diff --git a/notebooks/Advanced_cloud/read-SWOT_L2_LR_SSH_Basic_verD.ipynb b/notebooks/Advanced_cloud/read-SWOT_L2_LR_SSH_Basic_verD.ipynb new file mode 100644 index 00000000..ff26de29 --- /dev/null +++ b/notebooks/Advanced_cloud/read-SWOT_L2_LR_SSH_Basic_verD.ipynb @@ -0,0 +1,10871 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "180973dc-a4fc-43aa-bbc5-d56ce3e9edba", + "metadata": {}, + "source": [ + "# Virtual dataset reader and plotter\n", + "### Example for NASA CMR Shortname: SWOT_L2_LR_SSH_Basic_D\n", + "\n", + "#### *Author: Ed Armstrong, PO.DAAC*\n", + "\n", + "*Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not constitute or imply its endorsement by the United States Government or the Jet Propulsion Laboratory, California Institute of Technology.*" + ] + }, + { + "cell_type": "markdown", + "id": "94ee7f47-1a63-43e1-aa35-1cb9edd98453", + "metadata": {}, + "source": [ + "### Necessary enviroment includes\n", + "##### earthaccess 0.16.0\n", + "##### fsspec 2025.9.0\n", + "##### kerchunk 0.2.7\n", + "##### numpy 2.3.3\n", + "##### xarray 2025.1.2\n", + "##### zarr 2.18.6" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dd12bb03-7260-4fa4-b8ac-55933ae37b1f", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "# install these versions as needed. Create a seperate environment for these dependencies and run it from there.\n", + "#!pip install earthaccess==0.16.0 xarray==2025.1.2 zarr==2.18.6 fsspec>=2025.2 numpy virtualizarr==1.3.2 \"numcodecs<0.16.0\" kerchunk==0.2.7" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "031b4227-5c42-4f0a-9e0a-84dab3514f79", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "if: Expression Syntax.\n", + "then: Command not found.\n", + "earthaccess 0.16.0\n", + "fsspec 2026.3.0\n", + "kerchunk 0.2.7\n", + "numpy 2.2.4\n", + "virtualizarr 1.3.2\n", + "xarray 2025.1.2\n", + "zarr 2.18.6\n", + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "pip list | grep -E -e '(^xarray|numpy|earthaccess|fsspec|zarr|kerchunk)'" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "fc0b1c0c-c8f9-412c-8038-4b674de896c9", + "metadata": {}, + "outputs": [], + "source": [ + "# Filesystem management \n", + "import fsspec\n", + "import earthaccess\n", + "\n", + "# Data handling\n", + "import xarray as xr\n", + "import zarr \n", + "\n", + "# Numpy\n", + "import numpy as np\n", + "\n", + "# Other mapping\n", + "import matplotlib.pyplot as plt\n", + "import cartopy.crs as ccrs" + ] + }, + { + "cell_type": "markdown", + "id": "6901e7c4-66ca-4dfb-bd8f-aaf2f0291764", + "metadata": {}, + "source": [ + "## 1. Earthdata Cloud authentication\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "20dbc070-d5f7-407e-b92e-4fda1b8a82ba", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Get Earthdata creds\n", + "earthaccess.login()" + ] + }, + { + "cell_type": "markdown", + "id": "20756ad2-4fdf-4f7a-8582-aa7d59ea35e5", + "metadata": {}, + "source": [ + "## 2. Perform CMR search request and Open VDS reference file" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "57c1c37f-5d58-4b75-ab6f-30c4f8846403", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "14\n", + "CPU times: user 13.9 ms, sys: 4.18 ms, total: 18.1 ms\n", + "Wall time: 1.05 s\n" + ] + } + ], + "source": [ + "%%time\n", + "# Do a simple CMR granule search. We need the results of the granule search to establish AWS credentials if reading the VDS \n", + "# in the cloud. Otherwise ignore\n", + "\n", + "lat_min, lat_max = -80, 20\n", + "lon_min, lon_max = 0, 120\n", + "\n", + "start_time = '2025-05-10T00:28:00'\n", + "end_time = '2025-05-10T23:28:00'\n", + "\n", + "short_name = 'SWOT_L2_LR_SSH_Basic_D'\n", + "granule_result = earthaccess.search_data(\n", + " short_name=short_name,\n", + " temporal=(start_time, end_time),\n", + " bounding_box=(lon_min, lat_min, lon_max, lat_max)\n", + ")\n", + "print(len(granule_result))" + ] + }, + { + "cell_type": "markdown", + "id": "33694329-e790-47c2-aa6b-cb286ba71a81", + "metadata": {}, + "source": [ + "### 2a. VDS wrapper function for access in cloud or out of cloud" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "15707ccc-fcb3-4bf9-94cb-71b11d468054", + "metadata": {}, + "outputs": [], + "source": [ + "# Open data using the reference file, using a small wrapper function around xarray's open_dataset. \n", + "# This will shorten code blocks in other sections. \n", + "def get_vds_mapper(vds_link, in_cloud_region=False):\n", + " \"\"\"\n", + " Produces a virtudal dataset mapper that can be passed to xarray. \n", + " \n", + " * vds_link: str, link to the mapper\n", + " * in_cloud_region: bool, True if in cloud in the same region as the data, \n", + " False otherwise.\n", + " \"\"\"\n", + "\n", + " if in_cloud_region:\n", + " #fs_data = earthaccess.get_s3_filesystem(daac=\"PODAAC\")\n", + " fs_data = earthaccess.get_s3_filesystem(results=granule_result)\n", + " remote_protocol = \"s3\"\n", + " else:\n", + " fs_data = earthaccess.get_fsspec_https_session()\n", + " # We set this header to identify usage of the VDS. This helps us support continued development. \n", + " fs_data.client_kwargs['headers']['User-Agent'] = \"virtual-dataset-consumer\"\n", + " remote_protocol = \"https\"\n", + " \n", + " storage_opts = {\"fo\": vds_link, \"remote_protocol\": remote_protocol, \"remote_options\": fs_data.storage_options}\n", + " fs_ref = fsspec.filesystem('reference', **storage_opts)\n", + " return fs_ref.get_mapper('')" + ] + }, + { + "cell_type": "markdown", + "id": "cbe50dd9-a8d3-4aaa-bb24-0f42c69326c6", + "metadata": {}, + "source": [ + "### 2b. Open VDS as xarray dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "41255174-1c42-4013-bf58-28d506b11e1e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 2.69 s, sys: 529 ms, total: 3.22 s\n", + "Wall time: 11 s\n" + ] + }, + { + "data": { + "text/html": [ + "
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<xarray.Dataset> Size: 3TB\n",
+       "Dimensions:                                (granule: 26175, num_lines: 9866,\n",
+       "                                            num_pixels: 69, num_sides: 2)\n",
+       "Coordinates:\n",
+       "    cycle                                  (granule) float64 209kB dask.array<chunksize=(26175,), meta=np.ndarray>\n",
+       "    filename                               (granule) object 209kB dask.array<chunksize=(26175,), meta=np.ndarray>\n",
+       "  * granule                                (granule) float64 209kB nan ... 2....\n",
+       "    latitude                               (granule, num_lines, num_pixels) float64 143GB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    longitude                              (granule, num_lines, num_pixels) float64 143GB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    orbit                                  (granule) datetime64[ns] 209kB dask.array<chunksize=(26175,), meta=np.ndarray>\n",
+       "    ppass                                  (granule) float64 209kB dask.array<chunksize=(26175,), meta=np.ndarray>\n",
+       "Dimensions without coordinates: num_lines, num_pixels, num_sides\n",
+       "Data variables: (12/24)\n",
+       "    ancillary_surface_classification_flag  (granule, num_lines, num_pixels) float32 71GB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    distance_to_coast                      (granule, num_lines, num_pixels) float64 143GB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    dynamic_ice_flag                       (granule, num_lines, num_pixels) float32 71GB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    geoid                                  (granule, num_lines, num_pixels) float64 143GB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    heading_to_coast                       (granule, num_lines, num_pixels) float64 143GB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    height_cor_xover                       (granule, num_lines, num_pixels) float64 143GB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    ...                                     ...\n",
+       "    ssha_karin                             (granule, num_lines, num_pixels) float64 143GB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    ssha_karin_2                           (granule, num_lines, num_pixels) float64 143GB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    ssha_karin_2_qual                      (granule, num_lines, num_pixels) float64 143GB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    ssha_karin_qual                        (granule, num_lines, num_pixels) float64 143GB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    time                                   (granule, num_lines) datetime64[ns] 2GB dask.array<chunksize=(1, 9866), meta=np.ndarray>\n",
+       "    time_tai                               (granule, num_lines) datetime64[ns] 2GB dask.array<chunksize=(1, 9866), meta=np.ndarray>\n",
+       "Attributes: (12/22)\n",
+       "    Conventions:                      CF-1.7\n",
+       "    title:                            Level 2 Low Rate Sea Surface Height Dat...\n",
+       "    institution:                      CNES\n",
+       "    source:                           Ka-band radar interferometer\n",
+       "    platform:                         SWOT\n",
+       "    reference_document:               D-56407_SWOT_Product_Description_L2_LR_SSH\n",
+       "    ...                               ...\n",
+       "    xref_param_l2_lr_precalssh_file:  SWOT_Param_L2_LR_PreCalSSH_20000101T000...\n",
+       "    xref_reforbittrack_files:         SWOT_RefOrbitTrack125mPass1_Nom_2000010...\n",
+       "    xref_geco_database_version:       v107\n",
+       "    ellipsoid_semi_major_axis:        6378137.0\n",
+       "    ellipsoid_flattening:             0.0033528106647474805\n",
+       "    references:                       V1.4.1
" + ], + "text/plain": [ + " Size: 3TB\n", + "Dimensions: (granule: 26175, num_lines: 9866,\n", + " num_pixels: 69, num_sides: 2)\n", + "Coordinates:\n", + " cycle (granule) float64 209kB dask.array\n", + " filename (granule) object 209kB dask.array\n", + " * granule (granule) float64 209kB nan ... 2....\n", + " latitude (granule, num_lines, num_pixels) float64 143GB dask.array\n", + " longitude (granule, num_lines, num_pixels) float64 143GB dask.array\n", + " orbit (granule) datetime64[ns] 209kB dask.array\n", + " ppass (granule) float64 209kB dask.array\n", + "Dimensions without coordinates: num_lines, num_pixels, num_sides\n", + "Data variables: (12/24)\n", + " ancillary_surface_classification_flag (granule, num_lines, num_pixels) float32 71GB dask.array\n", + " distance_to_coast (granule, num_lines, num_pixels) float64 143GB dask.array\n", + " dynamic_ice_flag (granule, num_lines, num_pixels) float32 71GB dask.array\n", + " geoid (granule, num_lines, num_pixels) float64 143GB dask.array\n", + " heading_to_coast (granule, num_lines, num_pixels) float64 143GB dask.array\n", + " height_cor_xover (granule, num_lines, num_pixels) float64 143GB dask.array\n", + " ... ...\n", + " ssha_karin (granule, num_lines, num_pixels) float64 143GB dask.array\n", + " ssha_karin_2 (granule, num_lines, num_pixels) float64 143GB dask.array\n", + " ssha_karin_2_qual (granule, num_lines, num_pixels) float64 143GB dask.array\n", + " ssha_karin_qual (granule, num_lines, num_pixels) float64 143GB dask.array\n", + " time (granule, num_lines) datetime64[ns] 2GB dask.array\n", + " time_tai (granule, num_lines) datetime64[ns] 2GB dask.array\n", + "Attributes: (12/22)\n", + " Conventions: CF-1.7\n", + " title: Level 2 Low Rate Sea Surface Height Dat...\n", + " institution: CNES\n", + " source: Ka-band radar interferometer\n", + " platform: SWOT\n", + " reference_document: D-56407_SWOT_Product_Description_L2_LR_SSH\n", + " ... ...\n", + " xref_param_l2_lr_precalssh_file: SWOT_Param_L2_LR_PreCalSSH_20000101T000...\n", + " xref_reforbittrack_files: SWOT_RefOrbitTrack125mPass1_Nom_2000010...\n", + " xref_geco_database_version: v107\n", + " ellipsoid_semi_major_axis: 6378137.0\n", + " ellipsoid_flattening: 0.0033528106647474805\n", + " references: V1.4.1" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "\n", + "# Path to VDSs, both HTTPS and S3 versions\n", + "vds_link= 'https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-public/virtual_collections/SWOT_L2_LR_SSH_Basic_D/SWOT_L2_LR_SSH_Basic_D_virtual_https.json'\n", + "#vds_link= 'https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-public/virtual_collections/SWOT_L2_LR_SSH_Basic_D/SWOT_L2_LR_SSH_Basic_D_virtual_s3.json'\n", + "\n", + "\n", + "# Lets open the JSON VDS as xarray dataset\n", + "vds_mapper = get_vds_mapper(vds_link, in_cloud_region=False)\n", + "\n", + "## No modification needed!\n", + "data_vds = xr.open_dataset(\n", + " vds_mapper, engine=\"zarr\", chunks={},\n", + " backend_kwargs={\"consolidated\": False}\n", + ")\n", + "data_vds\n", + "#print(data)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "db9fd4ed-14e3-4a51-bb22-4e8ac5f3b3fb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "SWOT_L2_LR_SSH_Basic_048_283_20260406T224034_20260406T233202_PID0_01.nc\n" + ] + } + ], + "source": [ + "print(data_vds.isel(granule=26174).filename.values)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "0e52ef97-15a3-4308-bc1d-250bc5957bd9", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/c4/bkn3x29559ggcdlgd9grtx4m0000gp/T/ipykernel_71055/869051093.py:2: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n", + " data_vds.dims[\"granule\"]\n" + ] + }, + { + "data": { + "text/plain": [ + "26175" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# number of orbits\n", + "data_vds.dims[\"granule\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "51c13000-ea53-472a-bc4c-5c44ac35a9ea", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "25531\n" + ] + } + ], + "source": [ + "# find the unique orbits.. user needs to track the non-unique ones\n", + "\n", + "n_orbits = np.unique(data_vds.orbit.values).size\n", + "print(n_orbits)" + ] + }, + { + "cell_type": "markdown", + "id": "ace148a9-4715-46ad-be8e-ebdcc27eb9a4", + "metadata": {}, + "source": [ + "## 3. Perform data discovery, masking and plots\n", + "### 3a. Use case 1: Parse granule metadata from CMR search request to find the start times of the orbits and use to subset into the VDS, mask and plot" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "f1a4bf72-3df1-47c6-97c8-c956f534b455", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "14\n" + ] + } + ], + "source": [ + "# Do a CMR granule search and find the orbits in a specific space/time window. SWOT is 0-360 in longitude.\n", + "# This bbox for Indian/Southern Ocean\n", + "lat_min, lat_max = -80, 20\n", + "lon_min, lon_max = 0, 120\n", + "\n", + "start_time = '2025-05-10T00:28:00'\n", + "end_time = '2025-05-10T23:28:00'\n", + "\n", + "short_name = 'SWOT_L2_LR_SSH_Basic_D'\n", + "#short_name = 'SCATSAT1_ESDR_L2_WIND_STRESS_V1.1'\n", + "\n", + "granule_result = earthaccess.search_data(\n", + " short_name=short_name,\n", + " temporal=(start_time, end_time),\n", + " bounding_box=(lon_min, lat_min, lon_max, lat_max)\n", + ")\n", + "print(len(granule_result))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "16e943a5-82ee-4009-a237-3853403a4071", + "metadata": {}, + "outputs": [], + "source": [ + "# Get granule start times from CMR granule search result. Will be used to subset into the VDS:\n", + "datetimes_str = [g['umm']['TemporalExtent']['RangeDateTime']['BeginningDateTime'][:-1] for g in granule_result] # -1 to remove \"Z\" at end.\n", + "datetimes_obj = [np.datetime64(dts) for dts in datetimes_str]\n", + "#print(datetimes_obj)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "a8d9ad5a-d76b-47ce-b397-243bdbdda63a", + "metadata": {}, + "outputs": [], + "source": [ + "# Subset into VDS ---- THIS DOES NOT WORK....the orbits represented by datetime_obj are not consecutive....re indexing does not work\n", + "#data_vds_subset = data_vds.sel(orbit = datetimes_obj)\n", + "#data_vds_subset\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "da215074-30a1-45af-8706-a45163fd2558", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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<xarray.Dataset> Size: 2GB\n",
+       "Dimensions:                                (granule: 14, num_lines: 9866,\n",
+       "                                            num_pixels: 69, num_sides: 2)\n",
+       "Coordinates:\n",
+       "    cycle                                  (granule) float64 112B 32.0 ... 32.0\n",
+       "    filename                               (granule) object 112B 'SWOT_L2_LR_...\n",
+       "  * granule                                (granule) float64 112B 1.657e+04 ....\n",
+       "    latitude                               (granule, num_lines, num_pixels) float64 76MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    longitude                              (granule, num_lines, num_pixels) float64 76MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    orbit                                  (granule) datetime64[ns] 112B 2025...\n",
+       "    ppass                                  (granule) float64 112B 340.0 ... 3...\n",
+       "Dimensions without coordinates: num_lines, num_pixels, num_sides\n",
+       "Data variables: (12/24)\n",
+       "    ancillary_surface_classification_flag  (granule, num_lines, num_pixels) float32 38MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    distance_to_coast                      (granule, num_lines, num_pixels) float64 76MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    dynamic_ice_flag                       (granule, num_lines, num_pixels) float32 38MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    geoid                                  (granule, num_lines, num_pixels) float64 76MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    heading_to_coast                       (granule, num_lines, num_pixels) float64 76MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    height_cor_xover                       (granule, num_lines, num_pixels) float64 76MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    ...                                     ...\n",
+       "    ssha_karin                             (granule, num_lines, num_pixels) float64 76MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    ssha_karin_2                           (granule, num_lines, num_pixels) float64 76MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    ssha_karin_2_qual                      (granule, num_lines, num_pixels) float64 76MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    ssha_karin_qual                        (granule, num_lines, num_pixels) float64 76MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    time                                   (granule, num_lines) datetime64[ns] 1MB dask.array<chunksize=(1, 9866), meta=np.ndarray>\n",
+       "    time_tai                               (granule, num_lines) datetime64[ns] 1MB dask.array<chunksize=(1, 9866), meta=np.ndarray>\n",
+       "Attributes: (12/22)\n",
+       "    Conventions:                      CF-1.7\n",
+       "    title:                            Level 2 Low Rate Sea Surface Height Dat...\n",
+       "    institution:                      CNES\n",
+       "    source:                           Ka-band radar interferometer\n",
+       "    platform:                         SWOT\n",
+       "    reference_document:               D-56407_SWOT_Product_Description_L2_LR_SSH\n",
+       "    ...                               ...\n",
+       "    xref_param_l2_lr_precalssh_file:  SWOT_Param_L2_LR_PreCalSSH_20000101T000...\n",
+       "    xref_reforbittrack_files:         SWOT_RefOrbitTrack125mPass1_Nom_2000010...\n",
+       "    xref_geco_database_version:       v107\n",
+       "    ellipsoid_semi_major_axis:        6378137.0\n",
+       "    ellipsoid_flattening:             0.0033528106647474805\n",
+       "    references:                       V1.4.1
" + ], + "text/plain": [ + " Size: 2GB\n", + "Dimensions: (granule: 14, num_lines: 9866,\n", + " num_pixels: 69, num_sides: 2)\n", + "Coordinates:\n", + " cycle (granule) float64 112B 32.0 ... 32.0\n", + " filename (granule) object 112B 'SWOT_L2_LR_...\n", + " * granule (granule) float64 112B 1.657e+04 ....\n", + " latitude (granule, num_lines, num_pixels) float64 76MB dask.array\n", + " longitude (granule, num_lines, num_pixels) float64 76MB dask.array\n", + " orbit (granule) datetime64[ns] 112B 2025...\n", + " ppass (granule) float64 112B 340.0 ... 3...\n", + "Dimensions without coordinates: num_lines, num_pixels, num_sides\n", + "Data variables: (12/24)\n", + " ancillary_surface_classification_flag (granule, num_lines, num_pixels) float32 38MB dask.array\n", + " distance_to_coast (granule, num_lines, num_pixels) float64 76MB dask.array\n", + " dynamic_ice_flag (granule, num_lines, num_pixels) float32 38MB dask.array\n", + " geoid (granule, num_lines, num_pixels) float64 76MB dask.array\n", + " heading_to_coast (granule, num_lines, num_pixels) float64 76MB dask.array\n", + " height_cor_xover (granule, num_lines, num_pixels) float64 76MB dask.array\n", + " ... ...\n", + " ssha_karin (granule, num_lines, num_pixels) float64 76MB dask.array\n", + " ssha_karin_2 (granule, num_lines, num_pixels) float64 76MB dask.array\n", + " ssha_karin_2_qual (granule, num_lines, num_pixels) float64 76MB dask.array\n", + " ssha_karin_qual (granule, num_lines, num_pixels) float64 76MB dask.array\n", + " time (granule, num_lines) datetime64[ns] 1MB dask.array\n", + " time_tai (granule, num_lines) datetime64[ns] 1MB dask.array\n", + "Attributes: (12/22)\n", + " Conventions: CF-1.7\n", + " title: Level 2 Low Rate Sea Surface Height Dat...\n", + " institution: CNES\n", + " source: Ka-band radar interferometer\n", + " platform: SWOT\n", + " reference_document: D-56407_SWOT_Product_Description_L2_LR_SSH\n", + " ... ...\n", + " xref_param_l2_lr_precalssh_file: SWOT_Param_L2_LR_PreCalSSH_20000101T000...\n", + " xref_reforbittrack_files: SWOT_RefOrbitTrack125mPass1_Nom_2000010...\n", + " xref_geco_database_version: v107\n", + " ellipsoid_semi_major_axis: 6378137.0\n", + " ellipsoid_flattening: 0.0033528106647474805\n", + " references: V1.4.1" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Mask (and subset)the entire VDS with the orbits found from the CMR space/time query and granule metadata parsing for start times\n", + "mask = data_vds.orbit.isin(datetimes_obj).compute()\n", + "data_vds_subset = data_vds.where(mask, drop=True)\n", + "data_vds_subset" + ] + }, + { + "cell_type": "markdown", + "id": "ee22fc3b-1f45-45e1-b95e-f352205de7c1", + "metadata": {}, + "source": [ + "#### Mask the SSH data for a valid range" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "9c76b7f8-d470-43c7-b838-79d81f89ef3b", + "metadata": {}, + "outputs": [], + "source": [ + "# Perform SSH variable maskings for the large numeric \"fill_values\" and other assignments\n", + "ssh = data_vds_subset.ssh_karin\n", + "ssh = ssh.where(ssh < 1000)\n", + "\n", + "lat = data_vds_subset.latitude\n", + "lon = data_vds_subset.longitude" + ] + }, + { + "cell_type": "markdown", + "id": "a77caf76-cb29-48a4-9497-2627412c8d6a", + "metadata": {}, + "source": [ + "#### Plot it" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "4277d8ac-3360-4312-9921-2fbbf6976166", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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", 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<xarray.Dataset> Size: 5GB\n",
+       "Dimensions:                                (granule: 45, num_lines: 9866,\n",
+       "                                            num_pixels: 69, num_sides: 2)\n",
+       "Coordinates:\n",
+       "    cycle                                  (granule) float64 360B 1.0 ... 47.0\n",
+       "    filename                               (granule) object 360B 'SWOT_L2_LR_...\n",
+       "  * granule                                (granule) float64 360B 154.0 ... 2...\n",
+       "    latitude                               (granule, num_lines, num_pixels) float64 245MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    longitude                              (granule, num_lines, num_pixels) float64 245MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    orbit                                  (granule) datetime64[ns] 360B 2023...\n",
+       "    ppass                                  (granule) float64 360B 289.0 ... 2...\n",
+       "Dimensions without coordinates: num_lines, num_pixels, num_sides\n",
+       "Data variables: (12/24)\n",
+       "    ancillary_surface_classification_flag  (granule, num_lines, num_pixels) float32 123MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    distance_to_coast                      (granule, num_lines, num_pixels) float64 245MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    dynamic_ice_flag                       (granule, num_lines, num_pixels) float32 123MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    geoid                                  (granule, num_lines, num_pixels) float64 245MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    heading_to_coast                       (granule, num_lines, num_pixels) float64 245MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    height_cor_xover                       (granule, num_lines, num_pixels) float64 245MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    ...                                     ...\n",
+       "    ssha_karin                             (granule, num_lines, num_pixels) float64 245MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    ssha_karin_2                           (granule, num_lines, num_pixels) float64 245MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    ssha_karin_2_qual                      (granule, num_lines, num_pixels) float64 245MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    ssha_karin_qual                        (granule, num_lines, num_pixels) float64 245MB dask.array<chunksize=(1, 9866, 69), meta=np.ndarray>\n",
+       "    time                                   (granule, num_lines) datetime64[ns] 4MB dask.array<chunksize=(1, 9866), meta=np.ndarray>\n",
+       "    time_tai                               (granule, num_lines) datetime64[ns] 4MB dask.array<chunksize=(1, 9866), meta=np.ndarray>\n",
+       "Attributes: (12/22)\n",
+       "    Conventions:                      CF-1.7\n",
+       "    title:                            Level 2 Low Rate Sea Surface Height Dat...\n",
+       "    institution:                      CNES\n",
+       "    source:                           Ka-band radar interferometer\n",
+       "    platform:                         SWOT\n",
+       "    reference_document:               D-56407_SWOT_Product_Description_L2_LR_SSH\n",
+       "    ...                               ...\n",
+       "    xref_param_l2_lr_precalssh_file:  SWOT_Param_L2_LR_PreCalSSH_20000101T000...\n",
+       "    xref_reforbittrack_files:         SWOT_RefOrbitTrack125mPass1_Nom_2000010...\n",
+       "    xref_geco_database_version:       v107\n",
+       "    ellipsoid_semi_major_axis:        6378137.0\n",
+       "    ellipsoid_flattening:             0.0033528106647474805\n",
+       "    references:                       V1.4.1
" + ], + "text/plain": [ + " Size: 5GB\n", + "Dimensions: (granule: 45, num_lines: 9866,\n", + " num_pixels: 69, num_sides: 2)\n", + "Coordinates:\n", + " cycle (granule) float64 360B 1.0 ... 47.0\n", + " filename (granule) object 360B 'SWOT_L2_LR_...\n", + " * granule (granule) float64 360B 154.0 ... 2...\n", + " latitude (granule, num_lines, num_pixels) float64 245MB dask.array\n", + " longitude (granule, num_lines, num_pixels) float64 245MB dask.array\n", + " orbit (granule) datetime64[ns] 360B 2023...\n", + " ppass (granule) float64 360B 289.0 ... 2...\n", + "Dimensions without coordinates: num_lines, num_pixels, num_sides\n", + "Data variables: (12/24)\n", + " ancillary_surface_classification_flag (granule, num_lines, num_pixels) float32 123MB dask.array\n", + " distance_to_coast (granule, num_lines, num_pixels) float64 245MB dask.array\n", + " dynamic_ice_flag (granule, num_lines, num_pixels) float32 123MB dask.array\n", + " geoid (granule, num_lines, num_pixels) float64 245MB dask.array\n", + " heading_to_coast (granule, num_lines, num_pixels) float64 245MB dask.array\n", + " height_cor_xover (granule, num_lines, num_pixels) float64 245MB dask.array\n", + " ... ...\n", + " ssha_karin (granule, num_lines, num_pixels) float64 245MB dask.array\n", + " ssha_karin_2 (granule, num_lines, num_pixels) float64 245MB dask.array\n", + " ssha_karin_2_qual (granule, num_lines, num_pixels) float64 245MB dask.array\n", + " ssha_karin_qual (granule, num_lines, num_pixels) float64 245MB dask.array\n", + " time (granule, num_lines) datetime64[ns] 4MB dask.array\n", + " time_tai (granule, num_lines) datetime64[ns] 4MB dask.array\n", + "Attributes: (12/22)\n", + " Conventions: CF-1.7\n", + " title: Level 2 Low Rate Sea Surface Height Dat...\n", + " institution: CNES\n", + " source: Ka-band radar interferometer\n", + " platform: SWOT\n", + " reference_document: D-56407_SWOT_Product_Description_L2_LR_SSH\n", + " ... ...\n", + " xref_param_l2_lr_precalssh_file: SWOT_Param_L2_LR_PreCalSSH_20000101T000...\n", + " xref_reforbittrack_files: SWOT_RefOrbitTrack125mPass1_Nom_2000010...\n", + " xref_geco_database_version: v107\n", + " ellipsoid_semi_major_axis: 6378137.0\n", + " ellipsoid_flattening: 0.0033528106647474805\n", + " references: V1.4.1" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "target_pass = 289\n", + "\n", + "ds = data_vds.where(data_vds.ppass.compute() == target_pass, drop=True)\n", + "ds" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "49ebb48d-063f-4fc5-b3d7-df055656ca4b", + "metadata": {}, + "outputs": [], + "source": [ + "lon_min, lon_max = 237.5, 238.8\n", + "lat_min, lat_max = 34.5, 35.5\n", + "mask = (\n", + " (ds.longitude >= lon_min) & (ds.longitude <= lon_max) &\n", + " (ds.latitude >= lat_min) & (ds.latitude <= lat_max)\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "2adc8eee-466b-4b90-acdf-e18bd013ea26", + "metadata": {}, + "outputs": [], + "source": [ + "ssh = ds.ssha_karin.where(ds.ssha_karin < 1000)\n", + "ssh_box = ssh.where(mask)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "d319be6a-4a08-4c25-bf98-4efb4477b8c6", + "metadata": {}, + "outputs": [], + "source": [ + "ssh_mean = ssh_box.mean(dim=(\"num_lines\", \"num_pixels\"), skipna=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "3b4d74f4-22e8-4085-8cd0-5ab96843bcf4", + "metadata": {}, + "outputs": [], + "source": [ + "ssh_mean = ssh_mean.assign_coords(time=ds.orbit)\n", + "ssh_mean = ssh_mean.swap_dims({\"granule\": \"time\"})\n", + "ssh_mean = ssh_mean.sortby(\"time\")" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "4d5c58dc-2c6a-4a53-a0b3-dd3404deb532", + "metadata": {}, + "outputs": [], + "source": [ + "ssh_ts = ssh_mean.groupby(\"time\").mean()" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "aa85cd1a-17ba-4ef4-bf63-a9af08770618", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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lFkRGRmLp0qX12sfExJinLwKAQqHAXXfdhf3795szvGQyGaRS49suvV6P4uJiBAYGomvXrhbj1lJ1nw8XLlxAaWkphg0b1qZjAsZxGzNmDD7//HMAxjEeMmRIg1MaDxw4gJMnT2Lq1KkoLi42Zw5pNBpce+21+O2338yZNnX7W1NTg+LiYnTq1AnBwcEN9vmBBx6ARCIx/3vYsGHQ6/XIyspqsv/33HMP1q9fj6uuugrbtm3DK6+8gmHDhqFz587mzEhTf3bt2oWnnnoKgHHa4L333ovo6GjMmjWr3tQ3APj666+xcePGej+XT1NtTG1tLVavXo3Jkyebr+2aa65BREREo9lSly9yMGzYMBQXF5tfe3766ScAwOzZsy3amRZNuDxzLiUlxWJRh0GDBpn7ERcXV2/7mTNnzNusfQ26nFQqNS98YHqNBYzTQocMGYLExMRGH0tERO0Xg1JERORWBgwYgLVr1+LChQvYvXs35syZg/LyckyYMAFHjhwxt6tbV0oIgT/++MNcNyY1NRUKhQLbt2+HVqvF3r17LabumYJNdT84NcTa4FVLDBo0CBs3bsSmTZvwxx9/oKioCJ9++qlF/aXHHnsMkZGR8PPzg0qlMn+Yq1sL6q233kJGRgY6duyIgQMHYu7cuRYfLBMTEzF79mx8+OGHCA8Px+jRo/Hee+81W0/qcr///jvuvfdejB49Gq+99prFPlOAZPDgwZg/fz5uvvlmPPHEE/j666+xbds2LF++3Nz25Zdfxr333ou33noLXbp0Qf/+/eHt7Y17770XABAYGNhoH0pLS5Gfn9/gj16vR3V1dYPbm9KlSxd89tlnKCoqwl9//WWeGvfAAw9g06ZNFm07depkETgxPR6AuVaSwWDAf/7zH3Tu3BkymQzh4eFQqVT466+/WnzP6/rhhx9wxRVXQC6XIzQ0FCqVCosXL27TMU2mTp2KjRs3Ijs7G99++22jU/dMwd3p06ebA6qmnw8//BA6nc7cn6qqKrz00kvo2LGjxX24ePFig32uGyABjMEywBiAa87o0aOxYcMGXLx4Eb/99hseeeQRZGVlYezYsVCr1eZ2SqUSb731FjIzM82ra3bt2hXvvvsuXnnllXrHHT58OEaOHFnvRy6XN9snwBh4LiwsxMCBA3Hq1CmcOnUKZ8+exdVXX43PP/+8wWmAzd2HrKwsSKVSdOrUyaJdVFQUgoOD6wXxLj+eKUjdsWPHBrfXvd/WvgY15K677kJVVRW++eYbAMDx48exd+9e3HnnnU0+joiI2i8GpYiIyC35+vpiwIABeP3117F48WLU1NRgzZo15v29e/dGUFAQtm3bhmPHjqGkpMScKSWVSjFo0CBs27bNXGuqblBKqVQiOjoaf/31V5N9+OuvvxAbG2vTYsjh4eEYOXIkrr32WgwePLheUfdJkyZh6dKlePDBB7F27Vr88ssvWL9+PQBYfJidNGkSzpw5g3feeQcxMTH417/+hR49euDnn382t/n3v/+Nv/76C8899xyqqqrw6KOPokePHs3W4TE5ePAgbrrpJqSmpuKrr76Ct7e3xf6vv/4aBQUFuOmmmyy2jxgxwhwUNPH19cWHH36I3Nxc/Pbbbzh+/Dg2bNiA0tLSBj9s1/XYY48hOjq6wZ9z587hjz/+aHC7Nby8vNCzZ0/MmTPH/EG6qdo/jXn99dcxe/ZsDB8+HCtWrMCGDRuwceNG9OjRo0W1iOr6/fffcdNNN0Eul+P999/HTz/9hI0bN2Lq1KlW10dqyk033QSZTIbp06dDp9Nh0qRJDbYz9f9f//pXgxlEGzduNAcVZ82ahddeew2TJk3Cl19+iV9++QUbN25EWFhYg/fBy8urwXO25Pr8/f0xbNgwvPvuu3jhhRdw4cIFi9+DuuLj43HPPfdg+/btCA4ObtVYN8d0zEmTJqFz587mn9WrVyMnJwf/93//V+8x1t6Hy4OjjWnseNacx9rXoIakpKSgX79+WLFiBQBgxYoV8PX1bfS5RURE7Z93802IiIhcW//+/QEAeXl55m1eXl644oorsH37dmzbtg0KhQI9e/Y07x8yZAhWr15tDnbUDUoBwNixY7F06VJs27at3j7AGBDIzMzEP/7xD3tcUoMuXLiAzZs3Y968eXjppZfM202ZKpeLjo7Gww8/jIcffhhqtRp9+/bFa6+9huuvv97cpmfPnujZsydeeOEFczbZkiVL8OqrrzbZl9OnT2PMmDGIiIjATz/91GAmU0FBAQDUy0oSQkCv16O2trbeYyIjI83ToPR6PbZu3YpBgwY1mSn19NNPN1okOSoqCkql0qLouGl7SzX0PAOMRaOFEBYBgRMnTgCAebW8r776CldffTU++ugji8devHjRoji8tUEFwBj0k8vl2LBhA2QymXl73Qy0tvDz88Mtt9yCFStW4Prrr7foZ13JyckAjNMWR44c2eQxv/rqK0yfPh3//ve/zdu0Wm2riuu3RmNjeLmQkBAkJyc3u6hCS2k0Gnz33XeYPHkyJkyYUG//o48+ipUrV+Lqq69u0XHj4+NhMBhw8uRJdO/e3by9oKAAFy9ebHDaZWu09DWoIXfddRdmz56NvLw8rFq1CjfeeKM584uIiDwPM6WIiMhtbNmypcEMCVM9lcuXFB86dCgKCwuxfPlyDBo0yFzTBzAGpY4fP47vvvsOYWFhFh/kAOCpp56Cn58f/vGPf9Rb6rykpAQPPvgg/P39zbVoHMGUxXD5PVi0aJHFv/V6fb1pNBEREYiJiTHXyCkrK6sXFOrZsyekUmmDdXTqys/Px3XXXQepVIoNGzZApVI12M40he2LL76w2P79999Do9GgT58+TZ5nwYIFyMvLM9fFaUxKSkqD06lMU6pCQkJaNNXq999/b3DZ+saeZ7m5ueYsKsB4bz/99FOkpaWZg19eXl71xm3NmjXIycmx2BYQEAAAVgVpvLy8IJFILIJ+mZmZ+Pbbb5t9rLWefPJJpKen48UXX2y0Tb9+/ZCcnIwFCxaYV+urq7Cw0KLPl9+Hd955p9nplC21efPmBrdfPoYHDx5EUVFRvXZZWVk4cuRIvbFuq2+++QYajQaPPPIIJkyYUO9n7Nix+Prrr5v9HbzcDTfcAKD+a8HChQsBADfeeKNN+m/ta1BTpkyZAolEgsceewxnzpzhqntERB6OmVJEROQ2Zs2ahcrKSowfPx7dunVDdXU1/vjjD6xevRoJCQmYMWOGRXtThtOOHTswd+5ci31XXHEFJBIJdu7ciXHjxtXLUOncuTM++eQT3HHHHejZsyfuvfdeJCYmmmvOFBUV4fPPPzdniTiCQqHA8OHD8dZbb6GmpgaxsbH45ZdfcPbsWYt25eXl6NChAyZMmIDevXsjMDAQmzZtwp49e8wZKr/++itmzpyJiRMnokuXLqitrcVnn30GLy8v3HbbbU32Y8yYMThz5gyefvppbNu2Ddu2bTPvi4yMxKhRowAA48aNQ48ePfDyyy8jKysLV1xxBU6dOoV3330X0dHR5npRgHEaz9dff43hw4eb+/vll1/ivvvua7Y/tvbmm29i7969uPXWW9GrVy8AxgLOn376KUJDQ/HPf/7Ton2XLl1w7733Ys+ePYiMjMSyZctQUFBgkbE0duxYvPzyy5gxYwaGDBmCQ4cOYeXKlUhKSrI4VnJyMoKDg7FkyRIEBQUhICAAgwYNarAI9I033oiFCxdizJgxmDp1KtRqNd577z106tSp2amn1urduzd69+7dZBupVIoPP/wQ119/PXr06IEZM2YgNjYWOTk52LJlCxQKBdatW2e+D5999hmUSiVSUlKwY8cObNq0CWFhYTbpr8nNN9+MxMREjBs3DsnJydBoNNi0aRPWrVuHAQMGYNy4cQCAjRs3Ij09HTfddBOuuOIKBAYG4syZM1i2bBl0Ol291422WrlyJcLCwsxTiS930003YenSpfjxxx9x6623Wn3c3r17Y/r06fjggw9w8eJFjBgxArt378Ynn3yCW265pcWZV42x9jWoKSqVCmPGjMGaNWsQHBxss4AZERG5Kecs+kdERNRyP//8s7jnnntEt27dRGBgoPD19RWdOnUSs2bNanAJd41GI7y9vQUA8csvv9Tb36tXLwFAvPnmm42e86+//hJTpkwR0dHRwsfHR0RFRYkpU6aIQ4cONdnXRx55RLT0z2x8fHyzS8qfP39ejB8/XgQHBwulUikmTpwocnNzBQCRnp4uhBBCp9OJp556SvTu3VsEBQWJgIAA0bt3b/H++++bj3PmzBlxzz33iOTkZCGXy0VoaKi4+uqrxaZNm5rtJ4BGf0aMGGHRtqSkRDz++OOiS5cuQiaTifDwcHH77bfXW/59165dYvjw4SIkJETI5XLRu3dvsWTJEmEwGKy7eTa0fft28cgjj4jU1FShVCqFj4+PiIuLE3fffbc4ffq0RVvTmG3YsEH06tVLyGQy0a1bN7FmzRqLdlqtVjzxxBMiOjpa+Pn5iSuvvFLs2LFDjBgxot49++6770RKSor5ubt8+XIhhBDTp08X8fHxFm0/+ugj0blzZ/N5ly9fLtLT0+s99+Lj48X06dObvXYA4pFHHmmyjen4hYWFFtv3798vbr31VhEWFiZkMpmIj48XkyZNEps3bza3uXDhgpgxY4YIDw8XgYGBYvTo0eLYsWP1+rd8+XIBQOzZs8fiHFu2bBEAxJYtW5rs4+effy5uv/12kZycLPz8/IRcLhcpKSni+eefF2VlZeZ2Z86cES+99JK44oorREREhPD29hYqlUrceOON4tdff7Xquk2a+/0tKCgQ3t7e4s4772y0TWVlpfD39xfjx49v8pym+3P27FnztpqaGjFv3jyRmJgofHx8RMeOHcWcOXOEVqu1qp8Njf3Zs2cFAPGvf/3LvM2a16DG+mjy5ZdfCgDigQceaPReEBGRZ5AIYYNKmEREREQeKCEhAampqfjhhx+c3RUit/Hdd9/hlltuwW+//YZhw4Y5uztERORErClFREREREQOs3TpUiQlJTW4iAQREXkW1pQiIiIiIiK7++KLL/DXX3/hxx9/xNtvv92i1SaJiKh9YlCKiIiIiIjsbsqUKQgMDMS9996Lhx9+2NndISIiF8CaUkRERERERERE5HCsKUVERERERERERA7HoBQRERERERERETkcg1JEREQeavfu3fD19UVWVpazu0JELqSmpgYdO3bE+++/7+yuEBFRO8egFBERURM+/vhjSCQSi5+IiAhcffXV+Pnnn+u1v7xtQEAAUlJS8Oqrr6KystIJV9C4559/HlOmTEF8fLx52+7du/Hwww+jX79+8PHxaXR1rHPnzmHevHkYOHAgQkJCEB4ejquuugqbNm2q13bz5s2455570KVLF/j7+yMpKQn33Xcf8vLyrOrn3Llz691XiUQCuVxubqNWqyGRSPDYY4/Ve/xjjz0GiUSC9PT0evvuuusu+Pj4tGpsHn/8cfTt2xehoaHw9/dH9+7dMXfuXFRUVDT5uNdeew0SiQSpqalWncea6weAzMxM876vv/660eMUFRVZf5F1rF69GtOmTUPnzp0hkUhw1VVXNdhuz549mDlzJnr06IGAgADExcVh0qRJOHHiRL221j7fGnPVVVc1eG/GjBljbvPll19CIpHgm2++qff43r17QyKRYMuWLfX2xcXFYciQIS3qDwDk5uZi2rRp6Nq1K4KCghAcHIyBAwfik08+QWOlXFevXo3BgwcjICAAwcHBGDJkCH799ddmz2XN9QN/v47J5XLk5OQ0eJy6z0cfHx/Mnj0br732GrRabQvvABERkfW4+h4REZEVXn75ZSQmJkIIgYKCAnz88ce44YYbsG7dOowdO9ai7ahRo3DXXXcBACoqKvD777/jxRdfxMGDB7FmzRpndL+eAwcOYNOmTfjjjz8stv/000/48MMP0atXLyQlJTUYSACA7777Dm+++SZuueUWTJ8+HbW1tfj0008xatQoLFu2DDNmzDC3feaZZ1BSUoKJEyeic+fOOHPmDN5991388MMPOHDgAKKioqzq8+LFixEYGGj+t5eXl/n/IyIi0LlzZ2zbtq3e47Zv3w5vb29s3769wX19+vSBv7+/VX2oa8+ePRg2bBhmzJgBuVyO/fv344033sCmTZvw22+/QSqt/93f+fPn8frrryMgIKDF52vq+i/38ssv49Zbb21xkKe58+/duxcDBgxAcXFxo+3efPNNbN++HRMnTkSvXr2Qn5+Pd999F3379sXOnTstgh/WPt+a0qFDB8yfP99iW0xMjPn/hw4dCgDYtm0bxo8fb95eVlaGjIwM83Pj6quvNu87d+4czp07h9tvv73F/SkqKsL58+cxYcIExMXFoaamBhs3bsTdd9+N48eP4/XXX7doP3fuXLz88suYMGEC7r77btTU1CAjI6PB4FFrrr8unU6HN954A++8806zx50xYwaeffZZrFq1Cvfcc49VfSEiImoxQURERI1avny5ACD27Nljsb2kpET4+PiIqVOnWmwHIB555JF6x5kwYYKQSqWiqqrKrv211qOPPiri4uKEwWCw2J6fny8qKyuFEEI88sgjorG3ChkZGaKwsNBim1arFd26dRMdOnSw2P5///d/Qq/X19sGQDz//PPN9jU9PV0AqHe+y82YMUN4eXmJ8vJy87aKigrh7e0tpk6dKgIDA0Vtba15X25urgAgHn/88Wb7YK0FCxYIAGLHjh0N7p88ebK45pprxIgRI0SPHj2sOqa113/27FkBQKSlpQkA4uuvv27VcRqTnZ1tHscePXqIESNGNNhu+/btQqfTWWw7ceKEkMlk4o477rDYbu3zrTHW3sfExEQxcOBAi23r168XEolETJkyRYwePdpi36pVqwQA8d1337WoP00ZO3asCAgIsHgO7tixQ0gkErFw4cJWHdPa6ze9jqWlpQmZTCZycnKsOs7YsWPFsGHDWtU3IiIia3D6HhERUSsEBwfDz88P3t7WJR1HRUVBIpHUa79mzRr069cPfn5+CA8Px7Rp0ywyJNLT0yGVSrF582aLxz3wwAPw9fXFwYMHzduys7Nx7Ngxq/rz7bff4pprrqmXSRMZGQk/P79mH9+jRw+Eh4dbbJPJZLjhhhtw/vx5lJeXm7cPHz68XtbQ8OHDERoaiqNHj1rVXwAQQqCsrKzRKVBDhw6FXq/Hzp07zdt27dqF2tpaPPnkk6ioqMCBAwfM+0yZU6ZMGltISEgAAFy8eLHevt9++w1fffUVFi1a1KpjN3f9Jrfffju6dOmCl19+udm2LdGxY8cGs78uN2TIEPj6+lps69y5M3r06FFvvK19vjWntra2yWmTQ4cOxf79+1FVVWXetn37dvTo0QPXX389du7cCYPBYLFPIpHgyiuvbHPfTBISElBZWYnq6mrztkWLFiEqKgqPPfYYhBDNTv1sTHPXb/Lcc89Br9fjjTfesOq4o0aNwrZt21BSUtKqfhERETWHQSkiIiIrlJaWoqioCIWFhTh8+DAeeughVFRUYNq0afXaarVaFBUVoaioCFlZWVi1ahU++eQTTJ061SIo9fHHH2PSpEnw8vLC/Pnzcf/992Pt2rUYOnSoOajxwgsvIC0tDffee6850LNhwwYsXboUL730Enr37m0+3l133YXu3bs3ey05OTnIzs5G375923hX6svPz4e/v3+z0+EqKipQUVFRL7DVlKSkJCiVSgQFBWHatGkoKCiw2F93mpbJ9u3b0aVLF/Tp0wcdOnSwmMJni6BUbW0tioqKkJubi19++QUvvPACgoKCMHDgQIt2er0es2bNwn333YeePXu26lzNXb+Jl5cXXnjhBRw8eLDBOkrOIC5Ne23JeFvrxIkTCAgIQFBQEKKiovDiiy+ipqbGos3QoUNRU1ODXbt2mbdt374dQ4YMwZAhQ1BaWoqMjAyLfd26dUNYWFir+1VVVYWioiJkZmbik08+wfLlyzF48GCLINzmzZsxYMAA/Pe//4VKpUJQUBCio6Px7rvv2vT6TRITE3HXXXdh6dKlyM3NbfbY/fr1gxCi3jRfIiIiW2FQioiIyAojR46ESqVCREQEUlNT8fHHH2PZsmUYNWpUvbYfffQRVCoVVCoVEhIScMcdd+Daa6/F0qVLzW1qamrwzDPPIDU1Fb/99hv++c9/Yv78+VizZg0yMzPxn//8B4Cx4PCnn36KvLw8zJ49GxcvXsS9996L/v3749lnn23VtZiyqRITE1v1+MacOnUKa9euxW233dZkvSPAmCFSXV2NyZMnN3vckJAQzJw5E//73//w1Vdf4b777sPq1asxbNgwlJWVmdt16dIFERER9YJSpmyXIUOGWOzbtm0bOnfujIiIiJZeqtmff/4JlUqF2NhYjB49GkIIfP/99wgNDbVot2TJEmRlZeGVV15p8Tmsvf66pk6dis6dO9s8W6q1Vq5ciZycHKvGuyWSk5Px/PPP4/PPP8enn36KQYMG4dVXX60XLL48YFlbW4tdu3bhyiuvRHJyMiIjI837ysvLcejQoTZn0L399ttQqVRITEzE3XffjSuuuAJffPGFef+FCxdQVFSE7du348UXX8Szzz6L1atXIy0tDbNmzcL//vc/m11/Xc8//zxqa2vx5ptvNnv8pKQkAMCRI0esuGIiIqJWcNa8QSIiIndgqsXy3nvviY0bN4qNGzeKFStWiDFjxghvb+96dXsAiJtvvtnc9rvvvhNz5swRcrlc3HrrreYaTn/88YcAIN5///165+zWrZvo16+fxbb58+cLAGLgwIFCJpOJw4cPt/qaVq9eLQCIbdu2NdmuJTV+NBqNSEtLEyEhIfXq1Vzu//7v/4S3t7eYNGmS1X2+3MqVKwUAMX/+fIvt48ePN9eO0uv1QqlUiqVLlwohhHj77bdFTEyMub/e3t5ixowZre6DEEKUlpaKjRs3im+//VY8/fTTom/fvmLdunUWbYqKikRoaKhYsGCBeVtLako1pKHrN9WU+te//iWEEOKTTz4RAMTatWuFEG2vKVVXUzWlLnf06FGhUCjE4MGDLeopXa41NaUacv/999er62UwGERYWJi5dtSff/4pAIiTJ08KIYzPG1N9uA0bNggA4pNPPmlTPzIzM8XGjRvFqlWrxNSpU8W1114rjh8/bt6fnZ0tAAgA4osvvjBv1+v1IiUlpV5tNms1dP2X18abMWOGkMvlIjc3VwjR+POxqqpKABBPPfVUq/pCRETUHGZKERERWWHgwIEYOXIkRo4ciTvuuAM//vgjUlJSMHPmTIsaMYBxNSxT25tuugmvv/46Xn31VaxduxY//PADACArKwsA0LVr13rn6tatm3m/yVNPPYXevXtj9+7dSE9PR0pKSpuvSdgog0av1+P222/HkSNH8NVXXzW68hdgzNIaP348UlNT8eGHH7b6nFOnTkVUVBQ2bdpksX3o0KHm2lEZGRkoLS21yJTKzc1FZmamudZUW7NhFAoFRo4ciZtvvhlvvvkmnnjiCdx8880Wtb5eeOEFhIaGYtasWW06V12NXX9dd9xxBzp16uTUbKn8/HzceOONUCqV+Oqrr5rNoLOFJ554AgAs7o1EIsGQIUPMtaO2b9+OiIgIdOrUCYDxuWGazmmrWmPx8fEYOXIkpkyZgpUrVyIpKQkjR44017UyTePz8fHBhAkTzI+TSqWYPHkyzp8/j+zs7Baft6Hrv9wLL7yA2traZmtLmZ43tlzFkYiIqC4GpYiIiFpBKpXi6quvRl5eHk6ePNls+2uvvRaAsdh1a5w5c8Z8nkOHDrXqGCamOjkXLlxo03FM7r//fvzwww/4+OOPcc011zTa7ty5c7juuuugVCrx008/ISgoqE3n7dixY70CzHWnaW3fvh2hoaHo1q0bACAtLQ3+/v7Ytm2beaqWLYucA8Ctt94KAOZpWidPnsQHH3yARx991BwQy8zMhFarRU1NDTIzM1tdRLqh66/LVFvqwIED+O6771p1jrYoLS3F9ddfj4sXL2L9+vVNBittqWPHjgDQ4HOjtLQUhw4dMteTMhkyZAiysrKQk5ODbdu2ISYmxjx1zVYmTJiAc+fOmV8DQkNDIZfLERYWVi9YZ5pS2prf0cauv66kpCRMmzYNH3zwAfLy8hptZzq/PWqBERERAQxKERERtVptbS0AWLXq1eVt4+PjAQDHjx+v1/b48ePm/QBgMBhw9913Q6FQ4LnnnsPnn3+OtWvXtrrfpiDN2bNnW30Mk6eeegrLly/Hf/7zH0yZMqXRdsXFxbjuuuug0+mwYcMGREdHt+m8QghkZmZCpVJZbO/bt6858LR9+3YMHjzYnOXh7e2NAQMGYPv27eZMmS5durSpH5fT6XQwGAwoLS0FYCwqbzAY8OijjyIxMdH8s2vXLpw4cQKJiYl4+eWXW3yexq7/ctOmTUOnTp0wb948h2ZLabVajBs3DidOnMAPP/xgk8w+a505cwYA6t2bywOWdVfW69evH2QyGbZu3WquNWVrpgwp03NDKpUiLS0NhYWF9bItTUXImxvfhjR2/ZczZUs1VVvK9BphzQIKRERErcGgFBERUSvU1NTgl19+ga+vr1Uf2NatWwcA5tXy+vfvj4iICCxZsgQ6nc7c7ueff8bRo0dx4403mrctXLgQf/zxBz744AO88sorGDJkCB566CEUFRVZnCM7O9tcxLwpsbGx6NixI/7880+rrrUx//rXv7BgwQI899xzeOyxxxptp9FocMMNNyAnJwc//fQTOnfu3Gjbhq6hsLCwXrvFixejsLAQY8aMsdju7e2NQYMGmQNPdbNhAGNGzG+//YadO3e2KfBw8eLFBlc4M01J7N+/PwAgNTUV33zzTb2fHj16IC4uDt988w3uvfde8+Pbev2Xq5st9f3337f4OltDr9dj8uTJ2LFjB9asWYPBgwfb5LjHjh2zmM5WVlZm8bsDGIN1r776KgBg9OjRFvv69+8PuVxuLrpe97khk8nQt29fvPfee9BoNG3KoGtovADjAggSicRi1cvJkydDr9fjk08+MW/TarVYuXIlUlJSLLLL2nr9l0tOTsa0adPwv//9D/n5+Q222bt3LyQSic3GkIiI6HLezTchIiKin3/+2RwsUKvVWLVqFU6ePIlnn30WCoXCou2JEyewYsUKAEBlZSV27tyJTz75BJ06dcKdd94JwFhH5s0338SMGTMwYsQITJkyBQUFBXj77beRkJCAxx9/HABw9OhRvPjii7j77rsxbtw4AMDHH3+MtLQ0PPzww/jyyy/N573rrrvwf//3f1ZlxNx888345ptvIISwqBeTlZWFzz77DADMQSvTh9z4+Hhz/7/55hs8/fTT6Ny5M7p3726+XpNRo0YhMjISgLG20e7du3HPPffg6NGjOHr0qLldYGAgbrnlliavIT4+HpMnT0bPnj0hl8uxbds2fPHFF0hLS8M//vGPetc2dOhQbNmyBQDqBZ6GDBmC+fPnm9tdbuvWrbj66quRnp6OuXPnNnr/tm7dikcffRQTJkxA586dUV1djd9//x1r165F//79zaufhYeHW1yfyaJFiwCg3j5bXP/l7rjjDrzyyis4cOBAq68XME49NU09KywshEajMT83hg8fjuHDhwMw1jT6/vvvMW7cOJSUlNR7btRdGc7a5xtgzNYZMWIEtm7dCgDYt28fpkyZgilTpqBTp06oqqrCN998g+3bt+OBBx6wCP4AgK+vLwYMGIDff/8dMpkM/fr1s9g/ZMgQ/Pvf/wbQ8HNj7ty5mDdvHrZs2YKrrrqq0fv02muvYfv27RgzZgzi4uJQUlKCr7/+Gnv27MGsWbPMdawA4B//+Ac+/PBDPPLIIzhx4gTi4uLw2WefISsryxzIttX1N+T555/HZ599huPHj6NHjx719m/cuBFXXnmlecovERGRzTmnvjoREZF7MK1aVfdHLpeLtLQ0sXjxYvNqeiaXt/Xy8hIdOnQQDzzwgCgoKKh3/NWrV4s+ffoImUwmQkNDxR133CHOnz8vhBCitrZWDBgwQHTo0EFcvHjR4nFvv/22ACBWr15t3jZixAirVy/bt2+fACB+//13i+1btmypdw2mn7qrrZlWcmvsZ8uWLea28fHxjbaLj4+3OH9D13DfffeJlJQUERQUJHx8fESnTp3EM888I8rKyhq8NtPqad7e3kKj0VjsKy4uFhKJRAAQu3btqvfYdevWCQBiyZIlTd6/U6dOibvuukskJSUJPz8/IZfLRY8ePUR6erqoqKho8rGm62xotbO2XP/lq+/VVfd5XHf1PWuvV4imxzw9Pb3eNTT2U5e1zzchRL1tZ86cERMnThQJCQlCLpcLf39/0a9fP7FkyZJ6v5cmc+bMEQDEkCFD6u1bu3atACCCgoIaXCXwiSeeEBKJRBw9erTJ+/TLL7+IsWPHipiYGOHj4yOCgoLElVdeKZYvX95gvwoKCsT06dNFaGiokMlkYtCgQWL9+vX12rXl+i9ffa+u6dOnCwD1no8XL14Uvr6+4sMPP2zyeomIiNpCIoSTlmMhIiIip7r22msRExNjzlQh4Omnn8bnn3+OU6dOQSaTObs7dudp19sWAwcORHx8PNasWePsrjjEokWL8NZbb+H06dPmlQKJiIhsjTWliIiIPNTrr7+O1atXIysry9ldcRlbtmzBiy++6DEBGk+73tYqKyvDwYMHW1WU3h3V1NRg4cKFeOGFFxiQIiIiu2KmFBERERERERERORwzpYiIiIiIiIiIyOEYlCIiIiIiIiIiIodjUIqIiIiIiIiIiBzO29kdaA8MBgNyc3MRFBQEiUTi7O4QERERERERETVLCIHy8nLExMRAKnV83hKDUjaQm5uLjh07OrsbREREREREREQtdu7cOXTo0MHh52VQygaCgoIAGAdRoVA4uTfuyWAwoLCwECqVyinRWXIsjrfn4Fh7Jo67Z+F4ewaOs2fiuHsWjrdnuHycy8rK0LFjR3Ncw9EYlLIB05Q9hULBoFQrGQwGaLVaKBQKvgB6AI635+BYeyaOu2fheHsGjrNn4rh7Fo63Z2hsnJ1ViojPNCIiIiIiIiIicjgGpYiIiIiIiIiIyOEYlCIiIiIiIiIiIodjUIqIiIiIiIiIiByOQSkiIiIiIiIiInI4BqWIiIiIiIiIiMjhGJQiIiIiIiIiIiKHY1CKiIiIiIiIiIgcztvZHSAiIiIiIiIi0hsEdp8tgbpci4ggOQYmhsJLKnF2t8iOGJQiIiIiIiIiIqdan5GHeeuOIK9Ua94WrZQjfVwKxqRGO7FnZE+cvkdERERERERETrM+Iw8PrdhnEZACgPxSLR5asQ/rM/Kc1DOyNwaliIiIiIiIiMgp9AaBeeuOQDSwz7Rt3roj0BsaakHujkEpIiIiIiIiInKK3WdL6mVI1SUA5JVqsftsieM6RQ7DoBQREREREREROYW6vPGAVGvakXthUIqIiIiIiIiInCIiSG7TduReGJQiIiIiIiIiIqcYmBiKaKUckkb2S2BchW9gYqgju0UOwqAUERERERERETmFl1SC9HEpDe4zBarSx6XAS9pY2IrcGYNSREREREREROQ0Y1KjMbF/h3rbo5RyLJ7WF2NSo53QK3IEb2d3gIiIiIiIiIg8lxACB85dxOiUSNx9ZSLeXH8M1bUGrJs1lBlS7RwzpYiIiIiIiIjIafZmXcCJggpMGxyPwclhGN45HEUVOgakPIDbBaXee+89JCQkQC6XY9CgQdi9e3ejbZcuXYphw4YhJCQEISEhGDlyZL32Qgi89NJLiI6Ohp+fH0aOHImTJ0/a+zKIiIiIiIiICMCqXdmIC/XHlcnhAIDkiECoy3Uo19Y4uWdkb24VlFq9ejVmz56N9PR07Nu3D71798bo0aOhVqsbbL9161ZMmTIFW7ZswY4dO9CxY0dcd911yMnJMbd566238N///hdLlizBrl27EBAQgNGjR0Or1TrqsoiIiIiIiIg80sXKavxwKA9TBsZBeikzKik8EABwplDjzK6RA7hVUGrhwoW4//77MWPGDKSkpGDJkiXw9/fHsmXLGmy/cuVKPPzww0hLS0O3bt3w4YcfwmAwYPPmzQCMWVKLFi3CCy+8gJtvvhm9evXCp59+itzcXHz77bcOvDIiIiJyZ3qDwI7TxfjuQA52nC6G3iCc3SUiIiK38PW+HAghLAqdJ6kCAABniiqc1S1yELcpdF5dXY29e/dizpw55m1SqRQjR47Ejh07rDpGZWUlampqEBoaCgA4e/Ys8vPzMXLkSHMbpVKJQYMGYceOHbj99tsbPI5Op4NOpzP/u6ysDABgMBhgMBhafG1kvHdCCN4/D8Hx9hwca8/kaeO+PiMfL/9wFPllf2dZRynkeGlsd4xJjXJizxzD08bbU3GcPRPH3bM4Y7yFEFi1KwvXpUQi1N/HfG4/HymiFDKcKqjg88/GLh9nZ99ftwlKFRUVQa/XIzIy0mJ7ZGQkjh07ZtUxnnnmGcTExJiDUPn5+eZjXH5M076GzJ8/H/Pmzau3vbCwkNP+WslgMKC0tBRCCEilbpXAR63A8fYcHGvP5EnjvuXUBcz54Uy97fllWjy8aj/mj03C1Z1CnNAzx/Gk8XYkvUHgQE4FijU1CAvwQVpsoFML/nKcPRPH3bM4Y7z3ny/H6UINHh8eU68sTwelL47mFDdaroda5/JxLi8vd2p/3CYo1VZvvPEGvvjiC2zduhVyubxNx5ozZw5mz55t/ndZWRk6duwIlUoFhULR1q56JIPBAIlEApVKxT94HoDj7Tk41p7JU8ZdbxB4e9nhRvdLAPz391xMuKJLu149yFPG25FcMfuO4+yZOO6exRnj/fOWXCSE+eP6vsmQSCz/VnaLKcTuzBJEREQ4pC+e4vJxbmt8pK3cJigVHh4OLy8vFBQUWGwvKChAVFTTf5wXLFiAN954A5s2bUKvXr3M202PKygoQHR0tMUx09LSGj2eTCaDTCart10qlfLFug0kEgnvoQfheHsOjrVn8oRx33W22CJocDkBIK9Uiz+zLmJwcpjjOuYEnjDejrI+Iw+PrNqPy6uSFZRp8ciq/Vg8rS/GpEY3+Fh74zh7Jo67Z3HkeJdoqrE+owBPju4CLy+vevs7RQTiy73nISBp11/uOEPdcXb277bbvLL4+vqiX79+5iLlAMxFywcPHtzo49566y288sorWL9+Pfr372+xLzExEVFRURbHLCsrw65du5o8JhEREZG63Lop+9a2I9IbBOatO1IvIAXAvG3euiMspE9E7cLXe88DACb069jg/iRVIKprDci5UOXIbpGDuU1QCgBmz56NpUuX4pNPPsHRo0fx0EMPQaPRYMaMGQCAu+66y6IQ+ptvvokXX3wRy5YtQ0JCAvLz85Gfn4+KCmMFf4lEgn/+85949dVX8f333+PQoUO46667EBMTg1tuucUZl0hERERuIiLIunR3a9sR7T5bgrzS5rPvdp8tcVyniIjsQAiBVbuzMSY1CqEBvg22SY4IBACcLuQKfO2Z20zfA4DJkyejsLAQL730EvLz85GWlob169ebC5VnZ2dbpJ4tXrwY1dXVmDBhgsVx0tPTMXfuXADA008/DY1GgwceeAAXL17E0KFDsX79eqfPqyQiIiLXNjAxFNFKOfJLtQ1mtkgARCnlGJgY6uiukZti9h0ReYodp4txtkiD+bf2bLRNtEIOuY8UpwsrcHU31pVqr9wqKAUAM2fOxMyZMxvct3XrVot/Z2ZmNns8iUSCl19+GS+//LINekdERESewksqQfq4FDy0Yh8kgEVgylT5In1cCutgkNWYfUdEnmLl7mwkqwIwqIkvbqRSCZLCA3G6UOPAnpGjudX0PSIiIiJXMiY1Goun9UWkwjJIEKWUO7UgNbknU/ZdY2FMCYBoZt8RkZsrqtDhl8P5mDoovt6Ke5dLUgXgDKfvtWsMShERERG1wZjUaKx50LhAigTA4OQwbHvmGgakqMVM2XcA6gWmmH1HRO3Fmj/PQyKR4La+sc22TVYxU6q9Y1CKiIiIqI3OX1oZqGcHJfR6waABtZop+y5Kyew7Imp/DAaBz3dnY2zPaAT7N1zgvK4kVQCKKnQorapxQO/IGRiUIiIiImqjrGINJBKgf3wo8stYhJraZkxqNDY/MQIAkBgeAAmAjY+PYECKiNze9tNFyC6pxNRBcVa1T1YZV+DjFL72i0EpIiIiojbKLK5EjNIPHUP9kF+mhRANrcdHZL0STTUAYGL/DhAAjheUO7dDREQ2sGpXNrpEBqJffIhV7ZNUAQCAM5zC124xKEVERETURtklGsSH+SNKIUd1rQEXKznNgNqmsFwHABjaKRw+XhIczi11co+IiNpGXa7FxiMFmDowrtkC5yb+vt6IUcpxmplS7RaDUkRERERtlFlUifiwAEReqgPEKXzUVupLQamYYD90jQpCRg6DUkTk3tb8eR7eXhKM79uhRY9LjghkplQ7xqAUERERURsIIZBdUmnOlAIYlKK2U5fr4C2VINTfF6kxShzKKXN2l4iIWs1c4LxXDJR+Pi16bFJ4ADOl2jEGpYiIiIjaoFhTjQpdLRLC/KEKkkEiAQpKGZSitiks0yI8UAapVILUWCVOFpRDW6N3dreIiFrlt5OFOH+hyuoC53UlRwQiq7gStXqDHXpGzsagFBEREVEbZBVXAgDiQgPg4yVFWICMmVLUZoUVOqiCZACA1Fglag0CJ1jsnIjc1Mpd2egWFYQ+HYNb/Nik8EBU6w04f6HK9h0jp2NQioiIiKgNsoqNdS7iw/wBAFFKGQoYlKI2UpfpEHEpKNUtKgheUgkOsa4UEbmh/FItfj2mxh2DrC9wXldyhHEFPk7ha58YlCIiIiJqg6ziSoQHyhAg8wYARCnkKCjTOblX5O7U5TpEKIxBKbmPFzpHBCKDdaWIyA2t3nMOvl5S3NwntlWPj1LI4e/rxWLn7RSDUkRERERtkFWsQcKlLCkAiFTIkc+aUtRG6nItVEFy879TY5VcgY+I3I7eILB6TzZuTouBQt6yAucmEokESSoWO2+vGJQiIiIiaoOskkrE1QlKGTOlGJSi1jMYBIoqqs01pQAgNUaB4/nlqK5loV8ich9bj6uRW6ptVYHzupLCA5kp1U4xKEVERETUBlnFlUgICzD/O1IpR7GmGrparpRGrVNSWQ29QZhrSgFAzw5KVOsNOKlmsXMich+rdmUjNVaBXh2C23ScZFUgM6XaKQaliIiIiFqpTFuDEk21ucg5YMyUAoyFqolaw/TcqRuU6h6tgEQCTuEjIreRe7EKW46rMXVgfJuPlaQKQLGmGhcrq23QM3IlDEoRERERtVJ2cSUAIL5OplSU0hiU4hQ+ai11ufG5E6H4u6aUv683klUsdk5E7uOLPefg5+OFm9Ji2nysZFUgAOA0p/C1OwxKEREREbVS1qWg1OWFzgEgn0EpaqXCcmOmVHigr8X2nrFKZOQyU4qIXF+t3mAscN4nFoGXVqdti8Rw45c/ZziFr91hUIqIiIiolTKLNVDIvRHs/3fwQCH3htxHyhX4qNXU5ToE+/tA5u1lsb1HjAJH88pQq2excyJybb8eU6OgTIepA9tW4NzEz9cLscF+zJRqhxiUIiIiImql7OJKJIQHWGyTSCRcgY/apLBcZ1FPyqRnrBLaGgM/lBGRy1u1Oxu9OyiRGqu02TGTVAHMlGqHGJQiIiIiaqXMYg3iQv3rbY9UyFHAQufUSupyLSKC5PW2p8QoALDYORG5tnMllfi/E4WYOsg2WVImXIGvfWJQioiIiKiVsksqkRAWUG97lFLOmlLUaoXlOqgayJQKkvsgMTwAhxiUIiIX9sWebAT6emNc77YXOK8rWRWA7JJK1HAKc7vCoBQRERFRK2hr9Mgr1SIurH6mFKfvUVuoG5m+BwCpsUocZrFzInJRNXoDvvzzPG7pEwt/37YXOK8rWRWIGr3AuZJKmx6XnItBKSIiIqJWML0pbihTKlIhR36pFkIIR3eL3JwQAuqyhjOlACA1RoHDuWUwGPjcIiLXs+lIAQrLdTafugcAyRGBAMC6eu0Mg1JERERErZBZbAxKxTeUKaWUQ1drQGlVjaO7RW6uQleLqho9IhT1a0oBxkypymo9zhTxQxkRuZ5Vu7PRNy4Y3aMVNj92RJAMAb5eLHbezjAoRURERNQKWcUayH2kDU6zirwUUGBdKWqpwnJjgXxVYGOZUsaVrDiFj4hcTVaxBr+fLMLUQfF2Ob5EIkFyBIudtzcMShERERG1QlZxJeJDAyCRSOrti1JeCkqVMihFLaO+FJSKUDQclFL6+6BjqB8OnWdQiohcy+e7z0Eh98bYXtF2O0dSeADOcPpeu8KgFBEREVErZBZrGpy6B8CcPcVi59RS5qBUIzWlAGO2VAYzpYjIhVTXGvDV3nO4tW8HyH287HaeZBUzpdobBqWIiIiIWiG7pLLRoJSPlxThgb7IL9U5uFfk7grLdfDz8UKgrPFVq1JjlTicw2LnROQ6fjmSj6KKatxhhwLndSWpAnGhsgYlmmq7nocch0EpIiIiD6M3COw4XYzvDuRgx+li6PnBtsVq9Aacv1CF+AZW3jOJVMhZU4paTF2uhSpI1uC0UJPUWCXKdbXI5rLoROQiVu3KxoCEEHSODLLreZIjjH93Wey8/Wj8KxgiIiJqd9Zn5GHeuiPIq1PrKFopR/q4FIxJtV8NiPYm92IV9AbRaKYUAEQp5FAzKEUtVFima3LqHgCkxhhXtcrILUVCeOOBUSIie9IbBHafLUFGTin+OF2Mf0/sZfdzJoQFQCIBzhRq0D8h1O7nI/tjUIqIiMhDrM/Iw0Mr9uHyvKj8Ui0eWrEPi6f1ZWDKSpnFxgyVhKYypZRyHDx30UE9ovZCXa5rtMi5SVigDDFKOTJyyjC2V4yDekZE9LeGvuT614bjCJB52/W9hNzHCx1C/FhXqh1xu+l77733HhISEiCXyzFo0CDs3r270baHDx/GbbfdhoSEBEgkEixatKhem7lz50IikVj8dOvWzY5XQERE5Hh6g8C8dUfqBaQAmLfNW3eEU/mslF2sgbdUguhLq+w1JEohZ6FzarHCch0ighp/Xpn0iFUiI4fFzonI8UxfcuVdtsJsQZkOD63Yh/UZeXY9f1J4IE5zBb52w62CUqtXr8bs2bORnp6Offv2oXfv3hg9ejTUanWD7SsrK5GUlIQ33ngDUVFRjR63R48eyMvLM/9s27bNXpdARETkFLvPltR781iXAJBXqsXusyWO65QbyyyuRMdQf3h7Nf5WKkohR1FFNaprDQ7sGbk7U02p5vSMNa7AJwQDyUTkOK7wJVeyKpA1pdoRtwpKLVy4EPfffz9mzJiBlJQULFmyBP7+/li2bFmD7QcMGIB//etfuP322yGTNf7H3dvbG1FRUeaf8PBwe10CERGRU6jLrcvYsbadp8sqbnzlPZPIS1lUvKdkrepaAy5U1lgVlEqNVeBiZQ1yLlY5oGdEREau8CVXkioA2SWVqNHzS5/2wG1qSlVXV2Pv3r2YM2eOeZtUKsXIkSOxY8eONh375MmTiImJgVwux+DBgzF//nzExTW+lKVOp4NO9/cSz2VlZQAAg8EAg4G/GK1hMBgghOD98xAcb8/BsXYdqkBfq9u1dbw8YdyzijUYnBTW5DVGXLrneRerENPEND935wnj7SgFZcYAkzW/hylRxhWu/jp30SHPL46zZ+K4exZrxtv0OtWcgrIquz1vksL9UWsQyCysQHJEoF3O0Z5dPs7O/v12m6BUUVER9Ho9IiMjLbZHRkbi2LFjrT7uoEGD8PHHH6Nr167Iy8vDvHnzMGzYMGRkZCAoqOHlLOfPn4958+bV215YWAitlt+GtobBYEBpqTEFXSp1qwQ+agWOt+fgWLuOeH+BiEAfqCtqGm0TGeiDeP/aRqfFW6u9j7tBCGQXazC2e3CT98qruhYAcOKcGh39Gr/v7q69j7cjncg31kjxrtFArW5+6kt4gA92n8pD3wj733eOs2fiuHsWa8bbp9a6oJRPbVWb3080RiEx/k3dfzoXQQi2yznas8vHuby83Kn9cZuglL1cf/315v/v1asXBg0ahPj4eHz55Ze49957G3zMnDlzMHv2bPO/y8rK0LFjR6hUKigUCrv3uT0yGAyQSCRQqVT8g+cBON6eg2PtWubeJPDIqv0AYFELQnLpv+k3pSI6KrLe41qqvY97XmkVdHqBlPhIRERENNpOJQTkPodQJfFtsp27a+/j7UgHiwoAAF3ioq2rK9UhGGcv6h3y/OI4eyaOu2exZryvC1chamM2Csq0DdaVkgCIUspxXZ8keEklDbRoO5UQCJQdQVG1V7v++2ovl4+zXO7cbG63CUqFh4fDy8sLBQUFFtsLCgqaLGLeUsHBwejSpQtOnTrVaBuZTNZgjSqpVMoX6zaQSCS8hx6E4+05ONau44ZeMVgsldRbwjlKKUf6uBSbLuHcnsf93AXjvUsMD2z2+iIVcqjLq9vlfairPY+3IxVWVMNLKoEqSA6pFR/mesYqsWp3tnkFaXvjOHsmjrtnaW68pVJg7k0peGjFvvqPvfTf9HEp8PH2smMvgWRVAM4UVfJ52Up1x9nZ99BtRtDX1xf9+vXD5s2bzdsMBgM2b96MwYMH2+w8FRUVOH36NKKjbffGnIiIyFWMSY3GtmeuQWiADwDglrQYbHvmGpsGpNq7rGINJBKgY6hfs20jFXLkN1EQlqgudbkO4YG+VgWkACA1VomiimoUlOmab0xEZCNjUqOxeFpfhF9WrzJKKcfiaX0d8p6CK/C1H26TKQUAs2fPxvTp09G/f38MHDgQixYtgkajwYwZMwAAd911F2JjYzF//nwAxuLoR44cMf9/Tk4ODhw4gMDAQHTq1AkA8OSTT2LcuHGIj49Hbm4u0tPT4eXlhSlTpjjnIomIiOxMAqCsyljvyNtLarf0+vYqq7gSMUo/yKz4FjhKIUdBGYNSZJ3Ccp1V0/ZMUmOVAIBDOaWIasfF9InI9YxJjUagzBvTPtqNF2/sjpQYJQYmhjrsPUWSKgCbj6khhHBIpijZj1sFpSZPnozCwkK89NJLyM/PR1paGtavX28ufp6dnW2Repabm4s+ffqY/71gwQIsWLAAI0aMwNatWwEA58+fx5QpU1BcXAyVSoWhQ4di586dUKlUDr02IiIiR7lQWY1ag4CPlwTqcmZYtFRWcSXiQv2tahullOOv8xft2yFqNwrLtYgIsj64FK2UIzTAFxk5pRiV0vZ6cERELXGxylhwfOKAjlDIfRx67mRVIEqralCiqUZYoPXBfHI9bhWUAoCZM2di5syZDe4zBZpMEhISIETTK5d88cUXtuoaERGRWyisMAaiukYFQc0snhbLKtGg56UMleZEKuTIL9Pym1yyirpch5Ro6xfNkUgkSI1V4nBuqR17RUTUsBJNNXy8JAiSOT6skBwRCAA4XahhUMrNuU1NKSIiIrIN9aX6M6kxShQyU6pFhBDIKqpEXGiAVe2jFHJoawzm6ZJETVGX6RDRgul7AJAao8ChHAaliMjxiiuqEeLv65QvXeLD/CGVgHWl2gEGpYiIiDyMacpejxgFijXVqNEbnNwj91GiqUa5rhYJYdZO3zMGGPKZkUbNMBgEiipaVlMKMNaVKijTQV3O5xgROVaJphqhAb7NN7QDmbcXOob64zSDUm6PQSkiIiIPU1iug0LujQ4hxsBKUQWzpayVVVIJAIizMigVqTDWB2JQippjqvWmakFNKQDmqaSHc8vs0S0iokaVVFYjLNA5QSkASAoPwJlCjdPOT7bBoBQREZGHUZdrEaGQmzMyuJy89bKKjW9+48Osm75nKlpdUMqgFDXNlMEYoWhZplSHED8o/XyQcZ5T+IjIsUoqqhEa4Lx6TsmqQGZKtQMMShEREXmYwnIdVIEycxYPi51bL6u4EuGBvgi0sqirr7cU4YG+zJSiZpmDUi2cvmcsdq5ABoudE5GDlWiqEeak6XsAkKQKxLkLVdDV6p3WB2o7BqWIiIg8jLpchwiFDGEBvvCSSswfhql5WcWVVmdJmUQEyRmUomaZFh0Ib8UqUqkxSmTkcPoeETlWscZY6NxZklUB0BsEsosrndYHajsGpYiIiDxMYblxhS+pVILwQF8GpVogq1iD+FDr6kmZRCnlnL5HzVKXa6H084Hcx6vFj+0Rq0TOxSpc0FTboWdERPUZDAIXKqsR6syaUqpAAMBp1pVyawxKEREReZjC8r9X+IoIkqOQq3ZZrTWZUpEKOQp4j6kZ6jJdi6fumZiKnXMKHxE5Srm2FnqDcOr0vfBAXyjk3qwr5eYYlCIiIvIgldW1qNDVmgtwRwTJWOjcSuXaGhRrqpEQ3sJMKYUc+aW8x9S0wkvTalsjPtQfgTJvHMphUIqIHKNYY/y7FurEoJREIkESi527PQaliIiIPIi6zLKYcoRCDjWzeKySdalmRVyLp+/JUKzRoUZvsEe3qJ0wLUDQGlKpBCkxChxmXSkicpCSS9OFnZkpBRhX4DvD6XtujUEpIiIiD1JYYQxK/T19T2YOVFHTskuMQamEVkzfEwKs3UVNUpdrEXFpRczW6Bmr5PQ9InKY4ktBqRAnB6WSVAE4XVgBIYRT+0Gtx6AUERGRB/k7U+rS9D2FDEUVOugNfDPXnMxiDYLk3gj292nR46KUxnudz2Ln1AR1eetrSgFAaqwCWcWVKK2qsWGviIgaVqKphkQCp66+Bxgzpcq1tSiq4EIP7opBKSIiIg9SWK6Fr7cUCj9vAMbglEH8XRuCGpddXImEsABIJJIWPS7qUvZLQRmDUtSwCl0tKqv15gzG1kiNMRY7P8xsKSJygBJNNYL9fOAlbdnfRFtLVhmzl1lXyn0xKEVERORB1Jfq1pgCK6bMDE7ha15msQZxYS2rJwUASj8fyLylzJSiRhWWW06rbY0kVSD8fLxYV4qIHKJEU+3UIucmcWH+8JJKWFfKjTEoRURE5EHUl63wZfp/FjtvnjFTquVBKYlEgiilnJlS1Cj1peeGaVpta3hdKnbOFfiIyBFKNNUIC2h9IN1WZN5e6Bjix0wpN8agFBERkQe5fIWv8EAZJBJmSjVHW6NHXpkW8aEtK3JuEhkkRz6DUtQIUxH8ugHj1kiNUbDYORE5RLGmGiEBLauxaC/GFfgYlHJXDEoRERF5kMszpXy8pAgL8OXKcM04f6ESQgDxrciUAoBIpZzT96hR6nId5D5SBMm823Sc1FglzhZpUKGrtVHPiIgaVqLRIdQFMqUA0wp8nL7nrtoUlNLp+AaWiIjInRSWa+tNEVIFyTl9rxmZRZUAgPiw1mVKRSlkDPxRowrLdVAFyVpcRP9yqbFKCAEcyWVdKSKyrwuaGoS5QE0pwJgpdf5CJbQ1emd3hVqhRUGpn3/+GdOnT0dSUhJ8fHzg7+8PhUKBESNG4LXXXkNubq69+klERERtVKs3oFhTXa+YckSQjNP3mpFVUgm5j9RcGL6lIhXGTCkhhI17Ru2BuoFgcWt0jgiEzFuKDNaVIiI7K9boXKLQOQAkRwTCIICs4kpnd4Vawaqg1DfffIMuXbrgnnvugbe3N5555hmsXbsWGzZswIcffogRI0Zg06ZNSEpKwoMPPojCwkJ795uIiIhaqFhTDSFQL7ASEcQsnuZkFWsQF+oPaSuXvo5SylFVo0eZltOqqL7Ccl2rA551eXtJ0S2adaWIyL4qq2uhrTEgLNA1glJJ4cYsZtaVck9WTVx/66238J///AfXX389pNL6caxJkyYBAHJycvDOO+9gxYoVePzxx23bUyIiImoT07Lzl2dkRChk2H6qyBldchtZxZWtnroHAFEK4z0vKNNC6ecahWHJdRSW68wfqtoqNUaBPZklNjkWEVFDiiuqAQAh/q4RlAoN8EWwvw9X4HNTVgWlduzYYdXBYmNj8cYbb7SpQ0RERGQfprpRl0/fi1TIUVihgxCizTVt2qusYg1Gdo9s9eMjLwWl8ku16BIZZKtuUTuhvlRTyhZ6xirx+e5sVFXr4efrZZNjEhHVdaHSGJRylel7EokESeEBOMNi526Jq+8RERF5CHWZDhIJ6qXbRwTJUKMXuFBZ46SeubZavQHnL1Qhvg2ZLOagVBkLypOl6loDSjTVNqkpBRiLnRsEcCSPxc6JyD6KNcaglKtM3wOMxc6ZKeWeWrzurBACX331FbZs2QK1Wg2DwWCxf+3atTbrHBEREdlOYbkOof6+8PGy/E5KdenDsLpc6zLferqS3Ita1BoE4kP9W30MX28pwgJ8UVDKoBRZKqowTqtVKWyTKdU5MhA+XhIczi1Fv/gQmxyTiKiukgrXypQCgCRVIH7OyGfWtxtqcabUP//5T9x55504e/YsAgMDoVQqLX6IiIjINTU2RchUYJkr8DUss9g4HSChDTWlgEsr8DFTii7zd6032wSlZN5e6BoVxBX4iMhuSjTVCJR5Q+btOlOEk1UBqNDVml9TyX20OFPqs88+w9q1a3HDDTfYoz9ERERkJ+pyLSIU9acImQJVBQyYNCirpBLeUgligts2vSpSIeM9pnpMK1/aqqYUAKTGKHHwPINSRGQfxZpqhAS41qIdSapAAMCpwooG3+uQ62pxppRSqURSUpI9+kJERER2VFiugyqw/gdfuY8Xgv19zB+OyVJWkQYdQvzg7dW2UpxRSmZKUX3qci2kEiAswHZBqR6xSpwsKIe2Rm+zYxI1RG8Q2HG6GN8dyMGO08XQG4Szu0QOcEFTjVAbvmbZQnyYP7ylEhY7d0MtzpSaO3cu5s2bh2XLlsHPz88efSIiIiI7UJfrMCgprMF9EUEyprw3IqukEvFtnLoHGKfvbTqqtkGPqD1Rl+kQHiiDl9R2NVB6xipRaxA4UVCOXh2CbXZcorrWZ+Rh3rojyKtTKy9aKUf6uBSMSY12Ys/I3oo11QhzoXpSAODjJUVcqD+LnbuhFn/lN2nSJFy4cAERERHo2bMn+vbta/FDRERErkcIAXW5rtG6NRFBcqjLmcXTkKxiDeLDWl/k3CRKIUdRhQ41ekPzjcljFFboEGGjIucm3aKC4CWV4BDrSpGdrM/Iw0Mr9lkEpAAgv1SLh1bsw/qMPCf1jByhRKNzqSLnJkmqQGZKuaEWZ0pNnz4de/fuxbRp0xAZGcnK9kRERG6gTFuL6lpDo3VrIoJkyC6pdHCvXJ/BIJBdUonJA+LafKxIpRxCGKdRxgQz25yM1GUNT6ttC7mPFzpHBCIjp8ymxyUCjFP25q07goYm6gkAEgDz1h3BqJQom2YAkuso0VRjQILrBaWSVQH48RADou6mxUGpH3/8ERs2bMDQoUPt0R8iIiKyg8JLWVARQQ0X/1QpZPgz64Iju+QW1OU6aGsMiA+1TaYUAOSXaRmUIrPCci26RSlsftzUWCUO5zJTimxv99mSehlSdQkAeaVa7D5bgsHJDU8ZJ/dmLHTuikGpQORcrIK2Rg+5j+usDEhNa/H0vY4dO0KhsP0fTiIiIrIfdTPLzkcEyVFQpoUQLFJbV1axcRpAQrjtglIFTXyYI8+jLrf99D0ASI1R4FheOaprOV2UbMvaqd6cEt4+1egNKNfWuuj0vQAIAZwt4hQ+d9LioNS///1vPP3008jMzLRDd5r33nvvISEhAXK5HIMGDcLu3bsbbXv48GHcdtttSEhIgEQiwaJFi9p8TCIiIndU2Myy85EKGXS1BpRpax3ZLZeXVVwJiQToENL2oFSwvw98vaVcgY/MDAaBogpdo7+XbdGzgxLVegNOqsttfmzybI1l3La2HbmXC5pqAHC5QueAMVMKAOtKuZkWB6WmTZuGLVu2IDk5GUFBQQgNDbX4safVq1dj9uzZSE9Px759+9C7d2+MHj0aanXDK9lUVlYiKSkJb7zxBqKiomxyTCIiInekLtMhwNcLAbKGZ+6bPjwU8pttC1klGkQr5DaZBiCRSBClkDMoRWYXq2pQoxeNZjC2RfdoBSQSIIPFzsnGBiaGItjPp9H9EhhX4RuYaN/PhuQcxZeCUq6YKRUS4IsQfx+uwOdmWlxTqrFsI0dYuHAh7r//fsyYMQMAsGTJEvz4449YtmwZnn322XrtBwwYgAEDBgBAg/tbc0wA0Ol00On+Xja7rMxYRNJgMMBgYIp0axgMBggheP88BMfbc3CsXYe6XIvwIFmjYxEeaPyAkV+qRVJ4QJvO1Z7GPbNIg7hQf5tdS6RChvxSbbu4NybtabwdLb+0CgAQHuhr8/sn95YiOTwAh86XYmK/th+b4+yZGhr3Xw7no0xbA8AYgGpo0veLN3aHBAIGA6eEuxNrfs+LLn15Fezn7ZKvB0mqQJwurHDJvrmKy8fZ2feqVavvOUN1dTX27t2LOXPmmLdJpVKMHDkSO3bscOgx58+fj3nz5tXbXlhYCK2W3362hsFgQGlpKYQQkEpbnMBHbobj7Tk41q4ju7AUIXJpo5nAkho9AOBUjhqdgvRtOld7GvfTBWXoEuFvswxqpS9wrqisXWVkt6fxdrST54xfbEp1FVCra2x+/E5hMhzIKrbJ843j7JkuH/c/zpbi6XWncU3nEFzdKRhv/3Ye6oq/n7veUuCVG5LQN6Lxvzfkuqz5Pc/MKzG2rSyDWu960+RiAqU4nnuRz78mXD7O5eXOneZtVVBKo9EgIMD6b01b2t4aRUVF0Ov1iIyMtNgeGRmJY8eOOfSYc+bMwezZs83/LisrQ8eOHaFSqVgEvpUMBgMkEglUKhXf6DiQ3iCwJ7PEWGQ1SIYBCaEOWbqX4+05ONauo6w6E7GhgYiIiGi0TaDsELSQNdnGGu1l3IUQyCk7iHF9OrT5npjERxTj1FG1zY7nCtrLeDtDzXnjh/nuCTGQ2WGlqH5JGmzdeAKhYeHw9mrb2HCcPVPdcd+deQFzfjyDq7qq8N7UPvDxkmLSkK7m95JZxZX4z6aT6JMcg4iIIGd3nVrBmt9z/ekq+HpJkNAhChKJ/T83tFSPjhX49eQpqFQql+yfK7h8nOVy59Z/syoo1alTJzz22GOYPn06oqOjG2wjhMCmTZuwcOFCDB8+3CL7qL2RyWSQyerP/ZdKpfwj3QYSiYT30IHWZ+Rh3rojFkv6RivlSB+XgjGpDf+e2xLH23NwrF1DUYUOXaOCmhyHiCA5CiuqbTJW7WHcL2iqUa6tRWJ4oM2uI1rpB3W5DhKJpF29WW4P4+0MhRXVUMi94SdrvD5PW/TsEAxtjQFni6vQNartQQKOs2eSSCQ4cL4U9326FwMTQ/Hu1L7mIKpUCgzppAIA6Gr1WLY9E98fzMPTY5TO7DK1QXO/5yWVNQgNkMHLy/aBdFvoFBEETbUehRU1iFKy2H5j6o6zs1/TrQpKbd26Fc899xzmzp2L3r17o3///oiJiYFcLseFCxdw5MgR7NixA97e3pgzZw7+8Y9/2Lyj4eHh8PLyQkFBgcX2goKCRouYO+OYRO5gfUYeHlqxr14NgPxSLR5asQ+Lp/V1SGCKiBzHmmXnIxQyqMt1TbbxJJnFxmkJcaFtX3nPJFIhR2W1HuW6Wijk9glEkPtQl2sRobDfh6YeMcYM/oycUpsEpcgzHVNXYtbak0iNUeKDO/s3uvCDzNsLN/aKxncHcvHkdV0hdUD2PTleiUbnkkXOTZJUxhlbpwsrGJRyE1aFxLp27Yqvv/4aJ06cwKRJk5CTk4OvvvoKS5cuxdatWxEbG4ulS5ciMzMTDz/8sF2ipr6+vujXrx82b95s3mYwGLB582YMHjzYZY5J5Or0BoF56440WJTStG3euiPQszAlUbuhq9WjtKqm2eW5I4LkUHNlOLPskkoAQHyY7YJSpjfIBaW8zwTz9Hl7CZL7IDE8AIe4Ah+10vH8cjy29gSSwgPw0d394efb9Oe88X1ikXOxCrszSxzUQ3K0Ek21SwelOob6w8dLgjNcgc9ttKjQeVxcHJ544gk88cQT9upPk2bPno3p06ejf//+GDhwIBYtWgSNRmNeOe+uu+5CbGws5s+fD8BYyPzIkSPm/8/JycGBAwcQGBiITp06WXVMovZm99kSiyl7lxMA8kq12H22BIOTwxzXMSKym8JL2U+qZj78RgTJuHx8HZlFlQgL8EWQDTOaoi5lxeSXadE5kpkrnq6wXIdoO3+T3yNGgcO5/L2mljtbpMGdy3YjItAXy+/ub9VrYf/4EHQI8cO3+3NwRRLfR7ZHxRXViLRjhmdb+XhJERfqj9OFrleEnRrW4tX3nGny5MkoLCzESy+9hPz8fKSlpWH9+vXmQuXZ2dkW8yFzc3PRp08f878XLFiABQsWYMSIEdi6datVxyRqb/46f9GqdupyfotP1F6YpuQ1l5HB6XuWsoo1Ns2SAmCeQpnPTCmCMSjVu4N9a+/0jFXi12NqGAyC06nIaucvVOKOpTuh9PPB2+OTEexvXWaMRCLB+D6x+PiPTMy9qUejU/3IfV2orEb3aNde3CtZFYjTzJRyG24VlAKAmTNnYubMmQ3uMwWaTBISEiBE81OQmjomkbsTQuB4QTl+OpSPnw7l4ZTauhfo5qb5EJH7KLQ2KBUkR4WuFhpdLQJkbvcWweaySioRH2bb1YRl3l4IDfBFAadJEgB1mdbuf29TY5WorNbjTJEGnSIC7Xouah/yS7WYunQXvL2k+OyegZDqylr0+JvTYvHOr6ew5Zga1/dkjdL2pkRTjTAXnr4HAEmqQKw7mOvsbpCVuHQGkZvQGwR2nC7GdwdysON0cZM1n4QQOJJbhgUbjuPahf+HMYt+x/LtZ9GrgxIfTOuHKIUMjX1XKoFxFb6BiaF2uQ4icjx1uQ7eUglCmvmm25TFw2wpI3tkSgHGYuf5DEp5PI2uFppqfbMLELSVqdg5p/CRNYoqdLjjw52o1Ruw8r5BrSoU3SkiEL06KLF2f44dekjOZDAIXKisQWigawelklUByLlYhapqvbO7Qlbg16BEbmB9Rh7mrTtiUQsqWilH+rgU8yp5Qggczi3DT4fy8NOhPGQWV0Lp54PrUiLx4o0pGNIpDDJvYwq1AQIPrdgHCVCv4LkAkD4uBV5M8SdqNwrLtAgPlDU7dceUsaEu0yIx3LYZQu6mQleLoopqJNg4UwoAohQy5Jcy8OfpzLXeAu0blAr290XHUD9k5JTi5rRYu56L3NvFymrc+dFulFbV4st/XIGOof4wGAytOtYtabGY//NRXNBUI8TFs2rIeqVVNdAbBEKtnM7pLEkqY1bomaIK9Iix7xRpajsGpYhc3PqMPDy0Yl+94FF+qRYPrdiHZ8Z0w4Wqavx8KB/ZJZUI9vfB6JQozLs5FYOTwuDrXT8hckxqNBZP61sv0OXn4wWDEEiJ5os3UXtSWKFrtsg5wEypurKKjQVS4+yUKXU4t2XTYaj9Mdd6s3OmFACkxii5Ah81qVxbg+nL9yC/tApfPDDY/KG+tcb1jsFrPx3Fj4fyMO2KeBv1kpytWFMNAC69+h5gzJQCgDOFGgal3ECLg1IJCQm45557cPfddyMuLs4efSKiS/QGgXnrjtQLSAF/Zzi9sf4YQvx9MCY1Gq/1jMIVSWHw8Wp+Zu6Y1GiMSonC7rMlUJcba1qkxCgw9p3fMfvLA1j9j8HMliJqJ9Rl1i07HyTzhtxHyqAUgOziSgCwS6ZUpEKOzcfUNj8uuRfTgiIqB9RwTI1VYsnW0yx2Tg2qqtbj3o//xJnCCnx+/xXoGtX2lUFVQTIM6xyOb/fnMCjVjlyoNAalwlx8+l6wvy/CAnxZ7NxNtLim1D//+U+sXbsWSUlJGDVqFL744gvodHzzSmQPu8+WWGQyNeadKX0w/9aeGNZZZVVAysRLKsHg5DDcnBaLwclhUPr5YOGkNOzNvoD//Xa6LV0nIhdSWKGzKhtDIpEgIkjO1TcBZBZXIkjmjRD/5pdAb6kopRxFFTrU6ls3LYbaB3WZDjJvKRRy+09cSI1VolxXi+ySSrufi9yLtkaPBz77Exm5pfh4xkCkxtouq2R8n1j8mXXBHOQn91dcYcqUsn+GZ1slqwJxplDj7G6QFVoVlDpw4AB2796N7t27Y9asWYiOjsbMmTOxb98+e/SRyGNZ+8HQlEprCwMSQvHgiGT8Z+MJFkUlaifUZTqr69ZEBMmgLuOXTdklGsSH+0MisX1WSZRCDiGMwULyXKZptfZ4jl0u9VKx8wz+Xfdoly+ao63RY+aqfdh9tgQfTu+PfvEhNj3fqJRI+Pt64dsDLHjeXpRoqiGVAEo/239hY2tJqgBmSrmJVq++17dvX/z3v/9Fbm4u0tPT8eGHH2LAgAFIS0vDsmXLIETjK4MRkXWsXSba1stJPz6yCzpFBGH26oPQ1nDVCiJ3ZjAIFFXooFJY9zoRqWCmFABkFlUiPtQ+xd4jL41FvhWZsNR+WTut1hbCAmWIUcqRkcNaZp5qfUYehr75K6Ys3YnHvjiAKUt3Iu3lX7DluBpL7uyHIcnhNj+nv683xvSIwrf7c/jZsJ0o0egQ7O/rFiU+TJlShiZWLCfX0OqgVE1NDb788kvcdNNNeOKJJ9C/f398+OGHuO222/Dcc8/hjjvusGU/iTzSwMRQRCvlaOxlXwLjKnwDE0Ntel5fbykWTU7D2SIN/v3LcZsem4gc60JlNWoNwuoPvypmSgEAsksqEW+HIucAzEusF5QxKOXJTPUcHaVHrBIZLHbukUyL5lxeEkJbY4DeAOjs+AXk+L6xOFOkwV/n+dxrD4o11S5f5NwkSRWAqho98vm31uW1OCi1b98+iyl7PXr0QEZGBrZt24YZM2bgxRdfxKZNm/DNN9/Yo79EHsVLKkH6uJQGC52bAlXp41Ls8m1F16ggPDW6Kz7cdhY7Thfb/PhE5BimouXWrL4HGFcC8/RC57paPXJLq+wWlArx94Gvt5SZUh6usNy6Wm+2khqjREZuKTNWPExTi+YAxveT89Ydgd5O2SRDksOhCpLhm/2cwtceXHCjoFTypRUkOYXP9bU4KDVgwACcPHkSixcvRk5ODhYsWIBu3bpZtElMTMTtt99us04SebIxqdFIiVbAx8sy8BSllGPxtL4Ykxptt3PfOzQRgxJD8eSagyjT1tjtPERkP+Zl560NSgXJUVpV49FTd8+VVEEIIN4OK+8BxoLykQoZ8pmR5tEKy62v9WYLPTsocLGyBjkXqxx2TnK+5hbNEQDySrXYfbbELuf3kkpwc+8YrDuYixou7uD2ijXVCHOToFSHED/4eElY7NwNtHi5jzNnziA+vullPQMCArB8+fJWd4qI/pZVrMGRvDK8NaEXOob4m9P9ByaG2n0+t1QqwYKJvXH9ot8x7/sj+Pek3nY9HxHZXuGloFR4Cwqdmx7XMdQ+mUKuLqvY+AbWXplSgLHYOafvea4avQHFmmqHZ0oBQEZOKTqEeObvtieytkagPWsJ3tInFh9uO4ttJ4twdbcIu52H7K9EU404N3lv4O0lRUIYi527gxZnSjUXkCIi21qxMwvB/j64qXcMBieH4ea0WAxODnNYgcEOIf6Ye1MPfL3vPNZn5DnknERkO+pyLZR+PpD7eFnV3lSE25OLnWcVV0LmLUWkHev9RCrknL7nwYoqTBmMjqspFaGQQxUkY7FzD+OsRXPq6hGjQJfIQE7hawdK3Gj6HmCsK8VMKddnVaZUSEiI1cvVlpTYJ/WTyBNpa/T48s/zmDygo9UfKO3h1r6x2HikAHPWHkLf+BCHvokmorYpLG/ZCl+mtp5c7DyrWIO4UH9I7Rj8j1TIcSSXwQFPVdjCWm+20jPWWFeKPIdp0Zz8Um2jNUqj7LBojsU5JBLc0icW/918EhW6WgTKWjxZh1yAEMKtCp0DxrpSDIa6PqteERYtWmTnbhBRQ9YdzEVpVQ3uGBTn1H5IJBK8fmtPXPef3/DMV39h2d0DrA5UE5Fzqct1LfrgG+zvA18vqUcXO88qqbRbPSmTKIUc+WVaCCH4euqBTEHflgSMbSE1RoFVu7P5vPMgpkVzHlqxr94+ey+aU9fNabF4a/1xbMjIx239Otj1XGQfldV6VNca3C4olVeqhUZXiwAGQ12WVSMzffp0e/eDiBqwYmcWRnRR2f3DkTVCA3zx1oSeuOfjP/H57nOY6uRAGRFZp7BMh5hg67MbJRIJVEEyj5++d42d655EKuWorNajQleLILmPXc9FrkddroNUAoQ5sNA5APSIVaKoohoFZTpEKZn17CnGpEZj8bS+eO6bDJRoqs3bo5RypI9LseuiOSaxwX4YlBiKb/bnMCjlpkzPnbAAx75utUWSyvgZ6myRBqmxSif3hhrT4ppSdWm1WpSVlVn8EJFtHDx3EQfPl+LOK1ynjts13SIxdVAcXvnhCDKLOD+byB0UVugQoWjZh09VkMxjp+/V6g04f6ESCXYscg4YM6UAsNi5h1KXaxEWKHNYfUiTnpc+lB3K4RQ+TzMmNRqPj+oMqQRYOKk3Pr//Cmx75hqHBKRMxveJxfbTRXzdc1PFl4JS7pQplaQKBAAWO3dxLQ5KaTQazJw5ExEREQgICEBISIjFDxHZxoqdWYgN9nO5VUqev6E7IhQyzP7yAGq5tC+Ry1OXaVu87HxEkAwFHjp9L69Uixq9QJwDpu8BQH6pZ95nT9fSWm+2Eq2UIzTAFxkMSnmk8yVV6BDij1v7dnDoojkm1/eMho+XFN8fyHXoeck2SjTGv1fuFJRS+vkgPFCG0yx27tJaHJR6+umn8euvv2Lx4sWQyWT48MMPMW/ePMTExODTTz+1Rx+JPM7Fymp8fzAXUwfFOfwNQ3MCZN5YOCkNB85dxJL/O+3s7hBREzS6Wmiq9S1edj5SIYfaQ7/Jziw2vnG1d6aUaUzyPfQ+e7qW1nqzFYlEgtRYJQ6z2LlHyiquRLydX9uaovTzwcjuESw87aZKNDUAgJAA95pynqwKwBlmSrm0Fgel1q1bh/fffx+33XYbvL29MWzYMLzwwgt4/fXXsXLlSnv0kcjjfLX3PIQAJg/o6OyuNKhffAgevqoTFm06yW9biVxYa1f4igiSmR/rabKKK+EtlSA22M+u55H7eCHE34fTWDyU2kmZUoCx2Dmn73mmrJJKxIU6LygFALekxeJIXhmO55c7tR/UciUaHYJk3pB5O29F8NZIUgUyU8rFtTgoVVJSgqSkJACAQqFASUkJAGDo0KH47bffbNs7Ig9kMAis2JmFG3pGIdzBBVBb4tFrO6NrVBD+ufoAtDV6Z3eHiBpgWkGvpR9+IxQyFGuqUeOBU3SzijWIDfGDt1ebym5aJVJhXKadPE9hmRYRQc4pNJ4aq0RBmc6jFzPwREIIZBdrnJopBQBXdY1AsL8Ps6XcULGmGqGB7jN1zyRZFYCzRRUwGISzu0KNaPE7rqSkJJw9exYA0K1bN3z55ZcAjBlUwcHBNu0ckSfadqoImcWVuHOw6xQ4b4ivtxSLJqchu6QSb60/7uzuEFEDTB86VS388Gv6sFxU4XnZUsbpLY5Z8TRKKef0PQ8khEBhhXOm7wF/Fzs/nMsFijxJsaYammq90zOlfL2lGNsrGt8dyGGQwM2UVFS7VT0pk2RVILQ1BuSWVjm7K9SIFgelZsyYgYMHDwIAnn32Wbz33nuQy+V4/PHH8dRTT9m8g0Se5rOdWegerUDfONdfOKBzZBCeGdMNy7afxfZTRc7uDhFdprBcB19vKRRy7xY9zvRh2RNX4MsqrkS8gz60RSnknL7ngS5W1qBGL5w2fa9DiB8Ucm9knOcUPk+SVVwJAIgLdUzQvSnj+8Qir1SLXWdLnN0VaoESTTVC/d0zKAWAU/hcWIuDUo8//jgeffRRAMDIkSNx7NgxrFq1Cvv378djjz1m8w4SeZKci1XYfLQAd14RD4nEtQqcN2bGkAQMSQ7Dk2sOorSqxtndIaI6THVrWvp6YirC7WkBEyEEskocN70lgtP3PJJ5Wm0LFyCwFVOx8wwWO/co2SXGD+RxTp6+BwB940LQMdQP33IKn1spqXTPTKnYED/4ektZ7NyFtblgQnx8PG699Vb06tXLFv0h8mirdmUhwNcbN6fFOLsrVpNKJVgwsTcqdLVI/y7D2d0hojpau+x8WIAMXlKJ+cOzp1CX66CtMThu+p5CjqIKHWo9sHaXJzNNq3VWTSnAOIUvI4fT9zxJdnEVwgN9EShrWeasPUgkEoxPi8VPh/JYl9SNlLhpTSkvqQSJYQE4zaCUy2rVq9KePXuwZcsWqNVqGAyWb6QWLlxok44ReRpdrR6r95zDbf06IMAF3jC0REywH165ORX/XH0AI1MiMbaX+wTViNqz1i477yWVIDzQ1+OCUqbpLQkOyiSIUspgEEBRRTWilM4LUJBjtXZVTFvqEavE/347gwuaaoS4YeYDtVxWicbp9aTquqVPLP776ylsPqrGjb2ind0dskJJRTXC3PT1IkkVgDOcvueyWvzJ9/XXX8cLL7yArl27IjIy0mJKgLtMNyJyResz8lFUUY1pV8Q5uyutcnNaDDYeKcDz32RgQEIoIhX8gEXkbOoyLQYkhLbqsRFBchR62OpcmcXGN6wdHfTBzfQ6mV+mZVDKg6jLdQiSe0Pu47xl1VNjFACAjNxSDOusclo/yHGyHbiIgzWSVIHo3TEY3+zPYVDKDehq9SjX1SI0wHVXBm9KsioQa/aec3Y3qBEtnr739ttvY9myZTh69Ci2bt2KLVu2mH9+/fVXe/SRyCOs2JmFwUlh6BQR5OyutIpEIsGrt6RC5i3FU1/9BSG4ogqRsxVVtG76HgBEBMk8rtB5dnElopVyhwULokxBKdaV8ijqstb/XtpKQlgAAmXenMLnQbJKKl0qUwoAxqfFYOtxNUo01c7uCjXjgsZYNzY0wMfJPWmdJFUACsp0qNDVOrsr1IAWB6WkUimuvPJKe/SFyGMdzSvDnswLuHNwvLO70iYhAb54a0Iv/HaiECt2Zjm7O0QerVZvQLGmutVThCIUMhR4YKaUIz+0hQb4wtdL6nEF5T2dulzr1HpSgLEeZEqMAhk5LHbuCSqra1FYrnPYIg7WGts7BgLAj4fynN0VaoYpcOjOmVIAWOzcRbVq9b333nvPHn0hJ9EbBHacLsZ3B3Kw43Qx9AZmuDjaip1ZiAiSYVRKpLO70mZXdY3AnVfE47WfjvKFn8iJiiqqIUTrV/iKCJJ7XqZUSSUSHDi9RSKRIEIhQz6DUh6lsJW13mwtNYYr8HmK7BJjvTxXC0qFB8owvHM4V+FzA6aglDvXlALAulIuqsU1pZ588knceOONSE5ORkpKCnx8LFP41q5da7POkf2tz8jDvHVHkFdn6kC0Uo70cSkYk8r53Y5Qrq3BN/tzcP+wJPh4tXlBTJcw54Zu2HaqCI9/eRBfPzgY3u3kuojcibmYcmDrMjIiFDIUVeigNwh4ST2jZmRmkQaje0Q59JxRCjkKOH3PoxSW69AzVunsbqBnBwWWbT+L0qoaKP3cc0oOWce0iIOj6uW1xPi+HfDo5/uRVaxxqZpXZKlYY3xPEeqmQSl/X28E+/ng50N5iFTIMTAx1GPe27iDFn9SfPTRR7FlyxZ06dIFYWFhUCqVFj/kPtZn5OGhFfssAlKAsbbFQyv2YX0GU2kd4Zv9OdDVGjBloHsWOG+Iv683Fk7qjYycUry35bSzu0PkkczLzrchU8og/n4j2t5drKxGmbbWoZlSABCplDNTysOoy3Wt/r20pdQY4/v2w8yWaveyiyvh7+sFVaDzn3eXG9U9EgG+Xvh2f66zu0JNKNFUQ+Ythb+v8xZoaK31GXkY+uavuFhVgw1HCjBl6U4MffNXm3zW5Ywj22hxptQnn3yCr7/+GjfeeKM9+kMOojcIzFt3BA392ggAEgDz1h3BqJQoRpHtSAiBz3Zk4bqUyHa38lKfuBA8cnUn/PfXk7iqqwq9OwY7u0tEHqWwXAeJpPWp9qZCzMaizO3r9akhmcXOmd4SpZDjaB6LTXuKyupaVOhqXeJ3KkkVCD8fLxzOKcOQ5HBnd4fsKKvEWC/PFVdK9/P1wpjUaHx7IAePXtvJJftIxqBUaICv242PKQnj8s+8piSMxdP6tnp2EGcc2U6LM6VCQ0ORnJxsj75Y5b333kNCQgLkcjkGDRqE3bt3N9l+zZo16NatG+RyOXr27ImffvrJYv/dd98NiURi8TNmzBh7XoJL2H22pF6GVF0CQF6pFrvPljiuUx5o19kSnFRXuH2B88bMuqYTesQo8PiXB1BVrXd2d4g8irpch7AA31ZPnzVlcpimAbZ3WcXGOhNxDg5KRSpknL7nQczTal2gppTXpWLnh1jsvN3LLqlyuZX36hrfJxZnizQ4eJ7PRVdlCkq5k+aSMABjEkZrsps448i2WpwpNXfuXKSnp2P58uXw93fsi9vq1asxe/ZsLFmyBIMGDcKiRYswevRoHD9+HBEREfXa//HHH5gyZQrmz5+PsWPHYtWqVbjllluwb98+pKammtuNGTMGy5cvN/9bJnP+GwV7U1u5opK17ah1PtuZhWRVAAYnhTm7K3bh4yXFwklpuPG/v+ONn49i3s2pzT+IiGxCXa6Fqg3ZGOGBMkgk8JiV4bKKKxEa4AuF3LG1dSIVcmiq9ajQ1SJQ1uK3ZeRm1JeCUhEuEJQCgNQYBX4/VeTsbpCdZRdrXHoxncHJYYhUyPDt/hykMbPeJbljUMraJIxrFmxFlFKOILkPFHJvBMq9EST3RpDcx/K/MuP/+/t6If37w5xxZEMtfvfz3//+F6dPn0ZkZCQSEhLqFTrft2+fzTp3uYULF+L+++/HjBkzAABLlizBjz/+iGXLluHZZ5+t1/7tt9/GmDFj8NRTTwEAXnnlFWzcuBHvvvsulixZYm4nk8kQFWV9YVOdTged7u9vjsvKjGn3BoMBBoOhVdfmaKpA615UVIG+Drkmg8EAIYTb3D9bUJdpsSEjH8/f0A1CCAjRPucgJ4X749kxXTHvh6O4ppsKwzqrPHK8PRXH2nmM0+5a/xruJQFC/X1RUKZt8THccdyzijWID/V3eJ8jLwUn8i5UIjki0KHnthV3HG9nKSitAgCEO+j9VXN6xCjw6c4slFVVNxsU5Ti7p1q9AecvVKFjiF+rxs4R4y4BcFPvGKzdl4M513dtNwv/uKPGxru4Qofo4NY9h5yloKzKqnYdQvwQFuiLcm0tsksqUa6rRYW2FuXaGlToatHSRCpTsGvXmSJc4aKJB5ePs7PHtcVBqVtuucUO3WhedXU19u7dizlz5pi3SaVSjBw5Ejt27GjwMTt27MDs2bMtto0ePRrffvutxbatW7ciIiICISEhuOaaa/Dqq68iLKzxJ9D8+fMxb968etsLCwuh1brHN8rx/gIRgT5QV9Q02iYy0Afx/rVQq9V274/BYEBpaSmEEJBKPeMP0Uc7c+EtlWBYR5lD7rEzjU72w89xQXjyy4NYcWcKgnylHjfensoTf7ddRW5JBeJD5W16fQn180KW+mKLj+GO434y/yKiFY5/PfauMX7JdSw7H0FQOPTctuKO4+0sp3OL4eslgbasBLpy53+DHi2vhRDAH0eykBYb1GRbjrN7yi3VodYgoPSqadXrm6PGfXicHEt/r8YPf57GlYlcPMtZGhtvdVkVEoN93Oozi0+tdUGpqWlh6Nex4dc/IQQqawzQ6PSXspr1+O3MRXz2Z0Gzxz11vhBJga5ZvuTycS4vL3dqf1oclEpPT7dHP5pVVFQEvV6PyEjL1NPIyEgcO3aswcfk5+c32D4/P9/87zFjxuDWW29FYmIiTp8+jeeeew7XX389duzYAS+vhlcXmDNnjkWwq6ysDB07doRKpYJC4T5vKOfeJPDIqv0AYJF+aHqLlH5TKqKjHJPqazAYIJFIoFKpPOKNTo3egO+PZGB8n1gkdfSMQniLpigx5u3f8c4faiya1MujxtuTedrvtiu5oD2CYSplg9PbrRUTmoWKWmmLj+GO455XnoGrukW36X61hiJEDyADOqmfw89tK+443s6ixQWoguT13p86S0iYAb7ex5FT6YXrmnn+cZzd04ky4/TMXknRiGjF6qKOGneVSqBL5DlsOavB+EGd7XYealpj412m/Qsd2viewtGuC1chamM2Csq0DU61kwCIUspxXZ+kFk2zC1AUWxWU6tRBhYgI182UqjvOcrlzF99odfGCvXv34ujRowCAHj16oE+fPjbrlCPdfvvt5v/v2bMnevXqheTkZGzduhXXXnttg4+RyWQN1p2SSqVu9Uf6hl4xWCyV1Fs1IDTAF6+NT3X4qgESicTt7mFrbTlSgIIyHaYNjveI6wWAmBB/vDq+Jx79fD9Gdo/AFdHeHjPens6TfrddhRAChRU6RCrkbbrvEUFynFRXtOoY7jTuGl0tCst1SFQFOLy//jIpgv19UFCuc4t71Rh3Gm9nKqyoRoRC5jL3SSaVonu0AofzyqzqE8fZ/Zy7UAUvqQQdQlv/+uaocR/fpwMWbToBTbUeQQ6u70d/u3y89QaBi1U1CAts23sKR5NKgbk3peChFfsgQSNJGONS4OPdcCJKYwYlhSNaKUd+adPBrkFJ4ZC6cE2puuPs7HFt8dnVajWuueYaDBgwAI8++igeffRR9OvXD9deey0KCwvt0UcAQHh4OLy8vFBQYBmVLCgoaLQeVFRUVIvaA0BSUhLCw8Nx6tSptnfaDYxJjca2Z67B5/dfgbcnp6FDiBz94oO5jKWdfbYzC/3iQ9AjxrPSk2/qHYNxvWPw0neHoS6vdnZ3iNqtsqpaVNca2lToHDCuwKf2gELnWcWVAIC40JZnEdhClELuMQXlPZ26XOcyRc5NUmMUyOAKfO1WdnElYoLlblGn6ea0GFTrDdhwuPksFHKc0qoaGATcrtA5YPysu3haX0QpLd8PRSnlWDytb6s+83pJJUgflwLg7+CWSd1gF4ucW6/Fr06zZs1CeXk5Dh8+jJKSEpSUlCAjIwNlZWV49NFH7dFHAICvry/69euHzZs3m7cZDAZs3rwZgwcPbvAxgwcPtmgPABs3bmy0PQCcP38excXFiI72nKCMl1SCwclhuLlPLB66qhM2HVXj/IVKZ3er3TqlrsD2U8W484p4Z3fFKV65uQf8fb3wysZMGFqxBCsRNa+wwhjgiFC07cNvRJAchRW6drsQg0l2iQYAkBDmnCXTIxXGb1yp/VOXaRHRxmCxraXGKnFKXYGqatesfUJtk1VciXgnBdxbKibYD1ckhuGb/eed3RWqo0RjrH0YZuVCWa7GIgnj9jR8fv8V2PbMNW1KwrBHsMuTtXj63vr167Fp0yZ0797dvC0lJQXvvfcerrvuOpt27nKzZ8/G9OnT0b9/fwwcOBCLFi2CRqMxr8Z31113ITY2FvPnzwcAPPbYYxgxYgT+/e9/48Ybb8QXX3yBP//8Ex988AEAoKKiAvPmzcNtt92GqKgonD59Gk8//TQ6deqE0aNH2/VaXNX4PrF48+dj+GxnFuZc3735B1CLrdyVhdAAX1zf0/oVH9uTYH9fvHlbL0xfvgef7czCjKFJzu4SUbujLjO+gVQFti0oFamQoUYvcKGyxi2/IbVWZnElAmXeTrvGKIUcx/LLnHJucqyiCh1ULpYp1TNWCYMAjuSVoV98iLO7QzaWVVKJPnHBzu6G1cb3icUza/9Cfqm23gd+co7iCuPshhB/930fYErCsKUxqdEYlRKF3WdLoC43fuEwMDGUGVKt0OJMKYPBAB+f+nN8fXx87L6U4OTJk7FgwQK89NJLSEtLw4EDB7B+/Xpzscjs7Gzk5eWZ2w8ZMgSrVq3CBx98gN69e+Orr77Ct99+i9TUVACAl5cX/vrrL9x0003o0qUL7r33XvTr1w+///57gzWjPIG/rzcm9e+I1XvO8RszO6isrsVXe89j8oCOkLVw/nJ7MqxzOCamqfDG+uM4pXbuag9E7ZG63BiUamumlGn6n7q8fWfxZBVXIj7MHxKJc95IRipkyOf0vXavVm9Asaba5abvdY4MhI+XBIdzOYWvvRFC4FxJJeJDnZMF2hpjekbBx0uK7w/mOLsrdEmJxhiUCmvHX061lnnGUVosBieHMSDVSi3OlLrmmmvw2GOP4fPPP0dMTAwAICcnB48//nijhcFtaebMmZg5c2aD+7Zu3Vpv28SJEzFx4sQG2/v5+WHDhg227F67cNfgBHy0/Sy+O5CD2wfGObs77cr3B3JRoavFVN5XPHJlB+w9X4nHVx/E2oeHuEWtAyJ3UViuQ6DMG/6+rV7PBADMH57VZTp0a8fJnVnFGsQ7aeoeAEQq5Sgs16FWb4A3XwvbraKKagjR9mCxrcm8vdAlMoh1pdqhEk01KnS1Tn19aymF3Aejukdi7b4c9IwNZgaKCyiprIaXVAKlH4vPk320+J3Pu+++i7KyMiQkJCA5ORnJyclITExEWVkZ3nnnHXv0kRwsLswf13aLwMd/ZLpUHRG9QWDH6WJ8dyAHO04XQ+9m9YiEEPh0Rxau6RqBjm70jZW9yH2kWDipN47mleGdXz1jYQEiR1GXa20yRch0DFPmVXtlzJRyXs2VKIUcBgEUa7gARHtWaMpgdLGaUoBxCt+hHE4hbW+ySpy7iENrxYX641h+OaYs3YnHvjiAKUt3Yuibv2J9Rl7zDyabK6moRoi/j0uvJEfurcVfoXbs2BH79u3Dpk2bcOzYMQBA9+7dMXLkSJt3jpxn+pAE3PnRbuw+W4JBSbadf9sa6zPyMG/dEeTVKQQbrZQjfVyK2xSS23/uIo7kleGpMV2d3RWX0auDErOu6Yz//noSV3dVoU8ca1kQ2YK63DZ1a+Q+XlD6+bTrleF0tXrkllY5dXpLpMIYpMgv1Zr/n9of0zRYV6spBQA9YpX4au95aGv0kPt4bnmB9ibbtLKoG2VKrc/Iw5L/O11ve36pFg+t2Mci0k5QrKlu13UlyflalSMukUgwatQozJo1C7NmzWJAqh0a2ikcyaoAfLIj09ldwfqMPDy0Yp9FQAr4+4+Tu3xr8tmOLMSF+mNEZ5Wzu+JSHrk6GamxSsz+8iAqq2ud3R2idqHQhsvORypk5gyP9uj8hSoIAedmSl0q5su6Uu2bulwHicQ167KkxihQaxA4UcA6j+1JVnElwgJ8EShr21RuR9EbBOatO4KG5kKYts1bd8TtZku4uxJNtVsXOSfX16pXqM2bN2Pz5s1Qq9X1ipsvW7bMJh0j55JIJLh7SALmrjuC3ItViAn2c0o/mvvjJIHxj9OolCiXnmdeXKHDj3/l4cnRXZj6ehlvLyn+M6k3bvjv73j9p6N49Zaezu4SkdtTl+vQNSrIJseKCJK360LnWcUaAHBqzZVQf1/4eEnadUYaGWuzhQXIXLJuWPdoBbykEhzKKUWvDsHO7g7ZSFaJxq2ypHafLan3JXRdAkBeqRa7z5bYfCU1alyJphphgQxKkf20+K/ivHnzcN1112Hz5s0oKirChQsXLH6o/bi1bwf4+3hhxc4sp/WhJX+cXNmXf54HJMDEfh2d3RWXlKQKxPM3pmDFzmxsOa52dneI3J4xU8o208AigmRQl7XfTKms4kr4eksR5cRpc1KpBBFBcuQ38feO3F9hhdblVt4zkft4oXNEIDJYV6pdyS52r5X3rP0CpD1/UeKKSjh9j+ysxZlSS5Yswccff4w777zTHv0hFxIg88aE/h3wxZ5zePTazk6pMdAe/jjpDQIrd2VhXK8YhPAFvVHTBsVh05ECPP3VX/jln8N5r4haSVujR2lVjc0+/KoUMvyZ1X6/dMoqrkRcqL/Ts1ijlHJO32vn1GW2qfVmL6mxShzO5Qp87UlWSSWGdAp3djesZu2XKa64WEB7ZgxKue5rF7m/FmdKVVdXY8iQIfboC7mguwYnoERTjXUHc51y/vbwx+n/Tqhx/kIV7hwc7+yuuDSJRIK3JvRCjd6A57895FIrPxK5E1P9J1t9+DVN32uvv5NZxRokuMD0liiFnNP32jm1DWu92UNqjALH8spRXWtovjG5vKpqPQrLdW6VKTUwMRTRSjka+4pAAuNCRwMTQx3ZLY8mhDBO3+OXxWRHLQ5K3XfffVi1apU9+kIuKDE8AFd3VeHjPzKd8oHE9MepMe7wx+mzHVnoGatE7w5KZ3fF5UUq5Hjtlp746VA+vj2Q4+zuELmlwopLy84rbBWUkkFbY0CZtn0uRGDMlHL+cumRCk7fa+8Ky3U2+720h9RYJar1BpxUs9h5e5BdYlx5z5n18lrKSypB+rgUAGgwMCUApI9Lcek6su1Nha4W1XoDZzCQXbV4+p5Wq8UHH3yATZs2oVevXvDx8bHYv3DhQpt1jlzD9CEJuHv5HuzNuoD+CY4N/nhJJXjxxhQ8vGpfo21c8Y+T3iCw+2wJjuaVYcvxQrxxa09IJK7VR1d1Y69obDoai5e+O4yBiWGIdVKRfSJ3Zar/pAq01ep7xi8GCsu1UPr5NNPavegNAucuVCIh3Pkf2iIVMhS049pdnk4IgcJync1+L+0hJUYBiQQ4nFOGHjH8Is3dmRZxcKdC5wAwJjUai6f1xbx1RyzqynpJJYgJluOabpFO7J3nKdFUA3DNVUOp/WhxUOqvv/5CWloaACAjI8PW/SEXNLyzConhAfj4j0yHB6WAv+tFhQX4ovjSC6PJbX1jMSY12uF9asr6jLx6f0gXbTqBYH8fl+urq5p7Uw/sPFOMJ788iJX3DXJ6rRcid1JYroW3VGKz5ZtN043UZTp0irDNin6uIvdiFWr0AnEuML0lSilHha4WFbpat1m+naxXWlWDar0BEU4sqN8cf19vJKsCcSinFJMGcGEWd5ddUgl/Xy+XDoQ2ZkxqNEalRGH32RKoy7WICJJD7iPFxCU78PbmE3hqdDdnd9FjmIJSLHRO9tTidz1btmyxRz/IhUmlEtw1OB6v/ngU+aVaRDUxnc7W1GVa/PuXE5g6KA6v3Jxq8cdp3V85WHcwD89W6BDuIn9w12fk4aEV+3D5RMeCMh0eWrEPi6f1ZWDKCko/HyyY2Bt3fLgLy//IxL1DE53dJSK3UVhuLKZsq2CuabqRurz9ZfGYprckhLnG9D0AKCjTIlAV6OTekK2Zfn9cuaYUYKwrlcFi5+2CaREHd83U95JKMDg5zGLb46O6YMEvxzGiS4RLl+5oT5gpRY7Q4ppSDRFC4Oeff8aECRNscThyQRP6dYDcW4qVu7Icet5XfjwKX28pnhndzfzH6ea0WAxODsOT13WDBMC/fznu0D41Rm8QmLfuSL2AFADztnnrjkBvaJ/Fgm3tyk7huOfKRLy5/hhOFJRDbxDYcboY3x3IwY7TxbyPRI1Ql9t2hS9/X28EyrxdepXT1sos1sBLKkFsiPOnCUeZglKsK9UumabVuvLCLICxrtTRvDLU6lns3N1llVSiowtkgdrSgyOS0T8+BI+vPoAybY2zu+MRTLNUWFOK7KlNQamzZ8/ixRdfRFxcHMaPHw+tlm+k2qsguQ8m9OuAz3dnQ1erd8g5fz9ZiHUHc/H8jd2h9K9fxyQ0wBezR3XBF3vOISPH+d/q7T5bYjFl7//bu+/4pur1D+Cfk46kK+lKBwU62KVsZA9ZiiiKe6Fe5eIVF4gLF4gL9XcvihO3XgeO6wJU7sWJyJTZsqEL6EqTzqRN0uT8/iiplA46kpyTnM/79eKlJCfnfMmTnCTPeb7P90wigMKKWmzLMXlvUD7ugel90D06FHPe346xz/6Ma9/agvmf7sa1b23BuOd+xrqsQqmHSCQ7nljhKy7CP/sd5RstSIoMQVCAW67RdYqrCrmIK/D5JUN1fVzdmTD2hIwkHWrtThwzmKUeCnVSvtHsUyvvtUWASsDyqwajosaOJd/uk3o4imAy2xChCZTF5yT5r3a/uqxWKz7++GNMnjwZffr0wTPPPIOFCxeipKQEa9eu9cQYSSZuHJOC0mobvtvr+URArd2Bxd/uw6i0aFw6JKnF7WaPSkavuHAsXbNP8uXK21pF4I/VBp6iCQrAVcO64nhZTZMfakUVtZj30U4mpojOUD99z73VGPoItV9O38s1mmWzMpUmKAC6kCAmpfxUSaUVEepAhAQHSD2UVqV30QKALC72UcfVOZw4UVYjm/ObO3WLDsUTl/TH17tOYvWeAqmH4/fKzDZO3SOPa3NSaseOHbj99tuRkJCAF198EbNmzcLx48ehUqlw/vnnQ6vVenKcJAM99OEY3ysW72/K9XgCaOVvx3CizIKnZmW0Ohc+MECFxRf1x/bcMqzxQrKsNW0tyZd76b6cOJwi3tuU2+x9nBJJ1LySqlq3V2PEazUo8cNkSZ7RIqsfbQlaDafv+amSKiv0WnlXSQGAVhOE1NgwZDIp5dMKK2pR5xTRXQb98jzh0iFJuGhgIh79OhMF5TVSD8evGc02Njknj2tzUmrkyJFQq9XYsmULtm/fjrvvvhvx8VySU2luHpuCvScqsOt4uceOkVtqxmu/HsPc8WltWulpXK9YnJcej2XfH4DFVuexcZ3NiNRoJLTyhVMAkKjTsDFjO3BKJFH7OJ0iSqttHpm+Z/CjSqn6HnWlOGaobvi7HMTrNKyU8lOemFbrKf27aLGPzc59mmsRB3+bvuciCAKenjUAYepA3Pv5HjglPIf7e89Tk9mG6DDfOHeR72pzUmrKlCl455138MQTT2DdunWST5UiaZzbOw7JMaH4oIXqlc4SRRGPfZuFuAg17prcq82Pe/TCdBirbVj5W7ZHxtUWASoBPVpYMclV67VkZjoC3LQilhJwSiRR+5gsNjicotsrpeK0/jN9b11WIcY99zOufWsr7A4RH23Jl02PugStGkV+2LuLAENVrdun1XpKRpIO+woqJf2hT52TZ7TIZhEHT9GFBuFfVw3Clhwj3t4ozff/vz5P/LfnqZHT98gL2pyU+u9//4t9+/ahT58+mDdvHhITEzF//nwA8NmlRqn9VCoBN4xKxnd7Cz0yleP7zCL8fqQUSy/u366+C91jQvH38al449S0Pyl8s+sk/jhmxA2jkpGoa/zFM0Gnweuzh2J6RqIkY/NVnBJJ1D5/rfDl7kopDaqtdTBbpatGdYd1WYWY99HOJhWYculRx+l7/suXKqUGJOlgsTmQXcpm574qz2RGl0iN3zenHtMjFnPHp+H//nvI69V9cv88cReT2cqV98jj2nWm6tatGxYvXoycnBx8+OGHMBgMCAwMxCWXXIKHH34YO3fu9NQ4SUauHN4NwYEqfLw13637NVsdePK7AzgvPR5T+rV/augdk3pCFxKEZ74/4NZxtcUxQzUe/joTlw1JwhOX9MfGBydj1dxRWHHNYKyaOwobH5zMhFQHjEiNRqJOg5bS3pwSSdSYofpUUkrr3kSt68e0L1dLOZwilq7Zj+ZqP+TSoy5Oq4Gh2up30z8IMFT6TlKq/6lm55zC57vyjRYkR/tnP6kz3Xteb/SMi8CCT3ej1u6dFcJ94fPEXcrMdlZKkcd1OH0+bdo0fPLJJygoKMBdd92FH374Aeecc447x0YypQsJwmVDk/DJtnzY6pxu2++bmwtQVVuHJRf379Djw9SBWHRBX3yfWYTNx4xuG9fZ1NoduOPjnUjUafDkqcbsASoBo3vE4JLBSRjdI4ZT9jooQCVgycx0AGiSmOKUSKKmXBWsseHu/QLpSnL5crNzX+hRl6DVwOEUUVrtu8k/aqrG5kCVtQ5xPtDoHAAiQ4PRLTqEK/D5sDyjBd38tJ/UmdSBAVhxzWDkmSx49oeDXjmmL3yeuIO1zoFqax0bnZPHdbqmMyoqCnfddRd27dqF7du3u2NM5ANuGp0CQ5UVP7ipNHVfQQW+2FOC+VN6Iimy4/PfZw1OwpDukVi6Zh/qHO5LmLVm6Zp9yCk149XrhyJMHeiVYyrJ9IxEvD57KBLOmBIZoQnklEiiM5RUWREZGgR1oHuXnXf9mPblSilf6FHnOs8V+3Dyj5pyLRKgD/edqeYZXXRcgc9HiaKIfJO8Vhb1tN7xEXjogr54f1Mufjts8PjxfOHzxB1MZhsAINrNF7qIzuTWicZDhw515+5IxnrFR2Bszxi890dup/fldIp47Nt9SI3W4OaxKZ3al0ol4PGZ/XGwqAqrth/v9NjO5ptdJ7Fq23E8cUl/9E3Qevx4SjU9I7HRlMhze8ciOFCFc/vEST00IlkxeKhvTYQ6EJoglU8npXyhR138qYq0IvaV8iuuH6a+UikFnGp2fpLNzn2RyWxDtbXOb1fea8lNo1Mwvlcs7vtiT0MyxVPa+jmx8rdjeGtDNo6WVPvkImHG6vrnkdP3yNP8u/sdedTfxqRi9/Fy7Dle3qn9rNqej93HK3D/5GS3NGQc1C0SVwzriuX/O4Ryi+c+lFx9pC4dkoSrhnfz2HGo3ulTIh+/OAMmsw2feSHxSORLDFVWt6+8B9QvaBIXofHpq76+0KMuJiwYQQECK6X8jCuZ6ys9pYD6pFSVtQ75JmkWj6GOyzsVs+4KqpQC6i9M//PKQahzOLHoy70eSwJZ6xzYdKz0rNvpQoIQH6HGP/93CFOX/4Zz//krHl+9D78fMcBa13rvK4dTxOZjRny7+yQ2HzNK1pvKldyLCmVSijyLc42owyb3jUPXqBB8sCkXy68e3KF9lFZb8dwPB3HFsCQMTgp329gemN4H67KK8OKPR/B4B3tUtcbVRypBp8FTp/pIkfekxIbh4kFdsPK3Y7h2RHcEBzK/TgTUJ6U8tQR4XIS6YXU/X+TqUTfvo6aLssilR51KVZ/8K2JSyq+UVNYiOEAFXUiQ1ENpM1ez86yCCqTEKqNhtr84fioplRyjvLjFazVYdtlA3PbRDnz+53FcfU53t+5/W44JD321F3lGCy7ISMC6rCIAaNTw3PUJ8tzlAzA9IxE1tvok1s8HS/C/fUV4f1MuQoMDMK5nLKb0i8OkPnGNFidZl1WIpWv2N+pZlajTYMnMdK+3rCg7dXE/htP3yMP4S446LEAl4MbRyVi7t7ChX0J7PfP9AahUAhZN7+vWscVFaHDX5J74cEseDhdXuXXfwF99pF5jHynJ3DGpJ4oqa/HlzhNSD4VINkqqaj1WjRGnVft0pRTwV4+6M6ciJOg0sulRF69Vo6jCd5N/1JShur6C0ZcuYMWGq5Go0yDrZKXUQ6F2yjNaEBMWjHCFfj+dnpGAq4d3w9I1+5FbanbLPitq7Hjoq0xc9cZmaEOC8N3d4/H67GHN9jw98/MkJDgAU/rF4+lLB+CPRZPxw/zxuGNSTxjNNjz0VSZGPPMTZr68EcvXH8brvx7DvI92NmmiXlRRi3kf7cQ6N/XybStjtQ2aIBVCg5X5WiLv4SuMOuWq4d2wfP1hrNqWj7un9GrXY7dkG/HVzpN49rIBiA4LRol7Pjca/G1sClZty8cTa/bjwzkj3PZl0NVH6rnLB7CPlIR6xUfggowEvPbrUVw5rCsC3TD10x0cThHbckynkgP1U4G4OiB5S4mHpu8B9cn+I8XVHtm3N03PSES5xY5FX2Xin1cORFJkqKzepwk6Dafv+ZmSSs+9Lz0pI0nHFfh8UJ7Roripe2daPDMdW3KMWPDZbnxx2+gOtwcRRRE/ZBVhyep9qLE58MQl/XH9yOSGz4vpGYmYlp7Q5u99giCgX6IW/RK1uGNST5SZbfjtsAE/HSzBexuzUWVtflqfiPoKrKVr9mNaeoLXPq9MZhtiwnzv3EW+p81JqSFDhrTpR/3OnU3L4sl/RYYG49IhXfHx1jzMO7dHm0/6tjonHv0mC0O7R57qx+T+udLqwAA8dlE65nzwJ/63vxjn90/o9D7ZR0pe7pzUCzNe+h3f7i7A5cO6Sj0cWZVck/KYrXWw2ByeS0pp1T7d6Px0eSYLkiJDcMUw+Z3H47UaHC4+e78S8h0lHlqAwNMyuujw3qYciKLoU1VeSpdvMiuuyfmZwtSBeOHqwbhy5Wa88vNR3DOtd7v3UVBeg8Xf7sOPB4oxLT0eT1zSH4m6ptPjXT1POyIqLBizhiRh1pAkbDxiwOx3trW4rQigsKIW23JMHT5eexnNNkSzyTl5QZuTUrNmzWr4f1EUsWzZMtx2222IjpauISjJw01jkrFqWz7WZRVh5qAubXrM2xuzkVNqxtq7xkGlEjy2usvkvnGY2FuPp787gIm99dAEdXyZdPaRkp/0LlpM7ReHV389illDkiStdFiXVYh5H+1skl51lVzLZWoQ+S9XwsiTlVIVNXbU2h2dOpfKQW6pGSmx8vzRlqDVoJir7/mVkiorhiVHSj2MdstI0qLcYsfJ8hp0jZLn+4WayjNaMLpHrNTDkNzQ7lG4a3JPvPzzUUzorcew5Kg2Pc7hFPHRljw8v+4gwtSBWDl7KM7vn+Dx7/3GNq4Y6M1p9CazFVFMSpEXtDkptWTJkkZ//9e//oX58+cjLS3N7YMi39I3QYtRadF4f1Num5JSx00WvPTTEdwyNgX9Ej07/U0QBDx2UTqmv7gB72zMwR2TenZ4X64+Ut/eOZZ9pGTkzsm9MOvVP/B9ZmGbk6Lu5nCKWLpmf7P1flKVXJPylJya8tXWparby1XpYaiyopuPX4XPKTVjeErbfqB4W7xWgyprHczWOn7W+AlDlRX6cM+8Lz1pQJIOAJB1soJJKR9RY3OgpMqK7j5+jnaXOyf1xK+HDLjns934fv74s/bZOlhUiUVfZmL38XJcP7I7HrygL7Qa7yxQ0NbPbk99xjenzGz32OIpRKeTRxMW8nl/G5OKHXllZ+09IIoiHl+9D1GhwVgwtf2ltB3RMy4cN41Jwau/HEVRB68+u/pIPXFJf/aRkpnB3SIxvlcsXvn5qMcq7s5mW46pSVPK051eck3kKYbqU8vOaz03fQ/w7lVaT3A6ReQazUiR6cpU8adWYfLkCnxyWW5cCeocThjNVo+9Lz0pTquBPkLNZuc+JL9h5T0mpQAgMECFF68ejNJqK55Ys6/Fc1+t3YH/++9BXPTSRlRb6/DFbaPx9KUDvJaQAoARqdFI1GnQ0qVLAfUtIUakem+WktFs5fQ98gpegiO3mNovDkmRIXh/Uy7+eeWgFrf73/5i/HSwBCtne3fVurun9MI3u07i+XUHsfzqwe16LPtIyd/dU3rhypWbsf6Ae3qHtVdbf6T7+o95kreSSivUgSpEeOjc6ro6W1Lp232liqtqUWt3IlWmy9y7VnIqrqxFD3242/fP3nfeZTTbIIrwyZ5SAJDRRYusAjY79xV5xvpVg5TeU+p0KbFheHxmfzzw5V78b38xyi32hvsSdRpcPbwbvtl9EgXltbhrci/cdm4a1IHen6IeoBKwZGY65n20EwIad9t1JaqWzEz3asW9iT2lyEtYKUVuERigwuxRyVi9pwDG6uZ/sJitdVi6eh8m9dF7PXGgCwnCfef3wVe7TmJnflmbH8c+Ur7hnJRojEyNxis/H4Uoev+KvxxLrkl5DNX11RieOk9FhQYhKEDw+WbnOaeWCE+Ra1JK+1dSyt1cve/ksty4EriSuL56/h9wagU+KT5bqf3yTRaEBAX45GqPnhShqb9Yc3pCCqivYn/xpyMIVKnw/fxxmD+1lyQJKZfpGYl4ffbQhosTLgk6jdd7kzqcIspr7ExKkVe0OSn10ksvNfpTV1eH999/v8ntnvbqq68iJSUFGo0GI0eOxLZtLa9SAABffPEF+vbtC41GgwEDBuD7779vdL8oili8eDESExMREhKCqVOn4siRI578J/ita87pBgHAp9uPN3v/Sz8dgdFsw9KLpUnuXDW8G/p30WLp6n1tnua1dM1+5JSa8dr13q3sova7e0ovZJ6swK+HDV4/tqvkuiVSlFyT8pRUWj36w1cQBMRFaHy+4i+n1IwAlYBuMu2RExIcAK0mEEUV7k3+na33HVD/mcepfO5lqK5/v/hqkqB/kg6l1TYU+3iFpFLkmyzoHh3Ki6incThFPLF2f6vbmG11SI11f2VqR0zPSMTGBydj1dxRuHRIEoICBGy4f5LXK1nLLPVVnkxKkTe0OSn1wgsvNPqTkJCADz/8sNFtL774ogeHCnz22WdYuHAhlixZgp07d2LQoEE4//zzUVJS0uz2mzZtwrXXXos5c+Zg165dmDVrFmbNmoWsrKyGbZ5//nm89NJLWLlyJbZu3YqwsDCcf/75qK317S/dUogKC8aswUn4aEse6hzORvcdKqrCOxtzcNfknugu0Tz3AJWAxy/ujz0nKvDlzhNn3f7b3Sexals++0j5iDE9YjCkeyRe/umI16/oBqgELLqgb4v3i/B+yTUpT0lVLfThnv3hq49Q+/z0vdxSM7pGhSA4UL7F4gk6jdsrpdj7ThollVYIAhAb7ps/7E5vdk7yl2e0SPY9W67Odu4D5HfuC1AJGN0jBhcP7gK7Q0RJC7NQPKns1GqAMUxKkRe0ufQjJyfHk+Nok+XLl2Pu3Lm4+eabAQArV67Ed999h3fffReLFi1qsv2KFSswffp03H///QCAJ598EuvXr8crr7yClStXQhRFvPjii3j00UdxySWXAAD+/e9/Iz4+Ht988w2uueaaZsdhtVphtf51cqisrG8A6XQ64XQ6m32MUtw4ujs++/M41mUVYsaA+oy+0ynika8z0T06FHPGpTT7HDmdToii6PHnb1j3SFw0MBHPrTuI89LjENFCA8NsQzUe/ioTswZ3wRVDkxQfV3fzVLzvnNQDcz7YgU1HSzG6R4xb9302W7KNCAoQoAsJQmn1X8v6BgUIiFAHYVRatCJfR956b1P9Cl8pKaEefa7jItQoqao96zHkHPecUjNSYjz7PHVWvFaDwooat46xuLKmzdu197hyjrfUiitrER0aDJUAn3x+4iOCER0ahL0nynFu7xjGWebyjGZM6Rfn1hj5+vvbk+c+T0uJrl/57mhxFRK9tFiCK96lpxJhkaFBsnteqPPOfF9LHWOfmY9ks9mwY8cOPPTQQw23qVQqTJ06FZs3b272MZs3b8bChQsb3Xb++efjm2++AVCfaCsqKsLUqVMb7tfpdBg5ciQ2b97cYlJq2bJlWLp0aZPbDQaD4iusYgKAwUnhePu3IxBsFhjNdhw2WPBnXhleubwXKkzGZh/ndDpRUVHfs0Cl8uzV67nnxGL9/iI8/10m7hrftcn9tXVO3PbpQcSGBeLuMXEwGLw/HczfeSre6ZEi+sSFYvl/D+DVK7yzuiMA/Hq0DKu2HceiKd0xs38sdp+shtFsR0xYEOLCg3DTqgN4+IudWHx+qtfGJBfefG8rXXFFDUKEiBarh90hPNCJ7BLzWY8h57gfLa7EOd09+zx1li5IRI6x2q1jDKpr2w+zoDpLu48r53hLLb+kHNEhAbJ+vZ1Nr9gQ7Mw1oKQkgnGWMYdTxImyGkQFOdz6evP193fbz301snufBjtFBKoEZOYWoY/OO0kDV7xzSk4lKywVKCkxe+XY5D1nvq+rqqokHU+bk1KbN2+G0WjERRdd1HDbv//9byxZsgRmsxmzZs3Cyy+/DLXaM1nc0tJSOBwOxMfHN7o9Pj4eBw8ebPYxRUVFzW5fVFTUcL/rtpa2ac5DDz3UKNlVWVmJbt26Qa/XQ6vlNK/hqUa8vTEXd3x5uOE2TZAKKnU44uLimn2M0+mEIAjQ6/Ue/8CLiwNuP7cWr/xyFLdM7NNkBaZHvs7C8XIrvr59DFISIjw6FqXyZLwXTBMx7+NdyK8JwvDkKLfuuzlFFbV49qe9OC89HnMnp0MQBCQmND6nPHFxAO77z17MGNy9oYJQKbz53lYyu8OJspo6pCZGt3iedYeUuEr8dqzirMeQa9wdThEFFVb075bm0eeps1Liy7Hj5Em3jvG8WD0S1uej6CzTAl/fXIz7tZEY1zOmzX1p5BpvOaiqO4HEqDBZv97OZmhqGb7aVf96ZJzl60SZBXVOEf2T4xEXp3fbfn39/e069xVX1jbbU09A/ZTp84akybLNQkpMKAy1Kq+dQ1zxdphqEKASkNY1ESoZPi/UOWe+rzUaaRfjaHNS6oknnsC5557bkJTKzMzEnDlz8Le//Q39+vXD//3f/6FLly54/PHHPTVW2VCr1c0m31QqlU+erN1pXVYh3tmY2+T2WrsTd3yyq9WVIwRB8Npz+I+JPfD5nyfw9HcHMHdCD5RU1SIuQoOiihqs2n4cz10+AOlddB4fh5J5Kt7n909E7/gjePWXY/jglhFu3feZnE4R93+5F+ogFZ67fCACAppfseXyYV3x86ESPPLNPgxPiWmyqoq/8+Z7W6nKquqnjCZoQzz6PMfrNDCabXCIQFBA68eRY9xPlltgc4hI1YfLalxnStCFoKTKChGC234kqVTAvef1xv3/2dvkPtcR5k/thd8OG3DTe9sxOi0G90/vg6Hd25bcl2O85cBQbUUPmb/ezmZA10i8/ls2jGY74yxjx8vqE84pse5/vfly3FUq4PGL0zHvo50QgEaJKde5b8nMdARJuOpea9L04cguNXv1uRcEAWUWO6JCgxEo0+eFOu/097XU7+02H3337t2YMmVKw98//fRTjBw5Em+99RYWLlyIl156CZ9//rlHBgkAsbGxCAgIQHFxcaPbi4uLkZCQ0OxjEhISWt3e9d/27JNa1trKPi5yWdlHExSAGQMS8PMhA659awvmf7ob1761BQs/34MRqdG4ang3qYdIHaRSCbhjUk/8dtiAvSfKPXqst37PxqZjRiy/ajCiWmkEKQgCnp41AJogFe77Yk+bV38kaivXinieXuHLtbpfqQRNV90hp7R+CkJqTNhZtpRWvFYDh1OE0c3P8468MoQEqRB3xuvEtdz4gqm98dW8MXj7xuEos9hw2Wub8PcP/sTBokq3jkNJ6lfF9M2V91wyTl2k21fA14Gc5RktUAlAUmSI1EORnekZiXh99tAmFwVd5z5vr2zXHmn68IbPLm8qs9jZ5Jy8ps1JqbKyskbT3H777TdccMEFDX8/55xzcPz4cfeO7jTBwcEYNmwYfvrpp4bbnE4nfvrpJ4wePbrZx4wePbrR9gCwfv36hu1TU1ORkJDQaJvKykps3bq1xX1Sy3xpZZ91WYV4+/emzftFANtzTPjvvpanb5L8XTSwC1Jjw/Dyz0c9dozMExX45/8O4dYJaRjbM/as20eFBeOfVw7CxqOleH9TrsfGRcpkqKpPXnj6x68r6eWrK/DlGs0IChDQJVLe1YoJ2vrxnW2qXXvszC/Dp9uP4+EZ/bD5oSlYNXcUVlwzGKvmjsLGByc3/CgTBAFT0+Px/d3jseKawThSUoULVvyO+Z/uQq4EP4x8mSiKMFRbPZ4s9rRu0SHQagK5Ap/M5ZnM6BIp75VFpTQ9IxEbH5zc4rlPrtJiw3CyvAa1dodXj2s02xDNpBR5SZvPWvHx8Q0r8NlsNuzcuROjRo1quL+qqgpBQc2vZOYuCxcuxFtvvYUPPvgABw4cwLx582A2mxtW47vxxhsbNUKfP38+1q1bh3/96184ePAgHn/8cfz555+48847AdR/8VqwYAGeeuoprF69GpmZmbjxxhvRpUsXzJo1y6P/Fn/kulLvru08xZcquqhjAlQCbj+3B9bvL8aBQvdf2bXY6jD/013om6DFvdP6tPlx43vpcfPYFDy77iAOF0vbUJD8S0mVFSoBiAn3cKXUqdV/it2YLPGmbIMZ3aNDEXiWqYdSi9e5nmf3JP8cThGPfZOFjCQtrhuZ3LDc+CWDkzC6R0yzUwRVKgGXDE7Cjwsn4ulZA7Al24ipy3/Dw19noqiZC1AOp4gt2UZ8u/skNh8z8jMUQGVNHWx1zoYKQ18lCAIyknTIYqWUrB03WZAcEyr1MGStLec+uUnTh0EU6y+qeJPJbEN0OJNS5B1t7ik1Y8YMLFq0CM899xy++eYbhIaGYvz48Q337927Fz169PDIIF2uvvpqGAwGLF68GEVFRRg8eDDWrVvXUMGVn5/faD7kmDFj8Mknn+DRRx/Fww8/jF69euGbb75BRkZGwzYPPPAAzGYzbr31VpSXl2PcuHFYt26d5M2+fFFbv3RJ/eWsPRVdo3vEeG9g5FazhiRhxU9H8MovR/HqdUPduu8n1uxHYUUt1t49rt1XJB+c3hcbj5Ri/qe78c0dY6DmXH1yg5JKK6LD1B7/gh0TpoZKqE+C+aJco7nJ4hZyFBumRqBKcFul1Mdb87CvoBJf3z6m3a+RoAAVrhvZHZcNTcKHm/Pw2q9H8eWOE7hxdDLmndsT0WHBWJdVhMdXZ6Gk2t7wuESdBktmpsu+CsGTXBfh4ry0lLsnZSTp8N3eQqmHQa3IM1owsGuk1MMgN0vThwMAcgxm9E3w3oJaJrMNPU4dm8jT2vxr6sknn0RgYCAmTpyIt956C2+99RaCg//Knr777rs477zzPDLI0915553Iy8uD1WrF1q1bMXLkyIb7fv31V7z//vuNtr/yyitx6NAhWK1WZGVlYcaMGY3uFwQBTzzxBIqKilBbW4sff/wRvXt7byl5fzIiNRqJOg1a+roroP5L6ojUaG8OqwlfqeiizgkKUGHeuT3wfWYhjpZUu22/P2QW4tPtx7FkZnqHPqw1QQF48ZrBOFpSheXrD5/9AURtYKiu9UrfmgCVAH2E2neTUqVmpMi8nxRQX6UUF6FGcSsXUNqqtNqK//vvIVxzTjcMaWPT8uZoggIwd0IaNjwwCbdN7IFPtuZjwvO/4M5PduKOT3Y1SkgB9SuTzvtoJ9ZlKTeRUeKlabXekJGkw8nyGlTU1Ek9FGqGKIrIN7JSyh9FhQZBFxKEbC9PnzZx+h55UZuTUrGxsdiwYQPKyspQVlaGSy+9tNH9X3zxBZYsWeL2AZLvCFAJWDIzHQCaJKZOX91C6lJZX6noos67YlhXxEdo8Nov7uktVVhRg0VfZWJ6/wRcfU7Hm+H376LDvef1wZsbsrEl2+iWsZGylVRavVaNERehgcEHk/Z2hxPHy2qQ4gOVUkD9SofuqJRa9v1BBKgEPDC9rxtGBURognDPtN7Y8MAkXDW8K9buLWx2OrzrNiVPh3f1evP1nlIAkNGlvkLjYIlF4pFQc8osdlRZ65AczaSUvxEEAWn6MBwzuO8C69mIoogyiw0xnL5HXtLupgo6na7Rsud5eXnYv38/IiMjG1VOkTL5wuoWvlLRRZ2nDgzAPyam4ds9Bcjr5Fx8h1PEPZ/tRkhQAJ69fAAEoXPJ1bnj03BOSjTu/XwPKmrsZ38AUStKqqzQe7iflEtchNonG50fN1ngcIpI85GkVIJW0+neXdtzTfhy5wk8OL2v2694x4SrMS299ZWK5bTAiRRKqmoRrg5EaHCbu2XIVkpMGMLVATjEpJQsub7jdGNSyi+lxXp3BT6zzQm7Q2SlFHlNm5NS7777LpYvX97otltvvRVpaWkYMGAAMjIyPLr6HvkOua9u4SsVXeQe147ojqjQILz+67FO7eeNDcewNceEF64ejMjQzn9IB6gELL9qECpr7FjybVan90fKZqjyYqWU1jen77maxPpMpZRW02xD8baqczjx2DdZGNQtElcP73hlZ2s4Hb51JZVWv5i6B9RPKU1P1DIpJVP5pvq4cPqef0rThyHbYIYoeqfqtOzUxVImpchb2pyUevPNNxEV9VcvgnXr1uG9997Dv//9b2zfvh2RkZFYunSpRwZJvkfuq1v4QkUXuYcmKABzx6fhy50ncLK8pkP72HO8HMv/dxi3Tezh1ub3XaNC8cSs/vhmdwFW7ylw235JWURRhMGLlVL6iM5X8Eghp9QCdaAKCVrfmJqd0Mnpex9szsOh4io8dUkGVB76DOZ0+NaVVFn9YuqeS/8kHZNSMpVntCA6LBgRGs+uhE7SSIsNQ0WNHSazzSvHK7fU945jUoq8pc31xEeOHMHw4cMb/v7tt9/ikksuwfXXXw8AeOaZZ3DzzTe7f4REHjI9IxHT0hOwLceEkqpaxEXUT9mTWwKNOm/2qGS8/tsxvPHbMTxxScbZH3Aas7UOCz7bjfQuWtwz1f2LIMwanISfDpTg0a8zMTw5Cl0iQ9x+DPJvlTV1sDmciPNSsiVeq0ZptRUOp+hT50tXk3NPJWjcLUGrQVVtHSy2unZP/yqprMUL6w/j+pHdMaCrzkMj/Gs6fFFFbbN9pQTUJ9eUOh3e4GdJqQFdtHjvj1xU1tgRGeY//y5/kGe0oDun7vmthhX4Ss2I8cIFqLIaJqXIu9pcKVVTUwOt9q9lKDdt2oQJEyY0/D0tLQ1FRUXuHR2Rh8m9oovcI0wdiDljU/Hp9uMoaWflwdI1+1BcWYsV1wxBcGC72/CdlSAIeHrWAIQGB+K+L/bAqdCGwNRxDcvOe+nHb1yEBk4RMJp9awpfTqkZqT4ydQ9Aw3TMjkzhe/r7AwgOVOH+89zT3Lwlp0+Hb44IZU+Hd13w8hf9TzU731dQKfFI6Ez5JjOn7vmx5JhQCAKQbfBOX6mK2vqkVJQb2lUQtUWbf2ElJydjx44dAIDS0lLs27cPY8eObbi/qKgIOp3nrsYREXXGTWNToA5U4c0N2W1+zHd7C/H5nyfw+MX9PfpjVhcahH9dNQibjhnx7h85HjsO+acSL6/w5Up++Vqz85xSs8/0kwLQMM2wvVP4Nh8z4tvdBVh0QV/oQj0/lWd6RiJevW4I4sIbHysoQEBchBoTe8d5fAxyVeLFXm/ekKYPhyZQxaSUDOWbLFx5z49pggKQFBmCY6XeWYGvzFIHXUgQggLcfzGWqDltrge/6aabcMcdd2Dfvn34+eef0bdvXwwbNqzh/k2bNiEjo33TYoiIvEWrCcLfxqTg7d9zMO/cHmctfz5ZXoOHvtqLCwck4sphXT0+vrE9YzFnXCqeX3cI43rFom+C9uwPIsJfy857qyLD9SPb4EPNzmvtDhRU1CA11nd+tLl6HrYn+Wd3OLH42ywMS47CFUM9f95ymZ6RgEGxAvIsgTBU2xAXoUFMeDBmvrwRz//3IJbM7O+1schFrd2Bqto6v2l0DtRXxvXShyDzZIXUQ6HT1NodKK60onuM7yTdqf1SY8OQ46VKqfKaOk7dI69qc/rzgQcewNy5c/HVV19Bo9Hgiy++aHT/H3/8gWuvvdbtAyQicpdbxqZCEIB3NrZejeRwirjns90IVwfimUsHQBC8M/Xk/vP7IDU2DAs+3Y1au8MrxyTfV1JViwh1IEKCA7xyvNhwNQTBt1ZUO26yQBTrl7X3FaHBgYjQBLarUurdjTk4ZqjGkx5sbt6SAJWAUWl/TYfvHR+B+8/vg/f+yMWWbKNXxyIHBi9XMHpLn7hQVkrJDFfeU4Ye+nBkl3orKWVHtBcqbYlc2pyUUqlUeOKJJ7Br1y788MMP6NevX6P7v/jiC8yZM8ftAyQicpeosGDcMCoZ/96chwqLvcXtVv52DNtzTVh+9WCvTH9x0QQF4MVrBiPbYMa//nfIa8cl31ZS6d1mykEBKkSHBqPYh6bvub7Ip+p9JykF1E/ha2tPqcKKGqz46QhuHJ2C9C7yqLS8ZWwqRqRE4/7/7IHZWif1cLzqr15v/tNTCgD6xoUix2hGtcLiKWd5xlNJKU7f82tp+jDkGc1weKH3KCulyNs4UZSIFOXv49Ngdzjx3qbmq6V25Zdh+frDuOPcnhiVFuPl0QH9ErW4//w+eHtjDjYdLfX68cn3GKq9v8JXnFbjU5VSuaVmhAUHQO+FVYvcKUGnQXEbK6WeWnsAocGBWHie+1cJ7SiVSsD/XTkQpVU2LPvhgNTD8SrXtEt/mr4H1FdKiSKwn9VSspFnNEMTpPK7qjxqLDU2DHaHiBNlFo8fi0kp8jYmpYhIUfQRalw7ojve+yMXVbWNq6WqrXWY/+luDEjSYf7UXhKNEJgzLhWjUmNw7xd7Wq3oIgLqf/zGab1bjREXofapRue5xvom596aiusu8VpNm6bv/X7EgO8yC/HIhX2h1chrykVyTBgemtEXH23Jx8Yjykm0l1RZERQgINLPpsCkRocgOFCFLPaVko18kwXdo0N97vxG7ZOmDwfgnRX4ypiUIi9jUoqIFOcfE9NQY3Pgg825p1aqOonNx4xY/E0WjNVWrLhmsKQrjqhUAv511SBUW+vw2LdZko2DfENJVa3XK4DiItQNq/75Al9bec8lQatB8Vmm71nrHFjy7T6MSI3GrMFJXhpZ+8wemYwxPWLw4Jd7m1wM8FeGKiv04Wq/SxQEBgjomxCBrAImpeQiz2hB92jfO79R+yRqNdAEqbzSV4qVUuRtbV59j4jIXyTqQjAyLRr/+t9hiGdMzb9pdDKSZdAMuUtkCJ6alYH5n+7GpD56JOhCUFJVi7gIDUakRiPAy02MSb4MEiw7H6dVY9Mx32lenVNqxjkp0VIPo93idRqUVFnhdIotNi5/+/cc5JkseH32MNkmQFQqAc9dPhDTX9yAp787gGcvHyj1kDyupKoWei9XMHpLRhct/swrk3oYdEq+yYLJfeOkHgZ5mEolICUmDNmGao8ep9buQI3dyaQUeRWTUkSkOOuyCvF7C9NI/r05D6N7xGB6RqKXR9XUJYOT8OHmPCz8fA9Oz50l6jRYMjNdFmMkadXaHaisrZOgUqq+p5QoirJNhLhYbHUorrT61Mp7LglaDeqcIkrN1mYbZp8os+Dln4/glrEp6JMQIcEI265bdCgevSgdD32VifMzEjCpj3//iC6psvpdPymXjCQdPt1+HDU2h9dW/aTmOZz1PYa48p4y9NCHe3z6nslsAwAmpcir2j0/xeFw4J133sF1112HqVOnYvLkyY3+EBHJmcMpYuma/a1us3TNfq+sbnI267IKsSOvDGeOpKiiFvM+2ol1WYWSjIvkw7XsvNcrpSLUsDtElPlAz7Pc0vqmsL44fS/+VFyLK5qfKvnEmv3QhQRh/lT5NDdvzTXndMOE3nos+nKv3/fLK6n036RU/y5aOEXgQBGbnUutsKIGdoeI7lx5TxHS9GHI8fD0PSalSArtTkrNnz8f8+fPh8PhQEZGBgYNGtToDxGRnG3LMaGwlR4tIoDCilpsyzF5b1DNcCXPmkuNuW6TS/KMpOPq6+TtZeddjdV9YQW+XGP9F/hUH0xKJZx6nptrdv7LwRL8b38xHr0wHeFq3yh8FwQBz10+ABabA0vX7pN6OB4lxaqY3tI7PhxBAQKbnctAvrE+6S6HtgPkeamxYSiqrIXZWuexYzApRVJo97eYTz/9FJ9//jlmzJjhifEQEXlUW39ES/1juz3Js9E9Yrw3MJIVw6nXqbd//LoqQEoqreib4NVDt1tOqRm6kCBE+eAqaDHhagSoBBSfkZSqtTvw+Jp9GNszBhcN9K1pvIm6ECy+KB33/2cvLshIxLT0eKmH5HYOpwhjdfNTLv2BOjAAveMjmJSSgTyTBSoBSIoMkXoo5AWuFfhySs3ISNJ55BgNSalQJqXIe9pdKRUcHIyePXt6YixERB7X1h8JUv+Y8JXkGUnLcGrZeW8nXFxJMF9Ygc+18p7ce181J0AlIC5C3SQp9cZv2Sgor8HSizN88t91xbCumNI3Dg99lYmyUz+A/Imx2gqnCL+dvgcAA5J0yDzJ6XtSyzNakKgLQXAgF1RXAlfFrydX4DOabdAEqtgvjryq3Wewe++9FytWrIB45pJVREQ+YERqNBJ1GrT0M05AfSPxEanSrtTlK8kzklaJRMvOa4ICoAsJ8omkaG6pGak+3AQ4XqtB0WlVk/lGC1779Sj+Pj4NPePCJRxZxwmCgGWXDYDd4cTi1f43ja9Eol5v3tQ/SYcjxVWotTukHoqi5ZvMbHKuILqQIMSGB3t0Bb4yix2RIb4xJZz8R7tfcRs3bsQvv/yCH374Af3790dQUOOrs1999ZXbBkdE5G4BKgFLZqZj3kc7IQCNeja5ftYvmZmOgBaWX/cWV/KsqKK22b5SgDySZyStkkrp+tbERahRUin/SqlcoxnjesVKPYwOS9BqGnpKiaKIx9fsQ0xYMO6a7NtV63FaDZ64pD/mf7obF2QkYMYA35qG2BrXAgT+2lMKADK6aFHnFHG4uAoDu0ZKPRzFyjNaMLCrZ6ZxkTylxXp2BT6T2YaoUCalyLvaXSkVGRmJSy+9FBMnTkRsbCx0Ol2jP0REcjc9IxGvzx6KBF3jKqMEnQavzx6K6RnS/zhyJc8AtFjVJYfkGUmrvpmyNNVy8VqN7CulKmvtKK22+WSTc5c4rRo5pdX4dvdJvPrLUfx8sASLZ6YjNNj3fzRcPKgLpvdPwKPfZKG0Wv4JzrYqqaqFIACx4f6blOqXqEWASkAm+0pJRhRF5Bst6B7tu+c3ar/UWM+uwGcy21gpRV7X7lfce++954lxEBF51fSMRExLT8C2HBNKqmoRF1FfdSSnJI8rebZ0zf5GTc+jQoNQZrGj5XQVKUVJVS0GJEVKcuy4CDXyTRZJjt1WuaW+u/IeAKzLKsTXO0+iylqH+Z/uBgAEB6rgLx0UBEHAU5dm4LwXNuCxb7Lw2vVDfbJH1plKKq2IDg1GUID/9vnRBAWgV1w4sthXSjJlFjuqrHWcvqcwafowrN1bAFEUPXK+NJptiGelFHkZX3FEpFgBKkH2K9c1lzw7JyUK//hwB5aszsLYnjGI0PjeqmLkHoYqq2TNlPVaNf7MK5Pk2G3lupqc4oNJqXVZhZj30c4m03dtdU7c/vFO2VR1dlZsuBpPXpKBOz7ZidV7CnDJ4CSph9Rp9RWM/lsl5dK/iw77ClgpJRXXRYHu0UxKKUmaPhxmmwMlVVbEa91fKW0y29A7xvc+M8m3degSzn/+8x9cddVVGDVqFIYOHdroDxERuZcreXbJ4CSM7hGDwAAVnpyVgeraOjy/7pDUwyOJOJwiSqttkjVTjouon74n54VPckstiAkLhtbHErcOp4ila/a32E8OAJau2Q+HU77PfXtcODARFw1MxOJv96GkUt5TQttCyl5v3jQgSYuDhVWw1TmlHooi5Rnrk+6slFKWhhX4PNRXqsxsQ1SIb31mku9rd1LqpZdews0334z4+Hjs2rULI0aMQExMDLKzs3HBBRd4YoxERHSGLpEhuO/8Pvhoax525JmkHg5JwGS2weEUoZeob01chBq1dicqa+skOX5b5JRW++TUvW05pkZTds8kAiisqMW2HP957z95SQaCAlR4+OtMWSc628JV1ervMpJ0sDmcOFJSJfVQFCnfaEF0WDCrpRWme3QoAlQCskvdvwJfncOJ8hquvkfe1+6k1GuvvYY333wTL7/8MoKDg/HAAw9g/fr1uPvuu1FRwRJeIiJvuXF0CgYm6fDQV5m8Uq1AhoZl56X58euaNmiQcbPzHKPFJ6futbWBvNwbzbdHVFgwnrk0Az8eKMGXO09KPZxOKamySlbB6E39ErUQBGAf+0pJIs9kQTdO3VOc4EAVukeHIscDlVL1/UrBpBR5XbuTUvn5+RgzZgwAICQkBFVV9VdHbrjhBqxatcq9oyMiohYFqAQsu2wgjhnMeOO3Y1IPh7zMlZCQqqeUq5dFSaV8V03LLTX7ZKVUW6ts/K0a57z+CbhsSBKWrtmHwooaqYfTIaIowlBllayC0ZvC1IHooQ/nCnwSyTdakMyklCKlxoYh2wMr8JnMNgBAFJNS5GXtTkolJCTAZKovF+/evTu2bNkCAMjJyfH5cmsiIl+T3kWLWyek4eWfj+KYwf2l3CRfJacqpaRadt5VCeIah9yUmW2oqLEjxQcbto5IjUaiTtPi+poCgERd/Yqh/mbJzP4IDQ7Ag1/65jS+yto6WOuciqiUAoCMLlpksdm5JPJMZvaTUqi02DBke+A7n9Fc/3muY1KKvKzdSanJkydj9erVAICbb74Z99xzD6ZNm4arr74al156qdsHSERErZs/pRcSIzV4+Cvf/BFHHWOosiIqNAjBgdIsOx8aHIhwdaBsp5C5riL7YqVUgErAkpnpANAkMeX6+5KZ6QhQuX85cKnpQoPw7OUDseGwAau25WPzMSO+3X0Sm48ZfaKxu6GhgtG/qthakpGkw4HCStQ5OIXcm2rtDhRXWrnynkKl6cNxvKzG7a0bysz10/dYKUXe1u5X3Jtvvgmns/4NcMcddyAmJgabNm3CxRdfjH/84x9uHyAREbVOExSAp2cNwOx3tuKLP0/gqnO6ST0k8gJDlVXyH75xEWrZTt/LPZWUSon1zR9t0zMS8frsoVi6Zn+jpucJOg2WzEzH9IxECUfnWZP6xGFsjxg88nVWoxUIE33g3+56P0g1rdbbMpJ0qLU7ccxgRp+ECKmHoxj5JgsAINkHK0Gp81Jjw+Bwisg3WdAzLtxt+zWZrQgKEBCuDnDbPonaot1JKZVKBZXqr6uy11xzDa655hq3DoqIiNpnXK9YXD60K57+/gAm9Y1TxHLkSmeokn7ZeX2EGsUynb6XazQjXqtGaLDvXvGdnpGIaekJ2JZjaljRbURqtF9WSJ1uXVYhNh0z4sy6qKKKWsz7aCdenz1UtokpQ3X9+0Hq96a3pHfRAgCyTlYwKeVFeUZXUso3k+7UOT309cnIbEO1W5NSRrMNUaHBEAT//owh+elQzf/vv/+O2bNnY/To0Th5sn6FlA8//BAbN2506+BOZzKZcP3110Or1SIyMhJz5sxBdXXrc2lra2sbqrnCw8Nx+eWXo7i4uNE2giA0+fPpp5967N9BROQpj1zYDwEqAU+s3S/1UMgL6pMU0v7wjdNqUFIpz+l7OaVmn+wndaYAlYDRPWJwyeAkjO4R4/cJKYdTxNI1+5skpAA03LZ0zX7ZTuUrqbQiLDgAYWrfTYa2h1YThNTYMDY797J8kwWaIJXknwEkDX2EGuHqQOS4udm5yWxDVFiwW/dJ1BbtTkp9+eWXOP/88xESEoJdu3bBaq2/IlRRUYFnnnnG7QN0uf7667Fv3z6sX78ea9euxYYNG3Drrbe2+ph77rkHa9aswRdffIHffvsNBQUFuOyyy5ps995776GwsLDhz6xZszz0ryAi8pzosGA8dlE/rNlTgF8Olkg9HPKwEhlUSsVHqGGQcaVUmt73k1JKsy3H1Gi64plEAIUVtdiWY/LeoNqhpKoWcVpl9JNy6d9Fi31sdu5V+UYzukeHsqJFoQRBqF+Bz+DepJTRbEN0KJNS5H3tvozz1FNPYeXKlbjxxhsbVRSNHTsWTz31lFsH53LgwAGsW7cO27dvx/DhwwEAL7/8MmbMmIF//vOf6NKlS5PHVFRU4J133sEnn3yCyZMnA6hPPvXr1w9btmzBqFGjGraNjIxEQkJCm8djtVobknEAUFlZCQBwOp0N/baofZxOJ0RR5POnEIy351w8MBFf7TyJR77JxH/nj5f8aj1j7TmGKitiw4MlfW71EcEoqaptMgap4y6KInIMZlw0IJGvPS9wZ7yLK2vatN2R4kqMTI3q9PHcrbiyFnqJ35ee0lKc+3fR4ueDJairc0Dl55V8cpFrtKB7dKhXXmdSn8+peamxoThmqHZrXEzVNkSHBTHeCnDm+1rqeLf718qhQ4cwYcKEJrfrdDqUl5e7Y0xNbN68GZGRkQ0JKQCYOnUqVCoVtm7d2uyqfzt27IDdbsfUqVMbbuvbty+6d++OzZs3N0pK3XHHHfj73/+OtLQ03Hbbbbj55ptbvfKwbNkyLF26tMntBoMBtbXynMYgd06nExUVFRBFsVHPMvJPjLdnLRiXgOs+3IenV+/BgonSNj1nrD3DbHPAYnNAI1pRUiJdVZxatKLa6kDeyUKEBP3VGFXquBvNdphtDkQF1kn6/CiFO+MdVNe2pNTjq/fjv5kncWF6DMal6iRbhfJMBaZq6DSBfvm6aynOXUOdsNgc+PPwcaREK6tKTCo5hkqMSdF55XUm9fmcmhcXAvx+pMqtr4GSSguSwsNQXl7OePu5M9/XVVVVko6n3UmphIQEHD16FCkpKY1u37hxI9LS0tw1rkaKiooQFxfX6LbAwEBER0ejqKioxccEBwcjMjKy0e3x8fGNHvPEE09g8uTJCA0Nxf/+9z/cfvvtqK6uxt13393ieB566CEsXLiw4e+VlZXo1q0b9Ho9tFptB/6F5HQ6IQgC9Ho9T4AKwHh7VlwccM9UO57/7yFcM7onBnbVSTYWxtozsk/1keiRpEdcXIxk4+hZFQAgF6JGi7jT+jdJHffcU1O7BvVIRFwcmy97mjvjfV6sHgnr81FcWdtsXykBQJxWjTvO7YGvdxXg4e+yoQsJwsWDEnHFsK7I6KKVdEpTee1BZHTTNvne6g9aivPY8EjgqyMorA3ECD/8d8uNwymisNKGvl1jvfI6k/p8Ts0bkFyHt7cUQhMRBW1IkFv2WWnNQlKsDpGROsbbz535vtZopL2g0O6k1Ny5czF//ny8++67EAQBBQUF2Lx5M+677z489thj7drXokWL8Nxzz7W6zYEDB9o7xHY5fcxDhgyB2WzG//3f/7WalFKr1VCrm/bxOHNlQmofQRD4HCoI4+1Zfx+fhtV7CvHw11lYfedYBAZI9zwz1u5nrLYBAOJ1IZI+rwm6+i8xhiob0vSNkz9Sxj3fVANBAFJiw/m68xJ3xVulAh6/OB3zPtoJAWiUmHKlmpZe3B/TMxJx45hUHC2pxn92nMBXO0/gwy356BMfgSuGdcUlQ7ogLqL5L9kOp+ixFQ1LqqyI10r7vvSk5uIcHa5BUqQGPx4ohkolKGaVSKkUVFhgd4hIjg3z2uuMn+Py0+PUBZccowVDund+KrMoiigz2xAdrma8FeL0OEsd63YnpRYtWgSn04kpU6bAYrFgwoQJUKvVuO+++3DXXXe1a1/33nsv/va3v7W6TVpaGhISEpqUJtbV1cFkMrXYCyohIQE2mw3l5eWNqqWKi4tb7R81cuRIPPnkk7Barc0mnoiIfEFggArPXj4As179A+9szME/JvaQekjkRiWnmotLvfKSq6FzicyanWeXmtFFFwLNaVMKyXdMz0jE67OHYuma/Y2anifoNFgyMx3TMxIbbusZF45FF/TFfef1xsajpfjPjhP4v/8dwrPrDmJSHz2uGNYVk/vGN0zvW5dV2GS/ic3styNq7Q5U1tZJ/r70tnVZhTBW2/BdZhG+y6yfjeCu55SayjdaAADJ0aESj4SklBpbX52cU2p2S1KqsqYOdU4RMVx9jyTQ7qSUIAh45JFHcP/99+Po0aOorq5Geno6wsPD231wvV4PvV5/1u1Gjx6N8vJy7NixA8OGDQMA/Pzzz3A6nRg5cmSzjxk2bBiCgoLw008/4fLLLwdQ3w8rPz8fo0ePbvFYu3fvRlRUFBNSROTzBnaNxM1jU/HCj4dxQUYiusfwC6y/MFRZoQlSIVziRvYR6kBoglSyS0rllpobvrCTb5qekYhp6QltrmgKDFDh3D5xOLdPHCosdqzeW4D/7DiB2z7aiajQIFwyOAlddBos++Fgk2mBRRW1mPfRTrw+e2inkiiulSilXhXTm9ZlFWLeRzs99pxSU3kmC1QC0DWKn+lKFqYORIJW47YV+EyW+grs6LBgAA637JOorTr8bTY4OBjp6enuHEuL+vXrh+nTp2Pu3LlYuXIl7HY77rzzTlxzzTUNK++dPHkSU6ZMwb///W+MGDECOp0Oc+bMwcKFCxEdHQ2tVou77roLo0ePbmhyvmbNGhQXF2PUqFHQaDRYv349nnnmGdx3331e+XcREXnawmm9sS6rCI98k4l/3zKCy0f7iZIqK+IiNJLHUxDqp+qUVMlrkY9coxnDU+S3Mhu1T4BKwOge7e+ZpgsNwg2jknHDqGQcKa7Cf3acwJc7T6D01LTXM4monxq4dM1+TEtP6PC0s4YKRq0yklIOp4ila/Y32/vLXc8pNZVvsiBRFyKb5v4knTR9GLJLq92yL5O5/vxVn5Rq24ITRO7S5qTULbfc0qbt3n333Q4PpjUff/wx7rzzTkyZMgUqlQqXX345XnrppYb77XY7Dh06BIvF0nDbCy+80LCt1WrF+eefj9dee63h/qCgILz66qu45557IIoievbsieXLl2Pu3Lke+TcQEXlbmDoQT83KwM3vb8c3u0/i0iFdpR4SuUFJVa1sqjHiItQwVMqnUsrpFJFrNOPK4dKuPEny0Cs+Ag/N6IfxvWIx+51tLW4nAiisqMW2HFOHEmEOp4iNRwwA6qdX9YqL8PtEzLYcU6NpkGfq7HPqSzzZp+xM+UYLkln5TKifwrcjr8wt+3L1qowOC4bTwqQUeVebk1Lvv/8+kpOTMWTIEIhic9dEPCs6OhqffPJJi/enpKQ0GZdGo8Grr76KV199tdnHTJ8+HdOnT3frOImI5GZS3zjMHNQFT649gIm9405dBSNfZqiyyqZvTZxWjWIZVUoVVdai1u5Eaix/tNFfjObmq6TOdO/nuzG6RywGJGmRkaRDv0Qtws4yTfbMPlW3frhDET2V2lohKbdKSnfzZJ+y5uSZzBiQJN2quiQfafpwfLnzBJxOEapOJkFNp86RkSFBMFnOsjGRm7U5KTVv3jysWrUKOTk5uPnmmzF79mxER0d7cmxEROQmiy9Kx9Tlv+Hp7w7gX1cNkno4suDNK9vuZqiyIk0mPZPiIjQ4Uuye6QPukFta318jJUYezw/JQ0sr8Z2pb6IWR0qqsGZPAWwOJwQB6KEPR0aX+iRVRpIO6V200Grql2BXck+ltj6nbd3OF3k7/qIoIs9owYwB/vmaovZJ04eh1u5EQUVNp3uMGc02RIYGSbpaMylXm5NSr776KpYvX46vvvoK7777Lh566CFceOGFmDNnDs477zzJ+1oQEVHL9BFqPDKjHx74ci8uG5qEsT1jpR6SpLx9ZdvdSqqs8pm+p1XLqtF5jtGMAJWAblyZik4zIjUaiToNiipqm+2BJKB+db+3bhyOAJUAW50TR0qqsO9kJTJPViCroALr9hWh1u4EAKTEhKJ/Fy02HClVbE+ltj6nI1L98yK2FD21yi12VNXWITmaSXdCw8WpnFJzp5NSZWYbK+lJMu1KharValx77bVYv3499u/fj/79++P2229HSkoKqqvlc5WUiIiaunJ4V4xKi8bDX2ei1q7clVVcV7bP7IXiurK9LqtQopG1jd3hhMlsk031QVyEBhU1dtm8pnJLzegWFYIgXu2l0wSoBCyZWb9Az5npAdffl8xMb0geBAeq0L+LDled0w1PzsrA17ePRdbj5+N/90zAv64chEl943CsxIyq2roWj3l6TyV/1N7n1N+0p6eWu+SdmlfFnlIE1K/AGBygcssKfCazDTFMSpFEOvyNTaVSQRAEiKIIh0MeX0SJiKhlgiDgmUsHoLCiFit+OgKHU8TmY0Z8u/skNh8zwuH0fr9AbzvblW2g/sq2nJ+L0upTy87LZIUvV28rg0yqpXJKzUiRydRGkpfpGYl4ffZQJOgaJ3QTdJo2TbMKDFChd3wELh/WFUtm9se8ST3adFx/7qnU2efUl0nRUyvPWJ986M6kFKE+MZwcE4qc0s4npYyslCIJtXn6HgBYrdaG6XsbN27ERRddhFdeeQXTp0+HSsUrkkREcpemD8ddk3rihR8P44s/jzdaIt2Xpq91lD+sFlVyaqU7fbhMklKnkmMlVVZZTJnLKTVjfC+91MMgmZqekYhp6Qlu6SfHnkr1Tn9O9xwvx7PrDuLJS/pjanqC1EPzKCnin2+0ICo0qKGnGVFqbBiOGTo/Y8lktiEjSeuGERG1X5szSbfffjsSExPx7LPP4qKLLsLx48fxxRdfYMaMGUxIERH5kJTYMDhFNEpIAb4zfa0z/GG1KFdFUpxsKqXqf3CVVEr/nDmcIo6bapDKSilqRYBKwOgeMbhkcBJG94jp8PQyV0+llh4toD7Z7689lU7nek7/MTENPePC8X1WkdRD8rgRqdGIDW+5ssQT8c8zWdCdizjQadL04W6bvsdKKZJKmyulVq5cie7duyMtLQ2//fYbfvvtt2a3++qrr9w2OCIici+HU8Qz3x9o9j4lNOb1h8qGkiorVAIQEyaPpFRUaBCCAgRZNDsvKK+BzeFkUoq8wtVTad5HOyEAjaYFK6GnUnMEQcCFAxLx7sYcWOscUAcGSD0kjxFFEWHqQJRW25rE38Xd8c83WZAsg4pUko+02DAUVNSg1u6AJqjj77f6pJQ8vleQ8rS5xOnGG2/EpEmTEBkZCZ1O1+IfIiKSLykas8pFrd2Br3aeaHUbX6hsMFRZEROuls0PXUEQEBehkUV1WfapvhpMSpG3KLmnUksuHJiIKmsdfj9cKvVQPOq1X4/hRFkNHpzet0n8AWDB1N5uj3++0cIm59RImj4MogjkGjteLVVjc6DG7mCjc5JMmyul3n//fQ8Og4iIvMEfpq91RL7Rgnkf78DRkmrcMDoZH23OA+CblQ31fXDkdTVTH6Fu6HUlpdxSM4IDVOgSGSL1UEhB3Nmnyh/0jo9A7/hwrN1bgKnp8VIPxyMyT1TgpZ+O4I5ze2DeuT1w64S0hvjrw9X41/8O4ds9J3HbuWluqxartTtQVFkri959JB9p+nAAQLbBjL4JHesJZTTXf35z+h5JpV2NzomIyLf5w/S19vrpQDHu+Ww3osKC8dXtY9C/iw5je8Rg6Zr9jarGEnyk0XtJlRV6mSWl4iLUspi+l1NqRrfoEMUmA0g6rp5KVO/CAV3w5oZjnZ5SJEe1dgfu+Xw3+iZG4M7JvQA0jX9shBozVvyOlb9mY/7UXm457nGTBQA4fY8aiQoNgi4kqFMr8JnM9T1GmZQiqbBDORGRgiipMa/DKeL//nsQcz74EyPTYrD6znHo36V+mvn0jERsfHAyVs0dhd7x4RjUTYeND06WfUIKqJ++J7dKqTitPJJSuUYzUmPDpR4GkeJdODABZpsDvx02SD0Ut/vnfw8h32TB8qsGIziw+Z9SveMjcOuENLz6y1Fku2FlNADIM55KSrHROZ1GEASk6Tu3Ah+TUiQ1JqWIiBTE1ZgXQIuJKblPX2uL0morbnhnK17/9RgWXdAXb94wDLqQxktou65sXz60Kw4VVaHO6ZRotO1Tn5SSVyVbXIRGFqvv5ZSakRrLKgIiqfWMi0DfhAh8t9e/VnPdkm3EO3/k4P7z+qB3fESr2941uRcSdBo8+k0WRLG5Nujtk2eyQB2okt1FCZJeWmznVuBjUoqkxqQUEZHCtNSYVwAwpkeMT1QLtebPXBMufOl3HC6uxsd/H4XbJvaAILScZBvfS49auxN/5pZ5cZQdI4oiDDKcvhevVcNotsHukC6xZ3c4caKsBilsck4kCxcNTMSPB4pRa3dIPRS3qKq1474v9uCclGjcMi71rNuHBAfgyVkZ2HTMiK93nez08fONZnSPDoXKxy8akful6cOQbajucPLTZLYhLDjA76baku9gUoqISIFOn7624prBWDV3FJZdNgB/HDPi+0zfvLItiiLe3ZiDa97cgu7Rofju7nFt6vHSLzECseFqbDgi/2kmFTV22BxO2V0pd1VulVZLN4XvuMkCh1NEKqe2EMnCjAGJsNgc+PVQidRDcYun1h5AmdmGf105qM3VxBN76zFzUBc89V39Yzsjz8SV96h5abFhqKyta6h4ai+j2YbocFZJkXSYlCIiUijX9LVLBidhdI8YXH1ON8wYkIBFX+5FQXmN1MNrl2prHe5ctQtPrN2Pm8em4JO5oxCvbdsUN0EQMKFXLDb4wPLlrr5NcVp5JaVclVtSrsDnWg47Vc+kFJEcpOnDkZ6oxVo/mML34/5ifPbncTx2UXq7V7977KJ+sDucWPbDgU6NId9kQfdont+oqYYV+DrY7NxUbUN0KJNSJB0mpYiICEB9cmbZpQMRpg7EPZ/thsPZ+R4Y3nC4uAoXv7IRvx0y4PXrh+KRC9MRFNC+j7cJvfU4UFiJkirp+yK1xnAqKaUPl1lPqVNJMimbnWcbzNAEqRAvs35bREp24cBE/HSgBDU2353CZzLbsOirTEzuG4erz+nW7sfHRWiw6IK++PzPE9iabezQGBxOESdMNayUomYlx4RCEICcDvaVMlls7CdFkmJSioiIGuhCg/DC1YOxLdeElb8dk3o4Z/Xt7pO45JU/EKRSYfWdY3HBgI71wxrXKxYAsPGIvKulXEkzuVVKxYSpoRKAYgmbnecazUiJCWO/FSIZuXBAImrsDvzio1P4RFHEI19nwuF04tnLB7Tan7A1157THUO7R+LhrzNhrWt/gq6oshY2hxPdmZSiZmiCApAUGYJjpR1bgc9ktiE6TF7fK0hZmJQiIqJGRqXF4PZze+CF9Yex53i51MNplrXOgcXfZmH+p7sxPSMBX98xpqF8vSNiw9Xo30WLDTJfvryk0ooITaDsmpEGqATEhqslrZTKLbUghf2kiGQlJTYMGUlan12F79vdBfghqwhPXzqgU6ueqlQCnrlsAPKMFrz5W3a7H593anpy93ZOHSTlSNN3fAU+k9mGGPaUIgkxKUVERE0smNob/ZN0mP/pLpitdVIPp5GC8hpc/cYWfLrtOJ6alYHlVw1CaHBgp/c7obceG4+WwinjaYtyXHnPJV6rgUHC6Y85pWb2kyKSoQsHdMFPB4thscnrs+RsCitq8Ni3WbhkcBfM6GAV7un6Jmjx9/FpePmXo8htZ++ffKMFggB0jQrp9DjIP6XFhiGngz2ljNVWTt8jSTEpRURETQQFqLDi6sEwVFnx+Op9Ug+nwYbDBlz40u8wVFnxxW2jMXtUcoenU5xpfK9YlFbbsL+w0i3784SSKqvsVt5ziYtQS9bovNbuQEFFDVfeI5KhCwckotbuxM8HfWcKn9Mp4v4v9iI0OABPXJzhtv3On9ILcRFqPPpNFkSx7RdA8kwWdNGFQB0orypZko80fRjyjGbUOZztepzd4URlbR0bnZOkmJQiIqJmpcSG4fGL++OLHSewdm+BpGNxOkWs+PEIbnpvGwZ2jcTau8ZhULdItx5jWHIUQoMD8LuM+0qVVNVCL9NG3nFa6abv5ZssEMX61ywRyUv3mFAM7KrzqSl8H23Nw8ajpfi/KwZBFxrktv2GBAfgyVkZ2Hi0FN/ubvvnar7Rwql71KrU2DDYHSJOlLVv9eQyiw0AWClFkmJSioiIWnTFsK64cGAiHvoqEyfL2/dFx13KzDbc8sF2vPjTYSyY0hvv/e0cRHngy5M6MACj0mJk3VfKIONKKX2ERrLVC11TFlJi+aONSI4uHJCInw+WyG46eHNySs145vsDuGFUMib01rt9/5P6xOHCgYl46rv9KD+VEDibPJOZK+9Rq1x9Nds7hc9kPpWUYk8pkhCTUkRE1CJBEPDMrAGIUAfink93w+Hlfkt7jpfjopc3Ys/xcrx/8wjMn9rLo6urTegViz/zTLL94ST36XuGKqvXXyMAkFtqRrg6EPpweT43REo3Y0AirHVO/CTzKXx1DicWfr4bCVoNHprR12PHWXJROqx2J55bd/Cs24qiiDyjhSvvUasStRpoglQ4ZmjfCnym6vqkVAwrpUhCTEoREVGrdKFBePGaIfgzz4TXfz3qlWOKooiPt+bhypWbERuhxtq7x2OiB65Yn2l8bz3sDhFbc4weP1Z71dodqKqtk3Wjc6cIGM3en8KXU2pGSmyo2/qLEZF7dYsOxaBukVi7R9qp4GfzxoZs7Dlejn+5aQGNlsRpNXhgeh+s2nYc23NNrW5bUWNHVW0dkqM5PZlaplIJSIlpf7Nzo5nT90h6TEoREdFZjUiNxh2TeuKFH49gV36ZR49VY3Pg3s/34JGvs3D1Od3w+T9GISnSOysOpcWGISkyBBsOy6+vlOFUv6bOLEvuSa4KLimaneeUmpHCJudEsnbRgET8etiAqlq71ENpVtbJCryw/jBum9gDw5KjPX6860YmY3C3SDzydSZsdS03p84zWgCA0/forHrow5FtaP/0vaAAAeFqzyVhic6GSSkiImqTu6f0woAkHeZ/uhvVHprelm2oxqxX/8APWUVYcc1gPDkrw6urDQmCgAm99dhwRH59pVz9muK08qyUco3LIEGz81yjGalsck4kazMGJsJW58RPB+Q3hc9aV38xpFd8BBZM7e2VYwaoBDxz6QAcM5jx1u/ZLW6XZ6pPSnVjo3M6izR9GLJL2zl9z2xDdFgwK41JUkxKERFRmwQFqLDimsEwVlux5Nt9bt//uqxCXPzKH7A7nfj2zrG4ZHCS24/RFhN6xSLbYMaJMoskx2+JK9kj175JseFqCAK83uzcbK1DcaWVSSkimUuKDMHQ7pFYK8NV+JavP4zs0mosv2oQggO99/MovYsWc8al4qWfjiDP2HyFS77RjMjQIOhC3LcKIPmn1NgwFFda29UXsz4pJc/vFaQcTEoREVGbJceE4YlLMvDlzhNY7abeIHaHE09/tx+3fbQTE3rHYvWd49A7PsIt++6IMT1joRKA34/IawpfSZUVQQECIt24PLk7BQWoEB0ajGIvT9/LNbpW3mNSikjuLhzYBRsOG1Apoyl823NNeHNDNhZO64N+iVqvH3/B1F6IDVfjsW/3QRSbLhSRZ7QgmVVS1AYdWYHPZLaxyTlJjkkpIiJql8uGJmHmoC545OvMTlcTlVTW4vq3tuK9P3Lx2EXpePW6oZL3NdCFBGFwt0hsOCyvKXwllVbow9WyLrHXR6i9XimVW1r/GkxlTyki2ZsxIAE2hxM/7i+WeigAgGprHRZ+vhtDu0fh1glpkowhNDgQT1zSHxsOG7CmmSqyPJMF3Xl+ozZwVQy3ZwU+o9mKKCalSGJMShERUbsIgoCnZmVAqwnCPZ/tRp2j5QatrdmSbcSMlzYiz2TGp7eOwpxxqbJJuEzorcfGo6Ud/rd5gqHKCr1Wnk3OXeK1Gq83Os81mqELCeKXaiIfkKgLwfDkKHwn0RQ+h1PE5mNGfLv7JDYfM+LJtfthrLZh+VWDEKCS7vNnSr94XJCRgCfW7EeFpXEVWT4rpaiNdCFBiA0PZqUU+RwmpYiIqN10IUFYcc1g7Mgrw2u/HmvXY0VRxMrfjuH6t7eiV1w41t41HsNTPL/SUXuM76VHVW0d9pyokHooDUqqahtWuJOruAg1Srzc6DynlE3OiXzJhQMTseGIARU13p3Cty6rEOOe+xnXvrUF8z/djWvf2oLPth/HJYO7IFkGlUhLZvZHrd2B5/57sOG2WrsDRZW16M6V96iN0mLbtwKfyWxHNJNSJDGfSUqZTCZcf/310Gq1iIyMxJw5c1Bd3Xpp4ptvvolzzz0XWq0WgiCgvLzcLfslIiJgeEo07pzcCyt+OoIdeWVtekxFjR23frgDz/5wEP+YkIYP54yAXoaJlkFdddBqAmU1hc9QbZXlc3W62IhgnDBZsHpPAXYcr4LD2bQ/irsxKUXkWy7ISESdU8R6L07hW5dViHkf7URhRdPpxZ9uO451WdI3X0/QaXD/+X3wydb8hs9U1xR5VkpRW7VnBT6nU0SZxcakFEnOZ5JS119/Pfbt24f169dj7dq12LBhA2699dZWH2OxWDB9+nQ8/PDDbt0vERHVu3tyTwzqqsOCz3ah6iyNa/cXVOLiVzZiS7YRb904HA9M74vAAHl+DAUGqDCuVyx+PyKfpFRJpVXWlVLrsgrx8ZZ8lJptWPDZHtzx5WGMf/5Xj//Yyy01I0UGVQ5E1DYJOg3OSY7Gd3vds1jG2TicIpau2Y/WUuRL1+z3ShL9bGaPSsagrjo8/FUmau0O/HdfEQCgtNomi/GR/KXGhiHHYG62af6ZKmvtcDhFTt8jycnz18AZDhw4gHXr1uHtt9/GyJEjMW7cOLz88sv49NNPUVDQ8gfaggULsGjRIowaNcqt+yUionqBASqsuGYIysx2LP52X5N+Ha4v0f/ZcQKXvvYHwoIDsfaucZiWHi/xyM9ufC89dh8vb9LfQwoOp4jSaiviIuTZU8pVhVBZ23gZ6uLKWsz7aKfHElOVtXYYzTakxLKKgMiXXDgwEb8fKfXK+XVbjqnZCikXEUBhRS225Zg8PpazCVAJePrSAThcXIVznvoR//ffwwCAOz7ZiXHP/SyLii6StzR9OMw2R5um0hvNNgBgT0aSnLRLHLXR5s2bERkZieHDhzfcNnXqVKhUKmzduhWXXnqpV/drtVphtf71Rq+srAQAOJ1OOJ3yaYrrS5xOJ0RR5POnEIy3f0mK1OCJi9Ox8Iu9+PlgSaM+IfFaNbrrgrD9eDWuGt4Vj89MhyYowCdiP65HDJwisPGoARdkJEg6ltIqK5wiEBseJLvnzuEU8fjq5qsQRAAC6qsQpvSNc3sj4eyS+ikKKTGhsntelITndGVwZ5zPT4/D42v2Yd2+Qlw5rKsbRtey4sqaNm8nh9dwvtEMEUCVtXGSv6iiPsn/6nVDMN2Ln0l8f/uWlOgQAMDR4irow1tPNpWeWi03KiSwIb6MtzKcGWep4+0TSamioiLExcU1ui0wMBDR0dEoKiry+n6XLVuGpUuXNrndYDCgtta7S2H7C6fTiYqKCoiiCJXKJwr4qBMYb/9jralPDpzZuLa40oriSisuGxCLhePiUVlmRKUUA+yAIADJUWr8b+9xDIuT7nXqcIpYu68UAHD0hAH9oyDpKlFn2nG8CkWVZ69C+N+ubAzrFuHWY+/Jrq9sCHdaUFLi3Qbr9Bee05XB3XEe3CUcX/+Zh4ndPFulEVTXtqRUUF0NSkpKPDqWs6lP8mc1e58r8b90dRYGxQpe+xzg+9u3aBxOBAjA3pwi9IhwtLptbkE5AMBZU4mSkvr3CeOtDGfGuaqqStLxSJqUWrRoEZ577rlWtzlw4ICXRtN2Dz30EBYuXNjw98rKSnTr1g16vR5arVbCkfkup9MJQRCg1+t5AlQAxtu/OJwiVry7r9VtNudXIyZWL6tkSltM6puA/x0ohl6vhyB4f+zrsorwxNoDDUmf5385jn/vMGDxRf28eqW8NfbCurNvBMAeGNLkQlBnmTIrEBMWjNRuiW7dL7UPz+nK4O44zxpWgyfXHkBQeCSiQj2XmDovVo+E9fktJs8F1Pe5Om9ImuSfUVuyjSipbn1KY3G1HXmWQIxKi/HKmPj+9j3dokNhsKrO+pnryLNCEICe3bs0vPYZb2U4M84ajbTtISRNSt17773429/+1uo2aWlpSEhIaHLloq6uDiaTCQkJHf9S3tH9qtVqqNVNm82qVCq+eTtBEAQ+hwrCePuPrTnGVitlgPpKmT/zyjG6h3e+RLvLhD56vL85D7mmGvTQh3v12OuyCnHHJ7uaTIsrrqzFHZ/swuuzh2J6hvTJmHhtSJu3c/f7Pc9oQWpsGM8jMsBzujK4M84XDEjE0jX78eOBElx9Tnc3jK55KhVw0aBEvP17TpP7XCmoJTPTERQY4LExtJWh2tbm7bz5XuP727ek6cORU2o+a7zKLHZEhQY3ee0z3spwepyljrWkSSm9Xg+9Xn/W7UaPHo3y8nLs2LEDw4YNAwD8/PPPcDqdGDlyZIeP76n9EhEpSUlV26Ytt3U7ORmVFoPgABU2HDZ4NSnV2mpRp/dpmpaeIPmV/RGp0UjUaVBUUdvseF1VCCNSo91+7ByjBb3jvJssJCL3iIvQYGRqDNbuLfRoUirPaMan245jaHIkCsprUXRa0/MEnQZLZqbLIsEPoM2LWch10QuSh7TYMPx4oPis2xmrbYgKDfLCiIha5xPpz379+mH69OmYO3cutm3bhj/++AN33nknrrnmGnTp0gUAcPLkSfTt2xfbtm1reFxRURF2796No0ePAgAyMzOxe/dumEymNu+XiIha589fokODAzE8JQq/Hyn16nF9bbWoJTPTAfxVdXCmJTPT3Z48E0UROYZqpMSGuXW/ROQ9Fw5MxKZjRhirPdMTzlrnwB2f7ERMeDA+uHkE/nhwMlbNHYUV1wzGqrmjsPHBybJJSAF/JflbOlsKABI9lOQn/5GmD8fxshrY6lpvXm0yWxET1nT2D5G3+URSCgA+/vhj9O3bF1OmTMGMGTMwbtw4vPnmmw332+12HDp0CBaLpeG2lStXYsiQIZg7dy4AYMKECRgyZAhWr17d5v0SEVHrzvYlGvDtL9Hje+mx+ZgR1rrWG4a6k69Vn03PSMTrs4ciQdc48agOVHlsmmGZxY7K2jqkMilF5LMuyEiAKIr4776zV3V0xLLvD+JwUTVevW4oIjRBCFAJGN0jBpcMTsLoHjGSV5qeqbUk/+lTDeU2bpKX1NgwOJwi8k3mVrczWeyIDvPsQgNEbeETq+8BQHR0ND755JMW709JSYEoNp448Pjjj+Pxxx/v1H6JiKh1ri/R8z7aCQFoNIXL9ffHLuzns1+iJ/SOxXPrDmJHXhnG9Ij1yjF9sfpsekYipqUnYFuOCcWVNdiVXYQPthejW3SoR46XU1r/ZTslhkkpIl8VE67GmB6x+C6zANeNdO8UvnVZhXh/Uy6WXtwfGUk6t+7bk1xJ/qVr9jeqmJXbVEOSrx76+s/FbIMZPeNaXvXWZLaia9dIL42KqGU+k5QiIiL5au1L9N3ju8hmpbiO6JegRWx4MDYcLvVaUkrKPk2d4apCcDqdGB4fgJ+PVuK1X4/h1euGuv1Yua6kVKxnkl5E5B0XDkzEI19norTaithw90wlOm6y4P7/7MX0/gm4cXSyW/bpTacn+UuqahEXUX++99WLO+Rd+gg1wtWByC49S6VUtQ0xrJQiGWBSioiI3KK5L9HDkyNhLDVIPbROUakEjO+lx+9HDFh0QV+vHNNVfXbbRzub3OcrUzgCVQJunZCGxav3IdtQjTQ3N4rPKTUjQatBaDC/yhD5svP7J+DRb7KwLqsIs0d1PoFkq3PizlW7EBkahOeuGAhBkO95sjWuJD9RewmCgNTYMOQYWk5KiaIIo9mGqFAmpUh6PtNTioiI5E/u/To6anyvWOwrqIShyjPNeJszLT0B8Vo11IGNP6oTdBqP9WlytyuGJiE2XI03fst2+75zjGZWSRH5geiwYIzpEYPv9ha6ZX/PrzuI/QUVeOXaodCFcGUxUqY0fRiyS6tbvL/G7oC1zomYcCalSHq8vEhERHQW43vpAQAbjxpw6ZCuXjnmmj0FKK604qt5Y2Ctc/rkFA51UAD+Pi4V//zfISyY1guJuhC37Tu31IyBXX2nTwwRteyigYl46KvMhvNcR/24vxhvb8zBYxelY1C3SPcNkMjHpMWGY2MrKwcbq20AwEbnJAuslCIiIjoLfYQa6Yla/H645S947lTncGLFT0cwtV8chiZH+XT12fWjkhESFIC3NuS4bZ+iKCK31MyV94j8xHnpCVAJAv6bVdThfZwsr8G9X+zB1H7xuGVsivsGR+SDUvVhMJptqLDYm73fZGZSiuSDSSkiIqI2GN87FhuOlMLpbK71uHt9u7sAOaVmLJja2+PH8rRwdSD+NjYVq7blw1jtnumPhiorzDYHV94j8hNRYcEY2zMWazs4hc/ucOKuT3YiXB2If17pu32kiNwl7dRFm5am8LmSUjFh7llcgKgzmJQiIiJqg4m99CittuJgUZVHj2N3OPHSz0dwXnq8Ty1j3pqbx6QAAN7flOuW/eWcWlGIlVJE/uPCgYnYlmtCSWXt2Tc+wz//dwh7T1TgpWuHIJKNm4kaPh+zW2h2bjyVlIoKY981kh6TUkRERG0wLCUKIUEB2HDEs6sJfr3zJPKMFr+oknKJCgvGdSO744NNuaiqbX4qQXvkGs0QBKBbNBudE/mL89MTEKgS8EM7p/D9crAEb/yWjfvP74NhyVEeGh2RbwlTByJBq2m4iHOmMrMN4epAqAMDvDwyoqaYlCIiImoDdWAARqVF43cPJqVcVVIzBiQgvYvWY8eRwtzxaaixO/Dx1vxO7yun1IKkyBBogvhlmshf6EKDMK5nbLtW4SusqMHCz3djUh895o5P8+DoiHxPayvwGc029pMi2WBSioiIqI3G99Jje04ZLLY6j+z/PztO4GR5DeZP8Z8qKZcEnQaXD+2Kt3/PQa3d0al95ZRWc+oekR+6cGAXbM8zoaji7FP46hxO3L1qF9SBAfjXVYOh8rFFIIg8LTU2rMXpeyazlUkpkg0mpYiIiNpoQm89bA4ntmab3L5vW50Tr/x8FBcOSESfhAi3718O/jGxB0xmK77483in9pNbamGTcyI/NC09/tQUvrNXS73w42HszC/Hy9cN4Y9romak6cORU2pudoEWk9mGGL5vSCaYlCIiImqjHvowdNFpPNJX6vM/j6OgogYLpvZy+77lIjU2DBcO7II3NmTD7nB2aB9Op4hcoxkprJQi8ju6kCBM6KU/6xS+DYcNeO3XY1g4rTfOSYn20uiIfEuaPgzWOicKKmqa3Gc02xDFpBTJBJNSREREbSQIAib01mPDYfcmpWrtDrz6y1FcPKgLesb5Z5WUy7yJPXCirAZr9hR06PFFlbWw1jkblrsmIv9y0aBE/JlXhoLypj+kAaCkshb3fLYb43vpMW9iDy+Pjsh3pLWyAl8ZK6VIRpiUIiIiaocJvfU4ZjDjZAs/mDris+3HUVxZi7un+G+VlEt6Fy0m943Da78ea3ZKwdm4VhJipRSRf5raLx7BgSp8n9m0WsrhFDH/090IUAlYftUg9pEiakXXqFAEB6iaXYGPjc5JTpiUIiIiaoexPWKhEoDf3VQtVWt34LVfj2LWkCT00Ie7ZZ9yd8ekHjhaUo31B4rb/dicUjMCVAK6RoV4YGREJLUITRAm9tbju2aSUi/9dARbc4x46dohiA1XSzA6It8RoBKQHBOKbEPjFfhsdU5U1dYxKUWywaQUERFRO+hCgzCoWyR+P1Lqlv19sjUfpdU23D3Z/6ukXIYlR2NEajRe++UoRLF91VK5pWZ0iwpBUAC/whD5q4sGJmJXfjlW7zmJb3efxOZjRmw8bMBLPx/Bgqm9MSotRuohEvmE1NgwZJ9RKVVmsQEAYsKZlCJ5CJR6AERERL5mfC89PtiUC4dTREAnpo/U2Bx47ddjuGxIkuKmo90xqSduencb/jhqxLhesW1+XK7RjFSFPVdESuOa2Xv3qt0Nt6kEoE98OO6Y1FOaQRH5oDR9eJMejsbq+qRUVCiTUiQPvMxIRETUThN7x6Kixo49J8o7tZ+Pt+ah3GLDXQqqknKZ0CsWGUlavPbr0XY9LruUK+8R+bN1WYVY+NnuJrc7ReBgUTXW7y/y/qCIfFSaPgwFFTWotTsabmuolArjFFiSByaliIiI2mlQ10hEaALx++GOT+Gz2Orw+q/HcMWwrugeE+rG0fkGQRBwx7k9semYETvzy9r0mDqHE8dNFlZKEfkph1PE0jX70dKkXgHA0jX74ejAIglESpQWGwZRRKNm50ZzfVIqmtP3SCaYlCIiImqnwAAVxvaIxYYjHW92/uHmPFTW2hU9FeX8/glI04fhtV+OtWn7gvJa2B0iUmKYlCLyR9tyTCisqG3xfhFAYUUttuWYvDcoIh+WdmoBldOTUqZqK4IDVQgLDpBqWESNMClFRETUARN667H7eDkqauztfmy1tQ4rfzuGq4Z3Q7do5VVJuahUAuZN7IEfDxTjUFHVWbfPMdZ/qWalFJF/KqlqOSHVke2IlC4qNAi6kKBGK/CZzDbEhAVDEDreE5PInZiUIiIi6oDxvWLhcIrYfKz9U/g+2JQLs9Wh6Copl1lDkpAUGYLX29BbKsdQjeAAFbpEhnhhZETkbXERGrduR6R0giAgTd94BT6j2cYm5yQrTEoRERF1QLfoUKTFhmHDkfYlpapq7Xjr92xcM6IbkysAggJUmDs+Fav3FCDfaGl121yjBd1jQju14iERydeI1Ggk6jRo6R0uAEjUaTAiNdqbwyLyaWmx4cg2/JWUKrPYEMN+UiQjTEoRERF10Phesdhw2ABRbHvT3ff/yIXF5sDt57JKyuXqc7ojKjQYb2xovbdUTqmZ/aSI/FiASsCSmekA0CQx5fr7kpnpTEwTtUOaPgzZhuqG7yrGahuiw5iUIvlgUoqIiKiDJvTW40RZTaMGoq2pqKmvkrpuRHck6Dj9xCUkOAC3jEvFF3+eQElly71ico1mpOmZlCLyZ9MzEvH67KFNzpEJOg1enz0U0zMSJRoZkW9Kiw1DZW0dTKdW3TOZmZQieQmUegBERES+alRaDIICBPx+pLRhhZvWvPdHDqx1Ttx+bg8vjM633DA6GSt/PYa3N+bg4Rn9mtxvq3PiuMnCSikiBZiekYhp6QnYlmNCSVUt4iLqp+yxQoqo/VzfT7JLzYgJVzc0OieSC1ZKERERdVCYOhDDkqOw4bDhrNtWWOx45/cczB6VjDgtq6TOpNUE4YbRyfh4Sx7KLbYm9x8vs8ApAimxyl2tkEhJAlQCRveIwSWDkzC6RwwTUkQdlBwTCkEAsg3VcDpFlFlsiGJSimSESSkiIqJOmNBbj83ZRtjqnK1u9/bGbNidTtw2kVVSLbllXCrqnCI+2JTX5L7cU1MkU2NZKUVERNRWmqAAJEWGILvUjIoaO5wiWClFssKkFBERUSdM6KWHxebAjryyFrcpM9vw3h+5uGl0CvQRai+OzrfEhqtxzTnd8N6mHJitdY3uyyk1IyQoAPFcCp6IiKhd0vT1K/AZT/WVig7jdxGSDyaliIiIOiE9UYuYsGD8fqTlKXxv/Z4Npyji1glpXhyZb5o7IQ3VtXVYtS2/0e05pWYkx4RCxSk8RERE7ZIWW78Cn6khKcVKKZIPJqWIiIg6QaUSMK5XLDa0kJQyVlvx/qZc3DQmBTHhvDJ5Nl2jQjFrSBLe+j0b1jpHw+25RjOn7hEREXVAmj4M+SYLDFVWAExKkbwwKUVERNRJE3rpkXWyEqXV1ib3vfl7NgQAt45nlVRb3TaxB0qqrPhq58mG23JLLUhhUoqIiKjd0mLDYXeI2HuiHCoBiAwJknpIRA18JillMplw/fXXQ6vVIjIyEnPmzEF1dXWrj3nzzTdx7rnnQqvVQhAElJeXN9kmJSUFgiA0+vPss8966F9BRET+aHyvWADAH0dLG91uqLLi35vycPPYVK500w4948IxvX8CVv52DHUOJ2rtDhRU1LBSioiIqANS9fWfn9tzTYgKDeZUeJIVn0lKXX/99di3bx/Wr1+PtWvXYsOGDbj11ltbfYzFYsH06dPx8MMPt7rdE088gcLCwoY/d911lzuHTkREfi5Oq0HfhAj8drjxFL43fjuGQJWAv49PlWhkvuv2c3siz2jB2r2FWL27AKIIWKx1cDhFqYdGRETkUxK1GmiCVMg6WcmpeyQ7gVIPoC0OHDiAdevWYfv27Rg+fDgA4OWXX8aMGTPwz3/+E126dGn2cQsWLAAA/Prrr63uPyIiAgkJCe4cMhERKczE3np8teskRFGEIAgoqazFh1vycNvEHogM5RfA9hrQVYf0RC3u+2IP6k4loh5fsx9vbMjGkpnpmJ6RKPEIiYiIfINKJSAlJgwHi6qYlCLZ8Ymk1ObNmxEZGdmQkAKAqVOnQqVSYevWrbj00ks7tf9nn30WTz75JLp3747rrrsO99xzDwIDW35qrFYrrNa/+oZUVlYCAJxOJ5xOZ6fGolROpxOiKPL5UwjGWzmUFOuxPWPwxoZsfLotHyHBAfghqwhBAQJuHpOsiH//6dwR93VZRdhfWNnk9qKKWsz7aCdevW4IpmfwgpIcKOl9rmSMszIx7v4jNSYUB4uqUGOvw6ajBpyTEo2AM6bxMd7KcGacpY63TySlioqKEBcX1+i2wMBAREdHo6ioqFP7vvvuuzF06FBER0dj06ZNeOihh1BYWIjly5e3+Jhly5Zh6dKlTW43GAyora3t1HiUyul0oqKiAqIoQqXymVml1EGMt3IoKdZ5hSYAwENfZzXcFhaswg+7sjGpZ5RUw5JEZ+PucIp4fHVWs/e5Ju8tXZ2FQbFCky/U5H1Kep8rGeOsTIy7f/jlaBl+O7VK8N4Tlbju7W2ICw/CPed2a/QdhfFWhjPjXFVVJel4JE1KLVq0CM8991yr2xw4cMCjY1i4cGHD/w8cOBDBwcH4xz/+gWXLlkGtbn7p7oceeqjR4yorK9GtWzfo9XpotVqPjtdfOZ1OCIIAvV7PE6ACMN7KoZRYr8sqwuIfcprcbrE58fDabMVV9XQ27luyjSiptre6TXG1HXmWQIxKi+noMMlNlPI+VzrGWZkYd9+3LqsID6/NxpkdGQ3V9ibfURhvZTgzzhqNRtLxSJqUuvfee/G3v/2t1W3S0tKQkJCAkpKSRrfX1dXBZDK5vRfUyJEjUVdXh9zcXPTp06fZbdRqdbMJK5VKxTdvJwiCwOdQQRhv5fD3WDucIp787kCTL3tAfVWPAODJ7w7g/IxERVX1dCbuhmpbm7fz19eVr/H39znVY5yViXH3XR35jsJ4K8PpcZY61pImpfR6PfR6/Vm3Gz16NMrLy7Fjxw4MGzYMAPDzzz/D6XRi5MiRbh3T7t27oVKpmkwXJCIias62HBMKK1qeui0CKKyoxbYcE0b3YFVPW8RFtO2KXVu3IyIiUiJ+RyFf4BPpz379+mH69OmYO3cutm3bhj/++AN33nknrrnmmoaV906ePIm+ffti27ZtDY8rKirC7t27cfToUQBAZmYmdu/eDZOpvu/H5s2b8eKLL2LPnj3Izs7Gxx9/jHvuuQezZ89GVJSy+n8QLjoM/QAAHlxJREFUEVHHlFS1rZdgW7cjYERqNBJ1GrRUVyYASNRpMCI12pvDIiIi8in8jkK+wCeSUgDw8ccfo2/fvpgyZQpmzJiBcePG4c0332y4326349ChQ7BYLA23rVy5EkOGDMHcuXMBABMmTMCQIUOwevVqAPXT8D799FNMnDgR/fv3x9NPP4177rmn0X6JiIhaw6oe9wtQCVgyMx0AmiSmXH9fMjNdUdMhiYiI2ovfUcgX+MTqewAQHR2NTz75pMX7U1JSIIqNZ8s+/vjjePzxx1t8zNChQ7FlyxZ3DZGIiBTIVdVTVFHbbM8GAUACq3rabXpGIl6fPRRL1+xvNPUgQafBkpnpmJ6RKOHoiIiI5I/fUcgX+ExSioiISI5cVT3zPtoJAWj0pY9VPZ0zPSMR09ITsC3HhJKqWsRF1H9x5nNJRER0dvyOQr7AZ6bvERERyZWrqidB17j8PUGnweuzh7KqpxMCVAJG94jBJYOTMLpHDL84ExERtQO/o5DcsVKKiIjIDVjVQ0RERHLE7ygkZ0xKERERuYmrqoeIiIhITvgdheSK0/eIiIiIiIiIiMjrmJQiIiIiIiIiIiKvY1KKiIiIiIiIiIi8jkkpIiIiIiIiIiLyOialiIiIiIiIiIjI65iUIiIiIiIiIiIir2NSioiIiIiIiIiIvI5JKSIiIiIiIiIi8rpAqQfgD0RRBABUVlZKPBLf5XQ6UVVVBY1GA5WKuVJ/x3grB2OtTIy7sjDeysA4KxPjriyMtzKcGWdXHsOV1/A2JqXcoKqqCgDQrVs3iUdCRERERERERNQ+VVVV0Ol0Xj+uIEqVDvMjTqcTBQUFiIiIgCAIUg/HJ1VWVqJbt244fvw4tFqt1MMhD2O8lYOxVibGXVkYb2VgnJWJcVcWxlsZzoyzKIqoqqpCly5dJKmQY6WUG6hUKnTt2lXqYfgFrVbLE6CCMN7KwVgrE+OuLIy3MjDOysS4KwvjrQynx1mKCikXThQlIiIiIiIiIiKvY1KKiIiIiIiIiIi8jkkpkgW1Wo0lS5ZArVZLPRTyAsZbORhrZWLclYXxVgbGWZkYd2VhvJVBbnFmo3MiIiIiIiIiIvI6VkoREREREREREZHXMSlFRERERERERERex6QUERERERERERF5HZNSRERERERERETkdUxKERERERERERGR1zEpRUREREREREREXsekFBH5FKfTKfUQyEuKi4tRUFAg9TCIyIN4TlcGns+J/J8oilIPgbzg+PHjOHz4sFv3yaQU+azc3Fy89dZbeOmll/DDDz9IPRzysIqKCgCASqXijxgF2LVrF0aMGIGDBw9KPRTyEp7TlYXndOXg+Vx5eD5XFpPJBAAQBIGJKT+3a9cuDB8+HJmZmW7dL5NS5JMyMzMxcuRIrFq1Cl9//TUuuugi3Hjjjdi2bZvUQyMP2L9/P5KTk/HMM88A4I8Yf7dnzx6MHz8el156KSZPniz1cMgLeE5XFp7TlYPnc+Xh+VxZ9u/fj/j4eCxYsAAAE1P+zHU+v/7663H55Ze7dd+CyFcN+Rij0YgpU6bgoosuwlNPPQUA+OGHH3DRRRfhwgsvxD333INJkyZJPEpylxMnTuDiiy+G2WxGaWkp7r//fixatAhA/bQPlYq5dX+yb98+jB49GnfccQeWLVsGh8OBzMxMWCwW6HQ69O/fX+ohkpvxnK4sPKcrB8/nysPzubIUFBTg0ksvRV1dHQ4dOoS5c+fihRdeAFA/lU8QBIlHSO5y8OBBDBs2DAsWLMDTTz+Nuro6bNq0CWVlZdDr9RgzZkyn9h/opnESeU15eTkCAwNx3XXXQRRF2O12DB48GP369cP27dvxyiuvYPDgwYiKipJ6qNRJTqcTX375JVJTU3HnnXdi27ZtDVfWFy1a1HB1nT9i/IPVasUNN9yA8PBwzJ8/HwBwxRVXIC8vD3l5ebBarViyZAnuv/9+iUdK7sRzunLwnK4cPJ8rE8/nyiGKIn755RckJydjwYIFyMvLw8033wxBELB8+fKGiikmpnyfzWbDokWLEB4ejlmzZgEALrvsMuTn56OwsBBlZWWYN28eHnvsMcTGxnboGExKkc+pqqrCzp07UVRUhPT0dAQHB8NisaBbt254+OGHMXv2bEyfPh1z586VeqjUSSqVCjNmzEBcXBwmTZqEwYMHQxRFLFu2DAB/xPgbtVqN5cuX47bbbsM999yDw4cPIzY2Fi+99BI0Gg02b96M+fPnIyIiArfddpvUwyU34TldOXhOVw6ez5WJ53PlEAQB48ePR0REBMaMGYMxY8ZAFEXccsstEEURL7zwAhNTfiI4OBiPPvooHnnkESxevBi5ublISUnBu+++i5iYGOzduxeXX345tFotnnzyyY4dRCTyMXa7XbzhhhvEnj17iq+88oq4atUqMSoqSrz99ttFURTFBQsWiNdcc41ot9tFp9Mp8WjJHU6Po8FgEJ999llRq9WKy5YtE0VRFOvq6sTVq1eLBoNBqiFSJ50e419++UVMSEgQJ06cKBYUFDTa7t577xUHDBggGo1Gvr/9BM/pysNzun/j+Vy5eD5XntPjWFdXJ37yySeiWq0W77nnHlEU618TH330kZiZmSnVEMlNtm/fLo4ZM0acNm2amJOT0+i+FStWiHq9Xjx58mSH3tuslCLZKygowMmTJ2E0GjFt2jQEBgbiwQcfxKuvvoolS5YgISEBt99+e8Pc9YqKCpSVlSEwkC9vX3R6vKdOnQqVSgWVSoW6ujoEBgYiNjYWt9xyCwDgmWeegSiKMBqNWLFiBfLz8yUePbXX6fGeMmUKAODcc8/F2rVrsX//fuj1+kbbazQahIaGIioqilfefBTP6crCc7py8HyuPDyfK8vx48dx4MABGAwGTJs2DZGRkQgODm44nwcEBODKK68EANx8880AAIfDgddffx1Hjx6VcujUTqfHeurUqdDpdBg+fDjeeOMNHDp0CF27dgXwV+8wQRCQmJiImJiYjp3P3ZE1I/KUPXv2iN26dRPT09PFwMBAcfDgweKbb74pWiwWURRF8cSJE42uvDmdTvHGG28UH3zwQdHpdPIqjI85M95DhgwRX3/9dbGqqkoUxforMC4Gg0FctmyZKAiCGBUVJW7fvl2qYVMHNRfvV199VayoqBBFURRtNluTx9x2223iLbfcIlqtVr6/fRDP6crCc7py8HyuPDyfK8uePXvE+Ph4cejQoWJwcLDYv39/8f777xfLyspEUWx8Pq+rqxM//PBDns99VHOxvvfee0Wj0SiKYvPn8/nz54tXXHGFaDabO3RMJqVItgwGg9ivXz/xwQcfFHNycsSSkhLx2muvFc855xxxwYIFYnl5eaPtjx07Jj788MNiZGSkuH//folGTR3VUrxHjhwpLliwQKysrBRFURQdDkfDY2644QZRq9WK+/btk2rY1EFtjbdLQUGB+Nhjj4lRUVGMt4/iOV1ZeE5XDp7PlYfnc2UpLy8Xhw4d2pCYqKmpER966CFxzJgx4iWXXNKQrHAlphwOhzhnzhxRq9Uy3j6mrbF2yc7OFh977DExMjJSzMrK6vBxmZQi2crMzBRTUlLEPXv2NNxmtVrFxYsXiyNGjBAfeeQRsaamRhTF+g/H2267TezTp4+4c+dOqYZMndCeeDudTvHDDz8U4+PjxR07dkg1ZOqE9sR727Zt4pVXXil27dpV3LVrl0Qjps7iOV1ZeE5XDp7PlYfnc2XJyckR09LSxF9//bXhNqvVKr777rvi6NGjxeuvv74h+ex0OsXvv/9eTE1NZYWUD2pPrDMzM8WLL75YTElJ6fT5nEubkGwFBwdDEISGnhJ1dXUIDg7GY489hokTJ+K7777D9u3bAQCxsbG4//778dNPP2HIkCFSDps6qD3xFgQBY8eOxdatWzF06FAph00d1J54JyYm4qqrrsKvv/6KwYMHSzhq6gye05WF53Tl4PlceXg+V5bw8HCEhoYiMzMTQH0foeDgYNx0002YPXs2Dhw4gG+++QZA/fl86NCh2LRpE4YPHy7hqKkj2hPrHj16YP78+fj55587fT4XRFEUOzl2Io+wWq0YN24cEhIS8M033yAgIKChkZ4oihg0aBCGDBmCDz74QOqhkhu0J94il5f1eW2J9+DBg/Hvf/9b6qGSm/Ccriw8pysHz+fKw/O5stjtdlx77bUoLCzEJ598guTk5Eb3n3/++QgKCsLatWslGiG5S1tiHRgYiO+++86tx2WlFMmS0+mEWq3Ge++9hw0bNmDevHkA0PBhJwgCLr74YpSUlEg8UnKH9sabP158W1vjbTAYJB4puQvP6crCc7py8HyuPDyfK4soiggKCsJrr72GY8eO4e6770ZJSQlOr2uZOXMmSktLUVtbK+FIqbPaGmuj0ej2WDMpRbKkUqngcDiQkZGBDz74AKtWrcKNN96I4uLihm1ycnIQFRUFh8Mh4UjJHRhvZWG8lYcxVxbGWzkYa+VhzJVFEATYbDbExcVh3bp12Lp1K2bPno0///yzIb67d+9GTEwMVCqmFnyZlLHm9D2ShTNL910lwNXV1bBardi9ezeuu+46JCcnIzo6GjExMfj222+xefNmDBgwQMKRU0c4nc5GJzPG278x3srDmCsLP8OVg7FWHsZcOZqbSu1wOBAQEACj0QibzYaamhpccMEFCA8PR11dHdLS0vDTTz9h48aNGDhwoEQjp/aSW6yZziRJubKurtyoKIoNH3a5ubno3bs3tm/fjilTpmDfvn2YMWMGkpKSEBcXh23btvHDzseUlpYC+OsqG1D/GmC8/RPjrTyMubIcO3YMZWVljb7YMt7+ibFWHsZcWXJycvDFF1+goqKi4TZXkiI3NxcDBw7ETz/9hLS0NGzfvh0LFizAtGnTcM4552D79u1MSPkQWca6U2v3EXXCoUOHxAULFoiXXXaZuHTpUjE7O7vhvvz8fDE2NlacM2eO6HQ6xbq6OlEU65cZFUVRdDgckoyZOu7QoUNiRESEOHfu3IbbXHFlvP0P4608jLmy7N69WxQEQXznnXea3Md4+xfGWnkYc2XZs2ePGBsbKy5atEg8cuSIKIp/xTE/P1+MjIwU586dKzqdTsbXx8k11qyUIklkZmZizJgxKCsrg9PpxA8//IBVq1ZBFEXY7XZ8++23mD17Nt566y0IgoCAgIBGj2dTVN+zf/9+hISEIDMzE//4xz8AAAEBAbDZbFi9ejVuuOEGvPHGG4y3n2C8lYcxV449e/Zg7NixeOCBB3DLLbc0uf+bb77hZ7ifYKyVhzFXluPHj2PmzJm46aabsGzZMvTs2RNA/TRNANi2bRvmzJmDlStXQhAE9o3yYXKONXtKkddlZ2dj8uTJmD17Np566ikAwN///neEhYVhxYoVDdu5ygjJP/zwww9YsGABbrnlFnz88ccYM2YMVq5cCQA4ceIEunbtKvEIyZ0Yb+VhzJXh4MGDGDBgABYvXozHHnsMTqcTv/76K44ePYqMjAz06tULer2+SV8x8j2MtfIw5srz2WefYeXKlfjll1/gdDqxePFiHDt2DDabDXfddRfOPfdcqYdIbiLnWAdKdmRSJIfDgfXr12PKlCm49957G5qshYSEICsrCxMnTkRycjJuu+02jBkzptkmbOSbBgwYgGHDhuHvf/87goOD8f7772PhwoWoqKjAiBEjcMsttyAoKEjqYZKbMN7Kw5j7P6fTic8//xwOhwNXXHEFAGDatGkwGo3Izc1FTEwMUlNTsXz5cvYX8XGMtfIw5sp0/Phx6HQ6AMC4ceOg1WrRpUsX2Gw2TJ48GW+//TZuueUW/ibzA7KOtdcmChKdkp2dLWZlZTX8fenSpaJGoxGfeeYZcfHixeLVV18tpqWlNeoxRb7PbDaLAwcOFHft2iWazWbxzTffFGNiYkRBEMS9e/eKovhX/xnyfYy38jDmylBUVCTeeuutolqtFjMyMsTLLrtM3L17t2iz2cSvvvpKPO+888Qrr7xSrKqqknqo1EmMtfIw5srz8ccfi/Hx8eLbb78tzpgxQzQajQ33Pf3002JgYGCj323ku+Qca9ZdktelpqYiPT0dAGC1WrF161b85z//wUMPPYSlS5fizjvvRHV1NY4ePSrxSMld7HY71Go1EhISUF1djdDQUPz000+w2+3o2bMn3n77bQDgdE0/wXgrD2OuHPHx8XjqqacwZ84caDQaPPXUUxg0aBCCgoJw6aWX4oILLsDvv//eaFUf8k2MtfIw5sozduxYjBw5Eq+//josFguio6PhdDoB1LdXSU1Nxb59+yQeJbmDnGPN6XvkcQUFBdi5cydsNhuSk5MxbNgwCIIAh8MBtVqNNWvWQKVSNcxPj46ORnx8PKKjo6UeOnXA6fFOSUnB0KFDG6bsDBs2DEePHsWbb76JDRs2YM2aNcjMzMSzzz6LwMBA/Otf/5J49NRejLfyMObKcnq8u3fvjuHDh0Ov1+PRRx9FXl4eevToAeCvPpA9e/ZEVFQUgoODJR45tRdjrTyMubI095ssOTkZEyZMwPPPPw+bzYacnBykpqYCAMLDwxEZGQm1Wi3xyKm9fC3WTEqRR2VmZmLWrFmIjY1FdnY2UlJS8OCDD+KKK65ouGLumrPqapj44YcfQqPRIDk5WbJxU8e0Fm8AUKvVuOWWW5CSkoK1a9di6NChGDhwIFQqFc4//3yJR0/txXgrD2OuLM3F+4EHHsCVV16JxMREJCQkNHyGuz7Tf/zxR3Tt2hWhoaFSDp3aibFWHsZcWZqL93333Yerr74a9957LxwOB1588UXMmjULb775JsLCwvDFF1/AYDBg6NChUg+f2sEnYy3JpEFShKNHj4pdu3YVH3jgAbG8vFz8888/xZtuukm85ZZbxLq6OtHpdDbaPi8vT7z//vvFqKgocc+ePRKNmjqqtXjb7XZRFEXRbreLt99+u7ht2zZRFMWG14DD4ZBs3NQxjLfyMObK0pHP8Pvuu0+Mjo5u6CFGvoGxVh7GXFlai7fVam3Y7uOPPxYvuOACURAEsX///mLPnj3FnTt3Sjhyai9fjTWTUuQRVqtVXLhwoXjVVVc1egO88847YkxMjFhaWtpo++3bt4u33367OGjQIHH37t3eHi51UnvjTb6N8VYexlxZ2hvvrVu3irfccovYt29fcdeuXV4eLXUGY608jLmydOTze8eOHeKRI0fE4uJibw6VOsmXY83pe+QRTqcTXbt2Rb9+/RAcHNywtOSYMWMQHh4Ou93eaPvhw4ejpqYGjz76KBITEyUaNXVUe+Pteoxryib5FsZbeRhzZWlvvEeMGIGqqio88cQTSEpKkmjU1BGMtfIw5srS1ni7bgeAwYMH8/PbB/lyrJmUIo/QaDSYNWtWQ/M0l8jISAQFBTX6wNuxYweGDRuG8ePHe3uY5CbtifeuXbswZMgQWZwAqWMYb+VhzJWlI5/hU6ZM8fYwyQ0Ya+VhzJWlrfEWBIGf3z7Ol2Mtj1GQXygsLMS2bduwbt06OJ3OhjeEw+FoyMZWVFSgrKys4TGLFy/GtGnTYDQaIYqiJOOmjulovKdMmcJ4+yDGW3kYc2XhZ7hyMNbKw5grCz+/lcNvYu3d2YLkr/bs2SMmJyeLvXv3FnU6ndi3b1/xk08+EY1GoyiKfzW7PXTokKjX60WTySQ++eSTYkhIiPjnn39KOXTqAMZbWRhv5WHMlYXxVg7GWnkYc2VhvJXDn2LNpBR1WklJidi3b1/x4YcfFo8dOyaePHlSvPrqq8V+/fqJS5YsEUtKShq2LS4uFocMGSJeffXVYnBwsOzeEHR2jLeyMN7Kw5grC+OtHIy18jDmysJ4K4e/xZpJKeq0ffv2iSkpKU1e4A8++KA4YMAA8fnnnxfNZrMoiqK4f/9+URAEMSQkhCt4+CjGW1kYb+VhzJWF8VYOxlp5GHNlYbyVw99izZ5S1Gl2ux11dXWwWCwAgJqaGgDAs88+i0mTJuH111/H0aNHAQBRUVG4/fbbsXPnTgwePFiqIVMnMN7KwngrD2OuLIy3cjDWysOYKwvjrRz+FmtBFOXS3Yp82YgRIxAeHo6ff/4ZAGC1WqFWqwEA55xzDnr27IlVq1YBAGpra6HRaCQbK3Ue460sjLfyMObKwngrB2OtPIy5sjDeyuFPsWalFLWb2WxGVVUVKisrG2574403sG/fPlx33XUAALVajbq6OgDAhAkTYDabG7aV8xuCmmK8lYXxVh7GXFkYb+VgrJWHMVcWxls5/D3WTEpRu+zfvx+XXXYZJk6ciH79+uHjjz8GAPTr1w8rVqzA+vXrceWVV8Jut0Olqn95lZSUICwsDHV1dfJZdpLahPFWFsZbeRhzZWG8lYOxVh7GXFkYb+VQQqwDpR4A+Y79+/djwoQJuPHGGzF8+HDs2LEDN998M9LT0zFkyBBcfPHFCAsLw+23346BAweib9++CA4OxnfffYctW7YgMJAvN1/CeCsL4608jLmyMN7KwVgrD2OuLIy3cigl1uwpRW1iMplw7bXXom/fvlixYkXD7ZMmTcKAAQPw0ksvNdxWVVWFp556CiaTCRqNBvPmzUN6eroUw6YOYryVhfFWHsZcWRhv5WCslYcxVxbGWzmUFGvfSJ2R5Ox2O8rLy3HFFVcAAJxOJ1QqFVJTU2EymQAAoihCFEVERETgueeea7Qd+RbGW1kYb+VhzJWF8VYOxlp5GHNlYbyVQ0mx9q3RkmTi4+Px0UcfYfz48QAAh8MBAEhKSmp40QuCAJVK1agBmyAI3h8sdRrjrSyMt/Iw5srCeCsHY608jLmyMN7KoaRYMylFbdarVy8A9dnXoKAgAPXZ2ZKSkoZtli1bhrfffruh878vvimoHuOtLIy38jDmysJ4KwdjrTyMubIw3sqhlFhz+h61m0qlgiiKDS94V6Z28eLFeOqpp7Br1y6faapGZ8d4KwvjrTyMubIw3srBWCsPY64sjLdy+HusWSlFHeLqjx8YGIhu3brhn//8J55//nn8+eefGDRokMSjI3djvJWF8VYexlxZGG/lYKyVhzFXFsZbOfw51r6bTiNJubKzQUFBeOutt6DVarFx40YMHTpU4pGRJzDeysJ4Kw9jriyMt3Iw1srDmCsL460c/hxrVkpRp5x//vkAgE2bNmH48OESj4Y8jfFWFsZbeRhzZWG8lYOxVh7GXFkYb+Xwx1gLoqsOjKiDzGYzwsLCpB4GeQnjrSyMt/Iw5srCeCsHY608jLmyMN7K4W+xZlKKiIiIiIiIiIi8jtP3iIiIiIiIiIjI65iUIiIiIiIiIiIir2NSioiIiIiIiIiIvI5JKSIiIiIiIiIi8jompYiIiIiIiIiIyOuYlCIiIiIiIiIiIq9jUoqIiIhIYn/7298wa9YsqYdBRERE5FWBUg+AiIiIyJ8JgtDq/UuWLMGKFSsgiqKXRkREREQkD0xKEREREXlQYWFhw/9/9tlnWLx4MQ4dOtRwW3h4OMLDw6UYGhEREZGkOH2PiIiIyIMSEhIa/uh0OgiC0Oi28PDwJtP3zj33XNx1111YsGABoqKiEB8fj7feegtmsxk333wzIiIi0LNnT/zwww+NjpWVlYULLrgA4eHhiI+Pxw033IDS0lIv/4uJiIiI2oZJKSIiIiIZ+uCDDxAbG4tt27bhrrvuwrx583DllVdizJgx2LlzJ8477zzccMMNsFgsAIDy8nJMnjwZQ4YMwZ9//ol169ahuLgYV111lcT/EiIiIqLmMSlFREREJEODBg3Co48+il69euGhhx6CRqNBbGws5s6di169emHx4sUwGo3Yu3cvAOCVV17BkCFD8Mwzz6Bv374YMmQI3n33Xfzyyy84fPiwxP8aIiIioqbYU4qIiIhIhgYOHNjw/wEBAYiJicGAAQMabouPjwcAlJSUAAD27NmDX375pdn+VMeOHUPv3r09PGIiIiKi9mFSioiIiEiGgoKCGv1dEIRGt7lW9XM6nQCA6upqzJw5E88991yTfSUmJnpwpEREREQdw6QUERERkR8YOnQovvzyS6SkpCAwkF/xiIiISP7YU4qIiIjID9xxxx0wmUy49tprsX37dhw7dgz//e9/cfPNN8PhcEg9PCIiIqImmJQiIiIi8gNdunTBH3/8AYfDgfPOOw8DBgzAggULEBkZCZWKX/mIiIhIfgRRFEWpB0FERERERERERMrCy2ZEREREREREROR1TEoREREREREREZHXMSlFRERERERERERex6QUERERERERERF5HZNSRERERERERETkdUxKERERERERERGR1zEpRUREREREREREXsekFBEREREREREReR2TUkRERERERERE5HVMShERERERERERkdcxKUVERERERERERF73/7o6QXlPY2wGAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(12,5))\n", + "\n", + "plt.plot(ssh_ts.time, ssh_ts, marker='o', linewidth=1)\n", + "\n", + "plt.title(\"SWOT Pass 289 –- Spatial Mean SSH Anomaly \\nBBox: (122.5W, 34.5N, 121.5W, 36.5N)\")\n", + "plt.xlabel(\"Time\")\n", + "plt.ylabel(\"Mean SSH Anomaly (m)\")\n", + "plt.grid(alpha=0.3)\n", + "\n", + "plt.xticks(rotation=45)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "b1565654-a7c7-49fb-80ef-631cfd822e43", + "metadata": {}, + "source": [ + "### 3c. Use case 3: Spatially plot just a specific cycle/pass from our previous time series (plot one time step)\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "878d9839-9536-49f0-b7f7-968d7ac4b43d", + "metadata": {}, + "outputs": [], + "source": [ + "ds = data_vds.where(\n", + " (data_vds.cycle.compute() == 29) & (data_vds.ppass.compute() == 289),\n", + " drop=True\n", + ")\n", + "\n", + "# find the granule number (index) for this cycle/pass\n", + "granule_index = ds.granule.values" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "78b0961b-164f-4dd6-8420-656200779b68", + "metadata": {}, + "outputs": [], + "source": [ + "ssh = ds.ssha_karin.where(ds.ssh_karin < 1000)\n", + "\n", + "lat = ds.latitude\n", + "lon = ds.longitude" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "d86f1c8e-253d-4205-a043-1ab6f6187db7", + "metadata": {}, + "outputs": [], + "source": [ + "ssh = ssh.squeeze()\n", + "lat = lat.squeeze()\n", + "lon = lon.squeeze()" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "48ab220f-a511-4025-be85-906d490b5605", + "metadata": {}, + "outputs": [], + "source": [ + "# swath plot area\n", + "lon_min, lon_max = 232, 240\n", + "lat_min, lat_max = 30, 40" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "4fd64d22-0336-4f9d-b05f-3e7d9770209d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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/fv2ElZWVxmSfiFQxCdQgOjpanD9/XowYMULY2toKKysrcePGDeXxhGrCjBkzhEKhEC4uLuK3334TQnz9Ynd2dhYrVqwQX758EdbW1iqd0NNaCYyIiFA7pk0S+K3nz5+LDRs2iDJlyggAap2yE6T0HHQ1MKRFixbCz89P3Lt3T7ndvHlT2NvbixEjRqic6+PjI+rUqaN2jcqVK6sMJrGxsVHr/C+EEDt27BAAxO7du1Xi3Lhxo8p5K1asEADEuXPnVPYnJC/fDqY5deqUqF69ukrSnLB9W93RNDBkyJAhwtHRUXz69EkIIcTw4cOFra2tSvKoyatXr8SLFy+U24cPH4QQQmXfixcvNFYpE6S1EhgXFyc8PT1F586dhRD/T2K/TWA2btwoAIhDhw4le63ESWCPHj2SrSgnVLRS48WLF8Lf3194e3trTFSePn0qypcvr7y2XC4XQ4YMEaVLlxaZMmVK8fq7du0SQUFBwsbGRiVGmUymch4A8eOPP6q938fHR3Tq1EkZKwAxatQotfMGDBiQ6iTQ1tZW+QvYyZMnxZMnT1TOiY+PF7NmzRK5c+dWVhgTtqpVqyrPu3nzpsiePbsAIHLnzi169uwpTp06pXKtTZs2CVtbW2FhYSFKlSolxowZk+QgtqSk9DOqU6eOqF+/vsq+t2/fChcXF9GyZUuV/fPmzRMODg7Kz5M7d24xffr0VP0yQmTu2CdQA2tra5QqVQqTJ0/GwoULERsbi82bNyuPFylSBE5OTjh16hRu376Nd+/eoVy5cgC+dsgOCgrCqVOnlH0Fv+0PmClTJnh6euLq1avJxnD16lVkz54dzs7OOv98np6eysEXefLkwR9//KGxr2BKz0EXIiMjsWvXLoSEhCBPnjzKrWDBgvj8+TPWr18PIYTKe+RyucZrJT4vLZK6Zkr3evDgAapXr443b95g1qxZ2LNnDw4dOoQBAwYAABQKRbL37dChAz5+/IgdO3ZACIH169ejfv36KtMPaVKqVCl4enoqt4QBHN/u8/T0xKZNm5K8RsK0QNeuXUv2Xgnkcjnatm2LrVu3IioqCseOHcPz58/Rvn37VL0/OQqFAjKZDPv378ehQ4fUttQOlIiIiEBwcDDCw8Oxf/9+eHl5qZ2TPXt2nDp1Cnfv3lUOQJo+fTqePHmCvHnzJnv9v/76Cw0bNoStrS1+++037N27F4cOHULbtm01/v3Tx99VTeRyOWrUqIEaNWqgYsWKyJEjh8rxyZMnY+DAgahUqRLWrl2LAwcO4NChQyhUqJDK39ECBQoopweqUKECtm7digoVKmDMmDHKc1q2bImHDx9i3rx58PLywi+//IJChQph3759qYo1pZ/Rw4cPsX//fjRs2FBlv4uLCypUqKDS5xoAevfujZcvX+LMmTP4559/cPv2beW/n5R+nkTmjvMEpqBkyZIAgBcvXij3yeVylClTBqdPn8apU6fg7OyMgIAA5fFy5cph06ZNyJ07NwDVQSEAUL9+ffz+++84deqU2jHg6xdNaGgounfvro+PpGRlZYXAwEDcu3cPb968gYeHR5LnanoOurBt2zZERUVh4cKFap3D79y5g59//hmnT5/W+JyS4+Pjgzt37qjtT5gYO2GwTHrt2rUL0dHR2LlzJ3LmzKncn9rJagsXLoxixYph3bp1yJEjBx4/fqw2Kbcm69atw5cvX5Sv/f39AXwdlPGtQoUKJXmNBg0aYMqUKVi7dm2Sg5QS69ChA2bOnIldu3Zh3759cHV1Re3atZXHc+XKBQC4fv06atSokaprJrxPCAE/Pz+tv7ijoqLQoEED3L17F4cPH0bBggWTPT/hFw4AuHnzJl68eIFOnTol+56tW7fC1tYWBw4cgI2NjXL/ihUrtIrZ1dUVdnZ2Gkexavr7q60tW7agatWqWLZsmcr+8PBwtX93Dg4OaNWqFVq1aoWYmBg0bdoUkyZNwogRI2Brawvg6y8bPXv2RM+ePfHq1SsUL14ckyZNQnBwcLJxpOZn9PLlSwBQGzAFfB2IpukXVgcHB5V5WA8fPgw7OzuNMyIQ0f+xEvifY8eOafztfO/evQCgMgUB8DWxe/36NVasWIGgoCBYWPz/UZYrVw537tzBn3/+iaxZs6pN4jxkyBDY2dmhe/fuKqMEAeDdu3f48ccfYW9vjyFDhujks927dw+PHz9W2x8eHo6zZ88iS5Ysyqlq0voc0mvt2rXw9/fHjz/+iObNm6tsgwcPhqOjo8YRqSmpW7cuzp8/j7Nnzyr3ffr0CUuWLIGvr2+KCUJqJVR6vn1mERERaUoKvvvuOxw8eBBz5sxB1qxZU/wiBb5O95NQ+alRo4YyCfx2X40aNeDp6ZnkNcqWLYs6depg6dKl2LFjh9rxmJgYDB48WGVfYGAgAgMDsXTpUmzduhWtW7eGpeX/f5csXrw4/Pz8MGfOHLURvclVv5o2bQq5XI5x48apnSeEUPt3klh8fDxatWqFs2fPYvPmzSoJQUoUCgWGDh0Ke3t7/Pjjj8meK5fLIZPJVBKU0NBQjc8vNeRyOWrXro0dO3ao/Bu9deuWTieulsvlas918+bNKtP6AFB7ztbW1ihYsCCEEIiNjUV8fLzayH83Nzd4eXmluDpJan9GuXPnhoWFBTZt2qQS89OnT5VTwiTnzJkz2LZtG77//vsUK+pE5o6VwP/06dMHnz9/RpMmTZA/f37ExMTgzJkz2LRpE3x9fdG5c2eV8xMqU2fPnsXYsWNVjpUpUwYymQznzp1DgwYN1Nb/zJMnD1atWoV27dohICBAbcWQN2/eYMOGDcqqSnr9+++/aNu2LYKDg1GxYkW4uLjg2bNnWLVqFZ4/f445c+Yok5m0Pof0eP78OY4dO4a+fftqPG5jY4PatWtj8+bN+PXXX1VWYUnJ8OHDsWHDBgQHB6Nv375wcXHBqlWrEBISgq1bt6ok7elRq1YtWFtbo0GDBujevTs+fvyI33//HW5ubqmumrZt2xZDhw7F9u3b0aNHjzR9zvRavXo1atWqhaZNm6JBgwaoXr06HBwccO/ePWzcuBEvXrxQNjUn6NChgzI5TNwUbGFhgYULF6JBgwYoWrQoOnfuDE9PT9y+fTvZFTly5cqFiRMnYsSIEQgNDUXjxo3h5OSEkJAQbN++Hd26dVNLSL81aNAg7Ny5Ew0aNMC7d++wdu1alePfxtmvXz9ERUWhaNGiiI2Nxfr163H+/HmsWrVKpZqrSb169TBr1izUqVMHbdu2xatXr7BgwQLkzp07xS4eSRk3bhz279+PihUromfPnoiLi1PO1aftNROrX78+xo8fj86dO6NcuXK4du0a1q1bp/zlIUGtWrXg4eGB8uXLw93dHbdu3cL8+fNRr149ODk5ITw8HDly5EDz5s1RpEgRODo64vDhw7hw4QJmzpyZbAyp/Rm5urqiS5cuWLp0KapXr46mTZviw4cP+O233/DlyxeMGDFC+Z5Hjx6hZcuWaNiwITw8PHDjxg0sWrQIgYGBmDx5sk6eHVGGZvhuiMZp3759okuXLiJ//vzC0dFRWFtbi9y5c4s+ffqorZQhxNdZ6S0tLQUAcfDgQbXjgYGBAoCYNm1akve8evWqaNOmjfD09BRWVlbCw8NDtGnTRjlyNSlpHRjy8uVLMXXqVFG5cmXh6ekpLC0tRZYsWUS1atXUVopIy3NI78CQmTNnCgDiyJEjSZ6zcuVKAUA5Mjmpe2oadPHgwQPRvHlzkTlzZmFraytKly6tHBCSUpwJA0MuXLigsj9hQMPr16+V+3bu3CkCAwOFra2t8PX1FdOmTRPLly8XAERISEiyMSZIGAmaeAoMQ/j8+bOYMWOGKFWqlPJnnidPHtGnTx+V6U0SvHjxQsjlcpE3b94kr3nq1ClRs2ZN4eTkJBwcHERgYKDKtChJrYaxdetWUaFCBeHg4CAcHBxE/vz5Ra9evcSdO3eS/QwJUyAltX1rxYoVokiRIsLBwUE4OTmJ6tWri6NHj6b0mJSWLVsm8uTJI2xsbET+/PnFihUrNH4eABqnUvHx8REdO3ZU2XfixAlRokQJYW1tLfz9/cWiRYvStWJIYgmrv3h6ego7OztRvnx5cfbsWbW/k4sXLxaVKlUSWbNmFTY2NiJXrlxiyJAhygFq0dHRYsiQIaJIkSLKn22RIkWUA+OSk5afUWxsrJg3b54oWrSocHR0FI6OjqJq1apqP6d3796JRo0aCQ8PD2FtbS38/PzEsGHDNE6tRUTqZELouIcyEaVZkyZNcO3aNdy/f1/qUFL05s0beHp6YvTo0Rg1apTU4RARkZbYJ5BIYi9evMCePXtStXKHMVi5ciXi4+NNJl4iItKMfQKJJBISEoLTp09j6dKlsLKy0vto8PQ6evQobt68iUmTJqFx48bw9fWVOiQiIkoHJoFEEjlx4gQ6d+6MnDlzYtWqVclO0WMMxo8fjzNnzqB8+fKpmsaGiIiMG/sEEhEREZkh9gkkIiIiMkNMAomIiIjMEJNA0htfX1/Ur19f6jCU9u/fj6JFi8LW1hYymUxtRQtTIZPJ1CYoNwdVqlRBlSpVDHpPX1/fFJeSMxamFCsRGQcmgZRqoaGhkMlkKpuzszOKFi2K+fPna1zr01i8ffsWLVu2hJ2dHRYsWIA1a9bAwcFB6rCStHfvXrNM9IiIyHA4OpjSrE2bNqhbty6Ar+vk7t27F3369MGjR4/wyy+/SBydZhcuXMCHDx8wYcIE1KhRQ+pwUrR3714sWLBAYyL45csXlfV6zcXBgwcNfs87d+7obIlBIiJjY37fJJRuxYsXV1mLtWfPnggKCsL69euNNgl89eoVACBz5swpnvv582fY29vrOSLt2draSh2CQSX8PKytrQ1+bxsbG73f49OnT0ZdlSaijIu/4lK6yWQyuLu7J1mdOnjwoLIvXsGCBbFt2za1cx4+fIgWLVrAxcUF9vb2KFOmDPbs2aM8fuvWLdjZ2aFDhw4q7zt16hTkcjmGDRuWZHxVqlRBx44dAQClSpWCTCZT9p2qUqUKChcujIsXL6JSpUqwt7fHyJEjAXxNHL///nu4u7vD1tYWRYoUwapVq1SundBEPmPGDCxYsAD+/v6wt7dHrVq18OTJEwghMGHCBOTIkQN2dnZo1KgR3r17l+zz7NSpExYsWKB8tglbgsR9AseOHQuZTIa7d++iffv2yJQpE1xdXTFq1CgIIfDkyRM0atQIzs7O8PDwwMyZM9XuGR0djTFjxiB37tywsbGBt7c3hg4diujo6GRjBYB79+6hWbNm8PDwgK2tLXLkyIHWrVsjIiJC5by1a9eiRIkSsLOzg4uLC1q3bo0nT56onJPcz0NTn8DUxn3o0CFUqFABmTNnhqOjI/Lly6e8bnIS97NbuXIlZDIZTp8+jYEDB8LV1RUODg5o0qQJXr9+neL1OnXqBEdHRzx48AB169aFk5MT2rVrBwBQKBSYM2cOChUqBFtbW7i7u6N79+54//69yjWEEJg4cSJy5MgBe3t7VK1aFTdu3Ejx3kREibESSGn2+fNnvHnzBgAQGRmJffv2Yf/+/RgxYoTauffu3UOrVq3w448/omPHjlixYgVatGiB/fv3o2bNmgCAly9foly5cvj8+TP69u2LrFmzYtWqVWjYsCG2bNmCJk2aoECBApgwYQKGDBmC5s2bo2HDhvj06RM6deqE/PnzY/z48UnG+9NPPyFfvnxYsmQJxo8fDz8/P+TKlUt5/O3btwgODkbr1q3Rvn17uLu748uXL6hSpQru37+P3r17w8/PD5s3b0anTp0QHh6Ofv36qdxj3bp1iImJQZ8+ffDu3TtMnz4dLVu2RLVq1XD8+HEMGzYM9+/fx7x58zB48GAsX748yXi7d++O58+f49ChQ1izZk2qfy6tWrVCgQIFMHXqVOzZswcTJ06Ei4sLFi9ejGrVqmHatGlYt24dBg8ejFKlSqFSpUoAviYfDRs2xKlTp9CtWzcUKFAA165dw+zZs3H37l3s2LEjyXvGxMSgdu3aiI6ORp8+feDh4YFnz55h9+7dCA8PR6ZMmQAAkyZNwqhRo9CyZUv88MMPeP36NebNm4dKlSrh8uXLKhVaTT8PTVIb940bN1C/fn0EBgZi/PjxsLGxwf3793H69OlUP9vE+vTpgyxZsmDMmDEIDQ3FnDlz0Lt3b2zatCnF98bFxaF27dqoUKECZsyYoaw6d+/eHStXrkTnzp3Rt29fhISEYP78+bh8+TJOnz4NKysrAMDo0aMxceJE1K1bF3Xr1sWlS5dQq1YtxMTEaP15iMhMCaJUCgkJEQA0bj169BAKhULlfB8fHwFAbN26VbkvIiJCeHp6imLFiin39e/fXwAQf/31l3Lfhw8fhJ+fn/D19RXx8fFCCCHi4+NFhQoVhLu7u3jz5o3o1auXsLS0FBcuXEgx9hUrVggAaudWrlxZABCLFi1S2T9nzhwBQKxdu1a5LyYmRpQtW1Y4OjqKyMhIlWfi6uoqwsPDleeOGDFCABBFihQRsbGxyv1t2rQR1tbWIioqKtl4e/XqJZL65wlAjBkzRvl6zJgxAoDo1q2bcl9cXJzIkSOHkMlkYurUqcr979+/F3Z2dqJjx47KfWvWrBEWFhYqz18IIRYtWiQAiNOnTycZ5+XLlwUAsXnz5iTPCQ0NFXK5XEyaNEll/7Vr14SlpaXK/qR+HgnHKleunOa4Z8+eLQCI169fJxljUnx8fFSeVcLfoxo1aqj8fR8wYICQy+Uqfwc06dixowAghg8frrL/r7/+EgDEunXrVPbv379fZf+rV6+EtbW1qFevnsr9R44cKQCoxEpElBI2B1OadevWDYcOHcKhQ4ewdetW9OrVC4sXL8bAgQPVzvXy8kKTJk2Ur52dndGhQwdcvnwZYWFhAL4OgihdujQqVKigPM/R0RHdunVDaGgobt68CQCwsLDAypUr8fHjRwQHB+O3337DiBEjULJkyXR9HhsbG3Tu3Fll3969e+Hh4YE2bdoo91lZWaFv3774+PEjTpw4oXJ+ixYtlFUvAAgKCgIAtG/fXqWZPCgoCDExMXj27Fm6Ytbkhx9+UP5ZLpejZMmSEELg+++/V+7PnDkz8uXLh4cPHyr3bd68GQUKFED+/Pnx5s0b5VatWjUAwLFjx5K8Z8JnPnDgAD5//qzxnG3btkGhUKBly5Yq1/fw8ECePHnUrq/p56FJauNOqDL++eefUCgUKV43Nbp166bSRF+xYkXEx8fj0aNHqXp/jx49VF5v3rwZmTJlQs2aNVU+S4kSJeDo6Kj8LIcPH1ZWnL+9f//+/dP/oYjI7LA5mNIsT548KiNsmzZtCplMhjlz5qBLly4ICAhQHsudO7fKlxUA5M2bF8DX/nQeHh549OiRMmn6VoECBQAAjx49QuHChQEAuXLlwtixYzFkyBAULlwYo0aNSvfnyZ49u9qgg0ePHiFPnjxqI0O/jelbOXPmVHmdkBx5e3tr3J+4n5cuaIrB1tYW2bJlU9v/9u1b5et79+7h1q1bcHV11XjdhEE1mvj5+WHgwIGYNWsW1q1bh4oVK6Jhw4bKvokJ1xdCIE+ePBqvkdDMmUDTz0OT1MbdqlUrLF26FD/88AOGDx+O6tWro2nTpmjevLnWI38TP+ssWbIASN3P1dLSEjly5FDZd+/ePURERMDNzU3jexI+S8Lfu8TP0tXVVRkDEVFqMQkknahevTrmz5+PkydPqiSB+pAwVcjz58/x9u1beHh4pOt6dnZ26Y5JLpenab/Qw5Ldmu6VmvsrFAoEBARg1qxZGs9NnMgmNnPmTHTq1Al//vknDh48iL59+2LKlCk4d+4ccuTIAYVCAZlMhn379mmMx9HRUeV1an8eqY3bzs4OJ0+exLFjx7Bnzx7s378fmzZtQrVq1XDw4MEkn1Fy0vNztbGxUUs+FQoF3NzcsG7dOo3vSSrRJSJKDyaBpBNxcXEAgI8fP6rsv3//PoQQKtXAu3fvAvg68hIAfHx8cOfOHbVr3r59W3k8waJFi3Do0CFMmjQJU6ZMQffu3fHnn3/q9LMk3PPq1atQKBQqX9iaYtKHxNVTfcqVKxf+/fdfVK9eXev7BgQEICAgAD///DPOnDmD8uXLY9GiRZg4cSJy5coFIQT8/PyUVWBDx21hYYHq1aujevXqmDVrFiZPnoyffvoJx44dM4p5I3PlyoXDhw+jfPnyySbBCX/v7t27B39/f+X+169f66W6TEQZG/sEkk7s2rULAFCkSBGV/c+fP8f27duVryMjI7F69WoULVpUWcGrW7cuzp8/j7NnzyrP+/TpE5YsWQJfX18ULFgQABASEoIhQ4agWbNmGDlyJGbMmIGdO3di9erVOv88devWRVhYmMpoz7i4OMybNw+Ojo6oXLmyzu/5rYR54wyxtF3Lli3x7Nkz/P7772rHvnz5gk+fPiX53sjISOUvAAkCAgJgYWGhnKaladOmkMvlGDdunFqlTAih0jStj7g1TclTtGhRAEjVFDiG0LJlS8THx2PChAlqx+Li4pR/D2rUqAErKyvMmzdP5VnOmTPHQJESUUbCSiCl2aVLl7B27VoAwIcPH3DkyBFs3boV5cqVQ61atVTOzZs3L77//ntcuHAB7u7uWL58OV6+fIkVK1Yozxk+fDg2bNiA4OBg9O3bFy4uLli1ahVCQkKwdetWWFhYQAiBLl26wM7ODgsXLgTwdUqNrVu3ol+/fqhRowa8vLx09hm7deuGxYsXo1OnTrh48SJ8fX2xZcsWnD59GnPmzIGTk5PO7qVJiRIlAAB9+/ZF7dq1IZfL0bp1a73c67vvvsMff/yBH3/8EceOHUP58uURHx+P27dv448//sCBAweSHHxz9OhR9O7dGy1atEDevHkRFxeHNWvWQC6Xo1mzZgC+VrkmTpyIESNGIDQ0FI0bN4aTkxNCQkKwfft2dOvWDYMHD9Zb3OPHj8fJkydRr149+Pj44NWrV/jtt9+QI0cOlcFIUqpcuTK6d++OKVOm4MqVK6hVqxasrKxw7949bN68GXPnzkXz5s3h6uqKwYMHY8qUKahfvz7q1q2Ly5cvY9++fWp9P4mIUsIkkNJsw4YN2LBhA4Cvndxz5syJIUOGYPTo0Wp9nfLkyYN58+ZhyJAhuHPnDvz8/LBp0ybUrl1beY67uzvOnDmDYcOGYd68eYiKikJgYCB27dqFevXqAQDmzZuH48ePY+vWrSr9o5YtW4bChQuja9euKpNLp5ednR2OHz+O4cOHY9WqVYiMjES+fPmwYsUKlcmD9aVp06bo06cPNm7ciLVr10IIobck0MLCAjt27MDs2bOxevVqbN++Hfb29vD390e/fv2SbcItUqQIateujV27duHZs2ewt7dHkSJFsG/fPpQpU0Z53vDhw5E3b17Mnj0b48aNA/C1z16tWrXQsGFDvcbdsGFDhIaGYvny5Xjz5g2yZcuGypUrY9y4cSojuqW2aNEilChRAosXL8bIkSNhaWkJX19ftG/fHuXLl1eeN3HiRNja2mLRokU4duwYgoKCcPDgQeW/FSKi1JIJffRQJyIiIiKjxj6BRERERGaISSARERGRGWISSERERGSGmAQSERERmSEmgURERERmiEkgERERkRlK9TyBUVFRiImJ0WcsREREpAPW1tawtbWVOgyNpMonjPmZSCVVSWBUVBT8/PwQFham73iIiIgonTw8PBASEmJ0SU9UVBT8fBwR9ire4Pc21mcipVQlgTExMQgLC8OTJ0/g7Oys75iIyABmzpyJ8ePHIzg4GAsXLkSWLFmkDomIdCAyMhLe3t6IiYkxuoQnJiYGYa/i8eiiL5ydDNcjLfKDAj4lQo3ymUgpTcvGOTs7MwkkyiDGjRuHYsWKoXPnzvjpp5+U60ETEembo5MMjk4yg91PAcPdy5RwYAiRGWvcuDFmzZqFdevW4dixY1KHQ0REBsQkkMjMdezYEeXLl0e7du2wb98+qcMhIiIDYRJIZOYsLCywadMmBAQEoG7duli/fr3UIRFRBhcvFAbfSB2TQCJC9uzZsX//fjRt2hTDhw9HVFSU1CEREZGeMQkkIgCATCbD1KlT8eLFC8yePVvqcIgoA1NAGHwjdUwCiUgpT5486NevH0aOHIlRo0YhPt7wc3kREZFhMAkkIhXTp0/H5MmTMXnyZOTLlw+//fYbhOBv0UREGQ2TQCJSYWFhgREjRuDcuXMoUaIEevXqhXPnzkkdFhFlIAoJ/kfqmAQSkUalSpXChg0b4O3tjTVr1kgdDhER6RiTQCJKkoWFBZo1a4Zdu3axSZiIdCZeCINvpI5JIBElq0qVKnj69ClevHghdShERKRDaVo7mIjMT8Ji61++fJE4EiLKKAw9bQuniNGMlUAiSlapUqVgZWXFJeWIiDIYJoFElCwXFxfkzp0bp06dgkLBEXZElPFNmTIFpUqVgpOTE9zc3NC4cWPcuXNH5ZwqVapAJpOpbD/++KNEEWuHSSARpahVq1bYtGkTypUrh9jYWKnDISITp4BAvAG3tDYHnzhxQjk91qFDhxAbG4tatWrh06dPKud17doVL168UG7Tp0/X5WPSO/YJJKIUjR49GiVLlkSjRo0wc+ZMDB8+XOqQiIj0Zv/+/SqvV65cCTc3N1y8eBGVKlVS7re3t4eHh4ehw9MZVgKJKEUymQz16tXD999/j/nz50sdDhGZOFNbOzgiIgLA1+4x31q3bh2yZcuGwoULY8SIEfj8+XO67mNorAQSUaqVL18eS5YsQXh4ODJnzix1OEREaRIZGany2sbGBjY2Nsm+R6FQoH///ihfvjwKFy6s3N+2bVv4+PjAy8sLV69exbBhw3Dnzh1s27ZNL7HrA5NAIkq1EiVKAACuXbuGihUrShwNEVHaeHt7q7weM2YMxo4dm+x7evXqhevXr+PUqVMq+7t166b8c0BAADw9PVG9enU8ePAAuXLl0lnM+sQkkIhSzdKS/8kgovQz9CoeCfd68uQJnJ2dlftTqgL27t0bu3fvxsmTJ5EjR45kzw0KCgIA3L9/n0kgEWU8CUvHWViwOzERmR5nZ2eVJDApQgj06dMH27dvx/Hjx+Hn55fie65cuQIA8PT0TG+YBsMkkIhSLSEJjI6OljgSIjJliv82Q94vLXr16oX169fjzz//hJOTE8LCwgAAmTJlgp2dHR48eID169ejbt26yJo1K65evYoBAwagUqVKCAwM1P0H0BP+Ok9EqZYrVy7kzJkTixYtkjoUIiK9WbhwISIiIlClShV4enoqt02bNgEArK2tcfjwYdSqVQv58+fHoEGD0KxZM+zatUviyNOGlUAiSjVra2uMHTsWXbp0wY0bN1CoUCGpQyIiE5QwibMh75cWIoX+it7e3jhx4kR6QjIKrAQSUZrUqlULAPD48WOJIyEiovRgEkhEaXLo0CEAQJ48eSSOhIiI0oPNwUSUap8/f8bo0aPRuHFj5M6dW+pwiMhExYuvmyHvR+pYCSSiVJsxYwbCwsLwyy+/SB0KERGlEyuBRJQqnz59wowZM9CnTx9WAYkoXYx9ihhzwUogEaXKli1b8OHDB/Tp00fqUIiISAeYBBJRqixfvhzVq1eHr6+v1KEQEZEOsDmYiFIUHR2NkydPYvHixVKHQkQZgAIyxENm0PuROlYCiShFz58/B4BUrZ9JRESmgZVAIkpRQhLo5eUlcSRElBEoxNfNkPcjdawEElGKXr9+DQBwdXWVOBIiItIVJoFElKK3b98CAFxcXCSOhIiIdIXNwUSUordv3yJz5sywtOR/Mogo/eINPDDEkPcyJawEElGKPD09ER4eji1btkgdChER6QiTQCJKUfv27dGyZUt06dIFsbGxUodDRCYuoRJoyI3UMQkkohTJZDI0bNgQHz58wO3bt6UOh4iIdIBJIBGlSo0aNQAA27ZtkzgSIjJ1CiEz+EbqmAQSUarEx8dDJpPh77//hhCcdIuIyNQxCSSiVPHy8sKKFSuwb98+3LlzR+pwiIgonZgEElGqNW/eHFZWVjh8+LDUoRCRCePAEOPAJJCIUs3BwQHlypXDwYMHpQ6FiIjSiUkgEaVJgwYNcPDgQYSHh0sdChGZqHhYGHwjdXwqRJQmbdq0QWxsLKZMmSJ1KERElA5MAokoTby8vDBlyhRMnz4dc+fOlTocIiLSEhcCJaI0Gzp0KN68eYP+/fujVKlSKFeunNQhEZEJEQaeu09wnkCNWAkkIq0MGDAAALBlyxbOG0hEZIKYBBKRVtzc3NCnTx/Mnj0bu3fvljocIjIhnCLGODAJJCKtyOVy/PrrryhUqBA2bdokdThERJRGTAKJKF1at26N7du3IyIiQupQiMhExAsLg2+kjk+FiNKlS5cuiIqKYjWQiMjEMAkkonTx8vJCjRo1sH79eqlDISKiNGASSETpVq9ePZw9exaxsbFSh0JEJkABGRSwMODGgSGaMAkkonQLCAhATEwMbt++LXUoRESUSpwsmojS7e7du5DL5XB3d5c6FCIyAYaetoVTxGjGSiARpYsQAosWLUKdOnXg5uYmdThERJRKrAQSUbrMnz8fV65cwZw5c6QOhYiI0oBJIBFp5dOnT1iwYAFGjx6Nvn37onLlylKHREQmwtBz98VzaUuN2BxMRFo5cOAAhg0bBjc3N0ybNk3qcIiIKI1YCSQirTRs2BBBQUGIjY2Fra2t1OEQkQn5OkWM4QZrcIoYzVgJJCKtWFpaol27drh8+TJatmyJz58/Sx0SERGlASuBRKS1Ll26AACGDx+OOnXqYMuWLRwhTEQpUsAC8QasQynAPoGasBJIRFpzcHBAnz59cOjQIdy9exclS5bEpUuXpA6LiIhSgUkgEaVbuXLl8M8//8Dd3R01a9bEq1evpA6JiIhSwCSQiHQiR44c2Lt3L2QyGdq1a4c3b95IHRIRGamEKWIMuZE6PhUi0hlXV1ds2LABly5dQkBAAA4fPix1SERElAQmgUSkUzVr1sT169cREBCAunXrYuvWrVKHRERGRgELg2+kjk+FiHTO09MTe/bsQbNmzdC8eXNUrFgRe/fulTosIiL6BpNAItILKysrrF27Fhs3boQQAk2bNsWGDRsQHx8vdWhERAQmgUSkR3K5HK1atcKBAwdQq1YttG3bFr1795Y6LCKSWLyQGXwjdUwCiUjvHBwcsHPnTsyaNQuLFy/Gli1bEBMTI3VYRERmjUkgERlM7969Ub58ebRo0QIeHh5YunSp1CERkQTi/1sxxJAbqeNTISKDsbKywsmTJ3H16lU0btwYXbt2Ra9evRAXFyd1aEREZodrBxORQclkMgQEBGD58uUoU6YMevbsiUePHmHjxo1wdHSUOjwiMgCFsIDCgBM4KwTXDtaElUAikky3bt2wZ88enDhxAjVr1pQ6HCIis8IkkIgkVbt2bSxfvhznzp1D48aN8fnzZ6lDIiIyC0wCiUhyzZs3x8aNG7Fv3z7MmjVL6nCISM84MMQ48KkQkeRkMhlatWqFXr16YcqUKTh58qTUIRERZXhMAonIaEyYMAFlypRBcHAwjhw5InU4RKQnChh2wmiF1B/YSDEJJCKj4eDggN27d6NChQqoX78+bt++LXVIRGSGpkyZglKlSsHJyQlubm5o3Lgx7ty5o3JOVFQUevXqhaxZs8LR0RHNmjXDy5cvJYpYO0wCicio2NnZYdGiRXB2dkaxYsWwY8cOqUMiIjNz4sQJ9OrVC+fOncOhQ4cQGxuLWrVq4dOnT8pzBgwYgF27dmHz5s04ceIEnj9/jqZNm0oYddrJhEh58pzIyEhkypQJERERcHZ2NkRcRGTmPn/+jHr16iEyMhKnT5+Gra2t1CERmQRj/s5OiG3hpVKwczTcVMVfPsahR/ELWj+T169fw83NDSdOnEClSpUQEREBV1dXrF+/Hs2bNwcA3L59GwUKFMDZs2dRpkwZXX8EvWAlkIiMkr29Pfr27YvLly/D19eXFUEiSrfIyEiVLTo6OlXvi4iIAAC4uLgAAC5evIjY2FjUqFFDeU7+/PmRM2dOnD17VveB6wmTQCIyWk2aNMGdO3dQpkwZNGnSBG3btjW5PjdEpC5eWBh8AwBvb29kypRJuU2ZMiXFWBUKBfr374/y5cujcOHCAICwsDBYW1sjc+bMKue6u7sjLCxM589LX7hsHBEZtTx58mD79u1Yu3YtBg4ciICAAOzbtw8lSpSQOjQiMjFPnjxRaQ62sbFJ8T29evXC9evXcerUKX2GJglWAonI6MlkMnz33Xe4efMm/P39UalSJXTv3h3nz59HKro1E5GRUUBm8A0AnJ2dVbaUksDevXtj9+7dOHbsGHLkyKHc7+HhgZiYGISHh6uc//LlS3h4eOj8eekLk0AiMhmurq44fPgwBg0ahL179yIoKAiBgYGYM2cO3rx5I3V4RJRBCCHQu3dvbN++HUePHoWfn5/K8RIlSsDKykplPtM7d+7g8ePHKFu2rKHD1RqTQCIyKY6Ojhg/fjxCQ0Oxb98+5M+fH0OHDkWOHDkwe/ZsKBScFpaI0qdXr15Yu3Yt1q9fDycnJ4SFhSEsLAxfvnwBAGTKlAnff/89Bg4ciGPHjuHixYvo3LkzypYtazIjgwEmgURkouRyOerUqYPNmzfj2bNn6NGjBwYOHIg6derg+fPnUodHRMmQamBIai1cuBARERGoUqUKPD09ldumTZuU58yePRv169dHs2bNUKlSJXh4eGDbtm26flR6xXkCiSjDOHToEDp27Ahvb2/8/fffUodDJAlj/s5OiG32P+UMPk/ggJJnjPKZSImVQCLKMGrWrInff/8d58+fx9q1a6UOh4iSEA8Lg2+kjk+FiDKUevXq4bvvvkPHjh2xf/9+qcMhIjJaTAKJKMNZsWIFSpYsiV69euHFixdSh0NEZJSYBBJRhiOXy7Fw4UK8evUK06dPlzocIkpEIWQG30gdk0AiypCKFy+Ofv36YdGiRXj48KHU4RARGR0mgUSUYY0YMQJxcXHYt2+f1KEQ0TcUBh4UomC6oxGfChFlWM+fP0dcXBy8vLykDoWIyOgwCSSiDOvBgwcAgAsXLqBmzZro1KkTB4oQGQGFsDD4Rur4VIgow6pRowZy586NKVOmIDQ0FPv370fBggWxe/duqUMjIpIck0AiyrAsLS2xZMkSdO/eHYcPH8bNmzdRqVIlNG/eHMePH5c6PCIiSRluzRYiIglUrVoVVatWVb7+448/UL9+fQQHB+PChQsoXLiwhNERmad4yBAPw03bYsh7mRJWAonIrERGRqJLly6wt7fH8uXLpQ6HiEgyTAKJyKzs2rULbdu2xbt37zB79mwcPnxY6pCIzA4HhhgHPhUiMivVq1dXeV2zZk3MmDFDomiIiKTDJJCIzIqPjw/Onz+vsm/IkCHYtWuXRBEREUmDSSARmZ1SpUqhX79+Kvvatm3L5eWIDCQe/x8cYpiNNGESSERmqW3btrC3t0euXLkAAB8/fkSzZs3w5csXiSMjIjIMJoFEZJZKly6NZs2awc3NDXPmzAEAXLlyBV27doUQwqCx/PLLLyhatCiWLVuGmJgYnV5bCIH3799DoVDo7HoLFizAH3/8oZPrkXniwBDjwKdCRGbr6dOncHBwQN++fdG6dWsAwLp16zB27Fi93/vjx4+4d+8epk+fjuHDh0MIgR9++AH+/v6YNWsWPn78qPW1hRBYuHAhSpYsCUdHR7i4uCBz5sz4888/0x33tm3b0Lt3b4wfPz7d1yIiaTEJJCKzdOPGDRw7dgydO3eGTCbD4sWLUbBgQQDA+PHjsXLlSp3fc8mSJahXrx5atGiBnDlzIm/evPj555/RtWtXXLp0CTdv3kTNmjUxbNgw5MyZE2PGjMHbt2/TfJ9Tp06hZ8+eyJo1K8aPH4+NGzeiUqVK6NixI+Li4rSO/8KFC2jevDkAoHbt2sr9QgjEx8cbvIJKROnDJJCIzNK8efPg6empTGqcnZ1x8uRJlClTBgDQuXNnnU4dI4RA9+7dsXfvXpw9exatWrXCrl278OjRIyxatAhyuRwFChTAihUr8PDhQ3To0AEzZsxAiRIl8PLlyzTdZ+nSpZDL5VixYgUGDRqEkJAQnD59Gl++fMH79++1in/dunUoXbo0AMDGxgbe3t4YPnw4pk6dCgsLC1haWsLCwgIlSpTA33//rdU9yHzECwuDb6ROJlLxq1tkZCQyZcqEiIgIODs7GyIuIiK9ef/+PbJnz44RI0Zg1KhRKseioqIwdOhQzJs3DwDw+PFjeHt76+S+Hz9+RJYsWTB37lz07NkzxfMfPXqEsmXLIkeOHDh27BgcHBySPT82NhY//vgjli9fjt9++w09evSAEAJVqlTByZMn0bRpUwwaNAgPHz6EQqGATCZD4cKFUaxYMY3XE0LgzJkzmDx5Mvbu3QsAyJo1K6pXr55sn0BXV1c8f/4clpZcmVQKxvydnRDbiLN1YOtoZbD7Rn2MxZSy+43ymUiJ/0KJyOwsW7YM8fHxaNeuHXr27In9+/dj8+bNKFGiBGxtbfHrr78iW7ZsGDNmDPbu3Yvu3bvr5L62trZwdnbG8+fPU3W+j48Pdu/ejUqVKsHf3x+WlpYoWLAgSpYsCW9vb2TJkgVNmzaFjY0NPnz4gJYtW+Lw4cNYvXo1vvvuOwCATCbD4cOHMXPmTEydOhXbtm1TuUeuXLlw/fp1TJ06Fb///jsUCgUCAgJQtmxZbNy4EXfv3lWeW7t2baxYsQJ+fn4AgGrVqsHW1hb58+dH2bJlcfr0acyZMwevX79Gw4YN0alTJ7Ro0QIyGddtJVUCMigMuJ6v4NrBGrESSERmJS4uDrlz50blypVRuHBhDB06FACwaNEitWRv165dKFu2LLJly6aTe2/ZsgUtWrTA5cuXUbRo0VS/7/Tp06hQoYLGY3ny5MHWrVsxfPhw/PXXX1iyZAlevXqFixcv4t69e3j//j3Cw8MRGxuLnDlzQiaToU2bNli9ejWuXbsGALCzs0N0dDQ6d+4MLy8vXLx4ESdPnlQOTpk4cSKaNWsGPz8/LF68WDnH4s2bN5E9e3YULlwYT5480Rhf5syZ0atXL7Rp0waFChVKw9MibRnzd3ZCbMPPBsPGgJXA6I+xmFp2n1E+EykxCSQis7Jy5Up07twZly5dwvbt2zFhwgQAwIABA9CyZUsEBQXppXIlhEBQUBDs7e1x/PjxVL8vOjoaBQsWRFhYGAYNGoQCBQrg1q1bWL9+PR48eKB2vo2NDQCgaNGiyJ8/P7JmzYrMmTMD+Jq0Xb16FXfu3EF8vOr0ucHBwRg8eDDKly+vvEbx4sXx6dMnjBkzBq9fv0b//v2V5xcrVgwXL17Exo0b0bZtW/Tu3RuZM2fGxIkTsXPnTuzatQu///67yj1++eUXDB48ONWfnbRjzN/ZCbENOVPP4EngL+X2GOUzkRKTQCIyG9HR0cibNy/y5MkDJycn7NixA8DXJlM3Nze8fPkSBQoUQKdOndC+fXt4eXnp7N7Xr19HQEAARowYgYkTJ8LCQr2j+rt37xAeHg5/f3/ExcUhJCQES5cuxfTp03Hw4EHUrFlTeW58fDxatmyp0rzr6emJvn37omvXrsiaNWuyzyEkJATv3r3Du3fvcObMGSxbtgyvXr2Cvb098ubNCz8/Pzx58gT//POPxmtMmzYNQ4cORWxsLFq3bo1t27bB2toaOXLkwP379yGTyXDy5Ens2LEDs2fPVnsf6Y8xf2czCTQuTAKJyCzEx8ejUaNG2LNnD8qXL4/Tp09j0aJFaNOmDZydnREfH4+jR49ixYoV2L59O2JiYtCkSRNMmDABBQoUSPf9Q0NDUbFiRTx9+hTu7u748ccfMXz4cNja2irPCQ4Oxv79+5E3b158/vwZT58+hbW1NUaMGIExY8aoVSjj4+Nx+vRp3LlzBwEBAShRogSsrLT7YlUoFLh69SqOHj2Ku3fvIiQkBA8fPsTHjx/h4eGBkJAQREREKM+vV68edu/eDeDrQJsBAwYga9asGDJkCDw8PFSu/fjxY/z8889Ys2YNAODIkSOoVq2aVnFSyoz5O5tJoHFhEkhEZmHv3r2oV6+eyj65XK5x3rzw8HCsX78eM2bMwIcPH3DgwAEUL1483THEx8fj7Nmz6NSpEx48eIC+ffti7ty5yuN+fn4IDQ1F586dYWVlhbp166JkyZLInj17uu+dXkII3Lx5E48ePUJMTAxq1qyZ4mjlxO+fO3cuBgwYgFWrVqFDhw56jNa8GfN3dkJsg07XN3gSOLP8bqN8JlJiEkhEZiE+Ph6nTp3Cly9f8PHjRxw7dgz16tVD3bp1k3zPu3fvUKNGDVy7dg1Hjx5FxYoV0xXDzZs30bVrV5w5cwYA0KRJEwwYMABWVlbo2bMnLl++jDJlyuD48ePKfnkZTVxcHORyOUcM65Exf2czCTQunCKGiMyCXC5H5cqVla8TJolOjouLC86dO4fKlSujT58++Oeff9I1993u3btx5swZzJs3D+3bt8eyZctQqVIlAICVlRV27tyJ4ODgDD2/Xkb+bJR68bBAvAHXqzDkvUwJnwoRUTKsra0xd+5cXL9+HZUrV8a6devURtamxufPn5VL0d24cQOZM2dGy5YtlceXL1+OBg0aMEkiIoNhEkhElILSpUvj2LFjiIuLQ/v27dGqVSsoFIo0XePly5e4desWAMDX1xcA4O3trVyZZOjQoXj8+LFO4yYiSg6TQCKiVKhYsSL+/vtvbNy4EVu3bsXkyZOxa9cudO7cGa1atcLvv/+O8PDwJN/v4+ODUaNGIXPmzBg+fDguX74MAOjduzeOHj2KFy9eIH/+/OjQoQMqVqyI+vXrq4zGJcpIFEJm8I3UMQkkIkqDli1bonHjxhg1ahQaNmyIU6dO4cmTJ/jxxx9RunRp3L9/X+P7LCws8OTJE2WiWLx4cXTt2hUKhQLlypXDwIEDERQUhPv378PX1xcnT57EoEGDDPjJiMjcMAkkIkoDmUyG7du34/Hjx5gzZw5u3LiBM2fO4O7du5DJZChatCjq16+vsuZuguvXr6u8Xrp0Ke7cuQMbGxvMnDkTx44dw5kzZ7BmzRp07doVy5Ytw9OnTw310YgMRgELg2+kjk+FiEgL3t7e6NevH6ytrQEAuXLlwtmzZzFixAjcvXsXZcqUwdChQ/Hlyxfle0qVKqVyjV9//RX58+fXeP0XL14AAIYNG6anT0BE5o5JIBGRjri4uOCnn37C6dOn0alTJ8yfPx+VKlVSJnTz589H6dKlIZPJcOrUKfTp0yfJ+fImTJiATJky4caNG4b8CEQGES9kBt9IHZNAIiIdc3V1xaxZs3Dq1Ck8f/4cXl5eqFWrFrp3746HDx9CCIHk5un/+PEjevTogYiICFy9elWlmkhEpCtMAomI9KR48eK4cuUKChcujJMnT+LAgQN48+YNAGD9+vVo0KABAgICUK5cOZw6dQrA1zV8ixQpgkOHDgEAVq1aBTs7O8k+AxFlXEwCiYj0yNXVFefOnUNoaChmzJiBvHnzAgCOHz8OIQQqV66M+Ph41KlTB3fu3IFCocDDhw8BAGvXrsV3330nZfhEesEpYowDk0AiIj1zcHBAjx490KpVK8TFxeHy5cu4efMmdu/ejfnz5+Po0aOIj4/HihUrYGlpiV9++QUA0L59e+TOnVurFUqIiFLC9YmIiAzg2bNnaNGiBTZt2qQ2GMTBwQGlSpXC0aNHAQDdunWDnZ0devfujQcPHiBbtmwICAhA+fLloVAo4OXlhX79+knxMYh0QggLKITh6lDCgPcyJXwqREQGkCVLFsTGxiY5Grhz5864cOECNm3aBGdnZ/Tq1QtCCPz999/o1KkT/vrrL0ydOhXTp09H//798fr1awN/AiLKaFgJJCIygEKFCuHPP/9M8ninTp1w+PBhtGnTBlmyZEGtWrUAfF232NvbG3PmzIGdnR06dOiA2NhY2NvbGyp0IsqgWAkkIjKAMmXK4OHDh3j8+LHasfDwcFSvXh3r16+HEALZsmVTOe7p6YkhQ4bgy5cviIiIgKurK7Zu3ZrsNDNExiweMoNvpI6VQCIiA6hduzYsLCxw4MABdO3aVeXY3bt3cezYMQDA1q1bUbx4cbX3T5s2DUWKFEHPnj0RGRkJALh//z7Gjx+v/+CJKENiEkhEZACZMmVC/vz5ceXKFbVjfn5+AL42CTdt2lTj+2UyGdq1a4fatWvj5MmTuHHjBkaPHo2iRYsm+R4iY6UQMOi0LQoWzTViEkhEZCBFihTBv//+q7Y/ofl3z549EEIkOXgk4dymTZuicePGuHHjBtq3b49r164hV65ceoubiDIm9gkkIjIQZ2dnREdHq+2XyWTo1asXXr9+jSdPnqTqWhYWFli2bBni4uKwf/9+XYdKpFeK/6aIMeRG6vhUiIgMJCoqCra2thqP3blzBwCUfQNTw8HBAcWKFcO5c+d0Eh8RmRcmgUREBnLv3j14enpqPNazZ08AX/sFHj9+PNXXLFOmDJNAItIKk0AiIj2LjY3FkCFDcObMGdSsWVPjOVWqVFH+ec+ePTh37hxevnyZ4rWLFCmCBw8e4PPnz7oKl0jvFJAZfCN1TAKJiPTs9u3bmDFjBnLmzIm2bdtqPCdLlizYvHkzXFxcMGPGDJQtWxZ58+bFb7/9hqNHjyIkJETjvIAFChSAEAK3b9/W98cgogyGSSARkZ65u7sDACZMmAAHB4ckz2vevDlev36NZ8+eYevWrShZsiT69OmD6tWrw9/fH61atVJ7T2BgIDw8PNCvXz/ExMTo7TMQ6VK8kBl8I3VMAomI9MzNzQ1eXl64efNmiudaWFjAy8sLTZs2xZEjR/DlyxfcvXsXY8eOxebNmzF+/HhcuHBBWRV0cHDAtm3bcP78efTp00ffH4WIMhAmgUREehYREYHnz5+jYMGCaX6vtbU18uTJg5EjR6J9+/aYOnUqSpcujSpVqigTwbJly2LevHlYsmSJxnkIiYg0YRJIRKRnMpkMNjY2CAsL0/oaVlZWWLNmDcLDw5E7d26cPHkSJ06cUB7v1KkTnJycsHjxYq4pTEaP8wQaBz4VIiI9c3Z2Rtu2bTFs2DDIZDJUq1YNBw8e1Opa1tbWGDFiBNzc3FC1alW4u7ujffv2WLBgAX7++WcsXLgQrq6u8PPzw4YNG3T8SYgoI2ESSERkAAsWLEC+fPng5OSEqKgoNGrUCLdu3dLqWl26dMHTp0+xZcsWdOnSBX///TeGDBmC58+fY+fOnRg4cCAKFSqETp064c2bNzr+JETpp4AMCmHATYspYk6ePIkGDRrAy8sLMpkMO3bsUDneqVMnyGQyla1OnTo6ekKGwSSQiMgA7OzscPXqVYSHh+Pw4cPw9PTE9OnTtb6elZUVmjVrhilTpuDevXuYMWMG5s6dCycnJ4wcORJ9+vRBTEwMevXqhS9fvujwkxCZh0+fPqFIkSJYsGBBkufUqVMHL168UG6mVn23lDoAIiJzYW1tDQCwt7dH2bJl8eDBA51du0+fPti5cyfq16+PFi1awMvLCwDwxx9/YMiQIShZsqTO7kWUXsLAEzgLLe4VHByM4ODgZM+xsbGBh4eHtmFJjpVAIiIJ+Pj44N69e1AoFDq5nlwux59//on+/fvj0qVLWLZsGfLly4eRI0eiRIkSOrkHkamLjIxU2aKjo9N1vePHj8PNzQ358uVDjx498PbtWx1FahhMAomIJFC/fn2EhYVh27ZtOrumk5MTJk6ciH///RdhYWG4ffs2Jk2aBJmME+USAYC3tzcyZcqk3KZMmaL1terUqYPVq1fjyJEjmDZtGk6cOIHg4GDEx8frMGL9YnMwEZEEypUrh5o1a2LMmDFo0qQJ5HK51CERGUzCgA1D3g8Anjx5AmdnZ+V+Gxsbra/ZunVr5Z8DAgIQGBiIXLly4fjx46hevbr2wRoQK4FERBKZNGkSbt68idWrV0sdCpFZcHZ2VtnSkwQm5u/vj2zZsuH+/fs6u6a+MQkkIpJIqVKl0KpVK4wcORJxcXFSh0NkMBlxsuinT5/i7du38PT01Pu9dIVJIBGRhAYMGICwsDCMGDFC6lCI6BsfP37ElStXcOXKFQBASEgIrly5gsePH+Pjx48YMmQIzp07h9DQUBw5cgSNGjVC7ty5Ubt2bWkDTwP2CSQiklBQUJBJTzFBlFH9888/qFq1qvL1wIEDAQAdO3bEwoULcfXqVaxatQrh4eHw8vJCrVq1MGHCBJ02Mesbk0AiIgkJIfD+/Xt4e3tLHQqRwUg1MCQtqlSpkuw63AcOHEhPSEaBzcFERBJ6+/YtoqOjkT17dqlDISIzw0ogEZGEnj17BgBMAsmsKAy8Yogh72VKWAkkIpIQk0AikgorgUREEtq3bx+yZMliUtNKEKWXKfQJNAesBBIRSejo0aNo0aIFLC35OzkRGRaTQCIiCeXKlQuHDh2CQqGQOhQiMjNMAomIJNSvXz+EhITgxo0bUodCZDAJzcGG3Egdk0AiIgkVK1YMALBnzx5ER0dLHA0RmRMmgUREEnJxcUHDhg0xYsQI5M6dGydOnJA6JCK9YyXQODAJJCKS2KZNm7B37174+vqiZcuWiImJkTokIjIDTAKJiCRma2uL4OBg/PLLL3j16hV69uyJqKgoqcMiogyOSSARkZEICgrC/PnzsXz5cixbtgwfP36UOiQivWBzsHFgEkhEZCRkMhl69eoFJycn9O7dG05OTmjUqBEiIiKkDo2IMiDOTkpEZGROnz6NXbt2wdHREaNHj0alSpVw+vRpODo6Sh0akU4IGHY9X2GwO5kWJoFEREamcOHCKFy4MACgatWqKFOmDHr06IE1a9ZIHBkRZSRsDiYiMmKFCxfGokWLsHbtWixdulTqcIh0gn0CjQOTQCIiI9e+fXv88MMP6Nq1K/r06YO4uDipQyKiDIDNwUREJmDJkiUoWrQoevfujdy5c6Nv376QyVjdICLtsRJIRGQCEkYON27cGP3790eDBg0QHh4udVhEWmFzsHFgEkhEZEK2bt2Kbdu24fTp0yhVqhSuXbsmdUhEZKKYBBIRmRALCws0adIE//zzD+zs7FC6dGmMHz8eL1++TPU1/v33X4wfPx579+7F58+f9RgtkWasBBoH9gkkIjJBuXLlwt9//42BAwdizJgxWLRoETp37oxu3bohZ86cyv6C165dw+LFi+Hs7IySJUsiNDQUgwcPhp2dHT5//gwnJycsWbIErVu3lvgTEZGhsRJIRGSi7OzssHDhQty6dQtVqlTBvHnz4OvriyxZsqBkyZKoXLkyAgMDsWDBAqxevRrNmjXDoEGD0L17d4SHh+PmzZuoX78+2rRpg19++UXqj0NEBsZKIBGRicufPz/Wr1+P9+/f46+//sKNGzfw8OFDhIeHY9SoUahevToqV66Mp0+f4tOnT8iXLx8AoECBAli3bh38/f0xdOhQyOVyDBw4UOJPQ+bA0E20bA7WjEkgEVEGkSVLFjRs2BANGzbUeDxHjhxq+2QyGSZMmIDo6GgMGTIEVapUQfHixfUdKhEZATYHExGZOZlMhsmTJ6NgwYLo0aMHFAqF1CFRBieEzOAbqWMSSEREsLKywsKFC3H+/HkuT0dkJpgEEhERAKBChQro1KkThg8fjtevX0sdDhHpGZNAIiJSmj59OgBg2LBhEkdCGZkCMoNvpI5JIBERKbm6umLKlClYsWIFzp49K3U4RKRHTAKJiEhF165dUbhwYYwbN07qUCiD4oohxoFJIBERqbCwsMDQoUNx4MAB3L9/X+pwiEhPOE8gERGpCQ8Ph5WVFVxdXaUOhTIgQ0/bwiliNGMlkIiI1Bw6dAiVKlVCpkyZpA6FiPSESSAREam5du0anJycpA6DiPSISSAREamIiopCaGgoduzYgRIlSmD9+vVSh0QZDAeGGAcmgUREpOLMmTPKP1+6dAndunWTMBoi0hcODCEiIhVXr16FnZ0drly5gl27diFLlixSh0QZDAeGGAcmgUREpCI0NBQ+Pj7ImzcvBg0aJHU4RKQnbA4mIiIlIQSOHTuGggULSh0KEekZK4FERKS0d+9eXL16Fb/++qvUoVAGJgw8WIPNwZqxEkhEZGaePHmCH3/8EatXr1bZHx8fj1GjRqFChQqoVKmSRNERkaEwCSQiMiNCCEyePBmLFy9Gx44d0aZNG7x69QoxMTHo0KEDrl69imnTpkEmY+WE9EcAEMKAm9Qf2EixOZiIyIyMHDkSixYtQs+ePeHn54dJkyahatWqcHBwwJUrV7BhwwaUK1dO6jCJyACYBBIRmYn79+9j6tSp8Pf3x/jx45E1a1aULVsWDRo0gLe3N06dOoXSpUtLHSaZAQVkkMFw1WaFAe9lSpgEEhGZiVq1agEAfv/9d+Xcf+XLl8fbt2/Z/EtkhtgnkIjITPTs2RMAUL16dcjlcly5cgUAmAASmSkmgUREZmLw4MH4559/0KJFCwDA3LlzJY6IzFXCiiGG3Egdk0AiIjPi6+sLPz8/AMDdu3cljoaIpMQ+gUREZmTv3r2YPn06ACA4OFjiaMhcKYQMMgNW5ww5MbUpYSWQiMiMtG7dGpkyZUJAQAB+/vlnqcMhIgkxCSQiMiNWVlaoVq0aYmNjpQ6FiCTGJJCIyMy0atUKt2/fxvbt26UOhcyUQVcL+W8jdUwCiYjMTIsWLVCgQAGsX79e6lCISEJMAomIzIyFhQV69OiBrVu34uLFi1KHQ2aIU8QYByaBRERmqGfPnhBC4MiRI1KHQkQSYRJIRGSG5HI5cuXKhcOHD0sdCpkhVgKNA5NAIiIzNWTIEBw6dAhPnz6VOhQikgCTQCIiM+Xj4wMAiIqKkjgSIuNz8uRJNGjQAF5eXpDJZNixY4fKcSEERo8eDU9PT9jZ2aFGjRq4d++eNMFqiUkgEZGZKlGiBGQyGU6cOCF1KGRmFEJm8C2tPn36hCJFimDBggUaj0+fPh2//vorFi1ahL///hsODg6oXbu2Sf1SxSSQiMhMubq6olSpUli0aJHUoRAZneDgYEycOBFNmjRROyaEwJw5c/Dzzz+jUaNGCAwMxOrVq/H8+XO1iqExYxJIRGTGMmfODEdHR6nDIDMj1WTRkZGRKlt0dLRW8YeEhCAsLAw1atRQ7suUKROCgoJw9uxZXTwig2ASSERkxp49e4bjx49j6dKlUodCpHfe3t7IlCmTcpsyZYpW1wkLCwMAuLu7q+x3d3dXHjMFllIHQERE0lm+fDlmzpyJbt264cSJE5g0aRJy5swpdVhEevHkyRM4OzsrX9vY2EgYjfRYCSQiMmOlS5fGhg0bMHfuXBw+fBiNGjWC4EKrpGdfm2gNOU/g1/s6OzurbNomgR4eHgCAly9fqux/+fKl8pgpYBJIRGTmLCws0KdPH6xevRpXrlzBvn37pA6JyKj5+fnBw8NDZcWdyMhI/P333yhbtqyEkaUNm4OJiAgAUKNGDVSrVg1NmzZFlSpVkD9/fgwYMEA5nyCRrhh6FQ9t7vXx40fcv39f+TokJARXrlyBi4sLcubMif79+2PixInIkycP/Pz8MGrUKHh5eaFx48Y6jFy/WAkkIiIAgEwmw+7du/HTTz8hJiYGa9asQd68eTFgwAC8efNG6vCIDOqff/5BsWLFUKxYMQDAwIEDUaxYMYwePRoAMHToUPTp0wfdunVDqVKl8PHjR+zfvx+2trZShp0mMpGKzh+RkZHIlCkTIiIiVDpUEhFRxvXp0yfMmTMH06ZNAwAMHz4cgwYNMvvO9MbOmL+zE2LLtWYE5PaGS5biP0fhwXdTjPKZSImVQCIi0sjBwQE//fQTHj58iC5dumDMmDEoWrQoLl26JHVoRKQDTAKJiChZ2bJlw5w5c3D58mXY29ujWrVqWL58OUcRE5k4JoFERJQqhQsXxrFjx1C/fn18//33GDJkCBNB0ophp4cx7CAUU8LRwURElGrOzs5Yu3YtgoKC0LdvX7i4uGDkyJFSh0VEWmASSEREadanTx+8fv0aP//8M7y8vNCpUyepQyJTIv7bDHk/UsMkkIiItDJ27Fg8f/4cnTt3RunSpVGwYEGpQyKiNGCfQCIi0oqFhQV+++03uLu7Y/78+VKHQ0RpxCSQiIi0Zm1tjQEDBmDRokWYM2cOB4pQ6hh6UAgHhmjE5mAiIkqXIUOG4NmzZxgwYACKFCmCqlWrSh0SEaUCK4FERJQuFhYWmD17Ntzd3TFz5kzEx8dLHRIZOSEMv5E6JoFERJRucrkcy5cvx759+9CmTRv8+eefePXqldRhEVEymAQSEZFO1K1bF2vWrMGJEyfQuHFjuLu7o2LFijh58qTUoZGR4WTRxoFJIBER6Uzbtm0RFhaGx48fY9WqVYiJiUHdunVx48YNqUMjokSYBBIRkU7JZDJ4e3ujQ4cOOHr0KHLmzImhQ4dKHRYRJcIkkIiI9MbBwQGtWrXCuXPnoFAopA6HjEXCtC2G3EgNk0AiItKrqlWr4t27d/j333+lDoWIvsEkkIiI9Kp06dKwtrbG8ePHpQ6FjASniDEOTAKJiEivbG1tUbNmTSxZsgSRkZFSh0NE/2ESSEREejd58mTcvn0bf/75p9ShENF/mAQSEZHeFSpUCFmzZsWcOXPw5MkTqcMhqQkJNlLDJJCIiPROLpfj8OHDeP36NQIDAzFt2jR8/vxZ6rCIzBqTQCIiI1Twp9ko+NNsqcPQqaJFi+Ly5cto0qQJhg8fjkGDBkkdEkmEK4YYB0upAyAioqQllwjenDTAgJHoRtasWbF8+XIEBgZiwIAB8PPzw5AhQyCT8UuayNCYBBIRmShNCaKpJIb9+/fHmzdvMGzYMBw4cADLli2Dr6+v1GGRIbGfnuSYBBIRZSCmVDmcOHEiypUrh549e6JEiRJYt24d6tSpI3VYREYtOjoaNjY2OrkWk0AiIiOjr76Axlg5rFu3Li5duoTvvvsOdevWxV9//YXy5ctLGhORMdm3bx82btyIv/76C0+ePIFCoYCDgwOKFSuGWrVqoXPnzvDy8tLq2kwCiYjMmDEkhi4uLti5cyfKly+Pbt264fr16+wjmMEZerCGKQ4M2b59O4YNG4YPHz6gbt26GDZsGLy8vGBnZ4d3797h+vXrOHz4MCZMmIBOnTphwoQJcHV1TdM9mAQSEZEKjZXI//pv3ZysnwRRLpdj2LBhaNq0KV68eKF1ZYMoo5g+fTpmz56N4OBgWFioT+bSsmVLAMCzZ88wb948rF27FgMGpO3fJ5NAIiJKtYIjVRNEXSaFhQsXBgDcuHGDSWBGZ+gJnE1wEMrZs2dTdV727NkxdepUre7BJJCIyIgY7dyA37amJfOFWvCn2VpXDf39/WFra4vz58+jZs2aaY+RiNKESSAREaVeSgngt69Hak5ok0oO5XI5mjdvjgkTJqBMmTKoXr261mESZSRCCGzZsgXHjh3Dq1evoFAoVI5v27ZNq+syCSQiIq1o2xScXHK4bNkyvHjxAl26dMHdu3d1NhUGGRsZVMvLhrif6erfvz8WL16MqlWrwt3dXWcDp5gEEhFR6smQcv+q1JyjQcGRsyETwMesufD4yBG4FSuLlZNGoW7dukwGyaytWbMG27ZtQ926dXV6XSaBRERGwmj7A6ZVOjrhCxlg45EdDv75Ef3mBZo2bQqZlTUccuRC1qLlYZU5Ky7N/QlOTk66i5cMjwND0iRTpkzw9/fX+XWZBBIRUbrpMoG1dHBCzlbdAADRr8Pw8d51fLh/E4+2LwUAOK+YBveywXALqgmbCIFYexnk0V/fe/F341oVhUgXxo4di3HjxmH58uWws7PT2XWZBBIRUZrpa77AxGxcPWDj6gGXstURfvksPobchk3mbHh5dh8ss7kgU6ESsPrw//ML/jQbdq+Az55fX8dbA3d/ZmJIpq1ly5bYsGED3Nzc4OvrCysrK5Xjly5d0uq6TAKJiChtJOhjL5PJkKV4OWQpXg4AEPspEs/3/YEvn97Aq0htOL6IR4yTBRyfAbH2qgHmHzsb9i++/tkyWuD8yoGGDp8SY3NwmnTs2BEXL15E+/btOTCEiCijMZn+gMl9mRrwi9azTgvIbezw7ugB2OfOC/j5AQKIc/h63CIasIgHLD//F9d/35lxtqY9SpTM0549e3DgwAFUqFBBp9dVX4eEiIgoGYmbgpUJrAHzK7mVDTxqNoGtew682bUD8ZYKOL5QwDlUwOoDEJ0VsIgD5NGAPAaIdTRcbJQKQmb4zYR5e3vD2dlZ59dlEkhERKljZE1qMpkF3Gs2QtSLJwi/dh4Rfv//SrN/AcjiAYtYIP6/2WU+e/6/ryCRKZk5cyaGDh2K0NBQnV6XzcFERGRSZOJrYUcmAIccuZCpcCm82L8FTm+sYJclAJ/crRH7X9FEFgdkfiAQbw0ImQzXf+EgEWMgxNfNkPczZe3bt8fnz5+RK1cu2Nvbqw0MeffunVbXZRJIRCQxk+kPmBpaThSd6suL//9/QiLoVbclAIG759dDUbw5srwqg4826s1/dm9NPBMgszVnzhy9XJdJIBGRoWzeDIweDXz4oLL7aORHiQJKOw9nR2D1TOXrsMiPOGrA+3+ytsH8isE4mL+IMhGEXA7P+q1hYWmN+5c2w9PmC+wKVoXzIxkyhcTiRTkr2L4BIvMo4Dd/JkJ6DzJgxETp17FjR71cl0kgEZGhjB4N3L6ttttDglC09iFC5aUUsff+ax8O5i8C4P8VQQtYwKN2M8gdHPHi9G5kjf2AzIH1AQCeZ2LxOtAKMpdoCaIljThFTIo+ffoEBwcHvZ0PMAkkIjKchAqghQXg+f8RCmGmVgn8hiFjd/0YCbkQcIhRT+aEDIBMBtdKdWBp74iwQ9sh3n+Ae+1m+BykgEwej2xZPuJC8GSDxUuUHrlz50a/fv3QsWNHeHpqHtEkhMDhw4cxa9YsVKpUCSNGjEjTPZgEEhEZmqcn8PQpABPoD5iogvLt9DDJxq5F5UWWwnuOLBgHj0SVSE3vy1KyAuT2jni+ex3e/XYJWGQBG3dPTJk1AydPnsSnT59QqlQpZMuWLe1Bkm4YetoWE5wi5vjx4xg5ciTGjh2LIkWKoGTJkvDy8oKtrS3ev3+Pmzdv4uzZs7C0tMSIESPQvXv3NN+DSSAREaWKoZaK04VMBYrC1tUDUa/DEP/lEz7cu442bdooj7u5uWH9+vWoXr26hFESJS1fvnzYunUrHj9+jM2bN+Ovv/7CmTNn8OXLF2TLlg3FihXD77//juDgYMjlcq3uwSSQiIjS75tVObS+hCzlamBarmWTzQM22b72Wny+fzPu3LmjXG6rd+/eaNSoEW7cuAEfHx/d3JRID3LmzIlBgwZh0CDdD2jiZNFERJQ02TdbUkSi/094nxZ0sciDTKgnkzKZDPnz50e+fPmUFRZnZ2eMGjVKu5tQuiT8jAy5kTomgUREEjH6/oCpkfjLVcDwIz+14OzsjC5duuDw4cNSh0IkGSaBRESUopuTDL9esK6qNzemaO7LmDt3brx48QJr1qzRzY0o9YQEG6lhEkhEREnLwF+g5cuXBwB06NABd+7ckTgaIsNjEkhERNoz4QQxLi5O+ecaNWrg8+fPEkZjZhJ3/jTERmo4OpiISAKm1B8w8dQwhoo94XtbX536z507p/zz06dP8ezZM+TJk0c/NyNKp/DwcJw/fx6vXr2CQqFQOdahQwetrskkkIiItCeDUVcDk+oPCACLFi0CABQvXhyjRo1iAkhGa9euXWjXrh0+fvwIZ2dn5VRHwNeR70wCiYhIt4wgudNnFfD8+fPYtWsX6tevr5+bUNK4dnCaDBo0CF26dMHkyZNhb2+vs+uyTyARkVRSmn+P9EIIgWHDhiFv3ryoW7eu1OEQpejZs2fo27evThNAgJVAIiKDC4v8+PUPJlid0Ngf0MibhBMLCwvDyZMnsX79elhYsBYiCVYC06R27dr4559/4O/vr9PrMgkkIqIkJbtesAG+WNOzlFxS/QE/fPjw9drCxDMD0puxY8di3LhxKvvy5cuH27dvSxJPvXr1MGTIENy8eRMBAQGwsrJSOd6wYUOtrsskkIiI1GXg/ChPnjwIDg5G3759ERAQgICAAKlDIiNUqFAhlRVlLC2lS5m6du0KABg/frzaMZlMhvj4eK2uyzo4ERFpx0T7NMpkMqxduxbe3t4oW7Ys1q9fz6qgoZnAiiGWlpbw8PBQbtmyZdPus+qAQqFIctM2AQSYBBIRURKSnR/w2y9XGfSaEGozz29yU8MAgIuLC06dOoXGjRujXbt2CAwMxPz58xEREaFllGQKIiMjVbbo6Ogkz7137x68vLzg7++Pdu3a4fHjxwaM1DDYHExERGmnaTCInopp+pomxsHBAWvWrEGnTp2waNEi9O/fH8OGDUP37t0xcuRIzJgxAzExMciWLRv8/f3RokULyOVy/QRjbgy9isd/9/L29lbZPWbMGIwdO1bt9KCgIKxcuRL58uXDixcvMG7cOFSsWBHXr1+Hk5OTISLGr7/+im7dusHW1ha//vprsuf27dtXq3swCSQiIlWpTbpMsCk4MZlMhho1aqBGjRp4/vw5fv/9d0yZMgWzZ3+teubNmxfv3r3DmzdvsGLFCmzatAmZM2eWNmjS2pMnT+Ds7Kx8bWNjo/G84OBg5Z8DAwMRFBQEHx8f/PHHH/j+++/1HicAzJ49G+3atYOtra3y76MmMpmMSSAREUkoA3Sp8/LywpgxY9CkSRP07NkTxYoVw7x58wAAR44cQfPmzZEtWzYULlwYmzZtQr58+SSO2HTJhP4qvEndDwCcnZ1VksDUypw5M/LmzYv79+/rOLKkhYSEaPyzLrFPIBGRgSjnBzQBaV4vWI9VQUO2GgJfKz+nTp1SJoAAUL16dVy9ehXTp0/Hq1ev0LJlS8MGRZL6+PEjHjx4AE9PT4PfOzY2Frly5cKtW7d0fm0mgUREpEqbpEvPVZ20JIIpDQrRlre3NwYOHIi5c+fi6tWrCA0N1ct9SHqDBw/GiRMnEBoaijNnzqBJkyaQy+Vo06aNwWOxsrJCVFSUXq7NJJCIiP7P0Cs5mKBatWoBAE6ePClxJCbMyKeIefr0Kdq0aYN8+fKhZcuWyJo1K86dOwdXV1ftP3M69OrVC9OmTUNcXJxOr8s+gURElH4mtnRcemTKlAleXl64d++e1KGQnmzcuFHqEFRcuHABR44cwcGDBxEQEAAHBweV49u2bdPqukwCiYgMoOBPs3FU6iC0lGR/wIQ5Ao2IvpqCE/P29sbTp08Nci+izJkzo1mzZjq/LpNAIiJSkex6wZqYSQXwWx8+fECmTJmkDoPMxIoVK/RyXSaBRET0VWqSOQNNEG3sXr9+jaxZs0odBlG6MAkkIqLUS2j+NdPkDwBCQ0Px+vVrBAQESB2KyZLBwPMEGu5WerNlyxb88ccfePz4MWJiYlSOXbp0SatrcnQwEREppTg/oBGPHjZUf8CjR49CJpOhcuXKBrkf0a+//orOnTvD3d0dly9fRunSpZE1a1Y8fPhQZXWTtGISSESkZylOtGyKZMgY5RUtbN++HWXKlEGWLFmkDsV0JawdbMjNhP32229YsmQJ5s2bB2trawwdOhSHDh1C3759ERERofV1mQQSEVHa1gs28PepoZcYS867d+9w4MABSSYNJvP1+PFjlCtXDgBgZ2eHDx8+AAC+++47bNiwQevrMgkkIiKjlJbkz1BNwdu2bUN8fDxatGhhkPtlWEY+WbSx8fDwwLt37wAAOXPmxLlz5wB8XVNYCO0/HJNAIiI9MqWm4DSvF2xES8UZysaNG1GlShV4eHhIHQqZkWrVqmHnzp0AgM6dO2PAgAGoWbMmWrVqhSZNmmh9XY4OJiKSyrdJlJQJj4lXSQwlPDwcx48fx/z586UOhczMkiVLoFAoAHxdQi5r1qw4c+YMGjZsiO7du2t9XVYCiYikIvtmy2DNVxnRP//8g/j4eOzcuRMhISFSh2Pa2BycJs+fP4el5f/rdq1bt8avv/6KPn36aD09DMAkkIjIOMg0bBIyhmZsYxkMkqBkyZIoUqQIDh8+rJclvIiSUqtWLWWfwG+dPn0aderU0fq6TAKJiPTEGBKp1ErzUnGA5IlqAkMNCsmcOTOuXLmCDRs24PLly+jbty+ioqIMcu+MJmHQjyE3U1amTBnUqlVLOSoYAE6ePIng4GCMGTNG6+syCSQiMldG3kxmrNO7NW3aFJMmTcK8efPYP5AMYunSpciZMycaNGiA6OhoHDt2DPXq1cOECRMwYID2vwQxCSQiIu3pMUkz1gqOTCbDyJEjkS1bNnz58kXqcMgMWFhYYOPGjbCyskK1atXQsGFDTJkyBf369UvXdTk6mIjIXCUMSEkkTc3YOk7SZCJt1T9DNQUnplAo8O7dO7i7u0tyf5Nn6Cq0Ef4ykZKrV6+q7Rs7dizatGmD9u3bo1KlSspzAgMDtboHk0AiIjOnVX9APUio+hlj9S+xmzdvQqFQwM/PT+pQKIMqWrQoZDKZymTQCa8XL16MJUuWQAgBmUyG+Ph4re7BJJCISA9MaVAIpd3evXthb2+PihUrSh2KaWIlMEWGmIaISSARkTnT1PSaRDMxfSWEwB9//IEaNWrA1tZW6nAog/Lx8Unze+rVq4elS5fC09MzVedzYAgREWlHx4liWkcCS9Uf8N9//8XFixfRoUMHSe6fEXCKGP04efJkmgYrMQkkIjJjNydpWC/YTL4wtZU9e3a4u7tj/vz5Kv21iEwNk0AiIh1jf8CMzdXVFWvXrsXx48exevVqqcMh0hqTQCIiMhrGODm0JjVq1EDbtm0xYMAAhIWFSR2O6UmYCdyQG6lhEkhEZKY0NgWnhR6+V1Pbd0uq/oDfGj9+PN6/f48LFy5IHQqRVjg6mIhIhwr+PNu8Rtea02dNJKECmCNHDokjMUGcIsYosBJIRESkhTVr1sDLywuFCxeWOhQiAMDIkSPh4uKS6vNZCSQi0iVzrDjooBpoalN4PHr0CCtWrMCYMWNgZWUldThkJm7evInHjx8jJiZGZX/Dhg0BACNGjEjT9ZgEEhHpkqZ+ciaQ4JjSiGYPZ0epQ8CECROQOXNm9O3bV+pQTJKh5+4ztV8yEnv48CGaNGmCa9euqSwlJ5N9/Q+OtsvGsTmYiEjXTOALJ/GgkHQxgc+rS69evcKaNWswcOBAODpKn5BSxtevXz/4+fnh1atXsLe3x40bN3Dy5EmULFkSx48f1/q6rAQSEelIwZ//q6aZ02wUOkgATa1Ks2LFClhYWOCHH36QOhTTxYEhaXL27FkcPXoU2bJlg4WFBSwsLFChQgVMmTIFffv2xeXLl7W6LiuBRET6JkPGTAxN/ItVWwcOHECVKlWQNWtWqUMhMxEfHw8nJycAQLZs2fD8+XMAX9cXvnPnjtbXZSWQiMjMad0fMJ0DQmTCNOfwrVSpEqZOnYotW7bA29sb0dHRyJ07N7y8vKQOzXQYej1fE/+FpXDhwvj333/h5+eHoKAgTJ8+HdbW1liyZAn8/f21vi6TQCIiXUv4wklIkows0dFZf0AzbAoGgGHDhuHChQto0aKFcp+VlRUGDRqE9u3bo2DBgsoO+0S68PPPP+PTp08Avk5SXr9+fVSsWBFZs2bFpk2btL4uk0AiIh1Q9gf8NqkRUN9HJs/Ozg67d+/GpUuXYGVlBWtra2zYsAG//PILpk6dinLlymHatGmoUKGC1KFSBlG7dm3ln3Pnzo3bt2/j3bt3yJIlS7p+4WCfQCIiXTGnZM+cPqsGMpkMJUqUQGBgIPLnz49x48bh7du32LFjB6Kjo1GpUiWcO3dO6jCNl5Bgy2BcXFzSXXFmJZCIyEA8PkQo///ovHHSxODsCKyaqXwdFvkRRyWJJO08Pn2QOoRk2dnZoVGjRqhfvz5Kly6NHj164MKFC7C05Fctpc+nT58wdepUHDlyBK9evYJCoVA5/vDhQ62uy7+ZRES68G0/QE37E0lICA0u0X09pIkiff4bJWms5HI5Fi5ciKCgIGzcuBHt27fX6jpCCMTHxyM+Ph5xcXGIiorC+/fv8fHjRxQqVMi0VyrhFDFp8sMPP+DEiRP47rvv4OnpqbM+p0wCiYjSSePo2hS+dMKcMuknmBQkXm0jLPKjJHFow8PZ8WsCOGGC1KGkqHTp0ggODsb06dPRrl075Zd2dHQ0QkNDERISgpCQEDx8+FD559DQUHz+/BlxcXGIj49XrgqhSZYsWdCoUSOUKVMG79+/x5s3b/Dp0ycUKVKEU9dkQPv27cOePXtQvnx5nV6XSSARka4l8d1dcOQsw8ahQeKRwdXSs1xcOqeHSYsbU3S4womBDB06FFWrVkXt2rXx8OFDfPjwAa9fv1Ymd5aWlsiZMyf8/f1RokQJNGvWDE5OTpDL5crN0tJS+WcbGxu4uLjAysoK+/fvx+bNm7Fy5UpkyZIFrq6usLCwwKJFi1CkSBGJPznpWpYsWeDi4qLz6zIJJCJKLxOdDcSU1gs2RZUrV8b48eOxePFiBAUFoWjRosiePTv8/Pzg7++P7Nmza91fsEKFCpg4cSLi4+Mhl8uV+z99+oS7d++iePHiuvoYesG1g9NmwoQJGD16NFatWgV7e3udXZdJIBGRLnw7H2A6J1HWF2NYL9jUv4zTQiaTYdSoURg1apTe7vFtAggADg4OyJUrl97uR4ZTrFgxlb5/9+/fh7u7O3x9fdX6g166dEmrezAJJCLShYT/VieeKDojyqifi8iING7cWO/3YBJIRJQOykmiE8uoiZIB+wEmMMX+gETpNWbMGL3fg5NFExGZoXStF6wlU1wnmMgYPHnyBE+fPlW+Pn/+PPr3748lS5ak67pMAomIdEn2zWZEjGm9YCKuGJI2bdu2xbFjxwAAYWFhqFGjBs6fP4+ffvoJ48eP1/q6TAKJiLSUbFOwiX/pGAs2BRMB169fR+nSpQEAf/zxBwICAnDmzBmsW7cOK1eu1Pq67BNIRKQPGXFgSEb7PCQZThGTNrGxsbCxsQEAHD58GA0bNgQA5M+fHy9evND6uqwEEhHpWkpNwQZuKk7cFCxFf0Ai0l6hQoWwaNEi/PXXXzh06BDq1KkDAHj+/Hm6VohhEkhEpC+yJDZN52Vwhq78kAlgf8BUmzZtGhYvXowqVaqgTZs2ylVhdu7cqWwm1gabg4mItJBkf8CUfPuFJEv0Z2P+sjLm2IgyuCpVquDNmzeIjIxElixZlPu7deuWrhVEWAkkIjKE5CoSGaRaoUl6KoAcFEL01ZcvXxAdHa1MAB89eoQ5c+bgzp07cHNz0/q6TAKJiPQhpeaoxFVAmYb9emCo9YK1bvrNQE14lAxOEZMmjRo1wurVqwEA4eHhCAoKwsyZM9G4cWMsXLhQ6+syCSQi0oekkrmEhC+5xFCHiWC65weUYIUQY5xnkUhKly5dQsWKFQEAW7Zsgbu7Ox49eoTVq1fj119/1fq67BNIRJQeCYlOcknft+clPl8gbf0Bpeg7qMX9hEzLJJDJn1ngFDFp8/nzZzg5OQEADh48iKZNm8LCwgJlypTBo0ePtL4uK4FERGmkMijk26rVt4net8mdgHpyI5L4c1IS38PIpfdLl/0Bif4vd+7c2LFjB548eYIDBw6gVq1aAIBXr17B2dlZ6+syCSQi0qXkBn+k9lw9VcOMvj8gEWk0evRoDB48GL6+vggKCkLZsmUBfK0KFitWTOvrsjmYiEgX0pLkpUbiZl8trqWz9YKJdM3QgzVM/BeT5s2bo0KFCnjx4oVyjkAAqF69Opo0aaL1dVkJJCJKL11/wWj6gjTQ6GG1OLR5WzpjZFMwGYsFCxbA19cXtra2CAoKwvnz5yWLxcPDA8WKFYOFxf9Tt9KlSyN//vxaX5NJIBFRGhT8abZhqxiJp48xgYoGm4MpJQkDQwy5pdWmTZswcOBAjBkzBpcuXUKRIkVQu3ZtvHr1SvcPRCJMAomItKXvZDC5wSQpvE9n6wVrIb2VQCJjMGvWLHTt2hWdO3dGwYIFsWjRItjb22P58uVSh6YzTAKJiIxVOvsEppuWyRwrgZQiI58sOiYmBhcvXkSNGjWU+ywsLFCjRg2cPXtWiw9snJgEEhEZC5mG7dtjhsZkTm/Wrl2LHj16IDo6WupQzEpkZKTKltTzf/PmDeLj4+Hu7q6y393dHWFhYYYI1SA4OpiIKJW0alLVth+fprkFU9s8rIvkTYoEUAA3pmbcQSH379/HqVOn8Pz5c/z0008AgOLFi+O7776Dra2txNGZB29vb5XXY8aMwdixY6UJxgiwEkhEpE9pWQkkre/9dsBIMpVCQ/YHBLTsE5iBq47h4eGYNm0aihQpgs6dO2PMmDH4/vvvAQDdunWDi4sLJk+eDIVCodX1nz17hsWLF+Pz58+6DFu/JGoOfvLkCSIiIpTbiBEjNIaXLVs2yOVyvHz5UmX/y5cv4eHhoYsnYBRYCSQiMpRvk6PUJnipuWaia0m5XrDWMvBgksWLF2P48OHK17lz54afnx82btyIQ4cO4cqVK/jpp5+QOXNm9OzZM8nrREVFYe7cuQgJCUG+fPlQqFAh3Lt3D5MnT8bz58+xc+dO7NmzxxAfyWQ5OzunaoUNa2trlChRAkeOHEHjxo0BAAqFAkeOHEHv3r31HKXhMAkkItI1TUu8pdS0m0GkZ1BIRp0fsGfPnpDL5Th//jwCAwNx5coVjBs3DrGxsSrnvXv3Tvnn3bt3Y/Xq1YiKikKJEiXw6NEj/P3337h79y4KFCiA1atX48uXL7C0tEStWrXw5s0b2NvbG/qjac0U1g4eOHAgOnbsiJIlS6J06dKYM2cOPn36hM6dO+s+QIkwCSQiSgW1JtWk1vLV1AdQUwVQF0lgRmpCzUifJREnJycMHjxYZd+jR49w4cIFFCpUCHK5HPHx8ciTJw+Ar+vBNmjQAADg7++PY8eOIV++fMiePTs2btyIgIAAxMfHIzQ0FNmyZUOmTJlQrVo1/PPPP7hy5Qr8/f0N/hkzolatWuH169cYPXo0wsLCULRoUezfv19tsIgpYxJIRJQaSSV9CceEhuMJ+zUN8khvMmikSZOQaVnhyaCV0aT4+PjAx8dH4zE3NzfMmjULI0eOhLW1NW7cuIGcOXOqnCOXy5ErVy7l65UrV6JatWooVqyYyrQmlD69e/fOUM2/iXFgCBFRaiSea+zb16kZpZvUXGVpSZg0zXmWaDoZKSeJ1pq+J902QQMGDMBff/2FN2/eoFWrVikOGsmZMydu3bqFrVu3onr16gaKMh2MfJ5Ac8EkkIhIKsmN6k2cZCaXaOrySy4d10lzP69v4s7IU8Noq2TJktiyZQvOnTuHAQNSfj5WVlaoUqUKcuTIYYDoKCNgEkhElAJJqmnJNT8b4r5a4HJxule5cmXMnTsXv/76K/bu3ZvkeXFxcZgxYwa8vb0xe7YJVX9ZCZQUk0AiogzK0Mkrl4vTjz59+qBq1aqoX78+mjZtinPnzkGhUGDPnj1YtmwZmjdvjrx582LYsGHo2rUrtm7dKnXIZCI4MISISErfDhpJZxKV7vkB00HrwSBMHFMkk8mwd+9erFmzBjNmzEDZsmVVjhcpUgTBwcHo3LkzSpYsicjISIkiTT1TmCLGHDAJJCKSmrF8QRkyjm/uxf6AKbO1tUXXrl3x/fffY9GiRVi8eDFq166NUaNGwdHRETIZ2+Ip7ZgEEhElQ69NqsaS/CUwZGWOOYtWLCws0LNnz2RXFiFKLSaBREQZkFbJq7ElpZRxGXqwBv9ua8SBIUREGYBO+gNyZDCRWWElkIiIJJNR1wum5HFgiHFgJZCIiL5K5xclq4FEpoWVQCKiZJjkMmwS0nrtYCIyOCaBRERpkFTfOymTQykTVSZ8pBUODDEKTAKJiHRAU3JoclVDLaaISU/lj/0BiaTFJJCISE+SG7FrcgkikS6xEmgUmAQSEUlAX83K6Xq/Fl+UbA4mMl1MAomIjEhak0Mp1wsGtG8OZlOweZPBsIvGcOC6ZkwCiYhMgF6TvXRU81gJJDJdnCeQiCgDMURl0NAT/RKRfrASSESUweh7QErCpNBMBElrHBhiFJgEEhGZEY1T2YzkSGUic8QkkIjIzN2crF1iyEEhpC2uHWwcmAQSEZEaTYlhgoQEkV+sRKaNSSAREaWJpgSx0Ag2KROZGiaBRESUbkk18TI5JI04MMQoMAkkIiK9Yf8/IuPFJJCIiIgMj9U5yXGyaCIiIiIzxEogERERGRSniDEOrAQSERERmSEmgURERERmiM3BREREZFicIsYosBJIREREZIZYCSQiIiKD4sAQ48BKIBEREZEZYhJIREREZIbYHExERESGxYEhRoGVQCIiIiIzxEogERERGRQHhhgHVgKJiIiIzBArgURERGRY7BNoFFgJJCIiIjJDTAKJiIiIzBCbg4mIiMiw2BxsFFgJJCIiIjJDrAQSERGRQXGKGOPASiARERGRGWISSERERGSG2BxMREREhsWBIUaBlUAiIiIiM8RKIBERERmUTAjIhOHKc4a8lylhJZCIiIjIDDEJJCIiIjJDbA4mIiIiw+LAEKPASiARERGRGWIlkIiIiAyKK4YYB1YCiYiIiMwQK4FERERkWOwTaBRYCSQiIiJKB19fX8hkMpVt6tSpUoeVIlYCiYiIiNJp/Pjx6Nq1q/K1k5OThNGkDpNAIiIiMqiMODDEyckJHh4e+r+RDjEJJCKzUvCn2Sqvb04aIFEkRJSRTJ06FRMmTEDOnDnRtm1bDBgwAJaWxp1mGXd0REQ6lDgBTGofwOSQSK8kGhgSGRmpstvGxgY2Njbpvnzfvn1RvHhxuLi44MyZMxgxYgRevHiBWbNmpfva+sQkkIhIg6SSQ4AJIpGp8vb2Vnk9ZswYjB07VuO5w4cPx7Rp05K93q1bt5A/f34MHDhQuS8wMBDW1tbo3r07pkyZopMkU1+YBBIRpZGmBJGJIZHxe/LkCZydnZWvk0vQBg0ahE6dOiV7PX9/f437g4KCEBcXh9DQUOTLl0+rWA2BSSARkQ6wWZko9aQaGOLs7KySBCbH1dUVrq6uWt3vypUrsLCwgJubm1bvNxQmgURkFpJr3pXqvkwQiUzf2bNn8ffff6Nq1apwcnLC2bNnMWDAALRv3x5ZsmSROrxkMQkkIpIIm5XJbGWgFUNsbGywceNGjB07FtHR0fDz88OAAQNU+gkaKyaBRERGrODIr4nizclMDomMUfHixXHu3Dmpw9AKk0AiIiP1baUwIRlMjMkhmSpD9gkkzZgEEhEZCY1NwTJ8bcpK+P9EmBwSkbaYBBJRhifVoJB0S5z0JZEIaqIpOWRiSETfYhJIRGTsZLq5TFJVQ4AJIhmYEF83Q96P1DAJJCIyVjpK/lKDlUMi88MkkIjICCTuD6iSlBkwGVTeUgCFRmiuHN6YwuSQ0keqyaJJFZNAIsrQTLY/YGIG/hIT/yWemr48v00OmRASmS4LqQMgIiINZJCkApiYSCYGJoBEpo2VQCIiI6PWP0+ipiw2oZHeZKAVQ0wZk0AiIompzQ+YhqlgdI2JH5H5YBJIRBmWyfYHlDAREzImgqR/MsXXzZD3I3XsE0hEJJXUJFsG7hfIBJDIfLASSEQkpURJl1T9AdOa/HFQCKUL+wQaBSaBRERSMYLRv0RkvtgcTERkSIkqEmqDQoiIDISVQCLKkEx2UIiBsQ8gSYErhhgHJoFEREkR0E2TbeIvIBP/QmJ/QKKMgUkgEVFyvk3YkkoIU0oWNc37p+F8tUEhBsApYUgSQnzdDHk/UsMkkIjoW8l9V2hK9kSi/0/quIZr3ZwsfUWNCSCR+eLAECLKcPTaHzClqS2+Pa6r5mQ9YPJHRKwEEhF9K7VLtqV0jpEmgN8mf9okguwPSLrAgSHGgZVAIiLg/xU8bb4skusrmMpk0FD9AYURJqZEJA1WAomIUuvbBEok8WdNWIUgUsUVQ4wCK4FEZB5S+hJITYVMh19cxjAohIjMGyuBRJShJDsoJLmm2bQkdyZcVUhP3yj2ByRdYZ9A48AkkIgytqSmbkkstQNC9ECK+QGJiNgcTEQZj6ZkLjUJngz/Txb1OIDC0E3Bhq66EJFpYCWQiDKm5BLB1CZ4CedlkASKiSAZDa4YYhRYCSSiDCPFSaITKn1JJYiJp3RJwxQvxkwX08KwPyBRxsNKIBFlLLqersXEE0AiY8SBIcaBlUAiMh+Jvwi+fZ14DkCh4c86kLg/IAeFEJFUmAQSUcaR3mleMmjVj1UQItKEzcFElCHorKIm4VQx+qCLBJD9AUnnuGKIUWAlkIjMl6bK37cjiDNoZZCICGAlkIjo/yOAk2oi1lMVQd/9AdkMTMaKA0OMAyuBRJRxpLVyl3gASFLn6AjXCyYiY8JKIBFlHKlN2FJT3dNl5YDNykSqFOLrZsj7kRomgURk8rRqVs1gA0C+pcumLw4KIcq4mAQSkfkxdPKn4X6cH5CIpMYkkIjIANgfkOgbnCLGKHBgCBFRYuzDR0RmgJVAIjJpemlWNeGqAfsDkimQwcBTxBjuViaFSSARUVISryesI/rsDyi+iZlzoxFRctgcTESUFAGd9F2Sqj+gYPmDiJLBSiAREalhUzDplRBfN0Pej9SwEkhEJovTrGj2bTMwq4FElBRWAomIDMgQiWtC4sc+gWSsuHawcWAlkIiIiMgMsRJIRKRHUgwKYdWDjB4nizYKrAQSEWUgukgAOSiEyDwwCSQik2SKg0IM2R+QiCglbA4mIsog2AxMpkImBGQGnLbFkPcyJawEEhHpiVSTRBMRpQYrgUREpMT+gGQQiv82Q96P1LASSEQmxxT7A+obm4KJKK2YBBIRGQATVyIyNmwOJiLSA0P3BxQyVgPJdHBgiHFgJZCIiACwPyCRuWESSEQmhc2qRBmAkGDTo0mTJqFcuXKwt7dH5syZNZ7z+PFj1KtXD/b29nBzc8OQIUMQFxen38BSwOZgIiI9Y+JKlLHFxMSgRYsWKFu2LJYtW6Z2PD4+HvXq1YOHhwfOnDmDFy9eoEOHDrCyssLkyZMliPgrVgKJiDIA9gckks64ceMwYMAABAQEaDx+8OBB3Lx5E2vXrkXRokURHByMCRMmYMGCBYiJiTFwtP/HJJCISMekmCSay8WRSRHC8BuAyMhIlS06OtogH/fs2bMICAiAu7u7cl/t2rURGRmJGzduGCQGTZgEEhERB4WQWfD29kamTJmU25QpUwxy37CwMJUEEIDydVhYmEFi0IR9AonIZJhi3zpTjJlI32TCsF0YEu715MkTODs7K/fb2Ngk+Z7hw4dj2rRpyV731q1byJ8/v05ilAKTQCKiDIJzBRIlz9nZWSUJTM6gQYPQqVOnZM/x9/dP1bU8PDxw/vx5lX0vX75UHpMKk0AiIh2Soj/gt7RJBNkUTAb3TT89g90vjVxdXeHq6qqT25ctWxaTJk3Cq1ev4ObmBgA4dOgQnJ2dUbBgQZ3cQxtMAomIiIjS4fHjx3j37h0eP36M+Ph4XLlyBQCQO3duODo6olatWihYsCC+++47TJ8+HWFhYfj555/Rq1evZJuk9Y1JIBEREVE6jB49GqtWrVK+LlasGADg2LFjqFKlCuRyOXbv3o0ePXqgbNmycHBwQMeOHTF+/HipQgbAJJCITETBn2YDMuh95n+taZiihYNCiDSTKb5uhryfPq1cuRIrV65M9hwfHx/s3btXv4GkEaeIISLSBQHcnGQcfevSMmcg+wMSmS9WAonINAh8rbZpSnCMtToooW8TQY4YJqNjAgNDzAErgURkGpKrbnG1DCKiNGMlkIgyhsSJoEjiWOL9qS0QJFxDJPE6EfYHJCJjxySQiIxewZ+0SKiSqg4m3p+QCKY2IUwh+TNGCU3DbBYmoyFg2H9D/LuvEZuDiYhkif4/8Z9T8X6Nk0Qn1YdRIokHjHBQCJF5YyWQiOhbmiqCmhK5b8/TVGUwwYohkaHIhIDMgIM1DHkvU8IkkIgoMU2VweTOS+kcI/n+YXMwEX2LSSARGTWt+gNKTC1mI0kEtVlXmEgvOEWMUWCfQCKidEp2kmgj++5J6BfI/oBExCSQiEifjKQK+K20rChCRBkXm4OJiIjIsAQAA64dbGy/iBkLVgKJyGhliP6AgFFNE0NElICVQCKidEi2P+C3jKRZWCbYH5CkxylijAMrgUREhsDvICIyMkwCiYjMBKeHIaJvsTmYiEhHTLEPI5EkBAw8T6DhbmVKmAQSkVFiQqV7nBqGiL7FJJCISEupHhQi8drCCc3AQgbcnMxBIWQEuGKIUWCfQCIiQ0ntmsRERAbASiARkb7JkvizgEGmjmEzMBkdBQz7y5AhJ6Y2IawEEpHRMcX+gFrFzOSMiCTEJJCISAup7g+YGjIYJCFkf0Ai+habg4mIiMiguGKIcWAlkIiIiMgMsRJIRJROOuvDqMdBImwKJqPCKWKMAiuBRGRUTHFQiE5xsAgRGQiTQCKiNNLpoBAiIomwOZiIyFiwxYrMBZuDjQIrgURE6aDT5ms2BRORAbESSERGw+z7A+oJB4WQ0WEl0CiwEkhElAZ67w/IaiARGQgrgURERGRY/2vv7l2r2Lo4AK8UahCJEQyksVBSSLo0flWW6cXexkZBEC2Eq4J6VUTQQizV2ImtZQr/gLdJdS2F2GhjERBM7vXMW2jiMZlz8nVmz545zwMHEx0zE5UzP9dea49nB2dBJRAgN6qBQAJCIMAONaGHUT8g0IvlYCALjQhUKfcHrPDpIVA3zw7Og0ogQK4sCwMVUgkEANKyRUwWVAIBdiDJ8vUu71v6AYF+hECAXFkOBipkORionaEQGDKdImIk4RJtx3JwGZVAAIAhpBIIsE1N6AeErBkMyYJKINBeI+s+HqIeO0MhwGZUAoFaJamqrYa/HRYD9APCoCWuBCqtl1IJBNpnfcWviObdA4aoagnUQwgE2qtpwQ8gIcvBANvQiO1s9AOSO4MhWVAJBGozsEC1fgCk6Pq5kdjZUMiv42vrB3TPAiqmEgg0S68wtxr+uo9Zf2z355uFLCEMqtNJ3Khrs+hSKoFAe2y12teE+4HBEKBiQiDQHFsJRr0CXnfhYYdLxPoBgTaxHAzkbzthrd9yMZCHovPzlfJ8bCAEArXIpqrWp0/QJtFAmwmBQD16ha+yAY861HnuJvQswm7YIiYLQiBQv35TvHXI4fzuWUDFhECAiE1D1/TNp9mHM0MhNIYtYrIgBAJ0+xX0SvsB3UeAFrFFDJDc9M1MhkK6dW8ZU7YcnDIACpvQKPfv348zZ87E/v37Y3x8vPSYkZGRDa83b96kvdB1VAIBVglfkEbLBkNWVlbi/Pnzcfr06Xjx4kXP4169ehWzs7Nrn/cKjKkIgQCregyEZLOdTR/6AaE+d+7ciYiIubm5vseNj4/H5ORkgivaGsvBAOv883dNgSpxrzzUpojf1cAkr5+nXVpa+uO1vLyc9Nu+fPlyHD58OE6cOBEvX76Mouata4RAAGAoHDlyJA4ePLj2evjwYbJz3717N96+fRvz8/Nx7ty5uHTpUjx79izZ+ctYDgaSynIoJAcqgFC5T58+xdjY2Nrn+/bt63nsjRs34tGjR32/3ocPH+L48eNbOvetW7fWPp6ZmYlv377F48eP48qVK1v6/VUQAgH6SNIPuMsAqB+QxqlpMGRsbOyPENjPtWvX4sKFC32POXbs2I4v6eTJk3Hv3r1YXl7uG0arJAQCAKwzMTERExMTlX39hYWFOHToUG0BMEIIBPit1ybRwGB1OhHRSXy+6iwuLsbXr19jcXExfvz4EQsLCxERMTU1FQcOHIh3797Fly9f4tSpUzE6Ohrz8/Px4MGDuH79eqXXtRkhEEim8n7AInb33N/UzwzWBwitcPv27Xj9+vXa5zMzMxER8f79+zh79mzs2bMnnj9/HlevXo2iKGJqaiqePHkSFy9erOuSI0IIBNpk/bN9U4e67RAAoTXm5ub67hE4Ozv7xybRuRACgXYaQACcvvl0Y7DMjKEQGqllTwxpKiEQaJedhr+yfsCq7hvuR0AGhEAgiez3BywLj5lXAaGxVAKz4IkhAL1Ucd9wLwIyoRII0EsVlcABfk39gDRWJ/GDsjv+91VGCAQoUcnytfsQkBHLwQAR8c/fJVU1oQ1oMZVAoHLZD4UASRVFJ4oi3RNDUp6rSVQCAVIZ4ObV+gGB3VIJBFhH5RIqVhRphzVsEVNKJRAgFfchICMqgcBwKeL3suyvULbhSSFdvwbQVkIgUKnal1Z7hTkhD+pTJN4n0HJwKcvBQHvtNABmfr8wFAIMgkogQJfpvyqsXHoWMfzU6USMJNy2xRYxpVQCgXbaYtja0A84wG1cNhAAgYyoBAJ0E9SgenoCsyAEApVJPhQyBO/z+gGBQbEcDLTHLpdyK+0HBMiMSiAAkFTR6USRcDDEs4PLCYFAO+xgKbh0k+gqDMEyNdA8QiBQiaT9gDmHrJyvDepiMCQLQiDQDKvv4SMlP5ejCq7NUAgwSAZDgGoMKgQlKhgMZCgkcXEDYDdUAoFqDGLT5bJANaCQVWk/oCAI/XWKiBHLwXUTAoGBm/7r6c5DoPdqgCSEQKAaZT18mx1f5SPbUqjw2cD6AWmVooiIlM8O9r/LMnoCgXzU9D490E2iR6L5YRYYCiqBwOD1C0HdFb+aQl/l+wMqOkBfRaeIImFPYKESWEolEEinWPdjG3R/T6aDgQYRAoHq9AtFbQpLFX8v+gGBKlgOBgaqtL8u48A30H5AYGuKTqQdDPHs4DIqgUC1DEkAZEklEKhGzcMfvVQ+FAJsymBIHoRAoFpllUDvxwC1sxwMDMz0zV08KaSJEoRZQyFAVVQCgbQyqgIaCoGaGAzJwrZC4NLSUlXXAbTAj+Xv5b+wukF0zQHwf7cv//E+1vN6tyLR9+J9l+1qwr+Z/+LfpO8H/8W/6U7WICPFFrolv3//HkePHo3Pnz+nuCYAYBcmJyfj48ePMTo6Wvel/KHOPJHrn0mdthQCI37+xa2srFR9PQDALu3duzfbsFNXnsj5z6QuWw6BAAC0h+lgAIAhJAQCAAwhIRAAYAgJgQAAQ0gIBAAYQkIgAMAQEgIBAIbQ/wEBkMEsvUq7QgAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Do the spatial plot\n", + "fig = plt.figure(figsize=(10, 8))\n", + "\n", + "ax = plt.axes(projection=ccrs.PlateCarree())\n", + "ax.set_extent([lon_min, lon_max, lat_min, lat_max])\n", + "ax.coastlines()\n", + "\n", + "\n", + "pcm = ax.pcolormesh(\n", + " lon,\n", + " lat,\n", + " ssh,\n", + " shading=\"auto\"\n", + ")\n", + "\n", + "plt.colorbar(pcm, ax=ax, label=\"ssha_karin (m)\")\n", + "plt.xlabel(\"Longitude\")\n", + "plt.ylabel(\"Latitude\")\n", + "plt.title(\"SWOT SSH Anomaly -- Cycle 29 and Pass 289 \\n Bbox from time series in red \")\n", + "plt.grid(alpha=0.3)\n", + "\n", + "# add the orginal bounding box (spatial average) outline\n", + "lon_min, lon_max = 237.5, 238.8\n", + "lat_min, lat_max = 34.5, 35.5\n", + "bbox_lon = [lon_min, lon_max, lon_max, lon_min, lon_min]\n", + "bbox_lat = [lat_min, lat_min, lat_max, lat_max, lat_min]\n", + "\n", + "ax.plot(\n", + " bbox_lon,\n", + " bbox_lat,\n", + " color=\"red\",\n", + " linewidth=2,\n", + " transform=ccrs.PlateCarree()\n", + ")\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c204a927-bb28-4e2b-b3e0-f327e7299829", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "806314fc-3818-446c-8f95-b5aced85b113", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.12.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}