diff --git a/.github/workflows/check-wrappers.yml b/.github/workflows/check-wrappers.yml new file mode 100644 index 0000000..24eaf2e --- /dev/null +++ b/.github/workflows/check-wrappers.yml @@ -0,0 +1,32 @@ +name: Check Wrappers + +on: + push: + branches: + - main + pull_request: + +jobs: + check-wrappers: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: "3.10" + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install . + + - name: Generate wrappers + run: | + export PYTHONPATH=$PYTHONPATH:$(pwd)/src + python src/earthkit/climate/generate_wrappers.py + + - name: Check for changes + run: | + git diff --exit-code diff --git a/Makefile b/Makefile deleted file mode 100644 index 24c1f79..0000000 --- a/Makefile +++ /dev/null @@ -1,33 +0,0 @@ -PROJECT := earthkit-climate -CONDA := conda -CONDAFLAGS := -COV_REPORT := html - -default: qa unit-tests -qa: - pre-commit run --all-files - -unit-tests: - python -m pytest -vv --cov=. --cov-report=$(COV_REPORT) --doctest-glob="*.md" --doctest-glob="*.rst" - -type-check: - python -m mypy . --no-namespace-packages - -conda-env-update: - $(CONDA) install -y -c conda-forge conda-merge - $(CONDA) run conda-merge environment.yml ci/environment-ci.yml > ci/combined-environment-ci.yml - $(CONDA) env update $(CONDAFLAGS) -f ci/combined-environment-ci.yml - -docker-build: - docker build -t $(PROJECT) . - -docker-run: - docker run --rm -ti -v $(PWD):/srv $(PROJECT) - -template-update: - pre-commit run --all-files cruft -c .pre-commit-config-cruft.yaml - -docs-build: - cd docs && rm -fr _api && make clean && make html - -# DO NOT EDIT ABOVE THIS LINE, ADD COMMANDS BELOW diff --git a/README.md b/README.md index 541c32e..1b5e8f4 100644 --- a/README.md +++ b/README.md @@ -1,11 +1,45 @@ +

+ + + + +

+ +

+ + ECMWF Software EnginE + + + Maturity Level + + + Licence + + + Latest Release + +

+ +

+ Quick Start + • + Documentation +

+ +> [!IMPORTANT] +> This software is **Emerging** and subject to ECMWF's guidelines on [Software Maturity](https://github.com/ecmwf/codex/raw/refs/heads/main/Project%20Maturity). + # earthkit-climate -**A toolkit for statistical analysis and processing of climate and geospatial data.** +**earthkit-climate** is the package responsible for the climate index calculation within the earthkit ecosystem. It includes a wrapper prototype that allows the use of the `xclim` python package to compute a large amount of pre-defined climate indices used by the climate science community, and to define new ones. + +`xclim` relies heavily on the `xarray` python library and the `numpy` & `scipy` ecosystem. Its main elements are: -`earthkit-climate` provides tools to compute and analyze **climate indicators** (e.g., precipitation, temperature) and perform **unit conversions, percentiles, and provenance tracking**. -It is part of the **Earthkit ecosystem** and designed for reproducible, modular workflows. +- **Climate indices**: available to be directly computed with python functions. The input and output units are defined in these functions by using a decorator and are validated during runtime. +- **Climate indicators**: climate indices wrapped in an object that provides more metadata and validation facilities (health checks) of the input. it includes attributes for CF metadata (cell methods), references, keywords, and more. +- **Lower level process functions**: these include aggregation, computation spell length and counting, optimized computation of reference percentiles, bias correction methods and ensemble statistics. These functions are used by the implemented indices and can also be used to build new indices not included in the library. -______________________________________________________________________ +--- ## Disclaimer @@ -13,7 +47,7 @@ This project is currently in **BETA** and **experimental**. Interfaces, structure, and functionality are subject to change without notice. Do **not** use this software in any operational or production system. -______________________________________________________________________ +--- ## Quick Start @@ -33,14 +67,14 @@ from earthkit.climate.utils import conversions pr = precipitation.simple_daily_intensity(precip_data, freq="monthly") ``` -______________________________________________________________________ +--- ## Documentation For full documentation, including API reference and example notebooks, visit the [earthkit-climate ReadTheDocs page](https://earthkit-climate.readthedocs.io) -______________________________________________________________________ +--- ## Development & Contribution Workflow @@ -52,51 +86,52 @@ It provides fast, reproducible environments and replaces Conda-based workflows. Install Pixi following the [official instructions](https://pixi.sh/latest/#installation), then run: ```bash -pixi install --locked -pixi shell +pixi install ``` This command installs all dependencies as defined in `pyproject.toml` and `pixi.lock`. -### 2. Install the package +### 2. Common Tasks -Inside the Pixi environment: +This project uses `pixi` tasks to manage development workflows, replacing the legacy `Makefile`. -```bash -pip install -e . -``` +- **Quality Assurance**: Run pre-commit hooks to ensure code quality. -### 3. Quality checks and tests + ```bash + pixi run qa + ``` -Before pushing to GitHub, run: +- **Unit Tests**: Run the test suite using pytest. -```bash -make qa -make unit-tests -``` + ```bash + pixi run unit-tests + ``` -You can also perform type checking and integration tests: +- **Type Checking**: Run static type analysis with mypy. -```bash -make type-check -make integration-tests -``` + ```bash + pixi run type-check + ``` -### 4. Documentation +- **Build Documentation**: Build the Sphinx documentation. Note that this task runs in the `docs` environment. -To build the documentation locally (using Sphinx): + ```bash + pixi run -e docs docs-build + ``` -```bash -make docs-build -``` +- **Docker**: Build and run the docker container. -### 5. Optional: Sync with ECMWF template + ```bash + pixi run docker-build + pixi run docker-run + ``` -```bash -make template-update -``` +- **Sync with ECMWF template**: + ```bash + pixi run template-update + ``` -______________________________________________________________________ +--- ## Project Structure @@ -104,12 +139,13 @@ ______________________________________________________________________ earthkit-climate/ ├── src/earthkit/ │ ├── climate/ +│ │ ├── api/ # API wrapper logic │ │ ├── indicators/ # Climate indices (precipitation, temperature, etc.) │ │ └── utils/ # Type conversions, percentiles, provenance │ └── __init__.py ├── tests/ -│ ├── integration/ # Integration tests -│ └── unit/ # Unit tests for indicators and utils +│ ├── unit/ # Unit tests for indicators and utils +│ └── test_00_version.py # Version check ├── docs/ # Sphinx documentation ├── ci/ # Continuous integration configs ├── .github/workflows/ # GitHub Actions (push/release) @@ -117,11 +153,10 @@ earthkit-climate/ ├── pixi.lock # Locked dependency versions ├── Dockerfile # Pixi-based container ├── pyproject.toml # Project configuration -├── Makefile # Developer utilities (Pixi integrated) └── README.md ``` -______________________________________________________________________ +--- ## License diff --git a/docs/_static/earthkit-climate-light.svg b/docs/_static/earthkit-climate-light.svg new file mode 100644 index 0000000..c5438cb --- /dev/null +++ b/docs/_static/earthkit-climate-light.svg @@ -0,0 +1,243 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/docs/conf.py b/docs/conf.py index e372fb1..b09b66c 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -35,7 +35,6 @@ # ones. extensions = [ "autoapi.extension", - "myst_parser", "nbsphinx", "sphinx.ext.autodoc", "sphinx.ext.napoleon", @@ -77,6 +76,7 @@ # a list of builtin themes. # html_theme = "sphinx_rtd_theme" +html_logo = "_static/earthkit-climate-light.svg" # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, diff --git a/docs/development.rst b/docs/development.rst new file mode 100644 index 0000000..6b6362c --- /dev/null +++ b/docs/development.rst @@ -0,0 +1,61 @@ +Development +=========== + +Development & Contribution Workflow +----------------------------------- + +1. Setup environment (with Pixi) +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +This project uses `Pixi `_ for dependency and environment management. +It provides fast, reproducible environments and replaces Conda-based workflows. + +Install Pixi following the `official instructions `_, then run: + +.. code-block:: bash + + pixi install + +This command installs all dependencies as defined in ``pyproject.toml`` and ``pixi.lock``. + +2. Common Tasks +~~~~~~~~~~~~~~~ + +This project uses ``pixi`` tasks to manage development workflows, replacing the legacy ``Makefile``. + +- **Quality Assurance**: Run pre-commit hooks to ensure code quality. + + .. code-block:: bash + + pixi run qa + +- **Unit Tests**: Run the test suite using pytest. + + .. code-block:: bash + + pixi run unit-tests + +- **Type Checking**: Run static type analysis with mypy. + + .. code-block:: bash + + pixi run type-check + +- **Build Documentation**: Build the Sphinx documentation. Note that this task runs in the ``docs`` environment. + + .. code-block:: bash + + pixi run -e docs docs-build + +- **Docker**: Build and run the docker container. + + .. code-block:: bash + + pixi run docker-build + pixi run docker-run + +- **Sync with ECMWF template**: + + .. code-block:: bash + + pixi run template-update diff --git a/docs/examples.md b/docs/examples.md deleted file mode 100644 index 067984e..0000000 --- a/docs/examples.md +++ /dev/null @@ -1,12 +0,0 @@ -# Examples - -Examples of how to use earthkit-climate - -```{toctree} -:caption: 'Notebooks' -:maxdepth: 1 - -notebooks/aggregate-temporal.ipynb -notebooks/aggregate-climatology.ipynb -notebooks/aggregate-spatial.ipynb -``` diff --git a/docs/gallery.rst b/docs/gallery.rst new file mode 100644 index 0000000..c492342 --- /dev/null +++ b/docs/gallery.rst @@ -0,0 +1,4 @@ +Gallery +======= + +(Coming soon) diff --git a/docs/index.md b/docs/index.md deleted file mode 100644 index 1b2d8a9..0000000 --- a/docs/index.md +++ /dev/null @@ -1,23 +0,0 @@ -# Welcome to Earthkit-climate's documentation! - -**earthkit-climate** is a library of software tools to support people working with climate and meteorology data - -**earthkit-climate** includes methods for aggregating data in time and space, and future versions will -include tools for bias correcting, downscaling climate data and standard caculations for climate metrics -(e.g. indicators and risk factors). -It has been designed following the philosphy of Earthkit, hence the methods should be interoperable with any -data object understood by earthkit-data. - -```{toctree} -:caption: 'Contents:' -:maxdepth: 2 - -examples.md -API Reference <_api/index> -``` - -# Indices and tables - -- {ref}`genindex` -- {ref}`modindex` -- {ref}`search` diff --git a/docs/index.rst b/docs/index.rst new file mode 100644 index 0000000..9633d06 --- /dev/null +++ b/docs/index.rst @@ -0,0 +1,46 @@ +Welcome to Earthkit-climate's documentation! +============================================ + +**earthkit-climate** is the package responsible for the climate index calculation within the earthkit ecosystem. It includes a wrapper prototype that allows the use of the ``xclim`` python package to compute a large amount of pre-defined climate indices used by the climate science community, and to define new ones. + +``xclim`` relies heavily on the ``xarray`` python library and the ``numpy`` & ``scipy`` ecosystem. Its main elements are: + +- **Climate indices**: available to be directly computed with python functions. The input and output units are defined in these functions by using a decorator and are validated during runtime. +- **Climate indicators**: climate indices wrapped in an object that provides more metadata and validation facilities (health checks) of the input. it includes attributes for CF metadata (cell methods), references, keywords, and more. +- **Lower level process functions**: these include aggregation, computation spell length and counting, optimized computation of reference percentiles, bias correction methods and ensemble statistics. These functions are used by the implemented indices and can also be used to build new indices not included in the library. + +.. toctree:: + :caption: EXAMPLES + :maxdepth: 2 + + tutorials + gallery + +.. toctree:: + :caption: DOCUMENTATION + :maxdepth: 2 + + user-guide + API Reference <_api/index> + development + +.. toctree:: + :caption: INSTALLATION + :maxdepth: 2 + + installation + release-notes + license + +.. toctree:: + :caption: PROJECTS + :maxdepth: 2 + + earthkit + +Indices and tables +================== + +* :ref:`genindex` +* :ref:`modindex` +* :ref:`search` diff --git a/docs/installation.rst b/docs/installation.rst new file mode 100644 index 0000000..f5a11b4 --- /dev/null +++ b/docs/installation.rst @@ -0,0 +1,11 @@ +Installation +============ + +Quick Start +----------- + +Install the package in editable mode: + +.. code-block:: bash + + pip install -e . diff --git a/docs/license.rst b/docs/license.rst new file mode 100644 index 0000000..0060fd5 --- /dev/null +++ b/docs/license.rst @@ -0,0 +1,13 @@ +License +======= + +.. code-block:: text + + Copyright 2022, + European Centre for Medium Range Weather Forecasts (ECMWF) + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at: + + http://www.apache.org/licenses/LICENSE-2.0 diff --git a/docs/notebooks/climate_indices_analysis.ipynb b/docs/notebooks/climate_indices_analysis.ipynb index cd7c8a0..176b133 100644 --- a/docs/notebooks/climate_indices_analysis.ipynb +++ b/docs/notebooks/climate_indices_analysis.ipynb @@ -16,29 +16,28 @@ "\n", "- **Temperature-based indices**:\n", " - *DTR*: Daily Temperature Range (Tmax - Tmin)\n", - " - *WSDI*: Warm Spell Duration Index (≥6 consecutive days above 90th percentile)\n", + " - *WSDI*: Warm Spell Duration Index (\u22656 consecutive days above 90th percentile)\n", " - *HDD*: Heating Degree Days (based on temperature below threshold)\n", "\n", - "We’ll load **ACCESS-CM2 CMIP6 data** for both *historical* and *SSP585* scenarios.\n" + "We\u2019ll load **ACCESS-CM2 CMIP6 data** for both *historical* and *SSP585* scenarios.\n" ] }, { "cell_type": "code", - "execution_count": 16, "id": "1b36bd42f74117db", "metadata": { "ExecuteTime": { - "end_time": "2025-11-14T10:32:46.126222Z", - "start_time": "2025-11-14T10:32:46.124310Z" + "end_time": "2025-12-01T21:58:48.501709Z", + "start_time": "2025-12-01T21:58:48.498192Z" } }, - "outputs": [], "source": [ "import cartopy.crs as ccrs\n", "import matplotlib.pyplot as plt\n", "\n", "import earthkit.data as ekd\n", "import earthkit.plots as ekp\n", + "\n", "from earthkit.climate.indicators.precipitation import (\n", " daily_precipitation_intensity,\n", " maximum_consecutive_wet_days,\n", @@ -48,9 +47,15 @@ " heating_degree_days,\n", " warm_spell_duration_index,\n", ")\n", + "from earthkit.climate.utils.percentile import calculate_percentile_doy\n", + "import warnings\n", + "\n", + "warnings.filterwarnings(\"ignore\")\n", "\n", "plt.rcParams[\"figure.figsize\"] = (8, 5)" - ] + ], + "outputs": [], + "execution_count": 36 }, { "cell_type": "markdown", @@ -59,28 +64,18 @@ "source": [ "## Loading CMIP6 data\n", "\n", - "We’ll use *daily gridded data* from the ACCESS-CM2 model for precipitation (`pr`), maximum (`tasmax`) and minimum (`tasmin`) temperature, for both historical and SSP585 future scenarios.\n" + "We\u2019ll use *daily gridded data* from the ACCESS-CM2 model for precipitation (`pr`), maximum (`tasmax`) and minimum (`tasmin`) temperature, for both historical and SSP585 future scenarios.\n" ] }, { "cell_type": "code", - "execution_count": 17, "id": "5c6692d99197d4af", "metadata": { "ExecuteTime": { - "end_time": "2025-11-14T10:33:47.982446Z", - "start_time": "2025-11-14T10:32:46.170125Z" + "end_time": "2025-12-01T21:27:58.826458Z", + "start_time": "2025-12-01T21:25:56.199912Z" } }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - } - ], "source": [ "# Load precipitation\n", "pr_hist = ekd.from_source(\n", @@ -110,7 +105,17 @@ " \"url\",\n", " \"https://sites.ecmwf.int/repository/earthkit-climate/tasmax_gridded_day_CMIP6_ACCESS-CM2_r1i1p1f1_deepESD_day_ssp585.nc\",\n", ")" - ] + ], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " \r" + ] + } + ], + "execution_count": 2 }, { "cell_type": "markdown", @@ -119,34 +124,18 @@ "source": [ "## Inspect and visualize the raw data\n", "\n", - "Before computing indices, let’s plot a few example grids to see how the raw variables look.\n" + "Before computing indices, let\u2019s plot a few example grids to see how the raw variables look.\n" ] }, { "cell_type": "code", - "execution_count": 18, "id": "51a81669f2d9f6fd", "metadata": { "ExecuteTime": { - "end_time": "2025-11-14T10:34:06.179271Z", - "start_time": "2025-11-14T10:33:48.036754Z" + "end_time": "2025-12-01T21:28:17.485423Z", + "start_time": "2025-12-01T21:27:58.838384Z" } }, - "outputs": [ - { - "data": { - "image/png": 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" + }, + "metadata": {}, + "output_type": "display_data", + "jetTransient": { + "display_id": null + } + } + ], + "execution_count": 3 }, { "cell_type": "markdown", @@ -199,43 +204,28 @@ "## Precipitation-based indices\n", "\n", "We'll compute:\n", - "- **SDII** – Simple Daily Intensity Index (average rain on wet days)\n", - "- **CWD** – Consecutive Wet Days (max length of a wet period)\n" + "- **SDII** \u2013 Simple Daily Intensity Index (average rain on wet days)\n", + "- **CWD** \u2013 Consecutive Wet Days (max length of a wet period)\n" ] }, { "cell_type": "code", - "execution_count": 19, "id": "4f6e09420f604684", "metadata": { "ExecuteTime": { - "end_time": "2025-11-14T10:34:07.061113Z", - "start_time": "2025-11-14T10:34:06.226632Z" + "end_time": "2025-12-01T21:48:39.507484Z", + "start_time": "2025-12-01T21:48:37.823637Z" } }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/cuadradot/predictia-projects/git/c3s-indices/earthkit-climate/.pixi/envs/test/lib/python3.12/site-packages/xclim/core/cfchecks.py:77: UserWarning: Variable does not have a `cell_methods` attribute.\n", - " _check_cell_methods(getattr(vardata, \"cell_methods\", None), data[\"cell_methods\"])\n", - "/home/cuadradot/predictia-projects/git/c3s-indices/earthkit-climate/.pixi/envs/test/lib/python3.12/site-packages/xclim/core/cfchecks.py:79: UserWarning: Variable does not have a `standard_name` attribute.\n", - " check_valid(vardata, \"standard_name\", data[\"standard_name\"])\n", - "/home/cuadradot/predictia-projects/git/c3s-indices/earthkit-climate/.pixi/envs/test/lib/python3.12/site-packages/xclim/core/cfchecks.py:77: UserWarning: Variable does not have a `cell_methods` attribute.\n", - " _check_cell_methods(getattr(vardata, \"cell_methods\", None), data[\"cell_methods\"])\n", - "/home/cuadradot/predictia-projects/git/c3s-indices/earthkit-climate/.pixi/envs/test/lib/python3.12/site-packages/xclim/core/cfchecks.py:79: UserWarning: Variable does not have a `standard_name` attribute.\n", - " check_valid(vardata, \"standard_name\", data[\"standard_name\"])\n" - ] - } - ], "source": [ "# SDII\n", - "sdii = daily_precipitation_intensity(pr_ssp585, wet_day_threshold=1.0, frequency=\"YS\")\n", + "sdii = daily_precipitation_intensity(pr_ssp585, thresh=\"1 mm/day\", freq=\"YS\")\n", "\n", "# CWD\n", - "cwd = maximum_consecutive_wet_days(pr_ssp585, wet_day_threshold=1.0)" - ] + "cwd = maximum_consecutive_wet_days(pr_ssp585, thresh=\"1 mm/day\")" + ], + "outputs": [], + "execution_count": 31 }, { "cell_type": "markdown", @@ -244,8 +234,8 @@ "source": [ "## Inspecting the computed precipitation indices\n", "\n", - "Now that we’ve calculated the precipitation-based indices (**SDII** and **CWD**),\n", - "let’s take a closer look at their structure and metadata.\n", + "Now that we\u2019ve calculated the precipitation-based indices (**SDII** and **CWD**),\n", + "let\u2019s take a closer look at their structure and metadata.\n", "\n", "We'll explore:\n", "1. The list of fields available in each index object (`.ls()`).\n", @@ -257,14 +247,24 @@ }, { "cell_type": "code", - "execution_count": 20, "id": "26d2a1e8539a1c63", "metadata": { "ExecuteTime": { - "end_time": "2025-11-14T10:34:07.114393Z", - "start_time": "2025-11-14T10:34:07.108341Z" + "end_time": "2025-12-01T21:46:17.795728Z", + "start_time": "2025-12-01T21:46:17.779112Z" } }, + "source": [ + "# Inspect the SDII object (Simple Daily Intensity Index)\n", + "print(\"SDII fields:\")\n", + "print(sdii.ls())\n", + "\n", + "print(\"\\nSDII metadata:\")\n", + "print(sdii.metadata()[0]) # show first metadata entry\n", + "\n", + "print(\"\\nSDII xarray attributes:\")\n", + "print(sdii.to_xarray().attrs)" + ], "outputs": [ { "name": "stdout", @@ -314,10 +314,10 @@ "39 sdii None 2054-01-01T00:00:00 mm d-1\n", "\n", "SDII metadata:\n", - "XArrayMetadata({'units': 'mm d-1', 'cell_methods': '', 'history': \"[2025-11-14 11:34:06] sdii: SDII(pr=pr, thresh='1.0 mm/day', freq='YS', op='>=') with options check_missing=any - xclim version: 0.59.1\\n\", 'standard_name': 'lwe_thickness_of_precipitation_amount', 'long_name': 'Average precipitation during days with daily precipitation over 1.0 mm/day (simple daily intensity index: sdii)', 'description': 'Annual simple daily intensity index (sdii) or annual average precipitation for days with daily precipitation over 1.0 mm/day.', 'date': 20150101, 'time': 0, 'variable': 'sdii', 'level': None, 'levtype': 'sfc'})\n", + "XArrayMetadata({'units': 'mm d-1', 'cell_methods': '', 'history': \"[2025-12-01 22:46:06] sdii: SDII(pr=pr, thresh='1 mm/day', freq='YS', op='>=') with options check_missing=any - xclim version: 0.59.1\\n\", 'standard_name': 'lwe_thickness_of_precipitation_amount', 'long_name': 'Average precipitation during days with daily precipitation over 1 mm/day (simple daily intensity index: sdii)', 'description': 'Annual simple daily intensity index (sdii) or annual average precipitation for days with daily precipitation over 1 mm/day.', 'date': 20150101, 'time': 0, 'variable': 'sdii', 'level': None, 'levtype': 'sfc'})\n", "\n", "SDII xarray attributes:\n", - "{'earthkit_provenance': {'earthkit_internal': {'input_type': 'earthkit.data.readers.netcdf.NetCDFFieldListReader'}, 'indicator_definition': {'pr': Parameter(kind=, default='pr', compute_name='pr', description='Daily precipitation.', units='[precipitation]', choices=, value=), 'thresh': Parameter(kind=, default='1 mm/day', compute_name='thresh', description='Precipitation value over which a day is considered wet.', units='[precipitation]', choices=, value=), 'freq': Parameter(kind=, default='YS', compute_name='freq', description='Resampling frequency.', units=, choices=, value=), 'op': Parameter(kind=, default='>=', compute_name='op', description='Comparison operation. Default: \">=\".', units=, choices={'>', '>=', 'gt', 'ge'}, value=), 'ds': Parameter(kind=, default=None, compute_name=, description='A dataset with the variables given by name.', units=, choices=, value=), 'indexer': Parameter(kind=, default=, compute_name=, description='Indexing parameters to compute the indicator on a temporal subset of the data. It accepts the same arguments as :py:func:`xclim.indices.generic.select_time`.', units=, choices=, value=)}, 'cf_attrs': [{'standard_name': 'lwe_thickness_of_precipitation_amount', 'long_name': 'Average precipitation during days with daily precipitation over {thresh} (Simple Daily Intensity Index: SDII)', 'units': 'mm d-1', 'description': '{freq} Simple Daily Intensity Index (SDII) or {freq} average precipitation for days with daily precipitation over {thresh}.', 'var_name': 'sdii'}], 'call_info': {'xclim_function': 'daily_pr_intensity', 'parameters': {'pr': 'pr', 'thresh': '1.0 mm/day', 'freq': 'YS', 'op': '>=', 'ds': Size: 236MB\n", + "{'earthkit_provenance': {'earthkit_internal': {'input_type': 'earthkit.data.readers.netcdf.NetCDFFieldListReader'}, 'indicator_definition': {'pr': Parameter(kind=, default='pr', compute_name='pr', description='Daily precipitation.', units='[precipitation]', choices=, value=), 'thresh': Parameter(kind=, default='1 mm/day', compute_name='thresh', description='Precipitation value over which a day is considered wet.', units='[precipitation]', choices=, value=), 'freq': Parameter(kind=, default='YS', compute_name='freq', description='Resampling frequency.', units=, choices=, value=), 'op': Parameter(kind=, default='>=', compute_name='op', description='Comparison operation. Default: \">=\".', units=, choices={'>', '>=', 'ge', 'gt'}, value=), 'ds': Parameter(kind=, default=None, compute_name=, description='A dataset with the variables given by name.', units=, choices=, value=), 'indexer': Parameter(kind=, default=, compute_name=, description='Indexing parameters to compute the indicator on a temporal subset of the data. It accepts the same arguments as :py:func:`xclim.indices.generic.select_time`.', units=, choices=, value=)}, 'cf_attrs': [{'standard_name': 'lwe_thickness_of_precipitation_amount', 'long_name': 'Average precipitation during days with daily precipitation over {thresh} (Simple Daily Intensity Index: SDII)', 'units': 'mm d-1', 'description': '{freq} Simple Daily Intensity Index (SDII) or {freq} average precipitation for days with daily precipitation over {thresh}.', 'var_name': 'sdii'}], 'call_info': {'xclim_function': 'daily_pr_intensity', 'parameters': {'pr': 'pr', 'thresh': '1 mm/day', 'freq': 'YS', 'op': '>=', 'ds': Size: 236MB\n", "Dimensions: (time: 14610, lat: 48, lon: 84)\n", "Coordinates:\n", " * time (time) datetime64[ns] 117kB 2015-01-01 2015-01-02 ... 2054-12-31\n", @@ -339,17 +339,7 @@ ] } ], - "source": [ - "# Inspect the SDII object (Simple Daily Intensity Index)\n", - "print(\"SDII fields:\")\n", - "print(sdii.ls())\n", - "\n", - "print(\"\\nSDII metadata:\")\n", - "print(sdii.metadata()[0]) # show first metadata entry\n", - "\n", - "print(\"\\nSDII xarray attributes:\")\n", - "print(sdii.to_xarray().attrs)" - ] + "execution_count": 27 }, { "cell_type": "markdown", @@ -365,14 +355,24 @@ }, { "cell_type": "code", - "execution_count": 21, "id": "fb325cae63b747a", "metadata": { "ExecuteTime": { - "end_time": "2025-11-14T10:34:07.163062Z", - "start_time": "2025-11-14T10:34:07.157556Z" + "end_time": "2025-12-01T21:46:21.211487Z", + "start_time": "2025-12-01T21:46:21.200733Z" } }, + "source": [ + "# Inspect the CWD object (Maximum Consecutive Wet Days)\n", + "print(\"CWD fields:\")\n", + "print(cwd.ls())\n", + "\n", + "print(\"\\nCWD metadata:\")\n", + "print(cwd.metadata()[0])\n", + "\n", + "print(\"\\nCWD xarray attributes:\")\n", + "print(cwd.to_xarray().attrs)" + ], "outputs": [ { "name": "stdout", @@ -422,10 +422,10 @@ "39 cwd None 2054-01-01T00:00:00 days\n", "\n", "CWD metadata:\n", - "XArrayMetadata({'units': 'days', 'cell_methods': ' time: sum over days', 'history': \"[2025-11-14 11:34:07] cwd: CWD(pr=pr, thresh='1.0 mm/day', freq='YS', resample_before_rl=True) with options check_missing=any - xclim version: 0.59.1\\n\", 'standard_name': 'number_of_days_with_lwe_thickness_of_precipitation_amount_at_or_above_threshold', 'long_name': 'Maximum consecutive days with daily precipitation at or above 1.0 mm/day', 'description': 'Annual maximum number of consecutive days with daily precipitation at or above 1.0 mm/day.', 'date': 20150101, 'time': 0, 'variable': 'cwd', 'level': None, 'levtype': 'sfc'})\n", + "XArrayMetadata({'units': 'days', 'cell_methods': ' time: sum over days', 'history': \"[2025-12-01 22:46:10] cwd: CWD(pr=pr, thresh='1 mm/day', freq='YS', resample_before_rl=True) with options check_missing=any - xclim version: 0.59.1\\n\", 'standard_name': 'number_of_days_with_lwe_thickness_of_precipitation_amount_at_or_above_threshold', 'long_name': 'Maximum consecutive days with daily precipitation at or above 1 mm/day', 'description': 'Annual maximum number of consecutive days with daily precipitation at or above 1 mm/day.', 'date': 20150101, 'time': 0, 'variable': 'cwd', 'level': None, 'levtype': 'sfc'})\n", "\n", "CWD xarray attributes:\n", - "{'earthkit_provenance': {'earthkit_internal': {'input_type': 'earthkit.data.readers.netcdf.NetCDFFieldListReader'}, 'indicator_definition': {'pr': Parameter(kind=, default='pr', compute_name='pr', description='Mean daily precipitation flux.', units='[precipitation]', choices=, value=), 'thresh': Parameter(kind=, default='1 mm/day', compute_name='thresh', description='Threshold precipitation on which to base evaluation.', units='[precipitation]', choices=, value=), 'freq': Parameter(kind=, default='YS', compute_name='freq', description='Resampling frequency.', units=, choices=, value=), 'resample_before_rl': Parameter(kind=, default=True, compute_name='resample_before_rl', description='Determines if the resampling should take place before or after the run length encoding (or a similar algorithm) is applied to runs.', units=, choices=, value=), 'ds': Parameter(kind=, default=None, compute_name=, description='A dataset with the variables given by name.', units=, choices=, value=)}, 'cf_attrs': [{'standard_name': 'number_of_days_with_lwe_thickness_of_precipitation_amount_at_or_above_threshold', 'long_name': 'Maximum consecutive days with daily precipitation at or above {thresh}', 'units': 'days', 'cell_methods': 'time: sum over days', 'description': '{freq} maximum number of consecutive days with daily precipitation at or above {thresh}.', 'var_name': 'cwd'}], 'call_info': {'xclim_function': 'maximum_consecutive_wet_days', 'parameters': {'pr': 'pr', 'thresh': '1.0 mm/day', 'freq': 'YS', 'resample_before_rl': True, 'ds': Size: 236MB\n", + "{'earthkit_provenance': {'earthkit_internal': {'input_type': 'earthkit.data.readers.netcdf.NetCDFFieldListReader'}, 'indicator_definition': {'pr': Parameter(kind=, default='pr', compute_name='pr', description='Mean daily precipitation flux.', units='[precipitation]', choices=, value=), 'thresh': Parameter(kind=, default='1 mm/day', compute_name='thresh', description='Threshold precipitation on which to base evaluation.', units='[precipitation]', choices=, value=), 'freq': Parameter(kind=, default='YS', compute_name='freq', description='Resampling frequency.', units=, choices=, value=), 'resample_before_rl': Parameter(kind=, default=True, compute_name='resample_before_rl', description='Determines if the resampling should take place before or after the run length encoding (or a similar algorithm) is applied to runs.', units=, choices=, value=), 'ds': Parameter(kind=, default=None, compute_name=, description='A dataset with the variables given by name.', units=, choices=, value=)}, 'cf_attrs': [{'standard_name': 'number_of_days_with_lwe_thickness_of_precipitation_amount_at_or_above_threshold', 'long_name': 'Maximum consecutive days with daily precipitation at or above {thresh}', 'units': 'days', 'cell_methods': 'time: sum over days', 'description': '{freq} maximum number of consecutive days with daily precipitation at or above {thresh}.', 'var_name': 'cwd'}], 'call_info': {'xclim_function': 'maximum_consecutive_wet_days', 'parameters': {'pr': 'pr', 'thresh': '1 mm/day', 'freq': 'YS', 'resample_before_rl': True, 'ds': Size: 236MB\n", "Dimensions: (time: 14610, lat: 48, lon: 84)\n", "Coordinates:\n", " * time (time) datetime64[ns] 117kB 2015-01-01 2015-01-02 ... 2054-12-31\n", @@ -447,17 +447,7 @@ ] } ], - "source": [ - "# Inspect the CWD object (Maximum Consecutive Wet Days)\n", - "print(\"CWD fields:\")\n", - "print(cwd.ls())\n", - "\n", - "print(\"\\nCWD metadata:\")\n", - "print(cwd.metadata()[0])\n", - "\n", - "print(\"\\nCWD xarray attributes:\")\n", - "print(cwd.to_xarray().attrs)" - ] + "execution_count": 28 }, { "cell_type": "markdown", @@ -473,42 +463,18 @@ }, { "cell_type": "code", - "execution_count": 22, "id": "2dfb967617587dfd", "metadata": { "ExecuteTime": { - "end_time": "2025-11-14T10:34:18.333181Z", - "start_time": "2025-11-14T10:34:07.206648Z" + "end_time": "2025-12-01T21:49:05.664741Z", + "start_time": "2025-12-01T21:48:44.596435Z" } }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/cuadradot/predictia-projects/git/c3s-indices/earthkit-climate/.pixi/envs/test/lib/python3.12/site-packages/dask/_task_spec.py:759: RuntimeWarning: invalid value encountered in divide\n", - " return self.func(*new_argspec)\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "jetTransient": { - "display_id": null - }, - "metadata": {}, - "output_type": "display_data" - } - ], "source": [ "# Define domain (Spain north coast)\n", "domain = [-9.6, -5.4, 41.6, 44.0]\n", "\n", - "# Create figure: 1 row (2 indices) × 2 scenarios (historical + ssp585)\n", + "# Create figure: 1 row (2 indices) \u00d7 2 scenarios (historical + ssp585)\n", "figure = ekp.Figure(\n", " crs=ccrs.NearsidePerspective(central_longitude=-5, central_latitude=43), rows=1, columns=2, size=(12, 6)\n", ")\n", @@ -536,7 +502,23 @@ "\n", "# Final layout\n", "figure.show()" - ] + ], + "outputs": [ + { + "data": { + "text/plain": [ + "
" + ], + "image/png": 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" + }, + "metadata": {}, + "output_type": "display_data", + "jetTransient": { + "display_id": null + } + } + ], + "execution_count": 32 }, { "cell_type": "markdown", @@ -545,53 +527,57 @@ "source": [ "## Temperature-based indices\n", "\n", - "Now we’ll compute:\n", - "- **DTR** – Daily Temperature Range\n", - "- **WSDI** – Warm Spell Duration Index (based on 90th percentile)\n", - "- **HDD** – Heating Degree Days\n" + "Now we\u2019ll compute:\n", + "- **DTR** \u2013 Daily Temperature Range\n", + "- **WSDI** \u2013 Warm Spell Duration Index (based on 90th percentile)\n", + "- **HDD** \u2013 Heating Degree Days\n" ] }, { "cell_type": "code", - "execution_count": null, "id": "93b725acd1e4d5a4", "metadata": { "ExecuteTime": { - "start_time": "2025-11-14T11:47:33.001110Z" - }, - "jupyter": { - "is_executing": true + "end_time": "2025-12-01T22:20:41.322501Z", + "start_time": "2025-12-01T22:20:37.611062Z" } }, - "outputs": [], "source": [ "# DTR\n", - "dtr = daily_temperature_range(tasmax_ssp585, tasmin_ssp585)\n", + "dtr = daily_temperature_range(ds=(tasmax_ssp585 + tasmin_ssp585))\n", "\n", "# WSDI (using historical baseline)\n", - "wsdi = warm_spell_duration_index(tasmax_ssp585, tasmax_hist)\n", + "# Calculate 90th percentile from historical data\n", + "tasmax_per = calculate_percentile_doy(tasmax_hist.to_xarray(), variable='tasmax', percentile=90)\n", + "\n", + "# Merge percentile with target dataset\n", + "ds_merged = tasmax_ssp585.to_xarray().merge(tasmax_per)\n", + "\n", + "wsdi = warm_spell_duration_index(ds=ds_merged)\n", "\n", "# HDD (approximation)\n", "tas = (tasmax_ssp585.to_xarray()[\"tasmax\"] + tasmin_ssp585.to_xarray()[\"tasmin\"]) / 2\n", "tas.attrs[\"units\"] = \"degC\"\n", "tas = tas.to_dataset(name=\"tas\")\n", - "hdd = heating_degree_days(tasmax_ssp585, tasmin_ssp585, tas)" - ] + "hdd = heating_degree_days(ds=ekd.from_source(\"multi\", ekd.from_object(tasmax_ssp585.to_xarray()), ekd.from_object(tasmin_ssp585.to_xarray()), ekd.from_object(tas)))" + ], + "outputs": [], + "execution_count": 63 }, { "cell_type": "markdown", "id": "19bb9271df9f8a95", "metadata": {}, "source": [ - "## Inspecting the temperature-based indices\n", + "ekd.from_object(tas)## Inspecting the temperature-based indices\n", "\n", "Now let's explore the three temperature indices we calculated:\n", "\n", - "1. **DTR (Daily Temperature Range)** — Difference between daily maximum and minimum temperatures.\n", - "2. **WSDI (Warm Spell Duration Index)** — Number of warm spells: consecutive periods (≥6 days) above the 90th percentile of the historical period.\n", - "3. **HDD (Heating Degree Days)** — Heating degree days, estimating heating energy demand based on temperatures below a threshold.\n", + "1. **DTR (Daily Temperature Range)** \u2014 Difference between daily maximum and minimum temperatures.\n", + "2. **WSDI (Warm Spell Duration Index)** \u2014 Number of warm spells: consecutive periods (\u22656 days) above the 90th percentile of the historical period.\n", + "3. **HDD (Heating Degree Days)** \u2014 Heating degree days, estimating heating energy demand based on temperatures below a threshold.\n", "\n", - "For each index, we’ll check:\n", + "For each index, we\u2019ll check:\n", "- The available fields (`.ls()`).\n", "- The metadata and provenance (`.metadata()`).\n", "- The dataset attributes (`.to_xarray().attrs`).\n", @@ -601,14 +587,24 @@ }, { "cell_type": "code", - "execution_count": 24, "id": "eb9c38817b8d9d71", "metadata": { "ExecuteTime": { - "end_time": "2025-11-14T10:34:19.830398Z", - "start_time": "2025-11-14T10:34:19.824818Z" + "end_time": "2025-12-01T22:22:11.616721Z", + "start_time": "2025-12-01T22:22:11.605070Z" } }, + "source": [ + "# DTR (Daily Temperature Range)\n", + "print(\"DTR fields:\")\n", + "print(dtr.ls())\n", + "\n", + "print(\"\\n DTR metadata:\")\n", + "print(dtr.metadata()[0])\n", + "\n", + "print(\"\\n DTR xarray attributes:\")\n", + "print(dtr.to_xarray().attrs)" + ], "outputs": [ { "name": "stdout", @@ -658,32 +654,28 @@ "39 dtr None 2054-01-01T00:00:00 K\n", "\n", " DTR metadata:\n", - "XArrayMetadata({'units': 'K', 'units_metadata': 'temperature: difference', 'cell_methods': ' time range within days time: mean over days', 'history': \"[2025-11-14 11:34:18] dtr: DTR(tasmin=tasmax, tasmax=tasmin, freq='YS') with options check_missing=any - xclim version: 0.59.1\\ntasmin: \\ntasmax: \", 'standard_name': 'air_temperature', 'long_name': 'Mean diurnal temperature range', 'description': 'Annual mean diurnal temperature range.', 'date': 20150101, 'time': 0, 'variable': 'dtr', 'level': None, 'levtype': 'sfc'})\n", + "XArrayMetadata({'units': 'K', 'units_metadata': 'temperature: difference', 'cell_methods': ' time range within days time: mean over days', 'history': \"[2025-12-01 23:20:37] dtr: DTR(tasmin=tasmin, tasmax=tasmax, freq='YS') with options check_missing=any - xclim version: 0.59.1\\ntasmin: \\ntasmax: \", 'standard_name': 'air_temperature', 'long_name': 'Mean diurnal temperature range', 'description': 'Annual mean diurnal temperature range.', 'date': 20150101, 'time': 0, 'variable': 'dtr', 'level': None, 'levtype': 'sfc'})\n", "\n", " DTR xarray attributes:\n", - "{'earthkit_provenance': {'earthkit_internal': {'input_type': 'earthkit.data.readers.netcdf.NetCDFFieldListReader'}, 'indicator_definition': {'tasmin': Parameter(kind=, default='tasmin', compute_name='tasmin', description='Minimum daily temperature.', units='[temperature]', choices=, value=), 'tasmax': Parameter(kind=, default='tasmax', compute_name='tasmax', description='Maximum daily temperature.', units='[temperature]', choices=, value=), 'freq': Parameter(kind=, default='YS', compute_name='freq', description='Resampling frequency.', units=, choices=, value=), 'ds': Parameter(kind=, default=None, compute_name=, description='A dataset with the variables given by name.', units=, choices=, value=), 'indexer': Parameter(kind=, default=, compute_name=, description='Indexing parameters to compute the indicator on a temporal subset of the data. It accepts the same arguments as :py:func:`xclim.indices.generic.select_time`.', units=, choices=, value=)}, 'cf_attrs': [{'standard_name': 'air_temperature', 'long_name': 'Mean diurnal temperature range', 'units': 'K', 'cell_methods': 'time range within days time: mean over days', 'description': '{freq} mean diurnal temperature range.', 'var_name': 'dtr'}], 'call_info': {'xclim_function': 'daily_temperature_range', 'parameters': {'tasmin': 'tasmin', 'tasmax': 'tasmax', 'freq': 'YS', 'ds': Size: 647kB\n", - "Dimensions: (lat: 48, lon: 84, time: 40)\n", + "{'earthkit_provenance': {'earthkit_internal': {'input_type': 'earthkit.data.readers.netcdf.fieldlist.NetCDFMultiFieldList'}, 'indicator_definition': {'tasmin': Parameter(kind=, default='tasmin', compute_name='tasmin', description='Minimum daily temperature.', units='[temperature]', choices=, value=), 'tasmax': Parameter(kind=, default='tasmax', compute_name='tasmax', description='Maximum daily temperature.', units='[temperature]', choices=, value=), 'freq': Parameter(kind=, default='YS', compute_name='freq', description='Resampling frequency.', units=, choices=, value=), 'ds': Parameter(kind=, default=None, compute_name=, description='A dataset with the variables given by name.', units=, choices=, value=), 'indexer': Parameter(kind=, default=, compute_name=, description='Indexing parameters to compute the indicator on a temporal subset of the data. It accepts the same arguments as :py:func:`xclim.indices.generic.select_time`.', units=, choices=, value=)}, 'cf_attrs': [{'standard_name': 'air_temperature', 'long_name': 'Mean diurnal temperature range', 'units': 'K', 'cell_methods': 'time range within days time: mean over days', 'description': '{freq} mean diurnal temperature range.', 'var_name': 'dtr'}], 'call_info': {'xclim_function': 'daily_temperature_range', 'parameters': {'tasmin': 'tasmin', 'tasmax': 'tasmax', 'freq': 'YS', 'ds': Size: 471MB\n", + "Dimensions: (time: 14610, lat: 48, lon: 84)\n", "Coordinates:\n", + " * time (time) datetime64[ns] 117kB 2015-01-01 2015-01-02 ... 2054-12-31\n", " * lat (lat) float64 384B 41.62 41.67 41.72 41.77 ... 43.87 43.92 43.97\n", " * lon (lon) float64 672B -9.575 -9.525 -9.475 ... -5.525 -5.475 -5.425\n", - " * time (time) datetime64[ns] 320B 2015-01-01 2016-01-01 ... 2054-01-01\n", " height float64 8B 2.0\n", "Data variables:\n", - " dtr (time, lat, lon) float32 645kB dask.array, 'indexer': {}}}}}\n" + " tasmax (time, lat, lon) float32 236MB dask.array\n", + " tasmin (time, lat, lon) float32 236MB dask.array\n", + "Attributes:\n", + " model: ACCESS-CM2_r1i1p1f1_deepESD\n", + " scenario: ssp585\n", + " project_name: cmip6\n", + " project_type: projections, 'indexer': {}}}}}\n" ] } ], - "source": [ - "# DTR (Daily Temperature Range)\n", - "print(\"DTR fields:\")\n", - "print(dtr.ls())\n", - "\n", - "print(\"\\n DTR metadata:\")\n", - "print(dtr.metadata()[0])\n", - "\n", - "print(\"\\n DTR xarray attributes:\")\n", - "print(dtr.to_xarray().attrs)" - ] + "execution_count": 64 }, { "cell_type": "markdown", @@ -699,14 +691,24 @@ }, { "cell_type": "code", - "execution_count": 25, "id": "e0a036138ac7e2a7", "metadata": { "ExecuteTime": { - "end_time": "2025-11-14T10:34:19.880091Z", - "start_time": "2025-11-14T10:34:19.874015Z" + "end_time": "2025-12-01T22:22:14.171154Z", + "start_time": "2025-12-01T22:22:14.161783Z" } }, + "source": [ + "# WSDI (Warm Spell Duration Index)\n", + "print(\"WSDI fields:\")\n", + "wsdi.ls()\n", + "\n", + "print(\"\\n WSDI metadata:\")\n", + "print(wsdi.metadata()[0])\n", + "\n", + "print(\"\\n WSDI xarray attributes:\")\n", + "print(wsdi.to_xarray().attrs)" + ], "outputs": [ { "name": "stdout", @@ -715,119 +717,123 @@ "WSDI fields:\n", "\n", " WSDI metadata:\n", - "XArrayMetadata({'units': 'days', 'cell_methods': ' time: sum over days', 'history': \"[2025-11-14 11:34:19] warm_spell_duration_index: WARM_SPELL_DURATION_INDEX(tasmax=tasmax, tasmax_per=per, window=6, freq='YS', resample_before_rl=True, bootstrap=False, op='>') with options check_missing=any - xclim version: 0.59.1\\ntasmax: \\ntasmax_per: [2025-11-14 11:34:18] per: percentile_doy(arr=tasmax, window=5, per=90, alpha=0.3333333333333333, beta=0.3333333333333333, copy=True) - xclim version: 0.59.1\\n\", 'standard_name': 'number_of_days_with_air_temperature_above_threshold', 'long_name': 'Number of days with at least 6 consecutive days where the maximum daily temperature is above the [90]th percentile(s)', 'description': \"Annual number of days with at least 6 consecutive days where the maximum daily temperature is above the [90]th percentile(s). a 5 day(s) window, centred on each calendar day in the ['1995-01-01', '2014-12-31'] period, is used to compute the [90]th percentile(s).\", 'date': 20150101, 'time': 0, 'variable': 'warm_spell_duration_index', 'level': None, 'levtype': 'sfc'})\n", + "XArrayMetadata({'units': 'days', 'cell_methods': ' time: sum over days', 'history': \"[2025-12-01 23:20:39] warm_spell_duration_index: WARM_SPELL_DURATION_INDEX(tasmax=tasmax, tasmax_per=tasmax_per, window=6, freq='YS', resample_before_rl=True, bootstrap=False, op='>') with options check_missing=any - xclim version: 0.59.1\\ntasmax: \\ntasmax_per: [2025-12-01 23:20:38] per: percentile_doy(arr=tasmax, window=6, per=90, alpha=0.3333333333333333, beta=0.3333333333333333, copy=True) - xclim version: 0.59.1\\n\", 'standard_name': 'number_of_days_with_air_temperature_above_threshold', 'long_name': 'Number of days with at least 6 consecutive days where the maximum daily temperature is above the [90]th percentile(s)', 'description': \"Annual number of days with at least 6 consecutive days where the maximum daily temperature is above the [90]th percentile(s). a 6 day(s) window, centred on each calendar day in the ['1995-01-01', '2014-12-31'] period, is used to compute the [90]th percentile(s).\", 'date': 20150101, 'time': 0, 'variable': 'warm_spell_duration_index', 'level': None, 'levtype': 'sfc'})\n", "\n", " WSDI xarray attributes:\n", - "{'earthkit_provenance': {'earthkit_internal': {'input_type': 'earthkit.data.readers.netcdf.NetCDFFieldListReader'}, 'indicator_definition': {'tasmax': Parameter(kind=, default='tasmax', compute_name='tasmax', description='Maximum daily temperature.', units='[temperature]', choices=, value=), 'tasmax_per': Parameter(kind=, default='tasmax_per', compute_name='tasmax_per', description='Percentile(s) of daily maximum temperature.', units='[temperature]', choices=, value=), 'window': Parameter(kind=, default=6, compute_name='window', description='Minimum number of days with temperature above threshold to qualify as a warm spell.', units=, choices=, value=), 'freq': Parameter(kind=, default='YS', compute_name='freq', description='Resampling frequency.', units=, choices=, value=), 'resample_before_rl': Parameter(kind=, default=True, compute_name='resample_before_rl', description='Determines if the resampling should take place before or after the run length encoding (or a similar algorithm) is applied to runs.', units=, choices=, value=), 'bootstrap': Parameter(kind=, default=False, compute_name='bootstrap', description='Flag to run bootstrapping of percentiles. Used by percentile_bootstrap decorator. Bootstrapping is only useful when the percentiles are computed on a part of the studied sample. This period, common to percentiles and the sample must be bootstrapped to avoid inhomogeneities with the rest of the time series. Do not enable bootstrap when there is no common period, otherwise it will provide the wrong results. Note that bootstrapping is computationally expensive.', units=, choices=, value=), 'op': Parameter(kind=, default='>', compute_name='op', description='Comparison operation. Default: \">\".', units=, choices={'>', '>=', 'gt', 'ge'}, value=), 'ds': Parameter(kind=, default=None, compute_name=, description='A dataset with the variables given by name.', units=, choices=, value=)}, 'cf_attrs': [{'standard_name': 'number_of_days_with_air_temperature_above_threshold', 'long_name': 'Number of days with at least {window} consecutive days where the maximum daily temperature is above the {tasmax_per_thresh}th percentile(s)', 'units': 'days', 'cell_methods': 'time: sum over days', 'description': '{freq} number of days with at least {window} consecutive days where the maximum daily temperature is above the {tasmax_per_thresh}th percentile(s). A {tasmax_per_window} day(s) window, centred on each calendar day in the {tasmax_per_period} period, is used to compute the {tasmax_per_thresh}th percentile(s).', 'var_name': 'warm_spell_duration_index'}], 'call_info': {'xclim_function': 'warm_spell_duration_index', 'parameters': {'tasmax': 'tasmax', 'tasmax_per': 'tasmax_per', 'window': 6, 'freq': 'YS', 'resample_before_rl': True, 'bootstrap': False, 'op': '>', 'ds': Size: 1MB\n", - "Dimensions: (lat: 48, lon: 84, percentiles: 1, time: 40)\n", + "{'earthkit_provenance': {'earthkit_internal': {'input_type': 'earthkit.data.readers.netcdf.NetCDFFieldListReader'}, 'indicator_definition': {'tasmax': Parameter(kind=, default='tasmax', compute_name='tasmax', description='Maximum daily temperature.', units='[temperature]', choices=, value=), 'tasmax_per': Parameter(kind=, default='tasmax_per', compute_name='tasmax_per', description='Percentile(s) of daily maximum temperature.', units='[temperature]', choices=, value=), 'window': Parameter(kind=, default=6, compute_name='window', description='Minimum number of days with temperature above threshold to qualify as a warm spell.', units=, choices=, value=), 'freq': Parameter(kind=, default='YS', compute_name='freq', description='Resampling frequency.', units=, choices=, value=), 'resample_before_rl': Parameter(kind=, default=True, compute_name='resample_before_rl', description='Determines if the resampling should take place before or after the run length encoding (or a similar algorithm) is applied to runs.', units=, choices=, value=), 'bootstrap': Parameter(kind=, default=False, compute_name='bootstrap', description='Flag to run bootstrapping of percentiles. Used by percentile_bootstrap decorator. Bootstrapping is only useful when the percentiles are computed on a part of the studied sample. This period, common to percentiles and the sample must be bootstrapped to avoid inhomogeneities with the rest of the time series. Do not enable bootstrap when there is no common period, otherwise it will provide the wrong results. Note that bootstrapping is computationally expensive.', units=, choices=, value=), 'op': Parameter(kind=, default='>', compute_name='op', description='Comparison operation. Default: \">\".', units=, choices={'>', '>=', 'ge', 'gt'}, value=), 'ds': Parameter(kind=, default=None, compute_name=, description='A dataset with the variables given by name.', units=, choices=, value=)}, 'cf_attrs': [{'standard_name': 'number_of_days_with_air_temperature_above_threshold', 'long_name': 'Number of days with at least {window} consecutive days where the maximum daily temperature is above the {tasmax_per_thresh}th percentile(s)', 'units': 'days', 'cell_methods': 'time: sum over days', 'description': '{freq} number of days with at least {window} consecutive days where the maximum daily temperature is above the {tasmax_per_thresh}th percentile(s). A {tasmax_per_window} day(s) window, centred on each calendar day in the {tasmax_per_period} period, is used to compute the {tasmax_per_thresh}th percentile(s).', 'var_name': 'warm_spell_duration_index'}], 'call_info': {'xclim_function': 'warm_spell_duration_index', 'parameters': {'tasmax': 'tasmax', 'tasmax_per': 'tasmax_per', 'window': 6, 'freq': 'YS', 'resample_before_rl': True, 'bootstrap': False, 'op': '>', 'ds': Size: 242MB\n", + "Dimensions: (time: 14610, lat: 48, lon: 84, percentiles: 1, dayofyear: 366)\n", "Coordinates:\n", - " * lat (lat) float64 384B 41.62 41.67 ... 43.92 43.97\n", - " * lon (lon) float64 672B -9.575 -9.525 ... -5.425\n", - " * percentiles (percentiles) int64 8B 90\n", - " * time (time) datetime64[ns] 320B 2015-01-01 ... 2054...\n", - " height float64 8B 2.0\n", + " * time (time) datetime64[ns] 117kB 2015-01-01 ... 2054-12-31\n", + " * lat (lat) float64 384B 41.62 41.67 41.72 ... 43.87 43.92 43.97\n", + " * lon (lon) float64 672B -9.575 -9.525 -9.475 ... -5.475 -5.425\n", + " * percentiles (percentiles) int64 8B 90\n", + " * dayofyear (dayofyear) int64 3kB 1 2 3 4 5 6 7 ... 361 362 363 364 365 366\n", + " height float64 8B 2.0\n", "Data variables:\n", - " warm_spell_duration_index (time, lat, lon, percentiles) float64 1MB dask.array}}}}\n" + " tasmax (time, lat, lon) float32 236MB dask.array\n", + " tasmax_per (lat, lon, dayofyear, percentiles) float32 6MB dask.array\n", + "Attributes:\n", + " model: ACCESS-CM2_r1i1p1f1_deepESD\n", + " scenario: ssp585\n", + " project_name: cmip6\n", + " project_type: projections}}}}\n" ] } ], - "source": [ - "# WSDI (Warm Spell Duration Index)\n", - "print(\"WSDI fields:\")\n", - "wsdi.ls()\n", - "\n", - "print(\"\\n WSDI metadata:\")\n", - "print(wsdi.metadata()[0])\n", - "\n", - "print(\"\\n WSDI xarray attributes:\")\n", - "print(wsdi.to_xarray().attrs)" - ] + "execution_count": 65 }, { "cell_type": "code", - "execution_count": 26, "id": "c2303c3c80f8ae82", "metadata": { "ExecuteTime": { - "end_time": "2025-11-14T10:34:19.932104Z", - "start_time": "2025-11-14T10:34:19.924443Z" + "end_time": "2025-12-01T22:22:16.312218Z", + "start_time": "2025-12-01T22:22:16.300952Z" } }, + "source": [ + "# HDD (Heating Degree Days)\n", + "print(\"HDD fields:\")\n", + "print(hdd.ls())\n", + "\n", + "print(\"\\n HDD metadata:\")\n", + "print(hdd.metadata()[0])\n", + "\n", + "print(\"\\n HDD xarray attributes:\")\n", + "print(hdd.to_xarray().attrs)" + ], "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "HDD fields:\n", - " variable level valid_datetime units\n", - "0 heating_degree_days_approximation None 2015-01-01T00:00:00 K days\n", - "1 heating_degree_days_approximation None 2016-01-01T00:00:00 K days\n", - "2 heating_degree_days_approximation None 2017-01-01T00:00:00 K days\n", - "3 heating_degree_days_approximation None 2018-01-01T00:00:00 K days\n", - "4 heating_degree_days_approximation None 2019-01-01T00:00:00 K days\n", - "5 heating_degree_days_approximation None 2020-01-01T00:00:00 K days\n", - "6 heating_degree_days_approximation None 2021-01-01T00:00:00 K days\n", - "7 heating_degree_days_approximation None 2022-01-01T00:00:00 K days\n", - "8 heating_degree_days_approximation None 2023-01-01T00:00:00 K days\n", - "9 heating_degree_days_approximation None 2024-01-01T00:00:00 K days\n", - "10 heating_degree_days_approximation None 2025-01-01T00:00:00 K days\n", - "11 heating_degree_days_approximation None 2026-01-01T00:00:00 K days\n", - "12 heating_degree_days_approximation None 2027-01-01T00:00:00 K days\n", - "13 heating_degree_days_approximation None 2028-01-01T00:00:00 K days\n", - "14 heating_degree_days_approximation None 2029-01-01T00:00:00 K days\n", - "15 heating_degree_days_approximation None 2030-01-01T00:00:00 K days\n", - "16 heating_degree_days_approximation None 2031-01-01T00:00:00 K days\n", - "17 heating_degree_days_approximation None 2032-01-01T00:00:00 K days\n", - "18 heating_degree_days_approximation None 2033-01-01T00:00:00 K days\n", - "19 heating_degree_days_approximation None 2034-01-01T00:00:00 K days\n", - "20 heating_degree_days_approximation None 2035-01-01T00:00:00 K days\n", - "21 heating_degree_days_approximation None 2036-01-01T00:00:00 K days\n", - "22 heating_degree_days_approximation None 2037-01-01T00:00:00 K days\n", - "23 heating_degree_days_approximation None 2038-01-01T00:00:00 K days\n", - "24 heating_degree_days_approximation None 2039-01-01T00:00:00 K days\n", - "25 heating_degree_days_approximation None 2040-01-01T00:00:00 K days\n", - "26 heating_degree_days_approximation None 2041-01-01T00:00:00 K days\n", - "27 heating_degree_days_approximation None 2042-01-01T00:00:00 K days\n", - "28 heating_degree_days_approximation None 2043-01-01T00:00:00 K days\n", - "29 heating_degree_days_approximation None 2044-01-01T00:00:00 K days\n", - "30 heating_degree_days_approximation None 2045-01-01T00:00:00 K days\n", - "31 heating_degree_days_approximation None 2046-01-01T00:00:00 K days\n", - "32 heating_degree_days_approximation None 2047-01-01T00:00:00 K days\n", - "33 heating_degree_days_approximation None 2048-01-01T00:00:00 K days\n", - "34 heating_degree_days_approximation None 2049-01-01T00:00:00 K days\n", - "35 heating_degree_days_approximation None 2050-01-01T00:00:00 K days\n", - "36 heating_degree_days_approximation None 2051-01-01T00:00:00 K days\n", - "37 heating_degree_days_approximation None 2052-01-01T00:00:00 K days\n", - "38 heating_degree_days_approximation None 2053-01-01T00:00:00 K days\n", - "39 heating_degree_days_approximation None 2054-01-01T00:00:00 K days\n", + " variable level valid_datetime units\n", + "0 heating_degree_days None 2015-01-01T00:00:00 K days\n", + "1 heating_degree_days None 2016-01-01T00:00:00 K days\n", + "2 heating_degree_days None 2017-01-01T00:00:00 K days\n", + "3 heating_degree_days None 2018-01-01T00:00:00 K days\n", + "4 heating_degree_days None 2019-01-01T00:00:00 K days\n", + "5 heating_degree_days None 2020-01-01T00:00:00 K days\n", + "6 heating_degree_days None 2021-01-01T00:00:00 K days\n", + "7 heating_degree_days None 2022-01-01T00:00:00 K days\n", + "8 heating_degree_days None 2023-01-01T00:00:00 K days\n", + "9 heating_degree_days None 2024-01-01T00:00:00 K days\n", + "10 heating_degree_days None 2025-01-01T00:00:00 K days\n", + "11 heating_degree_days None 2026-01-01T00:00:00 K days\n", + "12 heating_degree_days None 2027-01-01T00:00:00 K days\n", + "13 heating_degree_days None 2028-01-01T00:00:00 K days\n", + "14 heating_degree_days None 2029-01-01T00:00:00 K days\n", + "15 heating_degree_days None 2030-01-01T00:00:00 K days\n", + "16 heating_degree_days None 2031-01-01T00:00:00 K days\n", + "17 heating_degree_days None 2032-01-01T00:00:00 K days\n", + "18 heating_degree_days None 2033-01-01T00:00:00 K days\n", + "19 heating_degree_days None 2034-01-01T00:00:00 K days\n", + "20 heating_degree_days None 2035-01-01T00:00:00 K days\n", + "21 heating_degree_days None 2036-01-01T00:00:00 K days\n", + "22 heating_degree_days None 2037-01-01T00:00:00 K days\n", + "23 heating_degree_days None 2038-01-01T00:00:00 K days\n", + "24 heating_degree_days None 2039-01-01T00:00:00 K days\n", + "25 heating_degree_days None 2040-01-01T00:00:00 K days\n", + "26 heating_degree_days None 2041-01-01T00:00:00 K days\n", + "27 heating_degree_days None 2042-01-01T00:00:00 K days\n", + "28 heating_degree_days None 2043-01-01T00:00:00 K days\n", + "29 heating_degree_days None 2044-01-01T00:00:00 K days\n", + "30 heating_degree_days None 2045-01-01T00:00:00 K days\n", + "31 heating_degree_days None 2046-01-01T00:00:00 K days\n", + "32 heating_degree_days None 2047-01-01T00:00:00 K days\n", + "33 heating_degree_days None 2048-01-01T00:00:00 K days\n", + "34 heating_degree_days None 2049-01-01T00:00:00 K days\n", + "35 heating_degree_days None 2050-01-01T00:00:00 K days\n", + "36 heating_degree_days None 2051-01-01T00:00:00 K days\n", + "37 heating_degree_days None 2052-01-01T00:00:00 K days\n", + "38 heating_degree_days None 2053-01-01T00:00:00 K days\n", + "39 heating_degree_days None 2054-01-01T00:00:00 K days\n", "\n", " HDD metadata:\n", - "XArrayMetadata({'units': 'K days', 'units_metadata': 'temperature: difference', 'cell_methods': ' time: sum over days', 'history': \"[2025-11-14 11:34:19] heating_degree_days_approximation: HEATING_DEGREE_DAYS_APPROXIMATION(tasmax=tasmax, tasmin=tasmin, tas=tas, thresh='17.0 degC', freq='YS') with options check_missing=any - xclim version: 0.59.1\\ntasmax: \\ntasmin: \\ntas: \", 'standard_name': 'integral_of_air_temperature_deficit_wrt_time', 'long_name': 'Cumulative sum of temperature degrees for daily temperatures below 17.0 degc', 'description': 'Annual cumulative heating degree days (temperature below 17.0 degc) using a combination of minimum, maximum, and mean daily temperatures.', 'date': 20150101, 'time': 0, 'variable': 'heating_degree_days_approximation', 'level': None, 'levtype': 'sfc'})\n", + "XArrayMetadata({'units': 'K days', 'units_metadata': 'temperature: unknown', 'cell_methods': ' time: sum over days', 'history': \"[2025-12-01 23:20:41] heating_degree_days: HEATING_DEGREE_DAYS(tas=tas, thresh='17.0 degC', freq='YS') with options check_missing=any - xclim version: 0.59.1\\n\", 'standard_name': 'integral_of_air_temperature_deficit_wrt_time', 'long_name': 'Cumulative sum of temperature degrees for mean daily temperature below 17.0 degc', 'description': 'Annual cumulative heating degree days (mean temperature below 17.0 degc).', 'date': 20150101, 'time': 0, 'variable': 'heating_degree_days', 'level': None, 'levtype': 'sfc'})\n", "\n", " HDD xarray attributes:\n", - "{'earthkit_provenance': {'earthkit_internal': {'input_type': 'earthkit.data.readers.netcdf.NetCDFFieldListReader'}, 'indicator_definition': {'tasmax': Parameter(kind=, default='tasmax', compute_name='tasmax', description='Maximum daily temperature.', units='[temperature]', choices=, value=), 'tasmin': Parameter(kind=, default='tasmin', compute_name='tasmin', description='Minimum daily temperature.', units='[temperature]', choices=, value=), 'tas': Parameter(kind=, default='tas', compute_name='tas', description='Mean daily temperature.', units='[temperature]', choices=, value=), 'thresh': Parameter(kind=, default='17.0 degC', compute_name='thresh', description='Threshold temperature on which to base evaluation.', units='[temperature]', choices=, value=), 'freq': Parameter(kind=, default='YS', compute_name='freq', description='Resampling frequency.', units=, choices=, value=), 'ds': Parameter(kind=, default=None, compute_name=, description='A dataset with the variables given by name.', units=, choices=, value=), 'indexer': Parameter(kind=, default=, compute_name=, description='Indexing parameters to compute the indicator on a temporal subset of the data. It accepts the same arguments as :py:func:`xclim.indices.generic.select_time`.', units=, choices=, value=)}, 'cf_attrs': [{'standard_name': 'integral_of_air_temperature_deficit_wrt_time', 'long_name': 'Cumulative sum of temperature degrees for daily temperatures below {thresh}', 'units': 'K days', 'cell_methods': 'time: sum over days', 'description': '{freq} cumulative heating degree days (temperature below {thresh}) using a combination of minimum, maximum, and mean daily temperatures.', 'var_name': 'heating_degree_days_approximation'}], 'call_info': {'xclim_function': 'heating_degree_days_approximation', 'parameters': {'tasmax': 'tasmax', 'tasmin': 'tasmin', 'tas': 'tas', 'thresh': '17.0 degC', 'freq': 'YS', 'ds': Size: 647kB\n", - "Dimensions: (lat: 48, lon: 84, time: 40)\n", + "{'earthkit_provenance': {'earthkit_internal': {'input_type': 'earthkit.data.readers.netcdf.fieldlist.XArrayMultiFieldList'}, 'indicator_definition': {'tas': Parameter(kind=, default='tas', compute_name='tas', description='Mean daily temperature.', units='[temperature]', choices=, value=), 'thresh': Parameter(kind=, default='17.0 degC', compute_name='thresh', description='Threshold temperature on which to base evaluation.', units='[temperature]', choices=, value=), 'freq': Parameter(kind=, default='YS', compute_name='freq', description='Resampling frequency.', units=, choices=, value=), 'ds': Parameter(kind=, default=None, compute_name=, description='A dataset with the variables given by name.', units=, choices=, value=), 'indexer': Parameter(kind=, default=, compute_name=, description='Indexing parameters to compute the indicator on a temporal subset of the data. It accepts the same arguments as :py:func:`xclim.indices.generic.select_time`.', units=, choices=, value=)}, 'cf_attrs': [{'standard_name': 'integral_of_air_temperature_deficit_wrt_time', 'long_name': 'Cumulative sum of temperature degrees for mean daily temperature below {thresh}', 'units': 'K days', 'cell_methods': 'time: sum over days', 'description': '{freq} cumulative heating degree days (mean temperature below {thresh}).', 'var_name': 'heating_degree_days'}], 'call_info': {'xclim_function': 'heating_degree_days', 'parameters': {'tas': 'tas', 'thresh': '17.0 degC', 'freq': 'YS', 'ds': Size: 707MB\n", + "Dimensions: (time: 14610, lat: 48, lon: 84)\n", "Coordinates:\n", - " * lat (lat) float64 384B 41.62 41.67 ... 43.97\n", - " * lon (lon) float64 672B -9.575 ... -5.425\n", - " * time (time) datetime64[ns] 320B 2015-01-01 ...\n", - " height float64 8B 2.0\n", + " * time (time) datetime64[ns] 117kB 2015-01-01 2015-01-02 ... 2054-12-31\n", + " * lat (lat) float64 384B 41.62 41.67 41.72 41.77 ... 43.87 43.92 43.97\n", + " * lon (lon) float64 672B -9.575 -9.525 -9.475 ... -5.525 -5.475 -5.425\n", + " height float64 8B 2.0\n", "Data variables:\n", - " heating_degree_days_approximation (time, lat, lon) float32 645kB dask.array, 'indexer': {}}}}}\n" + " tasmax (time, lat, lon) float32 236MB dask.array\n", + " tasmin (time, lat, lon) float32 236MB dask.array\n", + " tas (time, lat, lon) float32 236MB dask.array\n", + "Attributes:\n", + " model: ACCESS-CM2_r1i1p1f1_deepESD\n", + " scenario: ssp585\n", + " project_name: cmip6\n", + " project_type: projections, 'indexer': {}}}}}\n" ] } ], - "source": [ - "# HDD (Heating Degree Days)\n", - "print(\"HDD fields:\")\n", - "print(hdd.ls())\n", - "\n", - "print(\"\\n HDD metadata:\")\n", - "print(hdd.metadata()[0])\n", - "\n", - "print(\"\\n HDD xarray attributes:\")\n", - "print(hdd.to_xarray().attrs)" - ] + "execution_count": 66 }, { "cell_type": "markdown", @@ -836,41 +842,25 @@ "source": [ "### Notes on HDD\n", "\n", - "- The **Heating Degree Days** index estimates heating demand based on temperatures below a threshold (typically 18 °C).\n", + "- The **Heating Degree Days** index estimates heating demand based on temperatures below a threshold (typically 18 \u00b0C).\n", "- Metadata document the base temperature, frequency of accumulation, and calculation method (approximation).\n", "- HDD is a valuable indicator for **energy and climate impact assessments**.\n" ] }, { "cell_type": "code", - "execution_count": 27, "id": "ab5cf6b21d4cbb4f", "metadata": { "ExecuteTime": { - "end_time": "2025-11-14T10:35:09.467502Z", - "start_time": "2025-11-14T10:34:19.976755Z" + "end_time": "2025-12-01T22:24:03.287174Z", + "start_time": "2025-12-01T22:22:19.467624Z" } }, - "outputs": [ - { - "data": { - "image/png": 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CCCGEEEIIIYQQoegOYEsE24bg3XffxVVXXWXyw1OUZ15531z0V199tYmiHzVqlHmP0e/+4Lb2Rwvmsff3fjJRxLwQQgghhBBCCCGEEEKIpDBhwgQ8+eSTuOmmm/DRRx+Zwq127rzzTqxYsQKXXXZZ+3tutxter9dvFL4lxNvXW8+tVDipQOqciRBCCCGEEEIIIYQQQoisonPnzqaAK5fly5fjhRdewHHHHWfWvfzyy2Z5+OGHO6S94Wc2btzYYT8s/mpt47ue64hv+ptkooh5IYQQQgghhBBCCCGEEAnliy++wJQpUzpEtjMSnkVeyaxZs/DXv/4VN954IwYNGtThs4MHDzY56S1YMJaivlUQ1nf9ggULkJ+fbwrEpgoS5oUQQgghhBBCCCGEEEIklGHDhmHdunW4/fbbsWzZMsycORPPPPMMDjjgACOyX3TRRfjlL3+JoUOHmuKv1kIOOeQQfP/993jqqaewePFis4/u3btjp512MusnT55sUuLMmDED8+fPx91334399tsPhYWFKfMrK5WNECIqeMOsqKjIitZrbm7G2rVr0bdv32SfihBCCBEXGKXEvJ2pFEEUTzitmYW/6LwJIYQQ6UBdXZ1ZysrKkA2wX9KrV6+UygcunKdbt2646667cMcdd+Dkk09GcXExjjzySJx00kl48MEHsWHDBjzwwANmsUMBn2I9C8Lee++9RnTn61tvvbX9mjn++OOxevVqsw2j6SdOnIiLL744pX5GXd1CiIjhTXPu3Ln45z//mRWtxxv56aefbgzF6NGjk306QgghhOOi/OWXX26ih6666qqsaF1GTfG73nfffVkzGCGEECJ9Wb9+Pc466yycdtppOPzww5ENvP766/jyyy+N/sD0IyJz2WGHHXD//fdv8z6veS7BOOyww8ziD6bEOe+888ySqkiYFxHx5z//Ga+++mp7dePS0lKMHTsWp556KkaNGtW+Hf9xmAcqGByxOuKII8yyatWq9vdZpIGR2CeccIL55+JxgvHmm2/iP//5D3766Sez7Y477ogzzzzTnJf9fIj1j37BBReYKs233HJLyl8Bu+66q/k+Z599NlIB/v5s84ceeqhDni627bfffmsi0Pj7HXXUUSZPmFUNm0yfPh2PPfYYFi5ciJaWFgwfPtxcO3vuuWf7Nr7XAz/fr18/7L777uZ37NGjR/u6Rx991IyK+nLQQQeZ/GOkpqYG99xzDz755BNzbsxJdsYZZ2Dfffft8Jlzzz0XH3/88Tb7uvTSS03Bkd/85jeYOnUq/v3vf6OkpCSmNhRCiETAAkl/+ctfjI0cMmRIh3vx+eefj7/97W8d7r+MOuG9joOQe+21l5kt9Oyzz5r9cBopRVvaJNojK7/jypUrTUSLBbehyHnooYeaKBe7E2Vta9n/QDCKmcd96aWXsHTpUrPPXXbZBb/97W9NnkgL7mPcuHGmb0J+8YtfmPOjjU9lwm2HRPKvf/3L9KP4aPHVV1+ZKKUff/zRROcxVyejjn72s591EPRfe+01M914yZIlxvkZM2YM/u///s88WvB3scPrgradU4l/9atfmcJcFjfddJOZcuwLhYhzzjmnPYLu73//u+lrMvqJ/Qleu7xO7PB8Fy1atM2+6OAzYorXKa+Xxx9/vD2PqRBCpAq0bxQl//vf/4blJ9p9cN6Py8vLMX78eHP/ZDFFO3afi/5W7969je2nb9azZ8+Q58YCivQH33vvPTOzmP7R3nvvjd/97nftRRd97R2DnRgN+6c//cmkqEhl2ObXXHMNXnnllZSYNU17S7+U4qUlQIZrg2nDaef+97//md+cvw9tIK8bRqPb+4B2unTpgu22267d9tt1mVD21donB7/nzZvX3pejHbe3J331gw8+2O93/uijj0xw3GeffWb6BtkSOCCyDwnzImIoxt98883meXV1Nd5++21z87/yyivbR245NWTz5s3tn7nkkkuM00RB1GLAgAHtz3nzttbRyH/44YfGgNMhpyMeCN74mUuKzj8NCY9JZ45GhtNcAkU3szOQSGiQ6OzSOKUzFLYp2FCgZueNzJkzx3QImcOL79OAf/fddyaanlH11157rdmOHQYW7KARZ+eQwjzFoT/+8Y/m2qGQ7+964HY0+qy+zbxg/L2tzl5lZaURgCxRxsKals7OyoUXXmgceF5H7JxSYGKOMgr6e+yxR/tnuC92EHkt2bGi6I499ljTMaPIf8UVV8SphYUQwjl23nln8/j11193EOatQUg6OnZh/ptvvjFOlzWwzQjqTz/91DhFI0aMMNNIn3/+eeO00xnnVFELbjNp0iQ0NjYaB4wO4LvvvmtsAe1CJPC4dMZoKzjYzhySTz75pLELtAGBHGROW+3atStSRTBJp9R0tLH8rSz7yn4Y7SftIvtMnA7MPgwHejhIYznv7IdxwJrXBO3sli1bTHQb+wV33nlnBztLUcay9U1NTUbw53XEgXMe35pyTIGHfYo//OEPHc7TEg94jN///vfmWuUAE0X9J554wjj7HLC3X+vcFwM9OGBvxyoIRhHrjTfeMJ9nX1YIITIhVzN9cQ5y8x5I/4X3aAakMdDJjuVz0d+iv8RB8VNOOcUMfHI/wXxCfo73ctr/Pn36GH+N93Tmeuajv9Qj9B/pEycyHarvIH66QgGeM73Y17EE8nBsMH9b2kwK8hwIZ2AF/V72q/g52j/6yBa0/ezzWYI+bfR1111nbDbXhWtfea4MfKMYf/3115s+JFON0LazL2fl9+Z+CEV3uz5kDeLzu1522WXGR+cgj5U3XIhMQsK8iBjeIO03RDptt912G2644QbjzFPItDtF1mc4ih7oRuq7jqP1tbW1xtDQsPgz7BQQ6PhT9GdEs8U+++xjouY4qkpD449sycnmNC+88IIRPVhAw4K/EXOC0fhbv9OECRNMG9MI0+DzenjkkUeM4ebvZf+tGOnGzh87TRzl93c9sDPFa4sGmcI6O4xkzZo1xoAHuq4oNvA6sQv/7JDyOTs3dsGAnQIWDglm7FlwhIIRBQldQ0KIVIf3Rw6m8z7IwUULiu28z/LRDrejQ8W8jrx/Uli3Zg1ZMMKZA6x0rDnYaj+Wdf9kdN6BBx5oHDbahkgGwznYz4gufo5CvwUHEPgdODgcaLZbKkS0pSPsS9HG2u0fBW5G5Vmzz6zfIC8vz6w78cQTjVPN2RjsczFC0n6N/PrXv8Y//vGPDnaWgoz9GLvttpsRZzio/8EHH7RHT9IecxZmIHvMgSYODnAggfuw+gnsY/DasfqgFBTYl/T9br79U16nHBigjdc0eSFEukNfzX7Po39DoZ7CJwPYrAFYX5+L91HOIqLvzSAk+nj2mc92eH+nuEvfkP0My8eioMv7P49DO+EP+8w3ET60U2xTKwCBPnQ4NpiD6pzV7q9fRZ+YAj0D5SxoQ+3XDwdvKI7zWBzA5uz1cOwr+3P8HAcSLBGe1wqFefY32Ve0C/M8N+ta8oV9U+oLHPDhYIQQmUarCiZEjDDiiKIsRVOn4E2eN33mUvMHI9TYmfj5z3/e4X06jRxNZVVnjuYHOl97niqKwhwJpphPMYGGgZFXNBT8ThQl+N4xxxzTnsrHgqPBjMDef//9zYACI/ysaERO3+MUQ2tqOJ/bR+tZNZojzzSgnPpHo8ip5MFgFDg7SjwXGkp+fzrJfN8OpxXyvGnEmFKGAguPz3b74YcfzHMaWDsUsOkYM32BPzgCz/O0BHTCkflOnTptM3hC0d0+Q4Lb+YtkZAfj6KOPRkNDQ9DvzchMDgBwmp4FO4RWBJ0/2GEh9uPyPPma52PBY3MU35oFEAh2YPh5pvIRQoh0gLaUQqYFBU2K7rz3MrrNcogIHTcryt66R/retylc0gH0TRniC++nPAYHQe0z6ELByD7OsLM7j4SDBRQXaAN87Z3dltttLO0cHVMOqDJ9GW00o644M492k30FHodOLSP07TAVACPMaMu4cCYeZ4MROrncN/sDjEDjc86Ms+B2bCPaS9p3Hp8DycGg3WUkGb8DbTvtNtvCF4odPG9uw4Fv2nQen+c0bdo085witx060r6zwezHpZjNc7XD398u3lhwZiQFbNpNfpbRkr7b0RHnMdneobCEdc6QjMW2M2qe/T/2Gy2sazvYvgj7PbwmOCtPCCEyDd6TGbnMlCHvvPNO0G15H6X9oj/6xRdf+N2G9336QhR1fYVU9jk4sMroan9YvrE108yyp0xdR9+cNplpTWhTeV9mkBfv0bTDtMl2P5Dwc0yNw8+xj8ABBdoQwn1w37TTtNeWrbT7tbT//CxtG2dTc9ZfMDiDj7P6Lb2A52zvYxHugwEEPG/aQfr61rkQCtUcxLBrHLS5tOtc5w/OQuB3t9vqcG2w1Z/z3Y4zzKl3+AZUBrLVnIHB/mO49pW2mn6zPU0cfXnia6t53YVKFcs250xPXsdCZBoS5oUj8EbPkUzmI3UKGh/epK20JL7Q4POY/qLp6TRSDKAjHy50gGk42AHgSC6dck7NY050Rg4wfQ+j8ZiahTnVCQ0/R6QpOjAKgdGDjBpk9Bc7NIyqZkodK4csn1tiNTsm3D87CxQKGFFIx52GlMJJIG6//XaTF5jGnsejkaLwYDfkFAUY5chpaYx247Q1++gyoxkodNs7ZzTuFCYYceavTdl54HdiNIUdig78rdhuTG1kQePKjp1l7LkdO2EcDLCcasJ0Q9yO4n4wKJyzg2Y32mx/doaY886KhLcLGfyOTIPAHLn8zfh5zqKgGMXBAPt+rHQ7bFfui21GkcoOR/vZdqHqJwghRKpAoZ02xbo/c+CYNpvOKFPMWFHzHCjmfdaKfGJEG/OK0lGlYGkXw+n8BoqE8z02BVymNQsX2nZrCrUvdG55nw5Ve8YO7/n8LrThFLJp93juFLGZW5y2ixGBtMMc0CccvOaUcLYT13PhgASFDW7D86M9pxNNUYLPrVlZtL/WwD9z0/IYtFPsKwQKFiA8PiPXOaBO284oNPY37DP/OMDOAIKRI0eabTgwb7ftdMLZZ7Lbdp4vbZl9pptvcAFto69tZ7ABrw0OFtgHVpijmDabzjiFcTrrHORgOhj7oD7bJlShLmL1d6z6MdwHnW7+PrzOaI85SGEXzRkByPz0vDb5efZP2C/iZ+05+y3hgH0kijoMVOC581q3w30xn7JsuxAiVeH9zd8SLpydRL909uzZIbdlP4B2NpBfT3GW0dKBbDVtAsXrSKBwTX+O/iztEYPaaKspcjN4jr410+TZc4zTp+SMfQZO0T9majOmWKUPTGiXaZ9pp2mT+Nw6Zwa5cV/Mw87+AWcCcn/WZ/1BW0g/nm3IYDqmdmM7sb/ACHAL2iOmBOIsPwr01Cvstdn4PZle5v33329/j30zftdAtprHpM1l4IJFuDaYfTHaWLaj72/KPoe9bkwoW2354eHYV+6XAwdsD9pp7oN2mzbXN50stQdqIDxv7o/9J15jvtcl2813IESITECpbIRjMLccjWE00OG3jAmNHqO9mceWBs2fSEwoIPgWsYkFjnrToBM6gjT+FJKZA83KscdHFluh80bBmUI+p4XxOY0jR5JpNGgc6dBS+OBrju4S+1QvqxAtnV5rBJvGiJ0IrrNys9th7j92GjhQYBlba2o5OxvswLDjxbQxNMA8N2taNgUWRvNbMDKA62kMKeDT4FM04BRGf1iDEb4pXLgfnhen11EUZ2eKgwXcj11sp6DC35YdLuZp53nT6ebIv6/IYr8eaIAZScf0BRRP+Bn7qDsHXzjaz+uEnSC2G8/RmnbHz1GMsYtIPBd7NCaFI4oM7DixU8HOAzuIHKB58cUXOwwGMC/f559/7reNhBAi1bDsDp1GDpAyVygdIquQK20VI7CtgUhre95TmaaOgjEdUNoJDlzyns8UJ+H2C6wIs3ChbbfnOo0VDsJaucNp25kTnvaOU7etgX8+UjhnRBptE20IbQAFcNpQ2nYOzFMgpkPI6Hu2E22Db3o/CuW0J3y0+i9cT+eX/QnfwmrEinZntL/lIPM86NDyPCjAs4/BQWY65RTnLWgDLSGBx6ONZGQgHXyeG3PFk2DCvD/bzsFp9g8oJjBAgdcMoxhp3+39MgoTDCzgjDvad7YN7b9vsVdf287vxmNTEGEfiI44YT+Bbc1rh9GR3I79C4oybD/aaV67dO55jtasSWu6vD0nMo9HQYaDHJzxwEAIiggcYGF/wR7Fx/6k1RZCCJFK8N5lFzKjhffVcOwxbQfvnYG2pZ0mTtpqq6YJoS9J20XbTLto+Ym0SUxhZs3WZpvQ56WttnxG2hDaSA44c+YeF9+Uuvw8fVEO5Fr2kzaX35mCMGcKWLO57LDfwCA6zlyzcuTTj6WoT5vEwQQOLNN3ZIo0K70Mz5M+Nu2OPUCOg+2WDeNMNwb3BaqPR/vkL41qODaY/jL7c5xNwL4Oz51tzf6GPy2FfR7LVjOyne1BncFKWRyufWV/hX4525htR/ibciDBSm1D+JznSI2Fvjf7WWxL+ucceLGgoE/Ng23B/qwQmYSEeeEYTG8SSRSbHUa3c7HgfihqU3BNFNbUKgsrrYndybMq1FtTz+gQW8VwKdazw0BjRtghCAbFEEa32aeVcX90Timc+IMCPw2hVYndgh0LGjAKxjS2jE6k8GzPlWpFo1lwH+xEsFNA0ZodAho8q+ifL9Z39jeDgYME7FjwN2SkHo0oBxwYZWh1bDjNnBF+jETk1EEel7nn2DlhR8KeRsb3erB+Bwod9ryEdNLtMFcdvws7aRTm2Vbs0PE3sQR7Tr1kTnt24qxq9XT0fY9H4YlCCjsX7HBY8PcKlF5JCCFSDd47GRlPYZ6OJ4Vp5poljHDivZr3Sq6nDbBPS6bDRmeKkVxvvfVW+6wniryMhqODFAwr7VkkfYNAaWqctO205XZb5mvbaSsoSHBQghHwdLSt8wpm2+lEUvTnQIBdvKZdpm2lDfcnzPN9Djz7iud0mimyc9CEtnThwoVmYN6Or01mf+Dpp582fQwKBrTtTDsUaLp5INvO8+f3Z1/Msu106nm9MALQKvzLtmIwAa8r2lcOMDAFIAdBOGPPPnORjj0XOzw3Ci1WH4Xn4ZsWkdF+7GNwgICiCWfdMT0QfzeeE/sX/M6MBmQfwRJMeA68bu1wHX8fvs8BKQueJ2fTCSFEqsH7LCPC/cHgo3ChLQ7XHgfz652207622hLSaWfs52C31RTm2UehP0k/kvdvu33mc3/p2AiFX4rzvv40BW3aEdpkf8I836fvaC9cS1tJ282Bc9om2mkOKHPWmR1fG2ulzuEgBwfeOWs92ExEfmd/Pni4NpjnzaBHrmf6Os4YoE1lmjsGX9jb2Z6vnlj9k/POO6/9vXDsK6PnqQlQRGewJQdNGGzAQQTafWtwnBkEuNj7BbzGOHjCc7EGA3hNsq3kh4tMRMK8cAxOkw9UsCMUFKgtZ5PiMoVTCtSBouUJb8yRROE5idUh4fEZscXvTWebBomdiXA6SZxebnUw7HBfgQyONc3e93NWu1uf43ahfgt2eCheW8I8IxN8Oyh2Qk2X5DlZhpWzDeg8M/qBnQN7R4JCPBfOTqBgYI3026f42a8HCj8UFMJJS8SOA6MSKPwTdnI4/Z0dFisfMsV7TqVjB5cCfiAoUDE63popYMHfN1T+QSGESBXoyFAUpiPKKcxWHlNLmGdkGdPHUJj3V8CLn6egz4XCM505RkVZEc3BsNLnRNI3oCOdbNvO+z6nq9NWMRUNvyvtK58Hgw429+EvipBtwIFpf9Bm00769nms6DgemwujAUPlYOU5cxYfhXTaOwoJ1kBMMNseSIDhbDs6xlzo+FvpeRgRaD9fRjhyYYF32mBeVxyMp8hhn71gpZGjLWW7ctAoFOzv8Rqm4EGsWjmcpWfNymB0IAfT6cjbC9b6wv1wf9a+LNjXoJgihBCpBu9PVlR4LNAmW0FJwaBdoM0JZLstwTvZtpp2iEFg9F/pf3KAl76fVdstEJY/7WuradNoi4P54f5mDLKdGATGqHgr/3koW81BAArzTGdDn5P9h0Cz1q3fJNigSjg2mNcRZ75xsURyBl9wgMOe4pWD8tb3pL2knQ0ViOHPvnIgn+3Jc7GKCLOPwoF22nHa7EAwwJD2nGl0LWHe6jvIVotMRDnmhSNwmhOjygJV5Q5nlJwdDi7MD09BlMYqVBQgb/z+BGNGUrM4aqio9Vhhyh0aUoq8jFLj9w+348TvbM/JbsGo+0B59a1oAt+iJ1aOdOtz7GiEM5rMaDyKNezEMOd9sA6BVWTNXjSVz/k7+eZ642/DaWvMDUdHniIHt7N34Ni54HQ7/t4UhOzna78eGC3hT5RnehtGElKosGN/bYnqvr8JixLZp6wzwtFf0Tfuy7cTxPMMFIEhhBCpCG0TxXfOxqKzZTmMdAY5dZoDs4w2swq/EjqLvs4to5s4GM0BUCtFSjAoCvMz4aa+IbznBxKwmX7tlFNOiUu0nh1rBhUHIJgahkJGOMXRaBs4kOGvMBntXyDbThvHvoSvPbPbdgoOdGzDte38faZPn25eW+kBgtl2eyE2TtWnzfaNIKfTz8EYTlmnDeVMQd9ieRQ2GClnnYPvQINl29me/kR5/vacTecLRQ/LHvPYbBNLlLeOy2nzdtvOvg37IL7w+vG17VbUohBCZCJMO8olHF+dg/i8rwfalgO2tO2BbDWDq+wpSOIFhXmeI2dFM6iLaWCYCi0Ull/pa6utAYlgtjqQfadNof9qif2hbLWV954BcgxUYz/DLkD7Qvtkt9MkXBtszXb03R9TxFGU97XV/H0tW80+oj9RPhz7SntMTcAS5Qm/I9vXstW07fTnfWu/WBkI/PnhstUiE5EwLxyBRoEOpX1acLTw5k3Hj1O37UVRfOEUMArb9mKfllFllDZv2vEWUC2jYXcufSOs7dP57U43I9loCO2FTTh6TUea6/zBaXU0UMxhb4dT16x9EhpSGkz7iLK/jgSnubONmIqHn6EhDgQFHEKH3IKdMrY/p8L5Yg2KWHnmmU/On7PN7fib29PuhAMNM9PU2DsF7AwwVy9T09ijDRnBb4cClT0KhB1QRu3bB3JWr15titpa+7JHS4TT6RNCiFTBKsLK6cv2+hpW1DyFaKtGil2cZTSVP8ebtipUwW4OnjK6ngO+kThRdCZ5TKsorQXvz4wCoy2KNm1euNBW0xG12yV/tp3nYfUDCNuEwgBtnd3eUwzhAHQg28732Xfh72OHtp52llFotJOMNPPtF1mRf3Y45dwaOKdYEaz9LdtOm2fBY/K3e+GFF4LadvZfaNuZ6sjfdqGuEX/QOac9ZnFBC34X9gnttp1CulV8jrC9+RvZbTvbioKNPYCDQSQ8b3+23WoLIYTIJHh/ZI5xCqKsExIMpmNh6lAKtv7SuRDaxoMOOsj42742iPdqBjyFM5jtxPfyHeAN5IfbbTJtKvOa+/rTTMHC7YLZagaj2X1hbk+bz33SdtK28DEcW00tg5kCOMMtWHAcoX2y22kSrg1mICOzEdhtJqFtpH2153sPl3DsK201j23vJ/E70H5btpq/DWfNMxWQHas+nz2FLQcm2JeVrRaZiFLZiIjhqCyFTN5keYOno8ybJ/N92nOuxQIjqTlyzGg1OpX2kVYLTltmvjLmlWNUGYUH3ug5ek5BwDePaTygoMHOCXPtMh0Mo86tCEP7qLaVP50CNs97xx13NHnZKcKzkjujxikqP/7446Zd7TnN7VA453fm1DAaJu6Hzj5TsrDwjNX+LPLKdDrMGcdidTSS/Iwv1pQ25lFnHtlg8Nh07ilyU9C3jClH21nVnlPb2amw8rTynGiY2anjcXjeFAnYmWEb8D1eR5xCxwEd5oiNBIofjN6jOM/2ooHnIAGnvPG6IczvZ+WyY7EbbsOOBDtBF110Ufu+eHyKEMydx3ZjJ4MdBHZo2H52WBzQKlInhBDpAGcJ0Vbx/utPmGd+bkZk24uAsRA5o5hYyIv2gdHItDt0QOl426dHE9pd3tPp1NM54z2VkVG0Q5FAYZ4CNWdd8b7N47KvwWgvDjbbc5zGC9o4nj+dTto12j2rT2EfTKdt5wAGxQnOCmBkGNuLqe14npymzUEM9gvooAays5yBwN+FU/IZecffgY42bRr3Z9lHTtVnijgK13ToeWzL3tnhsfi7ciYYbXSoa4MDDBywtoQUijfso3DfPH/2w3gOHDBhIVaeL8+R/QKet9UHYp+EMDCAv2GoVEeB+n/cN/sUzFVLwYC/BUUGq4C9ZbN5bXEGB8+NbcVrkO1lwdy57KPS3rMPwgF99oXo1NsLyVt5ge3vCSFEusL7Nu0xRWP6phxkZYQy64P4zkJm4Ba3pe/DgVH2BygiU8j1539bsA4cg6Nop2mbGClOH4z+H300e2qUeEF7QfvKY3LgmpHnVoFVux/OlKg8V85057kx/Sqj+umX0h9l5Dp9V6Y+pU0LJMyffPLJxqbQd+fnOSjA47GN6QsTRs1z1j5n79N+UbBnZDv1CV/oT3IfbG8OdASD500dgcK2pSswxWA4NpgzDZlbnudMu8jMBLSpPCf2OaghREo49pV9HvZZmBqHmQX4m7APQT3BHsxJO87Utuy7sO3Z5+Lvyv6XXYRn39LqtwiRaUiYFxHDKHUaYYqynA5PAZ0Oq2UMnIIGnwaE06+siuW+0HHnSCqLmXDEmMICI78pcCdipJ5OKQcG2Hmh4eG0ajrjdNKZZ86CxpZiBtuJxpttxalhFH8ZlUDnn50fDi4wf2uwqWzMFUuDTGPK78znrGDOzoIFOyfM50anmg4824iCM9+zCq1YUNxmh40CfTD4e7MDRLGAv789Mo/fm50FRt5z5J0dIOb7oxNtTX/jb8VrhceyZjnwe7Ldoum88XzYwWTxGHak2LGkM8+pkyxIQ+isswPAdmBngb8Jt6GgZC+yR8Ge++BvwY4BxSeeKzs69qK57LBSCPEt6COEEKkMRXnaRs4C8k3tRRvA9b5T1ulQ0jF64oknjPPF57ynMtUMbR7FWTu813Lh53hvpyNIxy3SSCyKxLSrtCnPPfecuefSieb50cYkYsYSB4856EsbTeeWTiztNO2NffYZnVGmB2IeV+akpzDP8+R2zI3KgAV+f4rkFIx9C9Ha4T5opzhYzSAD9hFog+jMWtAG05bS9nNgn4MWtLO0Xb7tzLoqHEDxHYjxhSI8+x78HhT77Y4y+1EUF2gXOSjCtuf7/F2t34pRmPydOOuC585riXaWgwzRCN38Hmw7CiZ33HGHEZis4u/8HQj7PRRieB3y+BTWea78jP26ZN+Hbcr9sUgsAyAYLEBB3z4bgtGd/H4sUCeEEOkOhU36avQtKXbyvscgJXv0sQX9Oi5MgUL/jSI17Yol/gaCvhNtPu0d788ctKaISp/d7v/FEw4I8P7PgXsKzZbt5nlxppqlBXCwnO9zYfpZ9il4jrTJtFv0qalpUNz2LbDuay/ZL2BaPfqgHPigSMwgMArwdg2DgXYc5KBwz/anEG3VQLNgG1Fwp08bKH2OBfsR7IPRVlt+c7g2mNcA+w20mzwn9qs4QMOAAn4fnkOkhGNfOfBAu0z9g9tQg6B/TT3Cfn2xbXit8vyfeeYZI9zzOqK+YYeBdeyHUOcQItNweeOdqFMIkRR8q9EzSoCiPp1sOrkWHOnmLAh2MkLBkWp2gtgB8p0Gng1Q4Gc0Bjs18U6lIMKHkSacBnrgbZegx4pF4X2m3yC8M/VmM6XXPvgihBCpCkUAihD2qfscOKH9po2323wOjDAIgIXgQsH7JwcB6NiHEgcyEQoGHLinuCSSbMf/fgl6rAzTjvcdhHf+IDsuhEgtOKBMO233Fc8//3wjiNMPt+BAP2cJcuA/VIohwuAEztz2l0I2G/o/nMnJ6H5r9pxIEbt9zyXosSpMu91nEN75ney2PxQxL0QGQvGYkeNWxBujJBntyNF2S5TnFHdO62NqF0Y7hANH1Dn6ThEg2xxYplLgKD47RRLlhRBCJBpG3nFgmE4po8aYfoaRaIyes0R5Rvgz+pF5dhkxFw4UBJgahn0BTjnPJtiGnOLPmZZCCCFErHD2O2cQMKUNBXr63JzlZtlkCpqso0Obzuh9zoYLB6aY4z45Cz/UTPdMg23FqHprxp4QmYaEeSEyEObHZd59pvhhzlVON6QBt+eup7DO6fKMoufUv3DhNHqKAizUwqn72RL5wHZivmDf9A1CCCFEImDqHOZoteeZZWS8PXqMkXeMeqcAEKyguy/cnvvhdHymosuWAXfOKGAko78UD0IIIUSkcICbaV6Y7oYCvW9qGRY3Z4o4Bs8xFQ3TCIUDZ/jyc5zhRpuViLS9qcDMmTNNgCFnrtvT0AmRSUiYFyIDYUQ3RWQugWD0dzQw7xs7GywKmC0wdQAL7LAQncgeGJnCgk2+MH/2Sy+9lJRzEkJkL8xHywHxYIPijMqLBor8zJP7xRdfIFtgGgHOLAxUx0hkBuyzcmYJ6xtxpgmLPDLH8dy5c811z3zQLHAshBBOwHz1rPHGxR/Ms86ZbdFAf5SFZlnzL1uEeQYisOaMcsuLTEbCvBAiYsrLy02u+WyBRXPsBW9FdsBIFxYEtMPIFuWkF0JkIozq45It0MmXo5/ZLF++vEOaoubmZlx44YXmd+f7TGPEWRMMVuGguxBCpDosqppNMA+/EJmOO9knIIQQQqQi3bp1M4My1lJYWGjyRDKfsxBCCCFSf4D9gAMOaH/NFBKsu8T0RUz1xBkTjJpnvmchhBBCiGQgYV4IIYQIg9deew3bb789hg4dqvYSQgghUpj3338fP/30U4cZng0NDeaRA+0WfG69L4QQQgiRaLIqlQ0LZqnjJYQQqUNBQQE6d+6MdOCFF17ASSedlOzTyGpkx4UQIrVIRTvO2kC33347pk6das7PggPrTFnz6KOP4uyzz8Ynn3xiIuizLTVEIpHdFkKI1CIV7Xa2k5tNnYI333wTLS0tyT4VIYQQbeTk5GDy5MnOdA56RzAPrGdku549e7YpPnTIIYdEc2bCAWTHhRAiw+14N4a1R7BtAB566CFTL2HffffFypUrO5zrtddeizPPPNOI8x6Px+ScV375+CC7LYQQGW63hSNkjTDPSHmK8uPHj0dxcbFj+/V6vaZTZy08hv3R97n12vqsHZfLBbfb3WHhP431yPXWa9+F64LBTilzJOfn5zv23bORxYsXZ1VhtHj9L65bt87k9BTRU1lZaYxply5d0rYZN27ciM8//9xcE6nSMTj33HONCE84/f2MM84wz5977jkjynfq1CnJZ5i9xNuO+7PV/mw7t7ceCe2v/bndftvtdiD7Ha4dZ1TngAEDQm4ngiM7HjubN282/4+lpaW63GIgE/rmqWjHly5diqeffrpD0Vf7tXvllVfi5JNPNjb9+++/x1133YWxY8dihx12SMr5ZjLJ9r8te21/7Usw/zvQ63Dt9qpVq1BSUtJh1oaIHNltZ/4Xa2pq0KdPH12CMVBdXW3+n7t27Zq27ZiKdltkkTBvwU5Bjx49kIr4igN8tBbf183NzR3W8bOWOGAXCazOBKd0cuH2voK/9ej7npx//2Joql4/6UJtba25ftWOsUch8X5WVFTk0C8jyBVXXNGe8sxyIjmQ9N577+Hhhx9WI6UA6WLH/dlv+/OmpqYONt/6fCDBgNvz/unPXgd6lB3vCNuZg5mpev2kE3RM1Y6xsX79etOG6SzMpyJPPvkktmzZYsR3+311ypQpOO2008y9kYPwZPjw4fj222/NZ6677rqknncmk8n+tx3LB/fnfwey3bLboZH/HTu8JzY2Nqbs/2G6wP9n9iOdHGgUIiuF+VTGiqzj4gTsGFiRAryJMCrHN7LAimTwF2UQDH8CQLjPJRZkN9bgkYgdtaPz9Oy5bY6bl19+2RR9HTFiRByOKDKJeNhxyy7TjjNC2Z/A72vH7WJ/IIIJ+oGe2wX/dLz/WIKJiL0d0/H3F9kBc8efcsop7a/Xrl1r3rvzzjvx5ZdfIi8vr8P2LP7KQU+RncTT/6YQas0s8vW/fQftw/W/Q9ls+d/CH7y+1P9x5v9biHggYT6DsRxny0g7lfLCX2SBr+BPoYAigr/0AIHEAsvR8zdVMNwphYoSTH3k0Ksd0+16ffHFF3Hqqacm+1RElgsGubm5jk05DWTH7fbaEg78rQ/kmASy45Ha8HgN4MsxdQbZcbVjKsPUIVwsLMGVKRwOPvhgPPLII3jsscew//77Y+HChXj99ddx8cUXJ/GMRab631yY8sIJexYv/9siUJq9YEK/73YasE1dZLedQ9e5iAcS5kXSIwuC5QwM1LGgYGDPG+i7BBvNtCLmIl34vTmFkce2v6fR58iQMCLSiU8++cTkZGSBHCEyhUTa8UB22krlE2i7cL5DpHbcSkNgt+OaxRc5/H3ice1kGxJKEg/rRN1yyy345z//ifvvv99EM5911lk4/PDDk3A2ItNx8n883nbbn1/t+5ozAILZ9WCD9iRW/9tqA/nf0f3GEpRjR+0o4oWEeZFSxLPT4dv58NehCCYcsFPAKAQW8rF3QEJNabIPBPgKCf6EhWDb+D5PRwMrg6Z2TCcmTpyI6dOnJ/s0hEgbUtmO04azPofdjoczCBDMjoey1cFey44LEX/69u2LmTNntr+eNGmSWYQQ20b5p5rd5iAA86NH63+H42tng/+twDhnkI4h4oWEeZF1RNv5YCeB4jyjbSLB6jz464z4vmdFK9g7JP62sXdKrM6Bb+Ff67v6fudAj/7EgmDb+24bbkdFBs0Z1I5CZA/KaemMHWceaRba7N+/f8Ttb7fFoew57Xiw7X3tuO93sx/XXkwwUjseyJ77e192PPHIjgshsoVo7TZ9b0bqp5r/7fvdorXbweyy/G+RFnQD0BjBtsIvEuaFiPNIs12wTsbUb9+Oia9Y4E88sDoo/j4X7D1fJ9PfwAGjHsi6dev8igL+RIJw3/O3hLNdOiKHXojsQUVLnYF2LRY7nqzUdaHseKBHigyBbHYgG+7PbtvPg685wMGaB2vWrIm7Dc9kOy6EECK7/W/f9+Plf1u1B9avXx+2/x2L/c5Uuy3/W8QLCfNCZPgUsGR3THypqqoy58O8nr6djHBf+xtQCLQ+0DrfiIdwOjX2dRbW+/ZHfx2PYO9Fst56zgGOjRs3tudc9HcO4bwXzmOg94QQqS0oi8wY4Eg1O75y5UoUFRWZooYkHJsdyB7bRYhIbHe4dtxOIBvvuz5aO25dW4E+43sMy47b6xyEstWy40KIbEL+tzNUV1cbu1dWVpby/jfhe4F8c/s2ifa/mQ6RMy8Z+CD/WziJhPksIF0NWqqhdnReGLGPqqczVgchWOcj1Hv218TKe2xfZ3/PmtrpO63S32OgdYHWB9qP73cOJtKHGtiwOjdCiNBQvEwFQTbdkR13BusenkqDBalmxwPZXrsdtwoR2z/nu30464I9BnrPei07LkR8CPX/JcKD90y1o7PXo/zvwP63P/vtz/8OZuf97dP+O4S73ned7+8Y6neW/51eSJjPAuSIqh1T7XrMy8tDJpGMaHKK2uXl5SgoKEC6wnRG8+fPT/ZpCJHySJh3BvWH1I6pZMeZUqBXr15pLTrJjgvhH9kb59oxEwZ/UykwLlNIht3mTDf634WFhUhXZLdTk8z67xR+kUPvDOpgOYMiSNSOQgjZn2QgOy77k2qksygvhAiMUtA5g+y2M2SiMJ8MpGOIeKH/zixAHQNnUMfAGWTQ1I5CiMjQALszyI7L/gghRCJQpLdz7ShB2Zl21ECwEKmLhPksQB0D59pRHQO1oxBCJBrZcWdQoIIzqD/kDL65Y4UQmYMG1J1B9sYZFBindhSpjYT5LEAdA2dQx8AZ1DFQOwohIkOCsnP3TQ2wO9OOiryLHbWhEJmL7LYzyP9WO6YSGlAX8ULFX7MACfPOkIlFS5OBHHq1oxAicjuen5+vZosROfiyP0IIkQg00825dszNlWQVK/K/nUOD6tnJ6tWr8fzzz+OTTz7B/PnzsWHDBuOb9erVC2PHjsWhhx6K/fffP+rrQ3e5LECOqNoxldD1KIQQkaHIO9mfVEIzD5xrRyFEZqLAOGfQAIczSJhXO4roqKysxKWXXoonnngCu+66q1l22203FBUVob6+HlVVVfjhhx/wy1/+El26dMFNN92EY489NuLjSJjPko5BQUFBsk8j7ZGg7AzqGKgdhRCR25+cnBw1W4zIjjuDisgJIUTo+6TstjP2RinoYkcD6s6hiPnsYdasWUZk/8UvfoElS5agd+/eQbd/8803ce211+Ldd9/FPffcE9GxlGM+C1CknTOoY+AMEubVjkKIyFDknTPIjjuHHFMhhAiM7LYzyG47146y27GjmW7ZxbRp0/Diiy+iX79+IUV5MnnyZEyfPh3l5eVYvHhxRMdSxHwWoBF759pRI/ZqRyGESDSyP2pHIYQQ6YOEeWeQoOwMCoxTO4rImTp1qnmcNGkSdt55Z0yYMCFoDnqK95wpdc0110R8LEXMZwHqGDiDhBFnUMfAORT5IER2IDvuDLI/zrWjiB3ZcCEyF81YdwYFGDqDUtk4h2x39nH99deblDZr1qzxu3727NkYP358TMeQMJ8FqGPgDBLmnUHCiBBCRG5/5AjI/gghhEgPJCg7146ase5MO6ofGTsKTMhO/vjHP2K//fYz4nxzc3OHdS+//DL22msvE1UfCxLmswB1DJxrR3UMYkfCvBBCRAadKTlUsaM2dAa1ozPIwRcic9FMN2eQ/+0M8r+dQ32g7OSBBx5AbW0tzjnnnPb3brnlFhx33HG4+OKL8e9//zum/SvHfBYgg+YMMmjOIYMmhBBCiGxGfSEhMhf5384g/1vtKEQq0KlTJ7zwwgvYbbfdMGbMGHz55Zf4z3/+YxZG0seKhPksQAZN7ZhKKEJMCCGEEEIIkalImFc7phLSg4SInl//+tcYN26cKQDLyHlGyffr1w8zZszATjvtBCeQMC9EmCiyyRnUjs6gAQ4hhBBCCCFEpiK/Ue2YSsj/zk7mzZuHZ599Fps2bUJubq65L40ePRrTp0836W0oznfp0iWmY0iYzwJk0ITIPPR/LYQQQgghROqhfroQmYf+r7OTDz/80DzOnz/fpLCZNWuWebz66quxfv16U4dy2LBhmDNnTtTHkDCfBWhkT+2YSuh6FEII3TNlf9IX2XEhhNB9UvYmfZDdFiJ2hg4dapYTTzyx/b1FixZh5syZmD17dkz7ljCfBWhkT+2YSuh6dAZ1sITInjy1OTk5yT6NtEf5VZ1DdtwZZMeFyFx0n1Q7phK6Hp1Bdlv4MmjQILMcf/zxiAV3TJ8WKY9uHkJkJupgCZEdtLS0mCmSIjZUiE+kGrLjQgghRPoguy3ihSLmMxw5onEY5Khw+d9gWdt6EV47CiGECEuYV8S8wxHzb/ix44fKNoXbjkLEjW4AmiPYVogURDO0nG1LQ3UA/7tUNimidhRCpCQS5jMcCfMOd7ACifIk2Lp4kmYDAhppFkKI8JEdd7gd/Yny5MkwbHiNAyfibx9Xp48dl+DkbFsKITIPzXRzmECivO+60liP4+e9gPtMr/u3/G8hUhsJ8xmOIu0cdET/+VfEi/V5BXi991DU5+Ti5yt/QEljffgfVgS/EEJkLLLjDgrz8y5CvFhb3xmvrRiGAnczjuz/I7rmNYX/4WtcrYJAaeoL9hLmnUNCiRCZiWrDOGhv6u9AvNi4MR+vvz4Um6vy8fNDfkBZyZZtN/Jnmw2BBgtSz24LIZxl4sSJWLhwIdasWePYPpW0NMPRiL2DDn1zBE52mKwt6IwHB+2M83Y6FDX5ndDicuP8sZPx1IDRqM3Ji23nyYrgF0II4RgS5h1qx2lD4EZjbDsp2fat5bVF+PuPu+GiWQeDAdBVDZ1xzszD8NKy4WhscYe1D0NpAME+xZAwL4QQwZH/7eRMN+f976qqTnj44Z1wzh8Ow9rlXcBJ8VP/cgieeGFHbK7N8y/O+4um90vq2W0hhLOccMIJOOussxzdpyLmMxyN2DvUjmPK4d57skN7A5Z3KsJLfUfgi5J+2KdyMW6tfBvli+vMup+tmof/VIzGuTsfip+v+AGHrF6AfK8nenE+zVLdiPDQFHghsgOlsnEGL/Lg9sYozNtYsKkHXly2A+ZsKMdBfRbirl3fQLf8BrNu0ebueGrxjnhz5RAcv90c7NtrMXJc3o7ifLhpce52Aeekjh3X9egcsuNCZCYaUHcGT1V3uF0/d2hvwMqVXfHSSyPw6af9sdduS/HXP/0PvcprzbqfHTAPT/93FM656jAcdfAPOGy/+cjP94QZPe9PnE8duy2cQ3Y7vqxatQq33norZs+ejYKCAhx00EH4wx/+gPz8fCxatAg33XQT5s6di969e+Occ87BXnvt1f7ZN954A/feey/Wrl2LIUOG4LLLLsPIkSPbf7e7774br7zyCrZs2YLdd98dV155JXr06BHVeZ533nlwGgnzGY46Bg5Q4YKnpBzuptgd+gVdeuClfiPwfbeeOGj1Qtz51Rvo3tQAVGzdpk/9Zpw//1Ms7NIDT263I17vMxQnLPsOe1cu8TvFZVNuPlZ0KsKKTsXYrm49hmxeh1RFxsw5NAVeiOyx43l5Mc6gynbecMHjGoacGCPmGRH/fUs5XpyzA5bWdsNh/ebj98M+R+fcjtUqB3Vdj8tHT8d368vx5KIxeHX5MJw08FvsVrrSRObZxXnuc0NzAZY3FmNVQxF26FyJ/oWbtm6TYihiXu0ohAiO/G8HqHbB4+0Btzt2//unn7obQf6bb3rhwEk/4c4/v4ke3TqmjaVAf+4Zn2PRsu546qUd8eb7Q3D84XOw74TFyMnxbiPOb96ch+XLi7FyZRH699+IYcPaRturHcp3L1IS+d/xo7m52Qje22+/PR588EFUVVXhiiuuQJcuXfB///d/uPDCCzFixAg8/vjjmDZtGi655BI888wz6N+/PxYsWIBrrrkGF110EcaNG4cnn3wSU6dOxUsvvWQE/ueeew6vvvoqrr/+enTv3h033HCDWW655RakChLmMxx1DJxJ9+LJy4e7KbqpdDTl3xeX48V+O2BJl244fOV8/G7hF+jc0ubI20R5O9vXrsOVcz7EN9164akBO+K/fYfjiJU/oi4nD8s7FWNF52IjyPM1xfw+WzbhyQE7YmL1Mpy09Dt0aWlKuah5OvSm+J4QQoiw0My3ENiLtgYSsksAT3MeXJuis+MeL/Dl6r54cd4IrG8oxJFDfsTFAz5CQW5L0Mj30d0rccP+7+LTlf3xxNwxeGX1cEwevADr6jthRVURVmwpxvLNxWjyutG3YBN65tXiyTU74pB+C3FsxRzkw5NyUfOy40IIERzNLIqhmKu9Hb15cLsisNs2UZyD3nPnluHFF3fATz/1wKH7zsdZ136Jrl2C729QxXpcfs50fPdDOZ58aQxefXcYjjzoR9Q35GLF6iIsX1WMFauLsbkuH337bkKfPpvw5JNjsNtuK3DKYd9s3T+/Y2nq2G0hUp1vvvkGS5cuxaOPPopOnTph0KBBOPHEE/Huu+/i4IMPxpIlS3DfffehrKwMv/rVr0z0+6efforjjjsOb731FnbZZRcce+yxZl8U5RlB/+WXX5p88Hw+ZcoUEylPGG3/+9//HnV1dejcuTNSAQnzGY4cemdysHty8+BujmzEnu70rB59jCDP/PFHrfwBF//4EQo8LQHOB8Cyjm/xDMduWIMdv12Dj4dVYFr/QShp2YJ+zRuxy8pV6LdlE3rW1yKnbboci8g+tt1YnL/TIfjV4q8woXp5a6a7FBHneT1qpNkZ1MkSIjtQrtowRXlSE1ig9yAf7qKm1p6vPzHdT3qZFo8LH62owMvzR8DjdeGooT9gz/5Lkev2SUsTBJ7hhH7LsVufFXhvySCz9Oxci35lmzAeK9C/80aU1dbBzQ1LWovIPrBgF0yddQjOHPIlxvRY23oMfteTZcczBc08ECJzUWBcMChY+7wVIH+7x5MXcY55atCz3++NF9/aAZXVnXHEgfMw9fSPUVgQwP8OwOgRlbjhknfx6az+eGfGYPTotgX9+2zE2JFr0K/3RvQqq0VOz1abvHFxPh5/YSzOv2YyTj3ua+y529LW2XEpIs5rQN3ZthTxoW/fviaNDUV5C0a75+bmoqGhNVVkYWFh+zo+t95nmhtG2tvXMZJ+8eLFRpjn+lNPPbV9/dChQ819etmyZRg+fHjQ8+Lnd9ppJ7OMHTsWY8aM6XCOTiFhPsPhBcecTCK2wqj+IuabXS5szs3HxrwCbMwtwKbcAvN8U16+ec10NS0ul8kTv2fVUuT6u5FXBBDnfd5njPmeW5aZpZ2uAHyy1jAtzrkLPsc33XriX4PH4YPygfi/RbPQs6EOmOgCPk6uMZEj6hwa4BAiO5CDHwBGkUeQ6sXDHPNWKps2Eb6pxY1N9fnY2FCATfUF2FhfgE01+djYWGDe+2ptb3TNa8SUEd8bYd2I51FCMf/gQT+ZpQMcDNjqZ6BnYR0uGzUDn1T1x9/nj8fo8rU4rcvX6FbQ6nwkG9lx55AdFyIzYSCSUtD5I0L/25u/TcR8c4sLmzfnY+PmArNsMsvW13Pnl6OhMQc/P+QH7DV+KfLyPDHco4EJ45abxS9tAwrFRY34/Wlf4Lsfy/Gvp8bhg0+3w69PmoXezF+fAuK8AuOcQ3Y7fvTu3dss9uuWke7MM08hnUI7o+nPPvtsfPLJJyaCfp999jHb1tbWomtXimNbKS4uNu/7W8911vuhOOqoo/D111/jzjvvxLx588x7zGFPkd4u2Pfp0yem7y9hPsNRpF3sojxzuL/efwQ2lPTC0tGtrynA1+Xmo7ClCUVNjShubkBxUwOKmhrM8x6N9Thp6bfYZd0qv3nhA6WvCbkujCh7MmbDWtz29Vt4vt9IXLzTQTh64w84fPO8pP/Da8ReCCEiQ1PiA4jylqjtT5z3eb9qaSe8XTkc1RtasGpVD2zcUoBNWwqwpTEPnfKaUFzYYJaigrbHwkaUF9Xh7OFfYnTB2q154eOBn0h9VykwsXQ5xg5eg6fm7IgL3jsEvxj5LfZ73QX3YckfYFdKOmfaUQiRuf63PbJTkMgM6ebaPLw+bSQ21FVg6ZL9sHFTqwhfuyUfBQXNKO7a0L4UtT0yb/zxP/seu45ZiWRkTh09vBK3XPE2XnpzBC698UCTAodLKvjfEpRF3OgRn20feughbNy40aSgycnJwbXXXoszzzzTiPP0jZhznmK9dc/1B7ezP1pY/w++7/uDuewtmBqHQv3OO+9sBl+Zy/5Pf/qT2R9T7KxZswbRkuz7hIgzSmUTPXSZppcNwGMDx2JSQSFG1KzChGXfobi0AUWeRhS1NGzN/+pLTltEe8eBu4SS38+Dk/Ad9ly7FPf3GIcZnQfgrH1LMfT9APMFE4BG7J1DTr0Q2YEi5kMQSJw3Ngd4c+4QPPvVKEzeOwc7bbcY+w35AUWdGlHUqQHFnRqQy6JuQfLEx5UgqXdIl7wmnDl2FvauWIL7vx2HD1Zth7M2FKP/SRuRLGTHnUFCiRCZi+x2BPi4pRyz/HhmBR55bifsPq4Qwwetwh47fo+iro2tInyXBuTnRx8FH2/y8zyYcsQcTNptGe5/ahxmfDEAZ51chhHjq5J2TrI3zraliD8ffPABHn74YfzrX/8yg5ybN2/GlVdeiZNPPhmHHHIIvv/+e9x1110mUn2HHXYwASP+fhsK+oTCuX299ZxpciLhrLPOwj/+8Q8jzlu8/vrr5n3mvY8FCfMZjjoG0UXLry7oYlLBVBd0wgXzPkHPXQfDlduM0uK1QHS14+JHiAj7iuaNuKZyGt7rMgg3lO2F8/frhTHToh/NiwV1DJxDkQ9CZAey4z5c4yeFjR9xflF1d9z/8Tjz/OrJ7yN/4B4oci9HUU7lto3sb3+JwE+0/DbrAQwvqcbNg/+HV78bhqte3w9X7rHIFMVKBrLjQggRHM108yU8/3ttVWc88O9dsLqyK849/TP07dsPXm8eyrqt3XZjfzp3Wepcmf16b8Kfz38f738yEDffsyfO2dIHu+yzKinnIrvtHPK/48/8+fONCH/FFVdg5MiR5r23337biO/nnnuuec288N9++62JWL/uuutMAVdG19vZtGkTioqKzHPf9VxHfNPfhGLu3Lkmx7ydww47DPfccw/uvvtuxEISJvmIRKKOQWSiPPPGv9h3BC4dcyCGb6rCLV//DyO7VcGTmw93c6op8pH9ox9YuwjnVX+KO0ontOfHSjTqGAghROTIEbCJ8iGob87B49+PwbVv7oO9tl+C6w9/FwNLN8DjzdsmV21QQdxawt0u2BLtPnxy1P98zI84dbevccM152HlypVIBkpl41w76v9aiMxEA+p2QtvtlhYXXnl7GC6+4SAMHrAOt17xNnYcsbY1x7y9+GuVbfFHsHX+tgu1vxhhtoz9Ji7G1DM/xt0P7W5EvWQgPUikC9XV1Tj//PNx0kkn4dBDD21/v7GxcZu6HYyk5/tk8ODB+OGHH9rX1dfXY/ny5e0FYX3XL1iwwNThtFLhhMvuu++Oe++9d5v3d9xxR8yePRuxoIj5DEcdgzZY+DQE87qW4L7td0XX5kZc/+176Fe+CWj7X/Xk5sHd3FY0Lo3ZqWENzlz3JW6+7CJcXfk+BjTbRhYTUBhWHQPn0FQ6IURWEYYoP3tNbzzw9S7Yrtt63HLU2yjruqV9nacuD+7iKOx4BAVmw9pHjNH4++6+BLW5+bjuyjNx7YnTUFa89Tti98TYcQnKsSNhXojMRf63RWi7vWBxD9z/5DgU5Lfg2qnTMKDfVt+UA+p5rs2R/wDRCO1xjMAfPaISvz31C9zy10tx1XkfYGDFhq0rE1AYVvbG2bYU8aGxsREXXXQRBgwYgOOPPx5VVVv/KffYYw+Tuuaxxx7D/vvvj4ULF5oUMhdffLFZz/Q2jz/+OJ566ilMnDjRPHbv3t0UZiWTJ082gjpT3/Tq1ctEt++3334R1wJhZDzPhbnkL7jgAowePdqc96233oouXbrE9P0lzGc4cqBsonyAQql1Obl4asCO+KS0Aicv/Qb7FiyGu9ynHXMyQ5gnE7csR507D9eX742/rH0PPVvq2la44i7Oq2PgHBJGhBBZK8r7pK5Z31iAR2buhLnV5fi/HWdhfN+V29R48SAfbqSAHQ+VNicMEf/wcfOxuT4f1z+/N645YRqKOze2bvuGCzhUdlwIIZKJApFCs2VLLv7zyGh8+Nl2OOmob3Hgnj9tU7DV68nbGjGfjBTt0R7Tj6A/fqeVqNvyNa7/+95mAKJPz7YBh2pX3MV5+d/OIf87fnz77bf45ptv2oV0OxTVb7nlFvzzn//E/fffj9LSUpPX/fDDDzfrhw4diquvvtpsR9GdrymWWznkKfSvXr3abMNoeor3lqgfCcxn/9lnn+EPf/iDEf0Zxc/7PY/z4IMPxvT9Jcxnwc1DNxD/0AR+VtIPDw/aGSM3VuK2yrfQvaDB77bpnsrGF6a12ezOx1/K98G1a6ehh6c+IcfVFHjn2lEIIbIdjxd4b/UgPLV4R0yqWIY79n8TnfOa/W+LCFLZREqp7Xm1gxH5QdZNmfi9EedvfGEvXHngB+ic7/97O40cfLWjECI08r8DR8vPnNkHDz64C4ZuV43brnwLJd39+6EtTGXjakyOKB8LVf6F+n0nLEFtXT6uu3NvXHvhNJT2sM14iyMaKBLpwLhx4zBz5syg20yaNCngOuZ65+IP5qc/77zzzBIrI0aMwDvvvIOlS5fiq6++Mvvmuffp0yem/UqYF9mVwqatUOqK3CI80W0Mlrq64bcbvjApXoJhUtm0ZI4wT36+6Ucjzl9fthf+XPk+unqb4h41rxkcSRBGwt0uE8T+ngDyw9y2e5zPRQgR1xQ2Czb1wOM/jUVtcx4uHTUDw4prgI7pJ7eNmF/X5ExqGn+CvO97kQr0EcJb++n7z8bfXx+PW96dhMsOmo78XE/co+Zpx33zfIo42nH+nsGwX88JSGUkhBCh8X/fWrmyK556akcsXFiCX/96FsYNDF4M1ePJhyteA+qJFurbxPnDD5iPTbX5uO6uvXHN1Gko7toY96h5DagnAf6m4ZCAVEYiet577z0TGV9Ssq3zwJQ7XPwxffp0U7iWkf3houKvIqvyyq/J6YJ/9NgNl/fcHwOb1uO26rdCivJJyTHfP8TiECdv+BZDmmpwU9meqHflhJ2PP1rUMUi9gscRC/hCiISS1TNk/IjyS+uLccvSibjxu72wW+kK3LTzO62ifAhMxDwcdPBLw1gffn88Ktwu4He7f4GC3Gb87YM90FLlak1p86TseMbA3zPY5R1jzQIhhHCWbe1PZWVn/POfu+Kyyw5E376bcMcdb4YU5a0c8znuFEhB5wS2IrMnHPE9Rg1bixv/vhe21OdGJuRGgfxv59oxLCL5LeP4u4vYWbJkCfbcc0989NFHYW2/YcMGk3t+6tSpEeevV8S8yEx8xOUadyGeLx6JGZ0H4IDan3DX6jdQ7Anf0HdIZRNIGF+O2OkfwXYOHI+tdNa6L/G3kj1wW+lEXFz1EfLgQbxQxyCB7WiJ8v0dvD6FEAklq6cf+4jyqxq64pnKUfhqU28cXjoPfxj9OTrlhp++xQsXXExi55OfPiSxiuvhRtAHOk6wz9UAuW4vzt/vU9zw+l6496td8dudvzCCfbyQHU9gO9oHWIJdt5Y4/5lLUfNCiCTS8Z62bl0hXnxxBD74YCD2228R7rzzDXTv3pY2tjb03kyOec50a4sdi4lAtjTOA+j+4K3/jBNm4++PjMdf/zkJl/1hOvLz4ud/Z3VfMtF2W0J7RnH66aejX79++NWvfoXevXvjZz/7GcaPH4+ePXuiqKgI69evN4Vgf/rpJ7z66qt4//33cdppp+GDDz5Ap06dEiPMv/322ya0n0nzGdq/ePFivPbaa+bE+JoJ+5l/J1Cl8iuuuGKbUafLL7/cfMF3333XJNXffffdccABB5h19913H5qamvC73/2uw42FeYiY4+fSSy+N9quIDGajOx8vFY3Au10GY6+6Jbhj9ZsoCZZPPYAw7umRD3evJqAljmK5g5HwkcD/pnNqPsfNZZNwd8l4/LHmU7jjlNJGHYMEdQzaRPl6dw6+69YTX3Xvja937o2e9bU4dvYcjLRVOe8A95nN0blZhux46pO198xz2+5vpUBVYyc8VzkSn2yswCElC3D30NfRtWcYke8+QqYR5SOlNI556EudE/YLNrbgkt1n4M8f7YvHvhuL0/p+DdfdLuAc2fG0teNtonxtUx6+WdsLs9f2xneVPTGofD2OHTsHg8vW+7/mJc5nNLLbIh3YtCkfL788HP/73/aYOHEZbrvtLZSV2fKph5nqzeSYjyVivjqCbUpj3G+E/QV27X532he45d5J+NuDe2DqmZ8gJ04pbTSgniDaRPmGxhx8/2M5Zn/fB9/M7YWS7ltw7KFzMGp4pf8J6gkoACyi5+CDD8bcuXPx/PPP45lnnsGdd95pCsmyD8f/LaZ3HD16tNG/77jjDgwZMiSq40QlzFdXV5u8OfaQ/Ycffhh77703TjzxRMyfPx9PPPGECeP3l49n8+bN5ktceOGFKCgoaH+/S5cuqKmpwaxZs/DLX/4S//nPf7Dzzju372P58uX44osvjGAvQpO1098nulDrysN/i4bhza5DsNuWlbhlzdvo2VIXtTDuyWGO+caERbKHhYPHYpT8hdUf4y9l++CB7rvgzPWz4IqDOK/ir/GF7btixQrM7jPMiPE/FJdhYO16jF2/GufM/wwLu5bgrom7o1dDLY5dPgc7fr922wmnEuezAtnx9ICBDDk5ToSKpR/rWwrwwqod8MH6gdi3+2LcOeQNdM9rCB7tHmk0PJIUQefE/n1SmLDo7Z/2mI6rZ+yHrvmNOK58bqu4e7LzdlxFDZ1px0CDcYv/WYqv1ozAV2t7Y+H6EgztUY2deq3GwQMXGpH++rf3xtDyahy701wMLfe5ECTOZyyy2+nzv52dPrgLdXW5ePXVYXjjjaHYeedVuPnm/6F37zBC4wPg9eZFnmO+Oo4R9dXOCvy5OV5ccOYnuP6uvXDfk+Pwm1Nmwh0HkVZ2O77tyPdXrlyJ2R8NxVff98YPC8pQ0Xcjdhq1Gr899QssWd4d/3hsPMp61OHYw+Zg7Mg12wr0EudTmtzcXJxwwglmIbW1tUYDp5bdvXt3R3y1qIT5V155xYwKzJ4927z+4YcfTKS7Fd3OJPcff/yxEej9iegU5vnlysraqmDYaGhoQOfOndGrVy/zyNcWnA7w1ltvmWNTxBfBYec+2xx67xQXXuk6HC8XDcfohrW4bu176N+8KeZIda+rbQp8BlPobcFlVdNxdc/98O/i0fjFxu8cP0bWdwwCRcdF0oHn6GzXrnD9/OfAE09gy4BcfMuo+B69jRjfmJuDseXdsd/KRThv/qcottVGGLa5Bgeu+QnTeg7EfYN3RfeKeiPQ7/zd6o4Cve95ZqWDkdnIjqcH2SjMN5/jxjObR+OtuiGY0G0Zbtv+LZTl2yLtIiEaoT4J09qdonthA66Y+CGumr4fuuY1YnLJQsePkfV2PFAx1nAL7rZ/vgIu9xjgu9eweXUevl7b20TFf726N3Jdk7BTyWocvv187Fi+xgy6WAzpsQ6H7roAb/+wPf76ziQMLFmPY3eagxG9qjte977nGceCwCIxyG6nB9kYhOT1uvDaa0Px4os7YIcdKnHttdNQUbEx5v16mMoGYaasi1fB9Uj3G2pGnK0QLCnIb8Elv/sI19yxDx57fixOO+7rAKVzoycbNaGw0stEMgDCfbQUwrXlBKD6UdTX5+C7H3uaqPiv5vRGfX0uxo7sgb13X4JzfvU5uhVv1TBHbF+NAyb9hA8+HYgH/r0Liro2GoF+3I6rOrrcvuepKPqUhVq003p0xML8999/b9LVnHHGGe3C/Lhx40y1Wjs0SEw94w8K8127dvW7rk+fPkbkv/rqq00qHL62YD6fb775Bm+++SaOPfbYSE89Kx36jO4YTNn2JjsNA/Fel0G4supDDGryM803BVLHJI1g37ct8r6rtwmXV36Iq3ruBze8+NmkfHT9yLmiO9nYWXW0uCpFef5c3brhh5ISPH7wPphXVIpBteuw07rVmLr+EwxqWtda1ZtpzfxkrMnzenDwmp+w/9pF+LBsOzw8aGc8U9GIY7+ei11XrvTfGVQUfUYhO54+ZHwqGytljY0Xa0fi+8aeuKn0HfTptTkpp5VW+ARMl3euw+UTP8SfZ+xr8urv92guCk8LPxc/sv2aDAbTxJTEXnzV4wWWrO+GBbW9cO9X+2FRdQ8ML6nCTj1X48jyH1HReSNcQYSdTnnNOGrHHzF5hwV458fBuGPaBPTttskI9KN6B5gqT6Fe4nzaIrudPmS+CLrtDWb69AF4660h+NOfpmP77dc5JnSb2jAub/JE+WiJJF0dRb7OTfjTOdNx9W37IS/XgyMPKkDRdluF3VjJ6gF1J3K+VzNlCbBsVTfMW1KCp57ZGz/8VIaB/dabqPjzf/0JBg9YZ9ITBSI314sD9lyEfSYsxozPB+Dx58fimf+OwjGHzsX4nVb4/6yi6LOKiIR5Cu1Man/EEUeYiPf2neTmtr+mMfrqq6+wbt06E9nuj02bNqGxsRF///vfTcJ8JtQ/8sgjTaQ9OfXUU/2K9zwGj/34448bkb6ioiKa75w1ZFuk3XoU4EmMwcV5HwUW5aMU412RRAynQjqbSL+nbfsS1OOKVR/iXz3G4ey+R2DYkfti17Mvwm677WYKXcQC7w/Z0jHgPa6qqsoslaf/HJUTRqG6uTPyWlpQsmULutfXtz52q0fJ4EIUL6gLKHbU1dXhmwnD8NXe4/B1UW/kFHXBpC75OGjNQkyd9zG6WoWJfW+J9tfLOq7K9Xqxf+Vi7FO5BB+VVeDJXXbEM6NG4Zi5c7H78uWt4r4difMZgex4epFtdnxFcxFeqx1qRPneudFPf4+adImWDyEG9y/ahD9NmI6Hv90ZT87ZEaO+2gu7HnaVCaTxl2IyErLJwa+vr2+14ZWVqJxzHKpWjUbN5k4ozGtGj6716NFly9bHaYUo2iewHd+4cSO+fmxHfLViPL5e0Qtlpd0xdkiuEdhH912LTpvCHDyx/XwFuS04fNR8HDR8Id6bPwj/mD4eZV3qjEA/tq+fqfIS5x2D+WWZb/aTTz4xM8Q5pT0/P9/M+B47diwOPfRQ7L///o78r8hupxcZHxjnJ5/8Y4+Nxfnnf+qoKE9cW7xAYZqJ8lGK892LG3DFuR/ifqa0+dPPMGTgfthtwlTsuuuupuhkLGST3bb731WLj0JlzShU1XRGXm4LenSrR49uW9Cjez16FG9Bjw2d0G1gbVD/+7tPmJ5mFxMZz6i3vffKx36TFuGPv/7URL5HCtMX7TthiYms//jLCjzz6ig8+2qrQD9h3LJtBXqJ81lDRMI8i72Wl5dj1KhRJhe8L//973/x6aefGoN0/PHHm3w7/ujWrRsGDRqECRMmmLw8TE/zyCOP4Pzzz2//xwgUUT9y5EgMHz4cL730En7/+99HcvpZR7ZFNT2KnbAHlmM4LaFdsHYgMp6pbOLO8ijOdXl8ZgH07lOLK5d/iM2uPHxV2BtfzJtnil3w/58dBC6DBw+O+PoK1DFgyqp58+Zhzpw5xgHmtRvpwvtOqG0ocNFp4kycvn37moXPOeAQifjF78HcYu3CO532ysr253ykE857HdustFsvlDfWYbB3HZpy3VhX0gnL84uxLr8T1uUVmsfGE05A95IS9OjRw9w7KZ5wihTbZcGc77B9n6HYaf1qXLTmI/TJdWNN0YEYWG27AEKNU/qubxPqc+DF3lVLsWfVUnxa2h/PjRxpBPpj18zBxKplHQV6FpVdpunw6YzseHqRTQ4+o4jv3zAOR3b5MS6iPCPvghLIgfanY0cRJR2QcCKwAwkPQc5jcPf1+Mte07C+vgCzNvfBzNmz8dhjj6F///5moJ12nAEukTrrgew4HVimtmSBLAbnOGW3fRcW2aJIYdlvy54zPWYk/yv8HgwUCmTDuTBIiDaZdrysoBzlhbUY0rsG9Y25WFfbCUsqu2Hd5k5YV1toXnvum4LuPco72HH6OWyTJYt+xIheA7Fzv1U4esxcFHcvx2bXEPT1rtx6HYS6rgKMqeTnejB5h4U4cNhPeH/BQDzw8S4oKmw0RWLHVfhMlRcxwevj0ksvNbXUrP4w/58429sayOH/AWulsQ930003xTzLW3Y7vci2AfXHHx+DXXZZhVGjKp0V0KvCsNvh7jPYqZUjZSgvrcPl505H3ZZczP6uD2b+uBDPPfecsSXWvWb77bePyv/29xmK2Jb/vXbt2qj873Bsua//bdlu+t/2YN9woP9tt9O+9pv+d3FxcZvd7o2yPnUYVLEOzS1urNvQCSvWFJnH9RsKUbOhExobT0D37iXGZtN2c6EOuWDBAsyb9w0GVww3UfEXnv0x+vdpxoqaIzC4t0+0WxTw59hzt2WYOG4ZPv+qH55/YySefW0kjp78A/bcbSlycmz+tsT5rCDs/wRe7Mwbf8455wTcZr/99jOR7PwHp3Bu/fP5MnToULNYsGDs9ddfj2XLlmG77bYLeS6MmmfF288//zzif+YlS5aYf1oL3qR4swh34fbpMuKYTR2Dr9ALc1CO2/FWaqSqsY693GFxPtD+4vFd+wNd0YQ9ly/Dns9egGa48P3Snvhiznu47Zm+8LhcGLdlJXarX4nR9WtNAdkO+Ckcaw0W0XmZd+p2mHPMnWZ67k8//WTuFTvssIOpZG39r9kXf+9FujQ3N5sop1WrVpn7De8hLNZCI88Og6+jz/tLIKednRnO8jGGv6zMLEzpxUcjxpeWmugpFiP2jVb3hS3FXPHr71xiBj05k4jCBjsXrPA95p0b0WXp1tRg9d1L4fLa2juayUM+0fTsrk2sXo49qpfji5J+eL7/Dni2/ygcvWKuEe0ZYS/Sm0yx44sXL+5gxyOx3+lmxzN/SvxWpm0ZhM3efCPMByXKAq/tdWJKYhTl/b0fTFCN9FxDCbQ1keed37/vYuyPS9CwQw6+WdELM798B9e+1MekRBlXsRK7DViJEXlVyHH73OdPDmzHa+/Ixw8byjBn+5uNU8/+Nf/3GUDDe4MTNtvfQttLO07bvXDhQsyYMcM85/sU7H0H3ilI2G243Y6zn2zZbOtx4MCB7a9px839aYErpBhEE1nXkId12/9k7Le1sH9x7OhHMOrQtSjMb2nffmNLL2CjJ/RvXxJZJN6Bwxdh36GLMWPhADz+xVg8O3sUjhk7F7tttwJufg1FzUfNrFmzjMh+0kknmes9VBQrU69ee+21ePfdd3HPPfdEdcxMtduZ7n9ny4D6d9+VY/bsPrj9dpv/7QR+UnFGJcpXOrRNtKJ+oKh5nzzzvnTu1IxJuy3DpN3+iOYTXZgzvxwzv5mGO27ri+ZmN8aNWYXdxqzA6OFrkZ/vCZmX3JqxbgLhZg7AnOV3GbtN8Zn3MdrtQP63E344/W+mwqb/vXz5cnzxxRfGbnPwm+K8Za8t22353/58cNp6DlTY7TZnKdn9ceN//2i7XwRp6y31uVjnWtLBbtP/PuiggzD19OvRtctW/7uxqbvjNQd5q9hjlxXYfecV+PKbPkagf84I9HNNVD1T4IjUgTrN7bffjq+//tr07/wNpEdL2FZ1+vTp5h/hrrvuMq+tauM00Jyqx04BR5e4UODitL4vv/zSb8fAF36GUQWcBhgO7Cjvs88+JtKex40Edjw4EmZ9B2uUz9/C7+v7Hrf3B292/gSAZIoD2STMP4+ROAZz0QURVm5PRYE+UWlwwqVt9kFufy/GYo1Z/g+zsQjdMbNrX/y762isRlfz/m5YgV2wygj6pgbAM633CQrxjCBatGiR6QjM+XoW+mEMRr5wE45AJXZAFYqWNAJLIjivSGZE2Np0gJ/VnBmwalURVn3XFStzi/BNbhHeyi1Ci8uF8uY6lLW0LiOaa81jeUsderRsgXtJ8IEII8qHgasC6OxtRufj+qGv736sfVBIX2az4gwvtd6PFdu+6UrsXrMC42tWYFb3PniuYqQR6EdurER5Qy3KdhmE8kdfae8AReqcieSRKXacwpk/O86Ov91ec/o/nRD7+1b0Tjh2PBybzs/E244z4jYbeH7zDjijeDZy7flkI5wKvg1toqbX3NkCODeRivKhtrWE1dgyxjiHT+qT3bZbaRb+G8yrLMXMpX3xr092wYa6QuzSaxV267MCY8vXGNEeT7raxXk60LTjS5cuxQMPPIDFC4/AoK7rMXLjLZjSvxLDh1dtLVJa5XAb+OxnIP/l+rUtbaL4pi35WLmuCKvWFWHliiLMnNUVKzcWwe3yoqxrnYlE7F1ci9H961A+sg5lRXXoVlHfcdr4ED/XSI1rW8G8dFtxiLeBLoVN6FJfgf47+uzns5P9fCk3XF09QJ7Pvh1os1y3F/sOXYK9t1+CjxdV4D+zRptleM+q1rZYMBDlB7zePviQLb5CrEybNs0I3xSBwoGBFRR3KM5TmKbtipRMt9uZ6H9n04D6Cy/sgKOO+gFFRY2plW6mMoHHiXPEPYXZMTusNcvpU77CkuXdMPObvnj6v6Nxx4NFGLvDauw6ZiV22XEViplaxRZdbQLh5s0zg9i03999OxN9e43FyGE34bC9KrHDGZWtn3EaPwMrAwZzKl/H92rr8rBqbVesXFOEVWuL8O2XRXjr9SIz+FBeUouy0jqUl9Rh2Fg+1qKspA4l3bfAbbeZw/3YbbsoH4JOhc3ohH7oO8obMjd9a80D//eiWOEtadexq8ygy1ff98bzb+yA514fiZFDK03/pbx0EMoHtvrfvBdz9qBIPL/4xS9MQOkxxxyDTp1Y0M85wlZU2LHYa6+92l9zJOn+++/H6aefbqIGnn32WZO+xoIGL9AF89RTT5nps9b+eNPgFFhOOwmXfffd1xSf/eCDD6K+MO3GPFb8dTCs9ygO8Dv6vu/bybBPD/bXubC/9vfct6ORTalsxmMFPkF/HIyFjlcyd4R45p1PxMwAn2OwjQdjvVmmYA4q0Rlfog8+wEDch10xDNXYGauwacoYzBl6hBHk+T/PiJ6DFv4H5+HHVvHewXOKBRa9HdpYY5aoCSbC20V13/dDFTW2Xztt23u7u+Hq5gktyvu2UbBr0OcceRbj1q/CLutXYW5xGRZ37o6qgs6Y3aMPqq48H5U5nbHJXYDunnqUc8BiUx3KG7jUoqxh6/NCT4v/8/Q3kCHiSqbbcRMhEyW0v1wCCQW+dtyfyG8JJr7nFYkt97Xj2RR5N75wBT6pr8CuhatCbxwoaj6AqOlBHty0OSVxEOWd/GwC4WU1ole1WU7Z7VusXNIVM1f3xWsLh+Hvs8ZjZGklxvZcg8pLd8Icz8FYsWKFSUPJqfTHd3ocI/ZYjU65zdt+Xye/f5j74r9McedGFHeuxoh+bQpQOJHnbj8ifLBz8ddF8HcNMcI+hBBlHHxrpmE4aWyinSq//TJMHLwM36zsheXri1G1ubMpNlt113lYW9fFRPmXdN3SKnr0qEN59zqU92sVQHqWtj6aiEx/5+dvICMFuffee81g0iuvvLKNYH3WWWeZKE6mYw3F1KlTMWnSJCPMc4YkH8eMGRPUOee9/Zprron63DPdbqeK/20/r1j972wKjBs/fgVmzBiAww+fHzhlVhQpbEJSnQKivP14CUqHwzYeWLHBLMcdPhdVNZ3w5bd98dEXA/Cvf4/DkO1qjEBfW7cj5iw6ygiI/J9nGpx9d3sWf/jF9+HlRff3G5RF8ZlA68u2Fr0dMnCdWcKmKgoRvirAd7Dvq8oVxvdkpyE+wrz9N9559GqTPufHhaVYtKwHKms6G7G+8sPzTb78jZsL0L243thn+wCGNXhBIZ8DDn7xM6NChA9naXIWG22/04QtzFuj8RaWo2jlkX/nnXdMh515pxkVwJG5Aw44oH17RqxZkZXMEf/666+bkX2Onv/vf/8zU1IiKebKzgALxjI3faBc9onEcqidGL2yiwP2Dof1nBGAvh0Mfx0NdrZ4TtXV1QE7Ev4e7QKBFRGY6kzGAryN7fEF+mI82vJ1OkhExV+dTm+TBpSjDpOx0Cy1yMNX6I3Z6I1uaDAjiiNGjDBROUuuOx69PatQkOiZDdEOjPgT/6P9/SpiGGzwOX9T88CeyiacffhbtzyION92vvzvH4kqs5i+yJa2hbUBXDmoyulsRPqq3M6o9HbBD0VlqCzrYkT8mvxO6OJpNDMMzEyDthkHPfn4008xCakicmTHA2NFvjtlx+15N/3Zcl87HiianzmwCwsLzTn5Tif2Z9PDEQ1SleO6zsF5lYdiQWMPDMkPw0mLIKWNB/lwozH+onwicVjI7Vu0GUcWzcORQ+dhQ0MBZq3ug28qe6GXezNOOe0UDBs2zFyL858+C0O6r2wVleMlyjuxH0vsDrSv0iiO6aCAzlkc7cK8/fjxEOhdwE791pilAyXAlsZcVG7sjCpvZ1Su74LK9Z3x3Y89UVndxQgA6zcWorhrA8q6UbSvRRmFey49alGWuzjl7TjTJjz++ON+19EXpcgcSWFF+p6cwn7nnXeaSFTCFBCWWG8J9kzL4ASy24n3v33F/kj97y1btrSnPAjlawd7TAe7feCBP+Gtt4bg448rMGlS7Hm3fUVXv2lDqlNEkI9VnA+RziYcykq24JB9FpqFeem/mtPb5KYv6tKAn//858b/5j1k6dyjUd5tJToVNDojrMdKIKE83seviu3cvF72p+MrzFvw33/EkGqz+NLY6Db2ubKmixHtaa9//KkUH31RYd6rWd8JnTs1tYv2Pe3i/WD537HAGg+c1RUPHMlBQDF+ypQpJofeyy+/bET2E044AQMGtCaNYAfm/fffx3nnnWdejxs3zkyJfeGFF4zxoiB/2mmnRTy6zJsNc1Iz0iGToCHmIEasKSKYg5NRHIyE8NfZsHco2Nnw19HgYzD85R7zzUHmKxg4Jha0pUkh7I798vPP8fitf8bOWL1tvvMYCFl4JpWi51MAphOahGVmMdy8a+tvNcUFz04nwsUI6mQQabsHE8kRh98wkhkArhy4/E3rjXQWgb/vEkFqnAJvC/o1bzILGtreXLB1P6xLUJPTCZW5XVrF+5zOWJbXDbML+6Dyb38z0Uycii2Sj+y4s1g2L1Y7zohIBjEwnY1vkS3fR/4/hSMaBDrXYLY62DYx2fG7ttpxhn4c+/rrePTJTbi2ZFrsBStLfIT5Tk2ZI8rHmW4FDdhvu8VmMULxB2OBMV7gbhe8Pc9ujRhzSpQP93PBUhoFEmrCFeUjEePDFdBLQ0R1egNE3kVSvyAafPbfKb8ZA4ZvxABs9LtNU5Mb1es6tQoASzujan1nLFzRA5993w+Vb95i7i+pbMdvueUWEyhGEd4O/VCmhzn00EONOB8ul1xySftzpow56qijsPPOOxth+Mknn8Sf/vQnc09kmiDmVI4nstvx8b9jhb87bXa3bt228b/9DdJH4n9bs+v95f9OmP9tE8vZXL/85Sw88MCV2G23FdvmO69OUKS8U6J8qPONJbVenGFe+onjlpulld04JdykZPF6j4PL1RJ/wT1S/ETRh9wuiefWYaZbEuH/Wd/em83ij+YWlxHnq6q3ivfLVxabQZuq/95p/IVI05GJVn7961/jlFNOMenkGHTqy957741oidr6UHxnpXkLRgcEyrnnbx1z1HEJl7PPpiOwLRT0hX+sqXT2SEAnsXIEBhILuHCmBEeV/FXstjod9hQ+vvgrNBKo+AgHafoW5ePNlnGY3PID3M2NcHuaOhbJjAJPTj7cLU2ZI84nI3K/LT2L150LlyfA1KpEEG67909wO4Z7vOVbI+Y7zOLon0LXo03Yz4UXPRkh31K37XavfGBm88RSJEXEhux46mOlpLNP/Xcyr6TdjttttG86gEDrLdE/kB33JyAEs+NMEzH9xUfxEUZj97wlcHenHW/0HzUXTBj2Wefpnmf6BEFJB1E+UpHWye9099bfd5tfOoK0QhETjhDiJ+d7RPsLda7BirLWhCnO+xzXW++Gq8XLaIbg5+yUUB/lzIG8PA9696w1C0b4HH/I+yltxxkUxlQOFOB9hfn77rvPCOpMzRSJMO+bBucf//iHEecteBy+/6tf/QrxQHY79Ukn/5v4s92R+N8sKDx4cA5ee21X/Oxnc+F2N8LtboKrJgL/24/w6vGNTnZalI8m732A+3lMUfPwEYBDidCRRJm35Un3enPgdjWnjiAfTqR6tOcX7DeKlrZz8Ta7gS3e4OcW4ywIJ2Ah+J6MlC+l/+1zsqXyv2PBCjQ//PDDt1nHe2mooOZgqGpfBhPvHHdO5gj0h704kL1D4ZsiwC4aHPL7q/Du669gVM4weHLz4XHnmblAJvWHLSWN9Zq4Pc1wNzcZEd8S890tjXC1NCGnpREedy7qu5Shps8YI9C3Lo2tj2bbre9RdHYlUgyNNkLaqeNHiNeVY9o7qYT63k5EnUfz+Qi2ZY55dPc4W18gCQM22ZI7W4h0sOPxKCQVyHb7vrZH+x926h/w9Yy30LdoCTxd2uw4Og5Kegs7Wlq3txnuwia4vY1wd240+eTd3qbWx66NaGzqhi3ePljXPAbubk1wNTTC7WqC22U9ttlxVxNcrubYo/UznSCDIAHfi4RYHOpgkeqRivLhprcJJpgH+C4dpsRHMrAQjVBf4mAb+wxSpKodZ27x22+/3eSF9y2gvWDBApNT/umnn8bnn38e9THmzp27TZ7Zww47DPfccw/uvvvuqPcr0pt413hLNf+by0EH/QVvvPESxowZAq+XM/zy4N3ivw040M7IYwrFFPDdW2irt9pkl6sJOa5GU9S7vqUUNfVj4N7YZqe5He06rNeti8ssERBrMdpA4q8/cT6SIvbhplqJUPz1INf0bcI+RjKJ5vyqEyTQ026HipiPJk1PgklVu50OhJqFHAsS5jOYdC/+Gk3Hg5EkN998My7yPhPW9t42sdgS8dsfc7jkm9cNnUqN4N6c3wXenDy05OSbR7Pevm1OHrzurecaaDCAr7k/IwLs1AR3TZMZBDCDAy1t7ze3vdf22sVHs97+fjNcBRwcaNvGDApEmAs/UeJ823E8ObnJS2Xj53w6vHZin74sj1OBXpc75pkg2VgLQYh0I93tuBVRF+l3/s9/1uH3PZ8IK0WJsePIhac03xR59RS2PXLpxsd8NHm7At4WNHXtCk9LHjxeLvnm0Ws9b8prFRNgs+MBXH3a2lYRvwlud3O7uO+iyGCet73npsjQYtu2dZ15bpYWuBhdaLbn+1y8gXOZ298PJgg7XYDVdgwzKGLNnnYqnU24jnO4Od79ifOxivKhjh1x/vkAqWwiEemt41qEU/A2WFuH+/vFc3YJ65CG25UNUrP0oYcewsCBA02x0pUrO9aeop/AiHamCYuF3Xff3RSW5f7s7LjjjlFH4Yv0J92Lv0bjf5eXl+P666/HRRc9h5wcpk8Jvj1dY9pajycfnqo2m4z8Dra5saU7XGhB84Yu8CIPLd5882jWWza+Nh+evFx4Xbnb2Gy7T9yagsQLFwfxORBQ3Dp4b15zQB/Nba+bOj4369vEf+s1E3W2PXdVN8FdGoX/HSuRiPNVgLc2Fy53y7YFz9OdcGxkJAMjITDXUbg55sNN0yPSkvr6elNTlenIWIPJXos1WiTMZzDp3jGIO/1bp2O7lrfA3dRW0dLKk21jS9deaOhahp5LPnHsps6ULq2Cfp6JyPdU5sFrxP3WQQJvTm7rIEFOLpryWgcEWrfPbX2e2/a8pO3zZlCgrVMSZHaAq6t3a+eEgj7F/O2b4F7f3DZY0PbYLva3wMVZAeaxbXuP77Ydt9n6Hp+3dOwYJTuVjZ3+6XuMbVLZxAMJ9EKkBOlQAM7p72tNsQ9HFDR23DjSzQG3Y4RTblEdenb5OKx9hsLrdcHjzW0V9SkseHNbF08+vOZ5XofnTZ62CEIjOuS0PbYOBLTvxzxuFRdc9W02nN+wfqvI4HW32nBixIKyFri2tAkGnZva28I8wv7YAlcRBYYWMwDg3tgqLvB9I0SUNMG13tMqVBgRgvabSzNc/gqphoqaD0WkjnJJlOK8k/UEHBTnW4u/hrDjvuceaTR9sH1lMEuXLjXR8P6Kvr766qsm/c7JJ58c83EYGb/HHnuYnOIXXHABRo8ebdKH3HrrrX5zz4rsIBv970j7Kdzc2J51W4Cc1mK5vjRUlqKupT965gXxv5si9L+rc+Fx5cHjantEHryufHgYpOfi87YBAlcuWtxd2l7nwlPbtq6o9bXX2gc/35ILdNoq/mMD4O3U5otb9/hVrYPaxv+2BuJpd9tm6Rkb3fa+sb8ctHdttdet29oeud2qtm1K2+y0+Xzb9nystvnf/lLZpDORznhwLHqe/9dRBMalQRS9CA/OFLriiitMijyK8oSz8s444wxTFD6WOiUS5jMYRp1lW8egnbZio05A0ZtpapyiVRRvTYPT3qHoEmWEcpRpV9oHBxjx78qB150H7+qc9oECrmsdPGh7bHvdlFvQuq07p/09a5vW9zquMzMIirYee12fMZi/x1kdTsnfQEKrsN+2eO2DAvb3WhfzvnlNQcH3cy1B3zPH8Xpao/i9W1+jfTuP06V/HcHrcptzTAgS6IUQqSTMhxJtfSkFPPV5jtaKYVR7jov7awJy/NTQcIKaAI5lYes62nEjEDBqsCAHXooJHj5SOOAjhYdceItbBw34PpcmbyczAODtmgPP5tYZAmY7bl/Y+mhmEhrBgvtp60e2BQOtyx+DH8t+s1VwKGS+9K2DBYZOraILI8taHy3hgc/bBP9NlpjAgQHrfU/bY9u21vvFLXDVtj6n8IBObdttaH299XMd94OSNjvuijI9TRzFeQ7uhB15Bx9RIVJRwoko+TSCRVi3bNnSLr5b95MpU6aYKDc6zlbBWislx1577WUcbeadDxfWtvrss8/whz/8ATvttJNJB0bfi/t/8MEH4/TtRKqT7jPdYsHrbQSqHUiLVw20IM+krglIhLnlKVQz5Q0j4AOOiVZFGanuK7c0+klp06P1vm9sbdtAvLGz3py2GQN8r82Gt69vfWxBAbxmcJ+2uW2dses58C7bul37PtoG+S3WNYwxMw7sqYSs5xa048YWW0ubLW4f2O9CW9r23Nhty0772t8WuDb67se29LBsfmv/gL+0sev2/ZjncUpBFIM43z74Ei3RCPSxpB7SQIDjXHjhhWaA//nnnzf9Bt7vP/roI5x//vm47LLLTMH5aJEwn8EEK6qa8Q59KFE+glzrcSn+GuicEpQ+pMPggEWPOBzfZ+DgR9dvMOzT+8JIL+Q2or41CGDEASP4b33eurQJCNbzDtvmtz1327axfd46hs9rpomxfy6S6PX2/Mf2WQp2gYn/kxQJrMEAdjzMgELrAq//51tft35+S5dyNHYuMTUQ7O9b+7feM/sPsW7ra6/Paz7ybQoHXrhGbN0OK9u6dO3btm3n9f++2Q8/19c6jvFc4pqnTYhMIGKBOtOJMtUGp74zd20mQTueY0b3m6JvK6/PY5voHwyK8sM99/o/Rqk9TYG7dQCgXWzIaRMVWh9b11GQ2Lqu47YUGQrg7ZwDbxP31batfXuX9doNr6fteZ27fT3nFHBdO/x+dcGdbW+BC64qr4+AvvW1EdPrKSiwj90qOpg9GJHBs/X1Fto3673Wx1bhofWzmxsHmm2bO3due791qAVcv8nb8b22/Vv7QxcvXBvb3rfWtyV16vCa++rOS8Sz9bW1Xfe272StM1/O9rzt+O3Pzfq2PoC1/xS142effTZOOeWU9tdr16417zGarW/fvqYwpgUL1zK6nsVgmY4jGNyWAjzTZlqMGDEC77zzjonS/+qrr4wgO27cOPTp06d9m+nTp2PkyJEoLc2iaQtZTDYK81v1hlbxNybBsU18ZeQ6I8oTQiTipz9xPhzBtxpwlbYNDiTqe7Xx47rfYHiPe7c5HzteM57ibhvYbx2032qb3fDUt9notoH/dnve/l6r7TUpAq3P2m28ta+qNhttLZ1aXxt7bdlzY79t1Iew2z6C+bbrPFuXVS1A50C22W63+UlrwKDVttY3l6K+pRdy62rbtrNss2V7LbvZtm4b+922buXWbdDDst9tn11n2dut+7Xsduu+uLKjrW5P4uRrw9e2toBZzHeg3pOadjtdeOqpp/DCCy8YUd5eW6a4uBjHHnushHkhLMIaiOgfTcR8ggxoEgqyxu34fto5nPQrJi0BRd4WLontuMQT882N6N+2mHoEnLnATggf3QBFBrOeBYut19Zz22fZSi4XCjZX2t53tT83j8YpaBuQMMfmvtrOwXze9pkOr10dX/Pc2rYz34OPg633Oq5v/XXb9tG2rvV1W5ehfR8uYOFC1NXFKdJUiAwh2wbX27/zhmVA7yh3YBeL2xxlOoo5Lj+enYVvmpZUIFjktVPnGnFedFuEnZ92bt/G3PYpMnMwJMoBkVi/Y43zudPNgIOXdswNb01O23MGhLQ+N3bOEha6u+Fdz/9f2zq+X9w6WNC4qdjUHCjIY9ine5ttsMkSKSxBgyfQZs+5TRdX6zZGDLHsLT/TZpet11s6vuYOvJ3dwDqetyUetq0359C6/9bva7Pjluvf9hnzfF1q2nEK53bx3Jo9TLHcLphb23J9RUVFyP0uWbLERMf/61//wqRJkzqsGzBggFnsbNiwAddccw1mzJiBadOmxfitRDqRjbZ76z0jhoACm1jsCRYxH2G0vOOEI87HWgjWQTpEeQeIOrcEX8rtHQb8430pN4cxMyzYeE+ga6Gt7VulB8tWtg0CNLng7dHmfxt7t9VOm9fG1lrPt36W0f0cMCrI8WO3zXrLrlqDFq0FY7du49r29ZqtNtwbwI6b3Zhzsd7z3R4+7/nabds6+d8xwYF9ivC+MH0dZ+TFgiLmRUbReGo3AEc5mvO7NWI+gZF24aYOSUSO9GhJ5XNLElsjydtGqVsiaDefa4F1BnJaGtB97VykLRc+gHXr1mHevHnJPhMhRArReN1oeD2TIndgg4iqjJjPc28M/nl/4rxvodVk4q+gaTzE+XAGBKzHUueFf0cHHRzevnU8ujXyDWXNob9bkNqi9Y3lyM2pRfeuAew4/b5Q++8S4prw/X2cvo5LssuOn3766ejXr58pHNu7d2/87Gc/w/jx49GzZ08UFRVh/fr1Jt/8Tz/9ZKa6v//++zjttNPwwQcfoFOnTsk+fSHiRmMjr++jHd2n15uPHH/CfLJFeSfEeYSwoeFsEynx6D/Eg3DPM9R10Nb2WyPMfaLEo8727Eb3gjT2v4dml912mqOPPhq//e1v8cgjj5iir2TBggVm0P6oo4JokGEgYT6DyaYp8Mwl+eZpu+BVTMYkLDUjlC6HxOKERszHO7f38jDaIZbjhti3PcWLCK/N/P0mph0j+f8O99pP5mwNIUTW2nCyceNGvHreJLxdtw/277TI0egyRsyHNXXcEudrUiSi3vdc4iXOBzquv+9caDuXYJ/39zxVieYcIx1w8MWbE1uu2lDXRLiifEmCvm8SYfqamTNn+l13xBFHmCVcDj74YMydO9fkl33mmWdMepzVq1e3p9JknnkWgZ08eTLuuOMODBkyxMFvItKBbLLdjBB9662d8N//Hoo99liGnBxP9KljfO5jjJhn2peUFOWDEY44b982ATB/fMgsQ75tGzyzV/gE+/7R7s+JY0fRv2Q0vGsz09kF2EDZyjKeu+66CyeeeKJJY9e9e3dTU4YF5Y855hjcfffdMe1bwnwGk9bT6CaGlyN+C3LxJobgVQzDcJTgcnyIwVjvd9uQ+1seWJjPaW6tuhzOOTkudPb3s7/+6Rm5H04qm6wg2t/PKt7bw92Wg9bhY6jQqxApQ9rXibnGFZbjudGTj1drh+Htuu2xa0En3FD6Lvrmbt52w3CExQDpVcIW5oMJkJkszvsbjPD3XfleqJm6qS7El8QoNIf6XJizLEze21DFX8OdcVCa4BkFaSzSOwEd8RNOOMEspLa21qStKSgoMI66lTpHZCdpbbfDzFtSX5+Dt9/eHq+8MhxDhpTh0ktnYMiQddEf1o9NM6lsEpyLPWICFYN1UpyOJUChrV39DgKHE3FuEc25Vzq4L999JA2mlVF+9myma9euZkbc/Pnz8fXXXxu7zxoy22+/fcz7ljAv0k+UbxPk38L2+C+GYziq/AvyDgnYTGWT1+BHJAjnOP5E9Vjon6CoeaePGQ/iNRAST5xqS+ZqL2nZNi+fU0igFyLptLS0pK/AY4nyYQvyKwML8g4I463FXx1w8FNJnLeoTpBgHSSnvN9tsjFKviaSHPeuxDn4JQ7/Tun0OycA5pblIkR644pQkK+JXZAPYbdzXHUpJszGUAw2keJ8oH5BtG1ofS7U+Vc6uK9w95dAmOfdVeSlEOWfRNcQSFLNgmzjueeew3HHHWeeP/bYYx3Wsc7ORx99ZBZy6qmnRn0cCfMZCqstp+WI/ZTg57zFlYu3uoYhyDtIayqbxtjF1lQSOxMZee9kKptw0/A40c5OF+J1sK1ZgNWRKfCpXoxYiCy3425TxDmzRHm7ID+uYFVoQd4BWiPmE1grJh4Eip72Vygt1uMEwEx6C5QqO9vF2mCivZ/ZCCzsGjJiPhVFeSFE5qWxqXYFFfjsgvz226+LqyBvj5jPs3LMp5hAG5M4jygF+nBE2AD9AFP004k2dPJ3CJY6J0V/byPMJzNivjpB9QhEB6677jqTP56p6q6++moEgtqrhHmRGQ69jyjfDBdW5hZhcX53LM7rjiV53bEwvwdGNlTGR5APIEK2Fn9tcjYCPUvFzqhT2USblmV5jMdx4reKw+CHEeatIrLxJpUGlITIItIyYt5HlG/yuLGsqRhLmrpjcXN3LG57DCtCPhJKEhQxn8yo+VCpTZwW6P0eww3XOk/6Cr0lCRLew9iXSWWTiAF2IUTCSEv/m6K8jZYWF1auLMLixd3NsmRJNyxcWIJhw6rjI8gHsFktcNBuJ4tAYnq00fPR2PdKwJWfBrYmGWJ8pBHn3iSlsgn3d5dIHxe++uqr9ueLFrXVwIoDipjPUNLSoW9jWW4xnu42CrML+6C4pQHbNa3HwKb1OKh2Ic5etw49+9imtSVAzI1L8ddsFDsjHcBwQtgOR1gPJwo/DoVwY8MNJEqYj/WaTdVUSEKkOOlsx+fVleDptaMxp64cpe46DMxdj4F563FElx8xOG8dSnJCJSpP8Yj5VBXn45WDvs1x9XgY5d3S8VyynSjzrXs3u4HCONtxRcsLkVDSUphvY8WKIjz99Ch8+WVfFBU1YLvtNmDgwPU44IBFOPPMWejVq9aZA/kr/OoHL3PMWxHz8aYs/PNyVJyHw4VRAx3D3zkFI1Ujr6uTe84mYt6VwEGO6jRJc9O9Lf1+OBQjrVm6dCkqKiq2yUzS2NiIlStXYuDAgVHvW8J8Bjv0adUxuMCFteiMZzAKX/bsi8M3zcOZ62ahmyeMoqtxpjVivjH+onMmi/TRfjcnRF1/wnqk+41EnE+AEN0aMW8TRxKJ7/ezt4tEeCGy18G/xoWl9cX4z9rRmFdXiqPLf8AFFZ+gS06Tc0KxryBekkWpbJIlztscOy9y4UKSbE8yB1TiUezU64ZrowfojMSgQRTHmTVrFnbZZRe/6959910ccMABzh9UpDRpN6Be7UJVTSc88+oofP51Pxx66AKcccZr6N49BfxvznRDU+IiqZMhzseaez4Q/tqsOo1zl1fH8Zwj+FzrTLcE9YGc6MMpgt5xBg0ahNWrV6O8vOM/LQvBHnjggaYQfLRImM9ghz5dOgbrzyvECxt3wgcYiAPwE+5c/QaKPUl0oH1E2LhEzAc6bjaI9OHSPw6/aazR9ykCc/W7PSlSFT6F2kWITCKdHPw1l3fFM2vHY9amPji8dB7O6fc5Oq1vRkQZ5+IYhd4qKDtcLTuZUfPhiPOx4sdR9Xpz4XLFq+p4gnD6d4vyd2h18D2BzyfW37Ykxa7XDGT8+PH4zW9+g+uvvx7dunUz79Fh/+Mf/4gXXnjBRNCJ7CKdAuM2LCrEi2+OxbRPBmG/CYtw59VvotugGAX5amdzzBthPpFYeeKrHMozH4k4DwcE+kCDGIGKlcZLnPd3HUQrmsdKOAMfYX9X/m974586MB77jWeawyxgv/32M1HyrCNy9NFHIz8/v8P6uXPnGtE+FiTMZyjp4NDX1tbildP3wJs4FBO6LMNtvd9C2eotQF+HIpwTVfw1HmSSSN92/t5kC70ZJSAnIZWNECKhpIMdX7duHZ6/9ABM33AQDujxE+4c+gaKcxvDdwBqwhAPHYrc8lt7PFZxO5XFzlii5gO0txc5cDs9wJEMrN88nN8unOsjquvIlqs2ngMsIm5MmzbNiPDDhw/HzTffjPXr1+Oqq67CxIkTMXv2bLV8FpIOgXF1dXX47zPj8ca0yRi/0wrcesXbKC+ti48YG6swn6yZbvGKng/VvrFEzweLkmeqkWiI5HoI9ftHem0lWki2jhfkHL2c6WYv2h6PWQUS0FOSfffd1zx+8MEHmDBhArp27dq+joL9McccgylTpsR0DAnzWT4Ffu3atXjppZfQvXt39O/f3yx9+vQxVYfjRUNDA9544w288sorGIMuuBHvoG+PzSkjxLfvzxKU3QmKmA92Lukq0tvO1+vKCZ5+JaOE8/iS0OKvQoik2fFwbPGSJUuMTeW0SsuO9+rVC7m58evibd682djwt/77LCYWu3H7kLdQmrfFuUKaiRK7nRBEMy3ffBBH0+P1yTGfygMTTvz+kXy3CMX51ly1Cbbj6f57pRh77bUXZs6cifPOOw+nn366cc5vvfVWnH/++ck+NZHiA+pVVVVmVgVnWtj9b98oTCfhDI4333wTL7/8MkYOKcZ1F72H/n02bbuhr80oTY6YaFLZVDnkf1dnsDgfIo+8N56CdbXz4ndU+7V/LlaxPOg5MsIjjnZbonzKcvXVV5vHRx55BJdeeilKS50flZEwn40dg4rWsLFvuvXEnUP3wKSqpdji9WLaocdj+fLlJgKOTr3VUbCWvn37oqCgIKLz4HQP5lpioQRrYWVjFka4cvOLGOQ7z92JYp1O0X9rxLzL05xS55R2Ar0Z4MiFyxNAmJcoH7kwn4yq8EKI1LDj17Ta8Y82VOCBlbvgwJKfsMGTgzn9jjF2fOPGjcZm9+vXr4Mdj2bgnXa8urra2O9ly5aZR+ZWHjt2LG7c6R30rd8cmWNRE4WAaHe2ohAXmTYkrti/U0mGpbSxHce7Jm/bVDaZLPZG2q4l4e/LRN7FLplEdx6Z+nslGN5r//SnP+G5557DZZddZvwnPi5atAh//vOfUVKihs42gkfMt9qh778vx9/+tgd23305Ghpa8MEHJ5hrqaamxvjfvnabtrywsDDic+EMDstmW/43ixb+6fcvYvvt1jmXpzpOYmJSUtk4mdom3gTLvV/dcaabyYvu7zsES70TZJ8xE+yaShVx2o9A3zprsDE+6XxS5XuLoNC+xwsJ8xncMQg06k434JW+w/Fy3+H4/YIvMG79KqACwGtfm/V1rlysXFWE5d8XY3leMT7KLcaKgTujsrISZWVl2wj27EB06tQJW7Zsae0AnDQZSzt3w7LO3bC0azc0uHJQMXS46QwMGDAABx98MIb8aWh884E7SRGCO0/JOE8nBPoEn7fXneN/gCNVfue0wqVUNkJk8cy3Fq8LT67ZER9tGIBLt5uB4Z3bevSer4DRwOamPKzYUozl1cVYPr8Y0xqKsbxgVMiBd0bCGwH+hSOxdGM3syzbWAxvXrd2Gz506FAcddRRGPDydq2FK+vjJHSmq4CYrucdymmsoVASIJVNJKlhspWSjm3FiHmkcyFdgWHDhmHPPfc0giefkzPOOAO//e1vMWTIECO0iuwi2IC61wu89tpQPP/8SPz2t19g/PiVbWu+MX/r63OwYkUxli9vXT75hI+t/jejM/353507d0Z9fX2bAH8Ili7thmXLis3jli15qKgYauw27TeLEQ8rHR7bF0ygeOjdQkG5OTXONxIB2wlCRc2HKcoTrysXrjpPdHnxE0GqC9I2gb41lU1L9N8p1b+rCAsWd//iiy861JHhfZjByP/4xz8QLRLms6z4DMXzf47dAyvyinF99XvoU7TZCM92OnubMaRpnVnaqf4IDdPqsXLlSjOqz4UX5IsvvmjS4bBjwJx1vXv3RkW3XhiwZQMObZqPAWs3oGdLLdxW3yNcMTZeqWyiELJNpF04kfzJwN/3TqXztLWbx50Lt2/EvET5qGhNC6SIeSGy0cHfcGUh/rZsbzTDjZsGv4MeefXbiH9d85owPK8aw4urgd7Wyumo+7/aDnb8o48+wooVK4zj36VLF2PH+3WpRkVRGQYUb8AuvVaZx7JOdVtztM9vWyJ1OmpiFLkdyjWfENJRnA+jbb2+qWzCEegD/e7p1j6Oz3CIUyqbcPPmZ2v7OwintPvmlN11113x+eef4957703aeYnk2m1/s9Io2tx33+5YvLg7rrvuPfTrt20KmcLCFmy//TqzbOUjNDY2dLDbX375pUklx0LDlv/NAfeKit4YULYBh0xciAHHb0Cvss1Ikzq0QQpkR0E6iJ+x9GciEOWJtzoHrl4ZUBsmlrZ1orhuNeBtdrXa7doUjPa3XxexFhEWAbnppptw7bXXYpdddsFnn32GcePGmdShn3zyiUlpFwsS5rPIoadRZ+5DBsdfv/ZdFAbL9+2Hgv0KMehj7zYVh5uamsw0d07ZzN+3LdWNK0gUXaxibP8kRZr3T5N88eGI9f2TlcqmrWMgQT62tnS54jcFXgiRsnZ8wYIFuO2nA7Fb0Qqc2utr5Lpt94EwhLbOD3bBkHO8JprTt/YLo+k5Ky736byIIn87pFIpDeKchEq54rRYmE5Cfpqks/EiFy5XGKkFwk1XZJFtIjHTAm2IQyqbbGvHJHP88cfj8ccfxxNPPGEilt966y307NkTV1xxhVlE9uEvlQ0F9Ntuuw29erlx/fXvonPnICKpH9uZjwIMHOg1aWDtNDc3m1z1xv/eFFmq2aThZEqYdBDgnSZCUZ7t7cnJgdubQGE+FaLw4yZec6TLm3pCfKh1EuodgxHxTF932GGHobi4GE899RQGDx5sCsDPnx8oaik80ngcVUQyBZ7FidhJZEXhP9Z8GrEoHwxGBjBSvl2UD0T/AIJsJCKtU4JuBPtxzHHqH6A97Eu8SNRxQqWyKWqObjaEhPyObelyK5WNEFlmx9977z1cf/31OHHQdzhj1FfILfO2CnHWEgNMY0M7HlKUt2M/pu/xS1NLFE/KQGYqZLEI12kM87fyeHPhjkf6lZoQS0bCAfYoI+b9/c9Heg/I2HZNHDfeeCOuuuoqHHLIIVi8eLEJVGLkHJ+zIKzIPnwH1GfPno3LL78cEydOxNSpn/gX5attSwTwWjP+d7qI8v4I9J0rg9jtKNoqLam0PVpLhKJ8eyqbYMK8E4MlVbbF93Uq5uf3bddQ7Wsv2p4KNd4qo9g+zO8ogsMUdSNHjjTPe/ToYQZHyQknnICXXnoJsaCI+QzvGNCx56jO22+/jQsuuACjz9ox+p1SHJ3iAp7xYyj5frDPOUGyBGUnisb1j3K7VEpLE2sR3U5MvxKmQ58sIT7VUwO141YqGyGyRJin2PPwww/j66+/xpVXXonBrz0S247vdgHn+LHjT0Zh6+zR876R9P4i6BMdNd+W1zdp1KRBdHMEAyheLyPmk5AXPQNTr3g7cdAthIMf6jvH2iYZ2K6J5IEHHjDR8pMmTcLVV19t3qPv9Ze//AUTJkxI9umJJNptPjLd6+uvv45zzjkHO+20s/8PhCswV7uAUq//9zOUuBZtt9u9ZIn84czqCyWkBjp3mxjeKszHyW5XpWgUfbQzJkNG1POaTKIwL2E96ey999645ZZbzCwopq677777MGrUKLzwwgsmgj4WJMxnKOwQMJ/8Pffcg40bN5p8SJyi7ogo6ivOW6J8hkY1JzVlSCJS3yQwlY3bX/FXXwJdR/HM8x/s2k3B+gKtqWw8mTmQI4Roh+ll2PljgXXa8aIin6IwTonzoUT5kjBSkfjmF/cV6KuTIx56wQJyKVhkMw1TubS2ZZJy1WZYgVkTedfDC9hTTSfju4WKnM+Q9o5X5ByLcvq7b3uTOiIokhkYx4KAd911l4mk5KwKpjdyRPz1FefTTZSvikx89Ot/O9GOpSko0scRj6lL5rDdTtUoeCfTGfpJB2P6QPGoDRPpuYikcccdd+DQQw/FaaedZgbhDz74YCPIc+YxU9vFgoT5DGX9+vX429/+hh122AFTp05Ffn4+MNHBqPZgEfLxIJ1Ff6dnDKSp+BpyKl047RQPkTzc46ZS2zOVTU8P0BDmd1me6TMIhMg8WLuFdWGYgu7EE09sTWtDQd0p7PsKJr6VRJBrPthrS5z3FzVfE4OjVRL8PD3ePLjDyYueTGIVnQO1X6gBkQidVkbMu11ZVEQujni9boCzD1Jd+M6wAREnOe6443DRRRfh0UcfNa9dLhd++OEH/O53v8MRRxyR7NMTSfK/7777bpNzmKINxRpHBfRY9+VPUE3VfODJIJWKeSL2aHnidTHHfAoEJyQj97zVRk6kVqwEvLkuuDzexKVqlCCfcowYMQI//fRTez2RhQsXYs6cOaioqAg/CDoAEuYzkI8++gizZs0yncKDDjrIdBQ7iPLpJnLH63zDFHnjOpUuGlJNJA4TD3PMB+oYpFLqmnC3T1b79we8Pdxw1UYQjeVk+0ayrzS7RoVIBRhp+eabb5pCr2eccQb22GOP1hVOivKRCO/hfj4cgT6WyPko8XjzU1+YjyX1TbS5wqNwLD3eJEWLRTODIuVnJMSh+Gs8UdqbbWBU9Mknn4xevXoZJ33cuHHYsGGDiaajOCuyi88++wyff/65iaCcPHlyq/+d7Kj2qgi3iZdwGkWE9Tb+dzJE8lSNpq92MDCuLAOj5cNpr9LoZrrB6/EvmDtZYFWCfErDbCTz5s0z2UksKM5bqW6iRcJ8BrF582aTT/6TTz4xzvzuu+++7UapJsqn2vn44HG5w0u/kgzSTKBnx2Cbtkzm798/Ddu/f5oVf03x/28hUg2mQGDOYoryp556qhF64kqsorzvZwKltwl320iOG8621YCnGyPmG5H2+GufaET5GCK9vGDx13qkPP5mZJSkXsR80gc5IkXR8x3o3LmzySPO+zVrgBDOVLYKw4nsoLa21lwHH3zwgfG/U6K+QFWMnytLkljaJkhyyDIuA5exRDr71sxJFhEe3xNMmM8GUT6WdtzmeglS/DVkfvo4i/FRfR8RKUxXc/bZZ6O+ftu+MAdjmc4sWiTMZwCLFy820XUff/wxxo4da/LQrl27dusGVrR8uopky+N07uFEy7vz4fbEEGmXiDZPE4GeOeY7dAyibRsn0tk4HUGeiLbvcM4pUhU+C/j0009x5513YsmSJRg2bBiuuOIKDBkyJNmnJTIsQv7HH380dpyz3ejUMy/tsmXLtm7kdLR8NKlrwt1vsNzz9qh5f9uGOpfSCM+vFPA05cGVLhHzoQhUZDcYVns74JCZ4q/uFAhWCCa0B2qXlBPnk1xELhZSri2TC/sE6hdkH+wXvvXWW2amOov/3XzzzaistKlryYiWd0o4dTKKvipyEZGDwHErWJrOUfTVkbe1CYxzoi0zSZSPsr29XVxwNXiBbiE+F4lInwhBPppthV+oA1xyySVmKSwshJNImE9Tmpub8dkhg/Fm1yFYldsV+9cuwu21C1G24HHg+QuxdvJvgDfv3fqBdBXlk0yLOw+uaIX5RLd5KqRZCVV8xtOSmddjvAdH+m87vdOVDhHzac7KlStNjY7TTz8dBx54IJ588klccMEFpvJ6bq7Mp4iNhoYGzLh2B7y5cgg2N+XjoD4LcfrYRejW/Di8D/4Orp5nA2/fFzKHekCCRavDoXU1Dojz/vbjT5D3t74kw1LZhEOCo+S3KVjqr5BuqDyu0TqDpRGIwzXpFfHtNWmB0iiVjS9ZKs4PGjSoNUVJGDAPrcg8//uLLwbhzTeHYPnyYuy//yLccstC9Oz5GFB9CSrrfwNU2/zvRFGVornBIzkvm0DpQT7cSAO7nUiRPsr9M8e830GOeMyKCDXjIhl55p2EM9bZB4okNU680tJIZE9a/S8WfnValCdSFtIwsu7DDz/EU089hdKioZi8eQH2qFuOfJ+omw7Tv+IhgvruMwWFYCdgxHyOJ4op8P0zRCh28HdmxLwZsU+VtonXvhNQnJapbBQxH38YCbXddtvh17/+tXnN0fHDDz/cTFc+4IADEnAGIhPhNEdGxz///PMYmFOB4wd8j3Glq5BjE+k8rjy4vU3OppYJtZ9o0toEEkYjEedDHaM0tnNsFeYzIJVNCuDxV/y1OohAH6vjGCrSvyZ9RWUzwJ6uEfNZzJ///Of25zNnzsT//vc/XHzxxaYIHGlqasJf//pXUxhWZJb/zch4BmgUdx6BQ/ebj4m/WYb8fE+He11S6kYkIpI5mhQ3gc4rDLvgQR7cSDO7Hc9UNzHsszXHfFPiRPlMEOCDBid44l9oNhAS45PO0UcfjZdffhnnnXee4/uWMJ9mKWsefPBBk0v+nHkvYnRDZeoUfYxGCE6mQLs8jhHzyRaenRLo+zsrPJuOQWkzsBnJI1GphZbH+1zTJMd8BkTMDxw4sP01o+Q5XXn+/PkS5kVUzJ0719jxgoICXD7kJWxftM7vdh5XIdyFDbGLh5EWcI3ms8H2GUo4DVYMNpAgH+EMAo83DzmbG4EGP/sVkaey8RXm09V5THZxWK8LSLcc88JEylncc889eOSRR7YW6G6Deeb/+Mc/4oYbblCLZQBLly7FQw89ZGrA/OYXL2LMDmsQ5qSJ1BHlQ92Tw7WL4Qiu0QwU+EgarcEJjellU6IR6MNJM1cd+4z1mFPZpHoam0ScX1mbMO8NMfjmUOrADvsTKQPtOm38ww8/jJKSbTuP7733XtT7ljCfJkVlnn76aUyfPh3HHHMMDr3xKOQGGZH3uNtShiRKlPfdLoOi5z05EeaYTyVRPtrfpX98fmNPeQ5yWyxlJEZS/TqL9PwivG5aI+bTeAp8mtC9e3csXLiww3t5eXkdc4gKEQbr1683BYNYIPAXv/gF9v3uALgDOfYlHBQuQI7Xoftlsoq/Bltvf14awpnxJ8qHC4u/NufBZZ8S77TT5KTDlSrnFQAP8/7aU9lkisOYhBQ3XuQoYj7N+e6771BcXOy37zBnzpyknJNwjrq6Ojz77LOYNm0afv7zn+PwPY5FXl7gwTQvB9tSUYR0SiD2d/wyhwcI4pnKJtH2NVjgQbiR1g7YWK8rr2Mqm3hHy8frGKGOmYjjuVxwrW+B30vT/p2d6GdmSv8qwzjjjDNQVlaGgw8+GF26dHF03xLm0yBtzRNPPIHRo0fjtttuQ8nPQv+Xe/IK4G5KgEOfrqJpBOfmcefBHW4qm1QV5VOk4Glr8ZkkFo1LZs5/x1GO+USwzz77mGi4d955B/vtt595fP/9942DJkQkaWuee+45TJo0CX/729/Q9eGi1rqP/mgTBltcFObrQx+gJIbUHk6K8vbPRpLSBn4E+kDnEUigD3G+XvjJMZ8K4nx1kqZCx5gXvT2VTSY6jQmPotcAezozfvx4ExnPWVAVFRXmvRUrVpjaNLvvvnuyT0/EmLaGg+nDhw/HrbfeijJXqAqObWnT3E2pIzBGeo+Oxv5UOXA+lYFS2aRBjnmnxPk42lTmmHd7kqgLOU0So/cZGBfQbvvOJomlP+fktZDqsx3SjI8//tgM1tL+O42E+RSlsbER1x9/CDa6C3De+lkY/f0DwNN/DOuzLXmFyOnckNnFMKMlUjHZHWbEfKqL8vEgXHG+vz3HXZKE+Qz7fTiVjt1W4UMvAF3DbJUAg9znnnsuZs+ebZ6z6Ovvf/97XHXVVabgF6erjxkzxm+EnBC+bNy4EX/5/XHId7fgyj6zMHjLI8DDZ/pvqBI/qWyCRczHQ1R34vNOifXBzivCc6SDn4PabVckU5yvTsNI+mrA25gLV0OzyaaWyOMm5fsnQKRPmXQYqQTNa2u69tA4G6wWMY899hhOPvlkk/KuR48eJs98VVUV9t57bzz66KPJPTkRFezr3XjjAaiq6ozf/34WxvRbC2BqWJ9t8eQjx12fGkJZdYrdcyMQ5dtT2WSCMB/v3PNhprLJs/zvdM77XpUqOea9kaV6ikSgr07ftskWhg0bhqKiorjsW8J8ijLr0MFoKBqBW9a8vW3amkAiY5tI2lKRD3ezg8J8/ziIt5Huc7kD4mo06VdMxHxT1gi+jorzPm3jMdO2WxJz7CDnkQkolU38uOKKK9DQ0Hr/pADfrVs3nHDCCSalGKeuTZkyBdtvv30cz0BkCtOv2BWleT1x8YCP4A7WIfcj+rVGzPvY8XhH8Dq1/0BFZ/0JnZEI8uG8DpBjPi9QFGMyRN9oHK9kR/hXb02/4nbSjqcL/maiJLl4rEg+jJLnzGamtFmwYAFcLpdx2pl/VqQnX389ABs2jMatt77dmrYmgvu1x1MIt7shfQV5f/spTc45mVQ29hzzkUSepyrx/g4Brq/WwLiW6EV5J6/bsjQXnRkxHypff6A6DKH6cdVp3jZZwsknn4xzzjnH6AVu97ZRKhyYjxYJ86nIRBeml07EvrWLg+aSDyRAenILkdMcxoh9orALo8mKoI/yuEGF+QwUfKOifyRT6RIcMZ+xvxFT2WShOJIAevbsuc17nTp1Msu3335rpqlPmDAhKecm0oi7XZix/gAcXT43cC75IOKex1XQGjGfruJfOOK89V640clRRs2HzFWbSNE71aIYwz1uGx4Wf0USU9KlEv4GlSLIVe8NmM8qBQjn/5HbpOv9yWGYbpSLSH+mTx+AffZZErEovzViviF54lk8RN9YBfpg5xSkXFPGpLJJAeI+Yz2e13cqCM+2c/AWueGq9vrPMe9bcyGQOO/7/yRBPq24+OKLAxZ55eA8U5hGi4T5FGSzKw/fFPTC2etmRvX5ltwC5DgZMe9EtHqyhNIYBwI87nzktGzJIsE3zh0Dpx36VK9nECc4yJEWuWlbU66m/bTmJUuWmPQ299xzD84880wTRS9EMFbUFWF1c1fsPGC1/7QfwQStkraIedSH/jf3JwpGQqKFNX9CfKjziCJK3jdi3o0wa8WkumgSL3E+0H59ztnL4q9WjnkR+P8ujP/FlC3g7nvu/go2i9amqanB7bffbop6c1adL/4cd5G61NXl4csvj8Cpp34d1edNxLyrPvGCYiIiySMV6EOdUxBRPuNS2SD5qWySWuPNTiDBOtC2Th0zUsr8f44D6i6vJ7zvF+y7SoxPWzye+KUSljCfalS48MmIwRjVsBbF4RYd9cGTW+BsKhunxflE4YBgy4j5vMYNW99ItzZIIdqn0jmNP3E+w38nk+MuWMcgmWSAGG9n7ty5+M1vfmPS11xwwQX42c9+luxTEqnO3S5MXzsKE8qWIc/t5/80DBGaUd55sNmecPaRTtGroQYUHMyh7/FX/DXR0ehOOuROn2t1+Pv1Op2SLhXw99skYmZCfQihOxn/z4HOJ53uLQnkF7/4BX766Sccc8wxZladSGdc+Pzz7TBsWDVKSuqjume3eAqQU9uY2LiZRIu9oQT6cM4nhChvRcznen0Gu9I5nU0Sz7vVbnvSJ2I9mYJ8qM+a4q+e+AxERHouImE899xzOO6449prywSCEfO//OUvoz6OhPlUoqJ1Wuv0zgNwyOaFUe+mxaSyiUPx1+VpJHo6FEXNiHm3NUCSDt87hYnriH22/TamYlyKCPMZJsT7suOOO+Kjjz5K9mmIdOFuF7xeYPra7XDO8M+iFpxbUIgcb336CmSRRNaG+52i/O5hT4mPZzR6PPYZj9y/9v36OW8PcuFO11Q21UnKrxxtKpt4pYpR1LtjzJgxAx9//LEpCi/SmTb/e/p22GuvJVFHs7bUFyDHiphPBMkUqaM9dhiivDWgnoP1cIxUKKAeT6pCBMYxLa8TInGmC/JhzFh3sZMf6vj2do623dOgPbKF6667DkcddRTy8vJw9dVXB9xOwnwGCPF21hZ0xpK87ti1fmXUu23JzUdB3bZTKtM6ej6S4zmY2iRk8VeR/Ij5LCRkVfh4k+FivBBhc/e2dvzHja0e4LDi6qijwLcp/pougny8hL8Yvr/Hm5+8VDbxFE6SMJDgNTnm08yOx5rXPxyi+B0SasMlxscFzqRrbEyBNFkiQra12zU1hZg3rxRTp34M+MlgGo7o5fEWIsdV5+yvka4R4jHCVDYue/HXdK3RkgJ44xkYVxXjZwKkjHH0eA7idbmim30QqTgf6/eUGO8oX331VfvzRYsWIV4oYj7FmFE2AOO3rEBBDAImI+YdT2WTDqlt4pBr3JMjYd7RqXQS5p1pS1cSUtlIjBcipChPGC2/V88lHYu+RpKapQTwNBbAndvgPz99qhIv8S/GQQkTMR8qlY0/xz9I5Pg22wTbTzyJRWyI4hxNflWXH0E51kJm8fqeifwdfHFCBIo1at6J/8l0GhRMML/+9a9xyimn4I477kCXLl22Wb/33nsn5bxE5MyYMQDjxq1E5y3NUYtfLd4C5LujiPLOFvE9zGj59hR03qbMaKMkn7vH1HiLUkyON1XpJjK7gWj973DF+VgHO0RcmTVrFnbZZRe/6959910ccMABUe9bwnwKQVdnep/tcPr62YE36h9ejvm4pLJJFqG+cxyLf7ZGzCsaxrkRe80+cIYEprKRIC9E2DR7XPikqj+uHTstalGetJjIuzjZ8XAE51SJxnVAFGwt/hqF7QmnfVJBLEhgJGDAKO9UaIdwzqUmgWJ0iDbx1rsCb1MaRJy3F2MNhqLk4855551nHg8//HC/U9pbWtJsdkkWwzQ2Jx7+XUxCGHPMu3MjSGWTSvfNFBLlt6agywD/OxG/cVU4M9bjEDEfbzG4Ko0C43z7YYFE+FDifFX6t1GsrFq1Crfeeitmz56NgoICHHTQQfjDH/6A/Pz8DtudddZZZtv//ve/7e+98cYbuPfee7F27VoMGTIEl112GUaOHGnWeb1e3H333XjllVewZcsW7L777rjyyivRo0ePiM5v/Pjxpvbc9ddfj27dupn3Vq9ejT/+8Y944YUXYppFl06xWBmfxmbR4O6odedhdMPamHbdYoT5BOa4S5Yovzy+ovzWHPNJFpMrfJY0xYzYK2LeMUJkp3WGNL7ehEgGs9f1QXlhHfp33hS5wFfim181DsJ8ukzlLnEuUre18Fma5kUPl2rbkq7UxPH710S4/0i3h8OpbKrDOKeaEItTxGOfGYLH4wm4SJRPH5YuLUZNTSeMHbk6JjHM42WO+TDsdrrfq+MsyhMv8pBjDag71VaZ2OZVYQbGRaplJFvwjcfx7f2EaPtMrPFW7fG/j+oIvlugJdLPZxjNzc1mwJsi/IMPPohrr70Wb731Fh5++OEO273++utGuLezYMECXHPNNTj11FPx73//GyNGjMDUqVPR0NDQXsD11VdfNYL6Qw89hOrqatxwww0Rn+O0adPwySefYPjw4Xj00Udx5513mucbNmzY5pwiRRHzqUIF8GHn7bBn3dLAoyVhpo7x5BTA3ZLGo8z9I9gukcJ8otP3VAR5fxnSDjNin0q5adO0HYUQqcv0tQNMGhtDMGG5JPhrRnm7wo3yLk1gao0UzycfOP0Ksoc4/vYhC5ZGg6/YHOga8I1Iq07ANVqTItdxKoribP8hyDro3B933HHm+WOPPRa3InAiXrj8RstP3GUZcnPCqPsQRAxjKpscd0P2icNxoMWV35pjPp3bK0XO3RQsTdQsayeoSnD7R/A7eesZMe9Nj7ZIkesvEr755hssXbrUCN6dOnXCoEGDcOKJJ5oUMWeffbbZZvPmzbjrrrtw6KGHdhDCKeAzxcyxxx5rXlOUZwT9l19+iYkTJ5rnU6ZMMZHy5JxzzsHvf/971NXVoXPnzmGf41577YWZM2eaAYTTTz/d2HpG+J9//vkxf38J86lABdACFz7uXIHLqmbEvDsTMd+URhHzqZar3jeVTTIGOSrCXJ9GwnJrJfMUi1q0t3M6tWW44ojvdRTpd1wWh6j5NGpnISKhtjkPs2v64PTtv4pMlA9AWGJyIMHVV8AsjUOHPQ1EeZLUQtnxoDSK36/amTRGjrdloGsokEBfnUaCdk2M17nTKYrS0ElPRa677jocddRRyMvLw9VXXx1wOwnz6YHHA8z4cADO//UnMYtkjJh3u4L43/ofjChiPqoUdKmS+i0FUth0nLHusP8dr2jtUPtN8v+QCfQItx9kfZdIir7aPxcNaX6P6du3rxG5KcpbMJ1Nbu5Wyfq+++7DzjvvjN12262DMM+irCzIblFYWIj+/ftj8eLFRpjnekbTWwwdOtTMbFu2bJmJeA+X5cuX409/+pMZpGeqnHXr1plH7v/Pf/4zSkpKUl+Yf/vtt/Hee+/h4osvNifMRnrttdewZs0a83ry5MlmygHhyMUTTzyBjRs3mlESNmpNTQ3++te/4sgjjzSNa4c/0ODBg00OorRhmbdDOpvvCnqiq6cRA5vWxyxeM8d82kTMxyrKxzlq3uv2EZMTETWfwelDUiZoMc3bOKxOQUUchPpokBCfMciO+3COt0MB2M+q+mFEcRV69I5wYDzaPly4zmW6iPIiPKozwGmrSYH91ySx0CmPzemxdQk4h1T5zTOEr776qv05HfFUR3bbF/aft9rtH34oQ26uB0MHxX5TagmUykb/gxFjcsxXqy6ZE+Jta475CGasJytFir/jVqeZ/+1v4CeeRV/tx80AevfubRYLpoVjpLul8TJdDXPKP/300/j88887fLa2thZdu3bt8F5xcbF53996rrPej4Rhw4Zhzz33NH0BPidnnHEGfvvb35q89tSsUzrHPHP4TJ8+vf01c/AwVxCFeE4D2GOPPYwQb32Rjz76CL169TJVbZlDyLeDwSkMGYEtZ/j0zgOwV91S/8JlhEKw1xXBaF4sxCqIOyVw94+fWN46MprCgnGaC8xJyZ3vxLGWB1mSTSTtGc62EtaF7HhYTF+73dY0NvGmNMM778ppnZI4ksom0lzvTu0/nBzs0eZpdzLXu/1zsf6/xvr5ROWxF3FB/ndoPvzfdthr/JLQM9TCEM1aU9A1p6fNTTE8qZb+NJWIQsB1VBeqygBRPtH/l8HaLJZ88aHy5MeaUz9curX5JeEsrfVSw+Khhx4ygdpMQUNuvvlm/OpXvzI6sS+B6rpQ3Lc/2me1+Xs/FI888ojRoy1Rnuy6665moID562MhIcI8q9+OHj26/fUPP/yAoqIiI7yXlpYaYZ5R8/PnzzfrmaS/vLzcNHp9ff02jegr1qctH7feJOtdOfiiUz+TXz6d0rxEfW7xEtIT1VbxEl/TXWSPVYxPlwK3oX7/5UkUR6Jtu3iJ8xL1MwbZ8SBR8+xT13fCws09ML5sRfCGDJFbPmyS6ezHS5ArCVLgUqQ/sQjV4e47VGqcaI4dzhLJPhJFJDn4JbxnJLLbgWi1242r3fh0Vn/sNd6P/x0lHQR+ifLRsyWOs6zj/bvEc/+xiOKRplRJ1HnGK0I/ULFXe7HWCBdvfQxXZSQFX8M9p1DfPY354IMPTCD3jTfeaNLSsHArB5tPPvlkv9u73W54/eT/z8nJadeQ7eut5/Y0OeFgDRJQo/7+++9NDvtNmzaZ/TNqPqWFeZ4w09Xst99+7e+NGzfOJNzvcCJuN5qaWqcsMSk/09784x//wL777tthu0MOOcTkE2IqnIzgYy9mFvY1KWzKW+ocEZoTWpQi1cRzS/SP93FSITLaItWFbIuiFD7XZQ7/7nGOng8Y+RBPIXyZzxLO9iIjkB0PzYzKAdi1ZCUKc1pSt8hmqqewCbZvCfTpTazXTagI93ge22msc64P45oP5/82lMOuqPesRHY7FF7M+rYP+vXahD49NzsiHHbom6e5KOYYlVF8Rm2X3qK8EwS6BiIR0uOA+R8Pdaxojx3ruYf6fGWU/49JYP78+bjyyitxxRVXYOTIke2R6itXrsT+++9vCrBSsF+9erV5Tm2YBVwZXW+HgjmDwYnveq4jvulvQtHc3IxLLrkEPXr0wI477mhy3ffs2dMUkuW6WIhrjnkK7RzdOOKIIzqMRvC59ZrTB5ijh4nzrah6Rstfeuml5stxhMQOpw3wB3rppZdw7rnnGkE/3fmmsBd23bIyPaLk0/UcU0lI90eqCtZOUREnoSmRRHMNJaImQSIKtgY6TpoX0RWhkR0Pg3O8+PasfXBA758cuaQ4th7WtONIipiluigv0odIc7M7dd3EK9o+2dQEaceatveqU2gwRKQ8stvh8e0PvTBujM3/dkIMlaic3VSnnijvqP8daSR8sAGBYNHiwV5HS7iidHkU+7bOsTQJ/fNgQnwaUl1djfPPPx8nnXQSDj300Pb377777g7CN4O4mWuetUapHbPe6KxZs9rXM6KdhVqtgrBcz6wtzNhi5avPz883tUwjYerUqUbffv75582gALVspmHnObMI7C233JKawjwbjA01atQov4nwmbz/008/NTmBjj/+eHTv3t2veO8Lhf7bbrsNH3/8sUm+n+5s2f9EFL1xd3qI3bGmsEkWURaJTUiu/gqH9pGKgmhFlG2ZyO8TznFiGdhZHuH1H+hYts+n3CBHKl57whFkx8NjS9kkFOX+0FFMixIP8uF2hVn0LJLOfyYQYdum8gTCdMRVH6BBa4IIy4nEqfz1/q6xSL9LNPcAf+0YyTUfS8oeEXmz1dTg9ttvx9dff+23gBztZzKQ3Q6PLd7TUNT1Tmcanba4EUC+M7vLGMqjEwjj7n+nU98pxlQvrk5ewE9N4rT4PtGK1rGI0kE+693i2ro+GgE/nO/nxEBEmoryjY2NuOiiizBgwACjDVdVbb1YysrKkJeX1/6aadCZpqaioqI9q8rjjz+Op556ChMnTjSP1JZ32mkns37y5Mm49957MXbsWJMunUI/M7r4BoGHgvt94YUXjChvcdhhh5lisscee2xqCvNsSArnvilr7LAxxo8fj3nz5pkI+D59+qBv374h981G5jSGd955xzRuJDAFztq1a9sT/jO/EH9URt7zkQsHBOyv/S3W552g4YOXUOiNbepDQohFWE+XQYdUj4ZOB9Ip+j+RgvJy5z7vKvI6GzWfTu0gEkYq2/HKyo69zlA227LzdvvuqB1f+SUKhoaw42GKax4UwG3yXDjkYCYiWj7U+hgGKmLBi1y4XCogFzPW7xtqkqpdRE6E2BuvQrJOnHugwYpwP+srzluE074S2hPCL37xC/z000845phj0KlTJ6QC6Wa3k+l/1296GoUFDvjfipJ3jkS2ZTqI87HmX092Chsrar4qit8/BSPBO6SL9ifQ268p+/mXJnFWQBrdn7799lt888037UK6HYrqLLIaiKFDh+Lqq68221F05+tbb721PdCbQj9T33AbRtNTvL/44osjPkdG7VOE96VLly7b1EZNGWF++vTpZtTjrrvu6pBg/4477jBGnZ0C5vThwlEL5hJi8vxwOgaEoxTcPtJCsAMHDjQ5gSx4XlwYtW9f2OicmsBCtL7ruPAzvkUE+NouAPgTBbZ5b99C1JfuhQKvM46jx5UDl0P7MmSS8BxF1HzcI5Mr4rCvZEYvB/k+KRPlnSnR3ZFG4icbCfJpRzrZcdprf7aa73NaP2269dpux32x2/FAdnub968vQH3TZBTmODPA3uItQI6LoXcREM+OtxMCYIyzCKLdlwd5cCPM2Qdi23a24XW6WKsTkeXx2t5JaoJ4YOGksQl3f6HWCceZMWOGEcHHjBmTMq2b7v63tQTzv32Jyv92F6KhfhIK8oPY7arwba/XmyI+ToaQMj5jBuSUT3pbOiHKxyLGO9U/DjSI4yvQ+xvwCVWoNdA+A1EexrZpJMjb65DOnDkzrG2ZQYWLHUauc/EH7cB5551nllg4+uijTZFX5rxninUrLc4f/vAHHHXUUakpzB900EEdQvyZbP/+++/H6aefjiVLluDZZ581Ixd2o2qfnhAKjn4ceeSReOihh0wyf+YNigYelwt/rEiO7w+rgxFIILDEAft6z4FnYLuug1DfsDN+7Lylw/7cLc3Iaa6Hu7nBPOY0NyKneQvc5tH3/dbXXpcb7qYYRmviIfL1T09x3puoVDZOk6y0NiEGGSJuy1RNz5MCdOhkBZq5kahc8+EgUT4tSSc7bjnbseIrFPjacwoeHdZN+zNaBv4aO3Qbgpqeg1Gf02T+P12FXvNIUTjH24Acbz3cbj42IAf1cKMBOUUNyGlpMNHxOS6+3wC3qx5N3s5we2OLunAEp4tqOinOh3MsCvPdKcxHOMiRSGIVqONBgN/VCzdcaHF+//6ui2DR5ukkykdCoHYI57pIVB7/VLlGUwTmrqVNSCXSyW4nwv+2Bue3ff909B84CE3ucfhx+ZZ2P8XYbVczctz1cG9paLXNrga43fVbn7tszz2tz5k3zeVNrWshnUmY/+101HxpCgiiPlHyKa9lVKdJAeFqwFvv2jafvP08I01vE+0ARGUU3z3W2RfCwEHvE088ESNGjDCzyGgTmRefaWz+/ve/IyWFeWs03sIq0mrlkec0uEGDBhmDzultCxcubE/GHy4cpWDB2O+++w6pADsYgfLi+2Viq7j2916TsV/Npxjca337Kt5Cve5ctOQWwpNbYB5bcgvanrcuTYXFPu8XorGwGzaVbo/mgq4dp9u04W5pahP0G+BuaRUG3B6KA41wt9Qjx8PHNrGAj7bXLnjSW5SPUJz3cvaBJ02nwCda1E4VAThLcLSTtSzOKZskyqct2WzHw7blsx81nfNr5hyDU8e/iuL8Nse8pNWOM2Lb4ypEiysfLYWF8IDPC0y6mhZ0QqOnO1pQAI+3AC1ers/HFk9vNHhLUFff3+//u9vV2CbiN/g8bn3fCP/W+2hsFRDQAJfLm7kipvW+Dc/6fLi7pmjEvD+BOtpCqk4IpjVhpAVyQpiP5NjZVsA02CBFrPsJtX0k20mgN/z617/GKaecYqLROY3dl7333huJJpvtdgSfMH/v/cfBmDRmJob13/oPQNfZ681Fi6cAnupC88hZbB5voXnk0uQpMva6ZZNlywvR5C3CRu9w/Nj4G799dA7St9tqY58bWwfl0ehjy9veN+tbt3W7ovC/0zjPfMJl5FRMaVOVpqlrnM6xHo0AHUc6/G/7E+gtcT6cayrc7xkJ/tpEgryj0L6y+Ctnm7G+TEFBAUaOHNleZDYW4lr8NRDsDEyZMgXvvvsuXn75ZZO8/4QTTjCJ/iPlZz/7mcmRl/K0ifCGj70dXte7c7dJZcO1Lk8z3I2bAS5hUlfUG9UDdkfF9y9vs86IBDl58Fhifr8CtGzMR0tOITw5BfC489GQ1xUtbc/5XuvzAnhy8k00/rb7bP0ebp6rxxL0G5HjaYC7W2Pre14+NsLt9X3dJvx7G+HyNid7otU2eNx5cHua0lfMTpQ4H+b3SPpUukwm3vUOlqf4YJtIOFlpx8+13cPu8ra/9lQBTd4c5G9s2eoU1QCuEiDHRMw3Ic/uaXqD98DWt4xEg6cMvfI+3GYdp8tT7G8X89sfC+Hx5pvXRjRAfof1FPwpKFiCRId9tr2XU98It5tiQKsgYGw1H81r23PrfXcD3N6m1nW040iwHa/J0FQ2keYTt9ZHK5aGKco6IswnUihPZo77WIRrp37LeH7/dBvwiBPWlPjDDz/cr1jMyOxUIivtdger1DoX2qKhIQf5+T7+t4tLM9zuZiCnlkY8MLaJbfWe8v9n7zzA26iyt/9KcrfTbKfbKaSHDgklkBBaICyh99CXBZZdev+W3jt/YGELnQC7LG1hWXpZekkILQmBVLADKbYTJ7ZjW5bme84djTySVaYX6fyeR5Y0MxqNRmOde9977nuwJjINwwuf77EZif1ikJ4G5kU8Lo7F6BL5HsXokMpj65JjdyGkFAcR73+jSyX0x7L4lXgtlsVuQvSneK0eAIjFbY91z2wdBPaTOG+RKO/J/nejQbHaDjG+weQAR7prJ53HvJbPYMXnZEHecmgG1mWXXYYrrrhCeNjTzUocE+Yp+N9yyy3x51Q0Rk/hmOTXK1AGwHXXXQdfoRbpAQwPb8Dc0iEYih9M75pE92BX6inw9K6hSFjcCjs2AW2wBDm7vxARRcwX90WIlhQhGpCfR4IlCAd7i6xBIfpTxqBYLj+m7PTkwKEelSThXoj9JAIoIn9M4O8W+pPXhePbyMu6uvepIWvedmHeCewW53UMLnh+Kp2PMr41N7LM2tnUm/S29+C5Y4yT13FcLconPadHtcXNmLdxCHavNv+DS53xUCBNHA9QF50y4zuBwCZYQpMqux+KaBB7LLL75YGACMoQRh85459ulYWItMUeB2j7ggQ7APVjuhcZg3HhXxH45c8i1qHnOmW5sk1A3LQjhPnWTqAI3kJvhrKV2dYGi7PSlUcikOfFXLvfR4+HvhUCuxabHxbKXeuke528jts9SIwew2qaMe+bIRhR06x/V0nCGcVIsqlL+a6B2CA9wii0Km4r2f0okAfe44P0RSpxPzZYL/VGROpeLg/UywMCyaK/OnbL912xWXeqmBwX/2m5KnaLbWLP1duLuK29DxgNFIk2gOOksyhx2s7GiKBa7ZP+t16vdT3rrTyvabYVVjbZrp1UljaZjl09AMGCvKehGWhPP/20sIZLVQDWlxnzeUmqvnpMMDuu+Ttc23869sIK9DbphUqZ8GRTkxULs17l7H4SxcNAV2v3/hMt8w0jBINAIaRATPwXoj7ZA9BjWdyXAkUIh8oRLegnZ/iTSBAfBCiM3ycwOHavmpBA1jVC0I+GEQkWorXXCKyqnSk+H9n9KJ9T3KoV4b9LHhRQDQYExHPVQEAuivM6BF/Do/XsM5+SlNeV3Vnzqd4PGd6TRXkmTwhUA8cXf4uHft0BO41YhaKgObEmUwffMppSDNzHhIOEoJguhCnL27THACH8F5GALwsC8kBALI6LZYUIo1dsmSL2K9t332eDMu0UcaATvRFGb1DTKqgICHS/iYSCTgR7y6KBLDaoHysDAZRNaHEcd1ugNvj+UYTE+bD0WNyoiWCHxYuV76n1GFiM9wzt7e3CEoYKlpLNi9pKhvEuxx38Ha64fS/ss/ty9O2joe+cJW6TYO0kIrtfCOddKKBgbHFitCz8y3FYmYUXj8Vihl4RJBQhLJUjin7yeikpZosBgMKMg+PC11+izxEWMZlizabC0VhVPlMMxofi/Wr1jWK0qv8theVtaB/02Ez/22/Z836wr9ErupsVq23KFhc20Q0azrtWv/lMn1NvJj9nyDvCIYccgrPOOgtXXXVVytpmZizsWJj3ACPCzZi0+Rc8H52IU3p9bVqYJw/5jNgt3lm8fyEYSGFACqMgalGafzL1scz/QIEs+pMoXz4UkKLos36hLOzHlkuU6T+oDGFF/FdeE6ABgoKUAwEpZwOUxhojiMQaE3IDgxohcsOChH35Xl4nTzlMXte9fUQWGiRZlJBtBSRPCNyUkSGmJdboFG/9XPxVR6FhW0mXNa/FW14LbHPDMNiuYjUGFbXg9V9G46CaH01ZVlBHtjBoIIMv23u5CMWieKY/YgP4WsV/HYg4HssgJDFgQ2BLtKM/+rQsQrRPTCjYqAgN5ZA2yoKDVK4MAhTGhAWyD5Afd+879aw+OY53CWE/HqMTHitxugvBljACYgBAXheP/SJeq5ar7nVpLco11ZQj9gJ2FCpOJ5Y7aP0iVXrQWoDRDRUVpSntVAyORHmC/GZPPfVU3HPPPTp9zxmnqdlqE6bsWId//XdLnH7cfPMz3bxcaNyw8C/3MU0L/0XpfbS743Yhoi2F2BwaJGbS9+lYGOtnF8YS9CgZL9b/FvV7um9SfJncL5cjdGL2vzJ7L/75EBUz8hWxX+5Xx/rW7WEEy2P9b7L8UQYOkNz/jsVvMVCg6n9XScazn6t1iKxZRHlL0woaHMqS1yPKuylGpxLo1YM62cR5vaJ8puXpcLsQcQ7ywAMPiPtUtVnMWthxi8EJarNHsmM2LsAFA/fDTCzBoOROq04rG00Z83bgZ+/pmljmf30XgpEuILIZnV19UdrRgIqWn3tsi40WvGfsvy+KoCwABArimQmKLYAQ+8W9/JzWhwMlsQGAWEaCeF2sQRPbB0kgPWYIjAWgmkHZo4FCwr5ooHSlvJcbJRF51kB1bFvRQFGtE0JDJPY49lpE5M9YQQ3XQnsyEO1ES0Z4um3Uyy0U6XXPQHBqgMPprH2G8VAH9viB3+K6n/fAngNXoleh8Q46+cVbkjGfhxm1Io7HOspEAVpRCgkV+En2Ck53TloyWINUaskqDHXHYUkVy9Ui/8aC7jiOsliMj61Tx/HYNvJ9gaY40G07EEGwI4xAUD1AT48pToe7H6M7ZgcTtlGvUz+OiJkHsuWRLNBrzkh02+vcgxnn0vogAr0i5vzkGc389a9/xUMPPYSXX34ZQ4YMweLFi3HTTTeJ4m39+/fH6aefLjzT9XLRRReJInDPP/88pk6dKqxtPv74Y5x//vm4/PLLcfvtt/O35CrZ28pHHbgQ5127Pw7YcwlqBm8yN9MtjQUdoyNu99uMruYKFEcaUdGV1P+2GNE3VfrXcZFf6U8XQipTxeMAxe2SWJ+c+t89+97xZUr/e3BP94DkwQL5sar/rfSdA0n9b9FHjyXhKdv2VvW/1f30+H4ikCTZTpCOMyFhz26h26gtjd5MeT2DGBYgpSrI0JBFnM+GVlFeLyzK22pht2HDBlFAnaCC6n369DG9bxbmPZLJWhXZjP1aluLpgq1xQdlnpjLmi9uMC/uGyCUhTpXlTFnwJEL3WG8FqgzmIOgfnArtqQZU7NKtC1KLtMpsAdGgCHbfy42NUKzBQvfUeCmICQ9Kg6QsViNAHgyQGziKSCE/jvQuxcbIeCwLnwhJInUkIIQQqTRxcEAZLIg3XAYnnggxeCAyHKjhoTQ+IrHGS2y5aJSoburnCa/NsE7sMyJmTMjbRFXrY8tq6HujxxrRO1sgAwkNqxqPZPzXeHTGAMPYiWq688ihG7Bjyy94/ucJOHnUN4Z3SQXgqICbYZoctN6wKTvbKhKKv+rJqk63vDJdViFlyEQQQkdqLSjbe1sQ8yluijjcqogEIdW9ErNjMTz2nLYnQUke0A+qBIZQYhxHATrQF5sDQxEO9k0YMFAP8icP+As/1oqegwdKpqISg5XBgXh8VdaplynxepMqTpfSee+O3SRKdMdtOY4HiqJAPO4rsbz7Ne6Uxgt2f+k6BoE0FZu1wj4nh6ivr8ecOXMSstwvvPBC7L777sIjfe7cubj++uuFBQ3d9EBesy+88IIQ5RUOOOAA4T17+OGHszDvA8jC5jd7LcFTL26DS8/62PB+qJBrKGDTrO48g/qSlLluN6L/LVEh3I7UMXidBZY2ocwCqTJbIB6XReJdAaRmuk/R/47f0+z8NP3v+L5CoibQxqKxWNbnRPFcaaD0iNXK8+Ke64hAWwSBvkn9b7onC2B1v1qJz+Wx+2gs7kqq5xsiCAxSraN7ujVGEOhHj2PLOpXHyjbd93KcTzNrwEahXljZpCJZnGdylrVr1worGyqgroj05D1/xBFH4L777kN1tfELgYV5D3HIpsU4Z9BM/IhKjDXY081qZWO1iJdLonzSZ5LKihCirMdAjmUCp7C1EdkKEmUYdiGkzMCJZHi9HpvZGqBT6iMaPiOLnu5ermUU+dfkxktMLBANk5DqOQkKynOlYaJeT4+D3Q2WoFzwiF5HyxQRAvQcydurlsWKFHdvS51r9TH2LHioXpfQ0FFqHCgots4V8vRKSsNUBgPEq2OCAjVGNvYai5+Kj4gvlwcIaFs5n1FeJiUuo/eW1PcEiRvygId8kLH1yuvGyVJP/H3Wxh73j93H1ombOF7Vcnr9KOWMyJ9HOTdi+7a2+NRvhskVjhm+ABfO3w/7D1mqbfZbioxZ8l8PUkdRL1b5Ydsl7lW6I8xT1rxlZCqm6jLyxH1ltkC7+UGApO1aMBzNgYkYKr1m+FzJ0SEIaX0sTvdTxWkxMKAMIsRi+UZ1LFZtGyQLopKY0BCL4yliPtqCkKq72wmJ7QH5uXokhbLh1B3vbM8z0R276VMrAwZyLKX331gxHj8NSYrjSgwuUz2m5S2x+2pVfE6I791xnMQT8eVFYq/vpexfHc/l14ntVXFcXp4Ux+Mtm9h+4+KEP+I4Za3TlPNXX31VPP/yyy+xceNGXHDBBcJ2ZsSIEXjrrbfwxhtv6Bbmu7q6UhaAKy8vF77zjA+oAmbt8wPOuXomFv1YjYljGwwV+KQBziJssO0wc4L+2vp+YkDdAWHeC37zymwBSF1yGV4lvNDPSqZLsVpbLb+uQBkCvSWMan7CeMFTujWqYivF5mBS/5tuzRSbY7E9vp4ex2JvCw0oFEMqjS0LxuJ2a4iUTUh9VNtvDkEaLW8jbiFaFxCPxbbBnv1vdWIfNYGUWK0rbgvRX4oPAiCqPI71v7cYi58OPEJeTnFVGTig/ZfT41gfm25lqn53VH1PF7nc/8bGKAIDldfE7sXzWDyOHUu8ny0l3sdjdFQVw5VtykV6d3f/W1nng7jtZU466STU1dXhzTffxE477STaATTATzPlaN1///tfw/tmYd5DWfNlUheO2LgIc8q2xXXF7xnK4IlqLf5qBbkiVKeBRp9p2lhOflaHPeclqUB/0bhUgweic0u33PJxVCNtivkixoR/avTIwgM9l0s0bi4ahIEb3lNtQ8tj64XogO51qn3J9/KZ7N4fLVe8GJX3o8aSspyIbTtUfq04TiFodAstgvhxiCcJ+5Vfo7w+AKmhAa2tDs/u8SirV68WU+E//fRTMbW+ubkZRUVFGDhwILbddlvMnDkTe+21l/CuYzxME1BduRkzBi/DP1ZujfNLPzMk2kZE5p3GOG5Vtrpeu49Kf2TNS+qMebvIZkei59x4ONtZ9pjXeC7TfGYREZrk2QVxPVjeuabXa8bl61EewE+K3crAALWGgqUIF1RgYMN7PbehexI44jFUicvqfSbF8YT1sZhMoocYnAgIK0G0dL9Ova043tj7CCqUfcjvr3weP8bx//3vf1i+fLnwgFeE+RUrVqC2tlaI8gpjxoyJT0nXw6GHHorf//73eOyxx+Ki/tKlS/HHP/4RBx98sIWfhLGTkpIIjp61EHNe2BY3XvIO6X66s27l4q82DcZU5ZdVRbRvkajHkjMkDeJoJp1Ni46EXMqwp1nlWclwvccHfpUkLrusa7TuSys6/4dFHBRTIGXhX4j/sXuxPBjC5gGDMPDj9xKXi+1j/W9qu4nl6nVBoK8qbiuv2xSLteK1ymBDCNFiVf87/h6xuBuAPDhB97F9CZT3EpvF2g6tdMyquE23Cu/Hba/z/vvvi7YFifIK++yzj7DLo766GViY95g4v0/rcrxWMQYfoxa7G1BOKWM+1OVAlkauCdXpptIlW9lYQapCnH4R52sNzj5AUPjlxWGLk7TI3WF51Dx28npQEN2Mki6ft8iH/Rvr16/HggULkK+sW7cOl112GZ588klMmjRJ3CZPnoxevXqJbLuGhgbhhXvCCSeIDLxbbrlFTI9nvM2htd/j7LkHYFG0GhO19AyShF0qUCqmVqfb1mqaLBCjs4nzLgnNVNjVkcw7K7zCU81Y8NC5FB38dFPpmiw8b0avRw8hZ8arBiCSCIa6UBBpQ0mnQ3Fcz/lZp+O683Acpxh61113CdsatQhPgkRFRcxfKQZlvS9btkz3e5Dgf8wxx2D8+PHo27evKPba2NiIww47TExpZ/zDnlNW4NV3x+D9z0ZgzykrDRZ/tTgxrkrH+sbcyZoXGfO9wpoywm2nymVxPplqAwPq2YT5bM3UTOu1fKZsBV717k8rOv3nxew2ZTZZmqZOQftmlKzPcJC/pPmOfnKwyG5VlmVPeTdu+4HRo0eLPnkyZWVlGDVqlKl9szDvMXGeJvD+/ua7ceutt2JU63MYHPe30EY0lMHKJg/EdCuJBosQivjALzDT91rvYua86rjI604pxqdJlHcwm98yanPgMzCOMX/+fCGyH3fccfjpp58waNCgjNu//vrrwg/3nXfeiVeEZzzYYWsCyiq7cNrZl+Gexx7DbTs/jj7FHboESrlIdtg7xTO1kk6cr3Q7Y96hGVZGRWa934FLBUPJJiZh5puR4872eXJAlE9JUj9eKgzKljPq5TbaJViCU+e5L6Uwa9w2w3aPPPKIsKmZPn06fvmF1BKZSCS14qJ4xeqBBH4q/koz3b755hsxADBx4kTTnXPGYaqAYCNw5h//LIoCjxn5PGoKN+kSW0XxVyuF+SqD2/tFoM+WGEdx2yox28+YLG5Ks7TSzli3W5DXs51dOFwc1jUaM5xzr7ctfMbJJ5+MP/zhD7j22mvjM9mp/XDNNddg1qxZ+OCDD+LbTps2Tde+WZj3EiTk1UkYD4gpkHd/0h83rLwTVPtbX8Z8h72ifJ4I/NQwKPSKx50Xvoda48cmT4HXaGXjJ0G71p1BDzdK1THW8t577+HFF1/EJ598klWUJ/bff3/su+++QpynKfckODAe5WwJuwJYtGgR/vzrMFw+/ArQTFXNwhfNYnViTLjJY1niNojN0YBDGfNGrWiaHHofC4jHcTvEc7PnwQpSZZYZeb3WGK7MilO/njvQlvDzzz/jmWeeSSj6qkBF2qQUfsOU7a6F5557ThR5I554ItG3ua2tDR9//LG4ESeeeKLBT8A4TpWEMVUQ3+3dj1bixpPvQUlRRMPr5LvoaousbMz+BvhBoM+SNU8Z84VSq38+j92YKCpKNdSoOKsnsuT11JjzqDgv29H4CG5TWM5FF10k7vfcc88e60iUv/nmm8VjEu3TJQKkg4V5j3LQQQfh+++/x2Mrt8PpmK/LYz4YScoOY1HeRIe+0982NjUWZc2bEOW7M+0i2Y/FL6K81vNhkzifUESW8SU0vZ7YbbfdsP3222PXXUnKTe9BT+J9KBQSI/SMh7m6+3+TRJkrr7wSL/44AYeP+x45iZZs5yaNmfU2iM1RJzzmU2FHpny6fVQ6M6AS3RRKb2WT6b3swg5RXnmstzOrVzQSWYwp4jiL85bw1FNPYfPmzZg9e7Z4rgjxRx11FE455RRR/FXNpk2betjbpOOGG24QyVOFhYW4+uqr025HnXIW5v3HAQccIPrfj7yyPc46bJ7m10VKShDq09n9u1Sl8zfCagGtyr/iPNn5BZML6Xr982jBhc9AhVpF/9sKUd6sIO+GKG8xWYvImhhEMTWQwAK8YxiZXacVFua9RJ2UkNFBxYMuueRnfNS4TrPfvKg8bZdolyeZ8grRoE0e805/F1aJ81rfKwVRKYM3rZ9EeSMDKxaL85Jbn7Eux2oseIQbb7xRWNp89dVXothrMrScRADKAGT8BQk3559/Pi6/fC3GjWjAVl7qkVgtmBopcJptvQUCvdzB92Act/L8axXamzS8JsNxSUUpOvg6Xu8LUV69TEtH16DIItrqyRnzet9bK43515k/44wzcPzxx8efr127Viy75557hAd8XV0dWlpa4mI8FWylAXItfP311/HHVEiWyQWkhAEVKuh76aUr8d78Buy5gza/eernCAu6Kg/9r/lUnKcZ64FUiXFOf54c+H0Uwrx61qARUd4KQZ5wswnsN0sbtcDvp+POI5qbm+NF40eOHClq1ZiFhXmHBXc9UAFA6tTffHM7RrQ+jxpo8LvLczHdSrFUeNxZnTFvBTUOn5Na88clMuabMljZZPou6j1yPZsRlK0Q5+PvHwRKpZ6/3nUOWPOkQuv7siCfkvPOOw9z584V4jxVeVdPp3/ppZdExh951jEuc6+xOE6DLWeeeSbufagAt+w3B5Vl7akzyP2Mhz2+5Yx5j8Vxuwv4ahXckwdAmrJ38IPRNvevAbtFefW6dMKMaXEo2NPKJtX+q0wK940G1/tckKqsrBQ3BZptRgwePBhbb721KNR6++23i+z5L7/8Uojtl156qe73oQHz2trauM+sQmdnp/C1Z8s5tzEWt6mwH/W/b7ihFSMHv4gRg5s1vc6TLhdet4JJIc7TgHoonQWd1wcbPAZZ2cQH1PWK8lYJ8lpFeR98rymtbKzIks9Eqv0bFevtPtY8YM2aNcJjnvroilUNtTHIBo2KvldXGz/JQQuPk7GBsWPH4thjj8W1mI5l6KfvxWxhk1kgrM18i/YjYd7CTDsrhEmfDrTI3rQRc6J8qudOYcV3p1xbRl6jep2EIAKp6k4Y2X/y642+Lt17Z1rHxHnooYfQ2tqKs88+O76MRAMK8pdccgn+8Y9/8NnyMTvttBP2GvYJrv7Pnlj9c3lqodGvwqadWJCF75qVTSr0fM/Ktkb93JNvFhxX3JLOwGstw6r3atQpOijba31dFqRAMH3GfPL7p3rvbMdh9jjTvW8OUFRUhDvvvFNku1P/6vHHHxdF2yjjTS/0moaGngoJFYLddtttLTpixg2ogO8JJ5yAGx6fhh/r/D567vHBNhLnk+J2INOAuhOfpSo3vgcxoE4e81aK8nrjglcmi1abH+YTVja0H/XNDfS+v5vHmoPFXxcvXow333xT2OCtX78er732GhYsWICTTjrJ1L45Y94HzJgxAyUP/Q43YBrOw2fYFmvSbit+MHwq3hqmVofQW6vTY35wuDvhwm2rFTPfqxY7GzOZ3VmOLbouhGAgRcZ8uvfKdKy0zqlrvNbGfRq8TqloXMYOvY1FZ7PCArwhSktL8cILL2Dy5MnYZpttRAbfP//5T3GjTHrG/xwzciHKImFc+dFeuGznjzCq3/qeGzXFwg25K7Rk2FllHojymSxXmrRvK4vJGguPe9Vz3ooiuxYgF5Hr8u+1pKBXZLZBlJZtJy3wKXVSMDdbHNdFhgwZgnnzuv3CJ0yY0KNwqx6o6BtlyZN3/aGHHirEfjXkUW5E6Ge8xV577YWSppNw8xNTcfYRn2OHcav9Xfupyh+Z89T/DmUbUPfyZ/EQog2kjttmRPlGe4r9pvxOs8UZI8di1hKmfwAogfeoTvP5WIi3hffff1/McKekK4V99tlHJNlRzDADC/M+YRp+Rm904P+wC36L+ek953sht6l1wJJF7U2rzpjXIqjahc8HW0TGfHJVeCOifC6JzLVpzkWtlolOWToAesV5FtRd47TTTsOOO+4o/G0pqFOW/NChQ/HRRx9hu+22c+/AGMs5aPSP6Fvcjhs+nYbzJ32KbQasNZbh7RGhVjfZhNxKCz5vCn96190FtHrqexy5iFyXe8dsxXt6RMihjHlkKyLnVXws0FvF9OnT4x10KtyuLhxLgv1hhx0mCs0y/mfK1vXoXd6BO/85BSft/zWmz/jJ357PXra2iQm4ImNei5WsXeJ8Dv22ibi9scu4KG/V+dUjzmfDjWu3OjbTLZqlzo6bsBDvCKNHjxZ2Z8mUlZWJmVZmYGHeDxwldyu3wxr8CR/gVuyODSjBgViSuF2NnE2bkxixAIFKnDQgPAqP+VRT6ZwW6H0uypPQLhVoKBoX29Y1rBan010f6SxfNJLWyibVPus8Ksr7/Zq2kB9//BHPPvusmA5H/vLUqd9qq63w4YcfCnsbEudTNQAYfzKt9mf0LurA3XN3xW9Hzcfu4xP/SaOBEgSljuw7MlIg1ahAbHYQQI99i1XvqdCeNPvA6QGNJguteio9YklnhUDuhrDvJSFKq5WNl/HS+XSYq6++Wtw/9thjuOyyy1BVlUNKHtPND3Kfeqst1uGq89/HzX/eHRukEhw84wfZT14lavqu/13l3f91SY8FndXifI79K8sz3dL0vxsc/t61ivN20GCB4B10YUC9yuLvJMeub7esbMhj/tprr43Xl4lGo8ISj2rCffDBB/Ftp02bpmvfLMz7jNFYj2vxHm7ENKxHKWbjW7lQQA116KkwlwembFuNG77ZWqbA68lKrvWRgKk321rDMUoBahiQQuLSrAOnxOc6jduYOh4KAlFzNk+1Fn6/egZTWJDvgRLAlyxZIixs5s+fL+6p479hwwYEg0FRa2TRokU6TjTjZbYrXIM/bfUBbl24OzZ0luDAmiVx0TUSKEZI/VuZTYjXKtiaydo2IwobFWCT31P9vFL755EqfCaWeJgoxfENFmSL5bsor1jSWWFlw7gK+dQzeUA1MBIbcP1F7+HG+6ZifXMpTjriawRjgp0kBRBoj3lPJ+Pn7HqXsuxdqw3jlGjpoA2PtCnFjPV016X6mBodqCdgRKTXe1xm//+qk2vDSO5ej+kKwuvdD2OYiy66KG5pl6pPf/PNN4vHJNorxWG1wsK8H/iXFM+aJ4agBTfgXdyEqdiAnXDKkK9QgTCioSIEoxoy7fTilphmh5iqU5jMqS69Vp/5Op1CcibP9/ruEftCxePOSQsbJwR5I4MMJsR5GuQw7GVpx/moyfIdshiviTFjxojbMccck9DpJ1/cr776yvz3xLjLbAl4qjuijO61Htdu8x5uXDAN6ztLcWRkIUr6R2LCfEd6ATOd53om4dyqDGcrs/PNokWc94vvr0+Q2jR41XrRssdjorwgEAL8njHPCN555x3MnTsXnZ3dM2zb29vR3NyM+++/n8+SnxknAY3dcXtg/1Yhzt98/+6495Gdcdqx81FRHkZUKkIwGNbn/+xHHBKU5X6Ohy1DfIQo/hptNS/Kr9NfxFfz9lZn0Vv1v1adojaMU1Y2esR0Ft4dhbLj7YKFeZ/SD+0ic/7P2Amn/zILgwtasGWfDoxsL0OvrjL0D7XJ0+z8iFNiapb30TQtUUt2uZ+y5Y1mstdnFmnjU+Bz6Toym/VvUJx3NNNO7zXIIrxm3n33XWFTU1mZXu2k4nF0O/LII+PLyOJm4sSJPHXez8RE5SFlLbhhu3dx7+KdceqnB6O2fCO2HlqIYYPKUba5BJXFKTLn7UCP1YwV2flWZM1rFOd7xHErLWHMDohoHFzwCqbieFMeiu8ZEB18r3jMG7HFYgS33HILrrvuOuywww74/PPPRb0YsqT79NNPccopp/BZykH69O7ANef/D/c/sRPOuGwWBvZvwcSxbRg1qgS9i8rQv8rH/W+3s+fXqfs5DpOL4mYDIPXNYGVjpSjvZha9GjsHwDJZ2Vj5f5GL1yKjCRbmfZo1T5ShC5fUfIKOaAjLwv3wQ8E4LG8rx2NrZqA0GMb4ogaML27AuKJGDC/cgKDdUS6VyOilApR6M8HdxGsCp9ZzlSbrnWyWhC2QFdnyNT7NkrcMMq+K5t81mGP89NNP+OMf/4gHH3wQu+22W9btKfuO/OyoKOx7773nyDEy9mbNE/2K2nH1Nu+jrasASzZVYVlwR3zX2A8PLpqJvkXtGNe7AeNjtyFlm/THcasLjzb5T1C2haYMoqaec5Nq9oOW7ZymCYhWFiCoN2M+36+TjMVfPZAx3+StOgZ+gzLin3vuORxwwAHo3bs3nn76aWyxxRa49dZbhT0dkwNUJWbNEyUlEVx4+qfo7Axi2U+V+GHFaKyoK8Pj/9gXxUURjBvVgPF0G92A4UObEQp5ZBDOp3YsOYeD5030v9VxO1ux12S0CuV6s+Uz7Wedi6J8hgKqcvHXaGYRvcrk92ynKG/Vd8TArplyLMz7XJwnioMRTCxuwLCKCjSXLsQpQ95AXbgPFndW44eOKjy/cSK2K1mNP1TOdf6YtRRK9ao4bpcnu1ex8TOQX3/WEXs/iPIe+J5F8ddUHfoaCy2BWJS3HcqmGzp0qCgiM2jQIBx44IHYaaedMGDAAPTq1Uv4y69ZswbLly/HK6+8gv/973846aST8P7776O0tNT+A2QcE+eJsoIubNtvDWrLfkE02IAz+szFyta++GFjNb5ZPwhPrdwG+w1eimNGLLTuWMz4v7uFgaz5rPswcgxalhnBi4Meil+/6OBrjONOfgZfikMai7jbhdeuMZ/S1NQkZrAR/fr1Q0NDgxDmjz76aEyaNAkPPfSQ24fI2CTOE0VFUUwY04BhtcVY37IYJx/yCup/7Y3Fy6rF7d9vjMfEsetw3m8/5++BcZYGA3HbCfsau2iwVoRPhUSZMUr/W4uArieLvsqC87zOg99LDnKLjTPlWJjPISKhYoSinSKjbnhRs7jtV7EMf2mahMEFm+x982yCqFfF9wyZ4JZ409bmkChqxhedpsCvtrEwca2Bc1rvP1E+LswrHfpUn8usQO/V6y8HmTFjBr7//ns8//zz+Ne//oV77rkHq1evFgVjJElCYWEhttpqK+y///64++67MXr0aLcPmYG9AmwkSHG8AwVBSfjQ0+03Q5fghu+mYmhZmjhemUfiW6X2cymli+Nezwr2kjjflOT7qyVjnkX5rMhF5KLuWM145drKAaZOnYrbb78dd955pxDi//a3v2HLLbfECy+8IDLomfwgGi1BMNAhnC6GDd0objOmLcdD/9gefXrZUPvNC1g5ILrO5dowuWYd0pBUtF2J29my5RttEOWrDFxD6bLmGy0S5XUK8nGoDVQa1X+9GL2+jHr2M76dKcfCfI5kzRPRUDGCXYmetGSF9XX7IMys5imVetHkMW+HWJupmKpPkUfs03TotQrINQZE+Rod6+q9L8rL0HUZzX6NGBHonbjuvDpI5xI0yk7ZdXQjWltbxVS44uJi9O3bF6FQyO1DZOzKmk8hwEYDxSiKbkxY1hEJ4fuN/XH2uC+cs7Bp8pmYrdUT3S+fwwvifNL7kzCf1crG7WP2MupBjmAQgYqovnNpx0yPVNv45X/EA9BgOg2c02y266+/Xgy2U0ed4vecOXPcPjzGgax5IhItRijY0aP//dXCwTjvt5/x95CJdQb731YOEDTmkDjf0HPGuqmi7UaxOqM8HU4VVa4CpIoUVjZ2wSJ7Xs6UY2He7+K8SsSNhEpExryan8N9xLjz8MJm5DUGhNWMI/aeEmotoE7ndjrF1egGk1Y2VovyVp+bVMVvbUIaHEIgoqNhoEWg13vctdZfI5YwAEBY47aF8CTl5eXixuQnkWAJglLiAPvC5v6oLWtGn6IO7UVSjdLkIcFOz/ulHOQoRFBS/SBYcfxuCM8eEUqjNNCRqYPv9Lnxg4VNunNCHvOboumz4TP9H6ba3uhxMIaJRqN4+OGHMX/+fCHG0yD6smXLsGjRItTW1qK62mhaJuM3cV4W5hPj9q9rKrC5vQCjhvM/X0oyZGRrzpj3QwywglTic7W27eKJcXqy5c0Kx0Yzyhst8prPhN6f5arkou0OCPN+FOX7iuKX2iiCr5k2bZptM+VYmM8FYuJ8JFSEoo4N8cURKYBHN2yH6eUrc7tCvA1IVgjwtRZlzddbJKZa4T1u0NYmo8ddjUHRON37GxXHsx2HF6ghe7uAsWmeVgwaaPnOOSOeYQxnzZOVTVBSFROKhPDkCvKXX2adbY1VOkGTjkxvK8RlnfuIohBBZaTOI+K2Ltw85lTWQKKIuwW1YqzAD4JMhv8zyggNUEpt8rZaZ0roGShjXdAWgsGgmMJOnrKUNUdQpvz2229vzxsyniUqlSAU3Nz9PAo8/MwOmL7LSmFv41hWrx9Y58MYkOq9qhw47kzXjcZrSsx0a4o4JxpXOVhQ2E4Lm1Sfg/6Z1XE723lZ5yFRPldmhHgAspadOXOmLTPlWJjPIUubaLAEoUj3iP0zG7dEBEEc1dtEsbgcs1RJSbL4XgtIdSEEBrncAa03sN7J70trZnQdIPWnqXRh/aK4U6K8WYy8b62x9yCPeWFl4yQstjOMI+I8WdmEonIcp/b/Q0t3wJDSTZihCPP5YKGiHIfJY5cz5jv9Kcq7SYbvP+2gsBeuGa/QZMJj3sgAW6rr2+ysGf6f0cQhhxyCs846C1dddVVK2znKrGNyP2s+Ei1CUUF3Ytzzr05E2+ZCHHvwgtwU5fWK4joESsktUT6VnU2m92k0IHxqPW4Lr5koDahHDegZ6ox1M17yVTZ+f9U6zpVZUT5d3M50bvrr+D/QI8izyO4q48ePx/Lly8WsOatnyrEwn0OWNpGKIoRimXbzNw/Cu60jceuAt1EQcLiIitfQm/VeR4McSVPg/SJkGvGnr7NfoJe9abM0DJLFeTdEeaey5g2K8jKq4q9OwKK87VBwv+yyy3DFFVdwwbh8JSaERcqLEQp0it7puz+NxA8t1bh1+lsIWGW9pEWwq9Rom6F3ucOQMJ9xQDjXadL5nWjN1HYbr2TLmzkXZGVjVRy34zvJJM574RrwCA888IC433vvvXusoyLukYhHZpgwtorzovhrzMrm2+8H4PX/jcbNl7+NwkKHk2h8LsrHa8Nk6i868fvfmDs+9dLmLBZ0sEAsTvW5qwx6y2fKmk+1Lps4b4Egr7aygSLM93chG96D11e+EggE4oPxVs6UY2E+h4gWFCO4sh0NLaW4P7gTzq78HFUF3VPrbEWntYnt1LnYoXf7PKQS5+vdmXmgLBMj9lo85hVhXI8o76dZHRZcG2IKvFPCvNvXch5OiTfrT8f4NGse3Rnz5DG/srkPnly4Da6a8j7KCi0q3KVXUHNCYK+0TyyMoki2ssn2uT0ykGArFgitugry5aoob5EoLWfeeTxpJnlgjgX5lIPqDEMZ8zSg3rShBPc9ujN+f+JcDKhqy71seZtF+YS4bcX766XRotfbmSWuE0qM09T/1msjo7xGz3K976nVZ95sOQ+tx0vnsizqrAc8i/F5BQvzOZQ1HykogdTVibuxK2ZEl2G7kjXm9u0nwdPigqxSoMhcxrzbKOJ2vYlzZragaV2K4jNasFqUr/VAwV4zAnePz+iQlQ2L8o7CU+LzGJU4T77o7WEJd83dFbMnfouRfbunx5vCS6JapcUCc5rPFhVxvFPbPrUcl5fOYSa0FA418FkC7R4XkvXiok+7XETOJ9nUfrnuGcalrPlotJgqwuD/HtoFe+y6EpO2+TW3RPlG57zk5downd4blDWDnb7pWfYl9QkhGLUoucMqQT75NXrOj5EBhEz70kp/QOqbVBvGTliQz0tYmM8hogVFeLZrDIrRhSNhwlfe6zggsEbIyiaqoUPvZepdtMdJNWJvpmicEVG+1gMCvVlxO8VnlCSysrGxYcCCvCvwlHiGoP/sv341GaP7NWHv4StyR1izIyu9KfvMN8XeT/P+/J49b5cdDb3G7ck8VnXGmzTY/dj9P0NWNl7PmM/Gkz4/fgs49dRTM65/5JFHHDsWxj0i0RK8+MYo8fiYgxbk1lfhoCifUBvG7DG4iReONybwR4MaZ6xrQYs9jdfRe5z9E2e6OZIY55dzmcd89dVXKC0tFX7zq1atwjPPPINx48bhN7/5jan9sjCfQ9QXVOOTroG4FW+JnFrH0VoM1Oh+HcRwxryfRE0t2fIWivMBN0V5N7DpGDQXf9U7EOGFc5bH8JR4hljZ3A/1m3rj5j3eBtlZmiJPBXl15l0g3ZT4TPu2upimEzTZv2/hr+omVmbKwd3vOG3xV8ZXSCkGV7q6uvDiiy9iv/32c+WYGOdZtaYKH3w2BDdf+joKQjkyYGX0t9aEKN+dMR/2lsjtFA3WZ9XLM9Yj+gXhTLY86V6TzmKmQWdsVz9PZWeTyaNe7zGmI5VdDcVtO+zLWIj3FU8++aQYlKeB9+HDh2PKlCkoKyvDr7/+iiuvvBIXXnih4X2zMJ8jrEY5vgsMxLl4HH3R4e7BmBHo3bQbSR6x93vGvNVYIM77UpRXeeVr3t4K0n7OIAKBqLUzBViUd52ff/5ZVHSngjJqOjs78csvv2DEiBGuHRvjDEuaKvFjtAoXTv4EJQUmM5zcFpI9kHlueIA9WZx3+1x6QJQnPOGJbrc47xT0O8/+5L7n0UcfTbn8n//8J5566inHj4dxnrWNZfhm0VCcdcI/UNlXLgBrmHRe2U7a4pj5fTUpyvcQ5nPht94KTH7/hmZZWyHIp3reYCC2KyJ5OoHeavpnsKBLdy5ZXM8bbrjhBvzlL3/B8ccfjyeeeAIDBw7E559/jtdffx1nnXUWC/P5TieCuAu7Yrq0HhO9ZGpXl0X484gIn34qnY895q3Mlk+1rsanoryWay6VN39tln1YLWzXZCv+mqZhkOk4WHz3NCNHjsTq1avRv39ii/Cbb77BPvvsg+bmZteOjbGfTZ1FuHveLjhixlrUYJPxHbktIntAkE+wsom2GXuxIs67fT6zYcfxef0z58BnI3s/TfUPGF+y66674swzz3T7MBibCYeDuPvBXbHbbhuw7cS13SsaLC5YSdva3b03K4JbIMrHa8OQMG+XKJ8soHpF/E/3/XpI1tEkQFdbdC2nEurTCfRWkqGwq7CyiSYlzbAgn3fU19eLfjnx3//+F8ccc4xIqps4caLox5uBM+ZzgEexPSqxGaO80uOAv0T4VESDOS7Mez173i1RXgt2C9w12a1sTPn1M55izz33FAGdpsQfeuihKCoqSlj//fffC9GeyW0boz/P3wnbDViNoRXDgBYDO2myUWRv8pcgr868K9RrZWPmHDhJk/P7dd3KJoey5uXir9H8qX2QwzPdkmlra8N9992HQYMGuXJMjHPMeWEblJd1YswIHT9IegT55Nc15GaWfI+MeR609J4ob1aQT962QaelTSbxfJ39orxAWNCpEuNYlM9Ltt12Wzz44IM44IAD8Oqrr+LGG28Uy5999lnhM28GFuZ9zgdHDcc32Aq34m38iq3cPpycQYzY56ow7+YgiVFR22n7mlRZ81ZjeGCDPOZTZMxzRrwvmT59uhDl//e//4ksu4qKivg6EuwPO+wwHHXUUa4eI2MvL187Eevba3HB5E/wEyZ743SrhcBMmeOVXo/jJrKS1YKoH7LnzWLV52vM0GFN7mRX5as4T8Vfo9q/k3RFahlXIYu5ZPs5iufDhg3DY4895tpxMfbzyZu1+OLrbXHr5W9jzcaJ9ory6tc3+Lewq2ZhfpNN/W+vCqkNLojyWmJolQsDTanEeYVsVjdO1IZRarx59VpKxi/H6SPuuecezJo1CzfffDPOP/98jB49Gtdff70Q6F966SVT+2Zh3sd0HRXEgzgEV+F99EInfnX7gLyIXn/whCnwOr0C80kYrdF5XkpN/NpYIco7PRhh42wCOWNeyt9rL8e4+uqrxf3jjz+Oyy67DFVV3IrKJzY8XILnfzwAt09/E4WhUGLRMzOCqhkhL9X2lf4TB3Paks7oQIFTxW0zifNGtssxcT5r8ddM34cPB8lylRUrVvRY1qtXL1RW8peRy9Dgy9+f2hGX/P5j9OndgTUbHRDl1fuxQrRt9I4Yr0baFLOysRpuWqc/J+mEcLuvZ63ivHq5Gqfjv7CyiXrrWvLSseQJkyZNwqpVq7Bhw4Z4rKcZ7yeeeKIoBmsGFuZ9TCdC4jYmV9O4zNql1OoofpnCyqYwoqWlpZHkz2F3NradGPhOyBfdqfdyNWvegeOVzyVb2eQCZFGjzrabPDl9tvTy5csdOirGSTatK0avgg4M6mxFONDLninceqwwMm3nM60poYicFfg9az5V9rXVZOooW92JdluUNzFQlbGInJ+vsTzDbCec8SddawrQtvlwjNui0T1PeCd+Ox0U5BMT41qdEy+9OMBr4bWjyYJOj7hr1QCTFnEeWb6bTMdtw3cq9Q0gUCoB6+EuLMa7yhtvvCE85tUD8FttZY1rCQvzfuWoALpQhMKYQBcNhBCQckCsq8/wvMa57HnbrWycsEqxI3Nc73dQa6IivJb3sjtbXjmGei8NICRlzHO2vG+55ppr4o/nzZuHt956C5dccglCoZBYFg6Hcdttt+GII45w8SgZ27gvgLDUF4VBOXM20lyEUGm7tdnyyct8Jq6bwZI4ngv+3hYIvRRxErxVtXSEzWTD24FVgrcVM1Qo8y5VxjyL8r4bUM8ED6jnII0BhLsKEAhICIUkZPtZtAUzwr+HRXk6tmhZIQqt7H97KQalwuYBnKxx2w0xPt3+Mwn0esV2LcK+Hqo0zHSzG69fy3nCQQcdhPLycnF/+OGHY7/99utRH84oLMz7kSlygzBcE0JhzOsqWlCMYFenIaGwOVKMj9tqMbJoAyYUuzTEX69jmxqHpsBHLWoY1HhMnDeKm9nrbuOhzy5b2bjYMGAs46STToo/fuCBB4Qn7S677JKwzYQJE3Deeefhpptu4jOfS9wnx/GuaBAFgVgcD5Qg2NpBI5m6aWgvxcfrhmH7yl8xDBtzW2jWVUQuR61stNJkYdzJlPzhdMahlvezYzBKy/nU8D+WsoNv5rvKk/9pL8AD6vlMQIhjXSuDKCyIJcZJhQgGjcWZjZuK8MmXtagZvBFbjXNACfeyKB8j4vcab3oy8O2QXIzY0lglyFeb/IyZBPp0n0ePT77RdkqVztowVsOCvKdoaGgQWfOvvfYazjzzTLS0tOA3v/kNjjzySOy///4oLSX/ZmOwMO9TUZ4II4iCmEAXKShCqKtD8246pSC+3DwE77cNx8KOAagOtWGL8HrnhXknhWmdVjaOVIW3SpyvsfncmhSmdVvZeCFb3qtIVPw11jDgbPmcYcGCBejdu3eP5X379sWiRYtcOSbGXlFeEeYLg3IHPxIsQijaCTRrE9s2ry3A541D8f6aEVjW0g99C9vR2lKI4wYu4K9OyZiHBXHcK4MZeoVbC7OvpWBB+kyxbPY1VS6K8lZ9f0bOfWUWewH1+WRRvhsKg2Xe7cXygHq+oup/9wqhsCA2oB4tQTDYoVmwDIeDmL9gMN7/fDi++34gqivbUDukWb8wrzdr3uuifOz4JDjU/7YDK2KdXhkmS/yV2gP2i/LVJsR2s6/RI7zrzaJP+j6lYIoab3bDorznoDoyNJNdmc3++eef4+KLLxbPSZSfOXMmTjvtNJFJrxcW5n1Ml0qYjxaUIKgW5lP4s9Nsph87q4QY/2lbLYYUbsIeZSvxx8ovsLKzL+Y0b+vMgde77D2vZwq8A+9lWJy367hqLPb412pl46GsdC8jZ8xHWJTPMXbaaSeRGf/www+jtlb+56HiMhdeeCF23nlntw+PsYmwFErImA9FN2cU96ISsGDdALy/bATmNg7B6Iom7DFwJS7d8iN88dNQfLaxxj9CsyPFXy3s4PvJZsTiY5UCJMx3Gc84syqjvtGF82H0tcn/Z+r9jCb7SROZd3nw/+sHeEA9PyFxvaBILgIZ+bUIoUBmYZ7630tXVuL9z4aLDPmB1a3YY5eVOPP4efh1TS9RSNYTuCzKdw+o+yhjvspi33qL6xOI/rfeAfJqG7PpjQj0ahosEN6ziflV6ZMMHbWNZlHes2zatAn//e9/8dJLL4nMebKy+d3vfofDDjtMJNP99re/xQknnICbb75Z135ZmPe5MK94zEdCKTLmY2Lv2j+vwQcffCBuXVIXpu03DTd+/DsMKWyJb1pTuBGrunqJTn/Q4OBqVqzM4NYiGtcZK/zaw8rGCXFeLzX2++w79pmNvE8eZ4pTwyAYE/KY3OGJJ57A7NmzMWLECPTr10/4zNN0uWnTpuHxxx93+/AYmwiLjPnYzLdgcU8hOSbm1R9aJ2L4hx99KBqAe5S+iWN3+A7VJZvlbZqBmuKNqO/oOesiX5EQAlXjsYQ8FuUJaX0IgT4mzqUXC+w5cS7TvF5qCyCwQbL+u2qySMg3Udg2n+AB9fykqyuIAiVjvk8Jgs0phPlqoEFaF+9/t7e3i/bcdReeiZrBm+KbBQMb8cvaXuiKBFAQkuwRcRv9Icp3D6g7LMzrjU+5LJhW2+w3r369kQEILWK9nsx4Pd+lqA3jUMZ8Ll9jPmfGjBniN72iogKHHHIInn32Wey1117x+nC0fssttxQiPQvzeUR4bQgFA1QZ85HuhkEbCvAZavDBxJOw4uKLRcbl6aefjokTJyIYDAJfHJuwrz7BDhQFIlgXKcfAERZXQ7cLGwVzYWWzysGpdFqz5vV8Xo942EtuivJ6BiJ8QxDoz8J8rkFZ8hToFy5ciCVLlojicmPHjhUe80zuIjzmu6JCCItKRQhGO2Qrm0pgY7gIn6yrxfs4EmuuugpTpkzBBRdcgNGjR8vFB8kSRyWgDSnehLWd5ehsCKKIBu+4YW/Erp9JVZCvOISg2UyxVOKHnmvUjLBf6a4VUCqPeVNetUY/C4vslsID6vmJWpiPRIoQ6t3dX2xvD+Gzr2rwwfxTsXTpBWLw5tRTT8VWW20l978bZyfsq6I8jN4VHVi9tiJBsM8LUvymuyLMa6XKf4PRuq1knSwAa1akd/g7cKT4K7fbPc+QIUPw4osvYt9990VBQeoc98mTJ+PBBx/UvW/OmPcxFdFOrEcpzsd+2KWgBKO7OrAWA/E+hmMehmAsGsUIDjUKSkpKEl98lwRc0P1jHagF+q9vw5p+5RgInwjzWjAoykqBQgT0FH+ttVlIt3IAwmGxWs5atGjqVx5nyitI1UEEOGM+Z6FRdrox+UHfjnYs3lyNS5ftg13GDcDowHIs2zgE//t5BL5rGYitK9fgkJMPwQ477IDCwsLEF58tAdfG4ngjUIIIKoKdaIiUYUhBS+bpy+nsbHLI5sayDqmfaLLJ95esbKIWzT4wcRyacdpTXi9OdPDNZsLnyO+AnfCAen5SVhZGa2shzjtvP+y8cxHGjJHQUDQAH7w1HF98PRSjRzRh2t7TcMkll/Tsf1eRtUhibCKf+bUN5caEeYutT9wmbiWbTIONArFbYmm6786i75QS43R5oqc7t06cc7tFeiughJho1Ng1o8deh/E0jz32GN555x3ccccd6OxUD8q2o7m5Gffff7+oD3fMMcfo3jcL8z5mcFcLHsTL+AHVWFAwHa93DUITopiKnzAb36HqX22Zd0Di/F1y46ArGsCq9l4YVqpUnbMYD2Ru67eycaETmizOmxXkPZA1L4G8aVMI8zUOCfJGBiIMWiA5gSQFEFCKvzIM41+agPFljXh43EtY1NofiwMH4h+/jkO0uRx79P0JZw6Zh97XayjqHmvwr4+UoEMqwIBQq73FN32C40W6clSU7y7+GrE2g83J69JjVkRU/DXg1JR4I1n0LMrrggfU84sBA9rw4IP/wQ8/VGHBgql4661BWLs2jKlTf8JdB72B6jFZ+t8qcT4SCaD+194YNtSm/jdssLFJJzJaMAPK8towZjAbo5zIms/wHnKGd0RbWzCV+O7GIIj6fRu8NTglBUIIIsu1me4c52k7PBe59dZbce2114qEKSr8uuOOO4rM+U8//RSnnHKKqX0bFubffPNNvPvuu2I0uLKyEsuXLxfm92vWrEHv3r2xxx57iDT+VEQiEVxxxRWQkhqlf/rTn0SlWxqFoA9K9it77723WPe3v/0N4XAYZ511ljwVLMa8efPw9ttv47LLLkM+UgAJW2Id+jOIpuwAAJhTSURBVBf8ihnti9EP38kr/qWvwb+stRJVRZvRt0iDCJAndjaBGsmdQrVOeLs7mDWfMmPeKVE+eR91Ot/PSwK9ciwb6fcvzwQnxhY4jruISigsCkaxXa81qK5ag1kFX6O8OhZ4rtbwf07bnCN38L/vrMbYwkYUBEz+PuRQ1rxnscoLPNv+LPP9DaUW5o1YpOjtoDptB+CAiC9b2ThYRC4TbHPjKzhue4NQSMLEiQ3o3/8X7L33SlRVfRVboy/+/lTfBxVlnaiuVBV+14sTwqSW32Etg66NDtaG8cOgsY3fqRhQ15rhbQV6vN19OBtEFH9NdT69cL0wjnHffffhueeewwEHHCA076effhpbbLGFEOzJitZxYb6xsREffvhhwvNHHnkE++yzD44++misWLECL7zwgihgR16oybS0tAhR/qKLLkJxcXF8eXl5OZqamjB//nxRyfaf//wntt9+eyH8E/X19Zg7d64Q7POWTyRgSs/p2ZGCIpQkF3/VwgVy1vz3G6sxobdblV88PgXea4Vfrcqad0h0pg590Ggjq9bhAYlaD3rVJx2TBLayYczDcdxF1BY0Kqj4a0ipFaNFlFe4VxbnF4X7Y0JRijhuJGs+B8R5z1rZNHn8vDemyRQzMovQbx1WpzLrRSajxwbYvXDtMRnhuO0msjFIMtFoMQoLDVjQxLLmFy3tjwljbOx/N7qwj1S1RBp1iJ/JC50SZ+2IV2ay5k0K05ot6Mxmy1fZKNDrzZ63ExpQV89Y91v7hrGE9evXi5qdBGndDQ0NQpgnDXzSpEl46KGHDO+7O/VcBy+//LIoYqLw1VdfCSP86dOno7q6WmTKkyC/ePHilK8nYZ5S/mlbypBXbpQJ39HRgbKyMgwcOFDc03OF0tJSvPHGG2htzSEPdIuIhooR7Go3lC1PLN5UjQm9bPrVs9tKxc79+12U94Bvu2xl46I3barPW+sD//p0xylRk5WtbBhzcBz3HtFgMYLRWBw3wA+d1Rhf6IXeizfwpJVNk/9sV7qtbDwUx/Wg9Xw6eN4dKSJnBA9ee0w3HLe9hyj+GlLitoH+99JqjB9tQdyuziFhP5+otu97lYKh7rht16BDlYn1WmkwuL7RhrjdK2rd52J8ybRp03D77bcLT3kS4snVhbRpSkqnDHpHM+YXLlwo7GqowjgJ8sSECRMwbty4hO2oSFkoFEorzFdUVKRcN3jwYCHSX3311Rg/frx4rkBFTL/99lu8/vrrOPzww5G3pMiajxRQpp1xT7bGzjIMLGmx4OAYV8iW/Z7Naz6VAFxnoTBvVfFXK9EjxNd555jENE8u/sqYgOO4B7i6Z9a8yJiPGo/jTZFSDKKir8kY7UBwBq17omeqc1/pgHDamCnzLkUcd+KYnDrfTheR86Iwz2Tlgw8+0NWBtwqO297Mmo9GSxAMGreBbdpQikHVNva/nfA5Z8x9BzZZtkSDBQimitvJ761lWTJOCdNGz4uV13zss0q9Agi0ezDhg3GUu+++GzNnzsRJJ52E66+/HjNmzBCCPLnAzJkzxzlhnjzeX3nlFcyaNUtkvCsMHTo0YbuNGzdi6dKl2HPPPVPuZ9OmTaKK7Z///Gds2LBBvP6ggw5CVZV85Z944okpxXt6T3pv+tAk0tfWei3F1T1xPkrCfNh4pl1bVyHKQymqoFuBBwqQ5kSmXSpqdQj0er8Hi+xbhDetG36BVuGEKK/jp0ye5umT65PxHBzHvSvOR4NFCJIwb6BDQa4YrVIhygI2xXHGHE02D4xYIZBnuO6iwRCC6TLmvWh/4sEs+Z4Z8x6M4178Lj0GzQ7XQiAQEDXVrIDjtnfF+UikGKGQcWG+ta0IZWUctxUs798YsfJzg0zivEHhXvaYt6H/XeXQ4FCDwW0abfqcojYMD6jnO+PHjxe1VaPRqEhCX7ZsGRYtWiR0aXKDMYMuKxsq9tq/f39RfT4ddJDPPvusyKJPJ5z36dMHI0eOxP777y9GG6jh8thjj4nXKqTLqCdPH8rO//e//52wvVaSC876GpXNSqSgBEHFm9YArZFClBd4pAq6XvLBbkavmFub4Vw5XHiVMuaDRoqceWHczWOiPCFJSR53DKMDjuPeRWoPINBorI3SIYXEoF1JIKkTZrZD6tVsaOXYlFsSUarFQTO11Nuk+izJ6zNta+Hx6d6Hy6TNmHcCu0QVF8+rEOadLMrHWAb1PbXcrBLlCY7b3sWsMN+2uRDlpSzMZ6RaddOLV0R5s8dRrX/f8aLtVR6wRLLDvsYuUT6NVY1nLegYx6GBd8UZhjLlqSaqWVFeV8Y8Gdt/8sknOPvsszNu9+qrr4oCrscdd1zabcaMGSNuCscccwxuvPFG1NXVYfjw4VmPhbLmaRrBF198kZC5r4Wff/4Z69atEyc01QlWbuR3r36e6kavSd6Po5CX/FHy+0cLihA0UvyVXisBmyOFKLMrY96Horxni8ZZJVrryZ43mTkvW9n4MGPeg6K8DBV/9aA1kB5qcmiA1EfkUhynz5JMchxPvqWK67TMa5Y2RmiVikS2fDCQ41Y1TVmWxz6PhCIEN4etsTep9IDga/d31ajDq9brZCuuq3c/Npx3iX53jCQs2Inffgs8bmVD8Wjq1Kmm3y+f4raWvrcn+t+qrHnZysZYYpuY6UbCfJlFiXHpMqt9ZGfj+f63nVhsaUNxO2PRdicHOvRcg256ymf4fEKY58Q42/n1119xxx13CMt0Er333Xdf/PGPf0RRUZGoX3rTTTdhyZIlIln89NNPx4EHHhh/7WuvvYa//vWvWLt2rah3evnll8cLtVJy9n333SdqtWzevBk777wzrrzySlHANRuUUK415lA2vVE0R9UPP/xQ2M/ce++9CZnnFKD32msvYVszd+5czJs3D2eddZYo1KoVyo4vLy9Hc3Ozpu3J8maPPfYQhWDT2eWkgxoeqb4AJbuB7ru6usRj5TlNISSDf2WZckuVfU/LkhsW6cSA5OeGGhmxQq/Sjz8ieOHf9b/+roAQ5YMBCcVBj3US/DKVTqu4Wm/RoEKtRYK68v719orzvrSy8awoL2fMs5UNY4R8ieOpblRIXh3XM8VxgmJyOpEgXYw3HMdJnCd++AE44y/6X39OAK29e6O8qdOeTDGvCPg6CqdGg4UI9LMo2UCrQGt3BrbVVjVV2juzlDGfsYNvJ40WDtwY2YcdAr2VVjY2DiAw7lvZ5EPcThe7Pd3/jvUTo9EfEQw+1MN7PiuNAYTDQXR1hVBa4tE+kgtifk73b7SI00YtbVLsW8x0K+sC1hs52DTvYRQrRPlM62wW5QmJjEY4Y95Wurq6cO6552LUqFF4+OGHxWDuFVdcIeIU1Te98MILsfvuu+O6664TcY883seOHStuZKN+7bXX4uKLL8aOO+6Ip556SmxPLisk8D/33HPCkp0Go/v27SsEfrpRIddsXHPNNfHHFGvfeustXHLJJfGseYpVt912G4444ghTn1+zME+jFeqRf/KR//vf/45TTjkFgwYNEqMDNAJxwgknYMCAARn39fTTTwubG2V/FHTb2tp0VbKlhhGNpLz//vui0KxZlE44QV+eUahhQLfkRoTS6FA3MtQNEbUtj7rBQY2FZIEg1WNqtNE5TG5oZGxsXCCva62Ws+VdTT7wVLY8XQcWNgzqMyyv8YC9i1aB3qA4b8jKxk0bGw+L8vHrk4u/MgbIlzhudl8Ug9WD9cmxPFksUG+rvF6NEsezifq03+Q4njWj/5xYHI8UobwwrC8ryWtCnoUCo/Drl8L2H58HbGYMo6MjSx7zISN2idn8fdXHUGWyo22FKO8QErXPre7gZ/r/yVaDwGu/BR7GiI2qGfIlbuvNwDfa/04V09X7IJS+s9b+N2Vf6up/x0T81s1FKC0JIxTKYTFaB5afBa/Y2DhF0mC7VJnBY15v0Vcj51JvDHdTlNeC161s1N+fDcWEneDbb78Vs6sef/xxMchMmeo0s+udd97BtttuK+LfBRdcILTaESNGCIGcBopJmKf7HXbYAYcffrjYF4nylEH/5ZdfYsqUKeLxUUcdJTLlCZqF9oc//EHEwLKysozHRdbrCg888ICwYN9ll10StiEb9/POO0+I/UYp0DOqrvZ9VzqLNOJAAenJJ58UgX7w4MGiuKtCr1694iMgStAlj3iacjdw4EAxek4ntbKyUlcxV2oMUMFYOjF0DF5BCcZWiAOZBALlMZ1XahRQNmBjY2PC+lSNx3hj46VbERw9W3S0NhQHMX5cLVb32QMhqRPBaAdC0Q4EJbqXnyc8Jt/WHPaVjwYKEYyGnRGQ63V8HiPvpUdMt6lIrwTKmPfANeMVTA868FQ6xhgcx7WhnlpvBdniOAkG9JhiOWWHqLelGx1PSrH/7VsQGnOcqC/TFCjB8IpKrKnsRLBfpxzDYzcldsdjeITiuIc6F6kylCvNiasijlstzBs8FsfIJL42WuEx35Z+/1qF3UzH0eiydY2W97FKwLayiJzZAsEsyptizpw5IjOPxAQSBkgcpww/ulFNNbNw3PZm/5tuyf1vZV1yvFY/D4VuQzA4G6H2DmxsCWDChBFYvX4PhIKdCAY6EAp2IEi3QGf8sVgnluV2Xyov+ot2Zs2r3yM2Yz1lYpydorzVRV6zfVa7Cr2msVny7IyOao/WCtDJkCFDhI2NeuYXifCkIa9YsUJoxeoEarJmW7lypXhM6ynTXqGkpAQ1NTViPQnztP7EE09MeC39XpOVG2nTWlmwYEHKwWzSo6kIrBnMDU/HoJFzGm2g4jR0U3PLLbfgm2++wf/+9z8xNYGg6QUtLS144YUXhKhPJ5lGIvR2gqkqLo1OkBdRrqJVIKARJK0DG6KxMf9JRIcVIxIswobeQ9C5IYjSAWsQCRYjGixGR0GZuBfPA7F78bgQUiCU8seJlgWlLtEZDkY7EZLaxb0QBLronpZ3iMEA8VjcdyIUoXWdCMbuLf/Ry3Za6gxm2jmZ1e3Ue2UT57UK/bVJHXqozmeNz7Pl690tQixJHm4YML6F47g34viwYcO0x/G/PI1IqBjRqmKsbB2B6OahKClfJy8LFiFc0EvEeHos4nmoJPa4SHTYUIzUcRxdsRgux2gamA+W0HN63IkgOrof0zrQurDqeRiBJim7+GejwG2rMO83OyALOq5ZPeYzfT67stnsEuSzZZcnrzPwvcpF5ByM48r3o/5sLMibhjLjHnzwQZF5R0I8DbKSgEBCAPV5KXnMTjhu+7D/HX0S0YZiREqL0LJxINo3F6K0aA0i0SLhV9/RVYZotBiRaDGiYlkxIpL8WIoVeU/VBwgEosLrPrg5JvAHlHsS9MMIlncguLETIdByOY6L2C0ey7eE/bpgY+O5uO1VcV4jov+dLMzrFeW1YOZa8UKWfJWeAXUPDhz5VIRPxaBBg8RNgQY7KdOdZo61trYmJIkTJJAvW7ZMPE63npanWq+I68p6rey0004iM56sdpTf/lWrVokMfSUb33FhnjLcSXQn9tlnH3FLB009oJsa8qijm1bOOOOMrFMLGG0EdgsiVAOEwp2gnIKO1mJEW35Bn82LTZ/CKEIxAb8oJggUIxIoQrQ9JgaEitFZVIZIqPs5ecEqQkI0VJR236IxQh6C5bIgIGf1x8QAIR7IAwLief/YcsS2FY/lZSQSk/AQb4DUpmgYFHUCaz0gFrvxvhZnztM1odnKxk1RPhNazocWayILPp/kx+KvDg1aMPrgOO4dlMx4rQTODYLkAmEv0gm0beyDYLuEPi3fa9tBGlFOitmPUTwWsVsZnC8iMb8IUcj3HcFysVzEerFMfixifaAQSOOoIIsKUTkuVynivhLDY3Gc7ts7EerViYAURqi5E8FCRfjvvqd1gXzv4DsEJWQEN0TcH3zQUWfAtffXgh1WNlphQd4yHnroITFjfLfddsPVV18tlpGQS763u+66K+yA47Z/CQTI/gYIFcj9786OQkhdv6BPuQX9bykoRHxxayxERCpBRCpCNH4rRlgqQwdoXbF4HqXHpAEUynE9zmZK/+x+qgwGxON17CYP0Cf2t7tjdPc2Io7H7hP638mfIVAotskLGxszBXk1ivZiQF1tZWNlsVezwribBV4N4viAejaMfJ+XeOj4NfDII4+IwU+yoCF7m1QoDiHparoo65OdRJQ+l157uieeeAKzZ88WVjrk/EIxn2Y7T5s2Le0xOpoxz7hPugJ2mJK9o9/WVYjykDUV4cnmJkjTndGGhNloGyzZPaSaIKKthSrRoFAWA0QGYOw2oAjhQJkI8LKQUCi2lVT3QjhQ71eVgdAVKEdbcDDCY3vLDQy1oC+exxoelFWoei4L/koDRVkXRnBIGIFVtD6SKCI4kTleZ4M4r9NrnkQeX0xNTPeZrBqksGrQQbK4BoLdsCjPMFmhhmFaP/mYj3ymTlNrhOK4+Q4tvRMV66ZCnwXqOL42i6CnQ7CMIghJDN5TLJZn4slxPPF5R1s5pF6FiJSoY3xsWzF7r7sJm5xF2FFQia5QOVqLhiWI+cpjIRTQDD1lll98G3oeExCiynLVMi9ZADlItC1F5p1TmCnc6gQGBiSog+94ETmvFHHOIZqamkRB1GTWr1+fvl/G5BTpv+fs/e/WzYUoK7VGiA5SxnxoM0C3dOoOdc+TSfX2KfrsFGOVfrbof4u+dFGPWzio6n8HYv3uQM/+t1TafX6U2B3pKEVLQS0iwbIe8bq7P66+qfrfyrK+qu1o9h5S9L/9gsms+YSM+XQirh4LGytEcS2fx0lRvkpn3PZKG9BrWfJ9dZyaLKWzFKiOyaOPPipmpZEtDfWRUv3eKlbp6dYrs56SbUGVx3rrm1CW/AcffICFCxdiyZIlYr/kcU8uLmZhYT4HoAvLWEV5mYrCTqxo7Yf2SAglIW8LqJRpR9PrKUuwMJ3wabK4fWuwBk0F22Jo5+uxhkchJFBDpDCWLSg/Fw0PIfaXIBzoJQRodcNDabRI4RCiAwp7TEGUOtJNR+xCsHcXgg1UkLdLnoIYoMd0HxFTEOXlXbFliY/FPQkrv3Y/FkIL3espGppNnE8nZtf2bBgEpbbsIm1tDojyRgr6GsmY95MwzzBMVijTw4ynfa+CTny9YRCiEnXQHTzhBoRQIW5L7QhF2gF01yRKSZbV6VhfujU6C3qj/6bPY4K/covFbiH0x+K7GCQoRTjQG9FAQWxZYdJ2BfIy4YEriViukDKOCzFfFv2FqFAsC/yB0nDicikSexxbJgZFYtsKYSES266r+17P778VHdkmQKoqQCAStvf6qfSIKN/kUOadw0VEGes54ogjcPHFF8ez5KgvtnjxYpx11lmYNWsWn/Icx2z/u1d5J35e1Qeb2wtQWmKy82oVaWIGxR3R/5ZS9L+NCKAp8gHbgoOwLrAzaje8khifEbtXx2YRt0sQRoU8gK/0v1V9cDH7T7xW7n8nf54en5HicUzMVyfYKX1oOUkv1p9WEvREH1uJzaplFNNVryX9wumsedljvsuYKO+kEO9WlrzuWRUuznTzsihvA0uWLMGVV14pLOImTpwollGBVsqeV0N1TRV7mnTrlXqnyeuVmqjJ9jda2XLLLcXNSliYz5FMO10d+iThcMeWX/Fu2Ug8/fPWOHXk1/AsDom6FNBDIrhSgI4IAUFgRAvVKdLS4J1oSFQVICqRmF+IqJT4uHuZ/DgcLUtYLtG69bHHSqOE7qWCWFMkcUAgYbAgaV2wRMk0kEUGulc/Do5SGh+0DQkISgOke3lbcAiKouvROmQoglF5X2JgQXkNPa+l7cnKAc6RLeu/3sLv29JBhwDgFysbzpZnGPuEeVWnYp9+y/G/DSPwn8ZxOLj6h/wqepoCEtRDJHDHsv/lufnOQHGUitgpAwJCSGgmeyA5yz9R/JeXRwNkDSSvU5aLuB2bGaDU94lnG6bL/4vVmqTp1hLZpQyMis9PgkNAEfyjNLMxJixQTBbLuhDcSNvEYndEeU0XglVd2FwxEEVtDbJwQa8RNYPoXvWaPhSXotoyE5ssvr58dG0KRGPHhQF2o1nznG2fknvvvVdMaR84cKDoi1ENtebmZsycORP33Xef2W+LyVVhPibIbjNhDUaNaMITz2+LM2Z/iZxET0YyiuT+d1Ws/41Y/zsbFnSJ4jZ+cTGfxH2lD63EZGWZHKfDKIs/Fvex7ePxW+l/B7r73z2IWwbJMUHpg8sD9REEKFGvVY6xyoC/fB9BoF8YwWaK4bH+dywWi7gtRdBWXoNQSRtaW4fK26tfSzdK5hP9eY1x20kx3mXbGs9a2eSBKN/Y2Ijzzz8fxx57rIilCltssYUo1Ep1ShUxfenSpdh+++3j6+fPnx/fvr29HfX19fGCsLSeBs733nvv+GuLiopEgVivwMJ8jnTo006BT0a59lTXILUpTi/5EhetmYHJkV+wdcla/TYrRi1TrMDiTGvKinfLm5a+CxKpSUzQ3CBBiu/CUDpDzyKjNEAgraJGR6whIhoYlHmgPJbvhQghZhKEYo2SUvEaek7CfLh3H3RFysVzcaPBg9jrxOvX0fSjkOHK5zQTgHzXRSNGfZ/8uImeq7aN36hRQtvE7tdFEAhFE9dLynY0Wk5ZjpH4Y2W5GFyAejk12q0N4pLEGfMMk1dWNho6u6GAhD8O/QJ/Wr4Xtq/4FcNKErNG8k1oEwPsUYMx1CRy91s1IKAWjUttfvMkgVpqDCIaLIAUjMVuGhwIhrofbwx1r4/di/UFsrUQPaYBARLmQ+HNaK8YJC9Tthf7KYBUFoptG8wex9sBaVTPdULkpxgq7iOZ7zfFYrAYGIgC/eQBA7KHSdhPysexeK66h/K8KYpAsbK9arkNX5Vr1gp6itc25c9vhhEoA+/FF18UHfxvvvlGLKPp7EqGH5Pb6E6MS9HnO+3Y+bjo+hn4attB2H6r1cgZDHi8i9owqVLpHSBu46f0v5NDl116bKinAC1sg4Tgr+p/r4/FcGWZuA9BKk0cuBf975YCSL1D2Fw+RNTvoVpBYtvY68Vry2P970BQ9MW19L9TrevuH0cQaI3F6IHKYIHqpmxHN0oCUB5XK8tV/WyKvxto4EFZ3h3XKSbLAwuq+Kxso15Og2aZvrQqg8K8m1Y2eSDKd3Z2illow4YNw5FHHim82xVo4Ltv3764/fbbccopp+DLL7/E119/jUsvvVSs32+//TBnzhw8/fTTmDJlirin7bfbbjuxfv/998df//pXUfeUBtNp8HzPPfcUNjlegYX5HMBsw4DoG+rAaX3n44H1k3HnwDdQVh+bUuedQSTHkBsGFgjzbpw7CwdISFCmzAXUhBOzxyX9gay84Cf0Di21ZWBFnmUgC/uK6C8/ji37JbacbiFarzyXGyPdgwW0fQGijdSAIQ/k2DbKPXo+h7I81rCRwnRPwoR8LwYbegHSmvSzFHp8niyDEhs2T0B7V7VsbySEf2okKPfR2Gtp8EFu2vVYF0jcRmkCQr19fDuoXqesjy0TK2P7UY48bpUURaA/NTbl/cvrlO3p1iSyjJKnnDFMvmLWyoYYWrwJRw5YhD+v2gk3jXwHBcEsP9Y5LLRRHC+UDPrg5BDC/i/aCdDNRIZ5R2klBq58HyVtadLbtF5Had5XRAaKo3GxP9R93xy7j9+CQqCA8ly8TrV9iMSJ7m3l5co9bRdIeB3irw9C6lCWK+vkbbPG5hJ9cXx9zbb4cY8z4tvJYoIUGwyIxVwhNKRYJixw6DWqbWKvh3pfynpxQPJ23fuhhbQsdvbF+th2FbHj3hRFoJeyXtl3bF0vCYH168VDjuNA//79MXr0aJFBPXToUI3/DExeJcaloXdFJ844/kv89clJuPPKN1BR7mLRcqsylA0WXqXELi7aHrMNov43JQlKqtlwejLR18vWPCWd69Cn7fue4m4zTBPL7Ue0sVv0j/eT1TfE4rjSf1bitbgpsZkGDIohtcSeV6jiciDpfnNS3Kb7smA8XivbyseYov9dkqb/LYqyp4/bzX3GYXMpDXZ0xIR/JdbG+tjitYmxNmGdEn/jy1XxWonD8Xskbl+h6l+LdUn977jFjiquK6+Nby9RYRRP97+/++47fPvtt3EhXQ2J6nfeeSduvvlmkU1Pcfeaa67ByJEjxfoxY8aIIuy0HYnu9PyOO+6Ie8iT0L969WqxDWXTk3h/ySWXwEuwMJ9PDYMsQvEuZaswv30wrl+3B86r+gwDC1pTe2a74QVuxCLEiDBerzQMOt0T5Otc9lvX6zefBalfgchQT0mtRbMMhLBMQSncc5BCa5vZbJHXVN+7Dd/j8objUdvvRRSGWsWsBjnk0iBAbEBAkvM+5MGG2DrahgYeYjkhkvoxnSCxH3o9bSfvM/48tr2Mev8B1XrV4x7L5cZRNKpeLg/8dXV5xFOTYfyUMZ+h0zuzcgm+2jQIt/y8O86u+QJ9Cjq0CaWVOTjATp1aPQJ0pU0DGJUODYI02Wf5Qp1mmh5vhygPJTJQxzJibgDBFGbeS+d3S6L82Pf/Jh6LeCsaMvKAgIiz4nlMZBD2dcoy1Tr1MnQvkxtFsTiuPKfHyu9LwvaxuKy8ltigHE/sdbQ8VrhCyAD0nBJKw3J7K5/j+Nq1a4Wf/EsvvST6YgQNsJL3PAkD1dV5kOKYx5gaUFf5i++49a/YcZtfcN3/7YHzf/cZBg9ogW8xKMoTov9tRWKc39DqNa+zGCxlxpNVTcLrLUREhQaqvEPicorvTeuxNlqwTZX91+iKkcdi6KrXUNS5oTtui3gdTIyr8Riuit/xdUqs7XmfvF5eFwD6BoDO2D6Vfrb6seq1Ca9T+t+0TMTwAKRYvPZq3N5xxx0xb968jNs88cQTadcdcMAB4pYK6mOde+654mYWysx/8sknhbXOG2+8gQEDBgg/fLr16RPzlDQAC/P5IszXaBOOz+w3Dy9umoDL1+6N0/t+KcR6TQUta12ws6m1QRivAaSuQlE0VTWzyx/Yff5rDAjYNUA0TMXyUgjztR46F2ZFeQehLHxl9F/OipdHzd2bF2+k4TNA/C0stMBziWHyqYOfpUNBbe9Lh32MJ9dsg0uW7Ytzaj7HluXrsu83x7LnZWG+0zqx1uwAhh3n1kHRmmxrKPvO0WP1UTFXM8hZdXKWnC2z5JWBIasZwHH8pJNOEh3zN998EzvttJMQO+bOnSv8cWndf//7XxtOPONbC7oMguxpx8zHy2+Nw/+7dW/xeLfJDnSqNTQNnIQKuspWMnmGnpkKOsR5ymCP97+tHiPMdAxajs8KMT552yp7B47kJLdIYtwWgxIpNlbOt55ZDun20Qbr4LhtmptuugkPPvggzj77bCHEh8NhkZW/cuVKIfo/9thjhvfNwnyuW9l8IgFTtCt21Kk/vPf3mFC8Dvc07oKFHQNwct+vhYmHWxnXut/HAo/5Qkt/BXMkaz7VOa7Pvg1lbvdoaHlBlLfyenQoWz4+DS9uGcMwTK7EcSpClJJ7JeAc7XG8MBjFKYO/xsTydbizblf8pmoJDqv+3tni2k6RZkCBirEF1ofN7StTgVI3BjGaLMjEMyjSUsa88HA3Aovy7mOXOJ/nvP/++/jf//4nRHmFffbZBw899BD22msvV4+NcXtAnfrNAc2/0aTvH7LfDxg/ugH3PLwLFv7YH6ce8xUKQi4Xm9SDCdFTyZgPSe7UhvGVbZBG0ZfsXETGfLVHBHmtn9ljRV/jaC3+qj7fyedeq1DPk608C8V3ypbfbbfdhC0OQXHg+uuvx6677mpq3+aM0Rh/ZNoZEKsnFjfgwqpP8G7rSLQMSiMWJOOkkFxrn6e7Z6bS6UmWcKv4bk2amwoqLuPY+azTKMj7KEM+9c82C/NO8uOPP+LGG2/Erbfe2mMdecp+/PHHYpT8lVdecfS4mNzBCq/aZHbuvQqnDZ6PVxvHICJspbLgN+EuOZu9R/HXTkv3mXI7p7Dy/QwMKpClSiBqII5rOY/JN8Za8vi8rlmzBhdddBGmT5+OWbNm9chkW7FihSg0t/feexvKciNf+fLy8pRFYUeNGmXq2Jn8jNvjRzXi4jM/xnufjsTGTcXIF1HeU/1vO2hMullBdXYrm6DaysYMDSZE+Wyf2Y5zY8M1Koq/xr3cDQrq1aqb0X0wrtLU1ISqqp4X0/r164UmYAbOmM+RhoFS2CAl/5KAo/SlytF19fymiTi412L0Kezwfja3hYVWI1IRgkF3qsKnFZq9dr51QBnzCVXMa10S5e0S4x3MlifI750z5p1h06ZNYko6FaOhzve0adMS1i9YsEBMY6NgTFPZKFOOYWzp4CtZ81qn64pYFsCLDRNw7IDvsheC9ZOlTbZM9iYgWlqEQCrPU6P7d/NceUBUlYX5iHXHbXSdVe/P5MUsJBLlBw0aJER3Kvr2pz/9STynonIkyp9yyinYY489cP/992PYsGG63+Pkk0/GH/7wB1x77bWioJ7yvlSQjgYCPvjgg/i2ye0HJsdnrOvJmk/i+Vcn4sC9f0RlX5uzx/t7xM6mf+x8dhUhaMZK1gufxenM7wzZ8yJjvm8EqdxkNdNgYptsYrzvoP/lqHVCeipbIhblPQ/VkKEB/ccff1w8p9i/ePFiUW+G4r4ZWJjPi4aBSpzXKGDPbR+C+nBvkTWvi0xe807Z2ZhEEiP2HhHm3cyIr7XmvaNShuKvXhLlk/dR67OGAWM5nZ2dmDRpksiW/8tf/tJj/ebNm3H88ceLQjNHH300fwOMvXGcxPlrtXfy32wahcJABHv1W+Hvb6ZJ/7bRYCGCRjK89WK3ON/kDWsTTZliTgvvRt/fA8hF2hg7+fnnn/H999/j7rvvFkVYR4wYgRkzZuDDDz8Uwjwt33777YWobhQS/ok999yzxzoS5W+++eZ4x10pDsvkDvSdFhdny2rXJ87PXzAIy3/uh7NP/tz4gaXzIddaZNRG8T0TUZphHej0/0CDG+c4hUAvVRQg0NblvCifc4K82hpIslZEt8KLnnGUe++9F7Nnz8bAgQNF340K1jY3N2PmzJmi6LsZWJjPp6JxGkX5jmgIj23YDqf2/QpFtWk6Yl7MmreInJ5Kp5Va6wR6srIJKB7zdlwzdSYE+Uyv1XKNO5wtH8+YN1vzwUczWNyEpqqdeeaZaddPnjxZ3BjGsTiukQ1dxfjXui1xxfAPRO0YXXgla77JZBE5oxnz8MD50vLZdcyesEKcD5jx5s+0PI8EeQXPx/AcoLa2Fu+99x569eoVX0a/se3t7aIT/fnnn+Phhx829R7UKWfyF9PFX5PoDAfx6L+2x4mHf4OSkhwayNEgyhNRmrFutv9tVJxPJRjrja9eEJ2rE4XkoJGi7XZkyWc6N+usu4bstFqSAgE5QcGOrHbOlPcNZFX34osvYtmyZfj666/FsgkTJmDixImm983CfD41DO6SgAuy99Bf3DQewwqbsWPJr8YOKFPWvFHqk8Q+vQMD2bZVHW9UclCYr3dAzLTqPdTnsE6vlU3E+gGdOgden+l4XRSfAwHu1DNMXsbxq7VlzT+1ZhtM6V2HUaXrjR2Q2+K8VoE1jTjtWMZ8puOttFGQT/VYocp6oSBrhrdbnvw+EeIZ5yERXi3K01Tz1157DVdeeSWWLFkisthJnL/qqqvE+sMOO0zMgNPLV199hdLSUowfPx6rVq3CM888Ix7TTDomt9E+oJ4ha171G/3yW+MwoKoVu+zgg+nlsF5MjVo1Y12vOK9HTK7yqCCfQjSPFhQg0JjFyqbaIkEeNgnyyduaFehNEQCqeDCWAebMmYOnnnoKP/30E958800MGDBA2NuQvW2fPn0MnyIu/ppvmXYkzmegPtwLr7WMwcl9v0bAjsxfJ8XMWtVNx7bRPkUI1tjcoU9VgFRZZmV7LN17ZELr+dIhzAeVjHmzgnqd6mYWO65vB2aR8BT4DAxK+r/PdKNtGcaPcZzE+QwsbO2P+ZsGC295X6JVnFY6fGmKhqXMSk4uMmZn0bFUBU1TFTvVWvhU6zE2eizD22rx3IuFYnUeC8fxDPSJDWppuWno/77zzjvYbbfdhOhOPu9UCLaxsRFdXV1YtGgRrr/+epx22mnCru7111/X9T0++eST2HnnnTFv3jxhbTdlyhQ8+OCDOO6443DnnXfq2heToxZ0caSMv+e/rq3Af94ah1OP/gqxcgX+pr9BK1nymHcSvfHS7naDhdneUqAAgWzFXxs0FnbNtg10ngujlkNuWRVVA1JZUs08Ji+56aabxIA+WeORME815qjW58qVK3Huueea2jdnzOcAVk2l+7itFg9v2B7H9vkOgwpaka+IjHlqGOgVWbWIxVpF93qTAxn1Omcg2DgzQnjMq4V5I5nzbnjsexSeAm8v55xzjsiAI6gw3KmnnmrzOzKMjFI80ChkfflG0yg8s3YrnDF0HioKctSSTYt/6Qidr0vexoJpzwmYEZEbbXqN3cK2HYJ8jsBx3Dl23XVXkdm2dOlS3HbbbXjuuedQUlKC3r17Cw/4oqIibLnllkKkf/nll4X/vFZuuOEGIeiT6P/EE08Iz1nKwieBnwrBXXjhhbZ+NsbjRds1/jZ/Nn8oHnx6Rxx54EIMHbQJvsdgVrNlGfPKMWQTcb2W6Z4JrfUBGpI90Q16zFuRGZ/ueL1QB8AwPGM933nooYfEoDwN+F999dViGQ3Q0iA/tTfMwMJ8PnrTJlnabI4W4JEN22NhR39cUvUxxhc32pvZbkcRWCuE5gRhvtM7Fj7Q+dn0iP8OzGCQEExtvaKcq0wCfZ3N15od3xnja2gaWkdHh3hMHXeG8SRJljYbu4rwwKrJWBcux7Uj38Owko3OHk8m0bQyw/bJ67RkjWv0AjWFWf92s/hJMEhFPoryVtg/pfu/YEz5wVLhV7rV19fjhRdewNlnny0GQkmUV6D1JKrrgfa3zz77iMf//e9/ccwxx4j9ktfs6tWr+VvLcfQnxiVa2rR3hPDYs9vh64WDcMHpn2LLsQ4olm4WgNXgMR9wykrWo+egB1UpHmtuB5EwH7FPkHfrHK7TOfhjti2nsvvJhcksjDmamppEDbpk1q9fD0ldHNgAbGWTA9BFoDvTTmVpc8266eiQQrht4FvWifJ2WHokC6x2CapSwLiHt11WJlotbpy2Jay1IDMs1fdolV2NFnxWxJinwNsL+cRR0Ti6mfGJYxjbiVnahKNBXLpsX1QXtuHmLd72liifvD6VtYvVVAGB5MaxXVnn+SQYZLPhsdpixouWNXbGcS3/Fzl8Tqxm7ty5OOqooxI6yiSiFhcXY9SoUWhpaRHT0BXIH54y3vWw7bbbCuuaTz75BK+++ioOOuggsfzZZ5/FuHHjLPw0TM4Uba/qvh5vuHcaNrUU4/Y/veWMKJ8KVz27U2XMG8zwZlInxmm1XtFiVQMdFj5GsuWdtgjSW0yXZXkGwBFHHCH85EmgJ0iDpRo2NEtu1qxZps4RC/P5PAW+Btg8uAA/hfvgnK0/R8WwsHMe8E68Ty5mQqt96NUivNXe9E4L22rv+DoXrrVa/4j2PAWeYRg1a8PlYvjztCFfoSjoUf/LTGKinkKvRjDTwXO6g+jUe+kVdtvhHH4WnpsMxvGmPDtPDjB27FiRwXbXXXehrq5O+MD/61//wt577y0G4Mkf9rrrrhOFYN9//32RSa+3U33vvffi4YcfxtSpU3HGGWdg9OjRYjo7zby79dZbbftsjHcwakHXGQ5iyYoqnHPq5+hVYZF9Sw5gODHOyzRkudnYJkh5deo5BivF8nSifLp9Z3pPF8axuP/NKHGfPOVpIL+trQ077rijsMMbOnQo7rvvPpiBrWzymXpgbWc5qoo3oyDok0CYbL+i9iq3yJrF9Iiok/YoZsV4B+xsbBlhrnexqDDDMIzFmJn+uKazHAOLWt2x5sgXYdBuaxsnxX+935kT33EuXUdW2dFotcaxwkInB6EZb9SBvvvuuzF79mxhTUcZ7ccee6xYf+mll4oiblRLprKyEr/73e+w33776XoP6pBTpv2GDRvEPohDDz0UJ554IoYPH27L52Jyg4bGMvTt3Y7iIp1WIzlsc5NTGckNOrdVZWb3oNHYeyacTyctaryS7W6WTN8Jk9f2eC+++CKWLVuGr7/+WiybMGGCsLAzCwvz+UrMY35NpBwD0WJsH3oLeDrhNc94DstGmOtNDDAo67L5zWv1vneRnGq4+ohrrrkm4/r//Oc/jh0Lk3sYyrqLeczTAPsAO4R5Jz2vs4mLbmTLGxHnGz0ugHhJlG/K8cGXDNd0Qhxv0rAPrXZRLNAnQJ3lv//97ylPWUVFhRDmzUL2OIooT2y11Vam98nkMI2x/ndDBQZU2xS3G/zrM+97Gky8rtqG/rcVRVytem26grw+uR65/81Eo1FcdtllYlYcWeLRzUrYyiYfM+1UhV/XdpVjQIGJhkGmzHAvCJt1PpuqZLWVi132MFpQ7HVaTA7A6PHXz7ZdjeqW6br1wrXr56l0PODGMPZmy6sKv64JV2BgocEBdrO2GV4UAhtj1it6OnpaPdKNTLlOtx+nafKITYoXLVgaHfpeYp89HsebbPrevHZ+GSYH0R+7A7IIWUXCfDkGVrd4QxhW+8y7WPTcF/0bsx7tdr5/Mpt1vD5bG6ZRw81MTQMj152ddjbVOXZ9MpZAA/FPP/20mClnB5wxn28clZiVtwYViJQFsXBpf4QGRBEKSAgFuu8rizajrKDLPlsXI1nzmbKjLbBmsWRE1IidTZ0FsxEyvWe6fdphZ1Of4nym+p4zfY92oyWLnmEYxmsF5FSivGJlM7hIwsLW/nL8RmIcp6KwJUGLpsvbmZnb5KOspkZ/ZXppPrdNNp7TJge+C6v2Z9W+0n3mdgfEc86iZxgPkfgburahHNFoAAt/7I9QMIpQSOq+D0XRr087ysvC+t5CjzCcKXa5FNd8mZFspRhvZdZ8AyBVZTmf2YR4p6lK8d5VFsRuu60ImbzikEMOEYVer7rqqpR9t2nTphneNwvzOTBab7TwDDEYm/Bx2zA8Gd4GXc1BRAsC6JKCiEry/eZIAfYftBQHDv4RFQVpGgjZRGQ7xHk9768TS0ZE6xz2pq+z8FzpPZ91Js6nHaK43oEGFugZhnF5aiRlYRgR5Ylhxc34rnWgEOYjCCIiBRCR5HuK42EphIOqf8B+lUuzC/SK4K7FOkPZVovVhll0CAXRYCGCEZ2ChhOfwaeivGPvr4dGCzvf6fYF+zrzjgpQTT6Y5cIwecagkS344Z1qPPnCNuiKBBGNBBCJBhCJBMV9a1sRZkxbhln7/oDeWorDWp2t7YI475uM5AaLX2u1l3nsPQLpZnS4Lcins7RRYBGd8TAPPPCAuKdC8smQJkvJVkZhYT6fOvRJ2fLEAVgqbhgYW5AkaNZv7oXn6ifi7K8OwHHDvsO+A5fbI87bicXCva2kOs46B86HA0VgLSHVubDqu7Wi5oGfrjW7SXdN+eVaYxivZswncczAhTgGC9OuX7q5H55duyVeaRiL04bMx869VyWKc0aLR3q06KQQ5qMahIxcQi2+Jn+3FojIKTv4bgi+2UQDvYK6lv3lmkjAmfSW0tzcjB9//BGbN2+2NHOOyaH+d4qBuBkzlotbut+gX9ZU4LlXJ+Kcq2bimIMWYP/py6wXitXiezaxNNt+vIbVNicNNr5GnSlvJGveqsKujTrPbTpbGi2Yud6Sj8XMcaSCi74yWX777YKF+bxqGGggSTSrKd2Eo2sW4vuN/dEZNS4cZBXn9YqiNol7Rqx+daH3c9o1mJFNQNYqMDsx2FLnoBjuVEHifMzSz6fPyjBuxvEkRpeux5EDFuKGldNEFn0PKk16Wld6K+M8GiJhXmfGPLz1GTSR7liNfIYMr5GCIQSkiLb3tVOcN+LhX2XB/nJRnGcsYc6cOTjjjDPQ3k7eRNZmzjH5HbeHDGzBMbMW4Psl/dHekUGusdPX3EjWvNUiqV3YOSOgwaLXWy0Q6xXlswnn60x+71aJ8wyTI7Awn+eZdtmob+uF67/fA7OG/IDfDF6SfkOtwqgTmfMmRHtJKkQwYKBD70Xx1+x50yLep9uPWdyaXeHk9+PFa8CuayofPivDeDSOL26rwm0/7yay5af0qU8vohoVpZu81ZGWgoUIGBHmYUBYbvRfBrxepGBBtzWQHosjLwx4WPX95KI479EZL37iiiuuwKWXXipuJSUlbh8O47Awb2fcpoz56+/ZQ9jZHLLfD6k3anDJ99sGpFRJA15BT+a7mfdIFuKzZc83WHQMyd+tEbHciix6I/hlIIjJGUaOHJnWRpwGa4cNG4bZs2fjt7/9re59szDvc2zp0MfEtJWtfXDj4mk4cuhCzBiUxsLGCOnEeT0CXo3OdRqzqqNSIQJ2C/NeQavfvJOY8djXMziU7b2yXYtmZ2vkk1CdT5+VYTzWwV/Q2h931k3BmUPmyRY2avyUHa6DSLDIWMa8V0j+XpwqEpqGaCiEQDSiz6veanHeCwV2LRTnfeOlzGSksbERJ510Eovyedr/titjvu6X3rj+nmk4eMYP+M3eGZLirCZTBnPywLjFA5VRFCKIcG6L8pmK7WYS55FhuVYabRTlk1/PYjmTw5x88sl46qmncNlll8X7buFwGLfddhv23Xdf9O/fX6xbv349LrroIl37ZmHe51g2lS4pW3ppSz/cvHgqZg/7FnsNWJn5tU57atvoTx2VihAMdNkvLtuVRVyv83wlC9pO+3/bJfxr+RzZBPpU3xF7ozMM45MO/tebBuKe+l1wds3n2KHXauQLlDEfjHQ6mu2Xy1DGfKDVAksOo+I8f3fuw770KTn00EPx0ksv4dxzz3X6G2FyJW4nCd4r6/rghnun4ahZCzFjWoakOKuy5ZMF92zifCb6mxTmAxbVhlnnsJ1NgwN2aXbMjsgmyms5/ioXxXmt76FnEIn95ZksvPrqq3j88cex6667JiyfMGECzj//fHzxxRfYcccdcd5557Ewn2/YkTG/uKMKty3aDadu8RV2r66zR5Q3amljszBKGfPBoImGgZ7PZLU4X29QpLaxYCkVjaO/Kd/T6GdzUhz3oBAvn1OGYXIpjhcWFlq6z7kbh+CBVZNxfu2n2KZirb4XZ8vq8jhRypgvDycerx8E+iZvvqcQ5iNd1tikVPp8toYFWfO+zpX36/dmEzfddJPojD/66KOorOx5wb/77ruuHBfjz5luS1f2w81/nooTDv8G03f9Kf2GTljY6MWkEBtFkTUZ8057lpsV5VPtz0lv+VTnzYp6LlqtbXzkM8/9b4ZYsGAB+vTpg2Ro2cKFC8XjrbfeGmvWrIFeOGPe51hdfGZhe3/c0TgFZ/Sbh12qk6a9O5El77IftZwx3+lcxrdVnzfbPvRkwluYNS+hAEGpy9g5MzrQkI06l2Z6WHQd8BR4hsktrI7jnzTX4MFfd8TFwz7GxPIGa4uDuS3Oa8hwi/bLUPzVzoJvTgqeDmYwSxuDCOoV5rPhsm++qwSCZKgM35Bv348OTj31VFRXV2PGjBkoLy93+3AYHyfGLV5ahdv+uht+e/RX2G1ynbuivAtiqUiMQ6f/RXmj7Qt1+8qoON+gQ0TWam2jlXTtw2wCvU9EeYL73wwxadIknHPOOXj44YcxfPhwsay+vh4XXHABJk+eLJ7TTDrlsR5YmPc5VjYMFrT3x52NU/DHyi+wY+mv6Te0StDUmzVfY/J4NGSGi4ZBsse8m4VItaBV2M8kaNuUNR9FCAEYmAJvZLBC72fw+vfqBsr1wb7wDOPNOJ7FDuSj5lo88uv2uHzYhxhbplNR09Ihs9Fj1hKqKGM+gzDvBXHeyiK7ycsqrT+OaKgAgWhUx45zvLioyQEqKRhEQDJwPu0gV78jh/jkk0/w3nvvYaeddnL7UBi/Dqg3At8vqRai/O9PmIudtvsFnkCPON/fAx7zRgVeK9sDjd5pP0mBEAJSxJpzl2oAolpnbLRagLfDKodtbBgNPPbYYzjuuONEEdh+/fqhoKAADQ0N2G233TBnzhx0dnbiueeew//93/9BLyzM50DDQPMUeEVsSyHOrkQf3NW0K86u/Bw7lK5218LDzvfOIt4KYX59GNgEb2RLG7X8MYtFWfNSoEC/MF9v0fE57ZdvhnoPTaVjUZ5hvN3BTyPOf9cyAA//sgP+NPwDjC5bD19hRYe1SmVlI2Xp4LslzjfZLOBrEVp17le2srGxKJ/ZwrA+E+elQMDYQIcb+O17cZixY8eiV69ebh8G42MLOir0esffpmgT5RtMCo4NOuNh/yyiqoXiKFnZBJIT47TiRtZ1g8kM9GxtHpOWNhS3RYJCo8FjynatpStKa/fMykzXXKr3tfBY2MqGIUiQ//TTT/Hdd99h6dKlIrFqzJgxwtZO4cMPP4QRWJjPx4z5JL/uBpTiZkzF8X2+lUV5s9R4XOjLIHRHIy5VhTdqaaP3NXqy5i0QtsnKJgCLp8DnOWmn0llhi+S1/1WGyQMMxfEkMXNlex/cHSv0alqU12qT4oa1TaoOZdIxRAOFKIxszr4vp33nmxwSQjOJ8wb2L4VCCEQj1hxLLhURNXr9e83KhrPmDTN79mycffbZuOKKK1IOrk6bNs3cd8PkdMZ8U1MJbvrzVBw9a4E9onx1iudG9uNAIU9JKkRIr5WNVYK8XQP1jSZjiglxPqo1Y36dT2oYGBHl9aDhPLOVDaNAmfFPPfUUfvrpJ7z55psYMGAALr74YtEWSOU/rxUW5vO8YdCCQtyEqdgby7FX+UrzB1TjcEa4xfYrpqfS+QG9fvMwLtBLSGoY1DksDPspa55hmLzEcBG5mDjfEC7FLT/tjtkDv8MOvVab60A2ZRFxKx0Q59PtU2MnN6uVjYF9mqbJ4czkVGKrwQz86GATwryZ9/ZD4V4D178U8JCVDWOKSy65JG2R10AgIAZdmdzErJVsW1sBbr5hKqbu9BNm7LHcflFevdyDwiv1vwNa+99u+5JryZbXW0DV4naUmLGeSphvzFLwVe+1kWrwwOrP48DAEGMS0qK1ypHU/Onyd9H3Bx98MD4oHw6HhZ3NypUrce655wqrG6OwMJ/HDYMwgrgDUzAGTThy6KLuFUaFzBqHi7qmEuVrPFB8xus4KFTTiH1Q66+vldn/OQxPpWOY3IvjRgfYW3sX4ub5U7FXvxXYu98K2I4dGc96fFk1QBnzwspGeV26DmJjjtuFGC0om2pKvJnir+m88St12tm4XRsgHXpFiEAA8Jowb9VATh4OqjL5iZm43dUVwJ13TsGwIc049uAFzonyXvx9XacaUCcrm1wYy7LyPGrNmm9IYUHX0uXM8Zq03TEtyqeLv1rjssZj5/43Qzz00EN48sknhaf81VdfLZaRFnv99ddj1113hRksqFrC+LFhQE3J+ysnowgR/A5fin6C7fhARBUZ80Y97uyi1sJzavd3kCSuSyIDItYw4GKrlsBT6Rgm98Qdyq7USzgaxO2LpmBU3yYc2V81uG5Ftnw21NvaOQU8275TdLxEB79JFcfdFnMznVeviJ8ZjkMSxV8j9rxnk47z4Pb3aBFyxryHrGy8di366HebMuY3btzo9qEwPprpRv/6f/3rJFAOGPnKZwz9donybhe5XKe6xYgGNNSGYfQlxkld2rLlvYrHMuW5/80QTU1NqKrq2flYv349JJNtOxbm86lhUNN9e6pmG/xa1gsX4FMUpPOs1iMS1zgsDFtsYZMoJIeNi9JueHQ7fe51EE22srGSGmeuCV24eQzsD88wvkWvMB+VgPt/nIzCYBSnj3ZocN1pjAixjUB0cyEC0c7M+/KCyGu0uKv65gBRMx7zWsj2ORo98n1ZhKeLv+oZKMlzKCnq6aefxqpVq9w+FMZHM9afeWZLrFzZFxee8QkKCiT3MuVTbetEzZh1eWwl6yBSc0FinNESQ80WF7byOtKaKe9QtjzDKBxxxBHCT54EeqX/tnjxYpx11lmYNWsWzMBWNnnoMf8qRuMz1OBGvIMSmjNmVrA1+3o9PvOK8HlkUmPm2YAl9iYRqUh/xnx9ludWCOLZzlFNFoHWpdkKkrCyiVjvLe/hwQi74al0DJNbGMmWf3rl1vi1rReu2eZ/KAhK2qxAUtHoYtHIq5Pi+Dk6z0Oajlc0WIRQJJzecsRJkTedjYvZfajXmbUVynI8pq1szJBDgnycYMh7VjZqWJTXzCGHHCI641dddVVKkZaLv+YuRvrfb721Bd5/fwRuuPBdlJV2uW9fky2upvr9nZIUtz/RGLezZGhHUZS/wnyVPf3vQLpaO6m85XPpnNk0wMT9b4a49957ReH3gQMHijiw4447orm5GTNnzsR9990HM7Aw73NoyoSeTv1nGIrnMRHX4130RQc8gxZxPp0on4wJcV40DAI6PObrPeiF7iExWhR/tbrCR42Nmepmit06kC0vSQHvT6Wzo54Ew+Qweqc+vrZqND5dV4sbtnsXpQUW/b42mRR7s/m5ZxPl9ZL8Po2JVjY9MuZTbOcLtIikZsR5DfuPW9k0OpxZ6bfvKhcy5hldPPDAA+J+77337rGOi7/mNros6BqBed8Oxj+f3gpXn/8/VPXbnH5bJwuzZisEm/w7P85A3F6npzZMjtd4c7AYrdRHNWM917LlrRLldQ5meb7/zThCWVkZXnzxRSxduhTffPONWDZhwgRMnDjR9L5ZmPc5ekT5xajC3zAJl+IjDEGLfgHShmKrmsX5bKI8LVey5mFcGIwWFyIYDgNDNGxc74J9j5d92lOcDwkFCDRYKMzXWLytzwRkGq0PBDzcoffQoBDD5Fwcvy+AzxuG4rmfJ+K6bd9Dv6L2xPV6s+Ybs1hZVNpUCDOdKH+vpC1rPoMoT0jkMZ8uUww+ypbXu22lPRnQUjCEYEO7uYKn+Ui6wSrhMe/hOM5ohou/5nfc1hq7l67sh/sf2wkXnfkJhg21oSaBE3Yc6UR5yqBPzpo34F8urGySPdG9QLbBC48OKEdpplsqCzors+XzSJRnmGRGjx4tblbCwnyeQB6It2M3nIF5GO+VqGF11nGyOG/QY14Un/GZYOtVsVVaG0KwIGLvAIfRa6bewlkOjnnL07RZHrFnmHzMmF/cXIW/LpmESyd+hKFlm1JvZMTSJt32ZsT5dJ2kbJny2cT5bNPshSe6B4R5t+1ALHz/aFsIhREbPeZTYXcz1QoLIK3HnzSIIZH9hReLv2bC6dkSPuKdd97B3Llz0dnZne3b3t4uprbff//9rh4b4z6rV6/GrQ/sjt8eOx9bjs2iWLthYaNXeE4nzr9krv9NwnyAKuL6gUznTPl9dEtqaVRb2XQ5dxxVDvjJW/X+Bv5nfBaxGYsZOXKk5oHY5cuXG34fFubzgA0bNuCmi07H4fgRu0BVpKjGgYzkdK8zInxns7CxADGVzkqPO6sziO3MmrdBXI4GChAgj3mzOHFd+gBJCno7Y55hGFvs6H755Rfcvmg3nDFmHsb3ydLT0iLON+oUMJP3V6lB4NRrb5MNjfsRHVK7io47JcIbLQxrA3ErGzvwcJ6IpZ9JJc4LKxs/Z8zn4ndmkFtuuQXXXXcddthhB3z++efCa7agoACffvopTjnlFLcPj3GZjRs34qabbsKsfX7A7pOzdN6ctLDRK84bsbAx0P8O5ZLHvJZ6NsltGgsHPak2jG3tID2Z8lpEdydF+VxMjKv2wG9IjnPNNdfEH8+bNw9vvfUWLrnkknhtmXA4jNtuu00UhjUDC/N5wL///W9sVbwWB1QuNb4TxzKCTYrymbLms9nkKB7zlDHvNPUui/O1JkXuVMdfB0gV1DDoMve5a3QctxsCvqP/G9Qw8HGHnmEYQwXk/vGPf2C/IUuxS/WqnkJssjBulSivdX+w2Fc+VdZ8FvuaHpZfcAi7rGm8AnnVjipAIFXxV7N2Nm4KvFZmy6cSVzKI81KAMuY5jucClBH/3HPP4YADDkDv3r3x9NNPY4sttsCtt96KJUuWuH14jMv85z//wehhn2PWvj864+9tB1pF+YM1ZM1n+M2PDipEwC2P+UaTgxnpfvP1xMcqg99xmmsnShZ0lDGvxcamwWJR3goxPtP+tayz+P+F4nbAC/3vaptnvzApOemkkxJqyzz22GPYZZddErYhn/nzzjtPDMYahYX5PICmV9YU2uBpZxdmM+PrjG8fHUsZ8xY1DOzM3LZKnK+19/jlzEWbBjrMiPJ2HYMTGfNeHbFnGMY2YV7E8bKN1ou8donFJK671HF25DeyyYf7NiikR0MhBFMJ82aOI1eoMvDZg0EEWqSe54EtYnxHU1NTvOBbv3790NDQIIT5o48+GpMmTcJDDz3k9iEyLtLR0YGaQRuhoxyce6I87a/KvbgtbS5EcGO4OynZS7+HPhQ8RcZ8c8Te663KJUFey3qL/1dEwodTA+rsf+9pFixYIAbik+nbty8WLVpkat/Ze4OM7yvCi6nyfhHzHLCryYSEEALwYPGZdKJwrYnXWSUqp8mWJ6JmLQW0+srngSjfXfzVYa9fhmFsIxKJxKdCZiOQTrg1W/DV66K8UzSluPmZxqRbumWZXi+sbMir1qIOqR3Xnxe/qwyiQVorGy3fCeMppk2bhttvv114ypMQ/7e//Q2tra144YUXUnbcmfyqC0Nk7aa74SufCitEeT3xJZWVrDqRy6nfQ6veo8qF1zak/yxSwEILumyifH8LRfkqC0X5aiv/VxywsrHieFnUt52ddtpJZMbX1dUl1PK88MILsfPOO5vat2MZ82+++Sbeffdd4cdTWVkpjPFfe+01rFmzRjRe9thjD0yePFls29bWhieffFJ4sx1zzDGoqakRWQnk3XPQQQdhypQpCfumhhBlKOy7777IJ7Rm2mluQOgprlmTe6I8IW0KIGD2v8JpkVj9/dRZJB5b9BmoYRBMZ2VT72NR3jU87HHH5Dwcx+2J41qE+awD7FqKWSZ3QO0QM/0symtZbqS4bqb9G93OKrFBQxa9FAwh0BX2riif/NjOoq5a7JWyiQbBEP3jp19v1iLI75CerW2sEqKE0Wa4xt13342ZM2eKae7XX389ZsyYIfq0xcXFmDNnDrwAx213+9+BgJQforxJokhTk8zqWjVWZs0nL9PiK6/3PQ1eOxS3g9H27gXrbBTlM623mip3/keElY2dGfMsqPuGJ554ArNnz8aIESPETDnqw9FsORqof/zxx70vzDc2NuLDDz9MeP7II49gn332EdP9VqxYIbIL6MONHj0aH3/8MQYOHCiE+ldffRWnn356QgNjm222QUVFBfIdQ5l2XsVKUV6rX3sKQVcIH3XuC9quZnHXWHeuxYi9kYx5o6J8qs9vR7Fcl2ouyFY2HvC4Y/IOjuP2xXHNA+yBLMKtlkKsdpJrorzZbd1C73edSghu1Fj8VatoYrcon7zcKXE+1edTzmcakUbOmM/yv5Lv4rxPGDNmjEg0o99n+h1ftmyZmMpeW1uL6mr3lRaO2z5JjMsXUb4h/eeg/ndGrcIrAj00iPNa4l6Vvd81zVgvjJjMmM/mJ9/fY4I8YdvPLl2dNvS/3Q8TjE4ovn/wwQdYuHChqCVD7iVjx44VHvNmccTK5uWXX8ZWW20Vf/7VV19hyJAhmD59umi4kABPgvzixYvjnmz9+/cX4jxND1RDH57EekZ7h94Ubhd9tZNMonKdD0V5K7D4M0SFNVBE33vpmbmhBStte8wch2VWNizMM87DcdwDcbzFoFjZ6IDAnA+ivN3vYcWxNFokLKsQVjbZOvjpLAzstCNIJ747LcqnIsPnluj/3SprIMZVKKHs4IMPxp///Gd8//33IlN+++2394QoT3Dcdj8xzjK8cUnpoyHplmq5XqyMKY02fwdVGW5Wvk86j3l1Ylx/DRYqyTcviPJazpcD/yNyzTwfDLTZuV8mgS233BKHHHKIaANYIco7IszTaALZ1ey5557xZXTws2bNStiusLAwHuTIn4dsb6jaPYn3avbbbz8h7K9cuRL5jmVT4J0UlXeV5NuRSbdcEef9TI09gaxHVfjk9zT6vlqy5ZPXmxHVrRb4c9HKpl7HjBXGN3Ac90ocN4AdouirEvCk6uYxUT7lmUrlH+8lUd4KYcKK7zrFPqKhAgT1etW65ZfuliivR5Swe0o84xgvvvii8JZ/5ZVXsMsuuwjr1ZNPPlnYsa5evdrVb4LjtkdmrAdMCmhW+WRTZnyqmx3oEd3NCPRuUG2zEGrRvoQwn6n/rSdmOS3Kax3AcFCMpv8US2ess3jOOG1lEw6HRWOFRPiCgu63Gjp0aMJ25CW/dOnSuHhP2fKXXXYZurq6UFJSkrAtTRWYOHEi/v3vf+Occ86xP2M8BxoGhqfSuS5C+gi/Z8vbdPzCykZLMd2amKBrdbZ8pn3V+e//QJICbGXDOArHcR8NsGvtuDaZFOWdoMmYECt3niRv2M9YaZFjlxCvYX/CyiaiIY67gdrz3w37GgOChLCyiWr4P2I7G8+z9957i5vyW05WrNdeey1OPPFEMcOb+mluwHHbQx7zeuM2C3baces3Mp3fPAwOMqhfbxFR8pjv1ZXoLd/fgNe8UVHeye/Fif+ZQAiwakCd/8eZNNiqalPWO4nslOqfKbg9++yzIouePHsUSMhPFuUVSOgn37xPPvlE9zGR2E/vmU8NA01V4Z2AMuX9hB5B1uks4Zo0N6P7MIKGz6zLY77Gxmz5VNRqyI73kCgvEwTYyoZxEI7jPrWkMyLK+8E/Pcsxy9ON3RHD4lidje9WZqAeKxs7yXYuK13MlG/UL0SQlY3r16hevObr7CGoThpZ2Rx44IHYf//90draiuuuuw7z5s1z7Zg4bnsoMS5b/zuTfUgOFXe1DSvs24yQ7rsy8j3q3V6D+C+3haL2/u6nWq83090nCCtZsxnzdv6PMzmBbRnzVJ2WhPOzzz4743bkF9/U1ITjjjtO87779u2LvfbaC2+//Ta23XZbXcdFtjobNmyIZ5HLFdMD8XvqIFOwzXRL3oZe5/WGQcYR+1SCaCZBsiaHRPmkz2LQLMAcekX9Gv9k7lPxmaBkMtPOTnHcc8J7Zrj4K+MkfojjyTPCKB6ni9WZYro/4rjLQq5T2fJ6UWVMR4OFCEbCPdc5eRw5hkSZd25kzKvPp1tZ8XYQCNI/tNtHwVgAJZX9+OOPOOCAA3DsscfiiSeecN1f3q9x20/9b18lxjktyhvJGK92uP/daGPmvHqdmlTbWf1ToSo4LlvZhDVvn3IdMmTLpxPlncTJn1qzFnQsyOcMI0eOTBt7KC4MGzYMs2fPxm9/+1vvCPMffvghOjs7ce+994rnShC+++67RVAn25q5c+eKjIKzzjoLpaWluvY/depUfPnll7oLwZKNDhXrSQUdIwVb6iinutHnUR6rt1N/PkL5stQNiFQNjuRl9FyPQEDHQN78jleFz1FRnogPYHhVsPWS8K7Yz1iVMa/nfdV49buyrfirR/+fmJzDr3FcidHKDLl0cVwdz5NjeKbB+lSxO1ks0BPHNXfwtUyJt8O+xsuivJomIDqwEMFsnVGL39NySxaPEfWSlU2TB8V5nXYKImPeqpm7yv97DmYo+oFTTz0Vr7/+uoiVFG9IeJ45cyZGjx7t2jHlWv+blitxO3mbVP3b5LhtR//bssQ4u/FRpryp86Tnd9DqxIVM4nzydg6+pxhQJ4/5ZPE9m51NunOYqXhsptfZgQsit2S0xhsL8jnHySefjKeeekrYritxgOzjbrvtNuy7775xS/b169fjoosu8oYwTwdGwVvtI//3v/8dp5xyCgYNGoTly5eLavEnnHACBgwYoHv/ZHVz0EEH4ZFHHkFZWRm22GIL08eszrQzS6pGhvp5R0dHj2X0OFkgUB+b0pBQ7jdt2iTsfpSp8KkaHEqHP2BVtrwfRPcaY9no9KNrappSJo/0XBPls0HXUB2dU5O2AnkkumuDfptyw4qL8T5+jeNKTZuioiJT+1KL/KnEgkxxXHl98rGpYzTdU8ON2Lx5c4916jiuaUp8OrIJvlTANUeQNhYh0BIT5s0K3V4RyjNltTkBDTQ5neDhlXNvhzgvPOYtiONOXhMu2yl5lYsvvljcyL7mnXfewWuvvSYEcPrdpiz6e+65x/Fj8mvcdrL/nWq9nv53S0uLaF8oA+vp+t+m4nYOie7ZkJz6Hbbrd0yrOO9geyEqEuNicSaTOK8lbmXzlXdKlHdR5Ba1YfRmzLspynvpmswxXn31VTz++OPYdddde8ygO//88/HFF19gxx13xHnnnecdYb6iokLcFBSBmKbBUQeUKtZTw2Hw4MFCYFbo1auX5vegQrBbbbUVFixYAK9hZSMjuaGh3Le3twthXikwlJxRoNzTyE1w2yPwY9GGmEdWdwgMlocRjHYiKHUgRPfRdoQKOxFEB0KSfC/WxR6Le6lDXr5rhxvGL7aJ2dFAoTzty4wYXK/zfet9LspnypqvBaSSEIKNDmYv5jhsZcM4CcfxbpHfCpIFA3pMHfzi4mIRxynjInm9cj9ixAhsDh+HH4pa4/tTxFLKEA+2diAU6UCwVweCkU75cbQDoQ2dCA6gdZ0I0rKu7sehrk4EHvdBHNdBJBTLmPebsJsta74qjwTSTN+d17Ll1Wj8biiT0ZIick4N2OTDNWeS1atXC1sY6pfRbzk9X7ZsmSvHwnHb/v43ifta+t9ka1RQcjh+rF/fs/8dDCMY6EQw2IlQsAPBYAdCgY6E57Q+vi7YGdu+A8Hq9pyK2yKJCxH7xPnGHBRCM71flWJlo5rppjdzXr1d0r4dxwNZ53LGfNRzx8U4D+nOffr06bGcli1cuFA83nrrrYV9m15sE+Yz8dVXX6GtrU0Up6GbmltuuUXXvqjYDvn75TqphH4araeBjmzTECmDo9+CZzG2YnnCcqkGkFoKEQkUIRosQSRYhOjgYkSixYgGihFBMcKBPkKwjgSUZUWIhosRHXo1okuWZHxfZWpgcqaBennyevVjPXYAVhANFiEohUWmt8AKgT6TuO53UV4DURQgMDTSfU71wNnyaaxsOGOecR+O49bEcRL+Kysrs4oING1y65anMK7X6oTl1M2Pri9CNFQsYlikoASREMX0IkTaihENlSBc0hftBfI2kQJaRo+LEDnkKkga43iqGK3ludNxXAoViYEJ03hV2M8ngT5HkTPvLMoRZQsbVzn66KPx0UcfCV/3SZMmYe+998ajjz4qMum0WI06Dcdta+I2DaaTCFNeXp7xteTFX1b9HMbWLE1YTv/+klSISLQIUalEvo/G+t9SkbgPd/VGNFqEiFQcWydvEy25GtH1qeO22oLPtf63XoG6Wk6ME/1vq3ArPipCrQcylaXyUKIwb0Scz2Zfo+zTTtwWv5X3LwghUBK1cHoH41cmTZqEc845Bw8//DCGDx8ultXX1+OCCy7A5MmTxfOXXnop/tiTwjx1PBXRfZ999hE3o69XQ8L0ddddh3xElzct2foNTFomMu7CcjCMtspCqBbNbw9Jc4aBclNPFVRnBFKGYPI69S3jZ0pqfMRvffdGkDL7KYtQ3FOWf/djyvoXn1tZL3WJLIZoICbMK9RZLBTrLfJqwkLGK1nzwmOesiCUc6f12Gpzb5DCEqQUI/YM4xAcx92L4ylrxTTKcTyETjHjTdChUVx+Ul8cV8fp5Mep4ngq735dcXyLvYTAToVc5RkAnQhEwvJ9VL5X1tE9LaNzEQ0lFX/1myjvQa95EpIFeo7LaGa7xz67bUXkohFb/OsthweAMjJw4ED85S9/Eb7temZ8OwnHbevR6jGfDvpJDQTCImse6J4FZ4V9jav977JY/7s2jCDN1hN97c7EvrhyXynrDyn7335HLSbbKdJnGASRAiEE+kWAtcguzmulygaBXWvxXKdJev/kGS9M/vLYY4+Joulk40Y6NCVY0eD8brvthjlz5ogZVM899xz+7//+zx8Z84zzDQPLfkyOlFyx8kmF0unv0bDo+EkEeXELFiFcUIZosDC2rDDpsXxPdAXL0VY8GJ0FqYsTBcOqBgU1MvpQgyKMIN2kxHsh/KdaLh53IYhObd9JjQEh2w1xXuv0RL0CfT6TYsBDroPADQOGyRWUDDctBPQIZiZF+eQ4blf2ZzpRINpcF8/sJ7G9s7Bc3EdUy6TYc4liekg+vo7SSnQVlaOlMoXvsSTJYj4NyivCvngsPydxP7ghjGCvLgS7SEjoQoDuxXq6dam2pW1kUSHXEdndTQ4Uac32Hl62sYG+4q8iZVYv6v95zpT3BEqBVSa/0DOgbtmEsSof9L/Dqv53nyKEW8rkvrbojxci2qsQUZp5ryyL979L0VpQi3Aw9eBWvN8t+tLyvZJYKC/rEusTl3U/DiRsR3E7mvNe39FgQerir07aoFUbmGXgtiCf5hiElY0VFnSM7xk5ciQ+/fRTfPvtt8Kyjn5rx4wZIzzm1UXYjcDCfL5m2uUAymfv0fjYnDhlUCutxTVYX74tapr+m/IHuVvUj902FsqCgCLyD6QGRyHCgXJISqMDsW1RCAkFsce0Pf3rBVKOwiY876BGVqRb1KdGRYAek7hPmf5hBKu7ENxEyzvFtmJZJLaeMjIQW5bquVgGW7PmUwoX6oEEtUif7/Y1NZmfSxuDQEsUGOLgLAyGYVwnIY6b6VB5rNCrkmnXg8bMFjvpWD9wa4SLe2PAzx/3WCcFgnIMjwn74hYskJ8HCyG1xpYVFCFc0iu+jVQQi/3K81DsNTQYEOiO25liX4BisiLm031Eda8I/srzYV0IbuiKL5fv6TltE5H3sZn2JW8jbrAJEsvbDbyu0obZAlrF/iZvC/uS3uKvbmWtc7Y8w9iSMZ+z/e/w0swqU3dJwQTaQoPQULozhrW81GMdxVZ1f5pmYpMFb49+NtnuBmP977j4T/1u2rYgYTtN/W+xVUQl7FO/mh6TuB/rfyuPY6J/93bK41h/e2AXAo2x57FtaD8BG4V/MWNdiiXGWSHOpxoMzjRArFdg94Ign22mm99mrHMBWFvZZpttxM1KWJj3eUfdUWFeY7a850mTUZ7J445+jENUBDei9glIYkWK9zGJVEkNBWpQFECiRoVEjZCQ/JiWDyyEJBUgKhUIv0K6j0rlCFcWQmoMCX9C9fZiWzFIEJLvpe5GVaYGivqxPDBAjQ1F/KfGRURueKyXxX65MdKFtuBgNBTs1L29aIjIj+UGTwSB4bHnojFDj6nhomxDt2hOFTkyNzuCvB+jqV/DIj3D5Cwi8y4PsrPNQoJ5OiubgBQVMTxlHDdqodKUXfgV3xyJ+WIQoED44Edjz2WRnwb5VfcFhQiXFMsDAsp6cU/by8ukDtpOfr0oJprGv1z9XLGkIVFYFvojstgv7mMDAYrYTwMAzTRjoAttA4egYbudureh7Wm7KL0u0v1cWUe3su59iu2iGuO4WSsfK4R9uwkEASpQrBWuK8AwPs6YlxzLlvcrUgYrG2r3iP43Zao5eBroreSEuoKY2F/Y/bhvSB4kaJYT7uKJd8FyhKlvHaD1sf53bIBAKo/1v2ndZvm++70CCZ9XeZ78WB4koD6yMiBAt4hI0Atsolgb639LXWgrHYzG6sny9rS8r7yt6KeLZREEK+RtA42UOCAvk2/d2wTSie9VPhXYDeJbKxsW5y2HCr3fdddd+Oabb9Da2tOKLLl+qh5YmM8DKioqsHDjAOw9YEXa7GjqtwVyQZS/K6Dd7kUhJtJb7nFnNhO8JlYHICaAi7S1gI59NsNyJCkQHySQxf2QPCAgxP8QpOoCSGuUgYRQbMpgl7xtoAxd1CChdQHaviDWaIm9NvYa0YBR9hdbF6cjRaBcKgG9EgOnuiEjZhEESBSg+5jwr36esC5KqY3yAEFsHRK2p/to0n7k13Qvl+KvCwYoWyGqep28H4h7+djEelm60XT+0zbyM8xaYBjGm2i1sSH/4gUNA7Bd55q024g4HvBPtnxajjc+FEuZ7aEunSneVojyyc9VArD4fY/Z4SBs0XGZyGYWMwdCISH8k6ivCPximRD/CxBtUR6HEAyTv3+XeBwtKkZYeS09F6/p3lbcKmi58pwGDoI9Bg/EeZGkhMfx9R2Jgwn0WB4EiMqif3FMMKDHiuiv3G+K3SvrIonPIbaNIlCe9LrYPU1VF9vSvbKtso7uxbHIy8S2UUn1WNvgA52PYJfG/8Uql+xrOFueYUzHbtH//nEAZkxbhnQ6fta47RdR/hGdcbsqMW4Hg51AiXd+g+L9b6kLkNoTj1lW7eN9T1uOtSHVzAF5YEAW/qmPrAwcyI+llu7nZNNH9nzyYH+s/03JAGUhSK2UGBDrY9N9rfyaaLs80B+/lWVI3itNkQRQknityol20dhgQqyfrDzu8TzWb1atQ2x593bRxH0q28TXS/FltB/Rv46/Xt5GXta9neb+N1nZqK15/YSHihLnAscddxyWL1+Oww47DKWlpZbum4X5PODYY4/FVR8+i2frJ+Ko2kVo6yrAstZKLGvpF78f3LcFVw77IPdEeR2CuMiY15PFZESkd9KqxQaveRKFQ0JZUJ2n5NM+uFsgXitNRVXXfPszypMKGytQm4GCKc0MEEK/uI8917CMiq0mbkMzEpRlwfg2NMCA+Dby8sR9KM/pZHWvo23l50Fgc0/xPVmIb2+vQiRSio0bxyasp3tBS7d9QtYpmmJQgO6pMRRrpMQHFRAfMEBAabTEthHH071Mfk3SMtVrlBQXZV9iu9Cv8uG2tMBSBgAo0rgt1cpMLorEMB7ltxuvwRXNe2FQWQv2KVuBjdEiLAtXYlm4n7hfHu6HbYrW4A995+atKE9QdnlhZ5r58snYlZltNyZFADFzoCsKdIU1fa61O09F1Xca4riV2eiq46AOvyLuC7GfHlcpj2PP6X6Tar16nWoZZauLgYdwsby8j7xvUs1IqIB6f/S+tE1A9VpaF7uPP4+9npZnm7VAtPUfIuyIGrbaucf6+ONYXy9jHCdxgcQMEVqjquexe7GNLEKIZTH7HGUbsTdlXey5eEz3mxLXy8tjjSplu1/lOJ4qY4xhGOCoo47C1X96Ev94aWvMPvQ7tG0uwPKf+2HZT5VY9pN8X9W3Dddd9L/8EOXTDC5SJnk8Mc6rg4KZBkbt8GxPElPlmQNhIFMCoarps7ZjKqqavsr8Ho0Gi45XaSmWGut/i0EDEvjJEjg2GKDcVOvjSXoUV2PbJ25Hgwmx/rcYyZLX0z7lx7G+tnhNrG8de5z8GmVbEcOF4J7CKaA0MfZ2BPuhK9QLLYWjemzb47UaLJLEvaTuf9PzSGL/W4nBqj56vK8dX57U/5bS9L/pVt4dty3vf+cRH330ET755BPLbWwIFuZ9jFaLmvLyclw+/kNcsXAvfNgwHA2dZagtbcaoivUYUrIJ89YPwVkT5vpblH82YFz4jgnYYsReIrXOB3jdi72mO/NNEZzdgOKwLCZTQLNp0MVBK5sNG7ZER0clBg7MUFQkS9a8/LMhJkXK90LUp8ZJQAwiiG1isxQS1on1cm5BLAc0NuhAxPYlXqR6nPAaeTuxvLw87tPJMEx2qgo34/LhH+Ka5dPxYusEbIiUYHjhBowqXI/+oVZ82zEQs8p/yGtRnqDssHRWNpaJ6lper8c2xax9i80oWe0ZMeL9XqntnIjsNooVdFO+2rak15s5f5Xm7Yr0sHa73VHYsgH9li5IvYGGzHg5jAdkAULcU2MnGL8X28RmKXSvk7ftXpb0OsSW0QbNsf3G3ie+rXobjuNMnqK1/03ZlJf94SNccfte+Gx+DRrWl6Fm8EaMGt6EIQM3Ye7XQ/G7Y7/0tyj/UqCnMK1zdo8Q5mlmuF5xu8EhKxUtn8eugqp6rEhUYr6muJ3umPWK8imQo4U8Cy3jYIJXSbqOmovGYXPBEAxqe8/wLrtlcqWfHIu/saQ9sU3M4iieyAd13FX1v5X+tIj3cbPh7sexeO3H/ndDQwNeeOEFfPbZZ3jkkUcS1q1YsQIPPPAA5s+fjxNOOAEnn3xyfN1rr72Gv/71r1i7di1Gjx6Nyy+/HBMnToz/Zt933314+eWXsXnzZuy888648sor0a9fP93HN2rUKHR22qMXsjCfJ1Rf3oabmprQcN8YjCjfgKJgFOFoEFct3BOHD12ErQasg28xI8qroOlhVJTFVuo0Hqcmv3EX2TVLg/HTbiuZlJ+FLVcMfd+UWW/Wr1Juq1GojgVlNwz8e/f2fMOAYZzwqdVqZYOrJQwDcNNZFWiTCjGsoBkFAQmt0UJc2rgPTus9H8MKN+a1KE9EhMd8mgazFeK3hwV03SzJcm1U9bSZMSReN9kkeFvlGZ9pP03Wv6dc/DXFOdUhZinZ690ZdiZoTPH+WgQmjuMMk5XKUZtx483rsW7paAyvaUZxUQRdkQCuvWs6Dp6xGNttmd6ezleYsNoSVrJ6kqcadKxz0vPcCXH+kizx+LaA2F7YymgR9fUccz75yjckfy4Svc0Vf+0uOayK28lfp91Ndo/H7RtvvBH/+c9/hH1nSUlJD1H+lFNOwR577IH7778fw4ZRr0hm6dKluPbaa3HxxRdjxx13xFNPPYULL7wQ//73v1FcXIznnnsOr7zyith/3759cdNNN4nb7bffrvsYTzvtNBx//PG4++67RfJzMtOmTTP46VmYzysqKytReXX3r++cRx5Bxehfcdjll4tpuPkONQwKI5SGBW+I817Nls8myivbfKoeqTXph+71gQqz1Gv7jHIGe5Zgyl7zDJNTBeTUDHqge/opZYA8cMcdmDixHHue9aoNR+g/qDgq+arqzm5PxopsbDMibpPLojzRKMXFeUuPPdW5TT5XTg+AOPl+NBinWM046RufTLIY41ULCYbxOZSV2W9y9z/YP+bMQUHpchx50hUA2WT5FcqWtwDKmA81a6gNY8Qj22xWvZu/0cnHfKqGuE3C/W2q/ne1hvOnpcC4V86DS+K8sKPROFOGMadVPvbYY1iyZAn+/ve/J6wjIXz77bcXAnwyb7zxBnbYYQccfvjh4jmJ8pRB/+WXX2LKlCniMVmLUaY8cfbZZ+MPf/gD2traUFZWpusYzz33XHH/m9/8psc6SrYyM+jBaqxPkSu9Gw+In376KT7//HNxYeoVBlzPjk++WYRsZRPWJqKqb0aoc0iErnVBlNe6bY3Gz5rroryCpmtJQ8Y8z0ZgGN8I8yETnfL//ve/WL16NX7729/CV1B2fPLNIihjPkQZ800axNZM2yjrcilDXo8or0LTlHitZBLf1SJ9DkMWM4rfO4vhDJNfzJ07Fx9++CHOOeccU/HfcT4J9Lz1t2bXCR7z6bCycKWdRTDtErC1iPLIklVfnWVQoirFc+WGPMqWT3Wt0Ew3kxnzTHZ+//vfY/z48T2WNzc3C90yXX+HsunJYkaBsu1ramqwcuXK+Hqyt1EYM2aMENDr6uoM9d3S3czORGArmzzKtFP49ddfxSjUJZdcgt6xKS15TZ1qKl02j/l6DcvsFJLdzpbXiZZK55ZkeJudheCTzHm52Cs3DBgmF6AGnNE4/uOPP+L555/HDTfcIKZpMjJSRyECjV2ZT4eTwq+WrPl0ArUHkBqiCJz/e+fe0Mhn99D50kJyMdishfb8ZrvAMDmMmf43eR+TB/L5559vyNvYk5A4b8YNtxGIlpHHfNhZEb2HVUlukbH/ncniJh8z4zUg+8Jz/9stlixZIhKSSZy/6qqrxLLDDjtMWMooRegrKioSXkMap1KcPnm9on9qLV5PVjhHHHGEePzEE0+k3Y6OkbzvjcLCvI879EZG2qlYwV133YVDDjkEEyZMsOXYfIVqoCwayDJiX2+tLYnvssP1ZMsrDLkAaPyb9s/t5CCHL+GGAcPkexzfuHGjmNJJmSNDhw615dh8R0ycjY4tTO8xr9rOUazyQncjW16SEPzjRcAcDXHcDXz4fUok6ilWNgoszjNMTgvz4XBYxO2ZM2diq622suXYfEejuv/d6WxmuxaqPDLoqSdbXmHyBcCqv1lTVDbTPvIBKqY7NKgt2TBfoXHGIo3bduofzGtsbERXVxcWLVqE66+/Hj/99JPwi6+ursb++++fNlOdfq/V9wqK60jy8nRQEtTBBx+MwsJCXH311Wm3Y2E+TzHaMKDqxlVVVZg1a5Ytx+UrkmaviIaB2ptWjd6M7mzivN+yu42I8urXxorBZoWF+IzXjlz8lUfsGSZf4zi9hooekZfi7rvvbtux+YYkYTYqir+GvZdZbZU43+icKJ9QoNio37waNz3kvUQg2G1l4xVxPtWxMAxj2YA6ZVlSxiZleTKJvzE0Yz2gToxzSpD3Q9a8EVE+yW/eFnHe6+fNajYGEejjzYKp+UA4HBZZ7jfffDOKioqw5ZZbCpH+5ZdfFsI89aUokSQZ5bea2rHq9crjggJtOepff/11/DHZ4tgFZ8znUcPg/fffx7fffovbbrvNX77ydlCn0WPeDr9uv4nybgv76dAq9ueUOJ/Fyob95Rkmp+P4v//9b2zYsEEUNspr0gi70VABgl1JcdwrIrCXMueN1DMicd5qzIr9PkS2skkTx90S5xmGsW1A/ZNPPhHe8tz/Tj3wR4lxIcqY1ysSN3hYNPaKVVg6v3kzZBL7c9rKhjPm3aKqqkq0RUmUVxgxYoSwtiGogCvNJlazadMm9OrVK+V6Wkck299o4eeff0ZtbW2PWp/kSvLLL7+I4zIKC/N50jCg4gZU5fj//b//Z+gizCnS1HmQPebD9gqceSTKpxq5dFzsrw/klDgvSSTidbh1RAzDuBjHFy5ciFdeeQU33XRTQuM0r8gmsosCXZJ7onw2YdVn4nyCMG8HWsR+tXif7tw5/T2b+R7pfz7T9GkW5xkmZwbUSah58MEHcemll3JdN6QWq6U2qg2TpfirQkOOZML7GS1if46J92JAvTkKcEknVxg1ahRaWlqEhc3w4cPFslWrVmHgwIHi8RZbbIH58+fHt29vb0d9fX28ICytX7x4Mfbee2/xfOnSpaIfRQVi9TJy5EisXr0a/fsnVr/+5ptvsM8++4hCtUZhYT4PGgZ0cZKv/JFHHimqEPuaI5OCwbM6fvizFF6OBgoQrOu0r7ZHHonynqFGyilxPmPxV86WZxjfxXHyK9QCZcnfc889OOOMMzBo0CD4mieT4vjxAXvEVSfFWi9kxvlRmNcq3o/xYBzXcn2lEO8lsrLJlrjA4rwlrFmzBrfffjvmzZsnMucOP/xwnHzyyWLdl19+ifvuuw/Lli0THeyTTjpJeMgyjFUD6kpdt0MPPRTjx4/394mdkvSb9UlAn090uhjZAEQHZanxFttOF1rF+RwV8W1PjjNro+M76H9e4+ARYzkDBgzAjBkzcN111+Gyyy4TA54vvPCCSDgm9ttvP8yZMwdPP/00pkyZIu779u2L7bbbTqwnuxsqvL3tttsKMZ9i/5577omSkhLNx0DbK5Y49JuenCD1/fffC9HeDCzM+7hhoEWYp4vn73//uxgRooIzOQcJ9XcF0ovfWcR4taApVag85u/KEtAuyKVg4606CJaTC+I8FIE+zVQ6FuUZJmd/I2k7EuWpsbnzzjsj5yCh/gBrfqMlqPbzWZY4vksgf7LmDdqjiOKvXojjS7KI85UesizK8l2nLP6aSchyy3fe54NN9Lt50UUXiYFMmjFMGW5/+tOfxHMqvnnOOefgd7/7nSgkRyI9FZIbMmQIJk+e7PahMzmSGEd13WjQ58ADD0TOQUL9SwFTgrxCNFjU3f/Olo19iYP9ObMDpC79jnpiQD2VOF/tocK+OqEB9WCUrWzc5NJLLxUzhk855RRUVlaK+E2CPEGJx1SUlcR3Et3p+R133BH3kKfkZGoD0DaUsEz9qUsuuUTX+0+fPj1uDb7rrrsmOJDQ/xvVDznqqKNMfUYW5nO8YbBkyRJRHIFG7D3xI20HF6jEeS1CfBoxU2QxUbp8NlGe0LJNNvRk+/sQzzQMcoV6QKLiMwVRoNXtg2EYxqk4/tlnn4kpnMcff3zunvRXrRHnA+1S9/6ykU2414Jd4r6VmBAW4sVfGevE+XTFXxlLIR9YymC7++67UV1dLXxfKePuww8/FPae48aNi2fPk1/s22+/jY8++oiFecaSAfXly5eLAR+6/jwxuGkHB2cQ5zMJ0g0pZqxTxrwmixQL4nZOZXJ7eEBdTfKsBJ+J9HLSRzRnZ1h4jVmzZombGhLCSZhPxwEHHCBuqaD/h3PPPVfcjEKiPkED/ZS1T773VsPCvI8bBlqmwFPDlBqfVPSA0ZBdbIXgrifb3w1x3o5CrF4X5v2eNa9qGAQCPGLPMLkizGvpPJGItPXWW8czP5g0NMU6T1pEeasgcd8NcZ4yyPMtjvs1az5JnJeCVPxVx/fHtjaGILH9vffeixd/I2gglLLlpk6dKjLe1BQXF/NvLGOZBR3FbcrazLu6bjoE+W4CCFwSzU2bFXXW/KnOxG1PDajTuX4ky7FU+0CgD4QS6xcxecuKFSvwzjvviILeZFemQG0L8pe///77De/bY8NpjNWZdr/++isGDx6c+yeWsuYzCfHqm5Yp8F6lLklspls2ap0X5T05Yq/lXHkdic4nZ9oxTD5Z0lEcJ4uFnMeMoK4IssecB999ZvXnbtLQyXdIlPecMA9nP7ttUBG5aMTto8h56LdVLcpT4bfXXntNZOGR3zfZ2Sg0NDTgiy++wF577eXS0TK5ljGfN3GbsuYRE58NifI+6X8nf2blc2uhyjlR3pNxW+tnr/Z4YpwWCzom57n11ltFO+KVV14RVnivvvoq3nzzTbG8o6PD1L49pJoxeuCGQRpxPlmE1+G9HdjjfPeL2RoRmbUKzg6K8p4bsc8RJATTF39lGCZnhfm8GGAnSKQmcTrTLRm3s6SNWuKoBXmtgxJW2O/4sVaMFty+DjQeH9kmwu3CfF6mT2x2gZYbbZsFymzbbbfdhBXYtGnT4j6x6mucpqhTFv2WW25p3+di8ioxjooT5oUwT2QSqRuyZ0IHJrvQ/9Zim5Pts2oV5/WI+LkozOuh2qsCfczKhsl77rvvPjz33HPC+q60tFQUmqXHmWx2tMLzon0KNwwMWNFkKth6lwTphx/gCnotbYxkfjssyvu+YeB1jzuGYXyPFisb+h2lDn7eCPOZxGeyjKnMIMbS69yK49lsVqyYHeCwKE9wHLfBbikY1Gdl40bx1xyCLGueeuopLF26FLfddpvoUB9xxBHx9VRYe9WqVbjllltcPU4mtyzoaEB95syZyBsyZUVnso25xMX+t15LGyMCu8OifM7E7WpvWdtIZGXDGfMMgPXr12PixIniXPTr10/MuNtiiy1w9NFHY9KkSXjooYcMnycW5nO4YUDbrFmzBoMGDXLsuDxNFv94V4OYWb95D3qo50TDwGtI5HHHwjzD5AJa7L6oAUi/o9T4y3uyCNO+jzkk1nusmKwnz2lyMVVlmV/YHAS8ZGXTmNsDAFRjiwq/0q2+vh4vvPBCXJh/6aWXxO3RRx9NsL1hGDMz3WibvJrpZjI73dUYo8UD3WgBXJfwnJVsDojzwsqGPeYZQMy8u/3223HnnXcKIf5vf/ubmG1HbYvevXubOkcszOdww2DdunUoLy/Pv8IzfsWorU2mTHoS613yVmcrG48Vf1XXJ0hXg4BhGE+hZMt7Thz1IK6LyFb4n6cafCCx3oVseU9b2ShCfLJA7wNExnyTBGSvH5maSgsHJDJ5QvscKsxGnednnnkm/rtA1zIVeSXmz58vMujvuOMOjBw50uWjZXJpxnpTU5PYpk8fDV5LjPuY9X9PlRVPYr0L2fI51//2iDgvW9BxYhwD3H333WI21EknnSQ85mfMmCEEeWpbzJkzx9QpYmHep2jpLOWVvx3juYKnOTNi7zGPeUNWNulEeYZhPA1n3eWAiGwWl0R5Twx2ZKPJxSx9gwMFUpCKv0az7zNVFntliudWnYPG3MqaHzt2rJhxdNddd+Goo44SM4j/9a9/4ZhjjhGZ8xdffDFOOOEEjBkzRkxFV6iu9qTBMeOjOKMUfvX0bydjLy6J8r6I274U54M8Y50RUPH45cuXx5Okly1bhkWLFqG2ttZ0+4GFeR+T7UeXMuXXrl2Lrq4uFBTwV50tiDHWknMNAy8g2dAwINGes+YZxpNQHKdOPv+e5rEw7yJ83anQIqRrQZ15Z9U+jZDD2fIEZSvfe++9Irtt9uzZIqPtoIMOwrHHHouHH34Yzc3Nwgs22Q923rx5rh0zkxu/iRS3abCns7MTRUVFjh0bw+RsYpzL4rwUCLDHPBOHYoAyc4oy5bfffntYQY791zJqKAuERm6oUjCTGe58Wk9ONgz8bGXDMIzv2GmnndDS0oIFCxa4fSieh4X5PGgbVbl0LJXWCeiai79qzV73oZ2PU0yYMAF///vf8cEHH+CVV17B6aefLjrTdE8CfKobw2Qj228iWSPV1NSI647JDCfGWU9OWdmocXUyk8EZ60xOMmfOHOy3336iCGxdXR06OjrELDwa8DcDq2Y5HMjoR5myQ/7zn/+IH2kmPdyhz4MOfQ4gSfST7aGicQzD2BrHSUQ68MAD8fLLL/OZzgLHcevhc2o9Qpj3Qps8WfjPIRsbhnFbSOb+t/bzyX1Fa+Fzao/HfIBmurHTWd5z00034aqrrhLC/MqVKxEOh4UzCT0+99xzTZ0fFuZ9itYgRtWCycrm66+/tv2Y/Ax3Pu05p9zYspogAgGdHXr2l2cYX3ec9txzT+FnSI0+Jj0cx62HO/g6adJoZeMFYZ5gMZ5hdKE1bm+33XZCrKEixEx6OG5bT07H7Wr3arwFwDPWGQj7uyeffBIXXHBB3M6G7qkQ7EsvvWTqFLEwn+OQlQiN2pu9UHIdbhhYT043DFyCGwYMk38xp6SkRGRmcNa8deeU0QbHcZsz5is9Is6zQM8wlkL9n4MPPlj0v9muJT0ct60n589ptYb1qW5moAH1vjxjnQGamppQVdWz0UTF5s3+1ufwfy2jMHXqVFE87scff+STkgbO7rYe7tDbcVJpoMMjmXYMwzjWcdp///3x5ZdfioLujDXnlMkOt41sgBIWlOKvXobFeoYxxZQpU4RY8/333/OZTAPHbevJy/63FgHehEgvaryZOT4mZzjiiCOEnzwJ9AT9ry1evBhnnXUWZs2aZWrf3IPJg44SVYQ/4IADRKECKkSzZMkSUUyOSTyn3KG3/jrlc2pDxrye4q9sY8MwniQSicSnQGqhd+/emDZtGh5++GF8/PHHwtqmra3N1mP0GxxzrIeLuNtwTrUWf2UYxlPozYYkK5vf/OY3wvaA+t+UIMf970Q4bltPXgnzRrPhdYr0UgVZ2XDGPAPce++94rd94MCBoh+24447iiKwQ4cOFevMUMAnOD+CGE2Db21txaeffiqy59esWYOysjIMHjwYgwYNwpAhQ7D77rtjwIAByEe485kHDYN6Dx2LKSsbjZl2LMozTE7F8cMPPxz//ve/RQf/l19+wbp169CrVy8RvymOUzzfa6+9hIifj3gu5uQAfE41otOSxlJhXouvPcMwrsTtfffdFxs3bsRnn30m+t+rV69GaWmpiNfKbbfddhMxPB9hYd568kLTIEG9wcJ9IcX+EkR7Op88oM5A6Kcvvvgili1bFq/hOWHCBCHOm4WF+TzItCOoETB79uyEfTQ0NIhGwhdffIFnnnkGI0eOzFthnhsG1sMdejtOKjUMNAjzLMozTM7F8b59++Lkk0+OP6fC7mRtQ3H8/fffx7/+9S9su+22eSvMUxzXe06ZzHAcz2Ma3T4AhvF/X7G4uBjHHXdcwj6o/02D62RPR/3vYcOGsTDPWHqdFhYW5v4ZrXZuf1zjjVEgC5u77roL33zzjUh6Tubdd9+FUViYz1MRmTqvNAUjHA6LivG/+93vsP322yNfYWHennPK2YsuWNmwKM8weRFzaColZctTNt53332HCy64QAyw5yt50xl1kLzIvPMznC3PMJ4eUE+Gfk8pCY72RYlxp556KiZPnox8hfvfeTCg/oiHjsVUbRi2smEgBlrJTvSwww4Tic9WwsJ8njYMCMqyu/7668X0+H322Qf5DDcMrIc79HacUyo+E7FelKfX1Ro9KoZh3IrjS5cuxW233YYzzzwTkyZNyusvguO4PefUUx18rWK1TmsZXxZebdKZ7c7FXBnGEzGGZrpdd911olAgFXbPZzhu54EwnwNwxjyj8NFHH+GTTz7BNttsA6vhNJg8DWLcKLD+nDKJcMPADjJ43HGmPMPkVcyhjI2bb74Zp512GnbeeWfkOxzHrcd3cbzJR5nkRgcPmjJ8vsYMFjRsTcMwrg+ok43NtddeK2q/HXjggXn/jfguxvgAXw6o51KNNyanGTVqFDo7O23ZN2fM52HDoLGxkRsFSfAUeOvhxpZdVjZJDQMW5BnGl3GcvGeNUldXhxtvvBEnnXQSpkyZYumx+RUW5vM8jjf5I3NeMnM+nRpwYBGfYSyvY7JhwwbR/54+fToOOeQQPsNcG8YWeMa6HZCVDQvz+coHH3wQf3zUUUeJup3/93//h/Ly8h7bTps2zfD7sDCfh51PqgxPPrTcKLDunDI94XNqAxJ16KP2CPJsZ8MwjgrzZmLOe++9h6lTp5pqAOYaHHPyuIOfTrD2oDgfkLLUiWHLGYbJybhNnvJDhw7FEUccYelx+RlOjMvzAXWfIAVCCKSbsc7kPNOnT++x7De/+U2PZfR/R3HCKCzM+xD6ws0UOKMf7N69e1t6TH6HO/TWww0DG4u/cpY8w+R15h29vlevXpYek9/hOG7POfV8Bz9bFrkHxXlbjidblns6wZ+z4xnGkRijxG3P/6Y6CMdt6+H+tw3nFFTjjTPm8/l3ygl8kAbDWB3E6Aeb6XlOuaFkLdwwsEmYr9MYHOoNvAEL/gzjq+KvTDfcwbeHnGgbNaW4edHKxq5seatFeT94+DOMxXDcth6O23k8081X0PlkYZ6xF86Y9yHcMLAniLFIYv055YaBxWwMAEVR7SI8La8xIc7X6nwtwzCOdUZzQjC1EB4MzgOsFIRdyqQPFEv+FOVZjGfyHI7b3jynTM9zyu1Da5ECQQTYY56xGRbmfQhnzNtzTjmI5bhIUmPBTJF6Fz9PTDB39JQqIj0L9AxjKdwZtR4+p9bjuRmWVhyPl9olVonyekV2FuUZxvHEOM/9nnoAjtt50P8+1YLr/hEvfB7OmGfshYco8zRj3lM/2B6AGwb2nNOcu86sEPetxohlDcMwrsIdfHvIuZjjMjl5PhVxzA3f+coUVjZOivK0LYvyDONKbRgm9TnljPkcF+a9Iu6bQAIXf2Xsh4V5H8INA3vOKTcMrCUnGwZeFefTodfGJhWcLc8wlpOzv48uwtmIjI6LxfmTFRsICFj53o02CvIMw/QYUOcab9bC/W/ryVkrWZfF+QB81P9nfAlb2eRhw4BgQSARbhhYT04LTyTOO2lr41ZRVhblGcaT5PTvK8PkCnZm5esR5RmGMQ17zFsPt2WsJydnrKvFeU/Y2jAJ9AFQpvGctAFYx+cvFTk4nJb7mA1inFWWmpwNYi7B59N6JASczZZnGIbxCRxzGF00Sq6I8j2sbIzglNjOBV8ZxlIrWSYRToyzB24Pudj/ZhiDsDDvU/gHl2HyxNKmzsA0OrawsZQff/wRN954I2699dYe6/7973/j0EMPxR577IHf//73WLlypbVvzuQkVsRwbgcwjMfF+RSYsrJhSxqGcRWzcZfjNp8Txn+WNmxjwzgBW9nkIdQooBFqphueRcB4Qpx30h6HycqmTZtw/vnn47vvvkN5eTmmTZuWsP7999/HnXfeiWuvvRajR4/GY489hksuuQT/+Mc/OKuKsTXmcBxnnCAv2kZWi/NjOI4zDJMa7n/nYYxh/CHOs0UO4zIszOchlZWVWLhwoduHwTCMFqFflf0u/fADMO6vfN4corOzE5MmTRLZ8n/5y196rH/jjTew//77Y6+99hLPzz77bOy7776or6/H8OHD+XtibI3ja9as4TPM2ApndxpgSRbB4McfgVs4jjNMPsbtL7/80u3DYBhGp9jP/W/GCfJOmN+4cSP8TltbG9avX2/49b1790ZLS4upfeQaZs8pw+fUCTZv3pxT16nXf4+rqqpw5plnpl1/5ZVXJhTiVrxH29vbHTm+fMXr142WDDGz/8vUwf/hhx9y6vfALBzH+Zz6gVy7Tv3+e8w4Qy5cJ2b/d3v16sX9b4vPKdMTPqfWw/1vxgnyRpgvLi4WoskXX3yBXGDJkiWmXr/ddtvh7bfftux4coGlS5e6fQg5h9nrlMn9c0q/y/T77EdKS0vjj0mMf+CBBzBu3DiMHTvW1ePKVTiOJzJy5EiO4zn+++gF+JzyOc3lOM7YC8ftRGgWJve/E+H+t/Vw3OZzmg2O294jb4T5srIyYTnQ0dHh9qEwDMMwqk4b/T5bwkAAFRq3bQGw1pq3Pf7440WBWBLqH374YbZ/sAmO4wzDMDkex/vQj73GbdsArLbmbRl74LjNMAyT43GbsYS8EeYJuvj4AmQYhmHScc455+Crr74Sj0855RSceuqpWU/WHXfcgQ0bNuCf//wnLrzwQjzzzDMoKSnhk2wDHMcZhmEYxj9w3GYYhmGYzOSVMM8wDMMwmbjiiiviM6uoHocWBg0aJG702j333BOfffYZpk+fzieaYRiGYRiGYRiGYZi0sDDPMAzDMDEGDBig+Vycf/75mDp1Kg477DDxnArB0o29dhmGYRiGYRiGYRiGyQYL8wzDMAxjgC233FJ4ytfW1oqM+eeee05M2d566635fDIMwzAMwzAMwzAMkxEW5hmGYRjGACeffDLC4TCuueYabNq0CRMnTsS9996LigqtFWgZhmEYhmEYhmEYhslXWJhnGIZhmCyQ+N4jgBYU4Pe//724MQzDMAzDMAzDMAzD6IGFeY/Q1NSEF198EStXrkSvXr0wc+bMuB0CLf/++++x7777YvLkyXjvvffwzTff4Lzzzou//uOPP8a7776LK6+8Mr5s7ty5eP311xOW5Rvt7e146aWXsHjxYhQVFWGXXXYRxRkJPq/6eOutt/DOO++kXHf55ZeL64+vU+O0tbXh7bffxsKFCzF48GCRjc3XKcP4B47j1sMx3Fo4jtsLx3GG8Rcct+2BY7d1cNy2F47bjFdgYd4DRKNRPPbYY+jfvz/++Mc/YsWKFfjnP/8pPIs3btyIX3/9FccffzyeeOIJbLfddhg2bJj4ke7s7BRiM7F8+XK0trZizZo1GDhwoFhWX18vvI/zmVdeeUWcv9/97nfYsGGDOK/9+vUTgx98XvUxbdo0MbCh5ttvv8UXX3yBhoYGPp8mIDuUBx98UGRgH3nkkUKYJ5YtW8bnlWF8AMdxe+AYbi0cx+2D4zjD+AuO2/bBsds6OG7bB8dtxksE3T4ABqirqxPC5mGHHSZEdRI/x48fj08++QQdHR3o3bu3WB4KhRCJRFBTUwNJkvDLL7+I00ePScyvqqoSAr3CqlWrhIifz1CmPGXIDxkyRPg/08DGokWL+LwaoLi4WAxoqG/fffcddtppJz6fJqH/9ZaWFpx22mkYPXo0ysvLxXL+/2cYf8Bx3B44hlsLx3H74DjOMP6C47Z9cOy2Do7b9sFxm/ESLMx7gPXr1wshThHjiBEjRohM2bFjx6K5uVn4G2+55ZYoKSkRP9ADBgwQDQqCtiPBftKkSXFhnp6vXr0674V5GgmlLGSFwsJCsYzPq3lodgbNyth+++35fJrk66+/xu677y7+t9Xwdcow/oDjuD1wDLcXjuPWwXGcYfwFx2374NhtHxy3rYPjNuMl2MrGA5SVlQl/K7U1DYnJmzZtEvdnnXWWsKmpqKiIv4Yy4UkUVewutthiC5FpS17zarE+361saDDj008/FeeGzidZr/zmN7/h82oBn332maiDQNcvwdepMej/lBpZ9Btw3333icx5EuRnzZolfg/4vDKM9+E4bg8cw+2F47g1cBxnGP/Bcds+OHbbB8dta+C4zXgNzpj3AJQdT5nwb775Jrq6uoQFDRV4DQblrycQCCSI8gQJ7mphnoTnoUOHihHqtWvXin1QVn1yBm6+ceCBB2LdunVixsEdd9whBjTIzobg82ocGkSaP3++sLFR4PNpDBLkyeeSCufuv//+OOqoo8TMF/Jn5PPKMP6A47g9cAy3D47j1sFxnGH8B8dt++DYbQ8ct62D4zbjNViY9wCUFXv00Ufjq6++wpVXXomnn34aY8aMiWcip4IE5sbGRpFJv3LlSiHMk5A/cuRIIeqRaJ/v/vLE888/L/z5Kev45JNPFueFMujTwedVG3StUu0Dut4ywedT24g9QUVf6f9+1KhRmDlzphj4IMGezyvDeB+O4/bAMdw+OI5bB8dxhvEfHLftg2O3PXDctg6O24zXYCsbj0DWFf/v//0/YWNBRTVffvllISinQ8mGnzt3rvBNV7YlSxsS5km0pyKy+Qxlyi9cuBCXX345+vTpI5bNmDEDb7zxBnbdddeUr+Hzqo0vvvgiIVs+HXw+s0OzYWi2Af0fq88bzZ6h0fzk2TJ8XhnGm3ActxaO4fbCcdw6OI4zjD/huG09HLvtg+O2dXDcZrwGZ8x7iFAoJARkmqa0YMEC4c+WDsqOJ+sayqqlDFsFekxZ4RQU8z1jXhkJVRd/pewIEjzTwec1Oz///LMoLLzDDjtk3ZbPZ3bo+qyurhbnVaGpqUksTzdrhs8rw3gTjuPWwTHcPjiOWwvHcYbxLxy3rYVjtz1w3LYWjtuM12Bh3kOQGEcZ3g888ACGDBmCcePGZdyehHfykycbG4XBgweLLFvKwO3fvz/yGfr8VVVVYvYBDVRQQHvnnXcwceLEjK/j85qZzz//HFtttRXKy8s1fQ98PrMzdepUvPXWW1iyZIkYWHv99dex4447xutM8HllGH/Acdw6OIbbB8dx6+E4zjD+hOO2tXDstgeO29bDcZvxEmxl4yHuueceMa1m2223xZ577pl1eyoAS6iFeRLyyM6Gsu4ziXr5kgFBvvJURPP+++8XI6M0C+GAAw7I+Do+r+mhQZ9vv/0WJ510kubvgc9ndsgWaOPGjfjnP/8pnvN1yjD+hOO4dXAMtweO4/bAcZxh/AnHbWvh2G09HLftgeM24yUCkiRJbh8EwzAMwxhl/fr1ePvtt7HP1peiX8UKba9pGYm3v7sV++yzD/r168cnn2EYhmHcjuPjLkW/Mo1xvG0k3v6B4zjDMAzDuBa3R+uM20s5bqciv1OqGYZhGIZhGIZhGIZhGIZhGMZhWJhnGIZhGIZhGIZhGIZhGIZhGAdhYZ5hGIZhGIZhGIZhGIZhGIZhHISFeYZhGIZhGIZhGIZhGIZhGMZxGhoa8Pe//x2nnnpqwvIvv/wSJ598MqZOnYrDDjsML730UsL61157DQcffDB23XVXnHDCCVi0aFF8HZVUvffee0Vdud122w0XXHCB8Mf3GizMMwzDMAzDMAzDMAzDMAzDMI5y44034sADD8Szzz6LdevWxZfX19fjnHPOwfTp0/H000/jxBNPFNvOnTtXrF+6dCmuvfZasfwf//gHxo8fjwsvvBAdHR1i/XPPPYdXXnlFvOaRRx5BY2MjbrrpJs99uyzMMwzDMAzDMAzDMAzDMAzDMI5SWVmJxx57TIjwydnw48aNExnztbW1OOSQQ7DTTjvho48+EuvfeOMN7LDDDjj88MMxYsQIIcpv2rRJZNkrrz/qqKOw8847i/2cffbZ+OCDD9DW1uapb5iFeYZhGIZhGIZhGIZhGIZhGMZRfv/734ts92TIvobsZ9QUFxejoKBAPF6xYgVGjRoVX1dSUoKamhqsXLkyvn706NHx9WPGjEEkEkFdXR28BAvzDMMwDMMwDMMwTM7w66+/isy5vfbaCzNnzsRdd92Fzs7OeEf9jDPOwLRp00Qm3Ycffuj24TIMwzAMkwSJ9VtttVWCD/0XX3whYjvR2tqKioqKhNf07t1bLE+1ntYpy70EC/MMwzAMwzAMwzBMTtDV1YVzzz0XRUVFePjhh3HdddeJ6e6PPvqoWHfRRRehuroac+bMwQEHHIBLL71U+NgyDMMwDKODfgCqNd5oWxNEo1FcffXVIot+yy23FMso+z3dtup7hUAgkHK527AwzzAMwzAMwzAMw+QE3377LX7++WdcddVVGDlyJCZPnoxjjjlGZMbT9PWffvoJ559/PoYPHy58awcNGoTPPvvM7cNmGIZhGCYN99xzD1atWoXLL788viwYDEKSpB7bhkKhuBCvXq88VqxwvIK3joZhGIZhGIZhGIZhDDJkyBDccccdKC0t7eFJ29HREfehVaDHynKGYRiGYbzFSy+9JG40861Xr17x5WVlZdi4cWPCtlT8VdkmeT2tI5Ltb9yGM+YZhmEYhmEYhmGYnIAy4Hfffff4c5qy/tprrwlPWir8RoXhHn/8cWFrQ1n0lEG/xx57uHrMDMMwDMP0ZP78+bjttttw8803i1lwarbYYgssXrw4/ry9vV1Y0ykFYZPXL126VNjcUTvAS3DGPMMwDMMwDMMwDOMuVJNNrstmaS/2kUceERlzVOiVpreT5/zvfvc7Ic6TaE+e817rpDMMwzBMvlNfX4+LL74YJ5xwghhYp+KvClQrZr/99hP1Yp5++mlMmTJF3Pft2xfbbbed2Gb//ffHX//6V2y77bYYOHAg7rvvPuy5554Js+a8AAvzDMMwDMMwDMMwTM7x/vvvi6nvDz74oOiIt7S04Morr8Ts2bNFh37hwoW49957Rad9woQJbh8uwzAMwzAxXn31VTQ3N+Ohhx4SNzXz5s0TYj0VhCXxnUR3ek5WdoqH/JFHHonVq1eLbSibnsT7Sy65BF6DhXmGYRiGYRiGYRgmp1iyZIkQ4a+44gpMnDhRLHvz/7d3byFWVX8cwH+VXe2uZfRPsaIGekkdgy52FbLJzIcwsjTKBy89jE3hk9pNI8rwoQjTsEQwSBGiLMmHLhQ9FJbMqIUFjhqJ5CXMoEbLP2v9O+c/k6Np5Toe/Xxgc+bstfeZzTkP6+zvWeu3VqzIi8U1Nzfn5w0NDdHW1haLFi2KmTNn1viKAeDYNWLEiLxVjB8/Pm8Hcvvtt+etO6m/nzx5ct6OZGrMAwAAcNTYtm1btLS0xOjRo6Opqam6v6OjI0488cQux6aR9Gk/AEBpgnkAAACOCilkTzVp+/Xrl6exp5q0le3qq6/ONWsXLlyYH1OpmzRV3uKvAEAtKGUDAADAUSGVpmltba0u/NZZqkM7a9asmDNnTsybNy969eqVp8kPHz68RlcLABzLBPMAAAAcFRobG/OicAdy3XXXFbseAID9UcoGAAAAAAAKEswDAAAAAEBBgnkAAAAAAChIMA8AAAAAAAUJ5gEAAAAAoCDBPAAAAAAAFCSYBwAAAACAggTzAAAAAABQkGAeAAAAAAAK6lHynwHAYdMnIs45yGN3RESbzwIAAACoDSPmAQAAAACgIME8AAAAAAAUJJgHAAAAAICCBPMAAAAAAFCQYB4AAAAAAAoSzAMAAAAAQEGCeQAAAAAAKEgwDwAAAAAABQnmAQAAAACgIME8AAAAAAAUJJgHAAAAAICCBPMAAAAAAFCQYB4AAAAAAArqUfKfAQAAAABQx86KiHMO8ljDwvfLWwMAAAAAAAUZMQ8AAED9jLw77jBfCwBAAUbMAwAAAABAQYJ5AAAAAAAoSDAPAAAAAAAFCeYBAAAAAKAgwTwAAAAAABQkmAcAAAAAgIIE8wAAAAAAUJBgHgAAAAAAChLMAwAAAABAQYJ5AAAAAAAoSDAPAAAAAAAFCeYBAAAAAKAgwTwAAAAAABQkmAcAAAAAgIIE8wAAAAAAUJBgHgAAAAAAChLMAwAAAABAQYJ5AAAAAAAoSDAPAAAAAAAFCeYBAAAAAKAgwTwAAAAAABQkmAcAAAAAgIIE8wAAAAAAUJBgHgAAAAAAChLMAwAAAABAQYJ5ADiAdevWxdNPPx3PPvvsPm3Tp0+PwYMHd9kWLFjg/QSAGtq8eXM8+uijccstt0RTU1PMnj07Ojo69jlu/PjxMWLEiJpcIwDwP7t27YrHHnss99vDhw+PV1999Y+WiK+//jruv//+uOaaa+LOO++MZcuWRWfLly+PkSNH5vaxY8fG2rVro570qPUFAMCR6KeffoqWlpZoa2uLnj17xg033LDPMdu2bYtJkyblLwIV6VgAoDb27NkTkydPjksvvTTmz58fW7dujWnTpuX+ecKECdXj3n333fjyyy/jggsu8FEBQA3Nnj07D4ibM2dObNmyJaZOnRoXXnhhDB06NP/QPmTIkHjqqafi888/jxkzZsTll1+et2+//TaefPLJmDJlSjQ2NsaiRYvy8W+++WacfPLJdfGZGjEPAN1II+vSCPi33nqr21A+2b59e1x00UXRu3fv6nbqqad6PwGgRlpbW2Pjxo155N3FF18cV111Vdxzzz3x8ccfdxmZ98ILL+TR9ABAbX3yySfx4IMPRkNDQ773vu222+Kjjz6KlStXxs6dO+ORRx6J/v37x6hRo+LKK6+M9957L5+XHgcNGhR33XVXbk+hfBpgl86rF4J5AOhGr169YuLEidGnT5/9vj8pmE/HAQBHhjTC7vnnn+/yQ3kaNdejx/8ni8+dOzcGDhyYQ3sAoLZ+/fXXLiPcTznllLxv/fr10bdv3y5tl112WbS3t+e/U3uaIdf5vDRwrtJeDwTzAPA3/Pbbb/Hjjz/mm/thw4bF6NGj87R4AKB2UmmaNOW94vfff8/1Z1Pd2iRNe3/77bfj4YcfruFVAgAVN998cyxevDh+/vnn2LRpU6xYsSJuvfXW/Pz000+Pzs4888y8P/mr9nqgxjwAR4WdO/9zWI7dn927d+cb/2uvvTZPp/v000/j8ccfzyP1BgwY8I9fHwCOJYerH08LyKVp8HfffXd+nhZzf+CBBw44Iw4A+Pf64r86tqWlJe69994c0Kcf1NNjKmeTBsF1Jx1TGSx3oPZ6IJgHoK6laW0nnHBCfPZZ8yGdl87584Iwzc3NeSG4JNW4Gzdu3H7PT9Pk0iI1nafUrVq1Kt555x3BPADUoB//s1Sf9rXXXotXXnkl99vLli3LC7ffd999Ph8AOEL67ZkzZ8Yll1wSzz33XOzYsSOeeeaZWLJkSRx//PGxd+/efY6vlKfbX3v6X/VCMA9AXTvttNPyr+mpBt2hSF8K0rmdTZs2rfo6aQrcoUpfJr755ptDPg8AjlX/Zj/eWeqPp0+fnvv2K664Iu9bsGBBfP/999WyNmmkXZoBd/311+fFYFPdeQCgXL+9YcOG+OCDD3JZ2PPPPz/vmzRpUrz00ksxZsyYPOuts7S4a6V8TXq97trPOOOMuvkIBfMA1L3UIR/o5vxgVb4IHIwPP/wwT49fuHBhdV+qh3feeef94+sAgGPJv9WPV6RR8WlafFr/pampqbr/xRdfjD179lSfv//++/HGG2/kqfL6bwAo32/v3r07P5500knVfWmWW0dHRx74lu6xd+3aVQ3j01oxlR/SU/sXX3xRPe+XX36J7777rsuCsEc6i78CwN+Q6sinUXfpZj51/mkhuTRlvnMAAACUlW7kp0yZEv369YtRo0bF1q1bq1vv3r2jb9++1e3cc8/N093T3ykEAADK6t+/f+6HUxmb9vb2WL16dcyfPz9uvPHGaGxsjLPPPjtmzZqV25YuXZrLx6aFYZNhw4bFmjVr4vXXX8/tqdRsOr6e1nw7bm93xXgAgKonnniiy2NF+tKQOv9169blReRSXfo77rjDOwcANbJy5cqYMGFCt20vv/xyDB48uPo8/ag+b968/AgA1Eb7H6F6a2trLnlz00035fXfevbsGV999VWuOZ9K1KXZbQ899FAupVORSuCk/v2HH37I675NnTo1Ghoa6uajFMwDAAAAAEBBStkAAAAAAEBBgnkAAAAAAChIMA8AAAAAAAUJ5gEAAAAAoCDBPAAAAAAAFCSYBwAAAACAggTzAAAAAABQkGAeAAAAAAAKEswDAAAAAEBBgnkAAAAAAChIMA8AAAAAAAUJ5gEAAAAAIMr5L0k1kfhAwAKQAAAAAElFTkSuQmCC", - "text/plain": [ - "
" - ] - }, - "jetTransient": { - "display_id": null - }, - "metadata": {}, - "output_type": "display_data" - } - ], "source": [ "# Define domain (Spain north coast)\n", "domain = [-9.6, -5.4, 41.6, 44.0]\n", "\n", - "# Create figure: 1 row (2 indices) × 2 scenarios (historical + ssp585)\n", + "# Create figure: 1 row (2 indices) \u00d7 2 scenarios (historical + ssp585)\n", "figure = ekp.Figure(\n", " crs=ccrs.NearsidePerspective(central_longitude=-5, central_latitude=43), rows=1, columns=3, size=(15, 6)\n", ")\n", @@ -897,7 +887,23 @@ " map_plot.legend(location=\"right\")\n", "\n", "figure.show()" - ] + ], + "outputs": [ + { + "data": { + "text/plain": [ + "
" + ], + "image/png": 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H2rVrMX78eABAVFQUPD09sXr1amEbQ8MPK9XNoWyIiIiIiIiIiIiIPhK2trb45ZdfMHbs2GzXO3HiBDp06IC2bduiYsWKmDhxIh4/foyXL18iJSUF58+fx9ixY+Hp6YnatWuje/fuuHjxYq7KsmHDBgwfPlzjsb/88kvUqFEDtWrVwtChQ/H3338Lr0dGRsLBwQH29vbCo3Tp0rk6dlFjYp6IiIiIiIiIiIjoIzFy5EhUrVo1x/WeP38OT09P4bmLiwvMzc3x8uVLmJiY4Ny5c6hRo4bwuqGhIZKTk4XnUVFR+O6779C8eXN0794dBw8e1Kl8CQkJCA8PVzl2pUqVEBkZifj4eGHftra2Ou2vuPqw+vcTERERERERERERUYFLTEyEhYWFyjJLS0skJCRAJBLBzMxMWB4SEoL9+/fj888/BwBIJBJ888038PT0xM6dOxEUFIRp06bB1dUV9erVy/a4CQkJAKBybEtLS6FMlpaWiIqKwsOHD9G9e3ekpqaiSZMmGD9+PEqVKpUv770wMDFPREREREREREREVJyVB2CQi/Wd9T+kVCrNskwkEkEmkwnPHzx4gBEjRiAlJQUNGjRAr169AAC3bt1CaGgotm3bBkNDQ1SoUAEdO3bE8ePHIRKJhGF00tPTIZVK4evrCwAYPHgw/Pz8NB5XuUyVKlWCgYEBPvvsM0RHR2P+/PlYsmQJpk2bpv8bLyRMzBMRERERERERERGRCrFYnCU5L5PJYGDw/gpBpUqVsGfPHgQHB2Px4sVYt24dRo8ejadPnyI+Ph6tWrUS1k1PT4ePjw+qVauGPXv2AAB+/fVX3L9/H3PmzAEAWFlZCcPhKB9bcTFAcey+ffuqlGvcuHGYNm0apkyZArH4wxi9nYl5IiIiIiIiIiIiIlJhZmYmjOmuEB8fLwwrAwDGxsZwdXWFq6srEhISsGDBAowePRoA4ObmhiVLlqhsb2JiAlNTU5QvXx6APBFvYmIiPAfe945XPrbid/WhdRQ8PDyQlpaGmJiYD2bs+Q/j8gERERERERERERERFRp3d3c8evRIeP769WskJibCw8MDQUFB+OSTTxAbGyu8bmBgACMjI2Hb0NBQWFpaonz58ihfvjwcHBxgb2+f43GtrKxgZ2encuyAgAA4OjrC3NwcUqkUXbt2xf3794XXg4ODYWRkhNKlS+fDOy8cTMwTERERERFR9qwB2Or4sC6iMhIREZHe0tLShN/9/f1x5swZHD9+HM+fP8fixYtRq1YtuLi4wNnZGWKxGPPnz8fLly9x//59bN26FW3atAEANG7cGOXKlcPUqVPx5MkTPH36FGPGjMHvv/+uUzn8/f2xdetW3LlzB//99x+2bNkCf39/APIhdnx8fLBkyRI8efIEDx48wOrVq+Hn5/fBDGMDcCgbIiIiIiIiIiIioo/emzdv0K9fP+zatQuOjo7w9fXFqFGjsGLFCsTFxaF27drCWPCGhoZYsWIFli5dikGDBsHU1BRt27bF119/DUDee37p0qVYuHAhhgwZAlNTU/j7++PTTz9VOeaIESM0luWrr75CbGwsvvnmGwBAmzZtMGzYMOH1CRMmYNmyZRg9ejREIhF8fX0xfvz4gjgtBYaJeSIiIiIiIiIiIqKPTJcuXdClSxfhuaOjI06dOqWyTv/+/dG/f3+N25cvXx7Lli3Tun9nZ2csX748T2UzNTXFTz/9hJ9++knj6+bm5pg2bRqmTZuWp/0XBx9O334iIiIiIiIiIiIiohKAiXkiIiIiIiIiIiIiokLExDwRERERERERERERUSFiYp6IiIiIiIiIiIiIqBAxMU9EREREREREREREVIiYmCciIiIiIiIiIiIiKkRMzBMRERERERERERERFSIm5omIiIiIiIiIiIiIChET80REREREREREREREhYiJeSIiIiIiIiIiIiKiQsTEPBERERERERERERFRIWJinohylJiYiMjIyKIuRqEJCgoq6iIQERHlKDIyEomJiUVdjELD+ExERMXFxxSTwsPDkZycXNTFICqRmJgnomxFR0dj4MCBuHHjRlEXpdB88803+OOPP4q6GERERFoFBQWhb9++CAgIKOqiFIqkpCQMHToU586dK+qiEBHRR+7XX3/FuHHjiroYheb69esYOHAgYmNji7ooRCWOYVEXgIq3GTNm4MiRIwAAkUgEOzs71K5dGwMGDED16tWF9YYPH45//vkn23399NNP6NKlC7p06YKwsDBhuaWlJcqXL49evXqhY8eOEIlE2e7n8OHD2LdvH168eAGxWIyaNWti2LBhqF27trBOly5d4O3tjRkzZgAA+vTpA29vb0yYMCG3p6BQHT58GDNnzsShQ4fg7Oxc1MWBTCbD999/jxo1asDPz09YdvToUfz+++949eoVxGIxatWqhSFDhqj8DZKSkrBz506cPHkSYWFhsLS0RJMmTTBixAiULVsWAHDr1i189dVXKse0sLCAq6urxs9Ds2bNkJKSkqWcf/zxB9zc3AAAZ86cwS+//IIXL17AysoKTZo0wejRo1G6dGlh/R07dmDlypVZ9tOuXTvMmzcPixYtwsCBA+Hm5gYfH588nz8iotw6dOgQZs2ahV9//RWenp7C8lOnTmHy5MlYvXo1GjVqJCy/fPkyvvnmG2F5RkYG9u3bh7/++gshISEwNTWFj48PRowYAXd3dwBAaGgounbtKuzDxMQE5cuXh7+/P7744gsYGxsLrynWVcRwbSQSCX799VccOnRIOG69evUwcuRIeHh4COv5+Phg2LBhGDFiBFJTU9GtWzf069cP/fr1y5fzV1A2bNiATZs24datW0VdFABASkoKvv32W3z66aeoU6cOAOj0tweAmJgYbNmyBRcvXsS7d+9ga2uLVq1aYdiwYbCysgLwvj6izNraGu7u7hg0aBCaNWsmLI+Ojka7du00lvPy5cswMTEBABw4cAC//fYbXr9+DTs7O7Rp0wbDhg1DqVKlhPUXLFiAffv2ZdnPwIEDMWbMGMycOROTJ0/G9u3bVd4TEVFBmzFjBm7fvo3Dhw9neU1TrFRu8xoYGMDR0RG+vr4YMGAAypQpo7K9cnvD2NgYjo6OaNu2Lfr37w9LS8scyxYWFoZNmzbh6tWriImJQZkyZdChQwcMHTpU+A5Wb2eeOnUK8+bNw+7du+Ho6Jjn81IY1Nv2Re369etYv349Nm3aJCwLCwvDxo0bcevWLURGRsLR0REdOnTAwIEDYWpqKqx3584dbNmyBU+ePEFSUhIqVqyIzz//HJ07dxbWUc+tiMViODk5oU6dOhg5cqTK3yundi0AREVFYe3atbh69Sri4+Ph5uaGIUOGoGXLlirbZNfW7ty5M65evYoffvgBa9asyTFnQ0S6Y2KecmRnZ4cFCxYAkN8y/b///Q9Dhw7Fjz/+iE6dOgEAJk2ahISEBGGb77//HlWqVMGQIUOEZa6ursLvTZo0EV6Lj4/HhQsX8NNPPyE4ODhLolbZ0qVL8fvvv+OLL77AqFGjEB8fj3379mHEiBHYunUrvLy8NG63ePFimJub5/0k5FJxqzzk1dGjR/Hs2TMsXbpUCL4rV67E3r17MWDAAIwcORLJyck4duwYhg8fjuXLl6Nx48aQSCQYPXo0wsLCMGjQILi7uyM8PBy7d+/GgAEDsGPHDiE5DwATJ05E1apVAcgT+levXsWsWbPw5MkTjB8/HoD8c5KSkoKvvvoqS7JcUTm5cuUKJk2ahPbt22PEiBEICwvDunXr8OLFC2zatEl4D+Hh4XB2dsasWbNU9qNI3nt6eqJnz55YsGAB9u7dC0NDflUSUeGoW7cuAODevXsqiflr164JP5UT8//99x8MDAxQq1YtAMDUqVNx7do1DB48GFWrVkVsbCz279+PAQMGYMuWLahcubKw7eDBg9G0aVOkpaXh6dOn2LlzJ06fPo1169blOmZOnjxZ6E1Vo0YNREREYPfu3Rg6dCj27t2rsdFvYmKCDRs2wMHBIVfH0ofyhYEP2Y4dOwAAX375pbBMl799QkICBg4cCAMDAwwaNAhOTk4ICQnBjh07cO3aNfzyyy8qf/v58+fD3t4eABAXF4czZ85g3LhxmDhxInr37g0AePfuHQBg2rRpwkVyBcVFnv3792PevHno1asXxo0bh4CAAGzYsAHh4eGYPXu2sP67d+9Qq1YtjB07VmU/ijpDkyZN0KRJEyxatAhr167Nj1NJRFRgFG1eiUSC169fY9++fejXrx9Wr16tEo8BefuxW7duyMjIwMuXL7F7926cPHkS69evV2k3qQsODsbQoUPh4OCAsWPHwsbGBvfv38eOHTvw4sULLFq0SON2zZs3h4eHR6El5YtbB7S8ysjIwIIFC9CvXz9UqlQJAPDmzRv069cPLi4uGDVqFGxsbBAYGIjt27fj9u3bWL9+PcRiMS5cuICJEyeiTZs2mDJlCgwNDXHr1i3Mnj0bQUFBGDVqlHCcypUrY9KkSQDkHeNev36N7du3o2/fvti5c6dwDnNq18pkMkycOBHBwcEYNWoUypQpg7/++gvfffcdVq1aJdQpdWlrT5w4EV27dsWJEyfg7++f/yeX6CPFbBPlyNjYWOiNBQBt2rTBkiVL8PPPP6N27dooV66cSvJAsY2tra3KdsrUX/P19UViYiL27t2LL7/8UmMi9O7du9izZw8mT56Mzz77TFjeokUL9O7dG4sWLcK2bds0Hu9DDv5Fadu2bejduzcsLCwAyHvo/frrr+jTp49KxaFVq1b48ssvsWbNGjRu3Bi3bt3Cf//9hxUrVqBp06bCes2aNUO3bt2wZ88efPvtt8JyT09Plc9DkyZNIBaLsXfvXgwePBg2NjZCw9/Hx0fr5+rYsWNwcnLCnDlzIBbLR+oSiUSYN28eXr9+jXLlygGQN/zLlSundT8A0LdvX+zZswdnz57V2hOQiCi/lS9fHnZ2drh37x66d+8uLL969SpsbW2FBL3CvXv3UKVKFZiZmSE4OBinT5/OEidbtWqFzz//HJs2bVJpoLu6ugrfgw0aNEDbtm3Rq1cvrFixAlOmTNG5zCdOnMDZs2ezfOc3bdoUPXr0wMqVK/Hzzz9r3LZChQo6H4fkUlNTsWfPHkycOBEGBgYAoPPf/tSpU0JySNHjvGHDhqhfvz66d++Ow4cPCwl3APDy8lKpQzVv3hyJiYnYuHEjPv/8cxgYGCA8PByAPHar9wJVOHr0KOrUqYPvvvsOANC4cWPExcVh586d+PHHH4UEfnh4OCpXrpxtfO7fvz8GDhyI+/fvo0aNGnk4g0REhUO5zevt7Q0/Pz8MHz4c06ZNw969e4XvcECe/FSs6+Pjgw4dOqBv376YM2cOVq1apfUY8+fPR6lSpbBlyxahZ3ajRo1QtmxZzJw5E1evXkXjxo2zbGdsbKxyRxvp5tSpU4iIiEDfvn2FZQcOHEBSUhLWrl0rtJsbNWoET09PfP3117h06RKaN2+O7du3o1q1akJPdkDePjYyMsLOnTvRp08fIaFuYWGhEgvr1q2LRo0a4ZNPPsHu3buFeJpTuzY4OBj37t3DtGnT8MknnwCQx/1u3brh6NGjQmJel7a2jY0NOnfujK1btzIxT5SPOMY85cnw4cNhaGiIv/76K9/2WadOHSQmJiImJkbj60eOHIGdnZ0QUBSMjY3RtWvXbCck6dKli0rvdR8fH6xevRpTp05Fy5Yt0bx5c0yZMgXx8fHYunUrOnfujGbNmmHgwIG4d++eyr5Onz4t9DJs164dfvjhByGQbdiwAT4+PggLC8ORI0fg4+Ojctv7sWPH0KdPHzRt2hSdOnXCqlWrkJaWlu15iYiIwPTp09G2bVs0bdoUw4cPx927d1XWSUtLw6JFi9CmTRv4+vpi4sSJQlkA+R0DDRs2VBkTLiEhAY0bN8bSpUs1HvfBgwd49eoVmjdvLizLyMhAenp6llsqRSIRhg4dKqyr+Duor1e6dGmMGTNG6F2QHR8fH0ilUgQHBwOA0PDPrldHSkoKzM3NhaQ8IK9AAPKe+Arh4eHZ9jwBAHt7e9SuXRvHjh3LsaxERPmpbt26KrHnxYsXePv2LXr37o3AwEBEREQAAKRSKR48eCA0oBTfvYpGoYKxsTFGjRoFb2/vbI/r6OiI3r174+jRoyp3weXkyJEjqFKlikpSHpB/57dv3x4vX77Uuq2Pjw82bNgAQD4UgI+PD3bu3Ilx48ahWbNmaN26NRYsWIDExEQsX74cHTp0QPPmzfHVV19l2e/+/fvxxRdfoEmTJvDz88PcuXMRHx8PQD4EgSImbtq0CT4+PggNDQUg7022d+9edO/eHU2aNMEnn3yC7du3QyaTZfu+X758iYkTJ6JVq1Zo0aIFvv32Wzx//lxlnbi4OPz4449o0aIFWrZsiRkzZmDhwoXCUAfjx49Hu3btIJFIVPbr4+ODX3/9VeNxL168iKSkJJXhZHT922uLz66urhg9erROHRl8fHwQFxeH6OhoAPKYamBgIPSs1yQlJUVjnUAikajUg3SJz9WrV4eTkxOOHz+eY1mJiIoTxXfy8+fPcfPmzWzXtbS0xJAhQ3D16lW8evVK4zrv3r3DjRs38MUXX6gMlwLIhzJxdnbGo0ePNG57+PBhlVi4YcMGtGjRAidOnMBnn32Gxo0bo3v37jhz5gyePXuGUaNGoVmzZvDz88OSJUuQkZEh7Cs6Oho///wz/P390bRpU/Ts2VNlyB8fHx9heLSuXbti+PDhwmu6tHU10aVd/c8//6Bfv35o3LgxunXrhoMHD8Lf3x8bNmxAdHQ0GjZsmKUtrOhFri0ncfz4cdSvX19lGLbk5GQYGRll+Rt4e3tjyJAhQvxLTk7WODRRp06d0L9/f6Smpmb7nu3t7eHu7q7yecgpbiqGplEMVQcAhoaGsLS0VMmd6NLWBuSdNF+8eIHHjx9nux4R6Y6JecoTS0tLVKxYEXfu3Mm3fb58+RJGRkYqY4Ere/LkCSpWrKixN/2gQYNw5MgRlQCZk927d8PDwwMLFixA//79cfLkSfTu3RsXLlzAd999hxkzZiA+Ph6TJ09Geno6AODs2bP4/vvv4eXlhSVLluC7777DkydPMHnyZABAt27dsHnzZtjZ2aFJkybYvHmzMETL3r17MX36dNSqVQsLFizA559/jl9//RXff/+91jImJCRgyJAhuHPnDsaNG4fZs2dDJBJh5MiRKkmb5cuXY9++fejRowcWLVoEDw8PbN26VXi9c+fOkEgkKhOmXblyBenp6ejYsaPGY//777+wsLBAlSpVhGUWFhaoX78+tm/fjuPHj6tUyJo0aSJUsurWrQsbGxvMmTMny2fks88+UxlDT5uQkBAA8p4mwPvKwk8//YRmzZqhadOm+O6774QEFQB88sknePbsGfbu3Yv4+Hg8e/YMmzdvRq1atVQuBoSHh+PBgwfo0qWL0GPg0KFDWcpQp04d3LlzJ8fkDBFRfqpTpw6CgoKERuHVq1dhbW2NPn36oFSpUrh+/ToA4Pnz50hMTBSGv/Hw8ECFChWwatUqXLp0SeW7q0OHDio9obWpW7cuUlNTtTbkNXny5IkQ69R9//332LNnj877AoDNmzejcePGWLx4Mfz8/LBv3z707NkTL168wPTp0zFp0iThd4Xdu3dj4cKFaNWqFZYvX47Ro0fjwoULmD9/PgBgyJAh2Lx5MwD5xfrNmzcLieSlS5di+fLlaNOmDRYuXIi2bdtizZo1WLx4sdYyhoaGYvDgwQgLC8MPP/yAH374AW/evMHQoUOF+AXIY9aZM2fw5ZdfYv78+TA1NVUZQ71z586Ijo5WGUv23LlzMDAwQPv27TUe+59//oGnp6dKfUnXv32TJk1gYmKCyZMnIzAwUGW/gwcPVrkYr01ISAgMDQ2FiwDv3r2DoaEhvvzySzRp0gQtWrTAzJkzkZiYKGzTvXt3XL16Ff/73/+QkJCA+/fv49dff0X79u2F/UgkEkRFReH8+fPo0KEDGjZsiJ49e+LSpUtZylCnTp0c5zYiIioIGRkZWR5SqVTn7evUqQORSKRTO7pevXoAoHXdp0+fQiaTaYzBpqamOHTokMrQsjlJTEzEb7/9hq+//hrz5s2DqakpfvzxR4wePRo+Pj5YvHgx/P39sXfvXhw4cEDYbvTo0bh58ybGjBmDpUuXomnTppg5c6Zwl9/mzZsxePBgAPIe/oohWnRt66rTpV395s0bjBkzBlKpFLNnz8aYMWOwb98+oe1oY2ODJk2a4MyZMyr7Pn/+PBo3bqwxJyGTyXDnzp0sHR1atmyJ5ORkTJ48Ga9fvxaWGxkZYdSoUUI9rXXr1rh27RrWr1+v0gHCzc0No0aNyvHCdEZGBt6+fSt0PANybtdWqlQJNWvWxJYtW/Ds2TPEx8dj7969eP78OT799FOV/QDZt7UBoGbNmjAwMMDt27ezLSsR6Y5D2VCeOTk54eHDh3naViaTCUndhIQEnDp1Cvv370f37t21jucdGxubZexSfXz66acYOnQoAPntXLdv38a///6L3bt3C4E4IyMD06ZNQ1BQECpWrIjKlStjy5YtwiSnEokEcXFxmD9/PuLj4+Ho6AhHR8csQ/kkJydj7dq16NKli5DEb9asGezs7DBz5kzcuHEDDRo0yFLG3bt34+3bt/jjjz9Qvnx5APLbyD///HOsXLkSmzdvRlRUFP7880/06tVLGF6mUaNGwvj7AFC1alVUrFgRp0+fRrdu3QDIKx3u7u5akykBAQEae7/Nnj0b06ZNw48//ojFixejZcuW8Pf3VxmLztraGkuWLMGPP/6IL7/8EuXLl0ebNm3QuXNnjX9DqVQqfB6SkpJw8+ZNbN68WRgqCZBf2be3txcmkA0ICMDatWsxadIk4SJEs2bNMGbMGCxZsgRLliwBIO8FuG7dOpUJaqytrWFubo4xY8bA0NAQv//+O2bNmiXsX8Hd3R3x8fF48+YNnJycNJ4nIqL8pmjA3b17Fy1atBDGlTc1NYW3tzeuXbuGTp06CY1WRawxNDTEkiVLMGXKFIwbNw4ODg5o3bo1OnfujGrVqul0bMV3nXpDLDuxsbH5Ok78sGHD0KtXLwDyeHb58mWkpKRg0aJFwpAn7969w9q1a5GUlAQzMzM0bdoU9erVE96nRCLBy5cvsX//fgDyWKCY60Z5uICQkBD8+uuvGDZsmHBxWXFb+ebNm9GrVy+VOXIUNm7cCABYv3690PutSZMm6NatGzZs2IDZs2fj6dOnuHjxIiZMmIAvvvhCeD9hYWFCz3pfX19YW1vj1KlTqF+/PgDgwoULaNiwoXBhWl1gYGCW+Kzr375ChQqYN28e5syZg969e6NSpUpo06YNunTpojEhoByf4+Pjcf78eezfvx/t2rUTegaamprCxsYGHTt2xNdff407d+5g06ZNSE1NFYYw+uyzz/Ds2TOVIZJq166tcjdjUlISnJyc4OTkhK+//hrp6enYunUrJkyYgD179qBixYrCum5ubvjf//4HiUSiMhQEEVFBCgsLU5nnJS+MjY1hZ2enU5zNKSYr7obO7o6l3Fq2bJnQFrayssLw4cPRvXt3IcHfqFEjnD9/Hrdv30bPnj0hkUgwadIkODk5oWzZspDJZPD29saxY8dw+fJlNGrUCHXq1BHuglYeIk2Xtq46XdvVu3fvhkwmw+rVq4V46u3trTJEaefOnfH9998LQ6O9evUKL1++1DoPTWhoKBITE7Ocb29vb0ydOhXLli3DJ598gpo1a6J169bo0qULrK2thfUGDRqEyMhIbN26FTt27ECjRo3Qvn17tG3bVmMORBF/ZTIZQkNDsWHDBkRFRQnz/AE5t2tFIhGWLl2KgQMHCnUrQD5evPKdjrq0tQH5/EDOzs5ZLu4TUd4xMU95JhaL8zwb99GjR3H06FHhuUgkQu/evfHNN9/kV/FypBwkAXlDvUyZMipXxxVBV9Fr0cXFBSEhIRgxYgQCAwNVhoaJj4/XeGsaIE+uJCcnZ+md7u/vjzlz5mhNzF+/fh21atUSKiqAPGj6+flhy5YtSElJwbNnz5Ceno7WrVurbKt+lb9z585Ys2YN4uLiYGZmhsuXL2PAgAGaT07me9bUU8De3h7r16/Hv//+i+PHj+PMmTP466+/0KBBA8yfP1+4Ta5WrVrYv38/zp49i//973/Yu3cvduzYgS+++ALjxo1T+ewoj1cPAAYGBvDz81P5PPj7+6uMZVevXj1YWlpi+vTpuHXrFnx8fHD79m2sW7cOPXr0QLt27fDmzRusXbsWc+bMwcKFC4Vj7tq1S+V49evXR69evfDLL7+oJOYVf8+YmBgm5omo0FSqVAkWFha4d+8eGjVqhNu3b2Pq1KkA5GNzb926FTKZDP/99x/c3NxUek65ublh165duHr1Kk6cOIEjR47gt99+g5+fH6ZPny4ktrVRnp9DV/l9V5F6fFYkjJXLrrgQEBsbCzMzMyFRO3/+fLx8+VKlt3Z2bty4AZlMliU+d+nSBZs2bcLNmzc1JuavXbsGX19flbhvZWWFFi1a4OrVqwAg3HXQqlUrlW2V/15GRkZo3749zpw5g++//x7R0dG4f/9+lknclMXExKjczaag69++efPmOHToEP7++2+cOnUKmzZtwpYtWzB69Gj069dPZZ+ahg/s0aOHStweOHAgBg4cKDyvV68epFIp1q9fj1GjRqFcuXI4ceIEDhw4gMGDB6Nhw4Z4/vw51q5di1WrVmHChAkA5DH34MGDKserW7cuunXrhh07dgjDICjOtUQiQXx8vNY7LYmI8pu9vb3GYUAjIiIwfvx4nfejaztasY62dQvirl7l71TFsCbqE9Xa29sL7WMDAwNUrFgR27Ztw+nTp/H27VuVC7rZ0aWtqz48jK7t6sePH6N27doqF7mV4y8gj4fW1tY4ffo0atSogfPnz8Pc3Fzr3WOK96wp7nzyySdo3bo1jh07hlOnTmHFihXYuHEjpkyZAj8/P+G9ff/99+jTpw+OHDmCkydPYtq0aVi3bh0WLVqkcp7/+eefLBeBXFxcMH/+fJXlObVrpVIpfvrpJ+HOATs7O5w4cQKrV6+Gl5cXatWqJZy/nNraCpaWllqH+iGi3GNinvIsMjISdnZ2edrW19cXw4YNAyC/RX/dunVo1aqV1t7ygHwYlcjIyDwdT1+KSs/ly5cxbtw4+Pr64scff4S9vT0uX76MTZs2Zbu9YhxW9R6FhoaGKF26tNbAFh0drbGXo52dHaRSKeLi4hAVFQUAWnvWKfj7+2P16tU4f/48ypQpg8TERKGSoElGRka2Fca6deuibt26mDRpEo4dO4b58+dj/vz5KhP8GRoaol27dmjXrh0SEhKwYcMG7N69G66urujRo4ew3g8//CC8TwsLCzg5OcHIyCjb9wNAGF83MDAQPj4+WLFiBWrXro0ffvhBWKds2bIYOXIkrl69qpJ0V2ZoaIjGjRtnGa9WkcTIaR4AIqL8JBaLUatWLdy7dw///vsv0tPThYnbGjdujEWLFiEwMBD37t0TbnNX375p06Zo2rQpUlNTsXfvXqxZswaOjo74+uuvsz22Is7mJr5bWloWeXzev38/5s2bhy5dumDYsGGwsbHBwYMH8eeff2a7vSI+q09aqnj/2cVnTROd2tnZCdso9p3TuezcuTP27duHf/75ByEhITAxMUGLFi20rp9dfNb1b29qaopu3bqhW7duiIyMFIbzqVixosokgUuXLoW9vT1EIhGsrKxQtmzZbOtqCs2aNcP69evx/PlzODs7Y9myZejYsSNGjx4NQD7esImJCWbPno3u3bsLE9Gqs7CwQO3atfHs2TOV5Yo6gmKoQSKiwmBkZAQvL68syxXjtOsiIyMDMTExOsXZnGKy4uJwZGSkcJdxYVG+KPDNN9/g1atXGDp0KCpXrgwzMzOdLlTo0tZVT8zr2q6OiorSeme4guLi+OnTp/HNN9/g/PnzaN26NUxMTDSur7jgoC0GW1lZoXfv3ujduzdCQkLw888/46effkKlSpVU7voqX748Ro4ciZEjR+L27duYOXMmvv32W/z1119CjK1atapwl5mBgQHKlCmT5cKCJurt2itXruDKlSvYuHGjUGds0KABgoODsXTpUvzyyy9a96Xe1lYwNjZm+5goH3GMecqTpKQk3L9/XxjSJbesra3h5eUFLy8vDBw4EK6urli9enW221SuXBmBgYEq45or7Ny5Ez169NA6+Wt+OXToEJycnIQhXGrUqKHTRGmKXuSKJLqComKmLchaWVll2QaQ98oQiUSwtrYWKiU5XbW2t7dHw4YNcfr0aZw/fx61a9fOtuwWFhYqE6YC8iv36hPrGBoaomvXrujcuTMuXrwIQD6ZkPqkdRYWFpgwYQLc3NyE9RQqVKggfB5cXV01JuXPnTuXZZIZ9V4igYGBWSp3NWvWBCAfgxGQD1tw7NixLJ8jTT1OFOdU250QREQFpW7dunj8+DGuX7+OatWqCXHC1dUVLi4uOHv2LIKCgoQhWQD596T6hWITExMMGjQIjRo1woULF3I87vXr12FsbKzz0DeAvIe/tknAlixZgkGDBum8r7z666+/ULduXWFs1OrVq+t0a7+id756rFWMtaotPltbW2u8GBEeHi5so37XnTbVq1eHu7u7EJ9btmyZ7Zw5FhYWWeo7uv7td+/enWVSc8Xt/2ZmZlk+I56envDy8kK1atXg4uKSJSkvk8lw/PhxrRMTAvJzGxkZmSWZpYjPAQEBws9Tp05l2Z7xmYhKkjt37iAtLU2ndvSNGzcAQOu6ih7WmmJwSkoKPvvsM2zfvl2P0ubs2bNnuHfvHsaOHYs+ffrAx8cHXl5eOnWy0qWtq2kbIOd2tYODg069ujt16oTQ0FBcunQJ//33n0qvcXWKOVHU28jr16/PMh9KuXLlMGvWLEgkEly5cgVv377FqlWr8OLFC5X1vL29MXr0aLx9+1ZorwKAmZmZ0D6uUqWKxvqILu1axZAz6jG4Ro0aQvwFdGtrK8TExDD+EuUjJuYpT1atWgWJRIKuXbvqvS9DQ0OMGjUK9+7dU5mcVF2nTp0QGRmpMgQOIO8tdfDgQVhbW+dq8te8kEgkMDU1FW71ByCME6tMLBarBLLatWvD1NQUJ06cUFnv+PHjkEgkaNiwocbjNWjQAHfv3kVYWJiwLCMjA3///Tfq1q0LExMTVKxYESYmJlnOnaI3gbLOnTvj+vXrOHPmTLaVDkB+q9ybN29UliUmJmL79u24cuVKlvXj4+NhZmYGQF5BW716Nd69e6eyTkZGBpKTk/P0d/rzzz+xcOFClWWKyqqnpycAeQVMfby7J0+eAHifIImNjRVuyVOQyWS4efOmSk8GQH4OxWJxjrPTExHlt7p16yI5ORmnTp1SGQMUkPeaP3r0KGQymTAePQC8ffsWGzZsEL73lCl/R2sTFBSEvXv3ws/PT2h86qJz58549OgRbt68qbI8NjYWx44dK5RefBkZGVnen6b4rN7LrX79+hCJRFni89GjRyESibKNzxcvXlQZMic+Ph4XLlwQbjFXNILPnj2rsq2mJESnTp1w5swZ3LhxQ+uk7Aqa4rOuf/u7d+9izZo1WYb6SUlJQXp6eo6fEXUikQjbtm3LclFAMUFxxYoVYWVlBRMTE5UEAPD+grkiPr969QqTJ09WSfInJyfjv//+E+K8QkxMDGxtbbP0pCQiKs5SUlKwcuVKVKhQQZhXRJvo6Ghs2rQJ9evX1zrPmpOTE+rVq4fffvsNqampKq+dOnUKL1++1Dj0WX6SSCQAAHNzc2FZZGRklqS4Iv4qt5F1aeuq07Vd7eXlhTt37qiUQ1P8rVGjBtzc3LBgwQLY2dmp9AxX5+TkBLFYnCUGX758GRs2bMiSIFcM5VOqVCmYmJhgz549KpPmqq+X2xisS7tWEWM1xWDlDgy6tLUVoqOjdeqcSES64VA2lKO0tDTcuXMHUqkU7969w7Fjx3D9+nVMnTpV47iredG2bVt4eXlh7dq1aN68uUriW8HHxwfdu3fHwoUL8ebNG9StWxcxMTE4cOAAwsLCMHfu3HwpS3Z8fX0xe/ZsrFq1CvXr18fly5eFnuHKV87Lli2Lf//9F2fOnEGNGjVQpkwZDBs2DKtWrYKhoSGaNGmC58+fY8OGDWjevLnWCkDfvn1x7NgxjBw5EsOGDYO5uTl+//13vHnzRhh/1traGt27d8eePXtgamqK2rVr459//tF4+36LFi1gYmKC2NhYtG3bNtv3Wr16dezYsQPv3r0TbtdXzND+008/oXfv3qhZsyZkMhkuXbqEkydPCreo9+vXD2fPnsWwYcPQp08fuLm5IT4+HgcOHEBERAQ+//zzXJ/7/v37Y9SoUZg5cybatWuH0NBQrFu3DnXq1BHO3xdffIHFixdj/vz5aN68OSIjI7Fx40Y4OTkJY/B7eXmhQYMGmDVrFkaMGAE7OzscPnwYz58/x5o1a1SOef/+fbi7u+e6kkREpC8vLy8YGxsjLCwsyzBcjRo1wh9//IGyZcuqNIy6deuGI0eOYMyYMejTpw+qVKmC1NRUnDhxAvfv38ecOXNU9hMUFIQ7d+4gJSUF9+/fx969e+Hi4pKrcXIBeWL+5MmTmDRpknAb+7t377B3714AwJgxY/J4FnTXvHlzYTI1T09PHD9+HKdPnwYgv6isSBg4Ojri0qVLqFKlCnx8fFChQgX06NED69atQ0pKCmrWrIm7d+9i+/bt6NWrF1xcXDQeb/jw4bh48SJGjhyJ/v37QyaTCb0SFUP1eXh4oEWLFli5ciXS09NRsWJFnD17FleuXMkyb0nHjh2xdu1a2NjYaJxzRln16tVx8eJFpKenCz0Sdf3bf/XVVxg2bBi+/PJL9OrVC87OzoiIiMCePXtgZGSUpw4XAwcOxE8//QQHBwc0aNAAAQEB2LhxI/z9/YXz99lnn+HXX39F6dKlUa9ePQQFBWHDhg3w8vIS7vpo1qwZPDw8MHHiRHz55ZcwMTHB3r17ER8frzKGPSCPz9WrV891WYmIClNUVBTu3LmDjIwMvHz5Er/99huio6OxevXqLHcgvXnzRuhN//TpU+zduxeGhoaYPn16tsf44YcfMHToUIwcORJ9+vSBhYUF7t+/j507d6Jdu3Z6T1abEw8PD7i4uGDt2rUwMDBASkoKNm/ejOTkZJWLwIqOTn/88QeaNGmC+vXr69TWVWdhYaFTu/qLL77A77//jjFjxmDQoEGQyWQqk5gq69y5M1avXo1+/fppzEMomJmZwd3dPUuSe9y4cRg7dixGjhyJTz/9FPb29nj9+jV27NgBe3t7tG3bFqVLl8aIESOwZs0aJCQkwNfXF2ZmZnj06BF++eUXNGrUSOsFGG10ade2bt0aGzZswLRp0zBs2DDY2tri3LlzuH79Or777jthX7q0tQF5L/3Y2FjGYKJ8xMQ85SgyMhJffvklxGIxbG1tUatWLWzevFm4BTm/jB07Fl999RWOHTuGzp07a1znhx9+gIeHBw4cOIDt27fDxsYGXl5e2LlzZ5bezgWha9euiIiIwIEDB/Drr7/C29sbP/30E7Zt24bXr18LV5O/+uorzJgxAzNmzMDSpUtRpkwZDBw4ENbW1ti9ezf+/PNP2NnZoW/fvkIDXpPSpUtjy5YtWLFiBRYtWgSpVIrq1atj48aNKud/zJgxkEql+O2337Bv3z7Ur18fXbt2zXK7uomJCWrUqAETExONtwYqa9y4MUqVKoUrV64Ik7+JRCIsWbIEf/zxB44cOYLdu3fD2NgYbm5umDt3Ljp06ABAfmV+x44d2LZtG/bu3Yt3797BysoKXl5e2LJlC2rUqJHrc68YQ37jxo34/vvvYWxsjKZNm+Lbb78V1unduzdsbGywa9cuHD16FFZWVmjQoAFGjRolJNdFIhEWLFiA9evXY+PGjYiKikKFChXw888/Z+kZefPmTXz66ae5LisVX4r/32vXrqlUzu/cuYNly5bh+fPncHFxwddffy2Mq0hUFIyNjVG9enW8fPkyS+Onfv36MDQ0VBnGBpCPG75p0ybs2rULx44dw6ZNm2BmZoZKlSph9erVWRrn27Ztw7Zt22Bqaopy5cqhX79++OKLL3LdC1kkEmHx4sXYvn07/vjjD7x9+xZlypRB3bp1sWTJEmHy1oI0ZMgQJCUlYffu3UhOTkbTpk0xadIk/PbbbwgKChKG5vnmm2+waNEizJw5E9u3b4eFhQUmTZoER0dH/Pnnn9i+fTucnJwwZswY9O3bV+vxXF1dsWXLFqxcuRKzZs2CgYEB6tWrh7lz56ok82fMmIGFCxdiw4YNMDMzQ/PmzdGyZUu8fPlSZX9lypRBuXLl0LRpUxgYGGT7Xlu2bIkVK1bg33//FZL4uv7tPTw8sHv3bmzZsgWbNm1CVFQUbG1tUa9ePcyZMwcVKlTI9bnv1KkTxGIxdu7cid9//x0WFhbo1q2bygWZsWPHwtnZGQcOHMCePXtgZ2eHjh07Yvjw4UISxNTUFGvWrMGqVauwdOlSxMfHo3Llyli5cqXKGPSK4RQVEyLTh23Dhg3YtGkTDh06BGdnZ7x48QLz58/Ho0eP4OjoiDFjxsDX17eoi0mUJ4rxvQ0NDVG2bFk0bdoUAwYM0Hg37uHDh3H48GGYmJjA0dER/v7+6N+/f45tNnd3d2zbtg3r1q3DvHnzkJaWhvLly2PEiBHo2bNnQb01gaGhIZYtW4aFCxfixx9/hLW1NXr37o2nT5+q9FD39vaGv78/9u3bh2fPnqF+/fo6t3XV6dKudnBwwKpVq7B48WJMnz4dLi4uwoVk9Z74irHXc7qjHJAnug8fPgyZTCbcBeDt7Y2dO3di69atWLFiBeLj4+Hg4IDGjRtj8ODBwmSxgwYNgqenJ/bs2YPZs2cjIyMDTk5OGDx4MHr37q3zOVfQpV1rZmaGbdu2Yc2aNVi3bh3i4uLg5uaGOXPmqMw3p0tbG5DfEVeqVCmV+WiISD8iWUFM5U1EhSohIQHm5uYqt+h/++23ePv2Lfbs2SMsi4yMRJcuXTBr1qwce8wDwM8//4yAgABs27atQMpdnF2/fh3ffvstDhw4wKFsikh0dDROnTqFtku+h83rFzlvACDaxR2nJixA27Zts4zFOHfuXBw+fBiWlpYwNTXF4cOHAciHgOjZsycGDRqEdu3a4erVq1i+fDl+//13rb1liYh0ERcXJ4yHC8hvMe/Tpw9cXFywePFiYfnTp0/Rp08f7NixQ+PEgurGjBkDS0tLlQnXPxYHDx7EmjVr8Ndff/GOtkIixOPV38MmVMd47OyOU19rjscKISEh6NWrF1JTU3Ho0CGUKVMGvXr1gpeXF7788kucPXsWmzZtwm+//VboE1sS0YdPPQY/fvwY/fr1E+aLU1iyZAmuX7+O33//Pcd9hoWFoXv37li6dOlHmZweOnQoKlWqhMmTJxd1UT46eYnFgG7xmIoWx5gnKgGmT5+O0aNH4/Tp07hy5QoWLVqEixcvCrd+R0VF4ciRI5g4cSIcHR1VKiLZGTFiBJ4/fy4MB/CxkEgkWLduHfr27cukfAlia2uLX375BWPHjlVZfunSJdjb22Pw4MEoV64cPv/8czg7OwtjJBMR5YVMJsNXX32FH374ARcuXMClS5cwbdo0PHv2DP379wcAvH79GgcPHsSUKVOECfN08c033+Ds2bO4f/9+Qb6FYic5ORlbtmxRuROOPlyLFi1Cu3bthOfBwcF49eoVxo0bhwoVKmDQoEEoW7Ysrl27VoSlJKIP0ePHj9G1a1ds3boVN27cwJEjRzBlyhR4enoKd8XevHkTGzZswO+//44BAwbotF8nJyf06dNHmHPvY3Lx4kU8e/YMI0aMKOqiEJUoTMwTlQBTpkyBi4sLFi5ciEmTJuHu3bv4+eefhaFlQkJCMG/ePEilUixevDjLmIba2NnZYfbs2Zg3bx6ePXtWkG+hWFm0aBGMjIwwfPjwoi4K5aORI0eiatWqWZZ369YNu3fvVllmaGiI5OTkwioaEZVAilvMxWIxZs6cialTpyIsLAyrV69G7dq1AQAPHjzAokWLUKZMmSxzAGTH09MT3377LaZMmYLw8PCCegvFSkZGBqZOnYoaNWpwmLkS4Ny5c3jx4gUGDRokLFNMXqk8zISpqWmWSS2JiHJStWpVTJ06FRcuXMC3336LtWvXolatWirj++/Zswe//fYbhgwZonUoXU2++uormJqaYv78+QVV/GLn2bNnmDNnDubMmcNe10T5jGPME5UA9vb2mDp1qtbxVmvVqoXLly/nad/NmzfHtGnTEBkZWSjj+BcHFhYWWLZsmTCpHpVshoaGQgVdKpXi77//RmhoKNq0aVPEJSOiD1358uWznZy+ffv2aN++fZ723bNnT4jFYsTFxcHBwSGvRfygVKhQASNHjizqYpCeUlJSsGTJEkyYMAHGxsbC8kqVKqFcuXL45Zdf8NVXX+Hy5ct49eoVWrRoUYSlJaIPVbt27VTuylG3bNmyPO3XyMgIK1euxI4dO/JatA/O27dv8cMPP3AOLqICwMQ8EeVI16FvSoqvv/66qItAyhyh+/1dZfJ+mCVLlmDfvn3IyMjAjBkzOIwRERV7n332WVEXodAYGhrim2++KepifNysAejaeT2b+Sq3bt0Kd3d3tGzZEqGhocJyAwMDzJo1C8OGDcOOHTsglUoxceJEji9PRMWOhYUFRo0aVdTFKDRNmjQp6iIQlVhMzBMREQEYMmQIPvnkE1y9ehULFixA5cqVUbly5aIuFhERUYkRFBSE3377DTt37szyWkJCAn788Uf07dsXHTp0wIMHD7By5UrUrl0b1apVK4LSEhERERUsJuaJiIgA2NjYwMbGBhUrVsT169dx5MgRjB8/vqiLRUREVGLs3r0bycnJ6Nu3LwD5JMmAfGimgQMHQiwWC5O0V6lSBf/99x92796dqzkYiIiIiD4UH1ViPikpiZMHEREVAhMTE5iZmRV1MXTyyy+/ICQkBNOmTROWicVilXFvKX8xHhMRFY7iFo9HjBiBfv36Cc/fvXuHESNGYMWKFbh9+3aW+X1MTU2RmJhY2MX8aDAeExEVjuIWj6n4+GgS80lJSThx4gQkEklRF4WIqMQzMDCAn5/fB1H5qFmzJtavX4+aNWvCx8cHd+7cwc2bNzFs2LCiLlqJxHhMRFR4ils8trW1ha2trfDcwMAAAODk5IT27dtj27Zt2LFjB1q3bo3AwEAcO3YMkyZNKqrilmiMx0REhae4xWMqPj6axHxqaiokEgkaNGgAKyurAjuOVCqFTCaDRCKBVCoVfip+1/aaNmKxWOVhYGCQ5blIJMqyXCQSAQAiIyNhYmICCwuLAnvPJdnLly/h5uZW1MX4IMXExEAkEsHaOpvZv0irV69eoUKFCkVdjDyJi4vDjRs3kJqa+kFUPLy9vTFz5kxs2bIFCxcuRLly5TB79mzUqFGjqItWIn3o8Vg97io/zy4ev337FpaWlh/E/0Rx9CF/JxY11gX18yF/9j60eOzm5obFixdj3bp12LhxI+zs7DB8+HB06tSpqItWIhVmPFaPterL1OOycjyWyWRCLAWQ6zisHo/DwsJga2sLExOTAnvPJZVUKkVISAhcXV2LuigfJNYF9cN4TCXVR5OYV7CysoKNjU1RF0MnMpksS4VF8VB+LpVKkZaWlqViAwCJiYkwNjZGUlISRCIRRCKRSoI/Nz8V239M3r1798F8XoqbjIwMGBgY8PzlET97BadLly7o0qWLyrIOHTqgQ4cORVSij9OHGo9zisna4nFCQgKkUikSEhK0xmPlZALj8XsymQzh4eEfzOeluElJSYG5uXmBJt5KMsbjguXs7Ixbt24Jz5s2bYqmTZsWYYk+Ph9yPNbULlb8np6ertKWVo7HihgMQGPcVY+92l7/2OJxRkYGYmJiPpjPS3GTkJAAGxsbJmbziPGYSqqPLjH/IVFc8Vfc4pkXwcHBsLOzE7781XsoqPcWVK/AqPdsUPRYUFRsFBURReVGW0JBW29/Tb0YipPiWKYPhUwmEyq8lHv87BEVH/kRj1+8eAEXFxdh7gJNvQV1iceKZL8iDquXUzkea4vBH1o8Vu8tSbnD86cfnjui4iM/4nFAQAAqVqwotFOyaxurx2P1u++Ue/Yr2siKn9rirKZ2sqbnxTEeS6VStu/0wHicdzx3VJIxMV/CSSQSlYqLIsjnt+xuS1QsU+5FqCnpr4ki8aDpdkRtFZj8SjZoSnqQ7qRSKYMnEVEm9casIi4ZGuZvVSynWCyVSpGamprt0AKaKBpE2i7E5/TQJx4zEaAfxmMiovfUE3xFGY8VSX9d47Fy+1TfdjHjceFjPCYiTZiYL+EKK3gWVMJfQb2SoqnyonzLoqb1FLc+Atn3flKupMTHxyMkJERrBUc9QaG+/GO7vVEZr2rrhxeGiEoW9QvlBaW4xWNNiQblIQW0xQnliwAymQxxcXF5isfKsfhjjUm8g00/jMdEJU9hxIOCjMeKO+eyi8XK8VhbLFa0jbNrtynHY4lEguTk5GzjcXZxmfGY8TivmFugkoyJ+RKusBIBBa2gEw0KyhWctLQ0pKamwsbGRmMlJiMjQ2sFR7EfRaVJOYhoGg5IueKi7Xf1hH926xeHCwPsUaEfVjyISp6S8H9dFPE4KSkJMplMYzyWSCTZxmP1C/PqFH8TbXcEaIq7OcXe4haP2ZjVD88dERU3yvGqoCnH0fj4eMTGxmqNx+np6cIkvuoXDrKLx8ptY8VzfdrFjMdE9CFhYr6E4+1SuaM8bqFMJoOJiQnMzc0L9JjqPR60/a54rn4HgPrP7C4MqFd41CsHyr0YtFVklCs02f2ekpICU1NTGBoaatzvx9xbgog+Pux1mzvK8djIyKjI47GmOKuchMguDmuLx5ou2iu//5xib27icWpqaraxmPGYiIg0UST/DQwMYGhoCFNT0xIXjxXUO88pfurTJlb+PTU1FampqZBIJIzHucSLGlSSMTH/EeAXWN4UVo/vwuzxkB1FJUW5IqReqVGv0Civo14ZSkpKAiCffV7bvrMLsNoSGMq9GrN7aKrkaHsA7yududkmu2X58fcgIqKPOx6rx9y8xuPo6GhhWCD1bXOKN7mNx7mJv7mNs4zHRERFh/FY+09Nv6vH4+TkZERGRqrsWz0e52f7uCTFYybmqSRjYp5Ii49tKJb8vkKfkZGBsmXLwtTUNN/2qaBeedGWxNDlobx+TvvObh3l5crlVD6nuvbOkMlkiImJwdOnT7WeA+WKTn78zMsyTc9FIvncDERE+eVjjsf5MRxhamoqypUrByMjI733pU7fGJxTPFYe/7gg43F2r30o8VhTbGY8JqL8xHisn8TERLi6uuZ7gllTTCzMeKwtJisvUy5rXuKxVCpFXFwcJBKJ1vPAeEwfKibmibT42Coe+a0gr2rn90WE4ujp06eoXLmyxtc0VXTy62dOy9R/17Q+/2+IKD8xHuunIM9fSY/HMpkMAQEBH0Q81vQ7/2+IVKnXYSl3GI/1VxAxU1OiuKRJT09HcHAwPDw8NL5eEHGY8ZgKCxPzRFqw4qGfgkzMfwyyazgU98pXcS0XUVHh96F+GI/1w89f3uV07hiPiT4sjCf6kUqlBXL3FVFOdInHxTnmFeeyUdFjVCLSghU3/chkMp4/PTB4E5UcTIzqh/FYP/z85R3PHVHJIpFI8mVIko8V47F+eMcGEWnCb9USjI0J/bDioR+pVMrPHxERmAjQF+Ox/hiPiYjk8YTxOO/YvtMPz13eMbdFJRmHsinBmAjQDxMB+mHw1A97VBCVHIwn+uH5o6LCugxRySKRSBhP9MALG1RUGI8LTkREBA4cOIBr165h69atWtfbtWsXdu/ejdjYWNSoUQPTp09HuXLlAAAxMTFYtmwZrl69CqlUCl9fX4wfPx6WlpYAgOvXr2P06NEq+6tQoQL279+vd/lfv36NuXPn4u7du7C0tMQXX3yBgQMHCq+vXbs2y/vq3r07pkyZovex8wsT8yUYG7L64Rh6+mHwzDueO6KShRfK9cP6jH54oZeISI7xWD/sMa8fxmMqbubOnYvDhw/D0tISpqamWte7dOkS1q9fjxkzZsDd3R2rV6/G5MmTsWvXLgDAlClTIJFIsHLlSkgkEvz0009YvHgxZs6cCQCIioqCp6cnVq9eLezT0DB/0tE//PADypQpg507dyIwMBAzZ86Em5sbWrRoIRy7e/fuGD58uLBNdu+1KDAxX4Kx4qEfJgL0x4obERHjsb4Yj/XDWJx3vFBOVLKwx7d+eP70w3iSd4zHBcPW1ha//PILAgICsHHjRq3rnThxAh06dEDbtm0BABMnTkS3bt3w8uVLmJqa4saNG9i/fz8qVKgAAPjyyy+xaNEiYfvIyEg4ODjA3t4+z2UdPnw4vL29MWLECGFZUFAQHj58iIULF8LR0REeHh64cuUKTpw4ISTmIyMjUbt2bb2OXdDYyinBmAjQDxMBVFRY8SAqWdiQ1Q/jMRUVxmOikoVD2eiH8ZiKCuNxwRg5ciSqVq2a43rPnz+Hp6en8NzFxQXm5uZ4+fIlSpUqhfnz58PV1VV43cTERKVHfFRUFGxtbbXu//79+xg0aBB8fX0xYMAA3Lt3T6fyP3/+HJaWlnB0dBSWeXp64tWrVzofuzjgt2oJxsCpH54//fBWvbxjxYOoZGEiQD+Mx/phPM47xmOikoUd1/TDeKwfxuO847krWomJibCwsFBZZmlpiYSEBFhbW6Nt27Yq9aUjR46gdevWwvOoqCg8fPgQ3bt3R6dOnTB37lwkJycDAN6+fYvRo0fDz88Pe/fuRfv27TFu3DjEx8fnqVxWVlZITExUOfaff/4Jf39/9OjRQxh+pzjhUDYlGCse+mHFQz9syBIRyTEe64fxWD+Mx0REcown+uH50w/jsX54/oqOVCrNskwkEmm8YHLkyBH8888/2Ldvn7CsUqVKMDAwwGeffYbo6GjMnz8fS5YswbRp07B//354e3ujd+/eAIB+/frh0KFDuHz5MkJDQ7Ft2zYAQGpqKu7duyck1leuXKm1XMrL69atC1dXV7Ro0QL379/H4sWLYWdnB39/f/1OSj5iYr4E463z+mHFg4oKe+gRlSycTFw/jMdUVBiPiUoWXijXH78TqSgwHispD8AsF+vb6X9IsVicJQkuk8myfJ/ev38f8+bNw88//6wypnvfvn1V1hs3bhymTZuGKVOm4OnTp7h27Rp8fX2F11NTUxEWFoYePXqgXbt2AIBp06ahRo0aQgLfwcEBr1+/zrFcs2bNEn6vVKkSAgMDceTIESbmqXBIJBImAvTARIB+eLtZ3rHiQVSyMBGgH8Zj/TAeExHJcWg5/TCe6Ifnjz5UZmZmWYaWiY+Ph6WlpfD87du3mDBhAoYOHSpMvKqNh4cH0tLSEBMTAwDw9/fHkCFDVNaxsrKCtbU1rK2tAcjHrbeyskL58uWFdczNzbOUKy4uTqVc6tzd3XHjxo1sy1fYGJVKMCYC9MNEABER5QcmAvTHi5VUFHihnKhk4R3l+uH3Yd4xnuiH569oubu749GjR8Lz169fIzExER4eHgCA5ORkjB8/Hg0bNsySYJdKpejatSvu378vLAsODoaRkRFKly4Nd3d3vHjxAuXLlxcednZ2QkI+p3IlJSWpTPYaGBgolOvJkyfo1KkT0tPThddDQkLg4OCQtxNRQNhKLMGYCNAPE/P6YeDMO1Y8iEoWJgL0wx5m+mE8yTvGY6KShR3X9MN4nHeMJ/rhZ6/wpaWlCb/7+/vjzJkzOH78OJ4/f47FixejVq1acHFxgUwmw/Tp0yGRSDBy5EhEREQIj5SUFIjFYvj4+GDJkiV48uQJHjx4gNWrV8PPzw9isRg9e/ZEQEAAli9fjlevXuH69evo0aMHAgICciyjm5sbqlWrhsWLFyMwMBAnT57EyZMnhWFqKlasCBMTEyxcuBBBQUE4d+4c/vzzT3Ts2LHAzltecCibEoyJAP0weOqHwTPv+NkjKlmYCKCixHicdzx3RCULO65RUWH7Tn88f4XnzZs36NevH3bt2gVHR0f4+vpi1KhRWLFiBeLi4lC7dm3MmTNHWPfs2bMAgC5duqjs56effkKXLl0wYcIELFu2DKNHj4ZIJIKvry/Gjx8PAHBycsKKFSuwfPly/PrrryhbtiyGDh2KSpUqqexr48aNGss6b948zJkzBwMGDICVlRVGjRqFRo0aAQAMDQ2xbNkyLFq0CP369YONjQ2GDBmCTp065ev50hcT8yUYEwH64Rc/ERHlB14o1w/jcd4xEaA/nj+ikoWJ+bzj92He8W58/bA+U7C6dOmiklR3dHTEqVOnVNbp378/+vfvn2VbJycn3Lp1K9v9m5ubY9q0aZg2bZrG1318fLBr1648lBwoV64c1q9fr/X1ChUqYPXq1Xnad2HhN0MJxi9//bCXFBUVVjyIShapVMr/aT0wHucd44l+eP6IiCg/MJ7oh+ePSjL2mC/B2GOe6MPEigdRycP/aSoK7KShH14UUmMNICMX6xIREQC274hIO9bUSzh++ecdz13eseKhHyYCiIjeYzzJO8Zj/fH8ERGxfaIvXijXD+szVJLxm4FIC1Y+8k4mk7HioSdWPIiISF9syOqH54+oZGH7Lu+YWNYP44l+eP6oJONQNkQ5CckhAJRjBU8dx1PWDyseRERyKkmU4xq+F6Myf/ZlLNaEiRT9MB4TEcmpxJOAbL4XKzEea8J4QkTaMDFPpIVIJMo5KQ/oto6yYADl81SkrIrpRQFWPIiIKD8IiQBNSXllqwow5kQBiMxhnZWMx0RExRkvVOpHOH/ZJeWBnF8vaMX0wgA/f/phfYZKMibmiTSQyWQQJSwGzPJ5x8FAUqoh/t7viduvndC28XM0936FPMdoxUWBYpagZ+DUD88fUcnB2+b1I5VKIQ6dUSD7jrcwxvEHnvgvpiz8nQPQ2D4EWr967ZB9cn5s5obFLEHPeKIfnj+ikoOJUf1IpVKII8cDVvm/75h4Exy5XBkBwXbo6vsE9aqEaY/HOVFcGChmCXrGE/3w/FFJxshEpIE0uBREovR83WdsvAn2XKqB0Vs6IfCNLdo2fo7jFyrhu8XtcfuBE/TK3eS2134BY8VXP0zkEZUc/D7Uj/SWI8TI33gclWqK7aG18fXJjgiTWKJ12RfY96o6ptxpg/sxDlk3sM38aafDYybjMRFRcSSRSGBgYFDUxfhgSV9Uhjif28fvosyw+a+6+GaZP+ISTeBb5xV+OVoHP21qiSev7PTbeVH33FfDOdiISBv2mC+hOMa3fqQy43yreIRHmeHwuco4f9MN9T1eY3avMyhnFw+UB5p7v8KVO+Wx7c86+OtMFfTt/B+quOd0v7wWIaJi03OeV7T1w/NHVHIwEaAfKYwgFqXly77Cki3wV0gVXI0oj6YuQVjQ4iQcLRIBAM3LvsL5txWw+kkDlLeOQx+v/+BeOka+YRTkyfkobXtWs0oEjGE8Lgl4/ohKDolEwsSoHqQyo3xrHwe/tcLBC1Vx65EzWnm/wJKxf8O+dDIAoGXdlzh10wOLdzdBZddIfNH+P5QrE5+3AwWIik3PeeZn9MMLG1SSMTFfQrGHVDbUe5erJ7NDRJDKbPVOBIS8tcRfZ6rixj0XNPd5hUXf/Q9lEpPerxAMiMsDzeoFo1GtEJy66oHF25qgslskvuj0H8qVjRfWk7oAEdFmCHlrhdfvrBD6zhJV3CLQov6rvN/mV4BY8dAfzx9RycB4nI3dat9z6hO4XhdBinJ695h/mWCNg8FV8W+0E9o4Psey1idgWypFZR0DOxla271EsypBOP68EmZfaY7aZd6id7X7KGubKKwnlQHv3pgjJM0Kr1OtEJZqgVoWb9HYKgQiPTv3FQQmlvXD80dUckilUl4o10a9d7l6MjtABKmsit7t46dBtjh4vioevXJAh4aBWDXhGKzMVfdpaCiDX+NnaFHvFQ5fqoxpG1qjUfUQfN7mIeysk4X1JBIR3kaZIyTcCq/DrfAm0gINvUJQr+obvcpYUBhP9MPzRyUZE/MlFHvoaaFpyBcNy6TSvPeYfxZsgz9PVcX9gDJo1+Q5VvxwHKWtUuUvJmrextBQBj/fZ2hR/xUOH6qMactbo66bvFLxOsoSodGWMDKSolzZOLiUjYOjfQIOn6uCszfcMfzz23BRJPGLSa95XtHWDyseRCUH47EW6kl5xTLFsDGZP4U72HLTYz3T41g7/BlcDQHxtvB3DsRQz39hWTb7pIKxgRTdKj1BmwrPcTCgKiada4cGTq+RJjHA6wRLhMVbwtQgA+WM4+BiEgdH4wTsjaiJ84luGGr+D8qYZl6ALya95hmP9cN4TFRyMB5roWnIFw3L8npHuUwG/PesDP48Xw0h76zQuelTfP35DZiZZmS7XSmTDPRs8xDtGz7DgbPVMH5FBzSuEYykVCO8fmeFsEgLmJdKRzmHOLg4xKGsbQI2HfJGpX8jMajTHdhapbx/L8Wg1zzjMRFpw8R8CcWKhwa5GIddKjOCWKx7jwCZDHgQ6ICDp6viZWhpdPQNwMjet2BeKrPyEqxlQ7XlpZCBno0fon2tZzhz3x3mpuloU/M5ytnGwdosFSLX9+t2bvEUh89VwdQVrdGxeQA+afMYxm+kQLAIaFy0lQ82ZImI5HjrvAarlBLwOZDC6H2PecU2ygl6RcI+8zVZJHAn2hEHg6viTYoFurg8wbdNrsLUUJKrIloYp6Nf9f/g5xGIc0FusLZJRQdxIMpZxsEqUbV+0FESgAPB1TDpn3b4tPxjdKr5FIZimfxCg/pdAIWMd7AREcnxDjYNcjEOu3wom8z4FwjAM4f1pcCtR87483w1xCWZoGuzJ2g14AWMjaS5KmJpi1QM6XIHHZsE4MKdCqhkFYWOTQJQziEOFmaqFwr8Gwfit1PVMWFlB/Ruex/tGjyDWIxikZxnYl4/zC9QScbEfAnFioeaXE6OKpUZQyRLR1yCMeISTRCXYIL4RBPEJxojLsFEvuydCeKTTRCfbIyYJFOIREDXtk/w3ZArMDGWaE/G66C0eSq6N3yc9YVgAOXlvxoayvBp28doXCcYm/+oh+/mt8ewNrdRo3x43g+cT5gI0A8rHkQlB2+dV7Mq87tNKZmeHanMGJClIybxfcyNSzZBXLIJ4iNNEJdigvhUY8THmyAuzQTRKaYwMZSgm+djtCj/CkYGuUsAqLN3ScZnLo/eL4gCYAKViwPGBlL0rvcATT2DsfGuNy6dd8Xw2rdRyTaXXfwLAOOJfnj+iEoOdlxTk8vJUeXxOBUx90wQl2qCuIsmiM+MwXEpJogzlbeX4xJNEJ9kjOi4UrA0T8UnLR6jSc1gGBrolxh3tEtEzzYPs12nlEkGBnW6C9/aQdh40BsX7lTAsG634eYUq9ex8wPrg/pjPKaSion5EooVj7y787gs/jrfDCkZjgh6aQmrUqmwLJWa+TNNeO7sHC8ssyyVCmebeHmF420BF1CR8M9M0DsmJ2Jqx4u4/KQ8VhxrhDpub9A/2QRWrVMLuCDasUeAfpgIICo5GI+VrFL7XssmOS+TATcCXXDicVPEJZvhTVgZWGXGYqtSqbA0y/zdNBXlSsfBskIqrNJSYWWcCieLBBiINSQAtPW4zw21HvrKylvFYWazszjzyh3zrjVD03LB+MLCCGbd8meyvLxgPCYikpNIJDAxMSnqYhQPuUjKy2TAxTuuuPCoId5GSBAT6QYr01RYmshjsKVpGixNUlFalAJXi1hY1UiFpXkarMxT4WQXj6IIQRXLRePnkadx/JonZmxuibb1n+OzNEOYVs9++JyCxPadfmSyoh+OiKigMDFfQjERoETH3vIx8SbYfrAOHjxxQP/2wXB3eg4Xk4vFcnJVACo98kUioFnVYNRxe4NdF2vh2+1+GPHaBQ36vy6SorHiQUQkJ5FIYGRkVNTFKB4UCXFbtWVqSe6IhFLYeqEuXoWXRj+/V/BweIuypv/otm9d5DYZr2l7LccTi4C29V7Ap2oott+sg28P+GF0eFnU+rKgr9prxh56+uGFDaKSg0PL5d6bSHNs+ssbEbFm6Nv8FTy8H8PeQMNd3ercCrxoOTIwkKFz0wA0qh6CLYfrYcKKDhjT0x5V20YUSXkYT/TD/AKVZEzMl1AcyiaTDkl5mQw4e90Nu4/WQqOKIVg28G+kGNaCDOLim5TXwsI0HV+1u41mVYOw5HATGHjdhre3d6GXg4FTPzx/RCUH43GmmTl/p0llwImHntj3b3W0qvkCYztdRyyawkSckvP+8zA5rLCdNuoXDbTtX8M+Spul4psW13EryAnLzjXGd00ewsvLKw8F1A/jiX54/ohKDl6ozKRDb/mMDBEOXaqCvy5URacmT/F9i8cID2oPU5kO8RiQj0EP5DgOvbCespy2ySX70smY1O8yLt11xYKdzfCjx3N4eHjk70F0wKFe9cMe81SSMTFfQvFWPQBXMwNfee2rvH5riY27vJGQYoxJnS+jinMkACApwxgGouRCKGTBqFE+HBO6XMGS5bPx3Q8/F3oygIko/TARQFRy8A42ZE3Ka+gl/zLWGhvu+EBmAEz3Ow/3SjEAgOh0pclfc6JvT/ic9qec/NfxWD6uYRjV7CYWz/sB02YuK/RkAHvoERHJMR5Dp6T80yBbbDjoA4tSaZj71WmUKxMPAJCKjCCW5XJoNvUEvaZEvLZtFPIhUS8SAb51giCViTBvxjjMmLcOLi4u+u84F9i+0x/PH5VUTMyXUB99xeNq9l/a6RliHDxQFUf/rYSu3k/Q1eeJyoQ0UhjBCEU/SYw+apQPx6gON7F4/g+Y1v0CPMrGvH+xccFecWYigPJVGQDGOq5bugDLQZQHH/2t8zn0lE+RGOCPB1449dIDPas+gJ93oMp4tFJZLhLz+rDL/BmZw3p56Jlfv24okozvYt6scZjZ6yycbRPev9iwYOMxe+jph4kUopLjo+84lENSPinFEHv+rokr/5VHnw7/obX3C9V4DGOIkZa3Y+uSkNd129wk+dW0sHyFxFpGmDNtBGZ3PAN7i+T3+6zEeFycMR5TScbEfAn10Vc8svHwmT027fWGjXky5n1xGk42CVnWkcqMIRYV3WRt+aV+xVAktbiLeQd9MfNztWRAAWLg1A/PH1HJwVvntbsTVRabAr3hahOLxa3+B3uzZECt6iKFUcHHYzu133VJzudSi+qvkJhqhNl/tMDs3mdgn1E4d+UxnuiH54+o5PjoO65pIZMB1x+4YNuRuqjmHo6l3/yN0papWdaT2hlBHF4M2sf6JPkBdKweiIQ0Y8z5X3PM6ngWVqZ5vNiQS+y4ph/GYyrJmJgvoT7qiod6b/nMSVITUoyw62It3HzmggHN76J5tVdax5CXJwIKJ0gLQrQsL6ffblt4vUJiihFmH2iB2b3OwN4yWX6OCrDXPCse+tH9/OlaOeGYfERF5aOOx1p6y8dkmGD74zp4GOuAwRX/RcNKr7OJx3r00MuJXTbLc0rO50HHeoFISDbGnN+VkgHHRYB/wcZjNmQLwfEczrHiYk4B3yFBRNp91B3XtPSWj4gpha2H6+LVm9L46tNbqFvljdZdyO9gK+T2cQH5vM5DJKQaY+7/muMnv3MwQ4b8HBVgr3nG40Kiw3BNBX13BFFufaSRqeT7aBMBGoawSUk3wMEbVTB2mz8yJGIsG3gCLby0J+WBzMS8plvnQ6A9gZ5bIWqP7NbTU8d6gWjl9QJzDzRHXFLmmCA5DPejD96qV0jy8/NIRAXio00EaEjKJ0kM8fs7L4wL8IN5RhqWeZ9AI/vXEEVr302+DWVjp+GR0/oF4POqD1HL+S1+/p8vktIy+8fsLth4/FF+/vKJTomU3aKchzfKy8TERJTvPsr2iYZEZXySMXadqIkJKzvAyT4BS775O9ukPADICmtouUIgEgGDGt6Bi3UcFl5pirT0zDipS1I3j9hxTT86xWNd/34F+Hcmygv2mC+hPsqGmFqiOT1DjJP/eeDPG9XgUSY66zjrgNakptTECOK0dO0djZW3y0uP9twmU0PyeBwlnzeW9wz4+U9fTP/sPMxMMvTbYTbYI0A/Op2/EKXXFZ8nrZ8REdhrnqhofJQNsbEilcR2itQAJyI9cTiyCrzMwzHb/SzKm8ZproUqJobN/CmFsW53sBVEIl3ffar3uo96nwxYfaEBFp5uiik+F2FsINXzQNoxHusnV+dPw6TGWV6/LmKveSIqPGoJyKQUQxy5XBnHr1RC3SphWDD6JBztEnXalVRmBFEJScwDgFgEjBp0E4t3N8GyXxtjQp8rKnPO5Td2XNOPTJbPf5sCvkOCKDfynJg/efIkTp8+jUmTJsHW1hYvX77E0aNH8fbtW9ja2sLPzw9Vq1bVuK1EIsG0adOy/HNNnToVlpaWOH36NK5fv46GDRuiTZs2AIANGzYgIyMDo0aNUvlCO3nyJJ4/f44RI0bk9a2USB9lYj5ThkSE8w/d8Md1L5S1TsCEzldQ1UXDPenZJMelogK8db6IiETAoJZ3sPpEAyw81BRTPr0I4wIa0uZj/vzlhxwTAUpJ+fhEY9x9UhZJyUZo7vMKpiYSLQl6JudLKsZjKlbGvv9MpEvFOBXtgQMR1eBhGo2pFS7Ao1SM/EUdx2mX38GWQzwuoN7tBUUsAkb53sTiE02w7FZjTKh/BYa7RUDf/P+O/igvDBWmVSLhsxyTYoK7dxyRYSaGr8crGBtquODC5HyJxnhMxYpSUj4lzQAnrnni8MUqqOYejlnDz6J82bhc71LkCb3HeC9ODA1kGP/FVcz9pTnWH/DBqB43IS6ghC0vlOsv2/On9HmPijXFnQBHGBjI0LRmEAwNtfw9mZynYiJPifnIyEhcuHBBeB4bG4tt27ahZcuW6N27N54+fYpdu3Zh/PjxsLXN2vJKSEiATCbDxIkTYWJiIiw3NzdHVFQU7t69i/79++OPP/5A3bp1hX0EBwfj9u3b8PHxyUuxPzof1Rf/VRGkUuDyE1fsu+YFC9M0jGx3EzVd32UdskaH3upSGEEs07FHQD70Zi+s44hFwKj2N7H4cBMsP9oIE7pchUEBJOdZ8Sg40isiPH9rg3+jnHDnsSNevi6NKu4RMBDL8NuJGujU4in8mgXCzDTzjojC+GxSkWE8puIoQybC+WA3/JHshbJGCZhQ7gqqmudi0HalXvMyM0OIoOUOr+KekM9mrHrDGBnG17+KuVebY/2/PhhV7ybEBZCcZw89/WRXn5GsFCMgzg533jri37dOeJ1gCS+7cKSLDfD7P9XRpeYTtKvyHCaGEtUNOaxNicR4TMVReoYYp2564M9zVeHmFIOpgy7AwyWmqItVPHjKfxgbSfF9/0uYubklfjlWB4M73YGoABK2vFCun+ziccZjMZ68csC/Tx1x56kj3kZboLr7O8QnmeD3U9XRrfljtPJ+CSNNF8yJioE8JeYPHTqEmjVr4p9//gEAPH78GFZWVmjVqhUAoHHjxrh69SoCAgLQsGHDLNsnJCTA0NAQ9vb2WV5LTU2FmZkZnJycYGZmhtTU9zOClypVCidOnECNGjVgamqal6J/NPL9Vp9iTPa7CDdTnfHblRoQi2QY0PwuvD3CNI8hr+MQMiWix7ym91ous2dA56uYe6A51v3PB6M63IQ4n5PzH29iXtN7zv15VT9/cXFxuHPnDu7cuYO7t7vC1CgDddze4NM2j1Cj0jt5L3kAz4NL44+TXhg9uxM6Ng+Av28ALELSlZLz7DVf0jAeF38fUzyW9hXhill5/J5QHRbiNIx0voma5houkOeCLEUEUQn9iBkbSPF9w0uYebkltt+vg0E17ug8pbeuPtp4rGky1jxMsqt+/qKjo4V4fO9mV1gapqKO7Rv0rnYfXnbhQhL+cbod9t/1wl/3qqJT9afoUO0ZShkpXWAq4El/P3Zv3rzB/v37hfgXGxsLY2NjlC1bFrVr14a/vz9at26dr/8bjMfF38cUjyWPxTj3jzv+OOuFsrYJGP/FVVR1029Wc1m+R6jiw8w0A1MGXcT0Ta3wxxkvfN7mYb4f46O9UK5pPPd8uOgREREhj8eXpuO/Z91ga5WMupXDMKDjXVRzi4CRoRQyGfDfszLYf9YLB85VQ1ffJ2hb/zmMjZQS9Ow1T8VArhPzDx48wLt37zB48GCh4uHj44N69eqprCcWi5GWpjmxmZCQAAsLC42vKSocP/74I6pWrQonJyfhtfr16+Pu3bs4deoUOnfunNuiU0mwL+sX++7/auLGWxf0avIAjSsHQ5yHHvLqZDDQ3kOvuNLlfWauYwwpvq9/CTOvtMT2c3UwqGX+JgM4lI2SEBFQTsdgHyICygHSiFYIikrAo6eJ+PeRE4LfWKGqUwTquL9Bj55v4GwT/z7R9Q5AefmvHuVjMGnIFbwKtcb+k9UwZm5HtG/6DJ2aP4WVRVpmgj5/Lh5Q0WM8/jCU2EZYv6zva6PEGwFxdhhgfRfeJmEQaf5o6San8bqLe295dVp6SZsZZWBK44uYfrEV9htXw2f53Gv+o03Ma5KbZHhmYl+CzngW8RL3XwF3XjkiLMESXlbhqGsbhi/qvIFjqcyxmdU+q1XLRmJq+4sIDLfBH3e9cPh+FXT0CoC/VwDMjDNUjqGCyXq9hIeHY/Lkydi1axd8fHzg4+OD+vXrw9LSEikpKYiIiMDjx4/Rv39/mJubY/78+ejRo4fex2U8Lv5K9HehhsTnst8aIyLaDCO730TNivpdIP9YWFuk4sfB5/HjxtawMEuDP/I/YVtiP4PaaJtkNTfJ8Mx9ZET3wuNH/+K/p6a489QR4TFmqFHxHepWfouBHe/CwSYpy6YiEVDL8x1qeb7Dwxf22H/WC3+elyfo2zV4BlNjifZyMllPhShXifn09HQcPnwYXbp0gaHh+00NDAxgYGAAQJ6Qu3v3LqKjo1GzZk2N+4mPj0daWhpWr16NmJgYuLi4oGvXrrCzk7eyBgwYoLFyYmRkhE6dOuG3335DgwYNUKZMmVy9WSp5nkeXxunnHljc/n+wM0t+n3PMQzJemQyi3CWqczPMjD5lUz6Onu/RzCgDUxpexIxzLfHtqw7wuVQL9bvtQ6VKlfROqpfoyq8GSUlJiLjvhIgYR4hEgI1VMmysUmBpngqxGDol52MemeLu4wr4d6cj4tJ8kJbyDu6O9/BZ+4eoXuodTI0k2jcOVn1aoXwsxg+8hpA3ljhwqhrG/NwRbRs9R5dWT1C6WqqGHbAn/YeG8ZiKm/tSB9yWOmOZ0QlYmOYwFJyO48sLckrSFwXFBLV5obadtUkqfmxyHj9daoVroeXg87IG6vf+Cx4eHnrH0o/tQnliYiLCz7ggIt4JhmIpbCxSYGOeDItSafKOGzqM7x71Ryncee2Gf0OckGpdBwmR5qhs/Rh9vf5DNbtwGMeq3Qqv6bOZ+Zn1dIjG5LaX8TyiNA7crYbR+zrBr1ogOlV/CguTkjOJYnHwzz//oEePHvjiiy/w6tUrODo6Zrv+iRMnMGvWLJw5cwZr1qzJ83EZjz8MH9MwIjceOOPFaxss+ebv94lH0ol96WRMG3wBMza3xPl/KsCnmhd8OhxDhQoVPqq2rb5kMpk8HoeWRmRsKRgZSuXtY8sUWJRKk18o0iE5H37DHP8+9cCdp46AeQ1Ev0tFdbdnGNz5X1StEKF97HgNvNwj4OV+AU+DbLH/rBcOnq+Kzs2eokNDpSFgiYpIrhLzZ86cQZkyZVC9enVERWVtjRw+fBjXrl2DRCLB559/jtKlS2vcj7W1Ndzc3NCkSROYmJjg77//xi+//IJvv/1WCJjaegzUqlUL165dw+HDhzF06NDcFJ9KGIlUhI23vdGrxn15Uh7QO1mtl8Icaz6fWJumYlH7/+FxhD1uxTlj5aLxSBM5w9vbGz4+PqhZs6bKOJe6yi4xn5CQgKdPnyI5ORlSqTRXD4lEkuM6BgYGKFu2LJydneHk5IQyZcoIDaO8kMlkiI2NRUREBMLDwzX+TE6Oh611M9iXll+pj44rheg4U0gkYlhbpsDGKgU2Vk1h4zwINjY2wsPIyAgPHjzAnUubERLdEV4Vw1Gn6hu4uT9GOfsHsCr1PEvSXSeZ25RDPMb2u4HQdxY4eLoqvvnZH60avEDXVk9gWzpFdRuORf9BYTz+MHwst82nycTYlOGNAQZ3YWFXAMlGfZPyytvnx/jeupYnF6MG2JslY3mbE3gQ6YBb0c5YPPsbSE1chB6/1atXh5GRUa6Lml08jouLQ0BAAFJSUvItBis/DA0N4ejoKMRjBwcHvRJjUqkUsbGxKjFY8bvieVpqImytm8LePAlSqQjRiaaITigFqUyE0uYpsLVIRukLi1RisY2NDQwMDHDv3j3cvbgDb+L9UcPpHeq4vEH5ik/hZnwBZngjL4TS/Ae5+Vx62MdgYpurCIqywoF71fD1Hx3RvsozdK7xFFamSj2oOcRNnp09exYHDx5E7dq1dVrfz88P7dq1w6xZsxAUFARXV9c8HZfx+MMgkUg+isR8Uoohthyuh68+vVUwSXl9J34NyOa1SnruO5+4OMRjzcSj+O9ZWdx85Iy5c+fC2NhYuAunWrVqKhfh8kNMTAwCAwORmpqabzFY+WFkZAQnJyc4OTnB2dkZdnZ2esfjmJgYlTisHo/T05Jgb94YdvZJSM8wQEy8KaLj5cNt2VimoLRlCmycFmeJxwBw9+5d3LmxF1Fx7VHT8y3qVQ2DY/lAVHY4DWODeL3OdWXXKPww8BICQ2xw4Gw1HL7YEf6NA+HfJAAWpZTqsBzihgqRzt8oERERuHLlCsaMGaN1nVatWqFBgwZ4+vQp/vrrL+EfX12lSpVQqdL7b97evXtj7ty5CA4ORoUKFXIsS9euXbFy5Uo8ePBA1+ILQkNDkZCQIPRiyO7xoQbvj6W38vFATxiIZGhf8VlRF+U9XZLz5VC0FxDUGIplqFEmHDXKhGNgxbsILmWFW88uYf92F6yIsELNsm9Rv0Yo6rmHwdpMqbd1NmPSK/dKiY+Px6NHj/Dw4UM8ePAAoaGhcHNzg6WlJcRicZ4fhoaGGpdLJBIEBwfjxo0bCAsLQ0JCgkqiXvG95OzsDGtra0ilUkRGRqpUJNQrGADg4OAABwcH2Nvbw97eHp6enrC3t4dDcH3YWiTDoIJM7RwASSlGiH5iiujEUohONEWMfVlERUUhJCQE0dHRSE5ORtWqVdGryQN4lQuHiYe8Av06piLEonyanCYYcEYCRn1xCz3aP8LB01Xx7QI/+Hq/widtHsPeRnFRKxdD7lCRYjz+cEgkEr0uDH4oDkiqoYwoEc3EQfm308ykp0jT3Ty6DmOjKXGqWJbXBH0B9tw3MpCiTpm3qFP1LYY2+hcvIkvjVvAl7F7vgnfx5qjt8gY+rqGoZx4GC2OlxmMOQ98o6oSxsbF4+PCh8Hjz5g08PDxgbm6er/FY8T+bnp6Oly9f4sqVKwgLC0NycjIcHR2F7yPleGxpaQmJRILIyEitjfyIiAgYGBjIY29mPHZwcEDVqlXlsdmwHmylyfI71ZQuishkQGKqEaITSmUm6p8h2nY5oqOj8erVK0RHRyMtLQ3VbU+gf4M3qFY1QpggLiimFkRSpXicm6S8hvVcbeMwruV1hMRY4s971TDmj45oU/k5upR7ChvTFPn6H1lyfsOGDdi0aRMOHTqUJU4NHz4cYWFhOHz4cI77mTBhApo0aYI6deoIj1q1amU77rqBgQFmzpyZ57J/TPFY+f/8Q/SxxOO9/6uJau7hqFvlTb7vW2M8zo3skvKaXs8uUZ+bdfPA2EgK76ph8K4aBqn0NgJDbHHr0QVs2+CM6LhSqFslDD5VQ1Gn8hvV3tY6JnKjoqJU4nFERAQqVqyIUqVK5TkWGxgYwMjISONrqampCAwMxMWLFxEaGoq0tDSVC+eKWOzk5ARLS0ukp6cL8VhTTI6IiICRkZFKLHZwcICXl5d82b3aKG2W8n6I4cyJdmUyICHZGNFxpoiOL4Xo+GeINl6G6OhovHjxAjExMcjIyEANl6MY1i0MlV0jYWggP6fPY5rq/xlU4lkuGpP6X8HLUGscOF8NYxZ3RIdGgejUNACWZpkXzJmcp0Kic2L+4sWLSEtLw8qVKwG87wW2bNkytG7dGq1atYKFhQUsLCxQtmxZBAQE4J9//tFY8VBnYWEBc3NzxMbG6lQWR0dHNGzYEEePHtV6O6A2Dg4OsLCwgEQiER7p6elISUlRWSaRSCCTybL0dhOJRMIXn6bEgbblhVmJ+RhuW05IM8K+B9Uxq9XZrGPKFzVF0j27BH1ukvPK+ynghL5IBLimxMHVJQ7dXR4jKtkUt0Odce1eOWw5XRfupWNQ3+U1fJxD4RyidOI/f/9/EhcXh5CQEJw/fx4Pr/6KsHhLVLSNgpdDOPpXCEflepEwNczHHhwyAJLMh+JcOQKoI/81IcUIb2IsEBplidB3lrj32BJ/pzVDWFgYRCIR0tLSYGZmplKxKFeuHOrUqSM8t7Ky0n6xKzZzPLtgCGO9A/JzaR6RDnO7dJSzU1zZ7wZ0VQvu+0Tvy63oHZ8uBgykQH7+GwcDZcsnYkTP2+jR7iH+OlMVExZ2QKPaIajmEQ57myQ4RFrArnpMvvcCofxVUuKxvb29kIzLbTxW/D9qi7vZxeXCvHCtuIunJIuQlcIxaSUsMjpZfMaw1SVpqutQNNntKy/D2ei4vkgk72XtYR+DnnUfIjzBDLeCnHE+wA0b3vqgsm0kfBxDUd/xNcrsVjrxSkn6mJgYhIaGyuPxpf14l2qOypaR8LIOxxDXcFSqHQljAx2GZckN9e1dAHjLf41PNkZYtAVCoy0R+sIS/96xxFFpY7x58wYGBgZITU2FhYWFSuLd1dUV3t7ewkVxS0tL7f/DUZkXmqOgcvFGBMAC6bCITEd5+7jMpZ8Cn6jF4+sLs+xSZiaGyFAGxKi9R13/7srrKZ2bcqXjMab5DbyJM8efN6th3Gk/+JZ7hUrlo+BgkQj7381h1yOuxH9/hISEYMeOHRpfO3bsGP79998ch6RR1qlTJ9y9exdLlizBs2fPIBKJUKlSJZVkfZ06dfJtuJeSHo8Vd7fmRzzWFJMLOx6X9PZxyDtLXLzriuXjTuT7vmUyqH4P5kZOCfn82C4ABdbjXiyW97Ku7BqFPh3u402kOW49csbf1z2x9kB9VKsQAZ9qofCuGgp75bHKlRK6kZGReP36Nc6cOYNHd/9CVHwpVHGNgJdbOL7qHA5Pl6hcDcuiM8UdDoYAKgLoIP9bxicZIzTcEqER8sfNJ5YIjWuAN2/ewNjYGCkpKbC0tFRpH7u7u6NBgwbCMnNzc83/w8dFgLmGcnjK6zaWZmmwNEuDq6MiHnfPmvwOmJ9ltzKIIcqvjmtK3JxjMf6Lawh+a4UD56rh68Ud0cr7BTxcouFQOgkOMWaw9U4o8d8fVLR0zr60a9cOvr6+wvO4uDhs3LgRgwcPRlBQEPbv368yeY5IJNKa3Nm7dy/KlSsn7C8lJQVJSUmwsrLSueDt2rXDvXv3cOvWrVxVroyMjGBmZqbz+upkMlmWCoriIZVKkZqaqnG5ohKj/uWlfIVTWxJB0+vZVWQ+hoqHsYEE5sZpiEwuhQqldauwFrqcEvTakvPa1i+CXva2pVLQruJztKv4HMnphrj7tixuhTrj4OOqsDJJhY9zKOo5hSH26lWVHnjt27eHRdBSDKrzDpVso2CSn4n47Gi4Y8HCNB2ejtHwdIxWWnoNUhkQE2iKUoYZKGWkNq6cHeQJ//DMh66yG3ZG8ffTMIGxernlcxxoqJzl5jOg6XOUefHAPiEZQxv8i0+9HuF/9yri1i1nhMeZIyLODAmpX8DGPBkOlklwsE6EvWUSHKyS4OCRCHvbJDjYJMHEWKL5vWZzFwXln5ISj42NjQssHkskEqSlpQkxWHm5Ytuc4nF2MVj5eXbx+GO4dd4M6TCCFDEyU5QVJeZtJ+rJXOXn6p1ds+stn9uksqYhbgqiR3xukvdaju9gkQR/r0D4ewUiMdUI/z5xxK03zvj9cXU4mCXCxzEUdcq8QcSlS0I8joyMRLt27WDzdBmGVwqHp2UUjMTS7O8k0EcO+7AslQbLUlGo7BwFCHNXXoVUCkQnl4K5cZp8PhX1/cgASCGf7Pyd2nFyU27lz04k5OPN50AGMUSQZk3G5+XOCw2fMceMRIysews9qjzEyRcVcT3ABRFpZghPMEfS/t6ws5DHYHurJDhYJcLeOUmeKKggj8nGxlLNZfD8MOLxokWL0K5dOxw5ckRleUJCAlauXImOHTsKk6nqYurUqcLvN27cwCeffIIaNWpAJBLhl19+wePHjyESiVC2bFmEhobqXX7GYznleJyRkZEl7irisXpMViT4NcVjXdrFys91iccl/UKXRSl5L9/4JBOUttQ0p1TeyZ4ZQCTOQ3sur0n5vCjA5LwyR7tEdG4WgM7NAhCXaIx/nzrh5iNn7P67JpzsE1C/2mvUrPgOb8Mu4MGDB3j48CFiY2PRrl07OBouR+vPwuHhEi30BM932Q03FCi/WG2FNFh5RqKqm/KYe1cgkYgQHW8KS7M0eXtP074j8qFcnmqvaZskVoUI8spAwShfNg7f9LqO0AgLnLrhgav/lUdEjBnCY8yQktYTdtbJcCidCPvSmXFY6Xf70knCnXZZsMc96UDnxLziar+CoqGpGCfv5MmTcHV1RcWKFfHy5Us8e/YMbdu2FdbPyMgQKiJVqlTB0aNHUbZsWdjY2ODkyZOwtbVF+fJK3U1zYGZmhvbt2+PPP//UeZv8IBKJVCbz0YdyJUa5kqL4XbnnoPrriqSCeo9+sVgsTLYRHBysMaGg7eeHNPyNsYEUfWv+h513a6NW2bcwFOfzjOn5ORFmdsPbfEDjepcyykCjcq/RqNxrSKQiPIm0w83XLth02xulH/wAr5ajMXToUHh6euLl/8aislnub6UtTOLX8gsPGuly10Nu6JJQV/mciJGl4pHbCzPa3oNSQt3WIgW9m6j+nVLSDBARb4bwOHOEx5khIt4MD0McEPGwAsLjzRCdUAoWpdLgYJmYmSiQJwscrJLg8K407NuEfDTjahcVxmO5wojHiuc5xWP1cimG81IkJBRl1RZ/c5NcKG7MRBnoafAA2yW1MUd0Jl9v9MnVN0l+9/TOzXZ56T2tRxnMTdLRrFwwmpULRoZUhIcRDrj1xhnr/q0PhydT4NVmHL766it4enri+f6vUdn1Ufb7L6hzZwft4+wrJbbFYsDOPFn7vnIzdJHyGPDZya5symRK8VhTMl7bxK/ZlVGDMmZJ6Fv9P5V1ktMNEW5ghoi49zH5fmAZhMeYIzzWDLHxprCySIW9tTxB4GCjlCgIKw0Hb/0TzwXp3LlzePHiBb799tssifkNGzagbt268PHxyVViXtnIkSOxZs0afPrpp8KyY8eOYfjw4Rg4cKBeZVdgPJZTjsfGxsZ67Uv9orv67+p31inHbk31T5FIBJFIhPT0dGFdTXG3JMTj0pap6NLsKXYcr42pgy7m676lMIIYuZhDpjAT8kXIyjwNLeq+Qou6r5CWLsb952Vw65Ez1uyvDye7qfCqPxHt2rWDu7s7nt0ajcq2T3TbsabkunoyW5dtdFlfab8GBjLYl07On/3ndOyc3o8amcwgf3M0WjjbJ2BAx3sqy5JSDOWxN9osM1lvjjsBjgiPNkdEjBnikkxgbZ6iGocVyfu31nDwzv+hpahwvXnzBvv378fVq1cREBCA2NhYGBsbo2zZsqhduzb8/f3RunXrPMeMfBmvwMPDAz179sSZM2dw6NAh2NraolevXkJF4u7duzh37hy++eYbAEC9evUQHx+PAwcOIDk5GeXLl8fAgQNz3biuX78+bty4kR9voUjkZ1IBgNArPz4+HlFRUbCzs8tSmVFMKKJekVGuzGgbvkdT5UWXZflaqVEaMqWJTIbjo9rg1HMP+HkWo3HmNSmsiWHVKZKwutfpdWIglsHLIQJeDhEYiLuZS88DXjJ5j/BSI/L3gLmhy7nWNcmdHwn63CTUM8su9NDL7fbZHV/H92BqLEE5u3il4XdUZUhEiIjPTBTEyxMFL9+Vxs1nLoiIM0PEr8Ngb2+P5s2b61lwygvG47wpqHgcExODhIQErfFYUyxW7tWvXkYAWuOtetwt8Hi863352kok+LtPR1yWusIXeo4zr5S4lNkYQpSqQw+9Ahz3Pc8USV9dk/Z5fA+GYhlqlXmHWmXevT/e64tAdxmwSgSUGaF9//qct+y2tdPyu4JyQlw52a2+T03b6lpmfecSyCSPx2qJgJwS/7k5r9lcLCmFDLgiDq6K4XfsVF9PSxcjMsoM4a8yEwXR5ggMscW1++UQHmOOyDVDUKZMGZUe3cVFSkoKlixZggkTJmRJ5AYGBuLw4cP4/fffcf369Twf49GjR6hTp47Kso4dO2Lt2rVYtmxZnverK8bjvCmoeBwREYGMjAyULl06S+xNT0/PNh4r9qNezpzaw9n9nq/xWKlHbpcKaTg1ujv+feKYf+PMBwJSGOuemC/KpLyuveZzmRTWhbGRFPWqvEE9lfN+SX4HU4AIMnyV805y6O1eIDQk6Avl2LocV4kMogIZykYXZqYZqOAYiwqOmkdqSEsXCwn78Bh5TH4abIcr/5XHu2hzRK0aBEdHRzRr1qyQS076Cg8Px+TJk7Fr1y5hAuj69evD0tISKSkpiIiIwOPHj9G/f3+Ym5tj/vz5KnfK6SrPiXlbW1vMn/9+7KfatWujdu3aGtfV9FqLFi3QokULnY83YkTWRJ9YLM52sp2PjaJHgFgshomJiV63JCpT9FzQVFlR7t2vLeGvnPRX7uWvqIyoV2y0VV6Ue/YrXus/bh0Wz52Mpq5BsDTWobKgNg64xverz8nKTmEm59WHGSmgBH0WmoZpKQrZneu8JLrzuwd9DseSmYghSpfl7916+fT5MzSQwbF0IhxLJ0LTOD/ShhIEBQXh5s2b+h+MdMJ4XPwo4rFIJIKpqWm+x2NtsTi7BIPiodiPtnisLfbmtKzf9/OwecEM1Je9hqkoF7e7Z5PElMIIYpFSbNe153Rhy8tY80Utu+GD9KHL30ixjqYEfW72o0luhpzRode8PBGg4fOcT4l/jXK6ayDzdWMjKZzKJsCpbILGckjcMxAUFIRbt27lX9msoHtFOZsRWLZu3Qp3d3e0bNkyy5AyCxYswKBBg/QeB75+/frYvn07ZsyYobK8Zs2aBZa4ZjwufgorHmuKy4re/TnFY/XyAsgSc3VJ9CsefQZ8j52//Yyann/rP1xKZvJU3mM+Tb99FZZCGtJGZ7oM01JQSffc0NaLvaDLpnPveRHkk8oVP8ZGUjg7JMDZIUHj6xnu6Xj16lWe7wCjovHPP/+gR48e6NOnD169epXjnDcnTpzArFmzcObMGaxZsyZXx+IMfyVQfo+hp9xzwcjIKN/2C7zvxaCtwqJcsVE8l8lkwnJDQ0O06dgL51O9UNlatXWlOk63DOLYNIjLpEOckg6xdRrEsjSIkQaxLF3pZzpEMinSRFZIEFeAGOnCcvn66RAhHXlOPxdVz/nCoHwxoHKRleI99XOdH2P0q+9D/W+ZT/MAyCCGSFYAFY9CuMAgFothbW1dcAcg+oAUZDzOb9risXpsVr8Qr3hYW1ujUafPcD7OC+5GMfKdZo4PLxOJIFJcBIAUIpN0iKWZcbeUIganwcA8DSKkwwDpEFmmQZphjHSpFRIkrhDbpEOckQ6xSPFIgwgZxWfCWX3kJSmu6WKA8vNVItV1sztWYSbl1dfXlBjXtp/c9JZXPzfaLp7kmJzXMLSctjLlR5Jex6S8LgwMDIQhVYqToKAg/Pbbb9i5c2eW144cOYLIyEj07dtX7+MsXboUrVu3xqtXr/Dtt9+iRo0aSEtLw5IlS2Bvb6/3/unDIpVK87UdWxjxOLtYLJVKkZaWpvE1JycnVK/ZFBcCa6KcQ5zqvpXaxyKRBGKRvG1rIEqDSKT6U/wmPfP1NKTDEqmwRgJc5TEb6SoPETLy3j4uCvr2Es+vHvfFISGvTDlJXphl0yE5X1hD2RQEQ0ND2NoWx9s7KTtnz57Fn3/+meXuO238/PzQrl07zJo1C0FBQXB1ddX5WEzMl0Af0uSvyr38tU2GlJMHDx4g9M4JdPbWfgVSBjGk74wgFRtDKjKGxMwIMhhDKjKCFEaQiowhhREkIjOkiyyQITJHrKFX5uvK6xlBlvlvI8usfigChPpzsUxeSVEk90WKJP+7dIht0yFGBsRIg0iUuQ4y5OuIlF5DBsSiDIheK17Xs9Kjwx0D+UFWXKpmBT1hboHtX4wCvHejcO8AIPqI5XcioCDlRzy+fv06Im8fRQfL+/IFGhKsMoghtcuMq2JjSAzk8VgiyvwJxU9zpMjskA4LxEqqQ5psDKnMSOWhiMdIyjpptnJMFovSIRKlQyzOgFiUJo+r4nThd7E4/f06mc9FwgUACcTizFgtypCvJ06HCJLsLwooEr7KCWH1Xta6tNFy0zNbQ/JZZioCEpRe17Tv3MptAj67cdjVE+Pq+87Psf9zc2dDZjlk0QYQWcugcfIE9YR+bsebz2nb3JyLD+iujd27dyM5OVlIvit6DPfs2RMpKSkwNDRE69atAUC4K9fX1xcrV65E3bp1dT6Ot7c3rl+/jq+//hp16tSBkZGR0Klny5Yt+f/GqFj7kCZ/VY7HeXXmTBkkvNuJylWeal1HKhNDKpPHVpnMGBKZkfw5jCANlv8U4jHKIh3WiBVVh0RkDBky28ZQrJd5bmMAWdn38VcRmxU/xbJ0iGTpEEsz28WZD5Hwe4bS8wy19dVfy4BIlhmP1d+crr3m85qIzsMY6SrbFmdFVT5N51S5LGJAFKWhfVwAwxIRAcCECRMAyOe90XSHmiYGBgaYOXNmro/FxHwJ9CFVPPKNxwgA2v9ZRJDCQJYKA0nmDPXZdH5KE1kj1cAeLmnH81wcGUSQwlBeaVFJ6mc+DzeCtEzm6zIjpKMUZDB4XxmCIWQwlCcfYAyZqUHm9gYqyQdNiQgRZIATIJJJIJJJMiswip8ZECdmQGQjT/KLZRlCwl8sU/xU9HqQZC5LV/o9A2JI5PsRLhTIsgyd86FezS4uNI5pWxCULywwSU+U7yQSCUxNTYu6GIWr3Q/ANe29XeXxOAUGshR5LFbcHGSL99cjMxOQSVInAAZwccohHmeTsJTJRJDKDCGTGUEqNYZUlhlbpUbyZZm/K9ZJl5pBlmEAidQ483XDzHUNIZUZQyYzkD+Haj1LBhFEKTKVC9OilMxeiWJJZvzMjKP2Ge+fy9LlcdUi86fo/YV4MTIgkmT+bi2BKDZzHcVrthKIotMhlknex2O1CwH/Z+/Mw6Qozj/+re459mZZ2OVadgEXBOQU1GAEwXhAlBgBxZ+KicYEj3jgkRiDQeOZKF6QQzRGBTRK1Bg1UVFEIcolggfXct/nsgd7zkzV74/ume2Z7Znp7ulrZuvzPPNMT3d1dXX1zLzd33rrfSO2JJnXfKwIfCzOeq0kE9SV7UwllrzWYyRCOTgQ0xbpvirOTaNaSB61NiBJO8yKrW+2975FTJ8+HVdddVXk8+HDhzF9+nQ8/fTT6N69O4LBYGTbkiVL8Nprr+HZZ59FcXGx7mP1798fH330EXbv3o1169ZBEASMGDEC3bp1M+VcOOlDe3s+JoQAnR8DcHHcMgKhEEgTgKboDSrCbC0q4EUturOPEvsOHYq/iYFIz7PEIznFEfm5mHhABS8Y8UnLxANGvAgIuaBEfgYOlzvmBRO8oJ29cjkPGFGxx2gdUI2aJYAYe4wgyHb5nYRtrPI9GFVe+QwsBGSbTWQbLA/gSwP3KomIwdwvyjtNWJzXO0gCcIGeYxl33HEHhg0bhjPOOCNumcOHD6cUgo8L8xlIKBRqk0gpk9GUOEct5nocz3EKLwSWWgw9AgYRAQCB1puXWPt8ANrF0KbkRSLskQ7FIERuYqR3UXoXPGANHtCu4YEDeRAAIijJRoDkSZ+JRx4IkPcNDxZEBghEUOIB6gjQLXyK0o3Pcc8QbIlJABt9U0SlgQMoXpEbnfC2YGSbNChA5XKx+8X/LIkVNGab9BkIL7sRB2LopSLSWz0zgcNJU9qjEBAbL1c3CnGRMi+EvBTtMWEQiWyPxYbU2pYMFTGUHQWYXwQ77mkdsIcnMgDPOijWs7A99oAiBwEmSoMDss1lQuvAPYMoeSnmiGBEWo6Q17p43DcEWzrL9jg8RiTfUzAQCNkhEBICOS6/IyiFN/BI76ROtp9EHpgnsu0k4fUq7x1CIA3ysvwSlPuFX4UhkONhm0xbZyDoTfCqh0QhbVRJEsomvG+SWPVxBXrlOaQawifVfWyiqKgoakp/+D+yW7dubQTzoqIiiKIYSZiaiCVLlmDYsGGq4QLKysriTilfvnw5Bg4cyMMMZDjpNKPcDAzb4ziCKCVeiCnGmCdgEFkLwFoAaLDHyRKhJhNiDyHKa156PhZlO+tV2FtP9DrSaotZ2B5HnoPlZ2LiAd3jAevskQf25edmJoKy6JmS0oA9Q3XNEGwREj0fxzy3RgYEop+XCULywEFs+dhXUHLOUy0Xbz8KOP18HOe6J52Rn8osBg4nAQ8++CAmT56MtWvXqorv69evx8UXX4ydO3caPgYX5jOQdnnjsW0eMDJOgVhRPgmU6Mg6nyoWxZwnkMRvsGaIrFm90E6YE9bmQNtVm3E9+nmejbsLgyCLCqLk6YDwIIAQuRliCIsNYmQ5fDMlDQr45PVyXZHtIgAh4WfJs0IAk10pYmceJCLRjAVJXGAgjCoGAJg82KAQH0Dl/WikrHJ9racCHlYHLzshr2etZRhruy5SF4v+HPXOVLYDkuDApPqYLD7sC29TlotejpQN1x3uh1AIoZA7E/NwOHbTHu0x/fARID9BIR0xzmkHH4SATfbYIgiRbUNRCCLi2GOtFKKtsOtXWadgc+fr0Y8+q+qVLWk2sg1loiwseMCYbI+ZV16WxQb5XfqsECHgA6MiWJ4gfW4Uo/aTXkLcz2hU2OMsAtKgwR5nAewIASEMjIWTFyvsMQmBEAo0MhBC5QSuFIQwkEblYEDY9lKAKOyjvHyipRcON4yWkxDLtjdfLlsn1Q0wkBwK1MbYXRK276z1vQOL/hySyxUCCCjsMZFtbCEFaQFAYuwxUdhjEmOPSfu0x7t27cIvf/lLPPfcc/j+97+ftHxdXR3uv/9+LFu2DJ988okNLeQ4SXsbKAcAdvTXptUlJX9NYo8rTTqYVm9pLUKsIqSN9HwsOWcltMdaHgnDZQ5raAMAulXENuEa9KXPx60u/HzMoHw2Dj8Lx3yOeS5u3eaLPFPHPh8z5XLkWG0/o9W6pPR8HH5vFfyZ4vmYxmxrtcWShqG0p9JyAynFQTK2tUzMszABBbZRkO4q9pcwlc8x9pioPB+H99sJxHsmjiz3VrHH/Pk4I7jtttuwevVqTJ48GZ988klUyM933nkHV1xxBSZMmJDSMbgwn4G0yxuPeBt0ivJA2GPeRiHAyXjfqcacj9O/yYx42KAKyhkFYdI0Co5kegWEBX/pBoi0ft4vbyPyZ/kd4c/dwvsSHBcHIpselEI9gLSWjQwmEERmLMj7SHUTeZug2C96HeRbl7blEb2vXFaqh8Ts23rDpgy8yyAAO3agocFir1QOJ01od/b4gwcV/ycqJItxHvOZMi8EosFDr0qlrnRGS4gULYRD2cTxypY81GV73CmgPY690yRpA2MEjMk2s0qQBwJku8dEsOMK28zCNlsA2iwTeIRTkeXZD1Ig20Cm2F4gAHVEHpzwAPkCWG24bgIwpU2Nsccsxh43xthjRsByBOA4idQVZYNZjD1mQmQ58rk6Pexx9+7dsWbNGtVtEydOxMSJEzXVc80116BHjx746U9/iq5du+Kiiy7C6aefjpKSEuTn56OmpgaHDh3Cjh078O6772Lp0qWYNm0ali5diuzsbDNPieNCKKXtyh6Tmj8DHXTulEAQZ7DRcU0P6eAlvRVg8MiCtDoRpzpQQEs/G3leduAZW/X5OGz3IgMCys+x5Vufjz3sBLJxULE+tiwB4AHdT4BuinpZ2BFP3oclscfhbUcUz8eCyvNx7PIu2R4Xqdhj/nyc9jz//PM488wzccstt+DPf/4zAGD27Nm4++67cc899xiKK6+EC/MZSHsTAhrW/BpAzA21FkE+jihNiReClql64WOYlUw1nkCvN0xIT+gbkNArzhsY7GgPhEf9o0LQ7NZRwU5ErkMWq0JBaDO8rD75fnquhw2Jf1HxAo4fP47NmzfbcDAOx920J495xhgamBc+EufBU0vMcSWdANrokz2V0wS1MClawpwoy6p9Vu6vJW663JcMaA1foyVuuRtE92RoaCMhTPaQD6knbdX69FME+EI1KOy2STVeMAAgGPM5B/oHVJTXJlmCVyVJvwftzx6ff/752LhxI9544w28/vrreOqpp3Do0KFIWA+v14tBgwZh/PjxmD17Nioq3K7occyCUqot/GkGwBhDfZMXnfQK8wkIwQsPNDyXuBGtiWCNosHDn0EEaWMw0pxkMyT6xnk+NogP1ejANmkrvF9+N/IXn2oegKMqx+bPx2lPdnY23nzzTZx22mkYMmQIvvzyS7zyyitYuHAhLrvsspTr58J8BtJehIBNmzZh0dzp2FPbBzeetrp1Q4rCMYUvucf8njjLQOripxPxupMNMujs06Qx4DKZVL5/8r6siwhyhAE9rKnfFoGew+G0i4Fyxhi++eYbLPrDbTgW6o5bCle2bjyG5MlDEyQilTzmNQrzbvGajyfOW3mMOOctCQEh65Kr2oXdbY05XlxRPlw2lUSrRkV5M46doXg8HkydOhVTp04FANTX16OmpgZ+vx+FhYUZ/5/MUYcxlvHCPGMMa9euxaL5v0ZjcxEmnrXFvLqThbIxK4yNEXSGtHGCiD3OBBy61lrD6kShd0aFmcl5eVLajOG6667DiBEjMHz4cDz//POYMmUKunfvjuXLl2P48OGmHIML8xlI2goBXyS4WVKI1ZuOdsKi707BntoC/Lj/fvz6rOXwidQ0T27JYz7BjUey4yi3OyWA6vWaD2NSHxoynLEkaosbhWUTZxIwECmGu1WzE7hAz+HYRloKAfeTpF6/jAHftJRg0YlTcCyUjUl5OzE2eyc8iURMLSiESqrXQ8+oOB9P3DQqCMdL9GkmyY5RBDDmARFVhID2Isqb0P+GHA30zJIIE+88tcw04eJ8QnJzc5Gbm+t0MzgcY1Qm/w9iDFi7uRsWfTwQjc1eTB5Xie8P2QNR1GGPkwiSIS2Oa07icnGewgMhnse8Bs9zwyjrTvXcnRx8QQqOf1rFeTNF+dh6HRwU4qROZWUlFi1ahLq6Ong8HhBCMGjQICxfvhwNDQ0YNmxYyvcZXJjPQNLSIyCRKC+z+WgnLNowELtrOuDH/Te1CvImI3nMxwllo1coTTWGexqSkre81v5NdfDD7FkOZgvoRIAZU/6S0g6/nxwOJwn3J/4PZwz4tqUEi04MxNFQDiblbTQmyBfFWVZAmQ+iUK2vXq3ivBYxM1UvfDtE0wTtY0UihNqAprKuxezBFp3XPamjQbz6lJ7w8UR6s2ZSpON15XBsJu2ejYGkorxSkG9o9mLKuA36BXmNUPjih3p1WLDVhUPifJsY83r6LFxWb7tjj2FWPQ6RkuNfOuQi4LiWTz/9FIAk0H/55ZdYu3Yt1q5di1mzZqG6uhqCIKBfv37YsGGD4WNwYT4DSTthfpHcVpXkp4wBm9d3wj8Vgvyvvv8/8wR5FWGSEi+87IQ59YePgbbHsRyjXvMpwogIwgyIykbbqlVcTlS/UYHaov5lEMyZdaAF7j3P4VgGY2mWzTosyqsIiVQW5P95YiCOhHIxKW8jxmXvSN1DPgGUeUG0JH+NxcywNmaI8+F67KQTQEOinEwOmSXehvsyXc7JqACfLufH4XDMJ4EoTynw1ZZWQX7yuI04a8huSwT5yDGJV91xzSWiLQDt4qsD4jwNh7JJpb+0tjvZMfQI9G66vqmSKLSMVd7ynIyib9++6Nu3Ly6//PLIuh07dmDNmjX46quvUqqbC/MZSFqK8gCCIYLdRztg55FC7DxSiF1HCrHraAf4SQgXmy3IK4kRZSm81kzVc8I7OXw8GwV6BhEkPwg06dgp1fbF61urQ8FYBCOCFMrGTvQI9DwBMIejibSyxwpP+QATsCvQATuDhdgZLMSuQCF2BTsgX2jBj3M3WS7Ih6EsheSviQR1J0J/KNti5fEVIjBjHpCcYPoLvMprWRVnfWx5k46ZcBagWdcxXvx4TkqsXbsWp556quq2jz/+GD/4wQ9sbhGHoxGFKN8SELDzQGHktetgIXYf7ICiDo2YNNZ6QT5M0hjzZlIB64VSm8V5BhHCYROSv6q126h4nijMTSYJ8rHECvRclOekQO/evdG7d29ceumlKdXDhXmOs+wBaCnw2a5yLPrgFABA75Lj6FVcjYkjNqNXcTU61TTCTm1DijEfx0MvVS90N8SftxhGxPgx9NQwS+RVivOpxNdPdF1sE6QJAJuF+TBcdOdw2i1BRrDkeG+8cWQg/CSIXt5q9PJU49S8A+jlqUZHocm4PVYTUZOIj1LyVwMe88pjxh7HDfG4zQxxk8AbmxV6QI6bIAS4BbU+i/1emXl9qwDSxOz/znBR3hROP/103HDDDXjooYdQUFAAADh06BBmzJiBf/7zn2hpSeG/hZNWpNXsNVmUbwkI+HDlSXjr0wHIz2lGr+7V6NWtGqefsg+9ulajML/Z1mZJoWxihHkrxVsj4rzeUCU2ivNstxck2yR7bEW/Z7IQHw8uyHNcBBfmOY7BZhOsPt4d/9gwCF6B4uc/+BJDyw+1feivtaExClGX2pXcxuw45y6Blnq0ZZ23QgA2o06XCNNp5GfL4XDikC5iAL2P4H81ZXj98Cno4GnCrYUrMNB31OlmgTEvRKMe80pSFVbNDI1jFsnCoxQBtFkEITbkK7EDNwyocNKKjz76CHfccQdOPvlkPP7446iursZvf/tbnHHGGSlPOeekF5RSCILgdDM0EQoRLF3bC//8ZCC6d67Db65ehoqex51uljSj3C6P+TB2eDRbLc7LgjfNEkFYBg2UczKKo0eP4s0338SKFSvwwgsvxC23YMECLFy4EDU1NRg0aBB+97vfobRUikddXV2NJ598El988QUopRg9ejRuv/125Ofnp9y+5uZm/OEPf8CSJUvAGMO4ceNw9913IysrCwCwcuVK3HTTTVH7lJeX44033kj52HbBhXmOI3wzqwte3X0O6kM+TC39Ft8bthcCgaRG7tVZmcke15R4QeJ5zAPWxW7PEG96Bk/yGPMuEb/dSkoJdDkcjitIByGAMYa19/fAq9vOAwD8pNs6jMg7AOJgwlIllPlaY8zbkUjVjcRLHKoBxjwQSDsQAsIDJ+n4/XDbgE8GMXbsWKxZswa33norpk2bBkIIHnvsMdx+++1ON41jM6FQyPX2mFKKFf8qx2sfXYAcfwA3TFqNIRWHnW5WhDbCvJ0e1loE+lQSe1olziv6iMEDwUgONg7HYh566CG88847yM/Pjwjdaixfvhx//etfcd9996F3796YO3cu7r77bixYsAAAcM899yAUCuGZZ55BKBTCrFmz8Pjjj+P+++9PuY1//etfsW7dOsydOxeUUvzud7/Dn//854g9r6qqQkVFBebOnRvZx+NJL6k7vVrLSYrbvfO2bt2KV5/6GfZVn4YpPTZgbPFOeAQmifE9kVyUt1rQ3QPQCh9EOzzmk7QjQjqJ9D3lGPPxQtlwQV4TtiV+5XA4luF2YX7Dhg149YlforpxGC4r+Q7f77BbGiDXQjwBVE1kPAbDyS+lUDYW22OtYVDM9ppPRUjW4C0PyDHm24Mwz+GosH//ftxzzz14/fXX8Zvf/AbHjx/Hb3/7W+zatQuzZs1CUREfFWkvUEohiqLTzVCFMYb169fj1b/fhZbgKbji/G9w+sB9toZx1QKFJ/7znV1YGXveTHFeZdCCEe4xz3EnRUVFePHFF1FZWYl58+bFLff+++/jggsuwLnnngsAuPPOO3HxxRdj586dyMrKwqpVq/DGG2+gvLwcAHDdddfhscce09WWZ599Fl9++WWbdrz//vu4+eabMWjQIADAz372M8ydOzcizB87dgzFxcXo3LmzruMZ5cwzz8S2bdtw6NAh0+rkwnyGoVUI+PTTTzF//nwUFhaitLQ06tW1a1dTR5gYY9izZw9ef/11bFy3DD/ufxC/7rUcPkFDDG0HhFxa6wXJSuAxb3eb9CTldAGUiOqhbLgorxnuMc/hpD+hUCipEMAYwwcffIBFixahU6dObexxly5dTBUTGGPYsWMH/vGPf2DXhi8wuecunOPbIQ2Qa8VG8TpKmLfDG1otwajb0DHIQZnBUDZqsfndjpuvWTzSqX/TkL59++L73/8+1q1bh379+gEArr32Wtxwww2oqKhAVVU6fmk4RtBqj//1r3/hnXfeQUlJSRt7XFJSYupgO2MMmzdvxquvvoojB9bgsh9UYsywXXDxeH7r04mT8chT8YxPhhnifJy+YURjqFcOx2ZuuOEGAEBlZeIf9vbt2zFx4sTI5x49eiA3Nxc7d+7E8OHD8eijj6KsrCyy3e/3R2mKVVVVeOSRR7By5Up07twZV199NX784x8nbd+JEydw5MgRVFS0/vj79u2LY8eOoa6uDvn5+aiqqrJ1sH3q1Kk4etTckJ9cmM8wEt54fEEQDBG89OkwrNneHTMuWAVRoNh7rAB7Kwvw0YoC7K0qQE1DFroWnkCPolqUDrklckPSvXt3+Hy+hMdvbGzEnj17sHv37sj77t27EQwGceGFF+LG7v9BjjeoLtK6RLhlxAtxTwAoVdnoZBuNetHb1Wa5TQxeCLEeAS65thwOh2MXCe3x/QTNVMRz+09FZWMn/LrHKgSZgL3bCrB3QwG+bS7A3uYCnAj50C37BHrk1KJ07IyIPe7WrRu8Xm/C4zc0NERssNImE0Lwox/9CHfk/A5+MaRP0NRS1kRxXpqB5ZIH2TQUUaVQNiF9QnuVynIanrvr4X1qOX//+99x2WWXRa0bOXIkVq1ahb/+9a8OtYrjBAlD2VQSNDR58Oc3TsOhqjzMvHo1Gpq82Hu4AHu3FmDdFwXYe7gAjc1edO9chx4ltSjtf6cuh7YTJ060scd79uyB1+vFJWctxXmXb4fXo8FhzUEis3nbY5JQLSTpF0rEts/HHF1wxzVnqa+vR15eXtS6/Px8nDhxAh06dIh40od59913cc455wCQ/oNvvfVWVFRUYP78+di9ezdmzpyJsrIynHrqqQmPe+LECQCIOnY4bn19fX1EmN+wYQMmTZqE5uZmnHnmmbj99tuRnZ2d8nmrceutt5peJxfmM4xEHvPHT2ThifdGwSuG8IcrFqMgR/IK798jOoBpQ7MHe6sKsK+qAHsDASxbtgx79+7FsWPHIh4EPXr0QGlpKURRbBXgKz9D1YlsdOlwAmWda1DWuQYT+tSg52m16HLiBATyMpBYR0iO3vjzYdRE9jhQwQfCWtwtJmtNHGvnOcgx+qNC2bi5D10MD2XD4aQ/iezx4ZYcPL7nTHT2NuCRPh8hR5T+MwfmRntfnMj3Yl9jAfY2FGBvYyM++eQT7N27F9XV1ejSpUvEFpeWloIxJj3wr3wWu2s7oLopC93z6tCzoAZl+TUYVlCDnqNqUdxUD2HP3wERxkX5ZOJ77PYUwtk4Mp3fraKp1j6UrxVr8oCEAkCuYn2y6xZvfbI+cWOCXLfC+9IWLr30UsyfPx8LFizAnj178MEHH6CkpAQzZ87EzJkznW4ex0YShbLZdyQfjy88E727H8eD05fA75MGgweddCSqXG29D/uOSCL93ro6LF68GHv37kVtbS26desWZY8DgYBkjzc/j90HO6CuwYcexXXo2aUGZV1qMPL0GpT9qAadOjS6LmRNu8eI17yGwQpGPO0vlI3Jsfv587GzUNp28JAQohpK+91338XatWuxaNEiAMCaNWuwf/9+/P3vf4fH40F5eTl++MMf4r///S8IIbjlllsAAIFAIJI4FgCuueYajB8/XvW4yjb17dsXoihiypQpOH78OB599FHMnj07rWw9F+YzjHgeeps3b8YTr5yLs/rvxhVnfQMxwbT1HH8Q/bpVoV+3KgBXA9Oksk1NTdi/fz/27t2LvXv3YsWKFQiFQigrK8P3Ov8Fl/WvQY+iWvhiR/z3AikNcBoV49Xq0CDQU4gQkKLXQqI26xgk0IyLBHBKPCDHQkC1gZ33wpr+4XA4HJuJZ4+//vprPL39XEwoqsSk4o3qcd1lUS4PAZzsPYaTC44BtT8FfivZ44aGhih7/L///Q8AUFZWhtGlu9Azvxbd8+rgFVVsWXPMcYxGc1Dup1VE1Ck4ZrR3lNZ+7wTDCWBVQ9nEuwbJ2mN0P7dhVZJYrWGQuOBuG4888gjmzZuHm2++Gffeey8CgQA8Hg927tyJW2+9FS+++KLTTeTYRDx7vGrVKvzl2XNw6TnfYcKorQlF8oLcFhTkHsWAXkcBXAv0lexxfX099u3bF7HHn376KTweD8rKyjDu1B3o2aUW3TrXwSNyUTEj0TiDQEr+miBULoejh57Qdz+Rm7xIMgRBaCPOM8ba/Ld+++23eOSRR/Dwww9HYr5v2bIFdXV1GDduXKRcIBDAyJEjMWDAALzyyisAgH/84x/49ttv8eCDDwIACgoK0NjYCCB6YCA8GBA+9pVXXhnVhttuuw0zZ87EPffc4+p8X0q4MJ9hxE7VY4zhww8/xD/+8Q/8/Ox1OPNkAyr3FwQYxZCVlYU+ffqgT58+bberEe9QekRkM0R5naQ8GpuszWrbM0iMZodECD4dHgEOXOOo42ZQ33M4HPcQ6zHPGMPbb7+Nd955Bzf1WIVT8w/qr3QOAW5myMnJQUVFRVS8RQDAQpL8Py1WQFQTKrWIwbFJU2MfEEzw+uXeUQoMzDhg8EBQCwWU6mBMPBE6XTy9ld/5JO1lDUSfmJ9IoNfaN+nQh2nA888/j/nz52P06NG47777AEgP8Q888ABGjRrlbOM4thLrMU8pxWuvvYYli1/FXVd+gYG9DcQKriRAX4bc3Fz069cvkscganumwcPYGIaFQ9lshbVx8t2GiV7zGe2skQbk5OSgrq4ual04xnuYQ4cO4Y477sDPfvYznH322VFle/XqhdmzZ0et8/v9yMrKQs+eUviHgoIC+P3+yGeg1TteeezwcmxonTB9+vRBS0sLqqurU449P2rUKAwfPhzDhg3DsGHDMGTIEGRlZaVUpxpcmM8wlDceLS0teP7557Fx40bcf//9KNv3orZK9Aili+Q/yLAQYKbI6pRg6wTKc01noXgPwHI0TtWLd32t8ppPdDxYdMxU4TMIOJy0Remh19jYiD//+c84cOAAHnroIXR99oX4Oxq9f1yo84FFTZxUiolhIfhYgvJWkELYG0PE6wMrz1GvMG6wPxjzgBALps7bmADYMjS2MTI4pFdwN9oH6dB3aUJVVRWKi4vbrK+urlades/JXEKhUCRP2okTJ/D000+joaEBj974ETp1aDT/gJkoynPaomOgghIPyB55oLw9ivNAygI9d9Zwlt69e2Pjxo2Rz/v27UN9fX3EabexsRG33347zjjjDFx77bVt9t2/fz/y8/NRWFgIQIrGkSx/JSCJ9Z06dcLGjRsxYMAAAFKi2q5duyI3NxeUUvz4xz/Gww8/jEGDBgFAJIdH+FipcOGFF+Lrr7/G7NmzsW3bNhBC0Ldv34hQH36VlJSkdJz08OvnaCYsBBw5cgS/+93vUFtb2yZDchR7VV5qLFK5wVCuS7SvEawS5a0W+80Ku2N2f9oIJXE89MJoOTezz11LfW7q7xNobY/ab9RNbeVwOKqE7fH+/ftxzz33QBRFPPjgg+i6qFt88U2LKDdHxR4nE+WLFC+19fE+A9GisM2hTGz1jqpC2zj6sS+zjmMTUTlfOOag9hviuJLJkyfjrrvuQlWV9KMjhGDLli246aabMHHiRIdbx7GT8IzynTt34u6770bnzp1x3333pS7Kqwnw6SjKb01epF15K2sR3HXOHmCHbYoxvxWarqcjVMa8MoHYc8qwc2xpaQ2/NGHCBCxZsgT//e9/sX37djz++OMYMmQIevToAcYYfve73yEUCuGGG27A0aNHI6+mpiaMGjUKpaWl+O1vf4vNmzdjy5YtuPnmm/H6669raseECRPwwgsvYN26dfjmm2/wt7/9DRMmTAAghdgZOXIkZs+ejc2bN+O7777D3LlzMX78eFPC2MycOROvv/46Nm/ejM8//xzFxcUYNGgQCCF48cUXMX78eHTr1g3du3dP6TjcYz7DCIVC2LNnD/7yl7/g/PPPx5QpU6Qv5BckdTFPTZznWIubvbnjEDe5jRNist5jumHmwl4AAzSWU0Ot3TYkTeZwONGEQiFs2rQJ8+bNw6RJk3DhhRdGpmMCSC3WdVicTyYKJvPkTeQtrrdtWjyl013EjO0Tvedjczx2ykR4hQQD5VaRLl7zGlAVo8K/D7PPMUP6zC3MmTMHV155Jbp06QJKKUaMGIGamhqMHz8ec+bMcbp5HBuhlOKrr77C3//+d1x55ZU499xzzas8HYV4nTAApLqdeSsnCsFiQHClXUUINRYL81tVlt3sma/Wjwm86l01OKT1OxAuN8GqhljHwYMHcdVVV2HBggXo2rUrRo8ejRtvvBFPP/00amtrMXTo0Egs+IMHD+KTTz4BgDYD37NmzcLEiRPxxBNP4I9//COuvfZaZGVlYcKECbjkkkuiyk6fPl21Lddffz1qampw6623AgB+8IMf4Oc//3lk+x133IEnn3wSN910EwghGD16NG6//XbT+iLMDTfcgD/96U9R7f7Pf/6DX/ziF/jJT36SUt1cmM8gGGNYvXo1li5dihtuuAEjRoyQNpghyttJOrXVLtJIoGdEbCvMp4MoH29/O/vczETHZsB/ixyOISilWLVqFT777DPcfvvtkamVbbzdrRTitNSdSJBXLitjzluVPFMF109bjtcPaoMfDiCFsnFAmAcyRpyP+x0089wyoJ/cSE5ODt566y1s3boV69evBwAMGDAAAwcOdLhlHDsJBoNYuXIlli9fjnvuuQd9+8rKXzsQ1M2CwSZv73TAoBc0gwjSkwJW5X91q5e8XmL7VyHUu+aeMAM84dWYOHFilKjetWtXfPTRR1Flpk2bhmnTprXZt1u3blizZk3C+rt3746nnnrKUNuysrIwa9YszJo1S3V7bm4uZs6ciZkzZxqqXysbN27EsGHDotb98Ic/xJ///Gc8+eSTKdXNhfkMoampCX/5y18AADfeeCN69+4tbXCbKK8n8atDGB6NtaOf00Cgp0SElzZJH1LpE7fEV7erz930O81gjh49ijfffBMrVqzACy9Ex/nesmULFi1aBI/Hg1//+tcOtZCT7pw4cQJz5sxBhw4dcOedd7ZObVQLQWMUsz3T4wny8cR5M0iWdNMlz1+GcFCMV0LhcTaUjR3x+tMd3jeWo5oom9MuqK6uxpNPPomysjLMnDkTnTt3ljY4LconE1Fd9nWl8EFgAaebYT+xXvMpCLKMeEGs6sNE36d0j2ev7PMuAA7BtGSyKbWF0y457bTT8NJLL0USyocZPHgwVq1alVLdXJhPc2pqavDxxx9j8eLF6Nu3L3784x+jS5cu0ka3ifJpgqHRWLv72Qqx2CQhPBLKxsnvnhXHtkqgV2mrq6bqZRAPPfQQ3nnnHeTn50dlU6+rq8OMGTPwzTffIDc3F2PGjHGwlZx0paqqCosXL8ZHH32EESNG4Nxzz20VAcwQ5bUKeFoTUaqFZUkmzscrq7UdOmDwQiDtUAgwEcZECFYkf9WL0nte+V1KA1HaUnucBuefbowbNy46ZFgClixZYnFrOE5x+PBhfPjhh1iyZAnGjBmDUaNGoahI/sE5Kcpr9Wq2MwyJhjbR7T4IHdupPTZJjKVEhGDFrINM8ZRPQpQ6ozMETkpwMZ6j4IknnsA555yDXbt2YcaMGRg0aBBaWlowe/bs1mc+g3BhPg1hjKHyrc74YF0FVm/rjhF9DuDWW1/EySefjF27dkEURamgVcKo0uu9p0XHcAhDDnpuEaDNEIxNEJ8Z8YAccmjqPGBPgl+zxPk4bXXNVL0Mo6ioCC+++CIqKysxb968yPqWlhaMHDkSDz30UGTmEYejBcYYNj5YgvcPVGDd8a743ujzcPfdd+Okk07C1q1bJXtsVJQ3ItppFeVj1ycT5MPLWkLaqB0vUQLZOO2jzAuCdioEmASDByRRMvZEJJsd0SnJ9ljUvitpEO7GMnus57wTzcBwef/ZzdixYyPLW7duxccff4zrrrsu8mwUDAbx3HPP4dJLL3WohRyroJTi6/e74/0vKrBxZzG+P3oC7rvvPpSVlWHz5s3SgI1TorxR8dQl3s6UeCFQq2KwtA8Y8YCAOnNwl3yPUkNAQqUmUU4AvXAxnhOHESNGYOXKlfjlL3+JYcOGwev1glIKj8eDv/3tbynVzYX5NIIxhpUrV+JfC2bieP2ZOG/INjz90/fRMa8JOD4AWAGEWqZB3P8GsK/BnIMmCz0T3m6mQF8K68TVJIIqI159U/XcNCPBqKiudg4pCPT0uEqMeaO4JZxNLKm2y03fm3bEDTfcAACorIy+4+rUqROuv/56J5rESVMopVi+fDnefuEhNIVOx/ndtuG6irUoCP0L+I9cpmQ6hP/OU6/ALjFNj5d9quK8HkG+SGVdDJT5uMd8ikgx5nX2odZwRcpyekV6Je0x3I1Zonyy7e2pT2WU8WfHjRuHhQsXYty4cVFlxowZE0lYx0l/KKVYsmQJ3nljNoDhuOB7W3HzpauQm/0voBlAJUCqp4Nsfdb+xpnhzWyl97zG9lG9z8ecNkg52Ezuw3biLQ8ADAIISzKwEX68MyrQc0Geo4H+/fvjo48+wu7du7Fu3ToIgoARI0agW7duKdXLhfk0Yd++fXjhhRdw+PBhXD5yC86o2AuP2HbUkMIPYV+zOQfVEw9+DzLCe57qif/mVnFVj2ic7BwMCNCMeCBQhzzm7bwmevtGR9t4KBsOx73s3LkTf/vb31BfX4/Ly7/FyE77IcT5ybbxtrUz2asVcebDxIrzaqiJtTraRJmNoWzC55KKwOxCKPNA0JP81WgOATP6z6Uhbky3x2aK8pyErF69WvVBubS0FF9++aUDLeKYzZYtWyQvxea1uOaibzCk4hAEwelWyZgtmprt9ayjfVTwQWDcYz4VGCwKZdNOYIRon3FgRKDnojxHhSVLlmDYsGGtodAUlJWVoaysTHW/5cuXY+DAgar7xYML8y6nqakJb7zxBj788ENMnDgRvx57H3ye+H9KrE6EYHTacqokE+fTIPErJT4IVIMQ4FZRPky8EDdG2q1T6GdlHvM85vXgxDWx6Jg8lA2H4z7q6+vx2muvYdmyZZg0aRImbL8YHkHHb9UqsVFL+BqlYJpIfE0mzscmg1WrL1acjTdgkKQ/JI95i4WA2LZr9QI/lmS7S2AQtYWyMSupr1n9Ek+QdkCwt8UecwHeEoYOHYo77rgD8+bNQ48ePQAABw4cwF133YXhw4c73DpOKtTW1mLhwoVYs2YNpk6dinPL/+geQR6wzpPZiZAklQDN4h7zqUKJB4Q5pNGkfRgbABAAptMeaxHouSDPScCuXbvwy1/+Es899xy+//3vJy1fV1eH+++/H8uWLcMnn3yi61hcmHcpjDGsWLECL7/8Mnr37o3HHnsMJdu6JN5pL4BsW5oXHzd7zmsQl6mg4cbD7aJ8LGa0V4s4Lx+HEhGEmijM6zg2J0PpAiBPY9lcKxvCaY9QSvHZZ59h4cKFGDRoEGbPno2ihZ2kcJfJsNNDXusx1YTTeMJsPHEeaCvQJ2tLvOU4WO4xn0yMjucFfizmXa2M08htY6IHRC35q1lCfLxjW9UfyQRsF3naxyU2rn66ifIFAESNZR22x/Pnz8cVV1yBsrIyFBUVQRAEHDt2DGeeeSZefvllZxvHMQSlFIsXL8Zrr72G008/HU8++SQKDnVwulnRWB1exAxxXmcbpRjzLhHm1UTWNBBXmZPCfAbAiGA8Rn88gT4NvjccZ7nmmmvQo0cP/PSnP0XXrl1x0UUX4fTTT0dJSQny8/NRU1ODQ4cOYceOHXj33XexdOlSTJs2DUuXLkV2tj5hlgvzLuT48eOYO3cuDh8+jJ///Oc49dRTgS/kqbR2CZCpeLdbEXfeJihJMlWvPQvA8QTymD5hggeClhsPt8aPdwE8lA2H4w4OHz6MOXPmoL6+HrfeeisGDRoUP5lrrCiYBeBEgsrjiYhGY26bJUrGhq5J5EUPtBUWE3nw6w5lY5HHvB5hOiw0J9on3jYnBHtFW2iDCKEgqLrN8jY4ce5akxFrRK9znmbSTYxPU/r06YMVK1bgm2++wdatW0EIQb9+/TBw4ECnm8YxwN69ezFnzhwAwN13341+/fo5l8w1HnbF/E4l7ryBNkrPxw4L84m8nsPbXCy0MqJxBptW0iW+vFnt9BCA0Pj1afktuPj7wXEv559/PjZu3Ig33ngDr7/+Op566ikcOnQIhBAwxuD1ejFo0CCMHz8es2fPRkWFsZFTLsy7kH8/Ow75LVn49WWr4WueC3whb9AgCrtK0HOTQK9RAI6bdb49C/JKtHwHiZjcI2Cv4j1VcT4Drw0PZcPhuINFv78IPQMhXDvwK3g+eRJQm5UYR/iLa4+TCYVGhMRURflY4TmZOA+Vz8napEecPwbQkBdCrks89OwStFMlpp0MIkgVBTq33WZLW9wwkyCl2PUCwO1x2jN48GAMHjzY6WZwUmThvMsxuLQWV5z/DQTyR80iG2Man431CogVBvYxGz3e80baKvexNKPcwRjzWmOFK8u5TIRlIM483zkRxsaC34WkLyToPyfCPHHaDR6PB1OnTsXUqVMBSOFNa2pq4Pf7UVhYCFHUOpUwwTFSroFjKqH/Cfjfpgvxm0uWJ4wlHw9XCnpGvO9LYZ7gqkP4VQ1lk4HCr5Uw4gExe7qjRm/9TMFVA2xqZGi/czhKmp/yYNWxifjj8MXxY8nHFeXj2GMrQm1YGbteTdRMRaDX5THvg3AiADTJK8wQeTNVnI5zXox5QBBMn4EFq9E5G4WxFKbOcxynqqoKTzzxBNavX4/6+vo225csWeJAqzhGqF3nx7fbLsQNk1brjiUv5Stpjl/AqIjotCgfJpn3vAntpMQLL000BdBC9CTwjN3PReK8KzUaM7H498AIAWFJ7DEX5zk2kZubi9xcc+P1cWHeZXy7pwR5WS3oVVztdFMyA53e2G2m6nEBUjdUEJOHsjHiJR8rzmfwtXHlzVsG9zeH04Y5BGuO9URZbg26ZLcVdAAkFPcYPNFTlu1M/GoUtXAtseK88phGPeY1QuGDAIU9NipyOy1KWyHOazwnKfmrA8nYw7jFaz6W2ETGahTJHo6EC/PpyhVXXIHt27dj0qRJumO9clxEJcEX35yEQScdRkGufq/tEPNDFGKEebeI6mZi9jkpRO2koV457RNbf0eCthj9bhPnM/G/hmMJXJh3E18QLNt4GkYP2A1iwGHWVC/bnkgtzrzTGAyPEpXchguRhpA85i1KbsOvib1kaH9PnDgREydOVN1233332dsYjmtZdqQMo0t2qW9MJDIXASH4IQjNgM+Splkj9CdKAAtoiyWfaH+dUOaFlzRGr4yXkLU9oWOgQRKWrWuKZcSeoxXXO1mc9yoAVACaaPyy6ZBsth2zfPlyfP755xgyZIjTTeGkyPL1ZZhwpjH3Z8r8rflKuEhmCMeSvxr1llfu7xKveVN1Gie/xw4dm5E0CS3H/2M4BuHCvFvYS9AUELF6Ww9MPfNDle3Jq6DwQ2AJpurpJV3F+RRillNB9gjIUEHSDqQYcA566GUAjoWy4d97DgeYQ1Db4sN31SW4qd/qttuTiPIAQJEFEUnssV2inhZR0yqv8hTOkSJB8le19qqdp9Pe8mHMGlDQeT6umH2lx2s+3vnpvY4mCfkMQuI+DHveuwGTE99mAhUVFWhp4V6+aU0lwaGqXOw+1AEj++83VEVoZxZEoQk4bHLbMpkYMZsSlVCvVpOqKO8y0jq+vAvEZk2hbJzABX3DsZd169YhKysL/fv3x759+/Daa6/h5JNPxoUXXphSvVyYd4q9bYW3Ndu6o1dxNYoLGgxVGSL+5EKAXpwS540KhCkmEpVi6DUmL8iJCxM0JH/lxMX25EBcjOe0Z+aoD4J9frQnBnc8hHxvjKijQZQHgBB8ECPB0TXubwVpKsoDsjAPHUJArADsFlFeibJN7cnrX4s4b+b1SlSXrn4nIMTF9zPJvP7bOddddx2uuuoqPPnkk6qxYMeMGeNAqzhxqVS3x8vWleGMU/bC59UpysmCWchsx7VMR8XDnAo+EDtD2WSYKJ/WuEV4JgKQKPmrEjvC2bilXzi2smDBAlx77bV44YUXUF5ejjPPPBM5OTk4cOAA7r33Xtxxxx2G6+bCvBOoiPLYAyzbWI7RA+JMm9cAhQ8iUxECUsVucd6IUJiiIB9GmqrHvWtSQRKWOcaxySOAC/IcTlyWHS7HxB6bo1dqFOVRBNCQHwJtBrxwzqvWbFE+WUzu2LIpQplOYR5oFYDdKMorsUmk1jz7yqk+c/KYGs6ZMRFoYUA8bb4T7P19cyFeF7fccgsAqHqxEUIQCrl40IUDQNLhlq0vx89/9KW+HRWiGbXCcS1TiRP2hRIvRLs95jnq2CUIu0x4ZhCc95h3WZ9w7OfBBx/E3LlzcdVVV+Hll19Gly5dsHLlSrz//vu48cYbuTCf9uwBquv92LC3GDdPWNl2u0YBLUSyrfMI6Cm/Wy3Q6xULTRLkw0ihbBy88VA7f5PP0WpcMXU+HYi91vJ1Zno8Asw6NofDiXCgMQ/7GvJxaqcDrSt1iPKA5KEX8Zg3W7RLJOo6GYPd5POk8EEgBuyxW0V5J2cvuOG4Wo+hRXw247umoT2MJZnBFh4I0iLO6xHwuQBvCpS6MOwBRxfb9nVEc4uIgb2PaN8pRjyT7DEX5lOBEl96Oq65JL582uFCAZoRAkDHf7qZXvMu7A+OM+zduxcXXHABAOC9997D5ZdfDkIIBg4ciIMHD6ZUNxfmnUYWuj/f0hNDex1EXpZxUThEfOl54+Ggh3wsjsTQAxL3wV6knTjvCpR96vb+U7TP8hh6XJTncBKy7HAZvtd5L3yC/DuMJ6bFrleGsmF+iPHio1tBrMhoV+gQCz2FKfPp95h3K3aGcUlntArStiVjFaBLCIhHVcw7xzL++c9/YsqUKQCAl19+OW45QgimTZtmV7M4Blm2rhxnDd0NQdC4g4qARuGHiHpT25WRJBCxbX0+5mFsnMWtIjQR9T8fGxXn3doHHMcZMmQInn/+eUyYMAHvvfceHnroIQDAokWLcPLJJ6dUNxfmnUThfb5sYzkuOX1j2zI6RDTTk79aiUvFQduzzmvth3A5twvMbsWN/Re3LRqFAKOzK0rj7MvhcKRp84fLcX3fNdIKNaFPwzqKLAh2DJQnEnTjifNGReBYUdHi8B0Jk79mElyUlzBDtDZZ+GYQQASKiKaX6Duv5hFvlxAf7ztkdYxdF/Lggw/i4osvhtfrxaxZs+KW48K8+wmGCP73dU/ce+1n2naII6aF4IePj4qlBCNee2PMm4HLvOU1h5ZzEhcL0szqUK8uPneOe3jmmWcwceJEPPzww5gxYwYqKirwwAMP4KGHHsLbb7+dUt22CfOLFy/Gxx9/jF/96lcoKirCzp078d577+HQoUMoKirC+PHj0b9/fwBAQ0MDFixYgNraWlx++eUoLS1FVVUV/vjHP+Liiy/GqFGjoup+9NFHce6552LkyJF2nY6p7K/Kw8HqPAzvldr0hxDJguh2Yd4sQdAiL3IplE2LPeIlF0etI17fpsHsAyl5boKp88lmV8Ti8vPl2A+3x/GprCtCkAoY0OGIYVEekDzm/cIJ/Q3QEutbj5BrVsx1BzQNigzymI9HuojyatffzIEZl2pmDAKIcqBcTXxXDoCZdR7p8r1wIevWrYss79ixw7mGaITb4/h8s7ULCvOaUN61JnnhBKJaCH73Px+7HEYECGbMHrILl4nynNRhxGCM+WRe81yQ5+hg5MiR2L9/P44fP46iIumG8JJLLsHVV1+N8vLylOrWOjEsJY4dO4bPPmsd7a6pqcHf//53DBw4ELfeeivOOOMMLFiwAFVV0h3t559/ju7du+P888/Hf/7zn6i6Fi9ejPr6NJ+OVsqiveU3leN7fffC64n5s9Ep3IbcntzGbCHaAmGbEodjzCcjHcX8vTEvO46XxkgeAXESkhk5N7vE+lKL6uWYCrfHMdwcPQi27HA5zirZDUHN01yrUA9JCNDsMd9J8bICK0R5G5JdUuYFQZp56GnlGGwRX1PO+VKF+GJzlcrL6DG0tCHRyzJUYtqafbxjKq9UsbxfOGbA7XFilq0vw+hhu5MXTCKsUZIFIZzzhcNxCFNysFkpItshUFfGeWmBCIBRj/mtilfsOqswco4c1/P++++DUhoR5QFg0KBBKYvygE3C/L///W8MHjw48nnTpk0oKCjAuHHj0KlTJ4waNQpFRUWorJS+tU1NTSguLkb37t3R1BRtSBlj+PDDD+1oti0wBizbWIbRA3ZFbzAgwLk6lI1VYqnJYq8UykYWAqwUGdNcPE4EA0ksxNsp0ptBKewVnYkAqN28pdJfVorzXJBPK7g9jk+QEnx+pCdGl+xqu1GHKA8AlGVB1CIqq4nxTiRujYeD4h6DAIGkkYdeIswWXjWS0tR5q6+9VtFfT10mv1i1GO0xH6/tRq6p0e+CowMVHDPh9jiGvq33vo3NHqzZ2B3fH6JBmE+ClPzVxU5XaUBahGFxMa7vP6sEaq3idDzBXvFiewSQQyYNbtghyHMykosvvhglJSX46U9/infeeQctLeY5EFkuzH/33Xc4fPgwxo4dG1k3cuRI3HLLLdENEYTIiZ1xxhlYvHgxnnrqqaj9AOC8887DqlWrsH//fqubbi2jpD+WLQc6gTKC/j2Otm4zKMCFiMVT9fYkL6KKXV7SJoi9VIhJbmOF4Jhqf7hZ0N4LQE/0Bjefi5rgbIMAbXiqXjKs6GsuyKcV3B7HQfaaX3+8K4r8jSjLrU25yhD8EEkKHnpuEOe5wNd+scr73a46TIIRAlLPzBe81QR5rQMGnIyA2+M4yOL86g3dcVLpcXQubExcXoPAJgnzSerhcCyEQYw/G9pKtAjQekRqDQK6VV7iLOwx71ZPdLe1h2MJR48exbPPPgtRFHH99dejuLgYV1xxBd566y00NqZmZyyNMR8IBPDOO+9g4sSJ8HhaDyWKIkRRBABQSrF+/XocP3484jVQXFyMu+++G8FgEFlZWVF19u/fH5s3b8a///1vXH/99VY233pGMSx78FSc1X83BIKUhbMQ8Vs3Vc/Nony8YxoSDYm6d5RZuFmITpV0ODet34lE5SzOP2B5chsl4fM0cj5clE8ruD1OzrLDZZK3vAlhWijTEcrGTejxULY4nI0p074zhfB1sSGEUMrib7zvhpZ6XSY8s9hk7LHnpvysFNv1JF122TlzrIfb4+QsW1eO0UNVZq8ZgMIPIVPDotlEWtljF4qjjIggLOh0M9qiRZR3S38SAYSqPB+H29fX1tZEH5vTbsjPz8eUKVMwZcoUAMDKlStx1113YcqUKcjOzsaECRNw3XXX4YILLtBdt6XC/JIlS1BSUoJTTjklEh9PyTvvvIMVK1YgFArh0ksvRWFhYWvDPJ6omxUlF110EZ566imsW7cOw4YNs6j19rD1YBGuGvC1KUIftSq5TTqJ8rHH1ykeqk41syMRbLqi0i8JE5emA1q+M6kI2skgIlRD2aT6PUw22KAk2XG4KJ92cHuchJsZtl79Q/y45yZTqpM85lO0x2YkbU2Gi0VBU6Z+hwXSdE2mGXt9kl0vhWjMGNEvppj9fdAz0GOkXssHKoS2zhqxx1ZrS7Lvm4t/d5lEVVUVnnjiCaxfv141/vqSJUscaBW3x0npy1C598eYfsmaxOU0evoyiBDgQlGU025gRITgJmFeq5e8i4RnRpLc01QidXHeRefLcS91dXV477338Pbbb+O///0vfD4ffv7zn2PSpEn47rvvcM011+AnP/kJHnnkEV31WibMHz16FJ9//jluvvnmuGXGjRuH008/HVu2bMHbb7+Nbt26oXv37knrLi4uxllnnYX//Oc/GDhwoK52NTU1obm5OeKVQIizMb+aPIOQ4/3SlLpMD2VjVJB3EwbEecswU8R1+rzS8Vz0CO566jRZnGckgce8XYNEbvnNcEyB22ON7fF1R47HnDi0lPnM8dCzUpy3yjPaTaSrIA8Yuz6Ka8IgghAHps6H22FHXcptRQaOm+T7yxLNokzkPR+PDAv143auuOIKbN++HZMmTUJ2drbTzQHgbnvc0tICURQhCIKj9pgxhqYWD3KyeFx4TmZAiQcEDtnjrQAqYE9yVwthRAChFvWhlYJ8mvc7J5rzzz8fn332GXJzc3HJJZdg0aJFOOeccyKz3c4//3wMHDgQU6ZMcY8wv2zZMrS0tOCZZ54BIBlZAHjyySdxzjnnYNy4ccjLy0NeXh66dOmCyspKrF27VtONBwCcc845WLt2rW5vh5qaGjQ3NyMUCiEUCkXaBSByE0IIiQgF4RsUj8cTWVZuU5YxQnPtVvhFc/5kKDFh6rxZYrybPMzNEH7d6DWfUsgeE46bTljZR3q855O1Yy8AEONZ5zkcFdxqj6urqxPaY8ZYXJurtL2m2eMTVfAL5thjBgJCTJo9ZLY4z4U9d2PSgAmDTiHAqe+F2nGNDkqYvY9fALIoUCN/jhXe1cR5KMpqHVTgWMLy5cvx+eefY8iQIU43JYKb7XFTUxNCoRAopYbssZotNmKPg8EgKBXg95pnjzka6At3eAyn6vnslvNQwIjHmRjzYYyIw1b0oZ52VMR8JgKQbFa+3u+OVd8TLsZnLN27d8dbb72F8847L+7stTPOOAPPPfec7rotE+bPO+88jB49OvK5trYW8+bNwzXXXIPdu3fjjTfewOTJkyPbCSFxT04Nv9+PH/7wh3jjjTciIxRa6NKlCzp27JiwDKU0IhSEX+F1gUAAjY2NbcqwOH8UaiJ/5POmHyCn4AywrG5oFHIgsmaIrAkCmg3FcpOm6un807fCKz4dhdt0xk7v+STX1pU3v3b1jRnHKQWYV1SPoac8jt7fWDr1Acd03GqPu3btasgeh19hUV+rPQ6LBGr2mLx8DvKLzkIopzsaa+shdgjb4xZD9ljzPsegLrx3iiljFlaEKnG713y6YPK1oRAhQKPHabqL8hbBYkPZqIWtiRdWJ955uOj8Mp2KiopI4lS3kK72mDEGxlhSexz77KzVHivtcvOO89G1y2looj0hskYIpBkiaYZAWswb8OZoxpFnOzPCkrgIKfmri0LZJCNVwdoMYTqmDgYBJJe2zgCIh9bvjtMDD5y05MUXX0xaprCwEJdffrnuui0T5sOj/WHCI+bhOHmLFy9GWVkZTjrpJOzcuRPbtm3Dueeeq+sYw4cPx4oVK7BrlznJYZRtFQQBXq83pXri3cRQShH65lwEkIesnCI0Z/fDEY8XIZKFEPygxC9Pn2178yGwAAS0RAR8kTVFBP0moRg14gAIaILIWiCwJoiQ3gUEWs1qJoSo0YtG8dqy5DZWD1bYIc5rOAcmiCDU4RsPo/3gElGZEQJSSIEQ0meQyyV9x1GH22PJHlNK24j4lFKEXjoXjWIhCgs7oCF3AE4IfoSysxAiCnssqNjj5oBkh0kzRDRBIJLNFUkTmmgxakL9FdubJXEBzSAIICpKgJrwnk4hWBKJ8ynEAk+rZHOpYIVQWwWwQo0e83YIxYk8y+1uiw4YEdTz5hgZkHLZubUHrrvuOlx11VV48sknkZub22b7mDFjbG9TutpjQggIIabaY7WBdbrnfDQGOqJzpw443jQIIZYFyvwI0SxQ5ot+PlY44wsISM+/kO0ta11uQmfUkJMhsmbJJqMlUpYg6EaXIldBiQcCcyCsUCrivMu85qU+TCNhXis2CtGMKGaUh4+bSKC3Gy7Ktxs+/vhjrF69Omrgv6mpCTU1NfjTn/5kuF5Lk7/Go0+fPrjsssuwZMkS/Pvf/0ZRURGmTp2Knj176q7rRz/6EebOnWtBK1Mn7k3MFwTwAMEQQeXWHigf+h48oeQPoAwAQ1jA9yFEskCJHyFkgRIfKDxoFEqkdcQPCr9UBj5QIh+/DkC3cH3SrYjAghBpEwTWAoE2S6I+bYZIWyCwZoi0WV7fDIFGlxFYIPrh2c1Cogbx2pUe31qxUpzXeF2Z4DEW/83pmPkugkGIH2PejfDrlta0J3sc9siLsse3SP/51QV+7NneGaXd/iPvEFPBCUQn1gRAfV5QZCHE/NKgOpMH15lfsse0i7zdJ9lpuRxj0bdeSrsjkIAkKqAlIuSLRPm5dX3rZ0lkEGIFfzWMxOFORjJRPrysQ8hkLI1tcSwOCbKs2gMihIC2OS/tI/Y7oKWcqxDiD25oHWzgOMYtt9wCALjwwgvbbCOEIBRyMLSECu3RHkdRSYBsoLEuHwf2ZaM0/z+JK5J/cwwEFF7J/kJ+RkYWqPy8zOBFI7pFBtulcrI9hidK7A/bYwIGgqBsj5sjjm6SqN8SWS85yYWF/kBkXZRDXJrDiBfECWE+VVwkzjseykYPyfrMKQFaUBkoj+c9Hz6HeAM7ic4x2fkpj8fF+HbHo48+ivvvvx8jRozAypUrMWLECHg8HnzxxRe45pprUqrbNmG+qKgIjz76aOTz0KFDMXToUMP7h+nRo4fuwPq284W6aQ6GBBAwBEIiPELyUVQCgCAAgQXgBRDrTHbUewa6Bj5NXMmB6I8MkrGgxIeQkIWQ4JNuWgQ/qOAHJT4ExDxQbyeEiA+0zXaFwHECwIDomxqBBiCEWiRBP9QMMbxMFcuRddKyGLUuYK7XXKYLwFacn47BFiqIEJz2mE93iACEp87HC1ujJ5yNHfH1OWlFu7bHt8Sxx0y2x1SAV6BJhWQCQDwegFgUgJfUtdl+NHg6unqT2OMYGJPigreK/F6F2O8DhR8BlgfKOiEEX0TolwYCfKAs2otRKfgTMAhEmnEnCGGRoUXhPah4sWZZYGiRBYbwthihIZHQHi9EiUZxnsIDgaShEBCLg2Itg6A9lE2qJArxonVfFyL9hhLcgxoN5RQbi55jCTRRWECX0K7tcWUcexwUQCkBpYCWEPUETJqthhZIHmgyTPoNHyOnoytbGlmnhYgzXETE98kOb5K9DcGPAAqk5YjgL5Wh8IGi7awC5QCAEBHxW2R7LA+4x9pe1hJlo8WI6G+f8E+JDwJ1yB5nSLx5RkQQpMHzcSqCtcVIyV9V/tMTec/rvfZazpGL8e2aP/3pT1i0aBEuuugiFBQU4JVXXkGfPn3whz/8AZWVqf3ZOOIxz5HI8oUwsvt+vL35ZFw+6DvrD6gSwoYAICwIgQXhoQ3G61YRCRkIqOCVxHzRj5DgBRV9is8+hEQ/At4CUMGHUGSb8j3JdEmGVlFfOQhAW2ThPxCzLQDheAuEkoAkSjB5OwvILY5zx5bKTAC7ZxGYKc7rbDsTvJLHfOx+XMDVTLwwVpYQe13cPOOFw7GQTt5G9M6qxgcHTsJFPVK7sUqWmyoehAAEQQgIAsSAm3MCgZN1lDwKKfyg9T5J9A8LCEQSGULIQgAF0iC8vF4SGHzRQkOWXGlTm6NI3vuNAQiCLCKwFhAEZGFBtr/5La2DBDWBiOgvdAxExAcGL4hdorJetITncYHYTPUmf41HIhE59jz1nneykDYOi9ZSKJsk4q4ecT7FASvV/bmwn5SmpiZs27YNzc3NOPnkk1XD2nBsJo4oDwBlXWtQkNuMz9aVY+ypqYXjofBBQLPu/SLOcAhA8jyTiWffddh9ycO/1bZGBH3ii3j+h5CDADpI9pj4o+xw2NM/2VFaxXzZDrMWhfAfsyyHyhX6BiBslz8z6VmZEq8zoWzCZEC8eSmUjYs95t3qJa+ECK2hbMzGDefHSQuqqqowePBgAEDHjh1x9OhR9OnTB1OnTsXIkSPx/PPPG66bC/MOc+V5X+M3C8/F+SdtQ1F2m6dc87AyrnwcMY+AQaSSBzyCJ9QLpYgk/reK+a3ivzwgIG8LePNA/eF1XlAq71PoBSXyeuJFbU5/bOk2PVI3AYvMBAAAQoOy2K98tYDQAMRQizTIQYOt3v40CKGhBUIoKJcJgITk/ULSdks8HhyaGcAEEeS4ikdAps1UsHLgIfbGw0iyV6OEz0PL8TLpenLaPYQA07quxyO7R2NsyU7keY0/hDJ4QIjND2BJBFFynEEsCnsUxqBXaMhSX82YAHrcJw8AhMV/pcgvDQYE6goiZajgbV2uCZfxIuTPxgnaCyGWIzclOtRAeAaAJJwE5XA+kogSFv0JAhBIMLKeEOX2oLyupXUZweShgJS4QHxPBIMn9WRzqQrvWuuNty1ROS0DIymL1ooZbIkIi+tG+ydRe5PVyRMwxyUQCGDmzJl45pln0NwsibN+vx/XXnstnn76aV1JVTn2IQjAtAnr8Zc3T8OZg/fA5zUuxoXgh2hAmLcSycO/uW27TBD9w1AIYEhkj6VX2OufEuk5mMIrPxv7Is/GATEfTZ4SNHmLo85BicACIEx+vmVh57dgZJlE1gcjoj+JiP/SesJkBzoWNDf2vwu85qXkry4V5tNBlAfABCFxuNxkSWET7cfhaGT06NF4/PHH8dhjj2HkyJF49tlnccopp+DNN99EQUFBSnXzOxI7iA0NqBDJuxedwOjyXXjt20G44bQ1hg/hSGx0F3jXSuK/FAffMLLAGBBysbt4Ek46NL91m+IcGSSP8FbR3yMvSy8m+ECJB1QMzwTIk8p39oGKUlkmeloHDkQPmBATa5gQ9URjkAcFQtLAgCTuByPivkCD8rqQdPMTkj93CkYGC1oHDQIgTC4XfqfBtl7aBq4vPSRCKEqDqXpqmDkrIgXRmkEA0SIEaBHsE7VDyzYX/MY5HNOIE8YmTEX2cQzpeAhv7RmAaX2+NnwYCh/Etu7kqWGGIGqxgEcIhYgm9XPXKTg0NRbjUN4YlPveUN+NETB4JBGBhcUHDyiTxAcGr7zslWYCsDww5pXiDbPW/SJ1wKMa+7+NXWwCICAi5AsIRrwqBQQloQGh1gEDBECiPrctQ+RX9LrUZ00xiBBS8Zi3auDBCnG/SGWdlmMl+T1I9ljjtTDrN2p0vzQW55999lk899xz+Pe//43u3btj06ZNePjhh1FZWYni4mL84he/wEUXXaS73jvvvBPvvvsu3njjDYwePRqUUvzvf//DjBkz8Jvf/AaPPfaYBWfDMYMhFYdRWlKL9z7vh0vO3tS2gEYxjcJvvj1OAwRQwKg9jkk+f8LfCzXZ/dGj+v04uxFQ4gEj3laBn8jPx6T1xeSwuQGSD0Y8CAk+eR+PvF+4Di8Yic4/wIT4s4lb7XEg2jYzhR3uF4KwPxCJEtD6Lj8LRwYHgpGBgfBnU+wx8bgzTn+aiPKApJEIycKTGRXnrcBFfccxj6eeegoTJkzAtGnT8MADD+C8885Dfn4+srKy8PLLL6dUNxfmrWZvcsH80nM34LYXxuPCfltQ1qHW0GEo/BCZTTcemSbWyedDe3kl7/6Y9WEIIIvYAQA6wv6Y0F8MBEzwyAK/B0z0gQqiJPyHRX95e2SdJxeBeg9YsUe66QmXIR7FuxdMEEGJByAkWogoTTJQwEIglEpe/zQI4XgIQX8OGjr1kAYMQkGQUFAaLCgMtQ4gsPA+IbkOaVnIkz8z+TMLfw6XUyzbFerFKCkI9eywAJLHgP0aCicS0JMdM9VZDJk2C4LTfunUuvh/vb7BXWvPxwXdt6KkqiG52KUiiIVYNgRiooeemQKplQK/ie0MwQehoaVN0t0whDBJxK5S2GM7hMmGcBgCjyT+Q5S9EkVQeCNCPyOeqM/hBIQMouyV6Ikp45GTEIbrac3VE5srQA1J/KcKkT+IZnREAB1AiVcWF8Lif0gxqBCKeQUl21sTAhGl7ZJIQWXbK7+Ycl+NaPl+pOpxbnS/ON8dRoh1U+fNxuUzOOKxd+/eqIfZQCCAO+64A2eddRZ+//vfY/Xq1XjggQfQr18/9OvXT1fdr7zyCt58802MHj06su6HP/whCgoKMHnyZC7Mu5yrxn+N+54bix+M3I6CXJXZXhoIIQsCc5fHvOuJ8TCnxJcwlA0Bg8gCANP5fKyHQ1ANZxNtj1vfo9bJNpd294Dt9yJA/GCy+E/lgQEWefe0eQ8fJ3bWXjxan1Vle8qCaPSWgMGDgKdQsp+sdVvEzkb2k9cz+Vk48jkIIVt+9o48Gwejn5W19qeWGQRuE5YFC0LZuO0cOa6nf//+2L59OxhjEAQB27dvx4YNG9CzZ0907tw5pbq5MO8EPRHlNd8hpxkTT96MBV8PwT2jlxuqMkSyIKhNUTebTBPlFbCDckxbF54jAVMMCuhkB/QLqEn6QEoaLICFBwcOimCCiPricgiBJnTcvk7eJkqzBHweMCJ/FuRZA15pgIAJImhnUdpOpM/SsijfNEn7RNYJotyG6BujeDdNSoGjtTCTb2JonPcQwKgUDzBqG40qC6isC3+Wt4GFQGpb10W2MyZtY1S6vvK+gYIChEQfAp48RXkmL7PW4yoviFGBPNXvugt/KxxOKpRkNeAHXbfjHzsH4Zb+qwzVEYJPPWSMVtJBYFMKmha0l0ER01brQIDVXsPy8aQwBAEgUQx8LWPHJo0vS0kKBVnY98iDBR7UkJPRhG7oyNaByesoESMDANIggAe0zi/ZXsg2FyKY16NYJ0TKMiLK6zzyMZPY4ybFcol6+yN2DiGQ3LDtDLW1zYixx4i1x0p7GmujQ7KTgcKWR45LQRpkewylvaUIIB9U8CEgKOwxWNRyG3vM0cVjjz2G8847D++++y4A4Msvv0RtbS1uv/12+P1+9OrVC4sXL8YHH3ygW5gPBoOqU8tzc3PR1NT+vKjTjfKuNTht4D78c8lAXDtxnaE6QvDb83ycwVDidS75axJ02+NusDSsjWSPW59pqWxHq3KHgRIfChu/k+1oWPhXlIUIKsj2WLa1NPxsTDxgR0SwbkLrfoLy2VmIzDJI+HxcLTvcdZe3xTjgRZ5jaQikPwUJyTYzFHbGU76HACrbU0qjtiNcTrENVLLDkTLK/RhV1CXbYyrbY7lsIDsfoBSBnDzF/ixqXzAGotVr3mpRXtkGPgCQ1owbNw5EY6zLJUuWGD4OF+ZdwoVjK/Hh307C14dKMKTLYd37h4gvvse8lfHlM4iQaEHWebcIlyZ7N0tJgykQosCu1j5ryesIf10Vco/FnLiQpEKbnVkYSJTQzyBEvQNEHhAQgbAwQQR5n9ZlRJYFKAcTWj8TqQykZUYEeR9RboPQWgek5cbsLgh489HiL5K2y20FkcUXIiAcCDmR10aiG7NEZZPtlzQ57ZYtaGiwyGPG5Rw8eBBvvPEGvvjiC1RWVqKmpgY+nw9dunTB0KFDMWHCBJxzzjmajTvHAaqAST034pY1E7CtriNOKjquaR+lIEyZHwLRKfqkgxivhkXtpsQnJ91THEcpuqdrf1mAlKSQAmiRXxI+1IHBg9zYmHxhrOxDjXVLzRFk2yaCVcs2FAo7G7bHRATC9hUq9lixT8SmRwYSBMkeQwAN226QtvYYrTYdEFCfXQpGRDQ29ZBtNInYc4CAZUs2Ovl5ak/qbqY9Zps3o7GxUdNxnWDp0qXYsWMHZsyYERHmd+zYgZ49e8Lv90fK9e3bFzt37tRd/yWXXILrr78eL730UkTU37p1K2666SZcfPHFppwDx1ouP/dbzHh6PMaP2orunfXnK6OkfYaySRmF17zjyV/NxsKY85JlCAEsBLBWe+yl9SCsBrktKQgDO1NsXJJzZoBkEwURbLsAJoYd6gT5Fb2M8GcilyXyNlG2sZF9RFDRAyjrIAQQBFAh/CxNWrcTAiYI0me5HhABdT36QGxpRF1ZX3kdiZRH5Blbfj4mBKRDnGfe8GDE0MSRAaLKom3ZRNtUacfPx+nO2LFjI8tbt27Fxx9/jOuuuw6iKA2GBYNBPPfcc7j00ktTOg4X5p0ixmve7w1h6ujvsGDVEDx67kcQdOo21I6pem4RmS2CCV4INA28KuJdB7NCl+i5zjFlmSBCCLk/xrzkURcEWFBTXjc7qS4ciOaszuhy8DOnm2KMn/8VVVVVqKx0ONOSjRw5cgR33303FixYgJEjR2LkyJE47bTTkJ+fj6amJhw9ehSbNm3CtGnTkJubi0cffRSTJ092utmcMMcQFc4mzxvApJ4bMX/HEMwq+1RbQlCFcBxClvZkc1aE7kjjWNNhKLxtvRydEuPtPq5a7HQDUHjaxpi3+lx0hqshRYDkcU4le+yy3HhHC0eCAOhUnSQHlJ7rpNZHVv1mT3avPW5qasLs2bNxxx13wOfzRdbX19cjLy8vqmxBQQG2bdum+xjPPPMMLr/8cvTv3x+FhYXweDw4duwYJk+ejLlz56Z8DhzrKerQhAmjKvHKB4Nx55Vf6N5fSv6aBs92bkQWsKngg8AyrA9tTgjLINoXclgNDedKAMkLfbP8YOyysZhDp46B//gRFO7YqH/nWA96JzzYH3WvPeYkZtasWZHlcePGYeHChRg3blxUmTFjxuDBBx9M6ThcmHeSGHH+7AE7sXj7/+HNjfswZaC+P50QiTN13ixv+QwX5QH5xsNMj3kz+0xLXVqEd4vjgjPR0zZjerLjuT1OeSoJVo1ACFw3WqCT9uQRvnbtWkyePBlXXHEFdu3aha5duyYs//777+P3v/89lixZgj/96U82tZKjiyrggu7b8HHLhXh/xz5M6KPxDl4W50PMD/FEs2mhSlSPo2d7Ggr1kjDvsqdCq1G7rimI9AweyXMvXt1morX+eMlZLQqJlDJEAKgGZ4NkYZT0/maToeO7YLo9LgSQpbFsgnIvvPACevfujbFjx2L//takOqGQ+ugMTZb0T4W8vDy8++672LJlC77++mv4/X4MHDgQJ510ku66OM7xo9Gbccefr8OydfswethuXftKyV/rLWpZO6Cv5DHv3evwzBuV+PLpBCWiFCbVCKmKyBmiAzNBlELYGMEloWTa0/NxprJ69Wp069atzfrS0lJ8+eWXKdWdLMAEx0YEAbjtttvw392j8O3hYl37qiZ/5aK8Lqjg0hh6dvZ/Ct7ygIrHfDqL8nuhfUDERBiE5NPhOK7hk08+wVtvvYWysrKkojwAjB8/HsuWLUPnzp2xe7e+B0yOhRyL/ui9NYQZM2bg9e1nYevxjtJKjd7AtM4PwU1T590oeCaBwucOYd6OvqvSeBydbWEQQeoC1oesMSrKa93mIAyCHCZIA1Vo2x96+kcPVUleLmf37t147bXXcOedd7bZJggCmMo9kMdj3JesX79+mDJlCiZOnMhF+TQkZ3AAM2bMwAv/OQf7juTr2lfymLcpXmYFtMW2TjMovBBKXWCP0xgmJ2HXTSqCciUyRpQHNIaL4XAsZujQobjjjjuwb9++yLoDBw7grrvuwvDhw1Oqm3vMO01PxXIpQwmA66+/Hs88J+IPZ81Hx2xtD/chEhPKhovyujHdY94M9Pa/XV7zcdpF1Tzm4+FWUd7Id97EmQiMCHLSOpNROy8zr0E7+q9QcscddwAAzjrrLAwbNgxnnHFG3LKHDx9GSUkJRFHE/fffb1cTOVqJCWlTVlaGn/zkJ3hyUQ7+MPI55Pm02YcQ/PBDfyxcTaSB6GYGFF544d7Y2BFSDSlk4fWkJ0R4rZw63w6+i4wQwIg9drpvnD5+EhYuXIjGxkZceeWVABAR4i+77DJcc801qK2tjSpfW1vbJrxNPP75z39iypQpAICXX345Ydmrr75ab9M5DtGvXz9MnjwZT7xRhIevfRp+jXGvQvBDtDrUaywZlvSRhpOx2xz+xXJsPB9KRBDoFOaNfncy6RopYIJgzB5zOCYyf/58XHHFFSgrK0NRUREEQcCxY8dw5plnJr3nSAYX5t1CaesI4GmnnYaNGzfimZVbMHPMZxCF5KODIeKDh8lT9XiyV0OY6jFvhkhptA6j4rzW4yUoxwQPSHjat1uF93ikes1SEeeVx6YC4KHR66zqy0TnrPWY7VSQj+XBBx/E5MmTsXbtWpSUlLTZvn79elx88cWGEthxTKIT2njGqzKr1eaOHTsWGzZswJ+/Og13nf65hjSPkhDgunisyUJt2F1PEgyHsgm3z4w43qmGH0k1vImROhX1Mr8ilE0qmCHyulwojo+oOWkrRzvTp0/HVVddFfl8+PBhTJ8+HU8//TSOHTuGPXv24MSJExExvrKyEiNGjNBU94MPPoiLL74YXq83Ki5sLIQQLsynA31bf38XXnghNmzYgL+9Mxw3Dk2S90GGxjquWUU8T/kMEOmj7HE4pIyd4m+ah7EBAEZECHpC2Rj5rmSoIB+BEOOhbDgck+jTpw9WrFiBb7/9FpWVlSCEoF+/fhg4cGDKdXNh3mpKjd3QX3HFFZi1eTMWbTiKywd9l7Q8RRZEZvKTT6YIbhrPg3bxwdtSY21btGJH3xsRkpO0Swplo0FMcZtob1Z/6+1TtXBARCWUTaoivdFZAEqMDuS0E2677TasXr0akydPxieffBI17f6dd97BFVdcgQkTJjjYQo5ScNfDz372M9xzzza8d/AILuqU/MmHkixtSb6U8bW1YFVIjHgUxSljUnLSRFCkkGwu3jnp6W+zYoLHE9JTuZYa62TEY2zqfJz6bN/fBUhT57kQYDZFRUUoKmr9EouiCADo1q0bBg8ejMLCQjz22GO45pprsGbNGnz99df4zW9+o6nudevWRZaXLl2Knj17QhCiI7c2NzdHxbXnOEBf/faYEIIbb7wRv/71LizNOYKxfXe1bqyAqphpSygbreFr4rTR7VCSgclfw9jkNc+gwx7r/Y5kuiAvY9mMcg7HAIMGDcKgQYNMrZPHmHcpHo8HM2bMwMfb++C/lcktfoj4IR5o5t7ysegQD2m1F8LBFu2xxTltoKIohbJJJB7H2+aUWG/2tdby/UlQJqkQYCS8kRnsjXlx2vD888/jxIkTuOWWWyLrZs+ejUmTJuH222/H66+/7mDrOEbx+/2YMWMG3lw/AJ9uLZdWJojvHGrwQ6xu1h4H2q640HqPqaeMyfGtKbEw+WuytpqdqNOKa62h3ykMTJ1X1p1qu6zimOJlOemfjD3d8Pl8mD17Nnbs2IH/+7//w/z583Hfffehd+/euuvq06cPjh1r+0XZtGkThg0bZkJrOXaTl5eHGTNm4KU1w7CquXt0XHeVx2VJmHdRzpc0jEGvmvPFLi/2DPCWB3QMlGsV5SthTwz5Cg0vuxAEgHvMczIY7jHvYjp37oz7xi7FQ8tG43hTFv5v0LeIl8w5VO23Z6qeE2gVAVP06KWiN9rbO7y/3YKxWWFwzG63hnYxwQMSSnDjkUyUD7/bNWPArvr1nBcRgGQhlbReXy6g20p2djbefPNNnHbaaRgyZAi+/PJLvPLKK1i4cCEuu+wyp5vHSYHS0lLM/N5neGTFaFQfy8KPKjbHtceUGAxlkyhMSaoe2nrrSQUTwt0YDmWjl1REdjv2SwEGnVPnU/Xit4NYjTUmL4TZMCLa46GXbJDBwnN0A927d8eaNa2hSQYMGJBSrNZx48aBEALGGC655BL4fL6o7du2bUOfPn0M189xloqKCtx11f/w+MIzUVP/Lc47fbtio6LgVoDCDwEq9tgs73UjwmSaec5L9lilD632NrdT/LdY4KZaQtlo+U7Y5R2v53tt0/eZJ3/lZDpcmHc5PQrq8OA5S/DQZ2NQ3ZSFX4z4Ep7YmPN7AFrsh0gzTJg36hlcamBfhIV5lRsPvQJ9KmKo3UKqyQI+Ez0gnYPAEZWNbvGUd0Ks1nFMRgQIWm48rBh8SZV2PBBw3XXXYcSIERg+fDief/55TJkyBd27d8fy5ctTztLOcQd9CqvxwOgleOiLMTjelIWrB62HoCLOS8nmDHro6RW11QRRq0LN6A29kwKqHnpOk2ahWRjxgGjpw3QQ5AGbPOSj4aFs0pOxY8cCAD799FOMGjUqKnEsIQSTJ0/GpZde6lDrOGYwsPdR3HfdUjz04hhU12Vhyjkb2g6WVwC0ygPSMQjVBDFOxn8PHzsNBPqEA+VWiNoZ4iWvRLLHCYT5RN8Du0PV6B1ssuk7zATRvuSvan2Qynmm4UwZjv1wYT4NKMpuwu/HfYI//u/7ePzzMzHjeyvg98h/7nLompDgh0hNnKrnpMBmRhJOA1DBmzg+utVCaAaImlQQIVCVGw+rRfkM6LswuoQAtUEjPX1hRvJXvcfMUCorK7Fo0SLU1dXB4/GAEIJBgwZh+fLlaGhowLBhw5Cbm+t0Mzkp0jW3Hg+ctQSPrBiNOV+egZtOXdVmsJwSn7p3mVGMhlwJl0lFSI8n/GtJQJrCceN66MUSL9Gr2aSZKA/IMW2TJX9NF1HeIRgEWB7KxoEBh0wnnPT1xRdfxN13341OnTJ8ykE7paxrLR6cvgQPvzQax+uycN2P1iImnQAIWNzZbVE45cUeT7DbmmR7bDkLYfCCJLLHZiaEzUBRHgjPvlKZUZ7s+rk9frydvxkiWJ/8NdHvLXablnPngnxGMn/+fCxYsAB79uzBBx98gJKSEsycORMzZ85Ehw4dDNfLY8ynCbm+AH475jN4BIrff3o26pp9UfHkDU+ddxMOx66mHl/yxKVWtc/twqbG9rHOcox5JZksypfGvMyAiIDeqXpGYr9rjYOfqF4ebz7Cp59+ipqaGmzevBkvv/wyZsyYgZaWFsyaNQujR49Ghw4dTMnYznGewqxm3Pf9paht8eORZaPReNgTFVubNRGQKpY8tnw8zCpjpKxyn0T7WRxHXHMom3YgDhsl4dR5o9fPjhjyVmBU/FZLxu4EXLw3xI4dO7gon+EUd2zA73/xCXYdLMQTr45CSyBa2mCqrvJxcJOIpjV+tw2xvhkECHbk2nBSlLf42AwiiJ7QcgAX5WNggsWhbPT+htwUf59jGw8//DDuvfdenH/++di5cycCgQA8Hg927tyJW2+9NaW6ucd8GuETKW4f9QX+tvZU3PvhONzTfxlKshoASCOxgtZs327EBeIeFX0QksX2ToYLzsNJmOAF0dKHZojYTvV1ssS2KbbLlqnzRtrYzr/bWunbty/69u2Lyy+/PLJux44dWLNmDb766isHW8Yxk2xvEL/ptwx/2nI67vtmLH5zyjIU+qRwcgRJHhz0eJwnC1WjFa0e7EZirlsQ2oZp9Zi3g3QToWUkj3nFfaHR742dxArQneKsj90nVntVK69cl0yrlcuyHAJSTYE6jftxXMfHH3+M1atXo6Wl9f+kqakJNTU1+NOf/uRgyzhmkZ/Tgt9d+yme/Mf38NCLY3DXVf9DXrb0LJLUHseSZvHfo0jntmc4lHjb6jRuCl+jFwe+Z4wIbZ3/zApHxUV0jkaef/55zJ8/H6NHj8Z9990HABBFEQ888ABGjRqVUt1cmHc7lzJgUetov0CA605dizdbBuC29ePRM7sWJ+cfRZ/CfHRuyUKRz+bM8/HEOjvisZsMFb0QghqEALND2rioD+KiRXAulULZRBlNq0L/ONFnWs8lVXGeEGtj6KXD9y2NWLJkCYYNG4aiovjqZO/evdG7d++omLbLly/HwIEDE+7HcRlXMmChbI+rAI/AcPPJK7FgxxDcuOpClOfWoH+Ho+hVkI+SFn9EqDeM2aJoIrE/1XqBtgJ9CqI9gwBih4deBsOIR/LQc3vC2mSiu5n1qZVJJP4TIdoeaxkEsEq8tzjRbSby6KOP4v7778eIESOwcuVKjBgxAh6PB1988QWuueYap5vHSYW+DKhsfT72+0K468rP8fy/T8X0Ryeid/fj6F9+FOUVeejq96EgV8dAr1aBm4t50aQSbz5DQ9iEkULZKJ6P03kAxam2E6F1Rrnab8+oSM9/xwCAo0eP4s0338SKFSvwwgsvxC23YMECLFy4EDU1NRg0aBB+97vfobS0VSSpq6vD22+/jX/+85/417/+FbXvypUrcdNNN0WtKy8vxxtvvJFy+/ft24eHHnoI69evR35+Pv7v//4PP/nJTyLb//znP7c5r0mTJuGee+7RdZyqqioUFxe3WV9dXQ2W4owOLsynIYQAk0s34ofdKlF5ogibajtjd2MH/G3dBBR4m3Fy/lH0l1+l2bWqyelMIZHAlyhhqt3CoEahlGr19jYTK/tCywBCacyylpjjsWUUdTDB0xpj3mgIGy3fKzsxMriQgjgv3bypCFJ6kxCrwUV509m1axd++ctf4rnnnsP3v//9pOXr6upw//33Y9myZfjkk09saCHHSgQCXN3na0wp24AttZ2wqbYzdp0oxHOrf4giXyP6dziKkwuOoX/BUXTPrtMW6zZVYgXVogTbrDiuCWNNusIPWEmaessDAIUI4biBmZRpfM6GSCDkMyK09bhVCuTxPPO1Cug8RI2l/OlPf8KiRYtw0UUXoaCgAK+88gr69OmDP/zhD6isdLtLKkcvosgw/ZIvceUFX2Pz7s7YtKsztu0rwl/nX4SSjvU4ufwo+suvLkX19thju7HAa9419jiNYUSMnsGWCP7XpAoTBJByBnTWUFhrcmUuygMAHnroIbzzzjvIz89HVlZW3HLLly/HX//6V9x3333o3bs35s6di7vvvhsLFiwAADz33HN46aWXkJ2djePHj7fZv6qqChUVFZg7d25kncdjjhz9m9/8BiUlJZg/fz62bt2K+++/H7169cLZZ58dOfakSZPwi1/8IrJPonONx+TJk3HXXXfhpZdeAiAllN+yZQtuuukmTJw4MaVz4MJ8OhDjNR8mWwxiSIfDGNLhMDYX7cOVp/0Lu+o7YFNdZ3xbU4JFe09Bsa8eDw9e4kCjZZwWAksV78naQggEPUk3YwVSp89VL0YF3nBfquzPBBGEphBSKRVRXm17KiK2lYl+EyCFsmGJ47oDjrWPE80111yDHj164Kc//Sm6du2Kiy66CKeffjpKSkqQn5+PmpoaHDp0CDt27MC7776LpUuXYtq0aVi6dCmys7Odbj5HL1cyYE5be5zjCWJY0SEMKzqEzZ334opR/8KOEx2xqbYzvqrqild2DMZJ+VW4Z9By69qWKElsmk3M0B1+gNMGBo/+mLbtTZRPAov1mA/jlKDOveZ1UVVVhcGDBwMAOnbsiKNHj6JPnz6YOnUqRo4cieeff97hFnJSIsZrPkxeTgAj+h/AqScfROXx3bjizH9h+/6O2LSrM1Z8W4qX3huG4ScfwC2XrTJ+7HYk6Fluj93gLW+DGB75ptrtcR6vf42cs1Pe8hUAiglwSOc9TTv6naZCUVERXnzxRVRWVmLevHlxy73//vu44IILcO655wIA7rzzTlx88cXYuXMnevXqBb/fj6eeegoAcP3117fZ/9ixYyguLkbnzlpGV9T5xS9+gREjRmD69OmRdbt378aGDRvwxz/+EV27dkWfPn3w+eef4/33348I88eOHcPQoUNTOjYAzJkzB1deeSW6dOkCSilGjBiBmpoajB8/HnPmzEmpbi7MpwtKcX6PehGRMPTJq0afvGr8sNtWfHDwJHxbW2JfG92OCfG/TcVNbQmjtY/iiMJU8EihbMwWjY0K9gm8+xPioOjNiAAc0jBApEegt/q7Fuc/qb1w/vnnY+PGjXjjjTfw+uuv46mnnsKhQ4dACAFjDF6vF4MGDcL48eMxe/ZsVFTwO8W05mZ1cR5A5PHVIzD0LahC34IqTATw5u7+ONKca12bkgmqRsR5Ix7waTYAkMmwZh3J5rggHwfBWM4XKwX08KAAF+iTctZZZ+Hxxx/HY489hpEjR+LZZ5/FKaecgjfffBMFBQVON49jBnHEeQCgzAeBtMDnpehffgz9y48BYzbj5f8MgSjywV+OfWiedWDmAEGyAQ/ldjd76cuPTAwuScZuBDcMPiXghhtuAICkM8m2b98e5RXeo0cP5ObmRoT5q6++GgCwZs0a1f2rqqoShnD99ttv8fjjj2Pbtm3o3bs37rzzTgwZMiRp+7dv3478/Hx07do1sq6iogL/+c9/NB9bKzk5OXjrrbewdetWrF+/HgAwYMAADBw4MOW6uTCfIaiNZq+v6YJTCw840Jp2gBne8k4OFFgkPDNBhJDIYz7RcZN5iGtdn4hk4X2c9kLfC6CzSnKbZPsA8duup5+SCew9NZZrh3g8HkydOhVTp04FANTX16OmpgZ+vx+FhYUQRdHhFnLsgMGjmoh9/fGumNDD4ScfrUlnjWKiKM+nzqcOg8ap81yUj4ulydhT9brn3vNJeeaZZzB+/HhMmzYNDzzwAM4//3wUFBTA7/dj/vz5TjePYzEh5ocotM29tr6yK66Z+FXinROFhGlnvhWOiMqZil0e53qF4HB5N13DmN8ZEwwOlJuFy8V1O6ivr0deXl7Uuvz8fJw4cULT/lVVVdiwYQMmTZqE5uZmnHnmmbj99tuRnZ2NQ4cO4aabbsINN9yAs846C0uXLsVtt92Gt99+G/n5+brbVVBQgPr6+qhjv/XWW/jLX/6CnJwcXHLJJbjqqqs0nnlbKioqTHe048J8OhH2mu+JKGFMzWC2UAHf1pTg2l5JbjyM4kZvb7twWry1mlTiowsekG4h6M7ZZ4cor9xX7Ro6fV3lc5JuPAx4BKTSJ1qFdqcE+RIAWtM/eK1siHZyc3ORm2uhhzTHWeJ4zVPBB5FFCwEnAl5sPVGEwYWHrWmLHmHVKhHWZE9514WyUUts62aqAJQguZzi9vMAEsdztxgpxrxBIcAO4TzRMdp5/HpKKf72t79h7dq1KCgogCiK2LZtGzZs2ICePXumPJ2d4yLieM1T5odAopOwH63OxpHqHPQvO2pX6+zFAuFXkz3mSV8TYmkfKkm1PxMl8LVrUCGe1kmIemg5K3Hz97MnoDVtAQBTVF9K2/Z/eHa4Fvr27QtRFDFlyhQcP34cjz76KGbPno2ZM2fijTfewIgRI3D55ZcDAK666ir8+9//xv/+9z/s378ff//73wEAzc3N+PrrryNx7Z955pm47VKuHz58OMrKynD22WdHPPM7deqECRMm6O6H+fPnY8GCBdizZw8++OADlJSUYObMmZg5cyY6dOigu74wXJhPN1TizVPig0Cjs80v2DUE/fOPorO/Uf8xMll0Nyo6G/H01lqvVf2danx1A+1iQpKp81pj81shyNuJ3nYqyseNaWsF3POdwzGOijgfErKi7DFjwAvbhuOMTnuR65FHl1IRsd0opGZy+Jp45xZe78brIbcpqZejG9uuhhaB2SoROlV7HE84N7O97VyAj4cgCHj11Vdx7bXXomPHjgAAv9+P4cOHO9wyjiWoiPMh5odIWu0xpcBzb4/A2FN3wuPRICSpJZBsd97yGnCTl7URbGi/plkHiURxLbhZRNZKgt8XI6J9oWwyoS8tQBCENiI4Y0zzrPArr7wy6vNtt92GmTNn4p577sGWLVuwYsUKjB49OrK9ubkZBw4cwOTJk3HeeecBAGbOnIlBgwZFBPzi4mLs27cvabt+//vfR5b79u2LrVu34t1339UtzD/88MOYN28ebr75Ztx7770IBALweDzYuXMnbr31Vrz44ou66lPChfl0ReE1HxL8EGmrh97nR0ux6ngP/GHwR9Yd323x2s3Eac9pteOb2dd646zrODYrEEH2JRm+VYrzXJRvW54IICojv6bDRXkOx3RCxAeRtXroLT7YB9tOFOGRYSbY43hCalGCbVaTSJS3QrC3MpGtsg+1HsPJvldD0ZaEHnpuarOLYcSEmLZcOHeMH/3oR7jxxhtx7733qgoHY8aMcaBVHLsIMT8E0vp8/Pay/qiuy8IdV3yur6J0EeMt8Ghm8CYOiZbuorxNEDBrPc7NFJLjDRAkCu+UKhp+Y4wQe56PuSgfl5ycHNTV1UWtq6urSxpqJh59+vRBS0sLqqurAQATJkzAtddeG1WmoKAAHTp0iHii+/1+FBQUoGfPnpEyubm5bdpVW1ubsF29e/fGqlX6E4A///zzmD9/PkaPHo377rsPACCKIh544AGMGjVKd31KuDCfjsSEtKGCH4IsBOxvzMNzO0bg1ycvRwdvc+J6Mp14ArRyvTI+d36CfeJhhlis5ZhmxLQ3ik6BXlMkQjtD19iFSW2UYtpa7BHARXlLoJTi7rvvxsyZM3liufZCjNc8FbIgyAPl208U4tWdgzFr8FLkeOQHWyOisvDlx/AAALcLSURBVBtFdy3bDWJbEBuz+lXZD05cK73HdJMo73rR2sIY8xzL+ctf/gIAWLp0aZtthBCEQjry+XDcT4zXPKVZEOVQNht2dMY7y/rh4Rs+hs+bgb9piwRTCi+EeLEkUxXl3SCApvvAghv6MBX0DHoRAfpj5eok3fvTYnr37o2NGzdGPu/btw/19fXo06dP0n0ppfjxj3+Mhx9+GIMGDQIA7NmzB16vF4WFhejduze++uqrKMG9oaEBOTk5mtrV0NCAXbt2oby8HACwdevWSLs2b96M22+/Hf/617/g9Uoxb/fu3Yvi4mLtJy9TVVWlul91dbXmkD7xEFLam+Mcl8oXvicQ6p4FkbagOSTiicpRuKTHRvQvMPi0kw4CqBb0eIU77SFvhGRttuKcNPRVSgn74nnPJ/tO7ol52Y2WNibaNwYmCECicECpwkV5ywhPnd+/f7/TTeHYyc2tN2Ih4ofIWlAf9OLJjaMwrfd69Mqr0V9nleKlBbNE8iLFK1kZi9rDEgkBZp1nsn41Kl5bHdanSuWld3+OZpgdQgDHMiilcV9clM9Q+irsMfNDJM2orvPj6de+h+mXfImuneoT7JyGbIWlntgUPghoabsh3QVtu6k2ub6+0CYiV8S8UsWs2SMG2sPizSjvm+ClFb3l2xEtLa2//wkTJmDJkiX473//i+3bt+Pxxx/HkCFD0KNHj6T1CIKAkSNHYvbs2di8eTO+++47zJ07F+PHj4cgCLjssstQWVmJp556Crt27cLKlSsxefJkVFYm/7Pp1asXBgwYgMcffxxbt27F4sWLsXjx4kiYmpNOOgl+vx9//OMfsXv3bixduhRvvfUWfvjDH+ruj8mTJ+Ouu+5CVZV0Q00IwZYtW3DTTTdh4sSJuutTwj3mM4AQ8UPo2IQXNgxHsb8BE7ttcbpJzpCCGJ2SoOwU8cIJJeoHMwT7eN77pSkk7NMT0iZMPIE5vL5nnO1mkeogVtz9LfKY54K8LfCp8+2bkOCHEGrCn7echv4FRzGuy87WjclE21RFU6P16wnbYma5OFB4QTRnezaAmeK0lUJ3urQzgzEllA2Hw3EEyvwQ0ICnX/8ezhyyB2ecss/pJpmLDck4VT3mnUpSGu+4RgXVdBxc0HOuasK3Wt4EvaQS0iYVYV8t+Wuy/uBie0ocPHgQV111FRYsWICuXbti9OjRuPHGG/H000+jtrYWQ4cOxYMPPqi5vjvuuANPPvkkbrrpJhBCMHr0aNx+++0AgG7duuHpp5/GU089hX/84x/o0qULfvazn6Fv3+iLOG/ePNW6H3nkETz44IO4+uqrUVBQgBtvvBHf+973AAAejwdPPvkkHnvsMVx11VXo2LEjrr32Wlx44YW6+2TOnDm48sor0aVLF1BKMWLECNTU1GD8+PGYM2eO7vqUcGE+nZFD2lD4selQPr497MMfBi4GMaox6xUanY4zb6JXOBU8EKhOIcANswtir4ET3v+KYxoa4DBTlI8tE0+cV0tCqwfLRHnJYz7h1Hm1c080CMEFeVvhU+fbN5RkYc3RzjjY2IyHhn3cao+tFuW1kIpgbkcsebkPKPFByA4AWSbVq3IMzWVjz83q68QFdHvQnKtARQjgpA2xsWpjeeGFF2xqCccJQsyPT9cWoiXQjCvP/9rp5piHDYJ8GEmYV3jMOyVmJzpueJtbRditAE7RWDZefPdUBXm1MnaJ8yZ52UcNlLv1Wqc5EydOjPL67tq1Kz76KDpH1rRp0zBt2rSE9YwcORJr1qxpsz43NxczZ87EzJkz4+63YMECAy0HSktL8de//jXu9vLycsydO9dQ3WEopbjvvvvw4osv4siRI1i/fj0AYMCAARg4cGBKdQNcmE9vFklP/AcaOuLjbT1x+6j5yKtPwcvMaaE9HjaIzUzwgugV5t2C3mSuibbZff2tEuUBazzm7egfIgBqU/USnXe8WQJclLed2KzwnPbFnqZOWHqgB24fsBBZojwIY3V4EyuxK7mrQpCmRPbQC6+zK3yN1fs7XT9HN4yIPMZ8GqMW7zUYDOKtt97CBRdc4ECLOHay80AxvvgmF7+54jV4PBkw88VGQT4MhQ8Ck5+PzRLl9YqqWo9bqaNuo+dixzUwKjrrFcATec/HGyCI3T9ef1iUMJn0zYDfMSdtCYesvfbaa9G/f39UVJj7RefCfJrTGPDgX1uGYEzPSpxUdBywO3SeVYKuzZ7fVPDp95jPRFIcnDEcyiaMWaK8Gce2aqAqSZ2Sx7zBfuRCvOPs3r0bPXv2BImZutTS0oL9+/ejV69ezjSMYzm1AR/ePzIQF3VdgR45ddp3dKsg64AoD8ge86wlervTgxtuvUYcS2FEAOEx5tOWv//976rrX3vtNcNeeZz04Gh1Npau64f/O/cddC5sdLo5qeGAIB8mEsrGKVFeL1rEeSPn4uA10IQVQrhWcd4mWEcC8BReHIexMmQtF+bTGMaAZ78cga7dWnBGt+3O5qdKRaB3QfJVKnj1CfNunFmQCD1x5+2aORF7DDNFeS3e8snC2TggygPhqXoxP2YuuKcNvXv3xsGDB9tkbN+4cSPGjBmDmhoDiUA5rocyYM7mM3BSv3qMyNsNtVxpqrhV8HVIlAdkIYAp7LEZxzPaz3Zdn3SJVW82nQAcc+C4Wr9TajFtOWnP9773PUyfPt3pZnAsIhgieOq17+G0ETUY3CeN48q7QAymxAvhgIOOa2aHznFAlLfUx9ushK7xzlGLOG8HfU1w/uNwTMDKkLVcmE9jPtx2EnYc74gZ398PUbMKYDFKoVPNA9lqFIlI9UAFH4SQS/rQDRgU59kJYkzQdtJT3ihWDV4QIVoIcOO5c9owbtw4EELAGMMll1wCn88XtX379u3o06ePQ63jWM2/9vRHbcCP07scgVDX3LrBqKgcK6ba6TFudugYtfoSiMWRUDbtBauSvBaYXHc7hCd/TW92797dZl19fT3mzJmDrl27OtAijh288sFgeEWKU06qhkCak+/gNlwgyIeJCmWTKukYF9yEayGFRDM5v5TZnurJxHnAOYE+Hb83nIzFypC1XJhPU7bP64h/fHs27h/3CYhnHMRAk9NNaouTnvA6k3tKHvMZKszr8ZY3iixSk1IXPMDqiS1vJAmsxbMJUgplw3GMsWPHgjGGpUuXYtSoUcjLy4tsI4Rg8uTJuPTSSx1sIccqvn2gBO/uG4VHhn2MBuFHEJlGISCeaKq23ux460br0rJPbPt1isOUeM0TAtyOWcJ5OgvwTnnNa4AhSTJ2o1iVP8HpkE8uo1evXm3CyjHGUFZWhhdffNGZRnEsZdXbPbB8/an44y8X40iwAqLgwufjeLhIkA9D93ujQ8u5HReKuEzwgNCgOZVZGTomWUJXtb61WqxXHJOBxC/nZmwM98NJb7gwn6Ys2dEbF1RsRVmHWuyEH2I6GU2riBcaRYPwqjuUjZ52aGyDI8QTpu0M1eO0t7xWcd6mPmGEgFDZs4J7y6cNs2bNAgC89NJLuPvuu9GpUyeHW8Sxi48O9MGkso3okl2PrYIfIrXQQ09rvPV4XupGhTsjgrxBKHytHvNcaFQnSV+n3QOsmeK8mbNNCIGuOJFajl2lspxKG2Pr47+ZCDt27GizLj8/H0VFvJMylcUrT8IVF3yDwvxmHK7ygMAkQdRKXCjIAwAqAZrvhZeecK4NWkOpuFCQD8OICCFVYd6t4q6Wfjcq3sfU7fpQNm69RhxTCc+QV0MQBPTs2RNTp07F+PHjddfNhfl0ZBFBS2gkOvilh39KfBCQRh4BVpCiaGqaMB+vHUY8s51Cb18qyrM4f1SGj6VXmNbjLa/Wjthr5EQuASJICSQ4aYPSSPfq1SuhZ/ySJUvsahbHDuYQtNAz0cEbtsd+CFo95u3GbC3KIi9tyWO+JfMFRr39p6O8JVPnrcQqUT7eujAavmOa7mr0zH7RUy5Z++Kdb6b/djRSXl7udBM4dlJJ0BIciw65rTZY72MJJxrTZrBZJZzrqVevQGzSgAkVPMZnXtkt9oaPZ+ZgUew1SnYdXDzIEoGL8O2W4cOH49VXX8XPf/7zSPLXYDCI5557Dj/4wQ9ACMGkSZPwzDPP4LrrrtNVNxfm041F0h1GkArwCNKffIhkaZ8673ZSSSKbAlT0mecxHw+zxHll3ySrz+YwLbpCsLgxga4L2hRJ/sq95dOGsWPHRpa3bt2Kjz/+GNddd10bg81D2WQYc2R7zAR4SOtDV5RXTzyRLBUhL5nwZoUoZ2OoFEq88NK61vNUO3a6C496+tNA30vCfBp4igLOhrFJVcRO5xBCGUoib7ZY+EB5BlEpXfNAUIDHk0YJm13sLQ9I9pi4dVZ+Ogi4ABjxGLPHToq/Vgj0YZTXrTLOehVcMROQC/Ltnq+++goLFy7EOeecE7V+zJgxeOihh7B06VKcf/75mDVrFhfmM5ovWv+QAiERXlHyhmIQdU/V29+Yh8+OlmPZkXJM6FaJi7o5mHJbTTzWK9AbTFYaxtRQNolIRZxXOz+DyW41168DXQZTy7Hs8pZ3G4QAu9PooYITCWMDSKLAwoULMW7cuKgyY8aMwYMPPmh30zhWMUdhj6kIr2DcO3l3fQE+PdQLy4+U4fLO32Jcx50mNDB9oVB46CUawEh3cV4LBoVfRkQI6SDMmynKGxXJjX6X7BDlE7WNDwqowgfK2yGVCnscbH0+1gtjwI79hfj0q174/Jue+MXFX+K0gfvNamVbXC7KA9KsfNGO5+NExIazSRNBPgwTxNYQpVpIRfw1O1GrWlus9KZPgKOhbLggz5FZvXo1unfv3mZ9jx49sGbNGgDAqFGjsHevfmGNC/PphixABxQe8wxEkyR6IujF50d74tOjvbC/MR+jOu3ByKL9qKzrBDghzGsRk1MU3LVCBR+8LbXWHwjQL85rOX+zBX8DMCHB1HkXeKKnC1LyVy7MpyurV69Gt27d2qwvLS3Fl19+6UCLOJagEMWCrNUea6WmxY/lR8rw2aFyHG3OwfdLdmN4xwPY2likTZjPYGGaEm9rjPlEaI3P7TYBU+usiBSgJIWp83bhpoSv8fq7KcG29koBgByNZR14yuQD5e2bYEi/x3xVTRaWrS/HZ1+Vo67Bh9HDduOUPoexdW+RdcJ8GojygIs85tNMjFdC9cxgMyIAq/VNPK90M7BarHcbXJTnKBg8eDDuuOMOzJs3Dz169AAA7Nu3D3feeSeGDRsGAHj33XcxYsQI3XVzYT5NCVEBXlkISDSCGLwlgHXr1uHTTz/FurX/wykFh3FRty0Y0XE/fALFprpOeG67/MWxQzw1Ih6nIs5rPJ5tHvNhtAjpZlwPq2PbR8WXF0FCKjceRs6jvXrLA2AnBBDqckGFE5ehQ4e2MdgHDhzAXXfdheHDhzvcOo4VBFsEeE9QoGOcArKI3nJpM9auXYulS5fiu3WrMLTjQUwp34DhHQ/AU82wpq4b3qk72c6muxJKfPpi2pqZ7NMNmCAEG546bxdmi/IWieeumDqvNgjHBws0wQfK2x/BkACvBmG+qWcjVq9ejc8++wybNn6Jkf33Y9qE9Rh80mGIIsPSteVYtaGHDS02SFhstViwZoIXohkx5t2A1kSyJsOIJ3nyV7ME+WTlrDp/K0PfyNhuj7kgz1Fh/vz5uOKKK9CzZ0906tQJgiDg2LFjOP3007FgwQK0tLTgH//4B5544gnddXNhPk0JUEF9ql5PeSrepkJ82vMJLJ8+HZ06dcKYMWPws5/9DIUvRCsHpdm1ONCYh9AeApFYOEUoVXHYYs95XcJ8ogSveognmhs9T4cTzDLBhKzzgLHY6nuQGeL8HkihbHjy17QlbLDLyspQVFQUMdhnnnkmXn75Zaebx7GAABPgJSFJLCtAlCc3Y0BlXRGW+h/BF9Ono3v37hgzZgxuuukm5D9RIJWrlt5K/bXY2yyvOwagk62n4RoovCBIwUNP6UnfTgXMtIoxnwoWX19Hp84rUYrz7fQ7bQQ+UN7+CASl52O122hKgY07i/HptvuwcuV09OrVC2effTZmzJiBnH25UWVLS2rx1tIB1jQyFfEyVlhVE1qNivUqdVHic4fHfBrDBA+IGc/HYVIZjDE71E0sFgr0ttpjLspz4lBRUYFVq1bhm2++wdatWyEIAvr27YuBAwdGyixbtsxQ3VyYT1NCVMCKvaXI87WAlUojiFWNWVi2qxyf7SpHnVCOs3qJ+N3vfofy8vLWHW9nwBMkIv7mIYA8oQUHg3no4a2zprFOicU6jmu7x3wYpZhu1cCDTYK9atZ5veeUSsJTPeK88jguFPRd4KPHMUifPn2wYsUKfPvtt6isrAQhBP369Ysy2JzMIsQELKsph4fQiEfP4ZYcfLapHJ/VlSOQ2wtj+uTjwQcfjIhDAIBZDLi/9ddeUluPppAHNYf96CA2t1txnhKfOR566ShgmtRmaeq88bwHltMJqXnNp+O1NYtkA07pPmPERPhAefsjFBLwydreOHPIQZAsyY7sP5qHz74qx7J15RD8fTBmTDH++Mc/okuXLq079mVRsepLi2tx6HguWgICfN40m8VqxJs+jlBLiQnPx+kahqYCpgjMSe2xVhHYzH6MrcvBVIOug4vynCTMnz8fCxcuxK5du/Dhhx+ipKQEd911F2bOnIkOHToYrpcL82nKT4atw7Jd5Xhm5Rno39wHCzaNw87qQozovh/TfvkHDB48OJLoqA0KsZQyoIWJkref20nmNa/crlOIpoIPhDrkEWCmIO+g13wbjwA955WKIB9bTzKhPfZY4c9OC/RyO1wxdZ6TMoMGDcKgQYOcbgbHBqZ3X4PlNWV4fM9oDCwpx8vbz8He5gKcXrAPv/jVYxg4cCAEQYhfgSxQBiDZbJHQ6G3tTJx3TUxbK7BaUJa/SyzXA6EwQz3mbRTlXWuPufiuCT5Q3v64+bKV+Pzrnpj9yhj0PbkcB3f/AAeO5WHUoL24+fbZOPnkk0FI8t91c8ADUWDQUNS9aBXoE4iylHj1hZZzO3rD2ZggzjPBAyHVgXKrBzfSQKi3xR5zUZ6ThIcffhjz5s3DzTffjHvvvReBQAAejwc7d+7ErbfeihdffNFw3YaF+cWLF+Pjjz/Gr371KxQVFWH79u3473//i0OHDqGgoABnn302TjvtNNV9Q6EQZs6cCRYzz+y3v/0t8vPz8fHHH2PlypU444wz8IMf/AAA8OyzzyIYDOLGG2+MMqiLFy/G9u3bMX36dKOnkpZUFB1HRdFx/GTYOnzlqUBLqBJDux5EjjcIyIkH4vIEA26X+nB3oAOyhSCKxQZrGmq3SGzweFTwOp913kpsEOylrPMGhACzRHllffFE9kTHciocTkybXDN1npM2cHvsLP1zj6F/7jEEhM34Oq8rAp03Y1juQWSJISDZ4MwsBtwi9WFlSxG6e+qQJ9hgi7QmTnUABo3JXzONVATnGO9zJnhA6oKt69vZ4I5ZuMoeZ3DCZ6uxc6Cc22NnGVJxGEMqDqOhZRc2HcxBqM9GDO17UPJ679s/8c5hr/m+wMYVndG33zF4B8gD5W4QKo22oRLxhd0kdTIigiANnPesJEVxnhERhKbQh07MOLA65I0BLLfHXJTnaOD555/H/PnzMXr0aNx3330AAFEU8cADD2DUqFEp1W1ImD927Bg+++yzyOejR4/ihRdewLnnnoupU6dix44dePPNN9GxY0dUVLT9lp84cQKMMdx5553w+/2R9bm5uaiqqsL69esxbdo0/POf/8Tw4cNRVCTdie7ZswdffvklRo4caaTZGQkjPnTw1qOip+yefKnGPy1ZnN/QXIwBviPp4xFgUax5Knid85g3m2Sx6y0S6KkgQlBL/uoEaiK7lgEAO73nzR6Q4LRLuD12D1T0oZNQi14F+6QVszTa42ckcX5Di2SP22Cm13ys+OtCgT7jPPTCWOXprRIShhIx2kOvHc684HDshttj98CIHyUdj6O0bL8sMmq0x30ZAIING4oxcKDCHrtQqNSFst06vMYZiFvnDRnHSBLYFMR5JnhA4t3TJBODnQ4D5FDC3JTgAjvHQqqqqlBcXNxmfXV1dZtBdb0kmFsdn3//+98YPHhw5PO6devQvXt3jB07Fp07d8Zpp52GiooKbNq0SXX/EydOwOPxoHPnzsjPz4+8BEFAc3MzcnJy0K1bN+Tk5KC5uTmyX3Z2Nt5//300NTUZaXb6M6rtxabEDwHG+2NjSzEG+I+m0qqMgDkVY94J9ipeJmJ6cptU2RPzchqN7XHt1HmOK+H22CFURHcqZEGgzSqFtbExUIwBPhPscTwBOJEw7KKY3Qwu9dCrSvAyAyODI3HitKva41RiupuNkbaY2dcaMc0em/W9cdHvlNMWbo8doq+KPWZ+CF2bDQubGzcWY8CADH0+1iG0umrWkNMYFHwpESGk4jHvNE4PDmilAlyU51jO5MmTcdddd6GqSrohI4Rgy5YtuOmmmzBx4sSU6tYtzH/33Xc4fPgwxo4dG1k3YMCANg3xeDxxY5yfOHECeXl5qtvCNxz33nsvsrKy0K1bt8i20047DaIo4qOPPtLb7IwlBD/EFGKx7gvko9xbbV6D7MACj2/Hkr/qIVbYTSTyahXeTRTpJY8AnTcebhDMY7HCW96N58lJe7g9dhchwQcxBWF+XzAf5Z7qthuMeDobFf3MFpsN4rrhyWT94YI+UxLXHrtBnNfbBgf7lotSHK1we+wi+gKhHn6IojF7zBiwb18+ysurzW0Xxz3YKDYzwatuj93uLQ9Igzh6POa3wpSEubrggjzHRubMmQOPx4MuXbqgoaEBI0aMwIABA9C1a1fMmTMnpbp1hbIJBAJ45513MHHiRHg8rbv26NEjqlxNTQ22bt2Kc845R7Weuro6tLS0YO7cuaiurkaPHj3wox/9CJ06SU+fV199terNidfrxYUXXojXXnsNp59+OkpKSvQ0PzMYxYBFrY+sIeKHyIx7SNRTH/KENAvhYkkoGwOiciwWhdkBkFzYjRcfXU9s+RTj0FPBk94eAVyQ56QR3B67gFkMuJ9EhMZQeRbEkI322OqY07FiqNXhbuTjMQ+JPna849oVc1uPKGxnHPAEAjclIgiLM4PNybA2ekR5Fw10uAoeaz4hylAyyRgzZowpx+T22AUo4sMDAKVZEARjwnwgICAYFJGba5HDlgkJRe0io2fx2hTShhERQsi404Zj6O0bO7/TXIjnOEROTg7eeustbN26FevXrwcgDcKbkVRelzC/ZMkSlJSU4JRTTom478dCKcWiRYswYMAA9OyprnR16NABvXr1wplnngm/348PPvgAL774ImbMmAFBkJz443kMDBkyBCtWrMA777yDn/3sZ3qanzlc2irOU5IFAcb/7BuYF7l2JJozC4uEb+LWWw8zhF2bxHnDyV/dABflOWkGt8cuQZG8ldb5IfiMDXS3MAEBiMghMfY4mYCaSKSL3VaE1MTOePuaLBK28VKOjYNfFbPNKpHSaF+ptcnuECzJps47Ic5rFeXdJshblYeBi+uWoPRYTwQhBKGQOc4k3B67BDk+PACEQn6IorGB8vp6H7KzAxDFGFuUbrG2TSDjZw3ZEEOdCSKEeAPl8XCDt7zLYIWEC/Ic11BRUaGaKyYVNAvzR48exeeff46bb745Ybn33nsPx48fx5VXXhm3TN++fdG3b+s/zuWXX46HHnoIe/bsQXl5edK2/OhHP8IzzzyD7777TmvzI+zatQtHjhyBIAgQRVHzSxCEqGz3bkEKZWNMmA8ygmbmQU46CfNOY5VHvBp6hd14XvOAvsSvBsV5SZhPY495M0lBlM/4m2BOymSaPVba2bS2x6LfcIz5BuqFnwThIYrfv1bhVI84bwV2JZBNFDvf7GOnKg4bbVOqgycymkLLuTEhrNtEeaWuZ/Saqp1Tqt9X7jUfF0qprcfLVHsctrXh0Dth+xz72a32mFIfvN5a+ZO+++r6ei9ycix+Ntbred0OBwVsQ684r/PaSTPYYv6X3C4wu8VbXtFP/PmY4xTjxo3TbOeWLFli+Diahflly5ahpaUFzzzzDABEss4++eSTOOecczBu3DisWrUKX375JW688UZkZ2drbkReXh5yc3NRU1OjqXzXrl1xxhln4L333otKsqOF8vJyFBYWglKKUCik+mppaWmzjlKqmmlXEIS4YoLa+vC6lG9iLpXaQquqIIRCgEp24ITcTtBAffCRILzE3ptYw9gpijuNVd7WWgV6A+K8FMpGh0eAWzzKrfCW53AspD3Y42AwmNAeK887jFIo0GOTU7bHz8j2+PBheL1eoGNHffvfT9DQIQ+5x1uMC6VOi/Ph4yD1Yxmav2bWOZopDIfbpDcUjhaSeJ8z4oEQatBxYItxQ2z7eKiFbLJzEMgoNs1gSTe0hrIhhGD06NEpHy8T7XHY/sba5JaWFgSDwSibnej5ONmge+x6c0R+qS2h0H6IYj6AfJ37EzQ0FCE3N2b2WzsVxl06n9x8LBTnpWTsaeQE6QZR3u0DF5x2hXIm3tatW/Hxxx/juuuui+SLCQaDeO6553DppZemdBzNwvx5550XdQNTW1uLefPm4ZprrkHXrl2xfft2vPPOO5g2bVrS2HavvvoqSktLI/U1NTWhoaEBBQUFmht+3nnn4euvv8aaNWt0x9IjhERuAlKFUhpX5A/fxMQKCommTsYK/cmWW1paJCFAD09IRrae+pAbO23ebFKMW+4qjAwMWBl3PhUsuC7SjYdGj/lMFuVTPLd2cxPMMQy3x+oksseBQKDNNi32WIsdVtpjv9+vr9H3y/Y45EOumEYPbonQKtDHETkNe0WlKppa4a1thSivASqI8OqdOu80VnrL6wkvpFhviT22Y2ZJOxbn7Q5lw+2xOmH7qhT6w+sCgQCam5vjDrqrEW/gPZ6dbmlpiYT/0Y5sj+t90fHl260ob4KXcjqFZLEorA0jMTPY3Jr01Q2CPBC3f/jzMccpZs2aFVkeN24cFi5ciHHjxkWVGTNmDB588MGUjqNZmM/Ly4uKaxc2doWFhWhsbMSCBQswevRodOvWDXV1dZFy+fnSSHUwGIwkxDn55JPx3nvvoUuXLujYsSMWL16MoqKiuDH31MjJycH555+Pt956S/M+VhAW0pXJfozCGFMVFsKfY4V+Silqa2tBCMGxY8ei6gEQ8TqIvWkRCs+FGGzBkWYPevq6orrDAIihFgi0SXoPNUOk0nvKBtks8VePuJ2srJE26RXXS1WWtdaRirCbKJxNLMnEeZ3ifZQw78bBiFhcKMoDfKoeJzncHqtjhT1W2uBYYSF2fXV1NWpqanDo0KGoeoBWexwrJAjF50KkzTielYPu6IaavAEQaDMEKtth2iS/t6T23+BEiJB4AmFsjHjEKWfmMbXsl0EwomOg3Ar0eshbLcobRPU3p/c7pvTAt0swb8fivN2hbLg9VidsjwHoH7COwYg9rqqqQmNjY9QgA2MsyiM/2h7fAFE8F8KhJtTuKkBJQUfUfDsAAmmCSFogkGaIpBkCaYFAWkCICffqLk8Cy6AhJFp7RuP1o4Ii50smiPJWfmcT9A9/Pua4gdWrV6Nbt25t1peWluLLL79Mqe7Un14BfPXVV2hoaMCSJUvaxNV59NFHsX79eixduhS33norAODUU09FXV0d3nzzTTQ2NqJnz574yU9+onuE/rTTTsOqVavMOAVXoPRU0OoFv3//fuTn50du8GJpczPzXgVCTVmgTX60hEqQ6yVozipGSPSBilkIiX5QwSe/+8EIiftHKNAAhJAkGAihZlncD7/LrxxZXGDNEGiLvCy9CAtqG/vUIvKmKtwPSKE+JYmE7GTe8054kafiOR9zLkwQIQQ1JFpyg7e8S0X5tCQdBmHaEdwem4MRz8Hdu3ejuLg4bqiCNvb4mb4ICVmggg/NwSzk+Aia/MUICX5Q0S+9C+F3n2SPVUIGALI9zpJtMAu/N0NgAckWM4UtjiwHJHtMm0EQssYXKVYgTOKlbMpjl15R0g2ivMltkGLMJ/GYtyK+vJGQNU6J8ibF89dEOxXJ3cD8+fOxcOFC7N69Gx988AFKSkowc+ZMzJw5Ex06dLD02Nwem4MRe0wpRc+ePeM+TzPGIrZYssvfILTDDyr60NxSgNxsAU3BYoRYFijzIcSyEKI+UOYHZT4wJHg+JoFWIV8Ii/otkfWtn5shoAUiWiAgAAHSZwExYrhDHvtU8EJgKczkSydv+TAWeM0zIkqhbNwankXr+Vo9iOTW/uFwFAwdOhR33HEH5s2bhx49egAADhw4gLvuugvDhw9PqW7DwnxRUREeffRRAMC5556Lc889N27ZoUOHYujQoVHrzj77bJx99tmajzd9+vQ26wRBSJpsJ9MJhUIJb1SibmYWkVbxsBoINNSiqSGILi3LdR+XQTLYNCIgeEHF8LJPehezEfAWSKIC8YMKXoSIJDRQ4gUjYmRaktrNjcACEKpbIPSRhQWl4B9qgUjl9QcDEDq1QAi2SOJEUC4bkgYONI2w1sEcgTFeDHc7BXk9XvNAYnFeh3BPBRHeTEn+qnbONgnQaTNVjwvyroHbY3dAKdVuj++P/p03VTUh0FCDLh79YgoDabXHRT6EiA+U+BS214eQkIMWsVC2vz7JThNfxDYziJG64tpjJttf1vqKEvgjgwAt0eWrW7cns8emeei1V4/hTgCOScnmdOV8MQOtorxdYnjscQx8JzTbYzd+39ww4OQwDz/8MObNm4ebb74Z9957LwKBADweD3bu3Ilbb70VL774ounH5PbYHVBKE4ayIYQoZtcRSZyUHfvraylo8350yV2n+7iMEVDmi7xCTBLzw++U+RCkuWhhRdJnwYsQ/KDwyS8vqEKeIWBAl+hjRNvaVrssDcoHYtYrPyuWWRCkb2J7TOGFcNyAMJ+OgrwSPeK8Bq95JngglAWBZCbZ7n5ziyCvAe4rz3EL8+fPxxVXXIGysjIUFRVBEAQcO3YMZ555Jl5++eWU6jbFY57jHHFvPL5I/jBRT73IMRhjngAQaQAiDQDBE/EL+gxVDwZpKjY9IAsIgg9U9EmiguAFFX0IVfkQEHNB8+RtHp+0zSN/Fn2gYuKZB4wQEBpCdZdTsH34lW2FfRqQBf5AZB2JWheIKkeEAAgNgdgRtiYeRrzBk4nziNmucn6RUDZumxUQS7z+SSXskonnlRZT9bgoz+G0IRQKqdvj+zXY45A3cYz5BN69BAyiPCMt6YOfASR77I0I/lQW9UPEB0Z80sA88SMg5En2l0ifpXdvpDwlSewxCEAI6vx9sb3TFbKgECv6ByCwoEL8D4BEBgECEBCUxYcASFULSBFNLK2mo3iZSACXtzFBBGEWhfQ4hmhvez1e8lbH8TdZHE9qj2PDMrlNnG/nPP/885g/fz5Gjx6N++67D4AUvuSBBx7AqFGjnG0cx1LiC/Ma7HGjF7lZBp+PCYNImiGiWdsOB5NsjxFPGQgo8bTa2KjBdq9so/0ICAWgHq/CZnsjdph2kgYAEsFAQOFFY+ceQCdAQAsIZJsc8fBXvlok+8vkcpFXsHVf2BtmKiVMFOdpsQekJsm52ynKuyVsjZKk3vIEXJ7nuIE+ffpgxYoV+Pbbb1FZWQlCCPr164eBAwemXDcX5tOcZB7zEVSEtGwhiD3BAgQZgceMWHkmQgCQPUEICMKDhrYFTBQGg6IP2067Bj03/FsS/EUvmOAFFcMvSeAPefwI+PPkbT7Fdq/kcVjvAe3nBRO0TbUkoRCEqgBIKAAhGIQQDEAIBkCCrZ9JMAAhFIIQCK8PgITksqEQhEALSCgUKUe6BSCEgnHDHSRES8z5BDDBA3IwgSrkBlE+HlpEeZsS+aaNxzyHw4kimYdeIrLFIHaeKARlgOCyvwACyOJ3AEA9YmfZmwUD0Cx2xL6OF6G0+h1J9CdesLCYEBH6vQgJfgRIXmTAgMVsl2bleSIzAeIi50YkLCgL/oHIuQosqLIcLhNUX4+Q4nNQDtln4v2VRhFcijGfRFgK15UspI3aMd0SskbNK14PRsPZJArJxMV511BVVYXi4uI266urqyP5PziZSWw8eT1k+4Oo3FMExgCDVVgGAYPIAhDDIWa02mOl8KtBH2cA6tEDR4VR6E4/lD35vRGvfkZaP4eQhQDypc9EuU1RHh4waLs/EhAAQTAi7keWWVAW+IPyeuVyUGW7pCMo33XZYzPE+Ypw8tcEz8d2iPJGwvO4wFM+DINgnbMBh2OAQYMGYdCgQabWyYX5NCcVIWBU9h58VN8H/6wdiMs7fJd8BzVR0qzkrnowWxwVRHgCTfA21yUvGw+dbWKEgAki6EEvqOgB8/pARQ+oxwPmlcV+jwfM4wX1eBHy+cByckFFEdTjBRM90rtHfi+S3wURVPRGcgOEwxLEir3KdQINSV7+oQCE3CAIC8kzA0IgNAiBBhXv8rqQVE5aL7030C7wFJxAQ3ODNHgQrpeGQEJBEE8QQigEsCQejFaRqqd8vGts8oCD6z3mubc8h6MKY8ywPf5Bx+1Ycrw3/nOsLy7qrPIElY6e3TohAEAEeGgjfKEU7LFOmCR1yIK+Rx4I8MjLYS/D1s8hwQ9G8mLKeMDgkQcHFOuIJ+o44f/32JBBrIOUP4CwEAijEXGfMNn2siCEuiBITggCDSjsr2yLw59ZCIQG0JRdgqYcadSBsJBkj1lIGiiQ95GS0VEQIyK7XuwQ5bXuoyXnQSpwcd41TJ48GXfddRdeeuklAFL4ki1btuCmm27CxIkTHW4dx61c9P0t+NXc8/DpV+UYe+oup5vjCHK6enhZPXyobVsg0aNKCo8xkj32REL6SKK+YpmElz1g8qBAEHnyoIAolSWeyGCAVM4rv7e1x/GejwmYNNB+cgjCsfCge+uAe/R7SBL/hwUjdlYaJJCWm8TOaPR2QVDIkdfTVnvMghAQ0j9okIxU4uTbLchriS1PBJB0mnHB4RiAC/NpjiZhPiykKQXEUkAAcENoNX596DyMzN6PCt/x5HVkIFTwQgi12HpMwhjITmkEP2VSSGTKAIAI0uCA6JHeS72ggggmeMAET8yyR14WERKzFNtFNBZ2AwFBU0ExmOgBE+VBAkEEqxPBhomgHk+U+0lCoUJlGwmFQCiV30Px3+VloVBaBqMgVBYiqLRM5HWkM23dh8k3S5QqluX986i0XrnvbgqI8nrufcXhtGtS8cD0EIZf9liFe3eMw7D8gyj12ydMuwlKUkw2ZwDpATxof0x2JVVyyCAIko0Ni/6CLDbUhD+LkjAhiNKMAMEDSkRQMQvMKy0zwYPGnC6o7XAy6vPKpXw+gjTwwIjY+pm02uNE9jf8GYgRLSK2MhT9oorlE/LnjorBAUoBFpIHEaTliE1V2N3WQYrYbRQ4HgLJom22g4ak+yunB7i5OO8K5syZgyuvvBJdunQBpRQjRoxATU0Nxo8fjzlz5jjdPI6bUHhH+30h3DRlFR59+SwM6nMYnQsbHW1ayhj0yKbwgsAJeyx5yqui5a/dhL//iD2GF6xKjMzCCw+4U8i2lMg2WrGeCtkIRsqKaPZ2Rk32AMl+yjaYEim3D+skSo4BitBCajOnkz4fIyQJ/lWy7eyssMNouyxElqliPQX2hUA6KdYzpY2XbS1otD2GwlYr9ovY9kQdrTHhq9bZFhxOOsOF+Qwg4VS9JIJ6Sa8GTMtZj7n7T8cfOy2Gj+gcjdQS/sSIV328dic6H4ODB7SfF0LI4I1Hmg9YEABgFGKwBQjKgxNboP+a7QWCp+ehU+Vq5Bw/EL3NJI9yaZaBIAkTsvAvLYtgggCq+IxugiRcHJM/E+kzhHAZWdgoFsGIXKfyXbEMIkg3UiXScaRt0nbUKZYVP8N4CRTVtsXeYFWfPBhbLp/etiyDPEjApEEARkGoJI5I26i8TfFOWz+DMUlEAWv9rKgHjEKKaBXeB4r6wusZUK7YF5AGOsLLjAFHj+LEiQR5JzicDCWuLY6NyR2Hnlm1mFS8EX/aezoe6LPEdSHm7IASHwRm70C5KygCSBUkjzDaAkDRBwY82puyS9B9zwfwtdSY1kQlDCQi8EfEfiKC1cj2WLktYldF2VbK9pmIAJHtcXj/BrlcYXg/0rovEYBG2TZ3V9pqQa5LuRzd1ih7nBXuJPXzUtrj46VDsOXsOPaYtdrjcMJiQsPvFK22VH7PlqI2t9pfhT2Gwh5DxR5Dsay0x1DsCyj2lxvZzu1xTk4O3nrrLWzduhXr168HAAwYMMCUWLAcd2M0jE2YfmVVOPf07fjLm6fhtz/9DAYnw6VGKl7PYVIIk8KIDyLaoT2GHMIPFEAzcBJSuhYn/L1Qevy9ts54faEprFAyGAhYpcIOQ7kstNrXmPWR5X1Cqz0WvKAkK9puR14kZp3iGTnqXQCgsMcxbY3Y0cK25xHv+ZjCi9rsftjSRcUeQ7bH8nyLiD0Ov0Nhj5XvkfUMQIw9brMNrfZVbpHS1hLE2mOmWC+Vae/2mJMcLsxnMkrROIE4Oq54J76q7ob7a8bitr4rUHxEJaa7GzAi1muAHvFBKAzYL7L3ROqidQre8glRS/iapCwTxbYeh2YmRWWSxzxCISCgcqOo7IvDSSoLn1e9xoOrfTcsipm/5fLp6PePZ9usl26IiHwTRABBuulB5EaJSAMPBFFlAMg3WIr1JLwfpHpA5M9E9qAkYEL4XWhdRwhQSyLtgeLFINXluoCcHE4acVGnLVh/oise3jUat/RYiUKvxgRyGQIlXhCbPeZdjcEwM4yIIBbOAJAefoNASHEMM2O1KzEaBz7FOhmAyrOno9+nz7ZZH7GH8mAAIERsIhNE2aYKst2V7S8EgACsoxiZrRixx+HH9/A6Rf2RZUAWPMI2l0TsbXifNtu4PQYAFBcXo6KiAowx9OjRw+nmcNxKTEzxS8/ZgN/NG4fHF56JGyevRl5OmtmmFGOXO+Ex71r0xJuPgREPSGwyABPjypNKadYfWFDbbAE3xI6vAHBIe/GgkINdnabgpCMvR62P2GMQSHZYYY/lMIXSsiDbWNn+yh74TPE5XC7KHkNhjyPbZPsuH7t1e+sMxHD9EXsMbo8zhXHjxsUd+BUEAT179sTUqVMxfvx43XVzYT7NMSN5ESHAjL5f4J97B+Lub87F9X3W4LSG/dorMOoVnyomCenUY38oG1OwSpRXouzj2Gsc0/9U8MheYjJ2JXvV2w9mfFcdSGRLWOvIvaMk+9116mQ4zjaHk86YYY8FAvymbBkWHh6CX20/Dzf3WIXBeclGGjMHRnwQaRraY5fBiBjxFrMFvcK5nvKOxacnrSKHQsiPPHrLHu66TXI4SpUdoW7auT0+fPgwbrzxRrz99tsIhaTfgyiKmDJlCubMmYPOnTs73EKOFTDGTLHHXg/Ffdctxd/fG4Zf/ek83DZ1BfqVpUnCFxOEXwpv/JAy7RGD4nybWVtmJnvV2h43iPEpEC/5a6sULj8fKxzUXUc7t8eZwvDhw/Hqq6/i5z//OURRmhESDAbx3HPP4Qc/+AEIIZg0aRKeeeYZXHfddbrq5sJ8pjKKAYu0j8wJBLis5wYMKDiKOVtPxyZ/Z0wr/NrCBuokVgw00budenwgQYduPMzwmreLJH3ORA9IyOYYvXpEeaOCvM0zKdRiC7qGNA/dxOFYSdyp888w4H7tv2uPwPCTrusxMOcIntr7PVzYaQsmFW/StnOax7amAveYj6ITDHnNU8FjTcx8MzSpNNG1mCC0Dm5YOTiQxr9Xt3P11Vdj7969+PDDD3H66acjGAxi9erVmDFjBn7yk5/gvffec7qJHAtInIidATrus/2+EK6/5EssW1eGR14ajannfYvx39tmSjvdDoUPIlw6i94pDIjzluQ8sUOQT3SMVAYXNMaVVyJ5pPPkrxzn+eqrr7Bw4UKcc845UevHjBmDhx56CEuXLsX555+PWbNm6Rbm+bBNJnOpfkMwuMNh/Lj7JnzbXKJvxzQW7KjHK8VYdwojnu9mesubFQNeUEydt2OwQWsflMKZGR0GcTxpHYfD0U1S77xZ+n/XpxXsxwVFW/FtvU57nExErIrzcgG6kr+6pM1uhAkeczzmzfyOuOh7pgkiyPFmLSbd+iWN+Oyzz/DCCy9g3LhxyM3NRYcO/9/encc3Uef/A3/NJD3oBfSg5ShytMi9IqCicikoh6DIqiyC97X6XVTEYxXEA0UFBRVZQVdR0J/H4skCHqCii6KoKAhIuY9ytlwt0DaZ+f2RJk3SHDPJZI7k9Xw8+qBNJpNP0tBP8pr3vD8NMWDAALz66qv4+uuvjR4exYjT6fRUMgam/v917zN2one3HVi/LS/ygelFo4psVswHUQxtq97VKEFsQ/kSqLsP3dj4+ZhM4aeffkKzZs3qXd68eXOsXr0aANCrVy/s3q0+HGUwb2FanKbnr8KRhIW7OuL6Rr9qt1OTh/aSLQlCpIu/akWPtjSB7PL6N8owXRZtEJ06nTqv5PnSIpDXsbc86aO0tBR33HEHzjvvPFx66aX48ssvjR4SxQFJkjQ/RbWspgEWlxXj2oLfNN1vUFqFg8GCfwVfUmUyxGM1gQNhpZdZlYaV06EWIFdM69eDxchC4FPnYyaeXssK7d+/HxMmTEC/fv0wbNgwzJs3z+f6bdu24d5778WFF15Y7zolioqKkJ6eXu/yBg0aoG3bthGOmswuqvk4SOC652AmvvmlFcZcrPHZ5BFUD+tFQlLwxdiLwnwlAoUBvc+Z0JEG+moDeaWhfAkiC+MjDe4jfG3IEPRtz0cURJcuXXDPPfdgz549nsv27NmDCRMm4IwzzgAALFq0CN27d1e9b7aysbDQp+rVukIGnlN+yt7/29kFZ6buRfuUCM6dNqrXvFLuQNUv1JXtyRCNamXjTe+2NoHuy/sylQcLJJvdVTEf68cQblxavQYNOqBk6lY2FidJEu6++260bNkS8+fPxy+//IJJkyahqKgIrVq1Mnp4ZGHhK/TgqppX0dLmzX1/Qb9G23Fa6lH1AwrW0kZJNT28bhtue//7iDJQlIQkJEkB5mOl+7V4K5+AImhnY3hlWRwEy7oH8/7ivNWNJEmYMGECmjZtinnz5mHfvn146KGHUFBQgEGDBmHbtm24/vrr0b9/f7z00kto2bKl6vu49tprcccdd+DRRx/1tBqTJAmPPPIIhg0bhhUrVni27dOnj2aPjYylaD5W0dJGloHXPu2GYef/iSbZidPaxVMxH0mYWgTL9zVXzB22Bwmro5qP1QbgagJ5KxFECGxlQyYwf/58jB49Gi1btkR2djZEUURZWRnOOussLFiwANXV1XjnnXfw3HPPqd43g3kLU/bGA8B4ZeH81opGWFlWiBlNlta/sgVMX/nuES4Y9gufJVsSbNUmeaNlVOV8ICpDelm0Q9gR46PZocahJJD33iaS13OMDzq4PibwVL1YWbduHbZv3445c+agUaNGaNOmDVatWoX33nsP9913n9HDIwtTXKGnMJxfW9EEG07kYmbRUt9gTu2imZGGegYF4ZKYBDHaxV/NEs77P4eRjimCOomoRRqsx0Eg7yEIrsVdjWaW17PGdu7ciQ0bNmDGjBnIzc1Fq1atMHDgQHz77bcYNGgQZs6cie7du2Py5MkR38e9994LAOjfv3+961asWIGpU6cCcK0P4tTrjE+KOeUV8wHC+QCB5ao/muPA4XTcP/Y7LYZnLiFCd+l4EsRUExSuWUWYgN7nunCV85EE5+FCea3D+BLo1tJHhk6t5YjCKCoqwo8//ojff/8dW7ZsgSiKKC4uRseOHT3bfPvttxHtm8G8hUmSpCyYV7IvGXh125m4MvMPNLJVBd4omnBej2r6SELTXYBUkISkwzXKb2+m8NxEZEGA0EKOXXgdTSgf6PpQr2ejDkIJAt94xFBpaSkaNWqERo0aeS4744wz2GuWoqb4QLkCDknAa3u7YWz+70jL81vAMxuRh/OxCk3d96HB/iUhCWKginm1go1Fj4Az2H1H8vxEGMpHfOaVGQN5g4JpV8W8SebjcM+BBQ+ItGzZEitWrEBaWprnMrvdjpMnT+LYsWP44Ycf8Nprr0V1H5JkggMrpLuI5uMgoeWpKhveWHwGbh7+M5KT4uj1pKAKXpKTIQpRzMeJVDXvTckCsYGuj2BhWQAJ8RzLgsCKeTKVrl27omvXrpruk8G8hTmdTuU99EJUzcsy8MGeDqiptuGiRiZZaV7tQYAowmDJngyxRkWFnv99qQnq3QFxrILfWO1/F8I+Tk+lt5YteZQ+t5Ee+DHZmSCyKELgB8mYadSoEY4ePYqTJ0+iQYMGAICkpCQcPHjQ4JGR1akKAkJUzUsy8NaBrsiyV+H8hjs1HGGMKQ0GAwXNOXXfSqKKxV/D7Csg73FqHfZqHY6qDeW97l84JQceT7QHafQOgL3XEtA5nJcFwVzzcaTtqUxKFEWfUH7jxo1YunQpJk6ciE2bNkEQBPzwww+YNGkSAODyyy/HmDFjVN/PmjVrkJqaivbt22PPnj1499130b59ewwZMkSzx0Lmoi6Yl4GSwPOxwyng9f92Q+tmh3Fm+33aDdCfngG2irY0kpwUXTBvJuECby0rvyOtTI9lKB+r1jVqquajWHtAhohIFm0m0lp5eTmee+45/Pbbb6isrKx3/fLlyyPeN4N5C1MVzAMBw/ljNcmYvaUnDlal457slbAJUf7RCxWQRlM1H8MAVUpKglgTwzcewaq13bR6XC2CfK/V/sOE8z4VetGE87E4IyHYa0+ngz+KGd3T1qwKtNnNGWecgfT0dMyePRvjxo3Dli1bMG/ePJ9wgCgSqhebCxDOl9U0wKzdZ+GUbMf4Ft9DEKBtxbtGVe0RCRUyu6/LASQxuX7FvJqAugzhw3k3pc+FkkDYZOFo0Ir5aMZpsscYc4LNHK1s3MzSzqYhlOcjCk7cWLZsGR5++GFUVVVh+PDh6NevHz7//HM4HA6sX78ejz/+OHbs2IEnnngCubm5GDRokOKhLliwADfccANee+01nHbaaTj33HORlpaGvXv3YtKkSbjnnnsU74usQ/V8XFw/nN9Xlo7n3z0HKckO3HXVDxqP0CAqg1FXMB9la7lIDjoEqyaPhNJAWmmLmQhovnZYAlTI18fPx2QOo0ePxtatW3H55Zd7ivy0wmDewiJuZVMbRv5+qglmlZ+Fs/P2YHz690gWLPwHL4ogWLInRbf4a6jAWk3f80gDdJMsuFuvN7r7OTFLiyCzL04MV8U8JFYExEpqaiqmTJmCSZMm4d1330Xz5s1x9tlnY8eOHUYPjSwu2lY2Px5rhjmlPXBh4624Mu8P2EW/vwMJEopKYnJdxbwRvdUDCVdlb4bfjd8Y4mKtEv/nVeeqeVkQggcBelfwmyWUj4FevXrhrbfewubNm/HMM8/gww8/RFJSErKysjB16lQkJyejU6dOWL9+PT755BNVwfyUKVMwa9YsjBkzBm+++Sby8/OxatUqLF26FLfffjuD+TjldDqRkpIS8e1X/NoSr//XtdjrZX02Qk3GH09kIyrmgwXp3pcrCc9NtLipJvNxNGG8iZ6LSLGVDZnFd999h5UrV2rexgYAEnSqiQ8RBQHjXZODJAPTy87FTY1/wY1Jv+oXyqsJn0OFqBoGrFEH81ppgdgEx4H2GWn1dyS3Cxe4FyrYRgklry0Tta0JJGQQQJro1asXli5dik8//RQLFy5Eamoq2rZta/SwyOJUV+gBrqp5AKckG2buPgd3tfgBo/PXaRvK+wd6Jg/4XD3mq6ML5WMZ6JcH+IpEmdeXFmOKNTMcfNCbEOTU+XK/f2MtznrL+0tLS0OrVq0wYMAAjB49Gv/5z3+Qk5MDQRCQnJzs2a5Vq1aq287t3r0bF198MQDgv//9L0aNGgVBENCxY0fs2xfD1iRkqIjm42LX//XyY6l45ePu+Oc13+LyfgaH8rGuEg9DkpMgQIPPx1G0MAmoxOtLyeVq920Wm72+9LxPUzLZGWyUsIqKilBdHeWZREEwmLewiN541DoipUIA0DO1VNtBxVKMqp2lpOTYtrJRqwWUhfTRBPl6L2AbLHzXehwmD97DEkTATD1t45Tdbkd+fj5OnDiBZcuWoV+/fkYPiSwumor5A9XpaGQ/hS4ZBzQelUmoCJ8lMQniIRPNx1pTGsYrfc7iNZTXcgHdCMlCgDVfAlXxR0LLNkoWtXr1aowePRqy1wK7oigiOTkZbdu2RUVFhc/ZbHv27EF+fr6q++jatSteffVVrFy5Ev/9738xfPhwAMD777+P008/XZsHQqYTzXy8rywDTXOPo11Lnf/waR1ea0TQuAuL5rQI47UUYByqW9loGcareV42e/1rsoCeFfNkFjfddBPGjBmDJUuWYMWKFfW+osFWNhYW8al6LYADW9LRxF4Zmwk3XMsQk7UUcfWYj/LIl4LFUSNioudJE3ocEHCH86HWOjAp2WaDIAeo0Av3mEiVPXv2oKSkBC+99BLat2+P8847z+ghkcVFFATU9pg/UJ2O/KT6CwgpFqp3vAGLZkZDrrJDkBzR70hNr/lYUhrCGzXWOKi4jhVZ9Otpq8VzpWYf4f7fWvx3V1xcjAMHDuDZZ5/FVVddhf379+O9997DqFGj0KRJE1x00UV47LHH8MADD6C0tBQffPABHnzwQVX38cILL2DYsGF48skncffdd6OoqAiPP/44nnjiCXz88ccxemRktIhavdb2mD9wOB1NsqOYjylyZgrXNeo1L0NFKxuTheGKafh8BSNDDPz5mEhn48aNAwAMHTq03nWCIMDpdEa8bwbzFqZ68VfAs/jr/qwM5B+viMGoamkVzvsv+ur9s/91EfaZN00rm1iK4eK5MRHtQq3+21sk0JYFoX6FHmC935/JjR49GtnZ2bj44otx3XXXGT0cigPRnMG2vyYDTZJVBgFqwnarBHhlAAoUfIgN9niMPgARbfudHK/vlQj3ezXj7z1cv36l+9Dhdy0LQvSnzof6HYR7HBY7qKZWw4YN8eKLL2LGjBm4+uqrkZWVhUsvvRR/+9vfAAD3338/nnzySVx//fXIzs7GzTff7GlLo1SPHj1QWlqKw4cPIzvb9WSOGDEC11xzDU477TTNHxOZQ0Sfj2vtL89AfmODgvlIFkpVs28yQJBFS80Ywpv6NSICrJgnE5Bi2NmAwbyFqa4IeK6uPH7/KVfFvGpaBoQmqZyX7XYI8R7M60CTVefDrSsQ6WtPbcW5UUG4IAYPAkzwfyVefPPNN0YPgeKM6or5R73m4+p05CerOFAex2FdVPyDTHfAHctqdKMWqA0TusunTNh/IFgbmEhez4Eev9b/L4QggYoSWh0UifNwvkOHDpg7d27A6zIyMvDkk09GfR+CIHhCeQDo3Llz1Pskc1N9oLzEaz4uT0f70w7FYFQRKoZ5KskTSSRV4IHa2Ag2CPCqoI02kA/2Wgg21jh5/bha2bBinozxn//8B3/9618BAG+++WbQ7QRBwNixYyO+HwbzFqYqCHhf8GkjUrYlDeuqm2DLgWzYBAk2yD7/tk8+hAEZWwMvCqs0tLRI+w0ZghaRcmB6HHzw37/egXLt/QsZct1Y1I5BTWAeyf7dovl9qDkjI8L7CVoxbxas3CcKSFUQ8KjvjFNWk4ZfK5rit4oC2AUJoiDDBgk2wTUfd0k/gP6NtrkWhY3jkA6I8gBvNM+Nf8CutnpdCxrdl1yu4tR5M9AqfNZyPwDkRkLdqfNqztLQ+kyFOA/nibSm6vNxid98fDQNi1cWY+XaQthEGaIowyZKsIky7HYJZ56+F+d33QmbLUZ/YwNVzcdJuJqIJMEOQXZGHsgr/b17bxfjtjJGcLWyibxFCIV36NAhfPDBB/jhhx/w2muvBd1uwYIFeOutt3D06FF07twZDz/8MFq0qAs9jh8/jo8//hj/+c9/8NFHH2k2vqqqKjz99NNYvnw5ZFlG//798cADDyA1NRUAsGrVKtxxxx0+tznttNOwcOHCqO97ypQpuPTSS5GUlITJkycH3Y7BfAJTHAS8X/+D7pUt/sC5ObvglAU4D4lwygIkCHDIIhwQ8b8TLfHx8fYYkbUBF6ZvQ1KggF6pUCGlkgBTTRgYQTsbS32A9RbseQv2fOkZqippRWPUAZtYHyzZ7fWv2vvx72lLRJagOAh4tP58fG3BGuytznTNx7IIJ2r/lQVUSzZ8c6QVPjrUHiNbrUcfaYcroI9TiuZj/5760YaWgQJxoyrhlQjXHiWaSu9YUdp2J9rfpX+IrXa/3uM8bgMqTPI8mrEtEZGJCUoWUSupv81tI1bjwOF0OJ0CnJIIp1T7r1PAqWo7Fq8sxgdfd8AVF/yBc7vsQoQdc9SzcjhvxrYtSqipmg/yu5Fhh1AWwbo50fyu3beNp4BeEAGr5jUW8MQTT+DTTz9FZmamJ+gO5LvvvsPLL7+MRx55BK1bt8asWbPwwAMPYMGCBQCAV155BW+88QYaNGiAw4cPazrGl19+GWvWrMGsWbMgSRIefvhhzJ49G+PHjwcAlJeXo6ioCLNmzfLcxm7XJupes2aN5/tt27Zpss9AGMxbWDQ99HKKTiJn10nXDwE62lyQvh2rTzbFtLLzYIeEARl+L0K1Ia+WYWioPvNmpMVjV3v7WD0vIRZvlcO9CY70OYjFY9GrjZLK+5FFEZBM8sbDIme8EJmBJEnKgoAAmiSfQJPkE0Gvv7DxNnx7tCVmlZyNNHsNzsndE+kw9RergDtRK4gVBLSSaIMgmaiyTE2oHKsFVpX0c/cjC4LrAIfe4yciwzTNrUDT3OCt5QaetRWf/dAWL7x3DhplnkLnNgd1HJ1CVg1kY3XwQc2BAf8+60pC7hBjlgUbBLWLQWr1HFj1QE4AMkQI7DEfM9nZ2Zg3bx5KSkqCtpcDgKVLl+Liiy/GgAEDAAATJkzApZdeiu3bt6NVq1ZISUnBzJkzAQC33XZbRGOZM2cOfv7553rjWLp0Kf7xj3942tHdeOONmDVrlieYLysrQ15eHnJzcyO6X6V27tyJwsLCep/5qqurUVpailatWkW8bwbzFhbRqvMKVUhJWHisI3qn7cAF6RodGdIrDFVZNa9Jb/Rw1Dz2WBzACHSZ2rMLQoXygHarpWvx+Hch5HgBhD+TwwCeIMBooR5/qDMyiBKUIAgRB/PhHHak4sNDHTC4WQnOzgkSyvtXkZMyZq6Mj5As2s0VzJuFypYwsiBq974mGLapibmjR49i06ZNOHnyZL3r+vTpY8CIyMoOHE7Hp9+djr9e8Ac6tY5RKB9sEVglwbVVQ/lY0LJSP1j1fJjfhyTYIMoqKubjKEzXlgaLsVNQf//73wEAJSWhX4Bbt27FsGHDPD83b94c6enpnmD+mmuuAQCsXr064O3Ly8sxdepUrFq1Crm5ubjmmmtw2WWXhR1fRUUFDh48iKKiuiNnxcXFKCsrw/Hjx5GZmYny8nKf9WRipXXr1ti3bx/y8vJ8Lt+wYQP69OmDo0ePRrxvBvMWp0kQ4Be0HXWmYMqhPihOLsNNjX6BGOgutAwuDV4E1lStbLR+HrSqNg8WcrvHG+2p81o+7l1+/wLBxx/otafla1vl45JFEYh1EKBEuNeN/1krRBQTh6ob4LEdfXF21h6MbrMWMcr+41eohV/NsnBrJG1WQlwv2+wQnBGcOq8VMx8gChSEBxtvqMXYA+0v0sfNcD5m5s+fj1tvvRWnTp2qd50gCHCqrWSlhFZ6MAOPvdYXg3ptxmV9/jRmEO5wOMYBriwLgGDA5xEtquajCeQ3o37VvFsE45J32CEUKJyP4zmUD/acKiQLYuzzGjUHteL5dxVCZWUlMjIyfC7LzMxERUXws4zcnE4n7rzzThQVFWH+/PnYuXMnJk6ciJYtW+LMM88MeVv3/r3vOzMz0zMmdzC/fv16XH755aiqqsK5556L8ePHo0GDBmofZkD9+/eHIAiQZRkjRoxAcnKyz/Vbt25FmzZtoroPBvPko9yZiscP9sVfUvfh2oa/BQ4BogkuIwnhY1y9rEvFPGDcAQj/kNW/at5boAr6cJXniPDUeTXPRajHoESoCnr370Wr11k0+xJE9ac8xoqStR+IKGb2V6fjse190b/RNozM22C9UN4M1ehlCB3O60GL/uoqQl9ZsEGUdArmzRzChxNm7IoXY2ewbloTJ07E/fffj/vvvz9k31yKL3IMClx27s/ClNf64LK+GzHkXBM0TfcO6MMFihGEopKcDBE16m/oT++nSov7CxXOqySLdmWLloYLeoM9Lo3GaXauxV9jUDFv5TNMWgJQ0zjDCaD+iWOqSAHeE7nD6nBWr16N0tJSvP7667Db7TjttNMwZMgQLFmyBIIgYNy4cQCAmpoaSJKE3r17AwCuv/56DBo0KOD9eo+puLgYNpsNf/3rX3H48GE89dRTePbZZzFx4sSIH6+3fv36AQC++eYb9OrVy+cggSAIGDlyJK644oqo7oPBfCLzbmXSAji0vQEeO9QX5zTYjb9lrdM+lI9EoPvTeAyaHIFVEF4D0D6cd+9Lq+dE6ePwo/jUebOGubFYXNj7sSr8vcuiDqfOE5HplVZl4LHtfTE4ZzMuzTWoMk9nMoTYnDGkdzivdeW0yv1JNp16zFs1lFc4blm0KQ8Con0uGO7HRFlZGa699lqG8glG67Zy20ob4Yl5vXHVgD8w8Kytmu47ajEKFiU5CaIQZTAfaUgeadW8CY6X+NgMSBkKDpQHe6xKHo97m3gP6AURAjR8XxPt/xsrL8YcBVEU64Xzsiwraq29adMmHD9+HP379/dcVlNTgx49eqBDhw54++23AQDvvPMO1q1bhylTpgAAsrKyPK3ovO/bfTDAfd9XX321z/3dddddmDhxIh588MGI1+T0NnnyZADAvHnz8MADDyAnR/sPFgzmCQCw/1Q6HjvYF/3Tt2FkZoDKvFi3rtG6pYja/unRiDDMjlqLAN8He86irTgPwxXMB3njEcue+Woo6TuvFf9Q3v1vuOdCyanzkfD/3RORMRT0gt95KgtTdvTBZbkbMSTHbJ80FYqgWl6yJUOUNKjQC8Q9Hi3eR8cykI4m1K8Vcj7WilVDeTUEAVBSMa+VaMJ5JWddJKARI0bg448/xp133mn0UEgn0SzEHkjJrmw89eb5GDv4N/Q7c4dm+w0rWJ/5SPYTAQlJEIXqyO/XipXy/vvTIOx2HeANEShHE8r7bx/H4bwMEYi2kNLK1fEmkZaWhuPHj/tc5u7xrkSrVq3w7LPP+lyWkpKC1NRUFBa6QpqsrCykpKR4fgbqDrZ637f7e//WOm5t2rRBdXU1jhw5omnv+W3bNFp7MwAG8xam1al6pScz8NiGvhicsRmXZhpYmWfAgpuyEGFP72gC3nCLjioJToNtEyq81jiM9yYLQd54RLrgbSzGacQBFJWPI+ip81r2czd4TQeieKN6Lg7Rk3r7yYaYsqMPRjVZhwHZKt78BQtKtQykY0wSk2IXzLtFUz1v1jDab1xc/FUbuiz+6i/aynnv1wJDejz55JPo0KEDXn/99YAfzJcvX27AqCiWJEnSpDoSADbuyMEz88/DTcN/wbldDfiQaqCoKuYtWk8QC7KgsJWNt0ifvzgO52UIkc/HsQrkE7BqvnXr1tiwYYPn5z179qCyslJRb/XWrVujtLQUmZmZaNSoEQDg1KlT9Xq1B5KVlYWcnBxs2LABHTp0AOBaqLagoADp6emQJAmXXXYZnnzySXTu3BkAsGvXLiQlJXnuS0vLli3DTz/9hOrquoOXp06dwtGjR/HSSy9FvF8G8xamRUXA4epUPLGhDy5pugmXOKP46+L/fsUiwZ+UlASxJsgbj1gGudGEo2apQPciiTaIkS42F+jxKBlbsG2MOoMhEJXPMVvZEFlPxEGAX/X8/up0PLGzD67OX4v+jbcr349/YByoWt37sliH9BH2lncF89Xhx6dk/zkhtlMSzps1hPcXYJySqGOP+XgmCrHpaasXq7yGY+iGG25ATk4OLrroIqSnpxs9HNKBJEmK2iqEs3NfFp6Zfx5uHfEzzu60R4ORGSCKkFZRMB/LAF5N6Kl0HOH25x/gahB0y6I9eMFBvIS6MVjjoB5BBOQI3tfEuko+AcL56upqT3g+ePBg3HfffViyZAlOP/10vPjii+jatSuaN28edj+9evVCixYt8NBDD2HcuHEQBAHTpk3DhRdeiFGjRoW9/eDBg/Haa6+hTZs2sNls+Pe//43BgwcDcLXY6dGjB5599lk88MADcDgcmDVrFgYNGqTZgVq3p556Co8++ii6d++OVatWoXv37rDb7fj+++9x/fXXR7VvBvMWpcWpeidr7Hhq4/nolbMLlzQtiTykDdUHPtrK8HD3FWrMCtrZSEnJEB01ddvrKVaVywZUzUd86rxFDuB4RNIeSc1jFEQgFpWO3r93qz3nRCYXVYVebRHnsQPJeHJHbwzN3qR9KO8v1lX0oULxECQxCaJTQYWee9zRLC5rhoVpoxEidJVFW2wXEU+QwFeOVWs5rSXI7yMSK1euxFdffYWzzjrL6KGQTpxOZ9RBTNnRBpj6Zm/87aJ1xoby0bSziSYM3QxISHYF8/uj2I9ZKA1OlSykq5IkqFirBIj+YEecVs3LECGadT72fs3EWUi/b98+jBkzBgsWLEBBQQF69+6N22+/Hc8//zyOHTuGv/zlL55e8OHYbDY899xzeOaZZ3DDDTcgNTUVgwcPxogRI3y2u/XWWwPe/rbbbsPRo0c9rekuvPBC3HzzzZ7r77nnHsyYMQN33HEHBEFA7969MX78+AgfeXAvvfQS3n//fVxyySXIysrC22+/jTZt2uDpp59GSUl0LwAG8xalKggI0CbEIQl47vteaNrgOEa3XKttKO9/vVZBYCRjdIftuwJcBkDKsENMrzZXlXUoalrDKHm+NFo8VvGq84HumzxkMYpT9cLh800UE06nM6oKvWqniGdKz0OXnP24tHGQdnJKFgVVGzbHclHUCMJ5TysbLcYVTfCuJOgM19Nbi7A0wn1HNB9TPYa0siFNtWvXTnHvW4oP0QbzJ07ZMfWN89G323bzLfSqVCTBrF8gLAlJEBFFj3ktKKlGDhdkRxuURhp0144raGu5eAlwderbLkMAoDKYN6KnvPs+Lfr7HTZsGIYNG+b5uaCgAF9++aXPNmPHjsXYsWND7qdHjx5YvXp1vcubNWuGmTNnRjS21NRUTJ482bMIq7/09HRMnDgREydOjGj/SpWXl6NLly4AgMaNG+PQoUNo06YNrrrqKvTo0QOvvvpqxPtmMG9R0ZyqJ8vA3J+7w3FSxB3tf4IYrvA+WGirNMw1Q0/rIMG7ZEuqq5g3Cy2er1C/m0ChfZQBfcBT50M9BqV99CNtZ2NRrlY2fm88dvt9b/T/JSLyEU3FvCQDL/x5NrKSqnBD219dC6+rCYbdyoJc7i1Q0GuiHvSqFn81S8V7oIBeqwpm//0oWDgYAGSbXdmZB5HcfyKxSsU8BTV69Gj84x//wMSJEwP+je7Tp48Bo6JYiubzscMhYPpb56JVsyO4asAfGo/Mi5oKW3corKSSWoNA3k1GEgSY7PNxIFotkhsjsmCDoPR9jVaPQ4+qeaWht1bjEGwQol38VU8J0OImUfXu3RvTp0/HtGnT0KNHD8yZMwedOnXCBx98gKysrKj2zWDeolRVBPgFl++v74gt5dl4rN1XSBJ1+tARbaAYo/BVspswmA9FyfNoxCK6ok37xebiKHBXTBBdSZ0ZsRUOUUCRVszLMjBvyxk4XN0AD3f5pu4gucIA1kNJKO++Xs9wVWXVvKfHPNTdTneBnmc92okovA9JtAVeRFyn+48XlljzJcF+J2rdf//9AAIv8ioIApyxbPlEhoh0PpYkYPYHPSGKMm67bDU0WMatvkBhptIAL1RAH2n4GSIIlpAM0QrBvMnJgq1+wYHVA1sDKtFdi7+qeF9jRLW8P4bzcWnmzJkYPHgwxo4di8ceewwXX3wxsrKykJKSgvnz50e1bwbzFhXpqXrLtrbG8m2tMeWC5Ugvi2LC1SI0jTZk1mAMkj1Zm8oyrYV6brwfd4A2RVHdpxpe912vx3y01fKh1i0Id1msRNJfXiVZFGMTqBBRzERaMf/pnnZYc7gAU/6yHCk2v4AoVDgfTRgXLJyPVVsbFeG87G5lQ1EJeup8IMFeDwx8Xa1sYrHmSzh6H0CLYxLfTyWcSOfjd77ojF37G+LRm7+C3R6DA3JaBYVaVSCHqc6WkMRgXgOSaIfNeSr8hlpW/ceyWl7N61jLcQgCBLWtbMyA4Xzcad++PbZu3QpZliGKIrZs2YL169ejsLAQubm5Ue1b22VqSTeRnKr3y94CvLW2C/55/nfILTsZ+Z1rGYaqCd7fk+u+NOJqZWNwD71o7Pb7Mohr1fkIFn8lH66etn5vPFoE+V5PiXj2ApFCkVTofXegEJ/uPh0Pdv4WWclRzEH+1fLlfl+BaBG6TpbrvpTK8fvyI4nJEJ0mn48tEFjLlTYIR2tCvwYA39cM1ScIxrWy4e8kapIk4b777sOxY8eMHgrpKJL5+LMf2uK731vin9d+i7RUjT/LFCN8mBltaF8s132FstnrK4y4qJg3KhD1en5lwa9wLdZjisdQHoAMm/L52AzV8t6U/A0gS1mwYAGGDBmCjh074sCBA+jYsSOefvppHD16NKr9Mpi3KLVvPLaUN8aLq87G3ef8gNMaqXjR6BHIKbkP/zD+PdkVUkYZVMqRtrJpEeQrQfmcOh+L/vgJUC0PwBUEBKrwSvDXF5GZqa3QW3ckD//ecibu7/QdChpUBt8w2+/fSIQLZ70pbR/jH8YrDefL/L78SGKS8l6ssWLlQLT2dy2LNojeLTqMar0TCyFeP1ozfPFXq/6OTEIURfy///f/UFpaavRQSEdq5+Of1jfDe8s64cFrv0V2loLK5liJNLjzD+MDhfMKw3hvrop5kx8o11oMwlNZtEGQwxzsMXGPfADqg+UYHByQobBingE4xdiTTz6JSZMmYeDAgdi+fTtqampgt9uxfft23HnnnVHtm61sLErNG4/9Fel46rvzcUO3X9El/0B0IWO0rVKUtGfxF6xC/j0ZuFKIagFQVysblW88InkMavbjvT+LhLGyaIcga3DKd4JXZluipy0R+XA6nUhJSVG07c7KLDy3oRf+r92PKMo8HP4G/qG8d1gXqFo+GP9FSiNtaRMshJ8sA48GaMqrpse8LRlJjijO5otWnAShks0OW7VfwOT9+w4W1Ju9fYr/aynGCxfLgmB8a7lQv5c4eb3G0vDhw3H77bdj0qRJAYuZuPhr/FFTuLZpZzZmL+yJe8f8Dy2aHNd+MGpDQrVtL0JVyEcZ9kpIgihbvGLeBCTBaw02K1bLq30Nx6hiXxZEwEqLv1LcevXVVzF//nz07t0bjzzyCADAZrPh8ccfR69evaLaN4N5i3I6nUhKSgq73bFjx/Dkt70xtN0m9D5tZ+CNzByGKm1bE2GALeUnQdiv8I2HESF5LMJ5LarP/cYkCzYIzprwYw11fbAxxGC8qm6vV7U8ABjV05aIIqY0CCgrK8PUdb3xt1br0D1nr7o70SqEiyaAVdO2JgI+i7/GUjwGml6PSRbtEJwBKvSULg5sxucn1AGeWK2PIKo4dT6WrHDQxKT+9a9/AQC+/vrretdx8df4pHQNttLSUjyz4DzcfNnP6Nj6kPYDibgCHsoC3FChfLEMbI5u9VpJMEkwH02PbvfvQM+WNn4HRGTRDjFcxXy8iGUbHQRo9eqP1fKkg/LycuTl5dW7/MiRI5CjLK5kKxuLUlIxX11djWeeeQZd0vfj0rQ/XQGjmpDRzIG9W5T95iVbMsTsmuCtaZS2qYnlc6VXT/8oyKINQk4UH3CUhvKR9tKPtBe/nqE8XBXzMFvFfKDfARF5KJmPT5w4galTp6Jv/nYMbLpV+c6DtaKJppVHuAr7SFuF+Af3Kvchabn4q3+v/XB9963M7zHJNlvkB3hj/fzEqgVNDPZriop5t3h83epAkqSgXwzl45OSNdiOHj2KqVOn4rI+G3FuFwu+qQ3XSx4ABkf5+dhKi7+GC4RDtWIpDnN9lGGzq8e8M/jBAa3a2BhdLR/TUL52Pg7VyoahPOlk5MiRuPfee1Fe7npjJggCNm3ahDvuuAPDhg2Lat+smLcoJRV6K1euhCzLuKHVrxCiO3BuDKWhu7ulTQQkWxJEpwXeeERbOa9mkd0ISKIdSVKYFgRqWwAlYCBsqiCAiBRRMh8vX74c2dnZuCrjD23vXK8FPJVWy7tb2kQQlEpicvTBfLwFmMEeT4i2NJJogxioYt5oZX7/Asoq3XXoJx+QILC1XBxYtmwZfvrpJ1RX152Nc+rUKRw9ehQvvfSSgSOjWFAyHy9ZsgRF+T9h6HkxKqWOejFXaFPlPVgGloT5fFyCgOONi8Vf/RnQlkVS0mM+WlqH4iZpX+NLDH4GG0N50tGLL76Iq6++Gvn5+ZAkCd27d8eRI0cwePBgvPDCC1Htm8G8RSk5Va+mpgb5+fkQI5kP9F5sM8rK96AChcFej0OyRdBjPsT+Ysp9P0oDeiXjimTsAe5fzrNDOBVB9ZGa9jV607laHgAgioDDhIGKN4use0CkFyUV8zU1NSgoKIAQYq3XekJVtEcj3KKyL0Q5H0c4vrAV8/EWugej5HGG2Ea22SFIJp9H3NSG9DqSzdLKxlui/B/QyFNPPYVHH30U3bt3x6pVq9C9e3fY7XZ8//33uP76640eHsWA0vm4ac5xaxStKamOVyNQ4B/gMik3GWJjCy3+WgRTLqIqC3aIsWpRquRMgVjTJZQHZIgQ/HvMM5AnA6SlpeHDDz/Eli1bsGbNGgBAhw4d0LFjx6j3rVsw/8UXX2DZsmW47777kJ2dja1bt2LJkiXYv38/srKy0LdvX/Ts2ROA65TvBQsW4NixYxg1ahRatGiB8vJyPPPMM7j00kvrNdZ/6qmnMGDAAPTo0UOvh2M4JafqKepzZIYAVItQXk1Y6N52twYV80Y8f973GcXCt5qNvYV71XmVbzxi2VM+WkaE8nAtbiOaLQiI5jVGpsT5WFtKKvRkWQZ+fxFoq9OgIhVtKB+FoPNxooSRGj1OWbQbs1aJ/wGZnBDXKbm9wWRBCN/TVk+J8v9AQy+99BLef/99XHLJJcjKysLbb7+NNm3a4Omnn0ZJiZ6Np4PjfKwtSZIghEncZVkGYhXKaxUWFgOaLHYZ4ctcEpIgbq5xDSERA9BIAucABwZk0QZhawzm42Dj0/N3pVMoD7g+H3ta2STi65FMo7y8HM899xx+++03VFbWr7Zavnx5xPvWpcd8WVkZVqxY4fn50KFDeO2119CpUyeMGzcOffv2xQcffIDNm11/0VauXIlmzZrhoosuwuLFi3329cUXXwR8EhKN0sXmhI1v6TCaKMSqUl6JFrVBQKSVZWYIK/UO5YMcAJEEW+jnUeniq0pC+V1BvrRiUCgPuHrMs5UNxRLnY+0pqdADNMoBYhleGhjKA+5WNn4VemYKI2M1Fo1730s2W+DFX/UWqHWNhchCiFPnyRLKy8vRpUsXAEDjxo1x6JBrkc+rrroKH330kYEjc+F8rD1BEMIG80DscnntGD0fJ0GQa+djo49hKQ1itQqKNQycZcEOQeuWuUaH8kUhxhArTUTgNCdDeTLc6NGj8d5776FTp07o27dvva9o6FIx/8knn6BLly745ZdfAABr1qxBs2bN0K9fPwBAbm4ufv/9d2zcuBFFRUU4deoU8vLy0KxZM5w6dcpnX7Is4/PPP8eIESP0GLppKQkCZFmuf9qPEnoFzkaG8rWk7CSIWyOYMKN9joxsBxKD368s2EP30Iu0R36gUD4Y93WFEdyPkv3rQRQBBvMUQ5yPY0NJhZ6q+TjKdiaq5EB5D/kY0nTxV63FMpTXmCzG8NT5QEIF73qG8mXQth2OaOOBcovr3bs3pk+fjmnTpqFHjx6YM2cOOnXqhA8++ABZWVlGD4/zsUFkWYYgxGDO0yw0NH4+liFC9F5s0x3OGxWMKu27b7KWNpJo03Y+NkMorxevxyRDiCzTItLYd999h5UrV6Jr166a7zvmFfN//PEHDhw44HmTAbj68PivWmu32z0V4GeffTa++OILzJw50+d2ADBw4ED8+OOPKC0tjfXQTU1pMJ8wWij4CkASkyHmW6iHXrSiCeVDBOuyaA/fyma337/Bro9WpBX0RofyMOGp8xRXOB/HhpK5VtV8HKve8sGYIJQHaiv0vCvmjayWL/f70mo/Wu03BFm0QXDqFMybrRpew/HIABd/DSQLrvUplHwZnH3PnDkTixYtwu+//47HH38cn332GbKysjBx4kRMmzbN0LFxPjZOTD4fx1EoH5LR1fNKRBMeaxw8y4IdQhuNPtcZGcrrVSVf7PXlxdVj3sKfjweb/P81Kda2bVufxeS1FNOK+ZqaGnz66acYNmwY7Pa6u2revLnPdkePHsXmzZtxwQUXAADy8vLwwAMPwOFwIDU11Wfb9u3b488//8Qnn3yC2267LZbDNzUlp+kBYU7VU9PLO9rQdKUJ/iAF6JUdUYWeUS1s1C7+Guz2MSAJNmWLzakZg5pq+UCUVtCbIJD3EAQIkgn+r1Dc4XxsPEXTdqxD+cXm/fvis8aG0aG8GfYRIdkWg1PnrUSrynmxtpWN+/+eyRanpfCKi4uxdetWyLIMURSxZcsWrF+/HoWFhcjNzTVsXJyPjafpwq8RB6PmnY9DKoExlfNKq+YB3xBZSQV9jEJnWenn43CMCuUNqpCvT4Rl/7+Q5Xm3nLvyyitx9dVXY+bMmUhPT6+3bZ8+fSK+n5gG88uXL0eTJk3QqVMnlJcH/pQiSRLef/99dOjQAYWFdQma3W73ebPi7ZJLLsHMmTOxZs0anHHGGbEYetyIyal6apkhlA+iXoWe2Sg9eBIsrNfpIIIs2iGqXfzVm/84ow3ltbqtzmTRZs6etlwA1vI4Hxsv4tNwzVaVbGaBXtrZUdxWi/vXmWTT+NT5YMz8uvQeW4SBuiyIrJi3uMaNG6Nv374YOHAgBgwYgI4dO6Jbt25GD4vzsQlo1hYjTntem7ZtiJpw3k3vfuheZNEWutWrktY7seidH+o+9X6+FPwfclXMm/Q1SXHP/ww1ABg6dGi9ywRBgDOKM1Zj1srm0KFDWLlyJYYPHx5yu//+9784fPiwqp54eXl5OP/887F48WLVpxIcOXIEhw8fxrFjx1BZWYlTp06hpqYGUhz2kQx5qp6aavlomCmUD/D4fCr0zEZtdXmgL53Igi18KxsKSxYE9rQlzVllPq6qqoLD4Ui8+ThUaxMtw0+9q+Vj3LIl4P2puVztNhYhi3YIktP12jFzeK6XCJ8DWRCBw15/i/hcWs5//vMfnHnmmfj4449x1llnoUWLFrj22muxYMEC7Nu3z5AxmXU+Pnr0KI4cOWLp+VhpixpztHo1wxgsymIHQ6I6OSNUSB7qeSgK8BXuer0XdQ3QsiY4AQBzBjKGJEmKvqIJ5YEYVsx/++23qK6uxgsvvACgbhKcMWMGLrjgAvTv3x8//vgjfv75Z9x+++1o0KCBqv1fcMEF+OWXX7B8+XJVtxMEATU1NTh16hScTqfPV7CJWhRF2Gw2n69Al3lfF67/ux4Mf+OhZygfcZsXQX2ArUf1sMWqk2XBDiHSRfss9lhjSXafOk+kIbPPxydPnoQkSZ4QQO18HGpO1mM+VtJart7jURIEWzWUD/TYyhHbyvVwt4mj4D0c2WaD4PSq0PN/HSmtIA/VwsUsIXUOlI0lkvY2glj/QLnWC8xSTF100UW46KKLAABOpxP/+9//8Nhjj+Gaa66JurItUmadj2VZRnV1NRwOh89nY0mSVM/HoeZlpa1YI6Fk/TWg9jmPdhhRhcPmD+XlqJ+gGHM//1boeQ+ErvQPVDUfLiAP9voz8OwAxSL4v8OKeUoEMQvmBw4ciN69e3t+PnbsGObOnYvrr78eBQUF2Lp1Kz799FOMHTsWTZo0Ub3/lJQUDBkyBAsXLvQsiqNEw4YN0bhxY8Xby7LsCQr8vyRJQlVVVcDL3RUG/m9ABEEI+obF+2f/7yMNFgJOq3pUyxtVKR8soA/6+AwYZ7iDB1YLqncDUr4tulY2fvvzYaFWNFEz+6nzka5vQIbifCwFDAPcc6uSOTjYfBxs34EIp6A8ILZqKB+K+7EHCegj/tCVQKG7ErJoc1XMBxMuXPZ/7flvb6ZQ3v1vDMJ5+aRg7vmYFNm2bRsWL16MxYsX45tvvkGXLl3w2GOPBTwNXQ9mnY8bNWoU8XzsfVDd/VVdXe0zD3sXwamdj0PNyd77UhrMA1H2mI/zUB4wcSsbf1YK6MOF82r2E+0+jBDF/xvLL/5KpEDMgvmMjAxkZGR4fnZPlI0aNcLJkyexYMEC9O7dG02bNsXx48c922VmZiq+j27duuGHH37Ajh07tBu4H+8gPVqyLEOW5XqhQbg3Mv7VCrIs48iRI/jzzz8943O/SfF/s9IgpxWONjgOm1wFUaqCTaqGaD8Fm7MKguyI7Hi4mdrTBKM03K6I6SjUM3MovxtBg1lZtEPY5QSaRrBP8pDFABV6ZsFQ3rI4H9fnDhX852DvoEHJfCxJEo4dO4Y///zTJ1jw/9dut0PObY2jGadc87DT9a9NOgVRqq6bj9WGngssMB/7U1M9r2Rf5EOGEP69ndrXmZkqxaMZh4rHIQti4AMcZnouKKT27dujpKQEQ4cOxahRo/DGG28YuugrEJ/zcXJyclT78g75vedk9/fulrOBPjt7czgcOHHiBGpqagLOx+7vU1JSYJPa4GiVBJtQBVGogk2sqv2+GgIcwYP7kOGiBefjeGGGgD5A5Xu9Mw8i6ZEfD6JuPyQADOYpzsV08ddgfv31V5w4cQLLly+vd6rdU089pWpfw4cPx6xZs7QcXswIggBBECCKIpKSkiLej9PpxLZt21BUVOQJ+gO9YZFlGbbkBjiZ0gxOIQWSmALn8RRIrZLhtKW6FpoEIFcIQKHvfYiSA6KjGjZHFURnNcT8Ktgc1RAfWQDboUOeNzyBQghRFD2PNW65Q0oGywDcFXqOKFoKEcBWNqS/RJ6P3R/Uo5mPq6qqsHfvXrRq1apen0H/+VhMTsPJ1OZw2lLhFJMhiSmQxGQ4xVTIVTbXB7gCrzFChgwBouyA6KyGzVkF0VkFUaqGzVkN8SHf+TjQXGyW1nqKWT1oz4bhjyFmlY5mqZT3F8lBhkD8zwoQRMCsB8pJkZtuuglLlizBihUrUFNTgyNHjmDw4MEoKjJnaSnn4+gOuldWVuLw4cNo0aJFwLnYez4WbOk46WgOp5QKp5wCSU6u/TcFkhwkHmkEiCUOiGIVbLYqiGK1519RfAs2m8nm4xci+xyuaAYpgTl7vRsdfPuF8wHn42jGaMbnPBwNxizDZp2zOIgipFswn52d7XlTMWDAAAwYMCDi23tr3rw5pk6dqskYrcL7VD1BEGC3B/41SpKEE1vWo6D85+A7C7QgKlwV0JItGU57MiRbCqRDKXAuWOvzxqampsbnzY5/RWGw0xUB1HuT4v3GJdCbmEDbahH8CxlR/pFXG9CHCqyV7sO/tUthwK1iI0jVfL3FX5UE9DyoUR8XfyUdcD7Wjvd8HOpDd01NDZx716FAWlv/yhDBogzXGh6SLRlOWwokW4or1H9grU/o4D8fe3/vno+BwP3wQ829weZj/8tVz8fBquZNEGyH5B6zicdo+t7A0Yhlpbrf/0NZDNFajlXzljBhwgRMmDABlZWVWLZsGZYsWYIZM2bAZrNhyJAheP75540eIudjDQWajwN9Rj516hQyhd9RkP6nsh3XBouyDMiyHZKUDKczFU5nMiQpGZIUfD72/5wcrNWtWzSfiyOej/3IsPt+pgvGHS6bLSw2unreK5wPOh9HEs6HW+w1jrnOBOTnY4pvhlTMU3ScTqeiqgJZliM6uigAECQHRMkBe80J14WpALKyVO8r2LgChfn+l7lPXQx0nXfQAADocGvd/msnQVFyQJRqar+qIUg1sLn/dVZDlGpwskE+yrt29dlO3FP7vdP9VQ1BCtP2R68K8UD91nfBFOF8yPUMFPf8TwDBHnsL16nzYE9bIsuIej4OU+0rABBkB0SHA3ZH7Xz8gnZ/I7xbCHifgedfbRhoPvZfUwcAsOQ5oKdrPvb+QCpKDtd8KrnmVNFZAzG1um5+dtbOxzldIdrq5l6f7SWHsvk4VrL9vjdxOG/a6vZo6B2ECwLPYIsTBw4cwOHDh1FVVQVRFLFv3z5s2bLF6GGRxlTNx6KCedQvCBUEQBAcEEUH7PYT7r2pH2iIcQX7XBzRfJxf/7OxABmC7IQo10CUa+dYubr2Z9d8LAsiTtlzcTitK0S5BkKg7WTXfC7AAcE7YDZTSG90QB+OmnDeTM+rGpqNWwRb2VC8YzBvQWreeGjmPe32pWWfYADA+MAf0SVBrG0VkFT3ZUuGJCbX/uzqieiwp0MWk+C0JUMWkyDlJNdtX5EMyZbkafsDAHJtJYJ3JZUsuBYJE501roMa7lBfqoHg+d5Re30NRKejNnRwuK4vrYGYXRs6OJ2u7Zyu7QRnbQhh5UVQlQbx8RrYK3lcuwEcEyGUSsBev+vYGojIlCRJ0n8+1pDm8/Fjc+pd5Kr6t7nmX1tS7VftPJvtmpOdtlQIsgRHUjqk9GSfbWTv7WvnY++QQT4l+Bz0cFVWyT7zqOiorgv2He752D3nOjxztGe+9r7OfbnoMO6gAKB40VbhpDlfa1YTsmLebNwHYljF72P06NH47rvvsH//fvTs2RMXXnghXn/9dfTq1Svo2cZkXUoXfw07HxsUgmo+Hy8NMh/D7vosLCTVfXl+TkaVvTEEOFFjy/DaxnW9LNZ9LwlJkAXfscrH/ObjRrXzMWogoAai95fsvsxR++Xq7+++XpDd2zpqb+/w+d71pYAR7W1qq+bDFkgqGVu412OcV8sDXPyVEgPflViQqlXntbhDDUN5PYmyBHHHSQAnfa+oDTllAIfyz0GTA98r32mIgFWGUNsCqDZ4qP1etiXXfV/bIkiy2VFjz3AFDqJrW9meBMnuDi3stWFEEmSbDTge+P583vxkChBkqTbMrwv1ff+tgSg5a693ev1cd70gOf22rb29+3vJAWG3BEGvsLgQ1j4ooYL7AE897N1PZEpOp1Pf+VjDanm9uKr+nRAdJwGH33xc+5neYU/DkZwuaLKvdj5WU40eYFsZgs886p5XJVuyax62110u25JQk5Tq+d61XZLXfF67n3Tfg/Q45Xt/7vlYhgCcgmvO9My3dfOw64CB988O3+0kJ0SHew52QHA6IZTVQGzshJARYD6WJAjxWCHvT+fH6Fr81QJBQFmA7xnQAwDy8vLw0ksvoV+/fqoWTyVrUlq4BiD44q6qWHQ+huuAc0DFwCnk4pTYFE3SV7ouiybU3l87Hwt2yEISpLbJkGCHhCRISIKMJEiC7881SHV9LyS5thXc13lvZ4eM+r9r74P23j+LpzshHHa6ztCDs/ZMAAdE2QGh9ksM8LOAust8r3O6DhzITgio+x6Q6t7rFQFopOA58g7e/Z9rq1bKa46Lv1L8YzBvQWreeFTLUR51t2goH7JCubYViyzYIUgKeuh5C9GSRYDsqoaXaoAadbsNOV6loXSh64OkK0RwHxSw14YM9tqQwXWd7HWZ054MOSUdks1Wt41ocwUR9trvvW8rinULB2e6guTDTbviz163BTyLwJu7RZLgDixkp+d7UXJAyHe6QgjJ90tsXBs+uK9zukMJp+9lkhOi0wlIktdlXt/Lkutnk1bByaIIwanyNUlEhlFzoDzq+diCoXxYtb3mJTHJNXdqRIAMm7MGcGq3z3o98UMcPJDLXX/P5doK/3rzsdccLNvrDgQ4k1Jd14k218F60eaadwvsdfNxpvd8bINc5Xr9uefc8nZ/wZ9/va3uuZDlwPOx54C8028udQf/fvNx7bau66S6yyT/7bzm7to5GF4/Q5Z852atfj9aE2tb2eQgPlsDJQAz9JAn/UiSpHgx9+qaIPOx4iA0TubjAI9XQhIE7w+yoYJjBQTIsMk1gFwDlJyov0G45zzKp9p1loAIuWESpC21BwgEm9+/dsiCK+x3nQlgh1NMda3xU3udJNhcBwQ8l9nqbue5bd3rSoCM8rS/4M/zboNwpP5ZfXUXyK7QX3JCaFf72dj9+dh9EMDzmdlRd73shFjgtT1Cf+86iCDVrh9Q+7MsAe5tvQ8qaEWjRYJdFfNx8n+OKAgG8xakNAjo3r07Pnq7KX4+2RTdG9T1xqiSbNhW0whbDzZGKhy4ANsD78AKofx4IbL2J7sBqVVy9EGAFr3TtQjla7cVCiXYHNWAozqCgURu019vRbsf6p8y6c11RoENsmBzBRW1gb8s1oYQog3yAZvnQIBs89rOUft9cnLtQQNbiH/Fup9FG2SbWPd97XXu8QiQffog+7dDcF9W7+wEr58FSQJkue7AgewEpNqfZVfwgMO1P0tS7UEDv+9lGYLTiePFxbBVVSH56FHXdbWXe+5HkiDkyK5go3b/rvuuvUx2X+f3s4y6nyXJ9QgkufYNGVz7df8ru97CQpZrb+/1Pbz24307v9uYtW0HkdacTqeiIODss8/GlE9aoWfmHnRMP+S5/KRkxzZHI2ypyUZj8STObxDkj74VQvkxEX6kKwektCSIFdXKK+XN3N8d7rV6JECq0maH3sGwfzW0X2i8aeStaLcwzHwsCJ550RP421zzruQzf9p95lPJVjffSknJkFPTAsy5gedfyWYDRL/52H2Q3+/AgffP4a4D6loLCrLkM3e65mPvn91zprNunnTPpZ452/Xv8WZtcLBrL9iTT7m2O+a6HeTa322m1xwsu/che827Qf4FfH52z5uC1/fw2cY1vwb9Pslre8B1uVi3HedjShRKC9fOPfdcPDttMbq124s2zY94Lj9xyo6t6xpjy5ZsNGt2HD17lgbZgwX+T70QYj4OE5RKSIIoB/h8HKt2MBqFt8G4zhKQAFTB1raq7j51sCn/VrTb7zcfb/b9UYZQ+9m4NvwXba6gX7TVHjiwea53Xy4Lous62eY6ICCmuraB1/ZwbRfoe/d+AfdloqctUb0zAOF7BkKwz8P+P7s+Y0oQjkiu0D/bfUaB7DpYgNrray9D7UEDz/dw1m4roVJogQNCb6/buPZR++x59lN3Xe1nXfe/st/PntsAgLtAoO463+28t5X9Lg/1fd32kCQIgsD5mEJiMG9BSt94NG/eHOOzv8ezZefisqyNKK3JxNaaxthdk4Um9krsRSaGY6MOI46RK6M7rqt1hR6AuqA+XnulB1OB+o/Z76CF64wCBwAHEKgoXKsDFDqS4aqKhCDWhgy1QYP7+9rLsd/7etF1vSC4DhK4vxdF2CsqkFJWhqTjx323rd0GdjukZMFzfxAE1+WC4Fo4VhRq33i5t6n9V/D6VxRdb5n8b4fan0URcH9fuw2E2rcYQm1lZu1+6y6v/b8oCJBLSnDiRICKGKI4pPRAedu2bXF785/w7K5zcWnuRuyqaogtJxtjb1UmmtgqsdeZib9lrA1843gO5WtJtiQISqrbTR7Ie2i5OKx/tbZ3r/kIK7ldQbUDcDpgq9Ho4IHBfOdjW90cKtQeOPDMd3Vzs//87Z4nZVGE/VQlUg8fgphR49r+lNe2ggBU2iE1dM+tomc+dc+zAHzn46D/AoDguX/37eB5PK5YyTMfA57bAoB8yuv72m0hALj5Ps7HlFCUzsedO3fGtUPW4On55+OS8zdhW2kjbNmTjQOH05GXV4l9+zJx880/B7m1BebjJUJUQbeEZIjwK/CKdZAd43C+nkBnAQS6/1g8bndP+NqA3rUgb+18rHY/ldoOTSvusxQ8wb8gQi4Tgbai6yBB7coDQKCfRa/vXfOqXT6BFBwCarfz3VYAYIcE0XN93XYCAPfnVZvnZ9f/YtHz2Tbg5aidVz37q51ffb6H37b+39e+N96yBbIscz6mkBjMW5CaU/U6px7E37N/wsoThWiTfBh90nagdfJhLDreDr8dL8AorAt8Q7NXy0cZygPuYD5GleUtoHzBT7NbKQPnhn6+vavOPbwfW5z2RvdURUIKfLABUPU7PtytGxpu3IjkI0dCb2jm5/PZuTh8+DBKSvReaYlIf2pay/XMKsVJaQ3WVBSgTephXNhoK1qdOIK3K7qgiaMSl6Zb9EB5lKE8oPBAuVVC+VgqkYFi0zZ/8bQmMoLvfBykf7IKB48dRsOj62Er83qf6H8gxAy93IMdnHnmFQDgfEwJQ8183O/MHaiusWHTzhwUF5Zj0Dmb0ar3Ebz8cg+0bn0EAwZsjfFoY2SJBvOxkATRu5VNvP/5CHVAwH2d/3MwrjYnCXFmQtgkpXaB2IiYfMHXurMUJEB21D0ZkRyAkYEUoRyN5PWajtF7/zFXzPmYwmMwb0Fq3njgORlnATjL66LffvsNn73wAp6e/TTsubmxGKIlSPuTIORrXDHvTWk4H4wZqsRXyr7/BnKuX6+8QGr7+oe8nlzVcVZYbE5vTQAkK9y2GsCBGI6FyIuaxV8xWUYfAH28Llq5ciV+fPNNPPPMMxCzsmIxRH1FWCku2ZIhOkMcKDdDKK8mdI7FeEtk338DMTK0N8PvSEOyINa1ezMr9r4n8lCz5guKZVxUDFzkddEXX3yBLVsWYerUqRCEtJiM0QpkeAXzemaIelfNq1GMwM/FuCDz8Quuim1XP/cQognnrSqC33PAAkCiOMNg3oJUvfHwU15ejlmzZuGOO+5ArlVCebXV8cFCXr9gWLIlwRarinklYhFG7wJQqNG+QoXxfhRNmOHC+Xil4gCNLIqmXZiWiOqTJEn5gXI/paWleOWVV3D//fcjyyqhfKjq+Gyvf4OFtEGuk2xJsB0N0GNej+prA6u8FckB8APnBd2JAnBIAhobPRAiUkJV4ZqfrVu34u2338bkyZORlmaRUF6D6vhAJCS5WtmwsNeXO5wPFsZ7GydDfjGltmo8DDXhvMkr5RUL1T4oAC78SokgsnSXDBXpGw+Hw4GZM2eif//+OPPMM2MwMmuRbMkQtO4x7y/SINroankVobyqbQMF1EpCa60ONhhF6etAEFgxT2Qhkc7H1dXVmDFjBkaMGIH27dvHYGQGUFIxHWibckCqDNJjvjzMfssVbKNkPNFWe0c7jlBUhPLyJsmzICpFx1Ux7/fc5wT53ijBxmCGsRHpLNLCtRMnTmDGjBkYO3YsWrVqpf3ALEZCMsTd0bcD042eYbWSUL6W/PfK8BXzbkUI/zjiJZT3xoM/RB4M5i0o0jce77zzDgRBwFVXXRWDUZlIiyBffuSmSbCFOnVe5f5UMXPrFjVBey1h1N3KN97t90Uess3GinkiC4l0Pn7ttdeQm5uLSy65JAajMpDacLp2W9mWBFHJ4q8K9hXx5ZEeWIhkG6VUVsrLsgzxhvEaDiBxyYLgmo/N3i7G/2ABQ3lKULIsQ1B5YFKWZcyePRunn346+vfvH6ORWUgJIO1NgigbdEa52qC2yO/fWBqsfj4Wzn5Y3X0UhfiKVwp+52xlQ4mAwbwFRVKht3r1anzzzTe48847Iz7NL660cC02F7ZiPlQAryScT5DgWWaYHJ6C14ssCLWL10W3HyLShyRJqoOAb775BmvXrsUdd9wRcVs6y/ML8F095mNwBpt3RXx5gMuj3a/JRBJMKVIObc4KMOnzFojPQXLvcN6M4bcZx0RkAUuWLEFpaSluuumm2PzttJLagFQSkyDKMT6jPAFE03qYfLGVDSUC9pi3ILV/6A8cOIB//etfuPPOO5GdbeZGqjqpDTYlMQliqGBeSQAaqn+4FUP5CKrlPUGA0tuem8BvfMP1m+fir0SWo+bD/K5duzBv3jw89NBDyMjIiOGoTCxIj/mkkxoEAd794oO0zQnZT15Jv3m9wuUI+sp75uNQC8R602qxWL3PJDBCGRh+E8WRTZs24f3338fjjz+O1NRUo4djLK+qZUmIMJj37pNuRIV3LBdSVVktD3jNx0rb37wQ48/Hgfq5m6WVTJgFYVkxT4mAwbxFKQ0CampqMGPGDAwaNAhdu3aN8agswCtsl8Rk2BwnQm6jeJ/+YasVQ/kIqa7QiyD8D6kwfiZrWRTDV8wTkWmo+dt36tQpPPfcc7jyyitRVBTP5yWHECScley1rWzc10dbQxCuL32cUj0fKw3wlQoV9IdaFNgqGM4TmZaav33Hjx/HzJkzcf3116NFiwQ/FdUvnFUVzAcLwo0O6U1A9Xyson+9It5Bf7DQ272grRmECeeJ4h3Pr4lz8+fPR1paGkaOHGn0UCL3nkYTld/7rnoV81r0jgcSKpQHYnjqvFK7LHZ6W6jXWLjFXxP8swORVcmyjLlz56KwsBCDBg0yejiRWxDh39swLVAkWxLEcq/5WIsFXSMVye1NcjKi4afOhwv6lZyNEOjLTMzec56IQpIkCbNmzcIZZ5yBPn36GD2cyEVQxV1PgFBWEpIhSmF6zG+G8ur0WFWxB2KigwCRtDrUlDvoDxd2WyAMZysbSgSsmI9j33//PVatWoVnnnnG+j3O/MP5K1VMdEHCTE8w3wLAeK/9Pxc/Fdh6MDyYB1zhvJUq592vSb+DOLIocvFXoji0bNkybN68GU899ZTxfy+j5R/OjwnzeBQEq5L34q/eLVyGGPRcKWlp488EFeGmmI9L5Mha5JgtgA+FlfNElvXJJ5/g8OHDuOeee4weSvS8w/klas6WCn6VT8W8dxW3uwI71kF7nFROy7JsfP4yTlb2unA/32apnidKQAzm41RNTQ3mzJmD++67Dw0bNjR6ONoL16tbQWWxlJMEsUENUOV3xfgYBKNqDiRYjCmCAKvyex3LghA4mGelPJFlVVRUYP78+Xj00UeRlpZm9HBiI8pQVapKhuiort9XfXEM5uNz4ne+itv5OJIDJVGSwz2PDOeJTENpdfLBgwfx4Ycf4umnn0ZycrIOI9PRYAUhrILg1bX4a3X91ipat1oBYt9X3UCWnI+NDuiDHJRhj3lKBAzmLUhWUFG7f/9+pKamomPHjjqMyADPycD4CP5I+/SYr60IiEUQ7+892ZhwXut+7gEYfuq8m9Wq5t28XpNChswQnsgilMzFALB7927k5eWhVatWsR2QURbIUVe2S/YkiA4NFn9V4gc5NuF8uIMTESzmqpbhp867qa2aj6ZtUYwCe0VnrzGcj8r+/fsxbdo0rF69GpmZmRg5ciSuu+46AMDPP/+MF198EVu2bEFeXh6uvfZaXHrppcYOmExL6WeRHTt2oHXr1igoKNBhVAYIFM6rDFllIQlCJIu/RmKcrH04H24RWC1aAClgmmBeyQEbf0YH9H7YyoYSgQnSNFJLyR/50tJSNG3aVIfRGOg5FX+kA/SPl4RkiDfp2PhOTa/8Qr+fd8nKe6nvqv1Xh1AeMNEbD8B6/eaJyLKUBgEJMR9HU9leXhvMf3ZQu/GEE01IvlhW/3h1COUBk5w676Z0YVkj1gQgw0mShAkTJkAURcybNw8PPfQQ5s+fj6VLl2LXrl0YN24c+vXrh7fffhvXXnstnnjiCfz0009GD5tMyul0wmazhd0uIebjwbIrUHV/qSQJSRD/z/908hiKphK/WHZ9+TNBr3nTFK4BkR+MKEZctBUisgJWzFuM0mqovXv3olmzZjqMyKSUtLLpPU3/CTOSynnvsFlpVbhOoTxgsmDe4niqHpF1KP3QtXfv3vgPAiJVG6rKNzxsjXnEO5Bf7HWmQKhwWKdQHrDofOyueFcbsJf7fa9x5XzYVjYUlZ07d2LDhg2YMWMGcnNz0apVKwwcOBDffvstdu3ahdNPP91TPV9YWIgvvvgC3333HXr27GnswMmUOB9rqNt4a8wj3mFzsQyUKBizTtXygEXn42CKYZrqeaJ4xWDeYtS88WjRIgF6YgSrmg+3gOt4GdKWLeY5kq0lnavG4+qNh8Esf6oez1igBKK0Qm/v3r3o0aOHDiMyWLAq8nBtbn6QIW3apP98rFVLG5OE8oDF5+NIA3o3peG8wu0UL8TOdjYRadmyJVasWOGz7obdbsfJkyfRu3dv9OrVy2f75ORk2O382EqBOZ1OxZ+Pu3fvrsOIDBasCj1c25hxMrBpk/bjCUdtSxslAbt/SxsdQ3nA4vNxIAzniWKK73AsRs2pemeddZYOIzIpBX3jDZsw35OBcxXcbyECV76Hqpo3IBg11al6REQ6URoElJaWJvYZbArbvhgyH6sJ5wM9jsUhbq9zKA+YrJVNpLJRP5xXWg0fLnQvV7gdxZwoij6h/MaNG7F06VJMnDgR7du399n2wIED+PHHH3HjjTfqPUyyCEmSFH8+Tuj5OBYLuGol2n7zgarm3eG8zqE8EIfBPGC63vNE8YTBvMXwVD3tGBooR9tqxkSVyXH5xoOIKAwlQYAkSdi3bx/nYzOLNkA3IIAPxjSLvxopWOjuH/aHCefZyiaIhgCSFW5bDeBk6E2WLVuGhx9+GFVVVRg+fDj69evnc73T6cQjjzyC3r17o1OnThEMmBKBksK1EydO4NixY2jSpIlOoyLVoj1wEKjfvEE90uPiQHkwOlfPs9UrJQIG8xaj9I1HRUUF33gokPAfYDXAYN4k6i0YbMgoiBKGkoO7hw4dQkpKCjIzM3UalTXJStuGUEimm48jrUz3rpqP5Pb+t1XTHqd2zIpb2VBUevXqhbfeegubN2/GM888gw8//BAjRozwXD9z5kyUlpbi6aefNnCUZHZK5uN9+/YhLy+PLZHC4HysDaVncViW/wGPkhDXBdpGBcu3eiVSIE4P48UvJW887HY70tLSsHPnTp1GRYmMrWy0E3FFgH8oH+wyItKMkgPlaWlpnqp5Cs5UYbKFma5CT4t2MZH2nHffNtTtA1XR1/7Linl9pKWloVWrVhgwYABGjx6N//znP57rPvroI3z66aeYMWMGD25SSErm44YNG+Lo0aM4cuSIPoOyKM7H2jDVgfIlOoyj2OtLyTYqzmRgxTwlAhO9eycllLzxSE5OxqBBg/DJJ5/oNCpKZKZ642FxrAggsg4l1VAZGRno168fFi1apNOoKJHFTSsbJWF8LHrEZ9d9Ka6YD7Twa7bfF9WzevVqjB492qc6VxRFJCe7+uT8/PPPmDZtGqZOnYrWrVsbNUyyCCVFQjk5OejZsyeWLl2q06gokfHzsQL+Qb1BbYfIdYbv3LlzccMNN4TcbsGCBRg8eDDOPfdc3HLLLdi9e7fnuqqqKjz22GPo168f+vbti0ceeQSnTp3yXL9q1Sr06NHD52vkyJGajH/Pnj24/fbbcd5552HQoEF44403fK6fPXt2vft+8sknNblvrTCYtxil1ckXX3wxfvnlFxw4cECHUVkTT9XTBt94EFEiUrr469ChQ/Htt9/i2LFjOozKmjgfayMu5uNAoXw0VfNmwHC+nuLiYhw4cADPPvssdu3ahdWrV+O9997DhRdeiN27d+O+++7D2LFjUVxcjEOHDnm+iAJRUrgGAMOHD8fnn3/uExaRL87H2uAZ5WQVTzzxBC655BK8//77OHjwYNDtvvvuO7z88su45557MH/+fKSnp+OBBx7wXP/yyy9jzZo1mDVrFl588UWsWbMGs2fP9lxfXl6OoqIiLF261PP173//W5PH8M9//hNpaWmYP38+xo8fj7lz5+Kbb77xue/LL7/c577HjRunyX1rhX8tLEbpG4+srCz07duXVXohWP7Dq0nERRBARKSS0vm4SZMm6N69O6v0QuAcog3LzcfhWs2Ew8Dbsho2bIgXX3wRmzZtwtVXX41HHnkEl156Kf72t79h8eLFOHr0KF599VUMGjTI54soEKUh6GmnnYaioiIsX75ch1FZj+XmEBPjc0lWkZ2djXnz5oUNqpcuXYqLL74YAwYMQNu2bTFhwgRs3LgR27dv91x/0003oXPnzujatStuvPFGfPbZZ57bl5WVIS8vD7m5uZ6vRo0aqRrrLbfcgjlz5vhctnPnTqxfvx4TJkxAmzZtcNFFF2HgwIE+n7vKysrQrFkzn/vOyMhQdd+xxmDeYtQcfb3kkkvwzTffsEqPYsp0PW2JiHSgZj4ePnw4PvvsM1bpUUyZKggoDjOOcr/v1faDN4NAbWxIsQ4dOmDu3LlYsWIFFi1ahJtvvhk2mw233HILVq9eHfCLKBClB8oB13y8aNEiOByOGI/KeljlrR1TzccWx1avsfX3v/8d7du3D7vd1q1bUVRU5Pm5efPmSE9Px/bt21FRUYGDBw/6XF9cXIyysjIcP34cgKtqPTs7eEXFunXrcN1116F379645ppr8Pvvvysa/9atW5GZmYmCggLPZUVFRdixY4fn53D3bQb8y2sxat54NGnSBN26dcPnn38e41FZE0/V00bc9LQlIlJBzXzcqlUrtGnTBl9//XVsB2VBnIu1Y5n52Iwhu1aCfe4z9+dBIktTsuaLW6dOndCwYUP88MMPMR6V9bDYSjsM5ineVFZW1qsyz8zMREVFBSoqKgDA53r3ou2VlZUAXOH4+vXrcfnll2Po0KF44okncPLkSQDA/v37cccdd2DQoEH4f//v/+Giiy7CXXfd5Qn11Y4rKyvLc7/u+/7www8xePBgjBw5EgsWLIjgGYgtu9EDIHXUHskePnw4Hn30UZSWlqJp06Y+X2lpaTEcqflxstQG33gYrNDoARAlpkjm45kzZ2Lz5s315uPU1NQYjtTcWKGnHdOFKuWoH0jHcyhPRIZQuuYL4Pr8N3z4cLz++uv4/fffUVBQgGbNmqGgoAAFBQWcj800h1gYn0ttsHQjiEIAaqK8EwA2RXeXkiTVu0wQBMiyHPQ679sVFxfDZrPhr3/9Kw4fPoynnnoKzz77LCZOnIiFCxeie/fuGDVqFABgzJgx+OSTT/C///0PpaWleP311wG4Fpj9/fffPcH6Cy+8EPS+vS/v1q0bWrZsib59+2LdunWYPn06cnJyMHjw4OieFA0xmLcYNRV6ANCmTRs89NBD2L59O0pLS/Hdd99h7969OHDgADIyMlBQUICxY8eiXbt2MRy1+bBCTzsM5g3EUJ7IMGrn4y5duuCee+7Bzp07UVpaij///BN79+7FwYMH0bBhQxQUFODGG29Ey5YtYzhq8+Ecoh1TPZflfv9qtU//oD9b4/tQKlAbm1BV8TwgQRQzav/2nXPOOUhPT8fu3buxd+9erF+/Hnv37sWhQ4fQuHFjNGvWDLfeeivy8/NjOGrzscxZVxZgqvnY0kQwnjcHURTrheCyLMNms3kOQnlf787b3J+Vrr76ap/b3nXXXZg4cSIefPBBbNq0CT/88AN69+7tub6qqgp79+7FyJEjMXDgQADAxIkT0blzZ0+An5eXhz179gQdl9tjjz3m+b64uBibN2/GokWLGMxT5NScqufWrl27esG7w+HAggUL8P3336tedCEe8Ci2dkz1Jq7QJOPQg5JQvhDArlgPhCgxRTKPdOzYER07dvS5zOFwYM6cOdi4cSOysrK0HKIlcD7WjqnmY6rDUJ4o5tT87RMEAV27dkXXrl19Lq+ursbMmTM9BWyJhvOxdhjMa0OGCAH1K6JJf2lpafVayxw/fhyZmZmeThze17u/D/a3tE2bNqiursaRI0cAAIMHD8YNN9zgs01WVhYaNmyIhg0bAgBSUlKQlZWFwsK6ICQ9Pb3euI4dO+ZppRNI69at8eOPP4Z6uLrjX16LUXOqXihfffUVVq5cicmTJ6NJkyYajMxaTHe6t4XxudSODIVv4FgpT2QKWnzoWrRoEdavX4/JkyfzQDlFJSHmY61Dbq32F6xanqE8kSXIsoz33nsPe/fuxaRJk5Cenm70kHTH+Vg7fC61IUNgMG8SrVu3xoYNGzw/79mzB5WVlWjTpg2ysrKQk5Pjc31JSQkKCgqQnp4OSZIwfPhwrFu3znP9rl27kJSUhEaNGqF169bYtm0bCgsLPV85OTmeQD7cuE6cOOGz2OvmzZvRpk0bAMCff/6JoUOHoqamxnP97t27kZeXF9XzoTX+tbAYLaqhli9fjvfeew+TJk1Cs2bNNBqZtbCqTDusCNCOolXnGcoTmYIWLdEWLVqEzz77DA8//DByc3M1GJX18MOrdhJmPvYPu6NdWLXc70sthvJElvfuu+/ip59+wsMPP6woDIpHnI+1kzDzccyxlY2RqqurPd8PHjwYy5cvx5IlS7B161ZMnz4dXbt2RfPmzT3Xv/baa1izZg3Wrl2Lf//7355WMaIookePHnj22Wfx559/4o8//sCsWbMwaNAgiKKIK6+8EiUlJZg5cyZ27NiBVatWYeTIkSgpKQk7xlatWqFDhw6YPn06Nm/ejC+++AJffPGF577btm2LlJQUPPPMM9i5cye+/vprfPjhhxgyZEgMnrHIsZWNBUXzR37FihV46623MGnSJJ9TQBIN33hohwc5dJS4/2WJ4s7SpUvx6aef4pFHHkm4PrbeOB9rh0GAiTCUJ7KMhQsX4n//+x8eeeQRNG7c2OjhGIbzsXY4H2uDrWyMs2/fPowZMwYLFixAQUEBevfujdtvvx3PP/88jh07hr/85S+YMmWKZ/vbbrsNR48exZ133gkAuPDCC3HzzTd7rr/nnnswY8YM3HHHHRAEAb1798b48eMBAE2bNsXzzz+PmTNn4p133kF+fj5uvPFGFBcX+4xp7ty5Acc6depUTJkyBddccw2ysrJw++2345xzzgEA2O12zJgxA9OmTcOYMWPQuHFj3HDDDRg6dKimz1e0GMwnkE2bNmHevHl46KGH0KpVK6OHYyi+8dBOQpw6r5OgrWwYyBPFlTVr1mDhwoWYPHkymjZtavRwDMX5WDsJ9Vx6LwSrcQjO2jyixLFy5UosW7YMjz76KHJyAq3qnDgSag6JMQbzWhEABvO6GDZsGIYNG+b5uaCgAF9++aXPNmPHjsXYsWMD3j41NRWTJ0/G5MmTA16fnp6OiRMnYuLEiQGv79GjBxYsWBDR2Fu0aIGXX3456PWnnXYaZs2aFdG+9cJgPoHs27cPHTt2RNu2bY0eiuH4xkM7fOOhnXqtbLQI5LkALJHplJaWonv37mjRooXRQzEc52PtWGo+9g7To21Fo6VsAIIIhGpVFS67Y7U8kW6ibSu3e/dunHvuuabrN2wEzsfasdR8bGIybMpavRJZHIN5i+EfeG3wjYd2+MYjRlglT2Rq/LunDc7H2rHMfOwfXHtXv0e7Lw3IoghBVlihZ4aDCmVGD4DIOJxDtCNJEux2xkNasMRcbAFc/JUSBWcxi4mmKkCLheriBd/EaYetbLTjaWWjdSjPkJ9IU5LEDwla4XysHUsE88GC9EgWXo1RZbosCBAC/R/Pgfmq5RnKU4LjHKIdfqYj8xHBVjaUCHhI1EIYrGuHb+K0w8VftSNADh2ie3e92K1y5+79sq0NUdQkSYLNZov49pzP67BCTzumD+bN3uLFXf3u38pGadtpsz8+ojjkdDqj+kzH+bhOtM8l1eHrShtc/JUSBT8JWYgWQYCpP7DpiMG8dkz1utqlwZugQgMfS2aQy7VsQ82AnihqWswhpvm7aTBW6GnHVK+pMg3m4xxjHo8sioEr5gMxMoxntTxR1J+PqQ7nY+2Yaj4erMF8vMSg+ZitbChB8C+vhTBM1g6rvLVjqmBeC1qE+xFQda9qq+WJSFNOp5MV8xrhexsKSotwXynvXvGCACjtMR9OrMJzhvJEALSZj+Pqc0wUOB9TUFqE+xERofJTMpEl8S+vhbBCTzusCNBW3L2ujAjnW/qdOh9LrJYnigrnY+0wCNBOXB7w0TOcryWLNghaPJdlXv9qGaQzlCfy4ByiHT6X2onL+diAcJ4V85Qo+JfXQqKtCKA67KFHYekczsuiCEFJhR6r5YkMx/lYOwwCyHDZvj/WW/xVbRAeLIjXIlBnKE/kg/Oxdjgfk9nIXPyVEgT/8loIw2TtsGKezKZeEBArrJYniho/vGqHzyWFpXfVvChG1spGSWV8pMG61lX3RHGCZ7Bph/MxhaV71TwXf6XEwL+8FsLFbbTDNx6kiF5V84UAhCCtbLwXfmW1PJEpsEJPO5yPSZFYhfPZ9S+SBRWLvwLqQ/NIKvCJKCAt5uO4bDsSAc7HpIiO4byrlQ3/f1L8sxs9AFIu2jceGRkZOH78uIYjsi6+8SDFdArnZYcDwo4dwOOv6XJ/RBS5aA+UZ2Rk4NixYxqOyLo4H2sn7qs+9aqcr6qCsG8fMPtdfe6PiCIW7RySkZGB3btZ+QJwIVwtxf3zqFc4X1kJHD4MtPhUn/sjMgg/CVlItG888vPzsW/fPg1HZF0MAoiIKFLRHijPz8/H/v37NRyRdXE+JrNh9SyRdWgxH/PzcZ24D5TJUniwiBJFwlXMW7lC7ciRI0hKSor4A2xKSgokScKBAweQlJSk8eispaKiAseOHWMrAg2cOHEChw8fNnoYludwOHDy5Mm4eC7N+Hd2zpw5eOWVVwJe99///hf5+fk6j4jM+DpR6ujRo3A4HJAiXBciLS0NJ0+eRHl5ecJ/4KisrMSRI0cS/nnQQmVlZVzMIUarqqqKm/c2Vv47S/qx8uvk+PHjsNvtqK6ujuj2mZmZ/NtZK17+7hlNlmU+lxqprKyMm+fSyn9nKfYSJphPSUmBzWbDjz/+aPRQDDVgwAB88803Rg/DFDZu3Gj0EOJGSUmJ0UOIGxs2bDB6CJqw2WxISUkxehgeY8eOxciRI30u+/LLL/Hhhx8ylNcZ52OXvn37YtmyZUYPwxQ4h2hn8+bNRg8hbqxbt87oIWjCbPMxmQfnY5ezzjoLX375pdHDMAXOx9rhc0n+OB9TMAkTzKelpWHQoEGoqqoyeihERHEvJSUFaWlpRg/DIy0trd54vvzyS4wYMcKgESUuzsdERPox23xM5sH5mIhIP5yPKZiECeaBwMEMERElns2bN2PDhg147rnnjB5KQuJ8TEREZDzOx0RERMbialtERJRwFi5ciAsuuABZWVlGD4WIiIiIiIiIElBCVcwTEZEF5QPIULhtBYADoTc5efIkFi9ejJkzZ0Y3LiIiokTSEIDS4uoTAPbFcCxEREREcYAV80RElFCWLFmCvLw8dOvWzeihEBEREREREVGCYjBPREQJZeHChbjsssuMHgYRERERERERJTC2sjGB8vJyfPjhh9i+fTsyMzMxePBgdOnSBQDw4YcfYsOGDRg4cCB69uyJr7/+GmvWrMFdd93luf23336Lr7/+GpMmTfJctmrVKnz55Zd46KGH9H44hjp16hQ+/vhjbNy4EcnJyTjnnHPQv39/AHwulfriiy+wbNmygNf985//xPLly/k8RuDEiRP48ssv8ccff6Bp06a47rrrAPB1qbd169Zh27ZtuOSSS4weCpkQ52PtcD6OHudj7XEuJrIGzsfa4XwcPc7H2uN8TFSHwbzBJEnCG2+8gdzcXPzf//0ftm3bhnfeeQcFBQU4fvw4Dhw4gDFjxuDtt9/GGWecgcLCQnz++eeorq5GcnIyAGDr1q2orKzEgQMH0KRJEwDA7t27UVhYaORDM8SiRYuwd+9e3HzzzThy5AjeeecdNG7cGFlZWXwuFerTpw/OOeccn8t+//13/PjjjygrK+PzGIGamhq88sorSEpKwhVXXIGmTZsCcD1PfD71tXDhQvTr1w+NGjUyeihkMpyPtcX5OHqcj7XFuZjIGjgfa4vzcfQ4H2uL8zGRL7ayMdiuXbtw8OBBXH755cjPz8c555yD9u3bY+XKlTh16hQaNmyIpk2bwmazwel0okWLFpBlGaWlpQBcb1y2bduGnJwcbN261bPf3bt3o2XLlkY9LMNs3LgR/fv3R7NmzdCxY0ecccYZWL9+PZ9LFVJSUpCZmenztXbtWpx11ll8HiO0cuVKVFZW4qabbkJRURHS09MBgM+nzo4dO4bPP/8cI0aMMHooZEKcj7XF+Th6nI+1xbmYyBo4H2uL83H0OB9ri/MxkS8G8wY7fPgw0tPTPX+MAKBVq1bYu3cv2rVrh7KyMjz88MM4/fTTkZqaipSUFDRp0gS7d+8GAM8fqB49emDbtm0AXEcgDxw4kJBHDGtqamC3150IkpSUhJqaGj6XUdi3bx/27NmDbt268XmM0G+//YbzzjvPc5Tfjc+nvrKysvC///0PPXv2NHooZEKcj7XF+Vh7nI+jw7mYyBo4H2uL87H2OB9Hh/MxkS+2sjFYWloaTpw44XNqjt1ux/Hjx2G323H77bejsrISGRkZntu0bNnS84dpy5YtaN26NYqKirBy5UoAwN69eyHLMlq0aKH/AzJYp06dsHLlSrRt2xYVFRX47bffMHToUD6XUVi1ahU6d+6MtLQ0AODzqJLT6cS+ffvQrl07vPjii6ioqEC7du0wbNgwJCcn8/kkMgnOx9rifKw9zseR41xMZB2cj7XF+Vh7nI8jx/mYqD5WzBusVatWSElJwWeffQaHw4E9e/bgq6++gii6fjWCIPj8UQKAwsJC7NmzB4Crv1ZRURGaN2+O6upqHDp0CHv27EGTJk2QkpKi++Mx2iWXXIJDhw7h0UcfxfTp03HaaaehW7duAPhcRqK6uhq//PILzjrrLM9lfB7VOXHiBCRJwvr16zFo0CBceeWV2Lp1KxYtWgSAzyeRWXA+1hbnY21xPo4O52Ii6+B8rC3Ox9rifBwdzsdE9TGYN1hycjJGjRqFNWvWYNKkSXj77bdRXFzsOfoaSMuWLXHo0CFUVlZi27ZtKCoqgiiKaN26NbZu3ZrQ/bUWLlyI/Px83H777bjuuuuwe/dufP/990G353MZ2q+//oqsrCy0bt065HZ8HoNzOp0AgCuuuALFxcVo27YtBg8ejF9++QWSJAW8DZ9PIv1xPtYW52NtcT6ODudiIuvgfKwtzsfa4nwcHc7HRPUxmDeBdu3a4cEHH8QDDzyAe+65B0lJScjPzw+6fZMmTZCUlISffvoJKSkpnm3btGmDbdu2Yc+ePQnZX+vgwYP4448/MHLkSBQWFqJ9+/a46KKL8NVXXwW9DZ/L0FatWuVTDRAMn8fg0tPTIQgCkpKSPJc1adIEDocDJ06cCHgbPp9ExuB8rA3Ox9rjfBwdzsVE1sL5WBucj7XH+Tg6nI+J6mMwbxI2mw0NGzZEdXU11q1bh06dOgXdVhRFtGjRAr/88gvatm3rubxt27bYsWMHysrKEvKIofvoq/fiNsnJyXA4HEFvw+cyuJ07d+LAgQM488wzw27L5zG4pKQk5ObmYufOnZ7LysvLYbfbg1b+8PkkMg7n4+hxPtYW5+PocS4msh7Ox9HjfKwtzsfR43xMVB+DeZMoLy/HH3/8gdmzZ6NZs2Y4/fTTQ27fsmVLHDhwAEVFRZ7LmjZtihMnTkAUReTl5cV6yKaTl5eHnJwcfPLJJzh48CB27tyJZcuWoWPHjiFvx+cysFWrVqFTp05IT09XtD2fx+B69+6NL774AiUlJdi9ezeWLl2K7t27e3plBsLnk8gYnI+jx/lYW5yPtcG5mMhaOB9Hj/Oxtjgfa4PzMZEve/hNSA/PP/88MjIy8Je//AX9+/cPu737VB3vP0yiKKJNmzaorq4O+UctXtlsNlx33XVYtGgRXnrpJdjtdnTq1AlDhgwJeTs+l/WdOHECv//+O6699lrFt+HzGNxZZ52FY8eO4Z133gEAvi6JTIzzcfQ4H2uH87F2OBcTWQvn4+hxPtYO52PtcD4m8iXIsiwbPQgiIiJ/hw8fxpdffokBXe5H44xtym5T0Rpfrn0aAwYMQOPGjWM8QiIiovjnmY9Pvx+N0xTOxyda48s/OR8TERFpwTMXt1M+FwO18/EmzsdmxsNKREREREREREREREQ6YjBPRERERERERERERKQjBvNERERERERERERERDpiME9EREREREREREREpCMG80REREREREREREREOmIwT0RERERERERERESkIwbzREREREREREREREQ6YjBPRERERERERERERKQjBvNERERERERERERERDpiME9EREREREREREREpCMG80REREREREREREREOmIwT0RERERERLrZu3cv7rnnHlxwwQUYPHgwnnvuOVRXVwMAtm3bhltvvRV9+vTBlVdeiW+//dbg0RIRERHFBoN5IiIiIiIi0oXD4cC4ceOQnJyMV199FY899hg+++wzvP7663A4HJgwYQKaNGmC+fPnY8iQIXjggQewe/duo4dNREREpDkG80RERERERKSL33//Hbt27cLDDz+MNm3aoGfPnhg1ahS+/fZb7Nq1Czt27MBdd92F0047Dddddx3y8/Pxww8/GD1sIiIiIs0xmCciIiIiIiJdNGvWDNOnT0eDBg08lyUnJ8Nut6OqqgoAkJKS4rkuNTXVczkRERFRPGEwT0RERERERLooKCjA+eef7/lZkiQsXrwYF1xwAYqLi9GiRQvMmzcPDocD33zzDXbs2IG+ffsaOGIiIqL4dOjQIcydOxc33HCDZvs8cuQI7r33Xpx//vm48MILMWPGDEiS5Ln+o48+Qo8ePXy+/vGPf2h2/1ZjN3oAREREREREZHJZtV9KqPiU+corr6CiogJXXnklbDYbHnvsMdx888148803IUkSJkyYgBYtWkQyYiIiIgriiSeewKefforMzEykpqZqtt+nnnoKZWVleO2111BWVoZJkyahadOmGDVqFACgrKwM5513HiZNmuS5TXJysmb3bzUM5omIiIiIiEh3X331Fd5880288sorSE1NRUVFBSZNmoSrr74aF198Mf744w+88MIL+Mtf/oIOHToYPVwiIqK4kZ2djXnz5qGkpARz585VfftHHnnE518AOHnyJL7++mu8/PLLaNeuHQDgiiuuwNKlSz3BfHl5OfLz85Gbmxv1Y4gHbGVDREREREREutq0aRMmT56MiRMnomPHjgCAzz//HKIoYty4cTj99NNx+eWXo3///njrrbcMHi0REVF8+fvf/4727dsHvG7nzp24/fbb0bt3b1x11VVYsWKFon3u2rULDocDRUVFnsuKi4uxfft2z8/l5eXIycmJauzxhME8ERERERER6aasrAzjx4/H3/72NwwePNhzeXV1NZKSkny2TU1NRXV1td5DJCIiSkgnTpzA3//+d3Tq1Alvv/02rr32Wvzzn//E7t27w962srISAJCRkeG5LCsry3M54HoPsGLFCgwbNgyXXnopZs2aBYfDof0DsQi2siEiIiIiIiJdVFdXY8KECWjZsiWuuOIKHDp0yHPdOeecg+effx5vvvkmLrjgAmzevBmLFy/GfffdZ+CIiYiITKIlgMYqtj8MYJO6u/j888+RlZWFO+64AwBQWFiIzz//HJ9//jmaNm2KJ598EgA8B82XLVsGAHjwwQeRl5cXcJ+yLHu+79y5M5xOJ4YOHYqdO3di6tSpaNCgAW688UZ1A40TDOaJiIiIiIhIF2vXrsXatWsBAIMGDfK57uWXX8b06dPxr3/9C3PnzkVOTg5uueUWDB061IihEhERJZw///wTW7duRe/evT2XVVdXIy8vD1dddRU6d+4MAHjhhRcAAOPGjQPg6ln/559/AgAkSYIo1jVpsdlsnu/d2wNAu3btsG/fPnzwwQcM5omIiIiIiIhiqXv37li9enXIbc477zydRkNERET+evbsifvvv9/nsvT0dM+X+2fAVVHvlpaWBgA4duwYGjVq5Pneu7WNvzZt2mD//v1aDt9S2GOeiIiIiIiIiIiIKMG1bt0a27ZtQ9OmTVFYWIjCwkLk5OQgOzs77G1btmwJm82GjRs3ei4rKSlB27ZtAQBHjhzBgAEDcPDgQc/1u3btCtoCJxEwmCciIiIiIiIiIiJKcEOGDIHD4cCjjz6KrVu3Yu3atbj22muxYsWKsLdNS0tD37598eKLL2Ljxo344Ycf8P7773ta1zVq1AjFxcWYOnUqtm3bhtWrV+ONN97AkCFDYv2wTIutbIiIiIiIiIiIiIgSXEZGBl588UVMnz4dY8aMQVZWFkaOHInzzz/fZ7tHHnkk4O0ffPBBTJkyBTfeeCNSU1Nx2WWXYcSIEZ7rH3/8cUybNg033HADGjRogIsvvhjXX399LB+SqTGYJyIiIiIiIiIiIkoww4YNw7Bhw3wua9euHebOnRvR/ho1aoTp06cHvT43NxdPP/10RPuOR2xlQ0RERERERERERESkIwbzREREREREREREREQ6YjBPRERERERERERERKQjBvNERERERERERERERDpiME9EREREREREREREpCO70QMgIiIKKR9AY4XbHgawNoZjISIiIiIiIiLSACvmiYiIiIiIiIiIiIh0xGCeiIiIiIiIiIiIiEhHDOaJiIiIiIiIiIiIiHTEYJ6IiIiIiIiIiIiISEcM5omIiIiIiIiIiIiIdMRgnoiIiIiIiIiIiIhIRwzmiYiIiIiIiIiIiIh0xGCeiIiIiIiIiIiIiEhHDOaJiIiIiIiIiIiIiHTEYJ6IiIiIiIiIiIiISEcM5omIiIiIiIiIiIiIdMRgnoiIiIiIiIiIiIhIRwzmiYiIiIiIiIiIiIh0xGCeiIiIiIiIiIiIiEhHDOaJiIiIiIiIiIiIiHRkN3oAREREREREZHINATRWuK0Qy4EQERERxQdWzBMRERERERERERER6YjBPBERERERERERERGRjhjMExERERERERERERHpiME8EREREREREREREZGOGMwTEREREREREREREemIwTwRERERERERERERkY4YzBMRERERERERERER6YjBPBERERERERERERGRjhjMExERERERERERERHpiME8EREREREREREREZGOGMwTEREREREREREREemIwTwRERERERERERERkY4YzBMRERERERERERER6YjBPBERERERERERERGRjhjMExERERERERERERHpiME8EREREREREREREZGOGMwTEREREREREREREemIwTwRERERERERERERkY4YzBMRERERERERERER6YjBPBERERERERERERGRjhjMExERERERERERERHpiME8EREREREREREREZGOGMwTEREREREREREREemIwTwRERERERERERERkY4YzBMRERERERERERER6chu9ACIiIj0sGvXLowYMcLnsuTkZKxcudKgERERESWmvXv3Yvr06fj111+RkpKCgQMH4v/+7/+QnJzss90tt9yCvXv34tNPPzVopERERPGptLQUTzzxBNasWYPc3Fz84x//wIABA+ptJ0kS/vWvf+Gjjz5CdXU1Lr74Ytx7771ISkoCADgcDvTq1QuyLPvcbunSpcjNzY1qjFVVVXj66aexfPlyyLKM/v3744EHHkBqamq9bSdPnoz//ve/WL16dVT3qTcG80RElBDKysqQmZmJ999/33OZIAgGjoiIiCjxOBwOjBs3DkVFRXj11VdRVlaGiRMnIj09Hbfeeqtnu8WLF+PXX39FQUGBgaMlIiKKP5Ik4e6770bLli0xf/58/PLLL5g0aRKKiorQqlUrn20XLFiATz75BFOmTEF6ejomTZqEV199FX//+98BAOXl5ZBlGR9++CEaNGjguV12dnbU43z55ZexZs0azJo1C5Ik4eGHH8bs2bMxfvx4n+3WrFmDJUuWRH1/RmArGyIiSgjl5eXIzs5Gbm6u5ysnJ8foYRERESWU33//Hbt27cLDDz+MNm3aoGfPnhg1ahS+/fZbzzYVFRV44YUXMGTIEANHSkREFJ/WrVuH7du346GHHkKbNm3w17/+Feeffz7ee++9ett+9NFHuPbaa3H22Wejc+fOuPvuu/H+++/D4XAAcH3OTklJQWFhoc9nbVFUHjnPmTMHt9xyS73Lly5diptuugmdO3dG165dceONN+Kzzz7z2cbpdOLpp5+27HsGBvNERJQQysvLGcQTEREZrFmzZpg+fbpPVV1ycjLs9rqTuefMmYNu3bqhR48eRgyRiIgorpWWlqJRo0Zo1KiR57IzzjgDJSUl9bbdu3cvWrdu7bPdsWPHsG/fPgCuM9MbN24c9L7Ky8tx7733ok+fPrj88svx0UcfKRpjRUUFDh48iKKiIs9lxcXFKCsrw/Hjxz2Xvfvuu2jQoAEuueQSRfs1GwbzRESUEMrKyrB3716MGjUKgwYNwj//+U8cPnzY6GEREREllIKCApx//vmenyVJwuLFi3HBBRcAADZv3oxPP/0Ud999t1FDJCIiimuNGjXC0aNHcfLkSc9lSUlJOHjwYL1tGzZs6Anh3dsBwKFDhwC4gveTJ0/immuuwUUXXYRx48Zh9+7dAFzV7HfeeScyMjIwf/583H333ZgxYwZ++eWXsGOsqKgAAGRkZHguy8zMBABUVlZ6xvDqq6/ivvvuU/X4zYQ95omIyNSOHWuuybannXYaunTpgiuvvBKSJGH69Ol46KGHMHv2bC2GSUREFNe0mo/9vfLKK6ioqMCVV14JAHj66adx3XXXoUmTJqrHSEREFM/UzK+htj/jjDOQnp6O2bNnY9y4cdiyZQvmzZuHtLS0etv269cP8+fPR69evZCRkYGpU6cCgOdMtyZNmqBbt2648sorkZaWhtmzZ+Ouu+7Cu+++i9WrV6O0tBSvv/467HY7TjvtNAwZMgRLliyBIAgYN24cAKCmpgaSJKF3794AgOuvvx6DBg2qNxb3GnGSJAEAnn/+eQwcOBDt27e33KKvbgzmiYjIlFJSUmCz2fDjj+NU3c5msyElJaXe5YMGDfKZ3B9++GGMGTMGBw8eRF5eXtTjJSIiikdaz8fevvrqK7z55pt45ZVXkJqaikWLFqGsrAxXX311NEMmIiKKK5HOxUDg+Tg1NRVTpkzBpEmT8O6776J58+Y4++yzsWPHjnq3v/3227F161ZccsklSElJwTXXXAMAyMrKAgCcffbZOPvssz3bP/HEE7j44ouxbt06bNq0CcePH0f//v0919fU1KBHjx7o0KED3n77bQDAO++8g3Xr1mHKlCmefbur+d0hPADIsux5TD///DO+//57LFy4UPVzYiYM5omIyJTS0tIwaNAgVFVVqbpdSkpKwCP9/tx98vbv389gnoiIKIhYzcebNm3C5MmTMXHiRHTs2BEAMG/ePJSWlnra2jidTtTU1KB379544YUX0K1bt8gfCBERkUVFOhcDwefjXr16YenSpSgrK0NeXh6mTZuGtm3b1tsuKysLc+fORVlZGRo0aIBt27bhzTffRPPmgavxGzdujMaNG+PAgQMAgFatWuHZZ5+tN6bU1FQUFhZ67sO9gKybuzreu5+8+/uMjAy88cYbOH78uKe3vDvA7927Nx588EEMHjxY2RNkMAbzRERkWmlpaYpCdiVuuukmjBo1CgMGDAAA7Nq1CwAYyhMREYWh5XwMuNZ9GT9+PP72t7/5fHB+8cUX4XA4PD8vX74c7777LubMmcP5moiIEprWczHgakeTn5+PiooKLFu2DJMnTw66bU5ODgDg448/Rp8+fWCz2QAADz30EDp06IAxY8YAcPWGP3LkCPLy8tCgQQOUlpYiMzPTs9DsqVOnkJycHHZsWVlZyMnJwYYNG9ChQwcAQElJCQoKCpCeno6JEyf6HKhYt24dJk2ahLfffhvZ2dkRPR9GYDBPREQJ4ZxzzsHs2bORl5eH9PR0TJs2Dd27d0d+fr7RQyMiIkoY1dXVmDBhAlq2bIkrrrjCs3gcAOTm5noWlQOA7Oxs2Gw2nwo6IiIi0saePXtQUlKCl156Ce3bt8d5550HwDVXe4fnx48fx9atW/Hxxx9j+fLlmDdvnue6c889FzNnzkRRUREKCgowZ84cNG/eHJ07d4YgCGjRogUeeughjBs3DoIgYNq0abjwwgsxatSosOMbPHgwXnvtNbRp0wY2mw3//ve/PQf0/dei2b9/PwBY7j0Dg3kiIkoI1113HU6cOIH7778f1dXV6N69O+6//36jh0VERJRQ1q5di7Vr1wJAvYXdXn75ZfTo0cOIYRERESWc0aNHIzs7GxdffDGuu+46AMC+ffswZswYLFiwAAUFBQCAl156CV988QW6d++O1157Da1atfLsY+jQoSgrK8MTTzyBY8eOoVOnTpgxY4ZncdjnnnsOzzzzDG644QakpqZi8ODBGDFihM84br311oDju+2223D06FHceeedAIALL7wQN998s8bPgrEE2d05n4iIiIiIiIiIiIiIYk40egBERERERERERERERImEwTwRERERERERERERkY4YzBMRERERERERERER6YjBPBERERERERERERGRjhjMExERERERERERERHpiME8EREREREREREREZGOGMwTEREREREREREREemIwTwRERERERERERERkY4YzBMRERERERERERER6YjBPBERERERERERERGRjhjMExERERERERERERHpiME8EREREREREREREZGO/j/DOHZsYd9+HQAAAABJRU5ErkJggg==" + }, + "metadata": {}, + "output_type": "display_data", + "jetTransient": { + "display_id": null + } + } + ], + "execution_count": 67 } ], "metadata": { @@ -909,4 +915,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/docs/notebooks/performance_analysis.ipynb b/docs/notebooks/performance_analysis.ipynb new file mode 100644 index 0000000..17e4a97 --- /dev/null +++ b/docs/notebooks/performance_analysis.ipynb @@ -0,0 +1,725 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "28ef162d4b412362", + "metadata": {}, + "source": [ + "# Performance Analysis: Earthkit-Climate Indicators\n", + "\n", + "This notebook provides a comparative performance analysis of the `earthkit-climate` indicators on the SSP5-8.5 dataset. We compare two execution modes:\n", + "1. **Lazy Execution**: The baseline approach where dask graphs are built and executed without specific optimizations.\n", + "2. **Optimized Execution**: An enhanced approach using pre-computation of heavy statistics (like percentiles) and strategic re-chunking.\n", + "\n", + "We profile 5 key indicators:\n", + "- **WSDI**: Warm Spell Duration Index\n", + "- **CWD**: Maximum Consecutive Wet Days\n", + "- **DTR**: Daily Temperature Range\n", + "- **HDD**: Heating Degree Days\n", + "- **SDII**: Simple Daily Precipitation Intensity Index" + ] + }, + { + "cell_type": "code", + "id": "cache_config", + "metadata": { + "ExecuteTime": { + "end_time": "2025-12-11T17:35:05.411512492Z", + "start_time": "2025-12-11T17:35:05.334785047Z" + } + }, + "source": [ + "from earthkit.data import cache, config\n", + "import os\n", + "\n", + "import warnings\n", + "\n", + "warnings.filterwarnings(\"ignore\")\n", + "\n", + "# Configure robust caching to avoid re-downloading\n", + "cache_dir = os.path.expanduser(\"~/.cache/earthkit/data\")\n", + "os.makedirs(cache_dir, exist_ok=True)\n", + "settings_earthkit = {\n", + " \"cache-policy\": \"user\",\n", + " \"temporary-directory-root\": cache_dir,\n", + "}\n", + "config.set(settings_earthkit)" + ], + "outputs": [], + "execution_count": 1 + }, + { + "cell_type": "code", + "id": "dynamic_resources", + "metadata": { + "ExecuteTime": { + "end_time": "2025-12-11T17:35:05.451533026Z", + "start_time": "2025-12-11T17:35:05.415349573Z" + } + }, + "source": [ + "import platform\n", + "import os\n", + "from IPython.display import Markdown, display\n", + "\n", + "def get_cpu_info():\n", + " try:\n", + " with open(\"/proc/cpuinfo\", \"r\") as f:\n", + " for line in f:\n", + " if \"model name\" in line:\n", + " return line.split(\":\")[1].strip()\n", + " except Exception:\n", + " return \"Unknown CPU\"\n", + " return \"Unknown CPU\"\n", + "\n", + "def get_ram_info():\n", + " try:\n", + " with open(\"/proc/meminfo\", \"r\") as f:\n", + " for line in f:\n", + " if \"MemTotal\" in line:\n", + " total_kb = int(line.split()[1])\n", + " return f\"{total_kb / 1024 / 1024:.1f} GB\"\n", + " except Exception:\n", + " return \"Unknown RAM\"\n", + " return \"Unknown RAM\"\n", + "\n", + "cpu_model = get_cpu_info()\n", + "ram_size = get_ram_info()\n", + "\n", + "display(Markdown(f\"\"\"\n", + "## Resources Used\n", + "\n", + "### Hardware Configuration\n", + "The performance analysis was conducted on the following hardware (dynamically detected):\n", + "- **CPU**: {cpu_model}\n", + "- **RAM**: {ram_size}\n", + "\"\"\"))" + ], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ], + "text/markdown": "\n## Resources Used\n\n### Hardware Configuration\nThe performance analysis was conducted on the following hardware (dynamically detected):\n- **CPU**: AMD Ryzen 5 5500H with Radeon Graphics\n- **RAM**: 15.0 GB\n" + }, + "metadata": {}, + "output_type": "display_data", + "jetTransient": { + "display_id": null + } + } + ], + "execution_count": 2 + }, + { + "cell_type": "code", + "id": "dynamic_dataset_info", + "metadata": { + "ExecuteTime": { + "end_time": "2025-12-11T17:35:08.886634702Z", + "start_time": "2025-12-11T17:35:05.458533533Z" + } + }, + "source": [ + "import earthkit.data\n", + "import xarray as xr\n", + "import os\n", + "from IPython.display import Markdown, display\n", + "from typing import Dict, List, Any\n", + "\n", + "# Dataset URLs\n", + "DATASET_URLS = [\n", + " \"https://sites.ecmwf.int/repository/earthkit-climate/tasmax_gridded_day_CMIP6_ACCESS-CM2_r1i1p1f1_deepESD_day_historical.nc\",\n", + " \"https://sites.ecmwf.int/repository/earthkit-climate/tasmax_gridded_day_CMIP6_ACCESS-CM2_r1i1p1f1_deepESD_day_ssp585.nc\",\n", + " \"https://sites.ecmwf.int/repository/earthkit-climate/tasmin_gridded_day_CMIP6_ACCESS-CM2_r1i1p1f1_deepESD_day_ssp585.nc\",\n", + " \"https://sites.ecmwf.int/repository/earthkit-climate/pr_gridded_day_CMIP6_ACCESS-CM2_r1i1p1f1_deepESD_day_ssp585.nc\"\n", + "]\n", + "\n", + "\n", + "def format_size(size_bytes: float) -> str:\n", + " \"\"\"\n", + " Convert a byte size into a human-readable string.\n", + "\n", + " Parameters\n", + " ----------\n", + " size_bytes : float\n", + " File size in bytes.\n", + "\n", + " Returns\n", + " -------\n", + " str\n", + " Size formatted as B, KB, MB, or GB.\n", + " \"\"\"\n", + " for unit in [\"B\", \"KB\", \"MB\", \"GB\"]:\n", + " if size_bytes < 1024:\n", + " return f\"{size_bytes:.1f} {unit}\"\n", + " size_bytes /= 1024\n", + " return f\"{size_bytes:.1f} TB\"\n", + "\n", + "\n", + "def extract_dataset_info(url: str) -> Dict[str, Any]:\n", + " \"\"\"\n", + " Extract key metadata information from a NetCDF dataset available via URL.\n", + "\n", + " Parameters\n", + " ----------\n", + " url : str\n", + " URL to the NetCDF dataset.\n", + "\n", + " Returns\n", + " -------\n", + " dict\n", + " Dictionary containing:\n", + " - Variable\n", + " - Scenario\n", + " - Description\n", + " - Dimensions\n", + " - Size\n", + " - Status (\"Cached\" or \"Remote\")\n", + " - URL\n", + " \"\"\"\n", + " ds = earthkit.data.from_source(\"url\", url)\n", + "\n", + " # Detect file size & cache status\n", + " if getattr(ds, \"path\", None) and os.path.exists(ds.path):\n", + " size = format_size(os.path.getsize(ds.path))\n", + " status = \"Cached\"\n", + " else:\n", + " size = \"Unknown\"\n", + " status = \"Remote\"\n", + "\n", + " # Convert to xarray\n", + " xr_ds = ds.to_xarray()\n", + "\n", + " # Extract primary variable\n", + " variables = list(xr_ds.data_vars)\n", + " variable = f\"`{variables[0]}`\" if variables else \"Unknown\"\n", + "\n", + " # Scenario metadata\n", + " scenario = xr_ds.attrs.get(\"scenario\", \"Unknown\")\n", + "\n", + " # Dimension string, e.g. \"(time: 365, lat: 180, lon: 360)\"\n", + " dims_str = \"(\" + \", \".join(f\"{k}: {v}\" for k, v in xr_ds.dims.items()) + \")\"\n", + "\n", + " return {\n", + " \"Variable\": variable,\n", + " \"Scenario\": scenario,\n", + " \"Dimensions\": dims_str,\n", + " \"Size\": size,\n", + " \"Status\": status,\n", + " \"URL\": url,\n", + " }\n", + "\n", + "\n", + "def generate_dataset_table(urls: List[str]) -> str:\n", + " \"\"\"\n", + " Create a Markdown table summarizing metadata for a list of dataset URLs.\n", + "\n", + " Parameters\n", + " ----------\n", + " urls : list of str\n", + " List of dataset URLs.\n", + "\n", + " Returns\n", + " -------\n", + " str\n", + " A Markdown-formatted table of dataset metadata.\n", + " \"\"\"\n", + " header = (\n", + " \"| Variable | Scenario | Dimensions | Size | Status | URL |\\n\"\n", + " \"|----------|----------|------------|------|--------|-----|\\n\"\n", + " )\n", + "\n", + " rows = []\n", + " for url in urls:\n", + " info = extract_dataset_info(url)\n", + " rows.append(\n", + " f\"| {info['Variable']} | {info['Scenario']} | \"\n", + " f\"{info['Dimensions']} | {info['Size']} | {info['Status']} | \"\n", + " f\"[Download]({info['URL']}) |\"\n", + " )\n", + "\n", + " return header + \"\\n\".join(rows)\n", + "\n", + "\n", + "# Display Markdown report\n", + "display(\n", + " Markdown(\n", + " f\"\"\"\n", + "### Dataset Information\n", + "\n", + "The analysis uses the following climate datasets derived from CMIP6 projections\n", + "(ACCESS-CM2 model, DeepESD downscaling). These datasets are hosted in the ECMWF\n", + "repository and are automatically downloaded or cached by **earthkit-data**.\n", + "\n", + "{generate_dataset_table(DATASET_URLS)}\n", + "\n", + "> **Note**: Dimensions and sizes are extracted dynamically. The first run may\n", + "download the files.\n", + "\"\"\"\n", + " )\n", + ")\n" + ], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ], + "text/markdown": "\n### Dataset Information\n\nThe analysis uses the following climate datasets derived from CMIP6 projections\n(ACCESS-CM2 model, DeepESD downscaling). These datasets are hosted in the ECMWF\nrepository and are automatically downloaded or cached by **earthkit-data**.\n\n| Variable | Scenario | Dimensions | Size | Status | URL |\n|----------|----------|------------|------|--------|-----|\n| `tasmax` | historical | (time: 7305, lat: 48, lon: 84) | 67.3 MB | Cached | [Download](https://sites.ecmwf.int/repository/earthkit-climate/tasmax_gridded_day_CMIP6_ACCESS-CM2_r1i1p1f1_deepESD_day_historical.nc) |\n| `tasmax` | ssp585 | (time: 14610, lat: 48, lon: 84) | 126.9 MB | Cached | [Download](https://sites.ecmwf.int/repository/earthkit-climate/tasmax_gridded_day_CMIP6_ACCESS-CM2_r1i1p1f1_deepESD_day_ssp585.nc) |\n| `tasmin` | ssp585 | (time: 14610, lat: 48, lon: 84) | 132.1 MB | Cached | [Download](https://sites.ecmwf.int/repository/earthkit-climate/tasmin_gridded_day_CMIP6_ACCESS-CM2_r1i1p1f1_deepESD_day_ssp585.nc) |\n| `pr` | ssp585 | (time: 14610, lat: 48, lon: 84) | 111.5 MB | Cached | [Download](https://sites.ecmwf.int/repository/earthkit-climate/pr_gridded_day_CMIP6_ACCESS-CM2_r1i1p1f1_deepESD_day_ssp585.nc) |\n\n> **Note**: Dimensions and sizes are extracted dynamically. The first run may\ndownload the files.\n" + }, + "metadata": {}, + "output_type": "display_data", + "jetTransient": { + "display_id": null + } + } + ], + "execution_count": 3 + }, + { + "cell_type": "code", + "id": "47d74c7c204e37e", + "metadata": { + "ExecuteTime": { + "end_time": "2025-12-11T17:35:12.058087337Z", + "start_time": "2025-12-11T17:35:08.995389510Z" + } + }, + "source": [ + "import time\n", + "import earthkit.data\n", + "import xarray as xr\n", + "import pandas as pd\n", + "\n", + "from earthkit.climate.indicators.temperature import (\n", + " warm_spell_duration_index,\n", + " daily_temperature_range,\n", + " heating_degree_days,\n", + ")\n", + "from earthkit.climate.indicators.precipitation import (\n", + " maximum_consecutive_wet_days,\n", + " daily_precipitation_intensity,\n", + ")\n", + "from earthkit.climate.utils.percentile import percentile_doy" + ], + "outputs": [], + "execution_count": 4 + }, + { + "cell_type": "code", + "id": "1c298d73e3b8c1b9", + "metadata": { + "ExecuteTime": { + "end_time": "2025-12-11T17:35:12.095922736Z", + "start_time": "2025-12-11T17:35:12.075465775Z" + } + }, + "source": [ + "# Data URLs (Access-CM2)\n", + "URLS = {\n", + " \"tasmax_hist\": \"https://sites.ecmwf.int/repository/earthkit-climate/tasmax_gridded_day_CMIP6_ACCESS-CM2_r1i1p1f1_deepESD_day_historical.nc\",\n", + " \"pr_ssp\": \"https://sites.ecmwf.int/repository/earthkit-climate/pr_gridded_day_CMIP6_ACCESS-CM2_r1i1p1f1_deepESD_day_ssp585.nc\",\n", + " \"tasmin_ssp\": \"https://sites.ecmwf.int/repository/earthkit-climate/tasmin_gridded_day_CMIP6_ACCESS-CM2_r1i1p1f1_deepESD_day_ssp585.nc\",\n", + " \"tasmax_ssp\": \"https://sites.ecmwf.int/repository/earthkit-climate/tasmax_gridded_day_CMIP6_ACCESS-CM2_r1i1p1f1_deepESD_day_ssp585.nc\",\n", + "}" + ], + "outputs": [], + "execution_count": 5 + }, + { + "cell_type": "code", + "id": "b15b477e2834eeb6", + "metadata": { + "ExecuteTime": { + "end_time": "2025-12-11T17:35:13.776963639Z", + "start_time": "2025-12-11T17:35:12.100018881Z" + } + }, + "source": [ + "def load_data():\n", + " print(\"Loading datasets...\")\n", + " tasmax_hist = earthkit.data.from_source(\"url\", URLS[\"tasmax_hist\"]).to_xarray()\n", + " tasmax_ssp = earthkit.data.from_source(\"url\", URLS[\"tasmax_ssp\"]).to_xarray()\n", + " tasmin_ssp = earthkit.data.from_source(\"url\", URLS[\"tasmin_ssp\"]).to_xarray()\n", + " pr_ssp = earthkit.data.from_source(\"url\", URLS[\"pr_ssp\"]).to_xarray()\n", + " return tasmax_hist, tasmax_ssp, tasmin_ssp, pr_ssp\n", + "\n", + "tasmax_hist, tasmax_ssp, tasmin_ssp, pr_ssp = load_data()" + ], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading datasets...\n" + ] + } + ], + "execution_count": 6 + }, + { + "cell_type": "code", + "id": "8ad3c950a1553b3e", + "metadata": { + "ExecuteTime": { + "end_time": "2025-12-11T17:35:13.872576032Z", + "start_time": "2025-12-11T17:35:13.810554635Z" + } + }, + "source": [ + "# Create 'tas' for Heating Degree Days (Mean of Max and Min)\n", + "print(\"Computing proxy 'tas' for HDD...\")\n", + "tas_ssp = (tasmax_ssp[\"tasmax\"] + tasmin_ssp[\"tasmin\"]) / 2\n", + "tas_ssp.name = \"tas\"\n", + "tas_ssp_ds = tas_ssp.to_dataset()" + ], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Computing proxy 'tas' for HDD...\n" + ] + } + ], + "execution_count": 7 + }, + { + "cell_type": "code", + "id": "39501b21479a8265", + "metadata": { + "ExecuteTime": { + "end_time": "2025-12-11T17:35:13.893829550Z", + "start_time": "2025-12-11T17:35:13.875932760Z" + } + }, + "source": [ + "def profile_run(name, func, kwargs):\n", + " print(f\" Running {name}...\")\n", + " start = time.perf_counter()\n", + " res = func(**kwargs)\n", + " out = res.to_xarray()\n", + " if hasattr(out, \"compute\"):\n", + " out.compute()\n", + " elapsed = time.perf_counter() - start\n", + " print(f\" > Done in {elapsed:.4f}s\")\n", + " return elapsed" + ], + "outputs": [], + "execution_count": 8 + }, + { + "cell_type": "markdown", + "id": "acbe90a484de3306", + "metadata": {}, + "source": [ + "## 1. Lazy Execution (Baseline)\n", + "In this mode, we simply merge datasets and pass them to the indicators without any specific handling of chunks or pre-computation." + ] + }, + { + "cell_type": "code", + "id": "a3e5144d71920175", + "metadata": { + "ExecuteTime": { + "end_time": "2025-12-11T17:35:14.273558905Z", + "start_time": "2025-12-11T17:35:13.897784414Z" + } + }, + "source": [ + "results = []\n", + "\n", + "# WSDI (Lazy)\n", + "tasmax_per_lazy = percentile_doy(tasmax_hist[\"tasmax\"], per=90)\n", + "tasmax_per_lazy.name = \"tasmax_per\"\n", + "wsdi_ds_lazy = xr.merge([tasmax_ssp, tasmax_per_lazy])\n", + "\n", + "# CWD (Lazy)\n", + "cwd_ds_lazy = pr_ssp\n", + "\n", + "# DTR (Lazy)\n", + "dtr_ds_lazy = xr.merge([tasmax_ssp, tasmin_ssp])\n", + "\n", + "# HDD (Lazy)\n", + "hdd_ds_lazy = tas_ssp_ds\n", + "\n", + "# SDII (Lazy)\n", + "sdii_ds_lazy = pr_ssp" + ], + "outputs": [], + "execution_count": 9 + }, + { + "cell_type": "code", + "id": "4aca6c8dc0f0975d", + "metadata": { + "ExecuteTime": { + "end_time": "2025-12-11T17:35:57.182908226Z", + "start_time": "2025-12-11T17:35:14.276631488Z" + } + }, + "source": [ + "t_wsdi_lazy = profile_run(\"WSDI (Lazy)\", warm_spell_duration_index, {\"ds\": wsdi_ds_lazy})\n", + "t_cwd_lazy = profile_run(\"CWD (Lazy)\", maximum_consecutive_wet_days, {\"ds\": cwd_ds_lazy})\n", + "t_dtr_lazy = profile_run(\"DTR (Lazy)\", daily_temperature_range, {\"ds\": dtr_ds_lazy})\n", + "t_hdd_lazy = profile_run(\"HDD (Lazy)\", heating_degree_days, {\"ds\": hdd_ds_lazy})\n", + "t_sdii_lazy = profile_run(\"SDII (Lazy)\", daily_precipitation_intensity, {\"ds\": sdii_ds_lazy})\n", + "\n", + "results.append({\"Indicator\": \"WSDI\", \"Mode\": \"Lazy\", \"Time\": t_wsdi_lazy})\n", + "results.append({\"Indicator\": \"CWD\", \"Mode\": \"Lazy\", \"Time\": t_cwd_lazy})\n", + "results.append({\"Indicator\": \"DTR\", \"Mode\": \"Lazy\", \"Time\": t_dtr_lazy})\n", + "results.append({\"Indicator\": \"HDD\", \"Mode\": \"Lazy\", \"Time\": t_hdd_lazy})\n", + "results.append({\"Indicator\": \"SDII\", \"Mode\": \"Lazy\", \"Time\": t_sdii_lazy})" + ], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running WSDI (Lazy)...\n", + " > Done in 29.2237s\n", + " Running CWD (Lazy)...\n", + " > Done in 6.6821s\n", + " Running DTR (Lazy)...\n", + " > Done in 2.8461s\n", + " Running HDD (Lazy)...\n", + " > Done in 2.2843s\n", + " Running SDII (Lazy)...\n", + " > Done in 1.8180s\n" + ] + } + ], + "execution_count": 10 + }, + { + "cell_type": "markdown", + "id": "39c8c972a9f62426", + "metadata": {}, + "source": [ + "## 2. Optimized Execution\n", + "In this mode, we apply two key optimizations:\n", + "1. **Pre-computing Percentiles**: We force the computation of the percentile threshold before passing it to the indicator. This simplifies the dask graph significantly.\n", + "2. **Re-chunking**: We re-chunk the data along the time dimension (`time=-1`) to ensure optimal processing for time-series based indicators." + ] + }, + { + "cell_type": "code", + "id": "f515f3d9cd6338f8", + "metadata": { + "ExecuteTime": { + "end_time": "2025-12-11T17:35:59.666352087Z", + "start_time": "2025-12-11T17:35:57.208333405Z" + } + }, + "source": [ + "# WSDI (Optimized)\n", + "print(\" Pre-computing percentile for WSDI...\")\n", + "start_per = time.perf_counter()\n", + "tasmax_per_opt = percentile_doy(tasmax_hist[\"tasmax\"], per=90)\n", + "tasmax_per_opt.name = \"tasmax_per\"\n", + "tasmax_per_opt = tasmax_per_opt.compute()\n", + "print(f\" > Percentile computed in {time.perf_counter() - start_per:.4f}s\")\n", + "\n", + "tasmax_ssp_opt = tasmax_ssp.chunk({\"time\": -1})\n", + "wsdi_ds_opt = xr.merge([tasmax_ssp_opt, tasmax_per_opt])\n", + "\n", + "# CWD (Optimized)\n", + "cwd_ds_opt = pr_ssp.chunk({\"time\": -1})\n", + "\n", + "# DTR (Optimized)\n", + "tasmin_ssp_opt = tasmin_ssp.chunk({\"time\": -1})\n", + "dtr_ds_opt = xr.merge([tasmax_ssp_opt, tasmin_ssp_opt])\n", + "\n", + "# HDD (Optimized)\n", + "hdd_ds_opt = tas_ssp_ds.chunk({\"time\": -1})\n", + "\n", + "# SDII (Optimized)\n", + "sdii_ds_opt = pr_ssp.chunk({\"time\": -1})" + ], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Pre-computing percentile for WSDI...\n", + " > Percentile computed in 2.4377s\n" + ] + } + ], + "execution_count": 11 + }, + { + "cell_type": "code", + "id": "b94d03495270e0e9", + "metadata": { + "ExecuteTime": { + "end_time": "2025-12-11T17:36:16.253595242Z", + "start_time": "2025-12-11T17:35:59.704488516Z" + } + }, + "source": [ + "t_wsdi_opt = profile_run(\"WSDI (Optimized)\", warm_spell_duration_index, {\"ds\": wsdi_ds_opt})\n", + "t_cwd_opt = profile_run(\"CWD (Optimized)\", maximum_consecutive_wet_days, {\"ds\": cwd_ds_opt})\n", + "t_dtr_opt = profile_run(\"DTR (Optimized)\", daily_temperature_range, {\"ds\": dtr_ds_opt})\n", + "t_hdd_opt = profile_run(\"HDD (Optimized)\", heating_degree_days, {\"ds\": hdd_ds_opt})\n", + "t_sdii_opt = profile_run(\"SDII (Optimized)\", daily_precipitation_intensity, {\"ds\": sdii_ds_opt})\n", + "\n", + "results.append({\"Indicator\": \"WSDI\", \"Mode\": \"Optimized\", \"Time\": t_wsdi_opt})\n", + "results.append({\"Indicator\": \"CWD\", \"Mode\": \"Optimized\", \"Time\": t_cwd_opt})\n", + "results.append({\"Indicator\": \"DTR\", \"Mode\": \"Optimized\", \"Time\": t_dtr_opt})\n", + "results.append({\"Indicator\": \"HDD\", \"Mode\": \"Optimized\", \"Time\": t_hdd_opt})\n", + "results.append({\"Indicator\": \"SDII\", \"Mode\": \"Optimized\", \"Time\": t_sdii_opt})" + ], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Running WSDI (Optimized)...\n", + " > Done in 5.7216s\n", + " Running CWD (Optimized)...\n", + " > Done in 4.0565s\n", + " Running DTR (Optimized)...\n", + " > Done in 2.2120s\n", + " Running HDD (Optimized)...\n", + " > Done in 2.5596s\n", + " Running SDII (Optimized)...\n", + " > Done in 1.9346s\n" + ] + } + ], + "execution_count": 12 + }, + { + "cell_type": "markdown", + "id": "b563555fb0100d6d", + "metadata": {}, + "source": [ + "## 3. Summary of Results" + ] + }, + { + "cell_type": "code", + "id": "28459f4a38c7ce02", + "metadata": { + "ExecuteTime": { + "end_time": "2025-12-11T17:36:16.349760661Z", + "start_time": "2025-12-11T17:36:16.292768260Z" + } + }, + "source": [ + "df = pd.DataFrame(results)\n", + "pivot = df.pivot(index=\"Indicator\", columns=\"Mode\", values=\"Time\")\n", + "pivot[\"Speedup\"] = pivot[\"Lazy\"] / pivot[\"Optimized\"]\n", + "pivot" + ], + "outputs": [ + { + "data": { + "text/plain": [ + "Mode Lazy Optimized Speedup\n", + "Indicator \n", + "CWD 6.682069 4.056488 1.647255\n", + "DTR 2.846073 2.211951 1.286680\n", + "HDD 2.284253 2.559555 0.892442\n", + "SDII 1.817978 1.934581 0.939727\n", + "WSDI 29.223651 5.721642 5.107563" + ], + "text/html": [ + "
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" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "execution_count": 13 + } + ], + "metadata": { + "kernelspec": { + "display_name": "dev", + "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": "3.12.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/release-notes.rst b/docs/release-notes.rst new file mode 100644 index 0000000..84ad5bf --- /dev/null +++ b/docs/release-notes.rst @@ -0,0 +1,4 @@ +Release notes +============= + +See the `GitHub releases `_ page for the latest release notes. diff --git a/docs/requirements.txt b/docs/requirements.txt index 7b0577e..e333fa9 100644 --- a/docs/requirements.txt +++ b/docs/requirements.txt @@ -11,4 +11,3 @@ pandas tqdm xarray filelock -myst-parser diff --git a/docs/tutorials.rst b/docs/tutorials.rst new file mode 100644 index 0000000..fd0cba3 --- /dev/null +++ b/docs/tutorials.rst @@ -0,0 +1,8 @@ +Tutorials +========= + +.. toctree:: + :maxdepth: 1 + + notebooks/climate_indices_analysis.ipynb + notebooks/performance_analysis.ipynb diff --git a/docs/user-guide.rst b/docs/user-guide.rst new file mode 100644 index 0000000..b6cdb96 --- /dev/null +++ b/docs/user-guide.rst @@ -0,0 +1,12 @@ +User guide +========== + +Example usage: + +.. code-block:: python + + from earthkit.climate.indicators import precipitation, temperature + from earthkit.climate.utils import conversions + + # Example: compute a precipitation index + pr = precipitation.simple_daily_intensity(precip_data, freq="monthly") diff --git a/pixi.lock b/pixi.lock index 5debc27..79775c7 100644 --- a/pixi.lock +++ b/pixi.lock @@ -9,14 +9,36 @@ environments: linux-64: - conda: https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2 - 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"setuptools-scm>=8", "wheel", - "setuptools-scm>=8" ] [project] @@ -15,35 +15,60 @@ classifiers = [ "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.10", - "Topic :: Scientific/Engineering" + "Topic :: Scientific/Engineering", ] dependencies = [ + "earthkit-data>=0.17.0", "numpy>=1.22", "xarray>=2023.1", - "xclim>=0.50", + "xclim>=0.59.1", "xsdba>=0.5,<0.6", - "earthkit-data>=0.17.0" ] description = "Aggregation tools for meteorological and climate data." dynamic = ["version"] +keywords = ["climate", "meteorology", "geospatial", "analysis", "earthkit"] license = {file = "LICENSE"} name = "earthkit-climate" readme = "README.md" requires-python = ">=3.10,<3.13" [project.optional-dependencies] -dev = ["black", "ruff", "mypy", "pre-commit", "make", "ipython"] -docs = ["sphinx", "sphinx-rtd-theme", "sphinx-autoapi", "nbsphinx"] +dev = [ + "black", + "ruff", + "mypy", + "pre-commit", + "ipython", + "pytest", + "pytest-cov", + "pytest-mock", + "ipykernel", + ] +docs = [ + "nbsphinx", + "roman-numerals-py>=3.1.0,<4", + "sphinx", + "sphinx-autoapi", + "sphinx-rtd-theme", +] [tool.coverage.run] branch = true [tool.pixi.dependencies] -pixi-pycharm = ">=0.0.9,<0.0.10" pytest = "*" pytest-cov = "*" pytest-mock = ">=3.15.1,<4" python = "3.12.*" +ipykernel = ">=7.1.0,<8" +pre-commit = "*" + +[tool.pixi.feature.docs.dependencies] +pandoc = "*" +sphinx = "*" +sphinx-autoapi = ">=3.6.1,<4" +nbsphinx = ">=0.9.8,<0.10" +sphinx-rtd-theme = ">=3.0.2,<4" # ---- Pixi environments ---- [tool.pixi.environments] @@ -58,6 +83,20 @@ earthkit-plots = ">=0.5.0" channels = ["conda-forge"] platforms = ["win-64", "linux-64", "osx-64", "osx-arm64"] +[tool.pixi.tasks] +qa = "pre-commit run --all-files" +unit-tests = "python -m pytest -vv --cov=. --cov-report=html --doctest-glob='*.md' --doctest-glob='*.rst'" +type-check = "python -m mypy . --no-namespace-packages" +template-update = "pre-commit run --all-files cruft -c .pre-commit-config-cruft.yaml" +docker-build = "docker build -t earthkit-climate ." +docker-run = "docker run --rm -ti -v $(pwd):/srv earthkit-climate" + +[tool.pixi.feature.docs.tasks] +docs-build = "rm -rf docs/_api docs/_build && sphinx-build -M html docs docs/_build" + +[tool.pytest.ini_options] +addopts = "-vv --cov=. --cov-report=html --doctest-glob='*.md' --doctest-glob='*.rst'" + [tool.ruff] ignore = [ "D1", # pydocstyle: Missing Docstrings @@ -84,7 +123,6 @@ select = [ # ---- Namespace package configuration ---- [tool.setuptools.packages.find] -namespaces = true where = ["src"] [tool.setuptools_scm] diff --git a/src/earthkit/climate/api/__init__.py b/src/earthkit/climate/api/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/earthkit/climate/api/wrapper.py b/src/earthkit/climate/api/wrapper.py new file mode 100644 index 0000000..7301d64 --- /dev/null +++ b/src/earthkit/climate/api/wrapper.py @@ -0,0 +1,71 @@ +from functools import wraps +from typing import Any, Callable, Dict, Union + +import xarray as xr + +from earthkit.climate.utils import conversions, provenance, units + + +def wrap_xclim_indicator(xclim_fn: Callable) -> Callable: + """ + Wraps an xclim indicator to handle Earthkit inputs and unit alignment. + + Parameters + ---------- + xclim_fn : Callable + The xclim indicator function to be wrapped. + + Returns + ------- + Callable + The wrapped function which accepts Earthkit inputs. + """ + + @wraps(xclim_fn) + def wrapper( + earthkit_input: Union[conversions.EarthkitData, xr.Dataset], + *args, + **kwargs, + ) -> conversions.EarthkitData: + """ + Wrapper function that processes Earthkit inputs and calls the xclim indicator. + + Parameters + ---------- + earthkit_input : Union[conversions.EarthkitData, xr.Dataset] + The input data, either as an Earthkit object or an xarray Dataset. + *args + Variable length argument list passed to the xclim indicator. + **kwargs + Arbitrary keyword arguments passed to the xclim indicator. + + Returns + ------- + conversions.EarthkitData + The result of the indicator calculation wrapped as an Earthkit object. + """ + metadata: Dict[str, Any] = {} + + # --- STEP 1: Load & Standardize Main Data --- + # Convert Earthkit object to xarray Dataset + dataset, metadata = conversions.to_xarray_dataset(earthkit_input, metadata) + + # Standardize units for common variables to Kelvin + for var in ["tas", "tasmin", "tasmax"]: + if var in dataset: + dataset = units.ensure_units(dataset, var, "degC", strict=False) + if "pr" in dataset: + dataset = units.ensure_units(dataset, "pr", "mm/day", strict=False) + + # --- STEP 2: Execution --- + # We pass the single merged dataset (ds) and the variable name mappings + output_dataset: xr.Dataset = xclim_fn(ds=dataset, *args, **kwargs) + + # --- STEP 3: Provenance & Output --- + metadata = provenance.add_indicator_provenance( + metadata, xclim_fn, dataset, **kwargs + ) + + return conversions.to_earthkit_field(output_dataset, metadata) + + return wrapper diff --git a/src/earthkit/climate/indicators/precipitation.py b/src/earthkit/climate/indicators/precipitation.py index 1863e2f..e0174b1 100644 --- a/src/earthkit/climate/indicators/precipitation.py +++ b/src/earthkit/climate/indicators/precipitation.py @@ -1,134 +1,59 @@ """Precipitation-based climate indices.""" -from __future__ import annotations - from typing import Any import xarray import xclim.indicators.atmos import earthkit.climate.utils.conversions as conversions -import earthkit.climate.utils.provenance as provenance -import earthkit.climate.utils.units as units +from earthkit.climate.api.wrapper import wrap_xclim_indicator -def maximum_consecutive_wet_days( - earthkit_input: conversions.EarthkitData | xarray.Dataset, - *, - wet_day_threshold: float | str = 1.0, +def daily_precipitation_intensity( + ds: conversions.EarthkitData | xarray.Dataset, **kwargs: Any, ) -> conversions.EarthkitData: """ - Compute the maximum number of consecutive wet days (CWD). + Compute the Daily Precipitation Intensity (SDII) using the xclim indices module. Parameters ---------- - earthkit_input : conversions.EarthkitData | xarray.Dataset - Input precipitation data. Supported inputs include ``xarray.Dataset``, - ``xarray.DataArray`` and, if ``earthkit-data`` is installed, any object - exposing a ``to_xarray`` method (for example ``Field`` or ``FieldList``). - wet_day_threshold : float or str, default: 1.0 - Wet-day threshold forwarded to the xclim indicator. When a float is - provided it is assumed to be expressed in ``mm/day``. Strings are - forwarded unchanged (for example ``"1 mm/day"``). + ds : conversions.EarthkitData | xarray.Dataset + Daily precipitation flux. **kwargs : Any - Additional keyword arguments forwarded directly to - :func:`xclim.indicators.atmos.maximum_consecutive_wet_days`. + Additional keyword arguments forwarded to + :func:`xclim.indices.daily_pr_intensity`. Returns ------- - EarthkitData - Indicator results converted back to the closest possible Earthkit - representation (same type as the input when feasible). + conversions.EarthkitData + The computed Daily Precipitation Intensity as an Earthkit-compatible field. """ - metadata: conversions.MetadataDict = {} - dataset, metadata = conversions.to_xarray_dataset(earthkit_input, metadata) - - # Ensure correct units for precipitation - dataset = units.ensure_units(dataset, "pr", "mm/day", strict=False) - - kwargs.setdefault("thresh", _format_precipitation_threshold(wet_day_threshold)) - - # Call the xclim indicator - output_dataset: xarray.Dataset = xclim.indicators.atmos.maximum_consecutive_wet_days(ds=dataset, **kwargs) - - # Add provenance - metadata = provenance.add_indicator_provenance( - metadata, xclim.indicators.atmos.maximum_consecutive_wet_days, dataset, **kwargs - ) + # Create wrapper inside the function + wrapper = wrap_xclim_indicator(xclim.indicators.atmos.daily_pr_intensity) + return wrapper(ds, **kwargs) - return conversions.to_earthkit_field(output_dataset, metadata) - -def daily_precipitation_intensity( - earthkit_input: conversions.EarthkitData | xarray.Dataset, - *, - wet_day_threshold: float | str | None = None, - frequency: str | None = None, +def maximum_consecutive_wet_days( + ds: conversions.EarthkitData | xarray.Dataset, **kwargs: Any, ) -> conversions.EarthkitData: """ - Compute the Simple Daily Intensity Index (SDII). + Compute the Maximum Consecutive Wet Days (CWD) using the xclim indices module. Parameters ---------- - earthkit_input : conversions.EarthkitData | xarray.Dataset - Input precipitation data. Supported inputs include ``xarray.Dataset``, - ``xarray.DataArray`` and, if ``earthkit-data`` is installed, any object - exposing a ``to_xarray`` method (for example ``Field`` or ``FieldList``). - wet_day_threshold : float or str, optional - Wet-day threshold forwarded to the xclim indicator. Floats are assumed - to be expressed in ``mm/day`` while strings are forwarded unchanged. - frequency : str, optional - Resampling frequency forwarded to :func:`xclim.indicators.atmos.daily_pr_intensity`. + ds : conversions.EarthkitData | xarray.Dataset + Daily precipitation flux. **kwargs : Any - Additional keyword arguments forwarded directly to - :func:`xclim.indicators.atmos.daily_pr_intensity`. - - Returns - ------- - EarthkitData - Indicator results converted back to the closest possible Earthkit - representation (same type as the input when feasible). - """ - metadata: conversions.MetadataDict = {} - dataset, metadata = conversions.to_xarray_dataset(earthkit_input, metadata) - dataset.pr.attrs["units"] = "mm/day" - - # Ensure correct units for precipitation - dataset = units.ensure_units(dataset, "pr", "mm/day", strict=False) - - if wet_day_threshold is not None: - kwargs.setdefault("thresh", _format_precipitation_threshold(wet_day_threshold)) - if frequency is not None: - kwargs.setdefault("freq", frequency) - - # Call the xclim indicator - output_dataset: xarray.Dataset = xclim.indicators.atmos.daily_pr_intensity(ds=dataset, **kwargs) - - # Add provenance - metadata = provenance.add_indicator_provenance( - metadata, xclim.indicators.atmos.daily_pr_intensity, dataset, **kwargs - ) - - return conversions.to_earthkit_field(output_dataset, metadata) - - -def _format_precipitation_threshold(threshold: float | str) -> float | str: - """ - Format a precipitation threshold for use in xclim indicators. - - Parameters - ---------- - threshold : float or str - Wet-day threshold to format. + Additional keyword arguments forwarded to + :func:`xclim.indices.maximum_consecutive_wet_days`. Returns ------- - float or str - If a numeric value is provided, it is formatted as a string with units - in ``mm/day``. If a string is provided, it is returned unchanged. + conversions.EarthkitData + The computed Maximum Consecutive Wet Days as an Earthkit-compatible field. """ - if isinstance(threshold, (int, float)): - return f"{threshold} mm/day" - return threshold + # Create wrapper inside the function + wrapper = wrap_xclim_indicator(xclim.indicators.atmos.maximum_consecutive_wet_days) + return wrapper(ds, **kwargs) diff --git a/src/earthkit/climate/indicators/temperature.py b/src/earthkit/climate/indicators/temperature.py index 87be679..eded17d 100644 --- a/src/earthkit/climate/indicators/temperature.py +++ b/src/earthkit/climate/indicators/temperature.py @@ -1,21 +1,16 @@ """Temperature-based climate indices.""" -from __future__ import annotations - from typing import Any import xarray import xclim.indicators.atmos -from xclim.core.calendar import percentile_doy import earthkit.climate.utils.conversions as conversions -import earthkit.climate.utils.provenance as provenance -import earthkit.climate.utils.units as units +from earthkit.climate.api.wrapper import wrap_xclim_indicator def daily_temperature_range( - tasmax: conversions.EarthkitData | xarray.Dataset, - tasmin: conversions.EarthkitData | xarray.Dataset, + ds: conversions.EarthkitData | xarray.Dataset, **kwargs: Any, ) -> conversions.EarthkitData: """ @@ -23,10 +18,8 @@ def daily_temperature_range( Parameters ---------- - tasmax : conversions.EarthkitData | xarray.Dataset - Input data containing maximum daily temperature values. - tasmin : conversions.EarthkitData | xarray.Dataset - Input data containing minimum daily temperature values. + ds : conversions.EarthkitData | xarray.Dataset + Input data containing maximum and minimum daily temperature values. **kwargs : Any Additional keyword arguments forwarded to :func:`xclim.indices.daily_temperature_range`. @@ -37,98 +30,13 @@ def daily_temperature_range( The computed daily temperature range converted back to an Earthkit-compatible type. """ - # Convert both inputs to xarray objects - metadata: conversions.MetadataDict = {} - tasmax_ds, metadata = conversions.to_xarray_dataset(tasmax, metadata) - tasmin_ds, metadata = conversions.to_xarray_dataset(tasmin, metadata) - - # Ensure correct units for precipitation - tasmax_ds = units.ensure_units(tasmax_ds, "tasmax", "degC", strict=False) - tasmin_ds = units.ensure_units(tasmin_ds, "tasmin", "degC", strict=False) - - # Compute the DTR index - result = xclim.indicators.atmos.daily_temperature_range( - tasmax_ds["tasmax"], tasmin_ds["tasmin"], **kwargs - ) - output_dataset = result.to_dataset(name=result.name or "dtr") - - # Add provenance metadata - metadata = provenance.add_indicator_provenance( - metadata, xclim.indicators.atmos.daily_temperature_range, output_dataset, **kwargs - ) - - # Convert back to Earthkit format - return conversions.to_earthkit_field(output_dataset, metadata) - - -def warm_spell_duration_index( - tasmax: conversions.EarthkitData | xarray.Dataset, - tasmax_hist: conversions.EarthkitData | xarray.Dataset, - freq: str = "YS", - window: int = 6, - **kwargs: Any, -) -> conversions.EarthkitData: - """ - Compute the Warm Spell Duration Index (WSDI) using the xclim indices module. - The 90th percentile threshold is computed internally from the historical period. - - Parameters - ---------- - tasmax : conversions.EarthkitData | xarray.Dataset - Daily maximum temperature data for the target period. - tasmax_hist : conversions.EarthkitData | xarray.Dataset - Historical daily maximum temperature data used to compute the 90th percentile threshold. - freq : str, optional, default "YS" - Frequency of resampling (e.g. yearly). - window : int, optional, default 6 - Minimum number of consecutive days above the threshold. - **kwargs : Any - Additional arguments forwarded to :func:`xclim.indicators.atmos.warm_spell_duration_index`. - - Returns - ------- - conversions.EarthkitData - The computed WSDI index as an Earthkit-compatible field. - """ - metadata: conversions.MetadataDict = {} - tasmax_ds, metadata = conversions.to_xarray_dataset(tasmax, metadata) - hist_ds, _ = conversions.to_xarray_dataset(tasmax_hist, metadata) - - # Ensure correct units for precipitation - tasmax_ds = units.ensure_units(tasmax_ds, "tasmax", "degC", strict=False) - hist_ds = units.ensure_units(hist_ds, "tasmax", "degC", strict=False) - - # Get 90th percentile over time - tasmax_per = percentile_doy(hist_ds["tasmax"], per=90) - - # Compute WSDI with xclim - result = xclim.indicators.atmos.warm_spell_duration_index( - tasmax=tasmax_ds["tasmax"], - tasmax_per=tasmax_per, - freq=freq, - window=window, - **kwargs, - ) - - output_dataset = result.to_dataset(name=result.name or "wsdi") - - # Add provenance - metadata = provenance.add_indicator_provenance( - metadata, - xclim.indicators.atmos.warm_spell_duration_index, - output_dataset, - freq=freq, - window=window, - **kwargs, - ) - - return conversions.to_earthkit_field(output_dataset, metadata) + # Create wrapper inside the function + wrapper = wrap_xclim_indicator(xclim.indicators.atmos.daily_temperature_range) + return wrapper(ds, **kwargs) def heating_degree_days( - tasmax: conversions.EarthkitData | xarray.Dataset, - tasmin: conversions.EarthkitData | xarray.Dataset, - tas: conversions.EarthkitData | xarray.Dataset, + ds: conversions.EarthkitData | xarray.Dataset, **kwargs: Any, ) -> conversions.EarthkitData: """ @@ -140,17 +48,14 @@ def heating_degree_days( Parameters ---------- - tasmax : conversions.EarthkitData | xarray.Dataset - Daily maximum temperature data. - tasmin : conversions.EarthkitData | xarray.Dataset - Daily minimum temperature data. - tas : conversions.EarthkitData | xarray.Dataset - Daily mean temperature data. + ds : conversions.EarthkitData | xarray.Dataset + Daily maximum, minimum and mean temperature data. **kwargs : Any Additional keyword arguments forwarded to :func:`xclim.indicators.atmos.heating_degree_days_approximation`. Common arguments include: + - `thresh` : str, default "18.0 degC" Base temperature threshold for heating. - `freq` : str, default "YS" @@ -161,33 +66,33 @@ def heating_degree_days( conversions.EarthkitData The computed Heating Degree Days (HDD) converted back to an Earthkit-compatible type. """ - metadata: conversions.MetadataDict = {} - - # Convert inputs to xarray - tasmax_ds, metadata = conversions.to_xarray_dataset(tasmax, metadata) - tasmin_ds, _ = conversions.to_xarray_dataset(tasmin, metadata) - tas_ds, _ = conversions.to_xarray_dataset(tas, metadata) - - # Ensure correct units for precipitation - tasmax_ds = units.ensure_units(tasmax_ds, "tasmax", "degC", strict=False) - tasmin_ds = units.ensure_units(tasmin_ds, "tasmin", "degC", strict=False) - tas_ds = units.ensure_units(tas_ds, "tas", "degC", strict=False) - # Compute HDD index using approximation - result = xclim.indicators.atmos.heating_degree_days_approximation( - tasmax=tasmax_ds["tasmax"], - tasmin=tasmin_ds["tasmin"], - tas=tas_ds["tas"], - **kwargs, - ) - - output_dataset = result.to_dataset(name=result.name or "hdd") - - # Add provenance - metadata = provenance.add_indicator_provenance( - metadata, - xclim.indicators.atmos.heating_degree_days_approximation, - output_dataset, - **kwargs, - ) - - return conversions.to_earthkit_field(output_dataset, metadata) + # Create wrapper inside the function + wrapper = wrap_xclim_indicator(xclim.indicators.atmos.heating_degree_days) + return wrapper(ds, **kwargs) + + +def warm_spell_duration_index( + ds: conversions.EarthkitData | xarray.Dataset, + **kwargs: Any, +) -> conversions.EarthkitData: + """ + Compute the Warm Spell Duration Index (WSDI) using the xclim indices module. + The 90th percentile threshold must be pre-calculated and included in the input dataset `ds` + as a variable named `{variable}_per` (e.g., `tasmax_per`). + + Parameters + ---------- + ds : conversions.EarthkitData | xarray.Dataset + Daily maximum temperature data for the target period, including the pre-calculated percentile. + **kwargs : Any + Additional arguments forwarded to :func:`xclim.indicators.atmos.warm_spell_duration_index`. + + Returns + ------- + conversions.EarthkitData + The computed WSDI index as an Earthkit-compatible field. + """ + # Create wrapper inside the function + wrapper = wrap_xclim_indicator(xclim.indicators.atmos.warm_spell_duration_index) + + return wrapper(earthkit_input=ds, **kwargs) diff --git a/src/earthkit/climate/utils/conversions.py b/src/earthkit/climate/utils/conversions.py index 9bea3b1..ee3e834 100644 --- a/src/earthkit/climate/utils/conversions.py +++ b/src/earthkit/climate/utils/conversions.py @@ -6,18 +6,10 @@ import xarray -try: # optional during tests - from xclim.core.units import convert_units_to # type: ignore -except Exception: # pragma: no cover +import earthkit.data as ekd - def convert_units_to(*args, **kwargs): # type: ignore - raise RuntimeError("xclim is required for unit conversion. This import is optional during tests.") - -from earthkit.data import Field, FieldList -from earthkit.data.wrappers import get_wrapper - -EarthkitData = FieldList | Field +EarthkitData = ekd.FieldList | ekd.Field MetadataDict = Dict[str, Any] @@ -131,5 +123,5 @@ def to_earthkit_field( dataset.attrs.setdefault("earthkit_provenance", provenance) # --- Use Earthkit’s official wrapper system --- - ek_object = get_wrapper(dataset) + ek_object = ekd.from_object(dataset) return ek_object diff --git a/src/earthkit/climate/utils/percentile.py b/src/earthkit/climate/utils/percentile.py index 98ab55b..5d34c8e 100644 --- a/src/earthkit/climate/utils/percentile.py +++ b/src/earthkit/climate/utils/percentile.py @@ -1,6 +1,7 @@ import numpy as np import xarray as xr from xarray import DataArray +from xclim.core.calendar import percentile_doy from xsdba.nbutils import quantile @@ -112,3 +113,42 @@ def pandas_offset2time_component(aggregation: str) -> str: else: raise NotImplementedError(f"Unsupported aggregation: {aggregation}") return resolution + + +def calculate_percentile_doy( + reference_dataset: xr.Dataset, + variable: str, + percentile: float, + window: int = 5, +) -> xr.Dataset: + """ + Calculate the daily percentile (doy) for a given variable in a reference dataset. + Wraps xclim.core.calendar.percentile_doy. + + Parameters + ---------- + reference_dataset : xr.Dataset + The reference dataset containing the variable. + variable : str + The name of the variable to calculate the percentile for. + percentile : float + The percentile value (e.g., 90 for 90th percentile). + window : int, optional + The window size for the rolling percentile calculation, by default 5. + + Returns + ------- + xr.Dataset + A dataset containing the calculated percentile, renamed to '{variable}_per'. + """ + if variable not in reference_dataset: + raise ValueError(f"Variable '{variable}' not found in reference dataset.") + + # Calculate percentile + per = percentile_doy(reference_dataset[variable], window=window, per=percentile) + + # Rename variable + per_name = f"{variable}_per" + per = per.rename(per_name) + + return per.to_dataset() diff --git a/src/earthkit/climate/utils/units.py b/src/earthkit/climate/utils/units.py index 066f1f6..97c1a4d 100644 --- a/src/earthkit/climate/utils/units.py +++ b/src/earthkit/climate/utils/units.py @@ -2,12 +2,7 @@ import xarray -try: # optional dependency during tests - from xclim.core.units import convert_units_to # type: ignore -except Exception: # pragma: no cover - - def convert_units_to(*args, **kwargs): # type: ignore - raise RuntimeError("xclim is required for unit conversion. This import is optional during tests.") +from xclim.core.units import convert_units_to def ensure_units(ds: xarray.Dataset, var: str, expected_units: str, strict: bool = False) -> xarray.Dataset: diff --git a/tests/unit/conftest.py b/tests/unit/conftest.py index 6bd263e..b043d7b 100644 --- a/tests/unit/conftest.py +++ b/tests/unit/conftest.py @@ -62,7 +62,7 @@ def common_mocks(mocker: MockerFixture, dummy_precip_ds: xr.Dataset) -> dict: Returns ------- - dict[str, Any] + dict[str, Any]+ Dictionary with references to key mock objects for assertions. """ object_ek = object() diff --git a/tests/unit/indicators/test_precipitation.py b/tests/unit/indicators/test_precipitation.py index 68c695c..bdccb6e 100644 --- a/tests/unit/indicators/test_precipitation.py +++ b/tests/unit/indicators/test_precipitation.py @@ -1,121 +1,53 @@ -import xarray as xr from pytest_mock import MockerFixture -from earthkit.climate.indicators.precipitation import ( - daily_precipitation_intensity, - maximum_consecutive_wet_days, -) - - -def test_cwd_end_to_end_returns_earthkit_object( - mocker: MockerFixture, - dummy_precip_ds: xr.Dataset, - common_mocks: dict, -) -> None: - """ - End-to-end test for maximum_consecutive_wet_days ensuring orchestration works - and dependencies are called correctly. - """ - mock_to_xr = common_mocks["mock_to_xr"] - mock_add_prov = common_mocks["mock_add_prov"] - mock_to_ek = common_mocks["mock_to_ek"] - object_ek = common_mocks["object_ek"] - - dummy_out = xr.Dataset({"cwd": ("time", [5])}) - mock_xclim = mocker.patch( - "xclim.indicators.atmos.maximum_consecutive_wet_days", - return_value=dummy_out, - ) - - result = maximum_consecutive_wet_days(dummy_precip_ds, wet_day_threshold=2.0) - - assert result is object_ek - mock_to_xr.assert_called_once() - mock_xclim.assert_called_once() - mock_add_prov.assert_called_once() - mock_to_ek.assert_called_once_with(dummy_out, {"earthkit_internal": {}, "prov": True}) - - -def test_sdii_with_frequency_end_to_end( - mocker: MockerFixture, - dummy_precip_ds: xr.Dataset, - common_mocks: dict, -) -> None: - """ - Test daily_precipitation_intensity end-to-end behavior, verifying that - the frequency argument is forwarded correctly to xclim and metadata flows properly. - """ - mock_to_xr = common_mocks["mock_to_xr"] - mock_add_prov = common_mocks["mock_add_prov"] - mock_to_ek = common_mocks["mock_to_ek"] - object_ek = common_mocks["object_ek"] - - dummy_out = xr.Dataset({"sdii": ("time", [1.23])}) - mock_xclim = mocker.patch( - "xclim.indicators.atmos.daily_pr_intensity", - return_value=dummy_out, - ) - - res = daily_precipitation_intensity(dummy_precip_ds, frequency="MS") - - assert res is object_ek - mock_to_xr.assert_called_once() - assert mock_xclim.call_args.kwargs["freq"] == "MS" - assert mock_xclim.call_args.kwargs["ds"].attrs.get("ensured") is True - mock_add_prov.assert_called_once() - mock_to_ek.assert_called_once_with(dummy_out, {"earthkit_internal": {}, "prov": True}) - - -def test_threshold_numeric_formats_with_units( - mocker: MockerFixture, - dummy_precip_ds: xr.Dataset, - common_mocks: dict, -) -> None: - """Test that numeric thresholds are automatically formatted with units (mm/day).""" - mock_xclim = mocker.patch( - "xclim.indicators.atmos.maximum_consecutive_wet_days", - return_value=xr.Dataset(), - ) - - maximum_consecutive_wet_days(dummy_precip_ds, wet_day_threshold=3) - assert mock_xclim.call_args.kwargs["thresh"] == "3 mm/day" - - -def test_threshold_string_forwarded_unchanged( - mocker: MockerFixture, - dummy_precip_ds: xr.Dataset, - common_mocks: dict, -) -> None: - """Test that string thresholds (e.g., '1 mm/day') are passed unchanged to xclim.""" - mock_xclim = mocker.patch( - "xclim.indicators.atmos.maximum_consecutive_wet_days", - return_value=xr.Dataset(), - ) - - maximum_consecutive_wet_days(dummy_precip_ds, wet_day_threshold="1 mm/day") - assert mock_xclim.call_args.kwargs["thresh"] == "1 mm/day" - - -def test_ensure_units_non_strict_warns_and_overwrites( - mocker: MockerFixture, - dummy_precip_ds: xr.Dataset, - common_mocks: dict, -) -> None: - """Test that ensure_units is called with strict=False and overwrites units as expected.""" - - def _ensure_units_side_effect(ds, var, units, strict=False): - ds[var].attrs["units"] = units - return ds - - ensure_mock = mocker.patch( - "earthkit.climate.utils.units.ensure_units", - side_effect=_ensure_units_side_effect, - ) - mocker.patch("xclim.indicators.atmos.daily_pr_intensity", return_value=xr.Dataset()) - - daily_precipitation_intensity(dummy_precip_ds) - - args, kwargs = ensure_mock.call_args - assert args[1] == "pr" - assert args[2] == "mm/day" - assert kwargs.get("strict", False) is False +from earthkit.climate.indicators import precipitation + +import pytest + + +class MockEarthkitData: + """Mock object for Earthkit input.""" + + pass + + +def test_maximum_consecutive_wet_days(mocker: MockerFixture, common_mocks): + """Test maximum_consecutive_wet_days calls wrapper correctly.""" + mock_wrapper_factory = mocker.patch("earthkit.climate.indicators.precipitation.wrap_xclim_indicator") + mock_wrapped_fn = mocker.MagicMock() + mock_wrapper_factory.return_value = mock_wrapped_fn + + pr_in = MockEarthkitData() + precipitation.maximum_consecutive_wet_days(pr_in, thresh="2 mm/day", freq="MS") + + import xclim.indicators.atmos + + mock_wrapper_factory.assert_called_once_with(xclim.indicators.atmos.maximum_consecutive_wet_days) + + mock_wrapped_fn.assert_called_once() + call_args = mock_wrapped_fn.call_args + ds_arg = call_args[0][0] + assert ds_arg is pr_in + assert call_args.kwargs["thresh"] == "2 mm/day" + assert call_args.kwargs["freq"] == "MS" + + +def test_daily_precipitation_intensity(mocker: MockerFixture, common_mocks): + """Test daily_precipitation_intensity calls wrapper correctly.""" + mock_wrapper_factory = mocker.patch("earthkit.climate.indicators.precipitation.wrap_xclim_indicator") + mock_wrapped_fn = mocker.MagicMock() + mock_wrapper_factory.return_value = mock_wrapped_fn + + pr_in = MockEarthkitData() + precipitation.daily_precipitation_intensity(pr_in, thresh="2 mm/day", freq="MS") + + import xclim.indicators.atmos + + mock_wrapper_factory.assert_called_once_with(xclim.indicators.atmos.daily_pr_intensity) + + mock_wrapped_fn.assert_called_once() + call_args = mock_wrapped_fn.call_args + ds_arg = call_args[0][0] + assert ds_arg is pr_in + assert call_args.kwargs["thresh"] == "2 mm/day" + assert call_args.kwargs["freq"] == "MS" diff --git a/tests/unit/indicators/test_temperature.py b/tests/unit/indicators/test_temperature.py index 945d18a..308b3c1 100644 --- a/tests/unit/indicators/test_temperature.py +++ b/tests/unit/indicators/test_temperature.py @@ -1,103 +1,103 @@ -import xarray as xr from pytest_mock import MockerFixture -from earthkit.climate.indicators.temperature import ( - daily_temperature_range, - heating_degree_days, - warm_spell_duration_index, -) - - -def test_dtr_end_to_end_returns_earthkit_object( - mocker: MockerFixture, dummy_temp_ds: xr.Dataset, common_mocks: dict -) -> None: - """Ensure daily_temperature_range computes successfully and returns an Earthkit object.""" - mock_to_xr = common_mocks["mock_to_xr"] - mock_ensure = common_mocks["mock_ensure_units"] - mock_add_prov = common_mocks["mock_add_prov"] - mock_to_ek = common_mocks["mock_to_ek"] - object_ek = common_mocks["object_ek"] - - mock_to_xr.side_effect = [ - (dummy_temp_ds[["tasmax"]], {"earthkit_internal": {}}), - (dummy_temp_ds[["tasmin"]], {"earthkit_internal": {}}), - ] - - dtr_da = xr.DataArray([10.0], name="dtr") - mock_xclim = mocker.patch("xclim.indicators.atmos.daily_temperature_range", return_value=dtr_da) - - res = daily_temperature_range(dummy_temp_ds[["tasmax"]], dummy_temp_ds[["tasmin"]]) - - assert res is object_ek - assert mock_to_xr.call_count == 2 - assert mock_ensure.call_count == 2 - mock_xclim.assert_called_once() - mock_add_prov.assert_called_once() - mock_to_ek.assert_called_once_with(dtr_da.to_dataset(name="dtr"), {"earthkit_internal": {}, "prov": True}) - - -def test_wsdi_end_to_end_computes_correctly( - mocker: MockerFixture, dummy_temp_ds: xr.Dataset, common_mocks: dict -) -> None: - """Ensure warm_spell_duration_index orchestrates correctly and metadata flows as expected.""" - mock_to_xr = common_mocks["mock_to_xr"] - mock_ensure = common_mocks["mock_ensure_units"] - mock_add_prov = common_mocks["mock_add_prov"] - mock_to_ek = common_mocks["mock_to_ek"] - object_ek = common_mocks["object_ek"] - - mock_to_xr.side_effect = [ - (dummy_temp_ds[["tasmax"]], {"earthkit_internal": {}}), - (dummy_temp_ds[["tasmax"]], {"earthkit_internal": {}}), - ] - - mocker.patch("earthkit.climate.indicators.temperature.percentile_doy", return_value=xr.DataArray([25.0])) - - wsdi_da = xr.DataArray([5.0], name="wsdi") - mock_xclim = mocker.patch( - "xclim.indicators.atmos.warm_spell_duration_index", - return_value=wsdi_da, +from earthkit.climate.indicators import temperature + +import pytest + + +class MockEarthkitData: + """Mock object for Earthkit input.""" + + pass + + +def test_daily_temperature_range(mocker: MockerFixture, common_mocks): + """Test daily_temperature_range calls wrapper with merged dataset.""" + # Mock the wrapper creator and the wrapped function + mock_wrapper_factory = mocker.patch( + "earthkit.climate.indicators.temperature.wrap_xclim_indicator" ) + mock_wrapped_fn = mocker.MagicMock() + mock_wrapper_factory.return_value = mock_wrapped_fn - res = warm_spell_duration_index(dummy_temp_ds[["tasmax"]], dummy_temp_ds[["tasmax"]], freq="YS", window=6) + # Call function with single dataset + ds_in = MockEarthkitData() + temperature.daily_temperature_range(ds_in, arg="val") - assert res is object_ek - assert mock_to_xr.call_count == 2 - assert mock_ensure.call_count == 2 - mock_xclim.assert_called_once() - mock_add_prov.assert_called_once() - mock_to_ek.assert_called_once_with( - wsdi_da.to_dataset(name="wsdi"), {"earthkit_internal": {}, "prov": True} + # Verify wrapper created with correct xclim function + import xclim.indicators.atmos + + mock_wrapper_factory.assert_called_once_with( + xclim.indicators.atmos.daily_temperature_range ) + # Verify wrapped function called with the dataset + call_args = mock_wrapped_fn.call_args + assert call_args is not None + ds_arg = call_args[0][0] + # The wrapper receives the raw input, conversion happens inside the wrapper (which is mocked) + assert ds_arg is ds_in + assert call_args.kwargs["arg"] == "val" + -def test_hdd_end_to_end_returns_earthkit_object( - mocker: MockerFixture, dummy_temp_ds: xr.Dataset, common_mocks: dict -) -> None: - """Ensure heating_degree_days computes correctly and returns the proper Earthkit object.""" - mock_to_xr = common_mocks["mock_to_xr"] - mock_ensure = common_mocks["mock_ensure_units"] - mock_add_prov = common_mocks["mock_add_prov"] - mock_to_ek = common_mocks["mock_to_ek"] - object_ek = common_mocks["object_ek"] - - mock_to_xr.side_effect = [ - (dummy_temp_ds[["tasmax"]], {"earthkit_internal": {}}), - (dummy_temp_ds[["tasmin"]], {"earthkit_internal": {}}), - (dummy_temp_ds[["tas"]], {"earthkit_internal": {}}), - ] - - hdd_da = xr.DataArray([50.0], name="hdd") - mock_xclim = mocker.patch( - "xclim.indicators.atmos.heating_degree_days_approximation", - return_value=hdd_da, +def test_heating_degree_days(mocker: MockerFixture, common_mocks): + """Test heating_degree_days calls wrapper with merged dataset.""" + mock_wrapper_factory = mocker.patch( + "earthkit.climate.indicators.temperature.wrap_xclim_indicator" ) + mock_wrapped_fn = mocker.MagicMock() + mock_wrapper_factory.return_value = mock_wrapped_fn + + ds_in = MockEarthkitData() + + temperature.heating_degree_days(ds_in, thresh="18 degC") + + import xclim.indicators.atmos - res = heating_degree_days(dummy_temp_ds[["tasmax"]], dummy_temp_ds[["tasmin"]], dummy_temp_ds[["tas"]]) + mock_wrapper_factory.assert_called_once_with( + xclim.indicators.atmos.heating_degree_days + ) + + call_args = mock_wrapped_fn.call_args + ds_arg = call_args[0][0] + assert ds_arg is ds_in + assert call_args.kwargs["thresh"] == "18 degC" + + +def test_warm_spell_duration_index(mocker: MockerFixture, common_mocks): + """Test warm_spell_duration_index passes merged dataset (tasmax + tasmax_per).""" + # Mock wrapper factory + mock_wrapper_factory = mocker.patch( + "earthkit.climate.indicators.temperature.wrap_xclim_indicator" + ) + mock_wrapped_fn = mocker.MagicMock() + mock_wrapper_factory.return_value = mock_wrapped_fn + + # Create a dummy input that represents a merged dataset + ds_merged_in = MockEarthkitData() + + # Call with single merged input + temperature.warm_spell_duration_index(ds_merged_in, window=10) + + import xclim.indicators.atmos + + mock_wrapper_factory.assert_called_once_with( + xclim.indicators.atmos.warm_spell_duration_index + ) - assert res is object_ek - assert mock_to_xr.call_count == 3 - assert mock_ensure.call_count == 3 - mock_xclim.assert_called_once() - mock_add_prov.assert_called_once() - mock_to_ek.assert_called_once_with(hdd_da.to_dataset(name="hdd"), {"earthkit_internal": {}, "prov": True}) + # Verify call args + mock_wrapped_fn.assert_called_once() + call_kwargs = mock_wrapped_fn.call_args.kwargs + + # We assume the first positional arg is handled by the wrapper as 'earthkit_input' + # Check positional args first + if mock_wrapped_fn.call_args.args: + assert mock_wrapped_fn.call_args.args[0] is ds_merged_in + else: + # Fallback if passed as keyword (though wrapper signature might not support it yet, test logic verifies call) + # In this test we called it positionally. + pass + + assert call_kwargs["window"] == 10 + # Ensure reference_data is NOT passed + assert "reference_data" not in call_kwargs diff --git a/tests/unit/utils/test_units.py b/tests/unit/utils/test_units.py index 9ebfbb3..8c1e167 100644 --- a/tests/unit/utils/test_units.py +++ b/tests/unit/utils/test_units.py @@ -31,7 +31,7 @@ def test_ensure_units_strict_uses_xclim_convert_units_to(monkeypatch: Any) -> No ds["tas"].attrs["units"] = "K" # Mock convert_units_to to avoid requiring pint configuration - from earthkit.climate.utils import conversions as conv_mod + from earthkit.climate.utils import units as units_mod def fake_convert(var: xarray.DataArray, units: str) -> xarray.DataArray: # fake conversion K -> degC @@ -40,7 +40,7 @@ def fake_convert(var: xarray.DataArray, units: str) -> xarray.DataArray: data.attrs["units"] = units return data - monkeypatch.setattr(conv_mod, "convert_units_to", fake_convert) + monkeypatch.setattr(units_mod, "convert_units_to", fake_convert) with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") @@ -55,12 +55,12 @@ def test_ensure_units_strict_raises_on_conversion_error(monkeypatch: Any) -> Non ds = xarray.Dataset({"tas": ("time", [1.0, 2.0])}) ds["tas"].attrs["units"] = "unknown" - from earthkit.climate.utils import conversions as conv_mod + from earthkit.climate.utils import units as units_mod def failing_convert(*args: Any, **kwargs: Any) -> None: raise RuntimeError("no conversion") - monkeypatch.setattr(conv_mod, "convert_units_to", failing_convert) + monkeypatch.setattr(units_mod, "convert_units_to", failing_convert) with pytest.raises(ValueError) as exc: ensure_units(ds, "tas", "degC", strict=True) diff --git a/tests/unit/wrapper/test_wrap_xclim_indicator.py b/tests/unit/wrapper/test_wrap_xclim_indicator.py new file mode 100644 index 0000000..e08acb3 --- /dev/null +++ b/tests/unit/wrapper/test_wrap_xclim_indicator.py @@ -0,0 +1,74 @@ +import numpy as np +import pytest +import xarray as xr +from pytest_mock import MockerFixture + +from earthkit.climate.api.wrapper import wrap_xclim_indicator + + +class MockEarthkitData: + """Mock object for Earthkit input.""" + + pass + + +@pytest.fixture +def mock_xclim_indicator(mocker: MockerFixture): + """Creates a mock xclim indicator function.""" + mock_fn = mocker.MagicMock() + # Setup return value as an xarray Dataset + ds_out = xr.Dataset( + {"out_var": (("time", "lat", "lon"), np.random.rand(10, 10, 10))}, + coords={"time": np.arange(10), "lat": np.arange(10), "lon": np.arange(10)}, + ) + mock_fn.return_value = ds_out + mock_fn.__name__ = "mock_indicator" + return mock_fn + + +def test_wrapper_call(mock_xclim_indicator, common_mocks): + """Test that the wrapper calls the underlying xclim function.""" + wrapped_fn = wrap_xclim_indicator(mock_xclim_indicator) + input_data = MockEarthkitData() + + mock_to_xr = common_mocks["mock_to_xr"] + mock_ensure_units = common_mocks["mock_ensure_units"] + mock_add_prov = common_mocks["mock_add_prov"] + mock_to_ek = common_mocks["mock_to_ek"] + object_ek = common_mocks["object_ek"] + + result = wrapped_fn(input_data, arg1="value1") + + # Check conversions called + mock_to_xr.assert_called_once() + + # Check units called (dummy_precip_ds has 'pr', so ensure_units should be called) + mock_ensure_units.assert_called() + + # Check xclim function called + mock_xclim_indicator.assert_called_once() + + # Check provenance called + mock_add_prov.assert_called_once() + + # Check output conversion + mock_to_ek.assert_called_once() + assert result is object_ek + + +def test_wrapper_units_conversion(mock_xclim_indicator, common_mocks): + """Test that units are ensured for specific variables.""" + wrapped_fn = wrap_xclim_indicator(mock_xclim_indicator) + input_data = MockEarthkitData() + + mock_to_xr = common_mocks["mock_to_xr"] + mock_ensure_units = common_mocks["mock_ensure_units"] + + # Setup mock dataset with 'tas' and 'pr' + ds_in = xr.Dataset({"tas": (("x"), [1]), "pr": (("x"), [1])}) + mock_to_xr.return_value = (ds_in, {}) + + wrapped_fn(input_data) + + # Verify ensure_units called for both + assert mock_ensure_units.call_count >= 2