Python for Finance New 8.ipynb

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 "cells": [
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   "cell_type": "code",
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   "metadata": {},
   "outputs": [],
   "source": [
    "# Provides ways to work with large multidimensional arrays\n",
    "import numpy as np \n",
    "# Allows for further data manipulation and analysis\n",
    "import pandas as pd\n",
    "from pandas_datareader import data as web # Reads stock data \n",
    "import matplotlib.pyplot as plt # Plotting\n",
    "import matplotlib.dates as mdates # Styling dates\n",
    "%matplotlib inline\n",
    "\n",
    "import datetime as dt # For defining dates\n",
    "import mplfinance as mpf # Matplotlib finance\n",
    "\n",
    "import time\n",
    "\n",
    "# Used to get data from a directory\n",
    "import os\n",
    "from os import listdir\n",
    "from os.path import isfile, join\n",
    "\n",
    "#Statsmodels is a great library we can use to run regressions.\n",
    "import statsmodels.api as sm\n",
    "# Seaborn extends the capabilities of Matplotlib\n",
    "import seaborn as sns\n",
    "# Used for calculating regressions\n",
    "from statsmodels.tsa.ar_model import AutoReg, ar_select_order"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dates & Other Constants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define path to files\n",
    "# For MacOS\n",
    "# PATH = \"/Users/derekbanas/Documents/Tutorials/Python for Finance/Stocks/\"\n",
    "# For Windows\n",
    "PATH = \"D:/Python for Finance/Stocks/\"\n",
    "\n",
    "# Start date defaults\n",
    "S_YEAR = 2017\n",
    "S_MONTH = 1\n",
    "S_DAY = 3\n",
    "S_DATE_STR = \"2017-01-03\"\n",
    "S_DATE_DATETIME = dt.datetime(S_YEAR, S_MONTH, S_DAY)\n",
    "\n",
    "# End date defaults\n",
    "E_YEAR = 2021\n",
    "E_MONTH = 8\n",
    "E_DAY = 19\n",
    "E_DATE_STR = \"2021-08-19\"\n",
    "E_DATE_DATETIME = dt.datetime(E_YEAR, E_MONTH, E_DAY)\n",
    "\n",
    "risk_free_rate = 0.0125 # Approximate 10 year bond rate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get Stock File Names in a List"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2887"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "files = [x for x in listdir(PATH) if isfile(join(PATH, x))]\n",
    "tickers = [os.path.splitext(x)[0] for x in files]\n",
    "tickers\n",
    "\n",
    "# On MacOS Only\n",
    "# tickers.remove('.DS_Store')\n",
    "# 2886 total stocks\n",
    "tickers.sort()\n",
    "len(tickers)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Function that Returns a Dataframe from a CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_df_from_csv(ticker):\n",
    "    try:\n",
    "        df = pd.read_csv(PATH + ticker + '.csv', index_col='Date', \n",
    "                         parse_dates=True)\n",
    "    except FileNotFoundError:\n",
    "        pass\n",
    "        # print(\"File Doesn't Exist\")\n",
    "    else:\n",
    "        return df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Merge Multiple Stocks in One Dataframe by Column Name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def merge_df_by_column_name(col_name, sdate, edate, *tickers):\n",
    "    # Will hold data for all dataframes with the same column name\n",
    "    mult_df = pd.DataFrame()\n",
    "    \n",
    "    for x in tickers:\n",
    "        df = get_df_from_csv(x)\n",
    "        mask = (df.index >= sdate) & (df.index <= edate)\n",
    "        mult_df[x] = df.loc[mask][col_name]\n",
    "        \n",
    "    return mult_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Markowitz Portfolio Optimization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Harry Markowitz proved that you could make what is called an efficient portfolio. That is a portfolio that optimizes return while also minimizing risk. We don't benefit from analyzing individual securities at the same rate as if we instead considered a portfolio of stocks.\n",
    "\n",
    "We do this by creating portfolios with stocks that are not correlated. We want to calculate expected returns by analyzing the returns of each stock multiplied by its weight. \n",
    "\n",
    "$w_1r_1 + w_2r_2 = r_p$\n",
    "\n",
    "The standard deviation of the portfolio is found this way. Sum multiple calculations starting by finding the product of the first securities weight squared times its standard deviation squared. The middle is 2 times the correlation coefficient between the stocks. And, finally add those to the weight squared times the standard deviation squared for the second security.\n",
    "\n",
    "$(w_1\\sigma_1 + w_2\\sigma_2)^2 = w_1^2\\sigma_1^2 + 2w_1\\sigma_1w_2\\sigma_2\\rho_1 + w_2^2\\sigma_2^2$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting an Efficient Frontier"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Stock Portfolio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Here I added the top 30 for each sector. You can obviously add as many as \n",
    "# you like\n",
    "# Then to keep the portfolio smaller I eliminated stocks that had an \n",
    "# allocation less than 1% to get this final list\n",
    "# I showed in part 4 of this series how to get the top sector stocks\n",
    "port_list = [\"GNRC\", \"CPRT\", \"ODFL\", \n",
    "            \"AMD\", \"PAYC\",\n",
    "            \"CHTR\",\n",
    "            \"MKC\", \"PG\",\n",
    "            \"PGR\",\n",
    "            \"NEM\",\n",
    "            \"CCI\",\n",
    "            \"COG\"]\n",
    "num_stocks = len(port_list)\n",
    "num_stocks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Merge all Stock Price Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GNRC</th>\n",
       "      <th>CPRT</th>\n",
       "      <th>ODFL</th>\n",
       "      <th>AMD</th>\n",
       "      <th>PAYC</th>\n",
       "      <th>CHTR</th>\n",
       "      <th>MKC</th>\n",
       "      <th>PG</th>\n",
       "      <th>PGR</th>\n",
       "      <th>NEM</th>\n",
       "      <th>CCI</th>\n",
       "      <th>COG</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",
       "      <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>2018-01-02</th>\n",
       "      <td>48.029999</td>\n",
       "      <td>43.599998</td>\n",
       "      <td>88.451561</td>\n",
       "      <td>10.980000</td>\n",
       "      <td>80.440002</td>\n",
       "      <td>348.970001</td>\n",
       "      <td>47.967422</td>\n",
       "      <td>81.579140</td>\n",
       "      <td>47.749058</td>\n",
       "      <td>34.842434</td>\n",
       "      <td>96.650520</td>\n",
       "      <td>26.996706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03</th>\n",
       "      <td>49.730000</td>\n",
       "      <td>43.389999</td>\n",
       "      <td>88.543671</td>\n",
       "      <td>11.550000</td>\n",
       "      <td>81.029999</td>\n",
       "      <td>353.029999</td>\n",
       "      <td>48.081146</td>\n",
       "      <td>81.480141</td>\n",
       "      <td>47.723183</td>\n",
       "      <td>34.550255</td>\n",
       "      <td>96.242355</td>\n",
       "      <td>27.118145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-04</th>\n",
       "      <td>50.070000</td>\n",
       "      <td>43.740002</td>\n",
       "      <td>89.063423</td>\n",
       "      <td>12.120000</td>\n",
       "      <td>83.110001</td>\n",
       "      <td>349.790009</td>\n",
       "      <td>48.384403</td>\n",
       "      <td>82.056091</td>\n",
       "      <td>47.714550</td>\n",
       "      <td>34.933739</td>\n",
       "      <td>95.124413</td>\n",
       "      <td>27.006050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-05</th>\n",
       "      <td>50.410000</td>\n",
       "      <td>43.529999</td>\n",
       "      <td>89.872673</td>\n",
       "      <td>11.880000</td>\n",
       "      <td>83.879997</td>\n",
       "      <td>350.880005</td>\n",
       "      <td>48.858246</td>\n",
       "      <td>82.110107</td>\n",
       "      <td>47.895683</td>\n",
       "      <td>35.061573</td>\n",
       "      <td>95.851990</td>\n",
       "      <td>26.865927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-08</th>\n",
       "      <td>49.529999</td>\n",
       "      <td>43.549999</td>\n",
       "      <td>90.767464</td>\n",
       "      <td>12.280000</td>\n",
       "      <td>84.639999</td>\n",
       "      <td>356.549988</td>\n",
       "      <td>48.910378</td>\n",
       "      <td>82.542084</td>\n",
       "      <td>48.042313</td>\n",
       "      <td>35.025055</td>\n",
       "      <td>96.135902</td>\n",
       "      <td>27.006050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-26</th>\n",
       "      <td>427.470001</td>\n",
       "      <td>142.970001</td>\n",
       "      <td>286.100006</td>\n",
       "      <td>107.269997</td>\n",
       "      <td>481.149994</td>\n",
       "      <td>797.400024</td>\n",
       "      <td>84.930000</td>\n",
       "      <td>142.419998</td>\n",
       "      <td>96.230003</td>\n",
       "      <td>56.630001</td>\n",
       "      <td>189.729996</td>\n",
       "      <td>14.710000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-27</th>\n",
       "      <td>437.109985</td>\n",
       "      <td>144.440002</td>\n",
       "      <td>289.779999</td>\n",
       "      <td>111.400002</td>\n",
       "      <td>484.700012</td>\n",
       "      <td>807.179993</td>\n",
       "      <td>85.220001</td>\n",
       "      <td>142.309998</td>\n",
       "      <td>97.489998</td>\n",
       "      <td>58.189999</td>\n",
       "      <td>190.970001</td>\n",
       "      <td>15.630000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-30</th>\n",
       "      <td>442.700012</td>\n",
       "      <td>144.449997</td>\n",
       "      <td>293.839996</td>\n",
       "      <td>111.320000</td>\n",
       "      <td>488.850006</td>\n",
       "      <td>814.200012</td>\n",
       "      <td>85.449997</td>\n",
       "      <td>142.929993</td>\n",
       "      <td>96.150002</td>\n",
       "      <td>57.509998</td>\n",
       "      <td>192.309998</td>\n",
       "      <td>15.740000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-08-31</th>\n",
       "      <td>436.980011</td>\n",
       "      <td>144.320007</td>\n",
       "      <td>288.720001</td>\n",
       "      <td>110.720001</td>\n",
       "      <td>488.899994</td>\n",
       "      <td>816.659973</td>\n",
       "      <td>86.290001</td>\n",
       "      <td>142.389999</td>\n",
       "      <td>96.339996</td>\n",
       "      <td>57.990002</td>\n",
       "      <td>194.690002</td>\n",
       "      <td>15.890000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-01</th>\n",
       "      <td>438.709991</td>\n",
       "      <td>144.940002</td>\n",
       "      <td>292.890015</td>\n",
       "      <td>109.989998</td>\n",
       "      <td>492.000000</td>\n",
       "      <td>818.440002</td>\n",
       "      <td>87.400002</td>\n",
       "      <td>143.839996</td>\n",
       "      <td>96.410004</td>\n",
       "      <td>57.880001</td>\n",
       "      <td>197.949997</td>\n",
       "      <td>16.260000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>933 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  GNRC        CPRT        ODFL         AMD        PAYC  \\\n",
       "Date                                                                     \n",
       "2018-01-02   48.029999   43.599998   88.451561   10.980000   80.440002   \n",
       "2018-01-03   49.730000   43.389999   88.543671   11.550000   81.029999   \n",
       "2018-01-04   50.070000   43.740002   89.063423   12.120000   83.110001   \n",
       "2018-01-05   50.410000   43.529999   89.872673   11.880000   83.879997   \n",
       "2018-01-08   49.529999   43.549999   90.767464   12.280000   84.639999   \n",
       "...                ...         ...         ...         ...         ...   \n",
       "2021-08-26  427.470001  142.970001  286.100006  107.269997  481.149994   \n",
       "2021-08-27  437.109985  144.440002  289.779999  111.400002  484.700012   \n",
       "2021-08-30  442.700012  144.449997  293.839996  111.320000  488.850006   \n",
       "2021-08-31  436.980011  144.320007  288.720001  110.720001  488.899994   \n",
       "2021-09-01  438.709991  144.940002  292.890015  109.989998  492.000000   \n",
       "\n",
       "                  CHTR        MKC          PG        PGR        NEM  \\\n",
       "Date                                                                  \n",
       "2018-01-02  348.970001  47.967422   81.579140  47.749058  34.842434   \n",
       "2018-01-03  353.029999  48.081146   81.480141  47.723183  34.550255   \n",
       "2018-01-04  349.790009  48.384403   82.056091  47.714550  34.933739   \n",
       "2018-01-05  350.880005  48.858246   82.110107  47.895683  35.061573   \n",
       "2018-01-08  356.549988  48.910378   82.542084  48.042313  35.025055   \n",
       "...                ...        ...         ...        ...        ...   \n",
       "2021-08-26  797.400024  84.930000  142.419998  96.230003  56.630001   \n",
       "2021-08-27  807.179993  85.220001  142.309998  97.489998  58.189999   \n",
       "2021-08-30  814.200012  85.449997  142.929993  96.150002  57.509998   \n",
       "2021-08-31  816.659973  86.290001  142.389999  96.339996  57.990002   \n",
       "2021-09-01  818.440002  87.400002  143.839996  96.410004  57.880001   \n",
       "\n",
       "                   CCI        COG  \n",
       "Date                               \n",
       "2018-01-02   96.650520  26.996706  \n",
       "2018-01-03   96.242355  27.118145  \n",
       "2018-01-04   95.124413  27.006050  \n",
       "2018-01-05   95.851990  26.865927  \n",
       "2018-01-08   96.135902  27.006050  \n",
       "...                ...        ...  \n",
       "2021-08-26  189.729996  14.710000  \n",
       "2021-08-27  190.970001  15.630000  \n",
       "2021-08-30  192.309998  15.740000  \n",
       "2021-08-31  194.690002  15.890000  \n",
       "2021-09-01  197.949997  16.260000  \n",
       "\n",
       "[933 rows x 12 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mult_df = merge_df_by_column_name('Adj Close',  '2018-01-01', \n",
    "                                  '2021-09-01', *port_list)\n",
    "mult_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot Growth of Investments over Total Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x288f028c7f0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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3vPrqqyxYsIAJEyaQlpbGp59+SlpaGgCLFy9m9erVDBs2DLvdTkZGBocPt75Ed8aMGbGpxCIiIiIicurybN8OhkF8ZHZm/NSpgJXEhj0eHIMHYwYDTSqroarqJmP0l2S1s3cDPmWsWrWKxYsXA1ZyumrVqti1BQsWsH79elatWsV3v/vdE47Vx4vMIiIiIiLSSbzbPyfutCzsSYkAODMzsaekcHTFCuo3b8bmdhOXdRrVa9fi22MdYRMoLGwyRn+ZBtznK6snqoB2hbKyMt566y1yc3MxDINQKIRhGNx4440AuFwuZs6cyX//93+zY8cOXnvtteOOt3XrVmbNmtUdoYuIiIiISC9lmiaezz8nad68WJthGMRNmUz9h5sjN4Vx55xB3aZNlD/7HMP/awWBwkIcw4cTPHIEUGX1lPbSSy9x7bXXkp+fT15eHocOHWLs2LEUNNqR6/bbb+fBBx9k0KBBxx3r5Zdf5o033uCqq67q6rBFRERERKQXCxQeJlRejnvatCbtcWPHxV4HS0oY/K//ihEfj+nzYQaDBIqKSFl0MRkPPoBz9ChsCQndHXqX6POV1Z6watUq7rrrriZtl112Gffff3/sfXZ2drNdgKMeffRRnn32Werq6pg6dSpvvfUW6enpXRqziIiIiIj0bt7tnwHgnnZ6k3bXmDGx14GiYgyXC2dmJmGPh8DRIgiFcGVmknLxxaRcfHF3htyllKy2w8aNG5u13XLLLdxyyy0t3r906VKWLl0KWOesrlixouuCExERERGRPsmz/XOMuDjixo9v0m4fmNrwJrLfjS0+nrCnPrZe1ZmZ2W1xdhclqyIiIiIiIr2A5/PPiZ8yJXYUTdSAc88l5fLLcKSmknzRRYC1LtX0eJWsioiIiIiISNcKHDlM4uyvNGu3ud1k3HdfkzYjwU2ovMJKVg0D57Bh3RVmt9EGSyIiIiIiIr1AuLYOW1JSm+61xbutNauFhTiGDsVwubo4uu6nZFVERERERKSHmaZJuK4OW+R81ROxpgFbyapzRP+bAgxKVkVERERERHqc6fVCKIQtsW3JqpHQUFl19cP1qqA1qyIiIiIiIj0uXFcHgP0kpgGHamsJVVf3y82VQJXVdrPb7eTk5DB16lSuuOIK6uvrAQgGgwwePJi7774bgDfeeIM5c+ZgRraYDoVC5OTk8MEHH3D06FEWL15MVlYWU6ZM4cILL2T37t099kwiIiIiItIzwrW1AG2urNrcbggEIBRSsipNud1utm3bRm5uLi6XiyeffBKwktOJEyfywgsvYJom559/PqNHj+bpp58G4Fe/+hVnnnkmc+bM4ZJLLmHevHns27ePnTt3cv/991NUVNSTjyUiIiIiIj0gVGtVVtu8wVKCO/Y6bsKELompp2kacCeYO3cu27dvB2DVqlXceuutPPHEE2zevJk5c+bw6KOP8vWvf505c+bw61//mo8++oi3334bp9PJsmXLYuPk5OT01COIiIiIiEgPik4DtiW0cc1qfKNk9bTTuiSmntbnk9VNL+ym9FBtp445eGQSc69s218ngsEg69atY8GCBXg8HjZs2MBvf/tbKisrWbVqFXPmzGH48OF8//vfZ86cOaxcuZK0tDRyc3OZOXNmp8YtIiIiIiJ9U7guMg24rZVVt5WsGk5n7HV/o2nA7eTxeMjJyWHWrFmMGjWK66+/nrVr1/LNb36ThIQELrvsMtasWUMoFAJg+fLlhEIhli5d2rOBi4iIiIhIrxNds2pv49E1htOqO6YuXtxlMfW0Pl9ZbWsFtLNF16w2tmrVKt5//33GjBkDQFlZGW+//TbnnnsuNpsNwzBi92ZnZ/PSSy91Z8giIiIiItJLxaYBt3GDpQHnnUfGI3aSF3yrK8PqUaqsdpLq6mree+89Dh48SF5eHnl5eTz++OOsWrWqxfvnz5+Pz+fjqaeeirV9/PHHvPPOO90VsoiIiIiI9JBAKMwPXvqML45WA43XrCa0qb/N7SZl4UUYjj5ff2yVktVO8sorrzB//nzi4uJibRdffDF//etf8fl8ze43DIM1a9awfv16srKyyM7OZsWKFWRkZHRn2CIiIiIi0oU+3FfGx3nlzdr3FtfywicFPPz6lwCEvVbOYPTT9aft0X/T8C5WW9t0U6elS5c2W4+alpZGSUlJq30yMjJ44YUXuixGERERERHpWVc9tRmAvAcuirXlldZxwWObANjwRTF7i2tJ9nkxnE4Mm+qJUfpOiIiIiIiIdIF6fzD2uqSmYbblK58WxF7HOWw8/d5+wl4fRnx8t8bX2ylZFRERERER6QK7jtTEXm/Jb5gKPDDRFXt92cwRvPxpIZ7aOoxGSwpFyaqIiIiIiEiX2Hm4Kva6qLqhslrlCQBw6znjueSMTPzBMOUVtdg6MVmt8wUJh81OG68nKFkVERERERHpAjsOV5Mc78BmQGltQ7JaWR9gQJyD286bwOhB1u6/3tr6TpsGXFLj46v3b+ClLQUnvrkXU7IqIiIiIiLSBXYcrub0ESmkJcY1SVarPQFSEpwApCfFEe+04avzdFpl9cUth6jxBcltVNnti5SsioiIiIiIdLJAKMyXR2vIzkhhcJKL0lp/7FqlJ0BqJFk1DINRaQkE6j2dsmY1HDZZ/dEhAHYX1Zzg7t5NyWo7HT16lMWLF5OVlcWUKVO48MIL2b17N1OnTm1y34oVK3jkkUdYvnw5OTk5TJkyBbfbTU5ODjk5Obz00kssXbqUsWPHkpOTw/Tp09mwYUMPPZWIiIiIiHSGvcW1+ENhsjOSGZzUtLJa5QmQ4nbG3o8cmEDI58OI73iy+t7eUg6W15MU52Dz/nLuePGzDo/ZU3TOajuYpskll1zCkiVLWL16NQDbtm2jqKio1T6PP/44AHl5eSxcuJBt27bFrq1du5aHH36Yyy+/nLfffpsbbriBPXv2dO1DiIiIiIhIl9lxuBqA7Ixk3k5ycfBgfexaZb2fScOSY++HpsRj+HzY4jq+ZnXVRwdJS3QxYWgSm/eXM3HogA6P2VOUrLbD22+/jdPpZNmyZbG2nJwc8vLyOjz2nDlzKCws7PA4IiIiIiLSc3YdqSbeaWPs4CSGJMdTVO0lFNmdt7TWH1uzCta6VVvAD50wDXhLfgXfnDiEhdOGc6jcw5WzRnZ4zJ7S55PVt5/5HcX5+zt1zCGjx/HNpTe0ej03N5eZM2e2eG3fvn3k5OTE3h89epQ77rijzZ/9+uuvs2jRorYHKyIiIiIivU5xjY/hKW7sNoNJwwbgC4bZX1JLWZ2fKk+Ar44bFLs3fUAccaEAflvH0jPTNKmo9zMkOY5vThrC+3fN7+hj9Kg+n6z2NllZWU2m+K5YsaJN/e68805+8IMfUFxczObNm7soOhERERER6Wr+YJiSGm9sE6WpmSkA5B6uYt3nR0l02Tl38pDY/UMGxOEMB/HanC2O11a1viCBkElagqtD4/QWfT5ZPV4FtKtkZ2fz0ksvdeqYDz/8MJdeeikrV65kyZIlbNmypVPHFxERERGR7nHdMx+zeX8550yyEtJxgxNxO+38/r08Pi+s4s5vTSTB1ZCKpQ+IIxQK4DHsHfrciroAAAMT+0eyqt2A22H+/Pn4fD6eeuqpWNvHH39Mfn5+h8a12WzceuuthMNh/v73v3c0TBERERER6WbeQIjN+8uAhqTRYbdxVtYgPi+sYmSam+u/PrZJn/QBcbhCAWo7WEssr7eOxxmY0LEKbW+hZLUdDMNgzZo1rF+/nqysLLKzs1mxYgUZGRmdMvYPf/hDHnrooU6IVEREREREutOOw9UEIxspNU4az50yFID/vGAy8c6mFdS0eAdOM0Q9Ha2sRpLVflJZ7fPTgHtKRkYGL7zwQrP23NzcJu+PXbM6ZsyYZvc888wzTd5fdtllXHbZZZ0Sp4iIiIiIdJ9thypjr532htrgFTNHMGHoAGaOHtisT1zYmr5b39HKaiRZ7S9rVlVZFRERERER6SSNk9V6fyj22mG3tZioAph+K8ms62B6VlLrA2CgklUREREREekuwYoKTNPs6TDkBLYdqiDRZU3nHTs4sU19zIBVWa0z25+emabJy1sKmDRsAMnu/jGBVsmqiIiIiEgXq//4Y4ofeQQzHG5Xf39+Pnvmnk29jjjs1cpqfRwq93DLOeN5+d/mcM1XR7epn+mPJKsho92ffbjKy57iWq6aPQrDaP84vYmSVRERERGRLlb82GOU/c/T5P/zNYTr60+6f/3WrRAM4tu/vwuik87yWYE1BThnZCozR6dhs7UtaTQD1jTg2tDx79uwq4jCSk+L145WWe2jByW0MdreT8mqiIiIiEgXcwwaDIDn00+txPMk+XbtAiBUVtapcUnn2nawEpsBUzNTTqpfdBpwTbj19CwYCnP9Hz7hyic/bPH6kSovAMNS4k/qs3szJasiIiIiIl0sVFWFa6x1tmY08TwZ3h07AQiWKlntzbYeqmTC0AEkxp3cmtHoNODqYOv3RJPR1iur1vXhye6T+uzeTMlqOxmGwTXXXBN7HwwGSU9PZ+HChYB1HM1NN90EQDgcZsmSJVx33XWYpsm6deuYNWsWkydPZtKkSdxxxx098gwiIiIi0j1CVVW4Ro/GkTEc786TS1bNcBjvF18AECwt7YrwpBOEwyafHarkjFGpJ903Og24wm9SFtnR91gHSusAsLcytfholZd4p63fbK4ESlbbLTExkdzcXDwe6y8b69evJzMzs9l9pmmybNkyAoEA//M//8OOHTu46aabePbZZ9m1axe5ubmMGzeuu8MXERERkW4UqqzEnppK/KTJscSzrQKHDhGurQUgWKZktbfKK6uj2hskZ2R7klWrshqwOfiv13Y2u74lv4Jrf/8RAG6nvcUxjlR7GZYc3282VwIlqx1ywQUX8Le//Q2AVatWcdVVVzW759Zbb6WsrIw//vGP2Gw2HnroIe655x4mTZoEgMPh4MYbb+zWuEVERESke8WS1cmT8R84cFKbLHkj04Zdp2UR0jTgXit6vur09iSrkWnAiYnxHKpo+rtR6wty50ufxd7HO1tO4XYfreG0IUkn/dm9WZ+vEVe+tg//4bpOHdOVkUjqt7NOeN/ixYu59957WbhwIdu3b+e6665j06ZNsevPP/88kydPZuPGjTgc1rc6NzeX22+/vVPjFREREZHeK+zzYXo82FNTiRt/Gpgm3i+/JOGMM07Yt+bNNyn8/m3gcJA4ezZVr/6lGyKW9th2qJJEl53xQwacdN/oNODp49J5tdLb0G6a3PniZ+SV1nH+lKG8sbOIGm8Q0zSbVFDr/UH2ldRy4enDO/4gvYgqqx0wbdo08vLyWLVqFRdeeGGz6zNmzCA/P5+PPvqoB6ITERERkd4gVGlV3OypKcRPngw0VEtPpOCmm62+ycnYU1MJezyYptnq/cGSEszQCc4/kU4VCIW58rcf8sKm3cwc4mp1TenxRCurg1KTKKrxEghZ5/E++4+DrMs9yt0XTOZ3187irgsm4QuGqfc3/RnvOlJD2ITsjOSOP1Av0ucrq22pgHal73znO9xxxx1s3LiRsmO2Ep80aRL33nsvV155JX//+9/Jzs4mOzubLVu2MH369B6KWERERES6U7C4GAD7oEE4hg/HnpKCb1fb1q3GjT8N3569YLNhS0gA08T0eDASmp+l6S8oZN+555J++78z+F//tVOfQVqXV1rHRwfK+cX7v2Pi64Uc2nk2KYsuJvn889s8RnTN6pCBiZhmJUervIxMS+CTvHIyU938y1xrJ+nBSXEA7C+p4/QRDcfj7CmqAWDSsP6VrKqy2kHXXXcdP/7xjzn99NNbvH7WWWfx5JNPctFFF3Hw4EHuvPNO7r//fnbv3g1YOwX/4he/6M6QRURERKQb+fbtAyAuKwvDMIibPLnNlVXniJEAjFj5GLbERIBW17vWbngTAP/efR0NWU7C3uJaME3GVh/GNWo03txcCm+5lWB5eZvHiCar6WnWFOLDkeNpqjwBBiW5YlN+z5k0hOR4Bw/9/YsmFfb9pXW4HDYyB/afY2tAyWqHjRgxgltvvfW49yxcuJCf/OQnLFiwgMzMTH75y19y1VVXMXnyZKZOncqRI0e6KVoRERcIIxwAACAASURBVBER6SrB0lL2X3Ipu7/2dfZ9awHhOmtfFf++feB04ho1CoD4yZPx7d4dS1COx/R5cU+fTsKMGVZlFWLjHqv2nXcBcI4e1RmPI220r6SW8/M/Ij4UYNDiKxly+78DEK6pafMYpt9aszpkkLVB0uGqhmQ1xe2M3Tcw0cX3z53Apj2lbNhVHGvfX1LL2EGJ7ZqC3JspWW2n2sj24Y3NmzePtWvXArB06VJ+/etfx65973vfY+fOnQwaNIiFCxeyZcsWdu3axc6dO3n44Ye7LW4RERER6XyeHTvY/52L8e3ahXNEJv78/FhF1bdnL3FjxmBENtyMnzIZ0+/Ht//ACccNe30Y8fEAsam/LVVWA0VF1G3eDDQkPsdT/NhjFD/2WNseTo5r65eF3LbtRQCcmZkYbqu6GY4ccdkW0T9cDItVVq1Nlqo8AZIbJasA18wZTVZ6Ig+83jCVfH9JHePSE9v/EL2UklURERERkQ4quOlmQpFpn+k33QSAPy8PsKYBu05r2GclusmS74sTTwU2vV6MeGudov0404CrXv0LhK1NeUzfiZPV6r++RsUf/9SmxFZat+1QJZ9+2TBL0pmZic0d/aPCySer7iQ3aYmu2DTg6mMqqwBOu40FU4dxoLQO0zTxB8Pkl9crWRURERERkeYaT/l0nzEDbDb8eXmEPR4CBQXEZZ0Wu+4aOxbD7abksZUnPG817PNhi7Mqq61NAzZNk8pXXibhzDOxpaScMAENe70EDh8mXFdH/ZYtJ/Wc0tT2gkriQw3fb+eIEdgSopXVtp+lG/2ZGU4nGanxHK60dn0+dhpwlNtpJxQ2CYRMDpbXEwqbZKX3rzNWQcmqiIiIiEiHhX2+2Gt7UiLOESPw5+XhP3AATJO4RpVVw25n0PXXEzh8GM/2z1sd03fgAP78/FhltbVpwJ5PPiGQf5CUyy7F5nJh+n3NxmrMn58Pkc15ajduPKnnFKjzBfnlm7sJhMJ8ebSGQQ7rezn07ruwJyVhi04DPsEfIhqLVlYNp5OMFDeHK714AiECIbPFZDXeaQfAGwyxv8RanjhOyaqIiIiIiDRW+uSTcMxmSY70dILlFU12Am4s+aILAQgWF7U4phkKsf+CCyEYxBZvJT+2hMg04LqmSVDtu++C00ny+edjuFwnrKx6c3dYMWYMp+btjcc9t1Wa+8X63fzyzT289tlhdhfVMD7ZWovsGjMGaKiAmye7ZtXhwLDZyEh1c7jSQ5XH+p06brLqD7G/1Kq0axqwiIiIiEg7+fbu7ekQukT9Rx83a7MlJRKuqcG3dx84HLhGj25y3Tl0KGBtjBTl23+AkpUrMcNhatavj7VHK6u2xJYrq/78g7gyM7ElJGDExRE+wZrVsqeeIm78eAZddz2Bgwet6q+0WUWd9f0Nhk2+PFrD2AFW4mhE/qhgnMSa1VBVFWY4jOn3YzitpDQjNZ4aX5DCCqt/a9OAATyBEPuKaxmcFEdyfPP7+jpHTwcgIiIiIv1f9RtvUHjLrWT+aiXJ553X0+F0qmBZGUnz55Mw+8xYEmpPTCKQl49v315co0djuFxN+tgSErANGEDwaEOyWnTfT6n74ENCNbVUrFrVcG90zWp0g6Vj1qz6Dx3COco6j/VEldVQTQ3+vDyG3HE7A+Z/k6L77qP27Y3EjRvXge/AqcUfsjayKq/zU+0NMnqYlTja3NG1xW3bDThYXs7ec84lftIkjPi42O9IRqrV/5dv7gFgeEp8s76xymogzP7SOrL6YVUVVFltN7vdTk5ODlOnTuWKK66gPvIXrqKiIq6++mrGjRvHzJkzmTNnDmvWrOnhaEVERER6luezzwDw79vfw5F0vmBpKY70dAYtXUryBRcAYEtKwp+fT+2bG5pNAY4Jh6l47jny/vmfKXv694RqrSS04k9/InH2bAYsWAA0VFYNpxMcjibJqmmaBA4exDXSOlvViHNh+lpfsxo4bO1c68zMxJmRQdzEiVq3epICkWR1e0ElAJlu62zT6BFDDWtWWz4PN8q7Ywemx4N3xw7qP9xMuKoKaEhW39tbCsCUjORmfd0uK43zBKw1q/1xvSooWW03t9vNtm3byM3NxeVy8eSTT2KaJosWLeLss89m//79bNmyhdWrV1NQUNDT4YqIiIj0KNNjnRtpOPvXxD4zGCRUXo5j8OAm7bYBDcmDe8YZLfa1JVtJSLimluKHH8a7fTsAaUuWMPK3T8bGtEXPWTUMnMOH4y84FBsjVFlJuK4OV6SyanO2XlkN1daRt3gxAM6MDACS5s2j/tNPCUUSJTkxf9BKVj/JqwBgeJyVrEaTVMPhsCrcJ6iser+wzkkd/cc/NGnPjCSrUXEOe7O+8ZG2o1VeKuoDqqxK6+bOncvevXt56623cLlcLFu2LHZt9OjR3HzzzT0YnYiIiEjPC9VaR7uEqqp7OJLOFSwvB9PEkd40WbUnWcmqMyODQUuXtth31P88xZgX/sy4v7zKoBtuACBhzlcZevddGE4ntkhF1YxU8gDixo/Ht2dP7H2owqru2QdZn2/ExRFuZTfg+s0fxhIox/Dh1ufNnAGhUGwjKDkxXyRZLa7xkT4gjgTT2ggp+kcFsBLXE61Z9X25G0fGcOKnT2/Snp4Ux3emZ3DV7FH86frZLfaNd1nJal6ZVb3NOCbB7S/6/J+21q1bx9GjRzt1zGHDhnFBZArHiQSDQdatW8eCBQvYsWMHM2bM6NRYRERERPqDQOFhAIJlpT0cSecKlVrP06yymmglq/Zj2htrPD04fspkwKqyRhmRtaqm19vQZ8J4at95h7Dfj83lIlxjJf/25AFWH5cL0990Z+Koxps5ReN1ZmZa1woPg/4d2yYV9Q3f34lDBxD2WJVuw92QMBoJCVSvW0egsBBXVhbJF16Ie2p2k3EChw/jGjUawzDA4YBgEACbzWDlVS1X46OildWCCmsp4qBE1/Fu77NUWW0nj8dDTk4Os2bNYtSoUVx//fXN7lm+fDnTp0/nzDPP7IEIRURERHqPwBErWQ2VlfdwJJ0rWFICtJCsRiqrjattxxNNXM1wKNZmxFmV1bCvUbI6bhyEQgQiy8xC1TWRzxsQ69PamlV/fj4AQ+64HcNmpQHOSIU1UFjYpjgFyusavr8Thg4g7LUqqLbIzwusymqoooK6Dz6g4k9/4sjddzcbJ1haGvu9mfD+e5z27jttjsEdqaweKrc+e/CAuOPd3mf1+cpqWyugnS26ZrWx7OxsXn755dj7xx9/nNLSUmbNmtXd4YmIiIj0GqZpEiqxKpDBsrIejqZzBSOVVfvg9Cbt0Z17DXfbklVXVhZpS5aQctmlDWNEKnVmozNc7QMHAhCqtNaYNq+sOltds+rPzydu0iQG/cu/NHxGQgL2gQMJHD7cpjhPdeGwSWltw/d30rABmHt84HTGjp4BsKcNhP2QOHcuiV/9CkX3/xx/fn7sCCPTNAmWlMSSVXtKCs1XprYuenRNtLI6OKl/JquqrHai+fPn4/V6eeKJJ2Jt9cecgyUiIiJyqglVVsYSrlBlZQ9H07mCJdFpwIOaXohUSG3xbVtLaNhsDL37LuInTIi1pV52KSmXXMLgRvuh2CObMoWqqyJfI5XVAVa74Wp9N+BAXn6z817BmgqsZLVtyur8hMJm7P0Zo1IJez3NKujxU6YA1vc2ce5cAOo/+SR2PVxXj+nx4Ehv+keOtop3WmlcQYUHl91Gcnyfr0G2SMlqJzIMg1dffZV33nmHsWPHMnv2bJYsWcKDDz7Y06GJiIiI9JjoVFlbQkKTKmF/ECwtxTZgQLNkJbre1Dkis91j2xISyPj5/TjS0hraojsIV1sV1dAxlVWbK67FyqoZDOIvLGw5Wc3IIFBYiBlZMymtK67xNnmflZ6E6fE2+/k7hw6zXoRCuEaOBIcDf/7B2PVgSTFAs4252ip6zqovGGZQksta99oP9c8UvBvU1ta22D58+HBWr17dzdGIiIiI9F7RZNWZmUGwvKKHo+lc0TNWj5X0zXkMv++nJH/72536efaUFMDaVTlQXEzJf/8CaDjj03C5CLeQrAYKCyEYbDVZrXnjDb6YejqTdu6IrWeV5oprrKr1tXNGM2KgG5vNIOzxNNlcCayqeN3mzaRddx2Gw4ErMxP/wYZkNbYxVzsrq3EOG4YBpgnp/XS9KihZFREREZEuFtuEaPhwAkXFPRxN5wqWljTbXAmsGXepl1/e6Z9nH2BVUEPVVRQ/9HCTz4PIBkstJKvRzZVcY1pOVqNCZWXtTqBOBcXVVmX1hrPHMWJgAgDhmprYUUVR9tRURj31u9h75+hRsZ8BNKzdtqcdM328jQzDwIzMRj538tB2jdEX6M8mIiIiItKlYpXVjIx+N9U0VFLaYrLaVQynE1tCAnUffEj12rXNr7ucEArFvs+1776LZ/t2/HmRZLWlymqjqcraFfj4dhy2pl03rmaGqqqwp6Yct59r5CgChw419Ims3bYPTG13LBeePowpw5O5+iuj2j1Gb9ehZNUwjNsMw9hhGEauYRirDMOINwwjzTCM9YZh7Il8Hdjo/rsNw9hrGMaXhmF8q+Phi4iIiEhvFywpwZaYiD05pV+uWW3vusP2sqWk4NmyBfug5lW5aIUvVGNtvHTohv9H3pXfxX/woPUzaKGPo1GbNlpq3fqdRfzxw3yunDWCOEfD3r2hqipsKcdPVh3pgwnX1samaEeTVUdq+5PV3/zTTP7v1rn9didg6ECyahhGJnALMMs0zamAHVgM3AVsME1zPLAh8h7DMKZErmcDC4DfGIZxMjs0i4iIiEgfFCwuwZGejuFwQCCAaZon7tQHhOvrCdfVYe/Gyio07AicfvNNnPbuO5z21obYNWemVSUNFBQSbrQrsD8/H+foUS1uxBM/ZQopixZZ/ZSstqigop7b/ryNaSNSuPfiqU2uhaqqYmuJW2NPjRw5VG6dMxyqqMSWkIDhcnVNwP1ER6cBOwC3YRgOIAE4DFwM/CFy/Q/Aosjri4HVpmn6TNM8AOwFZnfw80VERESklwuWRJJVV+Qcyn5SXY2eseoY3L1rPJ0ZGcSNP43Uyy/HOWRIkzWnzhEjAAgUFhBotKFP/ebNLU4BBmtqccYDP8eWkoJf04Bb9MG+Mmp9QR66fFpsJ16InCFcVYU95fgVUntaJFmtsDYYC1VWYO9AVfVU0e4NlkzTLDQM4xHgIOAB3jBN8w3DMIaapnkkcs8RwzCGRLpkApsbDVEQaRMRERGRfixYUoJ76lQMp5WsmsFgv6goNSSr3VtZzXjwATBNq1J9jGiy6j90KPb9BjADAeLGZR13XGdmhiqrrYhurDRmUGKT9nBdHYRCJ6ysRo8fCkYqq8HKSiWrbdCRacADsaqlY4EMINEwjH8+XpcW2lqcA2IYxg2GYXxiGMYnJZEF+b2N3W4nJyeHqVOncsUVV1BfXw9AUVERV199NePGjWPmzJnMmTOHNWvWALBx40ZSUlI444wzmDRpEnfccUdPPoKIiIhIlzNNs6GyGk1W+0tltSR6/Ej3TwNuLTmyJyVhT00lUFCIb88eAIbecw9D//Nu0r639LjjOjMyCCpZbVFRtY8Ut7NJVRUabZR0omnAA6PTgKOVVSWrbdGRacDnAgdM0ywxTTMAvAKcBRQZhjEcIPI1uj95ATCyUf8RWNOGmzFN83emac4yTXNWei/dOtvtdrNt2zZyc3NxuVw8+eSTmKbJokWLOPvss9m/fz9btmxh9erVFBQUxPrNnTuXrVu3snXrVtauXcv777/fg08hIiIi0rXCdXWYHg+OIekQqQT2m2S1qAho/1mZXcUxbBjB4mLq/vEP4iZOJO2afybt2mubHa9yLFdmJv7Cw/1mTXFnKq7xMjS5+UZGocoqgBPuBmyPVFZDFZE1q0pW26QjyepB4KuGYSQY1krtc4BdwF+BJZF7lgB/ibz+K7DYMIw4wzDGAuOBjzrw+b3G3Llz2bt3L2+99RYul4tly5bFro0ePZqbb765WR+3201OTg6FWhcgIiIi/ViwOHLGaj+rrIaqqyl75n9xjR4dq5r1Fo5BgwgcPozn060kfKXtW8Q4MzIw6+up27SJI//1X0paGymq9jE0Ob5Ze+CQtS7Y0cIuy43ZU1LAZiNYXk64vp7g0SIcQ/vv+aidpSNrVv9hGMZLwKdAENgK/A5IAl4wDON6rIT2isj9OwzDeAHYGbl/uWmaoQ7Gz+7dP6WmdldHh2liQNJkJkz4UZvuDQaDrFu3jgULFrBjxw5mzJjRpn4VFRXs2bOHs88+uyOhioiIiHQLMxRiz9e+zpA77yT1skvb3C96xqojPZ1ApBLZmWet1n/6KUU/f4CMBx8kbtzYThv3REpW/opgcQljnn8Ow9bRPUs7l2PwYOois/cSv/rVtveLbNR06Ib/B8DQO+/ESEjo/AD7oOJqL1ktTPeuXvc69sGDiZ86tYVeDQybDcewoQQKD1P77iZMn4+kb3yjq8LtNzr0vyzTNH9imuYk0zSnmqZ5TWSn3zLTNM8xTXN85Gt5o/t/ZppmlmmaE03TXNfx8HuOx+MhJyeHWbNmMWrUKK6//vpm9yxfvpzp06dz5plnxto2bdrEtGnTGDZsGAsXLmTYsGHdGbaIiIhIuwRLSghVVnL0vvvadL93506KH3mEYHHDVNmuqKzWbd6M9/PPKXrg5502Zlt4d+4kYcYM3NOmdevntoV9cKTKZ7ORMGtWm/u5MpvufRr2+ajfsoWCm2/GDHW4xtRnmaZJaa2fwQOabgoWqqmhduNGki+4oMXNro4Vl3Ua3txcin/xCxzDh5Mwa2ZXhdxvtLuy2lu0tQLa2aJrVhvLzs7m5Zdfjr1//PHHKS0tZVaj/5OYO3cua9euZffu3Xz961/nkksuIScnp9viFhEREWmPQGTpUlt38S35zW+ofXMD8ZFkzpGejrFvP9B5yWrRAw9S/swz1pj1nk4Zs62CxcW4zzijWz+zrRyDrApg/OTJsTNZ26LxETgApsdDxeo/U7P+TYJlZTiHDGmlZ/9W6wviD4UZlNjwu1/x4ouUPv4bTL+flIUXtWmcuKws6jZtArud0X/8Q5sS3FNd75qz0MfNnz8fr9fLE088EWuL7hJ8rAkTJnD33Xfz4IMPdld4IiIiIu0WPdLE1sZk1TnEWo/n3b4dw+XClpzcUFn1d06yGk1UAcKt/JurrQJHj7L7q3Pw7tx5wntN0yRYXIxzaO9M3qK7Eyd85Ssn1c+WkoKt0bTfsMdD3QcfABCqqOy8APuY8jo/AGmJDRssHf3RjwkePYptwIDYH2ROJG7CBADSb7mFhJmqqraFktVOZBgGr776Ku+88w5jx45l9uzZLFmypNWEdNmyZbz77rscOHCgmyMVEREROTknW1kNexoqnY70dAzDaHTOaudvsBSuq+tQf/+BA4QqK6n7cHPL1wsKOHjd9YQqKwlVVmL6/Th6aaXRmWmdtZr4tbNOqp9hGDgbTQX2bPuMUFkZ0HBES08JVVVR91HP7M1aFklWG1dWsVtH2Aw491ysvWZPLPnCCxjx618x6F//pdNj7K9Ue26n2traFtuHDx/O6tWrW7w2b9485s2bF3vvdru1G7CIiIj0Cd4dVsUx3Mq/gY7V+L7o0S6duWb12J1qQ/VWsnr0p/dhxMUx9Ad3ntR4oZoaALxffNHi9fJn/kDdBx9Q9swzlD35WwAcQ3rnbq7uM3IY+8rLxE+ZctJ9nSNGxM5nrdmwIdYeqqjotPjao/Q3T1D+hz+Q8d+PkHJR26bddpby2mhltSFZja7BHvbjti9JtMXHM+Dcczs9vv5MlVUREREROS7f/v3UrF8PWBUu0+8/YZ/Glc6GZLVzzlmtff99Ao3Osbc+z5oGXPHcc5T//vcnPWa4xkqufV+0fMqEc5iVmEYTVbASu97IMIx2JaoA7hkN63Br33oLe+RIlp6urHp3fwlA9Wtru/2zG6YBNySrocpKBpx3Hja3u9vjOZUoWRURERGR4wqWlAKQ/J1vAxA4cuSEfVpOVp2RAdt/dE2ospJD1/8Led9d3KTdrK8n2Kj6F25DQt1YuNaqrPr2HyDs8zW7bobCsddD7voPxvx5NfHZ7UsIe7PERqdYACQvWAD0bLJqmia+3Va113/wYLd/flmdn+kle+Cxhwh7PIQ9HkyvF3tqarfHcqpRsioiIiIixxWthLqnng7Qpk2IQnUN04DtqSlA50wDjibBofLyZtc8n30We+3PyzupcUPVNZEXIXx79jb/3EgyO/Daa0hbsgT39OltXqvYl7hzchh8y82x90nfOBsjIaFHpwEHi0sIlZVhuN0EDh3q9mN0ymp9PPD+b6n985+p++CDWOIe/b2WrqNkVURERESOywxYVcr47CngdLYpWY1OywUgckRHZySroWPWzGb+aiVD7rgdgJrX/x5r9+/ff1LjRpNRaHkqcKimBvvAgQz7z//sl0lqY6kXXxx77czMxJGaSqiy55JV784dgFXlNQOB2Jra7lJc01Bpr//oo0bJqiqrXU3JqoiIiIgcVzS5tCUmEjf+NLw7drR6b8nKldS8+WaTDZYMhzPyteNrVsM1DUml4XIx4NxzcQwbDkDVa6+R+LWvgWHg27fvpMYN1dTiGDIEW0IC3l0NmyyZpkn1668TLCnFNmBAu+PuS4xG6zDtaWnYkpMJ1bRtY62u4N25EwyDgVdfBUDRzx/o1s8vqWh49rqPPiZYXAyAY+DAbo3jVKTdgEVERETkuKLJpeF04s7OpuaN9Zim2azCGPb7Kf3t7zDi4jA9HlKvuJxgRQUDv3tlrL81XgfWrFY3JKvO4cMxDANbYuRs0FCIQTfcgD8vD//+kzsaMFxTjT0lGeeIEU12BPbm5lL4/dsA2r1pUV9ji4+PvbanpGBLSmzzLtAnwzRNzEDghGf3enftwjVmDO7TTyd54ULqNrd8vFBXqaiwfudsycn4vviCogcexJ6WRtzEid0ax6lIldV2MgyD22+/Pfb+kUceYcWKFQCsWLGCzMxMcnJyYv9VVlayceNGDMPg6aefjvXbunUrhmHwyCOPdPcjiIiIiLRNZEMkw+kkPjubUFUVgcLDzW7z5+VBKIRZXw+miWv0aEb++tfYUyJr+zpjzWqj6bqODKuiaktIBCBu4kQSZp+JK2sc1X/7G/5Dh9o8bqimFlvSAOInTcL3xReYYWtDJc/WbbF7bAkJ7Y67twuEwlTWW9O9jUbJqmGzYU9M6vA5ti2p+stf+HLa9BNu2OXduTP2hwJnRoZ1zu0xRxd1FdM0qY4kq0lnnw2mif/AAQZedRX25ORuieFUpmS1neLi4njllVcoLS1t8fptt93Gtm3bYv+lRua0n3766fz5z3+O3bd69WqmT5/eLTGLiIiItEfjymo0aYiuI2zMv9famGjQsv8HgH1gWpPrnbJmtXFlNSMDaNhtOG3JEgzDwH36NACO/te9bR43XFODbUASceNPI1xXR7CkBADPtoZkNVBS3O64e7v/eGk7OfeuJxw2MWxNUwRbUlKXVFar//Z/ANRu2gRAqLaOfRdeRP3WrbF7ghUVBA8fif3e2VNTIRjsknhaUuMLxnaHTpjdsFNy3MQJ3fL5pzolq+3kcDi44YYbePTRR0+q36hRo/B6vRQVFWGaJq+//joXXHBBF0UpIiIi0nGNk9W4iRPBbqf+Hx9R9dprTSpcvn37wTAYvGwZY1avIvmiC5uMYzhdTcZrj8aVVedwK1mNGzeWcX9bS8oliwAY/G/LGHj1VdS99x6+Nk4HDpaV4UgbhC0pyfqcemuDqPptW4mbNAmAQH73H5vSXV7ZWghAtbf5z8aWmEjoOJXVmjffZM835lGzYcNJfaYRmf5b9+GHAPj27Ma/fz9Hf7Iido/vS+t81fgpk4GGTY266yid4movcSGr4mxPbtj9N36CktXu0OfXrP5oTwG5tZ5OHXNqkpufjj/xIc/Lly9n2rRp/OAHP2h27dFHH+XZZ58FYODAgbz99tuxa5dffjkvvvgiZ5xxBjNmzCAuLq7zghcRERHpZI2TVVtcHHGnnUbFc89R8dxz2FNTcQwZSvF/P4ItIRHH4MHY4uNx5+Q0G8cW5wKbjVBF82Nn2ipU03TNalRcVlbsteFwMPjf/o2KF1+i4vnnGfbDe2LXwh4PhtMZ2+wJwAyFCJaU4Bg6FCPy7zLT7ydQVETw8BHSrrmW4i++IPHsue2Ou7czDDBN60zR1ISma0iPV1k1/X6O/PgnhMrLKXv69ww455w2f2b0eCF/Xr4VQ6Si62u0k3P0yJxo9bxJsjpyZJs/q72OVvmIC0V+/+PjGHzjv1H6mydwdsNniyqrHZKcnMy1117LypUrm11rPA24caIKcOWVV/Liiy+yatUqrrrqqu4KV0RERKRdGierAPGRSiOAZ+tWSlaupO7dTdS8/jqOIUNaHcdwOkmYNYuaY/5tdDLCjacBZ2a0ep8jPZ3kBQuoWrOGUG0doaoqih5+mN1fnUPJY481uTdUXg6hEI4h6bHNhUyvN7ZeNWHmDE579x1GHNOvP3FGEsWyWquKOOyn9zLqj38AwJaUiOn1Ygabb4xVu2mT9f1zOAh72l5AMgMBAgetSnWg0Krqhj1e62IwGDtLNVrhjq4Xtg/s/MpqoKio1Wp/UbWXuKD1PbHFuxl8881M2rUTw27vtM+X1vX5ympbKqBd6fvf/z4zZszge9/7Xpv7DBs2DKfTyfr163nsscf44IMPujBCERERkY45Nlm1pTRsLFO19m8EGm1k5Bg69LhjDTj3HIru/zmBwkI827dTeNu/M/7DD9p0DEi4vp66j/4Re9+4stqStGv+merXXqPq1Vfx5uZS9Ze/YDgc+A823XgpUGStRXUOHYrhsiqr1a//nfL//V8Ml4v4SZNiU1b7K6fdwB+C8jprfebAK66IXbNH7MKaWgAAIABJREFUp0bX1TVslhVR9dpa7GlpJMyadVLnn3q/+AIzECD+9NPxfv45oZoawt6GZLf6/9aR8u2FsfN6o8fpxCqrFZ1z7mu4ro6935jHwKuvYtiPf9zselGNl/hIZdXmju/3Z+z2Nn0+We1paWlpXHnllTz99NNcd911be537733UlxcjF1/lREREZFezvRHqk6RqbO2uIbdYgMHD4LDgWvkSPwHDuAYkn7csaLTgz2f51L+jFW58x/Ia1OyWr/lUwL5Bxn0L9fj238gtsFSq581bRrx06ZR8fzz2FNTSfjKVwjX1zfb2TZ2bubQoRCp6JX/7/9azx4O9/tEFcDpsIE/RGmkstqYLTGSrNbWNklWQ7W11L79NqmXX07Y4yHs9bbps6wjjn4LQPJFF+L9/HMChw9jNupf+sQTVjX8/vsjMVg7Pkd/T4Ll7Z9K3pg/Ut2teH4VwfIK0q69hrgJEzl813+QeumlZP7pr1wanaYc7z7eUNIFNA24E9x+++3NdgV+9NFHmxxdkxeZkx911llnsWjRom6MUkRERKR9zEDAWucZqSoZx+y3kThnDgPOPde65jx+Yhc3aRI4nXhzP4forrPhUJviiK51TbnsMkb+5vFYpfd4kuZ9A//+/QRLS60zQxMTmq2/jCWr6enNnm3gKbBka+OXxVTWW3+QKK9rKVm1EsVQbUOSHzh6lP0Lv43p85Hy7YXY4q2zdY8n7PdT/vzz7Dv/W9S+uQHX2LEkzJhhjVd4ODYNOP3f/x3//v0U3XdfrG9DVT8F24AB+PPzO/DEDfyN/o1e8/rr5F/9Txy55x5q39xAwY3LmfDh38k5ap27a3PHtzKKdBVVVtupttH/yQ0dOpT6yHx6sM5ZjZ652tiYMWOYN29es/aW7v3/7N13eGP1lfDx71UvtuTe7amePswAQy+ZAAFCS0gBQgqQhYS8aexuQvobdlMW0t6QHlgCIZtsQggklNAZJhlgqNN79djjXtX7ff+40pVk2R73ej7Pw4N8dXX1k63x46NzfucIIYQQQkwXqWA1RbGmA9LiT36Soo98mPCRI3Tdey+m4qKBLqEzWCzYliwhuGOnHqwOd69jap9iqhR0OFKZuOixYzjPOAM1HiPa2ZV1TirTasjLJxFIr6Xqe3fhuiy7o/FsdOP9b+i3u3zhnPv1Dsn+9N+/3hdeINbaCoBtzRo8zz53wsxqx4/vpvs3v8F+8slUfPP/4jjtdNSw9pjo8eMoZi00cb/nPfQ9+iiRI+lOzvoHJYqCdfFiIgcOjual5sgMVotv/SSBVzfjfeYZAFxXXcUTezo5/4C2ZS9z/qyYHJJZFUIIIYQQQ+ofrBoyso9l/3obptJSnKefzrz/+R1Fw9gWZVu9itCu9JzWuMczrHXEe3vBYMDocp345KTMslWj24XRmZdTBpxIBkwGm1XrWJxkqqjI6ho8G2WOHgKtG3B/xjwts5qZkU6Vhtc9cD+KomCw2bQmTP2ulyl86CDWZcuY94ffk//Od2LMc2IsKkKx2YgeP65nVg1OB7ZVqwa9jnXxYsIHDw75XMOR8PvxPPec/rVtyRLcV1+tf93wkU/zen6d/rXBLmXAk02CVSGEEEIIMSQ1GgVLZmZ14AyTY906DMPY32lfvZqEz6d3g01kjKMZSqynB6PLNaJOrJlZWIPbjcHpzAlW1VAYTCYUkykre5Yqf53NWj3Z2dCugfasZjRYSkkEtNuO004DQEmWyKrhMNG2NiJNTTnXSfR5MBYWZDUpUhQFc1VVcs+qltU2WK2YSkoGXbO1fjHx3l7iXV2DnnMiiXCYxk9/hvC+/foxc00N9pNW618/tLuL7uL0vmiDZFYnnQSrQgghhBBiSEOVAY+GbZUWEMQ6OoDs2alDiff2jqgEGLQANcXo0oLVeMb2LQA1HNIDkcw9q6kuuLPZofZ0AGo3G+nyD14GHM/IrCYCARSbTf/gwJBsPpQIBmm89VM0f+GLOdeJ9/VhdOf+/MzV1XiffZaOu7VxkIrZPHSwungxAOGDoysFVlWV5i98gcDmzVR+59sU33KLvo5X4+ms/VM7W1m9/jT96+HskRbjS4JVIYQQQggxpKHKgEfDumihPooEsmenDmU0waop43yj26VlS6NREpF0BjERDOkZ1czXNhcyq0e7tGD11a9cwHtPrh64wVIqs+rLzKwG9NmnAIpN+74FXn2V8J49RJubc64T93gGLOEeqKuzqXTwYNWSClZHuW811t6O97nnKb71kxS8972U3vZ5Fm98CVNxMb96JT3WKBxL8IEz5lN999243/++UT2XGJvZXYQvhBBCCCHGLDezOrZgVTGZsK1YQfCttwCIe4e7Z7UPc0XFiJ7LmBWsuvUANOH36yXLajiUDlIz9qga5kBmtakniNmoUJ5voyTPQrc/QiKhYjCkS3VTQWnWntV+wWoqs9p1/wOANlpGTSRQkk20VFXVglX3AMFqdXXOMeMQo4xMpaUY3O5RZ1ZjbW0A2E9aA4BiNGJOzgcudFi46V1fQTUaqS6ws7rajVJzMa5LLh7Vc4mxkcyqEEIIIYQYkhaspkt/FcvYglUAe0YDneFkVhPBIJGGBsyVlSN6HiUjoDKVlGQFq/q1Q2E9s5q1n3KMQflM0NgToLrAjsGgUOS0kFChNxjV7w/H4hzq1ALTRL8y4MyGQ6mxLqEdO7QgPxYj3ten368GgxCNYhhmZnWo91iqI/Cog1V9rm5Zzn0FDjOtzmLabAUsrcjPej+IySfB6ii1trZy3XXXsWjRIlasWMFll13G/v372b9/P5dddhmLFy9m+fLlXHPNNbS1tfHSSy9xxRVXTPWyhRBCCCFGLKcM2Db2IM62Ot3IJrVnNbh9O8EdOwY83/v8C6iBAPmXXjKi51EUBdvq1eS/6yIsixcPGKyqodCApc1zIVBp6glSW6QF9MV52vcgc3zNVx/ZyUU/2gjOPL2pEkDC378MOB24Fn3sYwBZDZBSgWtmd+YUc3VusGo/eS2uyy8fdN2ZHYFT/w1XNBmsmstyg9U8azqzXl82+zPr052UAY+CqqpcffXV3HDDDfzxj38EYOvWrbS1tfHxj3+cH/3oR1x55ZUAbNiwgY5k8wAhhBBCiJlovMuAAeyrMzKryWD16DXXArB8756c8/seewxTVSWOdetG/FzzH/qTHngaUmNYMpo6JcLhrD20c0lTd4CLV2olsMVOLXve5Y9Qn7z/mV3aLNWE3ZHVYCnu92HM2NObyqwCOE4/DX4Bsc4uvRlSajyR0TVAsFqVWwZssFio/uEPcF15BZa6upz7rYsXk+jrw//yK7T+539iqamh7jf3Des1x9rawWjEWJQ7EziWSAe99eX5w7qemDiSWR2FDRs2YDabufXWW/Vja9eu5cCBA5x11ll6oArwzne+k1VDzIkSQgghhJjucoLVcSgDNtfV4briCgxuN3GvFzUeH/TcWEcH/pdfxn3FlfoeyJHIzJCmutFmznZVg8ExN42aiQKRGF3+CDWFqcxqMljNGF8TjGo/l5jBiPepp+l+8Hc0f+1rhLZtzyqxTo0zUsxmTMXF2mO6OvX705nV3DLgoZop5a9fj3XhwpzjthXLAWi8+Waix47hf+WVYbxi7b3s27ABU2npgCOQQtH0+/Bdy8uHdU0xcWZ8ZvU/Ht/F7ubhbcofrhVVLr555cpB79+5cyennnrqsI8LIYQQQsw0kabjNHzso8z7zW9Qo9HsZjpjHF0DWgBZ/YPv0/KNb+B7aSPR48cHPbfvySchkcD9nqvG/LypYCm4bTt5556LYrGQCIcxJgOsuaSpR5trWlOoZZWL9Mxqugw4nsw0Glq0n0/XfffpDYqIZXzAkCzDtcyfhzE5dma4ZcCKwUD9pn9q43CGMacXwH7KKbiuuALPE0+kn8Pnx5iX28E58PYWzNVVmMvL6X3kUcL791N8y80DXjcUjZNnNbHpS+/E7ZBRNVNNMqtCCCGEECKH99lniTW30HX/AxNSBpxiyHcR93oJ79+vH1PjceJeLwfesZ6ePz1E4LXXsSxahHXRojE/XypY6vr1r2n97ne15wuFxmUf7kzT1KPNm03tWS1yZGdWo/GEfq4hHALAVF6uN6OKtrTo91vrF+M480wq77xT+x4bjcQ608FqIpnJNgxQBgxa8ytLXd2wuz0riqLPR03JfA9larj+eg6/+zIAeh/5C9b6ekr/7d8GPDcUTVBVYKPAMfYPZMTYzfjM6lAZ0ImycuVKHn744QGPb9y4cdLXI4QQQggx3lKZVM/f/44ai2GZP0+/LxWsjAejKx81FML7/Av6sbjHQ3j/AWJtbbR+85vY1pykjxYZq8xxNIHX3wCSe1at6de0eONGFOPsz+k0dmdnVk1GA4UOs55ZPZ7MvAK0LDuFyr1vo8aiWGprCB84mJUNN9hszHvgfv1rU1ERsa5OfR5rvC+5Z3WAMuDRsi5ehPO888Cg4N/4D8L79+E45eSscxJB7TUkAgHCBw8S2radsi9/adDmWaFYHJs5tzxYTI3Z/69wAlxwwQWEw2Huvfde/dgbb7zB4sWLeeWVV3jyySf1408//TQ7BulqJ4QQQggxXcV7ugGtEZFj3TpKMnp1GIZZqjkchjytiY3n6afTz93bS/jAAf3raHPzkHM3RyJzz2sqIFdDoawGQebyMkwlg++jnC2aegJYTQZK89JZ5SKnNmsV4Fh3QD/+tw/chuuqK4m1tmEs1BoTld3+RQB+9Ow+3jjanXVtY0kJvpc2su+UU2n81P8h8OabYDDo3ZjHg2I0UnfvPdT+6lcYXC5Ce/fmnBPrTO+bbbjxJhSrFfdVg5eTh6JxbCYJVqcLCVZHQVEUHn30UZ577jkWLVrEypUrueOOO6iqquKJJ57gpz/9KfX19axYsYIHHniAsgHaYgshhBBCTGex7h4AFj39FHX33oNt6VL9vvEsAza6tGBVDYUouOYaAOI92cFqvKNz3ILVTKk5oYlQKCuzOlc0dgepKbRnZRmL86x0JsuAG5LBarHTgj8O1gULiHd3E/d6cZ5zDoXXXENrX4ifvHiQJ7Y1Z13bVFys71kNvPYavhdfRDGbR9UgK9PX/7qDq362KeuYoijYliwhvHcfaiKRdV+sIx2sWufPZ96Dv8U0QBfglGA0gc0iwep0MePLgKdKVVUVDz300ID3PZ3xyWBKeXk569evn+BVCSGEEEKMj3h3N+baWizz5+fcp5i0PyHzLrxwzM9jyNeCVcXhwH3lFfQ+9BCRhoasYBXAWFAw5ufqT7FatRmdoRDKXNyz2hvQOwGnVBfYeeWQFuAd6/JjMRmoK3YQjMYxVVQCEGlo0GejvnpYO9cTimVdJ9UR2OBwUPntb3H83/4dNRxmrP5n87EBj1uXLqXn979n74qV1L+8Kd2RuFMbIVnzy1+Qt379CWfnhqNxbPlz770wXUmwKoQQQgghcsR7ujEWDZ7NrN/0Twyuse8/NCavkb/+HViXLEFxOOj4yU9I+HyYa2uJNjZq5xWOf7CaCAW1AEpVMdjm3pzVxu4ga2uzv6+rqt08uuU47Z4Qx7oD1BU5cFiMhKIJzJVa8yM1EMCQzES/ekjLnnpD0azrGEu0YNFUVoZlgNEziYRKXFUxj9PeYOuydOY/2tySDlY7tGDVvnr1CQNVSJYBy57VaUPKgIUQQgghRI5Ydw+mwsHLJU0lJeOyd9VcVQUmE+73vhej203xzf9CrKVF2yub0SzHNI5lwMWf0vbfJjxe4t3aXktT8eCvdTbyhKL0BaM5mdU1NVq33m1NfTR0acGqzWQkFI1ndepVknt8X0kGq55gdmY1/53v1G6YjFjmzaO/T/zuLeq/9tSo159IjtRJsS1bpt+Oe/r027HOTjAYhl1GHoomsJklRJou5CchhBBCCCFyJDyece3cOhhzZSVLX3+NvPPPB8BSlw5s7Ceng9XxLAMu+/zncV99NXGvV2/AM9fmrDYlOwHX9gtW68u0suyGLj+NycyqzWxMlgGng9Ww0cLXHt2hz2r19MusOtato+r736f6e9/T9wYbM/aKPr9Hm9X6lUd2EIqm57X+9z8Pc+5dLw645ofeaNRv+yPZwbG1vl6/He/pTd/u7MRYXIRiHF62NBSLY5fM6rQhZcBCCCGEECKHGotBxmzViZTqygtaJ96UrGB1nLvzGl35JPr69Fmgc6H7b6bG5IzV1NialHybCYMChzr8+CNx5hU78IZihKMJDDYbxoIC4r29bG0L8PvXtP2ja2rcdHhz96O6r7xCv73o2WcG7AT8v68fo8pt47MXasHmt5/cA0CXL0xxnpUuX5hvP7mHo11+thxLB6G+cIx8W/r9abDZqL3n1zR+4pPEe3r047H2DkylpcP+vgQjUgY8nUhmVQghhBBC5FCjUb2R0mQyJeepmkpLMVfX6McHKiUdC0O+i0QgoM8KnWvBaiojWluUnVk1GBQKHBa2N2mBoZZZNRBMZj9NlVqTJXPGBwynzCvE26/BUn+Wujp9H2l/P37hAH9+szHr2IF2HwCvHu7i0S3HMfTbbzrQ8znPPhsUJTtY7ewc8GfbF4yiqtmlxNsaewnHEuTbJJ83XUiwKoQQQgghcqixGIp5/OapDpcpOfLPWl+PwZkOiAzjOC4HwH7yWgA6fvITYO6VATd2B3BYjBQ6crPnBXYzhzq0YLE034rdbNRLdVP7VuMW7edx20X1uGxmvOEY8X77SPvLLPfNdPaiYr748HbOuTNd/psKVlMzX3/90VM5bX5632n/hk6gdak2ulzEe/sHq9mZ1S5fmDX/8Sx3v5DuON3Q5efjD7xBbZGd606vG/J1iMkjweootba2ct1117Fo0SJWrFjBZZddxv79+9m1axcXXHABS5Ysob6+nm9961tZn9o8/fTTnH766Sxbtoy1a9dy7bXXcuzYwC24hRBCCCGmihqLTUlm1WCzYVm4EMdp64bVvXW08s45h9LbbiPh9WJwu8elWdRM0tQTpLbQMeD3uMBhJhTV5pXmWU3YksGqqqp6R+CQwYzFaOC2i5bgsmsBr2+I7OqWYz0s+8bTvHywk0C//ab/fcM6Ll1ZwfHeoH7sUDJY7fRFUBQodFhwWNLvx8zM6rl3vch197wKgLGwkFhHB4EtW+h78klibW05ZcAv7m0H4MfPHyAW117nVx7ZQVxVeeCm0ynJk9E104XkuEdBVVWuvvpqbrjhBv74xz8CsHXrVtra2rjxxhv55S9/ycUXX0wgEOD9738/v/jFL/j0pz/Nzp07+exnP8tjjz3G8uXLAXjsscc4evQodXXyCY4QQgghpo+pClYBFv7tr5BsiFP08Y9jW7liQp6n+JOfIN7bq483mUvavSHK3bYB7yt0pAP3PJsJm9lAQoVIPKHPWg0aTHojIleybNYTiuIeIFMLsLPZA8Bf3m6iLqP0eH6xA6vJyM8/fAqLvvp3AJwWIwfavYCWBS10WDAaFPKs6fdjtz/C60e6OW1+IU09Qb2s2VhUhPe55/E+97x+rtGVn7WWTQc79dvP72nj0lWVNHQFuGh5OYtK8wb9nonJJ8HqKGzYsAGz2cytt96qH1u7di333Xcf55xzDhdffDEADoeDn/3sZ6xfv55Pf/rT3HXXXXz1q1/VA1WAq666atLXL4QQQggxFFVVIRpFMU/Nn4pKRmOn8tu/OHHPoyiUf/lLE3b96aw3EGVBSW7DIyAr4My3mvWGQ5mzVgOKGYdFO16QDG57A1FqB5kAZExmcDfsbWd3MnC9dl0tn79Ia6xkNCj8n/WLiCVUuv0R/rFf+wCh2x+h2KldP7Px0Zcf2UEkluBPnzgz63nMFeUEAXN1NVV33UnHz3+O89xzs85p6Apw5sIiGruD3P/yUS5dVUlvIILbPjkNxcTwzfxg9akvQ+uO8b1mxWp4952D3r1z505OPfXUnOO7du3KOb5o0SJ8Ph8ej4ddu3bxhS98YXzXKoQQQggx3mLJEsspyqyKidcbiFAwSHCWyqwaDQo2syEjWI2TX1UFgN9gxp4MVouc2nW6/LkdgVN6ApHk/6NUuu3c+b7VfHBdLUZDugz59ku1Wam/2niIh99qYkdTH0/tbOWMBVoEbMo4t9Bhps0TpqE7oB9LJFRM5VowbZlXh2PdOubdf3/OWlr6gpxXX8oFy8r47t/3sr2pF38kPuj3Q0wd2bM6jlRVHXRvRf/jXV1drF27liVLlvCDH/xgMpYnhBBCCDEsajJYVSZpdI2YXPGEiicUw+0YeJ9uqumS2aigKIpe7huKxrGvXUv5N77O/trlOJN7SFPBbSogHUiqUdKTnzuXJz93LtedXpcVqGaqL9NKcW964A0g3WzJkDz/tovq+cunzga0xkj6cwQieuZXsWWP5EmJxhO0e8NUuW1cu64Ou9nI/3tuP8CgJcxi6sz8j8uGyIBOlJUrV/Lwww8PePwf//hH1rHDhw+Tl5dHfn4+K1eu5O2332bNmjUUFxezdetWfvCDH+Dz+SZr6UIIIYQQJ6QHqyb54302SnXSHSyTWO7S9rKmmixllgErRiNFH/4w3ntexZ6MdYudWkOibn9uh96UHn+E6gI7K6vcJ1xffZm2x7TTp2Vq/+XcBQAYk2m2IqdFD5CPdqYzq22eEDVFya7OgwTC7d4wqgqVBXbcDjPXnlbLA68cBZAy4GlIMqujcMEFFxAOh7n33nv1Y2+88Qb19fVs2rSJ55/XNnQHg0E+97nPcfvttwNw++23853vfIc9e/bojwsEAgghhBBCTCfpYHXm5zVErt5AMlgdJJNY0a/xks2shQzBjNEzgUhc37OabzNhNCh0D1EG3B2IUOQcXsfl6kK7/pwrKl18+p2LgfS+13hCxWExYjQoPLmjRX9cuyeMITn/1VRYyEBakh2HK5Ov8QuXLNXvk2B1+pFgdRQUReHRRx/lueeeY9GiRaxcuZI77riDqqoq/va3v/Htb3+bpUuXsnr1ak477TQ+85nPALB69WruvvtuPvaxj7Fs2TLOOecc9uzZw/XXXz/Fr0gIIYQQIk2NasHMVDVYEhOrNzh0sFrZL1jNLANOyQxWDQaFQoflhJnVwmEGq0aDwsISrRS4OM+ScVwLXeKJgbfetXlC5L3jfEo//znKBukT09wXAqCqQCsTzuwwXDBIWbSYOvIbaJSqqqp46KGHBrzvpZdeGvRxl19+OZdffvkErUoIIYQQYhxIZnVW603uLXXbBw7OUmXAKY5kQOcPp2ebBiNx7BkfZhQ5zUNmVnuDUeYVD9x9eCD15XnsbvHonYAhXQYcT6hZ/09p84RRjEZKPvWpQa/bP7OqXVchnlAlszoNSWZVCCGEEEJkSWVWpRvw7NSXzKwOFpzl28z9vtbeB95QOlgNRGJ6ZhW0Jks9/TKrjd0BrvzpJto9IXyhGHm24b+fUk2WipL7YSEdRBf2y4D+9dPnUOy00OYNnfC6LX0h8q2mrNf4/lOqk9eVYHW6kd9AQgghhBAii3QDnt1S5bypfaEDufykSk6fr42McSUDu1RjJsguAwatXHd/m9Y0NDUhY1dzHzuO97H5SDfecIx86/BDj8XJJkupsTgAN52zgCKnhfeurc46t6rARpnLRrvnxMFqc2+QyoLszPF3rl7NJ85fJGXA05AEq0IIIYQQIot0A57donGtfNZsHDxY/fn1p+i3U5lVTzKz6glFCccSWXtQtT2rWnnxVx7ZgS8cY/3SMgB2He8jEkvgHEGwurRCC1bLXNnluu87pSbn3BKnlXKXlTbP4GXIKS19ISrc2WNtzEYDi5OZXDG9zNgyYFVVT3zSLDRXX7cQQgghJo8aTWVWJa8xG8Xi2kga0yDjXfqzmY1YjAY8yczqsS5tmsX8jD2oRU4LvYEI4VicJ7a3sKvZo+9xfftYD8CIgtUFJU4e/PjpXLWmatBzrllXg8tmwmBQKM+30XaCzGooGudwh495RY5hr0NMrRkZrNpsNrq6uuZc4KaqKl1dXdhsthOfLIQQQggxWrFkN2DZszorxZKNiUxDZFb7c9lN+p7Vo11+AOaXpIO+IqeFhAob9nbgC8foCUTwR7TztzX1AZBnNTIS5y8p1We8DuR7H1jD9jsuAaDcZaXTF9YD8YG8uLcdfyTORSvKR7QOMXVm5G+gmpoampqa6OjomOqlTDqbzUZNTW75gxBCCCHEeJE5q7Nbugx4eJlV0JoupYLVhmRmta4oO1gF+OuW44DWxCl1fiSmBZB51okrKy9z2Uio0OWP5HQzBnhxbxtf+PM25hU7OHtR8YStQ4yvGfkbyGw2s2DBgqlehhBCCCHErJSesyp7VmejdBnwCDKrNhOeZBfhpp4gJXkWHJZ0KJHq0Pv0rlYAVDU9JibFOcLM6kikAtQ2TygnWP3s/27h8W3NrKp28ZsbThtyr66YXuQnJYQQQgghsqQyqzK6ZnaKJkaeWc2zmdi4v4P9bV68oajeITilKKPZ0qJSbS9rU08wa19s3gj2rI5UhR6sZjdZiidU/r6jhQUlTv70ibOyGjaJ6U+CVSGEEEIIkUVvsCTdgGeleCKB0aCgKMMPVrc3avtO73pqL/5wLKdZUm1GSfB7kqNlmnqCzCt26CNuRtJgaaTKXdo81tZ+TZa6fGHiCZWPn7tgQp9fTAwJVoUQQgghRBY11WBJugHPSrG4OuxOwCm3v3sZAN5wDF84lpMlddvNfP3y5ayqdnFufQmgBY55NjNLyrUxNBOZWS3Os2IzG/j95oasJkstfVrwWikZ1RlJglUhhBBCCAFA89e/TvuPf4wakW7As1k0ro543+ZHz5zH9WfUsbfFgzeUm1kFuPm8hTzx2fMozigJzrMaWVYx8cGq0aDwifMWsrfVS2NPeq9sKlitcEuwOhPJbyAhhBBCCAGA78UNxLu79a8lWJ2dYokEphHsV01ZXuniD68dI9LlZ3mla9BKtoy+AAAgAElEQVTzSvOt+m2nxcQ7l5WxtbGXfNvEvp9WVrsB9PmuAK19WuAqwerMJJlVIYQQQggBgBqPY55Xp38t3YBnp2hcHVEn4JQVlVqGNBRNDNnZ12Ex4bZr7508q4lLVlbw9G3nj2iu62g4k92J/3mgk59vOAhomVWL0UCRwzLUQ8U0JcGqEEIIIYTQRKPkr1+f/loaLM1KsXhiRJ2AU5ZWuEj1ZDrRzNTiPC04nMyMZiqAvv/lI3z/mX00dgdo7AlQU2jHMMI9umJ6kGBVCCGEEEIAWmY1c1yNNFianWIJdVRlwHlWE/OSXX/zTjAzNRCOAwxZLjzeUnti273a+Jqnd7bS2B2kJqNTsZhZJFgVQgghhBCANl81c1yN7FmdnaLxBOZRlAFDOvg8UbOk3mAkeX7+qJ5nNBz91vTUzhaOdQeoK7JP2hrE+JJgVQghhBBCoKoqxOMoxnTGTILV2SkWH11mFdLB6olmlv77u5YCML/YOarnGY08S3pNJoPC28d66QtGqS2UzOpMJcGqEEIIIYSAmNZBVTGbqPz2tzAWF6NYrSd4kJiJYonEqBosAawYZmb1lvMXcvTOyye8qVImR0Zp8iWrKvTbq5JdgueiaLIce6aSYFUIIYQQQmj7VQGMJgo+8AGWvLwpK8sqZg9tzuroMqtnLSrmQ6fXccbC4nFe1dhlzo49e1F6fWdNw7VOlsfu3srz9++e6mWMmtR2CCGEEEII1FRmVUp/Zz1tzuroclZOq4n/et/qcV7R+KsusPP8v51PQmVOdgJWVZVtLzTSeriPRaeUTvVyRm1MmVVFUQoURXlYUZS9iqLsURTlLEVRihRFeU5RlAPJ/xdmnP8VRVEOKoqyT1GUS8a+fCGEEEIIMS70YFWyqbOdNmd1dgdwyytdLC7LZ0n55DV4mk7efqaBlx8+iNlmZNmZlVO9nFEb60dndwNPq6r6AUVRLIAD+CrwgqqqdyqK8mXgy8CXFEVZAVwHrASqgOcVRVmiqurMLqQWQgghhJgF9DJgyazOerF4Aodldv+cy/Ln3n7r7Rsa6WzyUbHAzea/HmbxujIuvGE5JvPM/QBq1O9SRVFcwPnAjQCqqkaAiKIo7wHWJ0/7LfAS8CXgPcAfVVUNA0cURTkInA68Oto1CCGEEEKI8aGXARtndxAjRj9ndSZRlNn9+gby6iOHiEUT7Hm5heqlBVx04wqMppndomgsv40WAh3A/YqirAHeAj4PlKuq2gKgqmqLoihlyfOrgc0Zj29KHsuhKMongE8A1NXVjWGJQgghhBBiWGTP6pyhlQHP7CBmMG9/413M8grnQRktBmLRBACnXjp/xgeqMLY9qybgFOCXqqqeDPjRSn4HM9DbRh3oRFVV71FVdZ2qqutKS2fuhmAhhBBCiJlClT2rc0Ysnhh1N+DprshpocBhmeplTLqQP0rYH2P+SSUsPaOC6qWFJ37QDDCWj86agCZVVV9Lfv0wWrDapihKZTKrWgm0Z5xfm/H4GqB5DM8vhBBCCCHGiexZnTu0MuCZn3UTab3tAQBWnFPJgjWzJ9k36nepqqqtQKOiKEuThy4EdgOPATckj90A/C15+zHgOkVRrIqiLADqgddH+/xCCCGEEGL8qFHZszpXROMJzHO1VnaW2r+5FYNBobTONdVLGVdj/W30WeD3yU7Ah4Gb0ALghxRF+RfgGPBBAFVVdymK8hBaQBsDPi2dgIUQQgghpol4Mlg1S7A628Xis7/B0my177VWyue7OLa7m/2vt/KBL63D2x1i18vNLDunkrzC2dUFeUy/jVRV3QqsG+CuCwc5/zvAd8bynEIIIYQQYvyl9qxilD2rs10skZAy4BkoFo3z/P27sdhNWOxGfN1hIsEYbz51FIB1754/peubCPLRmRBCCCGEQI1pBW+KyTzFKxETLRpXpQx4BomG4+zY2IQh+TOLBGNEgtqHS51NPva+3MKK86rIL7JN5TInhASrQgghhBACNRYFpBvwbNbQ5ecd338JQDKrM0TLwV6evncngb7IgPc3H+ghkVCpXV40ySubHPIuFUIIIYQQEE9lViWXMRm6W/z89isvs+2FRgC83SECnoEDkhN5fncbN97/OonEgFMhdU/uaNFvy57VmWHbi40k4iqVi91ZxxedonX8bTviAcBZMLv2qqbIbyMhhBBCCCF7VidZxzEvvp4wm/58gN0vN9Pd7KdsXj4f/MppI77WC3vbeGlfB7tbPKyqdg963tsNvfrt5RWzq2vsbNXXEaRsXj7lC9y0HOwDwGBQOO3yBRze2knr4WSw6p6dwapkVoUQQgghhB6syp7VyZHac2h1mLDnWyity8fTFRrVtY52ajM2Nx3sHPScWDzB5sNd+teXrKwY1XOJyaOqKp6OIO4Su74ftaDcwY13nUNxdR6ltXmE/FEUBRyu2fnvVoJVIYQQQgiREaxKZnUyhAPaHuGbvncu7/3Xk5m3qpiwP3rCUt6BHO3yA/DyEMHqtqZefOEYP/jgGjZ/5ULsFvk5T3chf5RIKI6r1I7NqRXEukrs2PMtACw7qxIAVQXDLN2DPDtflRBCCCGEGBnZszqpwoEYJosBo0n7c9zmNKOqEAnERnSdUDROS18Is1HhjaPdhJNdnfvbdKALRYELl5VR4Z59XWNnI0+nlml3ldipXlrI4lPLeMeHluj3LztbC1aVWbz9WH4bCSGEEEII1Ghqz6r8eTgZwoEYVke6dNOWp90O+iL67eHY1+oF4MqTqnhky3G2HOvlzIXFOedtOtjB6mo3hU7LGFcuJkuq4ZazwIrFZuKSW1Zl3W+2GPnwf56JOops/EwhmVUhhBBCiDku7vHQ/MUvAqCYJVidDOFgDKsj/b2252sB6j//tJ99r7UO+zrbmrSmSZ98xyIMysClwNF4gi3HejlrgCBWTF9Brxaspt4bAykoc1BY4ZysJU06CVaFEEIIIea4SMMx/bYi3YAnRTgQxWrPCFbztIxn454enr9/97Cv8+bRHkrzrSwpz+OkmgJeOdSVc063P0IsoVJT5Bj7wsWkSWVWHflzNxsuwaoQQgghxByXlU2VPauTQisDTn+v+5f+xuOJE16jocvP33e0cPGKchRFYW1tAbubPVlNmhq7A+xp0cablObN3aBnJgp6I5htRkxzuBmW/DYSQgghhJjj1HBYvy0NliZHOBCjqCpdvulwWSiuyaOryQdA93E/pXX5Q17jxb3txBIqn1q/CIDllfkEo3GOdQeYX6Jd+7zvbdDPL8mbnbM4Z6ugN6p3/p2rJLMqhBBCCDHHJUISrE6mY7u68HaFKK7K048ZTQau+/rpfORbZwLQ3uA54XV2NPVRlm+lplAr711a4QJgb7LpUn8SrM4sAU8ExxD7VecCCVaFEEIIIeY4NRTUb8ue1Ynj6Qry919u56l7dlJY4eCkC2pyznGV2LE6TLQ3pAPOpn09BH2RnHO3NfVyUo1b/3pBsZZNbeoJABCJZZcSl+RLsDqThHxRbHO8dFuCVSGEEEKIOS4zs4p5bmdyxsvGP+xjy7PHso417OjiyLZOYuE4F3xsOSZz7gcDiqJQNi9fz6zGonEev3srrz9+JOs8byjK4U4/J9UU6MccVu16gYg2a7XLH856jHMO732ciWLROGbL3A7XpM5DCCGEEGKOU8Mh/bZkVkcvHk+w/YUmouEYO/9xHICTL65L35/MdJ79/sVULHQPeA2Asnkutjx7jFgkjrc7RCKh0ri7m7caelhbW4DRoLDzuAdVhdUZmVWz0YDFZMAf0Wbmdni1YLXSbaO20IGiKOP+msXEiccSGE0SrAohhBBCiDksEZJgdTw07+/llUcO6l/37/AbDsRAgbUX1g55nbJ5LhIJlc4mHyF/FIC+jiA3/exVPnLhQm6/dBnbk/NVT6rODnqdFiOBsJZZ7fRpweovPnwKJ1W6UVVVAtYZJB5NYDTP7WB1br96IYQQQgiBmiwDrnvwt1O8kpmtt03bK/qRb51F/WnlmPoFGmF/FKvDhGIYOmAsm691AW5v8OLpTO8nnh8z8NCbjQBsP95HdYGd4n5NkxwWk55Z7fRq+1yLbGZ++9WX2fTQAXpa/RzZ1jGGVykmSzymzvnM6tx+9UIIIYSYdvybX6P1u9+d6mXMKYlkGbB99eopXsnM1tcexGQ24Cqx4XBbCAViWfeHAjGsjhPvCXYWWHG4LLQ3ePB0hDBZDITMMC9moNMXIRyLs72plzW1uaXEeVaTnlk92uXHZFAw+eIEvVG2b2jiD3e8xt9/uSNrFquYniSzKsGqEEIIIaaZYzfeSM+Dv8sqTRUTSw1q32vFKt1ix6KvI4C7zI6iKNgcZmLhuL5PFSAciGJznHgXXrrJkpeAN4LdZeGgEmNB3Iiiwp4WL43dwazmSikOq1HPrO5p8bC4LI+eRq2zcEltelSOpyOY81gxfaiqKntWkWBVCCGEENNUrL19qpcwZyTCIRSLBcUgfxqORW97EHeZNvPUmgxK336mAdCyZCF/DKtzeN2Wy+a76Gnxc/CtdgKoHDUlsCYUyuMKT+9sBXL3qwI4LSa9G/CeFi/LK110NPqwOc1c9fm1VNVrAW5Xs29sL1ZMqERMy3xLZlUIIYQQYhqKtbVN9RLmDDUURrHbp3oZM1oinsDTGaSgTPs+2pJB6euPH+Hpe3byq8+9RPtRDxbb8BpYrTi3CovdhJpQOdAboNmiZWirYwae2N4MwKqa3GDVYTHiD8fo8Udo9YRYXpmPrydMfrENe56FKz6zBhTobvaPx8sWEySVkZfMqhBCCCHENBRtk8zqZEmEQxikBHhMfD1hEnFVz6xaMsp9j27vpHKRFlgGPJFhXc/ptupZ0JCiEjIpOAutVMUNNPUEqS6w47LlZmmdVhN7W73c+MAbACyvdOHvC+N0WwAwW41YHaZhr0NMjVhUC1b7N+maa2R0jRBCCCGmF5MJYjHJrCYFt28nfOAgBe9/34RcP9rWTt/Df8FYWjIh158retu1TsDuUi2zakpmxCoWurj45lXkFVp566kGapYVDvuaqQAzpMDPrj+FxMsdLNkd44OnlnPJyooBH2NKdhre1qiNtlle6eJAX5jy+S79HKvDrI3REdOWZFY1EqwKIYQQYtpQYzGIaX9Ey55VzdFrrgUYU7Cqqir71p5M6W23UXzTjVn3dT/wAADxjs5RX19AT4sWrBYkM6tVSwq4+OaVLFxbqgcc6y6bP6Jr2l1asLqgIo93rShna3OYg2+1c8fFy3C6B86EN/elGyeV5FkptJsJ+qJ64Atgc5gIJ+e3iukpnsyszvU9qxKsCiGEEGLaiHV367fj/qlvANP4mc/gOHUd4QMHiLW2UPeb30z1kkZFDYVQw2Ha77orJ1iNtbVOzaJmgY5jXl57/DBBT4T2Bq8+sga0jr7168rHdP1UCajDrO1zLV+glRK3HfGwcG3pgI853pMOVpdX5hP0REAFR0Zwa3Wac8bqiOlFMquauf3qhRBCCDGt+F7coN9WA1M7WkONRvE9/wLtd91F3yOP4H/lVdSE9gekGosRPnhwUtag31ZHPxczERz8exncvgPr0qUseOxvo77+XLVjYxNNe3swJ5smLT61HEVRxu360eSP3G7U/mQvrc3DYFRo2tM96GO+94E1+u0VlS48ndpYImdBOliVzOr0pwerczyzOrdfvRBCCCGmDVVV6f6f32FbsQLr8uVDBliTITPLm3/ppQCowSCBt7dw5AMf5PAVVxLcsXNE1wzt28/h972PeG/vsM6PNDbpt9VweETPlSkRCAx4PNbdTbSpCfdVV2FbsmTU15+LVFWlaU8P81YW895/PYXrvnE6p1+1YFyfw1SmBZjuedp8VJPFSP1p5ex5pYVwYOBg8/QFRfzqI6cA2n7Vg2+3YzQZqFqc7hxsdZrp6wjy1tNHx3W9YvzoZcCm8fvwYyaSYFUIIYQQ04L/lVeIHDxE4cc+isFun/JgNd7VBUD1T3+C47R1AHQ/+CANH/kIsU5tf2do544RXdO3YQPh3XsIHzgwvDX0pAPmsXw/MoPVVHYYtOZNAPY1J4362nOVpzOItzukN0wqrs7DaBzfP62VEhs/dwWpXFWsH1t0cimxaILe9vT7IRKMse+1Vt586ijHdnVxxoJiLj+pkvOXlNK0p5va5YVYHenOwakZsJv/enhc1yvGTywm3YBBglUhhBBCTBPdDz6IsaQE12WXJYPVgbOBkyWWDFZNxSUY7FrTnI67f4JiMrHoyScw5OcT2r9/0Md7nn0W36aXs46F9uzRrt3RMaw1JPzpWZhjyayqGcFqZpfl0PbtYDRiW7Fi1Neeq5r29gCMqLvvSAUjcQKG9J5VSDddCiZHz2zf0MS9//oPnr9/N6/97TCb/nyAQqeFn19/CkVOCwFvhLwiW9Z1w/70flVfT2jC1i9GL5VZNcieVSGEEEKIqRU+cgT/xn9QeN11GCwWDA77lO9ZTQerRRgcdv147T33YHS7sdbXE94/eIa07b/upOuee7KOjSVYHVNmNeOxwe07UFWVaHOztl+1vh6DwzHqa89Vx/f14HRbKCifuO9dMBoHwGFJ90R1JIPVgFcLVv/5J+0Dk+KaPJafXUnQly4PTsQThP0x7HnZ81gdGZ2BWw97JmbxYkziklkFJFgVQgghxDTQ95e/gNlM4XXamBZlGpUBG4uLMdjTwapt2VIALHV1RFuaB3xsrLOTWEsLse6u9PW8XqLHjgFaIBsdxhzZ8cqsZpYBB7dupfdPf+LgBRfi37QJ++rVo77ubHRsdxf3f2kTkdDQ3XI7Gn2UL3SPa0Ol/gIRbQ12S/pPdj1YTWZWU5xuC84CK2F/FDWhdWYKJTOotjxL1rmnXDKP9/zryRhNBtqO9E3Y+sXopfeszu1wbW6/eiGEEEJMC4E338J+0kmYSkoAMNgdUxqsxn1+On/5KxSbDYPTiZIRrBryks1uSoqJd3QO2KU3tGuXdp2u9J7T8N69Wee0fOMbJ1zHcDKrcZ9/wONZ10lmqY2FhQS3bMH73PP6ffaTTz7h4+eSI9s6CfRFCPRFBj3nhQf30NsWoKQmb0LXEkpmVu0ZmVWT2YjFZiToiZCIp/cfn3fNEmxOM6oK4aAWpAZ92muw52dnVo0mAzVLCymty6ftiJZZbT7QSywSn9DXMxaqqqKq6rRe43iS0TWauf3qhRBCCDHlEpEIoV27sK9Jj9yY6gZLkYajJHw+3FdegaIoWZlVxaQFDsaSEtRolIQnt4wymApWe3sJHzxIIhQisHVr9jnbtqPGh/7DO94vs9r3+OMc+eA19D3+BKqq0v7DH7H/rLMIHx66UU4qs+o8+2xCu3YR3LIFgOJbbsZ9xeVDPnauaT2sZRqj4YF/Nl3NPva+0gJoTZUmUiAZmNkz9qyCtm814I3gTwbU6z+8lIJyBzan9t4MJUuBQ17t/7Z+ZcAp5QtdtB/z0tsW4NEfvs2fvvPGhLyOsYhHE7z19FH+9z9e4xef2sCvP7eRruNTP4N5IvS2Bdjwuz288Nvd7N6kVW3M9dE1phOfIoQQQggxcUI7d6JGo9jXZgSrDjtqMIiqqhNaZjkYNRkop0bWZAarKaaSUkAr+TW63Vn3hXbuSl5I5fAVV2q3DQZsq1ZRdNON9D36V/ybNhF47TWcZ5896DoyM6txr5fmL94OQPMXv4j32Wf0DKl/82asCxcOfp1gOlj1PPkkajRK+de+RtFHPzLoY+aSWCRO53EfRZVOupq0QCgaHrgMeE8yUF1yejm1y4smdF3pPavZwWpegZUjWzvx92ql4akZqlanFpSGkjNUU/tX7f3KgFMqFrjZ9nwjh7a0A1qwFPRGsOcPfP5Ei0XiPPPfu0jEVd79yVWYLEYadnax+a+HqVjoorgmj64mHy0Heyf8g4KpsP3FRva82oqzQPv+Vy5yD/pBw1wxt0N1IYQQQkw5/8uvgKLgPP10/Zhit4OqooamplNpKqub6gI8cLCqlSzHOrty7gvt3InB6cw65rr0UuoeeAD35ZdT87OfYsjLo+/xJ4ZeR8ZeU89jjwFQ+LGPAuB97nnc77kKY2kJwX5Z28Gu4zz7LP2YZcH4zgSdyV76wz7+ctdbHNnWSaqqOxLKzazGYwn2bW5l0cmlvOvjKzFbjTnnjKdgJI6igLVfKej51y1lxTmV9LYHURQorNDea6nARg9Wk02Y+jdYSilf4ALgwBvp/dMdjd7xfREj0NXs5+j2To7t6uKVRw8B0NuhvXev+Oxarv3aaVgdJjqbZkdmVU2ovPb4YXpatQ+lGvf2ULeiiBu+ew43fPcc3vfFU8d9HNJMM7dfvRBCCCGmVPjwEbruuw/b6tUYCwr046kgcapKgVN7PFNdgJUBuuWaSrTZl7HO7M6+0fZ2Yu3tWRnTwuuvp+qHP8CYpwUVBpuN/He9C++zz5IIhej42c9p/urX8G3ciBpLZ/QyM6ve557HMm8e5V/+MqW3fZ7C6z9E5Xe+g33lKsJ7svfD9qcGgyhmM+bKSv2YdcH8YXwn5ob2o1op97Fd6Q8eYpFEznkH3mwj5Iuy/JyqSVlXMBLHbjbmVBcUVTk5/0NLufHOc7jxrnNxl2rvU1u/zGrncR8Wu0lvytRfXqEVp9tC1/H0+6zj2MiD1W0vNI7qcf35e7RMceViNzs2NHF0RyeezhBWpwmr3YSiKBRX582aYLWvI8ibTx7liZ9to7vZT29bgOolEzcKaSaSYFUIIYQQU8b30kuooRAVX/tq1vFUJjMxReNrUmWzqXUMmFktTZYBt2cHq6nmSnnr1+vHnOecnRNwuK+8goTfj++ljfT8/vf0PfIIjZ+8laPXXIsa1YKNhD+AsbhYf0zhRz+KYjBQcuutVPzf/4tiMmGuqiTa3j7oawnt30/44CE94NYbRGUErnOdYtB+Nsf392K2adnS/mXALQd7eeGBPdjzzdSuGL/y32g8QSyeGxgDBKLxnBLgTAaDkhWI6sFqsvy39VAfFQtd+uvrT1EUyhdqJeyuUjuuEhsdx0YWCHY1+9j05wP6Hsux8CXLmt/18ZUUlDt48+9H8XYGcZek//0VVjjobZ/aGczjxdOl/X7zdIb43/98DYCy+flTuaRpR/asCiGEEGLKRFtbMDgc2E46Ket4KqOZCJy40+1ESO1ZTXUBVqzWnHMMLheG/HyijY1Zx0M7d4HBQN76d+jHMrPGKY4zzsBYWkLfY48R7+2l+JZbwGCg69e/xr/5NQxOJ/G+XkxFRfoYHfd735NzHVNZOYm+PhLBYE5QHW1ro+H6D5Pw+bAsWgTAwsf+RqSxCcUwt3IWiXiCRELFZM4N/lKfI/h7w5QuLaBjX29Og6VUU58LPrYcwyDB30h5Q1HOvWsDfcEoNrOBy1dX8cNr0nu3Q5E4tgHWOxgt+6hlVsOBKN0tfhafWjbkY0pq8ji8pYPSWu1DjOGWAXs6g2x9oVEfk5Oa+zpa/r6wPjM2r8BK1WI3h7d1YrYY9XJlAFeJnbA/RiQYw2Kf2aGMt0vb5nDaFQt444kjABPeYXqmmVu/pYQQQggxrcRa2zBVVORkHfX9oB0dAz1swqXLgLVs5EBNnhRFwVJbS6RfsBo+cABLbS2mjIzoQMGqYjTivuwyfC++CKqKqaKcwmuvAaDxlltouP56gm++lZVZNebl/iFrqigHINZvbquqqrTe8R8kfFqQ5Tj1VADMVVU4zziduWbD/+zlsR8Ptrc3/fNttGhZzv7Bqr8vgqJA3cpixsvRzgB9wSjvXVvFgpI8Xj3UmXV/IDJ0ZrU/xaBgyzPT2xqgaW8PqFCxyD3kY5adVcnysytZ/+FllNTm4+kI4u8L68F5PJoYsOz21b8eYseGJnZuPK6tdYhRP8Ox5ZljWa8jr8hGyBfF2x1i/kkl+n35xTYAPF1Ts599OHa/3Mwj33+L9obcTuGZvN0hFIPCqe+epx+zOuZ2Q6X+ZvbHEUIIIYSY0aKtrZgrKnKOm6u0PYHR5rGXFo5GusFSOlNZ8KHrcJ5xZtZ55ro6fX6qf/NmbCtXEmlsxDx/XtZ5AwWrAK4rrqD7tw8CYCoqwlRZicHpJOH3k3/xxZirq3GefTaBzZtxvyc3qwpgLteC1WhbO5b584k0Haf3oYfAoODbsIHiW24hfOQwJbd+chTfiZkvHk8Q9ETobPLR2eij67gvp5OskpG+8VgV7AYlN1jtDeNwWcYtq/qrjYc43qO9z24+byGPvH2ch97M/uAjGI3njK05EZvTzKEtHRza0oGiQPl815Dn5xfZuOBjywEordNKUP/nG68SiyS49afr2fJcA288cZSbvnduVmdac0YQnVdopbctQDgQHXWwlZormrmulCWnl+u3XcmSYE9ncNplIRMJlVceOci257Wf4z//tJ/3375u0PO93SGcBRaMRgMf+dZZREIDd6CeyyRYFUIIIcSUibW2Yj3v3JzjprIyMBimMFgNoFgsKMb0H+SV3/xmznmW2hq8L7xArLOTYzfehLW+nujx4zjWZf+B2n+0TYpt5cr0OYVFKIpC1fe/R/cDv6Xs9i9iqakBYOnWLSiWgZvkmMq1YD/aon2vPI8/Rtc99+jXL73t81mvYy7xdAb5291b8XQEsTq0P3v3bm5lxTmVegddyM6c7+8LUGM1DpBZDesjYsYqEktw51PppljVBXbcdjO+cIxP/u5NfvKhk7GajFqDpRFkVgH9dQIUVedhsQ3/z/3SWi1YTTWXCgWiHN7aSSKh0tHkpXZZeq9uLKqd4yq1M391MdtfbOJ333iVm394/ojWm9LXGcRoNnDNV04DtAAYwOG2ZP18UvtXWw71sXBt6aiea6Js/P1edr/cwur1NZitRt5+poFXHz3IWVcvzjk3HIzRsKOLmqVaQ6VUkyyRTcqAhRBCCDElEoEAsY4OzJW5nVUVsxlTeTmxKQpW1QH2fw7EVEj38GUAACAASURBVFYO0Sj+zVpzlPCBAyQCASw11YC2rxVAMQ0cMGTuGzUVa4FA/gUXMO/B3+qBKmjdgwfbY2qprcFYUIBv40YAYj09gLYnturO/5qzgeqz9+3id19/FU+Hlr0MB7Ss1dbnjvGHO16j+UDPgI/b3e1DMcD2F5t45Adv8eZTR5PjVLqzAsGxONqVvRe7wGHGldx/+cyuNh7fps1yDURjI86sxmOqfrusbmTNehwuS1ZA3t3i17v8djZmlwL7e8OYLAZtHmpyjWH/yDODh7d28MojB+ls9LJwTQlFVdqHCHmFWmZ1wZrsgNSWZ2bpGRVse6GRtqNDl9lOtiPbO6lfV8b51y3RS5fffuYYLQd7c8499FY74UCMky+el3OfSJNgVQghhBDjKrh1K9F++ycHEtq7F1QV24oVA95vrqoienyKMquB4IDjavozurVg1L/5VQCc558HgHXJEgAWPv4Y8/7wh2E9p7FodB1mFbMZ12XvxvfCi6ixGPHeXszV1cz77QNY6+tHdc2Zzt8X5sAbbSw5o5yLblyuH1+wJr330Zux5zGaSJeg9sUSetDVcrCP1/52mCd/sR0AW97A2e2ROtCWDvxqi+woioLLli6f/dYTu3mroYfDHX5qi078PsyUmRFO7e8cibJ56QB3/2utABhMir6HFaDtiIfmA73MX11CSU1+zrxZT2dQnx06FE9XkGfv28WW544R9EapXJwuly8od3D1F07hvGty38PnXVuPw2XhhQd2E4vmzsOdCtFInKA3SlGyxLxykZur//0UrA4TryebJ2Vq2NVFXqFVuv+egJQBCyGEEGLchA8d4uh1H8Jx1pnMu//+Ic8N7dwJZJfCZjJXVRF8661xX+NwDNRZdyCp8t7Aq5sxV1VRd889hI8cwTJ/PqDtJ03tKR1MxR130P7DHw66r3U4rPX1qJEIse5u4r29Y7rWbJCam7rqvGpcGeWVK8+r5sg2rYmRP6MhUDiUEfBkbEk98/p6igvtvP1MAwvXllK/buif5XDtb/NiUOC+G06jNF/LZLrt6WDVbTfzoXs2E4knOKVuZHM3o8l9j/NWFbPmwtoRr23h2lL9e7Rvcyv5RTbsLguBvrB+zssPHwDAYNS+WWvfVcveV1vw94WJRuL89f9twWQ2cP0d2Xu8+zqC7H+9lfYGL52NXnzJuaof/c5ZOAusGI3ZebSqxQO/j60OM+ddU8/T9+yk5UDfuI4SGq3Uhx+ujA8IquoLWHfZfF5++CDNB3qoqk//LJsP9DL/pJIBm7eJNMmsCiGEEGLcdPz0ZwDEOztPcCYEd+7EVFaGuXzg0RrmqiqibW2o8cnPnCSCgWEFq6ky3+jx49hWahli64IFI/oDtPC6a1n6xutjKtc1Jrsnxzs7iff2zflgteVgH4pBoaQuP2sOafkCFx/99llAeqYnZGcjDQq8UWXgEWeYP7R2M391Ce/7wqmsvahuTHtW/2dzA5f++B8AHGj3Ulfk4J3LylhVnZxzmgxWzUaFP996FvOKtYzqSIPVVNnsxTevHNF+1ZTFp5bpjZZUFeavLsaebybgjfLc/bto2tuNwaSFEKdcopWwmsxGlp1VQSyS4I0njuDtCtHTGsDXk92x95W/HOT1J47Q1x7AmpwJazIbcBXbcwLVEyko174/4eDUNyVSVVUPVjMbQwGsPL8ah8vC2xndjqOROCFflIIy2ad6IpJZFUIIIcSYBLdupeNnPye8fz+x9nYAEsETj5UI7diJbdWqQe83V1ZCPE6svV27PYnUwHAzq+mg0Lp8+RBnTix91E9nJ/HeXiy1I8+ozRYb/3cfOzceZ/7qYr1j7dX/fjJ5hTZsTjM2pxl3mZ0dG5o4aX0NBeUOouG4nlBdWJrHS+0+MEOtP5x17d9tbqDdE+LfL1464nV9/a9aJUG7J8SBNh+Ly7LLP1OZVavJSLnLxsO3ns2eVg91xSMrAz732nrWXTZ/VIEqgMli5KrPreW+L/wTgHmrSzj4VhstB/voavLh6QgRCcVYuLY0q6uyJbn+Lc8eo2y+i/ajHpr29WB1mJm/qhjFoNDR6KX+1DIuvnkVjXu7eezHW4nH1QHXcSKp0uOp7qDb2eTlsZ9sI+jRMvX5xdm/N8wWI0tOL2f7hiZ8PWEa93RRNk/7kCu1L1cMTjKrQgghhBiTnof+TODNN3GceQZlX/4SRTfcQLS1FTUWI9bdTSIQyHlM3OcjcuQItlUDlwADmKunZnyNmkgQPnRIf/6hpPasAtimMlgt1bJpsY5O4n19g3YfngtScz9Pffd8/VhVfaE+8gS02aGpc1VVJR5NkAAuumkFyyrSQWSo337Ih99s5KcvHuSZXdpezubeYM64mRPZ2tjLkU4/S8qzx67kJYNLazJr6XaYOXPhyGe6Go2GMXcttmQ0kqpY5MaWZyGSzGC2Hu6jtzWQlbGG7C7El35iFYoC215o5O+/2M6+11sJ+aN4u0KUJDsOpwK2mqWjqwKwJBtSRUNTt2c14Inw5C+264GqwajgdOfua16wppREXOW3X3mZFx/cy8Y/7APSHY/F4CRYFUIIIcSYRBoasK1aSfX3vkfxjTdiWbQQYjFibW0cOPscGj7y0ZzHhHbtBsC+evWg152qWavhffuI9/TgOOusE55rdGUEq4M0ipoMpmItqIk0HiPh8czZMuBAMmg494P1VCwcPGC/6CbtZxX0Rej1RzGpYFrtZukZFSyvTP9Mvf2ydsd7tc7CX3t0B93+CL946SC3P7ydncf7Trg2VzIYfXx7C7GEypLy7MxqsdOCosBXL5u6Dz1SMmfJWu0m7HnZs1MTCRWHe/BgNb/IRl6hTe8gvOXZY3qDpuLkbFSr3cT7bz+VS24ZvLpiKGabllmNhqcmsxqPJXj6nh0EvVHqT9P2MltsJpQB5vBWLnZTVZ/+N9lySHu/SGb1xCRYFUIIIcSYRBoasMxLj19INUzqe+JJ+P/snXd4HNXdtu/ZXrS76sWSLMtq7ja23E2zMcX0agKhJCEkQEgheQMhIYFQk/cDEtpLEkpIQu9gcGwD7jbulrtkSVbvXdvbfH+MtJKQZEu2qjn3dfnS7uyZM2dWa+088/wK4D50qNs+JyquBIRCf79ZEViWZaoefazHeQcCx5YtAJjnLzjhWEmrRWUyoY6KUnrDDhMqoxFVWBj1L/4NZBltp7Y33xZqilvYvaoY6BBEvZGYGUHShAiaa11UVCkiymJTXK5ZKR05osX1TmRZCVN1+wLU2b1cMi2BZpePF9bm89VhJez9rR0lHA9/IIjDqziAn+1TPs8Z33BWDVo1xx6/mKtnjZzfXVyqItwNncSq0aI8Ntu6uoJ6U9v2NlfXGtMhxBoqHOxfpzjenfM048fbQvv1F7VahVqjwjtMzuqWD/KpzG9myc0TO/q99pKqLkkSy+6cxnnfm8SND80jLFJ5j8IGqG/v6YzIWRUIBAKBQHDSBOx2AnV16FLGhbYZJ0/GNGcOdS++2G287PdTcd9vcGzdinbMGDTHadeiMplQR0R0c1YDTU00/vvfNH/yCVnbvh6wc2nHsXkL+oz0Xgs/fRN1eDi68eOHvapn5M034a+tw3rxxZjmzhnWtQw19eV23n18JwCRY8xd2q/0hi3GSMHuWqrKlT6ikfFKf8/OYtXu8VPS4CQlyhxyVRdPiKWkwcmKfZVUtbgJN2n5eG8Fv102CaOue5GsojoHb+0oJRCUmZ4cTk5pEyoJ0mKOL6iHm9ufOTvksBotHS7qtMXJbP+kkIj4rrm0ao0yNiZZOS9rlJFymogcY8br8lOwuwakgXUTtQb1sIQBN1Y52L+2jClnJZIxOy7U7/V4fwL0Rg1Zc+MBWHbHNKoKmlFrhW94IoRYFQgEAoFAcNJ4ixUnq7OzChB1++2U3nZbt/Gtq1fTsmIFAOZly044vzYhoZtYlV2KaAg6TtzHsb8EPR6cu3YRcf3yPu8T9/sHQjmjw0nMT3863EsYNmqKFbFw7W+yQ7mQx+PxlYfZt7eMRQ41x9Yqn6/YMYrI0qpV/PHyyRTVOXll8zH2lzcrYrVR+dwlhhtJjjCxr0wJ5Xz48inc/eYeVh6o5KqZHa7owysOEW7U8veNhdg9fhamR/HHy6dwxfObiTLrMGhPvvrzUKDtJLw7hwEnZUUw5f+dicHc1RGNGWthwVXpTFyYEHp+eEslGq2KrHlJbP2gAGRQawZOoOkM6mEpsHR4SyWSJDH7klSgowJwZIK5T/vHJFuISRb9VfuCEKsCgUAgEAh6JejxIHu9qC09X1j5SpTwR924rmLVvHABhkmTcB86hCqsw0Fq/eKL0GPb1Ved8PjaxDF4Co91XVO7SPUP/EWqa/duZI+nT/mq7VjOOWfA1yHoH/XlDjRaVah4z4lYn1tLnsrLguRIPKUufMgkJnR8Tm+ePw6vP8jr24r5aE85F09NoLhe+dylRJlJjlRcxenJ4VwyLYEnV+fyzs7SLmL15U0dn9sHL53ErQsVYfPIFVMIyidXAXe46BwGrNWruwlVUEJdzzh/bOj55LMScbZ4SUizYYs1KmJ1gNHqNUMeBizLMvk7a0ieFBkqMmWy6rjgh1NIzPx25ooPJsJ7FggEAoFA0Ctld95F3uw5obw9z7FjVD70ELLPB3RyVseO7bKfJEnE/e53ymN9R16Wt7wcfUYG8Q8+iHnBiXNCtWPG4KuoCB0flNDjwUAOBrFv3ARaLebZswflGILBob7cTuQYc5fCQCciKEFZpgk508JhXYBIS9eCQTqNiv+5IIsvDtfw3Ff5FNQ6CNNriLPqSY5U8i6XTIhFkiQumz6G7ccaaHQoBZ7kb4jRlOgOx+3yGYlcecbIyUvtC8ZviNW+oFJJzL1sPGMnR2GLMaEzKL1YBxKdQT3kBZaaa120NrgZNy26y/b0WbFdwqUFA4MQqwKBQCAQCHrFsXmz8nPTJgCqH36YpjffonXNGoqWX0/d8y+giYvrsSepaeYZRP7g+wTq6zl67mIA/BWVGKZNJeL65X3K8dSOGYPschFoagptCzo6WuH4ystP6fw6U3TtdTS88gqm6dNRmfsWzicYGdSX27v0/DwRDW2isqLFTV26iS2RMnpNdxH2g0WpXHlGIk+uyePtHaWkxZiRJInpSeGYdWqWTVVCXs+ZEEtQhg1HawFCxZTaSY44cc/ekYzOqAndCGivwttfbnvqLJbcMrAVs4cjZ7V4fz2ghEMLBh8RBiwQCAQCgaBX1OHhBJqaKP3h7Ziys0NOasV9v0H2Khf8+rTxve/fFgLsr6wk6PXir60NtaTpC5r29jXlFWgilIvDzrmqx669jswtm/t3Uj0gyzLugwcBMEwevhY0gv7jbPHiavX1KlZXH6zis/2VxNsM7C5u5Imrp9HoVD67hytbOVzZwvjonm9OSJLEo1dOYcW+Cly+AOPbiiJNSbRx4KELQjdcpieFE2nWsS63lstnJFLb6ukyT2K4qdvcowlJkjCEaXG2ePvsrHabox+ud1/RGTS01LkHfN7eqDrWzNaPCkhIV0KbBYOPEKsCgUAgEAh6RJZlgk4ntiuvRJ+eRv0rrxKoV1wFORDAMH0a7px9hF9zTa9zqMI6cgh9paUAaBP6LlY7eq2WY5yitLnpLFYDDQ19P6Hj0Nm5jbjhhgGZUzA0hPp3JnYIzkBQxun1Y9Squf3fuwDQqiV8AZklT64Pjauze4gy63hq+Yxe5zfpNPgCSljvwvSO0M/OkQFqlcTZmTGsy60hEJS7idWeqgSPNowWLS67b0ALJJ0qOpMGj9M3JMeyN7r5/IV9mG06LvrR1GGv/v1tYeR82gQCgUAgEIwoAk1NyF4vhglZRP3gByQ8+kjotaRnnyXllVdIfOpJLBdd1PsknS7oWj5T+q7qx6f2eQ0dYrWjInBnsaqOiurzXO34Kioo/dGP8Tc2dmxrKxSV9MIL3SobC0Y2jVXK5yGiUyXWJ1YeZuqDq7ntXztD23wBmfuXTQh9JM/OjCHKrOO17885YRuZn5+XAcAl0xJ6HXPuhFganT5yypq6iNVF6dG97jOaMIRp0erVI0qkmaw6XHYfwUBw0I91aHMlLruPi++aLnJThxAhVgUCgUAgEPSIv6YGAE1cHABhZ56J7corGfuv17AsPheV2Yx12bLjXrwGOgnC+pdexjB9Gobp0/u8BnV4OJLRSPMnnxD0epGDQVpWrgQg8tZbCTQ3Iwf7dqHq2r8fx9atNLz2L+zr1+M+eCj0Wu1zzwOgSxnb2+6CEciekkY2769BUkmYOgmIVQerAdh4tI6rZiaGtl82PZEFacoNjqtmJrLjt+cxJdF2wuP8bEkGRx+96LjtZs7KiEYlwdojNXy+vxKVBLcuGMcz3znjZE9vRGEM06E7yXzVwcJk0YEMLvvgu6uFe2pJSLP1uT2NYGAQYcACgUAgEAh6xF+tXPBrYhWxKqnVjHn8sX7NYbvsUuqeV4Sg7PUS85O7++XMSJKE9cILaf7wQ9wHDuIpyMe1ezfQ5rr6/QSam0P5rMej6NrrAFDbFHHSHvobaG7GsXEjmrg44aqOMp5ak0fY0WZSJTV2rx+LQalaG2PRU9Lg5D8/mEtKlIkPdiuFuOKsen5xXiab87cyIzm8z9WDJUlCqz7+2HCTjlkpEfz762KanD7uWZrJT5dknNoJjiCmL0kmdcbIcolNNuUGhbPFi9mmP8Hok0eWZRqrHMw4L3nQjiHoGeGsCgQCgUAg6BFfm1jVxsWe9By6lBTS168DwDhjBuZFC/s9R/h11wJK+K97377Qdk1sDAD+mtp+zRdobm772dS2v+Igx/76f5A04j7+aCEYlNlb0kScVkMzMnMe/ZKtBUpOdVWzm6tmJjI/LYpYS4eIkSSJ7HGRFD1xMSlRA++QnZMVS5PTx/gYMz86u/fCY6OR+PE2MmcPbOuZU8VkVX63zhbvoB7H6w4QDMgYwkT471AjxKpAIBAIBAJAaQPT9P77eI4dA8Bf3RYGHBNzSvNqYmKIuPFG4n//wEnlu6lMiqgIOhw4d+3uMi+Av7Z/YlWbrLgj7c6qr+08tW3hzoLRQX6tnXmNEjFOcEgyLl+A7/zjax5ecYiqFjcJNgMAGrWK8ybG8YdLB7/K88VTE4iz6nn8yqk9tsIRDCwmqyIeXYMoVt12H631SsVho0V7gtGCgUbcPhQIBAKBQIC/vp78Cy4Evx/TnDmk/Os1/NXVqKOikHSn5iZIKhXxD/zupPdv73nqLSrCW1hI2HlLsF1yCZpoJSSxz2JVqwWfj8ibvkvtM88SaFIc1lC4sxCro4pdxxqY4VUuZSdHmFlyzWQ2Hq3l5U3KzZYEW0drkZduyR6SNY2LNrPt/vOG5FiCDrE6GM5qZX4TG97Oo67Ujt6sfM4MZiFWhxrhrAoEAoFAIMCTl6cI1dmzcW7fjvvIEXw11WhOIQS4J6qLWsjfVdOvfVRmpUdl69qvAIi+4w6sF17YL2c1b8FC8PmwLltGxE03obbZOoUBt+fmDuy5CgaXwzkdn6MZ8xK4dPoYHrikwz2dkRw+HMsSDCFavRqtXo2zeeDF6o7Pi3A0eYgdZ8Xj8ANKkSnB0CKcVYFAIBAIBHgKCgGI++39lPzwh5T/7OcEfV4MmVkDepz3nlBaiaTPWtznfdqdVXfOPtQ2G4aJE5XtJhMqsxl/XS0BuwNJo0ZlMPQ4R3s/Vl3aeCRJQh0e3hEGXFODOjwclX7wCrQIBh5noZ2ACn74p0Uhx8ti0HL1zCSCstynKr+C0Y/JqsPZ4jnxQODA+jJyvipjylmJTDk7sdeesX5vgIqjTUw5M5GYFAtfvKpUDjeECWd1qBHOqkAgEAgEAryFBajCwtBnZZH09NN4i4vxV1RinDVzUI4ny3Kfx6p0OmgrfGSaOxdJ1XH5oomJwV9ZRV52NmV33nnCudQWq/IzPDxUaMlfXSNc1VFGY6uXuJYgqiQTRosOqVNV3yevm87Ty2cM4+oEQ4nJpsPZemJntbXBzeb382mqdrLp3aMc3lzR69jaklYCviCJWeEkpHXc9DAKsTrkCGdVIBAIBIJvObIs49y9B31mJpIkYcrOJv6hh2j+4AMivnPDoBzT4/T3L//Lr4ThmbJnddmsiYmhdc0aABxbtva4q9y2L4DKYgEUseotKVGmrq4ekfmqwUCQyoJmPA4/Pm+ArLkjqxLrcLJ5axkmWSL1jFMr/iUY/ZgsOhoqHccds/WjAnb/t5jO9d1qilt7Hd8+X1RiGNbojtxn7QjrM/ttQIhVgUAgEAi+5bgPHsJz5Ahxv38gtC1i+XVELL9u8I5p951UsZL2Sr7taGI6+j4apkzpcZ+guyNEUGVULjw10dH465U2J76aavQTJ/R7LYPJ0Z3VbHgzD7fDF9rWm1gt2FODzx1gwvyEoVresJOzt5pwYOGipOFeimCYMVl1lOU29vq6HJTZ/d9iAGZfksr2T5UCXEd3VJM5J46kCZHd9mmsdKLRqrBEKmkF3/vzIhorHSdVzVxwapxyGLAkSWpJkvZIkrSi7XmkJElrJEk62vYzotPY30iSlC9JUq4kSRec6rEFAoFAIBCcOk3vvotkMGC75JJBPU7AHww9dvUhbK8ntGPGdHnepa2OuufLGtnt6njscbftF43sdBJobiZQV482dmQ5q8dy6gBIm3ni8OT//u0AX752eLCXNGJodvooLW8loJOwWUSe8bcdk02Hx+nnyNeVoW2yLIf+3rjsyg2f6OQwZl6QwuKbJ3DRj6ZiiTLw6TM5HFhf1mU+WZapKW4hIsEcCi83WXUkZkUgGHoGImf1Z0Dnv5D3AV/KspwBfNn2HEmSJgHXA5OBC4EXJEkSXrpAIBAIBMNI0OGgZcUKrBdcgNpqHZRj5G6rYveqYlytHS5h58ffJOAP9ipmtQld3cPOYlX29jxnZ2e13X1Vt7W9yZs7D2R5xOWs+jwBwiL1nHNDR4GrnvJ8g4Fgt22nO+vyajAHJKyRPRfTEny7iBun5JRufjefYFD5P7JndQmv3b+FxioHjibl/3/2snGoNSomLhjD+DNiuPrebJInR7L+zTy+/OchvC4lXSB/Vw2VBc2kzxpZfxO+rZySWJUkKQm4GHip0+bLgdfaHr8GXNFp+1uyLHtkWT4G5ANzTuX4AoFAIBAITo2WVasJOhyEX3ftoMwvB2W2fljA7lXF2Jvcoe0ue+/O6qp/HOCV/9nUozhrzzltp6tY7XnOdmd1zJP/D31amrJfdNdcx4Fu0XOq+Nx+tHo1hjAtcy8fD0DQ3/39aKru5Br3o2jVcFDT6uZ7r26nvMl14sHHYX1eLRGoiI0zD9DKBKOZ5EmRXHj7FNwOH+VHlHDgxkoHrhYvnzyzl6pCpZCaObyrC683alh2xzRmXZjCka+r2PF5EQFfkPK8JnQGNWcsHTvk5yLozqnmrP4F+DXQ+ZsjTpblSgBZlislSWr/658IfN1pXFnbNoFAIBAIBMOEa88e1OHhGGcOTtXf8qNNIWdj/Ru5SCoJOSiHQvN6oj0E1usOoDcqlypKX9TmbjljncWqt6CAqkcfI/6393cZ0+6sqoymTvtFdxmjHWEFlnyeAIa2no4areIt+H0B1NoOn0GWZfZ8UdJlH51Beb/qy+1sfj8fvzeASiUxadEYMucMb4GmT3MqWZtbyx8/Pcjfbso+6XkKax2kBCXChLMqaGPc1Gj0Jg07VxZRcrgBl92HyaqEB294Kw+AsPDunxeVSmLeFWmUHGpg75oScrdVIUkQk2LpUmFaMHyctLMqSdIlQI0sy7v6uksP23q8BShJ0u2SJO2UJGlnbR8afQsEAoFAIDg5vGWlaFPGDlrhkLztVaHHdaV2zrkxC0kl4fcGehzf2R10tXQ4pWmrV5GxcUO38V1yVoHGt95CDnYNjW13VlWGDmdFE91VrI60asA+TwCtXsmW0uiUn35f1/Pas6aEI1sqCYtQzsvd6QbAF/88RF1pKyq1RF25nTWvHOLgxvIhWn0HD35ykPd3KTmBhypalJ+VLSc9X2GtnUMlTWiChM5bIFBrVaTNiqXiaBN715RQmd9E5BgzV/+6o3q4ydp7QTejRXlNq1PhbPYSP1706B0pnEoY8ELgMkmSioC3gMWSJP0HqJYkKQGg7WdN2/gyoHMJvySgxwZHsiz/XZblbFmWs2NiRElygUAgEAgGC19ZObrEwamoKssyx3LqGDspEkmCtDNimLggAY1Ohd/bPdcyEAiy9cOC0HNnJ7Gqttm6CVPoyD0N4fMRaGrqsinoUsKPJUNHCwpNVBQx99zTMU/EyCqeorikbWK13Vnt9J5VHG1k64cFpM2M5czlmQBs+7QQUEKvGyodTJifwBW/mEn6LEWIr3s9F18vNwkG5RwCQf65pYhfvpvDT9/cw8d7FbHc4vKfYM+ekWWZxU+uJzyg3FixxRhPsIfg20TnatledwC9SUvUmDBufmwBF985DVUvBdgAFlyVzuSzErnhwXlcc182My9IGYolC/rASYtVWZZ/I8tykizL41AKJ30ly/J3gU+AW9qG3QJ83Pb4E+B6SZL0kiSlAhnA9pNeuUAgEAgEglNC9vvxVVaiTRpYsZr7dSXbPimkqqAZt91H6gylmMmS701CkiQ0OnU3Z9XR7OGjJ3ezZ3UJcalKoafOYrU31OHhGGfNQtOp8JL/G1FZ7RWAOzurAJG33Bx6LKkGoubkwNHZWVV3CgNuZ/uKIiwRBhbfPAFDmOIK5W2rxuPy42j2EvTLWKOUsMeIuI7w5/b8vcGmpN7JzS93XOZ9ebiam+ansDw7GbvHf1L5tUX1TgDCg0KsCrqTkGYjOjks9Lz9/4Ul0sC4adG97QYo/VTPuSELtUZF3DhrKJxeMPwMxl/mJ4ClkiQdBZa2PUeW5YPAO8Ah4L/AXbIsD93tPYFAIBAIvuXIwSD+OiUf1H34MAUXVLSOjgAAIABJREFUXAh+P9rkgROrsiyz7vVcdn5exAdP7gYgNsVC3Dgr2rZwVq1O1c3h272qmJqSVs6/bTIX/Xgq0Lf2NpIkMe71/2BddlFom7+mpsuYnpxVAJV+ZIaRyrKMz909DDjQFgZcuLeW8txGxk6ORGfQoDd1XFjbG9y01ithz5Zo5Xw7h8tW5HV1nQeDN7aVcP5f1rO1sD607bIZifzh0smMizYTCMq4fT1XMX5+bT73vrcPt6/7JeKOYw0AjGu76WCNFmJV0IEkSVx857TQc4NJCM7TgQERq7Isr5Nl+ZK2x/WyLC+RZTmj7WdDp3GPyrKcJstylizLKwfi2AKBQCAQCPpGwz9f4+iiM/GWlVH529/hK1fCMs1zBq44v9cdwO8LMvmsRFImR2GNMRKVGNZljOKsdhUrLbUuIuLNZGTHYQzTggTOfvRilbQd+Wj+mr45q+2obCMrPy3gDxIMymh7CAP2uPysfHE/AJFjlPfV0qnQUGuDm5Z65XzbndXxM2I473uTiE4OozyvcVDX7g8EeejTg0xLDGf2uI7Q6lsWKGGVYW2OVaune4GtYFDmf1fl8vbOUt7cXtLt9R1FDUSYtFw/MQGjRSvcL0E32t3Ubz4WjF7E/3KBQCAQCL4lOLZsUX5u2oQ7Nze0XZcycPlZ9kZFKCVmhpOR3XPRop7CgFsbPSEHUKVWYQzT4mzy9LR7j0g6Xeixv7YXZ9XY3YlLX79uxDmsPo/y3oSc1U5hwJVHO5zR9vBenUHDrX9ayD/v3Yy9wY3boQjBdhErqSSy5sZTV2Zn39pS/N5AyK0daIrqnXj8Qa6bnczlM8ZQ0+ohMbzjfbe0nVOr20+sRclrLai1MyHeSl5Na2jc6oPVfG9hape5dxQ1kD0ukqYqJ+GdQpsFgnY02o7Ptd4kxOrpwMhK0BAIBAKBQDBoqK1Kp7n6l18BWSbljddJX7d2QI/R3qbmmz0NO6PtocCSvdFNWESHQ2iJMtLa4P7mrr2i6iRWfRWVVD32WCh3tcNZ7d66QhsXhzo8vM/HGWzKcxt5/89Ko4Vu1YC9QQ5tVmpTZsyOIyG9wxE2WXSo1BKtDR5a6tyYrLpugjQhzUbQL1NXZh+09edWKYJzQrwFrVrVRag2Vjko/8dRxvlU2N1KkaVnv8rnwr9sJK+6ldUHqwG4dlYSXx+rJ7eqlZpWN2uP1FDT6qao3snslAgaKh0hV1kg6I3IMaIP7+mAcFYFAoFAIPiWoLIohYt8paWELVmCaRB6q9obFbEadhyxqtGpu+Sj+rwBPA5/l9xKa5SB2tLWnnbvkc5hwM0ffYTs9eKvqibpmb8SdCo5nNIIc1C/iaPZw4rnc0JCvl1sthdY2r2qmOpjLcy/Mq1btVJJJRGVGEb+rmpMVh2WqO7CPDZFuVlRU9wy4K05DlY0c/8H+zHpNKhVEumx3cVkeV4TBGWWOXXYPYpYza1S2tgcKG/m7R2lLEqP5v5lE/nvwSpu+MfX1DuUz8lfls8AYHq0hZ1OP5EJQogIjk/7510wuhHOqkAgEAgEowx/QwO1zz5H0N135xGAYEfobeR3bxzgVSm01LlAOr6zqtGp8HVyVu1tDqqlk1i1RBlobXAjB/tWNbZzGLDsVQROsM1RdR85gnbs2BFX8feb7F9Xht8XZPwZSoueoL9NtLaJ1epjLaROj+aM88f2uP/Cq9NpqXNTVdjSY/Ehc7geo1VHbXHXmwBN1U5Wv3QAr/v4LWXsjW5qS7ruW1PcwruP7+C9T4+SU9bM1sJ6ls9OxqDtHmbcUtd20wBodSuhylFhyu/81c1FlDe5uH5OMhFmHe/9eAFJER3nsGJfJUatmjhJmTciQYQBC3pm+e/mcP3v5wxa72jB0DKy/2oLBAKBQCDoRvNHH1P3/PPUPv2Xfu0XsCvhn7q0NEzz5g34umRZpnBvHQnjbag1vV9ifDNntaHSAUB4fIdbZo0yEPTL2PuYt9rZWQ0RlJEDAZw7dmCeO3BFpAYDnyfAgfXljJ8ew/nfn8zCa9JJmxUL0CWcd/FNE3u9CE/MimDCfKXXZE/OqiRJxI61UPMNwfn1x4Uc3VlDTfHxnexP/rqXdx7b0aWS8+b38qkpbiViTzPXJEXzt5tm8cDFk7rs52jycGxfHdXHFBdVJys5q0AoHHh/eTNRZh3nT1LWnxVv4YM7F/K9heMAWJdbQ/a4CDxt7YwsEd3PTyAAiE4KI0qEiZ82CLEqEAgEAsEoI9CqXPQ7tm7t135BuwOV1Ury314ccNfB1epl5Yv7aax0MGFBwnHHdharJQfrKT/SiCR1zTGLT7MhqSQ2vp3XJ3e1s7MaIhjEffgIwdZWTHPm9u+EhpgjWyvxOP3MWDoWtVbFjPPGhorFtDurcOIKpwuvziB+vJXkCRE9vh6TYqGx0hEq4tRQ4aBgj1KQaufnx/C6endX23OIr7n/C1ranNHWBjfW8RYaVDLjc12cNTYS4zdyZde/mcvnL+yjoq04lAaJ+97dR0WTiwZHRzj4komx6Drd5FCrJJbPTgbAH5RZOikOR5tYNdl6+H0LBILTDiFWBQKBQCAYZfgrlCI73+wneiKCra0Yp0xGlzQwfVWdLV4C/iBVhc289fB2ig/Ws/CadCbOP75YbS+wdGhTBZ8+m8P+9eXYYk2hPqwA0UkWFl6dzrGcOrZ/duyEa+nRWZWDOLdtA8A0wp3VgxvLiUu1kpDWPZdUrev75ZohTMvVv84maUJkj6/HjrUgy1DXlg+8c2VRyLktz21i64cFvc4d0eZ8z3doyClUOhO6Wr1UBP1ssAaQfUGq2tzTdqqLWjiWU8fYyZEsu3MaZ7Tl2upluP3fO6lsdrEgLYrvL0zlV+dndTtmvLXDQV0yMQ5nsxeNThUqPiUQCE5vhFgVCAQCgWCU4W3rjxpoaiLodPZ5v6DDjso8MOFxHpef1//wNTs+O8aqlw6g0am49r7ZzDhvLJLq+K6tRqfG5wmw/o2O9jkpU6K6jZu2OImM2XHs+ryoWz5l9bGWrtuk7pc0ciCIY/s2dKmpaGNj+3mGQ4cclGmscpKY2XNVYrVaObfMOT23AuoPsSlKka3ig/Wsff0IR3dUM/WsxNDrncOu935RQtH+utBzj9OHSydhkSUOb6jA6/YrNx0aHEyaGAUSVBxt6lLF+b0ndgJKiHLqtGii2nJNn7xiKgcrWiiodZAUYeT3l04i1to9tNdm1KLXqJg8xkpiuBFnsweTTS/yEQWCbwlCrAoEAoFAMMrwVVRAW7EgX1UVvuoavGVlJ9wvYHegChsYsZq/sxqvy8++r8qwN3g4c3km0Ul9m1ulVoRGWKSeGx+ax/wr05h3xfhu4yRJIiM7FlmGDW/mEQwE8XsD7PjsGO/9aSdfvHqoY3Bb8Sh1THRok3PbNhzrN4x4V9XR7CUYkLFEdS+K1M4P/3IWS26d1OvrfcUcrsdk1bFrZTGHNioOfdb8eLLmKbmi7X1y5aDM5vfy+ez5faF93XYfNRYVRzUBPAeaaKpWbpTU+f1cPjsZW4yRvWtKeOvh7QT8wVC/V+hwZXVGpRHFrMRwfrk0E4BIc+/FuCRJ4taF47jznHRAea/MIgRYIPjWIFrXCAQCgUAwivAUFuKvqCTsvCXYv/gS9/791Dz9F9Q2G+M//ig0zltaSsktt6JNTib6zjsxzZmNv7JywMTqoc2VgFIYSKWSSMzsOUeyx3NwKI7o3MvHEx5n6taGpTNRicp6c7dVkTEnjqZqJ9s/VcKC23MggVBeqzYunkBtXZc5zHNHdr5qa71SJbenokjt6AwDd8kWm2KhaH996Hlkgpnzbp2Eyaoj58tSWupcrP3PkS77BPxBvO4Addog+40+0lvVbH4vH4DJqREsnRTH/sU+ju6oprKgmYYKB8GA8jtJz45lXJtzrjcp5+Fx+bnr3HTC9BrOzjq+6/2biyYCEAzKtNS5iEsd2LY7AoFg5CKcVYFAIBAIRhFN770PGg0xP/kJAJUPPoS/qgpPbi5HzzwL565dANg3bsRXUYFz2zbKf/YzKh94AABNZN9FZW/Ul9upKWpBZ1DyBmNSLP3KITzjgrGcdX0mGbNOHNbaWcA5m70c3FDe80C5rc1LfPc5zQsX9nltw0FFviK6rccRqwNJQkZHuPHZN2SFQmqTJ0YSDMi89ch2yo40hsZ43X62fVIIQIPfT61a5qguELpZMD1dyY+dek5SyP2tKW6hqUZxXmdfnBoKDW93Vr0uf5trmkpqdN96ph7dXoW90UPazJiTPneBQDC6EGJVIBAIBIJRguz10vzRR1jOPRfDhAmELVmC7HJhu/oqAPy1tRTfcisNr7+Oa+9e1DHRjF/5OUGvl+b33kc/cSKRN998SmsI+INs+aAAlUoifbYiDDOy+5dLabbpmXpO0glzW0EJA73iF2cAkLe9isaqnnN05YASBqwymVBZLKHtmdu3obZa+7W+ocRl9/L1R4oQtEQOjVhNO0NxMq3RBqZ0ylcdkxGO3qRBo1V1qUD8wf/uZs/qEgB8wI/PTmOftiNfeGpWR76xNdqAyapj5+dF5G2rQqWRsHXq+druEB+v6nBPBPxBtn16jOjkMNJnjtz8Y4FAMLCIMGCBQCAQCEYJrWvXEWhoIPzaawBIeORhPDfegGHaNBybtxB9xx3Y166l+uFHALAsXYo+NZWEP/yeinvvI+bun6Ay983F6o0t7+dTcrCeSYvGMO+y8diijUw5J/HEO54CiVkRmKw6yo40ojNqQkKnc0sb84IFSAYDkTffgvvAQQJqNfEP/mFECdWa4hbK85o4Y+nY0La6EqX37dnfyezST3UwscUYOXN5ZreCTmqNiqt+NQu9WYNKLVF6qIE1rxyivtzO2MmRlBxsIGDTcun0BP6xrgC3GvZpfPwguSMsV5IkLr5rGqv+cYCSQw1MmB+PupPwbXdWPc7+idVDmyporXdzzg3T+3STQyAQnB4IsSoQCAQCwShA9vloeOUVNPHxobBWTUQEmgULAMhYtxaA8Guvoe7//g/7l18R+8t7ALBdfjmm7Gw0Y8ac0hpcrV4OrC8na14859yohI8eL990IAn4lTDfrHnx7F+rFJPyugP4vQE0OjXa2Fgm7N0DgHn+fCSNBuuFFw7J2vrKp8/m4Lb7SJ8VG3JRa8uUFjLpfQiJHkimndtz+6LOvW4z58RjsupornUxadEYrnphM5E6DemxYUhqiefCXESadRi0XUV2bIqV6347hwPry5gwr2sbI71Rg6SSuhRf+iayLHer9lu4t5aoRDPJk3puySMQCE5PRBiwQCAQCASjgOYVn+HKySH2nl8gqbs7cA2VDnauLEKWIeauu0j94H1048aFXtcmJp5yu4/8XTUEgzJnLB075K1DMufEY7TqyL5oHFf9zyzGtokWZ4u329j4B35H3G/uG9L19QW/TxHcxZ3awdQUtRIWoccQ1kOf2BFA0oRIJp+pfHZKG90kR5jQa9Skx4YhSzAmoucKxnqjhlkXjsMc3rXSr6SSMFq0OJuV31ttSSufPLMXn0cJ496zpoS/3b2eQ5uVSsWlhxv44p+HaKl3ExFvFi1rBIJvGUKsCgQCgUAwCnDt2YPKasV66aU9vr5/bRnbPi5k49tHkWW5xzGngqPJw47PjhEz1tLFfRsqzlyewa1PLMRk1ZGQZmNqmzPoau3doRtJyEEZ2sKWy9sKEzmaPBzLqSV1+sgvGOT2Baize0iOVMTppAQlvDoqrP9tZMw2fegmw9YP8yk91EDxAaU68YEN5QT8QTa+c5SAL8hnL+wj9+sqWmpdQ5bTKxAIRg5CrAoEAoFAMApwHdiPccqUXp2lyoJmNFoVBzaUU7SvrscxJ0swKLPmlYP4PAHOu3XSsLhbkiSh6pSraLQoIsnV2t1ZHYm01LtCzmpNsRL6m/NVKXJQZsZ5ycO5tD5R1qgUtkqONAFwzSzlZoG3LTy7P5isupBYVbeFEFfkN+HzBmipcxGdHIbfE6CmpLXLjZfjtfYRCASnJ0KsCgQCgUAwwgm63Xhy8zBMm9rj6163n/oKO9PPS8YabWDn50UD6q7u/OwY5XlNnHV91rC4qj1htChhs84RKlZLDtbz5h+3semdowA0VDgASJ0eTUuti4+e3s3BDeWkzYrFGt1zKO1IYtXBagCmJirFlBakR/PQZZN56LLJ/Z7LZNPhaPYA0Fyr9JitLW6lqcoJMkw+UynY9dnzOQT9HZ/jsAh998kEgtOVlkr44Hb46E5wNgz3aoYNUWBJIBAIBIIRjvvwYQgEME7tWazWldlBhvhUG9YoI2v/c4T8XTWMmxaN9hQrzO5bW8qOz4rImhvPhPnxpzTXQDKSndXdq4rZ+mEBACq14gbXt4nV7GXjOJZTR3muEgrcuTLwSMUXCPLvrcWcmRHN+Jiw0PZbFow7qflMVh2uFi/v/WknjZXK+9La4Kb0sHJBnpQVwfTzknE0eYgaYyZunI2vPy4gLtV2vGkFgtFJYzGExYHWAH4P7H0DjBFwbAPse1sZEz8V5t0xvOscJoRYFQgEAoFghOPevx8AQy9itb5MaX8SlRRGslXHlg/zWf3SQfQmDVPPTcIaZUCtVZE2Mxa1+vhBVfXldurK7GRkx4Iksfu/xSSk2zj3uxNGVHEbrU6NVq/G1TJ8OasBX5BX79vE2d/JCvWaDfiD7FlTQvKkSMLC9RzLUUKyGyochEXqiU2xsuzOaXz+wj4SsyKITRk5rXV6Y9XBKqpa3Dx65ZQBmS8i3owsKwWn5l+ZhsfpY/fqEnavLiZ5YgThcSYWXZPRZR9RBVhwWlK6A145H7RmSFkAR1d1fX3CJVBfAFufh+ItMPkKmHJ1/44hyzCC/nb3FyFWBQKBQCAYwciyTOtXa9EmJaGNje1xTE1xC3qThrAIPZIkceZ1mWx+P5+gP8jOz4pC4/yeIJMW9d6+pqXOxTuP7iAYlHE7fESNMeNo9rLw2owuvTJHCkaLdljDgF12Hx6Hn3X/ORISqzXFrbjtPiafOYamaiduhw+fJ0BDhYOoMYormZgZTtKECOZeNn7Y1t4f/rm5iJQoE+dm9fz56y+Zs+NInhiJyaq440e2VoIMHoefeVekDcgxBIIRj98LK36uuKoZS6FgnbJ93l0wdh7s+bfipjYUwua/QuF6qDnUN7HaWIyn9jD/Ll9HSk0esxMXEr7ol4N6OoOFEKsCgUAgEIwgWr9aS82TT6LPzMCxYSNBlwuCQWLuuafH8blfV3Lk6yqy5saHnM+sufFkzY3H7w3QXOtCa1Cz4tkcjmyt7FGselx+8ndWs+X9fFRaFSazhu2fHmNMug2tQU3qtOhBPeeTJSzCgL3BPWzHb+/96nUHQtucbbmYthgjfq/yekudi8ZqR6jdjs6g4fKfnzHEqz059pc1s7O4kQcumdSlwNWpIKmkkFAFsEYrhZPSZsaMCqdZIBgQNj0F1QfgO29B1kXKtpZKRbyqVDDpMmXbuEUw82bY8iys/h0cXaOI257we+DN7+Au/Iqfx0az2aTkwy8sa+VFhFgVCAQCgUBwitS/9BLeggK8BQUYpk/DvGABaquNiOXXdRt7bF8dX752mKSsCM65Mavb6xqdmqhExc2bMD+BrR8W0FTtJDzOFBpzZGsl69/IDVWqXXRtBsmTInnzoW0U7a9n4sIENKeY9zpY2GKNFO2vH7bj+72Bbtvaq9waLToskX4AynIbCfplIhNHRnGq/vD2zhJMOjXXZicN2jFiU6xMWpjArIvGDdoxBIIRRTAIW56DiZd1CFUAa0Lv+6QtVn6+fg3cXwG6Hv6elHwNBV9yb2w0W0wdhduWzvzxAC186BFiVSAQCASCEYK3rAzX7t3YrrySoMNB7K//B11SzyLhWE4tX7x6iOhkC8vumIZGe3xBmTU3nq0fFZC/q4bsZeMApajNujdyiU2xsPCaDMJjjehNSpXdaecmsW9tGbMuHDeQpzig2GKMuFq8eN1+dIahv6Rpd05BCdeWJAlnixdJUsSq16WI1Yq2vqqRCaNPrJY0uMiIDcNq0A7aMTQ6NefeNHHQ5hcIRhxNReBt7d0h7Ym4yXDxU/DZPfC3s+C8h5T9NR1VsuWCr1hvNPKV2cQd036MRW/lzzv+zOKxiwf+HIYIIVYFAoFAIBghNH/yCQAxd/8E7Zjec0sB9n5Ritcd4PwfTEarP7HzaQ7XY4s2Uldmp6a4hc3v5VNfYUcOyiz9/mQskV17WC66LoPZl6RiMA+eSDlVbDGKQ9xc6yIm2TLkx/f7OpxVj9OPwazF2eLFEKZFpZJCwr+mqAWgi6M9Wmh0eIkK0514oEAgODHuZshdCU0lyvO4fhYtm3Ur7P4X1ObC2zdCdCbcsQWqD9AQ9PNQ8Yd8FR+DRtJwTda1xBhjuCbzGoyakd8eqzeEWBUIBAKBYAQgyzLNH3+Mae7cEwpVUMTRuGnR/RJAEQlmCnbXULi3Fjmo9K+csCChm1AFkCRpRAtVUMKAAZprhkmsdnJWvS4/rlYvhzZVhH4nOqNyE8He6MFo0Q6L+3uqNDi8ZMSGnXigQCDoirsFVGpw1MKRz6FoI+R/AYG2onAqDcRM6N+cKjX8aD1uTytF255Fs/EpUrY8w0M5z/FZmBm/VuLOuEUsmfsLYk1KQbTRLFRBiFWBQCAQfEtoqXOx7dNCMufEkzwhAtUJWrgMNe4DB/EVlxB9+4/6NN7r8qM39u9rXG9SxidPiCBrXjwb3spj1oUp/V7rSMEW0yZWa53DcvzOOasep59DmyoAaKpW1qPRqlFrVQR8wdBaRxtNTi/hJuGsCgT95ukp4Gnuus1ggytfVFrVaHSg63+0xeqi1dy38T58QR+axHiu3fMsH9ssXGubzA3WTNLP+m2X0ODRjhCrAoFAIBhW5GAQb3Ex+tTUAZ/b0eRBb9Kg1qrY8FYexQfqydtWzfyr0ph5viLS8nZUYbToSJ4wvH0c3QeUXqrmBfP7NN7r9qPrp1jNmhNP4Z5azr4hC2u0kcw58f1e50hCZ9BgtOpornUNy/Hbi1IBeJw+PG05qkt/MCm0XW/U4PR5sY5Cser2BXB4A0SOcIddIBhx1Bd0CNWYiYpAzXkL5t8J4WNPetpmTzMPbn2QzIhMbp50M3/a+hBv2iQyAyoeuPzNEdULe6AYWbeVBQKBQPCto/aZZyi8aBmegoIu230VFQQdjuPuG3S5qH/l1R7HBQNB/nnfZlY8l8PGt49SfKCehHQbAAW7akJj1rx8iE/+spdgW1jscOHOy0NltaKJP7GAlGUZr8sfCjPtK8mTIrn9r2djjR59wqk3wmOMNNcMk1j9hrPaXOsiaUIEmbM7foftbrZtFL7nTU4fABFm4awKBH3CY4dNT8PLnQonXf4cjJkBFz1xSkIV4I0jb9DqbeWhBQ+xbPwylmVcBcB3Z919WgpVEM6qQCAQCIYBWZaRnU4kvZ76l18BoHXNGvRpacrrfj/5i5cAELZ4MWP+/Cec27YRtnhxly/k6j//maY330LSqIm8+eYux6gtsQNQntdEeV4TM85LZsHV6ez9opQt7+dzeEsFEfEd1VkrjzaRmBUxqOd9PDy5eegzM/p0weHzBJBl+u2sno7YYoyUHmkclmN3zllVxKqT9FlxXca0/45GYxhwo1PJrYsUYcACwYlxNigitT4f0pbAufdDUvZJT7e3Zi9/3/d37ppxFxWOChLMCbx5+E3mJcwjK1JpVXb3GXeTEZHBpWmXDdRZjDjEt5xAIBAIhpzGf/2L6sefIP4Pvwef4t40vvEmEd/5DmqbDdf+/aGx9q++Ii97NgBj//Ua5jlzQq85d+wAwLFlazexWpbbAEBYpJ4pZyUy84IUJEli2uIkSg/Vs+4/uSRN7BCntaWtwyJWG996C399Pe4jRwi/6qo+7dPeEqW/OaunI7ZYI0e+rsLnDaAd4n6wvk7OauHeWjwOP9Hf6KXa7qxaY0ZfJeAGhyJWRc6qYDQQlIM0uBuINESiklTIsky1sxqLzoJZO0hto4q3KoWT7NXQXK6E/970YUdP1FPguT3Psa1qGxvLN3bZfnn65aHHJq2JqzL69r0xWhHfcgKBQCDoM7LPR9DjRR12al/8pa+9R3Ha1dQ9+z7m8TMZ98CvqP7eDTR9+CFRt96KY/MWAEzZ2YQtXkzNn/+sHN/j6boelxsAx9df42qwozYa0Bk1yLJM3vZq4lKtXHNv1zvbarWKC26fygf/u4uSgw0kZkXQWOWgvsx+Sud0Mviqq6l+/InQeRmnT+vTfu25kcJZ7Whf01LrIipxaKvWBnxBkJTKycUH6rFEGZgwP6HLGP0odlbr7MrnMsZy+hRrEZye/HHrH/ko/yN8QR8/m/kzYowxPLrtUVx+F3Pj5/LSBS/1um+LtwV/0E+koZ91C2qOwKsXAZ1SSKIzT0moOn1OHt/+OGHaMFp9rQCk2lJ5ZOEj1DprMevMzEuYd9Lzj0bEt5xAIBAI+oQsy5Tf80s8+fmkrfz85OcJBim2zKQ04WxKk5Uv9a2vNRIz71ckrStkwa3g2LwZw7RppPzn3wBIWi3Vjz7aLTc16PGgTUzEV17OK/dvxxpt4OK7prPx7TwaKhyce1PPbQH0Rg0X3zWNVX8/wIzzktm/toy68qEXq3X/939dBLhxWt/EqtelOHpCrHZqXzMMYrXdzVVrVbjtPhZdk4HmG+6u0aJDb9JgtIy+IkW1rW1iNUyIVcHIpdXbyodHPyQ7PpvS1lK2VmwFIEIfwez42Wwu34zdaydM1/XvQ5Wjin8d+hfv5b1HlCGKz6/6vG95nztehg3/D1qV6t/ccxiay5QQ4ITpp3Qu7+S+w0f5H4WeX5F+BQ/OfxC1amijRkYS4ltOIBgFeMvKkH2+QamWKhD0ldY1a2hdswYAX3UN2rjYfs/RUu8iUFNDbfhkrC1FTI+rQn/tzXzxrzwNtFYOAAAgAElEQVRqDanUksqkVatx7dtH1O0/DO1nWXwuu17dQNmuIEsv7JivyDaHhvGLsBmUi5OWOjcfPbWbYEDmzOWZTPyGy9UZa5SRa3+jhBdX5DVRtraUQCCIeoha2nhLSmh6732sl12Kc9t2TNnZaMf2rfiGCAPuoN2xrMhvYvyMmCE9tt8bRKNTERZhIGashdQZ0d3GzLwwhax58aOy+Emt3YNOrcIqPmeCEcqKwhW8sPcF/LKfO6bfwaqiVbyd+zYSEtdPuJ7FYxezoWwDt/73Vm6YeAOVjkrqXHUsTVnKz776Gb6gj0lRk9hft59frPsFT53zFCrpON8B9hpY8wfwtip5qfFTwTpG+fedtyB57imdz9Gmo8QaY3lx6Yv8+9C/uX7C9d9qoQpCrAoEo4KKX9+La88ewq+5mthf/hJ1eDgAVY8+hn3tWuRAgJif3EX41VcP80oFpyuB1laqH3kUdXg4gaYm3Af2o41b0q85tryfz541JcoTYzQzlyYx7bvfB6DoUBP5O5UKvYW/fghrQkKXz7NkMpGXeT2Uwsxye8hBK45diNdnoz65Q8G6Wn2cd+tEsub1LlS/SVRSGEG/TFO1k6gxQ+PONb33PgCxv/oV2tj+CX9Hk+J4GURLEfQmLemzYsn5spRZF6ZgDBu6/MqAN4BGq+byn89ArVH1KEjNNj1m2+h0JmtbPcRY9KNSaAtOf9x+N09sf4JmTzOXp13O9JjpVDmqeOPIGwDMipvFGbFncMn4S1hRuII/bPlDaN8Pjn5AmjaCZ875E2HRWZz59pl8WfIlu6p3MTt+du8HXfso+F3wk50QndH1tayLug2XZfmE/39KWkqIM8ehV+s51nyMVFsqGREZ/HHhH/v+ZpzGiNY1AsEIp/mTT3Dt3o0mJoamDz+i5smnAKVlR9M77+ArK8NfWUnlb383zCsVnM40vf02/poaEp/5K5JeT9M77yLLfW/1Unq4gT1rSkjPjiU7tZFp+15gykVZodcvuG0Kl/1MCZ/SXnED4z/5mGBEHPXldnzeAGqzGa1PCdNd9dJBgoEgPqcHrz6cyXG1XDinGZOjMjRfTIq1X+cXnaQI1PohDAX25OaiHz++30IVoORgPWabLhQC+21n/BkxIIOz2Tukx/V5A2h0KvQmbbfw39OBOruX6CEU/wJBX6iwV7Cjagc/+fInNHuaefWCV3lk0SOoVWoyIzJD4yZETkCj0vD4mY+z+TubuXfmPXycfDVxkpb0ALx8NIekD+4gPBhk5VUr0aq0vJv7bu8H/u9vYNc/Yc7t3YVqDxyqP8S9G+/l/PfOZ0vFFpw+JzuqduD0OUNjqhxVXP7R5Vz24WX8Ledv7K/bzzjbuFN4d04/hFgVCEYwQY+Hil/fC4D1oouwLruIltWrkb1e7Js2IXs8WJYqvbz0kyYO51IFpzmt69ahnzQR85w5RN95J/b16/Hm5/dpX1mW2fxePrZYI+d+N4uEwtXEBsrQRHYtZtFeKKdhwnlsW1XBy7/ayFsPb+ftR7bjC6oIqjRoVX4aKx3UldlpqmgBwGKG1BuXkda4JTRXeJwyV8Bup/nTT08orMPjTKjUEvVlx+/reqrIgQAlt/2QxrffwX00D33GiS94OhPwB9n2aSGFOXWkTo8RjlcbBpPiMHuc/iE9rrPFi9Fy+oq5dmdVMESU74a9b8Kry+DLh4d7NSOGGmcNv930Wyrtldz5xZ1c8P4FfH/V99lWtY3HFj1GdnxHEb0UW0rocWJYYuix1dnEd9f8P8ZveJr3S0p4q85JxNm/geZSePsmkoyx3DL5FlYWrWRtydrui2ipgK9fgMjxcPave1znhrINLH5nMb9c90uqHFUsX7GclcdWUumo5EdrfsSSd5fw/VXf56+7/xraZ0fVDvyyH41Kw3N7nwNgSvSUU33LTitEGLBAMIIJNHb0DlRHhGOanU3LJ5/i2reP1tVrUIeHk/j0U1Tcfz+uXbuHcaWC05mgx4Nrz16ivq+E7FqWLqX26adx7dvXJ7FVVdhCfbmdc2+aQP2fHsOxfgMxv7ynm9AKizSg1qg4sL48tG3auUnsW1fG+jdzCagNpBrLyHckUZ7XhMWoCBOLVYVKr8eSqIjfyDFmVCpl7sJLL8NfWYk+MxNDVha9odaoiIg3UzfIFYFb/vtfHJs24di0CQD98swT7NGBHJT57PkcSg83kjk3jnlXjB+sZY469Gblcsbj9A3pcVsb3CRmDF9v3sEiGJR5b1cZhytbyE45/c5vRFK2C17qVEW2fDcsuBuM4cO3phHCutJ1fFLwCTuqdlDZFkEzVh/JvYse5qyks7qM1ao6UiO6fMcc/AhayuCmj7ClnduxPWIcfPBDWPk/3LHsf9lYtpGfrv0pZyedzVPnPIXOY4d978D+Nsd1+X/A2PF/otXbytu5b7O2dC37avcBimhdX7Y+NOaBeQ9Q2lrK4YbD7K7ezfqy9dw35z78QT8fF3yMRWfh4ys+pqi5iHBDOFGGqAF6504PhFgVCEYwgYaG0GN1eATGWbMAcGz9GvvatVguOB9Jo0EbG0trTQ2tX31F6xdfkvDoI8JxEQwYgcZGCATQJiUBoBuXgspmw7V3byivtPRQA8dyalm0PDMkFNupzFduuphWvULTO28R9cPbiLrttm7HUakklt05lWBAprXeTeHeWhZem4Gklsj5ohSA8GADttgMKo42ERerHMdqU77KoqMgqWAX5z70Y+pfeon6l14m0NSknEPb/6Wg203Jrd8DSSLh4T+iT08n/4ILMGVnE5V+A+W5TQP99oWQg0HqX/xbl21hZy7q8/6Fe2spPdzImcszmHZu8kAvb1TT3sv0RM6qy+4l6Jcxh5+6WxgMBHE0eQmLPD2cR4fHj16jotbu4bN9lTzy2WEAMuMtw7yyIUaWYai/P+uOwhvXQlgcjJ0PKQtg5a8h502Yd8fQrmUEcqhqJybUNLuV75IPyypJ95VA+Eoo3AZzfgRFmyDghUmXs+LKFagCfnDUg7lN+JVug4hU6CxUAaZdB5U5sPU5dLkredxg4ioLrC9bz56NjzF30/9RH/Tys7gYLh03g+WxkwjKQV7MeZGtFVvZW7sXgFiTks5x48Qb+e7E7/LItkfYV7OPv5z7F2bHzw5dk72T+w4Pf/0w7+S+w7aqbWyr3MadM+5Eo9KQHpE+NG/oKEOIVYFgBONv6OysRqCJiECfkUHd888DYD3/fAA0sbHIPh9ld/8UAgHi7v01apttWNYsOP1oF3zthb0klQrDpIm4Dx8JjVn7nyO0Nig9Txdck45Gq0YOyjRXtpD/zjqMfiOud14n6oe3EXNPd1e1nbGTOu4oTz1HEcfzLhvPgXXlBPxB9N5GEjPCKdhTi+TWoXc3YLQqeZv6mCgyP36Jhp/uwpWT0+M5OHfswLVXubgoum450Xffja+4hObiEqL+ejt526pxO3yhwkVBj4dAc/NJ5ZV2xnP0KMeuuhrZ5yP+4T/i2LIFldmMYdKkPs9RuLcWQ5iWqWcnndJaTkf0fQwDfuVXiqN914sn7oPosnt570+7OPO6DMZN7V7l19HsRQ7KWCINJ7HikYPXH+TBTw/y5vYSosz6UG/VdjJjh7Yd0LDy+rVQtV9xz5KyTzz+VJFlOPA+rPk9IMH3VkJUmvLa/ndhx0sw98dDL56HmPY0DUmSkGWZZzf+jm0VW3js/L+TEpnBofKtTHfZubuhmV0GPWm+tgiKna8qxY4qc6BwA3iaYfKVpFz6V9j8V9j0F5h9G5xzH5Ru773/6Vm/gq3Pgb2aDNMkVpTmcUnyGH5b8DYxyclow8eR05RLDg3May1hReEKXvz/7J13eJRl1ofv6TWT3kMSQkIJvfeuUkUQdXUVFcF1dRUQRbfYsH6uFWysvSJYQRSkdyTUJECAJKT3Pkkmmcm0748nmSQmQMBQnfu6cs3MW573nZr395xzfidhGSBE6tKxS4n1jWVn7k76B/ZHp9Cx7JplWB3WZpFegBuib2B7znaej3segAf7PMh9ve+7MC/sVYK7ZtWNm8sYe3mTyKq3EApBixejiu2GPDAQ7dChgBCrABKlqJ2yG40X+UzdXM38XqwCqKJjsKSl4XQ4qDPbMBnFBe6R7bmsfH4/lSUmfn5pO189d5BiRTj+Pg5C31pKwCOPnHPUX66UcffLw+lTsxWvmixCOntjqbGRnlyDZ2UGUo0Qq3JfX7DbqU1IwPfe5pHbhudg2rUbiVJJp1/XoezUiaKXX3Zto/UQBjm1VXVY8/Mp+/IrUkaO4tR1E3DU90I9F1OpBmzl5eT98184rVbk/v54zZhB2BtvEPL8820ew+lwkpVURnisDxLp1X3hej6oNHKQwL41aXz38oF2GbM010RlcS2/vJNIRWFNi/e+qlRMzlzJYtVis3PHR3Esj8uiX7h3M6Ea5acDoHPgnySyWlsBKRugKh++vhXKMy7csY5+D2sWwLd3w/dzQGWAWT80ClUQIqs0FdLr00lPrIXik2C3iXO9ili4bSH9vujH6JWjmb1+Nh+k/0SipYS//jSTD3+9n+PWCvpqgunZby53V1YhkWvggTh4ogDGPgHH17iEKkk/wdaXIGsvKHWw/wNYNgJMRdBhUOsnoPGGe9bDgDnwt21EzDtCL7OFQrmcArWOFFMu/QL6oZAqeHT7oyxLWMb06Onsv30/P03/ie5+3ZFIJIwKG4VOoXMN+3uhCqCSqXhz7JvMjJlJlGcUd3a/8wK9qlcP7siqGzeXMU1rVqUaYRij7deXjt9/j9NiQVovTnXDhuH3wAMoI8LJe/yf4sK8jf0a3bg5G/YKMfkhbRKtV0VH46ypwZqXz4kDpTjsTqY/0BW7TMWatxLYumQXOcUKwnK2EhquoucLj7uiX+eDWqegg7IAe2UNITGNotlQmYZEVT9p498Y/VJ16YrHxIlU/fqreA71EzjVu3ehHTAAZWQkEV9+QcWKFZiTjmNcvRrT158BQ6kprqRo7gwcTSZ9auLiUMfGknnX3XjdeCO+c+5p03k7TCay7p6NJTUV/wXz8ZxxIxL5uf/rLcqswlxtJaKHu5apNSRSCSqNHEuNjcL0SmxW0VLmj1BjbBRuXz29l079/Bnz166o9eJzXJguDL4a2ihdaRzMLGPme6I/8YszevLXweGkFlWRU15LuI8Wb62ShJwKvHVXr4FUMzJ3i9vrl4g+msv/AvftBHk7Pv/0nbBmPpSdAqUHWGuEKJ30Ckh/Fz+KnS7cZ/d/JLZdcRtIFaD1AZsZHstouU9bSdsmRG/MNX/0GZ0XDqeDHTk72Ji5kb90+QubszYzKHgQIboQtmRuop/ZzHPabsy3pLCkUGRDTBj/MoQNg4kvNU/VHrlQRFdNxTDldbBb4diPUGcSKb7ekbDxSbHtmXqghg8RfwCGEF7sfi9LSuJ4aOwrRBoikUgkPLPnGb5P+Z7+gf15ashTKGTn9z9NIVXwzLBn2tTWxo1brLpxc1lja1KzqghrdLWTSCRI1I2z+TKDAf95D1Fz6DDgjqy6aV/sFRUUBA5k65JcdF4ldOobQL8YUVtjPnqUIz+XobU4UOw8Qeg/HkDnqSSnWOwbmfkrsR/8hOIPCNUGZN7eWE6eRO/dWCPoV3oUaf13QebbKOQUwUGE/vdl7E8/Rer4a7CXl5O78BHqUk/hdaOos5WqVPjcdRe28nKshYWYko9Bx6Fk/9/reBqNdPjgA7SDBpIyfAR5//4PEqUCW14+pri9bRarha++TmVGIYGvvoffpJHn/dzT4otBAh1ifc6+8Z8UlVbuSgOuLrO4HKFbw+lwthqhNpusbPzoGIOuj8JU0bwNTlp8CWX5h/jr0+KCN+dEGd5B2napf70UfLon03X/lgEitTw6wIPogMZI6pgufyz9/Yqi4AgggV63gkwJq+6HoiQI6dN+x9jzlhCq0dfArcvFcU4nVhRq6HsH7FkKKRtB7Qkx1zUa/RQeheBe53Z8Uyn8shCSVonHTxSB/OJ+fuOL4ln822JSK4Sb/E+nfgJg0YBFdPHpwpPaGCSrH0R+/yq+cdjZvekxcqPHEBU2rHGQpq+ZVAbjn2p83O16OPGzuB/UA7rdAHH1XgEBbe+aEDFiEa//btnfe/8djVzDfb3uO2+h2hS3UG0b7jRgN24uU5wOB7WHDiP396fbiePIvc/uyNiQptkQCXPjpj2wV1SQHToWvbcKjYeSIztycIR3wRESScY366mQBxKav5uqX34BwKc+0qSwmejyzecogoPb5Tx0gwdhKy7GkpxM12HBaDWgrS12TdwoIyJd2yqCgpAolci9vZF5eWJc/ROVa9cC4DG+ed2S3NubiE8/IfqLDwGoySlCERGObsRwpCoVAW++Q4aqO3X5hSgiwqlLSz/ruTqdTn5YvJ1VOQPYPfQF1m4+vxRik9HCbz+mEr85i059/dG4e16elqaR+8rS2hbrm77+dRZ7q2OU5laTlVTGz28nkJdS3mzdgEkRlOebsFrs2K0O8lIqCOt25U4eHMsT/yfe+Etv5DL35SBl6WAIFSIxpK9YVpLSfuM7nZAfD10mw1+/ESLxbGJl1KPg301EDiNGwMwPYe4WsS5j57kd32GHD8fDiV8an9+yEfBWf9E71GoWqcbWlt+d9qLMXMaDWx6kqq6KF0e8yEfXfYSXyos7ut1BF58u4HSiyNiDXOMD/t1QBPdizKxfuX3oP9t+kIgmojZihDBYWnAE5icIYfsHCNIF8figx/FSux2aLybuXyc3bi5Tag4coGbfPnznzmnzPjIvkabpjqy6aU+yE/KpMkTQ59oIeo4JxWFz8tkTcezq+gjxll7IrSZCak9Ql5aGrbwcnxBRsyNXylF3a7/+v7pRo0AioWr9Bsbf2Y0Z48VFVUNkVRHYGAWSNzFEknl6Ya+oQDdiBF2PJ6GMiKA1NPXpnVaFDv2Ika5Z78NpHqTE3ILxobfJGngPpUapqwb2dFQU1pCfb8fPnIneW4m52kpt1bm1VbFZ7Xzzwn4Ob8giqrdIQXVzehSqxgvRqlIzpXnVOB2NAtVmdbjun67FjcUkIrN1FhsZR0qbrfPwFZ+z1W8eJut4GTargw5dr8y2LlVmK2nFJhZN6MKMvlepYVdVASRvECKxLZSlgU9Hcd+nvi3UD3Nh64tQmPTHzsVug11vQHWhMPlpq2hSe0LXKeK+R5C4DesvBOyxVed2DpV5UJ4OE16A21aIZSXJYMwVqckvBIpU460vnNu4bcTpdHLbz7dhtBiZ128e13e6nkHBg9h2yzYer5XCm71gsRckLBcR5PNNcfZs4pTuV99aTSoFmTuZ9ErFLVbduLlMMSeKfl2GadPavI/MYAA464W0GzdtpfbIUVILtSjqqogdHox3UKN5hM0hpcojnG4nv8T3GtHrznLiBF3ChPFMeEjr0avzRREQgG7kCCq++w6nzQb1pkcSVWNKfNAzz+AxaSISRWOUTe7vh9TTk+AXXjhj2pVSLUciAeWwMfjPewiAvNQKTsYVAHA40cnxEn+ywsaTPGSoy1W4AXO1laoyM7XVdax7V7gR9x9mYHS9yDQW1Zz1OdrqGl+z4swqairruHZOdybc28NVK+mmdeTKRgGQdriYFc/u49CGxlRXi6lRoNbVtv7ZNNeL2Gtnd0eubH6JpPEQUe3C9Eo2f5qERAIhna9MsZpSJPoJX5XmSfs/hLcHwlc3iXYwP/xN1DGejfJ0Ud8IzVNjt78MH4yF+K+hpqzVXc+I0wmfT4PNi6HLFOh927ntP3AOBPUUrsAN9L4VcvZB0XExfvFJKD115nEaDKP8Ogvhq6hPk5/wAsxaBT1uEo8TvwFbXatDnC811hqyqrLIM+UxPHQ4U6OmutbJJFLhxKvUiaizVCH6y54vEgnc9An85aur3kX5z4J7msGNm8uU2qPHUISGtin9twGJXI7Uw8MdWb1CsaSmUr1jJ4Ypk1EEBl6w4zRtE3BsZy5FWVUMnxmNUi3HbjRiSU1F068fEokEa3YWJl0I/oEK5EpZizrAKF0+/iWJGCbMp2LlSnLmL8BRWckomZrIj5a1+7l73XQTufPmY/ptL/YqYXAjVTdeWHrf+he8b/1Ls32CnnoKZ521WeS1NSRSCSqdAntUD2odavTAwbUZyJUyBk0VEZfUAwXUefTGflKB8edfUMXE4LTbKSmD7/6vpQutb0wQzgDxmlUU1RIc3Xr6mLnaStyaNI7tyCV6QCBRffxZ/8FRAMK6XJmC6GLTNLKakyxSeBtMkKB5W5vKklqyj5fRa0wYMkWjKG2IrIZ39+GmxwdQmlfNxo9EVE1rUDYbK7CjQbgQX0Ecz6/k631ZWO0iyhxzNbWlcTqFsNz2EshUYK83yDryDVgq4cYPQG1ofd+aMmHQ09SN96aPobpIROp2L4FV9WJxyutCQDZgKoXsvWDMESK3119ArhZC6fjPQiRm7obxT8OIh89dQBlC4O+7mi/rewds+z/4ZJJI37XVChOm2WtPX8daXl++0BA9jhoDJ9cKIdxhkOg/2uc2+HKmeM363tGm0zNajNiddnzULVPia6w1/Jj6I/+37/9cyx4f+DhSSZOJoNJUMFfAtc9C/7vAUgWqPziJ0uPGP7a/m8uKK+tX1o2bPxHmI0dQ9+x5zvvJfX2x5uRcgDNyc6HJeWgedenplL7/PmHvvYu2b98LcpyNHydRWVLLtPl92Ls6DXO1FZ8gHb3HdyD7b/dRm5BA3uPfUG20MdynjBpNANE9QwDhyjtsZjROpxP/Dh4E+PWmuocV7ZAh6MeNw2EyURMXh9xuRtM5pt3PXT96NFIPD4xrfsJ85CiqmOhmxkqtoQxre5qjWqfg5N4CTu4tYMoDvchJLqfnmDB6jxepZcbiWo6kV7F91Jv03PMNxjXjkarV5E9cCE4tHXK2kt1hPAC9Et9F9fALKPzUSGUSCk5V0G1Y6/W7O1Ymk7K/EIBTh4tc98O6ersiem7OjELVeAHssNVPyDQxUTI3iaxu+eI4FpMN31Bds96+5horUqkEhUqGb6i+WXS1qVgF8d5cSbyxMZklmxtrMDUKGR18Tm9CdcVxfI0Qqr3/CuP+I3psjngYkn+FXx6BN3tAn9uh61SIHN5835z94jZsYOOyHjMb78dcK4yNtr0sDIocdhhwjzA/2vI8OJtE6tfMh543i+jnyjuA+jTkfne2X6RP5wcTXxSuvoYwUGhg3wew6gG4e41oxdKUOpOIvkpkYnuAG94Rzym0ST/ZTuOFeN31pngd25CK+7eNfyO5PJmJkROZ328+QTqRrlxSW8LDWx8mvlhkoNzb8150Ch2RhsjmAzTU3ja0lfmjQtXNVYdbrLpxcxnhrKujYvVq9KNHY83Nxfu2W895DN2woVT8uAqH2eyq5XNzZWArLkY7dAjWvDyy7p5N2Ntvox854oz71B47hrpz52Zpr7+nzmzDVGFxpfA2CKFVrx/GXC0u4LOPlxHS2Yvi1GLQBnNyf7HILouowSmV4xvRePHT99rmbZFUs+8GoMO77wBg2htH1Yb1yH3a33xGqlLhMeE6jKtWg81G0DPPtKujosFPQ0WhSNf95d1ENB4KYoeHuNZrPRsFS5EyEkuvrtTkl1KVUIBBo6fP2GCyhcklfmUiO0ImkxI7IoSjO3IZMKWjqy9nWnwxe1enYfBTk1lfHzn5gV54B2kpzqoiqrd/s6ifmzOjULasA2z60WhaM9wQQa0utzTb3mKyotLJXZ8plabxe9XU3Cp2ZAjdR4ZyJWCzO/h0TwZLNqcQ4qnm678NIbusFplUguxq6tm78zXw7wrT3hL1iVNeFcsHzhGGQpufhb3vCmfYWT+IyGIDmXtAKoeQfq2PLVeJSGOdCdY9BusWQdwy4ezbaRyM/qeIWL49AMxGIQJTNoqoaGUu9LtLCMz2ZMA94q+BsIFCHH8wXtSk+nduXPdmT6gpBb8ujbWbWh8YfF/zMSUSGL5A9H49uRa6TeVMpJSnkFSaRL+AfmzK3ERxbTERHhFsyd5CSW2Ja7tpnaYxr9+8xh3z4kW69rEfoa4aAmLFe+fGTSu4xaobN5cRpR9/QvGbb+Jxreh9pu5x7pFV/bjxlC//GtOe3/AYN7bFeqfVivlkMpoe3f/w+bppP5x1dTiqq9EOHIj3rbeScdPNlH366WnFqsNioWLlSgpffAm/hx7E/x//AES9ctLzy8jzH4xJZiCqjz/7fk7HarZzx3NDUNanLYZ29qKgSYpk5tFSMo+WwsD/1B9A3KQViMiLV1Db0wV1QwajG3KGfnZ/EM+p12P87nsANL3O/TtyJgI7Gsg6JoTj+Lu6ET0goFm/zsiefhzbmQtOKGQQhQD1gYrYqDrCHpgOC/e6tpfpxevWZUgQR7fnUpxVhVqnQK6QknqwiOoyM1IpGPzUjJvVjdD6lF+vgKso4nWRkKtaEatNxFhliTDk0nmp6HtdOLu+TaG6zNxse7PJhlrXKFCVmsYxGyYOvAK1jL39yriwziqtYf7KwxzOEj4GL9/UiwhfHRG+urPseYVRUyacdsc90bqRTmg/mPUj5CeIGtblt8KwB2H048J4aP+HIqqoPMv3rv9s0AeCwwbr/w1yDUx4sbElysyPRK0sAE64+2eREuzRPo7oZ6TLRLhrjRCs382G++v7xpqNQqgChA04/f4NxE4Xwn7XG8Lc6QyTgevS1yGTyHhtzGt8n/w9b8e/TVx+HNdGXEvfgL508+lGV5+uqGRNaoB3vQGbnhE1syqDEKvjnnTXl7o5LW6x6sbNZUT11q0AVG3cBID6PASlbtBApHo9VVs2typWS/73PiVvv03k99+h6e4WrBcTW3ExTqcTRUDL2smGOmOZlxdyHx/UvXthPpaEo6YGR00Ncj8/qnftRhUTg6O6itwFD2NJESl9levW4X3LLcj9/THtjSMxx4tKoxmFTkL+KaMrC+aWfHQAACAASURBVC3lQBEh0cIxurMuh0HzRnFibz6+IXriN2XRt2MlpV9+RVLsPWjNJdR5+JNjFtGApr1NLzXaQQORBwVhLy1FFR3drmPHDAhg/8/pzHikHyExLetL/cL03PXicOI3ZfHbD6cYdVtntn11EoCoif2QarUMVByA3HQivvjctZ9PsBAHx3bmsfmz4/Qe34GizEo6dPNh0t/bV3D/WWmoWVWoZVjNIi2zadTdWFyLxkPB3f8nUkAP/ZrZMrJaY0Wlbbw0kta3dOl7ncgmuH3xEDQe7W90FZ9dQdcgD9SKP9Zao4E6m4Pdp0qYt1z03l56W19Gx/jj2Q79ji9L0neI28hRp99GIhE9U2f9AEv7wY5XIO59qKsSwqkhEnsm5EroPl3c7z5D1Mk2Fccx18K8w/DxJBHhbXAVvlhEDIXh82Hjk1CZD4ZgyN7XuH7I/WcfQyYXBkdrH4Xk9UIEt4LVYWVt+lqGBA/BT+nFXeoOFEROxlMXyIIBC08//olfILg33PkTOB2iLjjgypj8cXNpcItVN24uExwmE7VHj7oeKyMjXVGZc0GiVKIfNZLqrdtw2u1IZM0vfurShGOg5fhxt1i9yKSMFBdS3U4cb7GuwcFZXt8rV9khnKp1v3KyX3+QSgl84j8UPvscABKNBqlKhSI8HGtWFnWpp0gZPQbl0FGUEEClx1BC83ahCvAmVdUXT0k5zopyUnbJyErUIHHYqXvnBYLnTCYkRkQEeo0LI/8/T6CypBI5tArja69xaspiCsqV4HQ0S3+91EikUvz+8QB1qaeQKNv3vLyDdPxj2bizbtd7XAe6Dg1GrVNgtdjZ/V0qwZ1F2vOgtx5rsb1SLcfgp3ZFbYsyKzEW1dJ16EWIuPxJaBCrHj5qyvJMAM1a1xiLa/D017ge671VVJf/PrJqRefVfGKm6efh9wZj7UFOeQ3T39nNbYPCeenG9pm4+HBXGv/9VUyi7Fg0lnDfqzhSX1UAG54UEc/Q06TxNsUzDB49CS9HgqXejHDCC+AVfsbdWnC69jM+UWL8S0XHesG+Zr5IPT76vWiBs+CIuG0Lfe+A/R/B93PhkROQe4DCggSO+EcyttNUZFIZXyV9RW51Lv8qzIf4rqhNxTwNIh15wELITwR7XfNortMJRSeEkZOmfjJQe+X2KnZzcXAXw7hxc5lQm5AAdjuGadcDIi30fNGPG4+9tJTahMQW62T1YshyKu28x3fT/tjKhXuprN79WRHWWA+nCAtzCVUAdWwsHX9aTfSG9QQ//xz2iK543HMfR00dOaAYjUOmJHLKYPQnhINkuPEggUUHKSu1k59eTceMn1HVVVK9YweWtDSKXnsNe2kppr2/oRs8mMg7p6Hz06FLrI/wS+uQyS6vfxfeN99M4L/OoVF8OyORSlzpon2uCeeBd8eiVJ95/rfH6DB6jg7FN0xPfqq4SPYNvYrcWC8xMrn4jDbUBAPUmRuNb4zFtRiailUfdSs1qzbUFzn6eCK/CoA9p0rOsmXb2Xy8CIDHJ3a9yoVqIXx4LRizYOC9IGvje9fUgGj806Km9GohqBfIlJCyHuK/gtgb4L6dbReqIAybxvxTRJ1fCqXkqxlcl/wBD+95gk1Zm7A77GzI3EAvVIwuyoDA7sKYCYRZVcpG+GIGfHt38z63xhwxprs+1c054I6sunFzmVBz4KCIoC1aRM3+AwQ8tui8x9KPHoVErabsi88xrl5NbXw8UatFA/GGCJ75yJF2OW83505rEe+G96VhMqHBnMj33rn4/f3vZN13H+ak4/j97V587roLqUZcdHtMv5F9cYHYc51IAm1ggYjM9XRb8gJZmz6h7/H38Co5QZ1MR0r0TSCREBbjiVIaSeFLop2ANTsbh6kGW14+unvvRSKR4HPHLKq3JnAK8Ah1z3yfDUkbjGoajKl+fieB0hzR57JppM/NuVFtsaFTylypvg3vgdagRCKV4HQ4sZob29VYTLZmzspag5K85OY9qc01wmDpYpKUL2rHHU0v6s8Tp9PJtuRijuUZuXtYJPeP6XT2na5UKrJgxe1QUwJ//Qairz23/QN7QOFRGHmGlNUrEakUoq8RBkl/39UoIs+V+v2cwBM9x+IwirKTR7c/ipfKC6PFyN/LK0Td79h/ixY9m54Rpknf3AVWkd1A8QnRFih8KOQebDa2GzdtwS1W3bi5TKg5eBB1167I/f2J2brlD40l8/DAd84cSt55p8U6W4lIQ6xNTMRhsSBVXT61iFczTofDdd9WXIwiKKjZent5c7GqHzuW4BdfxHPqFCRKJRGff46zthaprrkxSvbxMmqrrPh10FOSXU2Xk18Tmr8Lhepl9IOHUPfJJ0j1egImjMfz1CkqDRGEThyAatYUsu6+2zVO+fLlAGiHDAHA957ZeN/lYP8jO/Hwu8rMWC4xGn199EcijJXctE5eRS3eWiWaVlx+zVY7PZ5ezx1Dwnl+urjwbShPlUhEim9VqZn8U0b2rj7FoOujsFrszaLfGg8lZpMVh92BVCbFbndgNdubGSxdaOpsDjYdF+7c+RVmrHYHinPMYnA4nCTmGukRYmD+ynh+Scwn1EvDXwefY1rrlUJVAVhr4X+jRRrvbSuh84RzH2fOBpGmejUy/V1hJnUaUWhz2LA6rGjkzSfLHE4HVXVVeKo82VyVxsfBgQyrNbPbmMK/QyfwYu56ALp7xVBQkc5EU64wYQLwjoSbPxVmTuk7RJug+K9g+S1iYiGgu+h9q/Y8veuyGzetcHnldblx8yfFWVdHbUICmgH9221M37lzkAc31sM5raJtg620FIlKJY4Zn9Bux3NzZhxVVa771vz8FustqakgkyGrj6hKZDK8bpzhqsmUSKUthGp6QjHrlh1BqZFz02MDmPXCUCJ1+fjMEe0M1N1EqpXXzTfje889xJz6nq4nv0YT3QndkMF4zpghBqrvpScPDkYZGekaXyqTcu093RkwORI37UdDCxS9l6qZ0/CfndSiapz10cV96WWMeXUbNy3bg8lia7FtgVHUmn65NwuLrbmZktMJQVGNKY8H12W6IqxKdePrra03Sqqtb9/U0M5GdZHSgJ1OJ//58QiJOUaGR/ticzgpqrKcfcff8e62VKa/s5s7Porjl8R8bh8cztZHx9A58DLuV3mmKHJ1ESR+KwQpgM0CFdnifvoOeKs/LO0jhOotn5/WAOisKHUt+5FeLWi8m7fm+R2Pbn+UYcuHub5vDbwb/y7jvhnHlqwtfHXyaxLVKpZ5ezIydCS39p+Hon77t9KOs8rmQ5TKT6QdN2XAPSLKPeV16DJFCFW1F9SWQ2kqdJ7YumOzGzenwf1pcePmMsCclITTbEbbvw228m1EqtEQ+Ngich8WKU4Fzz6HJS0Na3Y22sGDMe3ciTU3t92O5+bM2OtrUgGqNm1C06eP6+LaVl6O8ccfMUyY0OZIt9PpZO17IpU7tLMXMoUUg68Gw88/u7YxTJyIvcKI1803IVGr8fUGQ1YcqqiOAAT+5z/ohg2lZt9+Kr79Fv2I4S16lnbs1c69Ad2grhdJBj93CnADe9NKufX9vTw3vQezhkQQv+MnHmEDL+Xdzn9/PcHiG3o02z7f2GiMdKrIRGyIAUn99LvT6eS6Od1JPVjkMlgyFgvh09C6CXClBNdW1aHzVGGpEaJVfRHSgCvNVt7eksq3B3N4aFw0/SO82Z1aSn5FLaFe4nORXFjF4axyJvcMxkPdXEDvTCmmk7+emjobSzeLxr5708oAmNk/DKX8MotFlGdAeSaED4HVD4KpCGatatmuxFYHH4wDYzZMeQ0GzoVV9wuToFu+EIY/Sp1oeeIVDt2mXZKnczqMFiMeSg+kkkv3+tdYa6iz1+GlbulmDpBcnszmrM0ALEtYRo2thskdJ9PZuzM/pvyI1WHl4W0P43A6CNWHMjRkKP/o8w8kGj++y82nSCZDYcmBoiToO6vle9h9hvgDmPgS4ISuUyF2moj2uqOqbs4Rt1h14+YyoOagqOPQ9m/fH3HDpEnUZWZR/OabVHz7LTIfH2Te3ujHjsG0cyeO6qqzD+KmXSheuhSTNhCJVg8ffYw1K5uQ115FIldw4uUPSQ+6DknIFJTZVfh3aB4RcdgdZB8vx1Znp1O/ACw1VtETtZ7TRT4lSiU+d85yPfaaORPTrl1ItcJwRabX4Xn99ahjY1GEheF961/a/4m7aUFDW5XgTudgeHI14bCDpUoYsYQPBYWGTQeO8qpiGZ67vMH3Tv6WPh/kUDTgMT76LZNJPYMZEuXrGqKgstZ1P6WoitgQAwERBgAieogJlnGzurL5M+G8nRZfDNAiDRigtlKIVHNDZPUCpwE7nU5mfRhHQo6RST2CePiazqQWixrmvCYi/NX1J9mQVMiza5KYMzKKO4dG4KdXUWdzMOujfXio5HQJ8kCrkvHv8V15Zk0SAD1DL7PPVW0FfDYNKjJBqRd9NQFeCoM7V4sepek7RJ/Tnx4UQhXgl0fg6I+QKYzi+GYW+HWGe9aLVFKb5bLqzWmymhixYgR3xd5Fn4A+dPLqxC9pvxCoC+Tmzjdf0GOXmcuwOWz4qn25d8O9VFmrWHXDqhai+fNjn/PGoTdcj99NeBeAT4996lr27LBnWZ+xnt15u3m4/8NMiGxMsY6KvZmo5F9h6jOwZkFjG5/T4R0Bt33d+Diy9b7hbtycCbdYdePmMqDmwEGUkZHI/do/iqXp09t133fuXHzvmY3TZqPw2eewV7nF6sXA6XRSuXYdcWNEDfGtA9MpeuVVSj76mG353Siu6I8kzIEz1Yxz1Smuf6gPAOZqK7u/SyEzqYzaSlFbJZHUt011gsZDwS3/HtTmHqh+9/0Nv/v+1mK5qlMnVJ2uYiOWy4xuw4Ipza2mz7VXaU1haxz4GAqPwaRXYN3jsP+DZqsXoUAls2KpUsBXq13LHx3hzcbkcv71wxG2PDLaFfnPq2gUdSmFQvz4huq5b+lo5PU1rl2HBtN5cBAfP7qTtMP1YlXTmAbc0C+1pkp8t1yR1QucBrw9uZiEHCOzhkTw5NRYpFIJwZ6idrnAKER4Yk4FG5IKGRDhjYdaztLNKXx/MIfd/xzHqXphW2WxcSCznBdm9GB810CeWZPEXUMjzrnm9YJSmQdf3Chur3sesuMgIBbi/gfmCvjoOtFKpiIT5Bqw1cK4J8XnpTJXGCA1pe8dja1OlO3vcmx1WDlUeIgBgQOQna41zWlIKRcGRJ8lfcZnSZ81W9feYrWopohlCcsAcc67c3dTa6vlmohrSCwRXQAOFh5kYNDAZvu8cuAVRoaOZPGwxYz7VrRken7485htZp6Pex6AyVGTmR49HavDilL2u9Zg098TvVGlMhHVdreduaxxOp3knjhG/Ia1+ISEMuzm2y/1KZ0XbrHqxs0lwul0IpFIcDoc1Bw6hMc14y/IcRoMewBU0UKQSORyJBoNjqrqC3JMN81x1tbStDLId84cyvbGE785h2K/zsQUbWbk+4+x5+dcMpPKXNvtWHGS1EPFRPXxJ7p/AIfWZ1KcVUWXIUF0GxpMYEeD68LczZWDwU/D5Pt7nX3Dq4WcA/Dzw+J++k4oqe9B2ed28I3GVG1k/Z4DOHvdyp66GMqObeIx+Qq6SbPRWEqYPTySxWuS2Hy8iGtiAwFRs+qlVeCrU3KioHHS7fffB6lUQlgXb04dbhlZ1RrEhbipQtSJWkxCrF5IN+DtycXc/cl+VHIpT0zt5krX9VAr0Kvk7EguoX+ENzPf+w2AkTH+/H1MFGNe2UZuRS1mq52TBc0nGSf1CMZHp2THorGEeV+i1HKHXZjpHPtRREj9u4jU34QVIlJ6x/cQNRp4CIvdgmrEw8LcaO0iSFwpxpDKYNpb0O9O0asz+VcY/xSkboa8Q3D0h8b00jbS8H+2rSzctpBt2dt4dMCj3NW9sZ3NjpwdvBj3ImabmY6eHekb0Jf7+9yPQto4sZFSkeK6PyJ0BGM7jOW5vaLlWJ29rqXwOwccTgfP732eWN9YZsbMZG3aWr5N/ha9Qo9eKdpfVVurWZW6isFBg4kriCO+KN4lVrMqs9iQuQGA+f3m46/1Z8WUFWzP2c7kqMkopAoMKgN2px2VTEx+tnq+EglI6r9jbqF6WZMct5vfvl1OSXYmKq0O39AOl/qUzhu3WHXj5hJR8OyzVHy9AkVEOA6jsV3rVZvS0LcTQBUT07hcr8deXYXdaMS0Zw/6MWNc7VDctMRhd3BgbQYRPf0IjDS0aR9ztRWVVo69qgqLqvF9MBbXskE2A/xAbS5lwM090fh54tehkhN7C4jflIXZZOXU4WJ6jgll5C2dAQiJ8SL1YCHdR4Vedn1P3bhxUZkHG58WfR6jxuBM3oAEcPa7C0lZmhAvd/8CoaLsYVN8Lgutg/hu4FBujPDmx8NhvLo+gI8si6CqkEg/cZE19/MDfH7PIEbG+LE3rZTOgR6EeKr5La309OcChHXzaVWsqrQK9N4qSurbCJUV1CCRSlwi9kLw0PJDAOhUclTy5sJ6Uo8gvjuUw67Uxn6r4b4aVHIZC6/tzKLvEikwmonPrkAhk2C1O1HJpfjolPXbXsR+qrY6kMph8zOQnyhMdMpOgcYHTjVxs5cq4IZ36oUq7MzZyUNbHuKG6BtYPGwx3Pi+6I8a0FWkCDcIy6jRrn3oNlX8jX+qzafndDr57/7/sr9gP19P/bqZqDwdtbZaduWKlOP3E99nRswMDEoDnx/7nFcPvEqANoCquiqOlhzlQOEBVp5cSVefrgwOHkwX7y6sObUGAF+1L08NeYpgfTCeKk8e3f4oqRWpxPrGtvn8f8+BggN8m/wtAO8lvEdRTRHBumA23LTBtc0HiR/wfuL7PDf8OWaumUlRTZFr3ZQfhWOvj9qHGG9xHdDdrzvd/bq7tpnUcdJ5n5+bS09dbQ2FaamYKsqxWa1sWLYUn9AwrrtvHl2HjUKhvnKd591i1Y2bS4C1qIiKr1eI+5lZAOhGDL8gx2qIrEo9PVE0cQeWenjgqKomc/ZsLEnHCX7pJbxmnKX+5E9EeYGJvavT6DUmjNAu3hSkVbL/lwwOrs9k8PUdyThSSkC4gR6jQ/EKbH6RWFlSy86VyWQcKSUoykCHUAn7hz7vWv/Ni/td973Lk/Gc8hAAQfU1jLu/S0UileAbqqP3uMbZUK1BSa+xV+7sqJs/ATVlsHKWSPntPAHSt2N3OJhueZ7ZoTOYOS2s2eZ1NgfP/ZxE50A9vcK8kEgk3NgvjBs7TYE3FkF1IRERjd+vrLIajuVVklJUzQszemCxOlgVn0dhpZlAQ+sXY+GxjRGgpmnAAAERBooyRZ/TjMQSQqI9mwna9qTAaKay3pX4lZtaRtZfubk3j03syvbkYhxOJxqFjEk9RIurkHrTpVPF1fxwKIdrugWy+IbuZzTVvSA47PD9HBFB1QUIo6SgXsLsaNwTIvKZsQsslRA6QLjSypVkVWbxwZEP+CXtF+xOOz+k/MCCfgvwVntDh4FnP24bOVVxir35e9mavZW4/DgANmZsZHLUZAAOFx0mw5jB1KipKGTNBeyR4iPYHDbm9Z3H0sNL+fjIx8zpOYfXDr7GyLCRvDr6VSrMFXiqPNmSvYVn9jzDvoJ97CvYB4BGrmF+v/nM6THHFc3t5Sfe5zvW3sH7177PgCAxKW2xW3A4HS1ax5yODZkb0Mq1zIqdxf8S/+c6XlPu7XUvd3a/E5VMRaA20CVWc6pyXNv08ut1Sc2f3LQ/WUcTMFWUs/mj97DUmFzLtZ5e3PzkC+i8rnzHa7dYdePmEmD84QcAwj/7jOpt21D36I4iIOCCHEuqUhH++Weou3ZtvtxDj/nYMaw54h+ZvbSktd2vWmoOHUbu74eyQ+vi7+j2XNIOF5N2uJhOff3ReonUKD9pGb/9KK4Q81ONJO8v4KbHB7icXfNSK1i37Ajm+nYYBWmVFKQ1H1ujVzD1/u5kvr+czgvGIDOISG1gpIFZzw/FarHjFaBFpnBfVLi5AnA6hctn6ibYsxTMlXDTx9DjRrBZeGbFLo4eNbPpeCEz+zcXqwczyympruOFGT2bO9jq/MVtdSFh3o1iNd9YS1qxCaVMytSeIaQWi5TYxWuOsfZIAYefvBZvXfPIqMFPg8FfQ2VxbQsh6h+uJy2+GGNxDWV5JobeeOFqt9cdFS2rNi0cTXSAvtVt/D1U3PS71whw1bQu3ZxCpdnG3JFRBHhcgkhJ/HIhVHvcJB5rfWDSf5sbHXUcidVuZVvONrZmbeVo6VFyq3KRSWXMjJnJkOAhLNi2gF25u7i+0/UcKT7CksNLWDp2KVqFllqbqNttq5BrYH/BfuZumIvD6cBD6cG0TtNIKk3i6T1PszlrMxa7hYzKDDIrM/lf4v/476j/0su/cdJg+YnlqGVqbu16K6eMp/j46MfsL9yPw+ng7u53o5Fr0OjFOU2NmsrAwIF4KD2osFSQUZlBv4B+qOXN35NgfTAauYZaWy2z18/mzTFvUmouZUvWFg4VHWJYyDBsDhvBumCu73R9s/NpSkp5Cl19uvJg3we5u/vdLEtYxugOo1ts15DCG6ANYEv2Fj479hlWh9W13l/rf06v6ZVMaekOCgpX42noh5/fONTq4LPvdAXgcNix22zI5HL2//QDu74W9dFqnZ4Zjz+NyViOzWKh+5hrUKqvjmw5t1h14+Yi47TbqfjmW7RDhqAbPAjd4EEX/Ji6QS2PIdN7YE5IBJkM7HZsTVqrXO1UrltH7sMLkWg0BD31VIuIstPpJD2xhA6xPoREe3JgbSZ2mwNdXQndty/GM3Q0+qFDiLl3BqvfPMwXT/xGUJQnPUaFsOWLExj8NFw3pzsKlYzAjgbKNm2jYN48or5ZTqU+Au9gLUq1nOBXH2pxbu52Jm6uGGx1cPwnSFotbgFiroNrniFVEsGDb+7g/jGdWJvuACAuvaxFDeG25CIUMgnDo39nLidXgj4Iik+glEsJNKgorLSQWlTNwcxyxncLwFOrIDbYE5lUwtojBYCIPA7QtaylC4/1IWl3HgpV88iqrn4SKj1BTNaFRLfe7qM9+CUxn65BHqcVqmeiIbKakGOkb7gX/SMuQbSkPEM49IYPhRs/cPVnbkqFuYKfTv3EF8e/oMBU4Fo+rsM4Hhv0GKH6UBxOBxGGCJYlLMNb7c2bB9/kZPlJFv+2mCeHPMnkHyZjUBn4ecbPLcY/E+8lvIe/xp/PJ31OiD4EgNLaUh7c/KCrXhNgWqdp7MzZyYdHPmTpuKUAZFdmszlrMw/0eQAPpQcL+i1gT+4eEouFWVFrIjJQJ+qntQqt63it8fqY11mduprdubtZsG2Ba3k3n25sz9mOzSGi7StOrmBG9Azm95uPEydqmdpVj5pmTOOaiGsA0Cv1PDrw0TO+Fg3fsVcPvIpcIsdX7UupuZRrwq85435XMjZbNeXlv1FZmYCnZ3+Sjj+GzVZJQcEqUk/9lwH9v0Wv73ypT/OcqKutIXX/Xuw2GxoPAx2692TXis85umUjBv8AyvJy6NC9F12GjiCsW098w67OzCu3WHXj5iJj2r0ba14eAYvO/M/mQiP1EO1R9CNGYD5+HHtFxSU9n4tJzf4DAKi7dCH/X/9CIpNi6jaSwvQq+lzbgapSM1WlZvpeG06PYQGYT6WTcAw6pP1K+P/eQ//Z51gPrsT/uTuZfH9PfnztMAVpRgrSjAR2NDD1wd6om7S/kJurkTptyDw82lzv6sbNZUtVIexeIiJsVXmi1nDYPOgxE0KEk/Wm7ac4UVDF/BXxAIyM8WNnSgkFlWaCPRsnZLafLGZAhA96VSuXI50nwJHvoM5E3L+vYfYn+1h/rBCAGX1DAdAoZcQE6F0mS4WVllZPedD1HYnuH4BE2txsR60XUdiMxBKkckmLtlHtRb6xlgOZ5Tx63fldLKsVMnqEGjiaW8ncEVHtfHZtJGMX2C0w9c1WhWqNtYbZ62eTWpGKp8qTpWOXMiBoAAWmAledJIBUIuWJIU+wcNtC7t90v2v52vS17CvYR7mlnHJL+TmZI+VX57O/YD/z+s5rJhx9Nb58NOEjVp5cSVxBHIWmQhb0W4DJaiLN2Jjysi5jHSCELECQLojlU5aTWpGKj9rHFbE8H0aEjmBE6Ag2Z21mwdZGsfreNe9hUBk4UnyEAlMBJ8pO8EXSF6xNX4vFbiFQG8iSsUsI1gdTYakgyrPt77vV3hhN7WDowFeTv0ImkaFVXMS65otIXV0JBw7eQm1tZrPlgwetxeGoY/+B6ZSWbrvixOqhtT+x+5svGxdIJOB04hceCU4nk+ctouuwUedkInYl4harbtxcZEy79yBRq/EYf2Hcf9uKVK8DwHPGDKz5+dgrjBfsWI66OipWrMD7ttuQKC5sW4i2UJebg6pbNyK++pLUMWOp3rmL+JxIMhJLqCiucfXBVO36kZR/fY1PeQUD9WH4RRjQjRyJ+eRJil97HePPv+AT1ZG5b4xi3bIj1NXauG5u92ZCFcBeKWripAa3UHVzheN0wtpH4Pga6DgabngLU+hInlt7kiGFvkz0t6NWyDiSYyTUS8P1vUM4nFXOA2Oi2ZlSwsvrTlBYaSGlqJr518RwoqCKf07q2vqx+twOhz4TTsIz/seASB+2nhRGSWO6NJZN9A7zconVnPKaVofS6JWEdm5pnKTRi+9qXqqRwEiP80q9//FwDqNi/PHVNwqaPaklfBmXiQQJ1/cOpqK+Lc7E+hrU8+HT2YPYmFT4h8b4Q+QngkInep3WE18Uz2M7HkMtV1NSW0JVXRWvjHqFceHjXG6yHsrmEwA2o4V+zh5su2UbO3N2sjV7K0G6IKwOK3H5cZTUiih3mjGNTl5tS8tuEJsTO05ssU6r0DK7x2xm95jtWtbRsyPbs7djsppYfnw5bx9+m8HBgwnVh7q2CfMII8yjZUr2+TI+fDy7b9tNcU0x8/b7XQAAIABJREFUPmofUa8L9AsURmOToyYzPWY6Sw4uYWfuTopqipi1bhZeKhHt7+nXs83HemroU6w8uZLcqlwWDljY4j24migr28PRY/Ow2arp2fNdPA19yc7+BK22E3p9FwAUCl9qatIv8ZmeOxmJh/CPjGL6oiepLCokI/EwAAOnzUSlvTonHlrDLVbduLnI2IqLUAQGIlFeOMfJtqCMiEAeHIx+3FjKly+/oJHV6k2bKHzxJVQxMeiGDr1gx2kr1pxcVFEdkchkqHv1ojY+nnLNDJQaOUk78wBQyW3YvnwPw3XX4nXzTSiCg5H7+yORSND27w9A3qMiOq7u2ZNBUVEEv/gCEpkMe0UF+YsX43XjTLQDB+CoF6sy/bmn/7lxc7EpM9WhU8lcbrW2Tc/jzNmPwrsD1oRvUTjMMPYJGL0Ih8PJ86uOsmJ/Niv2Z2NYLWd8t0DWHytgQvcglxCtqbPhq1OyOiEPX50Kq93Bk6tED80xXU5TRxc+WBxn6/MQEMuYLrN5Zf1JBkZ6N6tv7dXBk5UHsgHIKa89p+faMLHkdDgJjPJssT6nvIZQL81pIxcZJSYeXpnA2C7+fDK7sdzikz0Z7EguRiGTklVWQ58OXnio5ET5nf9vgJ9exW2DLnJv3rJ0SPga0ndA0XEI6tEsqvpDyg/km/IJ1YcyImQEt3W7jb4Bfc84ZMHL+8HhJPTFEYyPGM/4iMaJW7vDzrbsbSzYtoDpq6cTPyv+rP1OK+sq+fbkt/T060kHj7alQUZ5RmFz2hiyfAgAEyIn8OywZ9u07x/BoDRgUJ5+0jLKM4ol45YAUGYuY+G2hRwsPMi8vvPoE9CnzceJMETw2MDH/vD5Xq5UV5/EYimipiaNlNQX0Gqj6Nv3Szz04vcmOvrxZttrtR3Jy/+G0NDbMBguXtuwypIiso4k0GXYSBSqtteYZyQeZu/3K8g9kcTgGX/B4OePwc+fsNgeF/BsL1/cYtWNm4uMtagI+QUyUzoXfOfOxefOO5Eqlci8vLCcOnXBjlWbIOp+7MYLF71tK06nE2tODvqRIwHQ9utL4W9HMRbV0meoJ/oQX+wOCepPn0PTozthS5e0GEPTsyeeN0xD6ukJNjvly5djPnIE37/fh6pjR4xr11K17leq1v3q2kei0VzyCQo3fz7qbA6mv7ObmweEMXt4R9dyp9PJD4dyySyrYX96GSlFVfQL9+ZYXiW5FbV4qOQM6eTLaJ8K7jjwCgDmDBWb7H047Ijm/n4P4ge8vjGZr/dlMbaLP3NGRPH9oRw2JRUSG2LgofHRruNplXLi/j0eiUSCTCrhaK6RqW+JNiFdAs8Q9Rn1KBQkwJbniB10Ly/d2JPx3Zr/fvYOa6wzPV1k9XSo9Y1ZEMFRntTZHLyzNZVpfUKorLUy4909vHJTL24e0LoISisRbW/yjeZmy08VVTO2SwAdfDR89lsmMqmEbsEGpNJzSNcrPSX+Yq5tbmDUzhwoOMDGzI0cLzvOwKCBPND7ASEQnU74bBoYsyCoJ4T2w953Fh8nfkCwPpgaaw2/ZvzKpI6T+O+o/552/MqtWdiKapFq5NQeKwGHMKizFphQhjQX7zKpjLHhY+nm043jZcdJN6YT7d34OXI4HSw5tIRuPt2Y2HEiBaYC7t1wLznVOTzQ54E2P+emgnpe33nM7Tn3skul9FH78OF1H1JgKmjXCO+VgMmUilbbCYlEQkHBatLSlxIYOAV/v2vQ62OJ2zfZta2f33i6x76GXN7678i64goeq/oHPfmNtCPv4QhfTIXVzqKOQTiBkyYzhypr0NnyuM5Xh0rlf9qx2kKduRar2Yxa78HKZ/5JZXER6fGHiP7L3/HVqzBoFCTmGIkJ0JNRaiLMW4u/R/M081/feR2pTM7wW+6g/1R3lwa3WHXj5iJjKypG07Pt6TwXColEgkQlfiBlXl7YL6DBUu2RIwDYjZUX7BhtxV5RgdNiQREinAF9Zs1i5b4IAOo+egNleSKqjh2xJCdjWLSo1TEkCgUhL7/seqwfM5rsv91HXXo6qo4dqVy7ttn2vvfdhzIi4gI9IzduALsV4pZB50ng13hxn5hTQVJ+Jc/+nMTPicKN9tkbuvPN/my+/i0Vb6qI9JLyoCGZT1O7sFD5E0OCiinGi6LMOiJTT1EtUfNe8AscdUSyPUvUhHZLLkUqgXe3pTKxexBv/bUvCpmUETF+rZ4egLxJb+AeoZ7MHh55xqglIERaz1vg+BokxSe4bVD/Fpt0CfIgyKCmoNJMXoWZmjobWmXbLm9UGjkSqQSnw0lQlCdx6aUs2ZzChzvT6BMuRHB8dgU39Q+jzu5ALpUiayI4kwuFWNUqG6N/OeU1pJWYmNIrmI5+OupsDuKzK7h7WGSbzsnFzwtERLPPHTDlVVC0v/naqYpT3LP+HlQyFZGekbyf+D4Ou43rNWEs3fFv5tRW0HPgXJj8Ksa6ShZtX8Rv+b/ha/XEYNfT2asT9wfcQ112FQ6LHVtJLbbiGmylZnA6kcil1B6r74MrAVUnLxShHpiTSqk5VIQyRI+9uo6a+GL0w0KQSCVIJVJeHvUy01ZNI7EkkWjvaJxOJ5mVmaxKXcXHRz8GhLPtv3b+i6q6Kj6e8DEDgxpb4Djq7EiVp4/IhnmEcUOnG8ipzuHeXve2++vaXsil8j+dUK2uTiZu3yQ6dJiNj/dwjiUtBCAj4x0yMt5pJiQjI/9BVMcFSE7TjqfSZmfBiWyMTgNbJBPYUgekiuyp+Moq4qtMlNvE91nidPCf1PkMMajo3//b85q8sNusfPWff1CWV4gEGaUeBvJ7DOGLsjAqlorJOYNa7mphBRAToOOJ0ByKkpOoLi+n85ARmCrKGXPnvfSfcsM5n8PVyHmLVYlE0gH4HAgCHMD7TqdziUQi8QFWApFABnCL0+ksr9/nX8AcwA7Mczqd6//Q2btxc4XhdDqxXSaR1abIvLywG43nZGjRVpxWK+ZjxwCwV176yKrDJCIvUp2Y0ZcolTjr/9F1CJejv/YWyleuRN29O9533N6mMTV9xSx9XVoa1SoVtQcO4r9wIcVLluB33334z2vp+uvGTbtgt4r60UOfQ9pW6jY+y64hHzJ07FQ0ShlrEsSFWecADw5migmpKUt3MUSaxEH9e3jYSnFK/ZCUlXCXVILE5gTdAEKrjuM0KKh26DH2XcSiMaLez2Z3cN0bO/jPj0eoszsYGuXLa7f0RiE791rPp6/v3rYNA+u3K0yC0JZiVSGT8tu/xvHvH4/w9b5sYp9aT/pLk9v0WyaRSlDr5MgVMnReKtKSRJ/CCF8du1OFyNqZUkKXJ36lzu4g0lfL1kfHIJFISCuuZu0RMQFQVX/xuTo+12UqFR2gJza4MeVzUMeWLsUunE7IPQh5h8GYI27Td0BgD4j/Ujy+5TPwizn9GOfBnrw9OHGyevpqQnTBPP31dXx89CO+dDoxa9XEK/252UNDyraHKTeXc6joEM8pFzHgeGOUnsPFFFHseihRSJH7akAmwWm2oQz3wO9u8R5KtSKSXf59CtW7csHhxFZuxny8DLm/BqlShjm5HH8/DT5qH1aeXMnUqKm8dfgtPj32KQCDgwYTVxDH3A1z0cq1fDThI2J9Y13HN67PoGpbNpoefig7eKAI1KKK8W5hrvXc8Ocuu2iqG6ioEH3Is7M/ITv7E5TKACIjH8DT0BtjZQJG4yF8fUYSFDTjrO/f+9nFGG12fugTTU7Zfo5kLme4byjrZDezsTiPAGcet7GBcDJ4kWf4VHI/pZXfsv/kFq4PG8GK3RncM6IjPrqWWVEWmx1bdSXfPPtvSouKMHdQENs9iQ6TTUgqI9mcMYVdhTE4TVJivVMZqDzExsJxRPiquX1wR/6fvfMOj6pM2/jvnOktM+m9kISEXkMH6QiKXbH33tbe146KZUV3XVexgFjRT9eGgCBdWkKHhPTe60wyfeac748TEiLogm3X3dzXNdfMvKefOXPOe7/P/dxPs9PLhxvzKGxw8sXeDYyMN6PR6dj26YcARCanHPc5s7v85Na0MjQxDOMxzOp2lreQEm7qkVf/R8IviawGgLtkWd4lCIIF2CkIwmrgCuA7WZYXCIJwP3A/cJ8gCAOAC4CBQBywRhCEDFmWg7/sEHrRiz8OpPZ2ZI/nhMlq6b4mtHoV8Rm/TbkC0WSCYBDZ5+uKtv5a8BQUIHuVaMzh3M1/J6TOotmiSTEn8HV2ModE1tJnwUuobDai7r0HQas97o6MymJBHRmJ+8BB7N98gyY+nrArLif8qiuV0kC96MVvhW//DNtfw6uP4OPADMaLB5mw5So+2jqH7XGXsr2kmZejNzN9cDLfhOoYGqWio3wPw+s/Q7ClQ+x0hP0fw0n3ILhbISQOJt0FgABYOl+HoVaJLLt+HLd8sAubUcPLFwxHr/mNr/HQPqAxwoFPFdOlYzjRCoJA5BF1RxvavUSHHF+OWGiMidBYxXCutMmJSavi85sn8NqGYl5cXUBFiwuDRsWszGi+za2nrNnFm5tK+Ci7Er1axKxTU93mRpZldlcouf9/mt6XGf2je0Rcx6eFH3sHWsvguyeU4/shzn8XDi1XfudFU+FBpS42TYVgiQHdz5crBqUga8rXkGhJVBx0i9dyb2E2++KiidJaOSl6FAvqN/Ja6RdYtBbifJG8X/s8YW0mdGlWdOk2HKsU99WwCzIRzRrUEUZUIdqjiOEPYTsjDUEr0vF9TVdb8+KDPeZ55vRHub7wNiZ9NAlXQBlkPDnlZJ6Z9AyXfHMJuc25LJi0oAdRdayrwLGuAkntwr0f3PsVsyZVmJ6weRmobDpkTxBNjKmXqP6bIcsyHk81BkN35Njh2E9+wSMA9OlzO9aQodhsWahUyvM6JGQIiQmXHtf69+3ayastMnOiwxgfaka2TWaUeJCS0pc5nXc5U9SRkfEwRuNNaLShHKjU8F5ZM4vqr0bc4+UV/yacrV6ya+2EiCJWgwajVkX/2BC+3lfDtuJmhuvacGvTKEo6Ga+koU9FGdFNItvqktCqfExN3MwZ/WuYOe4Zvv/4NSanzyfOoMe+bjKmhgZm1DazJOkyIk86nYuvPg1Zknj7jutpq6slMrkPsizR1l6NKHipr/0Qn78ZWZbQaKzExJxJc+t+Fm7Q8nWekm9v1jg5tW8u9542l7LSFxEFNSmpD3Hz+xWkRep5/9pJv/Kv+PvgZ5NVWZZrgdrOz+2CIOQB8cAZwJTO2d4B1gP3dbZ/JMuyFygVBKEIGA1s/bn70Ite/NHgr1Xqzmmij5+slu1v4ptXlZzPy5+ZgDn01x8ZEztd5SSnE/HXJqv7lH1Hrf63yoC9paVok5OR3YoBi2hQJHXONoVIR82djsqmyP5+zjmwnHwyre8pFvNxzz+H2Juf2osTxIurC+gbZea0oT1rNgaCEisO1DFrYHSX6REArhbIWUxg8AXMLDwXbZiWedcMwPH5vVxa8jln16zBoneDHdgM80DRO6m0MPQCOOU5hezMeRaMPxH1+wEiLTqWXf87GqWJIoy9ETb9BSq2QMpEpd3VAnordBrwRB2R95Vb4zgmWd1S3ITDHejhqHv6bcMUZo5SpzU10oxWLfKn6X2pbnWzLKeS0X3CuGhMEt/m1jP1hfWIAlw6Nplbp/flq701PP5VLo3tXkqbnAyMC+HOmd2OuZ/eOI79VXZsxmPcE/YuU9yO/U6YeCeMvk4hrns/gNv2QmgKjL1JIbI1u5VjBnhtkmJ2dOUKUB2/w7ov6MMX9GHWmlm4cyG7GnbxcOKpsPF52LsMQTyFN7T3YxgQRceWGkaNuJplpZ9wmXQOmnI/kiuAyqoj7PxMRLMWb6kD08gojENPbABWUIvYTktDnxlG2xdFiEYNmlgT+oxQtMkh1D2XzYDmZC4bcBlLc5cyOGIwS+csRSWocO1q4JHEe6nq18j4kNG0fV2CHJAQ1CItO3fROOUDnLqDZKpfJCpzKv5aJ45vy2hctB9BKyJ7ghgGhWM9JRV12PGb3vwnIhh0U1P7CU1Na4mJPoPY2LP+3bt0THg8tVRXf4DTVUx8/EW0tx+kpmYZbnc5RmMfEhIuo60tm6amtQCkpd5NSsqN/2Ktx8ZhhdgruYW44vsxp/wgDE5FEERio66gaFMVXs1GBo+9hfj4CwGQJBlN/kEM2+qQZRBECaekDIptP9SIqBKQgnLXNvRqkQRnOTvlRAxqDeNidxMZEsInB/tR6oBrJvbhpilJGNVj0OuV+/mkc+/n8zfWIw+pIGTUu6iLptBvwjl8skfFVw16ZpS1sHpfNvn9JzPr5EY2ltXxfd4G3t8dhSDIaMV+RBgdTE9cQ0Bq4+OCMrzBbnO6oZF56HRxLMsdhVl8gfFx2ahURhZ+MZ86xwXcMHIb8D9GVo+EIAgpwHBgOxDdSWSRZblWEITDd7B4YNsRi1V1th1rfdcB1wEkJf3Ozne96MVvCH9NNQCa+GNe+kehtc7JqjcUx0xBgE3LCphzQ3e+qyzLFObUkzIoAq3h5/+dRZMSVZBcLgg7utMqBwKUnjeP8GuuxnrqqSe0bvfefajCwlBZrV0lXH5v+OvrKZl7GjEP/7krd/QwQT9MVs22X0bSI266EW9REYJGQ8gJnqNe9MIflPjrd4UAR5HV+cvzWLKlTDH6SWiDtkpkrwPP2ucwBL18FJxKRZuPj68fiS4kjMjLFkPj/Vg+OB9aS+H0v0H/05XPehtYYkFzRCf9BIjqvw1jblDIau0+kCX4/CawV8KE22Cm4uJqM3aTttxaByEGNUMTbD1yZS96YzsAZQu6/6OqI5yFK1tcDIzvdgW+aWoa7V4/87IS6RNh6mr/4NqxjE1VIqWZMUp081BdO6VNToYmdhs+AYxMDmNk8hHnuG4/fHqNQrQrt0PSeDjrHwoxBTjtZZjwp+7vogpOuhc+uhBaSiDvSwi4oSobNjwL0/78k6dOkiWWHlzKJwWfUNFegUbU8PTEp3k3dylneWHexn8gy2pauROX9yTIs+PJU1I2jMvhSk5B0PvQ9QvDMjFeiUp2nrPIq36ZO6k+I5SYe0Yd1a5NDsFT1Mbtp95OipDIJNVoRB80f5yHJ7cZK2DFRK0qGzpJhM9YR/mERxE0GrTqCAoDD2I1fox5aCa6VCvtG6rw5LegSTPiKWjDV72P6NtGIOr/8+xbHAdLEFUaTJkJCIJAc/MGWuq34ZMacXTsRa0yYzKl09S8Hr9fGcBoa8shMnIGYsBA0+KDhMxIQt/3t1FjnQiamtaxb/8NyLKiYmpsVDIAbbbRqNVm2tsPUlDwOBpNOLGx55CcdF2PaOvx4ru3X+PQlo14nR1MvOAythvDSKgto/rrJVSnp7HunTeoLylEEEQEMZLSVf9EEL8gJDKajpQsPixX/s9f3DyBvOblPHXAzECLRGNDGHXxOtob/MRXOUg1wjj/OhIyV6CL8WPSpzFxwueIoobpB2qpaHFxzcTUTjO1bgMxvcnMyEmPUmG/AQBj+npMUUa0B+ZQY/dw3muHY3ehbCgLBQqBODJCi4g2NhAVMZ59tZEsPqgMtA2Pa2dcWjgtLRs4UG9mwVmp9OtzFjNeXMd31ReQnnwemyvi+a6gkUExHk4fNfPn/Hz/EfjF/1BBEMzAp8Dtsiw7fkJWcawJ8jHakGV5EbAIICsr65jz9KIXf0T4qxXJkyYu7pjTfZ4A6k7ZWH2pg+/eySXgkxh7ZiqCILD1n8V88Ng2zrkvC51BTV2xndVv5ZI5NoYZVww45jqPB0dGVo+939V48/KouevuLrIqud3UL3iWiJtu+tFIccfGjdg//xzzlCkEW1uR/k05q978fAgGaV+9htCLLwJAMCjHbG9UIq2mX0hW1WFhJC9Z/Mt2tBf/WwgGQKVGlmUKKut7TNpZ3kq4ScvWkmaWbCkDwL7rM/hakcgJwGG7nSd36bhgVGLPnMjITLh5OzTmK06uggCGny4p8h8NcxSYImH3u9BWAT7F2IicxV1k1XxErtay7EqeX5XPn6alc+eszKNWJ8syO0pbGJpo65Ixy7JMrd3DzAHRXfMlh5t49WIlTzYQlLraDxNVgP4xSl7qi6sLqGx1cfaIfzEYefCf0HgIdCFw0j0w+X5QHdEdU2shqn/PZcJSlfePLwNHNQw8SyHtO96AiXeA3w3G8J6uwbKMXwrw0OaHWFG2gjBRxyxrJtmeBu7ZeA/x3ijm1Vmo17yA32kECYzDo9DEmlCF6hCNGjo2V6PvG4pxRBS1SJy6p4hgJfxjQDJZVhO/FQz9w2j7qoT2T0sZtzOeANU0pbTjq3CgjjAQaFLu2+axsRhHRNP09n6cY3cgqyTGjl4OCGzbPovKqqX07/cUKosW29xUmKucR09hK01vHcBT0IpxiBKdkrxB3OUNtEobie17JirVL3smOJoaqC8uou+Y8T3aZX8Qd14Lmn46GhqX0+HMp6MjH0FQo1ZZUNdH0uj/BknlIWrveYQmZpHnUXwPVAELNttI2lw5ONr3ERIyjCGD/4EoasnOOYu6ui+x5E3EV+6g7YtiYu7O+kXHcDzweGrpcObj9dQiIxMfd0GX4ZEkeck79CAmU1+GDP4HgqjB7SpHp4vBaEwmEOjAbt9Nmz2b5KTrUKuPv7ST3eXHoFWhFmT8Xg/71qwkpm8G26NSuNpnojEiistc9ejNZj56VCnjo7eEcM4DjxPwedm+bj37HWpWt+vJLQ1BL3t4vk81dcuL6RMdw+LUb7F7VtLuMNJUEs7Cfg/hCNcwYcVzpJ9WgVprJDZuLqmpdyCKykDZ7EGxP7nPfUfOxFSzALM5k4bGVVRVvctV/Yuo7ogjPtRCdbuVTFs+OvNEwi1WRDxk9Z2MVq0MThTUt3P2q1s4c3gcj542EI1KRJYnI8uBrn146NSBXLUkhweWa4gwtzN3aBJ3zMwgzPbrG7T9XvhFZFUQBA0KUX1fluXPOpvrBUGI7YyqxgINne1VwJHe7wlADb3oxf8Q/DU1CDodqohux0yP08/Wz4upLWyjtc5F//Gx1JXYaa1zIaoFZl8/iNRhkciSTMmeRupLHZTtayJlcDgHNyt/oZI9jaxcdICJ5/X9WTLhrsiq89hlH3xlZV2fgx0dqMxmHN+soG3ZMgBiH3/sqGXaPv+c2vsfAEA/ZDCu7TtwbtlK0fQZpH6z/FeXG/8UvMUlALh27MAyaxagEPT2Fg/bPi/BYNFgDvtjGg/04neALP+6pUM6GsHrgDenE0yfxdclErM7Pudp9SQeDFzN9e/msOpgN3k9KSMSg0YkoWAhHaKei3wPkRQRwnPeJ6gOhBBmDemqZ9oDah3E/n41BX9zxAyG4rVgTeomq0eMg0/OiOTlC4bx+e5q1uUrhj+7K49dP/qtzaXMX57H5IxI3rlKqY/a2O7FG5CItR67U6dWiTwydwCDE3rWYw01aUkINbC3qo25Q+K4fFwKOJuhrRzihve8dpqKlAhxfBZc+12P9Wyp3oJRYzx2Pc3QFBDV4G6DuS/ByCugYBXkfgFPdw5+DjgD5i1VPktBPG/P4lYa2KaB21taucrejkAhjTdv48r1d7Mw/3YMkh4pTI9lciTaeDP6geEIgkBQlllc3cTkc9MocXvZWlWPRaWizO0D4OHCar4c0RfNiZTiOQ7Iskww6MI0OpaK4qVUqr7HO7ma2P03QNkAQmanoM8IpeGVPUTdPAxtvEJuwu5MIT97BdGRp3RF5aKiZlNf/xUx0adhs43u4RirS7UiaER8ZQ6MQyKR/UEaXttDcdJ9eKyl+O0OUkZdg3NHLcYhkV3GUD32VZLxFrehsmjxVbYTaPEQdPjwhwdwbqqloD6bNnc9ZrsFizUC2RvEZ6qjpXkT7ZXF2BvWI4mdaSnoMUhpuKVKPKoq0MuYhYHURb5DnecdRL+BjKK/Qose2S1hGzSdqohFxOfeDDWhiLEmzOYBlBb9DU3LZ+jTkgkvOYOg04/KdPwy8RNFUfELlJf/o0ebwZBEeJgi1a9vWIHP18CA/s9hMCgUQK/rluCr1WbCwycRHv7T8lRvIMiK/XWkR5npHxvCB5sLePSbQtRygD6uMk6VDtKmN7H55Ev43ts9qHTLhHGEjBzCir+/SGttNdf+/W0EtZZ7P93HN7VpePwSYSYtZw4Ow7T+bQo2lKMzmvC6nCDIxIyIIT5LwBJfxUxW8pH5UpLOrcWgjSRr5LKfFQGOizsPUPJv+6TcQlyJklv6w9qwx0JGtIV9j87qUQJLEAQUOqZgWr9oFl8xiqpWF+ePSupRk/qPil/iBiwAbwF5siy/eMSkL4HLgQWd718c0f6BIAgvohgs9QV2/Nzt96IXf0T4q6vRxMV1GTtkLy9lx1elAKQMiSAYlDm0rQ5Zkplwbjr9xsV2Fa0XVALn3DOSJQ98z5rFuYhqASmgCA8CPonSfY20N7s5664RXdHZ40U3WT12ZPVIslr/5Hzinl2AJy8P+PHaqU2v/B39gAGEXXUV5ilTkJxOXNu346+uJlBX96uVcpEDAQR1z1uZLMsE29pQhyoSKF+JUkNW9vtpX9vZQdTpWf3WQYJBiXPvzkL9W5vE9OKPiY0vwL5lcPYbilzW9gtSUwI+2LwQNr0AQaXTr9q/jDMABLhIvZYEoZF/5J/LhaOmUmP3EmbSMn96OP41T2FTZbPWcjqPnnspI5JsCIELSJclvlcbTqx+5x8Vs56C/G9g8HmKjLZqB3jtSh6nMQxBEDhjWDylTc4usho4Is8sKHV/fmmNIrnOrVVSE5zeAKOfVu4NcbYfz2O8amKfng2SBBue5b2z5yLZ+pAa2RkZ+uQuJYIaNwIm3Qn9T1Pal9+hvB/+3gm/5OeO9XfgDri5dsi13Dj0RpbmLuW78u94YMwDDIoYBJd9AdaEbnlw+gzyx1xDqtaKJu9rKFzdFa3f/P2z3KhRYgVPBEI4a+JtED0Y9xsPIP99L2/i83oHAAAgAElEQVQOe4SA5MMcV4z1xssQND07tC+X1/NcaR0qASI1Gup8fgCS9FpuT4nmzkOVzMzJ5y+ZiYzsjLAWuTw8U1LLY+nxJOqPnbPv9zsQRWWaSqWc5512J48X1/BaHxe1pc9SZi8jMfYM2hPexGTKQHb7aY/ZgcU7BPP4OEStioSnFTIUDLooKHyKmpqPAEhNvb1rW2mpd9HSsplduy9Gp41m4KCXCbUpkmNBJaJNsuDOayZkVjKO1eW0SOvZZI3kK67j+sbNxBS00vpFPvlFj+GNKUMSPWT0e4hw8xQkdwBPURv2r0q6D05UCKyAgEpWMShkAoRAcG0bbSiDJtVDX6EjOgf6gKV+FOF1cxEcBhAktJ4YkMAeWkpgfAepA+bhCRyguux9bLpxxM2YiuT2U79wJ+p9iaTwJJg1OIvrkb1BIsacSY1mMQFLE82Re9C4I4goG4hh4I+Xk/q58HhqKSpaQH3D10RFnUJi4hVoNeHsyD6d4qLncMeVExExlarKdzAa0wnrJK8/B9m7a3hucwnZ1Upfw6JX0+4JEOFrJs0isF3oS4ioYffZYwj6Zeb3jUcrCBhVIkm2ECCEC554jvlfHeDsRTmUNTlp9wY4dUgsV03ow9AEK2qVSMtJMRTu2ELW3LPwupwUbPue8IREEgcMJhDooLG2jo+KOnDphzFt2NM/i6j+ECqVgYy+D53QMsdzr5/a7z+r4sQvxS+JrE4ALgX2C4Kwp7PtQRSS+rEgCFcDFcB5ALIsHxQE4WMgF8VJ+OZeJ+Be/C9B9vtxZWcTGDWdNUtyaa110lDeDsCwmUlMOCedTR8XsG9tFXqzhiFTExB/UA5CEAUmzcugaGc9IeEG0kZGEZVsQZZkyg80881r+1n3/iFmXnmcJSE6cdgZV3IdO7LqLS1FDAnBMm0aHRs2IEsS7t27AfDk5R41f6C1FX9VFaH33I11riIbjr7nHkxjx1F57bUEmprQJicjeTwgij/bjKhu/lM4li8ndfnXqI/ItW1fuZLqu+4m6e23MI0di7e4BMOwYXiLi3Fu2AjAru9bqS22M/PqAYTF/nZytl78QVC6Eba8AvUH4JrvFEObojVQsk6Zvmiy8p48AfqdCllX98z7PBbaKpX1tZQqNTIPfa2sM34kXlnF1/ZU7m0+lbtP7k92cR2vtlzHSa79nMR+OPSsUqYlYSa8/TK4lDIq0y5/BCI689A0egSOnWPzX4noAcoL4PKvoGg1LLsEavdC2tSu2fofUS4mIHVHWdpcvq7PHd4AmdEWSpo6kGWZTYVNXdNifiSyekxU58CGBaQkbYSrVnRu1KsQx4RR4GyCZZew7uzPuctu4+XWDuRpL5OadRGHu7oBKcCNq2/EFXAxMHwgi/Yt4sO8D2n3K8+Hi7+5mAdGP8B5GeehErsH1fa15HJxw7dMS5zGi5PuQvXP6xSC3O8U3s//EDRwXvTpzB3+IF53APvyMnyBx8AvwDblXFimxB9FVLe1dfBCaR2jrSYKnB7qfH4m2MxoBIHJYRYujAkjTK3mwcIqrjlYxu7xyvPmb+UNLG+0s7Wtg7tTYrgqodv8xR9w8U3hx3xVV0menEm8qp2PJl2GKGqYX1jAjnaBl3a/SZ04im+5F3WNnwe1JVyftZADB26jPZCPbWgaolZFm30n1VXv43QVEwx6cLmKAEhKuhaDIQlJCtJSVUlYQiLjxq6hqWktJaUvsWvXBRj0SajUJiIjZ2Ec14/A+3oa/r6HJt037BuyisXCs9gx84wxgmHf5SL1WU5b3HcYmwcj61zsz72VkLrRRB26FFVAeW6aT03E1C+K+sZSSl5ZS1rIMAzTowlJjWHXW59RJX+LbWQDYYnJuDoOYGweiF6cizY2jTpqSc7sw6ED3xOMqkWr07Nr5ZewC9S67zjpoisYNut1hE4HbJVZS+QNQ2n9tBBfmYOIqwahiTXRvOQgbM8g3foi2nNi2FczF7e1lNad5T3Iqr/BhedQC74q5doyj49Dl9JTKQAgyxJVVe8SFTUHna4n8amp/T8KCp4kGFTUDRl9H0GnU37ruNjzqKxaQn7BI+QXKPOnJj/UJdsWjZrjivTKsoxflulweDh7wyHEejdRJg1nBVR8E/CgCXp51hrBoLA4bqppIEdKQdrYSKxWw/vf1TM3PZLr+8fSKHZwsNXF6+uL2VraQowoMttoYHh4KOeMT0OX3H3soTFxZM08E8EnYwyxMmzWKV3T1GozfSwxQBERGa9gNP77c4H/l/BL3IA38+PPyOk/ssxTwFM/d5u96MUfGR2bNhFsaaEsZgoVOQ3EpIYw5oxUhs9K6hopO0ya0oZHHkVUDyN9ZBTpI3s+PASVQJ+hkYycnczOFeVkzUkhNOb4CdixIqvBDife/EPoBw3CczAXfUYGxrFjsH/+Od6CAnzlSskCf3kF3tJSdH26Iw7eAiVqocvomSumjlIeaIFGpWNYNGMm2qQkUj54/7j39TB85eVd7rutH36IJjYOZJmODRvwlZaCJFHz4IOkfvEF3uJiQmbPRh0TQ/vKlXi1VvZsqCdzbAwZo2L+xZZ68V+P7YtgxT1gjABPG7w6VnmPGqjILQeepTix+t0KGVj1IOxYBOcuBlMECKIS8ToMdyusexqy31TyCo/E9Edh0p1c/eZ2djpaefqcAZw/Kokbp/YF91Yl4lq0Bso2Q/E6KNuk7Mdpf1XI8a9cZ/MPC42+2xW4dk8PsnpkbdPsslZanD7CTFqand1kdXC8lVOHxLJgxSGcviCrc7tl1wmhJ0BWi9Yo7x1H5BznfaXIlCffD31OgmeT+UutkxptKJcOXoAnqKP/vhLWjVak258WfMr2OsX46fWZr/NCzgt8XvQ5AAunLGRZ/jKe2v4USw4uYeU5KwGF4L6x/w1Ugoq1lWsZVrmWkyPDueeL69m2eyi7RbhTnMfMDVOoX78LANGkwTIlCVOqE+cnHyH7VKgGPNjjcFxBiVvyykk2aPlgSCq35lWwosnOlDALtyZ35/LOjrSS7/TwTGktrs5c3m8alehhiz/Ig4XVTA0LIU5lp6bmY+ZXeFguzQAU5+ViCb7c9yzT087G6W0CIlkqXIMgwyUxZtY1O3hffRs3igZCQ8fS1LwWX3IFRfsfp7Fx5RF7LDB82FIslkGo1SFIUpBv/vYX8rdsJGPMBE678wFiYs7AZEpnR/bpeH2NWHQRlJa+DEDqyMex15VQNOBT7hTeAWCyu4Kt+mju6tPMbbpVeNxDKZfPJ9WShLluEY64jbQaD4AjgsYDVloXqxl40nT2r1uNzRTF0GmnYp3RB0EUCIzLI8yYg9+lpr66DrUhSFtBNCX7vuw6gsPOo3qzBU+HQiKNVhsRSSmsXfw6RdlbGXPHQ0QZDOhVIuoIA5HXD0Hq8KOyKAO98hQT6ze/RkejHefDrfQ9M4iUuBbz5omYVkcgCCBpfLRuyEPjCkUVqkP2BnHnthAyJQHLtCQEUcDna0KjCae1dSsFhU/Q1LyO4cOWAFBa+go1tR/j8VRjs44iPv4iQO4iqgApyXdhMg7AHJJOS/Nm8jbsYNeyAjShO7vm0Q8Ix9AvDEGvwl/TgbfYjjrKiO0MZTBClmXO+3oPO2od6OvdqJxBgpF6KgfZ+KtWRd/2IB9tc2J0CwhaFY8kR3JWTT2CVyLRG8AN/C23hg9ya2k+whrHDLwbEYktRIe/wUXja/vQ9w9DE2dGUAt0fF+D1KEoCESjGuupqahDdfhqnASa3FhDFZJd6/vBPf0HkP1BZL90TOl41zxBCW+pHdkrYRj4IyWtetGF/zwLtF704r8E3tJSfGVlWKZORfb7aVv2MWJ4BLXNalKHhzPr6qOjn9F9rIiiQObYn07S/zEMOimBnSvK+eCx7Vw6fxwhEcfX6eoyWDoislr/5JPYv/gCTXIS/ppawq+4HNOYMQA4vlmB1NFB2NVX0fLW27SvWoXuhhu6lvUcVOrl6TIyOBLqzlzdQHMTLe+9T7CpCXdTE8EOJyrziUU3Hd9+2/W56W+vHDXdOHYsrh07qLn7HiS7HV1aKqIlhPaVK6lInI4sw+i5fY5arhf/IfC5FMlnwAuWaEib/uvmjR6JLX+D5Ilwyaew5z3FtGfIPJj9bHdNz9QpyvvUB+Hg5/DFLbD4FMWVVW+DGY8pkmGVRiG6HjtkXQVDLoCwPtCQhyPvO6pSLiHR42dbSTPXTErl/FFHyIoNnS6ywy5SXpKkOPhaE5T80170hCFUqcFauhEm3K5cKxo9CaGGLqkgwMLVBTx55iCa2hXnb61K5M+n9qe8WbnfNXd4WXuonrlDYrlpSjoR5hM415UKyaStXJEjO5tg5QMQ2Q/SpoEo0hI1jBxtAldW7CA7PpMD6MhzeugIBNlevZ4F2QsYFD6IBSctwKqz8vDYh5mXMY8ESwKh+lASLYmc+9W5VHdU4/A52FW/i5d3vUxRWxG3j7idNm8bSw4uoVQ1gI90I6lsrWNpwwMYJQPqSAMhM5IBGW2yFXWnkZz1vkcUQq3uVrV4ghKX7y+hyuPns2HpmNUqMk16VjTZCdUc3V2M1Sud8Tqvnz3tLtqDEk/3jefBQsX1/uqc1QyVtpIjDaZQ6MfkEIk3hg6lwVnHzN01PNE6nGezcymjD/009QyP7M+50aFMCLXwcV0Lf8qrIMfhIsOq5BTv3HU+omggNfVOEhMuJ2/36ySmnYJBn4y33Y3KJrHq1ZfI37IRvSWEgu3fs/7dtxh3zoVYLAMZPXo5Om0EWm0EHk8tW7ZOpiTsUQiDUvP10DlWG7t6FVecIrDIcA3X8C4YUV7ArPxkzrZnEdG/A7e5gHBLHIFtg9m14kvSR41j8iVXYYtRnt+yHES2rsNZZSDG/AAhUXFU5u6nZN+3JA4YzPSrb6IoZxubP3yHwdNmMfO6W7HX16HR6zGGWEEQ2L3yaz5c/hW3ZheSoIKHdyynZFc25/75SRIHKJUB/D4vq996hfqOMmIz+jEi6wxqHI8DUD3xCXSbLIg+M1Uj/4JnYhF94x8lPuNigvYAbV8U4VhTQaDZg2YO7Mg5BZt1FB5vrXJZt22noyOf5paNlJQu7PrtMzMfx2zuORhdV1zIx48/QHRqOqffPYuKNTnUbhQZHzUOn85HoJ8IDX7IbcaT20w1EpvwMwY1fSrbqS9u5Sufh31ikJwONyIQMKuJTTbx1QVDcOhMfNvYymMldVwyJYTlWX05IAe5cF8JJEUyuzbIX+KiMI6NZczza2mWZC6OtDI+oCJdUGGaFE/COMX8THIHaPjHXjx5LXjyFDdllU2HdU4KCALuA020flLQfXBqEX1QQphpodLpodjloazdw7RIK1K7D+fOejx5LexyewgEJLaHq9gTqaFRL6LWiLRrBa6MjyTNrKe+2sHQb2uIbVWIcdiF/TAOjeREIQckvCV2OrbVdtU21iaHYBgQfpRawrmjDnWEHl2q7UfW9p+NXrLai178BpB8PkrmKBKSiJtuou2TT/A1NVN82pN4HAFShhx7JC0iwcw1C09Co/t5+ZPmUB1JA8KoyG2hKr+VAcdLVo8RWfVXKx0OZMDvxzB8BJrYWLTJyV3GSqbRo3Hv2o1j5SoiOsmqv6aGptdfRz94cFck9TBUNhuoVLS8sxR/RUVXe+H48WRk7zgh06X2Vd+iHzIEw6BBtH7wAeZp04i46SbKzj0XgMjb/kTHuvU0L1oEgDY1DSJjsFtSqI6bSMbo6OMm8734HSHLSqf/s2uh+AgDmqRxSs5iwshfd3sBr1ICZdhFSrRu1DXK66cw8EzQmWHba5A8HtY9BV/fDmFpEDcMZImWEbdQZ8hgQJwS5SuzjODMHDdtG7MRBOUwp2b+iw6KKEJ42q90oP+lGH4xrJ0Py++CnLfgrgIESzRjU8MRBThQ7WBflRLx21bSjCjA5vumEhWix+5WOotn/P172lx+5gyK7fq9jhvNxRA9SJF7f3Ub+4IGXku+iZOGTKOPw8UYm5l9Y+6DZhhVP4ir84NsHKniwbAgr+Rv5KOddzEwYiCvzXgNXaNA69oivKV2kgZFEDJN6VhmhmXyyrRXuGXtLby5702W5i4lXB/OE+Of4Ky+ZyHLMhf1uwjXOyXoWpSojzbVimFAOIZBEV0EtQdUGoXsd8InSTxWVM2m1g4e6hPF+FAl9/bW5CgkXy1ZnmU0NqbT1pZDU/N6VCo9Qd1MYBJ5TjevVTaQoNdwcZSW2KaPWd4SYLM0mw/l87o0eOfFpxCiVhFijefF/kaeKNITqbYzMrib61P7MzhGGbjpaGkm+N5r6Eaewu25ZVxSfoCMKBBFPePGfEvexl1UbP6YnK/WEZteQ0dbCwGfj5ShI8jbtI4J8y5h+JzTWLh0KTtWfEXFgb2c9+f5WCzdJmR6fSzJyTdQVvZ39NYJrJJPBzyEt9QzUKchumU9qyOnUCqkE+V18WT/FF4sqWHflNN5c8x9aA0G9h+4FYdjPzOeehF7Yz3h8d0eooFAO7V1/yQQbGPUlL8QF38mAP0nTSXrtLMxh4Wj1RuwxcQSHp9In+FZCILQRXS7Lu/Zc3muVsnVrApCbkUFRlEkf8smqkuLyV+/huaqCtp1Rk666W6mTp4CwDtPvoglXhmMKZl0L0cW3yisfpyqlndQqYyIA7XoEhNxbx9Kx3c5YIU2ezY22xgSEy6jvOINsnPORJJ8REbMxOdvwW7fg9GQjizLbP7wHSIMiYS0WXEWNZKecD6FzbvZdPerZIaMJi1eGbD+rvz/2FoJLpWRUwYmsT1iDF8erCUowyt4idFraLO345G79/O5ETrmjBqCKS4UUachArghOYYqX4A3q5r4e0sbH9YqRHNCrI1Fs1PRdg4ufvKnifj8EoMTj03ORIOaqBuGIPmCqEJ0yH4JQSMidKrcTKNjcKypQGXRYBwRjWjW0PppIQPs7bwpNfJSlZITP7tZItwZRAzKBEzw4QAlNUSUoV9AwBMMUieCySOzoLyua/uzMrS83jcdx5py2jdVoe8fhqASQIaCDjd/qW4kzaBjbpSNnXYnl8SFIx4xWOspaKX5gzxkzw+yKbfUIBrVhF82oEve7at10vpFEYYB4b1ktRe9+F+Cr6IC2e9Hl6Z0JAPNzdTcex+e3FySliym9aOPuuZtevVVdAP603HRY1TuhTGnp9I3K/rHVv2ziephzL1lKIvu2EhzVce/nrkTglYLKlWPyGqgpQXLyScTt+AZXDt2YJqkuPUZx47tIqva5GRCZp9M/TML8JaWok1MpPrue8DvJ/6F5/lhKStBpUIdFoa/ogLLnNnE/PnP1D05n/aVK2lbtgxfVRXh11yDJuqnzQF8VVV4Dhwg6p67scycScfmzUTeegv6/v2Juu8+7J99hmHoUPQDB+LJzSUoyWzYbaAirwJp5D0ADJx0fLVue/EboqMRvn8J2uuUKE/5VpD8ihRWCsDUPytSz/oDSj3JN6cpuaKn/uX4o6zuVtBaepYGORKt5YCsRD9PBOkzlBcocl9HNcx8vMs4Z9oT39Lm2kTpM6dQY/cw5YX1AFw+LpnqNjfDk0J7lpr5L0PQ6e+qfynoVYgnaPp23Bh1LXz/V4WogiLXzpzN3y8agSDA86vyWbKlDH9Q4ut9tUxIjyAqROlQhpqUqGKbSyGtJ2WcoBGN360MdIy4TMll3rmYa0a+Q4Uhjs9qZagt4um+8diNGdDcwIi0cKxqFSdtr0Uz3cySwp2MiRjKqzNfRdsq0PD6bpBBE2Oi/bsKpA4ftjPS8Ra30VdKIsxvZfHBxQyJGMJfzU/i+6SR1v6F6PuHE+JWgUNDEC+2M9IwjYnt6ngfRqnLS7nHy5SwnoS80uPj+oNl7HK4GCTvZZorF3gWAK9jB2NqLqEaUIYvRUBCELQITicwiasPlAFwdWgde/c+iK7jEHem3MxfkydT6PGT0+qgss3BiNZaqlpr2Lt6BbLLya77Hu18RvQ031nz1j+oydnGabWNrJ56Fo9H92dwyQO8kBrFt68uoXDHFvb0H0XLuDlM2bYKe1wyHsGHe9M6hpxzIRFzzuTtJgcvZY7j7CFj0L76JJ88+RDnPfI0BrOlazupfe4gNGwad1aY2dvcwe2NBRiXf8JZTz7Px8/u5/bRzyDWz+bce+YjCAJNKg0PFVbTLKqIBczmfjQ0fMPufReQmfkEshzHoUN/ps2+qyuP1mBIJiq6Z2ZcWFx3yoBKrSZ91NgfvcRWNNlZ32cQRlcHLqOZiLseI3TZGyyuaea7tPE8GBbNmKwxXB09iH9IAlWSjFoUaD0UScshGypdkNn3T8HRlgeOUdgr1NhS7bQ7vyYoloEsIoh5yGO+AsBaOYX0fvdhG6GQTLO5P/sP3IrON4em3f0YMn0GHy+6h/p19zF8+qkENzuwhGjxBltp9jVw3elDCIh9eXerE020HktmDJWyjxe/nYVd+ZuxsQ60TfX0HRBJRbgaf7OHhI4Ag/AxTCrhmZCByGqR004biqGzxNyReDI9nm+bHLxW2UioWsX2sf1JNvQckMmM+deDTqJR0yXVFX7Q7xL1aqXU0REIPacv93xTwF0BJ2fWyzgMIstDBYLhGvSC0EW0z4sJ5ZG0OCK1Girb3TyQU8L9IVYcVe20FLayJEPHlnAN7kwbxhYP9m9KqXlkC4gCTo3AVWOMFBuU/+7CciW9oD0ocXOS0i9q31yN/esSOiIk2rIEauz1OCqbCYSqsOot2KpVZLzuQx8XgiAK+BtctBncWGf+PMXefwJ6yWovenGCcG7bRtVNN6OOiyXt668BqH/qaZzffw9A6VlngyQRdvVVBOobaFi9mdopd1CYGyShn5WsU1J+0/0TRIHwOBONFe3Hv4wgIJpMPXNWm5tRjx2DaDBgnjy5q900dkwXWdUkJ2M5WSGrJXNOIfyaq3Hv2kXc88/9qNuvafw4EFXEPvkEglpN/MIXKa+tpf7pZzo3LBHz8E8XuW9fpUiALbNmoU1MJP3bVV3Twq+8gvArr1COS6sl6c03KD/YTNnf9jJgYhy5neV+YvqcYASlF78u/B54Z65SBzSsD4gaxdk1JAEGna3IcGMUmRvJ42DoBfDdk7DjdQiJVepTAgT94G1XokQ7lyhS2v6nQ/kWOPgZ5LytOLJeuaLbEKm9Xsk1FVWKzBYUOenPxTlvwvbXIGM2oDjLHiZAZc0uXlqjyMnunZ3JDSel/W7OvZIngDO7Dn+dC6nDR7DDT8i0RPQDwo8aSDpque21qGx6tIkW1GF6JJcfb5mDQJMb09jYHyWfAbsXx6oyXLsautpEo5rYB8YcJU37VWCwKZHwzZ1FCTrJ6uFyDUMSrPgCEjllrZQ1Ozl1SHeHLfSInLJ4mwGL/vhKfNR5/dyYW0aC7GJ89BwyQwYwYvJc5OmP0ri1oCuINcGq58HCavRygH4OgZjBUcgJWrTZtQxvCbI3dDoX7p5A+6FDBJpcCCqR6NtHoA43cPDDXFzba3HntSA5fDiQWSQ+xqvTvuLRpPtwvV2MyqrFub0O5/buiI3tjDTM43rW8fb4g7y/o4In6xrxhGn5v2FpTAxVSFuFs52ZOfn4ZYlbWMQoNlJXJ6HThmM0prJ8+9+x6WyMH3YvZlNfdLpY2tqysdmy8GHg9q2Kd0GqXMTolidplz207BnBvjfXIklr0JvMuNsdaIB//vA8FhUQ2zeT8n17+O7tVznv4adpq6uhOGcbcRn9SdbrGbz+E94ZNIn9qVl8/s4CTB4n8lW3s1qrDCxU9xtGnc6EWQrwrNjB9WIYru2HurbxmVdk1o2PkLZkIWvffo05t9yJ2GlSJQgCXzsTWNlcxfy+8YRnf4kjKpqIpBTCI0dR9c0Bzrr/THw+H2q1msFmRYmzv91NrE6L1ToCAIdjL9nZZxIWNpGWlk2d61YzfNi7WK0jEMWj3eqL3V7SjT9t0Fbv9XPXoUoGmw28lGLj+gY3D5fUw6jTu+bZOuci3CFG2jpJzfySGibYzNimzaX52y+QAiLhpkv46uEbgVVHrN2GMUqH165FlsCW5iA2zkxk5TyaKsoxxMTg2F2NPdeJp+o8grKOcJ2V7C0fER8cgLbJgP3TYtJDhhMMk5HGh/CWKoqAR7n4Lx9n4tqESO7tE8OX64qw+8E3NAztXiUS2jEklLxILRE+Fy0JRrYG/AzJO0iNVkcwwUSiy35Monr4d7shMZLP6lv5c1rcUUT1t4IgCJw8J4Op5Q60SRZAID+/kUCkgUGRFoKyjNg532EkWgy8N1VJ+ZJHyXjyWwgPU3NuXikTtuVxX1I0M6KMqAISxqGR3O9po0wn88TeJvR4+CxGxz6bhflF1SSU1BPf0ELl/lLqLQ7qOlogp3v/bG4b9g4HB33tFFhriGuxIRkFWs1Oqpz1pK6s5bLLLvtdztWvDUE+IuT+n4isrCw5JyfnX8/Yi178DnDu2EHl1dcgB4MgCGR8vxlfWRllF1xIxE034q+uxv7Flxizsoh+9Q1aqh2sWnQAj1eg7+hoxp6R9rPqoJ4oDpfEmX5Ff/odZ/5r0cknYxg4kPgXX0T2+zk0eAgRt9xC5C0395gv0NxM4YSJ6DIySP1SqUxVfulluLKzATCOGUPSksU/2Rn+IdrXraPqxpsACL3sUmIefPBH53UfOEjdI48gI5P62Wc/Ot+R2LSsgIOba7jmL5NoWLkBX6uDlMvPPO796wVK/mR1DjhqwByt5GTGDVfySUEhjO11PQ2A3K1QuAbaa5QakSqtIueN6AvvnaOYB13yaXeEsrMEyY9CluGf1yulZM5/D8wx8MkV4KgCvRU8dmRZg9NwEYKzHL24E5XQOWhz4UcKmdzzAXx5K1jjFfMbd5vi0ntPMZgiaOrwct3SHMqaXfSJMHHJ2CTGpUYQY/3pjqUsyXhymxHNGvZ6vMxbovwfksONlDe7uGVqOnefnPmT6/ilcB9owlvmUORkahFXToVfAKQAACAASURBVD1BuxfRqEZl1RHs8CG1+7Gdlop5QreyIOj0I6gERL2aQIuHti+L8Rxq6ZpuGBSOp8iO3JkDap6cgG1ON7mXJRl/nRPH6vKu5UxjY9FEmwg0uuj4vobIG4Yc03X0V0FHI/xthFK7NvMUuPDDrklOb4DRT61heFIom4uaePqswVw0RpGbNrZ7GfWUYpCU/dAMIi06pfTLzsUw5HzQHz2g5ZUkztpdRF6HG73fSatK6VC/PSiFPQ4Xf63oJukDm+6lXHcGHZYJPHDQw41XDuOmzbdwsHofZ7ddyNKBk4lQqfmoUkBr1dM4KJR/ljSxJreewoYOZun0zI+LZJk2wF/ya8lAZNmYdFy7GxGNaqLvGIm7tgO1ICAa1EhOP9pEC4JapNjl4bF1hUS4JHJKm6lscSMLEEwyYzFrWH9eFs+X1fFep4zyRc1zDAuLJyXlFgoKn6C5eSNl9nie3H4PUWaJbQ+eihQMsvfb5dQW5uNzuwgGAmzLHImvw0HKmk9QqYPIkkBUUj8SBgxGpdbQUl1JW0Mdg6bMJCxOueaMVhvLHrsfURTJnDCZ6kMHaaooQ1SpkIJBTLZQLn32r5hsoUjBIP+XvZM/ubXEu9sxmC0UBWG01cSUMAtLqpsYajGyutmBWSWiQmaeu5X65iYSdVoKNHrWWyIRJJm46hJOb6/nunnzcJlCuCevjA63mxJHB5uHJvP1wgXoI6OxDRvDsEEDqdm/m8SRY3nr7bfR6XQMHTuOSw740IRquWF4Evf1icHna0AUDZSW/Y3yivd4/9AFXDVlGiNT4mkS4/l7RQMnhVqYG9Utv3yrqpGHCqt5a1AKCXot6QYdJnXPwR9Zlrl0fymbW9tZMyqTdKMeZzDIO9XNvFvThAC0BYK0+BUZqEEUyTTp2dPerY562uCndeHjGK02XHZFCn/+YwswWkNx2Vspyt6GRq/HZA0lLrM/EUnJ7FnwKVGO7j6DX/KhEbWgFiBwDL4wwkjCvJG8V9PM3fmV3JwUxa1JUTx8oIJ/bq1AXeOCgIxk0XDThYP5a045skogsyWfk9f/E23Ajys+mYKZ57JWbyOIQKJey6dD+pBk+u9M05Flma1VtTxd00aOy4dBFEjVqGj0+WmQBc5sbyFxzxb8knK/9Ysqlo6bTUpzHdMO7USFQFRUFIOGDCYzMxODwcD+/fvJyspCo9Gwf/9+Nm/eTGNjIxqNBovFgs/n49JLLyUy8sRzY39PCIKwU5blrKPae8lqL3px/Ki69U+49uwm4tpruyOBgCo8nLRVqxDUKmpWfo9t1FDWLKugukB5QJz3QBZRyb9fJC8YlPjqr3uoLbIz99ahJPbrJgDBgMTub8sJizWTOrz7xlV+6WXIkkTK++/hb2ig6KTJxDz6CKEXXnjU+tvXrUM/cGCXXFdyOik+dS6BujpSln2EYejQE9pfWZYpm3c+nv37scyZTcLChcecr+W996mfPx8A27x5xD7x+DHn8zj97F9fhafDj7vdR9GuRtJHRDLrmkEntF+9OAJf39kttTwMaxKc84ZS93HJXGguhHG3QEg89J2l5J3W7Dp6XWqDYkx02suK2+6JwO+BJacqxBnAlqzIMB01+HK20ey9jaDcGVkSIfKCUHRfzoA+k8CaqByDIUzJLa3ZrRDqkVfCaS8hyzJ/W1vEi6sLGJJgxe72U97sQq8R+fTG8QyMU8hWIChR5/AQZ1Xqm3rL7HgKWmlfWwlAUCXwStDNSnxERpg4NyuBqyf2Qaf+9aSwckCi5aNDBJrc6NJsyEEZ57ZaEAUlRzAoI1o0hF/cv4skyv4gDa/uxV/rRB1tBElGNGrwVThAVgxGgg4vIGA9OQVdXxvuA020r68CUSDiigE4d9Th3tdE6LkZGEdG4S1so+XjfKQOP6JRjWl0DKZRMajDlY5msMNH7XzFhCji2sHo046dM+VvdNH6f4WIehX6/uEIGUbWtm5kWOQwEkMSj7lMD7jb4P+uUq6Lc9/uHgABHvhsHx/+P3vnGRhHda/938z2vtpVt7psy7ItuTdccAPjAqaXYCDUQBqBQAohN3ADgUAISSBAAqGGjk01BhvbuHdbtqpVrd5X2/vOvB9GyAibcgm5Se7r55O0O3PmzJnZmX99nr3KtXnm29OGNAhlWeaxjxtYUZpBrnOQ4K3uI3jxAuWeOueREw6zusvF96pbeML7PisO/Y66s59iia+Q6KAtNVqop7fjKQQpTI5axyP6e2iojiKaW6ie3cNT5U9h0Vp4YN4D9KnHcWNVMw+MzuKCZDuzf7sJfzjOjHwHnnCMLk+E8yeP4K9bj2t5bsKCLsPEYxlqjvYHONzm5lvTc/ivs8eh+lTG/pbyY7z5okJ0J1g0RLNN6Oq9EJOQZLBnmenTCkg2DaOjPpJ8JlpdIZ5YNZkpuUmEoz6ueno3e5uVCoHSLBu3ZXSy77XnkAFN/nisMS+uNoV7YMryczElOdCbzYybtwhR9cX3em/LMXavfoXGA3uJx6IYbXYcI7LInziViUuWo9Ufd1T6onHG76gAoNik59qsFJY7rDzwfg1bjvYQSUj0GEViEx2M31+F2htDb7KQrfLQ7BfI1fezc9xk2q0O9NEI4zqbqE3NxmdQrvmYuiOct+Nd/PZUYknKOzEnJ4eFCxfy1LMvcCSeQZ5Dj9rdyppoKQCR6cm8OnsM89Js+MIxttT2sru+mb/vVZz/t2+ew3ebO2gIRUjXajhw2lhUgwHc+XtrqAmEh85vgsVAXzROqlbD6Q4LFrWKXzcoFUC/HjmC67NT8Hq9WCyWYUFgWZaRUGJ4gqAUaDeHo7iicZYfrGNZio3vJTysX7eWNneAX9x6K+kpTlZ3D/DH5m4uzXDynawU1J+6b7r6fKx58UN8FYexRTvROdRMW34h4xYtwl3bjueZWtQmHRm3ToeEhMqqozkUYeG+o4xTa5nUG6fdHWZbXS+xhETcqkGISCSPtrP3shmM+PgwAK8VJpPn7SfgcTN6xmmo1Brqg2H+0trL+WlJzLKbv/D++aqQZXlozT7xdwRBwOPxoFarMZn+d2XrJEli3bp17Nu3DxlocabTl55Nh0qLIRom1TfAuI4mVLLMqlWrMBgMJIUN/Ly1nVflBKfp1SzOcNIQjrEsxU5EkpCBWXYzjs+QoEmShCAI/6PEwb8ap5zVUziFfxByNErtrNOwLl+O/aKLOHbRRVSNuQJ92EX64pm4nMW01wwQ8ESHCFQAcsc7WfH9/5nz9k0gEoyx5ncHcXUEKF2YxdyLlR6Uii1tbHm5FlElcO1Dc4mGlMis5947CZWVMfKjDYRramg69zxG/PGPWJec+dWO19REuKIC29nDxe4lSaZ+fzeNZb3MvWQ0oihgGKTbr9zWjiAIjJ2TiRQI0HL9DcixGPmvv3bC+L6NG2n7/g+GFtZ5042k3nzzSedy8MNmdr3ZgNagRmtQkTnSzrzLitAZTnU+fC1svg+23K/0B447D169XHH8+ush9hltXlGj9J1+grPuh4mXK5lXKQYtuxVZFlMKLP7V15uPrwseGsxS3lKFpEklWNGH+50GiMtYp4Ju+gR6/3IEy9wR2AZ+AUfXAiCPvwzO/hOCTosUjhE5XMfRAyE6YxJ/l8Ls6PYyOs3M+ltOR5Jkttb1ctvrR1CJcMeyYrIdRp7c2si6ii5+c14Jl4xLH3LG9MUOTDMyaFx9FJsvDhoR05Q0zLMz0aScvKTt05Al+YQ+w08j1hNENKqJtvlxr6kj4R2UYhnMeugKbCRfMx5BLSqGmcwJ4wWP9OJ6pQb9qCRQiSRcIXQjk5RxW32orFosC3KGkfJEOwPIkTi6PBtyTKLr4QMkXGFEixbJF0WdYsAwPllxUh0nZqB7nyonUu9GNGuwnZWHyqpDN8pOvC9EuHmAkLuFgYNNSKoeYjoBkzsVVcjBXn0dGzMb+f0V92DSfvn68fb34dALyj3402MKCRZQ1urm3D8rbRofXZvPyCTN50sAbboXtj4AQM+qdey3jSVVqybkijAnz8FPa9t4s6ufms0LUM37MfH5P2Pyth30SDbmWAXcTbfTHejkgv7FXNt7HoIs0Obs4/rU/wLgglEXcNdpdwGK8Xx+WT1HA2FuxsR971Xzx6un8qu+PhYHRN7YpDipV8zMpSTLxk/eOMILMwt5weNjfXXPsGkvLk7j/gtKsBm1tIajnL/2MO4DvRRPSWfc+BTS9VrOT7WTZ9Bx3dpyNu1oHbb/hGw7dd0+gtEE40dY6XCHcQWi3L6kiG6Xl+f3dTLGV8MCRwjb/Au5f0MD4zMtjG9az4qZxcy55HIaev0canEzMdvGyFSlzLi/vx+/309qaio+nw+r1cor67bQ2N7Lr266jEQ0QktlOSOKijFYrCQSCZq6Bvjua5X8euV4ZhQoZITpm8sYZdSxbUYxsixz4/P7WF/dy+IxTtz+MPvaAhhVMYIJDWadimhCJhpXyKacRjUzbB4MGTbet1pxa3XIwvGS9JWVOxjTVIPHohxr2qzZ7Nu1A5VKzYboSFpiFj4PORaRQEyiPzz8c7VNS3RWKhfYDbw8EOTm3DR+kp9OuS/EWQdqmS3EyI2H6UtKYb03jEUlkqcWqIzEkQYZqcbEQzycYsDV38+2bdsoLCykqKiI3NxcUlNTv9AJWbC2jGqtBGoRwRtFu6sXg1nDlAU5bIyGSQlKuLoCFOt15Moi187Kw6rX8K0nd+MdrKAYn6rn3VsWDjuOFE0oQS698i7ticS4qryJumCYlX2wem8r+ckmZo90csPcQkJ6kTJvkIlWIxmJKGvbusjNyBwi8AKIxWL4fD4cDgfRaBSNRkNfXx+xWIykpCRqamooLCzEav3ygH9nZyebNm1Cq9XS1dWFy+VCr9eTmZmJ2+2mv7//+DVSq7nuuutITz8uXxePx/H5fAQCATIyMlB9SdDlZJBlmUQigSRJHD16lI4OJfAgCALd3d00NDQwbdo08vPzaWlp4cCBA1gsFlatWoXZbGb9+vXk5uZSUlJyfI0kmWfae7mvsYuQdKJ0zmUZDh4eo1SM+OIJLGoVb3UPEJQkFjusHPGHGG3UkfO/VDL9dXHKWT2FU/gHEWlqonHpMjLuvw/rWWfRfO11vG+5Zuh7vVlDNBTHaNUyZlYG3ce8jJ83gqwxSWj1/xonyecK8+KvdiPFJW740+moNSo2PltFzW6lx6lwUgrNVS50BjWLk3bjf/F5ig6XEdi+ndbrbyD37y9gnHrCc+MrI+CJ8N6jh+lrVcieDFYtsXCcVb+eRXeTl3VPlAOw9MYSCiam0Pmru/CuXcvIjR+hsh0vGYzU13Ps4kvQFhQQrqoCSSLtzjtxrLr8hGPGIgnW/O4Aoihw0c+nfe25/38HWYa+WmjcopT4GuygNSslvBv/GyauUjJNoqgQy2gMSjarcTN0V8GYZUpZsCwrDKmNm0GtV1h2RRUJb4RoRwC1U/+VHLdPEKroI1TZD6KgsJt+oknnaYOgi2BXOq7VdRCXUKcYsK0oQD86STEMHjmE5I9hmp6CabREtFfFwPtdyJEEKrtOEar/1CvQLcgcmOxgwswsJn6KRfKdwx3c8moZCWn4+3JMuoUHZubjeOsYABl3zEBl1XL32xUc2t/B06V5BMt6QJIxz81CCsYQ1CLx/hDGiakYJ6UiiAJSOE7fM5XE+4IkX1eKNuPEaH+0w0/Pn8uUfxIy6jQjtqX56EfaQSWABIh8pSi6HJcQ1F+/f9T9TgP+nR3oRtkxjHVinJDyhZqCALGuAD1PHEEOx5GR6BnzIoHkI8QMfSAo6zoQtnKwZwKRhI5oXEtT2+lUxAw4RImrxo3g5ssnf/HEPuVoctkrULRUOV9ZZukft9He1U25fpDp+YYtcPA5WHz38HLfZ1fQ4Q4T0cDSgl8RqIggm9SoWwLo8o14RtmZoXFxX+uVhPMm40LF9Z7zCelLsXf9F5ZwB48l/5b03Vp0uTbMszJwZYS4adv3GOMYwz1z7kGnOm4wVvlDLN53lBEVHvRhidjcNI6Foiw0GOnf1cVFg1n5D2t7uPEZxRbSqAR+etYY7llbDcBdZ4/l7veqkGXQpRrwTEhCc9iFzZ/gyJ1nnNAjLckyC9fsoaXdg6EvRprVzEe3ns6eJhevH2jlSJuH0WlmLpicxcIxqbz9u3t5uVFij+04E3e2w4BKEDg2KP8zwm6g3R0CIN2q47picLfW4Xd1I8nQkHASRoNRiLItphAT/jCzidOmT8VsNrNmzRqkQSN8VyyXo4lUCq0y9yxwEo/HqenqJt2RwocV3ezt09AT0zJZ3UqpuouYLLI2OpaAYOD2s8Zw/dwCdjb08+PXDnPZ9Bw+ru3hUItS5XTn8mLOSA7x1rN/5b6zrgbgqt0fYoiEsCYl4y+YzzM7mymyShgDHRyMZ3Hn8mKSzTpe3tvClBSBjEQ3bw4I7AuZUXWGMAkRMtLDuEak0mF3oi3vR+yOkGQIMzLWw8DEfCqc6YxXyVhEgf2RBKt2rsMgS/hVGmrGTWFkQxVWn5uISk2PNYlkvwezKJCIRIbWXK/XEw4rXrHdbmfOnDlM/cz7WZZl3j3SyQ9fPkQi08DSaVns+LCJwKADCpCebkIMJ+hwK2PJwtBPkAybnvsvKGVfk4tHN9fz3fmF3L6k6KTPld5ojNP31uCLxFnmFvnoQDsrJ2by+4snDtsuHo+zZcsWdu3aRTweZ/78+UycOJFDhw5RUVHBwMAAkiSh1WqJRqPDzvMTGAwGVq1axYgRx9sXZFmmpaWFuro67HY7DQ0N1NTU8Gm/ZtasWfh8PioqKtBqtcycOXMo27hlyxYcDgfLly8nLy+PqqqqYfdhUlISkiRRUFCAwWDAbDYzceJEDAbD0HpIksSuXbvo6uoiGo1iMpmoq6vD5zvOGSIIAmq1GlmWEUWRBQsWDM0DIBKJIMsyev0Xt5oA7HX7uaq8iVSdhhuzUyi1GLm/sZMjviAHTxvHvQ2dPNbaw9kpdt7vc3/CcQfA0mQbz5T8e8v1nXJWT+EU/kEEDx2i+bJvkf3Xv2CeNw//QJjnfr4TUS2w/LulZBc7kCWZeEz6lzmnJ0PDwR4++GsFqblKdNjnCpOaZyUSiNHV6MWZZaa/zc/0Qhfmv/2SUbt20vn6Wgb+9HvGbtmA2vn1BKuj4ThrHjyApy/MglVFHP6olZ5m5QFuTtLhHzj+Ek7Lt3LBT6YQLi/n2GXfwnnNNaT++FZCZWUcu1QpQ1Y5neS/8TqNZ5+D5Pcz4uHfY126dNgxw4EYr927D58rzIJVYxg7ZzjRyCl8DmKhwdLaAyf/fsQUuHaDQkj0NdH91EE8/QeI6fsxmLJImjQR7RgDxxqeQPDqUfksGMPFWHTjME1JA1nJJLperkE0apATMnI4jvOKYlRJerSZZuL9IboePoA224J9eQGaEeZhRtXA2/UEdnUOm4faqafPpqGvP0TJxHQSqQaue72M88eksaQnTsIbJeOn01ANZv+lcJxw7QDeI71EInGafWE6u/yMN+i4M+QjA5E7MBC6uphfba0nEIlzuM1Dpk3Pzp8vIuGL0v9iNdFjXkBhnRR1KhLeKKJFgzbLQqwzQML9KaO0KAndyCSCB7tJ+KMIGhWJgTCCXo1pciqiWYNlbtY/5HD+I0j4ooTK+zDNPJFx9vPQ1vYioWAbec4f0vbRWzSm3InXk47flIZLVNM1oGJr/aW0e44/O1VCgqXpbTT0J1EdtfKHRaM594zjGdG1ZbWUZKeR4xwMbO17SpGwAYV0aflDQzWS68o76dnyV67qGyRiEtUK4/SFzyiEXoAcdHHkgYWsDN+LaaSJmDFO9IhyXT4x6M3OEHbZzfKsD9jXvYgjPZlMK36Zg8YM/nv8LOYcGI1c7kNl15FyXQnqryCPdffRNp5+7giJLCOMtTPRYqQ2GOaDnL10tD2L0ZDL3d5rOfyB4gyuu3kuxRlWajr78PvradQauWWrD02l4pBlppro7gty2fQc7jl3eOuDLMtEot30DBxkb9UvmVn8BLVb64m6upHicXQmMznjSrFnZKI3mdn20rNUb/+YScvP433DVLbX9aHTiNx6xmiyk4yc//hOAMbZ4hQ7RLp6etgeUDJVakFmYZ6ecEJga8tnUo/AQoeHrEAtUdS0JOxMToriKCzl3j0RzKoEnriKMzRHsQphemUzxxIOWqQkMvRxilQ9XH16EVIiQVZWFjk5OQgqzRCx1ifnKggCsixzsGWA7790iOwkI7+/ZALvHenkmZ2VaEZIfE/0kVs8gT/t97O7aYCJ2XZaXEFcAaVyofq/z8LwGUKxhCwzd3c1TR0+rE4DHlkiVavmigwnM7vb+Mu+Xuo8At0BiTzRRWZWlG2jSompNUxydfLnSUWkpaWxb98+tm/fjtPpZPHixaSnpxOPx3l0Yy2pKU6WjTQSCQUpKChAEATcbjdVVVXs2bMHj8dL8shSmhIOjvlFtFoNrkCU2u7hSgDpVj0v3zCD03ZXI3aGGOuXqev2c/ncPDb2eBhdmsqWoz0k3FHmTsrgjvHZvNU5wPvr6uns9HPbmaP5/sLjv7vXu1yIwAd9Xj7s8zClNsihRhcXTcnizhVjsRmOB67i8TgbNmxgz549lJSU0NXVRW9v79D3hYWFpKenE4vFiMfjBINBampqyMrKYtasWfT39yOKInv27MHn8zF79mwWLFjAwMAAq1evpqur69OnyuTJkznjjDOoqalBq9UybpxCbtTT04PRaMRsPp7R3b59O5s3byaRSGC1WgkGgzidTmbMmIHf72fr1q3E43FUKhWCIBCPKw7/uHHjcDqddHd34/f7aW9vx263EwqFiEajjBo1iqysLFQqFSaTidLSUkTxm3tWJ2R5qKQc4NVOFzfXtJCsUdMXi5Ou1dAVVaqb7hudRbU/xASLkVKLgRLLVw8U/yvwec7qv49FfQqn8G+OhFsxBFR2JePi6VUMhxXfnUD2WKUnVFAJaFX/GgPy85Ay6KT2NPswWLWEA3GyxzjILnbQUTdA8exMnrxlK71ROwZRQ6i8nHcOZmKc9jNKBx1VWZYp29CKc4SJ7LGOr5S9aa7op789MJQ1dWSY8bvC7H6nkaAnwpyLRpE73kl77QAfv3iU5op+8kpL0RcVEa5Ueq0GXnl1aLwRDz6AJiNDyeyhOK+yJLP77Ua6Gj3MOq+QoDeKzxVmyfXjGTnli+Vv/n+DFE18vnzIvr8pjuqZ9ygENe/eDFnTkEsvJ9bSS6f5EN1bLkSVsGE1lmJNKsGqmYQ2xYJo1X7p/RBzB2m0/RfBguqhz5o8gFI9i5BQI+vi6KJ55G29C//W9qHtNOkmUm6agCBC18MH6X9BGcO2LJ/4gGIAOy8bg8p6YnmTdVEOQrKeup4ARTYDmjQjb7p83LG2CoArIhaWJ1k5QoIfn5aF02Sg55FDdN67B32xAzkhEz3mQY5KiCYNOpOaUREotJqQvVEezUqjOR4n3hXirGf2YDdpGTdCcZz6Bw1dlUVL8tXjCB3uQ1tgQ+3UI0clgge6iTS4ifUE0YwwY1tegNqpJ1TRR2BPJ+GjA6jTjGjSTYgGNZrJqRgnp520zPZ/GyqLFvNpXz0Q5PVVcLRWKYPt7H6DeKqPuKzljxHYfO5qenwRlvxhKwlJ5oVrJzMtz0FTywvU1D6MVecnEtfy4y2/5kcbaxlbms7oNAv13T1875U6zJpDPLQyxpKpq0D/qX7Yo+uU7P/OR2DOLSxdfBccbSbYLxLXGLHmzILGj6Hz8JCzunr3A9xlmw1hCNQHKLSGaEBxNpdlbUXTX8Q7/Wn4MfAX19WYhARmVYSmprO4n1TmBvMIV/WjnZFOysqRRBISbx1ooyDFxOScJD4Pmd0RBElmZWkmK8ekEUxI3FjVzPb23RQgMxCLsD9hRkOI2WNScCSpebPsXiyup3mZK1krrCQ/o4MsdLS0aTAhcE6pjXNHbSUUsqPXZxCNDaBRW+nueZ+qKsWhd6Di0Gvrqd25C7MzGVEU8fb2UPbheyfMcfy8BUyw2Hi1dwcGg4GOXTWU97soUmWSKw6QTwS1V83IFCvZySHGFY+hvE9izaE2YgmZcydmcu95JdR2+3i/vJMttb1s6gaHcRZSIo47Dn2Cifo9ARwmHatvmsWlf93NBs9wUrLr5uRz54qxX+m+++S5JAgCU3IdnDk2jed2NTPnt5sHt1CBR0X34hk8tK4ZTyjG7y+ewPmTswhG4/x2XQ05TtMJjiqAShA4M8XGE+EoDr2at8bnUzzIFkxBBnNnKX8+tP4oj2yqJ0c0cW1UR1Uizo+mT6c7CvlGI/Pnz2fu3LnK2ofivFfRSVWHlxf29wF9rMu2c+PpBdgCMVIsOpKSkpg9ezbTp0/n0j+t50AlCPhJEoLYrBYMej1nZwQR+hvZTAl2s55nr55OfrKZd+aOpTEY4ZIMB6FoAoNWxb2D59MxLocVB+vYHA6xeb/CXk6JFU08zpPbm7jytDxua2inPxpnh/u4M3yN3cZLjW3csng0Ny8eXlo/MDDAY489RiwWY8qUKZx99tnE43HKy8vp7+9n0qRJOD8TDJckie7ubtLS0oY5eJMnT2bDhg3s2LGDI0eOEAwG0ev1nH322YwZM4Y9e/ZQXFxMRoZCDjVp0qRh46aeRA5vzpw5zJgxg5qaGsrKyohGo6xYsYK0NIU0cO7cucPebTt27GDDhg1UVlYiCALJycnEYjGmT5/O0qVLSSQSRKNRjMZ/rkOo+sz79vy0JKoDId7v9fCrnExuzE7h3V4P9cEw3878Yub3/xScclZP4f8cYt3daNI+X8f06yLhVoS5P+usWlP+vRnrLJ8ybhddWUxWcRKqQYfakamUG1qdeppag3im3ox0/6OQcyNBXTIddQOk5dnwucLsXKPoxuWWOFl6Y8nQGJ8HT49SHvaJI5+cZSY5y0zmaDuiKKDWqpTSYZvTBQAAIABJREFUl1iCg04de95pJHecE92oUQR27QIYclptF5yP6bTTgOMGiNrppHJ7Bwc/VKQT3n74EMnZZgRRIK/k62WD/90gheIKm6tpkARHJaLLsSDHJFS2E50zWZZBUoImQ5/FEnjWHcO/uxPzrAx0o5IIHe4FlaCU46oFIluTScQfw2I6E4PViXzxmwy8VU/oT93ERReNcx9BVkXRhNNwi9tgMFlpKCtCIzkxagqJCO2oRCNjJv0alUkLArjfbkBIEjkWe4igs5qCjNtIzTmTULAN18FDRNp7cUiLSV4ykQbfb+nkdYzXmtCHsokm+pEjMdzObRxtfB2LZTyWiyYS/DBO4lgcz/uK5IyhNPmkjiqAyqzlCa+fJ/Y0cPuSInITau77qJbp+Q4KU0y8sLuZ1gHlPh2dZkZj1SvkRDJEW3yIJkUQ3lCSjC7XOiyT6dvWjmdtIzlAj04kSaPj79dNZ0y6lVf3tZBmPf67E3UK8dAnEHQqzKdlntTh02aasczPJuGOoE4x/EcYGuF4mL9V/I0cSw4LcxZi0gwvY/a4lYx9bs4NxOM+ZDnBY01HGOXIRBAE3inrwB2M8dGt84Z6HYvyr8RhysRkzqMn0Mq1vY/xaPk1VB47SmHyOF76+ElgIiohwd0fRHE42vj9JiNPyTpMRqOie7tzkCBp+8Ow+C5o2cPSvDy8Ihy6/HX4yzzoOjI0z6c7PsYQvRKvQUWOqZOGvlQcehd3zniIDH8BOT25VCISQ+IsdJwniDybHOLVrhRuQeaq6g6O2FXUH27kJ+kaHv6oDlcgyph0Cx/8aB4ACUnGG4qRZNJS1eHltx/UsKW2l+n5Du4dZSXi66UjcgAo4o3wZP5YMI0dmgtI1LaRWJBBRnYSC/aU40ks4WL6WSus5MKkEJfH3yAo7ocRMH36WhoaHqS/+2N2dj/EJ9qoTufpqFQmNBon6enn0NfUx6Gdu5h3+dVMO+cCAALuAdprKpFlmYB7AHN6JrvLq9i0ey89PT24XC4EQSAjI4PJkyeR1dPD1KlnMn78ycnrfrGimD5fhDynCVEUmJSTxKScJH5ylsT6ym7WlnewqaYHkDjmCnH5jFx+fOZo7EYta384lxd2NfPnj+uH+k8vnZ7zte/TsZlKufdZ49L5+bIx/Pe7VWys6eEPH9UxLtPKC9fOoDhD2caoVXP3yi8m5Lsi08leT4BHi3MpMJ78GXTT/EIONA+wrbGfrccUabhvfaw8QM+ZkMmEbDvxhMS+YwNsre0lmlDOc2yGlWvm5HPP2ipu/PtBJmbbmVHgIJ6QmZaXhDsY40AvXD83n4tLktiyfi1tbVUQAa1Wi2gUWRE6wMyxU9BF3FRVtWCQJGxtbawrk7FarYwePZqkpCTUajWZei2vjc3m+UPlBFLSuSF/BOv7PNzniuLZ38fM32zEm6YnXmBBY1CzZtJIuiIxqg52IQpwwaR0+vr6GBgYwGKxIEkSa9euJRaLsWzZsqFyZbVafYIj+WmIojjkcH4aRqORlStXUlRURFlZGSaTiXnz5mEbbBdauHDhF16rz4NGo6GkpGRYf+gn+Oyzd/bs2cycOZOWlhbS09MxGIbbfmq1GrX6f9+t0ogCd40cwV0jj5dIn5N6ciK7/1ScKgM+hf9T8K5fT/sPbybjvvuwn/f1pUliXV0E9+3DNGcO6iQlIt7/9DP0PPAAo/fuQWW1sve9Jva918SNf57/pY7bvxptNS72rT3Gih9MQHOSKPGTt2wlGlJKXJz95fQ7jz+4VRqRREx5gY6enkbt3m4KJqZgTzPScKiHqUvzGDPrxJfLhmcq6ah1c9V9s086J1mWcb/TQGBXJ5HJqXywScmmTc7uw/7Cr8j+21O0XnsdqbffhvPaa4f2a/721QR37yb34228+Xg9Wr2KZd8t5aNnqmirGcCZZebSO6d//cX6FyPhjRCqcRGuGSDS4EaOJE66nTrViL7YgXVBNoGtVUSOdhEfkElEtBgKQS23EwtYiXidSH4JVCh9jTIIapAl5f+wuZWB3A9RJTRofXkYQ2NAHycst5CWt4IO+Xl6rK9T3PdXMi5YSLC7lbpjv6E/vAG9kEsiHiSmOl7WZWudjyBpSGpdhCRG6R73DGFbEyN01zBm9i+GncOn2Rl7ej6gvEKRSbJaJ+D1Hh7aThB1yJJSjqnTpTO++E/IH1uJdHhQLYtyrP93ZGZeTGbmJQiCwN4mF2+XtVPW6qaywzvsmAaNitdvnMWoNDPn/XknVZ1eitIsfPAjJYoe7QwgiKBJ+3KWyHhfiLg7gjpJh8qh/49wLL9pyLLM3bvuZnXdagD0Kj2LchdRlFREjjWHhdkLqam5g96+j5g7Zy+CINDp72T5m8tZVbyKW6feyg9fPsT+Y/28fv4I/K4+fP19NJUdoLPuKHO/dRUlC5dwzys/5dnKRdwwtp0z8gJc91EaVp2PSyUDDwaOB6fOzW/HZOzhnoYH8ZnVWPxxhNSxcNNOIvekMjVHCRqUX1UOb39PycDe3kDYHWDnn9bwI8nAQJKTX458gtcq5pBh6uYHzkY6iiawLJRBz3sFQ8dKv30qlcEIKwfJm2Ao1gEoPc3jMm2sPtjGrp8vJM2i57rn93OwZYDXvzOL5Y9sx6BR8b0FhVw4LokNf1+JrbAbjTHB3Yl7qFUXs0zlY09QhVYdJyJGcQnJpMpdREUrbtmIVU6wc3wWscR2qqp/MuzaZGZcjFpjQxR1RCJddHa+ocwxWEKa5QdseuYvZI4ew/k/v/uk964kSbz55puUl5fjcDgwGAzMmDGDkpKSb/Re/3S57ueN++TWRvKSTZwx9usHosOxBB9UdLGiNAO1SiQQidPUF6Cmy8fKiZlo/onv8YQk0+uLsL/ZxfrKbjZWd5OQZcKx42Q53z4tjwsmZ5GfYsKkVUpPe7xhrn1uP+XtSrBcpxaJDDruMwscvHTdTERRIJFIcPToUVpaWpg9ezYbN26krKzshHmIooharSYaHaz8UKnIyMggFosxMDBANBolNzeXKVOm0NTUxPN6B2URA1k9UY41DGBLM/LghaUUhAfYU93Cb/aESFMHOZ3KE45lMBhYtmzZSR3BUziFk+FUz+op/J9H3OWiccXZJFwudKNGkvfaa4iGL896ho/WEjp0CNOcOQBoUlM4tuoKwkeOoM7MIO222wgeKiNSXU3w0CHGVJQjCALbXqulemcnN/zh9G/+ZIIupTytcg20HYDis+H0n/xDPYNfhB2r6ynb0II5SUfU7UcT6OP0G2chGyx01Lk5vKkVh0nN8hV5VPeG2b+pbdj+1z40F71J6VORJZmtr9RSsbUdW6qBb90xjXCNi3C9GzmaQNSr0ebbCNe4hjJ82iwLG3tCuDqVLNf8A79E9CkSAIY/v4IHB56eID0tPuauyEQ6VsvHBwwMdAVZemMJ+aXJyJJM1Y4OLA49OeP+czKroYo+Yl1KxD1yzEukwa3IiCTp0I4woxmh6CZqs8z4d3UQrnVjnp1JtMVLpN49ZBmrhVZUQi8xKRcJ5fxVdKPWDGCxbEQXWEd83K3EtaPQH7oZrKkkrtnI7kMridB30rmJohZJimINT2XS7OdRD2ZzJSmO31+FxaIYrd6qRkRB5HD/VYSjHQiyiCwowQ+12kpx8f2kpiz5wnWIRl3s2buUaLQPgyGPiDiVqu4EHzeXUt6TzJy8AHmGjczK3AlSkNGj/4v6+geRpOFsxLX+JTy0ewV6jYriDAtJRi3fOb2AYDRBikVHhs0w1FNV3+Pnoid28tOzxvxDGZv/n/Fi9Ys8uPc+bhqzgnE6H62eOlq9x4jIAvm6BANCBkVaD20Rib2qOfzYdhVrHv8tveYgF156C1qfzA1bQtiD3SztfH9oXI1Oj6hSEQkGMFhtZM07jVursjgrtQqToZdXjy3irum/Z8zBH3CTEGUgdjy4ICCxZtSPcOVDYVOAPGESrFrNvt/n8Z3MVETgnXPf5cMd32d55W56FlyEXJZHJObmomNziBVaeS6pH9H43xiCBfzQ30xIiPCz8d/h7Df380iSnYyxo7lm6XeRJJm717xBsvw0pYWLkbxP81rNGRzoW8BT3z4do1bNkj9sJTtJS56tjY8bh+scrr9lHiNTtGxetwQMrWik8YjhYjJzL+C82n66Hek4XT0sLVtNyYIatrCQy41tHH7bwjZHNpk9rYzqbGLyikXEUh/Gap2AwzEHm20yTsc8hEHW277WJiorf0owXEPjh6mEXXpElZqrfvfnIf1TgEAgQGtrK4lEgsrKSqqqqpg4cSLnnntKl/qbhizLDARjNPT6EQWYkntyjeleX4RbXyvj4qnZnDU+nZv+fpCPqrvZ9pMFZDtOXnIaDAZpbm7G7XZjt9ux2WyoVCrsdjs6nQ6fz0d1dTUdHR0MDAyg1+sxmUwkEgkOH1YChaIo0mJ18N4ExTbKaAowMCjHlyb4SCDgkfWcpatl5VylpFev1+P1eonH40yePPmE7OMpnMIX4ZSzegr/ZyEnEnjeeRfPW28RPHiQlO99l94//gnnd24g9Uc/+tz9pHCYjtt/gm/DhmGfawsKiDY2Yr/0ErzvvocUCAx9p3I6Gb1jOwAbn62i7ejA52YOvzJiYYj6obsC2g/CwDE4/AokFL1DnIWKRMiZ98Ks7ymCat8wJEkmHk2g1SuMdVIgiMp83Pjz1Q7gebEaBrN8cZOGaKYZrT+K2OFHtmjRTEih1hcn7I/RcLAHAZhX4iCpK4AckxCNakSjhnj/IAOrAJYF2agsWtxvN2CcNwJ/ro13HznMGZflYt3yEu6eAJtZghSXUWtEVFoRURSIRyVElcCS68eTXXzyF/x/AgJ7uxhYUzf0vzrFoLCrTkpBLdUjmJKh7CXY/RhojPhtZnSmAjSoQK0jUttJOJCPIMqYr7+GtsQBOmsfYWJkAep596HyVMBrVyoyHfEwtB8grhKoG5dNWHLjN6mI6lQU1/owFJyLdvbP8HgPkkgEEVDh91djtU4gNfUs1OrPl2/4BJIURxAEfL4aDu67DJO2iAkzHkerTcYTilHf40ejEshPNmHRDwY3ZJndjS42VHUzd1QyGTY1le1+Ht5YT9tAiDSrjlGpFnY39hOXZEbYJB5a/AoB3+6h4/6l6k5MQj2ril8hIYmsqV/BVVO9iIlOUlKW4HTOw2Y7eelZLCEhEqW75z0M+ixstkkIgoZEIoRaffLsaiIRIRhsJBrtIRb3YrWMx2jMJxzpQqdN+4/PsEqSNGTkfh4xSCAW4MnDj3K0+XnOscfRCnFAh0plJS7F6AuIdIRHEQgn2NI2m66AkyS5ifnHqgnpLHSkFBEQDTTFHXhFE+dZO7lkejZ9vgA5+QVkjBjBli1b6Gpvw+rtp7fiEC8VXUphUiNt/kzissRlrs3Up8RJk87m6cDwANUPJv6ViakVpESSKG3SwKrVvPbkNPxjjeTqJI7FzORp/CTiMiq1cr0O9ZTwaNn1REuSSE/cwv3Wm1nT8RY7TNVYtVYScoIX9cWc69vPbVNv46pxVw2uV4zDR67H5do2dHy12s6UyW9iNuewq6GfG57fgS+iYtaIRsyqFja0zEerkth5iwWvq4mmtnuQ/WNYdPY7CIISlNy+ZzeHmltYdfpc3rz/l2Qu2ko8pKb2rTxUooGFV38Hx4hsjmx4n6ptm5m8fAULrrxxaA4fv/A3vL3d+Pv76aw/CoAlOYVF19yI3myl/lgz1tQ0amtrEUURs9lMeXk5weDxANCcOXOYP3/+v6S88RROjnhCwhuO4zBp/ynjh8NhXC4XZrOZvXv38v7+gxhjUQIxNevjxejlCH7RRCQBV0xycNeF07+WxMspnMJnccpZPYVvHImYROX2DgomJmNO+teRfng/XE/7oN5m6k9+gvOaq2m66GJEo5Hc5579/P0++ID2H92C49pr0GRk0n3PPQBosrNJ+8UdWObPJ1xTQ7y3j9Dhw/Q9+igAxTUKwcv7jx/B2xfm0l9+jZJTSYLqd2DvX6Hj0IlalWNXwtRrIL0UDEnw/Epo2gLWLLDnwOWvD2kI/rMgxxIKwUyLj/6XahANKpLOG0Ws00+osp9oiw9E6EHAKAqY4hI7fHHCskzJGTlkdfiJtfrQFzuwzM9Gm21BEAXirjBSIIY6zYg42Lc6sLqO4P5uzAuyeeODFvInpbDoymL2rW1i73tNnPPDiaQX2vC7wrx0l8LKM+fiUUxYmP1PXYN/JoLlvbherEE3yo7zirEgyQiN6xDa90HFm+BpOb7xqCVIJidbzRuw+uJM6khFSMSR9Gbkcx6hM7SP9p41+AOKQZqWdg7jxz184kEr36Kl53Xq5N0YNRlYElacPpH0A9sQrnwbCuZ/Y+cXi3nwR9R4wvDMjiZe299GKHa8pLkozcIPFo3kya2NHG7znLC/QaPiySunMmdUMgDecIyDzQN8+5l9aMQot0//O1LCS96oP3BW6TgCkTg1DU/h7noQAKNxJLFYP7HYAACTJ72MSm3EaMgjFGomEu1FrTITjfbTdOxR/H6FdEmttiBJEXS6dGbN3IQgCEhSjN6+DXg9ZQQCdXi8h4nHj89ZpTIxauQd1Bz9BRbzOPLzv09KyplDzKvhUBtW6wRE8ThLZiwWY9u2bZSWlmK322lqaqKiooKSkhIKCwsRBIHeYC91A3V0B7upc9chyzJFjiJWFKxAFERcYRfJhuShMXd37mZf1z6+U/odtCotkUiEPXv2DOn+eTweDAYDra2tdHd3k0gkMJlMmEwmotEoFouFWCyG3+/H5/Nht9vJzs4mMzOTadOmoVKJ+HyVBMJ9fLj3dpI1Xgwa5ZoGAnYqKxbSGUrmSDyDZsmBzJc77U4xxCRtJyPk/hPicKIootFoSCQSmPvaectQSoeQTlTSkmx/m3N7DYQjIcyjx/Bydx5+SUVCVpyqM3M3kWLoY0XKMWbVdMOqNfz+laVMKFG+b/Zm8ceD3+H7k54k6M1mfdtUKn2KpIrqtBSmig9R1a/cE5ekXYKt0cZb2rewJFto8DRwV96tlOhGodUbyJ0wmdbKI+x5+0W6W8oQRJlRK48BEO0ZzZjxt3Kw7yk2NU1i7OFa9MZ6xMkyGmOcLKvCZhoPq5g+aSNJGSd/pkXDIf5y0+WYbMlMO+dCcsZPwJZ6vCT2wyf+RMXm9cy/8jpKF53FwQ/eZfvLzwGQnJ3L2NMXYc4bSU19A0ePHh0mDaLT6TCZTHi9XlJSUpg/fz42mw2LxYLJ9OXl8Kfwfxd+v5/169cPBa527NiBRqPh/Ktu5O97Wvn+wpEkm/+9tTtP4T8Hp5zVU/jGsf21Og5vakWrV3HaBSMpmpmOWvPPj67JkoTk96OyWpEiEVquvZbQgYMUvPcuukLF2Oj81V24X32VzN/9DtuK5Scdp+d3v6P/uecpOrAfUasl7nIhx+Oo7HZE7fCIZcLno/X6G9Dm55N5328AePOhgwCc9+Mv0f77BNEgrLsdWvcqf3vbwFEABQvAkQ+pY2HEZEVqwfiZbGEiBgefh7W3Kv/fsAUyJ554jG8AsizT+9dyok3HjXF1mpHkq8YNMZHKsky01Ydo1HBkfzf732pkgVWN8TMyFkkXjsY09ct7jOSERP8L1YRrXHQ5DZT3hvn2/bNZ/eABZBku+tnxZ9drv9lHb4uPy++eiT3t35uG/bMIHu4l2uYj4VWkP7QjzKR8p1Qh7tn1GHz4c2XD9FKYdAUE+5XMeslFBIKN7N5zJgCpKUux2afQ1fU2Pp+iVWuxlJCZcRHhSCfNzY9TXPxbHI45J2T6yit+gNd7mNmnbT0+sUF5j38UnZ4QZS1u2t0h9jQp2VJQdCFXThzB0vHpxCWZ+h4/qw+20dgbQCUK3H3OOFyBKL/fUIvdqOGNG08jz2lEfZIesg8ruzjYMsCr+1pxmDR8dMv8IR1Jj+cQ+w9cSEb6+Ywd+yDBYBN9fZtoaHwYV0hDvTuffFsHTr3SYxuK6/ng2EIOdE/htpleRmc4CIffw+vdB8Ds03ai1SZxqOwq3O69gAZZTifgt9PaZicSMSIKMuNLNiKKCWIxM6JgQKXuRaUyoVZbiEQUZyQlZQmlJY8BEI1GWb16NUePHj3pOp5xxhkcMh7imYpniEpKb5lDrUYrROmKiTh1TowBI6qQiiumXsGSSUt4s+5NVn+8mrgQp9hUzNykubS1tNHf3w8ofcGf6BhaLBaKi4tRq9UcPnyYeDxOQUEBgUAAlUqFXq/HZrPR2dlJc3MzohghObOL/KxaNJrjUkADA+l0txcgyzH21BXRYcyjQUxFK8cYF6ojJ9ZJskEkzW6l2lpEvLGMWEEhqamjWTZtNONzkjHr1LS0tPDyyy9jNptZtWoVbrebzs5OCgoKMJlMvPLKK7S1tXE4ksRBSXnGL7W/hs8ym4/GTsfiq+YtXw6v92/h2Y4Jw9by9PRDPOd/BFat4db3r2T5GOXzB/bcxlHP8NLvdEMP3ZE0UpbmsGlGHj/b9jOy5CxSm1NoaW1FUMlss29GHQ5xxv7jz7UlN97M5uf+is5oJrd0IhWbN6CzRSg+W41srB36abVtyyPcOYKFV99Iza5txKJuolILcdqwWkdzznef/LyflnK/+rzoTCbEk7SD9Le38uytNwGg0RuIhUOY0kcwYuFSPD4/fX19uAcZ7XNycsjLy8PhcOB0OklNTUWn031hz+gpnAKA1+slGo2SnJz85Rufwin8D3HKWT2FE+DqDJCUZiQel9jxRj2TzsjGlvLVjP9ETOJvt23DkWlClmRFFsWiYdl3S+ms89DX7qO/LcDIqalMXZr3jc6799E/0/fooxSu/5COn99B6MABVLfeS3/qBDRakeYKF06pi5TnfoooJ8j686NEjx3DccUVCJ9yQpu/fTWS10v+mtVfesyAJ4JWryYSjGGy6xAEgVd+vRdrsp5lN5V+8c6JmJIV3f4HaN4B2TNBTsD0G2Dcef+zPtSW3fD0Eli1BkYu+ur7nWxa/iiBfV3Eu4PIgDpJj3VhDtEOP72PD5LbCGCamYF9WT7C5wQivP0hXvjFLuwqgaljk8iamYEcjiMY1Jgm/8/IMHoeP0y4N8h7HSHGzhtB5bZ2ZizNZdLC7KHjh8Jx2qpdFM3MUM5hTxex7gC6fBsqi5ZQtQsEMIwfZHDVq/5pBlgiEUYQVMMyZsrnQTo738Yil9Lb9hGagVSMgSJCZS5AQq23oC0xY12cjdZkU/QhP/gZUkYpQs4shDm3gmm4MdDT8yHlFd/F6ZiH23OQREKRDxAELWOKfk1GxgWDWcAo+/afj9+vVAAYjYVkZlyAVptCUtIsDhy4GKttIiXjH/lG1+JIm5tL/rJ7WPYU4JbFo7lsejap1uHVF95wjJ+tPsLIFDO3nllEVYeXZX/axt3njOOq0/JOGF+WZTo7O8nIyEAQBMKxBAlJxqRTD9tmYGAXdvs0vCGJDUda8MRVrN5fRXX38XsgxeAh366nrFtDVFIcYhGJ8aouStUdOGxdTJi4ngHXApzJfiRpH/V1s+jsLEAU1RgMBqxWK7NmzSIej3PgwNPYkw7T2TGNeDyNUaNfwWDwEQxmYLctwmTux+1+HyH1dY722Qj1HMNVuYNpkyeg1qsJSAEOuQ9xzsxz2LxhM5GOCPuT9zPZPJ7TchvQiS7khMJ6XdNyHq5uNYnQ8fVsMbWgS+jIV2kxm13EYjr6vKlkpmQze9ZsMjJihMNH6fE3EDdMBm0yU9KnoBJUeAIejrnbWNu0m+I0J76Yl55gD3UDdRjUBqo6Olii9pCQzejlGPZ4FCmho7x2JPKI0/Hok9lUrzhBRqLMUbUz3+xmztln03hwL0Gvl4b9e4iGgogqFT947g3UmuG/F1AyzYIgnLTcNBwO88QTT3DULbAuPBKrFOBczSFemnM2fr3yzppW9UcKoim83T2cQyDf2szGyB2IFz7Ft/feQZZ6FtWB6ZS15PHpO9WY/0deOuvn/Lo/i7Ass3bKaLq7u3n88ccB0PR3Ebc6kEURVSiAWqtl/plnUfX2qwx0tCGr1Fz2y3vIKh7PkY0fYk5yUDB5Gq0N71N19Bb6KuyE20u56Jf3Yk0eLqPxaaKxT9aiuroao9FIZ2cnPT09BINBkpOTWTqoLd3f38/u3bvxeDwUFhYqOpzRMFteehadRoth1Fi27z+IIAikpqbicDgoKCggNzcXh8NxqmzzFE7hFP7tcEpn9f9zRIIxWqsHKJyUgiAK1O3vZv1TlUxdlodaK1K5tR2zXcvUZfmfO8aRzW0c2dzKrPMK6W32EYskmLosj9zxTtqODrDu8XJW/1aRKDDatOhNGva83UjBhJQhiZRvAgMvvghAw5lLEDQakn7zEG9/bCQeVYw5e5qRym4DxVfeR86mR2j73vcB6Hnwd2T/7SlUFgvho0cJ7tmD87rjLLOyJJNISKg1KmLRBC2V/bRWuWitduHtO14ydca1Yxk9LZ1IKIbO8JlS3GgQGjcrWVJHPlSsgXd+oPSk6qyw4g8w5aqvf/LGwb6sYP/XHwOIu8L0PV1BvC+EyqZDjicIBeKEyvuID4QRdCoyfjYd0fDljwir00BuiZPeFh/pFxdh+gekfCwLsok+W8nphVa2bG1HBWTUuujc2aFs8P/YO+9wuapy/3/2nj29nzOn95rk5CSH9AQCIQVC6EgRQZqgoF5URGwIKNi5XkF/dgQVpEgLPYDpvdeT03sv0/vMLr8/Jp4QAgh4Ue+95/M8eZ6cmbXXXnvNnj3rXe/7fl+dQNYVU6iZnUuizU9obS+p7hDoBOKHThQJiu3JePUQBUSzjrwvzUFn/+A5PpqmEAzuZ3DoaQz6LCLRNhKJAVQ1RTzeiyCImM1l2GxTMOvLCQ+0EkrtQTYEjndiAkFvQFueQkCPwZhNOuVD2C2Qn8xF87YRWJhHwjCCILyC6cg+srIWY7dNIxQ+TDB4YMI4nTEaAtgRAAAgAElEQVTjF4iiGVkOoKoyRuOJgi2iaGD2rMfx+bfiHV/P0PCztHf8+IQ2ldm3feB5+Hv85I1WbCaJJz6zkPJsC01DYSpzrCeUcHkrDpOeX149Z+LvukIHW7++jELnO7dvbGzkmWee4bzzzmPevHmY3rJ5kpJVIkmZoWCceHIKP35kDfvGNGQybfIMMjfMziM02EHjWIpgysqhIZEK3ThzcxWWLZ7Pcy0JXmkU6VbdXBzJFFR3Z61nU+98Xuv8DmeUeJi2OI+hpIHXmsbIwciyvApq8jKhkhs2bOC881ZQXl7OU0/l4PNqxGIp9u0dQZJsLFhk4OvPduKNZ74f+cYGmrwRGiOvItmbEcQUr21+DfRwrvVc5o3Po9y2D4PWiHesELvdgF6fYmrp86jFFpyOm0mmCtm6p5WyRBm5WVFqqp5DEDKGz0hax8ZEDvPFDg4dfv4tM/kHFA3u3KmnKWWhRJdgXfOniEemYdL7KLJ0oCWc+NQziCpW0qqBtrccrROSNJR20ayvIzGgohMzERg/vnQml80pnvByA5TWZ7ycLds38/IDP6LujOXvaKhCpoTEOzGQSPHL3nHaTz2b6lefoV4cpcE0Rk92ORGThU/4engiqwzRtIIp0iucW/EGDQUl/GDbNCDjPY+ZnFh9XaTMIo8dumKi7yvLLDzZE8MkBbFLcb7UbKDZEOXiY2UfDu7eBUClkOa0628gnEqyevXzyBYrOpOF1zdsxOApQXAXkFI1DnX1EhEksqfWk5WVRW9vL9n5S1js2Um/+zAl02cSisUJ9PZSWnrcqysIAolEgq6uLgYGBjh06BCh0HEVa6vVSjQapaOjg6ysLBKJBBs3bkRVVXQ6Ha2trRNtJUli0ey5bNu2jeLiYi655BKysv7n5vVPMskkk0x6Vv+Xomkae17tpm33CIlomng4s/iyOg3MXF7CkY0DhL0JJKMOURRIxWUqGjwneQljoRRmm56wL8Gjd20/rskPVDR4WPnpenTHag+u/eNRmrcPUzU7l3M+U49vMMoT9+5kxQ11TFmQj6Zq9Db5GO0OkVvmoKz+gyu2JkZ9vHTLw9gi/ZT1vk7ZH//IG1skRnvDLL6smsIaF+7BZ1n7p1bak6fy8azvMLQ6CsrJ5T+kwgKqXnoJ0WKBZJgtqwc4uGEQu10jJUsk4yp6vUpRjZNwUMU7kBFaqpmby9k31fO7L21k6qkFnH5FbabDjvWw5hsw1gSCCMXzoX83FMyEM+6AquWg/wdze2M++HEFnPNDWPjZd22mhFPE9o0gB5JoKRVjpRPrnIyX82+5kgDOVRXYlxQDEN03Quj1bszTPdhOK0TKPtHoTCSGCIcbcbsXnCS2oygqoiAgiP+YB1PTNAKr24nuHCbpNhFLKrhjacwNORgKbcQbx0kNRBBEAS2tgijg/lg1ljl5KP4k8lgM0WEEVUP2xlGCSWIHx0j3R/DcVI+p2v2+xhGP9zE8vJqx8TeJRttQj4VioomYhWL0ooyqOjF2TwFBIe0ZIWzejyam0SVc2JJTkMUREEPU2D4O1iQd8TcJK324YgbMuizw9yBL4HUbEHQG3NmLkfQuNDVNOu0nENyDeqxci8VSgSgaMZtLmTnjV+97PhUlyfDwc2iaitlcQjC4Dw2Nyoov/cPe5hcPDiIrKpfMKuLpPf189dlD3LqsmtvPnvKh+9Q0bWIB/lZUVeWZZ57h6NGjGAwGli5dyoIFC1BVlUvvf4mDQT28LT9yfo7KXI9KKjgKoRFkWcZisXDOOecwdepURkdHycnJwWg8nm+15sgQtzy2j5VTs1hcMc4ZFSnO+a2JY1WdTmJumZvFNR4KnWYun1tMx1gUk14k22oknEwTjKXJNak8+uijeMVDPNJ7EWe5D2B3VPB8rx1Nyzw7JR1U5Cn0BQ5zmr+LCyumEDWK5NU8jMO+GIN6PQNdTRhzv0cqrEcnOtFZM5szscF8cqtziMaPohMd2OSbyS530Dn4AFp6FIANYYkuKjirsIHi8DMnXMO2wXn8/sg1LCneSiDhpMlXi9vkp8zWj1WL4RJDFFrLmD7rUkSzje++cpR+f5x8h4mnb1lEnsNEtzdKbd57C3DFI2HMtr8v0vVW9gSjfGx/O7Km8bcCH3d0HSDc282W2acz5Mxme0MZZ76xnbjFxnWNzzNv3otk7b6DywIlKBroBIWnp95J5XCIFxv03L3hQQCswD1LrXx1fRSbYYDKciu7KqaTFwlwn9uA4Pdy+OAB5GiEL3/1a9jcGYNve89WSrPKKbAW0N3dzaFDhwgGg8TjccbGxlCO/dbk5OQwNpYJNy8oKGDmzJk0NjbS39+PKIrcfvvtE/mgmqbx1FNP0dzcjCAIVFRUkJeXx/bt27nsssuor68nHA7z29/+lnA4DEBJSQnLly+nrKwMn89Ha2srr7/++sTcTZs2jfPPP38y53SSSSb5H8NkGPD/MY5sGmDj4y0U1bpw5lnw9kdIJxUkvchoT+bHbuqpBTRvGwIBckrs+AajzD6njLrTCrG5jRxc28eWZ9ooqnWTTsiM9oa54hvzaNo6SOXsXIqnnLjwj4dTDLYFKK3PRm/QoaRVfvOFDdTOz9S1623yEQ9lFv2SUcc19y3C4nj/nq7AvkbevH89o846AJalV1P47W/w2PeaWLhExxzHS9CxFnyd+PQNPNH3bea5VnOK9gxh97VEjg4hebIxz5pNsrUV9xWXYgptgANPoIy28cjoIyQ1G1NM60lpZurMaykx7kcnqIRylrHXt4q4YmUwVMQn7zuV39++mXnL3cxf4Ybdv88UoLfmwIp7Muq9jc9D2Wmw6kdg/GCLtHdCk1XUaArxpwUIZ9wOy751chtFI9kRwP98G4o/iWCWQJSRk1HsDZUIkkDs4Dg6pwHrOVnYassRdH/faJHlKNu2LyGd9qPT2SguvoaSkusxGj6avJXo7mH8z7eDquFYUYpjRRkASjSN/y8t6FxGTHXZGMsdiMb39v7K43GG/3MP7strJwz29yKdDnLgwPWEwoew2aaSlbUYq6UGcVMhqYMJRE0PyICEUTqC5BRIJUvRrF60tEyWcR1G/4sn9asBab2AIa2BuzzzzzMFpXQeQt0liOKJ1yHLYUZHX8dsLsbhaECn+/cpAZCSVWq/9RoAWVYDwViKmjw7t59dy4pp76yGq6oqqqoiSRKKoiAIAl5/gMbDhxgdHcXr9eLz+dA0DYPBgKIoLF++HEEQ2LBhA9FolKqqKmKxGENDQ1RXV9MYd/BEh45y0UeeGGZYtdOjZnFhucDPbjl34tytra34/X5mzZqFwfDuzxxN0zj3Z1toGsp4tTw2I+ORJJ85o5KV0/MQBYHaPDvd3ihfe/YQRwaOe78KnSYGg4kT+tPrBFZOz8ctyRztHeaQT+WnZ34Ts5RkQ8BBfVY18WADW9vcHImaCaZsJFQTZ9p3sczxJgV147S/UENkOHNveMo9ZOXX0tQ1yIhbwevJQi8luSj/dYRIJSMHDfj74gAIkkrlyn4iXjNtQ0uJKBbSisr8kp0E22QUVSBc4eDR0JVk63x8OXcXJbVzySmqwVNWgdVWhCieLJzSPhqmaSjMWXV5J3i3PwpuONzFzmCENXNqueVoD/tCMZY17WVeMsSTC89mht3CQ/UV3Pn0c/zek6l/euPmV8iSJd4Q6mhJZjYD7lp4P9VSLwmzjpvffACAz2R7SUY6acqeRlN+Nl5PNjURP0v3ZXK5RU1FjEXIEVVu/tED72u86XSajo4OnnzySQCmTp1KcXExe/bsmVBXrqurY9u2bQC4XC6KioomcofnzJnDsmXLJgzMZDJ5wmZKNBqlv7+fwsJC7PZ3/k1pbGzEaDRSXV39Qad7kkkmmeRfyqSx+n+I0Z4Qz92/j8IaJxfcespJ3q6h9gCD7QFmLivh0Tu3UTbDQ/EUN399JKN8aLRInHZZDVufbSMZlTGYdNizTdQuyGf22WUfaCyPfG0LsWAKyaijYqaHigYPVqeRFx7cT9n0bFbd8veLiw93Bjn44hF6jviQdSZKzR30JDLeTB0pNESu8vwHTnMYyhdDzdkw6xpefaiVgRYfnyy5E7PLBp9aA2PNmX/7/gThYRg9ynj2+ewJXkxHfzYXfixNSUkaml6CxbdlckubX4U9D0N4kOFULc/7f0BBuZmBriSL7Q/RYH0FEOCUq+Dc/wTDPy76k+wKkuwIIPsSCJJIqj9MejDj2TXoD5Kaux1t2rmY3cUMDT+NqFhIdgURfRYEWU/KPYS1qgSTO5fevkfQJayUr/8hokGHqcZNYmEzzX13UF7+efLzLsZsLjkp7/KteL2bOHDwBsrKbiEe72V09DX0ehenLlr/vkqafBgSHQFS3SHsS0v+IY+tllYYuGsbjpVlOJa+cy1NTVMYHV1DX/+fCIX2o2kKNdV3Ulx8Hao/RaIjQOC5duy6pzHUlRMNzUeS23HmrkcYOwq+TlBlECUonJVRc667CGz54O/KvB4dyyg5Owo/9LX8q1BVjabhEIOBBJGkzMObuzg8GOSMGg+dY1H6A/GJtrl2I0V2HXeeP525lcdz837yh2fZ0enFabfRH0ozKpsJaSbOMrQxzaMnOzubrKysCeVar9dLd3c3kBGEmTdvHlOmTOGN5nH+tOEoxvEWtqVKqXZLvPKVlaiKTDKZZGvrCMsbKtBLH86Q6g8E+NHGV2jsdGG3qEwtiXNqrYkzS5bgNDqBTNmWp5pWUyAtYE5JMT94tZl+f4wLGwoxSCLjkRRj4SRHB0OMhBP0++MoqobJcZjLZ29gllXAmW496dzhYBbP9l/F5oFazFKMOZ5OLrF7qKutJK+qlrjJxeefOMCBvsAJx11gH6A+2MQT4mzKinJxCGnOyk3xanuEtQE7afFEA73WpuDHzFgks3n42bIoX/vsFfw7EZIV6rYc5tPFOdxTXYSsalRtPMjc4Ah311ezsi/MNysL+EJZHoNjY8w+MgDAqsPbKfONkFYlQhh4KTWd66a8yenlb3Bn4tuMbLSSnurk+t716FWFZ2afybg9E/b7pV2vkgxHsY/1U15ZSVZBIbULT6ewduoHGvuhQ4fYuHEjV1xxBXl5eRP3899yRVevXs3BgwfR6XQ4HA7C4TAFBQVcf/31k7mkk0wyyf9ZJo3V/wMkImn2v9nD4Y0DGC0SV3xzHmbbe3su45EUBpOEIMBLPz9IdpGNofbAhPf1kttnUVjz/kIn34lXfnmI7kPjLLt2GtNOLZh4/cAb3Wx9rpOlS2NMTTzElt6zUCuXU1DlpKzew1//eJS+Jh+omYWyXovjDHRy5qJDePzP8euRpwGYWeentjJEXokFpp0PhuMhT76hKE/et4v66hHOCN2cUd71dWbeNDqJOht4ffhmhkYt6PQic1eVM/fc8ne+kEAf7H0EEDi4ppkt4Uyu6yfOPUKWPQp1F0Le9A89T39D0zSC6zsJrm9FlK0IWsZIk7JNmE/JJaH10R65l4Sr4106EEFQMRoLSKVG0TSVv8VuzxAfxbNwPv7oVg4c/NQJh1mttTTM/C0mUxGaptLReT+JxCBVlV8mHu/n8JH/QFUTLDljPzqdheGRl2hs/BJz5zyL0/nRqBL/dzLwne1YGnJwX3yyt0GWI+zbfzXh8BHMUjmu9GIMB6oxBypBFNCO1ZaVDAFynN9Hd9tWeHvtSVXNhH+b3f8jjdH3Iq2o3Pr4ftY0Dr/j+3pBZYEnTZExRddoEJ9iZkCxIwgiL94yF4OgsGZPKz/YlZgoZWKRNFxiiqGUAbNBwmXWE0rIXNBQwD0XTMek1yHLMmvXriWZTHLWWWcxFFG46Y976Bw/XvdYEmHDHUspdmc2iFa3r8YiWTi7/OwPfb1f3vBl3ux586TXp2dP584FdxKX4/zm0G/YNbyLEnsJV065kvMqzyPbfHJawxvdb9DobWRTRzeNPXpuPHU6X1l0LQIyvX1/4PCbW/A2Gzn/6zdiNORhd2S8g2sb27nx0YxScGmWhRXT8kjICru6fAwF4tx2Vi0lWRb29fg50BdgV7ePbKuB8UgKi0GHrGpomkZa0TitxMJVi2upyXewqbGP32/rYyQqs6Q2h7nlWcRSMl9YXoPxQxr3HxUvjPq5ubGHF2ZVs8CV0QY4b28rkiBwaZ6br7b281RDFUuyMptlPWPjLDrUw8z+Dk7tPIoqgE508edYBcVGhVmnv8Jjkc9g3DFO6pQsPC4NUklG7Znft+u83eQ+/RAAl33ru5TN+Gifa8lkElVVMZvNJwksTTLJJJP8X2TSWP03JtnRgc7lQsr+4Dmcb+WVXxyk54iX6jm5zL+wElfuh/PwKYrKkQ0D2LNNVJ6S8/cPeA+igSSJaJrsorcIEQ3sQ/vTJbwwdBuDqek4dCMElUL0BoF0KnM/iqLA9OlxDGN70QZ7sG3di7vAT/FyBeZ+ilfbL8Vs07P0mmnvef4Nj7fQuGkAt66fj2V/E+NZX6E5vIBA3M1QV5TR7jALL65k6qICTNZ39yy+FW24kY1/OoAs2Fhxx0Xv3VZRCW/oJ9kTAlXDfkYxptrjxr+iJEkmh0kHIoz3bMDn30bIsAtEFYu5BtU4ByXWhkg/FmsV0WgrcsJHcUchWa6PEXUVofNmERvqxTltGp5zZqOqCSTJjiyHEUUDicQg23esoLbmLkpKrqel9V76+//IGafvIRJpJRrroKXlLgD0+ixEQU8ylREnEgQJTZMxGHIpLLiMqqrbAYhEWti561zqpz9IXt7572ve/pWMPLAXnduE57rMhoKmaXR2PYDPt5lYrBtZDpM/fA2Ow6cjaBL6IhtqOIW+wIqpLhtDgQX9Yw0I9RfChT/7SMeqaRqKqiEKAq83DmM1SpxR+8G+h8F4mtFQgupc2zsugPv7+0mn02RnZ2Mymd4xNLZrPMpvN3Xy4oEBoimF86e58HceIamJFBnidMYtmGx2luQk8Q12o6oqhYWFVFZW4sfOHX8dQ0JFQkVBwCSJvPLFJdgsJtwWPYIg0O+P8f1XmzBKmXq7qw8Mcs8FddxwWgWapvHiwUH+sK2bxoEQkk5AEgU+daaTGxY0sLU9gE6EA9E/UeYo48KqC1nw+AIA9l+zH0n84PqBnYFOLn7hYq6adhUXV1+MTW/DorewfXA7d265E0U7nvvekNNAQk7Q4m+h2FbMixe/iF53/BlyeOwwV716FZIo4dQ7+ZS8EmVfL9nFJThz83HnF/Lm7/4f05es4JzPfemksfx5Zw9tIxFeOzJEOCGjEwQEAX58WQPn1OdPtPNGkjy2o5cjg0HqChzcdlYto+EEP3m9lcahII9/eiEO04nPtnhKwWz45xqnMUVlXyjKm94QB0MxHpxWSpn5nesz7ghE+OzRjGDe7oV1SMciK+7rGOQ3faNIgsA8p5UnG6rQveX+nrP6DeI6I5/Z9FdSWRX818LZTN/VToffTHHRy3RmXYPhsJ+CGhmkJF2lmQid/0yNMvLwz5h62hKmLDqdqrkLJg3HSSaZZJJ/MpPG6r8pmqbRPK0O0WZjyp7dH+jYwEiMzoNjDLUHifgTjPdFmL2ylEWX/BvnqvTthqeuBlEituhudu9zE41L5A//iVk5W9gRu5bW+BnMTz9BVtdrWKvcDG4QUaJJCj5zHq4v/hB0738RGguleOSrW97xPaNFYuFFldQfExj670ZLK4w9dITYUD+x2kOETftJGYaxajXIShTFGCZpGETRHc97kxLZGLTZ7LcM4Uy3ki+liCgQVA04DTaK3DOozr8G18OfzIQ7X/5I5lyqBsI778xrmsbuPZcQibRQUnIt4+PrMBg8zJn9xESb5uZvMTD4BCCSm7OSvLwLcDhm0Nb+Q1zO2RQVfeKE/DVZDrNx0ynk511EWdnN2GzvLqoTjjTj928nmRiiouLWjyxs+L0Y/9NRUv1hsq+ehhyO09r9bXyWN7Cm6tDHc7G3LsDin4b7shpM07LRhZvR1v8QwdsGxfMyZWS2PgAX/RJmXf3fNq6xcJJHd/SgEwRy7EZeOjjIUDBOry+GUdJNlIFxmCSW1OZwZpmRQjFEMplEEATMZjNz586lr68PWZYRRZGWlhbWdKboGBhBZzSzbN4MPnV6FQcOHCCVStExHGBD0xACKuWiD70IirOYlriV8hw7nzizgbKCHFY9uJlgXGZVfT6FYpDgkQ2kkCjIcZPvyWLmzJlMmzYNQRAYGhpCVVWKioomru3JLc1saxsmrekQ9EYun1fO0qm57zYVAJzzQCZf8O7z63jhwCBP7enDYkpTmDcGmp6gtJ6EcR8Og4NbZ93Kpv5NbB7YDIDH7GE8flwR2mFwoKFh19uZnTebexbdg0nKCJwFk0Gafc3My5+HKIj8peUvrGl9mb2+gxh0Bp4992myBAcmmx2dJBHxeznSsQd/tkpcjvN069P89MyfUmArYG3vWr60/kvcNvs2qsYcNDXtZiQwQHdqkOEimWdueI3GV19j8+N/wJbtQW8wEhobQZEzqk0rbvocDWedy99D0zQ0jRPUdv+diSoKjw/6OBqNM5qUORyJMZqSMQgCChpnuO2c5rJRZjZyNBKn1mpigdPKr/pGeah/nBKTgT/MqKDOdjxXe0cgwsX72ykw6nljbi05hhON8JufeoYXcqu5et1zzHKt5CuzrXh8vaR3a9Q7reySwBqIcXV8LReuWsnvxiK0+oOs3PQCtqxsbvivX2Ew/8+q3TzJJJNM8r+FSWP135DYvv0Mfu1rpPv6AKjZvg3J/f5CbqOBJH/+9g7SCQVnrpl0QiERTXPFnfPILrT9/Q4+CjQN3m4saVomfPbIcxlBmcbnMyJEH38U8mccb7fj1zB8CDrW49sfYGSP64Ru8u68E/cnr54wxjRN4+DYQY56j7K6fTVmycys3Fk4jU7cJjdPNT/F6cWn87lTPkfEn+SP39g60deya6dRMdODwazLqMomlUx5kw/haUiPRPE/24YcSCKIAlKuBclpRFNU0sNREqPj9K24l6Q6hFFfiBDWk5YC6DUXupQDXcSKTrBhc00hf9p52IpquPK1K2nyNVFlWcBgj4egqlFbFqQ3sQNV01CSuXwtInN+fIAvZ/2CpCXC/Gle3BaR8NB+skLDXC3lICy9E5wZ4yEcbqS55W7C4aNoWoqyss9SXfWVt3xMKul0AIPh/Zc4WLuuauL/Hs8KqqvuwGo9caNkbOxNDh3+LH8LRa4o/wKFhZdjMv3zQmU1TaXv4JN49+xE0ETirg5i2Y3k+C8hu/lStLAMUqYkjqU+G46uhmduAL0lI5A1sAfi/kze6a17M/fx+0BVNRoHQ6xtHsFi0JGSVR7f2YteEple6ABgffMYSVlB0zIzVOQ0UuA0UenS0Tvio8ymEZehy5egLaInqYmcpW+j8C0bHB6Ph6ExH2l0jKtW2hUPFTofMU2PABSKQaKagf1yEWHNRPItFcvKnBINjjgv9WVe+1uYrkFQkDWB7y/zkG+SWb9uHUOKnar5y/jaBR9deOQTu3r5xnOHJ/42ZG/AkPM6TqMdvain0lXJWWVn8Ub3G+wZyfwufHrGp2nxt+AyupiVO4vvbP8OAJdUX8JwdJjtQ9sB+OLsL2KWzMiqzBPNTzAQGaDaVc0sWz2jL26hYtiK4LFRUjWN/j37URUZBAGDyUwqHgOgduFidHo9ZTNOoXbhaeiNJjRN45rXriG6r53Fhz2oaGgC6DQBBAF3fgGhsVHKT5nLRbd/E0EU0VQV//AgwZFhSuob3rWcy7+SuKLy894R9gZjnOVxcGaWHYdOx4FwjDqbmWLTcW/8X4Z9/Kp3lCqLkbiiMZxK0RpNktY0PHqJtKZRbjZwW1k+p7lt3NU2wJPDvnc99w1FHr5VWYD1baHJiqZxd9sAVxRk0WA/2aj885rXud2Yx4p9G6jWlfLrhkockS5qd3g5qhSgCFBhDvClGrj4E1fT33SEp779dQCu/fHPySl799Jtk0wyySSTfLRMGqv/JsT27UdLpUg0NTF6//2ZXLdjFD3wAI5zVr7jca27h+lv8hMaj+MdjJKIpBFFIWOcFtkyJR8UbaKMzAlExiAZguwqGG8HZ3FGrXZgL8y4PCMIlIyA0QaJEJgc734BqpoxSAUB2v8KL9+WKdNidIC/BxquhPixRUhWJbS8ljFCs6szAjPOUrj6Lyfk9cljY4z9/P+RHhhA0JJE9+zHlGei9MkXibd0035kC6unRRhNefnmgm/iNrp5cN+DPN78OACSKCGr71xb4vuLv88FVRfQuHmAeCTNnHPKJgze2OEx/E+3oaUUkATM0z3I3vhEeR4llMQ6Jx99vgXJY0ZLq0S2DWKqdWOamoU8Fsf3dAtaSsU0LQvZm0AJJtGSMoJeBwaRobk/xy9vY9Ypf8DtPpW0kunccOxz0jTtBG9of7ifVc+t4qrqz/Hwq2Usqc1BEATePDqCaBght3QzEfEwehTu9Y7QYbDyR4cJ+djHLmgamiDwwMgYy2NxBmwz2JKsol0rYd4l/8HyqS42H93GY6+2cMopp3H14qm4re9PkTmUSGM3ShPj3bCxAUWJ0B+7kCLrOgRkFNsXWTHnUwiCyPadq0mE70CLm+lOfoWqwudQko0IgkRd3X8iIBKNtmGxVJKff+H7GsP7xevdTGvbfbjdCxEEkf7+RwEdoCKgpyLrC1RMvRqtfS3K4W3o+l9GSPpBMkAiCNk1cN2LmftUVWH0aKbGraPg752apKzw9J5+Ht/Zy9Gh0AnvlTh02AwiUVkgnkiRK4aplbsxCml8qpUcMYJeyDwTJElCkjLznZ2djdmVyw8PSYRTGqvq87EYdOxobCecEohoBlTe4bv/FgyCSkoTyDWLSAY9ZoOewUCceFrFIImcW59PvlWkubOXbl+CQmWEWinjqRxW7Vinns4PPz4Xve69z/N+0TSNtp1b2f7ME8RCQeRUknQiib+wntolZ7E1+DSdvidfQi8AACAASURBVL18fulXOH/Gx9CJuhOOfanzJWLpGFdOvfKEflt8LRz1HuWSmksAUDWVc587l4HIwESbUiGPi6QzONi1C0d3kqyIkZnLz8HX08NoVwfV8xdRNHU6sWCAiN9LdlEJLTu24B/oR0MjGY3iyMnj3P+4ncHWJvpHu+jYuhWTy8n5d93NjoEduAQrpv3jhL3j6A1GTrvyk9izPhr17P9OmiJxHuofY70vzGAyjUEQSL1tneCSdLw0u4bmaILGSJwHe0aw6UQsOpFcg558ox6rTuSiXBerclwnnUNWNYKywmgqTUBWaLBb2OQLM5BMMd9pZcY7GKLvh6FxL7MO93H+aBf+vi62zllGlZRi8br1PBWfDggstPZw1wWLmH7KLDRN48Abr1A1Zz4Oz3t7/SeZZJJJJvlomTRW/4VomkZs126Czd10/voJnKFuhvIXkq6ehVFM4dn6KMZUiKwbP0XeHXecdHwqIfPI17YiJxXyKhxkF1oxWPRUzPRQWJNZCGiKgvB2FcF4ANZ/D/b+EZRMvcaUXkA1WIgbNDQtjbvsMgSDNaN2m1UF3raMN2nKudC7HXq2worvQOlCWHcfdG8FWy4UzSXW+QKCJQezIR90epCT0LcD7AWgKhAdBWcJnHorzPv0hNfV599GONyIw9GAfkCg9+PXIqgiphkzUJUkyZkiwbNz8JpzCAtuDnT9lmqjSm9KpMAgkSNp9CZlyqzZFNtLMOkdoM8jLlipyDmD9oTCWHSY1Z2vsn90PzfU38AtDbcg+TTijV50dgNqQib4SieGYjvmGR6ie4aRx+Lo7AakPAvp4RhqOPX3P1sBHvAI6MsdJNIpPPqDLCzuZ3rpTNLpEG3t91JSdgfFJTfRPBzmhkd2M73QweOfXoisqGzv9LK9a5BwTMBkCdCceIZD/k1Ig3ei17J47Yun47Lo6RiLYDZIFLnMbO5q4uvbP0MonVEEXZBSuW10FKNs4bfyhbxZtR5ZEFg16uGasI8ZYjcAq13XcnqeTHt7MwuUfexTq/mi7lt8N3cdM8vzca/8xonCQePtcODPkAiSCg2TbFnHqHMmVSs/izbtQp548TFWNn4dQ0rjar7KqhmvUZvViSbYELQ4kAlhPW2HD1NKZdBkZ2jZ54gmnyedPtGrMnPGr8jJ+ZCiOAefJL3zZ0gYYPqljJbk0tz1A0QNZC2JqqVwOecx23FTpr27FKFlDWz4AaRjYHJBzhQYPJARyqpcSqR4CZolmwODEbyBEKOjo5S7jXi9XoqzrLidDrKysigoKEDTIJqSWd8yxsG+AGuODDMQiOMxqlQo/VTqvEiopJAwk+KtUZzFxcXU1dWRl5dHMpkklUqhKApWq5WS8hIsRgvtgU52DzYyp2AKP97xCzYezEaLVZOpK5pCr4uiCgoLSusosOfgjabY1DbIj692EEzEaOnJZWpuDufOyGdT6zirDwywvzdAJJnZ4BEFcJr1+GPpE6a1yq4yO1dk54iG2WJnzW1nvGceXzqVBFVDbzq5lrAip/EPDjDe30ssGMDhyaW38SD7X3uJnLIKCmqmENUSjKbG8e9sREod/10y2R18/J4f4Cn5YErkb2X38G5a/a0szF9Iy6EdtP3+OeRk5pmoM5tYcsNNzFpyzvvqS1UU2nZt468P/ZJEJDzxumQ0cvV3f4KntPxDj/OfxWgyTVxVKTEZEI99pqPJND/vHeGh/nFMosg8p4VbS/NY7LbRl0jx2KAXh6TDJun4emv/Cf2tyHbwm+llWP8NlGzrtxxhoRqn9/ABDtXNA+BbTh2/fK2LWFjHV0sHuOWWmxDfLpI2ySSTTDLJv5RJY/WfgBKJIkg6xLct1rrvvI8tHXkEXSeGSEoSyAqgQWmykfr4NiqefIK3c2RjPxufaOXSr80hv8J5wnvpwUGG7rqbZFsbla++is5mBTkFr92BtucPIIoIDZ8g7LLTFH+JsDF5wvE1bRGKR9IEi8swj3QTLCzGGdEwjvXRX+LA79BR2RXCFssYHlrOFFBloro4O6dmjLn8ousxiDoUJU6uYzGawUhaDuPW8tG5KpDMGW9CNNpOT89vGRp+9oQxCDHIs60k5Vbx+jYhaCeO8XhDiTFZhzedptpiI8tWiSjoCQT3AuqJTQUDeQVXsGZ8nD91bCRb9PBI273oUscX28ZKJ9nXTefNwQ1s6N7C3Yu+hslonFiQp/1xRL2OsbFhmjuOUOOsJr+uAnk8TqonxK6BMTr13yDL6iWStuA0+LEboieMYyyexbe23oms/i3MTwVEpubb6RyPotm3YMp/EU0TEY551FK+Uynnan546Qxmlb5zWLgv4aPF18LUrKm4TW6Co334FRMGs42r/vgwXstqBMMoK0pWMddZxKUvfwujBlHNiISKbM7GmjhR3VW77BGE+o9l/kjFUH91KqK/CyzZyIkokprAp9nIEiIMmmuJR8OU6cbQ6SSS5lz2ypXUmrexy11GhTrCUIkBS9rKooWv4m/ehPTql4k7q7CtuIFEcR16vRut8Rmag38hrI/jdi3A6ZpDlnsxbvf8d74H/oaqQmQYtfF52tu+R1+xGZ0qIMoKaYOINaLS0BjAkFbxuQxYFBfW4Ojxa9Vgb+EnOepcwg6/ja3DUOOW0Asq0XiCUChMADMB9eTapkZkisQAIDCsWYlpx7/vOlRypAQzhT4KdWHmz5/H/PnzicaiRKNRnA4ninIsD9XhwOU67nVSVIU9I3v47o7vMx4NEpF9GAU3SU407LVUHnI8H4NgRyaKzrH/2DUJpMaXkw7MIbf6KWJCNwDz8ufx8MqHT7oORdWIpWTEY8I93eMxCl0m0orGozt6eHxnD/5Ymjllbr5y9hSqjTF2vfAM0YAfmzuLaYuXEhofxdvfi39ogO6D+xBFHdNOP5Pc8kpyyipo37uLpp2biIyMnRBF8jdmLFuJ/bw5ZFs93Lr2Vgajg+SIbs5zLaUQDzW6EnavfoZEJELxtOk4cvI445M3YLa9v7znaMBP98F9ODw5mGx21vz6QbaqerKNBr5w/Q1kFRbTrcBGf5gbizwfSFTH299H5/7dVM6eR/vuHVTNmf8PGdT/DNKqxmcau1kzHkQDLDoRVdOoNBvpjCdJqRqfLMzmG5UFuPXvrg3wUP8Yz434uaeqkBqriaz3aPvP5uw9LVjR6G5vYyivBMhs62hxmaLeEZ6en0vl7Hn/2kFOMskkk0xyEpPG6keEEg7j/c1vMFRWMfKDH2CZPZt0fiU95noql0zBFh3kjd8cwJc9jUhNE/3mYWoPL0fU4NVFP2VR9hLKjszH17wLS3APH/v8TWSvWDHRv6ZpPPHNDchDg6yaH8Lz2VtIdXYi2u1Et21j5L7voskyWjJJ3t13kXXVVbD7IYbv/Q5DZUa8lwgoghtRCyCIegT3SkIK7BjaTa1umHKjik40o6jxE67Loi8glh4CQI8Ziy6HGAHSSohuKtGRxkmQMXJo1aawnDcQBQ0JhRMRKS//HAH/TgLB3QiCRE5gPmpPAUqoGdnfTHyVCVmKElF1HIwJHInrMFjr+fa8zyOmBhCUMJ7s07FYylHRE0gGyLEcV0cNh5tIpkbo9wbp9/lQk3spsMcJBTYBKggGesJuFnRdxEvuPci2IfKkQnyGpWwb3orFvBePpBFOTCOkq2G6eyFX1k2ju/0T+FMJOpMaMRUk0UKVzoVJX0lUqUCOr6PG1YPOMh2b0UNc0VDNU1jfX0FTe5JEYpA2fxWnT7ehWg7RFt2GX+7BnK7HLdSTMO5hXG6h0FLO3Ly5TM2eQo5Uh1HLY3FNzocOt0zJKjE5ynd3foc9w3vwJryssNRwd8sh1p/2Z1YsnIXDKGU8iwN72FD4aeZvuh6LkMzUiZ17IzxyDvTt5PrUV/nK5/+D2x/fAXKK06aXkdj/Fz6rPEmJOIZ29bMIZhc8ci4oSTRBRNBUxnIWoSy9GlfpYky2TB7Yj+77KubkOBuVelZNdWEYO4Ip2EabWEZF2SDlU7zEk/2AyNQp91JYeCWg0nLoy0SirQiCjliynxLXKpzNuxhLNeFz64laJVr9MxmIZFFtC1Ix1klq0MmRwo8jpMKYxo/QQCublXqajTOZ7kzyur+I1sSJ4e46VMxCCgQdEVVPnlmlxjyGYu6hS2sjHa1ANZhRU9lEIzmIKLjEIDZdGEFMMT23kNM9NgQ0wmYrG+Kb6U424tKVM5DahyToefljL+I2m08IaQVY3baa+3Z8j5SaQFAtpMK1GAUnim0bgmrl4qI7aPX2cqRPZmbWQi5oKGR/r5/hUIKblrp4peNlokIfmwbWTvR554I76Qn18FjTY/xy+S8ptBVS5crkGXd2HGHrU49imVaKaUY5S8uWYtGfGHqpqhrxtEJibJCXH/gRwbFRBAFceYWM93WjHjO6dZKEM6+Agpqp+MYH8XZ0TeR4Agx44nidKQK2NH57irhRoUTNYWXlOUybNp/Pr/v8RNt7T/s+C4uWY9AZ2BaIsNBlRfKNcXjt67Tt2kZgeIi8yhrKG2ZTNqMBvclMdkkpoqhDJ2UMJjmdZt+rL9B1YA9DbS0o6eMe45ZZi3lxwTlIAtxckktnLMlr40EAXpldwxzn8dJXE98nVcWXVmiKxNkdijKalFnvC/HLurKJkir/XewPxYjICotctgkF3H+Uh/vHeNMbosJspCeeYq0vxOdKcqm0GFnrDfHaeJA5Dgv1NjO3lORSYXlnhd7/KdxwuGviM12y/TUKR/p4c8UVXGvTIf76R9z44G9x5//vKi81ySSTTPK/gUlj9SPC9+c/M3LfdwEQzGa0eJz2ykvoLc0YnIKaRhNEtpc9T0dpKyZdLZ3uq3BH/Mzu3onL28jUeDl6bxhfahiLZmT2VXcxa2U9BrOEfyjC49/ZRW3bXyge3ow+20V6NONpUawa6UssxGdHkZpkLOvy0J06E39lC6pRI+kYxBgpQh/3oOrjuNsv4g/GA+y2H8FucJDQjXCNJ0ASIweiaVx6K22xGPOzS5hrN7A3GGZvVOHm4iIskh4VA78OVvOydrJypaTFENLDTDcluDCviDOyXVgjm+ns+ikAJlMRxUVXk9wcIf2jx0kaTKS0CK/NVTm43IJTDBE2TGFJyVKavE3cs+geCmzvnh+YSCukFJVIQiackHnx4AC/WH+89milx8rvr63GwmH8vq3HlG7/PkNpgb6kjnKDSK4h4zmWBTOiGkcUIKFCUjbjNMSJqfCc38Ce2MleBafBSY1rGt7kCJ2+QdRULuXWOmaVulk/8ArhdJgKZwULc5dyZsHHMOscmPQ6bEaJ4VACp1lPbd5x75GsqEg6EV80hc0oTeS8vh++v/P7PN36NNuv3IZJf7KnMJ5SSH+vGIdwzMAonAWD+7k3fQ0PK6uATAT376+by7KpeSTSChuO9FGq9iPrHQiCgKv7VfL3/gj9wlsy9W5LFoIo0jLo55rfbcNpEvHFNbyJd37eiKhcIO3ly/nbGJ3iJaQLUFh4JYZomO7gKwDYwzJ6WcXnzuTYipoOUSji14eWMa6ewZwyNzu7fBS7zdxwWjnLpuYB8Nz63Wxav5Z1ylRCin7ifGW6AMOag7iqw0yKu1blcOnC+RgMBu5ft5FH2/8LTF2oshU5OIuU7ww85hx80RSKqlHgUhgKgCBFMRc9hs48yGXlt7Kho5kx8U0EUUZTdYCAmC5BM3YBUGKezu/O/Ql7hvfwbNuz7B/NeEaVRD5yuB5D9AwevnYJM4qc/GlHO+fOzKPkmAf27TnOb+fQyEEODu3H1hoh2diLYDGyJraVpJYkx2/Es3AmgqIhrWnLeKI1AVlUkc0isxadhVlvJhrwEwsGCI2P4vDkEhgZJuwdo6BmCstv/Bx5FVVEA36GO9qwutzkVlQiijoe3PcgDx1+iHxLPp+puI7GvZvZFtvPZ8//BgW2Ag6Nt1DmmoaRGH9u+jNbxnqJO84hbayj3OrEJcZJSQUcjiQmrseiE/mvKSVcnJeJMNj90nPseuEZktEImqrSn1/GhkXnUDjaz6LAEPneIYLDmU223IoqSurqmXramfz0wFHWWbLwWhwYRRGPQaItlqTSbKTWamTNeIirC7L4ydRSNE1jfziGqkG2XuI/u4d5dsR/0lwLwK/qyibG9lbeGA/SEk1QbjZyQe7JOZsAIVnhm6399CdSlJuNZBskftc3RkrTKDLq+Wxp7t/19r5bfc60qtEaS/D1ln52hzLRHm5JR1rTuKHIw51VhRPH+9IK2YZ/H8/oP8rPe0b4dd8Y92QbGf/JPcTDmbxxW7aHVCzG53//BOK/QbjyJJNMMskkJzJprH5E9HzmZgLb99G17DocM+YT3LKHAdNUjhaNETb3o1GKFFlHpdpNjk3hxapL2Z+1YOL4mX6FsKSBCh9b+zri6B5AwOmczeV3XMfmH79Mj66WBSX/j1BZG4aQhtMXIWQ0kJilggiGcCEp++BEn1LUhS5qAdmCZ3UBRnMuSjKBUnkaVt6yo2wWWW1bh2CwMmKZwYKhIEOWTjba93BA34SAQI7spjC7mGvdH+d3Q2k25VfhSib4QkeSkGjkgFtHhV6PPD2bNwYPMUIhCAJGVeM7go0LK0P8NT2GyVhP34at9BxtZ+3isxk4VtPUkVK5sTvAvFoFa/kp7OsJ0RKNIxRa+HZ9KU69xLrmEbZ3eJF0IjajRL8/xpO7+9A0cCFQjw4PApc6bJTm2YhYJd44PIxR0TjVZcUeUwhnbyFu7+V+fzntwWJcZi8XNPQyJXcqp1XNQafP4qXDv8IR7yCU6EET/DzVN4PW7k+QVk0YPG/gzF1LSstI9FhFjWTahhyrp1S/hPIcPfVFdsrdHoLJKPv8a9jWdxCCS/GO1BFPZhZH+Q4Tl8zJpcvrp9aTx++3dBFNvd0bnWFqvp0cuxGDTmRz2zhZVgPDoQTGY4bqnDI3K6fns6IuD70o8PN17RS5zcyvyGL2sfDhpKzws83r+P2RP/D4FbczO282cLLR0/LdBUyRm+nPPo1iG/THdJzZdxOLavKZXeqid8RH86gXs6pRSABjKsB4XGNEtdGpZCMjUqv3871VJSiSlVgsxusHe3l6yIUODYeQIKwZaZAGKdf5kHVGVFkmhYQtr5QtIzoGUmayhQgzxE4+WbMGoTSTF2cdt4JwE0arkxafipJ6Fk9eF6/vuxxv0o3NZOC6VaeCksRutzM+Po7VamVoaAirw8XGI7081WtGEARmmHy4xCTT8/Vcd8XldCe7+eX+37B1KFMyJddUhIVSuqL70DQ9l1XeyLX1l2M3Gcm1mybm7oldfTy6o4excIL7L2/AF/dz947bEc2Z2pB19jO5YeYnOLtyIaIooqgK5/zlUkzdQ6R1KgO5xw0yLZWFEJ3NBWXXUeSycd6MAso9J3v43o2RznZe+8V/4RvsR3tLqG1WYTEIAr6BvpOOUfIszLjxKnQDYXr37ePo8GEKfWaMBhNWlxtVURAlPSaLFb3ZzOxVF1A1J/Pciqaj3L/7fl7qeAlFU1hWugyjzsjLnS8zK3c2A1TQItQhqEnyrYUU2UuptZp4eSyAL61QbTHilHTsC0XR1BQFwiDl7np2BaMoGpSYDFyQ42JJlp0fdA79f/bOO06uqu7/7zO97mzfbN/NbnolIQUIJPTQpAkqRVARH0FFREQfFUR5HgvKoyg/pIgU6UU6AqEHkhBCSG+7Sbb3nZ2d3u75/XF2s7sk1IRkB8779corM3dm7j33fu+5ez7nWw6NsThvzZuE02wiYUi8FjPxSISGdau5uC3MZl8hZmmQFibyg37GdLeytXoylS4HWRYzG0MxoobBTK+LKR4HF5UVMNHtIJw28AxUm/3FtmZub+5mptdFqcPKM12B3a7ZDyuL+FFVETaTifZ4knPW1NMQS7A438eCHA91kTgvdithtDUyZN+/TaqgLZ5EALc3d2MSsCjXy/ZInBWBMLOyXDTFEnQmUkzzOLmwNJ+H2ntZEQhzz7Rqjs0fmfoRTqdZGQizpKefR9r9eC1mFuV6Ge9ysD4UZWs4xqZwlJghMQFnFOXwm3GlHxrW+3liuIBPxKKsfOIRlj/2IAUVVRx78fcpHvfBy2xpNBqN5sChxepnQDocZsWiM9g463JyrWZS6XYS9iAPjR/H25OGwlRtMoadOEHhA0NyauBVTl9/MKtzNvLg2MkE1kQw+lMU+Cwc0tTN2P7XEekwFu/5yNR2cmrW8eghk0mnPSxIv8UU21IcxOkOTOT5nd9mncnFmeY6DravZblnG6tcWdQFEsxxVzK/fjabtzbQlTLjiEvO97dQbEiEMGGfeiSPF5TxN59BNJDAYTFR6bSSznMQ8EBFXNIWk+CxcHRXmvsqbZgl3PpulOkl2bim5WPEUvQ9UY9jch7RRJgNnXG6XBEeqi1kpRuKogYdziEvoJCSiojB3BDY7Bae9EqCZsiOG6TTkqBraMbbbkgqIhJHKIVhSLa19CP8CaTdzJxphZzVZeDpi1PnNfN2rpmYw8x/N6Yx++NkJSR2AzaSpp40Y80WzKUeDrtoBv5Igpc3d3H70h3s7A7jc1qxWUx0BfecK1vic3D05Hx8uduJB8djEKG+289bW1MkUnvuPx67hVA8hRCwoDafc+dVYreYuObJDTT2RnDZzEQSaarz3fzwmHF47BbiKYNgLInHbmV1o5+dPRGa/RHaAjEKvHZqCzzMrMimPRAjEE2yprmP7V3Ka+KwmoinDAa785ETCrCYTbxZ101kQAzPm7WMHx9xKs3BZv7fezdz67G3UOWrQgjBA8+/zouvv8lr6SkcVJXP6p3dmE0CIQSxtEBgkCXixKWFGCOX2ThqXDbJRII3GiI4STDe3AXARqMYnz3Jtw+RzJhQij1ox26209jYSDAYJC8vj0mTJjNmjPKA/uGxZTy+upmulIN8EeZP1dfT67Rww+ZLCRhOQtJOGhPTLG30G3baZDYxaabC5GeMKUhUWskyxegznESklV7pIiCdSAQ+q+Th7y1kXKGHN1re4NKXhkJPXRYXkZTyKqfCtZhsHViNIv505O84+iMGtsNF/9Mb1/HPLX/kBwdfzMLywwCIhoLUrVxG2O9ny/KldDco72qb10u7y00PU5gy9xCu/NJMirIcI/YbCfQR7O4iFg7R19FOuM9PT3MDTRvXk1dahsVmx2yx0LxpAzaXi8kLFmG1OzBbrVhsNqYeeSxWu4NAZwfxSJi8snKe/vet9HS18fWLrsZiG6oCfd3y63hwy4OUekqpza5lXvE8zpt03q5z64520xHp4NWmV7l/8/30x/s5quIoPFYPLza8SCQVoariUjabDyWYHhLMDpOg0GalMZag1mXnlIJsNoWj9CbTlNktnJbVybzCifjsPjaGoghg0rB1NdcHIxz7zlbKHTba40mSUnJhaT7TvU6W+kM82uHn52OLOa8kj2e7AlyxRQnzxflZxA3JhlCUBTleqp02Lq0owvUBofVJQ3JHSxePtPtZF4py1pgcTi/MoSeZIphK85Uxubsto9IQjfOHHe280ttPbzKNCViY68VtNpFvs3JygY+z3qtn+BNihlct+fKGP0h/yuAvEyv4SrFaLiqWNnAMtC+cSjPjrQ2E0gbX1pZwRlEOTbEEv6lvZUVfGAOwCsFx+VlE0gbv9kcIpNI4TILZWW6mep3M8LqY63OPWGLmi4hhpGlav46yyVN3hYprNBqNZvShxepnwP/7wyVMSm4g4nCxzVZOSbKTmYlt/Kb2Uk4OPo+jsBW/082jqXMIBz1YOgy6u830x5zDCu4osj0Sf9yMSBoUCsGlhp356RhOs4cbD13Lv2yHYq0LIBGYrFBkpOlsSyCSQ/ZzVvZSNiFBa3QMvfF8vO/1kkiogaMwSaShBp7FThOm7g5a3PkwsK5iTo6D3mAckRqclWaX8LG5LMSQmDxWXr1gHhVOOyaXlXd29rJsazdnbgsj+pOYnBa2GlsQD/0OJxYePPt82grmUpYws7A1QkDuJOJLck9HOdsHPECG24Iz287MAjd2A7rtgga3ie9tirE6x0y9z0yzy0zMDHGzwGZAWqh/H0a2xcxvxxQyt9hHc2eYVQ1+Hn63mcaeCGlj4MSyrORV+8gJpwkE4ywYX8jB+R7ShsQfTpKWklgyzSubO9nWGRqx/yyHhflj87jg0CqmlvjoCsV5e0cvr23txGo2Ueh14HNaOW5KEZOKh3Ij46k0nf1xynKcBOMpXFYzlr1YCqS+K8QDbzeytK6HS4+sYUFtPre8vp3n17eTMiQLxxdwaE0eVzy6nKgRwJ73CulYOcm+gzELgUVYmFjgpMsfoDVuo9bSg1OkWJcsQiAZZ+mmLCdKxLOCsK2HzlQ3lbnzmeE9GY8rxa2bfsv4whyK3SW4I8dT35jNu81BBOB09yKKb8ZkVRVT3VY3/z3vv2nsb+S7M767W94mQIs/wsnXP4ffcFBm6iMo7USkDTMGbocVh8NBS5/yWp08vRiXzcxD7zTvth+vI03UvA23y88hRRX818IjuGXLX1jduZpwcqgI1renfZuLpl3Elp46lq3rZkLJBEpyvdQWeoj6u1n55GNII43JbCHY043JbMZitWL3eBg35xCklMRCQSw2OyXjJ+HwDOUwdu7czqP/ezWRgKranD2mmINPOZPXVm4k2rgVc18bwkjjzPJxxDkXYnO5sNrsNKxbzbqXXyARHZlHjhC4snxkjylR3tpkknQqhTc/n4Xnf2uv8vAS6QSPbH2EdzvfZat/KzsCO5hZMJMrDr6CUDLE91/+/q7loRaVL+LiaRczrWAa9ZEYK/w9rOpt5uk+F4FUmhsmlHPmmBz6U2kKbOo51x5Pkms1Y/sUFVj/t76V1/xBDspyc2dL967tWRYTZ4/J5Vc1pbvyO5f1hYgbBgtzvJ+oWNJwkobE+gnyRZOGZElPgAluJ2Pfl++5vC+ECSh12GiLJ5np8Xw1dgAAIABJREFUdWExCVKGpCORpPRDhOTyvhA/3drM5vCQl9ZrNnFRWQFzfW7mZrt3Vd+VUtIYS+Axmz9XIb0ajUaj+eKgxepnwF//cBGnhV/BQ4wcESImrTjEUDEPA1hjruWFxOHcljyaqWI7V1oeJMsU5hZxAoUVXXSziFLzu8wsf5b/xM7gEf9JmNcFEMLgxzkNbPHFeD4xkXiLGjw5HZJoHJACaTNx9ZnTkF1N/O7NbpJxE+kKD5bGEBggzYLE7Dyk14o3HiIkXJjao5iCSUQkhYikSJe7eWyCnbmL5vPvdj/hjjAykmJjWz+PrmphSkkWaUMSMwy2tgW54JBKTppWzBNrWrlvRSMSKMl2cONXD+KmV+oINW6m5r3VLOhZQk1nCnNeLbZxx/Nc4QpenrqQlRvHUJ3v5tuHj2VOdS6rG/sYk+VgQU0epCXpSJJ4JImjyE3KkNgtJnr8Ud66fwMb4wk2+kz4LGZOlzY6xmVRODGfUFeE8T4XIZeZbZEYcUNy644OGlr6MfUlcPUlSfjjCJeFZJEDaTMjvVY8hU4kkJCS+ICAXZTj5fgCH2kpeaTdj8MkqHTYMIVSPF3XSTDPxvRsNycUZVNos3JErheLgHyr9RMNcPcGKSXbtm0jEAgwadIkPJ6PLvLyyKomfvzw2l3vq4pDJP2teJM+ugwPJiTd0o0cmLyYmCPx5t7DVstmDJOB1+blpqNvYnPvZm5Zcws9sZ5d+5pZMJOmYBOxdIw/LfwTO3rbuWntDYRSKiTyslmXUZ1VzU9e/wkJQ+UB/3L+L8myZ9EcbGZmwUwOHjP0bLr68fX8a0UDdpMknpbkOyQv/GQx2S4bhiF5YWM7JdlOppepXMDn1rVhs5hYMC6fbR0hCr12fvzmxfREexiXM46XG19GIrEIC2eOP5NJuZNYWL6Q5Y89iD0iyS+vZPXzz+BvbcbmdFI75xDMViuN694j1NuDzeUmnUzgzMnjncrJ2KJhCndsxhkYugYAZquV8fMOo6Cymra6LexcsxqH28PJP7yKwuoaLNaRE1SpRIL2+q0885c/EPKrPPSAJ5u3Dj4KUVyG8GRhttk4wmkmP9tHlsPONFuKyYVlu5aB2iekB9YoNiuRY0iDG965gYe3PrzL45znzGd87a9YH89helYWRTYrG8NR3vAPTeK4zCYemVHDrD0UKdpXPNfVx9pglGPzs5jmce23PnegSBgGT3T2EUob5FjMHJbj2TUBoNFoNBrN5wktVj8D0okEq1u7eachxKHlHjzeLDbd9i3mx9/iD87LqQmv4hzTEjwiRoBsfPRhYAXSmDBImE3sqHLSXOwk0F9LvqeFZksWN/svoWnl7kU7KnNdHD4+n9JsJy9s7cLstWD4E7zb2Mf82CZW2CcghYmqyE5qw/UkvE48U+cTMBdRv3YDFb42+nPzcMVChG0emlNF/HbJHYzbuY2OkrH8bMrZUFLGmbPKOPvgcv61ooE7lu7gjFmlLJpQyCX3vvuR18QbDxO0uzlnTimzfX28EnidNTsm0NTtxiQEuW4b3SElWAbXdyzw2pldmYvbZsZhNWOzmGj2R1jf0k9Hf4ye8Mj1Tk0CZpZnE4gm6Q0ndq0P+Y3DqnBYzYRiKR5e1UwsmUYIsLmtFIzPwTs2i8urxlDqsGECJrodu7wvnfEkv65vZak/RHtC7a/GaSfHamZ7NE5vMs0Uj4OTC7K5takLf2pknqlFQKXdis9q4dySfE4tzMZjMdPX18eKFSuIx+OkUilMJhOlpaUYhoGUcte/vLw8vF4vZrMZv99PVVUVjoElkJqammhoaKCrq4uenm5C/j76wso7KICJEyYwdfp0EvE4/cEgO3fsoLCwkOMXLx6xlmBLX5REyqDY58Bqhj/+9Y8kTAmai5pZH1jPlYf/D2+szeHUmSW8F3qA29bdyr0n3suUvCmYTWY6d27HV1iEyW7jpcaXqOur46zy00h09LLStJVr3r5217FmFc7i3InnklMXwwjFyC0r5+6ux1gafAcSKbqNvl3fzbJl8dTpT5HryCWcDBONW/jWnStZ06zyBn91ymQuPKx6j/fbG81v8OvlvyZtpCn3lrOwfCF2s53fvf07Lp99Od+c+k3e63yPuzfezXFVx7G4Sq2l2bp1E/f/8kpMZgtGOkVOcQkzjj2RroadbFn+Bql4HGeWjxMv/RFVM2eTMAyurmvd5dmzCrjRmWSmTeDJzSMWDrFl2VI2L32VeCSMr7CI0gmTOeyr55OVX7jHtt/V0s09rT2EUykS6TReAXUJA6uAWreTKaFtnLb5dszxANNCW8lOKWHYVnEUxRc8pNY2HsQwRq6R+3GREu45DWL9cNESGObt7o52s7J9JU3BFraa5/KvToMpHge9yTRt8SQ5FjNfL1X3uttswmsxj6olTDQajUaj0WQOWqzuJ9r9IX77zHrawpKDKrI5tNLDvK5HcDQthdpj4aBzob8V1j+KseMNTI1vEcyfzP3RY+nDybEz2sDfw88752LErMyqLuPfGxKYo4K5eUl2hE00xRykUIPK8UUeppZk8djqVs4pDmNJxdjmruHd+nbmTijh7m/NRwhBXyTB9u4wZdlOwvXree6mG4iEQmx11uIIWfnGxud4vXQGdXOP4ZlULgZq4Jsd66fP7gUhENJgkTeBx+Pi4Gyo/Mtv2JJbxgPTT6GoKJfjHAEOuv33XLHgUrZnl464Lj6nlYljvCTTBqcfVIoQgo7+GP5IgnUt/WxsDWAzm4ilDNKGxGwSHFqTR1mOi7IcJ5NLsgjFUmS7rCzd1s07DX58Tisl2Q7WtfSzpkmJH9vAuoEnTivm9FmlLKjN/0RLwEgpaYknaYolmJ3lwmZS+9sRjVPmsCFSKfx+P2a7gzWt7dxf10BvTw9Rkwm/K4tubzYhuxOvNDg1HaJo7UpikQgulwuz2UwsFiMWi31kO+x2O3a7nf7+/l3bXE4nllSScJ8fh0zhTifwpyCZW7hHT5sJtaxIKpUiy+Xk3Au/QWFhIb2dHTz+8EM0dvVQlZfD9PFj+d8dN7LF2c70/Ol8Y+o3uPb1qzm2roqDsqdTNLaWja+/TE9zI57cPCqnH0SydSPj5Hu8UJ9L0rBgcTjYPCnGEaedS6W3knnF81jz/LO8cuctI9tktiDMgnFXnEdtxVQSqQTnP3cB43NrMQkT63s285tDf8VJ1V/iiiWbWBmJ4i01EUjGGGsN0pOI4zElmeTNpbd/E++1Po/VUUow6wzSiU5k2+8QSGqza7n/pPtxWIateTxM0L1x/12889RjXHL7/bT2dFNcNAbHQA5nMhHHZDKptgpBwjD4yZZmHmjv5ZBsN9fUlPKN9TsosFl4etY4ommDJT39mITg5BwXyWgU6fZyfX0LR6WbOKKsGkwW6N5G5Jkr2e4o5lXPNKq6VmGzuUi68tlQeQIbXVXU+LK50O6n/K0/wKYnkfYsop5ikkXTSOfW8HZzPYt3PkL3nEvJr5oDwgTJKLx4NXgK4chfQO0xu7yku0hEIB4ERxYsuRY6N0BuDfTWww5VXIrTboaZ54zoC5vDMf7e1MWD7b2cmO/j9qlVCOCl3iAzvE7t5dNoNBqNRrNP0GJ1NCIlrHkAnv4h0jB4xHcxG/xq8Odzm5k/9xDqm9ppaGwkmRjyLgoh8OUWkOPz0Of3EwwG6XFV8HhnDjkiSoUzwXHTylg8o4Jg00bcDitZIkxu5SQsRZMA6O/uZOlD97LptZdg/DwmdGzH9+4aUiZB7sSpvHLqpdR0bWTHiw9SUFRKjxA4mhqYv60Jk4Qur4vGMXl0umxkh2NUdQewJ1PkhmMESsey9Mo/EYqniKUMclxWLllUS5bzgwe2hiExmQTJtEEsmcZuMX/s5VmklKzc6Wd6mQ+H1fyRy3sM0tnZid/vp6Kigvq6OtKGgcvlIhQKEQwGCQaDFBYW4nA4MJlM1NfXs379ehKJkZ7e2bNnk52djc1mY3tDA0u7/KworaHZl8+8nlZuWTCLMWPGDJynQSgUwmw2qzZKSU9rMw112+jr7iIcCFA4tpa+eJJUMkG0twd/4w6SO7YiDOXNnX7MYo65SBUI6qjfxmsP3Ut/MEjpuAkEGneQikYxCsbQ1NKKSKUQ0iCRU4DF7qDAl0V7dw9y4Po4G7diCStBLAWsn2+wKruJE5YXUeRXQq/S7WdxyTY6ZTHdFJGO9DPO10s+HXTFXAhfKTIWgFQM8/j5mB2l1BnjWPbi6+SVVXLmz35FT0sT9y9bwY5gmNy1b9NTXEra4+L16tn0e3Mo630Bq7OIrd45gFrzNI0JEyqcXjUwjUlGMYRLibQ98D9jfcx1hZhodmPd8G8omgaVh0L7OuS9Z0F2Ob2FM3m8B35fcQ5WryqiYxEw2e3EazFTbLcyw+vi+PwsNnQ28ded7WxLwJkVlVw3rgyLSfBQey8/2NSIKx2lJtbCrMB6jut5i6dn/4wWdzkyGeOyN7/Hgr7VH3j/9Xkr8JFCBNuA9z2H7T6YdzHMvwRcubs2BxJJdv7tcGb0bxr5fWEGXyn0NYK3WAnPcDeEOiDQBO/dB/GhiQ8KJkJ/G+RUwtiFsOU56KkDX7n6PLuC66f8hNsCZmb2b+YS6lmUn6fE7sHf2l0MazQajUaj0ewFWqyOZrq2wK1HYpTPY0nBRUTiSTZt2kQ8Hic7O5uSkhL6+vo44YQTiEaj7Nixg5UrV5Kbm0tJnhdf33qWtZk5nLcZxw6spDBjkE3/iMNI4F3nEWzLXoglr4oJ48ez6d/307ZtC0nDIDamkpQ7C3MkiDvUT8SThWG1YYpHcRgGcSkR0sBktpAymUAIzMkEjr5OjLiqpFve08/s0rHU3HXnZ3rJUqkU69evp6+vj3Q6zdixY+nv78ftdjN27FhMJhObN2+mvr6OUChMLBrFkBLDMDCbzSTicVrb2gYujLFH8WM2mUgPWwqk0tzFpIo8XDPPJBKN0rh6JVU1NST9PWSPKaFs0lRatmykacNa8ivH8r9hwbKcYp51RZl80GzC/l5WPP4wc089i56WRjq311H3zgq6G3fuOobJbEYakqKxNXTsqEcaBg6PlwmHHE7twfNw+rIprKxGfETIp5SS1f95CleWj8LqGv523a/YOnkuFR1NdPpyOXHSeMaVljB+wgQS0Qh/u/IyrKEAVpsN99cPJ3D7Syw8/1tkeaLULv0RQgikkcKUHhLq0uKkzZZHuzkLN2kmBLfQa8kiOxVESqgzj4exU6nqWU2HcFEnXUwM76Ag2YtVKuHdYi/g1Kk30uzZvThQSex1csPPY8gY1x9xA2N9leQ4svn18t+x5J3XOb3ym8icMqxZ2Xx9Ui1nraknq3cr9xvLsa6+e0icmSwYJgsN1nza7QXMDqzDJlOkMNGePZ5w3gS2Fszm5vzFmISgOxpmautrHNL3Ht9q/ffQ+ZbNQZz5D+jchHzzz/SG/HgCDdjTQ4WQ+iwe7q/8GtP8a1jQ+zY31V5MMy4MIUgKC71VR/O37F48RRMhr0b9qL8NmldC5yZY+wBkV8Dpt4K3aI+2fa29nWfq1rE+GCGSSuE0Epw2Jp8zph9GwdYn4T8/g2jvsBvZDmVzYPKXIOpXHtXpZ+362JCShg3P07/sFvotHlwmwZSmJThS4T0cHZh4Mnz5DrDY9/y5RqPRaDQazSdEi9XRzrKb4Pn/VgPL7AriZ95Nv7WA/Px8VfKmvwXsXnCoNfekkUY8dxWs/hekhgbLofyDsGQXQ/c2HH3bSEw5m0jRHAKxNM73/klhZAsGgiZzFT1pNzvLTkPmjKWpYSeBYJCSnGy6+/qJGwamVJJibxZ9/f0kAMNkIm0yYRICj9uF3WEn0tPKuOnzOHzuHJY/9gCb33wNp8fLhTfcjMuXDakEWD7+0glSSmKxGEIIIpEINpuNvr4+TCYTJSUlpFIpYrEYTz/9NJs3bwaUp3n4fWzCoHZAtG8warBIiZFM4HB7cLncpNNp+nu6sYYDmGMRvOMmE0umiG/fjDc3F5sQRPv85CQaOWZigqwpR2CkU7jX3YUwUsgz/8Hb9ZKl99/1oefSWFLNg1/6FqVtOyno6+KEyEq+Gn2Bemc5a8xjaXIVY8PCKdY+Kqcdj3fKUUhD8sb9d9Lb2kzJuIlMXLCIgoqqEfvtTaZYF4ziMpuY4XV+cIVV/06oewnqX2ZZT5RzJ/yYiNlFdrIfu5EgYPFSQz+prHK2hGPMWfMmi5b/B7PZzPTsNipmlVPa8jqt9gJOnflXXOkYhwbWYJqwmOPMfm6I5LItYeKsMTms6A0yvuEllmVPxyGjXNZ4D+e3PQ1Aj9XHRnctk1KdtBYexHqRy6KySrJMEvdrvyVVOI1Xp19DnsnKWX5B2OHi5uJObtlwA93Rbu5afBdT8qfsOq1oLMRt/3UhqWiUQ/IbmZLdQZelGq8rTmF0BylhZp1vDg9OvBizjFDTuQJvpIMbx36b+QXlJMxmjrjrMhYU9lFUWgydGyHYpjyGViesfwyCat3i1tpTGDN+IaZoHyz7K8QG1t90ZKuwWpMZTv4z5FbTbMkh9/Fv4uraCK48mH8J4UMv53V/kO5kCq/ZzEkF2R9eFEjKj108KS0lG0NRbmnq4pEOP1YhmJXlojLeyR/keziqDyeWVc4TAYOTCrOJG5L72nqoj8SpdtrVmpyRGA3RODFD4jGbKHPYaI0ncIU7uCSykgvzbNhKZyoPtRDq2vznKqg4BKZ/RT2Pwt3q+RQPwvzvQv64D2l0CvoalBe3eysE28HqUt7v6iNG5MxqNBqNRqP54qDFaiaw5gH493fU63HHq4Fg9xbleQl3AkIVVUkn2RU2OOMcsDrgnTuUx+Or9w7tLxlTnw3H3wDv3IFccQsiFSUsPHSbiyhP7SDtGYM10omccCI91afi61iGdcPDcMy1MPtC5PpHSXduxdS1EVPrauhXS4a8wRw2Fp7KuAIb0b4Q9s2PM7VYkpfuwBLtwph4Ci2lJ2IqnYXPlubdrS00NLchDQOfKUK6r5lUuBe7xUQq2s9mo4oUI8MMhRDk5+fT3d2NlJIS2jm5KkGBx0bDqqUUmLtpMYqw2WzkG21km9RyKe94z6Y7CGNSdeSkmsgyBemIevBbSnHnFlCeY5DjMiAWIGXLwVw+CxHuQnZtxmhehVmmSEuBxETanoM90c3WeDVPbS9lwQRBxJxHRaGV4jE+kttew8BEVkER0pmHkU6wrXULm91VHO5fRWHST7O9kLQwUxlrG3F+aWHGP/4U8hZejiiZudutETcMdkYTbA5HuWZbK72xMJPC2/GQwmyx8525x3F0vo+UIbl0UwPfXvt7Dt5yHwApRzaWWB9LcudT6nIyseU1hBxYOkiYeL76LC4rPp9+i5drXroP74Qazqv/CQAvVp5G7PCf0OMswmM28W5/hKe6+uhKqAqyd06tZnGBb1c7U4ZkRSBEPG1gev6nBHxjiU0+jQUllXtepmPdI/DYt2HW1+Gk/+OtjZu46957OLnAx9GX/oBA3VJyHv8ucWsO6ysvIx0Nkbf+JuIJg8nVbhyBbbt21Rlz81Dhcdw85UJ6bNn4Ar3kRoOU2q1kx8LkvvkCRd1D1/2I877JnFPOULmsD54LW54Fk1XlfE49A8ZMU+Gyg+Kxuw6W3wRlc2HalyGdgGifCr8dxEirbe683c/1M2Iwt/T+tl4eaO+hP2XgNJnItprxmE1si8TJtpiJGQYxQ5JrNdObTOOzmDk020OV08ZYl52TCrJ3FUgKp9O4TKY9h9OvfQieu2qk93YQexZULVCCdfY3IKtETZoko2pibdWdYCR3/x2oEOST/wzjjtln10aj+VzwCSaxNBqNJlPRYjVT8O+EJ74HO98Ai1N5HCx2KDkIjJQaIAc7YM19MH4xfO0B9UesrwncBbuL0w88TgN0b4Mnv6f2X30EBFqUGG5cNuRByipTeW+5Y5VwBsiphtJZkFWK3PYComszBiZMQ9mFdJFLK4VYSTGZuhGH7sdDq30c+ek28lPtuzUt4B5LXeW5WKvmEhdO6NpM7vp/4jN66Ck9BiFM1NbdjkQQS5lJS0E8bSY3y4LZmY0smECndzYF6/+GKTm0tIZ05WEUz8bUuR4x4DnDmavCMe1Z0L4Wwl3gzIH8CRi+MjbaFtLa1kd3UwNt27ZwatlGStxhEmWHkd360lCjhUnZKx2H/Akq3HLwGICceiay9ljE5C+xNQ7V5gS2SDd9gU6u60wzceM9fLX1KTzpKK/Wfo17Z1xFlcvOdK+Lu1u7WdYXYmAJXCYQ5Jm1P8TjH3ldbx37DW4rPJGLmh7iOy0Pc9+YE/l/5V+lzlnBtfU38Z2Wh8FdqIroeMfAthfUhEbTcuJZ5Xyl6gqu3n4zhYkeyuKdXLzgHn5+2PFUOkeGe0op2RqJ0xFPcniO51OvZ7mLZ6+Et28FbwmYLHRax+Lfvp4W+zSmWdZRYFYVeDcHChBCMCGrU7XD7kWc/GcYM51kykDkjaWhqZF7ooJzygtJr3+X7aveZuead0nGosw++XQKq8YSj0RIJxNMXLAIp8er2pCKw8YnoOYocOfv3fkcYF7u6effnX4Vih2J4zKbkEjGuRx8ozSfSR4n7fEkHrMJj+VTejJj/dC+Dsw28JWpvNqeOnjzL9C2Vr02WcDuUX1qkGlnw9hFkFer/plMytu68w145X/U8++UGyG7XEWZeIsgp2rvL4pGk6mkU6pit8UOX7n34/+N12g0mgxDi9VMItwDL10LM74GlYfs/rmUsP0VKJ8PNtfeHctIK6E1XHDEg8rLWzQVcqvhrb9C12ZVuOWE34PNPfL3y/4GsQBGbi3Rrgaee+otgs5qQtEoQQSHebaQiBrkO+PYZBS3DFPl7KEr5mJDoIhAwoHw5OEtLKXcFWBs338wCTCkoM9WiUf2YREppK8cc7cqLNMY9rHUOI7i6fOYsvBoCqvG7n5uO99UwtudD5WHqVzAwTy7YIc6Z1f+0JIfsYDyYhdM2G0WO51Kcu/PLqfG2cqh7ncRsQCUz4MppysvUvUitZ/hM+DJmPIkVcyHPXhLhxNJG/ynqRHnq9dxws6HebjiLN5xVOBKRaiJtjDFZSFRtRD32AVMXvIjTE0r4MTrIauE1tdupKTptRH7a5z8NdYefi25DjdrghF6oxF+bG3CXjl/5JInAI3LkXcsRiBJY6Kh+nhKS6dgP/oX+2c23zBgw2Pw6m+VyHkfXbN+Sr49jHjnDkiG4fAfK8+nM0d57j4CKSVGOo3ZoosC7Tf6muDFX6pJm6lfVmLWXaByZz/onmp5F24/BuTIZaGYfCqceYcu6qQ5sCQisPU5SIRh5rlDIeupODS8Be/8A758576/T1+/Hl6+Tr0+7e8w82v7dv8ajUYzStBiVbPfePi6X9C47j2Kayew8OsX0dWwg+qZs8jKL2TVM4/T391FaXkBhj2HQGcHbXVbiIaCJKNRupsbcZrizCxPk+00KExuI9sc4uHG6bRGsyhyBPFYEpSc+H3mnnnORzdmH2IYaYy0gcVqVaIU9r2YMwx4+ALY9OSuTWl7FmZhgtjQ2qR86a8qdBaUKPbvVJ93rFce3pnnfLK23XYUtKwiXT4f87ee3zfn8kmRUv3r2gS+MlLrHifZWY/zxGvVuUT7oHE5jDtW5zZ+Xgl1Qahd2Todh83PqBSHC56G6sMPdOs0X1Ta1sKdJw0Vbas5Co64UkUSbP3P0PcueFpNjCYjatIl0qsmfD8OoU41oTP43A62q1zwfxwPE09S0QfjjofTb9635/ZpCHWqaJhUXKVLTD9bbU8nVfTX8Ant0UY6ufuErUajGRVosarZb/S1txHq66V0wuRPHCJqpNOYzCOFSMTfxcpnnsJitTLxsIV48wuw2h17H346WpFSDVKESRXVsroBCW3vQcMyFbY8fvG+Fcpv36Zm70+/BSYs3nf71Wj2hv5WuGESnHC9WspHo9nftK1VYbjxIJz3KPTUw9M/VJ85c1QxtcGIEJtH/Z8IqdeJsHqmzvjKhx+jayvcNAcqDlVLSfXuUJXBQQnYS5bDM1fApqegeAYc+j2YfPpQVND+pLsOnrkcdrwxUEMjAaUHqyJ1/S3qO2Y7HPcbFVVksqpopU86wSil2jdCCX+z7ePvIxmDQLNKX0pFh8Rz3RJ44Dw49lqYdtaIZcEykmFrh39mfFS+dDKmUj2yyz98P6mEioyyOFQhQ41mD2ixqtFoNJrMQkr4fSVMPRNOukGtGesr18VmNB+PllUwZsYnC81tfkelt+TVQO92+Mexaru3GK5QFeh5+X/UvXjCH4YE28Yn1PESYVj38Mh9LvoZHH7FkEdPSjURE+tTFbbXPaTWSB5EmNSEZDoBR/5c1Yjo3Q7v3qMKwXVthuxKWHiVShfal4KlYwNs+DccdN7IfPFgh/KmvvFH9X7x71QO+o0zhzzOC3+qROu776uU7y1R4ctZJercxy768KrhfU1wz+nQM1RAj5xquPBplSP/QRgGrLwdlt6g2mF1q9z5Kacpu6x/ZNiXhfJYn36Lyq3PJAwDXv41LP87TDoFqg5TEx2D92ygCTo2qjSo029RRe36mmDF31X60uwL9rzfRFjZJxVTkzCr7oQlv4JFP1WTLz116vo3rVCvQ10DhTYFHHSuSqXKqYYjfrxr5QpAFVJ8/BIVLWPPUpMYoU5VK6X2GCg7eHR74zX7DS1WNRqNRpN53LEYmt5W+ebJiBpsnfMQOLP3/bGkhPWPwtI/Q8F4mHCiykvf12HnhgGdG9TAsm2NyoFc8ivlCao5akDIBFSUQzqlQkl16PvHI9YPkW7l8bn5kN2r5H8YbWvhlveFm9t9kFWswn6nffnj7afhLeU9KpwCT35feUntPpjxVVVDYdWdQ15IYYKqw9XAPdwFR1+jvE8fJECNtBK4y/6q7h2HT60KcNB5kFOponE+iI/yxK15QIkKmVb7Pf2Sv82eAAAanElEQVQWtcTUu3crjzISao6GY34FxdPVb2IBFfFjcw+F6vfUqwJ+vnLl4fzPVSOPY/PCUb9QoqjsYGWrN/6o9t2xHna8rj475Htq6bt0Cl77nfrtaX9Xx84fPzKcN+qHpy5TkwYVhyoPdNcmVUjSSKm+nVcDcy5S7dryjArjtrrgO69/uHj+sOvZtQkKJ++/CTQplWd/1Z2qAGYqpu53AGHePeff4lDf2YWAq3aq+1OY1MTEuoeVUO1YP1Rc0541NAmx66cmtS692a6qvu94XQlhXwVEelQ/6d2ufnvkz8GRpba/eI2acJl8mqoK371F2a9720B1eAHHXAMLLt+31yoVh7UPwsp/qPDvOd9UYfqFk/btcYaTjELDm+qeeH9NjVRCna8W5h+IFqsajUajyTwalsHmp9Vgw2JT3oTCSXDGbVA4cc9F4j4NwXZ4+kdqEDsci1MN0MZMU8dNhFV19nn/NXIN6Wifyq/t2qKE5fH/o8JEQW1reEu1sWMDbH9ViYCPS041zL9EeYC2PKsGiydev+/DGFMJ1cZMzul75sfKDuOOHconvWrnkC2GkwirgWM6pcTSa79Xtp7zbTWYtnuV1yq74tO3R0rY8pwqwFS3ZORnC38Kc7/96SqQpxJKaNS9qMSrTCuR8NX7hkRjPAiv/1F5wfpblLftpD+q0OLqI9S9uPxm6K1XQqd9nRpMn3SD8lB2bhw63oyvwaE/UH3gk/a1uiXKU+ctVpMJD52vvMN7wlui2jb7wpEFJtc9Ak/9EBJqWTqKZ6pzdecPpbGk40oEL/jRx2vjvWcpUZ1dodbZnnK6EvyDpJPquq3+l1o54KDzlLgVJnVtXv2tejYNhoOXzobyuaqo3PDJtO2vqv6/8Kfg36F+7x0zFA77cWpg9DUqcfjefUoMHfZDNWkAyr6Ny9Rky5hpyvvZskp55nt3qCXY+hrUd1ffoyZO4oGhffsq1DWI9qrzOvhbSuCvf1Q9Z6wu1R8KJqh22NzgKRzIq25VQnQwXHj9Y/DIN0a2vWwOnPuIuiaGofZtsUE8pM5p6f+p9p58g7p2H8fTPTw8OdwDK29T4rSvEVpXqza2r1WfW90qBHmQBT+Co6/e/XrHAmoiZbBYZtsa1b8c2VB7tJpM/DDSKfjnCdD8tgp/P+g8FRW09P+GhD2oqt6TTv7oc/wCosWqRqPRaDKfrc/DYxervMBJX1JFt+xeJSA9Bapa9Id5XQ0DNj+lwgOdOcrzsOExWHX30GB3/iVKtGx+RnmbfGXQ8o6qFm6xDYVsZleoAVI8qLy+MLTcl9mmxGQipAbogx4PqxvKZiuPn7dYDYCW/z/VnkmnqAFT4SQltNJJ9Z1V/1QDsOF4S+CMW/eu8FQ6pc5z5e1KtASaVLhfTiWMma7y0Do2KG+BK1cteebfqURe/ji1PatEiZ3cGpULWDzj07fn0yIHcvoTEXjh57tfq7PvVlWlQdnCSCnP1Eu/hsMuUx6luiUqrPWoX4wULPsKw1BeJ+8YdX94x+w7D0tfo7pXl98MSOV93PQUrBgoxlQ4GTxFKnxz8D61Zykxk4opW3sK1b1w+i3qdTwIb96ols9DQvXCfefdT0bVfeUrU1XAm5bDpFOVZ85b/MGiLRaAxhVKeL14tToXT5G6nhaHWhN+/n99/HYkIrDjNXjpNyrSwZENlyxT93Q8CPecoYTHB2F1KYGaU6U8u01vQ7hT9emLX1PXNhGCGw9S37c4VQ7tIFWHq3Du1tXKizntLBUiXTFfTR4IkxL1O15TYjwRUs+so6+BWRd88vBvw1CefiOpJvm2PKsmLi58emhCxkgP2fnTru/b8q6aREgn1TUomPjh9048CHefqgSrxaGeJe48mP4VtWJDTpW6V2xutc+lNyhvqcWh1jlvenvo+eouVNe/c6O6psddpzz0fQ1KXC+/GTY+rp6/niKYcIKanAt1wVM/UO0121Ukz/CilqDasvCqofoJUqrJjuU3KyHvHaMiZI74ifJ2v3vPgCfVo+zlylUTHyYLXPDkx1rNQK3d7leTIUZapTT01Kv2fVhI/Pvp3qau38c55gFEi1WNRqPRfD4IdalBwdoH1EBGmNUgsK9RDQBnXwjNK5Wnoa9BDcqduWpgGWxTS3+NQCgxc9QvIb/2o4//3n3w5A+Ux6BgvCo60/y28h6MXQjblqh1Y/Nq1ODS5lGDIu8YJTI/6fImUqpBq9mm9tG9DR79lhI/x12nBvFNK9TA97DL1GBt+CBTyiHRbHMpr9x7/1Jet0HxUnU4VByiBlmBFnX9or1qQJ5dob6XU6UGbBseU56D6sOVt86Vp0L7XHnw5TtUiOD+YvMzSmx0bRraNuciNcDzlatB7fSzlddm3SPwn58pQfF+Fv/+kwmd0UjDW8qzA+pecRfCtDPh2F+rbeFuePB8ZZ++RnXfnHqTEgaZRvt6uOtkFXVw9NVQc+Te7a9jA/z9cCV63IVD90jN0arPHfxN1e/XP6L62fSvqKr7w6MbpFTe7vd7FkF5PCsOVRNRgSbVhwPN6nkUDylxF2hSEykAiIEiXQOe5LK5cOj3VZ/bU5RApmOk1cTj2geVOE/F1bUZTlaZ6tfJsHpedW1RYnvCCSp9IupXrweFcTy4e1i8lLDkGhUCvicmnaLsm4yoibdJX1L7rVsCG5+EhqVw7qPq783r1yvvq82rRK6RVOHzP96mxGSgGepfVnYf/LtS/7Iq8mWxqzzfMdNVLvi449T5dGxQ55KKKq94T93QJGIqru7FQJPa19Qvq9SC4pnq/nn/xEKgRXncA03qfItnwtcf3zs7fcZosarRaDSazxfplBqYDP6RXnELPPcT9drqUmtF59WqgUGwTRXPMdtUgZHaY9XMeyKkPE95NZ/s2PGQmqkWQg2Aov79W100HoK7v6S8EQjlBR30+PoqlLcg3D1QUVW+L29tgMrDlId03HEw/oTdPTVGeiBH7X1hwdtehKIpI2fpOzfBA+eqMMcjfgLzv7t3ecWdm9RAcOqZHxyWnE7C9TVKXMz7jsqNS4bhzH8M5ZfefarKm/v2q/DbsiHP1kHnwUn/p8IHbW7l+fg8FO5a+5Cy+cSTP5u87tHEvq6G+8r/qlDwSaeogX35XBWSPOKY6Q/3EhoG/PUgFX2w8Cr1bCiaosLJP4p4UImZF36hvLyDYcVlc9Xz6fNwf35cUnEl3tJJ6FinoloGc0HHH6cKM+0NoS4lSLu3qXBsq1Nd4+GFod5PMga3LlTtQqpJwQU/UhMX8SBse15tq5j/4cfu2gJLrlXf3zU5gZoItLnVBKvdpwSuM0eFkefVqomT9rUqJNvmHlg+auC5PulL8OV/qolQw1Dh6Y98Y2j/JQepicSPCmU+wGixqtFoNJrPN+mkCu8cM015PT/vRYniIZWfOelkJVDf/D81OO5Yr0LNWlapkLbqgXBDu1fN9ludqrDN2EX7uD1BePZKWHO/er/gcuWtDrapQeCgl0NKFYJosqriUemk8nY3LldhoK2rh8Ivy+epAZbNrcKzBycV+lvVxMSmp+Ar/1ICI9KrcsMmnjQkcF++Dt74k1p25p7T4fRb1fXSRU4070dKFSqaVbx3+4n2qcmy4Tntms8H7euU0Jz+FZXj/EmjZIYT7lGisnCyuleKpqq/We+fEPmgcOzBYk4bn1BF0CoOUc/Yjg1DBdzOvkdFUmTIMk1arGo0Go1G80Xi0+ac7S0Ny+DtW1RIpNmmPH3uQuUlzalS+b/vX94F1AA/GVVegHHHqYHgmzeqAdjg4OvUm9T+1z6owu5yquG/ln5wUZaWVfCP45SHWBpw6dsqv0yj0Wg+Lyz/O7x1o/LEFkxQk36Fk1WoegZ55LVY1Wg0Go1Gs39IJ5VYbV8LnZtVDmD7epUTaLKooic1R6pwPCFUqGT+eBWaNzzPbFBwb39VhfSCKlQz63w45NKRa4F+EJ2b1fIpgRa4dMXn3+Ou0Wg0GYgWqxqNRqPRaA4c0T7l3bR7P93yOK9dr6r+nvKXT7fci0aj0WhGLR8kVvci2Fqj0Wg0Go3mY7K3BX8WXrlv2qHRaDSajGEfllHTaDQajUaj0Wg0Go1m36DFqkaj0Wg0Go1Go9FoRh1arGo0Go1Go9FoNBqNZtShxapGo9FoNBqNRqPRaEYdWqxqNBqNRqPRaDQajWbUocWqRqPRaDQajUaj0WhGHVqsajQajUaj0Wg0Go1m1KHFqkaj0Wg0Go1Go9FoRh1arGo0Go1Go9FoNBqNZtShxapGo9FoNBqNRqPRaEYdWqxqNBqNRqPRaDQajWbUocWqRqPRaDQajUaj0WhGHVqsajQajUaj0Wg0Go1m1KHFqkaj0Wg0Go1Go9FoRh37XawKIRYLIbYIIeqEED/d38fXaDQajUaj0Wg0Gs3oZ7+KVSGEGbgJOAGYDHxNCDF5f7ZBo9FoNBqNRqPRaDSjn/3tWZ0L1Ekpt0spE8ADwKn7uQ0ajUaj0Wg0Go1Goxnl7G+xWgo0DXvfPLBtBEKIi4UQ7wgh3unq6tpvjdNoNBqNRqPRaDQazejAsp+PJ/awTe62QcpbgVsBhBBdQoiGz7phe0E+0H2gG6H5RGibZTbafpmJtlvmom2XuWjbZTbafpmHttmnp3JPG/e3WG0Gyoe9LwNaP+wHUsqCz7RFe4kQ4h0p5cEHuh2aj4+2WWaj7ZeZaLtlLtp2mYu2XWaj7Zd5aJvte/Z3GPBKYJwQoloIYQO+Cjy5n9ug0Wg0Go1Go9FoNJpRzn71rEopU0KI7wHPA2bgDinlhv3ZBo1Go9FoNBqNRqPRjH72dxgwUspngWf393E/Q2490A3QfGK0zTIbbb/MRNstc9G2y1y07TIbbb/MQ9tsHyOk3K2+kUaj0Wg0Go1Go9FoNAeU/Z2zqtFoNBqNRqPRaDQazUeixapGo9FoNBqNRqPRaEYdWqxqNBqNRqPRaDQajWbUocXqRyCEEAe6DZpPjhDiCiHEcQOvtQ0zDG2zzEP3ucxG2ywz0f0us9E2y0x0v9u/aLH6AQghThVC3AXMONBt0Xx8hBDHCSGeB64Cvg4gdRWxjEH3u8xD97nMRve5zET3u8xG97vMRPe7A8N+X7pmNCOEEFJKKYQ4EvgNkAQOEUI0SCn9B7h5mg9gYFbLClwNLAR+C9iAOUIIK5DSD5PRi+53mYfuc5mN7nOZie53mY3ud5mJ7ncHHr10zQCDD5GB11VAHJiEmjn5p5TytQPXOs0H8T67zZFSrhx4vRC4Q0pZc0AbqPlQdL/LPHSfy2x0n8tMdL/LbHS/y0x0vxsd6DBgQAjxPeAxIcTlQogxUsqdUso2KeXLQAewUAhReoCbqXkf77Nb8bCHiHXgwb9dCHHCgW2l5oPQ/S7z0H0us9F9LjPR/S6z0f0uM9H9bvTwhRerQojTgQuAG4HpwC+EEDOHfeVeYDww732/0wnVB5A92O3nQojB3I+UECIXaADSB6iJmg9B97vMQ/e5zEb3ucxE97vMRve7zET3u9HFF16soh4QN0spXwF+BewAfjD4oZRyLbASmCqEOEoIcdXAdh0/fWDZk90uA2UbKWUv4ASOBBBC6Ht9dKH7Xeah+1xmo/tcZqL7XWaj+11movvdKOILe3GHzVptB84BkFI2AM8AbiHEl4Z9/X7gIuBBIP99v9fsRz6h3f4FzBVCOKSUxv5tqQZ27ye6341+9tJmus8dYHSfy0x0v/t8oftdZqL73ejkCyNWhRC+Ya/FsFmrR4CIEOLUgfdtwKvAZKHwAH8B1gHTpZRXgp712l98WrsNbHMCD6DDNA4kIyqO636XEXwqmw1s033uwGMd/kb3uYzhU9ltYJvud6MAIYR58LXud5nDp7HbwDbd7/YTn3uxKoSYJ4R4ArhNCPFNIYRdSimH3Zx+4N/AdwfEUADwAI6BmzYGXCalPElK2XZgzuKLx17YzT7sYfOElPI2KWXyAJzCFxohxHwhxL3AtUKIcYN2E0IMCiHd70YZe2Ez3edGAUKIQ4QQDwPXCyEm6z6XGeyF3XS/GwUM2O/XAFLK9LDtg4JG97tRyF7YTfe7A8DnWqwKIaYDN6FmSB4BjgJqYcTN6QSeR82a3CqEKAEOQq1/hZQyJaXs3M9N/0Kzl3ZLDe5n+ANIs/8QQkwF/go8DXQCFzO0ePagfXS/G0Xspc10nzvACCEKgb8BzwI9qNyqb4Luc6OZvbSb7ncHGCHEBcBdqKJJZw9ss8AID53ud6OMvbSb7ncHgM+1WAVmA3VSynuAFwEH0Dg4cyKE+A1q5qQIuAJVQvw+oA/43QFpsQa03TKd+cBmKeX9wG1ABDhXCDEWtP1GKdpmmc0MYKuU8p/An4DHgFOFEBMBhBDXoe03GtF2y2xaUJPpi4E/ghKfw7zjv0LbbzSi7ZZhiM9TWLxQi/TGpJQrBt4XAk2om/ECoBnYOPDvb8AdwNVSyrph+3BJKSP7u+1fZLTdMps92G8GKgfnIillnRDiGmAasAH4A0oM/VJKWT9sH9p++xFts8xGCHEaMBlYI6V8RghRALwFLJZS1gu1rML3ARdwLXA72n4HHG23zGaY/dZKKZ8eEDcmKWVSCLEUeEVK+cuB7xYCf0bb74Cj7Zb5fC48q0IIrxDiMdRMyHeEEDkAA6EVM1AFQ/5bSjkf5fo/CpgspTxnYGC26zrom3H/oe2W2ezBfrkDH9UDbwN3CCEeB+agwrndQHTAfvXafvsfbbPMRghRMGCfHwG9wD+FEF+WUnYBj6KEDigPwEtALio3TtvvAKLtltnswX53CCFOHwgDHcxx/A7wAyFEEahxjLbfgUXb7fPD50KsAgngZeA8oBU4a/ADKeVmYCLKOwewauA7gyGlJqlLTh8otN0ymz3aT0oZklL+BPge8E8p5clAHTBl0GbafgcMbbPMpgZ4U0p5hJTy76gQtR8NfHY/MFEIccyAnXpQYWxx0PY7wGi7ZTZ7st9g1d6EEMIspdwAPMxAmKgQ4oTBH2v7HTC03T4nZKxYFUJ8XQixUAiRLaWMo8JllgBbgYOFEOOHff0F4JqBnMevAlOBbtA34/5G2y2z+Qj7zR5uPynlWinlEwNvjwKWD+Yda/vtP7TNMpsB+y0SQvz/9u4uVLOqjuP49884iI4vRDlYSA7iDA3BKBjRRaHjpIRERDRdRCJGCZkjEVlQhKFeSBdmYpJCZHoRCBFEVF6JlBKE4kvWRcQpUXtRkBhzZsJzfl2s7fBgTPN69rPX7O8HhjPPPnsf1ub3cM7zX2uvtU6nddo9MBzfQJsa8dxw6rO0bRTurKoLgV20zr2NYH5jM7e+HUF+zw6vCwhAks8B11TVq8BFiyNzGoe5nZy6mrM6vLnOpU10XqM9uraJtuz3K8M5W2nzHA8kuXU4dhpwH7AZ2ADcmOQP49/BPJlb344yv/1Jblu49hLawiGrwHWLc0C0fsysb4fLbxgRWK2qzwAfS/KphWu/CmyjPZny+SR/HP8O5snc+nac+Z0PfAd4O/DFJL8f/w7mydxOft30HgxvtgBnAi8m2QVcT3sO/d43z0vyJ1pvyjur7RV4epJ9wLXANUk+bMEzHnPr2zHk966qunDoaAD4C3Bzkl0WPeMws74dJr/73nL6lbS5xVTVuQBJvg1cn+SDFjzjMbe+HUd+5wzH/gXcnuRSC57xmNs8nHL4U5ar2t5HtwAbquoXwFm0Hv83l5q+EXipqi5N8uhw/KdVtR34JXBGVe0cfvn/fTl3MT/m1rfjzO9XtPwuHzoYHl3OXcyLmfXtWPIDXgNWqm1u/4mq+kiSF5L8Zxn3MEfm1rcTlN9VSZ6nLVKnEZjbvEx6ZLXa9gpPAG+jLfZxK20j5Z1V9X44uIHvLcC3Fq7bDXwDeATYYS/luMytbycwP0fCR2JmfTuW/IY5WJ+ljRScBexM8sL//HCtG3Pr2wnM7/nRGz9j5jY/k56zWlUfArYkeXB4fQ9tcvQ+YE+SS6pNhN4M3AV8LcnKcB1Jfr2kps+aufXN/PpjZn07hvxuoj0ZtQd4IMmTy2n5vJlb38yvT+Y2P5MeWaX1nDw09IgAPAa8O8n9tKH/PWkr5Z0HrCZZgfbByw9fS2VufTO//phZ344mv7Ukf03y5yRf8oPXUplb38yvT+Y2M5MuVpO8nuRA2ga+AFcALw//vxbYXlU/p+1T5htwIsytb+bXHzPr21Hm9wQcXAFTS2RufTO/Ppnb/Ex+gSU4+Kx5aBtl/2w4vBf4Om3vzZUkLy6peToEc+ub+fXHzPp2NPllynN4Zsbc+mZ+fTK3+Zj0yOqCNdoG2a8AO4Yek2/Shvd/44evyTK3vplff8ysb+bXJ3Prm/n1ydxmYtILLC2qqg8Ajw//fpjkB0tuko6AufXN/PpjZn0zvz6ZW9/Mr0/mNg89FavnAVcDdyQ5sOz26MiYW9/Mrz9m1jfz65O59c38+mRu89BNsSpJkiRJmo9e5qxKkiRJkmbEYlWSJEmSNDkWq5IkSZKkybFYlSRJkiRNjsWqJEnrrKpWq+qpqnquqp6uqi9X1f/9G1xVW6rq02O1UZKkqbFYlSRp/e1LcnGS9wJXAFcBNx/mmi2AxaokabbcukaSpHVWVa8lOWPh9QXA74B3AOcDDwKbhm/fkOTxqvotsB1YAX4E3AXcDlwGnAp8L8m9o92EJEkjs1iVJGmdvbVYHY69CrwH2AusJdlfVVuBHyd5X1VdBnwlyUeH868DNie5rapOBR4DdidZGfVmJEkaySnLboAkSTNVw9eNwN1VdTGwCmw7xPlXAjuq6pPD67OBrbSRV0mSTjoWq5IkjWx4DHgV+Cdt7uo/gItoa0nsP9RlwJ4kD4/SSEmSlswFliRJGlFVnQN8H7g7bS7O2cDfkqwBVwMbhlP3AmcuXPow8IWq2jj8nG1VtQlJkk5SjqxKkrT+Tquqp2iP/L5BW1DpjuF79wA/qardwCPAv4fjzwBvVNXTwP3Ad2krBD9ZVQW8DHx8rBuQJGlsLrAkSZIkSZocHwOWJEmSJE2OxaokSZIkaXIsViVJkiRJk2OxKkmSJEmaHItVSZIkSdLkWKxKkiRJkibHYlWSJEmSNDkWq5IkSZKkyfkv30fDbJ7SPL4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(mult_df / mult_df.iloc[0] * 100).plot(figsize=(16, 9))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mean Returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GNRC    0.598098\n",
       "CPRT    0.324805\n",
       "ODFL    0.323745\n",
       "AMD     0.623055\n",
       "PAYC    0.489661\n",
       "CHTR    0.230481\n",
       "MKC     0.162225\n",
       "PG      0.153344\n",
       "PGR     0.189987\n",
       "NEM     0.137231\n",
       "CCI     0.193843\n",
       "COG    -0.137088\n",
       "dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "returns = np.log(mult_df / mult_df.shift(1))\n",
    "mean_ret = returns.mean() * 252 # 252 average trading days per year\n",
    "mean_ret"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Covarience"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GNRC</th>\n",
       "      <th>CPRT</th>\n",
       "      <th>ODFL</th>\n",
       "      <th>AMD</th>\n",
       "      <th>PAYC</th>\n",
       "      <th>CHTR</th>\n",
       "      <th>MKC</th>\n",
       "      <th>PG</th>\n",
       "      <th>PGR</th>\n",
       "      <th>NEM</th>\n",
       "      <th>CCI</th>\n",
       "      <th>COG</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>GNRC</th>\n",
       "      <td>0.159613</td>\n",
       "      <td>0.062755</td>\n",
       "      <td>0.061049</td>\n",
       "      <td>0.087651</td>\n",
       "      <td>0.087327</td>\n",
       "      <td>0.043597</td>\n",
       "      <td>0.033553</td>\n",
       "      <td>0.029501</td>\n",
       "      <td>0.041143</td>\n",
       "      <td>0.026130</td>\n",
       "      <td>0.043714</td>\n",
       "      <td>0.037308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CPRT</th>\n",
       "      <td>0.062755</td>\n",
       "      <td>0.099416</td>\n",
       "      <td>0.051345</td>\n",
       "      <td>0.067254</td>\n",
       "      <td>0.086628</td>\n",
       "      <td>0.038143</td>\n",
       "      <td>0.028973</td>\n",
       "      <td>0.026304</td>\n",
       "      <td>0.031401</td>\n",
       "      <td>0.017898</td>\n",
       "      <td>0.034677</td>\n",
       "      <td>0.029454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ODFL</th>\n",
       "      <td>0.061049</td>\n",
       "      <td>0.051345</td>\n",
       "      <td>0.100928</td>\n",
       "      <td>0.065668</td>\n",
       "      <td>0.063107</td>\n",
       "      <td>0.035235</td>\n",
       "      <td>0.028407</td>\n",
       "      <td>0.023554</td>\n",
       "      <td>0.037729</td>\n",
       "      <td>0.016320</td>\n",
       "      <td>0.030777</td>\n",
       "      <td>0.026825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMD</th>\n",
       "      <td>0.087651</td>\n",
       "      <td>0.067254</td>\n",
       "      <td>0.065668</td>\n",
       "      <td>0.310878</td>\n",
       "      <td>0.115725</td>\n",
       "      <td>0.056770</td>\n",
       "      <td>0.035622</td>\n",
       "      <td>0.031541</td>\n",
       "      <td>0.043595</td>\n",
       "      <td>0.035976</td>\n",
       "      <td>0.042983</td>\n",
       "      <td>0.035392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAYC</th>\n",
       "      <td>0.087327</td>\n",
       "      <td>0.086628</td>\n",
       "      <td>0.063107</td>\n",
       "      <td>0.115725</td>\n",
       "      <td>0.226168</td>\n",
       "      <td>0.052201</td>\n",
       "      <td>0.042189</td>\n",
       "      <td>0.033631</td>\n",
       "      <td>0.054628</td>\n",
       "      <td>0.022705</td>\n",
       "      <td>0.058568</td>\n",
       "      <td>0.039046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHTR</th>\n",
       "      <td>0.043597</td>\n",
       "      <td>0.038143</td>\n",
       "      <td>0.035235</td>\n",
       "      <td>0.056770</td>\n",
       "      <td>0.052201</td>\n",
       "      <td>0.084478</td>\n",
       "      <td>0.023507</td>\n",
       "      <td>0.025966</td>\n",
       "      <td>0.028844</td>\n",
       "      <td>0.015235</td>\n",
       "      <td>0.035133</td>\n",
       "      <td>0.023732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MKC</th>\n",
       "      <td>0.033553</td>\n",
       "      <td>0.028973</td>\n",
       "      <td>0.028407</td>\n",
       "      <td>0.035622</td>\n",
       "      <td>0.042189</td>\n",
       "      <td>0.023507</td>\n",
       "      <td>0.067610</td>\n",
       "      <td>0.033964</td>\n",
       "      <td>0.031042</td>\n",
       "      <td>0.019189</td>\n",
       "      <td>0.039238</td>\n",
       "      <td>0.022557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PG</th>\n",
       "      <td>0.029501</td>\n",
       "      <td>0.026304</td>\n",
       "      <td>0.023554</td>\n",
       "      <td>0.031541</td>\n",
       "      <td>0.033631</td>\n",
       "      <td>0.025966</td>\n",
       "      <td>0.033964</td>\n",
       "      <td>0.049657</td>\n",
       "      <td>0.030195</td>\n",
       "      <td>0.012378</td>\n",
       "      <td>0.034569</td>\n",
       "      <td>0.026913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PGR</th>\n",
       "      <td>0.041143</td>\n",
       "      <td>0.031401</td>\n",
       "      <td>0.037729</td>\n",
       "      <td>0.043595</td>\n",
       "      <td>0.054628</td>\n",
       "      <td>0.028844</td>\n",
       "      <td>0.031042</td>\n",
       "      <td>0.030195</td>\n",
       "      <td>0.073633</td>\n",
       "      <td>0.014716</td>\n",
       "      <td>0.035560</td>\n",
       "      <td>0.027867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEM</th>\n",
       "      <td>0.026130</td>\n",
       "      <td>0.017898</td>\n",
       "      <td>0.016320</td>\n",
       "      <td>0.035976</td>\n",
       "      <td>0.022705</td>\n",
       "      <td>0.015235</td>\n",
       "      <td>0.019189</td>\n",
       "      <td>0.012378</td>\n",
       "      <td>0.014716</td>\n",
       "      <td>0.106692</td>\n",
       "      <td>0.020386</td>\n",
       "      <td>0.015366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CCI</th>\n",
       "      <td>0.043714</td>\n",
       "      <td>0.034677</td>\n",
       "      <td>0.030777</td>\n",
       "      <td>0.042983</td>\n",
       "      <td>0.058568</td>\n",
       "      <td>0.035133</td>\n",
       "      <td>0.039238</td>\n",
       "      <td>0.034569</td>\n",
       "      <td>0.035560</td>\n",
       "      <td>0.020386</td>\n",
       "      <td>0.076781</td>\n",
       "      <td>0.026011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COG</th>\n",
       "      <td>0.037308</td>\n",
       "      <td>0.029454</td>\n",
       "      <td>0.026825</td>\n",
       "      <td>0.035392</td>\n",
       "      <td>0.039046</td>\n",
       "      <td>0.023732</td>\n",
       "      <td>0.022557</td>\n",
       "      <td>0.026913</td>\n",
       "      <td>0.027867</td>\n",
       "      <td>0.015366</td>\n",
       "      <td>0.026011</td>\n",
       "      <td>0.153033</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          GNRC      CPRT      ODFL       AMD      PAYC      CHTR       MKC  \\\n",
       "GNRC  0.159613  0.062755  0.061049  0.087651  0.087327  0.043597  0.033553   \n",
       "CPRT  0.062755  0.099416  0.051345  0.067254  0.086628  0.038143  0.028973   \n",
       "ODFL  0.061049  0.051345  0.100928  0.065668  0.063107  0.035235  0.028407   \n",
       "AMD   0.087651  0.067254  0.065668  0.310878  0.115725  0.056770  0.035622   \n",
       "PAYC  0.087327  0.086628  0.063107  0.115725  0.226168  0.052201  0.042189   \n",
       "CHTR  0.043597  0.038143  0.035235  0.056770  0.052201  0.084478  0.023507   \n",
       "MKC   0.033553  0.028973  0.028407  0.035622  0.042189  0.023507  0.067610   \n",
       "PG    0.029501  0.026304  0.023554  0.031541  0.033631  0.025966  0.033964   \n",
       "PGR   0.041143  0.031401  0.037729  0.043595  0.054628  0.028844  0.031042   \n",
       "NEM   0.026130  0.017898  0.016320  0.035976  0.022705  0.015235  0.019189   \n",
       "CCI   0.043714  0.034677  0.030777  0.042983  0.058568  0.035133  0.039238   \n",
       "COG   0.037308  0.029454  0.026825  0.035392  0.039046  0.023732  0.022557   \n",
       "\n",
       "            PG       PGR       NEM       CCI       COG  \n",
       "GNRC  0.029501  0.041143  0.026130  0.043714  0.037308  \n",
       "CPRT  0.026304  0.031401  0.017898  0.034677  0.029454  \n",
       "ODFL  0.023554  0.037729  0.016320  0.030777  0.026825  \n",
       "AMD   0.031541  0.043595  0.035976  0.042983  0.035392  \n",
       "PAYC  0.033631  0.054628  0.022705  0.058568  0.039046  \n",
       "CHTR  0.025966  0.028844  0.015235  0.035133  0.023732  \n",
       "MKC   0.033964  0.031042  0.019189  0.039238  0.022557  \n",
       "PG    0.049657  0.030195  0.012378  0.034569  0.026913  \n",
       "PGR   0.030195  0.073633  0.014716  0.035560  0.027867  \n",
       "NEM   0.012378  0.014716  0.106692  0.020386  0.015366  \n",
       "CCI   0.034569  0.035560  0.020386  0.076781  0.026011  \n",
       "COG   0.026913  0.027867  0.015366  0.026011  0.153033  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "returns.cov() * 252"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Correlation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GNRC</th>\n",
       "      <th>CPRT</th>\n",
       "      <th>ODFL</th>\n",
       "      <th>AMD</th>\n",
       "      <th>PAYC</th>\n",
       "      <th>CHTR</th>\n",
       "      <th>MKC</th>\n",
       "      <th>PG</th>\n",
       "      <th>PGR</th>\n",
       "      <th>NEM</th>\n",
       "      <th>CCI</th>\n",
       "      <th>COG</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>GNRC</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.498180</td>\n",
       "      <td>0.480992</td>\n",
       "      <td>0.393483</td>\n",
       "      <td>0.459618</td>\n",
       "      <td>0.375450</td>\n",
       "      <td>0.322995</td>\n",
       "      <td>0.331365</td>\n",
       "      <td>0.379509</td>\n",
       "      <td>0.200235</td>\n",
       "      <td>0.394875</td>\n",
       "      <td>0.238711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CPRT</th>\n",
       "      <td>0.498180</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.512578</td>\n",
       "      <td>0.382553</td>\n",
       "      <td>0.577717</td>\n",
       "      <td>0.416206</td>\n",
       "      <td>0.353394</td>\n",
       "      <td>0.374370</td>\n",
       "      <td>0.367005</td>\n",
       "      <td>0.173780</td>\n",
       "      <td>0.396908</td>\n",
       "      <td>0.238795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ODFL</th>\n",
       "      <td>0.480992</td>\n",
       "      <td>0.512578</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.370726</td>\n",
       "      <td>0.417694</td>\n",
       "      <td>0.381583</td>\n",
       "      <td>0.343890</td>\n",
       "      <td>0.332705</td>\n",
       "      <td>0.437657</td>\n",
       "      <td>0.157272</td>\n",
       "      <td>0.349614</td>\n",
       "      <td>0.215847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMD</th>\n",
       "      <td>0.393483</td>\n",
       "      <td>0.382553</td>\n",
       "      <td>0.370726</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.436432</td>\n",
       "      <td>0.350311</td>\n",
       "      <td>0.245704</td>\n",
       "      <td>0.253855</td>\n",
       "      <td>0.288142</td>\n",
       "      <td>0.197539</td>\n",
       "      <td>0.278212</td>\n",
       "      <td>0.162262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAYC</th>\n",
       "      <td>0.459618</td>\n",
       "      <td>0.577717</td>\n",
       "      <td>0.417694</td>\n",
       "      <td>0.436432</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.377648</td>\n",
       "      <td>0.341179</td>\n",
       "      <td>0.317347</td>\n",
       "      <td>0.423311</td>\n",
       "      <td>0.146166</td>\n",
       "      <td>0.444448</td>\n",
       "      <td>0.209878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHTR</th>\n",
       "      <td>0.375450</td>\n",
       "      <td>0.416206</td>\n",
       "      <td>0.381583</td>\n",
       "      <td>0.350311</td>\n",
       "      <td>0.377648</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.311047</td>\n",
       "      <td>0.400908</td>\n",
       "      <td>0.365723</td>\n",
       "      <td>0.160468</td>\n",
       "      <td>0.436236</td>\n",
       "      <td>0.208718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MKC</th>\n",
       "      <td>0.322995</td>\n",
       "      <td>0.353394</td>\n",
       "      <td>0.343890</td>\n",
       "      <td>0.245704</td>\n",
       "      <td>0.341179</td>\n",
       "      <td>0.311047</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.586171</td>\n",
       "      <td>0.439961</td>\n",
       "      <td>0.225935</td>\n",
       "      <td>0.544592</td>\n",
       "      <td>0.221761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PG</th>\n",
       "      <td>0.331365</td>\n",
       "      <td>0.374370</td>\n",
       "      <td>0.332705</td>\n",
       "      <td>0.253855</td>\n",
       "      <td>0.317347</td>\n",
       "      <td>0.400908</td>\n",
       "      <td>0.586171</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.499345</td>\n",
       "      <td>0.170056</td>\n",
       "      <td>0.559846</td>\n",
       "      <td>0.308733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PGR</th>\n",
       "      <td>0.379509</td>\n",
       "      <td>0.367005</td>\n",
       "      <td>0.437657</td>\n",
       "      <td>0.288142</td>\n",
       "      <td>0.423311</td>\n",
       "      <td>0.365723</td>\n",
       "      <td>0.439961</td>\n",
       "      <td>0.499345</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.166027</td>\n",
       "      <td>0.472930</td>\n",
       "      <td>0.262522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEM</th>\n",
       "      <td>0.200235</td>\n",
       "      <td>0.173780</td>\n",
       "      <td>0.157272</td>\n",
       "      <td>0.197539</td>\n",
       "      <td>0.146166</td>\n",
       "      <td>0.160468</td>\n",
       "      <td>0.225935</td>\n",
       "      <td>0.170056</td>\n",
       "      <td>0.166027</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.225235</td>\n",
       "      <td>0.120258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CCI</th>\n",
       "      <td>0.394875</td>\n",
       "      <td>0.396908</td>\n",
       "      <td>0.349614</td>\n",
       "      <td>0.278212</td>\n",
       "      <td>0.444448</td>\n",
       "      <td>0.436236</td>\n",
       "      <td>0.544592</td>\n",
       "      <td>0.559846</td>\n",
       "      <td>0.472930</td>\n",
       "      <td>0.225235</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.239958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COG</th>\n",
       "      <td>0.238711</td>\n",
       "      <td>0.238795</td>\n",
       "      <td>0.215847</td>\n",
       "      <td>0.162262</td>\n",
       "      <td>0.209878</td>\n",
       "      <td>0.208718</td>\n",
       "      <td>0.221761</td>\n",
       "      <td>0.308733</td>\n",
       "      <td>0.262522</td>\n",
       "      <td>0.120258</td>\n",
       "      <td>0.239958</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          GNRC      CPRT      ODFL       AMD      PAYC      CHTR       MKC  \\\n",
       "GNRC  1.000000  0.498180  0.480992  0.393483  0.459618  0.375450  0.322995   \n",
       "CPRT  0.498180  1.000000  0.512578  0.382553  0.577717  0.416206  0.353394   \n",
       "ODFL  0.480992  0.512578  1.000000  0.370726  0.417694  0.381583  0.343890   \n",
       "AMD   0.393483  0.382553  0.370726  1.000000  0.436432  0.350311  0.245704   \n",
       "PAYC  0.459618  0.577717  0.417694  0.436432  1.000000  0.377648  0.341179   \n",
       "CHTR  0.375450  0.416206  0.381583  0.350311  0.377648  1.000000  0.311047   \n",
       "MKC   0.322995  0.353394  0.343890  0.245704  0.341179  0.311047  1.000000   \n",
       "PG    0.331365  0.374370  0.332705  0.253855  0.317347  0.400908  0.586171   \n",
       "PGR   0.379509  0.367005  0.437657  0.288142  0.423311  0.365723  0.439961   \n",
       "NEM   0.200235  0.173780  0.157272  0.197539  0.146166  0.160468  0.225935   \n",
       "CCI   0.394875  0.396908  0.349614  0.278212  0.444448  0.436236  0.544592   \n",
       "COG   0.238711  0.238795  0.215847  0.162262  0.209878  0.208718  0.221761   \n",
       "\n",
       "            PG       PGR       NEM       CCI       COG  \n",
       "GNRC  0.331365  0.379509  0.200235  0.394875  0.238711  \n",
       "CPRT  0.374370  0.367005  0.173780  0.396908  0.238795  \n",
       "ODFL  0.332705  0.437657  0.157272  0.349614  0.215847  \n",
       "AMD   0.253855  0.288142  0.197539  0.278212  0.162262  \n",
       "PAYC  0.317347  0.423311  0.146166  0.444448  0.209878  \n",
       "CHTR  0.400908  0.365723  0.160468  0.436236  0.208718  \n",
       "MKC   0.586171  0.439961  0.225935  0.544592  0.221761  \n",
       "PG    1.000000  0.499345  0.170056  0.559846  0.308733  \n",
       "PGR   0.499345  1.000000  0.166027  0.472930  0.262522  \n",
       "NEM   0.170056  0.166027  1.000000  0.225235  0.120258  \n",
       "CCI   0.559846  0.472930  0.225235  1.000000  0.239958  \n",
       "COG   0.308733  0.262522  0.120258  0.239958  1.000000  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "returns.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate Random Weights Equal to 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Weights : [0.02125654 0.0863398  0.10370128 0.07141497 0.13453457 0.11800204\n",
      " 0.06616309 0.09840712 0.07043698 0.13111772 0.08559052 0.01303537]\n",
      "Total Weight : 1.0\n"
     ]
    }
   ],
   "source": [
    "# Generate 11 random values that sum to 1\n",
    "weights = np.random.random(num_stocks)\n",
    "weights /= np.sum(weights)\n",
    "print('Weights :', weights)\n",
    "print('Total Weight :', np.sum(weights))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculating Return of Portfolio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.28390185446891075"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Provide return of portfolio using random weights over the whole dataset\n",
    "np.sum(weights * returns.mean()) * 252"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculating Volatility"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.2155872767446207"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(np.dot(weights.T, np.dot(returns.cov() * 252, weights)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analyzing Returns & Risks of 10000 Combinations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0.22366768, 0.23713079, 0.27917645, ..., 0.25094577, 0.3137677 ,\n",
       "        0.27602019]),\n",
       " array([0.21091707, 0.21099248, 0.21953026, ..., 0.2001485 , 0.23880335,\n",
       "        0.2260317 ]),\n",
       " array([1.00118818, 1.06463888, 1.21475945, ..., 1.19134431, 1.26157233,\n",
       "        1.16585501]),\n",
       " array([[0.0099252 , 0.17746138, 0.18036987, ..., 0.03476538, 0.1236237 ,\n",
       "         0.14245444],\n",
       "        [0.00826212, 0.02766726, 0.00626476, ..., 0.15894628, 0.01553257,\n",
       "         0.06621301],\n",
       "        [0.07874556, 0.09581541, 0.10071715, ..., 0.09381277, 0.08243235,\n",
       "         0.09325075],\n",
       "        ...,\n",
       "        [0.0783439 , 0.05438719, 0.09017437, ..., 0.10600157, 0.09038185,\n",
       "         0.05181441],\n",
       "        [0.06976678, 0.00944471, 0.10398129, ..., 0.13647668, 0.10225679,\n",
       "         0.06320932],\n",
       "        [0.1101336 , 0.02937373, 0.01068159, ..., 0.08448402, 0.13293521,\n",
       "         0.10129792]]))"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p_ret = [] # Returns list\n",
    "p_vol = [] # Volatility list\n",
    "p_SR = [] # Sharpe Ratio list\n",
    "p_wt = [] # Stock weights list\n",
    "\n",
    "\n",
    "for x in range(10000):\n",
    "    # Generate random weights\n",
    "    p_weights = np.random.random(num_stocks)\n",
    "    p_weights /= np.sum(p_weights)\n",
    "    \n",
    "    # Add return using those weights to list\n",
    "    ret_1 = np.sum(p_weights * returns.mean()) * 252\n",
    "    p_ret.append(ret_1)\n",
    "    \n",
    "    # Add volatility or standard deviation to list\n",
    "    vol_1 = np.sqrt(np.dot(p_weights.T, np.dot(returns.cov() * 252, p_weights)))\n",
    "    p_vol.append(vol_1)\n",
    "    \n",
    "    # Get Sharpe ratio\n",
    "    SR_1 = (ret_1 - risk_free_rate) / vol_1\n",
    "    p_SR.append(SR_1)\n",
    "    \n",
    "    # Store the weights for each portfolio\n",
    "    p_wt.append(p_weights)\n",
    "    \n",
    "# Convert to Numpy arrays\n",
    "p_ret = np.array(p_ret)\n",
    "p_vol = np.array(p_vol)\n",
    "p_SR = np.array(p_SR)\n",
    "p_wt = np.array(p_wt)\n",
    "\n",
    "p_ret, p_vol, p_SR, p_wt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting the Efficient Frontier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x288f06daa00>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a dataframe with returns and volatility\n",
    "ports = pd.DataFrame({'Return': p_ret, 'Volatility': p_vol})\n",
    "\n",
    "ports.plot(x='Volatility', y='Return', kind='scatter', figsize=(16, 9))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sharpe Ratio"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "People want to maximize returns while avoiding as much risk as possible. William Sharpe created the Sharpe Ratio to find the portfolio that provides the best return for the lowest amount of risk. \n",
    "\n",
    "*Sharpe Ratio* = $\\frac{r_i - r_f}{\\sigma_i}$\n",
    "\n",
    "$r_f = $ Risk Free Rate\n",
    "\n",
    "$r_i = $ Rate of Return of the stock\n",
    "\n",
    "$\\sigma_i = $ Standard Deviation of the Stock\n",
    "\n",
    "As return increases so does the Sharpe Ratio, but as Standard Deviation increase the Sharpe Ration decreases."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stock : GNRC : 23.90\n",
      "Stock : CPRT : 6.24\n",
      "Stock : ODFL : 10.34\n",
      "Stock : AMD : 16.55\n",
      "Stock : PAYC : 5.04\n",
      "Stock : CHTR : 0.43\n",
      "Stock : MKC : 11.31\n",
      "Stock : PG : 7.49\n",
      "Stock : PGR : 9.51\n",
      "Stock : NEM : 4.66\n",
      "Stock : CCI : 1.99\n",
      "Stock : COG : 2.53\n",
      "\n",
      "Volatility : 0.24982450395435044\n",
      "Return : 0.38018664879640185\n"
     ]
    }
   ],
   "source": [
    "# Return the index of the largest Sharpe Ratio\n",
    "SR_idx = np.argmax(p_SR)\n",
    "\n",
    "# Find the ideal portfolio weighting at that index\n",
    "i = 0\n",
    "while i < num_stocks:\n",
    "    print(\"Stock : %s : %2.2f\" % (port_list[i], (p_wt[SR_idx][i] * 100)))\n",
    "    i += 1\n",
    "    \n",
    "# Find volatility of that portfolio\n",
    "print(\"\\nVolatility :\", p_vol[SR_idx])\n",
    "      \n",
    "# Find return of that portfolio\n",
    "print(\"Return :\", p_ret[SR_idx])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get Number of Shares & Cost Based on Weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# I'm going to use a similar portfolio that has slightly easier percents to work with\n",
    "\n",
    "# Calculated Weighting\n",
    "# Stock : GNRC : 21.90 \n",
    "# Stock : CPRT : 15.63 \n",
    "# Stock : ODFL : 23.83\n",
    "# Stock : AMD : 11.09\n",
    "# Stock : PAYC : 1.86\n",
    "# Stock : CHTR : 3.55\n",
    "# Stock : MKC : 2.87\n",
    "# Stock : PG : 1.09\n",
    "# Stock : PGR : 2.86\n",
    "# Stock : NEM : 10.11\n",
    "# Stock : CCI : 4.34\n",
    "# Stock : COG : 0.87"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Find percentage closest to 1 and use it as the basis for calculating all other shares\n",
    "Since PG is 1% : GNRC is 21.90 : Multiply cost of PG (118.20) by 22 (21.9 Rounded up) and then divide \n",
    "that by the cost of GNRC to get the shares to buy for GNRC\n",
    "\n",
    "118.20 * 22 = 2,600.4 / 102.01 = 25.49 (25 Shares) * 102.01 = \n",
    "\n",
    "In situations in which prices don't work either discard stock or force 1 share"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_port_shares(one_price, force_one, wts, prices):\n",
    "    # Gets number of stocks to analyze\n",
    "    num_stocks = len(wts)\n",
    "    \n",
    "    # Holds the number of shares for each\n",
    "    shares = []\n",
    "    \n",
    "    # Holds Cost of shares for each\n",
    "    cost_shares = []\n",
    "    \n",
    "    i = 0\n",
    "    while i < num_stocks:\n",
    "        # Get max amount to spend on stock \n",
    "        max_price = one_price * wts[i]\n",
    "        \n",
    "        # Gets number of shares to buy and adds them to list\n",
    "        num_shares = int(max_price / prices[i])\n",
    "        \n",
    "        # If the user wants to force buying one share do it\n",
    "        if(force_one & (num_shares == 0)):\n",
    "            num_shares = 1\n",
    "        \n",
    "        shares.append(num_shares)\n",
    "        \n",
    "        # Gets cost of those shares and appends to list\n",
    "        cost = num_shares * prices[i]\n",
    "        cost_shares.append(cost)\n",
    "        i += 1\n",
    "        \n",
    "    return shares, cost_shares"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get Portfolio Weighting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_port_weighting(share_cost):\n",
    "    \n",
    "    # Holds weights for stocks\n",
    "    stock_wts = []\n",
    "    # All values summed\n",
    "    tot_val = sum(share_cost)\n",
    "    print(\"Total Investment :\", tot_val)\n",
    "    \n",
    "    for x in share_cost:\n",
    "        stock_wts.append(x / tot_val)\n",
    "    return stock_wts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Returns the Value of Portfolio by Date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_port_val_by_date(date, shares, tickers):\n",
    "    port_prices = merge_df_by_column_name('Adj Close',  date, \n",
    "                                  date, *port_list)\n",
    "    # Convert from dataframe to Python list\n",
    "    port_prices = port_df_start.values.tolist()\n",
    "    # Trick that converts a list of lists into a single list\n",
    "    port_prices = sum(port_prices, [])\n",
    "    return port_prices"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Approximate Portfolio Weighting Based on Request"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shares : [25, 20, 22, 26, 1, 1, 4, 1, 5, 28, 3, 7]\n",
      "Share Cost : [2550.250053405762, 1869.6000671386719, 2801.878051757813, 1276.5999603271484, 271.79998779296875, 490.42999267578125, 327.7214050292969, 118.2088623046875, 341.39949798583984, 1168.7718505859377, 405.90911865234364, 115.7245979309082]\n",
      "Total Investment : 11738.293445587158\n",
      "Stock Weights : [0.21725901343559373, 0.1592735840013883, 0.23869551947614145, 0.10875515817054887, 0.02315498322246732, 0.041780348646859845, 0.027918999175514648, 0.010070361833484953, 0.029084253138533016, 0.09956914571984232, 0.034579908956436874, 0.00985872422318878]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[102.01000213623048,\n",
       " 93.4800033569336,\n",
       " 127.35809326171876,\n",
       " 49.099998474121094,\n",
       " 271.79998779296875,\n",
       " 490.42999267578125,\n",
       " 81.93035125732422,\n",
       " 118.2088623046875,\n",
       " 68.27989959716797,\n",
       " 41.74185180664063,\n",
       " 135.30303955078122,\n",
       " 16.532085418701172]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "port_list = [\"GNRC\", \"CPRT\", \"ODFL\", \"AMD\", \"PAYC\", \"CHTR\", \"MKC\", \n",
    "             \"PG\", \"PGR\", \"NEM\", \"CCI\", \"COG\"]\n",
    "\n",
    "port_wts = [22, 16, 24, 11, 2, 4, 3, 1, 3, 10, 4, 1]\n",
    "\n",
    "# Get all stock prices on the starting date\n",
    "port_df_start = merge_df_by_column_name('Adj Close',  '2020-01-02', \n",
    "                                  '2020-01-02', *port_list)\n",
    "# Convert from dataframe to Python list\n",
    "port_prices = port_df_start.values.tolist()\n",
    "# Trick that converts a list of lists into a single list\n",
    "port_prices = sum(port_prices, [])\n",
    "\n",
    "# Calculated Weighting\n",
    "# Stock : GNRC : 21.90 \n",
    "# Stock : CPRT : 15.63 \n",
    "# Stock : ODFL : 23.83\n",
    "# Stock : AMD : 11.09\n",
    "# Stock : PAYC : 1.86\n",
    "# Stock : CHTR : 3.55\n",
    "# Stock : MKC : 2.87\n",
    "# Stock : PG : 1.09\n",
    "# Stock : PGR : 2.86\n",
    "# Stock : NEM : 10.11\n",
    "# Stock : CCI : 4.34\n",
    "# Stock : COG : 0.87\n",
    "\n",
    "tot_shares, share_cost = get_port_shares(118.20, True, port_wts, port_prices)\n",
    "print(\"Shares :\", tot_shares)\n",
    "print(\"Share Cost :\", share_cost)\n",
    "\n",
    "# Get list of weights for stocks\n",
    "stock_wts = get_port_weighting(share_cost)\n",
    "print(\"Stock Weights :\", stock_wts)\n",
    "\n",
    "# Get value at end of year\n",
    "get_port_val_by_date('2020-12-31', tot_shares, port_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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