{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SlideRule Interactive Feature Find\n",
    "\n",
    "SlideRule is an on-demand science data processing service that runs in on Amazon Web Services and responds to REST API calls to process and return science results.  SlideRule was designed to enable researchers and other data systems to have low-latency access to custom-generated, high-level, analysis-ready data products using processing parameters supplied at the time of the request. \n",
    "\n",
    "[Documentation for using SlideRule](https://slideruleearth.io/rtd) is available from the [project website](https://slideruleearth.io) \n",
    "\n",
    "## Learning goals\n",
    "\n",
    "- Finding interesting features with ICESat-2!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from sliderule import icesat2, ipysliderule, sliderule, io\n",
    "import ipywidgets as widgets\n",
    "import warnings\n",
    "# turn off warnings for demo\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Paste `Show Code` contents from [Web Demo](https://demo.slideruleearth.io/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "icesat2.init(\"slideruleearth.io\")\n",
    "parms = {\n",
    "    \"srt\": 0,\n",
    "    \"len\": 40,\n",
    "    \"res\": 20,\n",
    "    \"pass_invalid\": True,\n",
    "    \"cnf\": -2,\n",
    "    \"atl08_class\": [\n",
    "        \"atl08_noise\",\n",
    "        \"atl08_ground\",\n",
    "        \"atl08_canopy\",\n",
    "        \"atl08_top_of_canopy\",\n",
    "        \"atl08_unclassified\"\n",
    "    ],\n",
    "    \"yapc\": {\n",
    "        \"score\": 0\n",
    "    },\n",
    "    \"ats\": 20.0,\n",
    "    \"cnt\": 10,\n",
    "    \"poly\": [\n",
    "        {\n",
    "            \"lon\": 13.648796,\n",
    "            \"lat\": 52.007611\n",
    "        },\n",
    "        {\n",
    "            \"lon\": 13.847923,\n",
    "            \"lat\": 52.007611\n",
    "        },\n",
    "        {\n",
    "            \"lon\": 13.847923,\n",
    "            \"lat\": 52.075609\n",
    "        },\n",
    "        {\n",
    "            \"lon\": 13.648796,\n",
    "            \"lat\": 52.075609\n",
    "        },\n",
    "        {\n",
    "            \"lon\": 13.648796,\n",
    "            \"lat\": 52.007611\n",
    "        }\n",
    "    ],\n",
    "    \"rgt\": 84,\n",
    "    \"cycle\": 7,\n",
    "    \"track\": 1,\n",
    "    \"asset\": \"icesat2\"\n",
    "}\n",
    "gdf = icesat2.atl03sp(parms, asset=\"icesat2\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Review GeoDataFrame output\n",
    "Can inspect the columns, number of returns and returns at the top of the GeoDataFrame.\n",
    "\n",
    "See the [ICESat-2 documentation](https://slideruleearth.io/web/rtd/user_guide/ICESat-2.html#segmented-photon-data-atl03) for descriptions of each column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Returned 39631 records\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cycle</th>\n",
       "      <th>sc_orient</th>\n",
       "      <th>background_rate</th>\n",
       "      <th>track</th>\n",
       "      <th>segment_id</th>\n",
       "      <th>rgt</th>\n",
       "      <th>segment_dist</th>\n",
       "      <th>solar_elevation</th>\n",
       "      <th>height</th>\n",
       "      <th>atl03_cnf</th>\n",
       "      <th>landcover</th>\n",
       "      <th>atl08_class</th>\n",
       "      <th>quality_ph</th>\n",
       "      <th>distance</th>\n",
       "      <th>yapc_score</th>\n",
       "      <th>snowcover</th>\n",
       "      <th>relief</th>\n",
       "      <th>pair</th>\n",
       "      <th>geometry</th>\n",
       "      <th>spot</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-04-01 01:18:14.833129216</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>712496</td>\n",
       "      <td>84</td>\n",
       "      <td>1.427102e+07</td>\n",
       "      <td>-26.952822</td>\n",
       "      <td>96.497551</td>\n",
       "      <td>4</td>\n",
       "      <td>255</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-18.253809</td>\n",
       "      <td>98</td>\n",
       "      <td>255</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>POINT (13.75534 52.07558)</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-01 01:18:14.833328896</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>712496</td>\n",
       "      <td>84</td>\n",
       "      <td>1.427102e+07</td>\n",
       "      <td>-26.952822</td>\n",
       "      <td>96.632645</td>\n",
       "      <td>4</td>\n",
       "      <td>255</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-16.830337</td>\n",
       "      <td>146</td>\n",
       "      <td>255</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>POINT (13.75534 52.07557)</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-01 01:18:14.833928960</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>712496</td>\n",
       "      <td>84</td>\n",
       "      <td>1.427102e+07</td>\n",
       "      <td>-26.952822</td>\n",
       "      <td>108.836823</td>\n",
       "      <td>4</td>\n",
       "      <td>255</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-12.584853</td>\n",
       "      <td>67</td>\n",
       "      <td>255</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>POINT (13.75533 52.07553)</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-01 01:18:14.833928960</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>712496</td>\n",
       "      <td>84</td>\n",
       "      <td>1.427102e+07</td>\n",
       "      <td>-26.952822</td>\n",
       "      <td>96.426636</td>\n",
       "      <td>4</td>\n",
       "      <td>255</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>-12.560813</td>\n",
       "      <td>244</td>\n",
       "      <td>255</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>POINT (13.75533 52.07553)</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-01 01:18:14.834029056</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>712496</td>\n",
       "      <td>84</td>\n",
       "      <td>1.427102e+07</td>\n",
       "      <td>-26.952822</td>\n",
       "      <td>108.848206</td>\n",
       "      <td>4</td>\n",
       "      <td>255</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>-11.873586</td>\n",
       "      <td>67</td>\n",
       "      <td>255</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>POINT (13.75533 52.07552)</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               cycle  sc_orient  background_rate  track  \\\n",
       "time                                                                      \n",
       "2020-04-01 01:18:14.833129216      7          1              0.0      1   \n",
       "2020-04-01 01:18:14.833328896      7          1              0.0      1   \n",
       "2020-04-01 01:18:14.833928960      7          1              0.0      1   \n",
       "2020-04-01 01:18:14.833928960      7          1              0.0      1   \n",
       "2020-04-01 01:18:14.834029056      7          1              0.0      1   \n",
       "\n",
       "                               segment_id  rgt  segment_dist  solar_elevation  \\\n",
       "time                                                                            \n",
       "2020-04-01 01:18:14.833129216      712496   84  1.427102e+07       -26.952822   \n",
       "2020-04-01 01:18:14.833328896      712496   84  1.427102e+07       -26.952822   \n",
       "2020-04-01 01:18:14.833928960      712496   84  1.427102e+07       -26.952822   \n",
       "2020-04-01 01:18:14.833928960      712496   84  1.427102e+07       -26.952822   \n",
       "2020-04-01 01:18:14.834029056      712496   84  1.427102e+07       -26.952822   \n",
       "\n",
       "                                   height  atl03_cnf  landcover  atl08_class  \\\n",
       "time                                                                           \n",
       "2020-04-01 01:18:14.833129216   96.497551          4        255            1   \n",
       "2020-04-01 01:18:14.833328896   96.632645          4        255            1   \n",
       "2020-04-01 01:18:14.833928960  108.836823          4        255            2   \n",
       "2020-04-01 01:18:14.833928960   96.426636          4        255            1   \n",
       "2020-04-01 01:18:14.834029056  108.848206          4        255            2   \n",
       "\n",
       "                               quality_ph   distance  yapc_score  snowcover  \\\n",
       "time                                                                          \n",
       "2020-04-01 01:18:14.833129216           0 -18.253809          98        255   \n",
       "2020-04-01 01:18:14.833328896           0 -16.830337         146        255   \n",
       "2020-04-01 01:18:14.833928960           0 -12.584853          67        255   \n",
       "2020-04-01 01:18:14.833928960           0 -12.560813         244        255   \n",
       "2020-04-01 01:18:14.834029056           0 -11.873586          67        255   \n",
       "\n",
       "                               relief  pair                   geometry  spot  \n",
       "time                                                                          \n",
       "2020-04-01 01:18:14.833129216     0.0     0  POINT (13.75534 52.07558)     6  \n",
       "2020-04-01 01:18:14.833328896     0.0     0  POINT (13.75534 52.07557)     6  \n",
       "2020-04-01 01:18:14.833928960     0.0     0  POINT (13.75533 52.07553)     6  \n",
       "2020-04-01 01:18:14.833928960     0.0     0  POINT (13.75533 52.07553)     6  \n",
       "2020-04-01 01:18:14.834029056     0.0     0  POINT (13.75533 52.07552)     6  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(f'Returned {gdf.shape[0]} records')\n",
    "gdf.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interactive Mapping with Leaflet\n",
    "\n",
    "<table>\n",
    "  <tbody>\n",
    "    <tr>\n",
    "      <th align='center' max-width=\"30%\"><a href=\"https://epsg.io/3857\">Global (Web Mercator, EPSG:3857)</a></th>\n",
    "      <th align='center' max-width=\"30%\"><a href=\"https://epsg.io/5936\">North (Alaska Polar Stereographic, EPSG:5936)</a></th>\n",
    "      <th align='center' max-width=\"30%\"><a href=\"https://epsg.io/3031\">South (Antarctic Polar Stereographic, EPSG:3031)</a></th>\n",
    "    </tr>\n",
    "    <tr>\n",
    "      <td align='left' valign='top' max-width=\"30%\">\n",
    "        <ul style=\"line-height: 1.5em\">\n",
    "            <li><a href=\"https://apps.nationalmap.gov/3depdem/\">USGS 3DEP Hillshade</a></li>\n",
    "            <li><a href=\"https://asterweb.jpl.nasa.gov/gdem.asp\">ASTER GDEM Hillshade</a></li>\n",
    "            <li><a href=\"https://www.arcgis.com/home/item.html?id=10df2279f9684e4a9f6a7f08febac2a9\">ESRI Imagery</a></li>\n",
    "            <li><a href=\"http://glims.colorado.edu/glacierdata/\">Global Land Ice Measurements from Space (GLIMS)</a></li>\n",
    "            <li><a href=\"https://www.glims.org/RGI/\">Randolph Glacier Inventory (RGI)</a></li>\n",
    "        </ul>\n",
    "       </td>\n",
    "       <td align='left' valign='top' max-width=\"30%\">\n",
    "        <ul style=\"line-height: 1.5em\">\n",
    "            <li><a href=\"http://goto.arcgisonline.com/maps/Arctic_Imagery\">ESRI Imagery</a></li>\n",
    "            <li><a href=\"https://www.pgc.umn.edu/data/arcticdem\">ArcticDEM</a></li>\n",
    "        </ul>\n",
    "       </td>\n",
    "       <td align='left' valign='top' max-width=\"30%\">\n",
    "        <ul style=\"line-height: 1.5em\">\n",
    "            <li><a href=\"https://lima.usgs.gov/\">Landsat Image Mosaic of Antarctica (LIMA)</a></li>\n",
    "            <li><a href=\"https://nsidc.org/data/nsidc-0280\">MODIS Mosaic of Antarctica (MOA)</a></li>\n",
    "            <li><a href=\"https://nsidc.org/data/NSIDC-0103\">Radarsat Antarctic Mapping Project (RAMP)</a></li>\n",
    "            <li><a href=\"https://www.pgc.umn.edu/data/rema\">Reference Elevation Model of Antarctica (REMA)</a></li>\n",
    "        </ul>\n",
    "      </td>\n",
    "    </tr>\n",
    "  </tbody>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dbf120f76b8d47559c83a2bd6e29f007",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Dropdown(description='Projection:', description_tooltip='Projection: leaflet map projection\\n\\t…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# display widgets for setting SlideRule parameters\n",
    "SRwidgets = ipysliderule.widgets()\n",
    "SRwidgets.set_atl03_defaults()\n",
    "widgets.VBox([\n",
    "    SRwidgets.projection,\n",
    "    SRwidgets.layers,\n",
    "    SRwidgets.raster_functions\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "22fe0ff549da40ca83185b5d05348e05",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Map(center=[52.04161000009321, 13.748359500025213], controls=(ZoomControl(options=['position', 'zoom_in_text',…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# center map on polygon centroid\n",
    "lon, lat = io.from_region(parms['poly'])\n",
    "cx, cy = io.centroid(lon, lat)\n",
    "# create ipyleaflet map in specified projection\n",
    "m = ipysliderule.leaflet(SRwidgets.projection.value,\n",
    "    center=(cy, cx), prefer_canvas=True)\n",
    "# install click handler callback\n",
    "m.add_selected_callback(SRwidgets.atl03_click_handler)\n",
    "# add polygon from web demo code\n",
    "m.add_region([parms['poly']])\n",
    "# show map\n",
    "m.map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# add any selected base layers\n",
    "m.add_layer(\n",
    "    layers=SRwidgets.layers.value,\n",
    "    rendering_rule=SRwidgets.rendering_rule\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Add GeoDataFrame to map\n",
    "\n",
    "For stability of the leaflet map, SlideRule will as a default limit the plot to have up to 10000 points from the GeoDataFrame\n",
    "\n",
    "GeoDataFrames can be plotted in any available [matplotlib colormap](https://matplotlib.org/stable/tutorials/colors/colormaps.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6968e96c55ea46b3a9eb2ee4cb74f77a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Dropdown(description='Variable:', description_tooltip='Variable: variable to display on leaflet…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "widgets.VBox([\n",
    "    SRwidgets.variable,\n",
    "    SRwidgets.cmap,\n",
    "    SRwidgets.reverse,\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "# ATL03 fields for hover tooltip\n",
    "fields = m.default_atl03_fields()\n",
    "m.GeoData(gdf, column_name=SRwidgets.variable.value, cmap=SRwidgets.colormap,\n",
    "    max_plot_points=10000, tooltip=True, colorbar=True, fields=fields)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "### Visualize photons as an along-track plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6081e4126177481a94488c5f8c89c179",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Dropdown(description='Classification', description_tooltip='Classification: Photon classificati…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "widgets.VBox([\n",
    "    SRwidgets.plot_classification,\n",
    "    SRwidgets.rgt,\n",
    "    SRwidgets.ground_track,\n",
    "    SRwidgets.cycle,\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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CCCHEueF/+5V7Y+7GyuddXIQQQgghhBB/kwq6EEIIIYTwCfWvzVtzN1ZSQRdCiEZqz4b9pOw47OswhBBC1DOpoAshRCM07bnZzHrlOwD+9dEDXHmvtJYVQjQ+Hi/2QffWvGeCVNCFEKIRWr/gz6rXq79f78NIhBBC1DdJ0IUQohG6Z+JwTBYj1gALd718q6/DEUKIU+LRvLs1VrLERQghGqFuA89nQcUsX4chhBDCCyRBF0IIIYQQPiFdXGomS1yEEEIIIYRoQKSCLoQQQgghfEJFwYPitbkbK6mgCyGEEEII0YBIBV0IIYQQQviEqlVu3pq7sZIKuhBCCCGEEA2IVNCFEEIIIYRPeLy4Bt1b854JUkEXQgghhBCiAZEKuhBCCCGE8AmpoNdMKuhCCCGEEEI0IFJBF0IIIYQQPqFqCqrmpT7oXpr3TJAKuhBCCCGEEA2IVNCFEEIIIYRPyBr0mkkFXQghhBBCiAZEKuhCCCGEEMInPOjweKle7PHKrGeGVNCFEEIIIYRoQKSCLoQQQgghfELzYhcXTbq4CCGEEEIIIeqDVNCFEEIIIYRPSBeXmkkFXQghhBBCiAZEKuhCCCGEEMInPJoOj+alLi6aV6Y9I6SCLoQQQgghRAMiFXQhhBBCCOETKgqql+rFKo23hC4VdCGEEEIIIRoQqaALIYQQQgifkC4uNZMKuhBCCCGEEA2IVNCFEEIIIYRPeLeLi6xBF0IIIYQQQtQDqaALIYQQQgifqOzi4p214t6a90yQCroQQgghhBANiFTQhRBCCCGET6jo8Egf9GNIBV0IIYQQQogGRCroQgghhBDCJ6SLS82kgi6EEEIIIUQDIhV0IYQQQgjhEyo6VFmDfgypoAshhBBCCNGASAVdCCGEEEL4hEdT8Gje6VfurXnPBKmgCyGEEEII0YBIBV0IIYQQQviEx4t90D2yBl0IIYQQQghRH6SCLoQQQgghfELVdKhe6oOuSh90IYQQQgghRH2QCroQQgghhPAJWYNeM6mgCyGEEEII0YBIBV0IIYQQQviEivf6latemfXMkAq6EEIIIYQQDYhU0IUQQgghhE+o6FC9VC/21rxnQuONXAghhBBCiLOQVNCFEEIIIYRPeDQdHi/1QffWvGdC441cCCGEEEKIs5BU0IUQQgghhE+oKKh4q4uLd+Y9EyRBF0IIIYQQPiFLXGrWeCMXQgghhBDiLCQVdCGEEEII4RMedHi8VC/21rxnQuONXAghRI3mTPqeIQG388iF/0ZVG/Oz9IQQ4twkCboQQpxlZjw/B0eFg30bD7Dim7W+DkcIIY5L1RSvbo2VJOhCCHGWiWoWWflCgTbdWvg2GCGEEHUma9CFEOIs89H2N/nl06V0uqwDTVrG+jocIYQ4LtWLa9DVRlyHlgRdCCHOMiaTkasfGujrMIQQQpwiSdCFEEIIIYRPqJoO1Uv9yr0175nQeCMXQgghhBDiLOTTBH3ixIl0796dwMBAoqKiuPbaa9m7d2+1MSNHjkRRlGpbjx49qo1xOByMHj2aiIgI/P39ufrqqzly5MiZvBQhhBBCCFFHHhSvbo2VTxP0FStW8Mgjj7Bu3ToWL16M2+1mwIABlJeXVxs3aNAgMjMzq7aFCxdWe3/MmDHMmzeP2bNns2rVKsrKyhgyZAgej+dMXo4QQgghhBCnzadr0H/55ZdqX0+bNo2oqCg2bdrEZZddVrXfbDYTExNT4xzFxcV8+umnzJw5kyuuuAKAL774gvj4eJYsWcLAgXKjlBBCCCFEQyRr0GvWoCIvLi4GICwsrNr+5cuXExUVRZs2bbjvvvvIycmpem/Tpk24XC4GDBhQtS8uLo6kpCTWrFlT43kcDgclJSXVNiGEEEIIIRqCBpOga5rG2LFj6dWrF0lJSVX7Bw8ezJdffsnSpUt588032bBhA5dffjkOhwOArKwsTCYToaGh1eaLjo4mKyurxnNNnDiR4ODgqi0+Pt57FyaEEEIIIWrkwZvr0BuvBtNmcdSoUWzbto1Vq1ZV23/zzTdXvU5KSqJbt24kJCSwYMECrr/++uPOp2kailLzzQFPP/00Y8eOrfq6pKREknQhhBBCCNEgNIgEffTo0cyfP5+VK1fStGnTE46NjY0lISGB5ORkAGJiYnA6nRQWFlaroufk5NCzZ88a5zCbzZjN5vq7ACGEEEIIUWeyBr1mPo1c0zRGjRrF3LlzWbp0KYmJiSc9Jj8/n7S0NGJjKx9f3bVrV4xGI4sXL64ak5mZyY4dO46boAshhBBCCNFQ+bSC/sgjjzBr1ix++OEHAgMDq9aMBwcHY7VaKSsrY8KECdxwww3ExsZy6NAhxo8fT0REBNddd13V2HvuuYfHH3+c8PBwwsLCGDduHB07dqzq6iKEEEIIIRoej6bD46VKt7fmPRN8mqBPnToVgD59+lTbP23aNEaOHIler2f79u18/vnnFBUVERsbS9++fZkzZw6BgYFV4ydPnozBYGDYsGHYbDb69evH9OnT0ev1Z/JyhBBCCCGEOG0+TdA1TTvh+1arlV9//fWk81gsFqZMmcKUKVPqKzQhhBBCCOFlGgqql574qcmTRIUQQgghhBD1oUF0cRFCCCGEEOceWYNes8YbuRBCCCGEEGchqaALIYQQQgifUDUFVfPOWnFvzXsmSAVdCCGEEEKIBkQSdCGEEEII4RMedF7d6mLixIl0796dwMBAoqKiuPbaa9m7d2+1MZqmMWHCBOLi4rBarfTp04edO3dWG+NwOBg9ejQRERH4+/tz9dVXc+TIkTrFIgm6EEIIIYQ4561YsYJHHnmEdevWsXjxYtxuNwMGDKC8vLxqzKRJk3jrrbd499132bBhAzExMfTv35/S0tKqMWPGjGHevHnMnj2bVatWUVZWxpAhQ/B4PLWORdFO1oz8HFBSUkJwcDDFxcUEBQX5OhwhhBBCiHrV0HKdo/E8uuoazAFGr5zDUebinV4/nPI15+bmEhUVxYoVK7jsssvQNI24uDjGjBnDU089VXkOh4Po6Ghef/11HnjgAYqLi4mMjGTmzJncfPPNAGRkZBAfH8/ChQsZOHBgrc4tFXQhhBBCCCH+obi4GICwsDAAUlJSyMrKYsCAAVVjzGYzvXv3Zs2aNQBs2rQJl8tVbUxcXBxJSUlVY2pDurgIIYQQQgifUNGheqlefHTekpKSavvNZjNms/mEx2qaxtixY+nVqxdJSUkAZGVlARAdHV1tbHR0NKmpqVVjTCYToaGhx4w5enxtSAVdCCGEEEKcteLj4wkODq7aJk6ceNJjRo0axbZt2/jqq6+OeU9Rqrdv1DTtmH3/VJsx/0sq6EIIIYQQwic8moLHS/3Kj86blpZWbQ36yarno0ePZv78+axcuZKmTZtW7Y+JiQEqq+SxsbFV+3Nycqqq6jExMTidTgoLC6tV0XNycujZs2etY5cKuhBCCCGEOGsFBQVV246XoGuaxqhRo5g7dy5Lly4lMTGx2vuJiYnExMSwePHiqn1Op5MVK1ZUJd9du3bFaDRWG5OZmcmOHTvqlKBLBV0IIYQQQvhEQ3qS6COPPMKsWbP44YcfCAwMrFozHhwcjNVqRVEUxowZw6uvvkrr1q1p3bo1r776Kn5+fgwfPrxq7D333MPjjz9OeHg4YWFhjBs3jo4dO3LFFVfUOhZJ0IUQQgghxDlv6tSpAPTp06fa/mnTpjFy5EgAnnzySWw2Gw8//DCFhYVcdNFFLFq0iMDAwKrxkydPxmAwMGzYMGw2G/369WP69Ono9fpaxyJ90Gl4vUGFEEIIIepTQ8t1jsZz/4qbMHmpD7qzzMVHvb9pMNdcF7IGXQghhBBCiAZElrgIIYQQQgif8KDgwUtdXLw075kgFXQhhBBCCCEaEKmgCyGEEEIIn1C1undbqcvcjZVU0IUQQgghhGhApIIuhBBCCCF8QtV0qJp36sXemvdMaLyRCyGEEEIIcRaSCroQQgghhPAJFQXVS91WvDXvmSAVdCGEEEIIIRoQqaALIYQQQgif8GgKHi91cfHWvGeCVNCFEEIIIYRoQKSCLoQQQgghfEK6uNSs8UYuhBBCCCHEWUgq6EIIIYQQwidUFO89SVS6uAghhBBCCCHqg1TQhRBCCCGET2he7IOuSQVdCCGEEEIIUR+kgi6EEEIIIXxC1by4Bl36oAshhBBCCCHqg1TQhRBCCCGET0gf9Jo13siFEEIIIYQ4C0kFXQghGrm5h1axs/hzzPZLaBKcxG3tuvo6JCGEqBVZg14zSdCFEKIRm7nnD9qZb2HstgeADCCDSVtWsvWWf/k6NCGEEKdIlrgIIUQjtWdXOh/snk2q2w/QYzI7CQwsp9RT4evQhBCiVtS/+qB7a2uspIIuhBCN1OTXFuC8XEWnVuBntXF3m98pJwCPR/N1aEIIIU6DVNCFEKKRat4ikuaJhwnS67goegcmvYdQYzlhZhtr0uf5OjwhhDipo2vQvbU1VpKgCyFEI/XQvy8l0Kih6awMDd9CrjOITzf2ZupvA5my/QdfhyeEEOIUyRIXIYRopKbsuZdCVxgGTaO5wcOruzqgbgzC4oEdyZ1gkK8jFEKIE5MuLjWTCroQQjRSna3bKXab+Cm/A4pepawgAJ0LDHbQOyCnsMzXIQohhDgFkqALIUQjlWC0k10SzOa8eI54dMRG52C0gc4DBifkFZb7OkQhhDghWYNeM0nQhRCikdJUFaXcTFZZOGYFnFgAKI9UqYhRScvN93GEQgghToUk6EII0QiVOCsoVQxM6vwT1i1G8h0BGHQeitu5scUr2OIU3tq7ztdhCiHECUkFvWaSoAshRCO0Je8QRzxhxAXl8uqA7/gl7zxKnQY8wUd7oGtkOWUNuhBCNEbSxUUIIRqhTYWrSS1rxaSMtpyvS2X3/FCKL/enedNsDqbFgKLQvXnjrR4JIc4NGnjtiZ+N+ZFtUkEXQohG6EjFAlLLwylz+5E6ykzwN6VoTiNmPKDToSkaK1Ntvg5TCCHEKZAEXQghGqF4Uw4eVSHEUo6+QsUTHYKnSE/zwBw0vQoGcCgaxQ67r0MVQojjkjXoNZMEXQghGiErTjJs4RTbLbgSAlBcbnDraBmeBzqNyk+MFRYfTvZ1qEIIIepI1qALIUQjY3c5CTM5aRacz6FVYVhzdKDTQZ5KntOCxeLAbjcDGgMTWvs6XCGEOC55kmjNpIIuhBCNzMfz1+KHnuScSGLT8tE8HkDD7FYwelzExRQRF5tPQtMcMsvyfB2uEEKIOpIKuhCi0dizYT/+QVbi2zbxdSg+5dJ56GrNp9xlpXybAbPLDW4PIcluNB1k5wVRYbcAGtsK02kT1tTXIQshRI2kgl4zqaALIepFYU4RT/R7gReHvYnb7a73+T8YN4PRFz3N3e3HsOyrVfU+f2Myamgv5pc14cFmG3BdbUVRPOh10KJCYXt2M2wO018jFQ6VyE2iQgjR2EiCLoSoF89fO4kty3bw+7frmDpmer3Pv+HnzVWvf5/7R73P35isyVlPFuHYgz0MHL6PnssyWZD9AZa4CA7uj0Vz6SobAGswvHUXX4crhBDHJV1caiYJuhCiXhiMf6+YM5iM9T7/XS/fitFswBpoYcSLN9f7/I1JhMWMRwU00DRQNBWAI1lFqJkWKDeglBihxEBKYYFvgxVCCFFnsgZdCFEvXvrx37x5z1SCwgN44P/uqPf5e113EQttX9X7vI3R4tQC0t2hZI93Y//NjS4QUtamwd50Qi1xlMeBhoYC+BnMvg5XCCGOS9MUNC9Vur0175kgCboQol74B/nxn28e93UY54TDFbMowop9eSEAaik8O+RV9CUuAlYdIDwggsKBwYSarHSOjvZxtEIIIepKlrgIIUQjYzIbsHnMKBdULiVSzAo5h/JQy8tRnU5KhgZgylew7XNxww8zfBytEEIcn4ri1a2xkgRdCCEamUBTPiadC+Mb4Ri+jaDLijY0bRMLbjehQSaUUg1dtgkcevb+IWvQhRCisZElLkII0choqoVAowtNc6HFwuBmg+izpxd5GQWExYSQ9M6reKyAAqiNt4IkhDj7SR/0mkkFXQghTpO9ws6YXs9yb9K/SNub7vXz6Q35ZNvMZOcEkbE/jGZ+zQGIiAsjbW8GnhJDZXKuADpILyz2ekxCCCHqjyToQghxmt5/bDo71+wlddcRXr5lstfPZ1bcZOyLIe/HeIpXxnHfCz9Wvffe6M/A7Ko2XkPzekxCCHEqjnZx8dbWWEmCLhq1j56cyfCEB5kz6XtfhyJO4OnBL9NfdxO3xj+Aqqq+DqfeRSdGVr0OjQ7x+vkcqg73fivKXzdAFf71tNDtq3ZTWlgGRsAJqIBLISYwwOsxCSGEqD+SoItGqzCniG/+bz65afl88u8va3XM+l/+ZLDlVq7yG86utXu9HKE4auOirQDkpRewe+0+H0dT/24bfwP3vX471z92JS/Of8rr5ztsiwBFAaXygaEoUJRXwtje/2H/5hR0OWb0LjDYwOCCMruzxnmyU3MYGng7AwzD+PatH2scI4QQ3iRPEq2ZJOii0bIGWFB0lX/4DKba3e884z9f43a6cdpdTP/PHG+GJ/5Hq/MTAbAGWmndvaWPo/GOYU9cw0OT78Lkhaeo/pMelcj2+ZUPI1LAaNBRml9K1UoWxYOmgEcPHh2s3Z9a4zxf/9+P2MsdaKrGN29Kgi6EOPNkiUvNfJqgT5w4ke7duxMYGEhUVBTXXnste/dWr2pqmsaECROIi4vDarXSp08fdu7cWW2Mw+Fg9OjRRERE4O/vz9VXX82RI0fO5KUIH7D4Wfjv6pcZfE8/pm6aVKtjLr3+oqrXfW7u6a3QxD9M3TSJL1Le4/vC6WckgT2buVQ3ra25JLbPokm/wwS1KmDuCyOJb9uEqx8eSETTcG4Kj0czAX9tr/yyosa5+g3vxdE2wT2GdD1j1yCEEOLEFE3TfHb30KBBg7jlllvo3r07brebZ555hu3bt7Nr1y78/f0BeP3113nllVeYPn06bdq04eWXX2blypXs3buXwMBAAB566CF+/PFHpk+fTnh4OI8//jgFBQVs2rQJvV5/0jhKSkoIDg6muLiYoKAgr16z8L3U3UcwmPQ0aRnr61CEqDOn6mT6nj4Ue/zIdIbSzprOyFYr2LNuHx16tsVgMDD6o3ksTjuE3laZfxtD9Wx+5tEa5yvKK6E0v5T4tk3O7IUIIc6ohpbrHI3ngm/Hovc3e+UcnnIHf974VoO55rrwaR/0X375pdrX06ZNIyoqik2bNnHZZZehaRpvv/02zzzzDNdffz0AM2bMIDo6mlmzZvHAAw9QXFzMp59+ysyZM7niiisA+OKLL4iPj2fJkiUMHDjwjF+XaNgS2jf1dQhCnDKTzkSqK4JQYxkJ1lx2bY3kqo7DQYPgiEC+zfmMCxKasjT5EHpP5aqXBP3xfzGFRAQREtG4fnEJIcTZrkGtQS8uruzVGxYWBkBKSgpZWVkMGDCgaozZbKZ3796sWbMGgE2bNuFyuaqNiYuLIykpqWrMPzkcDkpKSqpt55rCnCLmT/2VsqIyX4cixHEVZBUyZdQnbPx1i69DaTD2FqTye3ZLNhcksj6/BTuesVatPS/OK0VVVe4a2B3lr2Y5ClBUYfdZvEIIcSIaoGle2nx9caehwSTomqYxduxYevXqRVJSEgBZWVkAREdHVxsbHR1d9V5WVhYmk4nQ0NDjjvmniRMnEhwcXLXFx8fX9+U0aG63m9uaPcSURz7htuYP+zocIY7rgfPHMf/9X3l68Cuk7pb7SgBe2/ENdoeJdemJrMtoidoysOq9Jq1j0Ol0FJRUoOkrHyKqAsP7dvFdwEIIIerMp0tc/teoUaPYtm0bq1atOuY9Ral+F66macfs+6cTjXn66acZO3Zs1dclJSXnVJJekleKy+kGoKLE5uNohDi+8uKKqte5R/JleRLQOTyRTfnFHL27s+jhJrx44zD8Q/zoe/MlAAT4mdBV/F2BSTtS5JNYhRDiZFSUqmc6eGPuxqpBVNBHjx7N/PnzWbZsGU2b/v0LOCYmBuCYSnhOTk5VVT0mJgan00lhYeFxx/yT2WwmKCio2nYuCYsJpec13TFajAwY2cfX4QhxXGM+fJDI+HD63NyTbv07n3T85qXbeffRz8jLKDgD0flGS0tTwoPK0CkedIpKVJCdIQ/0r0rOAUwGA3pjZQqvAD9v3HPMPBOuf4MBhmE83N37fduFEELUjU8r6JqmMXr0aObNm8fy5ctJTEys9n5iYiIxMTEsXryYLl0qP6J1Op2sWLGC119/HYCuXbtiNBpZvHgxw4YNAyAzM5MdO3YwaVLtWu+di16Y96SvQxDipAbc2ZsBd/au1djMlGyevOJFAJZ+9Ttzc6d5MzSfeW3zNwREeGgZnQ9ovJ70SI3jHCYwuv56rT/26a2rv18PQPKmg6QnZ9KktXQ1EkKced7sV96Y+6D7NEF/5JFHmDVrFj/88AOBgYFVlfLg4GCsViuKojBmzBheffVVWrduTevWrXn11Vfx8/Nj+PDhVWPvueceHn/8ccLDwwkLC2PcuHF07NixqquLEOLsl5f+d9XcVoulW+88/DGLZiyn28DzmTD3CW+GVq/M/g6cHgMaKgp64q2RNQ9UwWOtrKDXdKNURJMw8tILMPuZiE48zhxCCCF8wqcJ+tSpUwHo06dPtf3Tpk1j5MiRADz55JPYbDYefvhhCgsLueiii1i0aFFVD3SAyZMnYzAYGDZsGDabjX79+jF9+vRa9UA/F+RlFBAUFoDJYvJ1KEJ4Tcde7el7yyVs+30Xd/znppOO//GDRUBlJTk7NYfohChvh1gvQsyhFGjlgB4NjSO2fML8wqqNUVUVvQY6p4YlOR+/DYeZ6pnBQ2+NqBozM+U9tizbSdIllb3ThRDCF1RNQfFSpVuVCvqpqc0zkhRFYcKECUyYMOG4YywWC1OmTGHKlCn1GN3Z4f/ueZ9fpy1Dp9fx0bY35SY7cVYbP2tMrcf6BftRUVyB3qgnNDrEazHVt3xPKWq2GfficNBruFvqIbz6mEUrdqMUedCjI2hxMqgac9/+iT43X0z7i9oAYDAYarWuXwghxJnXIG4SFd5zdJ2p6lH57cuVPo5GiIZj5oF3eWjySGYeeK/Wny653W4e7TmeG6PvYeW3a2scs3X5ToYG3s61oSNI2XG4PkMGQIcHz9pgcCpg0zN9ygqutN7KQOPNLPliBQCxUcF4AnU4w0Az6Kr6GPgF+dV7PEIIcTq81gP9r62xkgT9LHfV/f0BMPuZGPqgPFVViKOCwgK5/rGriGwafvLBf5n334XsXpdMcW4Jbz/4UY1jPnzic+zlDsqLK/joyZn1FW6VCqcfxmgHR1eX29cfwOVwo3pUvnp1HgCdz2uKx0/BXAzlA5NwJoQzbsYo+QRNCCEaCUnQz3L3TryNxeo3/FT2ZZ0SESHEsVp1+bvTVGR8zX+e/nfZyIWDvfCAIM1DSVcH7suKcfQtZcS4a6reuuymi/8e5waDDbRgP+yXtoFWNbedFUIIXzraxcVbW2MldwYJIUQtdbm8IxN/fZa9fyRz07iraxxz96vD6TqgMyarsWq9d33qFnmY3eVxuFq5sBhdXNKnO3MyPsJhcxKbWJmEH0jNxuRUUQ0KendlF5eLzmtW77EIIYTwDknQhWigVFXluatfI2X7YR5++y56XXeRr0MSVFbIT3ZzZec+53nt/P5GO0a9ilGvoaeyv3lYTGi1MRu2pYELnCEKuDXQQYisPxdCNEDSB71mssRFiAZqycwVrF+4mdy0fCaNfM/X4YgGQq9oOFx6nItt6LaW1TjmxsHnE5SvgEsFRWH04J5nOEohhBCnQxJ0IRqoJq3+frJjcETgCUaKc4Wq2km3haK9Uojh1QLsY8qqOrf8L4PBQHmwgsuqw2OEt3+rueOMEN5UVlSGqh77FFsh/peqKV7dGitJ0IVooM67pB0T5j3J9Y9dydRNr/s6HNEAqLiwGJzok+1oVPZx2bx0R41jPSbQu8BYrmEs0fhl694zGqs4t706/G2uC7uLIf63UZBV6OtwhGh0JEEXwgucTle9zHPJNd15aPJdBIQE1Mt8onHbnL+KUrcfxtGBKH4KRCrc8+rwGse+eGt/DHYNgwsMbnh92m9nOFpxLlvzwwYAXA43y+es8XE0oiGTPug1kwRdiHr27NCJXGUZznXhI3Hanb4OR5xFil17KXGbMF1sxLQwGtM34cfcIHpUi9AQdO7K304a4HJ7zmCk4lzX++bK+x7MfmYuv+1SH0cjROMjCboQ9WzDL1sAKCssZ8OvW30bjPCKnz9byvCEB3nj7jN7826fqFHo0AMKOrS/XtessNSGx6Sg/rUEc2hv73WWEeKfnvjsERbYZ/FT2ReERAT5OhzRgFVWur3VB93XV3fqJEEXNUrZcZjCnCJfh9EoHW2xZw200LV/Rx9HI7zhvw9+RG5aPoumL2fX2jO3tnt1wZ/klpuqvi62+bNq3h9c5T+c6yPvIjs1p+q9Pt1bg1HB46/gDlBIiK650i6Et5hMRl+HIESjJX3QxTHevHcqv3y2FBR4e+VLnHdJO1+H1KhMWvwfyorK8AvyQ6eTfwOfjawBFsqKygEIjztziW+sNYoKp5VMzYKmQbQplE+e+gKnzYXT5mL6c3N46vPRALzz2HTcaGjWyhL6noycE00thBA+IX3QaybZgzjG+p83V77QYJnc3HNKAkICJDk/i3245Q2GPNCf1xc/R3RC1Bk7r0WnUFriT156EPmZQTjt/nT6n6UrPYZ0rXq95fc9aH5gyfMQst/FH9tTz1icQgghTo9kEGeQqqr859rXGdn2Ubat3OnrcI7r5ievQdEpWAMtDBs31NfhCNHgRDWL5LGp93NBv05n9Lz+hgCUUgP6UhO6EiNxWgRjP36Q1xc/x4db3qD3sL8fSHTfS8PQ2VUC01VM5VCxueiMxiqEELWheXlrrGSJyxn04/u/snb+RgBevOktvs3+1McR1ez6x67i+seu8nUYQoh/CDeHg12HhoaCgt5deZNoTf9QuPiqC+C3ZWc6RCGEEPVAEvQzKCohoup1QKi/DyMRQjRGKcX7MfvbcZZbAY2xvS4CIDs1B2uglaCw6k+c1dBR2kTDUqSixZlqmFEIIXxL1qDXTBL0M+jiod0Z+8lD7F67j3tfv83X4ZwSVVXZ/+dBmic1w2SRX/hCnEkfHXyRKy+yo1c0VA1ahjzEZ+Nn8dVr80CBib88S7f+navGm93g9tNT6q+nVaR0cRFCiMZC1qCfYYPvvpyxHz94TKWrsXigyzgeufBprgsbib3C7utwhDinlKkaur9WVSqAwaBj+Td/3citwaJpfy9pSTmQjcfpQaHyL/oHrrzwjMd7Ltq1di83RN7Nrc0eIOdwrq/DEaLhk0XoNZIEXdRJ6o4jADjtLnavS/ZxNEKcW1yqG73mIj0/GKdDwaSzVN3UbTQbuOXf11aNTd6ThWrUobhB54SXvlrqu8DPIf99+GNK8kvJO1LAB+M+93U4QohGSpa4iDq57KaLWfHNGmITo6seyCOEODMCdXZ+XN+NCnvlGvRRrfO56r7+XHVf/2PGzn3+S3Tdo9ChRwNsZc4zHu+5qPUFLTi4tbKlZZI8Q0KIk/PiGnRkDbo4Vzw7+188O/tfvg5DiHNSnP9VVNiKUVAAhfc3rGPywGM7LjmdLg78mYK+VSCE+KMolUcI7xv36cOc3/c8AsMCuejKC3wdjhCikZIEXQghGondRftQdJGg6tHQGNGp5gTQZDIS1SwCW3IhznZ+aEaNIJ38dX+mXHF7b1+HIESjoWmVm7fmbqxkDboQQjQSLnJQg9yoVjdakAuL5fhJ98yD73HH6KEYXGAs1zBKPUYIIRoN+RtbCCEaCaPeRYDFRpnbH4PBRZvg8OOO1el0BIX4o3k0ND1oLs8ZjFQIIWpH+qDXTCroQgjRCNjdTnRouDP9MRQaUXKsOFX1hMcEBVnRzIBRoVR1nZlAhRCikVq5ciVDhw4lLi4ORVH4/vvvq70/cuTIynt6/mfr0aNHtTEOh4PRo0cTERGBv78/V199NUeOHKlzLJKgCyFEI2AxmChz6XC7Kz/41DQdGcUlJzymVWIUKJUVpBOn8kII4SOa4t2tDsrLy+ncuTPvvvvucccMGjSIzMzMqm3hwoXV3h8zZgzz5s1j9uzZrFq1irKyMoYMGYLHU7dPMWWJixBCNBKXBh/kUGwzsrPCCAkpo0V42AnHL1q79+8vGvHNUkIIcSYMHjyYwYMHn3CM2WwmJiamxveKi4v59NNPmTlzJldccQUAX3zxBfHx8SxZsoSBAwfWOhapoAtxBm1cvJX5U39FPcnSBHHu2b8lhcKcouO+b3c7yXUGckGHFK7st4kLu+w76ZzntYoGFRQVFEnQhRAN0NEuLt7a6tvy5cuJioqiTZs23HfffeTk5FS9t2nTJlwuFwMGDKjaFxcXR1JSEmvWrKnTeaSCLsQZsmzOal699W0A/liwiVd+Gu/bgESD8dod7/Dbl7+jKPDOuom0697qmDG/Ze/Ao9Oj/PVvO30tMu7zWsRK/3MhxDmvpKT6ckCz2YzZbK7zPIMHD+amm24iISGBlJQUnnvuOS6//HI2bdqE2WwmKysLk8lEaGhoteOio6PJysqq07mkgi7EGbJj1Z6q14d31f2GEXH22rhoK1BZ7Vn5zdoax1wS2QZUUP+qCnnUk6fe0RFB+F1YRvexG2g/aCMfjp9+wiq9N6mqyvpf/iT3SL5Pzi+EaKA0L29AfHw8wcHBVdvEiRNPKdSbb76Zq666iqSkJIYOHcrPP//Mvn37WLBgwYkvUdNQlLqVSyRBF+IMueulm2nSOobAsABGv3+vr8MRDciwcVej6BT8g/24fsyxTwYFOFK6jlCTHZeqx6EaiNSXn3TevIoK2l6cjL1UIe1uN9++toC724+p5+hrZ1zfCTxz5URuS3iI1N3yD1QhxJmTlpZGcXFx1fb000/Xy7yxsbEkJCSQnJwMQExMDE6nk8LCwmrjcnJyiI6OrtPcssRFiDMkICSA6Xun+DoM0QANe+Iahj1xzQnHpNsP09l0hAOOKBQ0+gYePOm8qtuDCx2ebLWqklReXFEfIddZ8p+V8WqaxqZFW0lo39QncQghGpYz0Qc9KCiIoKCgep8/Pz+ftLQ0YmNjAejatStGo5HFixczbNgwADIzM9mxYweTJk2q09xSQRdCiEbAoOvI/LLO2FQzFaqZn8vanvSYlXsOsWFrIjtCmuG81B9jkImRL91yBqI91i1PXYveoCcyPpwr7+vnkxiEEOJEysrK2LJlC1u2bAEgJSWFLVu2cPjwYcrKyhg3bhxr167l0KFDLF++nKFDhxIREcF1110HQHBwMPfccw+PP/44v/32G5s3b+b222+nY8eOVV1daksq6EII0cCpqsqs22ZjfsNEZSlcodxjPelxXZrF4jmi4VSNOJ6Ix2OwMHzQ9V6Ptya3PXsjtz17o0/OLYRo4BpIl6mNGzfSt2/fqq/Hjh0LwIgRI5g6dSrbt2/n888/p6ioiNjYWPr27cucOXMIDAysOmby5MkYDAaGDRuGzWajX79+TJ8+Hb1eX6dYJEEXQogG7o+Fmzm8/DCBFaHszYtFA7pEOk56XMuYCNBrVa3GXGrdHpQhhBDnkj59+qCdoDfjr7/+etI5LBYLU6ZMYcqU01vSKktchBDiOJx2J7/N+p2ivBM/sdPb2nZrgaJTSCsOR0WHhkKBLbZWx3qyTKgqqCoMCj3fu4EKIUQdHV2D7q2tsZIKuhBCHMftiQ9TmF2MwWTgh6IZmCwmn8QRFhPKl4emMmTeNGhSDigkWZrV6ljTZj88+UYUu47zByR6N1AhhBD1QiroQghxHIXZxQC4nW4yU3JOMtq7IpuGYy4LhO0BsMOfVp64Wh2n8ygYDpswZBvo2T7By1EKIUQdnYE+6I2RJOhCCHEcA0b2QW/U0+myDg2iLeDYoRcTaDTRMSqGe3p1P+n4T2evRucBgxN0Lgj2txx3rL3CzqM9xzOizWj2b0mpz7AbnLKiMtIPZPo6DCGEOK46L3FxOBysX7+eQ4cOUVFRQWRkJF26dCExUT46FUKcXZ747BGe+OwRX4cBVHZymVE4lXb9HDg9enS64Sc9Zvm6fah60P91b+ianYe4vGubGsd+NG4mu9dVPmxj4vD/8umut+sr9AZl9x/7eKzns2iaxpAH+vPY1Pt9HZIQ5zjlr81bczdOta6gr1mzhltvvZWQkBD69OnDmDFjeOmll7j99ttp1aoVrVu35o033qC0tNSb8QohxDkp055FiNmGUafib3SxJHvpSY/p37sdmgrlkWCLhPW70447tmnbv5fMhMeF1UvMDdGSL36v6tKwZv5GH0cjhBA1q1WCfs0113DjjTfSpEkTfv31V0pLS8nPz+fIkSNUVFSQnJzMs88+y2+//UabNm1YvHixt+MW54An+r3AVf7D+eiJz30dihA+l1p2hBKnhb1FURwqDcPuOXmbxeLDJTjCNTz+Cm5/hcOG8uOOvf6xqxj93r0Me/IaXl5YP4/BbohuHDsEi78ZRVG4YcxVvg5HCCFr0GtUqyUuAwYM4JtvvsFkqrmDQYsWLWjRogUjRoxg586dZGRk1GuQ4tyzZ8N+tizbAcC3k3/i/jfu9HFEQvhWoVMj1xaAhoLdY6TY6XfSY3pd2pYPp2/B3dYDelANJ+6DfvVDA+sr3AYrNjGaH0u/8HUYQghxQrWqoD/yyCPHTc7/6bzzzqN///6nFZQQTVvHoNNX/u8ZEhXs42jE6Xj7wQ8ZbLmVcX0n+DqURu1w+QYCTA6OloXaBp38z0WXC5qjtdMg2AP+HpIN6V6PUwgh6kQq6DU6rT7oZWVlqKpabV9QUNBpBSTObd++9SPTn5tNTMtoPtk1mc1LtjNgRG9fh3XOUFWVryf9QHRCJH1v7VUvcy74eAlosHXFTlJ2HCYxqXb9u8WxmvoXEedXjKJpxPpF1uoYZ7Cr8jYpBbLsvn3gkhBCiNqpc4KekpLCqFGjWL58OXa7vWq/pmkoioLHI4+SFqdu+n9m47A5Sd2RxrblO8+Jj9wbkueufo31CzcDUFpUXi/f/9CoYAqzi9Eb9cS2iDrt+c5V8ZaezM/cTY4tGIPiIdxUuwTdT7VQlg54dLSMDfVukEIIUVeaUrl5a+5Gqs4J+m233QbAZ599RnR0NIrSeC9eNDxNWsdycGsqKHBez3a+Dueck7E/u+r1gS2H6mXOzw+8y8pv1tJt4PlY/I7fh1ucWJ6jhOyKEBQF3JqBb9M2cGfipSc9blT73ry+ZBUAB9Olgi7E8Xz71o98/sI3tOyUwJsrXkCnk0fFCN+pc4K+bds2Nm3aRNu2bb0RjzjHvbfhNRZ/vpIOF7dpEA+GqW+LZiwjJDqYCwdd4OtQavTkjEd48cY3CQwL4P437qiXOS1+FgaM6Fsvc50rZk2cy3eTf+LCQV146vPRAHx7YB2qBnoFNA0uiai5n/k//bxsN8pfvYBVdyNekCmEl332zCxcDjc7Vu9h9ffrufT6Hr4O6ZygaZWbt+ZurOqcoHfv3p20tDRJ0IVXGAwGBt99ua/D8IqJt/+XpbMqK5mPTb2fIQ80vJup21/Uhq/SPvR1GOe86c/ORtM0lnyxkluevo6E9k0xaoG4C+04XAZMQXZaBkbXaq4D5nQUhwmj2YPBbfZy5EI0XuFNwsg6mAMKtOic4OtwxDmuzgn6J598woMPPkh6ejpJSUkYjcZq73fq1KneghPibPK/S0a2/76rQSboomGwBlqoKLGhKAqh0ZXdWl7ocj3XzZoFKKhF/rWeK7xVMTqrE0UBRZOP7IU4no+3vclPHyzmgis60qRlrK/DOXd4s9vKuVRBz83N5cCBA9x1111V+xRFkZtEhTiJR9+/lxdu+D8s/hYe+D/p6y6O79NdbzPvnYX0veUSgsICAdidllt5w5NSt49tjRYH6l/3CmmoJxktxLnL4mfhxrFDfR2GEMApJOh33303Xbp04auvvpKbRIWog06Xncd3udN8HYZoBCLiwrjvtdur7Vu4ehemQlAVjQhd7ZeqFBUFYQ4sx2hQKbdZ6ztUIYQ4PdLFpUZ1TtBTU1OZP38+rVq18kY8QggharAvN5+gVA2DE1DslFXYCahFVxydLpyMQhOaBibpSiGEEI1Cnf+2vvzyy9m6das3YhFCCHEc5ZoLvfOvLzRYuelArY575+Lr0Kk69Flm2pbFU2Z3eC9IIYSoI0Xz7tZY1bmCPnToUP71r3+xfft2OnbseMxNoldffXW9BSeEEKKSzaRiCAVLIahG6FbLLhPdo5txY0A3vt2/k12leTzy7Y/MuP1GL0crhBDidNQ5QX/wwQcBePHFF495T24SFUII79D8NYJ65FBe4YfNYSUqKKBWx6mqypbCpejskQQcdqBGub0cqRBC1IF0calRnRN0VZUuAEKIYxXllTD5vg+ITojgwbdGylP46lmLdqn0abkfRQGnWwc8WavjPtw3gQuSdqK+kYTiVijcvg313mHy8xFCiAaszgm6EELUZPygV0j+8yAAwRFB3PasLKOoT03Di8i3+1Ng8yMhOL/Wx+W7s1EdBpS/Cuceh4bb6cZkMXkpUiGEqAPp4lKjWpVQZs+eXesJ09LSWL169SkHJM4Oqqoy/qpXubnJffw263dfhyPOALfr76UTDrvzBCPFqVh3uDnzD3Ti94zWLDhwQa2PG9XmTTxmCOlRgmJUuWRQB0nOhRCigatVgj516lTatWvH66+/zu7du495v7i4mIULFzJ8+HC6du1KQUFBvQcqGpcVc9aw4efNFGQW8fYD8uj4c8HLP/6bjpe25/LhvRj54i2+DufsUxyEhgJoFDlrn2DvSy3gl88uY48aD22CePK1W70XoxBC1JXm5a2RqtUSlxUrVvDTTz8xZcoUxo8fj7+/P9HR0VgsFgoLC8nKyiIyMpK77rqLHTt2EBUV5e24RQPXpHVM1eugiEAfRiLOlKhmkby14tibx0U90bsxGDyoqoJeV/ub8Wet3IK+wknEN7vwAPdd8BQzdrzpvTiFEEKctlqvQR8yZAhDhgwhPz+fVatWcejQIWw2GxEREXTp0oUuXbrITUdelJ6cyaOXPIPL4eKFeU/S5fKOvg7phNp0a8XEn5/hz9+2M3z8db4OR4hGL0gLpsKQgdGg4i6v/RNBHxrUgzU//snRlZi5abVfvy6EEF4nXVxqVOebRMPDw7nmmmu8EYs4gY+enElJXikAHzw+gw83/5+PIzq5bgPPp9vA830dhmgg/lj4J7vW7uPWp6/FUosnYIrqyqzZBJhdgIIxqKzWx7VtEsWSL59idO8J5B/M5YbHBnsvSCGEEPVCSt6NRNcBnated7y0gw8jEaLuNi/dzrNDJjLrle8Y1WO8r8NplIKDHfDXGvS6WL0+mWtufocjoSE89Pmj3PX8TV6JTwhvUVWVu9o9Sn/dTTwz5FVfhyPqm6xBr5G0WWwkrn5oIC07JVBeWsGFg2rfwUGIhuDgttSq1wUZhT6MpPH68rKx3LXhNZyankvC29b6uIlv/Yyu2I1Og7dfW0DrVlG0aRfnxUiFqF8Ht6VyZF8mAOsXbvZxNEKcGZKgNyLnXdLO1yEIcUquGTWIVXP/IH1/Fo++d6+vw2mUmodEsqx/3W/u9DMbsf/P13v2ZkqCLhqV5knxWAMs2MrsNG0T6+twRH2TPug1kiUu4qyXsuMw7z76GWl7030dyjnLYDAweeVLfJ3xMb2uu8jX4TRK2zemMPrm9/ls8q91Om7KG7dREW1E1YPLqiO+nXTZEvXj1eFvM8AwjHs7jfXqU8YNBgNzC6bx4ZY3+HTX2147jxANSZ0T9BdffJGKiopj9ttsNl58sW4t1lauXMnQoUOJi4tDURS+//77au+PHDkSRVGqbT169Kg2xuFwMHr0aCIiIvD39+fqq6/myJEjdb0scZZyOl082OUJfnj3Z+7v9LhXf4kI4U3PPDid5F3pfP3ZSrasP1Dr43bm5GAPNVDc0oqtuYUubeO9GKU4lyybsxpN1UjdkcbeDfu9ei6DwUCLTs2lW9xZSNG8uzVWdf4//YUXXqCs7NgOAhUVFbzwwgt1mqu8vJzOnTvz7rvvHnfMoEGDyMzMrNoWLlxY7f0xY8Ywb948Zs+ezapVqygrK2PIkCF4PLXvEyzOXs4KB6qnMil3uzySoJ/AtpU7K7sFFZT6OhRRA6ej8kmtGnAoObvWx+1IzeJo23TVo7HnUO2PFeJEYltEA2A0G0ns2MzH0QhxdqnzGnRN01CUY9f0bN26lbCwsDrNNXjwYAYPPnHLL7PZTExMTI3vFRcX8+mnnzJz5kyuuOIKAL744gvi4+NZsmQJAwcOrFM84uwTEBLADWOHsHTWKgbf0w+DQW67qEna3nQe7zMBgN++XMmc9I99G5A4hjXUj4oiG+gU2p1f+2To3v4X8sW8DWhqZSkpPNjfWyGKc8z0ve+wdflO2l7YSlqnilMnfdBrVOsKemhoKGFhYSiKQps2bQgLC6vagoOD6d+/P8OGDav3AJcvX05UVBRt2rThvvvuIycnp+q9TZs24XK5GDBgQNW+uLg4kpKSWLNmTb3HIqrbvHQ714TcybDYe8lOzTn5AT7y4P+N4OuMj7nrJXn8/PFkHPi7qlpaUPse23X19JWvMNB4s7RKOwVXP9AbfXQAnQa2p915TWt9nJ/JxNfP30HvDs2ZOu5GIkMDvBilOJfodDq6XN4Rv4DaPzhLCFE7tS4nvv3222iaxt13380LL7xAcHBw1Xsmk4nmzZtz8cUX12twgwcP5qabbiIhIYGUlBSee+45Lr/8cjZt2oTZbCYrKwuTyURoaGi146Kjo8nKyjruvA6HA4fDUfV1SUlJvcZ9rnj/sWlUlNioKLHx0ZNf8Nycsb4OSZyii668gIuHdmP3H8mMfOlmr5yjoszGxl+2AJWt0uwVdqm61cGn3/+BFmxgzYEM0jMLaRIbevKDAKfTzUN3fYLL6SFtTRpz5j7m5UiFEEKcrlon6CNGjAAgMTGRnj17YjQavRbUUTff/HeikJSURLdu3UhISGDBggVcf/31xz3ueMtwjpo4cWKd18uLY3Xo2ZZDO9MA6HJ5Rx9HI07Xiz885dX5LX5m/IKsVJTY8AuyntPJ+b1J/yJ11xG6XN6RSUv+U6tj1CAdxQEurAeKcTmctT5XRnohLmflIvT8PO99OtJQpCdnkp9ZQKfLzvN1KEIIccrqvCC3d+/eqKrKvn37yMnJOeamu8suu6zegvun2NhYEhISSE5OBiAmJgan00lhYWG1KnpOTg49e/Y87jxPP/00Y8f+Xe0tKSkhPl46G9TVvz58gO6DzicoPEB+GYqT0ul0zMn4iI2/bqXbwM4nP+AslX4gk9RdlZ2mNi/dXuvjiptqxL25A51H4+GuT7Mw/7NaHRcTGww60FTwCzq7/1G08dctPD34FQCuuKM3T80Y5eOIhBAno+C9biuNtwv6KSTo69atY/jw4aSmpqJp1b+jiqJ4tXtKfn4+aWlpxMZWPqiga9euGI1GFi9eXLX+PTMzkx07djBp0qTjzmM2mzGbzV6L81wiPa1FXVj8LOf8/zOxidH4h/hRXlRBTIva9yR3OxzoPJV/53oqXLU+btfeTFx+lZ94lmqn18Uo/UAmsYnRDbbV3ap5f1S93rp8hw8jEUKI01PnBP3BBx+kW7duLFiwgNjY2BMuJTmZsrIy9u//u3dqSkoKW7Zsqbr5dMKECdxwww3ExsZy6NAhxo8fT0REBNdddx0AwcHB3HPPPTz++OOEh4cTFhbGuHHj6NixY1VXFyGEaEh0Oh3f5nzK4V1HaJ5Uu24sdrcbZ5SJ8laBWA+WEd2nRa3Pd37HeMyBJipcLvwsJlRVPaUE+/7Oj5Oy/TB+QVa+y/usQXZEuu3ZG1n57TpsZXZGvuideymEEPVMniRaozr/DZucnMy3335Lq1atTvvkGzdupG/fvlVfH112MmLECKZOncr27dv5/PPPKSoqIjY2lr59+zJnzhwCAwOrjpk8eTIGg4Fhw4Zhs9no168f06dPR6/Xn3Z8QgjhDUcfulJbBwvywQjpd7UEDZ47wT04/6TT6bB53KAoVDhcbNudzvnn1X1JX8r2wwBUlNg4uOUQbbqd/u+A+hbZNJy5edN8HYYQQpy2OifoF110Efv376+XBL1Pnz7HLJP5X7/+evJHWlssFqZMmcKUKVNOOx4hhGiIOkRFoytT0P311+W6g4e5LDGx1sd7jAo6p4aqg5Awv1OKodvAzmz8dSvRzSNpdUHtK/hCCHFC0ge9RrVK0Ldt21b1evTo0Tz++ONkZWXRsWPHY7q5dOrUqX4jFEIIgU5TUKj8ffPV5u082a93rY91+yt4zBqaTsH+1xNJ62riz8+e0nFCCHFCkqDXqFYJ+vnnn4+iKNWq3XfffXfV66PvefsmUSGEOFdpHlB0lV0J2kdF1OnY7t1bsCI5BRRwy+o/IYRo8GqVoKekpHg7DiGEECdgtlW2SlSAcOr25MZN6UdwBla2MvtsxQbeun2Id4IUQog6UjQvtlk82yvoCQkJ3o5DCCHqlaqqPH/tJA5sPcSDb47gshvr90nHZ9KRgiJUFXRUfmLbNbFpnY4vNrrhr0YJmwuzvRKjELXx3NWvsXPNHoaPv4Ebxw71dThCNFh1vkl0/vz5Ne5XFAWLxUKrVq1IrMPNS0J42y/TlrLux03c9cqtJLSvW2IjGq9ls1ez7qdNAPzf3e836gR93b60qocNacCdl3Sp0/FhgVZyyysAaB9dt+UxQtSXrct3Vv2Z/OTfX3Lj2KG43W4Wf76SDhe3kb+fz1WyBr1GdU7Qr7322mPWo0P1dei9evXi+++/r/Z0TyF8Yd+fB3nznqkAbFm+g+8LZvg4InGmxLWMrnodGB7gw0hOX7+klvxn/hIUmwu/YqiwOwnwq/1TQYdcEcH29J8wmdw8dv6NXoxUiOOLbRHF0Tudg/76M/lI939zcGsqKPDxtrdofgotQI9yu93c02EMmQdyGDCyD+M+fbieIhfizKvz0yoWL15M9+7dWbx4McXFxRQXF7N48WIuvPBCfvrpJ1auXEl+fj7jxo3zRrxC1Im9zFb12n2K3StE49T+oja8+MOTXPfoYKZuOv6ThRuDEau+QrOWE7vBSeg+J3ff8kGdji9xTaddk1xaRBYx58iDXopSiBOLahbJe39M5I7/3MgnOycDkJ6cWfmmBrvW7j2t+f9cso2M/dlomsbiGctPM1pxxmhe3hqpOlfQH3vsMT766CN69uxZta9fv35YLBbuv/9+du7cydtvv12ty4vwDrfbTUWJjaCwwJMPPkd1uuw8rh8zhD+XbOW+Sbf7Ohxxhl08tDsXD+3u6zBO27bcTOK26VBQASjML6vT8X5GFQ09oJ3W05+FOF1turWq9pCrkS/ewvTnZhPbKpoBI/uc1twderTBYNTjdnlIOI1KfE3cbjcfjP0cTdN4aPKIY56kO/u1eWxduYuHJ48kvm2Tej23ODfVOUE/cOAAQUFBx+wPCgri4MGDALRu3Zq8vLzTj04cV2FOEbclPIzL4eLSG3rwn28e93VIDdZDb43wdQhCnBYdegrbKlgzVRQVwjuE1en4EoeJQLMbUPCc4OFwQpxpN44dWm83iwaEBPBd/jT2/3mQpF7t62XOo9685wOWzFwBQHlROf+e+WjVext/3cKn42cB8K9N/+Hb7E/r9dxnO+niUrM6L3Hp2rUrTzzxBLm5uVX7cnNzefLJJ+nevbJSlZycTNOmcrOHN/3+3R+4HC4A1i3Y5ONohBDeNLnn1djidaTcaOLgjSYee772bRLXrNjDT39cwC/727DmcDN2Zd3gxUiF8C2/ACudLjsPna7O6c0JlRaUVr0uKaj+CZbD7qp67fGo9Xpece6q8//Bn376KSkpKTRt2pRWrVrRunVrmjZtyqFDh/jkk08AKCsr47nnnqv3YMXf+tzcE2tA5U1ivW/qeZLRQojGLHlxCrpcHZqmQ+8x0LNps1of++4bPxOxUCM7N5z9aXG80eNa7wUqhA989uws+utuYmjg7eRlFHjlHP+eOZqkS9pxXs+2/Hvm6GrvXXJNd24YO4R2F7Vi4s/PeOX8ZzVN8e7WSNV5iUvbtm3ZvXs3v/76K/v27UPTNNq1a0f//v2r/sV67bXX1nec4h+CwgKZXzITt9t9zFo4IcTZ5fuvV6MbGAXOynuetqRncH6TuFod271nK/K+30zLj9206RBLwgPSXUucXX6cuggAe7mD+e//wt0vD6/3cwSEBDD595eO+/6D/ydLKUX9OqXMTlEUBg0axKBBg+o7HlFHkpwLcfZToq3gAoMdNAMEW2v/JNF/jR9K+6QmOBwurrnpIi9GKYRvXDy0G4s/X4FOr6PfbZf5OhxRV9IHvUa1yu7eeecd7r//fiwWC++8884Jxz766KMnfF8IIUTdPDTqKl5auBIAnQtSswtIDKt9JXzQ1Rd4KzQhfO7J6aMY8cIwgiODsNTh+QBCNGS1StAnT57MbbfdhsViYfLkyccdpyiKJOhCCFHPbrm4Cy//laADRAT6+TCaxiczJZtXbn2b8NhQnvtm7Dn/yWNeRgE/Tl3E5cN7nTVP74xOiPJ1COIUSReXmtXqb6mUlJQaXwshGo8HL3iCg1tTueTaC3n+O3mQWGOi0+n46sFbeHH+b9zUrRNJTWPrdLzT6WLBh4vpeGl7Wp2f6KUoG67/XP06h3amAfDZ+K+4f9IdPo7It+5q+yj2cgezJ85lXtEM/AJqv2RKCHFmnHIZwel0kpKSQsuWLc/5aoQQ9eWVn5fx5fqtxAYH8vOoEZjq6c/WoZ1pHNhyCIBV8/6olznFmdU5PpbvHjm1h2091OVJDu8+AsBH294kMan2XWDOBmZ/c9XrgFB/H0bSMNjLHQCoqkZpfqkk6MK3ZA16jer827+iooLRo0czY8YMAPbt20eLFi149NFHiYuL49///ne9BynE2eLX5GRe+/13/CM0SrRyitIVrHojAy9SSXVu4I/1HUFTSC8qYdHu/Qzp2K5ezhvXOgaz1YTD5iQyPrxe5hRnTkWZjX/1eo6inGLGzxpD5z7n1en47NScqtd7N+w/5xL01xc9x38f/IiY5lEMf/p6X4fjc7eOv44fpy6ix5BusjREiAaqzn3Qn376abZu3cry5cuxWP6+GeOKK65gzpw59RqcEI1ZWmkxu/Jzqu177JcFpDmySfUcJCu7nDJjBbn+eRxxriM3OQzMKoQ7INKO0b/+HnhhMhn5NvdTXl/8HF+kvF9v84ozY8Zzszm4LZWCrCL+7566//zumXgb1gALrbu24Io7zr0uF/5BfoyfNYa7X63/9nuN0d0vD2de/nSemjHK16EIAdrf69Dre2vMFfQ6J+jff/897777Lr169UJR/m4A36FDBw4cOFCvwQnRWC1KTebSbz/kyvnTeemPpQAcyS/GobkIjCijY1QGZqsdJcCNomiEm8pJtQdD61JwK5BtZtwXiyh3OOstJoufhQv6dar3J+wJ72vZpUXV69jE6Doff93oK5lfMpP3N7wuSxKFEKIRqPPf1Lm5uURFHfuRWHl5ebWEXYizmaqqjFv6CwcKC3jj8kG0CY+o9v4rm+cCCuBh7qHN9EtszqRpv+MX4UDvVGjnn4EnBjbktSZiqZlWF2ShC+9AgNFFcVEw5gAHaAo/79jHjV2TvHINTrebP1KPcFFC03pb6y68Y8CdvbEGmEnbm8GwJ672dThCCFF/ZA16jer8W7l79+4sWLCA0aMrH3V7NCn/+OOPufjii+s3OiEaqOnbNzN3724i13u4d8ZnXHFZO54dN4Ql87fwaci3NIvI4EhxG3RWDzaDi7tXfUHrYCOtWmWSne5H54B0lhxOAtyYCo0EGOy0Dc6gQjVjbAttWmeiRyMvMI6c4uY8//ViWkSH8cTVveslflVV6fL6u7hVDaNex47xj53yXId2pfP9R78x6I5etOva4uQHNCJrNxxg0+ZURgzvSWDAme+vXFJQynuPfkbCefHn9Nppt+rm1R3fonpM/KfztfIpkBDirFfnBH3ixIkMGjSIXbt24Xa7+e9//8vOnTtZu3YtK1as8EaMQjQIa1cnM3nGEtzNrLTuZaFv650cXFh5E+dvK/ZQuDWDA/n7yR2j56KoCjrFHyGzIpAipx+uIhN5oUWEKxDfpIhkezTDWm7go4OX4WmrMO1wL2L9S8gu8qNlYgbNLIUYdR72li/k7o88HI5LZXWFht8KHY/0vvS0ryW1sBiXqqKg4PS4KLKXEGIJOqW5Rl/xKm6Xh0Wz1vL94f9isphOO76GYPe+TB5/bS5uPx2L1uxh/vSHz3gM4/pOIGX7YQCCIwK56r7+ZzyGhmDE6sn8kWkHFP7My2J+/4eZ9ecWXl6/nIgAfxbdchcW+RRIiMZJKug1qnMZomfPnqxevZqKigpatmzJokWLiI6OZu3atXTt2tUbMQrRIDz/7DdsDylnhyuPUvMP+AXbcFkBnYorQOHw/hzyIvyI8iuhxG2iaXAug2K3kRiUi2ozYFdMHCoKIy0rklKPlUN50fgZnfhH2Sl1WYkxFhPhX0JTv2KyckP5fVsHlGIP6dGHUILd6AM9fFG2tF6uZb8tB/+EYq4c9DtXDf2DYb/+h7bfvkjbuS/y9s66ncPt8gCgaRq7d6Tz1Jgv+eartfUSZ20dyM3HrZ7eTbUPzZ3FhU//l/unfMt3P/3Jui0HcYTq0VSV/IISnHZXPUVbe7Yye9XrotySk47fuXoPP7z7M263u9r+fRv3c5X/bQw238LaHzfUe5zeklJQSIe3/ktycS6oChTrSMkvAuCZ1UsoN7hItRdx9y/f+TZQIYSoZ6dUcujYsWNVm0UhzhUV4QZsTTyEb9NjVdyUqWb8h2fSvnkGFQcDyPykNW63isngYlt6PJ2apmEyaHg2hxDSpIyiPH8seHDs9KOgVSA/b+5K6w6HKCuMwrNBIfq6QlRNIa0wjNVbkgCFvNWhGC8txVUOoQ8eQlfqYdZLc09ruYOqqjy3fRodW2cRZHJiw8SRimD4q1X01L2rGHPe5Sf+XrgdPLz+c+weOzf/+0qWzlxLnxsu5PlnvqW8zMGfG1Jo16EJHTufvJ1fXkEZE/7vR7p1TmDkzT3rdB2v7HmO2T8F43YYMRn0bHri4Vqvp3e7Veas3kpQmYsPPYs5vMoKHpXdi1PYQwp6ix6d2UPo3nJskToueOVtnrt1EDd36FjrGE/Xiz88xet3TiE2MZpb/33dCcduXb6TcZdPAOC3r1bxzupXqt6bMeFrnLbKG46n/2cOFw/t7q2Q69XMPzfj9Li4JCaFX37rjtulx54L+zJzMRjg6C3Uep3c/yREYyVPEq1ZrSvoJSUltdrEucHtdvP+mM+Y9txs1NOsXPqaqqrc8toXdH/sv0yet/K445xhRoIOOfEYFNoGppOdGk6bZlmoZQp7ZrfF79JsHJfo0QF5ZUEs3dUBh2rA49RxSau93NhxHaZ0PQAH1jXFqrfDESMRvbJRSwzEmYq5NGQP2AGXgr4CPKoB/+0K1gVF6Is9KCp8PemHU77WHYWZ9Pn1GWL8i2hnzeI8ayr3hm6gTVQmqlvDfciK56AfWcUn/rM8btMc9pftI895kG+67KL15P4kX5GPzVXB0c8Uj1bWa+J2u1n/207KS2zcdP+HbNt5hE9nrWbez5trdR1pZYXctOIZisp243JUJuROt4d9Ofm1+0YAI6fM4YMxn/PO0DfIMZaCyUXfrptQ0NCVOrC7KlB1HhQg7So/ymJ0PLVsEWnFRVVz/DJ3I5P/M5fiwvJan7cuEpOa8cGfb/D8d+NOuu56x5o9Va/T92VUe6/3sEuqXl9y7YX1G6Q3HSjnzgHLMBlU3AbwBGl4AmDcb7/Quk0OltAKLKEVREbYTz7XP2SmF/LWxJ/YuP7gMe/t/mMfg0y30F9/Ez99uLg+rkQIIeqk1hX0kJCQE3Zp0TQNRVHweI7/S1mcPV4eNpnV368HwF5m46HJd53xGFJSc2kSG4rJdHprT1dsP8iurGw8sS4+X72Rf11XvU90UX4Zb373M80uPYAh0MHen9qgN2jsOdiMFm0y+GllD8JMKm0HpbBpTQyJftlkBASRlRFJhcdIQbRGU2Muny2+CpMD9G6NQ6mxBB320O5fh9lfHoPJ7SDPFUSIvpy1Wa3QVz7oD2u2ina5CyXehPZlZTWg46XtT+k6Fx/Zy5Mbv6V1RA6tAvLoHbyHaJ2LHLcfPaJT2b2jBZpLh9tf44ovprHjkePfOKpppVwSeYCDB2LZlGJkl3kz1/dax3mP6Uj5pjnqeQr3HZhP+QE77UOjmXX57dXWCN918QvkZRZTckEEOsUKbhVLgZOpL/6EocLD0Bu6nfBaHlr3Mf6WTKJMJSj+HijWo1M1XE73CY876mBRHtv3phK9v4Dii6KIthRxw4glbLG3xDK/EF2qi7yOodiidQQc0YMGhjLQ9BoHSwuIDw7hjxV7ePv5eQBs25jCtIWP13iuld+uZd47C7nu0Su57Ebv3Uh/09ihLJu9mry0fEa9c0+19wbc2ZvzLmmDy+6m+XnxXouhvunCPkbV69iTG4EnUAO7Amik24sxOzRQKr9elpVa57kfHPkxFeVOfv5xC1/OG01UdDBQ+Q/2J+9+l/IYM0f+lcRox1YKt0VwR6cu9XtxQghxArXObJYtW1b1WtM0rrzySj755BOaNGnilcBEw1aUU1z1Oj+zqFbH/D53HSu/WcudE4YR3/b0/r+555FpHDiYi8Fq4JKrz6NXx0T6d21T53mKnPlM+Okb7D3cYABXCxdO1c17P63l8982ERMagGn+YXaNM3Bzu1Ra6nPY7d+GIrsVnb8TPW5QFYoH2giwOMCq0cxSTKD/fmaURpNZGkSxZuFIaWUbRmcwKG5QzaC3gcngQTdTIXC9jV+GJNHSlI1Op6Ev1whKBTAQEVFCTmgwztlNMGW6eOnRuj+td29RDg+u+o5g/3Ka+RXg0IwUu/RkaMGgUzDrXZj1bkpC9IBCGU6m/bmJ8yKiubBZ02Pm6xU8jS9yenJkdzxaAKBAoL6Cg9Zotp4fgRbswqrk0zXuCAZlN/+3LZxnLxhadXxOdjH5lzXBFW7EXOHG/6Cbo//8nzNz9UkT9HKyCVMc2BQLES2zKVoXh6FMx8j/+5q2cRF8Pf6OGo8b/+lCNiYfobiFHUdbN1gs5N3alKERvxNusOFwKpisFXgwopqMNFtixxlowFSsoPNUVrDzcm3QFHKz/v4zUF5WcwX35rGfkf/2zyjAjtV7WGCbhclkPOG1nSqTxcQn29467vtNWsZ65bzeFBxUyn5HBOFWO0qgE82lA1WhfUIoOv9N5GcFABAfYKvz3Hbb3/cUrF65l7W/72PItRdgifYnr0kwpQkWmp+XhV6vMm3vMknQhRBnVK0T9N69q7d30+v19OjRgxYtzq62aqJ2npn9L/5zzeuYrSb+9dEDJx2ffiCTF298E4A/Fv7J/OKZLPxkCQBX3ntFrc9b6rRz/6LvyTyYC0BBGPy4bhc/rttFbHgQSc1j6nQd7+29B314ezBYAQXSjXR5bgr60sou5umFxcTZXOj1eqx6B6mpTXD6G/j5925ENivEhpXYoHwKLQYCdOUY/eyUui2UllpoqhSRXxqI6tGz/UgcWoAbpUJPbOdgsraV4vbT2H24CblFoYQ47Ghvmfn5qq60aJNB4W8J6DTAoKNZUAGH0iNw6P3o0jW9Ttd31PvJswCNJoEF9PRP5veituw3xaHpjETpijBqLqzNSijJCiMxrIC8gkBe/XUFoPBorx6MvrR65TfNEYqKjuDoYtweC3Gt8wjTl/NNWgvM+XrOv2AfwX7ltAnKq/w5FX5NUUk/QoL8AAga0Jx8IPbSI7Rvk4Ztrx+bf06kfKCGs6SMksIygkIDyC0ro8TmQDPAvoI8BiW2Zk7qGoKMFQyJ3MEuRwLDEjbwwfqhKJoeVNhzJI8Lxv+Xu/p2Y3T/yqUdySX7mbTyVTZtPA+/a7Ow7QsgpG05QRM9mPQOIg1FFKomjIoH4zAnjgNhKB4DBpuGocyFzmWp/B9CgTXJh7ihy3lceVN3li/dSdrBHJ5++cZjvucp6fnsUAtofGlxw2FN8Keo0J9QYwXBfhWUGirXZb7QvTtTU+YxoNkeXKqO9sGt6zTv6j2HKEww4p/mQheq5/23F1HeTmVV6Tb8MyHvynCaty9FZwZNA3NkxsknFUKcGuniUiPpSyVOSWTTcKZumlTr8eX/s0bXZXcxdewM5r79EwCpu9J56K0RJ53D7Va5/N2PMLQ7Ai2D0KeZqEh042jmARccys2vlqBXlNlR3W4CQgL+MY+bBR/9RotOCSTFHsTd0cGy0vak54WhocMZ4sKg0+FMdGHaa6awgx+mPzV2hDflmtZbYEMv0nNiaR1/kCNFIUR0zaOtvgxV0REVUsx+WzRb13QguHc2mssPg1shtTiW0E0lRC8qQDPAlFmjWJ18hJ/3+JHT04ZiV1BcKrp8PWUfx+IOBYMdPEbYnRdLYbkFs9nDnzmn9smDXdkOSiIRfjaaGIsod5sodvlxwBZFc6uZKFM5Or3KXRf+ToXHxOKcC9CZbNx35WJMurnMTe3K9QlvA/B/G34nVwlGh0qPrrtZm9uclKwoyiKNRIQUkulv4crYLWR6Qil2W9m1MpH035uylKm8Nu5qfvf/kaJB6airo2jeIofmxnyKEipYdV0zQr4vw/Kzg5uff5JLJw1l+uE9JMSmk+yMRGdROW97NGUBO1FVM2DAShkJgYU4m3mIsBTgTPGjxO2P06Dy3ur17C8s5L/DhjB1/yvsKY/AGGdDX6Dhn+Wg40UZNIkvQikCneqkVAukqTmfQ8VxoDMQeMRFYSsjEZvL0Bf74QkygAZ9WycC8NEfG5jftJDgQjsTv1nEnItaVfue/7ZxF5q/nsKhrfDflMW/xt+KwaA/pZ/fuWpTURBNLHnkO4Iot1lx2UwoOpVSx3JaW7LYZWuCVadyeXjzOs27bm8qeX08GH6GgjYGgrPd2K5xML7dYj5aPgBXuEZscBHZjmAURcHPUPcK/blm1bw/+PDxGbTp3orn5oz1dThCNHrytAdxRrTp1orrHh1M0zax/Hvmoxzceqjqvf99fSJzF/yJvkkGZrOH3KYW8jobsDfxoLl1aB4dH320lPsemkZWdjFrftjAtWEjuT7yXua9+0u1eZ644mXeGzODxy9/EU0DQzAMjN9DkMuNO0jFoGo42jrRLBqKQaWgewBlEVaSi0NI1SI4v8tedHoPZSktcVdcQHpBKEaTB7tTwWLSyCv3JzdBj81oQLF6UK0qihPC1lUuidC5YfMPmxl/zwB+f3oUXQ744V9swmK3Evu7irFQh1+mG0egRkigmfxDoVgtbvR6UPRw/bJ36/z9b2LKwKp3YnfrSXOG0iSwhCxnMCnlUfxZksiOkjgujDhEmNnG/vJwbui6mkeuWoCfzokRD8WOyvsN9hRns2DtMvwNdi4OTqZLQCpGVFRNx77SaAj2cNmFO4g35eNQdQQqZah7regrPJjzXUyduoR9xduxRFTg6FNBU0MeHf3S2FwST4DZTsCmysX3jnAz0/fvQqdzExBVjjncgSXURolxC62DsukQkoVD02FRwOEx4AEs0RWY1itoOg2UyhuXf92VzPe7tuFPJlGhpYR0yKbEbKI82EC0qRgLTjr7pZBjDwdgvzMOc1MboBKY6aZFngkqbETPP4TfnhIS91QwpEsHAN5Zu47IFblErC2kYP5+XnpjbtUN0w9c8TxvLf8DVdOwt4nCHBHDR5OXcGfvV+v8szuXLctoTZnbQjNLPg6bGVDQVD0b82JwKiZa+OXT3C+fbEdyneZtkRSGOcSO2e3BFaqjpIOOYEM5ieYCbmi3nkC/cvqG7OTOmFVYkhX2fteSi59+l8KyCu9c6Fng9TunkHUol5XfrGXlt2e2zapo3I52cfHW1lidVoJ+optGhfinh9++m2l73qH3sJ6M+eh+ohIiiYgPp6K0ggGGYdwUcy9FeX93D0nOyeNAbj6ZmYVcN+wdPpj9OwZVQ1HAUKEDlMp7xJwK0b8plKZWsCc9h0ffnsNPHy+p+mjr12nLqsVxZF9m1esZaRdi8Dixq3q0QDfxEdl44lxE+RcSZK3AP8uNM8SF0sRBfGQFhU4rTVvkc+OQFTQL2cWE8wfizDCjU2BzfiJNAwsptfuhVzV0mkqZ3YJi8eCfX4KuiV/lKgkF+t/coyoG3ZG/msW5NfRK5R9Kgw16+Efz85SHMK8Nq7xONFS3yoHswjp1znG63ZxnOkJ8cCE6NL7IvZgy1UKI2UGoqZycskD2lkVRppnItVlJLQ0iMSQff6UCOyZsmLFrRjbmHuba3z7EmFNOqMnO70da4kShdVgOBp2H9RnNMOigVVQ65aqJtuZMBgfv5vzeuzFUqLiNGk2uWU67gAz8DJWJeHmxDg8QHlBCuLUCzxA9KFDW0kJAx3ySeu2haVgevaL38uZ5c3iy7WKamfNQFPi9pAPri1uwpyKGIL9SlHyI7ZbFzYOXVP3N1vOKrczIeJ9W1jziQnPp02YfHvTYEvXodRrfp5/PdWG7+Cm1M0sy2nEoJQrXr2Z0WSXo8krQFZeDR8VU5iFqTT6sy+GbD34DIDjUgqnQTXEXCzlXNuXb9FTueHs2APu2p+JJcqBTQedW0ZdX3jyfn1VCSZEkebWxKusgOHX8sSaJVHs4BuPRG4A1DiWb0DRQ3ZB9IJS2AbfVae6esc1pH5uD5+ZyzHkaTaNz8TO5UTUdpjAnUWEltDXnkesOIG1fLKBQ7nDx3bod9X6dZwv/YL+q11EJkT6MRIizQ62XuFx/ffW+y3a7nQcffBB/f/9q++fOnVs/kYmzWpOWsXyZ8j6TH/iQhR9XrkUvyinm60k/cP+kO7jx4y/Znp4DCjTd4EZ1qdjCDBTuCyE8qICj2XeAzoHnQBCeQBd2i0pmX4V08rGHmNAtVlA1jRvGXFnt3I+8PYL/PvIZEU1CifbvzIxfEuk/YDtPd/iBmdm9OD9oC/jp2bWtOdohyOmp4efn5IKQw5S6jCiqyu9P9wCXwhMzZ0KLIKwX2dm0L4mWiVnkbwnG7NYRH1BA0fYIAjcbCV2egQLo9Apf7/4//IOsVfHcNLwHH7+3FH+rkY9n3M/K1ftYsWIP94y8hCnjvsDp8mAs8kAQONaG4/Eo9Nw5lXUvPVKr7/WHs1ZT0rYJ4eYyQk0V/LmwO4fMLhJbZzFtyHN0/eoTQoKM+JvdWA0uSm3B+Osq0BQdKw80Y9HOzhgrwJr4FT1aHSQ7M4JwXTFlqhWHy4CGjp6tDrA/PwI0N4vzWrOvPIZ7Y1cBCt+4kgjXgz3CSJuWR3DojDSxlpKW5yEs3gaaRqK1ALtqZJOlE7o7QTE7aBGeRqSllOb++bQ3ZZKlhRKuK0FBo1y1YnfpSSmIwK4asWt6is1W2l9+kAqjCWObEjpb04n0K2bZpiSGN1+Pw2Mm2JCDptfQihVybP64ND0Vmo6k0HQWp5yHMctCcFEpEZShuFXCwgMpKrKBR60qSCz/fhPFrQOpOFBBwdAwwptUwE4Nna2c9OmHWN2yNZf0aM+PweW4VSuaTsEVpMdU4iG+ZRRBIX4n/oEJAJyqE3uFGa3QyObtLYlrXoDDacSg97Bq62EKNg0k+KCG6jCw4avF/Pp5u5O2ojwq2i+QptZCDAYorogksnkJacWhbC+JZXFpEnGWIvwUB0a9QnzLDCI652MwaNgsesZPy+NQdiETbh9Am6aSiB419c9JzPjPHLoO6Ey77q1OfoAQ/6sRV7q9pdYJenBwcLWvb7/99noPRjQu70xZxMKF2+jcOZ7XX7sZVVVr/QvyqIqSympi6UVx2JKisHWOAmB7Rk5lFVQDl6qiB2xNndgjDBSvjiIwTcMepmFe4UdZpEborZlkFQbQKTifpMgsFAWG3PUAF0UMqDpXud3Jn6np9Lq+Bxde242rPp3J4g2ZtI4tIkhXTqxfGR1Csunsf4CFeV0gwYEa7aR9RB6HDkUT3NqGHieLt3ZF51JwWXUYbCquIA27x4y+1MT+dYmE7wb8VYp7+hOSruH4n2q3qmpVyfnYR2eybWsa53VsyqLVz1SNmfbZ79jtLp64+Fl0egOGSxMwxNmpSPdH8SgoQHm5E6fbfdKH8tidbmb9tBHDzh4E988ib28YmkePvULP7q3NCb0+gsviWrI8/SB6t4fz2xzG44Z9tihC9WUs3X8ehnLQu3QEOPJxYSCsWzGq6uG5tt/zdeGFRJjLKXAFEmIqIyagiPVZrXCX+DPfkkQbSx6qQUf5iHKUjVay3AGUu61k2f0pLvBnX3EcSUGZuD0KrhwLqDpCdzlwBejI6+aHwajSISCHfNUfnQKoCimOSA6XB+KvquSWBFPqsBLib8NkdbE9LZ52rQ4TEV5I97iDmDx2jEUKRRVWIk3FaBrobOB3xEByQjRBJhufZF3GXncMl0QdYH16EsXNglB76bkxugVjnruetUt38+WUxWT/1Vv85kf6M+bX5TjblKOGqHSN38MfcW0IueMIik3jxVveYdSKx1lSOJucSBVLIZQ8o8Ni1XF71ytP+POqDwXZxRhMeoJCA04+uAFzqk4iwkrIdYcQFOBBn+Em6P8K0KJ1ZPatQF+gQ7UDClTYXeQVlhMVHljLue3EWorZOaMTxmiF7PxgwgLKeHXFtQy4aBt2j4IVPf6KjdDOBZiMlZ/c/bYxhQNb3VS0cDJk6Yf8q3MfHurcy7vfiEYiNCqEMR+cvGGAEKJ2ap2gT5s2zZtxiH/Y+vtuJtzyDnqjgcmLxxPfuuH0gnC63fzfZ7+x5PvKh8ps2JDCnbe+T0ZGES1aRvHRZ/fWfJzqxoCuWhL/+KcPkVtazuIkP9A0PvtjB6Nv7U/zsBAOFRaBAqbLwgn800ZBnJ2AVD06u4qpHMylKqqioQ/yoKLROjKTNkEF6HWQX+rP42uWMrzVqxx0RONw6Vi98GKcHg1zsJ4SkxPsOrQwDadZJdJYyq6KWMKMpThUI3GWQlbvbsPQhzbRPjKPGfYeLMpoTYfgLMwGF8UxCopdwWPSgU1he0Ek0RGFZKRGgFslIFsj9+cYwjoX4SyIwZ4YQpxd45ZRAwHYs+kA27amAbBz+xFKiisI+usjYvvRR8o7XWi4sJtK8UNPRNNCMreHgKag01Syc0uJjw098Q9LVbHFarQfkMa2kqaY/giCaA30cH6Tyv+npve/CbvbzbWffMH6HXai/crJcISxPDcJRdFAg6CthQQvLkV9C9JKg5iRcRkTu/zA/uIYrGFHKHVbiQ0oJcFSwOpyI3mbg9hicpMdFcr5TY+wOy8C0wAXYUY7i9I70SU8lcSW6SzZkYQS4OHPnES0UiNooBkVzu+7F11MBTbNRLwpj0KPPxn2YIxWByoKNoeRAH87elVFTXYTklDKBa0yWFrcnj2lcTQJKiPX6YdZb8Fo13j9h+vp0nMPsdHFWG0KFVaN9OJgOkRks35JR8wXlrBfiyIA0GHkqUevYdgFlU8M7Xd1F/pdXb3FnqniB8rcetzlCvmuINADTg2NymYvsaqFksMB9Gq7gyOWUCItZQQZbby24wsuu9w769BVVeXhAa+TurWyJ/gzn91Pr6EXeOVcZ0LnsFjKXWZ0/h5yS4IIeT0DJdODbj8ogzQsZRqaBugUdIpS6+QcKv+hrGoKmk3DP81B1s4YdM3LsOTqiTMV83t+C34vaMIOtQlhhiLsSiBuVcXP6sAV7UaL8OB26nhzwwpubHM+kdbG/Y8hIXxKurjUSG4S9aGD2w6RnpxZ43sfjZ+DrcxBWWE5nzz79WmdJzO7mEf+8xVTPl928sG1MOHdhfy4fAeeow0pNJWD5SVk9jDzh18hdruz2vgnvlnIBZ+9wGWLnuGSxc+wv+Tva7b4WRj35SjwaAQf1AjIhNvHzuDHB+7g/Gw/Wqfo+fS263hq/BBcTg86F+jtABqoKlYMDG3aCrvLQITVTrihFIC1+1sSEFDOQUc0B2xRJOfF4dQ8+Jc4KAy1oQuyExBY2ZkhINBNoduPTEcQqqZjXVlrsh0hqA4DV0TvxqPpCI8p40BJLN8f7EpaRhS5XUzoi0rx6DQMHoWM7GjyggwoAS40A6hGHYYUKyXrImjTLYClq18m3AxT7nuPu88bw6gL/13Zv+0vqgYv3zKZgcab8XP/laDHhqHT64gKCqGi2IrJpNFy6D7iWmXgn65x82Of8dZnS4/7c1JVFZPJQKeL99I3eg+qR0Nv1AjIhoAM+OSOvx8dbzEY6BwXS3JGPFmHw9AUCPar4IaL1uIxafgfLMNuM1HhNJCVHYbdZSHDHkSJ048CV2VyUqb6YTQouArNoOg4siwGNIV9BRGYbAaSQtMJ1hUT4V9C16BDRPmVgVmjqMKfCruZ4C/1BBx2Uhan0LXXPvIcgaSXh5DjCiLNFkG6PZRofTlumwFtTShFpX60LEyj2XP7yDlkIUirIKcogBKXBYAMWwQHSkJpcV5l5ftwQRjLkzuhesBvgwFVM6Da9bhKrZStiET5KgxTsoZhtxNbxrFdO/ZsO8z63/eyOGsOlsBiDGk69KoOvUFDr3gofzQUJU7PNQ8P4IDJSUtXAYTBpZH7GNNsMffFreLJxFP/s5xyOJf8wrLjvj/jncUc2nmk6vfRr1+uPmZMeUlFo3jy79wv1/D4jIU4XJU1JF2FHqfOWNUrv8zioagNqCYd9nAdFWEKXyzaWG2O956cxVUxDzH6ileOueavXvqR+b8noagaBpeGajNQlh+EoQx+3NgZh8fIy6uuw+4xcGnIQcw4aGosRGvixBhpx5CvELnYRPgyM29+vpQJP/7GnA3bzsS3RghxjpAE3UdmPD+HB85/gpFtH2XR5yuOeb9Tr3ZVr7tdkXRa57pt3DQ2Hcjgy1//5OUPfj2tuQAO5uRjjSwl+yIDRa30ZF1kprCzGUewRklrhVG/LKg2/oc9ezDFVuDRdDjdCqPWV/80Js9dTES7PBQUUFWyNmcw5PY3yd+Rj/1gGY/e8RHjnv8GU6tybE08hO0oxrz5MJafNsGaPWz4ZR/FuYFY9U7aWbNJKQykZ8t9tArOp8hlwW43kFkaQmCTYgw5BhSjmzu6rcHPYkfn0bDZTWwqaMZ3R84nz+WPlmwh2x4IJo0MZyjnm1Nxe3To7BpqphHVqqHz6PDLdhG6qwi/lDK0fBMOjwlHGGT3VnEb3KCqKDkwqu9Anr/+Dfas3w9A2u70yjvLD2WAy81Nt1xESIgfK75eg+pRcfy+jRnv38GS9A/51TWHn7+YQKytDfpyNwNjdhNT8tfn+sDvG/fX+DP6fPdGev36by5fNo5Ag41gi4Po0FIsQ7MxdCohaGghAX6Wase8fvVAdG4Fc4nGgeJITCUazfyLMGkq+d1CUJzg9OhRbQays8P49kB3FEVl195mOPMUUj9qxc9fd0ez6wnamkfknw40dERbS1FVCDNV4FKsdAzNxGbXsyM1EatL5WBRNE6nAX2JQthOBxFbnETpCwlW7JjdLtDBzrJoQk0VlLitHDoQi36PFXV6DI4PK69B2W4ixx1IVGwZZsXF3h3RHEyL5EB5LAfSo9DbILsimI05zbFOVwk4WI7ldxPp+6PQFA3NrqF4lKp/NP0zEV4yfzNjbv+I/zwyk51p02l6xI51rxm3zUROWQAR+hIymzTh0F1JRN7TmWcX/kaQqRyHZqB38F4MusolEv46Fz8umM/1V7/F2FGfo6oqG5ds55b4B3igyzjKS2q+gfShp77kztHTuXbkVH78eXONY/bvzMATEQRUFo26DOpc7f3RPZ7m2pARDIu9r0En6TPeX8p/P/iVNfpsVIcOBZWkhEiKRnTA3jmCa8ZdiWIHZ5gOl7/y19NEYe6a6jdw/jR9BR63h+Qtqexcf6Bq/7LvN/Ld2wsosASh6RV0HgjZ58SS60YFDE1dZOYHoLd62JbTjGK3BYeqw6h3s6cwCleYm84luSgoaMAP6QeYs2EbE378jZ+27TmD3ykhzg7SxaVm0gfdR9bM31D1euU3a7ji9kuZdO9HHNydjjUxjpj4cF78dgwBwX50uPD0brhxqGrVL7GdByqr16Vldp55eR5bA4s4YrURarGw8t578TOZqh1bkFfGmuW7MbYIYostheSCQjZb8hg4dCcZyy5EGVSEyajg2BmKO0DDL8jGduN6Jm6HpztWVmg1E4SZSlHsenbmNqEA+HnHHiZ/8zsKcMVNmRgSbRSd58CUqqKGu3GiJzS7MgZ7mQO9yYjbrccdqGAsdqNm5AOgtoirXBZxwEL8+YVkOoI4XB7CwJjdGA0qh+2RJO+LQzM6MaLhjtARG1OEXqcR1LIYZ4ZKelYYlzTJ5lBpJKuSW+NeFUnQtRnoLC7e+/FKxl0zn0NbmgIqphwzBpuGX4UNTHqwe0goU3AWWcmzAnoF0BFwuATjkSIAFr33G38s+DupCgzzp1m7phzYeojbHr6CWx7qB0BYbAgFmUWYLEaiE6Oq/Rxebnkxv1i+ZHdeJBuVaAJ1GooK5/dKqPFnPiNlMVZrZdeLIn8TqqbgdBuwHQxGderxNx2bCLrdbgIqNCowUuAJIP23SM5vcYhAi4OibiaOXBlOrFaIIUuH3qbngDUaNUqPo9xC+sqW6FUd+fYQLDaNgEwNLUBHWlEQl0Yks8PoZndJFIezg+jULJvPtvQmTFeGc080Me0zyCvzp6IJ+B3WcAXoWbm1E37NHCQnt8XdbAchBjsoClN296XUbsZkAoMTnK1jiS13UlKmJ7csCM3jITc3FLL8qTigoutQBHlGrAXgaqpDDfRgLnShd7qwploptgSjmQGjgl++kwo/DXN2CQ++3xNVVfnw8Rns2pbO/kP58NcN8RZTEaZoJzq3hqFAIXlLArowB0G7jCgoTPzoN5RwOLwvhjZJ+/F44KArnFnvD6Q4NQBDwTYMyRns/iOZ29buI2/HQXC5yE8v4MPHP2fsxw8e87PZsfevB+UoMGX6CoYOPvaplnc9PpD1dx/BE1z5icbF/TtWe//oPxCLc0vY/+dB2nRrmDfypR/Op6LyjxvGLCOaXuP7cXeiu14Hz1WO+XHaDJJzCnDEgClLReeByztXv57IJqHkpBWgN+hIbFf5/IDZ7/zKjNd/QlUheK0RTa/iNkPw5hyUihBK25jx/D97Zx1uVZk+7HvFXrvjdCcculPAABTsAkcdu3XszhljjLHH7u7GRjFQpLvzBKf7nN216vtjI8iAAo7jz5mP+7rOdZ2991vrXfW8z/uEDrpmBZtAd6eTZXllnJM+l7mxcuxykj62OkaPb+OdjXkk7CKGYHLMgXPxZkRZxTdMTL6BQ/H8zrO2l73s5X+NvRr0/yPO+PsJyIqM1aFw2m0n8NHTX/Pdewuo60qwYXUjn2xew8ntH3N87Rssaa//t/q66vQJiIBFErnlokMBuOOBz1ixpoEGW0pQ647Hmb5p+1jCyaTGqUc9xD9e+YprZr3DKuNtfmioojivlS7NRfaIFtLdIaJBBdkRQxQN0nLCyIrOpy3zaY52UdPdjSU/xEE566nqSgmdcqvEtc9Np9Ufpsn00xJeyuSM1QRLRZJOgdBB0N3PQneFSCRHwBRAGxQkK6ObPgX1pB0YQPClXoCiaoBp4tikYhFNqpI5DMhopSthQ5FMCqztIJscMmQtyTQT3S2Qb/HTmnSiGjLaZjdSrYzborJP7maCGzPRkGjv8iCoIvaVFl647FiMsAWpRkFzpqyM05cmQLJgOG2cf+uxKDU6zmoZtkSCkwKJHxNPsujbtaTleEEQsDptvNX0DA/NvoNPQq9x4vXbzExerXmCW6ddyzstz+2QDv7baYvp7Lbz7YzRRLIlWg7VaT5c4wNh3U7PeZFNx6dE8X+aRV17Dm81jSBW6yLR4kT1W5HXl+5Q57PX55P9djOKFCO4Ph0UgeeWjmdQv7Uo+VEkWUczJBz5McQkaLbU48OSF8GUSO0YJAxEBEzTIN7PoLnLxwBPA/6knaZYGstbKnj6h4kkF2fRsSgbKS5R/1kphYvjlOh2BEFArmrjq/kj+aJyILpDYF0omyGeOtS4SW0si1jQRqAcgoWQNTGPN2uf4Iu3bmR+ZQUeVwIUHVM0SNpNbIFcrCEDWwRsjQpyi0jXcCeyRaIsCNk4wBSwWxXufeREPNNXYFlUxZm9L+W+Mx7ngxd+YP3stejGNjVMTd0AtByDPK0DUxYRHAYOIZnaAQJMFfrmZGJZaKU2lMV3kX682zYCf7WHzMntGPEkwpb2ujoj4LBubbtsUPFOz6fHZftx04RhP1OmZ5983vjgEo6eOpyHnjyNvILt/RP6je0NQFqOl57D/rgZoKdeuD9KKbi7DGwdEvZWmVdmLWVTXTtHnvkwk5QT0M7+lJvCeTx69OEocZBVmPaTRTDAcwvu4Ppnz+X1Vffi2hI5Z+PyOgBEj4fMNg1TFAkXShBNYFgEDBGS7dsikyU7XdS2ZaEKIi4hgaKYFHqCtNodGCd1YB/fRU55GxkZAbLkIOlSkGl1t/1uc7WXvfxPYP6H//5L2atB/z9izJEjmR5/c+vnhk1b1MWiiKGqhI6EkaWNaIg8tOEZXs26/Vf3dcxBg4mUL+OdFX5uWPk5DWsrsfgd5I7pxJFvoiuwqT2Px1bMY/66Or5cu4n9K0o5td9ANFUnmini6hnguLwlBNpdFDla+VPuEt7uHIGiJdnkL+SAfivIdAfo4+ygqcvHan8BGAmmNS2hKL+DppiHvllNrOooROm2YGJSMrCJhgwr5fYOAqITSdQJDLSQIUYoLatlk1JAQW0MfWUYzaHhlAxc1iSb2tPJlANkje7JBXedyN//Oo3kaIPVnTloCSt+q4U8BUwzTKmtm+z0brzWBKoqYLGrjM7ZTE08G7sRx+JIYF/lIqLL2CQdSTVQXWBscCJmJXC0GYTzJWxdKXtXa6vJAb2L2Thr1db5zcz2cNax+/Dap4vJ7zCp7pege5iLzFkxMGHSn0Zxwe1TWf7tagbs2wflX3YpfkRRLIw7euROf/vTBRO55JQlCOMFkMytphjufxHkAe646GXWDY2SZbORUK3kFYXoUl1IW+92Abu84xh6DyomkSVSuH8rdasLSLpN1E4bp4xbRvvmNHLtQVaGCrAXRRFbZeItTiy+EIJFRJ6UxPOchKNJp3W0jcbJGdg1nbguoCFjNVVkERRvnFi7BQMBpR0MPYzvkzoUdxodli7MRBy5poGcJ5rY/OwgdFmir70RMWnh3cpROKpkrE0KmhX6V+Ty4vl/AiDN5UBPyFRWFSCHTAo/a0PN8KI5DRwxMC0mmAJKQCFarPDQAxfTIytju+PfuLQaQ0+ZfnS1dONvDyAoFtA1EARM00QQBDoiWXT7gmhOAUezRnZxC5F0C/G0KI4VGiMn9iBRLxGUwGWNoSPSGfDgrejClh5Hzc5GaRARdIO80iwao15obgerhWMv2XmUl09euYj7n5pBdrqHM04cu/X7V29/j6bKFi5+9CycHgdZuT4uvuKQnbbx8Ow7SMaTKLadX39/FG79/Fti/TSUapPkFrfbdY1tzPx6Pd1LqrBrqXP06dMzKPWkjkWKGiQicc6/9lWevvdUAF545Qfe+WAxzjfm8dLTZ5GR7uIvdx7Hpg2NRCJJMroNLEUuvstL4Cx0Y+mIog9wkay3Q5oODjBsBmlGlE1qBl2anURSZl2oCFk2KHO1M7awhuk1A/DIcZKGRGtdBiWFa/+vpm4ve9nL/xB7Neh/ECaeMIazbz+eHmUZmPXNZGREaIj5aIl5aVEj/1bb1yy7jOcWb2BVu0a7ZS3pthDD/rySPodWMXnwCirb8pDbJVqXBvlk1TqSus7MZVWc98KHhAosGGPiVDgbUZGZ0mcRFdlNOC0GR2euIMuWEkKd3jiDvA3UdGTy9KaJzOnozaT3X+CtjXPwRx2siRTiV6woskZ+eSMnnPQVF078jKQgIogmOUInvsww7g6dm/p/QsIrUtyvGeHAAPZEnMz2LsJRK0s3l5E5K4CoQ1dNAK0rwkffXItZ42Tdgl40dmQgCQbrQznEDBubEzkkkRCARNCJrY8fu5BAN2DD+jL0DS5EA2KtduK6hdLSlHOgGJUpeSyAiUHSI4EBYtJgWI8Cxtq3mZ8oVpn+Q4o5+9gxzHz+EuLdSfJmgy1i49aPruCzuoe4+B8nIMsyIyYPwbbF7nvtvA0ck3Y6U7PPonZdwy7PYSQQQ2tScS3vQtQMsrICFMyvI+PSxVx+/e2cueAG7l/3IoZhsGjmOsLdNrzpESTdIGmKmICtKIw1P8yo8gKePePYHfroM7SYI286mIbmLCKIuFZoZH1tkNAlKnytLJrRj0StA/lTJ471JtZOG4mVPtR1bsYkBmBoBqIBgg5Ov4zUqWBVNb7x96W/txm1XiLtVRs9ZumMkDwYNgHX1+uREikTLEEzkJIpB1lRA+dXATBNxjqbWby5FAApJOJo1fBu1vAv6sBmkTEMg9NPfpL0lWCvM8j/OoyjNorhUnDVRrAEVGzNcbzrkjhCJjceNn4H4Ryg17By+o/tjWSROPzcg7ju1UspKk5DyMuFQBhBVdlnQh8qN2VgxASkk0O4NZVDh6wmlpRJ/9aPd02I9U+sZOX6RmJZFnq723DLCTLcIc4/5xP2G7QO+z5BYvsVkj+hJ9awH4ddQSjIYb8/jfvZ8y+KItdeeMh2wvl7D37CK7e8zdevfs91k/6+y2sI+MML5/N/2MjGBfVkagm8QzsQ7TqyO8mI0U66EjHivbMxhZRSLBaKsfHhLxAMA0zQFVhd1YKmGcTjSd56byGGYRAKx3nxtdkAbGjopDrPRSQQpaGyjap5lUhxk/DAbKK9s0AE3SIiYEGIWkAXSc8MkTRsCLJIti1Ab18DPd1tHJ61mrn+cupVH6YJb/3zEL58fV9eeuAAFiyt+b+dyL3s5b+IvTboO2evgP4HIKlpHHfPK9ykrGHTmemUDSiCkIGqSQQiNkLJf2+jI13eiENMgGCS4/ZT4WgmyxZOpVEXk1hUEzlkopVHsbmjlI6vQRR0hKiKViIytt9GxqTX4BaiPL9xX5b5S7GYSWpj6fR2NiFjoqDjEqPMby8HDRzrZS7oOYNko5OIbqUt5CSuijw4/GVOGT+XEm8bAd1Bjj1AujVMjZoFGuS7/CiCkdrNnxlFfMpPz8OGoVdY8QedyLJOMn2L1liAnKJ0qhZXsa+7iEili8112axsKCGQdPLx6qFU+bMp8vlBN/AJEeJJkbCqsKk7C0yQkqmXfc2rvSmafwIfnXEzxw3vzwE9y3BoApa6DhIeg+zFIXLnh1GWdnPk8SNJS3ciigInn3vAdnPdv1cuAHabhSEDin42Lvzjl71IJBAl2BHi6atf2eU5fPfxr4hbRPwjMhlU3IjjsyiOp9uJNodpObIWWWxkTeh7rj79VmKBMMmEjDM7TmRUnNaAm1BcIa5KWMuSvHTW8WS5dx4W7opDxqM12Sm+fwPWtW3Y/CrvtA+nLp6OKYhIcxzIGxTkVpnspSqeNQbuNVDSLNJry7HbulNCumiC51sXa5eU8tVLI3B85ERe3or04VpaPlqDpSuGqUiYgSBGNIrXY+PONy9h7NEj8WS4yXunkd7nrWb2pjKkkIBF0UnkJFOLACDijwPw4H3TaWzoJn29Ssn0EI5GFVOxgG6iWyWUjghy0sDdmKRXlcgpY3e03/6Rh2bfwReJt7j8qfPxZXq444NrEEURKTMDb46N6OnfojxTSeWcbDZ+n0fE4kARNBIJBUtX6k1gOK3IIQ1TEknoKUfCwb56FEWjaV02wbUZGHGZ2ncXUL20hugPy3jx1XO5+R9/2uV18FP87duy7sZC8V2WX/rNSo7ynMrUrLN+NnrUf5L3HvyEC8bewNzPF/9smY/eXYhqFYmsd+NOi5E7qZHsCU2Mze+HKYKR7qDrzFHoWS7U7CwSOXmkVUZQPalkUAmfxOINdRgGqV0mIeX4O2JoKQAzfkiZhJkiGMkkQkJHaQyjSyaSLHDW6GEUzolu3aFyBHTWhPPYGMjGTBqsWl+KS1LpYW/DKSXo6WhDshgkkhaScQU0A7NL4uq/v8d1d+xN2reXvezl17NXQP8D8ML0hSxztJC0GGwMdiLcPpz94iV0hpzEkgpdIRdJQ9t1Qzvh+2kLKJVaGdd7PZnp3aQrESZlrCFpWpAFkESDoaXVGCVJzGyDXvvU0VGdTizTxLcphrsgwGG5y8m3+3FKKl1dLn5o7EWL5uL9thE8uO4QNER8Uog2PQ3FGcMSEJBcKtmZfv40bDamLpBodRFLKhQrMQQ0CpUAm+MZlPq6iZs2IoYduxIjt18L67V8Ctc0wO3dGB9GWLmhjfjiYqJJO0lRpOaibPIuHMLNz53DZWNu4Mr9b6ajdjPBHiKaCsmkhc4uF4GgnUUz+iOvT8UNt8xzYzY6+aJ1AF0xF87MEKIKhgy6DPuN7sGV+9/M0rNfYVyLxl9uOxZvuhM5biKpKaGwbn0rLo+dt765lulLbuXEs/ffbr6fvOcU3nv2fD5/7VKsys8vrAbu33fr/0Mn7jpKz8EnjSHS20ufknrKve3Iy5MgCIjZmeTaA2QJIbSZLmo31iGkeyELVE2AuEy0zoVpiojTI7iP3sSU7LNpb+jcaT+iKFIuZGFpjyIFU0Jfmj2CgYniikMqYz0CIJvgqdXwVqt0dIR58ukz+ea7GxndqwiBVDzzQ8f0R/nSi7iuFd0qIDZ3Imyx0HFv7MaZmcnEk/blrEsPZODEvtxyzTs4B/Tg7canGDpxAEW98nh94ZGsDhSgrLciukA2TZRaP7lm6vGV+GlYT0VCNEGwWino0ug3sYIpZ4yjZ48s+g8u5O5H9ywlfF5JBv94+RyOPHUs/R9rJyHEUCw6pY/VU/ZKJ5aAQWvIidGu0Hm4lfbhacTzbNhqu3AsaWRDJI/1/mwmeVdSmcxjVksFutVMLUCFbf2I8p4/is+4/QT2OWI4PYeWceu0a3ZZ/qkrXyYWjhPsDPHc9a/vcX+/ltnfr+eOa9/kgVc/56tjMzhl7Xd8uX7TTssee8JobBGBYNxFcJ4PV1hFmFdEgSOLcw4fjaCDIMrse9gwhIw0BEEgmK1gWLZE4BFgwdo6HA6FKy85mPwsD2eesi/j9+vDrV9+yzeJemRZJDQ4B6OzCz0SIV5kJ5YnEsyFfUoKcW6M4F6bxNJlkv/4BloiPr7t6MPHtcMwJIH3q4fQprlRUMm1hTBMgSAKOcWdKHnRrad1zZbEVnvZy152wV4b9J2y1wb9/4AFC6tYunQzfQ5Pw+Gw4UxXKA03EdQddLWk801XNWMHeCAShi02mHFNQ/kFgW9ndDR1ccfU+zlltYgVld4FzWQoESSgVOmgVXcjGirH9ltMvegh2+0n2x5ihVGKmmYQKhcIuNw4BI2IaOW7tgLMGg9CRZyPu4fTEXYRiDuweOOsaC+lV04z3YIHIy2JNTfE+nAhAatCbiRG5+Ic1D4irf0d6KaAYEBjzEdb3MmCUBlDnXUcVLGBDzsG0qJ7aatxAlHE4jx0E8R2BdkPmk8kzefkufPO4dXb3gUTtBwf69JF7C0G7lqT5kIBDJmYCFJCIfyMj44SP4ggtyhE38slUiZhbxLRLQISWwTOhm7WzN0AwEs3v01+n0LiIQ1d8aDLIGnQq++uE0blZO06gsMF95/O0IkDUWwWhk4cuNMywUCUB/7+ERmZbi6+7jBeKDiH+5fdTIW7HeWyBMurMjEVC1bJYNG9Q9A7rUjd7UiKyT7p1fRxt7POEqarLQ3zcx3PM62YJoQ6w7x2+3tc8fTOs/5dfvC+/PWr9Ti/ryUxpASPGCOh5yKscyIhogsq2eke7r3zeO75+0eIosDVNxyxtf5jV03lhU8WkOl1csz4QRwzYxXikjC110jYv1OQw0mEYIhhR4zg9KsPo9egYoKBKC9MvAeAbz5fyZW3HMPdn98AwH73PElzOBssgB9ymgP4gwlCq5tZtbCKK645nE2bWvF3R/j7I6fQ3dhNbVMnj8xfTm1tM5VuP1+9+ZddnpOfY8g+PRmyT08eW/sgnVouRY+EqDnRgmC6sQYMvnx5fxS7RNBtQSkE72eNiOEk+lAnURU6gi48RSZWIUlZ30ZW55kY8xwk0koZVm/lkJMnkFeWs8fjkmWZ2z++frvvAuEYx938Ii3Ffvrm5fDOCWdv/W3g/v2oWZVykhzxLyEY/1N88ekyHvjHZxBP0nFMEVqaDiL8be5XHNynYofyo8ZVYH1TIeBL4q/OJFCdRY+ClDnSMfsP4qh9U4tZURQ5Zr876XSLxLKtCAYggigInHn4KACOOmIoRxw2mOUzV3PU1U+zLiOC0xPBNczA+mIXiCKSy4XulH98zLKmvR3TbSFeaMM1rxmjO4o43UWkj45aGAPdJBpy0xb28HWyL9X+TCQBlgdLkCe3o0RdJJsViIucdeLPmyztZUfaG7vwZnn2+D23l738r7L3Tvid8HeEeP2Bz2mXDGYtqEU8IISlOkCGJUpjx2BOHLKQ+z6ZgiWayv6zvLENmz2B59EYtsUNXFR2Nc+venCPbEhjoZQ9dauRDggUWbvIkcPUahnENRlJhDWRfIa5G6jIaGWwp4GwpqCkxfCi0TomDYs7iV+1042HhdFeUBjDUqPwRXQQ9rQ4piGCqLKuqRCXJ4nDriE1ywgFAjVqGnZJIze3m25y0VutzGgahOTRiWoKhmnSEnXRGvQwplclySSogoxhashH29DmquhBESGiQnU9fZYb3DT9SkYP64soihx72WF8+vQM2vqW4NlsottMrGFwrYVEucBN+09kwIG53PzN09TeWIojK4hudeKoNQlnCCBCIl0A3UQSoM+IHghbnAEBWltCCBYLxa9Uk3tQT+69/2xycny/2TUx+rBfzvL418teZ8OalBbO7XVw5oUT6f7iACzCesoH+0l/S6Orq5TuWCfJgBVLMIYcVTHjGj18LSztKKC7IQ3dAvbVnQimCUJKUzvq8OE/2++kgRVM+vIenrzyZV6tbWVFqIjG9TkYDgHf+gD2hhAR2lk4fQVPv3TuDvVFUeSco8ds/fzqa5dx0sib6fFmF5EhheRF4ZEPriI917e1jMO5/XWtqToNG5p4+MJnGVqRRnNPtmqckwl1a7mwP4bDofDSaz8JTTi4mLMueWHrR39ox6RDv4Zyays6IvOnlwMqaBqqzcRIyMimiafSJJyvI1Y2YOZkQdRBe7eJJKjM6irEZ1fRrCC7dIqnpLJ9lvn25dC+E3+T8QGcddvrNPXpBLtG4/Qqro+9yd1n/BmASx49m9GHD8XlddJvTO/frM9f4rkntiTSsinoIogOHUGAboI7lJ3x8ky+fXMOD11/DOc1vIPLEDGX2UhTDKZ/uhw1oXHU1BFbyx9/+jge/Xw+WARMPaU9n//0ZduZlV174N9Z8f0aWv8yCpAZNWwji98fRFZ7I6YtFT1HjoDmBEGD44cPwHmzyR2r5mHaZURVx/v2WpKDcug4MB/ZkyTNFWaIdzNfdA5mdXsxbjFJGx4Oy1+OLzNKxq1RrILG4OyUv4BmGIik7otoMs6ZCx6nKdbN0Z6xpHdkcNzEwXj+JSfB/xpLqht444flHDeyP49e9QHdnWFOPmd/TjlvAgB3nPY4sz9agmSReGnFPWQVpO9R+3WBDg557yViKlwwZBTX7bP/rivt5Y/Df1LT/V+sQd9r4vI78eq9n/LW3OV82N4IQMUB1fylcBb7utZT1xxmfSQfm6yhdIG9xSRR78T6dTq2JY0IhklLVSufPfv1HvVZ1LuAE64/mk2BbNpjTvJtIUqtnawL5uA3nAQidta1FVKnZuG1RgjqNrp0F0eXr8CmaIgxIKQzrX047QkndllHbpJxtEjY2mS83jCYoAZtqC1ONqwuwTAEFK9OsaONoGYnacq0f5WPtdNA7xPj7cX70hBKp1X10qKlI+si3XE333X25qPOoTTH0giqdtLNGN773fR9wUoPt4TY4SfRGeTRqY9ufQF70t282/I8J5w0DjnOVhvg7BUmx31jofnu+fTLzuTp9y6lpDQTR0OctNUJLIEk6Ws1VHvqpSxJIn+dehDZxVk8v/af5JRmAWAkUqYTogF/OnDkbyqc74rKzk7WtrRtfbZoWsq25PEzjmX5oj+z5usBfPH3/Zn5jo0l68voGCagOSRMw4BQhO/fqaAqlIW1HaSkQHB0DhaHAoqMaLdx91lPEezaeVbKmW/N5bTelzHtkc8grhJcmk4w7MDfB4TYNlvnFfO2T5L09+MfYLJ8PBeOvHa7790uG3e/fiGKJOFrMbjo9j9vJ5wDO9jq67rB63e8x+of1rHuhbkc5Mom0+7gnkMmcfMzZ1LaO4/DTtqHMZN3bh5UnpWOHNFBNxmcnbWr6d4tQqqV+k05NG3qgep10DUujWSOiKSCGDXRnBDsIRLt6aNjUimqT4FNCvGIk+ebDqBWy0JYayXLEqS5NY2ly3ry9vKdm3rsjBUdjWi7SDBU1eVHzFTJfyiOZ67OiruWU71+m735qEOG/W7COUB+0TZBq0eu78d0DIzMXsjdaw7mnjUHs6D5A9rq2rnvzCdYMmMF1992H1l5fswVNkRNoHJVEw/e/RmP/vNLHrj7063tnXTOeEb2L0mZtkgCgihsdx0t/moFK75fA4AgGxDTyLd2kd+7BTXdimizIQsmRaujeBo0DrXmYoRVXvjHx1hbIdovi/i4Egb2K8a1oImM9zZRmNWJGLIgRkRGuTYAJqEGD+2L8sh3BMixhFENmTn+Ct6uvJXeb/2Dijfvoddb93L+59M4+MsbKXDOZx/3Bt5+Zh1PfjCHqddvW0z+L6JpBmc+/i5fLdrADRe/Tmd7CMMwefvlbZlu532xAgBd1flh2qKfa2oHPqp/ndtWTeGsH+4irmsUl7cwPfgR9ZHWXzXWW+Z9zZ+nv0V90P+r6u9lL78lezXovxOeDCf+cW6SItj6trJ/7nq+aOnP9A0DGTOgCk2QyMrrILA2D0dTEkNWMEQwvHakrlQUlyET9jyj6NgrJvHep0vJHLiJmkQWeYqfZZ2lpDujRJucNOpORhXUEkwoZFmiCOj0czYRL1SIJ2RiYYWN4RzqYxkEkxYszRZAwNYgkByuYMYk7M3gqBPpFl10KQq6X2af9Go+WzOSbtOH5DKwrqjFmJIDXpXFdWUUVrSRKQdY3VgE6SaCJNKpu5EwqVxXQOSbDJTWONZeuRxzRD5PfrMcAKt9xx2EC8+ZwIH79yUQjDJqRDnPXP867z/0OQDdLQHu/fImnD/WMwwE3cTZFKcgLvH2jKu2a6uodwEvbXyED/75GT2HlZGel4EoixT32rVpy2/JlNfeIDJaIn+Jjq0DqipbAMjzeXjkpIs4bPI9mBKIhkgsXSBZoVKfbqM8aUdaFcH6tp/uPgVIFh1nqwymQsX9x7Ppho/QVZ1kXGXhF8s56KR9d+j7/nOfQk1omIaJc04l0hof1j8lcMbsRHukowTacDttXHDzMdvV++G9+QBsWlLD5jX1lPYv2vpb/2GlfLLyjp89XlEUueTGI/jwzQUceswwnC4bvYb34Lu35yJbJK6fsP927T05/aqfbQvg+huPIuPpb5EtEmefc8Avlt1dFkZ68s03I3DZdfQRpdgmdxMRRYrbQ+w3ZiV1sw7hY18S/9Q+2DpFkjYLcnoCQUiS0Cys6c5n89dl9B64mlXLK5AUDdGjcvmip3lw+Lk/61BsGAZDP7yBqO4EBCZkl/LMAafufJDhJBlKGDFqwQSKhnUwb8VzlPf5228yB3vK/Y+eyivPz6KsRxaz5Gaq6haDAoOywwhICAJ81/UshbbUjktkuJvMv9lYU5dLtlXAGtYQksbWnZ/qylamf7KMEaN78M6cVahOCTms413VhaSaPH//55x9dSpU5eu3v7d1HNkvrcB/ZF+CSTvVGW6MuwWkDp3Lhk7gg3O+Jb01wdqla1lUVoBS1Ykzx42jw8LN959L61dr2LCkhtiQPByuLjIyu3j6wyPoI7SSVa0QzjGREibdmh2vFOXx2omYiIQiFgRUQEZskPgyuZ5JPdqQJYP1C8r5cUsoGEn8rufk90YzDEwT0qpVdIuEiYYAaIrIGzXzeHneXMLlHlzruhAUiYNO2tE0qCUQ4qb3Z1Cc4eOmww9gcUsTcXEZ6/yvYJUEStI7EK064SYPoVVpHPXda3x9w1/IcDt2e5z/XPY9n7TOxGZTOeGrBuZOvfo3nIW9/BL/yWgre9rurFmzuO+++1iyZAnNzc1MmzaNY445Zuvvpmly22238cwzz9Dd3c3o0aN5/PHH6d+//9YyiUSCq6++mjfffJNYLMaBBx7IE088QWFh4R6NZa8G/Xfi8IsmYAxUQRQZvG81CcPC/O5i+hS0ENDsVIayEec4cTUksHWpaBaNZBqEjh2I/ajBvLDuIcoG7DxByS/RJyOLtgVFdKheuhIu7v7uGIps3TT4vbQ0pyPX21gXzmbxmgGYAtRFM1kbyeRw7zLGOqpx+pJEuh34/Q5EUcIUt/m2xZMWLBYVW6uINSKgSxANO3AP7UYQpFSkivo8Wrp8EIljJkWclTHSH41Q6uymU3WRlh1Bb7BhkU1EQ0MUwOyw4F7VhWdtJ63vr+KZG97emglVsSnEoztGrOjdK5dRI1LJV34a0SIRS2nBz7vpSBxuG56Ejj0aQwiEmTC2x07nTJZljr/maIYdOIjSfgX/EeE8Gp1NqKmEWFMpnY1ldPif3pp+vTnaSFiPI/dMYutIORQuXVhDeIvT5oIZK9Eau0g6JZKOLbJLu0J+z3bETmGr1t1v8xB1S4iJVLSaOYuq2O/olImA0+tg7FEjdhwYYP0xcY4okVaShwBkzQwhhTW839dAV4ieI4sp+Zd5ySpM2QordoX8itw9npMjpo7kufcuZuopKdOA4646kscW/IMXNzyynXC+O8iyyF8uOohzz5vws4LvnhCMx/GrNgTFIJIlkfDKjBm8jtN7zeG2qdM4q2QVl516H2CS9OmYW85CsTOLMQXriW7wMa+lnM6BkDQtiKJGad9mJJvB4rZK7pz71s/23RoPopo2Uo9rgZltm3+27GlD+hOZlwE+k/2fWMS4v63gcW8XPd+6nT7v3or2K53Nfy2KInPOXyZy4OSB/Ln/UOQGO3K1nYC+/UI7pySLc+4+Geep6fiSSQxdJOozsG3uxohHUG2g2wRaGrq578FPufbDa3lh+kIWVjeSrYlIamq+P35l7tY2J522bWHW79EJBPrKZDhCpO4yAT1Tol2KIkmp60Oxykw8bjQZmR7S5mzmjNIiJo3uzfHXHkW/fSpw+1UCLR6qqrOgK8rGqiLEpIirxUAwDTp1LwuDhZgIYGhkOfz0TGulKB7AkdQAk8pNuRhINKzPJpGhY0gm9PyJt/AfgGQ8ydJvVqJpv8210qZ20WNSJQ5vnM7BCuESJ5F8O0IvN/es/owscRPd++Wx+cp+bL6wHzd++e0ObZzz4gfMq6rj7fnLGf7s49y55D7m1T+JTU6iGhJue5J+vkbUTTZKD64h/8DNXLHgvj0a55etc/F64igWHYv3949ytJc/BpFIhMGDB/PYY4/t9Pd7772XBx98kMcee4xFixaRm5vLpEmTCIVCW8tcfvnlTJs2jbfeeovZs2cTDoc54ogj0HV9j8ayV4P+O/HDkhpyPV3USy5ihoWN8QKy7FFGZtbwXUMFglVEa7Uj6zrtwxXiuam04bEsmPn4tbh+JrnNrhBFkRyvixWf9UMfHSYYdbBoaT+EpIm7W4OolZrObEwD5raVI4gCXzQNYF/PZmZ+MRolI0IiS8FsFLFqSZxlAhNy+3JQrxLuXTAL/zd+1GwNUDC6LJBvMjC9gW7djqAksIRMHJ2QGF2OslEm7/0uDEGkMeYjqlpwp8Vw+RoJJ2QsksCauhwE0UJZuD0l4qhqyiZ8i1149cpajss6m08jPx+F4i//PJ2uFj+RQJQbX7sEgD6Di3l/yW18/d5CHrjidQTgs1dnc8GtU35x/v5xysP88MECxhw5gr+9feWvOgf/SlvTyViM77CJFsKGjsU0sUTvpCV0G25R5q3OAdiyR+H0JDBtNoQ4mAo4XKlroLx/IXJHADHLDmkeDM3AFASKM9rocJRAdgbEEkgJmfSPa9D7lSJtMds+7dGTuOa585Dln7/1n1x4F6/e/j7jjh7JymV1fPjCLLrGZGCr6U5lbgXWf7l6h3qvVD/G8plrGDCu9w6ZUH8NgiDQe+QfIx39Z2s3kjSt9DxqA92tPlzNGuM8NUxyhBAFgXZd4JtACacO+IobCitZnlSwmho3Vh7DnO6+SFEJPSmSKDBY1ZFNYZ9mMuUQY80a3n7xUL40mzAWf8Ytlx++Q995Dh+yrKMmZUBAEn7ezOXy647k47M2E/GZXNCrir+1jqSlOxMQSGoSYz66l0XH3giApnVS2f4xG9VGJuZeiEvZM7vfPeXbFZXkyw4Ksn2ICKimgAUT1RCRZZkTrj0Gb4OV5+Z9huC3YGuLIAAth2RhWoRUrPwZYTg9iJmQtrRqYi2zoK8WMA2TioHbNFSHnXMQow4bhmmYnLD2KQwTrLJOobOL2qYc0AVOOWg0Z360D49f/RqL3pvD1MwzeWLJvZT03daOosg88O3NjLvwAWLrBbzrWklf0I1h60Darxcd2SK+JSEaYz5+WN4PR2YM2W+S17ubI7NX81LjeCy6iRhUMBSRPLkD24guOr12NFknGf/jvIY1TWNq1ll0j+iB8dQMCnJ9vP3wWYiiyIb1zcyZs5EpU0fy8bTFvPXGPMrLs3nkydN3ugiOx5K88/oc3q5bhvvQBA1T48Tr3STQEBwGVqWFQzIXk12usyhZAFWpDK5fr69iTVMr/fO3OU77kwFIGuTPjTDknyvIcwUpDHYjiRrvdvdkiHszTptKTd8WWqsykN6Ko25q5fYjn+NvT52zw9i6OsM8fP900nLcrPZ3kZPhwTvEoDEs0rwpEzMmMub1BxFUOOPo0Zz3CzkK9vIb8AeyQT/00EM59NBDd96UafLQQw9x0003MWVKSnZ4+eWXycnJ4Y033uD8888nEAjw/PPP8+qrr3LQQQcB8Nprr1FUVMTXX3/NwQcfvNtj2atB/51o6QzhciWZeOAS6pMZ1ESzyHJGsIgqY3NqaOn2kPRJRPIUTGlLynBMvAs7uPO0J2mt7/jVfb9/2+n8ZdxBvD7kch485AgydBvoAhmftJO1wE+w2o5iiVPbmENzwE2GPY5spCQ6vc6JpUEmYw1YNygwO8nyy9/k7+NuxjWtCRERa5tMnmSh7N02PCsSTMpcy+ZAJvXNeaCLGBbApuBqFJGtFnDYeHfuWLoiLjqCTmJBicq33Gxoy0Q3ZWw1Bt3D0tDDIYyuTqz27YW9H7XiP4eiyNz2/lXc//XfdrB1HjyuF6KYmt/yvgW/2E4ynuTbN2ajxlVmvTuPSDC6ZxO/E1qazkcyv0PfkmzFjoggiamwg6KMLEgMtzQyuc9KfI4o4TPD0NqA1NDA5rUp/4Wcokye/P4Wzj16H+wRsBgazrIgZZ4AZcfXYPUkKDs/iU2UcG8KIiVTWngBuP3ERzjcdzZ/KrmIZHLnGrKckiyufu4Cxhw5nPNvPpYXfvgraYVu/CPdmFuUfUP277NDPVmWGTFp8NZkTL+GBV8sZ9nMNXtUp7vNzzv3fURbXfuv7ndXHNynJ5oGmijx5PA3uOGI98mTIySN1JslTZCIYuOGwkpU06BEjvBFZz+6dTsuZxRvQRJxsw0xYKFvWhulng5OyF3AplWl/Dip85dWYxgG37Quoiq0ffKqOwcOJsMexGcLs/Sonw+pKIoi375wCW+/dDGCCRI/nuPUWyqxRbb3x2p5eMNUVnQ+xGT5OaTO4Ty3diRrNvZifu31GP+iaV/aWc2N82/g402HUFN309bdnt2lIxjmia/n09EVZenmBj6qHM7sth7M7Sjl0PyHtpbbN3sCw3tvwpMWIjhGIZouY0pgCKDLJprPSqY1yH4HLaewuJXsnG7OPQesZ/bCf4fIvFNreHDFxxiGwW2vfcl5j3/EvJpmytxVOOwxbIJKiR5Gjkp4LAmum/4V+UUZ1C7cgGmaJOMq79z30Q7jX/rNKljbRVqNia1li29KXGNgTGfBQ5dji2jU1WegaTLJFV6ylBhWyUAWDIp7tKEWJJFCEBDt2EUdW1EUm13FYjFwOH/5efZ70tnYRTySQMtyEy4QqI4FqG/upr09yIUXvMjrr87hrNOf4fVX5pBMaKxf18SCeZWsqG7i0Jue47hrnscfjLK2rY0Tjn6AJ2csIu7rpDnkweo0uPegVznghCU49u3Ca4bond5FV9RGUpIQJAOvI4yMRmdwW3K+dYEqDtj/a3KiEUQdchzd5EhdNGkuVF0kaViIqRbShDDekgDhBjvuNX6kpMHc9xcT7N7R1+aaS19j5vJK3lq4htWVLXy9YCOd3SZt9enoLnC0i5AwMQ2T1z5ZuFtzF9aiXLTkMs5ffB4ru1ftugJQG27lL4se4a41r6Lqf5zr4H+RYDC43V8iseemZTU1NbS0tDB58uSt31mtVg444ADmzk3t3i1ZsgRVVbcrk5+fz4ABA7aW2V3+OEv3/3FOnDSUj5e8SbYrQGvYSyCikDAEejtbaO/0kPaxAzQBJBG5EcIFBq7KCJkz21hGG1etvpfXVt/7q/p22BTOPDQVeqwP2Qw4LYfJj72EJKTCi8V1O8oSiAwQiBoSue4gN284lmDfJI4aGUlLCRACoGxsJxpICaods9dy1CPnUr25neMnD+buJa+SViPQGHMRSNiRrRpyVCKUB0oYbpo6kT7nuXjy7k8JLovT7PNh7ZRx/6MRe1uEWLsPn96CbtiJF2djBoIIJsT8Ie747AYeOOsJ/G1Bxh0z6lefh6w8H28uv5PqtY0MGvPL2llZkbE5rcQjCRS7Bbvr34u0oGkdCOYn6IaIKRhogkECAwwTuyAhbjHjaTRsVNg6abb6UN6Q0P0p4eqhy17mkW/+CkBZvwK+X1CNtTlBuiNIs+lFwqD2cS+G20HVuy6uf2YcL/pWI3VHMNJdyJLI5iXVAAQ7wyz7djWjDxmyy3HnFWXw2WVncfA/nyEwqYJ+Benc+sCOWql/l2f/+jbvP/IFAIPH9mDjokpGHjyEG9+4/BfrndbjYuKRBC/89U0+Dr36b2nvNSOOiIwobv9oTHb24twcFz2UOAkgqYtEUajUIhRhYBMELIKBucXgUTdhvLuJy/JWEUcn1FfkqLcu5d4xryB6TN7x96HLdDBgn41sbMrirtPfYrOewSULvufS7EV81taDjniS3q4EbzUM5rrimdzTz83yUBZhrQ2HUvqzxyCKIgU5PqatszDOs4lonote2R1kiN0c62jiyoXLsegqGV6FY3whEASe7M7HKpgYsk5f6Q2eWz+XfZUGjKTE2/ES7GacC7IamZt0cVl9IWLNeYz11eO1DOGwkquJ6Ql6eQqJhFfwResXlLpKGJ5z4tYx2RQLsk2l96QqatrScLtUkqZMW6uP4QdsC7f4Uc0aPm0aRF5RO5VdZbQdnIMq6eAykeKpjbTWD0owRq3m2ONnAfDmvEtpiFeRl+vHIWl8XPkDz367Dlc1FB+/mXtWVlE2OEko6aQlbqMj7iA7Fie02stGsYmOQ8LsO3U07z/4KQgw+bTxO8xp+cBibK0RtPR0zLwcxEALxflpXPPU2YiiSGFxBt+02nE0GYDEmNL1SA4dAxObI4Fcb8UaFQm4PeiIyLIOaiq2o8Pyx3kN55Rk03tkD2b0BsMlggn18QDfrfh+SwmTUChGdraL1uYgggA9K3I55ZG3ia3oJmrCEec/TvNIifLuOGqhh9aoF3vCQFHjrDBKaGtL4+zy2cRyFZLY+LBhMG5bhLtPfo26tiwee/tIbrjqdXoNLuTFu87ENNrJcoTowk6GNUaGHObd2lGMza1kRTiPaFJiVSIfm6QSx0Jpj1ZUKZUszXGYzhfBz5ninYL8k3u6y1CJFFgRNTOViRaBlhUCao6I1GHBKItgNtkREFB8u3d+bll1I1HVz+LqYlasfIdi11JeOObPv7j7feWyxxmdNo+oaeeude9yUc/HybTtmTnf/wS/gwa9qGj7eb3lllu49dZb96iplpaUL1hOzvZhcXNycqitrd1aRlEU0tLSdijzY/3dZa8G/Xfiq6YqMpQoIiaGalI5N5fwYg818QwWzhyIFBcRtFR8cEWREUQBIaFvtfdOxtVfbH9PKMvL4KWTp+Lqm47R1Y1zeRDVCYgmZlymqiUbi2AgyDqGN0nWPg4evv14Rg8rQ5QsIKW2l3sO68FVF03m8ftO5oBJAzjy1LEINpkfOvuxoTMHKS+GWhQl3WXn9WtOZv/SQq4/9kFqF2yk17IQN8ljcawWsPgTqVT0ugvHyhjRodkk3aDbUw9GQYCKoWW80/wcM/R3uOX9f895x5PmZMi4Xru0TRZFkddrn+SSx8/h9dqndihf2dpJcg/sNNtahqAaEDTsvNg9lE5VJ2iYBAyDmKmR1DVMTHpYu7GiUuIOkDlgW4jA8gHbO5gcdFA/pHWb6XoTZEmjIe7DcDowPU5w2nnu6R8IHNKHRJrMhPG9mfHiRQwcl4rgYXfbGDq+326P3WVTkBfHUWICmyq7ef6tObuutIesmrNh6/9LZ6wg3B1h5ltzqN/Q+Iv14luc7HRVJ9gR+tlyhpH8Wc1vY+ulzKzuyTc1A/mgeiRzmlNOlc+vO4jW2hIMYB9njHTZxCaaWEUDhyCwMZnJJs3C2Z9MYfmKNAIJgQYVXMBwj584BgYmmRaYfsqD7FsYYLTLzzhPLXaivNo8mlcvfI1u006hJUi2M4Rq2qlNKByd3kKj7uW4/CUsD6Zx9qIpPLJ+PGM+eY2otmtt2yFenY+b+9M/u435K8s5wd3EpkgGua52+rhr0HVIopM0TLyYRHQXZbYkKyNu/Ngodeh8SgmhsIup6a0sMq1sjnhJmAonZy/hKPcmNkY3UlWzPx9tPpX1m8p5vPpiDrU/QR/jOiJNJVv+ijG6enLOlBnclD+LHt5Ozi6cxesV03hlyKsEo43EtdSif2JRBWHVRlPETWGPdnTFxMzTwRBIWw+6FYK5Ck+8fwTTftiHDYuuZ31rN9g00i1Ryh2tNK/KxVEcIG14J652Hb/Vxpq2UiRRZ22wiJKidsKbXYAAhsin89dxwf2n80rVY7zf/gKDx/ffYS7Tc9N45dPr6J3jpaJPAY9//zeemnMbWQXpbFhRR+O6JqSgSO58HSmhEwnYWN+di2DA7E29CVssWPzgqtL5YNEIEoYFpUkivsRDokPh8gXv7NY5/U8xa+ZaJu93FwfvfxcH3H0cukvExGRAn03c13Q/DTnf4BwQBIdO6Ykq1ac20nWYStNlGkcufIq2RCC1Y9MrSmhYHF96CNuRfuRQnKgLDF2kRfUimxq1L/dEEk1kxSRpWPDaEmRZQxgIPPv9ZHLmBXDXJ2j6tIrlC6vwKVYWBUoIVRhEr40QN2SqwpkMd9SyJNSD5sV5DE1r4K3q0bRH3QSLBWIP2Sh7uhvPxRrT26bzz40Pbne8hx8/AkMy6JoQgywNU9Nxz4sgBEUEU4AcnY4Dk/iHq4Qm7DpLL0DCaGVjay49JT/t7WmsWtHJyS+9+bPlg+EwvexLUUkpFEwEZrX9fPm9/HvU19cTCAS2/t1www2/ui1B2N5vxDTNHb77V3anzL/yx1m6/4+zbNFmrBU6S7sLkUzImwvGGQlMQyDmEslsjSIkNSI+A6Epgq04DzPNS6w4ijWU5KZX9yzRSjwa/0VTg3H9Shn3wXXcd/YTzHhxJqFh2Vj0XKyDM9gn3oNVz26kTDcRMCneJDDs5RJcosSl7yyDinJkReLhObds1+aFfzsa9blv+MxoQhIh885WHBtj2NxWel95Dstmrd9aNtAW5L2HZ5NhGgilRbC5gfSOGK0jy1JaDUSaLxpG0Wo/T/3jXNJz0/71EADwB6MIooDXZd+j+dldPOlujvrLjjZjxzzyKhtbOrBaJObcdAGO3fIR0FkRyWNpLAuHbPJw174M8Y3jjLJLtys1Cvhh9Z8wDQ37nyEzJ4kcV7n85jO2K1dYlIHLJmMujLH/1XV8U90XW4WEucXSIyKkUp0baQ6q27qx2RTum34DgY4g7nTXHjtPmob5Yz4Xajb/9uYkF957MjdNeRBJFomhEQ/HEUSB9Lydn/sfOerCg5nx8nfsc8RwMvO3t6OOBaehhS4jiUbCNDENgW5DosgCgmkiSRItqopbEHAKJqru4kBHG5L2CneuWkSaHMclQ9KAkG7gEiUckkBYU7CaSYplg27DQ2ewL+s2FHL8e4N44R/vsFkJUYGOJIBFELAiY0Hf+oA2ENFRmJzRgAOJXFEjU9ERYgYL4pnk2AwcImiGiNUKM40+mFv1KQKvVy7h3D5j+CVMA1RTJuh3kFfaiYDIPN0FosTR3iB/a+rPI2aSS9I34SJKk+bCAHItCUQ9db5FBAYpnSyK2ehpjbLWlChQAhSJAT6LljLW0UZfR5BZwWK+VQv5s7sRSZAwTBPRFDBFE93UwYQp6ZV4RJMTCuYzyR0klhR40j+Y/fRj+LS9J8dlViOKXr6f9CFHfP0UmqWJzH6ttAR84FMxZBkEEdUloiesbKwtotXeSH4fFys7Oym0dzHt/f0RK6LITo2gaNBLi5OT30XUb0PyRmhL+rBJKkpxlESNC0STw0ensvruKllUUUUBzz193g7fr15cA4C9TUEvDTHkiI18+f4+uCe00JCeRlxVIE8ne66BmDToSvNSWtxES5MXR0WApEvgq5a1hBZEeH7cmb84ht+SB57+ivdWrMHms1HakMr/YJrw5Pz5jBu0knJXB3k5Ad5pHIJhg41jHaR3yGyyduNPOrH00zB0C0aik9BwN5mjuhnRs4qaUAZOkixMLyPZw0RoMfHaI3THMtkcTaPXiCqyRT/1iTT8upciRydNsQxeqh9LyCqTrm57zjTXd7MuXcJQBeS8OMcUL2VZuBwjKtOqezA0kaQk0RDJIBZTCMh2vM44EdVFep8YK/wZNEd8tAYbueYnVnmH79ePZ+bNRJE1lH4R5EU2zIQGkoDFHqM4rYNNWi5Jp8HFA375PgO46d2PKenXSYfXTr0/F0cbWNISrA63MHHCLTiSErKioOsm17z0Ip3dDh5+7jjOuaKZZi2DlrAX0xRxZ/w2IWH/2/g9orh4PB48nl0nEfwlcnNTwQ9aWlrIy9sWJKGtrW2rVj03N5dkMkl3d/d2WvS2tjbGjh27R/3t1aD/ThQGbESTFloSadQH0kn4IFTvpiXkRS+MYemO4e/vwrm0GWV1PZmrDJxNOmJGBomeeTTuQfSF03tdzJGuUzmz72W7LHv+faeSV55D/uYozx18FAtOvZDKl1KC9I9rvca6bgA+e3NBKtkNkJ7h2mnGt8vOOZCuzWXke/zYN6W0v/FQgpWzNzDyoAEM3rc3DreNE688FNMwEHUQ3U7Egb35280nMuvpK7h64pbQfzaZq+89nfJBpTsd+59ue4lDLniSQ857ghlz1+32/Py7PLbqWza0pQTUhKqzoKZul3U6omtpSrhwSCpNeiYbElkkdGUH4RwgmdQoWvRnIqaN9euKWaAPYYFjKOHk9ho2wzAorsjFYyRJmjLNbek0l7q3/m4Lm2AAusm1J07Y+r0304MoihiGRij2NZqxY9KYnXHZeQciSwIej41rL9p+0aIZCea1Pc5a/8e71dbOyC3NYtTkQZxywzG8vPERTvnbcTyz4gGcnl8OlXbJY+fwSeg1bnrzip+MJ05t4wC04KUY6ICAjEC9plAqCaimhkWyoBoaEiALAkUyjHMkeDbQC0kGQTBREVkbT20aSaJBl6GT0EVU04oqmnSi4FNKuH3KoRROb8ezMsqVRx3FwILNOPLWsjZuRTAFkgbImISSBqujWXzYPoACM8q7zSVIgkSapDMz5kDFygRLPW1xC9loiKLBtPpyOqJ2BGFb7uqppbvOBPpISwkj02p5r7EPdd1pNCQlRggdgMnXEQ+npK9neagv59YewdC8BxnpUJkRdJKhpPT+CUNkJA20uq283LwvccMgzREkgpX+TgNVl9nf3YiChCKYDJa6qVatW/uXRBFhq/cDeGWDuGZhnCOCIRp8lMxlqmc1X3f24Pr85WzCyXDHBvztfYjQQSQsMzqrmlGZYZ4Z9zIf/+1hpk6aw+UTqkASMDEJxOLoSRMNCzWhDErymxA9KoYpkuMOo5YYHJy7inOHz+LPBQvwvQHVgRw8o7vImFpH+tR6snyuPb5WIRVnfd4nizjy5DEUlmehRDRshwXI9YWQdYHuRdl8XjuYUl8bciC1cyPHDdJnm0STFkwDvJkhTi+axd193qOH9R2+nL6CQw6+hwln/JPvl1fuYgS/ntb2IG/OXYHuiZE3aDlrPR1bLQy8w1oY33Mj330yDIcZxiKYJBIihatiGJkameUBpAgUu7qxyQnczgSyHCe/sIOYKVPhbmOQrx4AmzNG9iKd5EOZCEGB5mA6pWPrebVuLPd/PoXv23oRM2yIEtTGMlGKQnBWBCFdx+hncPCxw/i4fiXL/CUIsoHXEsOfdJDmiPJdqA8JTSCebvDt7AGYYQUMcApxSuJBPGKMzcFMErpMfcRLdWibUuHkj15j4vhFlDs7EdJ1TKuF5sMzMLwahmlgt+r0zmmhIrsNSdlxV66x1c/qylQSuRXNdXwfm4csqKiiiGk3GHDAekKyhbT1CVRJpKNAJqiqpE+qBNFgxdqeqIpIWHeysSOLT9YN4dP1g/BH9jyU8l5+P8rKysjNzeWrr77a+l0ymeT777/fKnwPHz4ci8WyXZnm5mZWr169xwL6Xg3678QpJ4+j+uvl1NGJv82JUGDFsUijuTAN3xa/AdEAIz8dsSMAqo6tS0A0QVSho7oLdsORPBKM0lSZStLQsKGJZDz5i9lHPeluXqncPpyQ1tAFhRmYgCjAUceksk4eefI+fP3RUgzD5NDjRv5smzNPP59nly6hatxMKmdvwpPuYtD+qeyfd79/OQCV65t5+c3FQErkOOvCiYwdn1JxnLffaM7bb/QvHuc/X/6a2upOfozl8PG3q5g8tu8v1vktqPR38lHbR6gZhVg6JHSXgcOza+35541n05koZkMiH1EwUEyN2wY+tNOyfxl6LXWVjfSYLdHUmIGpGCRNiQOeeZZFF/5lq+b7k6e/Zt28jYBJS9zNsPIaFmulxP0Sfc0MLr32cFbXtTF8QDE9S7fXzMTj1cQ69ydsSrwTKqBQ6UaWsplQPPNnNetTDx3G1EN3nv10Tv1UhlpWggZd0RtIz98zR0+AKw66g+aadma+O5/0HC+n33bCHrcBYBgas2vHMVj2ExPAAmimiSyItGtO4nIIY+tOo4CGyWJ/JgM8bSmNhWlB1UAWTDpVG99qvanUQqQR46Aei5FlmQIglKyjszHEWzd+w6DxmxD0lIhj6AbRYBxfpoux5ZvoDn5BLHw1HgwE2eDZluG4rBZeCRzASb3WMHX1QTxS/g0HuJxMdJzCG01v0cPSzmnTD+O8IYvIcWTxdIOTIk8bEc2BiUa6bdfxnWesOZZ+voVYvs5kw352btx8AH8p+g4xblJlZBI3g9ycP5OeOTOxO/KoSNuW0fRqI0oovoL98odzgChyQ//Uq2I8cIGhMa96IAkBXvHncWZaLaYApbYQt7SMpa9tLrKkoRoaspCKyyoJIqviEvmywbPNfbiucDUaMgPsBo1GBps0K33kNryyQVA3eK7Xm5TZk7wbKue6nrORAd0UsO3Xiij60ZeXc/mRHyPZTOa0lyFu7kWezU9e726KZQm/4aE55KLQq9LD1UYQNy0zctGWOYhnydiLQlg+suLOd2CMN3a45mdMW4w7zcmY8Tt/prz7wMc8c82rAEy5/Aie/TLluPv0so94r+tbME0cbSKBWTmYFoHcdUkSTgNrwESOQPvXacg9IxySvwKXqnLpopMgqvH1Sx/SOdyNAFz2/Ce8f+Np9MjL2J3Lfrf5uHotL65cjOowmHDcEiwyzAuU014BiDDE0Y6hQzxuIdcaob+3kaQuUTFgPW3lMpnOELVry8npFaSyLQctrnN4/1XkK36qtAJGedbzbusw0i1hoih4csN0WzJxLzOo7Cyky5qOmKljqbaQ7CPjF7z4lDghvwevI4J7cIz++1WRNGSWdC4jbCxEEdMwBYFN/mz29W1gujaYtpiH1kg6gs1Ay5IgJkPEwtjiKtZnlBAxrQjoZNmjhFUFu5QyJfGHY9Q5uziloJFeQjMPfH80Uk8LcgyShoYetBGKK1TWFAACD7VVcVLJtvl7+ZtFPPV8yv9h2KQ85meuJMcXwzBFYkkrsj1Jdn431g0qk/ZbzkdpY/A4wvjTvPzl+AWYCMzu7kFQkFkVLKA6sm3npuYnzrH/X/EHiuISDoeprNy2OK6pqWH58uWkp6dTXFzM5Zdfzl133UVFRQUVFRXcddddOBwOTjrpJAC8Xi9nn302V111FRkZGaSnp3P11VczcODArVFddpe9AvrvhNfn4IHjrmG/o+9B6QkaAtEimUSrD5sjAaKEsypGoncWYmEafz58GO+8u3Rr/aFDdi8GutPjIL9nDk2VrRT2zv9F4fxHkgmNC855jtamAMqK9WDIWDWDsl45ZGQ4yRZTV3jPfgV8svJ2tKT2i+26FRtX7jMOvhhH0B9mxgszaa5q2S50Wc8+eYwb34cVi2uYespYTjxzv522tWxtA8+/N5fJ4/pw1IGDAJg9az3vfbCYSF8Je6uA6hbZaAboCIbJ9Pw6bdjuEtdVvJYoRT2byRoSxjQ1hmfl77JeCa1EpEIcYpyEYeHPJWeRYd35dmbL5jbQoOoYFdvdYSJtLhAE/IkEGzs76ZOVqpeR59tSQ6Qt7ibdE2fc8EomHnwEp5VPBaD/oJ07HEU6DwDBZG3cxyhHAx5BJyEEqGzsQ6+ijXs8L8PlleimSdwQmVuZRc2s5znvqFNwObZpVNvq2jlv8NXEI3EufvQcjjh/0nZtxH6SsMXfsXta/R/pjq9jZfNU+lsCrEvaKJajVKnplCp+JCRMVCKmTm9rN2+FejDVXU0EFVEAlwjT2vpzxdoj+Gj0yxQJXXwcLuEgqZoP1d7UaXYiZk9uHfDYdoKcWynmnH3Po6u5m29e/4HxFxzGsnnVjDt4IL7M1HUoiiIZvsPAd9jWes/kxlnUvZyhaYNwyQ6uH7j9sVyefiLN7QFeXPg8dy7siSgKWA5xUNfZgWzRGZu+YwSdnfHMEadw2bsuRC2A43s7tZOLuFU9mZNK9uPC3r8c6ksUHXgdO9/al0WZ/XquI7fhLB5tCnFJoCc3F37PkqiXW3odzJfdh2AT8jk6ZwD+wB3EtUYyLVPp4R3F3Ja/4LMmeLClgksyNvHPjmwKhXbyhSB2GTRMbKJAniNOEoXhjmYMA6IiyCYUiSqLVDfFPTdjsSWY4qgnYZcY2auFFxuHc1rpd+zrrWNa81BK8/z4rBEUUQfDwFYWpu4QLwgC0ms6aBDpTvDRG3NpWrgR3dA57dYTeO6fM/j642UAnH/d4Rx7yo5ar+Uzt4UZXT17Hd1dYaoq2zh3xJE89+UCbN0GBgKS3SRtSQwBCWtCB1UHWcK3RKatzCRTjjC9YRCmIZDxURtJiwvYtg1f29b1mwro71Qv49pZX2BNmEj7JFBkmD2nH1hNDJsAmCSNJC/WjWa/Q1bgIYrdomGTEnT0dFJu78BrjVGY286m9ixkq0rAEJicto6QaWN1ZzFBTaFmbRHe3kFyxCDOP2t0P5YBooizWcTfy0ZGKIqsQevyPJRe3XSqMroqodh0xqZtoC6Rw/pAJtnKtShyBfvlVfJ9cwUfbBiFR4lhl1V8mVFsFpWoaYWwiGFAcrOVPqNa2ZCWi1+1MyK3HkVKme4kzC7Ax3uzViKYJsuTRezjqiURsSLkGWStAlOWULok6jrS+HHnpy24fbSPhz6ahc0wEENRFnuXc3DeWuZ1l1MdyWDT+iKk9ARrOhNMzl+JrzSOYoSgS4JmAb/hIRmPszmQjS9ksvD9/gyesp4SVycgcHzP036zc72XX8fixYuZMGHbjvOVV6bCK59++um89NJLXHvttcRiMS688MKtiYpmzJiB271t9/qf//xnKp/K8cdvTVT00ksvIUnSDv39EnsF9N+ZktwMaqr9hAtMTAn+1HMA7yTX0DbKJDNi4fNnLmHjwk08dsnzjBlUStrIXhw8aQADB+5+kqKXNz62Sxv0n/LYI19QV9sJ7d0kt6R/F8Ihuuwi1UurWTB9GTabzJHnHogoirsl9P/I+QOvoqOxi2eueZU36p/azkb4lvt2rSG97M530TSDpWvqGTmohLwsL01NfgxRJDkogV5pQ/ELtHSHueaVz3nx4uN3e2y/htWB9Vxb8AVvu0cT0BxopsSZC8+lcflYuiIJbjlkAscO3NHJzK0k8RpR+jmacAsxxmX9/Er69NuO55Xb3sXTr4iiskq67T6GldXQ3JVGz4zLt5bb95hRXPTQGWxYVMki1aQ2WYmMnZNGHLPL49DNlD10hdyFhEaV6qJRT0fEoFhrxSb/sj3uv6IaJk26zPs1/fjwrQOBIN+tfp2P7zhra5m37v6QyJYIQK/f8d4OAvrNr1/Cw5e+RGm/Ag47c/xu9+0PvU9dx1UMtWjoAgy0JonrsNk0mRPPp0Lq5m/3nElHo4thg4u55YYCWlWNCs/+pGyAktzoaWX+Vx9w6OyLcAcSHNZ/GcudeXhsHq7scQU93Dt3qI1HtjmQ7Tu+Nzc9sWsbYptsY7+sfX6xjMWy7UEuCgKP9JvMDae/ALrJcbeW79a89MzI4LMLzuar4RuYu2ozFxw4lpx0907LJuNJrjnoNrpa/Nz4+mX0Hd1rl+1XFL7AQ/kGd617kbvbKrio53EUpfXj1J+4DGRnbdudcwBH9/gGgMpQM5uSIf5e2otlrZ9w3GcDuWrMJ5xia0LfYkZXo7qpSrrx2qMomDhMWKqlc4Z3A+fsswq3RSRhCJyZW4lq6pyat5qnuipwmQbH5Kzly1BPvFIc0zSRBPggOALDJoIGhkVA0lL9vH7NSwRaAwB8+cJMsg4YvnXMa5fV7lRAv+CB09mwqApd1TnxluM54ciHME3o3S8f9WALsgbRfBFXQwJBkBEBUxYgaSBsqCfTbcHf0guroJHrCyB3GET7uQk5FaSkhjUqIllFJg6u2KHvf4dP6p9mnzKDmnV5OPMCRGMyca+J1xMgoSsImNgkDV1woxgmDgkimg0BnXXhPIKmjcOtq5l48FKeW78vEjo+bwIQiEVtdMZcLLT0JLw8g/g3Niou2owkga9/F13r0jFlAUkz6PbJuBMmjjodx2I37fsbuHv60U0Bj5RkfSAHpzWGxUxgmuCzxogGrZiGQDDpIJiAwXn9iLuWY0toOFvyqc9K4FotUz8xDd0UaYx7SLcmCKk2JMFgQ3Atb25cz7tzVyEPN2iKpLFWSWC6VISQhWiuSXm7gyYpgdPUSOqACIKaEtQ/3bieHJeLSCa41yfw97BwXo+5OESNRVIZCzt7oJsSykon0X4+crIqsaZp4NawumN4FsRpUNOxmCrIBoYoIIgm+fYgGd4IgmAyr/MBSj33/6bn/L+BP1Im0fHjx6dyr/xce4LArbfe+osRYGw2G48++iiPPvronnX+L+wV0H9nHrzzBI4772k8jQY5WR7uOOwgupJxGrIC3H/4IThdNv7+pwcId0eoW9fI9UcM2yPh/Ef2JBa1vmVrHq87FTLFNOkzqicNTSGMeBwzHueR859CjcaZctmOiVR+ie5WP5DyYN68pn4HJ75d8pP7xNANZs5YxVOPfoVR7sBiVdFlK74CP97cMB5tz+dpT+iMh3ll49s80EfBKSTpNN3opkBtTS4t/iCyTePur2dxaI9U+EbbT7THId1Oha0dERNtF64fx199FMdffRRJTePZDQdgZFjwiAlynAGaYkspdm7LAHrUBZPggpSgG0zGcMnWXTp/BuIb0TGRTQGXpNOmybTrLkZYG5EFkx+aLmVS8du7PS/BZBerkw5Cpkiwy0NK82TSGdzedvOA48fyyVMzABg2adAO7fQb3ZOnF9yx2/3+iBa4hBxZQkBEQ0MywRQh3+Jnc1JkXmcZHY0pjfbSFXV47H/C5/xxjkRApshTxrKpV9EeDrPPM8/w5pL9kUWRDZdf/ot9/+3dq3ji0hfoPaqCA47fuX3hugUb+eixLzj64kN2S/AFyPS5uPOCw/hs7lrOPGI0nz07e0tYPvjg+R84/JidZ4HdGZNG9mbSyN6/WOalv73F2rmpnZN/nPzIDmZvP4coivy1/9m7PZYf6enOA1JOVkNzjmTGlLHcu2ggmWIBh3vORDT9NOsyDtFgbTydntYuBNHEMEw8FhUREROwpkRfREQM0WSwrR27JGAR4hzl2YTPiNMtiDgtYXSriSDqmLKEeHQ+k5M5jBjVg3uOvnPruJJJnZaGrq2fL7hu58+7ot4FvNf6PACP3Pf5j3nU2LCuiWTPNGS7huqCeLqEtUsFSUSQJeyxCDF/kDA+cp7YSOwEK904yXCFSd8vQndYp1d5PQlTQV1u8Oajn3DCRYfvkUN3Vzz6syZQ5d421vmz0NOTWCxmKrKvYKAaErouoSYEOuMuku1W1reXMKM8SFfUwYr6Evpm1dMc87HMVohHjhGsdWP1JWhP2KnvkYZFMmht9ZHQFURZxz27npbT3RQpAQomNlIy0cZBoSN45vnvECo7QEuSyHMTzZGQ2iTMchlFSuKSYljlJOX2dsKGg+X1xWQ5A/ikKI73vMQLwJqEZ844BX9yCi7Zxu31X/DJ8vWodolnph2J5E4y5MB1+FUb+pYoKS+vr2JjYydaxIssaozMqsMQZE7edw61ndk8Mu4xvDYbzV1Bblr5It+1q5iAxyox4aXn2RzyAzA8kcaGvjoZi4MU2rvIlaPUr0vH4dKwZ0dRE3bUr9L4vN8wDEHFaU8Q/T4LR40fWTCwCyrOXgGklTbca+IoJ2lYRAPThO7kpt0+z3v532evgP47k53p5tVHz2TxiloOnzgAURR5aspR25VR7BZI+WXy/A1vcODJ+/9Hx3TZFYeyaEE1AX+Us16+jFFDiigbUMz6xdVce9BtxLYoCed+tGiPBfRTb/4Tb9/7Eb1G9GDYgQN3XeFfSD8igzV17UhWkZxsLw9O+5hIqUhgfARDFygYWs+YvDqylRBBrZlA03UYRgKrKKJiIACS43mcvsm77Gt3eLrfJzhNgeG2BrxikKWxCroEkdwRzYgS8H0LxxRcBMDlj5zG5JP3JazVsTReSH+lCUXUGZH/w271pcgy6ZYEuplg8ao+zPl6CK/bZvPerX126tjmUXYdyebxa98gWfYkUw4XkEWTdzt7scyfx1WlP+CTDAQBehmz92hO7lrwCAVpuYxyVDNx4DKWra0g3OVk0qTW7coNHt+fN+qeorO5mz6/QYbQYLyBWMcoRAE6dQFN0rCbJmE03Eg4JYFc9wQ85Q/zgfMxwpEEmb8QveZvx97PqtnrmHLF/rT1cnLRPr+s5QYYMWkwL6x7+Gd/1zSNy8f9FcMwmfnmbD6Lv/GLWVx/yqR9+jBpn5Q5S/TwQcz6MpX8ZMyE3fe1mPPRIp64/AV6DC7l1g+u+dljL/qJ+VnGLqLm/Cfo4cvg6UnHbPm0GicwBdgY+AYTk97e1I7TGWmbkAPjCeo6VkmgwxQowkQXQDYFEthp0UOUyjpOWcMqgscUqFYNvtn3eSzjVeZHc8mU/VjlbAYXfMnlT13AQ+c/habq7HfCWOasbANSuoqM7F1HfXD96MRcVQ/BMJ7DRqMqIogCsXwLutWkp99OYWYaow/uy4s3vA6iiAh8/s0ALMM1Tu09jxxriGBS5Cv/MNSFBtGbNV5mGks/X8N906/f5TjCySSjP3iYmKHisVhZ/qerdiizuLOYYFSmILubpCaz2Z9BxCohmykjYFOVkEwdMy5RvaGI3L6tzFk7EM1usqitL2LEwqCJ9TRGsrE1mlgiAjFsfL+uP1MGLcZY7qFL9SJEJHSPDfXJBPPG9sc0Rc4ZM4wTDhzKF5+soGllB6JhoGomhiwgJ0UEScNISLyxcCzDB27GNAVWhQoBgR/qelGyPkY8AZbqbcfjU1Jzf9tfDmP/hT3J9Dk59+0PsT21GusknYhu4UdTlQ2BVnIzg9ThwysmMEwRQzVZNiWNRGuC20bfy4Pf3ow1qeO8uYUhB4tkj+rL1yvaCMb9/Ojv3JCdgAhYKmKENBs5UhRREFATElZXEqWPyusnXco997zHt60BzIiAN6YQl2ysC+dQZuvCttGKvVFDjpo0Rbz4lBiiAILw2/ob/NfwB7JB/yOxV0D/P6CkIIOSgp+/Ec+77zTuPvkRADqbun623G+FYpV5Z9qOEV/6jCjn9g+v5cbD70IQBM6688973PbJfz2Ok/963K8aV1gLs7amA9EQMRJw6D9f5MgxZbwfakNxxsCQOL54GUNtLfSyRRHZAAZYRYmkoSFsiSKhhc8iGO2FJ//bXzWOH2n3/wM3BpoII52tDLB14xETVHrTUA0Rf8hB7lcpobR7WDqX1i7GuGcRJ45bwejCdjTBgoYFf3IJLtsRu9VnrmMKGyLTWTK3H4YhEo6avDB9Idf9eeKuK++ET178joP+YVKlO5B1E4cUZWmkB4r4PQFd4fJlxxBWrTzlaGFARu5utTmnRuXYDAtVahqdeiZ/njKD/s5W2lU3cM92ZbMKM8gq/PdfQi0NB7Iy3shQOyQxsaLRqFlIF1REyYs98wMUpfdWgfSj1y5mU3UrvXvu3HRn/aJKFk5P2R2vuuMrvoi+9m+PEcDQDAxji/OoYWJoxq966o4Z35dXv7qGaChOyc8cw8649/RHiQZjtNV28PVrPzD5tAN2Wu7QsyYiCFC/oYnT//7rnHP/E/TyHrjd5zJXBa+vGMmEkgXETBOPqBF3PoHD3pNE+xFIajfTgoO4MHcpdsFANcAimHhFE6+ssCKhMMjWgiKCSR1tzX2ZfFrzdvPy0iMz+G76Sqaevu9ujfGUM/dl7mdLqZ2felbH17cji2kIcRNBFDBcCu8/sS1akxZPMn/Gaqq0GCv0HIZFN5CWFcE0IUuKUGRpZ9mKHOQtWWAbqlp32u9P+cf873lq+Twkp47UYiUiGDSE/RS6fNuVi5sCfbObqQ152FhXgGzXEWUNXTPQdZHMtCClaQEKXAGqgyVULRqPKIUQTANR1jF1k4aWHJo0J7mzw8RKFIx9kyxYNYBEpw01ZAUTlGAcuaadrrF9Mc2UudaLc5dStijAcUNKeH5ZE9H2MEpjkDR3Jp0y2AwQIwJVsSz6GY04JI36SAZZtiDaN27ia62gpO6lYUNLd5iDA0eldqdeOOs4zv1wJR1RBSwgiqkEVwcU1WD6TTY5y4l3WWnPcyHOTZBo1jETCVZ9t4q7TnqI9vpO1s+phIUK6y8VMTN95Po6GNS7js5uL2uX98R0iOT36ebj7hHUhTzkvQZ1R9mI2uGM/GEc//rbZH5Wi1Cai7UVEi6DSH8bVslk5mfDSDTbcWsxDKvIJn8Oht9Kwm/lisk7hvHcy/+/7BXQf2fOPutZNm/uoLgkgxdf3PnNOOGEcbx55wfUb2jisHMO3GmZ34vB4/vzWeT1/5O+n1p/IYIwCCEqgEWg2gjwdHweXpdKApVLe8/iUHst6QqIgoxhGugYaJhoJlgMk/lxB32USEp4bygCyYpD+BMJMxt4Fdl2Fda0k3c5locXzGVo1pvMUQs53FVPUBdQxCReKeWw1OBPx0Skc4IPqYeVSG8v7twgYbdAn5wVW0NWAiT13ffU7+E7hFXBL4mlmRAWMDAZN6D0F+u8dfc0Niyq4qJHz9rBpMiX4abHfgHiuoJN1Mh0iNwz9ETqQq/zfO141gdzAZOLZn3I98desFtjLM42mdPVgwJrOpN8q8m0RElgwSnFae5+h7y039YvYFP9IJx0MMImEjdBEcCUTQrMJPn5mxDFHXcXZFmkb6+8nbSWIq8sG0EUMA0Td/pv52is2BTOvPPPTH/uGw4/96A98t/4V7JyvJDj3aM67jQX0WAq3GleefYvlj3kzF+36Ps9mbV4E489vh+PsR9ep8gXz24LrekqrOXIQjjU0Jje9Bplxl08tHkk/yj9jufaR3Jr7goiuhVBjgICkmAQ16GuLo/i4uat7Zxx6WTOuHT3d9wURea2f/6ZMz6dl/rC7SSYC46WbaFql1c18uE1bzDnw4UUVORxy7RrOfupt7A3mYTWZNN5hYtsJciGeA5rQvnED7Rj/0FHiZlc/MApuxzDBxvW4rAl0ZrtSLGUQPzwjHncN+XQrWXq6zshBNlZYVRkNgomyaiExWEgW1Lq4aQpsbnbR+hdHW9rDacdPp4nP/iBjsF2Cr5L0DxBY9GqChRJJUeLIQVUMnoFaFuSzfKmctI7DPzlIu6v6xATGmLMSEnHgkD2mxt5dk1qji58+EyOvugQDMNAlmUWbarnms0PIVTbkAMyn2UOJEOIEg/aSS7z4WnUENAQkgaIAg/cc+LOpgGAAQU5DPPlsCIUpiKznS495XeRKceI2AXcjaB3pfFV5UgsjQIZxrKtdTctrSa/Z0oxITmdOLpUjB5xxg7aSEMsjfrpJVh0kEaF2Kz4yBeDiKoIQSvFW9b0GwtqSOarCED6SgFN0XG16lhrAwjn6gQ6neh5GqwQQbQTfNPBMlLmmdMT3Qw6Y5en+3+PvRr0nbI3DvrvSGNjN5s3dwBQV9tJY2P3TsuJoshzq//Jl+rbXPbkH29FrelBVtQNZ0FtMSvqJ/1sdsZ/l4jm54iJi8jaEEP1gClBz7IGpgyZw/z9XuHYrEo8skHQ3PIiFAQMEUKGho5J3DAJaTbsooFPkJAEwEyQMN9ANB8BsxMtdiORppJfHMeXVZuY1fAKuiDjE2JMj5SwNp6BSg5jnO283f8t7JJKliuIZ/8k2iAfFEQo7d3Ixb2/AkEmbsjopkBSFyl0H/qL/f0UjQwaE2mMnbiMUeNWEsuDc9/7iPnVO4+9PvPN2Tx/4xvMnraAKw+4eYffH5l7JpIsEAraWPBpBcmIwKS8AZiuG6hwtiKjUe5qxy7uWmv3I+lZTWTZwgQNB2ti+SQR8KtOunU3M9ofIKp17nZbP/LEDW8xpexy7r/oxe2+39TyMqLZgYWUCYJkgoCEgoBV7L9T4Xx38GZ6eGbpPZx5+wm8uPqBX9XGz3HSDVN4tepxTrz+2N+03d3hiSX3cNRFh3Dze1cxcN//fBjS/zQ/TUgmStadlpFFmSMLz2BA8UYMy/4csuYMFgbLeDfoZaQ9QNQQETAI6qAJEDQl1tXtPHzo7lLQI487Pr2B8SeOw7s0RNbXLYixlAZcEKAkJ405Hy0EoHFTM9ceeT+dgSi+Gh3LIUG+qu/HLa8cybQXRhIO2InOyqPzgD60HdGHgQfu6HRuGAZnDLmeQ9LO4Y7Tn+TgogVM7rUCi0XHAFw/NLD8Ty9wlPdUOrbswra0BPBH7cxpLCepC2TnBbHVyaCDpougCUSiFlrftuB5vg3z0wSfPfUVzhaN4k+6kHST3LkpaccahEgPN5awTOgzL4VvBsj5LohWJpC3MIZa4MEEMqZtILdboNzuo4e+zS9q05JqRFHcau41vEcBrc0e9O+8eFcoWL5V6FIdxBocCEkTwQTdLmFKArfdNmWX5+Pxb/5Oz/R8wrqNlXWFrKwrpEhpINMXwppQcTSoWNosYJHpnDoIyWPH6XVw0aNnc8t7VzN26hgEi4ySkcSaF8MmxhjprCGpWcgd0YijIIqeJaMlRdo25ZC0b5MD83J9WBBoOygbQQf/aA0RDXH1ZhbUl6FnGohxmagvhtTcyUglc+u4O7r/Pw2zuJedsldA/x1xu7d/oWRl7Tyiwh+dVQ39EM0msoDNiW6+rhlBR7yKz+uuZW3Xb2MaALAheAiSoiIZP2ph4KiCVVyZuR7NELAJIqpkIJgGcVPDwEBEwAoYtjNIMJQsOYqBiQEgiChbN41SKdi7DZV2I0ltQ97PLjRUQ2dcxQaihoIgCaRJMdKspfQuXoosQNSEU3ospEdmB20BH1pBgANK1/PPsk8Y4KnHn3TxZecAGhI+5vh7oMi7n83MLjookto5r3gui1p6bFU0PDVn4U7Lh7rDW/9PxnZMHb6g61wkU+PVUycy67EBvHxyahs/rpdzeP4KPp7wJI+NfJsHhz6z22Nsi6ejiAYeS4LvWwdRICQZbu2gj6WV/kor1S2nYRhJorFvMYxdp802DINPnvuOSDjO9KolrKuvBSBQPxx/9EaSmBgiNKsiqmCSMHWSJqRlf7jbY94ZxX0KOPGao3D5nP9WO38kPOluLnn0bPabsmt7+v8GBvcp5LqzJzFhVC+eve2kXZZ/bvS53Nj/KB4aegWH9piJlL2eiuJVRLc8UjarLpKYCEYb7aG1/9bYRh82jKETByAv3ohreTuZs9twbQiQM7+DNJeDot4FAFgdCrIikSh2ECiXkHXY0JhD6cO1dDtzEQMS6CAZQFLg/Lvf2aGvNfM30VLbgeaS+aS1hjHF81kQ6EFZ/3pMxcQzvwlMiIXiTHvkcwBGjiynJJLFZn8GGztzCVV5UIISWZ8o0C1iNloRNjuQO1Rgi8DpD3DEn0YgxlXwh2kbqeCpAUu9gimK6GUejnL0QjLA2a5RODOMRRdw6V4Y3ItrnvkLP9x3BV9efibXvXwxmQXpFPct4IIHT9/ueERRZKC3Zyr3RtIg99NOEn4r4XQRZ10Me00A2R/Hl9DZd79fdnj+kQOz96c99KPTOkR1hc3NWcQcEtawib05dZyWdCcPLr+PD7tfZsSkwSg2JWWWabHQOcTHMQVLyBLDZCphghUajrJtz9ja1kxAoOkgK/7hFo4/dhh1H80jc0YzhkVEt5q4M2KEp8Qx8jKIJxWSxSqiKuBZGUZUDSpnrOWcI0ZxxH79ueKU8bt7uf1PIfyH//5b2Wvi8jvi8Ti4594TePXVOZx77oSdZuK86Yi7WPrVSvadMnq7zIi/lkUNDbyzajXnjBhO76x/L42wv/kwOrVleEQBuyEwN5HGYFsTgmEyt+FoSi2dyGFYG76WfsVN//bYHxx2CpO/bUY5M0KeNYTcoXKCtx4BET8GimniFlIZBdt0AatlMsVZDyLLvq1tZEY3E+8aiwlopr4l5pKAAWgYCJgkTQEVk7WNBfQrqEUUtzdDKE/7njrNQDZVVMGGCQzPewiACBlItNNl2rg1+3OOqDmP0TmbuK1iJjISfWSVVjFKQyKDhvYMPJK+R3OQ58hiuDeDLq2NRIZOjwH1GIaAZNm5ffhRFx7C+oWVbF5dz5XP7WiiYjGDaBETXU2tzdW4iKZpjMwahtYOX0ZLadU8FFs6KVf9rO68jQzbOMp8O/cjMAyDdLmVdcGUXbRH6IluQrch8kOiHFEw2N9YSaC5FBUIA6LldjKzfz7yhyiKWG0W2q+xIvQWWBCYSrbYRBJoMHz0xk+rbhLHxC8cQ+/088mwD9mTad3L/zFPPPgFH76zENki8tanV+Lx7jrx0o8cc+AgjjlwxyhAO0MURaYW75j0zJW5kJqW/Sm1RPECTYZAQ9chuK1Lsf1Eo7mnjD9xHM9e9xrRuI5oCrjqUmFFNU3judUPUrm0mtIBxbTWd3LufW+wqZfI2roCspJhMMHaO0gwDSSnCqFU9JFAV5hlM9cw+IBUsre/PvUZPyypxG6VqP1LBYYoYEUnFrcQ0lyAQLRXGu7l7QiCwIQTUxnuPq9fy6q0CJZ2k07DjXu1FdMKchTEVgXRFAAL/gNzsVeFSQ8J/O3tK3Bnevns+VmIBlg7dWQ19d4SgK+evpBETOWMbzcQiyQ4+NjhVAwr4fVX5rDvfmM59JRtAQ76jOzJm/VP/+zcvXLonzj602dIVnYhmFC6qo3OCS6iE2Q8z4MYTDJ44u7vAo0RSnj2+zSEQSYmsC48ldbNVViSItFMC5aYzpd3nENW1o4Kk16Dixl83j60xNchiiYduodO3eDQwUupas9FStOR7urEMj+O/29eDKuFYw8fTvvTy+ls6ETKyyV3cRRBFGk/RkBPF0mM8eJeC8G+kDmrMZWVWxAQBTj5sBE4XLsfeW0v/3+wV4P+OzNiRDkPP3wqAwYU7vBbd5ufhZ8vQ1N1vnt7LpqmMePlmaxbsOeJYwCqWjs48e13+GDtWo5+7dfZkRuGQX3nY9TV5yPpqzBMCCVtxJEYam/HJwokRQGvGCRNhGxRIl8UaWs69Vf19yNzllZx1Ld3IYk6shWKre28M/4dEmjE0MkVoVWz0ajKJJ1X0Le4gfK8F7YTzgEcjlJ8+Q1otpNZXVdO3NBpTyj8efUkTNNEAERMRFI3Q3PHXTuMpSN4DzZJpV7PokN1k2afgkdJxaIuyZtF0oT9nOtRBSfv7/MCt/aeiQpYMHDKIgd6GpnsXUeFtY07+u65o23vjLOZFe5FWa82HL449qSK7aehDP6Fa1+6mCcW30PPIWU7/BaWLiPHF6bXvo1IFp0JRw1BlmWybOk0aD66dSuiYNCo+VjROJSs5FuowUuobdi5TW5z6FOKHN0M8DQxwNPEZX1Frlp7G2vUHEosbZziriZP0UkAggEB3aQ5ehsrao8kkmzeob3rp3/JPo8/xaTnpjJoSDMv9XmHqeltWBCRRHCIAiuTOVQlsxCtFzC24Mk/hHA+f0EVixfX/F8P47+GD99N7QBpqsHtN773u/ef4yii0hiFSzBoMkycok62qLGh5d/baXC47EzrfInpoZfoNaAAWZYYf0TqHhNFkV4jeqLYFIoq8vjimau4xzuUC9rLKKgqJFGWjZyZRJJFkvsH6OoN/iIV4/XF3HDMA1w6/u+0dAb5cs46pA0BQoPzMEUBV5PBda+ezLH5S+mSLYhxDZc9Bwb05Mp3r6XnkDJiiST3rX4ba6WMstqK2GTHGgFrq0k4W8JUpNSWggwWv5XOE/rz6eZn6TOyJ3klGXjTUwuoQ8jE6U4pMEoL0rHZFLxpTqbNv5kvVt2Jx0hwz6F/p/3DHzjikB1Nc36Jad+sIhBNEMu2Y1pEkoeKZKRFyRwaRLs9yn2vnMstj+7aHv9HHn3oC5T5IqXPwJSlxTy0z1UcNioVMc20iRhZ1p0K5z8yXW3BaFBY5C8maDipihbQbvfQMrOQyMc5iLNiyIJC+cvd9Hmxi5yvW9i4pAoSSUynApKEKQgULPOiVdrwj3Czf7yIIY9o2Bu2KGpMk0vvPmGvcG7+h//+S9mrQf+dMQyDdfM2UjG8fAeHMXe6C8WukIwlcXod/PWIu1kyYwUAd35+A6MO2X07ybZAmBOfewrRZSE9L0QksGMIPs3QiBtxXPLP2+1uri3BIxvEMBFEEYsB7wQGo+hxzs5bjoKIBYM2zcNgxU+bYeAWTVTt690e68647cPPcB8QI5K0MFzZxC29FiGbEDRM7KJJHIEiSzG5Bd/tsi1RFGnrvozr7ktFDykpSEc/tpMTVim8PGAaSSBNEFFNkWDseRJNbTgtGeRk3Q6AV4wzUG5mnZ6Fhzjj82/Z2rZF9tG7uBmpbRqZ6pXoBoSFlLDfZppYNJ10SeLMzHWYDCItfdwez4XDdijNidexyRqRD9NIznWxEVjorGLUPj32qK2717QhSSeR8ecQ4ikFXDtx24IhoNyEGnuZMqUVRVApEuOs19w0amkUWGrYmaV+Y2gx/e0NVIvZpEkRertK+XDyZK75bAW3jfiYhGmAAFFdwBAMdKxY0IDVBFtGUi3YKM54Ga9jHJvaO3lv9RoAfJ7ruLWgAYsoIwABdNzIDLV206zZkcVy+ufdtMdz+Z/guRe+5403U85vZ52xP6ecvPN46P+/88A5T/LlSzPJ75GLLT+PeCxlYjBs5I4Lyd+DU3q+TXVDEWmCjk2AMCZuIUJ75w1kZfzj32pbFEUe+fDy7b77+Mkv+fjxLzjygskcffGhfPr6XJ6/J2V+YuuXg1GUDgRItNqJdNhAAntDOJVLC9hQ2s5NG+7GqlmxRE2SpQpmmop3tkDbPg5eWjkRWY+T2xBGSoqYVhvPvfcDt6yYj9akMvD0zYRr+qLpJglDIFRg4t0MBVYPYwf14tXPl5DIBYRUcqwfWfDtWgJdqZ2AZXMq+WbTvWiagSzvqN/78JHpYEIimuSDhz7jL//cdeKuH+lbtiU6kSyS9afBtCs16PhTqTnSYODw0t1uC6Bf/0LWrG5EBIYOTtU9beAh9LiyF9PnrOOMo0b9Yv30sIXGbCsNTblU+LqobsokpyaOrcUkkWVBzfdiE50Ioogai/PuPz4AQLKIjNq3gnmrUgqIWNIJTam52rCiFrFtW36ItGwPk0/YcYdnL3uBvRr0351Te1zM5fv9jalZZ6Fp2na/ybLM241Pc81LF/NG/VNUr6zd+tuK7/bMPnLV5mb2nbySvkNqkaNgaZN4Y3FKaxWOL+KbqkFctvw0rl95PtctP3+nbTQ1FOKWdSySiCJAh5FEEuBQz/9r777Do6i+Bo5/Z7anJwRSSAhFOogCgjQpCohiQVTEilhQFLv+RHwVEUEREQugIooNK6ioWLCABVSkSZPekxCSkJ7NlrnvHwuLMaFn2U04n+eZhy2zM2f3LsnJnXvPXctKZxrpJTYUiigdoswGJYbCpkOBoVGKRnb2fbhcuyhMP4uiPSOPOvZf1m4lJ9tJqjWXt1u8z6NN/sSj8NcOzjE09hm2o0rOD9iw5eCkx6ycQr7q9SCfnzeJqJg5RAA7vWF48BCvGzjUZ3hdr5O+OwnD8JCt4ggzuehs30mSufwS9B6Ph9GXT+KFAcsodoNJU3iVhgbYNLDoZ2CK+4iwhL+JrfvVUcf7b3azlQJ3FGdFbMS5JtzfIfDT92uO6TgZhYUUOL2Ueq3sctbC6Sr/3/+cpMs4zZpOrKmYaK2IPGVmYXEz9rijWeVMpcDlqw89Z+av9Gs1iovbPs7Kou9x6GW0C9tGqiWH2pF9mD1/Ob9/UA8DhRfwAhklNmyAGQMTJuJNZXhNBil6CcW5l5OzO5k/My4E3Fxy5o90TN6FR9OxaobvO6aZKcaDB0XzpDW0TJ1/XJ9lIKxceXDC7oqVlU/eFfDdzJ9QhmL3xgweuLsnHbs05qbhvRg8pFvQYmqYspNwXacEKDZ08j1W9ha/dcLHXb50G4MHvMAdN8/A4zFwudy8dMfrbF+7i5fvegOX00VOpm/1UqPMRXhmPg00G6UZDpy7I6DMBAoKOjpwxZnJvDCBuNtdZBbl467j+wmgzs8nLLYYt10RsUkjcnkxcV97UPusKKCsFqzsZODa40KhMMw68eZ84ta5waPwROlE94zjs6nDuLRFCyxefL2NBkRaD3YetWhbH93k+1mR0sA3TLKy5Bygy6VnAaDpGudeV3lJz0M5o1kKI3q3ZUDHpswYczWvdLiTolI7ZW4TVyQdXVnafxs2/FweG3MZT467nGuvP1gys8sZDRl7x4Wclnr4IZ8v3D6A6LUmirdE4/JYMNxmCubFYPIq9FIvtvhEVNj+ji/jYDetpuncMnYgud0iyewcRpHm2b90G5S59v/Ot1hof24rZi198pgWoaqpDqwkGqitupJvxkmWtX0vAM7iMjIqqW8bERNBn+u7Exbh4Pbnh+CIsJPUMIGrHznyzPV/W2yaTevIbUQbpeSvjcOdb+PZ2QvJzBjP7qxL2eOOQMeggXkv4aSTUbrL/1qXy0nmzhSsuqJ0/wIgNt2MHTBr0LrWI3za7RWa1l9NCe0wo3OGdR9FKIoNiNMgwaRD2QeU7Dmb30udfFs4j083taHEdeSx6XMWr8JjNjE+7SfCTAZewKRBmWEQpZtI0HQapx56iEdl+p/XmlZNk4mMsHPPzb5ycmFmOxERndCxkmgqokyBbgLfiEXf9JLNu87AbZSy0VOLVa4EvJYe5Y779uhPWPzlUjYs3cIz33fhx6IY4jQzdmUhuc7fpKbMI9LRCav5xBZ/uSypHttL4ynrVubrUbIYXH1d5b3xBblF3Hn2Iwxr+xBZO7P9j987bx5ej5niYhvFxTa61Co/2cqMFZtyk2oqIlF3801BQxpYM9jndrC2qC5T1/t6w+a8/RtKQa2zMmlh28OK0jT+cSWz0lnPdxm/fgKgc/erl1Dg1fAacPek25m7oRHhmod4s8KsmYjARBkKu6ZhwsQ2LYrb+8/j/NT1lAL7DI11bjMuw8BjKMLMt5JcNwOrNbQuB3e8sBllERplkRpd+lf/SimBcmAxJLPFRNserXjyucEMuv7oao1XtX1ZeUwY8jLzXv8er94UrxeiUZh0Aw8mXK7sCq/JTs9l5AVP8dKIGUesXPXko5+QvbeIDf9kct/wt9F1DW1/r7SmaaBrXHN3b1LrODB2p7Pnr3/IzczDme/7buuAXVPoVo3N/3canu5hRFtKySmNoPQ8L4W9vJToFoqKwihJ1nHkGCTNLyR6TR5gxaN52H6xlfDoApJa78R1QR4uZSG8fz6mcC8Nvi3kHlcaH142EIAmDRIYdHYbX0IDFJe5/e8lOi6CWX88xujXhzLtm4qLH/3bPa8M492tU/g0dyZN2jY86vYAeHXUR7z74IcsePJLvnp9AfUja7G433h+7j2RYc2Or9zwOd2b0amLrz66y+li4UeLKMorOsKrfMIsZpRJYd+jsWxZI+p59mFyGTgySoj+pxjdC7rFTK2UWF777iFufGowTdo34snP/8fMhX9R5vWiAIumY9J9Y81vHXspXfudTrtzm3PZg32P6z2JU4cMcTnJzu7fjt+/WkrD09P8s/oPpeegLvQcdOxDIlyeQpqZZ1Hfls1GRwrLgajwIiZeMx2T142mdHqE7aR7WAZRuge3ZuDK7UAWYMdMCR5s6GjAP85aNLHlEKeZUKZkkpKW+s8TY40gJmXuwfuuzazPOAezSfMNZ9R00CHP0Eg05/F5dns+zHyMh1o8SNu4ijPxs3JexFo2lctPP5+S0mK0/X3Fe70atXWFrgFh91Er9tgnz+q6zivjK6/6kFx3DRnpjTFjQhmKIsNGkbKQ63UQq+di08Ow40TTIMpSfgJZuZrZMxuQdOnNbNattIur2mEOF6U8wt95l9C57zrCLnBjKAhLrFilBeD5Ya+xYanvD5jx173E8wueACDXm7X/T3LfHx9XNGpT7nUlLjfvLDyHx3t/gUuDHWWJxFi2s8vlGxq0rtR3Cbrt+c14zfo3t5y/iHhzKR0cW8j0xNAlbDMAZzZP4cVHLmfVxnRSE5+n1L0apX7ijQ8GsrfDr9xxwSKUAqtmRts/x97ANx9AKRtOZSHZrLHBraErg+3uWNo2WF2ln2dVen/lavIb+Xoc31+xmgHntDnCK05Nr62cyMoFa2jSvhHhUUc/KTQQRnR8hD3b9zL/7YU8Ne9Z6jTvTyEQrvl6OLfs6Uiz1M3lXjOy71i2rdkJQJ3UWgx66NJDn+BfQ0R2787FbDbz9HeP8ukL87hkRD+sVt8E0NgICwdmLriy80lYqMjuEEmM3UG3VnYKohawc1EyaWen+649eT1E2gz2NYnBtQcsNg9hu01YC7x44yKx7NyLY9NeTKVerjt9GdHRRfyc0xy1Lwy3B0wxBjFPZFA6xMqXr/zANzMWMHvDRKx2K4Muas874/4mIh28VgOXx4N1fxnE6LgIOvZqcVSfbULa4evtH8rqPzb5b6/4ZT0DbjvvuI5zKNfUH05eVj4Wm4XP8t/yt8GhbN+4F0u2B3e4hdKVtdjsjSPelY/uNtDVwW7ZDuc0Je20BNJGXsbVI30daaZtu/nw978B6N26CY8P9L2XPxesI+WaDjw4bR7zn/6EpvVr8/aTJzZfq0aQOuiVCmoP+s8//8xFF11EcnIymqbx2WeflXteKcXo0aNJTk7G4XDQo0cP1qwpf1m/rKyMESNGEB8fT3h4OBdffDG7du0iVD0592Hmez/m1eUTj2r/EW/NpeX/nqfbk6/g+s+QmENZlfs6Z9qyKcWK16Yz4YKPmXzd6zSyu1GAXTewmwxizAZoOi4MIjULNkxoaLgMcGledHS2umsxYVFfnljZndjaCw97Xpu1EWZze7woDKXhUl6chkGEVsb64rqsLK5HjieCJ1a/jmEYFBV8wTtbpzN9y3TW70jFXvYsXlVEWp2PefCSL8lXGg40apkULgWOiE+IOY7k/Eh0PQIrGrV1nQKl8WtxXba57cRq+3AoX0+ZpvnmUNWNLD/J84r7+nP1I5fSc1Bnxs8bSaf4HlWenINv+FOiI4wYSwkxFl/Jr8V7365034S0g39E/HuhohZNV3Nx/RXUthfStvZ2WsWVX7gnwm6jVlh/NA0ynNFcEL2GvaXheJWGR+n+q7i7uug80vsLWoTtw4Ei0VLCmY50ws3J/mOd1TqNoZd1wm41Ext+BvddeQ6pdWJoWG8ktetmYI2YzYJNDXAZCg/gxKC0DAwDYswWMHSaWTw0tnhCOjkHyNpbiMkFJhdkZBUc+QWnKF3XObNX66An5wAlhaX+2znpeZSYHBgGlBm+IVlQQtl/rvb9u9fc6z18D/qEF65GN/mS9OuH+obwtD33dJ6c+zDtex/8A+7GpwZjD7ehmXQ0k4Xof8po9HY2I+NOp2hPJLXsxWRuSyA6vBhlKMxucOzViP1Cw+TwYtttwrr/73TNbsXTuC51ujSmLNpBu8RttA3L8BWf1TSynZFsK4hmW0EMnkLfu/S4veRk+IbaWNGISAfdAIsTPvxq2fF8tMfttqeuJDzaQXStCG4dc3yrTx9OXpbvfbrL3OzdXvEKyX916daEJM2KPctNzJoiNAX5jSMwbDqt29Xn5Q9v55nXb+SuRy8u97oCVw4WvT1v3fQiL187nWvO9s1lGn3bTB6/dSYj949VB1i/bW8VvkNR0wS1B724uJg2bdpw4403MnDgwArPT5gwgUmTJjFz5kyaNGnC2LFj6d27N+vXrycy0ldD/J577uGLL77ggw8+oFatWtx///3079+fpUuXYjKZTvZbOiEFTiePvf4Va77YTHiYjemv3ciCdb6e0NyiUhZv3En35keeUDV390L6REfg9Lp4uNZSqO2hzGtQpsChaVg0RYFhEKN7sWDCjgmXMijy6kSbvJiAPC8YeNg6twnLV/p6u3+I2M6F3Q8/M79F3c/Zs/tsPMYOrCaNAqUwaRBjdjI59XMaOryUet3kpL/H5wXNMCkXvSM241YaurJgUV7yNV9vaoY3jHSvib3ecGpZmtEw5tivJhytWsk7KMpsSCJm6lpcNLFlowGry2qRYCrBA5R6LcSGtavw2hseuyJgcf1bS7uVf1QeUaYyMtzRFDp/AP5XYb9bJ1xLZFwERcUlpA4/jZ0le0kNq03T8K3oWhnNYrPwqMr/Np9y9cUs2fEa3xc7qG0u4I+8elyatJIEayG7nDEAtIqtQ5o9lyg08pTu7/xonPLbIWO/pnc7runt++xefPhDfvlqBZt7X4Zn/6DXaTfX4YpULzO2fsICbwKbyqLJNqK59rSpJ/ahnQSxDgeZziI0ICGy5tRQr8n+76P7eOmO12nYpj79hvbCMDby5eY21Lfuw6NgQVETSvKHcnezT3Dsn0Q//utRPHvjVJIaJnDV/y497PFPa5zEtwsfOWIczc46jS8K32Xvrhxu7jIalx5GdFw4FwzqyOp5v7CqJB6vFWqZCnG7zETGucn7OQKTW8MIB3djN2qFGU+ECavSmfzsYB59/guKzogmoyyGRo4tmHUPdcJ830+vYUMBHQe2Yenc1ZzeuQlJ+8eVz/10GYYF9DLf/+eWp1VeyjVQWnY8jU82PV/lxy0ucvLB9IWc0ecMVv34Ny06NaVu40OvKnyA3W5lztx7GXH9a2woySByaymOZrGM/N9ldG9z6Mn5X24fRlsLOG0eWoTnUWb4FiRcv9J39cWSWYI7xgZohNlkEINfNe7pDpSgfjv69etHv36Vr6qolGLy5MmMGjWKyy7zXTZ66623SEhIYNasWQwbNoz8/HxmzJjBO++8w3nn+S4hvfvuu6SmpvL999/Tt2/1GuN14cx30L7OweSBgoJS3n7nN9rUi6Bn87doU3c7Ebb5TFxdxoXhO7DYe3FaUsWasvmuIsBNrtegvd2NDYtvoR4z7PGYidY9RGg6ytSUmOQfKcjoisu7BZtmwoOJIq+BzaRRaljYYTRh8562gG91s2VrdxwxQQdIqPu7L5bi+djK/qRH1K1sST+TemYdN4p8QxFu0kjVsugYnUeJgmLDhFsZmPANwPAqjdqmYrZ7Yokxu+lZ742q+6AroetmopJ3YBgl9MZKRnoqSoHbaeOqNVcBGlbdzbrTAhrGYTWufSv56bcxv7AVdcwFYGSzcu8s2tQuP3RH13XOH3E+t/z1PJvf3YkqXcjUGwZg0krwKBM6YOLQ9dijy17HvHIa21rtpG1MLrUtBex01cKkGxiGi/NqLWRubgJ1tJ3UNpkoBrz6uRXqx//04W/M/L8PaHfe6dw19RYA8rIL+fq9RQAYJW4IMwM6sVF9aJGQwAsJQ6rwEzs5Zt0/mCEvfIRZNzH9jqrv+RNV78xerXlj3Qv++7qukxIxnNKyZ1hQ2AQUxJqK+L/VtzO61TQizBHUqVebZ394/DBHPTZFeUXc3Oo+8rMLuX3SDXy+/aVyzz9wcTeuWPwZkUYRxYU2oiNK2LK2NkaEiXhdw+PR0CMUe64qJXyvlT/vvJ8tf28jfftO9PhYPtjekd/sp1GCnb3OSCJtZaD5fr72eqwro18uv0p12zPq887nS3BH6zSvFUfblvWq7L2eTH9+s4yX7pxBg1b1GD3nQe4YNJXMXb4kefJfE2l2euoxHS9yf41+e56HQc2bHTY5z8p9nRTTMpyYSDF78AAmXWP3rmROP+9FFsxZislmwZbvRZk0HM7qvIyOCLSQnSS6detWMjMz6dPnYP1lm81G9+7dWbTI9wt+6dKluN3ucvskJyfTqlUr/z6VKSsro6CgoNx2MmQ7/+GtjQN5f/OVZBf9AcBPe97n/e1PUeDKIbekmKgGBf6Vr1r1XMZz/R+jZWIOdawePinwcGPkZtY6oykq+Z7CnWkUpnfF6Tw46WV1xizCTKW0tpVgAco0L07ApRRJJi9eZcYW/wPJyT8CEJX0K3VS0tH0aMJ1N1u9YaxWF5KQ9Csd683nwSHnExFmIyEukuGDj63aQnR4b9LiRmE11yZCi0ahoaFhoFNiQPvIfbgxKDF0/i5JZIPHxC6vQeT+b6VJU3SsdSN9GqyskPwFiq6HoetmDDTMmuaPBRQ6wZ2cmBDWHbsqoa51H+3Ct+EssPLV2ndxeXLL7bdw9WZ6jXqVzWsM1B47FFi4e+YX5Hvs2HU3Fs2NxXTo+Q/3PDCLP94P459RTekV2Zl/ylLY7q7DFncCH+94gpzSyaSa85i09xye2duRcRm9SEx8qcJxJtzwMumbMvnile9Yu3g9AGFRDn9FiOSfsxjUuQ0vDr2YFikJVfhJnVzxURF8+X9D+WzUDcRGBH/4hjg+bZNux655qK0X0jNyLdtdcfQJW8bL63y1tw3DYPXePXg8B1fDdTrTycq8kN27LyQ98xxcrt1Hfb6Pn/uSnPR9eFweZj7+IQDffL2SqwdPYfLkbwizWnn+jPuJ+tPLvOld+X1vA2rlunFGWHFFGGgeEy6nBRcWohtGYzbrrPp5LfZ1WWDRyV0fx1959Sl1WdA0cBkm8Bjo28p4Y+MPFeLp0L4h0ydcxxPX9eXNYyiPGGrGX/MimVuyWDz3L75540f2ZR/8/bhj67EPKRn93FX0H9ieq286hxuH9yKrZA+T1t3CE2tuZ1Ph+nL75hT+H1G6i2Kl4VFg0jTMSmGg+GPNStzJ0XgdNnQvmFyKxg2r78+9qiRVXCoXstdXMjMzAUhIKP8FTkhIYPv27f59rFYrsbGxFfY58PrKjB8/nieeeKKKIz68/LyprMt9gd6OAsyAK+8XftgTT7JWyOlWF4t3zOSZfmE0CstjfWY8FpuHtNg8QOcbbwp3WfIwKQ2HRdEhfA8xZlBeDbOxgz17m2JG8XlhA64I280WSy1KDIiy+ibZlSmNfGUmOf5jEhyV11yNSlpNFPDf6T0dTq/P/NfvPOH3n5K6htz0hphx82dpEo3t2cSYfHW9rHjJUtHsKY1GA+5o/A3x5uB+NVNT0lm4tSEtozK4tu4y/izowiNtBwQ1JoAIi5W2pk1syqzHs79eCobG8u0f8vH1twOw8Z8MHnvja8ztcqFMxw0YaCQ320aZspLhNoOCS+oOP+Q5jH+VDItyD8BrfE0r2zbCTG6ynPl4rFDbXMo1tX5nxR8JWxcRIwAASUJJREFUmP68EWeqi4jk8sexOax49pcVOzCZ1mo188oPD/PDx0u44Lou1Kl7YtVthKhKCp22YdspVWbui19KsVK0dfxB9q669Jo9jC8GTiM7U2PaP10Y1vg3dDPoav8kZy9k722PARiO8eRptWkR3RvzvzoX3vl1OTtz8rivXzc6XnAms56aDUCzDo0BeO65rzEMxRefLeOPPzaRk1uC2WsifpWT7KWxhP0RQUxdyO5gxf63gbO1FxRM6OQrQ3jRbX348tX57PhlA7ktGhOxHgqiYnElurBiEDN4K3qJIqdeDmyr+P5bNE+mRfPkik9UI5GxERTt8131rZMWT06KDcc2D54wE+16NDnm41mtZkY8fKH//ntbrmaTy1cw/oWNY3mp7Tv+53a4I7CaoBQLBvuwaSYKla/MYuMm6Sxd2hgdxSP3X4DZauaczscejzh1hGyCfoCmlb8EpJSq8Nh/HWmfkSNHct999/nvFxQUkJp6bJe9jpWz6GmaWhVlgAkdXSnitGLqWDw4Dahn8WC1FPBPiYOdUeEMiNiEpjRcmglNgQ0z+V4zHmUQqSnWFETROqqQAsNAc5uJtCh62DLY4I3Do0zsUVZcHg/x+AaoNK93+PrM29buJizaQZ26cYfd70TEJW/BMAyK869gXkEiceZcro3ahcNkMDBiAztNd9OmzlDMQU7OX3vwbT6e9AURcZ0Zu7I5d57Zi9rhnYIa0wGJ5o7sLvuJNXvSwKOhK1i508kvm7fRrVF97rv9LfZ009GwEJ1ajKesGIpNtDttAztK4kiwFVPitdAi+tDj+Z96YiCvzVjA2R1Po1XzhixZn0+ypQBNwV6jhHWuuiwpaYJrj8GWaz3At/z4zq98mjOz3HGm/PU07z7xCV0GdChXsSi1UQJDHj72usZVbe3i9aS1TA2JSYsiNLRI+ovlu9sSb3JTpjTCAF0zkecxMbDV79gMsJs0Tovai0UH9/7kHHyTLG3o7DV0duaOp461hHcy6tO8zkTOju/Iu78u5+kvFgDwT/pe3r79Smauf5FdGzPoeEFbDMPAayh/zew9ewvRi124DUXzlnW5Lu40vkzdyPasAhw5GiXxZiyrfJVIki/zrYhptVt5c90L5BaU0HnCKzjW2zAsGq40O9akDPQSX6zOHcUn94M9jPUbMpj//RoGDmhPUlLMCR/v5T/H8+ao9zn9nBY899ovFNU1kd3DjjnbTJn70EP7KvPe+M94d/ynRNeKZMbKCYRHhdHKvoPLo9eyzROOS+lszH6TxvG+Kw6Z3lo0NmVQipVNnjDaaB7KDF+Z4JvvmEe3dSnEx+fTue3RrwtySpAqLpUK2QQ9MdE3QSUzM5OkpIMTOrKysvy96omJibhcLvbt21euFz0rK4vOnQ9dScNms2Gz2QIU+SHocZhUNmblG1ek0Eg2l+JFx67rmCjD6jWxTSUyKHILhUAJYDM81GMf+cpNJ+teJu9pSvewXVgowwC2O2OoYy5jrxfCdA82vZAP884gxZ5PnlfnH2ccVzX/67ChzRgzh0+m+BZ+efSNW+ly4ZmB+xh0naFNP+b7rI9wmMKJqX2R/7mUgJ312HzxynegoCinjLXvt6bl/aGRnAOkJs/kn63N6d58Jd+uO4M2HTYRFunks12Kbo3uw+3xopVCaXEYUVopjiZFGIZGsYpgtzOe3c54QGEYxiEXyGjXtj6vth3iv1/PGkuRUUwpVtaX1aVF+G5A4f1XIYSSgtIKx6nbKIn/vT2iaj+AKjKi0yP888dGTGYTs3ZMIy5RevIFWK11OCN1Fct3noHN7MasmzCjo5s8KGXGjYYJsOiKPK8JJ5Bg9uAEHPiqEbk9Fk6zFTA3vwWrS+rwd9lz/LK3Od7cnv7z5BT5Vuas2zip3IRFd4SOyanwKrAVujCX+q5AxUY7uPbWnlxtdOf9uX/x++rtdD6rIWuzs+lzRhPq1oou9z7iosJ4c9AA7n5mNpYSiF2nyC9NwhqXhTnXSaueB+cSbcjZywM/fUOD6DieP7ffSV04p6jYyfA730Ip+GreCr7+8oHD7v/88l95ccUiIq02Fgy8hTh7xT+uo+IiuXuab3z9U9MWUnKJl7uafc9F8bsochnAw0cd38eT52F4FfuyCvjq9R+59K5eNLIWUWiYQVOYNUgvGkeDuEHkOvfyY34TSiJtKE2jTdj9FHruxKv7KgPleu1ENMnnn7/qMOnup4iKCePF924jIqriKt9CQAiPQW/QoAGJiYnMn39wxUCXy8XChQv9yXe7du2wWCzl9snIyGD16tWHTdCDoXbiEtzUxarpGJoi19DJxwT4BkmZUehmRRkWtP1L5YRpBmWaxhmRGawtbUzL6CxuTixkpfculrmS+btQRxm+lRmjTS7WuG18UZDG9TFr+CavDZ/mduKCRj8eMbbfv/nbf3vhZ4dP5quCruv0SbyKbv9KzkPJmb1aA6CbdLpeFlrLMOu6Ga9mwWr2cGXXHwiPcaKZFH9t2UuzRyZREmkiYo8C3aAgx4HHbeKaBl1ZUZiMTXMBiiiT9ZiuUrSodS9ONCL1UurZ95LtieSMsG00OzObMy6rT2xCNLdNuiFwbzoANi3zVUfyerws/zG0yziGEsMw+GTSF8x7/ftghxIwK77fzoLxD5BZej35hheP8mDToI69iAIPmFDke0y4DR2nspLvNRGOhtNQ6EBdiwfQiNKLaR62m+TCXG6LeoOezW/ikYGzePmml5h8xSsVVpIucbnRGoRRFmvi7Iuak1Ar0v9c/v4hG7quc82lHXjp0SsY3LcdT17Tl24tK1b28hguTMnLad0+Dj3Biko2Y0Tq7Bnelt2PdsZ2+8Gfa0O//pS/9+7h803rmL4y8D///62wwMmBkuJlZUcuI/zm2qUooMBVxtvrlmEYrsMuGtWx02m80PYjBiVuJNxSRpx6iZz0c446vpadfEOPNE3j7AvOZMHOQaxzhRGGIhEvDtyEaV6y9n3Cn3ueJMrk4vfCRqwoTOWV/r9wW9s+fPdJAwzlG/Zixss3r5xFUYGT9B25vD214lyAU5GMQa9cUHvQi4qK2LTp4OIEW7duZcWKFcTFxVGvXj3uuecexo0bR+PGjWncuDHjxo0jLCyMq6/2Va2Ijo7mpptu4v7776dWrVrExcXxwAMP0Lp1a39Vl1Ch6xYS6/7hvx9eupl/MntQaDKB1yDJOgRlaUCD/Df522mijd3LPhR2zaBW7BTOjD64kuitdVzcsyKLn4vyuS0ljdXFr9AmApQRSYlXZ0puB0BjSP0hRFmjjhjb1Q9cyHMjZmK2mLnm/guPuH9NN+bz/7FtzU7qpMUTFhF6vRtnxE9kR87t1KlVhOGxUEcr4Ndtp2PxgsdmojDFAJui1G3DmW2jY/uNvL05gqxSHdBoV+vI34l/qxXWgQS9gLpmD7tNcazZm0LtqGJKnBae+eiZarlU9QW3nMcX076jVt04ul1+drDDqTaeHTKF79/9GYDs3blc//iVQY6oau3dnctjAycBsOhTK3P3puNy5eEseoMbO/THYW2C072dS8O/ITZsAMVGFpnFf2IOO4sER2v25XyCKr2X3W4LXSN28e6u1tzXcC3FeMnVLZxVJx1Ng0yVReauNGqbzNQyRaNrdj5ePZ5cmwfSzPySvZtP3hrCrTdPQbkUtzxxQbk4PZ4CwIPZXH5IYk7mPZR6PuLbwkZkF0exuXVzTK1h78IkNK8G+ysPt0k92GtvN5l4oeOHpOuROJWZDfkukqxOLKZGGM5v0PXG2CNO/PdpgauYO5Y9TaG7mNtPu5y+SZ1JSoqh/4VnsGzjUi4bMYesHa9gNRmUKS9oEKaZcSkDk+arPT+iYSsurvc3JsNEtnqR0kwTBYYbkwF5KBJNFtCgzPBi0qHL9Yk4dTtuNN7Y15IY3Y1Nc3Fjogez7kt/PEYpSzPuIt1VQq2wTnStPdz/M+2pzx5kzeIN1G2USFR8BEs2b+PvnS3p3GQ5GzyKRhYXSkFZ6f+INhy0j6yDroGh4MMMX+/+V2Nb0qXdk8TVv5YYE6Sk5bJ2r29OTqsz0074cxU1V1AT9L/++ouePQ9e9jswLvyGG25g5syZPPTQQ5SWljJ8+HD27dtHx44d+e677/w10AGef/55zGYzV155JaWlpZx77rnMnDkz5GugRzga0b7BzgqPD6h1K05PESvTO5Og5REe8SJx0ZeW28dutvJK+9H++zcttvL4tm04dJ15vUaj8C3THGmJ5GgkptYiMjYcR5iN6FoRR37BKaB+y8DOSTgRyVEXkL3PS7uw7Wz1lLE+qw5GuAflMrP3TJ2wFvk4iyJIC9+LR5nZXbyWLnF2FuY0RcfL/7W8/pjOZzXXItXs9c2f8Jbx9dbWsH+k7P+1cRFlDW51m+Mx4uWbGfHyzcEOo9rZuf5glZItK7cHMZLAKMk/OFTLvb9H12qNISnu4JwluyUNe8ww33PUIdbeyv9cbK3LycuHv3a/QM+wreTokWR7dGIsOmFaGZFmxVaPnWTNRS2zjhsPbmMvNjTaxN8LDAE0zmwcxk3LniD2vkIujF/BCs88srfqnGlzkm9kEan5xr+78OLAhE03Uax8q0SHaRqXR23jwdyevHPaR9jMHibu6054ah4XRWwkPqqYaNMkCtN9i8m93Rl+LEymhSmDxd552Aom4EHD0HU0TeFGUZwH6Nej1CwcmoELAwPQMe8vjavwYmBGRymFi3DMWn1QG8kxFLV1D+/ntGB4zA5Ojyom1/M+23dCjsfMef11LjZZSLK68WLgBXQUdnRcyoMFjVKvwqHrXJG2Fosyo3SNeppGmeHBoXSy8VJL1zFp4PYqbLrO5J1n0DV8Jx7DxacFDWhmzaFTWCYODQoz6mPSNHQ0VrrM5HuiaWLJIcL1Ixm7xhFhSURX4TiNUmqlpON16+zaDT/kdGXdqtMwl3gZ1HoFDs1CruHCrGmEa070/d21ugYD7zyPz175kdNOr8cZ3XqybTdgWFh/XSQ0KiUxJYZz+rYO3Je5OpEx6JXSlFLVOPyqUVBQQHR0NPn5+URFHVvvYqjILM0j3hbh7xU4FsPOGcOO9RkA9BzYgYemVt8SW6eKNemPE+GZzhp3HBZ3GbctvR6VEQYK2nVcx5PJPxLvcGJC5+PCNMJNHsyaQa4njNubHX5F2Mrs3pGMS1M8+PdFLN3nu6Re227nz8urfmVXEbq2rdnJo/3HY7FbeO6n0TVy7P6r/5vF4nnLuPp/l9Dn2mMrLXuAy1vC57vGsD5/La2s2+gWmYPLq0BXbHPbaGH1omkahYYbh9Ix6zp5HsU+ZaK2STG/OJXdefFcl7yUnR4HLWylmPYnvx5NYVYaZXgBjTDNjIaiEA82zYShDMyajsujYTb5zvNHSTQdbPkUKi/RZgs64FUKpRRuzcBraCwqSkCZLPQM34lZWUDzgqahDPCgcGgmdE2nDI8vEQc8hheLbsKrDEyajlcp3HixaiYMpTCjYSjQdNjudNDQ5sSLl33Ky94yKz/lNmVo8hpMmMDQ0HVQKNyGwmbScCuFSdMo9HpwYEIzgUX5ZnEpTcNjeNE0yPV6CdfBoZsp9ipsmuKSlYO5u95C0iJy+L60PpdHrKeOyQTKQNN1Xzljw6BYWdHw4NE8hGlmdKUwNNAwyHQrEiwmdBROL9y0aQDbt9TBtTucGQOncFq0C10pnLrB8rJa2HGTa0QQbU6mX4O55b4T23Yk8XdpAp/knMmF9pVclJCL0pPY6h6CVZuC3RRL3cRvMemB6/AItVznQDytbxqHKUAdPV6Xk1UzHgmZ93wsQnaSaE1XUlTKkMYj2Lcnn7BoB2GRYVisZkbPeYCGp9c/5uMlOmKOO5b6zZL9CXrzs468UqkIvqaJ/2Pdzuk0s+QSZgfd5mL+pW8SbXNS7LXjsDixYibL7SFMd/JPeiLLBsfgLdKpO/F7Lr712C5Zx8R/RV7Ohdj+VRypU2LDKn5XItTVb5nKu1tDf3XXEzHsmasZ9szVR97xMKymMK5IexqAbzK+49OiDzGTxbn2dBL1PSiloWmgKw1D0zFrGgqNWmYv0ZjoGZaNJWwPDk2jlc3ly3B9XdaYlYaGL4l0KA1d0/AqhWbsr16m+RJvs67QNRMGBnUshVh0nVyP4sCKFDpQioFC4TR0dAzSXWF4HIo8ZRBjUljQ8aKh6V40dPantej7p68ZmgEalBoGYfvXuTCh4TEMrLoJpbygmzAML7UtZSh0PHixKPhjY2PS0vLw4FttuhiFQxnoGuzymkjVPGgaeBSE6RrpXkW8V6dMd2HHDMpLlseEzeQhxqSR71VYNIWOYp8B99dbyMLc+tQOd3KJaSNOwwImw1dFbf/7cKNj033XA1Gg768AZ9FAw0IJCl/LQKGuGF3vF56kG+Zkg8SE39lR3IkY3YnZgGamHLZ4Y0kwFdLzP8k5QImWQEPrHrpYd9I/MRuvgrXZLuKjxmLSPRjGXjIyO5KSvPKEvnvVUSDHilfnMejVb/BoDfH9Oz+zb08+4Lusmr0rh4wte3j6uooLvgTa/14Zyh3PDObRN27loht7nPTzi2Nn1sMo0eoToYEZjSWd3iApTGHVLcRaDdwKdDTSlZna5mKKZxl48k0or6902LEqKG3ElU+PRFtpo7k1nAvqNePZsyufrzDt3je5psHtzJ36zQm+SyGqv/OT+nBz4xkMafwFqalLcZUtYcbn5+D1GITpGt8X1cGLwoZBOBoeFLXMTux6GU4FHsMNysCrDDxeHafXi9J8PdP5eMn1KMqUwatbO/Hh7iaUecxoykS+MuG7QK5hATyAFyvZbt8k1vX7YtGUb9Vmu2bQzpFHDjYWlyaQ5VGkezSUUtj3J7Bu5SXL68ZQCi8eDPaPFTfApaBQKQqUGw8KA18PvaZpbCy1UIivR7pEeSj1mPDo0LXhZt75uyP7PBouw0O4bvB1STKZbh0rXtZ7LeR6FUVE4cRBvKUJ8XU3EZuwhui6O4muu5v6KWtxWm8im4ZolnZEJ+2gTupu6qdsp1/zz5jY7UO+2nkx37ibMXtfO/Z5vRSq/dErcOPBvr8ay8ZSB158n6VHKfYZLjwoXMpLCV6ilcJmy+Wx0+Yy/Zw+NKpdm7PqbyImfhaFKgK3ZibNXErHlPmVfg9S63yJB51UWxFuQ6EUbCuMxWI6WPpRGTkB/z6K6kN60IPk7Avb8tKdVBgflZBW+6THous6/Ycc/cx2ERrOSvmVnN0pGIYGuq/yTwluorDj0HTSXeAy7BQpB236ZLHm3XhAo023Zsd8rlnfL8fp8rBuS0Ni91qZMmkAhmEw+rJn2bFuF/dOv43WXZuze3MGc16YB8DLd73BxcPPr9o3LUQ1N/H5b9i0+XS+/Px0up/TjIcf7s0324fSxvILDs23RoahoBjfAjfbDTNReInVINdQhGFirxfstmGYvb+ioZPnOJcy0z7GrY9h3PretIyrw3WlLZj75SIeGv4d9epuI8NbTKruZafXQb4ngbtXDmF3USEAVzRpybM9+/F/+Cr1GBi4jBz2lPxGfPFCrGoOZXgxAbmGjTD7tUR792A1viZf6Zj1OAq9uRQZGvFmcGiKAuXBjsZTG3vTK2ktNlzku9uwEwctrctIsBQwuF0aBebPia1Vnyh7PIOP4vOz6gcnxlrNETRNeLLCPrpuxqrXZcbiv5g/KwZrXm/sp0fz+CjfwlB7MobjMv5AMyWgWS/A5ujAqoIyHlo2m/daf4Ld4sGGRpzuYZfHRLjjChrWeoR4c3yFc9UOO4faaRuOGHekLYVWqevYuKErBga5hok2SbtYsrs+7etuRQGRkXcfxSdQA8kY9EpJgh4kderV5rN9b/Hj+7+y9NuVJNavTViUg2sfuyLYoYlqQtd1dNNwdpVNp77VQ6EqQwNyDN9EtzDLUP4pWEiJYaO0qZ2Onxdxuf0pTu/a4pjPdWGn5rz/wzKUgu5tfENbvpj6Lb999icAYy5/jo8zXyc8OvzA/FEsNktVvVUhaoz6afFs2pwFQLOmidjNYVza6ANcnjy25bzI+7MMykpaMvLui4iMsFP3X6893DJyYzoZ6OYf2F2cz/iOfRk0wDcU6d7/68Hnn4yg2f4FuQ50AfWu/yMzVy8D4OLGzf3H0XUdHR2znkCDqMsg6jLgBcIPcd4DFdiTDvH8Ne4VPLJsLhrwSufB3BqXxIub3sVtiea2hoMCWgVq344CIrcbviEsv+f7H09IqjhM66qGJbyx8XfOX34rtzTpyv2telExHT8xZnMUV7TwlTUu3DWS/9uRzfXxa/kypw1tEp+ifnS7Kj6jqM5kkiihN3FCiGMxZd1gejt+I9FiUKYUkfELsNt99XudniK+3zOTSEttusUPRD+OScQHFJWUkV/spG5t36/k3z5fwugBEwCo2ziRmet9w7OW/7iKH977hUEPXVJuBVEhhK+Heu6XK4iKstOrR/k/ll99ayHvzfb90duyaTLTnr3muM/R58Ln8HoNNA2++eJ+rNaK//c35O4lxu6gTlhgq3d59tcqN5/kkqyL/9zMyMc+ASA83MpXs0NrUvvi7JW8vmUOjSPr8XDzmwJ+vlDLdQ7Ec/qQwE4S/XumTBIVQgTBdY2m8NnuKdQhgfNTbi33nN0cQf+6d1bJeSLCbESEHVyBt8slZ3HPq7ey7veN3Prsdf7Hz+zV2r/Ykzh1PHP9S6xcuIYhYwbR54aeR37BKUrXdS69uG2lz/17KXqv99AL8BzNOV556Xo+nrOE/heeUWlyDtAk7uQMqTzZifkBnTo0YvAVHVm5aicjbj83KDEcTqf4NnSKbxPsMESIkh50Qu+vSiGEqE7+/nkN9/cYDYDZauZr5/vBDaia8ngMxkycy5YFq7np1vPoeZksoiWqTqjlOgfiaXNDYHvQV75VPXvQpYqLEEKIE1Ir6eDoaEdE9Vu4KlSYzTrOH/5mz3crGXf5c/wy5/dghySECBJJ0EWNtu6PDVwYdjX9bFex+MulwQ6nWtu+bhfDzniAkRc8hcfjCXY4IoTUbZzE+K9H0azDaZxz+dny/TgBuzak+2+vWbS+yo9vGMc/dEaIgFAB3qopSdBFjWUYBhOHTsXldONxe3ln9EfBDqlaGzNwIlv+3s5f36zgjZGzgh1OjeByunh+2Ku88eisap84rVm0nn/+3MRXr33PE5dNDHY41daIKbcQGRdBarO6XD/6yio7rrPEyYC4IfQ1D+KJgdI+InRoSgV0q65kkqioscZc/hw71u323+86sGMQo6l+ivKKiIg5WN0hPPZgobW4pJq3xHswPHbpBJZ+t3/lQAOGjjuxFSyDKXNrlv92Tsa+IEZSvXXq34452W9W+XH/+HIZRXnFACyau6TKj3+AYRgYhoHZLOmFECdCetBFjbVt9Q7/7a6XdeTqkZcFMZrqZWiLuxkQdyNXp93mf+zpbx/l/KG9uPGpwVx+30VBjK7mKMwt8t/O3ZMXvECqwJ0v30SzjqeR1iKFUR/cE+xwxH+cdcGZ2PZXYTrz3GOvsrTujw2Mu3oya37755D7LP9xFedbr6KfdTBfTa98RU0hKpAhLpWSKi6E3sxmUTWW/7iKsYMmER4dzou/jyMmXtr2aBiGQV/zIP/9D9NfIy5ReswPp7jIyTP3f4DNYeHBCYMOWdbuv7J27GX0wImER4Xx1Fcjsdqth9z3+3cXUlJQKquziuNmGAYFuUXH/LPQMAz62QZjeA00XePLkvewWisuRPboReP54yvf4kf1W6YyfdWkKolbVI1Qy3UOxHPGtU8FtIrLindHhcx7PhZyDUrUWGf2as3svVV/qbim03Wdhm3S2LJyO0kNEyQ5Pwpj73qPFYs3AeAIs3HfuMuP6nV16tVm6pJnjrjfe2M/YeZjHwKw/q/NPPjGHccV5/EmaKJm0HX9uNre4/Fi7K/LrgyF4fFCJQn6Rbf35Y95y0DBBbeed8LxilODpnxboI5dXUmCLoSo4NXlE3G53FitFt4e/SE/zvqVy++/mP7Degc7tNCnVf0hNyzd4r+9bfXO4zpGUV4Rg+oOw1XqosMFZ/LUl49UVXiihrNaLdzyzLV8+ep8zr+pF/awyns7O17Qlq+K38Pj8RIW4TjJUQpRs0iCLoSolNVqITs9l3fG+JbKfnH4dEnQD8FkPjidx2IxVfnxR0y5ma2rd+B2unngjeHH9NrdGzOY88JXRNeOwlXqAmDp/L+rPEZRs1354CVc+eAlR9zPardy6IFaQlQikGPFpQddCFET2cOsvh5hBaYAJJ41hcvp9t8uLS6r8uPHJ8fx9saXj+u1t5x+P+4yX3xhUQ5KCkrpOkAqGh3w+sj3+HjiXOJTavHmusmHnQcgwOPx8NxNr+Auc/PAG7cfsjddCHFiJEEXQhxSREwE4795lG9m/MiVDx2596ym27p6B5nb9tKpf7tyjz/y/NWMvetdLDYLdz0RWtWCDiTnADPWTiYuMQZdlwJeB8yZ/BWG1yBr+15+mPUr/Yb2CnZIIW3Sza/w/TsLAXAWOxn7xcggR3RiVi5Yw9irJhEZF8GLi54qV1pWnBwyBr1ykqALIQ6rfe82tO/dJthhBN1f365gZL+nAOg28Gwe+/h+/3MxtSKY+N5th3ppUN341GDmTvmG7ld0Ij45LtjhhJxGZ9Tnnz82oukabc9tFexwQp7HdXCVWI/bG8RIqsakW18hL6uAvKwCXn/4Pe55ZViwQxICkARdCCGOyu/7y8cBrPt9QxAjOTZXj7xM1gA4jBd+G8uyH1bRqE0asXVigh1OyHvgjeE4S8pwuzw8+sG9wQ7nhKU2TSZ9UyYALTo1CXI0pygZg14pSdBFyCvILcQeYa+07q4IvvHXvsBvn/7JOVd04qGZdwY7nIC55tHL+OWTxRTlFXPT+Oq74qcoT9d1uUJ0DKx2K2M++1+ww6gyYz7/H5+99DVJDevQ6aKzgh2OEH4yEFGEtNceeoeB8UPpH3YNG5ZtOfILxElVXFDCj7N+pazUxfy3F+JyuY/8omoqtk4MH6ZP56uSWZx3bfdghyMELpeb4Wf9j4G1b2ThR4sqPO8scfLw+WN5oOdoCnILgxBh6NN1ncvuvlCS8yA6MAY9UFt1JQm6CGk/vv8L4FscY95rsnR0qHFE2LHYfFc2bA4rZrNUehHiZPnshXlsXLqFgpwiXhg+vcLzE4dOY+l3K1m5cA1jr3w+CBEKIY6XJOgipF00rA8AZouJS0dcEORoxH/pus67W6dw26QbeHf7NKkOIsRJ1LhdQ//tOmnxFZ4Pizy4WJA9wnZSYhLimKkAb9WUppSqxuFXjYKCAqKjo8nPzycqKvhLYH81fT4lBaUMvLe/JDz4lieXz0EIISpa/uMq1v+5icvu619hno5hGLx0x+u4ytzc/cqtMo/nFBdquc6BeNpd+RQma2Dq6XtdTpZ+NCpk3vOxkEmiIebt0R/6V27csnI7/3t7RJAjCj5JzoUQonJn9mrNmb1aV/qcruvcPe3WkxyREMeuOo8VDxTJfELM1lU7/bd3rt8dxEiEEEIIIUQwSIIeYkZMuYnUZskk1K/NgzW4ZJ0QQoiaz+V08dGzn7Puj+qzdoA4yZQK7FZNyRCXEBOXGMsba18IdhhCCCHECRt25oPsWp8OwLRlEzjtjAZBjkiI6kF60IUQQggRENm7cvy3Ny3fGsRIRKiSOuiVkwQ9hD3QazS99Su4rtFwDMMIdjhChLx1f2zg+WGvsn3drmCHIoQAbpt0A+ExYTTv1IQ+N/QIdjhCVBsyxCWErVywBoDMrXvZvnYXDVrVC3JEojrxeDyMGfgcuZn7GDnrbuo2Sgp2SMdk+Y+reO6maSQ1TGD8t6Mwmw//46qkqJS7Oz+KUor5by9gXun7JylSIcShXHhLby68pXewwxChLJD1yqUHXQRCWstUACJiw0ltlhzkaER188bIWSz+4i/WL9nM6EufDXY4x+zpa19kz/a9rPhpNZ9M/OKI+zuLnBxY1sFd5gl0eEIIIUTASA96CHt91ST2bM+idmq81AIXxywiLsJ/2xEZmEUgAimmTjS5mXkApDQ98h+ocYmxDLyvPws/Wsyld54f4OiEEEJUBc3wbYE6dnUlCXqIS0irE+wQRDV19cjLcBY7ydqezYgpNwc7nGP2wqKxvPnohzRp35CuAzoe1Wtum3gDt028IcCRCSGEEIElCboQNdjQsVcHO4TjZg+zc/skSbaFENXPB09/SmFeMTeOveqI82dOeTIGvVLyrRF+bz/xEZuWbWXElJupnVIr2OEIIYQQ1c4bj8zi/ac/BSB9YyaPz34gyBGJ6kgGNgsAvnt7Ie888TGLv/iL+3s8HuxwhBA1lMvp4t5z/o+bW91bI8ph5mbu467Oj/DguU9QUlQa7HBOyG+fL2Ht4vXBDqPay9i6x387Oz3nMHsKkDrohyIJugDAWez033aXuYMYiRCiJnvlvrdY/es/bF+7i7FXTgp2OCds7KDnWff7Rlb8tJrJt74a7HCO27NDpzB6wATu7vIo3729MNjhVGt3T7uFpmc1Iq1FCo/MuifY4YhqSoa4CAAuvr0vm5ZtZevq7dw3/fZgh3NIG5Zt4amrnie6dhQT5v8f9rDqV51EiFNZYoODE99j6kQHMZKqERET7r8dWSsyiJGcmLWLNvhvL5u/kj7Xdw9iNNVbREwEL//xdLDDqD6U8m2BOnY1JQm68Ltv+m3BDuGIxl/9AumbMknflMnrD8/izheHBjskIcQxuPLBS9B0jb07s7l5wnXBDueEPfrxfUwZ8Qb2cDvDJlbf93P75BsYe+Xz2MNtDH1qcLDDEeKUJwl6CCjILeTmlvdSuK+Y258fwsW39w12SCGrVnIsuzakA5DapHqtjCmE8Lni/ouDHUKVsVot3PvqsGCHccI6nN+WuQXvBDsMcQoK5FhxGYMuTsiHEz5n3558PC4P7zzxUbDDCWnjvhnFFQ9czN3TbuWSO/sFOxwhhBCH8PYTH3Fzq3v56f1fgx2KENWOJOgh4Oz+7fy3m5/dpEqP7fF4eOnO15l6zxsYRjVeUms/q9XCrROuo/+w3sEORQghxCFkbN3DO098zPa1u3j6+peCHY4IZSrAWzUlQ1xCQOuuzZm58UUyNu3hjHNbcWPzu0nflEn/2/ow4qWbTujYT1/7Egs/WgRASaGTB2YMr4qQhRBCVLGvps8nffMebhgzCKvVEuxwTojFdjB+k1n6AoU4VvK/JkTUbZRE+75nsOTr5exan47hNfjyle9O+LhFecX+24W5RSd8PCGEEFVv7tRvmDzsNT6a8DmP9H0q2OGcsPjkOB775H46X3IWk395MtjhiBAmddArJz3oIaZ5p6boZh3DY5DaLPmEj/fwu3cx+tIJ6CadB9+U3nMhhAhFBya/A2Sn5wYxkqrT7bKz6XbZ2cEOQ4hqSRL0EBMTH8WH6dNZ/+cmzjr/jCo53uRfx554YEIIIQJm6Lir+WfJZvKy8nnkvbuCHY4QJ4/UQa+UJOghKCY+io4XtA12GEIIIU4Se5idF3+r/kNbhBBVQxJ0IYQQQggRFFIHvXIySVQIIYQQNYphGORlFwQ7DCGOm/SgCyGEEKLGMAyDq+reyr49+dRvlcr0vycFO6RDcjldzJv+A7GJMZxz+dlomhbskE6+QNYrr8Y96JKgCyGEEKLGyNi8h3178gHYtnpnkKM5vLce+5CPJs4F4KmvHqFDvzODHJEIFTLERQghhBA1RlKjBOrUiweg6VmNAJj+8Lvc1WUUG5ZtCWZoFbicbg50mpeVuoIbTJBIHfTKSQ+6EEIIIWoMXdd5b9s0PB4PZrOZ3z5fwkcTPgdgZN8nmb33zSBHeNCQJwcRFuUgNjGGLpeeFexwRAiRBF0IIYQQNY7Z7EtxzBaT/zFND62BA+HR4dw4dnCwwwguQ/m2QB27mpIEXQghhBA1VscL2jJk7FX8vWAtw1+4MdjhCHFUJEEXQgghRI12zSMDueaRgcEOQ1RGqrhUKrSu9QghhBBCCHGKkwRdCCGEOA552QU80Gs0j136DC6X+6Scc+vqHWSn556UcwlxMmgEsIpLsN/cCZAEvQbYl5XHoLq30j/iWhZ+tCjY4QghxCnhiQHPsnLBGhbP/YuXhr8e8PO9OHw6t55+P4NThvHX/JUBP58QIngkQa8B3n78I3Iz9lFWUsZr/3sn2OEIIcQpwWK3+G/bwmwBP98fXy/z3174oXTGiBpCqcBu1ZQk6DVA+/MPrjzWrEPjIEYihBCnjtGfPkiPQZ258NbzGD55SMDPd82ogegmHUeEnatGXhrw8wkhgkdTqhr/eVFFCgoKiI6OJj8/n6ioqGCHc1w2LNtC1va9dB3QMdihCCGEECLEhFqucyCerr1GYzbbA3IOj8fJrz+ODpn3fCykB72GaNK2oSTnQgghqrWsHXt55MJxvPHIrGCHIkRQSR10IYQQQoSEB3o9QcaWPSz5ejlJpyXSb2ivYIckAk3qoFdKetCFEEIIERK8Hq//trvs5JSuFOKA0aNHo2lauS0xMdH/vFKK0aNHk5ycjMPhoEePHqxZsyYgsUiCLoQQQoiQ8PS3j9Kyc1P6D+vNxbf3DXY44iTQlArodqxatmxJRkaGf1u1apX/uQkTJjBp0iRefvlllixZQmJiIr1796awsLAqPxJAhrjUeMt++JtH+z+NpsOE7x6jZZdmwQ5JCCGEqFRq07pM/nVssMMQpzCz2Vyu1/wApRSTJ09m1KhRXHbZZQC89dZbJCQkMGvWLIYNG1alcYR0D3ooXWqormb+3we4y9y4St28+X8fBDuc4/LyXW/Q1zKIG5rcicfjCXY4QgghhKgqRoA3fBVj/r2VlZUdMpyNGzeSnJxMgwYNuOqqq9iyZQsAW7duJTMzkz59+vj3tdlsdO/enUWLqn5dgpBO0CF0LjVUV10u7eC/3e2y6lnl5ctXvsPwGqRv2sOiz5YEOxwhhBBCVCOpqalER0f7t/Hjx1e6X8eOHXn77bf59ttvmT59OpmZmXTu3JmcnBwyMzMBSEhIKPeahIQE/3NVKeSHuITKpYbqatBDl9LhgrboJp205inBDue4pLVMYcvK7egmnVZdZYiOEEIIUVMc71jxoz02wM6dO8vVQbfZKl/5t1+/fv7brVu3plOnTjRq1Ii33nqLs88+23dMTSv3GqVUhceqQsj3oAfiUkNZWVmFyx01WYNW9aptcg4wbekExn/7KB/veZ24xNhghyOEqEIul5sbm9/NBY7BzBo/J9jhCCFqoKioqHLboRL0/woPD6d169Zs3LjR31n8397yrKysCr3qVSGkE/RAXWoYP358uUsdqampAXsP4sTpuk773m2IiosMdihCiCr2/dsL2bU+HXeZh/fGzg52OOIYGYbBN2/+yLo/NgQ7FFFdqQBvJ6CsrIx169aRlJREgwYNSExMZP78+f7nXS4XCxcupHPnzid2okqE9BCXQF1qGDlyJPfdd5//fkFBgSTpQggRBK27NUfTQCmo17xusMMRx+jhvmNZ/oNvbtj4r0fRvu8ZwQ1IiBPwwAMPcNFFF1GvXj2ysrIYO3YsBQUF3HDDDWiaxj333MO4ceNo3LgxjRs3Zty4cYSFhXH11VdXeSwhnaD/178vNVx66aWA71JDUlKSf5+judRgs9mO+vKGCD3Z6bkMaTyCslIXl93Tn9sn3RDskIQQxym1aV3e3PAiG/7cTPdBVd8LJQJr25qd/tsrFqyRBF0cO6V8W6COfQx27drF4MGDyc7Opnbt2px99tn8/vvvpKWlAfDQQw9RWlrK8OHD2bdvHx07duS7774jMrLqr/CH9BCX/wrmpQYROuZN/56yUhcA3775Y5CjEUKcqLqNkug5uCu6Xq1+JQng9ueH4Ii0k9QogcEjBwQ7HCFOyAcffEB6ejoul4vdu3cze/ZsWrRo4X9e0zRGjx5NRkYGTqeThQsX0qpVq4DEEtI96KF0qUGEjnOv7casp+bg9XjpMqDDkV8ghBAiIHoO6kLPQV2CHYaoxjTl2wJ17OoqpBP0ULrUIEJH3UZJzC16h6LcIqnqIoQQQogaR1MqUAN/qo+CggKio6PJz88vVydTCCGEEKImCLVc50A83Ts9itlsD8g5PB4nCxePDZn3fCxkwJ8QQgghhBAhJKSHuAghhBBCiJpLM3xboI5dXUkPuhBC1FAlRaV8OOEzNq3YGuxQhBBCHANJ0IUQooa6pfX9vP7we9ze7iF2b84IdjhCCFHRgTrogdqqKUnQhRCihsrN2Oe7oWDr3zuCG4wQQoijJgm6EELUUDc/fQ1hUQ5OP6cFnS85K9jhCCFERSrAWzUlk0SFEKKGGnhPfwbe0z/YYQghhDhGkqALIYQQQoig0JRCC9BY8UAd92SQIS5CCCGEEEKEEOlBF0IIIYQQwRHIaivSgy6EEEIIIYSoCpKgCyHEYaxdvJ4Lw6+mn30wf327ItjhCCFEzaIAI0Bb9e1AlwRdCCEOZ+ZjH+IqdeNxeZj52AfBDkeEmF/m/M5vny8JdhhCiBpGEnQhhDiM7ld28t/uOqBjECMRoea1h95hzOXPMXrABN5+4qNghyNEtXSgikugtupKJokKIcRhXHhLb87o0Qq3y0P9lqnBDkeEkLWL1vtvr/lt/WH2FEKIYyM96EIIcQR1GydJci4quPPlm4iOjyI2IZrhL9wY7HCEqJ4UByu5VPkW7Dd3/KQHXQghhDgOp53RgE+yZgQ7DCFEDSQJuhBCCCGECA6pg14pGeIihBBCCCFECJEedCGEEEIIERwGoAXw2NWUJOhCCCGEECIoAlkOsTqXWZQhLkIIIYQQQoQQ6UEXQgghhBDBIZNEKyU96EIIIYSo1jat2MqwMx9gzBXPYRjVeOCxEPtJgi6EEEKIau3xSyewZeV2fpn9Ox9PnBvscMSxCNgiRQHsmT8JJEEXQgghRJV545FZ9DFdwYC4IRTkFp6Uc9rDbf7bsQnRJ+WcQgSSJOhCCCGEqDKfTfkGpaAor5gvX51/Us753MIx9Lq6K7c8cy19buh5Us4pqoj0oFdKJokKIYQQosq0Pbc1v332J7qu0f3yTiflnDHxUYx89+6Tci4hTgZJ0IUQQghRZUbPeZBta3ZSO7UW4VFhwQ5HhDpZqKhSkqALIYQQokrVb5ka7BCEqNYkQRdCCCGEEEEhK4lWTiaJCiGEEEIIEUKkB10IIYQQQgSHrCRaKelBF0IIcVirfl3HhmVbgh2GEEKcMqQHXQghxCFNf/hdPprwOQD3vjaMC24+L8gRCSFqFEOBFqCebkN60IUQQtRAf327wn978dy/gheIEEKcQiRBF0IIcUi3PH0tNoeVsCgHQ8ddHexwhBA1jawkWikZ4iKEEOKQ2vc9gy+L3wt2GEIIcUqRBF0IIYQQQgRJIHu6q28PugxxESJElRSVclPLe7gs/kYWf7k02OEIIYQQ4iSRBF2IEPXumE/YsW43hblFvHD7a8EORwghhKh6Mga9UpKgCxGiWnZp5r+d2iQ5iJEIIYQQ4mSSMehChKgul5zFM/P/j+1rd3HJHecHOxwhhBCi6hmKgI0Vr8Z10CVBFyKEtT33dNqee3qwwxBCCCHESSQJuhBCCCGECA5l+LZAHbuakjHoQgghhBBChBDpQRdCCCGEEMERyGorUsVFCCGEEEIIURUkQRdCCCFEyFrz2z88Nfh51i5eH+xQRCAYKrBbNSVDXIQQQggRkjweD/d2fwxlKH7+eDFfOWdhNkvqImo++ZYLIYQQIiQZHgO1vxfUMBRGNe4RFYcgY9ArJUNchBBCCBGSrHYrNz99DUmNErjlmWuxWi3BDkmIk0J60IUQQggRsgY9dCmDHro02GGIQFEEsAc9MIc9GaQHXQghhBBCiBAiPehCCCGEECI4ZAx6paQHXQghhBBCiBAiPehCCCGEECI4DAMwAnjs6kl60IUQQgghhAgh0oMuhBBCCCGCQ8agV0p60IUQQgghhAghkqALIYQQ4qi5nC4uT7iJ3voVPDloUrDDEdXdgR70QG3VlCToQgghhDhqf369nPy9BQD8OuePIEcjRM0kY9CFEEIIcdTOPLc1VocVV6mLVl2aBTscUd0ZioAt+WlU3x50SdCFEEIIcdTCo8L4PP8tcnbnkpBWJ9jhCFEjSYIuhBBCiGNiNpslORdVQikDpQJTrzxQxz0ZZAy6EEIIEWLysgu4ut5tXBR5LQs/WhTscIQQJ5kk6EIIIUSIeXfMJ+zdlYOzuIxXHng72OEIEThK+caKB2KTKi5CCCGEqCrt+rTx327SrmEQIxFCBEONSdCnTp1KgwYNsNvttGvXjl9++SXYIQkhhBDHpVP/dkz5czyPfnAvT3z6ULDDESJwpA56pWpEgv7hhx9yzz33MGrUKJYvX063bt3o168fO3bsCHZoQgghxHFp0v40ul/ZOdhhCCGCoEYk6JMmTeKmm27i5ptvpnnz5kyePJnU1FSmTZsW7NCEEEIIIcShGEZgt2qq2ifoLpeLpUuX0qdPn3KP9+nTh0WLZOa7EEIIIYSoXqp9HfTs7Gy8Xi8JCQnlHk9ISCAzM7PS15SVlVFWVua/X1BQENAYhRBCCCFEJVQAVxKVMejBp2lauftKqQqPHTB+/Hiio6P9W2pq6skIUQghhBBCiCOq9gl6fHw8JpOpQm95VlZWhV71A0aOHEl+fr5/27lz58kIVQghhBBC/IsyjIBu1VW1T9CtVivt2rVj/vz55R6fP38+nTtXPvvdZrMRFRVVbhNCCCGEECIUVPsx6AD33Xcf1113He3bt6dTp0689tpr7Nixg9tuuy3YoQkhhBBCiEORMeiVqhEJ+qBBg8jJyWHMmDFkZGTQqlUr5s2bR1paWrBDE0IIIYQQ4pjUiAQdYPjw4QwfPjzYYQghhBBCiKNlKNCkB/2/qv0YdCGEEEIIIWqSGtODLoQQQgghqhmlgABVW5EedCGEEEIIIURVkB50IYQQQggRFMpQqACNQVfSgy6EEEIIIYSoCtKDLoQQQgghgkMZBG4MuqwkKoQQQgghRLU3depUGjRogN1up127dvzyyy8nPQZJ0IUQQgghRFAoQwV0O1Yffvgh99xzD6NGjWL58uV069aNfv36sWPHjgC8+0OTBF0IIYQQQghg0qRJ3HTTTdx88800b96cyZMnk5qayrRp005qHJKgCyGEEEKI4FBGYLdj4HK5WLp0KX369Cn3eJ8+fVi0aFFVvusjkkmiHCzDU1BQEORIhBBCCCGq3oEcJ9RKD3pwQ4BC8uAGKuZ3NpsNm81WYf/s7Gy8Xi8JCQnlHk9ISCAzMzMwQR6CJOhAYWEhAKmpqUGORAghhBAicAoLC4mOjg52GFitVhITE/k1c15AzxMREVEhv3v88ccZPXr0IV+jaVq5+0qpCo8FmiToQHJyMjt37iQyMvKkN8DhFBQUkJqays6dO4mKigp2OKckaYPgkzYIPmmD4JM2CL7q3gZKKQoLC0lOTg52KADY7Xa2bt2Ky+UK6HkqS64r6z0HiI+Px2QyVegtz8rKqtCrHmiSoAO6rpOSkhLsMA4pKiqqWv4wqEmkDYJP2iD4pA2CT9og+KpzG4RCz/m/2e127HZ7sMPws1qttGvXjvnz5zNgwAD/4/Pnz+eSSy45qbFIgi6EEEIIIQRw3333cd1119G+fXs6derEa6+9xo4dO7jttttOahySoAshhBBCCAEMGjSInJwcxowZQ0ZGBq1atWLevHmkpaWd1DgkQQ9hNpuNxx9//JBjpUTgSRsEn7RB8EkbBJ+0QfBJG5w6hg8fzvDhw4Mag6ZCrd6OEEIIIYQQpzBZqEgIIYQQQogQIgm6EEIIIYQQIUQSdCGEEEIIIUJIjU/Qf/75Zy666CKSk5PRNI3PPvus3PNFRUXceeedpKSk4HA4aN68OdOmTTvsMZ1OJ0OGDKF169aYzWYuvfTSCvssWLAATdMqbP/8888hj7ty5UoGDx5MamqqP5YXXnihwn6rVq2ie/fuOBwO6taty5gxYyos3btw4ULatWuH3W6nYcOGvPLKKxWOM3v2bFq0aIHNZqNFixZ8+umnFfaZOnUqDRo0wG63065dO3755ZdyzyulGD16NMnJyTgcDnr06MGaNWvK7VOd2uDfcnJySElJQdM08vLyyj0nbRD4Npg5cyann346drudxMRE7rzzznLPSxsEtg2WLFnCueeeS0xMDLGxsfTp04cVK1aU20fa4OjaAKCsrIxRo0aRlpaGzWajUaNGvPHGG4c99o4dO7jooosIDw8nPj6eu+66q8KiLtIGgWuDmvo7WVQTqoabN2+eGjVqlJo9e7YC1Kefflru+Ztvvlk1atRI/fTTT2rr1q3q1VdfVSaTSX322WeHPGZRUZG67bbb1Guvvab69u2rLrnkkgr7/PTTTwpQ69evVxkZGf7N4/Ec8rgzZsxQI0aMUAsWLFCbN29W77zzjnI4HOqll17y75Ofn68SEhLUVVddpVatWqVmz56tIiMj1cSJE/37bNmyRYWFham7775brV27Vk2fPl1ZLBb1ySef+PdZtGiRMplMaty4cWrdunVq3Lhxymw2q99//92/zwcffKAsFouaPn26Wrt2rbr77rtVeHi42r59u3+fp59+WkVGRqrZs2erVatWqUGDBqmkpCRVUFBQLdvg3y655BLVr18/Bah9+/b5H5c28AlkGzz33HMqOTlZvffee2rTpk1q9erVau7cudIGJ6kNCgoKVGxsrBoyZIj6559/1OrVq9XAgQNVnTp1lMvlkjY4xjZQSqmLL75YdezYUc2fP19t3bpV/fHHH+q333475HE9Ho9q1aqV6tmzp1q2bJmaP3++Sk5OVnfeead/H2mDwLZBTf2dLKqHGp+g/1tlPwxatmypxowZU+6xtm3bqkcfffSojnnDDTcc9pfivxO74zF8+HDVs2dP//2pU6eq6Oho5XQ6/Y+NHz9eJScnK8MwlFJKPfTQQ6pZs2bljjNs2DB19tln++9feeWV6vzzzy+3T9++fdVVV13lv9+hQwd12223ldunWbNm6uGHH1ZKKWUYhkpMTFRPP/20/3mn06mio6PVK6+8Uun7qS5tMHXqVNW9e3f1ww8/VDiGtEFFVdkGubm5yuFwqO+///6Q+0gbVFSVbbBkyRIFqB07dvgf+/vvvxWgNm3apJSSNqjModrg66+/VtHR0SonJ+eojqOUL5HVdV3t3r3b/9j777+vbDabys/PV0pJG1SmKtugMjXtd7IIXTV+iMuRdO3alblz57J7926UUvz0009s2LCBvn37+vcZMmQIPXr0OK7jn3nmmSQlJXHuuefy008/HfPr8/PziYuL899fvHgx3bt3L1eHtW/fvqSnp7Nt2zb/Pn369Cl3nL59+/LXX3/hdrsPu8+iRYsAcLlcLF26tMI+ffr08e+zdetWMjMzy+1js9no3r27f5+jEWptsHbtWsaMGcPbb7+Nrlf8LyJtcOyOpQ3mz5+PYRjs3r2b5s2bk5KSwpVXXsnOnTv9+0gbHLtjaYOmTZsSHx/PjBkzcLlclJaWMmPGDFq2bOlfrEPa4OjNnTuX9u3bM2HCBOrWrUuTJk144IEHKC0tPeRrFi9eTKtWrUhOTvY/1rdvX8rKyli6dKl/H2mDo3M8bVCZU+F3sggNp3yC/uKLL9KiRQtSUlKwWq2cf/75TJ06la5du/r3SUpKol69esd03KSkJF577TVmz57NnDlzaNq0Keeeey4///zzUR9j8eLFfPTRRwwbNsz/WGZmJgkJCeX2O3A/MzPzsPt4PB6ys7MPu8+BY2RnZ+P1eg+7z4F/D7fP0QilNigrK2Pw4ME8++yzhzyftMHRO5422LJlC4ZhMG7cOCZPnswnn3xCbm4uvXv39o+/lTY4esfTBpGRkSxYsIB3330Xh8NBREQE3377LfPmzcNs9q1vJ21w9LZs2cKvv/7K6tWr+fTTT/3f6zvuuOOQr6nsc4mNjcVqtR7x8z3w3OH2kTY4chv816nyO1mEhlN+JdEXX3yR33//nblz55KWlsbPP//M8OHDSUpK4rzzzgNg/Pjxx3zcpk2b0rRpU//9Tp06sXPnTiZOnMg555xzxNevWbOGSy65hMcee4zevXuXe07TtHL31f7JKP9+/Hj3+e9jVbXP4YRSG4wcOZLmzZtz7bXXHvbY0gZH53jawDAM3G43L774or8n6P333ycxMZGffvrJ35MmbXB0jqcNSktLGTp0KF26dOH999/H6/UyceJELrjgApYsWYLD4QCkDY6WYRhomsZ7771HdHQ0AJMmTeLyyy9nypQp/s/zvyqL/b/vSdrg6BxvGxxwKv1OFqHhlE7QS0tLeeSRR/j000+58MILATj99NNZsWIFEydO9P8wqCpnn30277777hH3W7t2Lb169eKWW27h0UcfLfdcYmJihb+Es7KygIN/NR9qH7PZTK1atQ67z4FjxMfHYzKZDrtPYmIi4PurPSkpqdJ9jiTU2uDHH39k1apVfPLJJ8DBH6Lx8fGMGjWKJ554QtrgBB2pDQ68jxYtWvgfq127NvHx8ezYsQOQ/wcn6khtMGvWLLZt28bixYv9w7xmzZpFbGwsn3/+OVdddZW0wTFISkqibt26/sQQoHnz5iil2LVrF40bN67wmsTERP74449yj+3btw+3233EzxekDf7reNrggFPpd7IIHaf0EBe3243b7a4wzthkMmEYRpWfb/ny5eX+01RmzZo19OzZkxtuuIGnnnqqwvOdOnXi559/Lldq67vvviM5OZn69ev795k/f36513333Xe0b98ei8Vy2H06d+4MgNVqpV27dhX2mT9/vn+fBg0akJiYWG4fl8vFwoUL/fscSai1wezZs1m5ciUrVqxgxYoVvP766wD88ssv/kuh0gYn5kht0KVLFwDWr1/vfyw3N5fs7Gz/+GdpgxNzpDYoKSlB1/VyvW4H7h+IR9rg6HXp0oX09HSKior8j23YsAFd10lJSan0NZ06dWL16tVkZGT4H/vuu++w2Wy0a9fOv4+0wdE5njaAU+93sgghgZt/GhoKCwvV8uXL1fLlyxWgJk2apJYvX+4vS9S9e3fVsmVL9dNPP6ktW7aoN998U9ntdjV16lT/MR5++GF13XXXlTvumjVr1PLly9VFF12kevTo4T/HAc8//7z69NNP1YYNG9Tq1avVww8/rAA1e/Zs/z5z5sxRTZs29d9fvXq1ql27trrmmmvKlUPLysry75OXl6cSEhLU4MGD1apVq9ScOXNUVFRUpSWd7r33XrV27Vo1Y8aMCiWdfvvtN2UymdTTTz+t1q1bp55++ulDlnSaMWOGWrt2rbrnnntUeHi42rZtm3+fp59+WkVHR6s5c+aoVatWqcGDB1co6VSd2uC/KquAIW0Q+Da45JJLVMuWLdVvv/2mVq1apfr3769atGjhL/EnbRDYNli3bp2y2Wzq9ttvV2vXrlWrV69W1157rYqOjlbp6enSBsfYBoWFhSolJUVdfvnlas2aNWrhwoWqcePG6uabbz5kGxwos3juueeqZcuWqe+//16lpKSUK7MobRDYNqipv5NF9VDjE/QDCdZ/txtuuEEppVRGRoYaMmSISk5OVna7XTVt2lQ999xz/vJISvnKNnXv3r3ccdPS0io97gHPPPOMatSokbLb7So2NlZ17dpVffXVV+WO8eabb5Z7zeOPP17pMdPS0sq97u+//1bdunVTNptNJSYmqtGjR5eLVymlFixYoM4880xltVpV/fr11bRp0yp8Nh9//LFq2rSpslgsqlmzZuV+YR8wZcoUlZaWpqxWq2rbtq1auHBhuecNw1CPP/64SkxMVDabTZ1zzjlq1apV1bYN/utQJeqkDXwC1Qb5+flq6NChKiYmRsXFxakBAwaUK/knbRD4Nvjuu+9Uly5dVHR0tIqNjVW9evVSixcvljY4jjZQyvdHz3nnnaccDodKSUlR9913nyopKTlsG2zfvl1deOGFyuFwqLi4OHXnnXeWK+cnbRDYNqipv5NF9aAp9Z/lroQQQgghhBBBc0qPQRdCCCGEECLUSIIuhBBCCCFECJEEXQghhBBCiBAiCboQQgghhBAhRBJ0IYQQQgghQogk6EIIIYQQQoQQSdCFEEIIIYQIIZKgCyGEEEIIEUIkQRdCCCGEECKESIIuhBBVoEePHtxzzz0VHv/ss8/QNI0ePXqgadoht/r16wOQmZnJiBEjaNiwITabjdTUVC666CJ++OGHk/uGhBBCBI052AEIIcSpYM6cObhcLgB27txJhw4d+P7772nZsiUAJpOJbdu20aVLF2JiYpgwYQKnn346brebb7/9ljvuuIN//vknmG9BCCHESSIJuhBCnARxcXH+206nE4BatWqRmJjof/yGG25A0zT+/PNPwsPD/Y+3bNmSoUOHnrxghRBCBJUMcRFCiBCQm5vLN998wx133FEuOT8gJibm5AclhBAiKCRBF0KIELBp0yaUUjRr1izYoQghhAgySdCFECIEKKUA0DQtyJEIIYQINknQhRCiCkRFRZGfn1/h8by8PKKioo74+saNG6NpGuvWrQtEeEIIIaoRSdCFEKIKNGvWjL/++qvC40uWLKFp06ZHfH1cXBx9+/ZlypQpFBcXV3g+Ly+vKsIUQghRDUiCLoQQVWD48OFs3ryZO+64g5UrV7JhwwamTJnCjBkzePDBB4/qGFOnTsXr9dKhQwdmz57Nxo0bWbduHS+++CKdOnUK8DsQQggRKqTMohBCVIH69evzyy+/MGrUKPr06YPT6aRJkybMnDmTK6644qiO0aBBA5YtW8ZTTz3F/fffT0ZGBrVr16Zdu3ZMmzYtwO9ACCFEqNDUgZlJQgghhBBCiKCTIS5CCCGEEEKEEEnQhRBCCCGECCGSoAshhBBCCBFCJEEXQgghhBAihEiCLoQQQgghRAiRBF0IIYQQQogQIgm6EEIIIYQQIUQSdCGEEEIIIUKIJOhCCCGEEEKEEEnQhRBCCCGECCGSoAshhBBCCBFCJEEXQgghhBAihPw/mSvNpk5ju5kAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "SRwidgets.plot(atl03=gdf, kind='scatter', title='Photon Cloud',\n",
    "    cmap=SRwidgets.colormap, legend=True, legend_frameon=True,\n",
    "    classification=SRwidgets.plot_classification.value, \n",
    "    segments=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
  },
  "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": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}