{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CDS API plugin for EODAG\n",
    "\n",
    "In this tutorial we will show you how to use eodag to download data from providers using [CdsApi](https://eodag.readthedocs.io/en/latest/plugins_reference/generated/eodag.plugins.apis.cds.CdsApi.html) `eodag` plugin. You can currently find two providers that uses it, `cop_ads` and `cop_cds`. For this tutorial we will use `cop_ads`, but `cop_cds` is used the same way. The API plugin and this tutorial have been developed in the context of DOMINO-X."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from eodag import EODataAccessGateway, setup_logging\n",
    "\n",
    "setup_logging(0)  # 0: nothing, 1: only progress bars, 2: INFO, 3: DEBUG\n",
    "dag = EODataAccessGateway()\n",
    "dag.set_preferred_provider(\"cop_ads\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Search (build download request)\n",
    "\n",
    "There are two use case, a search for a product already configured in EODAG, or a search for a dataset not already configured, where you will have a little more to do.\n",
    "\n",
    "For performance purpose, we can add a `variable` (Temperature, `temperature`) and one `model_level` to the request because `CAMS_EAC4` is configured to request for some pre-configured values. Check the dataset available values to make your selection.\n",
    "\n",
    "> Note: specifying your own variables will completely overwrite default values configured for `CAMS_EAC4` product type.\n",
    "\n",
    "### Search from an existing product type:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 product built EOProduct(id=CAMS_EAC4_20210101_9fa1614f23014d2fb17c38927a5e87ecb3dcf6aa, provider=cop_ads),\n",
      " having variable=['dust_aerosol_0.03-0.55um_mixing_ratio', 'dust_aerosol_0.55-0.9um_mixing_ratio', 'dust_aerosol_0.9-20um_mixing_ratio', 'dust_aerosol_optical_depth_550nm', 'hydrophilic_black_carbon_aerosol_mixing_ratio', 'hydrophilic_organic_matter_aerosol_mixing_ratio', 'hydrophobic_black_carbon_aerosol_mixing_ratio', 'hydrophobic_organic_matter_aerosol_mixing_ratio', 'sea_salt_aerosol_0.03-0.5um_mixing_ratio', 'sea_salt_aerosol_0.5-5um_mixing_ratio', 'sea_salt_aerosol_5-20um_mixing_ratio', 'sea_salt_aerosol_optical_depth_550nm', 'sulphate_aerosol_optical_depth_550nm']\n",
      "and model_level=['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '20', '21', '22', '23', '24', '25', '26', '27', '28', '29', '30', '31', '32', '33', '34', '35', '36', '37', '38', '39', '40', '41', '42', '43', '44', '45', '46', '47', '48', '49', '50', '51', '52', '53', '54', '55', '56', '57', '58', '59', '60']\n",
      "\n",
      "1 product built EOProduct(id=CAMS_EAC4_20210101_63a610e702b9132d1fca308e390ebd89f336f812, provider=cop_ads),\n",
      " having variable=temperature\n",
      "and model_level=1\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Request for all parameters\n",
    "products_from_product_type, total_count = dag.search(\n",
    "    start=\"2021-01-01\",\n",
    "    end=\"2021-01-02\",\n",
    "    productType=\"CAMS_EAC4\",\n",
    ")\n",
    "print(\n",
    "    \"%s product built %s,\\n having variable=%s\\nand model_level=%s\\n\"\n",
    "    % (\n",
    "        total_count,\n",
    "        products_from_product_type[0],\n",
    "        products_from_product_type[0].properties[\"variable\"],\n",
    "        products_from_product_type[0].properties[\"model_level\"],\n",
    "    )\n",
    ")\n",
    "# Request for temperature on one model level\n",
    "products_from_product_type, total_count = dag.search(\n",
    "    start=\"2021-01-01\",\n",
    "    end=\"2021-01-02\",\n",
    "    productType=\"CAMS_EAC4\",\n",
    "    variable=\"temperature\",\n",
    "    model_level=\"1\",\n",
    ")\n",
    "print(\n",
    "    \"%s product built %s,\\n having variable=%s\\nand model_level=%s\\n\"\n",
    "    % (\n",
    "        total_count,\n",
    "        products_from_product_type[0],\n",
    "        products_from_product_type[0].properties[\"variable\"],\n",
    "        products_from_product_type[0].properties[\"model_level\"],\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Search using a custom request:\n",
    "\n",
    "Here we use a set of custom parameters corresponding to `CAMS_EAC4`, which should result to the same request sent to ads."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Request using productType or directly ADS parameters result to the\n",
      " same downloadLink https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-global-reanalysis-eac4?date=2021-01-01/2021-01-01&area=90.0/-180.0/-90.0/180.0&class=mc&dataset=cams-global-reanalysis-eac4&expver=0001&format=netcdf&model_level=1&step=0&stream=oper&time=00:00&variable=temperature\n"
     ]
    }
   ],
   "source": [
    "ads_req_params = {\n",
    "    \"dataset\": \"cams-global-reanalysis-eac4\",\n",
    "    \"stream\": \"oper\",\n",
    "    \"class\": \"mc\",\n",
    "    \"expver\": \"0001\",\n",
    "    \"step\": 0,\n",
    "    \"variable\": \"temperature\",\n",
    "    \"model_level\": \"1\",\n",
    "    \"time\": \"00:00\",\n",
    "    \"format\": \"netcdf\",\n",
    "}\n",
    "\n",
    "products_from_ads_req, total_count = dag.search(\n",
    "    start=\"2021-01-01\",\n",
    "    end=\"2021-01-02\",\n",
    "    **ads_req_params,\n",
    ")\n",
    "# downloadLink property must be the same with the two request methods,\n",
    "# as they are built from the same ADS request arguments\n",
    "if (\n",
    "    products_from_ads_req[0].properties[\"downloadLink\"]\n",
    "    == products_from_product_type[0].properties[\"downloadLink\"]\n",
    "):\n",
    "    print(\n",
    "        \"Request using productType or directly ADS parameters result to the\\n\",\n",
    "        \"same downloadLink %s\"\n",
    "        % (\n",
    "            products_from_ads_req[0].properties[\"downloadLink\"],\n",
    "        )\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Send product retrieval request and download when available\n",
    "\n",
    "- download performed using ADS credentials set in `~/.config/eodag/eodag.yml` as for other EO providers:\n",
    "```yaml\n",
    "    cop_ads:\n",
    "        priority:\n",
    "        api:\n",
    "            outputs_prefix: /data/eodag_data\n",
    "            credentials:\n",
    "                username: my-ads-uid\n",
    "                password: my-ads-api-key\n",
    "```\n",
    "- you can check your request status from https://ads.atmosphere.copernicus.eu/cdsapp#!/yourrequests\n",
    "- See [support](https://ads.atmosphere.copernicus.eu/cdsapp#!/usersupport) for any problem related to the provider"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/data/eodag_data/CAMS_EAC4_20210101_63a610e702b9132d1fca308e390ebd89f336f812.nc'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "product_path = dag.download(products_from_product_type[0])\n",
    "product_path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Open dataset with `xarray` and plot using `matplotlib`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (longitude: 480, latitude: 241, time: 1)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 -180.0 -179.2 -178.5 ... 177.8 178.5 179.2\n",
       "  * latitude   (latitude) float32 90.0 89.25 88.5 87.75 ... -88.5 -89.25 -90.0\n",
       "  * time       (time) datetime64[ns] 2021-01-01\n",
       "Data variables:\n",
       "    t          (time, latitude, longitude) float32 257.2 257.2 ... 243.7 243.7\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-09-13 14:38:48 GMT by grib_to_netcdf-2.25.1: /opt/ecmw...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d4a0f1c1-1851-4385-b146-adec8b7ce753' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d4a0f1c1-1851-4385-b146-adec8b7ce753' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>longitude</span>: 480</li><li><span class='xr-has-index'>latitude</span>: 241</li><li><span class='xr-has-index'>time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6be48b4c-19d0-4697-8e65-a8cbabfe8f28' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6be48b4c-19d0-4697-8e65-a8cbabfe8f28' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -179.2 ... 178.5 179.2</div><input id='attrs-b3a9371a-5ca4-461b-9f9a-ff04267e49c5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3a9371a-5ca4-461b-9f9a-ff04267e49c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8826721a-86c5-40af-a29e-4af35720f329' class='xr-var-data-in' type='checkbox'><label for='data-8826721a-86c5-40af-a29e-4af35720f329' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-180.  , -179.25, -178.5 , ...,  177.75,  178.5 ,  179.25],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>90.0 89.25 88.5 ... -89.25 -90.0</div><input id='attrs-8da81e51-3810-4fb8-bbbf-eaf7994327b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8da81e51-3810-4fb8-bbbf-eaf7994327b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03a8d6b9-250e-416b-a1ae-2728881c87a7' class='xr-var-data-in' type='checkbox'><label for='data-03a8d6b9-250e-416b-a1ae-2728881c87a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ 90.  ,  89.25,  88.5 , ..., -88.5 , -89.25, -90.  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01</div><input id='attrs-552a502b-e21a-4362-85d9-4f22c39ad502' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-552a502b-e21a-4362-85d9-4f22c39ad502' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a78cf07-1403-4006-9e64-f7d3b62c3c59' class='xr-var-data-in' type='checkbox'><label for='data-9a78cf07-1403-4006-9e64-f7d3b62c3c59' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-774adaed-aa79-4eb6-8e8b-fb3d138a059b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-774adaed-aa79-4eb6-8e8b-fb3d138a059b' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>t</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>257.2 257.2 257.2 ... 243.7 243.7</div><input id='attrs-cf9345af-5204-4460-850f-781e24bed215' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cf9345af-5204-4460-850f-781e24bed215' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f0e3964-ef46-45e8-9166-2c6163e36b6e' class='xr-var-data-in' type='checkbox'><label for='data-4f0e3964-ef46-45e8-9166-2c6163e36b6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd></dl></div><div class='xr-var-data'><pre>array([[[257.194  , 257.194  , 257.194  , ..., 257.194  , 257.194  ,\n",
       "         257.194  ],\n",
       "        [256.0762 , 256.07764, 256.07983, ..., 256.07187, 256.0733 ,\n",
       "         256.07477],\n",
       "        [254.94028, 254.94391, 254.94826, ..., 254.92941, 254.93231,\n",
       "         254.93593],\n",
       "        ...,\n",
       "        [243.86507, 243.8658 , 243.86725, ..., 243.86145, 243.8629 ,\n",
       "         243.86435],\n",
       "        [243.82957, 243.82957, 243.83102, ..., 243.82812, 243.82884,\n",
       "         243.82884],\n",
       "        [243.74844, 243.74844, 243.74844, ..., 243.74844, 243.74844,\n",
       "         243.74844]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-99136ed9-fd9f-4338-b92e-892a4e468c3c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-99136ed9-fd9f-4338-b92e-892a4e468c3c' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>2022-09-13 14:38:48 GMT by grib_to_netcdf-2.25.1: /opt/ecmwf/mars-client/bin/grib_to_netcdf.bin -S param -o /cache/data7/adaptor.mars.internal-1663079928.4767008-29180-3-8ff8d474-daf0-4a6b-a3ee-9f407b0a7f69.nc /cache/tmp/8ff8d474-daf0-4a6b-a3ee-9f407b0a7f69-adaptor.mars.internal-1663079927.965011-29180-5-tmp.grib</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (longitude: 480, latitude: 241, time: 1)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 -180.0 -179.2 -178.5 ... 177.8 178.5 179.2\n",
       "  * latitude   (latitude) float32 90.0 89.25 88.5 87.75 ... -88.5 -89.25 -90.0\n",
       "  * time       (time) datetime64[ns] 2021-01-01\n",
       "Data variables:\n",
       "    t          (time, latitude, longitude) float32 257.2 257.2 ... 243.7 243.7\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-09-13 14:38:48 GMT by grib_to_netcdf-2.25.1: /opt/ecmw..."
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = xr.load_dataset(product_path)\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fb9482979a0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEXCAYAAAC3c9OwAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAADViUlEQVR4nOz9ebh121UXCP/GXPu896aFQCCQENovAcEKAWlFURoVqoDgp1IgFaSRgIQPEEQlUIpAbEBBqSqgwhdprKCGByIRQ9FYgNJDAgSSgNKEJuQDA5iEe+/7nr3XHN8fc4wxxxhrrr33OWe/9773zRnPc87ee625ZrfmHL/RzTmJmXFN13RN13RN15SpPNQVuKZruqZruqY7k64B4pqu6Zqu6ZqGdA0Q13RN13RN1zSka4C4pmu6pmu6piFdA8Q1XdM1XdM1DekaIK7pmq7pmq5pSNcAcU2BiOjtieiPiGh6qOtyTdd0TQ8tXQPEmzgR0auJ6MP1NzP/JjM/mpnnh7Jea0RE9xDR84noN4jojUT0c0T0kSnNhxHRLxHR/UT0g0T0Du7ePyWi/yrP/hIRfVJ69nlE9MtEVInok4+oz9OJ6KVS1kuJ6Onu3odI+a8nolcfkRcR0T8hot+Xv39CRHTZul3TNV2VrgHimh5utAHwWwD+DIA3A/AlAF5IRO8IAET0eADfCeB/BfAWAH4GwL91z98H4KPl2b8G4F8Q0Z90938ewGcBeNmhihDRDQDfBeD/AvA4AN8C4Lvkupb1LwF84ZFtexaAjwXwngCeJvX8jMvU7Zqu6STEzNd/b6J/AP4VgArgAQB/BOBvA3hHAAxgI2l+CMBXAPgxSfPvAbwlgBcAeAOAnwbwji7PdwPw/QD+AMAvA/i4B6EdLwfwl+T7swD8mLv3KGnfu608+2IAXzC4/iMAPvlAuX8ewGsAkLv2mwA+IqX7cACvPqIdPwbgWe73pwH4icvU7frv+u8Uf9caxJswMfMz0RjaR3MzK33lStKPB/BMAE8C8C4AfhzAN6FJ6K8C8PcBgIgehQYO3wbgreW5ryOidx9lSkRfR0T/feXv5ce0gYieAOCpAF4hl94DTdLWNt4H4Fflen72EQDe1z17UXoPAC9nZr9fzctHZV0gv593v3/+Cnld0zVdma4B4pqOoW9i5l9l5tcD+B4Av8rMP8DMOwDfDuC9JN1HoUnK38TMO2b+WQDfAeCvjDJl5s9i5jdf+XvaoUoR0RmaJvMtzPxLcvnRAF6fkr4ewGMGWXwDGhP+3kNlrdBFyrpMfq8H8Gjvh7ima3ow6RogrukY+l33/YHB70fL93cA8P5eEwDwiQDe5tQVIqKCZiI7B/DZ7tYfAXhsSv5YAG9Mz38VgD+OZgI7asdKie7Sv7c/tqyVvJ7j8vqGlbo/FsAfHVu/a7qmU9M1QFzTKZnPbwH44aQJPJqZ/8YoMRF9Q2K6/m/V7CMS9fMBPAHN97B1t1+B5uTVtI9CM4u9wl37BwA+EsCfZ+Y3HNs4aYv+/abk+bQk4T8NR5ismPkfurw+c1R3+X5Z89c1XdOV6Rogrul3AbzzifL6bgBPJaJnEtGZ/L0vEf2xUWJm/szEdP3fPtv71wP4Y2i+kwfSvRcB+ONE9JeI6F4Afw/NT/BLAEBEXwTgrwL4cGb+/ZwxEd2Q5wjAGRHdK9rKiH4IwAzgcyT8VjWZ/0fyKpLXWftJ97oIpxF9K4DPJ6InEdETAXwBgG++ZN2u6ZquTg+1l/z676H9A/AMNEf1fwfwtzCOYvrrLv1XAPhm9/vDAfyK+/2uAP4DgP8G4PfRmOXTT1jfd5D63UQzyejfJ6Y6/RKa+euHEKOsGMCt9Oxz3P0fkjT+78/uqc97AXiplPUyAO/l7v3ZQV4/tCcvAvCVaBFgfyDf6bJ1u/67/rvqHzFfmzev6Zqu6ZquaUnX6uk1XdM1XdM1DekaIK7pmq7pmq5pSNcAcU3XdE3XdE1DugaIa7qma7qmaxrS5qGuwKnoUY+7wW/xpEc81NW4pmu6pocB/fYr3vA6Zn6rq+TxFz7kUfz7f3Dcpscvffmt72Xmj7hKeQ8F3TUA8WZPfBQ++V//2Qs9M1G9VFnlAmvLDpVRDtyfDpS17/mrPXu4bwod1w/H5DV87pLv53bRzBdTuOcjFfTK6ztp7Muj7qnPjHGel3nm4HNH9kvdk/9V874ofcXT/t1vXDWP1/3BjJ/83rc7Ku3Z2/7q469a3kNBdw1AzEx4w+7eg+mOYWrTnjRlhdmN8h0xxmE6xwgz+GyxZJSesc88LYBA7+uE9/czKOQ65vqN2jBi3CPQHKfbA0rHvJtLgs0p6BDDn1cYfR085xlfTVst+XtnmEO5AUzc1zUG7q97AMjpQ31cusygM5jlPhmB3aj9Le/DgLEPPB96Ysx8Zwkxp6a7CCDKAiCOYTj7tIGRhL1koGPmvJre/fbM0qeb0vUtT/KsXOcp1Lt6gKG6BA25P4GNMXQQKVbeWh3WACxe9+nH+fhyPY1BaPxe9gHMqF6noENS7BgAxozUGDNF5qrpKwrOaA5lav/MXDD557i/w0IVlYuBgJaz+C2fCgL2W8rv9ez1WdSRx0ATAWgAFIN+PFarOAZMHmxiAPWkO9XceXTXAEQF4f7dPeHaIfNNTLvGkDIA7AeEzNj0+UJrYDCW7jXNCFDs3oixU0UBR82Dp8ZAfFmgXrbOPe75eeDIpPmOQKHXyd0bpMuMPjP1BbCsTMR9YHDIxHY0DXjTyBwTgISSJI7MoPW3MGbqADIbSHQmPXMxoAcrKHBn5F4DEKDwoOABoTIFIGj5R+YfwSaWETWMMVhkgDgEBKfQFPaZwW4X1YdQo30w6K4BCGbCeW2S9kUH2yGz0+h+CYx9HTQW9wwwlsAQwSACSweFleuO8Y4ApDN1TV97ucwoVLFF0zyUeVdQAwt2YEEV4IKJKipKBIkEDhPqAhAmd2/Ul1MAllG/7weWfc9aHkf6To6hbPKZV8wzBgjkGDXINAkDDmrMuoGEMur2TgJQ8NK8o6Bgn1LGVubFjBIAobJPTwEA5gwKTIHJj4Bp2Ccnoov6Lx4M0xSDMd/lO1HcNQBRQTifp/B7keYKg+YQSIzSHfU9AcYIXHyaDCYeSDyIeABZAw8FjgwaATDku4JFY0wCHmCAxmafDA4eGDIgBC1qxbSl7fJ0rN9nCDQHQOKQ9mFAEPwAFO+Tfu9MVp+b29vADEJhxhnNjTGjoKBgAjcmTWi2DCqo3PqkchSElMlveVoAgweFbS0LQFAwqFwMBBYag2ky+01Ia3Ssdr43j5T2mPkdTWGnBwwGsL3WIB4+FAf3yF4aBwmfYNDQCDgWGsX4936gWPkEB6BYuz4RL8BDgcNrHQoaGTCUOZ/RjILGYMAtrzOahWk1ZnVGaOYpWpqlRuDgQWGpWaxrZprH8trhd5DTLMFmkcXe/IGBmYmAyst7M2obe6JhNO2gGmBksPCgAK7JD6C+hdLNVgIO27oRhl+w5Qk7njAzYVcnAwV/DQB2XAI4AMfNnd5vy/e1b1y370vTqE+baR8YeBDT/JQPeBPcoXZclq59EA8jqhwBojIZCOTBD3SAWBs0hwBkBA6e/ATIaUeTiAagsA4QMU3WMvSa/p7st9MsHGBMxCi8BItZzElnNEv5vT+9n8KDBHjsU/DgoMAxJQYS/BUHw3TX7+8DhAwGUYM5npZSLTDRMp+JGTM1MCjg9htkfaUmI6BgRuuDWcx3M8Q85LUTZehOc9jWDW7VTdMiRFvY8oRdnUxL2NVpAQg6T/zcaW2JnTRm9GksuvGWr7X0daj5HkvHmMC8ZpTbcGpwYODaxPRwIj/Q2Q2YubZBxHZP0ssAGgFFfu+n1jZ8ZKNOIEqTh6jd88BBDhDITVAPFGvXNmUegsamNOZ/RrOBxQYztjx104cARQeIgjPsjMmpuWlCXDg0UcUZZgODM9rhjGozQUldJrADiv3AECNlxtcz5fwqR5CYncP+sgaDXH6uW3b4hmdTxJFpFEzY8gbnPGHLG9zkM1S5dpM3uFXPMHPBLQcO53WDmQnndWOAsKtFtIeyAINcHy94bEr3W21KY/obFT6o2vczGT8bHT9Z8FjxiyllYSL4bgbRVWs+lJ2Y3rZ1cu2VNhNhV6PJ7BR0dxuY7iaAYCzAYZaJ4YHBg4IOFAUDDgCxzzR1tapmcJjRwaF/RuBogBBBAgCmUlfBYiMTbyNp6kwdJJhQZXLvqkY5FUB8B15Fn1x9s5MciFFNTfuIv0fgcCbX2nU2iXsiYFph9jMYZ2DMCvCkjtler2F00TDiKLbpkBN0DYBG1xe+CPteHMMj8RX0aKEtN5+BgkLlEsBhy5P93apnuFnPsOMJt+aNgcR5lefqhF0tASCy4KTkBY7KZGDghY1NaYCwMTCoOJOxpNcm+a6goHm3ezWAArAfGHw/roGDT9cjtpYWg4WmdIkFeyNiMOZrE9PDgxhogAAKoDDXEjSGrEWwM0MBWICG5X/Af3HsMMlDsw6AAWgTy98L4ODAQhm51ywmmeCVhMnPfdKjdjPUBhXbOjUJkAu2aEefzcxm/1ZwyNFFZoYS09EZ7RpjMACYuz9DTUry3BlV3EBFIeAMjImAM13UR2RaSqYqUSNtLQBLp7N12ppGcUhi9OeVjgFmPXzzYLir1T1qCZpOTXX624PEzIRbfIZz0RYUHG7WM9yqGzww38AMwgPzGc7rBufzZgEMs3znxFSVCnFj5QQUjmZODw5qnlz6wCKT70xd1u6YZkYXOtzWhwFnf8MxTvbKZaEx+d+nIGZge3fjw90EEG0AqDlJgSGDAhsAdAnDg8GaFtHKSGWOBtqBAZMfIXeD0CdoBQVgABqY6LWpVMwsNu3SrrOASq0kEUnORizAgALTIFBgIFGoNnCgdm+0UK1IlJOaD27QrvsVqIHEDZrNv3CGGTdobuCBFqmj4KBaww0iFABnVDChgcNEI6bLqMKcKhiFAVAHiSipk2NUUQoF9jP5xToFt35A30t/bn018hqNFp41zaJIuKtEHPFkgHGTz0xjqEy4v94QgDhD5YKb8xnO64Sb86aBQ22RTLMAxEjo0S5magJFxbpPJzuA1V8CVMy8WfgVgCVwHIoa03L69/Gai1HYbR0CRNQYDCRqOYm5uBGtapZ3C909AMHAbp6CKSkDw0h78J/A5UHg6EHH0RfBTB0liMECFP6BmakBhb8mQIhSgQoQEZg6UKC042SrSIA7FGxQsavFpMLKBTs0kABKAxdT40WLwHIzsklNSQIOZwICCgYAFuDgfQ1F2jLJ5xkVnKGI9lCGGkQhxpZ7XWYwJhBmAYfKGs1TLDII6KGleU3CSJJv+ZYAEromoeXlIocuyGT2bbfhF7HNAg5qW1fNQbWGXZ0MHM7rBjsuuLlrmsN2nsz+PtdW95HmUIhBaNpmBYG4gXQlQnGm2h0KCvfxUysNou32A8FFQln3rbPIobY5GCWnGflaWLSIUxEjaq13I901AAEQ5koHgcGblPTdBuZ+AeZ/EV+EF4qZaRgBpdcZEukYyhU7uUhzRRyIcy1NCkTTKKbSHGckwKMTHmgMQNunktW+8E6gMcwzBxJqMmhaQzU/g2kOAhxZc8ggob6GEThM1L4BgK5UrTxjIkJ1nT6jmUc8OJxjCqCgYDACAW/GGEnxZgKS69kmfhkabU0RTSfFNIfmkJ7Mv3CrbhYaQ2XCrd2mrXmoLXpJx3utUQDSMcfUBYoJtQkbpdqYQdXtWERjGwBDpmNDu5f9QcPfIyf6KBJxNS3HCEZvdj4lXWsQDxNirGsNs5sozBSBYeigXinjgoPrUBjsPvIgQaJZQHwPsS5s2zoUiE9C71OXEIFkKuAW2VG5aQ5giMnKbengqKSQ1GKhqs20VFBxg3YdDFKUUv8U7QEU2OwIHPS6gsTMLKDA2IKxZeAmF9Matjw1py6mYN83oDgABOe8EXBpaZo/IK5KbvVYAsS+DRdHm98dcsAqQOy4aQXndZLIpOaAPhdtYa4F23kSfwOhmol1qR1nXxYTgFJAYECAhdTk5EBhX4j22vW175nWmP2he55G8zKDSecLp2PojGuAuK1ERO8K4N+6S+8M4O8BeHMAnw7gv8n15zDzS/ZmdkFePAKHNV9Eu7AcCBlIsumc7Tpb2oF5/WhSkKjCXMkx+2YigC20qiymAwWXZEPeN2ln0OrAiNFLbCumFw5pck5si2RZljmJz0HNSgWR+VZUzFxRUbFFxS2umMG4yYSbXHCTNw0guGCLSUBiEwBBHb6HwED/gBYqqb+9uSMzBB/VFUM3Oe1TtMzDO1qBbmP3IZrqbFZQqNxWSO/mybSF3Sy+htoFoBEjJOKmIBCjFNEmuKKUZpZsINfMUz68eh+N1vqM1vj4+0przPqiUUbHrLK+XXRqjeROo4cUIJj5lwE8HQCIaALwGgAvAvApAL6Gmf/p0ZlRGyiV1H1GgSkvmTmDhVmqhD5K1yq6BJB2IbcHIUxJvQkZKFo5zszknvPmAMveX0sgYRmQ0xq4OZlbSGOPdlpoEOxCHtM41zxGFHebjeGutjL6SMSewSisEViEvsNTta2Ud5hxk2fc4oqbzNgy4SZPuI/PbE2ADw/NgKCMvmsPceWxBwNddbyrE7ZcbKFZ77MS2jxakDhsp2P+YUEXZ2drjLjRSCTVFubaTF4KCsxA1XDuugy4iGtv5DcRmEWL4IJJfFUzUQiKOIbW1u4s7l9Bm855HcpP66LbwygT14itU2kRFYRzTIcTPozpTjIxfRiAX2Xm36CriNmO+uBF2+ZA57UOEAUJAN3wRMLEGQuzUzZHDcxTvmyWcgHqgKRF6yODydRcBX1yW3WRzE5iS26TRRrnTQYqBUrkkiUhxgY1mJmA2rZfKECR7R22FSilrabe1g1QdtjyZGsbmoS8Eb9Dk+BBDRzOuQGJX3FdQThD1Ua0EFquovE0gJhAFrG0RcXMjPuZcR9PuL/eg/v4hkT23MDNeoab3KJ71Eew5U0wDW3FRHOLz2wvoi0XWz9QBQxUQs/hobOz6SsVMcMALZpsotrXDhAPJVpl9mYLT3bxvFbH+xHmWjDP4gNhNE1Bw7e5a8NrjM8YK8l3kvEn40O1iaHg7ZtiY5f7eHSahjdfjcK2Q120L1cEieFzTEdrNsv8+GTA4Olag3jw6OMB/Gv3+7OJ6JMA/AyAL2DmP8wPENGzADwLAG689WP3OqgzBTXcTa4Q4eSvuYnY71tNlvknH4Fn+Bop2H6TuyZaDCDA0UNdLQ31ycJMKKUxXtQCIsZcgan02KMCmBOyoPdFAwa/cKjYuovKpYW7okXfBH8FGDOpSWcDYCefnWawOJQLZnFcVxBm9XWAocvy/PdJGj9z9zFsmXAfn+G+egNv5HtxX72naQ0CDhrlkwHBbzlxq26GgKDrBdSev50n7OZm8tnNpUvmbnz4MONmr5cw38J2zYOEmY8GizZ1y4y8JmdWU5GmrSSgIEAg9+HGb/j0JOOqf2dQEf+DjK9KnSH38euycMIM2bhUsCEzXXmhBYi7AJiQ4wpqi0R7v9p1dE1btV6vDalmrHmsmZS8/0F/n9JRfe2DeJCIiG4A+BgAXySXvh7Al6O9gy8H8M8AfGp+jpmfB+B5APCop7wth0Vxg8kd7LMJFDpYRFBATu9BQdPsG3Aq9gNgmxycfmMwkfTZFm2i1/S6AkUVYNCJOZUaQIK5fWdh8t5hbaaOEN0UgQKoFsk0cz+YZosJE1VsuQ8h3SICAM6w66Gw6rDm2kIpwZIri29BTFLcQ1bPMeH+eoYZhDfWBgz31Xtwf70nrA1QQOgaxGShoBWEW3MLBW0LyZoNP4eEngsw7ObJJHWuhDqXMA685F1Kl75LaQBRSjXwAKKpI0cW6VjNUXXK/GttL5mrXKsOENSU5AFhbQwG7QHOFKkjcY807jUGeZ7FDMUClGE8AiBWoUbDsyNYqHau/aKk5lJyDL8wG0homprSq59nzb+xdFKvN/fiRMOAhbuJ7giAAPCRAF7GzL8LAPoJAET0jQC++1AGLKYhH8Wx0CBsQnYN4aDpaAUQwgTVQcrhpz3mP0kkN29aMimPeuFMzozUZ8/BiQkUMzlNpTmuieU+k9j5fRRTr2y2h6ujdUMIB9a0TecKznlj2kFFQeGKLbUhNeEMhST8lXW7jYotZkzM2NIOYLgIp3462s26wRaTaAuTAUP7uzE0G3m/gd+H6HyeFlE/u1ls+rPY9GvBvCuoc0HdlQ76mRFrvxdu2hABZaqgSQBDQcPMLDqOOhBkAWU0Fg0QQIAABBig2scnhbG5h7QSUl+A2vgk1yg/Tv1jKrQUAsBtTBYJwy6Hx2PLhzvTT9rACCw8u62tWANaDzjs5o9q1JmWINHB+hTUZtk1QDwY9Alw5iUieltmfq38/IsAfvGYTKo48fS7SmQWD65Sm5toHQQcOCTGb0yCqQtkXnNIE5Xs3+DTHnMTV34G8BBpzVYL64SV2bg2MVE1f3HVE8liutK332C3wEgltMGc0Wgmf1/NTLo9RTszouKcNsbk/ZbhNzXKCdW24dC9evLhQRqS6kFhK76H++uNsFhM/Qhb26GUFqCwE+fu+a6Fh253skZibhE/825qTGNXgJnAM4HmBgyojSEbZuurLty6tjC4AHMpoIkxO4BozHMFJGws0nL8OYCApCOpR/OuOkHkKHBI4001AWBpU3LpbfyV/pjyQa5iShLJg4qCHlAKQM2I1U2oAoxRq0AAC2haNAbetYGW1sylMhd8VGB7tmspSh4UNN/boUWcwsRERE8G8K0AnoD2Zp/HzP9C7v1/ADwbrRv+AzP/bbn+RQA+Ta5/DjN/75UrMqCHHCCI6FEA/hyAz3CXv5KIno7WWa9O94bEvNQahrZbVdWzJpC0gHDNfrt76PeXjepMv89Id9v+6X1GmMzy16RVNUWxaRWyaY75LEhMG+KKaNCgUiZ6mKuGvoJgsRdRg2hagmoNnlq6YtLcGYBbrAuqamBYPvTT79mUDydS8msMzsXJfH+9gfvne2yh2ANzBwf1I6hDeSd7cI18CdvdhO1OtIW5tDEwE3gu4Fkk812zxxUFCBZliaOi17qAGuMUOz5PAhgTo04CCFMbLFT6w6tA4MeZgABVRIDQNHn87SMnmLTx1lBuVXgmN5w9MFADRQJB9jeBRevZQGvjsFaTX8wprKZQBQqgg0GsS/8x2ukYgNtqxptdWxQcsAxvHW3OGczJVyQWk+YJaIfmZ30ZET0GwEuJ6PvRAOMZAN6TmW8R0VsDABG9O5rP9j0APBHADxDRU5l5ue3BFekhBwhmvg/AW6Zrz7xcXj0ixGzIFaizmA0UIKpoAvq5x1y010TL4RF3g/p11QCGGbgvBgpsv7m0idX9EcIn1Jwk+TMXkV5lzoqxtjifxzETY3T0qafurygL22s3EfRnbZfXPceIziBs9RwDmXAeFPzKYV0PYOGfab8hXSzmfQnzrgFB0xLaeKCZgJlQFAxmAs0A7UgkdizAQYmL/E2Ng/JE4EmAYpJ3MjG4qF9ooIHm7w4M2ieZsT3UJZmV1sdfT2D3yAk7Ln0USCQ9Uxt7Mg5FzGh1FuEEaNoECM3sxDB0CNqtgoyvo47fPeNR7+hOxzov+r5j6ONdEpcDqkH2+VyVGFdbVW/5NGvJa+X7G4noVQCehLYW7B8z8y2593vyyDMA/Bu5/utE9CsA3g/Aj1+5MokecoA4JbEHh0odHAQUugkBMJuuNxkBi0nYrq0UKOOM8oR0CgRjPBgXkqleNJuxk+D8JC56zWkVFqYo6wikCepHaJ/jJhyKT2+gUPq2xi5UVu8DcSvrYT5uW4uc/5YnPDCfSXTRJiwO2+lKYRYnsmynolFGunrYO5armIuABgTYtU/aNaZMVQBhRhMSavte2lmqkgbL964APan5pYFD3QC8aaDBhds4K10rJMCAwJuHjOk7MAhahAGD+36A+lhCFFSsIvG3gQIBXMh8LKZdCyMnFmDURws3bcoDlvon0M1O6NUImsHavPDUo/56pBSzBAYoaIjGrH4OL6CMtvY/LV3ISf14IvoZ9/t5EmQTcyR6RwDvBeAnAXwVgD9NRM8FcBPA32Lmn0YDj59wj/22XDs53V0AAXRwmMnAgcWu3CTHDgyqRYTJxynDTBS/ZzWZ4KQ2xngapHz7xKc4iVWI8xpEWy7drxWR5DQjFVk1H4dYeVGTPxxm3147jalPsnxtCm3IjN+vGN5yX3cAwMxDukhM01eQbTh3a95gO09hszldFKa+A+akHaoJcab2bk0IILPhGyCwfPeagoADZYDI78oDxKSaBMyRXDdik58QxsZinHmGn8Gg9jTD3wPyDD8CBEzSXqTX8VE0Kgk9/FX2QyFuAgiH+nYZippDoI8/K5djoQpU4+qvk/PjMBroElqfKDBU9z1EQLnS2hb5F99g8RC113M0QLyOmd9nXwIiejSA7wDwecz8BiLaAHgLAB8A4H0BvJCI3vkKVb4w3V0AYT4F52tQYNDJtgYOCSCG5gWnHRztm1qZFcHJvbgh+VcaaxAV0YE4AeDmHKRUoD9cCNi/iVpxANI1hFag+iA81SQ9+X36NZpIzyjQ1cEaaur3JGIm209ouxP/AevK4KQViJlQzUSYqdvp1VTk3qsx38yEE0CoFkEHpHYFBTU11U1Lp+MOBPAkmp1/pU57WIKE+9R61XhtNC4XwBAYf7qO/l0BAWh5s4wrC39lljaJj4ubU5on0Saot1k12ia8xDrEDhjT/sV9ZGG1IAZxc4SrCZWphXB7kNBn19ZGnFqbOBXoENEZGji8gJm/Uy7/NoDvZGYG8FNEVAE8Hm3HiSe7x99Orp2c7hqAaIxEJUsBCI1McWBg6UViyiGrZtc9VN5oXDAAUJwPg+8jQNLrujaC9J9NcuqO0UKgSaS3TUWPT+/gEsMt24Iuf3KYHgIDREAAYE5gAKhUsatn2NbujBv5KvSYy5tzO7Pg5rzBA9sz3L+9gVu7CdVFEfk1Buw0PLC8L3XSKvOfCWUHlB2Bdp3xq1Zg1/Rzdjxpz4scMef2mwOA9AeAOqH7HQpQzxpI1DMHHKSMdlnGYgxoW5y2kP0gVo9UFw8GbVy4MaPmoNKBwYNI/t4c732sKQCq6Ymn5m8JY9BHdBFMs2X1j0k9l2stskqzfDd2ieSXjOlaWpSYBmbsBqHFo9XWfh3K6XwQFNYBXZaohWE9H8CrmPmr3a1/B+BDAPwgET0VwA0ArwPwYgDfRkRfjeakfgqAn7pyRQZ01wAEgAgOyviBwM1VSFJVmdQOxE4NPoK5BEogsBCY1rQTrZcHifxF7KxwarZJrG4SkgMDwP/2++TE40qBZWig7k1kjmW3aVzf06bIvlfx2ZvzGe7fneF8bqaiB7ZnuHl+hu1WnMbiMG6cFh0QxE9AVSKJjPm77zugbJ2U7z+dBlB23HwJ6T2MJOlF3weNw4EEusZAc2OWddOYpDHuCuebGLzvgQbgtQiv2XhfiNUlazKeAReJTlIHunxvWkGvDzmwCFK+LnFxYEE+r0kK5AYS5CYQc9IqNL+gPdCwv2NDMAw/pfDeCFwFLApZSDGV2pRt8cWNtvXIa1BOQYzTOKkBfBCAZwL4BSL6Obn2HAD/EsC/JKJfBHAO4K+JNvEKInohgFeiRUA9+3ZEMAF3EUAwo4Uv2gIjGjNrpcybdVCxu2mZhyTxwUMSKhDVjX15jepXCFQ5MjW9r5Ka+9MQQ9sKQZM7YPAnzcWV1O0AITBQ+UzS1sWmcn5zOtVKmtZR8MC2aRsPbM/wwK0znJ9vMN+aGjPZlq4dCPMrYi6ibWO+ZSv+gF1i/AoSyvzVTDR3Rl523J7f8YKpsoSnmoSc+lOtZQY8AhCymssYpzqlqTaHdJP+CSR+iWzWWXu/Iw3CTEsVKDMvNRDNKwEdy5oMZX7qhmKGMWsm9GXIyq/lupqZzPyk2sPk8pL8mXukEwqcsCJAoVq5jc890jprI1yf5P6Sivr8qIjJS66RBmpI/eeBBgFo/5xGe2jVpJOYmJj5R7BgOkb/y8ozzwXw3CsXfoDuGoBo0mhfBcvO3xD9Bn2DPruEnsa0ivTixyaCpQaQaU2b2AsQXhrzmkJvagAEgAMomPBm6nZ/duSENubPAOTAnTU7re6NE/4EIM6rnF2wmxo43Dpr4HCrLUQrO1q8E6oA7QjTuTDGW8B0y4GEAUFjmt6noEy87AAwY9oyaMsNKHY1vPcWYaSMXjiknJbkTTDdn9EBRk0mvKEW6y8O6bZspAE4TbQAiOAwzuSZf2pTmd21JvYONQhSoLOxyTqAB2lhwODrZUPM19lpH+Z6mrQM3fWYW3uZojO76vNdc9jnajOQyOAQ5qziBPU1QKItUGlhtQ3g2RKvbeh36g37rldSP1xINIg+wKgPPrlv5FVPGYEeKAJIePXfDeZDNu5VzeUYzUFBwU/aMIFZVvLK6l0NqXSqdVazh7uMSt/4T9UEDh3WoseW6vfK7WSz893UTjjbTphvTsADE8qWBCDQAwa0uizMf9sY/XQT2NwEplssjL8DQbfNs7PVM2inQFFRzitoW0G7ChKbBROBN6UvcjMNQhkYNfs60J6p8invgafmLOVZgGDTgI6p+R6oNp9Qt9lLnso7dBWy68JVv8fs2pXShDEiq7W7s6pnzGLCs6sq6StIpHFHfoxBNAp5xjQKRjOhmeAi71HCXUFofeCBIggxiQJAQIAmtTOTvKvm6yAb8w3wRbvQ6b46AU9HuuHi3Ux3D0AAfcHRgUEWSZlI+0f90pKYQvjjwQG9LGa1foH/yoQ1tdrsypyciQiT0BbPJco+B38AvYJB5bYn0eh4xvi95TMl5yAz4Xw34f7zGy0S6eYGeGDC9EABbckkfe9wXQDE3MBhcz9j8wBHU5EBtQCfAEWZGTQzUBllW1HOZ9B2Bua5ry+YCDxNCItBiITZANz2iFi8J+kwAQiAJzl/gWWpQGl14gLQBh18ClBl0VzQWIYA0dtXPDh4P8roZCoVIkxyljIq+joGTa+3941XN45UKyGvQeizXruoAp6ljT2Ww1jUf6H52jj2NAAESoEky/rJ+K4RfJv/hPp9eeDEysKwUg/m4UQPBd09AKGSVrjmZ+TKcyqxSyayqUBXu4HloF0Dh8HgvpAgM9IYfDSJ0x6gmsPQZjXIeuW+7lfkt6cAOijoBoh+GxPdxVR3LVWA2M2l+Ry2E3D/BtN9BdPNHoZqDmXH/NTu3qKUgOkm4+x+xuamaAPVSfS+j1nAY26fmBm0nUHnO9BubrGPumd0KaCpgpMoqxvOoZTFPSiz37S4SiKAK4NrAW0kGqZQWyBXWHwSslBuasyumg2/r/w18gDpo5dmFi2CwxgzZq0/BHjUuWy+AN9H+ygPG3KfJEzeFac+DR2LdZI0FnLdI5+aZtsd520x3nICeo38oMAl2oOZypwvJPg79k35E/NyRtsa5m6mu6h11NfcH0g2vKYSmcR8E9zE18lNPb6dfVac8tGfR4LDwoREfaKN9v3xNuVsb/XRTF5z0Bj3vHurnWk8F9x/fiMcdM8AuLbN7XimEAFCk9ucjtAXJ24n8LZgc1/B2Rub09mqUb2UjM4cTYNgbG4yplsV0/0zynbuAJClaAWN2sxJ4AYQ2O6A3c40jbboa2ohs7nj+8ZBIPFHeM0CpYnKbQFZeylU25qQUgtQOAKFhrmKj6KoFCuSd6iAA0gzm5mWxU5T5QETp242krxiu7oG6k1HTHFMejMp2fh3n9yVFd19QNtRxNdg60JU+yiwgACbM24xXqimBwQDiFEidNeKzQ95n7Zinfr82UcnND0xbtcK7TuH7h6AYLSFU2EGrH1y/K3P68uWKIlmPojLzwjcGaX+efXdqech71wnV1zQFuy7OAGzOUk1CJEivVlpLWBEN+nbcQFq3x2zoi1Q0/MQtrsJ83aydSHMskZhLm27CoYt3qsTy1oMmcC6eO28YJqBzf2Es/vEgQzHnBQkRIsoIjGXnQOImxXTrRnl1q4BwDwACBFpaWZgN7ffu137XqusngIwTcKFqeehmoV22KQhTAWY5HTszdSYHGBhn8QM3pS2ZSFXcCGUCvDGBQjVJl23bdVlXYBoYp5ZR4BonN7AYe7aA+WxQ4Dui2TtcPdZJO3gw3Jm8mw+sqmgYKPf1XSjddUhn8N+C8BzL2ep8fYIsH2+iFWzqyBDAzA2QFRA08V8wQQ1oK6BnZahnyjM9Y6luwogyjn1yBSRLMwso+NCF/X4wWTgoFEy7TsjgYRNcIaq9CEqh7E0cwFhTA61Bamjn1x9QRL6JnCFwSK5a5tskz6V5l2xVUXIUsFzOwfhAUmhW1dsdxO22wk8E+abG9B5CSvOy0wo54Ry3hkaO8nR+n4H0A4tGmlukUjTTWDaOs4DWJy/mlLKLL6GbdMUplsV080dyv3noJvb5kvIGkFrHMT+1dIwg+e5p9O02y2IGkO359x9oiJOVmpgUoqctlRBm6kt2y2laxS70nwaco2ngnpWQJNoWYVAG6DWZHayd6viPDuzGxtQlBk9gipvZlSkTWr+0S0sin8nZCu8+8I9IAOT+RVEgxH+29/T3AUYUgBI2kgYx+5aXGSHuD4jC2uOFtrOYp5Q1yI0G/Ih4E5L9OBqDXHb4JyAGMvdBO42umsAwpgXYBKHfveJPDiYUClSlZGX3pIUl9V0FU3suuSV03ltIUweCJjppCrsJhrDnz1gfgd53kcvZQd1O5WsTaDdXMJ1299oLthtp2YW2hFIIo78Vg80N3CYbsGuw5kVAGH62/Zn4apblqglkZC124UhFrWzb5ujuWxrczSf1+ZH2M7A+Xk7SHy7XUrLgGgKAgwKFkqlALNoN3AahWe63M7tBhNommD7VVcZTBr0IC+QazscCFwaaIuXmqoMEi1iRrPBs7bdczTVYmA+hyJH/xk4eP8DtXu2KK9yB0mtnK7TSFK8vqPF4j0XKGB1cT+9VtEHTmpGFnqkLiGSC+jg4LUKxLzsWTcn/EI9UjBTIGCXjwhxi8nm5m8o5KT8nK6PHH04kV/1uuTkPmH67SeEmY/ITaCuJaxm6SabZRvACXESKAAEKStpPQYOXVvQ8EZv/+9HQvbCTXvQujCc47ltg113BXw+AeelrUW4SQ0g5t6XVGEAYaG+PmtuGsF0DpRzxrTVa9zzEaYc4vwlQqlsmwmJds0hTec70M0dcL41fwKrBqESP9A0gspde3DgQKW06/4Ve/Cwd6agM0GjxVxnibbh8p0ax+KJQZhanrZISw/RgZnS9MzmBXfV/GrvE6oAZnYL5DqQsEoyCSANEAwYaAkOeXU3ABYtLjBPt+4iA8WhOAjHq6MWMfg+NLGip7M5IuZVXX+hQME9ueufltnCp+LmrFMiTqZFXGsQDyditA3RZAgZPnCcB+ERr1LvY/xJo9DywsZ/e8Ajm5S8dhCc0PLd+xtY9p4xBqbgIKYlOyzIkR67ar8F4NoW6LIL6q60lc23Csp5aeahW2TbWVjbVTvYwcwR2hY1F5VzxnQuaxeUwQ2icCD29TKzAQTtKmiuTWOoaABxvgVunQO3zpt2sBNHBolppzWyA0PyTwQwsCPFXJpyJIfg2neG07xKAaGAqTYgYjkLgRm6dkLXAbTT1oQjmROi90cDBgGHqs74plUEmiLjbhks/4bgoCu84eYEiSspYaatqOblvZaBSzsQiLRaUTuOjH+kOWjdfJqqda/tM2j7FJ8jTvVJc1WVawsYOBVA8MkODLpj6e4BCDQmxpNK/rJgiBj9YGZZ9enFENUWABtcIyezSYV6fWV3TiA+O7bPOnDwWoVqCEAEh9JHv99jSQuyE7o47uWqx1tqhBELQKACvCsoNwvKLcJ0q2kN5byBgWcOYVO8sLoXzXcwA5tbjOmmrGTeqeTLyz5U88lcm0mJBSB2FdjOjcEqOJyfg88FIGapkPoKLE+OjN8XtrjkGlXLEiTy7yrvgucuvvp8J2X6DRgYMu4q+h5I3IcY0KVX8y/YuNItO5rmQA7wWMfsni0r+vhJIKFnVagGoYpIBTC36yZKOPONLZSr/ZZ9D1K6a0MS7b3fwJdv91xe2USlDnKeBSg2vX1hjYUrbzHW/FhNbdy3+8dF6Xqh3MOFGD2+vkDi+Rmm4lNbkt9FCXloD6nJycBhpDGsAEPMaPk7+BmU2bvPrm1wzyP8KTg0YLDoKijfapn0PapKODynbAnlFmHzgDig3WK1haSoIOFAspmHGkhMGnm0rQ0gBruukQLELICgK53nWQBCzEjbrYDD1kxLLOYiMkaNxtAVHDzzpzRheSQKJ1JwKO5ZWVHdrqNxKyI94sx8MZqWapfUR5SjhvRaF0rYAKblKWlU0PFNckJFYMQEi3ozkNBgAo+rpTWBqix4pvbeTbgmREDQG2Gsx21PLK3UzzSJPJ7RQc+30+5p1JPuebURZdGBHhzghJ5x83K0A25wep+A2us6IdrcgXTXAASxahBtrjUBSDUHqFIhDH8QzaCaxPATsueOk66zRDWgHLVhDnL5rd/HqrfbQ4m0goMyTGCnAApg2HkKqNSc0Du3qvlW8zlMt9ABQp3KfqJb++EmX3NAN42hfU7binJrNg3Cb3NhTdpVkALCroJqbWGpPjxVgIHPz8HbHcAVXGXhVS2gotFIasNIADAABHZahl/vYIvoqCw1E0+zEzQ2F5MYgwbpyDuC+/dupjqa3MaDwdbvNImFeUfzd4y2UhewgI4HumXGYgi6cREFJoEzjbDyTJncw166dyChgFIntJ1zZ4DOWltqhZmcRow+mINrzzdoKifVIC50otzDku4agABgtnNzaql5Wjmd2oIP5eMH7mjQZdX1whW94HW76Qo1bUE+1UyuoOAAjucODuW8Hb2pwODNSgoQnkmYImbtdvsi7cTMtGPQtpmNdNGaOlXJz8ZdBe12AhBiOtrtLJSV57bQjXe7AA7ts4FD+6QhEIyIhyYoNP+BhrRm01Xr2MFDDlz28IXgkE2re9fKUO2s+7h4zMlyBJMvE057cEw5R82ZRiA+h7apo6SpvcrF5YvaJfCsYfaABq8VcK+i1SWCcPAT+AATAmhqmyBWPS2wADhDtyoWBGPAIq8MQOTSn1KDOJU6cofS3QMQMlBtkzGGSdL7n1NfQtcWshkpO8GuBA4DCnVNguwiCEY0A9M+FAR0m3NrQ9ck7LyFnQCEmpO2WGyr7TePa91DUscu9fXwzL4XUgMKZzqSyofn5xl0Pve1DQoQu1nMSTWCg49E4grIcaeqUSw7ckWrsNvU0ti6hwPaQwiJXWHYmlSl8dLSh91jhTmuBtZlrWEATlEbXRGDKX1P2qvlwe6+KmSarfgn7NqiIk5wkHpRvu+BzlUZ4OA/MG3V+auM4ev6Rm6FmdNbxnT2awBxzgZzGNyrTK6kqxDj2kl924mIXg3gjWjDcsfM70NEbwHg3wJ4RwCvBvBxzPyHBzNzg4MHTJ1zOlu01P9Inc/+gPmLSAleupLfOonaQJUZyrBVoDzJoion6qi0Y5Ebra+6TVdBQH0jeWtzwICvrUtoPgeNSNLPMQCysyuzMRVv27VzF7YcVjobOKgDF0BY8bzd9k/mBgYJFDiFqLaMi/vqGH2myrBNgjStPl9kvcM0gTYbt4Ja0uRQ2KLG+g4o2Ezt0zNp+V43pZlCzgh1k3eOje/GxqA7t8L6zidTkBUxfzgU165lYCBAt8lmIIzzsPZFhQV/Up+eyVH0PrXdgWXogaWvbZyIQGEgANPqYwMVGXQcym8xeVYpmydgrm1tD2QRoJmOc/86YPDdwdbwQX9dkq63+35w6EOY+XXu998F8B+Z+R8T0d+V33/nYC4joSoJZ8bw/Y2kPfR0WEzqBWVJKaU3CWt2371TRKXL4kBCRDQ9l9dLa5aDAzTvQB/Wpfa1DV66CyYIIGz8ltsYNpRzIZmWZJItswWsAlBUBNCwjfRkNTSLcblthrdHvKOy1AJCPbk7r7OzulADhTWz0mLV8gAcpgnwDFsfJV0xDfts/ZrEa+3boKXIrX3aSsrDgwSP3pfm6wWmQT2az78FN6ipya7rXzVsso1iW327sGPTyd0jPeqX2DQSv8Or1dE2e+I+nl0bbCsSEEppCwa1LtDIrT1DRouxclP/XYWYT3cm9Z1KdwpAZHoGgD8r378FwA/hGIBQYjdgnd/BMEHFDvNL5OePC2FdveZ+G0/3Uo6lEWCA+64nZSmTGPEJy6PvlBrO3HYSP4A2m9J9jXhxzejXZMbvM4cErUMZ41QkzFOYfqXmiB5xsMqy2E3XMzBW/QoCDFSoMWkAbYFaBwFdtKb1ic93zcG0iLJH8vPgYNqC+Cyc1mJAYe+XADUtCTiYKUSl9NCXCHlZkLJ/7/qOvDaA+N3nR/opwoCZXCuiXET2iL1rPcuh723kMBcNHFSjZRUmRGvwb5iYu6ZRScw6vW3eb8CFDWxoRgvhznOotppSJZSZUXXzP21G6fWCti3V6dTgoHTtg7j9xAC+j5q4/H8y8/MAPIGZXyv3/38AnjB6kIieBeBZAHD22MddouQorfTZBwcO1JlhAoJFFMYonVVW/nIMN/tARrIJA9EcvN06RBVpfZ1WoHhnJqnMkLy2UDqjMC3fOfntRmZs5hTpkiYL825rUGS2zgRSruS9nZW7KWe0S2uob6ssTVPXHDww+AipDBb++tTMQiQagEYvGWl6ve7BoUzRFKUOaovSIahWERzDhLgdCRD8YyPw9SDBLv/g9Eb6Lr9HgRWmMcprMal/oVZrvTtQeIFGI3rZYbitVdBkAVTIyu+nAC4lnWYGpm4OpjZu2lqNWMEQulphvgQT+DKfpuX3UzqoW7F0vZL6QaA/xcyvIaK3BvD9RPRL/iYzM60cZiBg8jwAeMTbPrmfJrgyCIb31xi6PsCH0vTPNa1Dy7TVoP56aTcNJMxhIR4Jx0zsvpssNvlskqHbATy6KDhImuokRTsAR+y6XdOS87CLu6btMMDTzeGKFFv7wsQdgKlrRfvmpg9jZQlhVVAwzUHBITN4T7U2IACM2ZMAhOaxoCIxlGvgoGWVpXkpvMcROLhwT2N6DmRzHrq4sa1nECHBH1pUyJmxeqfqq1bNmSQkVLWIHMChz/QX0O6198TmYNe0FTEPDyB+Xtn+SYIqc1EtN4KS1cHXuXRtQ8PKM/k22hwbgIFSbuOpBf436b2YiOjFR+TxB8z8yZetADO/Rj5/j4heBOD9APwuEb0tM7+WiN4WwO8dlZlOzkMDYSRxZE3BMfvA+AdlLkAiLzJydSP/XMing4QyFvKM3tdBfQ5wUlWqjkqEfSLrd+qLsTRiRaREcDfhm8RIJOHCbOVbVE4BmLidDcAAbwhAARc5LlR9Ep4hFmXuc/QDkA9jrR0YgA4OahoyU9LgJbt7JNt3Iz+n5LWXoF1QA4fN1MECwrCd9mDZjLBKmHm0t/eu8GNBvzOonz2hjL9Q60eXX9BSBmPdXreNlQ4SzTzU8vHb0izwSqQNvafbmJNu+1F6vW1MSF7mg3FCiEpvERg4bO9h/cLaXg55Wz8u6tr/1oTEQ8LjZYhB2NU37SimPwbgr++5TwD+j8sWTkSPAlCY+Y3y/c8D+DIALwbw1wD8Y/n8ruMyHPz520vNutGadrDvPjne7yWqDA5JalIp3MzN1T8nIKGTrBrnkO0udBY6sEpaijGM0ieqzrIW4y7bTBe1+YrCIRO67hpvrL4N1BYdUmWRTpsprMrJaXqolpoiUKn5F9itg8iMtRColra3kjJeWwinfobuTCa/FTcA8iuqPel8NU0gPhdIAcLvkFqmDmLifzBg0HwT2S63A63RRzARt34zX4GNUy8ctPzZtq3XPxcVNfnf7m/Rvv5ngouODa0gOlBEM1AfZHYAUPH1iWWaFsBeQOn94IUo+6sy+Nil0Z8CFMGfP2qnzkOdM74Zg7Snpjf1ldRfzMw/vC8BEf2DK5T/BAAvEiayAfBtzPx/E9FPA3ghEX0agN8A8HHHZDbUHII+vYIE+VYeiJ0vx2xHE4AwXFCng9iH4eaJATfBFmG5Enq4NujbhGW3JQE7BsWWB6YmQdLEbV0E0G3LrCvQxfeoz1j7CMwMPW+gNDE07Dqh8fRcScJyHUj4qCAVpcVsxLUaSADowKAA4h3MPi9P3jeRo4/0uqfs//D1VHCYUt1TPm1vr7YCehEYp1Kt2st9f8r9ti24HkrFlnfbe6hHRtXJaRCOQbOaojAY+1ZH11QdZ/DjuUs7XWInBPHdCx4TwDvYlh39SNhWPyr9MdvTyWfn+sGO42IsQMW0IDe3wqevfnHPr/TDqc1Lb/JRTMz8wkMZHJNmz7O/BuA9B9d/H8CHXTZfb5ddFoo4gHSmkG7uhx7FUfr+RtnEZEEZ3i6rE4+kiIxHDhBC+GHmU8pM9JGBLVYBQdtpceGTLEaaGLozrNq/WbQINTuQibGwVefK7KumKw2YgpbhT0yr+l1Agtu/IHUGkHB2/kK2t5GBxNRfjoHBNIkGQc4f4PKxB+T7JAVr+qS5LGhxxoLTGjK4jYhhDndKzlhvignaHQG6rsV8OvrsRPZcCJ/d5GsJhCSfoRik49M7mZOAYuNb89Ox4Zi0gZ3utKqnA0LGmJokveWlT6H+U8dlZv5aXVevcD0BgTe3hdMXR+2/Dbz82kkNgIieCuALAbyDf4aZP/Q21etq5KUhdju45pmjNn7H4Fns8lwAkh07hxt/iYrc9/Rv+VjEhzDgUGQa0MZLVCLUg4F8Wv1eAL4hDH9SIBCRX06aA6EdaKPbgRc98lLbJpv2MVBlbybeEqqcAVE21BYnVbTFUfJZZKFSm/gE2gE8c4t1rxCfQ+OChaX/GG1r8YlBk6DoVORYWGHczKBpapJxjbuYKoAs/AhqKlJTUGbgpZ/2tgYgwWRkJkEvZg9oZFqSNRxlK+/orKASo2wobDLLhcRs0riUAb7DyZawXauTc0pv1gHBnNi6KV82Obl8SdpqvoiBUNJ/ICoPOsb12gTUs/TsTHYyHuYYuKZ5Zk19ER5ugh3Z98Ux89Leqsfx6o61uj24mzOeD2QB7xTUophuA+rcQXRsFNO3A/gGAN+IfqTxHUlhrUP+A7poYvZVDtdNmvNSu472kA+cCJbKJ1gYqbfjB9+ANxE4cAiLiWzCdE0BBPCGwRsBAjkXuhgoAGWq8IcINc2BZNtv0YqonWlgBulCqCQLkbYd5MzkpMwLeq2vpG0bBbYDc1gS8ixcyYWBNslROKI6r80XITYHfzDQ6ChQDwylBJDgiUxjCKYhezkOIJQmmJkI+RwGIIJWBjCgO2sYjUEW3dLcSQcG9tRNf0yy9gMSFtr7S014INiKbD82zD+RpGhnKRoT9/lxDFszxjryryhznkWpY61QT0vu0lCbRurfnCQBnTrAw5kX/rfTorymzkDwEZ0SKN7UfRBKO2b++ttak9tBOkC4D/YgtMhAanOdJWoHgEhZpk7byuD2XI8nl0K8Dp3NTQ4gPCCEv4n7ANcjRwE32CUzSUubdvQlFUaZGFRq+yRGEbAobhZUbuAw14JKbTO/hn9yVjMX8NwlWR30pn2ghzkWuLBYAVUzgQjA6EltehYAE0VTk0n7XYwn9T2oaULNQ35TPV0JDQBT6ZqCXONSxDxTVp3KBg5emtVFfajIWoS9e7vAoWP0HVOtzcm+44WEHqR+lUcEBIqAa7D1q8YwUT84R53SWij6I2FzPne/3YygoDg0QpJ9kT55fQ/rvNF2uLL884sopBEFocsXCqctYTx/3KFIwUmt+dSelYX/HqjOscTAm3YUk+yJBAD/nog+C8CLANzS+8z8B7exbhejkTrrpInhBBL7r5qaLAuRhu2AIP2tIMMtoqeZkFRUSbNANYmsQVAfzOFzo4yWQ/3V8azaQpkqyoYxbeYGEAIIU2laQ/Ov1ibdozF7PYOaZsZMpR8kBDRw4AY2FbKWQdtL3elc5AHVJmznDOprJXiCmOeom78sQomc2UcQ2K9lyGKdag7qMPbbZKiGUBxIEDmAcFrFHhOx2ePNo1Jk5Tc6Jy8rIOHJtjsRDmnnSlPnfWLzryDxz3MDhw13DULa3RgeWZ82kxMiQGTtxJuXgG7Dz8x5xB21aGXE/rr/Q3xNXoKvk0wjdcK7NJehEDbrwUE0B9WwPDh4x73lU1ydtQ0Dn95lK/mmbmJ6KeIw+0J3jwG88+2o1GWI0QeITRJhrMEeq+cHF/TT2lRCd0RFOLyozly5b4oHbquOq8aeKBL4mYE+kb2SodLeBNRNY6L1THwIFn3EXbMxXwIbMGw2MzZiRpoKY6Iq1pquRahpCQDmWqAn0WGHLkUzYa5NI+HZ+2q6ycib6qkKOIgTkqs00Ut42telry4OGsPELVLJi9NeVbEXoBoEiVmpgQNvit3jTQKIqZjtHl5T0PcRBkxX8dqrc0DvtQSL0EFHxUTqv6C5vbtw3Gpi5DYkJs2OUDfc99JKUrKBQz5b2lcjS9kDTWBVkncml7BdxTGkgpdK7q6twAFwyPNNp1swCaIzfNdGOziI4DSsDh4qWGklbNea2eV7Amp4+CYMEMz8TgBARPcy801/j4juvZ0VuzBRHzRAclxNTTLnibuZRsHBMeCsmttW2kwtOmWG2I1lL5i5FUzQIyEVjGRQ5oPhEcGBz6ReZ82nQJP4FKAAIWakTW1awlRxtplxtpkxCRCo5qAmpYIOEirdbKmrwczN1MTM4Kk2HshF+CGbrbaKltR8Da6PZYVuj2aCaQwWucT+jG2R6DelAUOtIDskWTqpVSIyXws1Fa1BwWGaWl9vBAwEFJoGIWUVx2ictG2MXh2utQVZGvMu3D1sGQj8b5VAS7ov2pd36maJ23xPTKhTe0b9O1pP2ybcM0Zlgv1V9HzR03XtGFcnr6l40nZpvRNQHHJyaH2l69s1n97nSViUoafKjXwRpnH70kwAkLxOpUHgei8mpR8D8N5HXHtIKTiq1K7vTTcbFhu+MODSbflqnvGSt0p4LfpHHK21SZY8k5s/okEQCYPhHn7hXfoJHOpZbTb3GxU0VYs8Uu1BfQtTaQBxtplxY5pxNs1mRjK/gwKE/kZj7pUp+CN4ImmjSECyJoIrGjgJ828SnbTVxU566ZZGkislwJioMfZdbSajDQDsmi9i1lAvbmdEaKcDCCam4sBBtAbeNO2ibqhrKxsy5pop+KIUyxlgsPmcFmRbRLi/Gu97extxe+9thbDueEthgaR9TmjSbWHZBde3XfuTouSszNLGnXxP/W9jzaf3wJH6x/Ia8bpB+vCQSP46FhaVW8myawck76K3PTinvRaR/Q8KiPabl0BpiCr3dBv/ExDjTRwgiOhtADwJwCOI6L3Qu/2xAB55m+t2MSKg3uBo59c1ARLxo+BARZjx1KRykh1VzQwDAQaxIXMlzHOz3fPcrmu0U49hR9t7SLgAyczhtDUBb5rGUM8YfEMASpzOLfoIps0U6lrDVGoHB6rYlBrAAHDgIG2ozkZaeQYzYaoEmsjaN01txTOLxtGYKMleTY2bMutW5Ajx77b+I0t3kIk/KQARmIpFFbfKtjUPNJcGFBL2GgBCI6A2UzcpnTUNgs9KA4NN1xxYz2AQCj4gRtMAgca4q9tOfcTR9oCD90eE86J9OlGOaHLlA2YTb2tVenIi2PYpwZ4+ktBHTB8uPdz1lMcojbPGhGdy6GvupnzfB3jsIwaS9tUb4x3NXjPoGmkCCbvO8IASB5sILeIn2hfNfBFqW23scXLdBXRIg/gLAD4ZwNsB+GfoQ/ENAJ5z+6p1cWKS2OziQYKBScw3pZtraJJIn6liKtXs+dnPXGXC7uaCUtrxh3PpQNFiShlMxRaaAYiB7QoyAlYKEHyjgs6qOJ1rD1NFB6rJaQ1EjHumnQHFRmbhQntABIgdlwYUhTBzxWZqJqa5tD6ozLK9hWxzMZVmeuHOSFgOamnmJEQpzSYxiXrfOAnXBjKlEupZEXOVdE0BsJMHdwoU0nmz4y4W5tq0EN4UMynVTengsBGTjFtgpkQM20uKqEvzzQzWI66GYqUHB8tvhbtotUUabocoQTQJRIe19oG8Iw0XNsYv/Tla27BPSxhJ+kNwyBoELdP3BvfrakXVdg6jmtBBsN9Mlcog5QE09EFPO4r+M+3BA6iAw6IdzC7C8HRS/5u6D+JbiOhfAfgEZn7Bg1SnyxEB9UYNEgQXNOncwKE5eUthFAGGzdSk8UkkcqUqEnZlwrxpUUC7ebIDVupMqDtGnSUCZhY/hS4t0HpwBwYQwDcqcENA4awaUOXwVCLGZhIwEEA4m2ZsSsWN0j4BBEAoVINGsePSIo9KA4qJKqqA1yTaDbMwVqpgjWialItSX1wl7VZTgi4CJAcSVaRlKspJOieg2kNcaW4rp4m5aRK1tjUIzLLBn7wEcz5P8ldQRXOoZ2SHFCkwqEPXhoSay0hWOBPagrwqDE0YRmNumQNiv+aQpYksSBo4UFxHkKX4qUc26eaMzTQ3YIojoFhh+r2e/V4wvayl82AC9HU9x0jdpP3de3GwVKiX6bW9FW0kRyep/6ELJhBfol53/q9B8Ekr53Q2pjdpExMAMHMlor8J4M4GiImBx+z6AjEBhWmqBggqjd8Qk8090w43ymwSeQYIlb7P64TzecKteYPz3QYzE863G5zvJuy2E+bzqYUIimE/qvDcTFxnzcxVzmZMZxXT1P4aMFSTvrQOEzXwumfaBWBo4DAvtIVCtTmuZfBvBRzK1LUJJe/QtvZSi3SaSdwmRBIOW+x5IjE1VYA3za9sJ+VJaGbdtCaXHUBnQNmV9r1Czq5uawWKSNhlV9sCs11tDHUngCF1aCamBgz1bEK90TSHquVNZKuNqwtS8GGZjUlzO4O7dl5e0cCMdoyKisIk2oxkkKKrDBRKr5uu97AtPXRLcC1bjuqsclxn8EOU3nfdc+sYYZKeTfDwjBOO0SZ8Q8+yp8v8zDFwb97R+lse5MpxZZim6QCQ3bO2DmiFLH5iRcsIfSEBJxq5pFaCEIiigDH1702I8VraaQCCcQ0QSj9ARH8L7Zzo+/TinbQOggrj7N4OEMp4VUuYqOLGZsaNaWeAcO9mh3unLW6UHc7MZFNRuaCCsK0TdlxwPm9wkzbGWHfzhHmqKHOxSCOeIQMTfaLKAKZNNT/D5mzGJHUqogVoiKq1xa1nIOLmbwAHv0MDtPa8Bwa7hrYyGtzy3pSKHRcpp2kSzISJGVUC2FnMTGUCKk/Nj6KamJ4c5pnT1Jc3gGRxtNigmfoRkWpyKNv2XClozsKZwaW0Q2VESiUNBJCOMefzprSzns90pbFqD/JdGUhibirRFrhV3lJ3ZWpUuK/sltBcKhhHuxQYGPj9mvyxo8iM2GkTXGR4eIndJ3XSM3I6iumG2kOWmNc0Dd6TPv02LQLoPhRN4BcFelNRApEhqaI6AhEHEN6kGdoTNKwEDhoRWFpBPRhlX4UuTtcA0eh/ls9nu2uMO2gdBBHj3nu2wX4/UcVU2Ew092yaxnDvtMOmzLh32uIR0xb3lB3OqIcbVRTMTLhVN9jVKZhsNLTU1hwUYbCMNjCB7iAjmBN6OptDqGpe7ezbETUD7uAAxqbMBg4jYFBqeTR7V5FtXHO+ZG1o6dqZOdzVc4lGIl34xt0u3lYBA7r/FM1t3tousKX9IM2LBTRkIV2ZGdi0T94yCslePgT4w2KaBFmaz8GZk1Rb0dXGXSIXKVz7U9Y76DoOzROM5jyfZfU3aTQRRcAoyhE5ag1T0iCsbgockXEoE8yH7nhzzoIRDgd6v7eIUho948sYAMQiDDc9GzQMvZSYtLbNaw4904G8ni6EQIJcd6c5Lf1eDhQItkGlRSqK+da2n5EFpaei672YhHQ9xJ1MpTAedc95WCi2oWpO3QLGvZsdbpSmNZxRxSOmczxi2uLesjWAmEV7uCm7kU1gbLmg1E1jsGCLXFX7uy5o48pwSw4AkjUMm4pp00DlzC1y88RpoPnw1fAnjH9y3wGEdQ97+ymla6GyMLBQUV61IiokE5Bk8sFWldcz2K6wRfpCd4H12y3pDp/qxC4FLW9hlvosTc0/UXY1LLqqm4K6adpDdaassBUFxQim3rFNIyjMqFNzCGv9bZtthoCDnsVRDDDIv2yvNZRi31kW9LU1GN1RnhmyZ4TcqxcZYHayZ342EH69xrG4HqRu/3AE0lUihxHUNQPbsTUBw1Gy+QBEDEDTvaxFdJMbm9+haY9qVpJIxan5+DRKsVkSZky65ulENA8H3cWIiJ4M4FvRjj9gAM9j5n9BRF8K4NMB/DdJ+hxmfok880UAPg3NIvw5zPy9V67IgI7dzfUMwN8A8MFy6YfQzo/e3o5KXYYKMR5141aQkNWvoABxY9rhEdMWjyhbbMqMR5ZzPHI6xz1li8ls9xO2PGGmgh1NLXIVEjIKsrUFWkYzMUkU0MRuBjX7f5m6v0EjpiY36/dFQajE3/+6n8T7DzzT1+2HR/mWYBvQ+kt1nUZhYFHQFgZSN89gAiq3zSmg51OohE6iSRS0g4fQJm9pFUYlcj6ixnlUo+DS/BK0EwYtWzY0hkDgMzKQ6CYmcUzrHB0xydYZFp5bhcvpinBzeJLbJwoCDuLItzUtzvfgF+fZ7+K0CDU9jfwD7Mw0nvHpAjB9JyMTDKVPzWOgQXhgYP+cZGoO5BXBwhdpSXI9sklppIUgtinkI9/z9YVmQ72PYrgrd3BQM9JUMd2YMW2aWblo5N/UAj3KcTB2kNr6zpNoEDsAX8DMLyOixwB4KRF9v9z7Gmb+pz4xEb07gI8H8B4AnojmAngqM884MR1rYvp6AGcAvk5+P1Ou7Ttt7kGliSoefXZuv73ErU7dR4i/4RHTOc5oxiOnczyynOOMdiEvPWd2WwtmEM7rxhzVbRVyHxSEpr3UtpORXGwDUB3kk0gvXVJvyY6Jx46aw/iBXZ2GgFA1xFVBg6NK7IFulgglQteMtIFmZgKL7V7OghDNgObuhwChr8ZGu143XdMgYZrqpFaNQhll26OvbW2iZpoqfobogwBCKCiwZE7o1/VEvIYP1NZxTK2uNKFFURG61kDUgErDI4WC1iDpVXOoG3EwBJBYr18wFRXH/JSJOyAJj2aQyJqCpRuEe7rnDHzM0xyfNS1j0K+rYzeVv/Z8B4ReGa9FLPI3YQHBtKT+pL4AllHOKjabihtnO9yz2YVgjxvCC05FWfO/XB78WgCvle9vJKJXoa0/W6NnAPg3zHwLwK8T0a+gHdX841euTKJjAeJ9mfk93e//h4h+/tSVuQoVYtw77RbROoWqaRIbms3fcFbm9km7sG5gBmFbN7jl/s7nBhBzLQsmq2aZUhhM1V2DrYD2qu2x0ov5OBIwtJXRXUOoEte5lV0l1eRk4CAaz+K7tGGvFCTSJxVq9l3ZQgSbboqyo1KzZFj6bdUkDEDmpk0AkP2LWh40wbQVPXiHhQnXDRpAbNL+RCMGmEnqVKtGYqFFPkn4jWkpYmbC1LgRITEqNTG1joatV9A9oPS3SreyC2vQEjwz1z72jn9JZ0yS0XcgHQCB5tlAhiMz3tc3wv8DSPjbtLy2yGtpsYpty8+47328tC+hvawNS9glwgoUHLSORZ3QLRBk2jQ/3z2bHR5xY4sz8TuOohWvRhfyQTyeiH7G/X4eMz9vkSPROwJ4LwA/CeCDAHw2EX0SgJ9B0zL+EA08fsI99tsYAAoRfe0R9XoDM3/J2s1jAWImondh5l+Vgt8Zd9i5EARgU+bVF+aduN6Wr9TAoWDLE27VDR6Yb+CB+QZuzme4f3eGm7sNtlU1CAxAAtClUMrcp9JDWJXZe+1BmbyXQnyaTFVCSXZ1ahFK7rrmVVxeLUy3LICB3Z9S+53mPMkeU8Qm2RIA3qmIqxfchFclqrRrqlAIBsiaA7gDaNRmL1E+JIcPOZOF+hvmM8jWGuh7bbm+Wp33ygzFDlZ1C4y53WBhNm1bctFe7GQ7X4C8L4tcQgQHNTPpn0m8AhQpIsekYgeePtTUHNpwjHLlOZOmHXCskVMOrHtCGdrslMcQjH1eDlQuLFg7UGir+dl9d+Vrf1q73ZjS0HYJab/nbIdHbLYWmHJj2p3MvGTVPr6hr2Pm99mXgIgeDeA7AHweM7+BiL4ewJej9c6Xoy1W/tQLVO8ZAP7egTR/F8CVAeILAfwgEf0a2mt5BwCfcuSzDwqROJBBCGYVAKjEq0cDziiYufse7p/vwR/N9+CP5hv4o909OJ8n3JybFjHXFt2kzFRBwuaH2e97mK2Gq+rA7PvF0dGDS/dTam2o1kZ/377DX29axK4W7LhgJ+axrn2Q1AMBNOKeeRLlI95Is0goMshaAdsevchc10gd6R9m9PBPZXJoTBDiG7BzJArEHNTDV+vUNYi8/7/SWsy99ojFzuuGg2lbEK7ie9BsdB2EAgPBvkMAxYODrujOZzis/iVg8NcUHJSZs5WZ+jDluTA/Wef0z+APyEAx0gRWACAw7lGHj+6tESNpEzKevPDh2w/fFw1FqEDWPLWovzOLWKwtvL3sluVegZiBeXHk3eVI/LzfAeAFzPydLX/+XXf/GwF8t/x8DYAnu8ffTq5l+hpm/pYD5T5u3/1jo5j+IxE9BcC7yqVfFvvXHUUVZAd46CI3QBhhmVFogzOquEUbVOqMclsn3F9v4Fbd4L7dPfij3T34o+0N3Le9gbkW7ObSoptYTmVjwlwJVfZh8cAwOpfBr7eauYRn8/NAwYRqkv65todael0LsdoHvs3y19ZyTFJ2a4eCna4QV8BjaR+5yUdl7tcljJMKNU2CADDZLre6ZbQHGW8y0VXMmBzfqQBtWsKyQ3N0m5NanNFn8icA0XwQ8rw3TdT+u1dA1l4U2BoNY5JTf5aogHcM2ghA5W42BkWBeWr4bRVQqGfokVYlAlv1ETkFbcHhBl0ydiG7xoBL1CBUkrbwXlkslg+b0rZbH+nLkOuc0vh29pfDQwBgAy0nBXg6JKhn7cR9McGhoAUIJFOW+SCCeakHhJxtZtx7tsWjz87xyM15C3EX7eHUW2OcIj9qB7Y/H8CrmPmr3fW3Ff8EAPxFAL8o318M4NuI6KvRnNRPAfBTg6y/Y0+ZH8XM383M/3xf3Y7VIADgTwB4R3nm6UQEZv7WCzx/W0ljklUq3tUOEBDBeyfgUKhiSxMmZlvv8MB8hvO6wR9tGzjc3J3hfDcZQ1fp2n9PAphbW9DNWCpwqsag4OAlDyKyZzXkZ2LGjtseRpp3IUad++6sI6AIACF9YppDMDG1cyJqLQZ6QaORvEkNZ9S0NDsdjuE+2UwoxoRLZ/ILW7VcM55VYGYnNqbY310VQGh+iA4QZrJSHiXaiJqvZGD0fHUbFM+MIUy6okVmSXV1q/bcxd20QZ1hlx5+q4f9mK8kS/guYilcGzmppb4Gqlq+goOaxhR0snStP73WkMOQ8iC2dzQwFQXJncfaSgDmfcyTIxDlu/pes5pjL5uH5qUimoNuaLmh2oJUXMXmC9u/VltwEic1mq/hmQB+gYh+Tq49B8AnENHTpahXA/gMAGDmVxDRCwG8Ei0C6tkrEUzfT0Qfwcyv9heJ6FMBfDG6RrJKx4a5/isA7wLg5+B2zEeL3b00XSb+dx9VLqY57Grp6C4TbcelbUEx3+jPgPDAfIb7dzdwPk+4b3sD92/bd2Wcustp2OHV6el5iHigAGDMmLmtwq6VgnmKREprgkTbC2IrGgZz22SvoC/Q032YwD0U1vshNG/daXIWE5NGYM2VmkZUBbC0XTWalwC0EN7aRNhuVrKKy/qPBg4GFMDqjp4LCRfOjEDdqW1MkRoDV1BQgLCD6+E0iNpBwjt4ta8wQU68gzFljaTiCRaZ1drttJ4BSJivwDmrNbKqavht3k+J0m9/2I2BhYyFOljXQa5sXZNC2hbH0JV5KzAw9cVsgfG6FzEQNlbBAcvr8cFY5oIIfSzlPPSyBH+0YdERzvse9DwXMy+J30/3MNNtac5kYWnlpjWvmZsvTqdZKMfMP4JxT67yPGZ+LoDnHsj68wF8HxH9T8z8XwHo+om/CuDPHFO3YzWI9wHw7syn2ijX6ELxv/uIAbOzq1llV2VriYIgeZ+7qKXzusHN3Qb3bW9gW6fmjN5N2M0lmIEMFLI0rF8JBgrqkPZmJTsTWj4tfpxUYCOUUvthPgJIUyVsJvFBoC30Up9EvpbNSwpiGRwq2uduluu1axX6TFhMlKU4f11jY1UiN+dzb9sqeabD/c87apVx1qkDhZmYpsYIWcusslJbmaBWW3FN0cc7jpnDJoO6sR4xmZlJtThvc7foJPnO4kgPjF+ZfzrUZqE1WDrVIAEmVbEo9hM1MOib1rndiwnwq/g7D9ZTDxG3yZBGBef0Gq0MgWzKA9BPx3N9tshKgHkIEiNypi4WYOACO2TLrzc6G4AD0E3QpzQznZwjnpCY+SVEdAvA9xDRx6ItS3g/AB8s0VAH6ViA+EUAbwOJ1T0VXSL+d09m3RlbmczmDgCVZXO7mcP+7btacHPe4Na8wa1ti1I6307GNJf1jdeI+vbc+juEpKKDwm5WBl2CpE5ucnNtRo4qET21tNW/CgJTKdhMc3PqUl9Al8FBHdF6baE5MIkmU2Qr7wMOcwWbkalIGJZJjW7X1xFlxyZ7RiZmFQ8Q2fxim7VtuO/cqqauym0x3gxAtv5QLYGKy9czahCYWdZJKLA0pkkzGbB4baKbdcjViRyYUddwMiDId39UZpU4fmP6bfAIM+8c3UxJTtPopiXuQQBrHc9NcicgvMujhWBnVWKk8QAEjcFAIjNQ0jHPtrpyYbJy9crgxQV93YMApC5I3UwSvh424Oxh31sBh1Nuj3EiE9NtI/Effwra4uYfA/Ch+XTQfXQsQDwewCuJ6KcAmHOamT/mAnXdS0fG/+ZnngXgWQDwiCc8GrvanLGVyUJSgcY0N1RdNBBZmt3ctIbz7WT2+HkuroyxiOAZoPocVHsAluCgTLrOymxVZdbnZNJpmQQwVzvLQRfjAQAmiIbCFu7qB6pOAtuuXMxb3kFeBRhqJXA+9IQ45KfmGvZGbsgE1g3wNEprJtgmd8dqEcroNArKWT+sq7IZxplVpMrCtBpHaRqFlK310PzgmDxa6CyJJN00iPZ823iQgZkMgNTaYRpEilaqE0UAcHX32ksAvo0u+OpScgtsoGgqchqDOWld/wUma12Te5/N7KT9ZukXzw5oRTOw37WD6jAvEypEmMBAm1grWvqoHRPcvpv2IKulb2yW4AC03Y2bVWE6GUCo6fhOJSJ6I/qbvQfAhwH4PXGKMzM/9lAexwLEl162ksfQZeN/ZaHJ8wDgzd7tCXxeJwOG7TyZM+qMCTMVTNwGzFwbw97Vgu1uwnY3dYY5d/NPY1a0mA1eY/B7P/V6kUU8KTjUuTFpFmbtJ3A+W8AkLNnWwqJ/Jl0nUYBSTbPw5IHBAIK7g1wjlhS8uBawY+jtI4KDmqC8f5PU1KE8iakveChskUKmISFJmK4Lul0c8Rn9KwjSsuEU9WdZ3pdpISS/3XYgvYPRTWKeYVU4sxJs5beCBwT8uqkn1idK+PH36HwHFK85sOXXrUtsQGE+BrW9J1DIPM+9QfcCfIIOdmAKt0ZAMZSTDG0ljZnn+j3/HPs6i8Bhmzl6bWLcEGjUku3UGrSHtjGnRg7qfmW6DmhXJ+zqhPMTAgTghJk7kJj5MVfN49gw1x/ed5+IfpyZP/AyFbhg/O+eOqKf11CbdqArZ5vJg1FmGSxi7tnuZHX03IHBTEsNYxemkgAO+umAwkc6eXCotc1iZbg2QQYaAInTbeYJZXKb8VE7CU4Fo+aDQHg+AsQyekod5OzAwfwOqgX4SS1pzR5uICF9w21xG6FJ7Fyoe5qFEdqBOXCfvYvbZdU0XFHRjBWBwUezmNmEJMpKfSN7Jq9J9qSagta1PVd0hXeoFHfHsYGXi1TSdRsO2LqWsQSJavsKqVagmmOrYDevcPcvKAArY/WdaY2DObpjZ6d0htLShyOTkBZjNsFehg8OCIDgNQifj4GpAovonUQmcKy5uzwIkzmm2+ppPWxrKm2fMzXz6u4C5mucNzF45QR0p5uYrkoXCXPdR/de5qFLxP+uEoOwnXW/pC4pA5DzDhrjnWvBPMuaBgGGxiwjQ6Ey5i62Tqr01dLqnDamLGGsHhwUeHpZ8ttL5ibstXUFzZ7fOBLrVh16MlstYp6KmgvQ66H+hlwnMKTdCL4WM2loXUL9EsM1zZr7yW2686tjmsoUgkkOsKglAEsnqfKiBBILM4olOoJ83T2zEWk9h+XqKW9+gWPbe0qBiWJevo6petmHAjhgWABf76AwAr3foTjBZSGiw0Cmv06n+h3TP4t7XVPwJqkWMeZ9Ny7NKD+pTw8iks7WdwHq/qzloyECTs9h0YVxuv5IqUU0skQ0Ns3BAOJUJiYcv9j1oSAiehkzv/dV0pwKIC6raF0o/ncf1Uq4//wM59tNk6BdZI5VUiXn2TFpLx0Bpsb6ueSjk/Tc6FJq2DpYmfBuFgDyErp3AospxgCJB5KbSpNT20IciIDFTGDRLCYXoeHvjxb1qX9FQSqDYqyAZra8pYzajsgUCRC1OdXJR+BAAmsIwS5NrdIdQPSWSPZqrjIGCpeAudm61fSjZMd7pnblvtUy/C15B0XNJAUoMzDr2RXCEINUDq8R9HURAHRxL9THPIpYqhuIs101A+2s2FwN4wyno4VE/kuX5EVIdx0Yn7NxJ32ZwdY7ms18JO3XkGJb1Mj92sI5nUBUd9Y1/w1BQqQbCPt+tHdWeLwI0tEsUYs3542BgJqUtnXCdp5sbpyKLsv4HiT6Y0T08j33CcCb7cvgVABxKbpM/O9qXugmI4vM0cms0rBeU3OPV4N1YgdgANSUohpDXuPQ2hFNSmMm3Ceb1iEwM/2TyWF2dULQPioVzApWBDhRPmzAZxFTAlzV98lwkrkGab0kr9AvMkNtS3CpgtrJm+NR1gBUBu+oS+pek9B8NWrJSYeBoaSq2bPs8uR4fSTFBkG7YNl+eab2Jpp/RbUoYmdi8t02qicP/oBofiopD/IrodnukW5Qp30+mjGav7WLupVtJdCCleEnZhz6L4OD3FNgUJA4BiD61uryW4QAQhvbzVnNZtXzmmTTLqTSMt9QYULgXAtmaacP+9bdA2bVoPl0GoSaie9gercj0uzdU+9UAPGQ95IuQpt3xZh/dK62zxZlQ13C01techMGrBNyBA763Uvrcy2Yd8U0lJGWwiqFyt5FCy3CMUZdN6cAUWvb4qII0yfPUBxV3U5jbgaSDpgl+D+8lN8q1+tj4CkcWMFK+ycwRpZ/RLLrK3r/byDnMACTOow9QwfCSmGrSgYJVz9TUFj3iBKpdsD0M3O2Ko9ARzUaoEdTMfpq5tLL9/VkovEMUGbq65wp96k2RMGUHDiU/QDB0h+2dJPMOxMAp/e/pJaXG8G2g0EAB5HiFxqEA4ehlK/lWrsQQKKb1qin18pMOm9kTNW22y9XiOBTMM+MWRZ1bqkdFcxMojVgsSPCqWgUDn+nEDP/xlXzOHYl9aMAPMDMlYieioZM3+MODHrmVStyVbIQUgkj5VlGnEjDbauFgQmCACiT8ZNPQKKsgIOV6Rixlt8c3q5sJ5Gr3RYVQSKzdqBLxhbf7wFPtAigQrfoyGQmJWlniFYK4IBYMGJ9PbNgDUnU7hmUqyupCbLKl9HOXSgqHS6ZrHV/YrrGK1bmH9kzsS3etBN+h4eXABE2x0PvfwOk0h6kGkFZwWHEc5r2gQBU3uwUyMajgIMKLB4c1kxMWmHZNJEgizR1S3atDPz3ll5P1PNO5eh8jr9JgNQANWkQewECMF+PjQONOPNCEfTd9zUSGqHGFW19iq6HqCqcSfCJRtZR21IjaNHO7HoqupOjmE5Bx2oQ/wnAn5ad/74PwE+jnVP9iQDAzAedyLebGEDdlR6myk1KD8zOS+1K2bwBdCDQ/V0G4ADABpxGBdVZylcpfaZYtk0u79ijvm4AcGF/UvcKQA7P0clAhYCkQYRtxGUy6II8Da1dSk/6UO9Ei6BJGoTEQ3ZpXKV3nxWhbxWhEt4GoJ0IihPsqNFsjgmMWT8zE1dmrX4Ijnnk34FRpfwXwKPNU2XASbXG1AhAycKFq6sHilwXk4AlqXxXEPL1CRK2BwcXEOFJu4LENqmrpmPGqpWwPWNtEGYc/BAOYIOwoBqEAoI3KXmQiM0P/eADAnhaAkp4B6XVjeXlaL+xLYQkzKW0vpkB5ooq272MgEGFplMQA3e6ienKdCxAEDPfT0SfBuDrmPkrnVP5ziBGZM4jO3+SjNlEPMDCNuWPSpvJbe6MwcHWE8wioQsgKHM3U9IIGKxuCAynCcUyWZ1aTZC1BapFFOUfGsorbWIHWIPQ2lG/2ac31QRG0bbiDsyP0U0Z2gaVfJma41UZwqblYU5aNUm4Opgk6YrWPlnWEwYAS0l8RTsa4aKCqwKDvn+2ZjvgQ9QIsMxv7ZppO1pnjf7RMw/yc6bJdl9P2MolObI1/1oBkAA3yfuxhSroJiqgmS5BLiAgdtIIXIPikoEig4OXHbQaCmQCjF5z4dRf1hdWLTEtEcCzLLIjyFxrfzOaIDTJZBgBw0k1CD9P7nAioncA8BRm/gEiegSADTO/8dBzRwMEEX0gmsbwaXJt2pP+wSdhzKjJnGRawzhaaPm9q/JrmgPQpRPVHHRdAcTMFDSW2iVyqrIVRDIxsUjfALqpw2kRDDS7uJRXhMMGu7pMAoviSk769b478N2Ycme+a2cvQByJyiTqRMBGVn7vUvhrkjSNgWB93nnnaQ6VXTUrBUaDhXbCQAw6IPdbNQP5vqhWem7NJAaghwPr9xCk0CpsIKUSv6waJjmd0GsBvf4NFEg0AQM3BW3SvCNYNC0XLWz6QN2tDRk4HPB5cFiYTd371p11yfdrAiNoG2R/L+u/Ima+Sn0djgpDBLT91NsD3swa5sSh+XABejiYmIjo09F2nHgLtE1X3w7AN6CtrN5LxwLE5wH4IgAvkq1m3xnAD16qtreTvElpYOsfkmoMTnLr0hovJqNfV+Ajg/TAHHWmgantB2TOPfnU6I/Zm3HQJCp0sw1nLQIEVF2hzKgo7YhFN7Ftwz23WvvK0lJiwlxhjGiVoQjY8QTQxG07bRCKahCyo6rf3jubbRb5+foYWKUwV5+PvyQaQPjtsx+VLQzN/BB6ba2O/vqgvt6OzyuiVTZvGUN32m3e/0tX+nOq1MKZ7cc59LW6EwOJDJj9pz2b+tUDdWzESt+sPbtHU7GFhopf2SxnQpRo8FQFH1JwRosk2K9JX4qcEHZn07PRNun7SQBg5v9KRG99zIMXWUn9w0T0SPn9awA+53J1vU2kzMutL8hSb7ZzKyCwm4y6SjMzgbzlt6mvojGoJBPMStzBwRx5M4UQwUUzdDGWY8LNbi1Sk2gRiiq6l5NfZ2GroweMTyOvLtq33QdBYIlGotSPwbZAzQyAiZtGNXHb82hG34YCDTCtDMHEVSbs3qOZLNxkH/puS0qXmbdec9qFNUPTFgQgG5VjWeb8yX3fl4fvS7jxmIQVBYcguDB1KZ2643mkRVgZwabj+0FXo8MAUYFkFRe99oA9/cPpuwImYQg4ZvqziDIxdfp2i5DAFahEdsYQ4IIzVFgyrfqETP1hoEEAuMXM57aVPbXjuY558Ngopg9EW/H8aABvT0TvCeAzmPmzLlff20O0K32Q6YBS9dSDAzmpUk6k8tEiGrmkjNSAATCJoVZqTvFdAWSfJZqp7dcjJiZbaTp3jSGAgwIE9ToTo21XwVKwzNIWCcRgrsCmbQlOleWIT63nQIUmmE1ay1mAhH3ldlKcpAkgK07FoD0YwJJsoMbNiauNKQRs2uythYDKBpCFYRHYC7OFY1hM/Z15STY4q6361D+mnnYxEzyDdsxNTUsMdCnVS6wu/T5adK06ZEfrL6wD4iepOUlMSzlYIjQmFxry7uDgI6AsnFcAAbrWQsClMWKyPmiRURR9R4NqjMy4GY8UGEIf6XX/OksbQsrwhxqnjM86l1Znt8q8zk7Cl7qfVIPQMXjn0w8T0XMAPIKI/hyAzwLw7495MC/7WaN/DuAvAPh9AGDmnwfwwRev520kZWIrE9gYDZThCHNTjQFx8ikg+KM7VWXtkknjWurzyOYEc0oP/ryTT5/xZoiuQiNEjHQNpZu24qI8z1E7mdS5bzxbv8QO1PLD+g0z4VFo70L8JzZTgW0tkfcm8gDgHh1ep0X24VPT5I3xRmcxjPKz51257NPlvGn5F2iFGQUtNpVtX6/Ie9Z2Il6WFwM0mhaB2OY0rBaakv9cu6ZFunGe11MsFtsNgDmCO4VPrhoS7vNQ3iDj9ZRmIT7y76Glv4N2+NovoO1K8RIAX3LMg0cvlGPm36I4YveuwHtIKAxQFTvSdQcOwTTiB79K8m4WhAN11IyTw2ZtsLr68Ph6kLQoPSNV0y0Q2tbSbHlY9EcRn4s9n8o5Zh6M0oTJT8t6u/h0NZo3Cdz5BBa7HMIc8UzUGbTa43O9R8xpT5uaaYgB0OHAEsc8vGZJmj/3T9Mq5Noia72QmcCoviOwu1NITUuFm12/AICYb0A5yMk/FimP/5U2LjSNkdaR88vp7Fp7QayOap3H1Q0cmbOLcq9Md9JLXBIRTQBewczvBuAbL/r8sQDxW0T0JwGw7L76uQBeddHCHhQacYeRVOqiabKNtkU8wGkTDiwCULgiPBiE34iAMJAqTAUXfqvf8/NWpoKCrI+IaalnOmj/WC3WgrFg7F2z6fmyZm/bM3fuaVnkzQ6Fw/RtrhEZgQdakdLt033PWiAv3u1IZO3NtN8SWRaaPAKH1H9D8GGM2YTLN0jkKU/v3/Emsxzl1a7RQjPwplBfwUPmDx9FZJoDZAtuiImpwkBjUe9DtNJXe3/7d3AkqUCnDfLbjWj+1jepj65MD712sJeYeSaiXyait2fm37zo88cCxGcC+Bdop729Bm2x3LMvWtiDRk4sNAcYHAPZMz7apBR/Q5Bc/CSEk9hpPOC4b+exMCMdogwerPlxcM4SqIGEK1NXkY7bNp6xFldPiFEZHnRMKqS+SZ/WT2a19Zs4SkFse+z0UJTI9KvWVwFSwTKbhpJGsZDMM3kg8Ze171gEhKQH23hxoKJVN4l2VCa5ez4/DOq7uMlOiBBpmHVFNHUnK2BrXlSr6YKLyzbVQ0HFxowMQvU19a05JCPxRYC5b99uQtQRzHXUF1pn/b7SHfbdA+qeIrumQQ5RU5/I+O39e7gJRxGjA+edTY8D8Ao58O0+vXjMgW/HRjG9DrJq+o6nQbRGsPc6aclzbFsZrBMxjcqFc+zIKhxOvJ7HIhsPTrWFu5JbNXpx6s7QWAjFiWSAKCSqfItuQQ/DFZBoIbuOmbjnWQCiRWOhmZgcQFg69VEoICyAItnJkcDAS+peYABEW2kOc21qWCSXhIog1Hr8dGASpH29luqx5qOwVdoGXsKcxbRjkTrkG+mCKPSKgol8DxqZ1zxSJdRRTaUBup3LUFQASUKDr772nWXmO2tJikHjG+77nr+FNqbljcA7d3gey1ekh8M6CAD/62UfPDaK6akAvh7AE5j5jxPR0wB8DDN/xWULvq0UBg7HQWLgsHzMdu0EHxxDw/2MLlNHDJhGumZaBGBSp0aZ8JEjtJshcl8AIabeHuhlm/QVbwHKwOQQIwUJ1Z4600/Mamq7bVKe/L6dHhC8g1nrKtdDXyVQWPSrRvCgS8UeXAwAnNag7Q28Gf0Z66fqpOMBOPgqmDnRtZf81ipFQ5pZfExdizChJ5mSFu/OaRcWxWZayIixtYp3kMByS5TUFs+wF76clL8XeLIA5d9fOIVvFAiwElazT3Nerf8p6GEAEIcOfNtHx0YxfSPaQrmtFPhyAB9/2UJvG3mpAu67aQuDZ8wuiTixjnnxPv+rUpaOXPXW6rvq18htHWk/Agx9MRYWtu01W+3Cv1J7WK8P9YXsnBuiy7SdctRmOGVtwuJaBgdjEso41FwlIcstUooXTMciqZyAsACWYWNdHo5JDRmZ1is/v9qHbldh907ZR6lxj56zbVZEE2LArRSGjQ0DDDee/dbz3ky6109xqF/S79V2O2FjMWZ9EjcHQp+qMBCOWl2pV9YQLMxN59YKH7gsBfTa8/cQEhG9kYjeIH83iWgmojcc8+yxPohHMvNPpSim3YVrerspx5lfiG83EctvmWyS1yg1iYqvzldal2DMTEHL7Ib29KMmgRd1+yRYqPv+mVT/DgySJGgpnYmNaGECM42ArbFZC9IvbcdXgF0UVDYxRQ1ixZzkGb6vamD+/R0aE3XvgfN3p/loHtYMX3buC10ZDvSzsQ/xB+PyXXL353oDZNuuE8ECJ0rhoQYRgie8CiOqjTqd87gYr4lJNLru3oFqJlpc0CDhPnMXpHfmAWERouwApD3j1ZY0F0K9ZTaTqhmnE/tPIRvebvJnU8spns8A8AHHPHusBvE6InoX6LAj+ssAXrv/kQeZvJawxnCBxUBfOp0PlROeHuYZUoyY5ODe0HyR7DojJ/dwgK4B1cD23Jm6cfDxw6NitE5+4V8lWQxHKH5RoJvLth7CtAZu5zPr3wbyu522FjQJZSIFQVvwgMG+TRlwPZjsa6rPL2sJBKe19GuBgR0CBdd3BhK21gW22aRqEtXOGHEnFjIttnsJ62HsncCQarF2JmvLl2B4oe+171baPNIeVvs5R68V9HVLozJ8fkBPpwti5fk1M9WFaa1d+9r6EBM3+ndo69oO0rEaxLMBPA/AuxHRawD8Ou5ApzVv2BaWLWzflghOWvWiomP21CXskVbQpESR4ooKL50ZMdG6ZOEZpStvZApZMBqmhmge0FRyskikpcgWIl0W5Y7SJVTTDeDG2dt3H9na6i6nmoU2ijYwsT3LE1k0ltnoXf1WJfBcXYrv0JuT7H0PtjdZA98grY7K0yJdsbpGxaRobZN+ajm6upoINOvYIWB2Q1Q0Ed1eRcdYODhINIAACuz2JOPUP5Q0Pat4avqI4Wp3ybwIiw11GAK2NiecDwFXxgBMqxMOmOTTCRB2nnd6r6tmQjOfunFGslX+yTg2PSyimIjo/+1+FgDvA+DmMc8eBAhZaPFZzPzhcnBQOWab2AeddNAqQ2E9YH4EEo2x6uQJDi6K+ZljM0Q79e0ozMy0Yl8Kdtd0fcSP7fc+3ZXHg3xRhX3zwCYtxWuJyRPQ+2QEtr6qDojCPk1OEswxA9pWb57Y5xsYgoUHBv08ggkGYBhItWOTVXw+mKVGVfLyB3eQ8OVDACRKnTJ+xXREKlGjM2CrhqpQFf0MErdT7GJn2pKAwrUnfA7IwMGBcN+2o98PgpjL00yTGXgJ0axEiFqmSf99PA07m1phXcCTeQvn9L+AlnyQToU1t5c+2n3fAXg1mpnpIB0ECFlo8afk+32H0j+kRH0voT4z3OwdTGRAgQA2oLzpZbT3DetD1MsJETmHq7nnZvq+lp+feMM0fnYGbhJuW1UYZm7wgDYy63pm50EBWEqLTHqWxaBtLv8RaAzNCPuuBUbYKz00TSdgWIB4Bodcf88AnQQ9fLcc/5YnqgnzMgChvkBE+0e7g7itoPflMPUzSOxMklF7qGu8Behh0q6vs8DgPo35j/4w+O7Kp/zdAYXXJsxcZyZHFs2BndlpcHb3gML25nAHKZ0yNvXhARD/X2b+UX+BiD4IwO8devBYE9PPEtGLAXw74kKL77xILW876VinLom28cH+hw2qPvG75OGlT920z+cdCiHZ6EzyDDtejsTKY+ovtGpW2UPLUL/IvNsl6ZEak2iH2cI27Jl7Hhw4pcu/C+IaE9Z+0/ITeIyY/KgzBtgX3u+h/nPMGoxumkzFLXwb2NMve+poACTgYCeqOVAgXSBXlZnpePQgq8ET5Bh421GYKlrkGCNuce/AGMzAFMOkh37bFW1C+0Pxxv+27x4wR3mNXqcHB9McWExN0g/yaeHOLp+DIa4EaNBJ3hr90uQFpDub/jcA733EtQUdCxD3om3U96HuGgO4rQBBRB+BtoJ7QkPBf7z/AURxlDQaCYjiDOz+4oAWiseNhi04oGuFe0QEFZbtr3VCjwfM0IzhaGTrDqaNfc0WCXM47nOZNkl1p0s3a90GfKsFKwA4IFlIiv63AFHboZZjXZzfxgP1smhegFDnSL5gLPpgtf+4141qrLcJmRm0LklmVnG2edvZdWVcKACzMkYxGy3capKO5vb+aO4JnPm910MXvylTBzBU44YNccV6MJAi2xYrXfgIufGyPpZIngsmJg2DLi1Qoafh5nAezPWhVqP10nIVKE5ERwsLDwHJLtx/EsBbEdHnu1uPxZEHvh27kvpTLl69q5H4Pv4PAH8OwG8D+GkiejEzv3L/g4Bn5XCqZZAQSQ5Cl6gIcjHWVKptr9zq0n0N+fSuoEWs0WgQsZug6Exkn/19mO+aXSMwVAp2b1O7/UQSx+bioPph3ePpfAvmPZJG83Wd0E4a9KYl36WsAGjMQMrUTvMS8iGSNln70u66lxII9/WV0JoGoczV8snfdZBoGYBth2LlVYqHU2lfSd9oXxkOWF+6/pOG5/2crA57/ryvitO703oOhyilv8V6GAEHixxrv/1cDSbT3IkGYDKP0efwyegOBggAN9COaNgAeIy7/gYAf/mYDI5dSf21g8uvB/AzzPxdx+RxCXo/AL8ihxOBiP4NmmNlDBCqBeSXb9cHzJc6OPT995tpqRCjlBTywtSlEELTIi4w2EYS9z4aahV2c6VonfjGWPoq3LzNcTDtKNN325aPK9U/h+1JzED5uOYZzL9ea7DjNLHY6M+kaaeBaCBCMEUN+2JUd3LtdSChdfLt0DpnHHbgGLTDNYBEv0ejvtCyeSkYs3uXzbrkOkHb4I+5zWVKX1Hxh+30tu5dhezmSjtIyB0ohA4IfthdiFTrUMe0AAMUHCa4dTB65gj6ywhSlnwkh0d3VKP5XGru+MvTnaxBuIPevpmZf+MyeVzExPRuaD4IAPhLaKGu70lEH8LMn3eZwg/QkwD8lvv92wDe3ycgomehnbWK6S3ffJHBIjLJbshbLYiaA3XTUtHjPBEn8uiwneEpbdxn0MJBN6jOquRKKeG+9F4a9AyoJubvsw6iOvqZE/soA8Oe9nWJFY7TuXaNwMGBuufYJJpgPx2uF5Y1jo5MetFxNO6g4LUHbYs+yloNyw+BIXlgyKa1pca0zNN+p/5YJdva3YEAR3AIx9gmrIimJI7XDpAHAh/FpJpD6J/VTNJ9pz10E1NfI+PXuqjw1uZs7RtGcm5kJB9kQsRtsWE5pQZxwrxuH91PRF8F4D3QeDkAgJk/dP2RRscCxNMAfBAzzwBARF8P4D8D+FNoh1A8JMTMz0Nbn4F73vlJ7HhJpwXHQtIgIL4GmLRxzCvXgbdIPWISeyRLGlxedbLuMyepCWxRfjyfWwd0ABknkQ5NSwNNadXEhH492IF51E731WkT+h6YPefpGR+y6HXzIpbvQz79ojS/kC+8k4RV7L6Hfkp9EQQCzVaaEUBihbyma5pSqATiu7Kz18f5ekxZ3uShIJTrY20yjY2so3z8h6UflZfaxXpNAKFOCECBSU6IU41BwWFyTB9sAkEGC18HKq3jvW//yjSa03cmvQDAvwXwUWg7c/81tAOEDtKxAPE4NFvW6+X3owC8hYTA3rpYXY+m1wB4svv9dnJtTMLoeSYErmuA0JluiJG+gADAgIWC+v1u7BhDH9WTpNSFtAk3aZOkuSh0DSzAsrmbnmOdtAFvgqgOKHQC+X9rdXG2a7s8AocMKpok8/hRMzI4FAWCNqm7lD3siFhh4b4WT+Y1Dn0nc/srO/STzKQcY+DVVdm2u14Waz6b5LvJ4GIb5LnrvV2DZqVrlExH3s+gbQgebH13ftWw6+PgR9B7IxSx9H2MGACoRpGZpN5LQ1Kf9WeC8Aao8ucd0xBTE23YBAYqjLKpKJMzG7kV5Rray+g71xbRPooTBvmUi9seHgDxlsz8fCL6XGd2+uljHjwWIL4SwM8R0Q+hvf4PBvAPZeHcD1ymxkfQTwN4ChG9ExowfDyAv7qWmNAYCg+5UQSEBTAoc4DsaYMuvY4Wn/U9+nUXTQ8M1KV2Tir/skpRwKX46dMav+P+s++eCquDTXTPqBQcNBSSHT/wTCLVwzoWLl9/awQOSXoeSq5HzM8eGCBSYuD0WLy/XpGEdL4Cqj3V2D+rk1yBQTo8+mwiGOQ+8ODg67nXnJiTj8YB3DgTYLOzz3nwrA4Wctcc8PcMU7vWSIccpde4rx99nSh+X9tI0c44R48mpIlRJsZUqo0PLnJuFtrGhdHH1QUN/au1LA+zugLdyT4IR1v5fC0R/U8AfgfAWxzz4LFRTM8nopegOY4B4DnM/Dvy/QsvUtNjiZl3RPTZAL4XzVX1L5n5FXsfOkIiylto2NGh0OSlDb6iTErrQ+4P7UxqfdZL64BjzP27TryFrVof8RNk2CGujfLbQIIHnIERz4sWkKCZwvNLZhEZ+4VMrLltx0jGSZK2HWbhQEK/o38H0E0KCRPW6kXcwYH8+0hpCXD2frlMaFteuHof815NW0xtN9v7EbQw+3lN1QkiQTPVAv271Xtunhy1RbY1YFy30IeDfsjAkFdKe/AN/SISv5qAS2ngsJk6QMyVgFqab564O6G9QAgdV3LtlH6D0dYtdx59BRG9GYAvQFv/8FgAf/OYB4/atkp2APwwAO8pUUsbInq/A49dmZj5Jcz8VGZ+F2Z+7sF62rqFKBGZdK3pHCPuWyEX8FxQZ9n8DJ0BNa0CbtvlBg51lpGue/nrRHXAsMaEwkTK43Xf+PVO74EUqyYlDw7kwEFNLGEjPTnIPdvTR/Xw3Rvmmbs+0ibijdymPe31jyt4UPy92KbcZ23SNoV3MmTmrj4qmY/CfhfmQp+fVm90D3t4E/VIndV0yj3dew71dHUdmn2knM6Q2X6vkvaffV9Ls/J6HSBFTaEDRNDMXFPV3EiFUaaKMjVwONvM2EwV01QxaUCJRB+2ZxCiEW1tE6XFr1ckL2Qc+tubD9GTiegHieiVRPQKIvrcdP8LiIiJ6PHym4joa4noV4jo5US0uuBNlgs8hZlfz8y/yMwfwsx/gplffEwbj93X8OsAfCCAT5Dfb0Rbo3DnkEqfPkYacJJ9OlQFEE1AGPxO/uaCOhdn2yymOdTaVqzWmVB3ReLPdf1A1CCo7mHkK/VfkyozU1oydMc05HeQOtXuniN35ng9mCkuKWTp8wEksnkD7t4eWkSGBQ3xiDqqpO0ilYJWN3wm/WVH9ggQBoC4BkJaLW/2Wbzz/HsgCPQx0YWSobCQ8/Vaqte8bAwdfvEjjWmh5SC2b6Eh5L9BIVSaWWma+rqkaarYlPZ3VmaUIiAh6Vvaar4HFSCK+ywnNDGFBu772087AF/AzO+Otg33s4no3YEGHgD+PIDfdOk/EsBT5O9ZaIe5javXAos+Ye3+ITrWB/H+zPzeRPSzUugfEtGNyxZ6u6gUbqdhuv3ymdFs74Tm+KpN7Sb0CcGyPTWg/LdgLo2bmK1TD2uZizFpBRdzEO6bpGnyHKvpBpCRz/6ctIVh5hd7hjtoBX+IryO5+hHanjfyPdiDgUWIbKhbKtco3R9LxWstH98PK9vVEM7o5igHkqx9IICqbfD1Nodr4plB6neg59twlCCq/WwPpT9Xj8hAW+bdOe2keP307ZVr2hQ/DjW/yJgPoXMvzyRhA0lfcSzrkEDCtAf/O4O9b5tLZ2HnxE17KDNubHZiXiqYmMGsTL/2MQEYKKiWsWjbKegEWMPMr4Ucn8DMbySiV6GF+b8SwNcA+NsAvss98gwA38rtOMmfIKI3J6K3lXxG9KNE9L+jRTL5rZJedqhuxwLEVlQVBgAieivcodY3NR+Zs1r9C9DJ0zdGY2XqMwG7lo6YgMKouyLSR7te59IipFTj8BujeYasp6ulSWPE+8GhMXso72+UYtuNnzFAkDOEXf6aT5A4EzjYXkDF5cuuqsl23etPCyDYJy33RPrHoZ4j8uGKdpaySIPBB0MczIDwoG+gTfFEOw+ICg6Evg33qOpy354n148uv96A1G733QNB7Be4E9O0jxyguboHE1fScLjI+BiBczAvxZvDFdR+/JqwQaEvgykl8WCrh185rtlmwXohCMBMS5OsSZrUxFRmGxfb2ubpZppRqbQT9uYieTRw8GshmGE7JJyCLpDV44noZ9zv50mYfsyP6B0BvBeAnySiZwB4DTP/fDqsbbRG7ElYP6Pn6fL5Ze4aI26dNKRjAeJrAbwIwFsT0XPRlml/yZHPPrhEDB0Nujd/XF3aHFpeM6DqNAgGUEqLjih9YLUDWzpI6N43mndkyFGaz4AxNLdIWjvRbkUiM2BIjI1TPnDaQ3DMurDMIFF6nuQmL5N75oLzyoNdYErWR9wBVipgG/sBgfkvggv6I7FzOJn8NMQ319+13QmdwzYyYFrGqFztK2ueA3KTTPyff47QF4fJ96DZaUJff/cuh5sNlv78QlLPDTxWml4Bha6huj+Xtb2vfcbs3OeSeZmqaQ5EjLMy42yacWOasavt0CSglzFN1QKUaiXzN6hzm5lQ0Y5sPRkdPydex8zvsy8BET0awHcA+Dw0s9Nz0MxLVyJm/pDLPntsFNMLiOilaI5qAvCxzPyqyxZ6u8j2xTeuBPMTEKPvYFr0OEyKk0vMMJUIXAgVxXwarPmoFjGjRwQhPu8n0mjijCvv06nI2vM16VEmuQmuFU0rytJYAqXAXJThy2+7NWBiwb5+TDvccx5kssRoZjELE1O0k5+uzSMbtZ1BgGhaMnDQXU1nNw4ck/V12ru8YgTiCVCtbdrvSVJ2is0CLO27Xz2sY2kIgMI/Z+d70HUQ6PeHrym9W8t2NE7sJgVAsDHl1394zdT3m4CjrYfYM3ai9tr6oaij2UUv3TPtcKPMAIC5dtSZSkUBo0J9jV2LuG3ECFrTVYiIztDA4QXM/J1E9D8AeCcAqj28HYCXSXDQhdaIEdETAPxDAE9k5o8U/8YHMvPzD9VrL0AQkY+V/T0A/9rfY+Y/OFTAg0YMzLsm4bM4nWlbQFsC7YRxE6HObaFM2wSMRdJU5i/S5rZFM/G9hKqbgzE1M9S2axw0ozNNmQAWMeQmkP6taQ42saq7L2Jtlt4bQyFLoqaXYd4DkFqsg4B7To9jDEfDxTatrdZVJmig4xihHvaildatv41BV9hhQs3cQamMeEZHv0ymBZovaVeAnQv7rBTeBbifH14n4ccKEh4Mffv1EvffdtufdOb6ZsFndXFYkui5AHwm/b5R8bczHi+lK9iVnfzWz1nep4JMfi85cMNVsGuqtBQGLBCCemScAkKVeuzaZ1RhXTt1UFS71aqRgE37kAuAiUESpXS2aRrD2TTj3s0Wj9xscaPM2HEEh7PSTFGmHewQghw0JHY3l7YW4lR0AvyRKNHnA3gVM381ADDzLwB4a5fm1QDeh5lfJ0cvfLbsT/f+AF6/x/8AAN8M4JsAfLH8/i9o/oirAQSAl6K/4rcH8Ify/c3RvOrvdKiAB4uY0cBhbtFFtJO/mWQAO3VUB+wGwUTUJLPGEHmDBjIMsKQjdXYKM28AESXdsHo6MVXq1TBqZiUE6dAz2iylkN30n9S/lw4Wqzb1ASPcq3Vb/cZbcXgTjQfLXqCrK/cHCNz8Ocp9VYvA4Pm9RAZk0KgsOxfB1XfQSO+HCAxt38TPdSs9a9vKO9c7aQ5+zJhpSa8HJ3BXR7y2oIzZwltdeauaigc4Nd/lsaLlJ+HCtIcUWrtYQZ7L1a+5T/0zWqTtvYSgOejfjWnGJm+gqU0Xh3TD4WUoa+UWkVhrOamJ6UQKygcBeCaAXyCin5Nrz2Hml6ykfwmA/xHArwC4H8CnHMj/8cz8QiL6IgC6xmw+pmJ7AYKZ3wkAiOgbAbxIK0xEHwngY48p4MGk7CPQCeXXBBQCamkTwOaol6JmNOa1A2gjpz/o4DZJtG9bkRcoLZzTWYIvcZ6A4kRUK4vVbcX+b0xZtQgoE6C422U2Vfi6JaAZzZvODGhcl1G9NO8s0XLPUzUhQ0TPmNVpKkkADr6JUFl5L2xaXdTuFsAwAi7q/Rnqv2/yK2OfZA8hCrdaUSNB1fVBazOnh9wl966okmkMWXI37cG3R5ltfqccGxYEDu0r9a0pMLgouOB38CCxr59i98S+GIAtXORSQf/cUDcj7WpBlVy9ptAXxMECUXQszbX5H0661cYJiJl/BAfEIGZ+R/edATz7AkXcR0RvCeltIvoA9G2T9tKxTuoPYOZPdxX8HiL6ygtU8EEg6j6C9Fm8KQgtigmTDK50cItNAGUycBMvTFgn0bFj2FhKWGaWIQcAWZJE/J0dkjltZmJBEgbAXqvwz6QuWzN7WdocteIjqvaQNzH5gk0K1XsFbtsSNulVOXVr5gq3Zlj4sb3vKqZC1SASplDqL61n92nE/tG0a9qAmZikPh380BeG6T0vTGTGqH3qx6HeFlDQvaPKFraGZVFXBxSLehsoZTTjRTpvolsIOenT8vZt0e9r48TlIdNSzpvmvshNopf8WgZAtAH5Y/mca7H7RdJ2f4SAQy222PVkdGAe3CH0+QBeDOBdiOhHAbwVTnkeBIDfIaIvAfB/ye9PRNvP484hRg89zc47NzExA7RTTt1G8EhNtOcI/ZB4Z2JZSFQLScxNoDSZLBQR6F80nbbFMbO9TNlJv+AOeIcE4JxHoCxxqySZ67NCQZJ1IORNFNrGxoBkLYea+zREVX0Xmp4VLNAXOTL1QAS1y6vPCYiAwINrXoMgV69D/eTAQTUF9TNZng4gFu/Qv5wAwB6VpL92FIChbBPYkMsul+363iTnrLUswCFuHx7+0js8hkbOdqJ4Xf0kunurNxF5YNhxMXCYa8EsC1rnQigS8mp5it/BL3St9YQahBeY7mBi5pcR0Z8B8K5ob/uXmXl74DEAxwPEJwD4+2ihrgzgP+EKq/NuF5FjFEGaTEy8iAOrEjdNInNTZYgVYCKxK3OPVMoStZOegplpkMYwxIGE+iG8NLWQ0rxU6cBoweRqz38hPYbOSp+evPTKy/YE08BaPisSbPPzUH9GAgW4OqZgi/L03bA9b13gFyru5L3vnMaYJi7luvh6FkQ/xL4uUdDzO5JO6HH+XnovEZh8v3nABTwwIKw1KLsGCOW8/ek2KWE8lJjX8L379BoGTloRqST3clFdEIYzL66Cw9o4ysLPsFN7n+nW3rb/EjEqEyZCc0xXmOagOx3MlcT/0NctKdVaWvEOHN7UdnMlonsBfBba8QwM4D8T0Tcw881Dzx4b5voHAD73SrW83aQD2Um73gxkE1MnMaMNJlpuZmZat0x6W5GbmHWwx+qzK2PPgEHytMgdJJDQtuinyz9MTM+YnQTMU08zMk2FLhvU1UDKEiGAIrn66P2Qj/I5vwmbr0Pt0j1I+kMYj9l5nKRrkUfqg1Cs0JXRKRhBzTCLto46QIrzAKtNYP/FgbGBnpxfMIwccv0QLjkmbfXhLoAAMs6cxF62hLIFplvAtG39VLzpUzNLAk4u15g/ubIY8axw86tFM53ft2sxBhOo5vedgTCYlRZ92m6OzmSZuWBXi20OpOsZ5to0Cezae9RwV6CbosDALPumnRIgFF8fBvStaNsj/W/y+68C+FcA/sqhBw+FuX4pM3/pVdM8aKTMRh1tnsHqwFTJurSBXzX2HP06lMHUxpSoSFgsep6ZievjYbwMJDmiVk+/mMnX0zNbcnVHmmjGzErnYax5OYFwjXKEi0q6bimC1WkRqeIZnQNUlZpz+81Ho+1RRlMg5gzuW6AoEAvfUt9Eq1uXssEE3rkw5l1jppSla1dH9vUi12/C5Mld9+mQn3NrFliOxMSA6QTf1Ujq1v7VaDi4vt41TaicN3Ao225aCm2i+F4WUnvt/WZaDlMPZdax6LaN8Wa6pvE5gHDCQXjfAxAABnXzlDWuAeAAkAVuwHae7NpcC2bRIKqsnJ7ntsB0M9W+9Tejm5XW6nEVengAxB+XfZ6UfpCIxkc3JzqkQfx1InrDnvuEdk7Dlx5T2G0nz8TQpZdg4qluUgFy/GDfSZMLxbQg+MN4bNKsTPiRqcW+yjMa88/uuWCicGk9QOj1YFbiJOhqGa4+QYrT5iWpedEOy4vipBr0cTYnZb+DSf9pGxJr2ywrpSUD8vUf9DGzrHPZEcq2oJyTOW29tqjt9f2TtR0Gln4IIDJ3pGsOJMz/MKirb8dQ0vQA4bXE2rSGMgPTTdEebknUktZjilkRHAMnZeR2koZpEboti22dXjw4w8LDLYQWvY6LNTDU2+/HRegLFThyH4xAIWsj3JzLikIsR4XqegfzK8wFzMCOGBvIGkkZJ7r7so2bhd3zCrT2Xu88ehkRfQAz/wQAENH7A/iZA88AOAwQ3wjgMUekeeiJAfJS0GK9giQrfXEUqElLTARsZLuDicMEodrUWVvZ7A7dWTB0qYdqKRVNUOPRSlcPCo55R7t0ksD0utsmWSXgoZqP+JzeM6l5MCl7PakzsOyMZywkSdVkwvwL6SQ/cbLau9gBIOqr3Knn1747JGWAZU8sulkwPVAwPdCZaVgP4BjQwh8D91uZSQEwDRQBD6xqUpr6n3WAB3LXbmPceTEZS523bUzZeJS0083WT5ubwHTOzW8maeYbtGiTRjrxto+3BmBk5QEATwTesI1fBjVlggnlVtdays71J/q4tLHl1n7YGM7byI+YpwfXTTPTVdXC3DivlbBTjUE0+qkw6oYwccX5PGG7mzDvJszbAiptaw0f8jpXtzOzvlg1TZ6KHh4A8ScA/BgR/ab8fnsAv0xEvwCAmflpaw8eWgfxD05Xx9tNSYX0DE3JM2fAHMPKg7wtVJ3TAMwswkmi1GJHVbFP/+c1DFeuSf4+i5E0ps3cMyiNKSZGvUgzqrvZmcjKHjrkB3XKtKZhZTOFSdCSiUaxLJsoIFLV30Ao52KfP4eZrcw5rP6dFV4QTHmQ9Gquc4BkCZSxKUik9ziM1KkIbV74DBjmL7Hq1NaezS0BinPupiUfUkv9dVmeah4qwtuTP8rGBjuBR8e4AHcACI5lmTbm+1T6JQhAFWM/kDPlekd/z7RNCHUoz6IZ2PNTxURt+/3dXLCbi23KyLWBCgjBvBTHaxvX++bPRenhEMUE4CMu++CxUUwPC/KLuZT22eEXTE4XmJX+kJmF1Ezi0+/L2k0mtdJkDcHnb/VJRYyipIbkJeV9WvQIHNjP0Q4Ovo7BSa31XNNaXL5AYxbGzARsrQ5ey6D2j6XwZZ66nQaBth0cyrbnacxx3/tJkq85+PVT2hy0DG9Scv3rw019u0P/qQapz2g/zD29Xqe5m5QaQAA0S3+UPY2SMssOXUtWzUjL0Pqn8UZq0tq25yeJljJZQTS6vCBw1KemMWXG2fm/tGUJtHo6HpjBtaBWRuVoS9tM7fpunjDLugYoeMqztbrzW7xZScDH76F2ZXoYaBDM/BtE9Di0/Zs27vrLDj179wCEDbClRBckHJc+R1NYRNM+BuuzIJcsS516P+UXxpMyIZ2oKUEwL2WpjdY/sw8g1Idd+pxfLje1a2Hu0npl0HHAADSp15I4Sd/8Q54R535PUreulNboHmVqWhcNhoJqIQMpmHOd9Vpx/ZPNVU7aXaxvGIG+Aw6/piY0y2uo8tsilm5xk+p37dP8Vv59IH1XbUTSVQGFRd3879qjv6ZziLM/AcTkgsxU8MljMo2PUUCFSyorptNF0QSotEO5gMkyImLM1LQGAG1PpbnvwwU05s+lL6BjBRAxAfoFlSehJNDdqUREXw7gkwH8KuLs/dBDz949AAGVXCi+OB+GuPIyA+MAFpKxB4/RituFSWKQt5qGFkNTmQgSiA2kUgMZDzqOeY00CNVcTHs5NDdGAKXXEwPIIOPJ4vUhfDA5c43JmBQ7YIKedK2EhF+SC2lVH5NFImke+X36PvPMenDdM3OvPVjEk6s30IEvaFr+nkYLaZ5eIJA609yY9HSLG7Ou3ExGHJ/Nwo2Woe9YndgFIvX7tntGrnVTs9K5mJgEdG28K/gSwlwyE+kBJhmCDvI4kXdlWkcl8NxeQLWKw9ZFbKk1qMrJj/bCpE21EojUeT0Ahx2d1AfxMHFSfxyAd2Hm84s+OIrgXhARPZWI/iMR/aL8fpqsrL5zSCdk0iDU1tnCEXGYQWp2OqG8KixAYfdd2QvzS8prEbGB5fPRXuooaQfhdxl/9hAuV17KYyhRa19y/LSqeOkwM1ZyxRozF8flYPFaflerjk2VLHWfJb+baTo2VaX1LMX69od+RRIMsmbhgdc9o/W3envHrP9z1/KKZOujnUQsiclsOgeK+B7KvIKYru/0HZW5b8mhQRarTmMZCOZ7yH87xrRl02BUo8ghzwutMo9VpD5HusaxT8yJXMkCEvSvzgXzXLATx7Qe+2vrKLlpFLMeGzwvNQdbSHkqGs3dQ/P5wadfRNtg9cJ0rAbxjQC+EMD/CQDM/HIi+jYAX3GZQm8HNfstLZkawRaPMfVVqAvKUrGXlgQogC5V+ee0/MVgyKBAK2WneoyYUQAGBQG3psM7Zz3jI82QUt4+37V6uLYNHbGpbt7P4PcKMlOc789cjlYzS8f2PvsE132yhrH5peM4o9eLR32pddF3zVJH13Z2/ZuFAmOYjgGvahIZaOWfajyk5qVzRtkyyszdsT2QunU8hz5SJivXyfc3xXpZXR1ATGJamra9bPssAE2SZ77n2sXofZm1HKu7a4Ot61BHXW2aAs+6yWQrgEGocwXzBDAaODBF7GTYegc7a152VPAr7U95FubDRIP4RwB+VgT8W3qRmT/m0IPHAsQjmfmn0jL23YWqmIiIvgrARwM4R7ONfQoz/3c5cu9VAH5Zkv4EM3/mUXl6aS0xam87XY08UEc0ow3KQsI8DoyCgcTgo0aChL1Wdy+BIT6jRfjVu/Aag2pIxux6fa1cz8CRylppE+V2jZIN8vDSMYAelbQHjIIZwn8CfWfRmaJW4pmvlssYm6hGmtIgTejvlecCKHkJeO6/UTtQeUa4KM+BSNk2cJjOGTTL1i6Fll0/eicGTgzd/l3NTnmltzrDUd1WHttWftfIZL1EIRSdC9ouBQk1tXlyEWjedGSgpl0p98w/qO3R/biAHjlIOj4KeG458E4Ahe2mrOcAGA4c7IAvtwjwVAAhoPwwoG8B8E8A/AIuWONjAeJ1RPQu0HlO9Jexfv7psfT9AL5I9ib/JwC+CMDfkXu/ysxPv1BuXoLKt3RyO+nQ+w10gjYm3BI3SZSX0vGgXC8tDpM4YNAJomA1BA1l/HCJ0YHBm71CdE3hJRNkV/8jNJisKQz9EPvIS6fKENQRzb0/tJ3+OesTbomN2XvpXNehJGCAPTtq1Eo9aZnG3pX7HdLV+L6D2ShrCqkvRnVTyb/MjElXS8+MMms39IquaXu9Ptw/bQ+x0PVxnnD3N+hnW0/BXbKfWl5VzFU8IWwX4+tlWi1jEWJrIFlSn7GbWzYPVQVCDziw/iO3N5RoF7q4VRtZ0Q+PklXqRTbptPFzAjokb9xBdD8zf+1lHjwWIJ4N4HkA3o2IXgPg1wH8L5cpUImZv8/9/Akcuf3sPvL74wOwCIwgxQNBAjM7sOxJo2NwtFVz+6Q40Z12AnQGazwiMRwrH45hs8tLF5wlTUFNZbbHkZq8JqBuAJaFfnB5dq2ElyGSmVk5oIObvGEF7RqDc+310rRJsK48NVcM85B75tTlBgjKjDS01cxLozYkZhz8R76dCSw9c2PEvH1EmIKT2bFrbLMCHbTv3Bgb9R1VNmf7dIuxuVVB21Z4c553gSWMy/Q6PdNVH5SGfZsGoSYl7n6h6Wb729xSzaUDBBOanYBld3wiE0Yq0E2GOha9Nit1KdQAJYCqvueCBiSU+niG23kWYHIr7ZnS+yXQhvsYkzFjYGBHzwJl5zYgPBWdMq/bR/+ZiP4R2pbf3sT0skMPHrtZ368B+HAiehSAwsxvvGxNV+hT0Y7AU3onIvpZAG8A8CXM/J9HDxHRswA8CwA2b/a4heoPN5lMGkf/7aUWL+UyDdKoZOsZb6gM4mBJ0u0iuWeqHtC0bOdY9z4HAwZJV6cm5TUgZOcH6EAWQErrSf1voU15sPBgugIS/lnf9kX/6O2B5G6MVd9FFTAmmfxp6+mLTsyF9O1AeVhHvZTft4JDTe1NfRP8EFmDkHdAzN0PMHe/g40Hy6yJ0l6bXfpD+oAyzcu/N4qAb6a6HaIj2vpYTEzUGCtPQK2yVxYac2fRCPx4sq1H5FnbKh97+sP1mZqJrA90F2XJxOah/qgCQKU9q2M/Hxyl4HAy85Kr88OA3ks+P8BdY1w1zJWIPn/leitBzk/d8/wPAHibwa0vZubvkjRfjCanvEDuvRbA2zPz7xPRnwDw74joPZj5DTkTZn4emmaDe5/4ZDbTA+IAXKyqdcw8TKZKfcl/UHspAg9cPl7yHGgo+xhrllLVZGTagtvaIdjCPZAIONi5w1KUj1m3Cczumu8PX5/E9IJ5wLfFAw3iMzHT2Mb8e2GeY/RV0RVAcRKj2xL7IGVAWKM99V0wMMdc8zGf4XH/7oNfLHF+E06UQTMwM6h2jS+Yb0SaXsQeemHEvxPt11wf9BDhvqUMu08G7VqmVGT/Jg0v9mstRmNAOsF8Cx7MXD393ygi0LLK9tkw/wiYWHwM6GfHp4OjgkYLHDd+jqWHAUAw84dc9tlDGoTuw/SuAN4XTUUBmnP5p46o2Ifvu09EnwzgowB8mByjB2a+BVGDmPmlRPSrAJ6KA5tLBenTSU1qnhgulkNPa4M5M8gstfoJmz4Nf4yhYf8A8hKlfAY/gwOJABDQayzpuP9GA7QmeVEo3xz1a/VYMLTxpz1DMS33Klh9VeBbC6n1z6g93qTAyh3UkpnCSIEw9+WIho0/Iq0bIwoOwXyWH3X17H+8SBx8GHNn0K3TGPHchsE48H1xoF02xvX7HNtCUmaODGNmlAJUCQ+tTtNe607zGw/et9V1+KADWKt4n2MjLUzttGwqS39PuiPuUMA5Bbk+vZOJiJ4A4B8CeCIzfyQRvTuAD2Tm5x969qi9mIjoPwF4bzUtEdGXAvgPV6z0RwD42wD+DDPf766/FYA/YOaZiN4ZwFMA/NrBDN1kCwAxo9k6GUir9jtV97wydkhetTtFiRFUaCuaEM6ZGJkcvElnzbzhF7zVpEF07YGtTDjtAqXPWM8wPXCNflvxrr4LE5NjGIE5Z+kvlRParLQi/WbNRbdi174N0TC+jNAIx5RG9+HqMmASgRH5R/z4CAwV3Uekefs+9L4bju/Et9U0k52amHQPVgBE9v6ZKIAE5ffl+mDo82K0+QBYJJiZtczXxIBbe6FgXea2hQXVvk/Z2nw6yuySxlHQdBD7itI7M62D0Feoz2RRVao9BFNgHtOnolPmdfvomwF8E4Avlt//Bc2kfzWAcPQEtHBUpXO5dhX63wHcA+D7xWSl4awfDODLiEh32PlMObDoIC0AQq+nePCowiIO0Or2XErgoGUcDJfcJ6l4lTtd804+YwrqY8iStzktuZmXPOM1o7PUgdw1x9SD5J4nkGeI+Z6vi2PsoVkZHDzzTtJv1gx0awlUEuDl7lNJ/aoMJHT1qI9deq1eqL/vOm2PlzzNL+L6Ym0MpOcoxd1mxm5mncqLtMEn5TUIX/8MmgIm3vbPkLrIM+qkzhpj8EFpfrUNGhIfhApcq32Q8hvSQKtQn5OpngS0Dctdv0njw+FRINDENk+bZkTL97VvXl6S7mQfBBFtmHkH4PHM/EIi+iIAkMjRo5YLHgsQ3wrgp4joRfL7Y9Fiay9NzPz/Wrn+HQC+4zJ57tUggIXkFQvuzzMoMgf9DsTtIHI+XsLJE8gxx7xdh/keFBy8H2LEGLw2IZpEECETY46d1Ouqpptc9xyyGXw7QDTDecB1VbCFZ7kuvj/8z8yYhYk1B/1yE8bQFtUYFGBzWVqeu8ZaZhIYjHx9RiDp0i3AJgHtKhk4OEam7yOsa6HldiquPmq+Wpjx3LsmwPaXihqDbxsv6qtj2fuiDChycjfmrS17+sBre33OkP1ubaLhwtQAFJA5q++yunUyzmdiY/yUZqE7GCDQ3ADvDeA+InpL6NQg+gAArz8mg2OjmJ5LRN8D4E/LpU9h5p+9eH1vI8nACIwNaHvSzG6HTydpZ8mCCRaauJA43ODyjDUwDkRwWEwgin8a4h40h5L/XPiq46ZmRtm3iM8apR/KRVz7te9SHwbJWftS25gldp+Xa2uOuDLmnEE69Z/WwUdf5X5WgGGJptF0C2DwJH1lNnKNesmU3vuqacIjXHp2JD2HdmsaXZQ2dw2CJWoJhQwcuFAPZKBUrO8TDxJ6mTsgLrREBYYV8qAataJxn9iYH/XDSFBIz+Y2meLrgCS0V9+hOzlLV0sPw6F1TJ+I7mQNAr2XPx/Nf/wuRPSjAN4KRy4rOAogiOjtAbwOwIv8NWb+zQtV9zZT8eYg/+JINi5TCSMNTpOSKhCOHHWgYBqEzF3LYyGFwQZhjhgi+bTQwBS+qn4HALbwzYfqemDQdg0paSv7yJt3rJ3enFL7PaXhnNB+ZdfepLllE9MwD7jylflr+gEIeW1l4ffwYDzSILwWM6hPYG5pPC20iJr6cJFZfManXWhHMi5GmwSGtS6IzJdF21BByK+gzhL0yPRlzbF+k85K29+bAFQB0m1sXB+NtFDLF1iuTUFMl+ubASW8E7vXX+ziXeR8TwUQozF5Z9FbuUjUFwF4CVpH3QLw4QBefiiDY01M/wG9Kx4B4J3QtsJ4j4vU9naSlzwXAKHSvjL+JGGBHEP3g9JNKJO2HMNZMFUHEn7CxIqim0AcQFTndwgrpUfg4CRxI/8jMDNxKqZ7Iwk5xMfP/d6CgY0ANjNNr2WMmLZ7NtQDCGshdOuGkYYyAoAARGvpQ+EOJfZNdv98ZjhA77+BWYWpnbttz1p/c9AedJwyETCJ9uAXTK4skvN19AvqstS9kPoXfaqDGn1hZcqrNyq1Ra7Z9Mk+Gzd2FyYw7T9fL47jaiHo6DgevRNvPssAsQbglyDC6fK6TTQBeDSWI+aRx2ZwrInpf/C/iei9AXzWsYU8KMR958qFSYhhYa5VtgsgN5mg0Q6a12Awkp8IPg2nwShlNpWlS3FB0ss+Bu+Qds7n4e6znvlppnsGaYgC0cVmCqbaR9JvZQvbWZQcQARmpz6YPLmz85562zm3wwNS0lT0XiGn8Y36UPKvpfM1v/2IgezIVKd1ANDtfJ3PEDpQW/21vhQB1Byj3qQh4yFokCCT2NW/0vc/6ltb1E1BPSPMZ4S66Z9VF01S7/+ujVLvj03s++ZT6wy8a7uea7ZDmtozZFyBRYto2i21FfsOdAKz9Yyc032tr/hV6sbtKabvldFXXMPloa9nDRh1DLvfVLHYCn7hbzkVnTKv09NrmfnLrpLBpc6DYOaXycHXdxTliAzIzzBhCY2hqhSemY/OphFD0zy9dpGl31yn0XWVygY+B7WTL0FKOYNjYGuhOplcXYM2lBib34XVnHsefKTdvklBytOi8oR2Ur7m6TWvUaRJ2FRxRSMwM5aAE8OBQwDS9Of6xBoB2/e2fUp+5rPy79tpm+T6daS9rvlbetSSY9jmiyI5O7qDnh8PwQeRBQ63qFJBM0jRa5qSBxzJvUdQqSZDw7lhPg5gsY5Ib4yAe5/pyI9Tb9bdN+RtTOtCxhrzyRGJp6A1M90dQkcyiHU61gfx+e5nQfOM/85VC78txPGTALNje2e17YHmJ74+lwZinvR5gI2Ywmr1bNIhSLxhs72VfBaS+0r5o2GRJT4/WfR6mZsfJzj3vNSOVI5VNBbNrq4Lp6n2d7a/+7J4+Ue5AK3TGhC576vvQ4UE6SBzXANdU/L1Afz6tWVdU74+SfD1sAPluSNuW+fQwKFu0KOXBuPA2o8GkmHtjKtH0OwyWGn9lHkLyuqRr7q9RwMeCmPW18Vbz8hdX+QfBKH0XpLAFTRyNycXpiY3roITfQAOIaz3FJTf+51HH3bVDI7VIB7jvu/QfBKXCkW9beRelo1vWXBkg1cdnmoCSkzJBqcISkPpDxjjMsXvI6bk/Qve/7BgbJKHMSjNP2kRi3oNfnfnOfWJp1JWmjjh+xzbbtuVuPy95BiKXWHI9l5W/DaWj0qOnPrA9SOl/tbri9XGuS7cr3O63Zgt29kE9rpdvymDC4EKa0xiJK0H4GPrE10Ex2JO4on6GdCeCbq82Y3hsLBSE4mmbOZUOCGDuskL6PftXGjfl4XMJKRhxwHw/bzL1/W3mAP9DgFD4HPg4OdjeG8rwLIACD+nPWickE5qrjoxHbt+bB8dCxCvZOZv9xeI6K8A+PaV9HcMBZDwjEclq5HkkhjfgvJNx6BGzMmbOqLGACdlp5E25F5ugqfki8cV3PQshWzv9yalfM/tW2Nhl7k87U+tm7ZPJe/MIHw7vGlJJzWW6fbmo5VIGoW/PnSspr4L5hpo37K0Xa4pYJSeR4gS8+/X18N/lS/dpOTemY4TH9JqQKc3l+208QZEc2UaN+TrV2K53XzTtmeJYNt+RFMoRUFmT9+GOq6ZVLUOSVALDnU39oegDx3r7jMJIB5ATin13+FO6itTOZwEQDur4ZhrdwR1Ru1Gkh8Y+dPd14FU5C9MaLjxmQZaAAc38M1EkJ2ma1JumhiLicIUmEvUEPof6dGNDhwCUPiDd7zWYG2WyBr97oF0T111guaJHkwse5zTo8m7MKFpf6dmt8TL5+ODg0v5XXhJVxzccE5ubz83QMjvewBSnQn2Slj9C/XIpU1q04hparm+nlP/C5pqGne9bhTq3TSF9tf8IN2hbNddnh70hn3rxz25+ritY/x7HI13SmMGeeyk60hCh/e13RaT0GJ+rvw9TOnQbq4fCeB/BPAkIvpad+uxuOKJcreNnMDVxhz165l50PKnMTifxEmq5mh1QrWXkuzT12UAHh5ENJFt8eFCRdS0o21qDaMuUdmNQVeYlkB9YrnoG92rpjjwWIATEBiVfapkyvGWaQOM6LCEm+gp2mdYlitnbZKZ9D8CBclzYa7SOg+eCWV75lx7t1s6J33be/VlaP39exrVX8HBpGyKYOXrIO3Nmmr3E6Cvo5H3EPY30jI45rkwtxpgwExf/lyS0F/7ANnLLH7reg8yltng8cF7p5V3txBS8r3bQaOy7jI6ZGL6HbRdVD8GwEvd9TcC+Ju3q1KXpjRwvFSSJ//Q/ICePkhp3CeDTVAdqHmy+oGfGIrdz+UHpIkN8KfaZT69eN43UUBAtyrP0UoBHBbMmuPA1/7wUl6N7bMuYamO2r+9vwcDqW9lknmmruWbtG6Jep2s+/y78+BQWyhneH85v1CB9D3V0Uxp2rbiGK6WrV/9uAHQw0qbtqB9axK603zbNhoU/TGSPo85dqGjVt/q6qZ+pNBHOsBj21g2CfRjdq2vFtqbG9/e75bX+VjfJKa/AIYjGf4IUG679P6mDBDM/PMAfp6IXiCbPt25RINB7CcVMDQBLCZ/lmiBxcTIgLOYqD7yZCB1LrQHOCbp60JoUTVyRoUBBcd8c8TIAhy8xJ6Yczg9LknymXHrBAw+HF8fQvRLuLSWR9okbjGpR8CdACqkWwF7/96NOaoU7u30WSLdJxFrv7j3TR4onSO4vbvUn3DjQI7urCAbTwsfAsc/BVt2+eRxlwHCdjIuWAZneMDy2oOMUXWS25hNfbwg/y5IkhREB3c2dWlV1hhtFiD2AftKnQ4KA5ckwp563yV0yMT0Qmb+OAA/S7TsCmZ+2m2r2SWonmEJFIlB2eB0A5WAoZS4oMFAs7x00jspLtQj1ctZkSKjzEyZYM5Cm6SWp5OI3S11Ttt2x7YoC+EYzLydRpfEneaijEa3oK6yVINiO835qeDoAU9+LzSZBEgKNr5vGPH9ZSZkn15rqGibNBLsjKEyozmbC8Dg4FxmDPLR7yOpVNsL9C2vZ/cYOeBYeZYnsoWA2j6TsLUdCnSV7RmwjAkv3fsIJt//JIqc9qsKAgTbIiPvV2TjODmRkeq11i/Z9KU+hzqhaUvAQtMhlv7zQo9rw0K7Dy8tjn97Huhnvms/nRggWmF3N0IcMjF9rnx+1O2uyJVJB7Z+d9KcmgFsrCUnMUMGETvp0OWL0Xf9nSZEdnhmZ9xioqH/Htk0jUFSm8xRSyIn0cYZM1rnQO531hzco9JPpCXEJifJHNKfumrc3w/Sb66HmrRSn6gpzezk/ruAx1Bjcl2gfWZag0rPyrghETuD4kPHa56DPspaqPfHhE/H6HUcEHR8tkEXbPFiXrK+9UBWYn57WZOOO30nymw139T/dl+ZqdMgslYeTH+pzMXYVw0inafu5+RaQ/Td+nc80mxDm31+vt/2lHNpSsLn3UhZcQzEzK+Vr5/FzL/h/3CHbbXBkIG3aZEXvGkaRT1zv0eSlpNaMlP3TD9Iq1g+NzJdBbVfImG6LafXfahFJMYaDjUahKZCo5bcdho5+iNHeoRJvsIAW8y7MC3WcwtinUbMVDErRN8MHNMjBpz7Ze3+XvLPemC0a24L8ZrSjerGhEMMxoaGa+uoj02QUKd0cX/U8wigyrC+H46RAcPODNqvQbC54KR7ntpaBS7xvkYz2W83x3ja/2fPhXyXc2Bvp+Y5uK/zfdu1S3R+uvafikYRVcMoq315ED2ZiH6QiF5JRK8gos+V619ORC8nop8jou8joifKdSKiryWiX5H77326FkXaCxCO/tzg2keesiJXJpJwvAwOZwDr5waOYWMZ9pfvjZi+/mF53+fXTVntQJ+F/VUpTezAGBLzzQ7etZC/7GuwdMBSq8iMZQ0YXX0NKDKDyuQZtCtrWO6+V5sk8r3k6hIY56hslrOLE3jYnwFaBN1D5Yc2259WCva5sMt73xWAtokYh/FgAQQevLy26PvIa7C+nAwOU7y3Bg41A4UCSwKLugdA4ObCwc7co40HJ/jgOcDNZUlffT+figZC3fBvP+0AfAEzvzuADwDwbDkW9KuY+WnM/HQA3w3g70n6j0Q7afMpAJ4F4OtP16BIh3wQfwNNU3hnInq5u/UYAD96uyp1KSI3IAndRovOKIuzc+ozQB8wao5gvTV6sSpIenU5D+QADuiDG+tzYijN64R3z6eqA4xuZkJ6LpmRvCS9l0F7zcozT5e/lSNp1iZCZmYjqZqwMtHl+RB1pOUfkj5zH8of+zJDgwF/SlnPhyJ4YOUdrgKDgIMHl6yMuLHBo/zdhoJZa+AK24/K9ojS8a9lqZnJOait/fqu1Q8iWodf6+AZKrk+1M/QjsTI4zoMjmOL0mvMefEynZ+bI99D6lJro42jwVy6Cp3CSS2WmtfK9zcS0asAPImZX+mSPQq9h54B4FuZmQH8BBG9ORG9rbP4nIwO+SC+DcD3APhHAP6uu/7GUyzjPjWpdBO0AaCZZEqzwOQtJIzcRDCmF0aZ+23mAZjaapJNSQMxSeKZASwYdQYJn85ztTzJcnovUQbTSv++YIaDCWTMW7ZmiLZgd3ay7x9PjiFlBqf57KOsbXnAWADjWh20bE2ijNjdY23oCGh5+Z5GWoo53sN2JRyf92NopJ2Jr6SlJSw2f3Jj0saEmjDEMW9A4MuKj/Z1G8UBhXsnCz8L+r1c51AvTaOCk5hXjxWUhmMSvY5UI0hY+9bAIj1/UoBg4NROaiJ6RwDvBeAn5fdzAXwS2glwHyLJngTgt9xjvy3XTg4Qh3wQr2fmVzPzJ4jf4QG0bnm0HCJ0xxATlmruGYM33P0Qaj9N2xJk9XuoSk8YquA+r756tZ8TvTbRRuRNKQv7fWL0o+0qAgh4UxOn+0kKzf2YTWpH24rRn1lMmwvMo4UAPSqf0nc38XlPf6/5e4bmqNGnq2B4X/qp70RPissOed8mgvkegoARzJ8UGXZux8i3VLFkwF5oGggvh8apD8AIf6N5FOZENK/6/EN/j/o112k0Lj3D12ul/w19I5faw3pM2We19gfg8UT0M+7vWYu8iB6Ntsfd5zHzGwCAmb+YmZ8M4AUAPvt0NT+Ojt3N9aMBfDWAJwL4PQDvAOBVuIMODPJSffvkbi6amxSmYE9A2OPH1G8gLAAbSvM6IHN0hkZ9ZGkpTzgbzJxuDMjVd2+SJGQGxuEk+AxAPv+g5QwE1iaFts7q0j+FSZp9Oot+9JmuMcwENB54hh0h6UJRR4Jb0GJGfZ1BA+PP4FsxBt3PePDlGIgVCoXZfleVY/8lKXmxfYzkb5FFMn69YBsif1y+dp1CdtYmvxI+j5HeifFnDNrgITAsJYDBtUzWb+hhwdo/lNLkcbOo14GyjiRCr8sR9Dpmfp/VvIjO0MDhBcz8nYMkL0A7Ee7vA3gNgCe7e28n105Ox7prvgLNefJfmPmd0LaR/YnbUaGrUHOOcQOHCcDEgHzniRcLdvKeSQYwF4nO8FqJlrVglElUD4xh/N3T0IF6QPL15qXs7N5LI4acAG41yiv95vSc/9ybLt8bfOa6jN7pkGHA9ZVmk7WDYxhWSps1vqFTO/VtlsCDhOx9XPbXAVnrHcpOUVnWdt/fo/5YaVteq7Iwh6a899r4R/2fI+5yf6W8F0w+9Vc3aY36DsEScBKSIIKj/vYQERGA5wN4FTN/tbv+FJfsGQB+Sb6/GMAnSTTTBwB4/e3wPwDH7+a6ZebfJ6JCRIWZf5CI/vlVCiaiLwXw6QD+m1x6DjO/RO59EYBPQ1s+8znM/L2H8uMC1BssZh4OA5XMs9ZWruoCshEjyDZvIEmaTpJhDwoEGZg8niAA9Egay0ftwIzmbITLX7+uMPaF09ozPI1e8gxrzxj1Ezszj1xXLdg7IEfhw14jI8gccf6hIAV6hpiY/QIABszefEd5Lh5iWimt+Tf00lqf5X71TFm0B593bAMFG32gCjCRrX7W7bhtU70UGBHaPAArxrK/dJyZ41rKtSRea2CA5q5Uh2dcvy36xrIhaBQWO99Ky5ei+W2fGW4ELuR+rwkE/lkdW6cECOyfVxegDwLwTAC/QEQ/J9eeA+DTiOhd0XrnNwB8ptx7Cdoeeb8C4H4An3KSWgzoWID472If+08AXkBEvwfgvhOU/zXM/E/9BQnv+ng089UTAfwAET2VmedRBoE8OBQ/UvukpMJt+wq9N2Ac2cGl6riVoZN0Yuek5gVz7Rn2fKOqL4BROqPJ5pLRAFwzB2ElfX6WEMs5SKPyyC2kSjbokF4nozKB7EBFBCb//Eg7GL0bA/CR5O8lzdARKc1gLIT3dSx5huSuqXlopBGFMaFVIyBvNLkX7FK9136rJcuaTO4H0ndJGEBoBUhXhSJ9NueL44WWhcDiAXEEDFg+6wUalIu+1D10gqyY+Ucwno4vWUnPAJ599ZIP07EA8QwAN9E26PtEAG8G4MtuU52eAeDfMPMtAL9ORL8C4P0A/PihB4Pm4LvbD079nScnlgPMrqNPgC7Fsduh0pe7FINIM4Hcd9ssty0tyIx9VPsksFXAnvENGHUoTq7l6B5tG6W+CKaNPWTPcwKDIvHlzhcT+pEHn87PY1XxJgKKeflVuKHt6GCnma0C6uD7hSiPodF9+WTd2yJdC23y7dE8nEYZ6rvGKPfUY3E/g6BjrvZukdJcoK8CSETZzO73yq/ns3hXK2PT5x3q6gF0BRzuQA3ijqWjAIKZvbbwLScs/7OJ6JPQdoz9Amb+Q7RwLe/f0BCuBUkkwLMAYHrc41pdlUlfkBFkO/hQSicHBgXNv2GTnZeDmdu/dmD9sjyT5txEMNMBYKaY4WQYMcsEIlbOoK22XfmIASUmYaDDDQy8VB8nX2R8Vp6aJgjOXhHrY3VIdmOvVQzzduCZwWLUF6s0YMKhK1YYgfal1U+1JL8ffG5betdBKh+YcNaEAZ/mGJDXd6n9pGX67WVyWy8FqHSJ57T+h7T68e3lDT8/pD4jE+qViNGOjL2L6dBCuTdiPDUIADPzYw88/wMA3mZw64vRVv99ueT/5QD+GYBPPaLORsz8PADPA4B73v7JYvY8Dhy8qaVXGIFRRJ+DAwYggoNfAORFKWWI4AXDiEy4axE6QW0iq/kp1X1tEqkGEkwHCYByvkNpM/WTfs9mH+8AHJ0ZYD4WIIBD9hVgkPeqDwLL/IEOFjlA7BgGu2a2811oGie5PvbPe8nUR7coc8oOdAdmq8C2wmyzlmFa7h4GaO8eCKamMC58tQb9scx0vbzVNIl55zr4e6P27zOPrmoge/K7Cr1JaxDM/Jh99w8RM3/4MemI6BvRlpIDpw7hOmQWGEiacRJzYFLeEW3g4DUIwHEsGBcJE3CPNjFyXI8G9IgRQ543jNJ8Fa+0HanpecLa99wXLk0GiMXWJb5eGRj9Nb2eAMKDsa2OzwCRG6L9tibSrNCaGceKyHVdqTf59g8YlQeR1feXylloj1apQfojGJ8x15R/9k3kehyb/wgIhnX2ptZUh2PIxvSRD1zWsnA447sbIU64ZORilJaG/0UAvyjfXwzg24hI1108BcBPHZ2xGfDXb+8ViMKE4AXT2gcOq+aeVR0MCVQoTFIqWDpeR0zclcdi4rAVuVlyUp+G3A+2Y0rt99fcRA5ag/s9ktBMe3BS/ihc0p5JWoPlTzDnopfkwWSvPADQqL89ub73woDd1jLQmVgIbJDv7AC9otdrYefO/ZjrNGL4vm6u3nmNgu/3BUAN3onPV8eJN2fSIN0hqXshuR9BCy1Mxy36tYvSwmF+RN2vQm/SGsRtpq8koqejjclXA/gMAGDmVxDRCwG8Em0Tq2cfFcGUiVe+w0/+IykzWS+NrEglBkR7yvH1aOkFJDyj41jXNVOIpXXM1RzehODnABD9Aj6vzBCUoZX+nF+QuACIQRtDHV1djQbAFHwQAg7Dtgun7GYmTZAqsgcg1iLQFLLb+RjxvoItcfv0R3xyGhJBCxi9u0EdQ32srdrGMcja6uEEGIu+9UWRG6ujrhv1yxoDHpQVHxxcIsP59jkwqY5okWZkCbjdtCaM3EX0kAEEMz9zz73nAnjuxTJsH01ipX5BRuyxgLAvZO+2igsqpbqRboxlBSCCxKuGaMCAggm2kZs9501YA9PJSMqNjBphzcPCru7y0rosvq9048LunMHBm2dSF/S28Gr+qzQAnmwlZJ+OEE2CWD67sDyMJNkVkMhgbRWB++7/nFAQFowlocCrtSaEqN9rRtCGhhoWlnUbmR99WXuldzfWvHa29vpWQSFdU8AZ0lieuxQRYGtV7lZ6KDWIkxPVdhAM2YiDG/A0XKlp5MWqNEFiIVkqlpFNHVysjKwFpLL3hWSSG8mc7w8ZMbuZJgxqA3AVHkbte9j+YR9AeGadIorC2cIuzT6m0PtkJKYO6lFc+wOziw+uTs+L2BUWKhrMLNbMLuwEj1hPVETnOK9mmcpcqe6IGSO9rxUNwsx+gO0TljUvy0CfrRQur0nF2XS1HCcc27CnrQBEw+3amV8vs0h+hJCRTaUGFJofQ4So0zJ0elOOYnpYU+aqA4kuAMKx/GQkoSSQsDwHnIHWJmH6va7FxLoGe7wWoDH3jODHsHorlozKPAYgkvYAWu7WaXVFLo9XmVB4JtUhMKBjaI+2t3dhl9c8pQ7ah9bP3jfkGFvQ9AbgO6Jhf+Xrmr//vgYQAbA7kPs8o9PdRdDp6vZRRXPdnFAw1HjW2uGSqg+CCd1n5so/6MfL6R5s2jeO7xK66wBitMrTk9lb0/eW2DGlRcZ7Jq3nvL4gm8gOoII3L30eohXpMvsy1ARidc4TTZjdAqMGALF0FKdNCYGhhJ/7qjuraX+7A7NZSqVLM806stJKOfuAJmhwChJSPMth3MbQNG/te1fOQQ0itGH8PZisXFmL4eb7JgA4D1efmzyhTdRXomPHty3VM2oOHMZMaOuBNquyqxp/AKmREEOx3h40hiB7EWHi0sS4jmJ6mFGejMHko1QYzLS6CC2rz8MJngFBH7b7/U/L9wxr+H1fe9akS51MFCePMgtbje3r5T9zWVnqdMCgtm3bYkTzLZGR9+99BttkTxNqD39f5nXMpHfIx8JJj+IVQ0Giq2bav0wszn+5nt+t5LXoXur3lnUeVMdfS2PFb3vh84iaHq8LPJQeV9XIj7Wc/xqluTJsz9pL9oClIKWar2v6ECT21MesmA8CSFxHMd0NpCGkhGYuqG3yc6EFg/Y21aMpSTR2zWkPtPiOBBQDkXtUhtxiP4PCcy0Bl+Zz4QwS3D+C1mHP9rQZGJTxhC1G5DmVKM3kEhgc94/c3jWA8ICwImEvaKES9TwvM5ENJARobNsTQkeG+GFVPyrzC9Qjaw4jnutNfl2j00r5xMtnvf8sCBv6uae6CyEmhQtnsmg9b9Yq3HyImo/bQDC0mVz1B+/1wQCFWODdjRB3F0D40eIYqE30QnZEI4s02ySyJXPOqvMqeXDITJspAkBgkFjei5WQ/8n2vjJZ1xze5D9TCOECm5wkuAgx9YvXnONT71tfubUKi7o5kNTSR9E+4XOtcbmh+swiP8ZVuIYHLAV5V31JlB9ayyz9SOnWAyhowRiHwFriuD1k7olapzDtffXYR66fDnW3ChMtqKSV34QY18cKxm6euGr2vNbqod8pvsOj5vSxxMAFzoN4WNLdAxBJzQ1aLLtBCQpRJwoUo/xCnsfMGo6f5Ad4utafoXgvZYVW437NSZN7SesPxFWye5hFAAZ1QJZ8nVeBwbSIVEZf1EU9LPBQdx4ziTWPEQisaWajNEcSu3Gw1yy4oh3538bo3JgZgmr40ROErKVeIx/S0WYi3vPbF5qFoWPyHlHi9nGhnv8/lr0GXdKzHvTDcA+sU1C91iAeVpTt3w0S9GZXZUGNcYUzgD2tTbJjB5cfhZlhGGj0NJnhGM9TVCANtUz1zTMnVcE0hzqe86OJtAoM6PeRzBkKHDQCU2knMwsg0/H9mKs7ZFwrDDk/c8RcPta5vJfJqLaxB5HD6xtwQBNwhkAhT2ZTzimlY08JuLp5s02iMC5XnhuBX/DzuD7YCxLyY+gC9OXKmM5mt6FP5gp0vQ7iYUQ+Ft+I2m6qgNMmVJVFsitnctrDgt+b5zlXAmOGdSyTcpxjL0ho2XukVK2r+SKy9uKBQbWAQ8BAWG4vQgkcFn0pUrfqQqMQqr19coEZ7dsYXtr+x0bAs1BMDlUjgQuZlKwXEN7vsSA/rFc+0yBLx/sk92Ou5TqO6jAa+zT+fVABV4wIeJFAQupD7plRuYsx7YWfEY+4Cl0DxMOIRsxp5f0F6WVFg9A8lzb6ERNcVsV/Xpi0amsgMWIw+ugeySxrQyGWPUfBwH33Euox4LDCXIjQD5A51P78bAbcgWYWOiE/sy8/94xPsAgI2Ks5jOu9jxYO9JzHoLwhXtLK9fBg/FyaOwf1OtAmNdN2Bt7EgNBne55d9nl6Rn0jDhwWeSdQ7IDQx23wnZ2KGHHX3ruQ7h6AUMnWk03oNsuzZcOk2X15IoHCmoSWJlqODIl6speQkL5dkciVLzNqKDT6iZMmlPkX0O955p9BcmxWSp+XoczkD4LCnuccLRjTKJ1yIupvZ69ZI1EEs1TnUEaU+rMT1j++XtjK9xFlcODYH8PpkMZuyMv1Sd/7y5l1D8wTS5bBqlepzw4dywMgD5f9uHagELTgExCBr01MDyvK3D9I2R0k9OfaQIlmhcwo03V9YFBWn1i9MF9shAcK11bbhTgRhrTCjzy4BUfemhkJwAIY9FomQ8RBfVyHHjWfhnkMvl9Qc+iAsQdkhnWQPHGcBLooZ60MzToNpWGa1cJGBTu6oMjsNZqg3eQxsHiwJ+PB9dUqrgBGrlN4PvteXP3C2B6BQxYir0r17lYh7iKA4DT6/v/tnXuwJcVdxz9fVgIICCS7AhIISwQiECQBUyQ8pJRCggZQiBBjAoklRjHGMhhJNmVRoWIFMVhSQAyJVEKCgBEhFIUhoLxECOGxLM8NLKwK4RGCQFAkPH7+MX3u7TPTPdNzzsw5597bn6pz75zunu7f9OnpX/9+3dPjDZ2HOmrmFUXMegiNyOo6x7JC8MMoWREDUYYlHxolzZ1UKm/oZogojYq7InSu+195jqH84iMvfe2ErTkroixE6aSRlUPlIloQy680Yo32rUNtSLVKImg11Mkwd2JDfF2akuDBznQMv0pZYQxkqUz2lssdyqThe0t5KniyVJTDnKw2v7CiK4zsYlpQ+EPzWI/sK4qYaV5uRLEJ6QH+jeiVM/d1aNRTtSTAa/i+gqmRLWZFRPsCr9Ov3Og17qTaPP0qHiiJyAmNyqHSiUQKrR2BJloPTaNaL7wy/2Dzy46jdOnojrXFhOKGJsrn/TUV5RgtN6AY5r67dlJRFATyTqzvkPyNMpbTh+Qpp+1wkjq7mBYi5ZHfgHKvHOpkYx0z1QY71OeX28lAM3hWRBHshJDXaTaMZIfKbpK57lzvvMq8im8htenfYkrCT1JrFbQoC6p1Har7WN6BUX1l4tvP1w+X/1/hOg/1aHXX16aeayyFVpQN7VCSOcVSDffbSbRD9n+ThLY9EqU2XackeyUriAVERQGUXD+hhjxIVwqrNKzKJKwCPtpqIbZBIcNgEm7QMQ/dgL6Pfu5PRFZPlqTGX7YEmuZUUvKMdZChpKmddwohV15bWnbYQyvGykoihZBCSyVSx607vVRrLGQ1+HGlFX2xe6WyKKPlb1V7fS3jgh62zrSGZQWxcBi01vroavhwxxicmyiPJgfnBSe9Q5rIPYvh9atDJUQ6gvI8eDVBU3zAGqr8j1tMfjZJk7NJyiUhTSqVztcTNHHk2qTrOulLaju19ApJ1kkBt9vwiqWa4iPtaNh6KFkTZTn9rDwlUZkfKYkYpOmaU3+fUZV0U55ZQSwgQnd7qHersxgCLpa5dw9V+v754dawWe6NdEtp5146UyOSfzkhfTPsMqpRZuXvsfMabphaa6pvE94vx/en+8qhYZRasfRKI9tQxxUcQdfKl6hFywUlUJdtdULYHzUM/4+602oyLVsMFbdSrKcP3QKluGq5NTLVpG2q9mJx3ThmZ03e+YVBC4zQcp6G1UoV1wvh0bAfZn4n41kT9UrCK6fqsaq/nvJ1xDr+WFiTIhkFX7RAfpXBVVf3UmjSNeTKqYyOa1yOqYqhVlmOdoEjWQaxDAJKYH6CPhIeyDxqMXiKITRwKLKZjxjcHvPuVNLaXpej/KpB3x3ZglhADI0SQ9ZEKXnEapAfHixH/htNhwo3VHI3uYJHbvAJDbCPzn9QemJewfukbnTbUoYhvzbMBwwp6qLQoa1VnBz+b12ZgI0Odf2yOrmUkUhaPhtTBuXjSFbzhc3/r8w3lJVCTMHOKYoiYGgxRtf1FpKnMl84aCIdWxFG3qxvQVHuLCIO5loXTQpBtxVDN8nwRF1seJpQTnLa+ug6L9vIDDmbA+GxwschZimUlUfZoot4Qoos0ipjkkphQKNyaHIfpVxaoJMtWxC1ymHwPVRWWZH3QZt8WyywSMgsWxB9IeliYFf3dUvgWTPbS9KOwP3AWhd3i5l9JDnjBCWR7C4OuasSe4n4qLeUx0gKKq38JPm6oC6fiQ61B2Uyd3Eha6JMZyJ27MpIVQ61ZbZ054RWKQXdSbF8Sk1cFR9TRM5UEi29kLzzK9K6NLGzgugFMztmcCzp88BzXvQ6M9urXYYElAPDSsJrp0ONpRRXWc/fdvIxZdYsOb/0pH30xbXLBGtccF3LEI0ILXttsiZg9A7KL2PUNG29hjG3Ul2ZwdF8RJygm2ZeiNYT9qW855WEl1lnSjnR/deXBZMVRL9IEvCbwC+NnZmVeooGJVE9fz6u/LtXJqjL5w3JkCrrIPPxGtko/XE3LqZ+rYOgjCkdZI3LaS7fURVFF5fcsSscAjo7IGfjyqGA67WLn3h4FVl/HWrSUuwuizeDV1/tMMPZY+oKAjgAeNLMHvTCVkq6E3ge+LSZ3Rg6UdIJwAkAy7baajjSv1HmGsWwkqiYnIM4L/lcdrGGNUqDK7fkuhF5hyOfUW+Otis4uy4/SqOlxngj7ljanqmtpyHF54U3TXOlhje4aUatg5TxUO/eyD6siGxBjI6ka4BtAlGrzOyb7vh9wIVe3OPADmb2Q0l7A5dJ2t3Mni9nYmbnAucCbLTD9sNDHn85adldVFISc6eFzm2D18KTliTG4gKrMIrw8GmxDrzLDrntNEz3yqDDrELzLyO4ZkYrfIRzyj9wSNYmGaMKItFF0yHTmOzvBSOvYhoHMzu4Ll7STwC/AeztnfMS8JI7vl3SOmAX4Lb2AtA8JwFxRQFpPV3XLT42g1wzAurRcp9OWXVlVCywhONUupqjCDFOniEN3bbZRX645AnopDIGmSamb0OTDKnWYpdkC6JXDgYeMLNHBwGSVgDPmNmrknYCdgYe7rxkvxMOTV776XwShtL1LoJEf80ISmJB0YlrribPce7bunxDVCbxxyibeo9jfUR63smM2tZiE8Ud5B+9JadxX2QF0SvHMuxeAjgQ+Iyklyl2W/+ImT2TlFvKA2NDE5QlJeHOqXh46hRGqIi6CUN/Rcco9HkTTKOtJ0/qJ4RVvg/nHXf7pYkQpad6m4grJsHjOYmyqmnTKzW6yq5v8iR1v5jZ8YGwS4BLWmdWmWyriRsqsKQRAiP0USdpgyPBWlkS03XJJJVC20pM7dAbFAP0qBwWAqk6uHEeYwYqK8WFNUk5F7kF0fUL+KaLvI8fVk4zStZjtANT9RMuhKr8fWF02zmGLjLpoiNyxSyGtu6fxY4SPiUafx5Z+DPNawjd14nX2ytmaZ8aJG0v6VpJ90m6V9LHXPjpkh6QtEbSpZK29M75pKSHJK2V9Ct9Xd7iUhA+ocYSajwtGn6X90hKf9pVn1stvAfBx6VrhZXKNDqVNrTs/AcktZkURdCm8x710zUTK9OKVUwpn3peAT5uZrsB+wInStoNuBrYw8z2BL4HfBLAxR0L7A4cCpwjaVlXV+Uz7TmIbqkbmQfD2/VIs7g8r3FCs3LCmAX1wVirewLnB3yCzRO/HcjSBS2qOW31UcIFtflpZ+UeGLfNdCSD2fgvpTazxymW92NmP5J0P7CdmX3bS3YLcLQ7PgK4yK34fETSQ8A7gJvHFqbE4lIQPnWNoO6m6arxpPbYk9Y6oQ61iVnUjE1ENkhMVhQwGWWRULXJ1d/U5pLzSUw3ynld1emsNMmOn4Nwe9G9DfhOKerDwMXueDsKhTHgURfWOYtLQTQ1mjEUQ6s+stVeS83LZlOIrYoNl0m7G7WrR6mj+ZMmTyxd3ei/QVGUkwXzLdO2T2hZdZ1YBo33Qqo0LdP2ldcsKpZ2q5iWS/Kf5TrXPeg7h6TNKBbo/LH/YLCkVRRuqAvGlLg1i0tB+HRgWo/UJ461hHW8jrh3JVEurEvGVRKDOCLxDYo4SWGUyxmDTgccXSiDSbf1AakVMSsWQ5n0VUxPm9k+sUhJG1IohwvM7J+88OOBXwN+2WyusMeA7b3T3+jCOmcRKYiElRaJjWwhelQGtFYScye2LCj4EN+YFZc6D9CUrum6EmSfaBtI/cG66ui7cll1wSwsnR0De238OQi3YenfAfeb2Rle+KHAJ4BfNLP/9U65HPh7SWcAP0PxMPGtYwsSYPEoiJrVCb3e7DPYwEfalym1jrpYf970g9RFt31WJFnpzMjv2Lattk4/joU7+qmLk+YlrInsB3wAuFvSahf2KeBMYCPg6kKHFO/GMbN7Jf0DcB+F6+lEM+vlib3FoyCY0VFfChMQvO32UlG68Ms3CVBXH6MqsoXSuY0r57jtcsbqaaateaOTSWoz+zfCNX9lzTmfBT47duENLCoFMVFSfTkz2MJb+dtTabrMLhVIMP/yRbXPYmbo+6G0CTGDTb9TDLC81UYmyiK5A3pRGGXGraqF4iLqkxlsbovkFhgNM+jgOYhZJiuITIXGKYJpPfGcmShLuvNPxPL7IDKZYXLHkck4FrkFIVskuxFK+gHwHz1lvxx4uqe8RyXLlMYsygSzKddSkulNZrZinAwkfYtCvhSeNrNDxylvGiwaBdEnkm6re8hlGmSZ0phFmWA25coyZcos3t1cM5lMJjMWWUFkMplMJkhWEGmc25xk4mSZ0phFmWA25coyZYbIcxCZTCaTCZItiEwmk8kEyQoik8lkMkGygvCQ9F730vDXJO3jhe8o6UVJq93nb724vSXd7V4gfqbbuncicrm44MvLJR3qwh6SdHLXMpVkOEXSY179HNYk3ySYZB00yLHetZHVg5fGSHq9pKslPej+bzUBOc6T9JSke7ywoBwqONPV3RpJb5+gTDPZnpYkZpY/7gP8HLArcB2wjxe+I3BP5JxbKV40LuCfgXdPUK7dgLsotgReCawDlrnPOmAn4HUuzW491tspwEmB8KB8E/otJ1oHDbKsB5aXwv4SONkdnwycNgE5DgTe7rflmBzAYa49y7Xv70xQpplrT0v1ky0IDzO738zWpqaXtC3wU2Z2ixUt+HzgyAnKNffycjN7BBi8vPwdwENm9rCZ/Ri4yKWdNDH5JsGs1EGMI4CvuuOv0kO7KWNmNwDPJMpxBHC+FdwCbOna+yRkijHN9rQkyQoinZWS7pR0vaQDXNh2FC8MH9Dby8MjbAf8V6D8WHif/KFzRZznuUumIceAaZZdxoBvS7pd0gkubGsze9wdPwFsPR3RonJMu/5mrT0tSZbcZn2SrgG2CUStMrNvRk57HNjBzH4oaW/gMkm7z4BcE6NOPuALwKkUHeGpwOeBD09OuplnfzN7TNJPU7wd7AE/0sxMmv5+5bMiB7k9zQxLTkGY2cEjnPMS8JI7vl3SOmAXiheFv9FLOvLLw0eRi/qXl3f6UvNU+SR9CbgiQb6+mWbZQ5jZY+7/U5IupXCLPClpWzN73LlunpqGbDVyTK3+zOzJwfEMtaclSXYxJSBphaRl7ngnipeEP+xM8+cl7etWL30QmORo/3LgWEkbSVrJ/MvLvwvsLGmlpNcBx7q0vVDyTf86MFiREpNvEky0DmJI2lTS5oNj4BCK+rkcOM4lO47JthufmByXAx90q5n2BZ7zXFG9MqPtaWky7VnyWfpQNMZHKayFJ4GrXPhRwL3AauAO4D3eOftQNOB1wFm4p9MnIZeLW+XKXou3gopiFcr3XNyqnuvta8DdwBqKm3jbJvkm9HtOrA5qZNiJYuXNXa4NrXLhbwD+BXgQuAZ4/QRkuZDCXfqya0+/E5ODYvXS2a7u7sZbPTcBmWayPS3FT95qI5PJZDJBsospk8lkMkGygshkMplMkKwgMplMJhMkK4hMJpPJBMkKIpPJZDJBsoLIZDKZTJCsIJYQkl7oIc/DB1tpSzpS0m4j5HFdeRvzhPRrJR0eiNvR3zp6sSPpU97xJm577B9LWj5NuTKLg6wgMmNhZpeb2efc1yMptmSeBO83s16fjB48PT/jzCkIM3vRzPYCvj89cTKLiawgliBu+4TTJd3jXmRzjAs/yI3O/1HSA5IucFuIIOkwF3a7e5HMFS78eElnSXoXcDhwuhvFvtm3DCQtl7TeHW8i6SJJ97u9iTbxZDtE0s2S7pD0DUmbJVzP3pLuknQXcKIXvsxd53fdzqC/58I3kHSOu56rJV0p6WgXt17SaZLuAN4bk8eVeb2rj6sG20NI+iNJ97nyLqqReVMVO5XeqmKX4CNc+I6SbnTl3eHqFUnbSrrB1e09kg6Q9DlgYDVckPTjZzJtmPaj3PkzuQ/wgvt/FHA1xUt1tgb+E9gWOAh4jmITtA2Am4H9gY0ptlle6c6/ELjCHR8PnOWOvwIc7ZV3HW6LBmA5sN4d/wlwnjveE3iFYsuS5cANwKYu7s+APw9cx1y+7vsa4EB3fDru5TPACcCn3fFGwG0UL5o5GrjSXeM2wH8P5KZ4uc8nPJkr8gAbAv8OrHDhx3jX831gI3e8Zc1v8RfAbw/SUWwJsinwk8DGLnxn4DZ3/HHmt+lYBmzu/6alvNdTekFR/uTPKJ8lt5trBig6/QvN7FWK3TyvB34BeB641cweBZC0muJtei9QbE74iDv/QorOd1QOBM4EMLM1kta48H0pXFQ3OcPldRRKKoqkLSk64htc0NeAd7vjQ4A9B9YBsAVFp7s/8A0zew14QtK1pWwvbpBnV2APiq27oeiwBxvZrQEukHQZcFmN6IcAh0s6yX3fGNiBQsGcJWkv4FWKXYOh2HzwPEkbApeZ2eqavDOZTsgKIlPmJe/4VcZrI68w78bcOCG9gKvN7H1jlFnO76NmdtVQoPeO4wj/UyePpLcC95rZOwPn/iqFAnwPsErSW83slYhsR1npTYGSTqHYkPHnKeru/6B485qkA13+X5F0hpmd33AdmcxY5DmIpcmNwDHOR7+CokOr2zZ5LbCTpB3d92Mi6X4EbO59Xw/s7Y6P9sJvAH4LQNIeFG4mgFuA/ST9rIvbVNIu1GBmzwLPStrfBb3fi74K+H036kbSLiq23L4JOMrNRWxN4VoLEZNnLbBC0jtd+IaSdpe0AbC9mV1L4Y7aAojNoVwFfNSb43mbC98CeNxZNx+gsE6Q9CbgSTP7EvBlivc4A7w8uL5MpmuygliaXErhCrkL+FcKn/sTscRm9iLwB8C3JN1OoQieCyS9CPhTN+n6ZuCvKDroOyn8+QO+AGwm6X7gM8DtrpwfUMxpXOjcTjcDb0m4ng8BZzuXmLzwLwP3AXeoWPr6RQqL6BKKraXvA75OsYV75Xpi8ljxjuujgdPcxPhq4F0UnfnXJd0N3Amc6RRYiFMp5jLWSLrXfQc4BzjO5fsW5q2Zg4C7XF0eA/yNCz/X5ZEnqTOdk7f7ziQhaTMze8GNeM8GHjSzv56SLNcBJ5nZbWPkMbieN1BYT/vVKcmFhFstto+ZPT1tWTILm2xBZFL5XTdCv5fCDfLFKcryDIUfvvKgXAuucNdzI3DqYlAOcg/KUVgmr01ZnMwiIFsQmUyPSPoQ8LFS8E1mdmIofSYzS2QFkclkMpkg2cWUyWQymSBZQWQymUwmSFYQmUwmkwmSFUQmk8lkgvw/jEgRB6vnX6oAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.t.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "61f247d667a6ee5eea6229fe7c4e84dc8005a04f8c9b311bfb3247c5f19bf473"
  },
  "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": "3.8.10"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}