{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Met Éireann Reanalysis - compare variables\n",
    "\n",
    "<https://www.met.ie/climate/available-data/mera>\n",
    "\n",
    "Conversion table for accumulated variables:\n",
    "<https://confluence.ecmwf.int/pages/viewpage.action?pageId=197702790>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob\n",
    "import os\n",
    "from datetime import datetime, timezone\n",
    "from itertools import chain\n",
    "import cartopy.crs as ccrs\n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pooch\n",
    "import xarray as xr\n",
    "import climag.climag as cplt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Moorepark, Fermoy met station coords\n",
    "LON, LAT = -8.26389, 52.16389"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# transform coordinates from lon/lat to Lambert Conformal Conic\n",
    "XLON, YLAT = cplt.projection_lambert_conformal.transform_point(\n",
    "    x=LON, y=LAT, src_crs=ccrs.PlateCarree()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Ireland boundary\n",
    "GPKG_BOUNDARY = os.path.join(\"data\", \"boundaries\", \"boundaries_all.gpkg\")\n",
    "ie = gpd.read_file(GPKG_BOUNDARY, layer=\"NUTS_RG_01M_2021_2157_IE\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# directory of processed MÉRA netCDF files\n",
    "DATA_DIR = os.path.join(\"/run/media/nms/MyPassport\", \"MERA\", \"netcdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "URL = \"https://cli.fusio.net/cli/climate_data/webdata/dly575.csv\"\n",
    "FILE_NAME = \"moorepark.csv\"\n",
    "DATA_FILE = os.path.join(\"data\", \"met\", \"MetEireann\", FILE_NAME)\n",
    "os.makedirs(os.path.join(\"data\", \"met\", \"MetEireann\"), exist_ok=True)\n",
    "\n",
    "# download Moorepark met data if necessary\n",
    "if not os.path.isfile(DATA_FILE):\n",
    "    pooch.retrieve(\n",
    "        url=URL,\n",
    "        known_hash=None,\n",
    "        fname=FILE_NAME,\n",
    "        path=os.path.join(\"data\", \"met\", \"MetEireann\"),\n",
    "    )\n",
    "\n",
    "    with open(f\"{DATA_FILE[:-4]}.txt\", \"w\", encoding=\"utf-8\") as outfile:\n",
    "        outfile.write(\n",
    "            f\"Data downloaded on: {datetime.now(tz=timezone.utc)}\\n\"\n",
    "            f\"Download URL: {URL}\"\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Station Name: MOORE PARK\n",
      "Station Height: 46 M \n",
      "Latitude:52.164  ,Longitude: -8.264\n",
      "\n",
      "\n",
      "date:  -  00 to 00 utc\n",
      "rain:  -  Precipitation Amount (mm)\n",
      "maxtp: -  Maximum Air Temperature (C)\t  \n",
      "mintp: -  Minimum  Air Temperature (C)\n",
      "gmin:  -  09utc Grass Minimum Temperature (C)\n",
      "soil:  -  Mean 10cm soil temperature (C)\t\n",
      "cbl:   -  Mean CBL Pressure (hpa)\n",
      "wdsp:  -  Mean Wind Speed (kt)\n",
      "hm:    -  Highest ten minute mean wind speed (kt)\t\t                 \n",
      "ddhm:  -  Wind Direction at max 10 min mean (deg)                  \n",
      "hg:    -  Highest Gust (kt)\n",
      "pe:    -  Potential Evapotranspiration (mm)  \n",
      "evap:  -  Evaporation (mm)\n",
      "smd_wd:-  Soil Moisture Deficits(mm) well drained\n",
      "smd_md:-  Soil Moisture Deficits(mm) moderately drained\n",
      "smd_pd:-  Soil Moisture Deficits(mm) poorly drained\n",
      "glorad:-  Global Radiation (J/cm sq.)\n",
      "ind:   -  Indicator (i)\n",
      "\n",
      "date,ind,maxtp,ind,mintp,igmin,gmin,ind,rain,cbl,wdsp,ind,hm,ind,ddhm,ind,hg,soil,pe,evap,smd_wd,smd_md,smd_pd,glorad\n",
      "11-aug-2003,0,21.9,0,9.6, , ,0,0.0,1017.5,4.6,0,7,0,290,0,12, , , , , , , \n"
     ]
    },
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       "0"
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     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# view file\n",
    "os.system(f\"sed -n -e 1,26p {DATA_FILE}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(DATA_FILE, skiprows=24, parse_dates=[\"date\"])\n",
    "df.set_index(\"date\", inplace=True)\n",
    "df = df.loc[\"2003\":\"2005\"]\n",
    "# handle missing data\n",
    "df.replace(\" \", np.nan, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ind</th>\n",
       "      <th>maxtp</th>\n",
       "      <th>ind.1</th>\n",
       "      <th>mintp</th>\n",
       "      <th>igmin</th>\n",
       "      <th>gmin</th>\n",
       "      <th>ind.2</th>\n",
       "      <th>rain</th>\n",
       "      <th>cbl</th>\n",
       "      <th>wdsp</th>\n",
       "      <th>...</th>\n",
       "      <th>ddhm</th>\n",
       "      <th>ind.5</th>\n",
       "      <th>hg</th>\n",
       "      <th>soil</th>\n",
       "      <th>pe</th>\n",
       "      <th>evap</th>\n",
       "      <th>smd_wd</th>\n",
       "      <th>smd_md</th>\n",
       "      <th>smd_pd</th>\n",
       "      <th>glorad</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <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>2003-08-11</th>\n",
       "      <td>0</td>\n",
       "      <td>21.9</td>\n",
       "      <td>0</td>\n",
       "      <td>9.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1017.5</td>\n",
       "      <td>4.6</td>\n",
       "      <td>...</td>\n",
       "      <td>290</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003-08-12</th>\n",
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       "      <td>23.5</td>\n",
       "      <td>0</td>\n",
       "      <td>8.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1017.7</td>\n",
       "      <td>3.5</td>\n",
       "      <td>...</td>\n",
       "      <td>250</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2003-08-13</th>\n",
       "      <td>0</td>\n",
       "      <td>21.8</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1017.9</td>\n",
       "      <td>3.5</td>\n",
       "      <td>...</td>\n",
       "      <td>340</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003-08-14</th>\n",
       "      <td>0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1016.8</td>\n",
       "      <td>3.5</td>\n",
       "      <td>...</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003-08-15</th>\n",
       "      <td>0</td>\n",
       "      <td>19.8</td>\n",
       "      <td>0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1015.2</td>\n",
       "      <td>2.4</td>\n",
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       "            ind maxtp  ind.1 mintp  igmin  gmin  ind.2 rain     cbl wdsp  ...  \\\n",
       "date                                                                      ...   \n",
       "2003-08-11    0  21.9      0   9.6    NaN   NaN      0  0.0  1017.5  4.6  ...   \n",
       "2003-08-12    0  23.5      0   8.6    NaN   NaN      0  0.0  1017.7  3.5  ...   \n",
       "2003-08-13    0  21.8      4   NaN    NaN   NaN      8  NaN  1017.9  3.5  ...   \n",
       "2003-08-14    0  21.0      0   7.7    NaN   NaN      0  0.0  1016.8  3.5  ...   \n",
       "2003-08-15    0  19.8      0   5.8    NaN   NaN      0  0.0  1015.2  2.4  ...   \n",
       "\n",
       "            ddhm  ind.5  hg  soil  pe  evap  smd_wd  smd_md  smd_pd  glorad  \n",
       "date                                                                         \n",
       "2003-08-11   290      0  12   NaN NaN   NaN     NaN     NaN     NaN     NaN  \n",
       "2003-08-12   250      0  14   NaN NaN   NaN     NaN     NaN     NaN     NaN  \n",
       "2003-08-13   340      0  14   NaN NaN   NaN     NaN     NaN     NaN     NaN  \n",
       "2003-08-14    50      0  15   NaN NaN   NaN     NaN     NaN     NaN     NaN  \n",
       "2003-08-15    10      0  10   NaN NaN   NaN     NaN     NaN     NaN     NaN  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Global irradiance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "var = \"117_105_0_4\"\n",
    "file_list = list(\n",
    "    chain(\n",
    "        *list(\n",
    "            glob.glob(os.path.join(DATA_DIR, f\"{var}_FC3hr\", e))\n",
    "            for e in [f\"*{i}*{var}_FC3hr*\" for i in range(2003, 2006)]\n",
    "        )\n",
    "    )\n",
    ")\n",
    "data = xr.open_mfdataset(file_list, chunks=\"auto\", decode_coords=\"all\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
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       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (time: 8768, x: 158, y: 166, height: 1)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31T21:00:00\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "  * height             (height) float64 0.0\n",
       "    spatial_ref        int64 0\n",
       "    Lambert_Conformal  int64 0\n",
       "Data variables:\n",
       "    grad               (time, height, y, x) float32 dask.array&lt;chunksize=(248, 1, 166, 158), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 22:22:29 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7a5ee5ae-ef52-49e6-96ae-469eab440466' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7a5ee5ae-ef52-49e6-96ae-469eab440466' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 8768</li><li><span class='xr-has-index'>x</span>: 158</li><li><span class='xr-has-index'>y</span>: 166</li><li><span class='xr-has-index'>height</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6c645bea-7854-427b-9abf-01e6d8058b3e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6c645bea-7854-427b-9abf-01e6d8058b3e' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2003-01-01 ... 2005-12-31T21:00:00</div><input id='attrs-78466f74-663b-4908-b421-bb9cd500c71a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78466f74-663b-4908-b421-bb9cd500c71a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ddaedb6f-8c0f-4a54-ac17-e6df461f3cef' class='xr-var-data-in' type='checkbox'><label for='data-ddaedb6f-8c0f-4a54-ac17-e6df461f3cef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2003-01-01T00:00:00.000000000&#x27;, &#x27;2003-01-01T03:00:00.000000000&#x27;,\n",
       "       &#x27;2003-01-01T06:00:00.000000000&#x27;, ..., &#x27;2005-12-31T15:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-31T18:00:00.000000000&#x27;, &#x27;2005-12-31T21:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.15e+05 4.175e+05 ... 8.075e+05</div><input id='attrs-82edb129-77b6-4dbc-93af-a67c8ce248d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-82edb129-77b6-4dbc-93af-a67c8ce248d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9d314e2-4cc5-4061-99de-3910524ccf0b' class='xr-var-data-in' type='checkbox'><label for='data-c9d314e2-4cc5-4061-99de-3910524ccf0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([415000., 417500., 420000., 422500., 425000., 427500., 430000., 432500.,\n",
       "       435000., 437500., 440000., 442500., 445000., 447500., 450000., 452500.,\n",
       "       455000., 457500., 460000., 462500., 465000., 467500., 470000., 472500.,\n",
       "       475000., 477500., 480000., 482500., 485000., 487500., 490000., 492500.,\n",
       "       495000., 497500., 500000., 502500., 505000., 507500., 510000., 512500.,\n",
       "       515000., 517500., 520000., 522500., 525000., 527500., 530000., 532500.,\n",
       "       535000., 537500., 540000., 542500., 545000., 547500., 550000., 552500.,\n",
       "       555000., 557500., 560000., 562500., 565000., 567500., 570000., 572500.,\n",
       "       575000., 577500., 580000., 582500., 585000., 587500., 590000., 592500.,\n",
       "       595000., 597500., 600000., 602500., 605000., 607500., 610000., 612500.,\n",
       "       615000., 617500., 620000., 622500., 625000., 627500., 630000., 632500.,\n",
       "       635000., 637500., 640000., 642500., 645000., 647500., 650000., 652500.,\n",
       "       655000., 657500., 660000., 662500., 665000., 667500., 670000., 672500.,\n",
       "       675000., 677500., 680000., 682500., 685000., 687500., 690000., 692500.,\n",
       "       695000., 697500., 700000., 702500., 705000., 707500., 710000., 712500.,\n",
       "       715000., 717500., 720000., 722500., 725000., 727500., 730000., 732500.,\n",
       "       735000., 737500., 740000., 742500., 745000., 747500., 750000., 752500.,\n",
       "       755000., 757500., 760000., 762500., 765000., 767500., 770000., 772500.,\n",
       "       775000., 777500., 780000., 782500., 785000., 787500., 790000., 792500.,\n",
       "       795000., 797500., 800000., 802500., 805000., 807500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.075e+05 4.1e+05 ... 8.2e+05</div><input id='attrs-a602808d-2098-49cc-b7d1-c3396867e05f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a602808d-2098-49cc-b7d1-c3396867e05f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c439a71b-e1b1-4068-8aed-01c4c24a6747' class='xr-var-data-in' type='checkbox'><label for='data-c439a71b-e1b1-4068-8aed-01c4c24a6747' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([407500., 410000., 412500., 415000., 417500., 420000., 422500., 425000.,\n",
       "       427500., 430000., 432500., 435000., 437500., 440000., 442500., 445000.,\n",
       "       447500., 450000., 452500., 455000., 457500., 460000., 462500., 465000.,\n",
       "       467500., 470000., 472500., 475000., 477500., 480000., 482500., 485000.,\n",
       "       487500., 490000., 492500., 495000., 497500., 500000., 502500., 505000.,\n",
       "       507500., 510000., 512500., 515000., 517500., 520000., 522500., 525000.,\n",
       "       527500., 530000., 532500., 535000., 537500., 540000., 542500., 545000.,\n",
       "       547500., 550000., 552500., 555000., 557500., 560000., 562500., 565000.,\n",
       "       567500., 570000., 572500., 575000., 577500., 580000., 582500., 585000.,\n",
       "       587500., 590000., 592500., 595000., 597500., 600000., 602500., 605000.,\n",
       "       607500., 610000., 612500., 615000., 617500., 620000., 622500., 625000.,\n",
       "       627500., 630000., 632500., 635000., 637500., 640000., 642500., 645000.,\n",
       "       647500., 650000., 652500., 655000., 657500., 660000., 662500., 665000.,\n",
       "       667500., 670000., 672500., 675000., 677500., 680000., 682500., 685000.,\n",
       "       687500., 690000., 692500., 695000., 697500., 700000., 702500., 705000.,\n",
       "       707500., 710000., 712500., 715000., 717500., 720000., 722500., 725000.,\n",
       "       727500., 730000., 732500., 735000., 737500., 740000., 742500., 745000.,\n",
       "       747500., 750000., 752500., 755000., 757500., 760000., 762500., 765000.,\n",
       "       767500., 770000., 772500., 775000., 777500., 780000., 782500., 785000.,\n",
       "       787500., 790000., 792500., 795000., 797500., 800000., 802500., 805000.,\n",
       "       807500., 810000., 812500., 815000., 817500., 820000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-701a7fb2-00db-475a-aa67-64665b31b99f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-701a7fb2-00db-475a-aa67-64665b31b99f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-80db32b5-0738-49f4-80df-0dff575f4d06' class='xr-var-data-in' type='checkbox'><label for='data-80db32b5-0738-49f4-80df-0dff575f4d06' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-30113a16-e0e5-4738-9417-b82b3c978931' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30113a16-e0e5-4738-9417-b82b3c978931' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a016dd7-28a4-41f6-a913-7b56b6d551b5' class='xr-var-data-in' type='checkbox'><label for='data-3a016dd7-28a4-41f6-a913-7b56b6d551b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-2f3ba3ad-4681-402e-8a0a-611271903606' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f3ba3ad-4681-402e-8a0a-611271903606' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5fa60d7c-c908-4eff-a348-ae853d55ffaa' class='xr-var-data-in' type='checkbox'><label for='data-5fa60d7c-c908-4eff-a348-ae853d55ffaa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-df00bd32-2ae1-4427-8020-c742a5002e78' class='xr-section-summary-in' type='checkbox'  checked><label for='section-df00bd32-2ae1-4427-8020-c742a5002e78' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>grad</span></div><div class='xr-var-dims'>(time, height, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(248, 1, 166, 158), meta=np.ndarray&gt;</div><input id='attrs-7ab9fb86-410a-4588-9bc3-483b30398642' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ab9fb86-410a-4588-9bc3-483b30398642' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8bf82995-6cd3-429e-af91-1e17cd380214' class='xr-var-data-in' type='checkbox'><label for='data-8bf82995-6cd3-429e-af91-1e17cd380214' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>233253117</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Global radiation flux</dd><dt><span>GRIB_shortName :</span></dt><dd>grad</dd><dt><span>GRIB_units :</span></dt><dd>W m**-2</dd><dt><span>long_name :</span></dt><dd>Global radiation flux</dd><dt><span>units :</span></dt><dd>W m**-2</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 877.25 MiB </td>\n",
       "                        <td> 24.81 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (8768, 1, 166, 158) </td>\n",
       "                        <td> (248, 1, 166, 158) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 36 chunks in 73 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-22a17a40-5532-4130-b3f0-a4d96cef764b' class='xr-section-summary-in' type='checkbox'  ><label for='section-22a17a40-5532-4130-b3f0-a4d96cef764b' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9e368d60-210c-43b0-a49a-f7f1f2627c41' class='xr-index-data-in' type='checkbox'/><label for='index-9e368d60-210c-43b0-a49a-f7f1f2627c41' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2003-01-01 00:00:00&#x27;, &#x27;2003-01-01 03:00:00&#x27;,\n",
       "               &#x27;2003-01-01 06:00:00&#x27;, &#x27;2003-01-01 09:00:00&#x27;,\n",
       "               &#x27;2003-01-01 12:00:00&#x27;, &#x27;2003-01-01 15:00:00&#x27;,\n",
       "               &#x27;2003-01-01 18:00:00&#x27;, &#x27;2003-01-01 21:00:00&#x27;,\n",
       "               &#x27;2003-01-02 00:00:00&#x27;, &#x27;2003-01-02 03:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-30 18:00:00&#x27;, &#x27;2005-12-30 21:00:00&#x27;,\n",
       "               &#x27;2005-12-31 00:00:00&#x27;, &#x27;2005-12-31 03:00:00&#x27;,\n",
       "               &#x27;2005-12-31 06:00:00&#x27;, &#x27;2005-12-31 09:00:00&#x27;,\n",
       "               &#x27;2005-12-31 12:00:00&#x27;, &#x27;2005-12-31 15:00:00&#x27;,\n",
       "               &#x27;2005-12-31 18:00:00&#x27;, &#x27;2005-12-31 21:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=8768, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d063c8d6-1df3-4f93-959f-9da392c1c880' class='xr-index-data-in' type='checkbox'/><label for='index-d063c8d6-1df3-4f93-959f-9da392c1c880' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([415000.0, 417500.0, 420000.0, 422500.0, 425000.0, 427500.0,\n",
       "              430000.0, 432500.0, 435000.0, 437500.0,\n",
       "              ...\n",
       "              785000.0, 787500.0, 790000.0, 792500.0, 795000.0, 797500.0,\n",
       "              800000.0, 802500.0, 805000.0, 807500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=158))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9be30b48-dca1-4588-a900-6ecf4f4a386a' class='xr-index-data-in' type='checkbox'/><label for='index-9be30b48-dca1-4588-a900-6ecf4f4a386a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([407500.0, 410000.0, 412500.0, 415000.0, 417500.0, 420000.0,\n",
       "              422500.0, 425000.0, 427500.0, 430000.0,\n",
       "              ...\n",
       "              797500.0, 800000.0, 802500.0, 805000.0, 807500.0, 810000.0,\n",
       "              812500.0, 815000.0, 817500.0, 820000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=166))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>height</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a883d3a1-22c4-4348-a3a4-4e812d572193' class='xr-index-data-in' type='checkbox'/><label for='index-a883d3a1-22c4-4348-a3a4-4e812d572193' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([0.0], dtype=&#x27;float64&#x27;, name=&#x27;height&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ab33a342-88f5-49a4-860e-26d7fc1822bb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ab33a342-88f5-49a4-860e-26d7fc1822bb' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Wed Mar 22 22:22:29 2023: cdo -s -f nc4c -shifttime,-3hour -copy -seltimestep,3/744/3 /run/media/nms/Elements/MERA/grib/117_105_0_4_FC3hr/temp/MERA_PRODYEAR_2003_01_117_105_0_4_FC3hr /run/media/nms/Elements/MERA/grib/117_105_0_4_FC3hr/temp/MERA_PRODYEAR_2003_01_117_105_0_4_FC3hr.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (time: 8768, x: 158, y: 166, height: 1)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31T21:00:00\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "  * height             (height) float64 0.0\n",
       "    spatial_ref        int64 0\n",
       "    Lambert_Conformal  int64 0\n",
       "Data variables:\n",
       "    grad               (time, height, y, x) float32 dask.array<chunksize=(248, 1, 166, 158), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 22:22:29 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# note that the units are incorrect; it should be J m-2\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert to W m-2\n",
    "var = \"grad\"\n",
    "data_attrs = data[var].attrs  # copy var attributes\n",
    "data_crs = data.rio.crs  # copy CRS\n",
    "data[var] = data[var] / (3 * 3600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       ".xr-attrs dt,\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (x: 158, y: 166, height: 1, time: 1096)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "  * height             (height) float64 0.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    grad               (time, height, y, x) float32 dask.array&lt;chunksize=(1, 1, 166, 158), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 22:22:29 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b8c4fb8e-cc4e-4bfb-973d-f75815be00d7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b8c4fb8e-cc4e-4bfb-973d-f75815be00d7' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 158</li><li><span class='xr-has-index'>y</span>: 166</li><li><span class='xr-has-index'>height</span>: 1</li><li><span class='xr-has-index'>time</span>: 1096</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c019bfa0-0ca7-4836-9104-eb035c76abb1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c019bfa0-0ca7-4836-9104-eb035c76abb1' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.15e+05 4.175e+05 ... 8.075e+05</div><input id='attrs-e49b62fd-2b1c-4826-842b-9aedd89fbf35' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e49b62fd-2b1c-4826-842b-9aedd89fbf35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-990778dd-9265-404d-846b-80b8ad908389' class='xr-var-data-in' type='checkbox'><label for='data-990778dd-9265-404d-846b-80b8ad908389' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([415000., 417500., 420000., 422500., 425000., 427500., 430000., 432500.,\n",
       "       435000., 437500., 440000., 442500., 445000., 447500., 450000., 452500.,\n",
       "       455000., 457500., 460000., 462500., 465000., 467500., 470000., 472500.,\n",
       "       475000., 477500., 480000., 482500., 485000., 487500., 490000., 492500.,\n",
       "       495000., 497500., 500000., 502500., 505000., 507500., 510000., 512500.,\n",
       "       515000., 517500., 520000., 522500., 525000., 527500., 530000., 532500.,\n",
       "       535000., 537500., 540000., 542500., 545000., 547500., 550000., 552500.,\n",
       "       555000., 557500., 560000., 562500., 565000., 567500., 570000., 572500.,\n",
       "       575000., 577500., 580000., 582500., 585000., 587500., 590000., 592500.,\n",
       "       595000., 597500., 600000., 602500., 605000., 607500., 610000., 612500.,\n",
       "       615000., 617500., 620000., 622500., 625000., 627500., 630000., 632500.,\n",
       "       635000., 637500., 640000., 642500., 645000., 647500., 650000., 652500.,\n",
       "       655000., 657500., 660000., 662500., 665000., 667500., 670000., 672500.,\n",
       "       675000., 677500., 680000., 682500., 685000., 687500., 690000., 692500.,\n",
       "       695000., 697500., 700000., 702500., 705000., 707500., 710000., 712500.,\n",
       "       715000., 717500., 720000., 722500., 725000., 727500., 730000., 732500.,\n",
       "       735000., 737500., 740000., 742500., 745000., 747500., 750000., 752500.,\n",
       "       755000., 757500., 760000., 762500., 765000., 767500., 770000., 772500.,\n",
       "       775000., 777500., 780000., 782500., 785000., 787500., 790000., 792500.,\n",
       "       795000., 797500., 800000., 802500., 805000., 807500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.075e+05 4.1e+05 ... 8.2e+05</div><input id='attrs-d362bebf-a97e-4ff8-94a0-dccc58b9acdf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d362bebf-a97e-4ff8-94a0-dccc58b9acdf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-49b59a0a-3fca-4c74-9af7-025401f327cc' class='xr-var-data-in' type='checkbox'><label for='data-49b59a0a-3fca-4c74-9af7-025401f327cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([407500., 410000., 412500., 415000., 417500., 420000., 422500., 425000.,\n",
       "       427500., 430000., 432500., 435000., 437500., 440000., 442500., 445000.,\n",
       "       447500., 450000., 452500., 455000., 457500., 460000., 462500., 465000.,\n",
       "       467500., 470000., 472500., 475000., 477500., 480000., 482500., 485000.,\n",
       "       487500., 490000., 492500., 495000., 497500., 500000., 502500., 505000.,\n",
       "       507500., 510000., 512500., 515000., 517500., 520000., 522500., 525000.,\n",
       "       527500., 530000., 532500., 535000., 537500., 540000., 542500., 545000.,\n",
       "       547500., 550000., 552500., 555000., 557500., 560000., 562500., 565000.,\n",
       "       567500., 570000., 572500., 575000., 577500., 580000., 582500., 585000.,\n",
       "       587500., 590000., 592500., 595000., 597500., 600000., 602500., 605000.,\n",
       "       607500., 610000., 612500., 615000., 617500., 620000., 622500., 625000.,\n",
       "       627500., 630000., 632500., 635000., 637500., 640000., 642500., 645000.,\n",
       "       647500., 650000., 652500., 655000., 657500., 660000., 662500., 665000.,\n",
       "       667500., 670000., 672500., 675000., 677500., 680000., 682500., 685000.,\n",
       "       687500., 690000., 692500., 695000., 697500., 700000., 702500., 705000.,\n",
       "       707500., 710000., 712500., 715000., 717500., 720000., 722500., 725000.,\n",
       "       727500., 730000., 732500., 735000., 737500., 740000., 742500., 745000.,\n",
       "       747500., 750000., 752500., 755000., 757500., 760000., 762500., 765000.,\n",
       "       767500., 770000., 772500., 775000., 777500., 780000., 782500., 785000.,\n",
       "       787500., 790000., 792500., 795000., 797500., 800000., 802500., 805000.,\n",
       "       807500., 810000., 812500., 815000., 817500., 820000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-aa595a7c-884d-410b-81be-7b0461666f30' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa595a7c-884d-410b-81be-7b0461666f30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65b1f57c-5ddd-49a0-8b39-4cc5536a1e66' class='xr-var-data-in' type='checkbox'><label for='data-65b1f57c-5ddd-49a0-8b39-4cc5536a1e66' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-433e9581-4133-4783-bb70-f9d1bf402442' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-433e9581-4133-4783-bb70-f9d1bf402442' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be57ddfc-f7bf-47e2-b0ae-2972b226653c' class='xr-var-data-in' type='checkbox'><label for='data-be57ddfc-f7bf-47e2-b0ae-2972b226653c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2003-01-01 ... 2005-12-31</div><input id='attrs-175001d8-bb25-493f-9146-cbb444a2960c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-175001d8-bb25-493f-9146-cbb444a2960c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b9dddb2-8785-47c7-bb97-fcd1874c3480' class='xr-var-data-in' type='checkbox'><label for='data-9b9dddb2-8785-47c7-bb97-fcd1874c3480' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2003-01-01T00:00:00.000000000&#x27;, &#x27;2003-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-01-03T00:00:00.000000000&#x27;, ..., &#x27;2005-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-30T00:00:00.000000000&#x27;, &#x27;2005-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-a3c2ead3-d1ca-4cd6-8b11-a596081ce6b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3c2ead3-d1ca-4cd6-8b11-a596081ce6b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27b9610a-da95-4896-bbab-77583ec185a2' class='xr-var-data-in' type='checkbox'><label for='data-27b9610a-da95-4896-bbab-77583ec185a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-879b68cb-024c-4b40-a1b5-c807a383b210' class='xr-section-summary-in' type='checkbox'  checked><label for='section-879b68cb-024c-4b40-a1b5-c807a383b210' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>grad</span></div><div class='xr-var-dims'>(time, height, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 166, 158), meta=np.ndarray&gt;</div><input id='attrs-96785b45-066d-40b6-be3a-351fd60bce38' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96785b45-066d-40b6-be3a-351fd60bce38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af8e833e-d7ed-4d0f-87ff-6adb4c030044' class='xr-var-data-in' type='checkbox'><label for='data-af8e833e-d7ed-4d0f-87ff-6adb4c030044' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>233253117</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Global radiation flux</dd><dt><span>GRIB_shortName :</span></dt><dd>grad</dd><dt><span>GRIB_units :</span></dt><dd>W m**-2</dd><dt><span>long_name :</span></dt><dd>Global radiation flux</dd><dt><span>units :</span></dt><dd>W m⁻²</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 109.66 MiB </td>\n",
       "                        <td> 102.45 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1096, 1, 166, 158) </td>\n",
       "                        <td> (1, 1, 166, 158) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1096 chunks in 4459 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"485\" height=\"105\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
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       "  <line x1=\"45\" y1=\"0\" x2=\"45\" y2=\"25\" />\n",
       "  <line x1=\"48\" y1=\"0\" x2=\"48\" y2=\"25\" />\n",
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       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
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       "              430000.0, 432500.0, 435000.0, 437500.0,\n",
       "              ...\n",
       "              785000.0, 787500.0, 790000.0, 792500.0, 795000.0, 797500.0,\n",
       "              800000.0, 802500.0, 805000.0, 807500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=158))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-899e69e1-54af-4a8a-bf98-82c85c955007' class='xr-index-data-in' type='checkbox'/><label for='index-899e69e1-54af-4a8a-bf98-82c85c955007' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([407500.0, 410000.0, 412500.0, 415000.0, 417500.0, 420000.0,\n",
       "              422500.0, 425000.0, 427500.0, 430000.0,\n",
       "              ...\n",
       "              797500.0, 800000.0, 802500.0, 805000.0, 807500.0, 810000.0,\n",
       "              812500.0, 815000.0, 817500.0, 820000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=166))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>height</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-25fd5ff2-87f8-4e06-8227-e9c630533392' class='xr-index-data-in' type='checkbox'/><label for='index-25fd5ff2-87f8-4e06-8227-e9c630533392' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([0.0], dtype=&#x27;float64&#x27;, name=&#x27;height&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4194314c-95e3-4ed9-93b9-cd75a278c236' class='xr-index-data-in' type='checkbox'/><label for='index-4194314c-95e3-4ed9-93b9-cd75a278c236' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2003-01-01&#x27;, &#x27;2003-01-02&#x27;, &#x27;2003-01-03&#x27;, &#x27;2003-01-04&#x27;,\n",
       "               &#x27;2003-01-05&#x27;, &#x27;2003-01-06&#x27;, &#x27;2003-01-07&#x27;, &#x27;2003-01-08&#x27;,\n",
       "               &#x27;2003-01-09&#x27;, &#x27;2003-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-22&#x27;, &#x27;2005-12-23&#x27;, &#x27;2005-12-24&#x27;, &#x27;2005-12-25&#x27;,\n",
       "               &#x27;2005-12-26&#x27;, &#x27;2005-12-27&#x27;, &#x27;2005-12-28&#x27;, &#x27;2005-12-29&#x27;,\n",
       "               &#x27;2005-12-30&#x27;, &#x27;2005-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1096, freq=&#x27;D&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ffaab446-fa32-4a0f-ae6a-87e1a397c271' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ffaab446-fa32-4a0f-ae6a-87e1a397c271' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Wed Mar 22 22:22:29 2023: cdo -s -f nc4c -shifttime,-3hour -copy -seltimestep,3/744/3 /run/media/nms/Elements/MERA/grib/117_105_0_4_FC3hr/temp/MERA_PRODYEAR_2003_01_117_105_0_4_FC3hr /run/media/nms/Elements/MERA/grib/117_105_0_4_FC3hr/temp/MERA_PRODYEAR_2003_01_117_105_0_4_FC3hr.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (x: 158, y: 166, height: 1, time: 1096)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "  * height             (height) float64 0.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    grad               (time, height, y, x) float32 dask.array<chunksize=(1, 1, 166, 158), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 22:22:29 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# resample to daily - take the mean\n",
    "time_attrs = data[\"time\"].attrs\n",
    "data_d = data.resample(time=\"D\").mean()\n",
    "data_d[var].attrs = data_attrs  # reassign attributes\n",
    "data_d[\"time\"].attrs = time_attrs\n",
    "data_d[var].attrs[\"units\"] = \"W m⁻²\"  # update attributes\n",
    "data_d.rio.write_crs(data_crs, inplace=True)  # reassign CRS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract data for the nearest grid cell to the point\n",
    "data_tsd = data_d.sel({\"x\": XLON, \"y\": YLAT}, method=\"nearest\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
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       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (height: 1, time: 1096)\n",
       "Coordinates:\n",
       "    x                  float64 5.8e+05\n",
       "    y                  float64 4.725e+05\n",
       "  * height             (height) float64 0.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    grad               (time, height) float32 dask.array&lt;chunksize=(1, 1), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 22:22:29 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-526e902a-9b70-4fd2-9b5b-42841180ffb9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-526e902a-9b70-4fd2-9b5b-42841180ffb9' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>height</span>: 1</li><li><span class='xr-has-index'>time</span>: 1096</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0e9ec303-07dc-4e44-b77a-3594883dff51' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0e9ec303-07dc-4e44-b77a-3594883dff51' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.8e+05</div><input id='attrs-bc074f56-aa52-4fa2-8764-859a95388983' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc074f56-aa52-4fa2-8764-859a95388983' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-739202ce-b7f1-4ce6-bd5c-13e5943d4fd1' class='xr-var-data-in' type='checkbox'><label for='data-739202ce-b7f1-4ce6-bd5c-13e5943d4fd1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array(580000.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.725e+05</div><input id='attrs-5d6fb2a1-fe6d-420d-912b-fb0df65126c5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d6fb2a1-fe6d-420d-912b-fb0df65126c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18e61e4f-9956-4ba0-a9a3-6d06bb0adc9d' class='xr-var-data-in' type='checkbox'><label for='data-18e61e4f-9956-4ba0-a9a3-6d06bb0adc9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array(472500.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-4b86dd26-c2e8-487b-9d4c-a4dec55efc60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b86dd26-c2e8-487b-9d4c-a4dec55efc60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30d134b3-80ab-4c13-bbd3-149bfb33eac9' class='xr-var-data-in' type='checkbox'><label for='data-30d134b3-80ab-4c13-bbd3-149bfb33eac9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-86c1ea66-e240-4d02-86c2-e7f26ba56b5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86c1ea66-e240-4d02-86c2-e7f26ba56b5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b07c6c7-0058-4e79-8f51-f49e89f8db6b' class='xr-var-data-in' type='checkbox'><label for='data-6b07c6c7-0058-4e79-8f51-f49e89f8db6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2003-01-01 ... 2005-12-31</div><input id='attrs-1c4919bd-eb7c-4fef-9ced-e97a0df77bc8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c4919bd-eb7c-4fef-9ced-e97a0df77bc8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22517383-67d2-404e-b8c1-096981212a92' class='xr-var-data-in' type='checkbox'><label for='data-22517383-67d2-404e-b8c1-096981212a92' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2003-01-01T00:00:00.000000000&#x27;, &#x27;2003-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-01-03T00:00:00.000000000&#x27;, ..., &#x27;2005-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-30T00:00:00.000000000&#x27;, &#x27;2005-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-105372ea-aa12-4d0f-9f3b-123c664da438' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-105372ea-aa12-4d0f-9f3b-123c664da438' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df3588de-71ac-445a-b3a5-8e1feea8fa9e' class='xr-var-data-in' type='checkbox'><label for='data-df3588de-71ac-445a-b3a5-8e1feea8fa9e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0269aaec-0aa5-4f23-a48e-6a48c44779dc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0269aaec-0aa5-4f23-a48e-6a48c44779dc' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>grad</span></div><div class='xr-var-dims'>(time, height)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1), meta=np.ndarray&gt;</div><input id='attrs-e17a8c97-5ebf-4577-aa59-e8c8d4dfedda' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e17a8c97-5ebf-4577-aa59-e8c8d4dfedda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7167b49-a568-4524-b8e9-1d17c4cb45a0' class='xr-var-data-in' type='checkbox'><label for='data-c7167b49-a568-4524-b8e9-1d17c4cb45a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>233253117</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Global radiation flux</dd><dt><span>GRIB_shortName :</span></dt><dd>grad</dd><dt><span>GRIB_units :</span></dt><dd>W m**-2</dd><dt><span>long_name :</span></dt><dd>Global radiation flux</dd><dt><span>units :</span></dt><dd>W m⁻²</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.28 kiB </td>\n",
       "                        <td> 4 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1096, 1) </td>\n",
       "                        <td> (1, 1) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1096 chunks in 4460 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
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       "  <line x1=\"0\" y1=\"12\" x2=\"25\" y2=\"12\" />\n",
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       "  <line x1=\"0\" y1=\"25\" x2=\"25\" y2=\"25\" />\n",
       "  <line x1=\"0\" y1=\"31\" x2=\"25\" y2=\"31\" />\n",
       "  <line x1=\"0\" y1=\"37\" x2=\"25\" y2=\"37\" />\n",
       "  <line x1=\"0\" y1=\"44\" x2=\"25\" y2=\"44\" />\n",
       "  <line x1=\"0\" y1=\"50\" x2=\"25\" y2=\"50\" />\n",
       "  <line x1=\"0\" y1=\"56\" x2=\"25\" y2=\"56\" />\n",
       "  <line x1=\"0\" y1=\"63\" x2=\"25\" y2=\"63\" />\n",
       "  <line x1=\"0\" y1=\"69\" x2=\"25\" y2=\"69\" />\n",
       "  <line x1=\"0\" y1=\"75\" x2=\"25\" y2=\"75\" />\n",
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       "  <line x1=\"0\" y1=\"88\" x2=\"25\" y2=\"88\" />\n",
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       "  <line x1=\"0\" y1=\"100\" x2=\"25\" y2=\"100\" />\n",
       "  <line x1=\"0\" y1=\"107\" x2=\"25\" y2=\"107\" />\n",
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       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1</text>\n",
       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">1096</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-e507d714-fe32-45c1-b3c3-1747474a1c62' class='xr-section-summary-in' type='checkbox'  ><label for='section-e507d714-fe32-45c1-b3c3-1747474a1c62' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>height</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6c3b8d8f-ec72-468b-81a7-68640a7ffadd' class='xr-index-data-in' type='checkbox'/><label for='index-6c3b8d8f-ec72-468b-81a7-68640a7ffadd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([0.0], dtype=&#x27;float64&#x27;, name=&#x27;height&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e53c8973-cabe-4767-a7e6-cfe33d6cbdc7' class='xr-index-data-in' type='checkbox'/><label for='index-e53c8973-cabe-4767-a7e6-cfe33d6cbdc7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2003-01-01&#x27;, &#x27;2003-01-02&#x27;, &#x27;2003-01-03&#x27;, &#x27;2003-01-04&#x27;,\n",
       "               &#x27;2003-01-05&#x27;, &#x27;2003-01-06&#x27;, &#x27;2003-01-07&#x27;, &#x27;2003-01-08&#x27;,\n",
       "               &#x27;2003-01-09&#x27;, &#x27;2003-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-22&#x27;, &#x27;2005-12-23&#x27;, &#x27;2005-12-24&#x27;, &#x27;2005-12-25&#x27;,\n",
       "               &#x27;2005-12-26&#x27;, &#x27;2005-12-27&#x27;, &#x27;2005-12-28&#x27;, &#x27;2005-12-29&#x27;,\n",
       "               &#x27;2005-12-30&#x27;, &#x27;2005-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1096, freq=&#x27;D&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d19e16f3-3520-48fb-a3c4-93ad6128d072' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d19e16f3-3520-48fb-a3c4-93ad6128d072' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Wed Mar 22 22:22:29 2023: cdo -s -f nc4c -shifttime,-3hour -copy -seltimestep,3/744/3 /run/media/nms/Elements/MERA/grib/117_105_0_4_FC3hr/temp/MERA_PRODYEAR_2003_01_117_105_0_4_FC3hr /run/media/nms/Elements/MERA/grib/117_105_0_4_FC3hr/temp/MERA_PRODYEAR_2003_01_117_105_0_4_FC3hr.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (height: 1, time: 1096)\n",
       "Coordinates:\n",
       "    x                  float64 5.8e+05\n",
       "    y                  float64 4.725e+05\n",
       "  * height             (height) float64 0.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    grad               (time, height) float32 dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 22:22:29 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_tsd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert to dataframe for plotting\n",
    "data_df = pd.DataFrame({\"time\": data_tsd[\"time\"]})\n",
    "data_df[f\"{var}\"] = data_tsd[var]\n",
    "data_df.set_index(\"time\", inplace=True)\n",
    "# met data - convert to W m-2\n",
    "df_plot = df[[\"glorad\"]].copy()\n",
    "df_plot[\"glorad\"] = (\n",
    "    df_plot[\"glorad\"].astype(float) / (1 / 100**2) / (24 * 3600)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot\n",
    "ax = data_df.plot(\n",
    "    figsize=(12, 4.5),\n",
    "    y=var,\n",
    "    color=\"lightslategrey\",\n",
    "    alpha=0.7,\n",
    "    linewidth=2,\n",
    "    label=\"MÉRA\",\n",
    ")\n",
    "df_plot.plot(\n",
    "    ax=ax, y=\"glorad\", color=\"crimson\", linewidth=0.75, label=\"Station\"\n",
    ")\n",
    "plt.tight_layout()\n",
    "plt.ylabel(\n",
    "    data_d[var].attrs[\"long_name\"] + \" [\" + data_d[var].attrs[\"units\"] + \"]\"\n",
    ")\n",
    "plt.xlabel(\"\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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i7Vre+PhjDpeUMK6ggBsvuaTTLWyr1cqT//kP3//yCwAnTpnCLZde2tZ2HRzeyc+9/TYbd+6kuaWFrPR05s+axSVnndXBa9kX7372GR9+9RUVVVUcN3o0t195JWkpKX6PM1ABDo6GLv9+7z12HTzIyCFDuPq88zq0Afc1d5mpqR06XzrxJ8ADmT+AvYcP8/Trr7N1zx4GZWVxyaJFHcRgi8nEtQ8+iCzLvPDww22uFxDY3DU2N/P4iy/y4+bNxEZHM2/mTK45/3wkSWpb5pHnnuOHTZt4/PbbGe1yLP7mDRxNkp5/911WrFlDY3Mz0ydO5PYrryQ2OrptmY+++or/e/ttfnfBBSw+9dS258uNRp54+WU27NjR1sjmvAULOs1lqM7XQOY71HMbynkMZs4EAoEgHAgBLhAIBAKBQCAQhBGRAy4QCAQCgUAgEIQRIcAFAoFAIBAIBIIwIgS4QCAQCAQCgUAQRoQAFwgEAoFAIBAIwogQ4AKBQCAQCAQCQRjx3O+4j1JZU9PWuEQgEAgEAoGgL5MUF0dSQkJvD6NHaGhqwmazHbPH19P0GxvCypoaFl93Hc0urZAFAoFAIBAI+jLfvPrqMSdSbXY78049m6ZIFV++/TqJcXG9PaR+R7+JgDc0NdFsMvHU3XeTk5HR28PpdVpMrZRVVFNaWUVtQzMalUR9YzNTJ44iNysNjVrd20McEHz+3U+ccsJxaLX95qPUrykqraSqto6Jo4f39lAGBLv2HUar1TB0UHZvD+XYR1H45Ot1LDylc3MjQWhRZJnPvv2JM+ZO79H9PPr882zcsYOahoZjToB//M031Mao0Nvg5hMu4NVtn/X2kPod/U415GRkMDQ3t7eH0ScYV9D+f6vNxkvvfoZeG8nGrQew2e0kJ8STl5VGXlYasTFRvTfQY5j4mN2MzB/S28MYMJSW1TJl7BgGZaf39lAGBHv2l3L8uFEkJYjoVk9TW9/I0Lxc8fsWBmrqGhg2KK9H59pssbD74MEe235vYmptZenSfzK2zEZSo8z3Y/QUlZWJ4GiQ9DsBLvCM1WojOTGO2VPHA472zNV1DRSWVPDV2g00NrcQodeRm5lGblYa6SmJqFSiBrc7NLWYiI6M6O1hDChKK6uZOnFUbw9jwFBb30hifGxvD2NAUFFVS3pKUm8PY0BgrK4jJSmhR/fR0NR0zN6JvnnCYqz5OqbusaC3KmweouOWs67i/V8+7e2h9SuEAD9GOFJaSV5mWttjSZJISYwnJTGe48Y4bte3mi0cKa1kx95DfL12AwDpKUnkZaWRk5lKZIS+V8beXykuM5KTmdrbwxhQWKw29Dptbw9jQKAoCgoKkiT19lAGBBVVNQzOyeztYQwIKmvqyMno2e/uxPh4FFnu0X30BlW1tWwYqmPyPgtRFkcJ4cydZv53fCRb9+xhXEGBny0InAgBfoxQWFLOhJFDfS4TodcxfHA2wwc78jllWaaiqpbCkgo27zpAq9lCTFQEuUfTVlIS48WPrw+KSisZUzC4t4cxYGg1W4jQC/EdLhqbWogTqWtho6KqlmkTxN2dcGCsrmNSD9eRaNRqpk2YwMoffujR/YSbm06+GF2ahokHLW3PDSm3kVlt466rbuXT7z8RuiFAhAA/RqisrsOQkhjUOiqViozUZDJSk5l29LZ+U7OJwpIK1m/dg7GmHrVKRWZaMrlZaeSkG9CJ6GMbldW1pKVM6u1hDBhKKqrITE3p7WEMGMoqq8kwJPf2MHoEU2sry7/+mp+2bmX+rFnMnT6919MFzBYrer2uV8cwUGg2tRId1fPpg8nHWOHlwaIiduRqmbulFa29/XkJmLXDzLsnRvPtTz8xZ9q0Xhtjf0II8GMAu11GJUmoQnDVGRMdyejhgxg9fBDgsBoqq6imsLSCX7bsxmqzERcTRV5WOrmZqSTGxw7Iq11FUZAVReTRh5HS8iqyMwy9PYwBQ5mxhvy8YzMl4qn//Ictu3ezRH2YN57/ibdfgL+OkkjQSuhvXRb28ciyjMTA+x49lpFlme9+/rm3hxFSbvvVtSRFqxhZZOv0WnqdzLASKw/f9yizvliGViPkpT+EejgGKK2sIiO1ZyJVGrWanMxUZk4eywUL53DJ4nmcNHUCKpWKHzbs4PUPV/LW8q9Y9dMWDheXY7V2/mAei1TV1pOSGN/bwxhQlFZWk5kmIuDhotxYc8wWBS48+WRq6us5MRleGC8xLg6u3KxwqEXBvHRJ2MdTU9dIUoIodg0HLabWsNQ7fb9+PdFRx04K14YdOziYoWXmDrNX4Thjl5mGKIllK1aEdWz9FXGJcgxQWFJBXhht2eLjYhgXF8O4EQ77PavNRml5FYWllazbuAOrzU5CXHSb40piXMwxFyUvLjOKaGyYsVitogAzjFhttmPW337s8OGcNWcOd674gKWjJK4brCIvSuF3WxWuyoXzNj+AdsJDYRtPRVUtacfoxU5fw1hTj6GHHVAA3vj4YxaedBJ/f+21Ht9XTyPLMvf8/i5ybAp5RrvX5RJaFMYdsvL3fz7HmSefTHRkZBhH2f84Nr9dBxjFZUaOHzei1/av1WjIy05vuwhQFIX6xmaOlFSwdv026hocdkyZaSnkZaWRlZbS73/Yj5RWctJRy0dBz2M2W9Bphfh2cmDBwg6P8z//JKTbt1ptx/wt5N9feCGP//ABV29ReGoMnJkmMTwanjqo8OH/7eHW029lWn57VFoa+2CPjaW8qoYRQ4T/dzgw1tRhSOrZu5d7Dh2iqKyMaRMnwjEgwFesXUtFgooLV7X4TZQ6fq+Znblabp60hBd2fR6W8fVXju1v2AGAoihYrNY+VRwpSRIJcTEkxMUwbmQ+0B4lP1JayY+bdmKx2tqj5P0wl7y+sZn4uJjeHsaAoaSymsy0Y7MgMBQcWLAwpCK8vKqGdMOxHZFVq9Xckq/i9SKFO3YqvDFJYniMxP+NhbU56TyyvIj8tAhunp9FXrIeZduDPSbCjdV1zJoyrke2LeiIsbqOKT0csNq6Zw8zJk3q9cLeUGCxWnn04b8xosZOaoN/W8VIK0zZZ+Gn4ToqqqtJSxbf294QAryfU9fQREJc388ddI+Sg2PsR0or+WHDDmrqG9GoVWSmpZCbmUp2H3ZcsdnsaNSifCKclJQbyUoXKT9O8j//pFMUPJQivKyimoxjXIA7OS4BVla1P9afNp45wMzhcby1zshlL+xl/rhEzpyQxCjlAVTjQp+aYrXZ0PXzu4L9hZq6RhJ7ON++srqa1KRj4/Pz7uef0xwhMX23OeB1Jhy0sGWQlptPuYS3NokW9d4Qn/h+TmFJBYOy0vwv2Adpi5IfzSW32eyUVjii5D9v2Y3F6nBcyclMJTcztc/4kotiwPBTWlHdq2lWfZH8zz/BvHQJxV9Z254LlQgvM1YzIn9gpESUmyHdQ02eTqPisllpnDkhibd/NHLHO4eZOH4Ifxy+koiIU0O2f7tdRi3clMKGrPT8fFfW1BwTDWkampr413MvMaHQQpxJCXg9jQwzdptZMTGCfYcPM2zQoJ4bZD9GCPB+TmFJOSdNndDbwwgJGo2a3CxH4aaThqYWikorWb91D1W19agkiTRDErmZaeRkGHqle2dRaWWPd1ETdMRiFR7JntDfuoxsOrp2mJcu6baVXkNTC7EDpAlPhRnSPHyNSGNmA2AAbpgOV5utPPTMV1x2z3s8eWcLmalxACjbV3UrNaWqtp5k4agUFsJ1sVNdV0fKMeABftO085ByNEzZZ/G/sBsjim1sGiJz24XXs3zd/3pgdP0fIcD7OfWNLcd0LnJcTFQHX3K7LFNhrOFIaSVbdu6n1WIhUq8nJ9NATmYaaSmJPf4FW1xuZPLYnu2iJmhHFGD6JtS+1bLiiHT1hbtN4UCvgrJWx/9187znYUfqtTx283ze+HgTv7nrXf5+90LGDEtvE+pdxeGAElwTNUHXqKlrICkhrsf302o2ExnR841+epKSigq2DNZywk4z+i64C0s4WtR/OCOKn7ZsYep4YVrgjhDg/Riz2YJeN7DeQkdnzhQy01Laune2mFopKjOyY+8hvv1hI7KikJIYfzR1JS3k7bRFNDa8lFZWk9lDPveCztTWN5IY3/frSkLFGWnwahHsGpGPP4kgSRKXLJpEVno8N//lf7zx1/NJS+neXFUYaxh7NA1P0LNU1tSFxYLQYrWi7edBg1vOuIKYRDXjDlv9L+yF3Co7eRU27rvxPr78ZrloXOfGwFJvxxhFZUaRCgFERUZQMCSHgiE5gCOCV11Tz5HSSr75YSMNTS1oNWqy0g3kZqZ2ywaxOUxNHATtlJRXkZUucu7DRVlldY819vKFpwY4XY3uV9fVkRQfWM2IXiVx7YJsnl5ZyotXDEWSJL9R7TlT89myu4yXl63n7t+e3KUxOqmqrSelh23xBA6M1XXk5/Z8d1er1Yq+Hwvwnfv3sydby+m/mFAHnvrtkZk7zbx1UhSfrVrFmSd377NyrCEEeD/mcEk5I/PzensYfQ6VJGFITsCQnMBxR1NFLFYbJeVGjpRUtDULiouJIifDUeCZnBSPKoAf6+IyIzmiAU9YKa2sYvK4/l/Q1F8oq6xm9PDBYd2nU3writKt1BfnduaulrninHO44ZJLPC7Xajbzz39cz4ZDeiobrJw/1UpNk43Vexs4sSAwMXzRmRM496Y3uP7iGcR2IwvQZrcfE3Z1/QFjdV3bndOepLq+nvjYWEzmwJ1D+gqKonDHpTeRrpYYWtb9ztYpjTIjj1j5y2NPccqMGUToRQDLiRDg/ZjyyhpOnj6xt4fRL9BpNQzOyWBwTkbbcw2NzRwpq2T9NkeBp4REakqiwwYxw0BMVOcuXkWllYwaJi56wonZYiVCpPyEDWN1HanJCSHZViCC2rx0CVvqFZ49rLCrCaYlKtySL5Gz0H/OqLGmhotuvZXjxozh4qY1DI9p39fL//0vk8eMYcbEjt+RR8rKuO2hmxlsiOC+s3KI0Kl45OMiGlvt/OmjIl5+/EQC8X9JS45hxoQ8ln+zk1+fNT+ANTpjtdmE+A4jrRZLj3+XNDY309jcTIbBwMHi4h7dV0+wesMGig0afrXGf9OdQJm+x8LeLC1vf/oply/pfKdroCIScvopsqKgoAj7qm4QFxvNmOGDWXDSVC5ZPI+LFs1l3IghNDS1sOL7X3j9wxW8+79vWPPLNgpLKrDabFRU1ZA2QPyR+wJmi1X4I4cZuyx3WxTW1NUx44ILeOG99wDHLfkvVq+mrqGhw3Iljy3mwT0y9+5WODtD4qMpEjmRcGdxBIri/953fGwstY2N5Bet4YbtCn/bL/MfnSMt744zsrjnb3/m63Xr2pb/5scfufS2P3DO5BQeOzeP0dlR5KdG8Mxv8jHZJC5eMpXr/vQRNfUtAR3nhWdM4J1Pt2C3e2/P7YtwtUUXEND5FAoOl5QwOCurX+Y72+x2HrzjIfLLrGTVdO2c9kRMq8KkAxaefek/nb4DBjLil62fUllVS1qyqJwPJSqVinRDEumGJI4f7/CcNpstFFdUcaiojLXrt3O4uIJPvvrBUeCZEXjqiqBrOPKRRf53MHTVhtC8dAmtigatPBLz0ueAruVg73x4MbfuUIgHvvn4bS4rfpefahX+vEtBASbFw/REiaJWhc8q4Kx0eG+yRJTa8Tm66epxLHxqFztLTIzx0xxSp9UyRG9jUrzEWeeO4sP1NZTXW3n/+gKGpkUyITeaG//9L1764BUS4iI5VFzD0/efw9jh6Q77wDGzsVhtRGrUTBhZT3ZaPPNmDOfGRz/hhYeXEKn3ncc7riCduFg9aze8yonHXxn0XFVW1ZJmEN/j4aC5pdXjXc1Q8/E33/RbD/DlX39NbYyKM38xhXzbx+23sG2QlptOuIBXt4nmPCAEeL+lsKS8Q1dJQc+g1+vIz80kPzeT6toGfty0k5lTxlLkkroCkJqcSE5mKjkZBmKjB4Z/cjgQBZjB4amQMRhWN8WwubmBbfUyY+MkFgch5s0WC+/ffT4vHVG4cYjEkRYFowVa7QpPH3Q8NycF1qRns/5wE7mD9Lx6TgKDDBFYVmwF2m0A549L4LvqeMb42aey7UF0KrBPGkJqnI5r5nT8ThyZGcXyf/2GA0U1lFTUM218LglxDhHmLLQ854Y3KCqvJyUxip+3FnHPNSdz3z8aufvJL1h6xxmofXS9lSSJi86YwFufbuHEKd+CFFyRWbmxhkljhKVpOKisqcMQotQqb3z01Vf8uHkzby1d2qP76QlaTCaWPvkvxpbZSGwO/d0CnR2m7rHw/Rg9RWVl5GRkeF3WbrezbvNmPv/+e75YvZpHb7mF02bObHu9oamJp159le/Xr0dRFGYedxy3Xn458bHtjkRHysr4ywsvsH3fPobl5XHjb37T5y6M+t89EgEAhSWV5GYKB5RwUlRWSU5mKvFuqSsXLzqFCSPzaW4x8dWaDby2bAVvf/w13/+0hUNFZVgsXbdxGuiUVlSRJbqOBkR3xXeVReHNylhyVA1MSpB4o1hhWZmCsu1Bn+spisKylStZ+OvzWFer8OzVw5nzqzEsq1Zz1YUj+ZctiSFDEjjnknEknT6esyYl8/CSPK46KZ1BBodXsm7euDbxLY2ZzbS5M/n2p4NYrd4/O8q2B2k22zlgVjE2J9rjMtKY2URF6hg7PJ35swraxLcrrzx6LmqVRH5uMheeMQFJknjwulNoMVn428vf+01dmHfCMPYVVnGgqBqUb30u6051bQPJiT3vSy1w1Db0VLqPoij8+733eP7dd/nHvfcSG+35fOzL3DJxCVaNxPF7g2+6EyhjCq3EtSjcctZVPperbWjg0eefZ/327dhludPr9z/9NKs3bOCWyy/njquu4pdt23jomWfaXm9oauLq++5DkiQe+sMfyDAY+P1DD1FUVhbyY+oOQoD3U1rNFmGHF2aOlHq+6FGpVKQZkpgybgSLT5vFb5bM45wFs8nNSqO43MiyL1fz+ocr+O/n3/Pz5l2UVlZ7/FIRdCYcRVPHAt0V34qi8NAehVEpsVxkaOLMNIl/jJF4qULNt7vqvYpwWZZ5/KWXeOvVZ3hspMS/bp5AQUYU7/5o5IRhcewtN7FuXyP3LcoJyN3EGZWePCabdEMM73z+uefxHh3PpsJmRmVGEqHt/FPmbiW4p/4Ae+oPdFouJTGaT5+/nOrGRh5/aRW7D1YiqSSuPm8q732xldUbDvscs06r4Zx5Y3h9+cajgwtchIejLbrAQSiLi12x2mw8/MwzfPPjj7z2178yJCcn5Pvoaapqa9kwVMfkfRaizT2XK69WHLaE+7K0bNu71+tyKYmJfPbCC7zy2GOdXjOZzXy/fj0XnXkmZ8yezfxZs7j6vPNY9fPPmC2Oi4fPvv8ei83GE3feyclTp/LwDTeQYTDw3xUreuzYuoJIQemHNDa3EBPVv7ts9UfqGpqIjw0ssqHTahiUnc4glzSh5pZWissq2xoG2WWFpPhYcjIMZGemkhQfO2C6DwaCxWJFqxFfUf7wJL6DzQP/6t4lVFtgerSOKMkRdc6OlBibHc2O4hbmnHtWm+h1posAPH9YZnsdPDtWIk7rOHdbzHbe+qWeP984j/v+sYJ/3reYuGHBpcupVBKnzxrBd7/shrPO8rrcRxuqOXGEb9tAd9HtfFwQn9/+WAsP3zuD5Z8e4JYnPqG6xkRcdAS3XDaLqeP8C6qLz5zIBbe+xcof9nHqjGGdLlg8taq3iALjsFLX0BTyrtFNLS3c/vjjaDQaXnrkEaIiez7HvCe46eSL0aVpmHiw56LfToaU28istnHnlbfw6fefBP2bp1GpiIqIICstre25EYMHY5dlrDYbep2Or9etY+akSUQetTxUqVScPHUqn61axU2XXhrS4+kO4tPfDyksqSAvS+R/hxOHV6+qWwI5OiqCgvxcCvIdJmeKolBb30hRmZEfN+6kpr4BCYm0lESyMwxkD/B88t5qCNMXsVgdFyOezj/9rcu6JcKbn1jM/x1WuH6wRMnRzZe3KrylSuaQsZFHz+1ou6mbN65NhO9thktz2sU3wAe/VDM5R89/V2znkrMmMuao+Fa2r3Ici01mgzKE6RNyfX6eSo0NZBi8p9mtP9TEztIW/vyrzragzui3p4i3N9RqFUvOGsaSs4bRYrKi1agYkxJYfnZ8bARL7zyD6x5eTlFZHZeePQvVrtVtryvbHuwkwiur60gVhfRhQ0EJWcG8oih88+OP/O2llzjp+OO57cor+62dZElFBTtytczd0oo2dMYnXpGAWTvMvHtiND9s2sQJkyYFtb5Wq+X02bN56YMPmDhqFKlJSazduJGZxx1HTJTj97LcaGTquI4V3HmZmZRXV3e710AoEQK8H3KkpILjJ4zs7WEMKHpCDEqSRFJCHEkJcYwf6YjG2WUZY3UdRaWVrFy9nqaWVrQaNZlpyWRnpJKdloJ+gKRkFFeIAkxwdKW7+o9/xG63M2/mTG674griYjpG8roiwq02G7seOZcnDyhkR8DwhGhKLU3cv09mXZOaRZMkXrhiKJETvRcW2hVQufyWtVplXl9byWPn5XHzW4d4+IZTgXbxrSgK9y87wpr9u5kzLZ8/3TDP67bXby/mojM977uoxsxjnxRz47zMTukn0pjZHYT38kJHVHJRXkdnB1/iPCpS27aMM1Luj1H5abz5twu4/58r+X79If5842lkp7tE55WORZoVVbWkpQgBHg5C6bfe0NTEPU89RWllJX++6SYmj/FXKty3MdbWoqgkzhulI3lU+H5b/qcolBmNXVr3jquu4op77uGsa6/lzJNPZuOOHbz06KNtr1fV1XUoyASHZanNZqOusZHEuL5RdyEEeD+kqraB5IS+cQINFIpKK8kOQwdMtYsV4pSjVohWq43SymqH88rWPZgtViL1OkeUPN1ARmoyGk3/jL74orS8ikmjh/X2MHqFAwsWAtAE3KpT8TubzFgZ3lr5Feeu/Yb7hknM+vOHHdbxJcKdWGWFVdWwrExheyMYdHBOhsT5WXB/cSx7TU3oVREMT9fw1Y46Tls0B2cMuiV/OsafviUvJaItCi4rHQuJlr+1jdHZsUTq1ERoVSg716JEtJ+bNc021u1v5LObR7LgyT3cceVsYqM71rLsqT9Ac7OVrfvKeGL06A6vybLMK89ex2vflnHFKZnMG5PQ4XVv4tv1/+5C3B/BiPDM1DheeGgJb/5vE5fc+S7XXjCVs+aMarczdBHhFVU1TJ3Q810ZBY5i15SkwDqc+uN/332HRq3m3SefRNuP2833Z15ZtgxJkvjTTTfx+vLllFdVsWnnTuZMmwY4ouzuxdPOx33JNlgI8H6G40q+e6kQguApLq/qNbswrVZDXlYaeVntOW8trWZKyozsLyxh9S9bsdllYqMjyc4wkJORSmpyQr9sBOFKq2VgFho7xTfAcrXEeFlh+tGa3YdP0vBjrcKf9iqc+LuzufWpd4iMcDSt2XXgACsPy2xvBKsMDxVIpEc4vidKWxU+Klf4pBwGR8GSDIknR0PEUe/t1lmjOPKGlYbmEsZl6Zg7OgGLIZ+7n/qCOVOHUlJRz/rtxWiw8eVto1GpJHTzxjHUVsLGIiPTkxyPf3jjIPNGJzA6K4qTR8Zz1Uv7ue7KU5mpL0SSJIwNVtLitMRPmcuooXVs21vOjIntKSRO8fzzhjLGjEqh1Po2BbQ7Jvz88e18vLGGt24YSWZix3PDvejSVXx3l2BEuEolcclZk5gxMY8nX1nNv95cx+wpQzjzpBFMHZeDhEOE19Y3kpgQ63+Dgm5TWV1HaogcUL796ScuXrhQiO9eYu3Gjbzy3/+y8pVXiI6M5NQZM/jo66+59a9/5eVHH2XiyJEkJyZS39TUYb36xka0Gk2nyHhvIgR4P8Phi9zzkVhBR1rNfcuNIypCz7DB2QwbnN32XENTC8VllWzddYCK6loUBZLiY9vyyZMT4vrNhZvFahuQBZiu4rseWKGW+JvFob6zT3H84E9LlHhzEiw9qLD4mktIzxxKWWUlepqYMzKVLJONrUdaSD99OHvKTDz7/j52NsLpafDsOIlBUVKb5Z8TraJwQkEClx+vI27yHABkWSE2Wk9pZQPDB+Vz2xUn8oc/L2fzkWYmDXKkwFwwLYVLttRwzWWj0AE5SXpKah2FXLctyGLF9jqefn0tL0bq+NevUqg32YmPcryvyQlR1De1epyH79YUc/q8wQDsqXuRgoSrQPmWPeUmpg+L7SS+nTgFvC/xvbwwMugoeKDi25X8nGSeuf9sqmqb+XLNXv720vcYkqK5+NdDSTUcQFZy+1Q07ljGWF3HiKG53d5OXUMDuw4cYNr48SEYlaArrN24kcljxhDtUvB69ty5/OfDD/lm3TomjhxJpsHA4eLiDusdKikhI7VvWTcPvF+4fk5hSTmDRAFmWGlpNRPZh8S3N+Jiohg1bBCjhg0C2os8i8uM/Lx5F9V1jhbAhqSEtvSV+NjoPinKHTn3Sb09jLDiKr4BPlJLzJQVJp3SOdIWp5V47A/j2VPWQovFSmKUgbyUbHaVmrjutQP836X5bCps5q73DnPDvByeHJfo0arPiSRJJGVkEDf5uLbnVCqJ+bM6Nq446fh81tbKHHfmCSjbV5GdpOe4QTF8tLGGi6YbmDc2gTveOUxWoo6nviyl2WznN4unUFLRwIvbtcw7YTItaxw2fVqNGou1c9WXzSazZ18N9942te25PXUvUhCfj8UqE6XzbTnoLr4/W5fM6dOrvR57T5OSGM3FCydy/unjeX35Ru55aDVnnzmcOJ2wIg0XVbV1GJL8tFUNgH2FhQzLyyNCP/DuzPUVEuPjWb1+PVarte0uhMVqpaGpieijRZinnnAC/3rjDUytrURGRGC32/n2p584dcaM3hx6J4QA72eUlFcx47j+XfTR3yguM5LTD5seuRZ5jjta5CkrClXVdRSXG/n+5y3UNzajkiRSUxLJyUglKz2lTzivlJQbyUobOHd63MV3xIkavtug8NYkzxdHzgh2QUb7e2WzK9z9fiF3n5lNXYuNez84whMXDua4Qb6t16Qxs2lqsRFd4lmkuuZUV9e1MDg7kZq6Fg6Sz5DsJM6cUM+7P1Vx0XQD43KiufzEVD7aWMOfz8ljSGoEd/2vGL1Ow6pfDnLazOE0NpkBaGoxExPZ8cK2ID6fPfUHSEmOpKikkfzBCR1ej8obTtWOnT6Px5XP1iV3+NcpxLsSBfeEu6WhLzRqFTPmJjJo9Am8+tpB9JpCJk97lqgobcf1g+ymKfCP1WoPieWjsaaG1GThzNTTFJaWUlNfT1VtLQCHiovZtGsXSfHxLDzpJN78+GN+99BDXHD66ajVat797DNazWbOmO24ED9t5kxe+uADbvnLXzhvwQJW/vADVbW1LDn11N48rE4IAd6PUBQFm10ekLfme5Oi0kpG5Hf/9mVfwCm2U1MS23La7XaZiqoaSsqr+GrNBppaTKhVKjJSk8lKN5CdnkJUZHh950sqqpgwQAowXYsks0/RsrdJ4c5tCoszwKDvLMDd00ec0d/N24qIji8jpmAC9/5jBU9eOIgJeZ7Ft3u+dFmlhYxUvU9nEIvFzrKV2zl+bDYvvPczLSYLD15/KvGDxqBZv6ptufOnGjh/avvF0//dfzY3PPIxTS0WXl++kcqaJmTZ8V3m7ebLOWcN45l/b+bBu6YTF9cebRySk8SnXzYHbCV2+vTqNvHtjqc0lVCIcl84hPYBlpw5hrU/FfLXv//CpReN5rO9K5k0KJ/ZU4Z0cksRdA9/nUyDwVhbiyFpYN2Z6w1e+uADPv7mm7bHz73zDs+98w5nzZnDwzfcwMuPPso/33iDR59/HlmWGTN8OC898khbe/vY6Gj+/ac/8dgLL3D/008zfNAgnrn//g7e4X0BoeT6EdW1DaSItsVhp9xYzUnTJvT2MHoMtVpFZloKmWkpbc4rNpudcmMNxeVGtu4+gKnVjFajISM1mex0A1npKT2aE99qthA1AAowneLbmd/dale4bafCVbkSCz38VngT3wCV1c1U1jTxx6dX8NTdZzJhRGbA4yirNEN8NQ7/AM/U1rUSHaljwshMTp89gmff/pHTZg7jj0+vZEy257sm0pjZRAJP33cWi69/jS/WOLrfNZksjMpPZeeBSuZMGwo4rAqlMbMdIvVEMFaZuOvB1dxw7SRGDHeInuPH5mCyyHyxtY4F40Nv4ReqyLgvCuLz+al2H+eek8fbHzTwj2c3MCg3nhVff8OJkwc7LiwGoAiXZblHCscbGpuJC7CBmj+q6+pITkgIybYE3nn4hht4+IYbvL4+JCeHp+6+2+c2stPTeeb++0M9tJAiBHg/QjTgCT+KomCXFdTq/u0oEiwajbqteNOJxWqjrLKa4nIjG7bvxWyxoNNqyExNISvDQFZqckg8yq3W0Hn29mU8WQb+VAvZEXBWekch7C68oXMUe860fKrqmjl77mjiYwO/Y7Gn/gB7SmWmD27fp6fo8NwUCzOmZ7C/sJr3v9jGM/cvYsvuMrbuKeOBawf7HF+kXstzDy7h8nve5/mHFhMXrSc/J5mVP+wDXHzCXUT4eUtgWH4CT/5rA7+7ajwFs/JRq1U8du4gfvefA+Sm6Bmd1Vn4L8ozdRh/sPnf7naFXSnA9EdzM8TGSlxzhaOYT1EU/nDbN3y1YzO5OXGOVBxn8ekxinnpEpptCu+VwueVCoUm0Kvg+AQ4ZXYOJ46IJyGqXaJ46iYaCJU1oWtBb7fbB8R3kyA8CAHejygsKefUWZN7exgDitr6RpLi+45tUW+i82CHaLZYKa2ooqS8il+27MZssaLXaclKSyE7w+FRrtcFZ9dVZqw55jtgehLfAPU2yHDTzoGIb4DICC3TTk6gXC4hnsBEozPlxGqBz8p85/7v2VvLqjVFTByZxRuPn0+EXsPlSz/g9itOJGpSexTb2/gGZSVy4uTBrN9ewvBBBgZlJXKwuMbnPieOT2Ps6BTq681tVoAjTp3PH2uXc+tbh/jvDSOI1qvbhHt38Fas6cuCsKviPEYbjSS1R9olSWLUyGR27qnm1DETHds+hsU3wN4mhTt2KoyKdVhmDo+BZhusrYVVuxt4/LMSRmdF8esZBmYVdN3D21hdR1pKaNJGJEkKaUqLYGAjBHg/oqmltU8UyA0kikor+2UBZrjQ67QMzslgcE5G23OtZgulFVUcKa3kx007sVhtROh1ZKWlkJWeQmZqMjoforyk3HhMd8D0Jr4BmmwQ4yfA5kloBtNy3X15u13BX1BvUZ6Jmrh4Lls0mYPFNVx8+ztoNCrOmTeWk6e2i1BvIti5v9xhelZt2MNxs2Jp0Jiprm3xO9ZKYwupho7fe3POW8SnW17l0821nDe1/VxxFnG6R8H94S1PvCdoMdmJilC3iXfn3BwpauSyBY5GIgMh/aTJBsk6+KUOjBaFCBUY9DA5XuK2uAYS7hjLmr0NPLy8iMfOVTFlbNf2Y6ypZ8zwzndouoIECPktCBVCgPcTTK3mPuVDPVAoKjMy47jR/hcUtBGh1zEkN5Mhue05yK1mCyXlVRwpqXAR5Voy01LITjd0EOUlFVWMHxn62/59AV/iG8CigKvLnqfodyB4i9p6Eup1tVAuafEnV5MSI/j9RY7PQsUPK6lttjPi1Gl+x+FKdlYsyz5xpJ1ERmpoMpkdBZVjZrdFz91JTNBTW9fa6bguuGAuf/nXZ5x7fLLHgkxnCkmwQtyTU4r7cXQnLaWiykJaSvt3eUF8PnUNJiorTYwZlj4gxDfApASJlyZIGM0KJa3QKkOJCVbXKDx9CP49xcypYxL4dEsNjabOdpWB0tDUTGxMaAJXkkolIuCCkCEEeD/hSEkFeVkiEhtuahsaSRQpKN0mQq8jPy+T/Lx2UW5qNVNaUd0myq02G3qdltKKKiqqaslMSwk6faUv4G4p6E62B19vJ3oV1B61hw409cQbrmLVV4S8phrUsd5rHDwVJabG6Uj1UQ/ubX+bbAbKjSZazTYsFhlJkpBlBfXRjpzO43NdPzMjhq93tnLCtI7HNXlMNrKisOFwM5MHe7da9BcND2f0G6Ciykxaih5l+yoURWGLZjhvfLyRyWOy0OpOCetY+gIGvYTBWW+dCOdkSnxRqXDDG4d45eph7K9oJS2+e8GnUPU68NTiXCDoKkKA9xMKSyravJwF4cFul1FJqj7ZqOZYIDJC30mUNza38M7H31BUZuTnLbswWxyiPDPNYYmYmZp8TN0JUhSFQy2O9vCSJKGTwCIHHvn2l3oSSGrKL4fUROQFV2Ts60LA2z6XF0aiUkNqcgTGKhPLPt7H7JnZ7G86REF8vtdtThibytcvbENRhnT4LEqSxPlnT+e9HzZ3EODONBRXfIlwX1aFoaRs7Uo2HGrip2ID1tYirFYzBytbUdjN4uOSOWvSwLK309+6rNNzzjtE81MlvjJauPLFfRhitYzyUGwbCGazJaQX8SIHXBBKhADvJ1RU15KaEnrbLYF3yo01pBsG1o9ib1NX38SwwdmceHy7AG01WyitrKa0vIr1Wx2FnjqthozUFLLSUshMSyayn1oW/mW/wvJyRxHaaamO9BOzl993d4EabN63O05BKre2oors2YtMV2eRFVaZL78+TE1tK/dcMbXTsp3SPYYlEq2RWb+pgimT0jukf5wxewTPvL4aY+ZxuN4fDFaE+xq3+x2AYNJP6hpM/Hfldj76bD2NrXYmDYohOSWb47MiUO80cmEWjIkFqaUc1pRD5+nodWrq6vjmp5/4YdMmAOJjY/ndhReS2gN+2Ppbl2FeugSbrLC6BiTJwr1n5XR5e8baegxJCSEbX4ReT2Nzc8i2JxjYCAHeD7DLMhISKhGJDStFZaIAM9yUVFSRmdaxADNCr2NITgZDXAo9zRYr5ZXVFFdUsXHHXlrNFjRqtaN5UFoKmekpRIe5eVCwfF6psLke/jhc4rNKhdNSJVplRwTcHX/i25uw9OZp7VzeGc2TJCkkLds9XRS4ithKYwvVNSZ+/LmUh+45Ab1e3baeJ9HsHNu1V45n6dPrSUmOpMDl5kBstJ75s0fxyrL13HHl7A4R8mBEuDMK3tXjd89fNzZaef6bclZsr+PkkfE8dt4gRmVGAhKvf9HKPGMxGCR2NCqsNELCNiuZCuTf2qXddwlntNlbJNoiK7x8ROGDMpiaALOTJaIm5rGj5CCX3vkjT997FsPy2j+r3nL4g7UP1N+6jO0PLAZgcRpMG9r1FEBjdR0pSV13UHFn2oQJ/Pn//o8bf/Mbj68risKeQ4ewWK2MzBd3rAW+EQK8H1BWWX3M27L1RYpKK0XaT5gpKa9ibMEQv8vpdVrystPJy273xbdabZQZayitqGLr7oO0tLaiVqlIMyQ5HFjSUkJWjOUNf/nfTkpMCn8/oPDPsRK7mxxuENsaFF46ovD4JR3POX95376iuv4ivopZQaWXOrRsdxWhrgLeX+TXV0TeKcLX/liCosCMqZlkZXbM2/a1/ohhSVx60WiefnYjc54e16Gt+BVj7Zz/zE5+NcTMkFTHRVdXLAlDJb6/3VnHI58Us3BCEh/eOIKU6Y+0vdaw/mFisABgsivcuElmtAw7tSpuscpkL13iURCHGtdiYGXbgx1EsrLtQcpaFW7eoZAbCW9Pkto6supGJ3Dq+YsoWL2H396/jEduPo0ZE/IAx5yXrF7BGz8YOWhsZfFxycwZlYDWbfuBsGrwItjyEbf/410kfdfvbhlr6hk3wv/3SaCMGz6cZpOJpS+/zOXnnENSvEPcK4rC6vXr+debb2JqbSUyIgKrzcbvL7ooZPsWHHsIAd4PcDTg6VstVAcCpgHSjbEv0dLaSnRU1yLXWq2G3MxUcl3uWthsdiqqaikpN7L7wBEam1tQSRKG5MS29JWEuJig8/xtdjt2ux29rj0f3Z/4NgNlEmhaFf64R+GyXInhMRLfVslk6OH9UoWrTs1i8uD2iF8oLAd9HkeDzE5jHHhIqw+F+Ha/AHj/I0cnzF8tGh6wS4uTmdOzePXN7dQ3mjEkOX66lO2rMMRqsdhk0uJ7pmDXV3dMV/Ftsth54vNSfjrQyBMXDmZCbnQn4VmZciUG6W8AvLXKzkiVxO02mR0SPKFVEVejcEIPi3Bl24OdagycIlzZ9iCltWZ+v0/LxScZuHBaisfPxoJZBaQnx3DHE58zZng6C08awZdr9/HTliMsPmU0i2cY+ODDNfxzZRmPnz+I0WOC6+x53UUXcd1FF3X4fHWF6tp6UhJDFwFXqVS88be/8cybb3LmNdcQHRXFoKwsjDU1aNRqrrv4Yk46/ngkSeLTVav40zPPhGzfgmMPIcD7AUWllUweW9DbwxhQtJotROj7nwNHf8ZqC30HTI1GTVZ6SgdfcbssY6yuo6SiijW/bKOusQmA5IS4tvSV5MR4rylfP27Zwt1PPgnAf/7yF3IzMjqI7+xTtBR/Ze14bMBNOhUS0LRRYVE6nH+09rTCDIPHZfDDmkrumdBe59HdxjL++GxdMpmt9bRo20WOpyhwVy333MV3SWkTdrvCpReNYkrOKI/reEtDAbDZZEytdpLiO263qNpMcoyWaL3/cyfYHHB/yLLC1uIWvtpex5fba5mWH8trI6wkeRDfABVVtWSffwe8fz2r1RKL7Y58o9EK3G2V+dNeiTuGwpweEOGVNTWs++QB1u1vxGxTSIrRkBytITlG6/h/4W1sOdLMf9ZUcu2cdM6faui0DddzcuKoLD559jI+/Go7/1m+kVOmDeWPv5tDTJQjaDF/VgFfrdvH9c99y20RuzljNgGL8O4Kbyc2ux2NJrTfKckJCdx/3XX88fe/p8xo5HBJCUnx8QzLy0Pt8v11xuzZZBoMXH7PPSHdv+DYQQjwfoDFau2Xdmz9maKySrLTO/8ACXqOcBW9qlUq0g1JpBuSOG7McABkRaGmtoGSiirWb91DVW09igIJcdFkpqUgP/QwiS2NqBSF5zUqTlYUYoGbr7mWP1plnDFrp8Wguwj/WSVhUOBhq4xigZwhjuV088YxObmaRz4p5pzJycRFOr6SQym+fTl8RMlWylSd/QS9RXwDxZPQLS1vQqdTseBU301RvFknRrYkY0iMRq1WdYg876toZWhaePL9C+Lz+Xrdfr756QClh4s4Um0mPlLDvDEJPHfZUHI27wUkrykXFVU1TBg1FPn6tzn0/XmMcsn3H67A02Mkbt6hsLle4fpf/kjslD8FNT7X1BKrrLClAX6sVfjRGkFFg5Vp+bFMHxpLTISamiYbNc1W9lWYqDlgo7rZRlqclpevGsZgQ+f59HRORug1XHjGBC48YwJw9D2rb389Z5SKe26fwhNPr+aHXfu4+Lx9jEr+bVDH1FVkWe7RuilJkshMTSUz1XudUGyMd3tMgUAI8D5OXUMT8bHiQxxuisuMDB2U1dvDGFCUlFeRldY7HTBVkkRKUjwpSfFtTYAURaG+sZmSiip2GNL5JWoYRSoVFrsFdWM9xzXUUWVq5DadigesMsfPbb9IbrAqFE7SoN5kI1uBD9RSWwe9HDcf8EWTkkhP0DHFh5e1k0CLLwM+bkVB8SFSuhr9di92XJRngrx0Xn/h9IC36b7cPz/5gTnT8juIb7us8NraSs6Z3HM1Ms6LEavVzt1PfcGuA5X8ZkoMi4akk5WkJzNB1y645/reVrPJkWL14ekLydOoOjQ/cl68vTkJ/s+SyJy/bCc55lwyMoeSbjCQYTCQnpLi+P/Rf2Ojo9vWV7Y9SMXkAlZ/vJsfaxU21sOgKJiWCPeelcPorCg06s7vdagu9rzducjNiePRB2byj2c38tiTP3Pj72xMzv59SPbpi7qGJtHDQdCnEQK8jyPyv3uHsspqZh3ftS6Egq5RUl7FmILQtIwOBZIkkRAXQ0JcDBGH9/KxWqJUJXEtGuSYeIzxyQzKGoxereZNlYzF3kim1EB1YwP377IwJAr2a1WcaFeok+Aim9KhCY8zD1eSJKbl+8777glUiow9BBFCb8LLKcKDySX3htliY/mKTTx32VDAEZ21rNjKW8UK+kaFRZOGtS3rqZkPBH+x4jpui8XO88/vIkKn4e0rc4jQtvumB1pg6HScObBgIdvVEqNlz36TqWeM50Hg3oXZVDZaKauzUhE7kbKqKvYePsyqX36hvKqKsspKJEki3WAgPVniSGEZLRaZGcMSOH1SHA/lx5IY3f4TH67zyhMxMTruuuV43n5/N/c+tIZbb2hl3thbenSfxuq6kFoQCgShRgjwPk5hSUUHT2RBz6MoCja7HPJ8ZIFvmk2txESFNkc3lJRIMFRWyLRboNZIdq0RcEQuL9goYY+Oo2biSD77qZGTx2gZFKkw61ADy02NnNJYx2WzbN3afzDWg66vuTeayfvCMW5tjIwuzg49+PXiS3y7RrK9icMyYwPbvv6W936uYuqQWPJTI7Cs2ApAs03h1SKFF8dLWFdu61BYGGrx/dyzO4mO0vHITaeh2b2mfdxBuHvUNzbDN98AsEMlcZ6tPf/EeWHmegxajYqsRD1ZiXqkMQApR/9GsKf+AIqi0NJio6rGRIQpntTkGQxr2olK1XNRbl/4yt8HUKtVxE4/jiHRhfzp8R8p+83DTJuS2WEZ5zniydIwWCeVypo6cjKEjayg7yIEeB/HkYIS7X9BQciob2wmIU6k/YQTm82ORh1cN8Zws0El8YDVg0k3MCzKTktzHbP3/sgv9TJ1Vph6RKYuKpak2DjqMofwruywQEzERLrUQG6jhpRoG66H3VOuJ64ivHC+gbwvjGijZKzNKvK+MFI4v+v1Dv6El3MZV7x5RjuRZYVXP1zPa8t+YtKgGKblx3LZrNQ28Q2wpQHS9ZDjoq09zV93xHdeRB43PfUJCbER/PnmxxwX5WO71i6+oqqWxOZGWoHDEow4GgD3JL4DQZIkoqO1REdrKYh3Wu2lomxf1WvRbn/ngiMVKZWDY6ey9J/r2b23lrPPHEpCvB5ZVthzyMgv24v55YeD7C03YbLIGGK1nDY2kQWGj8hKPzvgsRir65g4epj/BQWCXkII8D6M5WjHP9EKPbwcKa3sYGUn6HnKq2pI68NdR2VAAo5IEjluraiLv7LSmqkm8qiQvihL4px1MnNRyGxuILm5gexTKhzbUaCOSKrGjWVLqRZjswZFgWidTEaclawkE+kpenQ63xcjrqLS3bs7kJbrhfMNjN1TQmuttpP4dgrQrqaLuBOI+HYVjSazlfv/9BaVjVbe+l0BGQk6LCu2Yv+qosM6k+LBDjy2X+Hea8Z2e5zuhae5Ebnc+OjHJCVE8acbH+32HbEKYw1JzY3skmCwAnrokJLkTjAXY85GRt7Wc183VO9tVxkyKJ7HHpjJu8v2cOOd36AoINsVUlIimTFuMAtOn8FtQ9OIjtRxuLSWz1fv4dd3vEte5pfc9dvbGTHEv7d3i8ncp++oCQRCgPdhisqNZGcIJ45wU1RaydSJI3t7GAOKkvIqsnupADMQVMC9VpmHtCrWyzBadlgLGiWolGBblcJJZXaKj2rzM9US76glbrF1FOsqCdLnDSOdVsZktLY932RWUdag5VBRK+s21mOxymi1KtSxTSQnQ1IyREY5LsTdxbfrv/6aybiK8NZsHYcKDB1e6yqBCjpfkW/Tpm9Zsa2W19YaGZERyfOX5aPXqjpEvV2JUEu8MA5uLonif1tqWXLpEo/LdYX8mMHc8MjHGJKieegPj3Swl+sqFVW1ZLY08qJGxTl2z/UATrpyJ8RVhPtbz9e2uivOvbnYuBMXp+fqy8Zx2cWjsdkUVCqprTOq6xiSEqKYNCqLs3+Vw5p1Jfz2gbu45bJrOHuun4pXgaCPIwR4H6awuJzhg3N6exgDjuq6BpITOluzCXqOknIjo4cN6u1h+GSQAk9YZDaoJHaoHKWABgUGy7DQLjPURWufYVe4XqfikKQw2HOtXQdi9DLDT57GcJfnLFaZnw83UVMFRw4rmEwKpS1q1FEW1HEq1h5IApUCLnfIAmmnfvr0ahRFYf/XHZ/rabyJ79I6C+//XMXyjTWMyozkxtMymTksNqA7f9EaiREZkbS6pQa5pkJ4az/vinuu+t9fW4PdLvNgiMQ3QMWW73lRJXPOYBW/yfF+bO7iO5gUpFCkKzm3EQohHsh4tFo1WrcbAZ7W02hUnDQrh0J9Go+9/AI7YovR6h0S5o7xF3dYtqXVTEREaLzEBYKeQgjwPkxZZQ2zp07o7WEMKOxHvWNF2k94aTa1EhPdd28X53/+ieNf4Pijz/nqfBkJnGNTeEOj4j43cWhZsTWgfF+dVoUhVcKQCo4EGPjosB65WcHWKGOwNhNhtyIBVpWaFpWWZrWOL35IZP6MWp/blk0KWTk2hhV0FN7d9f8OhgaTjYc+LGLD4SbOnJDEK1cPIy85uM6zunnjaP3wCB7qDgMW4e7i+6t1+/jy2628eW1ByAqxDz+ymC0NE/jDSBWnGjoO1vVccBXfvgpJw/E+eYuoB0OgIjxQlhdGkpAWSe6obL55bRWnXH4yak3ndK0q4YAi6AcIAd5HkRUFWZFR9/HCtGONCmMNaYZE/wsKQobNbket6n/nef7nn/gU4afKCivVEqtUEr/2s61Ai+YkSUIdI6GOUVF0OKHteY1sJ9puIdZuJs3SyP6vFNINFtQxKtSxKjRxKiR9+4WlvUFGHds+554EXSgEWIexj5ndIQr+w75GNhY2cfZxyeg1Ev/bVINdVlCrJC6clkJSTHtxorc0FJNFZtXuen57UprH4kNfItz9mAvi82loauWxF77jyfMGdbDw6w6tTyzmiSMRDE41cWqCd/HtDU8XDu72jj1FqM8BXwRTLDv5jImsenMNu9buZszszl1VK2vqMCQnhHB0AkHo6X+/egMEY3UdqeILJOwUlVWSK6yrwkqFsbZPF2D6Iv/zT7wW0mmBG2wy/9FIlLd2zEPxJii7ik2lpl4bSZk+jgNRKeyNNrC6OQNtihrZrGA6aKVps5nGTa007zKTWGvm+DQzZ2a3BC3k9tQf6HJUUxozu+1v1OzZLFkwEZ1GQiVJ6DQS0Xo1dS02Ln5uLztLWtrW8yZUv9hWy9jsaDITHZFzT2kurgJyUZ6p7c/TMv988wdOHhbJuJzQOE+Zly7h+2qok2I5Mbapw2u+8r731B9geWFktxsthYLuvN8QWCpLsMcpSRJTzjyOPT/uo97Y0Ol1Y3UdqSICLujjiAh4H6WwuJy8rPTeHsaAo6jUyJiT/VfYC0JHSbmx1zpghorsU7RUmBVe/sHOYAVmHm2yMmuulitKFK7eonDXMDghKXQeze7+3u4okgpNvBpNfHsaxVm5LTQ1wqpvoKYaDh9UkGUFjRaSkiSSjhZ8RkRKfgv6uhsdzctK5IZfn+AYq5twvuf9QlZsr2NUVlTbc+6R8H3NCv/cWMbfL/bfvMlbKoTr+HcfMvLNml0su2FE23PKtgeD9p924mwL/59ihdn5sWSqqtuOwx1P4tuJ63vs7nYTzpShnoqGByu+2+cjGdWg4/nijc3EJr/BXRPb7zPV1jeSmCC6YAr6NkKA91EKSys44+RpvT2MAUdLayvRkRG9PYwBRUlFFSOH5fX2MLrN77YqTM5W8XYtZAyRmJ3iENsXZkkMjYI/7lGYm6Jw+1BVexfMACzjfOFLhLuKtXahJhEbB1FRChee0u6R3Gq2U260UGY0c2CLmeYWOz9LpaQk6MhI1ZGRqiclSRfynF4nrvNQVdvM2oO7eP/vv0ZKjmkT5xX1FqpGDaW2xcbmVQf5uFbLHadndohW+7qYcR27JyH5/Ls/cfmsVOIiO/4sdkWEO8X3tgaFOo2OuPwcssbEodN0rsj1lfcN/i+03HE9tlC/V71pZehpDnQ5o7GU7Wf/+gM8rnqzrRhTlpV+mdYmGFgIAd5HMbVaiBJCMKy0mi3odd59eQU9Q1OLidjoKP8L9nHS9DAnRWJBKty1U6HCDJmRUGyCFUaFiGgtwyenoTved7Q/WNHkKrTdXVA8RUjNZgVDTEeXnwi9mkHZkQzKbo9GyrJCdZ2VcqOZLbuaMNZYkGUFi0omMUliXG4mzTo70ZGh7Rj76ocbOGP2CNKSY1AUhWe2aPns+z20NDWTkaAjPlLDiLxU/jovjol5wTXM8iYa9xwysm1nIY/e3Dmf2LJiK6xYgv7WZQHtwym+AT7XJfGrKTqsdqlNfHfnjoc/3I+vL4jxUOzX2wWIJElEDp/G3p++ZtiUfB7f8ia3jrnQYzdQgaCvIQR4H6SpxURMlBDf4aa43Eh2usj/Dif9tQDTE8OiYV8TXJIj8fRYeK1I4YdayBqazJXT4jixIA61izDoia6X/sQ3QHRrJukGs99tqVQShiQdhiQdYwvanze12vn50CEqqy1s2dVIi8mOJEkkJ2rJMByNlifqUKuDE0FWm52X/7ueL9fs5c0nLsBqtfPxt7v47ueD/PO+sxiSnQQ7vg9qm4Hy7/d/ZuqQWPaUmSivt1BWZ6G83orZJjOpSeHEZGBpR59xT4Lc7LbMwcpWTh2dwIF6/8Lb13sfCpvIcIjxnoiK+4v+qxPSsNns1Fc2cOnxOjYUvURSwviQj0MgCDVCgPdBCksqyM1K6+1hDDiKy4wMyc3s7WEMKCqqaklNOTZcZwpiJH6oUQCJghiJR0Y6BKhuXmcv/65GQf15WgeSE1xWaSYjNTi7P1ciI9TMHjm0w3Pu0fKqGgt2WUGvV5Fh0JNu0JNh0BHjwVnEbLGx/JudvLJsPUOyk3jziQv4cfMRlr6ymqhILX+/eyH5OUdFmJuTiivdab8+dVwOK1eW88TnJWTE60hP0JKbrEclwRd7rLy8qZHHRsKQ6PaLCvPSjlFxZduDbf+3nzSaN38wsq+iksSYGJITvH+vBCKGvTVa6moeeE+lEgW7TX/534Gk3pw+vZpla+zoIhx3L+vqEA4ogn6BEOB9kMLicqaMH+F/QUFIKa2o4oTJY3p7GAOKkvIqstOPjW6vkxPg7wfBriioXXzk3X2/u5v37Y4nAeargHJPSRVxuRIwtNMyTlxFbiDC1lu03JlbXm40s31vE00tNgCS4rUkJ2jYureQD1ZsYMQQA3+9dQGZqXH86dmvKTM28sLDSygY3PncCFRoBxOVPXf+OM6dP86juL9gmoGPNlTzuxWl3HF6NnMritpec+aHO8W3bt44apttXP/yfjLidbz+2+E02SNJS2lvCuPvffYlSgPteBoIgXas7Am8HWMgjaTcMTW2gqJwwVjH4/o6GDk8oXsDFAjCgBDgfZCq2gZSEuN7exgDCkVRsNntaDXiIxFOSsqNjDjhuN4eRkhI00uk6RW2N8D4MH183ZvI+MIZ9TSbQa+XPLpaeBKgwYpxVzzmlisK3/9SxOMvr2doTibnnDKXqEgdX69tZMPOrYwfkcl914whJalrUXp3QRkK946zj0tmZGYUt79ziJ8GJXDhtBSGpzuOyTXyXVZn4br/HGDu6AR+Pzcd1diT+GptNaNS9B7H5k6gjiCuQrW7big9FQ13J9BodzAFpwC1ZbUkZiS2edzX1yoiAi7oFwi10cew2exo1CrRiTHMNDQ2Ex8bXEGXoPs0NpuIi+n/BZhOTkiCNTUK4+M7fn7XvrsFZeJgjhsUg7ejDVQIBRrx9sTQ2CF8q9rf9jhYceqp2U2w/LKtiIee+YK/3rqA48flUPPT1/zlf8XsrzBzw/x8oocO48fNjdQ11oACsdEa0g060g160g06IvSeiz59zV2g0XD3ZkGuFGRE8ubvCnj5+wpuffswEjCzII64CDVatUSLReajLY1ccc7xXHLWpLb1jDUWDMl9u7g7FNHw7niWByK6874wUji/4x2R06dXs+27OqaOaP/utlohQi/a0Av6PkKA9zFKKqrI7OeeyP2RI2WV5GQcG6kQ/QW7Xe5QlNhf0d+6rK34bn6qxO+2KlyQpZCscxzbDzUKf9qrkHfkIHeZVVxxopHLZqaiHndSSPYfjID+pfAA8QneX/clQJ10R4Sv21zIPU99yd9uP53jOMC372/ikU+KmD82kYeW5BKhVSGN6Xj7oLHZRrnRzJHSVn7ZWk+rWUalchR9pqc4RHmtughVAEWfgVxw+Dq2OOCmyXCjorD7oJGfthbRarFistqRgJf+PJIhOR2bStnsClqNqsvi1ps49RQF7260vyvR8J4W3k48iW+AiPoqBo/MAhx3MmO1/n3hBYK+gBDgfQxHAx5RgBluikorRd59mKmoPnYKMJ0ifHCUxMI0hacOKvx5hEMQflSucP1giTPSHB0xb9pUw9C0CE5UOYSuq+Bzd6rw1wwnWLFVUw1JyR2Fqvt+uivCvY37h02F3Pv3L1l65xkMbd7NHz8rYcuRZv563iAmDWqPYLpvOzZaQ2y0hmGD2v2+7bJCda2j6PPbLUeor3MUgmq1kJAokZgEiUkQHUOnu4mhcOyQJImR+amMzPftmmSzK7TYm3slz7qrBCrCuyK8g00v8YZTfC/KM3FdYQO/Pt9hH5mt+zW7ozeEZB8CQU8jBHgfo7jcyPRJo3t7GAOO6jqRdx9uSsqNZB0jBZjQLsKvzJW4aKPCfbtlJsVLrKqGO4/WO6ZHSJw4Ip595a2cWOD7fPMmEJ0Cydvr3sTxnvoD1FQrDB/pP1IciAj3RFuhp8v4TGYr/3rzBz5btYcn7zqTphYz5z2zhxML4nnn9wVEeUkp8YVaJVGrKUKfAZMy2m0srVaFulqorYHSrQrNzY6oaGQkJCa1C3N9hOcc+K7gS6zW1ijE9eDXiqeixVAclz8R3vXulZ3J+8LY6Tn3aLcrruK7sclCc4uVVEMUBQlXcbCoDINoQS/oJwgB3odoKwTUirclnMiyjIQk8u7DTEl5FXOmT+ztYYQU/a3LYOkSXhgPa6phfb3CKSkQ4WJ1Ptig55eDTT02Bl8pFI0NEBfX+XlPoq0rItyT8Pv0u92sWLuPC88YzxMvf0+zycIDZ+cybWjXWoX7EoZarYQhFQypAO2fZ5NJobYaqqtg/14Fs1lBkuDn2H2MzEoj3aAjLVmHVhu4J30gUeLaGkdEPlD82Uz2BQIZX6A53f5e85Z24uRQYT2DcuMYmXQ1AMbqOgxJIpAi6B8IpdeHqKlrJCnBw6+joEeprK47ZlIh+hONzS3ExUb7X7Cfob91GSlLl3B2BixIg38dUjh1ncLIWIUz0yRGjYzg6RVllNSayUrs6PQRSHqJa5TZ13Ke1lGUzikZvuhqJNyVmCgdgzITKalo4MpfTeGkKUNQqaSg/by7k8YRGSkRmQ2Z2eAU5oqi0NQINTWVNBxKYs0vdViP1iUYknSkpTgKP5MTtexvPNil/dbVKgzO758X9l11R/Envn0J70BxFiLv3FXN0MEJbc8bq+sYPji729sXCMKBEOB9iMISkf/dGxwprSQ3U3TADCd2WUZ1DN9xcKajPHtYodgEn06V2NEEnypx/Ou1A5itCi+uquDB+y5pW8eTfR7472Do/pw34dTSohDZBcMZV0HcFTE+f1YB82cV+F+QnhHfXvclScTGQWwcQC1ZR5+32xUa6pspqYHtRQoN9Y4LF43GEc1OSHSkscTEdryYcY8ML8ozUV9H0Cko/qLgntxAwkl3ovTdEd/u0W+bTea7NUX8+6Fz256rb2wiPk64WQn6B0KA9yEKSyqYe4x4IvcnissqmXfilN4exoCisqqW1OT+eddh7R8X82mFwu1DJaJcnDfcW5Prb13G1usu4tZzMknLiyENmAPUt9gwWWVSps4JaH/Bik9vy9d6KMB0X687DiHBEmxDnXChVrfnirumsTjzy+tqYdcOR/QcFMosGtQxKjSxNtQxKiS9I51teWEkjc2tqNVKj43VNR/aSSjbwYfKI7yrwtvXxcYvG8sZnJnM0Nz2iLuicExf2AuOLQJPeBP0OI3NLceUJ3J/oamllZiovp13eaxRUl5FVnr/sttUFIVnbljMn/YqGC2O1BInunnjOjRkAbBsup8DlSZGZHQ8t+KjNKTH69BqOhYfhlI4eaKmGpKSfC+zp/5An3PsCGZeCuLze2wePyuN4gdTFDsjoijLjKaxwPEXNUKHJkGFvUXBdNBK02YzjZtaadpuRjbJfLBRR6up50S4K6E+9q6cC6Ho0umLRXkmrFY7b3+wm9MWZIN0MgBWmw2NJviCXoGgtxAR8D5Cq9mCXieaB4Qbs8WKXic+BuGmpMLISdP6dgGmoijsOXSISL0eWVF4+U/Xs6sJXp4goVPBr3dqeFGdxJyR8WQcbbHOT/ehGn0XEfseR5IkUmK0bDnS0qngsLuRZG8pAL46ItbWKIwYHVh00JPw6ukLBF/4ahTjaVyh7u7oK+VCpZVQJarRJqo7tIq3VNmwyAr2Jpll36pJ1zjOkagoSEiSSEyEhCRHV9K+Rl+7CHPnsxWHyM6M5fxZ97Q9V13bQHKiqKES9B+E8ugjHCmpEPnfvUBJuZGstGPHCq+/0NDU9+/2PHvTEj4uV5AASYJZSfDcOIlYjYRu3jj+eZyJZeurufv9QmqabShtQc5L0Wskbl2QxS0Lsvjrp8W8cMVQDLGOboi+xHd37d98CXOr1eES0lW8paiEojtmoPTGRUCgLdTdn0uxNDOhoAlduuNndk6ejKIotLRAXQ1UGWHfXgWL2XHiREc7hHlCIshWBdXR9+r06dUd9uGektGdNvTuhEp4u485lNQ3mPnk8wO8+benOzxfWV1HqrAgFPQjhADvIxSWVDC6QHTwCjdFZUYGZaf39jAGFM4CzL5s+2i12XinROHqXImz0iHCQ5fFoWmR3HFGZ8cFacxstu4p4+H/+5p0QywTxudzwfMHufE3M5k/czj6Tmu0E0rvZVc+OhhBgrqly+s78VQYGi7xHSyhiIL7mnN/AjNStrJmfxJz0hvatrUoz0R0tENsZ+WAqyNLc5Mjv7yyAgy1LRyuc6RTqCIkDJYmTCotJrUWu+TIHA1VqkdPdb50FeGF8w0hywNvbrGi0ahoifgfcHXb88bqOkYOze3SPgSC3kDkgPcRyqtqSBdWeGGntKKKzNSeidQIPGOsrsPQxwsw1SoVV+ZKfFutcPYvCnuagsvhHVeQwdtPXMj4ggy++/kg0yfk8dFXOzj1yhfZtLPE4zrehNDywshue0Pbm2QSkvruBY87zlz0nk6F6OrcBhLdjbBbaVV1jHF525ckScTESmTnSowdLzHzJBWxEyOImaAnIk/L+JHNxNrN5JlqGdZsZFZECc27zLQWWaksb4+id4VA7yp0Za5CmQ/unPPM9BjiYvU8/NcfeeW/f+OzVavYe/gwxpo60UxN0K8QEfA+gF2WAVCpxPVQuBGNj8JPcbmxzxdgqlQqLsiSuCBL4tsqhZu3Kzw3DnKjHCLWsmIrunnjfG5Dq1Vz9bnHc+qMYTz2wrfsOlDpcTlfwjtU2Btlkj3YI/trdd/TuPue+7JZDLbzZzA45zqU6RyAI3epW6tLqKMk1FEqJqZajz6rQlH0yK0KU6JaqSiHvbsVLBaFn7WlJMRqSUvRkZqsIzVFR1SE/8LEUHe+dMUZCQ9VFHx5YSQP3zeDbTuqKD/Uwu5Dn/LMW/UMyRzGyGGZjB8xostjFQjCiVAefYByYw0ZBhGFDTcNTS3ERvftPORjkZLyKk6aOr63h+ETV0eTk1MkGm1ww3aF58dDWpBFc4OyEnn+oSWYWq0cKqlh5JB2z3lPoqernQZ9RRttjTKJbqv4a3XfVQIVxN58z72NKRT79IczTcQXgUS/VYqM7EV8B7IPf0iShDpSIidXIicXnKksw+MyqG+0UVFl4UhpK+u3NWAy2wGIj9EcFeV60pJ1REd1duHp6vnoj1CIcHDM/enTq4nQa5gyKZ2Ckx3nhSzLPPXKfm569CH+cut8po6/tNtjFgh6GiHA+wCiALN3KCqtJEc04Ak79Y3NfboDplN8u0a4fwWY1lZy9Q9Gbp6fybwxCR7X9SUCIyO0jMpv/5x3VeR6E4CuDhzuyK0K0W5T7sv325friC+cjXpcG/Z4m5NA99FThZfehGUoBHKk3YpJpe3WNoLFOU8JcVoS4rQUDGl/wxVFoaHJTmW1mdKKVjbvbKDZZAcFYqM1GJIdnT9btI5mTd2pz3DOXSjv4DhxntvO98h5Djc22xk2KJHHj1/AHU98zoqXLkKrDe/8CwTBIgR4H+BIaQUTRw/r7WEMOIrKKpk0ZnhvD2NA0ecLMJVv2/5b3WTlpwON1LXYyUnWc2JBHMPSI3nqixLe+7mKO8/IZnh6u8gIVQTWF11xllCO2rN0Zc6DiYZ765Lp/rz7PAVrMehOV+a9q24yEJjDR5RspUWt7XIOdCDiNZiLBEmSiI/VEB+rYdigjsK8qcVOZbXF8VcVR2ldPaCg00NCgoTFakMdrUIV6f9z6zom946Z3YmC++r8uaf+AKXFCkokxOVKJCXr2LRrF8eP850iJhD0NkKA9wHMFisReuEBHm6MNXWkJIminXDiKMBMCOs+zUuXdHjcYlc40AzRahgUBRGnOdJhnELO+e81N7yBXm5hTFY0a/c2UFRjpqLByqjMKArSI7nmlf3857fDyU3WBy0CezLP2nmb3oncqqCKkFheGNFJtAXS/dJdhHuzIgwU57LehHioCEduvTci7VYa9LFA8JH0royvq3MnSRKx0RpiozXk5zrS8fbUNwJgNjs6f+7Yr2CtsiK3Hr2QU0uooyXU0SrUMSpUURKSyrMwD6UI90V9HSQcreuOi9XT1NJ9xx+BoKcRAryXqW9sJi6m796OP1aRZRkJSbQtDjPh7oDpFN8tdoXl5fBRmUKZ2SG8m21Qh4oxZQcYN2kk48yHGTs8nXLZ4VJy7QVTeeatddw8P5MIraNA2mpXeG1NJWv3NXDl7DQe/PAI/75iaJ/7InUV4fZGGU1s9wq8A2lRH4wIB+9CvKfWCyX+ouB62cacGXW4trLvDu4XVV0hkLQgaL/g0usl0tIhwtwxlUOxKdibZezNCuZSG3KLjKI46k03VMgkJErEJ0BCAmi64TvvxFv02zVVqL5OIW+whKIo7DtQy5jh4s6moO/T1343BhyFIv+7V+iNSKzA0QHzxOPDU4BpXrqEOqvCe6UK/61SM2VwLA/+2sDorCi0408CoLbBxLY9ZXy7bRfP/fcABw7Vk5CgZ3h+IsPyE4lP1PDrV0q4bPFxnJZUgVYt8ZsTDLy5zsiJBfF8WwhvH4rjkiDudvdUoZs37A0y2lR1234CSV0IVKyFAn8FlIGktgQzRveorLdlwH8qCnhOC0pPtiBJEV7X7UqhrbsId30v/d3JcJ/DYIpW3edL0kho4tVo3G4eKrJCfoKJulooLoIdWxXsdoXGllZUERLqGBXqaBXzj6viiw0pAUXBfaWeQPsctLRAZBSUljWj16tJTUoK6NgEgt5ECPBeprCknBMmj+3tYQw4jpSJAszeoK6hmfgwFGAefmQxb5UofFEJp0xI5tUlqQyaPQ84KoBdRHDacLhguMO6TJYVikoa2Xeglt17ajh4uI7cnDg+WLGNZ6oa+fVZk1hyymgWnqLhnX12Hrr+VC65811mHjeIwdn+f/S7K7670mHQ3iQTMSTwgjRPYs2JL9HWlSi4+z7ctx/o9rrrgtKdoktXUfzZumTUioyk6V7ktyuFtt7wdwHjad664oQjqSQSEqW2VBBn9P+jww7LRHuTjL1BxlJqY3izEQWwnajCpNbSqtKStKYBu1lqW8+f+HayvDCSWJqRJImvVx1h2pTMoMYtEPQWQoD3MrX1TSTGxfT2MAYcxWVGTpl5XG8PY0Ah91ABpmuOd3mrwnOFCmtr4Kx0eP/m0aTGaZHGzG4TFP4FbxQMTiNnMCRMaaJi7SYOHa7j+MkZbN5Vyksf/MKcafks/3onl5w1id9dOI37/7mSVx49F43ae6pHqCLfwYpwRaFDjq6vKLg/wetPjPsS4ZYVW9v+781DvasCvqcIJFruyunTq7HW2rHVdT3lx/neukeHPQnSUDi2+MrJd56zwc6DK07LRHWkCo4ewtAxjuPUyHYiZSsRsg3bNB162eYYkySR1VpPq0qDSa3FpNKgSJ7nVLEplJk1NDeb+W5NEY8/fGKXxikQhBvR+aUXsVhtaDXqvusIcQzT2GwSHuBhxlhTjyE5tEWvBxYspPgrR4OSTfUKl29WyIyAZVMkbr1mQgfxHWwnv0V5Jn49Sc2tf5jM7387gV17qtl9pIKCwQY+/W43+bnJ3PTYJ8yYkEeLycobH28K6bF1B2eEVLEpSOqO3y+eCjGdBBNFDlYs6+aNa/sLNaFqxBPo876wN8moY7r2ne7rwspVkHtarruFvZ7eT9e0lkCEfrDzZVOpadREYNTFcCQykX3RBvZFGzgQmUStNhIFSLSaGGKqYVZECY2bWts6gFpr7MhmBVuTnTFZdr5aVcjEcamcMGRMUGMQCHoLEQHvRYrLKsnOCOw2myB0WKw2dKL7ZdgpKTeSlRa68/3AgoUAZJ/iSK/45yGFW/IlTjVIbSLPNfLtxFW8eLuV7y42RhUk88j9M9l3oJb9B+swJA3jhl+fwOer97D4D69TMNhAanLfK6a2NcqoY9vFYCAiKphUklA1wAk1ru95oKIwVN0w7Y0yOkP3PKi95Ua7doR05oT7i4KH8v0MJhLubzlfd3IUSUWLWkeLut0drGBiNYqiILcqyM1H01nKbNgaZI7oFPbsi2D+zFHs2NeEIbmO5IQ41D7uSAkEvY1QIb1IYUkF+XlZvT2MAYdDCPbtVujHIiXlVcycEpp6B6f4dnKwWaHEBCcn41F8O8WAv8I28C7AVCqJgmFJFAxz5HrXUM7Uk+J5bdZ8RiV1zce/O7f2veF6PA4HFHXbvrzhXsTXnXzu7qzb1f250hXx7Up33w/ZrCAF2S0VAvd49yXCA7GVDJZg88F7oqbBeU67prNoj36F51Q2U91QiUZby7SJBow1FjZu30tNXcPRvgMqEuNjMCQnYEhKwJCcQHSk9wJZgSBcCAHei5RWVDHreNEsINwUlRnJFQWYYaeusYmEENU7FEtwWJJIHqvm5zKF14oUrh8sETW/3dM78JzvdroS/VSrVd0SPj0hwp3YG2V0aYF9zXdVhPdm3nZ3xHdXChoDHlcQaYVdaa7kKsJDjacoeKD54K6fn1Cd077en0V5Jr7bB+u3HuGieZPJyYggu/onSNqENPtBwNH8q66+CWNNHUdKK9m4fS/NplYAIvQ6UpMTSElyiHMRNReEEyHAewlZUbDLChq1ureHMuAorahi2sRRvT2MAYXTdz0U9Q6llZXcrVUxToaYKgWNCm7Nl5iV7Ni2r1vowRQwugvqnmyeE6gID1asyRYFlZdorOvxeTu2cEezg8GX+O4tZIuCKkDva2/vZSgb1EDXLpC6korifvEa6Dnt6zPpT3wDyDJkJCTy6ofrMdY0cUqyldQ4Lcq2B5HGPohapSI5MY7kxDhG5Od22Iap1Yyxph5jTR2bduylpq4Ru11GkiQS4mIwJMWTkpyAISmemKhIUa8lCClCgPcSVdV1pAof6l5B5ICHn6qa+pB1Hd17+DCDFbjdJpM9sj3X1rW4z5cY8+bf7CogPEWzfbVMdz7fndv//gRLoOLbmZbgbEHv3LYr7uMMNs3AsmJrjxRThopgoq+haHLjxN4ooz7a9MjT++XvAjDU4juUuJ8jgdwtCsRPPVhc9yvLCnG6GB6+/lR+3HqElZ+u4d976rlhXiZnT0qCoyLcG5ERenIzUzvdEZVlmbqGJow19ZRWVLF11wGamh371Wo1pCTGt4nzlMR48Xsi6BLirOklCksqyBUNeMJOY3MLsdE934pa0JGSitB1wJwydiz3SbBRBdl+lg2kkQr4F9/hwpdgCdZ+UG5RUEep/Ipvf897ozdFeHfzvoO5mHHFn1Dfui0Sk1pLQ6nnHGP37XVVcAeaftKduxehLLD1d3Hp6dz2NNfu53JzEyTGadBq1cw6bjAz9Uc4WNnKne8e5ucDjTx8Th66Tlvxj0qlIikhjqSEOAqG5HR4zWKxYqytp6q6jp37DlNdW4/F6rBPjI2OIiUpHkOiQ5wrstyFvQsGCkKA9xKFJRUsOGlqbw9jwFFUWklOhsj/DjfF5caQNZwqX3Ied0jwF62KhYrS4bZwsIIhlMLb3/quEXR/6S3ecmmDidTaG2WmDrHh2g492GP0JuB6M/od7HvsnusdiPj21wjHG4PlGqq1gdmbhkJ8O4+pu84t4SCY7qLe1nWlID6f3VXNyEm2Ds8PSY3g9WuHc9vbh/jHl6XcPqHrY/aETqclKy2lUyG/oig0NZvaxPmBI6XsO1wY2p0LjimEAO8lWlpbiY4Sldjhpqiskgkjh/b2MAYcdQ2haTjldD9Zr5IYFu85pzzQ4kvnj3owojQUeca+0ls87cOXuPJVDLehQibpaF58Vy4uuhI9dTbb6U2B7i3a2pU842DRyHZsKv91PaEU3z1FuO0lgxXfAMYaCzkZnX9HI7QqHj03j4uf3cu4NWs4bebM0A7WA5IkERsTRWxMFENyMgDYfySTV5a/3eP7FvRPhADvBZpbWomKEOK7N6isrsMgcu/Dinw0F7m7BUxO8f2jCn5US7w1umvb8yS8vYnNrooQT9vz1mbdk+OEE3+C35c4V1pimJybjloV/DwFK75du1w6H/sT4c7j7m6Rp785CjZ1p8u45Nx7ozs53t7Edzij355qBXxd3Hl6b4Jx/fElvsEhwCeNjmt77Fo0HBep4W8XDOL3L7zACZMmERMlGq8J+hZCgPcChaUV5In877DjFIIqlbCZCidVNfUYkhK6tQ1X3+9vVSoqJYm7dyncNASGRjsEpmXFVnRAwVELQvcfek/pJoG0XvcnwgMR8p62620d1/0FErn2Joh+VkrDIr6DxX0+XR/3VceVQNAqdqweot+hEt1OPKWdeDpPwjGXgaRddVeE+6LZZCc6yvsdh5HzFjBtxybe/+ILLl+ypNv7EwhCiRDgvcCRkgomje5a4w5B1wmFEBQET0m5kcxuNj7K//yTtv+/CLSYTCz/40Vct1VhUYbCFTkSEWqpgwgHWJTX+cffk/h2jeD6ity6C4quiG9/BBI9dx+TOy0mO5EtlSjb9wW1ra4eQ6ApJ/4uZvxFxQO5IxGssOuqD7cTp0iOslsxqbSdXg+EQIoqPUW9vQng7p6LgcxzoGlNXRXhXY3su4/9iiVL+N1DD3HhGWcQodd3aZsCQU8gBHgvUFldR4pIgwg7ogCzdyipqGL6pNEh3WZUZCQXPvEhJz62mCcPKFy8UeHOoXB8YrsIl8bM9itQ3FMnXJ9zikr3KLhTUAQaRQ8FgQpS53Kl1Toy4jy3Q/eW+tLTBLO/UI8tFGkovtrDA0Rn2LA0SUQ0tga1XV/i21eX1nCef64Ea1npa52uRMKdn70Wk51Ivf98+2GDBpGfm8vajRuZO316UPsS9A52u511mzfz+fff88Xq1Tx6yy2d8vj3Fxby5Kuvsn3fPlKTkjjjpJO4bPFiJEmi2WTihAsv7LTdK845hxsuuSRch+EXIcDDjM1uR61SoRKG/mGnqKySOTMm9fYwBhy19Y0kxcf2yLaz7v6QR5cuYU2NwqP7FMbHK9w0WCLxqAgH7yLVk/h2xTWP2ZMId92W6zpO3KPCvtJZ/I3FW4TZm/gqa9CSunc3lr21AY+nJ4Wct+P2djehJ+iqCA80mq2JlGkxer7o8Ya7+A60ELEnxXcoo9/u63gT4RD8nQtjjYXU5ABMBpVvGTd8OHsOHxYCvJ9Q29DAo88/j91ux+7BynHXgQNcdd99HD9uHA9efz0llZW8/MEHzJo8maG5uTQ0NQHwwHXXMSi73aw2LTkMtSBBIAR4mCmrqCYzrW+dBAOFhqYW4mJEIU44CVUBpi/0ty5j5tIlTDoO/l2ocOFGhbuGwklHBbQnkeJP8HrCm2D1ti1vhYi+RLs3gnUXKdndyFhVY0DLOuntrpdOcdYdIe5PxHkSuKFqjCNpFBRb4Oe5P/HtrwCxP+fLB4LzvfQ0D3vqD7CvRCE/KT2gbRmSqth7uCuO4ILeICUxkc9eeIHSykpO/+1vO73+3DvvMHb4cJbeeWdbTdc5p55KVKTjnKlvdHz3TZ8wgXRDYJ75vYEQ4GHmcEm5KMDsBaxWG1qN/9uVgtBSXVtPSmJoOmD6Qn/rMli6hBuHSMxNUbhlh8LIWEgLsS1ed9M3uiK+3ZcP5FjMaIiUbH6XcyfcItxTVLQ7HUW7ktLgLTIeXB63fwcUJ74KK8F/11LwXr/gSlfO+e6m/vj7fHQlfcVbIXV9nUJjejl76v373CfFR1Jdtyeo/Qr6JiUVFXy/fj3/uOeeDoYKTvENtEXAkxISwj28oBACPMwUlxmZOmFUbw9jwFFaUdXtQkBB8JSUV5GVHp4IhP7WZZiXLkGncm094yDU/tRdSWPxR/FX1g6Ps0/xnM7gb5umL7ehwv8+vYmkviLCna/5wpeYC7SIb3lhZFBNejyh1inYzZ2j310troTOxx7snZxAC4udhDLvPpRdNF1xFeNxDc3EumW2eTofCuLzGZSVxO6DlSjyN0iqOSEflyB8bNu7F0VRmDTae11RQ1MTGo2G3z34INv27sWQlMT5Cxbw67PO6lMuaEKAhxFFUbDabOi0YtrDzZGySnIyRQFmuCkpr2LapPBdcOpvXcZn153N0GjwlB7qLljcRS90FL7uy7sKma6ksfgaizvFX1m9inBf26wihhSafS4XiBtJb4tw6F40PFBco+au0XCnePYWCXcV1wlWE42KnahCU6fXfNFT4jsYQiWUAz1fQlWQWdKs5pOiiIAutPJzktDrNKzecJgTpwS8iwFF+iwNafrw1aap1nXO7Q4EY00NETod1bW13PG3v7Fx506y0tK47qKLmDNtGgBpKSkMHzSIRXPn8tvzzmPF2rU8+eqrqNVqLl640M8ewodQgmGktqGJxB4qRhP4pqS8iuPHj+ztYQw4auobeqwA0xs3PvkuN117PldvVhheZ2eIAkNkhTQg96ig9SS8nThf8yR+PYkef0I5mCi4t/0Gsk3n2MqVONKljvnfrssGKri6KsK7up5TdHanMLOr3tLuIhzoJMR9ESlbaVTrMc4PvNtrIOLb2zz2NfHtiWCj4MG8d4qs4Cwr8ZUr7kSSJO69dg53/XU5Lz8+n7zMzID3JehbWKxWJJWKO554gnPnz+c3Z5/Nf7/8kjv+9jfe/fvfyc/JYezw4bz1xBNt60wdP57yqire+PhjIcAHKoXF5eRlBVY0IggtFqsNvS64aKKge4SjANMTEXo9/3zhfVY/eB6/1MEalcRrGokWYPAqO0NkhZMlyDuatmsCtqugBQmDohABrFJJHFxl50y7zFSXQM1OCZZqVaRES9xVayfx6PO+RHugdCXa7YlyJZYpqiNtj72Jb2+3610Jtwj3NAZvdMUKz9c23COwrgLZX2pKlN1Kpa5/ie++jq85P22sEVVUx1SC5YWRPkX4ZA7wuznp3Pzoo7z95JPodaIosz9iSEpCURSeuvtuMlMdd7WPGzWK0666im9+/JH8nByP602fMIEfNm3CZDYT2Uf84IUADyOFJRXMmT6xt4cx4GhqNhETFdHbwxhw1NQ2kJwQ53/BHkCr1TLnkQ/JW7AQZ4FcPXBIgj0qiftkicXrTCQ3ynw4PRKbCmJNMo1RKtQJKo6TFabJCu+rVUw9aoO1VYKntCqusin8qxk8xeu8CXHXHPRABZS3CLc/6ogkAVOn9Z3i25dw9RR97g0R7otghbcv3NMhvFniebMHdNK4qZWCiQ7LR39iPZA28j2ZchJOvEXB3efdfb79zeHPG6OZlN/Q6Xl3Ee5+0bVkcjJryvW8/emnXLZ4cUDHIOhbZBgMmC0W4l0KALRaLZmpqVTV1npdz2K1otdq0Wv7TiBOCPAw0tDUQlxsdG8PY8BRVCYa8PQGJeXGsBVgesO1gyaA0wV+0urVPPHyy0wbP57EsjJefvRRNGo1r6jmti1rWxBN5tEofjPwpFbF7VaZZgkKFIkjEuiAQR4MMIq/shJ9ooZ1tdAqw8I00KqkLotv1+c8baPNr1wBaWM8EccFL7594a9Dpfty/p7rCsGMvatdFCH4NBZFaT8ButPsx1/kP5iLt0AIdfqJpwuunkpxiZRt/HgwkdlZTT6Xc68hkCSJayfX84e3HakIWo2QQP2NCSNGkJKYyOfff8+vTjsNcHRGLiwt5cyTTgJg+ddfc+ZJJ6FWO5zPFEXh6x9/ZGR+vijCHIi0mi0iBaKXKCqtZNzIni3kEnSmpKKK4yf0zbz7+bNmkZaczDuffcYjN92E5ugX9eXy120ivOKnVopnRLLqy2Y2DNWRGaditEHFc2qJXRL8WasiUYEnrTLuBpc7JHhqo8L4ODDZ4aNyeHUCQTfg2nKkmUPGVs4+rl3Y+conbzSriNW358x4SzkJJG/WE76EeE+K70DwJ5x7oqDzs3XJ6O1W0ixNHFmX6H8FF3xFar3h6yKsL9HT73uE3UqFLobP1iV3ujvhLxVl8LZ9pNlkft66lRMmicZsfZHC0lJq6uvbItqHiovZtGsXSfHx5GVmcs355/PEyy/TYjIxKDubdz79FL1Ox+mzZ1NdV8e/3niD5V9/zWkzZ5KWksKHK1ey+8ABXnnssV4+so4IAR4misoqyRUuHL1CZXUdqckJvT2MAUd1Xe+loATCxFGjmDiqs0OLU4Rn1NipMykcMajZPETL2etMfL9RRpWtYZhBwy2pKv6mVbFRBVNc8sTXqeAFjYqbmu2cMU2LoihcsEFhRyOMDWA6dPPGUd1k5ZXVlbz5g8OBY+7oBGIj/PvYlzVoyYhzpMF4Et/uItWbWPEnCEPlF90T2/clvrrb7MdThDtKttKi7npwxdNY/KXvBCPEQ2W9GQjhuuBSKzJ2qeuRzJNTJL7598Oc8OxHoRuUIGS89MEHfPzNN22Pn3vnHZ575x3OmjOHh2+4gV+ddhpajYa3/vc/SioqGDt8OC/++c/ExTjqMN5+8kle+uADPvzqK4rKyigYPJiXHn2UcQUFvXVIHhECPEwUFlcwclhebw9jwCErCgpKn7rtNBBw3pYPdwFmqHCK8Jk7zXw8NZKhZTZSGh0qe0SxjRHFNrYD1uMj2X7ESku5jZz5UaxVSXyvlrjfKjNYaXdIsSkK+qOnYFmrwotHFA61gFoCNaBRHf2/BHWbN1NoVTF3VALPXprP3e8fRh3gNJZHDSd/ZBRShqPmwVeerevz3UnZ6Ancc4cDST8J5hi8ba8rLiqRdiv12sDWc0ZrQzXfvmwxuyq8vc1NT9tBuuKtORLgyLPqJiNi4PtqMC9d4mjiJehTPHzDDTx8ww0+l1k0dy6L5s71+FpKYiJ3Xn11TwwtpAgBHibKjTWcPEMUYIabcHViFHSkr0e/A8Epws/82URmjR2AE0+Lanu9CXhfq6K4ReaHKRFEKDBRVnjj3//GdOmVbcs99a2NiDgV6Xr45yGZj8vhVxlwdrqEXaHTX6QaxsUpaFV13PW/Gq45OYsove/ot1Oslv+vnBnHJQCBie/ewl9Oub9Iqr/j6arA9edF7ckZJVK2Uq4KvdWm+xz4u2sQqkh3b3iye5p399QS53xrFRmbSu23MNYXOZFQfPQUqX98MdtP+SNTx49vS0UTCMKBEOBhQJZlFBTUIgobdopKRQFmb1BaXkXWMdB59HL5aw4saPeNLQc+V0tUS7BDJdEgSVgGa7ndKjNccSn6/PwTDixYyE4JPlBLnNAoc846iZPSJd6aJGHw0PCixa4gAZFHw91Gs8KGevhjTSngvZjVVahZrTI6rSpsBYvdxZMQD0UaQ3cEujcnFHecArBxk5kDrd6/292FYldyv6HjvPR0kyRPnuw9TaAXP9YaO/YGGeh62o+s0HZX6cmDCmseexhdgoGLFi7kV6ed1mds6gTHNkKAh4GKqlrSUpJ6exgDkqKySk6aJu48hJuSiiqmjBvR28MICfmff8K+BQt5Ty3xhVpinl1hqAIbgCl2hettMjF0dlzJ//wTfjljITkKGBT4k1Um+wgYhnsWDq8WKXxbBf83Fgx6ieXlcEoKRGskj4133IWq1Sqj1XQW38FGv3sqyuk+rg7uFGEs1oSOc+JNjAfSmdHZEKY70diuEK5Opd6i4T2F63vhbe7tzTKqaO85WYFcULbKEKGGLysVNtbD+5MlDpuqePHDl1n74cssHS0RfduHwR+AQBAEQoCHgcKSCgZlpfX2MAYk9Y0txAvrx7BTXdtAUmL/TkFxsn3BQv6uUdEiwVMWmcMS/Eur4veXXcalZ5/tM8/9gk8/4QKXx+alS7wuW2ICvQoe3afwt1GwvFxh6WjP2/YkWH86fBB1LED7OsFEgkMlvAMVbN1JaQi2bbkTb64Zzm0Gi9yidGoI44tQ3m0IpwjvDbzdibA3yWhTuucopleBRYZ/HFS4v0AiWiMxOhb+Nhpu3q7w9EGFu7u1B4HAP0KAh4EjpRVMGDW0t4cx4LDabGg1Iqcv3CjOwtd+WoDpyoYFC3lIq6JAUfitVeFdjcQGlcSTjz7KpNGjg96e/tZlXkV4hRluHCzxfKHC5ZsV0vQwPEbyG/l2Ct7aakg8WrcWiDgNVnz765wZzkhpd3DmEgdrX+cJe5OMOqbrqYX+XFl6qiAy3HccuoP7xZbcqqCK6Pzd4svNx/1CJU4DDTY4PxPeL1WYmuAoGNdIEo+MgKu2KPx3xQrOmTcvtAcjELggBHgYaDVbidCLtrfhpqyimozUrjfGEHSNmvpGkuL7f/T7wIKF/KySaJCgTpG4SScxx67w0ZtvttlddQVPIlxRFMrNjuKwf42V+LoKhp40FF1Ox7s3vpxBqqsVylWRbCz0Lwg9iW+nSPEkzrwJwXCJbk+pEF2NgjvxJMSDFeG2Rhlduv+fUX/b7C8XL6EkmPQW1/n7Zo/MnEGtXd6vbt44or7cgtkOl+VIXL1F4ZMKOCvd8XqcVuKJUXDla69x6owZ3fqsCwS+EAK8h2lsaiE2um85EAwUisqMogCzFygpryIrvf8XYAKMVhTOskOCAn+wKYxzy/PuKq4i/FCLwl/3KWREQIoeNJLE4ksCi3q7cqBKTUx21+46eEtl6OvCsLsiHDoLcVcR7k04O5f5bp/MrJE21IH6RHYR9zSZnnAk8dY2vi9hsykEalTia35UkkS0RsFkhwcLJH6/VWFyAmQejaznRknMimri3c8/5+pzzw3ByAWCzggB3sMUllSQJ/K/e4XiciOTxw7v7WEMOErKjUwe27caHnSF/M8/IR84sYe2r1z/Ns/fdj4flsFVeRJLMkAtdUw5CTQa/dHhCMCMJEmd/JMDKRB05hMH673dXYIRkt6cOVxFeKAOJp5wzQ/3Fwl3vma30+Pi23V/Trorvr1dcPV1Ed5QD3EBuMq6z497vrxu3jjGlh/g7wcbuXe4xCU5Eg/vUfi/cRBx2ngALhtv4tpX3+U3ixah14k72ILQI3zxepjDJeXkZaX39jAGJGaLBb1I/Qk7VbX1JCcJ73Vf/LJtG+feeCO7D8u8MUni3Eypk/j2hCdRvLwwEtmkoI7smhB0brOnxffywsiQ+JEXxOd3EliL8kwdRGooih39jdVuDzwaGypcj90pKC0rtoa0NX04CjshuHPMedzRljRGZqa3Pfb25wn3C4u/XTAYS0o8N5VEccY5IyExmvdjMtpeH5oWSbReTcma+7t2gAKBH4QA72Fq6hpJSgh9kwaBb5pNrURFRvT2MAYczg6Yx0IBZk9yz1NPceNvfsNtNqXNEzzQYktXnCLR3iijjlV57x7oB+e299QfCLn47orwVrav8isEQ5GCkfeFkbwvjG2P3efP17jr6yA+oXv7D3Ru3IWlp7lxCvGuinHX9cIlwn3hSVAbaywYkroeVHH9TEXqVDx+wSAmDYrhgv/bw7C0SF74rpwDFe0Xb/GRahpMdpRtD3Z5nwKBN4QA70GsVhsatarftuPuzxSLBjy9Qm19I4lx4oLTF1arldqGBnL/9JjXZQJJA3AVbk4B3h36Ur53oGkQvkR4qCz/vAnk2hpISOzed7t75N4VbxFdV3Ecysh3OPF3rnl7X6tqrKQkdc+CUBozu+38Uqskfj83g1evHkZxjZmmVplH/1fctmxcpJoGk61b+xMIvCEEeA9SUlFFdrr3DnaCnuNIWSU5GWLuw82xVIDZU1TW1JBgtRJM9oK/5jr2JpmV2zuf797yv8PZmr6rQjgYEd7VaHjhfAOF89vnLZiGOnW1Cok91F/N0/G43xXwJb6DFebO5fu6oLfaFHTa0MgWVyGelxLB3y8eTHKMho2Hm6lssAIQH6mhwWQPyf4EAneEAO9BDheXk5ct8r97g8qqWtIMovtouCmpqCJLXHR6Zd3mzfzu6t8yVla8LuMr9cRbykJ5lQ7F5U7b6dOrw96d0Re+XEVCFXn3FDHuySh4Qz3E9YDbpqeIt3tKSDiEciBpQF2hq9FvZ3pbqHEKca1GxaUzHXdNv99TD0BspJp6IcAFPYRwQelBSiuqmDl5bG8PY8ChKAqyoqBWhe768sCChUDnduOCjlTV1JMiCjA7cGDBQool+I9aRakKLrHLTJUDW9ddfLvz2bpk1IrMIKm27blQCe9AfZoDbcbTHTEcrO1esC3UA5kzd2cUWQZViB1QfKWbOAl3lNqXP3ywdOdiq6HJRlysxuOcBDI2f02PAJZMTubJL0p59utyfjUlhRaLHb1GpJAKegYhwHsIRVGw2WU0ohNj2KmuawhpIxinX3P2KVrMS5egv3VZyLZ9LHEsdcAMFbUNDfxbI/GDSmKxXeEOi4JrBmv2KY5HzgJMb0LCXXy7FgtG2S00qx3bCVR8+8o7DpZQRLB9CWzXAtGujM/VptA5P966YfrDKcJtVgVNCH89vaWceEI3b1xIRbj7tpyP3YuCg42Gh9rOsLLaiiFJG/R2Az0/pTGzid6+ij8uymFXaQsA24tbuHi6AWnsg8EOVyDwixDgPURVbT0pif2/G2B/pLjMSE5maAowXcW363NChHemtqGJhDjRNc6Va+6/n1TgHxaZYL8NPAkHTy4nUXYrLWrPzhCB+GKHuqFLVwl1cxnXKLh7w57u3CVYXhjJCVEt3S7A9HWs3U398Gdn6cRfHnmg2/FEVyLnvubEWGMhLbnnbWWXTE4GkmlstVNebyV/zqM9vk/BwEQI8B6isLhC5H/3EkdKKznx+K79cBwsKqK6ro5mk4naDx6j2Q7NNhgRC1MTQDrq1axse1BERdwoKTeKomM3Tps5k18OHCKWzvmr7tFvbziFozeLwSi7hWptVCdR6e6L7d6sJhCxG2wqR0/TnVQUb10z/aXGeFrnm31aJI3EeKw+990VAhHf3qLgwQjmQKLo3pYJZj+hau5jrLYwZnhwF/jBnLvu876rtIWC/AK0obzVIRC4IM6sHqKwpILTTpzS28MYcKy+bzE7zBM44+SpAS3vzO0G2CbBE1oVQ+MlYjQQo4ZoDUSr4enKCCLrVDy0OJchR5cXIrwjJeVVTBo9rLeH0aeY/tJ/+ESrYqlGxQK7zFAF9HS8o+IkGJGS94Wxzb1Dq8jYVO2pbt4EZVdzsIMR4e4iP1jcBXYoxL+7CA8WT8Ld3qSgz1Z3+3jdCSby7S7CuxOtDhZ3YR6OfTc224mNDjyl0/3cCfaOwyrjSCaOFI3cBD2HcEHpIZpNrcREh8/qSwDf3ruYP++DI2qFT779NqB1XIsqdw9Sc8kgFc+PV7F0tIqHRqi4Y6iK6wareO+6AhZNSuKaV/ez36VRg2jQ0I4owOzIgQUL0QOPWWVyFIXXNSou16l4yKCm0ebf0cEpGDyJuzbrPEVBoT2lwlPLck/Cw72pi6c/b8sHQndsDn2J7q5Glbub2uI+r/YWGVWU7xSUcNw50M0b1/bnD/cLvFCKZl/R9FDlgisoAffUCER8ezvXAYprzHy6ahUXL1zY6TWBIFQIAd4DtJhaiYwQV87hwtTaymd3Lebx/QrXDo9nsLqRg0VFAa+f//knZJ+iRSWBN4tZlUriV1NSuHV+Fte+eoA9ZS1trwkR7lKAGULnmd6gxWTi9scfp6aurlvbcd5ZyT5FS/QsDZnD1cweJLEoS2JnI2i7kD7sKW85QrbRqu4cTXcX3t7+7yvi6i5Ogm393V0R3lUB6+2YQi3CAxGD3UmB6G/4S2kJZC68LWM2y+i76P8diK2jO/9cWcbFZ55JSmJil/YpEASCSEHpAY6UVpKXmdbbwzjmcBZEApjsCmtr4OsqhZ9qYXQs/GGwRExcAvsq6tBv+hguvzzgbetvXYbuD2fTYleAjj+srg4VC8aAdvA+fv/8t9x8ioEF4xJRq6ROItz9x+hYL9qsa2giIbZ/F2Caly7hO6PCyt0KyYd/4OZ8VUDvm2sakytN0zTcv1tmXS2cnAIpOkjRSTwwHCLUUlARSGcahKuLx+nTqzGXObv0aTzmdrsWwgXSytzTmAIppnOmebina7hb94ULb3nH3U1vWZRn4qMDEUghth/saZxzIY2Z3eG97wlHFddzKFTRb2OthZQgWtB79RL3I7wtK7ayolJh0yGFh+5bFNQYBYJgEQK8BygsKWfCyKG9PYxjls8qFP55SGFYNMw1SNw5FBKOhhQ/tMeTKZWwtlGh9YnFRNz2YUDbNC9dwoQ4iRcKFa7O873sKdOHkZIYzd+f/YwXvi3n5JHxnDA8jom50Wg1jiiN+w/bse6ccqx0wPyuWmFuCuxpcjx2fd8sVitbdu+moakJWVGQZRnLJ0tRxmmQAUUBGbDIsNKoULxD4fwsiXuvHk1sZNe+aj3lL7sKcXuDzIIpNhISrT49pF1FtK9uir5yikNVTBcu/F04OOc2WFFub5JRx4ZWgPdk9NvfexZqEe6NQGsJPBXaVtVYSO2mA4q/ZkayovDSEYX/VcDS0RKRERHd2p9A4A8hwHuAyuo6DCni1lVPsKFO4f8OKzw1RmJETOcfQTNqFqfa+KwMni9U+MPWB1CNe8jnNp2R9SmJ8Jf98Ke9MhdnSQyJ7rx955f4eODlq4ayo6SFNXsb+OfKMg5XtTJlcCwnDIvlhOFxpA8gEV5SYWTCqP5dgCkrCj/Wwt/HSNy03dHMyarAx7cvZnX8cWzYsYPB2dmkJiejkiSUfeuQAJXkyOWTJNoen50uMf/CcWgDjJQGEl124hpR/maPTFy85FV8uwtqT897w1OhXVes5XorCu7E14WD+7w5H/sSivYmGXVM30618vX+uF+EhZru2hdC5/nfVSozZ0Jul7fnS3xXWRS+q4KP9zm6Y708XUXm3YEFbgSC7iAEeIix22VUkiSakfQAFlnhz/sU7hrWWXzr5o3DZJWI2hVH7Ljx/P0EKze9eZCS9wq5vOwOLHlXsHbjRq694IIOecquaS0aSeK1ifDfMrhum8LIWIVfZ0lMVRzFP+5f4pIkMSY7mjHZ0Vw7J4OaZhvr9jWwdl8j//qqjJQYLScMT+GEYbFMOBodP1adU4zV9Rj6eQFmoQliNVAQDXYFrt6iUG6GYdGwcIKRh294noSjvceVbQ9iWaEKSSFbIGLW2y31nzWljEzMbHscaHS7K7gKq/4YDe+KH7UnIZ4nWSiJ6VsF9sG+Fz2diuKNrtpaNtRDtaqIuvr27/1gcvoVRaG0zsKRajOH1hyipFVh3xGFMglqJThOVlgkK0ySIfPu5UGPTyDoCl0W4Ou3b0ev0zFm2LCAK5MHAmWV1WSkevbrFXQd89Il/K8C8iJhZpLnHO2iOh058RYADLFaXrpyGC9/X8Ht7xxGku7HZJU5IWETI3Z1/gFotStEqCXitRJX5MKpBrh9p8LvtikMrdjDq78dRrTetwVWUrSGMyYkccaEJOyywo6SFtbubeAfK8oorG7l+MGOyPgJ9feQFu/9dmp/E+jHQgGmeekStjXA2FjQqCROTFYoa3VEw0cvHu9YqPDJDm7e4RLf3mhqsREd6Tgn+3sBX3+iuQkW/z975x0mV1X+8c+duruzs733ZLOpm94LhEAIBAi9SBNFKYqAAqKi0pSmIvxEERQFUSlKESlBCCWhQyC9191s72W2TLvn98dkdmdnp9w7ZWeTzOd58iSZuffcc8vc8z3vecvC/lEx7oXz/ETbEu6PUES4LIPWazXJsw1/Yry+uYvXnl/NG5vb6e53MjY7gYJeQVGixDLZSa6AQsFAdVrPrFhx4kSbkAS40+nk3scfp7WjA6fTSVZ6OlecfTZnnXQSGo0GIZSnCzraOFjbQGlhvABPJLE+eC7tNsFThwS/nOj/uTrUoWdSTv/A/xP0Gr57Uj7fPSkfgCfXNfLI2/XMH5vDvi0N3DVBw/4eweNVgg/aYG6a4LtlEhOSJR47KChKgMoJ6by6oZ0lv9zC53dMG/DxDoZu2glMnwbTV8J3gbaOXj7eWMWHXx3kd3/YRbZZz8IKMxkmHXsb+9le14tGkvjGcTmcwZFlJe/s7iH1CA7AdK+CfNYumJ3mer7unDDoyx+MWFmC65ts5OcYR6xkeahEyv1EqcXTl7CM9D1SM75FusJnpIiW+PYMWveHGhEuywK1csLplPn7n1/kqQ8aObkyjdvPLmF6cVJQd8Q4cUaSkAT4tr17yc7I4KVHHsFmt7N+61aAAQuYEIJHn3mG4+bMYdqECQB8tmkTGo2G6RMnYtAPT5t1tFBT38y8aRNj3Y2jhl9852x2W6DbAStzYFqK/zdxY7eeE8otfr+/fHEO3f1Ovqrq4ZMmWJQueHi/4PIiidsq4O1muHG3lrvOLSHR0o6jz8ltq4r54cpCXq5NQ5K6Qz6PjLQkzjhhEmecMAmnU2brnkY+W7OOVouDWWXJXL44h16bk1uePUhFbiITjiARfiQHYDbdfw6ftcPeXsEXHfBjDzd2b/E92lwu6pusFPfvhAz/20RLhPvLMOLOhBJp1ArYSN0rb6Fo7RcYjOrbcbcRaSEeqiuQL/EdiWdFzaqQUhHeY4FkFfP76nVv8dMXqjDqNPzj2vEUprtu2JHyPo1z7BCSAP94wwYsvb00t7WRnZHBopkzB75r6+jg2ddf54kXXkCSJKZNmMCX27bx6nvvIYTgq+3bueaiiyJ2AqMJIQQ2ux2D4eidYIwk1gfPZZxJ4osOwbWlEif60HgDPqkCZAEaSfDlwR5mlw1/Y+u0EjesKODfn7fwyd5u7tkH915QxomT0wC4BKg81MON/9jPQ5eM4fnPWrj51U7+8POzuGKuS/grsRoFGxC1Wg3TJ+YzfeJFw9r87kl53P1KNY9/YxzJfvKLBxokB6xPIzjY1DY0M33S6LPwge8UgUXL9dT2CZ6rE6xughkpMNYEf5ouYda57rPaVGpqltQjJcIa9lQzd7L/Uuhu3OcykuJKKZ4pC/0J99FkPW5vh/T00Fd3lVZndN+raFzzQO+wSE3YIjlZ7eiA1DRl13z/e//j2qf2cfnibC5ZkI1jzRZYMS0uvuOMSkJy2tRqNGSnp3PjPffwtZtuYuf+/YDLNeUvL77Il9u2sWLxYiaMGQPAzv37WTZ/PtdfdhnVdXUAvPfZZzz+/PPIshyhU4k9nd09pKUcuUvxowm3W8BpOZCggXdbXBkqLH4qCLb3aUlLdPL5fgvf/ste3t7a4XO79Qe6eezdBipyE/jeyfkD4tvNtGITd5xdwq0v1vOda86kqdXCZ5sHi/pEwwoqVS4daPec2ZlMLTJx2sO7+fk7Vj5zjsEp+6+aWN0ruHGrzHlfyDxfK5APbzuSxYGa2zrIzkwbseMpxVt8Fy3X0zlfx207ZL6xUZCggWdmSfxmiobvlmkoSxoqvj3viz+UFIx5pSpx4I97n0hgNWWToA9cUdOz/8GqJnp+7+tPMNSel3ehnnAK90QL73PqaIe0ACsOkUKN8I60K0mooj+U/ZRMrjo7YLM1+LLDvkOtXP3kXq5bns+FlgaX+Cb8iWecONEiJAv4WcuXc+V556HVavnBfffx4ltv8dNrr+WXjz2GOSmJM5YtY+f+/WRnuN5UZpOJZ157jfycHOZUVgIul5TnV6/mxPnzqSgrA1yBnT29vSydNy8yZzfCHKyJ+39HAs/MJAlaiT9Nh3/WwNM1gu3dsCpXcMu4oXPHQx16StJsPPV+C2fPzuD+12qYUWoi2zy4GlHVauXH/6riqhNy+fP7jZzZWY/trYZhA8eyC86kLXUrl976HEmJBjbtrGfBdGUpsMINitICP5kGV7X38OaHu/m/pz+ipaOHlcdN4LTCHibkJ2JYMY3eNzfxRhM8elBwRbHEtFJ4uDWRz/95gF+cV0Jakm5EMq4IIXDKoy8A0/rguRQtd917WQg+bINfbJJpsMLXCiV+WgEmH9ZuN973UYnIVoI7JV+4fsEOp0CrkYb001OIeX7u/rd31otQicQk1N/1inXKQk983fP2NkFJaWTim4Ld/2hYv5USriU8kllyNh/Skjhe4/fZmJBaTnePlRvveZXrv/EdzjrpJKwPnkvNGo/VoTWrhgVYVtXV8dFXX5GclMTpS5ei1QYOso8TJ9KEJMBzMjKQZRkhBEvnzuUPzzzDhDFjqGtq4qEf/5i1X3xBT28vY4uLAVg2fz5Wm40Eo5HlCxcC0Ge1YtTrqaqrGxDgjz33HOkpKUesAK+qbeSE+dNj3Y0jGk/x7SZRK/HtUjipF76zWXBC1tABcE9DH1XtKUzK7mD9AQtv3jKZrGQ9N/5jP5ctymZKYRLPftrCm5vbuWFFAXqtxCSjgwStSzT6ylt73opKls0by3/f28HYoqE53Ucie0BWuonLVs3kslUz2XeoldfX7uQH/64jWWOnIN3ApmoNFbmJPDilhymHi4I8cXYFv3+7josf3cV9F5Yxo8QUdRHe1d1DqtkUtfZDwf0MWWXB6kZ4plaQoIXLCiVOzIakU/z/RqMhvN/4xDsrkquIzlmloYvwppbhhUmCCZ5A38cqi4r3tTltYeuoEOH+7ntfLyQmhd9+rHzB1dzn0RDE+0pVIrK9H43B/6RHCMGdv3+bRbMWcdZJJwGHKw+vGboCtm+lS4Sv37qV/3v6aRqam1k8axZVdXU8v3o1j95+O6lmc1TPJ04cT1QJ8M7ubt5Yu5bj5syhKC8Ph9OJU5ZpaW/nqZde4s7rrycpMZGevj4Kc3NJTnK9qcwmExeceupAO81tbeypquJb55/PZ5s3s3jWLBITEqiqq+PClSsje4YjSGd3D6lxF5So8J96wR8PCm4cKzHnsD+gQxY89HoN//2qjdlTMshP7CUlUcu/Pm/hm8flUJZl5M3NHTzwei1nzcrgpRsmkpGsp7vPwa9egXabIN3rxe45iGWkJfGNc2b77I8vq6IaX2E1A3B5cSY3XLaY712yiI0762jdsp5bTy+iIG14KsMfnFrIrLJkbn7mAMdNSOGWlYUkR1GE1zTGPgDT09WkaLmeDrvgxXp4oU4wyQw/GicxK9WVuUKJtRt8CzB/Ynu4wA6Mu4y8S2gOinDvZymQqKpvtpKfE0I0oB/8WdIDbeeJGvcT93X0dd2GXpvYiHB/5yKEQAh1GVAg+G89mpOfcNtWKsJHylrv/VxMSC3nmdc2UtfUzX03Xzlk2/LVrw55N1RJcM+qs6jRwCUOwUXLtGhs7yEyBb87ILj2O5fz7VKJGSlgPmUasuxa3XMKhvzbKbtc/Ryyq+hWYbph2DMR9zmPowRVAjzVbKa7p4enXn6ZVcuW8dX27bz32Wecf8opWHp7+elDD2Gz29Hr9UwcMwZLby9JCQloNBqcTicajQZJkth98CB6nY5Vy5Zx8c0389Nrr6W7p4fWjg4qK47ManpWmx2DPl7XKBo8Wyt4qV7w6DSJco/qlP9MyGXzzk5ev2kyf96cwq3Pf87Pzizm+c9aeGJtI7PLkrkxpZviORKGFYUAtFnsPPxWHQ6Nhn29gjkGZWmz/BGqNTyQEPeX31ajkZg1uRAh7w3Y9tKJqTx/XRK/fqOWx95r4JaVhVGzhNc2tDBt4tiIt6uUvStXsUOCj7QSzUj0bJCp7YdlmfCHqYPVTNUIhGiKb1/tukW4LxHsT4TXN1nJG9/Jrs6hA78/sac0+A98Ty6DtRdLRqooUH+fcuv3SAeOqj1/JYHcnv9XawmP1P2Q7QKNfvAZd4tv9/XdsruBPz/3EX+7ugL9znvA4x23d+UqDkjwhUbic41EhwTnOAW32gRjlg+6JkqSxA1j4MWUAp7f2clPd/dg/2wTWo2roJ5Ww+F/u2oEaDQSWmMCWocVi9XJFUty+MZxuRE53zjHFqoV42lLl/LymjXc/eijFObkcP1llzF36tSB7z/88kueevllNBoNO/btY+7UqciyPMS/atPOnZQXF5OXnc2k8nK+2LIFh9NJekoK+dnZkTmzEeZQfRPFBTmx7sYRj/Hml4a4oXTYBU9UCf45SyIvYfBFbFgxjePr+/j3V9205y9gttPKzJRifvtmHU9NtKPJg9cau7lqk+BnFbDkrc20z5/Id57ax+LxKbz6g0lkefiHh+u7HSrBhIwSX2Ffg2PWimmsmpnBs582D3wWDRHe3Bq7AMytK1fxqE5ivyRxsiw4cZqGbAMUJkD26cpcwZS4nERSfJe+2UzVqdkDll7P4/q7z74EZnuXnXE+FtuUCmMlz1W0Xa1OW9ga1gTGs2+RzPvtLz1eezukBcmAolZ4R+L6+jtXX20rEdKe27jFeKz80eUeGY3J5SroLb47u/u59b6X+OmqIoozXKtB7nfc1pWreEin4ZAG5jsFVzpkJgooXT40Q5nneV0CXLLQt/7wd433HWrlO3f9hyuuuQCNZni15DhxAqFagBfl5XH9ZZdx/WWXDRTckWUZWQh0Wi0Op5OU5GR+c+utA4FZ3gFa2/buHfAFTzAa2XngAN0WC1PHjz9iC/hU1TQyobw41t044rA+eK7LX88DTxH+fgssSGdAfFf3CjJOnkIGMP6kU9C/8BSfb2lmZlID46ekseGDg9yxC347ReLiQompZrhlu2BVl+D1Dbu5fHEOVywZOlEabfmdvQklYM/21maSxo+l1zo0y1AkRbgQAlnIaGMQgLlv5Sqe1kkI4CG7jAEoylRn7VZy3z3Ftz+xWPqma5JTdWpg44F7O8/2PN0tlIpwIQQImJg2LuqW6JGsluienCghWJ+iYRU39GUxrdhAeeqgGVxJNUZ//QsXNT79ofpy+4qPGUmcFhmtx6qnp7vWff86yMJxKRxXW42ttnpgG/ub53C/XkOOcFm73SKnyEN8Bzsnpc9OeXEmyUkGNu+uZ8bEglE/lsQZXYQ1crrFskajQXfYwj2nspKvn32236wIlt5e6pubmTfN9QNYNn8+re3tvP3xxxw/d2443Ykp9U2t5GfHS9CrwVfApRu3KH+nRXCiR9Dlk/Y0Tn9wGz96/iBX/ORf5GSY0HR0UJzmKkF/XZlErxOeOpw5sDJF4v5JEtV98PvLxw4R30rSzLkRW9cecdYNw1f76GzpGfj/x3u66Pvfpoi132XpJSU5AhFpIWAH3tdIXOMQDPeED44Sv2814lsJVadmDxGYnhZwNXRZHKSYXbJipF0d3L+BcI7rz7fb89p4WztjzYTUchpbrORmGYZ97v6jhEi9R0YyoDZW7icAY3U2tCaNz2dmwTgz6za30mUfTMUphOCBvYL0LIlrHcPFt7+Umu6xQE3qUfefC0+dxs9/9xZfbK0J/UTjHJNE3HSVnJTEjIn+K0EerK2lvbOTwlyXz9TJixaxet06unt6mB5gPzfvfPQlG7btoa2z22UJGgXIQiAQaLWjKxXbaCaQ+Haz2yLY3wuLPfLuTu3tYFqxifnlZq67ZCF/OD+LfoeGRL3A9tZmdBqJeyZKvFgv+Kzd9XzMSJV4YLKGiQWDYjHUQSLcwS0UQRGqCBmTBFYZTrx7I0vv2sh1T+9nc1dITfmktqGZgtzYBGC2AebDf7zxFAy2tzaHZP3zJb69xXaw/4NLZPsS2qGIb/ezV99ko8AjAPNIFOFuvK+P57+D+amPlLXR3Y+eXifJSeoWjd2CO5IT+Fhks1H6G1J7T4Kt4HR3wdkT+4d85j7HlS215BnhQO/gd0/XwG4L3D1RGnA3KVruvzBeKM+R56RrQmo5XzttOjdevphbHnidfYdCm1THOTYZ8ajByooK/vbAA0M+m1RezicbN5KbGdyCvHDmFCRJy0frt9De2Y1Br6e4IIeyojzysjNishze1NJObmZ68A3jAMrEtyzLPHJAcFmRhE4DGzoFDVZI18PGPT388YpyNJoD9Mk6EnSCnjc3ceqngufnSGQbJS4scAVvzvfhs6n2hes9qAVb3g7mMqK0BLOSvoD/ICm9RuK52WBxuGbaj1cJ9lhgQQjHraqtpaqujlSzmbSUFAqys6ltaGHKhDEhtBY+KYAE3KbXMEYIxsqwwCIYm+Q670CCIZj1O5D4VmPx9iSQ4FaT7UNsXUt991QqyoauPITzTIWC+zcQ6nHPKu0bcp09r4+a6+EvYDSSpegB1caekV4tC3S8SKUSDOaOEmnxDa4KxxqN6x3u652apIVeJ9hlwW/2Cb7ogMemSSRpXfsEcjuJ5ARu+cIKXnp7G7UNnZQXx1fC4ygjJmk7SvLzB/zHE4xGfv7d77LrwIGBtIWBSEpKYFxJCVMnuDIvWG12DtU3sWNvFe99vAGBID87k7KiPIoLcjCOQFn4qtpGSgvjUdBK8CW+ffmBP3HTefTLYHXC6Z8Kco1QlgS7e6AoPWHgpVzTYSCv/iB6jYTFKTj9M8GlhYLXGuGhSnXxBMEyRSjxh3S3EUq6QV+Eu79RI2E8vGrebhekhPBzqG1s5IrvfpcxAixAb5JEvxOWTpnJ1I82IU4fvCaeg733PY0kicDDNpl9EhzQSGzVwJu7BLX9UJYoGJ8ME5IlJiTDFHNsfFmVWLlDSbXXsPcQS+ZMDb7hEUioridKMreowfv4XRYHqWZlw2U0xXcks51EkmiIb9kp8Lanua+t+7y6HWDWuYwLdf3w9EyJZN3w9340xbebts5eMtJi45IX58gkZnnzPIMtM9PSWDRzZkjtGA16xpUWMq7UlWbOKcs0NLdxsKaB9Vt2YbPbSUsxU1aYS2lRXlSKhlTXNjLtpIURb/doI5Dl21OEf/Lzc3iuVvDUTIlvbxTcVC5xSo7redGfPBWbQwwEEtZ8/BUVlxXBM9fyz1kSl34l6Jfhj14pC5WIr2DWvFDSFfqzhiuxHKoRIe6++Rtw9/YIvuyE21Rm+ezr7+e6q67mHFlwhtNlBSyaq2dvj+DvdokLN0mcTg2XLcqmIN3IrknlJH61l5JEKepFgBKBSgGnLht8jfU7BXt7XBO1XRbBy/XgEPDNEjjz8KQ/GN7WWXD5J3tav73/7/5MKf4q+inBkZyNXj98pW+kreDRIpxJZ7TcUhpbbORmDc27HorV3dfvM5ZBjpEgGuIboLsb3HVx/D0TlWa4cavLQPPIVN/ie6RwOGSMhngq4jjKOeqeFq1GQ2FuFoW5WTDbtXTY0WXhYE0D732ygS5LD0aDgdLCXEoLc8nNSg+7jHaf1UZiQuSKYhyNKHE7sT54Lq02we27BLePl8g1StwwFn61VzAtBUrPdKWWS5h118A+9U1tHD9/OrqbX2Lcg+dyTp7AqGGI+FaL98veMxNEJAd4f4IpHAHizx3ll7sFN4yR6F7rIOfHytv79fkXUijB6c6hS/A5SQnMLzTz/VMm8MwnzVzyx90UpBuobbeh1Wh57rvjySE6qQ/Bv19nglaiMgUqU8Amg06CLzvg/w4Itr1Ww49PL0JNwWnPVHneAluN4Ab1rhW+LKn28cehP9ik6rjh4q8v4WYa8ZzoxLryZTAamm0U9+9EbLX53SaY5dvf5Nj9eThCfCSz1YRCKBPDjg6YUJDLhNQUYLj1G+CWcRouLxak6ly/faVEI0uOXqfFanNEtM04RzdHnQD3RpIk0lPNpKeamTnFZf7r67dSXdfElp37WdPajoREfm4mZYV5FOdnY1DhtmLp6SM5KSFa3T8qUCK+3dy3R3BGLizMcL1MT86WeBszu8dmUMrQCmNCCJyycyADj/Hml7jkl+fw7Y2C8/MFhYnqRbg/8Rturm9/7UYjgM6XCO+wQ80OJ2rWmXavXMX7Bg0/t8u4r6Rb+DbPmEahzU5uqoEfnFrIt0/IY2ddL1MKk/j3F61c9dd9/PEb5a5qneI9kJZF5uQUIoTgui2uanV3TZR4bJrED+v7+dUbtfxEgc7xFIfh5qt2txcIX8+Br2euoa6fvOxQ8r4MR016y2gJPO/r4q8qaCwRW9fSuDeNOZPsUT1OrFP+hYKa6r9qmJBaTn1/G9nFwZ/1XOPoSF2cnWGiua0n+IZx4hzmqBfgvkhMMDJhbDETxrrydjudMnVNLVTVNPL5ph3YHQ7SU8yUFuVRVphLSgC3FZf/d95Idf2owNM32FOcr+8Q7OuFeycNfaF29DrJSNYNe9l3dFlISxnMg9HU1sYF6wVmHfynQXDdmPADMI8W/jBV4ic7NbR3yNytYPt9K1exTYJUASU+4s9qu/RMzh3MTmBO0DLvzDMA+MZsMLy2ka//5QtuvHwxq4RAYmRF+Edt0OeE03Mlbtom+Ot0iV9/bQxnPbSdHzpldAoyFoUqwtVmOFEzCatvspKfrX61zdOlJlRrsz8RHinXF1/i2/3/WP1u3X3pt0sk6kPPujUSvtijzQoe7jPR3GpjwYxUIDp+9ZFe1czJMNHUZolIW3GODY5JAe6NVquhOD+H4nxXjmghBO1dFqpqGnj3kw10WXoxGvSUFORQWpRHnofbSlVtA/OmT4pl948oAhXdeblecHmRhEEzKJy77IKaNivFGcMtIYfqmijxqD4q/elbANhlVzqq75Yp8/k9UlAzCHlbwXMT4LgMOJAQXHjuW7kKgLVaiRPkQdHhmUu36Ss9y8oHBxvvQeySM2YwbUIed/5+DQfr2rnhssURtYR7V0z15mAfzE2DiwslGvoFt24XZHQdQhbQ9vm75CxcHpF+hJrL243aFZD6JiuTxkUmjiWU1ZdouGOFuwoUajGcYLjPUxYQzmtEjfgO1wruLcIDtTVSAZpqcd/DfptMglEbtvgOdj0j9TznZplpbI0L8DjKiQtwH0iSREaqmQwPt5V+q43quia27T7AOx99CUBedgYHaxpZtjC0ANJjDX9ZMdxi6kAvfP1wMdE1zYLn61wBdUlJkJU83C3oUH0zC2ZOBlyW9GSdK03h76dK7Ohm1IhvNUU6YOhAEM7g4xbhOy0uAVpghBvHBr4mbvF9UIIvNRKX21yVNL19rmUBbiOyv4GrsiKPP//iPL71sxcw6nV86/y56LT+RbgQgsaWFvKylflWBxLhFSb4Zw202GTyjKDXwFxbF3f8sBJzwlAv8ECWOm8rOAymJlQqvv1ZnH09F8Ey8XT1ODCb1HixR55IWVp9nb+adn3dt0hlH/LsR2eflrREZ0jtxELkKs0I4y9eJBKEa/0WQiAx/F2lpr9qJzLBrlcwgZ6dYWL91lpVx4xzbBMX4ApJMBoYP6aI8WOKAFe2lZr6ZnbsreK/az7GarORkmyitDCXksJcMlLNo0YAjgaCpaTTfv/f1FxwHqWHV8oP9kJ9P7wyVyLr9Erg8FL01EHx1trRRUaaeUCEaSSJ8/PhnzWCOybEpiiS53J8MBHg74UfyeVWw4pp7Hl6E1PNcM8k1zXxlfYRBsV3D/BrvYZvOQRpPtrrtmpINrqEebBBKT0lkcfuPIcfP7ia/7yzjcUzS5lUvpVJ5dmMK8nEoNfh3Pw+X1X18MjbdWyr6eXXF49h2STX0nOwAE5/Inx+usTvpsK+HjjQ60pR9mqjYF63HXOCNiy3hmDuKG7B7Z1JxRMl4tv9mXtbWQgkKXoTSzVZPby/8+eG4i/IUq34Vnu/whHi3v1o6NaRm6ze/zvW5d+VTJSiKcJDYWjRo9Ct39HwpQ9mKc/NTKaptTvix41z9BIX4CGi1WhACKZPKmfp/BkAdHX3UFXbyCdfbqOtswu9TkdhXjalhbkU5mah08XWchUrlOSD7vzN+WhwZa0A+FYJ7OmB/zTAtw9v4ynGnE4ZjSRh++15Q9q5sAC+uRFeqhecmx+bCZCSQX8kfTUrlo3jib/todshMB++wN4i3C2+ncDvdBpmOQXHycJnIYvaTj2FqXbFgignI5m/3nMBO/Y1sWFHHRt21PHs6xupaejEnGykvauP/BQd1yzLo2SlkRv+sZ+s5LFMLTYFzaIittw5ICJ6nYJux2BQVoVJosIEIHHDVVN54YtWrnxiD/deUMqis1cNtBGKD7M/67en0FTra+2vH+7PujoFmampIbXhK7ViMEbS9zqU34OS+6Ym0NQfTRY9YzKtYbWhFn8iXO09UbKaFo4I99efcOMCmtrsZGUMX/UM1NdwRPcDr9ewt7GfyQWJzCgxccKkVL8TXX9CvKI0ix37m7HbnegjEycd5ygnLsDD4KBXAGaK2cTUiWOZOtFVJMhud1Db2MLBmno+Wr8FpyyTmZZCyeEUiGZTPGk/uN1HJMqSXJXMFma4rHxXl8J1WwRXygLt9LuG7NPY0kbW3rdcJR49SNFLPFwJ12wS5BjgxIunD3wXaTERqpVtpAOlphWbOH56FvftaeGeiYMWVLcId1uQD0nwiE5DXpbEbZM06D188T0Ht9pOPZMWTQl4TF+DryYLZh9nZvZxZqAcq9VJtpRHZloSBv3gq+jurP3c8MjbFOamIhAI+WpkYUIIQVZ6Oj+99loKc3NdPuWH2Tp+LLc8vRengKtL4fx8kIHP28ExtZTjnYIL5mVRkZvATc8e5M8zWxhXmhXK5YwISoThK1WJQ0R8WyuQ3Mmuzq4RKz8fjghXKvjD+T24r0MgsadWhHtbjhstOhaUqstuEU2rcqj3JJBrihIR7k/gBhLh4P/eBLonza02sjMM0Dv8u2hYtz/d283FC7Lp6nPw2HsNrN7cwZ3nFJNk9G808z7vrHQTZYXpfLm9lgUzIt7FOEchcQEeBrUNzSya7V+I6PU6yoryKCtyiXQhBK3tXVTVNbLmwy/p7ukjwainpMDltpIXgZzkRwL+/Ha/USxx5y7BpUWwJAOcArqdoJl257Btq9f/Fbmvg4OSoDQRBK6qaO12aLXBlBS4fZ/EcQ4ZvU4TNfHt/rdaP++R5qZTC7j8cQuvZ2ZzRtugn2L1vefwZQdsLdOyphmuLZM4J29QpPsa7Jo0BZyQ5T8Th1LLl9GopYtmujwG2Qmp5Rw/dyx/u/9CuixWJMlVirq6pxYJ2LK9hUt+eD333LCSJbPLkCqXUlXbzq0PPMM9l4wlZ9sBbtshWNsK/eYkHE5B0qfN3Lu6kTNOmMR5Jy/ixoQyfva7t3j2NxdH1J0jGrmsPV042loFZYd9+EOx7HpbwZW2EQlLuPdkwrNtpQTqRzSLENkcEkZd6BlQQj5ugPzg4dwTf64p0bIuewtxJc9cc5uN8WOSfArwaFCaZcScoOXC+VlcvjiH+16r4et/2sOjV5STE6B8sPd9OHXJeB7624c8XHga+QpjWeIcu8QFeIgIIXA4neh1yi+hJElkZaSSlZHK7MrxgCu489Dh4M53P/oKgSA3M53SwlyKC3NJOsoK/ATKXHFClsSYax7i2ddf5+ZNm0gwGjlr+SSfIqmmQ88bbTZ21rm+szlkTEYtaUk60kw6Zk028d2paeh1GvaZp/DBS+upa+6iu8fKgmklnHXS5BH30Y9lijCjXsMDF5Vx5RN7mH5lBeW5LiF21282opVcPtNPzYSCBCngYCtVLsW5pw6dj6IXkRBAA22YwOCR7GNMlsv1oqw0lYrydH700Bvcd8cSSpKKuer2F7n+ihNYmNcC46bzV+Mm1uQU0d3v5LKrzkeSJKpq23lpzTa++dN/U1aYzv5Dbaxbf4Clc8cG7ZO3cPS27IYqvNWI6FeqErHU9VOdZeTszH7V+7sJ1NdAPsOhCL6RLrQTyOIaqiuKLEAzsq8JxYyUCFcivpX0Rc317+x2kJqiXp7460Owd29huoGadpebkVGv4Y6zi/nDE5v44ePb+ONUCZ3Gv0HCk0vOmIHdIXPlbbfx2mOPqe5/nGOLuAAPkdaOLjLTAvtjKiHBaKBiTBEVh4M7ZVmmqbWDqtpGNr/7CX39NpISjZQetpJnZ6ahOUqDO403v8R44I7rrgu6bV/SFCYVbGfRuFwunJdJokHrUxRKlUv52+/eoqOrj0UzS0lM0POXF79AIDhneWVI/QxlgB8N+XnHZCfwg1MKuPX5Kv5x7XgSDRqM2WYuXpjNkvEpQfeXKpfS3eMgOWn4smw44juQq4Iv4TZxfAYTxqVTdaiLD2o+pbQ0mePnjkFKnYLYuhbTqdM5i6GDcWlhOj+4Ygnfu2Qh73+xn5fe3sr6rTWKBLiSPoWK0gwsAEKApJGGWJM9n7tYlqEPdh7+UJNRRanY9Hc9Qik81NarJSMpdtUNlaTQi4YIjzVCuILq1aw7BAsa9vecWe0ya3d28auLygY+00y7i+selrn+2+fyyAHBD8oPG3qCVC2VJIlvnDOb1R/UsmnnTlLMZp/bxYkDcQEeMlW1jZQW5Ua8XY1GQ152BnnZGcyf4cov3tPXz6G6JjZu30NTawcSEnk5GZQW5FJckEOC8ciP+FASqOmm32rDaNAzbdEVvPHan/jWUt/3oSlvFm+/uoEtuxu48fLFTC7P4Q/PfkJPr43U5MhXL/U3wI8G8e1m1cwM3t/ZxctftnLJwmx0WgmbQw64j+fAVtdopTBv6LULVfgp8RH2V0DGZNLT1+egvCyVXbvbOPt7T3P60kl852vzMR/8bEifvft38qIKTl5UEXb/RwK3CJftAkk3OMH0FuGe+BOZSs4zGlbwcAlVYPoS4mrcIKTKpTTutpDbsV31scMJbBwNAjgUIhW0a3fIPo0p/gjnmA6n4BevHGJyQRKTClzvGnfQt0aj4b7f/YPzL72Uwio7i+TBdKyeQbK+zrsgJ4f2rq64AI8TkLgAD5GqmgZOPm7OiBzLlJjAxPISJpaXAK4UiA3NbVTXNrJh+x76rXaSkxIGfMmzM/xHcI9G1IhvgNqGFgrzsikvyeX+P0uunLFe5ytVLuW///6cx//1GVedP4/MtCTO//4/ueDUqbzyhyswm0Jz7VEr1mItvr0HBgm45OBr3P9aLRcvyGJ7XS+3nFYYdD83NQ1WJo51BQ9Hy+odaB+3oLPZnBgMWmZOz2Xm9Fw6Oq28+Wod3/rZCzx+57lkHN4nUFYRJahZNo+WkD+rtI+GOsFa81BfVH9+1f5Q6icdSp5vtT7YnpPVQMeLhKDz1TelxXsaW2xMnDENmj9TfdxQRHgo4juWlUK9iURfWtvtZKb797v2JNxj3fbvKtbt6uRf35uI/e0tw8ailORk/u+3v+Wam26ixC7DGlc6yqLl+oDpIi29vSQnxZMsxAlMXICHiKW3P2ZZTLQaDYW5WRTmZrEQVxCopaeP6rpGvtq6m+a2DjSSRF52JiWFrgqfo8VKrlZs++JQfRPlJQXkZWeTYDDwpXQ+c3hxyDYOp8wr72zH4ZC56oJ5rP5gF3a7k6sumEeiUdnL3RslAiMSac+izZwzTqf9xT/zsa0MQ+IBSo5foXjfxhYrS+enR0V8+8qt7Z3uzy06U1KMdHQOpoabXzKZed+dxINPfsDDf/+Qu693nVOowXmh3MNg+4Rzzdpa4fhxdj53DD67/sS3Pyuv+9lUEkAcirBR4woTTnEqtShJVeivT82tNo6fm4aUG/0y7+FYvkO9TkqL9qjtSzj3q6nVRk5m8PEqlHP1Ps9z52aSkqTl2qf28miFoMBHjQTD977PpRqJX+s03G+XSQRq1tiHpGj1PmdLTw/JpshUrI1z9BIX4CHQ128dNYLWTbIpkckVZUyuKANcebIbmtuormtkw7ZBK3lxQQ6lBblkHcG+5HWNLSyZMxWAn33nO9z20EP889v5ZB+2EHb2Orj11icpLcjkb/dfwE33v0ZNYyfXXbIQQxRysQcKNItU1cBQ8DdASZJEfnYK/3h1AyfOVyc0nbJgn2V/yH3yJb4DFbXxR0V5Oi+/uoeK8nTGjU0DXOd1walTueaO8CZ5/sRhuFZaXwJVqRW7rU1QXiFxVoJyi3eg9G+humUowbMdpZOOYL+TSJULD4SvyYjdKaPXaxT10RcjXehmtAjxcER4c5uNieWmgX6pKRCllgXlZhaUm3n6wyZ++lEdf5gGeIhwd32Ek2TBLg08ppP4vkMM1Oj054ritoDbHbGLH4gz+okL8BCormuipCAn1t0IiFaroTAvi8I8H1bybXtobjvsS56dQUlBDsUFOSQeARlXXNln5IGiRotnzeKCU07hxn/8hwXlLn+7Nds6WDoxle+fksbnB1qoqmvnXw9dil4fuvj2JyR8CcojwQqelZ7E2i8OcMPlixTvY+l1YNf2MCz5ukJCEd9vfJLps+jN8YsK0WokfvXwF5x7UiXjLx+LJEkU56XR0dVPT58NU6JrkhyqZVapGAm0nRKx4M/P3RObFYwJ4U2YPc/Nn1tGpJ9bX2I8nGNE293C8xo4nAJtBIwU4eTYDpVwhHisRXhLm53suYMGrkjeb3/nd/nibKpbrZzxWStTzIKpN5zNwnSJqcv11KyxIwHfdghu02t4WwMr5MDhoZbeXsxJSbR1dUWs73GOPo7+pNNRoKq2cSC395GE20p+6tJ5XH7OCi4+6yQmV5TS1tnNa+98wtMvvcULb6zls407aGhuQ5YDB+fFgq7uHtJShi7tffuCCzh3TiYmoxaTUcsPTi3k5pUugTaufw8OWeaRf34c8jGViu9Q/JpjxScbqwGYNFbZRHJX5z4+23eQrCz1guSVqkRV4rv0zWZK32wOuJ0kSSxZWMhvfnk8H2+s5sW3twKunOHjSjP595tbhu0zIbU8YvnalVo1xda1ftvydU18XStZdpWgHwmiGZCq5voHQo1ADHQ+/p5L9z6t7TayMgzs6tw38FmoYtCwYppfkR3NoMtQxHSs/cltDhmDfmSliSRJ/OysYl6eK3FRgYRDwA+3Cz5qG6wGbAS+55B5QSfhxOWGAkPfBWLrWoQQdPf2xl1Q4gQlbgEPgcaWNnKyZse6G2Gj1WgoyM2iIDeLBTMnA66MKzV1TWzeuZ/GljYAcjLTKC7IpSQ/h2RTbEVmdX0TxflDRaNGo+GCK3+P2HLnwGc2h8y6XV3sa+zH0tXDnCnDAw1HglgHYfqi3+rAZneyfOG4oMG6ngKmtQUKi5UfJ5QJiafwVsLc4sncc2MOV93+EqtOmITRoONXt5zGd+/+D3uqWrjukoUU5AxNsRjIL9xtAfUWId73MdqZKjxdU7o6ISX8jKdBs6XEeuVGSdn0QN8rFY5KVhzAFYDpTGoHIjf7iUWGk1Cs4b62VfsuC0XICxHdgkeBzqHVYufuNjM1h7rocYJVhi1dgsUZEuWrX2XfylWMEZAp4CsNzJUHfcE9XVHkLWtxOByqaoTEOTaJW8BV4pRlJKQj1n86GKbEBCaUl7DiuDlcfs4KLj37ZGZMGkdPbx9vffAFT7/0Fs+/9i4ffbmVQ/VNOJxORe2uXreO3r7wU5IdqhsuwN2400f1Wp2c8387+ffnLfTbZf7w9bEcl3go7GMfLeyvcbl0zJsWWE17C7b2NkF6hp+ND+O2KgYT376s2t7iW6kYH1eaxcSx2az5eC8ABTkp/ONXF1GYm8IltzzLf98dnkYukND0Jc6lyqVhWQaViJc3Pskccl3c17CtFTIyQ3vfqJkEjSa3qZDEm4JrrOZ6NDTbfD7vsbYQh0q4xgA1v4FQr1GXxUGqObQg+WAEO/8Pd3fx5UEL3z2zjD9Pl1izUOLaMs2AP3j56lcBWOEUvO1RsdrbEq7RSOh1urj/d5ygxKdoKmloaiM/R33Q2JGKRpLIzc4gNzuDudMmAmC12jjU0Mzeg7V88PlmnLJMeqqZkvwcSgpzSTWbhlhWP/zZOfxkq+CKYliWKfGHg4Kbb/8tE8cOLYLirpIphKBPhiStNCwivbWji8z0FKw+otXBJcLffPJ6KvISePjSwEVWlOZPPlLx54NZXpzJvT84hcUzy/zu60uEOp2g9ZGfNxKuN77EdtWpyks5X3DKVJ58+UtqGjv5akctQhZMKs/lirNn84s/vsuSWWVkpA3NWhTMEu7expNoBdV6Cm/3v09b2MorVYkUtPQwftLQ6+7rWfUO7vT8dyTycY+0hTyUax3I71jtc9rSbqNoyuD/Y71CEAki4UPvb6UiEhOTplY7ORnDBfhIBOGeNSsTCbj31UP8+IwS8usPDRtjyle/SuvKVfxTN/T36J0VJT01leq6OkbMdyzOEUlcgKukqraB0sLIF+A5kjAaDYwrLWRcqcutQwhBe2c3h+qa+ODzzXR0WwbcWzLXPcKvD2i4aazMG02Ct5sFE0zw+8fu5Pe/enqgTbHlTqp6Bf9pEKxrhQYrFCUIZl17NvMuvZnZU6aQkZaGhARb7wLwKcLFljt5+ctWrlkW2Ec/kuWqjzSMBh2nHT/R7/e+rk1/nyDBq3ZRNH3ePcW3OwjTU0R636fjEmv4v9Z2qndYuXx6OgDb7Xo+3VxNcX4qaSm++xqLKpLewj9YIOquBi1z5g+Nx1D7rIYrwt39HelJayjZOZSKTH/Xw31OTlkwOWPcsHMejW5lsSLSgri5zUZugBSEoU4glN6zM2dlYk7U8dvVtSyrHD7G7Fu5ijSgG7AD3lMFtyvKudP0/PO117h01SrVfY1z7BAX4Co5VN/E7KkTYt2NUYUkSWSkpZCRlsL0yeMAcDic7H7wW/yzNY2KsiLkVB3n5dkorTSTb+7nqie28MWWv1OSv5K6pv/x7PMH+WKX4Ow8uHeSRLkJ9vbAhk5Y/fqfufdxmbzMHMbnJrO6p5N5iyaRmaxHbLlzwPXE7QO+v6mfGSX+A2ACia1wRLh7QHfvH6uBOliVtlBobYHM7OhZc6pOzR6wgrvFt2f2E+9r68Z9jXVaif98f9KQ7xbTz1WTM5Eqzw16/FgIcXeVy9MWtvoU4Z4ZYP5bnaRKQHuXsYfhIjwSE86RmrSq8Q/3h+c1CXYt7Q4ZvdblZuCeMB0Lk/NY09xmo7IiOeA20c6Es6m6hxMnpwKu355bhLtTEmqB9MPf+jPzXDg/i7MefpfTlx6Z7kpxRoa4AFeJ1ebAaIiOj9qRihCCnz38MAlGIxVlZSQlJND22iO8VC+oMHXw029Xkm6SsFj1HOpwsl1M4qTFuTz+zEGsjt+i1dg4bs5U7ji7gyTjYKrAaYf/XAGIycfz2nu11DW1s2ZLFb96o4ZbVhZy+oyMYcGXdruMfu1WOGV6SOfjOdiO5jLlvnD7IQaq0hYIf+fb0jw0ADMc67c/i28gq7c/4a0ENXmER5vIkq0CjcE18QkmoJUUHQrVEq4kcDXSRMINSG0hJvexmlvtZGcqe8+H+luL48Lz/nRbkjAnB08Xq8b1Re2E7fP93fzo9CIMJYUD71Prg+dSdDglIUCGgHYJ8vzEjKabdJw6LY3V/3lI1bHjHFvEBbgKOrsspJrjqYW8aWlv5/W1aynOy2PHvn2Udu/DrIPrx0gsv3hQBCcbZSaftIDJwCnHZSGLCppbbRyq7+dQXT8vbtWh1wgKU+0Up9kpSLVj0LrecBqNhN2u57KzJpF88VR2H2zmprtfIMmoZdmkwRQRQoBOgj7ZlTbKE7flJNTqiN74sjKONgEXKdrbBFOmjYw/YyDxHYlVhUj7rao5rvt4Sp9BZ7cTrTmysfKeIlyNeI7U7yYY/srGe/YzVBEeaPLh2X5ji5XcLOOw7/wd80gS4aOldL2vZ0kghmVmUpMRJxIFhQ61WinNClwTox9ICLgFXLooh8sf2xVyP45lnE4nn2zcyOp163jzgw+496abOGXJkoHvb77/ft759NMh+2Slp7PmyScH/l9dX8/9f/oTW/fsoaK0lBu//nWmTRhd3gtxAa6CqtrGY97/2xcZqancf/PNfLltG59u3EibDa4plcj3UThkyMsSyAFyJJhdCBSCzSFR26WnukPPp1VJ2GUJs1Gm6NDntNUlkrhvJ0KCCuC8uZmsP9A9RIAb9RqmliXzeVEm7gLrvlwygokJpULD34A+mvxEIzHgOp2g0w1aYsPBn8uF+ztwXddgwttXLm61IijUFG2Rur/B3FAc3TK6NO3AtqHg3a47uDNUEe7ex5NIWcHVuIepEVuBfu+++t3YYmP21BQfW/tmNInv0SCuleB93a1WmU36prDajMTvMi1JR0u3nbSkQXlkvPmlIVbwLglSPKzfngGYbkozjcwsTWbdrngxHrW0d3Vx7+OP43Q6cfqoR9LV08PyhQu59MwzBz7TaQdXTrosFq762c8YV1rKXddfzzuffMJ377qLZx98kOL8/BE5ByXEBbgKDtY2ctzcqbHuxqhDq9Vy6nHHcepxx2F3OPjrLRfwjQ2Cq0rha7JAo/FvOfUlog5rccA1sHX1azjQZsBi1fLMV64Au+xkBxmpgvd3Vg3b/4J5WTz3aTMrpqb7dMmItCXczdFq/e7vFxiDmXs88Fe90hNvwent7+3L4qik+E2olki1VvFIWNrcz58/EX7awlYsmwUJxRqf4jvc5y1UEe557JF20fLVT6WCU835tXbYyaj9BDKC+56PJvF9JNPcbiM7w38A5kixcno6N/xjP/dfWMa0FdMGYozcIrzwJB3dHwkmnqjDGGBsE0LQ1mMfoV4fXWSlp/PGn/5EXVMTp1199bDvO7u7mVtZycxJk3zsDW+sW4fN4eA3P/oRiUYjS+fO5aIf/IAX33qL719xRbS7r5i4AFdBR5eFtJTAASLHOnqdjm8USyzNhHt2C955ci/fW57P5J37AhZ9cfvWwVBrgu2tzSQA5tlzmFPcy5IxPcgCWnp07GtJQNYX8bf16Ri0goIUB8VpNiryTOyvPcjmlzZRlADJhy23IyHC3W0fTbQ2M1ABM5D12zuVnhIR7o0v8a206qSbcN0B1IjxYAV7guFLhA9pzyk4u7xfVZvB8Lw3SkW4v1WUaE86fRXNUTJZCKdQj9i6FrkjHY00etw1lHIk9dWb5lYb2V4ZUGLxLv3OiXl8sreblm77gPh2Y7z5JVofOAeDhoDiG6D1jc3srYtuYaFjlS6LhYy0NL/fv/PJJyyZNYtEo8uVSKPRsGz+fN5YuzYuwI9EbDY7ep02aOXAOK6X1ETgKaeTf//vf/zyjTew2nNYNHMmWo0G+4Y36K6RkQFx+I9BJ3G6U1AgBsW4pxA/+EUrpVI7jClBI8HHuxp5Y1M7e2t7ueWkciYVmKjr0lPTYaB6p44Fk2bxeK+dpoYOrs/vZG5SD1rp6HwZBnOJCHdQbm2B/EL/4jtYGj0l+Msgo1Z8x5pQrrW3CHcjnIKiZCf+6qV5C1E1E0klItz7mYp2Lmbv/gea7PkL0AyEv/57n6fVIWHQCb/fj1aOZPEN0NxmZ/qkoQauaOXdD8TanV30WJ0cNz5lSJYtcAVj1vWDv0yJnhP/RC04j84hJ+Z0WSz89913+b+nn0aSJBZMn84t3/oWORmuylkNzc3MnzbUCFNaUEBDaytCDI8ziBVxAa6QQw3NfiswxvGNVqvla6edxkUrV7Jz/3427NiBBEhFV9P6h8fQ4JIWEtAqwW16DWc5Beccfmt5FjeoFynMl6oGrJu7G/rIS9MzvzyXvFQ9ei3kf/El+cBcLZyXCr1Cz8N2M5/ZcqlKMCMjkbndRHGajeJ5s8g4/ENUagUPlEFCjRAINFAGstzFSgi0tQr2pyYheSUniITwBt/i+0gT3uHiKcLdtDQLatIDDxT+nlu3eA10j5SsUvgimBCPhNVYaZxBKL7nwX5HTRYdOclHVhXDI118A7S228hMGx0ZxhL0GvQ618TXLcLdheLebREc51Uh1deKW1UfGDRgV1YsOuYYjp+EIXUEXYC+2BLyrpPHjWP6xIlcf9llHKip4Q/PPMP377mHf/z612g0Glo6Okg1m4fsk2o243A46OjuJj1FeXxHNIkLcIVU1TRQMaYo1t04IpEkiUnl5Uwq9xgoTzttIK+qm+VOwQ8MGk5wCtIPf+YW4Q406CVXMIbtrc0cbDFxwdxMlk1OG/gMr32SJDsHW1q4sqSVBVoJ/cnTaO/rocY8nU83dNDWYUeSJHKzDEgpgqwcSEz0LXiUCoJgg7talwbv73y1Hylh7kvMvVKVSLelH7NXBcxg4tufsAs2gYnEucTCJzfQBC7ULCPtrZAR4aK7pW82+6ww6j25VHIfvIW45z5qreX+qngG6mO0qPu0gUxs2PY1h/wsBZqcRJqjQXwDOGSBTjd8tWekreB6nYTjsBFoYFx5yyW+u+yC1U1wv0dlWl/PSFefg59VG7is0Mrj1dHv87HGE7/85cC/506dSqrZzI9+8xu+3LaNuVOnIuHywffE/X/NKLF+Q1yAK6a+qZWl82fEuhtHFeWrXx0iwjOA6bLgS43Ecnnwx7NrnRbz4kE/2Jo+wbaD3TxwYanftt0ivNcJ6YeNKpIEGUlOMieZmT7JNTt2yoKmFhuH6nV89UUT/X0CnQ4yMiWycyAzG/T6wR/sSIkAf0RrMPInvmWbQNKFL76VpH8L5HbiGSMAvrMOxAIlKyeB3CW8harnNrstzcydlEZail7xscC3gHUXOXL/2y3CQ7WCexLoeQzFGu4rvWeg58fbCh4oVaAbb9Hk+V2TmMBcTfXA52pEuNIJ9pHi1jJSyLIIKIxG6roJIfjz+4188/jh2c7abIIbtgpOzIKJhz1lfD0bNofMTc8cYNH4FE7ob+Hx6rgfSrRZOGMGAAdra5k7dSqZ6el0WixDtuns7kav0w2zjMeSuABXgCwEshBotZHNxxtnuAi3SBJpDE07JC/JpIhOAKyy4OaDBq5ZkYU50ffj6ynOzDroDrCarNVI5OcYyc8xklrWAoDDLmhtdRWf2b1TUN2pQdJb0aVq0KVq+M+BBCSNpFqIew/OofixutsZqQHc2SWjSxl87tWKb6V5l4P5fCsV3L4GxFAKdSgRjf4mLd74Cx70thh7H7Oj206qWdkr2tdxI+UiFC6hinClBPv9+HqmArk4dZBIGn1Dto30qkqgyp5Kq34eyZZv73dfe5eD9JTgz3q47z7v++59X9cfsNDe42BFZdqQz5usgu9tESzPhqtKJCRJ8vtM3PtqDalJOm46pYAD6T+Hr24Iub9xlGGzuww0yUlJABRkZ3OwpmbINgdqa8nPGV1uxHEBroDm1g5yMtNi3Y2jFrcI7wb2SDDBK+1njUhjhqYWw4pp7Knp5eBHu3nqgyZ+v6aeM2dm8KPTC322C5CsA4tDnVuCTi+Rmwe5eQASr1QlINsFzk4Ze4uT/gN2hAyfHJLJynZZyuWUwBYcT5QUGgmFUP2mAwlJR5cTfUbwynS+UJo6L1KTiVDEt9JtghHIRUlNppGBfwtAVAwJFvJ2UVGakcYX/lxRopXVJJgIDzUbUbAKqaH8JgTgneAiEjnn/RHM7QxiVzwqXILdU/fvoaVteAYUf4Qiwv09B96TqyfWNvKt43PQej0AD+8XLM2Eq0t9u8i42ffu//hgVxev3TQJ7fS7oDrufxJpPtu0iaK8PApzB1cp1nz8MZIkMXncOABOXryY3//jH/T195OYkIDT6eS9zz7j5EWLYtVtn8QFuAKqahooLcyLdTeOaspXv8ofTj+TmbLAe4GolSQy6QFgSlESv71kDOPzEkjUa7jqr/v42QtV0CDT64QeJ/Q6YWwS3FIukayF15xm/vDwDr62IIuLFwwXHW4CiQCNXkKTpUWfNShGG/plCgz97Nsj2L2xHgRkOlMoSrVRlGonLdGJGnezaJX0Dgdnl0xCqcv6rMb67S2+lYhO70HSVzYcNURTqAQSwu7r5Hk91LoudfZrSbU3Irbu8XkensccCUu3+96oFZ2e+0U6i0ow8R0K/UKHkdEXgKnmmvm7DiMp3NVMpnZ17qOpNYPifBXFBlQQbBLmFuEbq3uoabOxcnrGkP329wg2dMLPxwf2+wZ4YX8C58/NJGn2LyLU+2OTqro62jo7aWlvB+BATQ0bduwgIzWV1evWsW79es5bsYKpEyawa/9+/vzvf3PBqadSWlAAwClLlvCXF17gpvvv58KVK3n7449paW/n3JNPjuVpDSMuwBVQVdfI6csWxLobRz2fayVOdg41fxecpAcZEk4ZfOG5K186nAKNBt7Y3MFVJRLlJkjSQuqicTz7STM/aXIyd0Yy//dWPSunpfP3j5oYO3ceau5koKX90xa2spEkzprXx4TUAoQQtHy+n5oOAx8dNNHRp0WSICfZQVGqjeIyB3XOKp9tB7OQhiLO3QNLIOtjsIFSyCBpJVUiz1NoBupzMMGkRnh7D4ixshJ650IHhqX783cvPYVC/fS55Jt9F/FQkuHEE0//bzdu67evyqORdm9SKtqDPd+ez2q0JqpNJJMjWYJv6IfRnDd8pNNIqmFPQwuzKscq2lbJ8xlK7YAnGkx88/gc9FppyP47LTA3DRK1wa0pTqdMRoXv4jBxlPOXF17gv+++O/D/x557jseee44zTzyRu66/nn+tXs3aL77g+dWrSU9J4dqvfY0rzj57YHuzycSff/EL7vvTn7j9d79jfFkZf7j99iFWc3/86fnnw+r7eaecQmaAHOWexAW4Avr6rSQlRmd2HsdFX38/uyT4oZf7STPJZNMDDBfCD7xeQ4ZJR7JRQ/b0Ak6ZlzXw3eSCJG5+9gCf7O0GYEddLzdceRJ/ffELFkwvCamPwQSPJElkmZxkmfqYUegSoU4Zmi06ajr1vPNxG3UdMhoNNGr16FIdaFO0aAzhR2UHW2JVIwzcAk+2CSS9sr55CjkILpB8DaKGFdNCchlQY5X1JRLCFXOeQYP+Ssr7ItBSes2GViqkFiguC0vUKRXfwQjV3SKSvtOh3Cf38ZU+V00imRxCF+BHAtEQ4uEWM7P2Q43tINgGPwvlfofqhrejW7C7qpv7cyzY3qob8l2fExI8vPA8n2nva5iZlkRLe09IfYgzyN033MDdN/j3nb/otNO46LTTArZRlJfHH26/XfWx//jccyyZPZuM1FRV+8myzOtr13L83LlxAR4pLL19mBKVpaCLEzpWmw0dw2V2rUilSOoY9s2+xj7e3d7JM9dW8LU/7mbBuKGOKzqtxP0XlvHzF6tITU7ge1eeyPFzxvDgk+vYuqeByorIuBQFEy9aDeSlOMhLcTC3Moddnd04nYL/bNPi6JSx1tsQdsE/N0lMK5HJyoHSBCcJxtD8rn3hL4gs2KDp7HYFYCoVlErE90gEj/oLdvWHWh/8aJRf9xYOTcLMIumg4gBAt9B2i2tfwtsX/gogRZNoWImD9VupEG8SyVRoWiLWr5FGzf2LlBCPxu/B3a4aN6NQxbcQgj9VCS4vkjD4qG5ZnAhv+/g5+bpuGo2E7UhJ/B3HL98+/3ymT5yoah+n08lr77+vap94Wo8gVNU2UloYfNkiTniYkpIwAPfpNPxRJ/GeRsKGKwCzUOoc9nL9y7omLl2Uzfb6fiYXJFGcYRzWZqJBw4P3fIO7rj+ZB/68FrtDZtkJRfzl1Y/99sPzhe8vyO20ha0+U7cpHfy0WonzptlIKNGTPNWIeVYCF66UycmDtlZ4ZU0zT79cx/OvN/Dh+nYO1vQxJnGM6uOE2j83jk4n2pTArwjvaxHI11vJ8dVaTCNpYd3VuW/gj1o8J2KB0vq5nylfx6hZYx/4Y2mCxnesA98FunbeKQYDiW9v6zeMrPh2Eyx1oeefSBLseekigRT6A25jWDEtYDtHWorBaFxnNVitAsPw1zegTNzb3tocVuGu/zZCkxXOyff9/SQz7O6BbocI+vx8uqmaOZXxeiFHMpPHjSMpQb3HgzsINMHo52H2QdwCHoTq2kbmTJ0Q624c9eh1Ol555hlevPBieoB3tBL7CzWMx0CyZBuybVefgw92dXLbqiLe2d5BRrLvx9htoThh3lh+/ru3cDhkdm7r4spz5yjqk1tUeboXeH/nz5dXiTAcaj13ZV45fsJge/1WJ7WNVqpq+/l0Qyc2h0xiXzOFqUkUpdrJM9vRHzaUq3XfUDKwObtdAZj+3CoCBV26CWVg97ZW+svZHGrWEyWE4nPv7YoSKjatFp1zaCBgJM5rJP2+leBpCQ8myN34ug5q+x7MGu4rcDoWxZ1GmlBWJiJh/e7sgNS00NzwwhHe9f2C3x0Q7OiGB6e4rN+tNsHHbVDbL6jvhzorJGpgYTr8o0Zwo8f+3isIzW097NjXxNypcQF+JPPPX/86pP00Go3qfeMCPAjNbZ1kZajzBYoTGmaTiW+8/l+sD57LpU7BNzdKpPc7weT63i1s1+3qYlZZMn98t57XNrbz/VMKhrXlOZD09dux2504nTIHa9s5fs5Qa7L3oOOdDUVJ+XmlFTADZVrxFnzGPR8yFiifPyhSem0SdV169rUa+fCACYcsYTLIFKbaKZw3mzyzHfmd0AclT6u/cLoCML3xl+s70lkp/IketWIo1BR3oeA9aQuGtx940XI91SKNMaKHoqLIFRuKpPiOZB56te1EcqLg+RzZ3tpMj9CThN3vNmoIJ/AZhv+WvPeJVbpIT8L9Tbl/I9YaOwsKfQccB0Kt+HZnVco+UcffD8G/6gQXFkjcMR62dcNPd8h82g4L0qEsCealSxQkwPO1AoeAd3uNGN6p5zsnDTWVi61rqWu3csM/DvCNxZkk7PkYpq5QfT5xYsuBmhr2HzrEmKIixhYXD3x+7R138Nhdd0XlmHEBHgCHw4lWoxmSizdO9DHe/BI8eC7fm5jGnxs7aS8SpB8OVLS9tZm1bWayzXq21PTy7+9NJCdlqFDxHkCaWi1kZ5qob+mmMDcFrVYTctnsSOWxVhOk6PnvJINgXJaNcVmDqwI9Ng21nXr2tBhZdyAZZ+ZSEptaKJA6KZQ6ycaCZ4ZdJQOnbB8egBmoyI6ayYgnI1VUaCRFOCgT4t5WdnfWlwZhJo9un9tHqm++xHewVIOev4+RLg8ebQwrplHTaiC/S49hTGSs3b7ErNJ7qDR/djQYiUwunr8LZ49gfW8CG6pc7m5KVtOUim/vCrpO4MZ1MnYJfjBJQ5MVvr5BoJXg3HyJH1eA2avy79gkuHSbjq8vyeS/X7UNE+BrtnVwz38PceXxuVy2yH+a2zijl3+++ioPPvkkuZmZtHV2smjmTO66/npSkpP5ctu2qB03LsADUNfYQmFeVvAN40Qc480vIf36Jibq23mmVnDdmMGXYm1VJy3pJi6alzVEfPsbNPqsdqw2Jxt21FGSn+b3mJ5CPJRAQs9BwdsNxXNQi3SQoskgMz7byvjsQZ/hbqueqvf62SVy+ECMhS/TSDbKFMmdFOYW0ak/hCZAWi3vCpjREt+ef6vd3197/oiUCPdsJ5ilUmklUE8ahZnJmsaAffB0Cao6NVu13zeoEzS+ru3RJsIbLTpy/aR+HI1EW4TDyKTzlPtkNIkjY+R6RSuxQSuhF4J/1wmmmOG2ConpKfg0tBlWTCMb+HlFF7e/WIWl34ksCzSHgzV7rU7uf62GRy4fS2WRa6lWmnrniJxLnMjx1Msvc99NN3HKkiV0WSw8+OSTXHbrrfzupz+N6nHjAjwAB+MBmDGlXqRwWXYVV26ArxUKMg0SVlnQZoeu2h6WTVKWN1bK7OakBeP4078+487rlgfdPhRRocQi421ZisbSv7t989a1VJ5aQKXrSEA73VYNtS072N5dQWOLiU6rhcQkyMqSyMyG9PRBP2ZHlxNdmu9MLOGKbyWV/9S0F6xNT0IV4d6CxJ/wcX8e7BiB3D96POIeDCumDTk3fxZ1X1UtPfHleuJGrfgOJvxCLdoTLfw9G97XvrFbT2Ve4ADM0cZoLN6lBM94CSFA0kiKK+eqcT0pWq4fYgVfIAum2pwsXqbzmfHE17EMK6Zx3PgUAGQBzd12clNda4oOWeBwCtJNLikVF99HJgkGAzMmufK3pyQnc9f11/PUyy/z9R/9CFmWg+wdOnEBHoDahmYWzpwc624cs9jRUpwguKRQ4prNgm8Ww1+rBSk6mGoG3dpt2Bgc6AMt+Z59QRFnnlfIpPRxQ74PJ4gnHEIR355/K93e8zhmo8zEHCsT2Yq02PX9hvq9tDbDoSrYvEEghCA7sYfWNrCmaRGyQDo8UAWqbqnkfNRa07y393WMUCx0akW4tzuQGlcltb67sgC3LPAUsLs696kuwOPGV75v9zn5ev6VpK1UIvyUBiO7URKQqRY1kz2LVUOyIXKDbTSsx+5nwPNeet6LSK9KRNMd5azSPmSnYN0ewQkqqsSqxVOEFwjXZ0rEtzeSJFGek8Cuhr4BAW5O0LIkxckf32ngnruejFif44ws5596Krf99rf86e670WpdhqdvnHMOiUYjDzzxRNSOGxfgfhBCYHc40OvjlygWdFt6ScblUvHNEgmzDl6sF5Qkwg4L3Dpu8AXqOdB7DhhuweCuQKjRSOzq3Me45DFYbU607yv37fL2JXQTSpn0UMV3KPgTNe7rNDN/HLuS9lFcCm7p19creOd/gnFOK+17BbIMCYmwq+ewpTwDJmeMG9JWNM8hkm2MNGqtk20kkU7vwPMsVS4NOllQknHFl993JLLmeAs+7zaVinBv/3LPfo4IU46HvfVIUvvIHVMB/lY83O80XxxJIryrC8wpUWl6CN6WcDW4n2EJmF5iYmNVDwuqqhBC8KMdgqpeuPKiyyPb4TgjyhVnn82syZMHxLebi047TXU+cDXE1aUf2jq7yUgdgTdDHJ8cqm+i7NTL4e2fAHB+gcT5BRI/2i5zTh5MSxlqwfAW4QATDg8at04Dm93B55treOfTvbz/yZv0Wp0UGQRl3TIVMlQIQbEAteVv3C/1UIR4MJQMeoHEmaf48x6UvScpnmi1kJoGM2ZLDIjyPkFrM9QegqrtJtY76zAlainMNVLQox+SEjGU8xhpwvEHj4Qg8SeQGoWZomnpQJ9P1xNv67fSapbhiG/3/kqul2c6TKXWb3/XMlwhqeYeWXqcmE26qIt/Nc9dsEw6niI82q4oSrJFhUJnp/8UhP7OJ9SKueG8o21vbUbYZOZa2nhos+DSWRJvNEKzFf45S8J04okhtx1ndDB1/PiBf2/Yvp2Zk13eDxPHKnN1DYW4APdDdW0jpUVx/+9Ycai+iRmTKzDe/BLWB88d+Pz7YyW+vkFweq6gKHG4CHdjWDGNni/f5aM93by7vYOP9nRTnpPASSddyLcvuIG0p6/lo/ec7JEkdmrgv5KGdgnGCqiQBRVCUCGD0sX+mjX2oC94TzcStQN8KAOd96CsNCNDaytkZA29tomJEkUlcNLUwfYsvQ5qP1vPvi4jHx1OiZigFxSk2ChMtZNvdmCccXzI5xRt39ZoZUYJJtC9773nc9sgUpiVMmip89c/f8JbSYBvJNyuAh1nNPh+q50gNbTYyMsazBUU6gRLSfDiSGTkiUaAbDREeGcH5A/PIhuUUEV4OEjA1BRYnAHnfCHQAH+ZIdHwroPyH45oV+JEmatvv50vXngh6seJC3A/HKxp4KTFs2PdjWOWptYOsg/nX/cU4fkJEpcXwYP7BL+dMjxyvdMu+LAN3ntoI192unzFT8iSuPmGyWQvumdwwx++TPm7q6h9s4fpwHSgXw+NaVoa0rVsTNfSkKZBJ0Nuu5O8DpmyRgdZ3S4f0eNPSRrW50Ai3HvgCjZAKnE9UILSbB2etDZDds7wz73bSE7SDcu+0md35SmvajfwaZUJ+8E6jHoN+TlGl7U810hV/0FVffd3/EigNGhSKe576i3ElIqhVpLIMjl8fvfGJ5mKikFFo1y3r+NEgmBCN5qZVjx/G40tVgpy1Ve/8yZSwcBK88gH68toF+Gd7YKJk0LLgBKsoFKkEYf//LBc4opi6P7AgfTRiBw6zggjRug4cQHuh+6ePlKSh4usONFHFq7HX6MZTIPnKcIvLoQ3muCKDQKBwC7ALoNDQJcD5qXBiVkSt4+HlMO5rI2e4vsw5atfZZ3mpIH/J9ihtNlJabMTcP0IO5MkGtK1NKZreWlRIhNrHMzfZeWJLTYKphs5WRYEW9gMJfjQe0DzHJCDuRv4Qs0A2dYqmDB5cFBUI7wS9YLyTBvlmbaB87ZaZeqbrdQ09PPuV7XYbKDTQXqmRGYWZGZCgoI0ZL7OIVKi0LOdSFon1QogGQmtRvh8BvyJbyXHiJZIOVLTEHoHlO6uk5k5JXpLzb4INPnzzBKipi1/RCrVp3v/SIlwux0MxvBSEPpbcYnkM7+vx2XxTtO5jD65RjhyElbGUctIVX6JC3Af9FttJBgj79MbRxktrR1kZ6QN+9x480uuv4G/dnVxqL4evU438Een05GRlkai0aj4WL4s2W7W/a+XtF5BWq+DibUO5u628cEUI38+JZkMi0yzXsNSqzOoAPeHEmHuaxAOFIAVCex20OulsMSt57kZjRrKihKxmuvIrnBNqhx2QXsbtLbAwX2C/n6BRgPpGRIZmZCZDUlJvnPzeuLPwh8O3m3585+PFG4B0fG/HZgKzUBnwO39Wb7dRFpsRysIbzTFBlitYEpUGwESWwK9A6I9MfInwkH5BFaI6NoZIynMX6wXnJ0POh/ZU8pXv6q6vThxIC7AfVJd10RJQdz/O1ZU1zdRnO/DB8KD9JQU0lOiGyTrFufr/tcLQJJNcMqGfhbtkNhToCO1R8aUqQnUREgoGcCiIcInpJbTb3WSZWpmQmpeRNv2RqeXyM6F7Fxw2xucTkFHu0uUb94g6O0BSRKkprp80jOzXBkTfInyUILQQhHV0XSZaJ0znbxuR8BjeIvvSPp1jySjSXy7hWCscmqHYj32l4sffIvvaEyi/LWp9Hz6+yFRhadNpFxqfAnzQL+fHofg7WZXsKU3cfF9dBJ3QYkhVTUNTJkwJtbdOGY5VNfESYtnY33w3AGrdyw5/pSkAREOYNdJrK8wcN7HfbDIt9+oZxo5N/4GJX+DvposCOHi7kNdo5WCXOUrCN74G+T9nbvPc0wEil3/XFXcS1enS5Tv2i7o7nYJpmQzZGa5rOVp6QykmPQ8F1/4G8DViPFIVgn0zN5T36WnIMX3wrYvwRUt8e1LoERSwI2E+A7WX0+R2GMBkynqXYoYasW353cjNfFRIsI72yHFTwaUkSaQP/nqJpidCjlerjJx8X30cs2FF47IceIC3AcNLW2ctHhWrLtxzNLd04fx8csARpUIB/hSA0/qNCzZ2M85XuI7UBaUQINRqD7HkRbfALWNVorzQwtGUzu4K/FxffXQYRchA5y10HW+QggsFmhrgYP7BZ0dIMuChESXKE8s7Sc/24BeH9rqRDAR4/nvcEq0ew/2DV16ZhcNTvR8iRi1FtpIpck8EvO4KxWcHe0u16dY4uteu3/fvorvuPfxRMkzN5p89js7IC0t1r0ITFWv4K/VgvsnD30+RsOYFCd6XBUX4LHBKctISEMCAOOMHHa7A+3ejwcSchtWTENsuTNqJX7LV786JM2hJ74KN6QerlRYUWnEIQufPyBv63ekU45F0/+7rsnKvOmu7DNKKk+Gm6tcDW6LvyRJmM1gNkPpmMGBsa9P0NYC+6t7+ejLdhwOgcGgIT/blX2lIMdI+LklhhJJq2K/QyJRL4a06elXq7byqCdK0mSCb+u3mmqSSrYbSQLdH7fobW+D3Oh6XCnCn9VYSYn2WAjrcO9pZ4egsHjkJj5KMhJ5pjdstApu3Cq4tkwaUnciLr6PPXbs28fHGzbQ3NY2kCTCjSRJ/OTqq0NqNy7AvWhsbiMvOyPW3ThmOfh/V5MvpQ0XAuI9kJZF5ZjeucbduAWLpxAfJ+Aih+BRvYZOh8y5TjFE2CjJgext+fU1wCrZJhrY7DJGgyaoq4bSwVeV64kC/FkDwZWrvLAYoJ0TFrgEijsDS22jlY3bu+lrSkejgZxkOwUpDgpS7KQmOAkS6xkQXyJPrb+qU4ZA1bH9ie9A7idqK/+pFd/hbKuGaKYiBOhoH5r1ZzQzGoR3pLBYwJTs//tI+uSrrbTaaRfcsEVwXoHEmXlx8X0s89wbb/CrJ57wGzQcF+ARpKq2kZLCeADmSOEtfGtEGYVSJ+AKsBwyqMdAhMOgEN9tEfx2vUytBq63y1y8TIvWQ7l5Chg1YsSXL/dICW7PAc5qlTHq/YtvT5RYfqNZbESp/7s7A0tZkUu4i607ccjQZNFR36XngwMmOvtcyy0ZSU7yU+wUpNjJMjnQjuAiWLNFR3ay7/zfI0G44juaRCNtnpsJqeW8Y9uDwTA6BHigTCKjSXxH4tkQIniWoyHbh3G+avatnz2BW/60g+My4fKiuPg+1vn7K68wf9o0fnz11RTl5g4rVx8OcQHuRXVdEzOnVMS6G8cs9SKFOdKhgeA07xenNDU6AjwY/6kXPFYluLJCw9n5YPAyV6qp/ued4zdcsa3ESuRPDHtamWqbXAGY0bY4RopQglClyqXotq49bP12MBvX/rKA9l4t9V16NtUn0mzRIQQkGeQBUZ5ndmDU+baC+FoZCHYdPZ+Z+m49+R4BmEpdWwJVBAzX73s0EKnn0N/1lIUgxZAMuHzvY5UJxRtPd5TR0B83kZqUORwCnS7wipYnwYpLCSFosIJVhtRlk0gyaknUa9Bp1U2s3tnWwT2v1nBVvsS5+YOfx8X3sYvNbufSVasoLQihZGsQ4gLcC6vNToLREHzDOFHBhhaD5CqE40tYGKeOTD88xdHG6h6e+GwPf5ouUZLo2+LtiZJBKhzRHcqArCQrQW1DP4V5ygMwRzKrgj9CFeEwdFDXSJBpcpJpclKZ3z/wucWqof5wZc/Pqk3YHBI6jSDP7CA/xU5+ih2zUR5wYQk1X3h9l575JT1DPvN1faMxMRqt1u+RqOLY3mEnI3XoMDiaRLg/jkSfb0+6OqFO6HFXYfD1O/Z1/naHzO6Gflp77PRaZXZ/WsUOC+zoBr0GTFro3bKdXif0OaEoEWZPzmBWWTKzSk3kpxmGWN0dTsEjb9eRkaynucvOuzs6eOSysVRs3zuwTVx8H9ssnTuXTTt3smR25CujxwW4B13dPfHqlzHEIgyYsMW6G8MEid0hU1xgYtxZsVkZiWS1R18i3C046pqszJuWqqrNUEW42kp/0UCJpT/ZKFORbaUi2zrwmd0JDd166rv07GxKoNvq8lXJNDnJN7tEeZbJgfbwtVEiltp6taQnOYd9Hu1JjpqVm6ORhhYbudnGYb+N0SLCfRFJ8R3s+Qz12Qs22X9nrwGtl/93sMn0E+838NcPmihKN5Bt6ydBC2WJcF6+xKQKyPZKE+gUgn09sLG9nfeq2nio0yXSr1xRxIXzsgD44kA3a7Z1MqvMhCTBM9+ZQFqSDtt2Vxtx8R3nhssv55u33caMSZOYVO77nZCRqm7cdBMX4B5U1TZSGvf/HlE8X3D791ZR1tOHcfpEYLh/uPuzaL0UfYmR+g4bz33WQrIxuN9XID9TCM0nOtIiIFBqO5tNxmgcOcdn7zRravcLhVBzeLtXYwwrpqHXQnGaneK0QZcRWbhEtLcLS+LmjRRMnE6eZQf5ZjsJ+uEuLEK4Cj8ECsIMRKAcxkr28+ZotH57tut5fk0tNirKXEYXXyLc/fnRRjBXKTXPgNr32itViTgtNvQ5yn1p23sc/P3jZl68fqLLiq0wK9ZUYPyD53JhoYQQgj09cMObNUwuSKSyyMQbm9q5dFE2lyzMHtLmSK20xhn9OGWZzNRUrv/lL/1u89VLoWmSuAD34GBtA4tnV8a6G8csh+qamDZpcLDzFxg5UrnB393ewc3PHuSc5VNYtWwS0uTCsNrzHsjVFuaJFL4mBFabjMEjb/ZI+oFHo6KnL7xzeCvFU9h6Fs7xRCNBlslJlsnJVA8Xlh6bREOmgVrnRNbXW+lvbkKngexkO/lmVxYWjSRIMcqK++OPQP7g3tv5YzSI72jjKcIbW20snp028J2vCepos4ZH+rcZTuXMUMQ3gLNXJsE0PEbB0wrued3f2trOceNTVIlvN+5xRJIkxifDBQXwv9f3kHnRZNbu7OLGFQVRS3Mb58jnl48+yqZduzhlyRKKcnPR6SInm+MC3IP2zm7SU82x7sYxS2NrOzmZaUM+c788vQuKKBHhew4eJMVsJjczM6T+zCpLZvrEfBpauikvDq2NQIQyqCsZeJWKKM/jh1sBc7SgRHwrxZ+Y9SfCfWEyCMq7v2DcXPc9ycPhFDR99jF1XXo+OmiiplOPzSnx320p5Kc4yDfbyTXb0YcQbH+0upQEeqbDEaN2u4zBMHTVx9cE1fPfo0GMhyPClb4foun+JJwg+QmQ9OWKcqjNxvi8xJCFsqcxp9IMP94Br/zfdr65LJ/sRfeE1GacY4Ovtm/nliuv5IJTT41423EBfhi73YFep1OVFilO5HAnt/dVAMl480uwZhUAW9fY0c7XYdSA/pfnIAE1/XCg15W7NU0vkaSFjV2Cz9rBKeD/KiWm3fGy6j6lzzuJv8yW+d3fP+KSHz7Lg7eejpTZrWjfSA/SagbbUAbO2sZ+CiMswJUEfkb6eEcCOq1EwaLFFOC6V+/vS2ZMhpW0BCf13Xr2tBj58KAJh1NCrxXkWdrIzzGSn20kWRBWzvJAjFbrd7B+Kcnr7AunLNCE4PdzNLmmhDN5CdX67S+fsve2bhEutq6lvsPGtEVXqO+kB24RPj9d4j9zIUkLydf9Maw24xz9lBYWkpIcIGF9GMQF+GEONTRTlJcd624cs7S2dZKV7j+QoXz1q7x46zk8vF+Qv0dgk8EuXL63hQlQlgTpeonafkGPAwoSJJ6fDZ93wI1bBffdfg4L7vYvwsWWO4f83z2o67QabvrGcaTlC66+80XGjknlluvnoA9inozEsnW4eW/VCKq6RitzpqZE/Fie1yCaYjzYtQ7FYujPpUOtlTlYJcnGgw0sMu/GoBOkJlqZmOMR8DnhOBpbbNQ3Wdm5r4cuSwV0tZCW6MpZnm+2k5PsQBdmatrRJr5D6Y9SIe7errXdTma6/1SNIz2BVIOaZ9nftYyF+AYQVoEmIfDEx9MCLlUupaFzFwU5Oeo66QP3qmn4LcU5Vrh01Sr+/sornDh/Pnp9ZFO7xgX4YaprGxlbEvk8j3GUUV3fRHF+4NdiVa/gskKJb5T4fnn7EkanAuY9Xfz0pWr6LzoXgzEZvV6PQadDr9ej1+kwOJrQayX0WglDehYGnRb9/1aj12npEz3odBp0Og3HLSrk7feqkCRJUWBlIEvZaMuzbbXJJHgFmqoRrUqCG4P5wPsT0YGusZpJjuf5KC2h7h3gGEnx7cZulzHOON738YHi/ASK8wfTQwqRT/sXH1HfrWdHUwJr9+twyoet5WYHeYeFuWd6xHD7eCSh9HwaW6zkZQVOOTtaRHik3U3U/K7DfT68g6ydFoHW5D/Y21dMSH2HnbysrLD6ESdOKDgcDiw9PVx7552Ul5QM+z5eCTMC1Da0sGRuPPQ5EoQSJFlT38QJC2YG3CZFL9FmE8BwVRFIGC2uSOHNW6bQZ5exO2Ts4+ZjtzuxOZyuv3etx14yHZvd4fre7qSqqw6HQ8bu0GG3yzgcrj/fvmIaUzJDT0c4ksJb6eBp8wrA9ETt8r6aLCNKxXMkl/p99UvJRCNavtV2u4xepy7zjCRJZMxbQvrWtUz2SNpkdUg0WnQ0dOnZ2TiYHtFtLc8zO8hJHupbfrSJbzU0ttiYXBF8aTnWIjzavt5q8b4WvoqKBcps5OyR0SYPf+b9BWP3Wx30WJ1kpqWF0Ns4ccLjtoceAuBAbS1fbd8+7Pu4AA8TIQROWUYXwRKjxzpqRXhndy+pZlPAbYwS9AxPlTxMHPkaePSH//hk7GkD/3QNLhJFDGY8cQ8m54SYrWO0ZVHwpq7JSn5OYP9vtS4co6FIjxqikfVFyfk3ttjIDWKFVYpRJyhJs1PikR5RCOjo19LQpWNXs5EP9ptwyBL6jBxyswzk7bWQn2Mk1Xzsxb80t9nIzlC2pBwrER6NCXs0jQBKUoo6e2RWzbaTZPL/vLnfl2LrWqob+shPNfiMD4oTJ9pseFl9/JhS4gIcaGnrJDsjtETqcfyjVITbHQ502sAvVyEErzcJriz2/9IOR/D5Gly9BxN3YFCwbcNJqxepXM7+8GWhrm20UpgXPAAzFBHufazRzEimXnSjZPITDpIE6YlO0hOdTMr19C2vpKnFRn2zlQ++6KCjyyXaU5J15GUbyc8xkJtlxGg4ekWPwylUrz4cSUSqkqp3O+FMRs4q7ePdXTKJSb7f456GCndfN1T3UKmz+tw+TpwjmbgAx5X/O16AJzooEeH1ja0U5Ab27/tk40asMhznlQ3QLUCVijylA4c/S46vFFn+hLov/Ik8tcLbcz+lItw7D7b7mtU29jO7Uln6zVAyThxJQjxSIlzpudY3W5kwNvDKTzQw6DUU5SdQNMS3XNBtcVLfbOXAoX4+2dCJzSaj1UhkZRjIzzGQl2UkM10/LHtIOIVcYoHDIaNTmQEl1q4o4RLruJOBrCaCIXE03nj20/bWZr7cKTM37dhanYlzbBAX4LgqYK5cOj/W3Thq8S6m4y3Iq+ubKC7wH4DZ19/PvQ/cxY1jJTQqlslDHSxHsjIjhC6+1eCv2AaAtTkd455duJODKRFPsbAWjxShprULhS6Lg5Tk0eH6JkkSKWYdKWbdkEmBwyloabPR0Gxl/Xtbae11VflM0AvyzHbyzHZyzRrMHsWEYjnpUhLc29JuJytDvevPSLqSReL5i9QzHMgKflZpX9B3pvsdabcJskxmJqTmBeyv+53oFIIvO+Da0nDPIE6c0UdcgAO9fVZMSQnBN4yjCH8VLP1R29DM3KkT/H7/0E1fozIFjs9UJr7DsVIpHUhGE0qs4H4t7w5X9gxPlPpvqxGqo90i6otQJxmKC50czoccC99rNT762h3ryAVygekTBz/vs0s0dOtp6NaxtSERi0fQp0uUO8jdtA7jdN8ZXkYKXzEYkfS9H22oWRUbCdzvzAmp5dQ09JOd0Qv4f2+4xXfNGjvbJEjRaRj7s/+MSF/jxBlJjnkB3tPXT1LCkV8BcLThT4T7ckex2hwYjb4Hw4P3nMObTfDCnOiIFKXW7nCE92gOwKzv1pGfYh/2uRoL5pEorpUSzUlGe5eD9JTQ88pGcxVCSbuJesGYDBtjMmyD+3kEfe5rMfLxQRP2jZvRpmeTnWEgL9vlxpKRrkcbQhGcYPibfHunBG1osTJzcmh576NFOIHL3qtooYjwYM+T9zshmEuO5zvTfd2bW21k9exBbO0ftr3nObgrH3+slTjj65erOIs4ccLniy1bmDxuHKZEdavhajnmBXh1bSMlcf/vqOAtwn2J757efpISfU+ArA+ey2uNglOyIVXvP/Wg56ClxvqtRHz7E96h5Kx24z3Q+Sv4Eml8DbC1nQYKfQjw0U6w6xzpSU80Jhn1UQ7ADJVwRL2/oE+H3E6LRUfDQT1fNoyltcOOLARGg4bcTKNLmGcbSUnWRnVFwG0Nb22zk5kW2aIaoeIdm6GUYO8MNSJcqlzK/z39Idv3tXLzcUlU5Pl/N/qaKHi7ofgS3wBNu/YyPd/ht+9u4Q1gB77IzOC7ixcrOoc4cSLF1bffjkaSKCsqYmpFBZXjx1NZUUFFaSnaCGbLO+YFeFVtI7OmhJ7XOU5gggVgHgpQgMcpBK82wm8mR35ADkV8KxF1o9naDcNFeF2XnpmFvX63H23pBJVOsDy3G633pL7JqigPtT+OpBR1Og3kpTjIS3EA25CWup6pfquTxhYbDc02du7vocviAAHmZB15WS5RnptlIDFB2aCnJFByV+c+nCIRrTZ2gX3hXmelE3al7mkNLd08+fKXXHfJQq75+0bGZ2uZWZLM7DEmZpclD5sU+RPh3nimEwRo60nD/PEGX6UchrHvx7cw7p13KMnPD75xnDgR5MEf/Yid+/ezY/9+PvrqK155910kScKg1zNp7Fimjh8/IMrDqdB6zAvwptYOsjLTYt2NY5ZD9U1MGT/G53c7LWDSwvjk4NZvJcIsVHeT0SrgPAnV77PPLpGoF8E3HAWE6tuvtOLmSNPUauOEBaH5IR/pAbBuAZdg1FJamEhpoUepciGw9DhpaLFyqL6f9Vu66LM6kZDISNWRe1iU52Qa/BaQCoTDIeiTeyJ5OoqJxH1Tu1qm5N2Ql2XmnOVTOFDTxn8fvYKv3vwfG6p6eOC1WhKNGm4+tZDpJcOz9QSa8HiLbwCnkNBJvt83ntZvgOdef50rzzsvYL/jxIkGJy5YwIkLFgz8v7mtjR379rFj/372HzrExxs28Nwbb+BwOslITWXNk0+GdJxjWoA7nE60GnWZNeJElsbmdk5cNMvnd70OSPexShxMfKvNYuKJv6VTz0EkGhbhaLmhBLJg25zDAzDVtjESRDr1W6RK24eLUxboQrDCxtLvO9LH81mZVJIwJ+swJ+uoKBsUfbIQtHc6aGy2sudALx+u78DukNFKrjSJuVkuH/Nx6WPRaiW/97mjHVLT4+98b865oIS7fvk573y6l7MmpHL8hFSuX57P65vaueVve7h1nMRSj0B4A/7fhRNSy4c9T7IA0dgBPhYzvMX3NglaOzo4fs6ccE8rTpywyc7IIDsjg+PnzqWlvZ1NO3fy5bZtrP7gA9o6O0Nu95gW4EryTx/L7Fu5KuD3Rcv1qkvOeyKEQBYCrZ8KZw4BOq9xMpD4Viq83/hkaDLx0xa2Bu6n10ASCTEeyzR+7mPXd+nINzti0geljHTe5ZGqWtpvdca0yM1ocStSM7nTSBKZaXoy0/RM9vAadDoFLe02GltsbNphoaXdhtMp0OtMZGcacCa1kZ4ByWbQaCQ62iE9fXhgZrQZ7asWRqOWB25ZyVU/f5HKK0opz0lAo5FYNTOD5g2HWN8hhghw21ubMQATKpcO+9145/IGaBOJpFIy8Lm36HbjBJ7Uabjh8ssj6m8bJ04o1DQ0sH7bNr7cupUvt22joaUFjUbDhDFjWHXCCcyaMiXkto9pAR4vwOOfYOLbjdqS8560dnSRle4/E4FdQKAV5lDEmbf49ofSQTkc63CkgzH9LTV799F9zNpOPYWptmHbKyXaftaxKnoyEiK8odlGXtboC8AcaSIxEdBqJXKzjORmGZnmkSbRZpdpbrXR0KKjab+N3Z2uwM+WNjsTxiQhzEnkZhkQQkQ9FeRoF99unKkd3Hj5Yn70nw38/RuFJB6eJE5MhrUedoqaNXaKluuHiHA33rm83bQIE1mSZWB/f6zWShiBU5YsicxJxYmjkpfefpv1W7fy5datNLW1YdDrmTJuHKctXcqsyZOZMXEiSRHIkHJMC/Ca+mbmz5gc626MOpSKbzehivBDdf4DMAHs8lALeLCql0oKQqjF32Di2Z9IumhE0xUFhl67ui4DMwuVpVf0dY6e/p9HQtDjaKK+2Up+707EVtuIWqNHi+V7JDDoNRTmJVCYN7TGw9Mv1TFlfDJNrTb2VvXS0eVAIEg0asnNMgz8SUnWhS3MoyG8o5016ayTJvP5lkP8+hMnd1y3DLF1LVPPrGTf/Vv4yQ6Zk+ucjGdQRBfhEuGe+OpfCyaKpM6A4vsVrcQbWok77HJM8uPHiQPwi0cfRZIkFs2cyY+uuorj585FF4XVmGNWgAshsNkdGPTH7CXwiRK3E1+ILXciTb1T1bEO1Tdx/Lzpfr/35YISLqctbB1mBX/jk8yAbij+BjtPi3OoItyXK0o0B1jPY/VHKQAzEkv7R3LJ72CIrWup25lK5XjHwP/dREsgB2s3FhbaWE0GJIlhgZ8Am5v20tEGOxrgkx0Crc2VoSYpQUNOlsFlZc80YFaQKvFIsXj7YnfXfn567YlcfPOz/OedbZx90lLMW9fy7GyJj9rg180aJsmCyxyCHA4L8TVf+h0b3LSIZGZIdbR5fd4PfKWBDzQa6iS4xyYTdwyNE0t+cvXVrN+6lfVbt/Lxhg0kJyUxY+JE5k6dyuwpU5hUXh6RCeIxqz7buyxkpJpj3Y1Rh+dL1L3MGC06unpINQ+PrHfj8HBBiWRlN28R7i2+fUXvR5NY+IPbnaDThC++A2VBGGkf29GCknvZa9OQ7FG6PZJte3MsWb2DYbXKGPz43huNErn5kJsPrjx5vUxILaen10lji5WmVhvb91jo6nFNnEyJWnKzjORkuizmZpMWtq0bkfNQM0lX++50/14f/NHpXP/LV9h/qI0bZwmKV03n3Lc2M22bzO8OOPjBWAMrNYJznYIkho8X3pbu1ik62rYNpjzdIsH/tBo2aaBCwEKn4MF/PYvZ5H9MiBNnJLhw5UouXLkSgD0HD/L5li2s37qVP//73/z2qacwJSYyc/Jk5lRWMnvKFCorQktlfcwK8Oraxrj/dxDUiG+11m+Hw4lOqwk4i9SvvIGG/zyBdNI4RW2qcT/xZfH2lcfWHQ8IqQABAABJREFUuzqb9zVRYwVX41scihVczUBb360nP2VkAjDVCvFYW7+jPWGQhcsK602gZyfUCZpS8a2m4mckiNWkoLFVXQn6gWe3pJyxJUlDvrP0OmhssdHUYmPbHgvdFgd0pWMyyOQkO8g128lJdmA2yj7vd7h4/9493xehGCy8n/uK0iyee/ASbnrgNZ7olrl6WR4A45brefzmV3kkaTkfTzRyTY6Wy7VwkiwCupe4cQL/0kq8p5W40CG42iFIAcpXv6q6z3HiRJuKsjIqysq4dJXLO+BgbS1bd+9m8+7dPPXyy/zu6af58qXQ4uCOWQF+sKaBZQtmxLobRwWh+H/XN7WSnxM4IPLkRYv434cfcutze3jgojIMOv8RmZ7i223dDpbdxBO3+PZn/XYPLKGsCngKSrUiHAL7n4eK2gDMQIJJSfETODYs4koEbEuPjswk/5OfWLov+ArWjeYxool3/6XKpTS2WEMKfvX17CYn6Ugu0VF+WJi7j2examiy6Gjs1rGtMZHuftd7K8ktzJMdpH+1GTNWJClyq3uRXCV0k5aSyO3fXc63fvwM3zzOFa/jft9f37sGS8bJdJqMPJ6pY029nV9l+H5HW3V6DA473cDDeg124Fc2mbTD38fFd5zRTGd3N7sOHGDn/v3sra5mb3U1+w8dwmqzheUbfswK8C5LD6kpoVehi+MimPj29Cn3FK775RLysGD9uM1vGwlGIw/9+Mf85Le/5fv/3MqDF48ZiMr3h6driS8h7hbavsome4vvQOWSlYjwQK4Z/lJ2+cLTGh6pQbauU8+0fGUBmEpQKsLBvxCPteUbRmZy0NClIz9lqKUwGhbo0eZ6Eivh7fl5w84Uyk+p9Pm90iqawZ6RZKNMstHG2MzBCa7trc30CD3NJNMoktkmxtKFayKQsNpB/gQzOckOcswOUhOcaEZR/GFZYTpjshN4Z3snKz3e1VabjVdOzmDmxi6WbrGS3iPD8iSfbbQlJdPRZ+EWg4bFTsGlTjGQDjwuvuOMNtZ+/jk7Dwvunfv309jaihAul83i/HwqKyo444QTqKyoYOLYsSEf55gU4FarDaMher7NRzLh5PX2xp/4BqgTqczQ1AKBs6jo9XruO6WXO1/W8b2/7+N3l40l0LTJ07/bl/D293+l4tvXubjxFBhKxaSvfLm+RHakrVt9dg0mQ2wrYI4GwR1plPjz13frh2WfcbsvxTI/vDejqS9KCdbfjj4tqdUfIyTfE4JIiXA3nu8Rk2THRDtlUvuQbfqEjuY9ybRNmsjuFiOdfS5patAJlyhPdrmyZCSpF+Y76nrZWd/HkvEpZJuVj3ne1/HbS3P58b8O8kXHH1g8axYnzJuHLMtoO/tI6ZXJ6fIfz7BZgv+azTj7e7jvl79k7tSp6k4iTpwR5vv33QdARmoqlRUVnHvyyUypqKCyooKU5MgZbo9JAV5dHzj9XZzwGZJNZbGOd5oFTuHy/9MC3elaErROwCUu/WZREe+h00rcfW4J975Ww7VP7ePRCYtISR6aWswzBWEg4e1v4AwmvH2Jbk9RHIr49sTzuKGWlVeK3QnaCARgeqPGCn4s09KjI8vk3wVltAjf0dCHaOAWsbGu8OomUXJQQgfjSnqHfN5vl2ju0dFk0fHFIRNtvVqEAJ1WkG1yHBbnDjJNDvx55/3r8xa21fTy0Jt1lGQaOX5CCksnpjA+L9Fv/I2v+z5z3wEemyT4bN8a/lZdzTOvvcYPvtrMOZ/08/LCROwzjMySBTsE7Pqwn6WLEziggde1GhokOMlo4hsP3EN2Zlq4lytOnKjzqx/+kMqKCvKzs6N6nGNSgFfVNjKpvDTW3Thq8bZ8//GgzGuNMCMFtBL0o6fLaeejJpnliws4sd1KQboRxHsgLRtsSLwHQHWrldWb2knQa+jsdfDtn7/ILTfNJDVlqC+np3uJUuENrgHHW3h7BhMFEt/eA7gSAerP2j6QV/dwgQvP40SShm69qgqYakRKXIQHdycRAp+WTE9BOFpE+JFEsOvVZ5dI1A+11AbLbx8O4aYSTdALitPsFKfZgcH3md3JYWGuZ1N9Iq09OpwyaDWQkTQozLOTHRSlG9lZ18d/vj+JPQ19fLCrix88c4CK3ER+sqqIvNTAAame5zAmSWJMElwodnPTWpnXtBIXLErgBAQfCIn3NRpqO2X65ybwAhJpXTJnpAhOkgVfnryCjABF1+LEGS08+Ne/cvEZZ6gW30IIfvvkk1x21lnkZior+HdMCvD6plaWLZwZ624cNVgfPBcYnnbKLVzPypN4qV5wW4WESSexV06nWXSiWTiW9+oT+esT+8nNSuakBZ+zZFYTGo2EpdfGgdo2XntvB9WHmjl1WhrZZj2ahCR2H2zhzns/Zsa5i7li3vABxFN8B1sqDkXkGFZMC0t4ex7XW3yPBLWdegpSR+540cbXPR4NkwBfIrrHpiHJoCz9YFyER5bGbj05ycomnv5EeDRjBNQI9qzDf2Z4TNCdMrT2uizmu5uNfHjAhJSYgim1m7d3JzI2K4XzF2Ry1TIrz33ayMWP7uI7J+Zzvvw+Gq8ZYaC+aCSJi50yP9NrWOUUpANnOgVnIlj3Ye+w7SfK7/DFy2+h1QSO34kTZzTwz9deY/miRRTkqPOSEELwz9de4/QTTogLcH/Ismvwi78MIoNbfDdbBdkn6jD6MO0VJEgsyRDcu0dw90SoIZXKRakUpDo4/tyl/PRamY076njn03389OH/odVKJCcZyc1M5hvnzGHxrFJ0Oz8E4PyvL+CynzxDi8XJO0+9T2JtKeecMQ69fjASWU0ZeX8Es3qrFdzex1QjvMNNL+ZNbaeeqQoDMENZoo+GFVyt8PHcXmlfoiGuvEV0fZeOfLPve+7rWocanBkJ14ojaQKgpJ+NFh25KlZ+vJ+hYKto3kS7YiUMF8o5K6YNTDKEENzy3EEmZxhYMaGEJouOmsQz+GrvO5hSMrho6QQ+rO7k/X29XDTXxPQiDYnrNgRNmVizxk4hMFmGNVqJM5yD7mzHn5I0LKjS6ZTj422cIwYhBB9++SWH6utV7eeU5YFATaUccwK8saWd3KyMWHfjiKTPaqWzq4u8w0szbvENcMbnrgev0iyYlgJTUyQWZzAgyH9+7TRu/Md+7uvRM6G0iFxz+4BI0Gk1zKksYk5lkf+DH962rnMfP7l5Hj/8xafoE/S8+MoePvyklm9cMoXiIjMLyqYEHIxDFRWeVu9ggs57oPY+XjDx7ZllJRoD+GgIwFRKJESxu41A9y2alk1PMdzwRTtFmp0Bt/HXRqTEsPd1CPfclbpLxdrnurFbx8Sc/iGfKe2PWvEdKzzvxd8+bKKpy859F5Ri0DnJmP9zJgLMc8XcCAEWq8S/10s8+nYL07KSMRlnYNJBssZJltRDNj1kSRYy6EUnDc3znSME3V7H95XRpK2ji8y4+0mcI4TZU6awcedONu4c/p4OxpzKSpISldcjOeYEeFVtI2XxAjx+8RTVbpxC8Hoj/KlKYJUhSQuLM+CbxRLZRpfAzkvV8/vLx9Le62RTdQ8v7+/m4S1WvrU0l7NnZZCg0/DwpWO47un9yIY+tF8/PuQ+rutM5/TrTqFmVx17vthH4/4mHnj4CwB02vfIStaRn2agIM1AfpqBM3qbKD3TVfLe12AZSOT6snr7SmEIvl1MfB0jHHeTcAM01QRghiOWImEFj7QojoVbgTf1zVbmnjQP9nyoel+lIjxYMShfn4V6DaJt4Y0kXf1aUkKoPuoPJfdiJKzgvjj06iae/Erw/PcnY9BphgW4S1PvhC13Yk4QXNa7h5OLBX88KDhohYMdgl84JTSJyTQlJbPLlEtXoglZ0iBNFqT095DYa2GjrZfvdXUBLou7v3SCTW0dZGWkRfV848SJFE/88pcjdqxjToBX1zUyY7KyyopxXNy8TdBph/snSUwxw6E+eLVRcMlXgnPyBSefPp6+9ftIN+koz01kzphkvrU0l601PfzxnQae/KCRa5blcebMDH7x44u5//EN/Oova7n1W0sDVsIMJOA0Wg0lk4u4fmUm9Q0W3nm/mo2bWunutFCYbmBMdgIlmUbqt9TxrSZ4cEYP00t8lzj2N0j6E9+eaQ7dAZ9K0hh6Cu91/xvqK3n8Kb7z5/rrU6g0duvJU7EMHw7xgMzhWG0yCUbtwIqOWoKJ8EhamJUKTLVtxtIK7vm6CbUfai3egQpqRYv/1AtOyYaMz3Yi+Unx6hblxqlQAtz54LnUrLHzklbiHg383NLJOEvnkH1kSaI6IYm/mM1MNqdTk13Mfp0e0+KFbP7fB2RnppGTkUZ2ZhqpKcloJInm1g7KSwqifMZx4hx5HHMCvN9qJ8GovBTxsYbx5peGWcHnpUm8UC94rk7Q54QuBxQnwJMzJF6sF9z+YjWdfU60Xv7flUUm/nBFORurLNz+ejNpE2eQ3i5z2VmT+d0//sdDf/uQH8xxWaTCGZTz85L5xTWuzCvV697ikz3dfLSni9VftVKWBFlGeO6VPUy/fobfNrxFuLf4dlu9PQv9AAPiW6lvt7fw9vzclwgPNHiHUrq8tktPoYIAzEiJpHBEeDQqZ/rqTzgWYDU4nGLYbyQURkPqvHCIhQi3WDWYDMEzoAQiXFeTkRLiDiH4byM8UqnuWTPe/BKsWcW5ToEeuM2g4cd2mbEeC2ZVCO5z9nF6ay9nOgUSLsu3EIKe3n6a2jpobu1g94EaOrosCAR1ja309Vtp6+giOzONrIw0DPpjTnrEiTOMY+pX0G3pxWxS7p9zrOItwr9WCBOSJZptLvcTsw7+eFDwZSfcOFbDD1dMpMfqxGT0XZJ15umnc3XSDl55dzsnzp3PuDE67A4n73+4jetmTMCg0wwMbuEOzMUZRornG7lwfhaWNzexuQs+bRfMTVM+GIUivr2Ftz+hHQh/ItyzT25C9Rmu7dRTmdfvY4/oEa4lPNICOVaW+aZWGzmZsZv8j6bViEj93t0EWxlwBWCG5voVaR/vaLul7OiGNB2MNamf7JWvfpV9K1exyinIFIJf6DUUV9uZUm2nMU3L5+MNLFvfT3q9A8kj4FKSJJJNiSSbEhlbnD+kzb+9+CYzJo+jua2THXuraW7bjN3hWoVLNZvIPmwxz85IIyU5KeCqaJw4RxPHlACvqm2kNO7/rQhPEa6RJGanDf3+zDz4vF1wVp6E7a3NmHwsRXsOrsfPGcP9f36fiuJKHn3+XS5bNZOvlXYOS3+lxCrlLrrjnevbG4NGYk4azFEovr0L67gFi/t4ngV+AJ/iOxThHS18XcfePXUkz5oB+BcW0bBOjmYRPlI+4PVNVvJzjME3jBKjwQfeG89nMJpW8cZufUgCXEnMSChuYdG0hn/WDvPSQ9/fLcIXyWB508L6CiPvTE8gp1PmzM/6yOuQB7YLhhACjUZDfk4m+TmZw77r6u6hua2T5tYOtu85SFe36/2p12vJSk8jOyOVrMw0stJT41bzOEcdx9QTXVXbyIKZk2PdjSMGX+4obiYkw98PDf7fV3Cgp5hONScwY2I+67ce4tvnz+O8FZVh9c1X8KP3YOlpaQplkPQULL4K+8RKfIcqVBwOGZ12cDJypLkyREOEjyT1TVYWec9kY0ywyrAjia9jqnlGA1nBG7t1TFOYelMtgeJHghENa/jnHYIrS1y/c6Mf/+9guMX1d8Lsi6W3D7PJ96qeJEmkpiSTmpLMuLLCId/Z7A5a2geFeWt7J3a7q3KyOTmJ7IzUAct5itmEJm41jxMl+q1WEoz+DSeH6uspzs/3+30gjikB3trRRUaaOdbdOKLwJ8Iz9NDpFcsXLF/1Ld88mX3V/SxfrCxJvRKCiahArhuBRIZ78hBIoERafHu7n/i6huGI5oYWG7nZo88Ce6zQ0eUgPSW2r9xYWrtDQa2F3J8I77FpSPbKgOLdnvfqm9qMSd7bqRHhatoOhMUh2NPjqjocqviOJM2tHWRlpKrez6DXUZCTSYEPq3m3pddlNW/rYOf+arq6exACtFoNmempLqv5YYEej/eKEy7nXn89P776ao6fM2fI50IInn7lFR577jk+ee65kNo+ZgS43eFAr9PG/ctCwJcIT9RCr9P/Pu4ByHNQa2ixU1qYEM2uBsR7wFWbW9lz22hWsPRVBAjCt1jXNlgpzI2dAI8EIxUwGWmEEAhE/P0TBkqDJr1/18FqYwzZNsK+6WqIhDV8SxdMTIbUW1+OUK/Co7mtg5wIpiCUJIkUs4kUs4ny0qGZVRwOJ63tnTS3d7Kvqo5Pv9pOv80GQFJCwhBhnpGWglYbLw4UJzjTJkzg+/fey9K5c/nxVVeRm5XF3upq7nzkEXYeOMDlZ54ZctvHjACvbWihMC871t04YvEW4X1O0ElglYXP6pe+qKnvZ8ak2K1ABLNwqc2xPZLl4yMhCGob+plSEbnVh1CIhBX8SBThXRYnKclHxus2Wu4nSsRlpIr5eFYQ7bJqSElw+vw+0HG8USuOQ8nZH641fHePS4CPFppbOxk/pnhEjqXTacnNziA3e3ihvZ6+floOW82/3Lqbto4unLKMhERaSjJZHuI8Hggax5P7b76Zy886i98++STnfO97nLhgAW999BETxozhn7/+NRPGjAm57SNjRIgAVbUNlBWF5qcTZziZBonZaYJ/18FlAQpYetJnlUlM8J0pZaTxJzL8DZq+rN+RxO1+4rZ+eweERgJLn5NkU+x/8koqUwZjNIlwJcGc9U1W8mPo/qOUWIpv7+38iVc16QOlyqU0HeghT+dAqlTvChErQrWG77YIFmeMHvHY0WUhNSX2MwJTYgKmwoRhSRhkIejssrjEeWsH2/dU0dXdAxx2aUlLOSzO08jKSCUpYfT/ho8GnE4nn2zcyOp163jzgw+496abOGXJkoHv161fz7OvvcaW3bsxm0ycsmQJ137tawO+2j19fSy++OJh7V553nnccPnlqvszZdw4fvXDH3LtHXfwxrp1nLJkCffddFPoJ3iY2I/GI0RtQwuLZ0+NdTeOKq4rk7hmk+D0HEg3+H/pi61r6R+3hETjyCz5BcpSEEh4+0OJ68nxpySF7AceSHxHCodToDu8UhHpUuSh4uu4akT5aBLhELg/9c1WKkqVFVuKFSMhvn2tGvlzuQongNqTxhYbxfnhub7FopplKNbwVhvEMNHOMARiVAdIaiSJ9FQz6almKsYMtSQ5HE5aO7poaevkwKE6Pt+0g/5+GwKB0WAgOyOVzHSX5TwrLQWDwfdzHEc97V1d3Pv44zidTpzy0NiNL7Zs4Ye/+hUXn346F512Gpt27uSfr75Kb38/t11zDQBdFgsAd1x3HWVFg/c1N1P9CrAQgudef51Hn32WNLOZi1au5IX//Y++/n5uufJKivLyQj7PY0KACyFwOGV0utFhfT1aKEuSuKAAvrlRcMcEmJk69EXraU2uaeinKMxB0JtApd/99cPf97EimPiOlPW7odmK1tzjtxQ5jI4APe8+BBPko1GE+6Kx2cSSUZYBxZNQxLenm4c/lPy2atbY/YpwdxuBMiwFo7HFxuypKT6/i3a2l2DvHl+BoN6osYYnaMEqB99uJLDbHeh1R67E0Om05Galk5s1PKdjv9VGS3snrW2dA1labHZXVgJTYgJZ6alkZqTS02sZ6W4fFWSlp/PGn/5EXVMTp1199ZDv5k6dykuPPEJhrms144R58+iyWHjvs88GBHhndzcAC2fMIC87PNfjS26+mT3V1Vy2ahXfufhijAYD561Ywd2PPsp5N9zApatWhWRVh2NEgLe2d5GV7vsFHCc03IPmt0slJibDT3cIVuUJriqRBiytngNPdZ2VCWPVWQCVCisl7iFq/DG9A0iVBmu6xbRSS3iwrCeRDASrbbCSGcZ7KFYlxJW4q4ymCYQ/2vu70etDt5SMNjyfBbXBzN4EEt9uwhHhff1Okvy4vinpezQn6Eqvm1JruFHjis+xPnhuzLOgtLR3knmUjrsJRgNFedkUecWVCSHo7bPS0t5JS1snO/ZVx6iHRzdu8e3GZreTlDBo4HNbwDPS0iJyvH/86ldMHDt24P/jSkt5+oEH+Nfq1fzu738PWYAfE2HAB2sbKC06ega/WOHvhV6QABoJnjoEKz4V/L1G0GUfmnqgodlKXhR8YNX4ZoczkLoHevdAGEg0HH9K0rA/vrZxo0SAhEttYz9ZWYG3CWZtFlvXxiQ/NLjEdTCBPVpTHDrsAu0oXnyL1T2F8J/9YH2XhYAwPCAiIb5tb22OmIgPZkSYmiLxbovr3euvhsNI0dzWGdEMKEcCkiRhSnL5ms+eOp7Fc8KrdxHHPza7nZqGBp586SXe+eQTrrv00oHvuiwWdDod37nzTuZdcAGnX3MNT//nP8iy+uWhf/z610PEtycXrlzJy7//fcjncExYwKtrG1lx3NxYd+OowDMbitsKrpWgX4ZTsuF/zfBsjeDpQ7C4t4rCdANLJ6Ti7GhGu2M3blmu1prqKx9wKMJBbWaCQFa2ouV6xZlQPK3jvsS3Wuu3WtcLS6+TxKTQlIj3dY6VNVwJo80lBaC9HdIzR6cfbDiuJ+GiVnwHCpD21ydX7vXR4ZsbSlYUXwRySTkvH56pgT09ggqTFFNLeHNrB5PGlcTk2HHUI01YgJQ1glnKtDvC2v2Xf/wj/333XSRJ4p7vf58VixcPfJeblcX4sjLOOukkrr7wQt766CN++9RTaLVaLl21Sl03g1hPsjOGZ91RyjEhwC29/SSbEmPdjaMGt+h0D6AFCaAFri6VODMP7twlmJMKWWYdf/+oiVRTEumpAZKGB8GXAPTEX5BXONY1z8EykhlQlIhvJagRmQ6nQKuRhuwzWgIx1aIkjeFoE+FtLRDGO3rUEe4ELNTfZaDfib8+NTZbyc0aPcVYoi3CE7USlxfDYwcFv57sCjKMlQhvbuvguIzIB5THiQPwrfPPZ+ncuXy6aRN3PPII9c3NfOv88wGYOn48z/zmNwPbzp8+nYaWFv7x3/+qFuCnX3NN0EW01x5/XG33gWPABaW330pivBpWxNi3cvjDq9dIXFgocccuQYoOnvvBFIon5vDqhjbml5uZWppLUdpQS7FSy5sa/0yl1uhQUqL5w5eYKFqu9/kn2H7RorFluAhxu3Qoce3wJtbWbyX9HU3uKG2tgrljymLdjYjiq3iNLwwrpg0RnN7Pvfv7QKI02PeB+tHYaiM3axSlBSFyLin+rsk5edDlgJu2CTrssXNHsTscGPTHhI0vTgwoLSjgpIUL+em113Lj17/Oo888Q11Tk9/tF86YQUNLC31Wq6rjlBcXU15SMuyPw+kkLSWFs5cvD/kcjvpfR3VtIyVeuT/jqMdut/P82efSopUwC5goCzyTNl37rWkYP2jiyncbePEEme+fUsB1J+WBJPHWbgMLS3uGtRnMkqY0ZaA/4R0su4KbQEu6SkW4kmP5Eh8jQW2DlaK80DPQeAaqxVp8uxlNZe2D9aWvD8ym0ecEHq7vt5r9vX9jvp79SPwevN8pjS02Fs5IC6mtaGdHioQ13Ne7K0Er8cep8FiV4PKvBLdVwLz0kQ3MFMHKj8aJE0EWTJ+OU5bZW1VFQU6Oz21sdjtGvR6jXp3x63c/+5nPz+uamrju7rtZMnu26v66OeoFeFVtI9MnjZ7l6CMJt7V7vwT36TXkazWUyYJ9GvibTsPM7TIXF0rMOBzonm3Wk6DXkJfqsrbqda4FlrZeLemJvl1QfIlwNVXoRrIaZSDUWrRHSnwD1DZamVRuCquN0SK81TAaXFGEEJj1yfHKeozcMz/EZcxWgXGE6g/ECl8iXKeR+N4YiVmpgkcOCNp2w6IMwXE/OYf56ZCkdT2P0RLkXd09pJpjX4AnztHHp5s2UZSbOyT/9s79+wEozncVW3zlnXc444QTBvy3hRC88+mnTCovR6OJzPugICeHc5Yv54/PPsv//fSnIbVx1AvwptZ2cnzk8YwTGLf4bgDu1Wv4lkNmoUcAcT+CjWk6frlboDEZMe3fjc0heOJb49BrB8WGU3ZlSAmkP0K1xEVSfIdaeS5UglkDIxnoaOlxYA6hDPpoDraEI8MKnk0p6akdUT/+aJhsjDZkAVJ3C2Lrnlh3Jer4e38typBYlCFR1y/4sBVeqhfcvRumpQiOy5BYZbGQkhx5odzU1kF2xpFTeTTO6KKqro62zk5a2tsBOFBTw4YdO8hITWX1unWsW7+e81esYOqECdQ0NPDYc89x3Jw5jCkqorWjg9//4x+88s47nLJkCblZWbz89tvs3LePJ++7L6L9zEpPZ8OO0INJj2oB7nTKaCRpVFfiGo24xbcAHtVrONMphohvgATg/AKJc/Nhb4+N/pljqSwykaAfOrts7NaRZw5PKPsaWDzFtzvvtq90f2oIpfJcJPBXudOf20egCYv3tk6nQKNR9/x7+/eOZhEejJHMEe6ds3xCajlbd1vIH02lCT0IN3/3aKetV0tGkiPW3QhIpIIyIbARoSBB4sJCuLBQwuIQfNYOf64WGD78kAtOPTUix/ekubWD3KyjKPI4zojylxde4L/vvjvw/8eee47HnnuOM088kbuuv55nX3+ddV98wbOvv06q2czZy5dzzUUXAZCZlsazv/0tf3nhBV5es4ZD9fVMGDOGv9x7L9MmTFDdl617hk/gHU4ntYeFfzwLih/qm1rJy1FfevRYwldQpZuPNRIW4HSnoFYCKzDWy7VPI0mMTwbDGN/piw51GChOC12AqxHDkRTigY7rbXmPdkClGpHkna6xscWmKguEr2ONZhGu1AoebJtICnTPtuqbrFSOH71L8bES4Z7PU7SO39itJ9c8ugV4pFFiREjWSSzNEjxe5SooEg2a2zqonOA7d3KcOMG4+4YbuPuGG/x+f8kZZ3DJGWf4/T4rPZ0fXXVVRPpy+a23+nQhFEJgSkzkVz/8YchtH9UCvKq2kbLCeAGeUPlMA60S/FSvoV4CA/CITcYdzucZeOjPknOo08DU/E7Vx46mFVqJxWmkXVKigdi6llp5BoW5wS2wwUTQ0SDCAxEtS3lzq43szOhnYTpS3E98PUPh5PUPRKNFx4RsdRkPjhaCCfHXGiDTADMmTozK8bssvZjjqX/jHAX4mghoJInM9HQqKypITgrd4HdUC/BD9U3MnaZ+ySGOi9//9xU+O+1MmiQoE/C4TuL3OokznILxYngOS19+zX12iSSDsoh4NYLXswiOP4u3p2U6WgFgI5lOMBRqth/gxHHdwHF+t1GTEnI0i3AIP/1gOL7UvkS8Uwh02rgLHAQP5I20Nb7JouO4MZaB//t6v3i+F0Zqwj2SAdi+DAn9TsET1YJfT5aiGhwcDzyOczSwatmyqLV9VAtwm92OwTC6BdJopXz1qwAsWP3qgJvKVQ7BG1qJx3UaGiWXH7hxnROTSWKcCb5bJlGQ4Hrp2t7ajLxsOkZdYPEdzqCntBLlSA54o41uq4aUBNmnP/nR6P8bCSGuRoQHTD/Y7yShpxmxdc+ITlzU9H+kngGl5x9JEe5wSoh3NmMLsM1Ir3KF+i4K57p4i/BNXa7iaZPM0RHIVqsNY3zcjXMM0NbRweoPPlBd3MfNUSvAO7ospKWMXt/L0YxbfHv+f9/KVZiBi5yCi5yCXlw+4VbAZoftWTqu3Sx4eS5oD1s+Dr5ziDzaYXqaz+Ose34TT1QJpqbAdWUSOo3EF+2Ch/cLBPDbKRJ5CYEHCbUWaKUDWaCBOZjw964U6gvvgTgcIeAvo4o7A40nkcj9PFqt4J5EyiIeShtuAVzfbCMvxfUsjPR1O5KzokRChDtloKnDVaJ3lBCuISBcEQ6ud8VuC0yM4tDY3N5JdkZa9A4QJ04UuVdFVct91dXs3L8/LsC9qappoDTu/x0Ub7GtZruBAE4BJXscvJ+hZUsXzDicfaqGNMZKrdjeqh42+Gw+1MNduwQ3lUu81ij40Q5BWZLgxTrIMEBhAkSigJ3ncd0CKBIDfCBxrWRSEEhwh5MZwXPfJouOnORjKwjNG28RGoqYDpX6Jiv5hzMAjZT49uzvaBLhIz0BqX97H5kUjNjxghGu+I7kSsXeHsHstOi5hzS3dpAVT0EY5wjl32++qXjb/Oxsvn3BBSEf6+gV4HWNHD9veqy7cVRT7uGeAlDeJfPpVzBjmeuxahBmFkkHgOGi8sUvWrmsSOLkbInjM+GZGlflNoBJyXDrOAldmD6EgQa9QCJ8NARfuvsQysDtvta1nXoKUwMtwB97eApSJeI6nADP+iYr03OVZQDyPEYkRXMwET5aUxGG0y/bW5tpFrnkSN0R7tWRjfudkm6A9ijWL2tu7WD65HHRO0CcOFFkw8svj9ixjloB3tHVE3dBGQE8RfgkGd7WSpyxxo4AnMs06KRBH3BPEb5vbxtnjj1cjU0jkWsUjDfBb6ZI5Bol+pyCZ2sFqxsF9VaoMMEdE1zfhSJK/WVf8B7kwxHfgfoVaruhWsNtb22mtuA4ThgXFyH+iKSbii/6+p2YggQg+zp2qBlZQj2PkRLhaq3gofTL/TtrFGamaBpU7RstRlsMyhSzxNvNgv9n77zj5CjrP/6erdd7r+m9kgQILZTQpQUUEAFRpKhgQUUQIRRREfgJitIEEUVUqlJD6CXUkN7b5Xrb2+vbn98fm73b29syOztb7jLv1+teyc7OPPNM2/k83+dbID5W8E5rD4V5OXFpW0Mj3lz3m99w6TnnDOUMX7t5MzMmTSIjXf2sPuOyRq/d4cRkHLdji5RjKGDTI2iWYI0O+s1p6Ov7aVjtHOEv7Vi1AceqDfS6INPPP3N1h+ArVg/O91385y0n53wmWNctuKhK4htVEpt7wekZbkMtYp0WN500b+gv0nqJpseuI8fsibziQU483DTcHm8BJGnOsqD32Pbu3REFs1oDAzntpKpfv9J+dZJJIf0q9yZ64v3c+35P5aznY0EOrO+GDT3yslNFi9vtwWBIIed7DY0oWLNu3VAFToDLf/lLdtbVxWVf41Kl1je3UV1RkuxuHFT4LOE/d3r4lVHHorx8pvVa6QZy8QYmeoBBIP0IA612qEwfDlg0GiSaJLAAz+l1XDbgYVqf4McdOpYWS1w/RaIybXh/alaQ80du/u9o953IvOaOVRvQL5+Hbh1omcDkEehqEqv4/Xz/bory84J+F03b0fhxx5oPfTy5o7iRRsy+JZJ4ie5IcSPB9h1sm2KzxMrp8LMtgkf272dKTY1qffR4PNpvjsaYprK0lAeeeoqmtjbysrMRQvDBF19Q39wccpuvKExVOC4FeF1jK9MnVie7Gwcdk1/9H5x6Br93eHg+K581bft5wqQjAygVUCeBC0j73MPZbkH7W8MvyGPdgr8ZdLyglzjSI1jsEWyRwAM4Wj3sb4E1mwRHnDAc4BgvER6OsbA/00nzaOnRAjCTiaUTKlUqQa+J8Oj65RQ6DCR25ieevwvRDN7lrjs50zsD+d5nn6kqwLt6+sjPDV4VWUNjLPDjyy7jhnvu4Z7HHwe8+ewffeaZkOtLkqQJcH9a2jo59rAFye7GQYnPEl6elsHFvd4iGK1AiwS1AvJDbDdXwO+cHjwM+0UtEPBrp4ddksSnOon3DBI1ftU3/Yn0go7G/zSUFVyNl2ykvOVqFfZp7DFSmRt+X0qOUalLQLwqTaqJGhU1fVg6BYsnqiPAIXoR7ttGCfEU4bFkQ5Hbr04yKZQS536SDIt3LGzvE1y3WXBehcRlK1ao2rY3A0qeqm1qaCSSpQsWsOqxx6hvacFut3PRT3/KLd/7HtMnTlR9X+NOgHuEwCMEev24dG8fE0x4+UWkn942FOJTBpTJnA32v2oSUCFglwQ7dXDpJB1VVcO+hYEvvsAXe+DLOhZRkSjLd2AOcaVW/sZuI8sm9UVeMYB4zyqkUmq8eNLbA4V56hYjifbcxXKeU9ESLrc/bSKLUqK/95Wi9jMT7yxMf9onuKxa4twK9SthtlusVJdr7p8aYxuT0cjkaq8XxVUXXMDShQspLSxUfT/jTqW2dXRRUhjKzqqRCNo6uph0zldiaqMD+Kde4nvZej4q1HHvQh1fr/K+LPyDHkMFuUX6LhL+L9RYX67+L1S5Fu7AwNVo6bHpyUkLPQ2fzFSL8co6kkp4PKALrIJ0gFiEcSLPXSzPTzjkCGmx6d1Rf3JpE1kUS4kT4KDO8yQ3oDIWdq92ss4iOKkEzNc9p3r77Z1WigvzVG9XQyNZXHn++XER3zAOLeB1ja1MqCxNdjcOauqb2qguLxmVJzwYHcDregkHXj9xmwQ7JImtOji1QuIP5RKTMoeFtz/hxMGW3a088/omfvzNo8iM9YAUEuplGqmSpo8GP3ebaKxsbo83+DKVg6HGsyV8cFCQFiFjVSzuLok+d77nTE2LeDBXFDXaN500D8urEgUMxNxWolAquoP9hoQa4PvW3SLBBAFF18cn1/HAoJ3M9LTIK2poaIw/Ab6/sZW5JyxNdjcOauqb2zllWmR/qUHgBpOOI92CfKBeB+kCDvUIfne0nnT9aOEtxyL36vvbuevRd8lMN/HnB57lJ6dWAqFLtociFsu3WpYsf5cUuSK8vd9AcQwBmPFwQxmvYjsYlk4oLEzh0Y9C4iHE44EHCX0SMqAoeW7UFN++5YEi3H/ddTqJ4y/6uqJ9amhoqMu4E+CDdjsZaeoFP2lET/+gjcyMtIjW7zf1EtM9gm+6R74s/V8g0Yjvl9/ZxnNvbKKpvYeHb1tB+v61nPeHbVyj62BzL7zTKdBJUGKSWPTCeqadNU+xD2SsYkSuFdyH78Uq5yXf2G2kMie2UnfJyDAzXrB0wpLJlWHXidWVJJlBranoH+7D4ZIwJjgDyoj9R1HBNl7uJuF+V3bqJM6aNSsu+x0YtJGuvXs1NGQzrgR4X/8gWRnqVyvSkI/d4cRsMvC47oSg3x9zcsbQ/z/SSXzVNfJlqTQLyEvvbOWP//iIm646gQXsIbN3M2+8to2JZsHd73h4Wy9xvFtgAL6Q4PF0HWLDer5yWAk/PLkiqn35DwRCCXG5+cSjQa4Ib+w2csyk2LNAHGwiXC3/6q5OQdlhoYWImn7carqj+PcrUptqWMNjyYgSirY+A8VSV+QV40w8n51oBu6BdElQVlSkYm+Gabd0U1yQG5e2NTTGI+NKgNc1tlKj+X8nlYaWdhp/8++Q6Qbfe93rm1l7SgZtEszxM34Him+5L7CGlm7ufuw9Hr3jPCb3bAL09L62nvv2CC7rcTMoQbmQON8tWKODXZKOfrtgUaHEXEs7IE+AhxMLwayCkUS4//FG+1IN94LvtunJTXOH3V7pACEeokkOY8ln3OkEszl4fHs8gijVODeB/ZJrYfe/F2K1iqthWW/tM1CxsBDW74mpHTUI94yq7XoiBwFYgaKCAsVthKO900qRFoCpMc4YtNv52wsv8Mn69bR3dSE8I42GkiTxvwcfVNT2OBPgLRw6f2ayu3FQU9/Uxnn/unXEQCjQGi6AZ/QSX3EL/CV3MP/FSLjdHm754xtctmLxAfHtfbk91QCV/YKFApwCHjDAjUYdTuArbsE1LsH02fLzicsRnUpEuA/fcUfzgg3m0+4R3vSNqRyAqYR4i2+1hLHbLdDrQ4tiNXON+xOLCA/Xn2jaVSLGfeupNahr7TVyWE3yS9D7CCbClYjvWIS3j368L/x0c3zcRNotVpZUz4hL2xoayeJXDz7Iy++8Q21FBTXl5Rj0+sgbyWRcCfCOrh4K83OS3Y2DmqbWDo5cPGfEsss8b44Q4fuL9Xyuk7jSEZ2vZrCX9b1PvI9OkrhoUi8g4Vi1AZcQPL3Pw0q3t30DYJMkdkjwK4ebGWKk9TnwJRmLGIhFhIMyIQ7Dx9DeJz8AU06/DgY3FDUFcZcF8vLDj35SUYRHatdHNGI8Gmu2Wj7lXYN68jPcpFIN2Fhd0dQQ3+B1P8mLY2yqxdqrVcHUGHd88PnnfPu88/j+RRep3va4yQPucrkx6HWqFxbQiA6X24PRMHpcd5nnzaH/V3W4mSXgXqOOhwwSDxgk7jNI/MkgsVVG/mtfXuB/PPIMH63Zyt1n5qHXSUPrv/qWiyIB1cLr8rLqrQEyheBap4eHDDpKjo/vuFMNa57/AKFquXHoD7wvZN+fP45VG7wBmAEVMMP1R4m4TtUAvFSgqxMKDqSMDSeyA4Xs9NzJQ3+pzPbu3bIHD8lwVRICQqRfH5OoJb4BDIcYKIswOIwFj/Cg140bSaGhAUBhfj7zpk+PS9vj5mlpbO2gsiw+wSUa8uju7Sc3OyPk9z4RrhfwU6eHw92CWg9M98B8D7iB+ww69ssQ4W9v7ebx91v5wyWTyEk3DK3XsNrJx3qJwzzDpp66UgO1Ao7xCEoF/GX/aDNQJCuVT3iE+gskUHwoEbr+ottH4As58HOoEvRqi/DxgtqWaEunGBLgkYgktl+sSx/xJ4dEFeqRK8QTKcJtTgmzIfHpB+OFEvHtP1gP/OtwQpEpDh3F6wqoiW+N8chxhx3Ge599Fpe2x40LSl1DC7WVZcnuxkFNfVMbVTLLEKcBJ3lGviyP8sAtRon/6iXODihC488nEyZw2wv7+ePFk6nMN48Q3wBzPfCsXuJMt2DRyRk8adLxE6cHCbj1CB0XrRUsKxTMyh62BoUToXKEhpzp/3hkRgnEOqgnL0QAZji3gFB9C3VekhWMqSbxEKt9fZCZ5f2/HGu2zx3Fd/+o0adoXFESIdgTlbawtc9AabZ6FuNkE8odTWmmqA5H/AR4p1Vz/9QYn1zxta/x9euu49+vvsqsKVOCrjNn6lRFbY8bAd7Y2sHSRbOT3Y2DmvrmNhbPVT5VYwCucXr4uUnHcW4BfiJcCEGrHV5tg2c+2cPvZkpM3bILxxbvtv4vqSM9grf1Ej8z6rBI3s/TD2j9QpPEWWWCJxsEv54ZvMKmP7EIlFj9waNFTgBmJBGuBmoH1o0VhPDeZJIkReVK4i/C1UJOFpNElrVPBG19RkqzXHEf5CYapYI7kE6HoMgUHxeU9k4rxQV5cWlbQyOZHHnhhbjcbn798MOjXJyFEEiSxNrnnlPU9rgQ4EIInC53UN9jjcTR0dVNYYx5YMuAozyCPxh0LPMILG+72C5J7NSBC5jlgb8crqMszfsgBJumlYAfOT3skiAL+EQnca1Rx/XzdAz2C15ohnvnRH4RRStQ5Foe4yXCO8mUFYCplkUyUjlxpdlkxir9B6zf/vdALOfgrNrBmPsUSogrEd8v1qUr7lMirOAtvQamFtnjuo+xTIcDZmTFp+12i5XJNdHVU9DQGAv88rvfjVts4bhQrBZrL4V52vRXMvF4PEhI6CLcqP7BmEDQapkXugSv6mGNTqIAwVKP4BKXoBSvuHZ94KEhQn+ygKkCrjbpOMYjOMctuHmbQJLg+xMlFp47f9Q2kYSRHAESKMJDCQ8lIjyST2iTyKF07y6YPjIXfjzdRfzbliOwUsU6Hg/rr6UTCiKUoE/Wcat1vD5fdN9zEG2awniK8K66PtLr13l/JDRG0RlHF5T2TiuHL4xPhU0NjWRy5vHHx63tcSHA9zW2UKsV4EkqbZ1WShQUYZj86v9GifBM4Dy3wJsxXBlVy43s6BOUbResXOTN23ncoKDRBofmpUZ6PbUt4U0il8N1dThWtY46tkDhq6YYUtJOqghxNbFYoKp6pCiVc3xjxRXkrNrBoMGggf0PJ8jjIcKHn6EF4y7/vZr0uiArTm98m8NBmjlO6l5DI0Xo7e+noaWFytJScrJin04aFwK8rqGFE49anOxuHNTUN7VRXSEvADOQYCI8Fnw+k50OKPR7J1SlS1TJSyaRMNQU4d2kkYfXMhlqgJFqwjdRwZyJELndXYI588a3ApTjghLJKq6mCPc9OwPCSDpjIwAz3MBfjd+CUAXNTDpwRld6QRa+2AcNjfHKll27uOPPf2bb3r1Dy2ZMnMhNV18dMjBTDuMib1DfwCDZWaHT32nEn/rmNqplZkAJxuRX/xfV+u+9PjBU1t4f34vHdNI8rNOqKJmQL8vSLUcEyvV/DRR78RaYDaudUVfA9BdA0pxlo/78CbZMTeLplqB2cGM4XC4wGKIT4Gr3Ldq0hfEi0nlX+35qI4sSqS/q7UwnzRvxF28i7SOefUjTgS14gqSY6BsYJDtTe/9qjE9219fzzRtuYMBm43tf/zq3X3st3/v61xmw2bjsxhvZ2xDJITY0Y16AD9rs2tRXCtA3YCMrM7aXfjQiXADlp2SwUYLeEOt09Looyg6eQUCtypfBSEYxlS1rzBQwckASizUtmBiPtxCPB4m6Fk6nwBhlsop4DwxSRYiHQo17yfcct4ksSohegAdrL5muaWpYwENlTSkwQWccJgm0DCga45k/PPkkc6dN45n77+fb553H6ccey7fPO49n77+fOVOnct/f/qa47TEvwPc3tVFTofl/JxOHw4nJqI43kxwR3iDBf7+Sxf0GHf8y6PieScfL+tGWx44+J8XZxqGX2t4Bwe5+gcsjb8o0UeJNjRd+R1Yu5k2WUcvjkW0lHkI8nlbwRFzHrk7IL0hN95Nki/BwqCXC20QWJVKoobiyNuNBMlMklpigNQ5JYtotVopjzH6loZGqbNi+nQtPPx2DXj9iuV6v58LTT2fjjh2K2x7zAryusVULwEwyDa0dVJaqV4U0nAhvB24z6jjZLbjf6eEOp4e7HR7+pZdoDVi3bVcHeXuavNvZBVesF/xki+DnW4cF+HiwfgO0Z+dS1GsN+t14y4ushHhfF4uFERUwI1m3Ex14GY0In547edRfLEQ6VjUGdAMlJWThiKmNQOIpwn1/iWRChsSefvX9tds7uylSEICvoTEWMBmNOF3B0/s6nM6Y0l+PeQHe2mGhtCg/2d04qIklADMUoUT4J3qJBR7BSR4xlG2sBDjBLXjTzwpuc3rYJcyUmL2fH9kvWHF4CY9fM5vNdvkPjFwBooZQiYW+tAyybaF91MO97JVan8eSFRziK8KjKUEfinhbqmNpP1YxHs+y9b4YQPPJ0QlmOQI73u4o/mI83oJ8fg582ibYomLAO4C1p4+8nDglGNfQSDILZs7ksWefpW9gpItnb38/jz/3HAtnKU+/OaazoLg93pBunW7MjyPGNE2tHRxxSGKqkKYLcAaZ6T/KI7g/R48QAgH88tk6ZlWkc8iKGdR12nlv7S5ePKaE9fUDON0Ct0dgmHes7P3GKt7imQPZZ9OK5AARj9SLah9XvLOiqFXuPZDBAUjPGHkFQmUDSWbawViK6fhQekxycoYruZ/6HDqyzB7ZAjbaZyCe1WsTSU06zPEIHjBI/ODUM5gWZeB7KAQiYv0HDY2xyo8uvZRzr72W06+8kuMPP5yyoiJaOzp46+OP8QjBH3/5S8VtK1aua9atY922bbjccQirlklLm4XykhjNThox43S5MarkAx6JUiFo9/uxr1pupGq5kWOONyBJsLUPHtgn6OxzceuKGnQ6if99aeGshQWsqx/g5uf288DKc6MS32oRL2HZnZ5J7mCfrJLViRYSyZhqj4TaLhbecsTBv/NlA/H/SzbxsLTLPYfxOP7WXgOlWfKiC5UOQJNdM0ANJEniKpdgQJK426BjmwqWcKfTpVWg1hjXlBYV8Z/77uOQWbN448MPefDpp1n14YcsnDWLp++9l9Ii5e63ip6cQZuNOx96iP6BAewOBwV5eXxrxQrOXr6c/sFBsjISk5KoTivAk3R6+gbIjjH7STT0S5AlRkf6S5LECUWCfzYKNvbAEwsHMBl0CCFYtcnKNSeWc8O/9/HgbV9l7rSyhPVXzbzbVcuNQathdmTnMX1CbBkgYrE8jzUreDB8AlKJQHx+axp2XEDyjBFqEk11S3/kzi6onSe88fN2yqWesFNAagjoVLWER9MvM3C908N9Bh33GXT8OcZ9d3R1U5SvBWBqjG/Ki4v5vxtuAMDa00NejjqV1xUJ8I07djChspI/3HQTbrebjTt3Mmiz8cmGDTz6n/9Q19TEUYsW8YOLLx7q6KvvvYdOp+PoRYvISFdHsNU3t7FozjRV2tJQRn2z+v7f4XAi4ZCGy7L7hHiTTfB6GyzIhfm5kGuUcKzawKYegUFnYtmMXP74RjPWTZ8hHCMfnniIvUABEUlQyH2JBhPhttn5lEv7o+9kAlAqfJIhwqPFZ0l297rQZ+uIRYBHskrLdfsIVa0y2P5idUWJBTVFeLvIYp7UFHadVKh8Gy+iHRQYgWtcHr5l0jEwOBjT+7jd0k2xFoCpcRChlvgGhQL8oy+/pLe/n5b2dsqKi1kwYwb9g4O8++mnXHfZZRiNRu565BGeX72ay1as4IMvvuCzjRtJM5vZ19jIleefr0rn7Q4nZi0HeFKpb2pj4eypCdvfEo/gSYPEFglmCa8QbwVuMek42yU4fZ6eS74UdDkERh38eqfgggoHurc38f0ywV/ebeWoaSMfILliL95BgnIJtP5/4E4nn9jFVCpZwWPtj1KU+Ii7ej2YypRNw8sRy6GEarz82WMhmj751gt1fHLvqQGMZEqRXVDUEOGpagWPFjMwUcC6bds4YuFCxe20d1qZObVWvY5paCSZvzzzDEaDgUvOPhuAOx96KOz6kiRxwxVXKNqXoreG2WSiOD+fH/361wjg9muvZeqECZy2bNkBf0iJ8pIS1m3dCsCe+nqOPewwKktL+fuLLwLw/BtvsG3vXn727W+jD8ivKIfunj5ysjKVdF9DRdot1oRaQMzAxS7BPUYdWQKsEtiAb7oEp3gE7g9cLDVIfG+NhAdYWCFxzgGPkyMK4LYd/bS9vJ48o3e+2vdCDif2UkV4ByPaCphjzQqolggPFIVqZkRx93k4Z5aNyGGwIwkU38Es0kr6KdcKniqEs4ZHEuH21zcAC+LTsRCMFxE+yyP4YvPmmAR4R5eVovyx9ZuioRGOZ1etIj0tbUiA/+e118Kun3ABfu7JJ1NSUADAD++8k/+8/jo/+da3cLvd6HQ66pqa+HLrVi456yzAa7L/01NPUV1WxolHHgnApp07ee6NNzhn+XJmTJoEwCvvvsuAzcZ5J58csQ91ja1MqEqcL6/GaDwH8n/FKwI+VCrCSUKwaNcu0kwmCvPzyc3KGpEJZ6XNxkdffokQgmMPOwz3778KgFkncWyh4PlmuKzGu67vRWo6aV5KC+1QdJFBfkAFzFhINSs4qOtH7yOc6JNrxfUJ5je3eRRlYoqnC8hYFOEQ/YCjhzRysMWjS2HxDWRTTYhHMziY7RE88e//cOX552OKtozrARxOl2pF2DQ0UoGn7r4byU/TfPn883Hbl6Inp6SgAI/H+9I5atEiHn/uOW688ko+3bqVK2+5hdysLH5+xRWccvTRAJx81FFkZWRg0OtZumABLrebAZuN7MxMmtrahgT4Uy+9xPSJE2X1oa6xlaOWzFXSfQ2VSFYJYkmSmDM1tNtLeloaJyxdOvTZcN1z7D4Q8X/xUgNXbxAsyIWFucMPWajpaUufk0/39NHR56Qs10R5nonyXCP5mYahh9RfxMdCtJY100nzaGtKo0YCU/nwvkO1kQjrd1zTLfq1G60Y9w+ylJvXXY4It9sEZnNUXYkKpQGREF6Ex1P8q+0aE+6esiycS8na5rDbx/O+9287VcR4uN8Rn/taw2oncwSUC/jOuefx4H/+TXqUN7LPAKOhMZ6Ixsfb7XbT0tFBZamyZCBRCfDu3l5efvddli1ZQmVpKW63G2tPD+XFxQAcOm8ebz/xBA/9+990Wq1DIt1sMnH84YcPtdPc3s7ehga+e+GFrF6zhiMPOQSzyURDSwtXXXCBrL50acn/k06iAzBjYfKr/2P3qWdgWuPi+xL8fL2OU6skFudJzM6CfJM0JMLbXl7PM03wTqeg2QYLc6HMDJ85oMUGrR49NqeHslwTpW47pWYoM0uUPbmeqiMnUZZroizXiMkQvVU0WrHQ2G3isJr+oG0oFQSxun3EU4T7UCrG1S7G462AGXwGKN45wOVa6ZVYwmMR/rEQar+h7qnWPgO1h5Viyi9IRPfCkkpW8UiDeZ8Q//FqJ38ySHzrq1/jgb89QUFenux99PT2k5etvYM1xjeHrFjB43feyfwZM0Z99+5nn/GXZ5/lH7/7naK2oxLgudnZ9PX38+gzz3D6smV8unEjm3bsoLK0lNbOTory8sjLyWH+9On865VXOPXoo4ceaI/HgyRJSJLEtj17yExP57jDD+eR//wHs8lEp9VKb3+/LAu4b9pL0pL/J5WG5nZOOOKQZHdDNj4RvlDAbx0eXq+T+Fe/ji29kG0QFJuh/4t1tDng+CL42RSJWdlgGHWfCVzL5lD/6iZabBItdmi1Cz6zwkvP7qZVZ6Kt10leup6yPBPluSbK8oxeC3qukfI8E2V5JnLT9THfw5YBPQUZwbNv+L+EoxX2aohwXzvxJh4uKiDPkmvpgMIgaWDVDJyMVQwrtXaH22+k+yMWK3g0Iryt18ih1eq5YKlBqljF5QwIapcb+d5qJ0/rYcWll3KVy8MSz/D3odwA4cAMqJYBRWOcI8LM9PQNDLCvoUFx21G7oJx+7LG8+NZb3PXoo1SWlvK9iy5iX0MD//jf/zjj2GOZUFXFq++9R35uLv2DgxTk5SGEGOEjuWH7dqbU1lJaWMisKVN4//PP8Xg8FBcUUFwQ2ZLR0NxGVVlxtF3XUJmevgGysxKT810tfC+UycBhB5Z5PB72NzdjsVrJycqipLCQnKzwlh0zMGMxjB4Te3Gtv4WOXifN3U5arA6arQ7qOux8sruXZquD5m4Hbg+U5RopdXmt6OVm6YA1HcrSoMQEBp1En0uwqRc29Aj2D4JegvLpJZw0Jw/IDxuAGcv0uxoBkIkW4onOmtJlEUyZPvICxMNynKxsJ+HEcCRiya0eikARbnNJpBlT1xUi8PmLtyBXkumlZrmRr692ssAj+INRx0a34JtuEbFKX7vFSmlR8mceNDTU5uF//WvE5xfefJNP1q8fsay9q4u3P/mECVVVivcTtQCvLC3luxdeyHcvvHBo2ZSaGuqamrjmjjtwezzMmDSJy84+m+rycoBRVr4tu3dzxrHHAt6MKvsaG2nv6gpq4g9GXWMrUyZURtt1DRXxVkCLPntNKqLT6ZhQWcmESvXuKcP8W8m/ZwX5wKwDy0xnjLSM9bkErXYHzXaJVhu02AUfd0GzHVrt0OmAHIPA5oEZWTAvB44qkPAI2Lu3jZ+v76O0WKL/yx2cVAyV6SOfMzV8X9UStf5txFOMx8saHgqHA8xm73lPhstGIojVAq+21d8nwj1CfvafVCFRGVSi3UfVciOsdnK3w8OdRh0PSXClK/zApt1iZc70SbF0U0MjJXnlvffo6eujt78fSZJ4YfXqoOtNra3ll1dfrXg/qoQvm00mvvv1r/Pdr38dS3c3OkkK6cje09dHa0cHi+fMAeC0Y47hs40bee/zz0eI+nA0tXZyzKHz1ei6hkIaWzuoLFVegvVgwHzdc9jvWTH0OfClmGWQyDLA5APZNBtWu4Bh/0yXEHQ6oNDotYSPROIYdy77bb1saRZ8ez1UpglOLpZYXgwFJvWUidqiNhFiXK2BQzjx6HEPl6CPRqCmYv7uSITKUiI3e0k8AjOtn35Afvr4qD6qJkoFvq/I101OD7cYdbyng3AVHhJdBVlDI1G88MADQ/9feM45/OGmm5g7bWTRx/S0NMXZg3xEHyUWgYLc3LBRpA0tLQzYbJQdCNw8evFi3vz4Y2x2O7OmTInY/pad+7DZ7ehGCRKNRFLfpCwA037PihGidLxjvu65qLfxVbo0SBKlZimI+PbSTC6HZ/Tw0yk6XjpU4vIaiU+tgh9tjs+UvNj0ruqCOZ6WarX6G0pcdnfDpNKCcWv5Dsb27t0j/vyXx2Nf4WjNX0BpduQCPKlGKufir1puJB04wy34UMY7VovD0hjv3HbttcyeOpXc7OwRf7GKb1DJAh4Ns6ZM4d//939Dn4UQLF2wgNfff5/SwsKI29vtDgbtDv7+whsY9Hoqy4qprSylsrQIwzhxiRgLNLZ2cNiCmYq3t9+zQpE4HYvIPc7J14X/PnDgYiEDp6Off7RDh0PQ4YAd/XBkvtKeyiOWdIDBiHfWlHj4hk/PncyXDT2Ul2gCJJ6Ec0Vp7XQwZf486Pwkwb2KnVQu5lO13Mjc1U4eNYS+t+12B2ZT7AJEQyPVOeO44+LWdlIy6PtbyE1GIzddfTUXn3kmGemRp7OMRiPLj1zEjMk1OJ0uGls72NfQzIefb8Tl9lCUn0NtZRk1lSVkZ46tAMGxhMPpwhTjD7D9nhWYfvwsr7z3HjpJYvrEiUysqtKsKiHwd2kRAvpccMlawXFFUJUuMTUTLquGiQm87dUS46kuwoOJwOY2O4ctyI2lWwcVSt1QQrm5tHU4OPKQPKTy+Ke9jAepLMJnn2BA+ljQ1dNDfpAZ7fau7qTUgNDQSAZfbN7MK+++S0tHB07n6Fm3h2+/XVG7KVHCymgwMKW2Vta6za0dnHiUN3+F0WhgQlXZUEVMIQSdXT3UNbbyxvuf0zdgI81soqaihNrKUkqL8hVVrNMYSV//IFkZaaq09dvvncPnrjRqPDZ+3wuLc+H2788fEuHS3JWq7Ge84BPhXaRjsw9g1IFJB8UmOLEY9EkcvMTqK54IEe7bjxpYul3k52lWQB/xzh0eKMQdLg8mk/f3PFFBvgcLkiSRaxB09/YGF+BJKsKmoZFoXnjzTW794x/R63SYjEayMjPJzcqif3CQ/sFBTjziCMVtjzk1OuhwkpkeXPxJkkRRQS6L5k5jxSnHcMmKkzjjhKXk52azafte/vHiap58fhVvfPA5O/Y2YLM7Etz78cH+5jaqy5UV4PF3x3ALwQcWODXTzq9n6vjXIom9A/DHR4bT/YiNK2Pt7rihzWLhrY8/5uVWwXOWHNy2birS4AML3LJd0OcaXjeZfqapLoDU6p9AoFNxwPNiXXpKlY9XWsBHyXfR7sPtCX3upTnLhv4Cl6caqewP3u+G7MzMoN9pOcA1DhaefPFFTj7qKN558klWnHQSXz3lFP5z330894c/UJiXF5OLSkpYwKMh3RydxSk9zcz0SdVMn1QNeHM+t3R0sb+xlXVbdmGzO8jKSKOmspTaylKK8nM1F4gINDS1MW+mckuXz4qrlyTunwNXbhCUm+GEYol7ZsPl6wU7/m8dtTOKkYCst6/ixHN+weTqavUOYgwxMDjIDffey5dbtzLP1Ee2AQxFOWTbGzgsT6Ld4Q26zDV679tUeKkrdflIRBVNiN0lpbfPRXZGfH4+gwnfeJaOD4evL9HsP5jLiNpBml/U76YwPy/ieqkouscCPU7BQBgB3mntoTBPfsluDY2xSkt7Oz/+5jfJyshgYlUVn27wuo2lmc18/Stf4dFnnuEPN92kqO0xJ8DLY0x9p9PpqCgppKKkkMMXejM09/YPsL+xjc83bKfd0o1ep6OitJCaylKqy4pj9nUeb7R1WimJ0frhE+GV6RL3zoZrNwnMOjiqUOLxBfBJF7Q3dwBgKS/iqht/zJTJs7np6qupLC2N/SDGEEajEb1eT5noY2GuxPwc2JSRyfkFgwesgMMDxlQQ37GSSBHu21+0NLfbKS8xK9qvEjGqRAirif+gQG4f4plqscsCngwr27u7D6osNIniuWZYXkTITA8ut1tLeqBxUFBbWUlbZycAs6dM4fdPPIHT6cRoNFKQm8uG7dsVtz3mXFAqS9TPPZ2dmcHsaRM49djDuGTFSZx/xnFMqa2kua2T515/nyefX8ULqz7gy8076bT2hC1NOt7xCOGdelfBl97njjItS+J3syR+s0vw530eMg1wUonERVXev2v0nbxy3SwOK23joh99lxefuAaxceVB455iNBi45/rr+VaNRItNcNcuwfsW+O4GD3/e5+Eji6D3QNGMVArqikVEp7rlsrnNTnmJSbX25Lp7xOqiEo1YDSW0U8FVxtoF+QeKMI61nOqBpNqgudkmeLpJ8I2q4DPBHo9HVdcrDY1UZuHMmbz9iTfT0oxJkyguKOAXv/897376KU+88ALZGcqzHow5C3h+bvgS4Wpg0OuprigZkee6u7ef/Y2trFm7ma7u3gNW8iJqKkupKivGZBxzp1IRnZZuivLVy/zgE+GLgX9Zrdzww2/y3Q2C22dAqXn4R97z5kYuPWkeR07N5tt/2cWJc/JJN+kQG1ceFIGakiRxXJH3zyLS+dA9SLFRYn234O8Ngq19UGEWzM4BsWMdXzpN1FscHD0th/svHpvV6lLZHaWl3cHShXmq9eGs2sGEiFp/sSqnVHy4fr1Yl540i3y3VZCTO/z7IDcA1HedUz1OIVn0ugQ/3iy4tFpi5s3PB12nq6eP/NzsBPdMQyM5XHLWWfzuL3/xDjx1Om688kq+f9ttvPHRR+gkiVuvuUZx22NPNSZp5J2bncncGZOYO8MrZlwuN02tHdQ1tfLJl1twulzkZmdRW1lKTUUJ+bnZ49KXfH+zsgI8cijIy+PPjz3Hoz8+l29+KfjFNG/pdR+OVRto6hIIp6DX5iLd5LVAHiwi3Oe20yxyqNX1MC9f4vB87/lxeQQ7+mFNFzzTJLA4HRw6KYsrjy9Lcq/HBtGKcP8MHGMRf7EaKT1gKopwtxsMAXmqo8nCkqjBnVxSISWhRwh+sVWwKBcuvSd07QItA4rGwURpURF3X3/90OfFc+bwvwcfZOOOHUyqrmZCZaXitseeAE8RDAY9NZWl1FQO+yNbe/rY39TGR19spqtnfFrJ65vaOG7pwri1r9PpuOL3z7Pg5nO4ebvgiyLBdydIGA9UZbt7t+D26RJ5H2/DwfD0bbJFeGCRnHgVGTJf9xxNd/2chbrGEcsNOokBt+C5ZsGRBXBJtURN+gCmyuTmwo812DGRQkluX50uDwa9+oPrRFnBlZBKItztFoTygBvrIhzi60bmq7LrT9Vyr5/3a23Q54af//HZsMaj9k5r3IwwGhpjgeKCAo4//PCY2xn7ijCFyMvJIi8ni3lBrOSfrtuK0+UiJyuDmopSaipKKcgbe1bynr4BcrODR8aryaG3Pc/ffnMOt+8QXLlBcMcMqEiTyNDBp1bBofnenNeOVRtSRoT7E8++WMiggP4Ry15oFjxcJ1g5XeLQ/LF1T0Ui1UR4a4eD0iJlAZiRiCTCk+Xy4dt3ogYI4UT0x3t3kaOSF1yqiXAY6ROeKKu4EF6/76uvvRG9PnxwZbvFyiFzpyWkXxoaiWZPfT16nY7aA5btTTt3RtxmztSpivalCfA4EsxK7vMl//jLLXRae4YyrlRXlFBdVozZrF5gl9o4XS6MCYx8L/n58/zu7nN4ugm+tU5w/RT4w1yJn28VnPOZ4FczYG5OaojwugHBO52wo08wNUviO0KACn1p7ewkIy1tKB2YZ8NKpJJ8dJ3D63zZLXiwTvDIfInq9NQT3/EoBR9PIvW3uc1OeXH8ntNkiuxI+PqmJCuKXCJZsNNtpcyuAmhTZX+pKMJ9qO2aUrXcOMoK3rDayfq5Xilw5CGHRGyjf9AWshaHhsZY56qVK0k3m3nxT38C4OKf/SykoVQIgSRJrH1O2Yy3JsATzChfcreb5rZO9je28cXG7dgdLm9e8gqvL3lRYV7KRJw3tXZSUVqY0H2m/eR5LrxnBfNy4KZtgiPz4ceTJX69U/CRRTA3x3tuRrykVq2ImwtIMPbU13PVBsHyYjiyQOKZ/nSaXqjnlzdehEG8DVLoRP3/ee01tu7ejU6nQ5IkJElCJ0nk5eRw0RlncNsDD7Cnvp47f/QjFrj/TZ1FUN/Rw607PFxYKVGZBr/cJrhlmjLxHUxopqIYSaXgueY2O8ccmq94e6Ul2dUk1qqV8RokyOlTa4eD+TOzKA0SRKr0mCKJ8MDnJJH3YWCWFLWt4t3AfXsED8yTMBoiSwKJ1HgfaWjEg2u+8Q30fj5ut117bdz2pQnwJGPQ66kuLxlRWbK3f4D9TW18sWkHHV3dSEiUFudTU1FKdXkxGUmyPtQ3t1GlsAJmLJive47Z96zgbwvhrl2CG7YKCo1wWmnyXwTN7e1c/ZNruGaixGmlEqaT5nGS3c1Pn97Hbx5+m69+fQKwm+l5l4/aVmxcyYN/38TXDi0iP82AEL40j7Bt+yBfffVZbE4P+ZkGrvvt7SyuNlNnzWR6eSabe+GjLrj44jnY121hxqnT4ZNtsvsdzsIr11qdDDGcCplRuntd5GZrP52xolQsd3Q5KMofnoFQKw94NLM0odZNxL2p1Fd8/4DgzQ7YValnsNXDUo/gcA/80yBxSglMzYz8ezowaCM9LT7uVxoaqUBgZctYKl1GQnuLpCDZmRnMnjqB2VMnAOD2eGjt6KK+qZWN2/YwYLOTbjZ53VbKSygrLkCvj39GhsaWdpbMmxH3/QTDfN1zcM8Kbp+RfNHtw+lyce0Pv8PXKqQRg4EMs567br2I83/8FBNnptFYMBHq/sHP5l80vLF4G4ATZuXxn087uOr4Mk7tasQgSUMv2P9+aeF3LzcgTBnMrM5h3oJaprXYOG6qg/O/gAsvmkO6Sc+hk7JYu6+fUwOmq1Mtv7BaJLNQj68GwFiL3QhGMq3wsYhmt0egj0MQrBqkojuLEIL79gpeaYXTSuHoQgl7vp5Hd3jY7xZ8nqbj3zWSrFnDdks3xQXqpaHV0DiY0QT4GEDvV73zsAXeZQM2Ow3N7WzdXcc7H3+J2yMoys+huqKEmvIScnPUz5dud7gwJ7EqqC8NXyDJEpqPXfdVikxwUeXofmRlmLni23P4vwe+4LjvlJOencZd670ifLv1UabnTkaas4wbeJezFxVw72tNPNUquG4yHHGgjTMXFrCzZZDNXUaMBj1vf7yboxYezoTC3cytzuT97d2cNr+ACUVp7LfYh/rg7xMfT5IpNhLpkuJvDbf2uMjLif0ZSAU3lLGI0+nBmABjw3hCAM02KDLBGaUSkw9YurscOh7eL/jNVIninwfP+R1Iu8VKcYxVkDU0UpmVf/hD9NsozAWuCfAxSkaamWkTq5g2sQrwWjk6u3rY39TKO5+so7t3AKNBT0VpEdUVJVSVFmGKQTz3D9jISE/+1GOgCE+W+H7/tDN4KkPPEwulUdZQac4ytnfvZsa0AirnTeSTFz9j2UVHIUkSd63/B2fVjmxrZkUGD182mTef3sCNWwV/eXE9k8+aD8APf3wB37/9RRxON80dvTS0dKM/bxnXnNjHz57ex5JJ2WSn6WnvHQ6sSuQ5SbbFL1FC3Nd+k3mR4hL0auBvOU4lAR+YHSWcj3gs1u82i4PiQuW/Y6HO2VgsZy83QFMnSfxmJvyvFb67QXBJNVxYCWeXw8JciUNvkye+wZuCcML85MyCahw8uN1u1qxbx6vvvcdr77/PnT/+MScfddTQ919s3sw//vc/vti8mfycHFaceCLfOPPMERW69zc385uHH2bTzp1Mra3lB5dcwrzp0yPue9WHH454pwshsDkcQSugp5nNzJqs/LdDE+DjBEmSKCrIpaggl0PmeFNEOZ0umlo72N/cxqfrtuJwusjOTPf6nFeUUBxFgGd9cxs1SfD/DkawqdLAsvTxzIay+dQzuN+o41s1EuVpo8W3P3OOnc0bf3mLXZ/tYeqhI8WTzwouNr2LJEkcUyhxSTXc35vNfQfWM+h13Hv96bzy3nbe+WQ/5SVeoXPI6adzkeNzLn34U5ZMzA6ZFzkRxCLC1cqQkqiBQPOm7cwstQFHxn1f/qS6QAxMURiv3OBKU0BGGqyoEciZykiSxJllsDgPVm4XfGCBm6dFJ74Burp7tSqYGnGnq6eHOx96CLfbjdvjGfHdu59+yvV3381Zy5dz+7XXsmnnTu5/8kn0ej0XnXEGAD19fXznppuYUlvLrddcw5tr1vDdW2/ln/fcQ3V5edh9f/T00yM+r/rwQ/76/PP8/a67Rgj8NouFS6+/np9++9uKj1MT4OMYo9FAbVUZtVXD1RB7+wbY39zGl5t30m6xAlBSmD/kupKVGTzPb31TG3OmT0xEtxUhzV05QoQ7Vm2ISzaU7aeewd0GHdPKJM6vGF5uOmnekJD0vcxfrEtHb4ClKw5l9WNvgwTXnVsOSLS1D7D65TW8+fEuLJ3d2JweflALBUbQHyg65GsvI93EeSfPZcbEiTicwz9Gl52zmNqKfP702GpmV0VXcEft1IDBLNFKgzmV9isRIrytz8iySX1B/cMPdvxFeCjxHau4be1wsGRujuz1lcwS+LZR0tdEzwZFm6awIk3iz/PgqQb45peCezdv5pDZs2Vv7/Z4RmSI0NCIB0X5+bzy8MM0tbVx2hVXjPhuUnU1d/74x0OFcI5ZsoT2ri6eef31IQH+ynvv4XC5uPv660k3m1m2ZAnn/+hHPLtqFT+89NKo+vLX55/nG2ecMUJ8A5QUFHDp2WfzwFNP8YebblJ0nJoAP8jIzhoZ4OnxeGjvtLK/uY1V739G/6ANo8FA5QHXlcrSIoxGA60dXRx/ZOQcsckkUISDt0KlWiJ886ln8IBBIqNY4sapw64nocS3j9ziHJZ/6zi2vvQxP1u/k4EBF3a7izOOnc1t15xIRUkOPV++zzVP7mHQ4eGak4IHOTW22Fgwa6T16fjDJnPcoZPwbEyNwK9oBGkosaJExAeuHy8h5PaAfyr8RAjxsWSRjXexHovVSUFeZBcUNdxzYk3VmKroJYmLq8HugQ/WrpUtwN1uD4YIRXo0NOJNdXn5KCv29IkTef3994c+v7lmDUcdcgjpZu9smU6n47jDDuOVd9+NWoDvb2oiIz34b1plaSnrt8nPPhaIJsAPcnQ6HaXFBZQWFwxlOHE4nDS0dlDX2MqatZtxulw0t1lYt3kX1eXFKZWbPBA1RfjuU88Y+v8eCf7PqGOaENw6Q8KgGxbfPsK99C9ZbMS14Ei27rBQXJTOUZPmjMhck1+Uxl+/M5V7X2ti2fTgFr52i5PigtEFYCRJQqeL7/VIlhhRaqmPhzXc5pQwGUb7AYKyfsYSiJlK/t+BxLOQkEeIkPd6NOck1CAhsO9jQYQrLdZTYoZ17z8LF18sa/1Oaw8FeZr7iUbqsauujknV1UOfW9rbOWzeyFio2ooKWjo7h4rnyGVSdTXPrVrFsYceOuq7tz7+mOKCAsX91gS4xihMJiOTqsuZVO0dZXZYunn/sw2kmU2sHeG6kjeUwzw7KzoXiHiidqGKL3TwR4OOb7kEFx4//Mj4xHeg8AoVkGYw6Jg7qyjoC12as4yCTe9yx3m1QdsUQiDCiI944S9qwgmceIqUVBHhLb1GyrOdkVeUiVzBGCgCU1l8xxO7w4PJONr9QQ3h7f/9WBThSkjXe63gcg0U7RYrxQV58e+YRlLY3VuH1Ri/2atAPMITeSUZdPf28uaaNXzjzDOHlnVYreRmjxws5mZn43K5sPb2kp8j343t8q9+lR/86ld868YbOfekkygrLqbTauX199/n7U8/5QeXXKK475oA14hIfXMbU2ormT1tArOnTQAOuK5YuqlvbmP1h1/Q2z84nHWlvJjKsuKkpixUiwbJK75vcHqYFsT4GUkY+r/M5b7Eg7Vp/fxDcp2ZQMXoDUh+NpJ4B7GlQjn75l4D5TmhBXg8+zheRHcsYrat00Fp0cgZoFQ6L8l8/pRYwTP10Gz3Du7liPD2TiuTa4P//mhoJIv7n3wSk9E45P8NIMGorCW+z9HO3h+zeDF3/PCH3Pv449x0331IkoQQArPRyGUrVnDp2Wcr7rsmwDUiUt/cxjGHzh+xTKfTUVqUT2lRPovnelP7+Gdd+WzDNuwOFxnp5gNW8mJKixJTMEgt+oDfGHRc7BIcf8LIwURgqr9gQiCc+A72sg5XXa+xO43KMOIvlYgliE1t1ByYNPcYmVtmU6UtjehpabdTWjgswKMV33J908eqFTxaEX5oHvx8K2zqhbk5Xkt4w+rh35jJr/5vxPrtnVYOXzhLre5qaMTMy++8w4tvvsmfV64kzTycHakwP5/uvr4R63b39mI0GEZZxuVw+rJlnHjEEezev5/6lhaK8/OZXFNDTlZs9VY0Aa4REWtPP7nZmRHXC5Z1pX/QRkNzO1t21fH2Gm/BoPzcrCHXlYK8bNWrCqoRdNl/9zn8qVTPsgy4ZPLIwKNgrif+/ryBL2854jsSjT1G5peH9q2Nh/UtnMAJJmaCiRZQT4grDXhUS4QPOHRkmdWZNj2YUSpmWzscTF6UN9RGtMQ7QFQtYilzH40If7MDik1QE+KU7D71jBEi3O5wkmYeHYOioZEMNmzfzq0PPMAPLrmEJXPnjviuoriYfQ0NI5btbWykvER5KmWT0cjMyZOZGUPe70A0Aa4RFpfLjUGvUyySM9PTmD6pmumTvAESQgi6evpoaGrj4y+3YOnuQUKipCif6vJiqsqLyc5Mrj+5/Z4VPLBXIIBrJo087lB+3zAsNEMJT6UiUJqzjPa1GyjOcinaPlSbSggnYPy/8xfjalsPlbh6xCrCPQLCPQLR9ieVXCeSgZJ7wluF1BDTufPdl+HuY6VBpEoz8Mi9d+Tew77fqHBCvM0uuHm74L45ErnG4Ru7arlxhBXchxAC7y+ihkby2bV/P9fccQdnnXACF5911qjvTzzySP74978zaLORnpaG2+3m7U8+4cQjjgjSWmQ8Hg8bd+ygpaMDp3P08/GV445T1K4mwDXC0tzWSXlJoWrtSZJEQW42BbnZzJvpfQG7PR7aOrpoaG7njfc/p2/AdsCfvJCqcm8VT3OCLC/2e1bwSqvgvU54bIGEQRqd7STSCzOYsJDz4gwlLL0BmBAq/jJRvqehRMsrawo5bWnnqHVTTYTHQme/nsKM4AOgZPumj1WivSd6nX3s7Nmjyr5DCfFw4ltuf/3vh2hczeQQzUAy0BruFoJGG3xhhY+7vGL651sEp5UK5uZIzMmGqjSvCA+kb2Aw6YYRjYOHuqYmLN3ddHR1AbC3oYEvt26lIDcXnSRx9S23UFNezjnLl/Pl1q1D25UXFVFWXMzJRx3FX555hh//5jd87dRTeeOjj+jo6mLFiSdG35fGRq751a9oaGkZWubzJ5ckCaPBoAlwjfiwv7mN6or4VsDU63SUlxRSXlLIkgNljh1OF82tHdQ3t/P5hu3YHU7SzSaqDljJy4sLMRj0EVqODrFxJZt6BPftEfx5ntcyFOjrHe3LUw1x3NPnIqeyDGnO6BLz8RLfgVbGQKHyyprCkJ99YjzVRHgsVvDmXmPQAEwlYupgt34rYUPbLkxxGIPHM2UiJH9w5vv9eu9f67l/j6DXBQtyYVmhhFsI3AKq0yXe7xT8eZ93m9/MhFnZI0f77Z1aBhSNxPGXZ57hv2+9NfT5waef5sGnn+bM449HkiTau7po7+ri6z/5yYjtrrrgAq664AKyMzN55Pbb+fXDD3Pz/fczbcIEHrj5ZipLS6Puy68ffhiXy8XPLr+cNV9+SU15OactW0ZHVxe3/elPPHv//YqPUxPgGmFpaG5n0YHS9onEFMSffMBmp7G5nV37Gnn/0w243B5ysjKoKiumuryY4sK8UdWq5CI2rqStx8kNew3c8rUqZswcXQxHjSIzSmhosVNZmqZ4H4kWAf4W8XiVJFeKUhHe3GNkYeXI41B6XgNdlQ5m5AzKtnfvxmqBvILUrD2QaKK5h3e2DPL715to6DLx/VoHxxQy5E64KA++sVbw0ylwYaX3d/O9TsGPNgnumgXzc4fPd7vFSnFhntqHoqERlNuuvZbbrr025Pe3XnNNxDaqysp44OabY+7L5l27+MVVV3HK0Udjs9tpamsb8gM/47jjePDpp/nZ5ZcralsT4BphSaXAm4w0M1MnVjF1YtXQsp7efupb2lm3dTftnVYEgoLcnCFLeUFu5CBPsXElTpeH6/65l68uKeTYGMR3rMI7mFW3scXOvBlZo9bTSJw/eEe/YYQLihqDmlgK8Ywn5Ijwri7Iz09Qh8YAke7hth4nf36rmfe29XD5saWcaW3CGODDVmqWuKIWrlwvuGMGFH7mYunxBrIMYAuINW7v7Gb6pJp4HIqGRkqTl52Nyeh1y5pcXT3CMr9g5kzufuwxfqawbU2Aa4RkYNBGelpqiO9Q5GRnMjs7k9lTJwBe3yyLtZeG5jY+Xjsc5FlcmOcV5WXFIzK6+Kpm9js87God5MFvRu8iEW8x3G5xUOyXfi2a/SXK+l37Wjt1pxQPfU6kFVypCPdtG24d3/dCgF6n/vkMJjw1UT6M71xYLYLqGs0CLoc3N1u5/cV6zl5UyAs/mIH5/S1DASQNq50jfLy/WiFRkQY/We/hZgleetdNVbGOw/JHnmtrTx85MjJhaWiMN6ZNmMC6rVs5/vDDOWz+fNotFlZ/9BHLjziCLzZtoru3V3HbmgDXCEl9czvV5fH1/1YbSZIozM+hMD+H+bOmAAeKBnVaaWjp4J2Pv6SnbwCdpKPUs46qPDP5Zht/XN2IQSfRYnUwuXSkv3Msoss/CCrQn1wOQgjcHoE+wRUwwxHo/+0jUIRHItnFg3x9iPR9/6Cb9PqOoD748SCcNThWcZ5qLkE+IlnB+/shIwX0X7h+RlMpNtS60cRIhHp+nviwjVtX1LBshncmzxGhnSMLJC53CW406pCAxyd6f2v807kKRNQFTDQ0xgPnnnwyt/zhD/zw0ksxGY1ccNpp/PR3vyMvO5vuvj6+cuyxitvWBLhGSOqb25g5pTbZ3YgZnU5HaXEBpcUFLJrr9Wd3rl9Ja6+RHW067vtCoiBrOlecYqYxqway06gqM5NmjhzkGUpABksB5lsWjRDv6XOTm5XYx1SJyItGeI81mtvsVJSaI6+YwvgH0YZKFxmOSIMCOX7ckYi0jtr1ApSi5PmQu020ufMDZ3KcbsGWxgGWTAxeICSwuI6PS66D8x0OHE4n2ZkjRzpOpwujQZMKGgcnRyxcyD/vuWcovux7F11ETlYWX2zezJTaWi4/7zzFbWtPlUZIWtstHHf4wmR3Q3XExpUYdJCfZuOxt3azZGIW15xYjnvGEprb7TS02Plycw82uweTUYcxt4/CYjh80iTMpshBnpEKYThWbZAtwhtbbFSWKRd/8UjXd9rSzpBW8GQRz7SEzW12qspGB8EmAyV+45Fyt4cT4XKEoNx1lFrvBwcFaalfP0dVgp2rcOfZZw036iVmVWTwRV0/R0/LAYbTEUYqUGY2mTAHSTXT0dVNUf7ouBgNjYOBvQ0NTKyqGrHs4rPOCpp/PFo0Aa4RlCHXhzFUOl4OPp9vp1vw06f3MbkkjWtOLEc391h0wGBmE4WTofDAu87pFHS2Q2c7vLCrDYfTg9mso7I0jcqBLVTkgNHPUC63Cp1cEd7YamfOtNjK3UaDWv7H/nnBU9HlIRqa2+0smZeT7G7EDZ9Aj/d1UirCrRbIz08N63cy8T93wcS4bwB68ZFW7nmlkcUTskg/YDCIpTqwNwWhJsA1Dk4uuf56fvuTn3DEQvWNkZoA1wiKpbuXgrzsZHdDVXzi2+MR3Pr8fgx6iZvOrEY391gguPg0GiXKKmDZzOEXns3uprHFTt16E2vqMnG5JdKNHipznZSIXErpxSipU7K8rdNBSVHqBcKGs4KHE9+B7gpq+oEHlqoP1W60lnK73SPLHUkjMkpEeFcX5BXEqUNjlHCuKiddcBZvbXmC+99o4vrTq5DmroxpX+2WbmZO0TKgaByczJ4yhaa2tri0rQlwjaDUN7WNuQDMcNjvWYHppHl4PIK7X22kocvBny+djHH+sUB0AVRpZj2Tej9j0qThZQMOicZuE/unzGbNjn5c6MjEQbnUQ4XUTSm9GKSRpZzlWME9MQZgRiM2oxVGgdUvAwllUQ0mwkG9bDKR2onGXcXlTq0A2HiSqADNaEW41SLYbspAVzd8Hcb6rIpahPK/v+Gn53PeD//OV1ZMZ06M+2i3WDm6IDEByBoaqcYPL72UG+69l8rSUpYuWKBq25oA1whKfVMbRy6Zm+xuqIL9nhUA9NncrHx+P5Z+F/d/Y+LQ9Gy0wjOYwMswCaYW25labMex2+uG0i+MNItcdokiPhITcSORgZMKqZsKqYcSeiGMCO/pc5Gd4ADMUJxVOxjWlzjY+uEIZsFTW4irQVvnyBSQahFtsF2yULt6qQ85Itx3v/VabGTVBP8u1YV4NKXulRLsXsrNTuObZy/ir89/wd3XXxhT+06XC5MxNX6HNDQSzbOrVpFuNvO9226jsrR0VECyJEmKq2FqT5VGULp6+sjPSZzvcbz5uEvw6z9u48hpOdz51VpMBp0sK2gs4iNTcjJF6mAKHUPL+oSJZpHDTlHEhwdEefbGbCpznVTmOinNdmI4IEAb0xZRGST7RjzS9yUr93QwgZcIIS7XCt7cZqe8RL0MKIHnOZJf78GIv2gVwjtrFCoDSqqmVQw1WI3nwCFQiJ+zfDaPPvMZdY3PUVu5QlGbvvOvoXGwsq+xkcyMDBbNnq1625oA1xiFy+3GoNelTNqvWLDZ7dy5w8OnVrhhqotjzqwe+s4nwkJZ45QKIp9FO1hAZpbkYKrUwVR/Ud5kor1sPtvbzby3Jwu3BzJMHnrse1hQPohT2DDOjz7Dh1w3i2QXfgllDfbvf7Ks4s1tdo44JE+VtiKd58DvY62UGc2MRTgSbQX3n20RdoHOHP53aKxYw/1JlBD/6slzue9vH3LP9XlIuuOjbqu7t5/c7PFjiNHQiJZHbr89bm1rAlxjFC1tFsqKx0fUU6fVyocWWJQHM4O8R4KJcLXEhi/9VySyJAdZX37GdD9XlD67jn+szadzwMB/NuTjXreBDJOHyhwnlYfMpWzG0RgNuqFjAGUFg6IReD6xoJawC9aXUOc+nBiXc46DuflEsoJv795NV086+bmx/0zGM3d0MJRco2QI2Egi3N3nQZ8lLxPTWBXi8erv9u7dHH1iIWvu3s9tf3qTy8/robLs7KjaaLdYKSnMi0v/NDQOdjQBrjGK+uY2qivGRwBmZWkp/14s8VCdYMVnggmb1zFhcj4TitKoKTQzochMtfNt0hceFxcrXzhreDiyzB4yTR5OmNo3tKzfoaOx28iuTzbzgb4Cl1uQbtZTWTqfyjIzZU5v3vJ4E4sQD7aNvwCRMwhS4oITTe51Xz+EEPQ6+mOeCUrUDEOkcxtu3VQVre4+gT4nuntaSaGhZBJPEW4y6bn2+3N54eXdXPTTp5kz7R1++d1fUlooL49/e6eV0qLxYYzR0Eg1NAGuMYqG5nYWHCjjPh4ovP55bgSu7ulhX0MDdU1N7Gts5NV9Tex7ax1NXQ4KsrZy4rK5XP7VQ8nJDO/zq0QAyrGG+4vEXruOLPPIVIaZJg/Tiu1MK7YDOwAYnHwUja129tYP8tEX3Thd3jzlFSVmqsrSKC82YzYHFzCxCkN/0SBH9ETjFxsvt4doGBjwlj9X2pdkCu9IRCP44n0dwlnBn9qkw1Sh/DWVDKu40oFpvPqYk2PmV1edge0yF3959jOuXvlTfnn1T1g4a1bEbdstVuZMnxRxPQ0NjejRBLjGKGwOB+lpY7v0djDyc3LInzVr1IvHue4WGix2Hn13Lyuu3sDrP5mNzi/1XDA3BSX+yXJFOECdp5jK2ZGFT/ruD5g6ZxlTJ2QMLRu0uWlqs7O/ycYn67txOLyW8fISM5WlZipKzey375PVZ7lEEg9qu61EOwiKxvoNXlG4ev8uCgu990E0IjwRwjtebkCBJGoQFEqElxld9Jpi/y1KlBCXc11eWVMYNIVnvProu4ZpZgPfvfBwqstyuf6eO7n4rK9x8Zlnht22p2+A7MyDrAyphkaC0AS4xggGbXbSzKlX+CWeGBfcyoSNK8nLMHD0tJwR4lsOofyIgwlEuS4pTeQwfctmHFt7R2wXaj/+fUhP0zO5JoPJNcOi3O7w0Nxmp7HVztotvbT3etDroaBQorAICosgLX34uJORXSJwn2r55Ecrvn10dUJ55fDnSP2Jt/BOlOj2kegZiEAR7svAEW0KzHAk20/cV7zKv4hVoBhXs4+jApsliTOPn4UkSXyw9gMgvAD3baOhoTEap9PJzro6Zk1R5jGgCXCNETQ0t4+rAjxy2ZX9TV7Z8BOevWbGqO+iKdziTzgrbSQh3iayOEraM/Q5kg9zpD6aTTomVKUzoSr9gMjR4XIJuixg6YC6vQKbTdA8qEeXqcOQ6+J5m5mzp9kUv4CTnYVDqfD20WURzJo7+tgTmTVGrkUVIhdGCiTZLj7B8Bfh/X2QeSBwWk0RDvER4pH6F6pybDiLeCz9C3Z9xaZ3EULwv5d2c9KcvLDb2+0OzCaj4v1raIxFVn34oex1123dygurV/PR008r2pcmwDVGsL+5jemTqiOvOI54+5NP+M0Dd3PNieXkZwYk2VcgvAO3D+cqEcotxYOkqHJmOAKFo8EgUVwCxSUAEi/WpZPpEbj7Be5uN4N7nby1TyBJgpxcKCySKCiCnByYkTclJiGqVDT6iHRO5RDp2rpc3nOULKIVdNGc01QU3z58IryrC/ILRla/VHsWQK2ZHqXi2/97NUW4//UNfFbe2GSls8/FWYeE71O7pZvigryo962hMZa5/u67kSRJdg78ZUuWKN6XJsA1RtDSZuHYwxYkuxsJoc1i4a5HHmHnjrXccV4tiydmxSy4gxGtCO8TJjJxBF03nAgPZwWXW3VQ0kkYsiUM2TrMwAm1HoQQ9HRDZwd07Mlju9XBp6KJvJwcKkvNODLayMsDnV6eWA0lRuQKjcBzqWRQEuk6O5weDEn6dQwn5iIJuUiEE95KZ3rihdUCpeUjl6WaCI9mhiLa9XyCPNI+wvU92O/OG2/VcekxNRgX3Bq23XaLlWItBaHGQcajd9whe93y4mIqSpR7DGgCXGMIIQRujwe9Pv6p7JKF/Z4VeITghRZ4aJ/gnHK443vzMBvlVcZUSjRBg00ih3KpJ+T3SlLqhUKOgJAkidw8OLTWz6omBN29Lhpb7Via8lm/1oLHI0hL81rKN7vM6LMFUoAoj1VAyiXWa/npvj0jrK+JItT1UOO8BYrvYPdj4LJkCfLpuZN5v2sn02eNvgbxyEcfrQiXu+9YrpvcGY3Avvuus/+19B/g7+iHq5ZdF3H/7Z1W5o+jbFgaGnKIR8XLUGgCXGOIru5e8nPHb9Uz+z0r2Dcg+PVOgVPAA/MkZp0zP+i64USr0un7SD7hvpdkE7lMk9rDthVKhEdjxYxGwAQL5srLMZKXY2T21CxOpJDt3buxDQo6O2Bqp52Nm3QIN0gG0GfrMeTo0HvcuHV6YKSwCBQ/oc5xpEGMWoLR0gkFiRkrRCSSiKt9rZ26U4pHLQ8mynzIHQz6r5doMW4mE5MptCiOh194tCk0QxHumtW+NvxsB7tuvnV834VyTwlGoPgOdG8bcAvaPGYmVFVFbKvT2kNhXo6s/WpoaESPJsA1hqhvbqdmnAZg2u9ZwWttgnt3C75TK7GiHPR+wYX+4iLZpdkDAzDjgRxB4RMjocRboCCbnjuZ7eymshoqq2Fvfpp3fZfA1evB3eOh1mZFLzyUFzkY3KVDn63j1JkOhPCK+kguEuFQUyBaOgXVNYm1gAe7JsGEnL+AC8Qn1KIV34FCLdbBXax4PAKd3/0Q6plMhAhXU3wHEijG/T8HinAIbg0P7G8o8Q3w2TsuaqbVYtDrI/bN5XZjMEReT0NjvPO/t9/mlXffpaWjA6fTOer7lx56SFG7mgDXGKK+qY0jFiVu+iVR2O9ZAcBTjYJfzZBYku8VVj6RkUjx7dtXqBSFjlUbggZgBkNpUGYsgsW/36GEeCCSQcKYr8eYr2dGLYAO4THj7vMwz2Rn8wZBfz9kGTPYmdNOZamZ8hIzxYUm9DopocIbvPfAQD+kZ0ReN5GEE97+hBPfgYTKwuNbHnh/yRHhahRRsnQ7KcgdzsARToir7ZLiL8KjaTNWN6Fg1zdwdiOcEJ+eO3mU+G5YPVIsdOugMC8vYl88Hg86afy6ImpoyOXx557j/iefJD8nB51OR0FuLuXFxVh7e6lrbOSSs89W3LYmwDWGsHT3kp+bnexuxIVOh6DJBgtzRy5XIt7UEBih3FH6hIkMRo+wE0kkf9JA/EWZfxq5cNZJSSdx7lwHIMF0r6VTCIGl20VTq40N2/potzjweAQZtlzKc5xU5Dgpy3ZhNgwPTnz7DRRmSq+PrwS9JCU//7G/oAsnvn0C7bSlnVFZviPlovetI1eE+1+DWJ+R1g4HJUWj6xGEKtgD8ckXLod4xzWEcjGC4LNU4a5rPxI5WZHdDLu6+8a1O6KGhlyeX72aC047jeu/8x1+/8QTmE0mrr7wQtxuN5fdeCNTamsVt60JcA0A3G4Pep2UdNERD4QQvNoGc7PBoBtp/fYn0a4nwUR4+yHzqfiiOaZ2Y3EViMZ6Kre9QDETyt9bkiQK84wU5hmZO334+761u2nuMVDXZeKT/Zk4XBIGnaBsajUVe/opLzEfEM3D924sgryvF7ISPA5VKhz9xbePcCnofMgR3/7rKplpiUWEt3Y4mDYx+BREokS4HJS6m0RLOBHuI/BaB1q/AdIQDNhsEfenZUDR0PBisVo5evFiACZWVfHOp58CoNfr+eopp/D3F1/kmAPfR4smwDUAaGm3UFacIlFnKvPPRvhfi+CW6ak3uAgU4U3dRqYtLYVPGlTbR6BgkZPtQY6I8yeUFdyfYPuVI9AyTR6mFDmYUjScmtHphtaS6TS32VmzpYmBAZAkQXbOgXzlhZCTy1BV02gEuTcAM/XulVD4+33LmbGIRnzHilIR3tbp4KjFeSG/TwURnijx7d9GMBEezPodTHwDZAno7u2NuK/2Tis1FeMzHkhDIxom19TQ0NICwLzp0/n1ww/TNzBAVkYGJqORLbuVG+40Aa4BQH1zG9Xl4S0sY5Gevj4erxf8ZYFETXp8RVUw0ROtJbql18DRE/vwyFxfjWwogahh+Q50RVF7P6b5y6gGqsvTyJ3QAXhnOnp6vJU9d+/05i73pUYsOCDKCwrAaJLClpW3dApqJ6aO+0ko6k4pli2+Eym6A1Eiwp1ODyZjeB/kZIpwuVlOEoX/NfcX3++9PjBiPbsB9uTVY7FaKQjjC95usXLI3Gmq91NDY6xx2Lx5vPb++3zt1FOZWFXFlJoafvCrX7F86VL+89prlBYVKW5bE+AagFeAz5sxKdndUJ1Hfv4Nji4kqPiOJXhPDT/wYLg9EgY9IcrwRIccq3QgStPVRUss5y5Y0Kx/afHcXJg4efh62wYFlk5ob4XtWwVOh0Cvh7x8if2Fuygo9JY897mwWLtg3kLF3YsLwSyfkcR3MkV3INE8L263GJq5GEskQ3hHi9kF1du6ee6NN7j8q18NuV7/oI3M9LQE9kxDIzW56IwzsNnt3sBknY6V11zD5b/4BWu3bCHdbObu669X3LYmwDUAGLQ5yBhnP7gf/fIcXmqFfxwy8mUeSzn3aInGEt3v0JFhkmv79hLpWAJFOAT3dQ8mjqIR34HHqGYedX83nUjn0t/q6bO8p6VLVFRBRRWA915wuQTWLq+7yaYNgv4+AEFWFvR0Q5cF8vJFyFL0wY5BaQxBtJbawFSDkXI/x4qc50XN+IlOq5OifGPkFSMQLyt4oopJRUJp9c4lO+088fe/c/by5RTl5wddR2LsDYA0NOJBbnY2P77ssqHPU2pqWP3Xv7Krro7K0lKyMzMVt60JcA1sdgdp5thfeKnE57ecwy+2Ce6YIVFoGn6ZBEs9qBbRVLv04b9+Y7eRylx5GVCiGUQEDgLkCOBUs3wruV7BxLgPg0GiqBiKisEnyoUQWC2CLgs07IdN6wVut8BohPwCrwvLkokTyM4M/rMpZ5YhlrLnwQoXJUN8xzsXeEu7ndIic1z3oTZjwfrt46yj0mnyCJ68+FJ+9NJ/R30/YLOTljY6A42GhoYXg17PjEmxewxoAlyDhuZ2qsrGtv+3L9e3EILVHXD3LsHN0yUW58kX33LdNHwocUMJJ2wbu41MLbIH/S5Wq300lvhoxbcc63c83HV8yLFyRsrEAl4XFLsDqmth9jwJnzB3OgXZ9kqa2+ys/tBCX78LJCjMNVJeciBneYEJvV4Kew/5+uDvLhOK05Z2Bs35HEp4g7riO5r7TYlrUzhaOxzMmZaaKfBSxfodK5M9sDOEi317p5WSwuCWcQ2Ng5F2i4WnXnqJ7Xv3Yu3tpbaigsPmzeOsE06IKXOcJsA1qG9uY8qEymR3I2be6xQ82yxoscHv50jMzI7e8h1JKPiLDSWiMnD//gKqpdfAURP7gPi4ycgR4fEQ3/Eiln2FEsGWTsgP0FhGo0RtUTq1lcMi3iMEXVYnze0ONm7vo73TgdsjMJt1lBUV4M7spKDQ6/7iI9AlItLAIbDYSiLEd7j7LlFVMDssDooL1JmRU9MNZayI76rlxqFAzGNODp7KsUOCjBC1vto7rRQX5Ab/UkPjIGPHvn188+c/x+ZwMKGigqzMTD7buJHX3n+fZ15/nUfuuIN0s7IZO02Aa9Dc1snRSxLnFx0vHtgrOKYQfjdLwqSLj9tJJNEd6IYSzT7dHgljnCs/y/WllkMs4juU0Jfbr8DgS6UEuoR0dQomTRlp0Qh2zXWSRGG+icJ80whrrc3upqXdQXN7EWs/a8dm86qc7BxvakOX3YM+U0KKIsgwXGGkZAvveAy4XB6BwTB2qjBGKpKklntKsJzvPgJ/d/xFeCAu4E29xEpn8HiTdouVCdUzYu+whsY44J7HHqO4oIA//vKXVJeXDy1/+5NPuOn3v+e+J57g51dcoahtTYAf5AghcLk9GAxxVn4JYEY2FJjiJ76jJZp99jsk0o3RBWDGQqAQj6flO5qc4nIGCGqJbx/+Itxmg7S0yOI4VD/TzHomVKUzoSqdpQvzhipr9vZ4reuTbINs2a1HCJD0EvpsCX2WDkOODsk0uhBWoPhW2+qdChZvf1wuDwa9ugGAiS7O48MnmNUU4ZEwnTQv4n2xXgclAqpDWMC7xnFFZA2NaNm6Zw/XX375CPENcNxhh3HVBRfw1EsvaQJcQxndvf3k5SiP4k0V9g8IXmuD708YXjZWxDdAY7dJdgCmmigJtkwFtxO1BdWLdemcUT2ALkrDq5zZDkmSyMn1FgaaMEli4WLBi3XpCJfA1evB3ethsN2Jx+5VRLo0CUO2juOnOXG5vAGjgVb4eKYYjHYWIhLRuGq1W5wU5csLAIzmvgtXkVXOvZQq7iehMuAEI5QVvMIDLQYIFYHg8Qj00T4IGhrjlPLiYtJCuJhMrKrC7VFuONME+EFOfVMb1eVjv+KZG9BL4MteNlbEt2/quKnbyOQQAZiphBzxHejW4V/0JlymmGjOWzysmi9sTaM2V1mGklCEqwr6Yl06xnw9xvzh2SchBB6bwN3roaEeNm8QpEsZrDU0U+puojTbTHm2iwwBMcT+hLR8y7kG0QjfaOMkWjsclBVHFuBKBn2+cx7o9x+NEA8knGVbTau3fx74aLLoBBPh5cBcj+ANvcScgPXdbg96vSa+NTR8fOW443jl3Xc5YenSUd99tnEjy5YsUdy2JsAPcuqb2zh0wcxkdyMmhBD8qi2dH5ycR8aRY28wIc1ZRvOX6znyQACm//J4pQNUA38RFCheggU5+rLGBDuuUMJeSaCrUnHu6vVQUKxc1UZbfTRYPyVJYsUMm+8TIDE9twKn00Prp3tp6TXw/ruDWFkAQCYOSqVe7x99pEmuiPtVIr6VCF4l1661w87C2Tmq9SGQcOI1Wa4qcgn0/Q51fgPdUIKJ8OVuwVMGHT8K2LbT2kNBnuZ+onHw8tfnnx/x2e1289G6ddz16KOUFBaOWP7M66/z6+uuU7wvTYAf5HRaeyjMC/7CSza+1IL+mK97btSydS//lJ4BN984YuymUnRnFWPUW4GRQsj//8kW48EqUEJ4y2GgEPcX4cEIFFnhUj1GElOR+haIu8dDgczYM7UGR4H9DDwm37EbjToqc51U5jqZu2Xb0Pd9wkSryKZR5LFWVGHHgAQUMDAkzAvpxyAJRf7eSkWv0rSTHV1OCoMU4UmUm1M0IjxRft3BrN/hKtYGc08KFOEzBTRK0Gm1UuhXkt6bASVv1PYaGgcL9/3tb0GX//Pll4Mu/+Gdd7L2udG6RA6aAD+IcXs8SIwO/EoFgolvALFxJdLclSM+/+uTDlYsKRx1HMFERbxKyMfCwKCb9DR9UtxllBBJfL+ypjBopgb/7QOvQTiBFcs1i0aIuwc8ZAcZi8rdfyz55ZUW58mSHGRJnUxm+Hx7BFjIpFVksdlTRgeZUJKHcZ2gNNtFWbaTsmwXuWluJEl98R0LHiHQj8Ey9PHG/3kKF9QsNzbACMz3wPtffMHZJ5wwtLzdYmVybUVsndXQGMO88vDDCduXJsAPYlo7uigtTr2CC/Z7VrCpR/Byq2D3ABgkOLZQ4uTzZlEMeDbcQmv592n59C72ttv4ZE8fN51VnexuK6ax1U5l2diq/AejRW00gWr+olaO0ItVDMq1bOqiEH/RZJCJtshTOCJlutBJUEQ/RVI/C08qBQTQhcMl0dpnoKXXyM4OM92mUoSA7MZWyorNlBabKSs2kZGmj6mvSgdLDqcH4xhKP5gI6k4pHhF4GSwHPEQW3sGCMRd5BO9/9tlIAd5p5fCFs2LttobGmKW8OHEz6ZoAP4hpaGqjJoUCMJ1OJy/94mus7hDs6ofzyiVOLIZ+N7xtzOPh+7dRkGmg3+5GcDUV+SYKMg3ce+PZZM2SV0go1azfAI2tNiZVBy+Y4SPZ7ieRUJIlIhkW1lB4HAKdUcIrVkcTzgqejJkLOenmAl1OTAZBdZ6TmqOOGLG8t99FS7uDplYbazf10NbbgyRBdjbkFUjkF0BevjcbSzxp63RQWhg8AFPNAYwaJML9JFTgpVqpKA/xCP66YQMOpxOT0ev2Y3c4STNrZeg1NAKxWK1s2LGD+uZmqsrKmDd9+gj3LSVoAvwgpr65ndnTJya7G0Osu+Nr/GGv4MpaiV/PBPMBa6TppHmcADimHUljaw9pZgPlxdmqu87ILVKjZjEbgJY2B0cekhdyP6mIvzU5mPj2d0NR6l6hNuHcUdw9HvQ5OiB0SqlY3Zeisfj7rx+KUCI8Wl/v7EwD2ZkGpk7IONA33VDu8i4LQ9lYXC6BXg+5eTC7qozSIjOF+UbVXEZaOxyUFCVf/KVCMGawojtyUlH6LN1VyyNXEs0FJlVX8/mmTRyxcCFChEgMrqFxkPP0yy9z/5NPMmgfzlSWZjbzg4sv5oLTT1fcribAD2IGbDYy09OS3Q3A63Zi1kGhCc4uD15IxwxMqi5Qfd+BQjdUbudg66khwp1uD0ajLqUFt+84A8VjKMt3KPGtliUznDiV428dKLBcvR4MebqgaeoC2451FkXp9sECP8OJ7cBtI+F/3vxzl9dOBG82lsm4XB7aLU5aO+ys3dRDp9WJxyMwmXSUFZkoLfK6seRmG6IeILd2ODhsfvwyoIw1oh3A+ruZNKx2yhLhxyxezHuffcYRCxfSNzBIVmbqZoHR0EgG7376Kb999FHOOv54zjnxRMqKimjt7OS5Vau46y9/oaK0lGMWL1bUtibAD1LsdsfQtGOysd+zgkG31+fb5WeESUQub7mVGePFgM1Nulmf0uJbLXzCM5QIjyR+5QpXOZbmQBHu7vWQVm2Q1Y9UDOQNR6TnR4649R2vwaCjvMRMecnImAW73UNrp4PWDjs79w3Q3etCIMhM01NabKa0yERZkYmszNCvHIvVSX5eavwmJZNAv29/fL8T/tbvUCXnI4lwAazfvp2yoiJAy4CioRGMx59/nrOXL+eW731vaFlpURHzpk9H0ul47NlnNQGuER0NrR1UlSU/bZ/YuJLPJk7gzn/vYW42PDBXGmHVS6b4TgRNrXYq3PuT3Q3A+1IPZlENvAY+4RrJ7zuwjHo4wk35KxW7kazt/iJcuAWSn49zqLSAPmLJUx4L0aQ/VCuvt5xjNJt11FSkUVMxckatf8BNa4ed1g4HG7f30TfgAgE52QbKirzCvKTIG/gphECXghmZEom/37c/Su+zcCLcBrz/+ed89M9/At4MKMWFeYr2o6ExXtlVV8e3zz036HfHH3YYN3z4oeK2NQF+kFLf1Mak6vKk9qH9o1/wu1ca2dI4wE3nT2LplJHTz+NdfAM0rNvKhILYS9BHk5EjFHLdGXzC1WelCxTicguG+PAX35Gsz9EiR4S/sDctZFXJVLKGR3Nt1S6qo5TMDD2TajKYVDMcZCyEoLfPTUuHnfpmG59v7KF/wEVzu4OX3mqn9IArS2mhCbM5NbOi1J1SHLdAzNOWdgYdvAazfsslWDEeHWA2mchI9z5/bZ1Wpk+qUdhrDY3xSUlBAQ0tLUG/a2hpoaRAuVusJsAPUprbOjlycWAh4sTg8Xh47q/X8sCbLZyzqIBbV9SQZhx+0cY7q0SqiG+A5l4DSyf009HrZM2uXtp7nXyxt49zlxRy/Kw8WW0EFu6J5/H5BK2/9ThYzu9QBUOU7C9WIolwd58HfVZooRdonQ8U5LGK8FS6HxOBJEnkZBvIyTYwbWImAHWNg+ytH2DezBzaOhzsqR/g4y+t2B0ery95uoe8fG9Gltw8MBrHn6U8mPU70n0Vyv3Eh7/12///vu08nuGg457efnKyM2X1VUPjYOGYJUt48F//YtrEiSyaPXto+RebN/PQv/7FipNOUty2JsAPUlxuN0ZD4i//rro6br/nRoQQPPTNyUwtGxY3Y6UQjVr0DdjZ0+bgisd2sKfNxmGTs2jvdbF+fz9fWaB8VK2GNdyfUMGmobJFqCW+lfRJCfNMdtZly8++Ecw9JVoRHi/RrYa/dzJo7XBQVpxGQa6RglwjMyYPC0GPR/B5w26sFmj0y8ii00F2DuTlS+TlJyZVoj/xsIL7rN+hKl3GknbQn6rlRrb1CWo7h4vueDQXIA2NUVx1wQV8unEj3/nlL6ksLR0KwmxoaWHm5Mlcef75itvWBPhBSHdvPzlZ4fNOq4XYuBIAm9PDo++08uznHXz3hHLOXVw4VPQksMR5vIVbshFC8ObHu7jn8Q+ZXzuVK44tZfHELLr6XXzjoR388ZJJHDk1eDaIaIiXNdzfohzKPSOwWl+gMFQjG0o06SDD7c/SKdDnR+/qEOieIvfejcc1GeuD19YOB1MnBP9N0ukkcnMlcv0ysoBXmA+lStw/Upjn5HhzmOfley3miRTmSvAPvPQnXM7vSNbvSOzogxmTJgHgdLqSYpDR0Eh10sxmnvztb3n6lVf4bONGGlpamFhZyfmnnsoFp52GXq9X3Lb2xB2E1De1UZ2AAjw+8f3x7l7u/G89Mysy+Pf3Z1CydHnQ9eNtnVNb+CgVPb968C3Wbmni2m8cT07WIo4wPUPPoItr/76Hrx9erIr4DtZHpccf7DhDZRoJVSY7nMXa35Iu1/872nMf7t7q6wVdRWoLNLVQMvBJhJ+7tcdJXk50ryOdTiI3zyuwvQwL855usHZBfR1sWi9wuwWSpL4wV8MKHqzaZaRKl3LEd6Q0hNv7BNMneutAdHR1U5SfG023NTQOGvR6PRedcQYXnXGGqu1qAvwgpL65jcVzp8d1H2LjSix9Tu59rYm1dX3ccEY1R0/LCSqcAgVBPF74qSK+e/vtvPr+Dl5/9Ft8samcqtIipKqVPHzXdxiwezhvSfQVJeUSrRiXa1kORrD2I4nweBFOcAohaB7Ukz3Gp97VdMkJRrhnMvBaK+2HWoW1dLphl5QDLQMjLeb1+0cK8xGuLHmqdEMWocR3uCI7arGpF06dMgXwpSDUBLiGRjRYrFZeff99xcJcE+AHIR1d3RSq/GNrv2fF0P+NJ87lxbUW/vBGM19ZkM+z18wg3aQPWcwlGL999F32NVqYWlvElJpCFs+poqJEmWU4VcQ3wCvvbWPhrAqyMk+hue0tlh7iDeq4+vv30far73LfG83cdGa1Wl0NidpiTe459heKiSgvHqn9/n7QmSMLv1CZXqLN2pIKLlDxJtrBwMCgm/Q05dO4cglnMe/t8VrMG+thy0ZBb48NAH2GDn2mRKbLzqDeiEca7aqk1AoeTHwHorbo9tFmFzTZYN50ryGmzWJl1tQJcdmXhsZY4s6HHpK97u79+9m2Z48mwDXk4fF4kJBUDbbxF9/7BgS/fWwXdqfgT5dOYnq5168zGvE9PXcy73z6LkcsrCUvO42P1tVx35Mf8ve7zqe8OHoRrqYvdCzCddPOFh58+hMeucSb6svpcmEyeh/BzN13sXhSFjtaorcEBwqeeFtDffuIFTn3QiyzIeHa97m8ONpcGHKUl+COJte5RnC8AZjhg2DjOVjzF+Y+H/MX69IQQuAZFLj7POS6bJQ5+tAJb9YQh87AoN7IoM7AgM4YtQgPJb79rd+xiO9I7icfWOCIfIb8vjssmguKhgbAf157Tfa65cXFXP7VryrelybADzLaOq2UqFhswSe+7R7B3+oFz3ToueK4PL52aBF6nTQqwFIuK7+/nBv/73Xu/tnpfOvcJVx/z6u89sEOLjtHWcUpNUR4LKK2o6ufn9z1Mr/87glMzmxgcO2tmE0HspUc8JXf02ajKl9+No5A5Ppcx9JuMlBbeAVWwDQWRba+nra0c8gKHixYLtniOxFBmKEGQ7Huu7XDTmmR8vs+XkiShD5DQp+ho2m3nzgVApNwk+52kul2UOzoxyA8cDQ4dHrSt9lxDUq4BnV4nOCztPsIJ759xMvy7eO9TsFXSof75W8M0NA4mPny+ecTti/tiTvIqG9qo6pCnQBMn/j+3Cr47S7BlAm5PP21SkpzTaNeynJFlO9ldNi8Gq75xhE8+syn3P3T0/lk/X6u/cYRMfVXqQiPVWA4nC6uu+tlzjphNsdlNgDQ2GOkwvMZYuM7Q+t9vKuX355fq2gfoXyuIbb+R3u+QqVJk1vkR+1CPMHa98fd5yFtgrzy54HCO9p0i+NtIKMWrR0OZk3JSnY3RhCYYtN/AIYk4ZAMOHQGuvG7n4TAKDykz3VSuamLtEInOqNAAjwuCdegRNOsfE6e344QEmdPsMkqsvPe6wMjPh9zcmwZrPYOCLb1wZ0zvZ89QvkMkIaGhnI0AX6QUd/cxklHL4l6O383Ex/dTsF9ewWfW+H6cydy3EyvlShW8e1j2ZJJ3P3Ye3z0ZR01FflUlsY+RRpNjuxohGso66AQgt888i4FuRlcMcuGzxrW2G2kJm+klWvQ6SEnPXUeyUQLRp/gCVeWPhRyRHuwdoUHJL1yd6xQ+ZpBnQw0chirub999PS7yM6Kvw943JEknJIep05PfsvI51gyCDqOzSXd48RW56RM5+LTvZmsM7RQ5GqkJDONkmwX2UJCLw0L4kDxHYpILif+/GW/4MJKiYwD931Pbz952ak1ANLQSEXWbt484nNGevpQKk8lpM7bXiMh9A3YyMqMTuAEim8hBK+2wR+b9Jw8N49nTygn0+x9gSqxtvpEjNPlZtuedr7Y3MjaLY18ubWJipIcFs2u5DePvMPH6/dz+Hx1SiWrPWUfygr6j5fWsW5bE3+7tHIo7zlAc4+Rw2tGvlx1Ejjd6lujEuETLpdQ/VAiuoNtH1VApEsgKdR9/vsJJa6TbfEeCwghQMjLgJKIoN1QBAbhRotwSfQZzPRhJnOmneNrPUzPrcC+7j3a+w209Rn44v1eLMzDjYR9lpucwQG6F3ZibuvB1N6LzuGK+TgsDsEaC9w4dXhZe6eVYhXdEjU0xjodXV1899Zbue8Xv6C82Fuh1uPx8O2bbkKSJO/vFt70hE/fey9TapTpEk2AH0Q4HM6o/Pw6rVZW3XEZPU7odwtsFUX0293s77TjdAvu+0Y1syuHp0Mjiby+PgcNTX243B4q08vxeAROl5t39nzC2i2NbNzRQlVZLotmV3LGcTO5+bsnUJTvrYh38/dO4Jf3r6IwL4PTj5nB6ctmUJCXmGJCShBC8NC/P+Hld7bx569XDA1QfDjdEiaD9yHuHnDxu1caMeqlmHzA1USpeDSdNG/ENLoc15NYxXewtgKFeLB9RCpBH4xUC7pMlYGVUvoG3GRlyv9NSpQIj+WeDBeM6V/pUmx6F5MBKnOdFH/yBbP9fiL2b3XRk5ZB8axsvswpo+uIqXhM3vP0UZ6TvIG+ob90h112397rhMPzIUMvYb7uOQDaLVZKi5RX3tXQGG88/O9/k5GeTmnh6IH372+8kam1tQghuPOhh/jLM8/w6x//WNF+NAF+ENHQ2kFlaVHI732W7l39gqcbBe90wpH5UGKGnBnllJl1ZJq9Vu+lU3Iw6EdXsgxG604dv3/iA1o6eplcU4jJqEeva0Cn06HXS0ytLeKiMxayYGYFOZnmoG0cvWgirz38LT7f3MCLb27hhTe38J/fXzTCqpwquN0efvPoO2zc0cLjl1ZRmDVyetjmlDAbhi3dL6610DPo5unvTg95PPGqahkP5Ihun4gKFDrRWhqDBUQGa9cfn4je1i/ImgxVNW5ZgiuY+I72mkTjAhVPAgcPckWt2jn6WzsclKVgAKZSlKQjDOb3rROCvMF+8gb72f/u8EyZAOadWUB3RhaWzGz2FpczYEoj3S2RhosiqZ8i+iiS+slncIQ7C8CaLsExhcPiG7wCfM505dPoGhrjjQ3bt3PeySej04020JQUFAxZxb9y7LE88p//KN6PJsAPIuqb2qitLA36XdOvz2FdN7zQItgzAOeWSzyzGPKMXkFoWhZ8Owjt9wqwr7GLW/7wBr/64ckcOq8agz6CxVE6zq/ht0d8pdfrOGxeDYfOreb8Hz/FF5sbWDI3/jmzo8HucPGL379OT5+NR28/l8w9H49ap6nHSEXOsP93eZ6JfR02WrqdTCoZ7ROhhpUzGjeUeInDcPtXOsUfLjMJhHdJ6eoU1EyQIq7nT7BKn45VG2QHmfpIpBCXYzWWa1lW2+ovJwXhWKLuFO+LOVCI+5b7UFpsRwKy7Day7DYquzqGlleVG7EJAx1k0iEy+dJTRRfpeJDQI8hngGKpn8rcXnYO9I9os6dvgOwo3RI1NMYzDS0tVJSMTFYhSRJHLFxIZvrws5KTlUVzW5vi/WgC/CCiqbWDIw4UfvHnzz84h6caBXOy4dQSieXFYAqwxMoVGWLTuzjd3sh/g17inif3cPlRBSw17oOt+2DuygMrvj16Y3/x7fscZD1JkjjlqGn869UNLJhZgdGQGgFcvf12fvSbl8jLTuOPvzwL4/YPg67X2G2kyi8A88Q5eXT2Obni8V2U5hopzDSSZtSRZpK8/772FOmVE1ma08f8mkzVKgYGkiirbCjrdzD8hUygiImVgQFYWD4lrPCUW/1RzvMRbAASy8xGNAMzNUW4mrR22Jk/M/UCAMNmQZGBvxD3/X+E+0l9w4j1o0k7+N7rA0EzoaRJLqropkrqHrHcJSS6yKBDZFJdUMRbPbU88dvb0E07nOzMDDq7eti1r5HiwjxysjNVrRGhoTEWqa2sZGddHUcsXDi0TJIkHrj55hHr7ayro7q8XPF+NAF+EOF0uTEG+IDb71nBtj6BW0D9IDzTLHi9HXIMghwD3j+jRI4BCrZ1k5OuJyfdQG66nrQPt4wQ6t1OwQuZpTz9cQe56XpuXVHDl/v7+M3XvKn1JJ/4htHiOlB8h1rvAOedPJef3/sa3/rFM/zksmOYN70samEqhGDd1ib++/ZWAG753vKotveno6uf793+IvOnl3P95cvQ63WECqds6jFyaEAA5gWHF3PukiI21PfTb3djc3iwOT3YnAKb00Nvax23vGklzShx/mHFnLEgH6MhOv/lcFbweIvvaK34waby/cVMIK+sKQyZJtAfn6D2CMGnpuYRyyIR7Bz5WzGVWMIhce5FckU4JC5zSv+gm6yMsfEailaEAyPEdyjCiW+5WVAaVjtDZkIxSIJi+imW+pmRJnhmq6BYJ3HKZA+Wqh/S2dVNp7WHbbv3093bj0BgNBgoys+luDCP4oJcigrytDzhGgcNs6dM4blVq/jaKaeQnpYWdJ1Bu50XVq9mwYwZivejPVEHCeGmGX89U6LXBT1O6HH5/R343GwTbHdBz6t7h9brPrCOUTog1I3QZodjClt4+FszWPPydi57eCfnVoDh3c1Ifj6Howglvv2/PyDC/YXBNdfM4c139vOz/3sJs1nPsYdMZXJNIZOrC5hcXUh6mveFNGhz0tbZR2tnH20W77+tHX2sWVeH0aCnrDibjDT5abwCqW+2cvWtL3DGcTO54muHRhwIONwjfcB9GPUSiyaEtgZefXwZn+zp5ckP23lqTTsrz6lmTlVmVH0NVjUzVgLFdbT5x/1FTSQf2lAiPJzAgdEi22J1UpgX3vUh0rkJlfM8GGoHS8bSnpwBRyKs4b5MAtGSzGwokQoyBeI/MPQPvvQR74I7gUiSxM8mwy+2CY6yubA5nEyqqeDwhbNGrOd0uujo6qa908rWXfvp6NqA0+kGICc7g+KCvAN/ueRkx29WTkMjGVx1/vm88eGH/PDOO7nhyiuZUFk54vu6piZ+8/DDtFssXHn++Yr3ownwg4T65jaqgxTg8QXjZAChvbyDI4Rg0Gaju6+P7t5eCvPyKC7wRtNPLlnJua+vR3/gh9l+z4oRgT++6o/SnGVecR1GhG+3Php0uU4nceLxtZxwbA1btneyc1cXH6/v5x//+5L9TVbyctLoH3TicLooKciipND7V1qYxYTKfM48fiaTqgq4/p5XmTlZWXGibXvauOaO/3Ll+Ydx3slzh48vhHgLDMCMBp1OYumUHA6fnM3rG6388B97OW1+PlcfX066Sb41XC1raygRGE4cxiqc5IrvSNlKmtvslNn3IDZtHvVdOKIR3T7kiOV45acPRK61PxECt6fPRW5W6r6CAt1QfMgR3oHrKikuJdf6DdHlAZ+fK7FsfgH3vdHMV862UlyQN2odo9FAeUkh5SUjLf5CCHr6Bmi3WOmwdLNlVx29ff0IAQaD3ms1L8ilqDCP4vxcTCblhg2Ngxe3282adet49b33eO3997nzxz/m5KOOGvH9fX/7G2989BFGo5GzTziBb5177tD3/YODHHnhhaPa/da553LtxRdH3H9BXh6/+tGPuPn++znvBz9gWm0tNRUVANS3tLB9714y09O5/Qc/oKxYuWtk6v76aahKfVMbh8yeGnnFKJAkiYz0dDLS04eigoe+m7sS/aqR+cPt96zA872n2PbmL3G5BU9+2EavbScXnHcMJx4h0OmPH7WPUOLbH51OYs7MIubMLBoSGC63h9aOXrIyzORkmUdZaNxuD+9/sY8b7n2NBTMruOC0+dEePp9uqOf6e17lpquO54SlU2RtExiAqQRJkjhlXj6HTs7mdy83cP4D27j57BoWT0ycL60SEai2+JYTeBm0ONKmd2nekc3ccnnXQYnoVkowIT6WUw2GveadZZQWBc96FIlEWcF995LStISB1VIDB1hVy41BreDhxHeslTBNJ83j2kEX5/5hO7Xbd3HyMYfL3laSJHKzM8nNzmRK7Uir4JDV3NLNtt37+cDSjdPpzV2elZlOUUHukNU8LycraIYJDQ2Arp4e7nzoIdxuN26PZ9T3d/3lL6z64AN+fNllDNps3Pv44+j1ei49+2wAevr6ALjle99jQlXV0HbB0gqG4oiFC3n+j3/k8eeeY8P27Xy6YQMCmFRVxddPP53Lzj2X/JycmI5TE+AHCR2WbooSXGzBfN1zI4r4NA4KfvqtC9g9AGVmuPr0GrLT9Dz2r3d55D+fcvUFu6mcKa8oRyh8adIMel3Qypk2u4t/vryOf726nuKCLK677BiOPdSbgmvQ7kRCIs1sGPFyDybiVn24k18//DZ3/fQ0lsypGvV9KHwBmEIInvmsk5fWWRh0eMjNMJCTpic7Xe/1s0/z+tqP/KwnO927nkEvUZBp4Ndfm8C727q56Zk6Fk/MYnp5OmcsLCAvjn61agjCYIImnPuJHPEdaGUMJb4B2vsMFGeOLGwSq9AO5v+t9FwlU3THKmzlbr+poZlFkyojrxiCRLqi+N9b/veuHMt2tCkroxXfcqzfgfdmdrqBn51eyfPrNnLeqRFcAGUSzmreNzBIu6Wbjk4ru/Y1Yu3pQwiBTidRkJfjFef5Xst5Znpwn1uNg4ei/HxeefhhmtraOO2KK0Z8193by/NvvMGvfvQjTjziCAAGbDb+/uKLfOOMM9Dr9XT39gKwdMGCmCzU2ZmZsizmStEE+EGA54CvZTKi230i/OMuwcrtgm/XSBxf5A3uzFzodVc5dkYOH9hq+NPTH9Nq6WHyxDwmTcxj8sRcpkzMIytLnTRlX25t4he/f51Zk0v4/Q1nMGNSCdu7d7O9ezcfftzIX/++hUGbE4NBR06OidwcMznZJnJzNjCxuJSC3AycLjcffLGPumYrf155DjMmBn+4O/ucbG4c4JjpIwcBvgDMf37cwbOfdfLT0yrJy9DTY3PTM+j967W56R5w0dIzSO+BZT0219D/++xu0ow6sg+I8qw0PW6P4OX1Xby8vgujXuKCw9XNGOJDqTCMRSj5i2+56QbDiW8AjwD/jJiJsnIHnodUKOaTLKxdgtIYc4Anwx9ciTtJIpEbCHzCrFxe3W3ivc8/45Sjj45bfyRJIjszg+zMDCZVj8wY4XZ7sHT30G7ppq6pjS827aB/0AaA2WQ6EADqtZwX5uWMSiKgcfDx3uefI0kSRy9aNLRs+dKl/P6JJ1i/bRuHzJ49ZAEvyMtLUi/lod3NBwHeUsOjrcGJom5AcPM2wW9nSSzMHT0I0M09lmOAkqke2jsG2b3Xyu49Vl58aRd763rIyTYxaWIe06fmc8KyGkwmb9pBl8vD+k3t6HUSUybnkZXpfZmHKhbS22+nf8DBBafNHxLfAK+v3scLL+/ipusPo6Yqm0Gbi54eB909du+/vXa6e3poqGvH4xF8/SsLOHx+DelpRuwOlzeos7OP1o5eWjv72FnXwYdr67DbHaz66Wxy/azRDrfErtZ+Hn23lb9fOZWK/Oin4D0eQb/dPSTa+2xu8jMNVOabSDepl5JRLStsqonvQadEmnHYD18N8S3H+h3sPPiWjQUhrnYf7XZITwt+v0bjgpPMoEw1COWGEkig9TvQ8h1NBh4hBE+t6WDQloG1p0f2dmqj1+uGAjoDsdkddHR102HpZuP2PXR29eB0eWetcrIyKMrPo+iAQM/XXFoOGlra2yktKiLNPPzurCorw6DX09zhzY3f09eHwWDg6pUr2bhjB8UFBZx/6ql848wzU+o+0QT4QUB9UxvV5cqCDNXghRbBinJGiG/fy8L3ct3evRtJkigpzqCkOIOlh3oDHjweQVNzH7v3Wvnk8xY++qSJX/7scGx2N3fe/QlGow6jUcfuvVZKizOZNaOAmdMK6ZluZ0n1yMj+YxZP5PYfnMTP7n2Z0pIMpkzMo6Gpj+bWPm698QhKir0vuIx0IxnpRspKM3G5POzY1YXZNIhOJ2GxDPL31z7jvn++R3eXk74BByWFmZQWZlFalE1pYRaL51Rxw3eO46cr/8ELay1ctLQYg17C7pJwu93c+J86fnJqhSLxDV6f9+x0A9npBirzFTURFLXdHqIVRXWnFIfM+y3H5QQii2+A5h4j5dlewZNM8S3n+2QI80RlQJGk4IPlwOslp4iUfxtyqnWOZcEOsYlvgCc/aufNrYMcvXQGK046Sc2uqUaa2URVWTFVZQFFjISgr3+Q9gPifHed16XF4/G6tOTlZFGU7xXmRfm5ZGdlaFlaZLCqIY2M3sQVZHKMdu2WRYfVSm7W6HinnKwsOrq6ACgtKmLahAmcdcIJXPG1r7Hqww+5969/Ra/Xc9EZZ8TSbVXRBPhBQH1zG8uPXBR5xTjR4YAjC0L/AIZ7Gep0ElWV2VRVZnPMkVU88Mg6rr/lffr7HSw/tpavnjMNSZJwuTzs2dfN1h2dvPNBPQ8+tp78/DUsnTOBk46cRktHL419rUybks99vz2OjZs7aGju5fDKco44rGLIqu7D7fbwyqq9vPz6HvLz0ygryaSwII2K8izmzi6isCCdwvw0cnLMzMwPHoB5zZWn839/fom/fdBGbroenTEHgzGbMxcWcNr8AmUnU2WS4VISKaBNib83yBerzT1GynOcKSO+wxFs27FgLY9EXy9kZY9eHspPOppKrnLTLEJqCvFjTs4Y5QceKvBSSd75Ppubv77fxs0r5pI1ZTom49jKVCJJEtlZGWRnjXZp8Xg8dPX00Wnpprndwsbte+ntG0AgMOj1Q/7mPoGu+ZuPPSSCpzAVDLvZzp02jafuvnvou8Pmz6elo4O///e/mgDXSCx9A4NkZ8UWOa8Ut9vNjj74WsXo76IVf5Ik8b3vLMBaZ6KkIItJ1QVDL1CDQce0KflMm5LPWad5Led19T1s2NzOHY+8QUV5FkaDjhde3kVfn5Opk/OYNiWfgoI0LFYbvuGB0+WhobGXl1/fi8mk58brDqOmOnykcyg3grnTynjs/y6n8f1V2JyCzW25zCrzMLkosbl/A0lGBhO5RKp2Gcr/NhpR2tJr4JCqAUwnzYtJhCsV3y/WpcfkR5wIUe5vBVerbd/A66zaQboskJ8/clAeqbpoNCJcLslyX/G/7yK5n0RyPfFHTlGnf33SweGTs9EbMihOcGB+vNHpdBTm5VCYl8M0qkd853K5sVh7aO/qpq6hhS82bmdg0I5AYDIaKczP8QrzA+I8zaxO7JGGuhTm59N9wMfbhxCCnt5eivJDTwkvXbCAj778kkG7nXSzstlntdEE+DjH4XRhNCTnMns8Hq791a8oT4M5QaxdSpiRNwXyhj8HTj370OkkJtbmMrE2l7NOG2mhtnbb2bmrix27u3jmhR10We1D3+l1EpUVWRxzRBUnHFuDTid/6jKUYPG5mnzenE5lbveo7RJJtAImEeIkXIVBf+u3UvEdKEoGnDrSjaMtKLEi59z6RKi/GFWDSFl7/Akm0IL1XU1RHzjrYe2C8jAJUHwCNVEiHJJjDY+lEI//efE/J+FE+Me7evn7R208fvlUvnQcxqJxJsDDYTDoKSnKp6RotEhzOJx0WHvotHSzc18Da9Zuxu5wIhCkmUwUFeRSmJ9LUX4Ohfm5mLX85kmjoriY1o4OBm22oSqV+5ubcXs8lJeEdrV1OJ2YjUbMKTTjownwcU5TawcVpUVJ2XddUxN76ut5ZrY0wgdPybQpRBYEcq1ZeblmliwqY8miMkX9iEQoH1SHa2TwXyJJZat3KCKJbyUC0e0B/zGVUiu4nHtYzvlTW4hHIpyLB8i/T0IJ4VAW/0CsXYKZc4YvhH+/Aq+H77PvnMdDhEPo+0nt5yCa+01pzu9gIvzfn3TwyDst/O6CiUw8/jd88PwqzQXjACaTkYqSQipKRhsCfMGgnZZutu7aT6e1G4fDhUCQbjYfEOdeYV6Ul6MVH4ozxyxZgiRJvPvZcPae1R99RGlhIfOmTQPgxTff5CvHHote73UtFULw5scfM3PyZC0IUyNx7G9qo7o8PinpIpGTlUVfVzs2t0QsBe/Gg8+r3SVh1GviG4JXGAxXXVAN8e0TJO39BoqzXJE3iJJYBaG/W0q0eaYDCTUAVKsCajiCDYKDHYPLBUajNC6ebaWEs36HEt7B3E/k3Ht72238+a1m/n7VNKqO+bX8TmqEDAYFGLDZ6ezqprOrhy079tFp7cHh9F7X9DQzTpd91DYakalrasLS3T0UVLm3oYEvt26lIDeX2ooKzjv5ZH7z8MM4nE4GbTYe/ve/ufbii9HpdHRarfzx73/nxTff5OSjjqK0qIjn33iDbbt38/ivU+ve1wT4OKeptYPDF8xMyr4zH72MLL03CNMnwAOzn0Qi2hd0tD6dgUIwXpZIX+DfWCAW8R3KJSgQORUG5aQXjAZpzjKaX/90KAOKj2it4EpncCIR7Fwo8RdPdVHr8XgzoAQj3HXwd0eJlxVcbaItwiOXaO5Bj0dw+4v1XHFcGZUH3OEGBm2kp6WGH+xYJiPNTEZ5SdAsYwM2O2s3b01Cr8Y+f3nmGf771ltDnx98+mkefPppzjz+eG679lquu+wyDHo9f/7nPzEajVx1wQVDwZWFeXn88957+cszz/D86tXUNzczfeJE/nLnncybPj1ZhxQUTYCPcxxOV1KmxOz3rOBP+wTNdkg/kGAk1EsjlQRDrAFyEPx4GruNVOaODQGuhGDHLEeMB7OG+5ZHal8JLeZJLEnfpnj7eInvcKhxT8oRgNEI2nDrRhoE9/ZAdk7ka9qw2hk24HCsiHC1kFPxMhgvrLXgdAu+duiwK2K7pZuSILm3NdQjI81MWXFqZLsaa9x27bXcdu21Ib/X6XT86Jvf5Eff/GbQ74vy87n+O9+JU+/UQxPg45je/gGyMuLv4+dfbh58OX4l+lxQlQbfWCtYPC2HWwZd5KQbUualGcr6qobgCaSxx8iiqtAlplMFJdZvuWnfwonwWNqOhk6rg8JlRyJJkmpWyWju51ADjkjE6paSaMJd7y4LzKosHfrsuw7RZAZRSrS+7rEQNA5E5YqrkY6js8/JH1c38+dLJ6P3C37wFmfLU7UvGhoa0ZE63ugaqlPf3E51RXwL8PjEt0cInm0SfHudh2M+FFyx3kOWAf5wxQxe/flcctL13PmeI2XEdySUiKRw2JMYgJkqKHEnUhshhnPFRnsvRmP9juR+E42I9q0f7XbJJtT1MwzmU1oU3v1BqbU3HP4DLrHp3YT4xKtB1XLjiPMh5z70HdvdrzRy1sICppd7f8+kuSsBaLdYg1af1NDQSByaBXwcU9/UxoKZ8XPvEBtXAuAWgl/tENTb4KpzJjG3KoMtTYN8uruXyx7dyZFTc/jWt0/naz/8B84fnITRoF659EDUDB5Uyz/ckcQAzGiJ1oc+FlGd6CIzvX0usjPV/cmLZUCZSmI6XgPjYNdzbWczxxzqFZThRHAkEa5GnxORUSXUMcopQR/LQOTDnT1sbBjg5rNrgGHxDdDV3Ut+nkq5YTU0NBShCfBxTFtnV9ymGX3iu/eImfzmpQZ6stw8eOVE0g9UlDx8cjZLz/oK3x6w88+X13P5Tc/i9ggM+vhNusQ7bZ5S15TmoiVU5GyOQ4+SS6xiOdbtw13vYG03t9spL45/cY1kp28MhpwCLYnC5RYYDSN/B+S4ZiTD/z7eRCuwozkHv32pgZ9/pYp0k26E+AZwezzoUygdm4bGwYgmwMcpngOlWgNzXgb6a/swX/dc2PZ827mFoH7+NNbV9bNufz8f7ezhKwsKuP3cctKM3n35W5SyMsx856uHsnhOFY/+59MR+cAPFhpb7VTOnwW9nyV830qse8mqDhgNkfoXrChSc5udidXDsxqxCtKx4k4ViUQeh8sthnyRYzn/avY5khU80vMQbiAZ70FPuL7npBtwe8Ro8e3WxLeGRiqgPYXjlA5LN0X5uaOWm06aR69LsK1P8GmXoH5Q4PKIIYt2IIN2O5/99zqeMJXwo5ZMTvpc4mdP72NL0wCHTsriX9+bzk9Oqwwqvv1ZOLOCB24+W63DG0WiBKMS3/DGVhsVls/j0JuDk2iutf+6Le0OyiL4HsdKKgxcQvUhnkJb7nF3djkoyjeFLbwTjFit3/EQwtNzJ4cU36F8zE0nzVN8LHK3c214h8ffa6XJ6sC0Yd+o7zutPRTm5yjqg4aGhnpoFvBxSn1T26gATJvdzp9ea+TZtRKV+SayBm0026DDJVG2dQs1tT+gunw2lWVltHV08OXWrezav5dptUXML3Zz3uJCbl9RQ0HWyGnTsWoJjCUjRTSuKDa7Jy6lz+PJWLCCR4vD5cFk8g4UoxVkgeJHbhXIZBGqGI/az6r/MQebdQikZe06SgFGVwMPiZxzHyvR+IJHcp2Sc2+p6U7jv78Gi52bn9uPXifx11luytJGzzi2d2oBmBoaqYAmwMcp9c1tHL904YhlN/7f/zHQbuO/P5pFgV8wmsPlobHLQUPWVPa3dFPf/DlShp1zzyvi1PknkWbWbhO5BL6cHQ4PJsPYnGhKRRGupD/bu3czKXMiBr067k+JEN+++yiWdkOJcDUI169wlThb+7KZVz48eI02LV8yB/vhrN3JRgjBi2st3LeqiW8dU8pX+5qHsv0E0m6xMrm2IsE91NDQCERTVuOU3v4BcrIzRyxbtmQJzzy/gbz0kVlITAYdE4vTmEg90hlj05qdqjS32ykviX/gX7wIJjpSTZTLobXDMZT6LlbrdzwJPN+xDoLkWKWVoLRfHf0GCjNdstf3P/fxFN+R2g41oIjX/qNpWwjBPa818fGuXh751hSmLv9t2PXbO60cvnCWon5qaGiox9g0zWmExel0YdCPTvV3xnHHIYB/rGkPuW0qWHOiJRaBEu9UcI2tdirLQhdDkuYsC/sXC/FMLZes6qVK99vcpiwDSqyuJ75zFanf4dZJpUqxcgl1Ttwe8E0IRbJ+qznwCfcsKHlO5P5ORjrGUM95NH168K0W1u/v57HLI4tvAJvDQZp57BoFNDTGC5oAH4c0tXVSUVo4arlOp+OO82p5/vNObnthP3anJ+j2iRThY1HwRyPaG1vtVJSaFb9k1RDi4w0luceb2x2Ul5gTer8Fs2YHE+RyK4nGgpxBarTnJto+Od1gUJgPX41nIFah6yMwgDTcn28dOf0JvEZy+rbu2fX858NW7qocJPfQOyL3XYytWBQNjfGM5oIyDqlvaqO6PHgFzNpCM09eNY1bn6/nGw/u4NKjSzhxdh5m48ixWLxLNgdWpVO6LznCIlSgpdrW72CCZNDmJiPNOxvhn4s52mNNpTzOY5HuHie52dH93MUS/BcPUS3X7SOU/3g4n3DfvRXP5769z0CxTPeTeLmexNpWtNlb5PQjMJBV7n0x+Pp67tgh+NEkiYobnpe1Td/AINmZGdF1VkNDIy5oAnwc0tDSzpL5M4J+J81dSRZw1yLBu599xr9eeYV7/7uOM0rh/PNnUZE3cmoyXpXiEkW4LCdql5sPxOn0YDSMDISK5VxGI8LH8jWTQ6iKmkF9dX1Wv83vhWzPdNK8IUEl1/UhlBhOpstIoGVdqQ94PIR4a5+R0uzIAjzS+Y9ncGk4YhHfjlUbRhyX/++qkuvkWLWBdzogXQ8nFcvvh5YBRUMjddAE+DjE4XRhNkUo4yxJHHvooRx76KHUNTby9J3f4+v3beH0UvjBJF3Il4UaHCyWXG/lRXXzTmuW8NFEEi3WHhd5OZErDoYTfpHcBeT2JdHI6U+i7qfWtEksMm8b+uw/6AmFGpZitVFq+Q4U4f5EE+TpWLUBIQSP1QuurpWiKm7WbrFSXDC6PoSGhkbi0XzAxxl9A4NkZYQO+gtGbWUl1z/wAs8tkXi7Az7uEqP8GMei6IuXhTtYu8FeoI0tdirL1C/8EskvPNWs39u7d4/4SzTNbXbKS5Rfh1QS34kWnZGe+3D9CTxPFquTwkz3iGW+wjQ+YRpKoCY7847vPAQT3w2rnTSsdia0Px9YQAKOLIhuu7ZOK0WFefHokoaGRpRoAnyc0dDcTlUI/+9IFF7/PD+aJPGnvfEN1AnM8hGvQMN4ZTiR2643ADO6wVA0hDpnvip8/n/JItnCCaCpzU55z0ZF28oV34lEzWwpcu4Nte4fjxDo54Z+zqP1uU/UtZBz/FXLI8+wyG030jMrhODxesFl1dFZvwG6e/rJy8mKahsNDY34oAnwccb+pjaqy6NwCgzAM7cGf2NhvHMgxyK85byAz6odjHuqwVDCZ8DmJjMg53o4lFiK5Z6/sTiDoRZtnQ5KsuTnnvYR7b2ZSHGeaq4ukbA7PJgOBHrLzf7jI5mDHjl+30rEt3/7/oJbznP65ZRJDKSZOflC72+z+brn5O8PEbJAj4aGRmLRBPg4o62ji9KiKOo8B/DZ3j4OPaxixLRwqqHElSHeIjwQp9ODMUTlxUChHep45B5nNCL8YBTi7q52DPLHQUDql5qH2EV4VMVewqwrxw2lrdNBaeFwgLdcF6pI5zye1yQez0o4/3G5+/vLu61865hSdDopKvHtdLowGrSwLw2NVEF7GscoYuPK0Qvn3OK1cOiUj6s+39PHV5eMziGeCn7Fsb5sfSJcTd/wUOKjud1BWRC/Y6Wl1NW0eI71zDbRYLd7MBmic6kaC+LbRyIt4bHcN60ddkqKwhd/SZV7MpgQjiXloJpsbhyg2erglLn5SHNXRrVtR1c3RflaAKaGRqqgCfBxREdXN4V5OYq3b7NYsA64mFo6UqBGEiTxFAHxED7BrOFyRbn/tuGOu7HVRmXpSAEea0lxtc5zIoVOYO7qRLtOtHTYKcuWHyA3lsR3KhEpR3lrh4PDF+aNWKaWj7caz0aiZoZinVVs63EypTQNQ4jZtXC0d1op1gIwNTRSBk2Aj0E6rVY6WwaZUJw2ws2hobmd6gplAZgAn23cyCETstDphtuUE4SmtoU2GYLHX1irYSFvbLEzb0b20Gc1jimZqddiJVn9blq3ifJsd+QVSczAJJjQSxXLb6wEE+G+697V7SI/V/7rJtrnRe4gT4nQVsv67S++g7UpR5xLgNJilm0WK7Om1CrbWENDQ3U0AZ4AtlsfDfmdT+x5PIKfL/yGrPb++9Zb/PHv2zHqJSYWp3H0tBy+c2wZ+1vaWHbYfMX9/HzTJhZPHI6Qj9YXM1qRlaqWxbNqB4OKcLnWbxgZgJmqxxktSgcAyRw0NPcYmVNmi7heKBGsRAhGqjYZbPl4E+GB5yCa4L9Yn5dQ1yAVxHe49vy/CyXGdTrlArzD0k2RVoRHQyNl0AR4HGlub+eN9Q/S1+egr99JX7+T3gP/7+9z0NjlwjHowDHowKCTmHN9M1sMFfxs/kVh2z3z+ON5/D//4B9XTaOjz8V9rzdhdzVTOKmf3OxMxf39/It3ufDCiUB8shBE206gCE50IKVSnC6PoilipSRi+tx37caSFV5sepd+Rz5ZZk/IdcIJXyX3vZJzM5bEt5zBQuA5GLS5STNHjoJVc6Cq1n0qp1iQHJRUzvTvg49tTYPkZUYZUXwAp8uFyai98jU0UgXtaYwDLreb2x54gLc+eZ8Z0wrIzjaRlWkkO8tEWUkGWwazyEk3UZtu4sOtpZxx1ADNu1q48/4vOe27kVMIFublcdKcPF5ca+Hq48vot7uZV51Fq14XdV5YH2LjSqwDbgqzRt4SybDeJiJIMl5WNoCWdsdQBUw1z1+yS5yPJREuNr2LR4CWcU19orXYB2ZAUcKLdelJG4CrJcKV4tt3y6Lp/PPjdv5x1bSo2/AoNZtraGjEDU2Aq4zb7eaX991Hk2Urf7p3OWY/y8+Lden0AZvWFEK3d5kuDVZ9noVw5eG0f4bLIS9f8fmHFfGdx3axYnEhln4XU8oL0BlHZy+Rgy+jytSyNHa02lh6+HIgOvEYSZBFakvtqpWR+hMpaCyQaF7+jS02KsvMCRHfyUorOBZEeGe/nsKM0M+T2tbvSEhzlo24XtGI2MDrrIbVPLA/8aKl3UFphAwowc534G9CtDNiat6jyRbhQgh+9detXHZ0BRX50Vd17entJy9bK8CjoZFKaAJcKeLtUS8Nj0fw0OMbaO8Y4Oc/OhSTaaT4BnhljVck177WPmLbHTNbIbeajBx5QvSjXb0snpiF2yNIM+po6DZTPS9yAGZg+sLP9/Z6t7c4sDk97GodZKmsHqiDkuwjkUi2MGxstTN3ejYNca5OfTDm9I6Gll4jZTnBBXg8xLec+06JcA52nX3LxoL7SmungxmTM6LaRs7vQjSCXE5qwUhBkJGCKOPJ6+3Q5YTz+pqB6APttQwoGhqphybAlSDepq6pi0+2NjN1ch452WZ6eh089vdN9PY6uOG6Q3m1ebS14ZU1haOEN3gDlOz7N3H81xZwVu0g262PMj3v8pC7H/jil/ztgzb+fOlkbE4PpoxMGqUqFpXJq4DpdAteWmfhsElZXPPkXmoLzVQWmDhiSg5HTVWexjAUoQSN2lZvUEd8B+tXsClw33EF7rO1p4cGZ1/M/fCR7AFFKFLdCt7cY2RBZfzdFuSeg1QUzYmwgnf3OsnJCv2qUWu2wffchhPicoIg5WQjCSbG5QRaKqHNLrhvj+Du2RIGnYRj1YaoCvCANwNKWVGBqv3S0NCIDU2AR4t4m8ee/Ywn/vsFE2tzeOSvGxgYdKHXS5y6fCLnXblwlPgOZfX2sXuRnZxGweXHZA6/zMXbIB03at3+353Dfc5CFtRk/j975x0eR3nt4Xe2aiWtVlr14irbcsc2xZhuOqabACmQBBICN6QRQnpxCgkJIbkh5KYSIBAIEHpCMabYFAM2uPduq2/fVds23/1jvdJqtWW2qNie93n02FrNznwzszvzm/Od8ztMO/dCXnlnJ5MaQvQFZAqMyvIsW90BfvLsIT57WhUFeon6MgPLrhiH2TRyH4dMxPdI5n6mGleyPNRYAREOC7TZ1UglZKylnhxJ2Lt1KVNQ8kE68X0knKfoA4HSsWbzAJFtbUo2RL+n0XMT3S+lwjiwfGNGft3xy+YzXSUoC76zTXBtncQsc+QYZiq+IRIBn9M0OS9jUlFRyQ+qAM8E8QZ7Dzl5+Pl1/PxHp1FRnjhSCgOiO0oy8Q3gP7iJ6y+dwPTSKYNugoHlvx90sd37syv54Q6BudrPnd/7OAA799mZPK6SoKZb8W4EQxFXiGc/cvC1C+p44gM7n7t/N4/+/vPo9dlZ52USDY0XubHHaskix6C/DVfqiZKc00Ski7K5nFBqzY/YUMV3bsgCtNk3hU1LtudnrNoOKomGZzrurp5Qvx2nUpR8D+OvrzD02gFDxXfziuR5YQ3n6vv/n6kIHy5+u1dQboBPj4v8no34BvB192Auyv+Mo4qKSvaoAjwJ0Vzp+BvO/z22mqamUkXiO5XojrLvLBOa99s59eRZCf/uv2cpjoDgVRs8cFDwufPq+OTJlWhLIzmV++0d1FZVM65KSpu6AiDNWUZ5w38xF+3nF1c38PDbnZQU6Fh4ylwkTf6jVOmEfKIbaTbkmgqRaTpM7PKxYtxug4qKnIYCqOI7nmTpPokQm1fSE5Aw6RPbD+Yj/zvX8zOWRTjkr2FQhz1AdUXyosFExzuZD3+UZNeM6OuJhLgSmlcEx5QI/0+HYK0b/j5PQiNJWYvvKCM5C6GiopIeVYAnQN74I3a297GlpQfvrrWcOLuB2VNr2OHZw+LzavjZ3e/R3OqjoS7S6TD2ZhF7czhwYWVKEX7gwkpOn7KP5W+H+OXdH1Esv01xgYbiAi3FRi0F+krWHehiR3svp00t4Y83VTHj/IuAgRtXWBYcsBs5ZWFknb/a8M+0PuLWsoupLHuKvpoZnHxaHYUFei47ewa6HMOF8VFwJWIm25tlPkl2s4+/0Scba2xU3GETTJiU241uOPOqx6LoS0fs50jpTEubT09tyfBUwY70w1GiyPRInsdcttVpT++AMlKkin7HLjMWRPj2LsF9+wT/N0eiWJeb+Pb7AxgN+vQLqqiojCiqAI9BlmUe/OOtPLnGjkaSmD+hiJc3r+bHt57H7Kk1CCF49Y0DGEuKeNtpxhTMfkrvwIWVLFnk4LLxOs772RlYqcK3dS1dfWF8fWG6/DLd/jDXn1rFyY1mjHoN0uwz+8VIVPRJkybRvaabh98JMGHOODRaZSL8cx/7NHfcfS/nnzoVX7efh577kPu+dzkT6stSFk0qsf4abnL1BFYyxkRRtnQRtucOmCju68Zkyl6A57uNdpQjUXhD9p+nNq+eekv+BXg+xXcmUfCRPn/52l67PcDspuT2d8nsQFNFwZcscuRt5kwJIy3C3UHBt7cKvjlFYnJR7pFvm9NDpdoBU0VlzKEK8Bju+P4Nkc6Sn5rMlOoCXtro4kCPkYvOaGKHZw+Prpd5b52Ny756ETrD0EOX6KZw4MKIM0lsJDwqviEyLXhW03GRG3gSB5J+4e3ZMzTHXFiZamnmgzc/YsNrm1h4+QnUTqlJK8IvPusszjzpJIpN7wPwzIrN3Pj9f/Obb11CQW3yY5SPhhjpppiVEDuOXHK/E40j3c09mRAXsqC9Twtk1/RCFd8DpBLeSqLg7V49JzT05HtYCcnl3Ax3KspoO9V09YQoLkydA56pJ3+mZFoQGR8Fj65jJER4WAh+sF1wXiWcXZG7+AawOVULQhWVsYgqwA8jNi2jxRXgC2dVM7UmIsrKi/V0OJysObSV0tIC+rr9FFpMCcU3pI7MRIV4InZ49tCUpAAqKr6T5ZdrjTL+k4sxL7ycoKOF9559lcYFk5h91qy0IrzY9D6BYIgVq3ez6eBBPnHNNL7082dZct4kZs4oZ/IES7+XeaxQHUkRrmQZpSIjm8h3fApR7HmMF+Jhn4y2WMNzBwam3JUep+ESSaMtvuOP+UiJwb6QRIF+6IOQkjbqyT4nicY+VnPy49N2YOTtLMXh7otKco+jY4sddzYP6mMhpQ0SO6EosSl84GDk35sn5kd8Q8QBZd7MKXlZl4qKSv4YRo+AI4doweUVx1tZscXT//rJl1/C6afW8rs/fsRTuw30dfvRpsmTzscNQJp9Zv9PKvENoDfLdOkiRU768nouvOU8bAcdLP/ba9TY9rLN+deE29jh/htrDm3luu8+ykP/+YCnX9jFH+/fwGnXncm6ljC/e2Abn711Od/41XoeWRfOeZ8ScfmE3rxZDKaLmGbjepIofz/Ra9HzEvLKaC0Dn498ie9sRV4+xXey45vs2CZ7z0ikKIVk0CT4mio9HonOx9H6gDSc+LrDlBRlFuOJP87JvkOJrrPR16IWhGLzSkXuJ/HER7+zxXD+3EE/sa8nIiwET7UJ7pgiUfSNZ/IyBgCH24u1LP/9HVRUVHLjmBfgYtMyhBC8tsXNQ293cvykSL5i9Mb4sSum0WMs5r9/eIX3n1vDtIVT065zySJH/08qYm8uOzx7+kV39Pd04hvAUCxT+pav/3dTcQGLP30GM0+bzvMv7uFr336Dux/9Dpt27iQYingi73D/jeZWH9/76TvMnlHBuWdNQNJInP3ZsyirKeWEJfO58OZzWXrHpVhrS1nx9zcI9AYGbTefTXSiQjz2RwnxY8hE8GWTehIlWWFt2COjK4nMGIxW5Dv24W0kiRfiuQrtdMcl1fptXTqqigb7f2d7PJosjUeNI81IPPzE0mH3Q5F32LYbe32NFd/DRT4b7CQS4es8UGmEqd/Pn/gGCIXD6PLZnEBFRSUvHPMpKO/v8fH7V9voC8osu3I8J002DxLBGo3EKVctpPOAHVNxAeby5AVFiYi9SaQr4oumUsQXWibroAmgNQr2Lq4atF6NRuLLF5UjLjyVHbtdvP1uC9+796d02HqYPNGCVqth7z43cy+cT8G8iThlwdQTu1jxzzVoi0qR9MbDPwVIejNGk4H1KzZx0qXH9293uJvjZJsnnu5mn68Hhwkv24ako5xe0ILGKKU9NrmK7rEcNR1pkZeIeAeUbI5XtrMSmXRTHM7zmCilY6SIbnPLIUF55cBrSj/38WlAmRZkRqPfY534lJQ37YLzr7gur9uQZRmNdMzH2VRUxiTHvAB/d5eX2Q2FfOOienTaxLmKl0/o5TkqhrwGmQk6JekpsVFvSB2VPXhBBYZeB0hSwnVLksT0qVamT420IO7pCbJzj4tAIMyhktP7c9kljURH6TkULXAg/L2IYB8i6I/89HVhrS1DH5P3PlKdKZWI8HT56ErPT66uCpIQpEp1zUV0x9rQ5SLaYkVNpuMZ7kK5eJRsK5moazdM4uT5pUilw2O9lkjcxUdH0xXtjdRD1EjnfceeN7dLMGVado5AmYrw6DKx+5tpxDpV6slwFmBG132odQ9nTc5vt0qXt4syS2ZBIxUVlZHhmBfghQYtRr1IKr4TESv4kom/dMIv3ftiBWGi6PeBCyspCvlpmBhkauOA+E4lRgsL9cybU8VzB0yDTvyLq8uRJGh8VwAFh38GCg5dJJ7iTXZzz6dQU/Kgk2tUOxvxHV9Ue95sG8HOoZGmbAVQrMjLJaUkXX52JuMbaRGuhEQi3OkJUmYZuUtbPlMTjmTiPxt+PxgLRqb5S+x1KdPodzLhPdL+3x2eANX56OIVg82hOqCoqIxVjkoB7r9nKaCsba9xfwf2GmUXvUwiv4mWVRLNhdSdNGOF38LxLrRF2ozGlaoNfDzRNIt48Z1OtA3H9Hcu1oXZRrcTWUjGvh5LyBMpwByp2YF0KD32mUbFx6oIh8OpB0KAAM0wdf3LR2pDJp04R9NCUCmJPg9RB5RUpOu2mUkUPLp8fOt5SF6AOVoR72T4Q4ICQ36bFtkcbsbXVeV1nSoqKvnhqBTgUfz3LE0pwv33LCUkEjsmpCPTjo+gXMBH8xqTWRdGBbF1b4CTZktA/sVGdNvJpneVMFJibbibcqSykIwS9soYqgzAwM1+pMRTvo5xvjyjc11Htvuzw7OHnm5BWC9G3f86G1IVEad6qB2N/Ux3jrq7oKgo8/Vm44ue7rracK5+iAgfa+IbwFygpasnv971NqebBXOm5XWdKioq+eGoFuCQXIRHo+QHewXHlRtz2kaiG6ASERF/U42N8CQqLoqPRL+2HeZWDfV3zVbAHLiwclBxYSLxnS4CGH/zHIsR00TE59ArFfXR9/nWCTTG/D0IKREhw3Fc0wnXdNvMRgzmcz+cDrCWS4PWO5aEeLLzmu4Y5NqYKJ8oOV9uF5RZc/8+KL1+pMv9jgruRE12oqTL2R/uwk6zSYuvuzuv6+zu7aPIVJDXdaqoqOSHo16Aw1ARHhXfAAd74aJ9LXBi8jSU5w6YkOWBKVWlU/VR0kWtYm8y8SI8nqj4HmecSKXZDjCkQC+XFJBY8R2bchJ/80nm9pCoWHA4RXg+ot+pPIXjt5FoWSFHCjCV5Mfni+F8qMlW0A2H+I5POUgX7XQ6oLYu8TbGkhCP5Uh4QI2idKwuJ1Sn6KibSsxmEgVPl/sdjXxHRXcm4jt+DPG/51uQFxs1eRfgKioqY5cjToAHH/wq/qKByIrSbmGxojsWnQThuHTF6A0gKhzPqfBwy9dW8EF1KcdNr+X6y8qY5NlEKCz4zpP72dPRh6M7RFgWXHjmTL5389loNANjzCZdJRGxgnjnvm7G1QyO3MffuJQI31QiPyq8xaHmpIVmsa/H3sSU3EQz6aiZSf53utz5WJQ406RbJtwlM7NeZjhSgRKRy2co0XFMdA6SifD417IVt6n2QUnBbbLPjcspmDE78XkYyUixEkEHR5b4zgS3S9A0M//fh9gARaKalGwKYuPPlVLxH10uX0K8yJjfCHhPbx+FBWr0e1RRUAuhcuyStQBftWYNhSYTc6ZNw5jnwpFMSBXdVkKNETZWVHGqEINaJkcFZGPxJNYfaqXUbOLHF5fzwV4nN377Ua46oYJzZ1l4fauHC+aU8aXzajHqJG77516efsjNx264KuH24qPT8SJZaev15rYymiYXDnpdyY1DqUd1vPBWUsiUynot2X6mE1SxyyghmV/6cDJH78c0Qo3m0nX0zMaVJ5MHoXjyJWgzLbBN9rkJhUCvTyz8xrL4VnIOkzEWaw2CQTAYBp+H2AegXFI6Es00pYp+R/+frw6X8eRLiAfDggJjbumQsdicHiqtlrytTyVzev2B9AupHLNkJcBdXi93/fWvBIJBevv6KC0p4aarr+aKc8/F6fFgtQzfl17/2d/Bk18b9FpUhCsR31GxHl32ugaJH27zsL21l+tOraTYqMXTG2L9gW7WP3A/W1p6kCTo6pO5/YFdvLBQwwWzBf+7tYOvv9/BNbVgb3Xx5T+6uPeWGfzg8nF84YHdnDF9BS+0Wnj5rR1cdHoTN151YsLxKBXf8TfldpufsxaWAbl1+YtFbF6J//4X+3+PF92rXunhjAsGi/5UN7ZMppKTicBUxyST9JP4xjmgLPodT6Ixrn5LcNyC5GIjHyjt6JmtU0wuIjyedOc92Wc+07z72PdfPqGXUEigS3JFGwmRmuzhM/5YpPvOJzoXYzV9JhEihSd+Nt+LZDN58eJbifNJPNlGvxORa554lz+c14i1akE4+ng8XaM9BJUxTFYCfMP27cxsbOTX3/oWADv27cPmdPLfN9/kqeXL2dfSwrmLFnHbZz5DoclEMBjksf/+F0mj4bLFi7GYzTkNOpHYzkR8x65jcpHEP2+ZxkNvd/Kn19vpC8oUGjQcN76I606tYsaufZh1YAtI9IUj7600Stw5Q+I9l+Du3QKrAYwa+O7ftvHQHfO46oQKrrlvO7WlBr55YR3ffWYDC48bz6wp1f3bzyTyHX8zFkIgywJtBt7lscTeAONvXtEb16pXElfjx74eFeOxIjxdA5JU5LO9fT5QKkh7eqCwaHjST7JN1RgNYsWHksZBSj3vo0QfoBJ1lH3ugIlTTD2Ulg09D8MtXjNpuJPoO5+uxuBIEt8APi8U53aJV0wm4jtdFFxJgWy6c5GLCG9zB6gqz5+jk83pZuK46Xlbn0rmuH2qAFdJTlYC/N116/B2ddHS0UF9dTVNkyZRUlzMitWr+cXtt+PyeLjzT3/ihTfe4NolS3hzzRo6HA7MRUX868UXufnaa/O9H0NQ5AEes8xN8+GmFMuOS/DamcApoRBvrV3Lky+/zMSGBqQ5n+fm6UEWvfwd5jYUotdp+MTF1Tz96uZBAjwWWRaEAiFCwTDhYJhwKPJvKBTmZGsPH64PEwiEMei1zJhuZUJBI2UWd9r9g8Q3jGQFlUczSqLf2USA5bAYYmOptOh0rOX/ZhMFz1RsRPdZiee9UqJj3rkNrBWpRVI2NnfZkqn4jv6ezczMSJPqM+5ykfBBKEo0Cq5UrCaLfmca+Y4X3+kCBclsIZWI8ChKvx89/jBt7iCTxyW602SH0+2jzDJCT0IqCXF5VQGukpysBHhJcTHW0lK+8ctfAvDTr32NKePHc/1llxEKh6kuL6e8tJRteyIXsIOtrZx+wgmYjEb+uzJyQbr/3/9m5/793Hnbbei02jztTgSlhZn5QK/TcfbJJ3P2ySf3v2bQ6znh0l8jNi1Dmn0mF9f4uPbrj3LFObPYvKudl1bt4FCnC78/TCAoEw7LGPRa0GnR6rRo9VrKCiWMBi2tBi0GvZbyokZ8PT3c9+fXmdfUzHHTawkGrej1WlreWs6dLzRTX2Zg4uxZTKwvY2KDldoK86Bi0HQttGNvXmdcUJgwCh6fghJ7U4u9ocXehOJvZCMduc1H6gkkFnatnX4aa7pospQPWXY4BfZIH8PhtmBLRarzF/vAIHeVcOIs66BlE407XQOY4SaZ+E6EUvvPRORznxJFgZN9xt1OqE+hI3PZp9j3x6M07SRXMkmjUfqQsbO9l8aqAvTJcqiyQBYy2myaXKjkDY8aAVdJQVbf9msvuohKa+RG99U77+SJl17i9htuwKDX94vp3QcO8OkrrgCg0mrlF3/+M5MaGrjmoosAaG5vZ/k77/CZK65g5pSIl/Xfn3qKcDjMTddck/UOjaT4Toc0ZxmIN6iuMPOFaxZy0w+f4uyFjdzy8ZORyrowGDQY9Fr0es2gAtB4mko/3///3r4+Hnr6YTbt2sFV//MW93xiIka9ho0Huzl9Wgn7t2xl1co+Dtj9uHtCjKuzMrHeygS9l4kVRhr2HGK8CYp0g7eX6OYVL7ZjyUZ4j2VSRX5T3Wxb2vuor8lf4VQ68iG8U0VZ85kLrmQckDz6nci5JpH4jp6fD3ytmPe/g8giG0hJykz070oEVarodyKix0BJ0yeljES0P5EI97gFs+bkJyUrWWfQZKlz2TKcx0lJkebW1l5m1OXvoTocVsX3WCAUDI/2EFTGMFkJ8EqrFVmWkSSJU+bP55Hnn8d4880AyLLM/U89RXFREZeefTYAly5ezPi6iDnvnKlT8QcC+Lq7qbJaabfb+wX4y2+9xakLFmS9M2NJfPcjLQbxBp+8ZB5XXzgHvU57+KairNgmVnwDmAoKKCyYwL1XtPDihmq+8MAe/nnLNEKy4NL5VoqMA7MJvYEwB+x+9tn9HLDDylUHOdAT8T4v1gnGm2CiCcYXShRpoF6GCiDdfEQi8Z2J8M5E4KUSnImaFaUSMMlEZ7biG6Clw8/ZJ1sT/i3fUfB8Rb0znQHIV/Q72bGINoCK/T2WZBHv2HMjb1oJ3rJBxX+pUquGs9thNmIumf8+pE4ZS7cf+RbhSqwpP5BamVVRN2Q5pd+FZOMdLvE9UqQS4ttae5g/oThv23K4vZSXjZA1k4qKSlZkJMBdXi8vrlzJWSedRH11NaFwGKfH01840mG38+xrr/Ha6tXcfccdmIzGwxXxEvOmDxSDtHR2crCtjS9fdx3PrljBGSeeiE6rpbm9XbEAH5NiOxnSYgD0h3VrU+nirFcViWxIaOYu42JpGftsfu5f2cHEigL22fqY3VBEjz/Mv9c6+MTCCqbXFTK97nAk++xaAss3IguBLQD7D4vx/T2Cg5VaNnpBFnBySOaroQH/0lS5k8Md8Y6KkWTiMyrO0k3nZ5PzrWSa2dcVosQ8vHb6uQjvdMcv2fIjQewDVKzojj9XyRxBYoWMq1dLSWcHgeXbh2u4/SSLgmfa5TL+ATKd+E70QJGJGM8VJd+HsCzQJpnNO9KKSYeLRJ+f7a29fOq6C/O2DZvDTaW1NG/rU8mcnj4/RuPwWF+qHB1kpBzKSkro6unhb08+yQWnn86aTZt4b8MGbv3kJ2nt7OR/H3oIjUbDb7/znX6BHk1JkWUZzeEpsW179mC1WFh43HH8/pFH0Go0tHR0EAiFmDJ+fP738iii3eakpjJy05bmLOP43V/nDyvasfuCFOgjx/eZDx388bV2Ptjj4+6PT8JkGJiKjN6kxzFQWPrCIxvY6BUU62BJFVxWo6XBNPgmmsquayRSTZQK8UzWlS3Rm2dYBslXBgyN9qViuBoQpVpnsuOX7D2pxNJwiL5UojuRXWb8WA7JVdRIuT0IZRIpVrpsJo2wMhXf8eTiQJQOpeLZ4QpSXpZ/0ZFv8Z7LccrHWGJFuN0XpNkTonF84pm0bLA53TROyOy6pJJfHC4PpSVqEaxKcjK+Y11y1ln85803+d1DD1FbVcVdX/86/3nzTb7005/yyUsu4Rs33jiw8pjiSk1MPtqmnTtpHD+eSquVGY2NrFi9GgmoraigtESdNkvFobZOxtVV9f+unfwZtrT8iKUnlDOl2kQoLHjkXRt//Gwj//7Azhcf2sPdH59IhTn5TfGlcDHGsjAvfX4quhTWhpnmtSZC6c0r2bpjO+FlSibCO9k4Y0WRrUtHVXFIcf4wDG1AlGh86fYvlwcIJe9NZFMJqSOw2QoaJekl6cbRvCLIzglFTLS309w9NB1huBqw5AMl0f1cXYpG0vmlw+6nusLQv90omXaXjJLsczASzk3DXUgtzT4TIQR33vUfrrt0PgZ9/mbSOh1uTp4/M2/rU8kch8tLaUn+0opUjj4y/sbXV1dz87XXDrISnFBXx+XnnMPbH37I86+/TkVpKddcdBFXXXBBwqru7Xv3cvWFkem2QpOJts5Omjs6mDdjRg67cmxwqLWTuTMGbkrVFRVUmvV87fxaAF7d4qauzMC88UXMbSjk96+2ceXvtlFfZmRhYzGTqwqwmHSUFmqxFOqwFOr41iUNfObPO/H2hbEWDT1f+Yh2Z9N8I9n20gnVkUqjaPHqqbdEOp0paTOeTljn0g0xF5Q8bGRDIjEVPSax5zBV0xmlY3AXFVN60KdoWaWdKnMl1UNkIoYrRWMkHV467AFmTS0ect7SPaQm+/7k65hk+xAWex0ajvPz4qodNLd7+NU3Lsrrev2BAAXG0etQrRIV4EWjPQyVMUxeHrmXnHkmS86MXEC7enpYv20bfX5/QvHt8fnocDhYMDPydH7luefynzffZPX69YOi5yqJ6fUHKCwYcN2Y4Pwry785C4g06Hn4nU5uXlwDgEYj8dUL6vjiubVsaenhA185a9s9eA724vF14fb14XH76PKHCcvwp9fb+O6lg/3Dcr15p/NkTreNVFGokRSpUWKnjls8es5aMgcpTzng+d6fXARDIuEbFa65pKDEn0+lUe8oySKfsqRBK5LXLSQb73CJ00wfVFM9dBjOn6so4jvcOeBK6NzbzJnF7qSV3LlG46PfP6XHROk60zEc4nvnfhu//vsq/vDDyyPRbyn72qBYRMz3QGX0cLg91FWrKbUqycl79VhxYSGnHX980r+32WxoJKnfxnDBzJn88N57CYZCNE2alHb9u/Y1U1lWjsV87D1Z9vkDFBwu6tjX3Mx7L/2CyxdYMRkid7s1+7roC8icsfRSpBj/bwMw/ziYn2S94bCM98M3MOkH0oSURHRToaQBUKLXE203VTQ8l/Fku77oGL27WikpTqw0RsP7PFeRoDTanKvQixfhmXxWElFxTgGlskxDbfIo50gJb8iv+I4SO/5M0n5GMvotNq8kLJehS2OjFL+PqcaoJPLccK4+IyeUsfCgYnd189Wfv8C3Pn8mMxur8ya+Abp6ejEXJbeQVRkZAoEQesPYTX9TGX2G174hAdMnT+ap3/++/3dZCM4/9VSeWr5cURvecDjMm++tw+PrwaDX0VBTyfj6auqqy/Pe0Gescaitk4aaSvyBAF9fdjv77H7mjCtiVn3kYvuPtzu5/prT0GikjKZMtVoNZSedk1EucyLykcqQj3xVpfudKrqe7viFZYFGIyX0b89GfGcb/c53lDtfpDuHSmZGlNKBmWopcfqJ0nSTTNqNp2IkCpLHgoBMRCgMWk1m0ddMnWNiiY2CZyrCR5M+f4jb7voPl58zkwtPb8qr+AbVAUVF5UhhxAU4DC7O1Ot03PbZz3LD0qWYjOkbmkyfMqHfKSUQCHKo3caeAy28vWYjobCMtdTMhLpqxtdXH3VR8kOtnUyd1MAff/8laksNtHmCTK2O+Inv7uhluy3Mb86c3n/zylRUZCN8MxVSiaaNx6qgSCXCbY4AlVbDkOUzZSSF90h0sxzuiGui1IN2UUIN3kHLKBlXvsXyWGs8NdLRb1u3jsqi/Dceif8eJrOBjBfhidKQRnImJBGyLPjRfa9SX13CzdcszLv4hogDSmV5ad7Xq6KcPn8Aoxr9VknDqAjwRGTjfmIw6GkcX0fj+IjdkhACp9vHwdaOQVHy+poKxtdVU19dgS7d/OgYpq3TSXnZdp7/yMm3L2nA0xvGoIukjTz8jo2PLzkOo0EHCTRdVBzkEt1T+t5kQi9Zzma8fdpIujakczpIdtxaOvz9HTBTvV+p7Z+ScWbKSLaPz9f5UjLmeBFl22RhQZMPg6FB0ZiGQyiPVHFyOnI5D7nOgHV06ak2ZxaFTvRdz+RYxj+QpSq2zPRBP5uOp+n40+Pv0dbp5a8/vQpJc3ZG71VKp8NN02Q193g0cbjURkgq6RkzAjwfSJJEeVkJ5WUlzJ81FYBAMERzu439zW28s3YTobBMmaWY8XXVTDgcJU/VBn6sIIQgFGrnJ//3Bt+4qJ5ZDYU0O/34ekPotBpWbPPx4tfm9N+8knlNp7q55UMMZFI4F79MqhvkaEcX47ff0m6mfoaXHZ7kn53REN8jKbqjjHQUMZ6egIYig5xyLLl+fjLJW05G9PMwHMXDuZ6D2P3L9gG4w6djfv3gfcvVpjJKqih4PgsyM/3+pFs+9jj+d+V2/vPmdh7+5TUYjedlNT4luL1dlBxls79HGg6Xh/Iyy2gPQ2WMc1QJ8EQY9Domj6tl8riITZ8QApe3i4MtHbz1wUZc3i50Ws1AlLymMq9+rPkgHA7z1ppH2Ly7nXE1Fi765CWwZRWXzLey9I97Of34Seh0GkpLTHR4hnpNK73hx4uUsdS5brg9eTOl2elhWlH+xfdYOuZKGG3xLc88A82edqTZgwVePj8rmYoypXaS2dgtxjPaxz8WR7eO8sJQzuvJ5rueyKEn0d9jiT92w/HwGl3n+oPd/PrxZv76k6WUl12S9+3EozkCgkpHMw63l6mTGugLjLxTl8qRw9hSmiOAJElYLWasFjPzZk4BIBgK0drh4GBLB++t20owFKKkuIjxdVWMr6umvKwkr1HydpuNNrs97XLdPT2sXLOG5e++zoS6BqY2lrFkyZTIWGafyR2z4cqDDp5990MuvnASOzx7Ehb8ZdJ5MZZ8pK0cjciyQJJI+Zk4WgV3lOESfsnye5Nt3+EIDOm8mG+3nHQo3V6yz8RozFrEE3vcszm30uwzkT/ciFYz+PV0ke9k24oV4Zmck9hoeKptj+SDS4vLzx2P7eMnV45nysSrh3VbwWAoof2vyshid3lYtGAWzR2qAFdJjvpNJVIIOqE+kpISxePr5lBrJx9s2IbD7UUjSVRXWhlfV8242kpMBekLRgFkWWbvoUOs27Yt8rN1K32BAONqatKKer1OR7BG4owbzkHbaUA3TkdxkX/wDd8Cl14UuUFFxfeLqwe7ySxZ5Mhp+jtXIZ6vKeJ8WgnmgscNltLs3jucgnu4hVw6u7hEZLO/6UR47DjaOv3UVmaWi5/JdyCVdWYuIq7J0jgmhHcsuexPICijL68CXHnbXi7Xm0y3O1znwtEV5CsP7+PGM6s5/arfDMs2YrG7PFSoqQ+jjt8fVBsh5UAwFOKPjz3GiytXIgvBaQsWcMfnPoepIGI6EQ6H+d0//sGr776LXq/ninPO4carrhrlUWeOKsCTYDEXYWmaxOymiDd5OCzTbndysKWD9Vt30+cPYCowML6uinHdT1NVHOqP/gRDMm9s8/DfDS7WH+zGYilm3ow6Tpxdxxeuvoi+IgeSJPHcAdMQsZyIAztgWreNnc4KtEXOpMslW9eLq8v7W34PZx4qKI9gHsk47FBRmfmMyJEa7YbsxHeyvyl15FGSd93W6cc60c0OT2f/a0o6jib6/CtpBKQUpaknsaSrgxjLdDoCVJWPbcGR0wNGFufmgL2PL/1jL5fMs/KJz9+X9bYzweZQHVBUjnzu+fvfeemtt/japz9NocnEX594gluWLeOhu+4C4Ff338/yt9/m6zfcQG9fH7954AG0Wi2fueKK0R14hqgCXCFarYb66grqqytYdPi17p5ePnj5VzzeLOHzmwAJWe5l8wE7ZVY9V1y4iB/MHUeldaAgZodnDxJSZo1ZhEAASFK/yI4KaiUkWjbV9pOJB6W2honEU7ooeD6FRyYe6NlE0O02wey5mQnwXHyvRzvPN1vxPZzbjW57v01mQsy5SPe9UtoGXon4jkbBU3X3VEr0uxHfZTRd19GRdAxKRYc9QHWFAfzKls9n0ehIbA+Ui/BDTj/Pf+Tk6bUOvnReLUs/+/u078kXnU43M6dOHLHtqQwlEAiiH2N1ZEcSPb29PPnyy/zgi1/kinPPBeD4WbO4+OabeWvtWuY2NfHMq69y5223cd4pp0Te09fHI889x3WXXor2COoHo35KcuCmO27E2RViYaOZSnMkD1XSFPC5a07FH9DhdIV47R0feksblVVQXgE6vZQ0VSSeJYscvLi6nEI5SI/WMOj1VMvHvxbL5RN6FUUIExErLLKJbI5kfqaStJlsxWN3FxQVK18+106PSnNzR3r2YTSLYqPblmXQaNI/0CoV3pBd5DvTbq3RbaR6KI3/21iOkHfaA5xg2g4KzDdGWnznSux5SHcO1u7zcce/9nPxPCt/+mwj08775UgMsR+HmoIy6tjdqgVhLuxvaSEsy8xpaup/raKsjEXz5vHqu+/i9vmQJInTYzqun7toEf/70ENs2L6dBbNmjcaws0IV4FkiNi2jxy9z36cbaawq6H89enOJ3ohDQYHDDrZOWLFGgwiDxuhni72EAm2QPo0ODueCJxLWSxY5WLvSSLdW2fRurAhPJtSTifBEDwSx60jn7BEbeU4mBke6MCrfIlFJAWaUfIm72PeOdLQz39vLRxpO9Jz29Qo6QjqeO5C6HmM4xXf8OcnkgS+buohEAnAsRMGdniDW8vRNeEZDfOf72CQT4esOdPHNxw9w98cncsIkM9KcZXndrhKCwfCYc/E61lAfgnLDYjYD4HC5aBw3rv91U0EBbTYb7TYb1RUVFMQ0bmyoqUGn1SoytxhLqN9UhYhNywb+LwRtniBajYTNG+wX4PHiG+C/rZE28ZRCcWnkv3KfzLyKbkJuH+GeiH+xtlhDoFODzqJFYxws7opDfg4WlCoea6KodzLSReFTRdQTFbZlkv4Ry2gLCKV4PekLMJPtfz4id+nE1ljOwc+n+H7ugImgPYy2RB70d6UpWvl+OMoH6bo4RhmLkXBZCDTD7Hw3GmknyYg/B63uAHf8az93fmz8qIlvIcSIb1NlKA6Xt7854JHE6x+VoSnIYGo3R0KhxBeM2spKJtTV8ftHHuGnX/0qRoOBR194gbfWrqW8tBS7242leOg4S4qLsbuUF4GPBVQBrgCxaRk72np57D0bmw710Or2U2jQcnKjmclV6aNv8ZFjTYEGQ4EGQ3Xk77Is8LhlbJ2wdpcWOSCQtKCzaNFaNOhkCGm0THjZxoELKwcVVabbdqZMeNk26PcDF1YO+j3ZtmML2zIR4Uobp8SubzRTHxw2KK9IfOHIJc9bKUpERXSZXLapZDuZnJPhKEAN+WR0pZHKZyXFzMnGkknzqGyFb6Ljk6ouonlFMKUIH0v0+cMYDZq0y2UjiEfqoSibB9eoCA+EZL75r/18+tQqFk0pGRXxDRHnLovagGfUcbi8nHTc9NEexhGLRqPhzttu45t3380Vt96KQa/nmosu4qIzzmDD9u1IJH7YFBx5/veqAE9DNPL9zcf3c/ZMC7+4ZgL1ZQaKjMoT/dMJYY1GoswKZVaYNj0S0Xt2TwEhr0zIEaZQlpnWbcM4KUBloAuf1ogQQpEPdarc1KhoiRfdsURFf6L3xQvxTP3GM2lBPVaa8Njtgllzhh734Yx6Z0vs8VU6jmyjhqksIpWK70xTKcI+mYJxuoTiW8lDarZdWxOtJ9PjpkTwRSPiiYR4fAR2NNNQOh0BqvPsgJLr9yafxyJdAfndL7ZQbdFz/amVoya+QXVAGSv09vkpNBWkX1AlKbOnTuU/f/oTrZ2dWC0WCk0mvn7XXVRarZSXleHp6hq0vBACr89HRVnZKI04O1QBHoP/nqUJXzecP5fptSb+vcaOUSdxy9m1OW8rnaf1FY19kci5gHZjMe1GM5OaOwlN1lAZ7Gb3a4Kacj/aIg06S+RHU6AZJIBjt5Gsu1wq8R2/jNJoeJRUIiP2Bjkc4nq47Ba7fIMLMEci6p0PUnkfD5dwSye8Ex2fVEIy/nMiwoKX1lSkHUfsg2GqMSkR38OV/hGbfpLob2M5Gt5hD1DVvTNlAeaRkGKW6nqVTIT/55ENrLEbeOSWaWjm/ni4h5iSTqebmkrrqI5BRSVfaDQaGmpqgIjv96adO7nq/POpq6ykw26nt6+v3xf8YFsbYVmmtqpqNIecMennDY8R4sW34fy5/T8Av7x2Ik99eTr/fNeGuydxu2WlgiuT6fiQJ0zX4QLMfedU4dIXcqiglF1FlRTPM2Ks0yGCgt49QXwf9fHmCplN6wV6Ty3+gJxm7ZmRSKzHRx8zsldEefMUpTx3wDTofdHf43+yITLrMFCAeST7ekNEcIy0MBKbV/b/ZMqg1u2Hi2GXLHIkLV6OMlye96nY4dkz6Cf+b1Gi15d0AjuRQI8XhKP1wNduC1Btzr0F/Vgn/sGrNyy4d5/gBw0BzCf+dJRGNYDd6abKWjrawzimCQZD6HRHjg3eWKXPP9jP9JW338bj8/GxCy7gjBNPRJIkVq5Z0//3Fe++S3V5OXOnTRvpoeaEGgFnIM1Ef94c3tjm4bH37Ez9bzNnTLewcHJxv+CqKjFwytQSXt/qYekJyXNOk0Wbo39TQlQkhr1yQgeUiMCQ0BZLaIs1GBsir59W34PTDq2dftZs8hIIyJgKtDTUGAmbBVYrvNBcqGgMiUiUkhJLvsROdP8zSWvJRFhnEyG3hsczqcpLkyV91BXyk4t9NDAc+3+6uZdDDXDg8O+JRHiy2aAosRHPeDGrtCAyup5YlMzo7PDsoSnDvGMlkfDRSEVxN7dRuiC9A8rRxiPNgvkWmFMyNvJOvV09FBdlF1xQyQ8Ot5fyUtWCMFe++OMfM662lnNOPpndBw/yp3/9i09fcUV/isnHLriAu/7yFwLBIL19ffzliSf4yvXXo9EcWTHlY16Ai03LcPeEeKGohqfv3Y5eK/G5M6tpcQX41atOFs0389XrT8VoiByqha3lfLS1hauyKNrJxpO63W5AFA2+wKdK+9DpJE5vGryd7t4wLe19rNsHm9YLfF19HHQXUq7tRlsgE+6TgOG/iQxqKkLiaelso9O5vE9p18J1W7zU16Quuk1EvoT4WJzGH+mHi+jDrdMBZeUwL+bcJWs3n+lMRXy0OT4XO1UaSqLvcSr7Tmn2mRhInP6y6pUezrhg8MNyvAgfK7aEmdQ+KWnolYubTy773lY1n7f+8yrzxxcxtSb1NeVVG/xs+tgQ31GU2KOqDB8Ol+oBng+++ulPc98//8l3f/tb6qur+caNN3LNRRf1//32G25Ap9Xyx8ceQ6/Xc8vHP86nLr10FEecHcekABebliGEYP3Bbp5a42DlDg9nNln44RXjmDe+CEmSkGafyWXObr74k2c4/3P386mPN3HmaeOomCSz6uE9bNndwaxhsnyL3rDlPpmAZvB0ViYdMKMUmbRMm1SEsEaE9rP7jbS9a2bSWjv6ahmdUUYAoV4Nwa7IjxxMfCGPjX6nm+bP17FJJ5KVeprHEm+nqCQS3tLh55QFpWmXS0YyYXCkRshHc9xOh2BmXDGskvby+SZZLUOqB8Lo5y2VW9CqV3r6/40X4UqIPzfDJch7esOY9KlT3cbSg2OywmC7q5u7/76K9zccxO3r47uXNqQU4L1hQbsfJmc/mZhX/P4ARsPYrRM4VnC4PExoqBntYRzxHDd9On/9afK0Lo1Gw22f/Sy3ffazIzeoYeCYFODO7hDfeGwfzq4QV51YzjeW1FNaOPRQVFqL+NmPF/HSq/tYt9HGmaeNo6aqiJ986QK+9NPnePa+T2OJEeFKWmenK76MJeSWaWwKM7M+c9GdCkmSCGh07DipJiavW6AzCfTFMsUNQbQGgZAlgt0SwS4NexdVEZY0KUX3oBzdNE144o9Vpt05U3X0VGJJF19AqkSEuzxByiz5/8ooifblImKGwyJwpMV3/D50+SCBFewg8u1Mo7QYUslsTKaOQbkyXAW3Hfbhy/8eTk/7WCEeCstc981/seTM6fzrN5/kY19+kAvnlA55T+wsxd4emGgCnUbCePvTwzLGTLA5PVSq+d+jjsPtZcGcIysPWWX0OOYE+MG2Nm79y07Om13KrefUoknRPcLX7Wf56/t55oVdfOWWBf2vL17YyH3/XE2b3YfFXJDwppYsDzwTx4+QR8ZYn/gUpRKgiaI8sQ1MEiMR6pUI9WrojWpySaAvEvhOLOTU4nZEWGDdG6a8UuL4SQ3UFhnQ6zLPuYptWJTvlJNM/KCVWNVFH5pkISCuA2Y+hW2qNJVMRVOmrjJKUgJiyVYUDUpBSpLCocQdJ+oBm2q6PZNGO9lYD8aT6pjHfiaVzGBFo9+xv8dGwXNxRcl3ekqH3U9VcfYCPNvGXfnE29WHy9vLrMZq3ttwkHJrCd0BGXOKS1NrH9SbGBPiG8DmVC0IxwLdPX0UqRaEKgo55gT4j++7j6tOrOAzp1Wx4WA3ru4QtaV6qi0GJGBjcw8bD3az8Ymn2Lqnk1kzy7nx+tlIEqz+oJXTmmayrqUFl7eHiXX595yMFZbhHhlNUfJp9lQiHDL3YY7nwAURS5+IaDBy+YRe/H6Jwt469h7s4e3XdhKSwWyUabAEaLAEqSwOoU2hyRN1C40lVefNdGQivjPF4QxSURYphlUqcDMVtjD60/XpBFG+IpK52Pn1dA+2goxHSaOdkSL+Mxn70PfcARPfVHgIsk1FSUQ+RXiHPcCMsuQWikq2k+ozl00UPNn+JfveWi2F3Pu9y7jzT2+w5Mwmzjl5Ch//wzomVhZQWqiltFBHWaGO4hZBlQGmbgyxRytRffnYyTm1OdzMmzlltIehgpqHr6KcY06ACyH473onb27zsN/eh8Wkozco4+0NIwtBVYmeYosFQR+mQi0fru9g524n1VVFmM0GnnpmD/5AmG99/iwKjKkPXyo3lGREBfaz+w+3t4/7MmczdZ0++j2UaK53VCxEtzm3KnKRb/StgfmRZX1+Dc1uPZvaTXR26RACSk1hGkqDNFgClBeGI/Z9ceI7Op5kwnk4xHe8i0u8IEp2bFs6/NRXG7P2LM9GjOe6nVzXMdqRyWQ4HWAtV94MKVMaztUntP3Lhxd3/PdJbF5JYPlGmlcEh0S+h5N8paS4vEHMNfm1O82VTPYpKv4Xzh3PH390Bdd/63Hu/d5lXN/Uxz5bH+7uEK6eMO6eEI6AYI0LWvUaZghB0xhq+uFwe7GqxX+jSigUVi0IVTLimBPgv/7mNznU3o53y5/58sP7sJh0LGwsxtMTRqeBBquRhtmzqa8qIVDooaLchMEw+EuVyY0+GxEOcIa5l/31gkMJ/hYViokEdTIRGbtsug6Y8TaD8U1M4iNSZqPMjGo/M6oPe3fOOgOXJ0Rzex9r2v042gIAaFt3UV4p8VGggFfWVWRmnZCCROI7XmjH7ms6K8V4dnj20NJRwsnzS7HnNtT+9UXJt8hN93lL9JlJ9tCR7/SA2GYmuTSzcTqgftzg1/Kd751KbGc79ljxHR2v//4XUzbhUUIuswm5RMOFELz5wV70ThufXKTs+5Tos5nPz1gmke/YvzdZGqmvtvCFaxby4DMfcveSYuZPGJhmiXa49N+zlG+9GWK5VsOVU8ZOxDkcltFpVfE3mjjdXqwW82gPQ+UI4pgT4NbSUqylpTD9t3z+4M38bWUHP796AjPrB6Z3pdmRm1k0RzleoGQqTLIR4fZOqKySWHB42/HCKZ3LQjLSRYqTuZwkE9/xRG+A1lI91lI9c6eb2eHZgxCCZ7aa2NMeZvcOLdNkO6b2AKFeiZamMrq0BkIxji9Ko9/x+xMvtJMRK8KV5IIftLtZYqnA7k3891THPNWMxUhFmzP5vCQbbz5SOdIJxVhBmOx743YJZs0deHgbrUh9MuGa6OE4XnxHI99RRjL6HU+20fCunjCBYIC7X2zh4wsrhtTTjHY6VTZcungG//fYahxnTKG8OPIQFtte3nj701z+2qW8qYXjmppGaZSDkWVZTXsYA9jdXsrLLKM9DJUjiGNOgMdSVqRjRp2Jptqh4iS2QDBR05ZUIjzRDS1TEW7rFBx/Uv4uqomEd6oocPxUuRKSNSSJHr9XNpUfFsVh/IBf0qMzCWo2udEXyfgbDMiSRI9GT9AeRmvRoNGnPgZLFjnymvud6IErWvS307s36XvSrRNGTohnO+sSJXa8o10kl6iQOBSCWeXpo4/DkfudaaQ53jUo/lhmm3oyHO3pY4+XEvHcYQ9gNEQa8Oyz+2msyn/xWSbnMJvod+xyTZZGikwGZkyuYltrL6dN0w8S31EWv/gCf7/oUgpNY6PpjcvTRZkljSWQyrDjcHkYV3tktUJXGV2OWQEuNi1jzV4fdaUGtEmcUGIjWUqEaPzNIn56NxNh1NcHBabIuDKJaMdHcnMVp/GCNFFRlBIv5BdXlw+NSAuJUI9EqEdDL3CgqRJJCM6baSPklanx9eH3g04H5RUSFZVgrQCDYfBxiRXh6VJLMk0/AfB6wZwgvTJTBxcl+ftKBW86sRT/WUtXsDtWSCX8miyNBAIy1sLOtOsZC+I7ltjzHpv3nS3pxHc6ZxclMxGxJDovHfYAPf5uaivNdHgCWQnwfBX85iK+45nUYGVPp43TppUgNi1LKMIXvPRCVuseDlQHlLGBw+Vl/sypoz0MlSOIY1KAR1vP11uNINIvn434jn89dlo9SrIbRDAo0OmGCrxM/a3zGRmOjdCmar2dKNccUqeDxCIkCV2plquOCwARO5VgUOC0g90OO3cIQkGBTg9TKnqoqIDVPSbF+5xIfKdLP3HYoKJyaDHscJGpE0myFIJ8i/Dh9GWOrj8d7XY/NZWGpH/PZnyxuenxrydDiV1iPMOVehI7TqWWipnm4if6jHXY/XT3dlFfLOjwKnuYiH4m0z1k5vo5y1Z89/qDvPnBHn5xxUAzlVgR7vR42Ll/Pycfd1xO48snNoeb8XVq5HW06e7ppahQtSBUUc4xKcABtrb08OyHDp796oyUyyUT3+mazsSTqNgpuo74m4XDBu06A7Ff5WSFhrHE5jSnIxOHkdjIbawQT+SukionO1MG3aQrBv/N75dp6fSzbl8LVkcPB71aJJ3E2XXtaEs06Eo0SNoB0ZzLw4jDJmiamZ90IKUuNtmkfoxGC/J8kMmY2zoD1FYaE/4tXw8H6USpkvGmmz3LNPUk1oIwWfQ7Gz/zTAs4Y4V4V3sHNoeLs6dU0OEJKF5HvsV3Pj7z0THt2m/H5e7mhfUu9DoNs+oLI8d1+VKkrzzO2Z/5DADrn302523mC5vTrTZ/GQMIoVoQqmTGMSvAjTqJyVUFXH3fdurLjMyoM/HJRZVMqixAbF5JUwq/6kTiO9MIWire3KFDVzZgpq0kkhxvG5iOZCJQaUFeKivBTEV37NjjHVeSYTRqmDzORLBEAiSeO1CAHBSEvTIhVxj/wSAiDJJeQlei4fwZnWjNGl76oCLleqP7FLvfPt/gFJREUeTo/mfyYDMaZJpWNZKt3JXQ1uln5pSivG0//nub6Xc2VaQ19lhHo9/5Jpe0mChKGiTFI29aiSyXIYjMJG5rHfowkc0DYT7Edy71D3ObavnP12fy3EdO7vjXPpbMtfIFInUg3/vtbwH4+W23Zb3+4aC7V23+MtqEwmG0qRpgqKgk4JgV4I3VJh66aSr2hq/SuvoXvLfbx/V/3smr35yNyaDpv3nET+MrFd/Z8twBE2FvHwUTIlGudMI2kWuJ0sLJeHG1w7Mn7XvjU2hySWs4cGElSxY5mMVQ4Z3qRpzophsdh6Zci758wE1FDkREedAZpm9/kNONLbS4CujWGujSGujRGhK6oERFuBBiUGQj2b6OBeGtVOxk+/kYC/h6QpiLc7ts5fJ9zVRQxh/rTLedLPKdSCgnS6XJhGTvj9+e16+hrDDMhHIjgZDMe7t9eHpCWAoHn5tMHFZiv/NCiFGLJlYuOpfPmVdy6fwyrr5vB9d/bSZPPLaFFfvfZfHChSw588ibZVIZXlweH2WqBaFKhhyzAhxAM/fHVAFVF9/NcZuW8cyHDlw9IUyGSI5p9IbQFHPzWP7OLv7yxPtUGwP89KoJFL2zdVAxVT6cCYQMklZKmTaRSngrFU7xhXyZCq5ERaVKot9KhHcqIZDMqi7Rw4DGIKGp0KKvGBDl0wKC1e/psIT6qA340AjB9tc0TJwaRFeiQWuOpK88d8BEuFvGT4jnDiTPOx4ORlv8jvb2EyELgURuoiyfD8tKSeR8ooRE4jvTiHeybWV6nYqPknf49FSbQyyeYaHTG+ScWaV85ZG93POJSVSYh647XTQ89lr0yLudrD/Qza8/MSmjMeabqhID02tN/Oz5Q6zYL9Bptfz4y18e1THF09Pbh6kgcUqWysjhcHkpVxshqWTIMSvAh1S2z/4RknQNvf5w0vc88sI6Hvvver53y9l88Pq7fPK3m/mqL8w0BlpFZ2oPFl/AKPfJaIxDxXessE3WpTLTvPRYMrUgS8aBCysVp8nE2rLFbj+VSIrmrOaS76wxSJx6Rs+gY6yTwzQW2gk6IpFyIUCjlyL/miREWAzKKVdCph1LlZJJMWQ2loRjUXwDON1BrJbsL1lKxHeqnGglbjPJiC++TEc+xHcqosI8m4BBYPlGOqYsYlxpkMUzLHzz8f08+9UZ3PtqG99+Yj9/vXFKwuh1su9s9LMsy4IH3+7k96+2cf2p6Z2K8pV+kurzPrmqgLV7u7jprGr2+SdTUjy27P5sDjdV5WOnI+exit3loa4qf6YHKscGx6QAT2Qr9eaTX6fEpGVSZeJcun889xFPvLSRv/30KmorS1ik289Mu42fbdXwiZAgXQZeOrEYjdy+/0ERWiFDTMA1nfhW2iRHCZmK2iZLI5dP2AMMuJAo9RfPZtxRERLf1h6U+W3HRsiHpo3o0MekiMsBQfdWPyIE3Zv9kZkJXSSnPFGhZ74EtxIBrPQ8jWXxnU3+d21V9gWYuaZoJBOQ+T5m6cR3dAz5+L5nO3vXtsPHXM12Ss6fQYsrgAC+fF4t1/95J8s3u7lgTmpR+PSrm3n+9a1855wSplYXcNAZ4Ff/acbnDzPOahjUhTITcvXAj+cr59WikSR6gzKX/m4D3b29FI0R/2+ATqebSqva/GW0cbi8zG2aPNrDUDnCOCYFeDzyxh/xlzfbuXlxzZBubkIIHnhqDc+8toW//ewqaioieV7SnGWc/wsovOhSvm7QcFOK+otkQiNRIeO4sBubPlJkliySHF+sqDS6ls8IWrwYiaZ/JGqMEy9004nvREIpkQDJVHzH/z1d7rrGIIGAwiZDf0RvSKGnDBMsYcorJDrawVoO+jTNg0aKdEIkG+GYL/GXzexFW2eAudNHNwI5nIWF6fK947ebb1vIROkqyUR5HzpMUgjXSxvRaiTCssCg03DL2TX86fV2zmo9OCgKHt0HsXklzq4gv7l/GzedVcPND+zGqNMQlgVXnVhOjcXAw+/YWDRlZPJp030HTIZI6ppRr2HejBms/OCDMZUDbnO4mTSudrSHcczj6+rBXFyYfkEVlRiOWAHuv2fpkNeMtz+d8XrEpmWs2uElLAvOmj4QSTjk9LNis5uXdgbQ67T87acfo7r88M1fWty/3GkvvUDNZZfjNGdXAR3vIlLe2oVmZwAS5LpGc6fjBWy6ph7Rm2g6yzGlwiJ6048vVI0V4fHECl8lwi8qwhMJbxj68BK/jViS2T2mKyCNdsCMFRIavdRf6Bndnt8v4bSDrQPadhUTCMoYDBrqqozIxY5BzYPSMdwR6HytP59RWKXYnQEqrUNz8TOdQUn3sJrue5KJCE9V03DGBYX9qWuxKBHfSsil0U/sOuJFuCwGrk6PtQjOKwde30wAOEkIfukU7KiWiH1Wij2m9q4QNRYDnz6tiovnldHtlxlnNfDmdi8/efYgf75hCgX61NfTXK0H030PEn2+LzztNP67cuWYEuCRLphq8d9YQLUgVMmUI1aA55P7V3bwhbMi0e/eQJi/rezg6bUOLphTxtfPKuXkyy9GkqSIN3Pp54e8f/bis7CG34jcmeKQZp+Z0EUlttU9HO7m+K6V7mojByZHUjjiuzZmI76Vkqq5TrJodb5dN+JRGvVORvxNVonrS+w65V6B1pS8S2oUo1Gith7Omjmwfr9fprXTT3CXWgcAAGofSURBVEtHOdv2+fEHZPRaDbVVBuRiJ9YKKCgYvgt2OvvMfBH7GVAihHMRTmEh0GaYh5+IdCJcyUxRvh48hkt855N4Ee7BhIU+PEHBk63wwLyYB1RJ4gyr4D0XTC9OLOD7gjL2riC/frGFS+aVsaO9l9+94mVHey+//eQkptWkT/FIVbOSLA0llxkfgHP8Qf727w5eHEMiXBYyWo1qfzeahMPykJlzFRUlHDUCPJvod5R2T5DZDYW8sdXN3S+1cNy4Ih6/dTpVJZEbR/TJNpH4Bpg2cSK7FH7/EkVuo5w/x87WtQM3q2jEO0pUfMdG1dKJ73TWZZCd+E62fDzpxHeqafRk48pUeKdbLr5bZJQn3tOjLdEOeV+ifYrfptGoYdI4E5PGDYw1EJRpt/lp6ahg10d+evrC6LQS1RVGhNlJeQWQYzpnPvNfM2U4hWJvX5gC49BzkS35TMdKR7zYbzhXnzbdY6yI7yixQrpTFFMl+XikWXB2BdTHPaTWF0hs2RWmeYcY9N5oFPzx9+y4e8L8c7WNdk+A3R19XH9qJd8r9VK8Yy+BHanHEn/uElkdDsfDpsmo566vn8H//Ph+jps+nfrq6rxvIxNC4bAqvscALq9qQaiSHUeFAM9FfAMUGjRc9+edlJp0LLtyPCdNTvBlikk7icdcVIRTkgAxqGgq05tn2BNm+iyZuVWDRTcwJOoN6aeYk4nvVOPKp4BTIlQzGU8q4Z2NE0yslWH8tgAm4WfaDAlLaerjrPRmb9BrGF9nYnzdwH6EQjLt9gCtHVoObPKz+b1WNBqJSquB+hojdVVGSkt0iqY3U527sepsopQ2W4DaBC3oRzIFJhnZFHbGivD4CHG2DwfDbbEYFdKdFDNJcrLKAT+ZLg1ZRmgkPJrI9TARXzy3hpvPruGTf9zBKVNLWLOvi11rm5GKJbSSQAtopYEfnQRzSqBYJw3az5F8iIoyfXIVNyw9ju/85jf8/ec/R6fN30NhpjhdXqylqvXdaONweSlXz4NKFhzxAjxX8Q1w+5J6rEU6ZtaZEgudFOJbCME/7vsDn5LlhAVLSqO2ACGPjGmKIWG+dDp/7ES5pIlIJXa3u3fj8QZoafXh9vgpLNQTqC7C0r4Ri0lLsVGreKotV0eQVMI7X10n43N546eufV4oSRORzlXY6nQaGmoKaKgZ8NEJywKbI0Brp5+317px+4JISFhL9dRXR0R5uVWP5nBa1HCRb0u3XEjlgDLSZCt04x1HEl0vlD4oZ7KtdPxTK/GBRqJSwJmy4DRZJHVbb14RxLa4mJOkg8jAAwcFM8xwbkwkvFQI3CkeGOvLjDz2no0FE4pZekI5x7c281w7fOgWhAUDP0Sy+nrCsLcbrq2Ha+oGC/HY45VpgWy21qvXXTqfd9c9y13/+DZXX9kEJJ8dHU5sTg9V5aUjvl2VwThcHqorrKM9DJUjkCNWgOdDeEPEzeSMOdm//8lLLkPSalggD7wWH/1W2imyWhvinGkDK1IqviF5Lmmi6Vp5xum02XzsbXayr9nJ/hZX//9lIVNfV4y1rICenhDP9+3H4+vD4+6iNyhjLtAys66Q/7v7RiCznGwlJFtfqqZEuZBMhMd3wBxJtBqJmkojNZVGFsyKvCYLgdMdpLXDz9rNXvZ3uhACioqgvELCWgGlZSTMkc5GFGcr7JN1jc2Vtk4/82cNnplSEv3Od7Q0G/GdSAzn4sMdJZl3vlLx/eprPehD8O5phTS2BynpkXm00cDrFg3/E5SpSvCehnP1vB3WYpTC/GKGxBYfPNkq0EoSZ22PbNcCeJJsM7B8I5umTeZX/23hx0vHE1i+kdoCiVsmSimv6fuam/nLT77EVWvg6rqIGDfrpKxEeKLPTSZiXKOR+OlXzudjtz3MnFmVTJ82OuLL5nTTOKFuVLatMoDD5WXW1ImjPQyVI5AjVoCPFk6PhwMtLdjdbjqeupsntBpumqFhXFVkKjIqvjOJfANcXNfDO7uHipZU4jtRLmmitBN/UGbVDi9vbvOwu7OXg44NlBbqmFRZwKTpjcxsrOLiM6czucFKJ62DRKcQAr2vjO2rVnHIEWDdwS68UupIe6rod/S4JCqIjCXeHSZTMklNSCTCHe4gZvP+rLatdByZRN00kkRFmYGKMgPG2k4mo0EIQU83OOxwcD9sXCeQZYGxAMrLI6LcmuVzSz78lHd49uRNhPf6wxQWKJvuT/RdSedskg8CsqDz9ZDy5YGnXg+yoU7Lei8UVjZgfqSXEtFGSYEW83/+iWX8ZMzFRkqKCygpMmIuMmJu30yJSUtJgRaTQUPw1U3961QivtuAn+s1dFxQTHGfYEprkL01Oq55u4cpbSEeP72Q33TL3FUxOL+44Vz9IAeUcj2s9whcQVgUY/ttEeCOew4clEPuiYzx3x/YufBws8t0AZVJDQ384i/PsutnV/LgIcFVa+CqWsHH6yUsCUQ4JP5+KbkuKBHxldYiPnXtDB56dAu/WHZ62nUOB50ONyfPnzkq21YZwNvVjdlcNNrDUDkCUQV4htz5xz/y2nvvcXIZ1BfAFY0azjlsVBK9CcQ7nKRKmYiK1Y42mN4w0AUmlfDuCwv+0xG5EZ56mo6aAmmI20B0LK9tcfOz5w8xrcbE+bNL+eQplUyqMFI4qKDNhTQ7sryVKWx372bPPg8ffNjGBx+2Iwcl5s2oo1bq45xzT2Th3HH9+xkl0+h3rBAf6ah3IuJvuq0dfcweXw0k9mJXus5MtqmE2GMlSRJFxVBUDOMnQlQa9fUJnHYQ7nK27PKzLtiKQa+hptJI3eEUlqLCkcldzYcID8sCTdxMRDa538Mhwrf4BH/4UGabBnokiZ9KMDNx6nNkDMA6DazWSHyokZgk4OISiVt/8n8EgkF8XV14u7rwbH8EX18Yn/0gbc0hdhgr8ba14OsL4+2N/Pj6QoRCArMOzDowdguK9RomyIILwiJhBDtARHxP2+znY/sjwvuVBQUEdRJ+Hbw33YgAFm/ysyoghsysOSmkjB7sAcGtGwUnlcHjx0sU6ySaDy9TdHg7AQb1E+vn/bcPAHCOoRdIHfmOZ+r3n+GH9yyluVfw0CHBNWsF354KixOc21ghnk1n4HTfzZ2bu5h/XKKjPDL4AwEKjImOsMpIIgRDrk8qKkpQBXgG+O9Zyg80An0V7O6C2ydLjC8c/MWTZp8JcZHDRI1oYmmyNNKxw8W4vu2IzYH+1xMVW7qBH+s1VAtolaB5nMRXJ0tsmKPjxxtkuowFTK0pYPa7nYQrJ/Poq7v5w4+vZmbfdgDe2uHhwbc6aLAaOaOphDkNRXT5wzgOOmi3+Xhn3QGWr96OwaClbOo4vnzzfC46bsGQVIxEntrZkEp8J+oAGiXeHQaUpTwoTUloafezYHYJVUkKNJVuLx2ZinBF27QAcQYNgYBMm81Pa6efjdt99PSGI8We4TbqSoLUnbiAsrhiz3x3FcyWWP/vdEIqF4/vTCKmQgh+sVuw2gmXy4IvhwRPayV2aiRmhgVhYIMGvEj0AT0SHJTgI43ERAGnhAWfDckc/9ILiQd60kmITcuGjC1+PF0vb8AXAl8I9qwO0yXBJkniDoOGWTJcFJZpEpEL/X4JntRqmCgEx+2PXFMa20N85rVu9lXrWDW7AGexhqve7cGYIJDfvCLIvgoTBTN9/M9GwZIqiRvGS/1/ixIGEnlztPUJnmsXvOOEy6rhE/WZie8oxtufpuGepXxvmsSVPsF3twmae+FzGa8pNaki6e+uO8D2vTZ+ccMped6qMqI9ClRGF1mWVf9vlaxRBXgGGG9/Gu5ZyrJp8Ew7fGGj4JtT4OyKmJSNzStpmn3m4fbsiUmUZtKyo5SFc4P9AmJvt+BfrYKdrQL0GkwCZAn2SrAkLFgaFtxs0HBpdWTbu7oF5Xr47tUT2NHey5aeUg5uOMiffnQlk8dZEZu389YODz959hBfPq+WQ84Ad/2nmd0dfRQVGqkobaHSWsTEqUV89/aFrA1WIkkSm4FG796sjlfsfmYi5OIj36la2+er/TsMFsM2V4AK68CMQjKnlCMFg0HDhHoTE+pjHFg2rsTWpaPVq+edVzbj7tVCSQVlFn1/pHxK+WR2+7I7/5D+gUFJZLK11USNJBCbN6dcbrhdQGJ5qBl2dsFvfWGi5bNVAg5oIt4f9+g02CVoWnwWRSYThQUFnFlby7KFCykvLVW0DWnOsgSvDS4IN8+BaGZ80+F/rwF6ent54Y03+NeKFexrbkav01FeWspZJ53ErZ/6FAb9wGf7Ac05eAslPIUSV67uwRCOvJ6oqLulyMyzG22c4ZM5zy1o3jl03Cs1EtUiEv0OAx9pYLlGw551giUXXsKfL7iAxnHjFB2DZBhvfxr/PUuZaZb42zy47iPByS09zKofOubYz5gQAn9I0OMP8/o2D/9810YwLPjWxfUsPHBg0MPZ+3t8vLrFzQkbn+WiT17R/3ogGOKuv77JNz9/JgaDPCoFmF3dvRQX5l5zo5Ibbm8XpSWj251X5chFFeAZEr3wL62FGcXwnW2CjV7BbTcd179MVIRHiZ2GF5tXEth3kO1tvcwZF8kbCyzfiD88H2wb2NstuG9NmM0aiYvDgo8fdiRYs84PwDyfzKWnm1itAT+w4v0wb5dq8ITglokSTbUmmmpNXB4Xtdl4qJsfPn2Q3103mbmHt3vrubWEZ5yOTqvpHydEItGxD/VK27zHkqgJTirxmkkKS6JUHiX2g0oEmti8EmadAUmmFYfD5SObVJR8bFOrgZqSEDUlIRYQObdCuHCPP4XWDj+bdnTR6QggCxNBTTfWmLxyvT591Ccf4hugzavjxHE9KZfJRHznmorS1if4Z7PgnwskAm8NvD5HCJ7QaNjtkukxyryw4ulBQnckKTSZuHbJEq5dsoRgMIivpwerJbGlz5LOx7nvhs+xaLufXXU6LD2CC04wIjMQyQ4Db2gk1hSbOb11L5eHh0Zgt0vwvFbDAQk+F5Z5QiuxQitRLuC8sOAP/3wCkzF/TjbRa3GFQeK2yfCjf+zk0TvmYtBFRi2E4KMD3Tyz1sGafV30+MP0BGR0WgmTXsOccUXMm1DE2zu8fPuxffxjvsS4w5+jt+rH8/MXmrn+1Ep+8PRBFja+hnXhOQA89OxHTB5n5YwTJqV0yBpObE43VeVl6RdUGVYcLi/lZaoFoUp2qAI8C6IX/hlmiYfmw0+cZm76+25+de0EqkoGT5VHW7VHf9/T2cf3/r6dQ31wVS18caKEVxgIBv18/a0QmzUSlwn4n4BMVJKueqWHyTHbX/VKDx1LiuiRJHZoBF+aJHFC6VDBGA7LPPz8Op57bQtd3i6+e+m4fvEdJV58x/Pi6vJ+wZtOiOdbnKZKO4kdR7636/KGKC0ZWeE0GiI8EZIEZYfexTr7TGZPG4jsdPeE+WDfPmwdsGOrIBgU6HRQWhYR5eXlYCqMaVqVJ/EN4OzRYS0MJ/37cEa+E+UPu4NQYYDX3gkjNBJNsqAaaBBw/ju9uIo1/Gjzv0dNfMej1+uTim8Am8vFiQvmYWtbi0ZAS72O1yToASoEhCToAiYKWICGy4ODz0UA+KtOYqNG4sqQoHBbgHvnGDlFFnw3KDNRQGOyVJsciV6Lz6+EFXb4/r8PcuUJVna09fLsh060Gokrjrdyy9k1WExaCgxa9DFOQd96fD/2rki+zfPtgpNK4T8dgg0f7Ofez05jY3M3s+oLsZi0iM0raa2cxyPPr+PRez4xauIbIgK8UrUgHHUcbtUDXCV7VAGeBf57lgKRPOJK4Hey4O+rOvjUH3fys49NYGHjgF1a9ObdGwjz8MObeaxZ8D8TJc6qgG9vFVy7txY5pMFqgcU3fJa7L7qIQtPgaHBUyjygiURgzrigEMKCq8ORG2FDmdQ/HoiIBqe7h+/878uEw4KffOV8Zk2pRqORUuY1wtBItJL89Ux57oBpyHoun9Dbv+0lixxD0lAS5Xxnun2lUc+W9j4aasaG53S+USp84z8nRYVaFs+acvhBLfJ5C4UELic4HdB8QNDTA5IkMJdA7zgfddVGKsr0Cb3jMymMixQ5Jf7bSKadQOQz1PfkBvb2wOvlGopdMn/XaZgvCz4dEtQ7w9Q7w5QUHznT0rOnTuVPP/4x/Hjw6z29vbTZ7Rh0OoqLijAXFvHEf9+g8dc/Ys9Fl/Yv95hWwoPE/wZkHt0YYM0sI5e/2cPSUyLJOcMlvqNE88h/6vPx+Isv8uf31zGpfhI/ueM85jY1pczR/VbX9zhf9nCgFw70CP56UDC5EP51vMTat3fx5x2CB784HY1GQpYFv/jN01x32Xzqq0ZXdHU63DRNHj+qY1ABu8vDtMm5pVOpHLuoAjxDYsV3FI1G4vNn1TBnXBFf++de/vGFaUytiYhJ90sbeK4d/nFIsMACP+sOU7slElH6y/NPs2XPHg42O1h43AyqK1P7yd4gvzboxpew0+WsM1iz6RDf/t8XOeOUBq6+chpabTe7fHtpsjQmFN6JWrEnSglJJ3xztdxLJsIzEd/ZuGPEj61llZ0Fs3K/wWbqvpAuCj4aXR9TNSvS6SQqq6CyCqKiXAhBuTyetk4/67Z4sbuCyLKgyKSl9nBeeU2FEaNRo+j4+Pwaio1ywr/lU3xnMvswwQRfnSRxbT20vSboRvCsVuIbBg2fv6iQ4Eup02WOFApNpkG52h12FxVlkUh640svsOeiS9knwStaiT8GZF54v483Fpq4/L1eKnxy/3IjhcVs5gvXXssXrr1W8XvKF93J6e8uJWIkOCDUPUHBj7YLfjNLom7dTvqE4Je7Bd3GIj49tTvvY88Uj7ebEtX6btTxeLspVc+DSpaoAjwDxKZlKaOoWg0UF2gJrN7Jiz2wwib4wA2zA4LvhWUmdg0sG70xzZs+nU3bliueTmx86YX+hwAYHPXusPu4+WsP0t0T5HOfnsPx86oHpY1kUkCYKt87k3bv8e/LtIgxKr7zEXmPJ5nosjuDVJQNPNzE7+No5GuPJuk6hsYyvXQKAJVWA3OnD8wEdfWEaOsMcKClj/fWewgczsWtqphDbe9OaktCWArCxAcr27x6as1Dva1zEd+5WhFaDRKfbIj8P+rF/6mw4ERZcK9OQ8PFxVzqclFRdnTl6HbYnFRXDOxT40sv0H3RpUwW8L1ucC80ce76Pqo9Iy++cyGaxhKLVopYO27vgnqT4Dd7BLYA/N/nJ2PQaSLfiTmjl4IiGGrNqTLyCCHQaBJ5/qiopEcV4Hnk1c0eurtDfGcbNBRE3FG+MxV8KwfnTMbemOTDdlKZfImjAmLjoW5KbH1MWnwBAM+9/yFarcT/3rWY/7YU0Xxg4D3ZFFLGk63wzoT4KHg+USKcIx0wRcK0if5lMuial00UPNv3jiTxIjzdA1FxoY6pE3VMnTjgUhEMyXTaA7TZZvDWtr14eiPe5KWmMLUlQWrNQVo8OiaXB5KtNi/ka9ZhmoB7gjI/02tYtXYtS887Lx/DGzN02F3MmT550GtzX3qBH110Kfe2h2hqCVLSG7me3SC/NhpDzJp4EV6sk7h3Dvxkh+BPB+CSavhRk4R+5RYY5oZO6QgGQ+h16q17tJGFGBIwUFHJBPVbnAGJbMFi+c5swXcTfCOrvp38PXanh0pracr1CiEIhUL4g0EMO3/ZX0R0z5s+mjs8fN2ylqmNZbRbJ9BFK1//+VpOvGQBJeWDW3cnS99QEpXOh/hWGv2OFeHR35WSTWOb2H1zZ1iAqaR4MlshPVbFd5RcZyH0Og31NQXU1xQgJC8Qyfd292lp8+rY1lnA2uZCDrqNmPQyNeYgteYQtSXBhA1e8k02x7+PiN/3KfPm5X08o43N6abCOrSYc/pLL/B/ozCefBPvST4VeHh0hpISu8ujOm+MAbw+NQ1IJTdUAZ5HsjHkP9Taybjawd3UAsEgm3buZM2mTazZtInNu3YRCoUIyzKfOLmCb33rUzg9Pew69AA3XDebX/x+HQaTgaoJlUyYPZ6P3rPzyl9e4+rvXNG/zlSOIelSQ2ItFDMlXpxm2jFzOIjf19jfgx3V1GdYgJmusDX6t7EuqEeT6PGRJCgzhSkzhZlZ7afNq+e64130BSXafXrafDo2txfgC88DwEoPNZKPGslHOd1opdQNSuLTTzJtV54o9aXhXD2HVgT5SAOPazWcLgtqKpN71x+phGUZnXZkOqiqJMfmUC0IxwJ2l0d1QFHJCVWAjzKv/vBvLJH3sifgpxd4r0nHoy2CaiOcNK+KzywoZv4VTbjrF3D9tx7ns5+/nO3u3TzwyGYqJ9fgbpiKbuFJBJxtHHDZCB90Ivd1oSmp79+GEru+ZCI8kfhOJELSCRslAj922fgoeDry1SCnpb2PeTPN6RdMQLpo+JEswkfDJjEYBq0mIqgL9IKJ1gATrZF0lEDbRmQRaY3eIcxskmtwUISMRAEhqiUfNfiolnwUSpEcciW539mcn/dcgnv1GoLA1WGZkxPXjB7RBEOhMSu+4/O3YWg0+2ii0+lm5tSJoz2MYx6Hy9tflKyikg2qAB9F9lx0KZZZJ2DY4udJrcSLWomTuwX3zZGYceVAY59g06nceMuDnHzceF78cB3/fr0df4+fwNRLeXF1AZIE+vJ69OX1cVvITw51VJSkKnxL1dwkkcsKKEthSJZ+kg/BnSgvfm+Hi/NOG2yBmE/hfKSK8JEQ3/HHprNLT1Vxgp7oh9FIUEEPFVIPs+jof71X6OjATLsws1GupRc9ElC5vYjakiA15hAVRSG0cWUX2bS57wsLvrNNcGtY5iQ5cQv2owGb0zMmfaePNfENkbRFVfiNPg6XhykT4u+5KirKUQX4KLHnoksJaTRoZJnf6yS6JIn7T9AwvnBwGos0+0zaWlzYnN1s3tfGxs5iahur2R08Ho0ufa6y0mY1qaLfMFh8NK8YcKWItULMhGRpLdHGRdEoeL5QEk2PFGCSsgAz7TqGMSf8WKPNq6O2ZKgDSjpMUoiJuJgoufpf0503F0d3D20+PRtaTdi6dQhzBQWHOqitNFBTaaQmoKHIMDR8nerBc70XphbByTHOg0eK+0cmxDugjAWORfENEAqFMejVW/do4/Z2UWo5cvz+VcYe6rd4FIh6eduLLezr8eKWJL4flBlfmHiKd0J9GY8/eEm/iHxxdTlSmjOXzEEkUb5yutSTqACJFd5RmlcE+0V4NAqeToCmyimPCthMLQtzyS2PNgbq7oKi4qGFmcPB0STCh8umsc2n5/RJiT2XDefPTSmM17oF80pAd/hhSiNBZXGYyuIwc2v7Do9zLr19YdptAVo3bGaDz0xPQIMkgbUwROX+vVRLPsqR0CXJLf/QLTihFLBFfj8axTdEHFAWzJ422sPo51gV31HXLJXRR5YFWtWCUCUHVAE+wsQ20tlYUsb7PR6mCPhwpo4+n2BaMRReEEk/iQqZHZ49g8R3OmK9s5OJ3dhIbTKxGfueROJbCfEiOpeCzliGo5jTYYeKSmnI8ch0rErzpWNFeLLlx7pIT/YQBbkLcU+vFktB8hb0yVjnEdy6SXBKGdwzi6R+yWLzSkyzz2Si5wMmThx4XRbQsXw3HZjZKtdgp4gwEgbCVEldVB/OLTfj592Dgk+HZBrO1R/VAtDh8o5p542j+djH4vV1YylRnTdGG6E+CKnkAVWAjyCx4htAZ7bw7bYD7BOCXd2CBw/BtXUSn49ZRkkUOFG0O5X4VkKivO/1EtQLSObvkK7ILV9R5XyL72iqi90mmDwlP8aumYjwdH8fCyI8289QpiI8ur/R+1sqY6Ho5y0+Ev6uU3DjOHi6DbyLZlKVwlYy0X5pJCiXeiiXeph5OLe8eUWQgFaLq8jM/qISPiqaiNdYgGU6uHp72XjuZ6lp7aS6ogyDIbu0rLGMLOQxFe07VgR3PDaHO61trcrw4+3qocRcmH5BFZUUqAJ8hIgX3wBhjZYp4TBnnatns1ew1i2YfPg7HStcUgnOePEdn/OdrIDScP7cIQIpXozEp548otPQJsFXQjILFTg9JGvUokTM5cvVJBXxOeYeN5w0Ibfod/x785GOEV3HWBDimZKtCHeveRuLSVn0O/7Bb+vfd3PD6VW89Uorru5gSgE+aKxCsKezjzf+s5O+sOAUq8RMM7S9FikENYTDVHvdeH1uPJLERo1Eb3MQ/34N5q8VsudgK+9+tJlAMIRWo6GyvJSaSis1lVbKS0uO2I55gUBQzTkeI3Q63dRUWEd7GMc8DpcHq2pBqJIj6lV1GEiUnxhPr95AeVWI0kodd++WecMOX50scWrMtTU29SRKqu6QseI7nXNJNF87mahL9r7PhgR/1mkwB2VmJpiFi02byYZ0Yi0f0e9ExZ1CCIp0RTkVYCYin/Z9+YiGO7uCrNjiYf3BbkwGDdYiHfMnFDFvfBGFxoEaBCEEB+x+Djr9BEOCU6aWYDKMnIBsK5tHrX1rxu8Ly4JtrT3Mqi+k2y9jMii3zvv+vw+y7mAXp5kEJi3ctUvQ2S1YoJM4XhbISPzbLeMq1jCpPURxn+C0/QH0QZjeOJ7pjeP71xUKh7E53LTbnKzduAOn24ssBAVGQ78or6m0Yi4a+1G0DodL9Z0eI9idbuY2TU6/oMqwoloQquQDVYAPA76QYFdXZPq8TA8TTEPdQrbL5fi63Hx8m+AUKzx2vETlxQO531EBq9QPW6nbSSyJrAOTCe8QYJPgBFlQFhL8Qa/h3oDMhMP7pcRjOR2JhGom+54tTZZG3N4gFrNr0OtHYsQ5FVtaevjMX3Yys66Qq04sJxgWdHiC/G1lB9vbeplaXcDEigIcXUF2dfShkWBKtQlnd5C3dnpZduX49BtJQDYPIW2dAZpKklsQJmN7Wy+VZj2WQh31ZQbufrGFJXPLOL2phOKCxGI8sHwja1yC9bsF/1ogUXDYn/Dr9z1Na2cnb61dy6q1axFCcOvZZ7N44UKMhtS9OHVaLbVV5dRWDa7Z6Onz025z0mFzsmn7Xrp6IgWhZZbiflFeXWEdUxHnDruL6ko16joW8HX1Ulw0+s3MjnUcbi8Tx9WM9jBUjnDGzlX+KMHhdvP59YIiHegkaPdH/j3NKjjdKlFugL2Tx/H67hKa7a3cdf0UFkwcsDJKJFTyaccXTyoniVh2S1AloAw4TgYnUL04u49PopSKRK4sIyW+AVo6/NRXFwwZV67k2z87lyj4jFoT37mkgT+81s6ujj5uWVzTL0p7AzKbmrtpdgaoMOuYUFHAeKsBSZLY09HLjffv5uLjfEyoKKDSrMuq62smdNr9nD4hs8JfIQSPrbZxwZxSAH79iYm8sc3Dixtd3PnCIeYXySyukDjdChb94PH/5aDgSxMlCrSR16M5xnVVVVy7ZAnXLlmS+04BhQVGJo+rZfK42kHjdnu7aLc52b2/hXc/HEhjqbDGpLGUlYxKHnaHzcXJC2aO+HZVEjPc3z2V9Lg8Psos2TVsU1GJogrwPBIOh7n5hz9EI8GyJonxJgkhBLu64S0n/GG/oMtgYLrfS0XDdO789hkUGIfmpw5n/nM2Ht4N5+p59fUQ4w9Xxm2RYLplQKzER7+Vjj+ROM1EfEdR4nGebpmWdj9zpxcfEVHvbEW4RiNx1YkVLJ5h4XfL27joni2cNrWEC+eWccoUMydNNnNSgtlta7Gec2eV8sfX2zlg99MXlJlVX8jVJ1Vw1gwLeq1Eq8uPAOrLjAm3nWkUPOSyoc9wpv3hd2xsb+vlWxdHmmOUmHRcvqCcyxeU43xxA287Jd6wC36zB2aZBfNtMifJAjOww6BhvC1MMyNvJShJEmUWM2UWMzOmTOh/PRQOY3d6aLc5+WjzThwuL7KQMRr0VFdYqakoo6bSSom5aFhFmSo2xgZ+f+CoLPA9EgmH5THbGVblyEEV4HlEkiSuu+wytjx1H59fL7h+HFzfIDGtGGYvncv/EBFPshD889k2DvQdhL7U68zGOSRZ/ne8lWAmYrxWCF6SNIBg/2Qts0Ukcqfkxq9kH2JFe75TbpQs07mvhQqL6+htZRiDtVjPj5eO56tdtazY6uGhtzv50dMHufnsGj5x8lCPm7IiHT+4fFz/777eEO/t6eLR1TYefreTxdMtPPR2J5IE//piE9WW1OkZ6ehbvwqDTnl+pRCCf6628dh7Nh68aSpm09DLWrFO4sIquLBKojcs+M/KEKs1Eg/rNFgETBdgYmz5eOu02v7odyx9/gCddhftNic79jXj8XUBUFxoiqSwVEbEeaGpIC/jEIikVo4qI4fN6aHSquYdjzaqBaFKvlAFeB7RaDRcce65XLTh/7h+nOBTHwkuqx463b324B6kQkE6tZepc0gs6cR3LKnE9/4ewdNtgr1aDQc0Eu1A7b4wfzJp2dsjuGcmxMotsXklTRmmXWQa8U/m9BKP0oirvGklsigb0po8V0aifXsuWIv1XHNSBdecVMEhp5+bH9hNkUHDZQtSe82bTTrOm13KubMs/PK/LTz1VhsPzJZYtlOw+cVtlJVLCWsClETBxeaVtPv01JiTf15lWSBJkQfeAw4/f3m9nd2dvdz/uSlUWwxIc5YNeY9xTsz/geu+CdcB/kCAjTt2MHvaNEzGxNH7sUaB0cD4+mrG11cPer2ru5d2m5PWDjvrNu+ip+9wfnmJmerKMmoqrFRVlGHMIIra5w9QkCbfXWVksDlVC8KxQFePmoevkh9UAT5MlOpBC3SHwRJ3v7N1QmVV6ohSInGpNF87nmzEd3dIcO8+wUoHXFkDZ8oyF4cjHuA1MpzQHeZ/zVru2SP4vhA4ukK8vtXD7s5e/mdcD1ZL4aDx50uMKhXfSrctNq/E69dQUqDAV1EBIyG6hyNNZpzVyB8+3chNf99NbamBEyenTjmIfha/boAvLpD4xlZBUIYG08DfMxXh0f1q8+qpMScvwLzjX/t5f68Pa5GObr/MZfOtfP/yBkwGbULxnQqjwcCJc+akX/AIoLjIxJSieqZMrO9/LZpf3mF3HbZJ3EIgGEQjaSgvK6G6oozqSitV1lJ0uqFT6mOxBf2xSqfDzfyZU0Z7GMc8DpeXctWCUCUPqAI8S8SmZSlv9itsEeFdVzAQDYwKD1unYO685AI8nYd3vKCOiuhsu1XGYjh/Lh/t7+KHTx/khEnF/HuSi2KdRPPuwZ7MWuB/2sP8sEzLOT/dQFCr4dSpJVhMOq772kM89ZXpFOgHQsq5CvFUwjvRg0ms+EsnWFs8ehosgazGFWWsR7uVMKHcSLVFj6MrtftI/PF+sjVSaHz/PAmtglSF+M9C/Plp8+qZVZM8N+vGM6r5YK+PbyypZ1GjGb0u8jnLVHwfC8Tml8faJIZlGafLS7vdyZad+1jp9BAKhwf8yyusVFeU0drpVB1QxghOtxfrGO5Geqxgd3koV1OBVPKAKsCzQGxa1v9v/E0/6gGuk+BAL0jnDI2u9XRDUXFioRIrMIUQ7H1+I5t9sHdLmCIBRQiKJSgCigQUAwdXBJMms/QCByRwSVAqoOywk0n8ZLsQgq3TG3n26YO8u9vL9y8bx5nTLQSWu5Meh0Lgb8dJeEMw4dI5SJLEttYeXljvJJmddiIh3mRpHJSGEhXbzx0wDXI5yeesQCwtHgNzarJzU8lWeCdzgMnkffnm+XVOdBqJ82eXJvx7omPtCwn+fkjw1UlDxXeyKHiUZPvSHdBgNiafkZjVUMj/nFPLn99o5+TGgUh9uodilQGiQruyvJQ5Mb7SoVAYm9NNh93Fuq272Lh9L+WlFtZt2UVVeSnVFVaqK8uwWsxHbGOhIxW18G9s4HB5GV9bNdrDUDkKUAV4hohNywjLgje3edhv99O1/At0Fy3A192Nd/NbdIXBazDi6wtzy9kV6A87hURF1hbHbpJdQ5ssjXT3Bnj2ked5970WNntBHxRMlQXlQLMGutDQLUE30HX4Xz+gD0JBUGA8/KMPCVzFGnwmDRM1YBXgOSzEXUTytisLJawbZXwh6JS1WHcc4rL5Vm67cDqlhTqkOcswsIzA8o00nKtPGnkv1kUibTZfkK8+so8fXTEOgy71zTk+FSFehAM5ie904i8WW5eOyuLMPaezIZHoVOoQMpzi29cb4g8r2vjf6yYnbEYkzVmGcc7QJlMFGrhpvMSDhwTdYfhUQ27FerJI3X4+yidOrmDtvi5uf2w/P7i8gaqSSJ6yKsJzQ6cb7F/e6XBz3RXnEQyF6XS46LC7+GD9NpxuHwKBQa+PpLEc/im1mNWCzWFAlmXVfnCM4HR71S6YKnlBFeAZEI18/255K2v3dbGw0UyxUUvlrlco1kFxrUTpokbMBVomLz4fXVxV3w7PHpwOsJYPvpBGxeU7H+3n+7/5LydOKuaSKri8LUyfBJvf78PcKyjqE0TfecYFkRzrVa/0IEvg10v49dCnl/DrJQI6idJuGatPRhtTtH3GBYUIoAswHK/DFYSy06ZSVaLHWqRDM+esyILS4sg/c5bB8ojoSpYvHhW6335iP9curGBx2yECbYeG/H3I8YyLhicS4bHHJ5X4bl4RVGyrGI8syHsBZiLS5auny40eTv78ZgenN5Uwq35oZ8ZYQWu8/Wn2XHTpoL+fQcTi8Lf7NCyuiKRdRcnkQQjA2aPFWpj+YUiSJJZ95+Nc8aV/8IqtnOtLfP1/U0V4fpEkCYNeR0NNJQ01g11y/P4AHQ43HXYnez5qxe3pQiAoMBioihXmJcWqgMwBl6eLMktx+gVVhp1wWE5YL6GikimqAI8jKrKT0ReUeWqNgxe+PhNrUeTwBfwdAENyvRNh74TKqqHWeGLzSv784E6+0RBChDzcu1XQbdBQ5JKRZxfgM0kICWYcCjHrYJBVr/T0v1cjwBQQmAIAqS2SVr3SwxkXFGIGGooO+3jXFQ4e92HxHcV4+9NDIp/x2HxBdjV38/v6HuLzT9LlaCcjmQuMUoeXdOJPmn0mXl8I8+bNaceSK0pEdCIRPhLiOxiSeWqNnfJiPTc/sJvyYj1zxxWy9IRyjPN/kvR9AmgHXtZKrNJKfDcYpq4gN5/iNq+e2pgCzEBI5pAzgD8o4w/J+EMCd3eITb1lvPunJzj9hIlcd+l82Loqp+2qDKW7p4/CgtRWhkajgfF1VYyvGzwl3+cP0GGPRMx37W/G4+1GIDAZjRFhXl5KdaUVyzB7mB8t2JxuKstLR3sYxzyqBaFKPlEFeAqkOcsGCXJ/UOYPK9qYP6GIvZ19PLmvi43N3XR1yFj1ULprPRVN1VSveYqzZ5ZSvvCcQetrsjSy3tPOySdW4uv20+nsovPD1XR6A2xp6cVu6yEwHv66TeYLIRn3yz2D3u8qktgyXs9Tp5gw9wqKe2WmtYaY1jo0YniD/Jri/Rzy0CHeGCTCUz2UGM6fS7snwGP/2spJpaBLlvydavsxwjORZ3e+c75h4GGjuaOP+pmTgPV5WW+ujEYjIL1Owyt3zKLTG8TeFcLuC/Lbl1ux+YJ8WTc4muy/ZynPayVe0kr0EinGPSMsuCcgMzfLGYgogeUb2ReaQsEELX/Y5mSdvYKte/ZQabVSWFCA0WCgwGCguLCQ2dOm8aMvXctxTU2RXOQ5Z+e0bZWhdNidVFdm54BSYDQwob6aCXFWib19fjoPC/OdMcK8wGigujwSLa9SI+ZDsDncjKtT845Hm55eP0WF+fHXV1FRBXgSoqIjVoSv3d/FMx86GF9u5KfPHeLcWRau0HdRMlHCFQRXAFz7OvmotJT7Xm3ji+e4ufqkciRJosXl5/6VHXQGJvO//3gSCagq0VNVoqe8q4uGAom/Hiex7F2Zi2QxRHwDlHULTtsWYNH2AG1WLYcqtLy8oIDxti4KYoLAmYjv/n0Vbwx+8bAIF5uWIYTg0HFTeXuXj51tvfhDMsGwwB+S2X/3FgK9QeaUwI3jlN8w46PTyVIw0onv2Oi30jSU2O20tPuZNa0YqSq77pKZdngcq5SYdJSYdEyphg/2+nB2h5hcGbnRRFM6orMgPuCksOCKsKAUkFDeVTURgeUb6Q4JfrJT4C0vQt6ynuPPv4obz5zJcdOnU1w4NC1GZfjpsLvybkFoKjAyoaGGCQ01g17vF+YON7v2t+DxdSGLwaksVeWlx2yOuc3pZsGcaaM9jGMeu8uj5n+r5A1VgCcgPn80KsIXTChCr5VY2GjmlsU1SG9shvJENwMPB2YKlr3ZzH9XNTOhsYy3dnhZemI140oKuOuyWRhWbQGCh380NK8I0rcLFmvg97LE4lodU9pC9BglugokfIUafAUSXSYNPpOEz6TBadZw9kZ/TuJ7YCcXg3iDJ17eyLsfHcBiLsBifovu1kO8s9OLJMFp00pY2FhMgV6DQafBoJOotxqpWbs9q2hVJvnB+Yp8x9PpCHB2eaSAL9v0j7EqwrMZk9i8ErsvyJyGQi6YMyC+xKZlhIRgeSesKNBwgl8m+tdcxbc7KLhts2BqMcwtl7jxV89kvT6V/NFhdzF72qQR2VYyYd7nD9AZzTE/0Irb60MWAqNBT1V5RJRXVRz9riw9vX6K8tTZVCV7HC4PFWWqBaFKflAFeBzJirekOcsoBF5/RB640C9Ivp5pwEOhEG+8/z4tHR184+vn0d7pwu3rwjxvJpw4ePnG2w//Cxy3ezd3/OpXrHC5KDKZqK6ooKaigrqKCqorKqitrKS6ooLGceMoKc5fYc5vn3yV115r4SvXn0p3rx+3t49K60w+cbKNyZXGhCI7sHzjENuKRDnZyURarAiPCtl44atUfGca/YZIV0WtNvHDQ6KxJCOVz/lIp5VkbY0oBE9+YOf1rR42NffwwFsd3HRWRBCFZcEdWwRdYfjKJInazSJn4R3lXSf0hOGrjQZenzX2HmSOVXzdPaPe8a8gSY65PxDE5nDT4XCxZsP2iCuLEOh0WiqtpVRVlFJdXkZ5mQXtSFRYDzMiTW2PysjgcHmZM31y+gVVVBSgCvAMySTKotfpOP/UU/t/X7NhJzOnTkj7vllTpvDcH/5ASJaHtT22EII9hw7x1tq1vPLef3C6+vjht07mtMapg5dLIiAzaXefKj0kXoRnQjpnliiJRKm3K4S5KL9fgdHI4c4X3rWv8/MXmgEw6CTaPUGCIRm9TsO7u7w4gvD3eRI6SaJZYd1qohmO+M/N+ZXw0CFY4TVTf9j+TmV0iRabjdU8bKNBT0NtJQ21g11ZgsEQNqebToebdVt343B5CMsR/+zy0hKqDqeyVFpL0euPjNtfd2/6YliVkcHhVrtgquSPI+MKdJTQYXey+JT5ipbV6/XkVtKWmEAwyIdbtrBqzRpWrV1LOBxm7twirrxkCjOnl2MwaNnh2TOoGFJJJFhJF85srAIzTT1JJPiSRYRb2vuor0n9gJNJFHwskEtjoBKTjnU/nYe3N8Ttj+1nT2dfvye4Qaeh0w+/2SOYYILxEogVQcalOJ+JzoX/lQ2EBQQFBOXIvz1hmGGGV7xmvleldl0cC3R192IuOvJy7/V6HXXVFdRVVwx6PRQO43B56XS42Lb7IKucGwmFwkgSlFnMg9JZCoyGURp9YuwO1QFlrBAKhY+YBzeVsY/6SRohhBDIQqAd4TxF/z1LcQYE77rgXV0J7+/1MamygDPPOI7ffvsc5FLPoChXOhcSyCzyrZRE+eC5iu90YrSlw8/MKalTeI4k8Z0Nifbv4XdsdPWF+csNjWgPC/CFjWZ+N1viIw/s6RH8Q69BAuZskynTg1UvYTVAmT7yI4AdD2xgR5dgBwW0uQMEgzJBEXFO0WlAL4FeAwYNnGCB2VJxfwMYldGl3e7MewHmaKLTavs9yWkaeF2WZVyeLjodLvY1t/H++m30BQIAlBQXHhbmEXFeXGQalRmBTqebKlWAq6gcdagCfIRwun1YLSMzdSWEYNeBA6z6zy95c73M/h5Y2GThjKYSvntpA9ZiPdLskw4vXTn0/SlE53AVQyaKlkZfS7bNZAWcSqPAnfYAi09OHu06EsV3JgWhifZv1Q4Pyze7eeCmqZhNgy8Pc3/0DNEjLoRg5cWXcbBNQmrS4gwKdnSB87AbkACaimGeReL6W+6koaYGg16PTqtFm6QV7MPPLMdUMHwpVyrK6bC7hkSRj0Y0Gg3lZSWUl5UwY8pAeqAQAm9XD50OF+12J5t27MXXHXGmMhmNVJaXRiLm5WWUWYqHtQDU5nAzaVztsK1fRRk9vX3q9Uklr6gCfIQ41NY5bD6u2/bs4aVVqzjU3k5zezvNHR1YTTKnN5Vw69JGFkwsGtQaPpnbR5s7QLFRg/GtrRltP1Gb+kTLJCOdE4oSp5RsUi/CYmgB5pEouuNRIsKT7ed+u59Tppr7m0xFGeIMJEmc9eILka6Y20JJz6/x9qcVjTkcltFIR36x3NFCh83F/FlT0y94lCJJEhZzERZzEVMnNgz6W0+fH5vDHYmaH2rD5Yk4s+i0WiqsFqqspVRWlFFZZslLukKkC6Y55/Wo5IbD5aW8TM3/VskfqgAfIQ62dnL6iXPyvt6d+/dz609+wrVLlrDkzDMZV1NDfdVOive9N2i5RKLb1xdm7V4f77y5n/dd0B0GvwxTg4KTwoKFsiB2EjqViM7WESOTNuXxJBOZqdrZR/F1hyguHPj450t4p5ohyGVfMyXb1vYzak28tsU96LVUbd0bX4qI8OgDWOznQKn4BrXT31ijp69Ptb1LQmGBMWGToWAoFMkzt7vYums/dqeHYCiERpIoLTH3R80rraUZNXORhTziqYsqQ3G4VQGukl9UAT5CuL1dlJbkxzIw2hDFExR8dZ3gtokS5zc/Ds2HRd6+weJUbF6J2LySUFiwuaWHd17ZxQdu2N0Ns82wsEziNm+I8QL8wHoNPKXV8Fe9hmtCMteGh8cCK50gVRrVTiS4Ey0TK8Jb2v3UhQ4gNm9TtI18kInveT6IF+FKHjK8veFBv6cS31GiIhwGCm0zEd8AbZ0O6tT87zGB2m47O/Q6HTWVVmoqBxcSy0Lg9nZhc7g51NbJR5t30t3bB0BhQcEgYR6fzhIKh1XxPUawuzzMnDpxtIdx1LN282Y+//3vJ/xbXVUVL/7lL9x+11289t7gIGNFWRkrHnhgJIaYN1QBPgKEwmF0Wk1eCnj89yzlYI9gjRueahMsroDzqw47VcSJO3nTmxxyBnhvt493VzfzoRtqC2CmR+YKWTBdgLEHRAe0SPC6RmKHBrZJEkEJrg3JnHdYfOfi+RxPvoR3JsRHwJs3bmd6Ve7Fo/EYzp87bHny2ZBJZH9zcze/erGFH1w+DlAmvqM0vvRCpkMbRFung4XzZua0DpX84PF1YzHnr7/AsY5GkrBazFgtZpomjxv0t+7ePuwON51ON3sPtvans2g1GirKLBgNegx6Hf5AEKNhOHyxVJTicKkWhCPB9MmTeeAXvxj0WjAY5Bu/+hVXnHMOAN7ubs5dtIhPXXZZ/zK6JLVFYxlVgI8AbZ2OnN0dev1+XvrBx3m2XdDcCwvL4IsTJU45HGyJilpvb4j393Tx/nOPsHq3j2BPgJNKYX67zKdlQWkPrHqlBw/wHrC3RscH0wz0GCTqnWFqnWG+MV3PuMNuFcnIxrFkOIS3kuh3PGLzSjq6yjizsav/tXTjzyRynUqEj3QUXAlCCJ74wM6f3+jg+5c1cNq0kozEdz5wuL2Ulap5rmOBDpuTmqPIAWUsU2QqoChBB9BQKIzD5eHDzTvpCwR57tV38Me4s1RaIxHzyvJSSsxFaMaoX/vRRDAYUh+CRoDiwkLmz5gx6LUHnn6a8tJSblh6ePbf5+PE2bOHLHekoQrwEaC5zTakYYQS/PcsxRMU/PmA4OXOSPT6c+MlzrCC7rA9XFAWbGmazHsr2nhvj499tj7mjS9i0RQzH5OdTCqUaHktBESEd5Ruo8TLCwrwGyQW7ggwuT1E9BJ+cH+QiRcMeADHRr+TicfY1xOJz3yK70xFd2z0OxoRlmWQV2wkoHAdmTqxpFvXWBHhPf4wP33uEHttfTx401TGlxtHXHwLIRACVUSMEdrtLibGCUKVkUWn01JdaaXQVMCc6ZMZVxsp4BdC4OvuxeZ0Y3O42b73IF5fN7IQ6HU6ystK+oV5ZZkFgyoYVY5w7C4Xf33iCe759rfR6yOfZ29XF9bS0tEdWB5QBfgIcKjNlrWjQE848jOlCFr74IfbBdVGqCsQaCXY1KNh3L4WFi1awlfPncdx06dj0OsRm5YRWN7eXxwXK76by7W8vKCAWQeDLNwRIFWGoRLxHU+m4lKJ+M4m0p1IeAN0+TUUdNpTh/gVkGo/06WiZCLC/UGZe19tZZzVyKz6QqbVmDDqB87aluYeVu3wMLGigAvnlipOdfL1hbn5gd1MrTbx0BemUaDXjLj4BvB191JSfOQ1fTla6bC7WDjvyI4sHS10OtycPH8gNUuSJEqKCykpLqRxfN2gZYPBEHaXB5vTw/Y9B3nb6SYQjARfSooLqYhGza0WLCXF6gNvBvT5A2r0e5R4evlyaioqWDRvXv9r3q4unn/9dX73j38gSRInH3cc3/jc56iyHlmN3FQBPgL4A4Gsu6vVFkgsaxq4UPplQXtfRIz7Zbjz8plYT/7ZkPdJc5bB8qWDXhPAmqkGNkzSc/66PibYwkPeB3DG4eh3VHwna3CTD+eQkcj3jh/ngTeaqZOyd3jI9EEk15zwXR29PL/OybmzSnnuIyf77X1MKC/g82dVc+6sUtYf7OLvqzposBp5Yb2T335y0iCBHk8wLPhwXxd/eHoPc8zw9aI+pDfcSBkWTuaLSIrWkXXhPJrJ5Xqlkl8yORd6vY7aqvIh6Y79UXOHG5vTzY69B/F4uxFErBPLS0uoLC+lwmqh0lqqnvsE2F0eKqyW0R7GsFBUELkXlr+5jxJGZuYrQDdughSZTCmXk2WZZ1as4FOXXjro9ZlTpnDc9Ol8+brr2NfczB8efZSv3Xknj9x997B68ucbVYAPMz19/rxe0IwaiQmFMOFwwNCYQHz3L3v707DiUla90kOvQeKV+QUEdfCJVT0U9yV2OkglvuPFcq5t2nNxOUnUsTMRibp4tjKZqZJd0fvjySZ1JFk0XGkUvLHKxMy6Qra29HDurFLOmzWBf69xcMe/9nP9qZXcdkEd6w92M6XKxM6OXn7/ahvfWFKPLAve2ulln62Pbr9Mlz+MsyvEB3t91GvDXFApcXVdJKqWqWtJPmnrdDA5LpqnMjrIQiChRkbHAvlyoxkUNZ8w+HsWCoVxuL3YnG72HGjlvY+20hcIICFRaDJSYY0KcwtWSwla7ZEjbvLJ0VyAOXXiRMxU084WzFSPyPe/jS0YKOTcRYtSLrdhxw7abDYWL1w46PW//WxA95w4Zw4Ws5lv/frXfLhlCyfOyb/d83ChCvBhprnN1p+/Nxr4gQ8b9Xw4xcDMg0EWbQ+gTXJdTya+UwnlbEV4JpHvJkvjIBGei/gG6BRmTpX2Kd5+lFzytnMR4SaDhj98upGPDnTxxjYPn/nrLgoNkRvhw+/YWHp8OfP7vOzt0vHDy8dx6W+3cfZMC794oRmjXsMJk4opMmoYV2RkZl0ht11Yh/X97f3rH03xDdBuc3LKglmjOgaVCC63T236Mkbo6u7FXDS8qVk6nZbqijKqExTddvf2YXd6sDndfLipA6fbS1iW0UgSlpJiKqPivMyCubgwLy5fYxWHy0NT4/jRHsaw8ff//Q5Xf+1ruDiIlQnp35ADPbhwc4hf3XFHf053MjZs347FbKa+ujrlctH0lP0tLaoAVxngUGsn07P84iYSRlEP8Njfjbc/jcPt5mBrK77ubnw9PThcLtY8/yAfGjTMnm7k52GZ8eN1MF43KB88yhkXJL/QZ9LeXAnZrEup6I6STHwDhJHQSSPvdZyLCNdpJU6abOakyWZuOquGQEjmlgf2cMDhx7NqB94QiEMOTG+7mGSQufUfe7n9ojquOqEczdwfD13hafnaq9wJhkJqsdgYocPuTCjGVEaezlFuTlVkKqCovmBIwyFZlnH7urE73LTbnGzesQ9fVw+Cw4WgpSVUWC1HVUqL3eXllKM0Ag6RKLiVibSzhVIa0ORaIJUEgaCNTRRi5bxTTkm7/Ibt25kxeXLa5QLBSK1bceGRVUukCvBhpt3m5KyT5+Vtfcbbnx4kwrf6BI98/go+6C1i8rhxmIuKKC4spGTPW1xYJfG9qRJlBgnQ9hdkphLbsUWXSoRhJtHv4cj3jiXZWGJFb7fQU0jm/t/D7VqiNB1lb2cf96/sYPUeH+eWhDCbYYMXnmwV3DcnEoG6qEriWp3gXFcrmrn3Deu4cyUYDB2R/q1HKx12F1Mm1o/2MFQAm8NNpbV0tIcxBI1G0+9rPo3BvubBYGhwSsu6rfj9kettQYGBSquFirJSKspKsJaVoNcdGRLkWKiLeOz+H3Dh576And1U0TQs2/DRThc2Hvj5zxXNmBxqa2POtGmDXnt/wwYaamoGRcVXvPsukiQxc8qUvI95ODkyPv1HKEIIwrKc97w54+1P4/nVlfzpgGB5J3x2nMR3p/ZQrNt5WMT5gHmD3hNYvnFIM51E7cOTER8FP9jm5q9PfsDuHfs5o6mEpSeUU1WS/AI1XOI73QNAfMS5VViolbwZbUOp+JZmn0l3b4Dbvv8wx40v4szpFmbUmtBoBi406TzCk20vsHwjISH47jrBacdX8+BNU6n5cAe3bZZ5pk1w0wSJxqLIdpbWRv4d7dQSJXTYXUM6B6qMHp0OF6ceP3u0h6EC2JzuIY17xjp6feJuoBCph3I4PdhdHjZu34vD7SUUCiMQlBQXUl4WSWepsJZSaike0Q6gQgh2HTiA0+OhyGRi2sSJGA1Ht+COp7q8nM9dvZS/P/kMViaiw5jX9QtkWtlECXXMn6ms6ZrD46G0ZPDMw0urVrFq7VquOv985jQ1sWPvXv765JNcfeGFTKg7smqJVAE+jLg8PqzDkE+5+gdXcucuwSwzPHq8RKk+/ZOk/rw5BF/dlPBv0fbhiYiNzMaK3d1b3WzZ3M63L6nnta0ePvF/O/nZx8azaMrYmaZLJHRbKWFKBgWYSsR37MNFYYEeUVjKK5tsrNjsxucPc0aThTOaSjhpshmTIf1NJZlAf7QZLHq4Se5E+tCG8fanufdwq+ojNf8yH02qVPJHIKimA40VPN5uLCVHT0fSwgIjhXVVjKsbXBMVdWmxuzzYHW72HGzF7e0ayDc3F0dSWsoiaS35bjzkcLu541e/ot1up6G6Gk9XFwdaWpg8fjyXnX02l5x51jEjxj975ZU8+OTzdLCdeo7L67qdHMBPF4//4S5Fy4fDYTw+HxbzYA31oy99iSdeeomVa9bw+EsvUVZSwi0f/zifueKKvI53JFAF+DByqLVzyMUmFw60tHD/T25ltQu++7FJnDVDmS2StzfEZ367mQurJM7dGUpY46xUhEPElzokg70ryAmTijlxspnzZ5dy+2P7+PMMmYmFkS0Md9pGNsWfncLMKdL+tMtlO3ZJkvjOFxZz47cf5VOLKjm9qYQP9nbx8DudfO/fBzh+YjGnhgWnlUOFIXKcojMRscSfi4O9gkeaBQ/Olwa5lhzp6RutnQ7OmtQw2sNQgcOC59h0uRiLCMQx4dUd69IyeVztoL/JsozH191fDLptz4F+C0WtRkOZxUx5mYWKshIqsiwGfXHlSspLS/nrT3+K9vD1tM/vZ+OOHTzw9NO8vOodLl98QdL3b929mzabjVMWLMBkzG/UeKQpLizkji98hrv+8lcqaMRIfh4Aw4RoZyvlTGJivbIUN61Wy0dPD53FlSSJa5cs4dolS/IyttFEFeDDyMG2zpymc4UQ/Pnxx2lub6e1s5N9B3Zy1QnV/PvUSkpMQ09dbCQ2Kk732fpY9uB25pbAy/tkZI3EBXLiAsTmFUH0p+v42wFBnwyygJAAGQhvWY8oN9Ptl9nZ3ktjVQEfX1jR/97ZO/dyjkXmNbvE5w7XnA5nx8dMU0+ihNCgl+Sk78vHeCd5NvHPW6Zxz0ut3L+qg9pSAzPrCjlrhgXL3jbe8gju2w/VAZn5skCjlfBK4AV8kkQ30PhmiMVhwbTDp+rXOg2XCUFdge6ISC1RirermxJz0WgPQwVwuryUl42dGaxjmUAwdMTkRw8nmsMiu8xiZmrcg3o4LOPy+nA4PbR1Otl0uBgUQKuNvC8aNS8vLaG4yJRQnDeOH88/nnsOm9NJTWWkY3WB0chJc+dy4pw5/N8/n+SRF56lsEjDBacNrV5fsXo1Ty9fTigc5tolS7jxqqvS+luPZZaefz6/+cujtLGZiZycl3Xa2IVMiCcf/GFe1ne0oH7DhxGXpysnSy954zL+9fxmPn1qFRedYGL+VTP7UxjS5VR39YX565vtPL/OyWdrIn7Prx8K80edhvNlwVtxTijRwswfr5apQjBDhso5WjSATgKNBFqpC2MBNNVDsa4Pwn0EX7UBkYeFtW74bpKGn/lyUsnFdzxSgJm8+Xwi8Z3ooUbJmOrKjNzzyUkEQzJ7bX28ttXDY6vtPDNH4oIqiZAsePWNMBs0ElqgRkCTALOQKQC2ayR+odfwvaDMBAEfaeArAXFUie+oz/GRmj5ztNGuOqCMGewuDxVlR2fjl3yh1WoiArvMMqRkMBQO43L7sLs8HGrrZP3W3XR19/Y3H7KWmikvtVBqKeajrduwFBfz7vr1LD3vvEHrkSSJmY1TmdM0hbvv/wtrNm3iGzfeSEFMpLu+upqT583jts98ht8/8ghX3Hort37qU1y2ePEIHIX8o9fp+MW3v8TX77qLbhwUkVuKYJA+bOzgfz557VHRPj6fqAJ8mAiHZbQaKSdxodFInDjJTG9Q5uRG86BivmSCVgjBf/75LPcub2PRFDP//vJ0Khbdif+epcwQEJLgYMyQPIUSa6YaeLMlzLnjtGzVwNcCgkKADaGE43If/oml+XgdEnBcggCaoyvInc83UzEhzPduPlvx/qcT27IsBh2TdLSJkqQFmMm6fcZuK5szqddpOOQM8OQHdj61qBICnQDoNBIXnaPnijhBveeiSMev6WFBtRD8XqfhWyEZKzDrpReyGMHYxeXtoqxE9ZweK3TYXcycMrwewCrKsDtG14LwSEen1VJZXprwGIZCYZyeiDhft3UH6zbvYfqEWdjtvTz2/GuH01pKDqe2WLA7PVxyziIevecefvbHP3L1177GgpkzMRmNfLR1K62dnXzi4ouprqjgZ1/7Gpt27uTu++/n7089xfwZM0Z+5/PA4oULKaKcNjbRyJk5NefpYCsa9Fx3+eV5HOHRgSrAh4k2m4OaytyLy75yfi23/mMv9WUGLl8Q12L4sECNisXtezv5xe+eJxCS+fUnJjJ3XFGkJT0RRwxpxaX4AbsUEd476/R81KjnuH1BdDI84RZcXXZYfGdAALhro8xnwjKSFMld7g0LVjrglX/sYeOhbiZWFPDGy5v4+mdOx1SgzHUlHbc8uIewEHz74gam1gye8kvkNtKKhcmSY8h60onvN97fww/uXc51C61cOr+MXR19nHhgPzoFD1eG8+fS1RdGkiSaak0YmgbGlSia3fjSC/0ifKEMf9RBmwTFI29bPuy0dagFmGMJm8NN5cL8Fl6pZEen083MqRNHexhHJTqdlqryUqrKS9m4YzMTGqz88NabgcORc48Ph8tLa4edTdv3smt/M/9+aSVajYazTjidE2cfj6/bS1gO8b1bbmHW1KmDanHmTJvGQ3fdxZbdu3nm1VdHazdzQpIk/vjLb/Lpb30LL61YyM6atA8vDvaz7Eu3HvH58cOBKsCHiXwVYJYV6RBCUFeavAo7Kla/cvcWLptv5ZazayLR98PiO0rjSy+w+JLL+KdWg/3UQuodYT7+Vg+Wnoi6O2F3ZLlVGY5xW4MOQ4OeEy0SzSuCdAPftmiZYIJTTzYzo7aQZz508OnLF2DQpy8aVJpmsrO9l4WNZm55cA/3fGIi8yakLhjpEGYWxRVgphPfz67Ywh8eXc3Pv3YBjz7+Jn9b1cHEAkGpDm6ZCDPM0P7awExBfPFkYPlGzg4LXtYL7ny+mRdvj0wRpEoliYpwDTBNwI6jNEWjrdPBzKlqxHWsEAqH1bzjMYLdqaagjAQbd+7kxNkDdVo6rZZKa+kg/3VfVw/XXXleJOfc48Ph9uJweXC4vGzefohN2w4hSRIWc1F/5Ly8tIQZjY0UGI08tXz5KOxZ7sxtasJCPW1spoRaJDIv0G5jMwWYufQITccZbtSr7TDR3GbjuJm5m8I/8b6dmfWFnDg5MlW/ereXZz90ct0plcwZFyle6w2E2XCwh0BI5m8rO7gh3EnRN55JuL5l/3k+5fYe0JyT8RgPVeqY1B4Ci55WKVIwuMACYQF/fqODc2dZ+PMNjUw95/SM152KH105nl+80MxPrxrPbY/u49Z6mfMqI9sNHy4gDQvwheAtB+wrkej1hflYHRRqI6I2VaHooTY3//uPt3noF9cwob6M0064AZfXi8Vs5pE7PsbPdgraegTj9RomCcGFYQExjiZRMf7L3QKDBh6eHiK0YpOiPO6oCG+SBWs02Vz6xj6dDldem1SpZE/osJ2lytggGAph0Ku35+HE29XFuq1bufGqq5IuEwgE0R8OGmm1mv4On8Q1IIp2B3W6vDjc3v9v796jo6zPRY9/35kJyeSeyf0KSSAEEhICIVzlXkAsoljr6batolbr7vbUU3e7jrtq7Vpe2lrZ1R5blSpFTndV8FIpohwQud9CwiUECCH3ZJLJTDK5TiZzO38EskG5BAnzJszzWcvFchhmnpnfet953t/7+z0P5VV1WNs7MVkGXvJ2KPq/f36K2x/9VyxUEsW1daPupJl2jLz2zDP91WXExeQIv0Fs9l4CA67/lsur/89IsmEEDa12fr+5gfImG7UtvcRZrWwFitrgbBdkBMOdkTApTbls8j0QK93bOHvrsku2q7+cBIuLskQd67QK27QKi1weDrcrFETAP3827pIVWy5noLPfvVuOcbzKTYYf5FdW8cexHl466+Hls6BV/vs/nQIBkfEUaMxE6hyc7fLwgyJ4MxciR3w9CT+/tt7j8fDi6i+5787JjEyMAGUeGgUiz20iuX/VR3zv5RWc2eqgSoESjcLzfhr+0OvuX8JTt9VBI7BnhIZPZmoI0CrXvIlyvsvDJq1C5uULtwxbLrcbnU5OzEOBuaVtSHZd9EVuj+e61tyKq9t+4AAvvPEGC6ZNIy3p8mVQW9o6iAy/+p2IC7uDjr5guUZ5TQ1//eTdQYlZDcnx8USSThMniSAFLQPrEeDBQwPHCSaaGXl5NzjK4UsS8Bugxz44bWsdzr6sy9jm4N7Xy7h3ejRPLktixcsnKOmASWHw6CiF7BAI0A5e98P0zRvh3DrkgSTimXUOjuX60+b2sKrXzat+GuZHwSOjNIy4huT7qz44ZKbaYueOSZEkHSnrf9zl8bCmBv7ZBGvz+j53RrDC6lzlopraSQv9+r+PM5V1NG54iYJMDW/VeHi8xMOfcyBYd+kk/IN6A+bWLr6/LA+US98+83/iQ/RblzHOA+NcHqoV+EKrkO32EOsBPXBaozDe7cG83dn3vV6jSODnDjfWm2wZSo+912eaWwwHTc0txEpH0iGhvaOLMCnNOeicLhfl1dWs+fBDTlZU8JsnnmByVtYV/425pc3nS3NueOcZ5v/wQUyUEc+Vv6/zrNRho5V3V62SKldXIAn4DVBrNJEcH33dr+On0/Dlk9mcNNpIifQnIXwEvVuOsXX6paurDGaJuvNLIGYvDrxqEq5zw/c2djJncSBbNQqdQFyFi6m18ErrUWbf07ex68LZ5aLSBioO7uc7U6Iu+7qvb29kbrCThw42kxcG2SEKVoeHL8wQ6w9rJir9s9jw9YY2F34f9U1m0u79JXUPPsgioE6r8MgxDWvzQKcouDweaj45imlCGhUmO69vL2HNb/8FP7+FA/qeAO52efgPPw1BWgUbMMENQXjQnHveN5XlATw31y7MxuYWaUE/hDSZWwdlyZy4fs1SAeUbc7lcFJWWUtvYiMfjwePxUN/UxLHTpzl59ixxUVHMmzaNZx97bECbAi3WNlKTh1d788EWHhrKYz/8Hq++8zeiSMOPK9c4d+OikRIiSCEzLc1LUQ5PkoDfALUNpq81DfgmlAnPEg5Mv+Ax/wnX/bI3hELfbHnX0iCqFXjh3Lq50UH/PbvsdntY9/p6PjhkRlEUWrucFyXg56uD2N0eOp1gt3n4UZbCT1Lhn41gyl6GXq/nt1OmMD49/WsXIelPXD4+o8nCzMnZ+J1LmJ+Zq+Wewx5OdsBOi5v3GiBUBwmnz5KUGsFvvzuSUUkrBvTZzyfX6cA/LBaiwsPpstnYfuAAW/bsGXDnr8u97s2orwW9JOBDhdSdHjpMLVa5OP0GjpeV8eTLLxMUGEhmWlpfF1FFIcZg4MHvfIfsMWMIDb62zo6W1nbyczJvUMTDx/duu40/vbOeRkpJZvIVn2vhLA56+K/VT3spuuFLEvAboLG5hdk+Ws5rmctDksfDazoNP3G66dkJLPSj5pOj1GSm8lGhhRfuHsn4hEBm/fooLZ8e7V8GAmB1ePjJcQ/GHgjSQpiuryTSD1Zd3+y+0+XC79ympvTNG7G/vII742HVWQ9GO3xSoBDudz6ONvyXr/lG7xMb2VdWLzQ4mOULFrB8wbVvavUFRpOFCZkyOzJUuNxutFrZhDkUmFus5IyVY2OgPB4P6z/7jD+/+y5PP/oo86cNTvdGgC5bz6Ds5RruAvz9+dVPH+apV14hitHoufTFupNemjjF/SvuID76+lcB3OwkAR9kHo8Hp8t9UV3Q4W4gy1AA6g1a7ncr6EYoPOZwk+fpa/rz7A4XVSMU7IUVPL0iheykIHq3HMNPA6/vcjHD7SHl3AqLl3UKGR74jcuDG1AUv+teWtNt6/na7Ub/Jz7krpfuxNgDS/UXJt+Du5RHXFqXrYfgwOHbrvlm4pC250NKR6eN4CA5Nr6qx26n1+EgODAQjUaDx+Ohxmhk9fvvc7qykr+++CIjEwZ3uYjC9TXTu5ksnTOH519Zi5HjpDHrks8xcQpQWLliYHePfZ2cdQeZtb2T8NBru801FJ1f13wtGgxauvR9s2h/1WlYA7QrcI/Tw9vvfoBOq+0/mflluRnT8jTmY8f5lZ+GhS4P3QrUKAr/5nSjAFoGJxmubzKTGPf1teYhP/+IJ6/71cW1crvdUuVhCDHJmuMhR5K+ixWXlvKLl17CZrdj6+khKLCv1lSQXs+cKVN453e/G/RGLw6nU6o0XUCj0fCHX/8vHvnVr+jARAgX9znppQszZ/n3B1de81IfXyUJ+CCrNTaTMggNeNR0qeT7arPgK93bQLOAKeW9ODXQGqxhyowAYj0w/hJrmTUaDW89/zwA+25dxie6vpTseYeb86fRwVoDXd9oJjU5flBeS1w/c2v7uVq6YihoMrcQFyVrjocCu72XESMGVurNl/x90yb+ZdkyVq5YgdPlorOrC7fbjeFcWdgbocXagSHctyugfNXU3FxCiMXIcYKZf9FEipET+KHnu0uWqBjh8CKL/gZZbYOJpEGogKKWK818z1586Sb1K93bLvpT54bodjdVn3VfMvn+qumbN/KQ08NDTg/nr5sHcwNi34Y/aXk+VMh4DC1N5lZioyLUDkMAzS1tRMvF6deMS0/H3NoK9HWrDA8NvaHJN/RtTPb1EoSXsuaV/8CGlVZq+h/rphUrtTz383/Fz08uIAdKEvBBZrG2E3kTXzV/NQk/n3Rf6v+/+ndXcmHCPdjVPxxOl3SVG0IkAR9aWqztGMJD1A5DAM0tshzoUhJiYqhvavLqe1pa24m6iX/Lv6nRI0diYBSNnMCNq7/pTiAGvjVjhtrhDSuSlQwil9uNVnPzbNq4XCJ8tYa015J4D+T9rkd3jx39IDRFEoPH0tpGlMwsDRlujweNtKEfEkwWK3lSj/0in+7YwYtvvsnj993n1fe1tLYxKWuMV99zuPj7W0+z5MGHMVNOAKF00cyaF164aXIfb5Gz7iBqam4h9iZZS3mz1KBuaDSTcIkNmEI9kvANHXZ7L/6y5njIsLS2YZCL04t8efAg/3bvvdy1aJFX37ez20ZQYIBX33O4iI2M5KG7V9DEaRo4RigJ5I0fr3ZYw86wmwGvNRrVDuGyjp+qICRIT3lNzdWfPETVKpD8+mvD+jNcqLDkFImxUTfN5xnubD12Ors7ZTyGiEZTCy63Q8ZjiGiymKmqr1c7jCEl2mDgWFkZk7Ozvfq+5tYWztbWXtdrDOV85Xrdv2IFa9Z/gp0u3nvtt2qHMywpHs/w6HFtamnhzp/8hC6bTe1QhBBCCCGuKkiv56PXXiPGcHPcHb/QifJyOru6mJrrm40Hr9ewScChLwlv7+xUOwwhhBBCiKsKDQ6+KZNvcf2GVQIuhBBCCCHEcCc7oYQQQgghhPAiScCFEEIIIYTwIknAhRBCCCGE8CJJwIUQQgghhPAiScCFEMKHyL77oUPGYmjweDwyFsLrJAG/RrVGI8dOn8bhcADgdrtxuVwqR+Xbfrt6NfuOHMHW09P/mJxQ1WNsbmbNhx/S2Nx80eNut1vGRAWFJSXsO3IE57nz1Pl20W63W82wfNb+o0cxt7YCXNS6W8bDu1wuF+XV1UDfOJwfC/ntEN4y7Dphqq2otJTPdu1ibkEBc6dOJTYyUu2QfJq9txdjczP/529/Iyk2lul5ecyaNImoiAi1Q/NZ5tZW1n/2GdsPHCBr9Ghuyc9nyoQJ+OnkdKOGA0eP8vdNm5iQkUFBTg4z8vIYm5qKRiPzL2r43erVdNlsTM7OZmZeHlNycogxGGQ8vKyusZG7H3+ccenpTM3JYfrEieSMHUuAv7/aoQkfIXXAr1FdYyO7i4rYffgwJWVljE1LY+ns2UyZMIGEmBi1w/NZVfX17Ckq4tDx47R3dpI9ZgyLZs1i7KhR+Pn5qR2eTzp0/Dh7ioo4XVmJoihMz8tjdn4+yXFxkmx4WYvVyp7iYgpLSmg0mzGEhTG3oIDJWVlysaqC0vJy9h05wsmKCmw9PaQlJTF7yhTGpqYSGhysdng+o8duZ09REUWlpdQ3NaHT6cjJyGBqbi4pCQnoJRkXN5Ak4NehvqmJHYcOUWs0EhIcTFZ6OnMKCtQOy2d4PJ6LbhsqioLD4eB4WRkfbNlCdUMDqUlJfPfWW5mQkaFytL7hwjE5z9rezu7Dh9m8axfdNhvj0tO57447iI2KUilK3+VwOqlvamLL7t3sKS5G7+9PfnY2991xh1yoqqC9s5PTlZV8umMHZdXVRIWHs3DGDJbNm6d2aD6l1+HAZLFQeOIE2/btw9reTmJsLN9dsoRJWVlqhyduUnJP+Bp02WyUlpcTERpKeGgo3TYb0QYDHV1dNJhMbN+/n1V//Sv/+NOf1A7VJyiKwtqPP8bW00NkeDg1DQ1UNTQQERrK6JEj0Wq1bNy+nfSUFEnAvURRFNZ98gkhQUH09vZSUVtLk8VCclwck7OyKD55kr9v2sSKb31LEnAvaO/sZPfhw+gDAjA2N1NVX093Tw8jExKYlpvLjkOH+Mv69Tx0991qh+oTjM3NGE0mbHY7FXV11Dc2omg0pKekEBIUxCdffIGtp0cScC9oMpvpsdupN5k4W1tLs8VCcGAgM/PyOFVRwT+++ILMtDRJwMUNIzPg12Dr3r08/eqrAERFRJA7dizhoaG0tLVRWVuLTqcjMy2NX/74xypH6jsef+EF9hYXMzU3l0UzZxIXFUVdYyOt7e1ERUSQHB9PenKy3Nb1kvbOTu567DFsdjtL58xhyoQJjNDpqDEacbndJMbGkhwXR2Zamtqh+oTCkhJ+9PTTJMXGcvuCBaQlJdFls9FgMhEUGMiohARS4uMZmZiodqg+4fV33+WN995jclYWC6dPJyIsDFNLC20dHcQYDKSnpJASH0+0waB2qDe9h556isMnTnDb3LlMzMxEo9HQYDLhdrtJiY9nzKhRjEpMJEivVztUcZOSBPwanK6s5IMtW+jo6iI2MpIxo0YxLTeXyPBwoO/2rtPpRB8QoG6gPqTWaGRvcTEfb92Kw+lk8axZLF+4kBj5AVOFw+nkRHk5W/fuZdu+fcRGRXHnwoUsueUW/EeMUDs8n9Pe2cm+I0f4dMcOTpSXMzEzk7uXLGFqbq7aofmk6oYGvti/n807d9LR1cX8adNYsWgR6cnJaofmcw4cPcrWffv48uBBDGFh3D5/PkvnzCEiNFTt0ISPkAT8G6hvamLLnj0cLysjMCCAhTNmMGn8eJllVdnxsjJ2Hz5MR1cXGecujuKio9UOy6d9sX8/R0+dQlEUJmRkMCkrS37gvOSr6/FNLS3sPHSIyro6QoODyRs3jqwxY2SGTyXHy8o4eOwYFquV+JgYJo0fT3pyslTh8LK2jg4KS0o4UV6O0+kkLTmZvHHjSIiJkX0R4oaSBPwa2Hp6aO/qIiQwkEC9HovVyj+2baOwpISEmBgWz5pFfnb21zahiRuj5MwZTlVUEB0RQWJcHIqicLqigr1HjrC3qIjunh6eWLmSu5csUTtUn1F88iTW9nbioqKIioigrbOTIydPsvvwYQpLSvDT6fjNE0/IDKyXHC8rQ1EU4qOj0fv7U2M0cuDYMXYeOkTJmTPERkXxp2eeISkuTu1QfUJ5TQ0hgYHERkXhcDgoOXOGvcXF7Dh0iIq6OnIyMvjzs8/K3aIbzOF00tbRQXhoKDqtll6Hg0PHj7OrsJA9RUUYzWaW3HILz/30p2qHKm5isglzgIpLS3nxzTcZn56OzW7H3NqKVqMhMz2dkYmJ7Dh4kG3797N97Vq1Q/UZ+44c4eTZszSYTFQ3NBAVHk7WmDHER0fzrZkz+XzXLrpsNrXD9Cmf7tiBsbmZ8upqLFYrqUlJjEtPJy05mbCQELbs2SMlCL3E6XLxzscf09rezqmKCpwuF+PT0/s3JUeEhbGvuJigwEC1Q/UJppYW/rB2La3t7ZytqUEfEED2mDEkx8UxLTeXiLAw6hobJfn2grKqKv64bh0WqxVjczOG8HDGp6cTYzAwKz+fohMnaLZY1A5T3ORkBnyAWtra2LRjBzqNBp1OR2hwcH/1E0VRCA8JISEmhgXTp6sdqs/Y8Pnn6HQ6Fs+ciT4ggPbOTkwWC06Xi8jwcKINhkuWxRM3zlsbNpCalERBTg6BAQE0ms1Y29vRaDTERkXJ8hMvsvf28sZ77zFlwgQyRo1Cq9HQaDZjs9sJDAggMTaWYEm+vabBZOK9Tz/llvx8YiMjcbvdWKxWXG434SEhjExMZIQsefCKohMn2HX4MNNycwkKDMThdNLZ1YWfnx/RBgNpSUnyuyFuOJkBH4CSM2fYU1RERGgoC6ZP7990KdThcrl4ctUqJmdl0WWzUWM09jewuHAdviTf3mOz2/njunWkxMdjsliw9/YSHBhIQkyMNKhSQWt7Ox9v3YohLAxLayuh2dn46XSEywWQKprMZg4cPYohPBx7by/J8fEAUn1GBfVNTZhaWggNDiYsJOSSFZlkXlJ4g9wLHoBn//hHskaPZoSfH8+//jqd3d0AuN1uXC6XHKxeZmlro95k4p6lSwF4+e23gb7E/EKSfHtPRW0t1Q0N/I/bbqO8pobX330XQI4PlRSWlHC2tpZl8+axbf9+3t+8GZDxUMvG7dupMRqZnZ/P2o8+Yvfhw4CMhxrefP99jM3NZI8Zw6o1ayivqQEuHgv57RDeIDPgV+F2uxmVmEiDyURIUBAnzpzpv20ra1nVEazXkzduHK+uW4fb7eaW/Hygb6wURZFxUUFkWBiJsbH8c/t2tFotY0aOBMBD37gAaLVaFSP0LVHh4aQmJmJsbsbpchETGQn0JRaSXHhfZHg4QXo9Oq2WTput/07d+WNDo9HIuHhJgL8/GedqfNc1NRF8rgqQ2+MBt1vGQniNrAEfgCazmS8PHqTX4eiv/e1wOtFqNJLsqaSto4PtBw7QZbMxfeJE0qSOrqo8Hg9nqqt5a8MGcjMzWb5ggZS3U9myRx9F7+/PU48+Stbo0XIBpCJbTw+vvPMOjWYz9y5bxuSsLPntUEljczO/fu01ggIDuWvRIqZPnKh2SMJHyQz4AMRGRXHP0qV0dHX136Ly08lXp6Yao5GK2lo8Hg+/eOklAEaPHMmMvDxunz9f5eh8j6IolJaXoygKx06fJiQoiGXz5vHZrl0UnzzJ1Jwc5hYUSNLhJQ6nk7rGRu6/806CAgP7k2+Xy9U/Cy6zfF6kKMTHxPCD5ctJjI2l1mjk7Q8/pL2jg6wxY5hbUCCTCF6UnpLCvz/wANBXnea/Nm6ks7ub7DFjmDV5MlERESpHKHyBZJEDUFVfz9qPPqKntxen09m/iWZyVhazJk+Wnete1mK18uIbb3DP0qUU5OSg1+tJiI6m1+Fg/9GjNJnN3L9ihVwkeVGN0cir69bxs/vvJzU5mc937eJ/PvccI/z8iI+O5i/r1xNtMDAhI0PtUH3C6cpKYiMjmZiZyf/+/e+57447+Pa8eTILrpLi0lL+sW0b991xB2eqqnj+jTcYm5pKRmoqR0+dorKujp+tXClVgrygsKSEg8eOAX3HySvvvENbZycp8fF8tHUrpysreeKBB9DJsSJuMJmOGoBnXn2VQL2e3MxMZk+ZwsxJkwD4fPdu3tqwAVtPj8oR+pbjZWW4PR6WL1hAfHQ00ydO5MuDB/nurbey5JZb+PLQIYpLS9UO06ecrqwkJjKSb8+bR9bo0cwpKMDucPCLH/2IJx54gDkFBbz9wQdqh+kzSsvLGZuaypyCAp57/HE+3bmTZT/+MS+//Ta7Cgupqq+nx25XO0yf0XquORX0VdUKCw7myYcf5pF77uH3v/gFAf7+/GX9epWj9A0VdXX9e1R2FRai1Wp57emnefFnP+PJhx+mrKqKj7duVTlK4QtkivAqyqurabFa+fmDD/Y/dr5+6/Gysv6Zve8sXqxilL4l2mBghJ8ff9u4kZyxY/l461aCg4IAmJ2fT2NzM+9v3kxBTo7KkfqOjJEjCQsOZtWaNUwYO5YNn3/OpPHjiTEYAAjU63E4nSpH6TsKS0pIOVfqbmxqKq8+9RR7i4vZd+QIm3bsoMtm49tz57J41iyVI/UN+VlZ7C0q4t1NmxiXnk6j2Uy3zUagXo+fnx+Kosjx4SVNZjNdNhtdNhvdPT3MLSggPDQUh9NJZloa6SkpNJhMaocpfIAk4FcRHhpKWnIyv3/7bb6zeDFxUVEE+PsTbTAwf9o0ggMD+cPatZKAe9H40aO5Z+lS9hQV8cX+/YQEBfHQ3XcD0GSxcPDYMdJSUlSO0reMTEzknqVLeW/zZposFn64fDmbd+1izYcfArCnqIilc+aoHKXvGJWYyPS8PKBv3bdOq2V2fj7j09OprKuj5MwZqc/uRbFRUdy1aBG/Wb0a28aNtLa3U1RaSsaoUdQ3NQFw/4oVKkfpG2ZMmsTmnTtZ+eSTnKmu5vvLlvVfDFmsVuqbmrhr0SK1wxQ+QKqgDEBhSQl/27iRsOBgUhISiI2MRKfT0dzSwonycgxhYRfNkAvvaG5pocduJykurn9DWfHJk+wpKmLZvHmMTEhQOULfVlZVxeadO6msq2PW5MncNmcO+oAAtcPyCb0OBzqtVja9DhEXNgU7U1XF4dJSTBYLLVYrgXo9P1y+nLjoaJWj9D2d3d3Ye3sJDwlBq9Xy9gcf0Nndzfdvvx1DWJja4YmbnCTgA3S6spJdhYWUnj2Lw+kkMCAAa3s786ZO5dvz5klLZyEuwWa3o9BXe1cMDdJsZGhwn6s5LYaO8upq0pKTZVyEV0gCfgUej4e2jo6vtW+2trdjtloZnZKCsbmZeJm5EEIIIYQQAyQJ+BUUl5bywC9/ybj0dNKSkpiUlUVuZiajEhLQarV0dndz2yOPsGPdOrVDFUIIIYQQw4RswryCts5OpmRnk5OZSYPJxOr336fJYkHv709mWhoj/Pz6Kw0IIYQQQggxEJKAX0F6cjLfX76c2fn5Fz1efPIkZ6qq+M+1a/nB7berFJ0QQgghhBiOJAG/guT4eJLi4nC73f2PaTQa8saNI2/cODZ8/jljU1NVjFAIIYQQQgw3koBfhaIol60WcOfChUzNzfVyREIIIYQQYjiTTZhCCCGEEEJ4kRS7FEIIIYQQwoskARdCCCGEEMKLJAEXQgghhBDCiyQBF0IIIYQQwoskARdCCCGEEMKLJAEXQgghhBDCiyQBF0IIIYQQwoskARdCCCGEEMKL/j8TVHTTxeCAXwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 864x672 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# map\n",
    "plt.figure(figsize=(9, 7))\n",
    "ax = plt.axes(projection=cplt.projection_lambert_conformal)\n",
    "data_d.isel(time=90, height=0)[var].plot.contourf(\n",
    "    ax=ax,\n",
    "    robust=True,\n",
    "    cmap=\"Spectral_r\",\n",
    "    x=\"x\",\n",
    "    y=\"y\",\n",
    "    levels=10,\n",
    "    transform=cplt.projection_lambert_conformal,\n",
    "    cbar_kwargs={\n",
    "        \"label\": (\n",
    "            data_d[var].attrs[\"long_name\"]\n",
    "            + \" [\"\n",
    "            + data_d[var].attrs[\"units\"]\n",
    "            + \"]\"\n",
    "        )\n",
    "    },\n",
    ")\n",
    "ax.gridlines(\n",
    "    draw_labels=dict(bottom=\"x\", left=\"y\"),\n",
    "    color=\"lightslategrey\",\n",
    "    linewidth=0.5,\n",
    "    x_inline=False,\n",
    "    y_inline=False,\n",
    ")\n",
    "ax.coastlines(resolution=\"10m\", color=\"darkslategrey\", linewidth=0.75)\n",
    "ax.set_title(str(data_d.isel(time=90, height=0)[\"time\"].values))\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Total precipitation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "var = \"61_105_0_4\"\n",
    "file_list = list(\n",
    "    chain(\n",
    "        *list(\n",
    "            glob.glob(os.path.join(DATA_DIR, f\"{var}_FC3hr\", e))\n",
    "            for e in [f\"*{i}*{var}_FC3hr*\" for i in range(2003, 2006)]\n",
    "        )\n",
    "    )\n",
    ")\n",
    "data = xr.open_mfdataset(file_list, chunks=\"auto\", decode_coords=\"all\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (time: 8768, x: 158, y: 166, height: 1)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31T21:00:00\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "  * height             (height) float64 0.0\n",
       "    spatial_ref        int64 0\n",
       "    Lambert_Conformal  int64 0\n",
       "Data variables:\n",
       "    tp                 (time, height, y, x) float32 dask.array&lt;chunksize=(248, 1, 166, 158), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 18:03:40 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-76cf37e0-d2fc-4459-8294-a524c1292aae' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-76cf37e0-d2fc-4459-8294-a524c1292aae' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 8768</li><li><span class='xr-has-index'>x</span>: 158</li><li><span class='xr-has-index'>y</span>: 166</li><li><span class='xr-has-index'>height</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-84572969-724d-47f1-9a7d-309ab1ffa821' class='xr-section-summary-in' type='checkbox'  checked><label for='section-84572969-724d-47f1-9a7d-309ab1ffa821' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2003-01-01 ... 2005-12-31T21:00:00</div><input id='attrs-f13ab043-12c0-4dc8-aec0-3f943fb1dab8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f13ab043-12c0-4dc8-aec0-3f943fb1dab8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ecd0423-5be4-47a7-a439-da25c61fd037' class='xr-var-data-in' type='checkbox'><label for='data-5ecd0423-5be4-47a7-a439-da25c61fd037' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2003-01-01T00:00:00.000000000&#x27;, &#x27;2003-01-01T03:00:00.000000000&#x27;,\n",
       "       &#x27;2003-01-01T06:00:00.000000000&#x27;, ..., &#x27;2005-12-31T15:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-31T18:00:00.000000000&#x27;, &#x27;2005-12-31T21:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.15e+05 4.175e+05 ... 8.075e+05</div><input id='attrs-41a2bd6c-6ce0-4350-a3cb-f57c539b818d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-41a2bd6c-6ce0-4350-a3cb-f57c539b818d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c4bcb47d-4b6f-4469-b31c-8fd451022694' class='xr-var-data-in' type='checkbox'><label for='data-c4bcb47d-4b6f-4469-b31c-8fd451022694' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([415000., 417500., 420000., 422500., 425000., 427500., 430000., 432500.,\n",
       "       435000., 437500., 440000., 442500., 445000., 447500., 450000., 452500.,\n",
       "       455000., 457500., 460000., 462500., 465000., 467500., 470000., 472500.,\n",
       "       475000., 477500., 480000., 482500., 485000., 487500., 490000., 492500.,\n",
       "       495000., 497500., 500000., 502500., 505000., 507500., 510000., 512500.,\n",
       "       515000., 517500., 520000., 522500., 525000., 527500., 530000., 532500.,\n",
       "       535000., 537500., 540000., 542500., 545000., 547500., 550000., 552500.,\n",
       "       555000., 557500., 560000., 562500., 565000., 567500., 570000., 572500.,\n",
       "       575000., 577500., 580000., 582500., 585000., 587500., 590000., 592500.,\n",
       "       595000., 597500., 600000., 602500., 605000., 607500., 610000., 612500.,\n",
       "       615000., 617500., 620000., 622500., 625000., 627500., 630000., 632500.,\n",
       "       635000., 637500., 640000., 642500., 645000., 647500., 650000., 652500.,\n",
       "       655000., 657500., 660000., 662500., 665000., 667500., 670000., 672500.,\n",
       "       675000., 677500., 680000., 682500., 685000., 687500., 690000., 692500.,\n",
       "       695000., 697500., 700000., 702500., 705000., 707500., 710000., 712500.,\n",
       "       715000., 717500., 720000., 722500., 725000., 727500., 730000., 732500.,\n",
       "       735000., 737500., 740000., 742500., 745000., 747500., 750000., 752500.,\n",
       "       755000., 757500., 760000., 762500., 765000., 767500., 770000., 772500.,\n",
       "       775000., 777500., 780000., 782500., 785000., 787500., 790000., 792500.,\n",
       "       795000., 797500., 800000., 802500., 805000., 807500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.075e+05 4.1e+05 ... 8.2e+05</div><input id='attrs-904106c3-e4ca-46da-9751-7fbe20d8ff33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-904106c3-e4ca-46da-9751-7fbe20d8ff33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6bb70c38-07f8-44a3-bad6-e39ebdee6b0d' class='xr-var-data-in' type='checkbox'><label for='data-6bb70c38-07f8-44a3-bad6-e39ebdee6b0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([407500., 410000., 412500., 415000., 417500., 420000., 422500., 425000.,\n",
       "       427500., 430000., 432500., 435000., 437500., 440000., 442500., 445000.,\n",
       "       447500., 450000., 452500., 455000., 457500., 460000., 462500., 465000.,\n",
       "       467500., 470000., 472500., 475000., 477500., 480000., 482500., 485000.,\n",
       "       487500., 490000., 492500., 495000., 497500., 500000., 502500., 505000.,\n",
       "       507500., 510000., 512500., 515000., 517500., 520000., 522500., 525000.,\n",
       "       527500., 530000., 532500., 535000., 537500., 540000., 542500., 545000.,\n",
       "       547500., 550000., 552500., 555000., 557500., 560000., 562500., 565000.,\n",
       "       567500., 570000., 572500., 575000., 577500., 580000., 582500., 585000.,\n",
       "       587500., 590000., 592500., 595000., 597500., 600000., 602500., 605000.,\n",
       "       607500., 610000., 612500., 615000., 617500., 620000., 622500., 625000.,\n",
       "       627500., 630000., 632500., 635000., 637500., 640000., 642500., 645000.,\n",
       "       647500., 650000., 652500., 655000., 657500., 660000., 662500., 665000.,\n",
       "       667500., 670000., 672500., 675000., 677500., 680000., 682500., 685000.,\n",
       "       687500., 690000., 692500., 695000., 697500., 700000., 702500., 705000.,\n",
       "       707500., 710000., 712500., 715000., 717500., 720000., 722500., 725000.,\n",
       "       727500., 730000., 732500., 735000., 737500., 740000., 742500., 745000.,\n",
       "       747500., 750000., 752500., 755000., 757500., 760000., 762500., 765000.,\n",
       "       767500., 770000., 772500., 775000., 777500., 780000., 782500., 785000.,\n",
       "       787500., 790000., 792500., 795000., 797500., 800000., 802500., 805000.,\n",
       "       807500., 810000., 812500., 815000., 817500., 820000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-8a8b055f-4a41-4e5b-b818-50f859451bfc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a8b055f-4a41-4e5b-b818-50f859451bfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71f30863-08b5-4bcf-b22c-a85de9536257' class='xr-var-data-in' type='checkbox'><label for='data-71f30863-08b5-4bcf-b22c-a85de9536257' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-35cfbbde-e2f0-4c63-8543-f3acb9a85b2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35cfbbde-e2f0-4c63-8543-f3acb9a85b2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-baad1347-380f-401b-ae25-65ad32f06aec' class='xr-var-data-in' type='checkbox'><label for='data-baad1347-380f-401b-ae25-65ad32f06aec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-0d8e6988-f96e-4e2e-ad19-46c99e64b054' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d8e6988-f96e-4e2e-ad19-46c99e64b054' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-686ad02f-d935-42e5-af06-c6c76a7d575c' class='xr-var-data-in' type='checkbox'><label for='data-686ad02f-d935-42e5-af06-c6c76a7d575c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-14cc3185-e855-48c2-a846-cd64c193ab2e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-14cc3185-e855-48c2-a846-cd64c193ab2e' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tp</span></div><div class='xr-var-dims'>(time, height, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(248, 1, 166, 158), meta=np.ndarray&gt;</div><input id='attrs-aff8d8f6-d2a6-43a1-a9ae-6702bdbb707b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aff8d8f6-d2a6-43a1-a9ae-6702bdbb707b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d39ba607-fe9d-4a89-9b72-fab1737e903a' class='xr-var-data-in' type='checkbox'><label for='data-d39ba607-fe9d-4a89-9b72-fab1737e903a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>233253061</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_units :</span></dt><dd>kg m**-2</dd><dt><span>long_name :</span></dt><dd>Total precipitation</dd><dt><span>units :</span></dt><dd>kg m**-2</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 877.25 MiB </td>\n",
       "                        <td> 24.81 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (8768, 1, 166, 158) </td>\n",
       "                        <td> (248, 1, 166, 158) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 36 chunks in 73 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-d4298f89-a6c2-47bb-944b-07870ee9764f' class='xr-section-summary-in' type='checkbox'  ><label for='section-d4298f89-a6c2-47bb-944b-07870ee9764f' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6f97a42a-5ff4-4a64-b5fc-fda4c261c694' class='xr-index-data-in' type='checkbox'/><label for='index-6f97a42a-5ff4-4a64-b5fc-fda4c261c694' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2003-01-01 00:00:00&#x27;, &#x27;2003-01-01 03:00:00&#x27;,\n",
       "               &#x27;2003-01-01 06:00:00&#x27;, &#x27;2003-01-01 09:00:00&#x27;,\n",
       "               &#x27;2003-01-01 12:00:00&#x27;, &#x27;2003-01-01 15:00:00&#x27;,\n",
       "               &#x27;2003-01-01 18:00:00&#x27;, &#x27;2003-01-01 21:00:00&#x27;,\n",
       "               &#x27;2003-01-02 00:00:00&#x27;, &#x27;2003-01-02 03:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-30 18:00:00&#x27;, &#x27;2005-12-30 21:00:00&#x27;,\n",
       "               &#x27;2005-12-31 00:00:00&#x27;, &#x27;2005-12-31 03:00:00&#x27;,\n",
       "               &#x27;2005-12-31 06:00:00&#x27;, &#x27;2005-12-31 09:00:00&#x27;,\n",
       "               &#x27;2005-12-31 12:00:00&#x27;, &#x27;2005-12-31 15:00:00&#x27;,\n",
       "               &#x27;2005-12-31 18:00:00&#x27;, &#x27;2005-12-31 21:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=8768, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dce1d977-7b3d-47d7-9690-1d810e676bcc' class='xr-index-data-in' type='checkbox'/><label for='index-dce1d977-7b3d-47d7-9690-1d810e676bcc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([415000.0, 417500.0, 420000.0, 422500.0, 425000.0, 427500.0,\n",
       "              430000.0, 432500.0, 435000.0, 437500.0,\n",
       "              ...\n",
       "              785000.0, 787500.0, 790000.0, 792500.0, 795000.0, 797500.0,\n",
       "              800000.0, 802500.0, 805000.0, 807500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=158))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-132a7ce4-4bee-40be-9776-9b5e217122cc' class='xr-index-data-in' type='checkbox'/><label for='index-132a7ce4-4bee-40be-9776-9b5e217122cc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([407500.0, 410000.0, 412500.0, 415000.0, 417500.0, 420000.0,\n",
       "              422500.0, 425000.0, 427500.0, 430000.0,\n",
       "              ...\n",
       "              797500.0, 800000.0, 802500.0, 805000.0, 807500.0, 810000.0,\n",
       "              812500.0, 815000.0, 817500.0, 820000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=166))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>height</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-eed18bc9-64cc-4c2e-9ab7-bedf95e52e70' class='xr-index-data-in' type='checkbox'/><label for='index-eed18bc9-64cc-4c2e-9ab7-bedf95e52e70' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([0.0], dtype=&#x27;float64&#x27;, name=&#x27;height&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-77134dae-c223-4a63-bb45-13962b6cd099' class='xr-section-summary-in' type='checkbox'  checked><label for='section-77134dae-c223-4a63-bb45-13962b6cd099' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Wed Mar 22 18:03:40 2023: cdo -s -f nc4c -shifttime,-3hour -copy -seltimestep,3/744/3 /run/media/nms/Elements/MERA/grib/61_105_0_4_FC3hr/temp/MERA_PRODYEAR_2003_01_61_105_0_4_FC3hr /run/media/nms/Elements/MERA/grib/61_105_0_4_FC3hr/temp/MERA_PRODYEAR_2003_01_61_105_0_4_FC3hr.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (time: 8768, x: 158, y: 166, height: 1)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31T21:00:00\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "  * height             (height) float64 0.0\n",
       "    spatial_ref        int64 0\n",
       "    Lambert_Conformal  int64 0\n",
       "Data variables:\n",
       "    tp                 (time, height, y, x) float32 dask.array<chunksize=(248, 1, 166, 158), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 18:03:40 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (x: 158, y: 166, height: 1, time: 1096)\n",
       "Coordinates:\n",
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       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    tp                 (time, height, y, x) float32 dask.array&lt;chunksize=(1, 1, 166, 158), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 18:03:40 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-3734f7a1-ca85-4bd6-a9e6-7bbd32623301' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3734f7a1-ca85-4bd6-a9e6-7bbd32623301' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 158</li><li><span class='xr-has-index'>y</span>: 166</li><li><span class='xr-has-index'>height</span>: 1</li><li><span class='xr-has-index'>time</span>: 1096</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-eefdacfb-8a31-4080-9ee5-9f3397d36a30' class='xr-section-summary-in' type='checkbox'  checked><label for='section-eefdacfb-8a31-4080-9ee5-9f3397d36a30' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.15e+05 4.175e+05 ... 8.075e+05</div><input id='attrs-87e51913-d6e4-4392-a3a4-3f13a041d46f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-87e51913-d6e4-4392-a3a4-3f13a041d46f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-379a56c5-7430-48cf-b94f-912d1b4788ed' class='xr-var-data-in' type='checkbox'><label for='data-379a56c5-7430-48cf-b94f-912d1b4788ed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([415000., 417500., 420000., 422500., 425000., 427500., 430000., 432500.,\n",
       "       435000., 437500., 440000., 442500., 445000., 447500., 450000., 452500.,\n",
       "       455000., 457500., 460000., 462500., 465000., 467500., 470000., 472500.,\n",
       "       475000., 477500., 480000., 482500., 485000., 487500., 490000., 492500.,\n",
       "       495000., 497500., 500000., 502500., 505000., 507500., 510000., 512500.,\n",
       "       515000., 517500., 520000., 522500., 525000., 527500., 530000., 532500.,\n",
       "       535000., 537500., 540000., 542500., 545000., 547500., 550000., 552500.,\n",
       "       555000., 557500., 560000., 562500., 565000., 567500., 570000., 572500.,\n",
       "       575000., 577500., 580000., 582500., 585000., 587500., 590000., 592500.,\n",
       "       595000., 597500., 600000., 602500., 605000., 607500., 610000., 612500.,\n",
       "       615000., 617500., 620000., 622500., 625000., 627500., 630000., 632500.,\n",
       "       635000., 637500., 640000., 642500., 645000., 647500., 650000., 652500.,\n",
       "       655000., 657500., 660000., 662500., 665000., 667500., 670000., 672500.,\n",
       "       675000., 677500., 680000., 682500., 685000., 687500., 690000., 692500.,\n",
       "       695000., 697500., 700000., 702500., 705000., 707500., 710000., 712500.,\n",
       "       715000., 717500., 720000., 722500., 725000., 727500., 730000., 732500.,\n",
       "       735000., 737500., 740000., 742500., 745000., 747500., 750000., 752500.,\n",
       "       755000., 757500., 760000., 762500., 765000., 767500., 770000., 772500.,\n",
       "       775000., 777500., 780000., 782500., 785000., 787500., 790000., 792500.,\n",
       "       795000., 797500., 800000., 802500., 805000., 807500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.075e+05 4.1e+05 ... 8.2e+05</div><input id='attrs-38eec926-71fe-44e6-bb8c-36b7352f396c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-38eec926-71fe-44e6-bb8c-36b7352f396c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-730cdb96-9625-4565-be4d-3001088beb41' class='xr-var-data-in' type='checkbox'><label for='data-730cdb96-9625-4565-be4d-3001088beb41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([407500., 410000., 412500., 415000., 417500., 420000., 422500., 425000.,\n",
       "       427500., 430000., 432500., 435000., 437500., 440000., 442500., 445000.,\n",
       "       447500., 450000., 452500., 455000., 457500., 460000., 462500., 465000.,\n",
       "       467500., 470000., 472500., 475000., 477500., 480000., 482500., 485000.,\n",
       "       487500., 490000., 492500., 495000., 497500., 500000., 502500., 505000.,\n",
       "       507500., 510000., 512500., 515000., 517500., 520000., 522500., 525000.,\n",
       "       527500., 530000., 532500., 535000., 537500., 540000., 542500., 545000.,\n",
       "       547500., 550000., 552500., 555000., 557500., 560000., 562500., 565000.,\n",
       "       567500., 570000., 572500., 575000., 577500., 580000., 582500., 585000.,\n",
       "       587500., 590000., 592500., 595000., 597500., 600000., 602500., 605000.,\n",
       "       607500., 610000., 612500., 615000., 617500., 620000., 622500., 625000.,\n",
       "       627500., 630000., 632500., 635000., 637500., 640000., 642500., 645000.,\n",
       "       647500., 650000., 652500., 655000., 657500., 660000., 662500., 665000.,\n",
       "       667500., 670000., 672500., 675000., 677500., 680000., 682500., 685000.,\n",
       "       687500., 690000., 692500., 695000., 697500., 700000., 702500., 705000.,\n",
       "       707500., 710000., 712500., 715000., 717500., 720000., 722500., 725000.,\n",
       "       727500., 730000., 732500., 735000., 737500., 740000., 742500., 745000.,\n",
       "       747500., 750000., 752500., 755000., 757500., 760000., 762500., 765000.,\n",
       "       767500., 770000., 772500., 775000., 777500., 780000., 782500., 785000.,\n",
       "       787500., 790000., 792500., 795000., 797500., 800000., 802500., 805000.,\n",
       "       807500., 810000., 812500., 815000., 817500., 820000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-6c0619e1-8b60-4d19-8896-20dad231de3c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c0619e1-8b60-4d19-8896-20dad231de3c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36b25931-ad7f-4e11-9a44-f3c1eee3f85a' class='xr-var-data-in' type='checkbox'><label for='data-36b25931-ad7f-4e11-9a44-f3c1eee3f85a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-0a77f883-c54e-48fc-9d43-ec054aba7bfe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a77f883-c54e-48fc-9d43-ec054aba7bfe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca322d63-8921-4cff-b5c9-4269fdcef9d4' class='xr-var-data-in' type='checkbox'><label for='data-ca322d63-8921-4cff-b5c9-4269fdcef9d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2003-01-01 ... 2005-12-31</div><input id='attrs-aa6f0b5e-f70e-48d6-acdb-940a3073c569' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa6f0b5e-f70e-48d6-acdb-940a3073c569' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-924167eb-b5cf-4ebb-95cf-5a80ef84c9b4' class='xr-var-data-in' type='checkbox'><label for='data-924167eb-b5cf-4ebb-95cf-5a80ef84c9b4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2003-01-01T00:00:00.000000000&#x27;, &#x27;2003-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-01-03T00:00:00.000000000&#x27;, ..., &#x27;2005-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-30T00:00:00.000000000&#x27;, &#x27;2005-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-a6bac0b5-ae54-40e3-953c-76e3670e414b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6bac0b5-ae54-40e3-953c-76e3670e414b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8db13801-9864-4569-bfbc-544f51d1c2dd' class='xr-var-data-in' type='checkbox'><label for='data-8db13801-9864-4569-bfbc-544f51d1c2dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-325a08f3-4016-4618-bab7-03261bb6c8df' class='xr-section-summary-in' type='checkbox'  checked><label for='section-325a08f3-4016-4618-bab7-03261bb6c8df' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tp</span></div><div class='xr-var-dims'>(time, height, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 166, 158), meta=np.ndarray&gt;</div><input id='attrs-dc2774ba-e97f-468c-99ec-73f5799e2a8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc2774ba-e97f-468c-99ec-73f5799e2a8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55a718c7-d6e3-4b92-8edb-4dd5acd9ff97' class='xr-var-data-in' type='checkbox'><label for='data-55a718c7-d6e3-4b92-8edb-4dd5acd9ff97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>233253061</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_units :</span></dt><dd>kg m**-2</dd><dt><span>long_name :</span></dt><dd>Total precipitation</dd><dt><span>units :</span></dt><dd>mm day⁻¹</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 109.66 MiB </td>\n",
       "                        <td> 102.45 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1096, 1, 166, 158) </td>\n",
       "                        <td> (1, 1, 166, 158) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1096 chunks in 6651 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"485\" height=\"105\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
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       "              430000.0, 432500.0, 435000.0, 437500.0,\n",
       "              ...\n",
       "              785000.0, 787500.0, 790000.0, 792500.0, 795000.0, 797500.0,\n",
       "              800000.0, 802500.0, 805000.0, 807500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=158))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c1cf7751-ebb2-427f-9d5a-bbfb0fa3b3f3' class='xr-index-data-in' type='checkbox'/><label for='index-c1cf7751-ebb2-427f-9d5a-bbfb0fa3b3f3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([407500.0, 410000.0, 412500.0, 415000.0, 417500.0, 420000.0,\n",
       "              422500.0, 425000.0, 427500.0, 430000.0,\n",
       "              ...\n",
       "              797500.0, 800000.0, 802500.0, 805000.0, 807500.0, 810000.0,\n",
       "              812500.0, 815000.0, 817500.0, 820000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=166))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>height</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2be10622-712b-4661-9ea2-b0f06be0f4ad' class='xr-index-data-in' type='checkbox'/><label for='index-2be10622-712b-4661-9ea2-b0f06be0f4ad' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([0.0], dtype=&#x27;float64&#x27;, name=&#x27;height&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a4bdb8e3-cef9-4cd6-beb9-28ce71204c80' class='xr-index-data-in' type='checkbox'/><label for='index-a4bdb8e3-cef9-4cd6-beb9-28ce71204c80' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2003-01-01&#x27;, &#x27;2003-01-02&#x27;, &#x27;2003-01-03&#x27;, &#x27;2003-01-04&#x27;,\n",
       "               &#x27;2003-01-05&#x27;, &#x27;2003-01-06&#x27;, &#x27;2003-01-07&#x27;, &#x27;2003-01-08&#x27;,\n",
       "               &#x27;2003-01-09&#x27;, &#x27;2003-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-22&#x27;, &#x27;2005-12-23&#x27;, &#x27;2005-12-24&#x27;, &#x27;2005-12-25&#x27;,\n",
       "               &#x27;2005-12-26&#x27;, &#x27;2005-12-27&#x27;, &#x27;2005-12-28&#x27;, &#x27;2005-12-29&#x27;,\n",
       "               &#x27;2005-12-30&#x27;, &#x27;2005-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1096, freq=&#x27;D&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-46e97533-7326-4ba0-a4e4-02f438f71f4c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-46e97533-7326-4ba0-a4e4-02f438f71f4c' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Wed Mar 22 18:03:40 2023: cdo -s -f nc4c -shifttime,-3hour -copy -seltimestep,3/744/3 /run/media/nms/Elements/MERA/grib/61_105_0_4_FC3hr/temp/MERA_PRODYEAR_2003_01_61_105_0_4_FC3hr /run/media/nms/Elements/MERA/grib/61_105_0_4_FC3hr/temp/MERA_PRODYEAR_2003_01_61_105_0_4_FC3hr.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (x: 158, y: 166, height: 1, time: 1096)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "  * height             (height) float64 0.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    tp                 (time, height, y, x) float32 dask.array<chunksize=(1, 1, 166, 158), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 18:03:40 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# resample to daily - take the sum\n",
    "var = \"tp\"\n",
    "data_attrs = data[var].attrs\n",
    "time_attrs = data[\"time\"].attrs\n",
    "data_crs = data.rio.crs\n",
    "data_d = data.resample(time=\"D\").sum()\n",
    "data_d[var].attrs = data_attrs\n",
    "data_d[\"time\"].attrs = time_attrs\n",
    "data_d[var].attrs[\"units\"] = \"mm day⁻¹\"\n",
    "data_d.rio.write_crs(data_crs, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# clip to Ireland's boundary to remove NaNs after summing\n",
    "data_d = data_d.rio.clip(\n",
    "    ie.buffer(1).to_crs(cplt.projection_lambert_conformal), all_touched=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
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       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (x: 158, y: 166, height: 1, time: 1096)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "  * height             (height) float64 0.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    tp                 (time, height, y, x) float32 dask.array&lt;chunksize=(1, 1, 166, 158), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 18:03:40 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-48741dc0-5715-4101-bc2c-894baad0c02a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-48741dc0-5715-4101-bc2c-894baad0c02a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 158</li><li><span class='xr-has-index'>y</span>: 166</li><li><span class='xr-has-index'>height</span>: 1</li><li><span class='xr-has-index'>time</span>: 1096</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f79a39f7-3e88-407f-b6c1-c68b77bfd3ea' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f79a39f7-3e88-407f-b6c1-c68b77bfd3ea' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.15e+05 4.175e+05 ... 8.075e+05</div><input id='attrs-6ef26a86-f5cb-4071-93c2-edded7287603' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ef26a86-f5cb-4071-93c2-edded7287603' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0672e9a-3d2e-43e0-922e-02c52af0de48' class='xr-var-data-in' type='checkbox'><label for='data-f0672e9a-3d2e-43e0-922e-02c52af0de48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([415000., 417500., 420000., 422500., 425000., 427500., 430000., 432500.,\n",
       "       435000., 437500., 440000., 442500., 445000., 447500., 450000., 452500.,\n",
       "       455000., 457500., 460000., 462500., 465000., 467500., 470000., 472500.,\n",
       "       475000., 477500., 480000., 482500., 485000., 487500., 490000., 492500.,\n",
       "       495000., 497500., 500000., 502500., 505000., 507500., 510000., 512500.,\n",
       "       515000., 517500., 520000., 522500., 525000., 527500., 530000., 532500.,\n",
       "       535000., 537500., 540000., 542500., 545000., 547500., 550000., 552500.,\n",
       "       555000., 557500., 560000., 562500., 565000., 567500., 570000., 572500.,\n",
       "       575000., 577500., 580000., 582500., 585000., 587500., 590000., 592500.,\n",
       "       595000., 597500., 600000., 602500., 605000., 607500., 610000., 612500.,\n",
       "       615000., 617500., 620000., 622500., 625000., 627500., 630000., 632500.,\n",
       "       635000., 637500., 640000., 642500., 645000., 647500., 650000., 652500.,\n",
       "       655000., 657500., 660000., 662500., 665000., 667500., 670000., 672500.,\n",
       "       675000., 677500., 680000., 682500., 685000., 687500., 690000., 692500.,\n",
       "       695000., 697500., 700000., 702500., 705000., 707500., 710000., 712500.,\n",
       "       715000., 717500., 720000., 722500., 725000., 727500., 730000., 732500.,\n",
       "       735000., 737500., 740000., 742500., 745000., 747500., 750000., 752500.,\n",
       "       755000., 757500., 760000., 762500., 765000., 767500., 770000., 772500.,\n",
       "       775000., 777500., 780000., 782500., 785000., 787500., 790000., 792500.,\n",
       "       795000., 797500., 800000., 802500., 805000., 807500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.075e+05 4.1e+05 ... 8.2e+05</div><input id='attrs-65afaea6-8344-4163-bc41-1ab6524b3e58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65afaea6-8344-4163-bc41-1ab6524b3e58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-715619ce-6cf8-4b63-957d-dc80ed965add' class='xr-var-data-in' type='checkbox'><label for='data-715619ce-6cf8-4b63-957d-dc80ed965add' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([407500., 410000., 412500., 415000., 417500., 420000., 422500., 425000.,\n",
       "       427500., 430000., 432500., 435000., 437500., 440000., 442500., 445000.,\n",
       "       447500., 450000., 452500., 455000., 457500., 460000., 462500., 465000.,\n",
       "       467500., 470000., 472500., 475000., 477500., 480000., 482500., 485000.,\n",
       "       487500., 490000., 492500., 495000., 497500., 500000., 502500., 505000.,\n",
       "       507500., 510000., 512500., 515000., 517500., 520000., 522500., 525000.,\n",
       "       527500., 530000., 532500., 535000., 537500., 540000., 542500., 545000.,\n",
       "       547500., 550000., 552500., 555000., 557500., 560000., 562500., 565000.,\n",
       "       567500., 570000., 572500., 575000., 577500., 580000., 582500., 585000.,\n",
       "       587500., 590000., 592500., 595000., 597500., 600000., 602500., 605000.,\n",
       "       607500., 610000., 612500., 615000., 617500., 620000., 622500., 625000.,\n",
       "       627500., 630000., 632500., 635000., 637500., 640000., 642500., 645000.,\n",
       "       647500., 650000., 652500., 655000., 657500., 660000., 662500., 665000.,\n",
       "       667500., 670000., 672500., 675000., 677500., 680000., 682500., 685000.,\n",
       "       687500., 690000., 692500., 695000., 697500., 700000., 702500., 705000.,\n",
       "       707500., 710000., 712500., 715000., 717500., 720000., 722500., 725000.,\n",
       "       727500., 730000., 732500., 735000., 737500., 740000., 742500., 745000.,\n",
       "       747500., 750000., 752500., 755000., 757500., 760000., 762500., 765000.,\n",
       "       767500., 770000., 772500., 775000., 777500., 780000., 782500., 785000.,\n",
       "       787500., 790000., 792500., 795000., 797500., 800000., 802500., 805000.,\n",
       "       807500., 810000., 812500., 815000., 817500., 820000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-bfd61c98-c01d-4be1-89a1-b70c18f9c5df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfd61c98-c01d-4be1-89a1-b70c18f9c5df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41e36395-1f19-4bdc-89a5-4ae5b9253c56' class='xr-var-data-in' type='checkbox'><label for='data-41e36395-1f19-4bdc-89a5-4ae5b9253c56' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-e5f11eb8-c57d-436b-b95a-6ba26f445608' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5f11eb8-c57d-436b-b95a-6ba26f445608' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2bac6f9f-f2d1-40bc-982a-c30ddf3ffb1a' class='xr-var-data-in' type='checkbox'><label for='data-2bac6f9f-f2d1-40bc-982a-c30ddf3ffb1a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2003-01-01 ... 2005-12-31</div><input id='attrs-8fac793a-d437-47b5-b895-6f9c1e5d4e0a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8fac793a-d437-47b5-b895-6f9c1e5d4e0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3fe4a17-14f9-47f8-9988-a784c2d6a28f' class='xr-var-data-in' type='checkbox'><label for='data-e3fe4a17-14f9-47f8-9988-a784c2d6a28f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2003-01-01T00:00:00.000000000&#x27;, &#x27;2003-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-01-03T00:00:00.000000000&#x27;, ..., &#x27;2005-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-30T00:00:00.000000000&#x27;, &#x27;2005-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-603bc746-2547-47c9-b5be-3309de87dc49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-603bc746-2547-47c9-b5be-3309de87dc49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4302a7e6-07aa-469c-95a6-43e0e18b382c' class='xr-var-data-in' type='checkbox'><label for='data-4302a7e6-07aa-469c-95a6-43e0e18b382c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f7fca77f-a89b-464a-8526-d4cfebf19405' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f7fca77f-a89b-464a-8526-d4cfebf19405' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tp</span></div><div class='xr-var-dims'>(time, height, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 166, 158), meta=np.ndarray&gt;</div><input id='attrs-3d96b552-1a5e-48e2-a23f-d6c8de08a291' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d96b552-1a5e-48e2-a23f-d6c8de08a291' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c24c0add-18d3-4ece-9342-bb94078b922d' class='xr-var-data-in' type='checkbox'><label for='data-c24c0add-18d3-4ece-9342-bb94078b922d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>233253061</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_units :</span></dt><dd>kg m**-2</dd><dt><span>long_name :</span></dt><dd>Total precipitation</dd><dt><span>units :</span></dt><dd>mm day⁻¹</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div 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       "    <tr>\n",
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       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 109.66 MiB </td>\n",
       "                        <td> 102.45 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1096, 1, 166, 158) </td>\n",
       "                        <td> (1, 1, 166, 158) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1096 chunks in 6653 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "              430000.0, 432500.0, 435000.0, 437500.0,\n",
       "              ...\n",
       "              785000.0, 787500.0, 790000.0, 792500.0, 795000.0, 797500.0,\n",
       "              800000.0, 802500.0, 805000.0, 807500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=158))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4da68601-dcbd-4250-a809-d41065b05d3c' class='xr-index-data-in' type='checkbox'/><label for='index-4da68601-dcbd-4250-a809-d41065b05d3c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([407500.0, 410000.0, 412500.0, 415000.0, 417500.0, 420000.0,\n",
       "              422500.0, 425000.0, 427500.0, 430000.0,\n",
       "              ...\n",
       "              797500.0, 800000.0, 802500.0, 805000.0, 807500.0, 810000.0,\n",
       "              812500.0, 815000.0, 817500.0, 820000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=166))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>height</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1e735158-64ed-42d5-bbfe-e4b5147c4693' class='xr-index-data-in' type='checkbox'/><label for='index-1e735158-64ed-42d5-bbfe-e4b5147c4693' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([0.0], dtype=&#x27;float64&#x27;, name=&#x27;height&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-00894eff-fe8c-4576-a791-6c015d03f649' class='xr-index-data-in' type='checkbox'/><label for='index-00894eff-fe8c-4576-a791-6c015d03f649' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2003-01-01&#x27;, &#x27;2003-01-02&#x27;, &#x27;2003-01-03&#x27;, &#x27;2003-01-04&#x27;,\n",
       "               &#x27;2003-01-05&#x27;, &#x27;2003-01-06&#x27;, &#x27;2003-01-07&#x27;, &#x27;2003-01-08&#x27;,\n",
       "               &#x27;2003-01-09&#x27;, &#x27;2003-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-22&#x27;, &#x27;2005-12-23&#x27;, &#x27;2005-12-24&#x27;, &#x27;2005-12-25&#x27;,\n",
       "               &#x27;2005-12-26&#x27;, &#x27;2005-12-27&#x27;, &#x27;2005-12-28&#x27;, &#x27;2005-12-29&#x27;,\n",
       "               &#x27;2005-12-30&#x27;, &#x27;2005-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1096, freq=&#x27;D&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a9c8c04d-ea67-4906-94cf-540d3e62e711' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a9c8c04d-ea67-4906-94cf-540d3e62e711' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Wed Mar 22 18:03:40 2023: cdo -s -f nc4c -shifttime,-3hour -copy -seltimestep,3/744/3 /run/media/nms/Elements/MERA/grib/61_105_0_4_FC3hr/temp/MERA_PRODYEAR_2003_01_61_105_0_4_FC3hr /run/media/nms/Elements/MERA/grib/61_105_0_4_FC3hr/temp/MERA_PRODYEAR_2003_01_61_105_0_4_FC3hr.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (x: 158, y: 166, height: 1, time: 1096)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "  * height             (height) float64 0.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    tp                 (time, height, y, x) float32 dask.array<chunksize=(1, 1, 166, 158), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 18:03:40 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract data for the nearest grid cell to the point\n",
    "data_tsd = data_d.sel({\"x\": XLON, \"y\": YLAT}, method=\"nearest\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "\n",
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       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
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       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
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       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
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       "\n",
       ".xr-dim-list:before {\n",
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       "\n",
       ".xr-dim-list:after {\n",
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       "\n",
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       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
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       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
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       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
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       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-index-preview {\n",
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       "\n",
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       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
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       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
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       "\n",
       ".xr-var-data > table {\n",
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       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (height: 1, time: 1096)\n",
       "Coordinates:\n",
       "    x                  float64 5.8e+05\n",
       "    y                  float64 4.725e+05\n",
       "  * height             (height) float64 0.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    tp                 (time, height) float32 dask.array&lt;chunksize=(1, 1), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 18:03:40 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-190ee9f4-73ef-42ba-90c6-6c8d63411067' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-190ee9f4-73ef-42ba-90c6-6c8d63411067' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>height</span>: 1</li><li><span class='xr-has-index'>time</span>: 1096</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-63adec11-6fe7-438d-a861-0f4b03d54d89' class='xr-section-summary-in' type='checkbox'  checked><label for='section-63adec11-6fe7-438d-a861-0f4b03d54d89' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.8e+05</div><input id='attrs-2fe682c1-5d12-4716-b27d-457b6a2059f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2fe682c1-5d12-4716-b27d-457b6a2059f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b8ccc13-9d5d-4caa-9d95-f018f591f8d3' class='xr-var-data-in' type='checkbox'><label for='data-4b8ccc13-9d5d-4caa-9d95-f018f591f8d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array(580000.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.725e+05</div><input id='attrs-1991ee03-7c98-43a4-83ae-aef17714612d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1991ee03-7c98-43a4-83ae-aef17714612d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a77ab106-8516-4e69-bb24-8c6ec1746aea' class='xr-var-data-in' type='checkbox'><label for='data-a77ab106-8516-4e69-bb24-8c6ec1746aea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array(472500.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-6d71faf0-98b1-4699-af21-5d427a328a0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d71faf0-98b1-4699-af21-5d427a328a0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7c6d030-67d6-4a99-923d-6091d840afac' class='xr-var-data-in' type='checkbox'><label for='data-c7c6d030-67d6-4a99-923d-6091d840afac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-510947e9-469e-44bc-89a5-70f26cc91700' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-510947e9-469e-44bc-89a5-70f26cc91700' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55f2509c-eafd-43a7-a21f-a5c199eb503d' class='xr-var-data-in' type='checkbox'><label for='data-55f2509c-eafd-43a7-a21f-a5c199eb503d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2003-01-01 ... 2005-12-31</div><input id='attrs-b19efd6f-9d5a-4a6f-8035-c104cd1800d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b19efd6f-9d5a-4a6f-8035-c104cd1800d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ddbfe081-0308-4589-a9de-bb631236f14f' class='xr-var-data-in' type='checkbox'><label for='data-ddbfe081-0308-4589-a9de-bb631236f14f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2003-01-01T00:00:00.000000000&#x27;, &#x27;2003-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-01-03T00:00:00.000000000&#x27;, ..., &#x27;2005-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-30T00:00:00.000000000&#x27;, &#x27;2005-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-b3429870-e25d-43f8-acbc-57fb616a3d5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3429870-e25d-43f8-acbc-57fb616a3d5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6eb5a3fa-f203-466b-a854-bc8f82c6aed2' class='xr-var-data-in' type='checkbox'><label for='data-6eb5a3fa-f203-466b-a854-bc8f82c6aed2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-437d126e-2e15-417e-ad23-5cfa4f5dec74' class='xr-section-summary-in' type='checkbox'  checked><label for='section-437d126e-2e15-417e-ad23-5cfa4f5dec74' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tp</span></div><div class='xr-var-dims'>(time, height)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1), meta=np.ndarray&gt;</div><input id='attrs-2d739a34-d0f9-46ff-bde3-e379c0e7bba3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d739a34-d0f9-46ff-bde3-e379c0e7bba3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2839691e-0dca-473d-bc2a-a0bf30c82bc4' class='xr-var-data-in' type='checkbox'><label for='data-2839691e-0dca-473d-bc2a-a0bf30c82bc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>233253061</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_units :</span></dt><dd>kg m**-2</dd><dt><span>long_name :</span></dt><dd>Total precipitation</dd><dt><span>units :</span></dt><dd>mm day⁻¹</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.28 kiB </td>\n",
       "                        <td> 4 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1096, 1) </td>\n",
       "                        <td> (1, 1) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1096 chunks in 6654 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"6\" x2=\"25\" y2=\"6\" />\n",
       "  <line x1=\"0\" y1=\"12\" x2=\"25\" y2=\"12\" />\n",
       "  <line x1=\"0\" y1=\"18\" x2=\"25\" y2=\"18\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"25\" y2=\"25\" />\n",
       "  <line x1=\"0\" y1=\"31\" x2=\"25\" y2=\"31\" />\n",
       "  <line x1=\"0\" y1=\"37\" x2=\"25\" y2=\"37\" />\n",
       "  <line x1=\"0\" y1=\"44\" x2=\"25\" y2=\"44\" />\n",
       "  <line x1=\"0\" y1=\"50\" x2=\"25\" y2=\"50\" />\n",
       "  <line x1=\"0\" y1=\"56\" x2=\"25\" y2=\"56\" />\n",
       "  <line x1=\"0\" y1=\"63\" x2=\"25\" y2=\"63\" />\n",
       "  <line x1=\"0\" y1=\"69\" x2=\"25\" y2=\"69\" />\n",
       "  <line x1=\"0\" y1=\"75\" x2=\"25\" y2=\"75\" />\n",
       "  <line x1=\"0\" y1=\"82\" x2=\"25\" y2=\"82\" />\n",
       "  <line x1=\"0\" y1=\"88\" x2=\"25\" y2=\"88\" />\n",
       "  <line x1=\"0\" y1=\"94\" x2=\"25\" y2=\"94\" />\n",
       "  <line x1=\"0\" y1=\"100\" x2=\"25\" y2=\"100\" />\n",
       "  <line x1=\"0\" y1=\"107\" x2=\"25\" y2=\"107\" />\n",
       "  <line x1=\"0\" y1=\"113\" x2=\"25\" y2=\"113\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1</text>\n",
       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">1096</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-2e693769-37e5-4a4b-9b2f-1a0736f88436' class='xr-section-summary-in' type='checkbox'  ><label for='section-2e693769-37e5-4a4b-9b2f-1a0736f88436' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>height</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-58295a46-dd6a-441e-bce8-514b25156ff6' class='xr-index-data-in' type='checkbox'/><label for='index-58295a46-dd6a-441e-bce8-514b25156ff6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([0.0], dtype=&#x27;float64&#x27;, name=&#x27;height&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0de50ded-c817-4862-af16-523e0044a9b4' class='xr-index-data-in' type='checkbox'/><label for='index-0de50ded-c817-4862-af16-523e0044a9b4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2003-01-01&#x27;, &#x27;2003-01-02&#x27;, &#x27;2003-01-03&#x27;, &#x27;2003-01-04&#x27;,\n",
       "               &#x27;2003-01-05&#x27;, &#x27;2003-01-06&#x27;, &#x27;2003-01-07&#x27;, &#x27;2003-01-08&#x27;,\n",
       "               &#x27;2003-01-09&#x27;, &#x27;2003-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-22&#x27;, &#x27;2005-12-23&#x27;, &#x27;2005-12-24&#x27;, &#x27;2005-12-25&#x27;,\n",
       "               &#x27;2005-12-26&#x27;, &#x27;2005-12-27&#x27;, &#x27;2005-12-28&#x27;, &#x27;2005-12-29&#x27;,\n",
       "               &#x27;2005-12-30&#x27;, &#x27;2005-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1096, freq=&#x27;D&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-faffc90f-f434-4cef-aad2-6522fd137525' class='xr-section-summary-in' type='checkbox'  checked><label for='section-faffc90f-f434-4cef-aad2-6522fd137525' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Wed Mar 22 18:03:40 2023: cdo -s -f nc4c -shifttime,-3hour -copy -seltimestep,3/744/3 /run/media/nms/Elements/MERA/grib/61_105_0_4_FC3hr/temp/MERA_PRODYEAR_2003_01_61_105_0_4_FC3hr /run/media/nms/Elements/MERA/grib/61_105_0_4_FC3hr/temp/MERA_PRODYEAR_2003_01_61_105_0_4_FC3hr.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (height: 1, time: 1096)\n",
       "Coordinates:\n",
       "    x                  float64 5.8e+05\n",
       "    y                  float64 4.725e+05\n",
       "  * height             (height) float64 0.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    tp                 (time, height) float32 dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 18:03:40 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_tsd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert to dataframe for plotting\n",
    "data_df = pd.DataFrame({\"time\": data_tsd[\"time\"]})\n",
    "data_df[f\"{var}\"] = data_tsd[var]\n",
    "data_df.set_index(\"time\", inplace=True)\n",
    "# met data\n",
    "df_plot = df[[\"rain\"]].copy()\n",
    "df_plot[\"rain\"] = df_plot[\"rain\"].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot\n",
    "ax = data_df.plot(\n",
    "    figsize=(12, 4.5),\n",
    "    y=var,\n",
    "    color=\"lightslategrey\",\n",
    "    alpha=0.7,\n",
    "    linewidth=2,\n",
    "    label=\"MÉRA\",\n",
    ")\n",
    "df_plot.plot(ax=ax, y=\"rain\", color=\"crimson\", linewidth=0.75, label=\"Station\")\n",
    "plt.tight_layout()\n",
    "plt.ylabel(\n",
    "    data_d[var].attrs[\"long_name\"] + \" [\" + data_d[var].attrs[\"units\"] + \"]\"\n",
    ")\n",
    "plt.xlabel(\"\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x672 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# map\n",
    "plt.figure(figsize=(9, 7))\n",
    "ax = plt.axes(projection=cplt.projection_lambert_conformal)\n",
    "data_d.isel(time=90, height=0)[var].plot.contourf(\n",
    "    ax=ax,\n",
    "    robust=True,\n",
    "    cmap=\"mako_r\",\n",
    "    x=\"x\",\n",
    "    y=\"y\",\n",
    "    levels=10,\n",
    "    transform=cplt.projection_lambert_conformal,\n",
    "    cbar_kwargs={\n",
    "        \"label\": (\n",
    "            data_d[var].attrs[\"long_name\"]\n",
    "            + \" [\"\n",
    "            + data_d[var].attrs[\"units\"]\n",
    "            + \"]\"\n",
    "        )\n",
    "    },\n",
    ")\n",
    "ax.gridlines(\n",
    "    draw_labels=dict(bottom=\"x\", left=\"y\"),\n",
    "    color=\"lightslategrey\",\n",
    "    linewidth=0.5,\n",
    "    x_inline=False,\n",
    "    y_inline=False,\n",
    ")\n",
    "ax.coastlines(resolution=\"10m\", color=\"darkslategrey\", linewidth=0.75)\n",
    "ax.set_title(str(data_d.isel(time=90, height=0)[\"time\"].values))\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Maximum temperature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "var = \"15_105_2_2\"\n",
    "file_list = list(\n",
    "    chain(\n",
    "        *list(\n",
    "            glob.glob(os.path.join(DATA_DIR, f\"{var}_FC3hr\", e))\n",
    "            for e in [f\"*{i}*{var}_FC3hr*\" for i in range(2003, 2006)]\n",
    "        )\n",
    "    )\n",
    ")\n",
    "data = xr.open_mfdataset(file_list, decode_coords=\"all\", chunks=\"auto\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (time: 8768, x: 158, y: 166, height: 1)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31T21:00:00\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "  * height             (height) float64 2.0\n",
       "    spatial_ref        int64 0\n",
       "    Lambert_Conformal  int64 0\n",
       "Data variables:\n",
       "    tmax               (time, height, y, x) float32 dask.array&lt;chunksize=(248, 1, 166, 158), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 23:16:44 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-312d80f5-a70a-45e2-84e5-951b53d08803' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-312d80f5-a70a-45e2-84e5-951b53d08803' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 8768</li><li><span class='xr-has-index'>x</span>: 158</li><li><span class='xr-has-index'>y</span>: 166</li><li><span class='xr-has-index'>height</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0d5dbfe8-439d-416a-888b-fb87d96014bc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0d5dbfe8-439d-416a-888b-fb87d96014bc' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2003-01-01 ... 2005-12-31T21:00:00</div><input id='attrs-f32ceccb-51bc-4079-a076-6f6b4d9bd5c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f32ceccb-51bc-4079-a076-6f6b4d9bd5c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31965cc1-a860-4947-8634-58aa87be5932' class='xr-var-data-in' type='checkbox'><label for='data-31965cc1-a860-4947-8634-58aa87be5932' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2003-01-01T00:00:00.000000000&#x27;, &#x27;2003-01-01T03:00:00.000000000&#x27;,\n",
       "       &#x27;2003-01-01T06:00:00.000000000&#x27;, ..., &#x27;2005-12-31T15:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-31T18:00:00.000000000&#x27;, &#x27;2005-12-31T21:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.15e+05 4.175e+05 ... 8.075e+05</div><input id='attrs-4f85dfee-7100-4306-aaf1-c3422c654013' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f85dfee-7100-4306-aaf1-c3422c654013' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-323dd0af-8bf2-481e-bb9d-7013744b2850' class='xr-var-data-in' type='checkbox'><label for='data-323dd0af-8bf2-481e-bb9d-7013744b2850' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([415000., 417500., 420000., 422500., 425000., 427500., 430000., 432500.,\n",
       "       435000., 437500., 440000., 442500., 445000., 447500., 450000., 452500.,\n",
       "       455000., 457500., 460000., 462500., 465000., 467500., 470000., 472500.,\n",
       "       475000., 477500., 480000., 482500., 485000., 487500., 490000., 492500.,\n",
       "       495000., 497500., 500000., 502500., 505000., 507500., 510000., 512500.,\n",
       "       515000., 517500., 520000., 522500., 525000., 527500., 530000., 532500.,\n",
       "       535000., 537500., 540000., 542500., 545000., 547500., 550000., 552500.,\n",
       "       555000., 557500., 560000., 562500., 565000., 567500., 570000., 572500.,\n",
       "       575000., 577500., 580000., 582500., 585000., 587500., 590000., 592500.,\n",
       "       595000., 597500., 600000., 602500., 605000., 607500., 610000., 612500.,\n",
       "       615000., 617500., 620000., 622500., 625000., 627500., 630000., 632500.,\n",
       "       635000., 637500., 640000., 642500., 645000., 647500., 650000., 652500.,\n",
       "       655000., 657500., 660000., 662500., 665000., 667500., 670000., 672500.,\n",
       "       675000., 677500., 680000., 682500., 685000., 687500., 690000., 692500.,\n",
       "       695000., 697500., 700000., 702500., 705000., 707500., 710000., 712500.,\n",
       "       715000., 717500., 720000., 722500., 725000., 727500., 730000., 732500.,\n",
       "       735000., 737500., 740000., 742500., 745000., 747500., 750000., 752500.,\n",
       "       755000., 757500., 760000., 762500., 765000., 767500., 770000., 772500.,\n",
       "       775000., 777500., 780000., 782500., 785000., 787500., 790000., 792500.,\n",
       "       795000., 797500., 800000., 802500., 805000., 807500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.075e+05 4.1e+05 ... 8.2e+05</div><input id='attrs-64708b8e-56ea-453e-a3c8-32932b16e5b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64708b8e-56ea-453e-a3c8-32932b16e5b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec7ef989-fc1d-4553-9438-070007769cd7' class='xr-var-data-in' type='checkbox'><label for='data-ec7ef989-fc1d-4553-9438-070007769cd7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([407500., 410000., 412500., 415000., 417500., 420000., 422500., 425000.,\n",
       "       427500., 430000., 432500., 435000., 437500., 440000., 442500., 445000.,\n",
       "       447500., 450000., 452500., 455000., 457500., 460000., 462500., 465000.,\n",
       "       467500., 470000., 472500., 475000., 477500., 480000., 482500., 485000.,\n",
       "       487500., 490000., 492500., 495000., 497500., 500000., 502500., 505000.,\n",
       "       507500., 510000., 512500., 515000., 517500., 520000., 522500., 525000.,\n",
       "       527500., 530000., 532500., 535000., 537500., 540000., 542500., 545000.,\n",
       "       547500., 550000., 552500., 555000., 557500., 560000., 562500., 565000.,\n",
       "       567500., 570000., 572500., 575000., 577500., 580000., 582500., 585000.,\n",
       "       587500., 590000., 592500., 595000., 597500., 600000., 602500., 605000.,\n",
       "       607500., 610000., 612500., 615000., 617500., 620000., 622500., 625000.,\n",
       "       627500., 630000., 632500., 635000., 637500., 640000., 642500., 645000.,\n",
       "       647500., 650000., 652500., 655000., 657500., 660000., 662500., 665000.,\n",
       "       667500., 670000., 672500., 675000., 677500., 680000., 682500., 685000.,\n",
       "       687500., 690000., 692500., 695000., 697500., 700000., 702500., 705000.,\n",
       "       707500., 710000., 712500., 715000., 717500., 720000., 722500., 725000.,\n",
       "       727500., 730000., 732500., 735000., 737500., 740000., 742500., 745000.,\n",
       "       747500., 750000., 752500., 755000., 757500., 760000., 762500., 765000.,\n",
       "       767500., 770000., 772500., 775000., 777500., 780000., 782500., 785000.,\n",
       "       787500., 790000., 792500., 795000., 797500., 800000., 802500., 805000.,\n",
       "       807500., 810000., 812500., 815000., 817500., 820000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-d2f7e98b-2328-490d-80d0-40893cc22c14' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2f7e98b-2328-490d-80d0-40893cc22c14' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac9a193b-ca6b-48c7-8430-239972436891' class='xr-var-data-in' type='checkbox'><label for='data-ac9a193b-ca6b-48c7-8430-239972436891' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array([2.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-9d8c7ce4-cf76-442b-b119-e09676cff1fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d8c7ce4-cf76-442b-b119-e09676cff1fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3cc0db6-6a6e-4291-bac9-a6ca3a2af946' class='xr-var-data-in' type='checkbox'><label for='data-c3cc0db6-6a6e-4291-bac9-a6ca3a2af946' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-efce15e8-edb6-4917-9eca-1c2c1b4c85c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-efce15e8-edb6-4917-9eca-1c2c1b4c85c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c4081c60-9ad7-4c30-81b0-039cbf01dd13' class='xr-var-data-in' type='checkbox'><label for='data-c4081c60-9ad7-4c30-81b0-039cbf01dd13' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-60aedaf0-88b3-4d55-bd65-b15103ed626c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-60aedaf0-88b3-4d55-bd65-b15103ed626c' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tmax</span></div><div class='xr-var-dims'>(time, height, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(248, 1, 166, 158), meta=np.ndarray&gt;</div><input id='attrs-64001f73-9077-4a21-8d12-6ced3cd7a173' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64001f73-9077-4a21-8d12-6ced3cd7a173' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34d592fe-5cba-4e8d-be1d-86e8a57511a9' class='xr-var-data-in' type='checkbox'><label for='data-34d592fe-5cba-4e8d-be1d-86e8a57511a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>233253015</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Maximum temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>tmax</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Maximum temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 877.25 MiB </td>\n",
       "                        <td> 24.81 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (8768, 1, 166, 158) </td>\n",
       "                        <td> (248, 1, 166, 158) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 36 chunks in 73 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-edfc8569-d947-43ef-bd53-c2c574588e78' class='xr-section-summary-in' type='checkbox'  ><label for='section-edfc8569-d947-43ef-bd53-c2c574588e78' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a972f907-faf4-46f9-bda9-8ffc152cc6b1' class='xr-index-data-in' type='checkbox'/><label for='index-a972f907-faf4-46f9-bda9-8ffc152cc6b1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2003-01-01 00:00:00&#x27;, &#x27;2003-01-01 03:00:00&#x27;,\n",
       "               &#x27;2003-01-01 06:00:00&#x27;, &#x27;2003-01-01 09:00:00&#x27;,\n",
       "               &#x27;2003-01-01 12:00:00&#x27;, &#x27;2003-01-01 15:00:00&#x27;,\n",
       "               &#x27;2003-01-01 18:00:00&#x27;, &#x27;2003-01-01 21:00:00&#x27;,\n",
       "               &#x27;2003-01-02 00:00:00&#x27;, &#x27;2003-01-02 03:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-30 18:00:00&#x27;, &#x27;2005-12-30 21:00:00&#x27;,\n",
       "               &#x27;2005-12-31 00:00:00&#x27;, &#x27;2005-12-31 03:00:00&#x27;,\n",
       "               &#x27;2005-12-31 06:00:00&#x27;, &#x27;2005-12-31 09:00:00&#x27;,\n",
       "               &#x27;2005-12-31 12:00:00&#x27;, &#x27;2005-12-31 15:00:00&#x27;,\n",
       "               &#x27;2005-12-31 18:00:00&#x27;, &#x27;2005-12-31 21:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=8768, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-db9eda31-c71b-4431-8406-d29309e05bea' class='xr-index-data-in' type='checkbox'/><label for='index-db9eda31-c71b-4431-8406-d29309e05bea' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([415000.0, 417500.0, 420000.0, 422500.0, 425000.0, 427500.0,\n",
       "              430000.0, 432500.0, 435000.0, 437500.0,\n",
       "              ...\n",
       "              785000.0, 787500.0, 790000.0, 792500.0, 795000.0, 797500.0,\n",
       "              800000.0, 802500.0, 805000.0, 807500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=158))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-48a4ec74-6013-45cf-b688-c4b780cdc0ff' class='xr-index-data-in' type='checkbox'/><label for='index-48a4ec74-6013-45cf-b688-c4b780cdc0ff' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([407500.0, 410000.0, 412500.0, 415000.0, 417500.0, 420000.0,\n",
       "              422500.0, 425000.0, 427500.0, 430000.0,\n",
       "              ...\n",
       "              797500.0, 800000.0, 802500.0, 805000.0, 807500.0, 810000.0,\n",
       "              812500.0, 815000.0, 817500.0, 820000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=166))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>height</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4fde7621-0dae-4163-9be1-ce2ed6ebf764' class='xr-index-data-in' type='checkbox'/><label for='index-4fde7621-0dae-4163-9be1-ce2ed6ebf764' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([2.0], dtype=&#x27;float64&#x27;, name=&#x27;height&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ffa127c0-97ae-4dfb-88ca-a71dcfa97035' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ffa127c0-97ae-4dfb-88ca-a71dcfa97035' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Wed Mar 22 23:16:44 2023: cdo -s -f nc4c -shifttime,-3hour -copy -seltimestep,3/744/3 /run/media/nms/Elements/MERA/grib/15_105_2_2_FC3hr/temp/MERA_PRODYEAR_2003_01_15_105_2_2_FC3hr /run/media/nms/Elements/MERA/grib/15_105_2_2_FC3hr/temp/MERA_PRODYEAR_2003_01_15_105_2_2_FC3hr.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (time: 8768, x: 158, y: 166, height: 1)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31T21:00:00\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "  * height             (height) float64 2.0\n",
       "    spatial_ref        int64 0\n",
       "    Lambert_Conformal  int64 0\n",
       "Data variables:\n",
       "    tmax               (time, height, y, x) float32 dask.array<chunksize=(248, 1, 166, 158), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 23:16:44 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert to deg C\n",
    "var = \"tmax\"\n",
    "data_attrs = data[var].attrs\n",
    "data_crs = data.rio.crs\n",
    "data[var] = data[var] - 273.15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (x: 158, y: 166, height: 1, time: 1096)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "  * height             (height) float64 2.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    tmax               (time, height, y, x) float32 dask.array&lt;chunksize=(1, 1, 166, 158), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 23:16:44 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6d0a857c-61b5-41da-a0c9-0a50fa363501' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6d0a857c-61b5-41da-a0c9-0a50fa363501' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 158</li><li><span class='xr-has-index'>y</span>: 166</li><li><span class='xr-has-index'>height</span>: 1</li><li><span class='xr-has-index'>time</span>: 1096</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-870ed0e5-3a70-4b1d-9bb8-170745e2d986' class='xr-section-summary-in' type='checkbox'  checked><label for='section-870ed0e5-3a70-4b1d-9bb8-170745e2d986' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.15e+05 4.175e+05 ... 8.075e+05</div><input id='attrs-746f98f5-a383-41fc-9b13-db7cd20d817d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-746f98f5-a383-41fc-9b13-db7cd20d817d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6de4925d-e663-469b-816a-177e3e604938' class='xr-var-data-in' type='checkbox'><label for='data-6de4925d-e663-469b-816a-177e3e604938' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([415000., 417500., 420000., 422500., 425000., 427500., 430000., 432500.,\n",
       "       435000., 437500., 440000., 442500., 445000., 447500., 450000., 452500.,\n",
       "       455000., 457500., 460000., 462500., 465000., 467500., 470000., 472500.,\n",
       "       475000., 477500., 480000., 482500., 485000., 487500., 490000., 492500.,\n",
       "       495000., 497500., 500000., 502500., 505000., 507500., 510000., 512500.,\n",
       "       515000., 517500., 520000., 522500., 525000., 527500., 530000., 532500.,\n",
       "       535000., 537500., 540000., 542500., 545000., 547500., 550000., 552500.,\n",
       "       555000., 557500., 560000., 562500., 565000., 567500., 570000., 572500.,\n",
       "       575000., 577500., 580000., 582500., 585000., 587500., 590000., 592500.,\n",
       "       595000., 597500., 600000., 602500., 605000., 607500., 610000., 612500.,\n",
       "       615000., 617500., 620000., 622500., 625000., 627500., 630000., 632500.,\n",
       "       635000., 637500., 640000., 642500., 645000., 647500., 650000., 652500.,\n",
       "       655000., 657500., 660000., 662500., 665000., 667500., 670000., 672500.,\n",
       "       675000., 677500., 680000., 682500., 685000., 687500., 690000., 692500.,\n",
       "       695000., 697500., 700000., 702500., 705000., 707500., 710000., 712500.,\n",
       "       715000., 717500., 720000., 722500., 725000., 727500., 730000., 732500.,\n",
       "       735000., 737500., 740000., 742500., 745000., 747500., 750000., 752500.,\n",
       "       755000., 757500., 760000., 762500., 765000., 767500., 770000., 772500.,\n",
       "       775000., 777500., 780000., 782500., 785000., 787500., 790000., 792500.,\n",
       "       795000., 797500., 800000., 802500., 805000., 807500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.075e+05 4.1e+05 ... 8.2e+05</div><input id='attrs-06e49383-33db-4dfe-9f08-7dbdcd733aad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06e49383-33db-4dfe-9f08-7dbdcd733aad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-12620d10-8450-4c10-afb3-0ae9362efd73' class='xr-var-data-in' type='checkbox'><label for='data-12620d10-8450-4c10-afb3-0ae9362efd73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([407500., 410000., 412500., 415000., 417500., 420000., 422500., 425000.,\n",
       "       427500., 430000., 432500., 435000., 437500., 440000., 442500., 445000.,\n",
       "       447500., 450000., 452500., 455000., 457500., 460000., 462500., 465000.,\n",
       "       467500., 470000., 472500., 475000., 477500., 480000., 482500., 485000.,\n",
       "       487500., 490000., 492500., 495000., 497500., 500000., 502500., 505000.,\n",
       "       507500., 510000., 512500., 515000., 517500., 520000., 522500., 525000.,\n",
       "       527500., 530000., 532500., 535000., 537500., 540000., 542500., 545000.,\n",
       "       547500., 550000., 552500., 555000., 557500., 560000., 562500., 565000.,\n",
       "       567500., 570000., 572500., 575000., 577500., 580000., 582500., 585000.,\n",
       "       587500., 590000., 592500., 595000., 597500., 600000., 602500., 605000.,\n",
       "       607500., 610000., 612500., 615000., 617500., 620000., 622500., 625000.,\n",
       "       627500., 630000., 632500., 635000., 637500., 640000., 642500., 645000.,\n",
       "       647500., 650000., 652500., 655000., 657500., 660000., 662500., 665000.,\n",
       "       667500., 670000., 672500., 675000., 677500., 680000., 682500., 685000.,\n",
       "       687500., 690000., 692500., 695000., 697500., 700000., 702500., 705000.,\n",
       "       707500., 710000., 712500., 715000., 717500., 720000., 722500., 725000.,\n",
       "       727500., 730000., 732500., 735000., 737500., 740000., 742500., 745000.,\n",
       "       747500., 750000., 752500., 755000., 757500., 760000., 762500., 765000.,\n",
       "       767500., 770000., 772500., 775000., 777500., 780000., 782500., 785000.,\n",
       "       787500., 790000., 792500., 795000., 797500., 800000., 802500., 805000.,\n",
       "       807500., 810000., 812500., 815000., 817500., 820000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-ef13b9a2-4fc7-4f10-8731-8d84010db9a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef13b9a2-4fc7-4f10-8731-8d84010db9a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb253c99-8544-4ed5-bc70-7677ddefa677' class='xr-var-data-in' type='checkbox'><label for='data-cb253c99-8544-4ed5-bc70-7677ddefa677' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array([2.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-95418995-cd2e-40dc-a4bb-eb86d8566941' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95418995-cd2e-40dc-a4bb-eb86d8566941' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b5a97ee-b2e1-46ba-8833-0d056b070d9f' class='xr-var-data-in' type='checkbox'><label for='data-6b5a97ee-b2e1-46ba-8833-0d056b070d9f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2003-01-01 ... 2005-12-31</div><input id='attrs-a5b0de1c-a8ad-42a5-a692-6c2cd1879f42' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a5b0de1c-a8ad-42a5-a692-6c2cd1879f42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56fe5e86-9965-4bef-8d53-2c4fa3d80897' class='xr-var-data-in' type='checkbox'><label for='data-56fe5e86-9965-4bef-8d53-2c4fa3d80897' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2003-01-01T00:00:00.000000000&#x27;, &#x27;2003-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-01-03T00:00:00.000000000&#x27;, ..., &#x27;2005-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-30T00:00:00.000000000&#x27;, &#x27;2005-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-5c28581f-0a51-4580-87d2-549db5184105' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c28581f-0a51-4580-87d2-549db5184105' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55fe371c-937d-461c-9d7f-d3bda7b3f24b' class='xr-var-data-in' type='checkbox'><label for='data-55fe371c-937d-461c-9d7f-d3bda7b3f24b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-18725791-0a54-4547-9e94-414f71a3c63c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-18725791-0a54-4547-9e94-414f71a3c63c' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tmax</span></div><div class='xr-var-dims'>(time, height, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 166, 158), meta=np.ndarray&gt;</div><input id='attrs-ddce18f5-d0b3-4ea9-bd39-553f309ff529' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ddce18f5-d0b3-4ea9-bd39-553f309ff529' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-197de0d4-8ecf-4841-99d6-93359a791ac8' class='xr-var-data-in' type='checkbox'><label for='data-197de0d4-8ecf-4841-99d6-93359a791ac8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>233253015</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Maximum temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>tmax</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Maximum temperature</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 109.66 MiB </td>\n",
       "                        <td> 102.45 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1096, 1, 166, 158) </td>\n",
       "                        <td> (1, 1, 166, 158) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1096 chunks in 4459 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"485\" height=\"105\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"3\" y1=\"0\" x2=\"3\" y2=\"25\" />\n",
       "  <line x1=\"7\" y1=\"0\" x2=\"7\" y2=\"25\" />\n",
       "  <line x1=\"11\" y1=\"0\" x2=\"11\" y2=\"25\" />\n",
       "  <line x1=\"15\" y1=\"0\" x2=\"15\" y2=\"25\" />\n",
       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
       "  <line x1=\"22\" y1=\"0\" x2=\"22\" y2=\"25\" />\n",
       "  <line x1=\"26\" y1=\"0\" x2=\"26\" y2=\"25\" />\n",
       "  <line x1=\"30\" y1=\"0\" x2=\"30\" y2=\"25\" />\n",
       "  <line x1=\"33\" y1=\"0\" x2=\"33\" y2=\"25\" />\n",
       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
       "  <line x1=\"41\" y1=\"0\" x2=\"41\" y2=\"25\" />\n",
       "  <line x1=\"45\" y1=\"0\" x2=\"45\" y2=\"25\" />\n",
       "  <line x1=\"48\" y1=\"0\" x2=\"48\" y2=\"25\" />\n",
       "  <line x1=\"52\" y1=\"0\" x2=\"52\" y2=\"25\" />\n",
       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"25\" />\n",
       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
       "  <line x1=\"67\" y1=\"0\" x2=\"67\" y2=\"25\" />\n",
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       "              430000.0, 432500.0, 435000.0, 437500.0,\n",
       "              ...\n",
       "              785000.0, 787500.0, 790000.0, 792500.0, 795000.0, 797500.0,\n",
       "              800000.0, 802500.0, 805000.0, 807500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=158))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3999f451-f32a-42ab-aa6e-9a027a980f00' class='xr-index-data-in' type='checkbox'/><label for='index-3999f451-f32a-42ab-aa6e-9a027a980f00' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([407500.0, 410000.0, 412500.0, 415000.0, 417500.0, 420000.0,\n",
       "              422500.0, 425000.0, 427500.0, 430000.0,\n",
       "              ...\n",
       "              797500.0, 800000.0, 802500.0, 805000.0, 807500.0, 810000.0,\n",
       "              812500.0, 815000.0, 817500.0, 820000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=166))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>height</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1a90a247-392c-4c79-9aff-b19039236b57' class='xr-index-data-in' type='checkbox'/><label for='index-1a90a247-392c-4c79-9aff-b19039236b57' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([2.0], dtype=&#x27;float64&#x27;, name=&#x27;height&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-856f62a8-c248-4136-9571-b5e6373de04a' class='xr-index-data-in' type='checkbox'/><label for='index-856f62a8-c248-4136-9571-b5e6373de04a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2003-01-01&#x27;, &#x27;2003-01-02&#x27;, &#x27;2003-01-03&#x27;, &#x27;2003-01-04&#x27;,\n",
       "               &#x27;2003-01-05&#x27;, &#x27;2003-01-06&#x27;, &#x27;2003-01-07&#x27;, &#x27;2003-01-08&#x27;,\n",
       "               &#x27;2003-01-09&#x27;, &#x27;2003-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-22&#x27;, &#x27;2005-12-23&#x27;, &#x27;2005-12-24&#x27;, &#x27;2005-12-25&#x27;,\n",
       "               &#x27;2005-12-26&#x27;, &#x27;2005-12-27&#x27;, &#x27;2005-12-28&#x27;, &#x27;2005-12-29&#x27;,\n",
       "               &#x27;2005-12-30&#x27;, &#x27;2005-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1096, freq=&#x27;D&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-39d378b9-eaf5-42ee-970e-5e777c5fe05f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-39d378b9-eaf5-42ee-970e-5e777c5fe05f' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Wed Mar 22 23:16:44 2023: cdo -s -f nc4c -shifttime,-3hour -copy -seltimestep,3/744/3 /run/media/nms/Elements/MERA/grib/15_105_2_2_FC3hr/temp/MERA_PRODYEAR_2003_01_15_105_2_2_FC3hr /run/media/nms/Elements/MERA/grib/15_105_2_2_FC3hr/temp/MERA_PRODYEAR_2003_01_15_105_2_2_FC3hr.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (x: 158, y: 166, height: 1, time: 1096)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "  * height             (height) float64 2.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    tmax               (time, height, y, x) float32 dask.array<chunksize=(1, 1, 166, 158), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 23:16:44 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# resample to daily - take the max\n",
    "time_attrs = data[\"time\"].attrs\n",
    "data_d = data.resample(time=\"D\").max()\n",
    "data_d[var].attrs = data_attrs  # reassign attributes\n",
    "data_d[\"time\"].attrs = time_attrs\n",
    "data_d[var].attrs[\"units\"] = \"°C\"  # update attributes\n",
    "data_d.rio.write_crs(data_crs, inplace=True)  # reassign CRS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract data for the nearest grid cell to the point\n",
    "data_tsd = data_d.sel({\"x\": XLON, \"y\": YLAT}, method=\"nearest\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
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       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (height: 1, time: 1096)\n",
       "Coordinates:\n",
       "    x                  float64 5.8e+05\n",
       "    y                  float64 4.725e+05\n",
       "  * height             (height) float64 2.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    tmax               (time, height) float32 dask.array&lt;chunksize=(1, 1), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 23:16:44 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-fb6e3fef-71a1-4749-952c-3006c775bf2d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-fb6e3fef-71a1-4749-952c-3006c775bf2d' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>height</span>: 1</li><li><span class='xr-has-index'>time</span>: 1096</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3bd0215b-88e1-4dfb-a910-525562d323e5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3bd0215b-88e1-4dfb-a910-525562d323e5' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.8e+05</div><input id='attrs-3e0e4635-cca5-44a3-a875-224d10fc8962' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e0e4635-cca5-44a3-a875-224d10fc8962' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec863e85-0b42-4750-b3e8-0471b159127b' class='xr-var-data-in' type='checkbox'><label for='data-ec863e85-0b42-4750-b3e8-0471b159127b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array(580000.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.725e+05</div><input id='attrs-d3043b7f-5d57-4681-bcbc-f433b27200ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3043b7f-5d57-4681-bcbc-f433b27200ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ff0d08f-e77f-41d5-b68a-bd0774138c0a' class='xr-var-data-in' type='checkbox'><label for='data-9ff0d08f-e77f-41d5-b68a-bd0774138c0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array(472500.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-5a2c8550-1720-4311-9505-fc59ba5fee62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a2c8550-1720-4311-9505-fc59ba5fee62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-599904a9-1313-4e1b-9e2b-d3dc307a380e' class='xr-var-data-in' type='checkbox'><label for='data-599904a9-1313-4e1b-9e2b-d3dc307a380e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array([2.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-7de840db-91d0-4c2b-8a5d-76018f1afe78' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7de840db-91d0-4c2b-8a5d-76018f1afe78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18d44ab9-cfc9-4a8e-a190-e78b7c8d1f8f' class='xr-var-data-in' type='checkbox'><label for='data-18d44ab9-cfc9-4a8e-a190-e78b7c8d1f8f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2003-01-01 ... 2005-12-31</div><input id='attrs-241daf5c-314b-4e26-9ad8-5cfd0aa3bb1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-241daf5c-314b-4e26-9ad8-5cfd0aa3bb1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3b96a10-bfcb-47a1-bae0-505c44fa7b25' class='xr-var-data-in' type='checkbox'><label for='data-a3b96a10-bfcb-47a1-bae0-505c44fa7b25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2003-01-01T00:00:00.000000000&#x27;, &#x27;2003-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-01-03T00:00:00.000000000&#x27;, ..., &#x27;2005-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-30T00:00:00.000000000&#x27;, &#x27;2005-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-a80d4d5e-c3fb-4384-8257-d55158c43c2b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a80d4d5e-c3fb-4384-8257-d55158c43c2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6451304c-0d6f-4668-aefe-b12ca39f8987' class='xr-var-data-in' type='checkbox'><label for='data-6451304c-0d6f-4668-aefe-b12ca39f8987' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e44aac51-c4dc-42af-9e82-5e42091baf48' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e44aac51-c4dc-42af-9e82-5e42091baf48' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tmax</span></div><div class='xr-var-dims'>(time, height)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1), meta=np.ndarray&gt;</div><input id='attrs-bd24d9a6-cede-46cd-b785-59ff2a1dbdce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd24d9a6-cede-46cd-b785-59ff2a1dbdce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15943c4f-32a7-423a-97e1-1d1b70ad3cbd' class='xr-var-data-in' type='checkbox'><label for='data-15943c4f-32a7-423a-97e1-1d1b70ad3cbd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_paramId :</span></dt><dd>233253015</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Maximum temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>tmax</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Maximum temperature</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.28 kiB </td>\n",
       "                        <td> 4 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1096, 1) </td>\n",
       "                        <td> (1, 1) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1096 chunks in 4460 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
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       "  <line x1=\"0\" y1=\"56\" x2=\"25\" y2=\"56\" />\n",
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       "\n",
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       "\n",
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       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1</text>\n",
       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">1096</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-7eb4647a-fe62-4ba3-a7f5-9162015d586c' class='xr-section-summary-in' type='checkbox'  ><label for='section-7eb4647a-fe62-4ba3-a7f5-9162015d586c' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>height</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0018ae1a-05cb-4185-bb9d-6040df14abe0' class='xr-index-data-in' type='checkbox'/><label for='index-0018ae1a-05cb-4185-bb9d-6040df14abe0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([2.0], dtype=&#x27;float64&#x27;, name=&#x27;height&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6d9f73e5-5ea9-4fcb-8dcd-2fd8627080ce' class='xr-index-data-in' type='checkbox'/><label for='index-6d9f73e5-5ea9-4fcb-8dcd-2fd8627080ce' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2003-01-01&#x27;, &#x27;2003-01-02&#x27;, &#x27;2003-01-03&#x27;, &#x27;2003-01-04&#x27;,\n",
       "               &#x27;2003-01-05&#x27;, &#x27;2003-01-06&#x27;, &#x27;2003-01-07&#x27;, &#x27;2003-01-08&#x27;,\n",
       "               &#x27;2003-01-09&#x27;, &#x27;2003-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-22&#x27;, &#x27;2005-12-23&#x27;, &#x27;2005-12-24&#x27;, &#x27;2005-12-25&#x27;,\n",
       "               &#x27;2005-12-26&#x27;, &#x27;2005-12-27&#x27;, &#x27;2005-12-28&#x27;, &#x27;2005-12-29&#x27;,\n",
       "               &#x27;2005-12-30&#x27;, &#x27;2005-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1096, freq=&#x27;D&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-62207df3-60d4-44ad-a4d0-86835300d13a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-62207df3-60d4-44ad-a4d0-86835300d13a' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Wed Mar 22 23:16:44 2023: cdo -s -f nc4c -shifttime,-3hour -copy -seltimestep,3/744/3 /run/media/nms/Elements/MERA/grib/15_105_2_2_FC3hr/temp/MERA_PRODYEAR_2003_01_15_105_2_2_FC3hr /run/media/nms/Elements/MERA/grib/15_105_2_2_FC3hr/temp/MERA_PRODYEAR_2003_01_15_105_2_2_FC3hr.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (height: 1, time: 1096)\n",
       "Coordinates:\n",
       "    x                  float64 5.8e+05\n",
       "    y                  float64 4.725e+05\n",
       "  * height             (height) float64 2.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 2003-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    tmax               (time, height) float32 dask.array<chunksize=(1, 1), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 23:16:44 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_tsd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/nms/miniconda3/envs/ClimAg/lib/python3.10/site-packages/dask/array/reductions.py:640: RuntimeWarning: All-NaN slice encountered\n",
      "  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)\n"
     ]
    }
   ],
   "source": [
    "# convert to dataframe for plotting\n",
    "data_df = pd.DataFrame({\"time\": data_tsd[\"time\"]})\n",
    "data_df[f\"{var}\"] = data_tsd[var]\n",
    "data_df.set_index(\"time\", inplace=True)\n",
    "# met data\n",
    "df_plot = df[[\"maxtp\"]].copy()\n",
    "df_plot[\"maxtp\"] = df_plot[\"maxtp\"].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot\n",
    "ax = data_df.plot(\n",
    "    figsize=(12, 4.5),\n",
    "    y=var,\n",
    "    color=\"lightslategrey\",\n",
    "    alpha=0.7,\n",
    "    linewidth=2,\n",
    "    label=\"MÉRA\",\n",
    ")\n",
    "df_plot.plot(\n",
    "    ax=ax, y=\"maxtp\", color=\"crimson\", linewidth=0.75, label=\"Station\"\n",
    ")\n",
    "plt.tight_layout()\n",
    "plt.ylabel(\n",
    "    data_d[var].attrs[\"long_name\"] + \" [\" + data_d[var].attrs[\"units\"] + \"]\"\n",
    ")\n",
    "plt.xlabel(\"\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/nms/miniconda3/envs/ClimAg/lib/python3.10/site-packages/dask/array/reductions.py:640: RuntimeWarning: All-NaN slice encountered\n",
      "  return np.nanmax(x_chunk, axis=axis, keepdims=keepdims)\n"
     ]
    },
    {
     "data": {
      "image/png": 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289Q77/DX6tUAHDZpEjdfdFFLO3ew115++aOPWLdtG03NzWRnZHDMrFnMP+mkNrWaO+KTH3/kq0WLqNDpmDBiBLdedhnpKSler9NXIQ72xjCvffop2/ftY1j//vzfWWe1aS/e0dxlpaW16aTpwJsQ92X+AHYdOMBz773Hpp076ZedzfyTT24jCpv1eq66/35sNhuvPvBAS5UM8G3uGpqaePz11/l7wwZio6M5euZMrjz7bCRJahnz0Msvs2L9eh6/9VZGOF2Lt3kDe7OlVz75hF+XLaOhqYlp48Zx62WXERsd3TLm60WLePGjj/jXOedw6lFHtbxertWy8M03Wbt1a0tDnLOOPbbdXAbqfvVlvgM9t4GcR3/mTCAQCIKJEOICgUAgEAgEAkEIEDHiAoFAIBAIBAJBCBBCXCAQCAQCgUAgCAFCiAsEAoFAIBAIBCFACHGBQCAQCAQCgSAECCEuEAgEAoFAIBCEAPd9lHsoldXVLQ1QBAKBQCAQCHoySXFxJCUkhNqMbqG+sRGLxXLIXl+w6DXlCyurqzn1mmtocmqxLBAIBAKBQNCTWfz224ecWLVYrRx91Ck0Rir45aP3SIyLC7VJvZZe4xGvb2ykSa/n6TvuIDczM9TmhJxmvQFNRRVllTpq6psIU0jUNTQxZdxw8rLTCVMqQ21in+CnP1Zx5IwJqFS95k+pV1NcVomuppZxIwaH2pQ+wfbdB1CpwhjYLyfUphz6yDLf/b6SE49s3yRJEFhkm40fl6zi+LnTuvU8D7/yCuu2bqW6vv6QE+LfLl5MTYwCtQVumnEOb2/+MdQm9Vp6nXrIzcxkYF5eqM3oEYwe0vp/s8XCG5/8iFoVybpNe7FYrSQnxJOfnU5+djqxMVGhM/QQJj5mB8MG9A+1GX2GMk0Nk0aNpF9ORqhN6RPs3FPG5NHDSUoQ3q7upqaugYH5eeL7LQhU19YzqF9+t8610WRix7593Xb8UKI3GHjyyecZpbGQ1GDjr5FqijUa4STtJL1OiAvcYzZbSE6M4/ApYwB72+eq2noKSytYtHwtDU3NRKjDyctKJy87nYyURBQKkavbFRqb9URHRoTajD5FWWUVU8YND7UZfYaaugYS42NDbUafoEJXQ0ZKUqjN6BNoq2pJSUro1nPUNzYesivTN409FfOAcKbsNKE2y2zoH87NJ13OZ6t/CLVpvRIhxA8Risoqyc9Kb/ldkiRSEuNJSYxnwkj7Mr7BaKKorJKtu/bz+/K1AGSkJJGfnU5uVhqREeqQ2N5bKdFoyc1KC7UZfQqT2YI6XBVqM/oEsiwjIyNJUqhN6RNU6KopyM0KtRl9gsrqWnIzu/ezOzE+Htlm69ZzhAJdTQ1rB4YzcbeJKJM9xXDmNiPfT45k086djB4yxMsRBK4IIX6IUFhazthhAzscE6EOZ3BBDoML7PGeNpuNCl0NhaUVbNi+F4PRRExUBHkHw1lSEuPFl3AHFJdVMnJIQajN6DMYjCYi1EKEB4uGxmbiREhb0KjQ1TB1rFjtCQbaqlrGd3OeSZhSydSxY/ltxYpuPU+wufGI8wlPD2PcPlPLa/3LLWRVWbj98lv44a/vhG7wEyHEDxEqq2pJTUn0ax+FQkFmWjKZaclMPbjc39ikp7C0gjWbdqKtrkOpUJCVnkxedjq5GamEC29kC5VVNaSnjA+1GX2G0godWWkpoTajz6CprCIzNTnUZnQLeoOBb37/nVWbNnHMrFnMnTYt5GEERpMZtTo8pDb0FZr0BqKjuj+sMPkQS9DcV1zM1jwVczcaUFlbX5eAWVuNfHJYNEtWrWLO1Kkhs7E3IoT4IYDVakMhSSgC8BQaEx3JiMH9GDG4H2AvUaSpqKKwrILVG3dgtliIi4kiPzuDvKw0EuNj++TTryzL2GRZxNkHkbJyHTmZqaE2o8+g0VYzIP/QDJV4+p132LhjB2dNVvLBdx/wyY8f8uRtJ5AYFwnSEUG3x2azIdH3PkcPZWw2G3/880+ozQgoC864iqRoBcOKLe22ZdTaGFRq5oG7H2bWz1+iChPy0leEijgEKKvUkZnWPZ6rMKWS3Kw0Zk4cxTknzmH+qUcze8pYFAoFK9Zu5b2vfuPDbxbx56qNHCgpx2xu/wd6KKKrqSMlMT7UZvQpyiqryEoXHvFgUa6tPmSTB0884giq6+qYPSqJt67qz5ghmVx42yfsK64GeUnQ7amubSApQSTFBoNmvSEo+VB/rVlDdNShE9q1dutW9mWqmLnV6FE4Tt9upD5K4stffw2qbb0d8chyCFBYWkF+EMu5xcfFMDouhtFD7WX7zBYLZeU6CssqWbluK2aLlYS46JYKLYlxMYec17xEoxXe2SBjMptFomYQMVssh2x9/FGDB3PSnDnc/MYvPHfFCG64cCb9cpK47O7PueqcKZx+tI2wsLlBs6dCV0P6IfrQ09PQVteR2s0VUwDe//ZbTpw9m2fefbfbz9Xd2Gw27rz6dnItMvlaq8dxCc0yo/ebeeb5lznhiCOIjowMopW9l0PzU7aPUaLRMnn00JCdXxUWRn5ORsvDgCzL1DU0UVRawfI1m6mtt5dxykpPIT87nez0lF7/BV9UVsnsg6UiBd2P0WgiXCVEuAO5cGGb36X8BQE9vtlsOeSXlq8+91ye1K7g4mc28r8HhnHynOEMLUjliTf/4rOfN7Pg0hKmjrHXmdbod5EZdWW32VKuq2Zof1E/PBhoq2tJTere1cyd+/dTrNEwddw4OASE+K/Ll1ORoODcP5u9BlBN3mVkW56Km8afxqvbfwqKfb2dQ/uTtg8gyzIms7lHJVFKkkRCXAwJcTGMHjYAaPWaF5VV8vf6bZjMllaveS+MNa9raCI+LibUZvQZSiuryEo/NBMHA4FcuDCgYrxcV01G6qHtoVUqldx6Wn/e/r2Emx74lE/+PY4hBRN47YHTWLJqLw++tJiBecncdPFMwhNB0/xKt4lxbVUtsyaN7pZjC9qiraplUjc7rjbt3Mn08eNDngAcCExmMw8/8ARDq62k1Xsvxxhphkm7TawaHE5FVRXpyeJz2xtCiPdyausbSYjr+bGFrl5zsNteVFbJirVbqa5rIEypICs9hbysNHJ6cIUWi8VKmFKkVwST0nIt2RkiFMiBlL+gnVc8kGJcU1FF5iEuxB1MGhjPr+u0Lb9LksScqQOZOaEfH3y/gfm3fcTsGVnMnZWNXPAyWdFXBdwGs8VCeC9fJewtVNc2kNjN8fiVVVWkJR0afz+f/PQTTRES03YYfd5n7D4TG/upuOnI+Xy4/sdutO7QQPzl93IKSyvol53ufWAPpMVrfjDW3GKxUlZh95r/s3EHJrO9QktuVhp5WWk9pq65SBoMPmUVVSENv+qJdKcY12irGDqgb4RKaGqMZCTak/fkorVIeRMACFeFccmpE5k8Vc23Px/g4WfXM2JIItdf/iL9Eq4O2PmtVhtKUX0paNjk7p/vyurqQ6KxTX1jI/97+Q3GFpqI08s+7xdmg+k7jPw6LoLdBw4wqF+/7jPyEEAI8V5OYWk5s6eMDbUZASEsTEletj3B00F9YzPFZZWs2bQTXU0dCkkiPTWJvKx0cjNTQ9INtLisstu7sgnaYjKLGsvu6C4xXt/YTGwfaeZT7iTEXdHod5GUoObic4ZwzqkDefa1zdxy/9/cc5OJ9NTWRLSuhKzoaupIFhWYgkKwHnqqamtJOQRqiN849Syk3DAm7TZ5H+zC0BIL6/vbWHDutXyz8vtusO7QQQjxXk5dQ/MhHascFxPVpq651WajQltNUVklG7ftwWAyEalWk5uVSm5WOukpid3+QVtSrmXiqO7tyiZoRSRqdkygEzVtst3z1RNWn4KBWqWgtNq+7O7whrsjQq3k39eM4asfD3DTfSu575bxDBmQ0OXz2yum+NeMTdA5qmvrSUqI6/bzGIxGIiO6v2FQd1JaUcHGAhUzthlRd6IqsQTM3Gbkq+lRrNq4kSljRHEDTwgh3osxGk2ow/vWW2jv9JlCVnpKSzfQZr2BYo2Wrbv2s2TFOmyyTEpi/MGQlvSAt+kW3tngUlZZRVY31ckXtKemroHE+J6fdxIoTpqSzpu/lbBxfz1jvUTjSJLEaccXkJEWxX+fWsfTD0wjNblrJdoqtNWMOhieJ+heKqtrg1K60GQ2o+rlzoObj7+UmEQlow+YO32MPJ2V/AoLd99wN78s/kY0wPNA31JxhxjFGq0IkQCiIiMY0j+XIf1zAbtHr6q6jqKyShavWEd9YzOqMCXZGankZaV1qXxiU5CaQQhaKS3XkZ0hYvKDhaayqtsahHWEa4gNdN7bX1VbS1K8bzklapWCK4/N5flfq3j9MNmnfaZPSmf77ho++3YfV18yolM2OtDV1JHSzeX0BHa0VbUMyOv+brFmsxl1Lxbi2/bsYWeOiuNW61H6HhrulpnbjHw4O4of//yTE44Iftfa3oAQ4r2YA6XlDBuQH2ozehwKSSI1OYHU5AQmHAwhMZktlJZrKSqtaGk6FBcTRW6mPRE0OSkehQ9fwCUaLbmikU9QKavUMXF070986i1oKqsYMbgguCc92M1Sln0Twh4Pc1DMz71hGZeefjrXz5/vdpzBaOT5l25i7Z46KmtNnHPiBKrqdrJ0zX4Om+Sbd/rkY/rxr9uWcdHZg6ELi24Wq/WQKHPXG9BW1baspHYnVXV1xMfGojf6XmmkpyDLMv++6EYylBIDNV3vlJ3SYGNYkZlHH3maI6dPJ0ItHFmuCCHeiymvrOaIaeNCbUavIFwVRkFuJgW5mS2v1Tc0UaSpZM1meyKohERaSqK9fGJmKjFR7Zeci8sqGT5IPPwEE6PJTIQIBQoa2qpa0pITAnIsn4S1vIT128v43/v72bq3ghnj8vn3ZYeTnuI9PEZbXc15t9zChJEjuXhqA0NyWvNl3vziCyaOHMn0cW0/I4s0GhY8dg/9c5K4+/pZREaoePClxTQ0GXngpd95MyeJvMwEr+dOSYpgwugUfv2zhIGnex3uFrPFIkR4EDGYTN3+WdLQ1ERDUxOZqansKynp1nN1B0vXrqUkNYwzlnlv3uMr03aa2JWt4qMffuCS004L0FEPHUTATi/FJsvIyKLsVReIi41m5OACjp09hfmnHs15J89l9ND+1Dc28+tfq3nvq1/55PvFLFu9mcLSCswWCxW6atL7SH3lnoDRZBb1lYOM1Wbrsjisrq1l+jnn8OqnnwL2pfqfly6ltr6+zTht1ffc/ewv3PbkT5x29Eh+fOUScjMTuPGR75Fl72vi8bGx1DQ0MDihmH+9tJVHP9/L66vsLbhvu/xw7nr6cX5fubJl/OK//+ai227m9KNH8sjNxzByUAYDcpN58b5T0BvMnH/iOK7579dU1zX7dJ0nz8vn218KsVo9t/3uiGC1Wxfg0/0UCA6UllKQnd0r46EtViv3//s/DNCYya7u3D3tjhiDzPi9Jl564512nwEC4RHvtVTqakhPFpn2gUShUJCRmkRGahKTx9hrVhuNJkoqdOwv1rB8zRYOlFTw3aIV9kTQTN9DWgSdwx6vLOLD/aGz5QvlwoUYTKA2RSAXbgI6F6O9e+V/uOG1bSTEqVmyahFXnpXGmi2FPPiSvbHHxBE5TB+fT1FZLd//sZ1TjhzB18/PJyrS7qm8/oIZnLD8bbbuqWCkl+JE4SoVA9LVTBwYz/ETU/lquwKNtoHPnzmfgfkpjB2axfUP/483Pn+LhLhI9pdU89xdJzFqcGtjMZPZQo11H8MGxxOd2MT0ySn868FPefSuKUSoO34gGToogdiYcL5b+TCnzLzH77mq1NWQnio+x4NBU7PB7SpnoPl28eJeW0P8m99/pyZGwQmr9QE/9oQ9Jjb3U3HjjHN4e7No8uOMEOK9lMLS8jZdKgXdg1odzoC8LAbkZVFVU8/f67cxc9Ioip1CWgDSkhPJzUojNzOV2Oi+UX85GIhETf9wl/DoD39u07N+by2b91YypiCOM/KWgORbgpXRZOLLT27n1V+KWXDZHArLaqisbsRgtPDU20u55ZJZHDV9EL//vZc1W0rIy0zg7UfOol92WyGqUEgcM2sw369Yw8jB53Z4TrlwIeEqBQazlfTR07nKpUv8sAFpvLJwOoUljZRXNnPDqIHExdaj0bd65S696U80Fc0kJqjZsKWKay8dgfYlPY//bwN33TQepcLzg7YkSZw8L59vfjnAlPGv+F1PvFxbzXhvTxuCgFBZXUtqgEKuPPH1okX8vWEDHz75ZLeepzto1ut58qn/MUpjIbEp8KsH4VaYstPEXyPVFGs05GZmehxrtVpZuWEDP/31Fz8vXcrDN9/MvJkzW7ZX1dbyxz//8MmPP1JYVsaqgytvHXHLo4/y+99/t3ktJTGRRW+91fmLChBCiPdSCksrGT10QKjN6FMUayrJzUojPjaa+NgCRh5MaLPZbGirainSVLJo2VoamvT2Ki3pKeQerNISHt57M+hDSVmFriXhVtAxXRXh2joT7yyp4bDhkWQlxPP64kpI3MwZ8+hQjMuyzFeLFvHKB68xOCualx44k+y0OE7815+8+9jZPPn2X/TPTeaUuSPswnXOcE6e03HC3KChCl5+pwLz+Z7LwMmFC2kyWNhT1sSofPfx5Br9LiIjwhg6MIGhAxPcjll431TmX7uEfjkxnHxMPyRJ4sYrRnHPY2t45d3t/OuiYR3Guc+amsEbH+6gsKQBcvwT41U19SQndn9da4E996G7woBkWeb1zz7jy99+44V77yU2OrpbztOd3DzuNMwDw5m8y//mPb4ystDMhv7h3HzS5Xy2+geP42rq63n4lVewWq1YbbZ2239bvpx3v/mGhqYmn89d39TEkdOmcf5JJ7W81lPyM4QQ76UYjCZRRi/IFJVVctjk0e1eVygUpKcmkZ6axKSDbdhNZgtlFTqKNZWs2rAds8VCVEQEuZmp5GSlBaXx0KFAMJKrDgW6KsJlWebeD3YxIm8o82eriBk0nvEza7n0rs9JTohi6OhdbgWmzWbjiTffZM26xTxxyTBGHzYbgNc++4cZ4/ux64CWleuL+OjJc32uhqLR72L0sCRSkyP5+KefmO/0xdlqsL3Kyvp99QzPiyEiXNnuGA6WaVoTOGdmNrY7VFKCmrefPZyHnl3Py+9u49Jzh1CQG8t5pw7gjof+YeKYFCaP81wmNlyl5Ni5eXz54wFuumIUmmbfxXgw2q0L7GirahlckBPw45otFh5++WV27NvHu489RmpS78sh0tXUsHZgOBN3m4g2dl8svVK2lzP8fnIkm3ftYtRg906WlMREfnz1VcoqKznuiivabT/n+OM55/jjefnjj3nryy99OnddQwOTRo5k3LBhXbqG7kAI8V5IQ1MzMVG9u2tXb6S2vpH4WN88HeGqMPrlZNDPKXyoqdlAiaaypfGQ1SaTFB/bIs6T4mP7TDdDXzCZzKjCxEeUN9yJcH/jxP/44U509SamjYolZpDdW52bmcDIwRn8vX07Q0cPtgvMyLZfnC9/tJKtW7bz+nWjiR86BYBmvYkPv9/Agzcczd3P/srzd59EbHR7p4GzWHYc1/GaQiFxxIxMNmzYAe6E+EG+/ruCw0a0FT6eRLjr786ifKcpldOuOJLSNZt4/H8b0VYZiI4K4/ILhjJ2hPea6qcck8+1d65g6SoNs6Zktp8rNysKJpGIHFRq6xsD3oW6sbmZWx9/nLCwMN546CGiIrs/Br07uPGI8wlPD2Pcvu7zhjvoX24hq8rCbZfdzA9/fRe077z6xkaSEhKCci5/EZ8CvZDC0grys0V8eDCx1/pVdOlDIzoqgiED8hgywN6+T5ZlauoaKNZo+XvdNqrr6pGQSE9JJCczlZw+Hm8eqsYyPRGT2f5Q4u7+k/IXdEmMm/c9wfPfF3LDif0otqc8oNHW887X69hfUs0N/5rkcd8d23Zz6VE5xEW1fpV89stmJo7M4YtftzD/pHGMHNT2s8pktvDr2lWMH53Scj3O4tlBhVZPZqr7euZy0VrW1qezrWwjD91xPJK6/VeZqwj3tl2hVJA7ZSwXThnLuPgaVCoF4Srflq5jY8K5+8Zx3P3Yahqrojj6mDg0+l2tYlxuH2tfWVVLmki4DxoycsAS62VZZvHff/PEG28we/JkFlx2WY8Jc/CX0ooKtuapmLvRgCpwhVI8IgGzthr55LBoVqxfz4zx47v/pNiF+LeLF/Psu+8iSRJTx4xhwWWXkdYDVjCEEO+FFJVWMHlsz1teOZTpDlEoSRJJCXEkJcQxZpg93t96MN68uKyS35auobHZgCpMSVZ6MjmZaeSkp6DuI6EaJRUiURPsXe7+7557sFqtHD1zJgsuvZS4mLYisjNi3GyxsGfVgzz+5T5yUyIYkptMaa2BO57+meXrDnDK3BG89sDpWMJLPdpmtdEibuSitRjTx/Det+t45OZjuemR73jg+qPa2iPL3Pvcb/y5di8zJmVwi2t2pRObtlVzycnuu1YW6/Q8/PYSbrxwJhFOItwh6B0ie1FZW+F1ZJZvy+7r6xLdhrF0xKD+8Xy88ALuff43/lpj5forB0O6ZzFeoashPUUI8WAQyHrt9Y2N3Pn005RVVvLgjTcyceTIgBw3VGhrapAVEif1iyQ5iC0yvrOBRqsN2vmGDxzImKFDue6CC9hfUsILH37IjQ89xPtPPBHyUpNCiPdCdDX1JCeIBJ9gUlxWSU4QOmoqnUooTjpYQtFstlBWWWWv1LJpJ0aTmUh1uN1rnpFKZloyYWG90xvTEWXlOsaPGBRqM0KCQ1TXN1u4+bH13H9OAZMHJ/C/77dx1rWXcd95g5h29INt9ulIjDswW2ws2VzF58vL2XSggbT4cM6cmcl5h2dx5/sV7ChtRq3WM7hfKr+t2M3RMwaRfDCstllvobC6hnynKic2WUbhVFXk+z+3M3JgBlERKiLV7ZMsq+uaWbGhkHeePYKLrl/CVRcOIzqq/bjGJjO79tUxfkRbIW6z2XjrzZt4b0kpl545jaNntN4f3kS44zVfxbjjOP4I8qy0OF79z2l88P16brnvH847vYAL5hW0zoWTGK/QVTNlbPd3eRTYk2JTkuIDcqzv//iDMKWST556ymMisaDn8fqDrZ+Xk0aNIj42ltsWLmTt1q1MGjUqhJYJId7rsD/Zdy1EQuA/JeW6kJUZU6nCyM9OJz87veW1ZoORUo2WPYWlLF29CYvVRmx0JDmZqeRmppGWnBDyp/yuYjD1zYRkZ+H8zu8lTB2awJFj7SsDd541kJU7arj/w13M3n8vN150J5EREciyzPa9e1n8ayGbDtRjtso8dMFgMpPsuSSlVQa+XFHON6sq6J8RxRkzMnjuv+e3CMT6RgMHtH9Q31jHmNwU5k4diNFk4Y6nf2bKhCQ0lc1s3lZNWJiCRW9c2SK++w/qx5rdOmYMS0TKm8Bf733LvBmDGTEwndlT+nPZ3V9wzXnTmDXBXo1EW91ERkosg1NHMGLgDiqLYpg+Lr9daMry1eWMHZlMo/Q+sbQmPq7e/B7f/lPJB7eMJXtc+yVtdyJ87fJ0JsyoaPndHzHeGRQKifknjWfQMJnXP9jBO5+8ypQJ6Zw5dzJTRuciYRfjNXUNJCZ47x4q6DqVVbWkBahiypJVqzj/xBOFCO/lTBs7FrA3YBJCXOAX9rrK3e+ZFbTFYOxZ1TuiItQMKshhkFMVgPrGZko0lWzavpeKqhpkGZLiY1vizZMT4nrNA5zJbOmTiZrOIry60cwXK8r58NaxbcZMG5rIZ89fwmOv/8mp115ORmoumspK1OFW5kwdQFaSiU0HGkiOC2fzgQZe+bmIrUUNHD8pjdcfPoeCnPYxkbHRamaMG8ilZx7RklhZ2rQTi6oflTo9BXnpXDl/GPc+vpbfN67iqHFTATj3uLFc8O+PueKyE4kCcjPjKa20B5rfeulh/Lp8N8+9t5zXP1/NC/ecTF2jgbgY+8NBckIUdY0GwJ6s6SzGf/uzlFOP7QfQWoVEXsLO/TqmDU0gK9m3ZPW1y9Nb/u2sGF+mifE7TAUgPyeW/942iepaI3+t1PDI67+RlKjm+stGkpG2C5tcIJqBBQltVS1DB+Z1+Ti19fVs37uXqWPGBMAqQSgxmc0AxESFPg+r733T9XIKS8vpJxI1g0qzwUhkDxLhnoiLiWL4oH4MH9QPaE0GLdFo+WfDdqpq7U1MUpMSWsJa4mOje6Q4t8fkhz6JJpi4hpW8vaiEYyakkpXUVnRKeROIAx66cR479mvR600kxk8iPyuB7fsqueaBbbx47ylsaDRw+xs/c/386Tw5a2ibWGpXJEkiKT6KRkUhjQeb6ikUErOnZ7UZN21CGqs3aBk51B77nJMRz8SROXz9+zbOO2Es82YM5tYnfiQ7LZ6n3llKU7OJC08ZT2lFPa999g9HzxhEs8FemUEVpsRkbs0Oc4hxi8XG9l01PHxHa5KoowqJ0WQhKrx9GJa7ZE9X3IlxV7rqKXckaDrbk5Sg5pRj+3Hi0Xl88cN+brh7BWefPIjonv+Rcsigq6klNclzPoKv7C4sZFB+PhHqvrdS19toaGpqqee+auNGcjIyyE5vXVVetGIFkiQxfODAUJnYghDivYzSch3TJ/Tu5JDeRolGS26W5zrCPRXnZNDRB5NBbbKMrqqWknItf/2zkbqGJhSSRFpKIrmZaWRnpPSISi2l5Vqy0/vOyo+rCNfWmfhmVQWf3T6uw/2GFqQeFH1NWG3x3P7kz9x+xWxqGvTc9fQvLPz38UwYkd3hMTT6XTTrQfIgDJ2ri9TUmcjLjqa2zsim7SuZ1H8MJ8wexsc/buS8E8Yyekgml5w2ka9+38qDNxzNgLxkblv4E+rwMP5cvY95MwfT0GgEoLHZSExk+5OGhSlITYnkQEkjg/u3jeuNilChM7Yv7eAqfjuLQ5y7CnJ/vOKe7FAqFZx10gCmT8rgpTf3Ex5WxMwZ/2uJkXdcg7/dOQXeMZutASkVqa2uJi1ZVHLqbgrLyqiuq0NXUwPA/pIS1m/fTlJ8PPlZWazfvh2Acq0Wm83W8vug/HxioqL46PvvefyNN3jq9ts5YsoUfvrrL/5as4bTjz6aUUOGsHPfPl777DPOPOYY8rOyPNoRLIQQ70XIsozFauuTS/ahpLiskqEDur6s2RNwiO60lMSWmHer1UaFrprSch2Llq2lsVmPUqEgMy2Z7IxUcjJSiIoMbt360godY/tIoqarCN9Z2sg97+3ijOkZpMW39bxJeRPa/O4s+hatX0W42kZMZDh3Pf0LT91+AuOGef6Scd5Xp4UUlwI1ruX9zGYrPy8pZsyIZD78cg/NBiv/uTaB+Bg1YWGt+QjnHDeGc45rXbp/8d5TuP6hb2lsNvHql39SUdWAzWb/LHNdjHGI0XNPHcDClzby+D1TSIhrnYP+uUn88JcVct2XPJuZ2cgyTQxHZsksKpPaeMD9wV3oiut8dCZcBSAnM5pzTh7BHyuLuH/hWq6cP4wtO2rISKtg6oR0vxoCCbwjy4HLB9DW1PTKhj29jTc+/5xvFy9u+f3ljz/m5Y8/5qQ5c3jg+uu55I472ox3/P76gw8yceRIkhISSElIIP5gdan7rr2WT3/6iT9Xr+aTn34iMS6Oq845h4tOOSVo19QRQtH1Iqpq6kkR7ZCDTrm2itlTx4bajG5DqVSQlZ5CVnpKS6UWi8VKubaaknItm3bsRW8wogoLIzMtmZyMVLIzUro1Zt5gNBHVBxI1XUW4wWTlxle3c8UxuZwyNb3Nto5EOEBVjYGqGgN3PfsT99w83mcRDqDTQYZTxJu7GtyN9XoiI5WMGJLInBlZfPjFfubNHMQ9z/3GqEGew+UiI1Tcectwrlig48+VGgD2Vm8jLz+MbXsrmTO1/dLwvNm5VGj1XHfnCm67dgwjhyah0e9i8qiBGAwWflq6k+MOG+rxnJ3B3zjyzlRVcVBdLXHhWXk8+raee5/eREZ2AvUVhUwZn4YkSX1SjNtstm5JMK9vaCLOx0Zs3qiqrSW5hzaFOZR44PrreeD66z1u3/D11x3uP2/mTObNnNnyuyRJnH3ccZx93HGBMjGgCCHeixCNfIKPLMtYbTJKZe+uQOIvYWHKliRPByazBU1lFSXlWtZu2YXRZCJcFUZWWgrZmalkpyUHpMa52Ry4mr89GXelBlfuqCU3NYJTp7X9O/cmwgGmT0ynutbIvNk5xMaE+xWqoasCRzlkT41wIiLDmTMjmwPFDfywqIiX7j2NjTs0bNqp4f5rj/R4bI1+FxFqJQ/fMYlb/vM3j941mZhoFXnZMSxdVQRMd7vfhWcOZujABB5+dj03XTmaSWNTUSoVPHLzMVx1/1fkZyUyYmDrw4rDm+7qFfcFT0mdvtAZQd7YCJuaYjj+rImA/XPmhYd+5Kv1Nk4bb7/3D3kxLi+h6WAX1h/+3MGB0hrU4UrGjUpm+sR0poxPIy629fOks3NRWV1LWnJCQEy2Wq194rNJEFyEEO9FFJaWc9SsiaE2o09RU9dAUrwoMQYQ7qaMotFkpqxCR2m5jtUbd2A0mVGHq8hOTyEn017jXB3uX5kvjbb6kO+o6U6EA9Q2mclK6txKQEREGGec0L9T+5pMEB7ecTfK4v06Fv1VwvDBiTzzwDTS42O45MnPufXSw9zWDIe2Dww5WTFMGZ/Gpm3VFOTFkZsVTXFpU5sOlK4PD5PHpTF2ZAq1dcaW7UMKBnPP1XO5+dHv+fL5+US7iTPvjBh34CzGu6u6is4QRrxTXI4kSeQPTKNwr5ZlmQOZmdl4aItwYMd+LTc98h0jB2Xw0I3zGFqQSpPexNI1B/hhxQZeencbQ/oncOpx/Zg8rvM5OtqqWtJTAhNOIklSQENdBAIQQrxX0dhs6BGJdH2J4rLKXpmoGSzU4SoKcjMpyM1sec1gNFFWoaOorJK/12/DZLYQoQ4nOz2F7IwUstKSCe9AnJeWaw/pjpqeRDhAo8FKTETbj2VfvOFdiV+2WKHaFMYyTWsegDsBmpmTyGnHF1BU2sgNd69AGfY3Z80byxFTBrg9rjs7o3Jy2LzjACcf04+kRDU1TgLb0zXtLjWSPabtg9mcKQP48c8dfP/Hds4aYQHs8+SctOksxl3xV5z7irsHGdf34o/CaMLCTe3GVWpqGTu5AOi897c30dhkJDUxmlWbiqisbiRSrSItOZpJI3N54F8nEh0VztI1B3ji9T95+OZ+ZHay1LO2uo6RgwsCYrMECBkuCDRCiPcS9AZjj6pj3Vco1miZPsF9m22BeyLU4fTPy6J/XmuMssFoorRcR1FphZM4V5GVnkJORmobcV5aoWPMMPfirrfTkQgHMFlsqML8C4NyJ/589c4u08TQXGslIq61EolDpLqK8dj4SI490+651lUbqG8wMWOo7yt0yzQxpGZYWL6omWWaGCanWNHrLciy3GEJzZi4CBrr9UBkm9fPPnY0j774M2cOH9dmf3di3BV/POVdbQDkfP6ZmY3o62xExLV9j5ubjFRrG8nKS+LMAed3+ly9iYkjc3j3sbOprG6ktLwOvdFCSUUdf67ex1NvL+W1/57O0TMG8eOfO2hoMnb6PPWNTcTGBMaBJSkUwiMuCDhCiPcSikoryM8WntlgU1PfQKIITekyEepwBuRnMSC/VZzrDUbKKqpaxLnZYkEdrqKsQkeFroas9BS/w1p6At7EdkeowxTUWMw+j+8olMRb7LJju77WRlSCXRi6ilNPIjQlKYKUJM+VdFw93I5zpaTHUVvdjMlo4Y8DESCBTQaliyZ2vq7ktDi05fUs0+QxM7OxJZRl4sgcbLLM2r31TBzouX25JzHuCXcx4oGsOZ4t6UnoB3mZRmRZZtuuWv74cT/jRiRxzpD5nTpmbyYtKYa0pNb356xjRvPDnzu4/qFvefuRM9ldpCMjxff3zx2B6pUgEdgqLAIBCCHeaygsrWipBS0IDlarDYWk6JENbw4FIiPU7cR5Q1MzH3+7mGKNln82bsdosovzrHR7KcWstORDamVIlmX2lTfTPyMKSZIIVykwWmwt213DUjzhKhSdRaI3Edpca2N3XDi2ToRr+JIQ6nx+pVJBXEIkdTVNLPttO0cdloNS0fF5BwzJ4IfP1nD4MW1XpiRJ4uyTpvDp0i3thLhrXXHHw4izLc5e8QkzKvxO1PTXUz4kXMviZdVs2RKJ3lyG2WqiqKQRWYZ5R+Rw9OE53g9yKCEd0f41eQkAxx8+lN+W7+bSOz8nNTGa4QPS24/1AaPRFNCHeREjLugOhBDvJVRU1ZCWkhhqM/oU5dpqMlJFzdhgUlvXyKCCHA6b3NoFz2A0UVZZRVm5jjWb7Amh4aowMtNSyE5PISs9mcheWurwoU/38uXKch6aP4RjJ6SiDlNgMtu870jHAttTYxp346KrZWypwYuZtlhsrFm+l4Z6PVfc4L4euDM5BcnIssyurWXMyrILbodX/PjDh/LC+0vRxgzBdb3QXZOfjrzjna053hHNTUbW/72PnWv30dRsZtTQJNLihzJiRCJp0TmkJ8cwekhGj37Yr66tZfGqVaxYvx6A+NhY/nXuuaR1Rz1t6QiQl2C2WPlj9T4kCe66yo1g9xFtTR2pSQkBMy9CraahqSlgxxMIQAjxXoHVZkNCQtGDP6wPRYo1IlEz2JRW6MhKb5uoGaEOp39uJv2dEkKNJjPllVWUVOhYt3UXBqOJMKXS3oQoPYWsjBSig9yEyF9+WF3Jur113H/eIL7/p4JjJ6SiN1nbeMRdceeB7ijWuSNBvqhMgoPevbUrWsslBkqQuhO8tdVN1Nc2s31DMc/+ZwoRau+l4CRJ4oSzJ/H52ys4fNAEBvZr9X7HRqs55rDhvPXlGv592eE+CVpnMd6ZqioOOnrIaajXs/SXbWzfWMzgkdncft1YBhXEARK//xrDBUePBWDzrnJ+WbaLYQPSyM8KsqPloPfZk2faZLbw2mer+fjHjUwfl8/cqQWow5Vs3V3BRbfdwD23jKEgzx6256h64xZ3x+8I6Qh27PsIgDOOHsW0sfn+7e+EtqqWlCTPYUv+MnXsWB588UVuuPBCt9tlWWbn/v2YzGaGDRAr2ALfEEK8F6CprDrky7n1RIrLKkU4UJApLdcxaoj3EnzqcBX5ORnk57QKSLPZgkZbTVmFjk079tFsMKBUKEhPTbJXbElPCVjSlid8jQ8v0RlY+NU+Xr56JNuKG0mJC2fTgXpe+6WYxy4eAvgeluILnsSmZJIpr2ormJ1DNJzFpj+VWDx5nbeuKwIZho/LJTfb/Rh3++YWpHDUyWN57PmNvPDoDMJVrQL+sjMmcdZNH3DmvNH0zw3OClZHIlxRspf33tzC3MOyOey2Y7hk7GUt2/boXiE2yv61qzeYue7Bb5g4MofHXv+Txxccy6RRS/wXrp3BIcId/3c+p7yEssp6rn3wG/KzEvniuQvaxHAfOW0QgwtSuePhxdx69WgmjG7tNVBaWc/7365nX0kVpx05kjlTB6AK8/+afltpT868+dK7Qer8ape2uo7RQztX0tMdowcPpkmv58k33+SS008nKd4u8mVZZumaNfzvgw/QGwxERkRgtli4+rzzAnZuwaGLEOK9AHsjn87FyAk6j76PdHfsSTQbDERHdc6TrVKFkZeVRp7TKobFYqVCV0NpuZYde4toaGpGIUmkJie2hLUkxMX4HRpgsVqxWq2ow1vj1b2JcIPJSqFWT1xkGHe+u5PLj85lSE4Mv2+qIjNJzcd/abjsqBwmzZ3rkw1dqZUNdsGdQhPhWL0P9gNnIe0aR/3XL1sBWDDffy/nyPF5LPlmHY2NZpISW4V4amI0JpOVdB8T+vxJ3HSHqwh3PKAYDBZeeW8HG7bouPum8QwfnEhm1GVtd248gfSUfwD4/o/tjBuezcJ/H8+aLSXc+sSPPHD9UcyaQPeKcWcR7vzawbCQ0sp6/u+eLzj/hLGcd8JYt38bx84aQlhMDY88t4EhAxOYO6ucv1aWs2lrDaceOYJT547gs18289z7y3ni1uMYPsA/MX7NeedxzXnntfn76gxVNXWkJAbOI65QKHj/iSd44YMPOOHKK4mOiqJfdjba6mrClEquOf98Zk+ejCRJ/PDnn/z3hRcCdm7BoYsQ4r2A4rJKJo4aEmoz+hQGo4kID01KBN2D2RL4jpphYUqyM1La1CW32mxoq2oprdCxbPVmahvsQio5Ia4lrCU5Md5jKNjfGzdyx1NPAfDOo4+Sl5npVYSbLTZOf2QdCkmitsnMKVPTOfcwe5JqeY2R/NRIlu2o544bT+vUdTrEob+dJGMwUUXbVYKueMNdRbjj3yOzZHQV9dhsMkedPJaEOP8fcK0WG816C/HxbfctLq8jOTHKbWOf7mZ6egPbdtWydFU5f63UMG5UCp8/cxENUqHbWuAVuhoy06YAO/lp6U4uOc1e/nHiyByevfNEbnzkO+688giOnEbAxXhldTUr13/Eyg2FGE1WkuMjSUqIItnxE1/Khp0a3v16HVeePYVzjhvT4fFGDk3izWcO5+clxXz5w35mTMrg+stHEB1l/9wcM3EUy/4p56r/fMGV84cxZ+Yun+ujd1WAO7BYrYSFBfYzJTkhgXuvuYZ7rr4ajVbLgdJSkuLjGZSfj9Lp8+v4ww8nKzWVS+68M6DnFxx6CCHeCzCZzb2yjFtvplhTSU5GqveBgoARrORYpUJBRmoSGalJTBhpj221yTLVNfWUVuhYs2knupo6ZBkS4qLJSk8hy/oDafE2lAp47+OtnDoplvjoMG5/+FZe+NcIEqJVbUJJ5KK1bc65ZLPd6/36daPb1c2eMGk0D76ymDOOHkVcTNfi2t15xx2i2x3ZVXVE72kGWWLr1CyP47zh6mV2VwYxt7qBMJWSm87KoDPUVDWSlKhGqZDaxCTvOqBjUF5wGkAdmSWzY1MJO7eUQlMDL2qaiI0J57CpGTx85ySmDrLfAzGSe8FZoatm7PCB6E3T2b7vRSYMz27ZNnpIJi/edyrX/fcb1m0r4+pzjcREH+OfgU7ebrPZyoYdZSxfX8iK9YWU6xqYOiaP6WPziYkOp6q2meo6PXsKq1i1sZiqumYyUmJ586EzKMjx/neYGTkYDbs4eV4/Tp7Xz+2YmZMzyM6I5oGn1rL3QD2XnvsSObH/8u+aOonNZuvWvCpJkshKSyMrzXMeUWxM11ZfBH0DIcR7OLX1jcTHij/mYFOi0TKwX7b3gYKAUVquIzs9NB01FZJESlI8KUnxLc2EZFmmrqGJ0godW3eq+HUT7C3XU2vMxqYIZ+aIaCpqzZz7xAZeefBsnIMtGpJGsGHpUrKTI+ifEcVrvxQ78iLbiHApbwIn58pkpMYyaWTb8nXOrd/d4U38emPE32VIg2WQuyZWfAn1ODJLhqxsbnv0NCSpY++6p8omtTv3MH1SRps5sVptvPvNWs44un3bRU+1zJ3xNGeOhxfnxNXZaRa+fn8N5SU1zD8ln4y0DDLSokhPjfTZ09ukt4derdr4DoPyU4hy8eIPLUjl02fO59l3l3HERa+RkvgBGSk5ZKSmkpmaSkZKiv3/B/+NjY5u3VleQrGmlhUb7MJ77dZS+mUnMn1cPnddOYcRg9IJU/rXLCoQFOTF8tyD03nk+Q3c89gabr/ueYakX9ft562tbxQ9IAS9AiHEezgiPjw0aCqrmOVUQk/Q/ZSW6xg5JDCtqAOBJEkkxMWQEBfD8HAj7y4uoVJXy4PnDsZkjaS4Wklu5nBmKw088vI2zj1+GNkZEehqa7jrmR8ZkJvEvsLdHDshjaoGM9ce3zYu2uFBlySJqWPy2mxziEjHv66l+NyFgDhw9Yo7amS3uz6FjM3W/ZWYOhPi4jrOZLLy0p8lvPbAmW1e//D7DUSqVZw8d3ib1z3NlTPuRLin1QObxcrnb69ApVLyxhPTUIe3hiD4KsJb6k/LS1i9uaTdg5eDxLhI7r/2KO66cg6V1Y1sKd2GuX4cGp2OXQcO8Ofq1ZTrdGgqK5EkiYzUVDKSJYrKa2nWm5k+Lp9jZw3h/muPIjEu0u05gk1sTDj//fdE3vp4Fzfcs4J7bzYwfeit3XpObVVtQEsXCgTdhRDiPZzC0oo2NZUF3Y8sy1istoDHKws6pklvICaqZwgHdxyo1DMyP4Z+aeGAlcGZ9iRHKW8Cp133PhZbPpVVCn74o5IjJs6gICeR48dW8t7i3ZwyLZdTp7WGZHiqiOKpQY4/Itzxb0ce8hF/lxEWI2Npdj/G10Y1nkSuu/39qbrioFKnZ+eeWr5fVMS0MQUMyG2tHtWkN/HGF6t555Gz2qwydEaEdxS+Y7NYqfplOWp1GI/fMoKwsFavsq8iHKCuoYn4mBogjTVbSrjqnKkdjleplGSnx6OISwYc16QA0oF0ZHk4Tc0W5MY0yrUNpCXHMLhfKgovDZI84TxvHZYj7CQrK+MYOmci/fN3cvtD/3Dtpfcza0qm2/M5Qrva/J34GTNfWV1LbqYoPyvo+Qgh3sOxh6ZEex8oCBh1DU0kxIlwoGBisVhDsmzuD0u31vDyNSPbvS4XrWVwQTIGYyNzp+Wwdpue2oZqzhqtR1uvIC1+ENoGJR8st19fUmYqWQ31ZKWrSUkKb+ks6UuXSmd8qR/eEaooG+amzs+5P9VH/BXhNpvM59/v44vv9zNqWBKHjx/Kxae0fXhZv62MjNRY8rISWl7zZQ59EeGOkBSb2cLOb5ajigjnl3uf6dLDeYWuhvQUNXqDmZ0HdIwZmul9pw6QJImYaBWZKakM7hfYfBZvYVEO3DVN8kTLPZCZTV52DP99eh1bd9Zw9skDyIy0v+e7C3Ws3lLC6n+2sausCYNlLSmJUcybOZhjZ9WRnXGKz9egrapl3IhBPo8XCEKFEOI9GNPBDoI9uevaoUhRWWWbEniC7qdcV016D+5iarPJKCTYq2liQEb7WuSGWh2REfYv/fknjeOUq99k/qQx5KdFkploAyz248hQG59AWYWBDdsb0FWbsdlkoqOURCdCaiqkJIPKQ262Q/w6i0nneGZ/4sTDom0YauwnciRqemrm05WSf/6KcIPRylMvb6KqxsAnT11AZmqc23ETR+Zgs8k88OLv3HnFEahUXVvBcr12q9mC7qdl5CZF8M7dT3d5haxCW01e2H7Wb09kaEEqkV6qMrkTuI73oTOrC/7gj0fcHzHuYGBBPM8+OJ33PtvNZTf9iSz/ic0GmamxTByZw7FHT2bBwHSiI8M5UFbDT0t3csG/PyEz4xvuveoehvb3Xhu8WW/s0StsAoEDIcR7MMXlWnIyReWOYFNcVsmUccNCbUaforRcR06IEjV9QaGQeP7KEVz14hb+2lLNhIHxmCw2NNVGyqqNrN9bz9kNhchFdcQD58/O5qWfCnn0oqFtjyNBUv0mkodMYNSQ1kSyxiYLW0rqKCuDTZvAbIYwlV2Up6ZASipEu+h/V0+ucyMen65JJWMzd61aijf8EYxGk5W/Vmr44of9jByQw8L/zkUd7vkrKkIdxlsPn8nVD3zN939uZ+oM7yXv3HnD3c3ZnHQrn7yxnNi4SN6+86k2Zek6S4WuhvwMPY+8uIrLz53V4VhviabLNDEtc+ur99ob3RGO0hEJcWquu2wkV144DItFRqGQiFAr29mRlBDF+OHZXHheFkuWl3Hl/bdz00VXcoqP9fYFgp6OEOI9mMKScgYX5IbajD5HVW09yQnuvXCC7qG0XMuIQf1CbUaHDM6O5qNbx7JsWw1r99QRqVaSmahmSE4M58/OYmR+q7A+7/AsTn5wDTtLGhmS492bHBMdRn4e5DvlbJrNUFUFWh3s3Q/F1WGAAQ0KSkoSicJEMypG/K0B7F5tZ3HekSjfOjWTUVSwdWrnSgn6gjcR7hBcZZX1fPbzJr7+fRvDB6ax4OI5zBzfz6eVwOjIcIYWpGIwWoD2QtxTBRYHrnPkiG1f/P0WbDaZtwIkwgG0mo1c8+UmTp2WzkkD9R7H+RLj7tjW3Z5xX3G8l/56xgHCVUqcq/O6Plg4jhkWpuCow3NoiM3k8ZdfpSmzhHC1XcKcOeD8NsdsNhiJiAh+XXmBoDMIId6D0VRWc/iUsaE2o09hPVh7VoQDBZcmvYGY6J67jCzlLwAgIx/OGANn0HEnzSi1kkuPyuW57w7wv6tGdOp+UqkgI8P+A7BME4EsyxTug4LoOrQ7I4nCTPxgI1aLxKT9RZibJDaPzMaKosMExEgs6Altb4Jd2q0889pmNm+vZu6sbN5+5EzysxL9Po7BaEGSJI9i0FmM+5KEumNTCXs3F/Hcg9MDlrBduu5B1u+VufaEfOaN922V05ekXAeB8op3la4Icmc87b9ME0NaJgwbncMHL//JhdccgTKsfZ6DTlRMEfQienZ2VB/GJsvYZBvKHp7AdqhRoa0mPdV/MSDoPBarFaWi993nDnHuiTOmZ1BZZ+KHNVqvx/ImXByiTJIkbJEKzCkq9pLMZjKo2aWmsUiFxSARHmdjiq6I0ZQzkgr6UUMyTaixAK3iLRYjjS4eZGfv8KIyyW28ueN1f2uWu2PtJi1btlczb3YOUZFhfLdkO8+9t5wXPlxJdW2zT8fQG838uXofsya2lr10J0hnZjZ69R7PzGxkTGwNi79ey+3XjSE+LjAeVduBJ3jsixL6pyt9FuHOdDTXzmK9q+I3VCzTxLT56Wicg3mnjSMyOpyVS3a4HVtZXUtqckKgTRUIugXhEe+haKtqSRMfJEGnWFNJnih5FVQqtDU9OlGzI6T8BR4946owBQ9eMJirXtzChAFxZCZ1rWtmR9gsEqY6Jaa6gx7cPTZQyFRNjicWEynUoMZeblFPGJGYiRxiJTupyR647gFvlVl8LXPojoEF8Rw7JxeFUkIhgTo8DIVColzbwHm3fsRTt5/A8AEd91D4eelORg3OIDutbShZR97xjnjn011Mm5jOnNFTOnFF7ZELF/LH5mpqmlWcNyoKR9KuJxz2ukvKdcbT3Pckz7ivD5e+vu7M7xoFsTMnsPy936jJyOXMAW23a6tqmTR6qPudBYIehhDiPZTCknLys7svflPgnuIyLSOP8J6RLwgcpeXakHXUDCTlNUY+WaphSE40xxz0fA7JieGyo3K55NlN3HXWQGaN8P+Bo9MVS2wSeX9XuyRjykRgYUpcCZZmJeoqI8gyslLCGqXAGq3AGq1EVvnm8e6KGM/JjObic4a0/O4sIO94+md+Wba7QyG+64CW595bwbN3ntip87uy90A9f6/R8dXz81tflJf4Xb+6ZdeDD2hvLSrh8DHDyUq0ed2nMxVIXGPFe4oY9xdf7yXHw4k6LpqcGSPZ98tqrkiM4dXDL2gZU1PXQGKC6Kop6B30vvXgPkJhWYUooRcCmg0GoiO7z3MpaE9phY7sjN4vxP/v+c3UNZt59tsDLNlU1fL6BUdk85/zBnPfh7t59Of6ds18PJWp87ZU78BT1ZOtU7PcbJMYMaMaWSVhyFPTNCSCpqGRNBeoscQqUeplIouMRO/QE71DT+QBIyqtGUWzFeT2IsmTcOpMEqFjHnQ1TSxfd4DzThjbZnuFroEtu8tZtvYAL360kmv++w23XX44o4e4r8fti6DNjBzc8vPFN+VcctpE4mJc/v7lJX5fi0OEbzpQT3WjiZioWNLj2wpxR9Madzjmr7MPOT09TMX1vnaIa28hT67b08YMQFJIVG7ax5VLP2x53WaTe2W4m6BvIjziPRS9wUSUEIRBxWA0oQ4PbQJbX6SxWU+sa22+XkhGopojx6Rw/MQ0Fry5nfJaIznJERRbUvh5mY6IyAgG5iW32cdbmTpXfI3NdifOHTHgkkVGDnM5TpiENU6JNU4JjiROWUZhkFE22QjXWVDqZbv3PKzVe25JVhCmDlxis0a/iw++Kuf4w4eSnhyDLMu88OFKfvxrJ3qDmczUWOJiIhjWP5XHbzmWccOzPR7HHZ48xTv3a9myq5xHbjrGvWF+eMadQ5W+XVXJGTMyMVslOqjE2CGeuqQ6e5B7UgWVruLOM+7pvpckidxZo9n362rSxgzgs70fcFq/czvdXVQgCAVCiPdAGpv1xEQJER5sSsq15GSIVYhg0lsTNd0xODuaXWVNXDw3h5euHslbi0pYtq2G7Dwll542kcMmFrQkX3fUrMVXJsyoaKmM0pHwdkXZZMUa5cOcSxK2yIPJoU5fFZLFLs6VzVZKt1iwGGWQQB2jICpewYyBBqxW8LfgiMVi45Nv9/Lj0mI+fvICzGYr3y7Zzh//7OP5u0+if06ST9Vn/BXhAK999g9TxuSyc7+Wcl0DZdp6yrUNGGsqmDwontmjkolUt/Vgu0vWdc0X2FfRzFHjUtjrIV9XLlrbboXEEZ7iWu3F3wTZUIeodCbMxpWOrtlx78tyGkrL3+ir6iE7jg83f0BqwhCP+wkEPQ0hxHsghaUV5GV3nKQkCDwlGi3987qvuYmgPRW6GtJSDo0qNUNyolm+rQaAoTkxPHbx0HYiCwIjwh04xLav9cMBlE02rNG+Pfy4C41YVCZhiVcye1jrMWRZxtgoo6+z8fv6cGLMJmw2CA+HlBR7Y6KUFIhys/BhMln59c8SPvtuP3nZ0Tz30HT+3lDEk28tJSpSxTN3nMiA3OT2O7qhI+HXkTCdMjqXRSv38MSbf5KZGkdmaiz5WYkocpL4fs1+Xvt1A09cOqxtV1UXL7mzCNcbrXzwZxm7y5pIjIklSe8+Ptzd/eGMtzroPdkr7qsI9+Ttd4e7kpwTZlSwbpMV5cFOpYYGm6iYIuhVCCHeAyksKWfSGJHxHWzKKnTMmDgy1Gb0KUrLdeRkHBrdY6cMTuCpr/Zjtckou2lp3JNn1J+OmjX71URP6ThxsKPYZHfbJEkiIlYiIlZBYg44mutMSmpEV2VvTLRnLzQf7GMTHwfxcVa27Snn+993M6BfDLdfN4b01Ciee30LNdU2Xn3gNIYU+HZv+Cr6PInxM48ZzZnHjHa7zznHjeHrRVv5vxeWc+tlh3HcYU6fzQ4x7hRHXtNo5tqXt5KZpOa9m8bQaFKTHm9tc0xvAtydN7kzXvGeSEf10T3RUU18c6P9pgqPsfchMNTbSBuQ0HkDBYIgI4R4D0RXU09KYnyozehTyLKMxWpFFSb+JIJJabmWoTM6FiW9hfQENemJajYfaGBsf/edWbsric5bUp9D8Kxdns5oylmzyl6RyZ2A70pJQldWV8eABKRAeIpdns/IaOSfdTW8/F4xBTmpnDxnBpGRKlb/o2fTjhLGDh3ExVePJCVJ7dM5gpGYeMqRIxg2II0FT/zAP5uKOef4sQzpl2IPlTkowqW8CWi09Vz9+NfMnTaMq2eGI0kSv29RMCzb4lV8u+IuRKW30Jn3xCG2ne/JjgS4Y2zN3lqi0xI46mC6gKFBFh5xQa9CqI4ehsViJUypEJ0dg0x9QxPxsb3ry+5QoKFJT1xM70/UdDBreCJ/ba1uJ8RXbSrCbLYxYWQBtbb9XTqHwzPaGcEsIeO819rl6W2ETyBFuDtmZjayfouOp17dwB3Xj2PsiGTq6k28+PZ6DhQ3cdk5Y8iKG8jfGxqobagGGWKjw4hMqCU52R7iovZNn3uks7HTQwpS+fCJc3nzi9Xc8tj3SEjMmtiP2Gg1qjAleoOZrxZt5dLTJzL/pPEt+2k3ajh8RPeFGna1nnug6UiE++IN9ya+HTju26bKGkYMaA1vs1pkItSivb2g9yCEeA+jtEJH1iFQU7m3UaSpJDfz0AiR6C1YrbZuC+EIJs5NfY6bmMblz2/mvMOzSIkLRy5ay3JtMvf97zf6ZSVy25M/cdnpE5l3TFyXKjt0VnhFYaYJzyKlO0Sdc9zyus06HvvfBu66cRyjhyXz99oKnn9jK7OnZ3LzVaNRhyuBCnIGte7f1Aw6HVSUw9ZtYDKCpICEeHvceXIyJCb4nxzaGWKj1dxw4Uyunz+DHfu0rNpUjMFkRm80gwRvPHgG/XPb1oq3WGVUbtqwH4p0dnXCV/HtwPnhMbq+hvQBeYB9ZTMnOq9TNggEoUII8R6GvZGPSNQMNsVllSIuP8hUVB06iZoOMd4/I4pTpqaz8Kt9PHqR/X764pul3DB/BifNGW4PXfjP1wzMm8mgka1dFj2FH7hLvnMd5zqmozCGGDet7V294oHE2ba1G7U88dIm7rlpPP1yY1n40ia27arhjuvHMnKo50ZH0VEQnQf5TvrKZoPaWnvs+e7dUFNjf02lgqQku+c8OQViY6A7FhclSSIhq5Z5WW2bxmRGthfh3f2w2VO84f500nT2hnsT4SP+LvNYK//ILJnnS2uZe+IYAI7LPJ1F+zzXZxcIeiJCiPcwSsq1TBs/ItRm9DmqakVcfrApLdeSfYgkakKrGP+/ebmc9eh6bn9nBxMHxrNkczV3nlUHQGZqHIdN6s/uoioGjfR8v3VU/cIh2j2N6SimOBYTpXTccdCTV9wfwe883mC08s6nu1iyvIx7bhpPU7OZq29fxpTxabzwyAwiI/z/GlIo7II7KQkGOXnPTSaorgZdFRSth4ZGQIbIqIOVW5LtHnQNvoWn+OvhdR2vq4KIWAD3TYf85VBJ2HTgLMJH/F3m0z6Oh8Yjs2Sam4wY9SYSk6I5c8D57CvWkJqU0B2mCgTdhhDiPYiWhEGVeFuCic1mQ0IScflBprRcx5xp40JtRkCR8hcQWbiQN28YzdKt1fyzu5ajx6UQGd4amlCQk8jqzSVkRk5qI9yCUXouK7mBPVVtvba+esOdhbe3BwVnFi8rZenfGk46Op9X39tOs97CjVeMYvyowIfghYdDRob9x5nmZrsortTCth1gNEBEWBlJ8SrSU9RkpIaTnhyOSuW5zntnqK6C5KTW43W1rndPFOGh7OJZUVpLelYCZw2yt7fXVtWSmiQcKoLehVB8PYjq2gaSEtxXWxB0H5VVtYdMiERvoqGpmbjY6FCbEXCk/AWkFi7ktOkZHD8pjWe/3c/hd6xixMADnDR3OEP6pfLce8sprahD0YU/d09ecW+e6gkzKr2GA3iLFfd0Dnf2REWGkZMZTbm2mbNPHsDUCWlB73wYFQV5UZCX2/qaLDeiNhVQrjWya38zy1bXYj6YtxAR2+o9T0iwe+A7wlO4UFV1W499oAR5T8FXEe4tSdNXb7grB/ZUkpXX+mCpraplcEFOp44lEIQKIcR7EIWlIj48FBSVVZKXJTpqBhOrzYbiEF6BkPIXgLyE/735F8VNan5783K27K7gm9+38sw7yzCarLz++WquuLRriWW+lrU7Mkvm9wMysso+5754wf1J3OzIQz57ehazp7eP8XWIUV/EnLe4eNdjOujo2JIEJvV+RgwazAgnsVzSuIuaWnv8+Y6d9lh0mwyqMHsoTHKy3csdFwfLy93Pv8PefRoDkydZ2m33VrnF2W5f3+NgNvPpjAB3xd8ETWh731qtNjatPsB5Vx7W8lpdQyPxcaL6laB3IYR4D6KwtIK5h0hN5d5EiaaSow+bFGoz+hSVuhrSknvnKsQ/i+7m21WV3HHmAKIHTW7d4NRl0fH7+u0fs+CSWSTFR3HYxAIOm1hAXYMBvdFMckIUOvNev8/f2ZrSyiYblmj/Sos4vJcdCfLuFoC+Xq87YetLm3XX7Uplazy58/mtFpnqehul5TYMO20Ym2XAgFIlERmnIDJOIiJegSqiNcxNtsHKSvcrF87ndbbdk709JSylKyK8M9fgKVFz5+ZSElNiSM1oDUWRZQ7pB3zBoYkQ4j2IhqbmQ6qmcm+hsdlATFRkqM3oU5SW68jO6F1lOmVZ5pVXb+DrvyvIS43gmcWN3DXIeUDbludm0yL2FlUxtH/b1Zb42AjiYyMODvLPhq40dhkaZmV7JxtWdeQdd9jkryAPZGxxR95lX8S4LyjDJKKTlEQntX2YsZhkDPU21hXJKPdYUJjsXUuz4iWMzTYaKq0sMUajUkse5ygQ9rkLVepszXR3dFcsuLewFHdVU2wWK3/8uJl5p43nzAHnA2C2WAgLC0INS4EgwAgh3kMwGE2ow0UTgmBjNJlRh4s/g2BTWqFl9tSenagpyzI79+8nUq3GJsu8/d5/2VbcwPs3jyE8TMFZT27hxdiVzJk6gMxUR7D3T0iKWUSG/42kkEhJjGbDjjKmjc13ew5/RGJXuyvq62wcNl5CGda5yhvevOMdVXLpLL6UdAx1vPUfOgWgAJcE0f01FvrFy+jrbVSXWLAYZfYSRn6ypU2IS0SE52M7rt9dub/uKjnpjlAmZLqjfN0uUtLjuP34W1peq6qpJzlR5FgJeh9CgfQQikorRHx4CCgt15KdfuiU0Ost1Df2/NWfV1+7ga9WVqCQ7PHEh49M5o3rRhMbFYaUN4H/3T2AL37byu1P/Ux1XTNyiz59G3W4kgWXHMYtl8zisdf/5LUHTic1qXOJqYFqb26z2L260CqmOxLkzjG8zqLPF++4O/wV6YFs6x4or7g/KCwyhREqDh/Y6qWVZRmzIZz4sGYqKmD7djAY7dtiY+zCPOmgQHfXQdRbXHV3eMV7mgg3NxvQrN7Jl08/2+b1yqpa0kTpQkEvRAjxHkJhaQUjhhSE2ow+R7FGS7+cDO8DBQHDkajZk8tFmi0WPvyjjCuPzePUqelEhLdd8paL1jIwfwK3XX642/037dTwwIu/k5Eay9ihmZx98wfccOFMjpk52OcVmEAKUZtVRnKzau+LIIf2TX8604HTnxCWQF47dE1MdlSXvSOUzTaMaao2cyVJEuGREsXEMHNc6zzIsr3meXUVaDSwdSsYTVBlMBAeJRFuU2KNUjBhSjlrV7X9vOrOFvc9TYQDWAxmIsIV/N30O3lc0PK6tqqWYQNFV01B76Nv9N3tBZTrqskQJfSCTlmFjqy05FCb0afQVtWS2sMTNZUKBVfMy+X3jTqO+88adpS0F49ykecOfqOHZPLRwnMZMySTP/7Zx7Sx+Xy9aCtHXfY667eVtoxzJ3SWaWI6FH6LyiSPP57Q19uIjPP8ce+LkOtMlQt3eBO1/ojerjblCbTgd0ZhsGGL8O1hU5IgLhb69YMJ4+GoI+GE46D/VDVpA1XYVBJh9Vai9hsZTTmHJR8gcr+R8AozygYrVnPr++fumnqioO4skUmxRMWo+eClP7nptXv48c8/2XXgANrqWtGUTdArER7xHoDVZk/uUXgrVisIOKKBUvApKdf2+ERNhULBebOzOW92Nr9v1HHdK1t5/brR5Ke1TeqVi9Yi5bmvdKRSKfm/Mydz1PRBPPLqErbvrfR6Xm8C3BvOY5zFtb7WRmR8x58vrl0bJ8yo6FB8d8UT250C2F8bOpts6hUZu8LuApIkoY6WsCRJOIogqgZBkxyBwiij0NsIq7dSvNHWIsbDIyW+2qdmSoGRJC8x6J2h2+arAxwJm46Vmbwz5tKvoZyivVp+Xvkxez+00T9rEMMGZTFm6NCg2SUQBAKhQHoA5dpqMlOFVzbY1Dc2Exvds+OUD0VKy3XMnjIm1GZ0iFy4sOX/c8ek0KC38K+XtvDm9aPJSGwbvOssxt15yfOBV/5zGnqDmf2l1Qzr775mvSdx6k6AuxPIrsl7zsmV+job6YNVbo/vTDDFeGcIVGUWd3PdWYHptu28VUZWehbhXRaxkoQtQsIWocCSCP0OvgeyLGPW2xNEy8thm1MMenp8JWnJ4aSlqElPDic6yv8KI87z5m2+OhvS4wtKVRhDRmYzZGQ2MzMbsdlk3v3QyPUP38tt147huMl3dct5BYLuQAjxHoBI1AwNxWWV5IpGPkGnrqGpZ3fUlJe0e+mUqRk06K1c/MxGbjq5gKPHpbSJce8oTMVBZISK4QM8/517Ei7uhJ47gewax+1gUZlEdLXMzhoFR/rw3OlJjAezSoczvjbv8RVfQmO6KsaVzTaskYqWbZ3Bn2ZNDiRJsseURykYn9k6RpYh2ppEZZWRsgoDG7bV06S3ggyx0WGkJoeTnhJOWnI4sdHKgOVvOObRcS3u7uWtU7O8ljB0V0vc8RC4TBODqdmGOjmcO64byyPPb+CoN8yoVN4fPAWCnoAQ4j2AorIKxjm3dhMEhWJNJeNHHhqtpnsLPT5R86AIl/ImUFXbxN8bi6kt2k1uSgSHjUhiUFY0T3+zn0+Xabjt9AEMzvbtgaKjEBZnuupFdFvazlHORZJYdFDveBOH7sR4Zwhm+EJn8ObR9+e9cE58VTbbGJUjkeDm2P4mq3YUkuSryJckaA7bx6B+gxnUr/WelWWZxmYrlVUmKqtMbN3VSEOTFYAItYLIOHs30aQkiI316VRBxfH+GRpkImIVNCTlExW/m/XbtzN59OhQmycQ+IQQ4j0Ao8lMhFrUEA822upaUpJEck8wsSdqJgT1nM5hJgDNRit7bblERYbTPycJhcIudFzLvF1x71eo1UpGDsxg+eo6iov3UVFrZHhuLEOyo7nyhc28c9MY8lID2wzKnRj31SvuwPn1SRM02NRt48N96ZjpNuTCzRh39AQB7ikR1oHj2tzNRVceho7MkinWWomM77pHtrPdNH2df0mSiI0OIzY6jAF5bZdLmg1WtFVx7NIUU1QMDQ2gMxhQKCUiYiUi4hRExiqwptm7kXqzx3VOne/fjrzizt5wTys+ao0Na5QCS5mEPiyCxuZmXy5f0EOxWq2s3LCBn/76i5+XLuXhm29m3syZLduramv5459/+OTHHyksK2PVp5/6dMxn332X31asQKVSccrcuVx6+undeRk+I4R4iKlraCIupgcv0x+i2Gw2JCTRDjnIBLujpkOENxutfLminC9XlqOpMVOQs5dGvZGaOj0jB2VQ0F/FsEGJDB1oIjbG/lB89mm5vPvpbm6+eBYRavtHpdli5Z13vmP59houOyqX+z/czWvXjUKpCOx9FAgx7mD/2jhUWNGUxfnt2fZW3jAYMeKhbtjTGUzNMuFR7ecsFKUbO0tUhJL87EjCk5xftfBncTSGBhuGepmqQgu/7AObDEoFxMcf9KAnQmIiuIsO8fSA506Mu4akeAqRUuhlTMkKu4dfU8XIwb3vnhG0UlNfz8OvvILVam0pZuHMb8uX8+4339DQ1OTzMR9/4w1+XbaMmy+5BL3BwFNvvYVSqeSiU04JoOWdQwjxEFMo4sNDQig8swJ7R83DJgcnUVMuXEhNo5mPN8p89vNmJo7M4bp/jWHwgHiUSruHuK7exI49tezYU8sXP+xn+546YuIiyMlPJis/mfTUSM5e8A5nnNCfc+YehipMyUUXnsgHl7/B4UcfxpJdv/HRRgXzTx7fel438eK+hKX4gi9ealdiMaIjup2A8UdAd+a8gaArItxdE5+O4vADikyXw69CMd/ucJ1HZZhEdKKS6MS2DxZWK9TWQXU1HCiEdRvAcrDUS2wsVCvMRMQqDpbRtF+b64Oku1jwjnDsO4pyNmvSGT50D4owJWlJSV72FPRkUhIT+fHVVymrrOS4K65ot/2c44/nnOOP5+WPP+atL7/0ery6hga++u03HrrpJo6aPh2AZoOB97/5hgtOPBGltyWdbkYI8RBTWFrOjImjQm1Gn6NIIxI1Q0FtfRPxQUjULF3/IO8tKeXHddVMn5TGE/dNIjszmmWaGFa6VhHMTGJAJgyYBcfZZLTldZQWVlO8X8vePfWkZcXz0+Ii3v3sdU49rh8XH3sEJx4xjI9+2MB/rj2K+bd9wswJ/SjIsX/5+yq6vdV29jV505tXPBozB+h66JurWO1OoRgML7hjHgMtwi0mGWV457zh/uKP/d7m1Nc8Bk8olfaOoMkuGliW7WEtS/dKNNfYqC6yUGCUqTSArJKYXlCMNVLBxm1pGAjDIdI94flel6jcvI+kIbmdvgbBoclfa9YgSRKzJrTe30dOm8Yz77zDxh07GD9iRAitE0I85NTUNZIY1zOWIvsSJRotR84MjJdS4Bu2bkrUdI4B11QbeOHHQpZtreGUo8fw4mND2W5IYT/w2lpfzisBiZCfSHT+AAaPacCwehOlJU0MHZ3H1p01HPP168yYlMGvf5Yw7+hEzj+jP/c+/xtvPXwmYcrA9gIIRAk4BTKyi7jxJt5cq124wzlsJZglDHs6BjfNk3wV4Y75DpU33Bcx7u89KUkQFwfxGWHEOzUF3V8mIZnttdCVehsTszTUlYUjAVYkmlHRTDhNqGhGhc1D/0ElNqxIjJlQzIY3DjBq/tE+2yboG5RrtaSnpBChbi09m5ORQZhSiUanC6FldoQQDyEmswVVWOBKRQl8p6FJL2qIBxltdR2pyYFNjnUW4Wv31HHb2zs4fXoG3716OU2KQvsGTauwcfWmeYuZjkiMJeLoGShKtBQu34DVYmVAvzgWLyslPyeG/zy5lrtvGsf3vxXx0he/ct1Zx3R4PH86HPpaV7wjb7hDpPiLPyX8XEV4T0jUhNB1k9TX24iIazvnnSmJ6MD5/fWUrBiMOH13YT7+4CrgHSsSVpUSa5w9NGBzmf1aFdiIwkwUZlJpIgozCuzXaCCsRaA3oSICC82EY9y0g4SCDNRx4nO9M+SOaCItLHgP1Mri4OXG6WpriY9p/3kaFxODrqYmaHZ4QgjxEFKiqSQnMzXUZvQ5TGYL4aKbZtApLdeSnR64+921Gsqz3x7g1tP6M298KlK0mia998Q3X+tjx+WkEnvWkQwz6SgtqmaIOobZx49i67oirliwlAH5cSQnRbQTK+4EjDf86a7pLVEzBhONbsJSfBFvnhq29JRkQk+Eup27vt5GfIb/FVN8mddQ1nPvDjyFWdlQ0IiaRtQue8iosRCNmViMZNBILEaiYkxoi5VMGzOUVMxUVtWSnBDXkgsi6NtI2Et1uiJDjyjYINRICCksrWBAfnaozehz2AVhz26xfihSWq5j5qTA5EO4ivC9miaKdXrmjEn2O87VV3EjSRI71KkceXjrvTN19hAmzxqEQqlw6yHsDg+4A28iHCAGIw0HxYy/Iq6jjokOepoo72i+g2WrWS+jivT9y91fu9y9j4H0inc1Vrx7kTCiwoiKauye7xm5RZTWVmOSy8kaVIChwca6Lbuorq0/2LdAQWJ8DKnJCaQmJZCanEB0ZESIr0MQTJITE6lrbPt5Jssy9Q0NpCQmhsiqVoQQDyFlFTpmTRZNB4JNsUZLnkjUDDq1DY0kBCgfYn9FMztLm5CABr2FtxaVcONJBYQXTALaCjJPYSkj/i5rqdLgj0h1rTutOOh189by21/B5asAd1d/2XFdsZiopPuWgJ3DDQIZkuJa093XfdzhS5x7oPEWbujPqoc7utMz3p0ivDva3isNMuV7DjBnVj7RSUrmjdAD68mMuhKwNxGrrWtEW11LUVkl67bsoklvACBCHU5acgIpSXaRLrzohyZZqalU6HToDQYiI+wPYUUaDVabjcy00GsBIcRDhE2WsdpkwkJcNqcvUlahY+q44aE2o0/hqNseiHyIsspKLnx6I1MGJ6BUSKiUEv8+vT+Hj0xuM66jL3xvLbXdCTRXgeT8e6CawXg6lwNnEd7RNTi2JQ42siOpNRzIWcC5O4e76/AmsLsrJtwfMe4qwkPlqTcbZcLcVEyBztvkS614b/TkWuxdLo1pk1GqVaxYvJOGOgPDjk4kOTECTfMrZEZdiVKhIDkxjuTEOIYOyGuzq95gRFtdh7a6lvVbd1Fd24DVakOSJBLiYkhNiiclOYHUpHhioiJFPlcvoqGpidhouxPisEmTkCSJP1ev5phZswBYtGIF6cnJjO4BNeeFEA8Ruqpa0kQd65AgYsSDj666LmBdTHcdOMDQ7BgWXjqszesOT55Gv6td9QlPAtbZK+7Ak5e0I8EQyNAAd+fwxQveHhnZaawv3n9319GVRMNg0FNEOIChzkZkfOc9qqGsHR6scJRAesUnTC+HXdD/mEn0b6xg+8YSrr59K5eeM4SjZ+e0iHFPREaoyctKa7dCarPZqK1vRFtdR1mFjk3b99LYpAdApQojJTG+RaSnJMaL75MAU1hWRnVdXUsi5f6SEtZv305SfDz5WVms374dsFdDsdlsLb8Pys8nJiqKj77/nsffeIOnbr+dI6ZMITY6mjPmzePRV1/FZDajNxh49dNPuX7+fBSK0K+AiLsnRBSWVpAnGvkEnYamZmKjA9uSXOCd0orAddScNGoU9z3TxLJt1cwc3rZosbuQlI5wiNPOLPO7VrMIhBj3JRnTNxEOyggZq6H1S6azoTgQOjHuzSvek0Q4OCqmtM55oIR1ILzivQVfr3XCjAoUBhmbWoFCqWTgsEwGDsskz5bLI8+tZ8PWKm65qnOhnwqFgqSEOJIS4hjSv21dcpPJjLamDl1VLdt2H6Cqpg6T2d65KDY6ipSkeFIT7SJddtMVUuCdNz7/nG8XL275/eWPP+bljz/mpDlzeOD667nkjjvajHf8/vqDDzJx5EiSEhJISUhoUynllksuIUyp5KWPPkKlUnHVOedw/oknBueCvCCEeIgoLK3g2NlTQm1Gn6O4rJLczNDHhPU1Ssq1AWtcFVX5AgsvG8ZNr23jr0entlsudhVjnr7U3YnwjoS0s6jydMyOxLinUJaOcLbNcU6H3d4EuSpKxtzUdm5cxbi7c3m6hlCIcX9CKrpbhPvyoKWvt5GYExYwAd5XxLcr7sS4+9b2NqyRbT2aRYoMnvnvdB58ej1vfLST+z07xDtFeLiK7PSUdgn/sizT2KRvEel7i8rYfaAwsCfvIzxw/fU8cP31Hrdv+PrrDvefN3Mm82bObPOaQqHgposv5qaLLw6AhYFFCPEQ0WwwEB0lMreDTbGmkrHDBobajD5HbX1gGlc5qqX8taWaQVnRnY7ZdNdKu6si3NsxfImFdW6S44pDiDgL8o7EeFi0DYOufQ6Ku3Acx3F7khgPVFxzV1cqnN8Lb+9fdK3M7uquLXX76g0OJl2tIe6Kp5rizvhyjUq9DUtM+3t8dVU8/75mDNffvZxfli1rJ8q6A0mSiI2JIjYmiv65mQDsKcrirW8+6vZzC3o3QoiHgKZmA1ERQoSHgsqqWlJFbH5QsR2s39rVRCeHCP99o47fN+r4+NZxnTqOswh1fNn7KtQcIsmTmA0UvgryjsR4WKQNi979R3xX7HcWUIES5Z0R3c7i0J033BcB7e1998uz7aZOcbA82n21s6lSb8OU6r5m+8aGRI4/fwaPvvoqM8aPJyZKNPoR9ExCH6XeByksqyBfxIcHHYcg7AnJGX0JXXUdqUkJXTqGc93wb/+ppKzayIK3trO7rKnNuMzIwS3i0CFO3HnWJsyo8FmEeyp/6HwsX47TGY7Mktv9uJ7Xk6BuSIpk69Rstk7NcjvGnYB3vkZfROgyTUzI47Ld4auAXlQmuR3r6XWwz5G7e0Eyy9jCFW3GdQeu93NPE+GZkYN9erByfYhzd497QzLLyCrPKx4ZOYlMHTuWz37+2edjCgTBRnjEQ0BRaQXjRwwKtRl9jkAIQoH/lJZryepiAyUpf0HL/597EJr1er7/8m6u+N9mTpuWwf/NyyXiYCMSuxh3eEsPikQPy9ydFTG+VlpxxtVD29lzO3vLHbG0rvaEYWUQVe28591FV0NW3NUAD2bJPW/C3Z2odn0tiWYiMVOqcV8dyPXBpzPvhy8iPJQVbpzfM1+6yjpsdX2Y8/VvY28hDPAy9tLTTuNf//kP5x5/PBFq106dAkHoEUI8BFRW1ZIiwiOCjkjUDA2lFTqmjR8R0GNGRUZy1vlPMnvUwzzx5T7Oemw9d541kKm0inGNfldLLKqzePUmXvzx8E6YUdHmeF3pOulNQLkTKw4x7kpYnQVlsw3jwfb2rvHlvuLPA0OgG/s4RJy/grw7EyWdxbSrkI7BRL1TS3ZvybSuZSX9xdN91x34Iqq7sp8nQd4RFpOMUuX9vR7Urx8D8vJYvm4dc6dN8/n4AkGwEEI8yFisVpQKBQrRGCDoFGsqmTN9fKjN6HPU1DWQFB/bLcdOG30nj8cvZOnWah74eDfj+8dx86lmkodPbSPGgTaCHLouXlwFcEfH8yYOfbHFnVjxlAA6TGkjKk9BbGrr9Tp70LuTQMeQeyth6Kt46+x1exLUrq/H9zdRX6Qi2+LfZ7sv8fqePOG+zG+om/k4zu+PIAfv76uhwUZErOcwQ8ffxaKyDxk9eDA7DxwQQlzQIxFCPMhoKqrISk/2PlAQcOobm4mLEQk7wSRQiZodIeUvYBYLmTAwnpd+LOTMR9Zx11l1zD1xXhuPnK/t2D01HHHnee5IEDkfx1Uwd+WBwFPFCedjHlhtI7mf+4/3YNakdjePnRHnHXnHfW0Q01EVDk/z4WvNdgApTEb2U4R7wpOt/t43wRTh3s7ljyD3BbsQ99xgy5nfqvcyMSzV7ViBINSIrLUgc6C0XCRqhgCz2YIqrH2ZK0H3UlVTR0piYDpqdoSUv4AotZJbTu3PM/83nP9+sodyXQPQViDMzGz0Wwh21GnTcUxPOG9zjO+OkAJXG63m9q3W3SV6hoKemODpnLzbOQKXMOnO++2axOjtvvE1YTIUBMouQ4PcxiPuSLB1t0KkiopgU+nmgJxXIAg0QogHmRKNlhwRpxx0yip0XU4YFPhPabmO7IzgeKIcCZ3hYfYvYtnpizfQosSf0AB3YtzXfX05puvr09IaSY2ytDx0+HueYHrLgynIfanI0VkxrgyXsRq77g13rsDjzl5376dDdDv/BBt/z9lVOxeVSRTrZJbVKzqscOMgIimWitJaPt3zfqfPKRB0FyI0JYjIsozZYiFcJaY92BRpKsnNEg9Awaa0XMfU8cODdj4pfwHffXU1g7OiSYkLRz5YSQXaLo27EwHOS+au8di+VKdwPaan43W0nz/L9p4Edk0NJCa638c5RKantE3vriZB3lYyHLhrJOPaxdQbyTShxkpZZpxf4Sy+nsPT/PRUr3dX6egBreX9kmXwMeQtMjmOsDAle7aXg+jnJuhhCEUYRGrqG0nspqQ1QceUluuYPGZYqM3oc1TX1XdboqYnrvvX09x835Vc/MxGJg2KZ2iOluFTppKTHo9CIXkUL+4EsS8hAN62uRPk3vbtClodpHpY/PG1Q2h34a4KSyBEuGs8vj+4a57kb5WZGEzUEAm4F9aexLm35lIdzU2wRbinCiidtcPdsTwJ8HYeb5vvIhzsOSrHnjGer97/m/MnlJGf1X2lPAUCfxFCPIgUlpSTn50RajP6JCazBXW4+w5sgu4hGIma7ohQq3n2v6+x8rf72FHSyC/rtDzz7cc0GiwMHZDJsP6pnDRnOAOlQgD0qaNYvaWExiYTmWmxRKpV/PBnOdv3VnL+iWOZM7XVhbZuWym3PP4tKQmxvHjvqRzUXh3ij1DpbJk4Z3Q6GD2qS4c4pHAnZt0Jvo4EuTf0yyVK8JwL4RDcnkoWuorwniTAOyKQtnjrjuqMwihjjfDvcyV/YBqHzRvJTQ8/zEdPPYU6PLxTdgoEgUYI8SBSWFrBnGmda8st6DyNTXpioiJCbUafo7qmnuSEuJCcW6VScdhxDzPLqSNndaOZnSWNbNyv46p7PuWlq0cyICOKG+//EJNZJiMng7LKBhqbjcyaUMDcaQN59bN/WoT4qk1F3P7kz9x+xVzue+43YqJC80XeUQgMQH09xIVm2r3SHd5w52P5WjqxozJ5zjb6WpM8JbmZyKFarx50d95yX8R+TxHfgXhQhPb3rOt74G3eD6yLQ4mN8pKOV9tc53bc1AL0RUo++uEHLj71VD8sFgi6DyHEg0h9YzNxsdGhNqPPUawRjXxCQWm5NmiJmp5w7siZDEwfAdOBghFLufrVN5k6ZgwGKYM3Fz5MmFKJ7CTcv11VRl68jFy0lga9hdseX8PCS4fREKZkzNBMdhfqCK/exZBs98vp1Y1mVlTEYzCaOWXuCMI0G9radjB23RV/QwCcQ2Bk2V6/w3kRwp2n0ZNgDGY1lc6WMexIlIakq6QsQycXfZznu6OQGm/XHUwCbYc/Itxx3+ZT0xIK1BFrl6e3mWNJkhg4K54P3vyW8088EVWYkECC0COqpgQJg9EkQiNCRHGZSNQMBaUVOrIzemalmmNmzeKJW2/FbLHw0I03Eqa0l7Z0Fu65KRHsr2hGlmW+WFHO9KGJTBgYz7K/1rB2awnX/OcL7nx3FxZrewG1dk8dZzyyjiV/rGXxn+u58Oa3sNnajpOL1rb8uOIQO5WFsaxabvZZ/DQ3Q7SHUvnevIwd1UnvSWj0uwJWi9obvly/wiBjU/v/VepJhHt6mHBcd7CuvbvoyH5fRDhANGaa8O/71HHs9KwEkpNl/tm0ya/9BYLuQjwOBoliTSV5QgyGhMqqWtKSE0JtRp+jqjZ0oSm+MG74cMYNb1/RRcpfgFy4kNEFcRhMNlbuqOWDP8p48V8j7Pv1j8NotnHdifkseHMHy7ZVM3tUa5Ou3zboeOSzvTw8fzBThyYiyzKnP7KOLUUNjO7nfj4cYtzhJa+qbeKDL8t5/7ufAJg7bSCx0Wq3+zrIjBzMygO72iRq+loeMNCecFcx6WpHSDzX3YRSb8MapfAr+dVXT7gnepKHvCt0tnxlGDasdL4vxIzJ6fy44m1mjBedlgWhRwjxIFFYUsGwQfmhNqPPYZNlZGQUCrH4E0zkECVqBgopfwHKwoXccFI/bnh1G3PGJDMoyx5WdvykNI6fZH+oTowOQ8Z+vTtKmvh1vZYf12h56V8jGJJjFxmSJGGxyqhV9nuwrNrAqz8Xsbe8GaVCQqmQCFNKhCkklIqt1DSZOaA1ceS0gbx03ync+fQvKBW+zaNWB7k53sc5l+jzpYujP3jrMtqdeIufd4c321y7orqibLZhTlAGvRxkbxTjgfCG+9s8yTU8BWBQQTx/r61E0/wKmVFX+nU8gSDQCCEeJMq11RwxXSRqBptgdXYUtKWne8N9QcpfwFwW8tTlCsb2b38t9c0WirQGVu+q5ZHP9hKlVjJjWCJvP/E/MvXvtox79ZciIlQKMhMjeOab/Xz9dwVnzcrktOkZWK0yVpuMxQZWm4zVKhOlVjCmIA5VmIIFby7liqMyidRuBg8x5Q40+l1UVcPYMb5dX6AFuAOHqO0oIdLdmEDjawiHLw8I7iqqOFA027Bm2sMkfBHj3rzhHdnjOl+9SYx7ez86euBxntdwrJj88Ia7u8+zMqIoq2gG4EDti5Tum8qUMWNaQtQEgmAihHgQsNlsyMgohVc26BSXiUTNUFBWriP7EOhkKuUvYBatCZzFOj2f/KWhss7E6t211DZZMJhsPHnpMEb1i3WKMbeHt6zbW8drvxQzb3wKpzy0lsNHJvHp7eNIi28fZtJstCIBkWq7GKisM7J6dx3/OW8QQJvmRJ6wmEHlIXTWm2e3KwLcXShKID3gvoa2eBN7vohcb95xaCvIJZsMSt9qkHc1BCgYDzDdga8PRd7uUYCoTsSHO47twGajZZXp3Q/K+GvNQlRh0Zx34omcMW8ekeqOw8AEgkAilGEQqNDVkJ6SFGoz+iTFoqNmSLAnaoa2YkqgkPIXYLPJvPRjIRc+tZFItZIReTEYTDYOH5nEJ7eNcxHhrfs16C0MyIgiMzGC168bxX3nDnIrwgHe+LWYcxduoLLOCMBXKys4elwK0RGt/hJ3iZ0OLBbobBGIQIrwjnBtR+6LWHc3xiH0/RH7vnqaHW3k3bWTd9DSfr6DxjLOonvCjIp2ItyfOXcVp87X0lOTNwOdXOqYP3uiZtdKhxpNVtRqJX+sKGPV5n1888JFPL5gDqs2LuaWR/+NxfJ7IEwWCHxCeMSDQGFpBf2yQ99Kui9S19BMvCgZGXSqaupJSuzdoSkOGnc+yp3v7aJRb+HT28azq6yJ+z7YxVXnzeeiU07pMA5+9vGPMPv41t+dyyO6UlJlQK1S8N+P9/DU5cP4amU5z17RPpnUE7oqSG7NGfW5aU2gQlH8wXH+I7PkLre492X/znrnve03I85GdarEdg/bu+IBdxXfru9ZV+etq4TiAWDCjArqlyup8qWTFp7nP1ylwGy28ur7O7jlqlFER4YzanAGz9xxItf+9xueensp/758biBNFwg8IjziQaCorII8IcSDjtliQRUmYv6CjexIkO2liZrO6DY/zMXPbCI1LpyHLxzCKz8X8cBHu3ni9vu5+NRT/U5GdfWaO1NeY+Tmkwuob7Yw/8mNpCeo29Uo9xSaotHvQqeDFB+jgRwe3WCWJ/S1OY4rwRCbzh52f0S7od5GZJwioHPpumrgC8EUxYHycvvTSdOZzJRGRkyv8jquo1j8LY2JNDSZmTc7h29/KaSseScAYUoFjy84lhXrC/ni11+9nkMgCATCIx4EDEYzEWrRTjfYaCqqyExL9j5QEFCq6xpIiu/93nC5cCF/bKmmtslMVYOJMx5dx8lT0vn8hTeJi+l8/LOjPGKbc8kymhojeakRvHLNSH7doKMgrW1BcG/x4Vot9DtYmCkYFUp6Ev54h13Fnr8Jk87o62wkZLd+jboeqyNh6avYdo01nzCjgkVlUtC94oEU+50V4UBLx6quxOKr1WEYjTbOPnkAt9y/kl//LGHebPv5M2MG8+wdJzL/9nc5avr0Lv2tCwS+IDzi3UxDYzOx0b4towkCS7FGKxI1Q0Bpec9t5OMvEwbEMf+IbI4ck8KP907i1htfDMgXs7NnfF95M5c/v5msJDWp8WoiwpWcNDmdUf3s7bulvAkdinCHQGpqguheFIXljwe5O8VmZzzQDgyNNiJiO06A7Yqn3J3I9FSVpbu84sFoIuTz/NtkZJdSno74e4f49iUcSFJIREeFYTBauPXqMbz50U7KK+1VVDT6XYQnaZk8Pp5PfvrJvwsRCDqBEOLdTGFpBfkiLCUklJRryTlEBGFvorRce8hUTCmYfC8XXfIMJ5zxOHHDbg/o8Y0Z1/HCD4Vc9twmjhqbwhvXjyZM2VZkePOCOwSSLAOSPW+wO7zhDrHaFdHaVTpKnuysN9zXbZ6QraBQdt98uBOVgW6+1BHdIcD9aWnvikJvwxbhebynuXF3jrScZB56dQ9ZGVGceWJ/nnx5U5vut6cfX8CH33+G0WTy2T6BoDMIId7NHCgtJz87I9Rm9EmMJhNqERIUdHQ1dSQnidrtHbF682bOvOEGCiv1fHLbOM45LKtN0x5vXnBoK5Lq6yEutveEpHS1SosvlU28sXZ5esuPA39Eoc0qIwXhG9TZ4+tNhAdaOHd3jXJ/H36UehlrVGAm/fSLpmE2W7nugfUcPi0TgK9/OtCyvV9uLFGRYWwsfD4g5xMIPCFixLuZ6toGkhJiQ21Gn6NJbyAqMiLUZvQ5HB01D4VEze7kzqef5rbLL2du9op22/wR4A50OqhRqemOjAh3YskRo9wZujtBNDNysFdB6hre4a77ojcMDTIRsb6JQl/qY/uDYw7dPYR4u/be0gDIHYPDrMRnKYlK8D0W33WMY+5U4WGcduE0lv66lStvW8HcGRl8+NUeJoxJIT/H/p0dE6OiscksOnAKuhUhxLsRs9lCmFLRa9t892ZKRCOfkFBT10BinHjw7Aiz2UxNfT2zM5cDvoeieBJYyzQxlB0wkZDVsxc4PQnwQMZ/B1NkGuptRMYHd86d57Cz8+a4j3qLIHe+5v0lNtJj2jfz8TdJ1jFeoZA4/JiRjJyQz69fraep2cL/3tzKE/dOBSA2OpyGJnMgLkMg8IgQ4t1IaYWOnEOkqUlvo0hTyYhB/UJtRp/jUErU7C4qq6tJiVG2CUUB9yLcnfh2F35iqLcRMdT/boO+4M6bG8yyh8GgM3HX+nobSXm+f4X64xXvSfPrywqDP8zMbGy5h/2ta2+zgiLM+xx6m2vXFZ3k1FjOunQmrzz8HVt21FBVYyA5MYLYGBVhppRe89Ai6J30bBdKL+dASTn5OSI+PBRU6mpITxXdTIPNodRRsztYuWEDN95/E5MHt42h90WEd1TjWrbZvXv+EupW6b3VGw5gbLQREePfnPsisL2N6UpcfE/B1X5f6to7wt58xds8ugp1ZZiCM07oD8CqdZUApMenUtdo8Ou8AoG/CI94N1JWoWPmxFGhNqPPIcsyNllGqQjcc6aj7nNHDVkEoKuuI0UkarZBLlzIvvJmnv5mP4WVem44qR9zRnccze0swp3Ft1svn0Umyiyx38+4bYcYchVFPS3h09meQAnQCTMqWuLEO2r80hGyzV4Gz188eWt9EeCBwt+HFufxnYlBd7ePs2fcF8bGNWFLcT8Pgbpnj5mTy2sf7OC9z3Zz2QlH0qQ/QHi4aAon6F6EEO8mZFnGYrURJjo7Bp2q2vqANpRxbr4iFy4UYtwDh1JHzUBRU1/Py5/v5Zd1Wi49KpcnLxtGeFjbB0RXb7gnoeMs3pxFpLLZhjVa0TLGVzHpqRmMLwKpK8maXcHXBjau4RSOa3IWwa7hKP5cj80io+jCt6ev5+oOz3dXVw46s78nIe+4Ptf7zd11FxVBQoLfp/aIu/cgKjKM6y8fyZ79dQBs3V3B+SeOA+mIwJ1YIHBBCPFuQldTR0pi7+8u2Bsp0WjJzQpMoqZrB0T7i0vEB7MbauobSYjrWd7UUHPlvffSP8nCl3dOINFNkpk3HALFIR7dVfvIoY7sEa3CxVscsi8i0JNAcsa1CkVncBzfk+D0x9Op0e/ySSQ629vZBwp9g83niin+0l1hJz0lztlhhztB3hE1NZDkYSHJ3cOjv1VqHDYcOyeXzMi5NDQZ0egaGJB3ml/HEQj8RQjxbqKwpELEh4eIorJKDps8ulP77isupqq2lia9noaiz2nUW2gyWBmWG8P0o+e2VsARYrwdpeVakZzswryZM9m2+ScSot1/1PriDXcV4SP+LmvZtnVqFrEYWbc1g9EzdH7b56uHuaPkt0AkcvojuL2Jd0+4E2udfYgw1AW+Yoqv1+NNUPeWqijuBHlHVNfAwIGBObcv7/v2vZUMKRiIKkzIJEH3IpI1u4nC0grys0RHzWCz8te72bt7FbHRkT6NlwsXtvys+u1uLr7tJl58+wm+/OYlVm6vYX+FnqbwFJ76oZz5t33CvuJqp52XdNNV9E5Ky3WHREfNQHLumL0U6wz8++0drNlTh8FkbdnmrV64O5xFuON3FTbMKD22PnfFH0+hszh0TqjrSMgEq/umO/HuKupcxWigvM36epmIuMB8ffqafJkZOdgnce3ruJ6Cr9fU3AxRUV07l7t713X+Hfb8sdrEuGHDunZCgcAHxKNeN9GkNxDjoxgUBIalP93JQ5/spX+umu+WLOGUI4/0uo+Uv6Al/OSvLdVceEQ2lx2d23ZM3gSuu2AGX/62hSvv+5KX7juFgfkHBafwjLcgEjXbIhcuJDJcybs3jeGtRcU8++1+9miaGZIdzfNXjMDXwDVnb/TWqVkuHvFMRmGPde5MCT5fBKCnmHHXEA9XghFH7s477k6MewuD8DfZz9hkQx3d9YcNb/MfTEEtF63tcHtHD47u9vXnQdOX61QrY5Ak3x+kXFdx3AlwT3aUlNfxw59/8sVzz/l8PoGgswgh3g006w1ERojW6sFCbzCw9Of7efrb/Vx9wjB2aST2FRf7vL9DjEsSqDzUqFUoJGYcpsYcNpD/u+8z/nvbJGYOm2jfKMR4a6JmACvVhIJmvZ77nn+eO664gqQuZIY55xbUNJqJiQhjxrBERubH8vnyclQF4/0+pqPSh0OMb52aRRQmmmkbe+6uNnNX8SZenUWPc5fKUCV1+ovfMeoyfjVq89cTH2yPtjcR7usY1/GdWfVxh9FoQ63q3GeLLwIc2s75c+8v5/wTTiAlMbFT5xQI/EEI8W6gqKxShKV0A7YvL2n5v94ss0ydzm8bdPy9o5aR+bHcdHIB0VGJUKYhOtI/76CUvwC16lqajdYOx82enkVYmIK7H13NgkuiOXbWEJRKhfcwlUNcqNfWN5IQ27sTNeXChSxbr+O3FTtIUx1gwWn9faqQ4zahF9he3Mh7S0pZvr2GI8ckkxIXTmpcOP+9YDCRat8SN12rfTiLcYBYjDSibhG+zqLDk8faXXt0T8Kvo/jdjqqrOFd1CYQY95Y86i7W3fmaOtuUxt15rWYZpco3Ed7TBTj4L7BDgbbGREpSuN/vY0edSD3N9c9Ld7Jhh4b/XHdy54wVCPxECPFuoLC0nLHDApRVImjH93uNPLtWz6DERo46vB93njmwpSLFZ38ryUmysnSnBtm2GEkxx6djyoULGTcgnpd+LOSqY/NbXnfn0Zk5OYNB6QN55p1lvPLpKo6YPICZ4/sxblgWKpWHcpWHuNf8UOmouXhTFUeNTWF7if1L27lcpclsZuOOHdQ3NmKTZWw2Gzbtd8g2GZsMNllGlsFotvHLei0lOgPnHZ7FHWcMIDaq9aPWXy+hsxgHwCkEJaLQiClVhQ1Fh2K3I69gR+LPW0Kdr7WguyLGnW11/n9H9cXdXZO/yYGebNCUgzau4xXP3t5wp6ehqzaRlhze6QdDX+53m03mlU9X8e3ibTx354lERkR0zWiBwEeEEO8GKqtqSU0RS1rdwZpyM8+v0/Pc3BiGJYchTWhbmcZokTjrzKP57q7PeeHDlVxzHl7FuMOjOWVwAg9+sof7P9zF/Dk5DMhomxnUxsM2FN56+Ey27K5g2boDPPf+cg6U1jBpVC4zxuczc3w/MlJiXU506Irx0gotY4cPCrUZXcJmk1mxo4YXrhrBtS9vxWaTMVtlfvpkAUt2J7B261YKcnJIS05GIUlI+t1IEigkCYUEkgIkJJQKOH1aBkeOS0GltC+nd3WJ3l1bcIC9hTb6DwBJau/l9gVfPbAdNWnx5hnvTOy6g46ux5cQg462d7Zte1UVTOhnoiDT1Kn9PdGbEiyDiUa/i30VMNiH6XG9F30R4NrqJhav2sOPf+1EluH9x88mOfGELtstEPiKEOIBxmq1HfxiFk1NAo3JKvOfFc3cPS2aYcntb129CSISk1GHh/HMHSdywyPfUqSp5dLTtBjNY1i+bh1XnXNOmzhm57CCMKXER7eO5bNlGq7832aG58Zw0bnpTBiR7TYeVJIkRg3OYNTgDP51zlSq65pZub6IZesP8L/3V5CSGM2M8f2YOT6fsUPt3nJN8ytkRl3ZPRMUQrRVdaT28kTNA5V64iLDGJITjdUmc/Gzm9BUGxmSHc3xk5Q8cP0rJMQdTLGUlyAXeW7W1Rnh7U0Yuu2AeTBWORQhEK5hAh2VOOwM3e1V9qdbpDNV1ZCX1/Xz+1o6sq/i/J7U1kK8jx8v7uY0I2IQpRV1FGpqKdbUUrxrF8U6A0VaPbpGG7Mm9OOik8cza0IBqnDvSf4CQSDptBBfs2UL6vBwRg4a5FfSyqGOprKKzLSO21cL/Mf25SV8u9dEv3gFs3Lcx9cWVynJzVADkJoUzZsPnsmbX6xmweM/Ilm/Qm+yMSN7B6P7ta9XYTBZiQhXkhCt4v/m5TFvfCo3vbOfy+/5goF5ybzz6FlER3a8HJ0UH8Xxs4dy/OyhWK02tu6xe8ufePt3SsubGDMimYljUpk45hlSkyM9i6Fe5jU/FBI15cKFbDpQz+h+saiUCg4flURZtZEXrhrB4Oxo+6CaV5FrWkV2oBLRHDiEra8CcXxCI8ZE3z3D3Vlf2pNX3F3sencSDK9yYwN0NR0iUC3Zu0pPjQ93ve+tNuhMk+pKnZ5//jby01/v09BkpH9uEjkxZnJTIhjXP46clEj6pUei7j/JvkMv++wVHBp0SohbrVYefuUVqmprsVqtpCQmctEpp3Dy3LkoFApkWe6z4vxAaTn52aKRTyCxfXkJNQYbb27S88hhnr/AiquUDJvQGtcXoQ7j6vOm8a+ZdgH91qISnv+ukClDEjhQ0cyD84ewt7yZF38o5K8t1UweHM91J/ZjaE4MLyypJy8jgRED0/luyXZmnPcSqz+91nMMuAtKpYLRQzIZPSSTU09JprbOyNpNOtZs1PLWxztJTlRz2PgKEuMj2VNYxfa9lUiSxCWnTeCE2fSqL4S6hibie3GipmNVZOWOWiYNsrvdHrxgiNuxgRbfrrgKyY7CKHRaSHETlu9JjHaHSHWXPNeVUJSu2tKVfX31istAZ7/eeooADwad/VtxfR9sNv/nOy18IO99u563v1rDUTMGce81cxkzJNPnnCGBIJh0Sohv3bOH1KQkvnz+eUxmM2u2bAFo8YjJssyLH37IrIkTGT3E/oW2auNGFAoFY4YOJVzlf6vn3kKJRsvk0UNDbcYhw0O3nc3OagsNJpnjBqgZk+b5lq2oUzJbvxWwfwG4envmH5FNg97Cur11rNxRy4xhiTz59X4umpvDPecM5Nd1Oq5+aSsP3Hgs6vAqTGYrd105h1svO5x3flyCpOj8w2VCvJq5s7KZOysbq01m155aNmytorpWZsKIbC48eTzNehO3PP4Dg/JTGFLQe+LJe3OiZu22R1i5s5bdpU38s6uWu89yn2Td3QLcG+4EuU4H6Rntx3SGjjyj/ly7u/AUb81/PI31J3QjWPHVBgNEqAN3PBGe0hZ3D0MNDdCgCGeZpnVFsqNVoGJNLZc88xnh4WF88MQ5ZBn3IOVl9ZrPU0Hfo1NCfMX69TQ2N6OtriY1KYnp48a1bKuureWjH37g9c8/R5IkRg8ZwtqtW/luyRJkWWbdtm1cefbZAbuAnoQsy5jMZsLDD90Hjf9n77zj2yjvP/4+bdmS955xnO1sJ2QSEhL23ntTSpllFPiVQltaKAUKtKVA2bPsQGnYYYUwk5AEsrcd771ka9/vD0W2LJ+k07JlR+/XSxCf7p57buiez32f7xhMnMsvYWyKkh9qbVw1Xc+yYt/nVRTBKYJCEFm3uZqZxroB66iUAtedMIo3Vtfy7bY2/vjqLu65YByHT3OJyDMPzWVCYSK//scnPHjb8bz2wUauvuc1/nTrLE4/fjQqZWRcL5QKgYnjUpk4zhXQ6ykirjp3Hn98dCVP/PFUOoV/D/i+3zH7E08y0u5Fiuq6RqZNLB20/QWDr9SCVU1mXv6ymvfWNDCzNJnSnASeuX5qb3aToRbevvC8F0ztdUyelUmrc3fURLj7eznnw9s9JZA7SqSKAA1mkGNzM6SH6HkYt4b7xtdsxOpaA+21dnRGccByKTG+t6qFX/7hbS44cQbnHT8DoerHAx2Ki/A4sUtIQlypUJCZmsr1d9+NUxT5wzXXMGH0aBwOB0+/9RZbd+/myAULGF9SAsC2PXtYMmcOZWPG8M+XXgLg8++/Z8e+ffzijDOGtW+pJ+2dJlKSDp6HbTRx5ww/vlTDWzssfFppJUEtMC1ThUEzcABvNQmkJDr5YUc7Vz76NfddMoEjpg+00q7d2cbjH1QyNjeBE+dk94pwN9MWLeH3umJuuf997vldOXc/XMOGTc3MmJIxwH9XDnKmuz3XmbdAw8ZdOo7+xVPMKc9m6cI8HGUiSoUwYN9CUTn71q7mvrdcZdTPXpTH2Yfmohw1a1AztDS2tJGZnjIo+woGKRG+qaKTFz6r5ocdbZwyL4c3b5tJVorLxBkN8S11/SMlHC1WJ63O3f32E0rbQlF5xCziIM8f3LP4jxupIkByLMah/C5DpbkF0tIi195ItIZHUoQDmDtFEtMGagTve6OiqpM7/rKKa8+fz4mHTwJcbkRx4sQ6IQnxk5Yt49LTTkOpVHLDX/7CWx9/zO1XXsmfH38cY0ICxy9ZwrY9e8g88MQyJibynxUryM3KYtbkyYDLVeW1Dz7g8DlzGDtqFOAKADV1d3PYIYdE5ugGmX1Vcf/wSOBZuEenEnjmaCMvbjHz3CYzm5vtnFSq5dY5CQjlZb3r7W9WUpTu4LmPazh5bjb3vrGb6SVJZCb3TWdWNPRw2/Pb+cVRhTz50X5OWyB9rRYfMprmtm5+fceX6HRKtuxsZcaUwXG9UCgErrqkjLNPGcOX39bwzCvbaW23sHh+Hocv7GB0sSvQNENdyntfbOMfL23h0sNzmFaSxP3vNfBtRTV/vq6MlCT9oIhxURRxOGMvUNNThDudIqs2t/DC59XUtlg4f3Eevz9nDIm60HN7u/EltP29gEVCOFZ17cAmoTICvfj52q/7+L0F+WDODIST6jCccxpUxpRmKB3df1ncvaSPSIhw75kDc6eTTVo1otX18iblvmTqtvGHB9ZxzfmXc+LSpQMKrHnWA3BTUVPD1z/+iCEhgeMOOwylMoRo0DhRweFw8O2GDXywahUffvUV99x4I0ctXNjv+7+/8AKffPMNarWak5cu5dLTTvPb5k333sun333Xb1lGaiorn302KscQDCEJ8ay0NJxOJ6Ioctjs2fzrP/9hfEkJNQ0NPHTbbXy5Zg2m7m5GFxYCsGTOHCxWKzqtlmXz5gHQY7GgVaupqKnpFeKPv/oqqUlJw1aIV1TXs3jOtKHuxrDGU4S70asFrpimZ1mxgys+7mRJkbqfCN9ZY6KiKZWJuSbW7mrnwz8eQkaShuuf3ML5i/MoKzLyyqoaPlzXyHUnjkKtFCgrMqDX+H7wnnbkZCZNFVm5qprC/L6BYTCsb66ByEDm9HTOmj6FxroONv1Ywf/dt540g5KcLD1btq9k/Khs/v7bE5kyzvVC8fQ8B/986RvOvuk/3HvTMUyfkBd1Md7RaSLZmBi19kPBLcItNifvrWngxc+r0WsUXLi0gGXTMlAp+2ZUopFm0Pt7b2GxMLcr7AwmLS0QSvXtQPsdDOEtZQ0v+66GzXPzesV4KC4q0Zqx8sTUDQkHygsMd1eTSGdMiYYIX1kjkNguIuYK/ZZ53htf1STy5Wtfsah8MSctXXqgM0sGVjs+8Cxcu2kTf3/hBeoaG1kwcyYVNTW89sEHPHrnnSQbvWo/xBkSWjs6uOff/8bhcOBwOgd8f9/TT/Px6tXceMkl9JjNPPjssyiVSi46+WSfbXaYTCybN4/zTjyxd5kqRl6+ghLi7Z2dvP/llxw6axYFOTnYD5ykptZWnlu+nD9cey0Jej2mnh7ys7MxHHhiGRMTOePoo3vbaWxpYWdFBZedfjrf//QTC2bORK/TUVFTw5nHHBPZIxxE2jtNJMddU6LC8h0WHlnfw42z9Mw5fjoANoeTB9/Zy7vfN1A+oZzcpB6SElS8vrqWS5YVMCpLz4frGvnrW3s4aU42y387kzSjhs5uO/ct30NLl400g2+/85RkLaefMNrn99HAcyDq86FNZtmxU1h89GT272uiu8vClRdqyc7UAx2AS4irVUpuvPhQysvyufHeFSyaVcL55+SRmLAjarnLq+qHPlDT2wWltcvGG1/X8vpXtUwqNHD7maWUj0kekMkpGOHgT7C5r5mUVVRKrHlaUEMVj41NkBnGaY/WC6WvNIbe/uBuEV72XU3vMl9iPBiLs/u4vK+Xr1SOwSCKgAhf1/m/pr5wnxup9YZ7MZ9oiXBfeIrxlp82U9/Yw0O3XOrVqSVA38vGzoom/v7ir9lb1cLV587j6IVHo1AIiGIZDz2/ml/98SauPGsuMybmoW34CacTnHnTcDhFnE4Rh8OJff/G3r/tThGFIJCfru19tghF5XF/9AiQkZrK+088QU1DA8decUW/79o7O3n7k0+4+4YbOGL+fAC6zWZe+u9/Of+EE3zObLR3djJ78mRmTJwY9f4HS1BCPNlopNNk4rm33+aEJUv4ccsWPv/+e04/6ii6uru5/aGHsNpsqNVqJpSU0NXdTYJOh0KhwOFwoFAoEASBHfv2oVapOGHJEs656SZuv/JKOk0mmtvamDx2eFbns1htaNTx+kjR4KUtZt7aYeGJI42MSe37kT23soqf9nby3p2zefIzNbc8+yO/O2sMr31Vy1Mf7ad8bDI3nzqaokx97zYtnVYefncfdofI7loTaWNTer8b6gA9aRHe9/eyPCganQnATjtkIz3wHzZ7NK8/dB53PfEeL7/VzRUXTIyaZby6rompEwb3ZcUT5777Wb+ng49+bKKu1Uxjh42qph6WTsvg39dMGVAdNRgC+a76Wh5IjHqLy1BEcVMTTPeYfJOyugdiMH2rI13sxx9S1y3UKpqedPdAO2pSfHwvV4x7M1QiPFBsQLSQcy3c94pgFxFVwgC3JbcIzzRV8cg7u3nwj3PRqFYDfc8457772V5t4oufm/n85xaaTT9y6amzePDW4/qN1YIgcMNFC/nPig289O6P3HL/+9jsDpRKBQrFDygVCpRKwfV/7K6CfQoBlUKgy2znoqUFXLy0AHDPMqwb1GD5g41Va9ciCAKHlveN18vmzePh559n47ZtzCwrk9yuo6uLtJSUQeplcAStHI897DDeXrmSux59lPysLK49/3xmT5nS+/3qdet47u23USgUbN29m9lTpuB0Ovu9pWzcto3SwkJyMjOZWFrKmp9/xu5wkJqURG5mZmSObJDZX9tAYV7WUHdj2KM49dl+7imtZidPbDTz2glJ5BoU/VxSFk1O4/XVdbSYVJSXqplRNIYH39nLf26ejkIQ+O/39Vz88E/84ZyxLJqcRn2bhV89uokFE1P53x2zyEjq8x8P1joa6cHTnwgPpT82XTXLFuXz7kf7+hZGQYw3Ng9doKZpx1/54ys72bq/i1Pn5zB3QgpZSRoKMnQkJ4aXuSiQe4nUNfIMMPS3rqelF/pcVYK5pzo6wd8suj8rfbTx9SIymGI8EngfQ0eDA33SwGly722COedDbQn3FRsQLYJ9uVX0OKmoly6p2dNt5Z5/bODOK4+gfNSBtKMHnnFd2+/lty9sZ3ddN0umpHPLqaOZfthin5mvBEHgvBNmcN4JMyS/d+N9nnbXdXPVo5u4cEk+ijDS28aRT11jI9kZGei0fXlEC3JyUCmV1DY1+dyuo6uLdz/7jL+/8AKCIDB32jRuvuwysiIZfR0iQQvxgpwcrj3/fK49//zewj1OpxOnKKJSKrE7HCQZDDxwyy29AVzegVybd+3q9RXXabVs27uXzq4upowbN2wLAVVU1TO+tHCouzHscC6/BMWp/YMlPMX455U25uWpyDW47qGKhh6MCSrSDGrG5iaiUQms2WVnxmgl43Iz2Li3g9tf3ME/rpjE+UvymVaSxPVPbuHkudm8+309FyzJ56ID1otwkOPjK9cKFwlfU6l96XVKunscvd/n6sdFVIyLoohTdKIcgkBNseIBHnxnL6IIb9w2E606cn1wn8tAgto744e376qU6PR0u4D+1nG5fuNuFwk5j8qhCiT0JcYD4XZPGWqk+m5ud6JPjtx9NtQi3JNwreOBUlzKce1y4/m72f+TARv9XQ3cv7EfP/iBhTNKWTpvTG8fAGz2Ndzw1Fby0rS8fXs5aqXCZ98CuTB5432eSnMSMOhV/FTRyfSSgRWbhxO6eXnoEwfxWf5qW0ibNbW1kWwY+PtMMhhoam31ud2kMWOYNmEC155/PnurqvjXf/7Dr+++m5fuv3/Ikw2EtXe3aFYoFL1O77MmT+bCk0/2eWBd3d3UNjZyyNSpgCuQs7m1lU+++YZFs2eH050hpbahmdzMeGn7YJAKzHSjOPVZhPIyPqmwcsSoPsv1Ex9Wctwf1nDrc9u4+OGfyErWolAaKEx3Cc7rThxFt8XB05/sB2DKKCN/u3QCFQ09PHJlmaQIl3pIyxXRtT07fH5CIZIWwwS9ii6Trffvb9ZX4HD4t+gFQ0dXN0mG0F0/wsFqd7JiTQO3n1kaFRHuycoaoV+Aofvjpuy7mt6/3ev5EuGe//dcz1OMBLp3ukwgMQ75xJ8gjoTLhi+kXgDcIspXdhRPER5ssGYkWF1r8Hm+ejqc6GQI8VgP4hQr10l+wiFUEe6PdV9nk4gNEwNntxbmdjFjcgZfrd1L+7bve/sviiJ3v76bBK2SO84ei9qHBdzXMzqUvp6xIIc7X9rB2p1tQW8bJ3gEXNfZGxFQ+LFOPPXnP/d6cJx5zDH89pe/ZMvu3azbvDl6nZVJxF8DDAkJTJ/gu7LkvupqWtvbyc92DUZHzJ/PB6tW0WkyMc3Pdm4+/Xod6zfvpKW9U/JiDAVOUURERBmhgi8HA/5EuJvtVV3sbnOwML/vQTyjNImpJUbmjEvhquOK+devyjDbBPQHtLpaqeDei8fz+uo6vtvWemCbZP522UQmFIQ+QObqx0XFguU9aPsSH6GIksJ8A1arg3Ou/JSzrviMq+56h43ba0PqpxTVdY3kZQ9NoGZju5WURFXYLii+cF8XT0HtKaDdeAYbeotxf0i1JVfA+Spt74+hEoehWONDTWEYLoHOkd0iotYOzxlbICKCW4pwYmsCzTrpsWH2EOKez8GLjjmc3Ewje+q6e5c9+/yPbN/ZxD0Xjkfpw1Uk2KxH3ghF5f0+55x/Atdfejg3P7eL3R59iRMd0lNTae/q/1wRRZGOzk4ygkglNW/6dMClSYeaQVeOk8eO5fm//rXfsomlpXSaTGTLKFk2b0YZKpWSr9f+zItvf8yr//uMr9dtorq+STLNzWDQ0NRKdnoIucQOUjxFuKfPd791nE4efncfF5bpUClgXb2N9/ZYSDWo2bCng5PnZjN3fAqCoESnFrHZnRx627c0tlvJStZyzqJcXvqiRrJtT+RYwz0FeCTFuK+Bf1me2DvgeP47WNQqBf++/1De+vuFvPPIhZx+5GS2720Mqa2K6mpWrVnDxm3bqKipwWazHShtPzQxHakGNYIgcPHDG7n3zd28810d26q6sNmj8wzwFs5l39UMyPgRKlLC3Z8YkMqYIkfw+rrfomkVh+FRtCaQCA/W6BNrVvFo+YAHEuHBuKRItg+I9P99eN5PCYIZk8WB9YdN/OmRH3h7p4WHDzeg37Qt6P6Esp6bZfPGUjY2mxohf8iD/kc6eZmZ1Dc10WM29y6rrK3F4XSSmyU/Ts9qc80Wu7P7DSVDkuajKDe3179cp9Vyx1VXsX3vXlknJCFBx5iiIqaMd2VqsFht7K9tYOuuCj7/Zj0iIrmZ6YwqyKEwLwvtIJSbr6iupzh/oIUrzkC8LeHius3AwGILzz5zAz1WBxaHyJFvtJOTqKAkWcn2XZUUZOh7A2OqWpQUpDtQqxR09Tg48s4fuPDwfN79vp5//lJa5PtDjs9goIItgTJYyB2kIzE1X5zcl6qppb2HGZbgLeLV9fVcetM1jE9T0qnW09plw2xzcNj0QyhPW4nYI/0YiWbmgAStkjdvm8HW/V1sqzKxdmc7L31eQ3WzmVHZesbnG5hQkMiEQgNTio0+rWOhsnluXj/xLcevuXxBfT9BL1XARk42leYWmCkRUxaqX3a4BPo9+MN93rx9w6PlliLlMy/nnNl6RNQJkbuHBtM/PBZFuBTeL6QCIikZFsrHu34jnveE+/x1dNsxVlTyaKWV6i4n/zk+SbLy8mDQ0t5NWsrQi7qRzqLZsxEEgS/XrOHoQw8FYOU335Cdns7UcX2/q06TCWOiq8bF9xs3UpCT0+uJ4d5GEAQmjRkzuAcgwZDl2/MMykxPSWH+DP/Ryr7QatSMKc5nTHE+AA6nk7rGFvZV1bH25+1YbTZSkoyMys+muCAnKsVHKqvrmbp0XsTbHWn4c0fxrHy25tM7+M+XNbx883Quemgjt5w5lmNmud50RVHEahd7162q/pGxZQVgfYHXb53BmX9dT4/FwZPXTGFMXvDX2v2ADzUziq+80ZFGjpXRs/87K5pY89M+7jhpVlD76TGbueGuG7nkmFGctzi/r70aE89+4eTku9dy3KxMzl+cT166jp/3dZKUoKI4Sy9ZzS6SJOpUzBqbwiyPFJQ9Vge7arrZVtXF9moTb31Th90hcvmRhRw7K1N2MLhb1LozfXiLaBgovuW4VPhax1cBG6n7UC0aUKmkr38gMR6rVSDd53Iw3FJCySjT0+FEnxTcBHIs5AwfivSEcpCTVWfWzDocDb6t4WLlOqaMMnL1Fw3kaEUePcLoU4S7g0k9n+/+COUa2e1OtJp4CuNIUFFTQ0t7e2/w5d6qKtZv3UpacjLFeXmcftRR3PvEE1htNnrMZp54/XWuu+CC3tjEV1as4L6nn+bB225jyZw5fLBqFavWruW0I49kyvjxbN+zhyffeIMzjj6a4ryhDw4fcXeNUqEgPzuD/OwMKHcJt7aOLvZV1fH5t+vp6DKh1Wgozs+mOD+b7IzUsCNmeyxW9Dpt4BUPYvyK8HWbEcrLECseoLnDyu0vbOeP540jO0XLDSeVcM8bu5k2Oom8NJ1rFmXMb3q3rW1oYdGcaQjKmxnLA5w2PwetWhGSCPck0INYygoYK9PRUn3//SOfcOPJJaQE6VP91NM3U5Kt59zD+j+sslMNHDJOy/XHzuA/X9Zw7gMbyEvXUd1sRqkQePU308lK0UZdjHuj1yiZMsrIlFFGrHYnKoXAmp3tPPjfvWzc28Ftp5f6TTPmeV2lxLg3bnHuS0C6xXUwQbj+xLLV6kStVoRlhY4GkSiY48afNTyctIzev89gfq/mDpHEtPA9OWMpU0o4DIb7hbLHiVOv6L0f3Nfc8xzednoplywrIGn7TnQq/78xz8wunm143qvhXB+1SonFag95+zh9PP3mm7z72We9fz/+6qs8/uqrnHj44dx13XXcdMklqJRKHnvlFdRqNVeefTbnnXBC7/ppKSlkpKT0Zlf5/TXX8PoHH/DlmjW89sEHpCYlceXZZ/utxDmYjDgh7o0gCKQmG0lNNjKjzFUsqMdsobKmgZ+37WFlcysCArnZ6YzKz6EwNxNNEO4sXaYeDAm6aHV/RCAnMNPNXa/t4sQ52SyY6PK5P2pmJh+sa2RzRZdLiHuIOlEUcTgdvRl7hOKbuWDJn7j44Y2cdWgeBRmxf13cg0swosCXCPE3iLS1tNPRneByCZO5H/ve+/nfDw3868qyAZbk6hYl+amO3pely48sZFtVF2VFRt7YpOQXj6zlsasmk5emG3QxDq5744pHfsbuELn7gvE8fd0Urn9iC/ct38Ntp5f63daXGHfjKar9WXA9twlFkLvxtIrXNVnJydQM6Kcnw8Uq7j3L4O9cSonocI9BbiXUhbldfLIZFo0DrTbw+pHuZ6wRCREuJ9f8eJUDY66yd32QfsZlp2hhzuQDbo4H+ugj9kiKSL0cZaYl0thiikhbBzt3XXcdd113nc/vFQoFN1x8MTdcfLHk90ctXMhRCxf2/i0IAmcdeyxnHXtspLsaEUa8EJdCr9MyfnQh40e78n47HE5qGpqoqKrnh41bsdntpCYZKS7IYVR+Nkl+3Flc/uE5g9X1EYFn3nC3SBfXbWZtUj67a03cf0n/7DltJhtpxoEvR20dXaQk9VU1aWhp4eS712HUCLz1TR3XnzgqOgcQAbwHZ8+//Q3uoYhwgH9fPYVbnt1KU4eNm64P3D+x4gHW7mwnzaiWnF2ocRYwaZIBIVuLWLkOo17FIUuXAnDxWNColVz49zVcf8ECTlgSvcqevvhqcys9VicnzM7iuic28+KN07n/0omc9Ke13HzKaFRK/4I4XItzoOw3UoLc0z3Fl4CrbbCQmzm8Z988z4G3+I5mykI5gtjXOhbLQBHuXj9WZsJijUC/IX9iHGBftUhmqUJShEu53LjFt6cgH0yy0hJpaBlZL11xBod4vj1AqVRQmJvFwtlTOOfEpVxwypEsmD0Fh8PBZ9+u54XlH/Pais/59sfN1DQ04/TIzlJRXRcP1AwCqeI9bt5csZ2LxirRqPpuy45uO1VNZgolrNv7axoo8qhmqvnoBgBsTpHnPq0a9PSWcgf6UMpg+1sesABM5TpyUrUsmpxGXaslYB/FigcAWLGmgeNnD4xCF4rKqW+ykp2h6f3b20p27vHT+ftvT+CF//7IP1/+5kDDnwfct1wCWdj3NXRzyNhkzl+Sz6GT0rjhqS3c8/ounCK0drmi5eX6zwZr0ZQjJn1lw/EU6FK5xWsbLORmhS/EB1M8+ssO5O9vfwymlVmUWTxJCs9+DoVbSqRdSCLdnr/r6LCLHFYUvIXZ2xrumWpQLqHkV8/OMFLfHBficYLnoLSIB0IQBNKSjaR5uLOYLVYqaxrYvGMvn37t+nHmZKaxr6qeJfNCCzQ92PAW4Z7LncsvYU+bg4vLdIjrNvPxPiuv7Fews6abBK2yXzl6N/trG5k7YxLgsqwbNAKpOoHHjzCypdkeU1VagxUOntYif9vKGdy37u/ixqe2kpeu5aZTRvtd1y3Ct1d3sXpLC7/2mlVwD2ZOp4gygFV58tgcnvzTaVz2uzfRqlVcdvpsVErflnFRFKlvaiInU15KRKH45t7+ejMuL5EXPqumqcNGbpoWtVLBvAmp/P6csRj1fY89fxUBg7WKyxGS3lZAqbLvUlU3wSXGO0wGjInK3r/l4N3+UBTK8YW/vki5bQ2Fm0dnJxiNvr+Pdau4HAEqR3CGIsLl/Iakzt+CnC7adX1teBKpvsoV2Z7r+Ws3My2RtZuGPid1nOFHXIjLRKfVMK6kgHElrsqMDqeTqtpGtu6q4N2V32CxWkkyJFKcn01RfjZpycaYEoJDjS8R7sZ50lPsf/k0RiW7RMa+dgc1dd188Ic5JCVI36bNbR2kpRh73VsUgsCZ47W8uNnMXQsjnx1HDlKDSqjiIVKiY0e1iaklRv56scvlx5fPtlvUdnbb+c0z27jltFLSkzQDBp/OLjuGRHmPjtQkPY//4RRu+9sHvPPpZhbMKGZi6SYmlmYypigdjVqFY99aftzTwT//t48tlV3cd+kElkxx1RQIZPn2JcbnTkjl0V9NZletiT113dS0mHnnuzpmlib1E+IQuDy3HOQISu+/3feJlBiHPlcVtxgXRbA4uwI+V4ZaFHoKr1D74nnO3L+pwRbhbgHYVt3F6BwHufrkoF7MhpNvuPv+9yVOw/l9BCPG3eesuxv0CcHNIgxGAKm/Z0V2uoGG5s6o9yHOyCMuxENEqVCAKDJtYimHzZkOQEeniYrqer5dt5mW9g7UKhX5OZkU52eTn52BSqUc2k4PEYFEOIDpjctQCOAuTvqLqTq2tzp4642NXDxZh1Be1k+UORxOVznbyr/1a+ecCVoueL+Tt8xpnC6jb5EQYd4M1gAsd5AqydHz+IeVdHbbMR54qfEW424xa3eI/O7lHSyclMox5dKW6ep6C/nZ8t0jstIMPHP3GWzd3cD6rTWs31rDK+9toKquHaNBS2tHD7kpGn55dBFFmXque2IzGUYNU0YZAwZ6eorwbouDjm47Oamuvo3LT2RcvuuF7Orjinlrq4ZL//4V91w4nnkT+hfgcgsQX/dCNKyenm36EuNuVtcamJzQRXJSYEt4oL56C/yhxFdffS2LRn8D/Y7qm62MLkzoXddXgKy7j55/y91HrOAtyCP1bJQrxt20tkKxj5kxoag87Oe29wvHX9/aza6abiYVGZheksTiKWk+X3h97XtscQZb9zRiszlQD5zAjRPHJ3EhHgb7vAI1k4yJTJkwmikTXNP/Npud6vom9lXV8vXan3E4naSnJFF0IHWiMTGe/B9cbiVGjUBJspIfau0syHdVTfzVND1XftLJhWVaVF5irL6phWzN1gFtJWkVPHL9DC77x09kJbv8ogMRykM9UqnjBiMN3dRRSSwqS+NPr+3irxeP7x1g3CLXLWZ313Vz50s7SDequeGkkt7tvc9PVZ2ZiWOCn3GYWJrFxNI+n/Mei422jh7SUxLQqFW9+7lLX8R1//yE/OxkRERE5xU4xUREUSQjNZXbr7yS/OzsfiL8x93t3PzMNhxOkauOLeLMhbk4RfhuexuWpFEsmlXCGcVKxhRncOM97/DE1ZMlg1C9j1Xq+vhyJwnF5SOQGPds96udOsZmmAe0EQlCzZsv1Y4cvC3eIM96Hk76Qk+COdb6JivzZqT029bXcQ71i02kiIZ1OZhnnaMrm8w03/IkmGJCcq71d9vaOGdRHh09dh5fvoMPVir4/fxEEudOllxf6kUlIzWRUfmprNtSzdzpAXcZJ04vcSEeBtV1jcz3kyZJrVYxqiCHUQUusS6KIs2tHVTU1LNy9To6TT3otGqK8lzuLDkRyGk+HPCVzvDSKTruWG3iwjIdiwrUOESRDouIUsKiXrnpZZwOE3vr7RSLIiLQYRFpG1NKc5uFycVGfvvCdj6/Zw5qVeBzGg3LuC+8BwZfOW3lbi+HG08u4YIHN/D2t/WcOr/v5bFu492s2dnOz/s6+Xh9I1cfV8xp83MGWIM8z09Dk5XFc32/4MipTgqg16rRZ/Zlw3G3v2j2aJ6/90w6uiwIAigUgmv2QxD44af9XHDLr7nr2iNZcMBgVtHQwy3PbuPuC8aRn67jlme38dlPzfRYndgVehL0bdz97884fvFETjtiMtdffBh3vPwt/7l5ekTdx6ItxnvanOw3JDCB7oj0F6KbXs9XKkBfhJLKMxCReLmw2pxoNf2fIcGIyuFiDR8MpM6FlGhe19LIuJLgDFW+roecl8ziLD2GujrOGK3h/GON/OW7bi76oINHbT+TmaDwmQ7RW5AfvXAcDz2/mofzjyVXZqxLnDhxIR4ioihidzhQq+SfQkEQyEhLJiMtmfLJrgeD2WJl/4Eg0M++/hERkez0VIrzsynMzyZhhBUK8pdT/PAiDUUn380r773Hdd9tRKfVctIR8yTFUlWzkvd/2MW2fS0AWB2QqFeRYthKSqKKmaXJXHl0EWqVgl01Jr7a0kpti5nOHgdzxidz0pxsv2IzGkRiQA61Da1awV8vnsClf/+JaSVGSnNd1uA7XtqBQhCYPzGFl2+aTl564NzrDqfoM/2f1GDoXhZM34vzUiWXTyjJZMrYbK7/y//4z/3nYNv/E1f8axPXHF/c627y4o3TeH9vAp0mC+efMANBEKiobmX5ys1ccvsbjMpPZU+9mVWbWzhscvqAffiyinsKxUgHPMoR46M7neiMgizxHIorTaSs4uH0QS6D5VbjdIqul0AJ5FZpjOMfqXuuvdNOcpK8sTUS5z8/XUd1u+sFV6sU+P38BB7faOaWL7t44igjgTxN3IL83ONnYrM7ufS3v2XF44+H3a84BwdxIR4izW0dpKckh92OTqthbEkBYw8EgTqdThqa26ioruenz76lx2wlQa+l+IDVPDM9xefAMNxRnPos44DfX311wHV71OOYWLCF+UYdZ4zXolcJqBSCpOXihc+raeuyMW9iKgkaJU9/sh9RhFPmDcz/LkeMB/vgD0bc+BvcwxVJJdkJ3HBSCbc8t52XbpqGXqNErRQ457A8Fk4K7MID0GmyY0iQjnUIdF4idd5mTMpn2vhcduxrZMdPTZQVGVjkIajVKgUnL+1/HxTnp3LDRQu55tx5fLFmD8s/2cTane2SQhz8u6hEw3LrjZQYF50gHKgKGowQ9c5d7v0S4Z2ZJZz7bDArfg6GGG9ps5GW4r/AW6xVOR0JiCKyxrlQz7vbzxzAYnPy5aZm7rtkIjRUAKA87Tl+dYqTbb+7jH/s13PzbJkN7/+Ri8rhg68MbNy2jSR/6XbixDnAyPeDiBIV1fUUF0Q+f7hCoSAnM4050ydyxrGLufDUIzlm8RyMhgQ2bNnJy+98wktvf8LKr9exc28VZos14n0YCuQEdLoxW6xoNWqmzjqXnxsdGDUKVBJly+vbLLz8RTU/7+vklPk5HD41nR93t2MyO0j2kYkF/Ke1CubBn6sfF7KocW/nbiNSlsoTDsmiOFPH29/UAaBSKbDanAG2ciFWrqOm3kJ+zuBULK3t2dH78SbZqKOr20pZ+XTMVien3L2O+97aTUe33e+LlFqt5Ij5Y3ns96cETuXodR94Xwc5OeGDwbstT8Es2EXq7cG9gEu1J8eSH66o9D5HkWBljdD78WR1rSGoFyLPe8rXveVJXZOVnIzAkXf+fp9xkR4cNrszYMEtOdfOe30p7A6RP726k0mFRiYWJCKUl/WORQqFgrt/+0++2NTMJ+ub5B8AkJeVRWtHR1DbxDl4iQvxEKmoGrxCPol6HRNKizhq0SFccMqRnHPSUiaOKaaptZ13V37NC8s/ZvmHq1j703YamtsGvZBNuAQjwgGq65rIz8lk2vjx/NSZ4PN43/2+noff3cfR5ZmkG9Wcce+PZCRpeOd35Rw+LSMSXffJULqheOItJgVB4NzD8lj+bT2iKLKlsoux+fIDL6vqpDOmRFtseLdvttjRadUcWl7CY1dNZvn/zcRsc3L54ztpaev2u224+BLk0bDOusXzIXoHpbn9H9dyBKjcPnm3FclzFuy58VxXSnxLLfOFHNHt71jrm6xkyRDiEPcFjxTNrTbSU33PQkTy3vztC9tZubGZa44vRhCEARmakgwGHvjtPdzzxi721suPzejq7saQEE/GEEcecdeUEOnqNg9Z1hOlQkF+dgb52RnMwzUF32XqobKmnh837aCxpQ2FIJCTmU5RfhaFuVnotLGRTylY0S3F/toGSovyyMnMRKfR8OO46yjf+WC/dewOkXe/b8DuEPnFkYV8+GMjNrvI5UcVoteElkZyuFi2AhWqKB+TTGuXja+3tqJRCRRm6GW3Xd9k4bA50v7b4eBLVHqKMk9f89RkPU2trqp7QlE5GcCdZXP527Nf8fCLq7nr2iN7t/MlkDynp0NByo0oWq4SPW1OEpL7C3G5+5LrShNJVw8pd41gxbinL34g4R1u333FMTQ2W1k0O0V2O97HHRfnwdPQbCUrXXq8iuQzWCgq59T5bSQlqLjy0U08dc0U8hiYLnWC6m2uPWEUNz+zjRdvnEaCNvD40WUyYUgcmloWcYYfcSEeAj1mS8wIWzeGRD2Txo5i0thRgCvPdl1jC5U19azfvBOzxYYhQUdhXhbFedlkDGNf85r6JhbOmgLA7371K3770EO8dLiTzASXUGk32bjluW0UZel57tdTufHprVQ3m7nquGI0MjKoBBOw6avqX6QD3+Qiq+qcIJCbpuXlL2pYMlXaR1pyu6JyHD/WBJw2DgY54hAGntup43J56s0fmDo+h8ljXb7+giBwxtFT+OXvl8vef7hiHMIP2pNj2e5ud5JWLO9xLTfXdazjHcAKgQV5uHift04rNNk7wC5fVMfFd3g0tliZUDpQxEbDEDLviKXMOwKef+6/3PLcNp64ZgoJHrUL3ClST5mbzU97O/jTq7u458JxAbMtuS3iNrs94n2OM/KIC/EQqKxpoCgvK/CKQ4hSqSA/J4P8HAmr+eadNLa0ISCQk5lGUV4WhXlZ6IdBhhZXthpnb3GkBTNncsZRR3H9R68zL08NNftYuaGJwyan8euTSvh+exuVjT28dssMWWkMgyHWBE0wgjI9ScOqTS1ce8Io2dt0ddtJ1EeuKJX3+fMlsqSKz5TPUaBUzuH6e/7HiUsmct0FCxAEgcKcFNrau+na8T2GcXNk9SOSRUsgOMEg9x5y2ERUmr7zE6hgTKBc14Nx78oNYvTuu/cMg2df/RU+CsYqLicfucMBnqEnvl6uI1385mCnqcVG5uzBNXRdeNGJVDa+zlF3/kBZkZFpJdeyYFIqU0clAa6X/NtOL+Wih3/irW/qOH1Brt/2urq7MSYk0BL3E48jg7gQD4GK6nqmTvAf6BWLDLCaO53UN7ZQWdPAxq276bFYSdBpXVbz/Gyy0lNiLq95R6eJlKT+1pLLzziDlL3/pcPihOYmbji5pLdE+ti8ROwOkX+uqODGk0ukmgwJOZX/BtMqHqxV97ttrQBMLJA3fSoUlVO9x0R+9sBAzVAsVb5E+Lqv+8ddlC+ol6wEKQgCxy4az9xpRfzqj++Qn5PM6UdOQaEQGJOXwJtf13HxEBkm5QpQuWJYdIqEMnklp/CMrz5E6r711Qd/7Xtv491XXwGnvkS1v/PsT5C3tUFqat96C3O7hmym62DCaneiUUd23Al0zQRB4I7fnMU1W7/jp72dbNzbwQ1PbuUP547l0DJXRimdRsld547l+ie3cPLcHJ8zg6Io0tndjSExMS7E48giLsRDoL6phayM4W/9UCoU5GVnkJedwdwZkwAw9Zipqmngp217qG9y5ejOSk+hMC+botwsDIny/YmjQWVtA4W5/WcjFAoFZ972n94c5cKUdKx2J6s2tbC7tpsus4NZY/ynmgzHmuWZFm4oyoYHK8LNVgdWu8iy6elBFbSprrcEXWRDCk9h5Gnd9Bbh7mW+xHhtzw7QwN3XH8kv7lzOCYsnotWouO+3Z3DVXe+ws/0jrj53HnlZSWH3OVgimdLO3CWiNQwM1Az00idn/1L3aqSFpnfBKjnt+/K/lxNL4Ek4lv/mFkhP89+G529vMIuCjVT8JRqIdt725jYTv39pB9XNZkxmBxabk5/2dXJoWVpvBeLxBQayUrR83ZjGYTmtPo4B7HZ7UDVG4hzcxO+UIHE4nQgIw9a/OhCJeh3jS4sYX1oEgFMUaWxqpbK2gY+/WkNXtxmtRkVBbhZFeVnkZqWjUgZ2V/hg1SoOmz2bBH14Qn5/TQOHTJso+Z3i1GdxLr8E03ebOPN/HeQbFExKV/LIYTom+Sh1L3fg9PXwj7bPaiBC8W/eU98DwOyxKbLWd5+j+kZLUIFrUvgSNZ4ivOy7GgA2z83rt46UGAdIzGphwuhMVn6zi+MWTyAvK4mX7juLF/77I+fe/Ao3XnwoJx4+Kax+h4K/iqlS50HqXnJX1ExICWwh9BS5oYqVaFt7g23fn3U8ki+8Uu01N0NXSgJ6P+uMVEIpwhUJOrrsJBsD520H+fe43GP4at0+1u3p4o/nlFJWZCA7RYtS0ZdJxS3GT1+Qw/JPNrH49hMln78KhYBapYr7h8eRTVyIB0ldQwu5WfID3IY7CkEgOzON7Mw0Zk+dAIDFYmV/XSO79lXz1Q8/4XA6SU02UpSbRVF+NsnGxH6W1m//dT7/90kXl0zWsbRIzT92Kbjxyt8zYXR/9x53YIwoinR/v5kEtTAgy0pzWwfpqUmIFQOj28Elxj/667mMTVHy0OH+rWGhWq98iUlfQjFahBpkWJqTwD0XjGP+xOCyn9gdIqoI+tl7u6O4Bbibsu9q2Dw3r9cq7t5G6hwvXZLOq+9tpKq+nR+3ViM6RSaWZnPRyeX86bHPWDhzFGkpsZlOzN/L3MoaAX2VE0u2msNltOVPnMgtLx5rhJqdxpf7k9yqqG1tkFgo9G4rZ7uRZhUfLFcc97WtrAGtESBwefhIF1I6eWkZgiBwzzOfc9vppeTN1A0YY4Tim5nTdjePvL/F9bePYO/U5GQqa2oIyacszkFHXIgHSUX14OUPj1W0Wg1jivMZU5wPuIRza3sn+2sa+OqHn2jr7Op1e8ne8Qz3/mDhN7P1rNhj5eN9ViaUpvLIy//gkTse7mtU/Jx99d289U0dX25qobbVQmGGjvLdVzJr7nmUl5WRlpKCgIDAF4ggKcbFigd4e6eFX07zb3mPxGDpLSTdYtGTaA1k4WT60KoVHDMruGBjU7dDMlAz1MDEQCJcbntuQTZ3ZhbPvrqDyto2LjxxJgCbd9Xz3U+VFOYmk5I0tC5V4aAwO3HqBNli0BfDJf2mFMH23Zf7k+ffUhVGPWnoNlMqUSgsTmTxvLatrZCWHpwLU7Avn/446fBJJCVq+duTKzlqZuaAMUaseICMJA2tnT1YbXY0amkJdersRF5esYLzTjghqP3HOTiJC/Eg2V/bQPmU8UPdjZhCEATSUpJIS0li2qQxANjtDvb853pe3KllXHEZjmQdp8+yUTg+ibwJY7j8zlf4aO09TB91BT/vf4qPVzazZuM+Tpufw32XTGBMbiI7a0ys29XOh6ve5p5//5uc9CzGFefy/ioDc6ZOIK1jW78HpduivqcTph85GTZvH/RzMdhW8cFArFxHtWNCWBU1Q/HV9XZNAd/WTKVSwVN/W9Rv4F0wc1TQ+4wGERHAwkDLbKTzfh9s+HuxcTpEPOPU5b4AjSRrOET/vvD+bbS2QWlpZNoOte8bttVy+LS+WW/3GOMeX5QKgczURBqaTRTkJEtaxc88NJeT/vwZxx12WOgHEOegIS7Eg8RitaPV+PdhO9gQRZHfPfwwOq2WsaNGkaDT0fbNk7y1w8K4VCW3zUkgVafAVDaZ/YrRbN7VzaJZs3j9rU5esD2IQmFi8ewi/nD1MhL0fWmrJpXApAVwAVBt2s6Xq83UNXaw8ps67n96FTdfsohjR5t6H5Dgiri32Z0kapUI5WWI6zYPwRnpz0jItFBdZ2HsqOBcO/y58IB/a7inCJeaaQBp94SRcK49EaxORPVAi24wlvFAgj0aFVx9ISVaAonXobDkmzud6IyxlTFqpCF1XU0mcNfBCccqHs49/cNP+7n1xJx+yzzHGIDMNAONLV0U5EgnAUg1qDl6ZiYfvP9IyP2Ic/AQF+JB0N7RRbIxXi3Lm6bWVt778ksKc3LYuns3JeJ+kjQCvy7Xc1ihS1gL5WUYEJlUZCA1v4aps/SIop6WVqirg86mZN78sAm1SiA/W0dRno68bC0atYLanh0oFAIOm56TjtVTmnYoO/Y1cuO975FwyaEsmVPaO7iLIqiUAj1WJwkHxPhII9wCNKFQ12hhocxATX/Wbyl/6M1z8/qJcV8i3FN8+hKWsSbCw83lrex2Yk/s7xIUrAj3/H+4FvRw772huHd9FQPyPo+e52ZbB6iKoQ6N5PeRZqiCI30htx++rmeoMwMioblVR9JffH9dG6NmnAxtW3yuY7bY0HsYjaQ4b3E+Fzy4ISJ9ijOyiQvxIKiorj/o/cOlSEtO5t6bbmLd5s18t2EDzYKTX01PIM/QJyDEdZtdFurKdeR6PKTzEmBy/oF1KtdhtUN1i5LKmmK+Xd+GzS5iTEyhMFeLuauTklTXyuNGZXLaUZNZs6mKxbltve1p1QqmFBtZvaWFI2f4DvgJJ6jKs/z2yhrBp8XWk1gbaIPF7hAHFESSGvgCiUtfBVncYnykiPBgRIG/IjUTlA4MxUoM6QPFdyBh6CvXvfe2cu7NoRDQEJkc9W6CeYFpboZJE6HOHPTuDwoC3Q9ynq/e4tlqhXAmmyP1+08x6mlqNZHs8ZP0dE0BaG3vIfVA3Imvc1GcpWfG6CRWbZZOcxgnjpv43FsQ7IsLcUmUSiVHH3oot195JcsfeYRZOSrOf6+T17eZcUrkhRUr1/VZsA/82/23RgUlWQ4OzdnD2dNquKC8lqXz01CrFHR1O3j5v7W8+HYNH65qIj0pk82bKwe0f8bCXF5fXRvRYwzlIS8lCIZjwJzJIqDXBU5RGW61xlBFeK5+3JCK8NqeHQM+cvA8Fm+RuCxPdKUubBfRJ4f3mF5ZIwwQ+qtrDQOuVyzdm8GcRzdSxyQX7/uqrR2SkwO/7HiKzXD8w2PpJdIfns9qOesGwvO4W9sgJSXEjkWQYxeN59q73+Wnfa5iPJ7pC+FAcoLOHlKMOr/HKIoiLZ226Hc4zrAnbhEPgraOLlKSYquseayhVqm4dIqexYUa7vrWxMcVNq6ermd6lhIOWMXd9CuG4eXL7bmesWUjhsSJzJ6axMJZqThFkaYWG7srFDgVeTy/SodGJZCX6qAwzcHYPCN763rYur+LggwdRr30bR5Jq3gwRNuPWfQ6z+FS3aKgIEfbb5mcvNih4hbh/lwHhppIiVYpFxXP43Y6RJQqoXfdYPG8N6WyhXhbyAfbx17q9xdJK3igCqK+EEV6gzWDEeMjmVBmRYKxjLe2QlpwGVWjwq/Omcs3GypoardKpi/s6voQjeoHNHUb/bbT2eNgV213NLsaZ4QQF+IysVptqFXKoCoRHqwoTn2WMcCzFzl446OPuPv997FssDF/xgyUHylwdqzH4RQRRRGnCM7GVrQqgXMnailOcllevcVkVa2ZUQWuqUCFIPDN+p289+U2du2v4eYTFUwsTKKmVUlVs5KqlmTmTp7FI++ZaGiv4YapVg7JtKCaNVCcRjrvr9zp7+EkxmvEIsb4yZgSrMjxdOnxlfoxll1RIm059nyp88TpEMlKsIckwOX46fsS5IMlxgdLhAeL1Qo+stJFlVi1ig+WW1JrK4wbOyi78suXa/Zi6ujg0LJSyfSF1dVdZBgDzxDqNQrJGeE4cbyJC3GZ7K9rHFBaPY5/lEolZx97LGcdcwzb9uxh/datCIBQUICw8SUEAZQCCFkq6rudXPJBJxeW6bh4skv0eYrJ6r11zC+f0Nv29n1N5GQamVNcSE6KFrUSijMcFGc4ENdt5sxx0O1Q8beNKr5tTmWvIwnn/+ykFiRSmOagMN1BaqIYVGCQp0+jHPEZSAj4K6YSSz7ldQ0WFs5K6f3bs99SRVPkvIz48q+XI8Bh5IhwN96W8YW5XTQ0wF7pgrBB4Vm1FOhXHAmC852OJtF0jZEbHAvQ0gppETjvsc5gCOxgjBxtbZCc0n/ZUD0HdRplb0yMd/rClRuaWVQW+AbZ19CDWqXAandEta9xhj9xIS6Tiqo6xpYUDHU3hiWCIDCxtJSJnglijz0W5/JL+q136lgtZ7zbwfGlGjL0Bx6CB8S43UG/YMF91S2ccfRUDvfImOJNgtLO3oZWLp/SyfxcNaIIbWMnU9Wi5LudGlpMCgQgK3kTRRNKKMjRYkgM/ScRjWIrUgORr2pu0UIqUBP8F02Rg1uMy3VBGeqXEn9C0Z/Ik2uZ9V6vsQkyM+T1Taovvq6J9yxEtHKT+8NboEVjlkFqmRwx3twM6SO8eHKsiXAAhxNUPgzNgynIVa17sNud/Za5RXhHt50Vaxr422UT/bbR0W3n1ue2cdHh+Tz6/sA4pjhxPIkHa8qktqGZvKwQRsU4PvEuX5+ZoGBunorVVf0DXNq7BZL0fWJtf20bW3Y1MGty4BejbptIms4lSAQBUrdvYmqRnWNnWDh/YQ9nz+9hcqGNji47H69u5sW3a3jlf7V8+X0reyq7sVidAfYwOAxVIF135vR+gZpSMwKhiHA3ckR4rARj+iKQuAs1iLCpCTIOJP6Re/yB9uOZJtLTUu59DaN5v/kTaO5zFcz58rxnFuZ2+X2R8CXQPWlpgXQfBs+hfhkcqTid8tIWRvs5KIoiT35UySVHFA74rqXTyi8e+Zll09KZWOA7jbHV7uTGp7cwf2Iqh08d4W90cSJC3CIuA6co4hRFlMr4e0ukUZz6bD/LeIdFJE3f/4lc1aKkMN01vWex2rn27nf55VlzSErsH0AohVEj0GnrE3veftNKBeSmOMllF4dMcwkEq81JbYOF/bVm1vzcgcXqRK9TkpTeTnYWbLcn9gZy+RKhvsSAlMCQa4H09N0dDKu4UFROzT4T+dna3v2DfxEeTIClnNzWsSB8/OUoDkYwBmtt7uwC44Hmw3kRcOMW4Z5pItd9nS2ZfnOoznuo1vhgtgtkGe/ogKSkgctj4V6MBLFmDa/t2UFnJyQZ5a8frWux5rPPaO2yceSM/ka3hjYLv/zXJo6ckcGVxxT5jRW75/VdJCeoufGkEvYqzwLWR6WvcUYOcSEug8bmNrLSU4a6GyMWtxhvtzjZ1ORgWmb/23J/s5KZJS4r+c6KJvZVt/Ls22v558vfcOKSidx6lNHng9GoEei0ikEFLmrUCorz9RTn63uX7W3dQX0DrNqsoafdguiEOqcCjUGB3aDE6fHyEKyYCEagyRXjkQrUrK6zMLpILykEA1nCAx1TrLqgSCG3YIjUOZHrsuR53KIoolPUkpeQF1K+9kB452wPFimhJUfgxUqGEX/3plZhIC8h9HMTJzADStu3QmoQGVOiJcaf+mg/lx1RiFLR/3f8wNt7WTI1nV8dW+x3+z113Xy1uZUVd85CWfIbqIy7pcQJTFyIy6Ciqo7i/JzAK8YJGcWpz/LxX85lfr6KZG3/mYemTgUZRpeLyOSxOTx02/GMG5WBXqvm8v97md81JKJQCHRbHHSZ7XS3dFGaouSWQxIw5KTy3wYb//jzWs5elMc5i3wPsL4yqNT27ECng/1qA7kHXANX1ggIFieqLieaRhu5ONldAVqDgp1dkJ0NRmP/6VYpS3Ig31xvwSUnq0UkRLj7PNQ2WFhQnkKTvX9/whGcUsSi+A6EXPccfz7Yvo67vdNOcpK63zpDmedbjoB2rxPpaouh4nlu5Zy7XP04zBYHOm1jNLsVcYIRpUNtDfd1HVpaIWeIS3Ss//JzqprNHDOrfyG43bUmftzdzh/PDZzS5c2vazl9QQ4J426NVjfjjEDiQlwGFTX1HLdk7lB3Y8TzeaWV08b1dzdxHtB2ngaKJXNcQZ92hxOFAO+va+TKo4sYk5dAolaJfl8lr9br+M2PNmaPS+Dv7+7jmPJMXvy8mpLsBOaOT5HdJ3/uGKJWgU2rwJauojTPlY5xcoKJ+npYvxE6O1xCPC3NJcxtOFHrFANyO3uKtGCJhouK50Bqc4g02XcBgYMAPZFr4R+OAjwUfGWT8SWiahos5GVJl9AONVONu3qp+9+euLePRKCm5/3jvjeDrbIYKr7up0AvM+7v65usZGcEdnmLBYI9X0NVHRUC97W1FSYeSIol130vWKu49/F7vzg+9dF+LllWgNrLBXVrlYlDxqWg1wZOWehwQqohjPKgcQ5K4kJcBj1mCwl633mU44RPj9nMT412Hljc/yHcYNWTlSQdMPnXJ78gPTOdulYzaUY1S6cd8OubkEqZQ+Smp7fw7VZXeeGt+7u49vhRPPtVm08h7iuTg1zLpyAIpKZAagpMGO9a5nS6gr9W79DS3Wqjuk0kURBwJCqwGxQ4EgM/3KUYjFzP3T0OUMkTZnKqX45k5BR2cgtmOa5ItQ1WJoxOCNied9tS33njq4Kpu0+RvFbBWMHDsfzL7bP3Pry3q2u0kp0h/QIUS3ifo8EuxOSLUHLDr641UNVmZl2bDtp8rxOOGJd6CfFctrmyk501Jh68fGA2lG6LA53Gd3yYpzEkzaimOV5NM06QxKMPA9DV3UOiXh94xThhYbFaUSsEEtRegZpmQ2+gpueDc1dlM59+t4s/XnsEKqWCuRNS+m2nUgrce/EEjAkqkg06rrl4CcuOX8aeqhY2W/IH7D+QCJcqE+7GnzVRoYCMDMgoUVM0U4tpgh7TWC22FCUKs4i+wsLub8zs+d5M3XYrnQ0OHDYxYPYHf30PB8+2ahosZB2YpZVrDffuc7gZT4ItGx8tIr1/f7MfYuU66ivryOzZ7HMdKfzdo26kRHis5BF3475n5Nw3od5fvrarbx4eQjxYhtolRQp/2XGk7mNf6wb6bQY6dlEUefyDSi5aWoBGIk1rUaaeioYeyW29j1khuLKmxIkTDHGLeAAqquspzh9i57WDgMSEBDRK+PVnXaTrBaZnqThylIb9ZiPLqrZAvmvQdPtxP/3WGs4/YQZbdzcwqdBAYcbAlyW9Rsnf/nA+X/ywh7sf/4x504s546ipvPnRz0y+5gifD2gpEe6LkESMQsBhUOIwKLGipjRPxGEXGas0Ud8ADdtgxc+gVkNWVhf1Sj36FEVvqXOIjoXZe1DZur+KfC+Xem/Lrz9LeLh9HGrxHQjv7BvBWMWl8LwfHU5Q+5ksCeSTHghvER6MS4q/QlSRxpeVPFr7be+0kWyM7WExVn4XcoS3nGxDdqtIvU1gr9d9K/WcCTbzkJwXkLe/q6e+1cLpC6TjwMoKDeyoNtHZbceY0HdveB6/2yr+/Y42Ljo8Xm8kTnDE9hMnBqisrmfWlPFD3Y0Rj1qlYvlTL7HqsSvotDp5Z6eVNbV2xo1WY1TZ+lXZbN/2PV+t3cvtv1zCyhWfkmaUtmC5H5SLDxnN7/7+AdVdO/hs7VauPP1QyfVA2h3Fl8CSWwXSH+42Dis0AZDnIXwtVmhsAGdDD41bwG6HT7SQlQX2IjM5mZreQjvh+opLDapNTTBtqu8+exJpET6YhCMsQxHjbrxFhfsaWCxONKqtkn2Usgp6F+iR+s4TfyLc3/FLiarBcokYzPvJX2q6g51IzL55u/opO52o9P4n50MpOhXoeVjTYuah/+5lS2UXf//FJDQqBc0dVlZvaaWq2UxNs5nqFjMJWiXzJ6by/GdVXHP8qH7te56PxnYrW/ebmDU2OWDf4sTxJC7EA9DY0k5GWvyHNRgYExM57uaXcS6/hBNKtZz/QRcpOX3+dm4xvmpzCzMn5fPoK9+x4rO9/PrEUQPa8nxA7m3dgs3uxOEQqa4xsWhWSe86csWrp8AK1goebBBmr+jQw6hkqC3oE0DJlFJdb2F3RTer17Ric4gk6pUU5OjIzy4j27zZZ3W6YLHbXVb5QERDhA+G1S+YffgLJgxHjLv74XnO6pos5BTnIRT1z+fmPUPjLbI9BbmUAHd/5+6ju+9u5Irwwaq+OdiYuh0k6iL044kS/u7ZaL0UhSq+5abdVPY4cXoIcc97V+rlMlwsNifPfVrFq6tqOHtRHnedN47NFZ3c+tw2vtnWyvwJqZRk65kzIYX8NB2vrKrB7hD5ZEMTSoUgmcKwuqGD6x7dxMVL89FrYvseiiOPK+64I6ztf3fVVRTl5spaNy7E/WC3O1AqFHELySCjOPVZ9Msv4ddzsnlsSwutBU5SdX0l77/cpCAzQcWmHT28cdsMspL7ZznwtnA3tVpIT9XR0GwmOyuBBuuufrm45eJLgIciSqSs6YEyPrgZOyqBsaP6AvlM3Q6q683s2NfNqoY87F2tGHQi+WkOCtIcZCU5gxbnPWYHGo/T6qsIynC1hPsSNKGKmWDEeKAsJ7UNFnI9MqZI9dWX0Pb3XaiiRsoaPxLFeH2ThawY9g+P9MupVHYbX99HA/fvQ9njxJKllrxvPQtOBWMV92VgcThFbnp6K1a7k5tPGU19m4Vz79+AUiFw+oIcfnfmmH7uJwCluQmc+df1XLgkn3e/r+8nxMXKdXxancSfH/uMS5fmcv7ieP75kcKaTZu4/PTTKcoL7po6HA7uevRRunuk4wqkiAtxP9TUN5GfEy9rPxQoTn0Wnv4tE41NvLjZzHXlfcKzptlCU7uVMxfk9hPhvgIuv6vS0GkWWbHGRH6O/0wUbkIRGd4CTmrg9FV5MhwBm5igZFxJIuNK3GWXc+nY8SPVLUq2Vqv4YosSp4hLnKc6yE9zkJ3sxF+h2Op6C2PysoCGAX31RSRFeKTS2UkRqF1fYjxQn+SK8UAzKrUNFsrG9X/pCSZ1pBSeIjwYa7g/l5iRJsbrm63kZEY/dWGgFIpy1w8Gz9k/KYEdiuiOVKyAwizi1AmSMzmRtog//2kVX29tRaOAntYuJk/K4s6zxzB9dJJPg1tKopo7zhrDnS/voKvHgdMpojiQT7fb4uAvj33CP38xicnFrtKgQvHNEe1znKFjYXk50yZMCGobp9PJH//1r6C2iQtxP+yLB2oOKTWWRC4aX8tF71k5d5KODL0Ci0OkpcVEu11gydT0gG2srjWQUwATpubz1cdbOO6s2f2+9/bzC6UISCCkrMmhCHBfKdekMOpEJuTZmeDxMt/ZI1DdKi3OC7QWsjM0KJWuAaa6zsKoAnkpO4eLFTwYwrGMg293JDluTV3dDoyJqt5+uPHlkhIMwQRn+rr/vS36sZI6L1zqG61MHhecG1mwBHIt8cTXi5/nveV9Hf1di0hauKXSJ4aMKPZWPvMnvH3F5Hgfr2SqwnWuDESHqxzMPtbIuFQlGqUAmBFKA7ueHlqWBoBTFGnssJKd4nphsztE7A6xN3d4XISPHC486SSy0gNrDG8EQeDCk04iLSVF9jZxIe6H6rpG5s2YNNTdOGixOZUUGeG8SVou/7CTy6bqePInM0aNwNSxaST4KbDgLWCOPHkGR5w4HUEhAP0HL1+WonDFhedAGsnc2lKDnixxrheZoJcW51t2dfHFd1YcooghQUVNvZlRBToyNWNptO6UbG+wxVckBF8wgkFqf8Fa6v3FFkjdE06nOMAyt7rWMECEB1OiPtw0heFa44cLnd12DAnR8+8NVqx6rx8rsxLhiG5Po8SyPJGVVfQvP+yDUO9dtwB3U5wU+vUVBIHS3AS2V5l6hbhRr+SwyWk89kEFd9/+ZMhtx4k9brj4Ytnrtnd2kmw8MCMiCEFtC3Eh7hNRFLHZ7ajV8VM0FHR2dWNQWgG4fKqeJI3AG9stFCcp2NLs4Lc5ln6ZVMB3iXr3Q1xQCCzM7cLhFOkx29A1/NRvPanKa8GU65baXkq4RUPAeotGuYGobnE+sajvzb/TZOfFt2vYVdHN12vbcDgNJCYoMaS1k5UF6elQaBj+FlAYKG7kWBjliHFvwSH1vWd7bprbbKSnqHv37YmnCHf/35cY92dZlOPXH+j4RppVvKZ7B2YH1JmlXzqlCGU2K1T8BXx7i/FoXotIu4stTHKyVudfiMt5gXUTSuYo73HEFwIwrSSJDXs7WDQ5DVF0+Zvva+jhkrN+EfR+48Q+bR0d3Pa3v3Hfb35DkkH6N/jj5s389qGHeO2hh3rFeLDEVaYPWto7SUtOGupuHLTsr22gaMFZsOteAM6coOPMCTpu+qKL08dpmZblunXdFg/3g9Qtxt0D0cJc18BhtTnYuLmFv6+o49t1DZjNn1CYrmVysZEpxUYmFxspzU1AqegbFPw91OU88L37EiqDnTdYrRLISNOwdH6fOO8y2amuN1BdY2HLRgt2Rw2JeiX52Vryc3TkZGhQq6NfHyzSIsPbbUiuhVGOeJUb4NqvjQOBmv58s92l6r1FuJxpfblZUgLhLY6Gqwh3n+fubkiUFz4yYFsIPu1jMHjfA1LBvoMpxsPF83dh7nIyMU8gXabFO1rB4d7jiC/mjU/h/rf3csnSAv63poGGdiuv3ToDzejDI9KPOLHFo6+8Qld3N4YE3w+HmWVlFObm8tgrr3DbFVeEtJ+4EPdBZXU9xQVx//ChYn9tA9MnjUUx9Vmcyy/pXX7TLD3nrejk+FINhca+aUbPB6lbJPdkTmHTeoFPv9vF1z9WUJifwDELTubas+eSlfYzO75fzc+rtrN+TSsvfmCnscfJhDQVUyZn9wr0rJToBm/5suLD4Alw7/1X11vIy+p/3IZEFeNHqxg/OrF3WVe3nRp3KsW1rdjtIjrdAXGerSU3U4vGT2noUAlHZMixZoc63S9VfMaXGPfexk1to4XpE4141uaTcgnxVaZeilBEuLdb1epaQ1CWyVAZrMI93jQ3u2Z6QsXXPRnOb1hKgHv/22/2HYk+herW5rluJJ5L7nvK3OHEmCXPXWQwXHA8XVm8RbkgwNSSJBaVpXHcXWtQKgSev2Eaan9R73GGNeu3bOGc449HofB/jY9dtIhX338/5P3EhbgP9lXVsXRBdNM3xfFNQ3MbmQfytytO7RPjeQYlF03Wcf8P3fz9cMMAf9q2b35mlSqLzzY2s3bnt0wtMXL41HRu/ucFZKQd77FmNhMbXmbiBB1nHljSYXGyqcnBpqZm3tlWz5+bHGiUMDlDxZTp+SycmMqYvESCwVtoy506HcrqedV1ForyAgdqGhJUjCtReWRrgW6zg9p6CxXVZr5b347V7kSrVpCb5RLnedladH58++USTOBqIAKJ5WDxFuTBCIimFhsZaRoaLP2XB5uSMBrZeXwRzbzxg+Vm0dwCWZnhtxdssLcv/Ilw7+X+UvrJ6UMkf0veBMq//9IaNZml/kWOr99PtF/SBsy2iq7PbaeP5tIjCkjSq9BH4FkWJ3apbWwkKy0t4HoZqalU14ee4ScuxH3QaeohyRDkXGWciOAUXQOL51uopxg/b6KWFbstnPdeJ6IINqeIzQk2J3RancyZqGLZ9AzuOm8cSQdywgr9RPjANgGStArm5yuYn+/y0RVFkaouJ5saHWzaUcsvP67g2NEarrhgBt9ub6W508Zp83PQqMKziHiLde/iKTC4qQNrGyzMmR5aEasEnZLS4gRKi/t+OxaLk9pGC1V1ZtZu6sBicaJSCX3iPEtHYohBcpESEZEW4+BfhPjqr9Mp9nOPggOi2iu1m1Q6Ql+EKsIDBRuH0qYUQ/HS6b3P5maYEIECypE4Fu/Kk4EIpeqkFNEU5L5w2EWUat/HGAvpMcV1m9nV6kDhsJO8YwcoBLII7MYSJ3QcDgffbtjAB6tW8eFXX3HPjTdy1MKF/b7/+wsv8Mk336BWqzl56VIuPe20gG0Gu82Y4mK27tnDwnL/Rtlte/cyKj9f/gF6ERfiEpgtVnRaGSUF40SFpuY2MtNSBixXnPosAFrg6aM62F9bi1ql6v2oVCrSUlLQayPjTiIIAoVGJYVGJceM1nD5VB0Pru1h6e3fMTpZyfZWB8fPzgooxD2FdjApxMIR4eGUu7fanGgj6FKi1SoYVaBnVIG+3z7qGq3U1Jv5aVsXph4HKoVAVoaGvGwt+dk6RKWshApBIycfuCeRdoXx1VZ3jwO9V2XHfm4hXtZvuQLc3z4DIeVuE26bsYjZAnp94PWiTaRfBqNBMO4p/tYTQ0uE0tsHOQjlZQMyp4TCGzssnDJWi1ox8IEUT1kYeVo7Orjn3//G4XDgcDoHfH/f00/z8erV3HjJJfSYzTz47LMolUouOvlkn22Gss2syZP5z4oVnLhkCdkZ0jVl6hobe9cJlbgQl6CypoGivLh/+FBRWdtAYW6W33VSk5JITRrcYNpUnYI/LUzkmhl6PqmwUtBgx7BlOyKRs44EW3Y9Eni+KJgtjoiKcF9o1AqK8nT9XGDsDpGGJivV9WbeW70HkwkQIDXF5TaQmQXJSdLiPBIuDNGyvsntlytQ0/dLZKiVXSNxn3iLr0jde0PpguUmHEEYSeS6o8hpJ5x7ebACPXt6oDDN7vP7SM3C9LqWhCjITTaRj/Zaef3E/uONuG5zr3EoTmTJSE3l/SeeoKahgWO9AiDbOzt5+5NPuPuGGzhi/nwAus1mXvrvfzn/hBNQKgfOroayDcDlp5/OJ19/zcX/939cde65LJs3D73ONWb1WCx8vHo1/37tNQx6PVeefXbIxxsX4hJUVNVRNr5kqLtx0LK/poGlC8pxLr8kJh903XaRZ3428+RRfamK5KbACpZQBqOQUngdEOM19RbysqNfXVAKlVIg74AfecFYl/XX6YS2NmhohJ9/hvYOQARjEmRlQGYmpKVBgFiaYUFtY1+QrFSwpCdDMWU/XCzgwQrJzi4wDrEhOlIiPFwG8xq3trpesk1BbBNO/0K1jr+328LsHBVZCf0fMrE4Nh0MrFq7FkEQONTDXWTZvHk8/PzzbNy2jZllA8fhULYB0Gm1/POOO7jrX//izn/8g9//85+kJycjAi3t7QBMGz+eO6++ulegh0JciEtQ19TC0gUzh7obBy2dph4MH18NEHNifHWVjTu/NnHDLD2lKdEN1BnsICWxch1V2zQUpjsQK/f0Lo9kRb5AeFtIFQqX0E5L6/PhFUXo7HSJ8527XAO60wl6/Q7G5GWRl60jNzOy6RQHw0pY22ChfLL0LE84WVyGM8Eeg/v+CeZ6tYSZMSVcwnVHkZopCcUqPtj3S0srpKVKC/FQCqDJMUAEK8b3tTt46mcz9x/W/xrF0ph0sFHX2Eh2RgY6DxfUgpwcVEoltU1NEdvGTVFuLk/9+c+sWruWTTt3snf/fgBKCguZPGYMi2bP9ru9HOJC3AuH04mAEDBdTZzoYLPZUdWuhdy+ZWLFA1Hzw/MO2AxEqk5AIYDD6QoSdfsMRsoaHsj/MhKDkT9q2xQcUmoNq42g9xmke4IgQFKS6zOmtG95dzc4OtTsqezm63WudIoajYLcTJeVPS9LS4I+9JenaItxs8XZz0fcn3+2J1LrDQcRLve4ItWeL5pbIC838HqxiL84gWDE+GAWJ3LT2goNugS0mv7LI1mFWAq5Yrze5OTqlV1cNV3fW7cCRq4IF6aOQ4hyut5+vPFtSJs1tbWRLFFcJ8lgoKm1NWLbeLNo1iwWzZoVXGdlEhfiXtQ3tpCTGThdTZzoUPX6jeTrXD+YflUzY0SMl2WouHKanru+7abVLHLJlNCno4JlMMSV1S7gHafsL9d5OETaPzghAUioZnFJ33lyZ2yprrewYUsnPWYHVrGLtDSXW0tmpsstQW5QaLTEuMMhopAIBAP51304iG+5DJYIB1fGlMmTQ958SAi15LsUQ3Xf7G1UMbq0/z0fqggP1gARyG+8zezkqpWdnDley8lj+8TpSBXhwwkBV0Yzb0RA4eNBHso24KqauXn3bgqys1kyZ05oHZZBXIh7UVFdT1F+PFBzsPAWwPvNuRTopK04Qy3Gt7fYeWR9D3vbndy1IIFjSlymnEj7hgeTacOTcK3hFhtoVIMTuTZYQXpSGVvsDpEt1TtpbIL1611uLgDJyZB5wO88NXVw/c4bW6xkpWsCrxhHkmCDST3Xt1oZYJUdapbliQP8xEMR3+EGbnoTqd/t6loDiOYBdSCCIdznHUhbxys7HNz8hYlFBWoumtxnaImL8NggPTWV9q7+97QoinR0dpKRmhqxbR575RXe//JLTlq6lKfffJP/ff45D952W2QOwou4EPeisqaBGWVjh7obBy01lkQOSXYF6kUrADIUlu+w8OiGHi6fouNvi7VolJF1SfHGLRTkWqvkDkq+LNti5TpqWpXkpQ5MFRUJBjM7RqDzplIKTC0aR23mDpjoWiaKrkDQxkbYsdPlvyo6XSntMg6I88kFY6KWUSZQxpSDiXBTLQaDKEYnRWYkiJTVW24a1EBEMke60yGikPASk/PiIPWsE0WR2lYLFpuTBK2SBK0SvUaJShn44nqK8U8rrNzzfTdXTtNz+ri+t7O4CI8d8jIzqW9qosds7g2QrKytxeF0kpslnW0tlG3+s2IFd159NUfMn8/SefM47brrqK6vJz878obauBD3wmK1oYs188hBhNWpRKPoE4Pe1gqheLB7BBsb7Px7Yw/PHG2kKKlv9JArwkN16xgsEe7+rrq+lfwJOhC3yN5OilhISRdscRJBgJRk12fsmL7l3T3g7MintsHKO1sbsFpdxYhyMl0+57lZWoyJyrAsexBeEaU4odPe4Yo1GEqiUUxKikhbx0PZvxtLl4jWIP1S66+fNpuD7RWdNHfa6LY62F3bzZbKTrbs70KlVGDQKTFZHPRYHHRbHBRm6plZmsTM0mRmjk4iN03b77dqd4j8c8U+0gzJNOys5fNKG/843EBZxsj3CR+uLJo9G0EQ+HLNGo4+9FAAVn7zDdnp6Uwd1/e87zSZMCYmBrWNJ+kpKVRUVwNQUVODSqkkScLPPBLEhbgHHZ2meDXNIaTLriJRaRvqbgzA6hQpTFL2E+GxgqxMATKFdE2DhUOmJiNoy3vbHY4i3BN/1nFZgbF6IA3GjkrsXW6zOalrslLbYGHrbhOdXXYQID1FQ16WhtwsLRlpmgEVMv3R3G4jNeXgKiIWqgtWJPe/e8+OIc2Y4ibWxbi/34lnv6Xaljouc6cTXZKin/uN5wyAZz/dv+En3/iBZ978noIMHdkpWnQaBSXZCZyxMJdJRQaykvvPKDmcIrtqTfy4u4MvNzXz8H/3olYquOSIAs5c6IrOXbOzjZUbmphZmoxgTObl4yyk6PpXdI4z+FTU1NDS3t4bSLm3qor1W7eSlpxMcV4epx91FPc+8QRWm40es5knXn+d6y64oDfJxisrVnDf00/z4G23sWTOHIyJiQG38eb311zD7Q89xIovvqC9s5PfX3NNr7CPNHEh7kFFdT3Fcf/wQcXzQVe9q4IiUw+KaROAgf7j7mWD+XCs7XLy2jYLiV5lmKNtDY8UwezfanWi1SqC3s5NrIlwOYQi/NRqBYW5Ogpz+/xHnaJIS5uN2gYLG7d20dhixekU0euU5GVryc3UkpulQacd+DIniiKi6D9oaKQy1AGmzc1QXDSkXejFLTyHQ3VNkO6nnL6vrBHQVYvY0pSQ2H859AlyTzHe2tHDi+/+yPJHLiKnZ6esWCEVMKEExuc/wDmL8hBFkR01Jq56dDOTCg1MLjby/tpGzjssj3MX58crZMYQT7/5Ju9+9lnv34+/+iqPv/oqJx5+OHdddx03XXIJKqWSx155BbVazZVnn815J5zQu35aSgoZKSn9MqUE2sabGRMn8v4TT9DW0UGy0Rj2rKc/4kLcg33VdSwoH2bh8yOI/TUNTJ3Yl4/OVwDlYInxzyqt3PyFiVPGaDiudPi5KwUjpi1WJ5oI5t2OFQZL6CkEgYxUDRmpGqaM71tu6nFQ22Chqs7Mmp/bMVucqJQCWekuy3lulhalApIM8UfxUNDSCjOmD3Uv+uMtyL2tzHKKO/kTxN5W8VAyAYX6suAW2wqzE4fONQO07muX8at8QX2/dZblib19fePz1cyank5uZhIIwQlmofhmV6C/IDA+38BZi3JZuaGJdKOaLzc1c/2Jo+IiPMa467rruOu663x+r1AouOHii7nh4oslvz9q4UKOWrgwqG28+dszz3DO8ceT58OH3BeiKPLgs89y/kknkS1zui3+9Pegtb2T1GRj4BXjRIX65lay0lP6LQtHjO/ct48ko1H2j8GbmVkqpmUqqTU5QyreM9TW8GAYyoqa0WKora0AiXolY4oTGFPc5/Jmd4g0NLtcW75Z18b+WjNWm8h/Vza4cp5nacnOiGxBojjS2G2gjlGPIF8uJIPt5+090xWKCPfOANPWoOXnhpx+y9yCvJcF9b1ifO0eG1OKjCAsCXrf0CfGAaYWG7n5mW0s/7aOS5YVkjnltyG1GWdk8/KKFSybPz8kIf7yihUct3hxXIgHi81mR61SRXX6IY5vnAdyfEr5a3mK8eYeJ/XdTrRKAfVzFyIIUNXpZE+bgzaLSKpOIEElsL7Bzrc1NpwiPLLUwKRfvBh0n1J0Cp48ysg/f+zh/Pc6uf+wRCaky/vJDKUID2Xf1fVm8sMU4oF8rgeTWBDhvlApBfKytL3l7L/4roWSQj0pSSpqG6zs3NfN6rVt2BxO1CoFORkHrOeZWoyG8AND47hwOMVBTVEZS0QycNPbpcTX9+AW2yJTcFm/y76r8dnuOvLggJW8vbWbcYecE1Y/3WJ87oRUVvx+FolaJZrSW8JqM87IRRRFVq9bx/7a2qC2czidkjnL/REX4gfYX9dIQU7mUHfjoKW5pZ2MVN9ZIxSnPss7953L39b2kJeowOoUsTnACeQbFJQkK0nTCVR1OjHZRPINCt46KZkfam1c86WZ+0bfwaylf/LZvrfV3e0DrgZuUGxmYrqVqz/tYlJJCg9ePhF/jiqDKcKFovJ+AZvB7Nszs0hNvYVZU8JPHzGUYjyWxbc/6pqszJ+ZgkajINmoZkJpn+Os1eak/kBg6LbdJjq67ACkJqvJzdKSk6khO12DSnWQKsowaG61kXyQJqqJtAj3/rcUbou3FgcWVH5FOLhE+jryKF9QT1VDd9CWSSncLijSmaPjxOmjvKyMDdu2sWHbtqC3nTV5Mgl6feAVDxAX4georK5ndFHeUHfjoKWytoHCXP8P2n3tDi4s03LZFP83uGcg5TJAP7GVW5/bhvmJ09BoE1Gr1WhUKtRqNWqVCo3YhFqpQK0S0KgUaFQKVD9vO/BvAbVKh1qp59i5ybz1dZ3fvMPDzRIOLkFusRokAwlDQW5p9mDaGsnYbE40PvKTayQCQ0VRpLXD7srassvEqu9bsTtENGoF2ZkaV2Bo3HoekG01+2IiY8pwwtMtJZDwBgl3E2DS1lpUOpFumfJj3dfZ0NFNTkaG/I7GiRMmT/35z4O2r7gQP0B1XRMLZ08Z6m6MCEIJpqyqbWDx3Bl+10nWKmgx+y444yuTyYKJqXz4x0PosTqw2Z1Y7SI2hxNb5kSs+zdhsydjtTux2Z3Y0kqx2RxY7Y7+/2+swGYX+e2ZpaiVsWV9DDfDic1GVAI1A4noYCohjlRsNpf7STAIgkBaspq0ZDVlYz1yM1v7rOdbd5voNLms5ylG9QHXFg1ZGZqg9zdSaW6G0tFD3YvBJxo+5lKC2xNP67cqR8TeLe8Fsey7GjYdkoXDbCc9JSWcLsaJE7PEhTguC5PD6USljL080cOVYMV4e2c3yUb/OTq1SuiySvteBUonqFIKGPV9t3uveC08zOc2rmwCkw78Nb13ua/c3cMpONOTxkaGpKrjwSq+PalvspKdEZmMPFqNgqI8HUV5/a3nbR12ahstbNvTzao1rdjtImqVguwMDTmZLv/zZOPgx8eEmqs+UrS2gY/q1j4JlDM71hlsES7lfqLSOzE3BxEha24DrdFnvuc4cYY7cSEONLW0k5l2kDoLRhG5Ytxmt6MKYGUWRZH/7bFy+RSd3/Xk4G/g93ankLLaDlfB7YmnL7e5LYv8nOGXnnEkUBPl0vaCIJCarCY1Wc0kj4qhVpuThiYrtY0WvlrTRluHq5BWkkFFzoGc59kZWrQ+XGbCRW412GjicIAqjBFwqCtV+kOqQJC/vsotfBVM4SFfPuAKtYhTZt22zXPzEOt+RjDmytsgTpxhSFyI48ofHi/kEx3kiPHa+mbysv37/327YQMWu8hhhQMtKXKL6wTCU3RLDTYLc4Mrmz4cyNWP46v6Osonx9N2DgW1jRbGj45OtTZ/aNQKCnJ1FHj5nnd2OahttLB3v5lv17djtTpRKgQy0jTkZmnIydCSnqpGEUTVUG9iQYTv79pBjHmYRRxP0RzNF4byBfX9rOKBgjAFj//6Y/NcV8yW2FnDqPLwA8njxIlV4kIcV0XNYw6bM9TdGLF4ZyTxFuaVtQ0U5vkO1Owxm7nnwT9x0yx92NUHpazZvgS4d/lltwXMM9vIcMbdf4vFGbFAzTjB0dFlJ8kQG+deEASSjCqSjKp+Lwd2h0hTi5W6RgvrNnXQ3GbDKYrotEpyMjTkZLqytxgTAw8nwYjwaP7O2lohFJfjWLKA+zovns+zSPVXyiq+LE+UFbDpZvPcPJQ4GU8jW+b2N3y5xbtbfLuZOa+W9T9XklR4eJhHECdO7BIX4kB3j4XEhPBdHuK48FWExxfVdY3M9ixH6MU//nARUzNVHFY40H0iUtZwuXhOR4dSkS7WsFqd8cIxQ4Q712ysZzZRKYUDYru/C02P2UFdo5W6JgubdnTR1d0XHJqT6RLo2RmakAKBPcVkMIJcbqae5hbIGCYZU4J9xoSatSjQ8yxUFxVPcZ2AjW6J5K+e67grbAKM62liU4KO50+4Qta+4sSJJhu2beOZN99kx759tHV08Pxf/8r4khK+WruW/OxsRhcWhtTuQS/ETT1mEnQjq6JgLOBLjEu5qVisdrRaaR/lqhcu5P09Vt45ZeDUpKcI97Z0S1neAlnDvfFVoMJ7++EsxmsbLeRmxu//oaC1w05qkrygtVi8z/Q6JSWFekoK+9KJegaH7qro5pt1bVjtLveWzDQN2YKKnGQnaQanT9cQX79JX4I8lDSZzc0wwfe7/6ATjWsrx2LuC18zF7lF5f22l7KKe1u13ZQvqEfTaENUCKSnW/3u3/3s/XD5fi476viA/Y0TJ9p8u2ED1/7pTxw2ezbnnXACDz73XK8x5fuffqK1vZ27b7ghpLYPeiFeWV1PUdw/PCp4i3EpEW7qNpOglxaCzuWX8O4uK0eXaEjW9h+1A1nC5RS6kRqQgrH0eLYTayJJLlV1FvJzoivEh/P5iSa1MgI1vS3DkTqP3vd+pNr1FRxqd4g0bt5AXZuCdXvVNHcpEEXQqkSya1t7Lehy3HQikZ++rY2DtpiPVNGt1bUGPlvxEz0NP3D7L45mjJ9JGvf2cp+VnhZuRY+T8kkq9El9Rg5vF0BwPYdtdiePb27m9+cvkHtoceJEjcdeeYWzjzuOmy+9FIfDwYPPPdf73azJk7n/6adDbvugF+IV1fXMLBs71N0YsQQK1Nzvp5CPwyny7i4LDx/e/2HvLcJ9ZTEJJjuKJ/4GGF8+l8NVbNY0WJhZFt1ATbnnZajT2Q02tQ0WJo31LWSk7tFI3GfRatcfKqVAToqTnBQnYO9dbsmeTn2TlbpGK9v2mGhobwMREhMhPd31yUgHbYTfFZ0ixEK22lDPuRxfe3+/I08xvrrWQEdrN99+vp0LzxjLFXcuZ1xJBjNyBcrHJFE+JrnXfUqsXIdQVD5AzHuK7XVfZ/f7G/oE9p79TrSJguR3btzP2J/XT2JMUS1FufGMKXGGnj3793Pl2WcDA90JVUol7Z2dIbd90AvxhuY2MtJThrobBy37axsoG1ci+d3WFgeJGoFxaZG7TeVa07zFuJygp6ES4+EI2B6zA70uBhSJB/5ExkgS6Q3NVhbPPXjSRnrOUrmvow4oztdTnO9yb6ntaUMUobsbmpqhvh62bAWLxZVnIympT6CnpYI6iHTUbuz28NIWRopQnhXBBLsGU+8gKTWB6XNK+HG3hScfXEDNHj0/fr+ev761B71WyU0nlzCtRF7mEk8R7i2yRScolILf56n7vLz63ntcetppsvYZJ060KcjJYcuuXcyfMbDw4Jqff2ZUfn7IbcfA42josDscKBVC2Jk44oROfWMrh8+fKfmdySaSqvMf6OXL5URqkAt2SjuWMiR44muAdVur/OF5bqw2J5oYqbIoV2DIOcbhgsMpolIO7rMnEm4d4SBnlkoQXBbxxEQoLur7XhSho8Pl311RAes3uES1QnAV5klPcwn0lBT/1u6WFpeIHyqiYQUX120esMyX+54vq7ZqzgyqX1/J1z/Uc9Exh7No9miu3beW99Y2cPMz2/jtmaUsmZLe7zfoekYaBviJewpw93PU6YQOvf/nqvvcrNtcTXNbG4tmzfK5bpw4g8nJy5bx8PPPk2QwcPShhwIuDfneF1/w2vvv85vLLw+57YNaiMvJX30wIyfzSbCl7D0RRRGnKKL0UTHN7gSVTJ3iqxCPrwwCwRS7iCUCCdZghKrLR/ngscjGEmaLI2rFckJhOLhVCYLLrzs5GUZ7lKZ3OKCt3SXQd+x0+X+7i/WkpfUJ9KQkUChc66WnDc0xRFqESwlw7++kBLm3mF5da0CpVnHKBXP596NfMH5MMnPHlqMcNYsTFOto7bLxw442lkxJ793eM3DTl3uJJ52dYDzgBefvPNj3reX+xzdw3QVXoowF/6E4cYCzjz2Wnfv28ZcnnuC+p54C4PLbb8dqt3PS4Ydz2pFHhtz2QS3E44V8fCM3/WCwpew9aW7rICPV93Sn3SmiDtNiGEiAey8PVZAHO8CGkiM5EoVQPPdXXW8hPyc20nZ6B9eOdOoareRk+Hd8lgqqCxepF9NYEOHhHKdSeUBspwEe4T42G7S2uoT3ps3Q3uGyqre1QvEoUBzYzmh0ifxoM5gi3N96nsLc+x7LzElmyXFT+cs/NvDwnxIoSZmIUFTOxMI2Pvupud/v1C3Gzxjt+/p5HnN7jYmSbDu5et9RsmLlOl5dVYNOreSohQtlHV+cOIPFHVddxfGLF/Ptxo1U19WRn53NIVOnMmvy5LDaPaiFeFVtI3OmTxrqbsQcweQAd68fihjfX+M7UBPA5oRIprj2FuHu6VRPa44vv/BIipVQMmEE6xsqxypeXW9h+qTYqagpJwXlSKG2UV5pe2+hFKn7MNIBn+G0Fy13GbUasrJcH0/+9x6UlkBLK+zf77LUirgCQt2CPi0dDImRE+jRDMoMus11mxHKywY8J9zPwWmHjKJiVwOPP7+FX1/hskhPnLuQ3c/s4Ob73uOCuQlMHZXUr3+5Mp43jS1WCj0ruUoc2wufVfHKqloev2pyzOfXj3Nw8c7KlRx2yCHMmDSJGZMiqxsPWiEuiiJWmx2N+qA9BZIEK8LdiBUPIBTfHNQ2+2sbWHTINJ/f250QrAuzL5cTXxUzvf+Wkzs8HIYiY4UvzGYHCTEWqOnJSLaS19ZbmDJeXprMaFjGY4WhOC4ByMtzfTwxm12FflpaYO8+MJlcy3W6PheXtDSX77pcjTjYArzni/29/9Yv9l1cxFOM5xaVszB3R+8zUhAEjj5tJs88tJJ//beRq0/KpEtRwVt/P59Va/fym2e+ZkaqyHUXTiMvXSe7v42VOmakWBAr+z9jeywOVm9p5YN1Dexr6OHZ66eSvWcXzA7lDMSJEx0efv55cjIzmTvNt2YJlYNWhbZ2dJGWHDvWwIORtg4TycZEn9/bnCJqReARzzMNlze+rODgSrMF/aP8V9YIvWLcs4pmJAhVdIQyKAeyittsTlRyHfCHEPcxjLTUhiazA0OC/MdvLLiP+CLUvg2FCLdafWda0ekgP8/18aSnp0+g794Dpm7Xcr2uL3tLejokJAyOi0ukcItxKbQ6NaddPJ/XnvqKxrpC7vzFaHIzjJxx9FSOKzXz/MvrOffedZw6TsulF0zHoAt8L5ssAonaPhH+w4423vi6lu+2tTG52MgR0zO467Y/YkxMhOmROso4cSLDvBkzWPPzz3EhHkkqq+vj/uERJFhruN3uQKVU+J1+VMz6BTWv/Eu2IHcj5XLiudwbqby3kUZKdMgR+tGyCNc2WmW5RsQKI0WAAzidYsxmapLrBhPLLwb+aGlxieZg0OuhIN/18aS7B1qaXSJ9954+C7pe77Kcj80toCPDjjFRGZSbxWDPAklZxQGycpO57MYjePO5b3j1HZGbznOVIk0Ydyu/+iOc8tJF/Gt9D6f84XuumKbn5DEaVP6e063jENftwOEU+fdGM//bbeGKaXr+70QDqToBxakPRPtQ48QJmf+74gp+fc89/POllzjzmGNQS+RATQuxSthBK8T3VdWxZO70oe7GiCAU//DahmZys/yPiEfMn89Hq1dz65c/ce+iRDR+AjelrOG+hPdg4ylugqnaGc0BubreTH52bARqHmw0tdpITwkhrISmbQABAABJREFUAXaUGanuL540RTBjSoIeEgqgoKD/crdAb2qxsmVnFx1drgJGiXolWRkasjM0ZKW7qogOph+0223F02XF2yruXT8hIVHLcWfM4rXHP+OME7dRZJzQ+13O+c9zuukC9nc6uee7br6ttvG3JdLPtx6HEp3SQZvZye2rTdgc8NJxSaTrXb6H4WTfihNnMLjw1ltpam1l/datPLt8ueQ6P/pYHoiDVoh3dJlITgqulHmcgQR6gPryOa9oyyFf042Y96lPa7pOq+Wh227j/x58kF9/toa/LTGgD+BOsbJGkHQ5iTZSft7hCJtoW8Wq6yxMnRB3zRoK5JS2jwWGa7VYf7S0QJFv1+mIkKCH0rEDz5up20F9s5WGJgtbd5loPyDQ9VolWekugZ5p2U5ygis3erj0fLFf0k9carlnOkLvuJr0LCOF+Qa+/qGOomW/6t3GYrXyy8+sXDpRxS2z9RQn94838fRXr1Sn0yTUc87eVpYm2Pn1SVm91vO4CI8zHDhm0aKotX1QCnGLxYpWE3sWqVggkg9Ff4Gf1eZEZhobAf+Bnmq1mntKt/LHegXXftrFP26chW+vchdyBXj5gvoBbilShSi88SWwAwlvX4Gk3mInEiI8kCtHj9lBoj52AzVHMrWNFmaWyatSOFhI3bsjTYQDdHjkso4Wvs5bYoKS0Ql6Rhfq+y3vNjtoaLLS0Gxl+14N7d0uK7FGJZKV5CQr2UlWkoO0RBHPkgtCeZnfFIb6xYVsbbazvcXBgnw1Bo/l/vruvhc8n3+JJ5dy/yOb2Ln9XyyYOZPFhxyC0+nEoLCSZ9AzIX2glNAvLqTni/2sNSt5wZaO097Nn/9wN7OnTPG5/zhxYpVfnnVW1No+KIV4Za3/tHlxwsdThO/vdLCt2YFTBLsoohIEOlRK9If0TXP6EuNixQOoFAJ/XJDAX3bruPLRTfzryskkJaj6iU33lOqyPNFnFhQpVxUpES4lwH2JbH+uJp7tyCkgNFi+oTa7c9ArOsYqoeRzD5fmVhsZqZEzBARTyjxWGEo3mGh6g4RyHyXolIwq0DOqQI+Yuqt3udkGjR0KGtqVrNmtocWkQBRBpYRMo4OsZCeZFj3pGjMqwfXs8hbZb2y3sLnZwUPreigyJjPP3s3SFjvjUn27xXjmmnf/O3f2OCb8eQLfbqjg+Xfe4T8rVvD3qdU8doSRX33SyQ+1dg4tUJOmU5CsFUjSCmxvcfAfewr7e5wcMzWNMy+9mcz0lKDPT5w4I52DUohXVNczsbR4qLsxYvG2hP93l5V3d1mYkaVCpRAwO5S06Xr45u9bOXxqOodPTScvXTdAjIsVruCd/UWj+WBtIzqNnXaTnV888jOP/aoMbw9zTzEuhXu5nHLM/pDr5+1rvWjlJ5dLXaOVnGHgGjGYDKYgdzpFFGH6Hsh5aZObaeZg8A0HV3pCbYDbXu6LtRSRvnd0aihMd1KY7uy33GaHxk4FDR0KfurKoMmqwykKKASRdLWZLE0PmQc+BUYF21ocvHNyEjtaHXxVpeLGz02MSVXyf3MSyEn0nR/W83jEynWUACXT4OwpGdz68A+8vFXJL6bq+c/xSXywx8r/dltptzhpt4i0WURGJSk4ZrSWk8doeFO9mDQ/xdvixIl1nnjttYDrXBGi1fygFOK1Dc0smTdjqLsxYgiUe/zUsRre2m7hzvmJJKoFdpiSacpOw2m389lPzTyzsorsFA2HT01n4aQ/oFBAV4+DfQ09rPihgcrGHo4uzyQzWYNCIbCj2sRlj+3k/t+MZWxxRr99SeUN98ZTkIcqwuUEgkq9EPgS4YOZKaG6zkx+9tAL8aGu7jgUAtTU7SAhhlyC5FREHCk0t/gP1Az0gu0vy9Fgni+1CvJSneSlOqE4qdc9xSEKNNt0NFj17OhO4eu2XIRUgcRuG5+0OClJNHPG5B5+Ma2b17Z2ce6KDq6cpuOMGa4XQ++Up1LPJHHdZgTgqul6Lvuok/Mn6sjQK7igTMcF0pkQUZz6LM63P0apiGB1tjhxBpnHXn3V53d6rZbMtLS4EJeL0+myLsQfCpHBLcIbu50kaQW0Ei4PeQYlhxao+dO3Ju5emMh+s5GJTTvJX1DCoWVp2B0iG/Z28NnGJm5/cTsqhYBBryIrRcNFS/NZMCkVtdJ1vU4/82gu+92bmHqsXHbH6xx/RDFnnTQajbq/uJEaML0H2mCK93gLcHdAqBs5fumDJcIDWUCr6ixMGeJAzViwwkaraqU/ahst5IU5GxHs/eIrp3wsXIPBJJTUhcMBt6+4UhDJ0vSQpekBXEXrfvOliYkGBUdkptJg1VM19nLWrfsviZkqzkoR+bqxhy+fauKshalMK1aTXLHOp+uOpz/6qGQlM7NUvL3LwrkT+2df8o4zcjic8fE2zrDnixdekFz+2XffsfyTT3jqz38Oue2DTojXN7WSnRGh/FUHGT0WC+0dHeRkZgL9LeFHvdkOwJQMJdOyVEzLVLGwQN0rzH87N4Fff9bFXd92M65Ez+K0nt7UWSqlwKwxycwa4z8Hp1BUjhH41x0nc/HvXiExQc1/lu/i869ruPLCiRQXGMlI01Jg6PM99xQb3qm5PPFnDfcU4d4C3E2gXOSxYAl3M9SBmrEmAIMV4OEUF6ptsPQr832wMhTVQpuboWSU9HfBpBX1JhZmD9wpCD3F8vObLTR0O7nn0EQ0SgvpZz3u+uKQqTiXX4IoQle+kjc7c3j0/Tqmjc4iUa/HoFNh0AlkdtWRqXa5uLj80PvvM8+goN3S35ghFezf0tZBetwtJc4wJ9lHlPcpRxzBlt27+ceLL/Kbyy4Lqe2DTohXVNczKl7IxydSbiYOp8j/dlt5fGMPFjvo1QKH5qu5fKqOzASXpSMnUcE/lxpoMzvZ2Gjnje0WHljTzWVT9Jx85nR0G7fy0BID13zahbPFiSLXCQh+q7t54hY9tT07QA+P/3Uh3/3YwHufVLJhczO/v98ljlQqBZmp35CbaSQ3M4m8rCROWVaGYKwDpMW4LxHuywpe9l1N7zqb5+YN3BBpv/NA2VHcg6ic8+GLQOIwFgM1h1LIBLPvAdcrBEFe22hh9tShFyWx9jI0GHSZXOXpwyHS1XY9iUi2pAPW8XqTk+c2mXn1hCQ0SmGAQFac+izO5ZeQNGcClwLHlut55L297Nveyv5OJ08elQwJiTRa9WzszKDZ5vJDFwSRNLUFo6Kb1Q2N/GmO0JsO0VfGrYaWNjLSUsI+tjhxYpXZU6bwjxdeiAtxuVTW1DN90pih7saw4tefd9FmFrn/MAOTM5RUdjr5704LZ77bwanjtCwtUtNjE0nVCpSmqCnPUXPpFNicUcRj71fw7N3r+OVRRZw4J4u7xorc+3YX91foueXU0SEXtPiuMYmFhyhYeEgO1bUmVq3q4vMfdtNlspKXlcTogjSKclOob+7iwtte47fXT2XiuFTZ7UuJcE8B7qbsu5oBYlwq+0osWM0A6hut5GQOvX/4SMKX64cUFqsTnTa82QihqDws0RYrInworOK+Hjf+ZssGi3Cva2875WUsf3otx5RoyElU+BTInstzi+HPqa7g+KefW8v1n7bzyDIn05NM/bZxiLCzQ8O96wSm5Wey1Z7M+nHjQCjH8NFXZKankJWWQmZ6CslJBhSCQGNzG6VF0gaLOHGGOzabjc+//x6z1RpyGwedEDdbbOi0mqHuRszitpR4MidXzevbLPxnq5luO3RanBQmKXnhOCNvbLdw59cm2q0iSq8ct5OBf/1qMhv2dHDnyztITlSRmpTNBYel8Pf/7uHhd/dxw0klAfskJXI8RW5+biI3XjyDGy8+lP21bXyzoYJv1lfwwVfbGZWfSmaqgRUrK5k4LlWWNdx7HV/uKNBnEXe7pcgV4VIDbjiWcJBnma2ut5CfExfioeBPKMkR43aHiDISlVoC9EVq3YOd7m5X6Xl/yBHj0bKGu3Ffq3AEud0h8vY+J48tDs4FSii+GbHiAS67eBbaz6u55NNqHrp8EhMLDb2zdbta7dzwWRvnTNRxwSQzgtCE4tRnEUURU7eZhpY2Gpvb2LG3iraOLkREauqb6TFbaGnrIDM9hYy0FDTqg056xBnmnHrttQOW2R0OmlpaMFutnH/CCSG3fVD9Gjq7ujEmBngaxxkgxs+dqGVCmpKGbieJagGjRuCR9WbW1tm5cVYCN84Ck00kUS0tMqaPTuIXRxXy7vf1HD4zjzFZ3djtTr74uZmrjytGo5IXyCMnw0Nhbgpn5aZw1jHTsNrsbNxWy9frKxg7YeA+Ag2qcjKjQGRE+GBRXWdm8riMwCsOErEyUyCXQGLcvY4UDc1WstIjZwSQI8a9+xIr1nA3njmro0lzC8gJDYoFyziEJ8i37O8kNVHFmKVT/Rb8kdzvATF+/pJ8slO0XP34ZhZPSeOkOYVs2d/Fk1/s5//OHM8RMzJ61wcQBAFDoh5Dop7Rhbn92nz+rQ+ZPmkMjS3tbN1VSWPLT9jsrqqiycZEMg9Y0DPTUkgyJIQ8SxonTjRJS04ecG8qBIHJY8cyd9o0jjvssJDbPqiEeEV1PcVx/3BZeIpxhSAwK6d/AZKTxzj5vtbOKWNd1lVfItzNorI0/vrmHsYWO/nXuxu5YHEeZy/KCzufsj80ahWzpxRSMKYnrHbcFTjd1m9Pd5TyBfU+UyAOpgiXa/U09ThITBja9HmDJb5ijWiUtvcnxkO1hA/Fy5HnPqNxXzQ3RydjSrTPldQ1DPQM+XZbG3MnuNzwQpllc4vxI2ZkMGd8Cs98sp8/vbqLiYUG/v6LSUwZZexdLxCiKKJQKMjNSic3K33Adx2dJhpb2mlsbmPLzn10dHYDoFYryUhNITMtmYz0FDJSk+NW9DhDSjhZUQJxUN3ZFdX1zJ0xaai7MWyQclNxMyFdyfObzT639Q7CTE5UM210Mmt3tvGLIws5dX6OrD74EhOeQVOeFeD84W3p8hV45V0YaGWN0D8jygIl5fi2gsPgZkaRK7jsMRaoOdys4W5C9eWtbbAwvzwlKv1xE05Gl1jB+76IhDBvboFxYd5u/n7jg0mg++/77W1cfqSrwqYcsSy5jwPbJQM3TIQbQmoFurp7MCYmSO9DEEhOMpCcZGDMqPx+31ltdppa+wR6c2s7NpsDAKMhgcy05F5LepIxEUXcih4nyqz4/HMWlJeTmjQw2H5vVRXrNm/m9KOOCqntg0qIN7d1kJYytPmThxu+xHi6TkGbRX4eboCbTy1jd4OaZZPlpS7wFBOeg3Ekp44DiXHwXQDIvZ6bYC3gkciSEgx1TVay44GaEcGXGPIngNs67KQmRfeRG64AD1ZcDkYe9kjMoPT0QEIYXomxIsID0WW2s73axIzSpJBFeCRpbG4jI81/WlopNGoVeVnp5ElY0Tu7ul1W9JY2tu2ppKPThCiCUqkgPTXZZUU/INTj8WBxIsWd//wnz95zj6QQr29u5pm33ooL8UDY7HbUKmXc/ywEpMS4XiXQY/MvxL2t4nXtKoozHLL2GSkR7t7WOwuKnGI+3v6icqzfbgJZTIP13fRFMMKrus4SExU1RwrBWMZFUUREHPLnTyQF5GC7FoWaZUUMzl4wgOEiwgE27u1kUqGBhLG3DnVXAGhsaSMrgqkLBUEgyZhIkjGR0uL+mVjsdgfNre00trazu6KG737c0pvJIkGn6yfQ01KSUCrjRYbiyEcUpZ/fTqeTr9aupcfs20MgEAeNEK+uayI/J3OouzFs8Rbj3XYRlQIsDlGymqYU1S1Kphfb/K7jL7hMrmuJFNEKworlQdmb6jozZWOlHWXd53k4HU8s4CnG/b0UdXQ5SDKMnMetlCCW6yI22JhMYAgif7j7WRHtDCnRYHtVFxMKwkyWHkEam9sZV1I4KPtSqZRkZ6aRnTkwKtfUY6bpgBV93aYdtLR14HA6ERBISTKQ4SHS4wGjcdwc98tf4nkn3PTXv6JV94+Xa+3ooMdi4fjFi0Pez8gZGQJQUV3HqILcwCvGkUWGXsGsHDWvbbNwYZnvNFmeVvEeq4A+iJlCOZZw94ApVwSEUtbeE7m5wQNZSyPhjhKsG0JXjwNDYv+f/MEWMDlU1DZYyB3hbkGDIcJDsYo3h1Da3pcIj8UXDU+2V5tYOEl+vYRo09bRRXLS0GehSdTrSMzXDUjW4BRF2ju6XCK9uY0tOyvo6HTlTlcqFaSnJB0Q6SlkpCWToBvZv+E4/Tn1iCPoNJlo7+qi5tNPyc/OJtnQ/37W63SUjR3LGSG6pcBBJMSr65pYUD5lqLsxorh2pp7LPuzkhFINqTr/03w9VtBr/ItgucLSM63gsjwxaDEeCWJ9QPbG7hBReWWoiYvwyBHo3q1ttDC2WDpobagYyjzk3vuOZnBpczNkRylZludxxEKAbFOHleyU2BGLImJMB1IqBIHUZCOpyUbGlhT0+85ud9Dc1kFTSzt799fww8atmM1WRES0Gg2Zacmkp7os6RkpSWg0ah97iTNcuez003v//c7Kldxw0UVMmzAh4vs5KIS4KIrYHU5UqqFN2zbSKElWctYELee/18ldCxMoz/b9IKpqUZKfJs8/3BtPy7R3bu++vyMrxgNZw4eaYAf9ukYL2ZmBpyNi1b0glpFzLeobrSyMQsaUUIl0Jp9g7hmpfQdTnTRYmltg0sTw2wl0jIOVscbftdNplFhszqjuXy42mx21avhKDJVKSXZGKtkZA2cYzBYrTa3tNLe092Z1sdpcudET9ToyUpNJT0vG1B07Y0ac8Fj/9ttRa3v4/kqCoLm1g4zUgZGuccLnl9P0TExX8n+rTJw4Rssvp+lQe1lexXWb2a+bwfhcu9+2vAdj9zS0XP9u75SG3gTjJy61brB+o5EqWR0JXIGagSvtxUV4dLA5nKjVsRMcFlSgaYRFslSxmmDaD9Y9xWIGXXBFJsMimi8Vga6ZTq2gx+pArHhgyLOmNLW2kz5Cx12dVkNBTiYFXnFnoijS3WOhqbWdppZ2tu6uHKIexokmzW1t2GwD491yMkOLQzwohPi+6jqKC+TlrY7jG3fAZs8X+wHQL3YF4eQblCgEeOZnM69vM3PZFD2njNWQpO0THrV7u1g0IfhUUt5ifFmeGLDiZaguF8GkSRtqy3Gwg311vZlJPgI140QXq82JWmb12MEkHDEeiXt/MFw5RBGIgGdE0KlJo2Adl3OtppUYWbmhmSNnZA65GG9saY9oxpThgCAIJCboSExw+aMnJ+t46IWh7lWcSGDq6eG+p57iw6++6q0M682Py5eH1HbsjQ5RoLK6nuK8eEXNSKA49dnef7sFuVKAHjscU6KhywYvbzVz4tsd3P6ViUfX97Cp0Y5TVKDcEDhln7/Bxp812i3OI5kZJZD1W45gF4rKY8J3tKvbgTHxoHjvjjnqm6zkSLgFiZXrBnwGm1i4N6NJZyckhVg6Ilc/rvcTKr6ubbDXXO56ZyzIZf2ednZUuwIOxYoHgutwBGlsbiMzPWXI9h8nTiS5/6mn+Oirrzh01izGjRrF4kMO4YaLLuKCE08kKTGRp8OovHlQCPGubjOGxDCqOcSRpM8irkApwJXTdTx+hAEBOCRXRYZe4MUtZja2qElVy8+x6T1AeQ6EC3O7BmQ+WZYnsixPZGFul2TOX+/tg8GzzXDyCUcr4E3OAG13iCgVgc2Cvo5nKIXiSKCmfmDGFF/nMi7GI0tTCKXtwxXfvggkyv0h9xrptUouOryAf723D6fT9ZwcKjHe2NJGxkFmEY8zcvn6xx+59oILeOCWW1h8yCEU5ORwwUknccPFFzNvxgw27doVctsjXoh3my3o49W1IobpumVAnwgHUCsFzpmo5XdfmUjWCrxyfBJ5BgX/223lkFw1k3NTKdC5RGwwhWwCiXH3x73ME+/BVM7AWtuzw6eVO5aLegQayOubLGRnDPwNuI/Bn/CQEg1xgqO20UJuVp8QD1jsKcbEeDCzOrH20tbSAukD00r7ZKjdzfymPJV5HU5fkEN7t53rnthCa5fLj3UoxLjNbkejjs/CxRkZOEWR4jxXEamSggI279zZ+90R8+fzwapVIbc94oV4ZXU9Rflxt5RwsdlsrLj8KF7tUPNpYRb7O/tnQLl8io7FhRoufL8Tk13k1+UJfHR6Mg8sTqTaYqRQ1ydkIyXGPT/u7+VYs7xFdTDuLKFaywZDmPjaR3WdhYIc6Wg1f8cSS1bb4UynyY4x0ZWxKZbPnVvoeX/kEosvbc3NkCZTiIeb+SVShGsd12mUPHntFMbmJXDO/ev5emsrDqc4qGJcDLecaZyDGpvdzj9efJGjL7+cIy+7jLv+9S+/lSu//OEHpp988oDPN+vXR6xPY4uL2bFvHwCzp0zh5x072LPf5Z7b0t5ORXV1yG2P+NfViup6pk0sHepuDEvc1u8dVgW/adRRqNIwYXQCu2rsPLi2hxlZKs6bpGVGlus2ykwQ0KkEchJd73fqAxU3W2w6UlWWkPvhGSjmHVAZTEoxqWwLK2uEfrnIPYklq7dcpII4q+stTCwNrtpeLIiokYBTFBEQEAThoDyn0cwgIgebDTQyJkQj/Vv3ZWyIRCEvCBxoq1YquP7EEsrHJPPwf/fS3Gnj0EmpLJp8G/MmpJKgdb0YRiuYs6PTRLJx6Av5xBme/O2ZZ/jgq6/49YUXkqDX8+Trr3PlH/7A8/feK7l+h8mETqPhsT/+sd/y0sLIVXVdNn8+zy1fzsWnnEJacjKHzZ7NFXfeybTx4/l6/Xqmjgv9GTLihXhDcytZEnlA4/jHLcKrbAI3N+q4IdXCkgQH+tkZAPTYRP6328Ifv+lGABLUAjanyJNHGfqlL3SIAgpBJNyaDt6pzjwHTjkCxy0IpLKwRKpfsYK3+Oky2TGOoPLqw4nWdjupyaqYvE9iAe8X40gKYqcTWc+dYPcZ0LXIz4yf+7tIVdYN1JeFk9JYOCmNmmYzX25u4c2v67jz5Z1MLzFy2OR0jknvIskQecHc0NJGZlpyxNuNM/Lp7unhjQ8/5I6rruLkZS4dUl5WxnG//CVfrV3LobNmDdimvbOTjNRUZkyMQMEAH5y0dClZaWkoFC5D4++vuYbbH3qI73/6iQmjR3PHVVeF3PaIHp0dDicKQYjpyl6xiFuEiyLc26LlXKONJQn9XVH0aoEzJ+g4fbyWXa0OOqwikzNU6FT9z3W9RU+2pjvoPkgNZu7BK1RR4y3GvZGbJzySokpctzliVjIpHA4RhYxAzTjRobbBQo6idqi7EZNI/QblpAWVm560vQOSA2jBwbKES603WGIcIC9dxzmL8jhnUR5dZjvfbm3j8Q8rUWSs5oyjjw67H940NreRnRGEc36cOAfYV12Nw+lkyvjxvcsyUlOZN306n3zzjaQQ7+jqIi0lJar9UqtULJo9u/dvQ0ICf7/99oi0PaKFeG1DMzlZ8dzJ/nCLbik+61bR6RQ43WijwiZgFgWme62jEATGpfm+jfabjRTqOoPqk6/BzHN5rygPcgrY01ocTNGeSIlvqf56L4vEAO0+zvomq2SgZjiM5CwbkaZm5z4mF4ZWUTbaDGaZ+WDwJ8aDqRHQ3AyluTnk6iNXVGYwXsKjfR0MOhVLpqbz6PsVjCkujso+GlvamDx+dFTajjOySTa68o02t7b2cy3R63TUNjZKbtPR1UVjSwunXHMN1fX1jC4s5Opzz5UU7aFywpVXcvcNNzDV4wUhUozoYM2K6npG5ccL+YTKlz1K6h0KflWv58r6BG5t1NFjC86Vo8pioEBnikr/wvHDdA/03qI7mmXsg7GWRYrqejP52drAK8aJCo0dCjKNwZccHwpXllCznQTaLpQ2Qy3K5UlLC2SnR+4lNBrXJBK/9VCE+7vf15OepGb6hAlh71+Kjq5ujPGUwXFCIDczk+K8PP750kvsq66mtrGRvz3zDF+tXUtDc7PkNqMLCykpKOD6Cy/kgVtuIVGv59f33MPW3bsj1q/EhASaWlsj1p4nI9oivr+2gdlTI//2crDwwMsr2HP1kdTZBUo1Th5SpfKHb0ycM1HH1EylLJefHoeKBKX/0vaehCtWg7Eme/qLS33Xu68wB+BQBttwp67dg3N1nYXD58WniIcKpwgqZWjbDlWgYzBVIUOtzCmHcMV4Sws4EyuB8NxPYsG/P5DLjvvcyulrj9XB4x9W8tDlExGi6LYZzbbjRB4hbwpCRojVr0JBsUZ6sULB3TfcwC3338/JV1+NRq3mzGOO4ZhFi9i4bZvkNmcecwxnHnNM79+zJk/muCuv5D8rVvCn66+PSHcvPuUU/v3aa8yYNInUpMjNssEIF+JWmw2NRj3U3RiWJP5jJQClj35CyfJLALjV7OTVbRbu+a6bqi4HCSpXlhSdEsamKrl2pp48Q5/qMDuUaBXyRXi4yBWu/rKweC4Ll3CtXZHwI+0w2UkyRu5nHivuC8OBHrMDnTr8YOChOueB9h0LAtUfdgeoQrz1Y+XYPJ9LcvznPX3GffmPb9zTQUG6jrKi6Igui8WKNj7uxgmDyWPHsuLxx6lpaCAtOZkEvZ4b772XTJm5SBP0eqaNH8++MFIKeiMIAukpKZx01VUsnTcPtdfDRRAE/u+KK0Jqe8QK8baOLlKS4umTQsEtwt0oTn0W5/JLSNEpuHK6niun6+myipgdIma7iMUBKyusXP5hJ/87Nbm3imO1JZF8H24p4rrNfJuQx78/rGTqKCPXnTgKtVLB97U2/ramBxD5++FGcg2BvadCEaveIkNuQZvBJhQx7j4uh8yKmnGiQ22jlZxRecCesNoZajEOA1/AQnVh8f7NRcIFRQqHA9y3vhwB68lQ/+bdhBrM6nmOpcT4tmoTEwujNzY2traTGa+oGSdMFAoFBTku12KHw8HPO3Zw2pFHyt7earNhSEiIWH9u+9vfev/9zsqVA76PC3EJKqrqKI77hwfEW3T7QnHqs/3+TgIMByzlAKUpej6vtPFTo4MZ2a7bar/ZQGlCh2R7PzXauXP1Dn5z6mje/b6em5/eSkl2Aq+v6iJdp6DAqCAzIbCIDMdiHGgKPtwBWSgvi6i/d7DUN1vJiqCPbJzgqG1wVdSUchsIVtgOdT7uiAUrD5IYb2uHUJIoxIoIh8idG28xvrPaxOxx0Ust2NjcRkY8dWGcMDBbLOi0fbFNH61eTXtnJ6cfdRQApp4e9FotCoWCru5uvlm/niMXLOhdv6m1lQ1bt3LeCSdErE/r3347Ym15M2KDNStq6imOV9SMKt7ifFqWiq0tfa4otZZEcjXSFvHlzXouPDyfo2Zm8uDlk5gyKonnP6umxw4T05X8ZVEiqkGy5koNvpEakIXysqimJ/RHdV3kAzVjSajEOm4h7sZftcpI+mPLJVbcjKJROKulGdKDTJgVifMb7O890LpS5yYUce55rVONalo6bUG3IZfG5jay0uO1O+KEzlV//CO//+c/WbVmDc+89RZ/eOQRLjz5ZDJSU2lua2PpxRfzm/vuA2DTzp387uGH+e1DD/H+l1/ywapVXHHHHSQmJHDBSScN8ZHIY8QK8bYOU9w1ZRDwFOMzs1R8sd/1gBdFcIgKVAppH9m99T1MK3EFPGjVCnJStYzPT+T905L562EGNAqBl7eYOXdFB0tebeOKjzupMwWffUIu7kE41MwRgRgKMV5dbyHfR2l7f8TFdmToMTtI1MuP1BwqMT7YglzqGCItxpuaIT2IGOWIn1cZgtxfilVPIn1uphQb2VQRXErZYGhu6yA9JbLBbHEOLq6/8EJqGhr47UMP8dHq1dx86aVcc955AGjUajLT0sjJzARg7rRpPHPPPSgEgcdeeYW/PvkkpUVFvHTffREvVmXq6eGFd97hdw8/zNV33UVVXR0A9c3NtHeG/psaka4pFqsNjXpEHlpM4vYhP7xYzcPruvm0wkp5noFkP2XtO1pNGPbsg5KpAHz8YyOXLCsgR2zg0worf/m+m+lZKi6YpKPO5OTJn3uwOcMLfAtEOIOxlJgZkKd5kF1VOrrsJBnkC8E4kcPhDK2QkpwCLdFwU5FbGCaaRNJNpa0NUmPAKOur3kEgkS43hiWovhy4xjNKk7j3zd1s2NvBjCikEXc4nKhCTRUUJw4wbcIEnvzTnyS/MyYm8r/HHuu3bPLYsfz517+Oap+q6uq44NZbUSmVlI0Zw7cbNtDV7SpW+I8XXiArPZ3rL7wwpLZHpEV8f20DhXlZQ92NgwrFqc+iVgg8uMTAX3/o5sGNanp62mk191mxnaJIp1WkosNBvclJvlGBuG4z4rrNJJtNVGysoLHbydM/m/nN7ARumpXAX743sa3Fzm/nJFAgI3AzVoika0soOJyuQM14CrGhoanFSkZqaJkjBtsyHq1ZoKHE4QRlDGlBt4U8GNeVSF8Td3tZyVr+fMF4bnpqK7sqKyO6D6fTSfyRE2ck8tennqJszBje//e/+duttyKKfYbBheXlrFq7NuS2h4+yCYKK6nqK8+L+4YON4tRnmZiu4o0Tk0hMSOaz3U2c9HYHx77Zxi8+6mTpa+0cc+DfF03WoVX2PbGPL9XweaWNU95pZ0KakkWFava2O1x5mBUCHVaRPe0DXVOGMhjSE7mD5mC4qIiV62hstpKZFp1AzZEm2qJBbYOV3CxtyCJXrhgP51qMRAEOYLcHJ8Jj+Ry4r5HnJxKMzU0gUadk1RrpXM6h0trRRWryIOaijhNnkPh5+3bOPOYY1Gr1AANXanIytQ0NIbc9Iv036hqaWTxn+lB346BEceqzJC+/hPwUA7dMVALJVHU5qep0MiZFSWaC9LvfIblq/nO8Gqco9hYKmpen4rljktjcbOeLShvv77Hy0nGx63s41JktPKmqs5CfE3ygZiyLkuFEbaOFWVOS4ECtqFDuDbnuItEowDOcUfYUU5TZRa4+PejUhcMBf9l3Aq0PsK2qi+uf2MKZh+ZyyamnRrRvrowpKRFtM06cWMBoMNDa3i753c6Kil6f9VAYcULcKYo4RRGlckQa+4cF4slPo3jsrwemKAUKjUoKjfJMVJ7VOgVBoDhZwZZm2Nxs58KygYGHQ5WRxBexIsard+1n8bKRJUCGE801DaQVV/SbcwxGMHuuLxd/7Q8XAS5VYCvYbdfv6SA7Q9NvmS+Gy3nxRSj9/+f/9nHZkYWcuTA34q5rjS1tFObG3ULjjDwOLS/n8VdfpWzMGEYXFvYur6ip4YW33+a4xYtDbnvECfGGptZ46qQhpqGplexpR0BD6IFXdSYnb++08PZOC0VJSh5cYmDKUdMCbhdIhESiWmUgAg2OwQRthtrfjh6BJENwP+9gBvVYeeGIRcTKdYiiHoUPW4Cccxeuy8lwJxhB7i2265utzCwLPHM2mOcpmBL03vh7VgT7bOj5fhMbdrXxl+kiQvHfAm8QJI3NbcycHDcAxBl5XHv++az5+WfOvvFGxpWU8P/snXd4HNW5h9+Z7UW9S5Yb7r2BDRgwYFoICQGSUEMJl5YA6SENkkBySSGVlnITSAFCwEBooQQMmBLAxmBMMc22rN52pe1l5v6xWnm1mu2zRdK8z6PH3tmZM2fKzvzOd74iCAI/uvVW3t+7l+b6ei4+/fSs2550QnxPezcztfzhRaWto4fWpnrE9ZFsKsnockv8810/gbBMS5mINxgp9rO9J8Txs4zcckwZc45elnKf8cLmrQ+6ueexN/nKeeuxxa2rhhjPNctEpmI8uk06hCUisxFt2yBP1lcNZeS9W3H5BGym/Gb4mSqkyqSiZPHuHwxSk2WgrNrEP5fSdjdS8dkQ29a27hDzqnRUnH57Wu1nisfrx2bJPGWqhkapYzGbuePnP+e2++/npe3bqauqwqDXc+7JJ3PBqadiNGT/zJl0QnxvezdLjz642N2Y0rR19nL8vFkp1/MEZc59ZIjjZhmpsYh86AhjNQgcOd3Ajw+zYTEISV8wiayKjz73Lj/94zPYLEZuveu/fHVjRIrHvpByEePR/eZi5YLM0xmmK8h7h0TqytLPua6J8NyJPYedDpGmynBa66tROn6qksjtRBrJGJSMfJ/nbGeLsg0+T3e7FzuCHLLxM1ntQ0NjqmMwGPifT3+a//n0p1Vtd9IJca/fj9WsbjVBjcxwe33YrOaU1vD73/ezol7PV9ZYM2o/0Uvu4c3vsOmJN+noHeL3PzwFq9nAqZf/ha8cfTA7HnuDp/YGEAWBBqvAmkYDs159E3HNkpz3nYtPbja5xVMJ8vZBHS3VyYXgaFua8MuZ+HPY6dAxo1Y7//kkkQgPBCQMhuTxQaV6zguRAerNvhBfXLQoL217vD4s2rtXY5Iz5HKxu70dx/AwM5qbaW1sREzkh5gmk0qIu9xe7FZLsbsxpfEHgpiM+pQiHOCJ3QEuXJb+9UpmZXpo89vc+PcX+O4lR7NyUTPW3h08/Wo/sxut3PKnrfzrfT+fmGPCIMJb/WH+uMMHwIntH/GlT6a23qfav9K6+RTjMPbFHSvK2wdEDl8QiKyTxB+5VAXJRELpHHY5RNYeEChCbzR6+gM01CRO21mIez7ZcyLR/lP9/r2b28Z8tmxoTbpeou97vTKNtbVJ95UtvQNO6qor8tK2hkaxkSSJG/78Z+597DECoRCyLCMIAo21tXzjwgvZcNBBWbc9qYT4nvZupmv+4UVlX1cvzd1PQIp42fcGw7S7JA5qzP0W3Nfl5Od/epY/Xncac6bXIO/dij8o8Yv7PuKbK/R4gjpay3VcstzMk3uCvNUfxhuSWdVgYIXsyHn/pUCsq43TI1Jhza+PshaomVhUBUICptJwUU4o8Eot21C6pMqC0tUXGM2YEkshB52JBr9qifBEy1J9bz5iGv1eidrq6qTbZktvv4Pamsq8tK2hUWxuvesu7njoIU484ggOW7OGMpuNfV1d3P/kk3z1+uu5+ZprWLs8dUIJJSaZEO/ioOULi92NKU1bRw+zj/8SYsyAKN46Lssyf3zDy5kLzRh06afPUvKrDYclrrnxCc4/ZQ0HsBt5724A/vp0O3OtYQ5tsRAMy/zgBTfnPTpMIAxnLTLxg0OtlBkj00mZBkOmSyGs4vFII4GaqbKS5SpMpnrWlETnLxSGiZA5tRDZgxKR6X0TDdhMJx94T5+ftSuKb5Utxdmmnqf3YRDtWEz5cR/pHXBwYOuCvLStoVFsHtuyhTM//nG+/vnPj1n+6eOP54vXXsvNd96ZtRCfAK+M9OkbHKKmqnQLvkwFOrr7aGqoGbNMPOXPYz6/1BniuX1BTpmbXeXH2Cpzv/jtvYgBF2et2G8BDoVl/vHUXr6wMuL2ohfBE4IdfWGuWmvl4weYRkX4mHbz4KNZSLEqb91J77BIXXn6gZoamZGqumG3U6S+PD3/8EKQKptGvv2Shemrx/1lQ7pFeQacIaoqx05HlKIojqVQA6L+sEC1nL9nw4BjWKuqqTFpGXK5OHjFinHLBUHgtOOO44O9e7Nue9JYxEOhMHqdqHqBAo3MCIUlDPrxt5V4yv5Uhmsa9Kxs0HPVs25aykRCEgQlMIpwxSoLleb9IjmZ5e6OZzp44Z1BbvvS8tEsCfLWnfy3PUiDVWR2ZaSIkNMvU2YU+MZBFn70kpu/nViOMYElPh/W8VjxkW9R0D6go6VqrBCMt16XujDJJ/k+9k6HjqYqbSBUrNkSGXlMUbCJcq+rNSOWjP6wSI0uf/emJEvocgxa09AoVVYtWsT7e/eyfvX4Z5vb42FmS0vWbU+aX017dx8tjfkJQtFID+ewm4qyxBlQopZxg07g50fYOWqGkXlVepbV6VnXpCcsw/eedyPJY/2blV5QT+/o589P7uO3Fy+m3Kofs95/9gQ4avp+a/vzHUHmVun42Cwj08p0/P4NX87HGk+6lQCTCRQ1xH/7oKiYMSWVJXeyU6jjTyd14WRCyeJdLBHu84cxxcx05ex+NTJjEP83UekPC9Tq8hM7Eg5rIlxjcnPpGWfw9wcfZMDhGPfdHQ8/zIU5pDScNBbxPfu6mNHSWOxuTGnaOnqYlmZ5Y4tB4LR5Y30Vj5tl5OLHhvnrTj/nLhlbFCLWUv3czgF+eOd73HjxYlpqzGO+BzioycD/7fBx9mITvhD8ZquXn26wIwgC315n5fQHhziy1cDi2swrTyYTGVExnmoaPddiQMlwuEUqkwRqqrnfieAnXujBh9OT/PwXg+gAL1cRWerXursvQENN5JmSU2XSFOcp3fOY6cA6E6t4bFaUVIGbUfrCAjV5EuL9Ds0tVGNy87+//z3DLhfHXXghOp1u/xeyjD8Y5Kqf/3xMcJYgCLx4111ptT1phHh7dx8HT9BMAJOFts4e1iydn/X2BlHgB+ttnPvIMJ+YY6Qq1kVFlulyyzz851e5+10/vzzCzqK+vch949s5dqaBf33g5+yHh+n1SBw708jyusitXmsROXmuidt3+vjpEfas+5ovcpmillcuRnghdaDmZKdYlv/oRE6pnv/ovZWuQCx14R1Pd1+Axros407yYOlWy80tUSrCTMmnRby330FddWVe2tbQKAWmNTYyrTE/xt5JIcRlWSYYCiv6JmsUjr5BJzU55pFtLdNx3EwjVz/v5sTZJno8Em/0htjRGyIkw6p6PbefUE6TPfE0qCAI/O9hNnb2h6kwCvxnb5BTHnDyjQOtVFsENu3y85ujsxPh6ViB083woDZ9w5lV1JyMFNP9xukRqLCW9vmfqGkL06G7L8C8Wda074FCuZnkO0ONZUNrWlbx/rDAfGN+7s/eAQcHTG/OS9saGqXADy6/PG9tTwrlOuAYpqZSmxYrJpIkISCMCZRSIj6DilLhn8tWWvjHOz6e3BOgziJy9HQjX1ptocWefjBuuUlkSS18fNMQH5tl5PwlZr79nBtRgCtXW1iSoVtKLPl2ycjWKr5vWyctc7IPGJnoFNsHvtOho6mytIV4ukw0aziAYzhI+eAbUKIzEsWmPyxSqwvlpe3efgfrVuanYqeGxmRnUgjx3e1dzNAK+RSVnn4H9VkUc4jNphKlzChkVHEzEZ0uiQarwDfXRgJIV9TraR+WWNuU39teDWt4NmK8w2/jkPZ3kHv8BbF8lpJYK7YIh0ig5vym5EInXznr1aSUrmtGyJm5BRUiU0km5NKXdKziwxLYxfy4pvgCAcym7NyCNDQmCr0DA7z65pv0DgyMSyohCALnnnxyVu1OCiG+Z18Xx6xfU+xuTGnaOnpobU4vUDMeJTGuBr1emVrLfheW1jIdrWW6JFukTyECFTMVCoNBE5V6P5D/6fAJK9bySI9Tx2ELEpe2LyXRp8REvqZubxhreLDY3UhIIQoopRLjRgGCedDhslxawckaGvngyRde4Du/+hXBkfL28Ux5Ie7yeCmzJ06bp5F/2jp7OPawA7PePh9ivM8rjRHi+SRfPuHpinFJHl9RcyJYX9WgFKzhACEJDOqM8wrORBbhMJIxpSJzt6BSsYqr1YdkYtwsyPhk9f12XB4vZTbt/asxubnx739n9rRpXPG5zzGtoQG9ijGJEz7xp9fn16bESgCXx4fdlps7Sbz/eDJkWebNvhCvdAVx+JRfwBEhPrEdRtN9QfcFzdQalPOjl4LQyCelICIDjSsxlleXRF+mIt19fhoqssvfPtkGqpYNraN/sVTrZPrD6j8PtYwpGlMBp8vFZWeeycErVtDa1ERTXd24v2yZ8EJ8b0cP05s1//BiEggEMRrUGR2mI8Y/coY546Fhrt7i5tbtPj55/xB3vj1ehPZ7ZWqt+2/xDx1h3h8ME5Qm31Rqh89Os8mV8PuJXowkFcUUwML01XT1+kdT5yXqy2QTfLmSbhEsSD3rka1FPIqwevHo32QiVozX6WR6QnkQ4gMO6nLMlqWhUeocvGIFH7Sll7M/Uya8EN/T3q0FahaZfd19tDSoV9U0mRjvdElc9sQwn55v4t5PlvN/x5dx58fLuPV1H+3DYy1isa4pvR6JC/49zJefdvGNzW7V+ppPMhHO7X4bLebUx6WJ8fzss7PHT1O9KcXaI9uUmNgrxnnLRoQnq4467A5RNm+lKn2bbKI8ah2fYZD4MKj+K7+330ltFoH6GhoTiSvOPpv7nniC9/fsUb3tCe8j3t03wMZDVxW7G1Oato4e1QdDiXzGn9ob4OBmA6fGVOVstus4eY6R+98P8IWVEfcYX0hm10CYsxZGXjy3bvfyqblGzlxo5oyHhlTpo1LAZiKhEL9esuqa2YjlwaCJqpFAzVSoETiWbrBq9BgLIfYK7Ssee0ydvQEWzyu9AlGTkfh7T5ZlkIG2barvS62qpMnIpW2l33Gi9g46rJ4/PuSg/4sbqbnxyaz3GY9jyEVluXbva0xuqisrmd3ayulf/Sp63fhgoEwqacYzoYV4WIpMRYrihDfsT2g6uvs4ZFVhrEc2g0BAYQb6uFlGrnrWzWUrzMjA1c+7WVSjY2mdjo+cYTbvC3L/yeW80RsmKEFYktGJuU/TxoqCZEIwHeGayQvZu7ltdNpZkiOpkzNJ3VZIMZ5s+yhqtVMsXO4QZbbkj9Po9S1EBo2JQtQynizYWWnQGvt52Ctgl9ObjSgW+bjeidpMNHiYUS6yyhTmxwMmrr58IxW/VUeMy8gp60doaEx0rr35Zja//DLL5s9XPVgz65Ze3L4di9nMkrlzFUcHhaCrZ4Cm+pqi7FtjP8FQGINKPuKpmFYm8uAH45X4wmodIvBWf5hHn+unN6DjV/Ve/M8Mcp/DyMcM8HpPmGtecPPbo+2qiPAo2QrBZFbxTOgPmqkxKgdqJkMtMQ7KQjr22MZZMRWEVTZivBREuCTLE7KITDH96pss88a4p6QS5Ml+K91OMetAzXQoVWt4KuIzwgiCwDUn1/HVTX18r8/MDy7fSFWOYjwYDGkVrTWmBC9t387lZ5/NBaeeqnrbWf2CvD4fP/7d73B7PPgDAaorK7nglFM4eeNG3F4vdmthUhnt0Qr5FJ0hl4eyHLOlZLS/gEyFabzqEQSBjTON/GXzADv8ev7U6MEogCzDU249F1cG+NZzLm7eWMbSutS3fT6slqnEaLa0++y0JAnUTNonlY4zk2NJ6JKTgRgvtgCP7efAYJCayomTualUMrvEi3FIz0IeT7dTR1NV/oR4rhRz9iNejFv0Ar8+tZarNvXxwz4zv8yx/b5BJ7VVWqCmxuSntqqKmS35qVydlRDfsWsXM1ta+O13v0s4HGbHe+/h9fn47xtv8Md//pM9HR2sX72aK885h8rySOn5R599FlEUOWz1aqwWdYRbW2cPq5fkJ3+zRnq0dWZfyCcbguGI/3c87cNhHv0wwKpGK8u7PFSMTNK8FRDRCXDMcY384V9DDAXSz5iSLzGuNh1+G+squ1RvN18ksm7mY5BSCDp7/TTXl74QLxUBHouSGIeIII8X44num26nyIqZQdX7VojA5nzkMY8/T/H7MOgEfvSpWo6+cxCP15vT+7h3wEmdFqipMQX41DHHcO/jj3PUunWqt52VEH/htdcYdrvp6u2lsa6OFQsW4PZ6eebll/nq+edjMBj46R/+wH1PPsn5p5zClq1beWXHDswmE7vb27n4s59VpfP+QBCTlkO8qLR19LBy8dyC7e/wVgO/3uZlW3eQVQ0GICLCL3rcxbmLTayfZuCsh0L41tViEAV++u9hzlltwqwXuHK1hf97w8uhLYa09zcRiuJkEqipoT6dPQGWLyzdYLVSFODZoiTGPQEBmym9AXahswal89wohhg36wXm1xnY/s47HLIy+2wzvf0OFs6dkVNfNTQmAnNnzuSuhx/mqhtuYMHs2eO+L3hlTZPRSF1VFV/+3/9FBq694grmzpzJx444AlmWEQSBpvp6tr/9NgAftrWxYe1aWhoa+NsDDwBw3xNP8M5HH/GNz38eXRY+5s4hF+V2Wzbd11CR3gFHQS0iFr3AlassfPMZN+UmgX6vjDck85U1Fj6zwAzAsTONXP4fF2EJVtTrOHVeZLC2fpqB77/gZtAnUWXOLMA30YuymALdu7kN0xGtEFdRMxMK1f9UWWMmqjUcoHcgQG11+gaBQt4zE0GEZ2IVB8YER2dSXX2ype5MNWOnJMaj2wGsbtCzdefOnIR436CD2qplWW+voTFRuODb3wbgo/Z2HtuyZdz3BRfipx53HPXV1QB86cc/5p+PPcbXLriAcDiMKIrs6ejgtbff5nOf/CQAleXl3HzHHbQ2NnLMoYcC8OZ777HpiSf41MaNo6OLR555Bo/Px2nHHZeyD3vau5k5rTGb7muohDTyFsxXxHyifOLHyzKt77+P2WikpqqKCrt9TOacr3zMxwuvvYYsy2xYuxbhgQsBMOkEjmw1cu8uPxcuU8c9Kt2XeyrxlW478eWrO7YMUm7rxftuZHl8Nb1UFCqDRyr/74kmvmOR0szAUyrl1NMlkRAuFYTpq3G8vY0Ka/aFfPJJJr+rfN0bSjMI0X2tbtDzy//cx8Wf/SxGQ/qzhLEEgiHVirlpaJQyj/z+93lrO6tfUH11NZIkIYoi61ev5s+bNvHtiy/m5bff5uJrrqHCbueqiy7i+MMOA+C49euxW63odToOXrGCUDiMx+ejzGajo6dnVIjf8dBDzJ81K60+7GnvZv2BS7PpvoZKFKu0sSAILJmb2B3GYjZz9MEH718Qk5P8vCVmLnxsmJUNelY3pH75DHglXukK0euVaLKJNNlEGm0iVWYBIYMBSCIXl2wFeJROYxVNwYFx62UqyAtBvBhXK2tMMfF4w1jM6c/oadbw8SQr7pNqMNBjmk9DxQdp7aeUB0LZ9ktpIJ1O0LOwejFrpDeZXiZyxRVn8Mtf/R2LKbMUkFIm0xEaGhOcXErYpyIjIe4cHubhZ57hiAMPpKWhgXA4jGNoaLSDBy1bxtO3387v7r6bfodjVKybjMYxDu6dvb18tG8fl51xBk+++CKHrlqFyWhkX1cXl5x+elp9GdSKCBSdQgdq5kK0QNDsSh3Xrrdx1TNujp9l5KAmA0tqdWNcVQZ9Ene/6+fpvUE6XBKrG/Q02kS2dYfodEl0uSV8YZnGEVEe/WuK+2zUjRfqaguBLkMVq9zjhUhsnvFUTJW81vlwL+rsTb+iZiGZDCI8Hbr7AkxPUto+fgCslhiPvWdyba9YgwPDgUv4X97khy94uPTys/jFT/9IdWVl2tsPDbupLNPewRpTB1mW+c+LL7Jr924Gh4a48NOfpqGmBq/PhyAImDMczEbJSIhXlJXhcrv54z33cOIRR/Dyjh28uWsXLQ0NdPf3U1tZSWV5Ocvnz+cfjzzCCYcdNvrDliQJQYhYEd/58ENsFgtHrlvHH/75T0xGI/0OB8Nud1oW8eh0WCYWSQ312dfZy9GHTJyqplExfmiLgb+eWM4/3/Vzx9s+dvaFKTcJ1FsEXEGZbo/MxhkGvrXWyuJaHXoFtwNPUKbLLdHpjgjzLrfEy12h0f/3eCQqTYKiQI9+rjClZ1VPZA0HGNTbqQorl7YvRTFeDAt4KqGTy7F39vhpLkEhrgb5dkvJVYQDdPf5OejopdC9Pel6sYI8VxEdf6/kIu7VEOGJrOLpYDhwCT9YLXPzn7bymUvP5zvrrBzRuj/eIZF7IIzMiGoZUzSmCINDQ3z+29+mo6eHGS0tvLdnD6ceeywNNTVce8stHNDayudPOy2rtjN2TTlxwwYeeOopfvrHP9LS0MAXzjqL3fv28fcHH+SkDRuYOW0ajz77LFUVFbi9XqorK5FleYwP7xvvvsucGTNoqKlh0Zw5PPfqq0iSRF11NXUjvufJ2NfZw7TG/E0TaKTHkMtDmb0wOePVIvpiaQauHFkmSRJ7OzsZcDgot9upr6mh3J7c0mMH5oz8KRG85zz6vPKoMO90S+weknipMyLWO10SYVlWFOhNNpEmu0idVcQgCrgk2OnXscOvoy0koAPq9DJHWUOgYi2ZMcU/JomFPN/Wxs7eAKuXlI/dZwnlOC9V0hXhqQYDPr+E2aQjXScJJQu50veJSFbNMpN7Te37MpfBpCgKfPHCNRz8yHauft7Dy10hvrrGkjL2p3fAQUNt6ve1hsZk4Cd/+AM2q5VH/vAHKux21sSI7nXLl/P3Bx8snBBvaWjgsjPO4LIzzhhdNmf6dPZ0dHD5ddcRliQWzJ7N+SefTGtTE8A4q99bH3zASRs2AJEMLLvb2+kdHGT5ggVp9WFPezdzZuYnsbpGekQqqhWnoqraiKLIzJYWVZP1G067jYZN59NgE1meYJ3hgEx3nFX9xY4Qna4wXW6JPp9MORJe2cYCo8RSU5hDLGEkGXaHRL4/VE2DxYfHaWCjLUSLfrwcycQqHstESNuYikJM+fv8mfmIa6gnwqWRDF2QebxBokFnLtbt2G0T/W5K1UcdYPXHVnBn1Ztc+Z9hfvSSh++ss5Ist1TvgIMl88encdPQmIy8+uabfPvii6muqECSxrrDNdTUsK8r+1oeqoQ7m4xGLjvzTC4780wGnE5EQRgt5BPPkMtFd18fa5YsAeBjhx/OKzt28Oyrr44R98no6O7n8IMSyRuNQtDe3UdLQ22xu1HSiDFBokqUGQXKjDrmVCkLuZAk0/5UO9U6Gb2Cceows4W2UB9vhQUu6rLQopc5xhZiozVElW6/KM9WjMN44TCRhbnahMMyujgjw1SxhseL6WSiOZHwjt0mk/aiDDpDVFUkf4VlI6xzFeNKFEKAq+FeVmYU+O3GMi5+fJhHPgzwiSTrFrqqsoZGMdHrdARDIcXv2rq6qKmqyrrtzJIpp0F1RUVCEQ6wr6sLj89H40iA52Fr1vCfl17C5/ezaE6iif79vPXebnx+P2Ia6cI08kdbR3aBmtKm85OK08lGMh/LVOhFgXq9sgi3bGily1jFQfIAX60O8ECLhwsqArzq0/HVXvO49ZP5mWeCvHXn6F8pk+/+yXu3jssfXmwRXigS5fxOtDxT0vVN7+7101C73z8/0SAkG3GqpqAu5G9Fjd+mzSBw9iIzj+8OpFxXi9PSmCoctGwZfxhJRBLL4NAQf3ngAQ4cMS5nQ8ETgC6aM4e7f/nL0c+yLHPwihU89txzNNTUpNze7w/g9Qf42/1PoNfpaGmsY0ZLAy0NtegniavERKC9u4+1KxZmvb206fycROpEIpfjtJ2y///uKzYC+1MTDjXWEXprB3d6DPSHBfrCAu8FRA62hBXbysUyrkQp+5SrmdUiER1vv0uTTkbeuzsv7WdDOqnrciVRAR7ITHjnnDGlP8CcGenFqOQixuPvn4ngtpXrPX9go56f/NeT8Hu/P4DJmF3ucQ2NiciXzzuPz3zpS3zysstYt3w5giDw+7vvZse774IgcPnZZ2fddlEy8cdazI0GA9+99FLO+cQnsFpST3MZDAY2HrqaBQdMJxgM0d7dx+59nTz/6g5CYYnaqnJmtDQyvaWeMtvECiScSASCIYw5PoilTecjfOpPPPLss4iCwPxZs5g1bZpmZUmA7TdPjs4myDIMB2Uu6LdzhCFAi15ijlHi3IoAMxV8xaOoLcajlLILSyJBFf99pnQ6RNYekNpqWGgKIcbzRSaZWnr6Ahy6qjJ/nRkhkatKuoK8lPOXJ6LaLCARsfZVKcxw9w46i1JDQkOjWFSVl3PPr3/Nr/7yF17avh1Zlnnr/fc5eOVKvnTuuUk9QVJREiWxDHo9c2bMSGvdzu4+jlm/NrKdQc/MaY2jFTZlWaZ/cIg97d088dyruDw+zCYj05vrmdHSQENt1ZjsLRrZ4XJ7sVvHuz9kw8++fTovdwaZWaHj170hDmwy8P1DrKNifKpYzdMl6nc+EDTh83vRi2CZZqe5VsdxM40Ent2Xso18ifFYStFanm0xpUQMukSq7KVZ1CTqJjORBHmm6RIDIQmjcezzPF9FopKJabUHeEpuZNn8XmPbyXR7QRCoNAk4h4eVhXiRirlpaBSTirIyrvnCFwAIhcPodep4YZSEEM8EbyCIzaIsAgVBoLa6gtrqClYvjTzUvT4/ezt6ePPdj3jy+cgDurGuOmI1b67HbDIqtqWRmL2dPbQ2ZVfIJzaAMSzJPLcvyKnzTHxusRlvUOaix4e59XUfl66IzI5MJReWVPQMDPDmrl0Mf+CnPVRGODDENLvIc/uC3PWOn0NbDFSMvHBT+YQXQoyXOrkOEGSg1ENVJpJ1PFUVzVjCkpwyvV6xyXagZ9nQmvT3G/9dqvWVtondNhGuoEyZzab4XW+/g+WLUsd0aWhMFr7/29/y+dNOG80GGCvCt+3cyUObN3P1iEjPlAknxC2mzNwhLGYT82e3Mn925IEjSRJdfYPsbe9m+1vv4/MHsFvNTG9pYEZLA7VVFZprRAr2dfSwbOEBWW8fFeM6UeCmjXY+/+9hmmwix8w08uuj7Jz36DDvDISZXiYiCGB//XSOufBnHNA6NYWjx+vlW7/4Ba+9/TbLK/2UGwV05XYqwp2sbTbQ64mkUqowRayD6QZmFkKMl4o1XG2GvQJ2c2law+OJtRCXuihPV4wPDAapqRr/LshnwGwhXUzif5eZCPNMSLTtkAQevy2hEO93DFFTmf1UvIbGROOBp57iU8ccMyrEY/EFAjz93/9OHSHelGPKPFEUaa6vobm+hnUrFwEw7Pawt72HV994l94BJzpRpLmhhuktDbQ21uXsCz3Z6Ol3UJ9jRbWoGJ9WpuO3R9u59EkXJj0cPs3IX08s46WOED0jArPXK3HJN65gzvzlfPfSS2lpaFDhKCYOBoMBnU5Hk8HL6gYjK+r1vB4o46zmTkQht/Rh0RdxPgT5ZBXhEPEPb6pUDootZSaCy0o0iDOZIO/uD9BQU/jZzInm7717u3JhspkrXEm3u2/YwFHWEEaD8rsvFA5ryRE0Jj1dvb1jPvc7HOOW9Q4O8vcHH8y6vD1MQCHeUq9+7uoym5XF82ayeN5MIPKQ6ezuZ09HN6+8/g7BUIgym5UZLQ1Mb2mguqJsylrNJVlGRlbF1z4qxudV6/nFkXa++YyLNw4Ic8lyM8fNGvuSvWKVhb+/9S5nXXEJX1pt4RNzTKNtTHYMej03fPObPPmrs3m1K8SjH3qwNwR55s1hVtTrWVmvZ1mdjjJj9tckF39SJSazCAfodOiYVaeuEE8ljtW09k4klxUlunr9LJqbvPptvih1MZ5IfCdbJ1aYd4UE/jls4Df1PsVtJUkqebcgDQ01OOGii/YXDRMEvvbTnyquJ8syXzr33Kz3M+GEeFVF/h++ep2O1ub6MXmyncNu9rZ38+K2nQw6h0es5rVMb2lgWmMdRsOEO5VZ0T/gpLaqQrX2okJ6JXDXZx18+1sXctHjLn58mI1G235hqRcFzl1i5tAWAxc+NswxM41Y9MKU8SEXBIGjZxg5eoaRgaCJZ/slGqaZ2d4T4vadPt7qC9Fs17G0Tkew38Rrfh3tIZFDzCF+luCFmre+TnIRDtDlEDl4bullTMmEUhXj6bim9A4EqKsu3kxlqYrxdER4su3cAvywDM6p9bP01scV1x0cclFVUZZ1HzU0Jgq3X389Qy4XTpeL7/7qV3z2hBPGzchbzGaWzJ3LgtnZV5mdeOqxSCPxijIbSxfMZumCyMkOhcJ0dPexp6Ob/772FsFQiIoye8Rq3lxP1SS1mu/tzK6QTzpUV1Zy80138+drz+Kch4e4+hAbh00b+7Lt9UrIRMrDW0Yq3UwVMR6dQWj32ZhpdbOi3MDBzZHzE5Rkdg2EeaEjyD+8OgYkkTWmEBdUFE4sTgUBHiUYFjAW+OmZj4wgpSbG0w3WDIVlDPrxM0D5ypqiRKmK8US8vGVYcflB6yOiWgJ+a4dFITj/z48kbEfLmKKRb4KhELfceSePPPMMkiyzftUqvv75z2MxJ87W9uwrr/CHf/6TvZ2drFm8mO9ceinVFbkZDZfNnz/6//uffJJPn3BCXmLVJp4QLxH0eh3TR1xVojiGXOzt6OGFrTsZHJqcVvO2jh6OPHhl3toXRZHPX3MnK289h28/5+bVLgNfXGnBoIuI7p/818OPD7NRbx37Ei62GI+vFpqvvoin/JmO31/DqvKeMcsNooA7KPPPd/0cYglzdrmXVkNhggmnkgAHCIZBQQNOWEpFjGciwvUlkq6mlMR4Mmt4IhEe+53/qDI8Avzvw/cmNSL19jvyZozR0AC44U9/4tHnnuNLn/scVouFP9x9N5d8//vcfv31iutvf+cdvvqTn/DZj32M8085hT/dey+XXHMNd95wAzqVUgz+4dprVWlHiYmvDEuIynI7leV2lilYzV/e/jbBUIhyu5XpzQ1Mb26gunLiWc2HXB4qypQj6dVk1SV/5Y7yc/n+Cx4+/9gw/3uYjZYyHVaDwMudQdY16dHFvYyLLcZjyWdf+oJmagxj3U027fJz6+tevlvm4UBzYYIIp5oAj9LjFGmomHiBmqVMJjnE+wYC1FSND9QslCU8nkKI8XRSFOaCDGwKhfn21d9LKVx6BxysWppZzncNjXTxeL3889//5nuXXcbJGyPVpFcvXsyJF1/Mc6++ymFr1ozb5m//+hfrVqzgaxdcAMDSefM4/sILeXH7dtavLr6RIRWTyK5TekSt5ocduIzTTzqKcz51LBvWrUSv0/HSa2/x1/ue4O/3P8nTL77G+3va8ftL2+c0GAphKGCkfPWZt/PLI20cO9PI5x4d5j97Aty80c7b/WFO2uTkjd7QuG3iLdOFYrczzJ93+PjmMy7+tMOLLMvIe36ec7vd/f0Mu92jn8P3ng/y2PzV27qD3PSyi5sqXQUR4cLqxVNWhEMkULOxUlK93VRCMp9Cs1giFjIv5NPdF6CxbqwQL2b/oTCDUsuG1qSB1KkyoSTj7daITe7QVatSruv2+hLW8tDQyJXd7e2EJYmlMW4htVVVHLxiBU+88MK49YOhEM+8/DIbDz54dFlddTXLFyzgSYX1SxHNIl5gxvmah8N09vSzt72HrTvexR8IRfKaN0d8zWtrKksmQr2ju5/mhpqC7lN36m2cvel8VtTr+dazbta3GPjaQRaue9HD8+1BltWNv4ULbRn/sK2N/3lsmGNnGjlsmoF/vOOnzVjBd1fK6Pf8HGHG1xJu+89//5u3P/gAURQRBAFBEBAFgcrycs466SR+eNNNfNjWxo+//GWWv/Mz9rgNtDncXP2hm7MWmZhWpuOqJ4f4bo2faSq4oqTKmDKVBXiUjkGRwxeU9qB5opCpCIeIEF++MOKGUWwBHkuh3FQytY4nc0sB8BgFnltk4pQXvRj0qSWBQGm8jzQmJxVlkZiF/sHBMf7YFrOZzrjUgQADDgfBUIgZLS1jls9obqZDYf1SRBPiRUav09HaVD+mUuWw28Pejh62vrmLvkEnAgINdVVMb26gtakOa5GsEW2dPUzLsqJmLoin/Jklm87njo+X8b8vefjGZjc1FpETZxe/Kmpnby+XffMKrlxt4eMHRFIqHjXdyDde83P9PR/wva9/FuSnQThy3LbSpvO59W4Hn1lgosokIskyEoAMb78b5tP/+ge+MFSZBb76w++wukHP3kAN82qGeLMvxPPtImcs0OGXBWYbcrfQFkOEFzK4Ti2GvCIV1vz43yfK8z3RzlE6ZCPCAfoGA9QquKZMJRKJ8ZkrXAl9xQdtAu81G+grFxGAOR0h5nSGeHGBkQX7QtQNpX6GeLw+LObs8yVrlC7dvg+RvLnVpcgEWVaevW2qq2NGczO//dvfuPbKKzEZjdzx4IM89+qr1FRWjlu/z+EAoMI+9r6vKCvjjV271O52XtCEeAlSZrOyeO5MFs+dCUBYkujuG6Sto5sd73yIx+fHYjJGUiw21dNYV41Ol38vo/auXg5ctiDv+1FCPOXPlG06nx8fXpzcwUoEQyGu/MYlnL7QPCrCAWzrlvCTFSFO/+lrbH75QzYcNHucGI+6rRw1w8g/3/Vz8XILp8w1jQlCe/ADPz972YMsCyys0bGsTs98Sy0b6vo4fafEp+ebsRgE1rYa2e7yc6x+vKtOuhRShJdCYGC2yCP6O9+TVNEAykIK8EIGbWYrwiFS3l6nE0pycFLo6pvpWMYPXF/GDYMB3p6mZ+G+ELO7QoR0AlsWmegvF/mgSc/nnnJzvvSflG31Djipq1Yvfa2GRjyiKPKjL3+Zb/zsZ5z8hS9gNBj4zAkncMLhh/P6O++MWz/6KJblscYRWZZV9yZ4+4MPeOG11+gdGECK258gCHzroouyalcT4hMAXUw10LUrIss8Pj/7Ont5+4M9bH7pNcKSTG1VOa3N9UxvqqeiXH3B6g+EMBWxymg0fV+pcNuPzqbOKnDOovEWIrtZz3VfOYmv//wR6lrdLG5aul+My08DkZf2t9jJyXOM/PJVL3e94+PrB1o5qClyjk86wMR7g2He7AtjEAWebguyfrGVmTY/S+v0PLcvwMdmm5hRrqO7shIG+7I6jnyXuY8ykQV4FIdHoNKqvn+4EqUoNHMlFwEOEAxKGApgdMiFYovxeKu4DAxZBGx+mUV7g9QOR+5fj0ngv/ONnPiKl0v9qUU4RAI163KsqqyhkYolc+fy0K230tHTQ3VFBVaLha9cfz111dXj1q2pqgLA6RobI+EcHqZ25Ds1uOuRR/jpH/84TvBH0YT4FMRqNjFv1jTmzZoGREZ//YND7O3oZvN/t+Mc9mDQ62huqKW1uZ5pDbUYcxDRbo8Pq6X4U5KlIsY/uu1z/P0tP387cWzmm1jL8cpFLXzyqMX86vc7+MHXjSPr7aLJMm/U2imsXszCrTv53bF2nt0X5Kpn3dx2QhnTy3UIqxdz5QqZy3+3k4AAXYND7HNJiAJ8caWFbz7r4sBGA2VGgT6vlFVmhUKI8GQCfKKJzc5BHU1pBmrGijHNt14degYC1NUYSv6+KaW0hiJw4qs+3mrVs+kQC2veD7DygyBL9wSZ1h/mO33KhXuU6O13MHN5cWZFNaYWoigyrbERgHA4zI5duzj12GPHrVdTWYnJaGT3vn2sXLhwdPlH7e2q5vz+6wMPsHbZMq666CKmNTSolhYRNCE+aRAEgdrqCmqrK1i1JGJ1CgZDdHT3sbezh5e3v00gGKLMZon4pDfXU5dBIGhbZw/Ti+AfroRSIGa8OM9nwKb7H+fxvS1uLlxmptmu/GOMis9PfrKaZ695l4ef3MvHj5mhvO7qxbB1J0e0GjlvicQvXvXy66+vBUCvE7jh8wt55NUeNosmmpvMCKsXs3LrTs5caOa8R4dZ06hHl+EMnGYFz45Oh8jClvEuQKUiunIln+4puVrDAbre2UVDgfLjx5KNm1B08FWM1IbxVvG168sQtgwzrT/M4yvNfNig59jXfBmJcIBB57BWVVMj7/j8fsym/Ya/x7ZswTk8zGnHHQeA2+vFYjIhiiJ6nY4j167liRde4FPHHANAd18fb+7axSWnn65anwLBIGeddBIzmptVazOKJsQnMQaDnhnTGpkxrXF02bDLw97OHl7b+R69Aw4A6muqRl1a7DblYI22jh6WzJ9ViG5nhZKlPB9i3H/PeXzjWRezKnScsWD/gyLW4hkVMp3eXRj0Il+/bDlf++FLCILAx46OCOD2bif3PbyHp97oZ2A4gC8g8ZWTZ1G9QEQX6B+zT6tJx2mHNrFgup5ASACCCKsXcx47mVEucst2L4trIz/l6Eu5UEI7F0rdqqlEz5COIxZGMqZMFvGdDU2WeXR60w+EylWER++VniETa2YHc2orl/1nQ6EEeSoOWl/Gy1uGOfV5L70by7jnaDuH7dzJqsXpz9aEJQmdWNquQRoTn8t+8ANam5o4et063t+7l1vvuovPnXwytVVV9DscnHjxxRy6ciU3XHUVAGeddBKf/853+Mkf/8iBS5bwx3vuYf6sWaxdtky1Ph1x4IG8/s47eclLrgnxKUaZfWwgqCRJ9PY72NvZw+PPvYLb68Og19My4tLS0lCLwaCnu2+Qow5NnWO2mORbjLv/cR7ff8GNgMB3D7ZG0g3GuRwoWRNbW+z8/Op1/Ozm13n4yb34vM/j9QX52BEL+OGZ1TTVmBn2hLj8dzvxBsJcftJMxf23D+pYMWO/CBFWL+ZIdrKh1UCsjTAfIlzeujNj94rJZA2PiqhQ/zx023dReJvsxCUbEZ5I+Pa7RKpthfHRV5v4308xhHm0nD0+CAJbtm1LW4iHwxJ6FafjNTQSceXnPseNf/873/7lL2lpaOBrF1zAZ044AQCjwUBddTWNdXWj6y+dN49fXHUVv/vHP3jkmWc4cMkSvnPppYgqDhqvOOcczv/2t1mxcCELDzhAcZ3qiuwCmTUhPsURRZGGumoa6qpHM6IEAkH2dfexp72bF7ftJBgK0dkzwPad79PaVFdSuc3jUVOMx7bzTn+Ibz/nZkmtnu8fasUgJhfh8dbC1hY7v/jBwex4Z4Cl0xbRXF+OTieOCo5qu4HbvrSMXzzwEUcsHh+QAtA3JFJXNlaERN1ain01JpPojhIvlHxhHSaxOBU1sxkIZb2vNN1TogI7kWU8lQDPxsosyzBZDLKx17MYorxagnfuuBfOOSet9fsdQ1RXam4pGvln+YIFCUvKl9lsPHjLLeOWr1+9Oq9VNMOSRE1FBZdfd13CdbZt2pRV25oQ1xiH0WhgdmsTs1ubAOgbcPLcK29gNhnZNsalpXI0B3qZ3VrEHueX5/YF+f4Lbr62xsoJI7nLMxHhUfR6kZVLammyVCp+X11m5Lqz549rD0DasxWZ0hQhE0WE5yp2ugNWGk2etNdXSzhH+12KYhzUtXgnwx8Eo37yzUXkcl8mCs5OlEs8FhMQAHYefjKLn70/5fq9Aw7qqisz6p+GxmThuptv5vV33+W49euZ1tCAPo3iV+miCXGNlLR19jBnRguL581k8byZwIhLy4CTts4ennx+K8Nu7/4sLU11tDTWFTXVoVp86Ajz/Rfc/PJIu2IVT0hPhEdJR7QoCaChqmVUNDgQpu+fjhst/lKADA2JBOBEEOFqnZtOv5WmFEJcy46Smmz9rXuGRBoqJqZbihKZ3JeZZkNKB4sMfbpIesN0xHhvv4MDZqgfqKahMRHY9tZbfO2CC/j08cer3rYmxDVS0tbZw+EHLR+zTBRFGmqraKitYs3SiBU3NkvLK2+8gz8QwmoxjVjN62ioLUzhIbUY8kt85WkXV66yjBHhSoGZkFqEp0MiYdve7aelwTRu3UKK8XhyEeGFCtRU85x0+m0ssfcn/D4fIjy+/6VqFc+kzWzpduqoL1dXiEePr9CBw/kU4ams4dGS92EB9pxg5187PTQNSnD4yWPWixfmvf0O1q1clFFfNDQmCzNaWii356egoCbENVLiGHJTUWZLuZ5Slha318e+zl7een8PT78YKTxUVWEfdWmprhybh1sN1AjODNxzHlc962b9NAOfmJP//OmpBE97l5/lC5M/BAopxuP7Gx2EqJGirlRxh/XYE1QvnayWcDXFeK5it9spcsjcgCp9iSf+GCdiRp9Meb9Zj80nU+VKb3DjDwQxm4x57pWGRmly1kkn8dcHHuCotWsxGNSd7deEuEZSQqEwep2YtVi2WczMn93K/NmRTB6yLDM45GJfRw8vvfYWA84hBATqa6tobapjWlMdZbbi+ptLm87nN9u8AHxp9dh0joms4dmSbhu9AwHqqse/BOPzGxfDMh47E6A0K1BMca7W+ZDkxGXt8ynC4/tfDMGfqxhXS9Q63CIVNnV9xEdnlGKOrxAiPF+/03R8wwFcZoF/r7Zw8osezAmyQca6q8iyjKzlCtKYwoRCIVxuN5d8//scMH36uO+1ypoaeaOzp5+m+hrV2hMEgeqKMqoryli2MJICKCxJ9PQNsq+zlyeeexWXxzfib17DtKZIVVBTgSwx0qbzeegDP5vbgvz1Y2XoxfQHIJnmVk4XWZaRJBkxQV/yLcbTSdGYjE7vrnFiPJ0CKUrHUCzLc3/QTK3BN255IfpTClUasxXjaopaGcjg55hZ2yPHV0hLeKGvqwT0iOA6uozNzoj6fvhACwvbgjQNhpkuQoOEYgYml8dbdAOJhkYx+fYvfwlEKnZue+utcd9rQlwjb+zt7KG1Ob8VNXWiSFN9DU31NRw4Uj45EAzR2d1HW2cvr77xLv5AEIvJyLQRq3lTXQ16vbo5baVN57OjN8QvXvXyh+PKqDCN9WdPR3QlE+PZWoaHXCHKyzL7qRbqJZ+PgQcUv/hJPJ1+G40m95hlRbFOJzkv+e6PkvU40Tpq4w2AOc8VNYvhjpLqd5qJf3gya/gbBvi7BTwCzA/BMeUGpK4QsgAVbokPG/RcY5QwmUSudMEBcVk6e/u1jCkaU5vX7rsvb21rQlwjKfs6e1m9pPCuBUYFf3OPz097Zy/v727nuZffIBSWKLdbmdZYR2tTHXU1lVkn8Jc2nU+vR+Lrz7i45hArB1SOFfmZiBy1XTH2dflpaTBnvF0hLW5bOu2sb3Il/F7JKl4o1DgPnX4rK8v7xrRZKNLte6ECOYshWLudukmVMSWWZPenUvn6TNirgzst0KODMzywOrjf4r3IpOfbFXClSU+9BPhgaxh+VgZfdkUEe5TeAQd1NZVZ90NDQyMxmhDXSEopBehYzSbmzprG3FnTRpcNDbtp6+pl+9sf0NvvQEamuqJ81HJeXZE6GFTadD7BsMxXN7s4bZ6JI1pL43ijtHf5WbYgsbWrVALLtnTu72MyUZ6KUrOGA/QHLdQYInEDpSjCY9efjIGj3U6RhoriFFMqBLkOFuOt4YMC3GOBbUY42QtHu8a/7GtkONUL15bBF90R4b08CFY5kl88lt5+J/Nnj/eL1dDQyB1NiGskxOP1YTGXliiNp7zMxuIyG4vnzgQi/tQDjmH2dfbw0rb9waB1NZURcd5YNyYDTLR6pjso8/5gmFuOGV85rtjCpncgQF1N5tdBLUFbSuIu277kKnQkGfRrCnsOsu1vJucokZtJqQzuonQ7dSxoVs5YM1lIdI9mahV/xQB/tMERfvi5E2LjW2eu2D9A3r3dzrF+WDLTy4/6zfyy3stTH1hpCMPSuFPtGHJRnkbmLA2NycrKT30qpVFPq6ypoTptnb20NuXXP1xtBEGgpqqcmqpyli+aA4wUH+p3sK+rj80vvcaQy4MoiDT0bmaauZJKcZibtrnRi9Dllsa4pSQTNEpiRfW8y7JMWJLRJYhSSySYSs2qPNHSGsZed7dfwBo2AeODNUuVXAdPhQ5cTMWQV6DcMvmzdqjhRvWQBS52w6q4bCixIjz280zgK1V+Lum2INhl/tDghbesY/KIy8iIKqeZ1dCYSHz2hBMUhfi2t97CZrFw2nHHZd22JsQ1EtLW2cPCOTOK3Y2cEUWRhrpqGuqqWb00IggD915At83Key4rv/6wieqKmVx0uEC75AGPi2lrW1GaDEhVAGRM9hIVRPmQK0yFXflnqtSHYgnwZK4omYrwZGKkGJb5LodIU2Xh3SKKnS2l1MT4VNGBStc9lVV85goXu7fbCQEf6mBRAhFu+82Titt/AjguECAQDFJmG2v5DgZDGFQs562hMRG5KkFGlCGXiwu/+12qKyuzbnvilDnUKDjdvQM01lYXuxuqI206H70gU6Vz8aeXP2CB/j1+uPh9Ptv0IbNW1tLTMJuHXjPzty0W/vGimS3ds9ktLCLQuHK0jXREdsr0fHu3plynvctHS+P4gkKlJMLzQam4wgB0DOpoqixOoGApnYdi4fIJ2EyT3xqeKl+8ZUNr0u1nrnChB2aF4R2FeiOJRHgUk9E4ToQD9A06qa2qSLqthsZUpdxu59Rjj+XPWbqlgCbENRIw6hIxgUrSp0PUJzwoyXz9GRcHVOr44kozgiBgPHAh02vDHDIvyGlrfZxz5iI+9amFtDSa2dfl4/7He/jrfR3c/UgXzz/5Bnv6dARTuK2mYzlPJsYjpe3HZkwpJRGeytqd7PtUgxk1RWg2QY9RimURj5LteUh1zOkMJtV2tcqGbqdI/STNmBKPGmL8RC/8zQqNy1zMXBH5SyXCkxFJXagJcQ2NRJiMRna+917W22vzTRqKDDiHqa4cH7g4kYmKcEmW+cELHvSiwHfWWRX9vqICxGQUmd1qYXZrpMKmvHcrvgC0D+rY06vjxfeMhMJgMci0VIdpqQ7TWClhiMl+GO+uoiikExRM6ekPUF9rHLNeoYkXBOkWd1HDLzy671wGGrkOUvwhYYybUjEqXWbjppKqb2qWr88n3U6RxkmcMSWK0vXKxk3ls4tdvN1n4haHkS9XB3IS4QC9A04WztEypmhMbR5//vlxy0KhEO3d3dzx8MPMaGnJum1NiGso0tbRM+ECNZMRK8JveMVL+3CYm4/ZXzkzWen6ePFrNsIBDWEOaNgvDjz+iDj/oFvPlnd1hMJgM8WI8woJvS5zIS3FBGqWamCmUhGjdEV4Kp/70fXyZBVORSgcqeaYqJ1CVv9UY1AyEel26lg6XZ2MKaWUJSZdH/xEYhwSF/z5SpWfc7qsHO8PsSbHfvYOODiselmOrWhoTGy++fOfIwgCsjzeTW5aQwPfveSSrNvWhLiGIm0dPRx64NJid0MVoiLcFZD5wQtuBnwyvz7KjkU/XoRDdi9lqwnmNoaZ27hfnLt8Ah2DIu916nnuHR1haUScV0XEecOIOE+03yGvQJlsQt7bmXC/pSLKcrV+5yMwMNdzI2/dSY/fSp27GjKop5TvQNPYdnLd10Swirv9AvYMfMSzOZ50B4TZkKw/mQxEE6U2hPGCvFwHZ5UF+duQMWchHgyFMBo0qaAxtfnjddeNWyYKAjVVVUxraMi6mCBoQlwjAYNDLqrKExeRmWi80B7kupc8HNqi50eH2TDq9ruj5CtPtt0sM68pzLymseK8fUDHu516nk0hztsHdLRUT/4p+ShqiXE1ByedfitNJo8qbeXjPpvswZxR41M6GVNyHVCoLcIz6Y/SuvH9STYjoiTIP24PcvuQkXcuPYYFtzyRdl/G9EHB+qehMRVZvTh/z1pNiGuMIxQOo9eJKZPXTwR8fj/Xv+Dmpc4Q3zvYysHNCukEKFzRGrtZZn5ziPnN+5e5fALtg+IYcW41ygz5BFZMDxIKM8ZyXihKVeQVchagy29jXWWXKm2V4vksdWv4sE+gLI384aV2HGr0J9HANF1BbhXhZHuQmx0mfnz5Ruy/zdxX3DnspqJs8hhkNDRKEU2Ia4yjq2eAxrrJkbaw3+FgS3uQNQ16FlYnV7PFyl1tN8vMbwozP85y/vctFvpdIv/8r2VUnLdUh2muGh8QqialKBijFNoVZzBookrvL+g+S4li5xHvcqQO1FRD9Kp1nKn6Eh9LoUSsm1eyWaJ0BPnFYZnP/7OfnwyY+NxlxzD35sws470DDuprKjPaRkNjMjLsdnPzHXfwwmuv0TswgBQ3WyQIAi/edVdWbWtCXGMcbZ09tDZPjkDNloYG7v1kBbdu9/KJ+4aYVSEyo1zHjOi/5Tpay0TM+sTW/2JkybCbZWxmmaOXBEaXuf0C7QMiH3Tref5dHSEJLIbVNLn20WJy02jyYBSzT/NWygK8GMgyyJR2IZlcgg9LzYqsRM+QjpaqxEK8VI4hnX4oifAtnfutzdGiWNH1ooI8lR95spgBk07gp3Ve/jZk5MIuK4tO/zjfv+l2GmpqUvYXIqkLGyZhLQkNjUy57pZbePz551k2fz5L5s5Fr2KRK02Ia4xjX2cvK0bKw08GKk6/jW+eDhcNDbF73z72dHSwu72dRzs62L39FTpcEtVmkY0zDFy4zEyZUTnoopBCddgrYDePHXHbTON9zj1+aH/Zx25vOS86GwlKImYxTJPJTYvZTZPJjSmFOM/0uLIVP9lmVolSaGv4UNhIuT6YesU0UPPeySb/9zh/4xIRsKnodoqsmhlQ/K5UjiFTER4rvmOJLo8V5PHW8VjSdVtpPrqVyze3cVFFgNuHjFx8yXlc84OfsHLRopT97h1wsGT+7JTraWhMdl7cvp3Lzz6bC049VfW2NSGuMQ5fIIDFPL6a40SnqrycqkWLxr2AAvecx75hiT/u8HHqA0P8+7QKxCKbQdsHk1sCo1hNMPewacyNWeZ5+QM6/TbafHZecTbgl0SMokSTyU3zyJ/1oAX563wciabj44VGMoqRHabLb6XJ5M65HdWypSQQfInObzIRl8k+i+me4g0IWEv4UZSpK0oiEa60zvom1zjreDr7lvduHZdlxbKhFTa38T8VAabp9Xzje1fxuXMv5JxPfCJpX4ZcHspslpR91tCY7LQ2NTEzh1zhydCEuMYYvD4/ZpMx9YqTCONptzFz0/lUmgQOazEoivBCu220D4gsbMkud7L1oAUcABwQs8wfhE6HlY7BBrYP6vBtEdCJ0FQZ8TlvrpKwm2XVLampfGIzEeOFptNvZY7VWexuAMrnPZmVNZWImwjkkrAj19kXNUglwp/sSDzY39gsKwryRCj5lSulPBQE+Jg9hAC8eNfvUgrxyDYl7JuloVEgPrVxI/c+/jhHrVunetuaENcYw77O3klVyCddPlh1DY/e/WXu+UR5wfaZzPez26njiIXKU/LZYDLAzLowM+vCQMTdIhiOBMN1Dup4y9GEyxtG91ondTVGWhpMtDSaKG9dFSlikIVVNJ3AtHiULLDFypXeHbByaI4ZU3IdwGUqwOOX5yLIix2o6fAIVFozj3lQuu/yMeDLZIYi9jolE+Dx68QK8niiLizx+2yyzEsqxmUZ/u3Wc5Qt+UDf7w9gMipnmdLQmGqcdtxxvPrmm1x1ww0smD3eXUsQBM49+eSs2taEuMYY9nb2MH92a7G7UVCe/u9/uf7X13P5SgtV5rH+4XmrkpjCsizJ+U9ZaNBBa43E9JUrR5eFwzI9/QHau/0887ID51AQBKitmkFLg4nmgQDVVcqzBrFkIsJjRVKxxV8sQUnEUKTg13REXlSgKQm7jc3y6DqJfI7jKaVzD5HBaENF4vOfqBhR9BizGQimQ6YuQpmI8K3PNwCw+tDu0fWj1zJZu1GiA68xFvIRMW7Z0Ip3cxtPefT0SwInphDivQNO6qork66joTFVeObll9mydStur5fHtmwZ970mxDVUo6tngA1rVxS7GwWhZ2CAn/7hD7y3879ct97G6sax1p9iZREZ9gnYMqgkmC3xgmJUSJRBSxm0zImIGkmW6R8I0t7t5+U3huh3BJBlqCw3RMR5vYn6GiM6nZBU/Ci5T6SiWNbwQBFEeLLBWSI3h0TCLlbAxYtxmBjuKt1OkVl1yeMkklUGbbLMS1uMJ00TmGVGFMhOhMf+f/Wh3WlZ0JWutdIxWTa0svmeHs4qC1KRIq9474CDOi11oYYGAP937720NjZyxec+x7SGBi1rikZ+kGWZsCSh02VfqrXUkTadjyTLbHovwM2veTl1nolrTyrHpBv7sitmKr9UFTXVSKeYUITHEbWu1dUYqasxsmJRWaQPsoxzOER7t583d7nY09OPLIHFAnV1kb/aGjCMjG2UrHexoqHU6A5YaTRmV1EznyI8kbCLFXFK1tT4c13KvvlRepwia+fk5p6VqRjPhnREeCpir5/S8ug1VVo/VqxHXVnWNylbxQE+0Ju47JpfpuxTb7+D5ZMoe5aGRi60dXXxw8sv5+AVK1RvWxPiGqMMOoepqpi8VdSkTefzkTPMdS96CEoyvzu2jLlV4/0/ip1Pu31AZEFzdoGa6ZBMhCvlNVZsQxCoLDdQWW5g8Vw7UEOndxceL/T2Qns7vP46hEIwGNJjqQhirRSxVonojekFfxXLGg6RjCmNGZa2V2tQFCVZsF9UeCUScEqkSo9XavhDAuY0XJSjVt9klvF8ka4IT2bVjr+Gi1/qGP3/znXNiusobR8V5IlcWQA8QZluv4GZ06YlXCdKv2OImsrCxcxoaJQya5ct44O2Ng5bs0b1tjUhrjFKW2cv0ydpoKa06Xwe+dDPz1/xctFyM5+eZ0Inpp8NIJ0cvtm2FU+yQM1cxWm+cy9bLTBjeuQvyjN7TXidEh6HxEBbiHBQRhBgXnOID7ywpHUWslmGtm157VsmdPptLDi4HsGSn3RVUTIV4Yms4JMNScq8kFIqQa42aljCUxEV5VFBni3R58buoTDTm5rQ61IHoITCYfT5DlTR0JggXPm5z3HR977H+lWrmDNjhqpta0JcY5S2jh4OmYTVFaVN5wPwt7f8/O/hNtY2JTazxVs1E73UU1W7S9h+GiIhX4GauUy9p2NVVHID2NJpR2cAe60Oe+3+g5IkmQOMIXr74LlXHDiGg+CxUGWTaK6SaOx4lzoj6IqUOW0oZKDMnF8//UwCMiE9K3i8C8NEZcAtUG3Lzkc/md94vslVhMdaw1MtVxLnyazhAIM+mZrKypT9kCQJUZi8LooaGpnygxtvxOX1cvpXv6o4kNVK3GuowoBzmKqKsmJ3Iy/0eyXaXRKrGtS95dUoeBLbhitJoGYu1vBMMz2kIpH1MV6Mr29yKYqTw1sihXLq6qDJUgeAtKeTQbdAx6COHa5aegMWJBmsuhDNpkiV0EaTJ2Wl0FyRZBCqyhEEb17aT1ck5uqKkg6xg6xiF++JJVXGlFTkW4ynSlFYCBJZy5O5lA35Zcrtqfs56HRNajdFDY1MaaitpaG2Ni9ta0JcA4BwWEInCpOyeIMsyzz8YYDldToMSdxRcvHxTUfApCMM2gdFxYqa+fKXVhLOSuuM6UvMsSoJ8nTajG9b3rsVQYBqu0zVu6+zuGb/Ou6wnk6/jb2+Ml52NhKQRHSCTKPJTZPJQ5PJTZkumLErQyKcC5ZQ9V5+xX4ilAReuiI83hqeyjoKpZs9pccpMq8ptziJfInxUhDh8cRf+0TX1WoAz7AvZXtaxhQNjbH84PLL89a2JsQ1AOjqHaCxrib1ihOQ2x7s5kHZwrWH2vK2D7WsiR0DunECRA0Rnq0oSbsEfVz7qXI5x7Y7RtgrHKtNF2KO1TmmymVQEukOWOj023jHXcVwyIAA1Bh9NI0I9FqDlwzCAIDIYKxzn46myvwI8Uyzo2QjwpMJ8FLNUhNPz5DIofNzvwZqi3G1c5PnOsMRaw1PZ+BVbhRxDg+nXK+338H05skZL6ShUWpoQlwDgLbOHlqb6ordDdUZcrm4fcjIXz5hZ3p5YsfrYmdKidLl1HHYgvRStqnV50xSvCUbbCiJHqW2E4nwTDCIEtPMbqaZ3aPLJBkGgmY6/Va2D9XSFzQjyQI2XWhUnDea3CldWzoHdSxuDWbVr2Tky1VisolwgGBYwDhB3k7FtobHEnuNo7+t2MHt3CodHz7XxoDDQXUSX/HeAQerlpbmbImGRiF46Omn0ev1HH/YYQDcdt99SdfXCvpo5ExbZw/LFowv2zrR+d2ln2G9RUgqwjMhvpR0LKms4on8qmO3CUv7AzVTWcLlrTszEuPJskqkY/lORzQnclVJ1Z4aVn9RgFqjj1qjj6VlA6PLI64tVvb67LzsrMcv6dAJMg1Gz6hrS4U+gLgmci57hkQ2lO0X69kG5mZCOmXr48lFgJeqSwpEfgOZzmRMRAqV9SY2h7jdKHBkU4hNTzzBhZ/+dMJt3F4fNou5IP3T0ChFfvO3v2ExmUaF+K//8pek62tCXCNnvL4A1kn24H3uouN4xG3iL03Jg+7SFbPxlt1s8zAnEnRuv4DVGBFU+cyhHbv/VFbabMVn/D6SDlDynC884toyxBzr0OiyoCTQE7DS6bfynKMZZ9CIsMVChVWi3yXQ7RSpr5AwzipO9g0Ym6pw9aHdbH2+QTErSrwIT2X5LmURDtA/LFJTVhwf/WSo6ZZSzNSTZ3gGufTOv3Hyxo3UVlUpriMwBUZCGhpJuPmaa9CJ+zMHPfL73+dtX5oQ18DnD2A2pVE5YwLx34uP5Xt9Zn5Y66dal/9y8WrQPiAmraiZDwqRJaOYIjwRBlGmxeymxewGeiNWQ9lLj1Ogy2HmnQ49z76jI7y9A6NBpLHOSCM6mqok1dMapivwkgVjpuN2UuoCPEq3U6ShorC/g1Jh57rmhCkMcyHWKj7DIHO4JcT9Xz6TC297dNy6Hp8fs9moeh80NCYSc6ZPH/O5qS5/rruaENdgX2cv0xontn+4+4qNAMgy/Mej55eDFr5T42O1OYxlQ2vC7XL1s463iucStNk+oGNuUygjcZqpe4oaJOtfqr5kI7y9m9tG/5/oWsYKjWwRBPAERBa2hFk/PzA6W+APSHT1+ul8V+StdgMuX8RaWG2XaKqUaKoMU1cuoVMh7XKsW8rGZnlcRcZMrN8TRXjH0+3Mj49+LkxEa3j8syj6G7FsaGXBg528HVB21+vtd1Bfo2wp19CYqvzyttu45IwzsJhM477r6Onh2ptv5pbvfz+rtjUhrkFbZw9zZua3gmAheM6j4z6Xga6QyA31XhYY8591QU2x0+XUsT7NQM1CkI2wVdPCHSvA80ns4KHTIdJUOdYaazKKzGixMD0cBCICUZJh0CXQ6dCxo81A75CIJINJL9M4Is4bKyXsGVrP4/OuJ/L9zoffd6nkEO8dFqlT0TUl/riKVexHiXxYv9OhJyxiFZXvrd5+B3XVFQXukYZGaXPv44/z+PPP883/+R82HHTQ6PK7Hn6Y3/z1r2kVykqEJsQ16Ozp57ADlxW7Gzlzq8PEemuI6+t8GNNwcczUkhyfkk9ti2NYAv324rhqxFMsl5FsxXe2/Y2/B7ocOpbPSJ2/WhSgpkympizEktb96/sCkQFVp0NkR5sBtz/ibVttl2jc/TrNCxdQW21EH1MyNJOsNfECXI17sFQEeJTYgOV8kCxoOVMyzZgSaw1XQ4QvfqljNIVhZPbEzvom1+hMXXygsbB6MYFX3uThoIlfVSrPpvQOOJjZuiDnvmloTCYevPVWbr3rLr7205+yftUqzvz4x7n5zjt5c9cuzjrpJC4944ys29aE+BRHlmVCYQl9Pt98BWK+MUyVKI8R4cncUrIlE+GULm6/gMWY2HoaFaj5OJ54CiXCsxHd3s1tqp0DpYGYJ7C/sml0NiQToWo2wsy6MDPrwsRazwdcAl0OHTveddE7ECAcljEaRRprTTTVGxHLwGqNuMfEW8XVEt+lJriVCIVBX6DK6pkELZc6sYG8WzrHinEYm/nnv9ZmmmzDzDIoP28GJ3GFZQ2NbKkqL+dbF13EWSedxFf+93+55PvfZ8ncudxxww3Mmzkzp7Y1IT7FcQ67qSzPX6GbQrE3KPCYx8Clle7UK6uA2tbw9oGRippDqdeNpxh+4rlSKLeTRCidr7DEuOqcaohXUYDaMpnashBL2I2wfsT33C/R1eens8dP1/uV9A45ACgrg9oaF7W1UFM9tq1M77uJIL6jyFt30nvAUmqLkDElmQtaokF3LvnD1XRJibeKb2yWFcV4lBn1FtqGJdxmUHryS5I8JluEhoZGhJ6BAW6+4w4+aGujqrycQaeTfV1dmhDXyI22jh5amyZ+BTUJ0CFTlUGGlHwJ2GwCNjsGdRzQEEooxAthCZ8qJLrm/cNiQURgVPSZTBHf8xktlpFv6unw7GJ4GPr6Yc8e2PYahENgN5XRUGtisNZFY72JqnI9QvyoIab9iYDSzEv39g7qkZG3DhQ+CDmDKpyZiPD46qjF8guP0rr3Q9Y26XnQYeDzcd+FwxI6NaKONTQmGX9/8EFuufNOKsrKuOnqq1mzZAm33nUX3/z5z1m1aBFfv/DCcZlW0kUT4lOcts4eDlqxsNjdyAlZlvlxv5nLKgPoM3RLKRVrcqdDx6HzA1ln/4huE3ssse0U6hij+8mne0su7inJzoNSoGa+SOSn3GydB1aY3zA2I08wKNHTH6CzN8ALWx0MdvUCYDfLNFSEaaqUaKwIM9GzznX7rawojxxb/D1UiHs4HTE+kUV4lI95hvidxzhOiPc7hqiu1NxSNDTi+cWf/8yZH/84l5111mjmlCvOOYcTDjuMa2+5hdO/8hVeveeerNrWhPgUp98xRE1lebG7oUg0JWEstt88OW7ZS5ccx5Bk5rNl2aU8y4cYz9QqHpbAoIKbfq4CWK2gx1wEeazILqQLS6dDx+pZhU2bl0z4xboUGAwiLY1mmgM7oQKYE1k+7BPodoi09et49UMDvqCAIECNPSLMGyslasukvAY/qklf0EyNwaf4ndJgMx1iz2+61WHV8BmPTz2ZbxIVfIoSe+zLTWH2BkX6HY4x2R4iGVMqx2+soTHF+ctPf8riOXPGLZ87cya3X389dz86Pid/umhCfAoTliQEhIRT3MVESYRHl8eKcfcVG9k0bOKT9uA4/95MKKYY9/hJGqipBnlzw8myTcuG1rTyg0eXp7NuKlL1td8lUmMvLf/k+PXiKTPLlDWGmdO435IvSZFj6XKKY1IrGnQyDRUSjSPW8wqrnNNvJh/IsoAuj33KJc8/jLeGK4ltpfzvkD9reNQ/PFaERwN84/3Do4MZgwCL/ALPbd3KyUcfPfp974CDA2Y056WfGhqZcN8TT/CXBx6gu6+POTNm8OVzz2XlokWK6z7z8stc+eMfj1t+8zXXcMjKlar0R0mERxEEgc9+7GNZt60J8SlMd98gDXWlV7hB2nQ+O/0ij7gNfBgU0SNzuDXMkdYQtToZ1+UbGb76TvZ89yx2B/W84tPx9Wr/uHbUyrCRi4UsnRd/x6CO5qr9QkrJPSXeMpwPn/FMrde5CvtMjqEg2WJkKFaMWqp7LBPxKIpQVy5RVy6xNCa1YiAUqVrZ5dDxXpcRp0dEliPuLY2VYRorJBorw1iK5N4SkEQMYuqBUC6DSrX855NZu+O/y0cBn6j4jidR3vnY444+S1YG4LlXXhkrxPsdrFupLHY0NArFUy+9xA9uuonzTzmF1YsX86+nnuKL117LphtvpKGmZtz6Q243ZqORW37wgzHLD2hV972xr6uLx7Zsoauvj2Bw/Ozp9y+/PKt2NSE+hdnX0cP0EgrUDAaDPPqrc3l8d5D3h218yuhjozWIWxJ42qPn/xxWKnUyHgnkiz9Pk95ElU7mx7U+bBM4vqh9UMes+sx8kxO5bGQrWHMV4fEiMjZvcWzbaqYfVBOXb3/awmKR7yBLox5aayRaa8aK3ah7S/ugjm0fGfAG91cObaiIWM/ryyUMKd4W8TmrUxF/b/QGLNQbvRkcUWHJJUuKmiiJ8GTW8Oj1iP+NrwjC3994g0AwiNFgAMAfCGI2TfBAA40Jz2NbtjCjuZkrP/c5AFYuWsRR557L89u2ccoxx4xb3zk8TG1VFSsX5i/e7blXX+XL119POBxGEAQMej16nY5wOIxOp2P5guxz72tCfArT1tnL4vmzit2NUd78vwv49VYvl66w8ENxEFOMYWm9NYxf9tMZEjAL0KBTf1o9mQ9qLkVAUlnFOx06Dpm7v6JmKmt4MpK5cChZErPx4Y5tI9H5yNUFoNB0OUQaCxSoWWooureMVA7tcup4t1PPc+/qCIVBJ0JdmURDZZiGCokau4R+5th7IBNBHivGuwNW6o2etPqcrlW82PnBY63hO9c15+yeksgSDomt4Ykol2F2ayuvvvkmh6xciSwXdyCqoRGl3G5nWmPj6GebxUJrYyN+//iZb4Ahl4vqHCpbpsNNd9zB6sWL+frnP8/djz5Kc309533qUziHhznza1/j65+PD31OH02IT2E8Ph82i7nY3QAi7igmHdRYRE6ZZ8Kr8L4yCTAzQRGKRGRjgU32ks+mXHYqQRLqG0L/+i6UjkztYEU1s5nEHntsruVkua6VrkUyQaVmf5Nd1w6Hjhm1U1OIKyEKULt4FTV7t7J42v7loXCkBH23Q2TbRwYGpBqk1zpGihMZaag10VhnpKIs81dLd8DCQeWJgw01lEkWoJmI3dsj1v3D16zh2Vde4ZCVK3F5vNhtlhRbamjknxM3bOCSq6/mqZde4qh16+jo6aG9p4cNa9cqrj/kctE7MMCnvvhF2ru7md3ayhfOPJPD1qxRrU9tnZ1cduaZzJk+ndmtrbz53nsAVJSVRaps3nEHP/vGN7JqWxPiUxS/PzA6HVlspE3n4w3KPPhhgJAkF73YC6SfoSGRME8rO8PWnXjDOsy6mYrf53oe8uEGonQ+4gueKBURyaS9+O8LUemzyyGy9oBA6hWnGPH3s14HTZUSTZUSwvTlo+v5/RLd/QG6+/y8t9uDcziETBPW0CANI8GhDRUSdvP44Wb0Gg8EzVQZlC1eSqSyiufLGp5uNpR8+IbHEivAlazhqX6HMvD6u+/SWFsLaBlTpjqv9NgoD1gLtr+QnPh3tGLBAr583nl85frrWbd8OUMuF9ddeSVNdXWK689ubWVvZyefOeEEREHg9vvv50s//jF/+9nPWHjAAar0t6WhgaHhYQDmz5rFH+6+G0mSEEWR1sZG/nTvvVm3rQnxKcq+7j6mNSrf1IVE2nQ+z7cHuf6/HpbV6fm1fVj1feQiSDNNmZauAI/S7rfRbBpbwlzNgUi+fLKjIicqwqOV/DJqY+ScKgmmMeXHVRTjicRbICRgUnFcmmnKvFIj/pqkErUmk8j0ZjPTm8fOsLk9DXS9tYPukQwuLl/k5VtuieQ/b6iQaKgIY1m9GPnBIKJK7mbFdklJRC7uKbFuKYlEuNJvMJGbmI+I3+sLd94JRDKm1NVUZtU3DQ01eev99/n7Qw/xoy9/mW07d7J1506ee/VVDluzRtGA+JkTTuAzJ5ww+nnNkiWceMkl3PHQQ1x75ZWq9GnJ3Lk8/9prfPzII1m5cCEmo5Ff3HYbnzzqKO557DH0uuxzxGpCfIrS1tHD7Namovah5+/n8vNXPLzVF+bb66wc3GzAu3kgL/uKils1ghmzztigICY7fHZmWiLlNJMJ8OhUcipmrhj/Is6HGI9m+WiyzKPTu0tVER5dXigBG/V9zoRMhN5E85dXE5tVxwFrVjB771YgkmVAliMBol0OkX0DOrZ+aMDtF+iU7TzcO4MGo5cGk4d6owdTiiwqiQZWibLQpHMtMhXx6Vq+S6WYTxQdYDIasVoi7ig9/Q7mz86uMqCGhloEg0G+cv31XHLGGZx4xBGceMQRXHDqqVz43e9y/e9/z9Vf+ELKNqwWC8vnz2d3e7tq/Trnk5/k6t/8ZtQK/qVzz+VbN9zAHQ89hCzLo4Gl2aAJ8SlKZ08/h65ZUpR9S5LEvT89m5u3ezl5jonvH2LDrM/eFBYrUpWEaCxqZBvJpuJfIotuZ8DKih2vsi8k8bJXT19Y4DW/jk/ag8zYlbm/ZvRcxJ+HXAcixSafLio9QyL15an9w0vJyjrRxH1sfwUhYhEvt4SZ1xQ573v6dHzUo2PZUBfdAQsfesp5ydGAX9IhCFBt8NFg9FJv9FBv9GJMI81hsr5EySbmI1PUEODZWsOTIRN5FkcZGnZTXmbLvpMaGirwQVsbXX19bDjwwNFlLQ0NfOaEE7jtvvvSEuIAgWAQu1U9V5tZ06bx15/+dPTzsYceyrSGBra99RZzZsxg3fLlSbZOjibEpyihcBiDvvCX//09e7j2uq8gA7ceU8bcquync5SsxImEaCpyKRiTrUDse6qN9ytmcHmnkd1BkTXmMPuG9LxngNV9emZk1WqE3dvtCa3j8WQ6CBmtmhlnFY8S65eaybnJxLdcTToHdTRVJhd2uQg0tQRzMneRiSDKkw0eepwijZUSVV4/VQY/C2yO0e8kGQaCZnoCFt7zVPKCo4mAJCIKUGPwUf90Nw3Lm8alWEwn/38m13V9k4stnfaEBXtiUdP6nY4Iz4YOHcxo3t+2JMuIpVbhSWPKUVVRAcCu3bs5aNmy0eW9AwPYRmZv3F4vFpMJURRxeTy88NprHHvooaPr9g0Osv3ttznrpJPy2tdFc+awKEmhn3TRhPgUxDnsptxemKAMadP5APhCMn/c4WPTLj+XrbBwyjxjyT70853rWpZlHn20kxuHylluC3F+RYCV5jA73rBzdQV8YxiWF7bSekYkEuNj1slCGBZDhAN0OkQOnZc4UDPflvBSsrQXiy6nyJzGAHSO/04UoNboo9boYxGDo8vDIwK9O2DlnY79KRZFAWrsEvUVYRpMPuqrjRgM+Sk0EO+Wki8BDslFuJI1PD6POIwdiO/RwYLZswEIBkNFMcxoaMTTUFPDMYccwjdvuIH/+fSnmdnSwva33+buRx/li2efTb/DwYkXX8yhK1dyw1VX8eZ77/HdX/2KzS+/zPpVqxAEgT/cfTc2q5VzPvnJYh9OWmi/vClIW0cPrQUo5BMV4f/tCPKj/3pYWK3jHyeVU2dV56UYtfhm4pqSLvl05fjhfb287jNxaYuF2s+czorbX2Ln63Z+XgbH+9QT4Yms4rHk4jMfL8ZHv0tQQERpeyWrpZKIz2fmFIdHpNKmbF1UEslR63/amWEyLHQzmUlkFXd6RCqtmVl4dQLUGX3UGX0IS/bHu4Ql6HeJ9DhF3t76Hs+F6wiGJURBoKbKQEONkfpaoyoCffWh3QWpnBkV4ZkI8FTs1sOyWZE6En2DTmqrKrLpqoaG6lx75ZX8adMm7nrkEXr6+2ltbOSqiy7i1GOPxeXxUFddTeNIBpV1y5fzpx//mLsefphb7ryTYbebA5cu5WsXXEC5PbciXB+/+OK01xUEgQdvvTWr/WhCfArS1tnDmqXz87oPadP5DHglfrHVy2vdIb611sr6aflJl6iW+FZCbUE+HJB5wq3n/hY3b595LdMaarH95knuO/5kfAIclX72tpxJJ6d3OmIaxovMdIRzrBhPtV6+iNYwiZ+cSSbAYz9nYsXXBHlyBAHFXPqZohOhvlyivlxiSSsI0yOFQcKSzMBgkO7+AO984OG5VxwEQyMCvdJAfa2RhhojdTVGjCkEejruKdmSrT94pjNK7+vh9JFp9UjqQk2Ia5QGZpOJy844g8vOOGPcd2U2Gw/ecsuYZUvmzuW6L31J9X609/SgE0UWz53LsnnzCIRC+BIUFcoFTYhPQfoGndSo/NCNWr8h4nrxwPsBbnzNy4mzjdzziXIshsxeWr8aMLInJHKAQWK2QWKVOUyjvniV39QS5P96rIvlJj31Nz7JUw8+xcGrIkL2O5vu4KunnsldFvh8esUFcyL+OBIFnKYKklRK71iIvN9q4fQIlFv2+4cnchOJF+G5EG8VTseXeTIRf/weP1iM+f9t60SBuhGhvSRGs4YlmQFHkJ7+AO9+5GHLVgfBYKRyb1WFAVM5VFdBdbVyu2paxaMiPL5IT7YiPNHs1IAAvSIsmx8xyPQMOFg0d2bW/dbQmIz89rvf5eFnnmHzyy+zu72dDQcdxMc3bODApUtV3Y8mxKcYkiQhIKjqnx0rwj9yhvnRSx78IZmbNtqZX53dLfasV886S5gKUeZln45bHEb+0OgtqhiH3PzHtz3Wzv85Lfy23gtAMBTCOBJdtuf4M1lkivhtqkk67inZpmOMJVvxnW6pcrWI31enY3+gZroiPDZnuloBprlk75joFvZup46GiuyzoOSKThSoqzZSV21k8dz9yyVJ5t2e9xgYgLZ98MYO6Bz2AWC0CBhlHWGLiGTZbz1Xo4x9LNlmRRkz0Iv7be7ebuc1U8QFLuoX3jeguaZoaMSzfvVq1q9ejdfn48kXX+SRZ57hkmuuoaG2lpOOPJKTjjySaY2NOe9HE+JTjJ5+B/UqFm2QNp2Pd3Mbfhn+5jSyyWXgvIoAZ53YgC6D6hzx2Ty+XePnB30mflQX5JyKIFf3mfiPR89Z5cWPYsxGjO/7zz6+02fhm9U+Zhsl+q88AdOx3wRg5+EnR9bRQX0B9EguqRozJZ2ZhFRFk0bdX3LoS6K2uxwic5tCaQvfLZ320X8zTReXCUriOh1f+olCrFW82ynSUJE6fWTCtvI0kBNFgcoKqKyA2RFXarZ0mpFlmaBX5oOPZPSuMLqeIIfX7MbRb8aPDmtDiJBXIOQVkYIA6T0H463haojwWGKfsVsNcHhMfHKsUUBDQ2MsFrN5VHj3DAzw2JYtPP3SS/zfvfeyfP58PnPCCRy3fn3W7Wu/vClGW0cP05rVCdSMivCtPh0/GzAxyyDx50YP9XqZwLP70hZ8Sin11pjDXFIZ4Hanketqfbzq03NJZQF8NtIkE1cV59NtfKfXwom2EIdbI4Jj+94mxH/cx86f/Gp0vTcN8MU8aLt0rOJK5CJ8469pOukh0xXkmfYvmVDrduo4bGPi72Ot4VERXiwmsvBWIirGu4d0LJoWiixTOV+8mi4/0esvCAJGq0CoSiBUtf/7N56vx0gY2ywbc3b3Ya4JIhpkBEAKCaPiPOQVCPsFdq5rGbcPtUV49FxGf3+7t9tpF+EjPVwx0qwkF3eWUUNjIlFfXc3ZJ53Eglmz+Mcjj/Cfl14iGAppQlwjfdo6ezj2sANTrxiH+4qN45Y5w3Cjw8RWn44vV/k5zJqZVStVKfdDLSF+PWjivz4drXqJ5iK7pSiRyjruebqNXw6YqNLJnF+x3wTVX1FB3aBjzLo+AewFPsREIjVbMZTqmqZDuu4qqYR5Om2EzJWKmTOU3FE08sOwV6DMvP/Gz0SM52INT+VWlCwuQDlQUyCAngB6PF1jX62CXkZvkdBbZKwVYXQmmWV0EUbAgxE3BlwYI0nTY2YSc5l1iRfhUe6zwAk+MI98Hhp2U1mm3d8aGql46/33eWjzZh7bsgWny8UhK1Zw/Ve/ypFr1+bUribEpxgujw+7LbOKjfEiXJbh3249NzuMHG0L8dcmDzaFJAOJRGoisRaS4d2AyHa/jtd9Ot7w62jSS6w0hflFWOAVn44DzdlPYecLpeOMHuPdwwbeCIj8vsE7+n7dvd3O4Ipy5u3ZO2YbUYZQQXqcG2qI7UTkIqwy3TbYuBKjvmfc8nQCM3N1S5lolTHzRusq4O1xWWvUIJU1PBPf/kwGYko+4nJIIDisIzi8f9nOdY2ISNgIYiNAE8PY3vODLPPhXjDZRN52RgJFFzbPYSD8ftrHoTSQ2b3djlOA1w1woXv/8t5+B3UquitqaEwm2ru7eeTZZ3l482b2dHQwb+ZMzjvlFE48/HCqKytV2YcmxKcQgUAwIz/AfoeDf3/5dJySAY8s4JHAIwnsDYmEZPhpnY+FpuROzVGR6t3cxlAYPgqKhNAhETH+BGXYFRR53adjZ0BHi15ihSnMCfYg36zxU6OLWMquqvZzXb+JalHmOFuI42whqnT5NR9n4tIRL05lGf48ZODfbgO/qveODlSiOc9DOh2GcGRQ4RLgL9bIj7EQPuKpUHqJqyW+k80eKAnpdFwLshG0wvTVdHV4aagzjlmeaXaUXAI1NTEOLk8Yu1n933GuLimZWsOzzZoiITKMiWFMrD60G/eInXpWo4TfLWPUBdjbBrt29uAP2vGFXZTZoaoqItCrqkA2ywgJRjLxv9utRlgWjFjDFz97PwC9Aw4aahOkhNHQmMKc/61v8fq77zJr2jSOP+wwjjn0UA5oVb+2iCbEpxD7uvtoaahN+H3U8v1BQOTuYQPPePQcbNFRr5exCjK1BrAJEkfrQhxkDqNP04r1n0c7uGnQSndYYJZBwiSAiIwogA44wCDx2fIgS00+yhKk7z3EEmZTs4fX/Doedul5yG3mL41eMogHTUlsYSClZemK8rAMvxw0sdMvcmuDl2qdPKadgF6PIbjf9v2MCdwC/NgJ+an/lz6lIsIT5fFWEr7Ziq7OngBNdaaU6+XTLWWqi/HuvkDWgZqFyrYTe/3jRXi+Kmv+p0tkY7PMAU1wANBkiWRmkGWZ9/reY3AAAkP1vLk7wIvuSDlSc3CQunIjdeUSdQEzVQbfuHZfN8DqwH4RDhEhvmT+bFX6raExmdj+zjuYDAYCgQD3PvYYf33gAbxJ8ohv27Qpq/1oQnwK0dbRw4wWZctN2xeOYbtfxwMuAx8FRU6xB7mr2U1ljun09gQFftRv4uoaP6vTEO+23zw5+v94lxidEAniXG0Kc16Xhdf8Olbn6KqiJL6TrZtKjPtl+GGfmWEJbmyIWMLj9zFQXk710NDo59owdJqgX4SWAlvEk/ni5tMFJZZkIlypiE4suVikO3v8LJpjS7leIjcUNdIWFptCp4+Mp7svQGO5ujf9RMzJnixveOx9JggC8+rmQd3Y7eW9W/EFoGdYR+8bnbwaqKe3XUKqbkUnS1SFXdASoCnopg33mG2HXB7KMnRX1NCYCvzwiisKsh9NiE8hOrr7OGTV+JfuTeeewF1DVhabwhxvDXG0LYQxB0tzaOQdohfgxkET55YHWWuJCOao0FYK/owV4dHPSuvted3OajP8zW2hwjX+Jp65wpWRwM6EZGLcJcFVvWYqRfh5vQ+joCz0ByoqqHE4Rj+vDYLTB983S9i9Ms02HSYZjBD5VwYTsDQI80LpJkNLTDrpFwslwuNJJMKjVsl4UZzIhSAdkTzsDlFmH3v3RLdL5poQ33Y6Fu1k4rBYVvHoIExJjBeqyFB3n59ls0rAHyuOJsu80XtgfZMr4axIVEBn6pqSbfVMJaL3jtkI02vCtJb3AuB9M/IbDiPy5nt1OO12WspreHX6DG760g8pP2IdZTYr/YNDvL+7nbqaSsrLbKrWmNDQmMicdOSRBdmPJsSnEMFQGEOcj7j7io28GzATBvaFRDa5DDzh0VMuypSJMuUiI//K+5fp9i+PFexDYdjkMnDPsIFyEb5T4+MNv44f1EamSGOFdrzIjhfhidaLCtuj/XCjHn5YDud4YE6MQE1XhMvALj08O+Im/D9pZkdUEuP9YYGv9phZagrzpaoAuiTvsoHycubuHRuoeawfyp5301WlY8ZyKwEB/EBAiPy5Bfi9LSLKj/XDYf7cfryZBtLmi0TW2KgIihdAsZ+TCZVUlnNJlpOOaNK1dqsloAstxuNnQlKljswXbq+6PuL5HjwkKm0fra6ZaUGfRCI8GcnuE6UZLh0SFW43FW43rd3wSDlYvLBy2zYa77+N/kEn/Y4h3vlgL85hNzIyBr2e2qoK6moqqauuoLa6UsszrqGRJ7Rf1hQh2fTjdbU+hiUYkgSGJYGhmL9hCbrCAu8FxLjvI+sbBEZFendY5HBLiN82eHnVp+fSbgun2INYxcRCG5J/F/3efcXGMQLbJsPXXfCUCW6xRSzHS4PQEoZp4ci/0fRcPmBQhIG4vx2GiI96bcy66RIrxvcFBb7ca+EEW5Dzy4OjGSASDQhC+v2BmrHoZGgZCLMqQc2i07zwph4escC/TXCRGw5I0zNHafBQLKt3IqIiSkmER8VPrFhJ5rutZDmPFdcDjiA1lcb4zdImU9GcjoW5UGJczTzduSDnmL8632416VrF41Gjumb0/o3es+ncF7HXNdFvWwDO88Bv7bDECb5AkNnTm1m3ctGY9YLBEH2DTnr7Hbz9/l76Bt8gGIw8bMrLrNRVV478VVBeZksYLKqhoZEaTYhPEdo6e2hVKOQTFcHlwPjyEsmRZRmvz4fT5cI5PExNZSV11ZHo+1lXbOQUe3DUMuy+YmNC/+/47+KJrhvvciICG/1wlB/e1sP7+khRnH+boUsHZRJ4BQgKUC1F/qpG/m0Kw+H+iGD/rR1mZpE3cPd2O7t18ItqiQvKA5xcFhrznRIBvR5DSHlnB60vS7o/EVgWgqXD8JIRbiiDQ/0RgZ465HB/n7Ip7jPRUHJliRXjnT1+muoyF+K5COVSEeNqF83JliFXiAp79q8gJRFeCJeaVFZx2O96oiTIY91SsiV2EJLqWsY/i+aHYFUA7rLAOf0O6qorx21jMOhpqq+hqb5m7H5lmSGXh94BB30DTt56fw/DLjeyDHq9LmJFr66gtqaSuqoKjEZDbgeqoTEF0IT4FKGto4dVi+eq2qYgCFgtFqwWC011Y6OHlPy73VdsRPzpQ7x+5ScIySJ3DhsZlgROtQc56vKNlP12vBiPb0PJ/1sEFocif1HCRIIfrXLEeh7/2pSA1wxwkz3id33s+AQDKdmphxvtcIFDZEWvmd1pbDNYXk5VTKBmNgjAwQFYHIykPfxWBfyPGxamOZhIR5AXWrQns4bnQnwp+qgY7+wJsGxBmi5MkzCriZIYL7RbSldvgIbadIaQxSORVTzejSQqzGPFOCQX5IlIZg2PvWa5DKY+64VvVsCKd9/nuMPXpb2dIAhUlNmoKLMxZ8ZY082oFX3AyTsf7GXLgJPgSHYou81CbXXFqBW9styOKBY7R5SGRmmgCfEpQt+Ak9oCF22IF+PtIYGrzvk0HwatNOgkLqwIUCbK/GXIyO1DBi795VkcNd0wOs2ZaHo1nWBMHco5uQPAY2Z4wgSVMpzlgdUjriB+IiI3HTvpfw1wmw0ud8GiDKzp/RUV1DgdyMB/TLDFCH4hMlgY/ZPiPiss0wHlMnzRDdsMcLMt0o8Z4Yj/eFkas/7p+NLHr6OmMC9k+rl4Md7WC0cfkjx3cj4EeKlYxSH5+S9MoGaA6c1mhGnqHm+0rWTHEL+/dI83kYtKrJU81u873kIez9bnG8ZlTIHUIjwZsc/NRL9xmwyfc8NL23dw2gnqBKQls6K7PF56B5z09Tt4f3c7jiEXsiwjigLVleURkV4VsaTbLJk6CmpoTGw0IT4FkEZ8MYsRDR8V4//16ri238R5FUGOtPooF2UMI91Zb/Hygk/H/+3w8ZOXPSyu0bO4VseiuY0c8E4X5QopFLPJjPKuPuJPPjMMX3FF/o3yohH+bI0ERuqACgnKpYjYjf03LMB2A3Tq4JvDY9uIxSnAB3rG+XtHAzUfM0X828/xRESzeyQg0y1G/nUJEYt+dJlH2L+OR4gMFqLi3CqDJMAWE2wB9CMBnWqTiwhPmkM8zhquRLqBbImIF+OSBD2B9xIGZeZTCJeSGE+H6HXJNV1j/PXt7q/gwGXlWbeXykc8/jwnDXJMck1ireKQnhiPkm1WlUJwYBB2mIw8++orHH/YYXnbjyAIlNmslNmszG5tGvNdOCwx4Byid8DJno4etr65C7c3Mj1pMhpHAkUjlvSayvJxyQY0NCYD2l09BYiUMK4o2v73BAV+0G/mx7VeVpjHm6kFATae0MzRskyHS2Jnf5idfSH+/KaPt3tsVOpkFhrDLDVJfMIexDTyrpu23MW/3rKjI5I1xZZCq3mEiM/4cb6xAvpxE/zLAt8dhtYweIEhceRPiPzrFKBbF3FpOc4HS0aq0wXYH/zZP/Jvmy5SOCMowI0OsMf0K6TX0UaYByzwwyGoyyJzm0TkOGKFebkMdVkEnRaLZAIqW7eUWBGkJNyjYtznA1ORPSLSFePRdbMlXSGaiEwrjWbShsPtxGKOCNR8DTzUajM+rWXsoC72fk3mPw6pBXm6KQsTkW4Atkwk4Nvr8+PI0VUuF3Q6cTTwMx6fP0DfoJO+ASc73v2Q/sEhgiPxNeV2K7VVldSOCPUqzdVFYwKjCfEpQFtHD61N4wM1C8W/XAZOtgcVRTjst5YKgkBLmY6WMh3Hzow4iIQlmXf/087bfh2bvXr+49bz63ovXhm+0mPBWBMm7NbxoR7qwxE/6QVBWBCKiNNYVgbhEnfEL7whDAeEoF0XsW5fPbTflcUKWCVolCAEvKcHoxjxRR8QI5Uw77NEhLdXiASANlvD1Osk6nUyhxkkzvvAzG/ssNkEJ/giVvagTkc4HOYmO5ztyU6EQ6QfUReVQpEvX/FsfcOVxE46bOm0MzPsonakwKxStc5CWaLTDSzMRpArtVsMK3siES7LgDD2/Bd7FiCd6xFvHYf94jnefzxVQGf0s1rEi/BkM4aPmGFruZWNixdwyrHHqtYHNTGbjExrrGNa49j4I1mWcbm99I6I9A/2RFxdJCni6lJZbqe2KiLQa6sqKLNbtawuGiWNJsSnAG2dPWw8tHjV5vrDAgdbxvtwpCoqA6ATBRYdM41Zm9s4wRbiun4T53dZGZLgk/YQF1YE2PO6nRDwkQ7eMUSE8h9sER/wBUFYF4iIZomI5fwXjkh2lXYdHBSIBD7G+4WHiWRfecQcybLSEI782xyOWMNrRrKvlMswW0mkLnfx2R127rDCw+aIVdxQXo4pMMThfjg0kMWJLBK5ivB0rnMh6e2Dutpi9yJCJlk+0hGqari8qOUfriTCo2LV75YYFoNAUHEwFE86RajUIFsxDuNdVlJZx2NJVEkzH3iAh8xwiWBj7sL5GA0TK7OJIAiU2a2U2ce7ukiSxOCQi/4BJ529A+x49yOGXR5kZPQ63ag/elSoa/7oGqWAJsSnAC6PlzK7tSj7DofD7AroOK0sQXLsDBAE+G6Nn1f9Oup0EjMNkZdXVCjOAY4hYgmSgL26SK7wv1ojAlpPxAVlWIBl1hBLTGEWmSSsOmk093dQho+CIncNGTELMr+pCnCAMTvT9dFLXRyw3U6vGHFh2VdTwfQuJ01ZZGgpFvkQ4VG3lHjBk4lLSiKRE+XJDiGhX/nONgOnLdh/P6YjBPOJWmI8nTbSykcd059sz0syEQ7gdUpYKsRRd6FiX4NY0gn2TCTGsyF6n+bqlpIuT5gjxgRDlZ26Agfw5xtRFKmpLKemspx5jH32hEJhBhxD9A462bOvi6073sXj9SMjYzQYqKkqjwj0EZFuNmVfZ0BDIxM0IT7JCQRDGPTFucySJHHFj35Ek15isYKYzcTKZdnQindzG4IAB5qTV7GJisfZwAbg8rjvB8ICb/pF3vTr+JPTSF9ov6DTCTDDIHG8Lcgn7SFEFWY0oy4ou8vKqdm7L/cGC0ShUhdmK2iSuQBElyuJ8XBA5tVBe0bCJ1HGCrUyv2QrxguR3SRTUolwAN+QRFn9+CjsTN1T8lnUJ9U1yVSMJws4TnUvqpX3fYceHjVHXPGGz/jUpBPiydDrddTXVlFfWzXuu0AgSJ9jiP4BJ+/t3seL23biDwSRkTEbjdRWV1BTVUFtVTk1VRWYtPzoGiqiCfFJTkd3H80NxZmH39PRwYdtbdxV50MNF72oGM+Vap3M4dYwh1vTLEupEkG9HmOCYj6lhhoivFAuKakEeSyytD+pfHwmlYTbJBFBagrBTMV4Nu3nm3RE+JMdAtZuGY9Nx8bq9K9DodxTYkk14ElHjGcrwNW+Xk+Y4H4LXOmCYzbfz1/ve1xzzRjBaDTQXF9Dc1zqRdgfNNo/4OTt9/fS73ASCISQkbGYTCMiPSLQayvLtSJGGhmjCfFJzt6OHlqb6lKvmAfK7XZcfT34WsA+iWNllMRBdMAQTbMY1OnQhwor/LOlWJU3MykjrkQqdxUA37CMuWx8doVcXCOKJcYzbXfcspEBRj7zuSe6nkJYjkw/kXvEcb5L3edCIhGuJMDz6ZrTIcI9Frh2CI7cfH/e9jMZSRQ0CuDx+ekfdNI/OMRbu3bT7xgiEIy4vVnMJoKhPOSR1Zh0aEJ8ktPR3ce6FQuLsm/T907DJlrpDwvYReUXUlSwpmPpUsMaHk/8fjPZR7rWuZkrXLy8p5Wq4eKlCUuHdAR49JjVuBZR0ZmOVTE+M0UiomI8kQDyOCWslemnOUvXJaCUxWC8CE/nmNQaECgNro5ukvhoL8xW8I1WGjCkc68VYlChBrHHqrbwTjRjKAF/tMEp3v2ZoTxeHxZzaVc1nQhYzSasTfWKWck8Pj/bdr5dhF5pTDQ0IT7JCQRDRZkqc1+xkVudRrrCIuY0rOGZCHI1SLSffO0/UlHTmZe21SCVCI8/L6kEebbnMZWLQjpW82SuAF6HRO2s/Dz21BLjuYrgpIVrFES4Wv1O11/a75Ix2sYOhtQSpbHHEnusuR5fugV/Et2f8fd1vlJmKonxZ0wQEuCYGONs74CTeoXc3RrqYTWbaKxLXr1XQwM0IT6pGXZ7sFvz7wMYW8YeIjmCBQFckkCLXuK8LisrTWGuqvFRnsIYmUiQq2kNL0Y6vcAsK9XPFTdQM15sR/MMZyrC0/0uEUrCT80sFMnwuyVMCn5SSkIwmwC5kraMqxTwlynx4tQ7JGEZeRAoDbxy7Wc+BxvZkEiE59tnf+YKF6+/buduC1w1HKk/ECVS5K0yr/vX0NBID60U1SSmrbOX1ub8FvKJinBJhvuG9VzUZeGoNhuXdluwizI/q/Nyb7ObMlHm5wPpT4VGhbd3c9uEF+EAfkHPvCWOoux75gqXothOtDyWfJ2vqFiS924dFSRNlnn5T2Enk7S4hxriSN66M3cxWeDCNoriNeba5Mr6JteoIPU5JSwVwujnWGGq1I/oPZjrvZjLNclmhiL2mKNkI8Kz7ffu7Xb+aoXD/TBjJDxl8bP3A9A74FCsZqmhoVF4NCE+iWnr6GF6HitqRkV4WIYfD5h4zG3ggooAD0xzc0FFpGLNZd1Wfj5g4vTyAJs9ekIZxGblwye8UMSKhoCgwyBH3oSZBkJGxXI6ojnR9qVKrMBQEuRqi/KgT0If4yeVNGOFCtbjYlmg1SYdQZ7ubMb6Jhf2UICj5nqB5MI09vev1oAwX9ck9l5NJMALZQmP8roB3tdHfMNhvwgHGHQOU1VZVpB+aGhoJEcT4pOYnv7BvE0/RkX4QFjgmj4zvSGBX9Z7WWcJUy5Gcn1fWhng7mY30w0SX+y2EEZgfObg0kJYvTjjKexU63cbKmkIOkY/pyuOE1mx0912IlTEjBdG8aJPTTHucUhYK8RxQimfAkkN63imKFlv0wrQTLFOovOTqUtROAx6/fjzHrv/fA7CM70euQat5nIPp9PXRM+f261wngdMjBXhAGFJQidqr38NjVJA8xGfpEhyxPQsxj1s4/25o9h+82TS9mKt3x8FRd7w63nDr+O/Pj3H24J8ryKASeG5bhPhvIogq8xhbncaVcknni9iX2jZiPH4l2Y0cKrTUE1TYHDMd9G0hkqkEtDJtk1n+1JDKeNFfHVHNfzHvU6JQxcE0u7PVCRTX+psRLhOVAhWTHDOi5E7PJZMRHjsfaoYc5AnS3iic2eTIxlTxonwsCbCNTRKCU2IT1L6BpzUVlUofjcsQUdIZEgSaNJJNOplpE3nI57y53Hrev1+Xr38E7zhN7DDr+NNv44qncxyU5g15jCXVQao16f2N1lmkrihvri13fP9QlcS4wCdhkqWeXaPW56LYI5uGy/I1RLhxRA/8SJQ7ZzaXqdEbVy9jkK7CxSK+AqVie5NJfIZ2OhwwLSYi5DqvOczRiHTY0wmsqMk+i7b+yuT6waRgUtYhjuHDfSJYFZ4NPc7hqipKs+qPxoaGuqjCfFJSltHz7hATZ/fz42DRh5wGWjWS5SJMl0hkb6wQMN9TqY/eRrTVxxLS2MjPX19vPb227z/0XvMrbSzRPLySXuQ79b4qdKNf7rHvjAnsm+32lg2tOJ/w4BZDual/UyE90S4RonEuBpW8SpDCENMJs+8B4bGkI3wy3UgoiTGo31Jue80+ht7PWKzoiTzve/vh4ZaY2QfCi4pUDr3Zuy5jz3WTIo/pSPA469xtqLdu7mN9pDAdf1mdMhcOwS10vj1evu1QE0NjVJCE+KTlLbOHo46eOWYZd/+5S8ZDorc3eymKsZZOyDDwKpm2obDtPU8TdsHEnVWgStn61l8YCVmvQCUp50zeiIIPiXUsATGW7ACkjgaqFlMlK6R2jnA1SLVdcimAqcUltHF3POxQipW+Ew2t5R4MQ7pW1nT/T3EX4tkJev9QzU0LjSmbLOUUBoAphLj6YpppYFWdFm0jXSul+fpNh5267nFYeKc8gAHfWhKGADWO+DggBnNafVPQ0Mj/2hCfJIy7PZQXmYbs+yIAw/kH9uepyLuCW0UoPG1DmalEGBKRVxSiTY1KzFORDr91jGBmsUgWfGiUr0uYwqzKFjFMxXj841u9ozU1kgkwicraopxJSt9uteiyTKPpwc7qaky5nTeM3XXyGofKWYi1LiHlCzu2czSeJ5u47cOIy/7dPy23svSWx9Pun5vv4N1KxdlvB8NDY38oEVsTEKCwRB63fj8JCcdeSQAdw8rV9pMV5RZNrSO/qVLsa2sxdp/h99OU3Aw9YpFIv5aFvs6xRKf3hBSp4lTYn2Ti74+qK1NLnRKzRqupn+8ouU1zdkfpcw2kJ1oDEsyet3+iO1kecOVKHRRHiVruJoivNO7a5zbS/w6yfBubuP/nEZ2+HXc3JBahAP4AgHMpok1K6GhMZnRhPgkpKOnn+aGmnHLRVHk6hof/3IZuL7fhF8hkCdaQCcfltJSEnmJUFuMdfhtNAZKV4jHMhGuD4wXgFFBnkyU9/VBXe3YZaVsDVdThKvRZqrfRToDomBQwqBL/MqJn2mLvx8LJcLTPU9qiPBsiT6j3/aL3O/Sc32dj6Ybk2e+ApDlDAo5aGhoFARNiE9C2jp6aE1QyKfVIPOHRg9uGS7ssvBvt15RkMNYUZ4vcV4ICikwxwWehfVY8hSoORVQsopDYmtsrCiPFefDwzC3bq5iW/H7mczEi8xMxG26MxRKorzJMo+egQB1NYakAraUnjHJrOFqxRVs6bSP+Uu031ii5yhaSO3KqgDTb3oirf25PF7KbNas+6uhoaE+mo/4JGRfVy8HLl+g+J3tN09iA26QZZ555RX+8cgj3PjGNk60h/iUPUhjilSE0ZfARLGeZtrPXKxu8S/koCQi9A5n3Z5GhHh/cWDUZzxKMvEiy2DW2REEQVEElpIIz4clXGkf2VpzU/nuKxG9Tj19ARpqTWPaiqUUXFISnf98xRVEBy2xAa7pptR8xqvDIsBGayjt/WkZUzQ0Sg/NIj4JCQRDmIzKfuBRBEFgw0EHccv3v89tv72FoAwXdFn57WB6voPZWMjzae1SmsrORIRnU1EzFZFATaeqbWZDKVkZsyWRn3KUaAnxeEt5k2UeluAsKsuVLbGlJMJLiWSzYKks44no6guMpi7MhUJdM6V7SukeyuS5kUjoJ3PtUao4Kstwu9PIuRUB9ryeftBy74CDumrl+hIaGhrFQbOITzJcHi92qzmjbWa0tPCtvz7CBV/cyHmdVg4yh1lrKX7KvXSJFdyFtIDHoiQO2v02moKlIYKLXaFQDeIrcMZax2OJF4WdPX6adJ2KbZUShbCGx+4r3fR4SveOUmrD6HlPlAFkwBGkptIAOdScyud1S3b+U7miqPUcSWYNjx0UPe/VEfDqaO62ZNR+T7+DubMm9nNAQ2OyoQnxSca+zl6mJfAPT0XDjU9yxYXHcavDyFqLN61t0hV4+bLKZiMus31pZjql37Ybjs4hY0qiY5toFu58p5tLVfim472PWNiyf2A51UV4Nii5pEXFePz5T2Qdl2QZYd+20W3TJV9uKUqpGSF5gR01751UVTgT7UuW4fYhIyd7QVBcIzHOITeV5Znl4NfQ0MgvmhCfZOzt6GHp/FlZbx+QBerSKFkfSyoxnotwzIcVN5PCPeOC2+KKbSTDKxqxSoGM+pbO8cavMxGEuZpiXOn6jakgGXPN5L1b6RmycMTCwOi2uZLs3om32k824n/ricR4PL4PtmIMZDZTB+PPo9qDOqXrlei3net+0xlspVNt9FW/Do8kcOBIDPjiZ+9Puw8yMqKQqXzX0NDIJ5qP+CSjp2+QhtqqrLff5texypS5W4raYjDTPOX5INmLc4zYU3hBByURvaxQXzoBuRxvutsWW7CrKU6TiSJ579bRP4CwBHpd/kV49PuJIMKVCvykS6L7KKGA3buVniGR+vLI7yHd61DI85iqT/me0Ym9X5OJcIDbnQbOqQgwe4UrIxEeDIYw6DXbm4ZGqaH9Kico7is2jltm/fUTEYuHmP34aptPx8m12aXbi5++zkb4FVt8R8nVVaArYKU+RUVNtY91IlQxzbdlPB5/EIx6uSAifCoRaxlXyqQSL8q7nToaKtIfmBbjXCe6n1S7X9OYRVMKzIzlbb9Id0hkozWE7Tep84bH0jfopLZKC9TU0Cg1NIv4JKJv0ElNZXnW2/cMDOCUBOYYIi/M3duz8yXMJqNKoS3g8tadebVytftsSStq5vNYk5W0LwbF9MnucuporExfAE5lMhW/sb/xRPneo/Q4Rerb3inIvRCdlZgosxNRUolwgL6wwGyjhD4L75Lefgd1NZVZ9k5DQyNfaBbxCUi/w0F7QGSGYewDeV9nL63N2QVqAryyYwcrTGFEYb8I373dzswVOaQ5SIFa4nCMj2cGL/tM/MUzod1vZ0MCIZ7tMWd7jKVAvvqb6vp1Doo09nwIttz2k09BV+hAzXQss5YNrRkPppP5xw+0u6hs9GfUXiLGxQekuAcymYXJ1/Mg1T4zwePUs7vdTqa97BlwsGjOjAy30tDQyDeaEC8ASm4kMFaQhSUZnRhR1eIpf07a3r+eeorfdlrRAy1hWBGEL81zsbejhyPWLs+6n6+++SarzOFxlvB8ifFMC3gkemHlGtCVKPgvF4HkDeupObxhnJhRK8tLqmOMF1Kl4vJTaDreG2JxjbvY3ZiQpCPGE6U2HIc8DzFPMYJqC+cxrjb59A1P0Hayc977kQXJlPDrpPQNOKnVivloTBDue+IJ/vLAA3T39TFnxgy+fO65rFy0KOH6z77yCn/45z/Z29nJmsWL+c6ll1JdMTFcsTQhnkc6e3vZ9q2zGZL0DEkCQ2EBpyQwJAkMSwLD/3Li9MsMBWQEAX53TBlL61Jfkk8cdRR/vO0vXDcEDhHutMDvHEYah91UlGVv+nv56cc4qD/Lp3wGZFtBT+nlmGj9QqTMS0RQEtAJ6rhDZCsyStlPvBBEr707PA+7Pv3KgxOBdCzaalnZs7GMx+MN6zDrClOXIFHqwWyfB/l+jmTC7u129pihLLOkVqMEQyGMBu2Vr1H6PPXSS/zgpps4/5RTWL14Mf966im+eO21bLrxRhpqasatv/2dd/jqT37CZz/2Mc4/5RT+dO+9XHLNNdx5ww3odLoiHEFmaL/KPBAKh/nhTTexefN/WG4yUCHKlIsyFTqZaQaJ2qU1VJgEKlbMpcKmp8Kq58V3HHxz04fc/c3FpPLyrqmsZF0ANpvgNC94BVhilnHoRIQsU1O5r9jIYMBOBvFUaZOONTaj6nQFmjpOJ6+wEl0BG00mj+J3mRTW0UR4apLNnEgyTNVMbYlmdLIpz55MjKdzL/cELNQblX8PicglxWj8d/kU42o/ixKd593b7XSJ8G8zXDeUebuSnKV619AoAo9t2cKM5mau/NznAFi5aBFHnXsuz2/bxinHHDNu/b/961+sW7GCr11wAQBL583j+Asv5MXt21m/urRrNIAmxFUnHA7zvV//moGXn+K+Zh/muHBYy4bW0Ye3MH01nd5dWCzzWNsSwHXHLryBcEohDnCMH35UBkf5YUiEA8rL6KgfP1JMB/cVG9m93c70MmjTQYWKBkS1RXgxyFS8dPhsNJsSu/JMhiqXaqLk86vGdgNBMzUGX26dU9hPMcnkXowX42lZ0hOITqWMPEr3sJKQ3GedTWV4EK+/K+F2SqT0/Y4T4NGKnlGiBXMyLcSVyBUstl+J1ssHu7fbkYE/2+ATPqjLwlgyNOymskwr5KMxMSi325nW2Dj62Wax0NrYiN8/Ps4kGArxzMsv891LLx1dVlddzfIFC3jyhRc0IT6ZifX7jvpUT1/u4voBE90hgZ/X+TAlEOHRF0indxdbOu2sb9rFg4/vYd2KWTQsPSSt/b9hgIUhkACjDB3G6rQCNeP91bf5dAy+Z6fHCAEhIsSXqCTEU71w8/kiK+Z0crvfxpKy/qLtfyKRTPRkIniUrnen30qTqfT9w9ONR8jGmp3NNslIliIzkTW311DOHF9nwvWSPScSifHY8xUrwLd0Rp7F65tco8sTVbDMFjWeW5k+n14wwpAAx2U5rtQypmhMJE7csIFLrr6ap156iaPWraOjp4f2nh42rF07bt0Bh4NgKMSMlpYxy2c0N9PR21uoLueEJsSzwH3FRtqCAh8ERRYbJaYtd7HjDTu/6zPjkAR+UedVFOGxREU4wHPtNv712B5+8IUTAJD3/BxhxtcS7n/r4SfzcCX8ttmDAFj7zHQaqzm4sS6t/odkeNStZ405zNd7zTTYoF6CpUFYnkEK8VymrMcFWGbo/pGKdKeh1Xipxu/LE9Zj0+XXL7lU/FZzIZ3iOLnQ6bexorwvpzYKRS6uJOnETGRCOr+dTGZ0hnRWyiRv1n0Zt0xBhEefpVEiBg7XmG3kvVvTOrZ8ZU5Jtd9Ez9IBAf5uha8O739hZ1LIByIZUxprqzPaRmNq8Vy3gMlTOF++YJKZnRULFvDl887jK9dfz7rlyxlyubjuyitpqhuvcfocDgAq7GOfARVlZbyxa9e49UsRTYhniPuKjfzVaeDOQRMzQrDHLOOSQF8t82mDxPcrApgS3MtRa3isCH+yQ2DWUBdGo8iqRc2jL15p0/mK2VOcl2/k4elGVoZFDjBK/MetZ4ZBwi/oMZuMKfsf9TW8vhLOKgugDwvUSfA/brBl4UaYaxaQQqduS9QPtQhJAjph/4lUI9gtnmxEeKm5wxRiWr8vaKbGkJ0AjFLQ6o4ZDj6V7oP4ZaXiVpOP13u8CH+yY/9eNjbL48R4JqglxnMdMAdluLUhzHEOHQeMxLtmKsIhYhFfOn92Tn3R0CgUb73/Pn9/6CF+9OUvs23nTrbu3Mlzr77KYWvWYDQYxqwb/dXLcXEQsiwjTpAgIa2gTwa4r9jI7qDA3wdNXDsE33TBzX0Cz05381Srm0srx4vwdArVvLLlPT5x3IxxgZbxbiS7LjuGy7ot7AuJfK064iv1flBktlmHRQqkfRzBkd38y2nkTA8MiHBdGRQit0S6IjzVd9E/NfqhBtH2ugJWGhIEasaSrTifDJbwQiHLArocnsOlImLjyaQYVXTdYt03btGEVVInfzgwxq0Pxovwrc83jPm8pdM+znc83eua67lT45z/ZtBIjU7mpBGXlGxEOMCw20OZzZJzfzQ08k0wGOQr11/PBaeeyolHHMH3LruM+2+6if++8QbX//7349avqaoCwOkaO+h2Dg9TO/JdqaNZxBOQKPf3HxwmFgWhJmZaRSnPdrz4VrKGAxxk83BbWz+nH3Xq6LLYB7j7io0MhAWedOu5fcjKOeUBPlMWHM3J6wgLtJRX0hwYwH3FxpRljxc/ez/OI07GKsEXXfCwGawyLAnmx2qlBukI9lyDsdSi3W+jJc4vOVureNQql8kLPdl+SsUqXgiB6wnrseTgHlRqIlwNUVfoIEOAXn05dcHkaT6i96zSvZnMMh0rwqMCHCJifPWh3TzZIbCxeb+VLNOgzXT7obRupij9bh926XnRaeSHzojFLFsRHiXbjFoaGoXkg7Y2uvr62HDggaPLWhoa+MwJJ3Dbffdx9Re+MGb9mspKTEYju/ftY+XChaPLP2pv54DW4r/v0kET4gq4Lt/I+0GRtwMiw5LAKlOYhaaI8j67PMDlbj3tIrSkEOPpEPAF8fnDXPi9e7CLfuwWHXaXG7tRwFxRy2s9Id4dCLO+Rc/Nh5pZUBN3yZ5346lppqX/PYC0xPghz9xP5Ukn4xMigZlmGQ73Q6bZNlOJy1xFX65uK/EiNlMBkmr/8S91YfViOh7xsrhm77h1sz0Xk80CXigRGAnUzCxlXimSj+ufL0GuNODsNVRQF3SmtX2igWIxql0qkaof2V4rpefo0zvs3FgG3xkGK7mJcL8/gMloSL2ihkYJUDVShGfX7t0ctGzZ6PLegQFslsisjtvrxWIyIYoiep2OI9eu5YkXXuBTI6kNu/v6eHPXLi45/fTCH0AWaEI8BkmS+Onxp/CkyY4ArC4P8qRbz7dr/Cw0Scgy3OcyUCdFrMjZEuu3KDcKfOxXZ+Mc9jG8eyfDb+1m2KzHFZDxhGTOXmRiXbMB08gce/yL4ATbIH962sgBjSamzZpG6Nl9Cf3LY/nCV7/E1b/8FesC4BYilvGvD0OTQgBFtlU1E1XdG82KkWP1ynTI5gWebp+UUsO5y6qx6z/MeJ9qkI7VvZhW8UKKqU6/jRaz+tVgC0UhBmDJBHm2Obfjs6r06stZ6E1/NijV/Rn7zFjf5BoXpBklahWP0undNSZ7itqFetSygu/ebmdYgF+Vw/lumCblbgnvHXBSp1XU1JggNNTUcMwhh/DNG27gfz79aWa2tLD97be5+9FH+eLZZ9PvcHDixRdz6MqV3HDVVQCcddJJfP473+Enf/wjBy5Zwh/vuYf5s2axNkbIlzKaEI/h4o+fgsMAX3VBaxhe8BqYVx3mGGtkirsjLPCSV8c/ZrrofkOdnKyCIDCjuSoi5BZWIXs6lNdL4Fu9Vt7Kq3sM3P+ujptec3L1IY0cTOJgzygnbtjAEQcdxJ7jz2TmChcPuvT82GDkf+t82N+2qnJskFqMZ4NSWrJcpp1jSZabOFkaNGH6aoIfbUUnllY1PiWKIcYLbdHs8ltZU95T0H2qhZqW1SipUgSCutcoah1368zYMvQRV+OZESvC1USpH2qI8GgKXAm40Q4HB+CgYO4iHKB3QEtdqDGxuPbKK/nTpk3c9cgj9PT309rYyFUXXcSpxx6Ly+OhrrqaxpgMKkvnzeMXV13F7/7xDx555hkOXLKE71x6KaI4McIgNSE+ws7DT6a3HD7lhekj0ekVEvSGBQYlgRqdzGBYoF4vY1G4tulajZss88YFD8HY9Fqg/HKMD1QCMJYvZfYcJ188bhmvvOfgO/+3k5PnmrhomRlSiHHhqk/QvBwed+vpDIl8sSrAN3stfGaWn5XmMPONUsIMMJmg5AM66v+coHqlEkrnTU1SFQhJVDAkSrdTpKGiMKW8NZLjkwpXVl1NchnAJYtFSOaHrca+lTAf0Yqu04J12f59qpVBKNFzFPaL8Fj/cDVziadznhLlSk9kBY9yvzny76e96ohwiGRMWbFojiptaWgUArPJxGVnnMFlZ5wx7rsym40Hb7ll3PL1q1dPiOI9SmhCnIgIBzjCDy8bYc1ILu2PL3HR6TByTZ+ZG+q8DIYFDCPCNFt3DSXip00htQCPpuZ6Y89uWpuaEKav5kC2cue3D+RbN23jvEeHOW+JmQ33nIfhtNvG7dN9xUYGw3BVrwVRgDf8OvTI/O3j5dz/foDf9Ib4qCfEweYwl1T6mWbIvURyvKUr3k0l9ljTYdx0s0pW8Uz2H6XJMo92ZtNSvTvSlxK3iudK/IAx1Xr5JvZ8h+SxKSQLido5vaOkm68/VWBwIWdDhsMGyvRjCxPkI50njLeAR0V4svSFav9GU513JWJFuAQ8aYarh2CZSiIcoN8xRHVVOvWaNTQ0isHEsNvnkZ2Hn4wMvGKI+EkvGEm0EBXaF1QEqPt/9s47PI76XNv3zPau3ty7ccPGgKmmmRBIQgwJIb3Xk35Cykk9aSQhnSSHk0qSLznphPSEmGAcOhgMLtjGXbb6aru2zsz3x2il1Wp2d7ZIWtlzX5dsaXbKb2dnZ555532f1yTz6l4nXxi281J3GR1v8igmEnvjByfY8uVb9OXadWXzIh/oddPfD7ZGtWudMH8jzV4rd3x4E69fY+cnexPc8Icwd37mFew+eJB0Rn1zWRvGt/Y52WiXeLE7jQmF7z3fy/ImMx8638nPX+Dlny9vZNVKN+8MuklfOEdj1OWTf0HKvxAW2kd6o+HF9mE5lBt9740f5FR/grlrc26gpjkdYyZyv4WNqwu+z5kqsBtMOWi1VucfXolAq1bUFVq+XIFX6jiYCiGcJXs8CBtXM7DgLNqX+iYdB3qO02rGmC/Ca91ZM5/49u6KxpsrwgGeNUOjDFdtv7tGI1PJSBJmU7ml+AYGBtPFGR8R32OGXzkhBbw1BqszE6PdJgE+1ZLk6YRI10UdtD6pncNdC3IjvFpCUKsw6digmc2ezNiywvyNmE7sZMuNG7jqBoVdf3+Gvx5J8pdb/4tTUYkVJgkzdvanTLy3Mcl17gy2y+by3ONxPvpIioXtJrxOMz6nGZ/LgteUpMEm8K2n4nysyOPVctCKjANFo+OF9ovW0wQttAorC71eKbERCY/LDK7xyHyuCDldIuTF2tLDzLtc9M2AY0qx5jpTvS/q1ZayP2Ri7sqloOyb9ASllpHxLV3KJKtCvSK82qh4pe8hX4QDPGGFF73+1RWPRQtZlhGFMz7eZmBQ15zxQvwZCyzJwGtGitv3XfB8NSKsN85WKA1DObGTTo0WzYX+Bm0BDnBhW5SwE7L2sLliXDmxE0EQ2HDt2awfvdBEUgq7BzMkJIULOy04LONOLB/aqLBVXsBwcIRQNEEokiAcTdBva2al0IPLY0HYuAhl517Ni365FyQ9BVmFBHmlYjxLvve4XhGe/znkPvaWJEgpk1tqT9iuhiCrtTifakGmR1TOhAjP3Y+9SRcXNPTNyLaLvV5qv1TrVKI1bSqj38UQ5m9kYF8/G1usCI7ap4zlnwMqEeHVUut922OCFy+ubffLQDhKo682xgIGBgZTwxkvxG0KWCkuwnMvdOVEcvREqooVHRUS4KBebPr7oaVF+/VcIZgVAF7g4gLzCoAvfpDdiht8Fi7rFADH6BgvKziO3AhXLpVa6Wm6EuQJ5lqI8dz1VUr287mkM4p/GJqby19HLRwYpot68HLWQyBto8Fcu26OtWIqnhSUOr/kvp5fsKmngLMaRhISTsfEM2s5Nxta54dS39npEOHVCnCtaDioHY7bC53QK2TQbzimGBjUO6elEM8WX+qpOncA/iLOINVepHIvJrlR8UJR3mLiO0v2YtPXD+3t4+vIp1jXSUEjKv9Ar3usNfS2Hg+QjTT1jF/g8lI8ChXt6Y3IFRLjY+MsECHXSlUpltddzoW53PzwB3rdNAxHaWubeENQSfGo3iLIeqKS7qZThaKAAmOdZ6d8e2V+TjOZtqMlyqcKRZlYLKvnu1CsKZqefVZKhBfavp6bg+l4shBNyNit1pquc9AfZH5XW03XaWBgUFtOSyGeZe/mrUXF+N7NW5HsIJZpsFBufmNu5Cnfti9LVuBe0qlPBHY6lvNvfx+Xnd2Kw168EKdQFCnfhSW/VXRum+isS0uuh7dW1F1LkOsR49l589ES5bk3MsVy6gu910qiZaVukAYGYNOmsldbkHoS5MVEUO6xNd2uNRPGMSqmtJw66o1iYlxLFOZ+h+ohF1wPoUiGBo92N8dCwrcaJ6pi7ihQ/CaxHr5jALaMQnSktrUNg8NBzlk7tSk6BgYG1XFaC3EoLMazUfNeEyzNaC+be9HLvXhUGh3JRn8LiUuYGHGG4gIyERjGPnCK7H1EudZ/WfRE4bPz5V/wJuVbFxASoC86nr9MLrm5tnrSVQqh1RCoWkbi4KpdH6QxZlqQFxSMBY61asR4Ocev5lOejavp3XGKTlusou3XC1qfea0F+FTnkPcPpWhvmRjdzT82Ki3YLPb0MP87XYsbw+nKs29xmojEanvsxuIJXA57TddpYGBQW057IQ6TxXhWhAP0iXCJjr4fkqzUxOuxkGMIMClSnpuCMTb/6OvxFDisds3XsssWQkuwZlNS9FLMw7tQxKvc/Hqt5WGy/3glYjz7HmqBIisTUiGqTU/RolhUulYifSZSJvQcp4XSrrT2a1/LIha3S3Csvrtq6klRmY6bsKmKsPc9d4RFayc3kalGjOceK3qCB/WQKlUOToWaC3EDA4P6Z9YJ8cOvew/JHOGst/tYrvjOxYTaSKEY4aTMNbc8SJdbZE0mycu9AgstChkF/nvIzpG0yLAsIClwtSvDLY3JojmqhSK/hWz8tOh+5CRz0naUnf0TlhlbVxmOIGqUe/TCltMYQ8uJIMtU24JpoZXiA0zKuZ9u4mGZpqYZ23xFFonViO5S+1rvzUepTqaFpufe5MDE70l/SOSi5amS264FtT6+C+XazwYLzMnWhSKbmgvnO+eeH0qJ8dx1ax0jWrnhekV4Pe1PR42F+Eg8gdNuRMNnFGVmGosZzC4qFuI7Hn8cp8PB2uXLsdW4wKQcikW79dAsw36L6h+e1c7ZoqH49m4yCjx3Vgdeq8BH7VF2Jky8s9/J9e40Vzgz3B83cZUzw9sbUlgF+PCgnT/FzLzYXSDfJY9C7d9z0YqMdSfnsMIZnLSMHkGee8HKXtiyF7NLOiePUUt0V5JzWatHvLkpPvlivNyouB5KRd9GAjJLNfbbTFDoBqhW0e5a3PAUE+D6ipUnpmvlri/9wD6sZqBK8TrVTwey69fan0WLrGeJy04yI2C3VddEZkJqYIHjrlIRXs5+m6puoPmkUVt714rB4RCtTb6arc+gfOLJ6QkKGMxuKhLigXCYL37/+6TSaeKJBA1eL2+56Sa2btnCcChEk2/qvvxLfnI7yVe/Z8K0rBjXI8Kzoj077wsT8G0XHDXBdYnRx4MC/PaAmxMNGZ5NmRBPRogqAh9L2fn9nBGe78rwxaMu/ma28tKGFH5J4JZBO7e1JvhIU5L3DDi42CHx16iZv/ptXJSC6xPq9gsVJOktWMzSl3RyWePk5kLFBLnWxaxUZFs5sROF6i9stb6QaYnxYmjlt+tBjzAcCci0n132qqeMqRKRekV4MSFUSIRn97OeFKltPZ6cpzXjjj4t5qWYPY0I81dNGMdM59kXIr9rbpb8iD8Ud/wYm6fA+5vu9y8r470NQOP9ZfscaETFJ9kVFjmWyxXh9fD5F7IuBIgL1DSCbVgXzjyhUOUFyAZnDhUJ8af372fVkiV85cMfBuDA0aMMDg/zl+3b+d0993D01Cm2XHgh73/d63A6HKTTaX7xl78giCLXX3EFPo+nqkFrie5yRHjuOuZK8Lkw/NkOv3NAUlAfES7LwJVDZj53VhSPAEOSQFwZP5G+G7UZ0I+x0u6UsAnwWb+dO9rjXO9O8+puF80yvHYEvuOGNWlYLI0vX0qQa5G9WClAumkeqQMnxqbnoyXIy82ZrMWFazoiSYVsIbNkRV6u77ce9BaxeknjchV+fSbdREoxnSk9WiI8V4DnOvYArH6kh70XdGmvLCeFKptWtVQ8hNMHvfHIpEh5MavN6SY/1WJyo6jJufF6LCLzn4bki9ipaiiVv95AVKCpU7XMK+fpVKF8da0bFr0ivFaf9XRExU8mJdoqaUZQgMHhIAvnrazZ+gzKJxgxhLhBaSoS4g899RThaJRT/f3MaW9nxaJFeN1utj38MF/4wAcIhEJ8/n//lz/ddx83X3cd2x9/nH6/H4/LxS//+lfedvPNtX4fk9CTO547T6mAppYkWw28NJPh3088wW/+/ncWzp2L681v5l3pNPOvuYllGXUHX5OA+2ywuIAzlaxAcvQnoQijvwukRv9PjL5m/WsPG+yQsrhokMZzCcuJpk9Hd8fcMdUjegS5Xj93SYJ/5FXxTnVHv2qZiXx6vSJ89SMTn/Lk/51lJ6pAz7XYfOSwDYtdABKTCj31FBOXQ6XL56ak5IvwYlahY8uXEOTlPg2ZilqO/pCJNqEHaCmYKqbn5rTUe6kkJ7waqhXjxaLhCSDsEFk8r3bFs8PBCI2+6oJeBtURCBtC3KA0FQlxr9tNU0MDt3zpSwB89n3vY+n8+bzm+uvJSBLtzc00NzTw7OHDAJzo6eHSc8/FYbPxl/vvB+CHv/0tB48d4/Pvfz9mU3W5hPnoLeCsBRazmSsvuIArL7hgbJrVYuGl/7qb2Hu2cGyXm4uT8FEfXJaEw2bY2SjRd8pJUlZFdwawCdkfRfN/14ZLiYyM8N/P7OLs9g7WSCHSClgE6M0IfGXYRuddA8w3y8y3yCywyCy8ag6iMPFRf7GLbj2L52JUmoqh1bJebxQ8K+KHh5nRQs1y0RLhWkJpKm8mcreXm4pSSHTrYVuPwPKgTMdKbe/qWlKNcC2USjXeSEuYUCRdiFo+ZalUjBf63vWHRJZ3Fq+R0SvCS6XvFFtXOR08i1FpZ+VyOG6G+QhYzLXzT5AVGZNYC68vg0oJGRFxAx1U9K2/+dpraR1VH+/9/Of59d/+xgfe8AasFsuYqD50/Div3boVgNamJr7w3e+yaO5cXnbttQCc7Ovjngcf5HVbt7JqqWpz9aPf/Q5JknjLy15W8RuaThFeCtft21j4ni0sBN4csfAFk5XNjgxvcmVYbJGxiarItjIxp1JrPVniiQQ/+vQn2HvqOK8ZcXJrSwKroLA7aeJCR4rjaYEHExa60yLBnwWYa1ZF+TyzwgKLPCbUXSXOz7nRm2oabUwVxWzX8qNwegV2OV1NswwMQltO47p6jobrdSnJfU3v+yknLxwm7uv8lJRKSceV0Yh4/VBpI57cmoZ8q9CpoJgYL/dGdyAscvGKcS+qQlHxUkJ5qkV4OVaq1YrxYtFwUGuUFumr79eFJBkivB7IpHV4Ixuc8VQkxFubmpBlGUEQuGjDBn72xz9ie9vbAJBlmR/+7ne4XS5edOWVALzoiiuY36U+Sl67bBnJVIpILEZbUxN9Q0NjQvzv//43F59zTsVvpp5EeBbX7duIvWcLN3nS3OBOYy5TJ+SKcACH3Y7nvKu5LXYb91jMvHvAzg874mSAa13pCQI7LkN3RuR4WuREWuShuIlfpC10Z0RcosJ8s8wCi/q/rdtGlwQtMpP80ou1nq4niqVc5AtovZHvQstnGRiA885Vf58tIjxf2GjtC70isFwBXkz8F8wHL8DGnDzxqzpljhyDS7vGU7YKCbZqI9rVkl1H5/yNXNKppqds6VImRMNzj7fpOq5qVeSblgSs5so9/ouNY7pFeCFqERl/7IHI2O/HrvGwvIZC3B8M09zord0KDQwMpoyyhHggHOav99/P5eefz5z2djKSxHAoNFZg0j80xN333su9Dz/Mlz/4QRw2G4qiIAgC61eOF42cGhjgRG8v7371q7l72zY2n3ceZpOJk319uoV4PYruQuSL6WpQIx0C7tu3cc17tnAsLfLTsJUFZpnjaZFVNpkRGf4QtfBST5rlVpnl1vHo1LFdbmQgIApIy5KcyIjs6bXRa4fnzKqn+vkp+I867iuR3/F0qimWSx6LwbLW0s4z9YTWEwMov5i1XBGeu+3cpxQbJxRearPzwfZJ8+WmcKx1xlDaxrdRaJx6hbReN55i5Aq1Qo28smJcZbKzTyERXs4xNZ3FwpLMhB4K+WI8O60cssdMLQozq+2KnEst01SOmtRaolox6A/S2tRQuxUalM1IIonNNvWpcgazn7KEeKPXS3RkhB/85jdcc+mlPL57N488/TTvfOUr6RkY4Bs/+QmiKPL1//qvMaGeTVWRZRlx9FHZs4cP0+Tzsenss/nWz36GSRQ51d9PKpNh6fz5tX+XpxF9g8N0tKo3Pq7bt7H+Ldfw/ZAVvySQfSr/p6iFH4SsPJEw8dYeM/nOtCKqfzoHHLQBKSscNKtuMZcm4fLkNL6hMpmqToBalBKkbbZlOC19BV+vJwGe7yijFaEsx96xEhGuRVZM59sW5k/feHH/pNzp3PEePgxLuzrodHgLjq/caHa+GK82Gl5MjIO2W8rYvBUeS9nPYrrEuD8q0uyZ2CKtnOZihSgmwqcjAp5dR63EeG40PGYTGDTB3BpmMQwOB1myoLwnTAa1xR8I0eA1imUNSlN2asoLL7+cP2/fzjd/8hM629r44n/+J3/evp13ffazvPKFL+SWN75xfOU5RZhiTr7a7oMHWTJ/Pq1NTZy1ZAnbHn4YAehsaaHBazxOK0Z37wDzusaTkl3vuo1nP/UprnelWWyVySjwc7+ND8fgXpuZL3rgvVFoKFL/tcOmHgi3B9VOo/nMZFpKMeFdTcSyVN54IVGaKwj6BpO05XUPrCfxXYrse6llA6RyxFbuZ1CoQLGY+Ibx97A35GfxMlvNLeymojtsoeZdnXn7rtpjKf+z0GOBWC19T56iTRFRdg6p26zCPrVW1LK4Uivnv5QYL5YfrgD/Wmfj+QmoZex0wB/kgg2rarhGg3LxB8I0eMtLgTQ4MylbiM9pb+dtN988wYJwQVcXL77qKh7YuZM//utftDQ08LJrr+Ul11yjWQW+/8gRbnr+8wFwOhz0Dgxwsr+f9WedVcVbOTPo7hlg3VlLxv5ub2mhxSTzH41qGPu+ETOtMizPwNIM/MoBt/igTVa9zOdI4FbUH4+s/v/6GHzKCzEBvNPYkXcqo9t6clLLbfCTH6k82ZdkTvv484Z6F+GFIpNanVbzp+evo9Q2shRrIpVNUSkXrXH1n+jnsq5jE+4kZ9ovXC+5Pvh654fSN6KFfPX1kr+snvENpJyscg+PL6Pha647PUhj/OV+x6bKCarSItx8DswxE3KJ3BCvxajGSaZS2G0z1/HaICvEizSYMDAYpSZeSddddhnXXXYZANGREXY9+yyJZFJThIciEfr9fs5Zpd6t37BlC3/evp2Hd+2aEE030CaeTOG0j4u/1i+9jj/MUX9XFPhxv52XjOYaisAr4nBTHI6YYY8ZnrWonUOjIkQF9WdEAFlQGxq9QcPrfCqKNau5gOmNhNey3b2W+DvVn+DyTU11L8DzKSaWa5GTrGc5Yf7GqooQ89crKw7MoyK8XgR4Ocd4JWPW1SMgT8xWc6zqSW8ZTDlotWiryoreY87NYzlPO6bLilXPdhauj06Kip9/iYe/PBNjxxobH0uIWKhd3ZOiTGM0xaAg/mCIrnYj1dagNLUzLR3F7XRyycbCUZjewUFEQRizPzxn1So+efvtpDMZVixaVHL9zx09SWtjMz7PmXenmUimsI8Wfxw9eZIdn3gLL3CBYzTr58mkiZQA69MTlzOjRsgLVeXLqNFw2yw4f5ebjlILMV4oMhwecOAZ7ob6cswrm5m4kajlNuOP7ccWWoiy83DN1jkbKVRgWst9XUqMZxQBs1j7E0k572E29EMICvCn8x1ctjvJosWOmpoPREfieFzOmq3PoDJSqQwWq1GsaVCamgvxUqxcvJjffetbY3/LisLzLr6Y391zj672vpIksf2RpwhFRrBazMztaGX+nHa62ptr3hio3ujuHWBuRyvJVIr3ve8/OJ6xsdoqcZZNLY76v7CF6xKT7QdLIQKeEtfOWkbFS0UKK839LvQovlDkVY9ALyTCJVn1fi/m/14P6IlCTofzTK3Qej99KQ8dtgJta08jCgnM/JzzWn2ehb5PhcR4RgKzUL0Ir+V7qEdSwNc8cHVK5CU1FuFgOKYYGMw2pl2Iw8QiTovZzPtf/3recOONOGz5/h6TWbl0wZizSiqVprtvkMPHT/HA48+QkWSaGjws6Gpn/pz20y5q3t0zwLJFc/nWm7fSYRbplwSWjFoTHkmJHEyJ3LoySu/TU1sgkn3MWokwnyoRXgnFihVLpU0MhkVa89wh6o1yrPq0qFX785oJwwJj6U266LDVsd9mDSgW5c3PV9abQ66HcsT4YESkxToxLUVr3PV0DphuZOC7LmiT4MbE1NjwDg4HaW1uqPl6DfSTSKawGdFwA53MiBDXohK3FKvVwpL5XSyZr9o0KYrCcDDCiZ7+CVHzOR0tzO9qZ057C2bz7I2a9w4M4/rJR/lL1Mp/NiUJywJWQRXG33fBlRLYpjBCm5/nmP93tRHzqRQOxSgnVzkrPk4FTMxpqt+uabVsPDMV69FMoahweyePKSwPP0dcTk2rvWUulRy7tbbd0xLkUylq88V4f0ikY2UzDJ4sOc5Cn1O5463VzeJ0cZcDhkzwsTCsmaJeGAP+ICsWG7nJM4k/YDRUMtBP3QjxWiAIAs2NXpobvWxYvQyAVDrDyb5Bjp3s5cEndpORZBp9buZ3tbNgNGou1Ht+AepNRmLXDr44bOEVYRHPsINuL+x92o0ZeMwK3wgWFselWizXglLpK+WKpGodE6aSU8Mim1emZnoYs5ZckVipkMoKz5GmeTjl1IRpMD2e8/nCUc9N4FgBYon3X4vmM7UQ43pvbvtDJjYsSMNgeWOsNbVstFPsvFlO4GHh+ig/3+fmASt8OgwbprAhXTAcxXuaPQ2ebfgDIZobfTM9DINZwmklxLWwWswsntfJ4nmdgCpoA+EoJ0718+/HniEQjmI2ieNR845WrJb62i2SJLHt3S9hn3Mlc8wKrzwryvGn3Vyagg/5YH0KTMrEPO/8i4RW5X4+euaZLsrJTc2nWtu2YuvNEo6L+Jz1Wd06lRHCYgJnJqLRMgIiM/M55Arc/OOtWP1BZ56f91REdXOj43rFuJbV4NhrOlJU/JHJzXxmM6XOheXUzdyzx83P3PDRCFx0/901GF1xxFkQXDqd8QfDLFs0l0Sqxr6UBqcl9aU4pwFBEGjyeWjyeVi/aikA6UyGnn4/J07188hT+0hnMnjdLuZ3tTG/q53mRm9No+Z9g4P0Dg2VnC82MsL9jz/Otnv+ysKWDtak/LyyOYEgqKL546i54Y8kTKxUYOHCdNH16bloVBNBrzYaPiFKWqWY1uNnXen6ZFk1SqnkkKhl/m4tmarOg/love9qIuN+s5umzOTjbqpvCrREuF53nmy79lwRqyXGs++h1GeT+13N/w5mP5NyI+Na85cS47ICJpEZui2aSLVRcb3nPz1ivCcj8E03vC0Gz7/v7orHpId0OqNpG2wwvQwFQlx4zmpO9htC3KA0xjcWtWB0wRw1VSVLKBKju2eAx55+Fn8wjCgItLc2Mb+rnXmdrTjspQtLAWRZ5kh3N089+6z6s28fiVSKeR0dJcW9xWzmQsthfvziBvYkujjf10+zdVxgxLd3s9gqs9g6MQqlJULKvSjVMqVlpvJ2c6lUmGtF4AcjIq3e8iN/uUKrXgR5ra3eqsn/LTcy7Lh8Hv2PQns6OGn6VKJHhOvt2povxmHyDUkxUVmobiNXHOoR41r7vRzxnsqAxVSeBK9Fekqx46WWKSrFKFa8PiwJvO+Ei+uT8Kp7757ysQwFQrQYKREzTjKZNhoqGejGEOIF8Hlc+FYsYs0K1dtckmT6hoY5caqfXfsOkUimcNitzO9qI/WxL9AQjSKONlLIAE9Y4cnWDM8kTXhFhXU2ibNtEm++tI0FXhHx3FadI1Ev9DsecNB8gRtBGL/46G3/ruzcqzu6lk/uxWU60lamy7qsUJfJ3NcKcWq4doWapYTnVO6Lqew6mH9s6n0f5YrxfksDZ48cG/t7Om/68kV4MfGdywO9bi7pPDhWJJyfcqUlyLVEZbHvY36ktlaR8UJR8cGwSFsFN6eltldq3lJMlxiHyZ9Hrwi3eeBFzUne9eO/TssYBv2GY4qBwWzDEOI6MZlE5rS3MKe9hQtHp8VG4vzhte/m8NwOEm43ICDFYzyXDNCQHOYFtgQfakrSMhopyoqEcsWVJIPoakRcsEq9EBZ5lF9q3cWESqkLVqWuKKXWW2hM+WJ5Koo1K1nnqYDIpSvKK9SsNAd4KiPn0yVSKnHCAH37LNzZxpyOIKLQUMnQqiJflF7SGdUU49t6Jj752tKlng+yKSqgXf9Q6qak0pqOSeK6xH7WI8b7QybafOUJ8YLf+xof89MpxgH6Rdhhg3/Z4OYReOdP/jZt2x4YDrJq2cJp257BZFKpNJY6qzMzqG+Mo6UKXvOyVxASYM2JIRpkaGhPIdpcXNjoI+1YTMhk59+KREc6wOLVZrrkGFZx4sWqWAFi9mI3MJCkvSWqXrhzRGmtxVktUlqmgnpySwEIjUx/oeZUPSmYCpFSq6i0rgLDBxyYzp0a68Biy+aOLbd7ayExno8aFS/vxlbrsyr0xErrplnLTaUcr/l8MZ5Lf8jGeUvSutent2YEamN1OV1ifJ8ZbnfDJSn4rwhcO8U54fn4jdSUGWcoaFgXGpSHIcQrZO/mrcR98KEIzJVzL3wpSAUgdQyAtGCi19JId2Ixj4baSXsb8DyhMH/5POZ12mlRFEStaFhOxGnP8eN4miY+0i4WJdbrLqKH3AvmdKUy1HNnvUoKNWvpx11qv1SyrUrTlmYSYf5GoiMZXE1+hPntJefXijZPeL3M/TYmZEejw+WI8W09gmZUvFryxbeWMM8X47ViOCbS5JoYZNDTCVQPtbC6zG5X7zFeydOGA2b4lhveE4VVmalp1lOKdFqqO9evMw3jZsigXIxvrE72bt469rsCDImqZWBAVIV4oep5iyKx4iIHK+gFVAEQjgt0+4+y86iJoUwTQjxIq9fGvGaJec0SnuXnjC3fGz9Ifz/43S7MjItxYIIgL0QtcpC1ctJnk2irJUMRkZYa5MJWSi2jhPnUKmo4lR7Rucf73u4jOBuhNx4quozW96SQMJ/q5jA7H2xn48X9mq/V8gZaq4hTS4yXQ9FjTwHhqeJFptUcE9V6zZdLuSJ8UIRvuuEdMyjCFaUe/GoM/IHwWJNBAwM9GEJcB3s3b+W4Cf5hh0MmGDSBXYG1aZhTZs2esnMv3o2rWT03w+q5GaAXWYaBsEi338Q9z9iIPb4Pq6+JOe02nM0wMgJNNmEskpZ9rJ2NwNUqoqbbSSSn+LMQ5V4AZ0tU/FTAxJzGme+omS+KZlN3wVrQGz/I0BB0dIxP04pC535PshQT5nr3p1bOdLlRcRj/HtfqO1yMWohxmPzdTKTBZi4uAmfCOWm6ggVp1HSUFyRg3QyJcFCdvnxGI58Zxx8Ic/7ZK2d6GAazCEOIlyAbCb/dDeel4F0JaJXAoTGv3gYP+Rd5AWgf/TnXBMKlq0l1tHGqL8EzR+HUgEjgoQQOSWDHgInzFov8W1E7glYjyLMX01xRUkq0FMpNL8dybTZzaljk4jILNaeSWgvwqYiKT9VN1ZAfVq9Rf88VvbmpH/liuJQw1yPIi72XXDFeiNyoeLFc8am4ucoX41kqSRcBdV8MhEy0RXqhafJ8M2VdOp3nnv/nhGYZrkvMnAgHwzGlXognkjgd9pkehsEswhDiOeSmn+SzMAP32sACvKRMj/5Kok/WvqdYPH8jQ0mw2WSibU6OHVMwR2R27s3QiQwKnPJYcTWLXLEyQS/lR9ZKW7D1jAkFLVE+th6NnNvTUYwHR0QaihRqnmmR6WJo5SOX8rEuR7CnUmCzjh+zue4k+U4lwNjTpFzyhXmprpcFx6+jAdXOByfmsmvlihdLT6ll23atxj+56D1fKTv30h9qo91WPzen1VJOWsrDVthngc+EYM0MinBQHVM6WjXuhgwMDOoaQ4iPUkyEA7w7BsOC2lL+eYmJ7eRzKRUVz209rYeR4Rba24eIKqBYRdLNIulmM0eBqzplEhGF2LDEH7Zb8JLGZDrIkq4W5prUFIpCLQVyBUWuCNcSMKBemLK56VA4Pz1fRFQjxustPUUe/cyLFWqWO956Eu7V5tOWcuqA8q3yJr0+KnhbLUsxmQ4B42kgWVGbewznTtOyEcwV5rlpIlqNdopRbudWvVHxqaKW56n+lIMlzmCthjbj6C3UTAA/d8J7I3DeDItwgKHhIOtWLJ7pYZzRpNMZzGbTTA/DYJZhCHHGRbgCPGFRc8HnS3BOClZn1NQRgHPOjrLuOTdPWOGKZPnbyRU6eqPkPf1JlqyCTnOUrCAeR8DhFXB4RVgIl3SmyWRADjvo7l3AEzt7SA4ux2GSmGuLMtcepcM2gklQxUmueMiPFE6I3o0Vl+WKlsmP3ydFzMvskqhFPYnxoYhIi6e2hZrl+DlPJbWIthayzyv35rMUyomdDNjWML+tmU5HM73xg2NCNleQ57KlS5kkxHMj0tllC4nxYmildhXLD1/9SA97L+hSv2MX90+Jg4oe9KTS6TlPBdM2GsynT0RcL39xwMo0LJv5khEAwtER3C6tpEmD6cIfDNPcYFgXGpTHGS/E927eSkSAf482YDAr8OKEWgX/ExesS6tNGZaPXrAu70ywK2FiYUuyrEeYWkJHz0UuIymYRz8lPR7FZjN0znGwYI4Dpe0Iys6DjEhmTiZc7I81cn+gC9nno/FJmXnRCLbGXnyjTkvbeoQJAnyCYIAcQQ75NwUFH/Hr6OpZah/UgxhXdu7lVLiFLkEGOqdkG+V2lawHCn0HCrVaz6UaYd6z/wCdXWr0LytecwV5PlmBXkqM51NKjBerr8iuH8ZvbFc/0jPh/510jX6vxqPi2W3W8nh47IHI2O/nX+IZ+71aMR7f3o3UNI/Ewcnf7enID6/lMQXQlxF4OG5i3aoRTPucRed92Arvmt4HGSURyvFVNag5/oDhIW5QPmekEN+7eSsKcNAM97rgKQtsSMNbYrA8JwJ+aRK+5IF3N8B7o2auc2c4xybxv0EbzybTmgWbtSS4/0l87rmaQkNvO21h42qcO/ey3BVixea5AChKnFDDOrp7E+zeA0f6zSAksAsiLcQIY2PZIwPAuGCAUdEAbLy4f0xgaBXF5QoKmGh/WE0u6kyL8VNJFxc29FW8fKH0hVLtzWczxYReIYGn57PuDYhc3HoQGLf6LFYoOS7QJ+eTa65fR3S60OeplbOuh9w+AVC7YyBXhGf/zhfjWcrtnhsXrNjlmYmGFwpuVIJfEvhmwMoTCTMhWeCWxgQ3FElRSQB+EebWSTQ8mUxhs1pmehhnPP5AiAVzO0rPaGCQwxkpxMMCfMMNYRGuTMJrRrRzvhsV+GIYHl+S5JGEievcGeZaFP6rKcEtg3Z+sTbK8O6JJ2qtC1mlUZpuv4m51j6UE91j9mhQuSAf+12ARp+FRp+F1gW9XEqGf/e4OH5IYZktQOCQDdMFIjICEayEsRFGrQLP5rVqRRH15LlOdZSs3Fxdvb7NwsbVBB9w0LSpPH9hPePRas403dHxqeyqWk4OOejLyQ6OiDS4lElFkoXEc76tYLEoeLH1FKKYU0p+NDyX1Y/0sJMuttzUV/L7U2m9xfmXeCaJ8ULodX7KMmjx0poOa742VX7ytS4Azyjwlj4Hz3NluLNjhNf2OtniyhR94nnKBF2SegGdSaeULIPDIVqbGmZ6GGc8/mCYc9ZOX3qZwenBGSfET/T28t9e2JSCm+IgFpl3RIADixP8JGTl0y3jSeGXOiW+G1Lok0SWV9CBTS/dfhPnLk4DOS4OOYIcxnO1iwlyXcVmgsCVywS29ZhwtcuAALKCMxZnTjSKKSojSAqdpwScjSIxv4ijQWTz3FjpddcoylssUqpXgOdHOgu5wOSjp1Cz3LFoLVdP0XE9HTfL6UBYSJCXK9iUMj6LLIXSV2pdKFlpNDxLqRsAvWI8/3OZKjE+aPbRmincUKmWYnyqHJgiMgRkgZVWiScSJhpNCiNy8c9vwARtcn2IcIDBYcO6sB6IjSRwGdaFBmVyxgnxT3/721yZhBcm4DmzGh1vltUfAThkVlNWDpnhqAk2JUx8oDGJANwbM7PIIhORISgJLDCrhXvZi16touFZ4eWPn0tzXnFgriCH8cfxWmJCT7FZ7vKTnCdEAcljQvKoVeBbuhQyKYXFYoz+fhjaA39+GpxOaG+H9jZoagKxwN1NUTeMKsSmlvAtFqGckMuuIcq19plfR6FmKQGuNaZ84aX1mdVCkJe6GSu2bj2CvBzKEXpaN0rhuIDXIU+anruM1meYfxNb6HuTO0+1nS6LRcOz5HfaLLXNYucUvZ9RfnpKpQxYvCxPnKp6PaWYShvURhN8uTXBV4ZtPM+V5jJnhteedNHpUZ+UehTwyOr/jbLaTyIowJIbXjBlYyqXQX+Q9auWzvQwDDDy9A3K54wT4oqi8IAVdlqgx6SeXBOCGv2WUU+0DgWsDgmfLPBA3MzulIkus0KDqHAkLZJU4H2NKWw5grOcx7l6GuLIChAMIzx5kNyH6GOirIhvcTnuC4UEa25hW+5j/MsXqBHwTcvH1x+JZujuS3DyWJJnnkwhywqNvkHmdtiZo4g0u+WS0ctS7iF6ovqlGqkU85AuFSU/FRAndNQsJwKv53U9NwSVpKvozauvpklT9tiv5slQrrNKrqe4lijtDZrobCh8U1RIyGrdxBajlCDO/Q4Wy08vJsL3XtDFh7vUtJQJNwAV3nTlfkblPK3IJ/9mqVBkOyQ6cMuJirZRT5xrl/haW5y39jn4cmuCS45b6TFBRICIqP4fEmCPDf5oV2uJVjc2zvSwx/AHwzQZRYIzSiYjGdaFBhVxxgnxr3zoQ3T39bHnnR/hyx7wSLAmDVEBTEC7BGd1Jeg0K3SaZTrMCg1XVB+ByqJH8AAMpJy0WcvsHJRDrgVbsXmKkZ9Hm9vYJxeP28yqpW5WLVUv+oqiEAhlONmX4PG+efifVgs/W+e2MbfDztwOGz6Pmb7Ec5rRx3KKMvMbEmUplKqTe3ORnWeS44uGKO45PMgFGxoQGvQVRJXat4Xmz992NWK8kv1YKjWmWHRcryAv5V+d3wQon57hOSxzBlGCE9Oi9L7fCe9Rhxe+1lgK3RDrcTYCVYCDdjRc631r7e9q8/pLRcVLiXFFgX/HzYhhCy/zpnVvt9aUm9deiC6zwut9aX4etvJmBVZkxl/LpqDE3rOFz/lt/C1m4aal9ROBliQZs8kQgTPJcDBMk6/6p0xnOk/s2cObP/5xzde62tr46/e+N2n6/Y89xntvvXXS9P/51Ke4aMOGmo+x1pxxQrypoYGmhgbOvvduDl6zlT844J1RWDQa7Mw9oetJK6n2sX0hsdGdcDPPNjmnsxz3kGKR8XKEYu7j+zFHhxLRwkagaeVG1q30AC3IisLQcJo9J46x+yE4PmRGEM3Yvcc4b3GK9nZYojNfO0vprqCFc3ULCfLc9eW+3+FQmibfxK9LuWJbD/mCvNJCzkpz6fNfz9rogbYgh8nHfiFBrlcslfId7086uaShd9L0Sm5Q9BxnWuvN/R5mxXhuVFzLKhEmC/AtXcpYNDx/LKXOKfnCOH9+PdHwasR4VLKQSqf4ZtDGSz1pxAJPvWqRJ14qN74cMV5sn13rSvODkJWbBPCNxiFy88Bdt2/jlW9/Hn+LWTh7xQr9b2AKkWXZSIeoA4aCYZobfTM9jFnPysWLufMLX5gwLZ1Oc8ttt7H1qqs0lwnHYtitVu749KcnTF8yb+otVGvBGSfEc/HKauv6BRoWVNmTtR7Rq8crW2uZYnQn3Dyv+YSudRWjlmKxmmYj/YnnwAl+n5vtMUF1kZMVTHEZa6+A51iSf40cxGSCRZ0tzO04izkdNpz24lEeLRGuJYDy24vDZBvGfEGeXb+igIAHQRAq2p+VFARqFZXqLeSsRIQXyl/PvREotM1SKSuVUui7lGyaR+bAcTJ508uxwtQif7/p6QKaXS43Mp4fFc+K7yzFRHh2nXrPI1mRO5U51IXEePdjUaxJtTDteEZgkaW4E001FHp/5abe5B8j+fvOJcL8pMBRM6xPaxdjrv3fe/jzO7fgdNRH85xAKEqjb2oMAwz04w+EmNfZNtPDmPW4nU42nHXWhGl33nUXzQ0NvOHGGzWXCUUitDQ2TlputnDGCvG9m7eyzw2t8kTnlOxFp1bV/uW2+M4yIllwm/OlxmSxMBVR2XzyOw5Cec4guWI5VyTvfLiDjRf3swsTWxZZsAEXtEYZGhpiKNDG089GiCckLBaRrjYbcztsdLXbsNvKfwS78eJ+TTGeJbexS75wDobA5o7QG9fnOpElV4xp+ayXopQYh8nR8VqJ8Pzta7V8z4+QT6UYzJISTFgUbfPmcrZfyL+8EMXOB9nouHJiJ53zN06IipN33G3M6aSZK8Jzt13uftQ7v5Zzit6CTS0xPuhaykg8QrtJZiAjsshSW1PtUu+rkvz3Uk8RAOZIcNKkCvG9m7dqivG539lW9ranCsMxpT7wB8JsWLVspodx2jEUCPD9X/+ar37kI1gs2qmh4WiUpoaG6R1YDTkjhXi2pX2bDKViOHpSQUqlCuht8Z2dT9y8AKs4+aI2wQs854KvVYRYC7TEaSWFoPmWbrnCJLdr55YuhUcGR0VwxwALV6pR2VRKpmcgycm+BE/sDpNMy9gsoirKG6GtdeJ2C6UFlBLjhRgYgDaNQIdeD3et5SoV48WYioZHhcR47vaKNWyqNQNmH23pwnZ5etGbc507b+4y+fPmnic6Hcu5pPPghOMj339fS4TrjfrqedKgR6SW65qSbz85aPERGzlMl1lmQCqeGlFuYGMqj6NiYzmwy81OH7wzp/wgV4wPh0IcPHaMC84+e8rGVy6D/iDzu4xI7EwTG4njchrWhbXmrnvuoaOlhQvXry84TzgaZXB4mBve9S5O9fezeN483vnKV3LpuedO30Cr4IwU4qBaE95ng68GS8+rJcb1WAPmo/ficirhpstWuBCtmAgvNK1ccZ4VsvmpG/mFjaXIFeGFrNz2XtClvjZWuDaxiLLTsZyFcx0snDv+KDiZlDk1kOTZE7BnD/RFEpgsqse5s1HkyjaRfw1M9lHML44rNu7sPhsYgLVrJ7+naqjUv7qYvWGxZYpRzPFD7/arFeN6o5sH57fjisc5Nlh4fj1uIYWaC+ml0M21lptRfioKoEuEF3oPxRok6aFa28JsdDwm2hhMpdnsViPitULP51Bt74ZC2zhhUhu9/dsKFgUWj8ZD9m7eyrJ7f8OVr3sdALvuvruq7deSweGg0USmDlCU2W1duPvxVgTb9KU4STrOGbIs8/tt23jVi15UdL7F8+ZxoreXl117LaIg8JO77+Z9t97Kz778Zc5asqRWQ54yzlghbkFtT/xhnxoZX5SB5yegS9aXnpKf0wnjJ/dqL5QnE24WOLS71eVe5PUIwkJiTyvKmtscKD+qnI2OlyMg8yPh2Yh0fs5s9jWYGDEshs0msnieA0dLdlt2MimFkaBMdEhi8FCaRRKYrALOBpG9kgnJKYKp/BNlKAw+78T3dLpRSIxXUxegh3IFVcDrZV5/8ZspPeuspq17LvkuL7k3Reox7J7wZAnQLMyshEIFisXefy28wwGO7nIT3WgGBeaYZfanSqeLlYqK670RKnaDUs1neWyXm2XAN4Jwvw2+6YaLU/CyuPrk9KNf/zoAt77//RVvYyqIxY0mMjNNRpIwmWp3M2qg8vSBA/QODnLFpk1F53vZtdfysmuvHfv73DVreMHb387//fnPfPa9753qYVbNGSvE50rw32Fou/tHPPTSN/KMGT7hg/8JgC1nvuzFQysqrhXNyr1IVCLIHZfPo6fXxYUNfWPTststZNWXTzERmy+stLyQi7UBL1eE55ObHpIbnc7dViGbxFKYrQLeNhPetnFRkEkpjARkzgpkOHpYAVlBMQtk3CYkl4jkEsnaPeQLJhjt4qiU18VxtpLf7EZr/9dCQELlEc2E1YYjmarJGLTGUomQm1QHopUrzuTvTrmFmVrkis+p6vCrRdxmwx1P0JERSCoCjydMhCXwltDjhcR4/j5QCnznpuo95q63QYEXJ+DSJHzEB9cl4F822PbQQ1yxaRPXXXbZlIzBYPYSCEVoNKwLa87T+/fj83iY015eSqnT4eDsFSs4dmrqm43VgjNWiAOsGc372/qvu1m2eSvbbepjydYiDRT/+dQQ37v7IO0ukc9c7ML+iPpBF7tAaL1W7IKfUUQsojoIvSK8HPENEwVV7u+dY84PB4tGf3NbhpdLIQGubrcyEV4Is1XA227C225ij1e9sgtpBVNMwhKSGHnGRFNzfEycx+wCDp+IOBo5D4XANwWOVNXk8ZeTFlVOUW0u9SbCF66PcnSXm9JVHdVR7nc1SyGBmb2pzU9JqSVTJU6LWRsGPR4aohE2puFwr43L21J8cNDBra0Jmk3FP6NSBZO/DFvYnTTx+daJjYL0Puko92aq0HqbFFgowQ9d8JgVzCYTn373u8ta91QzEk/gsNtKz2gwpfgDYZqNhko15+n9+zlr8eKKlk2l07idzhqPaGo4Y4V4fiX8qvt/j3D9DSRHozBaJ/Sfbz/FL/55nI9e4OTx3jSv/F2Az7aIuJ4t/8PWWr/j8nmEMxY85tSknHCYLHpLtecuxAQRnmPBln2tkA2blkguJMhzl9WKrFf7HrS2WYrsOLb1CGQazGQawDYXYjjGxHl4QKL/uTRNlgzb7GpkzuuFTAbMZv0NWwpRq0La6aaYeCynC2SlIhzAtxHmuKov1CyXciLmWg4qWt+bWkTDp5Ksu0ohMR70eGgJBjk3Bbe74SvHrUQd8CnBzrfa4iWfIGm9b1mBn4ct/G/Ixis86lOPSo6XcsR4qfXPkWCfGW6IQ+TK8/G66ys1bdAfpK25fjp8nqkMBUJ0tTXP9DBOO7p7e1m7fLIeiMXjOGw2RFEkOjLCQ089xfMuvnjs9aFAgF3PPlsyt7xeOCOFuJYd1f/bcgMuB3RpNPYB+H97E/zmWC/fe56HTrfIhV0WVvQH+dCgnZfY4MpkbcZ2MuFm3kofoHaqKxUJLxa51GrVPmG+HAGV36AkX0Tkb69Uu3CtZYtRTQS8mDDOjiF3nlxBnkWxCFy+yoTaX1VdLh6H+7ZDMgX/vBekDNjs0NYapVd04PSJiOaJiqPWQrvaJwNaxYO5r2XRM4/m6xW2Yi+HrLDqt/gQD89sO3U9Ii9fjE94rUDnzHpGS4wHPW6WdnfTKkG2JvrlcfiExcQvn3XzilXF99Efo2b+FrPwgcYkSywyJzMCXw/YiMoCc80yHT1Wjh23Vjzmaut0stw8otrbJgW45emnicXjuOrEPxxgYDhIa5PRRGam8QfCrFtRWeTWoDD+UIgG78QnDf5gkBe87W1cvGEDX/3IR9jz3HN8/BvfYPtjj3HJOecgCALf//WvcTmdvObFL56hkZfHGSnE89mzeSt3eeHG+ERPcVAjonfuTnD3oSTfe56HDpc6h3jjnVx7Iyx+x9W8WnJxSRLKuWxoRcMBuhsWcU5zeoIwKlVEV0gslfsIPD8PPr+AT6ur5iQHDQ1hXqh9fMnxFBGRxVxjYLIgzv+7UA587rwOhxqlu/Ti8XzVRAIGBiE9EGfoWTVSbrWqFoptrZBKqX/XgkL7qtrUBs2bsgqOlUqoNJ/52C43B5a3sSA0uaNmPZM9hmudjjLd5IvxtNmCNZNhRFBvXSXUAviXxOF3Drhgl5tFBURwQBL4dsDG630p3jvgwCooSAq82J2h3Szzi4iFdenajLvatJ1sCaRVgfVnncX9jz1WVznig/4gi+Z1zvQwzngi0RE87tmRBjFbkCSJUCSCzzMxCGC1WGhtaqKjVfUtvuDss/nRrbfyy7/8hTt+8QsisRjnrV3LLW98Y909wSrErBXiWS/wXLQi3XrW85QFZGBjzsn/ZFpge9zMPTEz1pEU37/GQ5tzXIRnWXHHP2l/4VZOmWCRjn4WWhGa3C6eQw+ItK5eD0wUsFpuJVrOLVpo2dsVWiY3mpdt211qm8VahhdbR6UUE+F6I9JakfL85bUKNe12mD9P/cmSTKrivK8Pdu+BdBosFmhtVf3HW1vBVoY4r7VTSa1FoB7P/FJUIsjDLhe+WKz0jDrJpl9U4qetJyoO4103c6fpRY8NYyHyG/dA9Y4pWTGu3r6q//7NDhemVBEOahOcnzrhmAmEAvvJLwm0m2Ve6U3zfFeGERnmmBUeiJv44rCdb7bFMffXn6h5/iWX8Jf7768rIa521TSKBOuB2WxdWI+YTCaevOuuSdM9Lhd/uuOOCdPWLFvG5973vmkaWe2ZtUK8ltztGI+GJ4A/OOBfp1xc403xroYUm5/fPPYlyxXhWdZddRkn/nJ/USFe6sItbFyNLAPOBkSNL3R+nmk5F/f8SLee1t25AiL/tWLTJjnL1FgElivCi4naUukztuRCuppDdDomdgzKf0Jhs8H5y5bTO3d8eioFg4OqQN+3D1JpMJugpUWNnK+ZvwSXo/wOofUeWS3XR7wcQa4IIqIytcWaetFKfdDyFtf6vlRr01cILfGt9XoxQV5qHQAxhwNXPEFEgHts8Nkcp1URNaDxjKVwYCKhwLAk8s2AlWtdGZ5LiXwnaOZQSuQLrXGWWmWOlRzF9NP1qW9yau0c/lpHYlxWZEyiYZs3k0iSjCgaItygck4bIV5JNDzLsAiLM/CEBf6fE5Zl4Ish2LBQLRhK3H8Sx+XzNEU4wPKFC9lvvh80XNWKCfB8l4XBiEibeRhQfbZLpYYUaotdrH13vlAu5PYwIaJXQEyUahNebafH/LSUYsWZhXLZi6GVPpM77ZnjEea0T/bnLbTuCevjIHPmwJw546+l0jJ9g0lO9Sf52/YhRhISZpNAe4uNOe3qj8et/ZWsJwGu1eI+l+xxUYkgL0RCsNDojU8S7uX6aOdSC0/tYoK82nXqRY94rmb+/GW7bmyjIRLhL3Y4P6X2YcilTYLeIveYv4tYCMoCv45YGciIHE6LvMKb4uPNGVx1rCltwFv2neLLP/whZ69cWbalWq3JSJIhwuuAQNiwLjSojtNCiFcjwgHsCnzSB24Z3hqD1Rl1eu4j6EIiHNRHJcN558NyBHiWbr+Juc3SJG/vXEqJ8Ny/Swllva27tbZRaju5y+pJjSkl2isV4aUEbKH9DHCqL8m56yqzpNJan9UiMr/Lwfyu8WKvTEambyhFT3+S/YdjRGIZRFGgtcnKnA4bnZmDNDiVuvQxL/WUpZhFXbn0W3y0p4Njfxf7flWT0lEp1RQHVjPWakR1pewesnCeJ8JOK7xT4+36FNhfRB++pSHFm3wp3tDnZJMjw86kjaNpke0jZsyjOefi8jj+ow6y5dPL0lAPySoLJbi2L8x/fe1r/OjWWzGbyn+qVSuGA2GaGgzLvJnGHwjTbHwOBlUw64V4tSIc4NUj4JXVR6laesd1+7aCyyqKwk9u/x9u1umaUqyzXLffxJa16opyxXi+mCwmwnMpJpS1llMUOHXvSY6lRfySgFtU8IkKXlHBawK3MNb7ZtK6ir2v/Ci5nnSaUsWqWaoR4Vrz5O7zoR4HTYuOo+jUVuV4dme3awLmAHMagVEXMkmGwbBIT4+JBwNWgiMiAtDklulqlOhqlGn2yJqfRbnU6gmG3ig5VCbK+y0NE4R4vTKdNwC1EuEPrrRypMOMJ65w1sk0y09lNM+DWVLtPnwDfShuNa1vcQYuyImM+2QIFVlBl1nhu8+6WW6BdYfs/HhNjD9GLTyZNCEpauGnrAhIbRlkBYYjZk664JoEXJMEZ4nspNz9UqtOorlcm4Bn9hzg1utewkvi6rRaXIfKZXA4RFtzw7Rv12Ai/kCI9pammR6GwSxm1grxWp34Vu+4m2oSKH6+5QZwwNk5hZ6FHFHyyRc+0YSAxz5+lSmVo61X0ORHvKP3ddMnCRxPixxLixwf/TmWUQXfQotMi0kmJguEZIGwpP6fUMAjwgqrxNfaEhPWWYoJvuh5oi1/P5QS4cXsCnM7QlbiVjH2xGH0YyhH7BZzeclffzFMInQ0yHQ0yJyzSJ0mKzAcFegJmNh51II/IqIAXocyKs4l2rwy5jICdPmiudgTDL3oqUWoJHWl39LA2pHjuuefiaj4dKMlMssR50kzWDJwssXMWSczeEdkdi6xsne+hS27Enjj2opXtpp56v4gV3pE+hpN3LvIwqlTad7RqaZxeWW1MZoWx3a5edYMP/XC20ZPkx1mhbc2pIoGPI6ePMlX3/Iu/tMHVyfg+Ulw6SgXqLQgtxgi8PYofMwHa9KwIlOzVZfF4HCQJQu6ZmbjBmP4A2FWL1s408MwmMXMWiE+UwyHQhw/dYqhYJA9n7qNfznUdshZvZYrwvMFajGBk8qApYSIqtQyLqnAQ3ETO0bMHPnFEN0ZFw2iwgKLzAKLzEqrxPNdaRZaFBrEiWkQigLHMgIHUyZOZQSeTpqIyOWFYgu9b63p1YjwWhKICTS4irRYLUAhMV5tjrcoQItHocWTYQr4TQsAAF+9SURBVN189cqvKBCOq+J83ykz2/eZkGRw2pSxyHlng4S1zG95LQR5/vKlUleguDBPiFYcSnmedtMtxtOMu4foIYVa1PioFQ6YwbtgLh6XC3H3AVwK4z+yGgV25f/Iat5y7rcxKziLCfKgS+CP5zsIO0XcCYWlPWmOdJh52QMjLO3N8KtLnTywysZ1Oyd7tiuCMHaX6kwq9DSbiNsEFgxIPHZYdVXxKdoR8exnkU3j22aHzSl1eqnAyqK5c/n23+5m/zuu5n+OuVRBnoTnJ8CdI8inK1WnUYFXjKg1RZ8Ll55/KhjwB7lgw6qZ2bjBGOFoDI/HNdPDMJjFGEK8TD5/xx3c+8gjrEtBmwkuTcEmjSLNXJFRLOILqkjrCZiY06RtM5AvYuIZhbv+1oeAmQsdEh3mwqGh7SMmbhu2s8wicaUrw8s8aYRnndgRyHdND43+KEDirBG2x83cP2ImqcBam0SnWeFyR4Zz7ePj1BMNz6VQuk3ua1DaJxwqa55T6GYm/zM6FTAxp1GHH6XWNqbJO1oQwOdU8DkznDVnfHosKdAbEDk+aOKR5yykJQGLSaGzQU1t6WyUce7ZU3L9+W47VY21ROoKFD6WJAXMfXYc6wofa4VEfDViXM+yh03wo3iGnmYTKYvAJ8KwskCE9LEHImREON5m5rkuM0fbzbSFJJYdzXDng3eSSqeJRKOEo1EG//eTHO+2ExNgyAQxIe9HhBGTQkYWxoS5c1Scz5dgy2YPR3dMFqUZEf54voOzj6ZZd0wV4P84x07aLJA0wyMrbSjAFbu1c+3SzS6sw1FiNoHfXeRgwaDEa/4Vw5YZf4/nXuIhKWjWrgNqp0qAC0c3Uc7TzZV3/JMvvGcLJ9MCdxx1cYsP3hSD82rkO14OO62qXeNMkUylsJfji2owJSgKmk5nBgZ6MYR4GezdvJVXAgkXnDDBa0egMydoWkmhVlasdftNzGseF36FnEqGJYH3DdjpMps5kRY5mcnw7sYUf42a+WPUQkSBpRaZs6wyEvCbiIWvtsY5y6YO9Pd73exwQ7sEG9KwNAMjAoREGBLVCN3jFnD57VzuzPCp5gQrrXLFxYITUlJyhHauIC/kjlJrEV6MfJeYU0Pz2eAdQPFPjgrqEacz6XLisiks7ZBY2jF+PKUy0Bs00RMQeeaEhVj/ckRBodWaoMsWo8sWo8GcnPQ51yo6nkWPIM9nKOWg1Vq8o2a5tomlyH6XC9krKsAPnfC0Bc4+nuGap+I8vszGc11WVmbUPOfdFogIkBAgLsCuc+wcazPTGpZY1pPh0r1J3hUvkI5x/t+JvWfLpG3nn2NSCkRlgYgMEVkgLAvsTJj4eMjKyud7mP/ECJ3DEiYZBr0ij62w0hKWOfuYqiCX9GV43b0xjrab2bHGzrBb5CUPjYwJ63ySbT6U4TC/vdjJWd1pzn9ustyWGb/Fzx37oAj32WCXFS5PwLXJylIMXbdvY+57tvD55VGeTYr8V4+TviS8qMghotUdtBqescBxE/xHbU9DulHqxMbzTEeWZcM/3KBqDCFeBqt33M3ezVt5RwzutcFnvPCGGJw/GhXJdVnJLWDMFzNaIu3koSjnRw6jnFAF8+GgxP89m+DwCbUayCUoyNg5kDLxUk+K13jT3Njj5IVudeOH0iLNJoUP+FI8lxJ5NiXSnRH5RluchRb1pP1Q3MQPXPCyEeg3wY+d0G0ChwINCjTKcFFLktc4Myw0qykq5eR/6xVXuVaBlYjwcig3Mp19D0MpOy0W7St7LS0aa4HWfs8fl9UMC1okFrRIQBpl50EkRWAw5aAn6eShYAfBtBoNbbQk6bLF6LTFaLXGMQlTI8j1Hi99KScd1tKNfGohxgvdTOdHx/9oh+Nm+HII7HPtMNdOwgbdoirSb3erKRgrr7oMl8OB027nps5Orti0ieaGBl1jyeZMF9vjLsZqfMe4GnhPPM6f7ruP32/bxl9OnsRiNtPc0MDl55/PO1/1KqyW8SSaO8WrcK+wI5vhcxHYXSTnOTK3gQcdw6zem+bcQ5NF+PmXeNhuVW/0rag3JLss8C8bHDLDi65/IT+85hqWzCvvSdqk9337NmLv2cJZNpkfzI/xmm4Xq9Pq9gulpzz2QITzLvGQRr0xesKqNiTKAK8bUQMTuewxq2lDqzJq06IsaeAnTjUQY2VmCjWjsThup6P0jAZTSjAcpcF7eteiGEw9hhAvk6wY35JU3QJud8PBNLx8ZPLOzHctyQqPtKSwf1hibev4EhllBVZRZu89p/hx2MKTCRM3edJc6ZMRUYgp6l33QkuSOWaF+0ZMJGSBnQkznxkyE5IF3taQYplVxrLPySomioo9SZHP++28LwLLRgOlL4vD3LOjmDVu6LUEeMkiyzxxpRUNz837LuSGkhXh23qEgm3opxJFUcWUnkLNStM3qhHzeps4lVq3SVDosI3QYRsBhtTlFAhmbPQkXeyJNjOQcqAoAg5Thk5bjK4HTtC5aT62cpKhC6BXjPcmXZzrHahoG+WkpZR6opUV44Mi/NUOXwiNt0AHtXDv9w4IiurPL3//mwmCdzpxOhzcfN113HzddaTTaSIjIzT5fJrzXjfwK174pjfz0jg8ZoW2yz30PBLFnVDG8s83XuLhJycSBM5qZMnfDnGOhgjvaRT5ulu9uX/tCNxlVyPgTQpcmYA7fv8rHDZbzd5jVoy3mBTe35rgu7Kdz4XHxbgC9DSZ2LPAwskWEymzwO1mBVEGiwQdAYkVJjO7rPBtN3w+BB2jTzgft8CPXHBdAu5wqZ+tZ/RU9Gc7zBl9ojgTIhzUQs225vxbMIPpxh8I09xoWBcaVIchxCsgK8YXS2qhzh0u+JwH3hMFNNo650bpetd38fEHYpwIS9y0wsa7z3EQTltI9Ab44EMDPJmw8wpvmo80JXHmpHBnBUUaYH2UY2mRmCKwJynyH40pNtokRGGi8JAU+GXEwl+iFmIK3NKUYNGQGkXR63OuWVBZRNxlxZXWPPnRbj3pJVpivNBytWoNH8zYaLTo9KNEf7S4kOjUs3ylhbpa6y62LkFQI+KNliSr3cNj02OSmd6kkxMJN4/dkyTla8AsQrtPzTnvapTw2Mv3O9cjxv1pO00Fnk7UCq3vg1aEfeH6KEd3u2mQYb9FvWFbllGt+7pkeG8Uekzwut//bMZEeD4Wi6WgCAcYDATYuP5sjj/2NCYT3C9C/xY3UVmhVRDIAN8TYIHHztKQwpKDE78bGRHuW2enf46FFyVgbVo9J16QgluisECaOsGaFeNXOzP8y5PhDsnM5Uno3+Lh77KMKCusPpHmggNJ7CkFswSmnNPJ3zbaCc5RP6en5qeYd9LKDhscNMMtETWKvzgz7tAyIMLf7ep5f6ZEOKhCvNWwLpxx/EHDQ9ygegwhXgF7N28d+92twAei6qPqT/jgHYXEuKzma//qzyHe1pBkc3uGjx2SuDHQjJwRafJZuOKlb+Kz116L0zH5kePqvO2+wZfmDb7ClUIhAb4+aEdS4GPNCc6yjvpOVyDAtYpLi1FMUOamnBRLP9nWo63oyu2gWUmu9qmEiy5b6VSISdsqcAOiV0RXKranYt35lpcuU4alzjBLneMWEZmzV9MXEukNmjjQYyOSUD+zZrdMZ6NEV4NMi0emVPO/kmJc0W8jWUl6SiERXmh9jctGODng5J82NZ3rp07VvvSVI2qh5soMeN2z53H1mmXL+N9Pf3rS9JF4nN6hIaxmM26XC4/Txa//ch+v/NFnuFO8amy+o1d5sJrgSyE1d/rnTvhYRC0ahakXrNkUns9FIvzqr3/l7089xaI5c/jm1VezbsWKojm8Ky7byuGI2gk06BJ4plWiJWTiSyHYZ4G7HPCpsJrzLqOmpFybgNbyDZVqyoA/yIrF82d2EAYMBUIsX1xdmpWBgSHEyyRXDGcRga0JtfDxqx74dBgYjUwnUB/P/skB57rTfLd9hLmjOdvf/9ld7D18mBMn/Ww6+yzaW4s3BVi94+6xAq5CKKiuBP/rghdaZd7kS2mmnmQpZrFYyBO7Wnu+rMiuJu1kKgR4llNJFxu8QxUtmyvGp1JYZ8kXieW62JRaX/603PWbn97LvI2rmdcsM/qsBlkBf0SkLyjy1HELQxERRQGnVVHFeaNMh0/SndoSyVhwmSu3pqiFhWG+GF9gUXh3Q5KbPGm6n3YzIsCf7PBRH7wuBptm0Emjljgdjgm53P1DAVoa1cj6G+R72bt5K8dM8L92+HpQfRJwpws+PI0iPBefx8Nbb76Zt958s+5lLrr/bnybt0IaFjaPRvrbYffTbv7HpUb0u2RVhN/pVHPLXzC1D2d0EQrH8BqWeTNOKByjwfgcDKrEEOJloCXCcxEZ7/r2iFX92WOGNRn4SATmBy1kTlo4xvgFav3Klex+9h7djxmzj2K1GMgIfMyruqC8YQRuXFTIQKx8AZ5bYKlFsaLIQoJeTw547uvZaHj+GGrtUDKUdtBiiVe8/FQJcD2RXq159IjzcppD5a4v/ymAKECrV6bVK7N2/njVXzQh0BcUOT5k4tFDFlIZAVM2taVBpnPlGrzP7pmU2tKXdNJpHdE1tumi0aTwcq+qtrPR9FXAxt1u7nDDgxJ8KRCgpfH0yuHtHxymvWX8Pa3ecTexy7ayMANfd6sF4B9rizMv6Bh7fTagFeBYtDaK67iboyZok1S/8GFRvcmoh4QjBcWwzKsDFEVBLPXIz8CgBIYQryGPWtWIyTdH7QHPT8GbYxMbTsDEC5Q8akNVyZd5T1LEIyosGI2wP5EwYQK+Eir+wepNQdEqpsztXKmHUp0mq42OlyvC81NHJnWXVLK+sBUNZ8qoxg0kv2i42nWXEuO507O4gKUbV0+wVExLMDCa2vLvA1aCvepx1WhJ0mEbodMa41TSxWKHvo4ple6jYyXqOvSyZW2US2R451E3O554ghuvvrqi8dQr/UMB1q5cPGHa+fffzf++ewu/Clu42pVRexqsjxbtklmP5Ac43CJ8a26Mz/nt/CZp4rIkvD2iuqTMNOl0BovZuHTPNLJSfk2MgYEWxre5DEpFeL6sKGV7ig4Nh2htaig6j6IoZDIZkuk00oevH0s1uT1goycj8KXWBKttMhc5MvzNleFbLrilSX+xYT6F3ExKUUx098YP8kCvu2Dudz5buhTd85ZDKbeSYMZKg6Xwk4TZTC19trXEOBS3sswX7BYTzGmSmdOkJtwqysFR1xYrfUkXz8aa2Blu5UTCgyOUUR1erCN02mK4zRld70dvWoqWGK+Eg7vdnPTBRevXV72uemNwOEhL0+Siz8ZvbePtMzCeWpN/87AS+NnMDKUoQ4GQ4dRRB4QjRnqQQW0whHgNqcTYv7tngHmdbROmpdJpdh88yOO7d/P47t3see45MpkMkixzk9vK+5pSBCQ4lhZ5f2OSTw7Z8YkK6+wSW1wZHoybeXOfk3/M0y44zBdRMNlesBxnk1JkRXg11LqBD2iLxVNJN3NsM9SlowC1FNB6KSRgc8Wq1nFUKi2nmN2jsHE17NxLoyVFoyXFWe4AfUknr+o6SEIy0Z9y0pt08vRzNmKiDaFpHo2ZKO3pIO3pIC2ZCCLjT1bKzQ2vRowrCjycMPE/HrgoBR2trRWtp56RZBmzyTTTwzjjGfQb1oX1wFAgZDimGNQEQ4jPMEd+/QMujewjJieIyXB31MIvwxYaUiJnpeHKDHzhrCgBSeCt/U5e5U2jKPCjkJVNjgzXujM8z5VhV9LEgZTIMwkT/RmB9Tlt6EuRK8LzBXM1gjw/sp6NcO98sJ2NF/ePTS+UljITHuI9CRdne9RCzVIpHacrxQRsvljVEuOl0Ou9npYFTIJ6DNhNEgscEdoe3cfZo6/LCATMLvrNDex1zMdv9iALAnY5jeVYnMbmMI3hCLa0/upJvWI8+57j27t5NG7iuyErIyMmbojPTLv1qSadydStCJfvesOkaeKNd87ASKaHgeEgq5YtnOlhnPH4A+Gx4mUDg2owhPgMsnfzVqJXrsMuJbgzbOG3ESvn2TN8sy2BuM85Np9FgHcOODjPnuHppIl/jpgJSgJfblULCk0CbLRLbLRLmqKoUEQ1VwwVEs35YjibH67Vmj4XrfSWbLpJVoRrFWLCZFvDWkbDS+WID6YdtFrHCzXPJBFeaRpHpWIcilsXDqSctBUp1BRRaM5Eac5EWZU4OTY9IVh4OtxBwOvlaFcXKYsVUPDERmgMh2mMRPDGYogF2oTrEePZ71RCho8N2fl4c4L5fQ5O17KtweFQXfpWn2kiHNR0RkMAzjz+QIilC+bM9DAMTgMMIT5D7N28lYwokhgW+azfRkQWuKN9hPmjhZe5ft8n0gJDksjhtEJcFjjPIfFCVxqHqK8DZrF5hPkbJ6WjlMrNzhZI5hdKlirMhMnCXktkZ6c90OvWfD23YDS7zUqdU3KFoFqoKYwVataLCK9F6/ZiVGLvpyXGC1FsPxZLZelLOum0jQtxvfug7ykb7QRoHw6MTZOBiMtFwOvhaFcXYbcLRRCwptM0hiM0RCI0hsPYR6PneiPjTydNLLPKXO6UODY6bba4hZRDvmNKPXAminCATEbCajEu3TNNMBylwTd7+gUY1C/Gt3kGyNogDvu8HEmE6QlZ+M7iKLYC+ne+ReHB+eOioJiwhnErwVLdFHOFczERXsg2MJ/cKHmnY3nRos9ijXmyyxWLhOe7t5TbdEiLUMaKr4yOmsXQ28lyJqnWX1uvWK00xac35eKShp6yxpNlrxlWZMZPcCLgi8XwxWIs7O0bmy9lNhPweAh4vRzr6iRptSIoCp6REY4MRFjd1U9LJoIJ7Q4uTyZNbLSNp4GdjiIcVMeUc9bUpnNtLThTRbhc4CmOwfQjywomw7rQoAYYQnyayfUi39PUwBOJIIsV+Ml+N5cuHmGZVS7YgEePAM//PStI81My8osztdDK0R6LhmsJ+42rC4pxLVFdSNhnp5dybylmpVhOpDwbFa9loabetvczRbUiXGs9etM59AryYNqKz5yasKyecew3w61eWJ9Su94+8UCE8y/xaC5nzWRoDwRoD4xHzxUg4nQS9Hp4JLSYkNuFLIo0eBO0pUO0pUO0p4O45QQ7Eybe2aDevJ2uIhzUfNh6duo4E0Q4qE4dPq/h1DHTKMYNkUENMYT4NJLfEMji8fGBfd0cFeCwCf7Q6+QVTUle7dVX7aUlwnPFa6djedFGO7lc0hnlgV53wdSRTsdyHtp1nIUk6Gyya64jW4SXL8YLUaoBkNay+eK8XF/zQggbV3PqH+GxQs1aUatoeG5xYL2iJe61xLmenPLsdU4QyhPhALsscEMcttlg++NR3MBjRcR4PgLgHRnBOzLC/L7xouK0yUTQ4+GIp5FDizs5GfXgXAgHw3Fsb3odHT0DtLc0YrXWQ8uX2iIrcl1F/84U4Z3PoD9Y0u7WYOoJR0fwepylZzQw0IEhxKcJra6cksnEopTEImC+CfZZwNltg9WlhXgpEV4JWTFeiG/+9EFOnPLzuYscXDF/vLVFbqQzV4znjy9L7mtaDhpjUXwdOee1ZMjVTqu1foUu1CZfvFbR8HK3VU6Bp5omlCr6Xgu9j0NmuD4BT1ggbhNwJ1VVX0qMK8BJEzxlgZQAZ6dhSYaxAkyLJNEaDBKOBDk2AHssarOuNZIdj9vJ4RM9PPTkHlLpDCZRpLW5gY7WJjpam2hu8M7aDnypVNrISa4TBoaDdLQ0zfQwznj8gRBNhnWhQY0wzq5TgJbozidhtWJLpRgR4NcOeNwKrxqBDQU0uFY3zFyhWkyEl5OmoVUoORZxTo1wyw2L+fwfDmPfN8h6+8S82ay4yhfX+dud1M2yQJOdUs4stURRQK7DjppaVCPGn37azWM2OGgGmwI+Rc2lDu+IYM1xvFSAeZs99JlAAlI7Ilh0OmIWErvluK30Jl20HD2p+Vp2XVrIwFEzLM5AKCljkSY+4Skmxu9wwQEznJNW980PnRASVUG+IQWyANtt0COq8yzKwJYkuJQEK5fMZ+WS+WPrykgSg/4gfYPDPPHMAYaDYWRFwW6zjonzjtYmPK76j6r1+wOGb3WdMDQcZN2KxaVnNJhSDOtCg1piCPEpICbACdPoI24ZOmX191wGGxqIRIJ8yAeXetL8oiGJt0KbXr2R8Nw0lez/nQXEfL4IT2ckegNJLpEGab7Iya07JP6vc2RSPnuuGB/bbhGLuqmgokLNEQGfU5n2sVZKJakqzyZF3tUAiyS4KgEZAfwi3G2HI9e4aQnLNERlRmwC4VYzogLzJAiLMG+Lh/X/iOjaTjlpIFpiPL69m26Pm6XpgOYyRX3OTdAoq5Fq74jM/WvsrDiZZlF/Blum8Dj2mNWbky+HxtuYf/Yfd9MzMMC/n3iCHU88gaIovPrKK7li0yZs1uLNzs0mE51tzXS2NU+YPpJI0jc4TP/gMLv3HyE6kgCg0eceE+ftLU11FYHuHwrQ3mpEYeuBSDSO2+WY6WGc8fiDYRbO65jpYRicJtTP2f40wR8M8t9ecChgVmBIBBNqBG1DChoUOG6CZ9p8DEZ6+FzHyKTIcj6V2ujpyZ/OTQMpNu+eB3Ywp8lGq1PE+mg/g5ILSUGzsLRQ+/Pc1/PJzl+s2YueG45KbQxPBUzMadTfBKleKHRsaO3jFVaZW5oT/O+QnW4z3DgC2XhsEoE/708ScoqsX2KnKwztozeQJ03wGQ80N5tojMq4ksqkG8t8yhXj+QyafVyYPjBpejERrgD/sMOFKXX7L7DA4Q4zB+ZauG+dnTl+iavdZqJpVajn8jsHvGJkXIRnCy+72tq4+brruPm663S9l1I47TYWz+tk8bzO8XErCsFwlL7BYQ4dO8VDO8fTW1qactJbGr0zkqfdPxjggnNWTft2DbSppIOzQW0JhCI0+vSd3wwMSmEI8RoiSRJv++QnERX4jyh0yKo4OGGCJy3wK6caLV/tSdPZ6OTTpgHsgqIZEcxSrZd1KTGuN6f7SN8IS21pwMpTCRMrLDI2sXgOcLUUSr0p1O0zP/e86LrzxP6pYRPr5p8+LRG10ldEAV7szrDZEeO2Iy7e26CmXVyUgnVpeMnKUVmetxt8Mpyfgr3nOzkhy2RMAu0BiXXH0izuy2BSIOwQUATwjYwrXC0xrtfyMCOImPMsA0vltv/VrkbE19yrRu7taVjdnWF1d4akGcTNHh6zwv9zwhJJfU/npsCjwHGzug9g+t1PBEGg0eeh0efhrKULxqZnJImh4RB9g8M8uecg/kAYWZGxWS20tzTR0dJIR2sTXo9rSsWZITrqg2QydVoWAs9GJEmu206zBrMPQ4jXEEEQePX11/PQV77Np7zwogS8MAELJPXnhoQqVhXgNxaFxivmaq6npKNEnjtJKc/useUKCNVJaSQaUeV5gT5+OSwR397NzoSVNTaJfAcnvSJLi6L5whoiPEtup88selJLJnXU7F1O6xqL7rSUWt4s6aVcb/JC6SuNJoW3xeDlglqb8Gc7fNcFN8bhGg0bdY8Cbx7rqyPy70cinGg189RiC08usbKkL8POpVZQFF55/wieRHExXoqUYMaqFMkjyUMB/m6Df9jgxfdGNVNQbBlVeF+cggTQuzzO9hEzv4xa8CqwLAMO6suC0GwyjUXDc0kkUwwMBegbHObA0ZOEIup3zu10qKktrapIdzq03Y3KRUFBNKKwM87gcIjWJiMveaYxrAsNao0hxGuIKIps3bKFZZ/5Ni+Mw0d8cHly8mPwYbObpkx5gjVf+OVHsjtLFDUW8/+eMF+eKD/yr2f47cEkvVGZ5wISJ+0Ca2wSXxi2cyQt8h+MH0SVivDseypFrgivZdt7tVBTQHyqtLjVivRX2rCmXCrNXdeKji9cH+XYLjdbkmrBYb8It3rArsBlqeLru/QCD489EGFpb4bta23sWWDh5Tti/OMcB4M+EU+iuhSfAYuPtnSo4OsyasqMAPSJcJcDuk3wiQi0nuvWLaZfCCRTKZ45cIA1y5fjsNmqGvd0YbdZmT+nnflz2idMj8bi9A0O09M/xFN7nmMkMZp/7vXQ3tpIR0sTbS2N2MqIqiaSKewl8uENpofBYcO6sB6Ijhh5+ga1xRDiU4RHUXPDR4TJQvyUpZk5KT9ZY7RSkc58EaVVEKmH3PmL5WkDxNIKX//2Y2zvTnO9NckWq8SNbdBpVphrkbjYEePDg3Z+Pz/NS09YCAlwV8TMkbSJN/mSNI4+tSun4YteainCAcKSFa+5hPqkdLpNviAvNP90RdDLoV2GD0fgc15okWF1iYD0+ZeoYvyK3UnSpiR/Ot+BJEBDrHS0qNSTkz5LA+3p4KRlsnzTrVoH+mSIC7A5CW+MgZ3yI9o2q5Xz1q4ta5l6xe1ysNQ1h6UL54xNy+af9w8FRu0V95JKpxEFkeZGL+0tjbS3NtHW1IDZPPlRez22tj9TGfAH2bBq6UwP44zHHwjTbFgXGtQQQ4hXyN7NW4te9B+xqgK8TaMO85S1iYsj+4GWSa/lu3YUEnNaEfL89eSSfb2YmMy+tish8nm/nXPsEr9sSeLKyQXvRhXUJgE+3ZLgrf0O/tUAGeCipAmvqPCWPie3Dorkx9H0pK5oWTPmoiXCKy3QzNKTcDHHrq8rpB70CvYsMyXMs1HxLB0yNMuqS0o5PL3IiijDzf8eQe+ixY6FfksDK+OFrQuvj6st7F89ouZ1Z09i9ZRWUi/k5p/n2itKssxwIEzf0DB7Dx7l/uEQGUka9z9vaaK9pZGegWHDMaVOGA6Gaarj7qZnCkOBEM1GipBBDTGEeAVkfcK1xHj2NRPQa1IFav5OjpgceOV4ye2M3NfNqYzA3pQJvyTgFhU8ooJXBI+ojP0t39eNKKDpVDKSVjgYkOh5YoAmUaHZJNBiUrDnKSZFgWeSIn+OWXg0YeJDjUkucU5OMcgVTy4RvtceJywLdJgUBAHu2+3mL97Jdo3FKCZEtSwVs5TbUbOQAD6VdLHGPax7uVqjp9PkdLDDCiYFNpV+OACoUfF/PxLhseVWNu9J6hbhWQqJ8Zhowy0nCxZnLpHgpXH4vQPW5hSWlro5NhgnK7hbmxtYm+NLnclIDA4H6R8K8NS+53hm/xGaG3w8tfc52pobaG9por21kSafZ9Y2KJqtGAWC9YE/EGZ+Z9tMD8PgNMIQ4mWyd/NWZGCnBXpM8MtrtmK/4flEYjH67v03MQ9ERTUl5SUjE3fwwvVRMoiYlIlh8txodiyt8IdDSR7aHWFvyoVdUFhtk2g1KRxLi0RkgYjM6P/qT1IBpwie//PjEVRxbhfhRFqkXxJYbJFpNVkYlgT8oz82AZpNCo0mhYgMA5JIk6hwnTvNuxqS+Ezgun0bsfdsGRu7Fi4RBp9xcRwICPBVH7wlBlpZqHqj4dWi5QVeKLfbcfk8BlIOWq0jBT2ttciKxFql2xRLa5kOkR4T4DdO+EAETUGdFbj5zarMElywP8ljy62kLHDO4cnOM8UKNvPFtgLEzzGVdEi5JgnPWuAbbnhTDJpGM2IMMV4dZvNE//MBf5BXb72adEZiwB+gfyjAY7ueZTgYQUHBarGo6S2jPw0+j1HYOQXIsmzYFtYJw8Gw0VXToKYYQrwMVFHq5hcOtR392rTqF+783d9pVWC1As7RnzmSGhXPkhVsfZYGOvLyX7M8eCrNJx+McY6Y4jpXhjf7UsRHvbpT+500KLBYQ/hlFIjKEJUFDux3ERMgIcBblo2w0CJP8vpWFIjIMCSJBGQ10t5qUmgU1ag2qCI8+39WjGuRK5i+7YarE6qPcz6FBKuWyKx1N81S6TjppnmkDnSXnDdL7nvWmwNfSFjmL1OsGFSLWon03ztgfQoWa9RZ5grb1TvuniDGTQqccySNK6Hw93MdLO3J4I1PzhPX654ScTrxjIyUnE9AveG7xQcP2+AFifHXDDFeWwRBwGoxM7ejlbkdrRNeSyZT9PuD9A8Nc/jJHoKhKAoKdquVtlyB7nUbQrIKAqEojb7iN6cG04MkyZr1FAYGlWII8TyKtadfuB5SwL/s8PUgeHW4GOULrR5rtlBzckrC95+J85+uEWQEvhuyEZFhrlkhPmLC71PdIl4QsPIid5oFlvGNn3x6/AS9JHdj+5zkZtpmxyII4DWB16TdSCgrwnP/1hLjueIyMNpN9L/ymi8WE6e5771UbvhUERHteKRE6RlHKdrVsUCUvJJl9KInraVUVD8D3GsD+4jMhyWZ+V4zyzJwRRLWFxG0jz4QIeQSeHqhlQNzzVz/yIimCM/y2APqwVFMkAe8XhrD4wdRGtXRJS1ASlD/johwyAxPW2BDGq7V//EZlEFsJIHTXtwC0WazMr+rjfldEx/VJ5Ip+ofUCPpzx04SCsdQUHDYbKpAb26gvbUJ3xR7oJ8uDA4HaW1umOlhnPEY1oUGU4EhxIuQH/07uMvNrx2wIg2nTPBPsyoIEoIqyr2y+n+TDOel1N/z82B7rI2six0lKsOgJDD4tx4GJYH9KZGhuJmUT+DHYSu3NCU5166GJ7OCqVeEXQ3w7n4HbWaFNpPClc4MWnX05UQE80V27D1bJojxQhHx7Pvqzwj88rCLtenJqTiF0BvJzc0Dz+aLl+wWqqPYdWyd1kY6C7RSr5RSaRWFlpkqMV4o3SZbrGkGvh2EYVEkZBMJpOH/nBAQwZIXXd67eSt/scM/bRC5xoWowMqTGV65fQR3Ut9FKivIYbIoH/R6OfzQEZ6YB93nrmbf4cO0NjXhtNuxWa3YrVbcTidrli/n5rPO4uwVK4xc5Smif2iY9tbKHFPsNisL5rSzIM9iMZ5IMjAq0A/mCHS7zUp7sxo9bzMi6JMY9AeZ12XkJc80I/EkLmdt/PkNDLIYQrwAWfGRK8aftcB9duiQ4AcutUHIVUlwKRARVLeJkAD7zfBrh1pQtiWpiqwBEf5gh+Q6O7cftyOOpoO0mmRaTQpzLDJ3dMT58rCNl3rSYyI8l04ZLmxI8RZfit1JkScSZj7jt3GHoI4hf+x60Yp4Z8V47D1bUBQ4mhZ5OGHiUEokpQikFUii5qGnFFjblOGtvhQLrdpR9iyaqSg6c8O1BHi+Y0o5Ihyg19LEiiIOHblUIrDLoRoxXg65vuLZ7R3b5cYlwTxUR5KwqKZXAdwpXsUb5HvHvgdRAeYcS3HuoRROHe3ui5EV5SkT3HOOHW+Dk/6WJNe+5mauXrWKs1euxO10VrEFg0rpHwrU3LrQYbexYG4HC+Z2TJg+JtD9QZ47dopQJIqsTExxaWtuOGNz0AeHg5yztrzidIPaMxQIGfnhBjXHEOIa5AvZrBhfkQazouaG3xhnkj1fLj0i3OGGB62qLdxTFtgiWWgcSfPGADjHWpKMR/Oi2HjB8jhfGrbTbJK5zCERlAWOmMAvqj+ZgJV+SaA/I3IsLfLBpiSu4fE79EpzY7Oi+/cRM48kzPhEBe9rrmNEsfFI3IQAXOiQONcuYRfAKihYBegyy8w1j+eWazFVxYbFRLheBs1eLsmEazWkqplOMQ6To+MAQRGWZCbm+t8pXoUswIE5ZnassbPYDC6dEfBSxK0Cf9jkoCUssXhA5s4df6rJeg2qo38owJrli6ZlW4UEeiKZYiCbg368h2A4gqwo2KwW2ppVcd7Wcvq7uIzEk7hq1CnVoHL8gRAtjYZ1oUFtMYR4HoWEbHb6DlnWdcJfDVyeyXDfo49yqr+fz119NX0DAYKRKOet/2zR5eYfOsQHb7uNz/QFcDkctG9ooaNF/WlvaeHs1lbaW1pYMm8eXnftorS/Dlv4TdTCOxqSxGSBkCzQgsJNbSkWlhDbhdAjwrNdQqF6T/BykQUBE/WV9zddYhwmRscXnB3l7qiZHQN2Dpvhj3a4IaGmjzzyQIQ/ne8gaRG4ZG+Cuf7qumfmcqzNRMoMlx9UaPz8VTVbr0F1RGIjM95B0F4gBz2ZSjPoD9LvD/D40/tVFxdFwWw20drUQFtLA+3NjTQ3+jCZZr9AV+rsHHWm4g+EWbtycekZDQzKwBDiZVJO1MViNvO8iy8e+/vxpw+yatmCksutXrqUP3znO2RkeUrbbiuKwuHubv79xBPc96s7GcpY+FZ7nA5zbU765UTCy4lma6WyaC2v1do9l4hox11GoWZ+A5ypZCbEeESBrwTsYAGLMvoEBvUkcbzNxIhN4CuyCdMCB491R0qtVjfLT2V4fJmVY6uaWDVqm2cws2SL0uo1T9tmtTC3s5W5nRNdXNLpDIPDQQb8QZ7adwh/IIQkq/7bzQ1e2kZTXFqbGrBYZsflLxYvXTRrMD34g0ZXTYPaMzvORKcJ/UPDXHHRBl3zWiwWTS/uakml0+zcu5cdjz/OjieeQJIkLkr08DqvxAa7hK2Orrv53tpZyhHtxcT4VBRq1pJae5UXw3H5PNjezYPzo4Rl+M+jbk6axhOnVq9yst0NP01BpwRrNns4tSNSdn64AsgCyCJIIkiiQNoM7UGZo2ub6WwzujjWA9FYHI9r9uXmWyxmutpb6Gqf2LU4I0n4A2EG/AGePXSCHcPPkMlICAI0+jwT0lzstmJJh9PPkN9wTKkXMhlp1tzAGcwejCNqmlAUBVlRME1zHmPsPVsISAIPxU08FDfzRMLEAovMxY4Mtzok1lzbReJ+na0Uy6CSvPBCgnmqWsL3WRpZnugpa5lKouJ6PbQLoSc6XovunNmbll+GrUhOiQ8OmMaE+JoMfDgCz5rhpAn+agfhBR4a+tM4kwrOpIIjqeBMqf8DDPhEBhtMDPhEwk4RWQDJJCDICiYZRAVMsoJJgnlDEoszrrFGMgYzS9/QcM0LNWcSs8k05mnOivHpsiwTCEUZ8Ac4erKXR3c9SyKlng+9bueoQFdFutvlmJEnBAPDQdoMIW5gcNpiCPFpYjgYock3PY+0FEXhuePH2fapd/Bg3MHxtMi5domLHBluaUrSaFKFUla4aXVz1MNMtWUvV3QWen+DZi8Xp58te/vlivFqRHgWPdHxQk8QyuHBuIl/jZi5o32EUP/E9/iC++7mBaO/K4rCPVfcwEmvRXUKOplk0CcyYhOI20QUoDUk0eWX+OSvb2duRwdWiwWzyYSpQJvu//f7e3DYpy4Vy0A//UOBSVHl0xFRFGlu9NLc6OWspeNpg4qiEI6OMOAP0Dc0zO4DR4jE1EZTDpuN1uYGNYLe3Eijzz2lhaKD/iCL5nVO2foN9DESTxjnJ4MpwRDi00R378CU+cA+e/gwf9uxg+6+Pk729XGyv5/G9AgXOQTe7Eux3i5hzQnkaAm1+PZu+jICLlHBo/OaUosobO66yp2/3G3np6nIglh3hZql0Bsdh8oE+Ym0yCZ7hkYThHKm5xcxC4LANdvHrT2vabVN8AfP8gb5Xl3blSQZUZj9RXWnC/2DATasXjbTw5gxBEHA53Hh87hYtnDuhNdGEkkG/UE1it7dSyCkOrmYTSZamny0NTXQ2tJIa6OvJmkMalfN6m/mDarDHwjT3GjkhxvUHkOITxMnega49Ly1NV/vwWPHeOdnPsPN113HdZddxryODhq/9lbceZpGS5RFUgpP9KV54IkgjyecRGVIKQKrbRKXOTJc6pRoMU29UNUS4VoR50Lt4MuNjse3dxMVbbgq6KiZHcN0Fm5qjUVP3rjWfi21r5ZbZbaPTMyRLWaJmd/0Khe9IhyMzoH1xkgiYdjlFcBpt2k2K0pnMmoe+lCAfc8dY2g4RDqTQRQEGryesSh6a1NDWU1hZEWe9pRGg8n4g4YQN5gaDCE+TQTDURq8tRFuWeHTtDbKe/qcvDIkcuF3fjEuzgqI8IyssHdI4uGeNI/2pjk4lGGNTeJ8u8znWtIsscgkFHg0YeInIStfCdh5ozfFmxpql0MubFxdstiykMAtJEArSVV57uE0HelgyXnzxzKdBZTFqHQcpfLtI/LE9evxpc+K8fMv8YxFxcsR4QC9A366jPzwusBo410ZFrOZjtYmOlonFhzLikIwHGXQH6S7d4An9xwkFleDAE67fYJAz09zyUiSIcLrhKFAiFXLFs70ME57ntizhzd//OOar3W1tfHX731P87Udjz/O93/zG0709nLu6tV87B3voMk3OzzfDSE+DWQkCbNJrEmhz97NW+kVYa8F7h9wcLkzwyvmaAtlRYFTGYHH/tTL4wkzTyZMdJhlzrdLvN4ucfYcCZuoznciI/CXmJndSRPPJE2kFHiTL8n17kzBsVSS+pAvwvOFYaVR5nLFeK+1iWVFCjVLjWOmouH5VHtjkLv/9yVFvhGw8+GmJAs7JFy3b9O9nrFOtBWNQhXim9avqnBpg1oSisTweerj+D4dEAWBJp+HJp+HFYsnnqNi8QRD/iADw0GOnOgZS3MxiSItjT5sVgtWi5lkKo3NOhU+WgZ68QcM68LpYOXixdz5hS9MmJZOp7nlttvYepV2n4ld+/fzgS99iZuvu4433HgjP/rd73j7pz7FL7761YI1SfWEIcSngd4Bf9VuEPFkkh+/4Gbu80C/Se3uecOwia2r4hPmC8uwM2Hi8YSZx+Im0sB5dokrnBk+2JSkKSfVRFZgx4iJH4esBGWBs20Sa20SN3nSLLbImArcN0xVkaYecVsrf221UHN/xeOoN6rZL4oCd0Ut/Chk4UNNSS50lCfCa4E/GKaxwciDrQf6B4fpOI0cU+oZl8OOS6OjaCYj4Q+E2LnnIIlUmj/880GSOW4urU1qBL21uQGvx4VYp37vpxPpdMa4GZoG3E4nG846a8K0O++6i+aGBt5w442ay/zsj3/kgvXrueWNbwRg7fLlPP/Nb+bhXbu4ZOPGKR9ztRhCfBo42Ts4qfGEHvZu3kpEgN864EErtNrhhjickx7/4CTgmYTIYwkzjydMHEuLrLNJnG+XeGlrmkUWWbMjpl8S+PSQjbAs8EZfikscEuI0t6kvt0BTz/p0j7PVhSkgT5o81SI8m7pRCyeVfCoR4yMy3DZs42ha5LvtceZalGkX4YqioCgYYqJO6BsKsDBPGBpML2azifbWJpwOO2tXLmZep1rorygKkVicweEgg/4g+4+cIByJISsKFrOZ5kbvmEBvbfRhNYSjwSxnKBDg+7/+NV/9yEewWCYfz+lMhvsfe4yPv+MdY9Nam5o4e+VKtj30kCHEDVS6ewcrdiBICOrPfAkGTPAdNzTL0CqDSYFDJ13Mtchc/KKX8f716zl75UqsFgux92wpuM4nEyY+7bfxQleGN/pSBSPfUL4ALySu89dTqQivRTQ8mjHjMhVOuZkqcl1FyhHkKeBXTmiXYHFGPRZyyykPm+Apq9poR9nlZlGBfZR/k9GyLsp7+h0sscp8rz2OTWTaRThAJBbH6559zWNOV/qHAmxaf1bpGQ2mnAF/kAs2jKdsCYKA1+3E63ayZH7XhHnT6QxDgRCDwyH2Hz7BA8NBUmn1POd1O2nJRtGbfPi8buPGtwwSyZQRDZ8h7rrnHjpaWrhw/XrN14eDQdKZDAvmzJkwfUFXFz2Dg9MwwuoxhPg0kEylKu7W1irDO2Ljf6eAIREGTervty6KMec7k8WT6/Ztk8S4rMD/C1v4XcTCx5qTbHJIRbetV4TrEdWl5tETia5VgeSppJs59uktttSy9is0PV+cd5tghxXOT8H9NugxqaJ7axzOT8NBM/zRDm0y/NsG/7nLzfK8fZW7fzOojXl+e8zN4gx8dFkcQZgZEQ7Z1C2jo2a9UM35yqC2lPNZWCxmOtuaJ6VBjkXR/UEGh4McOHKCUDiGgmq52NzgpbW5gZYmH61NDcZnr8FQIERL0+wo/CsXl1118Jn/1EG8TM+TsBQxniWFy+EoOp8sy/x+2zZe9aIXFZxnKBgEwOeeqCF8Hg/PHDxY9VinA0OITzEjiWRNT2xWoEtWfwBNEZ4lV4wHJfis386IIvDDjjitZqVgod9MNeophl4Rric95VTSxQpncJKveHY7tU5PKSTCi82fK8bnSrBIgiNmVYxvSsG9dvimB66Lw9J/Rlh0rp11DRa6zWr0/DW73MjALgucMkHcAXEBwgLssUC7DBcl4XlJOP60W5c7ylTRO+BncV50z2BmkBUFASNSWg/Uyr1mQhR9wcTvWSYj4Q+GGRwOcvh4D488uY9EKoWAgNNho6UpK9B9NPm8mExnpoPL6VyouWzhQjy008dePLRPy/e/l71YcbLlwguLzvf0gQP0Dg5yxaZNBefJjjb/+6Ioyqx56mMI8SnmZO/gWH7fTJCU4XdRC/8XtnCdK8PzjluJ9bqIlV5UF8VcT/SK51LCtxqLPi1R3p90srmhp+Y56rUkV4zbUNvL7zfDE1b4by/YR885f3XAa10Cc4ckDqYU3u2z8n4fnJeCO53qjdtZaXAo4JVhsQKvjKvpTVlmUoQD9A0Oc9E5lfqtGNSSQDBiNI+pE6KxOB7X1KZsmc0m2lsaadcozo3FEwwNhxgcDrJzdz/DwTCSLCMKAj6vm9asSG/04XE7a+IKVq/4AyFWLJk/08OYMn70jf/ipve9jwAnaGJB6QWqYIQAQbq57YMf1Mz5zuXp/fvxeTzMaW8vOE9zo3rshqITdUIoEqGlcXYUnRtCfIrp7hlgZYVfYC2BlN88Ze/mrazecTf+YJATPT1EYjEiIyP4AwEe/dUPeDrh4hy7xO1tCRZbZWgs7QleacfMqfDcrjYdRUuUS4pAescJzflnOhpeCBOwOqP+3BCHxx+PctdFToJukZRZIGlR4xj7/h1h7rUebvPAq0bgyiSsmWGhXYp0JmMUldUJ/UPDmqLMYPoZmOEmVy6HHdcc+6TGRbIsE4zEGPIH6RscZs+Bo0SiIyiMFow2eGlp8p1WqS5DgTAXnaYRcVCj4k0spI+9NDAXkamx/FNQ6GU3Tpq4+qKLSs7/9P79nLV4cdF5mhsasFmtHDt5coLbytFTp1gyr/6e7mthCPEppm9wmMsvWF+z9eV3Mjxsgtuv3cq+JheL583D43LhdjpxP3Uv1zhl/qspQWMF3yk9YjxX5BYTsLWyHKyW+PZupEsWYRsIzvRQdKEl4ofdIo8tt3LiMifLT2Wwp0z0NJl4epGFGx5WrSzn7kuwJK1w1WLHjEe7S5FOZzDPAp/XM4X+oQBLF84pPaPBlDPoD9La1DDTw5iEKIpjvujLmXiNSKczE1NdntpHMpkGwG630trko6WxgZZGL02NXizm2SFBzoS6iV/88BM8/01vZYhDtLFiSrYRoY8og9x56626nqB09/aydvnySdNj8TgOmw1RFDGbTFyxaRP/fOghbrj6agD6h4bYc/Agb3/5y2v+HqaC2fEtmKUoioIkyzXPq1u9426e3LyV3zjhYStcH4c3d8dY1fwEjIzOVIPat2Ji/ERY4rt+G0fSIqtDJq4QoKlISmMhMT7dnt1HH4/TaQpovlaLscSBr3tgeQbOSYECNcu4kwX4+zl2Fg5keNkDSRpiCn/Y5GD3QgsXHEjRMtoWc+1x9cK3+uTdNdry1NE/FJjUidBg5hjwB7h445qZHoYBMDgcnNQAqN6xWLS7i4JaL+UfDjEUCPHM/iP4g2EyGQkFBa/bSXOjmubS0tRAg889rR1FFUXhuePHGQ6FcDkcLF+4EJv19Bbe+bQ3N/Omm27kR7/5PU0sxIytputXkOlhN1662LBKX/M2fyhEg3fikwh/MMgL3vY2Lt6wga9+5CMAvOpFL+JNH/sYX/rBDzhvzRp+8NvfsmLRIjatW1fT9zBVGEJ8CgmEIjRNQb7lb6/cyvd9sCQDXwyBR0dNj6Kg6SdeimzUO1eQx7d38+yIiWdTVl7pN/G4FT7mg3dEYV0RV8B8MV7r3HA99FoaWZLsmzSuWmFHFd8PW+FRK4Se52JRX4ZF/RnmDUlYihvVFOXJJVYcKYUL96cQUNvIv2a0BfZszc+sRbMrg9qRShtpQvVCKBzD5519zcUK4bTbcHa1Ma9rYs1U1tVlKBBiyB/k8IkeguHoeD66x62mujSq6S61bmDkDwb54G230Tc0xNz2dkLRKMdPnWLx/Plcf+WVvPCyy88YUf76G27gx7/5I/3sZw5n13TdwxwnSZRffeeLuuaXJIlQJILPM1FDWS0WWpua6Ggd782ydvlyvvaRj/DdX/2Kv95/P+etWcPH3vEOxGm8masGQ4hPId09A5NOOtVw/NQpvv6md/K0G94Qg41pfWI1LMM7+pw8z5Xmtd50VYIcIKmoFnh+SWTVaN7yBSn4uhs+FR53dNFCr+itVoQX2s7AFT4ujB4oayzlIACvj8FnvHBtAiyPxeluMfHkEiv/OMfEHL/E4lFh7krqd0UIuAR2LrHw8n+PjIlwYNandfQM+Ll80dyZHoYBjAqf2XHhOhNQmD2uD9WQ6+qyeF7nhNdkWSYUiY0VjT57+PiY9aJJFGn0eWhu9NHS6KWlwqLRv95/P80NDXz/s58da4eeSCZ55sAB7rzrLv6+40FefMU1BZffd+gQvYODXHTOOThstY0iTzdup5MPvvV1fPF736eFJdiozTVSIkMf+2hmEQvn6Et9M5lMPHnXXZOme1wu/nTHHZOmX7Jx46xo3qOFIcSnkBO9A1U95lUUhe/+6lec7OujZ2CAQ3v2cYUCXwrB6rP1CdXjaYEv+O2ssUn8a8RMusfGluTk+bLCtz8j8KOQlaSidu2UFAEZkBSQgZgscCgtssgisyU2fsJbOSrGH7XCDYmK33JNKCawI2ErJ3dNrRPBHBk+F4afOeGZy1y0yLAoA1ekwOs2s61F4YFVNhpiMgsGMogKxK0CzjlWToYzJM0C7SGJVSfSdATVu5oHV9nYeDiNb0QZE+GnA+FoDK/HNdPDMACGA2GaG0/fgrTZRCqdmTX501OJOCq2G30eluXdsEuSTCAcwT8condgmN2jRaMAJpO6XDaK3tzgxe1yaIr0JfPn89M//IHB4eGxKKvdZuP8des4b+1a/ufnv+Fnf7obp0vkmksumbT8tocf5q577iEjSdx83XW88SUvKemPXc/c+Lzn8bXv/R+97GEhF9RknYM8h0yG3/z4kzVZ3+mG8U2fQgKhaFVWYHsuu4GfNcALE3C1BO9Kq1Z2eqLFMRnuDFn5a8zCa70pXupJs22vmx+44Krk5LzlbNrIV4ZtdJplzrHLmACToGACRMAkgE2AFVYJlwjH+sYFrwLstcBbauCLWE00vJgIT1gs2FLpitddDq0yvD+qPjk4aVJtB/9hh2+E4GKnhYf/EaGn2cSJVhPIsK7diicNm21mjjwdo6fZzB83OXjxI3GaIzLH2sxc82T0tBLhWd/X2ZpWc7rRZzim1A1DgRAtjadnA5laYTKJqtBu9E0qLcxIEoFghKFAiO7eAXbtO0Q0Fh9rYtTU4KG5wUeDz82T+57F53bz0K5d3Dha7JdFEARWLVnG2hVL+fIPv8fju3dzyxvfiD0n8j2nvZ0L1q/n/a97Hd/62c/Y+s538s5XvYrrr7hiGvZC7bGYzXzhI+/iP7/4RWL4cVFd6mCaBIMc4B2vvJmmhobaDPI0wxDiU4QkyZhEoSqRIQKr05AUYE1a/bsUigL/GDFzR9DK+XaJn3WOMO87/yT2ni2syKjCsNuktkkHGBDhD3bVb3rlXje7vAr/3ZLApWNjuc1vdptVcb9cI0c8JMCPXNAgwxtGJr+ev069yAqIObu3VKrJsM9HUyike/0TtoW+/Z+PGXUf/9OmpqpkufBiD489EOGTA/dMmH/v5q2sW+3isQci+GIy92yw88LH47gTCm9Nnz4iHCAQjtLoNTyr64X+oQCrlk6th7CBPob8M2tdONsxm0y0Njdo7sNMRmI4pIr0p/Yd4Kk9h1m5YDVDQ3F+8cd7R9NdvKMpLz6GhkO88KoL+b+vfpXP3XEHN73vfZyzahUOm40n9+2jZ2CAV7zgBbS3tPC5972P3QcP8uUf/pAf/e53E+z0ZhNXbNqEi2Z62c0SLquqyU8/+xCx8OoXv7iGIzy9MIT4FNE76KejtfoitJfH4UseaJXgshIW4AdTIl8btpECPt+SYI1NHmtb7rp9G8LmrSQF8ItqQ5iHrfBXOzwvoQrxe+2wNSYw+IybQfSL4hTwExe8cmQ80p4AdlrhASscMkOnrEaFXzGiFjRqUW4k/L0DdmQE/rMxiWlf6XQTv8/H8L0nCJ1UbQHzW8kX4gkLfNcFz0/A5pR6I3N2Gt1OqyOCKuIX5BVqakW3s/aU51/iQXkgwr1n2wm6RGzp2nTZqyd6+41CzXpi0B+kdVNtC7QMKmNgOMiqZQtnehinJWazibbmBtqaG3jmwB4WzG3ik+98GzAaSQ9F8AfC9PQPsXv/EZ47dpLf/u1+TKLI5edeynlrNhKJhZHkDB97+9tZvWzZhFqdtcuX85MvfpG9hw7x+3/+c6beZlUIgsAdX/oQr/3whwnTg4/KLE0ThPFzjP9+1ztnff78VGII8SmiVoWaHllN+2gpUgCZ5UODdq5zZXiTL4VJYEyEZ1m9424uu2Yrv3ZARISVafhsGNpG1/2ivNzuYhHmrGheuD7K/9vnpk1Si0dBFZ4f9UKnBOvSanv2+2zwgrgq+IutrxwOpU2cFRd4V9zJ+8ywQiMan+vF3TPXTkdfUPO1QqJ8uxV+44R3xNTUkj84YI4Ef7fDTSOwWFIFee7TgXwuSsEjNviRE74ZGn3SUcTfOyvGN13iYTsgnO3EdRoaWfQO+Fm1zIjA1gsZSTLykuuEoWEjNWU6eObgQc5bM17HZTaZaG1qmODfHomO8OobrlZz0kMR/MEw/kAIfyDMnv3d7H62G0EQ8HlcY5H05gYvZy1Zgt1m43f33KOx5fpn3YoV+JhDL3vw0olQwTPhXvZgx8OLZmmaznRhnHWniJO9g5y9amnV69lmh8WjziQAz5jhW8+5eeP8EVbbVAUdl2F30kRKEfhJ2MobfalJIjzLZ/9xd9Ht5XfuLERu18xj7WmussosXJrm4Wfc3O6GVRm12PMuB5yfgo9GYF4B675KRPixXW7eZIEfu1SR/HU3vHxELRiVUT23JWDppR4e2RXjSIcZS7OFnoVm1h1NYc0ZSyER3i/CL5zw32E1ov+qf95FIBzG5/Hwjee/hO+51acLS2wSy4dtbMpJ+cnlRy6wKHBruLQIz5IV48sz8KS1srSYemfAH6hpsyuDysmM2mAa1AfpTAarxbg8TyXhaJSn9u3jjS95ScF5Uqk0Fosa7TaZxLGOoeQ1Msp2Gx0OhPEHwxw6dpJgOMqAf2gq38KU87M7Ps717/gP/BylhSVlLRtlkDC9fOeTnxxzozHQxvimTxHxZAqnvfpHMb90QrsEg6LqwtFtgn4TtB5z8ifgiE/iSFpkmVXm8pjAFQvi+L6lLcL1kN+5sxTHdrmZY4N/WuG5HhvbvWox6ONWNa/9GyFw1SCrQivafMQMCzJq1P0jEfiJE37qAlFhvMAUcL9yKSu7h/AKEn1LbNy1wsYnw9BQZFwK8GOnWijbKY+L5+bRYpNb/nk3127eShxIrUzyZNLE15tkPj8okpskMyDC0xb4RlAttC230+VlSfinW2GtrQoD8jpFkmXMZuMEXQ8MDYfqsovjmYisKFXl5BqU5r5HH+XW736Xqy64gMVzC9unDociNDeUfjKR2210aU4ax6ETJ/jxH39ZkzHPBPM6O2lmCf08SyPzMaHv0ayCQg+7cdPKRRs2TPEoZz+GEJ8CEsnatMPNZloMifDxUV/q18fgQz417/qsDLx4yMSyDFhHM5ZXf+8fVW+3XDF+SVIt+GwS1QZDd7hhUwpeGi+8jJ4o+B+iZvacsnN5kgkZajLwezvssMHnRmsvF0rwqckd4ceE73NHT7L7k7dxY0xd9jYPfDzMBNGcm6qye4GFnoUWNu8YYbWkXSS5esfdxN6zBYCz7TJH0iK7F6c5xy7RZZYZfMbNQTOclYYV66MFn1IUYuH6KAuBzydE/NLpFa1MJFNnTJOM2UD/4DDtRofTuiAcieEzLD1rTkaSOHT8OHfedRfPHjnCFz/wATauXl10maHh0Blv6fnbn36SK1/7JgY4SCfF91eWICeJE+CXX/ua4YqlA0OITwHdvQPM62wtPWMJzMB3A3DMBO2yaokH8L2gdtv0cqOtxShHjFtRI98Cak51VFC7fr6qCT4cUSPWWRauj6IosCshciwtstVTuBXn94bsnCfA57yqT/nSDEQEeMwKzTJ8NqRGtbMCOjfFZGGe8D3VP8S5X/o4zV98Je9T4JsBK19ymPhkvwkTqrgPOwTCThG/R+TRFVZuemCENxcQ4Vlct28bE+Ov96Z5W78DT0QhJgucOyeDR1RwK5Pz9cthg10eHeHpQ9/gsNHavo7oHwrUJJXOoHoGDceUipEkiSf37aO7rw9FUVAUhVP9/Txz4ADPHj5MR0sLV1xwAf/97nfrKh70B0Msmtc1DSOvXxq8Xt792ldw+09/TguLsVDcI11Goo89NDKflYsXT9MoZzeGEJ8CunsGJjUfqISssN5U9ZqmnuyNQUyEEyb4yqgmnpejs+efHeXnYQt/jFoQgKAkaArxg7vcxAVI+eAlcTX3+34bKK+4nk6Hg6+ddx6rliwZu9PWc4/eO+Dn4o1rsIwK5/c2pnhlr5P4WSP8+ZiTv9vBfZVadNoqw/uT8LKIPvGcFdnrgLv9floaGojF49z36KPc8+CDujuJFVrv6Yja2t4Q4vWC4VtdPwwMB42b1ArYffAg//XVr+JyOlm5eLHalVQQaGtq4k0vfSlrli3D6y6vU6Q/EObcdSunaMSzh1e84AX8z09/Qx/7mEfx7pV+DpMmwf99/xPTNLrZjyHEp4C+wWE2n6E2YNcmoEuC77ngrTFoHM3Dtq+J8WjCxJ+iFj7VnGClVeZ5J13EZCZ4lu9+2s2tXjUn3qGAW1FF/n/+8+6qxpWRJCyjxU/ZKPaL3Wm+EbDR65L5ll/Ek5MzXunThfZm1Y7P63bz4quu4sVXXVXVuE9Xegf8rF1pREvqBUmWMZlOr/Sn2crQcJB1K4zvhl4UReE3f/87d/zyl3ziHe/gygtq0w0SIBZP1KTWa7Zjt9n41Hvfyse/+U1aWIoD7Zv2DCn62c/rb9xKZ2v1WQFnCoYQrzGKopCR5Am+omcKz5rhO27VreQdMTUl5aQJfuqEE71Okgp8uDnJqlG3F4sAdzzn5oIUzB2tRbzTpea+3zqiJmMIVJ9yMxJPTHoM6bp9Gze+ewt9ksC1LoW1c9MTXjOYWmLxBG7n7G0DfTqRNtqp1xWRaBy3y/hu5JNIJkml07idTkRRRFEUTvT28v1f/5oDR4/y4y98gQVdtU0jEaiuKd/pxHWXXcbnv/kTetnNYi7RnGeA/YDAG268cXoHN8sxzr41JhiO0uAt7/FXPVJOsWaW58wQGA2q/cwBihPCAry1Ockrvv8nzCbT2ElNlmWWfeIT+J/cy+c9cHlS9R/vNsPbR/PNTdQm7/1U/xBzOlomTW/81jY+VvXaDcpFlmXDFaKOGDBykusOQ/xN5Kl9+/jQl79MPJkknkjgcqpl9i6Hg8vOO4+f3nZbzRvGpDMZw9UpB1EU+can38/bPvUpIgzgYWKflBQxhjjMLW96Q9kpQGc6hhCvMd29g8yvQSOfmaSQCC/WtGb1jrth81auT0Aa6DGpQrpVgnP++LdJ84uiyA8//3kADv3H1XzviAsR1bPbmrvOGnCqb4hF8zprsi6D6hkKhEe9eA3qgf6hYTpajJzkeiCZTGG1nobdu6rkF3/5C6980Yt4w403kpEkorEYsizTNGonOxUMByM0NZzZjin5bDr7bDy008tu3Fw5IaDSy14sOHjZ858/gyOcnRhJgTWmu2eAuTVwTJkpSkXCF66PTrAeXLg+OiaYs/9bUNu5z5XgHB1ieun//JNPLY/yqeXRMc/xWjrAqIWBRiv1esH4POqL/qEA7S2NMz0MA2BwOESrcZM6ibOWLGEoEADU7pcNXu+UinBQC5jPdOtCLe785keJEyTAibFpIwQI0s3nPvgfWCzGjWS5GEK8xviDYZpPw7vofN/vrCDPz6fOFdDliOnsenKFfa1IZySjS10dYQjx+mI4GKapQbu7rMH0MjhspAlp0dXWxqn+/mndpj8QpuU0vJZXy9IFC2hiIX3sRUYaa97jpImrL7popoc3KzHUSQ2RZBmTePoUd1QqiCtdbiqKJEcSSRw1aK5kUDv8gRAtRqSpbpAVBdFob18XDPiDbDD83Cfw1/vv5wvf+x7ve93rpnW7/kCIc1Yvm9ZtzhZ+8cNP8Pw3vZUhDmHHS4xB7rz11tNG+0w3xtm3hvQPDtN+muRa1joqPVP09A3RpVGoaTBzGMKvfkgmU9iMnOS6wR8I0WTcpE5g+2OP8a5XvYqXPO9507rd6Egcl9M+rducLbQ3N/Pmm26knwP08AxeutiwatVMD2vWMusi4t29vTM9hILs3n8Ej8vBoRMnSs9cp5w0wZKf3D6r30MuT+zZz5z2ltPm/cx24okk0ZGo8XnUCX0Dw0hy2vg86oR+/xDHTp2a6WHUFa1NTTxz8CAb16yZ1u0OBYY53N1d1TrqWa9Uy+tvvJE7f/NHksT41Xe+NNPDmdUIiqIopWebeQaGh7nhne8kFo/P9FAMDAwMDAwMDEricjj4/Xe+Q1vT6fG0PJe9hw4RjcXYdPaZ2cCwVswaIQ6qGA9Ho6VnNDAwMDAwMDCYYbxu92kpwg1qx6wS4gYGBgYGBgYGBganC0bFlIGBgYGBgYGBgcEMYAhxAwMDAwMDAwMDgxnAEOIGBgYGBgYGBgYGM4AhxA0MDAwMDAwMDAxmAEOIGxgYGJxBGPX59YPxWdQHiqIYn4XBjGEI8TLp7u3lmQMHSKfTAMiyjCRJMzyqM5svff/7PLxrF/FEYmyacWKdOXoHB7nzrrvoGxycMF2WZeMzmQGe2LOHh3ftIjN6nsq2oZZleSaHdcbyyNNPMxQIAExoCW58HtOLJEkcOn4cUD+H7GdhXDsMpptZ11lzpnly3z7+/u9/c/n553P5pk20NzfP9JDOaJKpFL2Dg3z75z9nbns7F27YwCXnnENLY+NMD+2MZSgQ4Dd//zv3Pfooq5cu5dJzz+W8tWuxmI3TzUzw6NNP84u//IW1y5dz/rp1XLRhAysWLUIUjTjMTHDb979PLB5n45o1XLxhA+etW0dbU5PxeUwzJ/v6uOl97+OsJUvYtG4dF65fz7oVK7DbbDM9NIMzDMNHvExO9vXxwJNP8sDOnew5eJAVixdz3ebNnLd2LV1tbTM9vDOWY6dO8eCTT/L47t2Eo1HWLFvG8y65hBULF2KxWGZ6eGckj+/ezYNPPsmBo0cRBIELN2xg87nnMq+jwxAd08xwMMiDTz3FE3v20Dc0RJPPx+Xnn8/G1auNm9YZYN+hQzy8axfPHjlCPJFg8dy5bD7vPFYsWoTX7Z7p4Z0xJJJJHnzyyf/f3p0HR1nneRx/d7pD0p2r0+ncd5qEhAbCEcMtBBAwyiEOslXrjMp4/jE7lu5aa3mUW+UcVeO4M1i64oGD1OzKpSgLLFQAQzgiuThyQBJyJ53upEOnc3SS7nT2DzClO67CbtmP2t/Xn/3Xp/pXTz3f5/t7ft+HytpaOq1WNBoNs7KymJ+bS0pCAlopyoUPSCH+/9BptVJcVka7xUJYaChmk4ll+flKx/IbExMTX9tOVKlUuN1uLtfXs//YMVq7ukhPSuKBu+9mZlaWwmn9w1fX5EsOp5PTFRUcKSlh2OUix2TioY0biTUaFUrpv9weD51WK8dOn+ZMVRXaoCDyZszgoY0b5YFVAc7BQa42N3O4uJj61laMej2rFi1iXUGB0tH8ypjbjc1up7ymhuPnzuFwOkmMjeWBtWuZazYrHU/8xMle8W0YcrmobWwkMjwcfXg4wy4X0QYDA0NDdNlsnCwt5fW//IVP33pL6ah+QaVSsfPAAVwjI0Tp9bR1ddHS1UVkeDhTU1NRq9UcPHkSU0qKFOI+olKp2PXZZ4SFhDA2NkZTeztWu53kuDjmmc1U1dXxH4cOsemuu6QQ9wHn4CCnKyrQBgdj6emhpbOT4ZERUhMSWJCbS3FZGe/t3cujmzcrHdUvWHp6sNhsuEZHaerooLO7G1VAAKaUFMJCQvjsxAlcIyNSiPuAtbeXkdFROm02rrW302O3E6rTsXjOHK40NfHpiRNkZ2RIIS6+d9IRvw1FZ8/y0rZtABgjI8mdNg19eDh9/f00t7ej0WjIzsjghSefVDip/3j6t7/lbFUV83NzWb14MXFGIx3d3Vx3OjFGRpIcH48pOVm2e33EOTjI/b/6Fa7RUQqXLeOOmTOZotHQZrEw7vWSGBtLclwc2RkZSkf1C+XV1Tz20kskxcayfuVKMpKSGHK56LLZCNHpSEtIICU+ntTERKWj+oW3P/qI7bt3M89sZtXChURGRGDr66N/YIAYgwFTSgop8fFEGwxKR/3Je/TFF6moqeGe5cuZnZ1NQEAAXTYbXq+XlPh4MtPSSEtMJESrVTqq+ImTQvw2XG1uZv+xYwwMDREbFUVmWhoLcnOJ0uuBG9u+Ho8HbXCwskH9SLvFwtmqKg4UFeH2eFizZAkbVq0iRm5kinB7PNQ0NlJ09izHz50j1mjkvlWrWLt0KUFTpigdz+84Bwc5d+ECh4uLqWlsZHZ2NpvXrmV+bq7S0fxSa1cXJ0pLOXLqFANDQ6xYsIBNq1djSk5WOprf+eLiRYrOnePz8+cxRESwfsUKCpctIzI8XOlows9IIf5/0Gm1cuzMGS7X16MLDmbVokXMnT5duq4Ku1xfz+mKCgaGhsi6+ZAUFx2tdCy/dqK0lItXrqBSqZiZlcVcs1ludD7yP9/Xt/X1caqsjOaODsJDQ5mTk4M5M1M6fgq5XF/P+UuXsDscxMfEMHf6dEzJyTK1w8f6BwYor66mprERj8dDRnIyc3JySIiJkXMTwiekEL8NrpERnENDhOl06LRa7A4Hnx4/Tnl1NQkxMaxZsoS8GTP+5rCa+H5UNzRwpamJ6MhIEuPiUKlUXG1q4uyFC5ytrGR4ZIRnH3mEzWvXKh3Vb1TV1eFwOokzGjFGRtI/OMiFujpOV1RQXl1NoEbD7599VjqyPnK5vh6VSkV8dDTaoCDaLBa+uHSJU2VlVDc0EGs08tbLL5MUF6d0VL/Q2NZGmE5HrNGI2+2muqGBs1VVFJeV0dTRwaysLP7tlVdk9+h75vZ46B8YQB8ejkatZsztpuzyZUrKyzlTWYmlt5e1S5fy6q9/rXRU4QfksOYtqqqt5XfvvMN0kwnX6Ci916+jDggg22QiNTGR4vPnOV5aysmdO5WO6jfOXbhA3bVrdNlstHZ1YdTrMWdmEh8dzV2LF3O0pIQhl0vpmH7lcHExlp4eGltbsTscpCclkWMykZGcTERYGMfOnJHRhT7iGR/nwwMHuO50cqWpCc/4ONNNpsnDy5EREZyrqiJEp1M6ql+w9fXxp507ue50cq2tDW1wMDMyM0mOi2NBbi6RERF0dHdLEe4D9S0tvLFrF3aHA0tPDwa9nukmEzEGA0vy8qisqaHHblc6pvAT0hG/RX39/RwqLkYTEIBGoyE8NHRyWopKpUIfFkZCTAwrFy5UOqrf2Hf0KBqNhjWLF6MNDsY5OIjNbsczPk6UXk+0wfCN4/TE9+f9fftIT0oif9YsdMHBdPf24nA6CQgIINZolNdSfGh0bIztu3dzx8yZZKWloQ4IoLu3F9foKLrgYBJjYwmVItxnumw2dh8+zNK8PGKjovB6vdgdDsa9XvRhYaQmJjJFXoXwicqaGkoqKliQm0uITofb42FwaIjAwECiDQYykpLkviF8Rjrit6C6oYEzlZVEhoezcuHCycOZQhnj4+M8//rrzDObGXK5aLNYJj+E8dX39KUI9x3X6Chv7NpFSnw8Nrud0bExQnU6EmJi5ENXCrjudHKgqAhDRAT269cJnzGDQI0GvTwIKcLa28sXFy9i0OsZHRsjOT4eQKbVKKDTasXW10d4aCgRYWHfOMFJ+pPCl2SP+Ba88sYbmKdOZUpgIL95+20Gh4cB8Hq9jI+Py0XrY/b+fjptNrYUFgLwxx07gBsF+ldJEe47Te3ttHZ18Xf33ENjWxtvf/QRgFwfCimvruZaezvrCgo4XlrKniNHAFkPpRw8eZI2i4U78/LY+cknnK6oAGQ9lPDOnj1YenqYkZnJ6x98QGNbG/D1tZB7h/Al6Yh/B6/XS1piIl02G2EhIdQ0NExu58q7rsoI1WqZk5PDtl278Hq9LM3LA26slUqlknVRQFREBImxsfznyZOo1WoyU1MBmODGugCo1WoFE/oXo15PemIilp4ePOPjxERFATcKDCkyfC9KrydEq0WjVjPock3u3H15bQQEBMi6+EhwUBBZN2eEd1ithN6cGuSdmACvV9ZC+Jy8I34LrL29fH7+PGNu9+TscLfHgzogQIo+hfQPDHDyiy8YcrlYOHs2GTKHV1ETExM0tLby/r595GZns2HlShmLp7B1Tz2FNiiIF596CvPUqfIgpCDXyAh//vBDunt7+ft165hnNsu9QyHdPT38y5tvEqLTcf/q1SycPVvpSMLPSUf8FsQajWwpLGRgaGhy6ypQI3+dktosFpra25mYmOC5P/wBgKmpqSyaM4f1K1YonM7/qFQqahsbUalUXLp6lbCQENYVFPBfJSVU1dUxf9YslufnS/HhI26Ph47ubh6+7z5CdLrJInx8fHyyKy5dPx9SqYiPieHnGzaQGBtLu8XCjo8/xjkwgDkzk+X5+dJM8CFTSgr/uHUrcGOazb8fPMjg8DAzMjNZMm8exshIhRMKfyLV5C1o6exk5yefMDI2hsfjmTxsM89sZsm8eXLS3cf6HA5+t307WwoLyZ81C61WS0J0NGNuN6UXL2Lt7eXhTZvkYcmH2iwWtu3axTMPP0x6cjJHS0r4h1dfZUpgIPHR0by3dy/RBgMzs7KUjuoXrjY3ExsVxezsbP75tdd4aONG7i0okK64Qqpqa/n0+HEe2riRhpYWfrN9O9PS08lKT+filSs0d3TwzCOPyFQhHyivrub8pUvAjevkzx9+SP/gICnx8XxSVMTV5mae3boVjVwrwkekPXULXt62DZ1WS252NnfecQeL584F4Ojp07y/bx+ukRGFE/qXy/X1eCcm2LByJfHR0SycPZvPz5/ngbvvZu3SpXxeVkZVba3SMf3K1eZmYqKiuLegAPPUqSzLz2fU7ea5xx7j2a1bWZafz479+5WO6TdqGxuZlp7Osvx8Xn36aQ6fOsW6J5/kjzt2UFJeTktnJyOjo0rH9BvXb37kCm5M4YoIDeX5xx/niS1beO255wgOCuK9vXsVTukfmjo6Js+wlJSXo1arefOll/jdM8/w/OOPU9/SwoGiIoVTCn8iLcPv0NjaSp/DwT/98peTv305//Vyff1kp+9na9YomNK/RBsMTAkM5K8HDzJr2jQOFBURGhICwJ15eXT39LDnyBHyZ81SOKn/yEpNJSI0lNc/+ICZ06ax7+hR5k6fTozBAIBOq8Xt8Sic0n+UV1eTcnNE3rT0dLa9+CJnq6o4d+ECh4qLGXK5uHf5ctYsWaJwUv+QZzZztrKSjw4dIsdkoru3l2GXC51WS2BgICqVSq4PH7H29jLkcjHkcjE8MsLy/Hz04eG4PR6yMzIwpaTQZbMpHVP4ESnEv4M+PJyM5GRe27GDn61ZQ5zRSHBQENEGAysWLCBUp+NPO3dKIe5D06dOZUthIWcqKzlRWkpYSAiPbt4MgNVu5/ylS2SkpCic0r+kJiaypbCQ3UeOYLXb+cWGDRwpKeGDjz8G4ExlJYXLlimc0n+kJSaycM4c4MZ74Rq1mjvz8phuMtHc0UF1Q4PMd/ehWKOR+1ev5vfvvovr4EGuO51U1taSlZZGp9UKwMObNimc0j8smjuXI6dO8cjzz9PQ2sqD69ZNPhTZHQ46rVbuX71a6ZjCj8jUlFtQXl3NXw8eJCI0lJSEBGKjotBoNPT09VHT2IghIuJrHXPhGz19fYyMjpIUFzd58Kyqro4zlZWsKyggNSFB4YT+rb6lhSOnTtHc0cGSefO4Z9kytMHBSsfyC2NuNxq1Wg7H/kB89eNiDS0tVNTWYrPb6XM40Gm1/GLDBuKioxVO6X8Gh4cZHRtDHxaGWq1mx/79DA4P8+D69RgiIpSOJ/yEFOK36GpzMyXl5dReu4bb40EXHIzD6aRg/nzuLSiQT0UL8Q1co6OouDG7V/wwyEdLfhi8N2dWix+OxtZWMpKTZV2ET0kh/i0mJiboHxj4m89CO5xOeh0OpqakYOnpIV46GUIIIYQQ4jZJIf4tqmpr2frCC+SYTGQkJTHXbCY3O5u0hATUajWDw8Pc88QTFO/apXRUIYQQQgjxIyOHNb9F/+Agd8yYwazsbLpsNt7dswer3Y42KIjsjAymBAZOTiYQQgghhBDidkgh/i1Myck8uGEDd+blfe33qro6Glpa+NedO/n5+vUKpRNCCCGEED9mUoh/i+T4eJLi4vB6vZO/BQQEMCcnhzk5Oew7epRp6ekKJhRCCCGEED9WUoh/B5VK9b9OF7hv1Srm5+b6OJEQQgghhPgpkMOaQgghhBBCKECGZQohhBBCCKEAKcSFEEIIIYRQgBTiQgghhBBCKEAKcSGEEEIIIRQghbgQQgghhBAKkEJcCCGEEEIIBUghLoQQQgghhAKkEBdCCCGEEEIB/w3VBMpKzGwFfwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 864x672 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# map\n",
    "plt.figure(figsize=(9, 7))\n",
    "ax = plt.axes(projection=cplt.projection_lambert_conformal)\n",
    "data_d.isel(time=90, height=0)[var].plot.contourf(\n",
    "    ax=ax,\n",
    "    robust=True,\n",
    "    cmap=\"Spectral_r\",\n",
    "    x=\"x\",\n",
    "    y=\"y\",\n",
    "    levels=10,\n",
    "    transform=cplt.projection_lambert_conformal,\n",
    "    cbar_kwargs={\n",
    "        \"label\": (\n",
    "            data_d[var].attrs[\"long_name\"]\n",
    "            + \" [\"\n",
    "            + data_d[var].attrs[\"units\"]\n",
    "            + \"]\"\n",
    "        )\n",
    "    },\n",
    ")\n",
    "ax.gridlines(\n",
    "    draw_labels=dict(bottom=\"x\", left=\"y\"),\n",
    "    color=\"lightslategrey\",\n",
    "    linewidth=0.5,\n",
    "    x_inline=False,\n",
    "    y_inline=False,\n",
    ")\n",
    "ax.coastlines(resolution=\"10m\", color=\"darkslategrey\", linewidth=0.75)\n",
    "ax.set_title(str(data_d.isel(time=90, height=0)[\"time\"].values))\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "ClimAg",
   "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": "3.10.6"
  },
  "vscode": {
   "interpreter": {
    "hash": "c4e659d1bedfc73d1fd31d7c0e2c79d7cc7aac22204994016c65a9e44686eb91"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}