrpK5baTWCyGOXPmYPXq1Vi5ciVmzpyZOaZpGu655x488sgj2Lp1KwoLC3HppZfi5z//eabN0qVLcfXVV+PLL79EZWUlfvGLX+Dcc88FAEQTKdx4y6/w73+8hi2b1sNus+Gwww7DXXfdhUmTJgEAWltbceONN+LNN9/Etm3bUFRUhNNOOw233nor8vJ6t5k8UhDFYoi4Zv5EvPllPf67sQV//XQ7zjqosk/97WmC6eg21Vm6xWz3KIAEg2yBYsoUUgr0+nqcfvpkVFSo/m02lZnF7QZWr6a/uSKv0UjXmD2bdjL9frJihELUb3s7teUdX1YIOGe8309j9/vpnJIS4JhjaDyaBnz2GcWK+Hz0k5+vrBE8EXMGHIeDBDWdjsY8ahQJlTU1dLy+npQovZ7GEwyS8uNw0H2UlpKwmkzSsVCIBEK2ksRi9ON0UttUio7zjjfHpexNZKcp5YDgnp2bzlifuBAaBzObTPQser3KCseZy5JJenZCIXrfaqX/Ke/gezy0q24wKEW0sJD6LC6mHfSxY2kcoRD97LefsorF4/S9mDULWLCAnr9Nm1TsEO/SW610TnExKekcM+Hz0fU++4yUE5uNjpeW0nkVFfT8h0KkrHi96vPjfisqdhXIOWVrSYn6fqZSu1osu2JPykLHc/e0gdHZMcmiJAj9R7bbIH/X2Qo5kGmPrVYr7rrrLvzwhz9Efn7+btuuXbsWbrcbfr8fK1aswJIlS/DYY49h6dKlmD59eqbd1KlT8e9//xsACeB33303Tj75ZGzfvj0jdP/85z/HXXfdhauuugq33347ysvLsX79ejz88MP405/+hCuuuGK3Y7nuuutQXl6O1atX73LsiiuuwJtvvom7774b06dPR2trK1o5gA3A5s2bcdJJJ+Hiiy/GM888g7fffhsXXHABysrKcMy847ClJYRPln2Isy+4CCd+4wikUin87Gc/w/z58/HVV1/B4XCgtrYWtbW1uPvuuzFlyhRs3boVF198MWpra/HXv/6125//SEQUiyFijNeBy4+dgF//ay1++coXmD4qD5NL3QN2va7cprJ3HTdtop3/QIBeu1wkdJeXK2tGKgXU14dRXNz5dSwWEtZsNuqvsZGuaTaTgMfZZtJpuk5LCwnn6bQKHPd4VIpKq5Um1GBQ1eFwOkl54bSZBgMpGbNmUaaZxkYVcM47sGPGkJLAAacWC70uLVWWi8MOo88iGgVWrACWLaPPw2ik3ehRo5C5b4+H2tbXk0LDc5LdTgI2C5qsRLCSxJYU9uXnzyEWU7vR3I4tM7wrz9mCWNhm4RNQhRFdLvp/ud3UL1uFuKI6B+umUtSer59IqIxE2alGWSjk+gKJhArQt9tVvA5XR2aFjqvBB4M0VqtVZTDiys38OSUSQHNzCC6XORNL4PfnFmErKyMBXdOU4B2P534O7FbncND/xmik91IpGtfEifT8cdByWRndAwu9nQnGrGTzfUajNA6/n94zm6k9WwNHjaJnl79zNpuq/7B9u1K8rVZ6lqqrVUY3/m7G44OTCrU35+7ueE9dmARB6B6cXIGTJvDGYFsbzVGdbT70F/PmzcOGDRtwxx13YMmSJbttW1xcDI/Hg9LSUkycOBGnnnoqDjjgAFxyySX44IMPMu2MRiNKS0sBAKWlpbjlllvw+OOPY926dZg9ezY+/vhj3H777bjvvvtyFIixY8fiuOOOQ3t7+27H8c9//hNvvvkmXnzxRfzzn//MObZmzRo89NBD+OKLLzLWhaqqqpw2Dz/8MKqqqnDPPfcAAPbbbz988MEHuPfe36B65mGIJ9N47Lm/YXyRMxNX8cQTT6C4uBiffvop5s6di2nTpuHFF1/M9Dlu3Dj86le/wve+9z0kk0kYjXuv+L333tkI4OKjxuGjTS34z/pmnP/E//CXiw9Fhcc2YNfrSpCIRkkJ2LqVBBqvl9r7/SQ0RyKkFNhs3Xf98XhI0Pf7VeC2u4PeZLOpzFMd02h2FHI6E346u4/SUlJW2L2J8+5zGl1AuTVxvAawqxA3dixl09m6ldoUFpIiEg6TMtHUpPzkS0qU8Mw76wAtBBs3Kjevykrlf8+WDk4VXFlJY2LXr6YmUpI4A09JCbVjl5kdO+iH79XtJuWpupo+C5uN3HxGjQK++op2zNln3+mk/lmA5XookQgtWhMmqJ39QABoaFDZjMJh1QdbCdjKFAyqlKYc3B+LUf+jR6tCZskkudg1Nal4ly++8GPq1HxUVdHueWsrXWPMGGDSJBX8y8puOk3jCgaVRYyvybFBrNBxMDG75XW1y9eZYNzxvY4F0zrLVpTdlr9vo0cDc+bQ3519H4YyFaooAIIwvGltpbkm22BgNtMPp4bnKvb9jcFgwO23346FCxfi8ssvx6hR3U84Y7PZcPHFF+Oqq65CY2MjijvZkYzFYnj88cfh8Xgygv4zzzwDp9OJSy+9tNN+PRwA1gkNDQ248MIL8fLLL8PO/phZvPbaa6iursbrr7+O448/HpqmYd68eViyZEnGvWrZsmWYN29eznnHzZ+PK6+8CpFECka9HlVeR06wts/nA4Ddumj5fD643e69WqkARLEYUgx6He7/zgE486H/YlNzCN97dDmevXAOyvIGTrkAdhUkWltJSGM3EqawkIS8xkaa0HozcXVUJroznu626Uzoy7audCWccbDtnoQ4t5t87Ds7t7o6dzcb2LWv6mrgoIPoOizs87HOFK7sXWu2MpjNShjmzF9s3QmFKFDW56PXmkaWAJuNBNmxY+kzmT4dmDuXXM+2bSMBnSuvaxoJxAUF9LmxopSthNXVKf95vo+2Njq3vFwtduEwPUfsCsZxMgUFKqCexzt6NMXcbN9OisfYsX7MmqUsJxMn0ljy8+kzMhhIoM8W3ktLu/4fDqRbTk+VgI4xT7tDhHxBELKJxWj+dTg6P+5wKKv3QM0fp59+OmbOnIkbb7wRjz32WI/OnTx5MgBgy5YtGcXi888/h3Nn5cpwOAyXy4Xnn38e7p2L4fr161FdXQ0T+y93E03TcO655+Liiy/GQQcdhC1btuzSZtOmTdi6dSteeOEFPPXUU0ilUrjqqqvwzW9+E++88w4AoL6+HiVcfXNnvwaHB8GAH/FoFONHF8KSVQQvnU7jyiuvxOGHH45p06Z1Orbm5mbceuutuOiii3p0TyMRUSyGmHyHGU9fMAdnPbwMm5tDOP13/8UTP5g9oG5R2cRitOvNee07woWxWlpI8NTrd23Tsb+h9qvu7nX7usvbHSGxqzadKVw9EVhtNrIUcHxAZ2472f1WVVHfhx5K/08ungZ0bVHie7DZcn17Y7HOd+j3pLDxuHi3n93mfD4gmYwjL0/FQVRU5FZT3p2S2BkD5ZYzHJ7vntLTMY/EexSEvRV2Qe5KxuYU0gOd3fCuu+7CMcccg2uuuaZH53GAd3aCmkmTJuHVV18FAAQCATz//PM466yz8O677+Kggw7KnNNTHnjgAQQCAVx//fVdtkmn04jFYnjqqacwceJEAMBjjz2GAw88EGvXrs1YTbLHX++LIhQjv+PRXvsuGaAWL16ML774IsfdKxu/34+TTjoJU6ZMwU033dSrextJiGIxDCj32PD8Dw/BuY9/gg2NQZz54H9x+xnTcerMij2f3Ec4sxHntO8Iu8Bwdd+uFIuhCizbG+mNMNddRQdQ1oju0pcd+u70Re51LTjsMFJuerLDP1iMxOe7p2MeifcoCHs7nOmOLdgdYSvvnjb9+srcuXOxYMECXH/99ZnsSN1hzZo1ACg+gjGbzRg/fnzm9QEHHICXX34Z9913H55++mlMnDgRH3zwARKJRI+sFu+88w6WLVsGS4eF46CDDsKiRYvw5JNPoqysDEajMaNUABRDAQDbtm3DpEmTUFpaioaGBmiahgZ/DE3BGFqamuByu1Gcn7sDd9lll+H111/H+++/36mbWCAQwPHHHw+Xy4WXXnqpx1aYkcgAP4oDw+9+9zuMHTsWVqsVc+bMwccffzzUQ+ozo/LtePHiw3BotReheApXPLcKP33xs4yWPFDo9SpINtnJpTg7j8m0e6Vixw5yj+F0kxaLKpYXjQ7oLQiDREd3rv7qy2IBnM4kPJ7ho0hkMxKf756OeSTeoyDsC3DtHa4N1ZFQiI4Pxtx555134rXXXsOyZcu61T4SieCRRx7B3LlzUVRUtNu2BoMBkZ1m94ULFyIYDOLBBx/stG1Xwdv3338/Vq9ejVWrVmHVqlX4xz/+AQB4/vnn8atf/QoAcPjhhyOZTGLjxo2Z89atWwcAGDNmDADg0EMPxdtvv40GfwyNAZr8Vn/0Pg479NDMOZqm4bLLLsNLL72Ed955Z5cAcIAsFfPnz4fZbMarr74K6z6yQzPiFIvnn38eV199NW688UasWLEC+++/PxYsWIDGxsahHlqfybOb8KfzD8blx4yHTgc890kN5v/mfby9pmHArmmxKBencHjX4xys6/V2PXFlB5aZzSqzUH6+2gUVhJHKSHy+ezrmkXiPgrCvwFbDtrbcxBSd1Z0ZSKZPn45Fixbh/vvv7/R4Y2Mj6uvrsX79ejz33HM4/PDD0dzcjIceeiinXTKZRH19fabtbbfdhq+++gqnnnoqAGDOnDm47rrr8OMf/xjXXXcdli1bhq1bt+Ltt9/GWWedhSeffLLT648ePRrTpk3L/LBVYty4cRlrwrx58zBr1iz84Ac/wMqVK/Hpp5/ihz/8IY477rhM+4svvhgbN23C9T+9Dps3rMM///IUXnnpRVx11VWZay1evBhPP/00nn32Wbhcrsz9sHLESkUoFMJjjz0Gv9+faZPqST72EciIUyzuvfdeXHjhhTjvvPMwZcoUPPzww7Db7fjjH/841EPrF4wGPa6ePwnPnD8Ho/Jt2NEewflP/g8XPfU/rG8IDMg1CwrIZz4apeBazt/f3EwuK8XFXU9cPQksE4SRxkh8vns65pF4j4KwL8HZ6DiGzedThScHMtVsZ9xyyy1IdxHQMWnSJJSXl+PAAw/EnXfeiXnz5uGLL77AlClTctp9+eWXKCsrQ1lZGWbOnIm//OUveOihh3D22Wdn2tx111149tlnsXz5cixYsABTp07F1VdfjRkzZuCcc87p9fj1ej1ee+01FBYWYu7cuTjppJOw33774bnnngMApNIabAVleOCJ57HsP0vxrQVH4pHf/RaPPvooFixYkOnnoYcegs/nw9FHH525l7KyMjz//PMAgBUrVmD58uX4/PPPMX78+Jw2NVw0ay9Fp/U2SmYIiMfjsNvt+Otf/4rTTjst8/4555yD9vZ2vPLKK7ucE4vFEMtaEf1+PyorK9Hc3JzJQDBcCceTeODdTXj8v1uRStO/Sd+7At17JJ3UIxUwIxGwIh03Qgcd9OY4DK4YjK449EY1kWialgnESif0SPhs0JuT6Kx4uKYB6bgRprwI9KYBji4TRizZz9RwYiQ+3z0d80i8x+4wXJ8pYWTTm+eq3GXATUcXo7h8FHTGTgIlekA8Kz7NPAxdR0c62QJxaZ4VhY6+/b/2eD1NQyAQgMvlGvL5KhqNYsuWLaisrNzFbcvv96OwsDCTMnd3jKjg7ebmZqRSqZw0YABQUlKCr7/+utNz7rjjjpzy8cybb77ZaY7j4cZ0ANdOB/5Ro8dnrXqkB0oNNKRh8EShd8aRTpAhS29KQ7dToci9ri5TZZnfTqd00Bl2HZyW0mXaDdjYhb0A9UwNJ0bi893TMY/Ee+wew/OZEkY6PX+utJ3fs/54HE1ZyoQ83gODQQe4TYA5FYXfPzgBZoHAwHik9IR4PI5IJIL3338fyQ5Bt+HOfOW7YEQpFr3h+uuvx9VXX515zRaL+fPnD3uLRTbnA/BHEoglh3bHMJFM4P333sfco+bCZKTsBvV1Ovh8uTUwGH6/tEymQKFzOnumhhMj8fnu6ZhH4j3ujuH+TAkjk94+V8l4DP6WeowudOwzAbwjFb1ON2CeIZ0x3CwWNpsNc+fO7dRi0V1GlGJRWFgIg8GAhobcYOaGhoZMefiOWCyWXVKPAYDJZBpxab+8w2C8iUQCbjNQnu/MfH4FdpU5xuGgDFKJBGWrGF0y+D6gwsiis2dqODESn++ejnkk3uPuGO7PlDAy6e1zFY0aEWrTw2w0wGw07PkEYZ+B41V0Oh30A50zeA/o9XrodLpO5eOePO8jKnjbbDbjwAMPxNtvv515L51O4+2338ahWWnAhMFlOAWWCUJ/MxKf756OeSTeoyAIgjD8GFEWCwC4+uqrcc455+Cggw7CwQcfjPvuuw+hUAjnnXfeUA9tn6anRdQEYSQxEp/vno55JN6jIAiCMLwYcYrFt7/9bTQ1NeGGG25AfX09Zs6ciTfeeGOXgG5haBBBRNibGYnPd0/HPBLvURBGAiMoCaewD9Jfz+eIUywAKqF+2WWXDfUwBEEQBEEQdgv7p4fDYdhstiEejSB0Dmd+6mtc2ohULARBEARBEEYCBoMBHo8HjY2NAAC73T7kGYCE4UE6nUY8Hkc0Gh2y4G1N0xAOh9HY2AiPxwODoW8JBkSxEARBEARBGEA4cyUrF4IAkFAfiURgs9mGXNn0eDxdZljtCaJYCIIgCIIgDCA6nQ5lZWUoLi5GIpEY6uEIw4REIoH3338fc+fOHdLU2CaTqc+WCkYUC0EQBEEQhEHAYDD0mwAnjHwMBgOSySSsVuteU3NnRNWxEARBEARBEARheCKKhSAIgiAIgiAIfUYUC0EQBEEQBEEQ+sw+F2PBBUD8fv8Qj2RkkkgkEA6H4ff79xp/QGFokWdK6G/kmRIGAnmuhP5mpDxTLDN3p4jePqdYBAIBAEBlZeUQj0QQBEEQBEEQRgaBQAB5eXm7baPT9rEa8+l0GrW1tXC5XEOeM3gk4vf7UVlZiZqaGrjd7qEejrAXIM+U0N/IMyUMBPJcCf3NSHmmNE1DIBBAeXn5Hgv57XMWC71ej1GjRg31MEY8brd7WH8JhJGHPFNCfyPPlDAQyHMl9Dcj4Znak6WCkeBtQRAEQRAEQRD6jCgWgiAIgiAIgiD0GVEshB5hsVhw4403wmKxDPVQhL0EeaaE/kaeKWEgkOdK6G/2xmdqnwveFgRBEARBEASh/xGLhSAIgiAIgiAIfUYUC0EQBEEQBEEQ+owoFoIgCIIgCIIg9BlRLIQ9ctNNN0Gn0+X8TJ48eaiHJYww3n//fZxyyikoLy+HTqfDyy+/nHNc0zTccMMNKCsrg81mw7x587B+/fqhGawwItjTM3XuuefuMncdf/zxQzNYYURwxx13YPbs2XC5XCguLsZpp52GtWvX5rSJRqNYvHgxvF4vnE4nzjzzTDQ0NAzRiIXhTneeqaOPPnqXueriiy8eohH3DVEshG4xdepU1NXVZX4++OCDoR6SMMIIhULYf//98bvf/a7T40uWLMH999+Phx9+GMuXL4fD4cCCBQsQjUYHeaTCSGFPzxQAHH/88Tlz15///OdBHKEw0njvvfewePFifPTRR3jrrbeQSCQwf/58hEKhTJurrroKr732Gl544QW89957qK2txRlnnDGEoxaGM915pgDgwgsvzJmrlixZMkQj7hv7XOVtoXcYjUaUlpYO9TCEEcwJJ5yAE044odNjmqbhvvvuwy9+8QuceuqpAICnnnoKJSUlePnll/Gd73xnMIcqjBB290wxFotF5i6h27zxxhs5r5944gkUFxfj008/xdy5c+Hz+fDYY4/h2WefxTHHHAMAePzxx7Hffvvho48+wiGHHDIUwxaGMXt6phi73b5XzFVisRC6xfr161FeXo7q6mosWrQI27ZtG+ohCXsRmzdvRn19PebNm5d5Ly8vD3PmzMGyZcuGcGTCSGfp0qUoLi7GpEmTcMkll6ClpWWohySMIHw+HwCgoKAAAPDpp58ikUjkzFWTJ0/G6NGjZa4SukXHZ4p55plnUFhYiGnTpuH6669HOBweiuH1GbFYCHtkzpw5eOKJJzBp0iTU1dXh5ptvxpFHHokvvvgCLpdrqIcn7AXU19cDAEpKSnLeLykpyRwThJ5y/PHH44wzzkBVVRU2btyIn/3sZzjhhBOwbNkyGAyGoR6eMMxJp9O48sorcfjhh2PatGkAaK4ym83weDw5bWWuErpDZ88UACxcuBBjxoxBeXk5PvvsM/zkJz/B2rVr8be//W0IR9s7RLEQ9ki2q8GMGTMwZ84cjBkzBn/5y19w/vnnD+HIBEEQuibbhW769OmYMWMGxo0bh6VLl+LYY48dwpEJI4HFixfjiy++kJhCod/o6pm66KKLMn9Pnz4dZWVlOPbYY7Fx40aMGzdusIfZJ8QVSugxHo8HEydOxIYNG4Z6KMJeAvuVdsys0tDQsFf4nArDg+rqahQWFsrcJeyRyy67DK+//jreffddjBo1KvN+aWkp4vE42tvbc9rLXCXsia6eqc6YM2cOAIzIuUoUC6HHBINBbNy4EWVlZUM9FGEvoaqqCqWlpXj77bcz7/n9fixfvhyHHnroEI5M2JvYvn07WlpaZO4SukTTNFx22WV46aWX8M4776Cqqirn+IEHHgiTyZQzV61duxbbtm2TuUrolD09U52xatUqABiRc5W4Qgl75JprrsEpp5yCMWPGoLa2FjfeeCMMBgO++93vDvXQhBFEMBjM2X3ZvHkzVq1ahYKCAowePRpXXnklbrvtNkyYMAFVVVX45S9/ifLycpx22mlDN2hhWLO7Z6qgoAA333wzzjzzTJSWlmLjxo247rrrMH78eCxYsGAIRy0MZxYvXoxnn30Wr7zyClwuVyZuIi8vDzabDXl5eTj//PNx9dVXo6CgAG63Gz/60Y9w6KGHSkYooVP29Ext3LgRzz77LE488UR4vV589tlnuOqqqzB37lzMmDFjiEffCzRB2APf/va3tbKyMs1sNmsVFRXat7/9bW3Dhg1DPSxhhPHuu+9qAHb5OeecczRN07R0Oq398pe/1EpKSjSLxaIde+yx2tq1a4d20MKwZnfPVDgc1ubPn68VFRVpJpNJGzNmjHbhhRdq9fX1Qz1sYRjT2fMEQHv88cczbSKRiHbppZdq+fn5mt1u104//XStrq5u6AYtDGv29Ext27ZNmzt3rlZQUKBZLBZt/Pjx2rXXXqv5fL6hHXgv0Wmapg2mIiMIgiAIgiAIwt6HxFgIgiAIgiAIgtBnRLEQBEEQBEEQBKHPiGIhCIIgCIIgCEKfEcVCEARBEARBEIQ+I4qFIAiCIAiCIAh9RhQLQRAEQRAEQRD6jCgWgiAIgiAIgiD0GVEsBEEQBEEQBEHoM6JYCIIgCIIgCILQZ0SxEARBEARBEAShz4hiIQiCIAxLjj76aFx55ZXDpp/+GIdOp4NOp8OqVav22P7cc8/NtH/55ZcHfHyCIAh9RRQLQRCEQSRbWMz+Of7444d6aL0m+57MZjPGjx+PW265Bclksk/9/u1vf8Ott97aT6PsHv/61786/f9k/7z55pu97v/CCy9EXV0dpk2btse2v/3tb1FXV9frawmCIAw2xqEegCAIwr7G8ccfj8cffzznPYvFMqDXjMfjMJvNA9Y/31MsFsM//vEPLF68GCaTCddff32v+ovH4ygoKOjnUe6ZuXPn5gjz06ZNw6WXXopLL700815RUVGv+7fb7SgtLe1W27y8POTl5fX6WoIgCIONWCwEQRAGGYvFgtLS0pyf/Px8AOQuc/nll+O6665DQUEBSktLcdNNN+Wcn06ncccdd6Cqqgo2mw37778//vrXv+a0Ofroo3HZZZfhyiuvRGFhIRYsWIBAIIBFixbB4XCgrKwMv/nNb3LchJ566il4vV7EYrGcvk477TR8//vf79Y9jRkzBpdccgnmzZuHV199tU/j7ejCFIvFcPnll6O4uBhWqxVHHHEEPvnkk5x+QqEQzj77bDidTpSVleGee+7Z7bg7YrPZMv+TVCqFlpYWHHnkkTn/K4PBAADYtm0bFi5ciPz8fBQUFGDRokVoa2vr0fX++te/Yvr06bDZbPB6vZg3bx5CoVCP+hAEQRguiGIhCIIwzHjyySfhcDiwfPlyLFmyBLfccgveeuutzPE77rgDTz31FB5++GF8+eWXuOqqq/C9730P77333i79mM1mfPjhh3j44Ydx9dVX48MPP8Srr76Kt956C//5z3+wYsWKTPuzzjoLqVQqoxAAQGNjI/7+97/jBz/4QY/uwWazIR6P92m8Hbnuuuvw4osv4sknn8SKFSswfvx4LFiwAK2trZk21157Ld577z288sorePPNN7F06dKce+wJK1euBADMmjVrl2MbNmzAgQceiPHjx+Ojjz7CW2+9hQ0bNuDaa6/tdv91dXX47ne/ix/84AdYs2YNli5dijPOOAOapvVqvIIgCEOOJgiCIAwa55xzjmYwGDSHw5Hz86tf/UrTNE076qijtCOOOCLnnNmzZ2s/+clPNE3TtGg0qtntdu2///1vTpvzzz9f++53v5t5fdRRR2kHHHBA5rXf79dMJpP2wgsvZN5rb2/X7Ha7dsUVV2Teu+SSS7QTTjgh8/qee+7RqqurtXQ6vdt7OvXUUzVN07R0Oq299dZbmsVi0a655ppej5ff47EFg0HNZDJpzzzzTOZ4PB7XysvLtSVLlmiapmmBQEAzm83aX/7yl0yblpYWzWaz5dxjd7n55pu1ysrKTo8dd9xx2g033JDz3l//+letqqqqy/6y70fTNO3TTz/VAGhbtmzZ7TgAaC+99FK3xy0IgjBUSIyFIAjCIPONb3wDDz30UM572fEEM2bMyDlWVlaGxsZGALRTHg6Hcdxxx+W0icfjOOCAA3LeO/DAAzN/b9q0CYlEAgcffHDmvby8PEyaNCnnnAsvvBCzZ8/Gjh07UFFRgSeeeCITnL07Xn/9dTidTiQSCaTTaSxcuBA33XRTr8fbkY0bNyKRSODwww/PvGcymXDwwQdjzZo1mTbxeBxz5szJtCkoKNjlHrvLihUrOrVWbN26FW+99RY++OCDHFerVCqFysrKbve///7749hjj8X06dOxYMECzJ8/H9/85jczbnGCIAgjDVEsBEEQBhmHw4Hx48d3edxkMuW81ul0SKfTAIBgMAgA+Pvf/46Kioqcdh0DwB0OR4/HdsABB2D//ffHU089hfnz5+PLL7/E3//+9z2ex8qS2WxGeXk5jEbjoIx3IFmxYgUuuOCCXd5fvXo1CgoKsHz58l2O2Wy2bvdvMBjw1ltv4b///S/efPNNPPDAA/j5z3+O5cuXo6qqqk9jFwRBGApEsRAEQRhBTJkyBRaLBdu2bcNRRx3V7fOqq6thMpnwySefYPTo0QAAn8+HdevWYe7cuTltL7jgAtx3333YsWMH5s2b161d+K6Upd6OtyPjxo3LxF+MGTMGAJBIJPDJJ59kArzHjRsHk8mE5cuXZ+6xra0N69at6/G1m5ubUVNT06nFwmQyIRAIoLy8HHa7vdf3BJDSePjhh+Pwww/HDTfcgDFjxuCll17C1Vdf3ad+BUEQhgJRLARBEAaZWCyG+vr6nPeMRiMKCwv3eK7L5cI111yDq666Cul0GkcccQR8Ph8+/PBDuN1unHPOOV2ed8455+Daa69FQUEBiouLceONN0Kv1+/i5rRw4UJcc801+MMf/oCnnnqq9zfah/F2xOFw4JJLLsmMf/To0ViyZAnC4TDOP/98AIDT6cT555+Pa6+9Fl6vF8XFxfj5z38Ovb7neUo44LszxWLOnDlwu904++yz8ctf/hIOhwMbNmzAG2+8gfvuu6/b11i+fDnefvttzJ8/H8XFxVi+fDmampqw33779Xi8giAIwwFRLARBEAaZN954A2VlZTnvTZo0CV9//XW3zr/11ltRVFSEO+64A5s2bYLH48GsWbPws5/9bLfn3Xvvvbj44otx8sknw+1247rrrkNNTQ2sVmtOu7y8PJx55pn4+9//jtNOO61H99af4+3InXfeiXQ6je9///sIBAI46KCD8K9//SsnJuHXv/41gsEgTjnlFLhcLvz4xz+Gz+fLHH/iiSdw3nnn7THz0sqVK1FSUoLy8vJdjhUUFOAf//gHfvKTn2Du3LnQNA0TJkzotpLEuN1uvP/++7jvvvvg9/sxZswY3HPPPTjhhBN61I8gCMJwQaftaXYVBEEQ9kpCoRAqKipwzz33ZHb9mWOPPRZTp07F/fffP0SjGxhuvPFGvPfee1i6dOmgX/voo4/GzJkze2TVAMhd6qWXXuoXJU8QBGEgkToWgiAI+wgrV67En//8Z2zcuBErVqzAokWLAACnnnpqpk1bWxteeuklLF26FIsXLx6qoQ4Y//znP7FkyZIhu/6DDz4Ip9OJzz//fI9tL774YjidzkEYlSAIQv8gFgtBEIR9hJUrV+KCCy7A2rVrYTabceCBB+Lee+/F9OnTM23Gjh2LtrY2/PKXv8Q111wzhKPd+9ixYwcikQgAYPTo0TCbzbtt39jYCL/fD4BSDg+3rFmCIAgdEcVCEARBEARBEIQ+I65QgiAIgiAIgiD0GVEsBEEQBEEQBEHoM6JYCIIgCIIgCILQZ0SxEARBEARBEAShz4hiIQiCIAiCIAhCnxHFQhAEQRAEQRCEPiOKhSAIgiAIgiAIfUYUC0EQBEEQBEEQ+owoFoIgCIIgCIIg9BlRLARBEARBEARB6DOiWAiCIAiCIAiC0Gf+P1rKVLo7l6BKAAAAAElFTkSuQmCC",
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",
       "text/plain": [
        "<Figure size 800x400 with 1 Axes>"
       ]
@@ -762,7 +762,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 900x400 with 1 Axes>"
       ]
@@ -837,7 +837,7 @@
        "      <th>Tp</th>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>index</th>\n",
+       "      <th>date</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
@@ -905,7 +905,7 @@
       ],
       "text/plain": [
        "                          Hm0         Tp\n",
-       "index                                   \n",
+       "date                                    \n",
        "1996-01-01 00:00:00  4.819627  16.666667\n",
        "1996-01-01 01:00:00  5.004158  16.666667\n",
        "1996-01-01 02:00:00  5.091169  16.666667\n",
@@ -997,51 +997,51 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>7.529565</td>\n",
-       "      <td>1.595490</td>\n",
-       "      <td>0.182459</td>\n",
+       "      <td>6.746905</td>\n",
+       "      <td>1.523609</td>\n",
+       "      <td>0.092796</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>12.115343</td>\n",
-       "      <td>2.669366</td>\n",
-       "      <td>0.219278</td>\n",
+       "      <td>14.522477</td>\n",
+       "      <td>3.910731</td>\n",
+       "      <td>0.134162</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>16.567481</td>\n",
-       "      <td>2.636207</td>\n",
-       "      <td>0.073010</td>\n",
+       "      <td>10.760460</td>\n",
+       "      <td>2.055257</td>\n",
+       "      <td>0.179867</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>10.216278</td>\n",
-       "      <td>1.743338</td>\n",
-       "      <td>0.160776</td>\n",
+       "      <td>14.970050</td>\n",
+       "      <td>1.998624</td>\n",
+       "      <td>0.134551</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>13.455188</td>\n",
-       "      <td>4.738885</td>\n",
-       "      <td>0.041351</td>\n",
+       "      <td>8.404868</td>\n",
+       "      <td>1.898824</td>\n",
+       "      <td>0.211971</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td>8.692400</td>\n",
-       "      <td>2.779776</td>\n",
-       "      <td>0.171362</td>\n",
+       "      <td>12.500668</td>\n",
+       "      <td>2.700447</td>\n",
+       "      <td>0.122227</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
-       "      <td>19.900045</td>\n",
-       "      <td>2.707808</td>\n",
-       "      <td>0.018114</td>\n",
+       "      <td>19.891189</td>\n",
+       "      <td>2.952800</td>\n",
+       "      <td>0.018382</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
-       "      <td>14.290462</td>\n",
-       "      <td>2.808907</td>\n",
-       "      <td>0.133650</td>\n",
+       "      <td>9.426510</td>\n",
+       "      <td>3.342735</td>\n",
+       "      <td>0.106045</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1049,14 +1049,14 @@
       ],
       "text/plain": [
        "          Tp       Hm0   weights\n",
-       "0   7.529565  1.595490  0.182459\n",
-       "1  12.115343  2.669366  0.219278\n",
-       "2  16.567481  2.636207  0.073010\n",
-       "3  10.216278  1.743338  0.160776\n",
-       "4  13.455188  4.738885  0.041351\n",
-       "5   8.692400  2.779776  0.171362\n",
-       "6  19.900045  2.707808  0.018114\n",
-       "7  14.290462  2.808907  0.133650"
+       "0   6.746905  1.523609  0.092796\n",
+       "1  14.522477  3.910731  0.134162\n",
+       "2  10.760460  2.055257  0.179867\n",
+       "3  14.970050  1.998624  0.134551\n",
+       "4   8.404868  1.898824  0.211971\n",
+       "5  12.500668  2.700447  0.122227\n",
+       "6  19.891189  2.952800  0.018382\n",
+       "7   9.426510  3.342735  0.106045"
       ]
      },
      "execution_count": 11,
@@ -1103,7 +1103,7 @@
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1124,7 +1124,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "work",
    "language": "python",
    "name": "python3"
   },
@@ -1138,12 +1138,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.4"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "15fd306e44580d8cf431083454c399b84f9cc4f7f2c761501397671836835f49"
-   }
+   "version": "3.11.10"
   }
  },
  "nbformat": 4,
diff --git a/examples/extreme_response_MLER_example.ipynb b/examples/extreme_response_MLER_example.ipynb
index 3433d0f72..db3655b36 100644
--- a/examples/extreme_response_MLER_example.ipynb
+++ b/examples/extreme_response_MLER_example.ipynb
@@ -4,13 +4,13 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# MLER example\n",
-    "Extreme conditions modeling consists of identifying the expected extreme (e.g., 100-year) response of some quantity of interest, such as WEC motions or mooring loads. \n",
+    "# Extreme Conditions Modeling - MLER Approach\n",
+    "Extreme conditions modeling consists of identifying the expected extreme (e.g., 100 yr) response of some quantity of interest, such as WEC motions or mooring loads. \n",
     "Three different tools for estimating extreme conditions were adapted from [WDRT](https://github.com/WEC-Sim/WDRT): full sea state approach, contour approach, and MLER design wave.\n",
     "This noteboook presents the MLER design wave. \n",
     "\n",
     "This example notebook shows users how to utilze the most likely extreme response (MLER) method.\n",
-    "This method is an alternative to running long (e.g., 3-hour) simulations for each sea state in which we wish to estimate the short-term extreme response.\n",
+    "This method is an alternative to running long (e.g., 3 hr) simulations for each sea state in which we wish to estimate the short-term extreme response.\n",
     "To accomplish this, a given RAO is combined with a wave spectrum corresponding to certain extreme sea states.\n",
     "MLER then generates the resulting wave profile that would cause the largest response for that degree of freedom.\n",
     "See full explanation and derivation of the MLER method in \n",
@@ -96,7 +96,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -109,7 +109,7 @@
     "Hs = 9.0  # significant wave height\n",
     "Tp = 15.1  # time period of waves\n",
     "pm = resource.pierson_moskowitz_spectrum(wave_freq, Tp, Hs)\n",
-    "pm.plot(xlabel=\"frequency [Hz]\", ylabel=\"response [m^2/Hz]\")"
+    "pm.plot(xlabel=\"frequency [Hz]\", ylabel=\"response [m^2/Hz]\", logx=True)"
    ]
   },
   {
@@ -121,7 +121,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -130,13 +130,13 @@
        "<Axes: xlabel='Frequency [Hz]', ylabel='[rad]'>"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -146,7 +146,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -162,8 +162,9 @@
     "    y=\"WaveSpectrum\",\n",
     "    ylabel=\"Conditioned wave spectrum [m^2-s]\",\n",
     "    xlabel=\"Frequency [Hz]\",\n",
+    "    logx=True\n",
     ")\n",
-    "mler_data.plot(y=\"Phase\", ylabel=\"[rad]\", xlabel=\"Frequency [Hz]\")"
+    "mler_data.plot(y=\"Phase\", ylabel=\"[rad]\", xlabel=\"Frequency [Hz]\", logx=True)"
    ]
   },
   {
@@ -181,7 +182,16 @@
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\mcve343\\MHKiT-Python\\mhkit\\wave\\resource.py:1185: RuntimeWarning: invalid value encountered in divide\n",
+      "  yi = xi * xi / np.power(1.0 - np.exp(-np.power(xi, 2.4908)), 0.4015)\n"
+     ]
+    }
+   ],
    "source": [
     "# generate parameters dict\n",
     "params = (\n",
@@ -233,7 +243,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -250,7 +260,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "mhkit_release",
+   "display_name": "work",
    "language": "python",
    "name": "python3"
   },
@@ -264,7 +274,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.2"
+   "version": "3.11.10"
   }
  },
  "nbformat": 4,
diff --git a/examples/extreme_response_contour_example.ipynb b/examples/extreme_response_contour_example.ipynb
index 0ee20f4c9..5591e6400 100644
--- a/examples/extreme_response_contour_example.ipynb
+++ b/examples/extreme_response_contour_example.ipynb
@@ -6,13 +6,13 @@
    "source": [
     "# Extreme Conditions Modeling - Contour Approach\n",
     "\n",
-    "Extreme conditions modeling consists of identifying the expected extreme (e.g. 100-year) response of some quantity of interest, such as WEC motions or mooring loads. \n",
+    "Extreme conditions modeling consists of identifying the expected extreme (e.g. 100 yr) response of some quantity of interest, such as WEC motions or mooring loads. \n",
     "Three different methods of estimating extreme conditions were adapted from [WDRT](https://github.com/WEC-Sim/WDRT): full sea state approach, contour approach, and MLER design wave. \n",
     "This noteboook presents the contour approach. \n",
     "\n",
     "The contour approach consists of the following steps: \n",
     "1. Sample the environmental contour for the return period of interest at N points near the maximum $H_s$.\n",
-    "2. For each sample $(H_{s}, T_{e})_i$ calculate the short-term (e.g. 3-hours) extreme for the quantity of interest (e.g. WEC motions or mooring tension).\n",
+    "2. For each sample $(H_{s}, T_{e})_i$ calculate the short-term (e.g. 3 hr) extreme for the quantity of interest (e.g. WEC motions or mooring tension).\n",
     "3. Select the sea state with the highest short-term expected value for the quantity of interest as the design sea state, and some metric (e.g. 95th percentile) of the distribution as the extreme/design response. \n",
     "\n",
     "**NOTE:** Prior to running this example it is recommended to become familiar with `environmental_contours_example.ipynb` and `short_term_extremes_example.ipynb` since some code blocks are adapted from those examples and used here without the additional description. \n",
@@ -99,7 +99,7 @@
    "metadata": {},
    "source": [
     "## 1. Sampling\n",
-    "The first step is to create the environmental contour for the return period of interest, which is 100-years in this case,\n",
+    "The first step is to create the environmental contour for the return period of interest, which is 100 years in this case,\n",
     "using the `wave.contours.environmental_contours`. See  `environmental_contours_example.ipynb` for more details on using this function. \n",
     "\n",
     "Next we choose 5 sample sea states along this contour. We choose 5 equally spaced energy period values, between 15-22 seconds, to sample the contour. We then obtain the significant wave height for each sample using the `wave.contours.samples_contour` function."
@@ -131,22 +131,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x1fdc554ff50>"
+       "<matplotlib.legend.Legend at 0x2182a63c090>"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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qtu+BBx7A7NmzkZ2djXPOOQdqtRrr16/Hxo0b8dBDD2HYsGEIhUJ4/vnncfrpp2P58uVYuHBhp+bh+uuvx/PPP48LLrgA99xzD+x2O1atWoUjjjgCI0aMwB133IG//vWvGDp0KCZMmIA33ngD+fn5eOedd9p9jZycHHg8HixZsgTjx4+H2WxGXl4ezjjjDFx55ZV4+eWXYbVacffddyMzM7OpCtfMmTNRXV2NJ554Aueccw6++uorfPnll80MNIlEcmigKAqK63xYubMWK3fVYsXOWlQ3BJodk2iJb9dY2szMnhCxZ9FogL15eH2VRIsBx41MwXEjydjwhyJYt7sW73yzCg3GVKh/+AFp7pq2B1AUoKSEDKg+fq8SSXcysBsBHCL8+uuvmDhxIiZOnAgAuPXWWzFx4kQ88MADTcfceeeduOGGG3DVVVdhypQp8Hg8+Oqrr5p6WACUcDxy5EiccMIJmDVrFo455hi88sorB7y+3W7H2WefDYvF0mSoMKeccgr++9//4ptvvsGUKVNw1FFH4ZlnnsHgwYMBAOPHj8f8+fPx+OOP47DDDsM777yDRx99tFPzkJiYiO+++w4ejwfHHnssJk2ahFdffbXJe3HjjTfi1ltvxW233YaxY8fiq6++wmeffdasItSBmDZtGq6++mqcf/75SE5OxhNPPAEAeOONNzBp0iTMnj0bU6dOhaIo+OKLL5quPWrUKLz44ot44YUXMH78ePz888+4/fbbO3WfEomk/1Hh8uOjNXtw2wfrcczj3+PYJ5fi7o834NP8MlQ3BKDXqDFpcDz+PGMIXv7jJPzjpZsoRKitcCaVCsjKapbsLOk5jDoNJg+Ox0mZCl774+F49eT2GXTrf94MX/DAlbgkkoGCSmm1DebAxe12w263w+Vy7bNa7Pf7UVhYiNzc3GYKt0QQGwoV26DuhBNOwJgxY/Dcc+1x3ku6wkB7T0OhEL744gvMmjWrQ6V5JZK26AvvVCAcwZqievywvRpLt1VjW2VDs/1atQoTshyYNjQRRw1NxOHZ8fsmVXNVKKD1ZGcZw39QafZeLV8OHHfcAc+54MJHkD90AmbkJeOUMWk4YVQKHGZZoENC9IX/Ve1hf7pzS/p+nI+kT1NfX4+lS5di6dKlzcrDSiQSyaFGSZ0PS7dV4Yft1Vixs7ZZszmVChiXacfUoUmYNjQRk3PiDxxq28vJzpL9cIDyuYpKBXdiKsrHTYbfGcQ3myvxzeZK6DQqzByRgrMmZuL4kSm9U6FLIulBpGEh6RITJ05EfX09Hn/8cYwYMaK3xZFIJJKDRjSq4LdSF77dXInFmyv38UokWQw4dngyjh2RjOnDkhDfzn4MzeiDyc4SHLB8rgqA/eUXsPSsE7GlvAFfbarAN5sqsLWiAYv3vi9WgxazxqbjzImZODI3AWp1H6viJZF0AmlYSLpEUVFRb4sgkUgkBw1/KIKVO2vxzeZKLNlSiaqYpGuNWoVJg+Mxc0Qyjh2ejFFptu5RFvtBsvMhSTs8SioAozNsGJ1hw60nDcf2ygZ8sq4Un+aXodTZiPd/LcH7v5Yg3W7EWRMzccGUbGQntt6HQyLpD0jDQiKRSCSS/eAPRbB0WzX+t6EcS7ZUNgtxitNrMHNECk4anYrjRqTAbu67cdKSHqCDHqXhqVbc+buRuP3kEfilqA6f5Jfiv7+Vo9zlx4tLd+LFpTsxPS8JFx+ZjRNGpUKnkTV2JP0LaVhIJBKJRNICfyiCZdvJmPh2cyW8McZEms2IE0en4KTRaThqSAIMWhmWdEjTCY+SWq3CkUMSceSQRPz19DH4bmsV/vVzMX7cUdP0lWw14PzJWTh/Slab3cQlkr6GNCwkEolEIgFVclq2vQb/+60M326pgicgyoRm2I04bVw6Zo1Nx4QsR9/rai3ptxh1GswaS+9Wca0P//qlGP/+tQTVDQH84/sCvLC0ACeMTMWfpufiyNwE+e5J+jTSsJBIJBLJIUskqmDVrlp8vLYU32yqQEOMMZFuN+K0semYNS4dE6UxITkIZCeacdfvRuKWE4fj2y2VeHd1MX4qqMG3Wyrx7ZZKjM2040/TczFrbLoMk5L0SaRhIZFIJJKBQyQC1Q8/IHPZMqji4qjXQCvx7gVVDfhobSk+WVeKcpe/aXuazYhZY9Nx2l5jQlbqkfQGeq26yYuxs9qD//upEB+t2YMNpS7c9F4+HvtyKy6dloMLjsiG3STzeiR9B2lYSCQSiWRg8PHHwE03QbtnDyYDwPz5VKHn2WeBOXNQ6wng8/Vl+HhdKX7b42o6zWbUYvb4DJw1MROTsuOlMSHpUwxNtuCRs8bi9pNH4J1Vu/Hmyt0od/nx6Jdb8dySHbhkWg7+dEwuEi2G3hZVIpGGxUBg5syZmDBhAhYsWNDborQLlUqF//znPzjzzDN7WxSJRDJQ4C7VLZqVKaWlwDnn4KXrHsN862EIR2m/Vk2NyuYcLhuVSfoHCXF63HBCHq6cMQSfrS/D//1YiG2VDXhp6U4sWl6EP04djCunD0GyVRoYkt5DBuhJ+jwPPvggJkyY0NtiSCSSvkokQr0EWumArFIUKIqCM998EtFwGOMG2fHg6aOx+i8n4LW5kzFrbLo0KiT9CqNOg/MmZ+Grm6fj1UsmY2ymHY2hCF5ZtgvHPP4d/vb5ZlS6/QceSCLpAaTHoocIBIBoFFCrAYNcPJBIJJKe48cfmzcoa4EaQEZDDZYdpcWgOcccPLkkkh5EpVLhpNGpOHFUCpZuq8azS3Ygv8SJ15cX4u3Vu3Hxkdm4/rhhMkRKclCRHotuxu8HysqAoiKgsJC+l5XR9p4kHA7j+uuvh91uR1JSEu6//34oMat39fX1uOSSSxAfHw+z2YxTTz0VO3bsaNrfmldgwYIFyMnJAQAsW7YMOp0OFRUVzY65+eabMX369Dbl2rFjB2bMmAGj0YjRo0dj8eLF+xxz1113Yfjw4TCbzRgyZAjuv/9+hEIhAMCiRYswb948rF+/HiqVCiqVCosWLQIAzJ8/H2PHjkVcXByysrJw7bXXwuPxdGTaJBLJAKB86652HTco4DrwQRJJP0OlUuG4kSn4z7XT8NblR2DS4HgEw1G8sbwIxz65FM8v2QFfMHzggSSSbkAaFt2I3w+UlgL19eSlsNvpe309be9J4+LNN9+EVqvFzz//jGeffRbz58/Ha6+91rT/0ksvxa+//orPPvsMK1euhKIomDVrVpMCfyBmzJiBIUOG4O23327aFgqF8M477+Dyyy9v9ZxoNIo5c+ZAr9dj9erVWLhwIe666659jrNarVi0aBE2b96MZ599Fq+++iqeeeYZAMD555+P2267DWPGjEF5eTnKy8tx/vnnAwDUajWee+45bNq0CW+++Sa+++473Hnnne2eM4lE0n/xhyL4aM0enP3SCtyyrLJ9J6Wn96xQEkkvolKpMGN4Mj68eireuvwIjMmwwRMI4+nF23Hsk0vx9qrdCEWivS2mZIDTpwyLZcuW4fTTT0dGRgZUKhU++eSTpn2hUAh33XVX0wp1RkYGLrnkEpSVlfWewC2oqyPjIT4e0OsBlYq+x8fT9rq6nrt2VlYWnnnmGYwYMQIXX3wxbrjhhiblfMeOHfjss8/w2muvYfr06Rg/fjzeeecdlJaWNpvjA3HFFVc0eQsA4PPPP4ff78d5553X6vHffvsttm7dirfeegvjx4/HjBkz8Mgjj+xz3H333Ydp06YhJycHp59+Om6//XZ88MEHAACTyQSLxQKtVou0tDSkpaXBZDIBIG/Jcccdh5ycHBx//PF46KGHms6TSCQDk3JXI578eiuOfuw73Pbv9Vizux5rsg9DXXwKlLb6TKhUQFYWsB/vqkQyUGAD4/Prj8GzF0xAVoIJ1Q0B3PfJRpz8zDJ8saG8WUSDRNKd9CnDwuv1Yvz48XjhhRf22efz+bB27Vrcf//9WLt2LT7++GNs27YNv//973tB0n0JBICGBiAurvX9cXG0PxDomesfddRRzZo3TZ06FTt27EAkEsGWLVug1Wpx5JFHNu1PTEzEiBEjsGXLlnZf49JLL0VBQQF++eUXABSmdN555yGujZvesmULsrKykJGR0Uyulrz//vs4+uijkZaWBovFgvvuuw/FxcUHlOfbb7/FCSecgMzMTFitVvzxj39EbW0tfD5fu+9JIpH0fRRFwepdtbj2nTU45vHv8cL3O1HrDSLdbsTtJw/H8r+chITXXoIKICMiFv59wYJW+1lIJAMVtVqFMyZkYsmtM/Hg6aORGKdHYY0X176zFhe+ugpbK9y9LaJkANKnkrdPPfVUnHrqqa3us9vt+8Tn/+Mf/8ARRxyB4uJiZGdnHwwR2yQapcIkujb61Oh0gM9Hx/VF1Gr1PisYLcOkUlJSMHv2bLzzzjs47LDD8OWXX2Lp0qVduu7KlStx8cUXY968eTjllFNgt9vx3nvv4emnn97veUVFRZg9ezauueYaPPzww0hISMBPP/2EK664AsFgEGazuUtySSSS3qcxGMGn+aVYtKIIWysamrYfmZuAS6fl4KTRqdBy9+E5c4APP6TqULGJ3IMGkVExZ87BFV4i6SPotWpcenQuzpmchVeW7cLLP+zEql11mPXsj/jjUYNxy0nD4TDre1tMyQChTxkWHcXlckGlUsHhcPS2KFCraTEsFKLwp5aEQrRf3UM+otWrVzf7fdWqVcjLy4NGo8GoUaMQDoexevVqTJs2DQBQW1uLbdu2YfTo0QCA5ORkVFRUQFGUJs9Hfn7+Pte54oorcNFFF2HIkCEYOnQojj766DZlGjVqFEpKSlBeXo70vbHNq1atanbMihUrMHjwYNx7771N23bv3t3sGL1ej0gk0mzbmjVrEI1G8fTTT0O9d1JlGJREMjAoczbizRVFeO+XErgaaYHDqFPjrImDMHfaYIxMs7V+4pw5wBlnIPz998j/8ktMOPVUaNvovC2RHGpYDFrcetJwnDd5EB7+3xZ8ubECb67cjc/Wl+GOU0bi/ClZ0KhVtEr6449AeTnlJU2fLv+GJO2m3xoWfr8fd911Fy688ELYbG18yAAIBAIIxMQfud3k+guFQvusyIdCISiKgmg0imgHXQs6HYU71ddTTkVLGhpou07XM16L4uJi3HLLLbjqqquwdu1aPP/883jyyScRjUYxdOhQ/P73v8eVV16Jl156CVarFffccw8yMzNx+umnIxqNYsaMGaiursbjjz+Os88+G19//TW+/PJL2Gy2ZnNx8sknw2q14uGHH8a8efP2O0/HH388hg8fjksuuQRPPPEE3G53kwHBczx06FAUFxfj3XffxZQpU/DFF1/gP//5T9MxAJCdnY3CwkKsXbsWgwYNgtVqxZAhQxAKhfDcc89h9uzZWL58ORYuXNhs7IFKNBqFoigIhULQDIB/9vx32N5CApKBy6YyN/5veRG+2FiJyN5GdlnxJvzhyCycfXgm7CZyCR/oXQlNm4ZSrxejp02DEo32XVexpF8xUP5XpVp0eO78cVgxORN//99WFFR78Zf/bMDbq4rwnH4Xhj58H1SlpU3HK5mZiMyfD+Wss3pR6oFJf3mnOiKfSumjGTz7684cCoVw9tlnY8+ePVi6dOl+DYsHH3wQ8+bN22f7u+++u0+4DCcIZ2VlQd+a2+EAUKlZFQIBFcxmBTodeSp8PhUMBgUZGQqMxg4Pe0Bmz56NkSNHIhqN4sMPP4RGo8Hll1+O++67r8n74HQ6cffdd+PLL79EKBTCtGnT8Pjjj2Po0KFN47z++uuYP38+nE4nTj/9dAwbNgxvvvkmfvvtt2bXe+SRRzB//nxs3LgRaWlp+5WtoKAAN9xwA9auXYvs7Gw89thjOOecc/D222/jtNNOAwA88MADeOeddxAMBnHSSSdhypQpeOyxx5o8F4FAAFdddRV++OEHuFwuvPDCC7jooovw4osv4vnnn4fL5cK0adNwzjnn4JprrkFRURHsdnt3TnGfIhgMoqSkBBUVFQiHZQlBSf8mqgBbnCp8X6bCDrdw6ebZopiZoWC0Q4G6jZxsiUTSNSJR4MdKFb4qUWPG5pV46ZNHoAIQ+yfHSuIvd92F8lbyJCUDH5/Ph4suuggul2u/OjfQDw2LUCiE8847D7t27cJ3332HxMTE/Y7TmsciKysLNTU1+0yO3+9HSUkJcnJyYOykBcDVnxoayJuo0QBWK5CQgB4xKg42iqLg0ksvhdPpxKefftrb4hyS+P1+FBUVISsrq9PvaV8iFAph8eLFOOmkk6BrK0lJMuAIhCL4dH05Xl+xGzurvQAAjVqF0w5Lw+VHD8aYjP1/eO0P+U5JeoKB/F7VunwwjBgOe11Vq1V9FJUKyMxEeMcOGRbVjfSXd8rtdiMpKaldhkW/CoVio2LHjh34/vvvD2hUAIDBYIChldbXOp1un4cYiUSgUqmgVqub4vY7itlMXwOx87bL5cL69evx4Ycf4pNPPun0HEm6hlqthkqlavUd7s8MtPuRtI7TF8Q/V+7GmyuLUOMJAqDY74uOzMal03KQ4TB127XkOyXpCQbie5W2cR1QV9XmfpWiAHv2QLdqFTBz5sET7BChr79THZGtTxkWHo8HBQUFTb8XFhYiPz8fCQkJSE9PxznnnIO1a9fiv//9LyKRSFMX6ISEhE6FLvUkA8WYiOWMM87Azz//jMsuuwwnnXRSb4sjkUj6EVVuP179cRfeWV0MX5CKMWTYjbjs6Fycf0QWbMa++6EqkQx4ysu79zjJIUufMix+/fVXHHfccU2/33rrrQCAuXPn4sEHH8Rnn30GAJgwYUKz877//nvMlBZ0j7N06VJEo9GmBHiJRCI5EMW1Pry8bCf+/eseBPd2/R2VbsPVxw7BrLHp0Gmk51Mi6XXa2ZXe7UhC54MUJYcCfcqwmDlz5n67QfbRdBCJRCKRtGB7ZQNeWroTn60va6rwNGlwPK4/bhhmjkhu1tBTIpH0MtOnU8+X0lKgFV0rCqDCmoQzf4nisdxKHD8y9eDLKOkX9CnDQiKRSCT9m/UlTrzwfQG+2VzZtG3G8GRcN3MojshNkAaFRNIX0WiAZ58FzjmHutXHGhcqFVQAXplzI6p8YVy+6FdceEQW7jttNOIMUo2UNEe+ERKJRCLpMmt212PBt9vx444aAKSb/G5MGq6dOQxjBw3c8s8SyYBhP93rVQsW4O7Tz4Dm6234v58K8a+fS7C8oBbPnD8ekwYn9J7Mkj6HNCwkEolE0mlaGhQatQpnTsjENTOHYFiKtZelk0gkHWJv9/rWOm8bAdw/ezROGJWCO/79G4rrfDjv5VW47eThuHrGUKhlwxkJpGEhkUgkkk6wZnc9nl2yA8u2VwMAtGoVzpk0CNcdNwxZCeYDnC2RSPosGs1+S8pOG5qEL2+ejvv+sxGfrS/DE19tw6pddZh/3ngkWQZgSUxJh5CGhUQikUjajTQoJBKJzajDsxdMwNHDEvHAp5uwbHs1Zj37I567cCKOGnLgHmOSgYs0LCQ9Bnfo/uSTT3pbFIlE0kXWFdfjmW+bGxRnH04GRXaiNCgkkkMNlUqF86dkY0JWPK57dy0Kqjy46NVVuOmE4bj++GHQyNCoQxJpWEgkEomkTbZVNODJr7fh2y1U5UmjVuEcaVBIJJK9jEiz4rPrj8ZfP92Ef6/Zg2e+3Y5fd9fh+QsnwmHuW82LJT2PNCx6gkik1cQniUQi6S8U1/rwzLfb8Ul+KRQFUKuAsw8fhBuOz5MGhUQiaYZZr8WT547H1KGJuPc/G/Hjjhqc/o+f8MofJ2NUumypdyghW552Nx9/DOTkAMcdB1x0EX3PyaHtPciHH36IsWPHwmQyITExESeeeCK8Xi9++eUXnHTSSUhKSoLdbsexxx6LtWvXNjtXpVLh5ZdfxuzZs2E2mzFq1CisXLkSBQUFmDlzJuLi4jBt2jTs3Lmz6Zx58+ZhwoQJePnll5GVlQWz2YzzzjsPLperTRmj0SgeffRR5ObmwmQyYfz48fjwww+b9tfX1+Piiy9GcnIyTCYT8vLy8MYbb3T/ZEkkkjapdPtx3ycbcPzTS/GfdWRUnDY2Hd/cciyePHe8NCokEkmbzDl8ED6+dhqyEkwoqWvEnBdX4PP1Zb0tluQgIg2L7uTjj6m5TGz9Z4A6WZ5zTo8ZF+Xl5bjwwgtx+eWXY8uWLVi6dCnmzJkDRVHQ0NCAuXPn4qeffsKqVauQl5eHWbNmoaGhodkYf//733HJJZcgPz8fI0eOxEUXXYQ///nPuOeee/Drr79CURRcf/31zc4pKCjABx98gM8//xxfffUV1q1bh2uvvbZNOR999FG89dZbWLhwITZt2oRbbrkFf/jDH/DDDz8AAO6//35s3rwZX375JbZs2YKXXnoJSUlJ3T9hEolkH5y+IB79cguOffJ7vL2qGOGoghnDk/H59cfghYsPx7AUS2+LKJFI+gGj0m34/PpjMD0vCY2hCG741zo8+sUWRKL7dvSWDDxkKFR3EYlQUxmllT8cRaFuUTffTPWhuzksqry8HOFwGHPmzMHgwYMBAGPHjgUAHH/88c2OfeWVV+BwOPDDDz9g9uzZTdsvu+wynHfeeQCAu+66C1OnTsX999+PU045BQBw00034bLLLms2lt/vx1tvvYXMzEwAwPPPP4/TTjsNTz/9NNLS0podGwgE8Mgjj+Dbb7/F1KlTAQBDhgzBTz/9hJdffhnHHnssiouLMXHiREyePBkAkJOT0x3TI5FI9oM3EMYbywvx8rJdaPCHAQCTBsfjjlNGyOouEomkUzjMeiy67Ag88fVWvPzDLry8bBc2l7tl3sUhgPRYdBc//rivpyIWRQFKSui4bmb8+PE44YQTMHbsWJx77rl49dVXUV9fDwCorKzElVdeiby8PNjtdthsNng8HhQXFzcbY9y4cU0/p6amAhDGCW/z+/1wu91N27Kzs5uMCgCYOnUqotEotm3bto+MBQUF8Pl8OOmkk2CxWJq+3nrrraYQq2uuuQbvvfceJkyYgDvvvBMrVqzohtmRSCStEQxHsWh5IY598ns89c12NPjDGJlmxeuXTsaHV0+VRoVEIukSGrUK95w6Cs9fOBEmnQY/7qjBnJdWYHett7dFk/Qg0mPRXZSXd+9xHUCj0WDx4sVYsWIFvvnmGzz//PO49957sXr1alxzzTWora3Fs88+i8GDB8NgMGDq1KkIBoPNxtDpdE0/q1SqNrdFo1Go1R23Rz0eDwDgf//7XzNjBAAMBmqoc+qpp2L37t344osvsHjxYpxwwgm47rrr8NRTT3X4ehKJpHUURcEXGyrwxNdbsbvWBwDISTTjlpOG4/RxGbJ7rkQi6VZOH5+BYSkWXLHoF+yq9uKsF1fg1UsmYdLghN4WTdIDSI9Fd5Ge3r3HdRCVSoWjjz4a8+bNw7p166DX6/Gf//wHy5cvx4033ohZs2ZhzJgxMBgMqKmp6ZZrFhcXo6xMJGWtWrUKarUaI0aM2OfY0aNHw2AwoLi4GMOGDWv2lZWV1XRccnIy5s6di7fffhsLFizAK6+80i2ySiQSYM3uOpz90gpc9+5a7K71IdlqwMNnHYbFtx6LMyZkSqNCIpH0CKPSbfjkuqMxNtOOOm8QF766WiZ1D1Ckx6K7mD4dGDSIErVby7NQqWj/9OndfunVq1djyZIlOPnkk5GSkoLVq1ejuroao0aNQl5eHv75z39i8uTJcLvduOOOO2AymbrlukajEXPnzsVTTz0Ft9uNG2+8Eeedd94++RUAYLVacfvtt+OWW25BNBrFMcccA5fLheXLl8Nms2Hu3Ll44IEHMGnSJIwZMwaBQAD//e9/MWrUqG6RVSI5lCms8eLxL7fiq00VAACTToM/HzsEV04fgjiD/BiQSCQ9T4rNiPf/fBRuei8fizdX4oZ/rUNxnQ/XzhzaFBUh6f/IT5TuQqMBnn2Wqj+pVM2NC/6DWbCgR/pZ2Gw2LFu2DAsWLIDb7cbgwYPx9NNP49RTT0VaWhquuuoqHH744cjKysIjjzyC22+/vVuuO2zYMMyZMwezZs1CXV0dZs+ejRdffLHN4//+978jOTkZjz76KHbt2gWHw4HDDz8cf/nLXwAAer0e99xzD4qKimAymTB9+nS899573SKrRHIoUusJ4LklO/DOaqrypFYB50/Jwi0nDkeKzdjb4kkkkkMMs16LhX+YhEe/2ILXfirEk19vQ1GNF4/MGQudRgbRDARUitLa8vrAxe12w263w+VywWZr3rTF7/ejsLAQubm5MBo7+aH78cdUHSo2kTsri4yKOXM6L3gfIRqNwu1245lnnsGnn36K/Pz83hbpkKNb3tM+RCgUwhdffIFZs2Y1y+uRdB5/KILXlxfipe93oiFAlZ6OG5GMe2aNwvBUay9L1/O09U4FAkA0CqjVwN7ULomk3cj/Vd3LP1cW4a+fbUJUAU4YmYIXLj4cRt2h1Uy4v7xT+9OdWyI9Ft3NnDlUUlZ23pZIJAeZaFTBJ/mleOrrbShz+QEAo9NtuPe0UTh62KHbE8bvB+rqgIYGqgyu0QBWK5CQAAwA21wi6Zf8cWoOMhwmXPvOWizZWoVL/u9nvDp3MuymvqtgSw6MNCx6Ao0GmDmzt6WQSCSHEGt21+Nvn2/C+j0uAECG3YjbTxmBMw/xpGy/n1Lf/H4gLg7Q6YBQCKivBxobgcxMaVxIJL3FCaNS8c8rjsQVb/6Cn4vqcMErq/Dm5VOQYpV/lP0VGdAm6RR//etfZRiURNIHKHc14qb31uHsl1Zg/R4X4vQa3HHKCHx3+0zMOXzQIW1UAOSp8PuB+HhAr6eUN72efmdPhkQi6T2OyE3A+1dNRZLFgC3lbpy7cCWK95bClvQ/pGEhkUgk/ZDGYATPfrsDxz/1Az7NL4NKBZw3eRC+v2Mmrjtu2CEXq9wagQCFP8XFtb4/Lo72BwIHVy6JRNKc0Rk2fHTNVGQlmLC71oezF67A1gr3gU+U9Dk6FAr12WefdfgCJ510UreVN5VIJJJDHUVR8N/fyvHYl1tR6mwEAEzJiccDs8dg7CB7L0vXt4hGKaeirZxInQ7w+eg4iUTSuwxOjMNHV0/DJa//jK0VDbjwlVV4+09HYkyG/L/Wn+iQYXHmmWd2aHCVSoUdO3ZgyJAhHTqvtznECmVJ+hny/Tx02bDHhb/9dxN+KaoHQHkU98wahdnj0mUd+FZQqynlLRSi8KeWhEK0Xy199xJJnyDFZsT7V03FJa+vxvo9Llz82mq8fcWROCxTGhf9hQ7/O62oqEA0Gm3Xl9ls7gmZewwu9eXzydg+Sd+F38++XJpO0r1UNfhx54fr8fsXfsIvRfUw6tS45cThWHLbTJw+PkMaFW1gMFD1J6+39f1eL+2XpWclkr6D3azDP/90JCZmO+D0hXDRq6vw2x5nb4slaScd8ljMnTu3Q2FNf/jDHw5Y77YvodFo4HA4UFVVBQAwm83yA7sF0WgUwWAQfr8farnMd1BRFAU+nw9VVVVwOBzQyBLGA55QJIo3VxRhwbc74Nnbj+LMCRm469SRSLfLENP2kJBA1Z/q65tXhfJ6qRpUQkJvSyiRSFpiM+rw1uVH4NI3fsGa3fW4+LXV+OcVR2JClqO3RZMcgA4ZFm+88UaHBn/ppZc6dHxfIC0tDQCajAtJcxRFQWNjI0wmkzS6egmHw9H0nkoGLit31uKvn23E9koPAGD8IDseOH0MJg2O72XJ+hdGI5WU5T4WPh+FP8XHyz4WEklfxmrU4c3Lj8Blb/yMX4rq8cfXVmPR5UfI/4F9HNnHogUqlQrp6elISUlBKBTqbXH6HKFQCMuWLcOMGTNkKE4voNPppKdigFPh8uPhL7bg8/VlAIB4sw53/W4kzpucdciXju0sRiOQkSE7b0sk/Q2LQYtFlx2Byxf9gtWFdbj09Z/x7pVHyUIVfZguGRZ+vx+//fYbqqqqEG1RVuP3v/99lwTrbTQajVTgWkGj0SAcDsNoNErDQiLpRoLhKN5YXojnluyANxiBSgX84cjBuO3k4XCYW8k8lnQYaUxIJP2POIMWb1w2BZe9QcbFJa+vxvt/norhqdbeFk3SCp02LL766itccsklqKmp2WefSqVCJBLpkmASiURyqLC8oAYPfLoRO6spy/jwbAf+dsZhshKKRCKRADDrtfi/S6fg4tdWY32JE394bTX+ffVUDE5so0mNpNfodPbtDTfcgHPPPRfl5eX7VIOSRoVEIpEcmDJnI657Zy0ufm01dlZ7kRinx5PnjMOHV0+TRoVEIpHEYDFo8eZlUzAyzYqqhgAuenU1yvb28pH0HTptWFRWVuLWW29Fampqd8ojkUgkA55QJIqFP+zECU//gP9tKIdaBVw6LQff3T4T58pcColEImkVh1mPf15xJHKT4lDqbMQfXluNGk+gt8WSxNBpw+Kcc87B0qVLu1EUiUQiGfj8UlSH0577EY99uRWNoQim5MTjvzdMx4O/HwO7SeYt9VcCASprG5A6jkTSoyRbDXj7T0ci02HCrhov/vh/P8Ptl8V2+gqdzrH4xz/+gXPPPRc//vgjxo4du08i74033thl4SQSiWSgUO8N4rEvt+L9X0sAAAlxevxl1iicfXimLN3cj/H7RSnbSIRK2VqtspStRNKTZDpMeOdPR+Lcl1diS7kbV/9zDRZddgT0Wtlfq7fptGHxr3/9C9988w2MRiOWLl3a7INRpVJ1yrBYtmwZnnzySaxZswbl5eX4z3/+gzPPPLNpv6Io+Otf/4pXX30VTqcTRx99NF566SXk5eV19jYkEomkR1EUBR+tLcUjX2xBnTcIALhgShbuPnWkrPbUz/H7gdJS+h7bfK++nrwXmZnSuJBIeoqcpDgsumwKzlu4Eit21uKOD9fjmfMmyFDSXqbTpt29996LefPmweVyoaioCIWFhU1fu3bt6tSYXq8X48ePxwsvvNDq/ieeeALPPfccFi5ciNWrVyMuLg6nnHIK/H5/Z29DIpFIeoyCKg8ueGUVbv/3etR5gxiRasWHV0/FY2ePk0bFAKCujoyK+HhArwdUKvoeHy88GRKJpOcYk2HHwj9Oglatwqf5ZXj86629LdIhT6c9FsFgEOeffz7U6u5zO5166qk49dRTW92nKAoWLFiA++67D2eccQYA4K233kJqaio++eQTXHDBBd0mh0QikXQFfyiCF74vwMIfdiIUUWDUqXHzicNxxTG50Gmkq34gEAhQ+FNcG9Uu4+JofyAg+2dIJD3J9LxkPH72ONz27/V4+YddyLCbMHdaTm+LdcjS6U+4uXPn4v333+9OWfZLYWEhKioqcOKJJzZts9vtOPLII7Fy5cqDJodEIpHsj2Xbq3HKgmV4/rsChCIKjh+ZgsW3HIurjx0qjYoBRDRKORVt9QnV6Wh/i96xEomkBzh70iDcccoIAMCDn2/CVxvLe1miQ5dOeywikQieeOIJfP311xg3btw+ydvz58/vsnCxVFRUAMA+5W1TU1Ob9rVGIBBAIKZMh9vtBgCEQiGEQrKKQEfhOZNzJ+kuBso7VdUQwCNfbMP/Nu79X2Uz4P5ZI3Hy6BSoVKp+f3/9iYPxTrHR4PNR+FNLgkFhfMhHPzAYKP+rBipXHp2NPXVe/OuXPbjpvXy8c4UO4wf17X5A/eWd6oh8nTYsNmzYgIkTJwIANm7c2GxfX6pw8uijj2LevHn7bP/mm29gNpt7QaKBweLFi3tbBMkAo7++U1EFWFGpwufFavgjKqigYEaaglnZXkR2r8GXu3tbwkOXnn6namsN8Hr1sFj2/dD1eHSIiwti505Zf3ag0V//Vx0KTNEA6x1qbHYCl7++CreNjcDRD0IR+/o75fP52n1spw2L77//vrOndoq0tDQA1JgvPT29aXtlZSUmTJjQ5nn33HMPbr311qbf3W43srKycPLJJ8Nms/WYvAOVUCiExYsX46STTtrHSyWRdIb+/E7tqvbi3k834dfdTgDA2Ewb/v770RiTIf+39CYH653iqlCBAGA2i6pQPh/lVXS2KlQgQN4OtVrmZ/Ql+vP/qkOJmSeEcf6rq7GjyosPKxPwzuVTYNJrelusVukv7xRH+7SHDhkWv/32Gw477LB2J2xv2rQJI0aMgFbbafulidzcXKSlpWHJkiVNhoTb7cbq1atxzTXXtHmewWCAoZX/zDqdrk8/xL6OnD9Jd9Of3qlgOIpXlu3Ec0sKEIxEYdZrcPvJIzB3Wg40stRhn6Gn3ymdDsjJEX0sfD7qY5Gc3Lk+FrInRv+gP/2vOhRJ0Onwf3OPwBkv/IQNpW785dPNeP7CiX0qmqYlff2d6ohsHdL4J06ciIqKCiQnJ7fr+KlTpyI/Px9Dhgxp1/EejwcFBQVNvxcWFiI/Px8JCQnIzs7GzTffjIceegh5eXnIzc3F/fffj4yMjGa9LiQSiaQnWVdcj7s/2oBtlQ0AgGOHJ+Phsw7DoHgZWnkoYjQCGRld9zLInhgSSfeRnWjGwj9MwsWvrcZ/fyvH8FQrbjxB9jw7GHTIsFAUBffff3+7cxOCwWCHhPn1119x3HHHNf3OIUxz587FokWLcOedd8Lr9eKqq66C0+nEMcccg6+++gpG+d9WIpH0MN5AGE99sw2LVhRBUahz9l9PH43fj8/o0ythkoNDV0OWYntiMHo9fdXX0/6MjK5dQyI5lDhySCIeOvMw3P3xBsxfvB15KRacOjb9wCdKukSHDIsZM2Zg27Zt7T5+6tSpMJlM7T5+5syZUBSlzf0qlQp/+9vf8Le//a3dY0okEklXWbqtCvf+ZyNKnY0AgDkTM3Hf7NFIiJNN7g4GAz3nQPbEkEh6hguOyMa2yga8sbwIt/17PYalWJCXau1tsQY0HTIsli5d2kNiSCQSSd+jzhvE3z7fhE/yywAAmQ4THpkzFscOb184qKRrHCo5B+3pieHzyZ4YEklnuHfWKGyraMCKnbW4+u01+PT6Y2AxdD33V9I6sluTRCKRtEBRFHyyrhQnzv8Bn+SXQa0CrjgmF9/cMkMaFQcJzjmor6dVerudvtfXi1yEgYJaTUZTW6XiQyHa3866KRKJJAatRo3nLpyINJsRO6u9uOuj3/YbHSPpGvLflEQikcRQ5mzEZYt+wc3v56POG8TINCs+vvZo3D97NOLkKleHCQQo+TjQwXYOsTkHej2gUtH3+HjhyRgoGAzkifF6W9/v9dJ+GQYlkXSOJIsBL1x8OLRqFf73WzleX17U2yINWOSnpEQikYC8FO/9UoJH/rcFDYEw9Bo1bjxhGK6aMRR6rVyDiaU9OQ9dCWM6FHMOEhLIAKuvb14Vyuul+UpI6G0JJZL+zaTB8bjvtFF48PPNePSLLRg3yI4pOfIPq7uRhoVEIjnkKanz4Z6PN+CnghoAwMRsB548ZxyGpcgkv1jaayx0tXTqoZhzYDTSvLTsiREfP/BySiSS3mLutBysKXbi8/VluO6dtfjfjdORbB0gqxN9BGlYSCSSQ5ZoVME7PxfjsS+2wBuMwKBV445TRuCyo3Nlo7sWtNdYCASAsjLA7QZSU8X5HSmdGptzoG+l8NZAzTnorp4YEomkdVQqFR6bMxZbyt0oqPLg1g/y8eZlR0At/993G50yLGpqavD6669j5cqVqKioAACkpaVh2rRpuPTSS9vdQE8ikUh6i+JaH+78aD1W7aJg/Sk58Xj87HEYkmzpZcn6Jgfqs1BWRopxbS1QXEw/KwrgcDRfbW9PGBPnHNTXt25YeL0kx0BVugfqfUkkfYE4gxYvXXw4Tv/HT/hxRw1e+2kXrpoxtLfFGjB0eL3nl19+wfDhw/Hcc8/BbrdjxowZmDFjBux2O5577jmMHDkSv/76a0/IKpFIJF0mGlXwxvJCnLJgGVbtqoNJp8GDp4/G+1dNlUZFGxwo50GjAQoKgMpK8mSYzXSsy0VGhtMpkrd1OgpzOlAYE4f/1NcDwSAZKcEg/S5zDiQSSVfIS7XigdljAABPfr0NG/a4elmigUOHPRY33HADzj33XCxcuHCfbrOKouDqq6/GDTfcgJUrV3abkBKJRNIdFNZ4ceeH6/FLUT0A4KghCXji7PHITjS3erwMSSEOlPPg9VI4lM0mwpiCQZq/ykqgpgZISQEsFjI42hPGJHMOJBJJT3LhEVlYtr0aX22qwI3vrcN/bzhGVv7rBjo8g+vXr8eiRYv2MSoAil275ZZbMHHixG4RTiKRSLqDSFTB6z8V4qlvtiEQjiJOr8Hds0bh4iOyW42tPVQas7WX/eU8BALkkbBYhAGm0wE7d9Jc2WxkmKhU5MGorARGjGifoRabc9BITc9hMh3aRp5EIukeVCoVHjt7LH7b40RhjRd//WwTnjp3fG+L1e/pcChUWloafv755zb3//zzz0iNzdiTSCSSXqSgqgHnLFyBh7/YgkA4imOGJeHrW2bgj0cNbtOo6Gxjts72bOhtDiT3/vosRKO03eHYV+FXFECrpWM49KmVNan94vdT3kZlJeVxFBXR9wM1yAuF1P3yWbRGf32vJJK+jsOsx4ILJkKtAj5cswef5pf2tkj9ng57LG6//XZcddVVWLNmDU444YQmI6KyshJLlizBq6++iqeeeqrbBZVIJJKOEIkqePXHXZi/eDuC4SisBi3uPW0Uzp+S1arHlTlQknJrFY36q4fjQHLHhoK11WfB7aZjLXvTUwIB2p6dTcdzfkU4THNqNtP+9vSg6EzZWr+fjJCqKhOKioRR1NefRWv01/dKIulPHJGbgOuPz8NzS3bgvk824ojcBKTbTb0tVr+lw4bFddddh6SkJDzzzDN48cUXEYlEAAAajQaTJk3CokWLcN5553W7oBKJRNJeCmu8uO2DfKwtdgIAZo5IxiNnjUWGY/8fFp1pzNbVng29xf7krq+nkKNQqLlCm5hIuQ6xOQ+pqeTV4VAl9k5YrWRsqFT0PT2d5kxRKCSqPT0oOmrk8T15PIBOF4XNRtv7+rNojf76Xkkk/ZEbjx+GZdurkV/ixF0fbcCbl03Z7wKUpG06laVy/vnn4/zzz0coFEJNDTWUSkpKgq6tzD6JRCI5CESjCt5aWYTHvtoKfygKi0GLB2aPxrmTB7XrQ6Izjdk64+HoC7QldzQKbN9ORkBubusKbWJi86T22PAxrZa8E04nfbdagbQ0YYi1twdFZ4w8vieHA9BqFahUJH9ffxat0V/fK4mkP6LVqPHUueNx2nM/Ytn2arz3SwkuPCK7t8Xql3SpvZBOp0N6ejrS09OlUSGRSHqVPfU+XPzaajz4+Wb4Q1FMG5qIr2+ZgfMOEPoUSyhEXx5P2/tjleKOKL99if3J7XSKZG1FIY+DXk8KLofmGAzk0QDI2FCpyOAwmUQuxLZtlHvRcuq9XjI2DhQG1R4jL7ZsbX99Fq0xkO5FIukvDEux4I5TRgAAHvrvZpTU+XpZov5Jp+tqud1uvPHGG6ioqEBubi7Gjx+PsWPHwmxuvWyjRCKR9ASKouCDX0vw9/9ugScQhkmnwT2zRuIPR7aenN0asbHs9fVkWGRk7NvcrWVjts54OPoCbckdCNC922w0Jy3lZoXW5aK5iI391+nIyLBagXHjaB5DITomGgWSksiD0d4eFB3tvh17T+Hwvsf31WfRGtEozSUbdy2NsP50LxJJf+Kyo3Px9aYK/FJUj7s++g1vX3Gk7MrdQTptWMyZMwfr16/HlClT8Pnnn2Pbtm0AgKFDh2L8+PF4//33u01IiUQiaY1Ktx93f/Qbvt9WDQCYNDgeT507HrlJbSz1tkLLWPasLGDPHqCkhJTiQYNIwfN691WKO6r89hXakju2epNava/cOh0ZDCUl5ImIjf0vLCTDZPhwUWbW6SRDpbaWlP5hw+gcRTlw8nZHu2/H3lNrDqq++ixa4vcDFRX0pdHQ/VkszY3c/nIvEkl/Q6NW4clzxuPUZ3/Eip21eHv1blwyNae3xepXdNqwWLlyJZYuXYopU6YAAAKBADZs2ID8/HysX7++2wSUSCSSliiKgs/Wl+GBTzfB1RiCXqPGbScPx5+mD4GmjdWltprdtRbLnpVFSm1ZGSnR6emtN2brqPLbV2hLbjYm3G7yMLSUmz0QVislbTOKIhRdp5NyKoxG+h4IAMnJZGBwiE97Kxy1VonK46Evk6m5kRd7T5ZWGqj31WcRS6yRGx9PMhsM5CHy+8W89od7kUj6KzlJcbj71JH462eb8OgXW3HciBRkJchonPbSacNi3Lhx0GrF6QaDAZMnT8bkyZO7RTCJRCJpjVpPAPd/uhFfbKgAAByWacP88yZgeKq11eP3V7JTpWo9lp2V4rg4Oj89HU0VhlrSVhnW1jwcfYnW5FapaI4iEVohb0k9NSxvZoQBwtNhswkDgpVeg4H21dWJkrNGIxkhB6pwFNt9u6ZGGIFGI41ZVkZGhNXavCQuJY6roCjUAbw7n0VPdmOPNXJNJnoOPh+V6PV6gepqut++/F5JJAOBPx41GF9sKMfqwjrc/+lGvHGprBLVXjptWDzxxBN44IEH8OGHH8Igl00kEslB4JtNFfjLfzagxhOEVq3C9ccPw3XHDYNO03pMyIFKdiYk7D9HwmLZ/36gufIbW4a1NQ9HVzmQUtsRpbctuQcPpvlqbKRxolGxn70CLecjNmwqNpyKKS0VoT2BAB3L4T2NjfuvcMRKtNMpDMJQCKiqAjZupGtlZZEhmJREFau0WmqQ53aTzN3xLHq6p0TLhG02bjmcLBKh9zYlhQxdWWpWIuk51GoVHj5rLGY9+yOWbqvG/zaUY/Y4WYatPXTasMjJyYHb7cbo0aNx/vnn46ijjsLEiRORlZXVnfJJJBIJ3P4QHvxsEz5eS11Rh6da8PS5EzB2kH2/5x2oZKfT2T05EkYjKcY9tZp9IK+Lz0f3Egx2TOltS26/n7wBO3YA5eWk/JtM5JHQ6Wj8pCQxDucB1NQIbwTjdlOFqLg4konL0XJ4T2LivmVjW1JXR+FW8fFkoLChY7HQGE4nnRsOU0+NlBQgJaUR6ekkr8nUtedxMHpKtJZQHxtOFomQgcHhUBKJpGcZlmLBNTOH4tklOzDv882YnpcMu0lWQD0QnTYszj77bFRWVuLYY4/FihUr8NJLL8HtdiMhIQETJ07EN998051ySiSSQ5SVO2tx2wf5KHP5oVIBV80YgltOHA6jTrPf89pTsjMQIIPC6+2eHImecN62pdRWVABFRfR7bS0p1cnJpPBrNB1TeluTu7GRvuLjaYXc7ycvQUUFUFAATJxIie08tsNBpWYjETJ2FIXk3L2blOacHKE063RkALhcIl+irQpHsc+xro5+VxT6stno3GCQtlutJGd5OeB261BZKZK6u+JdOBg9JfZXCMBgoHs0mWTCtkRyMLn2uKH4/Lcy7Kr24vGvtuKRs8b2tkh9nk4bFhs3bsTKlSsxfvz4pm1FRUVYt24dfvvtt24RTiKRHLr4QxE8/c02vPZTIRQFyE4wY/554zE5p33B5e0tBetw0LF9NUeiNaU2GqVt1dWkjJrNtN/nI+U+LY1+76zSW1dHRoTVSnNQVUUGgFZL88PdrUeMAEaPpus3NlIYldFISr7PR/Ov1QLZ2SRnS8xm8jbo9W0rzPwc+Rlx5242GLVakXfBMhYXA06nAQYDXaMr3oX2GKi1tXSdrnhG+mshAIlkIGPQavDIWWNxwSur8O7qYsyZmNnuz6BDlU4bFlOmTIHX6222LScnBzk5OTjrrLO6LJhEIjl02VLuxi3v52NrRQMA4IIpWbhv9mhYDO3/l9XeUrCsEB6MHImO0pZS63TSvoQE8gjY7c29AFyZqTNKbyBA50SjFGrEfT2CQZqzxEQaR6MhAyMQAMaOJU8JzxeHVgUCdFxjI4VE2VtErmm1NHZOTtuyqdXkjdmzh66n0VDIVVKSSNpWq+n+eb7IuxOGXi8a/HXWu7A/A9XvpzErKmhuONyrs+9Nfy0EIJEMZI4akojzJg/CB7/uwT0fb8AXN01vM69P0gXD4qabbsKDDz6IDz74AI7WyodIJBJJB4lEFbz24y48/c12BCNRJMbp8djZ43DS6NQDn9yCjq4A92SORGdpTal1u0nx51yGcLj5ar/ZTMq620332FGlNxql4zlx2+eja4RCZGgoCv1utVLoldtN8xurrBsMoit0JCLCzlwuki82z8Jkap6vATR/DopC91NVRePqdPS9poaMCJOJjCi1mq7FIWMqlbLPvXGDP7ebxmnPc27LQOV+Ex4PzafD0b5KV/vjYBYCkEgk7eeeU0fh2y1V2FHlwZsrivCn6UN6W6Q+S6cNi3POOQcAkJeXh7POOgtHHnkkJk6ciMMOOwz61j7FJRKJZD+UOhtx58eb8HNhHQDgxFEpeOzscUiydF7D7+gKcF8wJmKJVWqjUfJE1NRQYrXVSqvxLaswabWksJeViU7XHVF6efU/GhW5C8GgmJtwmPZpNKJfRCAgkq9bJprX19P3tDS6tsdD3yMRMhoGDxaejNaS1L1eus+MDLonj4dkqK2l4+12UrydTsq5qK6mHhs63b6GRSRC+Rd+v0hCj02Cb82obMtAZa8Re4p4PjvrGYk1pvqikSuRHMrEx+lxxykjcM/HG/Dstztw5sTMLn02DWQ6bVjs2rULv/32W1NDvEceeQRFRUXQarUYMWKEzLOQSCTtQlEU/Fytwr3/WAlPIAyzXoMHZo/G+VOyulw3vD+vALNiqdeLPItAgFboOQTI6aRjfT4RLhUOk/JtsXRO6TUYKNyppoauqVKRYWPe2x/K76drs7FiMJCBwHkfLRPNNRpg1y4K2crJIfmrqshrYDKRrDt3krweT/NzPR5hRKWkiGMbGsiAstnonsrL6RiTie6VwqJUCAaFt8fvp3Aqj4eS0S2W5knwFguN2Vqid0sDlfM9IhFRNjcW9owcqLs4y9VWxS+Tqd2vi0Qi6WHOm5yFd1bvxsZSN576ehseO3tcb4vUJ+lSudmcnBz8/ve/b9rW0NCA/Px8aVRIJJJ2Ue8N4u6P1uPrAg2AMA7PduCZ8ydgcGIbmbKdoKdLwXY3LRXNcJi6f4dC1K9BqyX5q6tJ+VSr6RwOM3I66ViAjotVejnnobZW5Eq0RkICKfIlJSIRW68X5Wy5YSA3b+NqRexFiE00t1opyXv3bhqPQ62434TLRcaI10vb8vKEZ0CrJcW9sZHO9/loPKtVVJ/yekXTOJ2OvoqLgdpaE0pK6P4dDpoXp1N0VQf2TYIfNKj1RO+WBqrXSwZKcnLrBioXBmir0lXss+7pMrYSiaR70KhVePD0MThn4Uq8/2sJLj5y8AFLnh+KdNiwsFqtmDhxIiZNmoTDDz8chx9+OEaPHg2VSgWr1Yrp06dj+vTpPSGrRCIZQCzdVoU7P/wNVQ0BqFUKbjo+D9cdnwdtDyXF9WVjgmlN0eTmaIBYqecwLqORjvP5aHt1NR2r15OSzl2uudcDj8UejoyMtjteDx1KBoNGQx6GoiJSvDMzaVy/X+Q8sKLeVvUkoxHIzaUytTYbKfr19WS0WCxknGzeTIp7RYXo1aBWk6LtdIrwtawsMig4wTw9nSpTsffBZqMxo1EVVCo6t7aWZEtMbG5oxSbBu1zk3WEvCHt2EhObhyixIcRGTTgsqovxXLa3/8nBKGMrkUi6j8k5CThzQgY+yS/DXz/biI+umSY7cregw4bF448/jjVr1uC7777DP/7xD0SjUZhMJowbN66ZsRFbhlYikUiYxmAEj3yxBf9ctRsAMCQpDnPSXfjzzCE9ZlT0F1pTNLVaUnyjUVLAk5NFUrPTKaogpaaS4m8ykYFhtZKCyknGgQCdz2FLLhf93HJVnD07oRAp7UlJ5EXYupVW0TkkisvHspETWxaWu3bHGnNcJWrQIFLEA4HmuRWxhlRVlbhPNoQ4LCgaJYWeDYlQiK7H3cKHDqX5++23EBRF5JYoSvO+G4FA8xCzhgYyFtj40GrJEKqtpXvVaEg+v5/GSk0lOQwG0eyPDaL2lIZtTxnb9oZTSSSSg8fdp47CN5srsbbYiU/yS3HWxEG9LVKfosOGxbXXXtv0c2NjI+Li4nDDDTegrq4Oq1atwmuvvYZgMIgIL7FJJBLJXtaXOHHL+/nYVUOlqi+dloPbThyK7xZ/3cuS9T5tKZpcTlWrpVCkWIWdS8o6HOQRsNloO+cA6PViVZ6VeJeLlN7UVDqmvJzGCQZJIa6pEQo3Gw1JScBRR9Hx1dU0pt8vVtfr6kQZWK9XGAQOB13LbhdVorjKk9lM14xGadWfjQpFETkYnEei0wljhZO3AboHk4nyMOrrhTFiNALx8UEMGkRyJSaSl4HPA2i8ykoRPsU9O1wuYXRxuJPNRgZMYSHd94gRdF02esxmuu/qahGWdaDSsC0rfrUM1WtvOJVEIjm4pNmNuO64YXjy6214/Mtt+N2YdJj0+2/YeijR6RwLADDtXUK68MILMW4cJbGEw2Fs3ry565JJJJIBQySqYOEPO/HM4u0IRxWk2gx48pzxmDE8GSFOCDjEaatfgsFAyqrTKUrAxsIdt9moAESycWWlSDgOhUhR5bwLv58U55ISUuRZmVapRG5DMEjnh8NkHCQmkhzRqCj76nLRqn4gQMaAx0MyNDbSeOzxUKlEJSu/nxTxxkahTHNTvpwcMgbi4ui6PE5yMu3nqk8mk0jAjosjpT8piWSKzTGJRkUOiMcjwrbcbnFffj+NFRdH91xQQM8iN5eMBO4kzp4L7hOSltY8xKy+nnJT0tMPnBvBFb88HpGzwXPBsnA4VX/JD5JIDhWuOCYX764uRqmzEYtWFOGamUN7W6Q+Q5cMi1YH1GqbjAyJRCIpdTbilvfy8XMRlZE9bVw6Hj7zMDjMsix1LPtr6OdwkDejoYGUYUXZf9lcTjYGaDWfx7bbRY5BRQUp1BqNWMl3u0mJHToUTV2rq6vJiFCphAHC+7gfRUEBVX5KS6PfOXeCvQ9+PzBsGBkmxcWUiG0wkNw8Rl0dncclcjm/gmVzOEiOuDga12YTYV319WQ8hEI0Bp2rRmWlCHXy+0W4E/fV4PK0nK/C3pjKSjJoEhIofAoQZX1tNjICAgE6Jy2Nfo5EaDuHQx0I9kps20bHt+zvUVlJRhbnh7SsGCWTuiWS3sOo0+DWk4bjtn+vx4tLC3DhEVnyM20v3W5YSCQSCfP5+jL85T8b0OAPI06vwbwzDsPZh2fKZLdW2F9DP6NRVEMCSPE8UNlco1HkM3DCN692c84Fx/E3NpJiziVUubO1y0XGRmUlKfa7d5PBkpIirqMoNEYoRGFV6ekkU2wYD6/mV1WRZ4GrNeXlCY+B1UqGByeFc1fvaJSuUVpKxwweLCoz1dYKr4jJROVkk5LIqKmrM8DlIkMgHObeFsKrUltLx3GoWW2tSJIHRFlZTibn44B9e4cYDOTp0GiEYdPSs9CW16GtP4VgkOY9GpUVoySSvsiZEzPx6o+7sLWiAS98X4B7Txvd2yL1CTpsWPzpT3/CpEmTMHny5CbPxMFSEiKRCB588EG8/fbbqKioQEZGBi699FLcd999UlGRSPoQnkAYD3y6ER+vLQUATMhy4NkLureMbFfpi+El+2voZ7eTMtlWI7fW4J4U9fXi2EBA5DhwfgAr2hUVdM3KStpuMJDxotXS9aqqSEZOKA4EyFDYuJGUclbOc3PFeVYrHcNeg2iUZKqsJA/B0KH0xfcbDoueEikp9L2sjIwGr5fGczhoXrj5X0oKGQxcllalAnw+DUwmukejkQwMnltFITlNJqoyVVxMHpO4ONEp3GIhY6SxUYQ+WSxkdLFHhfH76bocKhXrWQBa71PB4Wk5OSQjNw5Uq+lZazR0T4MHC0NTVoySSPoOGrUKd506Epe98QveXLEbc6flYFC8ubfF6nU6bFjs2LED//73v9HQ0ACtlk6fN28eZs6cicMPPxwTJkyA2dwzE/v444/jpZdewptvvokxY8bg119/xWWXXQa73Y4bb7yxR64pkUg6xtrietz8Xj6K63xQq4DrjxuGG07Ig66PVHxyuUg55GZ5fSm8pK2GflotKcHBYPNciv3BhlNcHCnG5eWkGPOqOoccxcWRUhwKkeLb2EiKdjgsEsO5b4TRKEJ17HZS9ktKaB8bKJEIbU9OJu9FICBKwwJkkAweTPtLS+lZpKcLI4S9JklJQqFmQ8LppJCroUOF4WGz0faKCpJXpaLQrLo6PRoaRPI4GzLBIN2DRkPHNTbSz7m5woBSq2kcvZ6+c+iTw0HGFffQ4ATvXbvo95wcugf2LNTXi+Naeh3q60kWvodYQxeg5885Ii2RFaMkkr7BzOHJOGpIAlbtqsMzi3fg6fNkRdQOGxY//PADADIw1qxZg7Vr12Lt2rV44IEH4HQ6odFoMHz4cGzatKnbhV2xYgXOOOMMnHbaaQCoSd+//vUv/Pzzz91+LYlE0jEiUQUvfF+AZ5fsQCSqINNhwjPnT8ARuQcoj3OQ8Ptp5ZuVSe6YbLHsP7zkYHs2Yhv61dWR0u90khKq15MiOmQIGRqtyRXbYM/nEwqoopBizQ31UlNJuedkbA55Kiujn5OS6BzOX3C7aXzu2xAK0XUsFjq2pkbMaTRK4xoMZHh4PKKxX2Mjnc9dwWtr6Ss3VySbc4I3K/keDynTmZl0jNstwrtYXpuNDBROHnc6DU3n7dghQp9sNpoTq5Vk3raNZB41SlR5SkqiMVwuUf2JvS1ZWbSNGweyB2Pw4OYdzvV6GhugKlIM76usRJPho9c3f4aNjfS8DYbWe2G0VTGqL3rhJJKBjEqlwt2njsKZLyzHx+v24MoZuRiZ1s7VnwFKp3Ms8vLykJeXhwsuuKBpW2FhIX799VesW7euW4RrybRp0/DKK69g+/btGD58ONavX4+ffvoJ8+fPb/OcQCCAANc5BODe++kYCoVkNZpOwHMm504Sy576Rtzx0Qb8utsJAJg9Ng3zTh8Fm0l3wHflYLxT3HiupIQUY04yrquj8JrUVFJIKytFeEmsgs7K2sH0bLjdwIYNdP2EBFJ+GxtJWd26lRTxuLjmcgEiN4FDabxU2RdxcaRUB4OkuKtUNAfV1WRAVFTQ/XJehV5Pyis3w+MStS4XjaHVknHBUaihkJDRbKbjduyg8dlDYDLR/ZSVUTgUl9bdto0MCr+fxrNY6LjSUpr7vDwygrgkbzBI19PpSI7UVNGhu64O0OvDUKlUiEbDiERIDkURPT5cLlGBi8vI2mw0jxZL89K8TqfIQYmPJ7m5fC73z7BaReI9EwyKufZ49lX02aCtrm6eswKIXh1czarlnwaX6Y1EaF9vv6uHCvLzT9IaY9Li8LsxqfhqUyWe+WYb/nHhhHaf21/eqY7Ip1IURelBWbqVaDSKv/zlL3jiiSeg0WgQiUTw8MMP45577mnznAcffBDz5s3bZ/u7777bYyFbEsmhxJoaFT7YpYY/ooJBo+Dc3CgmJyltJqX2BrW1BrhcejQ2aqHTKdBoxL89n08LszkEqzWEUEiN+PgAIhHA6TRCUVQwGsPQaBREIir4/VrodBEkJvqh1/dsg4GdO62oqTEjKcnftC0UUsPl0qO62ojUVC+GDPE0k0ulUhAMamGxhFBfr4fPp4PZHEY4rILHo0NcXBApKQGUlZng96thMkVQU2OCz6dGaakVLpceXq8W0agKWm0EajVgNoeRl+eCXh9FXFwQ1dUmqNVAMKiC36+DWq0gElEjHFZDrw8jHFYjGNTA79fsDTtSIxpVw+EIQKeLQqVSQadT0NiohaIoUKkUhEJqmM1hWCxBuN16hMOavSFEKmg0CszmAGy2CEymEPT6KAyGCNxuHXw+DTQawGwmWb1ezV4vhwKfT4fERD+s1gCKi61QFBUURbW37G0QdnsQ0agKPp8WVVUGDB3agMxML3S65h+JVVVGKIoCkykKjUaBWq3AaAzDag3trXplbppjVup1OgWBgAo1NVSSPTl53/dFUQCXSw+Nhuak5Xvm8WhgMCiIjw+gJfwsExMDCAbVqK01IhTS7DMGEEVCQgAGQxQ6nWyIIZH0FGU+4In1GihQ4c5xYWT2nXTCbsHn8+Giiy6Cy+WC7QDxuP2qKtQHH3yAd955B++++y7GjBmD/Px83HzzzcjIyMDcuXNbPeeee+7Brbfe2vS72+1GVlYWTj755ANOjmRfQqEQFi9ejJNOOgm6lgX3JYcUDf4w5v13Cz7dUQ4AmJhlx1PnjEV2QscM9p5+pwIBoKiIFLnKStFLQVyfjklKovh5h4NWqS0W8l44HM1Xm51O2tYTibMcyuLxkII6caLorRCNisZ1Gg2taE+eLCpFVVXRinVWFt3rnj30nXtGBIPkiYhERJK4RiOqUCUnA2PGkAyhEB1rMIjEcc4rUKtphd3vJ09EUhKFIKlUouFeNEr7g0FaMeekcF49NxppH5euVavJA8N9Kzh3wG4XFZs4/yQvj+Z/2zbyNCiKKENbV8er/GGUlGxBXt5YJCRoodfTmF4vhZGlpYn8jWCQxhkxgqpomc3NcyEyM0WjP97O/UCSkihUjUvaxvahMJvJ48K5Fy09FsEgnZOWRnK19DaYzaI/SKxMfG0O2ysrE+8k4/fT3JaX07ykpUkPRncgP/8k+2NDZD2+2FiJ3yKZuHJW+3It+ss7xdE+7aFfGRZ33HEH7r777qbwq7Fjx2L37t149NFH2zQsDAYDDK0Em+p0uj79EPs6cv4ObdbsrsPN7+ejpK4RahVww/F5uOH4YdB2IUG7p96pcFh0Y2ZlUhvzn4+V9IoKEdeu15PS6PWK0ClWyLg8ajTa9Th2Vka56zVXDmpooNh9VpZ9Pjq2poZCdhwOMj5UKtFQz2Ih40KjIWU7NhfCbKZjy8pof0oKfcXHAzt30jUGD6bfXS4aT60mg4zDqcxmEQpkNpM8Wq3Id2BjIhol+RSFxkhMpHniylBmM801510kJ5NCn5UFbNlC1w4GSdakJNF9224XJXeNRpqn2JCmSIRk4aRnjSYMQIv6eh3q6khJ50TpWGe1203XT00VoWKxSfNJSfT8Gb2enkt9vej7UVNDx3AfCn5vAJLNYtn32Xs8oqu51SrCr0wm8V5Zrfsm8icnCwOBK23Z7eI98PuFQZKYKOaHO5bLMrVdR37+SVrjphNH4IuNlfhqUyV21jZ2KNeir79THZGtXxkWPp8P6haZbBqNBtHWymZIJJJuJxyJ4h/fF+D57woQiSoYFG/CgvMnYHJO30jQbg1uDscryVzRiAmHSXFTFFrN5pXiuDiRK8DlRoHmibOdTZZtmWDNTejS04V3wOMBfvtNKMN8H5yEbjQ2N5D4+mwccSUjzr0oKCAjY9gwumZjI91TZiYpyG433bPBIPId+P54fKOR5GODh+P7g0G6TlUVjc1labkSUnY2zWNhoei27fPRWMnJdExxMW2zWkXDuVgjSVFIRs7DYHm5wpXHQ18aDY1TVhaPww8Hhg+n4379lcaoqaHrcWnbSISMKrNZ9KuIRkVfjraea1wcyczeHi7dq9UK48lmI4OltfLB3BSvrKztBnixifytvWetdWt3Oul4u130GImtuCXL1EokPcOINCtOG5uO/20ox3NLduDFiyf1tki9Qr8yLE4//XQ8/PDDyM7OxpgxY7Bu3TrMnz8fl19+eW+LJpEMeErqfLj5/Xys2V0PADhzQgb+duZhsBn77ioL0LzxnMMhwkRYCayuJoU0J4f2c7hPOEwKG5dR5fAc7gbNHo6OdkTmRHK/n5RNrmIEcOIxrTQnJACbNgnFW1Fon05HSei5uSIMChAhNI2NJGds9pzXS8p+SgqN4XKJfhgWC12vsZGOox4QdL8mkyhJm5xMx6nVNGcOh6i05POR0VBRQfvT0mg/e038flJmuY+EXi88GmwolJfT9aNRui4gnhEbUQ0NNEf8TFJT2YgQhiAbBC6Xvun5OBy0j+e+rk4YSDk5dF88h7GKOyvtrSn20SjJM3Qo3Y/T2bwXRVoa3UdmpvBGsdchPl4YsPwe7K8BXlvGTctu7bE9SgDhreP1OFmmViLpWW48IQ//21COLzZUYFtFA0akWQ980gCjXxkWzz//PO6//35ce+21qKqqQkZGBv785z/jgQce6G3RJJIBzaf5pbjvPxvREAjDatDi72cehjMnZva2WO2GcwoaG+lnr5cUQVak09MpHIYVuVjPhlYrVtmB5nkOnemIzOfHx4u4fw5lYe9IfLyowrR7N50XFycMGo75j21UV1dHhoNORz8bjSRjXR3JxoYSV8bin91uMpDq6sh4YAVcUcQ4BoPoqeD303nx8ZSzEhdHcnPREKORvAIqFSnWDgf1eQBI9sZGOpbDv9xuoRgXF4sSrFzVintJsNGSn08eEA5F48Z2XKnJ72djL4o9e0RfjIYGGsdmo2eakEDPWa8nOdLSmivbbFzu2bNv/oTDQdsAOt9opPNjj2MDTq8XssUaJ2Vl4j1gOtoAr2W3du4IrtXS/HLuBd9XW2VqJRJJ9xDrtXj+ux34x0WH97ZIB50eMSzUajVmzpyJJ598EpMmdZ8ryGq1YsGCBViwYEG3jSmRSNqmZQftSYPjseD8CcjqYIJ2b9Oy8ZzJJGLlueynRiOOj/Vs6HSiNCuHCBmN+yqErIhzInJrcLlULrMaqwgCYiXeZKKfR44E1q8n40JRhLKeliaUxKoq8iBotbRNr6dzNRpSLj0eUpy5jCx38GYPAJdfValEGI2iUHiQz0eysqFjMNCxLhed63aTEcFeF14112op9CocJiPA7abrBAKiGZxKRTJ6PCQnd7Z2OkU4UTBI12FvitVK968opJhXVYl8GM4/MJvJ4IlGVU05H3wPvMLPYWcOBxlJABmW7G0wGESuQm0t5X9w/oTLJXpsWK3N+0zEGibBoAjBa7mv5XvQkljPAr8nbYXbxXZr5xLAxcUi90WjEcZobFigRCLpGa4/fther0U5imt9yE7sX5+XXaVHDIvXX38dRUVFuO6667Bq1aqeuIREIulhNuxx4cb31qGwxgu1ily81x/XtQTtg0nLFeL9xauz0cDJ3bwC7XSSAsvJt2YzrX7HFpTz+0UYTCBACjRAimtLz0XLmHgOU2EPAntHYmVKTSVPBIc3cdO7mhoRRpScLJRrjt9PT6fk67Q00cCutJSU1j17RCO7xES6Tloa5ZhUVVFYUzgsQr/i4kguo5G+x8VRuFFtbfPE45oacX1Wjtnj4naTUaDT0TkNDbRdpxNeC6u1uYdIrxfzlZpKv2u1NNfshcnKEonMoRCdq9MBiYmNSEwU3hGWHaDfKypIVr+fEtgbGui5xsXRPNbW0nMNh8n4SEkR4VYVFSLp3OsV703se+d2k8ytGQOt5UbEotPR/ZWWio7oseF2HMbGRQnYaK6poefndJJhmJBA57ExxO+1DIOSSHqOUek2zBiejGXbq/F/P+3CvDMO622RDiqdNiyKi4uRlZUFVYti9Yqi4Pjjj0d2djYefPDBrsonkUgOMtGogteXF+Lxr7YiFFGQYTdiwQUT+0wH7QMRmxjdWv7DgVZ9ObyJDY8hQ0hJN5tJmWPFla9VUSGqHZnNIowlGm0eFhUIiKRkDv0xGJqHXcVWsIpEyEjJyyOllqsPcb6EwUCr8IMHN09G51Aan49+d7lIluRkkeTMnbGTk0lR5/ySuDi6NvWEIEOMu3+bTKLbNofT8Oq30UiKeCgkEp95P3t+FIWO8/lEt26nk86z20mp587aPp94JmYz3StXOGLPRHw8KfyBABkKHErG1ZCcTqVprjlkyGCgOY2Pp/vTaISSHhcnEuMBulZamuhYXlYm3iHOn0hMpGfCHq/YEDtOdGeFPpaWuREt8XiEgRpb5raigoxFi0V4I/jdZqM5N5fmQ1FEZatYYyihf/wZSyT9mj/PGIJl26vxwa97cPOJwxEf18of+gCl04ZFbm4uysvLkdKiZWhdXR1yc3MRiUS6LJxEIjm41HgCuP3f67F0G2k1p4xJxeNnj4PD3D/+KbZMjN5f/kOs56JlqFRskm1sQjZ3tGaFMLYCDyCU2IQEGqOujn6ONXTq60kZHTyYxo0Nu+JO1xy+xCvu5eXkZeDqVWo1rYj7fDQee2QYrZbG4x4YrJBnZZHM9fW0Sm80UtUkrngVCtG5Q4eS8aJWk2FTWUmKaU2N8C4AojIWh1TxvHEYFjWvo2M5lIk9CGYzKeecLM6ej0CArsFGltUqQro4n6S+noythARhKHLCd10dPcvCQpIpO5vmLBgUuSOVlaSgJyfT79y7hDteWyw05w0NdB2Tic7V62kOY/MnMjPJ6CgooHfMYqFtbDD6fHROrPHHJY1ra5vfA1NWJrw0DOe3VFfTvA4a1PzdTkqie8zIEIZja8nkfalxpUQyUJk2NBFjMmzYVObGP1ftxo0n5PW2SAeNThsW1DF13/9QHo8HRlkkWyLpd/y0owa3fJCP6oYADFo17p89Ghcfmd3q33lfoWVYU2xiNNMyIbalot/aqm9bMe2xybKK0rwCDyBKqBoMpMDV1JCCpyjC0NFoKJl540ZSejn8prBQ9GFgRTYxkWTdtImulZYmwmt27SLFsqFBrKIzXHLVYqFr8Kp+KETbDAaSzWqle+b5qaoixZrzSji0KDNT3E9CgkgQLygQuRuNjXQMK+9+P11HqxW9I2w2YUi4XCJHgQ1BTjjmZnucJ2A2k+Jst4tcAi6rm5XVvGoWJ4d7PDpEIsJz4/PRuJGIeMZscNTXiwaCbLRxorfJJOQuL6d55vyQ2DC75GRRFlhRhGLvdNJcDRsmvAX8/tXU0JixoWz19SR/dnbzd6+qiuTipP3YnitsrHJ4lUrVdjJ5a4nbnS2bLJFIWkelUuGqGUNw03v5eHNFEa6aMQRGnebAJw4AOmxYcBdrlUqF+++/H+aYT9VIJILVq1djwoQJ3SagRCLpWUKRKOYv3o6FP+yEogDDUy14/sLD+3SZvNbCnfR6ESffGnFxrSv6rXk0WNFqrSwnh+hUVJCix8oid0TmDsisfBsMtOrNyddcwnb7dlp9tlhILr2eQq7i4kgmp1PkBnDCNSuFGo1Y3SclurmsPCfsgYhGyQNQW0uKqd1OMnm9IjG8sZGMFS4xm5xMRkxtraiAVV9P23fuJM8QN4FzOumabMQpCn1xWJTVSr9HIiSP3S4Ufq2W5oxX8Lmbt8lEv3MIEodysQKsVnMuBTBqFM11YSGN2dAA6PXhJqWb79/vp/kOBkW/DO6VwR3PuWcGl8v1esVzr6sTpWo5mZ09NvHxdA8tw+N4nktKaDs/E4uFjI2yMvJGVVZSSBq/v1xK2O8no6KgQBiM0SjNET9vzmcBmodX7S+ZvK2/I9mhWyLpHk4bm47bPliPWm8QF7+2Gh9dM623RToodNiwWLduHQDyWGzYsAH6mABRvV6P8ePH4/bbb+8+CSUSSY9RUufDDf9ah/wSJwDgoiOzcf9po2HSd35lpadXP9sKdyovJwVs+PB949Y5t6GighTR9PTmsprNoh+C0SgUrUik+Wo5o1KRslhaStd0OGjM1FShkNXWksKYlETX4cZrHDJkMtEY5eWiKlJKCil3xcVoWm3nykw2m/BQcA6CWk3KsKLQfvYAhMMkS3k57ae+DmLuODG6thZYtUpUlKqsJAWZjRm7ncYrKRGJxC4XyRsI0HEej2imZ7OJZ24wkDfE56Prc1hPOEzHNjaK++aEZL2ewrDKymhfejrJ6HKRDGo1nRfrxdDr6bqRCMkzdCjJZLGQ1cMeisZGek7sEeB74wpcFRVCaWcjIRgkuWL7b1RW0jhsUHLeDRsoLcPj/H5huG7fTmMOGyYqd7Eyz8918GCaI85TYQOWDTI2ZKqqRBM99oQZjfsmkzNerzCG9vd31N6yyRKJZP9oNWpkJ5qxq9qLNbvrEYkq0Kj7bgRAd9Fhw+L7778HAFx22WV49tlnYWtreVAikfRpPltfhns/3oCGQBg2oxaPnz0Op45N7/R4B2v1s2W4E1dlYkXf76e8AIdDhLlwk7ayMlIkXS5SnjiRmVdx3W5SqMxm2l9VRfdjNgOjR9O9cFOzYcNIISsrI6WPS4OyTIWFpKg5HKS0eb3Ahg10jdgO3y4XKeB+P+1zOIRHoq5ONKHjHg1er8g9aGig65vNZLCYzaRUcnlYtxtYs0Z4RDjHQVFoXtio4dCehgb6fdAgmpuqKpG0zTkZNhvJy4nKXNFKpRJlebl/hcFAx7EyzAqvRiOOSU0VIUdqtWjO5/EIg6q6mq5vt9M9sNcpLY2OcbtpHvR6GoPmnPL8eOXf7RbGCIewcXiQ2y36e9TUUJlfnY7G5opYZWX03OLjRcUv9k5UVIhEcJeLvCsA3Ud5Oc01e8I43KmyUnhcuDgAV+5iA4ET/h0OmhdORucwp4oKOpefX2wyeWudvmMTt9sTNig7dEskXeO9K4/CEY8sAQCs2FmD6XnJvSxRz9PpHIs33nijO+WQSCQHCV8wjL9+ugn/XrMHADB5cDyevXAiMh2mTo95sFY/W9b/jw07sVop3r6qimTZuVOsQHNHZlZ0y8tJSXU4RH+C3btJYeVk3JoaEb5UWSkSZO12Uuz8fpKBY/Orq2lbTg6Nr1KRPKxwV1eTshaJiJCjmhpR7Yg9FKywciiWx0PGBUCKXkoKXZOvx96PYFAkD0ciJJPFIpR1tZquzwYE5yKo1cJjYTDQM+OGdxUVVGWIFc7EROHdYWOHjQqtVvQFAeh89s4kJJACG43S8eGwOJaVb5OJ8gocDvriPhlcVclspjEURbwH27bRfXPORWWl8Ka43UakpoqqUn6/KGMbF0cycyUrt5vOiYsTijU3BTQaRRO8oUNFvojLRR6pYLB5lSn2LnCVKv6dPT2RiPDa5OSIDt5JSbSdy/qqVPRO2mwif4RD59jI5ApaGo2oDsa5RgcqQtDePhoy50Ii6TwpNiMumToYb63cjbdX7ZaGxYFYsmQJlixZgqqqKkRbZIS9/vrrXRJMIpF0P5vKXLjhX+uwq5p6U1x/fB5uPL7rvSkO1upny/r/LcNOeMW2ulooYdnZpJyzEu3zkRJos4lxFIW+c2I1K3cmEymFWi0podXVwGGHNTdoMjNpvPp6OpeNq+HDRZKyRkMr4lyqliszcXhSZqZo3MYJzIoiVti5IVsoJMKwDAZSLFmh93iaJ1gnJtI9DR9O81ZX17xBHSAa8yUl0fW4Z0IkQrK6XKJ3h8FAim8wKMq8mkx0bbVaNO+z2YQBFQ6L/BebTeQ6hEIix8JopO3BIBmFaWlkJHKlLDYEUlNFmdX4eBqnoYF+r6wUyc0ZGXS8wRBBMEieo/h4EXqUnCzmg3NEGhtFbkluLs2FwSA8Xtwrgw2G2lrKeaivF+VgVSqRV+H1ihAm7n7O883VnQAyqIYOpePNZtHZmz1pbFxxbo5eL/JA4uLEc9Lp6DsbYQcqQtCePhoHq0O3TByXDHT+cBQZFos3V6LM2YiMLizi9Qc6bVjMmzcPf/vb3zB58mSkp6f36coxEsmhjqIoWLSiCI9+sRXBSBRpNiMWXDABRw1J7PLYPbH62ZayEQqJZGVWsmKrMnHdfi6xySv6nLC8fTsp/1lZtD0YpHG4zGh8PHk7OOSGV7+5bCon0nKHaTZoLBZaZXe7hbxWq0jm3bVLlIr1eER3bZ2ueUOz3Fw6XqMRiqLJRF4Kbpi2YweNw52zrVbaz4ZEfT3laHi9ogkeQPdis4meEnFxdEwoJMJ4qqtF7gdXeuKEX7OZrllWJjphswLKxgGXN2VvhF5PyjOHTNnttI0rTnGX7/h4Ur7dbhpr926RK8LzWVREsk2aRN8bGuj6eXnAunV0fny8KE3r92sQCIicg6FDSUaLhZT+ggJRRYoND4dDGIpVVaSgOxwi1IifJ3t0UlNFlSt+5h6P8LSYTHReNErjVFcLuWM9VomJdM2UFDqWjSHukA6IUDmA5oQV/+RkOq+xsbkBv7+/tQP10eB3oic7dMvEccmhwvBUK44akoBVu+rw7upi3H7KiN4WqUfptGGxcOFCLFq0CH/84x+7Ux6JRNLN1HmDuOPf67FkaxUA4KTRqXji7HHd1rCnO1c/21I2OPymoYEUZ4+HFBD2DgCkpBYWkhJrt4vSody4zu0WCdysWMfHk2LIJV7ZWGHPB4fO8FdcHK1Wm0y0yh8LJwKzceLxCEWJFf09e8SKs80mGvZxRSb2+CgKeQU0GjrO56Mxy8tpX0qKuCfOleAGdCYT/VxbKwwsn4+eA3tzABo7ECBZ2OPEPSYAsZqv01HITjBICnU4LHIJOGGcQ8w4hIuTv2M7irMnxOWi+VarScZIhIyDaJTuo7CQzueKVAYDeTH4PrZuJa+R0Uj3yRWVuOQqG5KcW8AJ19xzoqqKjBROAGclmxvOhUIks91Oz7uujoyRwYNpPhobhYHGngqTid47k4lyccrKRH4KGwPFxXSNpCQxj9GoqMrFVap27BB5NeEwfSUn0zxw8QFuLuhwiLK0anX7DfjYssntSfTubmTiuORQ45KpOVi1qw7v/VKMG04YBoN24Jae7bRhEQwGMW3aoVE6SyLpr6zYWYOb38tHVUMAeq0a9502Cn88anC3ehi7a/WTvQEtlY2KCqFEJSSQt2HPHrFyzj0jiovF6rlO17zRGpd4tdlISeN8g927SYmJVdy4ARvnHHB8PMfxu92kEGpb/PfkHhYJCaQg19YKb0ggIJqlsYwJCSQbb8/OpvE3bSKlb8gQOn/DBlKMOYnXYqExq6pofjgng7stc6IwV11KSBChUwAp8g0NdP98DzU1NIdWK43LuRNxcSJ8JzGRFOWSEmFARSI0dxzaxAZkOCwSiNkbwonRbCA0NooQNKdTeBs40ZzniHtPcOM6l4uUUs6bcLno2QM0BifqNzQYmsLxALofLn/L5WxNJjEvXq/o9REXR3ORnEzHjB9Pz7aoiPZxk0KvV9w3yz5sGM2VViv6WEQidE5ODt3Pnj30rtntIoRNr6d3y+Ohd9xioXNdLpKPcz3YW2ezkYHJdDR8qbVu820lenc3MnFccqhx0uhUpNoMqHQH8NXGCpwxIbO3ReoxOu3o/NOf/oR33323O2WRSCTdRDgSxfxvtuHi11ajqiGAYSkWfHrd0bhkak63GRVcwhMgJYzr/beEOy4faPUzVtngcBlWCrlGv15Pil5WFine0Sit9JeV0XW44tOOHaTkcX4Ah/yw54CTZdkA4WpL1dV03p49wgPDYUtpaaQc6/UiyZbzElwuuj+Tic71+2mcdeuA334jZTwSoXngVX6Ph8ZnT0dKilDw8vKAMWNIOeXqSRxaFArR2MXFNGcctlRdTedGIqTkshLNxkNdnaiYZDCIPBTOD/F6aR452Tghge45OVkouAkJtK+qiq7BuQQ6Hd0XV3diJZF7WvA8VlWRwdXQIEK+OJSIV9/tdnpuRqNI1vZ6xX02NNDzLSgQvTkqK4WXKy2NG99p4PfTdbirNxtdo0aJ0DaWedAg8pIkJtKzGDqU3rMxY0SIEnvmDAb6vnMnPQuAxtdoaK7Kymi8sWNp/jQaGpuTtx0O8f6lporz2OuUmEj7kpObd3UPBkXifFpa81V9NuC5qWFslbLW4G7z3HDP5aLvHILVUx6DjoROSiQDBZ1GjYuOILfnv34u7mVpepYOeSy4OR4ARKNRvPLKK/j2228xbtw46FrEQcyfP797JJRIJB2iwuXHje+tw8+FlDF6wZQsPHD6aJj1XarV0ERr4UocEtLZ1c9QSI2GBlFRiOGqSImJzZvAcadprRbYskX0X3A4SNHjMB1FIWVUp6Pzy8roGqzsVVRQB2xuTJeQQApheTkpjamptI0rKRkMlAeRkEDXCYdJWbfbSTmtrydlPS2NFMctW8iocDpFTL7PJ/IjtFq6tsVCx6el0c92u+jMbLfT/bHxwCvNHPevUtHzYC+KxULzHomIpG63m47hFWpeledVfPYo+P0iBIqTxCsqhLHi89F4Wi3NodEoVuxVKpHDoNHQONwbwmgUOQqct8IJ23FxNHdVVSI0CRDJ5kYjjcm9SthbENsnIhKhOQKEgVBRoTR5Z3JzaX4514EbzdXWivE4cb6+XpRw1etFDg975jweuh5XDuPSuZwzw7k9lZX0rOLiRFI1Gwd6PRktXHls926SLS2N3mNNTJSEw0HzkJpK887ytTTUOUG8vLz9OQvtSfTubvpS4rhEcjA5Z/IgLFiyHat21aGkzoesBPOBT+qHdEjT4OZ4DHfY3rhxY7PtMpFbIukdvt9ahVs/yEe9LwSLQYtH5ozF78d3X0xBW7HR7K0wmUhJaavMZVtwDkNLZYO3m82iUk4sHJ5jMJCyVldHiltqKsnHISq1taRwGY2kPHHYSX09fWdllEN+EhJEqBEnJHNTtWiU4u1tNlHeVacjD0JNDSlqycmkmNpsFHPPoTB6vfAg6HQ0j7ySzQo1r7iXlIjeD7zazhWFgkHRj0FRRPKwySQMEy5LWlwsVoBdLpHr4PeLFXFFofmJRmkMj0cowLzC7veL3ITERJoPNua2bxf5EIoiZGOvBSv/Wq3oNcEr0jab6Lnh8wnjg40mm01cs7hY5LdwQ7/YEr18D/xeRqMkk0ZD72hjo6jo1NAgEs7Z6wRQD4vMTHGN2lrRg6Kujp6Lz0dGE3t//H7yVPFqP0DnJSRQaJTTKbq0JyWJcKjMTBF+lpND9+l20/HcC4OLEWi1NBd6vTDk+D7r6kS4IHtTOpKzcDCrMfWFxHGJpDfIdJhw9NAk/FRQgw/X7MEtJw3vbZF6hA4ZFtwcTyKR9C1CkSie/HobXlm2CwBwWKYN/7jwcOQktRFv0EkOFBvN4RUdXf1Uq0U51VhlQ60WCb+8ssxwSIXXS0YEK5JcjpRX0H0+UtbS00np5x4BkQiNxw3xOImak7PtdrH6y92ZtVpSCC0WUkB9Pvq9ro4MLjaAgkHhDbBYyHjg5OiyMtF7IhSi8w0Gul5pKcmYni48AVxByGymscxmYUBxCVfu86DRUJhQYiKFFXGuB5e95fKnHC7T0CCeV0KCSNzmJnXx8SR3ba3wHgGiWlNdXfOmd3weN3PzekVZWE6YN5lEAjiXV+VqX5xbsnOnqDoVjYoqS8nJYuW+tFQkgbOXJRgkhR8AGhsNSEigMCbOPQkGRVdzXvVPTCQDhRvyDRlCxiC/uxUVolGi201z6veTbBwKZzYLI9fvF38THMo2bBg9Z34XIxHaP2gQHZ+YKMofB4Mid8RspmtwXxK7neTjQgZswANkVKSltf532ZdyFno7cVwi6U3OnTyoybC46YS83hanR+ie2AiJRNJrlNT5cMO/1iG/xAkAuHRaDu6ZNbLbq060NzaaFaz2jCfCIqJNeQdcyrWxkZQpTtbNyCBlxGQSXbOLi4UngkOu+FxW9rZsIeUsIUEkDXM51KIi2l5dTdfhfAYOXVGrSUa9nlaa2chwuWjclBShQDY20ld5Oe0bOlTkTyQmkmKp0ZBCywnbiiJktVhIqdy5kxq/lZaKlXarlb4UheThRmxDhpCCzrkH0SjNkcMhGqqVlgqjjJ3J7D3hVe20NJqHwkJSbllZbWwUx1VXC+8Fl6Hl6lBOp+gGbrWSIsv3p9WSQuzzCcORw4vYgxEO03wnJ4t3TKWi+airE2V6AeGBAOg8yqcQxiIbtWzUcblYft+4A7fLRc+CvRVsmFZUkKHBidGc0xEfT/KxoVVbK5or6nQ0h9zULj1dGDxczlZRRPWqcJhkKCoSRQk4+Z/LFrP3j3tlcFie0SjCoziPpry8bUW8Lza7683EcYmkNzllTBqsRi1KnY1YtasWUwbbe1ukbqfThkVsvkUsKpUKRqMRw4YNwxlnnIEE+R9CIukxvtpYjjs+/A0N/jBsRi2ePHc8ThmTduATO0F3xUa3zNGIRoHaWkPTav+2bc1XydkDYTCIJG3ukMy5AV4vKW3l5SLmPRwmZVitJqOEFUfupM0KKI/B1aV4vOpqsarPCiJXlTKZqOypx0PKa00N3QuHm3AJ1NRUUp5SUmh8j4d+TkmhcBz2CvBKO1c1Ki0V98nKpVpN16+qEh209XpS5LnELPeEGD5cdJTm7dyh2mwWFbO4WzUgciy43Cor9ty8LTYOn6tSpaeLHgp+P51jNIoeHtyngsdnYyM+nu4lGGw+v+zZ4Hvi3AfOYeDmgZyvwOdyOVuWjfIcdE1emlCI5OSwKW46WFtLzy4UovA2g0EYUZwDUloqKnxxnklODsnZ0CBKG7OBy/dhMjV/z9gI4NwaNlx5nrlTNzdltNuFN2PQIJFTwsQaCf0tZ4E9mwfqEC6RDDSMOg1OH5+Bd1cX48M1e6RhEcu6deuwdu1aRCIRjBhBzT62b98OjUaDkSNH4sUXX8Rtt92Gn376CaNHj+42gSUSCeAPRfDoF1vw5srdAICJ2Q48f+FEDIrvuWSw2NhoXjmPDXdqT2x0azka1IVaj+3bhZLV0CBCYzjO3mYj5Y0bl1mtpFRyrwBWUNhY4eZkQ4eS8s8hR2azSBTmsJv4eBovFCL56upEv4uUFLouewc4Fp9DtDjJOBqlsXhFnhVJDkWx2ylht6yMxmtooOPq6+lrxw7hBUhOpmtzU7TYTuPsscjMpDmprqZ5SE+nc1JThYLLijmHmnm9JCvnOfAxVVWiPC2Hp3AuCK+8azTCAFIUkTyelkYr6KxMcyWqSISuxfkj3DWclXP2qnAnbk7UttuFh4PP5fKqnKzPIXkGgwi9Auh3fi9DIXWTsREfT+9bdTUdm5JC71BpqUhy56ZznPRcV0ceMS45zPk1lZX0LqlUJAPn2HB39pISkiU7W5wbDotyyGyUsLHn95Ncycn0xf1AwuHmXor2/F32p5yF3kgcl0j6AudMGoR3Vxfji43luG/WiN4Wp9vptGHB3og33ngDNpsNAOByufCnP/0JxxxzDK688kpcdNFFuOWWW/D11193m8ASyaFOYY0X17+7FpvK3ACAPx87BLefPAI6Tc9qDpwUWlgouglzjDyHx7QWGx2rOMTmaHDlnKoqoLLSjO+/J0V7xAih0MfFCSVZpSLlbu+/GyiK6IpdXy/CdBwOUtxramgMDkfKyREKdl2dKHvKHoDSUrEqzmVIedWfQ264LC2vAHPcvlYrVua5PCor7Rxnz0oo50NwRSVFEbkZ7AHx+YSiCwjvhUol+kpw2JjbTYpwNErfHY7mydzcyyISofvgykfsYWAFl40azh/gkqWcAM33GI2Ke62qomulpYlwFjYGeAyvl55bZqYwlKqr6VibTYTqxMUJzw7fRzRKz6aujrwMHBqn04mEZQ630utFInUkAgBKk1LNCdMcKgeIXhmA6FUSDIqO63V19A5xCVyutORwUAiT0UjGnE5H8nMoGve54ORrfidY+eeu45yIrlbT9XbtojFtNnpXBw3av6Id+3fVn3MW+qpcEklPMTHLgSHJcdhV7cWSrVVo5c+2X9Npw+LJJ5/E4sWLm4wKALDb7XjwwQdx8skn46abbsIDDzyAk08+uVsElUgkwKf5pfjLxxvgDUaQEKfH/PPGY+aIlB69ZmxpUFY2OSwHIOWrspJCSWIjHznkqbZWhCG5XBTaweVPa2tJOWxs1CItja6xezdtM5tJiTOZRIUnnY6uwf0bOGY+MZGu6XTS99RU0bGYK+8YDGQ8lJSQUseK3ODBdGwgQPLw+TqdCK3i89mTUllJY3PegcFAx3IpVbdb9IXIzSVjiQ2NpCS6n4oKOi4tTTSos1jo/pxOGovj/DUaWt2tqxMdxQMB0WmaqzQFAiSTSiVCfPx+umf2QJjNJAsnUHO4GXsVOGyHnzl/5/4NvF+EsYkcCY6T53C0YFDkBLCByAYMH8dJ3Vwdy+ula8QaLzxObHgYd/nmlW72wLDhEwhomvpl8PPgvIvqapHDwPe/e7fol+Fy0fw5ncKY4MaAnN/DFawURfRD0WiEt6m6ms7TakVFrvh4GjM2+ZsrmtXUUHjd2LH0zralcLdV7hmQOQsSSX9ApVLh9HEZeHbJDvxvQwXOSuxtibqXThsWLpcLVVVV+4Q5VVdXw+2mlVSHw4EglxmRSCSdpjEYwYOfbcL7v1KcxZG5CXjuwolItfVcMHJLBYbzCAYPFsoVVyTi/AJeAfb7KSyoqoqOaWwkZZwbh2k0tC0S4YRqHSorSeEsKxMVelJTSRHn5OCMDBobEOEkgQAp1pygzCvFbjeNwcnme/YIOSMRWoXmJmNOJ12bQzM4n8Jmo/tXqYRCy7kfoZBQNk0mEedeWyu8CSzjjh3CAODSqLySHAyS0qnR0BevnDc0iLnmfgwNDSIMijtcu1yi9GlpKV0jM1OEh/HzCIVIWeVwKLVaVMji0CYOYeK8BK5IxOVyOSzJaqUxwmFh3PG7wEYL97vg+ScvgkjcDgSEF4YbDHKlqbo60fuC77OgoLkxodOJPIXYJHOtlitORREO0/tUX0/vESdH19aKHhtsNPG87N5N7y0bm+vW0XympIi8Fn7OkQhtz8ykeddo6Bnw3HE+RTgsvG2lpeLda2gQIWjsrWCDr62/ybbKPXN+S2fKPfcEMsSpbyOfT+8ye1w6nl2yA8t31uKUAZZm0aVQqMsvvxxPP/00pkyZAgD45ZdfcPvtt+PMM88EAPz8888YPnxg1umVSA4W2ysbcP27a7G90gOVCrjx+DzceEIeNOqe6xfTUoHhfIFIRFQRio9vngDNq7+cZF1SIprmcU6Bx0OrsgApmOEwKWZ+v7qpcZvJJCr8NDSI1Va3W4QJ8Uo+h8BwTLrdLjwLHMPPH5xsQPDKdWYmJTlzDgOH8XCjO4dDhBj5/bTN4yG5+XiAFFQOs/H5xGo0r8xzOJfbDeTn0z2o1WhqCBhbgpQVcs5r2LVLKORcujU1lY5hZYC9E1ye1GQCVq4khZXl4bAnNjC46zXPIVe+4upLgYBoEMdJv+zFYIWbE5A58ZqV6diKTRx6xnkgNhuFD7EhEgyKpHkuHczfLRb64rAvlgkQuRTBoPBscKI4h58ZDEpT+VYuO8yJ0PHxNGdVVaKql81G1zMYyKPldApjsrqajtFoRII3QEbshAmifwhXX6qpEYn+er3IlSgspLnPyhKGFBuWdjsdX1tL89mastdT5Z67k9Y8Kgdq1Cc5eMjn0zfIS7ViRKoV2yob8FudCuf0tkDdSKcNi5dffhm33HILLrjgAoT3FhHXarWYO3cunnnmGQDAyJEj8dprr3WPpBLJIYaiKPj3r3vwwGcb4Q9FkWw14NnzJ2DasKQeuyavYlVUNFdgOISFS2E6nc1r5nOTtmiUxtizh5RDt5uUNG4uFwySYREMUsiH08l5BirYbCLuPDmZFCM2BBSFPgxdLop55xCaUEh0mlapRHKwopACyQnWVisbMGK1OClJJH9ziM2ePWKFvaaGFEKLhZS2PXtoOzcmi+1PUFVFsnPoCSu73PgtEBCJ1rw6zeE0rPyzYcNlfTl3wGAQRgcrzYmJIqZ+8GCa96IiYbxxIzwmHBbnxxoKrFhwoz1Ovo6trKXRiLAnQBiSkYgIcQOEB4tX9Xk7K+FckYtD6NgQtVpFYzirVRhhXJ2JQ45YceeEbK2W5ovzQwBRDthmE7kxWq3wsDQ20nMaMqR5qWDuWs3zyjk1KpUI0fL5aN+gQeL9VKvpb8VobN4ckqticWUsLhnLc85/M2ykWa30Ph7ob7M7yz33BG15VNrbqE/Ss8jn07eYPS4d2xY3YF1Nzy0S9gadNiwsFgteffVVPPPMM9i1axcAYMiQIbBYLE3HcGduiUTSMTyBMO79zwZ8ml8GAJiel4Rnzp+AJEvPLEHGrmI1NorSpyaTCDfhVXRONI6tix9beaaxUeRPcIgLh3iwwujzkRLOuQlut76pig6vxsfHk9K3fr0I4zEYRFlQTpBuaBCN03w+ui4rtVy61OMRDfPS00UYDodicagPNxHjngkNDTRebNlVju5UFFLiuDrRzp10L7z6zDkJ3MGbPSjs8UhIoI7VXM3H4aDrcl6ARiPuRaOhMZ1OOoarCHEyuMMhelawbIBQvDmkiXMXNBoR9iRyEuic2NKlGk3zcq6cvO1wkNwcFsZKcqz3ABDX47nmVX+PR5T4ra8XRiLnsHBYE3fRZuODvVMcEsX3wo30uMIUhWOpmhrnsSHE+S+7d4sqU3FxZJT5/XRedbV4b3w+oYAlJtLPHo/IJykvFyFZdXUkw5AhtM3tJmPBZhPzNGwYychd1Ln4AXvaampEqd2WtFXumRcDYvt49BYH8qj0pUZ9hyLy+fQtThuXjqcXb8d2lwp13iBSHW3UjO5ndLlBnsViwbhx47pDFolEAmBjqQs3/GsdCmu80KhVuO3k4bh6xlCoeyj0ye+nkJvGRhF+wo3ZIhGRh2CxkNJss4kkWSa28gx3r3a5SAGtrxe19FkJBsT1SOGMQqejDziu+sMr+tEohY7Ex1OeRnExKW3DhpGR4fXSsTt2iGpHLFtSkkhKHjxYeCu4IhXfG/fECARIOeeKRtxlmcOaWLHl0rTBoDCqEhNJDl79A0SIUWUlKazcp8JoFMYK/85Jxo2NdH0OBWMPiVYr5pGvzQab0ylCiPR6+p0NgXBY/Mz5BAwbFJxnwSFTbISxYs4hRnxdVsJ5bvg6gAhX4upH7FHgvhWcjA2QkcVzwJ4RDiXj81heDnfjsCZWzBkO6eL8HUVRNfUy4RA7ftYVFdQvRaejDupcOre6mp5fYqLo+cEdxJOTRRI354mwLHwMV6ZKSRHX5bwYjYaMDrsd2LiRjo2LEyGBLheN11Y1qJZlZf1+YWjGGh2Zmb3jsWivR6UvNeo7lJDPp+8xJNmCUWlWbKlowDebq/DHabm9LVK30CHD4tZbb8Xf//53xMXFtdkgj5k/f36XBJNIDjUURcE/V+3GQ//dgmAkigy7Ec9dOBGTc3qupIvfD2zeTDkRHFLEJSu5EhOHPXFH6tpaoWizchxbeSY2VIarDfEqM5ctTUggJZtXowMBpalbM5fx5CZlrIBVVdHxOTkiPj4jQ5Tb5PKxfA1u1BYI0P3V1NDxXq9I4OXeFgkJoskeJyVzKVmdjpRi9rKEQqS8JSTQuDYbrfRx2Vm9XoTZ8PGKIio4seLIx7JCX1srFHUu7cq/s+LIBgCXR925Uxgj3AxOpxMlV1np5+ZunEzecnWbV/7ZAAmFmvdFYIXc6xU5AXtrdDRdj8dgrwbQPA+ES88Gg81DjhISSBHmErKcxFxeLnJOOByKjSr2vvD1+D1jQ4MqYEWb3kWDQTQ+LCkRz0OjERWbdDqRD8O5HzqdaBbIxoTPR+8n97Xg7ykpdN36enrvcnNF+BPnt+j19A42NgoDi40ltZoM6LZ6O3D1qNpakpP7p5jNooeGWk33xTlFB5PuaqAp6Rnk8+mb/G5MKrZUNGDJ1kPUsFi3bh1CewNm161b1+ZxqrZKWkgkklZxNYZw14e/4atNFQCAE0el4qlzx8Fh7rkK1+ypKCsTZV25OzJ/wHB4DjcvS0ujMBKNRiivZjN5BliR0enEii2XiOUOyawocUhVKETfXS5dU/M6Hpuvy4nJRiM1u3O5RJUgjYZWn7mEa1qaUDAtFpKVw2k8Hjq2rIwUP7OZ5HO5RFWonBzh0cjJAX75RZRgZS8OQPfGuRdckQqgcCzOh1CpROfrmhrhHeBwKYeDxlCpRPlcfi6s/LNSyoomzzHLU1MjGtPxfHFVJlbweTWeic2x4LH4O98H5wFEo8JTwtW0uHoU51Hwij2HS7FxwuezbFw+2GYTRk1VlfAAcflVk4lLEIsSvZwjwtdnWaNRGlelovPMZuHl4QRom03kPvC7x0nb/A5waBZ74uLiRAPGmhoyfriSFHtS7HZxn5y8bjLRu5GdTffKRgGfw+//0KFkdHApZg61MptbT6xlORsaSB72eAweTONzYYO0NBGKeLBDWrqzUZ+sWNT99NdGigOd40cm45klBVi5qw6NwQhMes2BT+rjdMiw+P7771v9WSKRdJ71JU5c9+5a7KlvhE6jwj2njsJlR+f0uIFeVyfCkbgSk04nkqy54RevdHEfi+xs4d2oqxM5E4mJpICp1XSM200eAS67yUnUCQmkoDmdQF4ereBv2xZtMjZ45bq6WoSK+HyiS3VDg8ibKCqiSjsGAxkXWVmiXOmWLSS3zSaqCHGSMjdHGzSI5OJQl9RUCqni++a8jlBIdGd2u0khVBQxf1wlqb6e7o/zVDipnJVaVvw5ZIu9KaxI8mpi7Kohr86zUs2r7PxcOH+Cc044zIhX2ltbgeRXiz0YrCCzUcZN29gbAIiKWZxnEFuClg0K9qjEwqFp3AuEq1Kxl6GxUYQx8X1w6dfYOQgEaK61WhGmx+9rrLeEZYgNz4oNyWIj0m4XnhlOag8ERDhWJCIa9WVnk0LPz4a9LmywciM/v5/e05SU5h6Dlk3quOt0YqJQoBWleUgiy8d/Kw4HvVvsrWpooHefK05xrxCuONbRkJauKvPc2LArjfpkxaKeozuej6T7GZFqQbxeQX0wip8KanDS6NTeFqnLdCnH4scff8TLL7+MXbt24d///jcyMzPxz3/+E7m5uTjmmGO6S0aJZECiKAoWrSjCI19sQSiiIDvBjH9cNBHjBjl6/Nocb8sGQjgslFru0cAhNhzzzpWUzGbKQ+AeFayUcafroUNpXL2exi0vJ0UuHBbKdGIiMGoUnVdeDgBqjB7dPCeAm8mFQiIpl8M9amtJkeLwIq7axM3HVCpS+LhPRGUl3c+QISLUimPxfT66F1aSCwtFAi97brjSEB/HDdAA+m42i6ZmFgvJUVMjqkexksyKa6zhxivsbIC0BicqNzaK8Tip2u8XSdqxRgSvQALNjYDYztk8Nh/PeQgtQ6K4JKzBIOaFk6s5fyA2PIk9HqzYswHBnopwmJ5Nejr3MREGBtC8qhQbOlyFSqsVSeBWK823TkdzHtspnJvo8XvEOR8eDxmRnMfBPUh41Z8T4vlnu12ULU5PF53Ly8uFkR0I0DjsofN46H1hL1dbTepYiWstJJGLBbCyzcn/3DsjK0uUwY1VCDsa0tKdyjwb1Z1p1CcrFvU8XXk+kp5BpVLhsHgFP1aq8N3WykPbsPjoo4/wxz/+ERdffDHWrl2LwN5PTpfLhUceeQRffPFFtwkpkQw03H4KffpyI4U+/W5MGp44dxxsxp6tCsGKFyu4drvoNGy3k3JRWSmUTA7X4SZfcXGk1JeUiBh0ViQjEdrOSqTbTWMmJIheABUVdM7EibR9925SwqzWYFNZT1Zkk5PpA5CTW7lsqVZLcrIXgGPPq6ooRIRXalkBt9nEhygrqLt3i5V0XtUvKaHwKpeL5iASIRnr65s3wONSrNwzghVeNgqKi0WpXFa0AVHxiD0MHC7Fq+2shLcFh1JxCVhenWfDi79ivQaxJWcBYcC09CrEXoPnI1aB5ypNHo+4Ho8HNH8HOK+hZWUnvmf+4rAjTpJmA4MNH1Z6uLQsK/dsOLBcbLCw8calXyORMKxWYUBrNPR+Wa30TnBncjZiNBqSIy6ODAbO9eDyvenplOjt81FuS0mJ6DgeDNI4iYn0xV6wjAwyahISRHhWS49AayGJXi9t4xwds5kMXrNZeH04J6mmhuSwWIQxw/NxIO9Ddyvz3EeDDZWONOqTFYt6nq48H0nPMSZBwY+VwJItVYhGlR4r1HKw6LRh8dBDD2HhwoW45JJL8N577zVtP/roo/HQQw91i3ASyUBkY6kL176zFsV1Pug0Kvxl1ihcOq1nQ59arkq6XGQgpKXRBwonAtfWCoWde0RotaKnQH09HcsKqNMpVs4dDvp582Y6LzOTFC5OMrVaRdJqfr5IeqVE7QBqakRHar52ZSWdzx2ZWREFSOEwmYTngVf81Wo6lhVjTsqNjxchS7t20b1wJ2buNcAds1k5c7lom8cjrsFeCC6Jy0qc0ymU0+pqYbhwGE7LnzlXoDUvwv7gc2MrOnH4E3DgcfZnWLCBxEZYrEcktioUwwZRSw8IG6KAqGjF57Ghxcnw7Alh2Thfgz1XfDzfb+zcsZeNG+6xl4EU/QiSk0V+D+disBHq9YrCAvX1dJ2yMnqmycmiFC1XKxsxguRJSqLxy8ro/eRO5DYbhfYNHizyZnjlf38egZYhiewRYc9YJEL7amvpmgkJZNSUl9O76/OJ/CV+HgkJ4p73533oCWWew7w6ElolKxYdPDrzfCQ9S55NQZxeg6qGADaWuQ5K1EJP0mnDYtu2bZgxY8Y+2+12O5xOZ1dkkkgGJIqi4O1Vu/H3vVWfMh0mvHDx4ZiQ5ejR68auSnJoUmUlKScAhSTpdCJx22AQFZzcbtFjISWFzisspA8jVsBZUS0vF+Vihw4VSdtlZWI1PzFRhO1w+AmVpzVCo6GxOfmbQ5xYceWqOiNHCsW/slKUBOVEaW5K5vEIrwVfr6qKjmOPRFycyAWpr6eEbc5NCAREDD+v1nPZVE765lK6NhvdazBI3bxVKvJcsMIaDosKQKwwcuWnQKB5+NCBiC392t5zGD6eczViQ5VYqedcCX6u0agIU+JrxlZh4u2tXYerE3FIFcsOcElYMQ73R2EZYnN7tNrmY3MHbJbVbicFOhIRyes2WxgJCSI3h8O5OGFcqxUhWMGgUGrZo8XzkpQkxudmhvHxJHtZmfCCjB1L+Q6swCcmivebQ6U4B4I9AklJ+4Ykut2ilLBGQ3+7fH5dHeUAqVT0N8KllhWFxuaKUYmJzfOSWvM+9LQy35FzZMWig480JvoOWjVw9LBEfLO5Cku2VB26hkVaWhoKCgqQk5PTbPtPP/2EIUOGdFWuNiktLcVdd92FL7/8Ej6fD8OGDcMbb7yByZMn99g1JZKu0uAP4Z6PN+C/v5UDoKpPT587HnZzzzfEKS+n1XStlmr3c5Kew0EN2lavJgVn/HgRepKaKkpbslIe29m6ro5WdbmCUkUFhWTU14tu22lp9HttrUhwTUgQoU5+v6h04/drmkKy2IjghGmuTMUKFCvj3MyME8+5ogmH77Cnwucj5YxXfRsaRJgO94rw+US4VkKCKDPL3gReqdfrRbM9zqWorhbJxqEQ3TuvjMc2oYvNc2CFnZXsjhoIrKR3Fk6WZloqbFxelb0VHHoUaxxxQjw3yIsl9ncOb2MPBCeOxhojnCweKwf/zvOl1Tb3VBiNomyv2SxW7Nnxx6WKOdnbYGgemlZfT99tNmE8KgqNpdeLa3i9opKY3U5jVFaKeYmLo78XLinLHhidjv4u2IB1uUS1MoeD3t+amuYhiTU19J37UPB97dxJf6NeL71fI0fS33BdHd1PXBx54aJRuh9u3qdWkwelNe9DX1LmZcUiyaHOsXlJ+GZzFZYX1OCWk4b3tjhdotOGxZVXXombbroJr7/+OlQqFcrKyrBy5UrcfvvtuP/++7tTxibq6+tx9NFH47jjjsOXX36J5ORk7NixA/GxflyJpI+xucyN695di8IaL7RqFe4+dSSuOCa3x6s++f2kXGzbRh/KRUWkRA8bJlarsrJEadetW0UVnKQkUqaiUTrP4xGr5KxYq9X08549NC6vAFdUkCKzdauorsQJ4BwWlZUlyopSsy9Nk1LEDdNYeeWxWRmrqhKViTjZm2Pdo1HRKwEQq8VcEaq+XignOp3oJcBKIpcl9XpFj41YxZhDdGIrQ3HeA1f4YYWZFXO3u3mOCBsVLRu8dYSuGBXAvh6GlnB4V6xHg402zvFgLwSwr8eFj4s1FmLDt2I7gHPuBffrYIWXDQieOy4AYLHQeNxIkJ+XzUb7EhPpfA7dY4+VRiNCptiw5Xtj5Zq9cDabaEKn09G4nDfExi+HLnFIHzfcS0kh4zQSob+NlBRhAHEjPL9feBX4eTgcIkQxIUF4ilwuYQyxscQd2g0GMha4wz17RRSF5mTHDhq3Ne9DbyvzLUNxulKxSIb1SPo7U4dS5nx+iRPeQBhxhi7VVupVOi353XffjWg0ihNOOAE+nw8zZsyAwWDA7bffjhtuuKE7ZWzi8ccfR1ZWFt54442mbbm5A6OhiGTgoSgK3vulBA9+tgmBMDW8e/6iwzFpcPcYwvv7MOXwJ47757AkbqSVmCjCVGKTVC0WUa2orEzkMHBybWwyLivqfHx1NSk4HF5SW0uyJCUJr0IwSMpZVZVQTH0+oLra2FSlh5NwOSTJ6RQhJFqt6EXQ2EgKEyfF8sowVw7iYzhEhnsVxIY5sScmMVF4HTweMSdqtQgx4cRtztPg5nrsReHGezx33GCPDavWkrN7M7QjtuRsSwKB5uVeuddCbA+JWOOkpceFw7xit7M3IbbhHydps0ER22CPf+cwKM7rYYOA+2N4vSKfRlHoHaDcIKXJW5aTI8Zk44HfZU7Cj+06zhWiODensZE8Ag4HXcNupzE3b6awKZNJGAp+P/0d7NpF95ieLuaaQ+s4d4cNAfZScM5HURHdj9NJ7+GYMcKY5T4iLCuPbbeLa/M8c/W0MWOaN0QEeq/8aFtVqMzmjlcskuVpJQOFrHgzshJMKKlrxM+FdThuZEpvi9RpOm1YqFQq3HvvvbjjjjtQUFAAj8eD0aNHw8LLST3AZ599hlNOOQXnnnsufvjhB2RmZuLaa6/FlVde2eY5gUCgqWIVALj3tosNhUJNzf4k7YfnTM7d/vEGwnjgsy34bG/o07HDk/Dk2Ych3qzv8tzFfpiyYdHyw7SykqstkaLBHgDOD3A6RfWamhpSILg6iMdDPSA8HvIsAKTUcFhSURF94Dc0iDAnt5t+b2ig3zl0hstmcvgMf+dytZmZQEpKGC5XEFptGOXlJF9cnGhCBtDPDQ3085AhdP8AKSIcZsUKKxseHGPu8dCxbBC1VK64rwLH9odCFOaVmEgy1tbSdm54xk3p2NDhpPXYKk2BQPO+Eh0NdToYdMTrwV6b9p7DZV5j4RVyDkNjAyU2iZ1Dz9i7EWsk8uo5G3IcysYGttMpOnQDYahUUUSj4SYvm1ZLz5RzC9iwNRrpfeNqTG43jeNw0PEWC/3udtPfE5f9ra8XngynU/RgcbtFrgcXLGipuOv15E1MSKBQpYYGMlLUauqtUl8v8ieMRlFNDaAQQ64eVVgoKrixNy89nX5no6m8XHhS+P1mrFaSl0smszLPuVZWq3ifu8MjwAse3DGc//6qq+nnxERR9a3l/zY2BtszltvdM+Vp5eefpLuJfaem5iagpK4UP26vwjFD+1YkTkfeeZWidNWpfvAw7v0vceutt+Lcc8/FL7/8gptuugkLFy7E3LlzWz3nwQcfxLx58/bZ/u6778JsNveovJJDkzIfsGi7BpWNKqihYHZ2FMdlKOiOCnLBoBq1tUaEQhoYjWFoNAoiERU8Hi00GgVJSX7o9VFUVZmg00Wh1Sqor9ejttaAqiozDIYINBoFfr8aBkMEVVVmOJ26JoVxyBAX9HqgutoEt1sHlQrIzvbA4QjAaAwjGlVh2zYHqqtNUKsjKC21wO/XQKulARoadPD7ddBoImhs1CASUUGn438xKmi1YSiKGoqiIBjUwGoNwuEIwWIJwePRoqrKhFBIvbekaxjZ2V6oVFE4nSaEwwpUKiA11Ye4ONLU3W4dGhp08Hq1CAa1AFTQ64Pw+/VQqyMwmcJoaDAgElFBr48AUABoACh7w2wURCJqaDRkbahUCozGEPT6CKJRDZxOPQA1NJoIolEVABUiEXqQfr92r0GjwGQKQa2OQKNRQ61WoFJF4XYb4HbrEIlouv7gBwAqlQJFUUGlikKrje41Euhd0GgUqFQqRKNRBAItg/6jAMhKUatpDJ0uAoDODYfVMJuD0GoVqNV0rMkURlqaDz6fBoGAFhZLGCZTGJGIGqGQGl6vFg0NWjQ26qDVRmEyRfbKpkCvDyEcViM+PojBgz1Qq1Xw+9Ww2wOIi4uivl4PnS6KrCw3VCoN1OoofD4tTKbIXsNShcTERgSDWgQCaphMEdjt4kO5sVENr1eHqioTMjM9SE31o65OB59PA6NRQTSqhtOph9OpRThM45pMYeh0ClwuHXS6CCwWev/r6nQIhbRwOAIoLLQiHP7/9s47TLKyyv/fyrk65+mZ6ckMMGRRUWAlG1bFdVVQUQFXxASLORB0F8UV0f2pqLuCqOiakF11VWQJogjIDBkmp865cq77++Pw7fd2T/dM5zBzPs/TT3dV3fve91ZX3XvOe8LXgbVr43C7LWSzLni9Jfh8ZZTLFpqa0li9OnHA/yWfd774vXWjXHbA6bTg9xcRicicJ3rN6516uG1gwIdUyotw+EAjJZn0IBTKo6Ymh0LBOeJYeDzjH2eyYynKUmFzvwPf3+5CS9DCx45bXKtR6XQaF110EWKxGKLR6EG3nZFjce+99+Lee+9Fb28vymNi+t/73vemO+yEeL1enHzyyfjLX/4y8tyHPvQhPPbYY3j44YfH3We8iEVrayv6+/sP+eYoB1IoFHDPPffgnHPOgWeiqr8jmJ9v7sD1v34e2UIZDREfbnnLJpw8w9Qn+2rhwIBR4eVrw8OyssnnW1pkxa6uzqSO9PSIxkM8LquC7MHf3S2rk7t3y4rghg3yw9SewUGJELCbU3u7FJJ2dcmcurtl20DARAkAU5htL6Zl6hEF1Zj+4XAUkctlUFUVQCLhHkk1crvlHJiOEY/LWGyRC5jOQL29MjemHnEFOZcbXTTLwtpMxrwOmFVlpt5w/tTusCwZp1g0ueyAWV2ncBnrBjhOR8fo9qxHGuw25fGY/7+9E5S9U5Rd48O+P6NRfJ5pQIB5v8NhU0gtqtxFVFYOoaqqCqWSG+Gw/L9ZB9TfL5+RoSGTCsfidHY8q6+XFKKVK4Gnn5bvwcaN8jnLZKTzGVOvUqnRInytrfLdYLoTU5OGhyXix8aJRx8tc+rqMvUaFRWm6xjreBwOiWxEo/KZAuR8enuNHodlyXeF0RFGYnI5iWLU10vL3IkiDqwFcrvlOGMjAmOjGfaIwGQiGrmcnDt1Z8bCNMiVKyfXnna2xpoKev9TZhv7ZyqeK+OlX3oAAPDIJ85EdWicD/cCEY/HUVtbOynHYtqpUNdffz1uuOEGnHzyyWhqaprzQlQAaGpqwsaNG0c9d9RRR+EXv/jFhPv4fD74xrmyeDwevTDMAH3/RpPOF/HZXz2LX2xuBwCcvq4OX/3H41ATnv5dbWz+cKkkhlBDg9zks1kxKnI5MSCCQTFwhofFKGFvfRp15TKwZYsUVbODUXe3jBOJiHHV1ydGU1OTGPWWZQyk/n5Ty0Bjx+sVg8ReFMux2UaVaVHMYWc6C41OSXFwIpt1w+2WzxRrGwoFOZfGRpkju0Wx7oLb+HxGhKy93RiqrG3gj8cj7xEL1pm/z7mw+Nr+wzQcQOadzxuDlk4Vc+OZ589UsaUTD54b7JcIFkmztoHvo73eYmzKGNer2MWK2/BzxP8fa0CcTjGuRYHdhWzWjWhUJsHCZaY2DQ7K54epWXYlcWqYDA/LD7s2Mb3IrrtRLBrtB6bfcVyXS8T2hobEEGaqHztkPfqo0amoqjLCd4mEGMWhkHznXC75DnDc/n459tq1sl1vr8zN7zfOPeuNmptlO34fx162x6tToGp5qSTXAeL1yrisrWJDhsnUOFBrg3oiY2Hb4vHmOJaJxqKDw7S5yYw1HfT+p8w2Ho8HjUEPNjRG8EJ3Ao/vj+PVxzYt9LRGmMrnfdqOxa233orbb78d73jHO6Y7xJQ57bTTsHXr1lHPbdu2DStWrJi3OSjKWHb0JnDFDzdje28STgdw9Tnr8P4z18xIPXM8Rdx4fHQx9vCw3EhZh0Bjt7ZWjIuuLnEsALnJr1snY913nxSc9vaaVpcNDWLcJJPiXPT0yBgsjO7vFweDgmzM6eZqrT3/no5FuTxaPI2FutRBoLMhXXvkokUniAJ0brdpNVtbaxwgFlLTUdi1y0QNaFzQgAOMYcq5AaPHp4PDWg77vHkeNGDs+g58noXirCtge9oj3bEATI0EBQy5Ks5uUIBxFOzQOKSTyqJlisjxMZ1G1oGwi1OpZKGpyRi/rPtIJo0IIGsR8nkTMWD3KHZK8/vF6O/tFWV26lrEYnKc9nb5nrE1MyMJxaKMSdFGFoP39Jh6JsuSz9vu3fJ9bmsTR2R4WL5zrC2wt/mlw9LaKts7nXKt2LpV5kGlehY9NzaaOp+x7/FEyts9PXIdWL58/P9pKGSiPozaHEq1eza7UI0dK5s1kVt7G92WFhNdVJSlwCkrq8Wx2Du0qByLqTBtxyKfz+PlL3/5bM7lkFx11VV4+ctfjn/913/FP/7jP+LRRx/Fd77zHXznO9+Z13koCvnl5nZ8+q5nkCmUUBfx4etvPQEvW10z43HHU8T1+yXVaWjIFK7aeyVwFc/plFXKvXvFQKiqMjd9p1PazcbjYqxVVVFHwqTssLh7//7RGgFDQ2Iw+f2ji1gpYmZP+aEByJVZGpZOp/xNo5ypS3ydqVPUjKipMQ5FJGL0OCjuRkVszqVYlHNhcS4jKzTweZxw2LQypUPBrkGplNFNYKTILizHVXQayHzPeK6ACnkRRiLo6DFqMVZHwx6tYPSIgn2E/yN+zhiRAkzkip8b6QqVw/HHS+peLCbHZAtdtice2xKXTgwgn/tEQhoZHH+8iVQwpYlRj95eeY0F/0zb4/eVET3qX/h84hRwThTYo/o7U54YPbMscQ4AExmoqpJULC4qsH1uZ6cxzvlab69Jk2QrWxr8EylvR6Oil8E2vmOhsxaJSHTTvu9Eqt2z2YXKPhZTMpmyxc53Tqc4P+x+pyhLgRNXVOIHf92LzfuGFnoq02bajsVll12GO++8c840K8bjlFNOwV133YVPfvKTuOGGG9DW1oZbbrkFF1988bzNQVEAIFso4dq7n8V//W0/AFHNvOUtJ6AuMvOE3okUcWk89/TIjdThkBW5igq5eabT5m+vVwwdv9/03WfbWKdTDI1AwKQy9fcb45i1EjSc+/vNijx1Gbq68GKBtRg6NAZo6Dkcpp8+UyqA0f34cznTAtPhcIw4ANQnYOpLVZWJLDid8jo1KwiVr7m6y3FZA0HKZVNDQUeMq8CsK7EbwmOhAczzoVM1VqtBEca22GXtib1t8UTNRuj08T2lkwKMboXLlDQ6HnQcKyrSaGqSiAKjW3QmAfP5oLp8sSgGKZ0eOinDwxKpePnLTdpRZ6c4B83Nsqo/OGhSlkolcTDY0Yjpc5WVcvzGRnMMOg+hkNHeYGojVeV9PtmHn9FcTiKMdBwA+T5s3Ci/+f1JJIymCzu62aMJDsfEytuMsAwPiyMy1thPJuU71DTBgupEqt3V1VNvKTsRHGvvXhmjpsZozITD8p5lMgc6OIqymDlxuXj5z3bEkSuW4HMvveYfU3Isrr766pG/y+UyvvOd7+CPf/wjNm3adED+1c033zw7MxzDa1/7Wrz2ta+dk7EVZTLs7Eviyh9txgvdCTgcwIfPWosPvmotXLPR9gnjK+JS3RoQg2Jw0Kwasq0sV+aoQUDdCjoDLFIdGJAfCnv5/SZPOpWS30zpYCHp0JARKmNBLefFdBSv1xRT88eyZHwaiPY8dnur0ULBMZLCxGiMxyPnwfaujY1iPHHFu6NDHJxs1gjaZbOmpSmP7/WaYwOmbgIwjhGLPZkqNVnnwG44250mZXzGRn9c49wzx75/dP74tz2yQW0NtqClZojk+1sYGpLP8DHHiEMAiKOay8l3gOlr/GGUhJ9TwIgmxmLipLjdUgTNVfC6OpNCl83KZ4qf4T17JALBsahWzs89o3nUi6HjzPeKDjjnnsuJQT1eQ0O/37Ri3rFD9rE7zsPDYnDncnK8qqqJlbd9PnFEOjrG/zyzDe5E3eUnUu32+8Wp4fWGDR6qqqauPeH3SzSTc2QL6IoKmTu1b8ZzcOYaFexTpsvy6iBqQl4MpPJ4piM+a7pX88mUHIstW7aMenz88ccDAJ555plRz89HIbeiLAR3P9GBT/3yaaTyJdSGvfjaW0/AaWtqZ/UY4+Uis56irs4UC6fTpkA4m5VVTArP9fTItg0N4lTYuzwND4sh/dRTpm8804n8ftNDPp+X57myCpi/6RTk86aDEyMQrMFg7QGNdxprNATpoDDlhDnkNPBotLM2g07SwICM2d8vq5Xcx+OR+abTpvjULrZmN3LofNAAotM0k2gDjVtlclDX5GCMVfOmMU5n0a6JQacCYC2SF9u3y2faXptBnYlSSbbj/vw8UNuCgo1utzjufX3y2Wtrk7FYh8RicNY+rF5tnAvWIdBhqKoyaYeWZYrDJcIivxl1q683qX21tfIamzEMDJjmBXb8fvlOd3bKtpYlRrZd9ZtF7zzWRDUP4bCMF4+biA+jC4GAeTzevsmkKYgfW+Pg90sEYTaMb69X3htGR8eONZGDM1eoYJ8yUxwOB05YXoU/Pt+DLfuGDn/H4r777pureSjKoiZbKOHzv34OP3pkHwDg1LZq/PvbTkB9dPbvFmNzkakGzVVKtkplB5ieHrnZNzTIc11dsn1dnRgYzKPes0fyxQcHTbtXOiaWJcdNJk2hLNMqeGOmU8CVf0YdWLdgF4gDTP0BjRLe3Gkc0hkQY6AAy3KPOC1cQQZMLcWePcbpYZSChdeMvJTLMmd7qsx4xivbx2YyZnV5pmikYu5hJMp0EzNpO1RTZ0pUV1dwpGPYsmXyWl+fMYxDITHC2aCAqYS1tbIPxfLq6+W56mrTKSqXM5/TZFK+g4GApAZxfg6HUcNmaiLF20olqWHq7pZjV1bKuK2tJiWoVJLV+KYm48zQaO7pkd/Llh1olJfLpuMZ21IDRvV7eFiuAWvXHrzmoViUeiwuNoyNLgwOHrgvi6g7O41jkkyOb1jPxko+F2HoGI5lKgXhM2WiQviJitkVZSJOXFH5omMxvNBTmRbTrrFQlCOFfQNpXPGjx/FsZxwOB3DlmWvwkbPXwu2au7uVPReZhnguJwZFIiGGTk2NWRUcHJTOSHyuqkoMl/5+MYZSKaOyncuZAuzhYVPIzVVg5onH4yZqwSiCvRiaRdiAcTL4N+sOmL9Np8jjMcYGIwUUmQOMswHIfFhgy5QoGjJM7UilzErxVBSu7alcyuKHWhjsEsWC/3LZ/P+DQfmxLEYYHBgcNPoS0ah8ZlhHxM/1qlUSAejrM/U4+bx8tpxO2S8QEEPd5zPK8XV1psUznfRCQRwRFnAzwkDdh3xeuje1t8t347jjZN8XXjBdoUIh+Wlvl5X9cFg+p5WVxnAfGhLjfWhIrhU1NabmgkXtE6Upeb0monComofmZpNeOTa6MHbfUknmzELxZcvk/zKbhvXYecxmQfhMmagQfqJidkWZCNZZbFmiBdzqWCjKQbjnuR5c/dMnkMgWURX04Ja3noAz1tUdescZYs9F7ugQJ4G1AFx9y2ZNIbPfL4YRi7ArK+VmumuXWZXv6hIDgGlLTHNiDQSdA7a2ZM0BQ/o8rj0/nLD9J3O67e1YWUwajZoUJxpjRhhNBme6C2BWo+1aB6GQibawhiKTMTnqfN5eFExtidmISigLg71bGB0Ldu3K541uC9OjpJjfGol8xWLy2WF0w14Pkc0aA5Wfe3v9BguVo1GZx+7dsn1Pj+mYFAzK5zCZFK2Y4WGjQVFXJ9t5vWL8r1ol3zlGNQIB4IQTzOo7o4hutzgMgYCMG4uJgUoByXTaFJL7/RJdaG42zjvrpMaSz5tUr8nWPIxnmI/dl5HS1lZT4wDMjmF9sBSj2SwIny4TNdwg9mJ2YG7rL7S+Y+mzsVkuLJ2xLIbTeVQGF49Q3mRQx0JRxqFYKuPLf9iKbz+wCwBwwvJKfOOiE9FcOfdN0e03hupqMVLq602uMxW4LUuMm0JBDJSqKnEuYjGj/bBli9xcikWMFLLSgGJ+Nw2uTMYUr9q1JwCTk05jCDgw9YcOgL2tLI0g7kvl3mRy9DFKJffI3xQBY340i609HplrNis/PH6pZDQKmPZk7zTEDjzqWCxd6MjSqAyFjANsL7J2OmWlXNLwrBGtkkTCdDWjUw1INIM1D7W18rmjw0s1bzrY/NyyroD1FYwQOJ3iBHR3i0PQ2mpWrwcGgO3bJZ0vk5G0RSqG+/0mktjZKYsI/I7m80bLggsCfr9sF4/L+GwZzXojpm0NDcm1gC1Y2e2NbapZ/zCTmgfuG4+bLlGRyIHbTdQlajJMJsVotgrCp8t4DTfseDwy3/Z205Z6tusvtL7j8CHq92BZVQDtQxk835WYlRb284k6Fooyht54Fh/48RY8unsQAPDu01bikxccBa97bhN1x7sxpFLGmHjhBTFMqOlAY6mhwRRT9vebtA4Wa/NGXy7LYxpOrFGgYB0dBhGsO7DgGTh4gbI9VYqpK4yAsK0tO/ZwZZkGT6lUHlldpqNkX0GmajCFy9i9ifsczGlgPryydOH3gS2O2TDArp1Cx5VaFamUB7W1YuxS5HF42Ajosd0woweJhBhhjY3GaHW7TRSACvUmymZE+lj7EYkYxwcwBeBDQ+azns8b55jie6yZoBZDNCrGdHe3GbO5WX46O0WbgwrjbJfrcMjfgYA4F3SyqfVCg5Yd1BhhoOE5k9VttvKdapeoyTDZFKPZKgifDocS/0sk5JoMjNYVmmmaGM83n5fPt9Z3HD4c1RR90bGIq2OhKEuZh3cO4IM/3oL+ZA4hrws3/cNxeM2muVe/HG9VjgXLsZhsw7B+uSwpEAMDJoUjEhFBq/37jVYF6w+GhsyqPiMKdoG6sS1hAdP2dbLYlZNp7NMJYUtavm43yNjtyekUi4MiZ5y/fVumW2WzJh3G7vxM5DyoU7H0oWPBiBqdCLartafpxWLm81hVJYY2leIHByVNh2l/rIFgpzSXS6KD9fXme8M0O0YFIxH5njU0yN+lkkkFymZN4XUuJ9/JUknGK5WMY19ZadS79+0zDQSoHUMthmxWrgM+nywstLeLsxEIyHFYrM52uPX1cl2ghg1VsYtFcUiyWYmmTLX+4VAG+2yqao897mRTjFhzsRAcqtajq0v+Vw0N5rmZ1F+MXYTq75ffK1aY42t9x9LmqKYo7nmuB893xRd6KlNmRo7Fn/70J3z729/Gzp078fOf/xwtLS34wQ9+gLa2NrziFa+YrTkqypxTLlu49cGd+Lffb0XZAtY3RPDNt5+I1XUTLMHNMuOtyjGFp6fHpEVZlqx8UX06kxHno6NDfoaGTCtWGjdsd0lHwd4u1q4uzbazNCDsYm927QrCIm/ApEHZjXjWNTAy4XKJkWSfgxGwkx2LRWMc0NCz571zG+5vP552ZVqasP2pZR3cmWU9BbVK2JUpGDSr8XaHNhgsoLLStDF2u8WYp5DismXymenrM85vOCzPt7XJ57K/X74TjJRFImLY83ObSsn3i3NidKGjQz6zTU3yu7ZWjH+2XrZH7XjOe/caHRi/35wXNWgSCaMVs3q1cVRqamTb7m4Zgwa+iQbKdrnc1OsfJpteM1dF1JNJMZrPdrIHY6Jaj6Eh+b1ixfj7TTVNbOwilF37p7tbIm72/81M0tCUhWNjk6QaPN99BDkWv/jFL/COd7wDF198MbZs2YLci1VJsVgM//qv/4rf/va3szZJRZlLYukCrv7pE7j3BVGhuvDEFvzLG45FwDuOetccMN6qHAW82ttNZygaGVTTzWSMsFsmY1ZOBwZMznc6baIQHo+pn6ARBoyOTjCCQUOPjCdaxhVIpi7Z6zGYtkLnxbJMfjph7385X8/IuJwvC7Ht+hJsbascPjDqxM/TeEbi2JQ3Gpv8/PCzxmhcMAiUywVUVZkOYnRE+HvfPvnecAy2WE4mjSDj8uVirOVyEqVg3n4iIQ4950JHPRg027B+IZeTbaNRcQgGB2XMQsFEJvN5+WlpMe9BR4fMrbLS1EwMDJhoTWWlzIP1SlTubm6W1xj1KxRkXlOtf5hq+9S5KKKey0jIbKdMTVQIz25ds5UmNnYRiorvlZVyfxgels/udMdXFgdHNUkB97aeJIql8px2oZxtpu1YfOELX8Ctt96Kd77znfjJT34y8vxpp52GL3zhC7MyOUWZa55qH8b7f7QZ7UMZeN1O3PD3R+Mtp7TOq8ijfVUum5UIBVtJPv+8/A6HTUrE8uWS9vDoo3JTqa42BaTUoLBrTbCDjM9nIgD2VVPAGO+8+RwqDYqrwvaIhZ1i0YjQuVxmbmPHGPuc3cnhzX/s6+OpNStLG7aAnYiJohmM6hWLYrgHg2LUVlQA+XwRJ5wgz23dKt8VdkirrpbvRChkhPPYkrmmRr5zgHzvqqrk9ZoaSTVqahIjcutW2b6uzjgumYxEO+rr5bvFY+zfbxwPatB0d8tx2FRh1SpxPNiFik5JPC6GYm2tSYPs7JR93G5xJqjLwYJsfj+rqiQNZ3hYznm8VeuJDM+ptk+dTVVtMtuRkLkucB6vEB4wbcFn6hyNtwhFp7tYlM8Wa9D4nsynlocye7RWBRH0upDOl7BnII019fOTPTEbTNux2Lp1K04//fQDnq+oqMDw8PBM5qQoc45lWfjRI/tww/88h3ypjOXVQXzz4hNxTEvFvM/F3mayq0tWCdkxJhSS1c7OTowUonL1nwrcFIfq6zOruvY2r1xRZQG03UAbq0sxWWjocZV4rGPBVWg6L3an5VAcysjU7k5HFl6vSWeyQ2eatTqAfCeohF1Tk0dLi4lYAGKM07D0+Yz69PCwqTvYuVPGjcXEoHc4ZNvjjjPpJsEgcPLJol7P4zJKwaJwp9MUbqdSMvYLL8j3uLZWHJKODmM883NNh6RclghFKmW24wJEf78sOtTXmzRDNl1Ip8WRYcvcVEpSpNiWORqV/WhIj2d4TrW2gcymqjaZrUjIZCMwszH3sfvNlnM0XmoYP8exmPxvmc4KyLkMDsp7pGlQSwun04GVNSE81xXHnv7UkeFYNDY2YseOHVi5cuWo5x966CGsWrVqpvNSlDkjnS/iU798Gr96ohMAcM7GBvzbm49DRWCCRN45hobF1q1iMLBDC1fVqAHBdpEUxAuFZD8WM+fzxpFgypDdILN30LEzk+LmQ+2r4XdlJjC1yZ4ixdoB4vebVXqqS8diQC7nQleXFMwyCrF6tVGnp1J3Om069cRiciwa6U6n0blYvlyee+45k95XVSXzWr5cftfWGkHKdFocA5dL5hCPS/rV8LDJha+qkmMMDorRGQ7LNaCjw6RSMdJCR6WpSb77dO75nc/ljFie2y1z2LnTOBs9PXK96OqSv9etk/dqPMN2prUNUzViD2bMz1Yk5FARGOqBzEU042D1F2yjPRkmSg2jeCI/b+wS1ddnOnZ1dmrr2aVGW+2LjsVAaqGnMiWm7Vhcfvnl+PCHP4zvfe97cDgc6OzsxMMPP4xrrrkGn/3sZ2dzjooya+zoTeKKHz6O7b1JuJwOfOy89Xjv6aumnfo0WytzoZDc4JlDXSyKcdHbK2OHQnJDZXtMKlcHg6ajDQ2TbNZsy/auU4lGKMpiwR5JY/0NV9a9XjG+fT6TBkTtiZUrgWXLBuFwrEI8LoZXc7OJBsTjJuJBQ6u9XX7zu+h2y/fP5TLf7WXLZF+mE7JL2bp14jTQWXE6xXmg0+L1inPBmqTubtm/sVGiCzQuqR5PETvqTbhcsrjA6ITTKcXAfX1i/KZS8nvVKuMMsL4qFpP58vgVFXKdefZZ2b6i4sBV/7mqbRjLZFOTZhoJOVQExuUCduyQKNJstoO1z9/uHA0NyW/ANARIpQ5t+E+UGub3y2dp7175X/N3XZ04u7OtgK7MDytrReHyiHEsPvGJT6BcLuOss85COp3G6aefDp/Ph2uuuQYf/OAHZ3OOijIr/PeTnfjEL55COl9CXcSH//e2E3Dqqun1h57tXF2unPX1Gb2H/n652TDlIJs1bSi7u+Wxw2FWNMtl2dauTsxc6/HUshVlqWAvumbqH430dNqktzgc8h1cswYACohE5DtDBXlqmnB/dpXq75fj+HziqNOZiMfle03dh6oqUz/BNq99fcZx2LdPvptsrBAOy/cwlZJIw6pV8lp3t4lQVlebjlS5nDEG02n5PldUGGehqUmeC4dlblTQjkTk/O0d1SiGVyzKvJua5H1KpUznuGXLRhuadsPd6xUHZLw0mul2ebIz1eJw/n+mw6EiMKmUHJMK6cDst2ulcxSLiRMbiUzPiZko+pHJSOSMaWJj/2/aenbpsaJGPOE9/ekFnsnUmLZj4XA48OlPfxof/ehHsWPHDiSTSWzcuBHhiVofKMoCkSuW8K+/eR7ff3gvAOClq6rx9bedgPrI9JZtpnNDPGBOY1be8nnTKSYaNf36SyXTpYaFy/39YjTQgaCAHHCg/gQDMfZCa0VZ7IztDsXiVOo8sOCan+lQSIy0FSskWuFyAb29fgwOyvdl3z7Zrq5OHAOu5jscEpVg5yRqu3CVt7fXiNZlMmKcR6NiHIZC8trKlTJOPi9GWzIp1wC2Y6bTH4vJ33V1RtegtlbSs+JxcVD8fnMNAGTcujqJuFDw0rJkHjU1RigTkGNRaZvXjYEBcUx4nYpE5HGpJA5UIGCiLvZUIy5mpNMy12jUpFixm9vYLnZTjSTYi8rnWnthvAgM51wsyjzC4fEjMPZ6ktkogE69uPg8XU2Lg6WGhUJG+X28SJO2nl1atNXKl2x3/xESsbjsssvw9re/HWeeeSY2btw4m3NSlFmjfSiNK+/cgif3DwMA3n/malx9zroZtW6barcUOxNFOvr7jW5DJmNyvJkGIkrCxlhh33KOCZibpB0Vh1OWItSJ4Oe3XDZicOwEBZgUopYWMb4tS1aDq6uBYtGJ7m4xYIeG5DnWVrBWibn1TD8slYy4XC4n37l4XIx1QAzxl75UDMxdu8Q4o2G+b58Y9oGAbNvXJ8dhFDORkCjF0JApxk4k5LsfCokx2NEhcwwG5RoSjYrR6/UaIUzWe9AR8nhMi91iURyKeNykQ9bUHJhCVijIWJYl2/GaRseB1xSmXT7/vIwdCIhj0tIiBuzAgGzH69FkIrfZrJzj1q2yfSolRr1dXyMUkrGDQZPuNh6TdWjsKUTlsrynyaRZiGlvB9avH38Mez3JTB2L6RbFj2Wi1DC2HV8Kuh/KoVlRIxeezlgGuWIJPvfSaIk4bceir68P559/Purq6vDWt74Vb3/723HcccfN5twUZUbcv7UXH/mvJzCcLiDqd+OrbzkeZx3VcOgdD8JMbgwTqWs//TSwe7eJQvT0mFQKCm0xYsEbSalkcrIpGKftBJXDBaYaAaYRAXP6vV75/FdUmOJln08M0FhMvlOSxuNDPi/PFQpGA6a3d7Q4XTZrjFqHQwzQgQEZz+2W/dNpMaY7OoAnnpBjZzIm2kENjJoaIwQ5MCDf28pKYxxTObtYFLG6igrjxNijMcGgRDLcbukklcmIIckOb0NDYpx3dYlRzlqMmhqT6sX6q54eOZZ9BZv1WYGAEfirqpK5MWKTy0nxNwX59u6V+bCDVTYr1y3LMrUah4rc8hrIdLOqKhNpyWaN/sLQkIngskmF3VmZTioqtUC2bZPPEaNC1Next/m1M5N6krGG/2wL/o29x8xXbYwyP9SFfQh4XMgUSugczo5EMBY703Ys7r77bgwNDeFnP/sZ7rzzTtx8883YsGEDLr74Ylx00UUHdItSlPmiVLbwtT9uw7/ftwOWBRzbUoFvXnwiWquDMx57JjcGrgoyVSGTkZt+d7fJ0/Z6jbr2/v1yA2YPdLaUpLgdIxs8lq5CKYcLrDkA5HMOmO+ey2U63Xg8sl2xaNKTnE4xuHt7wyPOO1vBMrWnokJSUVjU6nRKvQHTptxuo/vAVMdYTL6XHR3Ahg1iyAaDYtwlk7JPNivzYeTD6xVngoZssSjGcG2tibYwSrl9u5wj1bl7eky6Fq8TtbXiJHg84tSUy3J8zvHJJ8UwbmuTtLCBAdmvqsqogzMNjE5KPm/SupJJE52Jx43QZSZjzpXRl8FB8z9i8fihIre8BlZXGwFMeyevnh7TTtvvF6esUDBpU2w4OdlUVLthz+5h1POhiGhzszhkvb0Hisvx3FhPcih9HzKR48P/91wZ/nOlgK4sDA6HA40VfuzuT6EnfgQ4FgBQVVWF9773vXjve9+L9vZ2/PjHP8b3vvc9fO5zn0NR29AoC0B/MocP/2QL/rxDYvRvf+lyfOY1G+H3zE4IcaorQryxFQpitGQyRhl782YxJvJ5uaHF4yb1o6tLHgcCcuNkUTadh1JJXleUwxGm9bE2iClQjE7QkeD3g/UXQ0Omg1Jvrw8+n2l8YK9ZYrrPhg1iVMbjphZieNi0hy2XjfbF1q3y2O83wnqVlWJwL18uKVWs+2C0paVFjOX+fhkDEEM2nzeLBO3tYvCxXS4gx9i2Tc6JxvzQkMwpkRi9wh+Nyjhsd5tKiQNUXw+ceKL83dMj49bUGJXvUMikPrW2mvfd7TaCgRTmZNe5/n4TXenuliL5mprRomysRRgYkNdoxNqjvexgF4sZZepgUN6LcFhe9/tHpyx1dZno0qFSUaurDzTsvV4Zq63N6OowkpDNyjnu3WucACqXT1U1/FA1eNQWmSvDfy4U0JWFoyHqG3EslgozcixIoVDA3/72NzzyyCPYs2cPGuxVSYoyTzy+dxBX/mgLuuNZBDwu3HjhsXjDCS2zeozJrghZlhgavLElk+JERKNyw3riCeDBB+VmG4nIDbajQ7bnCi11K4JB49AAph2lohyulEryXXA6TU2F2y2GEZ0OOgLxuBEJC4dNZ6ZiMYBgUFbnBwaMo+J0inHlcIjRTcM9mTSG8/CwfO/cbmMQR6NGYyadlmsA28JSBbuqyjgt7DgVDMoYmYwxGqnU/cILplibBvn69aZYnYrb2aw8rq2VOe/dK9efXbvEeGRnqaOOMmKYDQ1ybWltNbUbFAZsaZGxikVZqW9vF0eEx6XAJSDvE9+DdFoiMQ6HaafrdIqTRWM2mZS/WRO2apX5v9mjvXQQ7AXnsZhxEugQ8v/gdst5d3ay69eBhELyP+T7azesBwZMPQvrYOxwAWfXLlPTsmyZOIJT6fR3qBo86pPMleHv98v/lql4jDrNRAFdWTgaovIPO2Ici/vuuw933nknfvGLX6BcLuPCCy/Er3/9a7zqVa+arfkpyiGxLAvf/8sefOE3z6NYtrC6LoRb334S1jZE5uR4h1oRCgbl5pTJiKHj94t69s6dJu/50Uflwh+NyspkX9/oQm2u1FL8jquL7AKlKEcCNHBpjLGDGsXrHA5jqNKQ9XioNeFCJmMiHDTOuU0wKN8ndkYaGJDvnc9n0mXicTF2a2vF8B4clO9sOCzbp9PymFoawaDs19kp33O2mmX9RjptVvdTKSNqaS8Sz+fl76YmmQ/n6/NJ5IGr4WvXGodo9265XqxYIXOlIwbINmxzGwqJoczIgtst21M8j1GEQEDe32TSRC2Gh2XfYHD0tS6dNp2icjlzLUylJMozPAxs3Chj2qO91F5gVILaIrW1Mu9s1kQzAFN7QgFC1kjY8XjkfxSJyPtHvF5TvN/fbyI0PE53t+nm1dIi73s2O/XmF5Opwcvl5LzZSny6gn/jMTYFC5D/dW3t6PdSWTrQseiOLZ0b/7Qdi5aWFgwODuL888/Hd77zHbzuda+DTxP3lHkmnS/ik798Gne/qKL9mk1N+NKbNiHsm5Vg3LgcrN0fnYrOTrmZbd8uN6zOTrlpbt8uBglXO7u6xKlgC0J2dmFqAzDakVCnQjnSoKPtchmHmx2jGA1km9ZMRraT75ATmYxs5/cbI56NEFpb5Ttr76zE2gqK3JF4XL7DpZKJONCoLhZl4YBFxg6HWbVnDQijHFREZiTD4TB1BKGQEedjPUM6bYzVXE6Massy2hZ0ggCJ1OzfL+NRo4Mwnai2VvanIc3oT6Eg58BIQH+/vM6oCwUDacyXy+y8Zcbn+0oNneZmUxD+3HOSljU22kvnIh6X93b5chm3p8fUetg/B0xTYpvasSYHC7DtTgXx+STawjQx7js8bGppKirMOVZUTL3t7WRr8LxeGX+2BFaBiVOwUin5fzIypywtRiIWiSMgYnHdddfhzW9+MyorK2dxOooyeXb3p/C+HzyOrT0JuJwOfPKCDbj0FW3TVtGeCvZ2f0xdcjjkwt7ZKTfA9naT3xyPiyGTSIgBkEqZ8HwsZrre8OYMjF4tKxa1k4dy5MIaChpiLtfoVXl7Sg4NUMsqj+hhlMtizHE7y5LvLdNWuGIeDhujnuMwB7+/X4zgclm2p1OTyZgVaNYZuN1yvGjUpEdRNZtdiKhNQSMTkPl3dcmx2R0ukZDrQzwuz1VWHlhIzDSs7m6ZC6MShM6X2y3bUJvD7Tbv7f79oyOl7MbV1ydjMzoCyL4VFUbng+KDhYKMydc9HplPX5+cV1PT6GhvqSTva1+fKcbfs0eOO3bVn617czm5tjY1je9YULF8PGprjbNQUyP/y6EhmQdb3tqZqu7DVGvwZnMtdiZt0JXFS0NUPiQ9sSPAsbj88stncx6KMiX+8Gw3/vmnTyKRK6Iu4sM3LjoRL2mb36q0sWFnKmUDkvbU2Sk3St506VDEYiZiwTxx4OACdvYIhqIcadChoFPBrkZ0HPJ5kxZVLDL1SJbTs1mj0WB3RoaG5Pvo8ZgISLEoBuaKFbLPM8+YVXmmIdoNxlzO1CB4PFID4HSa1EWnUxwCGs0OhzHoMxn5nUjICjpF57q7xWDft0+M39Wr5fVsVozugQEpOmfkxOGQv+vr5THrsizLrFizyJ01JPa0mHJZ9mGr2bY2WQQJhcRQZxTA6ZTXLct0V1q1anTKUyQizhTTwwA5R6qYNzebaG9/v1wji0WjNl4sSt0JO15FIqP1eRi1GR6WYzY3GzFD+3lOZNi7XLJPJGLS0VgET+fJznTavy5EV6bZ0sdQFh+1YfmHDaaXTmHljPNFnnvuOezbtw/5MdWkf//3fz/ToRXlAIqlMr5yzzZ86/6dAIBTVlbhGxediPro/MR4aeAwpYFhZ6YAsNtTR4dpv8jUBRZJUpwrk5laFELF7pQjFRr9dABYhE2Dlw4GHQUp9i2PtEYtlcx30d5qlYZ+1rYYGI0awzkYlP2ZGpXJiLFfLMr3P5GQ+oHmZjk+V/pLJRMNYP1Ff79JnaIKNlW3HQ5j4DNlpbZWCrC9XjMHn8+cKzsdAabIfMUKcTocDjHA7bn7XV3irNTVmXPN5eS6tGePnHdTkzhWrC9obDRRE4/HFBbb03d6esQZKZdHd4EixaJ571kvw2hvXd2BKU3r1omT88QTcnymYHEbpxM4+mg5t74+MeLpYLAb1MEM+9ra0dFm/i9mq/3rQnRlmm19DGXxEPGLmZ7ILp1Oq9N2LHbt2oU3vvGNePrpp+FwOGC9aPUwDaV0sOVXRZkGA8kcPmRrJfue09rwyVdvgGcGKtqTZbzoRCYjK3tsZZnJmBSGbFZW81iIyR73PT3GuKCCtqIoh4aaDTTYaaxmMiaVkKk88ts1supNo5bq9nQcnE5Z/c7njV4MWzv7/WKUp1Ly3ecYfX1yPBYaL1tmUqlqamTsvj4Zg61b+/rkHCiAF4uJoR+JmPQbdkGKRIxjwXNkq1kWh7POpK5Ots9mZZ6bNklRN4UD7bn7lZVy/FTKRFQGBuSa5PdLxIMRHRZxs5aBjlI6LfuypmVoyDhiO3aMb4DbxfjsbbjzeXm/7AZ9NitjtrQYRyYcNu16m5rkfBsbzZxZrM00n8ka9qxPYYev2YowHKwGb666Mqkw3uFL1C/eYjyzdIyFaTsWH/7wh9HW1oZ7770XbW1tePTRRzEwMIB//ud/xr/927/N5hwVBU/sH8YVP3wcXTFpJfulf9iEvz9uZgmjByucs79mWaOL4pg2MDgIPP+8Uejt7zfGBCA3bCrr7tplOkVlMqanvqIok4OtZ2lAAfK95ffJskzqjOgSiGPB1B2mQlGbAjC1S2zpGovJ97pcFkN8eNgY+TxuJmO6DK1cObrmwuMxtRXDw2JYZrOyTTBoROeoQ9PXJ47J6tWmDS5VvRkhcbnkOc6zt9esvCeT8tjjESfD5ZIOUXYlahIMivFNYU06DjU1JkWmUDDGZzAo47NuhY7HeMYyIO8bazzo/DECw6gAr7MTrbCzkLqpyWhdsH0vr5d0Kvj/5/x5DlM17OciwmCvwZut4uyDocJ4hy/RgHxJcsUycsUSfO7Z0eSaS6btWDz88MP4v//7P9TW1sLpdMLpdOIVr3gFbrzxRnzoQx/Cli1bZnOeyhGKZVn40SP7cMP/PId8qYxVtSHc+o6TsG4GrWQnUkW13yDtr7EtZF2diTp0dspNl0WHuZzUVVD4igJRoZAYEPv2ybgUl1L9SEWZPIxIsI6C0T46FFRWZgtZ6XTkGFmppcNfUyOvh8Ni8FH9moXf1HGgwrbfL07C8uWme1IsJt/tgQHTApoRAkZC3G4xkhkNsSzTzpZRAXY9yufF+C2VTH0CV/hpnCeT8vy6dRLp2LHD6HyUSuJ4rF4t16iJlKjZdnRoSJwEdqkKhcQ5oUI5DdNSyTxP8b6aGjHsvd4DjeWNG6X7E7VBvF45D3Zbshvo462w25W/WSfT1GScCrbsHdubY7w0n6kY9jONMBzsGPNpyKsw3uFJxOceSQFNZIvwhQ9jx6JUKiESEeOutrYWnZ2dWL9+PVasWIGtW7fO2gSVI5dsoYRP3/UMfrG5HQBw3tEN+Lc3H4eIf4JE0smMOUFLvqEh+eEXmK8NDABPP226sgwMyKrczp0YaWU5NCQ3pL17TZ2F3y8rkb29pkCbBo/WSijK1GCNBUUiCwVjZJbL5u/BQbMSzucYQczlxKGIRk1Uw+Uy3092jmL9AlN1UinTqYjOiNst323Ogyvnw8PyfCBgWrBms8a4DoXMeTQ0iPFaVSXpS319JrIByP6RiOnkFAya9qxtbXKMclnOmZ2paKSzxW48bmoagNHGZyplnJ/+flPYzPeqq8sURHPsri55vGrVgUZzZaW0lO3qkuMyUsRFG7uBPt4KO/8HbrfsX1FhjhEIyHaM/tg5WJrPZA376UQYDrZAtRBtXRciBUuZe5xOB8JeNxK5IuKZwkgx92Jm2o7FMcccgyeffBJtbW049dRTcdNNN8Hr9eI73/kOVq1aNZtzVI5A9g2k8b4fPo7nuuJwOoCPnb8B/3T6qhm3kj1YSz76w+vXy2+2mGRuN1MXmIrgcMiNcc8es6rGkDxziJkLTaVgtslUFGVqsH7CXptEZ8DrNSvXrF/yeMojK+blsnwnBwdl1Z71AkyPojp2uWyKl6nAXVFhUnQocEYHg8dkPUOpJNeIykpZWKitNZo2bW1mGxZ1M9rC82A6VmOj6fQDmDSgWEyM1/p6MRRzOaM8TmeJgnNMN2K3IKZl1tRI1DUWM7Vfy5fL4/375djJpDgz9fVGtK+nR8bs6pJ9Vq8+MHLh98t5TsZAH7vCzqL6gYHRrV+pqt7fL+OPdSBmM81nsmNks3IfGG+Byh4lmm/mOwVLmR+iAY84FkukgHvajsVnPvMZpF7srXnDDTfgta99LV75yleipqYG//Vf/zVrE1SOPO57oRcf/skWxLNF1IS8+Pe3nYCXr6md8bgHa8nHCzH/9vnkxtHXZ9It6FBwpa2nR26+NEKYu8wQP/uj07nQYm1FmRlcnWadAr9brL0IBMxzTJtibQYLvVk3QAMfkO+w1yvGrNdrFgDSaXmd7WwDAbmGDA3JNkwxovYD1a1p0NOwY7Ez10UcDrmesNi7u9uofQ8Pi3FfV2fqFhwOGcteuAyYgnQqkg8NjdaoSKXkODt3SqqS3y/nVFFhNCV6e019ys6dwJYtMk4waFLHADNmqSRR3M5OMaCDwQNX6idjzI5dYWekyekcfY6A/F96ekaLIy5kms9i14xQZ+LwwucWbzpfXBqrktN2LM4777yRv9esWYMXXngBg4ODqKqqmheBMuXwo1S28LV7t+Pr924HABzfWolvvf1ENFUEZmX8g7Xk4+oOIDfbHTuARx4xfdwZ6m5sNJ1l2DO+WDQRC95483n50eiEoswedBaoxM2aJofDpCBKq1lgeNg5InbHaIfTaboNZTLyHabBXlEh27BYmF2jikUjnmdZpmC8okIMyWRSVtkzGaOqzDqB1avl754eU1TNubI9Kzs9JZPyu75ejGbLkrSt2lo5fip1oCic0ynnH42ahQ0qOvf3m0jL3r2y/erVZnHF6zVOT0+PRF7pqITDMo/ubllc2bTJ1JJRxJP1Ij7f+Cv1k61vsK+wt7TIvGMxU5sCyPu1YoWJ0hwszWeuV+sLBScSiYlF+FQzQplt3C6xqYulpWFQTNuxeOc734m/+7u/w+mnn47Vq1cDAKq1OkiZJsPpPD78kyfwwDbpy/iOl67AZ1571Kx2QJioJR/TlnI5ebxzJ/Dss2blsLpantu/X24YTFkYGDAGAFdPuXJpvykqijIzvN7RRdcs3GZBLzUp7OrPhYJzJIJAKivN6jaNea6DZTKyCs/CY6Y+USiuXJZrAtOSqD/BY7M7FY35qirj7LhcYny73ab+o6ZGtt+7V4xmqkCvXClpVPZ2sd3dpkMSnatCwahRW5YpfKY2BRc26utl385Oc652o5jn4PXKnOjQsBA+mZSOdhs2yDnTqaJyeHW1nCtX6qklMZXaAxrgjDR1dpqUK+prrF4tTghrXcY6DvNV88BaENWMUOYL94urnoXy0jAqpu1YeL1e3Hjjjbj00kvR0tKCM844A2eeeSbOOOMMrF27djbnOCFf/OIX8clPfhIf/vCHccstt8zLMZXZ55mOGN73w8fRPpSB3+PEv77xWFx44rJZP87YgsGx+cg9PaaHfbls2iaylWM8Lq8Hg+bGlsmY3vdMdVKHQlFmF+qvMi3H6TTpQR6PcRL43ZPXSygWZfXbsoyGBPVmWETNCALrHxjZoMo2GzKwyDsQEMN6aMiMweJytrINh8WY7e42BckNDWYRwuEwtRsOhzgv4bD87Nghj9euNbUgFRVSMJ1OH1iY29IiDSl27JBjxGKmfiQYNJEVRlYLBdmPjtLgoBjyqZTMr6ZGjk+Bvbo62a6ry/w/gkEjHkgDmiKAw8OjG2BMtvYgmxUHhh30ymUZg+8vx21pkf/B2H0nasoxnUjKwaAgo2pGKPOF50iJWPzHf/wHAKCjowMPPvggHnjgAXzlK1/BP/3TP6GpqQnt7e2zNsnxeOyxx/Dtb38bmzZtmtPjKHPLzx9vx6fuehr5YhnLq4O49e0nYWNzdM6OxxSI7u7RirxsC7lnj6z2LV8ur9GQYBeXRMK0mKyoGJ1uoCtUijK3ZLOjxfAAU78AGINTaiKcI2lMgHxf6XxQWZp58VTDTibl+sBOUjScmdpEp8NeN8WUKYdDtne5JH2JqZHs2sQuR1zxHhqS/ZiWtGKFvL53L/Doo2LsL1smPy0tEiGorDTXGrsI3rJlEkHt7ZUf1h1QsZr6FNXVpjaMBe1MLUul5MftNsXjAwPmWO3tcm7Llsm5UAOETlipJOPW1EiEgUy29qCzU87dPodCQf6Xvb2ji93b2kbvO7bmge9RMChO1nQjKePh8ZQRichnRTUjlPnA/aIIcKG0NFYtp+1YkKqqKtTU1KCqqgqVlZVwu92oq6ubjblNSDKZxMUXX4zvfve7+MIXvjCnx1LmhkKpjC/8+jl8/2FJ/j1rQz1u/sfjURGcfivZycCCwVjMpDV1dMgNFDDRiExGHmcyps98IiE311jMrM5R40KdCkWZH5h6BJhoIVegafy/uOVIETaN42BQ9ucYxaL5zSYN1Jp5sZs6ikXT2tXhMGmO1MDgXLgCzpa4gFnIoPo0rxMUn6urEwOa6tl79pjry9AQ0Noqj6mp4fePbnFNA9neoYoREnvklFEPplNx/6oqqaHYvl2OEYkYJ6ulRaIHTz1lVudrakwqWTot8xkaMq11OzvlvWIKmJ1QSK6z1OiwG965nFxbWVCfz8u1tVyWx0ND4lysX29UzJuaTM0F60bGRqH5P0mnpx9JGY/qajMv1YxQ5pqRiMUSMTSm7Vh86lOfwv33348tW7bgqKOOwhlnnIFPfOITOP3001Flb5UwB1x55ZV4zWteg7PPPlsdiyVIXyKHK3+0GY/uGQQAfOTstfjQq9bC6Zyfon+mHjQ0SEFlb6/c0MJhI7RVLMqqYypltCvSaWMkDAwYx0LF7hRlfmFXKOa5MwWRK9rSwtU1ki7FVCX7YxYjM82KKVVsXet0mte8XhPdJKWSRDYtS64FTqdEFAIBY3AXCiadB5BrTCQiz9PZ2bFDDFG32xjmXKk/+mjZb/9+o0cxNuUnkQC2bZNzoYPicsnzqZQ5JjtalctGH2P3bklxotJ4fb28T1u3GgM+EBCHoqpKxt25U8ZhRCGbFWeBxyoUjAI3jXVqAPX1mUhLKCTjUmmcCz39/UZssFg0TTKSSWDNGnm/GXFpaRld49bTM7orVrEo8+rqkijHypXm/zeTLk6qGaHMJ64XbaPS4V5j8cUvfhF1dXW49tprceGFF2LdunWzOa8J+clPfoLNmzfjsccem9T2uVwOOVblAoi/GBcvFAooaO/PKcP3bLrv3VPtMVz54yfQHc8h5HPhK286FmcdVY9SqWhbaZxb2Pt971652XHFj51aikVZPaMR0dMj2/f2yo2EK1NcMVRmSnHMb0URqPEwFhZo21+3OxYuVxEORxlOZ3Gk3azbbTpIFYujFaZDodHpToxC0CFhLQUN3sZGuR5wBZ6d4lifkE6LoR6NikFMrYlly2QsRknZUSkeF2M0FDKd53p6xOl4yUvkHPfsMV2rWKRdKMi+LpcR0AOMSB9b3gYCYlzHYib6Qg2LmhqJjHR2yuuVlTK3nTslorJ6tRyHiuI9PRLhSCRk25oa0w2LKUCplDgIbBO7Z488VyiIE+H1ynvs98v4Lpd5nY4BIMcoFuV93LNHHJ7aWtONq1gUA79cNos/FRXm/8pi8FjM1JeMxeuV6zrTxg6G/f7H2jsKLtprNtS0UCbLZGwqtpl1WOUFs1unclyHZU2v1PTJJ5/EAw88gPvvvx9/+tOf4PV6Rwq4zzzzzDlxNPbv34+TTz4Z99xzz0htxZlnnonjjz9+wuLt6667Dtdff/0Bz995550I8uqlzAt/7XXgZ7ucKFoONAQsXLq+hIbZ6SQ7JQoFJ559thIdHSEUiw50d4dQKjlRLDphWRYGBrzI512orc0iGCyht9eH9vYQ0mkvnM4yPJ4y0mkXcrm5TdtSFOXguFwlWJYD5bLkIDudgNdbBOBEPu+E01lGseiEx1OE31968fUSMhk3CgUnHA4HXK4yfL4SSiUnLMsBy7LgcJjbYihUQjCYB+CA02nB7y+hXHbBskrI5TzweIrI511wOh3w+4soFp3w+cqors6gUHAhm3UinXbD7bbg8ZTh81mIxdyIxTxwOi0EAqUXOz1ZqKzMo7Iyj1zOhULBgaqqHDZsGEZFRQFDQ15EowU4nWWUSnJ+xaIDmYwb1dW5F9O0HKiszCOZ9CCR8L6or+NGJFJ4MU2rBJerjL17IxgY8MOyHIhECohEinA6y0gkPMhk3IjFvC8WcufQ2JhGKFSC11tAMulFJuNCOu1CPu9GVVUOLhcQChXQ3JxCPu9COu2Bz1dCOu2Cy1VGPO5DNutEJuNBMul6MSpcQn195sW2tQ54vSX09/uRSHjh95de1CQpIhbzAbAwPOx7MaqSR0tLAlVVBWQybgAW1q6NIZFwY//+CCoqCnC5Rps0sZgXyaQb1dVZ1NVl4fGMft2ygHTajfr6NHy+pZFqohxZ3Py0C3uTDly2voRjqxcmapFOp3HRRRchFoshGj14Hey0HYuxPPnkk/jqV7+KH/3oRyiXyyjNwVLur371K7zxjW+Ey5bEWiqV4HA44HQ6kcvlRr0GjB+xaG1tRX9//yHfHOVACoUC7rnnHpxzzjnwTNRvbwz5Yhk3/m4rfvjIfgDAWRvq8OU3HYuIf8YlPtMiFgPuvht4/HFZPevpkZXCaFTC7j09NFBklaurS1a0WKBZKskq4RJJd1wC2CMVC/OZUJY2LLamgrVlFWEu++6RjkvZrNGaKRZNUTNTndiJKBKRlfNcTlbEKypM6hRXwC3LpNwkk3Ikl0ty/1taTEtqr1e2p0AeNSAAua7U1JhoCKMwPp+k1Hg8kv5z1FGyrcsl51EsGj2H3btlznV1plVsf79ERdhhqbVVisOZptPXJ+lToZBJw2Iq2NCQXAeLRYmwrF8/uiteOCxjDg9LC9pg0BSnV1TI9ZPK1MGg7NfdLe9RNGo6V7HOxeeTKE0qJREa1sUwipHNyr7NzRIBOfpoGcey5ByPPloiJY8+Ku91KGTSoNiet1iU7VetOjBNia3GV66cXMRiqvc/RTkYk/lMvf6bD+O5rgT+850n4vS1MxcLng7xeBy1tbWTciymfRe3LAtbtmzB/fffj/vvvx8PPfQQ4vE4Nm3ahDPOOGO6wx6Us846C08//fSo59797ndjw4YN+PjHP36AUwEAPp8PvnGuFh6PRy8MM2Cy719fIof3/+hxPLZnCABw1dnr8MFXrZm3egpgdHtB5ucyPWFgwBT8dXTITSgYNPnVTH9iPnc2a1KmlNmkCLkc6XdSGR+mtYz33eNrbKkqyGfK4/GMMlL9fqPGTe0Lpufwe892sLGYUdmmoBw7w+VyMhbbyPp8pt6KwnH19XLtoMZEIiEORiQijwcH5bX6ejlmKiX7RyJiLOfzMrf9+434HztasXbD4zF1YvX1kuLZ0SHPh8MyD6p7l0pyXhTnY0GzPcXT75d92RGvpsY4VdS/oKhgICDnwWtjXZ04I+3tMm+PR5wbOlV8LwIBOXa5LMerrJRza2mR96i3V+ZC3QwqkVdXyxzsnfnyeRlj+XIjEkiHsaZGxu7rkx/Wz9hJJs24k2U69sNcC/cpS5uDfaaKL9ZWBLwLZ7dO5bjTdiyqq6uRTCZx3HHH4YwzzsDll1+OV77ylaisrJzukIckEongmGOOGfVcKBRCTU3NAc8rC8+WfUO44oeb0R3PIuJz45a3Ho+zjmqYt+OPJ5iUSo1+jrnWAwNiRBSLpnjbrpBrN1o0f1ZR5h/WUBCuSgNmhXssdAiyWTHsaJACRgODKt4+n6yE87pAozebFQOXbadzOaNhE4/L/uxQxIhAc7O8lkzKCj51L6iBARitCSpnezxybHZMSibF2HW5jFhnKCQGMguN43HTrSkeNx2rmppMc4m1a2W/7dvFYGfzCjoWO3eazneVleIwsDg+l5Nt6Iy43XLt9Pmk1oHvv9s9WueDtSKseamvN3UYjO6wKxYjS6GQOCXbtsn7EYnIeQwNyVilkjgxrI3hfOlc1dbKtvX1BxrwVFsfKzA4H12c5ku4Tzl8YZtZj3tpiKNM27H44Q9/iFe+8pWaTqSMy08f24/P/OoZ5EtlrK4L4TvvPBmr66awJDRDxhNMSiZlNS8elxuQxyM3nr4+U4SdTMqNlGkBbEGZz5tOLoqiLDz2bFu7sJ39O8ria3aBovEOMGXKGHpMUWLXJnYv4nWCiw1cfaceRjJpDPaaGkm3YZoP28ayoDudlmuJ02kiIXSKAgExqNkOdnBQoiGhkBjQ7e2mcJtF2amU0dNh5LW21kRhpJDdtMQeGJDr37Jlpg0vYKIODQ0yRiQiRr89GlIqybXS6RTHprFR5tnXZ5w6tmBlZyxGMVjc7nCIs9TfL/NzOIyjwI587KxUKsnvXbtgS2sziuM+n2n3S40Odu3jNT+fl/n4fBINKZXmt4vTVIT7FGUiWLztcR3mjsVrXvOa2ZzHtLn//vsXegqKjXyxjBt+/Sx++Nd9AIBzNzbgK/94HCL++Q3fjRVMYr7z4KB0F2G+MPOBk0m5SbOTSD5vnApAoxSKstigUJ2dsY5/uWxWiblSTaeAqZGhkPxmxyJ2iaLmAyMIFNZkuiQNdqZXlctiMNtTjKjQTAOazgBTMCsrZU4DAzI+a0EKBRmDLWwLBblu7dkjRn1Ly+ioRk2NMWJzOZm/0ynXv2zWaEMwqpBISO2Y2y1dmXp6ZBvWSjQ2mqgIHQpqYyxfLuMz5YhRmXBYznHZMplPf79sU1Eh11s6VYwKMTWoosJEbfJ5GT8el/P3eiUCEYvJez48LMeuqpL3JZMZLUZnbwFLrQ5AHCU6TI2N5n8x1ylJY+9DwMza3CpHJqm8hAZD3nHCsosQrZRUZo3eRBbv/+Fm/G3vEBwO4Oqz1+HKv5vfegpgtGASIBd2Km17vXID6+2VGx+VeLnaCZjohKIoi5eJ+oP4fCadCTAr81SIpsFvr9mgkUvtBC4spFKmYNqy5HrR0GCcEBb+MpLgdJoWtC0tsn1lpVxv7GJtgYBci5hixNXsQEBW+ItFk17FeglGAPr6ZJ/Vq8WA9/lkG6fTpAoxVcvnk33SaRPFYGG6328iMJWVsnLv88nfjHpEIuIo9PfLMbdvB/72NxPRoaG+apXMl1EfamW4XHJ8n0/Oq6ND6kWoI8RoTThsrsuRiLz3tbWyT2urcRIKBTkOdTPGpjExDS0Wk+OwVmW8SMFcOxVj70NjCYXk9VxOay6UiSmXLcQyYpDMtYDwbKGOhTIrPLF/GP/0g7+hJ55DxO/G1956PF61Yf7qKexwlZK1RsPDcvGuq5Mb/eCg3HSGhuTmxEgFDQVFUZYujEgQRjFo9DJ6YS8Ep6geO0XlcmLkc5yBAfntco2u9WCKEfelQV0qjU63ZNMHQJ6jZgajHdXVRoG7tVVSNhkpyOfFyG5pkcdMPwqHxWjet0+2CYXEwB8eNk4IC83zebnuASZawFSi3l5xcPx+Me5rakynK9aWxeOmaDwalTmk00Y0kHOnMODwsJwjna29e+X6ak/BojMWjcr5szPXwICcW329jMeIkctlNIVKJaMCPl4qUSolc2+w3YLmO1Iw9j40FrtSuqJMRCJXHLneVATUsVCOEO7a0o6P/+Jp5ItlrK0P4zvvPBlttRMs08wDzCumKuzAgNx8Egn5e88ekzKQSpkbpEYpFGXpQ2N/PBjlYBoTI5U0gGMx44AUi/I8IxqWJdcRFv2yVSqF3liXxZx/dnoaHDSdqEolOW6xKIZxJCJjRaPSUrarS2oKhofleUYnCgXZhs5Ie7tss2KFGNputxj3jY1S/NzVJXMvlURUzueT47W0iHGdycg4NHzZcYric3SuIhGTpgWYqIbLZYT83G7ZhsXWTJPyeuXaumKFREHojLjd8ndDg0RdWPeQzRrFc7tqN6EjwpoMRmD4fyCLJVJgvw/ZFdtJoSCvM1KuKOMRS4thEvC44HNrKpRymFMqW7jp9y/g2w/sAgCcfVQDbnnr8Qj7FvZj5fPJDWr3brl479ghzw8MyN89PXKzTqVMhxKmTSiKsrQ51AqwPTppr7mwq23TkWANBSMVyaSp2aCzAJjtWU+QSplaC3YkyuVMa1m/33QoqqmR1/r65FherxjfXV3iQLB2gzoOLPSmCncgIEZ9Z6cYzYGAGO3sZsVajjVr5NiVlSbFiulEwOji56EhORfWejC6w+NS6dvhkHnHYnJ9bWmR84lGTXcmFq9ThZzvgV1TgqloLS2msJtdu5JJcbYcDtGa8Hhkm7175X1qbhaHiNGLxRIp8Pnk/zI0NL5jkUqNrg9RlPEYzkgaReUSSYMC1LFQpkkiW8Q1v3gC//dCLwDgyr9bjX8+Z/2811PY4c2JhXsDA0afIhYDnn9ebtRMW6CRMAdajoqiLCIcDiOMR4PS5ZLnqA3h9ZroAGAM07GiekxLKBZNFIJF4JGIGK21tfJ7cFAMerfb1DnEYkbDweEwGg779slYGzbIAsgLL4iBHQqZui9GPwIBMz+KdbKdbnW1GO7UnairE2O/rc2kPwFikO/aZerOXC4x2Fmo7XDI9ZJF2qWS7M+0sXRarrXDw2b1PZGQ94I1G/ZianZiamo6MIWJxjXTnuz79PfLtitWyDZ2sb1MRn7stROLKVJAZ43O1Xy2uVUOD0bqK5ZIGhQwB47F2WefjV27dmHXrl2zPbSySOjLAG/+ziPY2ZeCz+3ETf+wCa8/vmXB5kN17L4+ucn19soNyemU6MS+fdKrffduuQnzpsIUKEVRjgwcjtF/s40p05+4Sm53IJgaZK/HoNAb9/F6ZazOTjEW83kxgFl/0d9vVK7pqPT3y/WopkYM6p4eeX7zZimSpl5GPi/jd3bKcWm0RyLy9549sk1lpTgty5bJOWQycl2sqpLr4mOPyWsNDXI8eySG9RgeD3D88aPF/lIpGT+ZlO25f3u77MN2sy0tksKUTIoh/cgjwLnnigMzFXE4FmAz1alUknP1eo34n8tlai1SKUkjo15Ec/PiiRT4/eM7V3Pd5lY5fBhMacQCb3zjG9Hf3z/bwyqLhId3DeDmp11Il1JoiPrwnXecjONaKxdsPsPDwHPPyU18YEBugMxhTqflxrp3r9xwaQTwdXUqFOXIgO1k7dBRYBQjmxVng5oM9kYOrI1gATBgxDI5jsMhRjVFN71eiRiwWDmRkFV2wGgbBINiBBeL8lNdDfz5z3K98vuNrg6F/nI5UyTOVCpAnJbBQbne0XDOZsV5oTPQ1ydRkN5e003K6QTWrROHgl3z+D5QdI+iok6nOBNut2kZ29Ulc1q50rTFZSepri453ktfaox4u77GoQx7n890jfJ4ZC579shrgYARO+zvl+t/c7OpnVhMkQK7o6TK28pU6YpJ14emisACz2TyzLpjceWVV872kMoiwLIs/OCve3H9/zyHUtmBTcui+I93noL66MItuWSz4lR0dpp6iUzG1FY4HFLISCEqOh2FwuiuMYqiHFkw6mBPfSJjFxxYuAyMXpCwq32z+YPbbVJsymW5Ju3ZI+k/+/cbkbz9+8XQrKyU61RVlSkMp9ZEoWCiBtSiYBonO0WxmJuaHJYlx9u/37SyZcvcE0+U6G2hII6Nzwe85CXShaq3V9KnLEuM9EhExs3nJQpBx6u/X4rB1641aUjhsJy31yv7Uc+iosJ0cfJ6p6c+bU9rGhqSOTQ1GYfK4ZDjMKISCJhakMUWKVBnQpkOXcNyAWqqWDrhLa2xUA5JvljGdf/zLO58RETvTq4t4/b3nIJwcGE/6F1dchMsFMS5KBQkapFKmQLAwUG5+fIGo0XaiqJMt3CXGg1MpyyXxahmwbBlyWNeawIBkyLl85liajoDDodpex0KGZE6Oj7sWMVWr16vKTYvFuU4iYTphJXPm9cTCVOz0NkpEYjaWkkLZaH3wIA4Cqx9YKek/n4jvEedH49HjPitWyUK7HRK/cbatbIdHQpArsV+v0kZYxeqqapPswC6p8d0hSoWR9e/hMPioFFQj46dRgqUw4GOYYlYNFceARGLq6++etznHQ4H/H4/1qxZg9e//vWo1uqkJc1gKo8rfvg4Htk9CIcDuOactWiJPw+fZ2HbnuVycpNOJiXE39EhfzudcvPq75d0gnhcbl6plDoViqKMz1jti4ngNtTDYJEzIEatZcn1hnULpZJxJLxeU+BdVWXE+NgOmxECwEQtqIHhdpu6CdLdbQxttqz1emWsTMY0qGAdxd69sl08LtGJigrZn0Y7jXhAnJKaGvm7WDRGekODEZfLZIDHH5c50zmqrBw950DA1EJMV326ulq2SaVkvnQw2J62osLobqxceaDzoM6EspTpismXvrnyCIhYbNmyBZs3b0apVML69esBANu2bYPL5cKGDRvwzW9+E//8z/+Mhx56CBs3bpy1CSvzxwvdcVz2/b+hfSiDsM+Nr7/teLxydTV++9vnF3pqIy0Y9+6V1behIZOKkM3K6hVvWhSmUhRFGY+ppkYyamHXvLAXebOea3DQOC2WJUZufb0Y24WCGMksFGddGDsw0SFgZIN1Hlz1d7mM48IWucGg/PZ4zL59fTLnWEzmWFdnVLf9fnn87LPSIeqUU2RfjgHIXNlJqlSS7RMJcSIiEelgFQ4b56SmRqIfXq9JW5qJpoTfL+ladC4YmaZAHtXOAwGJyCjK4UTnSCrUERCxYDTitttuQ/TFirRYLIbLLrsMr3jFK3D55ZfjoosuwlVXXYXf//73szZhZX6474VefODOzUjlS1hRE8R/vPNkrG2IoLAIVOSyWVmte/554MknTXenZNIU9DFaoU6FoihzQbFonAb3i3dSRhyoRcEWrfm8GM/Dw2KYl8tyjcrnjYPCCAOjrrmceZ21HcGg1DwUCjJuMCiOg92xKBRkDKZhsSi7WBRDnx3xmCYFSBSivV0iv6xb6Ow0AnTV1TL3yko5Riol+y5fLhGP/n4j9udyyQ8jHJnMzDUlKiqkbW9PjxEFZM0cO3mtWCHbKcrhQiZfwtCLAnnNR4Jj8eUvfxn33HPPiFMBABUVFbjuuutw7rnn4sMf/jA+97nP4dxzz52ViSrzxx0P78F1//0syhbw0lXV+NbFJ6EqNE7fvgUgm5WbX1+fFByyaJGrf1zV6+kx4neKoijThTUUNH6Z/mRPn6JiNIu5acg7naMjCPG4aZfqcJi2r/m8GOYUeOOYrKsgfr8Y9vaicZdLHJFk0qQwNTfL9ZHOSChk2t+ysQULtPk3lbqZprRtm4xdWSnb1dbK4927Te1FVRWwaZNEhxk1zufFoVizRubI4mvWp9hrHaaiKcFOT9msKSjP5eRxNHrwdCpFWYrs7BMjpiroQTSwdEqipz3TWCyG3t7eA9Kc+vr6EI/HAQCVlZXI23v2KYuaUtnCF37zHG778x4AwJtPWoZ/eeOx8LrnQUlokjC1ifm1VVUSBvd45LlUSm6uzFFWFEWZLnQeuIDhdJrohF2/AjBtYJkSVSya1EwK8ZVKJoIQDMqYVP92ucRgHh6WRRKPRxyPmhpxGvJ5I0q3apVsG4vJsUslWa0vFuV5n0+cEHvkxO83KUlMV/L7zbhut4xrFxEMhUaLALJAnGmnQ0PicDQ1mTq2ZFIiINTzsCxxRhiZcTpNwXUmM3lNibGaEHSqGhpUE0I5PKFjsbY+AoddhGeRM6NUqPe85z34yle+glNOOQUA8Nhjj+Gaa67BG97wBgDAo48+inXr1s3KRJW5JZUr4kM/3oJ7X1TS/uh56/H+M1cvig8ze5/ncuJEeL0mfF4um3SAYlG2mUxoXVEUZTKwKxJg6h6ocs3aCNZBAEapmiv1NNTzeZOqydqKUslECei8UL+Br5VKsiLvcBg9ieFhGcvnE6O+v980p6DDs2yZcTACAdmH6UterzguNTWy/f79EmGorZVob2WlMfxTKdM6t7paxh0cNOdFRysUMufN4vZEwmh4MMXK65X5Mq1pKv1dtNOTciSxvUccizUN4QWeydSYtmPx7W9/G1dddRXe+ta3ovjiFc3tduOSSy7BV7/6VQDAhg0b8B//8R+zM1NlzuiKZXDp7X/Dc11xeN1O3PyPx+G1m+Y+rnyom0M2K3m+VHjN5+V3Q4OkE+zfLz9+v9zo4nFT/Kg6FYqizBT7dYQpSbxmMRXH6zU6OdyeBdyMcjB1yd4qlu1RfT4x6AMBMd7t0Ypi0azKJxJGs4HGOnUvolHTwralRSIJxaLst3atibQMDcmcGWXJZOSYNTVAW5vMye+XSAg1KaiHwaiFZZn23tTVYA1FJiPzZqvZ/n6jKxGLiY6G3y9j+v3mZ6qoM6EcCWzvTQAA1tYfIY5FOBzGd7/7XXz1q1/Frl27AACrVq1COGzegOOPP37GE1Tmlmc6Yrj0+4+hJ55DTciL715yMk5cXnXoHWdANju+WFIoZG7MDoc4Dzt2mJUuy5JVrocflhtWLmc6rzC3l60eFUVRZgNGEbgiTyObhjxF6oDRdRdjnQy2gmV0w+Uy3Zm46u/xmGhrfb2MTcXodFqe5yILRecYCVm2TK6T7JbE2gPqS9TXyzVzxw4R0fP5JA2ptVVSoHw+0/rW7jDQoaI2BqMZVAdnC9xMxkRCwmFxYvr7ZT7RqMwpnZZz8Xgk0lIoHLwjlKIcyWzvfTFicaQ4FiQcDmPTpk2zMRdlnvnjcz340E+2IJ0vYU19GLe96xS0Vgfn9JgsvraLJSUSwNNPm5aBXq8819cnjysr5QYVDMoNb/dueVwqyc2svd2s9I1VzVUURZkMdArszgG1KZieVC7LNct+nbGnXTIFiK+zKJntaOko0NlIpUyKUygkBnljo1z/qFjNdKpCQSIKjD4w9SoYlL8bGkRdu69ProcUoevpAdavl+OxVmPFCnmuslIci8CLDWdYSB0Oi+Ng77LElC/LAk44Qcbu7pZzSKVkW6ZeAaYbVE2NmWsoJD+x2GilbEVRRpMvlrF3QFYT1tZHFng2U2NKjsXVV1+Nz3/+8wiFQhMK5JGbb755RhNT5hZ756fT1tTgmxefhIrABD0BZxEWX1MsKZsVBe2+PrkRRSJyA3v8cbn5rF8v7RldLulS8tBDkv5kz11OJuUmp06FoijTZWykARidVunzje5ixPSfsR24GYXlbxrVDodpR8t0KhZEp1LyWiwmDgIjFDU1xrjP58XgZzcpLrS43XIcdpcKBMRxSCTEqYhGZTHH3rFp9Wr5e98+uf42NUk6lsdjhO6yWZlPMCjHiMXk9WhU0q3a2sy1e3hYzsPvl2t7JGKuz/ZUKRIMHqiUrSiKYWt3AqWyhYqABw3RpRXSm5JjsWXLlhEdgy1btky43WIo+FXGx7IsfPn3W/HN+3cCAN5yciu+8MZj4HHN/dWdPdXtYknDwxJ98Pvl5vXMM3Kz2rdPbnyplOnP/te/Atu3m7QCruDRyVAURZkNaLBTvI4tWstlExk9WMqlwzG6tsJevM36DLuTQs2Kctk4IoGAWfUvlUzKFIup6+vNsQoFSW9qaBCDv6ZGjHsqU+/aJcc56SR5zFqLujoZL5OR5zheJiOpS6mUXGNTKblGNzbK8w6HOFptbVJMzfNh291yWcZwOiXyMlZf4mBK2YqiAE/sly/kca2VS86mnpJjcd999437t7I0KJTK+MQvnsYvNrcDAK4+Zx0++Ko18/ahZW4yV69yOYlgsJhxxw5R0na55IaXTMrrDz5o0gY8HrlhJRImD5g5voqiKLMBIwlskQqYVKjJpO4wJcrunFA9O5czHZwYuQDEkQiFjIK1yyULKvm8RA/sAnqMfmSzsjCTTstiSyAg+1H8rq3NiOYxXaqnR4z9ykq5nlKMr75exmFB9cCA7FNZKc4DtTu6ukxdnL3NK9OpABmP+hq53OjIR7Eoj1UpW1EmZsv+YQDA8a2VCzqP6TDlZeqHH34Yv/71r0c9d8cdd6CtrQ319fV473vfixxbTiiLhlSuiMu+/zf8YnM7XE4HvvSmY/Ghs9bOqyfMFTymDtDRcDjk5tjXJzefykoJ+RcKciPdsQN46ilZkduzR2osurtFAGpgwKQXKIqizAZc7LA7EWMfT4TDIdcvv9/UU4x1TgBTsM3n6HTwNUY5+BofUzivt1e6M7EjXiol18OuLkkl7eyU663HY4rE9+6V6+nQkLze12fGLpeN0J79Fm5Zsj0dHtZSDA2Zermx+HwmHaqxUfZhxJqCgWvWqFK2okzEkyOOxdL7kky5ePuGG27AmWeeide+9rUAgKeffhqXXnop3vWud+Goo47Cl7/8ZTQ3N+O6666b7bkq06Q/mcN7bn8MT7XH4Pc48c2LT8SrNjTM+XHHtpPlzWZoyOTWulxyI+vpkRt3MCg3SCq5dnTI6lYmIzfbfF5uVqnUnE9fUZQjnFLJRBTGOhX2Im/7NvZWsayjsKdSOZ0msmB/jQZ+NGrqIZhyRaO+utoY/ewW5XJJtIGRiX37xJj3esVwb24Wx4NRCrdbni+V5LlkUh5TCK+rS8apqZFzaW8XB6SuzqRqUZ17aEgcm/FUr6mUzbSqysqFUcpWzQtlqRHLFLCzT4yc45ZVLuxkpsGUHYsnnngCn//850ce/+QnP8Gpp56K7373uwCA1tZWXHvttepYLBL29KdwyW2PYu9AGtUhL/7zkpNxwgK1k62ulp/hYVk5CwZlhSyVkihEsSj7dHYaQTyuxLGbisNh0ggURVHmGqdztAAeINcmu1Nh3yYaFSM6n5ftQiFZOGHNgcdj0qMoclcqSZSD3aI8Hrluskajqmp0i1p2mGKb7mXLzLyots1aiXhcnA2vVzQtWJPm8chPZ6cc2+czjTGqq42qeC4njko6LdfuxkbzPoRCJgox1mhfaKXsg92HVKVbWcw83R4DALRWB1ATXnre8JQdi6GhITQ0mNXuBx54ABdccMHI41NOOQX79++fndkpM+KZjhgu+d6jGEjl0VodwPff/RKsqpvbfsjjtZO1tz0EZEWsv18u+MWi3PT6++W1cllWxwYGTKRC2xEqirJQFItiNLMgmwsbrDngD9u0sjVtJCIOBiMXTufoLlPsmBQIyLYch7UW4bBcIzMZGdNer1EsHlhXwfoItp9Np2Vf6m1Eo0Zrwq49EY0alWxGJugkMEXK7ZZxmSbF1z0eOc5E1+iFUso+2H0okxGHR50LZbHy6O4BAMAJrXO7CDxXTNmxaGhowO7du9Ha2op8Po/Nmzfj+uuvH3k9kUjAM7a3nDLv/G3PIN59+2NIZIs4ujmK2959CuojV2Pn0QAASbtJREFUc38lHdtOFpAbSjwObNkiv6uqzI1y714JtedyclOLxUxRYjqtYneKoiw8+bxJXbJ3aPJ6R9dNOJ0mhcnjMboRdsO8WDQRBRrbbLNNA5zF26GQ7BcMyrUxHDYtYRmZcLuNeF40aqIZNPijUem+ZE/RisVMO9uqKvl7YEDGshdU0yHinMcu9Ng7W9kZLw12PhnvPjSZ9C1FWQw8tENWWl+xZml2N5iyY/HqV78an/jEJ/ClL30Jv/rVrxAMBvHKV75y5PWnnnoKq1evntVJKlPjT9v78N47HkemUMJLVlbjP991MiL+uXf2xmsnm81KRKK9Xf5mf/feXpMaUCzKhZ4RimxWftSpUBRlMWBZplMUH9OotsOIQCRinIdIxEQrvF5ZXGGdRSAg10OqXWezo6Mjq1eLQ9DfL+N5PBL5ZceqTEbGpRq2ZRmR0UgE2LBBBPD27zftZRsaZMU+Hhenh5GN+nrZz35OPp8Ry6Nuht2JSKXMQhGwONKPxrsP2TlY+paiLDTxbAFPvpgKddraI8Sx+PznP48LL7wQZ5xxBsLhML7//e/D6/WOvP69730P55577qxOUpk8v3umGx/68RbkS2Wcsa4Ot779JAS8rkPvOAuMbSebzYqoXUeH5ObScairkxvn8LBEKaikzZs3V98URVEWAnthNtvG8vrm9ZpOdCzuZitVh0NW/NmUgik4Y8dgh6lAwLSOjUbFCchmxaEIBmX/bNboQrDtLAXrymUpvLYsGcPrleerqqSeYtkyEzGgQwPI44YGGY/1bh6P7Lt7twjs0RGgWF53tykKp8aQ3y9OA7B40o/G3ofGcqj0LUVZSB7ZNYhS2UJbbQgtlYFD77AImbJjUVtbiwcffBCxWAzhcBiuMUs2P/vZzxAOz20evzI+d21pxzU/ewqlsoULjmnE1956Arzu+ZM1tbeTLZclUtHTIzeZeFxWiVhfUSgYx6OrS26WXD1TFEVZSOyq2GzvyhoIyzJRBcsydQ2AiRjQKamqEgM8HjfF2IGASZdyu2WbcBhYt07GYtQiEjHd73hddLlk+9ZWGXNw0HTRozJ4KARs3AgcfbQx5Fkovm2bEenLZiX9KRIRvYtwWMbftUu2W7nSRFv8flkQCgTE+eA87JGIxZJ+ZL8P2dY8R5gofUtRFgN/fjEN6rQ1NQs8k+kzZceCVEzQgLqayxfKvPKDv+7FZ3/1DADgH05ahi9eeCzc86CmbcfeTpZtBUMhuQEnEhKhYGeVZFLSobq75Xnt9KQoykIwVl8HMCkyTFOihoRlmTQmdqnjvnbHIRCQ618+bxwJbsPiaKdTDHquzQWDcp1kMTfTQenchEJiyHs8svrv9Yqxvm+fOBnLl5uC8WOOMSlUAwPifORyct0NBCTKkUiYSInHY9K21q+XKEZvr0m5situj1eEvZjSj8a2NR/L2PQtRVlMLPX6CmAGjoWyeLjtz7tx/f88BwB418tX4nOv3Qinc34l4HM5UzORSklOL7uTDA+b0HQ2K3+3t0ubw3hcnQpFURYOOhaAcRbsEQkWPBOHY/SqN7s0ORxyjfN6xQiPxWS7aFSuj/x72TJ5zM5NDgewapVEGIpF4OmnZcGltlYcAG6Xy5nuTqWSzLGpyaT2bNokBnWhINfWvXvl2sv2t8GgHHt4WM4jFJL9UylxIpYvl+f9fnF4EgmJMFDF+2CdnRZb+hE1NIaGRqdljU3fUpTFxL6BNHb0JuFyOvDSVUdgxEJZHHz/L3tGnIr3nbEaHz9//byqaWezchNrbzcKsOydXlMjr/f2SpidbQ63bZPth4dVNVtRlIWFjgEjDkyRCQbFqM5kjHhdIGCMa7aOdbuNsep0yrXPXuTd3y/Xvqoq2XZ42DgNQ0OS1rRxozxmx6c9eySycdRRMrfhYVmsicVkrEJBog9+v9HB2LNHHIu6OvldLsucgkGZQ0uLjF9XJ9ffri6ZR6EgUQ1ACrj9fqOj4fPJOezeLedFR2tsQfZiSz8aq6GRTo+fvqUoi4nfPdsFADi1rRqVwXG+SEsEdSyWMHc8vAfX/vezABbOqdi5U254xaIpKmROMoWYBgYkXN/XJze4/fvlRmlPPVAURZldTFs5Rh9crvFFNnn9ooBdICALIzSsWetAg5tj+nxipIbDppYsmZTt2eZ1aEjGZlpoVZVEChIJ+R0IyPa8HiaTUm/BVCU6KR6PbM92tOm0vM42tZxDJGK6R3FBJ5uVY4TDsi3rMqqqxKGJxeSaXC5L2hMdhXhcrvGDg6YInPvbC7IXY/rRQmloKMp0+d0z3QCA849pPMSWi5sl5VjceOON+OUvf4kXXngBgUAAL3/5y/GlL30J69evX+ipzTs/+OtefO5ucSr+6YxV8+5UAHKz6e01aQOZjNyMAbnp7dghr+3eLd1CePNii0RFUZSZwq5M+bz8mI5Ocj20d3iyt4y14/eLIc1UJr/faEKUy2LsU7vCLmRXXS3GfC5nujT5fDIOHY7qaklFqq6WTkxVVbLts8+a6yXbzu7aJUZ4IGBSn/x+YM0aU6vhdss4jFKk0xJpaG2VaEQiIWPa5876jaoqU0heVWWKyL1emWMmI9do6mg895wsDLW2GoG+dNoY6IGAKcherOlH6kwoS4GeeBab9w0DAM7dqI7FvPHAAw/gyiuvxCmnnIJisYhPfepTOPfcc/Hcc88hNFHV2GHInY/sGynUfu/pq/CJ8zfMu1ORy0konX3beTNMpeRGlc9LnnBvr+kElUyam56iKMpsQAVrl8t0ZyoUDlS85t8sQGYhttstDkA4bF7nQgnbwlKoLhQSZ6BQkGtgPi/b5fNiwNbVyfY1NbKCX19vohVVVVLjUCqZujPLMimig4NijAeDxnhPpyXywBbde/bIdZQq2oBst3y5HMPvl+swu0VxroGAOAiMXHg8Eqlwu43atscjc92zxzgJu3fLGKzV8PlMhINq3SzI1vQjRZk+f3y+FwBwwvJKNFYs7S/LknIsfve73416fPvtt6O+vh6PP/44Tj/99AWa1fzy66c68elfPQ0AuOwVbfjkBXPnVEwUQs7nnejokOLAWExuGPv3yw1scFBuTl1dpji7u9ukAyiKosw2LJ4OhcRYTqUAy7JGtCNoNFOtmvv4fGIwU8fB5TKOAGDqKFpaxKBmgwoa9omEiWaUy/LY6xWjOhg0LWXpiAwNydzKZTG4OzvFKaCxz+LqXbuks5PTKfUQmYwcv6bGdIZKpWReuZxEFFIpmbvHY1rVZjIyN543RfGcTqPi7fHI+8DUq3TaRBeqquQ84nFxSurrZdtg0DTssEeANP1IUabHH54Tx+L8o5d2tAJYYo7FWGIxUSc8UlrcPritD1f91xOwLODtL12OT7/mqDlxKg6mniqFfn7E43JzGR6WHNw//UluZG633Ii7u2UlLJs1K2uKoiizDXUZSiW51vCx211EqeQZiUKwxSsNYXstQKlkIhLJpBQ1V1eLA7Fjh3E6GhtNnQYjADTcabwHAmKIOxxi+IfD4lDE42KYB4OyX02N6Q7FCEKpJM+xQDsWk/2Z5lVVJWNEo3J9DQTkWstITTwuY9F56u6W94RRg2JRosfhsDxXUyMpUHSMOjvlcUODLBZ5vfJaNCpjx+MS3aCTQoXwsagzoSiTZzgHPLx7EABwwTFNCzybmbNkHYtyuYyPfOQjOO2003DMMcdMuF0ul0Mulxt5HI/HAQCFQgGFJZTo/8T+YfzTD/6GQsnCa45pxGcuWI/iHIQAqJ6ay8nNiqJLLLwuFApIp90IBotobweefx545hkJ1zPXOZmUxy/6fYpyCIpjfivKoaGTwKJs+2+ns4hczgOnsziies2C5HLZOAGWZTo7VVWJYU/ngnoPwaA4Bmyf7fPJ60x7isfFGPd6jVYP227v3ClOSiRi2sx6PPL6smUyRjwuEd50Wsaoq5O5sM2ryyXHb2mR16i+7fHI4k84LM8xFbW7W57v7DQLQxS/czplPjU1oq5tdwAYcaZyuNttFMRZEB6LmSL0dFqOyVSzIwHaDEvJdlAWN4VCAY/2OWBZwMkrKtEU9SzKz9dU5uSwLJa1LS2uuOIK/O///i8eeughLFu2bMLtrrvuOlx//fUHPH/nnXciyGWeRU53Gvjasy6kiw6sryjjvRvKmCtB7YEBH1IpL8Jh8yEqFJxIJt3o7Q0gk3EhHC4gn3cinXajvT2EbdsqUS47UCo5EIt5USw6MTy8dFulKYqyuKGT4HCUYFlOWBZQKjngdFrweIooFh0AXHA4LDgc1Fgow+OxYFnlF/d1ALDg95cQieQRDucRj/vgdpcQiRQRCJTg8xXR3h5BPu9Ec3MaLpeFVMqFYtENl6uMfB5Ipdzw+0twOl3I5x3weksIBksoFp0oly2USk4cd1w/Vq1KwuMpo7Iyj3TahXzeDYejjN5eP5JJD9zuMgKB0osRFguNjVlYFpDJuDA46ENVVR7BYBGFggNDQ15kMm6Uy07U1mZRKjng8ZThdFro6/Nj//4wLAtobMygujoLt9uCz1dCdXUOuZwT+bwLoVAJfn8RLpeFUsmBeNyLWMyD5uYUfD4LQ0NexOM+5PNOFItOeDwlFApOVFTkkEp5EY3msHp1HF7vPIlTKMphiGUBX3jChf6sA29bXcJL6xenSZ5Op3HRRRchFoshGo0edNsl6Vh84AMfwN13340HH3wQbW1tB912vIhFa2sr+vv7D/nmLAb6Ejm86duPoCuWxaZlUdzxrpMR8s1+oIn5svv3y+oU0wSyWYk+8PUXXihi27YX0NCwAcWiG8mkdA5xuWSFrKvLbKsok8MeqViyQVRlnqDeBFfOKWpXKpm0nHK5iFKpBJ/PhXTaPaKWzXqCUklW9yMRo5Tt9ZqaC0CiEIwK5POmtqGjQ7ZNJEybWLfbRD1Y5xGPy+suF/CmNwGnnGJqOQoFqVHbtk22C4eN6B07U61bJzULsZgpjh4cNBGJNWtMTQi7OyUSElnO56XuoqnJnE8sJhEYdoaKREw7W6fTnBO7YfHaTxHTdNq0ja2vF42NysqF+AQsHIVCAffccw/OOecceCZSA1SUKfDXnX14x+1bEPC48PDHz5gT+242iMfjqK2tnZRjsTjPYAIsy8IHP/hB3HXXXbj//vsP6VQAgM/ng2+chE+Px7PoLwzZQgnv//GT6Ipl0VYbwu3vPhWVodmNBNjrKVIpcQwsS24efr/kEZdKcuMbHmbXJwcaGtzYudMz0vvc4ZAxymUVvVOmQxFyOVrc30ll7mH3JvsPINeWXM4Y8WxzTYeCjgM7NCUSeTgcPrjdnpHtAbnmsWaCgm/sZLdmjRjfHR1iwLMGgYZ1RYXs19dnulAxRYgiesDowvBAQJ7LZOTY5bI4Fh0dMmY0alrQlsti8Gezcu2trBRHpbFRrsfsgNXaKmrdliXX5WRSOvBZlihw5/PiVNhL8KJRGdflkjm1tpp0MhZZd3aObhfr8ZjxSyVJk1q7VsY+krs8LQX7QVka3P2UFG2/+tgGVIYDCzybiZnK531JORZXXnkl7rzzTtx9992IRCLo7hYxkYqKCgQCi/cfMh0sy8LHfv4Untg/jIqAB9971ymongOnoqNDfvNGMjQkN7RcTm527IE+PCw3Prcb6O8PYP9+uQl1dMgP2wvagkOKoihTgloRjEpUVJgWsPm86TbEuoF83nRoYktZt1sMcqczh3w+iIoKuT5ZlnEoaDS73UbxenhYrmUOh2wzPCw/kYgY0azFYISEDkc2a8Tpkkl5fflyeV3mIdfKQEAcl0hEWrr29cm1dflyMdQLBTmPnh75u6dHnqcaNtvbUsWbjlJjo7wWjcq4ra0yNuswiNst4+dypt5i7JrbWC0Kn0+eczjEyVq2TN4vRVFmTjJXxP++KIr3phNaFng2s8eSciy+9a1vAQDOPPPMUc/fdttteNe73jX/E5pD/t//7cB/P9kJt9OBb118ItpqZ1+nY3BQbopVVea5UEhupgz/53Ly93PPyQre4CDQ2RlCuWxW1YaGVJ9CUZSpwxV16jdQWK5QEAOanZqKRbn+AGaVPR43xnEkIts0NJj0ILdbsnz9fhm3VJLt2HUplTJpm3x93z5ZIKmqMt2fHA7jMDCCsmKFSR9KpSRawGJmt1uKrFn4HQjI/sWi6dqUTo92cvx++YlEzDWYbWkLBaN4PTQkUYOxKUiMjng8Mt9w2KQ+Eep6ZLPyPo3XuWkiLYqGBtWiUJTZ5qeP7UcqX0K938LJKyoXejqzxpJyLJZgOci0eGBbH27+4zYAwA2vPwYvX1M768fI5cQpcLvlb4bUBwelb/rgoCmQ7O6Wbaur5YZbUZFFZ6esisXjcvNRFEUZi1312o49xcnpNKv7jAywwxMVrvv7zXPUhqisFOM4m5VxmOLj98u1rFBwjnRo8vnkp1iU/dxu0yo2GJTnqCWRz8t20aiJnACyf2OjSYOiFkVNDUYWWlj34ffLmDU1Mu6qVbL/8LCcRz4vr1dUmBoJ1rW5XKY2I5mUayxVvHm88Qx8p1Mck0xGxs5mxbkIBuV8YzE5v2j04CrYqkWhKHNPqWzhtr/sBgCc0VSed5HjuWRJORZHAl2xzIhWxcWnLsdFpy6f9WMwBWrfPrnpFItyw8vn5aY3NCQ3oVzOCDtFo+ZGk0h40NcnN1j7zV5RFIVwNb5YNCrTgEk1osFODQevV4zYUMiIzLHddbks1yrLEsO3VDK1EXY9injcCNY5HNbIPtGoqcVwOk1KUE2NRBeCQTHc3W4Tga2uljmUy+b4+byMzWgAVbtbWuRvtqlta5MUJu7b1CTnwnaygYBch+3jAzKnzk5Z2Dn2WHFIkkkzLlOVxiOVklQl6SQl55ZMmhqJQEAiLc3Nk4s8qDOhKHPHH5/vwf7BDCoDHryk7vBqta6OxSKiUCrjQz/egsFUHkc3R/HZ126c9WPQqeAqGCMSW7fKjYfF16GQ3FwHB03h4LPPyn779weRSBi1W3UqFEUBTGqTtH81zgMN+lLJ1FF4vabuoVyW689YPQjWCASDsr9lybWposKkCrndYqCHQsbwZ5EzHZrBQTHow2FZUBkeFsO/qcnoR5TLJmISj5tUJr/fpIZSzbpUMulQTqdxULZulZqJZctkP69XzovpWYxkWJaJfDBNyrIkMtzVJWO0tMi5RCLyMzQk74XfP7rAulCQeTHSAJhUJna7WrlSUqi0PkJRFgf/+ZBEK956yjJ4C9sXeDazizoWi4iv/XE7HtszhLDPjW9cdCL8HtesH4N1FRUVUhy4bZvcDONxWS2jcBMNgIEBE0LftUuckFhMlru4yqYoigKIcezzmeinvUMc1a1ZW+D3i+HL9qw1NWL4J5OymEGlbIdDWrOy9oBNJCjMxogGW8LSsUgkCgiHR9dusL0qIx4s0qbjwMLsYFCcDgrAWZa8xvF43HRajun1yjGWL5doxerVJoVIrpnyHlRUyHNMVUok5LwtS7br6BDngK1m7YRCco1ubBRHwl4DQWVt7qOpTIqyeHmmI4ZHdw/C7XTg4lNbsfkhdSyUOeDJ/cP45v07AABffNOxWDkHxdosxHa75SY2PCxdRHbtkpsiO6ukUnJDDQblptXVJTfidJo3VP3YKIpi8HhMbQRTjsaLZDJ1iU4DIwU0/CMRucY0NsrvbNaoZLPuoFCQaxfrBFif0NQkBjZTf3w+E+moqJDt2RHJ5zPjsfMU04Y4l3DYnBfrOWigr14t58KFmmBQujFVV8sY8bjMxbLkNbaCbW6mMriJMITDJlri8cjY4zU5ZNG31ytzPpTjoM6EoixOvnX/TgDAazY1oTF6+HVEUAtxEZAtlHDNz55E2QJed1wzXrupeU6Ow5W64WFg925gxw5xMFIpU8jY3S0rY9EoW8vKc/ZcaUVRFEJD3bLkOkLnwo7DYbo8scYiEBCngIsYPp+k6+TzkupTKomxD8i1a2DAOAxut1yPWG+Qy5mOS16vGOuJRGmkS1IiIYZ7RYU4Lz6fSf+srZVr3sCASS2ig1MoyPgNDfI3BeRaW2V+DQ2SUtXSIuMwtYuGPyMK69bJOIWCRC9cLnGe7BGWQkEWcVwTBKrZmapQkHmr46AoS48XuuP4zdNdAIArzly9wLOZG9SxWAR88/6d2N6bRG3Yi+v//ug5O47TKTe6nTtFYburS27AzCFmB5VMRm7axaLczFKp0Tc/RVGObOgcMNrACIW9QJv1FhS0CwbF6C+VTGpQOCxGOqMS+bypIQgE5HUubog4p+xHR4ZOBlvQejxyzZLnrJEWsWxZ29Ul2zQ3m2seU7Pq6010o6HBRAQyGXk+GjUK2Z2d4hSsWyfbMgWpUJDzbHmxJf3YiMLBogxsSzs0NLogPZuVxaDOTnO9Tia1/auiLEW+9kdJe3rNsU3Y0BhF4TA0qtSxWGD2D6bx7QckLHb93x8z6yJ4dkSNVhwL5iqXy6YgkTdQtqJlG0TmJSuKogBGdZpGPVWn3W7T5YiFw8UXG54Ui6MXJ6jlwHaxHo9cd1IpiT4wIhCPSwSB6UIs+uYcymVxHMplk9Yk1y7nSL2E2y1jsFYCAE46ybR9dbtNalJVlRjwliXORi4ntQ+dnaYGg3VqY52DVGq0eN1YDhVlGCtQVypJ++/hYZnnsmVy3kNDsl1LizoXirJUeK4zjv99phsOB/Dhs9cu9HTmDHUsFpgv/u8LyBXLeNmqGrz62MY5PVYsZpyJ/n6jsp3Py/O84bIVI1Ma1KlQlCMPphs5nSYqwdQiKjGzHWxfn1llZ40F6xMYuaADQWOfHZW6usSBqKiQ6xC7J7F5RKkkxwmFjDPBNq2sS4jH5bV8Xn6n06O1Mlhcnc8bB8PhANaulR86RJYlv7u6jEOUzZrakOZmSWEaGJDmF4xo1NaaeU+kETGZYuqxAnVdXRKdaG01Oh88n6Eh2a55bjJnFUWZZb52r+iTvebYJqxriCzwbOYOdSwWkC37hvCbp7vgdACfe93GORdIGRiQm1prK/Dww5IOlUqZFUAWbrPDCtVoFUU5cmB6EKMNbrc8R+M+GBRjN5MxAnhMcXK7jUPBznL2ltSMNHCfTMYUc3d1mShBICCPeR3iOKwFo4HO6EQqJeN3d0vbV4mMONHQYBpT5HJGCZupVzwvalBQ1dqy5DENe49HWrYuW2aKtTs7ZczhYRl/48bx05OyWeMosAVvJDJxKhMjJ/G47NvUJNuPhS3Bczmtt1CUxc5T7cP4/bM9Eq046/CNVgDqWCwo37hPukC98YRlOKopOmvjjrcyFo+LYwHIzbKvT26GTE3IZuUGak9VOAxT/xRFGQPrEwCjMcEWqzS+x9ZQVFSMNpSDQbnuZDKj28zSaM/lzLhsIcs2sDU18lomI+PW1BjF6GBQxmGDCbZ89ftl+3hcxnO7xaGorpZtee2qrzf7NDfLeIxA8Nq4fbtJp6Khv2aNGPN798rjWMxECfJ5GW/tWqMHlMuN3p9QN4iq3CwOn0wqk8cjP+HwxK8zcqMoyuLFsizc8D/PAQDecHwL1h7G0QpAHYsF4/muOP74fC8cDuD9fzc7nQHGWxmjwFQiIRGKnTuBRx8dnZaQz8sNKp+XG7SiKIc/9lQhLkTYjX+mFtGZsIuxUc+BRjENXK9XjPueHrNwwc5IHo+JaLCdK/dnGlEuJzUFtbUmpSmRMIXZdAZ4XevuFgegtVUiEew0BQAuVxk+n2hLtLbKmE6npIFSA4L7sMYiHpe/V60yERqvV86Z18joi2tALB5vbJQx+/sPFKBjO9qqKvOc1zu5VCb+DwqF0cXcpFCQ1/k/VBRlcfLrp7rwt71DCHhc+Nj56xd6OnOOmpELxB0Py1LYq49pwuq6CZakpsB4K2OJhAjgcTUtFpMVuP37JToRjcqNKRYzxoNGKRTlyMCyTB2BXSGb6U3ZrLzODE2XSwxspuVks2Jo+3xilIdCYnznciadiPUWHNOuD1EumzQj1jawMxKLsru75TEXP6qqxPB3uUxdBeslqL9TWUldiiIsSxyLujqZbzptHKJoVNKXxjpX6bRxOlwuOYdi0UQtsllzToz2hMPm3O0doBIJeV/G41CpTD6fUdwez7E4VKG4oigLT7ZQwhf/9wUAwPvOWI2minFEag4z1LFYADL5En79ZCcA4OJTl8/KmHahJqYspNOmhzvbOLKmgjnRDocp1KZzoSjK4Y/9+84aCEYsC4XRToHdiM7nxagHRgvIsS6jp0euKazPcDrl2hQImKJsXn8GBoy+RCAg48fjRryO7WPZoW5oyKReOZ2SNuX3i3HNBhROp9QlDA4W4fOZDkt1dRJdYEvtFSvGF6LjNbOmxhj2bjewb59xEjj/piaZW2Wlab9LqBvE6MpYJpPKNLZLlD1qdLBCcUVRFgffeXAXOoYzaK7w472nr1ro6cwL6lgsAH98vgeJXBHLqgJ46aqaGY+Xy0kYPpORG3W5bFbY2G+eNz0KWIVCcsPOZkfnV6tzoShHLrnc6MdsHUvjmNo2+bypx8jl5Dri95ttKTLHhYtQSFb1mV7FY7lcsk2hYBY+mEJFhWm3WxwHFmnbi6/p+NARsSzZv1AAymUH8nnjEEWjMl65bBS2x8Nu8FdXS9Rk2zapTfP5TCSDjlQkYuog7GlJs5HKNLZLFNPKqqpUx0JRFjudw5kRle1PvPooBLwTqF8eZqhjsQDcv7UPgLQcczpn3gkqnZYOJV6v3MDZ4aS726QPdHfL6hlvulSFtWtVqFOhKMp4UPHZLnwXCIhRnM8b54JdlgAT5WChNh2JYlHGKhbl2lRXJ9sPDMiYoZBELfJ5GTObNVEKRjsokBeLyTEiEYlGBAJGk6dQcI6oahcKUmPhcMi1cXDQXBvtbVx5rjT4eQy3G2hrkwUcRiJYf+H3m3OxpyXNVioTu0RNpl2toiiLA8uy8NlfPYNMoYSTV1ThdZuaFnpK84Y6FvOMZVl4aIc4Fq9cWzcrYw4Pmxsbays6OuSnvV1esyy5gUcicoOOx00xImCMBUVRlIlgyiQjG1SiZmc5qliHQrINdSU8HuNcAGL4F4smYsHIRygkRjNby1qWSYfy++Uax9oFp1OOGwphJDJRLMpjEfu0EAyaYvIdO2T1n07IwIA4DdmsPKZzYTf4d++Wx0cfLduxKD0cNqmnAwMSCRkvLWk2U5nUmVCUpcP/PNWFe1/ohcflwL9eeOycywksJtSxmGf6Ejn0xHNwOoCTVlQdeodDwJt3XZ04GLmc3Ax7euRm1t8vTgRzjdlCslg0P16v6Q2vUQtFUQ4FU47YtpUd5SzLrPTn83J9qa01Rc+AGO2MStApyeVMKpXbLQZ7sWiiIIxUOJ2mSJwq29GoGOp9ffK3adGaG7nWuVzijASDMg4dlFxOnJahIampsBv8uZy5dlK52+sVZ4QpScmkiPs1NU2sSaGpTIpyZDGYyuO6/34WAPCBv1t7WIvhjYc6FvPM9t4kAGB5dXBW8u0Ylvf55MZK0SbeUHt75YbW0CDbs8tJuTw6vaBQMIYBO8UoiqKMRyDAOgYTVWDNA+so3G6TnsmUy0DARFb37DE1HLmcaQVbUWEMcBr1TqcY6JmMGOSMcAQC4hB0dhqHBmBXqtJIRye/3zgugPzd2CiLMUNDkirq9cpYNPipycH6Dra7ra+XcymVZP+GBqO3MR6ayqQoRxaf//VzGEzlsb4hgivOnB05gaWEOhbzTHdMlu1aqw9yJ5oC+bzcjLu7TXrT0JApgqyvH62kncnIDbuyUvZPp+U3O7i43fKcKm4rijIRDocY9WxJS8eCHZo8HjGkmdLkckk0oViUawvbzrJIO5ORcdmpjoTDJt2pWBSnw+uV8bNZcQIaGmQ8RjdKJdZhlFFTY2oswuHRhdJ0LiorxUFobTXXRUC2DQRMPZpdo8LrlTEtS85rMo6COhOKcvhz3wu9uGtLB5wO4Ev/sAle95EnNKOOxTyTzEk4IOqfoCXJFMhmTTeoRMKspPX1yU2Pj5ub5Tfzgb1euRlWVkraVCJhhKVYoKkoijIeVONmoTZbvLpco4uU6Sww8rBs2ejUp8pKk4YJmNX8igqTulQsyvPsMMW0pkxGnquqkufWr5eFlVxO0kJFXK+AaFSiEIODxukZC9OrxraeZfF1KmXa2QaDJhrc3S3HajpyajIVRTkIfYkcPvrzJwEA7z6tDce3Vi7shBYIdSzmmfIsFjFQu6K1VRwGdnZiSkAuJzdCFj8yb5kCU2wJyfa0XM1jRxS2ilQU5ciDaZN0IBjFZMSgXBZjndeLigox9FmczG0sS64z3HZw0IjhUXWa16BEQo5XVWWcCWpr8DWPR8ZYvhxYt05eq6mR7bq75VooehcW6utlEYVzHo+DdWdi8TXfD9Zd0IHZuFHrJBRFAcplC9f87En0JyUF6qPnHf4K2xOhjsU8w0hFPDsziWu7qqtlSXQimzUF3IA8X1NjlGSHhkyHKMsyhYrs1pJIGF0Ldndh9ENRlMMfu5aN222McYfDtFdlJyfWUUSj4gS43aY7U0ODaUVbLMqqPuslfD6TclRXJ9eblSuNUzI8LB3tvF65rlEFPJuV/QcG5Jp13HHiWLDFbDIpURGfj12k0mhoEOeA0dqpdmdi8XUgINfHTEbOPRqduGBbUZQjj+/9eTce2NYHn9uJf7/oBPg9R4ZmxXioYzHPNFXKnWjvQHpG49hVXR0OuTHGYnKjTSalzSzTn7JZuZF3d5u84BUr5Cbb2Wm6urDIkbnSfX3meBTasyytv1CUpQYNeqYwMSXJ7jgAZuHB65VrB+siUilxFMJhuZYEg3INYj1FQ4OpRchmZXwKx7EuIpuVa05Tk0QbWNBdXS2P2QY2nweeeUauV8uWmUiszyc/2axsW1FhmlJUVJji6Lo6Oe6WLXGsXGnE6/z+6XVn0uJrRVEOxjMdMXzpdy8AAD772o1HXBeosahjMc9sbIoCAPYNpjGczqMyOI5y0iQYq+paWSk33FwOWLNGDIX2dlmlY4Fhfb2suOXz0gKyrU1u8n19cqN1u+UGHQiIATA4KAYEb+ymuLs84thoe1pFmRk09tmpjU48oTHLbZiyWC6bjm72KCNgrg9ut0QtGxtlwaFQMMrWPp9Jd7Isea5QEEN71Sq5DlCBOhiU/ZkW5PfLtcPtlutEJCIr++zUxDTMYFCO7XBIPVg2C6xeLcfbs0euXStXijNAoTq/X45fW2ucE49HrkOZDEbqJsZGIFgozmudz1ce5QDM1EFQZ0JRlLEksgV86MdbUChZOO/oBlx86vKFntKCo47FPFMZ9GJdQxjbepL4vxd6ceGJy6Y1zlhVV3v7xFJJHASu6pVKklpQKMjKYEODyTkeHga2bZMx/X4xHthGsb5ebsJ9ffK4UJBt+vszcDq9IwJWjGJQfZc3bRpDRFOqlCMdtk4NBIzeQiBgUnXYQIG1DdmsabUaDosRD5jWqXQUAGPEp9MSYSiXZfHg7LNN5LK7W45RLst4jFBms3KNqKoyhn9Dg1ndb22Va8n27cDevbJ9KGSioStXShS0t9cUQSeTpo1rXZ04LKWSSYvauNEUfrMFbT4vc6+oEOcinTYpmi4XRlKb6IBMFIFwHSQLQR0ERVFmg3LZwlX/9SR29afQVOHHl9606YgSwpsIdSwWgPOPbsS2nh24a0vHtB0L4EBVV59PnmPxYygkfw8PY0SBtr5ebvw+nzgCmYzpA19VJTfqVEoMCXaP+sMfgH37TLvaUimHYNB0U2E3mGJR5tLRIdsGAsbIYNF4LCbHogEFmDQNbkdxLUWZSxwO4wBTh8DrNSv4FJCkwjPTCCeCNQlerxF6o0aDyyWOfn29iTiEQrIq39EhK+lHHy1OfHu7fI8cDrNiv2yZ7Ccr8fK99PtlPkND5vtC9elcTvY95xxxFCIRozeRTssxnE7TXjqblZqFtWtl/FRK9nM4gJ075TtrWZJqecwxJnVo3z7ZpqbGdHrKZOR7H4/LGBs3mugHnR9GC7LZg6cnVVZOHGE4WARCFzEURZlrbrl3O/74fA+8bidufftJ085AOdxQx2IB+IeTWvH/7tuBP23vx7OdMRzdXHHoncZhIlVX+6oenYdg0CjHEuYsu1xm1ZQpE8yJzueBN7wBePRRWY0UIymD5ma56Tc0ABs2mPoMpxN49lkxTAAxZGprpa1tLCZGUGWlSa+Kx013KsBEXNgJhilXdoejVDKGlMdjVjrpoHi9pmakVDKCgF6vaRVJA5Grt8rhj2gbmDaljY1itLNzWkuLfD527pTPYSIh3w2XS74Lvb2m2LdQkM8uc/+rqsS45sr84KD8sLNaTY187qNR00q1qcmIVK5dK2P4/RK56O2VHzrvjY3yw1asw8OSWmRZwGmnyRgul8yP352mJgrFyfc7EjFFyqGQOAtcPKDT4/ebOggWWLPzUSYj7xe1JezOByMKxaLMq7dXrg0bN8rc+L6NLXieTHrSoSIMGoFQFGW++d0zXfj6vdsBADe+8Vgcd4S2lh0PdSwWgOU1QbxmUzP+58lO/MtvnsePLjt12uGzQ92Y6TywK5R3HIe6WJS6jJqa0Tnc6TTQ1SWGSWurpEFISlUGp5wCHHusOBXRqElhYNpCb6/sw1SPo44Ctm4Fnn9eni+XxTDLZGTMZFK2XbvW9JuPRiWVgrndhYIch8WhoZCcezAoK7DDwzKGzyd/ZzIyVj5vnC6uJPOnWJTX2B+fRiTTM1wuOX46bdLB+L4yFUWZfxgNsDuFjD4wgsbagEhEPkusIWppkZX3xkZJFRoclM+iXagtFhMj/Nhj5bPR2SkpQPv2mZQ/RjSCQYkobNggTvSqVfKZyeXk87Fvn2xXVyfjdnfL53b5cvnOnHSSzKlcls/ZqlWmxWsuJ2MuWzZa4C2TkbEGBkyEkkKYrENoaRldl2G/LkzkLAwNHdgliTUPXMCIxUZHFgDzms8n7zHfe0DO4VBF0uocKIqyVNjancDVPxW9ivec1oY3nTT9zJPDEXUsFohrzl2HPzzbjb/sHMDPH2/Hm09undF4h7oxj02bGq/doj09ChDDwG5QbNwoToHT2Y03vnEDWlrM+IGA6cwSjQJPPil/U5HX7ZZjnHKKrGTG4xLFSKVk3OFh2ZYrvnQI2DM+Hpe5x+OyT0MD8KpXyXwsC3jqKakVicXkp6rKRCPodLEDTigkhprDIXNetkyMyv375fXubnGinE6ZTzIpzk8oJOfR2CjGarEor6VSYhAySpLLyU84LNuWSvI6V7xZl3I4YW9TyoLgqe1bHok+UQiNxcwej3wWa2pMFI6dy4pF+eykUvK83y//U67gV1bKqrrLZRzR2loZs75eVtBXrpR5pFLyc9RRJiqWz8v34sQTgfPOk8/frl2mdoir9H6/7FNfL046ayZiMTneU0+JcxIIyOuNjbJfS4t8/lMpcVZqasz7x3FbWg40yNmytaHBfD9LpQMjlhNxKGdh7L6HWsAY7zXtoqQoyuFGbyKLy+54DOl8CS9fXYNPvXrDQk9p0aGOxQKxoiaED521Fl/+/VZ89u5ncOyyCmxojM7Z8SZKm7KvOu7aJSv/iYQ8jkTE6G5uNtGMUgno7k6jvn784/h8YqwFAjJeb68c0+sVA4/dZsplOc7AgBjn5bIpHK+sNC0q/X4xuJJJo8MRDovzwraZLpc4GSeeKJ1mentNwTlXYFesECeBBac+nzxubDSRi5e/XN6LbBbYvBl4+GF5P9xuWY1etgwj511ZKdt2d4tDw6LaYFAMbBqadCLoJDGSwlx+vg+5nFmN5naMzHBVnt2CaGzT+ASMMGIkIv+vaFTGZVSIiuos1i2VZHsev1AwHYnsrUZpFFJfoFAwBfrBoKnXoToyHTqqwSeTMle/33QwonIz36dCAejvTyES8Y7UEsTjo0XYmprEQLcsY3jn86PfB6bVhULyv3G75blSSea1bp18/li03NQk50CjdzzDmE42zzOblXnE4/Kc1yvbMxq4bJl8dvmdCwSM/kN7u3G8/X75LK1aZTq68buZz89PK9Tp7Huw16eawqQoirKUSOaKeM/tj2H/YAbLq4P4fxedCLfLudDTWnSoY7GAvO+M1fjrrgH8aXs/Lr39b/jp+16GlsrAnB1vIkMimxUnYO9eMWhqamT7eFyM5kxGnIJAYPKpP5WVYujH46ZwOzrGbwoETOepsW00xxo54xk/451HY6M4K0xvYt99ttEFTFoT6zWAA424lSulm87evbJNba04Ium0OBN9fSZPvqHBGM9cWQckyrFzp0nzam01+feMdLBVcGurzImpX3194iSxA09Dg2zHlJmODvnhuUaj4jytWiXvRSAgaT7LlgHPPScr5szZD4dlfBqw1EPJZMQIXrvWrOwnEkBPj+lmlE6bMRglYJQpmTQtTVncn8vJ+MuXGyGzYlFS7Pr6TL3LM8/EcfTRVWhrk9XzwUE5xooVwPr1pviXzm65LPNKJk1EjMdkbRAdOhYTMy2PtQbjRQHGPh773FjBtPG6Fdm35fdt+XLg1FPl7/G+DwvZClUdAEVRlIOTL5ZxxQ8fxzMdcdSEvLjjPS9BdUiLtcdDHYsFxOV04OtvPQFv+tZfsKs/hbf/xyO48/JT0VQxd84FcKAhMTgoRhrTSEhtrRh5vb1ieDc3T/1YY52JycxnstuMZ/TZoysTGWcstj2UEReNSo79ePuuWjV6NRs4cKxVq4CTT5bj0Njna+M5XPZVa0YZvF5jDLPzF6M7qZQUysZi8tiyJBIQCIghu3KlvCfHHgucfrqknu3bJwY6ldctSwzi6mp53+go2Z2wri6TP8/zGBqSfZub5f3gtj09JhWMdTLV1aagnvNdvlxqbtrbxfFYuTKOE080kZN162QuVVXyHrlcYtDbjffGxon/h3OZljNVJ2BszdPBUCNfURRlcVEuW/jYz5/En7b3I+h14XvvOgUra0MLPa1FizoWC0xVyIsfXnYq3nzrw9jdn8Ibv/EX3P6eU+Y0LcpOLier3uxrPxYKYw0MiOHJqMLBxlvovOrJHnemq7yTMRIn2mY8h2sqBmsgIJEC1geMl7ZjH7etTcZ+2cvk/0nxNGDiiBLPIRAYncefy42/Qn8oh43z4mo/0+ZiMaBYzKOiwtRBtLSMVlM+mJM4HnOVlrMYPt9TZapzXornqCiKMhdYloUb//d5/OqJTridDnzz4hO1A9QhUMdiEdBcGcB//dNL8a7bHsOO3iTe9M2/4F8vPBavP77l0DvPEHY2Yk/7sTAFhuq+EzkW9tV21j1MlHKiHJzpGHOTdXQAE42YLDNZoZ/MWJJeN4CXv1ycm6ms8M8XS/HzPdU5L8VzVBRFmSssy8JX/rAN3/3TbgDAl960CWeun6DAVBlhSVadfOMb38DKlSvh9/tx6qmn4tFHH13oKc2YZVVB/OJ9L8fLVtUglS/hwz95Ap/4xVNI5Ypzelyn0xTJFsc5FLvzeDwHdyo6OiQ9hu0mfT4jlpfNzukpKPPE2HSu2RrL5wPC4SIqKxePI2FnKX6+pzrnpXiOiqIoc4VlWbj5nm34f/ftAAB89rUbta3sJFlyjsV//dd/4eqrr8a1116LzZs347jjjsN5552H3t7ehZ7ajKkIevCDS1+CD71qDRwO4CeP7ce5X30Q9z7fM2fH9PlMilM6feDrLNatqZnY6BscFMOjqkpy6dlZqKrKrIIqylJlKX6+pzrnpXiOiqIoc8VX/7gd//5/4lR85jVH4dJXtC3wjJYOS86xuPnmm3H55Zfj3e9+NzZu3Ihbb70VwWAQ3/ve9xZ6arOC2+XE1eeux48uPRXLqgLoGM7g0u//De+942/Y3pOYk2NWV0vOfDYrxbXs39/fLykr9fWjBbPs5HKSOhGaoI4pFDLtVBVlqbEUP99TnfNSPEdFUZS5IJkr4uY/bB1R1f7Ma47CZa9ctcCzWlo4LGvpSHXl83kEg0H8/Oc/xxve8IaR5y+55BIMDw/j7rvvPmCfXC6HnO2OGI/H0draiv7+fkQn07JoAUnni/j3+3bhtr/sRaks/ybn9AS6D0m56EQp4UUh4Uc574YDDji9ebgiObgjeTjdRuLYsqwRpfBywYlCLACnt4jxxMMtCyjn3fBUZOD0lA/cQFEw+jO1mFiKn++pznkpnuNkWKyfKWVpo5+rw5uyzSL+xPnrcOlpK+f0eIVCAffccw/OOecceKjiuwiJx+Oora1FLBY7pO28pIq3+/v7USqV0NDQMOr5hoYGvPDCC+Puc+ONN+L6668/4Pk//OEPCAaDczLP2eRYAB89FvjtfieeGnSO+tDPKq4yXJVZOMN5lAsSyHJ6ynC86FCMPq5jRGWZT5dLDjhcB07OKjlGtpuzuSuHAY5FqUa+FD/fU53zUjzHybE4P1PKUkc/V4c7YY+F81rKaIo9h9/+9rl5OeY999wzL8eZLunxcuUnYEk5FtPhk5/8JK6++uqRx4xYnHvuuYs+YmHnUgDxTAG54sKuGBaKBTz4wIM4/YzT4XGLd93d5UAsNloDg/D5xia9EivjM95najGxFD/fU53zUjzHg7HYP1PK0kQ/V4c/fo8LEf/8mcZLKWIxWZaUY1FbWwuXy4WentHFzD09PWhsbBx3H5/PB984Vccej2dR/xPHo2YRzLdQKCDqBZqrwiPvX3XQdI4JhaSDVKEgAmzLG0STQNtVKhMx3mdqMbEUP99TnfNSPMeDsdg/U8rSRD9Xylyx2G3SqcxtSRVve71enHTSSbj33ntHniuXy7j33nvxspe9bAFndmTj94vhQXG0WEx+V1UtPYNEUcayFD/fU53zUjxHRVEUZfGxpCIWAHD11Vfjkksuwcknn4yXvOQluOWWW5BKpfDud797oad2RDNVETVFWUosxc/3VOe8FM9RURRFWVwsOcfiLW95C/r6+vC5z30O3d3dOP744/G73/3ugIJuZWFQQ0Q5nFmKn++pznkpnqOiKIqyOFhyjgUAfOADH8AHPvCBhZ6GoiiKoiiKoigvsqRqLBRFURRFURRFWZyoY6EoiqIoiqIoyoxRx0JRFEVRFEVRlBmjjoWiKIqiKIqiKDNGHQtFURRFURRFUWaMOhaKoiiKoiiKoswYdSwURVEURVEURZkxS1LHYiZYlgUAiMfjCzyTpUmhUEA6nUY8HofH41no6SiHAfqZUmYb/Uwpc4F+rpTZZql8pmgz04Y+GEecY5FIJAAAra2tCzwTRVEURVEURVkaJBIJVFRUHHQbhzUZ9+Mwolwuo7OzE5FIBA6HY6Gns+SIx+NobW3F/v37EY1GF3o6ymGAfqaU2UY/U8pcoJ8rZbZZKp8py7KQSCTQ3NwMp/PgVRRHXMTC6XRi2bJlCz2NJU80Gl3UXwJl6aGfKWW20c+UMhfo50qZbZbCZ+pQkQqixduKoiiKoiiKoswYdSwURVEURVEURZkx6lgoU8Ln8+Haa6+Fz+db6Kkohwn6mVJmG/1MKXOBfq6U2eZw/EwdccXbiqIoiqIoiqLMPhqxUBRFURRFURRlxqhjoSiKoiiKoijKjFHHQlEURVEURVGUGaOOhXJIrrvuOjgcjlE/GzZsWOhpKUuMBx98EK973evQ3NwMh8OBX/3qV6NetywLn/vc59DU1IRAIICzzz4b27dvX5jJKkuCQ32m3vWudx1w7Tr//PMXZrLKkuDGG2/EKaecgkgkgvr6erzhDW/A1q1bR22TzWZx5ZVXoqamBuFwGG9605vQ09OzQDNWFjuT+UydeeaZB1yr3ve+9y3QjGeGOhbKpDj66KPR1dU18vPQQw8t9JSUJUYqlcJxxx2Hb3zjG+O+ftNNN+HrX/86br31VjzyyCMIhUI477zzkM1m53mmylLhUJ8pADj//PNHXbt+/OMfz+MMlaXGAw88gCuvvBJ//etfcc8996BQKODcc89FKpUa2eaqq67C//zP/+BnP/sZHnjgAXR2duLCCy9cwFkri5nJfKYA4PLLLx91rbrpppsWaMYz44hT3lamh9vtRmNj40JPQ1nCXHDBBbjgggvGfc2yLNxyyy34zGc+g9e//vUAgDvuuAMNDQ341a9+hbe+9a3zOVVliXCwzxTx+Xx67VImze9+97tRj2+//XbU19fj8ccfx+mnn45YLIb//M//xJ133olXvepVAIDbbrsNRx11FP7617/ipS996UJMW1nEHOozRYLB4GFxrdKIhTIptm/fjubmZqxatQoXX3wx9u3bt9BTUg4jdu/eje7ubpx99tkjz1VUVODUU0/Fww8/vIAzU5Y6999/P+rr67F+/XpcccUVGBgYWOgpKUuIWCwGAKiurgYAPP744ygUCqOuVRs2bMDy5cv1WqVMirGfKfKjH/0ItbW1OOaYY/DJT34S6XR6IaY3YzRioRySU089FbfffjvWr1+Prq4uXH/99XjlK1+JZ555BpFIZKGnpxwGdHd3AwAaGhpGPd/Q0DDymqJMlfPPPx8XXngh2trasHPnTnzqU5/CBRdcgIcffhgul2uhp6cscsrlMj7ykY/gtNNOwzHHHANArlVerxeVlZWjttVrlTIZxvtMAcBFF12EFStWoLm5GU899RQ+/vGPY+vWrfjlL3+5gLOdHupYKIfEnmqwadMmnHrqqVixYgV++tOf4tJLL13AmSmKokyMPYXu2GOPxaZNm7B69Wrcf//9OOussxZwZspS4Morr8QzzzyjNYXKrDHRZ+q9733vyN/HHnssmpqacNZZZ2Hnzp1YvXr1fE9zRmgqlDJlKisrsW7dOuzYsWOhp6IcJjCvdGxnlZ6ensMi51RZHKxatQq1tbV67VIOyQc+8AH8+te/xn333Ydly5aNPN/Y2Ih8Po/h4eFR2+u1SjkUE32mxuPUU08FgCV5rVLHQpkyyWQSO3fuRFNT00JPRTlMaGtrQ2NjI+69996R5+LxOB555BG87GUvW8CZKYcT7e3tGBgY0GuXMiGWZeEDH/gA7rrrLvzf//0f2traRr1+0kknwePxjLpWbd26Ffv27dNrlTIuh/pMjccTTzwBAEvyWqWpUMohueaaa/C6170OK1asQGdnJ6699lq4XC687W1vW+ipKUuIZDI5avVl9+7deOKJJ1BdXY3ly5fjIx/5CL7whS9g7dq1aGtrw2c/+1k0NzfjDW94w8JNWlnUHOwzVV1djeuvvx5vetOb0NjYiJ07d+JjH/sY1qxZg/POO28BZ60sZq688krceeeduPvuuxGJREbqJioqKhAIBFBRUYFLL70UV199NaqrqxGNRvHBD34QL3vZy7QjlDIuh/pM7dy5E3feeSde/epXo6amBk899RSuuuoqnH766di0adMCz34aWIpyCN7ylrdYTU1NltfrtVpaWqy3vOUt1o4dOxZ6WsoS47777rMAHPBzySWXWJZlWeVy2frsZz9rNTQ0WD6fzzrrrLOsrVu3LuyklUXNwT5T6XTaOvfcc626ujrL4/FYK1assC6//HKru7t7oaetLGLG+zwBsG677baRbTKZjPX+97/fqqqqsoLBoPXGN77R6urqWrhJK4uaQ32m9u3bZ51++ulWdXW15fP5rDVr1lgf/ehHrVgstrATnyYOy7Ks+XRkFEVRFEVRFEU5/NAaC0VRFEVRFEVRZow6FoqiKIqiKIqizBh1LBRFURRFURRFmTHqWCiKoiiKoiiKMmPUsVAURVEURVEUZcaoY6EoiqIoiqIoyoxRx0JRFEVRFEVRlBmjjoWiKIqiKIqiKDNGHQtFURRFURRFUWaMOhaKoiiKoiiKoswYdSwURVGURcmZZ56Jj3zkI4tmnNmYh8PhgMPhwBNPPHHI7d/1rneNbP+rX/1qzuenKIoyU9SxUBRFmUfsxqL95/zzz1/oqU0b+zl5vV6sWbMGN9xwA4rF4ozG/eUvf4nPf/7zszTLyfH73/9+3P+P/ecPf/jDtMe//PLL0dXVhWOOOeaQ237ta19DV1fXtI+lKIoy37gXegKKoihHGueffz5uu+22Uc/5fL45PWY+n4fX652z8XlOuVwOv/3tb3HllVfC4/Hgk5/85LTGy+fzqK6unuVZHprTTz99lDF/zDHH4P3vfz/e//73jzxXV1c37fGDwSAaGxsntW1FRQUqKiqmfSxFUZT5RiMWiqIo84zP50NjY+Oon6qqKgCSLvOhD30IH/vYx1BdXY3GxkZcd911o/Yvl8u48cYb0dbWhkAggOOOOw4///nPR21z5pln4gMf+AA+8pGPoLa2Fueddx4SiQQuvvhihEIhNDU14atf/eqoNKE77rgDNTU1yOVyo8Z6wxvegHe84x2TOqcVK1bgiiuuwNlnn43//u//ntF8x6Yw5XI5fOhDH0J9fT38fj9e8YpX4LHHHhs1TiqVwjvf+U6Ew2E0NTXhK1/5ykHnPZZAIDDyPymVShgYGMArX/nKUf8rl8sFANi3bx8uuugiVFVVobq6GhdffDGGhoamdLyf//znOPbYYxEIBFBTU4Ozzz4bqVRqSmMoiqIsFtSxUBRFWWR8//vfRygUwiOPPIKbbroJN9xwA+65556R12+88UbccccduPXWW/Hss8/iqquuwtvf/nY88MADB4zj9Xrx5z//Gbfeeiuuvvpq/PnPf8Z///d/45577sGf/vQnbN68eWT7N7/5zSiVSiMOAQD09vbiN7/5Dd7znvdM6RwCgQDy+fyM5juWj33sY/jFL36B73//+9i8eTPWrFmD8847D4ODgyPbfPSjH8UDDzyAu+++G3/4wx9w//33jzrHqbBlyxYAwIknnnjAazt27MBJJ52ENWvW4K9//Svuuece7NixAx/96EcnPX5XVxfe9ra34T3veQ+ef/553H///bjwwgthWda05qsoirLgWIqiKMq8cckll1gul8sKhUKjfv7lX/7FsizLOuOMM6xXvOIVo/Y55ZRTrI9//OOWZVlWNpu1gsGg9Ze//GXUNpdeeqn1tre9beTxGWecYZ1wwgkjj+PxuOXxeKyf/exnI88NDw9bwWDQ+vCHPzzy3BVXXGFdcMEFI4+/8pWvWKtWrbLK5fJBz+n1r3+9ZVmWVS6XrXvuucfy+XzWNddcM+358jnOLZlMWh6Px/rRj3408no+n7eam5utm266ybIsy0okEpbX67V++tOfjmwzMDBgBQKBUec4Wa6//nqrtbV13NfOOecc63Of+9yo537+859bbW1tE45nPx/LsqzHH3/cAmDt2bPnoPMAYN11112TnreiKMpCoTUWiqIo88zf/d3f4Vvf+tao5+z1BJs2bRr1WlNTE3p7ewHISnk6ncY555wzapt8Po8TTjhh1HMnnXTSyN+7du1CoVDAS17ykpHnKioqsH79+lH7XH755TjllFPQ0dGBlpYW3H777SPF2Qfj17/+NcLhMAqFAsrlMi666CJcd911057vWHbu3IlCoYDTTjtt5DmPx4OXvOQleP7550e2yefzOPXUU0e2qa6uPuAcJ8vmzZvHjVbs3bsX99xzDx566KFRqValUgmtra2THv+4447DWWedhWOPPRbnnXcezj33XPzDP/zDSFqcoijKUkMdC0VRlHkmFAphzZo1E77u8XhGPXY4HCiXywCAZDIJAPjNb36DlpaWUduNLQAPhUJTntsJJ5yA4447DnfccQfOPfdcPPvss/jNb35zyP3oLHm9XjQ3N8Ptds/LfOeSzZs347LLLjvg+SeffBLV1dV45JFHDngtEAhMenyXy4V77rkHf/nLX/CHP/wB//7v/45Pf/rTeOSRR9DW1jajuSuKoiwE6lgoiqIsITZu3Aifz4d9+/bhjDPOmPR+q1atgsfjwWOPPYbly5cDAGKxGLZt24bTTz991LaXXXYZbrnlFnR0dODss8+e1Cr8RM7SdOc7ltWrV4/UX6xYsQIAUCgU8Nhjj40UeK9evRoejwePPPLIyDkODQ1h27ZtUz52f38/9u/fP27EwuPxIJFIoLm5GcFgcNrnBIjTeNppp+G0007D5z73OaxYsQJ33XUXrr766hmNqyiKshCoY6EoijLP5HI5dHd3j3rO7Xajtrb2kPtGIhFcc801uOqqq1Aul/GKV7wCsVgMf/7znxGNRnHJJZdMuN8ll1yCj370o6iurkZ9fT2uvfZaOJ3OA9KcLrroIlxzzTX47ne/izvuuGP6JzqD+Y4lFArhiiuuGJn/8uXLcdNNNyGdTuPSSy8FAITDYVx66aX46Ec/ipqaGtTX1+PTn/40nM6p9ylhwfd4jsWpp56KaDSKd77znfjsZz+LUCiEHTt24He/+x1uueWWSR/jkUcewb333otzzz0X9fX1eOSRR9DX14ejjjpqyvNVFEVZDKhjoSiKMs/87ne/Q1NT06jn1q9fjxdeeGFS+3/+859HXV0dbrzxRuzatQuVlZU48cQT8alPfeqg+91888143/veh9e+9rWIRqP42Mc+hv3798Pv94/arqKiAm9605vwm9/8Bm94wxumdG6zOd+xfPGLX0S5XMY73vEOJBIJnHzyyfj9738/qibhy1/+MpLJJF73utchEongn//5nxGLxUZev/322/Hud7/7kJ2XtmzZgoaGBjQ3Nx/wWnV1NX7729/i4x//OE4//XRYloW1a9dO2kki0WgUDz74IG655RbE43GsWLECX/nKV3DBBRdMaRxFUZTFgsM61NVVURRFOSxJpVJoaWnBV77ylZFVf3LWWWfh6KOPxte//vUFmt3ccO211+KBBx7A/fffP+/HPvPMM3H88cdPKaoBSLrUXXfdNStOnqIoylyiOhaKoihHCFu2bMGPf/xj7Ny5E5s3b8bFF18MAHj9618/ss3Q0BDuuusu3H///bjyyisXaqpzxv/+7//ipptuWrDjf/Ob30Q4HMbTTz99yG3f9773IRwOz8OsFEVRZgeNWCiKohwhbNmyBZdddhm2bt0Kr9eLk046CTfffDOOPfbYkW1WrlyJoaEhfPazn8U111yzgLM9/Ojo6EAmkwEALF++HF6v96Db9/b2Ih6PA5CWw4uta5aiKMpY1LFQFEVRFEVRFGXGaCqUoiiKoiiKoigzRh0LRVEURVEURVFmjDoWiqIoiqIoiqLMGHUsFEVRFEVRFEWZMepYKIqiKIqiKIoyY9SxUBRFURRFURRlxqhjoSiKoiiKoijKjFHHQlEURVEURVGUGaOOhaIoiqIoiqIoM0YdC0VRFEVRFEVRZow6FoqiKIqiKIqizJj/D/1UxohFrRfFAAAAAElFTkSuQmCC",
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",
       "text/plain": [
        "<Figure size 800x400 with 1 Axes>"
       ]
@@ -166,7 +166,7 @@
     "    data_label=\"bouy data\",\n",
     "    contour_label=\"100-year contour\",\n",
     "    x_label=\"Energy Period, $Te$ [s]\",\n",
-    "    y_label=\"Sig. wave height, $Hm0$ [m]\",\n",
+    "    y_label=\"Sig. Wave Height, $Hm0$ [m]\",\n",
     "    ax=ax,\n",
     ")\n",
     "ax.plot(te_samples, hs_samples, \"ro\", label=\"samples\")\n",
@@ -202,11 +202,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Sea state 1/5. (Hs, Te) = (12.296107471329824 m, 15.0 s). Tp = 16.599299336182796 s\n",
-      "Sea state 2/5. (Hs, Te) = (13.015332686697155 m, 16.75 s). Tp = 18.535884258737457 s\n",
-      "Sea state 3/5. (Hs, Te) = (13.259537828803623 m, 18.5 s). Tp = 20.472469181292116 s\n",
-      "Sea state 4/5. (Hs, Te) = (12.922246639791062 m, 20.25 s). Tp = 22.409054103846774 s\n",
-      "Sea state 5/5. (Hs, Te) = (11.849171349367342 m, 22.0 s). Tp = 24.345639026401436 s\n"
+      "Sea state 1/5. (Hs, Te) = (12.296107428008783 m, 15.0 s). Tp = 16.599299336182796 s\n",
+      "Sea state 2/5. (Hs, Te) = (13.015332640851637 m, 16.75 s). Tp = 18.535884258737457 s\n",
+      "Sea state 3/5. (Hs, Te) = (13.259537785465055 m, 18.5 s). Tp = 20.472469181292116 s\n",
+      "Sea state 4/5. (Hs, Te) = (12.922246604002359 m, 20.25 s). Tp = 22.409054103846774 s\n",
+      "Sea state 5/5. (Hs, Te) = (11.849171325785678 m, 22.0 s). Tp = 24.345639026401436 s\n"
      ]
     }
    ],
@@ -247,7 +247,7 @@
     "Finally, we will choose the sea state with the largest expected value as the design sea state. \n",
     "We will then use the 95th percentile of the short-term extreme distribution as the extreme design response. \n",
     "\n",
-    "First we find the sampled sea state with the largest expected value, which is Hs = 12.24m, Te=15s. "
+    "First we find the sampled sea state with the largest expected value, which is Hs = 13.3 m, Te = 18.5 s. "
    ]
   },
   {
@@ -259,7 +259,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "c:\\Users\\sterl\\anaconda3\\Lib\\site-packages\\scipy\\stats\\_distn_infrastructure.py:2998: IntegrationWarning: The integral is probably divergent, or slowly convergent.\n",
+      "c:\\Users\\mcve343\\anaconda3\\envs\\work\\Lib\\site-packages\\scipy\\stats\\_distn_infrastructure.py:3036: IntegrationWarning: The integral is probably divergent, or slowly convergent.\n",
       "  dub = integrate.quad(fun, d, ub, **kwds)[0]\n"
      ]
     },
@@ -267,7 +267,20 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Design sea state (Hs, Te): (13.015332686697155 m, 16.75 s)\n"
+      "Design sea state (Hs, Te): (13.259537785465055 m, 18.5 s)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\mcve343\\anaconda3\\envs\\work\\Lib\\site-packages\\scipy\\stats\\_distn_infrastructure.py:3036: IntegrationWarning: The maximum number of subdivisions (50) has been achieved.\n",
+      "  If increasing the limit yields no improvement it is advised to analyze \n",
+      "  the integrand in order to determine the difficulties.  If the position of a \n",
+      "  local difficulty can be determined (singularity, discontinuity) one will \n",
+      "  probably gain from splitting up the interval and calling the integrator \n",
+      "  on the subranges.  Perhaps a special-purpose integrator should be used.\n",
+      "  dub = integrate.quad(fun, d, ub, **kwds)[0]\n"
      ]
     }
    ],
@@ -287,7 +300,7 @@
    "metadata": {},
    "source": [
     "Next, we choose the 95th percentile of the short-term extreme distribution at this sea state as the extreme design response. \n",
-    "This gives an extreme design elevation of 14.1 meters."
+    "This gives an extreme design elevation of 18.7 meters."
    ]
   },
   {
@@ -299,7 +312,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Design (extreme) reponse: 14.134870969092166 m\n"
+      "Design (extreme) reponse: 18.71051873209217 m\n"
      ]
     }
    ],
@@ -313,7 +326,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "work",
    "language": "python",
    "name": "python3"
   },
@@ -327,7 +340,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.4"
+   "version": "3.11.10"
   }
  },
  "nbformat": 4,
diff --git a/examples/extreme_response_full_sea_state_example.ipynb b/examples/extreme_response_full_sea_state_example.ipynb
index 76266e05e..b1007b429 100644
--- a/examples/extreme_response_full_sea_state_example.ipynb
+++ b/examples/extreme_response_full_sea_state_example.ipynb
@@ -5,13 +5,13 @@
    "metadata": {},
    "source": [
     "# Extreme Conditions Modeling - Full Sea State Approach\n",
-    "Extreme conditions modeling consists of identifying the expected extreme (e.g. 100-year) response of some quantity of interest, such as WEC motions or mooring loads. \n",
+    "Extreme conditions modeling consists of identifying the expected extreme (e.g. 100 yr) response of some quantity of interest, such as WEC motions or mooring loads. \n",
     "Three different methods of estimating extreme conditions were adapted from [WDRT](https://github.com/WEC-Sim/WDRT): full sea state approach, contour approach, and MLER design wave. \n",
     "This noteboook presents the full sea state approach. \n",
     "\n",
     "The full sea state approach consists of the following steps: \n",
     "1. Take $N$ samples to represent the sea state. Each sample represents a small area of the sea state and consists of a representative $(H_{s}, T_{e})_i$ pair and a weight $W_i$ associated with the probability of that sea state area. \n",
-    "2. For each sample $(H_{s}, T_{e})_i$ calculate the short-term (e.g. 3-hours) extreme for the quantity of interest (e.g. WEC motions or mooring tension).\n",
+    "2. For each sample $(H_{s}, T_{e})_i$ calculate the short-term (e.g. 3 hr) extreme for the quantity of interest (e.g. WEC motions or mooring tension).\n",
     "3. Integrate over the entire sea state to obtain the long-term extreme. This is a sum of the products of the weight of each sea state times the short-term extreme. \n",
     "\n",
     "See more details and equations in\n",
@@ -147,7 +147,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x400 with 1 Axes>"
       ]
@@ -215,206 +215,206 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Sea state 1/200. (Hs, Te) = (2.840183371772305 m, 10.181962895642807 s). Tp = 11.267563328978767 s\n",
-      "Sea state 2/200. (Hs, Te) = (2.435150836386068 m, 9.253557835748264 s). Tp = 10.240171762684351 s\n",
-      "Sea state 3/200. (Hs, Te) = (2.380182396284662 m, 9.145665731349082 s). Tp = 10.120776206888838 s\n",
-      "Sea state 4/200. (Hs, Te) = (2.6586225636340433 m, 9.245181682418751 s). Tp = 10.230902544257528 s\n",
-      "Sea state 5/200. (Hs, Te) = (2.489418873168824 m, 9.168527592693843 s). Tp = 10.146075598878438 s\n",
-      "Sea state 6/200. (Hs, Te) = (2.4554983906019254 m, 9.076055379984771 s). Tp = 10.043744002942633 s\n",
-      "Sea state 7/200. (Hs, Te) = (2.8264441787710775 m, 8.352759030940048 s). Tp = 9.243329829171866 s\n",
-      "Sea state 8/200. (Hs, Te) = (2.440636821165454 m, 8.454371440140704 s). Tp = 9.355776148944692 s\n",
-      "Sea state 9/200. (Hs, Te) = (2.2107044601389494 m, 8.139285537198479 s). Tp = 9.00709580097473 s\n",
-      "Sea state 10/200. (Hs, Te) = (1.773654332308055 m, 7.14357692017975 s). Tp = 7.905224775274031 s\n",
-      "Sea state 11/200. (Hs, Te) = (2.33221680310332 m, 9.019225599053808 s). Tp = 9.980855033283783 s\n",
-      "Sea state 12/200. (Hs, Te) = (1.4652901970781362 m, 7.467449653557229 s). Tp = 8.263628805151397 s\n",
-      "Sea state 13/200. (Hs, Te) = (2.37380465141513 m, 9.137972634616318 s). Tp = 10.11226287252288 s\n",
-      "Sea state 14/200. (Hs, Te) = (1.9418617270615008 m, 8.786718919588829 s). Tp = 9.72355850194371 s\n",
-      "Sea state 15/200. (Hs, Te) = (1.682708754224695 m, 9.005540858375955 s). Tp = 9.965711226160469 s\n",
-      "Sea state 16/200. (Hs, Te) = (1.461238938616968 m, 9.679214804474308 s). Tp = 10.711212258578739 s\n",
-      "Sea state 17/200. (Hs, Te) = (1.9389947758035828 m, 10.03218336557303 s). Tp = 11.101814312041364 s\n",
-      "Sea state 18/200. (Hs, Te) = (2.2114494380999004 m, 10.769142843100967 s). Tp = 11.917348376449572 s\n",
-      "Sea state 19/200. (Hs, Te) = (2.3798499882325825 m, 9.899703813443036 s). Tp = 10.955209795926086 s\n",
-      "Sea state 20/200. (Hs, Te) = (2.8107970520086796 m, 10.711433106791901 s). Tp = 11.853485630609148 s\n",
-      "Sea state 21/200. (Hs, Te) = (3.9450344430779625 m, 12.237764463240708 s). Tp = 13.542554368735527 s\n",
-      "Sea state 22/200. (Hs, Te) = (5.208290345944717 m, 12.779909428576214 s). Tp = 14.142502806282762 s\n",
-      "Sea state 23/200. (Hs, Te) = (5.064261814083509 m, 11.637831173755485 s). Tp = 12.878656218475125 s\n",
-      "Sea state 24/200. (Hs, Te) = (4.379521879521117 m, 10.312278693768631 s). Tp = 11.411773391733709 s\n",
-      "Sea state 25/200. (Hs, Te) = (3.5851473474648303 m, 9.202172592956305 s). Tp = 10.183307827579942 s\n",
-      "Sea state 26/200. (Hs, Te) = (3.685482708071981 m, 7.779449820330637 s). Tp = 8.608894415898781 s\n",
-      "Sea state 27/200. (Hs, Te) = (2.9763084662416763 m, 7.623162087670313 s). Tp = 8.435943292098646 s\n",
-      "Sea state 28/200. (Hs, Te) = (2.522737928991046 m, 7.032634458082821 s). Tp = 7.7824536327780285 s\n",
-      "Sea state 29/200. (Hs, Te) = (1.8248226200631286 m, 6.173217780864412 s). Tp = 6.831405987467631 s\n",
-      "Sea state 30/200. (Hs, Te) = (1.5073537401283845 m, 5.798538866794911 s). Tp = 6.416778824161261 s\n",
-      "Sea state 31/200. (Hs, Te) = (1.544648128528352 m, 6.991514600764015 s). Tp = 7.73694957809163 s\n",
-      "Sea state 32/200. (Hs, Te) = (1.1824969929468647 m, 6.59815195035135 s). Tp = 7.301646619300026 s\n",
-      "Sea state 33/200. (Hs, Te) = (1.0552074511072387 m, 7.163058124004591 s). Tp = 7.926783064188546 s\n",
-      "Sea state 34/200. (Hs, Te) = (0.8070976865959585 m, 7.601417023502728 s). Tp = 8.41187977015183 s\n",
-      "Sea state 35/200. (Hs, Te) = (0.43594988466745865 m, 8.895171963861962 s). Tp = 9.843574804997713 s\n",
-      "Sea state 36/200. (Hs, Te) = (1.1925410643512184 m, 9.872043847355096 s). Tp = 10.924600725477926 s\n",
-      "Sea state 37/200. (Hs, Te) = (1.8028237883891736 m, 10.88264042709196 s). Tp = 12.04294706782291 s\n",
-      "Sea state 38/200. (Hs, Te) = (2.0536026727829158 m, 11.313724254083688 s). Tp = 12.519993033371104 s\n",
-      "Sea state 39/200. (Hs, Te) = (2.9552188313626924 m, 13.585806588148326 s). Tp = 15.034324685343892 s\n",
-      "Sea state 40/200. (Hs, Te) = (3.6331136496492835 m, 13.97990050373177 s). Tp = 15.47043687676642 s\n",
-      "Sea state 41/200. (Hs, Te) = (5.144265805980378 m, 16.494051026966694 s). Tp = 18.252646017526228 s\n",
-      "Sea state 42/200. (Hs, Te) = (5.799748193230507 m, 13.531617551407685 s). Tp = 14.97435801590407 s\n",
-      "Sea state 43/200. (Hs, Te) = (5.880641596533005 m, 12.031691730764155 s). Tp = 13.314510170641965 s\n",
-      "Sea state 44/200. (Hs, Te) = (6.51238308153145 m, 12.003103839792574 s). Tp = 13.282874240000137 s\n",
-      "Sea state 45/200. (Hs, Te) = (5.580209865963464 m, 9.727880824002659 s). Tp = 10.765067046955512 s\n",
-      "Sea state 46/200. (Hs, Te) = (4.100873196672923 m, 7.9730435784224145 s). Tp = 8.823129131910912 s\n",
-      "Sea state 47/200. (Hs, Te) = (3.1340604795919393 m, 6.764084114821338 s). Tp = 7.485270463802562 s\n",
-      "Sea state 48/200. (Hs, Te) = (2.56485636049072 m, 5.9144283344779724 s). Tp = 6.545024421760062 s\n",
-      "Sea state 49/200. (Hs, Te) = (1.9133076193222602 m, 5.739115906958378 s). Tp = 6.351020190976688 s\n",
-      "Sea state 50/200. (Hs, Te) = (1.451516130573119 m, 5.529526324054767 s). Tp = 6.1190841760191725 s\n",
-      "Sea state 51/200. (Hs, Te) = (1.1108464969032716 m, 5.620177089281756 s). Tp = 6.219400121822961 s\n",
-      "Sea state 52/200. (Hs, Te) = (0.5408216661607194 m, 5.786678826645898 s). Tp = 6.403654267056419 s\n",
-      "Sea state 53/200. (Hs, Te) = (0.5380468022216697 m, 6.366389882593204 s). Tp = 7.045174090134016 s\n",
-      "Sea state 54/200. (Hs, Te) = (0.3365260257595956 m, 7.308686450335826 s). Tp = 8.087938276228511 s\n",
-      "Sea state 55/200. (Hs, Te) = (0.13904048508259811 m, 9.353861073536656 s). Tp = 10.351169327246874 s\n",
-      "Sea state 56/200. (Hs, Te) = (0.016222817409913045 m, 10.555122094632276 s). Tp = 11.680508745250528 s\n",
-      "Sea state 57/200. (Hs, Te) = (0.9853173366828838 m, 13.099921941116929 s). Tp = 14.496635038748579 s\n",
-      "Sea state 58/200. (Hs, Te) = (1.473244705812314 m, 14.122791226249372 s). Tp = 15.628562601795295 s\n",
-      "Sea state 59/200. (Hs, Te) = (2.75132120738797 m, 16.45603635813758 s). Tp = 18.210578226388876 s\n",
-      "Sea state 60/200. (Hs, Te) = (3.6161379238827065 m, 16.408517026993035 s). Tp = 18.15799238626064 s\n",
-      "Sea state 61/200. (Hs, Te) = (0.06168214841402529 m, 12.829541181563107 s). Tp = 14.197426294576688 s\n",
-      "Sea state 62/200. (Hs, Te) = (0.8144132100052286 m, 15.079313073296817 s). Tp = 16.68706876584456 s\n",
-      "Sea state 63/200. (Hs, Te) = (1.516942605361148 m, 16.537563949182438 s). Tp = 18.30079828558297 s\n",
-      "Sea state 64/200. (Hs, Te) = (3.5189950096049984 m, 17.443166728395703 s). Tp = 19.302956393038976 s\n",
-      "Sea state 65/200. (Hs, Te) = (5.142358500915479 m, 17.095909887023208 s). Tp = 18.918675042607017 s\n",
-      "Sea state 66/200. (Hs, Te) = (6.688164513590967 m, 15.49638894389953 s). Tp = 17.14861324731346 s\n",
-      "Sea state 67/200. (Hs, Te) = (7.38093521608525 m, 13.973338528525257 s). Tp = 15.463175264053787 s\n",
-      "Sea state 68/200. (Hs, Te) = (7.0401547336088806 m, 12.390922649193692 s). Tp = 13.712042273696882 s\n",
-      "Sea state 69/200. (Hs, Te) = (6.78506479000579 m, 11.942048671980722 s). Tp = 13.21530937289815 s\n",
-      "Sea state 70/200. (Hs, Te) = (5.429163429903464 m, 9.382949943110583 s). Tp = 10.38335965080746 s\n",
-      "Sea state 71/200. (Hs, Te) = (4.638215677462449 m, 7.951976580697559 s). Tp = 8.799815971820943 s\n",
-      "Sea state 72/200. (Hs, Te) = (3.844888983563724 m, 7.138788533096206 s). Tp = 7.899925850571548 s\n",
-      "Sea state 73/200. (Hs, Te) = (3.137219896709583 m, 6.146710336025804 s). Tp = 6.802072320033404 s\n",
-      "Sea state 74/200. (Hs, Te) = (2.0531097877647 m, 5.282256705596885 s). Tp = 5.8454506817841 s\n",
-      "Sea state 75/200. (Hs, Te) = (1.400213943382828 m, 4.84359372140781 s). Tp = 5.360017469633588 s\n",
-      "Sea state 76/200. (Hs, Te) = (1.0439873396686965 m, 4.8568106143709855 s). Tp = 5.37464354713959 s\n",
-      "Sea state 77/200. (Hs, Te) = (0.7636698181099354 m, 5.091330002497621 s). Tp = 5.634167382049754 s\n",
-      "Sea state 78/200. (Hs, Te) = (0.5164301455498969 m, 5.271200170082657 s). Tp = 5.833215298942646 s\n",
-      "Sea state 79/200. (Hs, Te) = (0.27764628706602273 m, 5.770502054768426 s). Tp = 6.385752728477266 s\n",
-      "Sea state 80/200. (Hs, Te) = (0.12019246831682381 m, 6.422497059929555 s). Tp = 7.107263412234976 s\n",
-      "Sea state 81/200. (Hs, Te) = (0.9435318150397511 m, 17.686766663680846 s). Tp = 19.57252894264383 s\n",
-      "Sea state 82/200. (Hs, Te) = (1.8095106472743567 m, 18.69492089098288 s). Tp = 20.688172529045467 s\n",
-      "Sea state 83/200. (Hs, Te) = (3.259242038934493 m, 18.12023589435014 s). Tp = 20.052214643504133 s\n",
-      "Sea state 84/200. (Hs, Te) = (4.553386977816094 m, 19.559176338719734 s). Tp = 21.64457485437285 s\n",
-      "Sea state 85/200. (Hs, Te) = (6.079815681228885 m, 17.580622913690455 s). Tp = 19.455068150726802 s\n",
-      "Sea state 86/200. (Hs, Te) = (7.756236359086145 m, 16.334746346569563 s). Tp = 18.0763562791551 s\n",
-      "Sea state 87/200. (Hs, Te) = (8.032314897416262 m, 13.853555311897695 s). Tp = 15.330620766170338 s\n",
-      "Sea state 88/200. (Hs, Te) = (7.437035773606835 m, 12.219920335227009 s). Tp = 13.522807700582689 s\n",
-      "Sea state 89/200. (Hs, Te) = (6.272689262948052 m, 10.341413873554192 s). Tp = 11.444014963098644 s\n",
-      "Sea state 90/200. (Hs, Te) = (5.680501796529699 m, 8.999952214580796 s). Tp = 9.959526721411192 s\n",
-      "Sea state 91/200. (Hs, Te) = (4.295403919706385 m, 7.407648031465147 s). Tp = 8.197451136758348 s\n",
-      "Sea state 92/200. (Hs, Te) = (3.802009467884611 m, 6.735058106015025 s). Tp = 7.45314970322185 s\n",
-      "Sea state 93/200. (Hs, Te) = (2.989442106573119 m, 5.947499898935134 s). Tp = 6.581622074956081 s\n",
-      "Sea state 94/200. (Hs, Te) = (2.1700845237542685 m, 4.95257206736844 s). Tp = 5.48061508201776 s\n",
-      "Sea state 95/200. (Hs, Te) = (1.6133443085967656 m, 4.56969222054859 s). Tp = 5.056912602874126 s\n",
-      "Sea state 96/200. (Hs, Te) = (1.2266847114435944 m, 4.571489478117535 s). Tp = 5.058901483965535 s\n",
-      "Sea state 97/200. (Hs, Te) = (1.1303877451521183 m, 4.660379638074873 s). Tp = 5.157269108843737 s\n",
-      "Sea state 98/200. (Hs, Te) = (0.4872278356806693 m, 4.633757768877119 s). Tp = 5.127808817130256 s\n",
-      "Sea state 99/200. (Hs, Te) = (0.4798540716715929 m, 4.8704655677404585 s). Tp = 5.389754391033024 s\n",
-      "Sea state 100/200. (Hs, Te) = (0.31668721479335277 m, 5.383362621384034 s). Tp = 5.957336505838085 s\n",
-      "Sea state 101/200. (Hs, Te) = (0.9159629695168572 m, 18.536545272385226 s). Tp = 20.51291090900176 s\n",
-      "Sea state 102/200. (Hs, Te) = (2.7901658222821446 m, 19.71513088475056 s). Tp = 21.817157267199796 s\n",
-      "Sea state 103/200. (Hs, Te) = (3.6108764062877143 m, 19.64828596034304 s). Tp = 21.74318533991013 s\n",
-      "Sea state 104/200. (Hs, Te) = (6.753018218293009 m, 19.628479599524695 s). Tp = 21.721267225777854 s\n",
-      "Sea state 105/200. (Hs, Te) = (7.585465267742793 m, 18.93939426620065 s). Tp = 20.958711644709915 s\n",
-      "Sea state 106/200. (Hs, Te) = (8.635760904114186 m, 17.1930692826929 s). Tp = 19.02619356874327 s\n",
-      "Sea state 107/200. (Hs, Te) = (9.05426230998776 m, 15.60503313558586 s). Tp = 17.268841077909393 s\n",
-      "Sea state 108/200. (Hs, Te) = (8.626994106919245 m, 13.664271430098866 s). Tp = 15.121155445270777 s\n",
-      "Sea state 109/200. (Hs, Te) = (8.249276423093754 m, 12.089069676425865 s). Tp = 13.378005750330896 s\n",
-      "Sea state 110/200. (Hs, Te) = (6.546720844163918 m, 9.609606714783245 s). Tp = 10.634182557445284 s\n",
-      "Sea state 111/200. (Hs, Te) = (4.6701612388987925 m, 7.257490338569866 s). Tp = 8.031283637291722 s\n",
-      "Sea state 112/200. (Hs, Te) = (4.247473885467209 m, 6.845251449907407 s). Tp = 7.575091856563489 s\n",
-      "Sea state 113/200. (Hs, Te) = (3.1407263408032344 m, 5.61649903202472 s). Tp = 6.21532991026395 s\n",
-      "Sea state 114/200. (Hs, Te) = (2.551617919566844 m, 5.052936353097902 s). Tp = 5.591680203450128 s\n",
-      "Sea state 115/200. (Hs, Te) = (1.8905541932864423 m, 4.58657204053238 s). Tp = 5.075592148517581 s\n",
-      "Sea state 116/200. (Hs, Te) = (1.5613774797899114 m, 4.417758226719366 s). Tp = 4.88877941334659 s\n",
-      "Sea state 117/200. (Hs, Te) = (0.8528945597991013 m, 4.288719454514684 s). Tp = 4.74598253295999 s\n",
-      "Sea state 118/200. (Hs, Te) = (0.7535671669252131 m, 4.366286078627602 s). Tp = 4.831819307103156 s\n",
-      "Sea state 119/200. (Hs, Te) = (0.3511622723387135 m, 4.5626616143918675 s). Tp = 5.04913239380011 s\n",
-      "Sea state 120/200. (Hs, Te) = (0.23409447683192347 m, 4.831684374307781 s). Tp = 5.346838348472796 s\n",
-      "Sea state 121/200. (Hs, Te) = (0.6567506058522764 m, 20.65466056484252 s). Tp = 22.85685956020476 s\n",
-      "Sea state 122/200. (Hs, Te) = (1.9109048595321103 m, 20.232119606821662 s). Tp = 22.38926730393905 s\n",
-      "Sea state 123/200. (Hs, Te) = (5.150072039646266 m, 21.75628304033487 s). Tp = 24.075936975282378 s\n",
-      "Sea state 124/200. (Hs, Te) = (8.216295742464304 m, 20.537645676815334 s). Tp = 22.72736854999455 s\n",
-      "Sea state 125/200. (Hs, Te) = (8.60693817012891 m, 18.967871991795526 s). Tp = 20.99022566414745 s\n",
-      "Sea state 126/200. (Hs, Te) = (9.398789015485178 m, 16.100608602045437 s). Tp = 17.817254778671455 s\n",
-      "Sea state 127/200. (Hs, Te) = (9.40047294257686 m, 15.347435783673259 s). Tp = 16.98377870773571 s\n",
-      "Sea state 128/200. (Hs, Te) = (8.79993692151442 m, 12.79158147602177 s). Tp = 14.155419326910422 s\n",
-      "Sea state 129/200. (Hs, Te) = (8.177600332494796 m, 11.910657841670044 s). Tp = 13.180571653648933 s\n",
-      "Sea state 130/200. (Hs, Te) = (6.949387711018023 m, 9.748680946742258 s). Tp = 10.78808487786111 s\n",
-      "Sea state 131/200. (Hs, Te) = (5.977891095364696 m, 8.28691724719266 s). Tp = 9.170467997355125 s\n",
-      "Sea state 132/200. (Hs, Te) = (4.51101544283036 m, 6.834717588605634 s). Tp = 7.563434875435892 s\n",
-      "Sea state 133/200. (Hs, Te) = (3.1807875598100446 m, 5.360130005515921 s). Tp = 5.9316268294942605 s\n",
-      "Sea state 134/200. (Hs, Te) = (2.5974274134022024 m, 5.0469024266918066 s). Tp = 5.5850029400776435 s\n",
-      "Sea state 135/200. (Hs, Te) = (1.7390452207300586 m, 4.245268668775884 s). Tp = 4.69789902636861 s\n",
-      "Sea state 136/200. (Hs, Te) = (1.6719550940091157 m, 4.273249097729748 s). Tp = 4.728862727419275 s\n",
-      "Sea state 137/200. (Hs, Te) = (1.2706497306606221 m, 4.121193500467361 s). Tp = 4.560594969105915 s\n",
-      "Sea state 138/200. (Hs, Te) = (0.7236083260991419 m, 3.953915214219135 s). Tp = 4.375481479380716 s\n",
-      "Sea state 139/200. (Hs, Te) = (0.5662113586554597 m, 4.165911158867419 s). Tp = 4.61008042226563 s\n",
-      "Sea state 140/200. (Hs, Te) = (0.22380262429040848 m, 4.428588430704851 s). Tp = 4.900764333201723 s\n",
-      "Sea state 141/200. (Hs, Te) = (0.9422263633698529 m, 21.68156229851667 s). Tp = 23.993249511278247 s\n",
-      "Sea state 142/200. (Hs, Te) = (2.6808185912102096 m, 22.65619752776177 s). Tp = 25.071800305533483 s\n",
-      "Sea state 143/200. (Hs, Te) = (5.284470291643777 m, 22.420384661431555 s). Tp = 24.810845081830916 s\n",
-      "Sea state 144/200. (Hs, Te) = (7.449969927903553 m, 21.84994192365026 s). Tp = 24.179581764592026 s\n",
-      "Sea state 145/200. (Hs, Te) = (9.184267967048088 m, 20.471169146791553 s). Tp = 22.653804295281518 s\n",
-      "Sea state 146/200. (Hs, Te) = (10.717866496341058 m, 17.115719729476954 s). Tp = 18.940597009586504 s\n",
-      "Sea state 147/200. (Hs, Te) = (10.671834020151834 m, 14.880105357839954 s). Tp = 16.46662153258152 s\n",
-      "Sea state 148/200. (Hs, Te) = (10.191452698929544 m, 13.818581919045513 s). Tp = 15.291918511719986 s\n",
-      "Sea state 149/200. (Hs, Te) = (8.37690632915727 m, 10.962421795675256 s). Tp = 12.131234722393874 s\n",
-      "Sea state 150/200. (Hs, Te) = (7.4694526641366625 m, 9.888932685570508 s). Tp = 10.943290250876458 s\n",
-      "Sea state 151/200. (Hs, Te) = (5.212528893273048 m, 7.249094730639045 s). Tp = 8.021992890014861 s\n",
-      "Sea state 152/200. (Hs, Te) = (4.063796625344188 m, 6.135879435017965 s). Tp = 6.790086628839425 s\n",
-      "Sea state 153/200. (Hs, Te) = (3.3787764210161813 m, 5.419027822055873 s). Tp = 5.996804328627211 s\n",
-      "Sea state 154/200. (Hs, Te) = (2.795945700731734 m, 4.958285027601677 s). Tp = 5.486937157818241 s\n",
-      "Sea state 155/200. (Hs, Te) = (1.9272686719719325 m, 4.228829976069561 s). Tp = 4.679707640973425 s\n",
-      "Sea state 156/200. (Hs, Te) = (1.568113495064289 m, 4.032997225028029 s). Tp = 4.462995210682322 s\n",
-      "Sea state 157/200. (Hs, Te) = (1.1822964652570693 m, 3.8685969019191884 s). Tp = 4.281066532399067 s\n",
-      "Sea state 158/200. (Hs, Te) = (0.7856775833759984 m, 3.797389763440326 s). Tp = 4.202267291966823 s\n",
-      "Sea state 159/200. (Hs, Te) = (0.3291798465609936 m, 4.03461070522861 s). Tp = 4.464780720070485 s\n",
-      "Sea state 160/200. (Hs, Te) = (0.15420429246200082 m, 4.3518582866098265 s). Tp = 4.81585322453894 s\n",
-      "Sea state 161/200. (Hs, Te) = (2.0790807412143555 m, 23.553887059988554 s). Tp = 26.065201455959503 s\n",
-      "Sea state 162/200. (Hs, Te) = (2.9005504155626443 m, 23.487521867586448 s). Tp = 25.99176040968044 s\n",
-      "Sea state 163/200. (Hs, Te) = (7.085064893935304 m, 23.617650072612047 s). Tp = 26.135762878167114 s\n",
-      "Sea state 164/200. (Hs, Te) = (10.008361591286254 m, 21.465144157914505 s). Tp = 23.75375687810255 s\n",
-      "Sea state 165/200. (Hs, Te) = (9.97460629881344 m, 20.66827347686875 s). Tp = 22.8719238803088 s\n",
-      "Sea state 166/200. (Hs, Te) = (12.515562162825644 m, 18.442195805046968 s). Tp = 20.408501905631287 s\n",
-      "Sea state 167/200. (Hs, Te) = (11.318704374242229 m, 15.379037771055806 s). Tp = 17.018750097614454 s\n",
-      "Sea state 168/200. (Hs, Te) = (9.831621741618951 m, 12.589522993573661 s). Tp = 13.931817378005688 s\n",
-      "Sea state 169/200. (Hs, Te) = (8.719753268757158 m, 11.001963549202046 s). Tp = 12.174992415931788 s\n",
-      "Sea state 170/200. (Hs, Te) = (6.697280646131268 m, 8.394469020363612 s). Tp = 9.289486935821916 s\n",
-      "Sea state 171/200. (Hs, Te) = (5.9260094336014575 m, 7.621869198633718 s). Tp = 8.434512555290185 s\n",
-      "Sea state 172/200. (Hs, Te) = (4.880617435847239 m, 6.717945332768991 s). Tp = 7.434212366849642 s\n",
-      "Sea state 173/200. (Hs, Te) = (3.876024525693232 m, 5.700254261167271 s). Tp = 6.308015118231136 s\n",
-      "Sea state 174/200. (Hs, Te) = (2.783776276233764 m, 4.665403840101326 s). Tp = 5.162828991067907 s\n",
-      "Sea state 175/200. (Hs, Te) = (2.232050172695443 m, 4.35064714713621 s). Tp = 4.8145129534282445 s\n",
-      "Sea state 176/200. (Hs, Te) = (1.4397061034565646 m, 3.8710858327287654 s). Tp = 4.283820832901415 s\n",
-      "Sea state 177/200. (Hs, Te) = (0.9917868156814885 m, 3.749108919277857 s). Tp = 4.148838746336396 s\n",
-      "Sea state 178/200. (Hs, Te) = (0.8379479685905803 m, 3.6939930215454 s). Tp = 4.08784639402683 s\n",
-      "Sea state 179/200. (Hs, Te) = (0.3649362767346382 m, 3.9015035570249985 s). Tp = 4.317481693615992 s\n",
-      "Sea state 180/200. (Hs, Te) = (0.26122851286335796 m, 3.8182178899126895 s). Tp = 4.2253161123619325 s\n",
-      "Sea state 181/200. (Hs, Te) = (1.85918793399297 m, 24.795749666965783 s). Tp = 27.43947139913466 s\n",
-      "Sea state 182/200. (Hs, Te) = (4.002691094113826 m, 24.82391450267687 s). Tp = 27.470639168382846 s\n",
-      "Sea state 183/200. (Hs, Te) = (8.434042106183172 m, 23.892405089109275 s). Tp = 26.439812262364136 s\n",
-      "Sea state 184/200. (Hs, Te) = (10.54951299048162 m, 22.368492149045327 s). Tp = 24.753419792070545 s\n",
-      "Sea state 185/200. (Hs, Te) = (12.438371651972409 m, 19.928667490533087 s). Tp = 22.0534611364409 s\n",
-      "Sea state 186/200. (Hs, Te) = (12.877658419178392 m, 18.405021605067592 s). Tp = 20.367364194095234 s\n",
-      "Sea state 187/200. (Hs, Te) = (12.20514433636702 m, 15.560744193082908 s). Tp = 17.219830050316762 s\n",
-      "Sea state 188/200. (Hs, Te) = (11.349999320223956 m, 13.573437147754268 s). Tp = 15.020636415762421 s\n",
-      "Sea state 189/200. (Hs, Te) = (8.943249528459614 m, 10.699541456942468 s). Tp = 11.840326093579028 s\n",
-      "Sea state 190/200. (Hs, Te) = (6.974694569119304 m, 8.532352187066413 s). Tp = 9.442071199656622 s\n",
-      "Sea state 191/200. (Hs, Te) = (6.794991647155438 m, 8.321004825044408 s). Tp = 9.208189991248899 s\n",
-      "Sea state 192/200. (Hs, Te) = (4.788840720460295 m, 6.38163862650819 s). Tp = 7.062048654450392 s\n",
-      "Sea state 193/200. (Hs, Te) = (3.2611200777648106 m, 4.933748144257159 s). Tp = 5.459784153057397 s\n",
-      "Sea state 194/200. (Hs, Te) = (2.863068054464451 m, 4.600269207998482 s). Tp = 5.0907497073727574 s\n",
-      "Sea state 195/200. (Hs, Te) = (2.3124781374766226 m, 4.192805730047 s). Tp = 4.639842491434172 s\n",
-      "Sea state 196/200. (Hs, Te) = (1.7972861360694252 m, 3.77507151907285 s). Tp = 4.177569477372569 s\n",
-      "Sea state 197/200. (Hs, Te) = (1.0994765211194881 m, 3.465224057093012 s). Tp = 3.8346860927085795 s\n",
-      "Sea state 198/200. (Hs, Te) = (0.8655202915109887 m, 3.438356041093707 s). Tp = 3.8049534100324585 s\n",
-      "Sea state 199/200. (Hs, Te) = (0.4625658856258066 m, 3.5756134401100295 s). Tp = 3.9568451868576466 s\n",
-      "Sea state 200/200. (Hs, Te) = (0.00764320162167542 m, 3.881423657080205 s). Tp = 4.29526087562771 s\n"
+      "Sea state 1/200. (Hs, Te) = (3.0519011698370164 m, 11.04583834537762 s). Tp = 12.223545140933947 s\n",
+      "Sea state 2/200. (Hs, Te) = (3.4454122915496477 m, 11.169309543379487 s). Tp = 12.36018083260262 s\n",
+      "Sea state 3/200. (Hs, Te) = (3.6662634602868733 m, 10.826118052470603 s). Tp = 11.980398280120792 s\n",
+      "Sea state 4/200. (Hs, Te) = (2.843537679463958 m, 9.454411623864956 s). Tp = 10.462440572801366 s\n",
+      "Sea state 5/200. (Hs, Te) = (3.2498724114450663 m, 9.102778237322505 s). Tp = 10.073316050147112 s\n",
+      "Sea state 6/200. (Hs, Te) = (2.5432758740513246 m, 9.068212764645198 s). Tp = 10.035065208302626 s\n",
+      "Sea state 7/200. (Hs, Te) = (2.4264778631768715 m, 8.911382062896639 s). Tp = 9.861513224074097 s\n",
+      "Sea state 8/200. (Hs, Te) = (2.3680978175067704 m, 7.789046740670324 s). Tp = 8.619514559460379 s\n",
+      "Sea state 9/200. (Hs, Te) = (2.2754848647911032 m, 7.730579014941564 s). Tp = 8.554813007401878 s\n",
+      "Sea state 10/200. (Hs, Te) = (2.2013893785282765 m, 8.531209614759113 s). Tp = 9.440806806340483 s\n",
+      "Sea state 11/200. (Hs, Te) = (2.2734303870548245 m, 8.840100909846239 s). Tp = 9.782632077639974 s\n",
+      "Sea state 12/200. (Hs, Te) = (2.1023284019631188 m, 8.616579481658642 s). Tp = 9.53527880467084 s\n",
+      "Sea state 13/200. (Hs, Te) = (1.4905589789833533 m, 8.267748616842887 s). Tp = 9.149255608485758 s\n",
+      "Sea state 14/200. (Hs, Te) = (1.2979444609623636 m, 8.430409347607648 s). Tp = 9.329259219166191 s\n",
+      "Sea state 15/200. (Hs, Te) = (2.132588467318634 m, 9.0814844673542 s). Tp = 10.049751939367129 s\n",
+      "Sea state 16/200. (Hs, Te) = (1.6432774588959944 m, 9.638029185709314 s). Tp = 10.665635430963668 s\n",
+      "Sea state 17/200. (Hs, Te) = (1.6876474061826714 m, 10.244402846851779 s). Tp = 11.336660625022391 s\n",
+      "Sea state 18/200. (Hs, Te) = (2.3000321378643753 m, 11.28775917735869 s). Tp = 12.49125956131476 s\n",
+      "Sea state 19/200. (Hs, Te) = (2.4146227608441593 m, 11.147740911966473 s). Tp = 12.336312554662857 s\n",
+      "Sea state 20/200. (Hs, Te) = (2.6103200843167143 m, 9.983394136743243 s). Tp = 11.047823177792889 s\n",
+      "Sea state 21/200. (Hs, Te) = (4.068731647379028 m, 13.47865291827843 s). Tp = 14.915746295934497 s\n",
+      "Sea state 22/200. (Hs, Te) = (3.6954884327563504 m, 11.566787354484731 s). Tp = 12.80003771033773 s\n",
+      "Sea state 23/200. (Hs, Te) = (4.480207105259814 m, 11.52005655504381 s). Tp = 12.748324475128467 s\n",
+      "Sea state 24/200. (Hs, Te) = (3.9561742254336414 m, 10.01673299203202 s). Tp = 11.084716620357161 s\n",
+      "Sea state 25/200. (Hs, Te) = (3.8531220807180997 m, 9.102625782286212 s). Tp = 10.073147340361595 s\n",
+      "Sea state 26/200. (Hs, Te) = (3.5663781572345914 m, 8.07240817659649 s). Tp = 8.933087979144979 s\n",
+      "Sea state 27/200. (Hs, Te) = (2.908241307240586 m, 7.952039998258466 s). Tp = 8.799886150959386 s\n",
+      "Sea state 28/200. (Hs, Te) = (2.464190314138586 m, 6.351176628326459 s). Tp = 7.028338799370605 s\n",
+      "Sea state 29/200. (Hs, Te) = (1.8859920748196535 m, 5.834077602503495 s). Tp = 6.4561066982983455 s\n",
+      "Sea state 30/200. (Hs, Te) = (1.7529151360331678 m, 6.187059223348201 s). Tp = 6.846723203936496 s\n",
+      "Sea state 31/200. (Hs, Te) = (1.1446025863887235 m, 6.175904417658782 s). Tp = 6.834379073358122 s\n",
+      "Sea state 32/200. (Hs, Te) = (1.2892599022789482 m, 7.0427301077881275 s). Tp = 7.793625680208137 s\n",
+      "Sea state 33/200. (Hs, Te) = (0.8966054052018009 m, 7.2246845535200235 s). Tp = 7.994980100891668 s\n",
+      "Sea state 34/200. (Hs, Te) = (0.6457634910721332 m, 8.242602318588398 s). Tp = 9.121428213024211 s\n",
+      "Sea state 35/200. (Hs, Te) = (1.1549727781983783 m, 9.080002152257277 s). Tp = 10.048111579900173 s\n",
+      "Sea state 36/200. (Hs, Te) = (1.2334407129813119 m, 10.628185539873787 s). Tp = 11.761362211790303 s\n",
+      "Sea state 37/200. (Hs, Te) = (1.2431677156081726 m, 11.406426838366153 s). Tp = 12.62257956308726 s\n",
+      "Sea state 38/200. (Hs, Te) = (1.1698012492327046 m, 12.996421545991407 s). Tp = 14.38209943607513 s\n",
+      "Sea state 39/200. (Hs, Te) = (2.618620581508073 m, 13.325913201158178 s). Tp = 14.746721476934301 s\n",
+      "Sea state 40/200. (Hs, Te) = (3.470102355731644 m, 14.741323374979535 s). Tp = 16.313042620850247 s\n",
+      "Sea state 41/200. (Hs, Te) = (5.692307434347409 m, 15.021145316541375 s). Tp = 16.62269916543804 s\n",
+      "Sea state 42/200. (Hs, Te) = (6.063254834692772 m, 14.912923656204937 s). Tp = 16.502938916465823 s\n",
+      "Sea state 43/200. (Hs, Te) = (6.480903322872717 m, 13.062850502306475 s). Tp = 14.45561104477273 s\n",
+      "Sea state 44/200. (Hs, Te) = (5.772781251171104 m, 11.063804638270845 s). Tp = 12.24342699918036 s\n",
+      "Sea state 45/200. (Hs, Te) = (4.817270478445196 m, 9.409534348102964 s). Tp = 10.41277848388365 s\n",
+      "Sea state 46/200. (Hs, Te) = (3.8173661650453172 m, 7.153726211432188 s). Tp = 7.916456183510652 s\n",
+      "Sea state 47/200. (Hs, Te) = (3.555645519825636 m, 7.0772788368068404 s). Tp = 7.831857993185889 s\n",
+      "Sea state 48/200. (Hs, Te) = (2.3757710877788805 m, 5.743160152018138 s). Tp = 6.355495633265744 s\n",
+      "Sea state 49/200. (Hs, Te) = (2.0006463135772363 m, 5.725278997544492 s). Tp = 6.3357079908934395 s\n",
+      "Sea state 50/200. (Hs, Te) = (1.5326631253318903 m, 5.450682138605642 s). Tp = 6.03183362700667 s\n",
+      "Sea state 51/200. (Hs, Te) = (1.0513428658700548 m, 5.250602616249876 s). Tp = 5.810421634831748 s\n",
+      "Sea state 52/200. (Hs, Te) = (0.5265157588947252 m, 5.743448169453037 s). Tp = 6.355814359106806 s\n",
+      "Sea state 53/200. (Hs, Te) = (0.4532800070739075 m, 6.025390228156072 s). Tp = 6.667817067631559 s\n",
+      "Sea state 54/200. (Hs, Te) = (0.3375768229335862 m, 7.7442235989089925 s). Tp = 8.569912376308078 s\n",
+      "Sea state 55/200. (Hs, Te) = (0.30102216405234467 m, 9.656746479427033 s). Tp = 10.686348361709246 s\n",
+      "Sea state 56/200. (Hs, Te) = (0.12542290090024186 m, 10.426998603044929 s). Tp = 11.538724732660175 s\n",
+      "Sea state 57/200. (Hs, Te) = (0.6729890509283177 m, 11.570361355358964 s). Tp = 12.803992771027009 s\n",
+      "Sea state 58/200. (Hs, Te) = (1.5175554651966627 m, 14.539941741525709 s). Tp = 16.090189686549614 s\n",
+      "Sea state 59/200. (Hs, Te) = (2.542385963739924 m, 14.83027643922333 s). Tp = 16.411479856867146 s\n",
+      "Sea state 60/200. (Hs, Te) = (3.843301514688319 m, 16.274667680028315 s). Tp = 18.009872027845976 s\n",
+      "Sea state 61/200. (Hs, Te) = (0.21703512911091222 m, 13.455423054650405 s). Tp = 14.890039665274477 s\n",
+      "Sea state 62/200. (Hs, Te) = (1.0647431724172083 m, 15.96883933443384 s). Tp = 17.67143627757849 s\n",
+      "Sea state 63/200. (Hs, Te) = (1.9266398513146878 m, 16.76677465034196 s). Tp = 18.554447421556524 s\n",
+      "Sea state 64/200. (Hs, Te) = (2.9446481669173643 m, 17.411128698164656 s). Tp = 19.267502469442523 s\n",
+      "Sea state 65/200. (Hs, Te) = (5.325927110106066 m, 17.28929200677703 s). Tp = 19.132675555410962 s\n",
+      "Sea state 66/200. (Hs, Te) = (6.358535119949946 m, 16.75931175233696 s). Tp = 18.546188829696494 s\n",
+      "Sea state 67/200. (Hs, Te) = (7.412694605997036 m, 14.620760342427937 s). Tp = 16.179625163103456 s\n",
+      "Sea state 68/200. (Hs, Te) = (6.912756247780623 m, 12.373393694903546 s). Tp = 13.692644383076056 s\n",
+      "Sea state 69/200. (Hs, Te) = (6.836728394398719 m, 11.960299344373112 s). Tp = 13.235505931173343 s\n",
+      "Sea state 70/200. (Hs, Te) = (5.355536467460859 m, 9.079058011369364 s). Tp = 10.047066774752572 s\n",
+      "Sea state 71/200. (Hs, Te) = (4.671151051589706 m, 8.180105150206973 s). Tp = 9.052267599315739 s\n",
+      "Sea state 72/200. (Hs, Te) = (3.4423336307698715 m, 6.6820931438917155 s). Tp = 7.394537619180891 s\n",
+      "Sea state 73/200. (Hs, Te) = (3.042300100254776 m, 6.127122298527252 s). Tp = 6.7803958068436145 s\n",
+      "Sea state 74/200. (Hs, Te) = (2.3786123268272035 m, 5.496412100399395 s). Tp = 6.082439315303118 s\n",
+      "Sea state 75/200. (Hs, Te) = (1.5041052101768 m, 4.9882001950273755 s). Tp = 5.5200418790709875 s\n",
+      "Sea state 76/200. (Hs, Te) = (1.1787130334573301 m, 4.923771573828079 s). Tp = 5.448743881130676 s\n",
+      "Sea state 77/200. (Hs, Te) = (0.7230899256428956 m, 5.085896456279929 s). Tp = 5.628154511374791 s\n",
+      "Sea state 78/200. (Hs, Te) = (0.6595252571108683 m, 5.241814253185951 s). Tp = 5.800696256886872 s\n",
+      "Sea state 79/200. (Hs, Te) = (0.4307357404436535 m, 5.7331571793437535 s). Tp = 6.344426144087493 s\n",
+      "Sea state 80/200. (Hs, Te) = (0.07857080829669981 m, 7.233311179831642 s). Tp = 8.004526497718864 s\n",
+      "Sea state 81/200. (Hs, Te) = (0.46027925182362306 m, 17.190680093637045 s). Tp = 19.023549644456015 s\n",
+      "Sea state 82/200. (Hs, Te) = (1.1980708521021082 m, 18.013198526276145 s). Tp = 19.93376495598297 s\n",
+      "Sea state 83/200. (Hs, Te) = (3.3456270989608847 m, 19.22345321864848 s). Tp = 21.27305695009685 s\n",
+      "Sea state 84/200. (Hs, Te) = (4.7172043745682934 m, 18.93499681508312 s). Tp = 20.95384533754884 s\n",
+      "Sea state 85/200. (Hs, Te) = (6.847539405620025 m, 17.01205239650382 s). Tp = 18.82587667015952 s\n",
+      "Sea state 86/200. (Hs, Te) = (7.7231278201867735 m, 16.002541319345347 s). Tp = 17.7087315666298 s\n",
+      "Sea state 87/200. (Hs, Te) = (7.629081235847672 m, 13.589062961401245 s). Tp = 15.037928252968927 s\n",
+      "Sea state 88/200. (Hs, Te) = (8.452363775230276 m, 13.697027484905862 s). Tp = 15.157403949191693 s\n",
+      "Sea state 89/200. (Hs, Te) = (6.786448289244335 m, 11.096803430725068 s). Tp = 12.279944121425705 s\n",
+      "Sea state 90/200. (Hs, Te) = (5.894927231129716 m, 9.486667762348933 s). Tp = 10.498135859343025 s\n",
+      "Sea state 91/200. (Hs, Te) = (4.358786891532466 m, 7.463316562369551 s). Tp = 8.259055043964198 s\n",
+      "Sea state 92/200. (Hs, Te) = (3.9467659355519693 m, 6.83220935253828 s). Tp = 7.560659211350037 s\n",
+      "Sea state 93/200. (Hs, Te) = (3.1553632519540327 m, 5.7986464312643555 s). Tp = 6.416897857149677 s\n",
+      "Sea state 94/200. (Hs, Te) = (2.4326564397131407 m, 5.386310322285478 s). Tp = 5.960598490479192 s\n",
+      "Sea state 95/200. (Hs, Te) = (1.9880614356841193 m, 4.766775125231435 s). Tp = 5.275008478132455 s\n",
+      "Sea state 96/200. (Hs, Te) = (1.293408716110891 m, 4.581909760591489 s). Tp = 5.070432776495719 s\n",
+      "Sea state 97/200. (Hs, Te) = (0.9616341076852011 m, 4.6589618685367205 s). Tp = 5.15570017678017 s\n",
+      "Sea state 98/200. (Hs, Te) = (0.666386186607189 m, 4.855002832015561 s). Tp = 5.372643019109433 s\n",
+      "Sea state 99/200. (Hs, Te) = (0.264660735105467 m, 5.103153352076978 s). Tp = 5.647251336638027 s\n",
+      "Sea state 100/200. (Hs, Te) = (0.12685463433629815 m, 5.661138705021298 s). Tp = 6.264729063219917 s\n",
+      "Sea state 101/200. (Hs, Te) = (1.1268237311741414 m, 18.301713991606317 s). Tp = 20.25304192745854 s\n",
+      "Sea state 102/200. (Hs, Te) = (1.845198442336088 m, 19.674565478195856 s). Tp = 21.77226677879343 s\n",
+      "Sea state 103/200. (Hs, Te) = (4.413499842939948 m, 20.172795771988145 s). Tp = 22.32361836446093 s\n",
+      "Sea state 104/200. (Hs, Te) = (6.483193116894594 m, 19.359981891388735 s). Tp = 21.424142303882665 s\n",
+      "Sea state 105/200. (Hs, Te) = (7.841572973402071 m, 18.519669560552952 s). Tp = 20.494235909520757 s\n",
+      "Sea state 106/200. (Hs, Te) = (8.790048122755998 m, 17.636792469179515 s). Tp = 19.51722650173635 s\n",
+      "Sea state 107/200. (Hs, Te) = (8.753396102235087 m, 14.14643164730843 s). Tp = 15.654723563501475 s\n",
+      "Sea state 108/200. (Hs, Te) = (8.426752536347962 m, 13.182638875844871 s). Tp = 14.58817124939662 s\n",
+      "Sea state 109/200. (Hs, Te) = (7.538945072970559 m, 10.89657968634219 s). Tp = 12.058372530277524 s\n",
+      "Sea state 110/200. (Hs, Te) = (6.52392465965872 m, 9.485481750157293 s). Tp = 10.496823394583998 s\n",
+      "Sea state 111/200. (Hs, Te) = (5.209202704421955 m, 7.9749237506419925 s). Tp = 8.825209768009335 s\n",
+      "Sea state 112/200. (Hs, Te) = (4.0540640761131765 m, 6.580592173706031 s). Tp = 7.282214620045882 s\n",
+      "Sea state 113/200. (Hs, Te) = (3.3049358170467524 m, 5.894452158235983 s). Tp = 6.522918386491186 s\n",
+      "Sea state 114/200. (Hs, Te) = (2.169848292969151 m, 4.7404643760311345 s). Tp = 5.245892478016787 s\n",
+      "Sea state 115/200. (Hs, Te) = (1.9534343747113685 m, 4.584560512331687 s). Tp = 5.073366151269149 s\n",
+      "Sea state 116/200. (Hs, Te) = (1.4832783753736873 m, 4.356627084101155 s). Tp = 4.821130471007753 s\n",
+      "Sea state 117/200. (Hs, Te) = (1.0598538682129985 m, 4.317024005381985 s). Tp = 4.777304913788158 s\n",
+      "Sea state 118/200. (Hs, Te) = (0.7258158734724787 m, 4.42511891003475 s). Tp = 4.896924892391318 s\n",
+      "Sea state 119/200. (Hs, Te) = (0.3218056251115961 m, 4.837161638335263 s). Tp = 5.352899598148494 s\n",
+      "Sea state 120/200. (Hs, Te) = (0.1529178499563497 m, 5.0948910210045915 s). Tp = 5.6381080761923466 s\n",
+      "Sea state 121/200. (Hs, Te) = (1.4617033785832907 m, 19.967713785536485 s). Tp = 22.09667054568959 s\n",
+      "Sea state 122/200. (Hs, Te) = (2.798041717936526 m, 21.495323765808678 s). Tp = 23.787154234454817 s\n",
+      "Sea state 123/200. (Hs, Te) = (5.259564944383678 m, 21.394671367392732 s). Tp = 23.675770281774085 s\n",
+      "Sea state 124/200. (Hs, Te) = (8.35812856579741 m, 20.660736018189226 s). Tp = 22.863582778118428 s\n",
+      "Sea state 125/200. (Hs, Te) = (8.439618161440924 m, 19.14134618167327 s). Tp = 21.18219566447295 s\n",
+      "Sea state 126/200. (Hs, Te) = (10.292141263188919 m, 18.299482065544524 s). Tp = 20.250572033538813 s\n",
+      "Sea state 127/200. (Hs, Te) = (9.289089256709273 m, 14.555275372180486 s). Tp = 16.107158188226222 s\n",
+      "Sea state 128/200. (Hs, Te) = (8.542968895321545 m, 12.324863083963992 s). Tp = 13.638939440545823 s\n",
+      "Sea state 129/200. (Hs, Te) = (7.468390108552663 m, 10.287748814954023 s). Tp = 11.384628138325445 s\n",
+      "Sea state 130/200. (Hs, Te) = (6.5707446111457015 m, 9.319715314854362 s). Tp = 10.313382949284977 s\n",
+      "Sea state 131/200. (Hs, Te) = (5.60872818188617 m, 8.051983881072617 s). Tp = 8.910486046136219 s\n",
+      "Sea state 132/200. (Hs, Te) = (3.991538414403644 m, 6.252186602100548 s). Tp = 6.91879446092924 s\n",
+      "Sea state 133/200. (Hs, Te) = (3.626524247915902 m, 5.902411884648774 s). Tp = 6.531726778581856 s\n",
+      "Sea state 134/200. (Hs, Te) = (2.6518984771001484 m, 5.066182973924612 s). Tp = 5.606339178403159 s\n",
+      "Sea state 135/200. (Hs, Te) = (1.8091038427854655 m, 4.457956383976893 s). Tp = 4.933263496351967 s\n",
+      "Sea state 136/200. (Hs, Te) = (1.2989406338592269 m, 3.994531032515327 s). Tp = 4.420427754426217 s\n",
+      "Sea state 137/200. (Hs, Te) = (1.0499593452251907 m, 4.193532941030377 s). Tp = 4.640647237620415 s\n",
+      "Sea state 138/200. (Hs, Te) = (0.6433991714660491 m, 4.216701883166105 s). Tp = 4.666286451341325 s\n",
+      "Sea state 139/200. (Hs, Te) = (0.35316386403086203 m, 4.501882113825003 s). Tp = 4.981872585572572 s\n",
+      "Sea state 140/200. (Hs, Te) = (0.2744545504333075 m, 4.488377393677282 s). Tp = 4.966927992760345 s\n",
+      "Sea state 141/200. (Hs, Te) = (0.8068170560899437 m, 21.216684038752813 s). Tp = 23.478805952031312 s\n",
+      "Sea state 142/200. (Hs, Te) = (3.069808490956658 m, 22.045232858515607 s). Tp = 24.39569461029022 s\n",
+      "Sea state 143/200. (Hs, Te) = (5.267494602662645 m, 22.51536680045854 s). Tp = 24.915954212317576 s\n",
+      "Sea state 144/200. (Hs, Te) = (8.574728268404309 m, 21.303061011945967 s). Tp = 23.574392434283755 s\n",
+      "Sea state 145/200. (Hs, Te) = (10.671063465675838 m, 19.060263176557495 s). Tp = 21.092467592940014 s\n",
+      "Sea state 146/200. (Hs, Te) = (10.876296838223272 m, 17.532968720866293 s). Tp = 19.402333069972638 s\n",
+      "Sea state 147/200. (Hs, Te) = (10.534388756527077 m, 14.801445206897775 s). Tp = 16.379574639826952 s\n",
+      "Sea state 148/200. (Hs, Te) = (9.779306267722461 m, 13.051496141467442 s). Tp = 14.443046082483523 s\n",
+      "Sea state 149/200. (Hs, Te) = (8.921235180657721 m, 11.717822520116258 s). Tp = 12.967176238644907 s\n",
+      "Sea state 150/200. (Hs, Te) = (7.273929502655918 m, 9.597743252685069 s). Tp = 10.62105421354321 s\n",
+      "Sea state 151/200. (Hs, Te) = (5.55737098699723 m, 7.627379062574176 s). Tp = 8.440609880680139 s\n",
+      "Sea state 152/200. (Hs, Te) = (4.408665215071578 m, 6.445613979770078 s). Tp = 7.132845057045867 s\n",
+      "Sea state 153/200. (Hs, Te) = (3.312948927456145 m, 5.3889083767085015 s). Tp = 5.963473549349823 s\n",
+      "Sea state 154/200. (Hs, Te) = (2.9187259448491996 m, 5.025725684161813 s). Tp = 5.561568334196267 s\n",
+      "Sea state 155/200. (Hs, Te) = (1.783850908447242 m, 4.109944171454214 s). Tp = 4.548146237131219 s\n",
+      "Sea state 156/200. (Hs, Te) = (1.3804145578511127 m, 3.948052538207203 s). Tp = 4.368993725111841 s\n",
+      "Sea state 157/200. (Hs, Te) = (1.101209720396516 m, 3.8107141547419805 s). Tp = 4.217012329279396 s\n",
+      "Sea state 158/200. (Hs, Te) = (0.6155862117958195 m, 3.848386306392394 s). Tp = 4.258701084071616 s\n",
+      "Sea state 159/200. (Hs, Te) = (0.525084466395597 m, 3.9369025968803957 s). Tp = 4.356654977534205 s\n",
+      "Sea state 160/200. (Hs, Te) = (0.09750512397836705 m, 4.300920721697868 s). Tp = 4.759484698710284 s\n",
+      "Sea state 161/200. (Hs, Te) = (1.8205359120028697 m, 23.730249683977565 s). Tp = 26.260367855113387 s\n",
+      "Sea state 162/200. (Hs, Te) = (3.976921009811278 m, 23.565594395719824 s). Tp = 26.07815702730834 s\n",
+      "Sea state 163/200. (Hs, Te) = (6.204240115221088 m, 22.723791210681824 s). Tp = 25.146600823935152 s\n",
+      "Sea state 164/200. (Hs, Te) = (10.125799848939408 m, 22.40066350074622 s). Tp = 24.78902125186606 s\n",
+      "Sea state 165/200. (Hs, Te) = (10.66793996073962 m, 21.6908578381681 s). Tp = 24.003536140955944 s\n",
+      "Sea state 166/200. (Hs, Te) = (12.060622651625676 m, 18.266815645632505 s). Tp = 20.21442272138141 s\n",
+      "Sea state 167/200. (Hs, Te) = (11.121735584154075 m, 15.855584181171377 s). Tp = 17.54610586488723 s\n",
+      "Sea state 168/200. (Hs, Te) = (10.998739267749489 m, 13.56417998032559 s). Tp = 15.01039224955217 s\n",
+      "Sea state 169/200. (Hs, Te) = (8.956292813877395 m, 11.186026584968262 s). Tp = 12.378680244425786 s\n",
+      "Sea state 170/200. (Hs, Te) = (6.621433952777892 m, 8.741275725438278 s). Tp = 9.673270156443893 s\n",
+      "Sea state 171/200. (Hs, Te) = (6.533492611294109 m, 8.37223466140765 s). Tp = 9.26488195049804 s\n",
+      "Sea state 172/200. (Hs, Te) = (4.835217043872919 m, 6.811976335865213 s). Tp = 7.53826895133469 s\n",
+      "Sea state 173/200. (Hs, Te) = (3.611112043718707 m, 5.53893766445577 s). Tp = 6.129498953117237 s\n",
+      "Sea state 174/200. (Hs, Te) = (2.833447601414693 m, 4.825371501732234 s). Tp = 5.339852397702617 s\n",
+      "Sea state 175/200. (Hs, Te) = (2.0009470208228026 m, 4.0628436045232785 s). Tp = 4.496023809838518 s\n",
+      "Sea state 176/200. (Hs, Te) = (1.5779173712229868 m, 3.847821538178794 s). Tp = 4.2580761002960745 s\n",
+      "Sea state 177/200. (Hs, Te) = (1.2643248630801083 m, 3.814335921677443 s). Tp = 4.221020248845238 s\n",
+      "Sea state 178/200. (Hs, Te) = (0.8497384887288895 m, 3.660673074170486 s). Tp = 4.050973875337359 s\n",
+      "Sea state 179/200. (Hs, Te) = (0.5569801970656724 m, 3.580383590440513 s). Tp = 3.9621239304052653 s\n",
+      "Sea state 180/200. (Hs, Te) = (0.15728439930305368 m, 3.9432178300420313 s). Tp = 4.363643540576057 s\n",
+      "Sea state 181/200. (Hs, Te) = (1.1422392525115137 m, 24.57816097776294 s). Tp = 27.198683413518285 s\n",
+      "Sea state 182/200. (Hs, Te) = (4.420537323675632 m, 24.662533773594717 s). Tp = 27.292052033107773 s\n",
+      "Sea state 183/200. (Hs, Te) = (7.755814565466879 m, 23.99477020392714 s). Tp = 26.553091541193766 s\n",
+      "Sea state 184/200. (Hs, Te) = (11.148663000514297 m, 22.117310762471593 s). Tp = 24.475457457176223 s\n",
+      "Sea state 185/200. (Hs, Te) = (12.473228354145467 m, 20.601270499596303 s). Tp = 22.797777048564743 s\n",
+      "Sea state 186/200. (Hs, Te) = (12.819497160322692 m, 18.09058901457892 s). Tp = 20.019406814723713 s\n",
+      "Sea state 187/200. (Hs, Te) = (13.145047626413522 m, 17.4098903839333 s). Tp = 19.266132126202617 s\n",
+      "Sea state 188/200. (Hs, Te) = (10.547709475660533 m, 12.521271889157314 s). Tp = 13.856289343856886 s\n",
+      "Sea state 189/200. (Hs, Te) = (9.943350925680063 m, 11.66905560140366 s). Tp = 12.913209793217327 s\n",
+      "Sea state 190/200. (Hs, Te) = (7.5242441111748075 m, 9.07975143213084 s). Tp = 10.047834128004949 s\n",
+      "Sea state 191/200. (Hs, Te) = (6.760594320713308 m, 8.273354886983919 s). Tp = 9.155459618901123 s\n",
+      "Sea state 192/200. (Hs, Te) = (5.109171994744844 m, 6.763731790622878 s). Tp = 7.484880574813655 s\n",
+      "Sea state 193/200. (Hs, Te) = (3.949044029389487 m, 5.6211544147327634 s). Tp = 6.220481649670304 s\n",
+      "Sea state 194/200. (Hs, Te) = (2.8239259484743475 m, 4.63068616046699 s). Tp = 5.1244097139673705 s\n",
+      "Sea state 195/200. (Hs, Te) = (2.344941275016907 m, 4.180452084450019 s). Tp = 4.626171700690346 s\n",
+      "Sea state 196/200. (Hs, Te) = (1.3703724180063444 m, 3.5598449780265367 s). Tp = 3.939395492044637 s\n",
+      "Sea state 197/200. (Hs, Te) = (0.9714898696699685 m, 3.4362402988581957 s). Tp = 3.802612087453428 s\n",
+      "Sea state 198/200. (Hs, Te) = (0.858186544460902 m, 3.4532722006476217 s). Tp = 3.821459929857905 s\n",
+      "Sea state 199/200. (Hs, Te) = (0.5908442916930283 m, 3.5489601073269093 s). Tp = 3.9273500769127194 s\n",
+      "Sea state 200/200. (Hs, Te) = (0.09805058620711124 m, 3.879098338016793 s). Tp = 4.292687631148663 s\n"
      ]
     }
    ],
@@ -475,7 +475,7 @@
     "Here, we will look at the survival function and the 100-year return level. \n",
     "\n",
     "The value of the survival function at a given return level (e.g. 100-years) \n",
-    "may be calculated using the `return_year_value` function. This gives a 100-year wave of about 11.1 meters.  "
+    "may be calculated using the `return_year_value` function. This gives a 100-year wave of about 11 meters.  "
    ]
   },
   {
@@ -487,7 +487,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "100-year elevation: 10.542254436353211 m\n"
+      "100-year elevation: 10.978019989377701 m\n"
      ]
     }
    ],
@@ -514,7 +514,7 @@
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x2351c2b0850>]"
+       "[<matplotlib.lines.Line2D at 0x23482d13190>]"
       ]
      },
      "execution_count": 8,
@@ -523,7 +523,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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s7Gzk5+cDADIzM1FY2HLpfHp6OoqLiwEAaWlp0Ov1AFpmzioqKgAASUlJMBgMAIDExETU1dUBABISEmA0GsHzPBISEsDzPIxGIxISEgAAdXV1SExMBAAYDAYkJSUBACoqKpCcnAwA0Ov1SEtLAwAUFxcjPT0dAFBYWIjMzEwAQH5+PrKzswEAubm5yM3NBQDF25SSlIgN945CgKcLTpbV48Wdx1BbW2s3bRJFEUePHsXFixeZzomVNtXW1iIzMxOiKCrSJnN7KCf7aZP5kJwztckZc+pMm+Li4uDv7w8/Pz/4+Pigb9++kItDXCXHcRzi4+Mxe/ZsAEBzczM8PDzw7bffYs6cOZbtnnrqKWRlZWHfvn0d3vfvv/+OtWvXdugqubNnz8LPz88yovXw8LBM96nVavA8D47jLGWVSgWVSnXFsslkglqttpQ1Gg04jrOUgZZR8+VlrVYLSZIsZfOnJHNZFEVoNJorlgWhZTbHXDbX/UplJdt08Ewl7t14CKIExM0djnmRwQ7fJmfMidp0fW06f/48Pv30UyxevBiBgYFO0SZnzIna5BxtMplMaGhosLSjqqoK4eHhslwl55ADppKSEoSGhiI1NRXR0dGW7VauXIktW7YgLy+vQ/udPn06/vjjDzQ0NECn0yE+Ph5jx45ts515wFRdXQ1fX185mkT+z7rfT+Ptn/PgolFhx2PRiAj1sXWVIIoiiouL0atXL1o7hwFK500337Uv1L/ZYjAY4OfnR8sKcBzX6v+SJLV57Gr27NmDixcv4tKlSzh//ny7g6XLmY/nEvksmdIPtwwJQjMvYvn2LBhNtl9MThRFXLhwgfJmhNJ5u7q6ok+fPjRYshPUv9kiZ84OOWAKCAiAWq1GaWnrtXzKy8vRvXt3xV6XrqqQn0rF4e15IxHo5YrT5fV466eTtq4SNBoNoqOjKW9GKJ13bW0tfvnlF9TW1iqyf2Id6t9sYeIquatxcXFBVFQU9u7d2+rxvXv3tjpEJzdaSl8ZOk8XvDNvBABgc9pZpORftGl9BEHA6dOnKW9GKJ13Q0MDUlNT0dDQoMj+iXWof7NFzpztdsBUX1+PrKwsZGVlAWg5ez4rK8uybMCKFSuwceNGbNq0Cbm5uXj66adRVFSEJUuWKFYnBzjdy2HdNCgI990QBqDlRr2GS802q4skSaiurqa8GUF5s4XyZoucOdvtnOSRI0cwdepUy/9XrFgBAFi4cCE2b96M+fPno7KyEq+//jr0ej0iIiKQkJCAsLAwxepEU7jK+seMIUg9XYEzFQ14/ccTWPXXUTaph0ajueb5bMR5UN5sobzZwsQhuZtuusmyINblX5s3b7Zss3TpUpw9exZNTU3IyMjAlClTFK0TTeEqy91FjXf/OhIcB+z44wJ+zyu3ST0EQcDJkycpb0ZQ3myhvNnCxCE5wqbRvf3wYHQ4AODF+BzUN/E2qUdjo/3dsoUoR8m83d3dERkZCXd3d8Veg1iH+jfpDIdYh8nWzOswybGOA7m2S808YlYn43x1Ix6I7oNXbx9m6yoRQghxQHK+f9MMkxVoCrdreLhoEDd3OABgy4GzyDhX1aWvLwgCcnJyKG9GKJ23yWRCeXm55Z5axLaof7OFDskRpzd5QCDuiuoJSQKe+y7bLha0JKQzKioqsH79ess9ugghjokGTFZQq9W2rgJTXpo5FAHdXFFwsQHrfjvdZa+rVqsRERFBeTOC8mYL5c0WOXOmAZMVaAq3a/l4aPH6HS3nL63fV4C80roueV1BEJCZmUl5M4LyZgvlzRY6JEeYERvRA7cM6Q6TIOH5HdkQxK65RoGuaGIL5c0Wypt0Bg2YrEBTuF2P4zj8a/YwdHPVILPIgM8PnlP8NdVqNQYPHkx5M6Ir8qbfJftB/ZstdEjORnjeNmsCsS7Yxx3P3TYIAPD2zydRYlB2DRWe53H48GHKmxFK5x0cHIyXXnoJwcHBiuyfWIf6N1vkzJkGTFbgOM7WVWDW38aHYXRvXzQ0C3hlV46i94HiOA5+fn6UNyMob7ZQ3myRM2caMFmBpnBtR6Xi8O87R0Cr5vBLbjkSjpUq9lpqtRr9+/envBmhdN4XL17Exx9/jIsXLyqyf2Id6t9soUNyNkJTuLY1oLsXHrupPwDgn98fR80lZRYC5HkeaWlplDcjlM6b53mUlpbS75OdoP7NFjokZyMqFf24bO3xqf3QL9ATFfVNiPspV5HXUKlUCA0NpbwZQXmzhfJmi5w502+MFaiD2Z6rRo237hwBAPj6cDEOnqmU/TVUKhXCwsIob0ZQ3myhvNlCAyYboSlc+zC2jw73jO8NAPjHjmOy3zaF53kkJydT3oygvNlCebOFDsnZCH0isR/Pxw5GkJcrzlQ0YG2SvLdNUalU6NevH+XNCKXz9vX1xbx58+Dr66vI/ol1qH+zhWaYbIQ6mP3wdvvfbVM+2leAXH2tbPumcxzYonTe7u7uGDZsGK0ubSeof7OFBkw2QlO49uW2iGBMH9YdvCjh+R3HZLttCs/zSEpKorwZoXTe9fX1OHDgAOrr6xXZP7EO9W+20CE5G6FPJPbn9Tsi4OWqwdFiA7YeOCvLPlUqFSIiIihvRiidd11dHRITE1FX1zU3jyZXR/2bLTTDZCPUwexPd283/D12MADgnT15uCDDbVNUKhWCgoIob0ZQ3myhvNlCAyYbMZmUWSiRXJ97xvXG2D5+uNQs4OWd13/bFJPJhD179lDejKC82UJ5s0XOnGnAZAVaSt8+qVQc4uYOh4tahaST5fgxW39d+1Or1Rg7dizlzQjKmy2UN1vo1ig2QlO49qt/kBeWTu0HAHjth+MwXGru9L5UKhV0Oh3lzQil83Z1dcXAgQPh6uqqyP6Jdah/s4UOycmguLgYN910E4YOHYoRI0bg22+/veb30BSufXvspn7oH9QNFfXNWJnQ+dummEwm7N69m/JmhNJ563Q63H333dDpdIrsn1iH+jdb5MyZk673hA8HpdfrUVZWhlGjRqG8vByjR49GXl4ePD0922xbW1sLHx8fGAwG+Pj42KC2pKOOnK3CvI8OAAA+XzQekwYEWL0PSZJQV1cHLy8vcBwndxWJnVE6b0EQYDQa4ebmRoeB7AD1b7bU1NTA19cXNTU18Pb2vq59MTvDFBwcjFGjRgEAgoKCoNPpUFVVddXvoc5l/8b00eH+CWEAgGe/O4qaRus/XXAcB29vb8qbEUrnXV5ejnfffRfl5eWK7J9Yh/o3W+TM2W4HTMnJyZg1axZCQkLAcRx27tzZZpt169YhPDwcbm5uiIqKQkpKSqde68iRIxBFEb169brqdjSF6xiejx2MPv4e0NcY8er3x63+fpPJhF27dlHejKC82UJ5s4WJq+QaGhowcuRIrF27tt3nt2/fjuXLl+PFF19EZmYmJk+ejNjYWBQVFVm2iYqKQkRERJuvkpISyzaVlZW4//77sWHDhmvWqa6uDrW1taiurkZ1dTWampogCAIEoeXmrzzPtyqLonjVsslkalU2Hx01lyVJalMG0KosimKrsnlV0yuVBUFoVTbX90plR2yTq5rDqvmjoOKA+MwLSDimt6pNGo0G06ZNs5wsaA9tcsac7KVNarUa06ZNg0ajUaxNZpST7dvEcRxuvvlmaDQap2mTM+bU2TY1NTWhqqoKBoMBtbW1si4Ya7cDptjYWLzxxhuYO3duu8+vWrUKixYtwsMPP4whQ4ZgzZo16NWrF9avX2/ZJiMjAzk5OW2+QkJCAABNTU2YM2cOXnjhBURHR1+zTuHh4fDx8YFOp4NOp0NcXByys7ORn58PAMjMzERhYSEAID09HcXFxQCAtLQ06PUtl7onJyejoqICAJCUlASDwQAArVYCTkhIgNFoBM/zSEhIAM/zMBqNSEhIAPC/lYMBwGAwICkpCQBQUVGB5ORkAC3naKWlpQFoOcE9PT0dAFBYWIjMzEwAQH5+PrKzswEAubm5yM1tOVHaGdo0urcf7hrWcrz6xfhj+P1QplVtSk9Pt7s2OWNO9tImc92VaJO5PZST/bQpLy/P6drkjDl1pk1xcXHw9/eHn58ffHx8EB4eDtlIDgCAFB8fb/l/U1OTpFarpR07drTabtmyZdKUKVM6tE9RFKUFCxZI//znP6+5bU1NjQRAOn36tFRTUyNVVVVJVVVVktFolHiel3ielyRJkkwmU6uyIAhXLTc3N7cqi6LYqiyKYpuyue7msiAIrcomk+mqZZ7nW5XN9b1S2ZHbdMnYLM1YkyyF/f1HaeGnhyzbXKtNzc3N0s6dOyWj0Wh3bXLGnGzdpqamJmnnzp2W75e7TcXFxdKrr74qlZSUUE520KbGxkZL3s7SJmfMqbNtMhqNUmVlpVRdXS3V1NRI+fn5EgCppqZGul4OcZUcx3GIj4/H7NmzAQAlJSUIDQ1Fampqq5mhlStXYsuWLZZPD1ezf/9+TJkyBSNGjLA8tm3bNgwfPrzNtnSVnOM6VVaHv/xnP5p5Ea/dPgwLo/tc83skSQLP89BoNHRiKAOUztt8WEKr1dLaP3aA+jdb5LxKTiNTnWziz7/skiR1uANMmjTJcnyWOK+B3b3w/G2D8fqPJ/Dm7lxE9vbFiJ6+1/w+8x9UwgYl81apVLRopZ2h/k06wyE/7gQEBECtVqO0tLTV4+Xl5ejevbtir2s+GY04lgcn9kHM0O5oFkQ8/uUf11xqgOd5JCYmUt6MUDrvyspKfP7556isrFRk/8Q61L/ZImfODjlgcnFxQVRUFPbu3dvq8b1793bo5O3O0mq1iu2bKIfjOLwzbyR6+rmjuKoRf/8u+6o36NVqtbjjjjsob0YonXdzczMKCgrQ3Nz52/UQ+VD/ZoucOdvtgKm+vh5ZWVnIysoC0HL2fFZWlmXZgBUrVmDjxo3YtGkTcnNz8fTTT6OoqAhLlixRrE4OcLoXuQIfDy0+vGc0tGoOPx8vxfp9BVfcVpIk1NbWUt6MoLzZQnmzRc6c7XbAdOTIEURGRiIyMhJAywApMjISr7zyCgBg/vz5WLNmDV5//XWMGjUKycnJSEhIQFhYmGJ1oilcxzayly9emTUMAPDOnjzsPVHW7nY8zyMlJYXyZgTlzRbKmy1y5uwQV8nZmvkqOTnOsie299LOY/j8YBE8XdT479JoDO5BmRLl6PV6bNiwAYsXL0ZwcLCtq0MIU+R8/7bbGSZ7RFfVOYd/zhqG6H7+aGgW8OBnh3HB0NjqeVEUUVVVRXkzQum8vb29ERsbSx+27AT1b7bImTMNmKxw+S0OiOPSqlVYd+9o9A/qBn2NEfd9egiV9U2W5wVBwOHDhylvRiidt6enJ8aNGwdPT09F9k+sQ/2bLXLmTIfkOoAOyTknfU0j5q0/gAuGRgwP9cHnD4+HjztdOUPk1djYiPz8fAwYMADu7u62rg4hTKFDcjZCU7jOJdjHHVsXjYPO0wXHLtTgnk8OoqqhGaIoory8nPJmhNJ5GwwGxMfHW+7LRWyL+jdb6JCcjVAHcz79Arvh80Xj4e/pguMltViw4QDKahqRk5NDeTNCFEXKmyGUN1towGQjtJS+cxoa4o3tj96A7t6uOFVWj7s2HEKvYWMpb0ZoNBpMmzaN8mYE5c0WOXOmAZMV6BOJ8+of5IVvHp2AMH8PnK9uxOwP92NfXvvrNBHnIooiLly4QP2bEZQ3W2iGyUaogzm3MH9PxC+diLFhfmhoFvHg5iP48LfTEEW6LsKZiaKIgoICxfq3VqtFz5496VYcdkLpvIl9kTNnukquA+gqObY08QJejM/BdxnnAQA3DgzE6vmjoPN0sXHNCCGEWIOukrMR+kTCBq2KwxNjfRA3NwKuGhX2nbqIGe+nYN+pi7auGlGAKIo4d+4c9W9GUN5soUNyNkIdjA2iKKKkpAR3jQ7Fricmom+gJ0prjVi4KR0v7DiG+ia6B5UzUfqcFr1ej9deew16vV6R/RPr0DlMbKEBk43QVRVs0Gg0iI6OhkajweAe3vjxyUlYOKHlps5fpRfhtjXJOFBQaeNaErlcnjdxfpQ3W+gqORuhpfTZIAgCTp8+bcnbw0WD1+6IwJePjEeorzvOVzfi7k8O4uWdOTTb5AT+nDdxbpQ3W+TMmQZMVqDz49kgSRKqq6vb5B3dLwB7np6Cu8f1BgBsO3gO01cnI5nObXJoV8qbOCfKmy1y5kwDJivQFC4bNBoNxo5tf+HKbq4axM0dji8eHo+efu64YGjE/ZvS8dx3R1HTaLJBbcn1ulrexPlQ3myhQ3I2QlO4bBAEASdPnrxq3hP7B2DP8il4ILoPOA745sh5xKzeh19O0GKXjqYjeV+PwMBAPPnkkwgMDFRk/8Q6SudN7AsdkiNEYY2NjdfcxtNVg1dvH4ZvHp2AvgGeKKttwsNbj+CprzNR1dDcBbUkculI3p2l0Wig0+loRsOOKJk3cV60cGUH0MKV5FqMJgGr957CJylnIEpAQDcXvH5HBGYMD7Z11YiNVVdX47fffsPUqVPh5+dn6+oQwhRauNJGaAqXDYIgICcnx6q83bRqvDBjCHYsnYiB3buhor4ZS7/4A499noGLdU0K1pZcr87kbQ2j0Yhjx47BaDQqsn9iHaXzJvaFDskRYqdG9fLFD09OwrJp/aFRcfgppxS3rt6H+MzzdFUOIYQ4MBowWUGtVtu6CqQLqNVqREREdDpvV40aK2IGYdcTEzEsxBuGSyY8vf0oFm05An0NnTthb643b+JYKG+2yJkzDZisQFO4bBAEAZmZmded97AQH+x8fCKenT4ILmoVkk6WI2ZVMr5OL6LZJjsiV97EMVDebLHZIbm8vDy8+uqruPnmm9GvXz8EBwdjxIgRWLhwIb788ks0NTnOuRp1dXUYO3YsRo0aheHDh+OTTz6xdZWIHXF3d5dlP1q1Co9P7Y/dyyZhVC9f1DXxeH7HMdy/KR1ltXROi72QK+/2dOvWDTfeeCO6deum2GsQ6yiZN3FeHbpKLjMzE8899xxSUlIQHR2NcePGITQ0FO7u7qiqqkJOTg5SUlJQW1uL5557DsuXL4erq2tX1L/TBEFAU1MTPDw8cOnSJURERODw4cPw9/dvsy1dJUfkIIgSPkstxDt78tDEi9B5uuCdeSNw85Dutq4aIYQ4JTnfvzs0YAoLC8Ozzz6Le+65Bzqd7orbHThwAKtXr8aoUaPwj3/847oq1pWqqqoQGRmJjIwMBAQEtHne/AOvrKy8avuJc+B5HpmZmYiMjFRk7ZzT5fVY9lUmTuhrAQAPRPfB87GD4aalcypsQem8m5qaUFxcjF69etn9B0kWKJ03sS9VVVXw9/fvumUF8vPz8cQTT1xzsDBhwgR88803eOaZZ66rUgCQnJyMWbNmISQkBBzHYefOnW22WbduHcLDw+Hm5oaoqCikpKRY9RoGgwEjR45Ez5498dxzz7U7WLocx3FW7Z84Jo7j4Ofnp1je/YO6If7xaDw0MRwAsDntLOasS8Pp8jpFXo9cndJ5V1VV4YsvvkBVVZUi+yfWUTpvYl/kzLlDA6YePXqgoqICAPDQQw+hru7qf9hdXFyuu2INDQ0YOXIk1q5d2+7z27dvx/Lly/Hiiy8iMzMTkydPRmxsLIqKiizbREVFISIios1XSUkJAMDX1xdHjx5FYWEhvvzyS5SVXf22FnRVBRvUajX69++vaN6uGjVemTUUmx4YA52nC3L1tZj1n1R8f7REsdck7euKvIn9oLzZ0uVXyTU3N6O2tuXwwZYtW7pkAbbY2Fi88cYbmDt3brvPr1q1CosWLcLDDz+MIUOGYM2aNejVqxfWr19v2SYjIwM5OTltvkJCQlrtq3v37hgxYgSSk5OvWqeKigrU1taiuroa1dXVaGpqgiAIlrPweZ5vVRZF8aplk8nUqmw+OmouS5LUpgygVVkUxVZlnuevWhYEoVXZXN8rlVlsE8/zSE1NRXNzs+JtumlgIH58IhrR/fzRaBKw7KtMvP7DCRibTZRTF7XJZDJh//79ln0p0SYzysn2bWpqakJqaqql3s7QJmfMqbNtampqQlVVFQwGA2pra3Hx4kXIpUMDpgkTJmD27Nl48MEHIUkSli1bhoceeqjdr67Q3NyMjIwMxMTEtHo8JiYGaWlpHdpHWVmZZRBYW1uL5ORkDBo06Krf069fP/j4+ECn00Gn0yEuLg7Z2dnIz88H0HJyfGFhIQAgPT0dxcXFAIC0tDTo9XoALYcazbN1SUlJMBgMAIDExETLzF1CQgKMRiN4nkdCQgJ4nofRaERCQgKAliv8EhMTAbQcVkxKSgLQMqAzD/r0er3lZ1FcXIz09HQAQGFhITIzMwG0HGrNzs4GAOTm5iI3NxcAmG+TSqVCfX295RCK0m06fSwD2xaNx72RLYeEN6UWYt6HKUhKO0I5dUGbLl26hOrqaqhUKkXaZG4P5WQfbTpz5gxEUYRKpXKaNjljTp1tU1xcHPz9/eHn5wcfHx/0798fcunQSd9lZWVYvXo1CgoKsGPHDkyfPv2KJy/Gx8fLVjlLJTkO8fHxmD17NgCgpKQEoaGhSE1NRXR0tGW7lStXYsuWLcjLy7vmPjMyMrBo0SLL6Pixxx7DY4891u625pO+z549Cz8/P8uI1sPDw3LSoFqtBs/z4DjOUlapVFCpVFcsm0wmqNVqS1mj0YDjOEsZaBk1X17WarWQJMlSFkURgiBYyqIoQqPRXLEsCAIkSbKUzXW/Upna1LVt2nO8FM99dwx1TTwCu7ngo/uiMKqnj0O3yRlzsqZNpaWl+Oabb7BgwQLodDqnaJMz5kRtco42mUwmNDQ0WNpRVVWF8PDwrrtK7nLh4eE4cuRIu5ffK+VKA6a0tDRMmDDBst2bb76Jbdu24eTJk7K+Pl0lxxae55GWlobo6GibXEVTWNGAJdsykFdWBxe1Cv+eNxxzInt2eT1YYeu8SdeivNnS5VfJXa6wsLBLB0vtCQgIsHxyu1x5eTm6d1duTRuVihZGZ4FKpUK/fv1slnd4gCfiH4/G9GHd0SyIeHr7Uby7Jw+iSKuDK8HWeZOuRXmzRc6cOzS8/uCDDzq8w2XLlnW6Mh3l4uKCqKgo7N27F3PmzLE8vnfvXtxxxx2KvS51MDaoVCqEhobatA4eLhqsvzcK7ybmYd3vBVj722mcqajHe3eNgrsLXd0jJ6XzLisrw9atW3H//fcr+oGOdIw99G/Sdbp8wLR69epW/7948SIuXboEX19fAC0ndnl4eCAoKEi2AVN9fT1Onz5t+X9hYSGysrKg0+nQu3dvrFixAvfddx/GjBmDCRMmYMOGDSgqKsKSJUtkef32mM/eJ86N53kkJydjypQpNp2yV6k4PHfbYPQN7IYXdmQj4VgpzlcfwKYHxiKgGy2AKBel8xZFEZcuXbJccURsy176N+kacr5vd+i3xXwWOgB8+eWXWLduHT799FPLVWV5eXl45JFH8Oijj8pWsSNHjmDq1KmW/69YsQIAsHDhQmzevBnz589HZWUlXn/9dej1ekRERCAhIQFhYWGy1eHPaIaJDSqVChEREXaT97yongjz98DirUeQfb4G89anYetD49Hb38PWVXMK9pY3URblzRY5c7b6pO9+/frhu+++Q2RkZKvHMzIyMG/evFaDK2dB95Ij9uDMxXrc92k6LhgaEdDNFVseGothIT62rha5Br1ejw0bNmDx4sUIDg62dXUIYYqc799WD730er1lIarLCYJwzZWyHV177SbOx2QyYc+ePXaXd9/AbtixNBqDe3ihor4J8z8+iLSCCltXy+HZa95EGZQ3W+TM2eoB080334xHHnkER44csaz8eeTIETz66KO45ZZbZKuYPaKl9NmgVqsxduxYu8y7u7cbtj86AePDdahv4vHApsNIOKa3dbUcmtJ5+/v746GHHrL51cWkhT33byK/Lr81yuU2bdqE0NBQjBs3Dm5ubnB1dcX48eMRHByMjRs3ylYxe0THvNmgUqmg0+nsNm8fdy22PDQOsRE90CyIeOLLP/BdxnlbV8thKZ23i4sLevXqJcs9Nsn1s/f+TeQlZ85W7ykwMBAJCQnIy8vDt99+i2+++Qa5ublISEhAUFCQbBWzRzSFywaTyYTdu3fbdd5uWjXW3jMaC8b2gigBz3x7FJ8fPGfrajkkpfOura3Fnj17LLdiIrblCP2byEfOnDt9TeWAAQMwYMAA2SriCOgSVDZoNBpMnjzZ7vNWqzjEzR0ON60am9PO4qWdOWjiRSyaFG7rqjkUpfNuaGjAwYMHMWLECLpoxA44Sv8m8pAzZ6tnmObNm4e33nqrzePvvPMO7rrrLlkqZa84jrN1FUgX4DgO3t7eDpE3x3H456yhWHJjPwDAv348gQ9/O32N7yKXc6S8yfWjvNkiZ85WD5j27duHmTNntnn8tttus9yJ2FnRFC4bTCYTdu3a5TB5cxyHv982CE/fMhAA8M6ePLy7Jw9WrhjCLEfLm1wfypstNr1Krr6+vt2TF7VardMfo6cpXDZoNBrExMQ4VN4cx+GpWwbghdjBAIC1v53Gm7tzadDUAY6YN+k8ypstNj0kFxERge3bt7d5/Ouvv8bQoUNlqRQhtuaof0wfvbEfXrt9GABg4/5C/PP743TT3g5QMm8PDw+MGTMGHh60Mru9cNT+TWzL6t+al19+GXfeeScKCgowbdo0AMCvv/6Kr776Ct9++63sFbQndC85NvA8j4SEBMyYMQNardbW1bHawug+cNOq8PyOY9h64BxMgoQ3Z0dApaJzNtqjdN4+Pj7tnsZAbMPR+zexjpzv21bfGgUAdu/ejZUrVyIrKwvu7u4YMWIE/vnPf+LGG2+UrWL2xLy0usFggI8P3YrC2UmSBJ7nodFoHPrE0P9mnMez3x2FKLXcj+7fd46AmgZNbSidt8lkQkVFBQICAugN2g44S/8mHVNTUwNfX19Zbo3SqQETa2jAxBZJkmA0GuHm5ubwf1B3ZV3Aim+OQhAl3DEqBO/dNRIaNS3Ydzml86Z7ydkXZ+rf5NrkHDBd11/OpUuXoqKCnXtZ0SE5NvA8j8TERKfI+45RofjP3ZHQqDjsyirBU9uzYBJEW1fLrjhT3uTaKG+2yJnzdQ2YPv/8c6e/Mu5yNJ3OBq1WizvuuMNp8p4xPBjr7h0NrZrD7mw9nvjyDzTzNGgyc7a8ydVR3myRM+frGjCxdjSPtfaySpIk1NbWOlXeMcN6YMN9Y+CiUWHP8TIs+TwDRpNg62rZBWfMm1wZ5c0WOXOmkxmsQFO4bOB5HikpKU6X99TBQdh4/xi4alRIOlmOxdto0AQonzfHcXBxcaHzZeyEs/Zv0j6bXyXHGvNJ33KcNEaIraUVVGDR5iNoNAmI7uePjQvHwMOF1qUhhDgfOd+/ZZth4nkeRUVFcu3OLokinffBAlEUUVVV5bR5R/cLwJaHxsHTRY20gko8sOkw6pvY/bTt7HmT1ihvtsiZs2wDpuPHjyM83Lnvki4IdPiCBYIg4PDhw06d97hwHbYuGg8vVw3Sz1bh/k8PodbI5r21lM774sWLWLduHS5evKjI/ol1WOjf5H/kzJnOYbICXVXBBq1Wi+nTpzt93lFhfvjikfHwdtPgjyID7tt4CDWX2Bs0KZ03z/O4ePEinTNjJ1jp36SFnDl3+MSF0aNHX/X5xsbG666MvaMpXDaIomhZmVmlcu7PFCN6+uLLR27AfZ8ewtHzNbhn40F8vmg8/Dzb3mDbWbGUN6G8WSPn+3aHB0wnTpzAggULrnjYTa/X49SpU7JVzB7RgIkNoigiJycHU6ZMYeIPakSoD75afAP+tvEQjpfU4u5PDuLzh8cjoJurravWJVjLm3WUN1tsMmCKiIjA+PHj8dhjj7X7fFZWFj755BPZKmaP6A7XbNBoNJYbS7NicA9vfL34Btz9ySGcLK3D3RsOYtui8ejh42brqimOxbxZRnmzRc737Q4PrydNmoS8vLwrPu/l5YUpU6bIUqmudOnSJYSFheGZZ5655rY0w8QGURRx4cIF5vLuH+SF7YtvQA9vN+SX1+PO9Wk4XV5v62opTum8/fz8sGDBAvj5+Smyf2IdVvs3q2xyldyaNWuwZs2aKz7fr18//Pbbb3LUqUu9+eabGD9+fIe2pQ7GBlEUUVBQwGTefQO74dslE9A3wBMXDI2Y91Ea/iiqtnW1FKV03m5ubhg0aBDc3Jx/ts4RsNy/WWSXywo4ovz8fJw8eRIzZszo0PZ0SI4NGo0GU6ZMYTbvXjoPfPdYNEb28oXhkgn3fHIQv+aW2bpailE67/r6eqSkpKC+3vln6xwB6/2bNV1+SM7aBSkvXLjQqcpcLjk5GbNmzUJISAg4jsPOnTvbbLNu3TqEh4fDzc0NUVFRSElJseo1nnnmGcTFxXV4e/pEwgZRFHHu3Dmm89Z5uuCrR8bjpkGBMJpELN6WgW8OF9u6WopQOu+6ujokJSWhrq5Okf0T61D/ZkuXzzCNHTsWjzzyCNLT06+4TU1NDT755BNERERgx44d112xhoYGjBw5EmvXrm33+e3bt2P58uV48cUXkZmZicmTJyM2NrbV4C4qKgoRERFtvkpKSrBr1y4MHDgQAwcO7HCdqIOxgc5xaOHhosEn94/BvKieEEQJz/03G+//ku90Ny2lvNlCebNFzpw7dC+5qqoqrFy5Eps2bYJWq8WYMWMQEhICNzc3VFdX48SJEzh+/DjGjBmDl156CbGxsbJVEGi5eWV8fDxmz55teWz8+PEYPXo01q9fb3lsyJAhmD17dodmjV544QV8/vnnUKvVqK+vh8lkwv/7f/8Pr7zySpttzfeiOXv2LPz8/Cwrh3p4eFim+9RqNXieB8dxlrJKpYJKpbpi2WQyQa1WW8oajQYcx1nKQMuid5eXtVotJEmylEVRhCAIlrIoitBoNFcsC4IASZIsZXPdr1SmNlGbJEnC2z+fxEfJhQCA20cE4+27RsJFzTlsm7oyp/Pnz+PTTz/F4sWLERgY6BRtcsacqE3O0SaTyYSGhgZLO6qqqhAeHt5195LT6XR49913UVJSgvXr12PgwIGoqKhAfn4+AODee+9FRkYGUlNTZR8stae5uRkZGRmIiYlp9XhMTAzS0tI6tI+4uDgUFxfj7NmzePfdd/HII4+0O1i6XJ8+feDj4wOdTgedToe4uDhkZ2dbfg6ZmZkoLGx5U0lPT0dxccshjLS0NOj1egAthxorKioAAElJSTAYDACAxMREy5R9QkICjEYjeJ5HQkICeJ6H0WhEQkICgJYp/sTERACAwWBAUlISAKCiogLJyckAWtbFMv8siouLLbODhYWFyMzMBNByDld2djYAIDc3F7m5uQDAfJsEQcAvv/yCsrIyp2nT9eTU1NSEIaZ8rJwzHBoVh++z9bh34yGcuXDRYdt0eU41NTX4+eefIQiCIjmZ29OVbXKW3z0l2pSXl4f9+/dDEASnaZMz5tTZNsXFxcHf3x9+fn7w8fGR9ZZtHZphsrU/zzCVlJQgNDQUqampiI6Otmy3cuVKbNmy5arLH7Rn8+bNyMnJwbvvvtvu8+YZpoKCAgQEBNAMk5O3SRRFZGRkIDIyEi4uLk7RJrly2p9/EUu/+AO1Rh49/dyx4d5IDO3p59BtMplM+OOPPxAVFQWVSiV7ThUVFUhKSsKtt94KLy8v5vqTvbWpqakJR48exejRo8FxnFO0yRlzkmuG6eLFi+jfv78sM0wOPWBKS0vDhAkTLNu9+eab2LZtG06ePCnr65sHTHL8wAlxdKfL67Foy2Gcq7yEbq4arL0nEjcNCrJ1tQghpA05378dclmBgIAAqNVqlJaWtnq8vLwc3bt3V+x16e7WbBAEASdPnqS8r6B/UDfsXDoR48J1qG/i8dDmw/hoX4HDngyudN6CIKC2tpZ+n+wE9W+2yJmzQw6YXFxcEBUVhb1797Z6fO/eva0O0RHSWSzcTPp6+Hm64PNF4/HXMT0hSsBbP53EE19moqGJt3XVOkXJvMvLy7F69WqUl5cr9hrEOtS/SWfY7cpd9fX1OH36tOX/hYWFyMrKgk6nQ+/evbFixQrcd999GDNmDCZMmIANGzagqKgIS5YsUaxOarVasX0T+6FWqxEZGWnratg9F40K/75zBIb39MXrPxzH7mN6nCqrw8f3RaFvYDdbV6/DKG+2UN5skfN9225nmI4cOYLIyEjLL/aKFSsQGRlpuZJt/vz5WLNmDV5//XWMGjUKycnJSEhIQFhYmGJ1oilcNgiCgJycHMq7AziOw303hOHrxTcgyMsV+eX1uGNtKn454Tgrg1PebKG82SJnzp2aYTp16hR+//13lJeXt1kU6lqX5nfUTTfddM1zIpYuXYqlS5fK8nqEkM6LCtPhxycnYekXf+DIuWo8vPUInpjaH8tvGQCN2m4/lxFCSIdZfZXcJ598gsceewwBAQHo0aOH5bJMoOXT5h9//CF7JW2NrpIjpGOaeRFv7j6BLQfOAQDGhevwn7sj0d2b3RvP6vV6bNiwAYsXL0ZwcLCtq0MIU+R8/7Z6wBQWFoalS5fi73//+3W9sCMx/8Crqqrg5+dn6+oQhQmCgOzsbIwYMYLOW+uk74+W4IX/ZqOhWYDO0wWr54/CjQMDbV2tdimdtyRJEAQBarW61QdMYhvUv9lSXV0NnU5nm2UFqqurcdddd13XixJi79zd3W1dBYd2+8gQ/LhsMoYGe6OqoRkLN6Xj7Z9Pghfs8/5dSubNcZxl0T9iH6h/k86wesB01113WZY9Zw19GmGDWq3G4MGDKe/rFB7giR1Lo3HfDS0XYqz7vQB3f3IQ+hr7uqRb6bwrKyuxefNmVFZWKrJ/Yh3q32yRM2erT/ru378/Xn75ZRw8eBDDhw+HVqtt9fyyZctkq5y94XnHXGOGWIfneWRmZiIyMtKy7D/pHDetGv+aHYHxfXV4/r/HcPhsNWLfT8Fbc0fgtogetq4eAOXzbm5uxrlz59Dc3Cz7von1qH+zRc73bat/WzZs2IBu3bph37592LdvX6vnOI5z6gETTamzgeM4+Pn5Ud4y+suIEAwP9cHjX/6BnAu1WPJ5Bu4e1wsv/2UoPFxs+6ZFebOF8maLnDlb/ZfKfGdgFtEULhvUajX69+9v62o4nTB/T+x4bCLe25uHDcln8FV6MQ6dqcKaBaMwoqevzepFebOF8maL3SxcKUmSw94/qjPokBwbeJ5HWloa5a0AF40KL8QOwRcPj0cPbzecqWjA3HVp+PC30xBE2/wtobzZQnmzRc6cOzVg2rp1K4YPHw53d3e4u7tjxIgR2LZtm2yVslcqFS3AxwKVSoXQ0FDKW0HR/QLw8/LJmDk8GLwo4Z09ebj7k4O4YOj6E8KVztvHxwezZs2Cj4+PIvsn1qH+zRY5c7Z6HaZVq1bh5ZdfxhNPPIGJEydCkiSkpqbiww8/xBtvvIGnn35atsrZC1q4khBlSJKE7zLO49Xvj6OhWYCXmwZvzhmO20eG2LpqhBAnYNOFK8PDw/Haa6/h/vvvb/X4li1b8OqrrzrlOU7mH3hlZSV0Op2tq0MUZp6yj46Opqtousi5ygY89XUWsooNAIC/jAjGv+6IgJ+ni+KvrXTely5dwsmTJzF48GB4eHjIvn9iHerfbKmqqoK/v79tFq7U6/WIjo5u83h0dDT0ev11Vcbe0RQuG1QqFfr160d5d6Ewf098u2QCnrp5ANQqDj9m6xGzJhlJJ5W/ia/SedfU1OCHH35ATU2NIvsn1qH+zRY5c7Z6T/3798c333zT5vHt27djwIABslTKXlEHYwOd42AbWrUKT986EDsei0a/QE9crGvCQ5uP4O/fZaPOaFLsdSlvtlDebJEzZ6vnI1977TXMnz8fycnJmDhxIjiOw/79+/Hrr7+2O5ByJnRVBRt4nkdycjKmTJlCU/Y2MLKXL3Yvm4x39+Th09RCbD9SjP2nK/DOXSMQ3S9A9tejvNlCebPFplfJ3XnnnTh06BACAgKwc+dO7NixAwEBAUhPT8ecOXNkq5g9ok8kbFCpVIiIiKC8bchNq8ZLfxmKrx65AT393HHB0Ih7PjmE1344DqNJkPW1KG+2UN5sselVciyiq+QIsZ36Jh5v7s7FV+lFAIC+gZ54766RiOztZ+OadUxlZSV++OEHzJo1C/7+/rauDiFMkfP9u0NDr9ra2lblq305M5NJufMoiP0wmUzYs2cP5W0nurlqEDd3OD57cCyCvFxx5mID7lyfhnf35KGZF697/0rn7e/vjwceeIAGS3aC+jdb5My5QzNMarUaer0eQUFBUKlU7d6bRZIkcBwHQZB3utwemEeo1dXV8PX1tXV1iMJEUYTBYICvry9N29sZw6VmvLLrOL4/WgIAGNzDC+/MG4nhPTu/KKTSeUuSBEEQoFar6f5ldoD6N1sMBgP8/Py6bh2mffv2YeLEidBoNG1uuPtnN95443VVyB7RITlC7MvubD1e3pWDqoZmqFUcltzYF8tuHgBXjf3d71Gv12PDhg1YvHgxgoODbV0dQpgi5/t3hy4RuHwQFB4ejl69erX5pCRJEoqLi6+rMvaOpnDZYDKZkJiYiJiYGGi1WltXh7Rj5ohg3NBXh1e+P47d2Xp8+FsB9p4owzvzRmJkL1+r9kV5s4XyZouc79tWz0eGh4fj4sWLbR6vqqpCeHi4LJWyV3QJKhs0Gg0mT55Meds5/26u+PCe0Vh/72gEdHPBqbJ6zFmXird+OmnVlXSUN1sob7bImbPVAybzuUp/Vl9fDzc3N1kqZa/o/AM2cBwHb29vyttBxA4PRuLTN+KOUSEQJeCjfQWY+UEK/iiq7tD3U95sobzZImfOHR56rVixwvLiL7/8cqt7IgmCgEOHDmHUqFGyVcwe0SE5NphMJiQkJGDGjBk0Ze8gdJ4ueH9BJGYOD8aLO3NQcLEB89anYdGkcPy/mEFw01753CbKmy2UN1u6/Co5AJg6dSqAlhPAJ0yYABeX/90U08XFBX369MEzzzzjULdH0Wg0iIiIAACMGTMGGzdubHc780ljBoMBPj6dvxqHOAZJkmA0GuHm5kafQh2Q4VIzXv/hBHZkXgAA9A3wxNvzRmBMn/ZvnK103oIgoKGhAZ6enlCr7e+kdNZQ/2ZLTU0NfH19u+4qucs9+OCDeP/9953iarGAgABUVFRcczsaMLFFkiTwPA+NRkN/UB3Yr7ll+Ef8MZTVNoHjgAejw/Hs9EFwd2k9aKG82UJ5s0XOAZPV5zCtWbOm3XuzVFVVOf3ClXQvOTbwPI+EhATK28HdPKQ7Ep++EXdF9YQkAZtSC3Hb+8k4dKay1XZK511dXY1vv/0W1dUdO6eKKIv6N1tsei+5BQsW4Ouvv27z+DfffIMFCxbIUikASE5OxqxZsxASEgKO47Bz584226xbtw7h4eFwc3NDVFQUUlJSrHqN2tpaREVFYdKkSddcXwqgq+RYodFoMGPGDMrbCfi4a/HOXSOx+cGxCPZxw7nKS5i/4SD+uSsHDU0tf0iVzttoNOLEiRMwGo2K7J9Yh/o3W2x6ldyhQ4cs5zNd7qabbsKhQ4dkqRQANDQ0YOTIkVi7dm27z2/fvh3Lly/Hiy++iMzMTEyePBmxsbEoKiqybBMVFYWIiIg2XyUlLasEnz17FhkZGfjoo49w//33O/0MGek4+vTpXG4aFIQ9T0/BgrG9AABbDpzD9DXJSD3dckie8mYL5U06w+oBU1NTU7u/bCaTCY2NjbJUCgBiY2PxxhtvYO7cue0+v2rVKixatAgPP/wwhgwZgjVr1qBXr15Yv369ZZuMjAzk5OS0+QoJCQEAy78REREYOnQoTp06ddU6VVRUoLa2FtXV1aiurkZTUxMEQbDcDobn+VZlURSvWjaZTK3K5tPJzGVJktqUAbQqi6LYqmzO5kplQRBalc31vVKZxTbxPI/ExEQ0Nzc7TZucMSdr2+TlqsG/bh+CrQ+NRYivG85XN+LejYfw/H+P4vuERMu+lGiTGeVk+zY1NTUhMTHRUm9naJMz5tTZNjU1NaGqqgoGgwG1tbXtrhvZWVYPmMaOHYsNGza0efyjjz5CVFSULJW6lubmZmRkZCAmJqbV4zExMUhLS+vQPswDHgA4f/48Tpw4gb59+171e/r37w8fHx/odDrodDrExcUhOzsb+fn5AIDMzEwUFhYCANLT0y0rn6elpUGv1wNoOdRoPtE8KSkJBoMBAJCYmIi6ujoAQEJCAoxGY6tj7UajEQkJCQCAuro6JCYmAmi5T05SUhKAlgFdcnIygJbbMZh/FsXFxUhPTwcAFBYWIjMzEwCQn5+P7OxsAEBubi5yc3MBgPk2abVaeHl5oaamxmna5Iw5dbZNE8L98P2ScZjUveXNYPuRC4g7qkHqmWpF2mRuD+VkH206e/YsevfuDa1W6zRtcsacOtumuLg4+Pv7w8/PDz4+PrJeuW/1VXKpqam45ZZbMHbsWNx8880AgF9//RWHDx9GYmIiJk+eLFvlLJXkOMTHx2P27NkAgJKSEoSGhiI1NRXR0dGW7VauXIktW7YgLy/vmvtMS0vDo48+armZ8KuvvmrZ/5+Zr5IrLCyETqezjGg9PDwsx0fVajV4ngfHcZaySqWCSqW6YtlkMkGtVlvK5qs2zGUAlqs5zGWtVmu5ykOr1UIURQiCYCmLogiNRnPFsiAIkCTJUjbX/UplFtvEcRyqq6vh4+MDtVrtFG1yxpzkaNORolr8/b9HUVTVMjt+5+hQvHDbQAR4e8jWppqaGhw9ehSjR4+2XMpOOdmuTTzPo66uDr6+vpYZFEdvkzPm1Nk2mUwmNDQ0WNphvguJTZYVAICsrCy88847yMrKgru7O0aMGIEXXnhBsTWYrjRgSktLw4QJEyzbvfnmm9i2bRtOnjwp6+ubB0wVFRXw9/eXdd/E/tC9pthS09CI5Z8m4Xc9IElAkJcrVs4ZjluGdrd11YgCqH+zpbKyEgEBAV13890/GzVqFL744ovreuHrERAQALVajdLS0laPl5eXo3t35f7IUedig1arxcyZM21dDdJFfDzd8dmymThytgrPfZeNMxUNeHjrEdwxKgSvzhoGP0+Xa+/kKoxGI86dO4ewsDCnv32UI6D+zRY537etPocJaDlJ69SpU9i/fz+Sk5NbfXUFFxcXREVFYe/eva0e37t3b6tDdHIzT98S5yaKIqqqqihvRpjzHt3bFwlPTcajU/pCxQG7skpw6+p9+OmY/rr2X11dja+//prWYbIT1L/ZImfOVs8wHTx4EPfccw/OnTuHPx/N4ziu1RUh16O+vh6nT5+2/L+wsBBZWVnQ6XTo3bs3VqxYgfvuuw9jxozBhAkTsGHDBhQVFWHJkiWyvH575GobsW+CIODw4cOYNm0aVKpOfaYgDuTyvN20WrwwYwhihwfj2W+PIr+8Ho998QdmDg/Ga3cMQ0A3V1tXl1wn6t9skfN92+pzmEaNGoWBAwfitddeQ3BwcJul5eW6dcjvv//e7npPCxcuxObNmwG0LFz59ttvQ6/XIyIiAqtXr8aUKVNkef3Lmc9hkuMYKCHEMTTxAv7z62ms31cAQZTg56HFq7cPw+0jQ6y6pYZer8eGDRuwePFiBAcHK1hjQsifyfn+bfWAydPTE0ePHkX//v2v64UdifkHXl1dDV9fX1tXhyhMFEVUVFQgICCAPoEy4Fp551yowTPfHsXJ0pbLqm8d2h1vzo5AkHfHzkeiAZN9of7NFoPBAD8/P9vcS278+PGtDpWxhI55s0EUReTk5FDejLhW3hGhPvj+iUl4+paB0Ko57D1RhltW7cN3GefbnJbQHo1Gg8DAQLoVh52g/s0WOXO2eoYpPj4eL730Ep599lkMHz68zRnoI0aMkK1y9oIOyRFCAOBkaS2e/TYbxy60LGo6dVAgVs4djmAfdxvXjBDSHpsekmtvCpPjOEiSJOtJ3/aEDsmxRRRF6PV6BAcH05Q9A6zNmxdEbEg5gzV789EsiPBy1eDFmUMwf2wvq85tIrZB/Zstch6Ss3qO2LwMOYtoCpcNoiiioKAA3bt3pz+oDLA2b41ahaU39UfM0O549rtsZBYZ8PyOY/gxW4+4ucPRS+fRavvS0lJ89tlnePDBB9GjRw+lmkE6iPo3W2x6SI5FdEiOENIeQZSwaX8h3k3MQxMvwtNFjedjB+Pe8WFQqVpmm+ikb0JsR873b6tnmLZu3XrV5++///5OV8be0QwTG0RRRHFxMXr16kWfQBlwPXmrVRwemdIXtwztjr9/l430s1V4eddx7D6mx7/vHIEwf0+Fak06i/o3W2y6cOVTTz3V6v8mkwmXLl2Ci4sLPDw8aMBEHJ4oirhw4QJCQ0PpDyoD5Mg7PMATXy++AVsPnMW/f87DwTNVmL4mGc9OH4zp4bTYpT2h/s0Wuzskl5+fj8ceewzPPvsspk+fLke97AodkiOEdFRR5SX8/b/ZOHCmEgAwKUSNAdWH6JAcITZg06vkruTIkSP429/+hpMnT8qxO7ti/oGfOHGi1VVybm5u8PPzA8/zuHjxYpvvM/9xrKiogMlkavWcr68v3N3d0dDQgNra2lbPubi4wN/fH6IooqysrM1+g4KCoFarUVVVhaamplbPeXl5oVu3bmhsbITBYGj1nHk9GKDlvIo/CwgIgFarhcFgQGNjY6vnPD094e3tjaamJlRVVbV6TqVSWW56XFZW1mZEr9Pp4OrqitraWjQ0NLR6zt3dHb6+vjCZTKioqGhTJ/PP8OLFi+B5vtVz5p9hfX096urqWj3n6uoKnU4HQRBQXl7eZr/mEz4rKyvR3Nzcpq3l5eXo0aNHm/1qtVoEBAQAaP9naF5vp7q6GkajsdVz3bp1g5eXV7s/Q7VajaCgIADt/wz9/f3h4uLS7s/Qw8MDPj4+7f4MOY6znGjc3s/Qz88Pbm5u7f4Mzb/fV/oZ9ujRAxzHtfsz9PHxgYeHBy5duoSamppWz5l/vyVJanMDbeB/v9/t/QzNv99Go7HNvdku//0uLS1ts0aS+fe7pqYGly5dsjwuCAKqqqowbNgwCIKAysrKVt93+e93eXl5myuBzb/fdXV1qK+vBwCIooSfj5fi49RiVDZxCNIYcfe4Xpgzujc06v/NatDfiNY/w674GyEIAkpKShAeHo7AwMBO/Y3w9vaGp6dnuz9D+hvxP/bwN8JgMGDo0KG2OYfpStRqNUpKSuTanV3aunVrq7uNDx8+HHPnzkVtbS02bNjQZvt//vOfAIBdu3bh/PnzrZ6bM2cORowYgePHj+Onn35q9Vy/fv3wt7/9DSaTqd39PvPMM/D09MSePXtw6tSpVs/FxMRgwoQJOHPmDL777rtWz/Xo0QOPPvooAODTTz9t84f/scceQ1BQEJKTk5GZmdnquYkTJ+KWW26BXq/Hli1bWj3n5eWFFStWAAC++OKLNp1q4cKF6NOnD9LT05GamtrqucjISNx+++2orq5u01a1Wo2XXnoJALBjx442HWfevHkYNmwYjh07hsTExFbPDRw4EHfffTeMRmO7P8Pnn38erq6u+Omnn1BQUNDquenTp0OtVqOurg7ff/99q+d69uyJRYsWAUC7+33yySeh0+nw22+/4dixY62eu/HGG3HTTTehuLgYX3zxRavn/Pz8sGzZMgAtv2eXv6EDwEMPPYRevXrhwIEDOHjwYKvnxowZg5kzZ6KioqJNnVxcXPDCCy8AAL799ts2A/sFCxZg0KBByMzMRFJSUqvnhg4dirvuugsNDQ3ttvXFF1+ERqPBDz/8gHPnzrV6btasWRg9ejROnjyJH374odVzYWFheOCBByAIQrv7ffrpp+Ht7Y1ffvkFJ06caPXctGnTMHnyZJw7dw5ff/11q+cCAwOxdOlSAMBnn33W5g+0eYZn//79OHLkSKvn+vTpg6FDh6KsrAybNm1q9ZyHhweeffZZAGj3Jrr33nsv+vfvj4yMDOzbt6/Vc8uGDMWeht7IOn0e1ZmJ2NS6W9HfiP9ji78RAwYMwD333NOpvxGxsbEYN24c8vPzER8f3+o5+hvxP/bwN+LPA6rrYfUM05/fQCRJgl6vx9q1a9GrV682HdsZmGeY8vLy4OXlZXmcZpha2NOnR7PrmWGiT48tHOHT4+U6O8ME/O/3u7m5WZYZJjM3NzdwHIct8T/jh7NAdbMKLhoVHojug7+MCEFoaAgA+htBfyNa0N+IFnL+jairq8OgQYPsY+FKjuMQGBiIadOm4b333nPKY/TmAVNVVRX8/PxsXR2iMEEQkJ+fjwEDBkCtVtu6OkRhSudtXlZgzt334+3kcuw/3fKGdUNfHd6ZN7LNuk1EWdS/2VJdXQ2dTtd1h+Rqa2stL0RXihEW/PnTM3FuXZF3oJcbti0ah88PFWHl7lwcPFOF2PdT8PJfhuCvY2iV8K5E/Zt0RoeuqfTz87NMt02bNq3NFCQr6NMIG9RqNSIjIylvRnRl3hzH4b4bwvDTU5MxJswP9U08/v7fY3ho82GU1cp3rgW5MurfbJEz5w4NmLp162Y5rv/777+3OdbOCme8Tx5pSxAE5OTkUN6MsEXefQI8sf3RCfjHjMFwUavwW95FxKxOxvdHS9qce0XkRf2bLXLm3KFDcrfccgumTp2KIUOGAGi5esPFxaXdbf98Fj0hhLDM09MTN9xwAzw9W6/6rVZxWDylH24aFIQV32Qh50Itln2ViT05pfjX7AjoPNv/G0sIsY0OnfTd2NiILVu2oKCgAO+99x4eeeQReHi0f6Li6tWrZa+krdHClYQQJZkEER/+dhprk06DFyUEdHNB3NwRuHVod1tXjRCHZtOFK6dOnYr4+PhWCzg6O7pKji2CICA7OxsjRoyg8xwYoHTezc3NKCsrQ/fu3a84M2927HwNVnyThfzyluUJ5kX1xCuzhsLbTSt7vVhF/Zstcl4lZ/WNdH777TemBkuETe7u7rauAulCSuZdWVmJTZs2tVnfqT3De/rghycn4dEpfcFxwHcZ53Hb6mTsz2+7/hDpPOrfpDPozoNWoE8jbFCr1Rg8eDDlzQh7y9tNq8YLM4bg20cnIMzfAyU1Rvzt00N4eWcOLjXz194BuSp7y5soq8uvkiMt/rwCKnFOPM/j8OHDlDcj7DXvMX10+OmpybjvhjAAwLaD5zDzg/3ILKq+xneSq7HXvIky5MyZBkxWoIXl2MBxHPz8/ChvRthz3h4uGvxrdgS2LRqHYB83FFY0YN5HB7Bq7ymYBFpEuDPsOW8iPzlzpgGTFWgKlw1qtRr9+/envBmhdN4qlQoeHh5tbitljckDAvHzU1Nwx6gQCKKED37Nx53r01Bwsf7a30xaof7NFjlz7tBVctnZ2R3e4YgRI66rQl2psLAQDz30EMrKyqBWq3Hw4ME2a6UA/7tKrrKyEjqdzgY1JV2J53mkp6dj3Lhx0Gg6tFQZcWCOlvf3R0vwUvwx1Bp5uGlVeCF2CO6fEEYzJh3kaHmT61NVVQV/f/+uW1ZApVKB47grrkBrfo7jOIdaPfXGG2/EG2+8gcmTJ6Oqqgre3t7tdiDzgKm6upquEGSAKIooLi5Gr169rmtWgDgGR8y7tMaIZ787ipT/u3pu8oAAvHvXSHT3drNxzeyfI+ZNOs9gMMDPz6/rBkznzp3r8A7DwsKuq0Jd5fjx43jqqafwyy+/XHNbWriSENJZ5eXl+Prrr7FgwQIEBQXJtl9RlLD1wFnE/XQSTbwIH3ct3pwTgb+MCJHtNQhxdHK+f3doeB0WFtbhL7kkJydj1qxZCAkJAcdx2LlzZ5tt1q1bh/DwcLi5uSEqKgopKSkd3n9+fj66deuG22+/HaNHj8bKlSuv+T10VQUbeJ5HcnIy5c0IpfMWBAHV1dWyz76rVBwemBiO3csmY3ioD2oaTXjiy0ws/zoTNY1s3u+zI6h/s0XOnDt9APfEiRMoKipCc3Nzq8dvv/32664UADQ0NGDkyJF48MEHceedd7Z5fvv27Vi+fDnWrVuHiRMn4uOPP0ZsbCxOnDiB3r17AwCioqLQ1NTU5nsTExNhMpmQkpKCrKwsBAUF4bbbbsPYsWNx6623XrFONH3LBpVKhX79+lHejHD0vPsHdcOOpdH4z6/5WPvbaezMKsGhwiq8d9dIRPcPsHX17I6j502sI2fOVg+Yzpw5gzlz5uDYsWOtzmsyn3Ao16eo2NhYxMbGXvH5VatWYdGiRXj44YcBAGvWrMGePXuwfv16xMXFAQAyMjKu+P09e/bE2LFj0atXLwDAjBkzkJWVddUBU01NDVQqlaWNHh4elnOe1Go1eJ4Hx3GWskqlgkqlumLZZDJBrVZbyhqNBhzHWcpAy+j48rJWq4UkSZayKIoQBMFSFkURGo3mimVBECBJkqVsrvuVyqy2qXv3/93Dy1na5Iw5ydEmjuMQFBQElUqlaJvMr6lUm56+dSAm9dfhuf/m4GzlJdyz8RAWTQrHM7cOgEYFh89Jrt89SZLQo0ePVn/LHb1NzphTZ9tkMpnQ0NBgaYfBYIBcrB56PfXUUwgPD0dZWRk8PDxw/PhxJCcnY8yYMfj9999lq9jVNDc3IyMjAzExMa0ej4mJQVpaWof2MXbsWJSVlaG6uhqiKCI5ORlDhgy56vf06dMHPj4+0Ol00Ol0iIuLQ3Z2NvLz8wEAmZmZKCwsBACkp6ejuLgYAJCWlga9Xg+g5VBjRUXLiZpJSUmWMBMTE1FXVwcASEhIgNFoBM/zSEhIAM/zMBqNSEhIAADU1dUhMTERQMsJbUlJSQCAiooKJCcnAwD0er3lZ1FcXIz09HQALVcGZmZmAmg5LGm+AjI3Nxe5ubkAwHybeJ7HTz/9hLKyMqdpkzPmJFebDAaD5XEl2mRuT1e0SX8sDbuXTcZdkT0AAJ/uL8TMD1KwedevDp+TXL97eXl52LNnD3ied5o2OWNOnW1TXFwc/P394efnBx8fH4SHh0M2kpX8/f2lo0ePSpIkSd7e3tLJkyclSZKkX3/9VRo1apS1u+sQAFJ8fLzl/xcuXJAASKmpqa22e/PNN6WBAwd2eL8JCQlSRESENGzYMOnpp5++4nY1NTUSAKmwsFCqqamRqqqqpKqqKsloNEo8z0s8z0uSJEkmk6lVWRCEq5abm5tblUVRbFUWRbFNWZKkVmVBEFqVTSbTVcs8z7cqm+t7pTKLbRIEQSopKbHs0xna5Iw5ydUmnuelCxcuWLKXu00NDQ1SXl6eZDQauzSnPccuSFH/2iuF/f1Hqf8/dktrk/KlZhPvsDnJ9bvX3NwslZSUSIIgOE2bnDGnzrbJaDRKlZWVUnV1tVRTUyOdOXNGAiDV1NRI16tDV8ldzs/PDxkZGejbty/69euHjRs3YurUqSgoKMDw4cNx6dIl+UZz/4fjOMTHx2P27NkAgJKSEoSGhiItLQ0TJkywbPfmm29i27ZtOHnypKyvT1fJEUIcUWV9E/4Rfwx7jrfMlo4J88Oqv45Cb38PG9eMkK7R5VfJXS4iIsIyTTZ+/Hi8/fbbSE1Nxeuvv46+ffteV2U6KiAgAGq1GqWlpa0eLy8vb3XuidxMJrryhAUmkwl79uyhvBmhdN51dXX4/fffLYc0upJ/N1d89LcovHvXSHRz1eDIuWrEvp+M7YeLrriunrOj/s0WOXO2esD00ksvQRRb7mH0xhtv4Ny5c5g8eTISEhLwwQcfyFaxq3FxcUFUVBT27t3b6vG9e/ciOjpasdelpfTZoFarMXbsWMqbEUrnXV9fj3379qG+3ja3MeE4DvOieuKnpyZjXLgODc0C/v7fY3hk6xFcrGt7FbGzo/7NFjlztvoquenTp1vKffv2xYkTJ1BVVSX7zQzr6+tx+vRpy/8LCwuRlZUFnU6H3r17Y8WKFbjvvvswZswYTJgwARs2bEBRURGWLFkiWx3+jC5DZYNKpaJb4DCElbx76Tzw1SM34NP9Z/DunlP4JbccmWuS8dadI3DrUOVm5u0NK3mTFnK+b1u9py1btqChoaHVYzqdTvb7GB05cgSRkZGIjIwEAKxYsQKRkZF45ZVXAADz58/HmjVr8Prrr2PUqFFITk5GQkKCoiuN0xQuG0wmE3bv3k15M4KlvNUqDoun9MOuJyZicA8vVDY045GtR/DCjmw0NLGxkCNLeRN537etPuk7MDAQly5dwqxZs/C3v/0Nt912m9PfwNB80pjBYICPj4+tq0MUJkkS6urq4OXlRTc0ZYDSeev1emzYsAGLFy9GcHCw7PvvrCZewHuJp/BJyhlIEtDH3wOr549CZG8/W1dNUdS/2VJTUwNfX1/bnPSt1+uxfft2qNVqLFiwAMHBwVi6dGmH1z9yZNS52MBxHLy9vSlvRiidt5ubG4YPHw43N/u6Ma6rRo1/zBiCLx4ej2AfN5ytvIR5Hx3A+7/kgxdEW1dPMdS/2SJnzlYPmDQaDf7yl7/giy++QHl5OdasWYNz585h6tSp6Nevn2wVs0c0hcsGk8mEXbt2Ud6MUDpvPz8/zJ07F35+9jlzE90vAD8/NQWzRoZAECWs/uUU7vr4AM5VNlz7mx0Q9W+22PSQ3J9VVFTg66+/xkcffYTc3FzZbzBpD+iQHFskSYLRaISbmxt9CmWA0nnzPI/a2lp4e3vb/ekLu7Iu4KWdOagz8vBwUeOfs4bir2N6OVU/oP7NFpsekgOAS5cu4YsvvsCMGTMQEhKC1atXY/bs2cjJybmuyhBiL+z9jY3IS8m8L168iP/85z+4ePGiYq8hlztGheKnpyZjfLgOl/5v+YFHt2WgqqH52t/sQKh/k86wesB09913IygoCE8//TTCw8Px+++/o6CgAG+88cY178Xm6HiejatIWHf5PZKI86O8W+vp54EvH7kBz8cOhlbNIfFEGaavScbveeW2rposKG+2yJmz1cNsjuOwfft2TJ8+nblROmvtZZVGo8GMGTMob0ZQ3m2pVRyW3NgPk/oHYPn2LJwur8cDnx3GwglheD52CNxdHHfRR8qbLXLmbPUM05dffomZM2fSLxtxavTpky2Ud/siQn3w45OT8EB0HwDAlgPnMGvtfuRcqLFtxa4T5U06o0Ojng8++ACLFy+Gm5vbNW9/smzZMlkqZo+ok7GB53kkJiZixowZ0Gq1tq4OURjlfXVuWjVevX0Ypg4OwjPfHsXp8nrMWZeKFbcOwuIpfaFWOdaJ05Q3W+R83+7QVXLh4eE4cuQI/P39ER4efuWdcRzOnDkjW+XshZx3OyaEEEdV1dCMF3ZkY8/xMgDAuHAdVv11JHr6edi4ZoS0T8737+teVoAFtKwAW2glYLZQ3taRJAnfZpzHa98fR0OzAC9XDV6fPQyzR4U6xM+P8maLTZcV2Ldv33W9oCOjQ3Js4HkeKSkplDcjlM67oqICn376KSoqKhTZf1fjOA5/HdMLCU9Nxujevqhr4vH09qN48qtM1Fyy/8UgqX+zpcsPyV3OxcUFPXr0wD333IN7770Xw4cPl60y9ooOyRFCOste7yUnB14Qse73Arz/az4EUUKwjxveu2skovsH2LpqhACQ9/3b6hmmkpISPPfcc0hJScHIkSMxYsQIvP322zh//vx1VcQRiKLz3l+J/I8oiqiqqqK8GUF5d55GrcKymwfgv49FIzzAE/oaI+7ZeAhv7j6BJt4+7/pAebNFzpytHjAFBATgiSeeQGpqKgoKCjB//nxs3boVffr0wbRp02SrmD1yxtu+kLYEQcDhw4cpb0ZQ3tdvVC9f7F42CfeM7w0A+CSlEHesTcXJ0lob16wtypstcuZ83Sd9C4KAn376CS+//DKys7Od8peQDskRQjrLmQ/JteeXE2X4+3+zUdnQDBeNCn+/bTAejO4DlYMtP0Ccg00PyZmlpqZi6dKlCA4Oxj333INhw4bhxx9/vK7K2DuawmWDKIooLy+nvBmhdN6+vr6YM2cOfH19Fdm/vbllaHf8vHwKpg0OQjMv4l8/nsB9mw5BX9No66oBoP7NGpseknvhhRcQHh6OadOm4dy5c1izZg1KS0vx+eefIzY2VraK2SPqYGwQRRE5OTmUNyOUztvd3R0jRoyAu7u7Ivu3R4Fervh04Ri8MTsCbloVUk9X4rY1Kdidrbd11ah/M0bOnK0+JBcdHY17770X8+fPR0AAG1dC0CE5QkhnNTQ04Pjx4xg2bBg8PT1tXZ0uV3CxHsu/zsKx/7udytzRoXjt9mHwcqNVtonybHZIzmQyYdCgQYiNjWVmsHQ5+kTCBlEUceHCBcqbEUrnXVtbi59++gm1tfZ3AnRX6BfYDTuWRuOJqf2h4oAdf1xA7PspSC+sskl9qH+zxWaH5LRaLeLj42V7cUdDHYwNoiiioKCA8mYE5a08rVqFZ6YPwjePTkAvnTvOVzdiwYYDeGfPSTTzXftzp7zZYtNzmObMmYOdO3fKVgFHotF06F7FxMFpNBpMmTKF8mYE5d11xvTRIWHZZMyL6glRAj78rQB3rk/D6fL6LqsD5c0WOXO2ek/9+/fHv/71L6SlpSEqKqrNMflly5bJVjl7Q59I2CCKIoqLi9GrVy+oVJ2+kJQ4CMq7a3m5afHuXSMxbXAQXthxDMcu1OAv/0nBizOH4m/jeyt+fzfKmy1yvm9bPWDauHEjfH19kZGRgYyMjFbPcRxHAybi8MznOISGhtIfVAYonbeLiwv69esHFxcX2fftyGYMD8bo3n545tuj2H+6Ai/vzEFSbhn+PW8EgrzcFHtd6t9sselVcs4iLy8P8+fPb/X/r776CrNnz26zLV0lRwghyhBFCZvTzuKtn1vOZ9J5uuCtucMRM6yHratGnICc79/MDpguV19fjz59+uDcuXPtXvZr/oFXVVXBz8/PBjUkXUkQBBQWFiI8PBxqtdrW1SEKUzpvURRhMpmg1WppRuMq8krr8NTXmThZWgcAuHtcL7w0cyg8XeU914j6N1uqq6uh0+lkGTBZ/Zv40EMPXfX5TZs2dboytvL999/j5ptvvuYaKTS2ZIMkSaiurkafPn1sXRXSBZTOu6ysjKlbo3TWoB5e2PXERLyXeAqfpJzBV+nFOHimCmvmj8LIXr6yvQ71b7bI+b5t9ced6urqVl/l5eVISkrCjh07YDAYZKtYcnIyZs2ahZCQEHAc1+6VeevWrUN4eDjc3NwQFRWFlJSUTr3WN9980+rw3JXQVRVs0Gg0GDt2LOXNCMrbfrhq1PjHjCH44uHxCPZxQ2FFA+5cn4a1SfkQRHne+Chvttj0Krn21mESRRFLly5F3759ZakU0LI67siRI/Hggw/izjvvbPP89u3bsXz5cqxbtw4TJ07Exx9/jNjYWJw4cQK9e7fcMTsqKgpNTU1tvjcxMREhISEAWg63paam4uuvv75mnZzxxsKkLUEQkJ+fjwEDBtCUPQMob/sT3S8APz81Bf+IP4bdx/R4N/EU9p26iFV/HYVeOo/r2jflzRY537dlOaCuUqnw9NNPY/Xq1XLsDgAQGxuLN954A3Pnzm33+VWrVmHRokV4+OGHMWTIEKxZswa9evXC+vXrLdtkZGQgJyenzZd5sAQAu3btwvTp0+Hmdu2rMgwGA2pray2za01NTRAEwRIIz/Otyuaz869UNplMrcrmqUNzWZKkNmUArcrm8yPMZZ7nr1oWBKFV2VzfK5VZbVNDQ4PTtckZc5KrTQ0NDYq2yYxy6nibvN01+M/do/DvucPg6aLG4bPViH0/BTszL1x3m8x528PvnqPnZG9tampqQlVVVav3a7nIdgZiQUGBpaFKa25uRkZGBmJiYlo9HhMTg7S0NKv21dHDcQDQt29f+Pj4QKfTQafTIS4uDtnZ2cjPzwcAZGZmorCwEACQnp6O4uJiAEBaWhr0+pabTiYnJ6OiogIAkJSUZDmMmZiYiLq6lpMdExISYDQawfM8EhISwPM8jEYjEhISAAB1dXVITEwE0DKIS0pKAgBUVFQgOTkZAKDX6y0/i+LiYqSnpwMACgsLkZmZCQDIz89HdnY2ACA3Nxe5ubkAwHyb1Go1ampqLB3NGdrkjDnJ1aZLly6htLQUarVakTaZ20M5Wd+mpqYmuOmP4qenpmBkqBfqm3gs356FpdvS8eOeXzvVpjNnzkClUkGtVtv8d89ZcrKnNsXFxcHf3x9+fn7w8fFBv379IBerr5JbsWJFq/9LkgS9Xo/du3dj4cKFWLt2rWyVM+M4DvHx8ZZL/ktKShAaGorU1FRER0dbtlu5ciW2bNmCvLy8Du23pqYGAwcORHFx8VXXSDFfJXfmzBn4+/tbRrQeHh6W46NqtRo8z4PjOEtZpVJBpVJdsWwymaBWqy1ljUYDjuMsZaBl1Hx5WavVQpIkS1kURQiCYCmLogiNRnPFsiAIkCTJUjbX/UplFtskSRKOHz+OIUOGQKvVOkWbnDEnudrE8zxOnDiBYcOGgeM42dvU3NwMo9EIT09PSJJEOXWyTSZewH+S8vHh72cgiBJCfNywev4ojO3jZ1WbmpubcfLkSQwbNszyN576k/O0yWQyoaGhwdKOiooK9OvXzzZXyZlHf2YqlQqBgYF47733rnkFndz+vCKs+Y9RR/n4+KCsrKzD2/v6+l71B375yWUdKWu12k6VOY6zlM2/FB0tX37MviNlFtskCEKr/TtDm/5cpja1bpM17bC2TS4uLu1+IKOcrCtrNWqsiBmMmwZ3x/Kvs1BUdQkLPjmIJTf2w9O3DLSqTddqK/Unx22Tq6srXF1dLY/LeQ6T1QOm3377TbYX76yAgACo1WqUlpa2ery8vBzdu3dX7HXpBEE2qNVqRERE2LoapIsonXdVVRX27NmD6dOnQ6fTKfY6rBjd2w8JT03Ga98fx7cZ57H+9wLsz6/AmgWj0C+w2zW/n/o3W+R837b6HKbGxkZcunTJ8v9z585hzZo1lmOWXcHFxQVRUVHYu3dvq8f37t3b6hCd3OgqOTYIgoDMzEzKmxFK593U1IRTp061e8Uu6Zxurhq8c9dIrLt3NHzctS33o/tgP744dO6a6+5Q/2aLTa+Su+OOO7B161YALSd0jRs3Du+99x7uuOOOVleoXa/6+npkZWUhKysLQMvJYFlZWSgqKgLQci7Vxo0bsWnTJuTm5uLpp59GUVERlixZIlsdCLvc3d1tXQXShShvxzRjeDB+Xj4ZE/v7o9Ek4MX4HDyyNQOV9VcfnFLepDOsHjD98ccfmDx5MgDgu+++Q48ePXDu3Dls3boVH3zwgWwVO3LkCCIjIxEZGQmgZYAUGRmJV155BQAwf/58rFmzBq+//jpGjRqF5ORkJCQkICwsTLY6/BkdkmODWq3G4MGDKW9GUN6OLdjHHdseGo8XZwyBi1qFX3LLMH1NCn7PK293e8qbLTY9JHfp0iV4eXkBaLnUcO7cuVCpVLjhhhtw7tw52Sp20003WdZ3uPxr8+bNlm2WLl2Ks2fPoqmpCRkZGZgyZYpsr9+erlo2gdgWz/M4fPgw5c0IytvxqVQcHpnSFzsfn4gBQd1QUd+EBz47jFe/Pw6jqfUhGcqbLXLmbPWAqX///ti5cyeKi4uxZ88ey1pI5eXl133Jnr2z5go84rg4joOfnx/lzQil8/by8kJMTIzlgyZRztAQb/zw5CQ8EN0HALA57SxuX7sfJ0pqLdtQ/2aLnDlbvQ7Td999h3vuuQeCIODmm2+2nOwdFxeH5ORk/PTTT7JVzl6Y12GSYx0HQgghyvstrxzPfpuNivomuKhVeO62QXhoYjhUKhoosUTO92+rB0wAUFpaCr1ej5EjR1rWT0hPT4e3tzcGDx58XRWyR+YfeGVlJV0WzACe55Geno5x48bRDToZoHTejY2NOHPmDPr27UsnG3exivomPP/fbPyS23I+06T+AXhr7jAUncym/s2Iqqoq+Pv7yzJg6tStUXr06IHIyEjLYAkAxo0b55SDpctd3l7ivFQqFUJDQylvRiidt8FgwHfffWe5zQTpOgHdXPHJ/WPw5pwIuGlV2H+6An/5TxpOG7tR/2aEnDnTb4wVqIOxQaVSISwsjPJmBOXt3DiOw73jw/Djk5MREeoNQ6MJryQW4/kdx9DQRCd+OzsaMNkIXVXBBp7nkZycTHkzgvJmQ/+gbtjx2EQ8OiUcHIBvjpzHjA9SkFkk393sif2x6VVyLKNPoGxQqVTo168f5c0IypsdLhoV/n7bYPxnbn8E+7jhXOUlzPvoAN7/JR+8INq6ekQBNMNkI/QHlQ10DhNblM5bo9GgR48edIKxnVCpVPjLuEH4efkUzBoZAkGUsPqXU5i/4SCKqy5dewfEodCAyUZoyp4NPM8jKSmJ8maE0nkHBgbi0UcfRWBgoCL7J9Yx5+2p5fDBglFYPX8kvFw1yDhXjdj3U/DfjPPXvB8dcRx0SM5GaMaBDSqVChEREZQ3IyhvtlyeN8dxmBPZEwlPTcbYPn6ob+Lx/749iie+ykTNJZOtq0pkQDNMNkJ/UNmgUqkQFBREeTNC6bz1ej3eeOMN6PV6RfZPrNNe3r10Hvh68QQ8EzMQahWH3dl63PZ+MtIKKmxYUyIHGjDZiMlEnzhYYDKZsGfPHsqbEV2RtyAI196IdIkr5a1WcXhi2gD897Fo9PH3gL7GiHs3HkLcT7lo5umEcEclZ7+mAZMV6O7WbFCr1Rg7dizlzQjKmy3XyntUL1/sXjYZC8b2giQBH+87gznrUnG6vK6La0rkIGe/pgGTFegQDRtUKhV0Oh3lzQjKmy0dydvTVYO37hyBj/4WBT8PLY6X1OIv/9mPbQfO0gnhDoYOydkIHaJhg8lkwu7duylvRlDebLEm79sieuDn5VMweUAAjCYRL+86jkVbjqCivqkLakrkIGe/7tTNd1ljvvmuwWCAj4+PratDFCZJEurq6uDl5QWOozubOzul8zaZTKiuroafnx+0Wq3s+yfW6Uzeoijhs7Sz+PdPJ9EsiAjo5oJ35o3E1MFBCteWXK+amhr4+vrKcvNdGjB1gHnAJMcPnBBCiGPK1ddi+ddZyCtrOZ/pvhvC8I8ZQ+DuQue/2Ss537/pkJwVaMqeDSaTCbt27aK8GaF03gaDAd9//z0MBoMi+yfWuZ68hwR7Y9cTE/HgxD4AgG0Hz2HW2v04XlIjcy2JXOgqORuhWxuwQaPRICYmhvJmhNJ5NzY2IjMzE42NjYrsn1jnevN206rxz1nDsPWhcQj0csXp8nrM/jAVH+8rgCjSARt7I2e/pgETIe2gwRJbKG+2yJH3lIGB2LN8CmKGdodJkBD300ncu/EQSgw0MHZWNGCyAt1bjA08zyMhIYHyZgTlzRY589Z5uuDj+6Lw1tzhcNeqceBMJW5bk4zd2bSqu72ge8nZCH0KZYNGo8GMGTMob0ZQ3myRO2+O47BgXG/sXjYJI3r6oNbI4/Ev/8D/++Yo6ox0HqSt0SE5QhRGsw1sUTJvT09PTJw4EZ6enoq9BrGOEnn3DeyG/z4WjSem9oeKA/77x3nM+CAFGeeqZH8tYhtMD5hWr16NYcOGYejQoVi2bNk1V3ClN1E28DyPxMREypsRSuft7e2NW265hZYksRNK5q1Vq/DM9EH4evEEhPq6o7iqEXd9dACr954CL9D96GxBzpyZXYfp4sWLuOGGG3D8+HFotVpMmTIF7777LiZMmNBmW1qHiRDSWU1NTdDr9QgODoarq6utq0O6SK3RhFd25mBnVgkAILK3L9bMH4Uwf5pp7Eq0DpNMeJ6H0WiEyWSCyWRCUNDVV21ldGzJHEmSUFtbS3kzQum8q6qqsGXLFlRV0aEZe9BV/dvbTYs1CyLx/oJR8HLTILPIgBnvp+DbI8X0t6ULyfmzttsBU3JyMmbNmoWQkBBwHIedO3e22WbdunUIDw+Hm5sboqKikJKS0uH9BwYG4plnnkHv3r0REhKCW265Bf369bvq99AhGjbwPI+UlBTKmxGUN1u6Ou87RoXip6cmY1y4Dg3NAp79LhtPfJWJmkt0QnhXYOIquYaGBowcORJr165t9/nt27dj+fLlePHFF5GZmYnJkycjNjYWRUVFlm2ioqIQERHR5qukpATV1dX48ccfcfbsWVy4cAFpaWlITk6+ap3oPlBs0Gq1mDlzJuXNCMqbLbbIu6efB7565AY8O30QNCoOu7P1uO39ZBw8U9lldWCVnDnb7YApNjYWb7zxBubOndvu86tWrcKiRYvw8MMPY8iQIVizZg169eqF9evXW7bJyMhATk5Om6+QkBD88ssv6N+/P3Q6Hdzd3TFz5kwcPHjwqnWqqqpCbW0tqqurUV1djaamJgiCAEEQALSMZC8vi6J41bLJZGpVNk8dmsuSJLUpA2hVFkWxVdk8mr5SWRCEVmVzfa9UZrFNoiji4sWLln06Q5ucMSe52iQIAsrLyy3ZK9EmM8rJ9m0ymUy4ePEiRFHs0jaJAo+lN/XDt0smIEznAX2NEXd/chBvJZyASVDud89Rc+psm5qamlBVVQWDwYDa2lpUVso3KLXbAdPVNDc3IyMjAzExMa0ej4mJQVpaWof20atXL6SlpcFoNEIQBPz+++8YNGjQVb8nPDwcPj4+0Ol00Ol0iIuLQ3Z2NvLz8wEAmZmZKCwsBACkp6ejuLgYAJCWlga9vmUhs+TkZFRUVAAAkpKSLPeXSkxMRF1dyw0dExISYDQaWy2wZjQakZCQAACoq6tDYmIigJb7VCUlJQEAKioqLLNker3e8rMoLi5Geno6AKCwsBCZmZkAgPz8fGRnZwMAcnNzkZubCwDMt0kQBBw4cADl5eVO0yZnzEmuNtXU1ODAgQMQBEGRNhUUFMDd3R0qlYpysoM2nTp1CocOHYIgCDZp0+BANzzevxZ/HdMTkgR8lFyIO9enIfuMnnKSoU1xcXHw9/eHn58ffHx80LdvX8jFIa6S4zgO8fHxmD17NgCgpKQEoaGhSE1NRXR0tGW7lStXYsuWLcjLy+vQfl988UXs2LEDKpUKN998M95//31wHNdmO/NZ9mfPnoWfn59lROvh4WFZFEutVoPneXAcZymrVCqoVKorlk0mE9RqtaWs0WjAcZylDLSMmi8va7VaSJJkKZs/JZnLoihCo9FcsSwIAiRJspTNdb9SmdpEbaI2UZuoTcq0aXd2Cf4Rfww1jTw8XNR4acYg3D2+T8uMlIO2ydY5mUwmNDQ0WNpRVVWF8PBwWa6Sc+gBU1paWqtlAN58801s27YNJ0+elPX1zQOm6upq+Pr6yrpvYn9EUURFRQUCAgKgUjnkJCyxAuXNFnvLu8TQiBXfZOHgmZarKGMjeiBu7nD4erjYuGbOwWAwwM/Pj91lBQICAqBWq1FaWtrq8fLycnTv3l2x1zUfzyXOTRRF5OTkUN6MUDrvsrIyrFq1CmVlZYrsn1jH3vp3iK87vnj4BjwfOxgaFYefckpx25oUpJ2usHXVnIKcOTvkgMnFxQVRUVHYu3dvq8f37t3b6hCd3OheU2zQaDSYNm0a5c0IpfMWRRF1dXV28wbNOnvs32oVhyU39kP80onoG+CJ0loj7v30EOJ+ykUzT78314OJe8nV19cjKysLWVlZAFpOBsvKyrIsG7BixQps3LgRmzZtQm5uLp5++mkUFRVhyZIlitWJ/uCxQRRFXLhwgfJmBOXNFnvOe3hPH/y4bBLuHtcLkgR8vO8M5q5PRcHFeltXzWExMcN05MgRREZGIjIyEkDLACkyMhKvvPIKAGD+/PlYs2YNXn/9dYwaNQrJyclISEhAWFiYYnWyxw5G5CeKIgoKCihvRlDebLH3vD1cNIibOwIf/S0Kvh5a5FyoxcwPUvDloSJaIbwT5MzZIU76tjW6lxwhpLP0ej02bNiAxYsXIzg42NbVIQ6ktMaI//dtFlJPt6wlFDO0O966cwR0nnRCeEfRveRsxF4/kRB5iaKIc+fOUd6MUDpvnU6HhQsXQqfTKbJ/Yh1H6t89fNyw7aHxeHHGEGjVHBJPlOG2NcnYn08nhHcUE4fk7JEjdDBy/ez5HAciP6XzdnV1RZ8+feDq6qrI/ol1HK1/q1QcHpnSF/FLJ6JfoCfK65rwt08P4c3dJ9DEC9feAePokFwXo0NyhJDOqq2tRXp6OsaNG0d/P8h1aWwW8MbuE/jiUMvFT0ODvfHB3aPQP8jLxjWzX3RIzkYuvycUcV6CIOD06dOUNyOUzruhoQGpqaloaGhQZP/EOo7cv91d1HhzznB8cv8Y6DxdcEJfi5kf7Me2g+fohPArkDNnGjBZgX4h2SBJEqqrqylvRlDebHGGvG8d2h0/PzUZkwcEoIkX8fLOHDyy9Qgq65tsXTW7I2fONGCygj0tdEaUo9FoMHbsWMqbEZQ3W5wl7yBvN2x5cBxe/stQuKhV+CW3HLe9n4LkUxdtXTW7wsTClfbIEadwifUEQcDJkycpb0ZQ3mxxprxVKg6LJoVj5+MTMSCoGy7WNeH+Tel4/YcTMJocv31yoENyhCissbHR1lUgXUjJvN3d3REZGQl3d3fFXoNYx9n699AQb/zw5CQsnNCycPOm1ELM/jAVp8rqbFwz50JXyXUAXSVHCCHEESSdLMOz32ajsqEZrhoV/jFjCO6fEAaO42xdNZugq+RsxBmmcMm1CYKAnJwcypsRSudtMplQXl4Ok8mkyP6JdZy9f08b3B0/L5+CmwYFookX8c/vj+OhzYdRwegJ4XRIjhBCHERFRQXWr1+PigpanZl0jUAvV3z2wFj8c9ZQuGhU+C3vIm5bk4zf8sptXTWHRgMmK6jValtXgXQBtVqNiIgIypsRlDdbWMmb4zg8ODEc3z8xEYO6e6GivhkPfnYYr35/nKkTwuXMmQZMVnDWKVzSmiAIyMzMpLwZQXmzhbW8B/fwxq4nJuKB6D4AgM1pZ3HH2lScLK21bcW6CB2SI0RhdEUTWyhvtrCWt5tWjVdvH4bPHhyLgG6uyCurw+1rU7Fpf6FDL+DZ1WjAZAVnn8IlLdRqNQYPHkx5M6Ir8qbfJfvBcv+eOigIPy+fjGmDg9DMi3j9xxN44LPDKK8z2rpqiqFDcjbC87ytq0C6AM/zOHz4MOXNCKXzDg4OxksvvYTg4GBF9k+sw3r/Dujmik8XjsG/7hgGV40K+05dROyaFPyaW2brqilCzpxpwGQFVtexYA3HcfDz86O8GUF5s4XybvkZ3DehD354chIG9/BCZUMzFm05gpd35qCx2bnO7ZIzZ1q4sgNo4UpCSGddvHgRO3bswNy5cxEYGGjr6hDSShMv4O2f8/Dp/kIAQP+gbvhgQSSGhjjHex0tXGkjrE7hsobneaSlpVHejFA6b57nUVpaSr9PdoL6d2uuGjVe/stQbH1oHAK9XHG6vB6zP0zFxpQzEEXHn0+hQ3I2olLRj4sFKpUKoaGhlDcjKG+2UN7tmzIwED8/NRm3DOmOZkHEG7tzsfCzdJTVOvYJ4XLmTL8xVqAOxgaVSoWwsDDKmxGUN1so7yvz7+aKT+6PwptzIuCmVSElvwK3rUlG4vFSW1et02jAZCM0hcsGnueRnJxMeTOC8mYL5X11HMfh3vFh+PHJSRga7I3qSyYs3paBf8Qfc8gTwumQnI3QJxI2qFQq9OvXj/JmhNJ5+/r6Yt68efD19VVk/8Q61L87pn+QF+Ifj8biKX0BAF8eKsLM/6Qg50KNjWtmHZphksm7776LYcOGISIiAp9//vk1t6cOxgY6x4EtSuft7u6OYcOGMbe6tL2i/t1xrho1/jFjCD5fNB7dvV1x5mID5qxLxYbkAoc5IZwGTDI4duwYvvzyS2RkZODIkSNYv349DAbDVb+HpnDZwPM8kpKSKG9GKJ13fX09Dhw4gPr6ekX2T6xD/dt6kwYE4OenpmD6sO4wCRJWJpzE3z49hNIa+z8hnA7JySA3NxfR0dFwc3ODm5sbRo0ahZ9//vmq30OfSNigUqkQERFBeTNC6bzr6uqQmJiIuro6RfZPrEP9u3P8PF3w0d+i8Nbc4XDXqpFWUInb3k/Gzzn2fUI4EzNMycnJmDVrFkJCQsBxHHbu3Nlmm3Xr1iE8PBxubm6IiopCSkpKh/cfERGB3377DQaDAQaDAUlJSbhw4cJVv4c6GBtUKhWCgoIob0ZQ3myhvDuP4zgsGNcbPy6bhOGhPjBcMmHJ5xl4/r/ZuNRsnzN2TAyYGhoaMHLkSKxdu7bd57dv347ly5fjxRdfRGZmJiZPnozY2FgUFRVZtomKikJERESbr5KSEgwdOhTLli3DtGnTMGfOHIwdOxYajeaqdTKZTLK2kdgnk8mEPXv2UN6MoLzZQnlfv36B3fDfx6Kx5MZ+4Djg68PF+MsH+5F93mDrqrUhZ84OcWsUjuMQHx+P2bNnWx4bP348Ro8ejfXr11seGzJkCGbPno24uDirX+Phhx/GnDlzMHPmzDbPmZdWLywshE6ngyC0XFrp4eFhGWSp1WrwPA+O4yxllUoFlUp1xbLJZIJarbaUNRoNOI6zlIGW46+Xl7VaLSRJspRFUYQgCJayKIrQaDRXLAuCAEmSLGVz3a9UZrFNAFBZWQk/Pz9oNBqnaJMz5iRXmwRBQGVlJQICAgBA9jadP38en376KRYvXozAwEDKycZtMplMMBgM8Pf3h/ntz9HbZMucDp+rwYpvjqK01giNisP/ixmIhyb0hquri03aZDKZ0NDQYGlHZWUl+vbty+6tUZqbm5GRkYGYmJhWj8fExCAtLa3D+ykvLwcA5OXlIT09HdOnT7/q9uHh4fDx8YFOp4NOp0NcXByys7ORn58PAMjMzERhYcv9eNLT01FcXAwASEtLg16vB9ByqLGiogIAkJSUZDnR/PJzHBISEmA0GsHzPBISEsDzPIxGIxISEgD875wIAJbDiQBQUVGB5ORkAIBer7f8LIqLi5Geng4AKCwsRGZmJgAgPz8f2dnZAFrO6crNzQUA5tukUqlw7NgxVFVVOU2bnDEnudrU0NCAw4cPQ6VSKdKms2fPIiQkBK6urpSTHbSpoKAA58+fh0qlcpo22TKnsWE+iF8yFiN1InhRwr9/zsOsVXtRWmO0SZvi4uLg7+8PPz8/+Pj4oG/flmUR5OCQM0wlJSUIDQ1FamoqoqOjLdutXLkSW7ZsQV5eXof2Gx0dDYPBAE9PT3z00UeIiopqdzvzDNPp06cRGBhIM0xO3iZBELBnzx7ceuutcHV1dYo2OWNOcrWpubkZiYmJmD59uqUOjt4mZ8xJrjYZjUb88ssvmD59umVG2dHbZA85mUwmxB8txavfn0CjSYCfhxZvzR2OaYMCbDrDVF5ejgEDBsgyw+TQA6a0tDRMmDDBst2bb76Jbdu24eTJk7K+vnnAZDAY4OPjI+u+if2RJAl1dXXw8vICx3G2rg5RmNJ5C4IAo9EINzc3qNVq2fdPrEP9W1kFF+vx1NeZyLlQCwC4d3xvvDRzKNxdbPO7X1NTA19fX3YPyQUEBECtVqO0tPXljOXl5ejevbtir0udiw0cx8Hb25vyZoTSeZeXl+Pdd9+1nAJAbIv6t7L6BXbDjscm4tH/WyH8i0NFmLV2P06U1NqkPnLm7JADJhcXF0RFRWHv3r2tHt+7d2+rQ3Ryo6sq2GAymbBr1y7KmxGUN1sob+W5aFR4YcYQbFs0DkFerjhdXo/ZH6bi0/2FXb5CuJw52+2Aqb6+HllZWcjKygLQcjJYVlaWZdmAFStWYOPGjdi0aRNyc3Px9NNPo6ioCEuWLFGsTuZjtcS5aTQaxMTEUN6MoLzZQnl3nckDAvHTU5Nxy5AgNAsi/vXjCTy4+TAu1jV1WR3kzNluf2OOHDmCqVOnWv6/YsUKAMDChQuxefNmzJ8/H5WVlXj99deh1+sRERGBhIQEhIWF2arKxInQH1O2UN5soby7jn83V3xy/xh8fvAc3tidi32nLiL2/WS8M28kpg4OsnX1rGK3M0w33XQTJElq87V582bLNkuXLsXZs2fR1NSEjIwMTJkyRdE68bx9rmRK5HX5JcDE+VHebKG8ux7HcbhvQh/88OQkDO7hhYr6Zjy4+TBe++E4jCZB0deWM2eHuErO1ugqObaYL/U1X0ZLnJvSeYuiCJPJBK1Wa7mMndgO9W/bMpoEvPXTSWxOOwsAGNzDCx/cHYmB3b0UeT3mr5IjRGn06ZMtSuatUqng6upKgyU7Qv3bdty0arx6+zB89sBY+Hu64GRpHWb9Zz+2HTwHe5+/oR5sBepkbOB5HomJiZQ3I5TOu7KyEp9//jkqKysV2T+xDvVv+zB1cBB+Wj4ZUwYGookX8fLOHDyyNQNVDc2yvg4dkuti5kNyckzpEULYotfrsWHDBixevBjBwcG2rg4hdkUUJXyWdhb//ukkmgURQV6uWPXXUZg0IECW/cv5/k0zTFagsSUbJElCbW0t5c0IypstlLd9Uak4LJoUjvjHo9E/qBvK65rwt08PIS4hF828eN37lzNnGjBZgaZw2cDzPFJSUihvRlDebKG87dOwEB/88MQk3Du+NwDg4+QzuHN9Gs5crL+u/cqZMw2YrKDVam1dBdIFtFotZs6cSXkzgvJmC+Vtv9xd1HhzznB8fF8UfD20OHahBjM/2I/th4s6PVMkZ840YLKCKF7/9CCxf6IooqqqivJmhNJ5e3t7IzY2ls5/tBPUv+3f9GE98PNTUzChrz8aTQL+/t9jePzLP1BzyfrbnMiZMw2YrCAIyi6wReyDIAg4fPgw5c0IpfP29PTEuHHj4Onpqcj+iXWofzuGHj5u+Pzh8fj7bYOhUXFIOFaK2PeTceiMdVebypkzXSXXAXSVHCGksxobG5Gfn48BAwbA3d3d1tUhxOEcLTbgqa8zcbbyEjgOePym/njqlgHQqq8950NXydkITeGyQRRFlJeXU96MUDpvg8GA+Ph4GAwGRfZPrEP92/GM7OWL3csm466onpAkYO1vp3HXRwdQVHnpmt9Lh+RshDoYG0RRRE5ODuXNCMqbLZS3Y/J01eCdu0Zi7T2R8HLTIKvYgBkfpCA+8/xVv48GTDZCd7hmg0ajwbRp0yhvRlDebKG8HdtfRoTgp6cmY2wfP9Q38Xh6+1Es/zoTtcb2TwiXM2caMFmBPpGwQRRFXLhwgfJmBOXNFsrb8fX088BXj9yAFbcOhFrFYWdWCWa8n4KMc9VttqUZJhuhDsYGURRRUFBAeTNC6by1Wi169uxJ6/7YCerfzkGjVmHZzQPwzaMT0NPPHeerG/HXjw/gg1/zIYj/u5ZNzpzpKrkOoKvkCCGEEPtUazTh5Z052JVVAgAY28cPaxZEItTXna6SsxX6RMIGURRx7tw5ypsRlDdbKG/n4+2mxfsLIrF6/kh0c9Xg8Nlq3LYmGT9ml9AhOVuhDsYGOseBLUrnrdfr8dprr0Gv1yuyf2Id6t/Oa05kT+xeNgmjevmizsjjiS8z8fLOHNn2TwMmK9BVFWzQaDSIjo6mvBlBebOF8nZuYf6e+HbJBDwxtT84Dth1VL4PKjRgsgItpc8GQRBw+vRpypsRlDdbKG/np1Wr8Mz0QfjqkRsQ5O0q235pwGQFOj+eDZIkobq6mvJmBOXNFsqbHTf09ce3j4yTbX80J2kFmsJlg0ajwdixY21dDdJFKG+2UN5s8ff2kG1fNMNkBZrCZYMgCDh58iTlzQil8w4MDMSTTz6JwMBARfZPrEP9my1y5szEgGnOnDnw8/PDvHnz2jz3448/YtCgQRgwYAA2btxog9oRe9TY2GjrKpAupGTeGo0GOp2OZqjtCPVv0hlMDJiWLVuGrVu3tnmc53msWLECSUlJ+OOPP/Dvf/8bVVVVbbZramqybE+cH8/z2LVrF+XNCKXzrq6uxo4dO1Bd3fa2DaTrUf9mizln8/v49WBiwDR16lR4eXm1eTw9PR3Dhg1DaGgovLy8MGPGDOzZs6fNduYf9KVLlxSvK7G9S5cu4bXXXqO8GaF03kajEceOHYPRaFRk/8Q61L/ZYs7ZKQZMycnJmDVrFkJCQsBxHHbu3Nlmm3Xr1iE8PBxubm6IiopCSkqKLK9dUlKC0NBQy/979uyJCxcuyLJvQgghhDgPmw+YGhoaMHLkSKxdu7bd57dv347ly5fjxRdfRGZmJiZPnozY2FgUFRVZtomKikJERESbr5KSkqu+dnuXlXIcd8Xt1Wp1B1tFHJk5Z8qbDZQ3WyhvtsiZs83PQoyNjUVsbOwVn1+1ahUWLVqEhx9+GACwZs0a7NmzB+vXr0dcXBwAICMjo1OvHRoa2mpG6fz58xg/fnyb7cwDK/MgzXzWvYeHh+VETrVaDZ7nwXGcpaxSqaBSqa5YNplMUKvVlrJGowHHcZYy0HL89fKyVquFJEmWsiiKEATBUhZFERqN5oplQRAgSZKlbK77lcostqmmpgaurq6W89mcoU3OmJNcbaqqqoKbmxuqq6sVaZPBYIDRaERdXR1cXV0pJxu3qaqqClqtFtXV1U7TJmfMqbNtMplMaGhosLTD/L4tx7pbNh8wXU1zczMyMjLw/PPPt3o8JiYGaWlp173/cePGIScnBxcuXIC3tzcSEhLwyiuvtNnOZDIBACZOnHjdr0kcR3h4uK2rQLpQnz59FN3/W2+9pej+iXWUzpvYF/P7+PWw6wFTRUUFBEFA9+7dWz3evXt3lJaWdng/06dPxx9//IGGhgb07NkT8fHxGDt2LDQaDd577z1MnToVoijiueeeg7+/f5vv79OnDwoKCqDValsdsnN1dYWrq3zLrhNCCCGk85qamlqd4C1JEkwmkywDZLseMJn9+bwiSZKueq7Rn7V35ZvZ7bffjttvv/2q369SqdC3b98Ovx4hhBBCnIvNT/q+moCAAKjV6jazSeXl5W1mnQghhBBClGLXAyYXFxdERUVh7969rR7fu3cvoqOjbVQrQgghhLDG5ofk6uvrcfr0acv/CwsLkZWVBZ1Oh969e2PFihW47777MGbMGEyYMAEbNmxAUVERlixZYsNaE0IIIYQlNp9hOnLkCCIjIxEZGQkAWLFiBSIjIy1Xq82fPx9r1qzB66+/jlGjRiE5ORkJCQkICwvrkvoptWgmsT+vvvoqOI5r9dWjRw9bV4vI5FqL5EqShFdffRUhISFwd3fHTTfdhOPHj9umsuS6XSvvBx54oE1/v+GGG2xTWXJd4uLiMHbsWHh5eSEoKAizZ89GXl5eq23k6N82HzDddNNNkCSpzdfmzZst2yxduhRnz55FU1MTMjIyMGXKlC6pW0cWzSTOZdiwYdDr9ZavY8eO2bpKRCbXWiT37bffxqpVq7B27VocPnwYPXr0wK233oq6urourimRw7XyBoDbbrutVX9PSEjowhoSuezbtw+PP/44Dh48iL1794LnecTExKChocGyjSz9WyJXNG7cOGnJkiWtHhs8eLD0/PPP26hGREn//Oc/pZEjR9q6GqQLAJDi4+Mt/xdFUerRo4f01ltvWR4zGo2Sj4+P9NFHH9mghkROf85bkiRp4cKF0h133GGT+hBllZeXSwCkffv2SZIkX/+2+QyTvTIvmhkTE9PqcbkWzST2KT8/HyEhIQgPD8eCBQtw5swZW1eJdIHCwkKUlpa26u+urq648cYbqb87sd9//x1BQUEYOHAgHnnkEZSXl9u6SkQGNTU1AACdTgdAvv5NA6YrkGvRTOI4xo8fj61bt2LPnj345JNPUFpaiujoaFRWVtq6akRh5j5N/Z0dsbGx+OKLL5CUlIT33nsPhw8fxrRp02S5qz2xHUmSsGLFCkyaNAkREREA5OvfNr9Kzt5d76KZxHFcfk/D4cOHY8KECejXrx+2bNmCFStW2LBmpKtQf2fH/PnzLeWIiAiMGTMGYWFh2L17N+bOnWvDmpHr8cQTTyA7Oxv79+9v89z19m+aYboCWjSTeHp6Yvjw4cjPz7d1VYjCzFdDUn9nV3BwMMLCwqi/O7Ann3wS33//PX777Tf07NnT8rhc/ZsGTFdAi2aSpqYm5ObmIjg42NZVIQoLDw9Hjx49WvX35uZm7Nu3j/o7IyorK1FcXEz93QFJkoQnnngCO3bsQFJSUpsbp8vVv+mQ3FXQoplseeaZZzBr1iz07t0b5eXleOONN1BbW4uFCxfaumpEBtdaJHf58uVYuXIlBgwYgAEDBmDlypXw8PDAPffcY8Nak866Wt46nQ6vvvoq7rzzTgQHB+Ps2bP4xz/+gYCAAMyZM8eGtSad8fjjj+PLL7/Erl274OXlZZlJ8vHxgbu7OziOk6d/y3kpnzP68P+3d/chTW5xHMC/j7GmNtNefM2XVWpkNF/IMKyJkA0MooQoM1kQvcdAVEqyJoZIklTErX/CRSESVEZSCSIqyjIiEWUJiRkqBb1gTFMx3bl/eH24S71LnXqx7wcEn3N+53fOHhF+nOds++svERISIpYuXSpiYmLktynS4nPgwAHh7+8vFAqFCAgIECkpKcJisSz0sshJampqBIAJP3q9Xggx9tZjo9Eo/Pz8hFKpFFqtVrS2ti7somnG/uvvPTAwIHbt2iW8vb2FQqEQwcHBQq/Xi66uroVeNs3AZH9nAMJkMskxzvj/lv6ZjIiIiIimwDNMRERERA6wYCIiIiJygAUTERERkQMsmIiIiIgcYMFERERE5AALJiIiIiIHWDAREREROcCCiYiIiMgBFkxENG9qa2shSRK+f/++0EtBXl4eoqKi5nweSZIgSRK8vLxmnUutVsv5/g/3kOhPwoKJiBY9SZLw5MkTu7asrCxUV1fPy/wmkwnv3r2bdZ7Xr1/j0aNHTlgREU0Xv3yXiP5IKpUKKpVqXuby8vKCj4/PrPN4e3tj5cqVTlgREU0Xd5iIyGmEECgqKsK6devg5uaGyMhIPHz48D/HmM1maLVauLm5ISgoCAaDAT9+/AAA5OTkIC4ubsIYjUYDo9EIYGzXJSkpCatXr4anpycSEhLQ1NQkx6rVagDAvn37IEmSfP3rIzmbzYb8/HwEBgZCqVQiKioKlZWVcv+HDx8gSRIeP36MxMREuLu7IzIyEi9fvpz2fRqfu6SkBMHBwVCpVDh16hRGR0dRVFQEPz8/+Pj4oKCgYNq5iWhusGAiIqfJzc2FyWTC7du3YbFYkJGRgcOHD6Ourm7S+NbWVuh0OqSkpKClpQUPHjxAQ0MDzp49CwBIS0vDq1ev0NHRIY+xWCxobW1FWloaAKCvrw96vR719fVobGxEWFgYkpOT0dfXB2CsoALGHot9+vRJvv7VjRs3UFxcjKtXr6KlpQU6nQ579uxBe3u7XdyFCxeQlZWF5uZmhIeHIzU1FSMjI9O+Vx0dHXjx4gUqKytRVlaGkpIS7N69Gz09Pairq8OVK1eQm5uLxsbGaecmojkgiIicoL+/X7i6ugqz2WzXfvToUZGamiqEEKKmpkYAEL29vUIIIdLT08Xx48ft4uvr64WLi4sYHBwUQgih0WhEfn6+3J+TkyNiY2OnXMfIyIjw8PAQFRUVchsAUV5ebhdnNBpFZGSkfB0QECAKCgrsYmJjY8Xp06eFEEJ0dnYKAOLOnTtyv8ViEQBEW1vblOuZam53d3dhtVrlNp1OJ9RqtRgdHZXbNmzYIAoLC+3G/noPiWh+cIeJiJzi7du3GBoaQlJSknw+SKVS4d69e3Y7RP/25s0b3L171y5ep9PBZrOhs7MTwNguU2lpKYCxR35lZWXy7hIAfP78GSdPnkR4eDg8PT3h6emJ/v5+dHV1/fbarVYrPn78iPj4eLv2+Ph4tLW12bVpNBr5d39/f3kN06VWq+Hh4SFf+/r6IiIiAi4uLnZtM8lNRM7HQ99E5BQ2mw0A8OzZM6xZs8auT6lUTjnmxIkTMBgME/qCg4MBAIcOHcL58+fR1NSEwcFBdHd34+DBg3LckSNH8OXLF1y/fh0hISFQKpXYtm0bhoeHp/0aJEmyuxZCTGhTKBQT4sdf+3T8O894rsnaZpKbiJyPBRMROUVERASUSiW6urqQkJDwW2NiYmJgsVgQGho6ZUxgYCC0Wi1KS0sxODiInTt3wtfXV+6vr6/HrVu3kJycDADo7u7G169f7XIoFAqMjo5OOcfy5csREBCAhoYGaLVaud1sNmPr1q2/9VqIaHFjwURETuHh4YGsrCxkZGTAZrNh+/btsFqtMJvNUKlU0Ov1E8acO3cOcXFxOHPmDI4dO4Zly5ahra0NVVVVuHnzphyXlpaGvLw8DA8P49q1a3Y5QkNDcf/+fWzZsgVWqxXZ2dlwc3Ozi1Gr1aiurkZ8fDyUSiVWrFgxYS3Z2dkwGo1Yv349oqKiYDKZ0NzcLD8OJKI/G88wEZHTXL58GZcuXUJhYSE2btwInU6HiooKrF27dtJ4jUaDuro6tLe3Y8eOHYiOjsbFixfls0Hj9u/fj2/fvmFgYAB79+616yspKUFvby+io6ORnp4Og8Ew4TOPiouLUVVVhaCgIERHR0+6FoPBgMzMTGRmZmLz5s2orKzE06dPERYWNvMbQkSLhiSEEAu9CCKixUqSJJSXl08o9GaqtrYWiYmJ6O3tdcrXrRDR72HBREQ0hyRJgqurK1atWoWenp5Z5dq0aRPev3+PoaEhFkxE84xnmIiI5tD4B18uWbJk1rmeP3+Onz9/Ahg7qE5E84c7TEREREQO8NA3ERERkQMsmIiIiIgcYMFERERE5AALJiIiIiIHWDAREREROcCCiYiIiMgBFkxEREREDrBgIiIiInLgb+JJ5xezTCxxAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -563,7 +563,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "work",
    "language": "python",
    "name": "python3"
   },
@@ -577,7 +577,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.4"
+   "version": "3.11.10"
   }
  },
  "nbformat": 4,
diff --git a/mhkit/__init__.py b/mhkit/__init__.py
index bbdb6cef2..6f9eefeec 100644
--- a/mhkit/__init__.py
+++ b/mhkit/__init__.py
@@ -14,7 +14,7 @@
 __version__ = "v1.0.1"
 
 __copyright__ = """
-Copyright 2019, Alliance for Sustainable Energy, LLC under the terms of 
+Copyright 2019, Alliance for Energy Innovation, LLC under the terms of 
 Contract DE-AC36-08GO28308, Battelle Memorial Institute under the terms of 
 Contract DE-AC05-76RL01830, and National Technology & Engineering Solutions of 
 Sandia, LLC under the terms of Contract DE-NA0003525. The U.S. Government 
diff --git a/mhkit/acoustics/analysis.py b/mhkit/acoustics/analysis.py
index 145757fdb..7c297ee88 100644
--- a/mhkit/acoustics/analysis.py
+++ b/mhkit/acoustics/analysis.py
@@ -50,6 +50,17 @@
 from mhkit.dolfyn.time import epoch2dt64, dt642epoch
 
 
+def _check_numeric(value, name: str):
+    if np.issubdtype(type(value), np.ndarray):
+        value = value.item()
+    if not (
+        isinstance(value, (int, float))
+        or np.issubdtype(type(value), np.integer)
+        or np.issubdtype(type(value), np.floating)
+    ):
+        raise TypeError(f"{name} must be a numeric type (int or float).")
+
+
 def _fmax_warning(
     fn: Union[int, float, np.ndarray], fmax: Union[int, float, np.ndarray]
 ) -> Union[int, float, np.ndarray]:
@@ -69,11 +80,6 @@ def _fmax_warning(
         The adjusted maximum frequency limit, ensuring it does not exceed the Nyquist frequency.
     """
 
-    if not isinstance(fn, (int, float, np.ndarray)):
-        raise TypeError("'fn' must be a numeric type (int or float).")
-    if not isinstance(fmax, (int, float, np.ndarray)):
-        raise TypeError("'fmax' must be a numeric type (int or float).")
-
     if fmax > fn:
         warnings.warn(
             f"`fmax` = {fmax} is greater than the Nyquist frequency. Setting"
@@ -120,10 +126,8 @@ def minimum_frequency(
     if not np.issubdtype(water_depth.dtype, np.number):
         raise TypeError("'water_depth' must be a numeric type or array of numerics.")
 
-    if not isinstance(c, (int, float)):
-        raise TypeError("'c' must be a numeric type (int or float).")
-    if not isinstance(c_seabed, (int, float)):
-        raise TypeError("'c_seabed' must be a numeric type (int or float).")
+    _check_numeric(c, "c")
+    _check_numeric(c_seabed, "c_seabed")
 
     if np.any(water_depth <= 0):
         raise ValueError("All elements of 'water_depth' must be positive numbers.")
@@ -143,6 +147,7 @@ def sound_pressure_spectral_density(
     pressure: xr.DataArray,
     fs: Union[int, float],
     bin_length: Union[int, float] = 1,
+    fft_length: Optional[Union[int, float]] = None,
     rms: bool = True,
 ) -> xr.DataArray:
     """
@@ -167,6 +172,8 @@ def sound_pressure_spectral_density(
         Data collection sampling rate [Hz]
     bin_length: int or float
         Length of time in seconds to create FFTs. Default: 1.
+    fft_length: int or float, optional
+        Length of FFT to use. If None, uses bin_length * fs. Default: None.
     rms: bool
         If True, calculates the mean-squared SPSD. Set to False to
         calculate standard SPSD. Default: True.
@@ -180,10 +187,8 @@ def sound_pressure_spectral_density(
     # Type checks
     if not isinstance(pressure, xr.DataArray):
         raise TypeError("'pressure' must be an xarray.DataArray.")
-    if not isinstance(fs, (int, float)):
-        raise TypeError("'fs' must be a numeric type (int or float).")
-    if not isinstance(bin_length, (int, float)):
-        raise TypeError("'bin_length' must be a numeric type (int or float).")
+    _check_numeric(fs, "fs")
+    _check_numeric(bin_length, "bin_length")
 
     # Ensure that 'pressure' has a 'time' coordinate
     if "time" not in pressure.dims:
@@ -191,9 +196,14 @@ def sound_pressure_spectral_density(
 
     # window length of each time series
     nbin = bin_length * fs
+    if fft_length is not None:
+        _check_numeric(fft_length, "fft_length")
+        nfft = fft_length
+    else:
+        nfft = nbin
 
     # Use dolfyn PSD functionality
-    binner = VelBinner(n_bin=nbin, fs=fs, n_fft=nbin)
+    binner = VelBinner(n_bin=nbin, fs=fs, n_fft=nfft)
     # Always 50% overlap if numbers reshape perfectly
     # Mean square sound pressure
     psd = binner.power_spectral_density(pressure, freq_units="Hz")
@@ -221,9 +231,9 @@ def sound_pressure_spectral_density(
             "units": pressure.units + "^2/Hz",
             "long_name": long_name,
             "fs": fs,
-            "nbin": str(bin_length) + " s",
+            "bin_length": bin_length,
             "overlap": "50%",
-            "nfft": nbin,
+            "n_fft": nfft,
         },
     )
 
@@ -234,6 +244,7 @@ def apply_calibration(
     spsd: xr.DataArray,
     sensitivity_curve: xr.DataArray,
     fill_value: Union[float, int, np.ndarray],
+    interp_method: str = "linear",
 ) -> xr.DataArray:
     """
     Applies custom calibration to spectral density values.
@@ -248,6 +259,9 @@ def apply_calibration(
     fill_value: float or int
         Value with which to fill missing values from the calibration curve,
         in units of dB rel 1 V^2/uPa^2.
+    interp_method: str
+        Interpolation method to use when interpolating the calibration curve
+        to the frequencies in 'spsd'. Default is 'linear'.
 
     Returns
     -------
@@ -259,8 +273,7 @@ def apply_calibration(
         raise TypeError("'spsd' must be an xarray.DataArray.")
     if not isinstance(sensitivity_curve, xr.DataArray):
         raise TypeError("'sensitivity_curve' must be an xarray.DataArray.")
-    if not isinstance(fill_value, (int, float, np.ndarray)):
-        raise TypeError("'fill_value' must be a numeric type (int or float).")
+    _check_numeric(fill_value, "fill_value")
 
     # Ensure 'freq' dimension exists in 'spsd'
     if "freq" not in spsd.dims:
@@ -295,7 +308,7 @@ def apply_calibration(
     freq = sensitivity_curve.dims[0]
     # Interpolate calibration curve to desired value
     calibration = sensitivity_curve.interp(
-        {freq: spsd_calibrated["freq"]}, method="linear"
+        {freq: spsd_calibrated["freq"]}, method=interp_method
     )
     # Fill missing with provided value
     calibration = calibration.fillna(fill_value)
@@ -340,6 +353,7 @@ def sound_pressure_spectral_density_level(spsd: xr.DataArray) -> xr.DataArray:
         attrs={
             "units": "dB re 1 uPa^2/Hz",
             "long_name": "Sound Pressure Spectral Density Level",
+            "time_resolution": spsd.attrs["bin_length"],
         },
     )
 
@@ -571,8 +585,8 @@ def band_aggregate(
     for val in octave:
         if not isinstance(val, int) or (val <= 0):
             raise TypeError("'octave' must contain positive integers.")
-    if not isinstance(fmin, int) or (fmin <= 0):
-        raise TypeError("'fmin' must be a positive integer.")
+    _check_numeric(fmin, "fmin")
+    _check_numeric(fmax, "fmax")
     if fmax <= fmin:  # also checks that fmax is positive
         raise ValueError("'fmax' must be greater than 'fmin'.")
 
diff --git a/mhkit/acoustics/graphics.py b/mhkit/acoustics/graphics.py
index fb61361f0..17fb9e946 100644
--- a/mhkit/acoustics/graphics.py
+++ b/mhkit/acoustics/graphics.py
@@ -24,7 +24,7 @@
 import xarray as xr
 import matplotlib.pyplot as plt
 
-from .analysis import _fmax_warning
+from .analysis import _fmax_warning, _check_numeric
 
 
 def plot_spectrogram(
@@ -61,8 +61,9 @@ def plot_spectrogram(
         Figure plot axis
     """
 
-    if not isinstance(fmin, (int, float)) or not isinstance(fmax, (int, float)):
-        raise TypeError("fmin and fmax must be numeric types.")
+    # Type checks
+    _check_numeric(fmin, "fmin")
+    _check_numeric(fmax, "fmax")
     if fmin >= fmax:
         raise ValueError("fmin must be less than fmax.")
 
@@ -128,8 +129,8 @@ def plot_spectra(
         Figure plot axis
     """
 
-    if not isinstance(fmin, (int, float)) or not isinstance(fmax, (int, float)):
-        raise TypeError("fmin and fmax must be numeric types.")
+    _check_numeric(fmin, "fmin")
+    _check_numeric(fmax, "fmax")
     if fmin >= fmax:
         raise ValueError("fmin must be less than fmax.")
 
diff --git a/mhkit/acoustics/io.py b/mhkit/acoustics/io.py
index c1743b0ed..8ba1ef98a 100644
--- a/mhkit/acoustics/io.py
+++ b/mhkit/acoustics/io.py
@@ -49,6 +49,8 @@
 import xarray as xr
 from scipy.io import wavfile
 
+from mhkit.acoustics.analysis import _check_numeric
+
 
 def _read_wav_metadata(f: BinaryIO) -> dict:
     """
@@ -132,10 +134,9 @@ def _calculate_voltage_and_time(
         raise TypeError("Raw audio data 'raw' must be a numpy.ndarray.")
     if not isinstance(bits_per_sample, int):
         raise TypeError("'bits_per_sample' must be an integer.")
-    if not isinstance(peak_voltage, (int, float)):
-        raise TypeError("'peak_voltage' must be numeric (int or float).")
     if not isinstance(start_time, (str, np.datetime64)):
         raise TypeError("'start_time' must be a string or np.datetime64.")
+    _check_numeric(peak_voltage, "peak_voltage")
 
     length = raw.shape[0] // fs  # length of recording in seconds
 
@@ -156,7 +157,7 @@ def _calculate_voltage_and_time(
     raw_voltage = raw.astype(float) / max_count * peak_voltage
 
     # Get time
-    end_time = np.datetime64(start_time) + np.timedelta64(length * 1000, "ms")
+    end_time = np.datetime64(start_time) + np.timedelta64(length * 1000000000, "ns")
     time = pd.date_range(start_time, end_time, raw.size + 1)
 
     return raw_voltage, time, max_count
@@ -196,15 +197,12 @@ def read_hydrophone(
 
     if not isinstance(filename, (str, Path)):
         raise TypeError("Filename must be a string or a pathlib.Path object.")
-    if not isinstance(peak_voltage, (int, float)):
-        raise TypeError("'peak_voltage' must be numeric (int or float).")
-    if sensitivity is not None and not isinstance(sensitivity, (int, float)):
-        raise TypeError("'sensitivity' must be numeric (int, float) or None.")
-    if not isinstance(gain, (int, float)):
-        raise TypeError("'gain' must be numeric (int or float).")
+    if sensitivity is not None:
+        _check_numeric(sensitivity, "sensitivity")
+    _check_numeric(peak_voltage, "peak_voltage")
+    _check_numeric(gain, "gain")
     if not isinstance(start_time, (str, np.datetime64)):
         raise TypeError("'start_time' must be a string or np.datetime64")
-
     if (sensitivity is not None) and (sensitivity > 0):
         raise ValueError(
             "Hydrophone calibrated sensitivity should be entered as a negative number."
@@ -225,9 +223,9 @@ def read_hydrophone(
     # If sensitivity is provided, convert to sound pressure
     if sensitivity is not None:
         # Subtract gain
-        # Hydrophone with sensitivity of -177 dB and gain of -3 dB = sensitivity of -174 dB
+        # Hydrophone with sensitivity of -177 dB and gain of 3 dB = sensitivity of -174 dB
         if gain:
-            sensitivity -= gain
+            sensitivity += gain
         # Convert calibration from dB rel 1 V/uPa into ratio
         sensitivity = 10 ** (sensitivity / 20)  # V/uPa
 
@@ -511,25 +509,22 @@ def export_audio(
     -------
     None
     """
+
     if not isinstance(filename, str):
         raise TypeError("'filename' must be a string.")
-
     if not isinstance(pressure, xr.DataArray):
         raise TypeError("'pressure' must be an xarray.DataArray.")
-
     if not hasattr(pressure, "values") or not isinstance(pressure.values, np.ndarray):
         raise TypeError("'pressure.values' must be a numpy.ndarray.")
-
-    if not hasattr(pressure, "sensitivity") or not isinstance(
-        pressure.sensitivity, (int, float)
-    ):
-        raise TypeError("'pressure.sensitivity' must be a numeric type (int or float).")
-
-    if not hasattr(pressure, "fs") or not isinstance(pressure.fs, (int, float)):
-        raise TypeError("'pressure.fs' must be a numeric type (int or float).")
-
-    if not isinstance(gain, (int, float)):
-        raise TypeError("'gain' must be a numeric type (int or float).")
+    if hasattr(pressure, "sensitivity"):
+        _check_numeric(pressure.sensitivity, "pressure.sensitivity")
+    else:
+        raise AttributeError("'pressure' must have a 'sensitivity' attribute.")
+    if hasattr(pressure, "fs"):
+        _check_numeric(pressure.fs, "pressure.fs")
+    else:
+        raise AttributeError("'pressure' must have a 'fs' attribute.")
+    _check_numeric(gain, "gain")
 
     # Convert from Pascals to UPa
     upa = pressure.values.T * 1e6
diff --git a/mhkit/acoustics/sel.py b/mhkit/acoustics/sel.py
index 781db3876..9083dc163 100644
--- a/mhkit/acoustics/sel.py
+++ b/mhkit/acoustics/sel.py
@@ -134,9 +134,7 @@ def sound_exposure_level(
     exposure = np.trapezoid(band * w, band["freq"])
 
     # Sound exposure level (L_{E,p}) = (L_{p,rms} + 10log10(t))
-    sel = 10 * np.log10(exposure / reference) + 10 * np.log10(
-        spsd.attrs["nfft"] / spsd.attrs["fs"]  # n_points / (n_points/s)
-    )
+    sel = 10 * np.log10(exposure / reference) + 10 * np.log10(spsd.attrs["bin_length"])
 
     out = xr.DataArray(
         sel.astype(np.float32),
@@ -145,7 +143,7 @@ def sound_exposure_level(
             "units": "dB re 1 uPa^2 s",
             "long_name": long_name,
             "weighting_group": group,
-            "integration_time": spsd.attrs["nbin"],
+            "integration_time": spsd.attrs["bin_length"],
             "freq_band_min": fmin,
             "freq_band_max": fmax,
         },
diff --git a/mhkit/acoustics/spl.py b/mhkit/acoustics/spl.py
index 2e9ef86a0..3be616c9b 100644
--- a/mhkit/acoustics/spl.py
+++ b/mhkit/acoustics/spl.py
@@ -19,7 +19,7 @@
 import numpy as np
 import xarray as xr
 
-from .analysis import _fmax_warning, _create_frequency_bands
+from .analysis import _check_numeric, _fmax_warning, _create_frequency_bands
 
 
 def _argument_check(spsd, fmin, fmax):
@@ -45,10 +45,8 @@ def _argument_check(spsd, fmin, fmax):
     # Type checks
     if not isinstance(spsd, xr.DataArray):
         raise TypeError("'spsd' must be an xarray.DataArray.")
-    if not isinstance(fmin, int):
-        raise TypeError("'fmin' must be an integer.")
-    if not isinstance(fmax, int):
-        raise TypeError("'fmax' must be an integer.")
+    _check_numeric(fmin, "fmin")
+    _check_numeric(fmax, "fmax")
 
     # Ensure 'freq' and 'time' dimensions are present
     if ("freq" not in spsd.dims) or ("time" not in spsd.dims):
@@ -59,9 +57,9 @@ def _argument_check(spsd, fmin, fmax):
         raise ValueError(
             "'spsd' must have 'fs' (sampling frequency) in its attributes."
         )
-    if "nfft" not in spsd.attrs:
+    if "n_fft" not in spsd.attrs:
         raise ValueError(
-            "'spsd' must have 'nfft' (sampling frequency) in its attributes."
+            "'spsd' must have 'n_fft' (number of points in each FFT) in its attributes."
         )
 
     # Value checks
@@ -119,6 +117,7 @@ def sound_pressure_level(
         attrs={
             "units": "dB re 1 uPa",
             "long_name": "Sound Pressure Level",
+            "time_resolution": spsd.attrs["bin_length"],
             "freq_band_min": fmin,
             "freq_band_max": fmax,
         },
@@ -235,6 +234,7 @@ def third_octave_sound_pressure_level(
         {
             "units": "dB re 1 uPa",
             "long_name": "Third Octave Sound Pressure Level",
+            "time_resolution": spsd.attrs["bin_length"],
         }
     )
 
@@ -272,6 +272,7 @@ def decidecade_sound_pressure_level(
         {
             "units": "dB re 1 uPa",
             "long_name": "Decidecade Sound Pressure Level",
+            "time_resolution": spsd.attrs["bin_length"],
         }
     )
 
diff --git a/mhkit/dolfyn/adp/turbulence.py b/mhkit/dolfyn/adp/turbulence.py
index 5002523ad..2707edae5 100644
--- a/mhkit/dolfyn/adp/turbulence.py
+++ b/mhkit/dolfyn/adp/turbulence.py
@@ -128,7 +128,7 @@ def __init__(
         self.diff_style = diff_style
         self.orientation = orientation
 
-    def _diff_func(self, vel, u, orientation):
+    def _diff_func(self, vel, u, orientation, tag):
         """Applies the chosen style of numerical differentiation to velocity data.
 
         This method calculates the derivative of the velocity data 'vel' with respect to the 'range'
@@ -156,16 +156,16 @@ def _diff_func(self, vel, u, orientation):
             sign *= -1
 
         if self.diff_style == "first":
-            out = _diffz_first(vel[u].values, vel["range"].values)
-            return sign * out, vel.range[1:]
+            out = _diffz_first(vel[u].values, vel["range" + tag].values)
+            return sign * out, vel["range" + tag][1:]
 
         elif self.diff_style == "centered":
-            out = _diffz_centered(vel[u].values, vel["range"].values)
-            return sign * out, vel.range[1:-1]
+            out = _diffz_centered(vel[u].values, vel["range" + tag].values)
+            return sign * out, vel["range" + tag][1:-1]
 
         elif self.diff_style == "centered_extended":
-            out = _diffz_centered_extended(vel[u].values, vel["range"].values)
-            return sign * out, vel.range
+            out = _diffz_centered_extended(vel[u].values, vel["range" + tag].values)
+            return sign * out, vel["range" + tag]
 
     def dudz(self, vel, orientation=None):
         """
@@ -191,11 +191,16 @@ def dudz(self, vel, orientation=None):
         'true vertical' direction.
         """
 
-        dudz, rng = self._diff_func(vel, 0, orientation)
+        if "_" in vel.name:
+            tag = "_" + vel.name.split("_")[-1]
+        else:
+            tag = ""
+
+        dudz, rng = self._diff_func(vel, 0, orientation, tag)
         return xr.DataArray(
             dudz,
-            coords=[rng, vel.time],
-            dims=["range", "time"],
+            coords=[rng, vel["time" + tag]],
+            dims=["range" + tag, "time" + tag],
             attrs={"units": "s-1", "long_name": "Shear in X-direction"},
         )
 
@@ -223,11 +228,16 @@ def dvdz(self, vel, orientation=None):
         'true vertical' direction.
         """
 
-        dvdz, rng = self._diff_func(vel, 1, orientation)
+        if "_" in vel.name:
+            tag = "_" + vel.name.split("_")[-1]
+        else:
+            tag = ""
+
+        dvdz, rng = self._diff_func(vel, 1, orientation, tag)
         return xr.DataArray(
             dvdz,
-            coords=[rng, vel.time],
-            dims=["range", "time"],
+            coords=[rng, vel["time" + tag]],
+            dims=["range" + tag, "time" + tag],
             attrs={"units": "s-1", "long_name": "Shear in Y-direction"},
         )
 
@@ -255,11 +265,16 @@ def dwdz(self, vel, orientation=None):
         'true vertical' direction.
         """
 
-        dwdz, rng = self._diff_func(vel, 2, orientation)
+        if "_" in vel.name:
+            tag = "_" + vel.name.split("_")[-1]
+        else:
+            tag = ""
+
+        dwdz, rng = self._diff_func(vel, 2, orientation, tag)
         return xr.DataArray(
             dwdz,
-            coords=[rng, vel.time],
-            dims=["range", "time"],
+            coords=[rng, vel["time" + tag]],
+            dims=["range" + tag, "time" + tag],
             attrs={"units": "s-1", "long_name": "Shear in Z-direction"},
         )
 
diff --git a/mhkit/dolfyn/adv/clean.py b/mhkit/dolfyn/adv/clean.py
index 95fba7430..09b5010b4 100644
--- a/mhkit/dolfyn/adv/clean.py
+++ b/mhkit/dolfyn/adv/clean.py
@@ -5,7 +5,6 @@
 from ..velocity import VelBinner
 from ..tools.misc import group, slice1d_along_axis
 
-
 sin = np.sin
 cos = np.cos
 
diff --git a/mhkit/dolfyn/binned.py b/mhkit/dolfyn/binned.py
index ef999e99c..2cc9e3f23 100644
--- a/mhkit/dolfyn/binned.py
+++ b/mhkit/dolfyn/binned.py
@@ -370,7 +370,6 @@ def _psd_base(
         noise=0,
         n_bin=None,
         n_fft=None,
-        n_pad=None,
         step=None,
     ):
         """
@@ -393,8 +392,6 @@ def _psd_base(
         n_fft : int
           n_fft of veldat2, number of elements per bin if 'None' is taken
           from VelBinner
-        n_pad : int (optional)
-          The number of values to pad with zero. Default = 0
         step : int (optional)
           Controls amount of overlap in fft. Default: the step size is
           chosen to maximize data use, minimize nens, and have a
@@ -413,11 +410,9 @@ def _psd_base(
         fs = self._parse_fs(fs)
         n_bin = self._parse_nbin(n_bin)
         n_fft = self._parse_nfft(n_fft)
-        if n_pad is None:
-            n_pad = min(n_bin - n_fft, n_fft)
         out = np.empty(self._outshape_fft(dat.shape, n_fft=n_fft, n_bin=n_bin))
         # The data is detrended in psd, so we don't need to do it here.
-        dat = self.reshape(dat, n_pad=n_pad)
+        dat = self.reshape(dat)
 
         for slc in slice1d_along_axis(dat.shape, -1):
             out[slc] = psd_1D(dat[slc], n_fft, fs, window=window, step=step)
@@ -474,8 +469,8 @@ def _csd_base(self, dat1, dat2, fs=None, window="hann", n_fft=None, n_bin=None):
         oshp[-2] = np.min([oshp[-2], int(dat2.shape[-1] // n_bin2)])
 
         # The data is detrended in psd, so we don't need to do it here:
-        dat1 = self.reshape(dat1, n_pad=n_fft)
-        dat2 = self.reshape(dat2, n_pad=n_fft)
+        dat1 = self.reshape(dat1)
+        dat2 = self.reshape(dat2)
         out = np.empty(oshp, dtype="c{}".format(dat1.dtype.itemsize * 2))
         if dat1.shape == dat2.shape:
             cross = cpsd_1D
@@ -517,10 +512,8 @@ def _fft_freq(self, fs=None, units="Hz", n_fft=None, coh=False):
         fs = self._parse_fs(fs)
 
         if ("Hz" not in units) and ("rad" not in units):
-            raise Exception(
-                "Valid fft frequency vector units are Hz \
-                            or rad/s"
-            )
+            raise Exception("Valid fft frequency vector units are Hz \
+                            or rad/s")
 
         if "rad" in units:
             return fft_frequency(n_fft, 2 * np.pi * fs)
diff --git a/mhkit/dolfyn/io/api.py b/mhkit/dolfyn/io/api.py
index 1b62bd60d..43f4c7332 100644
--- a/mhkit/dolfyn/io/api.py
+++ b/mhkit/dolfyn/io/api.py
@@ -399,9 +399,6 @@ def load_mat(filename, datenum=True):
         ]:
             ds.attrs[nm] = [ds.attrs[nm]]
 
-    if hasattr(ds, "orientation_down"):
-        ds["orientation_down"] = ds["orientation_down"].astype(bool)
-
     if datenum:
         func = matlab2date
     else:
diff --git a/mhkit/dolfyn/io/base.py b/mhkit/dolfyn/io/base.py
index 878ee1b98..6326f6e00 100644
--- a/mhkit/dolfyn/io/base.py
+++ b/mhkit/dolfyn/io/base.py
@@ -62,10 +62,8 @@ def _read_userdata(fname):
     for nm in ["body2head_rotmat", "body2head_vec"]:
         if nm in data:
             new_name = "inst" + nm[4:]
-            warnings.warn(
-                f"{nm} has been deprecated, please change this to {new_name} \
-                    in {fname}."
-            )
+            warnings.warn(f"{nm} has been deprecated, please change this to {new_name} \
+                    in {fname}.")
             data[new_name] = data.pop(nm)
     if "inst2head_rotmat" in data:
         if data["inst2head_rotmat"] in ["identity", "eye", 1, 1.0]:
diff --git a/mhkit/dolfyn/io/nortek.py b/mhkit/dolfyn/io/nortek.py
index 3510ef400..76d619143 100644
--- a/mhkit/dolfyn/io/nortek.py
+++ b/mhkit/dolfyn/io/nortek.py
@@ -4,7 +4,6 @@
 from struct import unpack
 from pathlib import Path
 
-
 from .. import time
 from . import base
 from . import nortek_defs as defs
@@ -97,12 +96,16 @@ def read_nortek(
     ds = _set_coords(ds, ref_frame=ds.coord_sys)
 
     if "orientmat" not in ds:
+        if "vector" in ds.attrs["inst_model"].lower():
+            orientation_down = ds.attrs["orientation_down"]
+        else:
+            orientation_down = None
         ds["orientmat"] = _calc_omat(
             ds["time"],
             ds["heading"],
             ds["pitch"],
             ds["roll"],
-            ds.get("orientation_down", None),
+            orientation_down,
         )
 
     if rotmat is not None:
@@ -144,18 +147,25 @@ class _NortekReader:
 
     _lastread = [None, None, None, None, None]
     fun_map = {
-        "0x00": "read_user_cfg",
-        "0x04": "read_head_cfg",
-        "0x05": "read_hw_cfg",
-        "0x07": "read_vec_checkdata",
-        "0x10": "read_vec_data",
-        "0x11": "read_vec_sysdata",
-        "0x12": "read_vec_hdr",
-        "0x20": "read_awac_profile",
-        "0x30": "read_awac_waves",
-        "0x31": "read_awac_waves_hdr",
-        "0x36": "read_awac_waves",  # "SUV"
-        "0x71": "read_imu",
+        "0x00": "read_user_cfg",  # User configuration
+        "0x01": "read_aqd",  # Aquadopp velocity
+        "0x04": "read_hdr_cfg",  # Header configuration
+        "0x05": "read_hdw_cfg",  # Hardware configuration
+        "0x06": "read_aqd_diag_hdr",  # Aquadopp diagnostics header
+        "0x07": "read_vec_check",  # Vector probe check
+        "0x10": "read_vec",  # Vector velocity
+        "0x11": "read_vec_sys",  # Vector system data
+        "0x12": "read_vec_hdr",  # Vector header
+        "0x20": "read_awac_profile",  # AWAC profile
+        "0x21": "read_aqd_profile",  # Aquadopp profiler velocity
+        "0x2a": "read_aqd_profile_hr",  # Aquadopp profiler high-res velocity
+        "0x30": "read_awac_waves",  # AWAC and Aquadopp waves
+        "0x31": "read_awac_waves_hdr",  # AWAC and Aquadopp waves header
+        "0x36": "read_awac_waves",  # AWAC waves + "SUV"
+        "0x42": "read_awac_stage",  # AWAC stage data (altimeter AST)
+        "0x71": "read_imu",  # Vector IMU
+        "0x80": "read_aqd",  # Aquadopp diagnostics
+        "0x81": "read_aqd_mag",  # Aquadopp with magnetometer
     }
 
     def __init__(
@@ -211,23 +221,24 @@ def __init__(
         err_msg = "I/O error: The file does not " "appear to be a Nortek data file."
         # Read the header:
         if self.read_id() == 5:
-            self.read_hw_cfg()
+            self.read_hdw_cfg()
         else:
             raise Exception()
         if self.read_id() == 4:
-            self.read_head_cfg()
+            self.read_hdr_cfg()
         else:
             raise Exception(err_msg)
         if self.read_id() == 0:
             self.read_user_cfg()
         else:
             raise Exception(err_msg)
+        # Initialize the instrument type:
         if self.config["hdw"]["serial_number"][0:3].upper() == "WPR":
-            self.config["config_type"] = "AWAC"
+            self._inst = "AWAC"
         elif self.config["hdw"]["serial_number"][0:3].upper() == "VEC":
-            self.config["config_type"] = "ADV"
-        # Initialize the instrument type:
-        self._inst = self.config.pop("config_type")
+            self._inst = "ADV"
+        elif self.config["hdw"]["serial_number"][0:3].upper() in ["AQD", "PRF"]:
+            self._inst = "AQD"  # Use AWAC configuration for Aquadopp
         # This is the position after reading the 'hardware',
         # 'head', and 'user' configuration.
         pnow = self.pos
@@ -243,12 +254,12 @@ def __init__(
         self.f.seek(pnow, 0)  # Seek to the previous position.
 
         da = self.data["attrs"]
-        if self.config["n_burst"] > 0:
+        if (self.config["adv"]["n_burst"] > 0) and ("ADV" in da["inst_type"]):
             fs = round(self.config["fs"], 7)
-            da["duty_cycle_n_burst"] = self.config["n_burst"]
+            da["duty_cycle_n_burst"] = self.config["adv"]["n_burst"]
             da["duty_cycle_interval"] = self.config["burst_interval"]
             if fs > 1:
-                burst_seconds = self.config["n_burst"] / fs
+                burst_seconds = self.config["adv"]["n_burst"] / fs
             else:
                 burst_seconds = round(1 / fs, 3)
             da["duty_cycle_description"] = (
@@ -256,6 +267,7 @@ def __init__(
                     burst_seconds, fs, self.config["burst_interval"] / 60
                 )
             )
+
         self.burst_start = np.zeros(self.n_samp_guess, dtype="bool")
         da["fs"] = self.config["fs"]
         da["coord_sys"] = {"XYZ": "inst", "ENU": "earth", "beam": "beam"}[
@@ -299,16 +311,13 @@ def init_ADV(self):
         da["inst_type"] = "ADV"
         da["rotate_vars"] = ["vel"]
         dv["beam2inst_orientmat"] = self.config.pop("beam2inst_orientmat")
-        self.config["fs"] = 512 / self.config["awac"]["avg_interval"]
+        self.config["fs"] = 512 / self.config["avg_interval"]
         da.update(self.config["usr"])
         da.update(self.config["adv"])
-        da.update(self.config["head"])
+        da.update(self.config["hdr"])
         da.update(self.config["hdw"])
-
         # No apparent way to determine how many samples are in a file
-        dlta = self.code_spacing("0x11")
-        self.n_samp_guess = int(self.filesize / dlta + 1)
-        self.n_samp_guess *= int(self.config["fs"])
+        self.ensemble_count()
 
     def init_AWAC(self):
         dat = self.data = {
@@ -327,18 +336,48 @@ def init_AWAC(self):
         da["inst_type"] = "ADCP"
         dv["beam2inst_orientmat"] = self.config.pop("beam2inst_orientmat")
         da["rotate_vars"] = ["vel"]
-        self.config["fs"] = 1.0 / self.config["awac"]["avg_interval"]
+        if self.config["avg_interval"] <= 1:
+            self.config["fs"] = 1 / (self.config["time_between_bursts"] / 512)
+        else:
+            self.config["fs"] = 1.0 / self.config["avg_interval"]
         da.update(self.config["usr"])
-        da.update(self.config["awac"])
-        da.update(self.config["head"])
+        da.update(self.config["adp"])
+        if self.config["adp"]["wave_mode"] == "Enabled":
+            da.update(self.config["waves"])
+        da.update(self.config["hdr"])
         da.update(self.config["hdw"])
+        # No apparent way to determine how many samples are in a file
+        self.ensemble_count()
 
-        space = self.code_spacing("0x20")
-        if space == 0:
-            # code spacing is zero if there's only 1 profile
-            self.n_samp_guess = 1
+    def init_AQD(self):
+        dat = self.data = {
+            "data_vars": {},
+            "coords": {},
+            "attrs": {},
+            "units": {},
+            "long_name": {},
+            "standard_name": {},
+            "sys": {},
+        }
+        da = dat["attrs"]
+        dv = dat["data_vars"]
+        da["inst_make"] = "Nortek"
+        da["inst_model"] = "Aquadopp"
+        da["inst_type"] = "ADCP"
+        dv["beam2inst_orientmat"] = self.config.pop("beam2inst_orientmat")
+        da["rotate_vars"] = ["vel"]
+        if self.config["avg_interval"] <= 1:
+            self.config["fs"] = 1 / (self.config["time_between_bursts"] / 512)
         else:
-            self.n_samp_guess = int(self.filesize / space + 1)
+            self.config["fs"] = 1.0 / self.config["avg_interval"]
+        da.update(self.config["usr"])
+        da.update(self.config["adp"])
+        if self.config["adp"]["wave_mode"] == "Enabled":
+            da.update(self.config["waves"])
+        da.update(self.config["hdr"])
+        da.update(self.config["hdw"])
+        # No apparent way to determine how many samples are in a file
+        self.ensemble_count()
 
     def _init_data(self, vardict):
         """Initialize the data object according to vardict.
@@ -397,11 +436,11 @@ def findnext(self, do_cs=True):
                 logging.debug("Scanning every 2 bytes for next datablock...")
                 searching = True
 
-    def read_id(self):
+    def read_id(self, log=True):
         """Read the next 'ID' from the file."""
         self._thisid_bytes = bts = self.read(2)
         tmp = unpack(self.endian + "BB", bts)
-        if self.debug:
+        if self.debug and log:
             logging.info("Position: {}, codes: {}".format(self.f.tell(), tmp))
         if tmp[0] != 165:  # This catches a corrupted data block.
             if self.debug:
@@ -456,40 +495,46 @@ def readfile(self, nlines=None):
         self.c -= 1
         lib._crop_data(self.data, slice(0, self.c), self.n_samp_guess)
 
-    def findnextid(self, id):
-        if id.__class__ is str:
-            id = int(id, 0)
-        nowid = None
-        while nowid != id:
-            pos = self.pos
-            nowid = self.read_id()
-            if nowid == 16:
-                shift = 22
-            else:
-                sz = 2 * unpack(self.endian + "H", self.read(2))[0]
-                shift = sz - 4
-            self.f.seek(shift, 1)
-            # If we get stuck in a while loop
-            if self.pos == pos:
-                self.f.seek(2, 1)
-        return self.pos
-
-    def code_spacing(self, searchcode, iternum=50):
-        """
-        Find the spacing, in bytes, between a specific hardware code.
-        Repeat this * iternum * times(default 50).
-        Returns the average spacing, in bytes, between the code.
-        """
-        p0 = self.findnextid(searchcode)
-        for i in range(iternum):
+    def ensemble_count(self):
+        """Find the total number of ensembles in the datafile."""
+        p0 = self.pos
+        id_count = {}
+        id_size = {}
+        # Find the spacing, in bytes, between each sample set of pings
+        while True:
             try:
-                self.findnextid(searchcode)
+                pos = self.pos
+                nowid = self.read_id(log=False)  # read the ID
+                if nowid == 16:
+                    shift = 22
+                else:
+                    # now read the next byte, which is the size of the data block
+                    sz = 2 * unpack(self.endian + "H", self.read(2))[0]
+                    shift = sz - 4
+                if nowid not in id_count:
+                    id_count[nowid] = 1
+                else:
+                    id_count[nowid] += 1
+                if nowid not in id_size:
+                    id_size[nowid] = [sz]
+                else:
+                    id_size[nowid].append(sz)
+                self.f.seek(shift, 1)
+                # If we get stuck in a while loop
+                if self.pos == pos:
+                    self.f.seek(2, 1)
             except EOFError:
                 break
-        if self.debug:
-            logging.info("p0={}, pos={}, i={}".format(p0, self.pos, i))
-        # Compute the average of the data size:
-        return (self.pos - p0) / (i + 1)
+        # Take median size of each ID data block
+        for id in id_size:
+            id_size[id] = int(np.median(id_size[id]))
+        # Return size of most common data block found
+        if len(id_count) >= 1:
+            sample_block_size = id_size[max(id_count, key=id_count.get)]
+        else:
+            raise Exception("No data blocks found in file.")
+
+        self.n_samp_guess = (self.filesize - p0) // sample_block_size
 
     def checksum(self, byts):
         """Perform a checksum on `byts` and read the checksum value."""
@@ -522,28 +567,29 @@ def read_user_cfg(self):
         tmp = unpack(self.endian + "2x18H6s4HI9H90H80s48xH50x6H4xH2x2H2xH30x8H", byts)
         cfg_u["usr"] = {}
         cfg_u["adv"] = {}
-        cfg_u["awac"] = {}
+        cfg_u["adp"] = {}
+        cfg_u["waves"] = {}
 
         cfg_u["transmit_pulse_length_m"] = tmp[0]  # counts
-        cfg_u["blank_dist"] = tmp[1]  # overridden below
+        cfg_u["blank_dist"] = tmp[1]  # counts
         cfg_u["receive_length_m"] = tmp[2]  # counts
         cfg_u["time_between_pings"] = tmp[3]  # counts
         cfg_u["time_between_bursts"] = tmp[4]  # counts
-        cfg_u["adv"]["n_pings_per_burst"] = tmp[5]
-        cfg_u["awac"]["avg_interval"] = tmp[6]
+        cfg_u["n_pings_per_burst"] = tmp[5]
+        cfg_u["avg_interval"] = tmp[6]  # s
         cfg_u["usr"]["n_beams"] = int(tmp[7])
-        TimCtrlReg = lib._int2binarray(tmp[8], 16)
+        time_ctrl_reg = lib._int2binarray(tmp[8], 16)
         # From the nortek system integrator manual
         # (note: bit numbering is zero-based)
-        cfg_u["usr"]["profile_mode"] = ["single", "continuous"][int(TimCtrlReg[1])]
-        cfg_u["usr"]["burst_mode"] = str(bool(~TimCtrlReg[2]))
-        cfg_u["usr"]["power_level"] = int(TimCtrlReg[5] + 2 * TimCtrlReg[6] + 1)
+        cfg_u["usr"]["profile_mode"] = ["single", "continuous"][int(time_ctrl_reg[1])]
+        cfg_u["usr"]["burst_mode"] = ["burst", "continuous"][int(time_ctrl_reg[2])]
+        cfg_u["usr"]["power_level"] = int(time_ctrl_reg[5] + 2 * time_ctrl_reg[6] + 1)
         cfg_u["usr"]["sync_out_pos"] = [
             "middle",
             "end",
-        ][int(TimCtrlReg[7])]
-        cfg_u["usr"]["sample_on_sync"] = str(bool(TimCtrlReg[8]))
-        cfg_u["usr"]["start_on_sync"] = str(bool(TimCtrlReg[9]))
+        ][int(time_ctrl_reg[7])]
+        cfg_u["usr"]["sample_on_sync"] = str(bool(time_ctrl_reg[8]))
+        cfg_u["usr"]["start_on_sync"] = str(bool(time_ctrl_reg[9]))
         cfg_u["PwrCtrlReg"] = lib._int2binarray(tmp[9], 16)
         cfg_u["A1"] = tmp[10]
         cfg_u["B0"] = tmp[11]
@@ -557,12 +603,12 @@ def read_user_cfg(self):
         cfg_u["usr"]["wrap_mode"] = str(bool(tmp[19]))
         cfg_u["deployment_time"] = np.array(tmp[20:23])
         cfg_u["diagnotics_interval"] = tmp[23]
-        Mode0 = lib._int2binarray(tmp[24], 16)
+        mode = lib._int2binarray(tmp[24], 16)
         cfg_u["user_soundspeed_adj_factor"] = tmp[25]
         cfg_u["n_samples_diag"] = tmp[26]
         cfg_u["n_beams_cells_diag"] = tmp[27]
         cfg_u["n_pings_diag_wave"] = tmp[28]
-        ModeTest = lib._int2binarray(tmp[29], 16)
+        mode_test = lib._int2binarray(tmp[29], 16)
         cfg_u["usr"]["analog_in"] = tmp[30]
         sfw_ver = str(tmp[31])
         cfg_u["usr"]["software_version"] = (
@@ -571,48 +617,50 @@ def read_user_cfg(self):
         cfg_u["usr"]["salinity"] = tmp[32] / 10
         cfg_u["VelAdjTable"] = np.array(tmp[33:123])
         cfg_u["usr"]["comments"] = tmp[123].partition(b"\x00")[0].decode("utf-8")
-        cfg_u["awac"]["wave_processing_method"] = [
+        cfg_u["waves"]["wave_processing_method"] = [
             "PUV",
             "SUV",
             "MLM",
             "MLMST",
             "None",
         ][tmp[124]]
-        Mode1 = lib._int2binarray(tmp[125], 16)
-        cfg_u["awac"]["prc_dyn_wave_cell_pos"] = int(tmp[126] / 32767 * 100)
-        cfg_u["wave_transmit_pulse"] = tmp[127]
-        cfg_u["wave_blank_dist"] = tmp[128]
-        cfg_u["awac"]["wave_cell_size"] = tmp[129]
-        cfg_u["awac"]["n_samples_wave"] = tmp[130]
-        cfg_u["n_burst"] = tmp[131]
+        wave_meas_mode = lib._int2binarray(tmp[125], 16)
+        cfg_u["waves"]["prc_dyn_wave_cell_pos"] = int(tmp[126] / 32767 * 100)
+        cfg_u["waves"]["wave_transmit_pulse"] = tmp[127]
+        cfg_u["waves"]["wave_blank_dist"] = tmp[128]
+        cfg_u["waves"]["wave_cell_size"] = tmp[129]
+        cfg_u["waves"]["n_samples_wave"] = tmp[130]
+        cfg_u["adv"]["n_burst"] = tmp[131]
         cfg_u["analog_out_scale"] = tmp[132]
         cfg_u["corr_thresh"] = tmp[133]
         cfg_u["transmit_pulse_lag2"] = tmp[134]  # counts
         cfg_u["QualConst"] = np.array(tmp[135:143])
         self.checksum(byts)
-        cfg_u["usr"]["user_specified_sound_speed"] = str(Mode0[0])
-        cfg_u["awac"]["wave_mode"] = ["Disabled", "Enabled"][int(Mode0[1])]
-        cfg_u["usr"]["analog_output"] = str(Mode0[2])
-        cfg_u["usr"]["output_format"] = ["Vector", "ADV"][int(Mode0[3])]  # noqa
-        cfg_u["vel_scale_mm"] = [1, 0.1][int(Mode0[4])]
-        cfg_u["usr"]["serial_output"] = str(Mode0[5])
-        cfg_u["reserved_EasyQ"] = str(Mode0[6])
-        cfg_u["usr"]["power_output_analog"] = str(Mode0[8])
-        cfg_u["mode_test_use_DSP"] = str(ModeTest[0])
+        # Mode bits:
+        cfg_u["usr"]["user_specified_sound_speed"] = str(mode[0])
+        cfg_u["adp"]["wave_mode"] = ["Disabled", "Enabled"][int(mode[1])]
+        cfg_u["usr"]["analog_output"] = str(mode[2])
+        cfg_u["output_format"] = ["Vector", "ADV"][int(mode[3])]
+        cfg_u["vel_scale_mm"] = [1, 0.1][int(mode[4])]
+        cfg_u["usr"]["serial_output"] = str(mode[5])
+        cfg_u["stage"] = str(mode[7])
+        cfg_u["usr"]["power_output_analog"] = str(mode[8])
+        cfg_u["mode_test_use_DSP"] = str(mode_test[0])
         cfg_u["mode_test_filter_output"] = ["total", "correction_only"][
-            int(ModeTest[1])
-        ]  # noqa
-        cfg_u["awac"]["wave_fs"] = ["1 Hz", "2 Hz"][int(Mode1[0])]
-        cfg_u["awac"]["wave_cell_position"] = ["fixed", "dynamic"][
-            int(Mode1[1])
-        ]  # noqa
-        cfg_u["awac"]["type_wave_cell_pos"] = ["pct_of_mean_pressure", "pct_of_min_re"][
-            int(Mode1[2])
-        ]  # noqa
-
-    def read_head_cfg(self):
+            int(mode_test[1])
+        ]
+        cfg_u["waves"]["wave_fs"] = ["1 Hz", "2 Hz"][int(wave_meas_mode[0])]
+        cfg_u["waves"]["wave_cell_position"] = ["fixed", "dynamic"][
+            int(wave_meas_mode[1])
+        ]
+        cfg_u["waves"]["type_wave_cell_pos"] = [
+            "pct_of_mean_pressure",
+            "pct_of_min_re",
+        ][int(wave_meas_mode[2])]
+
+    def read_hdr_cfg(self):
         """Read header configuration block (0x04)"""
-        # ID: '0x04 = 04
+        # ID: '0x04' = 04
         if self.debug:
             logging.info(
                 "Reading header configuration (0x04) ping #{} @ {}...".format(
@@ -620,22 +668,23 @@ def read_head_cfg(self):
                 )
             )
         cfg = self.config
-        cfg["head"] = {}
+        cfg["hdr"] = {}
         byts = self.read(220)
         tmp = unpack(self.endian + "2x3H12s176s22sH", byts)
         head_config = lib._int2binarray(tmp[0], 16).astype(int)
-        cfg["head"]["pressure_sensor"] = ["no", "yes"][head_config[0]]
-        cfg["head"]["compass"] = ["no", "yes"][head_config[1]]
-        cfg["head"]["tilt_sensor"] = ["no", "yes"][head_config[2]]
-        cfg["head"]["carrier_freq_kHz"] = tmp[1]
+        cfg["hdr"]["pressure_sensor"] = ["no", "yes"][head_config[0]]
+        cfg["hdr"]["compass"] = ["no", "yes"][head_config[1]]
+        cfg["hdr"]["tilt_sensor"] = ["no", "yes"][head_config[2]]
+        cfg["hdr"]["orientation_down"] = int(head_config[2])
+        cfg["hdr"]["carrier_freq_kHz"] = tmp[1]
         cfg["beam2inst_orientmat"] = (
             np.array(unpack(self.endian + "9h", tmp[4][8:26])).reshape(3, 3) / 4096.0
         )
         self.checksum(byts)
 
-    def read_hw_cfg(self):
+    def read_hdw_cfg(self):
         """Read hardware configuration block (0x05)"""
-        # ID 0x05 = 05
+        # ID '0x05' = 05
         if self.debug:
             logging.info(
                 "Reading hardware configuration (0x05) ping #{} @ {}...".format(
@@ -659,9 +708,84 @@ def read_hw_cfg(self):
         cfg_hw["hdw"]["firmware_version"] = tmp[7].decode("utf-8")
         self.checksum(byts)
 
-    def read_vec_checkdata(self):
-        """Read Vector check data block (0x07)"""
-        # ID: 0x07 = 07
+    def read_aqd(self):
+        """Read Aquadopp velocity block (0x01)"""
+        # ID: '0x01' & '0x80' = 1 & 128
+        c = self.c
+        dat = self.data
+        if self.debug:
+            logging.info(
+                "Reading Aquadopp (0x01) ping #{} @ {}...".format(self.c, self.pos)
+            )
+        if "temp" not in self.data["data_vars"]:
+            self._init_data(defs.vec_data)
+            self._dtypes += ["vec_data"]
+
+        byts = self.read(38)
+        dat["coords"]["time"][c] = lib.rd_time(byts[2:8])
+        ds = dat["sys"]
+        dv = dat["data_vars"]
+        (
+            dv["error"][c],
+            ds["AnaIn1"][c],
+            dv["batt"][c],
+            dv["c_sound"][c],
+            dv["heading"][c],
+            dv["pitch"][c],
+            dv["roll"][c],
+            p_msb,
+            dv["status"][c],
+            p_lsw,
+            dv["temp"][c],
+            dv["vel"][0, c],
+            dv["vel"][1, c],
+            dv["vel"][2, c],
+            dv["amp"][0, c],
+            dv["amp"][1, c],
+            dv["amp"][2, c],
+        ) = unpack(self.endian + "5H2h2BH4h3Bx", byts[8:38])
+        dv["pressure"][c] = 65536 * p_msb + p_lsw
+        self.checksum(byts)
+        self.c += 1
+
+    def read_aqd_diag_hdr(self):
+        """Read Aquadopp diagnostics header block (0x06)"""
+        # ID: '0x06' = 6
+        if self.debug:
+            logging.info(
+                "Reading Aquadopp diagnostics (0x06) ping #{} @ {}...".format(
+                    self.c, self.pos
+                )
+            )
+        byts = self.read(32)
+        # The first two are size, the next 6 are time.
+        tmp = unpack(self.endian + "2x2H4B8H6x", byts)
+        hdrnow = {}
+        hdrnow["n_records"] = tmp[0]
+        hdrnow["cell_size_diag"] = tmp[1]
+        hdrnow["noise1"] = tmp[2]
+        hdrnow["noise2"] = tmp[3]
+        hdrnow["noise3"] = tmp[4]
+        hdrnow["noise4"] = tmp[5]
+        hdrnow["proc_magn1"] = tmp[6]
+        hdrnow["proc_magn2"] = tmp[7]
+        hdrnow["proc_magn3"] = tmp[8]
+        hdrnow["proc_magn4"] = tmp[9]
+        hdrnow["distance1"] = tmp[10]
+        hdrnow["distance2"] = tmp[11]
+        hdrnow["distance3"] = tmp[12]
+        hdrnow["distance4"] = tmp[13]
+        self.checksum(byts)
+        if "data_header" not in self.config:
+            self.config["data_header"] = hdrnow
+        else:
+            if not isinstance(self.config["data_header"], list):
+                self.config["data_header"] = [self.config["data_header"]]
+            self.config["data_header"] += [hdrnow]
+
+    def read_vec_check(self):
+        """Read Vector probe check block (0x07)"""
+        # ID: '0x07' = 07
         if self.debug:
             logging.info(
                 "Reading Vector check data (0x07) ping #{} @ {}...".format(
@@ -689,9 +813,9 @@ def read_vec_checkdata(self):
                 self.config["checkdata"] = [self.config["checkdata"]]
             self.config["checkdata"] += [checknow]
 
-    def read_vec_data(self):
-        """Read Vector measurement data block (0x10)"""
-        # ID: 0x10 = 16
+    def read_vec(self):
+        """Read Vector velocity block (0x10)"""
+        # ID: '0x10' = 16
         c = self.c
         dat = self.data
         if self.debug:
@@ -709,11 +833,11 @@ def read_vec_data(self):
         ds = dat["sys"]
         dv = dat["data_vars"]
         (
-            ds["AnaIn2LSB"][c],
+            a2_lsw,
             ds["Count"][c],
-            dv["PressureMSB"][c],
-            ds["AnaIn2MSB"][c],
-            dv["PressureLSW"][c],
+            p_msb,
+            a2_msb,
+            p_lsw,
             ds["AnaIn1"][c],
             dv["vel"][0, c],
             dv["vel"][1, c],
@@ -725,13 +849,14 @@ def read_vec_data(self):
             dv["corr"][1, c],
             dv["corr"][2, c],
         ) = unpack(self.endian + "4B2H3h6B", byts)
-
+        ds["AnaIn2"] = 65536 * a2_msb + a2_lsw
+        dv["pressure"][c] = 65536 * p_msb + p_lsw
         self.checksum(byts)
         self.c += 1
 
-    def read_vec_sysdata(self):
+    def read_vec_sys(self):
         """Read Vector system data block (0x11)"""
-        # ID: 0x11 = 17
+        # ID: '0x11' = 17
         c = self.c
         if self.debug:
             logging.info(
@@ -746,8 +871,8 @@ def read_vec_sysdata(self):
         ]:
             self.burst_start[c] = True
         if "time" not in dat["coords"]:
-            self._init_data(defs.vec_sysdata)
-            self._dtypes += ["vec_sysdata"]
+            self._init_data(defs.vec_sys)
+            self._dtypes += ["vec_sys"]
         byts = self.read(24)
         # The first two are size (skip them).
         dat["coords"]["time"][c] = lib.rd_time(byts[2:8])
@@ -768,28 +893,27 @@ def read_vec_sysdata(self):
 
     def read_vec_hdr(self):
         """Read Vector header block (0x12)"""
-        # ID: '0x12 = 18
+        # ID: '0x12' = 18
         if self.debug:
             logging.info(
                 "Reading Vector header data (0x12) ping #{} @ {}...".format(
                     self.c, self.pos
                 )
             )
-        byts = self.read(38)
-        # The first two are size, the next 6 are time.
-        tmp = unpack(self.endian + "8xH7B21x", byts)
         hdrnow = {}
+        byts = self.read(38)
         hdrnow["time"] = lib.rd_time(byts[2:8])
-        hdrnow["NRecords"] = tmp[0]
-        hdrnow["Noise1"] = tmp[1]
-        hdrnow["Noise2"] = tmp[2]
-        hdrnow["Noise3"] = tmp[3]
-        hdrnow["Spare0"] = byts[13:14].decode("utf-8")
-        hdrnow["Corr1"] = tmp[5]
-        hdrnow["Corr2"] = tmp[6]
-        hdrnow["Corr3"] = tmp[7]
-        hdrnow["Spare1"] = byts[17:].decode("utf-8")
+        # The first two are size, the next 6 are time.
+        tmp = unpack(self.endian + "H3Bx3B21x", byts[8:38])
+        hdrnow["n_records"] = tmp[0]
+        hdrnow["noise1"] = tmp[1]
+        hdrnow["noise2"] = tmp[2]
+        hdrnow["noise3"] = tmp[3]
+        hdrnow["corr1"] = tmp[4]
+        hdrnow["corr2"] = tmp[5]
+        hdrnow["corr3"] = tmp[6]
         self.checksum(byts)
+
         if "data_header" not in self.config:
             self.config["data_header"] = hdrnow
         else:
@@ -797,32 +921,100 @@ def read_vec_hdr(self):
                 self.config["data_header"] = [self.config["data_header"]]
             self.config["data_header"] += [hdrnow]
 
+    def read_profile(self, skip_bytes=0):
+        """Reads AWAC or Aquadopp profile data"""
+        dat = self.data
+        nbins = self.config["usr"]["n_bins"]
+        init_bytes = 28 + skip_bytes
+        # Note: docs state there is 'fill' byte at the end, if nbins is odd,
+        # but doesn't appear to be the case
+        n = self.config["usr"]["n_beams"]
+        byts = self.read(init_bytes + n * 3 * nbins)
+        c = self.c
+        dat["coords"]["time"][c] = lib.rd_time(byts[2:8])
+        ds = dat["sys"]
+        dv = dat["data_vars"]
+        (
+            dv["error"][c],
+            ds["AnaIn1"][c],
+            dv["batt"][c],
+            dv["c_sound"][c],
+            dv["heading"][c],
+            dv["pitch"][c],
+            dv["roll"][c],
+            p_msb,
+            dv["status"][c],
+            p_lsw,
+            dv["temp"][c],
+        ) = unpack(self.endian + "5H2h2BHh", byts[8:28])
+        dv["pressure"][c] = 65536 * p_msb + p_lsw
+
+        tmp = unpack(
+            self.endian + str(n * nbins) + "h" + str(n * nbins) + "B",
+            byts[init_bytes : init_bytes + n * 3 * nbins],  # 3 b/c 3 bytes per row
+        )
+        for idx in range(n):
+            dv["vel"][idx, :, c] = tmp[idx * nbins : (idx + 1) * nbins]
+            dv["amp"][idx, :, c] = tmp[(idx + n) * nbins : (idx + n + 1) * nbins]
+        self.checksum(byts)
+        self.c += 1
+
     def read_awac_profile(self):
         """Read AWAC profile measurements block (0x20)"""
         # ID: '0x20' = 32
-        dat = self.data
         if self.debug:
             logging.info(
                 "Reading AWAC velocity data (0x20) ping #{} @ {}...".format(
                     self.c, self.pos
                 )
             )
-        nbins = self.config["usr"]["n_bins"]
-        if "temp" not in dat["data_vars"]:
+        if "temp" not in self.data["data_vars"]:
             self._init_data(defs.awac_profile)
             self._dtypes += ["awac_profile"]
 
-        # Note: docs state there is 'fill' byte at the end, if nbins is odd,
-        # but doesn't appear to be the case
-        n = self.config["usr"]["n_beams"]
-        byts = self.read(116 + n * 3 * nbins)
+        # The nortek system integrator manual specifies an 88 byte 'spare'
+        # field, therefore we start at 116.
+        self.read_profile(skip_bytes=88)
+
+    def read_aqd_profile(self):
+        """Read Aquadopp profile measurements block (0x21)"""
+        # ID: '0x21' = 33
+        if self.debug:
+            logging.info(
+                "Reading Aquadopp velocity data (0x21) ping #{} @ {}...".format(
+                    self.c, self.pos
+                )
+            )
+        if "temp" not in self.data["data_vars"]:
+            self._init_data(defs.awac_profile)
+            self._dtypes += ["awac_profile"]
+
+        self.read_profile(skip_bytes=0)
+
+    def read_aqd_profile_hr(self):
+        """Read high resolution Aquadopp profile measurements block (0x2a)"""
+        # ID: '0x2a' = 42
+        dat = self.data
+        if self.debug:
+            logging.info(
+                "Reading Aquadopp velocity data (0x2a) ping #{} @ {}...".format(
+                    self.c, self.pos
+                )
+            )
+        if "temp" not in dat["data_vars"]:
+            self._init_data(defs.aqd_hr_profile)
+            self._dtypes += ["awac_profile"]
+            self.data["attrs"]["hr_profile"] = 1
+
+        byts = self.read(52)
         c = self.c
+        # first two bytes are the data block size
         dat["coords"]["time"][c] = lib.rd_time(byts[2:8])
         ds = dat["sys"]
         dv = dat["data_vars"]
         (
+            milliseconds,
             dv["error"][c],
-            ds["AnaIn1"][c],
             dv["batt"][c],
             dv["c_sound"][c],
             dv["heading"][c],
@@ -832,61 +1024,73 @@ def read_awac_profile(self):
             dv["status"][c],
             p_lsw,
             dv["temp"][c],
-        ) = unpack(self.endian + "5H2hBBHh", byts[8:28])
+            ds["AnaIn1"][c],
+            ds["AnaIn2"][c],
+            nbeams,
+            ncells,
+        ) = unpack(self.endian + "5H2h2BHh2H2B", byts[8:34])
+        dat["coords"]["time"][c] += milliseconds / 1000
         dv["pressure"][c] = 65536 * p_msb + p_lsw
-        # The nortek system integrator manual specifies an 88byte 'spare'
-        # field, therefore we start at 116.
+
+        hr_bytes = self.read(nbeams * ncells * 4)
         tmp = unpack(
-            self.endian + str(n * nbins) + "h" + str(n * nbins) + "B",
-            byts[116 : 116 + n * 3 * nbins],
+            self.endian + str(nbeams * ncells) + "h" + str(2 * nbeams * ncells) + "B",
+            hr_bytes,
         )
-        for idx in range(n):
-            dv["vel"][idx, :, c] = tmp[idx * nbins : (idx + 1) * nbins]
-            dv["amp"][idx, :, c] = tmp[(idx + n) * nbins : (idx + n + 1) * nbins]
+        for idx in range(nbeams):
+            dv["vel"][idx, :, c] = tmp[idx * ncells : (idx + 1) * ncells]
+            dv["amp"][idx, :, c] = tmp[
+                (idx + nbeams) * ncells : (idx + nbeams + 1) * ncells
+            ]
+            dv["corr"][idx, :, c] = tmp[
+                (idx + 2 * nbeams) * ncells : (idx + 2 * nbeams + 1) * ncells
+            ]
         self.checksum(byts)
         self.c += 1
 
     def read_awac_waves(self):
         """Read AWAC wave (0x30) and SUV (0x36) data blocks"""
-        # IDs: 0x30 & 0x36
+        # IDs: '0x30' & '0x36'  == 48 & 54
         c = self.c
         dat = self.data
+        nbeams = self.config["usr"]["n_beams"]
         if self.debug:
             print(
                 "Reading AWAC wave data (0x30) ping #{} @ {}...".format(
                     self.c, self.pos
                 )
             )
-        if "dist1_alt" not in dat["data_vars"]:
+        if "dist1" not in dat["data_vars"]:
             self._init_data(defs.wave_data)
             self._dtypes += ["wave_data"]
         # The first two are size
         byts = self.read(20)
+        tmp = unpack(self.endian + "2xh2H4h4B", byts)
         ds = dat["sys"]
         dv = dat["data_vars"]
-        (
-            dv["pressure"][c],  # (0.001 dbar)
-            dv["dist1_alt"][c],  # distance 1 to surface, vertical beam (mm)
-            ds["AnaIn_alt"][c],  # analog input 1
-            dv["vel_alt"][0, c],  # velocity beam 1 (mm/s) East for SUV
-            dv["vel_alt"][1, c],  # North for SUV
-            dv["vel_alt"][2, c],  # Up for SUV
-            dv["dist2_alt"][
-                c
-            ],  # distance 2 to surface, vertical beam (mm) or vel 4 for non-AST
-            dv["amp_alt"][0, c],  # amplitude beam 1 (counts)
-            dv["amp_alt"][1, c],  # amplitude beam 2 (counts)
-            dv["amp_alt"][2, c],  # amplitude beam 3 (counts)
-            # AST quality (counts) or amplitude beam 4 for non-AST
-            dv["quality_alt"][c],
-        ) = unpack(self.endian + "3H4h4B", byts)
+        dv["pressure"][c] = tmp[0]  # (0.001 dbar)
+        dv["dist1"][c] = tmp[1]  # distance 1 to surface, vertical beam (mm)
+        ds["AnaIn1"][c] = tmp[2]  # analog input 1
+        dv["vel"][0, c] = tmp[3]  # velocity beam 1 (mm/s) (East for SUV)
+        dv["vel"][1, c] = tmp[4]  # velocity beam 2 (mm/s) (North for SUV)
+        dv["vel"][2, c] = tmp[5]  # velocity beam 3 (mm/s) (Up for SUV)
+        if nbeams == 4:
+            dv["vel"][3, c] = tmp[6]  # velocity beam 4 (mm/s) (non-AST AWACs)
+        else:
+            dv["dist2"][c] = tmp[6]  # distance 2 to surface, vertical beam (mm)
+        dv["amp"][0, c] = tmp[7]  # amplitude beam 1 (counts)
+        dv["amp"][1, c] = tmp[8]  # amplitude beam 2 (counts)
+        dv["amp"][2, c] = tmp[9]  # amplitude beam 3 (counts)
+        if nbeams == 4:
+            dv["amp"][3, c] = tmp[10]  # amplitude beam 4 (counts) (non-AST AWACs)
+        else:
+            dv["quality"][c] = tmp[10]  # AST quality (counts)
         self.checksum(byts)
         self.c += 1
 
     def read_awac_waves_hdr(self):
         """Read AWAC header bock for wave data (0x31)"""
-        # ID: '0x31'
-        c = self.c
+        # ID: '0x31' == 49
         if self.debug:
             print(
                 "Reading AWAC header data (0x31) ping #{} @ {}...".format(
@@ -894,33 +1098,29 @@ def read_awac_waves_hdr(self):
                 )
             )
         hdrnow = {}
-        dat = self.data
-        ds = dat["sys"]
-        dv = dat["data_vars"]
-        if "time" not in dat["coords"]:
-            self._init_data(defs.waves_hdrdata)
         byts = self.read(56)
         # The first two are size, the next 6 are time.
-        tmp = unpack(self.endian + "8x4H3h2HhH4B6H5h", byts)
-        dat["coords"]["time"][c] = lib.rd_time(byts[2:8])
-        hdrnow["n_records_alt"] = tmp[0]
-        hdrnow["blank_dist_alt"] = tmp[1]  # counts
-        ds["batt_alt"][c] = tmp[2]  # voltage (0.1 V)
-        dv["c_sound_alt"][c] = tmp[3]  # c (0.1 m/s)
-        dv["heading_alt"][c] = tmp[4]  # (0.1 deg)
-        dv["pitch_alt"][c] = tmp[5]  # (0.1 deg)
-        dv["roll_alt"][c] = tmp[6]  # (0.1 deg)
-        dv["pressure1_alt"][c] = tmp[7]  # min pressure previous profile (0.001 dbar)
-        dv["pressure2_alt"][c] = tmp[8]  # max pressure previous profile (0.001 dbar)
-        dv["temp_alt"][c] = tmp[9]  # (0.01 deg C)
-        hdrnow["cell_size_alt"][c] = tmp[10]  # (counts of T3)
-        hdrnow["noise_alt"][c] = tmp[11:15]  # noise amplitude beam 1-4 (counts)
-        hdrnow["proc_magn_alt"][c] = tmp[15:19]  # processing magnitude beam 1-4
-        hdrnow["n_past_window_alt"] = tmp[
-            19
-        ]  # number of samples of AST window past boundary
-        hdrnow["n_window_alt"] = tmp[20]  # AST window size (# samples)
-        hdrnow["Spare1"] = tmp[21:]
+        hdrnow["time"] = lib.rd_time(byts[2:8])
+        tmp = unpack(self.endian + "5H2h2HhH4B4H14x", byts[8:56])
+        hdrnow["n_records"] = tmp[0]
+        hdrnow["blank_dist"] = tmp[1]  # counts
+        hdrnow["batt"] = tmp[2]  # voltage (0.1 V)
+        hdrnow["c_sound"] = tmp[3]  # c (0.1 m/s)
+        hdrnow["heading"] = tmp[4]  # (0.1 deg)
+        hdrnow["pitch"] = tmp[5]  # (0.1 deg)
+        hdrnow["roll"] = tmp[6]  # (0.1 deg)
+        hdrnow["pressure1"] = tmp[7]  # min pressure previous profile (0.001 dbar)
+        hdrnow["pressure2"] = tmp[8]  # max pressure previous profile (0.001 dbar)
+        hdrnow["temp"] = tmp[9]  # (0.01 deg C)
+        hdrnow["cell_size"] = tmp[10]  # (counts of T3)
+        hdrnow["noise1"] = tmp[11]
+        hdrnow["noise2"] = tmp[12]
+        hdrnow["noise3"] = tmp[13]
+        hdrnow["noise4"] = tmp[14]
+        hdrnow["proc_magn1"] = tmp[15]
+        hdrnow["proc_magn2"] = tmp[16]
+        hdrnow["proc_magn3"] = tmp[17]
+        hdrnow["proc_magn4"] = tmp[18]
         self.checksum(byts)
         if "data_header" not in self.config:
             self.config["data_header"] = hdrnow
@@ -929,9 +1129,54 @@ def read_awac_waves_hdr(self):
                 self.config["data_header"] = [self.config["data_header"]]
             self.config["data_header"] += [hdrnow]
 
+    def read_awac_stage(self):
+        """Read AWAC altimeter (0x42) data block"""
+        # IDs: '0x42'  == 66
+        c = self.c
+        dat = self.data
+        # Note: docs state there is 'fill' byte at the end, if nbins is odd,
+        # but doesn't appear to be the case
+        nbins = self.config["usr"]["n_bins"]
+        nbeams = self.config["usr"]["n_beams"]
+        if self.debug:
+            print(
+                "Reading {} wave data (0x42) ping #{} @ {}...".format(
+                    self._inst, self.c, self.pos
+                )
+            )
+        if "ast_dist1" not in dat["data_vars"]:
+            self._init_data(defs.stage_data)
+            self._dtypes += ["stage_data"]
+        # The first two are size
+        byts = self.read(30)
+        dv = dat["data_vars"]
+        (
+            dv["amp_alt"][0, c],  # amplitude beam 1 (counts)
+            dv["amp_alt"][1, c],  # amplitude beam 2 (counts)
+            dv["amp_alt"][2, c],  # amplitude beam 3 (counts)
+            dv["pressure"][c],  # (0.001 dbar)
+            dv["ast_dist1"][c],  # altimeter range estimate (1 mm) using AST
+            dv["ast_quality"][c],  # alimeter quality for AST algorithm
+            dv["c_sound"][c],  # speed of sound (0.1 m/s)
+            dv["ast_dist2"][c],  # altimeter range estimate (1 mm) using AST
+            dv["vel_alt"][0, c],  # velocity beam 1 (mm/s) East for SUV
+            dv["vel_alt"][1, c],  # North for SUV
+            dv["vel_alt"][2, c],  # Up for SUV
+        ) = unpack(self.endian + "4x3B2x2hH2h2x3h3x", byts)
+        alt_bytes = self.read(nbeams * nbins)
+        tmp = unpack(
+            self.endian + str(nbeams * nbins) + "B",
+            alt_bytes,
+        )
+        for idx in range(nbeams):
+            dv["amp"][idx, :, c] = tmp[idx * nbins : (idx + 1) * nbins]
+        self.checksum(byts)
+        self.c += 1
+
     def read_imu(self):
         """Read ADV inertial measurement unit (IMU) data block (0x71)"""
 
+        # ID: '0x71' = 113
         def update_defs(dat, mag=False, orientmat=False):
             imu_data = {
                 "accel": ["m s-2", "Acceleration"],
@@ -1016,7 +1261,7 @@ def update_defs(dat, mag=False, orientmat=False):
         if ahrsid == 195:  # 0xc3
             byts = self.read(64)
             dt = unpack(self.endian + "6f9f4x", byts)
-            (dv["angrt"][:, c], dv["accel"][:, c]) = (
+            dv["angrt"][:, c], dv["accel"][:, c] = (
                 dt[0:3],
                 dt[3:6],
             )
@@ -1026,7 +1271,7 @@ def update_defs(dat, mag=False, orientmat=False):
             # This skips the "DWORD" (4 bytes) and the AHRS checksum
             # (2 bytes)
             dt = unpack(self.endian + "18f6x", byts)
-            (dv["accel"][:, c], dv["angrt"][:, c], dv["mag"][:, c]) = (
+            dv["accel"][:, c], dv["angrt"][:, c], dv["mag"][:, c] = (
                 dt[0:3],
                 dt[3:6],
                 dt[6:9],
@@ -1035,7 +1280,7 @@ def update_defs(dat, mag=False, orientmat=False):
         elif ahrsid == 211:
             byts = self.read(42)
             dt = unpack(self.endian + "9f6x", byts)
-            (dv["angrt"][:, c], dv["accel"][:, c], dv["mag"][:, c]) = (
+            dv["angrt"][:, c], dv["accel"][:, c], dv["mag"][:, c] = (
                 dt[0:3],
                 dt[3:6],
                 dt[6:9],
@@ -1047,6 +1292,52 @@ def update_defs(dat, mag=False, orientmat=False):
         self.checksum(byts0 + byts)
         self.c += 1  # reset the increment
 
+    def read_aqd_mag(self):
+        """Read Aquadopp velocity and magnetometer block (0x81)"""
+        # ID: '0x81' = 129
+        c = self.c
+        dat = self.data
+        if self.debug:
+            logging.info(
+                "Reading Aquadopp (0x81) ping #{} @ {}...".format(self.c, self.pos)
+            )
+        if "temp" not in self.data["data_vars"]:
+            self._init_data(defs.vec_data)
+            self._init_data(defs.vec_sys)
+            self._dtypes += ["vec_data", "vec_sys"]
+
+        byts = self.read(48)
+        dat["coords"]["time"][c] = lib.rd_time(byts[2:8])
+        ds = dat["sys"]
+        dv = dat["data_vars"]
+        (
+            dv["error"][c],
+            ds["AnaIn1"][c],
+            dv["batt"][c],
+            ds["AnaIn2"][c],
+            dv["heading"][c],
+            dv["pitch"][c],
+            dv["roll"][c],
+            p_msb,
+            dv["status"][c],
+            p_lsw,
+            dv["temp"][c],
+            dv["c_sound"][c],
+            dv["ensemble"][c],
+            dv["mag"][0, c],
+            dv["mag"][1, c],
+            dv["mag"][2, c],
+            dv["vel"][0, c],
+            dv["vel"][1, c],
+            dv["vel"][2, c],
+            dv["amp"][0, c],
+            dv["amp"][1, c],
+            dv["amp"][2, c],
+        ) = unpack(self.endian + "5H2h2BHhH7h3Bx", byts[8:48])
+        dv["pressure"][c] = 65536 * p_msb + p_lsw
+        self.checksum(byts)
+        self.c += 1
+
     def cleanup(self):
         """Convert and scale raw measurements to physical quantities."""
         for nm in self._dtypes:
@@ -1065,7 +1356,6 @@ def _convert_data(self, vardict):
             The variable definitions in the :class:`<VarAttrs>` specify
             how to scale each data variable.
         """
-
         for nm, vd in list(vardict.items()):
             if vd.group is None:
                 dat = self.data
@@ -1077,18 +1367,17 @@ def _convert_data(self, vardict):
             if retval is not None:
                 dat[nm] = retval
 
-    def convert_vec_sysdata(self):
+    def convert_vec_sys(self):
         """Convert raw Vector system data into physical quantities."""
         dat = self.data
         fs = dat["attrs"]["fs"]
-        self._convert_data(defs.vec_sysdata)
+        self._convert_data(defs.vec_sys)
         t = dat["coords"]["time"]
         dv = dat["data_vars"]
         dat["sys"]["_sysi"] = ~np.isnan(t)
-        # These are the indices in the sysdata variables
+        # These are the indices in the system variables
         # that are not interpolated.
-        nburst = self.config["n_burst"]
-        dv["orientation_down"] = tbx._nans(len(t), dtype="bool")
+        nburst = self.config["adv"]["n_burst"]
         if nburst == 0:
             num_bursts = 1
             nburst = len(t)
@@ -1110,15 +1399,6 @@ def convert_vec_sysdata(self):
             else:
                 t[iburst] = t[iburst][0] + arng / (fs * 24 * 3600)
 
-            tmpd = tbx._nans_like(dv["heading"][iburst])
-            # The first status bit should be the orientation.
-            tmpd[sysi] = dv["status"][iburst][sysi] & 1
-            tbx.fillgaps(tmpd, extrapFlg=True)
-            tmpd = np.nan_to_num(tmpd, nan=0)  # nans in pitch roll heading
-            slope = np.diff(tmpd)
-            tmpd[1:][slope < 0] = 1
-            tmpd[:-1][slope > 0] = 0
-            dv["orientation_down"][iburst] = tmpd.astype("bool")
         tbx.interpgaps(dv["batt"], t)
         tbx.interpgaps(dv["c_sound"], t)
         tbx.interpgaps(dv["heading"], t)
@@ -1130,38 +1410,37 @@ def convert_vec_data(self):
         """Convert raw Vector measurements to physical quantities."""
         self._convert_data(defs.vec_data)
         dat = self.data
-
-        dat["data_vars"]["pressure"] = (
-            dat["data_vars"]["PressureMSB"].astype("float32") * 65536
-            + dat["data_vars"]["PressureLSW"].astype("float32")
-        ) / 1000.0
-        dat["units"]["pressure"] = "dbar"
-        dat["long_name"]["pressure"] = "Pressure"
-        dat["standard_name"]["pressure"] = "sea_water_pressure"
-
-        dat["data_vars"].pop("PressureMSB")
-        dat["data_vars"].pop("PressureLSW")
-
         # Apply velocity scaling (1 or 0.1)
         dat["data_vars"]["vel"] *= self.config["vel_scale_mm"]
 
     def convert_awac_profile(self):
-        """Convert raw AWAC profile measurements to physical quantities."""
+        """Convert raw AWAC and Aquadopp profile measurements to physical quantities."""
         self._convert_data(defs.awac_profile)
-        # Calculate the ranges.
-        cs_coefs = {2000: 0.0239, 1000: 0.0478, 600: 0.0797, 400: 0.1195}
-        h_ang = 25 * (np.pi / 180)  # Head angle is 25 degrees for all awacs.
+        # Calculate the ranges. (Manually calculated)
+        if "hr_profile" in self.data["attrs"]:
+            cs_coeff = {2000: 0.00675, 1000: 0.01350}
+            bd_coeff = {2000: 0.00662, 1000: 0.00673}
+        else:
+            cs_coeff = {2000: 0.0239, 1000: 0.0478, 600: 0.0797, 400: 0.1195}
+            bd_coeff = {2000: 0.02228, 1000: 0.02266, 600: 0.02281, 400: 0.02289}
+        # Head angle is 25 degrees for all awacs.
+        h_ang = 25 * (np.pi / 180)
         # Cell size
         cs = round(
-            float(self.config["bin_length"])
-            / 256.0
-            * cs_coefs[self.config["head"]["carrier_freq_kHz"]]
+            self.config["bin_length"]
+            / 256
+            * cs_coeff[self.config["hdr"]["carrier_freq_kHz"]]
             * np.cos(h_ang),
             ndigits=2,
         )
         # Blanking distance
-        bd = round(self.config["blank_dist"] * 0.0229 * np.cos(h_ang) - cs, ndigits=2)
-
+        bd = round(
+            self.config["blank_dist"]
+            * bd_coeff[self.config["hdr"]["carrier_freq_kHz"]]
+            * np.cos(h_ang)
+            - cs,
+            ndigits=2,
+        )
         r = (np.float32(np.arange(self.config["usr"]["n_bins"])) + 1) * cs + bd
         self.data["coords"]["range"] = r
         self.data["attrs"]["cell_size"] = float(cs)
@@ -1171,15 +1450,15 @@ def convert_imu(self):
         """Rotate IMU data into ADV coordinate system."""
         dv = self.data["data_vars"]
         for nm in self._orient_dnames:
-            # Rotate the MS orientation data (in MS coordinate system)
+            # Rotate the MS orientation data (in MS 3DM-GX3 coordinate system)
             # to be consistent with the ADV coordinate system.
             # (x,y,-z)_ms = (z,y,x)_adv
-            (dv[nm][2], dv[nm][0]) = (dv[nm][0], -dv[nm][2].copy())
+            dv[nm][2], dv[nm][0] = (dv[nm][0], -dv[nm][2].copy())
         if "orientmat" in self._orient_dnames:
             # MS coordinate system is in North-East-Down (NED),
             # we want East-North-Up (ENU)
             dv["orientmat"][:, 2] *= -1
-            (dv["orientmat"][:, 0], dv["orientmat"][:, 1]) = (
+            dv["orientmat"][:, 0], dv["orientmat"][:, 1] = (
                 dv["orientmat"][:, 1],
                 dv["orientmat"][:, 0].copy(),
             )
diff --git a/mhkit/dolfyn/io/nortek2.py b/mhkit/dolfyn/io/nortek2.py
index 414790408..a536bca51 100644
--- a/mhkit/dolfyn/io/nortek2.py
+++ b/mhkit/dolfyn/io/nortek2.py
@@ -450,6 +450,12 @@ def _altraw_reorg(outdat, tag=""):
         outdat["data_vars"]["samp_altraw" + tag].astype("float32") / 2**8
     )
 
+    # Make sure altraw variables get variable metadata copied over
+    for ky in ["units", "long_name", "standard_name"]:
+        for dky in list(outdat[ky]):
+            if dky.endswith("alt"):
+                outdat[ky][dky + "raw"] = outdat[ky][dky]
+
     # Read altimeter status
     outdat["data_vars"].pop("status_altraw" + tag)
     status_alt = lib._alt_status2data(outdat["data_vars"]["status_alt" + tag])
@@ -696,6 +702,9 @@ def _clean_dp_skips(data):
     for id in data:
         if id == "filehead_config":
             continue
+        if "ver" not in data[id]:
+            warnings.warn(f"Dual-profile unknown ID: {id}")
+            continue
         # Check where 'ver' is zero (should be 1 (for bt) or 3 (everything else))
         skips = np.where(data[id]["ver"] != 0)
         for var in data[id]:
diff --git a/mhkit/dolfyn/io/nortek2_defs.py b/mhkit/dolfyn/io/nortek2_defs.py
index 8c4ea68ec..56cc0e052 100644
--- a/mhkit/dolfyn/io/nortek2_defs.py
+++ b/mhkit/dolfyn/io/nortek2_defs.py
@@ -4,7 +4,6 @@
 
 from . import nortek2_lib as lib
 
-
 dt32 = "float32"
 grav = 9.81
 # The starting value for the checksum:
diff --git a/mhkit/dolfyn/io/nortek_defs.py b/mhkit/dolfyn/io/nortek_defs.py
index c1c3fe935..c1863d6c3 100644
--- a/mhkit/dolfyn/io/nortek_defs.py
+++ b/mhkit/dolfyn/io/nortek_defs.py
@@ -113,33 +113,28 @@ def scale(self, data):
 
 
 vec_data = {
-    "AnaIn2LSB": _VarAtts(
-        dims=[],
-        dtype=np.uint8,
-        group="sys",
-    ),
     "Count": _VarAtts(
         dims=[],
         dtype=np.uint8,
         group="sys",
         units="1",
     ),
-    "PressureMSB": _VarAtts(
+    "pressure": _VarAtts(
         dims=[],
-        dtype=np.uint8,
+        dtype=np.float32,
         group="data_vars",
+        default_val=nan,
+        factor=0.001,
+        units="dbar",
+        long_name="Pressure",
+        standard_name="sea_water_pressure",
     ),
-    "AnaIn2MSB": _VarAtts(
-        dims=[],
-        dtype=np.uint8,
-        group="sys",
-    ),
-    "PressureLSW": _VarAtts(
+    "AnaIn1": _VarAtts(
         dims=[],
         dtype=np.uint16,
-        group="data_vars",
+        group="sys",
     ),
-    "AnaIn1": _VarAtts(
+    "AnaIn2": _VarAtts(
         dims=[],
         dtype=np.uint16,
         group="sys",
@@ -170,7 +165,7 @@ def scale(self, data):
     ),
 }
 
-vec_sysdata = {
+vec_sys = {
     "time": _VarAtts(
         dims=[],
         dtype=np.float64,
@@ -259,13 +254,6 @@ def scale(self, data):
         group="sys",
         default_val=nan,
     ),
-    "orientation_down": _VarAtts(
-        dims=[],
-        dtype=bool,
-        group="data_vars",
-        default_val=nan,
-        long_name="Orientation of ADV Communication Cable",
-    ),
 }
 
 awac_profile = {
@@ -385,26 +373,45 @@ def scale(self, data):
     ),
 }
 
-waves_hdrdata = {
-    "time_alt": _VarAtts(
+aqd_hr_profile = {
+    "time": _VarAtts(
         dims=[],
         dtype=np.float64,
         group="coords",
-        default_val=nan,
         units="seconds since 1970-01-01 00:00:00 UTC",
         long_name="Time",
         standard_name="time",
     ),
-    "batt_alt": _VarAtts(
+    "error": _VarAtts(
         dims=[],
         dtype=np.uint16,
         group="data_vars",
+        long_name="Error Code",
+    ),
+    "AnaIn1": _VarAtts(
+        dims=[],
+        dtype=np.float32,
+        group="sys",
+        default_val=nan,
+        units="n/a",
+    ),
+    "AnaIn2": _VarAtts(
+        dims=[],
+        dtype=np.float32,
+        group="sys",
+        default_val=nan,
+        units="n/a",
+    ),
+    "batt": _VarAtts(
+        dims=[],
+        dtype=np.float32,
+        group="data_vars",
         default_val=nan,
         factor=0.1,
         units="V",
         long_name="Battery Voltage",
     ),
-    "c_sound_alt": _VarAtts(
+    "c_sound": _VarAtts(
         dims=[],
         dtype=np.float32,
         group="data_vars",
@@ -414,7 +421,7 @@ def scale(self, data):
         long_name="Speed of Sound",
         standard_name="speed_of_sound_in_sea_water",
     ),
-    "heading_alt": _VarAtts(
+    "heading": _VarAtts(
         dims=[],
         dtype=np.float32,
         group="data_vars",
@@ -424,7 +431,7 @@ def scale(self, data):
         long_name="Heading",
         standard_name="platform_orientation",
     ),
-    "pitch_alt": _VarAtts(
+    "pitch": _VarAtts(
         dims=[],
         dtype=np.float32,
         group="data_vars",
@@ -434,7 +441,7 @@ def scale(self, data):
         long_name="Pitch",
         standard_name="platform_pitch",
     ),
-    "roll_alt": _VarAtts(
+    "roll": _VarAtts(
         dims=[],
         dtype=np.float32,
         group="data_vars",
@@ -444,27 +451,24 @@ def scale(self, data):
         long_name="Roll",
         standard_name="platform_roll",
     ),
-    "pressure1_alt": _VarAtts(
+    "pressure": _VarAtts(
         dims=[],
         dtype=np.float32,
         group="data_vars",
         default_val=nan,
         factor=0.001,
         units="dbar",
-        long_name="Pressure Min",
+        long_name="Pressure",
         standard_name="sea_water_pressure",
     ),
-    "pressure2_alt": _VarAtts(
+    "status": _VarAtts(
         dims=[],
         dtype=np.float32,
         group="data_vars",
         default_val=nan,
-        factor=0.001,
-        units="dbar",
-        long_name="Pressure Max",
-        standard_name="sea_water_pressure",
+        long_name="Status Code",
     ),
-    "temp_alt": _VarAtts(
+    "temp": _VarAtts(
         dims=[],
         dtype=np.float32,
         group="data_vars",
@@ -474,10 +478,35 @@ def scale(self, data):
         long_name="Temperature",
         standard_name="sea_water_temperature",
     ),
+    "vel": _VarAtts(
+        dims=[3, "nbins", "n"],  # how to change this for different # of beams?
+        dtype=np.float32,
+        group="data_vars",
+        default_val=nan,
+        factor=0.001,
+        units="m s-1",
+        long_name="Water Velocity",
+    ),
+    "amp": _VarAtts(
+        dims=[3, "nbins", "n"],
+        dtype=np.uint8,
+        group="data_vars",
+        units="1",
+        long_name="Acoustic Signal Amplitude",
+        standard_name="signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water",
+    ),
+    "corr": _VarAtts(
+        dims=[3, "nbins", "n"],
+        dtype=np.uint8,
+        group="data_vars",
+        units="1",
+        long_name="Acoustic Signal Correlation",
+        standard_name="beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water",
+    ),
 }
 
 waves_data = {
-    "pressure_alt": _VarAtts(
+    "pressure": _VarAtts(
         dims=[],
         dtype=np.float32,
         group="data_vars",
@@ -487,7 +516,7 @@ def scale(self, data):
         long_name="Pressure",
         standard_name="sea_water_pressure",
     ),
-    "dist1_alt": _VarAtts(
+    "dist1": _VarAtts(
         dims=[],
         dtype=np.uint16,
         group="data_vars",
@@ -497,7 +526,7 @@ def scale(self, data):
         long_name="AST distance1 on vertical beam",
         standard_name="altimeter_range",
     ),
-    "dist2_alt": _VarAtts(
+    "dist2": _VarAtts(
         dims=[],
         dtype=np.uint16,
         group="data_vars",
@@ -507,14 +536,14 @@ def scale(self, data):
         long_name="AST distance2 on vertical beam",
         standard_name="altimeter_range",
     ),
-    "AnaIn1_alt": _VarAtts(
+    "AnaIn1": _VarAtts(
         dims=[],
         dtype=np.float32,
         group="sys",
         default_val=nan,
         units="n/a",
     ),
-    "vel_alt": _VarAtts(
+    "vel": _VarAtts(
         dims=[4, "n"],
         dtype=np.float32,
         group="data_vars",
@@ -523,7 +552,7 @@ def scale(self, data):
         units="m s-1",
         long_name="Water Velocity",
     ),
-    "amp_alt": _VarAtts(
+    "amp": _VarAtts(
         dims=[4, "n"],
         dtype=np.uint8,
         group="data_vars",
@@ -532,7 +561,7 @@ def scale(self, data):
         long_name="Acoustic Signal Amplitude",
         standard_name="signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water",
     ),
-    "quality_alt": _VarAtts(
+    "quality": _VarAtts(
         dims=[],
         dtype=np.float32,
         group="data_vars",
@@ -541,3 +570,81 @@ def scale(self, data):
         long_name="Altimeter Quality Indicator",
     ),
 }
+
+stage_data = {
+    "amp_alt": _VarAtts(
+        dims=[4],
+        dtype=np.uint8,
+        group="data_vars",
+        default_val=nan,
+        units="1",
+        long_name="Acoustic Signal Amplitude",
+        standard_name="signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water",
+    ),
+    "pressure": _VarAtts(
+        dims=[],
+        dtype=np.float32,
+        group="data_vars",
+        default_val=nan,
+        factor=0.001,
+        units="dbar",
+        long_name="Pressure",
+        standard_name="sea_water_pressure",
+    ),
+    "ast_dist1": _VarAtts(
+        dims=[],
+        dtype=np.uint16,
+        group="data_vars",
+        default_val=nan,
+        factor=0.001,
+        units="m",
+        long_name="Altimeter Range Acoustic Surface Tracking 1",
+        standard_name="altimeter_range",
+    ),
+    "ast_quality": _VarAtts(
+        dims=[],
+        dtype=np.float32,
+        group="data_vars",
+        default_val=nan,
+        units="1",
+        long_name="Altimeter Quality Indicator Acoustic Surface Tracking",
+    ),
+    "c_sound": _VarAtts(
+        dims=[],
+        dtype=np.float32,
+        group="data_vars",
+        default_val=nan,
+        factor=0.1,
+        units="m s-1",
+        long_name="Speed of Sound",
+        standard_name="speed_of_sound_in_sea_water",
+    ),
+    "ast_dist2": _VarAtts(
+        dims=[],
+        dtype=np.uint16,
+        group="data_vars",
+        default_val=nan,
+        factor=0.001,
+        units="m",
+        long_name="Altimeter Range Acoustic Surface Tracking 2",
+        standard_name="altimeter_range",
+    ),
+    "vel_alt": _VarAtts(
+        dims=[4],
+        dtype=np.float32,
+        group="data_vars",
+        default_val=nan,
+        factor=0.001,
+        units="m s-1",
+        long_name="Water Velocity",
+    ),
+    "amp": _VarAtts(
+        dims=[4, "n"],
+        dtype=np.uint8,
+        group="data_vars",
+        default_val=nan,
+        units="1",
+        long_name="Acoustic Signal Amplitude",
+        standard_name="signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water",
+    ),
+}
diff --git a/mhkit/dolfyn/io/rdi_defs.py b/mhkit/dolfyn/io/rdi_defs.py
index 34b09ee1b..9023f44ce 100644
--- a/mhkit/dolfyn/io/rdi_defs.py
+++ b/mhkit/dolfyn/io/rdi_defs.py
@@ -4,7 +4,6 @@
 from . import rdi_lib as lib
 from .. import time as tmlib
 
-
 century = np.uint16(2000)
 adcp_type = {
     4: "Broadband",
diff --git a/mhkit/dolfyn/rotate/api.py b/mhkit/dolfyn/rotate/api.py
index 25cabc673..f06afc5a1 100644
--- a/mhkit/dolfyn/rotate/api.py
+++ b/mhkit/dolfyn/rotate/api.py
@@ -7,7 +7,6 @@
 import xarray as xr
 import warnings
 
-
 # The 'rotation chain'
 rc = ["beam", "inst", "earth", "principal"]
 
diff --git a/mhkit/dolfyn/rotate/vector.py b/mhkit/dolfyn/rotate/vector.py
index df37b0f9c..2f62b1b18 100644
--- a/mhkit/dolfyn/rotate/vector.py
+++ b/mhkit/dolfyn/rotate/vector.py
@@ -140,7 +140,7 @@ def _inst2earth(advo, reverse=False, rotate_vars=None, force=False):
         omat = advo["orientmat"]
     else:
         if "vector" in advo.inst_model.lower():
-            orientation_down = advo["orientation_down"]
+            orientation_down = advo.attrs["orientation_down"]
 
         omat = _calc_omat(
             advo["time"], advo["heading"], advo["pitch"], advo["roll"], orientation_down
@@ -252,12 +252,19 @@ def _calc_omat(time, hh, pp, rr, orientation_down=None):
       Roll Euler angle in degrees.
 
     orientation_down: array-like or bool, optional
-      Set to true if instrument is facing downwards
+      Set to true if non-cabled ADV is facing upwards.
+      Leave as None for all other Nortek instruments.
 
     Returns
     -------
     omat: array-like
       The calculated orientation matrix.
+
+    Notes
+    -----
+    For non-cabled Nortek Vector ADVs: 'down' configuration means the
+    probe was pointing 'up', where the 'up' orientation corresponds
+    to the communication cable being up.
     """
 
     rr = rr.data.copy()
@@ -270,11 +277,7 @@ def _calc_omat(time, hh, pp, rr, orientation_down=None):
         pp[lastgd:] = pp[lastgd]
         hh[lastgd:] = hh[lastgd]
     if orientation_down is not None:
-        # For Nortek Vector ADVs: 'down' configuration means the head was
-        # pointing 'up', where the 'up' orientation corresponds to the
-        # communication cable being up.  Check the Nortek coordinate
-        # transform matlab script for more info.
-        rr[orientation_down.astype(bool)] += 180
+        rr += 180
 
     return _euler2orient(time, hh, pp, rr)
 
diff --git a/mhkit/dolfyn/tools/fft.py b/mhkit/dolfyn/tools/fft.py
index 7d8c08503..2bd5b6511 100644
--- a/mhkit/dolfyn/tools/fft.py
+++ b/mhkit/dolfyn/tools/fft.py
@@ -246,11 +246,13 @@ def cpsd_1D(a, b, nfft, fs, window="hann", step=None):
     window = _getwindow(window, nfft)
     fft_inds = slice(1, int(nfft / 2.0 + 1))
     wght = 2.0 / (window**2).sum()
+    # Take FFT of first segment
     s1 = fft(detrend_array(a[0:nfft]) * window)[fft_inds]
     if auto_psd:
         pwr = np.abs(s1) ** 2
     else:
         pwr = s1 * np.conj(fft(detrend_array(b[0:nfft]) * window)[fft_inds])
+    # take FFT of remaining segments
     if nens - 1:
         for i in range(step, l - nfft + 1, step):
             s1 = fft(detrend_array(a[i : (i + nfft)]) * window)[fft_inds]
diff --git a/mhkit/dolfyn/velocity.py b/mhkit/dolfyn/velocity.py
index bb95c40c7..9b8dd557b 100644
--- a/mhkit/dolfyn/velocity.py
+++ b/mhkit/dolfyn/velocity.py
@@ -304,7 +304,10 @@ def u(
         - earth:     east
         - principal: streamwise
         """
-        return self.ds["vel"][0].drop_vars("dir")
+        try:
+            return self.ds["vel"][0].drop_vars("dir")
+        except KeyError:
+            return self.ds["vel_avg"][0].drop_vars("dir")
 
     @property
     def v(
@@ -322,7 +325,10 @@ def v(
         - earth:     north
         - principal: cross-stream
         """
-        return self.ds["vel"][1].drop_vars("dir")
+        try:
+            return self.ds["vel"][1].drop_vars("dir")
+        except KeyError:
+            return self.ds["vel_avg"][1].drop_vars("dir")
 
     @property
     def w(
@@ -340,7 +346,10 @@ def w(
         - earth:     up
         - principal: up
         """
-        return self.ds["vel"][2].drop_vars("dir")
+        try:
+            return self.ds["vel"][2].drop_vars("dir")
+        except KeyError:
+            return self.ds["vel_avg"][2].drop_vars("dir")
 
     @property
     def U(
@@ -412,10 +421,10 @@ def E_coh(
         """
         Coherent turbulent energy
 
-        Niel Kelley's 'coherent turbulence energy', which is the
+        Neil Kelley's 'coherent turbulence energy', which is the
         root-mean-square of the Reynold's stresses.
 
-        See: NREL Technical Report TP-500-52353
+        See: NLR Technical Report TP-500-52353
         """
         E_coh = (self.upwp_**2 + self.upvp_**2 + self.vpwp_**2) ** (0.5)
 
@@ -659,7 +668,7 @@ def bin_average(self, raw_ds, out_ds=None, names=None):
         std = self.standard_deviation(raw_ds.velds.U_mag.values)
         out_ds["U_std"] = xr.DataArray(
             std.astype("float32"),
-            dims=raw_ds.vel.dims[1:],
+            dims=raw_ds.velds.U_mag.dims,
             attrs={
                 "units": "m s-1",
                 "long_name": "Water Velocity Standard Deviation",
@@ -958,7 +967,6 @@ def power_spectral_density(
         noise=0,
         n_bin=None,
         n_fft=None,
-        n_pad=None,
         step=None,
     ):
         """
@@ -982,8 +990,6 @@ def power_spectral_density(
           The bin-size. Default = `self.n_bin`
         n_fft : int (optional)
           The fft size. Default = `self.n_fft`
-        n_pad : int (optional)
-          The number of values to pad with zero. Default = 0
         step : int (optional)
           Controls amount of overlap in fft. Default: the step size is
           chosen to maximize data use, minimize nens, and have a
@@ -1047,7 +1053,6 @@ def power_spectral_density(
                     noise=noise[idx],
                     window=window,
                     n_bin=n_bin,
-                    n_pad=n_pad,
                     n_fft=n_fft,
                     step=step,
                 )
@@ -1067,7 +1072,6 @@ def power_spectral_density(
                 noise=noise,
                 window=window,
                 n_bin=n_bin,
-                n_pad=n_pad,
                 n_fft=n_fft,
                 step=step,
             )
diff --git a/mhkit/river/io/d3d.py b/mhkit/river/io/d3d.py
index 7295d7e11..ac0f49f73 100644
--- a/mhkit/river/io/d3d.py
+++ b/mhkit/river/io/d3d.py
@@ -16,7 +16,8 @@
 from mhkit.utils import unorm
 
 
-def get_all_time(data: netCDF4.Dataset) -> NDArray:
+# pylint: disable=possibly-used-before-assignment
+def get_all_time(data: (netCDF4.Dataset, xr.Dataset)) -> NDArray:
     """
     Returns all of the time stamps from a D3D simulation passed to the function
     as a NetCDF object (data)
@@ -35,10 +36,18 @@ def get_all_time(data: netCDF4.Dataset) -> NDArray:
         simulation conditions at that time.
     """
 
-    if not isinstance(data, netCDF4.Dataset):
-        raise TypeError("data must be a NetCDF4 object")
+    if not isinstance(data, (netCDF4.Dataset, xr.Dataset)):
+        raise TypeError("data must be a NetCDF4 object Dataset")
 
-    seconds_run = np.ma.getdata(data.variables["time"][:], False)
+    if isinstance(data, netCDF4.Dataset):
+        seconds_run = np.ma.getdata(data.variables["time"][:], False)
+
+    elif isinstance(data, xr.Dataset):
+        seconds_run = (
+            (data.time.values - data.time.values[0])
+            .astype("timedelta64[s]")
+            .astype(int)
+        )
 
     return seconds_run
 
@@ -64,6 +73,7 @@ def index_to_seconds(data: netCDF4.Dataset, time_index: int) -> Union[int, float
     return _convert_time(data, time_index=time_index)
 
 
+# pylint: disable=possibly-used-before-assignment
 def seconds_to_index(data: netCDF4.Dataset, seconds_run: Union[int, float]) -> int:
     """
     The function will return the nearest 'time_index' in the data if passed an
@@ -87,10 +97,11 @@ def seconds_to_index(data: netCDF4.Dataset, seconds_run: Union[int, float]) -> i
     return _convert_time(data, seconds_run=seconds_run)
 
 
+# pylint: disable=possibly-used-before-assignment
 def _convert_time(
-    data: netCDF4.Dataset,
+    data: netCDF4.Dataset or xr.Dataset,
     time_index: Optional[Union[int, float]] = None,
-    seconds_run: Optional[Union[int, float]] = None,
+    seconds_run: Optional[Union[int, float, np.datetime64]] = None,
 ) -> Union[int, float]:
     """
     Converts a time index to seconds or seconds to a time index. The user
@@ -118,8 +129,8 @@ def _convert_time(
         provided, returns the closest matching time_index.
     """
 
-    if not isinstance(data, netCDF4.Dataset):
-        raise TypeError("data must be NetCDF4 object")
+    if not isinstance(data, (netCDF4.Dataset, xr.Dataset)):
+        raise TypeError("data must be NetCDF4 object or xarray Dataset")
 
     if not (time_index or seconds_run):
         raise ValueError("Input of time_index or seconds_run needed")
@@ -153,27 +164,30 @@ def _convert_time(
     return converted_value
 
 
+# pylint: disable=unused-variable
 # pylint: disable=too-many-locals
 # pylint: disable=too-many-branches
 # pylint: disable=too-many-statements
+# pylint: disable=used-before-assignment
+# pylint: disable=possibly-used-before-assignment
 def get_layer_data(
-    data: netCDF4.Dataset,
+    data: Union[netCDF4.Dataset, xr.Dataset],
     variable: str,
     layer_index: int = -1,
     time_index: int = -1,
     to_pandas: bool = True,
 ) -> Union[pd.DataFrame, xr.Dataset]:
     """
-    Get variable data from the NetCDF4 object at a specified layer and timestep.
+    Get variable data from the NetCDF4 or xarray object at a specified layer and timestep.
     If the data is 2D the layer_index is ignored.
 
     Parameters
     ----------
-    data: NetCDF4 object
-       A NetCDF4 object that contains spatial data, e.g. velocity or shear
+    data: Union[netCDF4.Dataset, xr.Dataset]
+       A NetCDF4 or xarray Dataset object that contains spatial data, e.g. velocity or shear
        stress, generated by running a Delft3D model.
     variable: string
-        Delft3D outputs many vairables. The full list can be
+        Delft3D outputs many variables. The full list can be
         found using "data.variables.keys()" in the console.
     layer_index: int
          An integer to pull out a layer from the dataset. 0 being closest
@@ -199,8 +213,8 @@ def get_layer_data(
     if not isinstance(layer_index, int):
         raise TypeError("layer_index must be an int")
 
-    if not isinstance(data, netCDF4.Dataset):
-        raise TypeError("data must be NetCDF4 object")
+    if not isinstance(data, (netCDF4.Dataset, xr.Dataset)):
+        raise TypeError("data must be a NetCDF4 Dataset or xarray Dataset")
 
     if variable not in data.variables.keys():
         raise ValueError("variable not recognized")
@@ -208,9 +222,14 @@ def get_layer_data(
     if not isinstance(to_pandas, bool):
         raise TypeError(f"to_pandas must be of type bool. Got: {type(to_pandas)}")
 
-    coords = str(data.variables[variable].coordinates).split()
-    var = data.variables[variable][:]
-    max_time_index = data["time"].shape[0] - 1  # to account for zero index
+    if isinstance(data, netCDF4.Dataset):
+        coords = str(data.variables[variable].coordinates).split()
+        var = data.variables[variable][:]
+        max_time_index = data.variables["time"].shape[0] - 1
+    elif isinstance(data, xr.Dataset):
+        coords = list(data[variable].coords)
+        var = data[variable].values
+        max_time_index = data["time"].shape[0] - 1
 
     if abs(time_index) > max_time_index:
         raise ValueError(
@@ -218,8 +237,12 @@ def get_layer_data(
             f"max time index {max_time_index}"
         )
 
-    x = np.ma.getdata(data.variables[coords[0]][:], False)
-    y = np.ma.getdata(data.variables[coords[1]][:], False)
+    if isinstance(data, netCDF4.Dataset):
+        x = np.ma.getdata(data.variables[coords[0]][:], False)
+        y = np.ma.getdata(data.variables[coords[1]][:], False)
+    elif isinstance(data, xr.Dataset):
+        x = data[coords[0]].values
+        y = data[coords[1]].values
 
     if isinstance(var[0][0], np.ma.core.MaskedArray):
         max_layer = len(var[0][0])
@@ -229,7 +252,14 @@ def get_layer_data(
 
         v = np.ma.getdata(var[time_index, :, layer_index], False)
         dimensions = 3
+    elif isinstance(var[0][0], np.ndarray):
+        max_layer = var[0][0].shape[0]
 
+        if abs(layer_index) > max_layer:
+            raise ValueError(f"layer_index must be less than the max layer {max_layer}")
+
+        v = np.ma.getdata(var[time_index, :, layer_index], False)
+        dimensions = 3
     else:
         if not isinstance(var[0][0], np.float64):
             raise TypeError("data not recognized")
@@ -238,76 +268,148 @@ def get_layer_data(
         v = np.ma.getdata(var[time_index, :], False)
 
     # waterdepth
-    if "mesh2d" in variable:
-        cords_to_layers = {
-            "mesh2d_face_x mesh2d_face_y": {
-                "name": "mesh2d_nLayers",
-                "coords": data.variables["mesh2d_layer_sigma"][:],
-            },
-            "mesh2d_edge_x mesh2d_edge_y": {
-                "name": "mesh2d_nInterfaces",
-                "coords": data.variables["mesh2d_interface_sigma"][:],
-            },
-        }
-        bottom_depth = np.ma.getdata(
-            data.variables["mesh2d_waterdepth"][time_index, :], False
-        )
-        waterlevel = np.ma.getdata(data.variables["mesh2d_s1"][time_index, :], False)
-        coords = str(data.variables["waterdepth"].coordinates).split()
-
-    elif str(data.variables[variable].coordinates) == "FlowElem_xcc FlowElem_ycc":
-        cords_to_layers = {
-            "FlowElem_xcc FlowElem_ycc": {
-                "name": "laydim",
-                "coords": data.variables["LayCoord_cc"][:],
-            },
-            "FlowLink_xu FlowLink_yu": {
-                "name": "wdim",
-                "coords": data.variables["LayCoord_w"][:],
-            },
-        }
-        bottom_depth = np.ma.getdata(data.variables["waterdepth"][time_index, :], False)
-        waterlevel = np.ma.getdata(data.variables["s1"][time_index, :], False)
-        coords = str(data.variables["waterdepth"].coordinates).split()
-    else:
-        cords_to_layers = {
-            "FlowElem_xcc FlowElem_ycc LayCoord_cc LayCoord_cc": {
-                "name": "laydim",
-                "coords": data.variables["LayCoord_cc"][:],
-            },
-            "FlowLink_xu FlowLink_yu": {
-                "name": "wdim",
-                "coords": data.variables["LayCoord_w"][:],
-            },
-        }
-        bottom_depth = np.ma.getdata(data.variables["waterdepth"][time_index, :], False)
-        waterlevel = np.ma.getdata(data.variables["s1"][time_index, :], False)
-        coords = str(data.variables["waterdepth"].coordinates).split()
-
-    layer_dim = str(data.variables[variable].coordinates)
+    if isinstance(data, netCDF4.Dataset):
+        if "mesh2d" in variable:
+            cords_to_layers = {
+                "mesh2d_face_x mesh2d_face_y": {
+                    "name": "mesh2d_nLayers",
+                    "coords": data.variables["mesh2d_layer_sigma"][:],
+                },
+                "mesh2d_edge_x mesh2d_edge_y": {
+                    "name": "mesh2d_nInterfaces",
+                    "coords": data.variables["mesh2d_interface_sigma"][:],
+                },
+                "mesh2d_face_x mesh2d_face_y mesh2d_layer_sigma": {
+                    "name": "mesh2d_nLayers",
+                    "coords": data.variables["mesh2d_layer_sigma"][:],
+                },
+            }
+            bottom_depth = np.ma.getdata(
+                data.variables["mesh2d_waterdepth"][time_index, :], False
+            )
+            waterlevel = np.ma.getdata(
+                data.variables["mesh2d_s1"][time_index, :], False
+            )
+            coords = str(data.variables["mesh2d_waterdepth"].coordinates).split()
+
+        elif str(data.variables[variable].coordinates) == "FlowElem_xcc FlowElem_ycc":
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+            bottom_depth = np.ma.getdata(
+                data.variables["waterdepth"][time_index, :], False
+            )
+            waterlevel = np.ma.getdata(data.variables["s1"][time_index, :], False)
+            coords = str(data.variables["waterdepth"].coordinates).split()
+        else:
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc LayCoord_cc LayCoord_cc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+            bottom_depth = np.ma.getdata(
+                data.variables["waterdepth"][time_index, :], False
+            )
+            waterlevel = np.ma.getdata(data.variables["s1"][time_index, :], False)
+            coords = str(data.variables["waterdepth"].coordinates).split()
+
+        layer_dim = str(data.variables[variable].coordinates)
+
+    elif isinstance(data, xr.Dataset):
+        if "mesh2d" in variable:
+            cords_to_layers = {
+                "mesh2d_face_x mesh2d_face_y": {
+                    "name": "mesh2d_nLayers",
+                    "coords": data.variables["mesh2d_layer_sigma"][:],
+                },
+                "mesh2d_edge_x mesh2d_edge_y": {
+                    "name": "mesh2d_nInterfaces",
+                    "coords": data.variables["mesh2d_interface_sigma"][:],
+                },
+            }
+            bottom_depth = data["mesh2d_waterdepth"].values[time_index, :]
+            waterlevel = data["mesh2d_s1"].values[time_index, :]
+            coords = list(data["mesh2d_waterdepth"].coords)
+        elif (
+            str(list(data[variable].coords))
+            == "['FlowElem_xcc', 'FlowElem_ycc', 'time']"
+            or str(list(data[variable].coords))
+            == "['FlowLink_xu', 'FlowLink_yu', 'time']"
+        ):
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+            bottom_depth = data["waterdepth"].values[time_index, :]
+            waterlevel = data["s1"].values[time_index, :]
+            coords = list(data["waterdepth"].coords)
+        else:
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc LayCoord_cc LayCoord_cc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+            bottom_depth = data["waterdepth"].values[time_index, :]
+            waterlevel = data["s1"].values[time_index, :]
+            coords = list(data["waterdepth"].coords)
+
+        layer_dim = " ".join(map(str, list(data[variable].coords)[0:2]))
 
     try:
         cord_sys = cords_to_layers[layer_dim]["coords"]
     except KeyError as exc:
         raise ValueError("Coordinates not recognized.") from exc
-    layer_percentages = np.ma.getdata(cord_sys, False)  # accumulative
+
+    if isinstance(data, netCDF4.Dataset):
+        layer_percentages = np.ma.getdata(cord_sys, False)  # accumulative
+    elif isinstance(data, xr.Dataset):
+        layer_percentages = cord_sys.values  # accumulative
 
     if layer_dim == "FlowLink_xu FlowLink_yu":
         # interpolate
-        x_laydim = np.ma.getdata(data.variables[coords[0]][:], False)
-        y_laydim = np.ma.getdata(data.variables[coords[1]][:], False)
-        points_laydim = np.array([[x, y] for x, y in zip(x_laydim, y_laydim)])
+        if isinstance(data, netCDF4.Dataset):
+            x_laydim = np.ma.getdata(data.variables[coords[0]][:], False)
+            y_laydim = np.ma.getdata(data.variables[coords[1]][:], False)
+            coords_request = str(data.variables[variable].coordinates).split()
+            x_wdim = np.ma.getdata(data.variables[coords_request[0]][:], False)
+            y_wdim = np.ma.getdata(data.variables[coords_request[1]][:], False)
+        elif isinstance(data, xr.Dataset):
+            x_laydim = data[coords[0]].values
+            y_laydim = data[coords[1]].values
+            coords_request = list(data[variable].coords)[0:2]
+            x_wdim = data[coords_request[0]].values
+            y_wdim = data[coords_request[1]].values
 
-        coords_request = str(data.variables[variable].coordinates).split()
-        x_wdim = np.ma.getdata(data.variables[coords_request[0]][:], False)
-        y_wdim = np.ma.getdata(data.variables[coords_request[1]][:], False)
+        points_laydim = np.array([[x, y] for x, y in zip(x_laydim, y_laydim)])
         points_wdim = np.array([[x, y] for x, y in zip(x_wdim, y_wdim)])
 
         bottom_depth_wdim = interp.griddata(points_laydim, bottom_depth, points_wdim)
         water_level_wdim = interp.griddata(points_laydim, waterlevel, points_wdim)
 
         idx_bd = np.where(np.isnan(bottom_depth_wdim))
-
         for i in idx_bd:
             bottom_depth_wdim[i] = interp.griddata(
                 points_laydim, bottom_depth, points_wdim[i], method="nearest"
@@ -332,7 +434,14 @@ def get_layer_data(
             z = [bottom_depth * layer_percentages[layer_index]]
     waterdepth = np.append(waterdepth, z)
 
-    time = np.ma.getdata(data.variables["time"][time_index], False) * np.ones(len(x))
+    if isinstance(data, netCDF4.Dataset):
+        time = np.ma.getdata(data.variables["time"][time_index], False) * np.ones(
+            len(x)
+        )
+    elif isinstance(data, xr.Dataset):
+        time = (data.time.values[time_index] - data.time.values[0]).astype(
+            "timedelta64[s]"
+        ).astype(int) * np.ones(len(x))
 
     index = np.arange(0, len(time))
     layer_data = xr.Dataset(
@@ -534,8 +643,10 @@ def variable_interpolation(
                 f"If a string, points must be cells or faces. Got {points}"
             )
 
-    if not isinstance(data, netCDF4.Dataset):
-        raise TypeError(f"data must be netCDF4 object. Got {type(data)}")
+    if not isinstance(data, (netCDF4.Dataset, xr.Dataset)):
+        raise TypeError(
+            f"data must be netCDF4 or xarray Dataset object. Got {type(data)}"
+        )
 
     if not isinstance(to_pandas, bool):
         raise TypeError(f"to_pandas must be of type bool. Got: {type(to_pandas)}")
@@ -583,8 +694,12 @@ def variable_interpolation(
     return transformed_data
 
 
+# pylint: disable=possibly-used-before-assignment
 def get_all_data_points(
-    data: netCDF4.Dataset, variable: str, time_index: int = -1, to_pandas: bool = True
+    data: (netCDF4.Dataset, xr.Dataset),
+    variable: str,
+    time_index: int = -1,
+    to_pandas: bool = True,
 ) -> Union[pd.DataFrame, xr.Dataset]:
     """
     Get data points for a passed variable for all layers at a specified time from
@@ -616,8 +731,8 @@ def get_all_data_points(
     if not isinstance(time_index, int):
         raise TypeError("time_index must be an int")
 
-    if not isinstance(data, netCDF4.Dataset):
-        raise TypeError("data must be NetCDF4 object")
+    if not isinstance(data, (netCDF4.Dataset, xr.Dataset)):
+        raise TypeError("data must be NetCDF4 object or xarray Dataset")
 
     if variable not in data.variables.keys():
         raise ValueError("variable not recognized")
@@ -630,49 +745,110 @@ def get_all_data_points(
         raise ValueError(
             f"time_index must be less than the max time index {max_time_index}"
         )
-
-    if "mesh2d" in variable:
-        cords_to_layers = {
-            "mesh2d_face_x mesh2d_face_y": {
-                "name": "mesh2d_nLayers",
-                "coords": data.variables["mesh2d_layer_sigma"][:],
-            },
-            "mesh2d_edge_x mesh2d_edge_y": {
-                "name": "mesh2d_nInterfaces",
-                "coords": data.variables["mesh2d_interface_sigma"][:],
-            },
-        }
-
-    elif str(data.variables[variable].coordinates) == "FlowElem_xcc FlowElem_ycc":
-        cords_to_layers = {
-            "FlowElem_xcc FlowElem_ycc": {
-                "name": "laydim",
-                "coords": data.variables["LayCoord_cc"][:],
-            },
-            "FlowLink_xu FlowLink_yu": {
-                "name": "wdim",
-                "coords": data.variables["LayCoord_w"][:],
-            },
-        }
-    else:
-        cords_to_layers = {
-            "FlowElem_xcc FlowElem_ycc LayCoord_cc LayCoord_cc": {
-                "name": "laydim",
-                "coords": data.variables["LayCoord_cc"][:],
-            },
-            "FlowLink_xu FlowLink_yu": {
-                "name": "wdim",
-                "coords": data.variables["LayCoord_w"][:],
-            },
-        }
-
-    layer_dim = str(data.variables[variable].coordinates)
+    if isinstance(data, netCDF4.Dataset):
+        if "mesh2d" in variable:
+            cords_to_layers = {
+                "mesh2d_face_x mesh2d_face_y": {
+                    "name": "mesh2d_nLayers",
+                    "coords": data.variables["mesh2d_layer_sigma"][:],
+                },
+                "mesh2d_edge_x mesh2d_edge_y": {
+                    "name": "mesh2d_nInterfaces",
+                    "coords": data.variables["mesh2d_interface_sigma"][:],
+                },
+                "mesh2d_face_x mesh2d_face_y mesh2d_layer_sigma": {
+                    "name": "mesh2d_nLayers",
+                    "coords": data.variables["mesh2d_layer_sigma"][:],
+                },
+            }
+
+        elif str(data.variables[variable].coordinates) == "FlowElem_xcc FlowElem_ycc":
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+        else:
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc LayCoord_cc LayCoord_cc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+
+        layer_dim = str(data.variables[variable].coordinates)
+    elif isinstance(data, xr.Dataset):
+        if "mesh2d" in variable:
+            cords_to_layers = {
+                "mesh2d_face_x mesh2d_face_y": {
+                    "name": "mesh2d_nLayers",
+                    "coords": data.variables["mesh2d_layer_sigma"][:],
+                },
+                "mesh2d_edge_x mesh2d_edge_y": {
+                    "name": "mesh2d_nInterfaces",
+                    "coords": data.variables["mesh2d_interface_sigma"][:],
+                },
+                "mesh2d_face_x mesh2d_face_y mesh2d_layer_sigma": {
+                    "name": "mesh2d_nLayers",
+                    "coords": data.variables["mesh2d_layer_sigma"][:],
+                },
+            }
+            bottom_depth = data["mesh2d_waterdepth"].values[time_index, :]
+            waterlevel = data["mesh2d_s1"].values[time_index, :]
+            coords = list(data["mesh2d_waterdepth"].coords)
+        elif (
+            str(list(data[variable].coords))
+            == "['FlowElem_xcc', 'FlowElem_ycc', 'time']"
+            or str(list(data[variable].coords))
+            == "['FlowLink_xu', 'FlowLink_yu', 'time']"
+        ):
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+            bottom_depth = data["waterdepth"].values[time_index, :]
+            waterlevel = data["s1"].values[time_index, :]
+            coords = list(data["waterdepth"].coords)
+        else:
+            cords_to_layers = {
+                "FlowElem_xcc FlowElem_ycc LayCoord_cc LayCoord_cc": {
+                    "name": "laydim",
+                    "coords": data.variables["LayCoord_cc"][:],
+                },
+                "FlowLink_xu FlowLink_yu": {
+                    "name": "wdim",
+                    "coords": data.variables["LayCoord_w"][:],
+                },
+            }
+            bottom_depth = data["waterdepth"].values[time_index, :]
+            waterlevel = data["s1"].values[time_index, :]
+            coords = list(data["waterdepth"].coords)
+
+        layer_dim = " ".join(map(str, list(data[variable].coords)[0:2]))
 
     try:
         cord_sys = cords_to_layers[layer_dim]["coords"]
     except KeyError as exc:
         raise ValueError("Coordinates not recognized.") from exc
-    layer_percentages = np.ma.getdata(cord_sys, False)
+    if isinstance(data, netCDF4.Dataset):
+        layer_percentages = np.ma.getdata(cord_sys, False)  # accumulative
+    elif isinstance(data, xr.Dataset):
+        layer_percentages = cord_sys.values  # accumulative
 
     x_all = []
     y_all = []
@@ -690,7 +866,7 @@ def get_all_data_points(
         depth_all = np.append(depth_all, layer_data.waterdepth)
         water_level_all = np.append(water_level_all, layer_data.waterlevel)
         v_all = np.append(v_all, layer_data.v)
-        time_all = np.append(time_all, layer_data.time)
+        time_all = np.append(time_all, np.asarray(layer_data.time))
 
     index = np.arange(0, len(time_all))
     all_data = xr.Dataset(
@@ -711,6 +887,7 @@ def get_all_data_points(
     return all_data
 
 
+# pylint: disable=too-many-lines
 def turbulent_intensity(
     data: netCDF4.Dataset,
     points: Union[str, pd.DataFrame, xr.Dataset] = "cells",
@@ -784,8 +961,8 @@ def turbulent_intensity(
             f"value of the max time index {max_time_index}"
         )
 
-    if not isinstance(data, netCDF4.Dataset):
-        raise TypeError("data must be netCDF4 object")
+    if not isinstance(data, (netCDF4.Dataset, xr.Dataset)):
+        raise TypeError("data must be netCDF4 object or xarray Dataset")
 
     for variable in ["turkin1", "ucx", "ucy", "ucz"]:
         if variable not in data.variables.keys():
@@ -852,6 +1029,7 @@ def turbulent_intensity(
     return turbulent_data
 
 
+# pylint: disable=too-many-lines
 def list_variables(data: Union[netCDF4.Dataset, xr.Dataset, xr.DataArray]) -> List[str]:
     """
     List all variables in a DataArray, Dataset, or NetCDF4 Dataset.
@@ -886,3 +1064,52 @@ def list_variables(data: Union[netCDF4.Dataset, xr.Dataset, xr.DataArray]) -> Li
         "data must be a NetCDF4 Dataset, xarray Dataset, or "
         f"xarray DataArray. Got: {type(data)}"
     )
+
+
+# pylint: disable=too-many-lines
+# pylint: disable=superfluous-parens
+def calculate_grid_convergence_index(
+    fine_grid, coarse_grid, refinement_ratio, factor_of_safety=1.25, order=2
+):
+    """
+    Calculate the Grid Convergence Index (GCI) between two grid sizes.
+    https://www.grc.nasa.gov/WWW/wind/valid/tutorial/spatconv.html
+
+    Parameters
+    ----------
+    fine_grid: numpy.ndarray
+        Results from the finer grid.
+    coarse_grid: numpy.ndarray
+        Results from the coarser grid.
+    refinement_ratio: float
+        Refinement ratio between the grids.
+    order: int
+        Order of accuracy (default is 2).
+
+    Returns
+    -------
+    gci: float
+        Grid Convergence Index (GCI).
+    """
+
+    # Validate inputs
+    if not (np.issubdtype(type(refinement_ratio), np.number)):
+        raise TypeError("refinement_ratio must be a numeric values")
+    if not (np.issubdtype(type(factor_of_safety), np.number)):
+        raise TypeError("factor_of_safety must be a numeric values")
+    if not (np.issubdtype(type(order), np.number)):
+        raise TypeError("order must be a numeric values")
+    if not (
+        np.issubdtype(fine_grid.dtype, np.number)
+        and np.issubdtype(coarse_grid.dtype, np.number)
+    ):
+        raise TypeError("fine_grid and coarse_grid must contain numeric values")
+    if fine_grid.shape != coarse_grid.shape:
+        raise ValueError("fine_grid and coarse_grid must have the same shape")
+
+    # Calculate the approximate relative error
+    error = np.abs((fine_grid - coarse_grid) / fine_grid)
+
+    # Calculate the GCI
+    gci = (factor_of_safety * error) / (refinement_ratio**order - 1)
+    return gci
diff --git a/mhkit/tests/acoustics/test_analysis.py b/mhkit/tests/acoustics/test_analysis.py
index ce792fb3b..b60f5f91f 100644
--- a/mhkit/tests/acoustics/test_analysis.py
+++ b/mhkit/tests/acoustics/test_analysis.py
@@ -52,7 +52,8 @@ def test_sound_pressure_spectral_density(self):
         self.assertIn("freq", spsd.dims)
         self.assertIn("time", spsd.dims)
         self.assertEqual(spsd.attrs["units"], "Pa^2/Hz")
-        self.assertEqual(spsd.attrs["nbin"], f"{bin_length} s")
+        self.assertEqual(spsd.attrs["bin_length"], bin_length)
+        self.assertEqual(spsd.attrs["n_fft"], bin_length * fs)
 
         # Calculate expected number of segments
         overlap = 0.0
diff --git a/mhkit/tests/acoustics/test_io.py b/mhkit/tests/acoustics/test_io.py
index 59e708d90..8d4642a4b 100644
--- a/mhkit/tests/acoustics/test_io.py
+++ b/mhkit/tests/acoustics/test_io.py
@@ -53,10 +53,10 @@ def test_calculate_voltage_and_time(self):
         np.testing.assert_allclose(raw_voltage, expected_raw_voltage, atol=1e-6)
 
         # Expected time array
-        time_interval = pd.Timedelta(seconds=1 / fs)
-        expected_time = pd.date_range(
-            start=start_time, periods=len(raw) + 1, freq=time_interval
+        end_time = np.datetime64(start_time) + np.timedelta64(
+            raw.size * 1000000000, "ns"
         )
+        expected_time = pd.date_range(start_time, end_time, raw.size + 1)
         pd.testing.assert_index_equal(time, expected_time)
 
     def test_read_iclisten_metadata(self):
diff --git a/mhkit/tests/conftest.py b/mhkit/tests/conftest.py
new file mode 100644
index 000000000..1f49e55a4
--- /dev/null
+++ b/mhkit/tests/conftest.py
@@ -0,0 +1,7 @@
+"""Shared pytest configuration for the MHKiT test suite."""
+
+import matplotlib
+
+# Use the non-interactive Agg backend so figure/animation tests run headlessly
+# on every OS (Windows otherwise picks TkAgg and fails without Tcl/Tk).
+matplotlib.use("Agg")
diff --git a/mhkit/tests/dolfyn/base.py b/mhkit/tests/dolfyn/base.py
index 8d74d7f3d..d03fbe8bf 100644
--- a/mhkit/tests/dolfyn/base.py
+++ b/mhkit/tests/dolfyn/base.py
@@ -29,18 +29,22 @@ def assert_allclose(dat0, dat1, *args, **kwargs):
             names.append(v)
     # Check coords and data_vars
     _assert_allclose(dat0, dat1, *args, **kwargs)
+    # If test debugging
+    for v in names:
+        dat0[v] = time.epoch2dt64(dat0[v])
+        dat1[v] = time.epoch2dt64(dat1[v])
+
     # Check attributes
     mismatch = []
     for nm in dat0.attrs:
         # Ignore datatype
-        if str(dat0.attrs[nm]) != str(dat1.attrs[nm]):
+        if nm in dat1.attrs:
+            if str(dat0.attrs[nm]) != str(dat1.attrs[nm]):
+                mismatch.append(nm)
+        else:
             mismatch.append(nm)
     if mismatch:
         raise ValueError(f"The following attributes do not match: {mismatch}.")
-    # If test debugging
-    for v in names:
-        dat0[v] = time.epoch2dt64(dat0[v])
-        dat1[v] = time.epoch2dt64(dat1[v])
 
 
 def load_netcdf(name, *args, **kwargs):
diff --git a/mhkit/tests/dolfyn/test_read_adp.py b/mhkit/tests/dolfyn/test_read_adp.py
index c1d37b92b..1ac29179f 100644
--- a/mhkit/tests/dolfyn/test_read_adp.py
+++ b/mhkit/tests/dolfyn/test_read_adp.py
@@ -29,6 +29,8 @@
 dat_awac = load("AWAC_test01.nc")
 dat_awac_ud = load("AWAC_test01_ud.nc")
 dat_hwac = load("H-AWAC_test01.nc")
+dat_aqd = load("AQD_test01.nc")
+dat_aqd_hr = load("AQD_HR.nc")
 dat_sig = load("BenchFile01.nc")
 dat_sig_i = load("Sig1000_IMU.nc")
 dat_sig_i_ud = load("Sig1000_IMU_ud.nc")
@@ -136,16 +138,22 @@ def test_io_nortek(self):
             td_awac = read("AWAC_test01.wpr", userdata=False, nens=[0, nens])
         td_awac_ud = read("AWAC_test01.wpr", nens=nens)
         td_hwac = read("H-AWAC_test01.wpr")
+        td_aqd = read("AQD_test01.prf")
+        td_aqd_hr = read("AQD_HR.prf")
 
         if make_data:
             save(td_awac, "AWAC_test01.nc")
             save(td_awac_ud, "AWAC_test01_ud.nc")
             save(td_hwac, "H-AWAC_test01.nc")
+            save(td_aqd, "AQD_test01.nc")
+            save(td_aqd_hr, "AQD_HR.nc")
             return
 
         assert_allclose(td_awac, dat_awac, atol=1e-6)
         assert_allclose(td_awac_ud, dat_awac_ud, atol=1e-6)
         assert_allclose(td_hwac, dat_hwac, atol=1e-6)
+        assert_allclose(td_aqd, dat_aqd, atol=1e-6)
+        assert_allclose(td_aqd_hr, dat_aqd_hr, atol=1e-6)
 
     def test_io_nortek2(self):
         nens = 100
diff --git a/mhkit/tests/river/test_io_d3d.py b/mhkit/tests/river/test_io_d3d.py
index f41ba4962..810ba2bc8 100644
--- a/mhkit/tests/river/test_io_d3d.py
+++ b/mhkit/tests/river/test_io_d3d.py
@@ -10,7 +10,6 @@
 import netCDF4
 import os
 
-
 testdir = dirname(abspath(__file__))
 plotdir = join(testdir, "plots")
 isdir = os.path.isdir(plotdir)
@@ -26,6 +25,7 @@ def setUpClass(self):
 
         filename = "turbineTest_map.nc"
         self.d3d_flume_data = netCDF4.Dataset(join(d3ddatadir, filename))
+        self.d3d_flume_data_xr = xr.open_dataset(join(d3ddatadir, filename))
 
     @classmethod
     def tearDownClass(self):
@@ -33,24 +33,33 @@ def tearDownClass(self):
 
     def test_get_all_time(self):
         data = self.d3d_flume_data
+        data_xr = self.d3d_flume_data_xr
         seconds_run = river.io.d3d.get_all_time(data)
+        seconds_run_xr = river.io.d3d.get_all_time(data_xr)
         seconds_run_expected = np.ndarray(
             shape=(5,), buffer=np.array([0, 60, 120, 180, 240]), dtype=int
         )
         np.testing.assert_array_equal(seconds_run, seconds_run_expected)
+        np.testing.assert_array_equal(seconds_run_xr, seconds_run_expected)
 
     def test_convert_time(self):
         data = self.d3d_flume_data
+        data_xr = self.d3d_flume_data_xr
         time_index = 2
         seconds_run = river.io.d3d.index_to_seconds(data, time_index=time_index)
+        seconds_run_xr = river.io.d3d.index_to_seconds(data_xr, time_index=time_index)
         seconds_run_expected = 120
         self.assertEqual(seconds_run, seconds_run_expected)
+        self.assertEqual(seconds_run_xr, seconds_run_expected)
         seconds_run = 60
         time_index = river.io.d3d.seconds_to_index(data, seconds_run=seconds_run)
+        time_index_xr = river.io.d3d.seconds_to_index(data_xr, seconds_run=seconds_run)
         time_index_expected = 1
         self.assertEqual(time_index, time_index_expected)
+        self.assertEqual(time_index_xr, time_index_expected)
         seconds_run = 62
         time_index = river.io.d3d.seconds_to_index(data, seconds_run=seconds_run)
+        time_index_xr = river.io.d3d.seconds_to_index(data_xr, seconds_run=seconds_run)
         time_index_expected = 1
         output_expected = f"ERROR: invalid seconds_run. Closest seconds_run found {time_index_expected}"
         self.assertWarns(UserWarning)
@@ -60,13 +69,17 @@ def test_convert_time_from_tidal(self):
         Test the conversion of time from using tidal import of d3d
         """
         data = self.d3d_flume_data
+        data_xr = self.d3d_flume_data_xr
         time_index = 2
         seconds_run = tidal.io.d3d.index_to_seconds(data, time_index=time_index)
+        seconds_run_xr = tidal.io.d3d.index_to_seconds(data_xr, time_index=time_index)
         seconds_run_expected = 120
         self.assertEqual(seconds_run, seconds_run_expected)
+        self.assertEqual(seconds_run_xr, seconds_run_expected)
 
     def test_layer_data(self):
         data = self.d3d_flume_data
+        data_xr = self.d3d_flume_data_xr
         variable = ["ucx", "s1"]
         for var in variable:
             layer = 2
@@ -77,10 +90,27 @@ def test_layer_data(self):
             layer_data_expected = river.io.d3d.get_layer_data(
                 data, var, layer_compare, time_index_compare
             )
-
             assert_array_almost_equal(layer_data.x, layer_data_expected.x, decimal=2)
             assert_array_almost_equal(layer_data.y, layer_data_expected.y, decimal=2)
             assert_array_almost_equal(layer_data.v, layer_data_expected.v, decimal=2)
+        for var in variable:
+            layer = 2
+            time_index = 3
+            layer_data_xr = river.io.d3d.get_layer_data(data_xr, var, layer, time_index)
+            layer_compare = 2
+            time_index_compare = 4
+            layer_data_expected_xr = river.io.d3d.get_layer_data(
+                data_xr, var, layer_compare, time_index_compare
+            )
+            assert_array_almost_equal(
+                layer_data_xr.x, layer_data_expected_xr.x, decimal=2
+            )
+            assert_array_almost_equal(
+                layer_data_xr.y, layer_data_expected_xr.y, decimal=2
+            )
+            assert_array_almost_equal(
+                layer_data_xr.v, layer_data_expected_xr.v, decimal=2
+            )
 
     def test_create_points_three_points(self):
         """
@@ -209,6 +239,32 @@ def test_variable_interpolation(self):
             np.size(transformes_data["ucx"]), np.size(transformes_data["turkin1"])
         )
 
+    def test_variable_interpolation_xr(self):
+        data_xr = self.d3d_flume_data_xr
+        variables = ["ucx", "turkin1"]
+        transformes_data = river.io.d3d.variable_interpolation(
+            data_xr, variables, points="faces", edges="nearest"
+        )
+        self.assertEqual(
+            np.size(transformes_data["ucx"]), np.size(transformes_data["turkin1"])
+        )
+        transformes_data = river.io.d3d.variable_interpolation(
+            data_xr, variables, points="cells", edges="nearest"
+        )
+        self.assertEqual(
+            np.size(transformes_data["ucx"]), np.size(transformes_data["turkin1"])
+        )
+        x = np.linspace(1, 3, num=3)
+        y = np.linspace(1, 3, num=3)
+        waterdepth = 1
+        points = river.io.d3d.create_points(x, y, waterdepth)
+        transformes_data = river.io.d3d.variable_interpolation(
+            data_xr, variables, points=points
+        )
+        self.assertEqual(
+            np.size(transformes_data["ucx"]), np.size(transformes_data["turkin1"])
+        )
+
     def test_get_all_data_points(self):
         data = self.d3d_flume_data
         variable = "ucx"
@@ -222,6 +278,19 @@ def test_get_all_data_points(self):
         size_output_expected = np.size(output_expected)
         self.assertEqual(size_output, size_output_expected)
 
+    def test_get_all_data_points_xr(self):
+        data_xr = self.d3d_flume_data_xr
+        variable = "ucx"
+        time_step = 3
+        output = river.io.d3d.get_all_data_points(data_xr, variable, time_step)
+        size_output = np.size(output)
+        time_step_compair = 4
+        output_expected = river.io.d3d.get_all_data_points(
+            data_xr, variable, time_step_compair
+        )
+        size_output_expected = np.size(output_expected)
+        self.assertEqual(size_output, size_output_expected)
+
     def test_unorm(self):
         x = np.linspace(1, 3, num=3)
         y = np.linspace(1, 3, num=3)
@@ -236,6 +305,7 @@ def test_unorm(self):
 
     def test_turbulent_intensity(self):
         data = self.d3d_flume_data
+        data_xr = self.d3d_flume_data_xr
         time_index = -1
         x_test = np.linspace(1, 17, num=10)
         y_test = np.linspace(3, 3, num=10)
@@ -250,7 +320,7 @@ def test_turbulent_intensity(self):
         points = pd.DataFrame(test_points, columns=["x", "y", "waterdepth"])
 
         TI = river.io.d3d.turbulent_intensity(data, points, time_index)
-
+        TI_xr = river.io.d3d.turbulent_intensity(data_xr, points, time_index)
         TI_vars = ["turkin1", "ucx", "ucy", "ucz"]
         TI_data_raw = {}
         for var in TI_vars:
@@ -284,12 +354,16 @@ def test_turbulent_intensity(self):
         assert_array_almost_equal(
             TI.turbulent_intensity, turbulent_intensity_expected, decimal=2
         )
-
+        assert_array_almost_equal(
+            TI_xr.turbulent_intensity, turbulent_intensity_expected, decimal=2
+        )
         TI = river.io.d3d.turbulent_intensity(data, points="faces")
+        TI_xr = river.io.d3d.turbulent_intensity(data_xr, points="faces")
         TI_size = np.size(TI["turbulent_intensity"])
         turkin1 = river.io.d3d.get_all_data_points(data, "turkin1", time_index)
         turkin1_size = np.size(turkin1["turkin1"])
         self.assertEqual(TI_size, turkin1_size)
+        self.assertEqual(TI_size, np.size(TI_xr["turbulent_intensity"]))
 
         TI = river.io.d3d.turbulent_intensity(data, points="cells")
         TI_size = np.size(TI["turbulent_intensity"])
@@ -297,6 +371,15 @@ def test_turbulent_intensity(self):
         ucx_size = np.size(ucx["ucx"])
         self.assertEqual(TI_size, ucx_size)
 
+    def test_calculate_grid_convergence_index(self):
+        fine_grid = np.array([1.0, 2.0, 3.0])
+        coarse_grid = np.array([0.5, 1.5, 2.5])
+        refinement_ratio = 2.0
+        gci = river.io.d3d.calculate_grid_convergence_index(
+            fine_grid, coarse_grid, refinement_ratio
+        )
+        assert_array_almost_equal(gci, np.array([0.2083, 0.1042, 0.0694]), decimal=3)
+
 
 if __name__ == "__main__":
     unittest.main()
diff --git a/mhkit/tests/wave/io/test_cdip.py b/mhkit/tests/wave/io/test_cdip.py
index 17d1bc2ad..dd5a798a5 100644
--- a/mhkit/tests/wave/io/test_cdip.py
+++ b/mhkit/tests/wave/io/test_cdip.py
@@ -7,7 +7,6 @@
 import pytz
 import os
 
-
 testdir = dirname(abspath(__file__))
 datadir = normpath(join(testdir, "..", "..", "..", "..", "examples", "data", "wave"))
 
@@ -130,18 +129,18 @@ def test_request_parse_workflow_multiyear(self):
         expected_index_final = datetime(year2, 12, 31)
 
         wave1D = data["data"]["wave"]
-        self.assertEqual(wave1D.index[0].floor("d").to_pydatetime(), expected_index0)
+        self.assertEqual(wave1D.index[0].floor("D").to_pydatetime(), expected_index0)
 
         self.assertEqual(
-            wave1D.index[-1].floor("d").to_pydatetime(), expected_index_final
+            wave1D.index[-1].floor("D").to_pydatetime(), expected_index_final
         )
 
         for key, wave2D in data["data"]["wave2D"].items():
             self.assertEqual(
-                wave2D.index[0].floor("d").to_pydatetime(), expected_index0
+                wave2D.index[0].floor("D").to_pydatetime(), expected_index0
             )
             self.assertEqual(
-                wave2D.index[-1].floor("d").to_pydatetime(), expected_index_final
+                wave2D.index[-1].floor("D").to_pydatetime(), expected_index_final
             )
 
     def test_plot_boxplot(self):
diff --git a/mhkit/tests/wave/io/test_ndbc.py b/mhkit/tests/wave/io/test_ndbc.py
index aa5b86a96..bee861732 100644
--- a/mhkit/tests/wave/io/test_ndbc.py
+++ b/mhkit/tests/wave/io/test_ndbc.py
@@ -11,7 +11,6 @@
 import unittest
 import os
 
-
 testdir = dirname(abspath(__file__))
 datadir = normpath(join(testdir, "..", "..", "..", "..", "examples", "data", "wave"))
 
@@ -100,8 +99,27 @@ def tearDownClass(self):
     # Realtime data
     def test_ndbc_read_realtime_met(self):
         data, units = wave.io.ndbc.read_file(join(datadir, "46097.txt"))
+        cd = np.array(
+            [
+                180,
+                12.0,
+                np.nan,
+                np.nan,
+                np.nan,
+                np.nan,
+                np.nan,
+                1001.0,
+                6.1,
+                10.9,
+                np.nan,
+                np.nan,
+                np.nan,
+                np.nan,
+            ],
+        )
         expected_index0 = datetime(2019, 4, 2, 13, 50)
         self.assertSetEqual(set(data.columns), set(self.expected_columns_metRT))
+        np.testing.assert_equal(data.iloc[-1].astype(float).values, cd)
         self.assertEqual(data.index[0], expected_index0)
         self.assertEqual(data.shape, (6490, 14))
         self.assertEqual(units, self.expected_units_metRT)
@@ -110,8 +128,26 @@ def test_ndbc_read_realtime_met(self):
     def test_ndbnc_read_historical_met(self):
         # QC'd monthly data, Aug 2019
         data, units = wave.io.ndbc.read_file(join(datadir, "46097h201908qc.txt"))
+        cd = np.array(
+            [
+                160.0,
+                2.7,
+                np.nan,
+                np.nan,
+                np.nan,
+                np.nan,
+                np.nan,
+                1014.9,
+                14.5,
+                13.4,
+                np.nan,
+                np.nan,
+                np.nan,
+            ]
+        )
         expected_index0 = datetime(2019, 8, 1, 0, 0)
         self.assertSetEqual(set(data.columns), set(self.expected_columns_metH))
+        np.testing.assert_equal(data.iloc[-1].astype(float).values, cd)
         self.assertEqual(data.index[0], expected_index0)
         self.assertEqual(data.shape, (4464, 13))
         self.assertEqual(units, self.expected_units_metH)
@@ -127,14 +163,34 @@ def test_ndbc_read_spectral(self):
     def test_ndbc_read_cwind_no_units(self):
         data, units = wave.io.ndbc.read_file(join(datadir, "42a01c2003.txt"))
         self.assertEqual(data.shape, (4320, 5))
+        cd = np.array(
+            [
+                [168.0, 6.1, np.nan, np.nan, np.nan],
+                [153.0, 5.6, np.nan, np.nan, np.nan],
+                [149.0, 4.8, np.nan, np.nan, np.nan],
+                [147.0, 4.1, np.nan, np.nan, np.nan],
+                [151.0, 4.1, 169.0, np.nan, np.nan],
+            ]
+        )
+        np.testing.assert_equal(data.tail().values, cd)
         self.assertEqual(units, None)
 
     def test_ndbc_read_cwind_units(self):
         data, units = wave.io.ndbc.read_file(join(datadir, "46002c2016.txt"))
         self.assertEqual(data.shape, (28468, 5))
-        self.assertEqual(units, wave.io.ndbc.parameter_units("cwind"))
+        cd = np.array(
+            [
+                [303.0, 6.2, np.nan, np.nan, np.nan],
+                [306.0, 7.8, np.nan, np.nan, np.nan],
+                [302.0, 7.6, np.nan, np.nan, np.nan],
+                [293.0, 6.4, np.nan, np.nan, np.nan],
+                [287.0, 6.3, 307.0, 9.7, 1819.0],
+            ]
+        )
+        np.testing.assert_equal(data.tail().values, cd)
 
     def test_ndbc_available_data(self):
+        # Can't test data values because datafiles are periodically updating
         data = wave.io.ndbc.available_data("swden", buoy_number="46029")
         cols = data.columns.tolist()
         exp_cols = ["id", "year", "filename"]
@@ -158,14 +214,18 @@ def test__ndbc_parse_filenames(self):
         self.assertListEqual(fnames, self.filenames)
 
     def test_ndbc_request_data(self):
+        # Can't test data values because datafiles are periodically updating
         filenames = pd.Series(self.filenames[0])
         ndbc_data = wave.io.ndbc.request_data("swden", filenames, to_pandas=False)
         self.assertTrue(xr.Dataset(self.swden).equals(ndbc_data["1996"]))
 
     def test_ndbc_request_data_from_dataframe(self):
+        # Can't test data values because datafiles are periodically updating
         filenames = pd.DataFrame(pd.Series(data=self.filenames[0]))
         ndbc_data = wave.io.ndbc.request_data("swden", filenames)
-        assert_frame_equal(self.swden, ndbc_data["1996"])
+        assert_frame_equal(
+            self.swden, ndbc_data["1996"], check_column_type=False, check_dtype=False
+        )
 
     def test_ndbc_request_data_filenames_length(self):
         with self.assertRaises(ValueError):
@@ -221,9 +281,10 @@ def test_ndbc_date_string_to_datetime(self):
     def test_ndbc_parameter_units(self):
         parameter = "swden"
         units = wave.io.ndbc.parameter_units(parameter)
-        self.assertEqual(units[parameter], "(m*m)/Hz")
+        self.assertEqual(units[parameter], "m^2/Hz")
 
     def test_ndbc_request_directional_data(self):
+        # Can't test data values because datafiles are periodically updating
         data = self.directional_data
         # correct 5 parameters
         self.assertEqual(len(data), 5)
@@ -236,12 +297,14 @@ def test_ndbc_request_directional_data(self):
         self.assertEqual(len(data.frequency), 47)
 
     def test_ndbc_create_spread_function(self):
+        # Can't test data values because datafiles are periodically updating
         directions = np.arange(0, 360, 2.0)
         spread = wave.io.ndbc.create_spread_function(self.directional_data, directions)
         self.assertEqual(spread.shape, (47, 180))
         self.assertEqual(spread.units, "1/Hz/deg")
 
     def test_ndbc_create_directional_spectrum(self):
+        # Can't test data values because datafiles are periodically updating
         directions = np.arange(0, 360, 2.0)
         spectrum = wave.io.ndbc.create_directional_spectrum(
             self.directional_data, directions
@@ -250,6 +313,7 @@ def test_ndbc_create_directional_spectrum(self):
         self.assertEqual(spectrum.units, "m^2/Hz/deg")
 
     def test_plot_directional_spectrum(self):
+        # Can't test data values because datafiles are periodically updating
         directions = np.arange(0, 360, 2.0)
         spectrum = wave.io.ndbc.create_spread_function(
             self.directional_data, directions
@@ -293,8 +357,13 @@ def test_get_buoy_metadata(self):
             metadata["provider"], "Owned and maintained by National Data Buoy Center"
         )
         self.assertEqual(metadata["type"], "3-meter foam buoy w/ seal cage")
-        self.assertAlmostEqual(float(metadata["lat"]), 36.785)
-        self.assertAlmostEqual(float(metadata["lon"]), 122.396)
+        # NDBC 46042 is a deployed buoy that drifts within its watch
+        # circle, so the NDBC output position can drift over time (observed
+        # lat 36.785 -> 36.787, lon 122.396 -> 122.408). Use a loose tolerance
+        # that tracks the buoy's nominal location without failing on real
+        # movement, while still catching large parsing errors.
+        self.assertAlmostEqual(float(metadata["lat"]), 36.785, delta=0.05)
+        self.assertAlmostEqual(float(metadata["lon"]), 122.396, delta=0.05)
         self.assertEqual(metadata["Site elevation"], "sea level")
 
     def test_get_buoy_metadata_invalid_station(self):
diff --git a/mhkit/utils/cache.py b/mhkit/utils/cache.py
index c4897c12c..78744dbf8 100644
--- a/mhkit/utils/cache.py
+++ b/mhkit/utils/cache.py
@@ -119,7 +119,11 @@ def _load_cache(file_extension, cache_filepath):
             )
         elif file_extension == ".pkl":
             with open(cache_filepath, "rb") as f:
-                data, metadata = pickle.load(f)
+                data_dict = pickle.load(f)  # some format of 'data' and 'metadata'
+                if isinstance(data_dict, tuple):
+                    # CDIP and WPTO hindcast call returns size 2 tuple
+                    return data_dict[0], data_dict[1]
+                data, metadata = data_dict["data"], data_dict["metadata"]
 
         return data, metadata
 
@@ -154,7 +158,8 @@ def _write_cache(data, metadata, file_extension, cache_filepath):
     if os.path.isfile(cache_filepath) and (
         cache_content is None or cache_content["data"] is None
     ):
-        return _load_cache(file_extension, cache_filepath) + (cache_filepath,)
+        data, metadata = _load_cache(file_extension, cache_filepath)
+        return data, metadata, cache_filepath
 
     # Store data in cache if provided
     if cache_content and cache_content["data"] is not None:
diff --git a/mhkit/utils/upcrossing.py b/mhkit/utils/upcrossing.py
index 7ab06a0ed..c48e18cc5 100644
--- a/mhkit/utils/upcrossing.py
+++ b/mhkit/utils/upcrossing.py
@@ -93,7 +93,9 @@ def upcrossing(t: np.ndarray, data: np.ndarray) -> np.ndarray:
 
     # eliminate zeros
     zero_mask = data == 0
-    data[zero_mask] = 0.5 * np.min(np.abs(data))
+    if any(zero_mask):
+        # avoid double counting zeros by making them small and positive
+        data[zero_mask] = 0.5 * np.min(np.abs(data))
 
     # zero up-crossings
     diff = np.diff(np.sign(data))
diff --git a/mhkit/wave/graphics.py b/mhkit/wave/graphics.py
index b54c18413..f6d0bfd8c 100644
--- a/mhkit/wave/graphics.py
+++ b/mhkit/wave/graphics.py
@@ -935,6 +935,9 @@ def plot_directional_spectrum(
 
     a, f = np.meshgrid(np.deg2rad(spectrum.direction), spectrum.frequency)
     _, ax = plt.subplots(subplot_kw=dict(projection="polar"))
+    # Set 0 degrees to be at the top, and positive angles to be clockwise
+    ax.set_theta_zero_location("N")
+    ax.set_theta_direction(-1)
     tmp = np.floor(np.min(spectrum.data) * 10) / 10
     color_level_min = tmp if (color_level_min is None) else color_level_min
     color_level_max = np.ceil(np.max(spectrum.data) * 10) / 10
diff --git a/mhkit/wave/io/ndbc.py b/mhkit/wave/io/ndbc.py
index 5fbad8ef8..bbcc29d89 100644
--- a/mhkit/wave/io/ndbc.py
+++ b/mhkit/wave/io/ndbc.py
@@ -19,8 +19,40 @@
     convert_nested_dict_and_pandas,
 )
 
-# Set pandas option to opt-in to future behavior
-pd.set_option("future.no_silent_downcasting", True)
+
+def replace_pandas_missing_values_with_nan(data, missing_values):
+    """
+    Replace missing values with NaN without silently downcasting dtypes.
+
+    Parameters
+    ------------
+    data: pandas DataFrame
+        Data in which to replace missing values
+
+    missing_values: list of values
+        List of values that denote missing data
+
+    Returns
+    ---------
+    data: pandas DataFrame
+        Data with missing values replaced by NaN and object columns converted
+        to their best-fit dtypes
+
+    Notes
+    -----
+    pandas versions above 2.x do not silently downcast in ``replace`` and
+    dropped the ``future.no_silent_downcasting`` option. On pandas 2.x the same
+    forward-looking behavior is opted into so the result is identical across
+    supported pandas versions and no deprecation warning is emitted.
+    ``infer_objects`` then converts the resulting object columns explicitly.
+    """
+    pandas_major = int(pd.__version__.split(".")[0])
+    if pandas_major <= 2:
+        with pd.option_context("future.no_silent_downcasting", True):
+            data = data.replace(missing_values, np.nan)
+    else:
+        data = data.replace(missing_values, np.nan)
+    return data.infer_objects()
 
 
 def read_file(file_name, missing_values=["MM", 9999, 999, 99], to_pandas=True):
@@ -57,7 +89,13 @@ def read_file(file_name, missing_values=["MM", 9999, 999, 99], to_pandas=True):
     metadata: dict or None
         Dictionary with {column name: units} key value pairs when the NDBC file
         contains unit information, otherwise None is returned
+
+    Notes
+    -----
+    NDBC documentation of measurement descriptions and units can be found here:
+    https://www.ndbc.noaa.gov/faq/measdes.shtml
     """
+
     if not isinstance(file_name, str):
         raise TypeError(f"file_name must be of type str. Got: {type(file_name)}")
     if not isinstance(missing_values, list):
@@ -147,8 +185,7 @@ def read_file(file_name, missing_values=["MM", 9999, 999, 99], to_pandas=True):
         data.columns = data.columns
 
     # Replace indicated missing values with nan
-    data = data.replace(missing_values, np.nan)
-    data = data.infer_objects(copy=False)
+    data = replace_pandas_missing_values_with_nan(data, missing_values)
 
     if not to_pandas:
         data = convert_to_dataset(data)
@@ -710,9 +747,9 @@ def parameter_units(parameter=""):
         }
     elif parameter == "cwind":
         units = {
-            "WDIR": "degT",
+            "WDIR": "degT",  # degree True North
             "WSPD": "m/s",
-            "GDR": "degT",
+            "GDR": "degT",  # degree True North
             "GST": "m/s",
             "GTIME": "hhmm",
         }
@@ -764,10 +801,10 @@ def parameter_units(parameter=""):
             "WWH": "m",
             "WWP": "sec",
             "SwD": "-",
-            "WWD": "degT",
+            "WWD": "degT",  # degree True North
             "STEEPNESS": "-",
             "APD": "sec",
-            "MWD": "degT",
+            "MWD": "degT",  # degree True North
         }
     elif parameter == "srad":
         units = {
@@ -777,13 +814,13 @@ def parameter_units(parameter=""):
         }
     elif parameter == "stdmet":
         units = {
-            "WDIR": "degT",
+            "WDIR": "degT",  # degree True North
             "WSPD": "m/s",
             "GST": "m/s",
             "WVHT": "m",
             "DPD": "sec",
             "APD": "sec",
-            "MWD": "degT",
+            "MWD": "degT",  # degree True North
             "PRES": "hPa",
             "ATMP": "degC",
             "WTMP": "degC",
@@ -797,11 +834,11 @@ def parameter_units(parameter=""):
             "PRES": "hPa",
             "PTIME": "hhmm",
             "WSPD": "m/s",
-            "WDIR": "degT",
+            "WDIR": "degT",  # degree True North
             "WTIME": "hhmm",
         }
     elif parameter == "swden":
-        units = {"swden": "(m*m)/Hz"}
+        units = {"swden": "m^2/Hz"}
     elif parameter == "swdir":
         units = {"swdir": "deg"}
     elif parameter == "swdir2":
@@ -812,13 +849,13 @@ def parameter_units(parameter=""):
         units = {"swr2": ""}
     else:
         units = {
-            "swden": "(m*m)/Hz",
+            "swden": "m^2/Hz",
             "PRES": "hPa",
             "PTIME": "hhmm",
-            "WDIR": "degT",
+            "WDIR": "degT",  # degree True North
             "WTIME": "hhmm",
             "DPD": "sec",
-            "MWD": "degT",
+            "MWD": "degT",  # degree True North
             "ATMP": "degC",
             "WTMP": "degC",
             "DEWP": "degC",
@@ -834,7 +871,7 @@ def parameter_units(parameter=""):
             "WWH": "m",
             "WWP": "sec",
             "SwD": "-",
-            "WWD": "degT",
+            "WWD": "degT",  # degree True North
             "STEEPNESS": "-",
             "APD": "sec",
             "RATE": "mm/h",
@@ -859,7 +896,7 @@ def parameter_units(parameter=""):
             "WSPD20": "m/s",
             "T": "-",
             "HEIGHT": "m",
-            "GDR": "degT",
+            "GDR": "degT",  # degree True North
             "GST": "m/s",
             "GTIME": "hhmm",
             "DEP01": "m",
@@ -1026,7 +1063,7 @@ def request_directional_data(buoy, year):
 
     data_dict["swden"].attrs = {
         "units": "m^2/Hz",
-        "long_name": "omnidirecational spectrum",
+        "long_name": "omnidirectional spectrum",
         "standard_name": "S",
         "description": "Omnidirectional *sea surface elevation variance (m^2)* spectrum (/Hz).",
     }
@@ -1062,7 +1099,7 @@ def request_directional_data(buoy, year):
     return xr.Dataset(data_dict)
 
 
-def _create_spectrum(data, frequencies, directions, name, units):
+def _create_spectrum_dataarray(data, frequencies, directions, name, units):
     """
     Create an xarray.DataArray for storing spectrum data with correct
     dimensions, coordinates, names, and units.
@@ -1166,16 +1203,18 @@ def create_spread_function(data, directions):
 
     r1 = data["swr1"].data.reshape(-1, 1)
     r2 = data["swr2"].data.reshape(-1, 1)
+    # a1 = degrees CW from N, according to NDBC documentation
     a1 = data["swdir"].data.reshape(-1, 1)
+    # a2 degrees CW from N, according to NDBC documentation
     a2 = data["swdir2"].data.reshape(-1, 1)
-    a = directions.reshape(1, -1)
+    a = directions.reshape(1, -1)  # degrees
     spread = (
         1
         / np.pi
         * (0.5 + r1 * np.cos(np.deg2rad(a - a1)) + r2 * np.cos(2 * np.deg2rad(a - a2)))
     )
-    spread = _create_spectrum(
-        spread, data.frequency.values, directions, name="Spread", units="1"
+    spread = _create_spectrum_dataarray(
+        np.rad2deg(spread), data.frequency.values, directions, name="Spread", units="1"
     )
     return spread
 
@@ -1209,9 +1248,9 @@ def create_directional_spectrum(data, directions):
     spread = create_spread_function(data, directions).values
     omnidirectional_spectrum = data["swden"].data.reshape(-1, 1)
     spectrum = omnidirectional_spectrum * spread
-    spectrum = _create_spectrum(
+    spectrum = _create_spectrum_dataarray(
         spectrum,
-        data.frequency.values,
+        data["frequency"].values,
         directions,
         name="Elevation variance",
         units="m^2",
diff --git a/pyproject.toml b/pyproject.toml
index c0c7df262..c9805d480 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -21,10 +21,21 @@ classifiers = [
 ]
 requires-python = ">=3.10"
 dependencies = [
+    # MHKiT-Python uses xarray everywhere, which leverages netcdf and h5 behind the
+    # scenes. xarray, netcdf4, and h5 dependencies should all be synced to avoid
+    # compatibility issues with individual modules.
+    "xarray>=2024.6.0",
+    "netCDF4>=1.6.5",
+    "h5py>=3.11.0",
+    "h5pyd>=0.18.0",
     "numpy>=2.0.0",
     "pandas>=2.2.2",
+    # pandas 3.0+ uses a new string dtype by default and stores it using pyarrow
+    # when pyarrow is installed, otherwise a more limited numpy fallback. pandas
+    # keeps pyarrow optional, so we require it here to always get the reliable
+    # pyarrow storage. pyarrow 16.0.0 is the first version that supports numpy 2.
+    "pyarrow>=16.0.0",
     "scipy>=1.14.0",
-    "xarray>=2024.6.0",
     "matplotlib>=3.9.1",
     "pecos>=0.3.0",
     "requests",
@@ -35,28 +46,22 @@ dependencies = [
 wave = [
     "scikit-learn>=1.5.1",
     "statsmodels>=0.14.2",
-    "netCDF4>=1.7.1.post1",
     "pytz",
     "NREL-rex>=0.2.63",
     "beautifulsoup4",
     "bottleneck",
-    "lxml"
+    "lxml",
 ]
 
 tidal = [
-    "netCDF4>=1.7.1.post1",
-    "bottleneck"
+    "bottleneck",
 ]
 
 river = [
-    "netCDF4>=1.7.1.post1",
     "bottleneck",
 ]
 
 dolfyn = [
-    "h5py>=3.11.0",
-    "h5pyd>=0.18.0",
-    "netCDF4>=1.7.1.post1",
     "cartopy",
 ]
 
@@ -91,11 +96,9 @@ dev = [
     "pytest-cov",
     "pre-commit",
     "coverage",
-    "coveralls"
+    "black",
 ]
 
-
-
 # Install all optional dependencies
 all = [
     "mhkit[wave]",
@@ -119,7 +122,6 @@ examples = [
     "utm",
     "folium",
     "mhkit[all]",
-
 ]
 
 [project.urls]
diff --git a/requirements-dev.txt b/requirements-dev.txt
deleted file mode 100644
index 83e60c9dd..000000000
--- a/requirements-dev.txt
+++ /dev/null
@@ -1,4 +0,0 @@
-# requirements-dev.txt
-black
-pylint
-pytest