tidy.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reshaping & Tidy Data\n",
    "\n",
    "> Structuring datasets to facilitate analysis [(Wickham 2014)](http://www.jstatsoft.org/v59/i10/paper)\n",
    "\n",
    "So, you've sat down to analyze a new dataset.\n",
    "What do you do first?\n",
    "\n",
    "In episode 11 of [Not So Standard Deviations](https://www.patreon.com/NSSDeviations?ty=h), Hilary and Roger discussed their approaches.\n",
    "I'm with Hilary on this one, you should make sure your data is tidy.\n",
    "Before you do any plots, filtering, transformations, summary statistics, regressions...\n",
    "Once you get to a tidy dataset, it's relatively easy to do all of those.\n",
    "\n",
    "Today we'll talk about what makes a dataset tidy and how to get there."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hadley Whickham (who I think is tied with Wes for number of shoutouts in this series...) kindly summarized a tidyness as a dataset where\n",
    "\n",
    "1. Each variable forms a column\n",
    "2. Each observation forms a row\n",
    "3. Each type of observational unit forms a table\n",
    "\n",
    "And most of the time it's just the first two that matter.\n",
    "As quoted at the top, this really is about facilitating analysis: going as quickly as possible from question to answser.\n",
    "\n",
    "We'll cover a few methods that help you get you there."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "pd.options.display.max_rows = 10\n",
    "sns.set(style='ticks', context='talk')\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NBA Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Note: I'm reusing this example from an [earlier post](tidy-data.html).*\n",
    "\n",
    "Based on [this](http://stackoverflow.com/questions/22695680/python-pandas-timedelta-specific-rows) StackOverflow question.\n",
    "We'll grab some NBA game data from basketball-reference.com using pandas' `read_html` function, which returns a list of DataFrames."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"0\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Start (ET)</th>\n",
       "      <th>Unnamed: 2</th>\n",
       "      <th>Visitor/Neutral</th>\n",
       "      <th>PTS</th>\n",
       "      <th>Home/Neutral</th>\n",
       "      <th>PTS.1</th>\n",
       "      <th>Unnamed: 7</th>\n",
       "      <th>Notes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>October</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Tue, Oct 27, 2015</td>\n",
       "      <td>8:00 pm</td>\n",
       "      <td>Box Score</td>\n",
       "      <td>Detroit Pistons</td>\n",
       "      <td>106.0</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>94.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Tue, Oct 27, 2015</td>\n",
       "      <td>8:00 pm</td>\n",
       "      <td>Box Score</td>\n",
       "      <td>Cleveland Cavaliers</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Chicago Bulls</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Tue, Oct 27, 2015</td>\n",
       "      <td>10:30 pm</td>\n",
       "      <td>Box Score</td>\n",
       "      <td>New Orleans Pelicans</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Golden State Warriors</td>\n",
       "      <td>111.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Wed, Oct 28, 2015</td>\n",
       "      <td>7:30 pm</td>\n",
       "      <td>Box Score</td>\n",
       "      <td>Philadelphia 76ers</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Boston Celtics</td>\n",
       "      <td>112.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Date Start (ET) Unnamed: 2       Visitor/Neutral    PTS  \\\n",
       "0            October        NaN        NaN                   NaN    NaN   \n",
       "1  Tue, Oct 27, 2015    8:00 pm  Box Score       Detroit Pistons  106.0   \n",
       "2  Tue, Oct 27, 2015    8:00 pm  Box Score   Cleveland Cavaliers   95.0   \n",
       "3  Tue, Oct 27, 2015   10:30 pm  Box Score  New Orleans Pelicans   95.0   \n",
       "4  Wed, Oct 28, 2015    7:30 pm  Box Score    Philadelphia 76ers   95.0   \n",
       "\n",
       "            Home/Neutral  PTS.1 Unnamed: 7  Notes  \n",
       "0                    NaN    NaN        NaN    NaN  \n",
       "1          Atlanta Hawks   94.0        NaN    NaN  \n",
       "2          Chicago Bulls   97.0        NaN    NaN  \n",
       "3  Golden State Warriors  111.0        NaN    NaN  \n",
       "4         Boston Celtics  112.0        NaN    NaN  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tables = pd.read_html(\"http://www.basketball-reference.com/leagues/NBA_2016_games.html\")\n",
    "games = tables[0]\n",
    "\n",
    "games.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Side note: pandas' `read_html` is pretty good. On simple websites it almost always works. It provides a couple parameters for controlling what gets selected from the webpage if the defaults fail. I'll always use it first, before moving on to BeautifulSoup or lxml if the page is more complicated."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, we have a bit of general munging to do before tidying.\n",
    "Each month slips in an extra row of mostly NaNs, the column names aren't too useful, and we have some dtypes to fix up."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"0\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>away_team</th>\n",
       "      <th>away_points</th>\n",
       "      <th>home_team</th>\n",
       "      <th>home_points</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>game_id</th>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>2015-10-27</th>\n",
       "      <td>Detroit Pistons</td>\n",
       "      <td>106.0</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>94.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <th>2015-10-27</th>\n",
       "      <td>Cleveland Cavaliers</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Chicago Bulls</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <th>2015-10-27</th>\n",
       "      <td>New Orleans Pelicans</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Golden State Warriors</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <th>2015-10-28</th>\n",
       "      <td>Philadelphia 76ers</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Boston Celtics</td>\n",
       "      <td>112.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <th>2015-10-28</th>\n",
       "      <td>Chicago Bulls</td>\n",
       "      <td>115.0</td>\n",
       "      <td>Brooklyn Nets</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               away_team  away_points              home_team  \\\n",
       "game_id date                                                                   \n",
       "1       2015-10-27       Detroit Pistons        106.0          Atlanta Hawks   \n",
       "2       2015-10-27   Cleveland Cavaliers         95.0          Chicago Bulls   \n",
       "3       2015-10-27  New Orleans Pelicans         95.0  Golden State Warriors   \n",
       "4       2015-10-28    Philadelphia 76ers         95.0         Boston Celtics   \n",
       "5       2015-10-28         Chicago Bulls        115.0          Brooklyn Nets   \n",
       "\n",
       "                    home_points  \n",
       "game_id date                     \n",
       "1       2015-10-27         94.0  \n",
       "2       2015-10-27         97.0  \n",
       "3       2015-10-27        111.0  \n",
       "4       2015-10-28        112.0  \n",
       "5       2015-10-28        100.0  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "column_names = {'Date': 'date', 'Start (ET)': 'start',\n",
    "                'Unamed: 2': 'box', 'Visitor/Neutral': 'away_team', \n",
    "                'PTS': 'away_points', 'Home/Neutral': 'home_team',\n",
    "                'PTS.1': 'home_points', 'Unamed: 7': 'n_ot'}\n",
    "\n",
    "games = (games.rename(columns=column_names)\n",
    "    .dropna(thresh=4)\n",
    "    [['date', 'away_team', 'away_points', 'home_team', 'home_points']]\n",
    "    .assign(date=lambda x: pd.to_datetime(x['date'], format='%a, %b %d, %Y'))\n",
    "    .set_index('date', append=True)\n",
    "    .rename_axis([\"game_id\", \"date\"])\n",
    "    .sort_index())\n",
    "games.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A quick aside on that last block.\n",
    "\n",
    "- `dropna` has a `thresh`old argument. If at least `thresh` items are missing, the row is dropped. We used it to remove the \"Month headers\" that slipped into the table\n",
    "- `assign` can take a callable. This lets us refer to the column in the previous step of the chain. Otherwise we would have to assign `temp_df = games.dropna()...` And then do the `pd.to_datetime` on that.\n",
    "- `set_index` has an `append` keyword. We keep the original index around since it will be our unique identifier per game\n",
    "- We use `.rename_axis` to set the index names (this behavior is new in pandas 0.18; before `.rename_axis` only took a mapping for changine labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Question:\n",
    "> **How many days of rest did each team get between each game?**\n",
    "\n",
    "Whether or not your dataset is tidy depends on your question. Given our question, what is an observation?\n",
    "\n",
    "In this case, an observation is a `(team, game)` pair. Unfortunately we don't have that yet. We have two observations per row, one for home and one for away. We'll fix that with `pd.melt`.\n",
    "\n",
    "`melt` works by taking observations that are spread across columns (`away_team`, `home_team`), and melting them down into one column with multiple rows. However, we don't want to lose the metadata (like `game_id` and `date`) that is shared between the observations. By including those columns as `id_vars`, the values will be repeated as many times as needed to stay with their observations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"0\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>game_id</th>\n",
       "      <th>date</th>\n",
       "      <th>variable</th>\n",
       "      <th>team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-10-27</td>\n",
       "      <td>away_team</td>\n",
       "      <td>Detroit Pistons</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2015-10-27</td>\n",
       "      <td>away_team</td>\n",
       "      <td>Cleveland Cavaliers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2015-10-27</td>\n",
       "      <td>away_team</td>\n",
       "      <td>New Orleans Pelicans</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2015-10-28</td>\n",
       "      <td>away_team</td>\n",
       "      <td>Philadelphia 76ers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2015-10-28</td>\n",
       "      <td>away_team</td>\n",
       "      <td>Chicago Bulls</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   game_id       date   variable                  team\n",
       "0        1 2015-10-27  away_team       Detroit Pistons\n",
       "1        2 2015-10-27  away_team   Cleveland Cavaliers\n",
       "2        3 2015-10-27  away_team  New Orleans Pelicans\n",
       "3        4 2015-10-28  away_team    Philadelphia 76ers\n",
       "4        5 2015-10-28  away_team         Chicago Bulls"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tidy = pd.melt(games.reset_index(),\n",
    "               id_vars=['game_id', 'date'], value_vars=['away_team', 'home_team'],\n",
    "               value_name='team')\n",
    "tidy.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The DataFrame `tidy` meets our rules for tidyness: each variable is in a column, and each observation (`team`, `date` pair) is on its own row.\n",
    "Now the translation from question (\"How many days of rest\") to operation (\"date of today's game - date of previous game - 1\") is direct:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       NaN\n",
       "1       NaN\n",
       "2       NaN\n",
       "3       NaN\n",
       "4       NaN\n",
       "       ... \n",
       "2455    7.0\n",
       "2456    1.0\n",
       "2457    1.0\n",
       "2458    3.0\n",
       "2459    2.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# For each team... get number of days between games\n",
    "tidy.groupby('team')['date'].diff().dt.days - 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That's the essence of tidy data, the reason why it's worth considering what shape your data should be in.\n",
    "It's about setting yourself up for success, so that the answers naturally flow from the (just kidding, it's still difficult. But hopefully less so).\n",
    "\n",
    "Let's assign that back into our DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"0\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>game_id</th>\n",
       "      <th>date</th>\n",
       "      <th>variable</th>\n",
       "      <th>team</th>\n",
       "      <th>rest</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2015-10-28</td>\n",
       "      <td>away_team</td>\n",
       "      <td>Chicago Bulls</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>2015-10-28</td>\n",
       "      <td>away_team</td>\n",
       "      <td>Cleveland Cavaliers</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>2015-10-28</td>\n",
       "      <td>away_team</td>\n",
       "      <td>New Orleans Pelicans</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>2015-10-29</td>\n",
       "      <td>away_team</td>\n",
       "      <td>Memphis Grizzlies</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>2015-10-29</td>\n",
       "      <td>away_team</td>\n",
       "      <td>Dallas Mavericks</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    game_id       date   variable                  team  rest\n",
       "4         5 2015-10-28  away_team         Chicago Bulls   0.0\n",
       "8         9 2015-10-28  away_team   Cleveland Cavaliers   0.0\n",
       "14       15 2015-10-28  away_team  New Orleans Pelicans   0.0\n",
       "17       18 2015-10-29  away_team     Memphis Grizzlies   0.0\n",
       "18       19 2015-10-29  away_team      Dallas Mavericks   0.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tidy['rest'] = tidy.sort_values('date').groupby('team').date.diff().dt.days - 1\n",
    "tidy.dropna().head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To show the inverse of `melt`, let's take `rest` values we just calculated and place them back in the original DataFrame with a `pivot_table`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"0\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>away_team</th>\n",
       "      <th>away_points</th>\n",
       "      <th>home_team</th>\n",
       "      <th>home_points</th>\n",
       "      <th>away_rest</th>\n",
       "      <th>home_rest</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>game_id</th>\n",
       "      <th>date</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>18</th>\n",
       "      <th>2015-10-29</th>\n",
       "      <td>Memphis Grizzlies</td>\n",
       "      <td>112.0</td>\n",
       "      <td>Indiana Pacers</td>\n",
       "      <td>103.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <th>2015-10-29</th>\n",
       "      <td>Dallas Mavericks</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Los Angeles Clippers</td>\n",
       "      <td>104.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <th>2015-10-29</th>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>112.0</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>101.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <th>2015-10-30</th>\n",
       "      <td>Charlotte Hornets</td>\n",
       "      <td>94.0</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>97.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <th>2015-10-30</th>\n",
       "      <td>Toronto Raptors</td>\n",
       "      <td>113.0</td>\n",
       "      <td>Boston Celtics</td>\n",
       "      <td>103.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            away_team  away_points             home_team  \\\n",
       "game_id date                                                               \n",
       "18      2015-10-29  Memphis Grizzlies        112.0        Indiana Pacers   \n",
       "19      2015-10-29   Dallas Mavericks         88.0  Los Angeles Clippers   \n",
       "20      2015-10-29      Atlanta Hawks        112.0       New York Knicks   \n",
       "21      2015-10-30  Charlotte Hornets         94.0         Atlanta Hawks   \n",
       "22      2015-10-30    Toronto Raptors        113.0        Boston Celtics   \n",
       "\n",
       "                    home_points  away_rest  home_rest  \n",
       "game_id date                                           \n",
       "18      2015-10-29        103.0        0.0        0.0  \n",
       "19      2015-10-29        104.0        0.0        0.0  \n",
       "20      2015-10-29        101.0        1.0        0.0  \n",
       "21      2015-10-30         97.0        1.0        0.0  \n",
       "22      2015-10-30        103.0        1.0        1.0  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "by_game = (pd.pivot_table(tidy, values='rest',\n",
    "                          index=['game_id', 'date'],\n",
    "                          columns='variable')\n",
    "             .rename(columns={'away_team': 'away_rest',\n",
    "                              'home_team': 'home_rest'}))\n",
    "df = pd.concat([games, by_game], axis=1)\n",
    "df.dropna().head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "One somewhat subtle point: an \"observation\" depends on the question being asked.\n",
    "\n",
    "So really, we have two tidy datasets, `tidy` for answering team-level things, and `df` for game-level things.\n",
    "\n",
    "One potentially interesting question is \"what was each team's average days of rest, at home and on the road\". With a tidy dataset (the DataFrame `tidy`, since it's team-level), Seaborn makes this easy:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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kpp2mXayNY77VzXsCY2xvdVy8mnLeu5pSs7uWjCfLy0mOoFy3/YESK/9Rd03U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PPpxm5P+2+OmQ/x2NP6mlraf0XVIv0eVeP65Alm/yTVncXZVCw/nKoxdOe2lwOT/bb3UE2sLqD6\nJd2dutn785h4RLxJt9VU18lmtkOpa/Ql1I3mhc18ULH2Gep88D2qlslf5VhT5nHrz8yPUbHzjmZ9\n/wQc0lyL5rP5FBPnU4m2T3WbsTmmDqZq+V1OJQZPZWxk36mW382vqGPy29RLmVc1tYGmZbrHX3Pe\nfhx1nXoZNWLsN6n992pg37aahZP9hkNp+uukHr5ayYlPU/E20Wedy91s1855aE7G3DTv1T5N3d+s\naCpatJ4D1lHPHU+mjvOTqITeNxj/3NSpfdpZVGLt8uaZ5jimfqaZaFldP+vl+tPUEPwaNRhC67rS\naiHStbVX851jgBc2tQVfSd2rfoaKlftSAzIMU9+33czJGOlVZn6HSiQfRu33V1KDqHx4kq+9k9ou\ny6hz54OAx2Rm11qHjfbf2bouXtFU4Pgn6pr5Meq+bUfgEU2Nyen8loupSkVvbmoL/iPVF/UV1PPD\nB6l7zPZ4/Cz1Euxyat8+LpvBgKZRztazSOe93CVU7L6Sit0TgH/KzM3adH9kdHT2jqmoJmBXUQfN\nOVFtvL8KLM3Mi9rmuz91knocdaCdQjVVePKsFVaSBixqJKzvZjNyXlTH8zdSN1zfmPTLW7ioAYuO\nzcyz+vlckjRzokYcPTYz7znoskiStKWLiI8Ct2TmvOp3drZrEO4FfD4zzwHIzO9Tbc07m6M9Gzg3\nM7+TmbdSbzoOjh46i5WkeeRFwNkRcZ+oPkjeQyUIO0dbliRJkiSpb7OaIMzMH2Tm81p/N23xH874\nTumh2qD/uO17q4BVVP9SkjQsXkL14fk1qr+JvalmtF1Hb51jpqq+PtAmE5IkSZI0TGa1iXG7qNE4\nzwduysyndHz2FWr011Papv0SeFFmTmc0GkmSJEmSJEmTGMgoxk0n4f9FjTb5zC6zrAEWdUxbTI0E\n08vyd6I6/2y3gOqc+IrMvH1aBZaGiPEj9c/4kfpn/Ej9MXak/hk/0phZTxBGxL7UqLRnZeY/TzDb\nT2hrThwRd6FGeflJj6s5mhrZdiMXXnhh74WV5paRGVqO8aNhZPxI/TN+pP4YO1L/jB+pf13jZ1YT\nhM3Q8F8ATszMEyaZ9ePAf0fEh4DvAW8FLsjM3/W4qmXU8NHtdqeGC5c0OeNH6p/xI/XP+JH6Y+xI\n/TN+pMZs1yB8PnAX4PUR8YZm2ijw7mb6aGa+JDN/EBEvAs4E7gZ8HTis15Vk5o3USJ8bRMRtM1B+\nad4zfqT+GT9S/4wfqT/GjtQ/40caM6sJwsx8K1UbsJd5PwV8avOWSJIkSZIkSRpuWw26AJIkSZIk\nSZIGxwShJEmSJEmSNMRMEEqSJEmSJElDzAShJEmSJEmSNMRMEEqSJEmSJElDzAShJEmSJEmSNMRM\nEEqSJEmSJElDzAShJEmSJEmSNMRMEEqSJEmSJElDzAShJEmSJEmSNMRMEEqSJEmSJElDzAShJEmS\nJEmSNMRMEEqSJEmSJElDzAShJEmSJEmSNMRMEEqSJEmSJElDzAShJEmSJEmSNMRMEEqSJEmSJElD\nzAShJEmSJEmSNMRMEEqSJEmSJElDzAShJGmTLV++nKVLl7J06VKWL18+6OJIkiRJkqbBBKEkaZOM\njo6ybNkyVq1axapVq1i2bBmjo6ODLpYkSZIkqUcmCCVJm2Tt2rWsXLlyw98rV65k7dq1AyyRJEmS\nJGk6TBBKkiRJkiRJQ8wEoSRJkiRJkjTETBBKkiRJmnMcIEuSpJljglCSJEnSnOIAWZIkzSwThJIk\nSZLmFAfIkiRpZpkglCRJkiRJkoaYCUJJkiRJkiRpiJkglCRJkiRJmqMctEkzwQThFswglyQNgtcf\nSZKkucFBmzRTTBBuoQxySdIgeP2RJEmaOxy0STPFBOEWyiCXJA2C1x9JkiRp+Cwc1IojYn/gs5m5\n+wSffx54DHA7MAKMZuYOs1hESZIkSZIkad4bSIIwIp4PnASsm2S2vwQempnfn51SSZIkSZIkScNn\n1psYR8TrgKOB4yeZZ2dgZ+BHs1UuSZIkSZIkaRgNog/CMzLzgcB3JpnngcBq4PyIWBkRX4+IA2en\neJIkSZIkSdLwmPUEYWZe38Ns2wLLqZqGuwNnA1+IiLtuzrJJkiRJkjTfLV++nKVLl7J06VKWL18+\n6OJI2gIMbJCSyWTmecB5bZPeHxEvAR4NnDPV9yNiJ2CnjsldB0ORNJ7xI/XP+JH6Z/xI/TF2NF2j\no6MsW7aMVatWAbBs2TIe8pCHMDIyMuCSzT7jRxqzRSYII2IpQGb+Z9vkbYG1PS7iaODYmS6XNCSM\nH6l/xo/UP+NH6o+xo2lZu3YtK1eu3PD3ypUrWbt2LYsWLRpgqQbG+JEaW2SCkEoGvj0irgCuBI5p\npn25x+8vAz7WMW134KIZK6E0fxk/Uv+MH6l/xo/UH2NH6p/xIzW2mARhRJwKjGbmSzLzoxGxC/BF\n4E+A7wJPzMxbellWZt4I3Nix/NtmuszSfGT8SP0zfqT+GT9Sf4wdqX/GjzRmYAnCzLwEuGvb30d2\nfH4CcMJsl0uSJEmSJEkaJrM+irEkSZIkSZKkLYcJQkmSJEmSJGmImSCUJEmSJEmShpgJQkmSJEnS\nQC1fvpylS5eydOlSli9fPujiSNLQMUEoSZIkSRqY0dFRli1bxqpVq1i1ahXLli1jdHR00MWSpKFi\nglCSJEmSNDBr165l5cqVG/5euXIla9euHWCJJGn4mCCUJEmSJEmShpgJQkmSJEmSJGmImSCUJEmS\nJEmShpgJQkmSJEmSJGmImSCUJEmSJEmShtjCQRdAkjR969atY8WKFYMuBgC33nrrRtMuv/xyttlm\nmwGUZmP3u9/92HrrrQddDEmSJEnaYpkglKQ5aMWKFRx62ttYstvOgy4KrL+D7TomveILZ8GCwVdS\nv/naGzjr8New7777DrookiRJkrTFMkEoSXPUkt12Zoe9dx90MRhddzujl/5s3LTt774rI1t7iZEk\nSZKkuWDw1TukLcTy5ctZunQpS5cuZfny5YMujiRJkiRJ0qwwQSgBo6OjLFu2jFWrVrFq1SqWLVvG\n6OjooIslSZIkSZK02ZkglIC1a9eycuXKDX+vXLmStWvXDrBEkiRJkiRJs8MEoSRJkiRJkjTETBBK\nkiQNkH3gSpIkadBMEEqSJA2IfeBKkiRpS2CCUJIkaUDsA3d+sTaoJEmaqxYOugCSJEnSXNdeGxRg\n2bJlPOQhD2FkZGTAJZtZ69atY8WKFYMuBrfeeutG0y6//HK22WabAZRmY/e73/3YeuutB10MSZJ6\nZoJQkiRJ2kQT1QZdtGjRAEs181asWMHz3n8KS3bbZbAFWb+eJR2TjrngXFiwYCDFaXfztb/lI0cc\nxb777jvookiSNoPly5dz8sknA3DMMcdw0EEHDbhEM8MEoSRJkqSeLdltF3bY6+4DLcPoutu5g++M\nm7b9nnsysrWPN5KkzWc+txiwD0JJkiRJkiRpCvO5/2gThJIkSZIkSdIQM0EoSZIkSZIkDTE76ZAk\nacC2lFFBYcseGdRRQSVJkqTNwwShBsYH4t75UCzNbytWrODQ005mya53HXRRYP16tuuY9IoLzhn4\nyKA3X7eSsw4/xlFBJWmGeC/eO+/F1cn46Z3xM3f0nCCMiEOBczLz1o7pS4AXZea7Zrpwmt9WrFjB\noacfx+Lddhp0UWD9HWzfMenlX3w/LBh8K/w1197IWS8+zodiaZ5bsutd2WHvPQddDEbX3c7o8vE3\nvNvffQ9HBpWkeWbFihU87/2nsWTXXQddFFi/niUdk445/4KBv5wCuPm66/jIEYd7L65xVqxYwT++\n/0y22233QRcF1t/Ooo5Jr7rgQlgw+Hu31ddew4ePOMz4mSMmPWIiYlfYkDc5E7gyIm7smO0BwFsB\nE4SatsW77cQOe+8y6GIwum498Jtx07a/+90Y2XrwNyWSJEnS5rBk113ZYa+9B10MRtet445vLh83\nbfs9786ItY60Bdtut93ZYa97DroYjK5bx+1cPG7a9nvew/jRtE2VUn4I8ClgtPn70rbPRoGR5t8f\nntliSZIkSZIkSZoNkyYIM/MzEbE3Ndrx1cD+wA1ts4wCqzNz1WYroSRJkiRJkqTNZspG6Zn5q+af\nG3XGFhF7Ar/vZ8URsT/w2czs2mg/Ip4FHA/cFbgYeGFmruxnXZKGz/Llyzn55JMBOOaYYzjooIMG\nXCJJkiRJkrZM0xmkZDdgGfDvwI+BrwAPBa6NiCdn5g+msaznAycB6yb4/P7AqcDjgBXAKVQfiE/u\ndR2Shtfo6CjLli1j1aqq3Lxs2TIe8pCHMDIyMsU3JUmSpJnnqLe9c9RbaTCmM6zN+4A7A/8HPA+4\nL9VH4XOBdwOP6mUhEfE6YClVO/DVE8z2bODczPxO851XAzdExM6ZecME35EkANauXcvKlWMVjleu\nXMnatWtZtKhzfC9JkiRp83PU6N44arQ0ONNJED4G2C8zfxURTwP+KzO/FRE3ULX8enVGZr4lIh45\nyTz7ABuGscrMVRGxCgjG94E4o3yr0zvf6kiS5iqv973xWi9JM8tRo6X+eO/Wu025f5tOgnAdsDAi\ntqNqCx7WTN8VWN3rQjLz+h5mWwKs6Zi2Bljc63r6sWLFCg49/TgW77bT5lxNb9bfwfYdk17+xffD\ngo26gpx1a669kbNefJxvdSRJc9KKFSs49LSTWbLrXQddFFi/nu06Jr3ignMGXovj5utWctbhx3it\nlyRJA7dixQr+8f1nst1uXYewmF3rb6ezXdqrLrgQFkwnvbZ5rL72Gj58xGF9379N5xd8BfgQcDNw\nK/D5iDiYal58fl9rn9ga2GibL6bHRGRE7AR0Zvl6OpIW77YTO+y9Sy+zblaj69YDvxk3bfu7342R\nrQdf7Vvz26bEjzTsjJ+5Y8mud2WHvfccdDEYXXc7o8vHvxHf/u57MLL14G8yZ5vxI/XH2JH6Z/zM\nHdvttjs77HXPQReD0XXruJ2Lx03bfs97zIsauNO5+3wR8GZgb+BvMnN1ROwLXAK8cobL9ROqOTEA\nEXEXYMdmei+OBo6d4TJJw8L40fQsXACLt4E1TXX7xdvUtOFk/Ej9M36k/hg7Uv+MH6nRc4IwM/8I\nvAIgIhY2096ymcr1ceC/I+JDwPeAtwIXZObvevz+MuBjHdN2By6auSJK85bxo2kZGRmBA/dh9Jv1\nDmfkwH2GecRo40fqn/Ej9cfYkfpn/EiNabVfiYgjgFcBe0XEPsBrgJXA6zNzdFMKEhGnAqOZ+ZLM\n/EFEvAg4E7gb8HXG+jycUmbeCNzYsfzbNqV80rAwftSPkT3uwsjShw+6GANn/Ej9M36k/hg7Uv+M\nH2lMzwnCiHgZ8GrgOKrfQYALgVOAO4A3TGfFmXkJcNe2v4/s+PxTwKems0xJkiQNly1lZMP5PKqh\nJEma/6ZTg/BI4PDM/HxEvBMgM8+JiD8ApzHNBKG0RVm4FSy5E9zcvCxacqeaJkmStmgrVqzgee8/\nhSW7DXiQufXrWdIx6ZgLzh34iNQAN1/7Wz5yxFGOSi1JkiY0nQThXsCPuky/CrjLzBRHGoyRkRFG\nD9gLvvmLmnDAXsPch5okSXPKkt12YYe97j7QMoyuu507+M64advvuedQjkgtSZLmnuncsVwOPB14\nZ/N3q8/BI4Dvz2ShpEEY2XNH2HPHQRdDkiRJkiRpVk0nQfhK4IsR8WhgG+CNzUAl9wYO3hyFkyRJ\nkiRJkrR5TTdB+FTgscBaYHvgq8DTM/OazVA2SZIkSZIkSZvZdBKEjwVek5nHbq7CSJIkSZIkSZpd\n00kQvhM4MyJOBn4O3NL+YWb+bCYLJkmSJEmSJGnzm06C8M3N/x/eNm0UGGn+v2CmCiVJkiRJE1q4\nABYvgjVNnYXFi2qaJEnqy3QShPfYbKWQJEmSpB6NjIyw1f77csdl3wVgq/33ZWRkZMClkiRp7uo5\nQZiZv9ycBZEkSRo6CxfA4m1hzdr6e/G21oKSejSyx24seMZugy6GZsLChbB4MeF43LMAACAASURB\nVKxZU38vXlzTJGlLs3AhLN4O1qyuvxdvN2/OV/PjV0gauHXr1rFixYpBFwOAW2+9daNpl19+Odts\ns80ASrOx+93vfmy99daDLoakLcDIyAgccH9GL/tB/X3A/a0FJWnojIyMsNV+B3DHty4DYKv9DvBc\nKGmLNDIywoL9H8b6y74GwIL9HzZvzlcmCCXNiBUrVnDoaW9jyW47D7oosP4OtuuY9IovnAULthpI\ncdrdfO0NnHX4a9h3330HXRRJW4iRPe7GyDMeP+hiSNJAjeyxBwv2eMagiyFJU9pqj73Y6hnPHXQx\nZpwJQkkzZsluO7PD3rsPuhiMrrud0UvHD6y+/d13ZWRrT3mSJEmSJHUafHUaSZIkSZIkSQNjglCS\nJEmSJEkaYiYIJUmSJEmSpCFmglCSJI1ZuAAWbzv29+Jta5okSZKkecsEoSRJ2mBkZISRA+4Pi7aB\nRdswcsD9GRkZGXSxJEmS1M3ChbB4u7G/F29X06Rp8qiRJEnjjOxxN0ae8fhBF0OSJElTGBkZYcH+\nD2P9ZV8DYMH+D/PlrvpiglCSJEmSJGmO2mqPvdjqGc8ddDE0x9nEWJIkSZIkSRpiJgglSZKkTbVw\nASxeNPb34kUO8CNJkuYME4SSJEnSJhoZGWGr/feFbbeFbbdlq/33tQ8oSVumhQth8eKxvxcvdlAL\nSfZBKEmSJM2EkT12Y8Ezdht0MSRpUiMjI2y13wHc8a3LANhqvwN8oSHJBOEWa+FWsOROcPNt9feS\nO9U0SZIkSZI2wcgee7Bgj2cMuhiStiBmnLZQIyMjcMBesGjr+u+AvXyrI0mSJEmSpBlnDcIt2Mie\nO8KeOw66GJIkSZIkSZrHrEEoSZIkSZIkDTEThJIkSZIkSdIQM0EoSZIkSZIkDTEThJIkSZIkSdIQ\nM0Eoaf5ZuAAWbzP29+JtapokSZIkSdqICUJJ887IyAgjB+4Di+4Ei+7EyIH7MDIyMuhiSZIkSZK0\nRVo46AJI0uYwssddGFn68EEXQ5IkSZKkLd6sJwgj4oHA+4H7AD8DjszMb3WZ7/PAY4DbgRFgNDN3\nmM2ySpIkSZIkSfPdrDYxjohtgPOAM4A7A8uA8yJicZfZ/xJ4aGbukJnbmxyUJEmSJEmSZt5s90H4\naGB9Zp6emesz80zgeuBJ7TNFxM7AzsCPZrl8kiRJkiRJ0lCZ7QThPsCPO6ZlM73dA4HVwPkRsTIi\nvh4RB85GASVJkiRJkqRhMtt9EC4B1nRMWwN0NjHeFlgO/DNwFfAC4AsREZm5cqqVRMROwE4dk3fv\nq8TSkDF+pP4ZP1L/jB+pP8aO1D/jRxoz2wnCNcCijmmLqdqCG2TmeVRfhS3vj4iXUE2Uz+lhPUcD\nx25COaVhZvxI/TN+pP4ZP1J/jB2pf8aP1JjtBOFPgJd2TAvg7HETIpYCZOZ/tk3eFljb43qWAR/r\nmLY7cFHPJZWGl/Ej9c/4kfpn/Ej9MXak/hk/UmO2E4QXAdtExEuB04BDgbsCX+qYb1vg7RFxBXAl\ncEwz7cu9rCQzbwRubJ8WEbdtWtGl4WD8SP0zfqT+GT9Sf4wdqX/GjzRmVgcpyczbgCcCz6aC8KXA\nX2fmLRFxakS8r5nvo8DJwBeB3wFPBp6YmbfMZnklSZIkSZKk+W62axCSmVcAD+0y/ciOv08ATpit\nckmSJEmSJEnDaFZrEEqSJEmSJEnaspgglCRJkiRJkoaYCUJJkiRJkiRpiJkglCRJkiRJkoaYCUJJ\nkiRJkiRpiJkglCRJkiRJkoaYCUJJkiRJkiRpiJkglCRJkiRJkoaYCUJJkiRJkiRpiJkglCRJkiRJ\nkoaYCUJJkiRJkiRpiJkglCRJkiRJkoaYCUJJkiRJkiRpiJkglCRJkiRJkoaYCUJJkiRJkiRpiJkg\nlCRJkiRJkoaYCUJJkiRJkiRpiJkglCRJkiRJkoaYCUJJkiRJkiRpiJkglCRJkiRJkoaYCUJJkiRJ\nkiRpiJkglCRJkiRJkoaYCUJJkiRJkiRpiJkglCRJkiRJkoaYCUJJkiRJkiRpiJkglCRJkiRJkoaY\nCUJJkiRJkiRpiJkglCRJkiRJkoaYCUJJkiRJkiRpiJkglCRJkiRJkoaYCUJJkiRJkiRpiJkglCRJ\nkiRJkoaYCUJJkiRJkiRpiC2c7RVGxAOB9wP3AX4GHJmZ3+oy37OA44G7AhcDL8zMlbNZVkmSJEmS\nJGm+m9UahBGxDXAecAZwZ2AZcF5ELO6Y7/7AqcA/AHcBrgfOnM2ySpIkSZIkScNgtpsYPxpYn5mn\nZ+b6zDyTSv49qWO+ZwPnZuZ3MvNW4NXAwRGx8yyXV5IkSZIkSZrXZjtBuA/w445p2UyfcL7MXAWs\nAmKzlk6SJEmSJEkaMrOdIFwCrOmYtgZY3Od8kiRJkiRJkjbBbA9SsgZY1DFtMbC6z/m6ioidgJ06\nJu8J8Nvf/nbC791www3cfNVvuWP12l5WM7Ruuf4mbrjhBn7zm99s0nLc3r3pdXs/9rGP3Rv4TWbe\nvinr25T4WX3VNaxffcumrH7eu+X6VTMWP27vqfW6vbeI+Ln616xf3fluTC23rLxxRmIH3N69mM72\n3jLi5xesX33zpqx+Xrtl5Q0zHD9u78n0ur23iNj5+dWsX93TI9bQuuWGlTN37+b2nlKv23tLiJ8/\nXv2/rF/9x01Z/by3ZuX13HDDA2ckftzeU+t1e08UPyOjo6ObsXjjRcTBwCmZ+Wdt034IvCEzz22b\n9jbgLpn5wubvuwC/BXbOzN/1sJ7jgGNnuPjSXHCPzPzFpizA+NEQM36k/hk/Un+MHal/xo/Uv43i\nZ7ZrEF4EbBMRLwVOAw4F7gp8qWO+jwP/HREfAr4HvBW4oJfkYGMZ8LGOaXcC7k71ebi+v+IPxD2o\n7fYY4OcDLsswmOvbe9OrBhg/6t9c397Gz3hzfX/ONXN9exs/Y+b6vpxr5vr2NnbGm+v7c66Z69vb\n+Blvru/PuWaub++N4mdWaxACRMR9qeTgfYH/BY7IzG9HxKnAaGa+pJnvGcC/A3cDvg4clpn/N6uF\n3QJExJ9TJ6bIzJ8Nujzzndt7fnF/zi639/zi/pxdbu/5w305u9ze84v7c3a5vecX9+fsmo/be7Zr\nEJKZVwAP7TL9yI6/PwV8arbKJUmSJEmSJA2j2R7FWJIkSZIkSdIWxAShJEmSJEmSNMRMEG75bgTe\n2Pxfm5/be35xf84ut/f84v6cXW7v+cN9Obvc3vOL+3N2ub3nF/fn7Jp323vWBymRJEmSJEmStOWw\nBqEkSZIkSZI0xEwQSpIkSZIkSUPMBKEkSZIkSZI0xEwQSpIkSZIkSUPMBKEkSZIkSZI0xEwQSpIk\nSZIkSUPMBKEkSZIkSZI0xEwQSpIkSZIkSUPMBKEkSZIkSZI0xBYOugDDJiLuD/y/zPzaoMsyXRGx\nF/BzYB2wc2b+oePzpcA5wIcz8/kR8UjgImBRZt62mcqyT2b+rMvnFwPfzMzXdUzfBrgFeNRM7IOI\n2Bu4b2Z+flOXtSWby8dtS0TsALwGeDqwF3UcLAf+PTMv63EZjwQuBrbtdkxHxCHA8Zl5jxkr+Pjl\n3wV4C/AU4E+AX1Mx9++ZeUvbPI/NzHN6XGZf+zYitgJWAa/NzFPbph8DnAT8c2ae1Db9aOBfM3OX\n6axnkvU/D3hrZu42E8ubCfMkTnYCjgWeCtwN+A3waeBtmXlT23x3AAdn5pe7LOPn1L45vYf1dT1X\nb0kiYmvgVcAhwD2B/wP+CzguM/+vmedY4AmZeVDz999Sv+u6aa7r59T5qZtR4NHNfwdn5kP6+Dl9\niYh11HllIMf2XI+tJl7arQN+BZyemSdswnL3prkHmeq+aFNNdn1r4viRE3x1FDgsM8/qY50bzg8R\ncSawTWY+u8t8zwPObNY1Aqyntu8HMvNtbfNNeN4aRnM5rjb38T7Jeo8E3gsclZnvm631Nuvu+do6\nzeVOGFuDLNcwmCcx2DIK3AicBxyTmX/cjOue8JjbXPeVbc+AL8/MZR2fHcs07suaZa3KzBUzWcaZ\nYg3C2XcusM+gC7GJRqkERae/A9pvgi8Fdp3p5GDjV8AuwJWbYdnT8SHgoAGXYTbM6eO2SZp9G3gU\n8AoggMcAVwP/HREHTmNxo5v4+aY4nzrunwr8OfAy4B+Aj7TN8w7gb6axzL72bWbeQcX4/h0fPQa4\npvl/u4OoC+tM+QRwvxlc3kyY63GyC/A/wAOAw6hj7CXAI4BvRsTOAyzeQETEQuCrVHLwdcB9gEOB\n/YCLI2K7ZtYTgCc137k78Clg+z5W+WAqxnehEu3fpRK1uwC7At9s5tuc55kt0ZyOrcYzGdu3f0q9\n7HlLk3jrV+c9yOY+LiZa/tMZ+22vAFYy/rjt6YXVBMs9vsd5V7aV4Z7AK4HXRsRz+1z3MJjrcTWI\n8+CzqWePwwawbs0/8yEGH0qdd/cA/pq6P3rXIAu1mb05InbtMn0656OLqWvjFskahLNvZNAFmAH/\nDTwN+FhrQkTcCTgY2FATKzNvp27YZlxmjm6uZU/TfNifvZjrv/Mk4DbgEc1xCVX77uVNzcJjgScO\nqnC9iIj70iQPMvOGZvKvIuIo4IKI2Ckzb2T6+2pT9u0lwD+2lXEBlUz6V+rBd0Fmrm8+Pgj4901Y\n1ziZeStw60wtb4bM9Tg5BbgWeEzbfvt1RHyNOrefDDxnUIUbkFdRN+/7ZObvmmm/iIgnUi8YjgRO\nyMw1wJrm863o88G1iWEAImI1sK4t3lvT+1n0XDfXYwvgpsxsv285MyL+nnq5enafy+zcLgPZTh21\ni38P3NF53G7qcnvQuc5fR8THqJdoH93UssxTcz2uZrX8TY3dg6gXRh+LiPtm5hWzWQbNO/MhBm9s\nu7ZdFxFvAT4IvGBwxdqsbgSWAc8YdEE2FxOEs6ip8roXcGpEHNg0w90HeDfwMOC31E3im1pJjKbZ\nxD8B96KaRH4ZeGFm/rH57Ajgk1TNhgXA26ms9OnAnzX/fna3ar5NlfLndSnqKHCPzPzVBD/ls8A7\nIuJObbUDHw/8lKrZ11r+o6gmxttm5m0RcQDwNurNwlZUzYgjMvNHbdWUn9Jsj92AzwGvBk6lmlT9\nDHhuZl4xk00LIuLVVC2ZHZsyvTIzv998tgv1FuRxVG2Qn1PNJD/dbL9HAo9o9mdnjal5Ya4ft00C\n8B+A57QlB9u9imru1Zr/z4B3Ag+nkoofB/5lgibF9wJOAw4Afgx8vuPzAN7TsZ3emJnrm+rlnwBe\nCxwH3JWKl+e1Jwna3EFdiJ/E+BqDFwJ/AdzUVHF/XrPuAzPznk0ZTmrKsG1Tzldk5tf62bcdLqES\ngTs0XQ4c0GzL04G3AgcCl0bEbsCeNDUIJ4irf8vMTzWf3wG8mTpOfk6dBz5BvZR4AXAG8EOq2euu\nzXcm3G9t27r9+8cBHwD+Cti62fYvzcxruvzOKc2DONmZevHz1LbkIFDJ2Ij4d+DsiDiq86E9Ih4O\nfJE6rj7Q8dl21H75a2AnqnbpiZn53rbZdomIc6nryErqHHt28/07Aa8HnkvFyDep5h1XtG33Lzbb\n+LFU0u65VML/GCpu3pKZ727mn/TY6+Iw4Iy25GBrm6yKiMcBv2iW297E+OpmO/+kaY72tqbMG5IU\nEfFt4OzM7Pct+9YRcRJjtVjOyMx/bpa9UXOxiLgOeHVmntV8/kfgzsDfUonNk1tNMZtE/9up5P/t\nVMKftmUtpOL7ucA2wDeAl2Xmz5vPx8VvZk6nhvZG5npsTeF26nzVWvbLgZdS58sfUl01fK1tO1xB\nnbN2AL5E2z0IHTWaJjj3H5OZlzSf39H8jldQ15CfAi/KzO80n096fZuuJkYeTB0zDwZeTMXuhOeH\nGWgqdvMk5ZnwXNClyXLLmZn5gojYvvnu06l9+BXq/HdD2/3p66lajBcCz6IeKP8O2I564XJ0Zv64\nz9+1yeZ5XLWWuR/VquLBwO+oJudvbj5bwPT3ybOBlZn5iYh4GxVzr+r4DROeW5t53kQd+9tQx9hf\nUl0zndV8PuEzSZffN9nzyyOo2PoL4Abgg63fPl3TuW42x9DXgdMy8996KOfPqRrGz6bOhfejrj3/\nBOxOPfu9ITPP7afsW7J5HINr2v/ocu06kIrHt1Ln0B2o8+TRmfnr5jvbT/Z5x/I3Ouaa6btQ3eQ8\nOjO/3kzbirrOHEnF6RFUvuHl1LH9Weo6uHaC3zYKHAWcHxFPyswLus0UVcNwGXVf+4dmHf+cmWua\nYx7gCxHxRqryxBZ1fbCJ8ez6W+pA/Req5tI21M3RD4D7A8+nstHHA0TEQ6mbszdTJ4K/p5pIvrRt\nmQ+kEm4HUg8hb6FOAkcBT6DedB0xQXlexlhzjPb/dqVqV3UzCnyNOok/ruO3fZrxN1KjzX+th8QL\nqCaJ96GqI29F3by2O67ZBk+lAuXb1EP9ftSJ8O0dy5+ucW9qIuIlwIuobb8vlfC4OCLu2szyUeqE\n8fCm3JcAH2j23cuph9VTqN8/X83143Y/KgHUtX+PzFzVulBGxI7Uw+5NwEOom/qnUjdZ40T1S/YF\nqj+yB1E3oa9s+3wb6gGuczu116LbqZn+N1QSfD+qn8Ru5fwxdSNwZkRcEREnRcSTgQVZ1gMnUjcG\n51I3xFB9gVzflHFfmn6vms+mtW+7+A4Vl61mxo8GLmmSqZcy1sz4YcC1mdnqEqBbXJ3erL/l76na\niC9s/r4b1XzhgVT/PzB2fullv7W+/5fN998E3KNZx37UjcJ7JvidvZjrcfIg6vz4rQmW93Uqjh7U\nPjGq/5zPAa/rTA42Tqa2+ZOopv0fBt4VEbu3zfMcKpb+grqOnNHsU6h99WwqsbsvdWP35Rhr2gvw\nb4w1Ob+JupG8N3WdOQU4Mcaag/Ry7LV+27ZUM+tvd9sgmfmdbPog7LA/tS0fBpxFNTf+h7bl3qvZ\nJh/vttwePQhYRB0fLwVe2ZwPenU48L/UsXkSlei/T/PZG6nmsH9P3dwexvj7xbdQx+rTqGPzWuq6\nOVn8boq5HlsbiYito/ptfgJ1viYi/pU6ll/d/K5LqAeIPdu++gJq3z21Kcdk9yDdzv2ndczzZuol\n1f2pxMaprfIxyfVtEzyZ2ncHUXHay/mhL1G17p9JxWA3k50LPsHYPt2FOhZuYewacQaVvHg0dZ1b\nQvVL2u7x1DH2euq4Opj6nfelaqAMulbjvIurds159mLq/L1vs/yXRcQ/NbMczfT3ybNp4rX5/yFN\norHdhOfWiHhN8/nzqetTUOfJVpmneiahl3mbJMhnqG5pgtrmr46Iv57i902kp+tmE7dfAj7alhzs\n5Tc9n3pJ8IymvO+mXvDdC/gP4ONRXQXNN/MuBqNeNr+MjWNpw7WrSTR+hrpf/9umTIuAz0dE6zl9\nqs9b69vomGvJzN9SL///oW3yY6nk/PnN3/tSL8EeRW3rv2Xqmo8XUsflKRGxaIJ5PkslSvejkpwP\noF4I0EyDelY5kf7ORZuVNQhnUWb+LiLWA39sMv3Pb/79L80sVzVvj8+LiNdSNyMvyMxPNp//OiK+\nTJ2cWxYCL8nMmyJiGXUyOC0zvwEQEV+hHrq6leeP1A3hdK2nboSeRjVtXECd2I+nAq2bJVQtjlZC\n8JcR8SEqIdju+Mz8QVP2y4FfZubHmr/Pom6cW6aqlv2qqIEROrUnFl9Nvcm6sPn7uIj4K+qh5i3U\ng+95rbcmEXFC89kemXlVRNwG3NxZo2Y+mQfHbavftPame4+kakO0ageMUsm651DH9wsycx3w0+bm\n5rzm4a3d46kL5wuaMv00Iv6SOuFDNUGZbDtBvd17edsx/x+MXTi6eQpV2+M5zf+PAX4XEUdn5scy\n8+aIuIVqarUqIhZTNwantyVBTwG+FNX8d1r7Nqtp/wZZNSGXUxfXr1IX3k83H19EXezezMb9D04Y\nV8BVzTynZWY2nz+S2kdvbaul9PC25fWy31rf/0Xz/XtQtUt+mZmrmzevfd+AzoM4+ZPm/7+b4PPW\n9PZtdE/qhuekbGrodfF1YFlm/rAp81uoJv37UMk+qGPhtObzN1HH9X0iYgVVk+BprXN0RLyAOkb+\nkUqMAHw1x2ocnk29iT2iiYcTqITXnwPX0dux19JKUv5+gt82kVYzxxszc21Tpi9FxI5ZNRGfCfx3\nZl4/zeV2ruOlTUxeFRH/Qj0YnD/51zbIttok72i+vx/wI+ph7l8z8yKAiDgMaMXittTN7MMy87vN\ntCOBX1Iv9Vpdj2yI3001D2Kr5bMxNljJ4mYZJ2TmJ5ppL6cGvvls8/e/RNUCejlVYwTgK9nUAGzK\nueEeJCLu3DZ9qnN/q5bwu7MZsKOJhXObB7Cprm/9+kNmbnhxExG9nB96dbeI+AN1TV9IPQReRr2c\n7mbS+zuabmwiIqgE6Usz8wcR8afUsX63HBuk6DnAjRFxUFu5T87Mq5vPj6SOy19l1TJ8CQPud2we\nxdVEDgd+2vZ7royqUXQ89VC+N9PYJ83x/xfU9QnqXudo6r7sc+N/yoTn1qOoGL+gWeZzaWt5xdTP\nJPQ476nUNf36rBpXv462Gu996OW6uROVqPlyZra/TOjlN3287T74adT92q+bsr8jIr7HJLWB56p5\nFIPfrdMkW1GJvBupY73dhmtX1MubxwL3y8wfNdOeRcXCkyPiF5N9zlht9omOuXZnA29vnpNGqfuv\nT2fmuqbMC4HnN/dmGRFfZPLnsJZXUbXuj2N8boKIeAx1z/nQ1rW22bc/jYhjMvPaZt03ZdUo3Jst\n7PpggnCw7g3sExHtwThC1dLYOzO/FxGrI+L1VDDfp/nOf7bN/7tWciozb2kOuJ+3fX4LdZO0kYg4\nle79SY0Cf5GZv5mk7J9lrBbSo4HfZObVMUHfSJl5fUR8KCJeRr0tDiqZ2Pkw2v6AtoZqqjXlb5nA\nGdRNQLs7UU1liIglVDOej0TEhzvm+d/m3+8HljYX+FaZoRI7w2quHbermv/vSNWGgHpoeEDz7wOp\nNzUj1An58ibJ1HIpda7sPLjvTTWfa98O32bsAWrS7dQ2rX2gnT80n3eV1cTgRMZqRD2Bugh/JCJ+\n1LrBapt/TUS8D3hORDyYjY/hcU1Jeyjzz9nYJcCBTeLgIYy9ybwYODaqOeJBVCy19BJX3dbVbRr0\nvt/av38yddN7Q0T8N1UboL3p9qaaq3GyK90fzFs1etprzJ3c/J4Jm51kNWn96ybJFFQSa5Tx+/qq\ntvl/3/zORdQN1lbUwCmtz9dFNc9tv8H937Z/rwH+LzNvbuZf2yyvtZ2mc05vvVTYsctnPcvMSyJi\nJfVm+gzqBvUdm7JM4BcdCfubqG3Wq86uOf5INVu+C/VSZUOTtsy8skm8QA2usQ01uFP791u1LVsm\nitWZMNdiq+VIqqbzKLAW+G1rH0bVurgLbcd641LGH+tX04NpnPs7rz9Q582prm/9Gndc9Hh+6NX/\nUdfzkeb7u1E1Mr8REQ/OjbvJmPJc0Nwnfgb4ZGZ+uJm8T7OOq2N8bZYFzXJa58/233oaVdvn2qiX\nap+jBpjZkszVuJrs93TWiL8U2DGq9tp098kh1Hm29bLzUiqJfBjjE4QTnVt3oo7J9uvZqoj4GUz5\nTDJuQMap5m0ST8uoGk7/Rr04+o+sGlX96OW6+QbqWNkwINE0flP7ee1LVDPk70bEj6kKKWdk5i19\nln0umasx+LRmHSPU/dJzgMsiYr/MbN2fte/jewNrWsm/pqyrIiKb37Vois9bCcKNjrkuPgO8D3hM\nVH/aT2/+a/ldju9C5g/U8TmpJpH3auC9UZU72t2bapV0U8d90h1U/FzbMf8Wd30wQThYC6naFS9g\n49pwv27esJxHZb8vokZJfCXjm/qsY2N3dJnWzeubZXbTefC2tMr5ZWBJ1NvSpzFWa6irJpnxHWAF\nVX36o1QA/VvHrJ2/p9ff0s1Nrbe3beVoPym2jv9DmnK1W93c+H2Z6vfqE82/r6NtIJYhNdeO2+9S\nD0MPpbmJyxrgovVmv735Vrc+JxZ0/L+ls28iGP+7Jt1OwN2bf3f2bdi1ZmxE/C01Kvh7m99wHfDh\niPg49Vb4sVSzhPbvLKFukP9AJcA+Q114J4rXqcrczSXUW/SDqJj7STP9u81vewSVjG31PzhRXHXe\nyHe7GZzoBrHX/bbh+03SZg/q7f+TqLesz6Ga0MyEuRYn326WvT/1AqjT/k15vtc27SPUsXdSRPxX\ndqlJHREfofpJO4u64bmMjROKnYlqqG02UR8wCxi/X3u6bkz3nJ7Vf+UPqd++UcxE9R2zLjO7NcHv\n7ALjY8DfR8S3qKbtn+m2zmmYaJt1WzdsfL+3UZ+qjNWmbl9WS2sbt5bzKDZ+wde+/zfnw9xci62W\n33bek7Tp9VjvabtO49w/2XEw2fWtX+PK3+P5oVfrs6lh3riyeaC8lur76gtt6+31XPDhpszttWEW\nNtMewMbb6AbGamO3X29+0tQSaTUj+2fg8IjYt/UyYwswV+NqIpPeF0xnnzTHyzOph/5W0gXqtz8x\nInbOsQFyJoqpdW3f6WbSZ5LpzpuZL4+qNfw3VK2rCyPiJZl5OtMwjXu2i5rPT4+IjzW1cHv9Te2x\ncgtwUFRz2ic35X9pRDwqM7/H/DZXY/DXHde270TEwVRrhFbtuvZz/1TXu16vh92OuXGampn/RSXg\nFlE17i9pm2WieJ1SZn4wIg6lEnxfbvtoIfXi+uAuy7quy3K2uOuDCcLZ137j/hOqvftvWjVfoprS\nvZR6UD2aeuPzotYXovrU6OkN8lSymkZ06z9pMqPNd2+NiC9QJ+6/oZqjTOZZ1NuAg1sTokaB7Oyz\ncNpl6VdTU+W3wO6ZueHtX0ScTjWX/F/qIWiPzLy2+exJzWyTPYjNR3P2uM3MGyPik8DrI+ILufFg\nI+0Jwp8Cz4yIrdtqoz2Uehi/kvHV+FcA94yIP8nMVu2r9v7ZptpO03V3QaKD4AAAIABJREFU4LUR\ncWbWiKktt1EX09YIYu376glUMmKHtmruL2k+63YM91Pm/6E6EF5KWzPizLwjqvnYYcB1bQ9uD6R7\nXHV7IO3VdPYbzTpfB3wvq3nfJ6IGUfpmROyZXTpB7tFcj5P/BN7YJPs21LaJsYFCPtXxpvXT1Kj2\nh1E14l7cvsyI+BNqIIuHZebyZlqrNlQv+/oqagCAA2n692rK8mA27r+2FxMde5OV5yzgNRHx9rY4\nb730OoruNQG7HctnU03TDgHOzy4dhM+g26iHOWBDH5091YJsjoPrqG4DWoNV7EU15YG6Lt5ONa9s\nNTFeQPWn+D7qeNgc5mxs9bjMPzbb/UDG93l5ENXP4EQ670Faf/dy7p/MVNe3TTYD54detJ5zOpMy\nU54LmtohjwEe2HHf8BOqxuyibDqRj4j/R50rXkslPsbtl4g4HFid1RXCeVEDtlxH1cT6+qb/zL7N\n9bia7B78p1QctHso1WXE9dPcJ4+iatE/l7ba1VTLis830zfqq7pdZv4hIn5DxdG3AaK6BbhX8/lE\nzyQfoAbB+WTbsiZ9fmleRL2GatrbanVyKtUX27QShPR+z/a5zPxoVDcgpwKPn85vavvsMcAjMvM4\nqpbm6yLiR1SycD4mCOdrDC5g4mT4T4FFEXG/zFwBENV64V7NZ1N93rLRMTfB+s6mkngjVEJxJh1B\nnRN2oQaVgdqPe1BdatzYlD+ocRQOZ+MXZVvc9cEE4exbTVUf3pHq4PINVNXr46kb8A8C32pqLlxL\nvUV5AJUAOJLqtLSvUTZnSPvF4Fyq2vk1bbWGJnItsGtEPIEK7idSbxbaTyzTvSGciRvId1APxCup\nC88LqZPwe6jaEeuBZzUPzvelmtTBWPXs1cCfdbw9nI/m+nH7cip5dWnUaKyXU2/5n0uNrLaceut2\nNvXbPhTVF9LuVH9m52Tm/zVvjVvH3YVU8ums5kHiXlTHvK1mWv9BJVUm2k7T/Q1nUgmJC6NqLv2Y\nShq+uCl7q2bIaupatDsVd9tSNZcupR42W33ybQPcyjT2bbdCZTX5vIyKm2M6Pr6Y6oOwvfnD9Uwd\nV9PVy37rtDfwvKh+Qa6jjoVr6a+mQst8iJNLqGPsOCoZdC+qj5UFzeftRpr9/3JqRLczM7M9mfFH\napv8XURcQ23zd1LH65T7OseaSb4rqm/Na6kH8G2pfT5d/Rx7y6jk99eapPIPqSYub6ea1Czr8p1W\nzYgHRMQ1mXlzZq6Iqs30Mvp7QTAd36aalh7clPF4KtZ79W7gDVH9AP2KGr1yPUBWv47vo5rVHN4s\n/3VUIqVbn78zZa7HVi/eQW33a6gE3YsZG9FzIhvuQZq/W9enXs793fR6fZsJrf6u+jo/dLFVRNyt\n7e+7UaNgXs/4PnBhinNBVH9tb6YGpbilbbnrM/NnUTVS/iMijqJqzp5ANR27kuqmofP+dCfgzRFx\nA9Wf5yFUdwgDG6WyMdfjagR4eFSfwu2+QQ1wdXREnEglxe5LXcve17zAnM4+OQS4unmAb/fjqCaB\nhzFFgrBxMtX1yi+pfluPp/ojbT0LdXsmOYQ6B3ea6Pnl3VT3GH9PNW1+G/WC6BFMPhJ56xmt3fVM\n/7p5FPD9iHhm8wJ2Or8J6tz0b83851PH2F40L6zmofkQgztHRKuv5sVUEuweTND0N6vbkvOoVlBH\nUXF3AvU7vpDVNcyEn3dZZOcx1+kLVLPhQ6jB42ZMZv44Ik6iEvKtBOFXqCThJ6Ka5Y9QCcx1Odb3\n9Gqqr+3LqP18/JZ0fZj1UYwj4mERcVlE3BQRV0bEiyeY71kRcVVE/DEizosuIzjNUadQVYfPaGoB\nPZ46MP6Heoj+MpU4g7qQ/Ya60F1EddB6FPU2ZyKbu0Zb+/LPpwJuo2Huu/gk1VTjbKoZ5MOpqrR3\nbruwT/QmvJey9PvZu6mL+onUDflfAX+dmVdk5jXUm4GjqaTmq6kkwi8Ye5N+GvVg9KUpyjrXzenj\ntnmDcwDVzOqN1L7+KvXw9XzqbeVo89ueQL0J+g5VI+A/m3nGlbWplfHEZtq3qBu9DbWJ2pY10Xaa\n7m/4PfX2+4dUYj6p2Lu9KX/rjdRZ1IPW5Zl5GbU/TqIuNIc0ZbqVsWN4Ovt2IpdQNwUXdUy/mKrS\nv2F6j3E1reOhx/3W6ZXU2+nPUMfDfYEn51jn/f2Y63FyA9WP5DepB6qkznHfAA7I8SP2jrZ974tU\n8/33R/U52YqRddQx92RqX59EJSm+weT7unMgqc9R145vUf3jPSIzu9WYnUirPL0ce+M0v+FxTRlO\npDqaX0bdAP5VR23e1ndWUde7sxgfOx+nYq/XgUSmo307fJRq0nwOzYsROrofmOz7mfkO6lg+g6oR\n2GpS1vIvVNx8hHrguwe1La7vXNYMmtOx1ePy30M9NL+Leon1EOBxrVpqEyyj8x6kdaxfRg32Mdm5\nf8LYm+r6NhOa2HoOk58fJipnNzsz9pLnGsaSgo9vi9NezwWHUC9FzqEe+lrLbfUf9zyq1sh51AvG\nO5r13Na+njZvp+LyQ836ng48pVW7ZIDmQ1ydTg1E0/7fnza13Z5E3Tf9gDq+TsyxkU572idRtdaf\nDnxggjK8F/iLiJhoYIP2bfAu6rz5Ueq8nFSisHXcTPRM8qMuy5pw3sxcTXWfcm/qOP08tc/eMEEZ\noRKIndvxDU2sHEmP92yZeQV1XL0zInaY5m8iMy+lXo68rFnfu4DXZGa3xNB8MB9i8GuMnSNXUDVO\nl2bmd9rm6fSP1PPM+dQzxE3AozNzbY+fT3bMdR5Tt1OVKH6Zme01gGfKm6hanK3ryyjVuvL3jN1D\nXcn4vg9Ppq6rb6TORa1uNraI68PI6OjstZCMqoJ/FTW6zjkR8UDqIX1pNqPlNfPdnzrYHkcdaKcA\nu2Xmk2etsJIkSTMkIt5NNUvs+mJUkjR/NbW6v9tqcdS8ULuRejn5jYEWTprHIuJzVE3MztHA1cVs\nNzHeC/h8Zp4DkJnfj4iLqaYP7TVPng2c28o8N80bbhiCZpyS9P/Zu/Mwucoq8ePfJgkhEVAMIKug\nCAeRIGRGBJxxw3FUxnFt91FBkUVRGddxwwVFBUFtZXEUnHHQcdTBQQQXxAVpmB8uOK3iEUERBelI\nKxJDJyH274/3VrpS6aW60qnq6vp+nidPum7dunXqVp27nPu+75U0j1QtSw6mXBF/bGejkSR1yLHA\nP0fEyZRWgydTCoSNN/yQNAsi4pHAwyjHXsd3OJyu0dYuxpn5o8x8Ue1x1d/+byldKertT12/66q7\nzghlfA9JkqRucSSli9UHsrqxhySp55xI6Xb4HcpwKHtTuqbPxh3CJW3qOcBbgFdn5iZ3ENbE2trF\nuF6UOzd9GfhjZv5Dw3Nfp9yZ5iN1024Gjs3MryFJkiRJkiRpVnTkLsbVTSm+RBmw8TkTzLKaMrB9\nvaWM3xlwuuUvowzwWW8B5W5LP64Gq5Q0AfNHap35I7XO/JFaY+5IrTN/pHFtLxBGxArK7ab/PTNf\nN8ls11PXnTgidqTcov36Jt/mJMrd2zbxjW98o/lgpe7SN0vLMX/Ui8wfqXXmj9Qac0dqnfkjtW7C\n/GlrgTAi7kcpDp6RmadPMetngG9FxPnAD4DTgEsz8w9NvtUA8OmGabuz8Y1QJE3M/JFaZ/5IrTN/\npNaYO1LrzB+p0u4WhMcAOwJvjYi3VdPGgA9V08cy88TM/FFEHAtcANwPuBI4utk3ycw7KHeF2iAi\n1s5C/NK8Z/5IrTN/pNaZP1JrzB2pdeaPNK6tBcLMPI3SGrCZeT8PfH7LRiRJkiRJkiT1tq06HYAk\nSZIkSZKkzrFAKEmSJEmSJPUwC4SSJEmSJElSD7NAKEmSJEmSJPUwC4SSJEmSJElSD7NAKEmSJEmS\nJPUwC4SSJEmSJElSD7NAKEmSJElSDxkcHKS/v5/+/n4GBwc7HY6kOcACoSRJkiRJPWJsbIyBgQFG\nRkYYGRlhYGCAsbGxToclqcMsEEqSJEmS1CNGR0cZHh7e8Hh4eJjR0dEORiRpLrBAKEmSJEmSJPUw\nC4SSJEmSuo5jqEmSNHssEEqSJEnqKo6hJknS7LJAKEmSJKmrOIaaJEmzywKhJEmSJEmS1MMsEEqS\nJEmSJEk9zAKhJEmSJEmS1MMsEEqSJEmSJEk9zAKhJEmSJEmS1MMsEEqSJEmSJEk9zAKhJEmSJEmS\n1MMsEEqSJEmSJEk9zAKhJEmSJEmS1MMsEEqSJEmSJEk9zAKhJElSBw0ODtLf309/fz+Dg4OdDkeS\nJEk9yAKhJElSh4yNjTEwMMDIyAgjIyMMDAwwNjbW6bAkSZLUYywQSpIkdcjo6CjDw8MbHg8PDzM6\nOtrBiCRJktSLLBBKkiRJkiRJPcwCoSRJkiRJktSE+Tp+tAVCSZIkSZIkaRrzefxoC4SSJEmSJEnS\nNObz+NEWCCVJkiRJkqQeZoFQkiRJkiRJ6mELO/XGEXEocFFm7j7J85cAjwXuAfqAsczcvo0hSpIk\nSZIkSfNeRwqEEXEM8AFg3RSzHQw8IjN/2J6oJEmSJEmSpN7T9i7GEfEm4CTg1Cnm2QnYCfhJu+KS\nJEmSJEmSelEnxiD8RGYeAnxvinkOAVYBX46I4Yi4MiIOa094kiRJkiRJUu9oe4EwM29vYrZtgEFK\nS8PdgQuByyJi5y0ZmyRJkiRJktRrOnaTkqlk5sXAxXWTzo2IE4HHAJ+d7vURsQxY1jB5wpuhSNqY\n+SO1zvyRWmf+SK0xd6TWmT/SuDlZIIyIfoDM/Fzd5G2A0SYXcRJwymzHJfUI80dqnfkjtc78kVpj\n7kitM3+kypwsEFKKge+LiB8DNwAnV9O+1uTrB4BPN0zbHbhi1iKU5i/zR2qd+SO1zvyRWmPuSK0z\nf6TKnCkQRsQ5wFhmnpiZn4qIXYCvAPcFvg88MTPvbmZZmXkHcEfD8tfOdszSfGT+SK0zf6TWmT9S\na8wdqXXmjzSuYwXCzPw2sHPd4xManj8dOL3dcc0lg4ODnHXWWQCcfPLJHHHEER2OSJIkSZIkSfNN\n2+9irOaMjY0xMDDAyMgIIyMjDAwMMDY21umwJEmSJEmSNM9YIJyjRkdHGR4e3vB4eHiY0dFm79Ei\naXBwkP7+fvr7+xkcHOx0OJIkSZIkzVkWCKWKBaX5wxa47Wf+SJIkSVL3skAoYUFpvrEFbnuZP5Ik\nSZLU3SwQSlhQkjaH+SNJkiRJ3c0CoSRJkiRJktTDFnY6AEmSJEmS5rN169YxNDTU6TAAWLNmzSbT\nrrvuOhYvXtyBaDa1fPlyFi1a1OkwpJ5jgVCSJEmSpC1oaGiI8869ht1227fTobB+/dpNpl126QgL\nFmzdgWg2duutN3Dc8bBixYpOhyL1HAuEkiRJkpoyV1pB2QJK3Wi33fZl770O6nQYrFs3ylUN0+6/\n54EsWrRNR+KRNDdYIJQkSZLUlKGhIU497yp26nArqL9M0ALq/MtWstUcaAG18tYbeMtxtoCSJHUX\nC4SSJEmSmrbTbvuy697LOxrD+nWj3NTQBGqX+z+EBbaAkiSpJd7FWJIkSZIkSephtiCUJEk9Za6M\noQZzexw1x1CTJEnqHRYIJUlSTxkaGuK48y5nu1336XQosH4dfQ2T3nzpzbCgs4W5u267kfMcQ02S\nJKlnWCCUJEk9Z7td92GHvQ/odBiMrVvDnYMbT7vP/fenb1HnWxBKkiSpdzgGoSRJkiRJktTDLBBK\nkiRJkiRJPcwCoSRJkiRJktTDLBBKkiRJkiRJPcwCoSRJkiRJktTDLBBKkiRJkiR1qcHBQfr7++nv\n72dwcLDT4ahLLex0AOpd69atY2hoqNNhALBmzZpNpl133XUsXry4A9Fsavny5SxatKjTYUiSJEmS\n5pCxsTEGBgYYGRkBYGBggMMPP5y+vr4ORzZ7rB00b3NqBxYI1TFDQ0Mcc+6n2Xa3PTsdCqy/h8Z0\nft2lg7Cg8ymy6tZbOP/457FixYpOhyJJkiRJmkNGR0cZHh7e8Hh4eJjR0VGWLFnSwahm19DQEJ/5\n8NXsucu+nQ6Fe9av3WTa1f99BwsXbN2BaDZ2y+9ugFfScu2g89UP9bRtd9uTe+/1oE6Hwdi6tTRe\nB9h+zwfSt6jzSS5NxKtozbMFriRJktTd9txlXx6050GdDoO194zCDzae9sA9DmTrhdt0JqBZZIFQ\nkrrQ0NAQLz3vIrbdda9OhwLr19FYfnvDpdfBgs4X5VbddjMfP671q2iSJEmS1AssEEpSl9p21724\nz977dToMxtatZXXDWMj3vv++tsCVJEmSpC7hXYwlSZIkSZKkHmaBUJIkSZIkSephFgglSZIkSZKk\nHtZ0gTAiXhgRm9ySMiLuFRGvnt2wJEmSJEmSJLXDlDcpiYhdge2qhxcAN0TEHQ2zPRQ4Dfjg7Icn\nSZIkSZIkaUua7i7GhwOfB8aqx1fVPTcG9FV/f3J2w5IkSZIkSZLUDlMWCDPzvyNib0pX5JuAQ4GV\ndbOMAasyc2SLRShJkiRJkiRpi5muBSGZ+evqz03GK4yIPYE7W3njiDgUuCgzd5/k+ecCpwI7A98E\nXpqZw628lyRJkiRJkqSJzeQmJbtFxBciYkVEbBMRVwI3AzdHxENn8qYRcQzwVWDRJM8fBJwDPBvY\nEbidMgaiJEmSJEmSpFnUdIEQOBu4L/B74EXAgZQxCr8IfKjZhUTEm4CTKK0DJ/M84IuZ+b3MXAO8\nAXhCROw0g3glSVILBgcH6e/vp7+/n8HBwU6HM78t3Jq+pTtseNi3dAdYuHUHA5IkzXcLFy5m6dJl\nGx4vXbqMhQsXdzAiSXPBTAqEjwWOr7ocPxX4Umb+L3Am8LAZLOcTmXkI8L0p5tkf+GntQTXG4QgQ\nM3gfSZI0Q2NjYwwMDDAyMsLIyAgDAwOMjY1N/0K1pK+vj6UPfxZ9S7anb8n25e++vulfKElSi/r6\n+jjs0KNZss19WLLNfTjs0KPd90iafgzCOuuAhRGxLfBo4Ohq+q7AqmYXkpm3NzHbvYDVDdNWA0ub\nfR9pRhYugqXbweq7yuOl25VpktRjRkdHGR4eH/J3eHiY0dFRlixZ0sGo5rdFeyzn3s9c3ukwJEk9\nZI89VtD/zLM7HYakOWQmBcKvA+cDfwbWAJdExBMo3Yu/PMtxrQYaz0SW0mQhMiKWAcsaJk94MxQJ\nylW0RYceybprvg7AokOP7NmraK3mz7p16xgaGtoyQc3QmjVrNpl23XXXsXjx3Og6sXz5chYtsgA9\nH7n/kVpn/kitMXek1pk/0riZFAiPBd4F7A08JTNXRcQK4NvAP89yXNdT1504InYEdqimN+Mk4JRZ\njknz3II9HsiCZx7X6TDmgpbyZ2hoiJeedxHb7rrXFghphtav2+QOSG+49DpY0Pmi3Krbbubjx8GK\nFSs6HYq2DPc/Uuu6Pn8GBwc566yzADj55JM54ogjOhyRekTX5w6YP+qYeZE/0mxoukCYmXcBrwaI\niIXVtPdsobg+A3wrIs4HfgCcBlyamX9o8vUDwKcbpu0OXDF7IUrzVsv5s+2ue3GfvffbIkHNxNi6\ntaxuuK/Cve+/L32LHPhfW5z7H6l1XZ0/9eN3AgwMDHD44Yf3bI8EtVVX5w6YP+qors8fabbMpAUh\nEXE88Bpgr4jYH3gjMAy8NTM3awTziDgHGMvMEzPzRxFxLHABcD/gSsbHPJxWZt4B3NGw/LWbE5/U\nK8wfqXXmj9S6bs8fx+9sr60WLmbx0vuyZnUpKC1eel+26tG7sHZ77oD5o86ZD/kjzZamC4QR8Urg\nDcDbKeMOAnwD+AjwF+BtM3njzPw2sHPd4xManv888PmZLHNzOYZa8xxDTZIkSZ3S19fHPoe9iBuu\nPh+AfQ57ka3NJLWNtYPmWTvoHjNpQXgCcFxmXhIRZwJk5mcj4k/AecywQDgXDQ0Nccy5n2bb3fbs\ndCiw/h4a0/l1lw7Cghk1+twiVt16C+cf/zzHUJNULFxE39LtGVv9JwD6lm7vXcAlSVvcsj0OYVn/\nQKfDkNSDhoaG+MyHr2bPXfbtdCjcs37TBo9X//cdLFzQ+eGVbvndDfDK+TX++qIFi9luyTLuurs0\nPN1uyTIWLZgbxdjNNZNq017ATyaYfiOw4+yE03nb7rYn997rQZ0Og7F1a2m8DrD9ng90DDVJc05f\nXx9bP/wo1l7zJQC2fvhRtuKQJEnSvLbnLvvyoD0P6nQYrL1ntNy5oc4D9ziQrRdu05mA5rm+vj6O\nPPjFfP0HnwDgyINfPG/OfWZSILwOeBpwZvW4Nubg8cAPZzMoSVJ3WbjHfix85ms6HYYkSZIkbVH7\n7LqCfY6aP60ia2ZSIPxn4CsR8RhgMfCO6kYlDwaesCWCkyRJkiRJkrRlzbRA+I/AkcAosB1wOfC0\nzPztFohNkiRJkiRJ0hY2kwLhkcAbM/OULRWMJEmSJEmSpPaaSYHwTOCCiDgL+CVwd/2Tmfnz2QxM\nkiRJkiRJ0pY3kwLhu6r//7Zu2hjQV/2/YLaCkiRJkiRJktQeMykQPmCLRSFJkiRJkiSpI5ouEGbm\nzVsyEEmSJEmSJEntN5MWhJIkaQtYt24dQ0NDnQ4DgDVr1mwy7brrrmPx4sUdiGZjy5cvZ9GiRZ0O\nQ5IkSZp3LBBKktRhQ0NDHHfe5Wy36z6dDgXWr6OvYdKbL70ZFnS2MHfXbTdy3nGwYsWKjsYhSZIk\nzUcWCCVJmgO223Ufdtj7gE6Hwdi6Ndw5uPG0+9x/f/oWdb4FoTSRudICdy63vgVb4EqSpKlZIJQk\nSVLXGhoa4tTzrmKn3fbtaBx/Wb92k2nnX7aSrRZs3YFoNrby1ht4iy1wJUnSFCwQSpIkqavttNu+\n7Lr38o7GsH7dKDddtfG0Xe7/EBYs2qYzAUnTmCutb8EWuJI0F1gglCRJkqQeMzQ0xHnnXsNuHW59\nC7B+gha4l106woI50AL31ltv4LjjbYEraf6zQChJkiRJPWi33fZl770O6nQYrFs3SkMDXO6/54Es\nsgWuJLXNVp0OQJIkSZIkSVLnWCCUJEmSJEmSepgFQkmSJEmSJKmHWSCUJEmSJEmSepgFQkmSJEmS\npC60aMFitluybMPj7ZYsY9GCxR2MSN3KAqEkSZIkSVIX6uvr48iDX8y9Ft+Hey2+D0ce/GL6+vo6\nHZa60MJOByBJkiRJkqTW7LPrCvY5akWnw1CXswWhJEmSJEmS1MMsEEqSJEmSJEk9zAKhpPln4SL6\nlm6/4WHf0u1h4aIOBiRJkiRJ0txlgVDSvNPX18fWDz+KviXb0rdk2/K3A/VKkiRJkjQhb1IiaV5a\nuMd+LHzmazodhiRJkiRJc54tCCVJkiRJkqQeZoFQkiSNW7g1fUt32PCwb+kOsHDrDgYkdYetFi5m\n8dL7bni8eOl92Wrh4g5GJEmS1DwLhJIkaYO+vj6WPvxZ9C3Znr4l25e/HcNTmlZfXx/7HPYiFi25\nN4uW3Jt9DnuRuSNJkrqGYxDOVQsXwdLtYPVd5fHS7bwLqySpLRbtsZx7P3N5p8OQus6yPQ5hWf9A\np8OQus7ChYtZunQZq1ffAcDSpctYaAtcSWqrthcII+IQ4FzgIcDPgRMy838nmO8S4LHAPUAfMJaZ\n27cz1k7q6+tj0aFHsu6arwOw6NAjvQotSZIkad7p6+vjsEOP5uprPg7AYYce7bmPJLVZWwuEEbEY\nuBh4F/AJ4IXAxRHxgMxc3TD7wcAjMvOH7YxxLlmwxwNZ8MzjOh2GJEmSJG1Re+yxgv5nnt3pMCSp\nZ7V7DMLHAOsz82OZuT4zLwBuB55UP1NE7ATsBPykzfFJkiRJkiRJPaXdBcL9gZ82TMtqer1DgFXA\nlyNiOCKujIjD2hGgJEmSJEmS1EvaXSC8F9DYlXg1sLRh2jbAIHASsDtwIXBZROy8xSOUJEmSJEmS\neki7b1KyGljSMG0ppbXgBpl5MWWswppzI+JEShflz073JhGxDFjWMHn3GUcr9SDzR2qd+SO1zvyR\nWmPuSK0zf6Rx7S4QXg+8vGFaUFoIjk+I6AfIzM/VTd4GGG3yfU4CTmkxRqnXmT9S68wfqXXmj9Qa\nc0dqnfkjVdpdILwCWBwRLwfOo9zFeGfgqw3zbQO8LyJ+DNwAnFxN+1qT7zMAfLph2u7V+0uamvkj\ntc78kVpn/kitMXek1pk/UqWtBcLMXBsRT6QUB98D/AJ4cmbeHRHnAGOZeWJmfioidgG+AtwX+D7w\nxMy8u8n3uQO4o35aRKydzc8izVfmj9Q680dqnfkjtcbckVpn/kjj2t2CkMz8MfCICaaf0PD4dOD0\ndsUlSZIkSZIk9aJ238VYkiRJkiRJ0hxigVCSJEmSJEnqYRYIJUmSJEmSpB5mgVCSJEmSJEnqYRYI\nJUmSJEmSpB5mgVCSJEmSJEnqYRYIJUmSJEmSpB5mgVCSJEmSJEnqYRYIJUmSJEmSpB5mgVCSJEmS\nJEnqYRYIJUmSJEmSpB5mgVCSJEmSJEnqYRYIJUmSJEmSpB5mgVCSJEmSJEnqYRYIJUmSJEmSpB5m\ngVCSJEmSJEnqYRYIJUmSJEmSpB5mgVCSJEmSJEnqYRYIJUmSJEmSpB5mgVCSJEmSJEnqYRYIJUmS\nJEmSpB5mgVCSJEmSJEnqYRYIJUmSJEmSpB5mgVCSJEmSJEnqYRYIJUmSJEmSpB5mgVCSJEmSJEnq\nYRYIJUmSJEmSpB5mgVCSJEmSJEnqYRYIJUmSJEmSpB5mgVCSJEmSJEnqYRYIJUmSJEmSpB5mgVCS\nJEmSJEnqYRYIJUmSJEmSpB5mgVCSJEmSJEnqYQvb/YYRcQhwLvAQ4OfACZn5vxPM91zgVGBn4JvA\nSzNzuJ2xSpIkSZIkSfNdW1sQRsRi4GLgE8C9gQHg4ohY2jDfQcA5wLOBHYHbgQvaGaskSZIkSZLU\nC9rdxfgxwPrM/Fhmrs/MCyjFvyc1zPc84IuZ+b3MXAO8AXhCROxMhPwpAAAgAElEQVTU5nglSZIk\nSZKkea3dBcL9gZ82TMtq+qTzZeYIMALEFo1OkiRJkiRJ6jHtHoPwXsDqhmmrgaUtzjehiFgGLGuY\nvCfA7373u0lft3LlSv50U7J+1Z+aeZue9efh21i5cn9+85vfbNZyXN/NaXZ9H3nkkXsDv8nMezbn\n/TYvf37K+lV3bs7bz3t/Hv4tK1fuOUv54/qeTrPrey7kz503Xcc9q/6wOW8/r/15+GZWrtx2s3MH\nXN/NmMn6ngv589sbv8/dq+7YnLef10Zu/xUrV/71rOWP63tqza7vuZA7N970Q1b5XU7p9uFfsXLl\nIbNy7Ob6nl6z63su5E/+6gf86c9+n1O5beWviJUrZiV/XN/Ta3Z9T5Y/fWNjY1swvI1FxMnA4zLz\nqLppnwN+mJnvqZv2P8B3M/P0umkrgadk5mAT7/N24JTZjF3qEg/IzF9tzgLMH/Uw80dqnfkjtcbc\nkVpn/kit2yR/2t2C8Hrg5Q3TArhwgvk2dCeOiB2BHarpzRgAPt0wbWvg/pQuzeubXM5c8ADgCuCx\nwC87HEsv6Pb1vflNA8wfta7b17f5s7Fu/z67Tbevb/NnXLd/l92m29e3ubOxbv8+u023r2/zZ2Pd\n/n12m25f35vkT7tbEG4N3Ai8FzgPeCHwHkrl8u66+R4KfAs4CvgBJWnvl5n/2LZg54iI2I+yYYrM\n/Hmn45nvXN/zi99ne7m+5xe/z/Zyfc8ffpft5fqeX/w+28v1Pb/4fbbXfFzfbb1JSWauBZ5IuUvx\nHZTWhE/OzLsj4pyIOLua70fAscAFwO+AXYBj2hmrJEmSJEmS1Ava3cWYzPwx8IgJpp/Q8PjzwOfb\nFZckSZIkSZLUi9raglCSJEmSJEnS3GKBcO67A3hH9b+2PNf3/OL32V6u7/nF77O9XN/zh99le7m+\n5xe/z/Zyfc8vfp/tNe/Wd1tvUiJJkiRJkiRpbrEFoSRJkiRJktTDLBBKkiRJkiRJPcwCoSRJkiRJ\nktTDLBBKkiRJkiRJPcwCoSRJkiRJktTDLBBKkiRJkiRJPcwCoSRJkiRJktTDLBBKkiRJkiRJPcwC\noSRJkiRJktTDLBBKkiRJkiRJPWxhpwOYqyLiIOA+mfmdTsfSiohYCrwD6Ad2BX4HXAyckpkjnYyt\nXSLiUcBIZg61+NpvAttk5tq66f8EfBJ4XWaeGRG/BE7LzI/NUtg9bR7k3V8aJq0Dfg18LDNPr+a5\nAFicmc9rd3zV+38TuDoz39TCa/cG3gP8HbAtcCPwb8AHMrPxs6sNuj1nACJiGXAK8I/A/YDfAF8A\n3puZf5zidS+q5tl1C8X1r8CCzDymhde+CLgA+F5mHjrB8x8FTgBenJn/PguxdnS7Mld1e35U+5Qn\nZObXGqb/PXBZZm7xC/3Vdv/AzLxkCy3/V8D96yaNAXcB/w94VWZePwvv0XJ+RMQi4CWZee7mxtFN\nujl3ImIv4JeUY7CdMvNPDc/3A58FPpmZx1TH/FcASyjnTL8E9s/Mn7cx5radT0yQc6uAq4GTZuMz\nb+l983wxT3KsZgy4g1JrODkz75qF92jLtjcingW8AjgIWAsMAm/LzP9r8vWnUPbTh1ePn045z7qt\nyoXTMnO3LRP9lmELwsl9Edi/00Fshk8CRwDPBx4EvBA4DLi0gzG12zcpO/pWjdU/iIh/BD5B2Wic\nWU3+a0qBRLOj2/MO4DnALtW/fSgFtfdExPM7GtW4pwGnzvRFEbEN8C1gNXAk5Xt6B/Ba4L2zGJ9m\npqtzJiJ2oRQCHgocDewHnAg8Erg6InaaZhFj0zzfSeuAFREx0YHhU4HZLKq/EjhuFpc3X3R1fkyj\nXb/98ynHk1vKGPA6xvebuwFPAnagfH+d9lzgbZ0OogPmQ+6MAf8wwfRnsPH29ypg17oGAXN5vzIb\n6nNuV8r54Qjw5Yjom8X30NS6PcfGgEdQfkd7AE8GHgZ8cJaWv8W3vRHxHuBs4D8o5/SPA/4EXFkV\ncJs1Vi3v/sDnge2q6f8JLJ+1gNvEFoSTm60NZNtFxPaUnd9hmXltNfmWiHgB8NOIWJGZP+hchN0n\nIh5NSfLTM/PdtemZeUfHgpqfujbv6vwxM4frHl9QXZ16BnBhh2LaYKoWWdN4HLAsM19aN+3miLgv\n8H7g9ZsdnFrR7TnzEeBW4LGZub6adktEfAe4BjgLeEGngttMI8DtlGLg2bWJEXE4cDcwPMnrZmw2\nrtbPU92eH3NBO9bhXQ37zdsj4lWUk7TlrfQEmUW92phiPuTOtyjb30/XJkTE1sATKPsXADLzHjbe\nHs+Hzz6d+py7PSJeDdwG/BXwvc6F1VO6/XfWB9xR9zu6rSq4fRx4ySwsf4tueyPiMOANwKMz88q6\np15YHYOeBhw1w8VuRV1xPDPXAGs2N9Z2s0A4gaoL3l7AORFxWNX8fH/gQ8DfULrrXgi8s9qp1JpT\nvxbYl3Lg/zXgpZl5V/Xc8cB/AW8CFgDvo7Rw+xilhd83gedNdJBfdY140QShjgEPyMxfTzB9jLID\nrBUIycyMiIcAN1XL3RY4k1LxXwb8FjgjMz9aPb+4ivM5wDbA14ETMvP31Tr6MaWr4faUq09LgA9U\n62gb4KeUZsbfrpb3F+DZwFuq9fQd4KWUFlZPp5wkHls3/67AAPB4SjX/f4DXZ+af65o2P4OSwHtV\nn/XozLyxaqoPcFlEvCMz3xkRD6MUMv4a+APwr5n5rgnW60Yi4q+r9z43M9/c8NyGLgHV93QXcO/q\n86wGzsrM99bN/07gZcBiSvezgyldHP69+m7OpuycV1G6P7w2M9dNF+N8MA/ybir3UJqt12wXEZ+k\n/H5XUQrPtVapVCdGLwf2BP6P0qX9O3XPv4HSymoH4PvAP2fmD6vnvll9rr+i5OfvKa1eP1n3/NXA\n24EfAj/NzP7quXcAx1K6kzUORfAXYElEPDozv1U3/VPAN+pi26hLXGNXuOr5FwGvBg4Afga8rHYx\nIyJOoHynuwM/r2KfC61I5pxuz5mqdeBTgX+sKw4C5aAqIt4NXBgRr6BsV38JvBX4Z8pv7ssNy3sS\n5Xd9ILAe+C6le8qtVRey/wT+pZpnZ0qXshfVLvRUr38/8ADgEkrerqlb/uOBd1XLv42St+dN8Hnr\nP/dFlFa7Z9dNfwblCvML65a9gLIvfA6lRcdK4PzMfGvdPFPtPzbqQhkRz6zW1b5AAm9o7KY633V7\nfszws25HORZ6GuWY7BuU7oK3VM9Pt12u3+7eALw1M79Yxfwo4JHVOnxs1er3A5T9yyJKl7JX1S4+\nTbKNPzYzZ1p0qB371L6brSm/6X+i5O/V1fv+uHp+0mPWhnV1L0ru/wk4KjPXRsQ/AO+mfO83UI7r\n/rPabpxfvW49ZduwHfP8WG0e5c5FwPsjYuu61oGPp/wmN7ymagRwBeV3U1suEXER8LvMPKF6/BbK\ncBj3qc5FtqccYz0UuIWpz6k26kIcEQFcD+w9wb5xf+BK4LzMfEs1barjvoWU/P8nyv7hu8ArM7O+\nC+h0VjfEsFG3yWra1ZTtxjurxycAJ1O2G9dR8nGTPI+Ij1CGEPnbzLw5It5OOf9bRjnGfU1mfncG\nsXa9eZRjjVY3TpjqnGayc19Kq/WNtr2Z+etpljXteXiDFwP/r6E4WPMS6gp91YXdD1COu24GzsnM\nD0/wupuq110fEUdTiqgbuttXrRLPpNRNfg98uHb+N5fOf3r1qth0nk4ZA+n1wKuqg46vAD+i9E8/\nBngmVTe9iHgEcB7lxGFf4FnAoyk/4JpDKM1uD6N0x3sPJWFfAfw9JRGOnySeVzLe9aL+366UHdJG\nqsT/OPCOiLgpIj4aEc+MiO0y82d1O8mzKD/0JwFB6Zb8wYjYvXr+Y8ATq89zOOWA7IK6t3oJpUvT\nP1YbjosprSX+ClhB2fk2njydxnj3sb+mJPcPqvl/wsYnURdRkvthlIPeh1JtLOqcQvk+HgbsxHhX\nx4dV/z8XOCMi9qVsGK+t3uuVwCsj4rWN66/BAcBlwG2Z+c/TzAtlffyC8jv5AKVr6UMAIuKN1fPH\nUJpkR7Ueai6kbBAeQvkN9jP5b2I+6uq8m0hELIoy1s3fs3FXqSdRdiLLgTMov9EDq9e8mVJEf0P1\nub9NKXTvWT1/IqWIdwzlt/xt4JsRsXPd8t9IKXAcQMmjc6K09Nug2g68BHhqRDwuIh5ave7YCYqD\nAJdTcvSKiPh/EfHuiHgssCYzfzHNqmjsavIuSqHmIMrO/Ozqsx1COTg6mfKd/gfwmYjYcZrl96pu\nz5m/ohw8/e8ky7uSUoD4q7ppj6/ie2v9jFHGSbuIMuTD/pQLZA9g4+4pyyjr5CnAY6rlvLF6/YMp\nOXohZb/4E8r+o7b8R1Jy6r8o+6J3A2dWhbipXAQ8qjqRrHkaZYzF+tYDb6R8V8+hHMi/A3hTlCvc\nzew/6tfFY4DPUI4DDqQccF8UEXtME+t80+35MZXGlif/TTlOe3oVwxLgkpi6u2CtCNK43f0U49vd\nV1EKcR8BnlYVIq6gHG89jpJnB1K21fUat/HnzOTDRemWfyrlQvTPqskfBZ5H2W+toBRgvhblYjdM\nf8xaK6R8gXLB7slVcXA55eLBmZTjr/cD50bEEyhdT19NaV22C+X39B/M/2O1+ZA7Y5SGCGspv9X6\nz9a4/a01rGj0lepz1Dy6el2taHYk8Jss42ROd041WYwbqeb/KvCpuuLgdMd976lieypl/d5KOVZb\nPMV717/nNpTjzp9Sio+Txlf3mqOB0yn7qgOr1325Wlb9fKdQLoodWRUHn0rZrjyPsp6uAb4QEb1W\nk5gPObaRKBd9X0nZh9SmTXlOw+Tb0022vU0sC6Y4D5/AwZQhbjaRmTfUzm2qPLuMcmH3IZTu+W+I\niInW5aGUbcTfUI69YHxfu4xy8e5XlOPaVwBvj4hnRMTBzKHzH1sQTiAz/1BVq++qqvLHVH/XutDd\nWFWwL46If6FU8V+Smf9VPX9LRHyN8iOqWQicmJl/jIgBSuKeV7tiEhFfp5zMTxTPXZQDrJl8huMj\n4nuUDczLKIOhr46I+vHzrgQGshqEM0qz4FOA/SPiLsrJ0ZPrKvPHUXfCBHy9rrXfUspG6GO1KxPV\nFaOvRsSCutYhH87Mq6rnv0G5IvDB6vF5wJeqA9rHUMaiekTttdX38LOIOLkuhndk5mD1/NnAa6rP\n//tycY4/ZubqKol/Vvcd3hDlKviplALNRPooYzb+H/DoiHhBZjYeBDfKulaJ74+I11M21j+h2hBk\n5qVVvP9E3RVMYG/KzuGWaif6JKDV7qBdZz7kXeWiGL9ZydJqGadn5n/WzfPD2hVY4APVTu9gysnQ\nqyi/k4uq519fFSdeRbmy9AbKleNaq723R8TfMd4aF+DyzPzX6jO+BTiJsrP8VsNnvKZaLx8G/gz8\nR2Zu1Cqrbt611QHK6yktgd9IOQH8TUQck5mXN7+K+FBdS5bTgS9Web8XZUd6S9Xy5f0R8YMqNjWY\nBzlTK1r/YZLna9N3pBzwQbkaXGsFf1hD3K/K8cGsfx0Rn2Pjk7sF1Tw/ql7/H4xfTDoGuDYzT6se\nvzNKK6uaVwIXZ+YHqse/iLKTeSPloHFCmfl/EfEbyjhYn66KMQsz89pqH1UzRLlhydXV449FxFsp\n3801TL//qHcC8IXMHKgevzcillBalvWMeZAfNfX7lJoFtT+qAteRwPLM/Ek17bmU38dRlML2VCbd\n7mbm3RGxtvr7zoh4MuVY5W9qF5KijK/704g4MKvWfEyyjc/MyQoOH4yIWm4tqOL5KqWF31hE3JvS\n2uOptX1fRLyEcqOsF0fEvzP9MetWlAsIO1K6lI1W018LXJCZtfGkfxkRB1BaNX0lIu4E/pKZK6vl\nPqCKbd4eq82j3FkPfIlSOLs0SkvtJ1OO/VdM8bpa8fArlAusu1CGjDiMUij4W8pF07+rHsMU51SU\nYnYzllF+W19raJQw6XFfRJxJOcb7m8z8fvXeJ1BaOT2Duu7VDepzbkn1//OmyNFGJ1A+74XVe76G\n0uJ+w8XoKgdfCTwqM2+oJu9NKdreUrUI+xdKL61u7247I/Mox75fHctsRfkd3UE5XqmZ7pxmwu1p\nZt4zwbZ3umVVH2XS8/BGOwB3NvEZXw5cWVc/+WWUVrCvBxpvoLKy+v+OLD1h6p97DjAKHFfVNjIi\nTqLkzd7MofMfC4TNeTDjRbOaPkrLhr0z8wcRsao6mD+AkqwPBj5XN/8fsup+UR1wwcZ3/7mb0ix8\nExFxDhOPwTQGHJCZv5nodZn5ceDjEbEDZSd2HHB6RPw8My/J0i3pyVGuAgXlysMY5eBsv+r/79Ut\n72eUnV3NTXXPra4KdC+I0iU3GN/5LqDspKEczNWsrl9GtQ62oqzXB1OaCP+xIbn+Ui279rob6p77\nU/XaiezPpq1UrgJ2iIidc+Oxb+p9h3KAeS7w4Yi4IjNvnWReKFdB6t0FLIpy1WA36q5UZOZIRNTP\n/y5Kc/BjI+Iy4L8y87op3mu+68q8oxw0fbeab5TSPaXxgOvGhsd3Urrv7kQ5eWm8onUVcECUrlF7\nAv8WpYtyzdZsnAsbflfVgQdMnhtvoRxE7gg8dpJ5astaRWmR9bbqJOmJlCt8X4yIB06RR40a8xbK\n/uirlKvQ34+In1IO7D+RmXc3udxe1205U2upuisTn0DVWl7Uj/U6YZepzPxFRKyuDgaXUz7XQWw6\nltJk+4wHU1qz17uW8aLagyktQupdxcYHwpO5iPFxsJ5Oae3VGP/FEfHoiHgfZX91MGWfsaDJ/Ue9\nA2hoOZWZp0wyby/ptvyoqe1T6j2SctM0KL+X1bXiYBXbSERk9TmmKxDOZLu7P/DLrGtlnpk/i4g/\nVO9VKxBOto2frBvuuymtXpdSWmccAby5bp3sRzk+rM+BdRFxbfW+zRyzPoXyXX+r2pfVHAAcGBEv\nrpu2gMnHCO3FY7VuzR0o29/anYEfQ2nxd1PDucWEqoJFVq/7LeXc4xLKRVIoLdpfVc071TlVs95G\nWae1lke1LvFTHfftQ1lv32r4TNtUcUymlnMA96IUPS+ICOqKUFM5gJIHQMlHSu5SxbEj5eLzH9l4\n//4ZSguxX0TE9ym9zz6RDcOM9KBuzbGnVu/RRym4vQC4JsqwXncyxTlN9feplELmlNvT6c6P6h5P\neB4+Sey/r2KezgHA3zd8NwuAhVFapTfrwcB19b/12oWpKBdx58z5T681523VQsqVoYMoXYseWv29\nH6WC/3eUJsF7UbpevJi6jXtlooOiZu9g+Na6963/dzClGflGIuJR1QYEKFcpqo394yhjRDy+mu/f\nKGP83UXpuvswxq/grGV6G3601Q7sWspdKG+kdCV+4QSvaVwPk62DhYw3Ea7/zPtRN7DwBHFOdgVq\ndIJpCxr+bzRGGdNwjLLT+zObdnFuNNF662P8c0+ac1lapuxNOUDYAfh8dQWyV3VV3tX5XWbelJm/\nzMzbJrkaO9GBUB8T/06h/EYXMH5R5/kNMT2YjW8SMtnvcCJ7ULqLbV8ta0IR8dKIeE7tcfX5zqZ0\nd1xEaU4/kYl2nhPGl5l3Z+YRlAPViylj1vwgIqa60q9x3ZYz11bLPnSS5R1axVNfuJvwYClKK6qf\nUbptXENpUTFR6/DJ9hljbJoj9etisn1IMweH/005uFxM6V68SYvDKON/1g70/5PS8rF2UjXt/qNB\nM/vvXtRt+VFT26ds+EcZA7Nmuv3GRDb8bifZ7v5wku1us+81k30QwMrqs/2Yst5vobT4qt0Jcrr3\nXTvN8qGM6fUo4IgoN+2rWUi562b9d3JgNe8mevRYrRtzp/Z7+Bpwr4g4glLM+EKT71nzFcrF00dT\nGg1cCTw8ynhxu1GNwTzNORVs2l13on3HFZTzqDdFxD4N80123Fd7/tENzwely+JkVtZtU4aq47lP\nUfXEmiDexpin28/8hdKCeSV1++LMvJ1ScKl14X8J5Thvz4kW0kO6McegtHi7KTNvzMzvZearKcON\nHUsT+4vMPIPmtqdbYt9zLZMcf0bEUyLis1FaHS+kHJfVfzcHUi6YzaSwPWnOzLXzH1sQTq5+w3g9\nZRyA31RXSIgycPHLKZXykyhd846tvSDKmHf1reNalmWA5d9PO+O4HYC3RMT5mbnhqk2WbhqrgOEo\n45H9E6VJeq2Lbq0C31fF/hfKFbDLq+eXU3a0+03wnn9PaSa8fY53CT6xbnkzdT2lcPGnHB9APihX\nq46r5mm2GTyUE8e/b5j2CMrVjduneN16gMz8U5Sm8pdExPE53o2tKdXrf0M5ea3djOHelHEGan+f\nyviAxh+NMiDxyyiDzfaKbs672XjPuyLiNko3lmvrnjoCuDpLF6/fAbtn5v/UnoyIf6UMyN7MVd9G\n/0oZe+3XwCci4qAsd91qdCDw2Ij4r8ysP+D4MyVPaq0t1rJxV8Z9aFKUMQ0fmZlvpxw4vikifkI5\nyPTO6xPr2pzJzDuidAN+R0R8KauBuKu4ajck+HzVGmo7pt7mHwv8b2bWWnYQZTiKZvc/Q5SW9vVW\nULppQdmHHNbw/CPY9Gr1RAYpLeaPA+6b1TAbDU6m3FCh1l3rPsD9KIXzKfcfE/g5Zd+9QZQ78n0i\nx7tR9oquzY8Z+BmlBfqGu/1GGbdoX8bH75t0u9zEdrd+Hf4MeEBE7Fh9ntog89vXvddmqY5VX0Jp\njfheyvdzI+VmJYdRWlbUthF/TRln6ibKfmiqY9arM/OqiHg/ZWiPL2XmnZTfxT5V4bW2Tl5Jaa3y\ntvrP32PHat2eO2PVa9dULZOeUv17fLOvrXyFMv7ljcDHM/OnEfFnyv7p25k52sQ5FTR3bPQ/mfmp\n6vd/DvD4Jo77vkzJjfvleBfjBZSWemfTMLTMNOqLLRvFWy1zr7p5a/uZL1TP91FaNNbO0UYy8/Io\nXSgvr85Jr4oybu9uWW7w8PUqf26nFDg/RW+ZFzk2gQXAVtOc01zTxPZ0w/KnOz+aYdw1nwJeERGP\nymrINIAo42G+jtLle31EXA88Lutu+hMRz6aMq/myhpa7Ux2n/hx4RtQNtxGl18gOlALknDn/sUA4\nuVWUpr47UAaKfBulefeplDEiPk45GVkbEbdSrkg+lFLhPoFSZW52zInZ9iXK3UkvjzL+2PcoJxrP\nolxxejblCtddlB/qbynV+zMpVx8WZ+aqiPg4cFZVGLuLcmXsmhzvsljvVkpz9mdFxFVU3UOq5xbT\n/C2+azvSr1MONv8zSpexPsrOcm1m3h7lLsbTnfitAh4SEddQdu4nRcQZlK4GB1LuZHl2Q7FjUpl5\naURcSOmm/bX6g8kmnQWcEhE3U046T6V0pxmrDgAeD+xVbRwXUAY6nuld/7pdN+fdbHk/pQvvbylF\ni5dRuky+uO75d0TEMGWn8VLKleUPzvSNIuLllHXWTyn0PQ94J2W8m0YfrN7nS9UJ1q8oB7ivBb6f\n43egu5ayw/0/4P6U8WeatYZycWOYctB7EOWAtNfyYCa6PWdeRRlo+htRxnT5BaWw8XaqMQPr5p1q\nm38rZX92OOVk47mUcf+aLVp8jHLjqndTuhI/jdKNs3bCcgbwvxHxOkqXtUdS1t+rp1twVfC4mNI1\n8cIp4j8qyl0id6R0//oL492BJt1/TLCsD1K6m32HUix5NuWK9xXTxToPdXt+TCszb6h+X5+Mcsfv\n1ZSbB/yW8fHRptouT7fdXQU8KEoXr8spJ7IXVsdmSyjHV1dldUfVWfpMv4yI0yhjrX0sM38UZRib\nD0bE3ZR8+RfKceenZ3jM+l5KD5f3U4oZZ1BOVl9PKXYcWs1TW0ergO0jYj/KyXivHKt1e+7U7y++\nSBkq6LdZbigyk9d+mzIMxm6M94y6kjKeWG37P+U5VTXPtcDRUcaNW8rGN9Bq9ApKK97nZBm/erLj\nvg9luZvy2ZTiynGU7p5vorR6PGmK99g+Iu5X/b2wmv/5lGFnavGeGqW17SClZeG96l5/FuVmPj+q\nYnp19VmvoRS6AMjMb0a5EHhulBsxbA28ryr2/D9K9+17Uc5be818yLGdoowVCOV3fRylwVCtdeOk\n5zRNnPvWtr1BOTac7vxoRjLz+1HGavxilBvBXU45/voXSivXI6pZazWEMynbkX0oN+5qvBFrLWaA\nh1Zx1ruQcmw7EBEfonQTP56yXZlT5z9t72IcEX8TEddExB8j4oaIeNkk8z03Im6MiLsi4uLY+A6d\n7fARSrPnT2TmasoBwTLKxuxzlKuStSr+2yl3Ivou5QD8z5SN+yFMbiat32akasH3d5RxMk6jHMxd\nSvmh/U1m/q66OvECSmX6Z5QrsG+uPkPtjpGvqR5fTLkC9WvKQO6bxJ+Z11DGevkA5S5Yz6e02FtT\nt7xmPnPtit8YpXntndV7f41yZerpjfNO4SzKSdQ7sowb+CRKi48fVXGekdUdwmbgVZSDgH+rrpZN\ndueziWL8IGWA7E9Rrg4k5USv1uT4KZSD3aspBx+/puwAeknX5t1mLr/+dR+m/FY+SBkS4HDKlauf\nVs9/iHLgeQbjrZ6enOPjT00UQ/3vtHbVak9KEeItmTmcmX+m/L5PjgmatGfmr6pY7qSMpZaUQkpS\ntiM1r6D8jn9E2f68mY1Nuo6qllUvo5yY/axaB2/MzMsme426O2eyDD59OGW79zHK7+m8KsaH11op\nNRHLhyndvy6ljDe7O6XwvV+Um2hNF8evKGNqPoHy230MpXVt7fkfVst7ISXvXke54cnHm/mclKLi\ntmzcvbj+8xxN6a7yY0pe/Rslz2r7z+n2H/Wf5Zpqea+plvd04B+yDHzda7o6P2aw/BdTbqj2ZUpB\n44/AY3L8RhyTbpeb2O6eRykefLU6NnsKZd1cSTnO/D6lGD/TmKeb//2UgtxHq8dvoNzM4EJKju9E\naXFR6wUy1THrBtU6ORl4SUQ8PDN/QMnt51Py5VTK56/l9oGAyvcAACAASURBVBWU49rrKN3teuVY\nbT7lzpcphalJbyg12Wur38t3gF/X/dZqrY0ureZp5pzqzZTC9jWULsiNBcL69/wxZf2fGRHbM/lx\nX23Mz9dThrL4N0qx7gHA39XFO5H3VfHcSmkd+Wbg1KxuxJDlhijvo5xLXUsZS/Tiuhg/S7mD8RmU\n7cqBwBOqY8lGr6Gcg74mMz9dve791bp6LfD8us/SS+ZDjn2H8d/REKUlaH9m1gpb053TTLU9rW17\nf0j5nNMta7IYJ5WZJ1Py51hK7nyR0iL3iCzj2JKlN+YTgIdX73sepdHSWydY3gjlGO7fGf/uas/d\nRalFHEzJmTOA12fm/8y185++sbEt/dsZF6XLzI2UO+x8Nsrd/C6n/JCuqJvvIMoP7nGUH9tHKM2R\nj5pgsVJXiIgnUFpa1e7GtJAy+P5Rda2vJEnaiPsPSZIkbWntbkG4F3BJddWhdkX+m4w34ax5HvDF\nLINdrqFcNXxC1b1B6lbHUrrlPCTKuBEfppzgNd5dWZKkeu4/JEmStEW1tUCYmT/KzBfVHld97v+W\n0lyz3v6UJqW1140AI0x9u3ZprjuR0j3zO5QxBfamDEA80V2nJEmqcf8hSZKkLapjNymJcueaLwHX\nZuYlDU/fizLIcr3VlMEvm1n2Mkof/noLKIOn/jjr7pQotUs1Fkh/p+OYjvkjtc780ZbQLfuPzWX+\nSK0xd6TWmT/SuI4UCCPiAZTi4A2Uu0A1Wk25M1q9pYzfGWY6J1FumLGJb3zjG00uQuo6093VuVnm\nj3qR+SO1zvyRWmPuSK0zf6TWTZg/bS8QVnfHvAz498x83SSzXU9dd+KI2BHYoZrejAHK3f/q7U65\nG46kqZk/UuvMH6l15o/UGnNHap35I1XaWiCMiPtRioNnZObpU8z6GeBbEXE+5ZbTpwGXZuYfmnmf\nzLyDMnh3/XuvbS1qqbeYP1LrzB+pdeaP1BpzR2qd+SONa3cLwmOAHYG3RsTbqmljwIeq6WOZeWJm\n/igijgUuAO4HXAkc3eZYJUmSJEmSpHmvrQXCzDyN0hqwmXk/D3x+y0YkSZIkSZIk9batOh2AJEmS\nJEmSpM6xQChJkiRJkiT1MAuEkiRJkiRJUg+zQChJkiRJkiT1MAuEUmVwcJD+/n76+/sZHBzsdDiS\nJEmSJEltYYFQAsbGxhgYGGBkZISRkREGBgYYGxvrdFiSJEmSJElbnAVCCRgdHWV4eHjD4+HhYUZH\nRzsYkSRJkiRJUntYIJQkSZIkSZJ6mAVCSZIkSZIkqYdZIJQkSZIkSZJ6mAVCSZIkSZIkqYdZIJQk\nSZIkSZJ6mAVCSZIkSZIkqYdZIJQkbbbBwUH6+/vp7+9ncHCw0+FIXcX8kSRJUqdZIJQkbZaxsTEG\nBgYYGRlhZGSEgYEBxsbGOh2W1BXMH0mSJM0FFgglSZtldHSU4eHhDY+Hh4cZHR3tYERS9zB/JEmS\nNBdYIJQkSZIkSZJ6mAVCSZIkSZIkqYdZIJQkSZIkSZJ6mAVCSZIkSZIkqYdZIJQkSZIkSZJ6mAVC\nSZIkSZJ6yODgIP39/fT39zM4ONjpcCTNARYIJUmSJEnqEWNjYwwMDDAyMsLIyAgDAwOMjY11OixJ\nHWaBUJIkSZKkHjE6Osrw8PCGx8PDw4yOjnYwIklzgQVCSZIkSZIkqYdZIJQkSZIkSZJ6mAVCSZIk\nSZIkqYdZIJQkSZIkSepS3pVas8ECoSRJkiRJUhfyrtSaLRYIJUmSJEmSupB3pdZssUAoSZIkSZIk\n9TALhJIkSZIkSVIPs0AoSZIkSZIk9bCFnXrjiDgUuCgzd5/k+UuAxwL3AH3AWGZu38YQJUmSJEmS\npHmvIwXCiDgG+ACwborZDgYekZk/bE9UkiRJkiRJUu9pexfjiHgTcBJw6hTz7ATsBPykXXFJkiRJ\nkiRJvagTYxB+IjMPAb43xTyHAKuAL0fEcERcGRGHtSc8SZIkaeYGBwfp7++nv7+fwcHBTocjSZLU\ntLYXCDPz9iZm2wYYpLQ03B24ELgsInbekrFJkiRJrRgbG2NgYICRkRFGRkYYGBhgbGys02FJkiQ1\npWM3KZlKZl4MXFw36dyIOBF4DPDZ6V4fEcuAZQ2TJ7wZiqSNmT9S68wfqXXdnj+jo6MMDw9veDw8\nPMzo6ChLlizpYFTqBd2eO1InmT/SuDlZIIyIfoDM/Fzd5G2A0SYXcRJwymzHJfUI80dqnfkjtc78\nkVpj7kitM3+kypwsEFKKge+LiB8DNwAnV9O+1uTrB4BPN0zbHbhi1iKU5i/zR2qd+SO1zvyRWmPu\nSK0zf6TKnCkQRsQ5wFhmnpiZn4qIXYCvAPcFvg88MTPvbmZZmXkHcEfD8tfOdszSfGT+SK0zf6TW\nmT9Sa8wdqXXmjzSuYwXCzPw2sHPd4xManj8dOL3dcUmSJEmSJEm9pO13MZYkSZIkSZI0d1gglCRJ\nkiRJknqYBUJJkiRJkiSph1kglCRJkiRJknqYBUJJkiRJkiSph3XsLsbSunXrGBoa6nQYAKxZs2aT\naddddx2LFy/uQDSbWr58OYsWLep0GJIkSZIkaR6yQKiOGRoa4kunD7L3zvt2OhTWrV+7ybSfXPh7\nFi3YugPRbOxXwzfA62DFihWdDkWSJEmSJM1DFgjVUXvvvC+x+/JOh8Gae0bh+o2n7bvbQ1i8cJvO\nBCRJkiRJktQmjkEoSZIkSZIk9TALhJIkSZL+f3t3H2VXXd97/H0mmZnwOGYGQzBCeIpfaIwCal3A\ntVbpbVEu2nY1KLWLtFrr07JX7IN6RUGLWupV1KEi9CKtLVCrVy2KVVHQhUzrXWKhI9qvPMqTMCED\nCg2ThGTuH/skTCZPZ3Zmzp5z9vu1Fiuzf2efvb9nn/kcku/57b0lSVKNeYqxJHUgb/LTOm/yo+nM\nT2vMjiRJUn3YIJSkDjQ6Osp1532Xo4aOrroUNm7Z8SY/93zqIfp6qr/Jzx3rbofzvMmPtjc6Osp3\nz/kmRw8eWXUpbNyyaYexh4bvpq+n2sbc7eN3wvlmR/PbyMgIF154IQBnn302J510UsUVSZLUuWwQ\nSlKHOmroaFYurf4mPxObJ+C+7ceOPXglixZ4kx/NX0cPHsmqg3+p6jKY2LwBHtp+bOWSY1i0oPoZ\nhNJ8Njk5yfDwMOPj4wAMDw9z4okn0mg0Kq5M2jlnr7fOGexSNWwQSpIkSeooExMTjI2NbVseGxtj\nYmKCffbZp8KqpF0bHR3lxvdfxYqhQ6suhY1bntxhbO2l/0pfT/XtgdvW3QvvdQa7VIXqPwEkSZIk\nSepyK4YOZdUh1V8eZmLzRrhn+7GVS49k0YLqLw8jqTrexViSJEmSJEmqMRuEkiRJkiRJUo3ZIJQk\nSZIkSZJaMDIywurVq1m9ejUjIyNVlzNrbBBKkiRJkiRJezA5Ocnw8DDj4+OMj48zPDzM5ORk1WXN\nChuEkiRJkiRJ0h5MTEwwNja2bXlsbIyJiYkKK5o9NgglSZIkSZKkGrNBKEmSJEmSJNWYDUJJkiRJ\nkiSpxmwQSpIkSZIkSTVmg1CSJEmSJEmqsYVVFyBJkiRJktQpNm3axOjoaNVlALBhw4Ydxm6++Wb6\n+/srqGZHq1atore3t+oy1AIbhJIkSZIkSS0aHR1l5PzLWHHQsqpLYeOWJ3cYe/iya+nrqb7dc9vD\n98M5r+OEE06ouhS1oPrfGEmSJEmSpA6y4qBlrDrkiKrLYGLzJrjrO9uNrVx6OIsWOGtPM+M1CCVJ\nkiRJlRoZGWH16tWsXr2akZGRqsuRpNppuUEYEWdFxA4nsUfEfhHxttktS5IkSZJUB5OTkwwPDzM+\nPs74+DjDw8NMTk5WXZYk1cpuTzGOiEOAA5qLlwO3RcS6aas9F/gQ8LHZL0+SJEmS1M0mJiYYGxvb\ntjw2NsbExAT77LNPhVVJUr3s6RqEJwKfB7Z+fXPjlMcmgUbz57+d3bIkSVJVRkZGuPDCCwE4++yz\nOemkkyquSNJ8MV/u3OldOyVJml27bRBm5hci4nCKU5HvBH4ZWDtllUng8cwcn7MKJUlS20w9zQtg\neHiYE088kUajsYdnStWwYdWa2WpYjY6OcuO5/8zRQ4fvfVF7YeOWTTuMjV08Sl9P9U2529fdDe/D\nu3ZKkjrKHu9inJn3NH/c4XqFEXEo8PMyO46IXwa+mJk7vS94RJwJnA8sAa4H/jAzx3a2riRN5wwo\nqRxP81KnsWG1Z7PdsDp66HBWLY1Z2VZZE5s3wP3bj608eAWLFsyPhqwkSZ1mjw3CrSLiGcAw8AHg\nR8C1wMnAAxFxWmbeMoNtvRb4CLDj36SKx58DXAz8GjAKXERxDcTTWt2HpPpyBpQk1YsNK0mSpL3T\n8l2MgU8Cg8DDwBrg2RTXKPwS8PFWNxIR/wt4K8XswF35XeBLmfn9zNwAvAM4NSKePoN6O97IyAir\nV69m9erVjIyMVF2O1DF2NQNKc6O/p5/FfYPblhf3DdLf4z+IJUmSJKlTzKRB+FLgjc1Tjn8T+HJm\nfg/4KPCCGWznssw8Hvj+btY5hmKWIgDNaxyOA9V+NdxGU2dAjY+PMzw8zOTk5J6fKElt1mg0OHP5\nWRzYO8CBvQOcufwsZ2tKkiRJUgdp+RRjitOBF0bE/sCvAn/QHD8EeLzVjWTmQy2sth+wftrYemDf\nVvfT6bwGVHv1LehnYNEQP59YB8DAoiH6PCVIatmqxcdxweKWJ5NLkiRJkuaRmTQIrwU+DfwXsAH4\nSkScSnF68TWzXNd6YHonbF9abERGxBAwNG14pzdDkaCYAfWKY9fwxVsvA+AVx66p7Qwo8yOVZ36k\n8syPVI7ZkcozP51h06ZNjI6OVl0GABs2bNhh7Oabb6a/f35MMFq1ahW9veVukDaTBuHrgb8ADgde\nmZmPR8QJwHeAt5fa+679mCmnE0fEQcDi5ngr3gqcO8s1qcsds+R43rXkoqrLmA/Mj1Se+dGM9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1wCBwWWb+aUQcDVwInAyMA5dk5oebz7se+AbwauCo5s//G7gYOBy4BnhNZk42j/MngF8H/qu5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\nkqQas0EoSZIkSZIk1dj/B9KXhl1Z9PzbAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115f507f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.FacetGrid(tidy, col='team', col_wrap=6, hue='team')\n",
    "g.map(sns.barplot, 'variable', 'rest');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "An example of a game-level statistic is the distribution of rest differences in games:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"0\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>away_team</th>\n",
       "      <th>away_points</th>\n",
       "      <th>home_team</th>\n",
       "      <th>home_points</th>\n",
       "      <th>away_rest</th>\n",
       "      <th>home_rest</th>\n",
       "      <th>home_win</th>\n",
       "      <th>rest_spread</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>game_id</th>\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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <th>2015-10-29</th>\n",
       "      <td>Memphis Grizzlies</td>\n",
       "      <td>112.0</td>\n",
       "      <td>Indiana Pacers</td>\n",
       "      <td>103.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <th>2015-10-29</th>\n",
       "      <td>Dallas Mavericks</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Los Angeles Clippers</td>\n",
       "      <td>104.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <th>2015-10-29</th>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>112.0</td>\n",
       "      <td>New York Knicks</td>\n",
       "      <td>101.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <th>2015-10-30</th>\n",
       "      <td>Charlotte Hornets</td>\n",
       "      <td>94.0</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>97.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <th>2015-10-30</th>\n",
       "      <td>Toronto Raptors</td>\n",
       "      <td>113.0</td>\n",
       "      <td>Boston Celtics</td>\n",
       "      <td>103.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            away_team  away_points             home_team  \\\n",
       "game_id date                                                               \n",
       "18      2015-10-29  Memphis Grizzlies        112.0        Indiana Pacers   \n",
       "19      2015-10-29   Dallas Mavericks         88.0  Los Angeles Clippers   \n",
       "20      2015-10-29      Atlanta Hawks        112.0       New York Knicks   \n",
       "21      2015-10-30  Charlotte Hornets         94.0         Atlanta Hawks   \n",
       "22      2015-10-30    Toronto Raptors        113.0        Boston Celtics   \n",
       "\n",
       "                    home_points  away_rest  home_rest home_win  rest_spread  \n",
       "game_id date                                                                 \n",
       "18      2015-10-29        103.0        0.0        0.0    False          0.0  \n",
       "19      2015-10-29        104.0        0.0        0.0     True          0.0  \n",
       "20      2015-10-29        101.0        1.0        0.0    False         -1.0  \n",
       "21      2015-10-30         97.0        1.0        0.0     True         -1.0  \n",
       "22      2015-10-30        103.0        1.0        1.0    False          0.0  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['home_win'] = df['home_points'] > df['away_points']\n",
    "df['rest_spread'] = df['home_rest'] - df['away_rest']\n",
    "df.dropna().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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lzb+XttoGKdMTDlK+GVOSJEnSMI0kjG87ZlVIkiRJj0LDDuNdX8jzCBFhUJckSZJGaNhh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\nJUmSpEr+P/kjHxDnxMX2AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11986d8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "delta = (by_game.home_rest - by_game.away_rest).dropna().astype(int)\n",
    "ax = (delta.value_counts()\n",
    "    .reindex(np.arange(delta.min(), delta.max() + 1), fill_value=0)\n",
    "    .sort_index()\n",
    "    .plot(kind='bar', color='k', width=.9, rot=0, figsize=(12, 6))\n",
    ")\n",
    "sns.despine()\n",
    "ax.set(xlabel='Difference in Rest (Home - Away)', ylabel='Games')\n",
    "plt.savefig('../content/images/tidy_diff_in_rest.svg', transparent=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Or the win percent by rest difference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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8Fnh9Zl7a5jhD9c9tfJzWdrWSJElSh5VeAb8FGIyIZcAVwNlUxwyubuwUEadT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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x119285be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 6))\n",
    "sns.barplot(x='rest_spread', y='home_win', data=df.query('-3 <= rest_spread <= 3'),\n",
    "            color='#4c72b0', ax=ax)\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Stack / Unstack\n",
    "\n",
    "Pandas has two useful methods for quickly converting from wide to long format (`stack`) and long to wide (`unstack`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date        variable \n",
       "2015-10-28  away_team    0.000000\n",
       "            home_team    0.000000\n",
       "2015-10-29  away_team    0.333333\n",
       "            home_team    0.000000\n",
       "2015-10-30  away_team    1.083333\n",
       "Name: rest, dtype: float64"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rest = (tidy.groupby(['date', 'variable'])\n",
    "            .rest.mean()\n",
    "            .dropna())\n",
    "rest.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`rest` is in a \"long\" form since we have a single column of data, with multiple \"columns\" of metadata (in the MultiIndex). We use `.unstack` to move from long to wide."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"0\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>variable</th>\n",
       "      <th>away_team</th>\n",
       "      <th>home_team</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-10-28</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-10-29</th>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-10-30</th>\n",
       "      <td>1.083333</td>\n",
       "      <td>0.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-10-31</th>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-01</th>\n",
       "      <td>1.142857</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "variable    away_team  home_team\n",
       "date                            \n",
       "2015-10-28   0.000000   0.000000\n",
       "2015-10-29   0.333333   0.000000\n",
       "2015-10-30   1.083333   0.916667\n",
       "2015-10-31   0.166667   0.833333\n",
       "2015-11-01   1.142857   1.000000"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rest.unstack().head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`unstack` moves a level of a MultiIndex (innermost by default) up to the columns.\n",
    "`stack` is the inverse."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date        variable \n",
       "2015-10-28  away_team    0.000000\n",
       "            home_team    0.000000\n",
       "2015-10-29  away_team    0.333333\n",
       "            home_team    0.000000\n",
       "2015-10-30  away_team    1.083333\n",
       "                           ...   \n",
       "2016-04-11  home_team    0.666667\n",
       "2016-04-12  away_team    1.000000\n",
       "            home_team    1.400000\n",
       "2016-04-13  away_team    0.500000\n",
       "            home_team    1.214286\n",
       "dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rest.unstack().stack()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With `.unstack` you can move between those APIs that expect there data in long-format and those APIs that work with wide-format data. For example, `DataFrame.plot()`, works with wide-form data, one line per column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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Xs5JtkyUmQRBeeL29XLGEbQvxQxomBxMBBfdpir8kx0ugQFlsYJUimfs0nnmb7RZ0TbnH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\nYRiGYRhGifD/AQZ+qz6tVUsqAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x119bdab00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax=(rest.unstack()\n",
    "        .query('away_team < 7')\n",
    "        .rolling(7)\n",
    "        .mean().plot(figsize=(12, 6), linewidth=3, legend=False))\n",
    "ax.annotate(\"Home\", (rest.index[-1][0], 1.02), color='g', size=14)\n",
    "ax.annotate(\"Away\", (rest.index[-1][0], 0.82), color='b', size=14)\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The most convinent form will depend on exactly what you're doing.\n",
    "When interacting with databases you'll often deal with long form data.\n",
    "Pandas' `DataFrame.plot` often expects wide-form data, while `seaborn` often expect long-form data (more on that in a future post). Regressions will expect wide-form data. Either way, it's good to be comfortable with `stack` and `unstack` (and MultiIndexes) to quickly move between the two."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mini Project: Home Court Advantage?\n",
    "\n",
    "We've gone to all that work tidying our dataset, let's put it to use.\n",
    "What's the effect (in terms of probability to win) of being\n",
    "the home team?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 1: Create an outcome variable\n",
    "\n",
    "We need to create an indicator for whether the home team won.\n",
    "Add it as a column called `home_win` in `games`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df['home_win'] = df.home_points > df.away_points"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 2: Find the win percent for each team\n",
    "\n",
    "We'll use a similar `melt` operation as early, only now with the `home_win` variable we just created."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"0\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>win_pct</th>\n",
       "      <th>n_wins</th>\n",
       "      <th>n_games</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>team</th>\n",
       "      <th>is_home</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Atlanta Hawks</th>\n",
       "      <th>away_team</th>\n",
       "      <td>0.512195</td>\n",
       "      <td>21.0</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>home_team</th>\n",
       "      <td>0.658537</td>\n",
       "      <td>27.0</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Boston Celtics</th>\n",
       "      <th>away_team</th>\n",
       "      <td>0.487805</td>\n",
       "      <td>20.0</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>home_team</th>\n",
       "      <td>0.682927</td>\n",
       "      <td>28.0</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brooklyn Nets</th>\n",
       "      <th>away_team</th>\n",
       "      <td>0.170732</td>\n",
       "      <td>7.0</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           win_pct  n_wins  n_games\n",
       "team           is_home                             \n",
       "Atlanta Hawks  away_team  0.512195    21.0       41\n",
       "               home_team  0.658537    27.0       41\n",
       "Boston Celtics away_team  0.487805    20.0       41\n",
       "               home_team  0.682927    28.0       41\n",
       "Brooklyn Nets  away_team  0.170732     7.0       41"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wins = (\n",
    "    pd.melt(df.reset_index(),\n",
    "            id_vars=['game_id', 'date', 'home_win'],\n",
    "            value_name='team', var_name='is_home',\n",
    "            value_vars=['home_team', 'away_team'])\n",
    "   .assign(win=lambda x: x.home_win == (x.is_home == 'home_team'))\n",
    "   .groupby(['team', 'is_home'])\n",
    "   .win\n",
    "   .agg({'n_wins': 'sum', 'n_games': 'count', 'win_pct': 'mean'})\n",
    ")\n",
    "wins.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pause for visualiztion, because why not"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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SExNh+PDhnBkaRYoUIbdbIYMEmDB41LEO161bF3x8fOCbb74xqBdsQsydOxceP37MqVuz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115ef3e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.FacetGrid(wins.reset_index(), hue='team', size=10, aspect=.5, palette=['k'])\n",
    "g.map(sns.pointplot, 'is_home', 'win_pct').set(ylim=(0, 1));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(It'd be great if there was a library built on top of matplotlib that auto-labeled each point decently well. Apparently this is a difficult problem to do in general)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ERERESoKCGCIiIiIiIiJSEhTEEBEREREREZGSoCCGiIiIiIiIiJQEBTFERERE\nREREpCQoiCEiIiIiIiIiJUFBDBEREREREREpCQpiiIiIiIiIiEhJUBBDREREREREREqCghgiIiIi\nIiIiUhIUxBARERERERGRklBW7AOa2XTgF8BkYAlwhXNubpZyXwKuAPoANcBnnHMvF7OuIiIiIiIi\nItJ5FDUTw8wqgUeAW4F+wI3AI2bWM6PcqcB/A6c65wYAfwb+WMy6ioiIiIiIiEjnUuzuJKcCCefc\nL51zCefc7cB64N0Z5XYCIVBhZnEgCdQXt6oiIiIiIiIi0pkUuzvJkcCijGUuWr53gXP/MrObgIVA\nAtiGD4CIiIiIiIiISDdV7EyMXuyfUVEPZHYn+Q/g48Ax0TY/BR6MuqOIiIiIiIiISDdU7EyMeqBH\nxrKewI6MZRcBtzjn5kW/f8vMLgfeDvzlQAcxs4HAwIzFIwuvrkj3oXYjUji1G5HCqd2IFE7tRmSv\nYgcxFgNXZSwz4K6MZbuBzKyLBNCc53GuBq4tuHYi3ZvajUjh1G5ECqd2I1I4tRuRSLGDGE8ClWZ2\nFXALcDEwBPhrRrl7gF+b2b3AAuAz+K4vz+V5nBuBuzOWjYyOLyLZqd2IFE7tRqRwajcihVO7EYkU\nNYjhnGs0szPxAYzvAK8BZzvndpnZzUDonLvSOfewmQ3FT6t6CDAfOMM5tzPP42wCNqUvM7PGtnwt\nIl2N2o1I4dRuRAqndiNSOLUbkb2KnYmBc64GODHL8isyfv8l8Mti1UtERERERDpWGIY0rKuh/o05\nJBt2EK/sQ49xM6kaPrmjqyYinUTRgxgiIiIiIiKZdq18iY3/vIHG9a/uu+K5m6kcOpGBp32eHqOn\nd0zlRKTTKPYUqyIiIiIiIvvY4Z5g7R+u2D+AEWlYv5i1936SnUufKm7FRKTTURBDREREREQ6TOPm\nlWz481chmWi5YLKZ9X/6Mk1bVhWnYiLSKeUVxDCzMWYWZFkeN7Nj275aIiIiIiLSHdS9fA9hIr8x\nKsPmBupe/kM710hEOrN8MzGWA4OyLD8ceKbtqiMiIiIiIt1FmGhiR82fC9pme82fCBNN7VQjEens\ncg7saWafBL4e/RoAC8wsmVGsL1DTTnUTEREREZEurHnbmyQbdxa0TbJhO807ainvN6KdaiUinVlL\ns5PcCtTjszVuA74D1KWtD4EdwJPtVjsREek0kps3klz6KuzaBT17Ep8wkWDAIR1dLRERKWHJRHNr\nN2zbioiMP85IAAAgAElEQVRIycgZxHDONQG/BTCz5cAsoNI5tzNaZs45V5RaiohIh0muWUXz4w+T\ndIsgDPcsbw4CYhOnUPbu9xIbOrwDaygiIqUmTCbYueRJtsy+tfCNY2XEe2fr6S4i3UFLmRjpVgPz\ngEeBL0bLnjWzVcB7nXMaIlhEpAtKLH2VpttvhqYsA66FIclF/6Zx2RIqLruK2LjDi19BEREpKWGi\nie2LHmPr3N/QtHlFq/bR204nVt6jjWsmIqUi34E9bwJeBX6UtsyA14GftXWlRESk44VbNtF0xy3Z\nAxjpGnbTePvNhNvqWi4nIiLdVrK5gbp5f2Dlr86j9rFvtjqAAdDvmA+1Yc1EpNTkm4lxIjDNObch\ntcA5t8XMvgr8q11qJtJOkm9uJDFrHsmlKwh3NRD0rCJ25DjiM6cRG6L+/SIpzc/9Exp251d4Vz3N\ns5+h/F1nt2+lRESkpCQbdrLtlfvZ+sKdJHZuylku3nsIiR0bcq5PGXDiJ6gaMaUtqygiJSbfIMYW\nYCKwLGP5WKCw4YRFOkiYSNB8/z9IzHll3+Xbd5JYv4nE0y8Sf9uxlJ19CkEs3yQlka4pbG4m8cLs\ngrZJ/GsWZe84S+1HRERI7Kqj7uV7qXvp9yR3b8tZrsehb2HAzEupHHU02176PZuf+zlh0/4B9KC8\nB4ecfKWyMEQk7yDGr4Bfm9m1wIvRsunAtfiZS0Q6tTAMabr7UZLzFrdYLvH0i9DYRPkF7ypSzUQ6\np3DLJthVX9hG2+pg+zbo1799KiUiIp1e846N1L14N3Xz/kjYlPs80vPwtzFg5qVUDa/es6z/cRfR\nZ8o5bK/5E7vemEuyYTuxyj70HDeT3tVnEa/sU4yXICKdXL5BjOuist8CBkfLNgA/Bn7YDvUSaVPJ\nfy85YAAjJTH7FWJTjyR+xKHtXCuRzifcvo3EwldIvDSnddsnmgnauE4iItL5NW1bx9a5v2X7gocJ\nmxuyFwpi9D7yHfSfcQmVgydkLRKv6kP/Yy+k/7EXtmNtRbqe5obt7Fg7n0TjduIVfeg9YhplXTTw\nl1cQwzkX4rMurjWzQUCjcy53XphIJ5N47uWCyyuIId1FuGUTiZr5JBbMJ3xj2T7TqBYkFiPo3bdt\nKyciIp1a4+YVbJ37G7Yv/AskE9kLxcroM/ks+r/lo1QcMqa4FRTp4hq2r2PdC7eyyT1GsnlvV6xY\nWRUD7UyGH3cZlX2Gd2AN216+mRiY2STgcqAaSJjZfOAXzrk32qluIm0i3L6T5LLCZgFOLnyNsKGR\noLKinWol0rGS69eRrJlPomY+4eqVbbLP2OSpBBVqMyIi3UHDhiVsmX0bO90/gOzB76Cskr5HvZf+\nx19MWd9hxa2gSDdQX+twD19F864t+61LNu+mduGDbHn9Kezcm+g52Dqghu0jryCGmZ0FPAjMBl4A\n4sDJwNVm9k7n3Kz2q6JI4cJEknDtepLLVpNYlDkebT47CAl37lIQQ7qMMAwJ16wksWA+yZr5hBve\nbPNjxE88pc33KSIincvutQvYMvtW6pc9m7NMUNGLftMvoN+xF1HWSzO/ibSHpl1bWPLI1VkDGOma\no3KTL7yX8h4DilS79pVvJsb3gW84576TvtDMvgH8BDiujeslUpCwsYlw5TqSy1eTXLaa5Io10NB0\nUPsMyuJtVDuRjhEmk4RvLNvTVYStm/PbsE9f4tXTiFVPIzHvBZIvHniWkvhJpxI/7IiDrLGIiHRG\nYRiya+ULbJl9K7tXvpizXKyqH/2O/RD9jv4A8Sp1LxRpT7UL7qOpPve0xema6jdRW3M/I477WDvX\nqjjyDWKMB+7Lsvwu4Jq2q45IfsJdDSTfWENy2SqSy1cTrnwTEjn6YbZG/z7Qp1fb7U+kSMLmZpKv\nuT1dRdi5I6/tgkMGEZsyjXj1dIIxY/dMkxo73Gju2ZPEs09mHysjCIif9i7K3nl2W74MERHpBMIw\npH7Zs2yZfSsN62pylov3GkT/4z9M36nvI1bRs4g1FOmewjDJhpoHCtpmQ80DDD/2UoIg1k61Kp58\ngxiPA5cC/5Ox/L3A3ws5oJlNB34BTAaWAFc45+ZmKXcyPsvjCOB14LPOuX8WcizpOsLtO0m+vjr6\nWUW4trb1gw/moWzmNIJAcyxIaQgbG0i6Rb6ryOIFsHtXXtsFw0YQq55GfMp0guEjs37mg1iM8rP/\ng/iJp5CY8yzJJYth1y7o2YuYTaRsxskE/ZUqLCLSlYTJBDvcP9g653Yaa5fmLFfWbwT9j/8Ifaac\nTayssog1FOneGnesp2nnhoK2adqxnsYd67vEIJ/5BjFWAp81s9OBZ4Fm4BjgFOARM7stVdA5d2mu\nnZhZJfAI8G3gVuDiaPtxzrn6tHLDgYeBS51zD5nZB4H7zWy4cy7HnE3SVYRhSLi5jjAKWCRfX01Y\n23Jfr6ziMYLRw4mNH0UwZCDND/0DdjceeLvePYnPnFr48USKKKzfSXJxDYkF80guWQRN+XWfCsaM\nJV49nVj1NGKDh+R9vNghg4i9+zx493mtrbKIiHRyYaKJ7QsfZevc39C0Jfegz+UDxzFgxiX0PvKd\nBPHyItZQRAB2161u1XbJXNMfl5h8gxj9gN9H/0+NBrIS+G30/9TjuwM9Gj8VSDjnfhn9fruZfQ54\nN/t2V7kY+Jtz7iEA59w9ZvYqkMyzvlJCwmRIuGGT7xry+mqSy1fD1u2F76iinNjYEcTGjSI4bDSx\nMcMJKvaeWGMD+9H46/uhoYVARs8qKi4/n6C3UiGl8wm31ZFY+G+SNfNIvuYgmcdXYhAQGz+B2JTp\nxCdPJejfNQZ0EhGRtpNs2s32BQ+zde4dNG9fn7NcxRBjwMzL6HXEqV0iJV2klITJZra+8Ry1NQ9Q\nt+L5Vu2jvEfXyJ7NK4jhnLvkQGXMrA9+ANCWHAksytx9tDzd0cAaM3sAeGtU5rPOuYMbqVE6hTCR\nIFy9geTyVX4QzuWroX73gTfM1LOK2PhR/mfcaIJRQwjiuQfjjB02morPfpjmx58juWAJJNNibvEY\nsalG2RknERukmzzpPJKbN5JcEE2FuuL1/LpRxcuIHTHRj3Ex6SiCXr3bv6IiIlJykg07qJt/H3Uv\n3EWiPvfgz1WjpjFgxmX0GDdT3W1Fiqxh2zo2LnqI2kUP07SzttX76TvqeMq6yIC7+WZi5KMn8Ang\nyhbK9ALqM5bVR9umOwQ4EzgPuAD4OPAXM5vgnKtrm+pKsYSNTSRXriOMBuFMvrEWGlsRj+rXm9j4\n0T5ocdhogiEDCWKFnUhjQwdS8ZFzCeu2k3xtFWFDA0GPKmKHjyHQQJ7SCYRhSLjhTZIL5vnAxZpV\n+W1YUUlsYrWfVeTIyQRVPdq3oiIiUrISu7ZS99I91L10D8mG3NmvPcbOYMDMy+gx+ugi1k5E9s+6\nOPixAIccdcHBV6yTaMsgRj7qgcwr655A5vD5DcCjzrknot9vNrMvACcCjx7oIGY2EBiYsXhk4dWV\n1gh37Sa5fM2egTjDVesgUXhPoGDwgCjTYjTB+FEEh/Rrs+h/0K8P8WMmtcm+ugq1m44ThiHh6hV+\nYM6aeYS1eQ7U1LMX8clH+fEtJkwkKFe/5GJTuxEpnNpNx2neUcvWF+5k2/z7CZtyDwLda8Kp9J9x\nCVXDJxexdtIStZvuoZCsi/JeQ4hX9GL3luUH3O+Aw99O//GntlU1O1yxgxiLgasylhl+qtZ0Dj+t\na7o4e8feOJCrgWsLrp20SrhtR9rMIasJ120oPFgYQDBiyN5Mi/GjlBlRfGo3RRQmk4TLXyORmgp1\na56D1/bt57MtpkwjNm5Ci12opCjUbkQKp3ZTZE11a9k69w62L3iEMJFjbLAgRu+J72LAjEuoGHRY\ncSso+VC76aIKy7oI6Df2RAZPfh/9x55IGCZ548nr2PTqX3JuMfDIsxh72le7VFewYgcxngQqzewq\n4Bb8AJ5DgL9mlPsd8LyZnYmf3vVTQCWQ7xSrNwJ3ZywbGR1fDsI+M4dE3UNaN3NInGDMMGLjfNeQ\n2NiRBD00NVcHU7tpZ2FzE8mljmTNPBIL/w07M5PQsgsGDvYDc1ZPJRg9liCmwdQ6EbUbkcKp3RRJ\n46blbJlzOzsWPQ5hInuheDl9q8+m//EXUz5gdHErKIVQu+liGrato3bRg2xc9EheWReDJ53LoMnn\n7jNFagCMf8e3GHLUB6hd8EfqVs4h0bCdeGUf+o2ZweApF9B7aNfLqCpqEMM51xgFJm4BvgO8Bpzt\nnNtlZjcDoXPuSufcfDM7B7geuAdYArwnfRrWAxxnE7ApfZmZ5TG3pmQKkyHhmxv9WBav+4E42Zbf\njdc+KsqJjR1J7LBRfvaQjJlDpOOp3bSPsGE3SbfIT4W6uAYa8hvENhg+Msq4mE4wbESXip53JWo3\nIoVTu2l/DetfZcuc29jpniTXU92grJK+U8+n//EfpqxP/lNuS8dQu+kakokm6t54jtqFDx446yKI\n0e/QExhSfT79Dj2BIJb71r330MldMliRS7EzMXDO1eDHtshcfkXG7//Az1IiReRnDlkfdQ1ZRfL1\nNbCrFTOH9OrhsyzGjyJ22CiCEUMJ4np6LN1DWL+T5KJ/k6h5haRbBM35DWQbHDqeePVUP8bFIF1Q\niohIYXatns/WObdR//qsnGViFb3oe/QH6H/shcR7akY2kWJo2LaW2kUPsXHRwzTt3Nhi2fJeQxg8\n+b0MmnTOPlkXslfRgxjSuYSNTSRXrPXdQ15fTXJFK2cO6d9nzyCcsfGjWjVziEgpC7fVkaiZT7Jm\nPsllSyCZx2C2sRix8RN8V5HJUwn69W//ioqISJcShiG7Vsxly+zb2L3qpZzlYj360//Yi+h79AXE\nK/sUsYYi3dOerIuaB6hbOZsDZ12cyJDq9x0w60LaNojRAPytDfcn7SCs3x11DYkG4Vz9ZutmDhly\nyL5Bi0P6tUNtRTq35KZakjWvkFgwj3DlcgjzGNG2rIzYEROJVU8nPmkKQa/e7V9RERHpcsIwSf1r\nz7Bl9m00vLkwZ7l47yH0P/7D9D3qPGIVmn5bpL01bFtL7cKH2LhYWRftJe8ghpmdBRwHlJMxS4hz\n7svOua3AmW1bve4puepNEv9eAtt3+rEkDh1BbOoRBGWFx5z2zByybJUPWrxZ24qZQwKCkUP2DsI5\nbqRmDpFuKQxDwvVrSS6YT2LBfMJ1q/PbsLKS2MQpfowLm0xQVdW+FRURkS4rTDaz49W/s3XO7TRu\nXJazXFn/kQx4y0fpM/k9BGUVRayhSPfjsy6epbbmQWVdFEFe75iZ/Rg/rc8rwLaM1YXeEksOyTUb\naLrvb4Qr1u6zPPHcy/BwT8reMZP4SUfnHOAvDEPCjVv9jCFR4CLctLXwisTjBGOG7xmEMzZuJEGV\nZg6R7ilMJglXr/BdRRbMJ9y4Ib8Ne/YiPnmqnwr18CMJyjWQrYiItF6YaGJ7zZ/ZMvc3NG/NHUQv\nHzieATMuoffEd+rmSKSdFZR10Xsogyelsi6GFamGXVO+32wfBT7qnLuzHevSrSXfWEvjLfdCQ47x\nKHbU0/zgE4RbtlF+zqlAauaQ2rRBOFfDtp2FH7yynNjYtEE4Rw8nKNdJT7qvMJEgufw1kjXzSdTM\nh7o8g4H9+u+ZUSQ29jCCeLx9KyoiIl1esmkX2155kK0v3Eli+/qc5SqHTWLAzEvpefjbCAINpi7S\nXlJZFxtqHmDbyjko66L48n0Xk8Cc9qxIdxbubqDx9gdzBzDSJJ56gXDbDtjdSHL5atjVUPgBe/XY\ndzyLEUM0c4h0CWEy6acwLS8nKCss8yFsaiL52qu+q8jCV6A+v4BgMGgIsSnTiFdPJxg1hiCmtiQi\nIgcv0bCdbfP+yNYX7yZZvyVnuapRRzNg5qX0GDtD03GLtKOGujV7Zxip39RiWWVdtK98gxh3AP9l\nZlc75xLtWaHuKPHyIj/+RZ6SLy8u7AAD+kZBCx+4CIYcopOcdCnJN5bR/PzTJBfM3zOdaTByNPGZ\nbyU+/XiCiux9gcPdu0m6hSQWzCP5ag005BcUDEaMIl49ndiUaQRDh6s9iYhIm0nUb2HrS79n28v3\nkmzYkbNcz/En0n/GJfQYNb2ItRPpXpKJJrYuf5bahfllXfQfexKDJ59Hv0NPJIgpI7e95BvEGAWc\nC7zfzN4AGtNXOudOaNtqdS+JuQvadH/B0IHRIJxR0GJA3zbdv0hnESaTND/8BxLPP73/ujWraL7v\nLhJP/53ySz9FbNBgv3znDhKLFpCsmUdyyWJobs7rWMGh44lPmU6seiqxgYPb9HWIiIg0b69l6wu/\nY9sr9xM27c5RKqDXEacxYMYlVA6bWNT6iXQnrcm6GDz5XCp6Dy1SDbu3fIMYC6MfaQfhhs2t3zg1\nc8hho33gYvwogt49265yIp1Y85/vzxrASBfWbqDxFzdQdsIpJJcuJvn6UkjmMa1wLEbsMCNWPZV4\n9TSCvppGWERE2l7T1tVsnftbttU8AokcXYuDOL0nncGAGZdQMXBccSso0k3szbq4n20r53LgrIuT\no6yLE5R1UWR5BTGcc99s74p0a2HhE7zEpkwgPnMasbEjNHOIdEvJN9eQePbJ/ArXbaX5sYcOXK6s\nnJhN8oNzTppC0FNTCYuISPto3Pg6W+bczo7Ff4UwR2/teDl9p5xD/+M/Qnn/kcWtoEg30VC3htqF\nD1K7+BGaD5B1UdF7KIMmv5fBk5R10ZFyBjHM7DvAdc65+uj/OTnnvtzmNetGgoH9CdfVFrRN2dtn\nEhutQWKk+0o8/0zb7KiqitjEKT5wYZMIKqvaZr8iIiJZNLy5mC1zbmPnktyB+KC8ir5Tz6f/cR+m\nrI+6MIq0NZ918UzaWBctUNZFp9NSJsZMoAKoB84AtgLZRq8rPI1A9hE/vprmh/+Zd/lg+GCCUYr8\nSfeWWHwQY8n06k188lRiU6YRO9wKnslERESkULtWzWPLnFvZtXx2zjKxyj70O/oD9Dvmg8R7Dihi\n7US6h911q9m48CFlXZS4nEEM59ypab9WA7OAR4FHnXMaH6MNxY+bQvPfns97utT4247VbAgiO/Of\n0ScldsREyk47g2DsYQRxRdFFRKR9hWHIrjdms2X2bexePS9nuVjPAfQ/9iL6Tb+AWGXvItZQpOvb\nk3VRcz/bVs1tuXAq66L6ffQbM1NZF51UvgN7TgPeGf1ca2YbgceAvwBPOOd2tVP9uoWgZxXlF59D\n06/vh0TLAw7Gjqsmflx1kWom0olVVkFT44HLpYmfeAqxw45opwqJiEhX17RlFXXz72fnkidI7NxE\nUFZJ1Ygp9J16Pj0PO2nPDU8YJtm59Cm2zr6NhvWLc+4v3mcoA46/mD5HnUusvEexXoZIt7C7bjW1\nCx9k4+I/5ZV1MXjyeQyadC4VvYcUqYbSWvkO7LkIWAT8xMwqgBOBjwEP4adb1XQYBylu4wg+8X6a\n7n2ccNPW/QuUlRE/5TjKzjhJWRgiQOywCSRfeSn/DeJlxA4d334VEhGRLisMQ7bOvZ3Nz94M4d4H\nTmFzA/Wvz6L+9VlUDpvM0Pf+gN2rXmLLnNtp2vR6zv2V9x9N/xkfpc/kswji6tIo0lZ81sXT1NY8\nkEfWRZz+Y09S1kUJyjcTAzM7HDg5+nkrMBZ4BWh5fkPJW+zwMVR86XKSbjnJfzvCHfVQXkZs7Eji\nx1YT9NSAgyIpZTPfSmMBQYzY1KMJeilFV0RECrf1X3ew+ZmbWizT8OZCVv7yHEg25yxTMegw+s+4\nlN5Hvp0glvdluIgcwO66VdQufCi/rIs+wxg86b3KuihheX17mtmbwCDgefzYGJ8GnnPObWvHunVL\nQSwgPnE88Yl6YizSkmD8BGITq0kurjlw4coqyk4/s/0rJSIiXU5T3Vo2P/Pz/ArnCGBUDp/MgBmX\n0fPwkwmCWBvWTqT7UtZF95VvCPjPwCn4AT63ApuAWjN7yTnX8iAOIiLtIAgCyi+8jKbf3Exy2ZLc\nBauqqPjoFcSGaEpiEREp3Lb590OYaNW2VWOOZcDMy+gx5jh1BxZpI7vrVlFbE411sWtzi2WVddE1\n5TsmxscAzGw0cCo+oHE5MMzMZjvnzmi3GoqI5BBUVVF++adJ/GsWiVlPEa5ft3dlZRXxY2cQf+vp\nxA4Z1HGVFBGRkrZzyZMFb1M5fDKDTvtvqkYe1Q41Eul+kokmtr7+FLULH8wv62LcyQye/D76jZmh\nrIsuqNDOeGuBpcBoYAxwaPSviEiHCOJxyma+lfiMkwlr18P2bVBRQTB0BEFFRUdXT0RESlxiZ8v9\n67PpN/39CmCItIHdW1ftnWEkn6yLyecxaOI5yrro4vIdE+MafAbGiUASeBL4I3CZc25FIQc0s+nA\nL4DJwBLgCudcznCamZ0O/A3o45yrL+RYItJ9BEFAMGQYqNuIiIi0oaC8Chp3Fr6NiADQvHsbGxc/\nwubX/kFz/WaCeAW9h01hcPX59B5WvV95ZV3IgeSbifEh4HHge8As51zuYZdbYGaVwCPAt4FbgYuB\nR8xsXLYAhZn1j8qJiIiIiBRd1ciphXUpCWJUDd//xkykO9q4+E+sePr7JJt27bN895blbFz8CP3G\nnsT4d15HWWWfVmZdnEtF78Ht+RKkE8p3TIzpbXS8U4GEc+6X0e+3m9nngHcD92UpfzPwe+CaNjq+\niIiIiEje+k47v6AgRs/DTqasr7ICRWoXPcIbT3yzxTJ1bzzHons/TEXvoWxf82LLO4yyLoZUn0/f\n0W9R1kU3VuwJqo8EFmUsc9HyfZjZRUA/fNeTL7Z/1URERERE9tXj0OOpGn0Mu1e9dODC8XIGzLys\n/Ssl0sk17dzIiqe+m1fZhrpVNNStyrm+os/wtLEulHUhxQ9i9AIyu43UAz3TF5jZGOCb+DE4qoCw\nkIOY2UBgYMbikQXVVKSbUbsRKZzajUjhSq3dBEGMYe+9nrX3XknjBpe7YLycoe+5jqrhk4tXOek2\nSq3d1C56mDDR2PodBHH6j3srQ6rfp6wL2U+xgxj1QI+MZT2BHalfzCwAfgN8xTm33szGRqsKmVz7\nauDa1ldTpFtSuxEpnNqNSOFKrt3Ee/Rn5IW/Zuu/fse2V+7fd8aSIEavw99G/xmXUjV8UsdVUrq6\nkmo3m5f8tVXbKetC8lHsIMZi4KqMZQbclfb7KOAtwDQzuxmI4QMYq8zsPc655/M4zo3A3RnLRuJn\nVRGR7NRuRAqndiNSuJJsN7GKnhxy0icYMPNSdq95hcTOzQRllVQOm0RZH91sSbsrqXbTuHNDwdsM\nnfafjD7x08q6kAMqdhDjSaDSzK4CbsHPTjIE2BOqc86twnc7AcDMDgWWAyOdc/sOa5uDc24TsM+k\n3mZ2EPlMIl2f2o1I4dRupCVhfR1NL/+JxGtzCRt2EFT1IT5hBuXTzybo0aejq9dhSr3dBPFyeow5\ntqOrId1MqbWbIF5R8Da9hk5SAEPyUtQghnOu0czOxAcwvgO8BpztnNsVZV2Ezrkrs2waUlh3EhER\nEZEOEYYhTc/9jsZ//AKaG/ZZl1gyi8a/3UTFO66i/IQPEQS6vBGRrqfX4COpWzGr4G1E8lHsTAyc\nczX4ATszl1+Ro/wKQCE5ERERKQmNf7+Jpqdvz12gaTeNj/4IGnZQcdrHi1cxEZEiGVx9fkFBjD6j\njqVqwKHtWCPpSmIdXQERERGRriKx/KWWAxhpGp+4hcTKBe1cIxGR4us/9iR6DrY8SweMOFZTE0v+\nFMQQERERaSONs+8pqHzTnMLKi4iUgiAW5/CzbqCy36gDleTQt11D39HHF6Ve0jUoiCEiIiLSBsLd\nO0gsfrqgbZprniBszGvcchGRklLZZxgTL/gNg6vPJ1ZWtd/6XkOrmXD2Txly1Ps7oHZSyoo+JoaI\niIhIVxM27qL5lcchmShsw0QT4Y5NBIcc6GmliEjpKe8xgLGnfplRJ1xN3YrnaarfRKyskt5Dqwvo\nbiKyLwUxRERERAoUhiHJ9a+RWDrb/7wxDxJNrduZphQUkS6urLIPA494V0dXQ7oIBTFERERE8hDW\n19G8bC6JpXNILHmecHvtwe+0R1+CPoMPfj8iIiLdhIIYIiIiIlmEyQTJNYtILJlN82uzSa6qgTDZ\npscoP+Ycgrgux0RERPKls6aIiIhIJLmtlsRrs6PAxVzYVZf/xpW9iI+qJrH8xfzGxiivonzGB1pf\nWRERkW5IQQwRERHptsLmRhIr5u8Z2yL55tKCto+NOJL4hJmUTTiB2JgpBPFymhc+ye57/qflQEa8\nnKoPfpfYgBEH+QpERES6FwUxREREpFtJblpF89LZJJY877MmCpnitGd/yibMJD5hJvEJM4j1Hrhf\nkbLJp9Hj0ptpeOwnJNcs2m99bHQ1lWd+jvih0w7mZYiIiHRLCmKIiIhIlxY21JN4/UUSS2fTvPR5\nws2r8984Fic2egplE04gfsQJxIYbQSx2wM3i446h55W/I7F6IYnX5hLu3k5Q1ccHP0ZOPIhXIyIi\n0r0piCEiIiJdyp7pT5c877uJrJgHiea8tw/6DyM+4QSfcXHYcQRVfVpdl/ioycRHTW719iIiIrIv\nBTFERESk5IX1W2l+7V8klvrARbh9Y/4bl1USH3f0nsBFMHgsQRC0X2VFRESk1RTEEBERkZITJhMk\nVy+ieenzJJY+T3L1ooKmPw0Gj/OZFkfMJD72aILyqnasrYiIiLQVBTFERESkJCS31UaziDwfTX+6\nLf+NK3sRP/wtlB3uB+WMDRjefhUVERGRdqMghoiIiHRKe6Y/jca2SK5/raDtYyMmEj/CdxGJja4m\niJe3U01FRESkWBTEEBERkU4juWkVzUt8F5HE6y9C0+68tw16HUJ8wgw/A8jhM4j1PqQdayoiIiId\nQUEMERER6TBhw86M6U/X5L9xLE5szFTKjphJ/PCZeU9/KiIiIqVLQQwREREpmjAMSb65dM8sIokV\n8x66FpIAACAASURBVAuc/nS4n0XkiJnExx9HUNW7HWsrIiIinU3RgxhmNh34BTAZWAJc4Zybm6Xc\n5cAXgCGAAz7vnHuumHUVERGRg+enP527Z2yLcMem/DcuryQ+7ljiE2ZQNuEEgkGHavpTERGRbqyo\nQQwzqwQeAb4N3ApcDDxiZuOcc/Vp5U4B/hc43Tm3wMwuBv5kZuOdc1uKWWcREREpTJhoJrl6Ic3R\nTCLJNYsgDPPePjZkvB/X4ogTiB86naC8sh1rKyIiIqWk2JkYpwIJ59wvo99vN7PPAe8G7ksrNwq4\n3jm3AMA591szuwGfvaFsDBERkU4mWbd+z7gWidf+Bbu3579xVe99pz/tP6z9KioiIiIlrdhBjCOB\nRRnLXLR87wLn7kz/3cxOBHpn2VZERERaIbl1HU0vPEjzwicIt28iKK8kNuYoyo8/n/j44w84QGbY\n1OCnP136PIkls0luWJb/wYOA2IhJxI+Y6ac/HVVNENcwXSIiInJgxb5i6AXUZyyrB3rm2sDMJuGz\nNL7mnNucz0HMbCAwMGPxyALqKdLtqN2IFK5U203jrLtofPynkEzsWRbu3k5i4ZMkFj5JbOx0elz4\nA4JeA/auD0PCTSuj6U9nk1j+IjQ15H3MoPfAaPrTEyg7/C377Fu6l1JtNyIdSe1GZK9iBzHqgR4Z\ny3oCO7IVNrN3AvcAP3DO/aCA41wNXNuqGop0X2o3IoUruXbT+NydND724xbLJN+Yx67br6Lq4p9G\nY1s8T2LpHMIthU1/Gj90mh/bYsIJxIZN0PSnklJy7UakE1C7EYkUO4ixGLgqY5kBd2UWNLNLgB8D\nH3fO/aHA49wI3J2xbCTwZIH7EelO1G5ECldS7Sa5ZR2Nf/2//Mquc9Rff2ZBA3IGA0YSn+C7iMQP\nO46gsldrqypdW0m1G5FOQu1GJFLsIMaTQKWZXQXcgp+dZAjw1/RCZnY6cBPwDufcrEIP4pzbBOwz\nf9v/s3ff8XFU5/7HP+qy5F4lZBs3+RhjTAvVNJtqk0IIhNyQH6kkoQZIz00ChIT0dklCIAFSCQEu\nAW5iU2167xjbj3u33It63d8fZ9ZerVfaXXl3pZW+79fLL2tnz8w8OztnZ+aZc84455q6GrRIX6B6\nI5K8bKs3za/+b7suJHHFS2CEH386+UT/+NNhY/T4U4kr2+qNSE+geiOyT0aTGGbW5JybjU9g3Aws\nBz5gZvXOuVuBkJldDnwNKADmOecAcoAQcIGZPZbJmEVERHqLloVPHPAyckdNJK/yRN9N5OAj9PhT\nERERyaiMDwVuZguBGTGmXxbx99kZDUpERKQPCFVvj18oWkEx+e6kIHFxPLmDRqU+MBEREZEE6Xlm\nIiIifUROQRGhpuiHhHWu6PzrKZh+VpoiEhEREUmOhgkXERHpI3JHT0tuhpwc8sYelp5gRERERLpA\nSQwREZE+ouDYjyRVPm/ySeQOLk9TNCIiIiLJUxJDRESkj8ibfCK5YxJsjZGbR+Fpn01vQCIiIiJJ\nUhJDRESkj8jJzaP4E78gd+TEzgvm5lF0wffUlURERER6HCUxRERE+pDc/sPo94U7KDj5k9BvUPs3\nc3LImzyDfpf+kYLDz+meAEVEREQ6oaeTiIiI9DE5xQMoOudqCk//Aq2rXidUsw0KiskbPY3cIQd1\nd3giIiIiHVISQ0REpI/KKSgif/KJ3R2GiIiISMLUnUREREREREREsoKSGCIiIiIiIiKSFZTEEBER\nEREREZGsoCSGiIiIiIiIiGQFJTFEREREREREJCsoiSEiIiIiIiIiWUFJDBERERERERHJCkpiiIiI\niIiIiEhWUBJDRERERERERLKCkhgiIiIiIiIikhWUxBARERERERGRrJCf6RU6544Efg8cCiwFLjOz\nl2OU+y/g+8BIYAHwOTPbkslYRURERERERKTnyGhLDOdcEfAwcAcwCLgFeNg5VxJVbjpwK3ARMBzY\nDNyVyVhFREREREREpGfJdHeSmUCrmd1uZq1mdhc+QTEnqtzHgQfN7DUzawS+DpzjnBuR4XhFRERE\nREREpIfIdBJjCrAoapoF0zssZ2Y7gB2AS2t0IiIiIiIiItJjZTqJUQrURU2rA0q6WE5ERERERERE\n+ohMD+xZB/SLmlYC1HSxXEzOuWHAsKjJYwCqqqoSClSkpzr99NPHAevNrCWVy1W9kd5M9UYkeao3\nIslTvRFJXrL1JtNJjMXAFVHTHPD3GOX2dh1xzg0HhgTTE3EVcH2sNy6++OIEFyHSY60CxgOrU7xc\n1RvpzVRvRJKneiOSPNUbkeQlVW8yncSYDxQ5564AbgMuwT9C9dGocv8AnnLO3Qm8AfwQmGtmOxNc\nzy3A3VHTCoGx+DE4WrsWfsaNx2+zWfgvVlIrm7fv+jQsU/VGEpHN21f1pmPZ/L1mg2zevqo3Hcvm\n7zUbZPP2Vb3pWDZ/r9kiW7dxwvUmJxQKpTOQ/TjnpuETGNOA5cAXzexV59ytQMjMLg/KXQD8ABgF\nPAt82sy2ZTTYbuacm4z/UXJmtrS74+lttH17J32v6aXt2zvpe00vbd/eSd9remn79k76XtOvL2zj\nTLfEwMwWAjNiTL8s6vX9wP2ZiktEREREREREerZMP51ERERERERERKRLlMQQERERERERkaygJEbP\nth24MfhfUk/bt3fS95pe2r69k77X9NL27Z30vaaXtm/vpO81/Xr9Ns74wJ4iIiIiIiIiIl2hlhgi\nIiIiIiIikhWUxBARERERERGRrKAkhoiIiIiIiIhkBSUxRERERERERCQrKIkhIiIiIiIiIllBSQwR\nERERERERyQpKYoiIiIiIiIhIVlASQ0RERERERESygpIYIiIiIiIiIpIV8rs7gO7inJsODDazZ7o7\nlq5yzpUB3wbeD4wEVgF3Ab80s9agzCrgh2Z2e5pjSdt6nHMVwDpgnJmt7aBMAfBl4GJgArAN+D/g\nBjPbluqYYqx/AfCimX3LOXc9cLaZnZju9fZE2V63nHNtES9DQA3wFvA9M3sywWUcjK+PU8xsabDM\nc8zssRTH+hRwCnClmf0u6r18YCsw0MzyUrneBGM7FZgP9DOzpjhlM/I7lS1Uh7pfRB3+pZl9Oeq9\nTwI/MrPybgkuSlDXdpjZu90dS0+jurR3OQe0HYJ9/odmdlDwusN9LqLuRGoEVgA/MbO/BOX2njcl\nsP7PA3eEz237umzfrwGccwOBbwAfBg4G6oEXgB+Y2UsJLuNUYAFQHOs8wzl3MfB9MxufssDbL384\ncDP+Omwo/lrln/jPUB9R5nQz+2eCy+zSd+ucywV2AN80s1sjpl8L/Bz4qpn9PGL6VcB/m1lZMuvp\nZP3tfiMyoS+3xHgQmNLdQXRVcJB4DRiDv3A/BLgRfyF/ZzeGli6hjt4ILtaewG+HbwGHApcAxwAL\nnHP9MxLhPj8F5mR4nT1JVtetwMeAMqACmAG8DswLDpiJ6nCfTaEQ0AScF+O904GBGYihI88D5fES\nGBKT6lDPcZVz7vAY0zNRvxO1AOgRCZUeSHXJO9DtcA9wWMTrePtcCB9rWfDPAX8D/uScOyko82Hg\n+/FW7Jw7Bfg9kPFkfA+W1ft1cGH/KnAacA1+/5gFrASecs4dn8Ti4v0Wp/O3+j/4/fuDwGTgauAi\n4M8RZX4CfCiJZXbpuzWzNvx517FRb80CNgT/RzoRX49TJfo3Iu36bEsMIKe7AzhAvwcWm1lkxVjj\nnNsBPOqcu8XMXuum2DLty/gKP8XMdgbTVjvnZuN/EC/DJxYywszqgLpMra8Hyva6BbDLzLYEf1cB\n1wUtn34BHJ3gMjK1HZ4CZjrnBprZnojp5wMvAidkKI52zKwF2BK3oMSiOtRzrANuA5I5qZaeQ3XJ\nO6DtYGaN+NYUicoBtkfEDfCj4G7t+cBzZrYrwWXl4i9Ee8N3mSrZvi1+jr8Bc0pwrgD+t/ZLQQuN\n64HZ3RVcIpxz04D3AWVmtjWYvNY5dyUw1zk3zMy2k/x3dSDf7dPApyJizMO31v1v4GbnXF5Ea6YT\ngR8cwLra6cJvxAHrk0mMoAnbwcCtzrnjzewzzrkpwK+Bk/AHib/jm+u1BPN8EvgKUIlv8vQY8Dkz\nqw7e+yJwL74lQB7wY3yG63ZgUvD3x82sOkY8dwGfjBFqCBgf3YXCOXcQcBYxKriZPeGcOx1Y2MFn\n/zpwOTAEn82/zszedM59Bt/k6qCIsqcC84BRweeMOW+MdfTHH1w/AAzDZwB/Zma/Dd5fEGyPo4Ez\n8V0/vmtmfwreLwF+i8/S7wJ+GOuzRPg0vpnhzsiJZrbDOXcGsDpYbh6+2dfH8HcQtgJ3mtl3nHOz\ngLnAyPCFYNDaZSU+QbKyo3ljfP7r8V0HTghen4D/wT4CWAPcamb/E1H2fUBR8P/ngcXA74LtU4Nv\nmvYVM2uOsx26XbbXrThuxd8hGGdmq51zDv+9ngQUA4uAa83s6c4WEpx8/go4AxiAb3b7bTO7P3j/\nfOAmfLeodfi601k3izfwdwDeD9wdLCMHn/n/ERFJjA5ivsbMnnHO/QUoMrOLIspfD5xlZjOccwOC\nuD8MtACPB/NujWg+/B3gOuBJfB3e28zTOTcGuAV/N6AG+IuZfSPG9pkCPAvcZmbfds4dSpbWh67o\nY3Wow30qWHdbsO5rgKnAEuBSM3st1furmX20g894LXCvc+7y6C5bEett113MOXc2MM/McoPXY/Hb\n+iSC4yF+/070/XJ83TkL2AM8hG8aXBd0xQJ/Z/5G/EnpLcBHgP7AS8BVZraok++lV1Jd4ktmti16\nO+DvEt+DP158Fn/+9GXn3Fn4Y880YBPwUzO7LWK7/MjMyqP3OTP7XhJxt+AvXqO74R4E/AH/vbTg\n73BfgW+iPz+Yt845NzM4Xn0c+CYwEd9N5XozeyBY7vX4Frnr8ds7F/iTmV0bvB9rXVdG3QTosbJ9\nvw6SFBcBn4hIYET6MtAcUX4S/priZPy+8w/gax10H6nEJ52Pw5/f/DvqfQf8T9R2utHMWoNrnnvw\n+9UN+G7684FPBsmIaG34hMMc2re8eBJ/vNoV7IufDNZ9vJlNiHMelvR3G+VpfLIifFPruGBb3o6/\nljoeeD6oA2MIWmIkcF7ahv9t+GLw3teJ+g0B3iGim2Vn31vEto6c/wZ8vTwTKAi2/RVmtiHG5wT6\nbneS8/E/bl/DZ/2KgEeAt4HpwGeACwiauTnnZuArxU34H4CP4ptAXRGxzCPx3ReOx1843Izfaa4E\nzsZnvL7YQTxXs6/JXeS/cvxFTLTpwf+vxlqYmT1lZg3R051zlwOXBp/vKPzOvsA5NxL4X2Cwc+7k\niFkuBP4T/Mh1Nm+0X+Iv2Ofgm4j9CfiV82NbhH0D/+MyFfgXvsIODd67Hb8tz8QnDb4U63MGn6kY\nfwHX0bZ4zfaNifEN/Pf6MfyP8o3At4KD+gJ8MiWyZctHgTfMbFmceWMJBfGNwieC7scfVL8KfN05\nF7kvnIvf/07E//j9DVgalD8f/z10tO/0NNletzqzCH/AOjR4/TCwGX9xfRSwNvgs8fwVf5A4OVjW\n08Dtzrki59wI/A/9r/H79feA3znn4jXRe5D2XUpOBrbjE2KRYsUcTpDcDcwJ6lTYhfgDJviDTAUw\nE5+IKMWPOxPpLPx3FU7uhetBIb7LVz4+qXIRcIlzLnqsgQrgUeCvZvbtYHI214eu6Et1KJF96ib8\nSeV0oBp/8Qap21+PZd/+GssSfHPgm4MTvUSF9/08fIK8Gf8dXBd8poTeD/wL37rvGPxF6uH48a8I\npgH8Fz75cRVwDv74Ow3/O/DXJOLuTfp6XQpfwLXbDsG0UcDo4PP81vkuG//GX8gejk+G/cI5d0HE\nOsP7ZPQ+F5dzrtg5dzX+nO+hGEV+h78oPBrfFfIo/EXNWnxCLoS/uHvB+XEO/oi/QJqOv4D8p3Pu\nmIjlfQh/gXgcvk5c5Zw7t5N1XZ/I5+ghsn2/PgZ/kRpzzAcz2xFOljjnhgDP4W9onoDf5z6I/+7b\ncX5svHn4c/mj8b/b10W8X4Q/v4jeTpGtEYYF0z+Er0vH4M//Y8W5CJ8Muss5t9A59/NgH8szrxVf\nP+7Fn6O9L5i1s/OwpL7bGF7DJ6nCXUpmAk8HCZ/n2del5CRgY3B9A52cl0Ys+6P4Vh2fC163+w0J\npoWPa4l8b+H5jwjm/x4wPljHMcAgfMKpQ32yJYaZ7XTOtQLVwQX6Z4K/vxYUWeGc+xLwsHPum/gd\n4rNmdm/w/jrn3GPsO3iA35aXm9ku59wt+B+B28zsOQDn3OP4H+9Y8VTjT84SNST4f3cS84DPnF1n\n+waDusE5dyY+G3uzc+4R/Engs87fyf0IvuVFp/Pif+wiPQvcYmbvADjnbsYfIKbg7zIBPGFmfwje\n/zb+IDPdOfcG/gJntpm9Grz/JXwlPtBt8S7wKTN7MXh9u3PuO8ChZvaSc+7e4POHT/guJLiz3dm8\n+DtdHbkceNbMwhV3lXPuBvwP1O+DaXsi3sc5Nx7/Q7vOzNY45+bgfwh6vF5QtzoT/g4GOt9a6Hbg\n9oiD7W/wXbni9dt9CHg4fHfCOfdTfD0ajT+I5OMPLuuAvznn1uEPap15EPi3c64wOFidj09M7pVA\nzI/jL5TmAA843wJiMv4u9ET878GocFLQOfcJYLtz7kT21etfmtnK4P3IC74zg893nAVNiJ1zXwAG\nR5QZht/vHzOz6yKmZ2196Io+VIcm0Mk+ZWYvBGV/HdHC4afAg8HxKVX764pO4g036/0B/iTs1/jj\nUzJOx7eqOtl8a8HFwd253yXyvvOtBCcDM2zfgN2fAZY45641s43+xh67gpYZ4/D7xNqg1cnlZHHf\n+QOhurSvLkVtB/AXGz80s1VB+Z/gj0vhgf+WO1/wG/ibMJGfY1vkPtdJjK8H5cAnVbbh7zi/GKPs\nOHwL4rXBndqPALlmFnK+mzTAFjNrcX6gwt+aWTiR9zPn3Pvw56nhpEs1vgVSa/BZrsVfGP2no3V1\n8jl6lF6wX48I/t/busH5O/P/Zl+3oRD+nOATQGsQfzP+d+/y4LP9d9Ryz8InTz4bxLTEOXcE/rcb\n/Lh5nW0n8K1QvmRmbwdx/Y19SbtY3o9vKfiJ4P9rgZ3OuavM7G4zq3XO1QNt5luHd3oelux3a2bt\nxvsIWpS8gE/ePYE/voTPBefjj5c3sf94GJ2dl4aPkbeZmQXvn8r+vyGRN8ET+d7C868O5h8P1AJr\nzKzG+RZCwzvZ9n0ziRHDIcAU51xkJczBZwrHmdkbzrma4KJ1Kr7iHwLcF1F+Z/jk3Mzqgx/uVRHv\n1+O7DOzHOXcr/guPFgKmmln0BUy4ZcEQIn4EOuOcK8U3Hfqzc+5PEW8VAuFM3N34k7Sr8VnafsB/\nEpx3LzP7i3PuA865T+NbYhwZfJbIi7ulEeXDB9UC/MlaLhDZTeVVOu4jFv78Qzp4PzKuh51zpznn\nfow/qTsCOCgirrvxCZwB+IpzJMHd7QTm7chU4OyofSsPyHd+QFLYfxTvm/BN+S51zs0D7jWzt+J9\nvh4q2+pWZ8KDZO4JLhZ+B3wiOHly+Iw6xN8nfg9c6Jz7WvR8ZvaWc+5h/A/9KvxB/U8W1VUqhufw\n2+EM/F3dD+Oz3nsTCfFiDk7m7sMn7x7AZ93nByesx+G/t5XBBWRYXrCc8EVh9L4cdgiw0iL6QJtZ\n9F3x7+L3i+gRvHtTfeiKXlmHghg726fCSYzIY0y4uXe+mTWncX9tx8wanXOX4U80z0lkngiHASui\n6vCLSbx/CP6O1K6IC0Lwd5IdsDFqfbfht8XG4GT2IXrnYN9d0dfrUrTIuA/Bt5qN9Dz+TnxXnRes\nIwTUmdnmTsr+CN+66IPOuSfwdfruDsoegj8mRMd6WcTr1db+SSZ78N9zsuvKBtm2X4eTUkPYdz3z\nEr4FEPjWIH8NPsMU4C1r3330efz1a7sfxOAzrbL2XV5eZV8So9PtFDEt+phTQAfMd+n4GT6RVo5v\ntXIl/nrpvXAyJKJ8vHPH6KfvxIs51jHsaeB451spnsC+FjcLgOuDa48T2XcjFTo5L40oE2tdHR1D\nE/3eIuf/Jf54tdX5J+89SPtuOvvJmsxjmuXjWw9Mx1eiw4O/J+Mzlmfim/IcjM9kfYr9T7Rj9c9u\nizEtlu9ErDfy3xHsf4ICfjyKEPuPQAuAc+4B51z0SLjhC+aLo9ZxCL5VAPimtqXOjxx9AfCv4K5u\nIvNGrv/P+D651fiTp2PYPwkR64kF4exr+O+wDvu+B/G9Q8fb4kbnW3rgfH/h8I/2PfhEzd6+VuYH\nQl2Db0Z2AX7gqY2JzNuJ/KB85L41DV/Bwz9W9VGf6ef4H6fv4n/k73e+NUs2yra61ZnD8fvnwiCx\n9yp+PJYV+L6Gl8RbQHCC+Rh+kKUqfD1pd1FkZh/GH0D+hD8AveR864MOmR+V+mHgvODA2Bx98Eww\n5ruBc4OD3wXsO7HLx++n0dtxMu3v0rXblyMk8oSS+UFs33L+Tnr4s/Wm+tAVvbIOkfg+1dGxAtK3\nv+7HzJ7Ad/X6HVASp3jkDaJmOj/Xivd+PrCc9t9/+LPs1wrQzBbj68tH8N3Jvgq8HNT/vq6v16Vo\nkfv/fl2QCW64JBlXpHVmttLMVsVJYGBm9+Dv+l6DPze6Dd+VMJaOYo284OrwdyPJdWWDbNuvX8dv\n9xnhCWbWGOwrK2l/bt3Rdx35f1i4FUekyM/V6XaKKBe978S8ieqcO985t7dLjpltMj+23wx8cub0\nGPMke+6YaMyRnsZfd52Iby0V7lb8evDZTgmWEx4Po6Pz0ujPHet42dExNNHvbe/85seTG43fNlvx\nycbHO1g+0LdbYkQ2wVmMPwFaH84aBU1lrsBnF68C/mZml4ZncH7wmJWpCCRo/rctbsF95Xc45+bi\nB+mZF/lecJfoQ0Rlqc1st3OuCqgws4ciyt+Ob3J0b3C36V/47Pl5BCPcdjLvH/A72L0R04YC/w84\nyYLmwM65cBO0REbcNfyPznH4Zn/g+42FOpwD/gJ8wzn3YzMLZ3jDg6Fdie8XB76Z12Vm9vfg/cH4\nPlmRcf0Dv/1G0/7uVSLzxrIYOCPc3CqY9yL8M6M/H3VnDefcIHxft/BAqL91fkDVz+MHXMoGWVu3\n4vgc8Lr5Lg0fwXdzGGj7mniHu151tk8ciU+AjY5IkIUTFDnON338tJl9CXgLuCloffARfAuLzvwL\n3094O1FdSQLnxIvZfLPjrfjvZ3ywTPDfYzHQz4IBAoM68Bf8eAU1dF5HlwLjXcQTVIKD/wfMLJzE\necjM/uqc+yz+QvHsXlIfuqIv1KEiOt+n3ksgtnTtr2HRZa7Dj5Hx1ajpTbR/nPHEiL8X4vf9wREt\nkY5N4v3F+OPRHgsGl3P+wPFj4AtEnUQ6302rJjhWPex815RN+MTos3E+b2+kuuTrUrz9fQn7P4Fn\nBhGtZpOUSP0C9l5E/RS4x8zuBO4MzpP+Bnw8xrLCsUa2JJiBP3880HVli6zdr81su/Pdt7/jnJtn\n+w/QOSbi7yXAx5xzBRF39WfgkyDLaN8l5l1ggnNuaMS1QOTTe+Jtp2SNBb7pnLvL2nerasJfxIef\nzBP5XZ1N/HPHZL7bWF7BH48uJKLLiJm1OeeexScJNkVcl3R0XhorKZSoZL43gnV+Cz8O4T3APUGL\nyhedc2PMd6/eT19OYtTgm+gMwf94fRff/Of7+H5YfwReDppYbwROdP5Z8Q34JmvTSexOfLpcBzzn\nnHsIfzKzGT+Ay4+BP5jZyzHm+Qlwo3NuC/6JBp/DV4LIgVP+gc/c1+IHmexs3ovxo9lGqsZv2484\n5zbg7wj9Ap+YiNkULZL5flB3Ar90zu3Bb+/odUS7BV9ZnwkqwTv4JnM/xjdVuiUotxF/1+5FfHeR\nH+AzzZFx/QOfrcyn/R2MROaN5bf4AaV+gW+uNRH4DR0MABkkjM4CDg4u1vLwfdiy6XG52V63AIY4\nPyhrDr7/5hfwB5Izgvc34E8aP+qcex6f8Q738+tsn9iM/xH/L+ebwk/DN6ELz7cb+IJzbjc+iXYw\n/m7GwwnE/AS+3/Fl+L6h0eLFHH401j/xY9j8J9ws08yWOuf+Dz9Gx5X4/tg/xTcLXIYfwCvWwS48\n7TF8XbwjuKgqw59cx3r08ZXAm865j5nZPb2gPnRFr69DCexTiUrl/hqtXRkz2+Kc+wb+t7wq4q1X\ngSudc+/gT2yvjphnvnPO8N/fN/En6Dcm+j7+RsFi/End14KYbsW3tgrf3a4BDnXOvYTfP74fJHcM\nf5yuww8E2RepLnmR2yGWn+Fb7HwVnww8Bf/5r+mg/N59zmI/1SPhix/z415Mx2/7K/DnnxfgzzXD\n6wI42vlx034C3O2cew8/OOSH8TfeOm2xmOC6skW279dfwl9gP++c+wH+pk34Jujl+C5QzfiBmr+L\nTzbdjB+89hbgn7ZvbJbwvvYkfn//S3C+UIn/LQ7vn3/DtxrpaDsl+xnuwp+vPOl8a+1F+N//zwex\nh28m1eBzzxX4a4l452EJf7exgjLf1fIl/PXdtVFvL8B30Y1MAMY7L+2KRL63aOOATzo/Dsgm/L6w\nkU5aqXVbdxLn3LHBRW5H71/qnFvqnNvlnHvZ+S4OqfQb9j1aqg5/0j8Mn8G6D3/SHc5a3oAfWO85\nfFOsWvyOe2Qny084C90VZracoKkQ/iTubXxlvYF9g3FGx/FrfELhZ/iM5Zn4O6GRj2N9Av/57g2a\nqMebN3y3LBTE1Yw/aToXn4n7Ob6CPse+jGisbRM57Rr8QJ4PBf9+G6P8XsE6zwjK/gx/1+EW/Mnf\nmREZ0k/hu3EsxDfV/zO++fHREctaGsT9mLXvoxx33g5i24C/A34c/kf6NvwJaGej4YdH1X4Rf+ds\nLe37evZ0WV23guXfjf/hXI/fF8cAp1owyJWZvYS/cPo5/sB1MT7D3kj7/TwU8Xd4f/gi/s7ImAQs\n9wAAIABJREFUEvxAZP8P/xjgo4PM+AX48Szewx/Abjez8BMZYsVKsOwmfMus3Wb2SnTBBGMm+Oyl\n7N9H+BL8WDUP408w2vCPswwfSDus18FvyQfxzfBfwdef283s1zE+x0L8PvQL5x/Flu31oSt6fR0K\ndGWfipbK/TXW52jH/OOOX4x670r8Pvo2vnlw9IBzH8bv+6/hj6V/oH2T5Q7fNz9w24fwCc6n8N/9\nsmCesF/iWyzdiE/e/wWfBF0SlHu/xX5EYF+guuTt3Q6xVmJmb+JvBl2CP8f7Kn6Awz92EFfkPtdR\n3Il8trBP4i9cnsDfSCrGj+1CEM9jBAMTBi2Cr8G3xnsXP+bBR8yss6bnia4rW2T1fh38Hh2HH4/k\nRvz3+AR+jKDPAKeYWSj4bGfjb3y8hv9tuy8o0y7WoGXD7GDay/j9M9wSm4hldbSdkv0Mu/GtC97B\nJ7YNf/OzJYg/3EruL/gL9LeC87Ab6Pw8LJnvtiNP448p86OmL8CPd7h3erzz0qBYUvtDgt9btOvw\n42Y8gN8fpgHnWvuxbdrJCYXS/fu7vyDL8nP8nYT9HtHpnDsN30XhdDN71zl3Cf7APsHiD3AnIiIi\n0u2cf2zy0Wb2SMS0i4AfmNmkeO9nPmIREZGeL+PdSYLm/hfiM2Rf76DYaOAnZvYu7H3axS/wfWie\n62AeERERkZ4kBPwrOPd5AH9+8x38gM+JvC8iIiJRuqM7yR1mdiSd9Gk2s7+Z2c/Cr51zM4D+9N0+\nnSIiIpJlgkHvLsA301+ET048hO/aFfd9ERER2V+3dCeBvaOr3herO0lUuan4wVp+YWaxBoETERER\nERERkT6gRz+dJBiV/h7gp8kkMJxzw/CDoETKw4+yutDMWlIXpUjvoHojkjzVG5Hkqd6IJE/1RmSf\nHpvEcM59Gj/68efN7N4kZ7+KDppiPvnkk7Emi2STrj63OR7VG+nNVG9Ekqd6I5I81RuR5CVVb3pk\nEsM5dzr+sZpnmtnzXVjELez/uLUK9n/UjIjso3ojkjzVG5Hkqd6IJE/1RiTQY5IYzrlbgZCZXQ58\nDSgA5jnnwGdmQsAFZvZYvGUFzx9u90x051xTB8VFBNUbka5QvRFJnuqNSPJUb0T26bYkhpk9DYyM\neH1ZxN9nd0tQIiIiIiIiItJjdccjVkVEREREREREkqYkhoiIiIiIiIhkBSUxRERERERERCQrKIkh\nIiIiIiIiIllBSQwRERERERERyQpKYoiIiIiIiIhIVlASQ0RERERERESygpIYIiIiIiIiIpIVlMQQ\nERERERERkaygJIaIiIiIiIiIZAUlMUREREREREQkKyiJISIiIiIiIiJZQUkMEREREREREckKSmKI\niIiIiIiISFZQEkNEREREREREsoKSGCIiIiIiIiKSFZTEEBEREREREZGsoCSGiIiIiIiIiGQFJTFE\nREREREREJCvkd9eKnXPHAv8ys4oO3v8v4PvASGAB8Dkz25LBEEVERERERESkB+mWlhjOuc8AjwIF\nHbw/HbgVuAgYDmwG7spYgCIiIiIiIiLS42Q8ieGc+xZwFb6VRUc+DjxoZq+ZWSPwdeAc59yITMQo\nIiIiIiIiIj1Pd7TEuMPMjgRe66TMFGBR+IWZ7QB2AC7NsYmIiIiIiIhID5XxJIaZbU6gWClQFzWt\nDihJfUQiIiIiIiIikg26bWDPOOqAflHTSoCaRGZ2zg0DhkVNjjmAqIh4qjciyVO9EUme6o1I8lRv\nRPbpqUmMxUR0HXHODQeGBNMTcRVwfRriEunNVG9Ekqd6I5I81RuR5KneSIc27lrKSyvuZenmF2lo\nrqG4oD+TR53A8RM/ykGDJ3d3eCnXU5MY/wCecs7dCbwB/BCYa2Y7E5z/FuDuqGkVwPzUhSjS66je\niCRP9UYkeao3IslTvZH9tLY18+CbP+LVVf9qN72huZpXVj3AK6se4JjxH+a8I79BXm7MB4NmpR6T\nxHDO3QqEzOxyM3vbOXcp/rGqo4BngU8nuiwz2w5sj1p+UyrjFeltVG9Ekqd6I5I81RuR5KneSLRQ\nKMS9r17P2+se6bTcq6v+RVNLPR879gfk5ORkKLr06rYkhpk9DYyMeH1Z1Pv3A/dnOi4RERERERGR\nnmzxpmfiJjDC3l73CNPHnMWhB52W3qAypDsesSoiIiIiIiIiXfTC8nuSKv/S8nvTFEnmKYkhIiIi\nIiIikiVqGneyfMvLSc2zbMtL1DXtSVNEmdVjxsQQERERERERkX1a21rYWr2aDTsXs2HX4uD/JV1a\nVm3jDkoKB6Y4wsxTEkNERERERESkm8VKWGzcZTS3NqRk+fm5hSlZTndTEkNEREREREQkg6ITFut3\nLGLT7qUpS1hEG1g8gkElZWlZdqYpiSEiIiIiIiKSJpEJi/U7F7Fh5+IDTljkkEOIUMLlj51wPrk5\nvWNITCUxRERERERERFIgnLAIJytSkbDIzcln1KCJVAw+hNFDDqFiyFQGFA/nN09eTE3jjrjz9y8a\nyvETLuzy+nsaJTFEREREREREkuQTFqtYHyQrUp+wmErFkEMoGzSJgryi/cp+asb/cOdzV1LXtKvD\n5ZUUDuZTM/6H/sVDuxxTT6MkhoiIiIiIiEgn0pmwGD1kKhWDD+k0YRHL6KFTufL0v/LEott4Z91j\ntLQ17X0vP7eQ6WPO4oypX2BoaUWXY+yJlMQQERERERERCeyfsFjEpt3LDjhhUTZoEhVDDulSwqIj\nQ0sr+Ogx3+Pc6dexatsbNDRXU1wwgPHDj6K0aPABLbunUhJDRERERERE+qT2CYvwoJs9M2HRmdKi\nwUyrmJW25fckSmKIiIiIiIhIr7cvYRE56GZqExajh0ylbNAk8vMKUxi5RFISQ0RERERERHqV1rYW\ntuxZyYZdi1OWsMjLyWdUkLAYPeQQKgYrYdEdlMQQERERERGRtNpTv5Waxh3k5xYyrP9o8nILUrbs\nWAmLjbuW0tLW2OVlhhMW/pGmSlj0JEpiiIiIiIiISMq1hdp4d/3jvLD8n6zZ/tbe6SWFgzlm3IeY\nUflxBvYbkdQyoxMW63cuYtOuZQecsNjbJUQJix5PSQwRERERERFJqebWRu55+Vu8t3HBfu/VNe3i\n6aV/5tXVD/LJGb/i4GGHx1xGZMIiPI6FEhaiJIaIiIiIiIik1AOv3xQzgRGprmk3dz13NVee/leG\nlBzElj0rfbIiaGWR8oTFkKmUDVTCItspiSF9TltbC9vWPMOO9S/T0lRDftFAho85kWFjTiQnN6+7\nwxMRERERyWrrdy7izbVzEyrb0FzN7+Z/kqaWhhQmLKb6x5oqYdErKYkhfUrV8kdZ9tKvaKzd0m76\n+vfupXjAQbgTv8KIcad2U3QiIiIiItnvpRX3JVW+rml3UuX3JSym7m1loYRF35HxJIZz7kjg98Ch\nwFLgMjN7OUa5bwKXAQOAhcCXzOyNTMYqvcu6hfdiz/+4w/cbqjfy9qNfZurMGzho8vszGJmIiIiI\nSO+xfMt+l3ddlpeTT9ngSioGH6KEhQAZTmI454qAh4GbgDuAS4CHnXPjzawuotxM4CvAsWa2wjn3\ndeA+YGIm45XeY8/WxdjzP0mgZIjFT3+PQSOnUTp4XLrDEhERERHpdRqaa7o0nxIWkohMt8SYCbSa\n2e3B67ucc9cCc4D7I8rVAiGg0DmXB7QBdYh00dp378bvUvGF2lpZt/CfTDnp6+kNSkRERESkF+pX\nMDDpRMac6ddx4qSLyM8tSFNU0lvkZnh9U4BFUdMsmL5vgtkrwG+B94AG4BvAxZkIUHqfluY6Nq94\nPKl5Ni39D22tzWmKSERERESk93JlM5IqX5BXzPvGfVAJDElIppMYpezfoqIOKImc4Jy7APg8cHQw\nz6+BfwXdUUSS0lC9iVBbcgmJ1uZamup3pCkiEREREZHe6/iJFyZV/vAx51BSODBN0Uhvk+nuJHVA\nv6hpJUB0W6OLgdvM7M3g9fecc5cCZwD/ibcS59wwYFjU5Irkw5Vs1tbazPZ1L7LuvXu7uITEup/0\nFqo3IslTvRFJnuqNSPKyrd6UDZrE8RMvTOgpJf2LhnHG1M9nICrpLTKdxFgMXBE1zQF/j5rWAES3\numgFWhJcz1XA9UlHJ1kvFAqxZ8tCNi2by+YVj9LckNzjmsLyCkoo7Bd9nOj1VG9Ekqd6I5I81RuR\n5GVdvfnA4V+lubWR11c/3GGZgf1G8ukZ/8PgkrIMRibZLtNJjPlAkXPuCuA2/NNJRgKPRpW7B/ij\nc+6fwLvAl/BdX55LcD23AHdHTasI1i+9UN3utWxaNo+qZXOp37P+gJdXXjmH3Lw+1ydP9UYkeao3\nIslTvRFJXtbVm7zcfC44+noOH302L664lyWbniVEGwBDSys4bsJHOGb8+epGIknLaBLDzJqcc7Px\nCYybgeXAB8ys3jl3KxAys8vN7CHn3Cj8Y1WHAm8B55hZbYLr2Q5sj5zmnGtK5WeR7tdUv5PNKx5j\n07K57NmyMGXLzcnJY/S0i1K2vGyheiOSPNUbkeSp3ogkL1vrTU5ODpPLTmBy2Qk0tdRT17SL/Lxi\nSgsHk5OT093hSZbKdEsMzGwhsN9wtWZ2WdTr24Hbo8tJ39baXM/WNc9QtWwu29e/SKittdPyObl5\nDBszg/LK2dTt2ciKV26Ju44pp3yL/kMmpCpkEREREZE+rzC/H4X50cMjiiQv40kMkWSF2lrZufF1\nNi2by5ZV82ltjt8gZ9Co6ZRVzmbUhDMp7Ddk7/Si0uEsf+nXMZ88UlQ6ksknfoVRE05PafwiIiIi\nIiKSGkpiSI8UCoWo2bGMqqVzqVr+CI11W+PO02/gGMonz6Fs0mxKBo2JWeagye+nbOLZbFk1nx0b\nXqalqYaCwoEMG3Miw8edQm6uqoSIiIiIiEhPldAVm3NuLLDOzEJR0/OAI83stXQEJ31PQ00VVcsf\nYdOyudTuWBG3fEHxYEZNPJvyytkMHDktob51uXkFlE06m7JJZ6ciZBEREREREcmQRG87rwLKgOjb\n4ZOAZ4CSVAYlfUtLYzWbVz1J1bK57Nz4BhDqtHxuXhEjxp1GeeVsho4+vi8+RURERERERKRP6jCJ\n4Zz7IvDd4GUO8K5zri2q2EAgdY+FkD6jrbWZ7eteYNOyuWxb8wxtrfEGV85haMWxlFXOZuT4meQX\n9s9InCIiIiIiItJzdNYS4w6gDsgF7sQ/EnV3xPshoIYe/Gxi6VlCoRC7N79D1bK5bF7xOM2Nu+PO\n03+Yo7xyNqMmnU1x6cgMRCkiIiIiIiI9VYdJDDNrBv4C4JxbBTwPFJlZbTDNmZllJErJarW71lC1\nbC5Vy+dRv2dD3PJFpaMoqzyH8so59B86KQMRioiIiIiISDZIdEyM9cCbwFzg68G0Z51z64DzzGxd\nOoKT7NVUv4OqFY9RtXQue7a+F7d8XmEpoyacQVnlHIaUH0VOTm4GohQREREREZFskmgS47fAEuDn\nEdMccDvwG+BDKY5LslBrcz1b1zzNpmVz2bHuJUKh1k7L5+TmM3zsDMoq5zB87Mnk5RdlKFIRERER\nERHJRokmMWYAR5jZlvAEM9vpnPs28EpaIpOsEGprZcfGV6laNpctqxbQ2lwXd55BZYdTXjmHkRPO\noLB4cAaiFBERERERkd4g0STGTuAQYEXU9HFAbSoDkp4vFApRvd2CcS4epaluW9x5SgYdTFnlbMoq\nZ1MycHQGohQREREREZHeJtEkxh+APzrnrgdeC6YdCVyPf3KJ9AH11ZuoWj6PqmXzqN25Mm75guIh\nlE06m7LKOQwcMZWcnJwMRCkiIiIiIiK9VaJJjO8HZb8HjAimbQF+CfwsDXFJD9HcWM2WlU+wadk8\ndm16PW753PwiRo6bSVnlHIZWHEtuXkEGohQREREREZG+IKEkhpmF8K0urnfODQeazGxPWiOTbtPW\n2sS2tc9TtWweW9c8Q6itufMZcnIZWnEs5ZVzGDHuNPILSzMTqIiIiIj0KnUNO1i44kHWVL1EU3MN\nRQX9Obj8RA6d8CFKiod0d3gi0gMk2hID59xU4FJgGtDqnHsL+L2ZrU5TbJJBoVCI3VVvsWnZPDav\nfJyWxvg5qgHDHWWV51I28SyKSkfELS8iIiIiEksoFOKV9+7g5ff+QGvUDbR1W17jxXdv5fhpX+CY\nqZ9WF2WRPi6hJIZz7lzgX8CLwKtAHnAycJVz7iwzez59IUo61e5cRdXyeWxaNo+G6o1xyxf3L6Ns\nkh+gs//QiRmIUERERER6u2ff+hWvL/lrh++3tjXz/Du/obG5hpOPuDqDkYlIT5NoS4wfAzeY2c2R\nE51zNwC/Ao5JcVySRo1129m84lGqls1jz9ZFccvnF/Zn1IQzKaucw+DyI8jJyc1AlCIiIiLSF6zb\n/FqnCYxIry3+E+MPOonRI49Kc1Qi0lMlmsSYANwfY/rfga+lLhxJl9bmerasXkDVsnnsWP8yoVBr\np+VzcvMZPvZkyivnMGzsDPLyizIUqYiIiIj0JW8t/UeS5f+pJIZIH5ZoEuMR4DPAN6Kmnwc8ntKI\nJGXa2lrYueEVNi2bx9ZVC2htqY87z+CyIymrnMOoCadTUDwoA1GKiIiISF/V2FzDig3PJDXPivUL\naGquo7CgJE1RiUhPlmgSYy1wjXPudOBZoAU4GjgNeNg5d2e4oJl9prMFOeeOBH4PHAosBS4zs5dj\nlDsZ31VlMrASuMbMFiQYb58VCoWo3raETcvmsnn5ozTVb487T8ngcZRXnktZ5Tn0G3BQBqIUERER\nEYHtu1fEbSEcrS3UQl3DNgoLxqYpKhHpyRJNYgwCwu28ws82Wgv8Jfg7PERwqLOFOOeKgIeBm4A7\ngEvwSZDxZlYXUa4ceAj4jJk96Jz7GPC/zrlyM2tMMOasFGprZfu6F9i8aj5N9dvJyy9m0KjplE9+\nP4XFgzucr756I1XLHqFq2Vxqd62Ku57CfsMYNelsyivnMGD4FI3yLCIiIiIZUV23meXrF7Bi3XzW\nb3mjS8vIyUn4IYsi0sskVPvN7NPxyjjnBuAHAO3MTKDVzG4PXt/lnLsWmEP7MTcuAR4zsweD9d/j\nnFsCtCUSb7basfE1Fj/1PeqrN7SbvmXlk6x45beMPexiJh5zGTm5eQA0N+5h84onqFo2l11Vb8Zd\nfm5+MSPHz6K8cjZDKo4lN1c//iIiIiKSfjur17J83XyWr59P1faFB7Ss4sJBDCgZmaLIRCTbpPIq\ntgT4AnB5J2WmANGPw7BgeqSjgA3OuQeAU4Iy15hZM73UtrUv8Paj1xJqa4n5fltrE6vfuov66k2M\nnDCLqmXz2Lb2OUJtcTZJTi7DRh9PWeVsRow7jXz1HRQRERGRNAuFQmzdtZTl6+ezfN0Ctu9enrJl\nHzrhg7oZJ9KHZbr2lwJ1UdPq8AmQSEOB2cCHgQuBzwP/cc5VmtnutEeZYc0Nu1n45Dc7TGBE2rzi\nETaveCRuuYEjplJWOZtRE8+iqGR4KsIUkT4uFArRUL+N5qZqCgsHUNRvuLqiiYjIXqFQG5u2vcvy\n9fNZtm4+e2o3xJ8JKC4cTGNzdUJjYxTk9+OIyRcdaKgiksUyncSoA/pFTSsBaqKmNQJzzezJ4PWt\nzrmvAjOAufFW4pwbBgyLmlyRfLiZsXHp/9HSFL0Jklc84CDKK2dTNmk2pUPGpyAy6Uuyrd5I5rS2\nNLBm6UOsXHIf1btW7p0+cEglEw65kLGVHyQvr7AbI+w+qjciyVO96V1a25pZv+WNoKvIAuoatiU0\n38DSciaNnsWkMbMoHzad1Zte4N/PfYXWTloZ5+UV8f4ZP2Fgad8biF71RmSfTCcxFgNXRE1zwN+j\nphkwIWpaHvsGEI3nKuD6pKPrJpvs312eN79oIKMmnEl55WwGlR1OTk5uCiOTPiar6o1kRn3dVl54\n9Er27Fy233t7di7jrRduZvXSBznxzFso6jckxhJ6PdUbkeSp3mS5lpYG1lS9xLJ181m58Rkam/Yk\nNN/QgROoHDOLSaNnMWKIa9eab0LFyVx4+h945q1fsXHrW/vNWzHiKE458hrKhk1L2efIMqo3IoFM\nJzHmA0XOuSuA2/ADeI4EHo0q91fgBefcbOAR4EqgCEj0Eau3AHdHTasI1t/j1O9Zn/Q8A0dOY9wR\nn2L42Bnk9tE7oJJyWVVvJP1aWup54dEr2LOz837Mu7Yt4sXHr+aUc+8kN68gQ9H1GKo3IslTvclC\njU3VrNr4PMvXz2fVxudoaW1IaL5RQ6cGLS5mMnRg5y2Fy4dP56Iz7mTbrmWsqXqZxqZqigoHcHDZ\n8QwfPCkVHyObqd6IBDKaxDCzpiAxcRtwM7Ac+ICZ1TvnbgVCZna5mb3lnPsg8BPgHmAp8P7Ix7DG\nWc92YHvkNOdcUyo/S0p1ofXEwYf/P0aOn5mGYKSvyrp6I2m3xh6Mm8AI27ntPdau+A/jJp+X5qh6\nFtUbkeSp3mSPuoadrNjwFMvXzWft5pdpS2D8tpycXCpGHMmk0bOYOPo0BpaWJ73e4YMrGT64sish\n91qqNyL7ZHxYXzNbiB/bInr6ZVGvn8A/paTXKx08jj1b30t6HhGRdAmFQqxccl9S86xafF+fS2KI\niPQ21bVVLF+/gOXr57Nh65uEQm1x58nNzWfsqOOYNGYWEytOpaR4aAYiFZG+KpVJjEbgsRQur884\naMqHkkpiDBw5jf5D+3yTOhFJsVBbK7XVG6jevYrtm9+mZvfqpObftX0xTY27KSwalJ4ARUQkLXbs\nWR0MzDmfzTsWJTRPfl4x4w86iUmjZzH+oBkUFQ5Ic5QiIl7CSQzn3LnAMUABUQNsmtm3zGwX/rGo\nkqSyytmsfP02muq2xy8MHHz4JWmOSER6s9aWBmp2r6V69yqqd62ketdqqnevomb3Gto6GRU+Ec2N\n1UpiiIj0cKFQiK07be+jUHfsWRl/JqCoYAATKk6lcswsDi47nvz84jRHKiKyv4SSGM65X+JHxH0b\niB5+OJTqoPqa/IISDj/r57zxnytoba7ttOzBh1/CqAmnZygyEclmTY17qN61KkhW+H81u1dTW72B\ndP10FxTpTpyISE/U1tbKpu3v7H0U6p7ajQnNV1I8nEmjZzJp9ExGjzqavNw+N4CziPQwibbE+BTw\nKTP7Wxpj6dMGjTqM933oDpY8+0N2b357v/cL+w1l/FGXMvrQC7shOhHpqUKhEA11W/dLVlTvXkVj\nfWKtu1Jl8PCpaoUhItKDtLY2s37LayxbP58V65+iriGx48LA0oq9j0ItH34YOV0YhF5EJF0STWK0\nAS+lMxCBAcMqOea8O9mzbQlbVs6nuX4HuflFDBp1OCPHz+yLjy4UkUBbW4sfryIiSVETdANpidOC\nKxk5OXmUDhzDgEHjaGmpZ+vGlxOed/yUC1IWh4iIdE1zSz1rNr3I8vULWLnhGRqbqxOab9igSb7F\nxZhZjBg8mZycnPgziYh0g0STGH8GrnPOXWVmrekMSGDg8CkMHD6lu8MQkW7Q2tJA9e41+7WsqN2z\n9oDHq4iUl1dM/8HjGDBoPAMGB/8Gjaf/wDF7E6atLQ08/e9PsXvH0rjLGzJ8GmMnnpuy+EREJHEN\nTdWs2vgsy9fNZ/WmF2hpbUhovrJh05g0ehaTRs9kyMCD0xyliEhqJJrEGA18CPioc2410O6ZxGZ2\nYmrDEhHp3Zoad+9rVbE3YbGaupqNpHK8ioKiQfslKgYMHk9J/7K4zYPz8os58axbeOGxq9m9wzos\nN2T4NE4489dqLSYikkF1DTtYsf4plq+fz9rNr9DW1hJ3npycXCpGHMWkMbOYVHEaA0rLMhCpiEhq\nJZrEeC/4JyIiCfLjVWyJSlT4f40NO1K6rn6lZQzYr2XFBIr6DTmg5RaXjODU99/FmmX/x6ol97Fn\n5/K97w0a6hh/yIUcPOkDSmCIiGTAntqNLF+3gOXr57Nh61skkvTOyy1gbNlxTBo9iwkVp1JSfGDH\nBRGR7pZQEsPMbkx3ICIi2cqPV7G+XcuKmt2rqd69Ok3jVYz3CYvB4xkweAIDBo0jv6AkZeuJlpdf\nzIRDLmT8lAtorN9Oc3MNhYUDKeo3NG3rFBERb/vulaxYv4Bl6+ezZcfihOYpyO/HuPKTqBwzi3EH\nzaCooH+aoxQRyZwOkxjOuZuB75tZXfB3h8zsWymPTEQkQTV71rJqyf+ycfUTNNbvJDe/iKEjD2O8\nu4Cy0TPIyc1LyXpaWuqpCY9XEdGyombPWkIJNONNVF5+MQMGjds3TkXQsqL/gDHd2uIhJyeH4pLh\nFDO822IQEentQqEQW3YuDh6FOp8de1YnNF9R4UAmVpzKpDGzOHjUceTnF6c3UBGRbtJZS4wTgEKg\nDjgH2AXEGqY4dZ23RUSSEAqFWPrOnSx641YIte2d3trawOZ1z7F53XMMGXEYx5/xC4r7DUt4uY0N\nu9onKXavpnrXKupqNpHKn7zCosH7dwEZPJ5+pfHHqxARkd6jra2VjdveZvn6+SxfN5/quqqE5ivt\nN9w/UWT0LCpGHkVerrr2iUjv12ESw8xmRrycBjwPzAXmmpnGxxCRbrf0nTtZ9PpvOy2zc+u7PP/I\nZZxy7p0UFO5rThsKhaiv3dxunIrw300NO1Mapx+vov3AmgMGj6dI/ZJFRPqs1tZm1m1+hWXr57Ny\n/dPUNSY2VtKg/qP9E0XGzKR82GFKeotIn5PowJ5HAGcF/653zm0D5gH/AZ40s/o0xSciElPNnnW+\nBUYC9uxczhvP3cjgYVOCZMVqanatpqWlLmXx5OTkUzpw9H6JinSPVyEiPVtt3Raqql6lqamGwsIB\nlJcdQ0nJiO4OSw5AU3Mta6peoq5hO/l5RZQNO4xhgyYkNG9zSz2rN73A8nXzWbXxWRqbaxKab/ig\nSf6JIqNnMXxwJTk5sRpHi4j0DYkO7LkIWAT8yjlXCMwAPgc8iH/cqs7QRSSjVi25v10QMgo9AAAg\nAElEQVQXkng2rn6SjaufPOD15uX32zdeRUTConTgaHLVjFdEArt2reTNt25l7bqnCIVa907Pycnn\n4LEzOfLIyxk08OBujFCSVd+4i5cW3s6ilf9HU0v7QZsrRhzF8dM+z9iyY/ebr6FpDys3PMOK9QtY\nvelFWlobElpf+bDDmDh6JpPGzGLIgLEp+QwiIr1Boi0xcM5NAk4O/p0CjAPeBp5OS2QiIp3YuHp+\nWpdfWDw4qkVFeLyKUWq6KyKd2rz5TZ6YfzXNMZ5OFAq1sHrN42zc9BJnnv4bRow4rBsilGTV1G3h\nvvmfZ1f12pjvb9j6Bg88dTlnHPNtpk08j9r6bazY8BTL181n3ebXaAvFH/w5JyeP0SOP8l1FRs+k\nf8nIVH8MEZFeIaEkhnOuChgOvIAfG+Nq4Dkz25PG2EREOtTYsD0lyynpX97uCSDhx5dqvAoR6Yra\nui08ueCamAmMSE1N1Twx/0uc98H76JfEwMOSeW1trTz07LUdJjDCQqE2Hn/lJt60u9m2ewWJDASd\nl1vI2LLjqBwziwkVp9CvSMceEZF4Em2J8W/gNPwAn7uA7cBW59zrZpZ4e24RkRTJyy+mtSWxJrlh\nQ0YcxsiDjt336NJB48gv6JemCEWkL1qy5J80NVUnVLaxcRe29H6OOPwLaY5KDsSqTc+xZcfiBEuH\n2LZ7eaclCvJLGH/QSUwaM4vx5TMoLCg98CBFRPqQRMfE+ByAc24MMBOf0LgUKHPOvWhm56QtQhGR\nGIaOmE7VumcSLp+Tk8dxp/+MfhpQT0TSpKWlEVv6v0nNs3TpAxw+/VJ1U+vB3l2e3HcaS3HhICZW\nnMqkMbMYW3Yc+XlFKYhMRKRvSnhMjMBGYBkwBhgLHBz8LyKSUeOnXJhUEqN87KlKYIjIAWlpbaS2\ntoramk3U1G6itraKmoi/a2ur2g3imYi6+q3U1W2ltHRUmqKWA7V5+6Iuzde/30gmBQNzVow4ktzc\nZE+7RUQklkTHxPgavgXGDKANmA/cB3zWzNYks0Ln3JHA74FDgaXAZWb2ciflTwceAwaYWeqehygi\nWW3U6BMYOvIIdmx5K27Z3NwCJh/+mQxEJSLZKhQK0dS0h5qaIDlRu4na2k3URCQtGhp2pGXdrW1N\naVmupEZLF76f4w69lBMO+4Ja2IiIpEGiKeH/Ah4BfgQ8b2bxh1iOwTlXBDwM3ATcAVwCPOycGx8r\nQeGcGxyUExFpJycnl+NP/znPP3oZu3cs7bBcbm4B7zvtZoYMn5rB6ESkp2lra6W+fptPTtQEyYna\n9i0qWloyf68kJyeXfsVDM75eSVz/fsPZ0VyT1DwVI49SAkNEJE0SHRPjyBStbybQama3B6/vcs5d\nC8wB7o9R/lbgH8DXUrR+EelFivoN4ZRz72Tpu39mtT1AY/2+J5bk5ORRPvZU3OGfZfDwQ7oxShHJ\nhJaWhr1dOmpqNwUtKvYlK2prtxBK4DGXmTa64iQKNLBjjzZ57Fm8tPD2+AUDJcXDGT3iqDRGJCLS\nt2W6c94UILpjoQXT23HOXQwMwnc9+Xr6QxORbJRfUMLUoy5jyuGfY/uWt2is30FuXhFDRhyqMTBE\neolQKERj4+523Tyix6NIV1ePaLm5BZSWjqJ/aTmlpeWUlpbRv3958LqMHTuX8dTTX014eVOmXJTG\naCUVDpt4Pq8uuovWtuaEyk+fdD55eQVpjkpEpO/KdBKjFIhuq1kHlEROcM6NBW7Ej8FRTCIP2haR\nPi03r4AR5cd0dxgiWaO1tYk1a55k9donaKjfQV5eESNGTGdy5Yfp3788o7H4rh5b241HEe72EX7d\n0lKfkVgKCvrTv3+QnCjdl5woDRIV/foN67SbwIABY5g44f2sWPnvuOuaXPlhDio/PpXhSxr0LxnJ\naUd/lSdfvTlu2VFDD+V9h3wyA1GJiPRdmU5i1AH9oqaVAHs7GjrncoA/Af9tZpudc+OCt3ISXYlz\nbhgwLGpyRbLBivQlqjciycvWerNu/TM8/8JNNDRsbzd9U9UrvLvwTionncdxx349ZXeTW1rqqa3d\nHDEexaZ23T7q6rYk/VSPrurXb7hPTPQvp39pGaWl5e2SFoWFAw5o+Tk5Ocw48bsUFJSwxO7tsNzU\nQz7O+46+lpychE9veo1srDfTJ10A5PDU6z/tcCDWg8uOZ86MH1OQH32qK3LgsrHeiKRLppMYi4Er\noqY54O8Rr0f/f/buPD6usvrj+CdN0n2lTaBNoSltOd1ZBEuLImUHUUFxA0UBQcsi4sbPFRVERQQV\nkUURBcEN2RQQZBERStlpS9NTutGN7nvTNm0yvz+eO+1kOpPMpJlJZvJ9v159Qe69c+8zM/fM3Dn3\nPM8DTAAOMbObgU6EBMZiMzvN3Z/P4DiXAle2QntFOhLFjUj2Ci5u3l70FP955uvEYg0p18diDcx5\n6z5qt67i2GN+1uy0kLu7ejQeJDNxPIpt29bl4qnsIXT12G9X9URITkTJip4D6dF9X0pLO+ehHWUc\nOeH/GDny4/ice3ln2TTq6jbRuXMvBg2ayEj7KL17d+gZ6gsubgDGD/8IwwdPZub8B3lr0b+p3baW\nstIu7DdgHOOHn8mgAQd3yKSU5E1Bxo1ILuQ7ifEU0MXMLgZuJcxOUgk8Ft/A3RcTup0AYGZDgAVA\nlbtnWkt6I3BP0rKq6PgikpriRiR7BRU327at49n/fTdtAiPRkiXPMtv/ykj7GLW1q9JOO7ply/K8\ndfXo3LlXQpJid3IinrRorqtHvvXtM5QJR2Q+PkYHUlBxk6h713149+hzeffoc9u6KdLxFGzciLS2\nvCYx3L3OzE4hJDCuAeYCH3D3rVHVRczdL0rx0BhZdCdx9zVAoxpZM9Mk7CJNUNyIZK/Q4mbu3Iey\nmkb0pZdv4KWXb8hTV48SuncbEComEsej6Lk7adG5c888tENyrdDiRqQ9UNyI7JbvSgzcfSZhwM7k\n5VPSbP82UJrrdomIiBS7efMfzmr71kxeJHb1iHfzSJzZo3v3fTWjg4iIiDQr70kMERERaRubtyzP\n2b5DV4+BjcajSJzZo1vXfdpVVw8REREpTEpiiIiIdBCdSlpa2FhC9+4VTY5Hoa4eIiIikg9KYoiI\niHQQffsNY8WKV7N6zAnH3cR++x2urh4iIiLSLqiuU0REpIM4aMQZWW1fWXEIVVUTlcAQERGRdkNJ\nDBERkQ5iyJDj6dVzcMbbjx37mRy2RkRERCR7SmKIiIh0EGWlXTj22Bvo2rVfs9seesgUDtj/fXlo\nlYiIiEjmlMQQERHpQPr1Hcb7T/kDgwe/FyjZY33PnlW896gfcPD4C/LfOBEREZFmaGBPERGRDqZX\nr8Ecf+wv2LRpKYsWP83WrWsoLe1CRcU4qgZN1FSoIiIi0m4piSEiItJB9epVxZjRn2rrZoiIiIhk\nTLdaRERERERERKQgKIkhIiIiIiIiIgVBSQwRERERERERKQhKYoiIiIiIiIhIQVASQ0REREREREQK\ngpIYIiIiIiIiIlIQlMQQERERERERkYKgJIaIiIiIiIiIFAQlMURERERERESkICiJISIiIiIiIiIF\noSzfBzSzQ4FbgDHAHGCKu09Lsd0FwNeASsCBr7j7//LZVhERERERERFpP/JaiWFmXYCHgNuBPsCN\nwENm1j1pu2OAHwIfcfe+wE3AP8ysXz7bKyIiIiIiIiLtR767k0wG6t39Nnevd/c7gBXAqUnbDQau\ndfcZAO5+J1BPqN4QERERERERkQ4o391JRgKzkpZ5tHz3Avc/Jv5tZkcBPVM8VkREREREREQ6iHxX\nYvQAapOW1QLdU2wLgJmNBu4FvuPua3PYNhERERERERFpx/JdiVELdEta1h3YnGpjMzsR+DPwU3f/\naaYHMbP+QP+kxVVZtFOkw1HciGRPcSOSPcWNSPYUNyK75TuJUQNcnLTMgLuTNzSzc4EbgAvd/a9Z\nHudS4MoWtVCk41LciGRPcSOSPcWNSPYUNyKRfCcxngK6mNnFwK3AOYQpVB9L3MjMjiPMSHKCuz/X\nguPcCNyTtKwqOr6IpKa4Ecme4kYke4obkewpbkQieU1iuHudmZ1CSGBcA8wFPuDuW83sZiDm7hcB\nXwfKgUfNDKAEiAFnuvvjGRxnDbAmcZmZ1bXqkxEpMoobkewpbkSyp7gRyZ7iRmS3fFdi4O4zgaNS\nLJ+S8P8n5bVRIiIiIiIiItLu5Xt2EhERERERERGRFlESQ0REREREREQKgpIYIiIiIiIiIlIQlMQQ\nERERERERkYKgJIaIiIiIiIiIFAQlMURERERERESkICiJISIiIiIiIiIFQUkMERERERERESkISmKI\niIiIiIiISEFQEkNERERERERECoKSGCIiIiIiIiJSEJTEEBEREREREZGCoCSGiIiIiIiIiBQEJTFE\nREREREREpCAoiSEiIiIiIiIiBUFJDBEREREREREpCEpiiIiIiIiIiEhBUBJDRERERERERAqCkhgi\nIiIiIiIiUhDK8n1AMzsUuAUYA8wBprj7tBTbfRK4GqgEngY+5+4r89lWEREREREREWk/8lqJYWZd\ngIeA24E+wI3AQ2bWPWm78cDNwMeBAcAK4I58tlVERERERERE2pd8dyeZDNS7+23uXu/udxASFKcm\nbXcW8IC7v+zu24ErgJPNrCLP7RURERERERGRdiLfSYyRwKykZR4tT7udu68F1gKW09aJiIiIiIiI\nSLuV7yRGD6A2aVkt0L2F24mIiIiIiIhIB5HvgT1rgW5Jy7oDm1u4XUpm1h/on7R4f4Dly5dn1FCR\n9uq4446rBpa4+87W3K/iRoqZ4kYke4obkewpbkSyl23c5DuJUQNcnLTMgLtTbLer64iZDQD6Rcsz\ncSlwZaoVZ599doa7EGm3FgBDgYWtvF/FjRQzxY1I9hQ3ItlT3IhkL6u4yXcS4ymgi5ldDNwKnEOY\nQvWxpO3+BPzHzH4HvAr8CHjE3ddleJwbgXuSlnUGDiCMwVHfsubn3VDCa3Ys4Y2V1lXIr++SHOxT\ncSOZKOTXV3GTXiG/r4WgkF9fxU16hfy+FoJCfn0VN+kV8vtaKAr1Nc44bkpisVguG7IHMxtLSGCM\nBeYCX3D3l8zsZiDm7hdF250J/BDYF3gWONfdV+e1sW3MzA4ifCiZu89p6/YUG72+xUnva27p9S1O\nel9zS69vcdL7mlt6fYuT3tfc6wivcb4rMXD3mcBRKZZPSfr7XuDefLVLRERERERERNq3fM9OIiIi\nIiIiIiLSIkpiiIiIiIiIiEhBUBKjfVsDfD/6r7Q+vb7FSe9rbun1LU56X3NLr29x0vuaW3p9i5Pe\n19wr+tc47wN7ioiIiIiIiIi0hCoxRERERERERKQgKIkhIiIiIiIiIgVBSQwRERERERERKQhKYoiI\niIiIiIhIQVASQ0REREREREQKgpIYIiIiIiIiIlIQlMQQERERERERkYKgJIaIiIiIiIiIFAQlMURE\nRERERESkIJS1dQPaMzMbD/R19/+2dVtawswagJPd/fGk5ScBj7p7zpNYZlYNjHX3f+Zo/wuBAxIW\nxYBNwIvAZe5e0wrHuAPo4u5nteCx5cD57n7L3rajGBRBTD0NTHX3b7bw8d8Cjnf3yWb2PuApoJu7\n17VmOzNoxxBgQdLi7cA84Fp3vzOf7Sk2hXyeJ5wbI919Th6POwW4CbjE3X+dr+NGx14A/Mjdb8vR\n/j8GXAKMB+qA54Hvuvv0aP1ngB+7+8C2ev3bK8VSi45bdLG0N9dhuWxXoSiSONoBVLj7xqT1HwX+\nAvze3c9rg/bt+vxuYv2P3H1QC/ffGfgy8ElgGLATeAW4zt0fbeJxe32NmfwZ1t7iSJUYTXsAGNnW\njciRWJ6O8ztgUg73HwO+BuwX/RsEnAr0I7x/be2TwHfbuhHtSDHHVKbisfccMDDfCYykdhzF7tgx\n4I/A783sPW3UpmJR6Od5vr4fEp0FvAWc2wbHzhkzuwb4NSG2DgeOBzYCz0Y/LOLir/liQjy+lc92\ntmOKpewVZSzJXin0OIIQS6elWP4RoCHPbUnWVJz/GRjXkp2aWRfgP8CngR8Ao4GJwDPAA2b2kSYe\n3lrXmInP7XDgD3u5v1ajSoymlbR1A4pAPl7DTe6+MuHvFWZ2GeEicZy7z8hDG9JRorAxxVTE3XcC\nK5vdMHdKgDVJsfPj6K7Bh4H/tU2zikKhn+d5bX9UsTcJOBu4x8zGuvvMfLYhF8zsSOAK4Bh3fzZh\n1Tlm9l/gR8D7Ex/j7g207edCe6NYykKxxpLstUKPIwg/5k8H7okviKoUTgZeaKM2NcvdtxMqXVvi\nm8CBhEqI9QnLf2BmnYCrgb+nOW5rXWPuOnfcfU0r7K/VKImRRlQ2PgS42cyOdPfzzGwk8AvgPcBy\n4G7gB9GJEi8Z+iowAtgKPA58zt03Reu+APyVcFKWAj8BngZuA4ZH/3+Wu29K0Z47gM+kaGoMGOru\ni/biufYiXEydAfQGngQudffF0fpG3VKSu6NEpYtfBaoI2f/vuPsDUZvfBxwdvYbHmtl+wM+AE4By\n4CFCt4/1Ccf6DPAlQsZxNnCBu7+c5dPaEf03/t50Br5DyGZWAlOj486M1nchvB+fALoC/wamuPvq\npNeqB6E8ayPwfnevM7PTgB8S3ve3CKVWf45KuX4XPa4eGAr0ItyVexewmVAC91V330GRK7aYSiiz\n+wghfoYALwHnuvu8aJsJwC8JWfjngDcTHn8M4VzqGp1HE4AfA0cQkl+vAF9w9zczPNapwPeAsUA9\nIQlxvrsva+p5pLCTUPJOFK8/J9w97hW14dvufm+0vl+0/gPRMR8kfHZsNbOyqK2fBrpE7fmiuy+I\nHtsAXEV4Dxe4+5Fm9j3gc0B/YDrwFXcvqGRKsZ3naZ7jEcC1hLsy64DfuPtV0bpS4EbCudqTcHF5\nqbvPamKXZwEro8/NHxPuIH8l6TlsAvoQEmy1wA3u/uOEbX4AXEg41+4ADiGUF98Zrb8CuIhQpfcK\n8GV3fy3N80u7rZkdDVxP+H5aBfw2/txT+CzwYlICI+58Uty9S1O+e320r5GErpKfj3dPyGB9L0KM\nnkGI7X8DX3L3VQnH+g6hXPlJQvVgtu9fTiiWFEuZau67KmnbkcCzwK3u/u0M2rmAcK12FuG7cRwh\n3uLXvXMI3cPaQ/XvHoooju4HrjWzzgnVBScSfic0eoyZTST81jgEeBu42d1/mfDcMm5/tP3nCEmU\nS4EtwC/d/SdJx7yC8NulJ3Av4XO4Lrm7SabXOWZWEm13XVICI+464FfRtqk+y2+KnkdX4BvAlYTX\nODGhdSXhejPdukZdi5O7k+QrvtPRXeL0PgwsAb4OXBb9yP0X8AahX+t5wJmELBhmdhRwK+GifATw\nMeAY4OKEfR5K+IFyJOHHyjWEgLkEOImQPf9CmvZ8kd1l34n/BhLKT7ORnJG9j1Ce9OGoDd2Af0YB\nlE4MwMwOJXwQXk543ncBfzKzAcBlhGTBr4Azoh81TwEVhC+akwk/uP6YtO+rCAE3nvBle3M2T87M\nBhHel5mEDzcIwXwW4cLxMGAp8LiZ9YzW3wacQnjfJhISHXck7beMkPGsAz4QfTiNI5SKXQ+MIVyM\n3GJmJxN+tH6JkAndj3A+/ZHwhTeG8Hp/lPTvebEp1pi6Mmr7EYRz+8dR+/sDjwLTgIMJ585FCY+L\nsTuOegKPEM6ZMYRuHp0IX8KZHKua8AX/B8IPmZMJSbOMuzKZWVcz+yLhC+fBaPFdhAvC90btega4\nLXrviI5phAuJEwmxc2207hrC+3U64f1ZBjyd8FgI7+nRwOfM7EOEz4yzon2+APw9uttQSIr1PCdq\n7wjChdFLhM/SLwJfNLOvRptcSjj/TiV8vq8hnEdNOYvd3f8eAM6OfsAl+jwwl/Aa/gy4xszGRG36\nv2j9eYTYMcJ5FW/zRcAF0frDCOfx02ZWmeL5pd02OhfvAx6OjvEF4Aoz+0Ca53UIIamwB3d/y93n\npnlccnLjB4QfaO8CVgOPRYn5TNbfTvihNRk4FugB/CNp/ycSzq/vEM6pbN+/XFEsKZYy1dx3VbxN\nVcBjwF0JCYxMntN5hGT9mVF7E697/8ju6972qBjiKAb8l3D9fXzSc/s7Cb9rzGxfwrXXvYRz4WuE\ncyuxPdm2/4jo3yRCXH7TzC5MWL8fMIHwOn2Y8JpdkNR+zOx0Mr/OOTB6TVKOY+Lum5NvtNL4s3zX\ncYGfsvs13o9w43U14XdOunW/S3XcuDzHd0qqxEjD3ddZuHu+KcrEnRf9/9ejTeZZ6LLwkJl9g5Cp\nPN/d/xqtX2xmjxMCKK4MuMjd15vZjYTAuTWegTOzfxN+QKRqzybCD/ps3W/hjmeiXV9o0Y/w44Bx\n7v5mtOyThKzm+4HmBuQcQgiSxVHlxrVm9iqwJbobWxf9/4bo5K0G3uPua6NjnQ3MssYlj79IqPr4\nKaHfV4m7p+tz9nMzi//YK43a8xihUiJmZn0IWfPT3f3JaL/nEwYx/KyZ3Um4+/QBjwY9MrPPR8vi\nOhF+IA4glAZvi5Z/FbjD3eN9xBaY2WhCZvVfZrYBaHD3VdF+h0ZtW+zub1u4e54qw1p0iiimkn3f\n3Z+Pjvdrdt/1+kS0/y95KBF/y8zeS/iiSNYDuMbd4+fx22b2O0JlRSbHKiNUFsUHkF1kZn8jfKE2\n5RUzS2zD6qi9U6NlDwIPxe+MRPH4OWBwdCF0NDDK3T1afyFwhJl1JXzRv8fdX4nWTSHcEfkIu8tB\nb0147PGEC5TF7r4oOgcepMDKYIv4PI/7PDA74fm8ZeEu6NWEO0PV0XNaFN3tv4gm+mKb2SFR2y+P\nFv2dcO6cxu5kWvRUdt3FudbMvk64WHuTcOH5PXd/JNrnp2l8Z+4Kwh2iJ6O/v2dmJxDO5WuSmtTU\ntjcD+wArou+7xdF5uzDN0+sHbEj33JuQfM7/xt3vgl3fXUsJSfcHm1pvZjMI8bZv/GLXzD4FrDGz\nSdF2EO7Ez4/WTyGL9y+XFEuKpSyk/a4iXOtBuPP9GPC4u385y+f0J3d/I9r36aS57m1h23OqiOKo\nnpCAPR14JErOfYAQL4clbHcR8Ky7Xx/9vcBC9cPXgfg1UrbtrydUZqwl/GY5GJhCSHzE13/Ww6Cj\nHr1eh6Z4DtVkfp1TQTjPdnXhiH5DTKdx1cSh7K4+T/ws3y/+OHevJVRdEV2HfhU4zd2XRJukWrfU\nQoVHOvmM75SUxMjcKGCkmSUGXgmhS0S1u79qZpvN7DuEE39M9Ji/JWy/Ll4SFP3Ah8YzBGwllO/t\nwcxuBj6VYlUMGJ1wIiabwp59248m3J2B8IVYG09gRG1ba2YePY/mkhiPEUqIXjGzWYQPmNvdfWuK\nbUcSysbXJhxrtpmti44VT2IkDmgWH4W4jN1BmuyHwJ+A7oSM6yTgWwmvyUGEJMSuO2LuvsPMXoqO\nexAh+fFywvrZhLvecR8ivNf/cffNCctHA2PN7LMJy0pJ3w/tKkLZ2gVm9ijwV3d/Pc22xa5QYypZ\n8vlanvD8pkcJjLiXgA8m78DdV5jZ7yxUQhxCyFwfRigvbvZY7j7XzGqji9Fx0bHHk3BOp3E64fWK\nET4HViStvwX4aLTfeJsgnOOjCQlKT3gezwHPWbir1wX4T0KSBEJZ40EJfye+V38iZOvnmtkrhK5m\nt7t7fTPPob0rlvM88flMS1r2HNDPwp3LWwl3oZaZ2fOEC7Sm7uicTUjkPp2wr5WEMvjEH17Jszts\nAsotVDwNovHn+1ozi3en6AHsD/zBzH6f8PjOJA2e2dy20Y+BG4Ffmdm3CXeZ/ujuy9M8t9WERMbe\n2vUd7u4bo+/nsex+fdKt30k41+Zb48rKUkI8x5MYiedStu9fPimWOm4sNaep76q47xLOlb9k2s6E\nv+cn/H82173tUSHH0f3sThxMBpa4+/yk64zRwElJz68UKLNQUd2S9nvibxfCtdz/Jfy91hvPmrKe\nUNWeLJvrnLWE9yXxO2QRobIXQoLuaRr3qkh8DnuwUKn+V+CqhORDs+tS7Cff8Z1SoZXptqUyQh+6\n8YQT6ODo/w8iZJhOIJRmDSF0mfgsCR+UkVQ/wjMdUfc7CcdN/HcIoUw7neXuPj/xH/BOwvptaR5X\nSuMP/0S7kl/uvtXdJxFK+B4i/EB7zcwOS/G4TI+VaiTdpu7Groqe20zC676YkKXtleFx65rZP4Q+\ng+8DJkV3suLKCGW8ie/J2GjbPXi4015N+DLtB9xrYfT6jqhQYypZ8vkaP5eS+xdCmkScmQ0kJPFO\nJWTZv01CP+bmjmWhomo2oZz8BcLdt+syaPviKHYWJCcwoh89jwPfIpz/NxLu/qZrS6L4Z8QxNH5t\njTBGSNyui77o+KMJ5dPPEbp+vWpm+2fwPNqzYjnP41J9nsY/v0s9TGtdTagAqCEklqdFFz2NROfY\nJwj987ea2Q7CAGiVhEqCioTN030vxF+bdNcz8XPxbBo//1GEO3NZbevulxHO4+sJfaeftMZlxYle\nAt6daoWZfcjM/mJ7lvqnsjPp71LCnb/m1pcRYiz5vT+IUGodlxiHGb9/bUCx1HFjKa0031Uns+f3\n71OEhM43zWxYls8pMUZSXfe+mua6tz0qxDiKv5ePAz0sVJKdTupBLcsI3bwTn99Ywo3U+Odmtu1P\n9RmbuH2qJMQevyuyvM6ZR0iEH5Xw+PqE33JvpzhG2kSamZUTPvdfcvdrMl2XRt7iO5NGSGqJ3Rdq\nCH3Glng0CKOFgRsvJmQULyVkmXb1gbLQ3zExe9tiHkpBk/s+tYbZQDdLmMXDQr++EeweT6KOMOBn\nXPzDHzM7Fjja3b9HCMhvmtmbhK4or9L4NZwNDDWzAb67tHVMtO/ZtAIP3UfOJ/wg/DHh/ZlH+AA6\nkqgvsIX+wocT+oPOJ3wAHQo8Ea0fR/iwjN81nuruz5nZtcDPzOwf7r6BcF4Mi5BtDP8AACAASURB\nVJdvRY/9IqHbyXcTn7+Fbi1XEwbpuQm4ycKgOBcSBhfqCIotptJ1cQKYQTQWjEeDZRGSDKl8klAJ\ncXJ8gZmdQuMvqKaOdQEwzd0/nvD4y2k6OdfU/iDEwzHAYI8GB7XQ/Ylov3OA7mY23KO+/RYGub2W\n8MNtJ6GMPd6dpJRwF+LXhAGyGjGzM4FBHgbf+ncUGyuiNrRVn/yWKvTzvKlzYzahz3CiowjdJlZY\n6Iq32d3vJpQnX0lInB9GuHBOdAxhvIZPA4kDA1YTqgA/TbgASiuqPFhCiK2XYNdn7Yho/QYzWw5U\nufuuu9Fm9hvCIJd/TdhXum1vA54ws2mEu29fdvfrgOuiu4ofZ/fdwUR3AZeY2fvc/ZmE/XUi/CDd\n5O71SXcRU3kXYcwczKxv9Nxez2D9fEL1UzePBoOM1t9JGHdqM0nvdZbvXz4olhRLzUn3XZV8I+FB\nd78ruka8GTgxm+eUsK656972qCjiyN23W6hi/lD078QU29YAx3s0iDiAmX0cOM7dL8zg8zaVg8ys\nu4duGRDGv5ie7U6yuc6JvhtuA75sZne6e3Jl7v40fl+bu6b7JbAvIYGSzbo95Dm+01ISo2mbCSVX\n/QgD93yXUDpzNaFv3W8JPxzqzGwZ4S79wYTs+hRCFnBp6l23D+7+lpk9BPzezC4h9Iv6KaHdj0ab\nvUS4EJsOHEAYlCduO/BtM1tJKBcaT8jexsvYNwPDo7sATxA+XO62UPLXjTDg5nOeZmTrFj6nBWb2\nI0L/rNvc/Q0L4wf83My2EjK93yBc3N3j7pvN7LfADdFFwyZCJv8FD/0HE3f/Y+Acwg+1zxPudr8Q\nPZ+/E368/TjhNdoM9DazgwhfACcCQ6IPrlLCnfdsZ14pZMUWU00lCf5M6JJ0a5T8mkS4U5ZqKrBl\nwEALM//MJlQ8XEDjL6WmjrUM+IiFEblXEJIip9F0crC56qMVhOTeJy2MrzEWuCFa18Xdp1vo93m7\nhf60nQnn/mNRTP2akKj7PKHE8ZuEgQUvTXO8zsBPzOwdQjnzZMI4Ha322ZBHhX6elwDvtdD/NtH/\nCJ/Zl5rZdYSLkbGEsVt+7e4NFkrSrzKzVYAT7tTUAqlmVDgbmB/9SEs0y0L5/Lk088MrcgNwpZm9\nTbg7dTWhe2E8fq4Fvh99T71K6LN7NqGKLlmqbT9FGMhvDaG8v9zCzA/9CN0zU3a7dPdXLJTUPmBh\nwMQnCAnubxDuxk3K4LkBXG5hfIu3CH305xN+YDW5ProI/gfwx+j7fT3h+92ibQey5+dANu9fPiiW\nFEtx8e/IRCto5rsqxX4uIVQMf8Ld/5zlc4Lmr3vbo2KIo7gHCN2HlkbVSsnicXV9tN0wwgQDt+7F\n8XsDvzWz7xOSZhcTfgNkK9vrnB8QviemRcd+gfDb5UxCtW4NYeaP3jRxTWdm5xJmhDkJ6Gpm8a4u\ndYSKlnTrmtLa8Z21NutOYmbvNrO0AWFmF5jZHDNbb2bTzOw9+Wxf5FeEUp/bo+zbiYRgf5HQN+xx\ndo8++z3C6L//I5RfbSF8UKYa2CWuuazZ3sp0/58lZBQfJowuux6Y7LsHr7yEEDRvEKZM/Fb8gR76\nwF9I+NE+m/Ch/3/uHk+A3Er44fKYh4E5P0R4bZ4lnMyvEH5sZdvm5ra/lnAhd1P09xWEPqF3E/qg\nVhAy6fES+q8Q3ruHCHeJFxFG3G0kek0uB843swnu/iphhpGzCdUfVxOe/2+jhzxFuOB4nVAq9yHC\nazmV8BosInxBdBTFFlNpj+ehf+QJhLtYrxLi5IY0m/8V+D3h/HyDUKZ6MtAn4eK3qef2S8II1o8Q\nzu8qwnl5kJl1z/C5JLd/KaHv5qWE2L6CcDdvIbsrSs4hJFCeIVQ5PRltB6Gk8D7CgLivEmZLOSEh\n5hod393vAb5PiN3ZhMGlzvbdA/4WkmI4z28jnE+J/4ZFdzpPJdwxfoNQzXadRyP9E8b8uYvQd382\nYWrP0zxpfnkL1XBnAL9J04abgNEWpqBM18a4nxPOs7sId0ad8AMsfhH2C8IPuOsIFVInEAZyfjPF\nvtJu62E8pNMIJbOvEb7DnqKJWYDc/XJCLFxAiIMHCFVKkzyMvdTcc4MwhlX8AhbClOf1Ga4/J2rr\nQ8DzhBLoE333FIXJx8ro/csjxZJiKe5o9nwdvxt9V02h6e+qXe2KvlN+BVxvZr2zfE6ZXPe2R8UQ\nR3EPE5IBe0yfC7uuXU4mVEu8TvgdcjO7Z+xobv+pLCKcTy8REsVfiRJgWcn2Oif6nD6ecI5+kfCb\naSrh/bsCOCyhQqOp53AO0ThlhGquZdG/vxNiJd265P3mMr6zVhKL5fq825OFkXF/Buxw91TTMh1D\nuKg/zt1nmNk5hBfrwBTlNCIiItJBWZjS+hXfPQtUGeFO0Ps9Gm2+UJnZAuBKd7+zJetFslHMsSTS\nEmb2GcJn7IFt3RZpLO+VGGb2TUK29OomNhsMXOvRGA3Rl3M9jaf3EREREbmA0E1xTNR3+5eEH17J\nMz+ISNMUSyJSENqiO8nt7n4oTfQdc/c/RgOBAGBmRwE9abs+mSIiItI+XUQYDPG/hGuLakKXiXTT\ncheS5spl819OK8WsmGNJRIpIm3QngV0j4f4tVXeSpO1GE/pZX+/uP81L40RERERERESk3WnXs5OY\n2YmEEf5/mk0CIxrRuX/S4lLCwCUzffd0hyISUdyIZE9xI5I9xY1I9hQ3Iru12yRGNB3MDcCF7r7H\nPM3NuJQwteEennzyyb1tmkhba25qzJZS3EgxU9yIZE9xI5I9xY1I9rKKm3aZxDCz4whTQp0QTWWU\nrRuBe5KWVRGmdxGR1BQ3ItlT3IhkT3Ejkj3FjUik3SQxzOxmIObuFxHmVC8HHjUzCJmZGHCmuz/e\n3L6iObST59GuS7O5iKC4EWkJxY1I9hQ3ItlT3Ijs1mZJDHd/BqhM+HtKwv+f1CaNEhEREREREZF2\nqy2mWBURERERERERyZqSGCIiIiIiIiJSEJTEEBEREREREZGCoCSGiIiIiIiIiBQEJTFERERERERE\npCAoiSEiIiIiIiIiBUFJDBEREREREREpCEpiiIiIiIiIiEhBUBJDRERERERERAqCkhgiIiIiIiIi\nUhCUxBARERERERGRgqAkhoiIiIiIiIgUBCUxRERERERERKQgKIkhIiIiIiIiIgVBSQwRERERERER\nKQhKYoiIiIiIiIhIQVASQ0REREREREQKgpIYIiIiIiIiIlIQlMQQERERERERkYJQ1lYHNrN3A/e7\ne1Wa9Z8ErgYqgaeBz7n7yjw2UURERERERETakTapxDCz84DHgPI068cDNwMfBwYAK4A78tZAERER\nEREREWl38p7EMLNvApcSqizSOQt4wN1fdvftwBXAyWZWkY82ioiIiIiIiEj70xaVGLe7+6HAy01s\nMxKYFf/D3dcCawHLcdtEREREREREpJ3KexLD3VdksFkPoDZpWS3QvfVbJCIiIiIiIiKFoM0G9mxG\nLdAtaVl3YHMmDzaz/kD/pMUpBxAVkUBxI5I9xY1I9hQ3ItlT3Ijs1l6TGDUkdB0xswFAv2h5Ji4F\nrsxBu0SKmeJGJHuKG5HsKW5Esqe4EYm01yTGn4D/mNnvgFeBHwGPuPu6DB9/I3BP0rIq4KnWa6JI\n0VHciGRPcSOSPcWNSPYUNyKRdpPEMLObgZi7X+Tub5jZBYRpVfcFngXOzXRf7r4GWJO0/7rWbK9I\nsVHciGRPcSOSPcWNSPYUNyK7tVkSw92fASoT/p6StP5e4N58t0tERERERERE2qe2mGJVRERERERE\nRCRrSmKIiIiIiIiISEFQEkNERERERERECoKSGCIiIiIiIiJSEJTEEBEREREREZGCoCSGiIiIiIiI\niBQEJTFEREREREREpCAoiSEiIiIiIiIiBUFJDBEREREREREpCEpiiIiIiIiIiEhBUBJDRERERERE\nRAqCkhgiIiIiIiIiUhCUxBARERERERGRgqAkhoiIiIiIiIgUBCUxRERERERERKQgKIkhIiIiIiIi\nIgVBSQwRERERERERKQhKYoiIiIiIiIhIQVASQ0REREREREQKQlm+D2hmhwK3AGOAOcAUd5+WYrtv\nAFOAXsBM4DJ3fzWfbRURERERERGR9iOvlRhm1gV4CLgd6APcCDxkZt2TtpsMfBWY7O79gH8Cf8tn\nW0VERERERESkfcl3d5LJQL273+bu9e5+B7ACODVpuy1ADOhsZqVAA1Cb36aKiIiIiIiISHuS7+4k\nI4FZScs8Wr57gfuLZnYT8CZQD2wkJEBEREREREREpIPKdyVGD/asqKgFkruTnAlcCLwreswvgPuj\n7igiIiIiIiIi0gHluxKjFuiWtKw7sDlp2dnAre7+WvT3D8zsAuB44OHmDmJm/YH+SYursm+uSMeh\nuBHJnuJGJHuKG5HsKW5Edst3EqMGuDhpmQF3Jy3bBiRXXdQDOzM8zqXAlVm3TqRjU9yIZE9xI5I9\nxY1I9hQ3IpF8JzGeArqY2cXArcA5QCXwWNJ2fwZ+a2Z/AWYAlxG6vvwvw+PcCNyTtKwqOr6IpKa4\nEcme4kYke4obkewpbkQieU1iuHudmZ1CSGBcA8wFPuDuW83sZiDm7he5+4Nmti9hWtV9gNeBk919\nS4bHWQOsSVxmZnWt+VxEio3iRiR7ihuR7CluRLKnuBHZLd+VGLj7TOCoFMunJP19G3BbvtolIiIi\nIiIiIu1bvmcnERERERERERFpESUxRERERERERKQgKIkhIiIiIiIiIgUhozExzOwAYLG7x5KWlwKH\nuvvLuWiciIiISKFasGkl9y54kWmr5rJ5xzZ6lXflyMoRnDl0AkN6Dmjr5omIiBSkTAf2XADsB6xK\nWj4c+C/QvTUbJSIiIlKodjbU87MZD/O3hdMaLV+9fRMLNq/iT/Of55MHTuJLY0+htERFsSIiItlI\nm8Qwsy8A343+LAFmmFlD0ma9gZk5apuIiIhIQYnFYlz1+v08vPi1Jrf70/zn2Vpfx7cOPp2SkpI8\ntU5ERKTwNVWJcTtQSxg343fANcCGhPUxYDPwVM5aJyIiIlJA/rt8drMJjLgH3n6Z4weN5cjKETlu\nlYiISPFIm8Rw9x3AnQBmtgB4Duji7luiZebunpdWioiIiBSAvy54Iavt/7LgBSUxREREspBpR8wl\nwGvs7l4C8KyZvWJm+7d+s0REREQKy/rtW5i2am5Wj3luubNlx/YctUhERKT4ZDqw503AbOBnCcsM\nuA34FfChVm6XiIiISLsVi8VYWruWWeuXUrN+GbPXL2XW+qVZ76eBGOvqNtOjvEsOWikiIlJ8Mk1i\nHAUc4u4r4wvcfZ2ZfRt4MSctExEREWkHYrEYS7aspWbD7oTF7A3L2LRjW6vsv7xTppdjIiIikum3\n5jpgFDAvaXk1sKU1GyQiIiLSVlIlLGrWL2PzztZJWCSr6NqLiq69crJvERGRYpRpEuM3wG/N7Erg\n5WjZocCVhJlLRERERApKcsKiZv1SZucwYZHKGUOOoFNJpkOUiYiISKZJjKujbX8AVETLVgI3ANfl\noF0iItLO7GjYydyNS9i8s5Ze5d0Z3mt/yjqVtnWzRDLSOGERr7LYu4RFCSUM6TmAUX0HMbJvFaP6\nDKJ/l56c++ytbNyxtdnH9+3cnTOHTmjx8UVEROJ2NjQwd+NaNu+oo2d5Z4b33oeyTsWZJM8oieHu\nMULVxZVmNgCoc/eNOW2ZiIi0C+vrNnHP/H/xwKJnWLN9w67lFV378eEDjuGTB55Er/IebdhCkcbi\nCYtZ65cye0NuEhaj+1ZxUO+BKQfkvH7Cp7jshTvZsjP9rCO9yrvy8wnnsE+Xni1uk4iIyMa67fx5\n3gzuX1DDmu27E+gDunbn9OqRfGLYOHp3Lq7BozMeScrMRgMXAGOBejN7HbjF3RfmqG0iItLGFm1e\nzsUv/IRlW1fvsW7VtnXcOud+Hl06lZuO/DqDulek2INIbjXEGkKFxfplOUlYjOpbxagmEhapHNK/\nmj8cPYWbZz/Bf96ZRX2sYde6spJSJg8azZSRx3NAzwEtbqOIiMjSLRu55LmHWbpl0x7rVm+r5bez\nX+XRxW/xq6PeT1WP3m3QwtzIKIlhZu8H7gemAi8BpcB7gUvN7ER3fy53TRQRkbawaccWLpl2bcoE\nRqJFW5ZzyQs/5e6jf0C3sq55ap10RLlNWFTtSlpkk7BIp7pXBT854pOs3raRl1cvYNOOrfQq78bh\nAw5kgAbyFBGRvbRlRx1ffO6RlAmMREu3bOKLzz3CnZM/TI/yznlqXW5lWonxE+B77n5N4kIz+x7w\nc+CIVm6XiIi0sXsXPsXS2lUZbfv2lnd4aPGzfHzoCTlulXQUyQmLWdGgm0110WhOCSVU9xwQxq9o\nxYRFUwZ07c3Jgw/O2f5FRKRjemDhbBZvyWyEh8VbNvLAwtmcPWJ8jluVH5kmMQ4E7k2x/G7g663X\nHBERaQ8aYg38/e2nsnrM3xY+wceqj6ekpCRHrZJilZiwqFm/lJoNhZmwEBERyYdYLMZ9C2Zl9Zj7\nFszirOHjiuI6LdMkxr+A84D/S1p+OvDvVm2RiIi0ueVb1/BOM91Iki3YvIz1dZvo16V4+lxK64sn\nLOKVFblIWIzuW8VBfQbSvUwJCxERKT6rttVmXIURt3jLRlZtq6WyW+EPxp5pEmMR8CUzOw54FtgJ\nvAs4BnjIzH4X39Ddz2tqR2Z2KHALMAaYA0xx92kptnsvoavKQcB84Evu/nSG7RURkSzVxxqYtX4+\nU1dO56nlr7RoH1t2blMSo8BsrNvK2u2b6VpaTmW33nQqab3p2BpiDSzespaaHCUsRkdJCyUsRESk\nI1m9rbZFj9u6c0crt6RtZJrE6AP8Kfr/ftF/FwF3Rv8fr0mJNbUTM+sCPARcBdwOnENIggx199qE\n7QYCDwLnufsDZvYJ4O9mNtDdW37lIyIijazato6pq2YwdeV0pq16kw07Nu/V/vp0LvzsfkcQi8X4\nzzuz+NuCaby4et6u5ZVde3NG9RGcWT2Bfl2yey9zmbCIzxCihIWIiHRUsViMmvWruG9BDY8tmdui\nfRTLVKsZJTHc/dzmtjGzXoQBQJsyGah399uiv+8ws8uBU2k85sY5wOPu/kB0/D+b2WygARERabG6\n+h28vm4OU1dOZ+qqGby1cXGr7fvQfYxe5UpitHc7GnbynVf+xhPLZu6xbuW2jdw6+0nuXTCNXxz5\nGUb2HZRyH8kJi1nrl+Ib9j5hMbRXBSP7DFLCQkREJLJ5Rx3/WjyXBxbWMGfDmhbvZ2y/Svp16daK\nLWs7mVZiZKI78Hngoia2GQkkj0Di0fJEhwFLzew+4Ohomy+5e3HUv4iI5NHiLSuYunI6z6+azsur\na9han5uCto9VH5+T/Urr+uHrD6RMYCRas30zl0y9g7vedxH7duuzK2ER/i3b64RFJ0qoVsJCREQk\npVgsxqx1q7h/YQ2PL5nHtvqde73PMw8c3Qotax9aM4mRiR5AcgeeWkICJNE+wCnAGcBHgQuBh81s\nhLtvaO4gZtYf6J+0uKpFLZai0xBr4LWVU5m+ahq1OzfTo7wXh1VOYtyAdxfFaL0tpbgpHrU7t/Hy\n6llMXTWD51dOZ0ntyowfW1rSifH9RjCxYhzvrhjDz9/8E6+vm9Ps446sGMdxg969N80uSIUWN7PW\nLeGfi1/LaNv1dbV89r+3sK1+RysnLKqwPgPpVlYcc9VL9gotbkTaA8VNx5BN1UW30jJ6lHfOaHyM\nwysGceLg4a3VzDaX7yRGLZBcw9IdSO6EvR14xN2fjP6+2cy+BhwFPJLBcS4FrtybhkpxmvbO09zx\n5vWsqF3aaPmD8+6iqmc154/9KodWTmqj1rU5xU2BisVizN20mOejLiKvrXF2xuozfvx+3fozqWI8\nEyvHccSAMfQq351X/vmEr/C1l3/BS6vTT+N1VOV4fvyuSyltxQEhC0hBxc29C1/Mavs127MbIyUx\nYTG6bxUjlbCQ1AoqbkTaCcVNkYpXXdy3sIZ/Z1B1YX36c8bQUbuSEt948QmmrVySdvsJlYP50buP\np6xT8Vyn5TuJUQNcnLTMgLuTljlwYNKyUnYPINqcG4F7kpZVAU9l+HgpQv9++35+/cZVadcv3byQ\nq1/4Ipe/64e8p+qkPLas3VDcFJD1dZt4cdWbPL9qOlNXzmD19vUZP7ZLp3IO6z+SSZXjmVgxjuqe\ng9JWIfUq785NR17BM8tf5d6FT/DS6lk0EKO0pJQJA8bw0aHH857Kg1t1RosCU1Bx88LKt1ptX/GE\nxai+VYzqM0gJC8lGQcWNSDuhuCkyoeriLe5fOJu3Mqi6OHHwcM4YOopRfQc0um77xaRT+N/yt/nb\n/Fm8vGop9bEYpSUlHF5RxUcPHM179htCpyKrNs93EuMpoIuZXQzcShjAsxJ4LGm7u4DnzewU4F/A\nJUAXIKMpVt19DdDoTDCzur1ruhSyBRvmcMv0a5rdroEGfvHadxnWZxQDex6Qh5a1H4qb9q0+1sCb\n6+bt6iLy5vr5xJqeEKqRoT0HMbFiHBMrx3NY/5F0Lc38h2ZpSSeOHXg4xw48nJ0N9Wyt3073sq4d\ntfKikUKLm007trXocUpYSGsqtLgRaQ8UN8UhFovxZjTWRbZVFz3LU3/ndiop4eiB1Rw9sJqdDQ1s\nq99J19Kyoqq8SJbXJIa710WJiVuBa4C5wAfcfauZ3QzE3P0id3/dzD4IXAv8GZgDnJY4DatINv4x\n/24aMiyv39mwg0cW/oXzx34tx60SadrKrWvD9KerZjBt1Uw27tiS8WN7lHVjwoAxTKwcx8SK8Qzs\nPqBV2lTWqZRenZKHMZJC0au8K1vrs7vmvXT0SXxs6JFKWIiIiLRQtlUXJ+0/nNOrRzG6X0VWxynr\n1ImenYr/+zrflRi4+0zC2BbJy6ck/f0EYZYSkb2ybedWnlv6eFaPeWrRP/jM6C9R1qk8R60S2VNd\n/Q5eXzuH51dN5/mV05m3KX3/xlRG9RnKpChpMbbfMMo75f0jXtq5IytH8NCiVzLevktpOR+uPkIJ\nDBERkSy1tOripMHD6ZGm6kKC1rzC3Q5k90tRJEe27NjEgg3O3PWzmLH6JeoashtZv3bnZtZvX8uA\nbvvmqIUi4ctt8ZYVu7qIvLxmFtuyuEu+T+feHFkxjomV4ziyYiz7dOmTw9ZKMfjo0AlZJTFOrhpP\nr/LimFNeREQkH+JVF/ctqGHuxrVNbtu9rJyTBg/j9OpRjMqy6qIjyziJYWbvB44AykkaYNPdv+nu\n6wnToork1ZYdm5i/YTbz1tcwb0MN89bX8M6WRa2w58zHGxDJ1JadW3l5dc2umUSWZjX9aSkH9xvO\nxMrxTKwYj/U5oCMPqCktMKpvFaftf2hG06z269yDz9nkPLRKRESksO2qulgwi8eXzmN7fdPd2Ef2\nHcAZ1aM4cfAwVV20QEZJDDO7gTCtzxvAxqTV+qUnebNnwmIW72xZ3OrH6VLalT5dkqfiFsleLBbj\nrY2LeD6qtnhj7Zyspj8d2G3ArllEjhgwhp66Ky576VuHnM72+p38e9mMtNv079KTXxz5GQZ275fH\nlomIiBSWTXXb+deSudyvqou8yrQS47PAZ939jzlsi0gjjRIW62cxb0NNThIWqRw9+BTKNR6GtNC6\n7ZuYtnomU6NqizXbN2T82C6dOnP4gJFMrBjPxMrxDOmxX9rpT0VaorxTGdcc/nFOWj6evy2YxrRV\nc3et27drH86oPoIzq99N3y492rCVIiIi7VMsFmPmupU8sKBGVRdtJNMkRgPwQi4bIh1bPGExd/0s\n5kdVFnubsOhZ3odhfUcxrM8oupZ1457Zv87ocZ3oxPuHfmKvji0dy86Get5cP4/nV85g6qrpzFq/\nIKvpTw/sWcXEyvFMqhzHofsYXbKY/lSkJUpKSjhm4GiOGTiajXVbWbt9M13Lyqns2ltdlERERFJQ\n1UX7kWkS4w/Al83sUnfPvA5aJIUtOzbt6g6Si4TFsL6jGN53NBXdBja6g92ppJQ/1tzY7L7OH/c1\nhvQesVftkeK3YutapkaziLy4+k027ch8BuieZd2ZUDEmqrYYx37d1HVJ2k7vzt3o3VndlERERJLF\nqy7uX1DDvzOsuvhw9ShOUNVFTmWaxBgMfAj4mJktBBoNn+/uk1q3WVIscp2wGN53NMP6jtojYZHK\nR0acS6/y3txVcyObdyQP7QK9O/fjvLFf4X2DT92r9klx2l5fx2trnalRtcW8TUszfmwJJYzuO3RX\n0mJs32GUdSrNYWtFREREpKU21W3n0cVv8cDC2RlWXQzn9OqRqrrIk0yTGG9G/0TSSk5YzF0/i+W1\nS/Zqn/GExfC+oxjWJ/OERTonVn+E9+3/fp5b+jhvrJpG7c7N9CjvxaGVk5g08HjKVcYvkVgsxqIt\ny3fNIvLy6hq2N2Q+/Wn/Ln04smIckyrHM2HAWPp16ZXD1oqIiIjI3ojFYsxYu5IHFmZWdTGqbwVn\nVI/kxP2H071MY+nlU0ZJDHf/fq4bIoUlMWExb/0s5q2vaZWExfC+o6Iqi71PWKTTpbQrxx7wQY49\n4IOtul9pW1t2buWFlTNZU7eBrp06M67fcIb2GpT1Pl5aPSskLlZOZ9nW1Rk/trSklEP2OYiJUeJi\nRO/9NbaAiIiISDvXkqqLM4aOYmTfAXlqoSRLm8Qws2uAq929Nvr/tNz9m63eMmk3diUsohlCWiNh\n0atzX4b1GZnzhIUUv/V1m7jV7+Ofi/9Hbf22Ruve1X8UFx50BocPGJXysQ2xBuZsXLSri8jra9+i\nPovpT6u6V+zqInLEgNH0KNO4AiIiIiLtXYuqLoaGGUZUddH2mqrEmAh0BmqBk4H1QKpfmJkPwS/t\n3ua6jcyPEhVKWEh7t2LrWj4/9RoWb1mRcv0ra2qYMnU23znkc3xw/6MByGl79QAAIABJREFUWLd9\nIy+smsnUVdN5YdXMrKY/7VramcP7j2Zi5TgmVYxn/x776jwWERERKRDZVF30KCvnpP2Hc3q1qi7a\nm7RJDHefnPDnWOA54BHgEXfX+BhFQAkLKWQ7G+q5/MXr0yYw4hqIcdXrv+WV1TXM37SUmg0Ls5r+\ndFivwUyqHM/EinEcss9Bmv5UREREpIDEqy7uX1jDExlUXYzuV8Hp1aq6aM8yHdjzEODE6N+VZrYa\neBR4GHjS3bfmqH0dzsa69Ty16CGmvvMkG7avpXNpV6zfeE6u/gjD+o5u8X6TExZz19ewotUSFqN3\nTW2qhIXky39XvIZvfDujbRuI8c8l/8to217l3ZkwYCyTKsdzZMU49u22z940U0RERETawMZdVRc1\nzNu4rslt41UXZ1SPwlR10e5lOrDnLGAW8HMz6wwcBXwOeIAw3Wr3nLWwA3ni7Qf4zcxrqUvq1794\n0zyeWHQ/E/abzGWHXUW3sqZf7sSExdzov62RsBjeZxQHRlObKmEhbe2+t59qlf2UUMKYvgfu6iIy\nuu+Bmv5UREREpACFqosV3L9wNk8smcf2huarLs6oHsUJqrooKJlWYmBmw4H3Rv+OBqqBN4BnctKy\nDuaxhfdyy/Qmx09l2vKnufqFS/nexJt3TQUaT1jMTegSsrcJi96d+zJMCQtp52atX9Dix/bv0mdX\nF5EJFWPp21nTn4qIiIgUqmyrLk7efwSnV49U1UWByiiJYWbLgQHA84SxMb4I/M/dN+awbR3G6q3L\n+e2MazPadtba1/jRi1+mW3mPnCQshvcdzYBu+ylhIe1eXcOOrB9z0qCJnDviNIb32l/nuIiIiEgB\ni1dd3LeghieXzm+26mJMNNaFqi4KX6aVGP8EjiEM8LkeWAOsMrNX3L0hR23rMB5/+z52xnZmvP1r\nq55v0XESExbDo3EslLCQQjWga99mB/VM9uEhkxnR+4ActUhEREREci1edXH/ghrmb8qs6uKM6pEc\npKqLopHpmBifAzCz/YHJhITGBcB+ZjbV3U/OWQs7gP8tfazV9xlPWAzrOzqaKUQJCykuJw6awO1v\nPZTx9hVd+3HIPgflsEUiIiIikguxWIzpa1dwf5ZVFycOHkY3VV0UnYzHxIgsA94C9gcOAIZE/5W9\nsGbbqr16fO/OfRvNEKKEhXQEZxwwmd/PfZj6WNNfYnFnDjlWA3aKiIiIFJBsqy5Oica6UNVFcct0\nTIyvEyowjgIagKeAvwHnu3tmcxzu3tehwC3AGGAOMMXdpzWx/XHA40Avd6/N5liFoqykjLosHzNx\n4HEcPfgUJSykwxrYfQBfGXM21868s9ltx/YdxqeGnZqHVomIiIhIoh0N9Ty9bAFPLp3P2m1b6Vxa\ntqtSYlCPPQdXz7bqYmy/Sk6vHskJqrroMDKtxPgk8C/gx8Bz7p75AA4JzKwL8BBwFXA7cA7wkJkN\nTZWgMLO+0XZFbVjfUcxY/VJWj/nsmMup7D4oRy0SKQwfH3oCnUpKuP7Ne9IO9DmpYjzXvOsiukYz\n+oiIiIhIfjy/fBFXvfoMa7ZvbbT8pVVL+cOc1/ngkJF87eCj6Fxa2rKqi6GjOKhP/1w+BWmHMh0T\n49BWOt5koN7db4v+vsPMLgdOBe5Nsf3NwJ+Ar7fS8dulk4Z8JKskxqGVk5TAEIl8tPp4jh14BA8u\neoYnlr3I2rqNdC3tzPh+wzlzyHGM6zdclUoiIiIiefbfdxZyxbR/Ux+LpVwfAx58ezbzN66lqkdv\nnl62IKOqizOGjuL4qgNVddGBZTsmxt4aCcxKWubR8kbM7GygD6HryRW5b1rbmTBwMvv3GsbiTfOa\n3bYTnThzxHl5aJVI4ejfpQ/njfgg5434YFs3RURERKTD21i3nStffjptAiPRjHUrmbFuZdr1qrqQ\nZPlOYvQAkruN1ALdExeY2QHA9wljcHQlJOoyZmb9geQzvCqrluZRWadyvvXun/Od5y9k1dZ30m5X\nQgmfP/ibjO5/WB5bJx1FocWNSHuguBHJnuJGJHuFFjcPL5rDlp2pu/pmSlUXkk6+kxi1QLekZd2B\nzfE/zKwE+D3wLXdfYWbV0aps6sEvBa5seTPzb98eVVz73ju5e/ZN/HfJo9Q1bG+0fmS/g/m4fZ5D\nKo9soxZKB1BwcSPSDihuRLKnuBHJXkHFzSOL5rTocT3Kyjn1gBF8qFpVF5JevpMYNcDFScsMuDvh\n78HABOAQM7sZ6ERIYCw2s9Pc/fkMjnMjcE/SsirCrCrtVt+u/bn4kO9yzujLeHXlc2zYvpbOpV0Z\n2W881X0OauvmSfEryLgRaWOKG5HsKW5EsldQcfNO7ebmN0ryoSHGl8dPUtWFNCvfSYyngC5mdjFw\nK2F2kkrgsfgG7r6Y0O0EADMbAiwAqty98bC2abj7GmBN4jIzy3YW0zbTq3Mf3jdY00FKfhV63Ii0\nBcWNSPYUNyLZK7S4KW3BoOqHV1QpgSEZ6ZTPg7l7HXAKcBYhCC8GPuDuW83sZjP7dZqHxsiuO4mI\niIiIiIi0gWF99sn+Mb2zf4x0TPmuxMDdZxIG7ExePiXN9m8Dpblul4iIiIiIiOy906tH8vKqZRlv\nP7ZfJcNbkPiQjimvlRgiIiIiIiJS3CYPGsr+PXpnvP2nDzo4h62RYqMkhoiIiIiIiLSa8k6lXHfk\nSezTJXliyj2db4cxedDQPLRKioWSGCIiIiIiItKqhvbux+3v+xBH7zck5eCGA7v34ruHvY/Pjz48\n722Twpb3MTFERERERESk+FX16M11E09i2ZZNPL1sAWu219K1tIyx/SqZsO9gSkt0T12ypySGiIiI\niIi0C7FYjFfXLGHayrfZvGM7vcq7cGRlNYf0r6KkBdN2SvswqEcvzh4xvq2bIUVCSQwREREREWlz\nL6xcyA0z/sP8TWsaLf/dnGkM6z2Ay8cew4TKIW3UOhFpL1S/IyIiIiIibeqxJTVc9vx9eyQw4uZt\nXM1lU//OE0s9zy0Tkfbm/9m77/g667r/4680adK9m7ZJ0wl8OhABZRQEWhFFFCdOvFFRkCGKcjtv\nb0FF3OuHyhIQlKGCILeyFCizZe+2n9KdJm2a7pE28/z++F6nPT09JzknzTnNSd7Px6OP5lzze43v\nNT7XdyiIISIiIiIiB8yKbRu47Pn7aSPW7nStsRjfff4+Vm3flKeUiUh3pCCGiIiIiIgcMLcve5GW\nWFtG0za3tfLXZS/mOEUi0p0piCEiIiIiIgdEU2sL91UvyGqef656nea21hylSES6OwUxRERERETk\ngFi4uY6Gluas5tnR0sS6ndtzlCIR6e7UO4mIiIiIiORFU2sLL2+sZf66FcyrW8EbW+s7tZxYB+1n\niEjPpSCGiIiIiIjkzOodm3mqbjnz163gufpqdrZmV/IiWd8+xYwqG9hFqRORQqMghoiIiIiIdJmG\nliaeX1/NvLoVzF+3guodm7t0+e+oOIR+JX27dJkiUjgUxBARERERkU6LxWIs2bqe+etW8FTdCl7a\nsDrj3kYARpQNYGNjQ8bTf2zqkZ1Jpoj0EApiiIiIiIhIVrY07eTpdSuZv24F89etpH5X5g1tlvYp\n5shRVcwqn8SsMZOYNGgENy5+mqsWPtnhvF+ccQIzh4/dn6SLSIFTEENERERERNrVGmtjwaa1zKtb\nwbx1K1iwaS1tWTSuOWnQCGaNmcSx5ZM4cuT4faqDnG3HMrhvP3634HF2tDTtM//AklK+NPNEPjT5\nzfu9LSJS2BTEEBERERGRfdTv3M68dSuYt245z6xbxdbmXRnPO7CklKNGT2DWmMnMKp/EuAFDOpzn\nI1MO5z0TZnB/9UKerl/JtuZGBvct49jySZw6fjr91Q6GiKAghoiIiIiIELo/fWljze4GOZdsXZ/V\n/NOHjeHY8knMKp/Em0aMo6RPcdZpGFBSyocmv1klLkQkrbwHMczsCOBqYCawGDjf3Z9OMd05wNeA\ncsCBS9z9iXymVURERESkJ6vevimUtqhbwXPrV7GrtSXjeYeX9g9BizGTOaZ8IiPKBuQwpSIiQV6D\nGGZWBtwD/AC4HjgLuMfMJrt7Q8J0s4EfAie7+6tmdhbwf2Y2xd035TPNIiIiIiI9xY7mJp5bv4r5\nUeCipmFLxvMWFxVx2IgKZpVPZtaYSRwytJw+RUU5TK2IyL7yXRJjDtDq7tdGv280s68ApwF3JEw3\nHvipu78K4O43m9kvCaU3VBpDRERERCQDsViMN7bW764i8tKGmqy6Px3Xf8juBjmPGj2BQX3Lcpha\nEZGO5TuIMQ1YkDTMo+F7Brj/OfG3mR0PDEoxr4iIiIiIJNjctJNn1q3kqShwsaFxR8bzlvUp4chR\n46MGOScycdAIilTaQkS6kXwHMQYCDUnDGoC0FejMbAahlMb/uvvGHKZNRERERKTgtLS18fqmNaGK\nSNT9aeadn8LkwSOZVT6JWWMmcfjISvoVqxcQEem+8h3EaAD6Jw0bAGxPNbGZvRO4HfiZu/8s05WY\n2UhgZNLgyizSKdLrKN+IZE/5RiR7yjddo27nNubXhaDFM1F3pJkaWFLKMeUTd/ckMjaD7k/lwFK+\nEdkj30GMhcCFScMMuCV5QjP7LPAr4Fx3/2uW67kIuLRTKRTpvZRvRLKnfCOSPeWbTmhsbeGlDTXM\nW7eceXUrWLZtQ8bzFgHTho2JGuScyKHDO9f9qRxQyjcikXwHMR4GyszsQuAaQu8k5cADiROZ2cnA\n74BT3P3JTqznSuDWpGGV0fpFJDXlG5HsKd+IZE/5JgOxWIxVOzbtbpDzufXVNGbR/emIsgG7S1oc\nUz6R4er+tNAp34hE8hrEcPcmM3s3IYBxBbAEON3dd5rZVUDM3S8Avg70Be4zMwgB5Bhwhrs/mMF6\nNgB7hafNrKlLN0akh1G+Ecme8o1I9pRv0ot3fzovqiZSm1X3p31484gKjh0ziePKJ3Gwuj/tUZRv\nRPbId0kM3P014PgUw89P+PtdeU2UiIiIiEietcVivLFlHfPWrWBe3Qpe3lhLaxbdn1YMGBJVEZnE\nW0ZVqftTEekV8h7EEBEREREpRC1tbTy+dikP1S5mY2MDZX1KOHTEON4/8VBG9RuU0TI2NTbw9LqV\nu3sS2diY3HFfemXFJbxlVNXunkQmDByu7k9FpNdREENEREREpAPP1K/k+y88QN3ObXsNf6JuGdct\nmscZk9/MxYeetE+DmfHuT5+K2rZYuDm77k+nDB7JrDGhbYvDR46nrFiP7yLSu+kqKCIiIiLSjifr\nlnPJ/LvTVvVojbXxl2UvUrdzGz8++nTqd27fXdLimXWr2N6Sefeng0rKOKZ84u4GOdX9qYjI3hTE\nEBERERFJY1vTLr7z7L8yaqti7polvOf+a9nQuCPj5RcBM4aP3d2TyMzh4yjp02c/Uiwi0rMpiCEi\nIiIiksY/qxdkVZIikwDGiLIBUYOcEzlm9ESGqftTEZGMKYghIiIiIpLGvate3+9llBT14c0jK5lV\nPoljyydx8NDR6v5URKSTFMQQEREREUmjpmFLp+arGDB0d4Ocbx01gYF9S7s4ZSIivZOCGCIiIiIi\naXSmxMTFh57EJ6e+Rd2fiojkgFoNEhERERFJY8rgkVnPc/ToiQpgiIjkiIIYIiIiIiJpvH/im7Ka\nfsawsRw8dHSOUiMiIgpiiIiIiIik8Y5KY1z/IRlP/18HvzWHqREREQUxRERERETSKCsu4RfHfoAh\nfft1OO1ZBx/FOyotD6kSEem9FMQQEREREWnHwUNHc8NJn+CY0RNTjh/dbxDfevM7+OKME/KcMhGR\n3ke9k4iIiIiIdGDioBH89vgzWLFtAw/XvsHGxgbKiks4dPg4Thg7hZI+xQc6iSIivYKCGCIiIiIi\nGZo0eCRnW/Y9loiISNdQdRIRERERERERKQgKYoiIiIiIiIhIQVAQQ0REREREREQKgoIYIiIiIiIi\nIlIQ8t6wp5kdAVwNzAQWA+e7+9MppvsEcDlQDjwCfN7d1+UzrSIiIiIiIiLSfeS1JIaZlQH3ANcD\nQ4ErgXvMbEDSdIcBVwEfA0YBdcCN+UyriIiIiIiIiHQv+a5OMgdodfdr3b3V3W8kBChOS5ruk8Dd\n7v6cuzcC3wBONbPReU6viIiIiIiIiHQT+Q5iTAMWJA3zaHja6dx9I7ARsJymTkRERERERES6rXwH\nMQYCDUnDGoABnZxORERERERERHqJfDfs2QD0Txo2ANjeyelSMrORwMikwVUAa9euzSihIt3VySef\nPAlY7e4tXblc5RvpyZRvRLKnfCOSPeUbkexlm2/yHcRYCFyYNMyAW1JMt7vqiJmNAoZHwzNxEXBp\nqhFnnnlmhosQ6baWA5OBFV28XOUb6cmUb0Syp3wjkj3lG5HsZZVv8h3EeBgoM7MLgWuAswhdqD6Q\nNN1twFwzuwF4AfgRcK+7b8pwPVcCtyYNKwUmENrgaO1c8vNuMmGfvZ1wYKVrFfL+XZ2DZSrfSCYK\nef8q36RXyMe1EBTy/lW+Sa+Qj2shKOT9q3yTXiEf10JRqPs443xTFIvFcpmQfZjZoYQAxqHAEuA8\nd3/WzK4CYu5+QTTdGcAPgTHA48Bn3X19XhN7gJnZIYSLkrn74gOdnp5G+7dn0nHNLe3fnknHNbe0\nf3smHdfc0v7tmXRcc6837ON8l8TA3V8Djk8x/Pyk33cAd+QrXSIiIiIiIiLSveW7dxIRERERERER\nkU5REENERERERERECoKCGN3bBuB70f/S9bR/eyYd19zS/u2ZdFxzS/u3Z9JxzS3t355JxzX3evw+\nznvDniIiIiIiIiIinaGSGCIiIiIiIiJSEBTEEBEREREREZGCoCCGiIiIiIiIiBQEBTFERERERERE\npCAoiCEiIiIiIiIiBUFBDBEREREREREpCApiiIiIiIiIiEhBUBBDRERERERERAqCghgiIiIiIiIi\nUhBKDnQCegMzOwwY5u6PHei0ZMvMJgLLgWZgtLtvTRr/EeAvwB/d/WwzOwl4GOjv7k05Sss0d1+c\nYvwjwDx3/3bS8DJgJzC7K46BmU0CDnX3f+7vsnqa3nquA+No59zMYZqXAz9y92vzsK4VwISEQduB\necBFXbHNZvZp4MfuPm5/l9XVeut53dXX8K62P8clyjsT04yOAXOif+9y9+M6sfxPA99x94OznTfX\nzOxGoMzdP9kN0lKweQvAzNqAu9z9w0nDTwIeAfrlIx+Z2fuBrwJHAC3A88DP3P3BDubL2z0kG9E5\n+mlCXiwC2oDNwH+AL7t7XQbLuBQ41d1nFdJ1LR+U7/Zr3bMJ59Ln3f2GpHEzgBeBL7n7NZ1Y9ueA\ny9y9KoNppwJvAAe5+7KE4e8E7gF+7+5fzWA5jwOPuPt3uypt+aKSGPlxNzDtQCdiP8WA96YY/mHC\nzSXuSWBcji4eq4CxhEx7IN0AZP1Q20v05nM9luuEHWAx4GuEPDgOOBbYCPzLzIq6cB3dUW8+r7uz\n/TkubyWcy2OBXxBe+saw5/x+CvgZcNp+pK+7ns/dSU/IWx8ws1R5Ky/H38y+AdwC/BN4CzCL8CL3\nDzP7cj7SkCN3syePjgdOBWYCf85iGfFjUEjXtXxQvuskd58L/An4kZkNTRr9O+CpzgQwEmST/r2m\nNbNZwJ3ADZkEMCKnAz/OQdpyTiUx8qOrHvAPpLnAB4Bb4wPMrJRwU5kfH+buLcC6XCTA3WO5WnaW\nesLxzJWesG/m0rlzvSdse0e2uXt8m+vM7GJgDeHB+bkDl6yc6wnHdi4H+BqeA50+Lu6+If63mW0H\nmt29PmmyFqChs+uQjPSEvLUCuNLMHnL3nflcsZm9Gfgh8B53fyBh1BVmtgy42cwedPeF+UxXF9mV\nlCfXmtnlwK1mNtTdt2S6oAK7ruWD8t3+uQR4D3AFcCGAmZ0JHAMclue0EK3/TYRA5h3ufkGm87n7\n5tylKrcUxMixqIrDROAqMzs2Kq47DfgN8DZgLSGC/v3oIhsvhvrfwMGEahAPEootbYvGnQf8Ffg2\nUAz8hBB1vxY4KPr7k+6+LUV64kX0ksWAye6+Ks2m3AX81MxKEyLZ7wQWEUpIxJc/m1DMqp+7N5nZ\nMYQI31GEkj/PA+e5++sJxZzfG+2PCuAfwDeAqwhFeRcD/+Xur3VUnSQb0ZeLC4DhUZq+6u4vRuPG\nAr8G3gEMjtb5P+5+Z7T/TgJOjI7n2/cnHT1Jbz7XE5aLmd0FrHX386Pf3wEuJRTd3GFmQ4D1wJuB\nauCXhEj4SKAG+Lm7/y6ad6+ivmZmwEJgUnL6o339OHCNu38nGtbeeV4C/Aj4L6AMeIJQBHJ5mv2S\nyl4veInFdxOGzQPuc/fvR7/PB74CVAIvEYoG7xMAMbPfAu8DTnD3lWZ2GfD5aD+9Alzi7k9kkdZO\n6c3ndXQNb4vWdzEwI5r+XHd/Npo+1fhz4sfUzMYBV0br2kq4xn/d3XdE4y8jzXGNrsW/AE4B+hKK\nyH7J3bekOS6nAZcBhwKthHP6c+5em2aftCtFcfTbCUX2fwoMI5TK+y1wI6EY//PAJ9y9JlpEkZn9\nkPCQu5OQNy9LWP57CS+gBxNKGP7I3W+Pxt1IuGdOB6YALwCt7v7uaPyngJuBGe6+KBq2Fvisu99n\nZp8EvgVMBZYCl7r735O2byDhxe7D7n5/wvClhKpd10Vf9n4BHA6sBK5y9/8XTTcYuI49x+dh4MKE\n7e9o//aUvPVdwjPD94Cvp9nWtNfb6J6xJv7i0d49I0Uw4nPAi0kBDADc/fZoWWcDX0s6pyYD70+R\nzmyfjb7j7ndE45cTzpUzCC9zq4CL3f2+aPyHgB8Qzudqwr0u22osrYTj0RQtM+35mbRds9n7ulZF\nuC69nVA18mbgW+4ei+6zvyCcg/2ABcBX3P3RaFkdXRPPJ5yjlYRn2O+6+91ZbmfOKN/tf75z9/VR\nXrnazK4hXGN/Gu2zJQnrP4TwjHc84Zy9BfiGuzeb2cnAH4G/R9t/DeF8SUz/1YQPDSe4e3Wa/RCv\nWvIA4bicnTTuceB+QunZk4F6Qr79U8L43dVJzOxCwrk9jvCM9iV3fyHFOvdKm5n9APgs4V7+MuHa\n8VS6NHcFVSfJvQ8BqwkZ7MsW2me4n3CADyOcbGcAlwOY2fGEE/kHhIvFR4HZRJG+yBGEoMCxhADB\nFYQLxReBdxGqOpyXJj1fYk/xvMR/4wg3lVRiwGOEDPiOpG27k70jujH2vMwNAu4lFOObScjEfQg3\nh0SXRfvgfYSizc8SvhYeRbhY/iRp+dnaK+JsZhcA5xD2/ZHAo8AjZlYeTfInwg36hCjdjwLXRcfu\ny4R2AH5L2H7Zo9ee60nuj7YjbnY0X/zF/mRgdXRT/BXh4es0wAg3tF+bWWWa9MXXu5do+geAPyUE\nMDo6z6+I0vYBwv6tBR6OjluHzKwf8B3CA97z7aUvYZ7PEorof4/wovk8oTpKv6TpLiVcC06OAhgf\nIOS9TxL203zgTjPLxz1M53XYlm9F27sN+H0H469KGHcXIdh1FPBBQvDueoD2jmv08PkwMDpK86mE\nc+aWhLQnHpdJ0bpuIhSTPpXwotZuPd8MJO6LkYSHtFOALwAXEc6FKwjHrILwEB83NUrzLMKL4cVR\nHoh/Nbud8IA7k/AAfLWZnZow/5nAz6Pt/y1wvJkVR+NmE6oBvS1a3hGE+9bDFr4I/iFa9mGEffIX\nMzsqccOiQNL/AR+JD4umqQT+amZjgPuAO6I0fg34hpnFz80fEPbxiYTjOxTY5wWyHT0hb0F4KfgG\n4fi+Kc007V1v7yd8tImbTfp7RrKjSShJlcLj0fri4ufUKSSVnuvks9G1SfeM7xHO1RmEoOT1ZlZs\nZqOB2wgvyocA3wd+387+2kcUXPgW8B9335nB+Zko8dm0lNC2RglhH38MOIsQoIQQLK0jlDA8khCM\nSa4ekPKaGOXD3xAC9QcTqr7cZmajMt3OPFC+2/98h7tfT3gf+Cnhur+O8HwDgJmNJARN6qNlnknY\n9z9LWEwl4R53BHB14vKjoMD7gLe3F8CIlvFvoBT4dFRqPdm3CVWIZhBKa1xtZsOSJzKzcwhBn0sJ\n58LLhGe00vbSZmZnEO5xnyDcf58D7rCuq2qckkpi5Ji7bzKzVkIx7G1mdnb0dzxquNRCncV7zOxb\nhJf2z7n7X6Px1Wb2IOECHVcCXODum83sSsIF45qEr1f/JpyoqdKzjXDBzVYr4WHnA8C90YPU6YSL\n3JFp5hkIXOHu8aDFSjO7gRC0SHS5u78cpf0lYKW73xr9vplwkYrrKENcYmYXpRiemKm/QYgQPhT9\nvszMTiF8DbyC8KXwnnj018x+Fo0b7+5LzawJ2FHIRbByoZef67Dn3Lyf8IVjLKHNiGMJD1onEB6c\nTol+Q3jAvNLdX4m25wrCzWMaoVRGJkYSReB97zqQac9zM/sl4QXsbe7+fLTu8wlfsj5MQpWDJL82\ns3h+7h/9/8k0N81Uzids7y3ROi8BGoER8QnM7AuEh5qT3D3e/s0kwgt4tbuvis6ff5CHIrE6rwH4\njUcNBEbXw7vNrCjhuKccT3hAPAQ43t1bo/FnA4vM7Ku0f1zfHY1/m7tvjOY9E1hgZod6KJ2XeFzG\nEEr1xB8EV5nZ39g7oLi/ioH/jko+LDKzXxGK7t4bpe8OwhfouO3Ap6JjttBC0f8vEkpu/Ddwo7vf\nFE273EKjcF8lXEMAXo+fR2a2iHDeHEV4aZ1D+EhwAiFgcQow190bzewrwO/c/cZoOT83s7cSrgln\nJG3TrcANZnZudIw+QriWbImO0ePu/suENF5GePm5mnB8dhDu2dstfJHN+GWtB+Ut3P0GM/sM4cVt\nVuK4KEjb3vU2m3tGshHApnaStom9j8nrCfuPEBfYrdPPRoQv0QB/TiiZ8X3Cl9wqQsmlEqA2eiH7\ns5lVE16m0znDzE6P/u5LyH+PEgItEF6a2js/0zklSvMx8ee46L7bKOfTAAAgAElEQVQzzMwGEI7h\ntfFSAxZKBT5gZsXx6xjpr3kTCc+b1dF2/tTMXiDkk25B+a5L8l3ceYSGPE+M1tOaMO4sYBehxEor\n4Z7xRUKg/jvRNDHCe9LyKH3xtH+R8Lx0oic02plCEaFh7qWEoM8lhCBEsgeioEu8xMn5hAB7cmnW\n8wnndvwd7CuEjxCJz2ip0jaJPffylWb2TfZ8IMlZOxoKYuTfdGCamSVm2CLCBXqSu79gZtvN7H8J\nGX5mNM/fEqbfFL/wRtFoCMX64nYSik3tw8yuAj6VYlSMUCy1vRvKXYQLBYQHqNXuvizpJribu9eZ\n2Q1m9iXC12YjPCwn33CXJvzdACRm2LTbksb1hK8MiUoJX4vjxWergJvM7I9J08SLgF0NfMTMvp6Q\nZgg3UMlcrznXE0UXcI/mqyGcz/8kfO2BUKz+y9G0N5vZ6Ra+zhohGh8ju3Ptu4R9+pf4gA7O8zcI\nX4jLgLlJ29QvSkc6PyR8TYMQpDwBuNHMSHwwbscMEkpWuXsz4etZ/OY9ivAldzN7B3FuIzwsLDGz\n5wlfyq5PemDIl954Xic2phzv3aSE0ONJe+OnE77Ob05aRxvhPEt7XC0Ub14eD2AAuPsiM9tE2K+v\nJS7Q3ZeYWUN03X5TtO7D6Pq2WpLvV+0dN/e9i08/T3S+E7bh0OgBPK6Yvevt774XuvsuM3sUmGNm\ntYSHyqsJX70hXFfi1UWms3cJRgglIs9PsT33Ec7fdxCCoR8BvpmQxnclnevFQImFkjK/IrzY1pvZ\nXMKXvpvovELOWxBK57xooSRA4tfb9q63h7j7rZneM1LYSHh5SacS2JDwO+ULURc+GyVfC4qAvu7+\nkpndQ3gxXk7Yvj+6e3sBmPsJ211EaJ+m3vdu+6Cj8zOd6cCyxA9R7v5/8b/N7PfAp6LAX/J2xu85\n6a55DxDy+fNmtoAQOL7e899mQzaU77LPdwC4+wIL1VLKfN8qF9MIVb0Sn1OeJOzXQxKGJVfhHUMo\nRbeBzD5mLSKU5v0acKmZ/dPdX02aJrGaSvx87ZtiWTMIpakA8FD1NPEZLV3abgHOJQTAnmPPvTyx\n0fAupyBG/pUQvr5+jn2/IlZHUe97CCfEw4RiR19l76o/zewr0xPlf9m7KFOidPWG4+l8EBhoZscR\nvubd2d6KLNSFfg54lXAz+hPhwvedpEmTt2d/TvrNyVFL27uoY/ycPzNKV6LtUST9QaCcUNT3QULD\nhe0V15TUes25nsL9hLq21YRi/I8Dv4xezCqAhwDM7CZCGys3E+rXzyehfQL2jWCnumY/TDhXrzWz\nW919KR2c5+x56J3NvkHF9koY1Sflr1ctdNV2CaE+bKqIe2KaO2oZvo3QRs6vCcHIz8HugOgMQvHO\n06LhF5rZ0d5+Mctc6I3ndarjVpTB+BLCC9Cp7Luv1kQPuymPK+ELVirFpAjyWShO/CThpfwxQvHu\n0+nakhiQ3f0qOcjWJ2H+EsJ5fl078yS/+NxPyB81hG19HBhv4enyeMJXcUi971LuNw91s+8kvJxu\nJAQS70lI4+2E0mFFSfO1AI+a2fgoTacRvr5+ihDc7IxCzFu7uftCM/s5odRCYsAofg2cTfrrbUb3\njBTmsXeR+GRvYU/JHtj3nEpOY7bPRk8nTZv2WuHuHzSzwwn58nTgPDP7YLwkUwrbvf02mtKen+yb\n9zpKI7A7mPM04UXvbkJgsD/7XitTbmcUrDjOQhWM9xDaHbnQzGaneMntLpTvss93iXaSelvTXYcT\n/4/Pn6iNcO78jlBV5QvtrDsGfCEKcv+IUMLkZjM7KrpGx3V0D29vug7T5u5ron32DsK94Bzggigd\nnWqTKhMKYuRH4oP9QkJxztXRV0gsNBh2IeHmfxGhOF68uBxmdjBpoufZcvf1hIZqshGL5m00s/sI\nF+X3E6KU7fkE0ODuu+v4mtm72bf+ddZp6ayoiOxaoNLd/5GQrmsJxceWEC544+MZz0JjcbAn3Tkr\nGtUD9NZzffe8kfsJF/mlwB+iaP0Ows360eiGM4LQ2NTbPGr8KHqhgz3nWhMwJGG5U1Os9x/u/icL\nfXhfBbyznfP8OkLdyX8RvmyNSShmWUz4Mv57Qk8WmUp8OdorvdEyJyZMu5hQ2uTOaHwR4YtW/Ca9\n0d3/Y6FK2H/M7AZ3f9JCfcsKDw22/dtCg1p1hLz6pyzS2lm9+bzeHwsJxba3etQbSPTC/RPgC2b2\nHtIf10XAZDMbFW0zZjaTcH4tStyuyDnA0+4e/4oWLwp7IFvhN9u7IdXj2POlcCEwNTEoaKHU4ijS\nt+MRb3+jlnAd2WZmr0TTr3D3FdF0iwhFoxO/lB4PeJrl3kp4GdxAqC4Qf6heCLwj8UXSzD5GCDqd\na2bfBl7w0Bjp7RYa8p5nZlVZBBcLPW8luxz4OHsX6V5CeMlr73rb4T0jzfquI7wsfMLdb0scYaH6\n1cEktHmSzn48G8VoP4/F26E4nNDo7JcJVUx+EF2LPkyoFtUZac9Pdz/X0pcwW0y4tgxx963RfBcS\n6vhfQ2jnZYjvqQIX7+mhw2uJmb2dUMz+MkKg8dtm9jrhxa87BTGU7/Yv32ViEfAhMytJCCgcT3j2\nWkL6apz17v5w9Bz0QPQclBwsTNQKIbBsoWrQ04Rq+8kfjDMRf0b7B4CFdseWENqCSps2M/soMNpD\no/QPRvfyesJHutv2WUsXURAjP7YTimoNJzTy811Ckb3LCfXZ/0B4+GqyUEz0OAt1Z3cRooqHkXn9\n+FxIvHDfTShSWOMdd9lVC4wzs3cRMvO7CQ+aiRfPbB8wu+KB9KfA98xsHeGm8nnChfr/EaK1rcAn\nLNSnPpRQZBb2FIXbDhxkZqN93y75erveeq4nz/soobRDBaFeJIQI/8cJrT5DqAO6DfiwmdUQ6hT+\nknDTjZ9rzwKftVD/dADtN1L4RUKRyo9HLxWpzvMzCfUdd1goMvs7C3WBlxMafno74YElnSEW2h6A\ncP94e7TM+M3yWeByCz0nPEUooTEwYf5fERqUejlK08XRts4noa6+uz8S5b+ro4ffUuAnZrYGeIbw\n5XEgoS5qPvS287qj62ym4/9NuPbfbqEIehEh0NYUla5Jd1xfIFQBXAjcEs3bn/Cw+aRHvSWw93Gp\nJeSlWYRAyCcIJQTiAY8DYTDhq9gPCFUqLyAELiGUNJofbdudhAYaf0xoDyYld3czqyM0rBdvXPVR\nQj76dcKkPyV0Q/k64eviBwklb04jtUcJ153zCPk57nfARRba0LmaEET9LXsaOZwEfDp6cF4TbVst\nGXw9TVDoeWsvUYD6AsLLUTx4uMNCkfn2rreZ3DNSrW9BdA5dZ6HHjbuiUR8k7MuvZ3j/gv1/Nkol\nfi3YQghcbiGUOpxIyBP3pJsxAx2dn+nS8iDhGFxvoRHpsYRGOn9GOHf7AR81sycJgcf/ieYrI7Th\n1J5G4DvRPvwX4fycSPfrglz5LuhUvsvQzYRnoz+Y2U8IAf3fALd6aJeko236j4WqKteY2ZFpqmYk\nl5B7wUKplG+Y2T3u/kyWaf4Vodva1wjPV5cQPlI9Q+hlJmXaCHnmp1Eg9DlCiYx+hIBlzhyw3knM\n7OjowT3d+HPMbLGZbTazp83sbflMXxf7LaGY1vXu3kD4+jWScFL8jXBBjUc4LyM0dPQEodjWDsLL\nyRHtLD/XJQMSl/8vwgvFHRnM91dCbwu3EFq4PYFQrHiomU1OsexUv9tLS2fH/YbwsvhzQrHJU4DT\n3f01D13DnUe4wC0iNHT1X4T+qN8SzX8N4SK4T5dm0mvP9b3mjaL3jwGr3L0uGvxo9P+90TTNhAfE\n9xDOtV8QHpaeYM+59j+Eh6r5hAe/5CBG4jpfI+z/X1roGizteR7N8nVCUdmbCA+sk4FTEtKbyk/Y\n85KyNErf5R41rOahQbifEG6EzxKK5O5+SHX3vxDqW/6ccE04lNCFZapGzy4hPPxd4qGRqe8RHrIX\nERpFPDNhW3Ktt53XsTR/ZzXeQ8Of7yO8wMwl7Kc3iHp2aue4vp4w7w7CQ+U/CXXN35uwnt3HhXC+\nP07IX08T2gL4CHCIhcb6cqGj4zaPPfn3x4QuHO+G8LAZpe9MQvselwPfdPc/dLDMBwgBh/hLUfy6\n8q/4BNGX9IsJD+yvEgI6H3b3f6daYLSv/0IoSXV/wvAawj37GMLD6DWEINT/RpN8lfC1+e/Reg4F\n3uPZtVXTk/IWAB4afPxL0rh2r7eZ3DPScfffEPLUKYRz7WnCS8QHonGZpn9/n43auxYsZ08vdK8T\nXpyvdferUsyTkQzOz3RpaYvSMYBwnt0UpeU37j6fUD3lF4RA6pmE3jUaO9jOeJqeJLQN8CXCfvo1\nIV931EBkvinfsX/5riPRc827CG3NPE94H7qNPfs1E18hBOfSBVRS7efLCPfZmy00bpouX8YS/o6n\n+RbCvegXhDxlhGe0VNXQdqfN3W8mlBL8OeG8vxj4eBYB1E4pisXyXzI+itr/Amh29/IU42cTXoBP\ndvdXzewswsV1irffCJCIiIiIiIiI9FB5L4kR1aG8iKj/4TTGAz/1qHXVKMLTyt7d+YiIiIiIiIhI\nL3Ig2sS43t2viBqNScnd/5z420Irv4OIuskUERERERERkd4n7yUxOqhvvQ8LrfXfAfyvJ/QXLyIi\nIiIiIiK9S7funcTM3kno9utn7p6uD+FU840kNFCTqJjQsvBrvnffuSKC8o1IZyjfiGRP+UYke8o3\nInt02yCGmX2W0ML9ue7+1yxnv4jQuvA+Hnroof1NmsiB1hXdzKaifCM9mfKNSPaUb0Syp3wjkr2s\n8k23DGKY2cmE/p9PiborytaVwK1JwyoJXQOJSGrKNyLZU74RyZ7yjUj2lG9EIt0miGFmVwExd7+A\n0K9vX+A+M4MQmYkBZ0T9ALfL3TcAG5KW39TliRbpQZRvRLKnfCOSPeUbkewp34jsccCCGO7+KFCe\n8Pv8hL/fdUASJSIiIiIiIiLdVt57JxERERERERER6QwFMURERERERESkICiIISIiIiIiIiIFQUEM\nERERERERESkICmKIiIiIiIiISEFQEENERERERERECoKCGCIiIiIiIiJSEBTEEBEREREREZGCoCCG\niIiIiIiIiBQEBTFEREREREREpCAoiCEiIiIiIiIiBUFBDBEREREREREpCApiiIiIiIiIiEhBUBBD\nRERERERERAqCghgiIiIiIiIiUhAUxBARERERERGRgqAghoiIiIiIiIgUBAUxRERERERERKQgKIgh\nIiIiIiIiIgWh5ECt2MyOBu5y98o04z8BXA6UA48An3f3dXlMooiIiIiIiIh0IwekJIaZnQ08APRN\nM/4w4CrgY8AooA64MW8JFBEREREREZFuJ+9BDDP7NnARoZRFOp8E7nb359y9EfgGcKqZjc5HGkVE\nRERERESk+zkQJTGud/cjgOfamWYasCD+w903AhsBy3HaRERERERERKSbynsQw93rMphsINCQNKwB\nGND1KRIRERERERGRQnDAGvbsQAPQP2nYAGB7JjOb2UhgZNLglA2IikigfCOSPeUbkewp34hkT/lG\nZI/uGsRYSELVETMbBQyPhmfiIuDSHKRLpCdTvhHJnvKNSPaUb0Syp3wjEumuQYzbgLlmdgPwAvAj\n4F5335Th/FcCtyYNqwQe7rokivQ4yjci2VO+Ecme8o1I9pRvRCLdJohhZlcBMXe/wN1fNrNzCN2q\njgEeBz6b6bLcfQOwIWn5TV2ZXpGeRvlGJHvKNyLZU74RyZ7yjcgeByyI4e6PAuUJv89PGn8HcEe+\n0yUiIiIiIiIi3dOB6GJVRERERERERCRrCmKIiIiIiIiISEFQEENERERERERECoKCGCIiIiIiIiJS\nEBTEEBEREREREZGCoCCGiIiIiIiIiBQEBTFEREREREREpCAoiCEiIiIiIiIiBUFBDBEREREREREp\nCApiiIiIiIiIiEhBUBBDRERERERERAqCghgiIiIiIiIiUhAUxBARERERERGRgqAghoiIiIiIiIgU\nBAUxRERERERERKQgKIghIiIiIiIiIgVBQQwRERERERERKQgKYoiIiIiIiIhIQVAQQ0REREREREQK\nQkm+V2hmRwBXAzOBxcD57v50ium+BZwPDAZeA77s7i/kM60iIiIiIiIi0n3ktSSGmZUB9wDXA0OB\nK4F7zGxA0nRzgP8G5rj7cOCfwN/ymVYRERERERER6V7yXZ1kDtDq7te6e6u73wjUAaclTbcDiAGl\nZlYMtAEN+U2qiIiIiIiIiHQn+a5OMg1YkDTMo+F7Brg/Y2a/A14HWoGthACIiIiIiIiIiPRS+S6J\nMZB9S1Q0AMnVSc4AzgXeEs3zG+CuqDqKiIiIiIiIiPRC+S6J0QD0Txo2ANieNOxM4Bp3fzH6/X0z\nOwd4B/CvjlZiZiOBkUmDK7NPrkjvoXwjkj3lG5HsKd+IZE/5RmSPfAcxFgIXJg0z4JakYbuA5FIX\nrUBLhuu5CLg069SJ9G7KNyLZU74RyZ7yjUj2lG9EIvkOYjwMlJnZhcA1wFlAOfBA0nS3A38ws78A\nrwJfJlR9eSLD9VwJ3Jo0rDJav4ikpnwjkj3lG5HsKd+IZE/5RiSS1yCGuzeZ2bsJAYwrgCXA6e6+\n08yuAmLufoG7/8PMxhC6VR0BvASc6u47MlzPBmBD4jAza+rKbRHpaZRvRLKnfCOSPeUbkewp34js\nke+SGLj7a8DxKYafn/T7WuDafKVLRERERERERLq3fPdOIiIiIiIiIiLSKQpiiIiIiIiIiEhByCiI\nYWYTzKwoxfBiM3tr1ydLRERERERERGRvmZbEWA6MSjH8IOCxrkuOiIiIiIiIiEhqaRv2NLPzgO9G\nP4uAV82sLWmyIcBrOUqbiIiIiIiIiMhu7fVOcj3QQCitcQOhS9QtCeNjwHbUN7GIiIiIiIiI5EHa\nIIa7NwM3A5jZcuBJoMzdd0TDzN09L6kU6UIbdu3k/1Ys5Zn6tWxvbmZI31KOHTOO0ydOZWhZ2YFO\nnoiIiIiIiKTRXkmMRKuBF4F7gW9Ewx43s2rgA+5enYvEiXSlWCzG9Yte5cZFr9MS27tm1LP1a7l2\nwSucO+Mwzjx4OkVF+7RjKyIiIiIiIgdYpg17/g5YBPwiYZgBy4DfdnWiRHLh16++wHULX90ngBHX\n2NbKla+9yHULX81zykRERERERCQTmQYxjge+6e7r4gPcfRPwHWB2DtIl0qXm163h9iWLMpr2+kWv\n8trG9TlOkYiIiIiIiGQr0yDGJmB6iuGTgB1dlhqRHPnr0swCGHF/W6rmXkRERERERLqbTNvEuA74\ng5ldCjwXDTsCuJTQc4lIt7WlqZGn1tZmNc9DNav49pHHUlZcnKNUiYiIiIiISLYyDWJcHk37fWB0\nNGwd8Cvg5zlIl0iXWbplE7Es52lua2Nj407GDRiUkzSJiIiIiIhI9jIKYrh7jFDq4lIzGwU0ufvW\nnKZMZD/UNexgbm01c2tX8+L6uk4to6Qo09pWIiIiIiIikg+ZlsTAzGYA5wCHAq1m9hJwtbuvyFHa\nRLKyattWHqmtZm5tNQs2bdivZQ0vK2NEv35dlDIRERERERHpChkFMczsPcBdwDzgWaAYOAG4yMze\n6e5P5i6JIqnFYjEWb9kUlbioZtnWLV227PdNPIhilcQQERERERHpVjItifET4DJ3vyJxoJldBvwa\nOKqL0yWSUlssxqsb65lbU80jtdWsacisc5yhpWVsa2qiLYPWMQaUlHDG1EP2N6kiIiIiIiLSxTIN\nYkwB7kgx/Bbg612XHJF9tbS18Xx9HXNrq3m0tpoNjbsymm/cgIHMqahidmUVh44YxRNravj200/Q\nEmtLO09ZcTE/PuZEyvsP6Krki4iIiIiISBfJNIhxP3A28M2k4R8A/t2lKRIBdrW08PS6NTxSW80T\na2rY1tyU0XxThgxldkUVcyqqOHjocIqKinaPO6miit+feDK/ffVFXtm4fp95jxw1hi+96QimDx/Z\nZdshIiIiIiIiXSfTIMYq4GIzOxl4HGgB3gLMBu4xsxviE7r72e0tyMyOAK4GZgKLgfPd/ekU051A\nqKpyCLAMuNjdH8kwvVKAtjc38eTaGh6pqWZeXS27Wlszmm/G8JHMrqhidkUVEwcPaXfaN48s57rZ\n72Lx5o08s24tO1qaGdy3lGPHVDBlyNCu2AwRERERERHJkUyDGEOB26K/h0f/rwJujv6Of+5ut8EB\nMysD7gF+AFwPnEUIgkx294aE6cYB/wDOdve7zezjwJ1mNs7dGzNMsxSAjbt28dia1cytrebZdWvb\nreoR14ciDh9VzuyK8ZxUUcXYAQOzXu8hw0ZwyLARnUmyiIiIiIiIHCAZBTHc/bMdTWNmgwkNgLZn\nDtDq7tdGv280s68Ap7F3mxtnAQ+6+93R+m83s0VAx2+40u2tbdixu0eRl9fXZ9TYZklRH44uH8uc\nyipOGDee4WXq/lRERERERKS3ybQkRiYGAF8ALmhnmmnAgqRhHg1PdCRQY2Z/B06MprnY3Zu7KK2S\nZyu2bQmBi5pqFm7emNE8/YtLmDW2gtkVVRw/toJBfUtznEoRERERERHpzroyiJGJgUBD0rAGQgAk\n0Qjg3cAHgY8A5wL/MrOD3X1LzlMp+y0Wi+GbNzG3dhWP1FazYtvWjOYb0reUE8aNZ3ZFFUePGUu/\n4nyfoiLSnpa2Nna1ttK/pITihIZzRURERETyId9viA1A/6RhA4DtScMagXvd/aHo91Vm9jXgeODe\njlZiZiOB5C4mKrNPrmSjNdbGKxvW82hUVWRNw46M5htZ1i80zFlZxZGjxlDSp0+OUyqpKN9IOq2x\nGI/V1vL3Zct5bl09bUBxURFHl5fz4SmTOX7cWPr00oCG8o1I9pRvRLKnfCOyR76DGAuBC5OGGXBL\n0jAHpiQNK2ZPA6IduQi4NOvUSdaa21p5vr6OR2qqeXTNajY17spovsqBg3Z3hTpzxKhe+wLUzSjf\nyD62NTXxzfnP8Fx9/V7DW2Mx5tXVMa+ujlljxnDFsUczoKRXlpxSvhHJnvKNSPaUb0Qi+X7ifBgo\nM7MLgWsIDXiWAw8kTfcn4CkzezdwP/BFoAzItIvVK4Fbk4ZVRuuX/bSrpYX5dWt4pHYVT6ytYXtz\nZk2VTB0ylNkVE5hdUcXBQ4dRpMBFd6N8I3tpaWvjv+fN56X1G9qdbl5dHd+c9zS/ettxvbGKifKN\nSPaUb0Syp3wjEslrEMPdm6LAxDXAFcAS4HR332lmVwExd7/A3V8ys/cBPwVuBxYD703shrWD9WwA\n9nrqNrOmrtyW3mZbUxNPrK1hbm018+pqaWxtzWi+mcNHMqeyipMqqpgwaEiOUyn7Q/lGkt27clWH\nAYy4p9et4+HVNZxSNT7HqepelG9Esqd8I5I95RuRPfJe9tfdXyO0bZE8/Pyk3/8h9FIiB8iGXTt5\nbM1q5tZU82z9WlpjHXeF2ocijhhdzpyKKk4cV8WYAclttopIIYjFYtyxbHlW89yxbFmvC2KIiIiI\nSH51ZRCjEXiwC5cnB0Dtju08WlvNI7XVvLKhno7DFtC3Tx+OKR/H7IoqThhXybCyfjlPp4jk1vpd\nu/DNm7Oa56X1G9jW1MTgUnWHLCIiIiK5kXEQw8zeAxwF9CWpgU13/7a7byZ0iyoFZvnWLcyNAhe+\neWNG8/QvLuH4sRXMrqxi1phKBvXtm+NUikg+bWnqXAnVrU3NCmKIiIiISM5kFMQws18RWsR9Gdia\nNDqTj/XSjcRiMRZt3sgjNaEr1JXbkw9pakNKSzlx3HhmV1RxdPk4yoqLc5xSETlQdmTYYG+yAX17\nZQ8lIiLSRV7fsI07l6zlmbrNbGtuZUjfYo4eO4wPTR3LzJGDD3TyRKQbyPRp8zPAZ9z9zzlMi+RQ\na6yNVzbUh65Qa6tZuzOjNlIZ3a8/J0VdoR4+qpySPn1ynFIROZA27NrFHxct5q7l2bWHATBp8GCG\nqRSGiIh0QlNrGz98dgkPrlq/1/D1rW3cu6Kee1fUc+rE0XzrrVMpLdbzqEhvlmkQow2Yn8uESNdr\nam3lufq1zK2t5rE1q9nU2JjRfOMHDmJO5QROqqhi5vCR9Ol9XSaK9Dpbmpr48+I3+OuSpezKsPeh\nZGdMmayuk0VEJGttsRiXzl/M3Jr2qzXfv7KeptY2Lp91iO43Ir1YpkGMm4CvmtlF7t65p1vJ2Pbm\nZp5Zt4aNu3bRr6SYN40YzcTBmXVPurOlhXl1tcytreaJNTXsaMmsSPhBQ4cxp6KK2RVVTB0yTDcG\nkV5iR3Mzty1Zyq2L32BHS0unlzNp8CDeO2liF6ZMRER6i7mrN3QYwIh7ePUGHqvdyEmVI3OcKhHp\nrjINYowH3g981MxWAHu1+Obux3VtsnqnzY27uHbhK9y3ajkNSS8TR44awznT38SRo8fsM9/Wpkae\nWFPD3Npq5tetobEtszjTm0aM4qQocFE1SHUMRXqTXa2t3Ll0GTf54rSNeA4sKeG9Eycyt7aWup07\n0y6ratBAfnX8cfQvUXsYIiKSvTuXrM16egUxRHqvTJ84X4/+SY7UNezggsf/w+od21OOf2F9HV98\nYh3fOfJYTps4hfU7d/LYmtCjyPP1dbTGOm5ftbioiCNHjWF2RRUnVoynvP+Art4MEenmmtvauGf5\nCm5c5NTv2pVymn7FxXz0oKl86pCDGVpayudmTOO2N5bwj+Ur2JhQLW10v358YMpkPn7QVPVQJCIi\nnbKlsZkX6jNrZD7u2botbGtqYXCpgucivVFGOd/dv5frhPRmLW1tXDLv0bQBjLjWWIzvPz+PW95Y\nyNKtmzPqFqa0Tx+OKR/H7MoqThg7nqFlZV2TaBEpKC1tbTxQXc11CxaxpiF1w759+/Thg5Mn85lp\nhzCyX7/dw4eWlnLezBl8bvo0lm7ZyvbmZoaU9mXKkCFq7ObwwtcAACAASURBVFdERPbLpsbO9Ya1\nqbFZQQyRXiptzjezK4DL3b0h+jstd/92l6esF3lszWre2LIpo2ljwJKtm9udZkBJCcePrWRORRXH\njqlgoL6QivRabbEYj9TUcu2CBazYljpQWlxUxHsnTuDs6dMYOyB9Ca2+ffowbfiwXCVVRER6oeVb\nMusxL1k/9VAi0mu1F76cBZQCDcCpwGYgVWuPmRQIkHbctfyN/V7G0NIyThw3ntkVVRxVPpay4uIu\nSJmIFKpYLMaTa+u45vUFLN6yJeU0RcApVeM5Z/p0JgwelN8EiohIrxWLxXh23RZuWrA666okAGMG\nlDKqv7r0Fumt0gYx3H1Ows9DgSeBe4F73V3tY3ShhZsya4052eh+/ZlTOYHZFVW8eeRoFesWEQCe\nW1fP1a8v4NWN6a8tJ1WM49wZ0zlo6NA8pkxERHqztliMJ2o3cdPC1SzY2H416vZ8YMpY+qgnPZFe\nK9OKZIcD74z+XWpm64H7gH8BD7l7+mbrpUNNGfYmkugL0w/jM9MO1QVcRHZ7beNGrn5tAc/W16ed\n5pjycs6bOYMZI4bnMWUiItKbtbbFeGj1em5aWMOyTlYfiRvVv5QPTt23tz6R3m5nSxuvb9jJjuZW\nBvYtZubI/vQv6ZkfuTNt2HMBsAD4tZmVAscDnwfuJnS3qm4u9sOofv2p6aBRz2SHjypXAENEAFi8\neQvXLljA42vSd1F32MgRnD9zJkeOHpXHlImISG/W3NrGfSvr+dOiGlZvT90jFsDkIf1554TR/GVx\nDZub0n/cG9GvL786YTpDy9Tem0jc+p3N/GnhBu5dvpkdzW27hw/s24fTJg/jv6aPZFT/npVnMm7S\n18wOAk6I/p0ITAJeBh7NScp6kXdUTuSmxZnX0CnvP4DDRo7OYYpEpBCs3LaNaxcs5D+ra9JOY8OG\ncd7M6cwaM4YiBT5FRCQPdrW0cs+yddziNazb2ZR2umnDB/Lp6eM5sXIEfYqKOHXiaP64cDUPrKxn\nV+uel7H+JX1414TRfGbGeMYMUE97InHLtuzi4rmrWL+zZZ9xO5rb+NvijTxSvZVfz57AlKH9Uiyh\nMGUUxDCztcAo4ClC2xhfAp5w9+xb4pF9fHDKQfz5jQW0xjJrI/XDkw9W+xcivVjtjh1cv3AR965c\nRVuaaSYPHsy5M6czp6JCwQsREcmL7U0t3Ll0LX9ZXMumxn1fquIOHzWET8+o5Jgxw/a6R40dWMY3\n3zqVLx42kVc2bGNbUwtDSks4bNRgBvZVd6oiibY2tfLVNAGMROt3tnDJo6u46dSpDCntGZ0/ZHo1\n+Ccwm9DA52ZgA1BvZs+7e7pnaMnQuAGDuPiwt/CLl5/rcNpDR4zi4wdPy0OqRKS7Wb9zFzcucu5e\nvpyWNEHPyoED+fz0abxrQhXFCl6IiEgebG5s5i+L13DHkjVsb05fHeTYscP49PTxHD56SLvLG1Ra\nwnHj1HaTSHvuXrKJdR0EMOLqGlq4e8kmzprRM6oVZ9omxucBzKwKmEMIaJwDjDWzee5+as5S2Et8\ndKpRBPzm1RdobksdF5o1poLLjz6efsWKRIv0JlsaG7l58Rv8bekyGltTPxyO7t+Ps6dN432TJqqk\nloiI5EX9ziZu8xruWlq3V/WPREXA7PEjOGvaeKaNUHfeIl2hLRbjriWbsprn7iWb+NT0kT2iXcVs\n34ZrgTeAKmACMDH6X7rAR6Yab6+cwD0rlvJwzSo2Ne6irLiYN40czYcnH8yhI0apWLhIL7K9uZnb\n3ljCrW8soaEldaR9eFkpnzbjQ1MmU1bcM4oIiohI91a7fRd/WlTDv1aso7ktdcnA4iI4ZcJozppW\nyeSh6gNAZH+0tsVYs6OZFVsbWbG1kUUbd1LX0JzVMtY2NFPf0MKYgYXfyGembWJ8nVAC43igDXgY\n+BvwOXdfmc0KzewI4GpgJrAYON/dn25n+pOBB4HB7r5/fTIVgJH9+vPZaYfy2WmHHuikiMgBsqul\nhb8tXcbNixeztSn1DWpQ37586pCD+dhBUxlQotJZIiKSe8u3NHDzohr+vaqe1jRNufXtU8R7JpXz\nqWmVVA7qOQ0JiuRDY2sb1duaQrBiSyMrt4a/q7c10ZQmYJiNdCWmCk2mT76fAO4Hfgw86e6ZVb5J\nYmZlwD3AD4DrgbOAe8xscqoAhZkNi6YTEenxmlpb+cfyFdzozoZdjSmn6V9czMcOmsqZhxzMkNLS\nPKdQRER6I9+0nT8uWM2jNRtJ9xrVr7gPH5w6ho8fUkG5ehARade2plZWbG1k5dY9gYoVWxtZs6OZ\nLohVpDWsrGeU2s20TYwjumh9c4BWd782+n2jmX0FOA24I8X0VwG3AV/vovWLiHQ7LW1t3LtqFdcv\nXMTahp0ppynt04cPTZnMp80Y0U8PhyIiknsv12/ljwtXM3/t5rTTDOpbzBkHjeNjh4xjWFnhF1MX\n6SqxWIz1u1pYuaWRFQmBipVbm9iwq1NlAvbLEaMHMLSsZ5TezfdWTAMWJA3zaPhezOxMYCih6sk3\ncp80EZH8aovF+M/qGq5bsJBV27ennKa4qIjTJ03k7GnTGDOgf55TKCIivU0sFuPpus3ctKCGl9Zv\nTTvd8LISPnZIBR+eOpZBpT3jxUikM5Lbq1iRULpiR3PXVd/oUwSVg0qZOKSUSUPKaGhu5e9L0gcY\nk33o4J7T40++rzgDgeRqIw3AXq39mNkE4HuENjj6QdqSayIiBScWi/H4mrVcs2ABS7akfkAsAt41\noYpzpk9j/CC15i5dLxaL8UL9Jh5ZXcfGxibKivswc8RQTp04jkF99TVVpLdpi8V4rGYjNy1czaJN\nO9JOV96/lDOtkvdNKadfSc8omi6SicaWNlZF7VWs3LqndEX1tqa0Ddx2RllxERMGlzEpClZMHBr+\nHj+olNLiPT3QtcVirGto4Yna1B/CEr2tYhBzqtrv2riQ5DuI0QAkf0ocAOze82ZWBPwR+B93rzOz\nSdGojLvlMLORwMikwZXZJlakN1G+yb1YLMaz6+q5esECXt+Yvlus2RUVfGHmdKYM6Tk3m56qUPPN\naxs2c8Vzr7Ns694vKvetXMPvXnmDM20SZ8+Y0iO6YZPup1DzTU/V0hbjoer13LxwNcu2pq7SCFA5\nqB9nTavk3RNH07dYXXnnm/JN/iS2V7G7GsiW0F5FV35ZH1zah0lDykKgYsieoMXYgX0zuv/2KSri\nB8eN5/tP1/BI9ba0082pGsx3j6nsUff0fAcxFgIXJg0z4JaE3+OBY4DDzewqoA8hgFFtZu9196cy\nWM9FwKVdkF6R3kT5Jode2bCBq15fwAv169NOM2vMGL4wczrTh/ec4n69QMHlmxfqN/KVx16gsS11\nEdedra38YcFS6hp28e23zlDX3pILBZdveqKm1jbuXbGOPy+qoWZH6sakAaYMHcCnp1fy9vGjKOmj\n68EBpHzThWKxGOt3tkTVPxJLVzSycVdrl66rvH9JCFJEJSomDg5/Dy8r3u97bFlJHy4/bjwv1Tfw\n9yWbeGbNdrY3tzGobx+OHjeIDx00nMNHD+hx9/J8BzEeBsrM7ELgGkLvJOXw/9m77/i2qruP4x9b\ntpU4e+9hAvklIey9d1KgtEA3FCizDRToeFpon7Z0DygtLaWMltlCoYWHUWhJKGFTUiiUAgknhDgh\ne9hZTjxkWc8f5ypWFMmSHFu25O/79cor1tW5V0dX99x7z++ewex4AufcMny3EwDMbAJQDYxxzqUP\nD+/oRuC+pGVjgs8XkdRUbjqB27iRW96Zz8ur16RNs9/QIXxhz2nsO3RoHnMmHaSgys3WSDPffPnN\ntAGMRH9dsoJ9hg7kw1V60LerNjdFqIs006+8jH4V6qpDgZWbYlPfHOWR99dw38KVrK9vSptu6uC+\nfG7qWI4cPaionuAWsIIvN/XNLWxsbCYcKu2QCnw2mltirNra1Bqo2BSMWbGlqUPHqwhtH68ioRtI\n/zAT+lfQp7xzu12VlJSw3/A+7DfcV6FjsVjRBS2S5TWI4ZxrMrOT8QGMHwOLgNOcc/VBq4uYc+7S\nFKvGyKE7iXOuBqhJXGZm6c/SIqJy08GqN2/mtvkLmLtiZdo0UwcN5At7TuOQ4cOL/mJTrAqt3Px9\n6Uo2NkWyTv+n95Zy6sTROj7bIdLSwuylq3jo/WUs2NA69s20wf35+KTxzBg/krLSntkkv9DKTbHY\n0tTMQ4tW88B7K9nYmH5mhP2H9ee8aWM5aPgAlf1upFDLTSwW41+rt/Lge7X8c1Xd9ulDR/Up5/Td\nB/HRSYPoX7HrlfzG5haWJoxXsbQTx6uIByom9Gsdr2Jc3zDloe5RXnpCuc37UMLOubfxA3YmL5+V\nJv1SQKMGiUhBWFG3ld8vWMCTHywjXXx/Uv/+fH7aVI4ePapHXGik+3hiSfqgWirvb6rjM7NfZmC4\nnF5lIXqFgn/xv8tK0y/bIX3rsnBpadEf9xsam/jqC68zf8POA/fOr93M92vf5uHFy/n5kfsxQC0z\npJNtaIjwwHsreXDRarZG0jeTP3zUQM6bOpa9h2o8JukYzS0xfvrqSv5WvWmn91ZtjXDzm2v5y8Ja\nfnHMeHYf2CurbW5uivpuH5sat3cFWbq548er6F8R8oGKYMyKeOuKEVmOVyGdS/MhiYh0gLX19dy5\nwPHokiVEY6kvo2P79OGSaVM5cdxYQroAShdYVpc8QVhmS7ZshfTjhbVLr1BSoKMs5JflGihJEzzp\nykBJU7SFr7zw+g6tL1J5q2Yj//PiG9x87IE9tkWGdK612xq5163k0cVraIymDquXAMeNHcJ5U8cy\neVCflGlE2uuXr69OGcBItL6+mSufWcodM3ZjRB8f1I3FYqyrb95hYM18jVcR7waSr+4u0j4KYoiI\n7IINjY3c4xby0PuL044zMKJ3by6cOoVTJ4xXZUW6VHe5HWuIttAQbYEcurbkqqsCJY8vWZExgBH3\nVs1GnvxgFR+eqHFHpOMsr2vgj++u4Ikla2lO04w+VAIzJwzjnCljmNi/Ms85lJ7g/Y0NPLwo/Uxs\niTY0RvnGS8uo6h8OAhZNbGvu+PEq4i0q4kGL8f06f7wK6RwKYoiItMOWpibufW8RDyx6n23NqfsW\nDwqHOX+KcXrVRMIhXSSl643rV8n82uwq2IWuawIlpSxJmrY2k4cWLVMQQzrE4k3buHvBcv6xbD3p\nhgCoKC3hw1Uj+OyU0Yzqk13zfZH2+L8sAxhx79Y28G5twy595g7jVWzvBhJmbN+KbjNehXQMBTFE\nRHJQ39zMA4ve596F77E5krpy1L+8nM/aHnxy0iR6l+k0K93HaRPH5BTEGNOnN1fuM5nGICBQ3xyl\nIRqlMRqloTlKfTRKQ3OLf52wrLG5xb+ORv06zdG0Y8QUso4IlCzYsJlNjU0MCFd0YM6kJ1lQW8dd\nC5bz/IratGl6l5VyxqSRfGbyaIb21rEmne+VVXWdtu0BieNVDAgzoZ/Gq+hpdHctIpKFxmiUhxdX\nc5dbyIbGxpRpKsvK+PTukzhrj93pV6GbROl+Zk4Yxe/eeZ/axuwGtL9oz0kcPWbELn9uLBajORZL\nCHxEg8BIYuAjGgQFfOAjHihpSEjXkLgs/joIpDREo2nHo+nuNkeaFcSQnMRiMd5Yt5l7Fqxg3pqN\nadP1qyjjk7uP5BN7jGJAWIPISv5sadr1sStGVJbt0KJiQjBmxaBeqsL2dDoCRETa0NzSwuNLl3LH\nAsea+vqUacKlpXxs0m6ca5MZFA7nOYci2assK+Onh+/Llc//m/po2zeYZ04ay4fGj+qQzy0pKaG8\npITyilL60XkVqUhLYnCjJSnwkSEokmZZY0KLk84KlPQt1+2YZCcWi/HK6o3ctWA5/12ffsTdQeFy\nzrLRnDFppPr8S5foUx6iLpJbG7xjx/bjqDH9gtYVYSrLNY6YpKarpohICtFYjKeWLed38xewfGvq\nPu6hkhJOr5rI56YYw3v3zm8GRdpp76EDufm4g/jpv+fzbooBKPuVl3HOlCrOsYkFNzJ7eWlppwdK\nmltau9UkB0rqm6Nc+/p81jdk19IFYPcBfRmkVhiSQUssxrPLa7h7wQoWbkw/7sqIygrOtjGcVjWc\nXmUKXkjXOWhEHx6vTt9KKFl5aQlfO3CUWllIVnSUiIgkiMViPLdyFbfOn8/izamfcpUCJ08Yz0VT\npzC6j6akk8IzZVB/7jzhEN6p3cTc5WuobWgiHCpl+pCBnDRupCo/bSgrLaVfG4GSVdvq+eV/XNbb\nO3PSuI7KmhSh5pYW5nywnnsWrGDpltStAQHG9e3FuVPHMHP8MMpDenotXe/MPQblFMQ4blx/BTAk\nazpSRETwwYt5a9Zyy/z5LNiQ/qJ7wpgxXDxtClX9++cxdyIdr6SkhOlDBjJ9yMCuzkpR+UjVGB5d\nvJzFWcxSMnlgP06dODoPuZJC0xht4YnqtfzRrWDV1tTjMAHsPqCS86aO5bixQwiVFlbLKSluUwb3\nZuaEAcxeuilj2n7lpVw0fVgeciXFQkEMEenx3li/nlvemc9/1tekTXPEyBF8fs9p2EBV+EQkvd5l\nZdxw1AF86YV/txnI2GNAP35x5P6afll2sC0S5ZHFq/mTW8n6hvSz3kwf0pfzpo7liFGDCq7bl/Qc\n3zh4FI3RFp5dnn78lgEVIa47ehxj+6lbnWRPQQwR6bEWbNjALe/M55U1a9OmOWDYUL6w5zT2HjIk\njzkTkUI2vLIXt59wCA8vXs7D7y9nWd227e9N6FfJmZPG8dHdxtJLAQwJbG5q5sH3VvHAe6vY3NSc\nNt0BwwfwualjOWB4fwUvpNurCJXywyPGMnfZZh56bwNvrms9Fw4Mhzhtt4F8fPJghvXWzDmSGwUx\nRKTHWbx5M7e+M59nV65Km2bPwYOYtec0Dho+PI85E5Fi0busjLMmT+Qze0xg1bYG6iIR+paXM6qy\nlyqfsl1tQxP3L1zFQ4tWs605/YxBR44exHlTxzJ9SL885k5k15WWlHDi+AGcOH4ANfXN1DY0Ew6V\nMLpvBWXqAiXtpCCGiBS81du28Uj1Ep5ZsYLaxkbCoRB7DR7MmbtVceCwYdsrDMvq6vj9gneZ/cEy\n0k2SuPuA/nxh2jSOHDVSFQ0R2WUlJSWM7tMb0AxG0mrNtkbufXcFj1avpSmaehrKEuCEcUM4b+pY\ndh+oQaSl8A3pXcaQ3qp+yq7TUSQiBe1P7y3ixrfeJhpLDEtEmLtiJXNXrGT/YUP5yt578Zf3q3l8\n6dKkdK3G9+3LJdOmcsLYMZQqeCEiIp1g2ZZ67nl3BU8uXUdzS+rrUaikhA9NGMa5U8cwvp+CXyIi\nyRTEEJGCde/C9/j1W2+3meb1des55+ln0ra8GFVZyYVTp3Dy+HGUlWpaOhER6XiLNm7lngUreHr5\netLELqgIlfKRquGcbWMY2Sec3wyKiBQQBTFEpCCt3LqVm95+J6u0qe4Xh/QKc/6UKXx04gQqNLie\niIhkqaE5yuvrNlPb0EQ4FGLa4L6M6dsrZdp3arZw94LlvLByQ9rtVZaV8rHdR/HpyaMY3EszNIiI\nZKIghogUpIerl6TtGtKW/hXlnDt5Mp+YtBu9ynQKFBGR7NQ1NXP3guU8Vr12pxlEDhk5kPOnjWWf\nof2JxWK8vm4zd81fzmtrN6XdXv+KMj65xyg+scco+lfoeiQiki2dMUWkIM1dviLndU4ZP56v7rs3\nfcs1lZeIiGSvtqGJy599h8Wb61O+P2/1Rl5dvZFPTR7FWzV1vF2zJe22hvQq5zOTR3PGpJFUlqsl\noIhIrhTEEJGCVNPQkPM6h44crgCGiIjkpCUW46qX3k0bwNieDvjTwvRTd4+sDHPOlDGcWjWccEhj\nMImItFfegxhmth9wC7AnsBCY5ZyblyLdxcDXgOGAA77qnHsxn3kVke6rIhSiPhrNaZ1wqZ54iYhI\nbl5ZvZG3a+ravf74fr05d+oYZo4fqgGkRUQ6QF7PpGYWBh4DbgcGADcCj5lZZVK6Y4EfAR9zzg0E\nbgL+amaD8plfEem+9hyc2+mgFJg6aGDnZEZERIrWI++vbtd6ewzsw48Om8x9M/fl1InDFcAQEekg\n+T6bHgdEnXO3Oeeizrk7gTXAKUnpxgLXOufeAnDO3QNE8a03REQ4s6oqp/RHjBrJiMrKzAlFREQS\nvFObeyuMc6aM5u6T9ub4cUMJlZZ0Qq5ERHqufHcnmQLMT1rmguWtC5z7Y+JrMzsC6JtiXRHpoQ4f\nNZJpgwYxf0P6aeviQiUlfG6K5SFXIiJSbBqjLTmvU9W/kpISBS9ERDpDvlti9AG2JS3bBqR9PGpm\n04AHgW8752o7MW8iUkBCJSVcd9ihTOzXL2O6aw46gOmDB+cpZyIiUkyG9KrIyzoiIpKdfLfE2Ab0\nTlpWCaRsp2dmM4D7geucc9dl+yFmNgQYkrR4TA75FOlxCrHcDO3di98fezR3vuv465KlbI5Etr9X\nAhw6YgQXTjX2GpL8tUQ6RiGWG5GuVmjl5vixQ7hrwfKs0w8Kl7PvsP6dmCPpiQqt3Ih0pnwHMRYA\nlyUtM+De5IRmdj7wS+AS59yfc/ycy4Fr2pVDkZ6rIMtNv4oKrth7Ly7Zcxr/XruO2sZGwqEQ0wcP\nYnSfPl2dPSl+BVluRLpYQZWb0yeN4A/vriAai2WV/qO7jaBCU6hKxyuociPSmfIdxJgLhM3sMuBW\n4Fz8FKqzExOZ2Qn4GUlOcs691I7PuRG4L2nZmODzRSS1gi43vUIhjhg1squzIT1PQZcbkS5SUOVm\nRGWYy/eZwA3/WZIx7R4D+/DZKXo4Lp2ioMqNSGfKaxDDOddkZifjAxg/BhYBpznn6s3sZiDmnLsU\n+DpQDvzdzMC3DI8BH3fOzcnic2qAmsRlZtbUoV9GpMio3IjkTuVGJHeFWG4+NXk0AL/571KaW1K3\nyNh3WH9+crjRpzyUz6xJD1GI5Uaks+S7JQbOubeBI1Isn5Xw98y8ZkpEREREpA2fmjya48YO4dHF\na5i7vIbahgjhUCnTh/Tl9EkjOXD4AEo1I4mISKfLexBDRERERKQQDa8Mc/H08Vw8fXxXZ0VEpMfS\nqEMiIiIiIiIiUhAUxBARERERERGRgqAghoiIiIiIiIgUBAUxRERERERERKQgKIghIiIiIiIiIgVB\nQQwRERERERERKQgKYoiIiIiIiIhIQVAQQ0REREREREQKgoIYIiIiIiIiIlIQFMQQERERERERkYKg\nIIaIiIiIiIiIFAQFMURERERERESkICiIISIiIiIiIiIFQUEMERERERERESkICmKIiIiIiIiISEFQ\nEENERERERERECoKCGCIiIiIiIiJSEBTEEBEREREREZGCUJbvDzSz/YBbgD2BhcAs59y8FOk+A/wQ\nGA48A1zknFubz7yKiIiIiIiISPeR15YYZhYGHgNuBwYANwKPmVllUrq9gZuBTwFDgTXAnfnMq4iI\niIiIiIh0L/nuTnIcEHXO3eacizrn7sQHKE5JSncW8Ihz7jXnXCNwFfAhMxuW5/yKiIiIiIiISDeR\n7yDGFGB+0jIXLE+bzjlXC9QC1qm5ExEREREREZFuK99BjD7AtqRl24DKdqYTERERERERkR4i3wN7\nbgN6Jy2rBOramS4lMxsCDElaPA5g9erVWWVUpLs64YQTJgLLnXPNHbldlRspZio3IrlTuRHJncqN\nSO5yLTf5DmIsAC5LWmbAvSnSbe86YmZDgUHB8mxcDlyT6o2zzz47y02IdFvVQBWwpIO3q3IjxUzl\nRiR3KjciuVO5EcldTuUm30GMuUDYzC4DbgXOxU+hOjsp3Z+AZ83sDuB14CfA35xzG7L8nBuB+5KW\nVQDj8WNwRNuX/byrwu+z4/E/rHSsQt6/yzthmyo3ko1C3r8qN+kV8u9aCAp5/6rcpFfIv2shKOT9\nq3KTXiH/roWiUPdx1uWmJBaLdWZGdmJm0/EBjOnAIuALzrlXzexmIOacuzRI93HgR8AI4AXgfOfc\n+rxmtouZ2WT8Scmccwu7Oj/FRvu3OOl37Vzav8VJv2vn0v4tTvpdO5f2b3HS79r5esI+zndLDJxz\nbwNHpFg+K+n1g8CD+cqXiIiIiIiIiHRv+Z6dRERERERERESkXRTEEBEREREREZGCoCBG91YDfC/4\nXzqe9m9x0u/aubR/i5N+186l/Vuc9Lt2Lu3f4qTftfMV/T7O+8CeIiIiIiIiIiLtoZYYIiIiIiIi\nIlIQFMQQERERERERkYKgIIaIiIiIiIiIFAQFMURERERERESkICiIISIiIiIiIiIFQUEMERERERER\nESkICmKIiIiIiIiISEFQEENERERERERECoKCGCIiIiIiIiJSEMq6OgMdxcz2BgY6557v6ry0l5kN\nAa4BPgKMAJYDDwE/dc5tTEjXAnzIOTcnxTaqgZ84527L4vOeAf7pnPtmB32FDmdm5cBXgbOB3YD1\nwF+B7zrn1gdprgFmOucOD16fif9eq3L8rGpgQpq3Y8Bxwb8POecOa8fXaRcziwAnFPKxnagnldUU\n650XpBnVSfn6HRByzl3QjnXPA+4EXnPOHZzi/ZuAWcDnnHP3dEBe7wTCzrmzdnVbhajQy0FwHUoU\nAT4AbnPOXRekafM3TnzfzL6LP4+369xqZk8BLzjnvp9F2qyvfcH1Je05P/n6k2OenwGOSfHWYufc\n7kGag4EbgH2BJcA3nHOP5vpZPZ3KW+fblXtKM5sI/Bg4CegLvA/cDVzvnEv+7hLoCcd1O7c7EZju\nnHvczCYA1cAU59zCdmc2/WedDfzQOVeV4r1053jw9Yrz23M/lVjW2ir3Cfd1MaAEiOL37++ccz9N\nSJe2XtmdFVNLjEeAKV2difYys5HAv4B9gPOBycClwNHAP81sWBdmr0uYWRnwD3wA45vAnsC5wEHA\nM2bWN0h6HXBKsM544EGgXzs+8kBgZPDveuDf+ArqxtxlRQAAIABJREFUSGAU8M8gXawd25ZWPb2s\ndufjJwLsb2ajU7x3OtCRN5NXAJ/vwO0VmoIuB4FP03rOnISvhPw4uKnLRuIxEKP7lo228rX9+tMO\nZ9C6/0YC+wN1+OsPZjYGmAPMA6YDdwAPmJm18/N6MpW3zncG8MNcVzKzXsCzwDbgBPzv9D3gf4Cf\npl9T0HGdzh1AYmC5s68t6bafeI7/ErCWHesVD7Tz83Ipa2sT8rAb8BXgG2Z2Tjs/u9sompYY+AhT\nIfsNsBI43jkXDZYtM7PngVeAXwKf7arMdZGv4k/OU5xzG4JlS8zsZGAx/qnwdc65bfiLH/jAXLtO\nVs65mvjfZlYHRJxz6xLT6N6xQ6isdl+1wBp8wOK38YVmdhhQj78Ydgjn3JaO2laBKvRyALDROZd4\nTNxpZp8EPgbcm2nlYjgGkq4/ua67Q6stM7sNeNk5d3Ow6ApgoXPuy8Hrn5vZScBhgGtnlnuqHl/e\nOltbrRAzOBEY4py7KGHZUjMbDFwLfH2XM1e8dFynlrxfumQ/JbWi3wS0JNcrdnW7WUj+zGVmdh/w\nKeAPu5qXrlQUQYygWc0E4GYzO9Q5d4GZTQF+BRwJrMYXhO8755qDdc7DR3n3wN+czwEucs5tCd77\nAvBnfAuAEPAz4BngNmD34O+zUt2EBU17zkuR1RhQ5Zz7ICn9MHyl4SMJlSIAnHONZvYj4F4z+2KK\nm56jgCeBLznnfpf0Xl/gF8BpwBBgBfBz59xNCclGmtkjwAx8BeV/nXP3ButXAN8GzgGG41siXOmc\nezthvz8Z7OMT8IGFc4CTgS/jn9r+2Dn3qyD9SHyz2BPxLSWqgW855x5Msa/AP+W+PSGAEd8ntWZ2\nIr5pbXJz3sXBfl5gZrPwUfwrnXPbC6qZvQrc65y7Ic3nZlJuZtcH+SPI49eCbe/UrMvMVgFXOefu\nCd7fAgwAzsTf/P4y3qzLzOLH2ueAZuB/Ez84aJ3yE/x+DgMvAlc456qD91uAH+CP32rn3KHt/I6d\noieVVfxvXI0vQ18BngaeSNreKcB38U9Zo/jf80Ln3EozOwa4H/hGkGY4MBc4Lx5wC9a/FqgCHscf\nM40J25+BPx6mA6vwQb9bU3zfxO/9MD7K/9uE5R/Dt3A6N2HbIfwTk0/jnyisA+5wzn07Ic33gUvw\nx+qd+CbxdyWUhe1lxcw+HuyrPfAVtKsKrWljtgq9HGTQDDQlvO5nZnfhj6E6/DH4i4TPbasZbMrv\nG7z/OfzxMhzf7DyUtP75+LIzBngb+KZz7ukUn3MNPli+BTgLH8T7oXPuzoRkbZ3zd+hukinf6QTX\n8pOBvRMWH4//Tbdzzs1MWu8qfEuwQfjWg19xzr0RvFeNf9J3Fv432Qt/bfmfYL8sBL7jnHukrbwV\nOpU3X96Cz74SuAwYB/wX+FpiV4QMx9Mzwfc6AN/tYz3++Lkr4f1/4q9XbwDznXOfCN77HnAxvol/\nbdJ3aAF6m9mxzrlnE5b/AX/djOdthybvZjYT+LtzrjTh/fPwT7ynAe8ClzjnXg3en0URHfs96bhu\n67gN9sPb+GOyPzAb34XjaDM7lNbzdnxbhm/tdiTQC5gPfNk591zwfqrj6GLn3GvB+3sAtwKHBOs+\nnsP32klwDTkQf590IP6e6UnaqL/Zrg8HsLWN/KStq9nO3VPi7nTOXWhm/YJ1z8D/hk/h66frrLVb\nT+I98WeAG/Hnq774B4GXO+fmZ/MliqU7yZn4PulfB640szD+AHgTf0NwAfBxgqY3ZnYE/gD8Ab4g\nfxI4Fl9A4vbDd1s4FF8R/jG+EH8RmIlvpvSFNPm5gh2biMb/jQKWpUh/AP5gmJdmey8A5UG67cz3\nhXsUf3P2uxTr/RJfaTgFMOAu4IagiWrcZ4G/4wvqQ8DtZjYoeO8m/M3PhfhmriuAOdbajQPgW/iK\n1l7ARvxBORU4Av/E+udmFu///wd8gTgK3zXkOeC24PfaQdC8cDLwaqod4px7zQVjYiQ5GL8vjwTu\nwVe8PpWw3T2CffKnVNvN0gFAb/zxcRnwFTM7NYf1Pw8swh+b1+Obze0ZvPc9fKXwk/jA0vnsWE5/\njD9WT8cfmyvxXWsS9+En8V0bEp9qdBc9sazOCPL37cSE5vtsPoyvgE0BPoQPRnwnIdkQ/D75KH48\nloOAq4P1p+Kbkt6LP6bfwV8Q4ts/Gn9x/TO+68uPgF8EwYK2PAwcY2b9E5adgT8/JF60rsb/Vp/G\n39x8D/hmcNOAmV2NP9YvwJ8PDH9c7sTMjsOXyd/jAy4PAA+b2dgMeS1UhV4OdmJm5Wb2ieCzEisG\np+CDy3sBP8dfE6Zn2Fab3zcIYt8WfMcD8OfIYxPWPwV/8/314HPvAf6acJ5NdgZQEWzrp8CtQQUp\nLtM5P9ZGvo9hx98pnW8CDzjnEltYTAI2mdmdZrbazOYl5svMLsVXDC/AX6Ofw18Phids4wL8jfDH\n8WXwV/iHDHsAfwT+ZGZDs8hfIVN58+v8L/6e7argez8H/N3MxgXvZ3M8XY2/rkzDXytuNt9iYjvn\nXBP+vvF0MzvRzPYJ1rs4RQADfLfhd4C5ZvYvM/uRmR0PNDrnFmXYFcktb3+AD17ujQ9M/jb4bvtR\nfMd+jziuMx23gQvx9xsfCfLxT3wd5MwUH/MYPlh9AP44/wC/XxIlH0c3x/OHrzOtD9a/Fl8h31Wn\n4n+7w/H1qGzqb+0SnA8+jb8uptJWXe1+Wn/TkfhjoR74dbDu7fgg4XH4IHwf/DiGiRLvib+Iv/c9\nBX/vV0MOrUOKoiWGc26DmUWBLUE08YLg73gTtPeDKN5jZvYN/A6/0DkXf8KxzMzm4H+suDLgUufc\nRjO7keDGxjn3ImwfRGxamvxswR/02YpfADakeT++PPFkuxs+GnZ9vKVDCi8ANzrn/hvk+cf4wQin\n4AMSAI/Fn8yaf2r6ZWBPM3sL/8Tm9PjTKzO7ED/Y0ufwJweAfyS03LgXH1H7gnNuq5ldh6/YTMY/\nBX40+LwPgvTX4SvaY4PtJooHUjal+W7pxJtM1TjnGoI8zTazQUGLjk8Dzzrn1uS43eTPuMw5F8Mf\nW1/Hn/ifaHu17Zxz7gfB39cG6x+Ev4hfjG8NMxe2P010wd+9gMuBI51z/w6WzQKW4qOY9wXbvDXp\nRrjb6GFlNX7z9Uvn3OIgL4ktY8rwrYRuCV5/YGZ/IaEyhn8ScqVz7s1g/T/ijxXwNyivOud+Erz+\nflLF6wp8ebs+eL0oeAJxNT64l5Jz7r9mthz4MHBfcPNX5px71XbsTvUWfpDP+Fgxt5nZt/G/zSv4\ni9N3nXN/C/J+Dv5mIZVZwEPOuRuD1z81s974pypFpwjKQdzD1jowW2Wwjeucc/cnpHnDtQ62eX1w\nQ7ov/slZOpm+7yXAX5xztwOY2eX4m8C4q4CfJTxlvcnMDgeuDNZNth5fwYoAzsyOxN+czQ7ez/ac\nnyrfT7Hj77QTM9sdf2N3QNJb/fCViJ/hn26dBjxuZgcE1/Wr8E/K40+rv2u+u8lFwXoAf0o4f5yO\nr/Qtc84tw19/XqeNp3LFQOVte3m7En9Ofjh4/+tBsPtK/NP5bI6nf8QfmpnZt/D3JHvjx7RI/I6v\nBPvl1/jj64/OuZT3SM65pqCC/XX8Q6er8RXI5WZ2gXPuH9nvIn6V0FLjOuARMyvBt1goqmO/Bx3X\nmY5bgKfiLSmCfDYBW4PvMSBheSU+KHOba23V9xt8PSHkWlvYpjuOZuAr7xcG679rZvuS8ACpnTa7\nHVtMZVN/y9YIM9uMfwhVhm/x8QrwtzTp09bVnHPvE3QrDu4nr8VfG980s0n4usgI1zrxwmeBmuD6\nG8934j3xLPxx+UHQWuNSchjjpSiCGClMBaaYWWJhKsE/IZ3onHvdzOqCG+5p+AI8FfhLQvoNLui6\n4ZyrD27eqxPer8cfCDsxs5tJ3Sc+Bkxzzi1PWh6PTI8i9cEZj7wltjz4ZfB90jbPcr7J9mlBRdjw\nN10xdmx2+35C+k3B9+yNDzyU4gcwjL8fMd8VI/EElhgl3wasd85tDdI3BNuL76dbgE8EN4CGj4CS\nlJ+4+PgUg1K8lzXn3HNmthYfjb0dH8S4dle2CSwJbmbjNuL3WbaSR0fegm+uPBQYhm+GCYBz7r3g\n5AP+qVwYeDapMhlvtRKXeJx2d8VaVmsSlqX8PZxzi8xsW1Ae9sJ/r72B15KSvpfw92b8viFI/3pS\n2ldprfhPxUfvE72EDy5k8jC+tc99+LLzfyny/5iZHWtmP8NfdPYFRgMh87O3jGbH80etmaUbGXwa\nPiibuP1rsshnsSi0chA3C98FKgY0AKuTzo2wc4B6ExnOl2m+7zRau1bscLw456Jm9kbCJqYBB5mf\n8SSuHH/jlsq/ggBG3Kv4G+S4rM75Wf5OqXwS3/T+P0nLm4HZrnWU/jfjARYz+xq+afXd5rsPxFWw\n4zljccLfs/FdBP5tZvPxT8hud87VZ8hfselx5c18V8ihJJyTAy8B08ysD9kdT9vP4UHFGVqvScm+\nha/UDMU/lU3LOVeHb4X4HTOrwnet+hK+8rib23HMhLYkXy/B13V6wrFfdMd1puM24fVisuCc22Zm\nvwU+a2YHsnNdJB7ESHccTcV31U7cx6+y60GMHe4Ts6y/ZWs9vmVNSbD+aHzZfNHMDnRBV6MEGetq\nwfni/4A/u6A7Gf4+sARYHAR8SFjPaL1nTvyut+KvfyvN7GV8AOWObL9YsQYxyvCtEC5k58FclgWR\n5cfwzbDn4kcX/wo7NtuPsLNsR+b/drDNVFamWPZqsO2D8ZWHZAcH+UmssNyNHxPiejP7q0sxyIuZ\n3Y1vynoP/qB4hZ2DHtHk9fD7rCFN/kPsWIiS91PKfRQc0HPw/ZfvD/5eRZqbyiAy/1/8d38oxfa+\nhx94M9XovMkX9fuAT5rZPHxz/Z0qZDlKt89SfTbsXM6aUqQpSVg3+ZiN7+P4do5l55YAib9/IV2U\ni7msxmfISfl7mNle+Avx34Hn8c1eT2PHlhiw8/GSeKylO1YgdRkOkd15//+Av5lvPngGKWYRCcrg\npfhzy/34G874k5B4PrLtspiqTPQkhVYO4lbHn6i0oa3zZUpZfN9Mx34Z/gndk0lpGkkt+SYu8WYW\nsvwOWf5OqZxM6uvSSnx/7ETv4puCx8vx2fhWUYnqEv7efv4JKmyHB0+9T8V3U7vM/FgEyQHRYtYT\ny1ume7psj6d09y+pjMU/mCnFd2l8MVUiM7sIqIs/eXd+jK/fmm+ZuBzfPThV+Uh1LUuZvx5y7Bfj\ncZ1tXSSr+96g8j0PH5h4BH9c9WbnekZb9+ltXXvaa4f8Z1l/y1Y0KFNx75mZw/8mJ+HvQeOfm21d\n7a4gz4kPxcqCZfuw8z5aR2tL5sRr0gLzXavjXUq+BnzezPaPPxBvSzEFMRIrjwvw/cCWx5+umB8k\n7zJ8lPByfNO2i+MrmB8rIatIXiZBM5pU4zWkS18TnKy/FwQktt9QWevgmg+6HQe4fAjffO98fMuC\nHZrImu+jeA6+68HLwbJ41DKbUXrfx9/YHUrQnynIy4EE07/laD985Wysc25lsL34tHTp8nMPcLWZ\n/cwl9KM0P8bGF0ndoiLVCeZefDeZs4EnXOeOiN+EL/wAmB9fJKvWJMFxsAo/WFB8AKEJ+HERwLd6\nacY31Yp3JwnhxxL4LUnNObuxnlBWa80PcJQqqBV3MTDPOZc4ZsuXyX4U7bfwF6BE++O7F4Gv7CQP\n7HoEO7cESuVlfMuqzwODnXMvpUjzZWCWa+1ONhA/dViJc26z+S4pBxCMa2O+SeceaT5vIf4csZ35\n2V5ud87dnUV+C1HBloM8yPR938KfJ+PvleBbAsUrXwvwTx4XJ6T5Ef5mLN4VMtG+Sa8Pxvcr7+h8\n7yQ4hx+Abyqc7GV27mKyJ7AgaDm5GhjjnHs0YXu/ww+m9uek9TA/zsDRzrnv4gOo3zSzd/CVumKp\nyKXTo8tb0GpiFf6akDjW2OH4AQJzPp6y8Dt8RfED/HhrezvnUgUSpwPHm9mfnXOJFeat+KBMvBVG\nEzt2MZyUbUaK+Ngv6uM603HbxqrJ917x1zPxDzP7x7uOmO/CANnde70F7GZmgxPqJcnn6F3SAfW3\nbMTr/8kB9ox1NfOD/x4P7Of8+DdxC/Atw3u7YGDO4L7wHnz3sDqSfhcz+zw+gHkvvtvTNfjr9P74\ngFxWX6IY1OGbUQ3CD9jzHXyzuB/iK4G/x1cYmsxsJT4iuw8+yjcL34w7135GHelK/FPMp4MmsIvw\nN/zfJegXn5S+JOjecSXwhJnd6Vr7poPvolAHfMzMVgAT8SPdRkjTFCxRQpOrG8ysHh+x+wb+AG3P\nlEdr8BejzwSVwOn4LjG0kZ8bgU8Az5vZN/EjEk/D9w+uDt5PFn9isI+ZrXDObXXOvRVEHa+g86e+\nfBXfTO1DQR5/SPqnf6n8Ct+ccgn+wn8DwZMV58cZ+S2+f/fng+1/E38yubyjvkAe9KSy2tYFZyW+\nfB6GLx+fwY9DkfzkNZ3bgCuCytld+BYTR9M6KNLPgXnmm50/HLw3C99iok3OuZiZPYYf3CpdeV8J\nnGpm/8Q39/wR/olNvDz/ErjGzJbiAys/xPd3TRXYuQHfTep5/CBvn8JH8+dmymsBK/Ry0Jkyfd9f\nA8+Z2RX4p0iX4q9xcdfiZwlaiD+GTsU/4Uk3APMkM/sFfvC2k/BN4Nts/t7OfKeyO/66+k6K934B\nvGxm/4N/YvgJ/GBr8TJ8LT6guhZfEbsIH6xPN/NWI/CtIP0TQd4msHMXtmKk8uaPl+8E94Rv4R9+\nxWesib+fy/GUlpldht9nn8AHI84Cvo8fdyPZDcHn/NXMrsW3Mp6Eb031bxeMx4C/v/qi+Va64/H3\ndNkq1mO/JxzXmY7bVOqA3c13R4HWe7GV+PPtJ83sJXwwJD4LYJj09+vx9Z/GdzW5J6jM74E/Djen\nWa894mOLtKv+lkKpmY1IeD0CP8vhGvxsM4narKuZH1T7B/jyXJ+w3ahzbqGZ/RX4o/kZ+jbiW+YY\nfp+NYud74iHAD8xsHX78v7PxD9C69+wkZnZw8OOke/9iM1toZhvNj8h9ZIZN/gbfhOp25+dtn4Hf\nOf/C9/eag3/yCb6ysRzftG0u/gT7RZKeBCZp64nqLnN+Dt/D8JHF2/A/5q1BHg9xO87EEUtY70l8\nH6JbzE+/GQuWR/AHw6n4StH1+IL6Iq1Rw1TfKXHZVcG278U3vxqGj2SvTZE2nXh+VuAHSrs8yM9V\n+EjjEtJEMYPvcGKQh5/jb/JuxD8VOCn4nZPXqcVX6O6h9fcG31qhkewH38xF4n74A777ygP4k8NL\nZH6il/h7Xos/lm/Ht6yIN+WK+zr+ZvZu/E1GFX5frEneVjfWI8tqCr/GdyP5G758jcHf8E02P/hU\npnwswTdD/xD+GDsO/+Qr/v4bwfbOxV/4v4YfJPT32XxPfOCjLzsOApr4fc7H94F8G1/m7sYf+/Hy\nfEOw7A/4cuDwwYydmmk6514JtvfVYHtnAh92fgC2YlXQ5WAXth/LYt3v0sb3DY6XT+ODF//B35Rt\n797l/ICeV+KP+Xfw155znHNPpcn7PPwT3v/gn1p+Kv4ErI3vkHO+0xgRbG+nWRuCMnwaPvj+Dv7G\n8SPOuXjA41f4m9uf09oy67SE92NJ23sJXwG4An8dvgG42jn3d4pfTy5vcb/G/+Y34I/1w4ATXet0\nhjkdTwnLYonvm5814kf4aRnXBs3CrwS+bGb7J28guJYdhh+/4z78teKu4P/EwOMX8RXQN/GVsB2m\noE+Tv/hnFOux3xOO60zHbapt3IoPRM9OTBNcO67B14nm4+tJM/H1g4x1o6D1xsnBsnn4hzO7Os7e\nDoK6z2dpu/6WLp+pDMMHb1biA1bxwMWMhHpUtnW1s/EP6x7AT+Eb3258zJLz8OP6PYZvSdgSfE5T\n4uck+Bn+HvGO4PPOwN/71ZCFklgs/3Ue8yPoXo8f02B4ivePxTddOyF4in4u/uS6W1KXCpGsmNmv\n8E2cUo1MLyIdLGiN9O8g6EMQZK0BTk14sibSpYLmq8c459rT8kJERES6QN5bYgTdAi4nmLc4jbHA\ntc65t8CP0opv3tLmNGUiyczsIDO7GN/sLHkeaBHpPBfjm/TvGfS7/TU+iDGva7MlIiIiIoWsK7qT\n3O6c2482+qE55/7onPt5/LX50YT7kmUfGZEEJ+CbR14fHwxTRPLiUnzz4Ofx5/uJ+GaFHTGSt4iI\niIj0UF3SnQS2j5j7l1TdSZLSTcMPpPIL1zpXuoiIiIiIiIj0MN16dhIzm4Gfp/a6XAIYZjaE1mkp\n40L4UV3fTpwWUUQ8lRuR3KnciORO5UYkdyo3Iq26bRDDzM7HT+tyiXMu1/mpLyf1nOs8/fTTu5o1\nka7WUfNEJ1O5kWKmciOSO5Ubkdyp3IjkLqdy0y2DGGZ2AnATfurIl9qxiRvx0zQlGoOfUkhEUlO5\nEcmdyo1I7lRuRHKnciMS6DZBDDO7GYg55y4Fvg6UA383M/CRmRjwcefcnEzbCuaX3WGOWTNrSpNc\nRFC5EWkPlRuR3KnciORO5UakVZcFMZxzzwHDE17PSvh7ZpdkSkRERERERES6ra6YYlVERERERERE\nJGcKYoiIiIiIiIhIQVAQQ0REREREREQKgoIYIiIiIiIiIlIQFMQQERERERERkYKgIIaIiIiIiIiI\nFAQFMURERERERESkICiIISIiIiIiIiIFQUEMERERERERESkICmKIiIiIiIiISEFQEENERERERERE\nCoKCGCIiIiIiIiJSEBTEEBEREREREZGCoCCGiIiIiIiIiBQEBTFEREREREREpCAoiCEiIiIiIiIi\nBUFBDBEREREREREpCApiiIiIiIiIiEhBUBBDRERERERERApCWVd9sJkdDDzsnBuT5v3PAD8EhgPP\nABc559bmMYsiIiIiIiIi0o10SUsMM7sAmA2Up3l/b+Bm4FPAUGANcGfeMigiIiIiIiIi3U7egxhm\n9k3gcnwri3TOAh5xzr3mnGsErgI+ZGbD8pFHEREREREREel+uqIlxu3Ouf2A19pIMwWYH3/hnKsF\nagHr5LyJiIiIiIiISDeV9yCGc25NFsn6ANuSlm0DKjs+RyIiIiIiIiJSCLpsYM8MtgG9k5ZVAnXZ\nrGxmQ4AhSYtTDiAqIp7KjUjuVG5EcqdyI5I7lRuRVt01iLGAhK4jZjYUGBQsz8blwDWdkC+RYqZy\nI5I7lRuR3KnciORO5UYk0F2DGH8CnjWzO4DXgZ8Af3PObchy/RuB+5KWjQHmdlwWRYqOyo1I7lRu\nRHKnciOSO5UbkUC3CWKY2c1AzDl3qXPuTTO7GD+t6gjgBeD8bLflnKsBapK239SR+RUpNio3IrlT\nuRHJncqNSO5UbkRadVkQwzn3HDA84fWspPcfBB7Md75EREREREREpHvqiilWRURERERERERypiCG\niIiIiIiIiBQEBTFEREREREREpCAoiCEiIiIiIiIiBUFBDBEREREREREpCApiiIiIiIiIiEhBUBBD\nRERERERERAqCghgiIiIiIiIiUhAUxBARERERERGRgqAghoiIiIiIiIgUBAUxRERERERERKQgKIgh\nIiIiIiIiIgVBQQwRERERERERKQgKYoiIiIiIiIhIQVAQQ0REREREREQKgoIYIiIiIiIiIlIQFMQQ\nERERERERkYKgIIaIiIiIiIiIFAQFMURERERERESkICiIISIiIiIiIiIFoSzfH2hm+wG3AHsCC4FZ\nzrl5KdJ9A5gF9APeBq50zr2ez7yKiIiIiIiISPeR15YYZhYGHgNuBwYANwKPmVllUrrjgP8BjnPO\nDQIeB/6Sz7xKcVtZF+XxRQ3cP7+eJ95vYM3WaFdnSURERERERDLId0uM44Coc+624PWdZvZl4BTg\nwYR0W4EYUGFmIaAF2JbXnEpRem9DM7e9sY1XVkaIJSwvLYEjxpbzhX37MGFAqMvyJyIiIiIiIunl\ne0yMKcD8pGUuWN66wLl/ATcB7wANwNXA2fnIoBSvV1c1MevJTfwzKYAB0BKDF5ZFuOTJTby1LtIl\n+RMREREREZG25bslRh92blGxDUjuTvJx4BLgAHwg42rgYTOb5pxrzPQhZjYEGJK0eEx7My2Fb3Vd\nlP99vo6GDL1GtkZiXP3sFv542kAG9epZ496q3IjkTuVGJHcqNyK5U7kRaZXvIMY2oHfSskqgLmnZ\n2cCtzrk3gtffN7OLgROBJ7L4nMuBa3Ylo1Jc/vJuA9siye0vUtvUGOPhhQ1csHdl5sTFReVGJHcq\nNyK5U7kRyZ3KjUgg34+aFwCWtMzYuYtJAxBOWhYFmrP8nBuD7Sb+Oz6nnErRiERjPLE4YwOeHTz2\nXgMtseyCHkVE5UYkdyo3IrlTuRHJncqNSCDfLTHmAmEzuwy4FTgXGA7MTkp3P/B7M3sAeAu4Eh9w\neTGbD3HO1QA1icvMrGnXsi6FamVdC3VNuQUk1tfHqK2PMbSypJNy1f2o3IjkTuVGJHcqNyK5U7kR\naZXXlhjOuSbgZOAsfCG8DDjNOVdvZjeb2W+DdI8C/4ufVnUtcCrwIefc1nzmVwrf2q1RHn2voV3r\nNrf0uJYYIiIiIiIi3Vq+W2LgnHsbOCLF8llJr28DbktOJ5JJXVMLzy1rYvbiRt5Y07zTTCTZCJXA\nwB42sKeIiIiIiEh3l/cghkhniERjzFsVYU51Iy8ub6IpwywkmRw1roJeZT2nK4mIiIiIiEghUBBD\nClYsFuOd9c3Mrm5k7tImNjV2XPePj1mvDtuWiIiIiIiIdIysghhmNh5Y5pyLJS0PAfs5517rjMyJ\npPLB5ihPVTcyu7qRlXUtGdMPryzlpIkVLN0c5cXlkYzpPzGlF/uNKO+IrIqIiIiIiEgHyrYlRjUw\nEliXtHx34HmgsiMzJZJsQ0MLTy9pZHZ1EwsFdIPCAAAgAElEQVRqMs+026e8hOPGVzCjKsy+I8oo\nLSkh2hLjpte38ed3Uw/0WVoCn92zNxft07ujsy8iIiIiIiIdIG0Qw8y+AHwneFkCvGVmyY+9+wNv\nd1LepIdraI7x4vIm5lQ3Mm9lhGiG3iKhEjhsTDkzqsIcMaaCcNKYFqHSEq44sA8fs148+l4Dr66K\nsDUSo29FCYeMruCje4QZ2SfUid9IREREREREdkVbLTFuB7bhp2G9A/gxsCnh/RhQB8zttNxJjxNt\nifH6mghzqpt49oNG6jM3umCvYWXMqApz3PiKrGYUGdMvxKX79+mA3IqIiIiIiHS9WDRG/ZoWog0Q\n6gW9R5RSEirOiQrSBjGccxHgHgAzqwZeAsLOua3BMnPOubzkUopaLBZj0YYos6sbeWpJIzX1mQfo\nHNevlJlVYU6qCjOmn1pPiIiIiIhIz9NcH2PtyxHWv9pMZEtrPaq8XwlDDypj+OHllPUurmBGtmNi\nLAfeAP4GXBUse8HMlgGnO+eWdUbmpLit3hrlqWrfXaR6U+Y5UQeGSzhxYpiZVWGmDAlRUlJchVFE\nRERERCRbjbUtvHdnA421Oz8EjmyJsWpuhNr/NLPH+b0ID87cYr1QZBvEuAl4F7g+YZkBtwG/AT7a\nwfmSIrWlqYXnPmhidnUjb6zJ3FckHIKjxlUwsyrMQaPKKStV4EJERERERHq2aGOM9+5KHcBI1Fjr\n0029rDehcHHUpbINYhwB7OucWxtf4JzbYGbfAv7VKTmTohGJxnhlZYTZ1Y28vLyJpgyzopaWwAEj\n/QCdx4yroLK8OAqbiIiIiIhIR1j/ajONNZm74QM01sRY/1ozI44o7+Rc5Ue2QYwNwFTg/aTlE4Gt\nHZkhKQ6xWIy31jUzp7qRuUub2NyUuYBNHhRiRlWYEyeGGVpZPM2dREREREREOkosFmPdvyI5rbNu\nXoThh5cVRZf8bIMYvwN+b2bXAK8Fy/YDrsHPXCICwAeb/ACdc5Y0sqouQ5MLYESfUmZMDHNSVQW7\nDcz2cBQREREREemZIptjWbfCiGusiRHZHKNiQM8JYvwwSPt9YFiwbC3wS+DnnZAvKSC19S38Y2kj\ncxY38m5t5gE6+5aXcNwEP87F3sPLKC2CaKCIiIiIiEg+tDTld73uJqsghnMuhm91cY2ZDQWanHOb\nOzVn0q3VN8d4YZmfWeTVVRGiGQKBZaVw2JhyZlaFOWxMBeEinbNYRERERESkszRvjbHu1dy6ksSF\nKoujDpZ1+30zmwZcDEwHomb2H+AW59ySTsqbdDPNLTFeX+0H6Hx+WRP1mScXYe9hZcyoCnP8hAr6\nhzXOhYiIiIiISK6aNrew5sUI6//VTEs7Yhh9xpVS3qcHBTHM7FTgYeCfwKtACDgKuNzMZjjnXuq8\nLEpXisViLKyNMqe6kX8saaSmIXPfq/H9S5lZFeakqjCj+4bykEsREREREZHi01jbwurnI9S83kws\nc8/9tIYdUjzjD2b7TX4GfNc59+PEhWb2XeAG4KAOzpd0sVV1UZ5a0sic6iaWbMpcWgb1KuHEiWFm\nVoWxwaGiGPVWRERERESkK9SvbWH1cxFq/9sMmedLaFO/3UoZvHfPC2LsBjyYYvm9wNc7LjvSlTY3\ntvDMB36cizfXZu4r0isER4+rYMZuYQ4cWU5ZqQIXIiIiIiIi7bVtRZRVz0XYOD8KaRrBl5bD0IPL\nGHpgGcueaGLLovRRjn67lzLpM70oKaIxCbMNYjwJXABcnbT8dOCpDs2R5FVTNMY/VzQxp7qJl1c0\nEckQ5SstgQNH+gE6jxpXQWV58RQGERERERGRrlC3JMqqZyNsfi99K/hQLxh2aDkjDi+nLBjfYo/z\nerHp3Sjr5jWzeXHUt9oohf67hRh2SBkDpoQoKbKHzdkGMT4AvmRmJwAvAM3AAcCxwGNmdkc8oXPu\ngrY2ZGb7AbcAewILgVnOuXkp0h2F76oyGVgMfMk590yW+ZU2tMRivLWumdmLG5n7QRN1TZnHubDB\nIWZWhTlhYpghvTVAp4iIiIiIyK6IxWJsXhRl9bMR6pakf5pc1gdGHFHOsEPKCfXaMSBRUlrCwGll\nDJxWRiwaI9oEoQqKquVFsmyDGAOAPwV/Dwr+/wC4J/g7vofarA2bWRh4DPgBcDtwLj4IUuWc25aQ\nbhTwKHCBc+4RM/s08JCZjXLONWaZZ0myZFMzs6ubeKq6kdVbM3esGtmnlJOqwsyYWEHVwOLpQyUi\nIiIiItJVYi0xNi7wwYttK9PXy8oHlDDyyHKGHlhGaUXmoERJqISy3h2Z0+4pq5qpc+78TGnMrB9+\nANC2HAdEnXO3Ba/vNLMvA6ew45gb5wJznHOPBJ9/v5m9yy4PadLz1NS38I8ljcyubmRhbeYBOvtW\nlHD8+Apm7hZmr2FllGqAThERERERkV0Wi8aofSvK6ueaaFib/vl/eHAJI48uZ/B+ZZSWqT6WrCMf\nr1cCnwcubSPNFGB+0jIXLE+0P7DCzP4PODpI8yXnXDtmxO15tkVivLCsidnVjby2OkJLht4i5aVw\n+JgKZlRVcNiYCiqKuOmRiIiIiIhIPrU0x6h5vZnVL0Roqk1fOes1ooRRx1QwaHqoqLuD7Kp89xHo\nA2xLWrYNHwBJNBg4GTgD+ARwCfCEme3hnNuU6UPMbAgwJGnxmHbluAus3RrlheURNjS0EA6VMH1Y\nGfsOL2tz2tLmlhivrY4wZ3Ejzy9roiGLOYT3HV7GjKowx46voH9Y41z0dIVebqTzrahpwa2IUt8U\nozJcwpSxIUYN6tnnDpUbkdyp3IjkTuWmMEWbYqx/tZk1L0SIbEkfvKgcW8qoY8sZYMU3CGdnyHcQ\nYxuQ3EunEqhLWtYI/M0593Tw+mYz+xpwBPC3LD7ncuCaXcloV1hVF+U3/97Gi8ubiCYd4xMHhLhw\n794cNyG8fVksFsPVRpld3cg/ljSyoSHzAJ0T+oeYuVsFMyaGGdk31NFfQQpbQZYb6XzVa6I8Oq+J\n6rVJPfrmwe4jS/noIRWMH9ZjzycqNyK5U7kRyZ3KTQFpro+x7pUIa1+O0Jz8CD9B36pSRh1bQb9J\npW0+sJYd5TuIsQC4LGmZAfcmLXPAbknLQrQOIJrJjcB9ScvGAHOzXD/vlmxq5oqnNlObJhCxZFOU\nb79Qx2VbWzhmfAVzqhuZU93IB5szDxMyuFcJJ00MM6MqzOTBIRUQSafgyo10vreWNnPn041E05xq\nFq1u4dePN3DRSWGmjO2RAwCr3IjkTuVGJHcqNwUgsjXG2pcirH0lQksb01H0nxxi1LHl9J3QYx8C\n7ZJ833HOBcJmdhlwK34Az+HA7KR0fwBeNrOTgSeBLwJhIKspVp1zNUBN4jIza9q1rHeexmiMq57Z\nkjaAkeim17dx0+tthPMCvcvg6HEVzKwKs//IcsrULEkyKLRyI51v3aYW7p6bPoARF4nCHU838o2P\nlTKob8/qXqJyI5I7lRuR3KncdG9Nm1pY82KEda82E0s3imMJDNozxMhjyqkcreDFrshrEMM51xQE\nJm4FfgwsAk5zztWb2c1AzDl3qXPuP2b2EeBa4H5gIfDhxGlYi8kzS5tYUbfrE6+UlsBBo8qZWRXm\nqHEV9NZItiKyC557J0Iki/F1ABoj8OKCZk47qKJzMyUiIiLSTTTWtLD6+Qg1bzQTS3fPVApD9ilj\n5DHl9BrWsx72dJa8t/11zr2NH9siefmspNf/wM9SUvT+uqhhl9afMjjEjN3CnDghzODeKhgisuua\nozH+9V5zTuu84iKcekA5pWr5JSIiIkWsfk0Lq59rova/UUjTmL6kDIYeUMaIo8oJ9/CB0DtaRwYx\nGoE5Hbi9HmPRhiwfdSYYFC7hI3v0YkZVmAkD1BxJRDpWzZYYjTlOal3XAJvrYwzsoyCGiIiIFJ+t\ny6OsfjbCxgXp62+lFTDs4HJGHFFGeX8FLzpD1kEMMzsVOAgoJ2mATefcN51zG/HTokqOoi2Zx8JI\nduWBlZxY1asTciMiAtsacz8vARnHzxAREREpJLFYjLolLax+NsLmRemDF6HeMPywcoYfVk5ZpR7o\ndKasghhm9kv8tD5vApuT3m7fna5sN7xPaVazjCTS9Kgi0hnWbGzh+XcizFuYW1cSgFAp9Outi7aI\niIgUvlgsxuaFUVY9F2Hr0vR1tbI+MOLIcoYdUk4orPugfMi2JcbngM855/7YiXnpsWZUhfn9m/VZ\npx/br5RpQ3vkVIYi0glisRgLV7bw7NsR5i/LvXtb3D5VISo0oLCIiIgUsFhLjI3zo6x6NkL9qvTB\ni/IBJYw8qpyhB5ZRWq77n3zKtibcArzSmRnpyU7bvRd/eLuexizrDh+zXpSWqKCIyK6JNMd47f1m\nnns7wqoNu96o7uhp5R2QKxEREZH8i0Vj1P63mdXPRWhYl/6+KDykhJHHlDN4nzJK9fCmS2QbxLgb\n+IqZXe6ca/9jOklpSO9Srjq0L99/qS5j2kNHl3PGZI2FISLtt3lbCy8uaOalBRHq2pgcqaIMhvUv\nYUVt5gDHjH3LqRqhbm4iIiJSWFoiMWpeb2b1CxGa2nio03tkKSOPKWfQ9BAlmomtS2UbxBgLfBT4\npJktAZoS33TOHd6x2ep5ZlSFKSuF6+ZtZUtT6sJzyqQwXz24D2UqNCLSDstrojz7djOvv9/c5gCc\ng/qWcPS0cg61MnpXwOw3Isz5TyTlOmWh/2fvzuPkqOv8j7/6mpncCSEX4Rb4hCQc4RIJkACCiLAq\noi4e7KLigvzQ1fVadcVrcdcDddFFWDxX8FwuFQSFECDcd0LCB8IZIAm5M5NJZvqo3x/faqbT6Z50\nT2Ym0zPv5+ORR6arq7q+XV3fqm996vP9Fpx2WIYTD1YWhoiIiDSOfEfE6gdzrLw7S7a1evBixB5J\nJs/NMMZSJJQNPyDUGsR4Mv4nfejEvZo5ZmoTf3uhgzte6mTtlgItqQQzJ6R5+/4tTB2lu5wiUp9C\nIeLJZXnuWJhl6YruBxDeZ2KSuQdlOGivFKmSYOmphzUx+8AM93kWfyXP5k4Y3gzTdk9x9AEZRrTo\nhC4iIiKNIbc54rV7s7x2T5Z8N8MSjto3yeS5TYzaN6ngxQBTUxDD3b/a1wWRoCWd4PT9Wjh9P3UZ\nEZGe29IZcf/TOe5cnGX1xup3F5IJOHTfFHNnZNhrYvVA6ahhCU4+tImTD+2L0oqIiIj0rWxbxMoF\nWVbdn6XQUX2+MdNSTJ6TYeSeuoE8UFUNYpjZJcA33L09/rsqd/9Cr5dMRETqtqY1PCL1Ps+xJVt9\nvuHNcMy0DMdNTzN2RLL/CigiIiLSjzrXF1hxd5bVD+aIqj1BPgHjZqaYPLeJ4ZPVLhrousvEeBPQ\nBLQDpwLrgUp5NDs+pL2IiPRYFEU8vzI8IvWJF/NE3RyVJ45JMGdmhiP3S9Osx4GJiIjIILVldYEV\nd2ZZ+1iOqNqjKZIw/tA0k+dkaNlVwYtGUTWI4e4nlLycCSwAbgJucneNjyEispPlCxGPPpfnjkVZ\nlq3ufrwLm5pk7swM03ZP6RHNIiIiMmhtXlFg+fxO1i3MV73dnkjDrkekmXxchqaxCl40mloH9jwU\nOCX+d7GZrQZuBv4M3Obu3QyJIiIivWnTloh7nspy1+IcG9qrp12kU3DkfmmOn5Fht110ghYREZHB\na9OyPMvvyLLhqWppF5BsgglHZ5g0O0NmpG7qNKpaB/ZcDCwGvm9mTcBs4CPA9YTHrQ7vsxKKiAgA\nK9YVmP9klgefyZGtfn5m9LAEx05PM3tahpHDdIIWERGRwSmKItqeL7D8jk5an62elZoaBhOPyTDx\nTRnSahs1vFozMTCz/YDj4n/HA3sDjwPz+6RkIiJCFEX4K3nuWJRjycvdRC6A3ccnmTszzax906RT\nOkGLiIjI4BRFERs8z4r5WTa9VD14kR6ZYNKxGSYclSbVrLbRYFFTEMPMVgC7AvcQxsb4OHC3u2/s\nw7KJiAxZnbmIh5bmmL8oy4r11buMJICZe6WYOzPDGybrOeYiIiIyeEWFiHVP5llxR5bNK6oHL5rG\nJph8fIbxh6VJaiDzQafWTIw/AXMJA3yuB9YAq8zsYXfvfjQ5ERGp2YZNBe5ekmPBkiybunmGeXMG\njj4gjHex62iNdyEiIiKDV5SPWPN4jhXzs3Ssrn5zp3nXBFPmZNjlkDQJZaUOWrWOifERADPbAziB\nENA4D5hsZve6+6l9VkIRkSFg2erwlJFHn8uT7yY0vMvIBMfPyHC0pRnWpJOziIiIDF6FbMTqh3Os\nvCtLZzeZqcOmJJkyN8PY6SkSSbWPBruax8SIvQo8A+wB7AnsFf8vIiJ1KhQiFr6UZ/6iLM92kxIJ\nsO+k8IjUg/ZKkdTJWURERAaxfEfEqgeyrLw7R66tevBixJ4heDH6gJS61A4htY6J8VlCBsZsoADc\nDvwe+LC7v1jPCs1sFvBjYAbwNHCBu9/fzfwnAbcCo9y9vZ51iYgMRFs6I+57OsedT2ZZ01r9xJxM\nwKx9w3gXe05I9WMJRURERHpHFEW0vVBg3aIc2baIZBpG7JFi/KFpUi1bBx5y7RGv3ZvltXuz5DdX\n/8xR+yWZMqeJkftoPLChqNZMjLOBvwD/ASxw91xPVmZmzcCNwNeBnwDnADea2T6VAhRmNjaeT0Sk\n4a3eWODOxVnu8xwd2erzDW+G2dMyHDc9zZgRGu9CREREGtOmZXlevK6DzSu3vmmz9rE8r9zSyaTZ\nGaacmCG3KWLlghyr7s9S6Kz+eWMOTDFlToYRe+jmzlBW65gYs3ppfScAeXe/Mn79MzP7JHAa8IcK\n818O/Br4bC+tX0SkX0VRxLMrCsxflGXhS3mi6okXTBqbYO7MDEfsl6YprbsKIiIi0rjaXsjz9M+3\nEFW5cVPohOXzsqxdmKNzfURU7TZ5AnY5OMXk45sYNlk3d6T+MTF21DRgcdk0j6dvxczeD4whdD35\nXN8XTUSk9+TyEY8+FwbrfHlN9+NdTNs9xdyZaaZNVX9OERERaXz5johnr6kewChV7WkjiRSMn5Vm\n0vEZWsYreCFd+juIMQIo7zbSDgwvnWBmewJfJYzB0QJ0c+9SRGTgaNsSsWBJlrsX59i4ufqhK5OC\nI/dPM2dGhsnjdGIWERGRwWPt4zlym3q2bCIDE45IM+nYDE1j1UaSbfV3EKMdGFY2bTjQVnxhZgng\n58AX3X2lme0dv1Xz7UkzGw+ML5s8td7Cigwlqjc7Zvm60GXkoaU5svnq840enuC46WmOmZZhZIuy\nLhqd6o1I/VRvROrXaPVmzSP1D6GYbIKJb8ow8ZgMmZFqI0l1/R3EWAJcWDbNgKtLXu8OvBE41Mwu\nB5KEAMYyMzvd3e+pYT0XARf3QnlFhhLVmzoVogh/Oc8di3I89Uo3kQtgj13DI1IP3SdFOqUT8yCi\neiNSP9Ubkfo1VL3Zsp2utJVMfWsTE4/K9EFpZLDp7yDG7UCzmV0IXEF4OslE4JbiDO6+jNDtBAAz\n2wt4Hpjq7t08aGcrlwHXlE2bGq9fRCpTvalRZy7iwWdyzF+UZeWG6l1GEgk4aK/wiNR9J+kRYIOU\n6o1I/VRvpKooili7rMCqF/Jkt0RkWhJM2CfFLrsP+fPooK83qaYh/ftKHfo1iOHunWb2VkIA4xJg\nKXCGu2+Osy4id/9YhUUj6uhO4u5rgDWl08ysm4f1iIjqzfat31TgrsU57nkqS3tH9fmaM/AmS3P8\njAzjR6kv52CmeiNSP9UbqWbV83mevL2D1lVb3yB45p4soyckmX5SExP2HpqP1my0etOya5JNL9WX\njdGyq4IYUpv+zsTA3RcRBuwsn35BlflfBIbm0UpEBoQXV+WZvyjLo8/lKXQzzPD4UQmOn5Hh6APS\ntOhugoiISM1eWZzj0T92VH0U+cZVBe7/7RYOe3szu03r90sYqdOuh6fZ9FLtMZaWSQmGT9WNH6mN\njgAiIhXkCxELXwyPSH1+Zfd3EvabnGTOzAwz90yRTCp4ISIiUo+2NQUe+3P1AEZRFMGjf+xg9MQk\nI3fRBe9AtsvBaV79W5Zsa20PmZx0bGaodxeSOiiIISJSYnNnxL1P5bhrcZa1bdVPvKkkHLZvmjkz\n0+yxq5LFREREeuq5h7IUuh8f+3WFPLzwcJaZJzf3baFkhySbErzh/c08/dMtFLaTkLHrkWnGz9Jl\nqdROe4uICLB6Y3hE6v3P5OjIVp9vRAvMnpbh2OlpxgzXXSAREZEdkc9FvPxkfY/jXLYox/QTm0jq\naV8D2og9Uth5Lbx4fSftr2yb1ZpshsnHZ5g8R1kYUh8FMURkyIqiiKXLC8x/MsuiF/N0l/A4eVyC\nuTMyHL5fmqa0TrQiIiI9lc9FbHytwIYVBVa/mCdf5/CUuQ7Y0hoxfKzOxwPd8N1STLughfaXC6xb\nlCfbViCZTjBijyTjDk7riSTSIwpiiMig0Lo5YtFLOdo2R2TSCfaemGSvCZUfx5bLRzzybI47nszx\nynaeYz59jxRzZmSwqUP+0W4iIiJ1Kw1YrF8R/m9dXSCq78EV29je+BkycCQSCUbskWLEHup+K71D\nQQwRaWgbNhW44YFOHns+T76sQTR1fJLTDsswc69wqGvdHLFgSZa7l+Ro3Vy99ZNJwVH7p5kzM8Ok\nseoyIiIiUou+CliUS6ageaRuLIgMVQpiiEjDWrWhwA9v2sL6TZUDEq+sKfA/f+3gzQfnad0CDz+b\nI9fNwGFjhic4bkaaYyzDiBY1jkRERKrJZyM2rioLWKwq9EuGxJRpKdIZnadFhioFMUSkIeXyEf9z\na/UARqm/PdH9gGF7Tkgyd2aGQ/dJkdIjUkVERLayTcBieZxhsQMBi1QGRk9KMnZSknRzgmfu6WZU\n7TL7HJ7p+YpFpOEpiCEiDemJF/Ks3NDz1lMiAYfsnWLuzAx7T9R4FyIiItAVsFi/PAQtXu8S0ksB\nizGTk4ydnGLk+ASJkhsHyRT4XdsPZEybk2HcbhpbQWQoUxBDRBrSPV77HZtSLRl407Q0x0/PsMso\njXchIiJDVz4bxrAodgfpk4DFlBQjd9k6YFHJAbObyLQkeGp+J7kKTytJN8OBc5vYe5ayMESGOgUx\nRKQhbe+pIpW88YA0Zx7dRIse5yUiIkNMnwcspsQZFjUELKrZ5/AMexyU5uUnc6x6Pk+uIyLdnGDi\nvimmTk+T1vlbRFAQQ0QaVPmTSGphU1MKYIiIyKBXHrBYvyJP2+qodwIWk0u6hOxAwKKadFOCvWdl\nlHEhIlUpiCEiDWns8ETdY2KMHaEAhoiIDC59FbAYE3cH6cuAhYhITyiIISIN6fD90tz0cO3jYuwy\nMsE+EzUGhoiINC4FLEREFMQQkQZ1tKW59bEsuXxt8x87PU1SDTIREWkQuThgsaGPAhZjJ6cYMzmp\ngIWINBwFMUSkIY0ZnuS9s5u4+s4KQ5iX2X+3JHNmqG+tiIjsmFxHxMtP5ljuOTo2RSTTCcbtlmSv\nWRlGT+h5tp8CFiIitVMQQ0Qa1lEHZEgmE/xuQQcdVXqWHLZvirOPbyadUqNNRER67pUlOZ74Swe5\njtKpERtWFHjhkRxTpqU49LTm7T5BQwELEZEdoyCGiDS0I/ZLM3PPFA8uzfH48zlaN0dk0gn2nphk\n9oEZpozTOBgiIrJjXn4yx6N/7Oh2nuVP5els38Ib39NCKh2CB6UBi/XLC2xY2QsBiyYYM1EBCxEZ\nuhTEEJGG19KU4LjpGY6bri4jIiLSuzo2RTx+c/cBjKI1LxV46PotNLUk2bAyT+vqCHozYDElychx\nCliIyNDW70EMM5sF/BiYATwNXODu91eY7zzgM8BEwIF/cfe7+7OsIiIiIjK0vfRElkKu9vlfW1oA\nCnWvZ6uAxZQ4w0IBCxGRbfRrEMPMmoEbga8DPwHOAW40s33cvb1kvrnAvwMnuftCMzsH+KOZ7evu\n6/qzzCIiIiIydL2yuI4IRo2KAYuxU5KMKe0SklDAQkRke/o7E+MEIO/uV8avf2ZmnwROA/5QMt/u\nwLfcfSGAu//SzC4lZG8oG0NERERE+sXmjTvQH4Q4YDEpydjJCliIiPSG/g5iTAMWl03zeHrXBPdf\nlb42s9nAyArLioiIiAxInZ0RT3uOl1/K09kZ0dSUYM+9UuxvaTIZXcA2imSq/mUmviHF1OlpBSxE\nRPpAfwcxRgDtZdPageHVFjCz6YQsjX9z97V9WDYRERGRXrHw8Sz33dNJtuzxz889m+eeuzt507FN\nzJipwYgbweiJSVa/UN8YFzNObGLkeD0dS0SkL/R3EKMdGFY2bTjQVmlmMzsF+A3wbXf/dq0rMbPx\nwPiyyVPrKKfIkKN6I1I/1Rup5KEHOnngvmzV9zs7Yf7tnXR2RMw6vKkfSzYwNFq92evQDKtfqO3p\nJADj90gqgCG9rtHqjUhf6u8gxhLgwrJpBlxdPqOZnQt8D/iou/+uzvVcBFzcoxKKDF2qNyL1U72R\nrSxfnu82gFHq3gVZpu6eYuKkHvRXaGwNVW8m759i5K4J2lbXNjbGfm9Sho30iYaqNyJ9qb+DGLcD\nzWZ2IXAF4ekkE4FbSmcys5OAHwEnu/uCHqznMuCasmlT4/WLSGWqNyL1U72RrTzxWG0BjKKFj+c4\n6ZQhF8RoqHqTTCU46qwW7rl6C1tauw9kTD+xiYn79nfzWoaIhqo3In2pX4+y7t5pZm8lBDAuAZYC\nZ7j7ZjO7HIjc/WPAZ4EMcLOZASSACDjL3W+tYT1rgDWl08yss1e/jMggo3ojUj/VGym1aVOB55bm\n61pm6TM55pzYRDo9dAZ+bMR6M2JskuPOaWHxHZ0sfypPoexnHj0hyQHHZZhygAIY0jcasd6I9JV+\nP9K6+yJgdoXpF5T8/ZZ+LZSIiIhIjTa3R6xbV2Dd2kL8f3jdtp279JXk89C+KWL0mKETxGhULaOS\nHHZGCx0nRqxcmqNjU0QynWDc1CTjdpbB5o8AACAASURBVEvqCSQiIv1E4WIRERGRMlEU0dYaxYGK\nqCRgUWDLlt5dl659G0vziAR7HqJxL0REdhYFMURERGTIyucjNmzYOkixPs6syOX6fv1NTTB8hKIY\nIiIitVIQQ0RERAa9bGdpF5CuoMXGDRGFQu+tJ5mkrs+bNj1NKqUghoiISK0UxBAREZFBo+J4FWsL\ntLXVP15Fd4YNg3G7JMO/ccX/E3R0Rvz+11tqCmSkUnDQweqWICIiUg8FMURERKShRFFEa3G8irVd\nQYv163p/vIrRoxOMjQMUrwcrdknS0lI5e2IkcOLJzdx2awdRN3GTZBLefEozY8Yme7fAIiIig5yC\nGCIiIjIg5fMRG9Zvm1mxvpfHq0gmYezYRFlmRYIxY5NkMvV39TjA0rS0wD13dbJ27baRjF3GJzj2\n+GZ23yPVG8UXEREZUhTEEBERkZ2qs7M0m6JrvIoN66NusxnqlcmwVZCimFkxekyCZLJ3x6XYc680\ne+yZYvmrBZa9lKejI6K5OcGee6WYPEWP4xQREekpBTFERESGqA0bCjz/bJ729oh0GiZNTrLHnqle\nv6CH0AVk82a2egpIcZDNTb09XsXwROj+UZZZMWJEol+DB4lEgt2mpthtqjIuREREeouCGCIiIkPM\nhvUF7r6zkxdfyG/z3ujRCY54Y4ZpB/ZswMlq41WsW1egoy/HqygJWFQbr0JEREQan4IYIiIiQ8ja\nNQWu/7/NVQfA3Lgx4va/dtK6MeLINzZV/ZzXx6vYKrMiYv36PhivomxQzXHjEowdlySdVrBCRERk\nqFEQQ0REZIjI5SJu+uOWmp7g8eD9WXadkGTq7qmtgxTx3xs29NF4FWWZFaNH9/54FSIiItK4FMQQ\nEREZIp5dmmfjxtojD7fc1EGh0LtlGD488fqgmmN34ngVIiIi0pgUxBARERkilizK1jX/jgQwRo9O\nbJNZMVbjVYiIiMgOUhBDRERkiFiztnfTKjRehYiIiPQ3BTFERESGiKiHMYymJkoCFV1Bi1Ear0JE\nRET6mYIYIiIiQ8TIUQnWrqlvNM5TT29mn31SGq9CREREBoTkzi6AiIiI9A87MFPX/GPGJBTAEBER\nkQFFQQwREZEh4sAD02TqiGMcdEhGAQwREREZUBTEEBERGSJahiU46ZRmaolL7L1PipkHq9epiIiI\nDCz93joxs1nAj4EZwNPABe5+f4X5zga+AUwE5gEfcffX+rOsIiIig82+b0jz1tNh3m2dbG7fdnyM\nRAIOnJHmuDlNGrRTREREBpx+DWKYWTNwI/B14CfAOcCNZraPu7eXzHcwcDnwZmAh8EPgZ8Db+rO8\nIiIig9He+6Q55x9TPPdsnmeX5mhvj0inYdLkFNNnphk1SomaIiIiMjD1dybGCUDe3a+MX//MzD4J\nnAb8oWS+9wHXu/tDAGb2OWCVmU1w91X9WmIREZFBKJVOsL+l2d/UZUREREQaR3/fapkGLC6b5vH0\nqvO5+1pgLWB9WjoRERERERERGbD6O4gxAmgvm9YODO/hfCIiIiIiIiIyRPR3Dmk7MKxs2nCgrYfz\nVWRm44HxZZP3AFixYkVNBRUZqE466aS9gZfdPdebn6t6I4OZ6o1I/VRvROqneiNSv3rrTX8HMZYA\nF5ZNM+DqCvO93nXEzHYFxsXTa3ERcHGlN97//vfX+BEiA9bzwD7AC738uao3Mpip3ojUT/VGpH6q\nNyL1q6ve9HcQ43ag2cwuBK4gPJ1kInBL2Xy/Bu4ws58CjwDfBG5y93U1rucy4JqyaU3AnoQxOPI9\nK36/24ewzU4k/LDSuxp5+77cB5+peiO1aOTtq3pTXSP/ro2gkbev6k11jfy7NoJG3r6qN9U18u/a\nKBp1G9dcbxJRtO0z4vuSmc0kBDBmAkuB8939QTO7HIjc/WPxfGcB/w5MAu4CznX31f1a2J3MzA4g\nHJTM3Z/e2eUZbLR9Byf9rn1L23dw0u/at7R9Byf9rn1L23dw0u/a94bCNu7356q5+yJgdoXpF5S9\n/gNbP3ZVRERERERERIaw/n46iYiIiIiIiIhIjyiIISIiIiIiIiINQUGMgW0N8NX4f+l92r6Dk37X\nvqXtOzjpd+1b2r6Dk37XvqXtOzjpd+17g34b9/vAniIiIiIiIiIiPaFMDBERERERERFpCApiiIiI\niIiIiEhDUBBDRERERERERBqCghgiIiIiIiIi0hAUxBARERERERGRhqAghoiIiIiIiIg0BAUxRERE\nRERERKQhKIghIiIiIiIiIg1BQQwRERERERERaQjpnV2AgcTMDgbGuvudO7ssPWFmw4GvAu8GpgAr\ngBuBi9197c4sW38xsznAWndf2MNl5wEt7t5ZMv2DwM+Bz7j7pWb2PPBNd7+yl4rdsFRndmjdY4CV\nwBPuflQPlj8TuNfdl/dCWf6BsE/v1sPlh/yxpzc1cr0ys3nAnCpvR8C57v7LfiwSAGY2EjjL3X/e\nw+V/BbyP8B0S8eR24Gngy+7+p4FQTuk9jVwPAcysAJzq7reWTX8LcLO7J+PXewMza9mHzWwv4Hlg\nmrs/3YMy/RPweXffp95lpXuNvL+a2SLgz+7+uZJp7wT+D/iRu19UMv0M4FpgnLu37cA6fwY0u/v7\nevJ+D9b3UeAn7p7vjc8r+dwjgAeAGe6+pGT6DcAZwJHu/nDJ9P8Dcu7+3mrHiL5gZl8E3uzuJ/TW\nZyoTY2vXA9N2diF2wM+BY4D3A/sB5wBHAzftxDL1t3mEi6ieikpfmNnfAT8hNFIvjScfAfxiB9Yx\nmKjO9NxZwDLgcDObUc+CZrYn8AdgVC+V5TfAQTuw/M/Rsac3NXK9eicwOf73z8BrwKT49RTgtzup\nXJ8FPrQDy0eEOje55N/RwBLgd/HFXW/Y0XJK72nkerg9pW2dnxKO3z1ZdkfXLb2nkffX+UD5zZwT\ngVfi/0sdAzy0IwGMGn0c+Kfe+CAzOx74MZDqjc8r8wjQSsn2M7MkcDyVt9+bgNvivycDt/dBmarp\n1bqvTIytJbY/y8BkZqOBdwFHu/uD8eRlZvYBYLGZHebuj+y8EjYeM5tLuLj7trv/e3G6u6/ZaYUa\neFRneu79hLsMpwDnAp+uY9kkvXgycPcOoKMnyw6A7TgYNWy9cvf1xb/NbANQcPdVO7FIRb2xTbeU\nfZfXzOxc4EzgNODyXlhHw/72g9BQ+S3q/Z5DZbs0mkb+XeYDHzSzhLsX2zYnAf8J/MDMJrv7inj6\nMYQbln3K3Vt78eOKbbZe/43cvWBmC4A30nWD9QigAFwBvBn4NoCZ7UMIXNwRL/tab5enPymIEYtT\nYPcCLjezo939Q2Y2DfgBcCwhPfpq4GvunouX+QfChcf+wGbgVuAj7t4av3c+8DvgC4To238SKt6V\nhLuV84D3VaoocRrTP1QoagTs4+4vVZgeAacCxQsJ3N3ju7zPxZ87EriUkGI0nhCl+467/yh+vzku\n598DLcBfgQvcfXW8jRYBJwOjCXehhgHfjbdRC7AY+KS7z48/rwC8F/hSvJ3uBD4CXEJo+L0KnFcy\n/xTgMsKF3UbgBuCz7r6pJI3xXcA349/rQUJ68rNxNw+Am83sq+7+NTM7EvgWoUKvA/7H3b9eYbtu\nJU7PugH4sbt/sey917uTxL9TKzAm/j7twPfc/T9K5v8a8FGgGfgZcCjwc3f/Zfzb/DdwONBGuEv5\naXfPbq+MO5vqzOt1Zl5crsMJdWM1IXPn591su6mEKPm3CMGDfzKzzxXTDOOuTb8B/hX4CjCREC3/\nhziI9lxc9iVmdm68L50CfB2YCSwnBN+uiD+vuG1vAD5ByOC4jlD3tsTv/4e7T4nn3y/+zscBncCv\ngc/FwY5K27eW7fgzYAOwZzzvc/Fn/rlkO97r7l+IXzcT9pG57n5nXO9+S0jp7yRkjvwjYX+aSlda\n//XVtnsjGAT1qtbv+Vbga8B0wnngW+7+P/F7XwcOBkYAhxEyE24APglcQPi9Hyd08bs7XuZ/CXVv\nV+AdwCbgu+7+bTP7MPDFeL5Od28ysybgYkIwcSJwD/Bxd19c51eJgFz8DzNLE85P7yVkoKwmnHe+\nUlLOVcC+hPPcs4Rz3M09KaeZLQN+BXwA2EKo/+cBnyJkvjwN/Ju731jn9xrShlA9/Bmh+9fx8fc8\n0czeCPwHcCTh4uth4Hx3f7Jk0bfF6ep7A/cD5/SkDN2tq+w7l14A/gPh7nLF99z9f+stR6MbBPvr\nfMLxfiaw0Mx2i8v1K+AiQkDj6vj4egTwjXg922ufHR+/P51w3L2q7BpglJn9nHBd0UZoN11a8h2a\n3f1922tDxfO/h3BO24PQXnsunu+rdGU7tJvZCXGb5n2ENt4bCOeBi9392vizLgZmAC/H2zFJuG74\nZIVtWtx+7yl5fRLheus24F/NLB3/7scAy4tdwYrdSQjt0HlsG2iZ5+4nmdlk4PuEgMgowrXYl9z9\nDyWf8/V4Gz3v7kfHdfu/CG21BcDrxw8zSxGu9d4FjATuAy6q9/yr7iRdziTsLJ8FPhE3oP9CaCgd\nTGhEnUVXxZlNiHB9nVDR3gPMBS4s+cxZhAPz0YSD9CWEyv//gLcQdqbzq5Tn42ydtlr8N4WQgr6V\n+CByFfBVM3vOzH5kZmeZ2Sh3f8q7xnj4HuEi+jTACGng348vqojL99b4+7yJ0Gj6WcmqPkxIr/q7\n+CB0I6Ff/+GExuZL8XYp9U3gY4SLtiOAJwjpT4cRdur/Lpn3OkIg4EhCWvIhhFTHUhcTfo8jgQmE\nbUv8GuBs4Dtmtj+hUj4Yr+vjwMfNbHt3vKcDNxMq+qe2My+E7bGUsJ98F7ik2D3AzD4fv/8hYDZh\nmx9fsuzVhEbmDMI++G6q7xMDjepMl88DfyLsO9cRGhK7VN90vI9wwrwtnn8i8LayecYTtuHbgRPi\n7fL5+L2jCCeaY4HfxifqPxEaHIcA/w5camZnlXzeYYRI/VzC73ImoT4XRQBmNg64G1hPOAacDfwd\nYd/eRh3bEcJv9zRhe14DXGdm07vZTuU+RGisnEX4LX5AuLAtNnZ+bWa71vF5A1FD16tamNmJhMbg\nNYT99T+B/zKzd5TMdjrwR8Jxcx7wZeBzhEb3IcC9wF/ixm7RBYTuHQcTGk//GTfkryY0wO4HivNf\nQdhW5xLOXyuBWy2M71Lr9xhBOL8l6Oo69UVCnX0PcADhd/pyHBgv+hjh3Hco8HvgBjOzHSjnuYTj\nx7sJDcZLCb/bAYRg6K/jei21G/T1MPYJQl36IfDO+KLwJsJFxwxC/Uuy7fH/PMJ+dxThXFXx/NCd\nGtZV+p2nAL8knD+u3857Q1FD76/uvhJ4htBGgdDmeSLO7JtHV5eIwwgBlbvj11XbZxa6VFwL/Dl+\n73zgcxbG1Cg6jRBsOAj4DuHaYWaV71S1DWVmxxDaID+My/NEvJ0gXBe9i9DG2gu4x8zeT2g3XUr4\nfX5BaMsVr2MgnEda4nVeBFxkZuXtxKL5wEwza4lfn0gInDwI5AltOaiexbKArt9nMqHNlyXO4AD+\nlxC8OI5QV+cDV8b7WdF7CNc3HzGz8YTrqPsJ5+v/I5z3ii4iBE9OIwSu1sTrqIsyMWLuvs7M8kBr\nHIX8UPz3Z+NZnjWzTwA3mtm/EqKWH3b338XvLzOzWwk/blEa+Ji7rzezywgHgStK7hz9lXDRU6k8\nrYQ7/PV8h/PN7CHCweqjhAZdu5mVjudwF3CZuz8Rl+ESQlBgmpm1Ei5YzvB4YCALgzCdXbKav5Zk\nTQwnHNCuLEZizeyHwC1mlvKuwWv+y90XxO/fRojCfj9+fQXwRzNLEA5aBwCzS+5Ifwh4ysxKo49f\ndfd74vf/G/iX+PuvDu1A1rt7u5mdDzxV8hs+E0cTv0E4WFVSbIw+Acw1sw+4+6+63/J4SWT3W2b2\nWcKB/0nCQewr7n5TXN4PEg5oRXsTTjTL3P1FMzuNcPE44KnOMI0Q9Qf4W8ld5C8RDtAHE6fsVfA+\nwiBWWeAxC1kG5xKCgkUp4BPu/nj8ub+iK1BXTGlf4+4dZvZx4EZ3Lzb+lsYXRZ8n9OOHsG0/5O7r\nADezv5R8XqkPEE56H47L95SZfYzwO37R3Tf0cDsCLHT3YiDmEgsDzJ1HCETU4tcl2+MdhEbBMndf\nRqh7jxDuwDeswVCvavBx4Fp3/178emkcbPg8XRch69z9B3H5EvEyX3D3G+L3PxUH7z5OV3Bvsbtf\nEv99SXwsPsLdnzKzTUA2Pk/sAnwQeJu7z4vXcS7h7tI5hL7Llfy9hcHmIJwrmgmNxJPdvXgseBy4\nzd3vi19fbmZfJvweD8XTHvWuDL+vmdmphDugn+lhOX9Vcnw6i1B/X3L3ZWb2H/F6t1T5TlLBEKmH\nuPtGM+sENrn7BjObBFxSci550cx+SsgILPWZ4j5uZlcRznn1GtHdukq/s5mdTbgQfGPJnf/u3htS\nBsn+Op9wwX4VIZOgmL1wOyHQDeEi/EF33xy/7q591g7sAqyM2wjLzOzNwAsl63zU3b8W//1dC4NP\nHkrIOi/XXRvqQuB6d/9h/PqLcbAed4/MrDjA+WvunouvaX7k7sWbxN+JA92fIwRIIGy/i+LroaXx\nMkcSgjLlHiIEHQ6P22KzCe3HnJndHW/Pu+Lpl5UvHGdpvBZvwwmEm8vfdPe/xLPcQGhjvhTP821C\nVv3uhCwSCPuGx+9fGJf/n929QLj+Oo6uMQv3JuyDL7n7qriNWfd4LgpiVHcgXRf2RQkgA+zt7o+Y\nWZuZ/RuhEs+Il/l9yfzr4igi7r45vsB+vuT9zYRG0DbM7HLCxUS5CJju7i9XWs7drwKusnDX5WRC\nFsC3zexpd/+Th7TzM+KGkBEirRHhgumA+P+HSj7vKcIBoei5kvfa4yDCB+LKZ4RIJfHnFIMYz5Ys\n3176GfE2SBK264GEbhnr421VVIg/u7jcMyXvbYyXrWQaIQpYagEwzswmevW+YHcSAjc/JtwdvN3d\nX60yL4Tof6lWIBNHIncjjBoMgLuvNbPS+b9OODifZ2Y3A79z98e6WddANhTrTNHTJZ/XGpe74n5p\nIUunmC1RdC0hS2iCb93nvtZ9/UDCHYhSC+i6EwBh264r+7ymCp81DXjMt+7StIBwvjBK9udS29uO\n8Wx3lS32IGFb1Kr02HELIfX4YTNbTLhr/5OSxs1g0ZD1qobvVB4oWEAIaBWVlm8yMI5t970FbN2I\nrngsrrB+I2zD0mNzZ9z46y4z6E+EoHmakCn4eUL68b0ln3O9mZ1oZt8i1KVDCZlWpceL8nrwAOFu\nVE/LWbqtbiIEUh4zsycZvPWivzViPcxROeM6Gb+3DXdfaWY/jQPjh9LVrltXNmvpsXg9oWtxXWpd\nl5kdBPwP8FEvSzfv7r0hrhH31/l0BaRPJNwMgXAzaE8z24OyTILu2mdxYOcy4IcWbi79mRDwLY6t\nAVtfn0Do8lptX+6uDXUw27bB7gXGVvmsA+kKzBQtoOs7A7zgWz/JpGobMA5W3EMIAjUBG0vqwzzg\nVAuZTzPpZjwRC9krvwWe9LgLZOzHwLvjGwPl13pFpfvGgYRMmkLJtAcJGR7QlWH4alzuG9g26367\n1J2kujShoXEwoZF9SPz3AYRo3smEhsJehCjhP7LtqOuVxjUoVJhWyb+VrLf036GE/sNbMbM58cEI\nCFHZOML6ZuAxQt9bzOwXhChcK2GHOZKu/k+dbN/rDSELqbQPEu4gP0tIqz2nwjLl26HaNkjT1S2j\n9DsfQOgvVVRezmoD5VS685Qq+79cRBhjIwI+Q7iru72KVWm7Jej63lXrWXwHYm9CqvQ44A9xJLkR\nDcU6U1RtH6jk/fH/15hZ1syyhKc4pNn2pL+j+3ppoLrWMtZVb2rdjrHyhnNpsDMqe69SkP3144+7\nb3b3YwjpjTcSTo6PmNlhFZZrZA1Vr2pUy/5aetFdLYsgxdb75I7s45U+r1ybuz/v7s+4+7cIA3n+\n2sxmFWcws38ndOGICN1ljid0ASnVXT3oSTlL60W7ux8dr/dPhGDLw2ZWT7BQttWI9XAd4cZQuXFU\nyfi0MC7ZIkKa9xOE8cz+pcKs5ftrxXOTme1hYTDB0vmKYzLstr11WXgU+bWE8QCuqfU9acj9dT5w\nYByY2i0uf3HwycWE7rNHU3IRvr32mbt/gnDRfSlhHI/bLDzqtKjScbdaO6u780uW+q6pq50De3I+\nKyo+4eUEts4CnhdPPwZ4xd2f23bR132bMF5TsZ1azIS8ldBVcgVhe59aoSyl5+zysTWgZH/y8CjY\nvQkZVEsI11v3x9eVNVMmxtZKG9FLCCk9LxfvSFoYbO9CwoXGRYSI3ut3jiyMwdDdzlEzd19NGBCs\nVuOAL5nZT70rrbWYxtRGGEW9mJp6rHd1xyjezUnEZS8QIpl/i98/iLDzHlBhnW8B9gFGe1f3j2Kf\np56MwLuEkJq00eMngFgI/f4nXY85Kr/Q6c5TcRlLzSZEWssblaXy8Hqa5T8BfzKz8929WopxRfHy\nLxP6MT8Ir5909y/5+xt0DUL0IzP7HCEd/wv1rGsnGup1pifOJjS8vlw2/RpCQPB72yyxrfJ68BTh\n5F5qNtvema7FU4S0+UxJNsZsQr14psL829uOpZklh5ctexRdd6U7CQMGF72hu0JaSNU8Pr5bsAD4\nQnzn+W2EMXcaWSPXq1pU21+9ShnWmdmqeJlHS96qZ5T60m26lHAhdTSh3y4W+hIfRjjf1eorhEFE\nrzKzI+Lg9z8TAuG/iz93F8Jgo6XHi0r14K91lvOWSgWykC59TJwifbeZfYGwvU8jXLRI7Rq9Hj5K\nqCPlF6ez2boelX7Ps4F2dz+1OMHCILyJKvNvz6WEgElxu4yh63v8fXfrii+eronn/+fSD+3uvSGs\nofdXd3/FzF4kjJ1Q/gjVeYRj2ATC4MZsr31m4WEAnwc+5e7F8S4uJwy6fGWPv1xli9j2uH4kXW2m\nam220syXqufAGs0nDAI6vuxzHyGcRz5I91kY7yVs++PcfW3JW7MI44DsXsxKt9D1vVKgomghYYyd\n4oCiULJ94murNne/mtDF6WLCgPSHsW2mYlUKYmytjZB+NY4wQMuXgV+Y2TcIO8VVwP1xOuerwDHx\n3Y0thBSgg+nqI9/f/kg4Kf0tTpt6iDAy+nsIaT3vJUQqW4F3mdkrhCjYpYToWLO7t1no2/i9eAdr\nJUTc7itJkS/1KmHQmfdYeLzPMcQjqxNSzGp9ZGOxEvyVULF/E6csJQh3ujrjtMO92P6FYxsww8zu\nA35EGAjnO4QD1kxCo/O/y1KcqnL3m8zsakJa/K3biWBW8j3g4vjA/CIhaDEciDz0Pz0F2CsOXqQI\nB+mHqn7awDOk60y9KzSzYwl3Ps6pkBb7Q8JAScUDfXf7evHkfkhcru8QotifIQwUejxh+/akcXc1\n4Xf8aZwVNJVwHPht3DApV8t2LJobl/F6QqT/ULoi/g8SBoS6mvgpP3SfHdZBCJ68RkgTPZiwbRup\n/lTTyPWqFt8mDG72L4Q00rmEQPXHulnmW8BXzGw54a7cBYTuGmd3s0ypNmCKme3t7i+Y2ZWE7oLn\nExpPXyK0iWq+o+vuWTP7f4QBes8nnK+WA2dY6PIxgZChmGfr48WbzexThLpzDiGV+929VM4sYSDR\nlYTxlmYRbg4MhnrR3xq9Hv4AuDZuf1xPSJM/nXDX/e9K5msD9rPQF/5Vwv73FkJ77K2EAETpRVg9\nAfw7gH+zMPDhZkKg/jfxe9tb11cIF4InALvEgQviz/kXQvBvbvl77r6xjvINJo2+v0K4EP8AYd8t\nNY8w8ON93vWUtO21z9YQ2iEZC2MDjaMrQ623/QBYEN/IvZUw7lnpjaRim+1wC2N3fYuQjfskoQv7\nOwkB8dN2oAwPEDJYplDSLcXDI1iL67iw0oIWBjO9ivC0lBcsjI1TtJJwDjvbzH5PuJYq3myr1g7+\nDWEogissdK08hhC0LGbVjwe+Ht+ccEI7sJ1wbq/ZTutOYmZHxTtdtffPM7OnzWy9md0fN/772g8J\nI83+xN3bCWnQ4wk7xu8JO2YxavkVwkjAdxNSsTYR+p/Porp6otd1iTMhTiZUzm8SorA3ERr1x7r7\nijga+wHCncqnCCNAfzH+DsULp3+JX99IOPm8RBisb5vyexjU6eL4cxYTdsK3EC4uDq+0TBVR/HkR\n4cS6IV73rYQo5pnl83bje4RAwVfjiOFphAPJ43E5v+PuX6qhTKU+QThQ/iI+UUbbKUfpe98njDr8\nv4S7xU4IZhQvzoqjD99LiD6+xNZ94gY61ZnKZaxW7vcRBputFGm+mpD+W7G+lZV9LaH/5S8Jj/h6\nlHARdA4hAv4ZwqBOV1X7jG4+u51QjycTLnx+SfgtP1Rl/u1ux5LZbySkhD5O2KanuPsL8XvfJWzX\nvxIa3FcCpXcDyo8/CwhZSx8n/DbfBz7v7jfX+50HoIatV7Vw94cIDZpzCfvrpwgDyP28m8UuJWyX\nywhBs8OBE929uztXpd+zOMDtIgvjFX2aEPy6hjB20jhCZk+9dw/nEe50fz2+M/iPhJHuFxHSm68i\nPDWo9C7ddYQLs2J3qzd71yMHay3nmgrfEQ8Db59P2KZPEQJGn3b3vyL1auh6GB8L30NoQz1KaIOc\nDpzp7reVzHoFYQyCWwj78i8I56PHCd31TgXGWFe3kHrKfSVh/7+OsF3m0/VEud8RzmPV1nUOYXs/\nQQjgvRr/+z7hrvIuVd4bqhp6f43NJ9zou71s+h2EtvLr07fXPoszOU4n3Ex5lNBGuZ1ts2BLba99\nX5G7P0xoI32asE8eSmjHFNv6Cwnb/3bgNA8DVP8zIet6ISEY/67tHKe7LZeHJ8E9AKx196Vlb88j\nBDHLMzGKn/kuwnb/LiFo8SpxvYozbC8gZO88RRh89IOEAVIrtoPjQOLJhMzzRwhttdIs428Rrot+\nGn/mO4HTS85rNUlEUf+3ZSyMb4UGMwAAIABJREFUmvtdwgjcEyu8P5dwcDvJ3Rea2TmEKNe+vvWg\nKiIDmoVR5x/2eLBGC8+4XkMYbf7ubhcWGUQsPHM9cveKwRCRocDM/pdwt/ij251ZREQGPAuPRm31\n8DCE4rSbgQXu/o2dV7LBrd8zMeL+mRcRP6u4it2Bb7n7QgijzxJSWWZ0s4zIQHQecLWZzYj7G/4X\nIYhR/tQUERERERFpLEcDt5jZcWa2Z9wl/3jC+GfSR3bGmBg/cfdL4gFmKnL3X5W+NrPZwEjq7Csj\nMgB8jJDidyehvi0gpNBXGvVZREREREQax38DewK/JnT5W0LoHqLr1j60U7qTwOuj5P6+UneSsvmm\nEwbNutTdv90vhRMRERERERGRAWdAP50kfnLDb4Bv1xPAiAfDGl82OUUYRXVRyeNeRCSmeiNSP9Ub\nkfqp3ojUT/VGpMuADWKY2bmEkUw/Wnzeeh0uIjw1Yxu33XZbpckijaSex5vVQ/VGBjPVG5H6qd6I\n1E/1RqR+ddWbARnEMLOTgB8BJ8eP0avXZWz7DPWpbPvIHhHponojUj/VG5H6qd6I1E/1RiQ2YIIY\nZnY54fF7HwM+C2SAm80MQmQmAs5y91u391nxc2a3etasmXVWmV1EUL0R6QnVG5H6qd6I1E/1RqTL\nTgtiuPt8YGLJ6wtK/n7LTimUiIiIiIiIiAxYyZ1dABERERERERGRWiiIISIiIiIiIiINQUEMERER\nEREREWkICmKIiIiIiIiISENQEENEREREREREGoKCGCIiIiIiIiLSEBTEEBEREREREZGGoCCGiIiI\niIiIiDQEBTFEREREREREpCEoiCEiIiIiIiIiDUFBDBERERERERFpCApiiIiIiIiIiEhDUBBDRERE\nRERERBqCghgiIiIiIiIi0hAUxBARERERERGRhqAghoiIiIiIiIg0BAUxRERERERERKQhKIghIiIi\nIiIiIg1BQQwRERERERERaQjpnbViMzsKuM7dp1Z5/2zgG8BEYB7wEXd/rR+LKCIiIiIiIiIDyE7J\nxDCzDwG3AJkq7x8MXA68F9gVWAn8rN8KKCIiIiIiIiIDTr8HMczsC8BFhCyLat4HXO/uD7l7B/A5\n4FQzm9AfZRQRkW1F2Yj80g7yC7eQf7aTKBvt7CKJiIiIyBCzM7qT/MTdLzGzOd3MMw24p/jC3dea\n2VrAgFV9XUAREekSbcyTvbmN3F2bYFNJ4GJUkvTxw8mcOpLEyNTOK6CIiIiIDBn9HsRw95U1zDYC\naC+b1g4M7/0SiYhINYVXs3R8Zw3Ruvy2b7YWyP25jfwDm2n+9K4kJ+60YZZEREREZIgYqC3OdmBY\n2bThQFstC5vZeGB82eSKA4iKSKB6I+WiTQU6Lq0SwCidb1Weju+upuUrE0kMG1oPvVK9Eamf6o1I\n/VRvRLoM1CDGEkLXEQDMbFdgXDy9FhcBF/dBuUQGM9Ub2Uru9k1Ea7oPYBRFr+XJ3dVO5pSRfVyq\nAUf1RqR+qjci9VO9EYkN1CDGr4E7zOynwCPAN4Gb3H1djctfBlxTNm0qcHvvFVFk0FG9kddFhYjc\nHZvqWiY3bxPpk0eQSCT6qFQDkuqNSP1Ub0Tqp3ojEhswQQwzuxyI3P1j7v64mZ1HeKzqJOAu4Nxa\nP8vd1wBryj6/szfLKzLYqN5IqWhNnmhtbVkYry+zIgetBRg9dAb5VL0RqZ/qjUj9VG9Euuy0IIa7\nzwcmlry+oOz9PwB/6O9yiYgIsKVnj0+NtkQkRvdyWUREREREYkNrBDYREdmuKIoovNCzmzuJkTqt\niIiIiEjfGTDdSUREZOeKoojCkx1kr91I4fls3csnpzWRGK4ghoiIiIj0HQUxRESE/NNx8MJ73r02\nfeKQezKJiIiIiPQzBTFERIawwguddF67kcLCjh36nOQhzaQOb+mlUomIiIiIVKYghojIEFR4JUv2\n+o3kH9pSdZ7kvhnSbxtFdl4b0aLqGRqpWS00/dM4Eskh9WhVEREREdkJFMQQERlCCq/lyN6wkfy9\nm6HKA0gSu6fJnDma1KEtJBIJUoe2UFjYQXZeG4UnOyAHZCA1s4X0SSNITm8mkVAAQ0RERET6noIY\nIiJDQGFtntwfN5K7qx3yledJTEqReedoUkcO2yqrIpFMkDqkhdQhLURRFIIYaRS4EBEREZF+pyCG\niMggFm3Mk/1zK7nbN4XgQwWJ8SkyfzeK1OzhJFLdByYSiQRk+qCgIiIiIiI1UBBDRGQQitoLZG9u\nI/fXNuio0m9kdJLMGaNIzxlBIqOsChEREREZ+BTEEBEZRKItBXJ/20T25lZorxK8GJEgc9oo0ieN\nINGc7N8CioiIiIjsAAUxREQGgSgbkZu3ieyfW2FjofJMLQnSbxlJ5pSRJIYreCEiIiIijUdBDBGR\nBhblIvJ3t5O9sZVoXZUROzOQPmkkmdNGkhiV6t8CioiIiIj0IgUxREQaUFSIyN+3mewNG4leqxK8\nSEF6zgjSp48iOU7BCxERERFpfApiiIg0kCiKyD+8hex1G4lerfa4EUjNHk7m7aNI7qrDvIiIiIgM\nHmrdiog0gCiKKCzqIHvtRgovZKvOlzpyGJl3jiI5Rc9BFREREZHBR0EMEZEBLu8dZP9vI4VnOqvO\nkzykhaYzR5Hcs6kfSyYiIiIi0r8UxBARGaDyz3WGzIsnO6rOkzywmcy7RpN6g4IXIiIiIjL4KYgh\nIjLAFF7Okr1uI/lHtlSdJ/mGDJkzx5Ca3tyPJRMRERER2bkUxBARGSAKK3Nkr99I/v7NEFWeJ7FH\nJnQbOaSFRCLRvwUUEREREdnJ+j2IYWazgB8DM4CngQvc/f4K8/0rcAEwClgEfMLdH+nPsoqI9IfC\nmhzZG1vJ390OhcrzJCanybxzFKkjhpFIKnghIiIiIkNTsj9XZmbNwI3AT4AxwGXAjWY2vGy+E4BP\nAye4+zjgT8Dv+7OsIiJ9LdqQp/Pq9Wz5/Eryd1YOYCR2TdH04bG0fGMi6aOGK4AhIiIiIkNaf2di\nnADk3f3K+PXPzOyTwGnAH0rm20RIpm4ysxShad/eryUVEekjUVuB7M2t5P62CTor9xtJjE2SPmMU\n6eNHkEgrcCHSiArLt5Cbv4r8ko2wOQ/DUqRmjCY9ZwLJSS07u3giIiINqb+DGNOAxWXTPJ7eNcH9\nATP7EfAkkAc2EgIgIiINK9pcIPfXNrJ/aYPNVQa9GJkkc9pI0ieOINHcr8lyItJLonxE9rfLyN2x\naus31mfJLd9C7m+vkT5pIpl3767sKhERkTr1dxBjBNtmVLQD5d1JzgI+ChxOCGR8HrjOzKa7e/Vn\nDYqIDEBRZ0Tu9jayf26DtiqDXgxLkHnLSNKnjCQxTMELkUYVRRGdv3yB/L1ru50vd9trRJ0Fmj6w\npwbpFRERqUN/BzHagWFl04YDbWXT3g9c4e6Pxq+/ZmbnAW8G/ry9lZjZeGB82eSp9RdXZOhQvel9\nUS4id+cmcn9sJVpfJXjRlCD95hFk3jqSxMhU/xZQdpjqjZTLP75huwGM1+e9azWFw8aRmjG6j0s1\nsKjeiNRP9UakS38HMZYAF5ZNM+DqsmlbgOayaXkgV+N6LgIurrt0IkOb6k0viQoR+Xvayd7YSrQq\nX3mmNKTnjiBz+igSYxS8aGCqN7KV3LzX6p5/qAUxUL0R6QnVG5FYfwcxbgeazexC4ArgHGAicEvZ\nfL8BrjKz3wILgU8QnqRyd43ruQy4pmza1Hj9IlKZ6s0OigoR+Ye3kL1uI9HyKjHXJKRmDyfz9lEk\nx/f7U66l96neyOuiTTkKS1rrWia/cAPRljyJliEVzFS9Eamf6o1IrF9b0O7eaWZvJQQwLgGWAme4\n+2YzuxyI3P1j7n6DmU0iPFZ1F+Ax4FR331TjetYAa0qnmVlnb34XkcFG9abnoiii8EQHndduJHop\nW3mmBKSOGkbmHaNJTlbwYrBQvZFS+aXlvWNrEEG0MTekghiqNyL1U70R6dLvLWl3XwTMrjD9grLX\nVwJXls8nIjKQ5Jd0kL12I4Wl1dsRqVktZN45muQemX4smYj0tSiKiF7aTO7RdeQfXU+0fEvPPiij\ngT1FRERqpduBIiI9kH+2MwQvFld/YFJyRjOZM0eT2repH0smIn0pKkQUnm0j/8h68o+tJ1qzYzdC\nE2MzJMYowCkiIlIrBTFEROpQWJYle+1G8o9Vv+Oa3L8pBC+mlY9PLCKNKMoVKHgr+UfWk3tsPbTW\nOs749qWP25VEUpkYIiIitaopiGFmewLL3D0qm54CZrn7Q31ROBGRgaKwPEv2+lbyD2yuOk9irwxN\nZ44meVAziYQuSkQaWdSRJ//kRvKPrif/xAbYXOVJQ2USk1uIVndALtr+zCPTpOdM2MGSioiIDC21\nZmI8D0wGVpVN3w+4Exjem4USERkoCqtzZG9oJb+gHapckyR2S5N552hSh7coeCHSwKL2HPknNoTA\nxaINkK0hEAEk9xlBatZYUrPGkpzUQv6ZNjouewa2FKovNDxF8//bj8RodSURERGpR9UghpmdD3w5\nfpkAFppZ+dl4NLCoj8omIrLTROvzZP/YSm7+JqhyAzYxIUXmHaNJHT1M6eAiDSrakCX3WBjforBk\nI3QTd3hdEpIHjCJ1aBy4GLf1uDep/UfS8q/TyF7/KvnH12/9mUlIzRpH5h27kZzU0qvfRUREZCjo\nLhPjJ0A7kAR+Sngk6oaS9yOgDT2bWEQGkagtT/amNnK3bYLOyndhE+OSpM8YTfq44STSCl6INJrC\n6o6QbfHoegrPtlXNstpKOkFy+mjSs8aSOngsiVHdJ7Mmpwyj+YI3UFjXSeHpVqL2PInhKVI2msRY\nZV+IiIj0VNUzsLtngV8CmNnzwAKg2d03xdPM3b1fSiki0seizQWyt7SRu6UNtlS5ohmVJPO2UaRP\nGEGiScELkUZSWL45DMz56Hqil9prW6g5SeqgMaGryMwxJIal6l5vclwTyTeOr3s5ERERqazWMTFe\nBh4FbgI+F0+7y8yWAe9w92V9UTgRkb4WdRTI3baJ7E2tsKlK8GJYgsxbR5E+eQSJlmT/FlBEeiSK\nIgovtoeMi0fWEa2s/jjkrYxIkTpkLOnDxpI8cDSJjOq8iIjIQFJrEONHwFPAd0umGXAl8EPg7b1c\nLhGRPhVlI3LzN5H9UytsqNIJvjlB+uQRZE4dRWKELmREBrqoEFFY2tYVuFiXrWm5xNhMGN/isLEk\n9x9FIqVMKxERkYGq1iDGbOBQd3+tOMHd15nZl4AH+qRkIiJ1ijYViFrzkEmQGJeqONhmlI/IL2gn\ne2Mr0ZoqI3amIX3iCDJvG0VidP3p4yLSf6JsgcJTreQeXR8G0WzN1bRcYkIzqcPigTn3HqHBeUVE\nRBpErUGMdcCBwLNl0/cGNvVmgURE6hFFEflHtpC7fROFxV3p4olxKdJzh5M+cQSJkSmiQkT+wc1k\nr28lWlHlIicF6WOHkz5jFMnxtR4eRaS/RR158os2hoyLJ9Z3/yjT/9/encdJdtb1Hv+cU1W9zdrT\nk5mE7OuTfWZCvIAJISEKhBAU9CqKFxEEDBGvuICIiqg3onBFDBgSzEXRAFcRuNGwRJMAYRVIMtnI\nE7KSddbuzNLd011V5/5xamY6ne6ZOjNd1V3dn/fr1a/pOnWWp0/1t6b7188yQXJEbz4x57p+ksNd\nElmSpE7U7E/pHwP+LoTwHuB7jW3rgPeQr1wiSW2XjWeMfWyQ2ndHnv3cYI3xz21n/KYdVC5eQvWW\nYbJHpyleJFB6fi+Vn15KusrihTQXZTur1O54mtqtg9Tu2QbjzSwpAulxi/IeF2v7SVd1t7iVkiSp\n1Zr9af3PGvv+CXBIY9tG4IPAB1rQLknar7G/n7qA8QxPZ4x/ctu0T5ee20PlVUtJD3fJQ2muyYbG\nqa7P57eox+3QTIeLFNKTluSFizXLSfu7Wt5OSZLUPk0VMWKMGXmvi/eEEFYCYzHG6X8rkKQWqz04\nRu2b+ylg7EN6Rjddr15Keoy/4EhzSX3TrnyYyG2D1B/cCc10uCgnlE5bmi+FeuZyksX2qJIkab5q\n+n/5EMKpwJuA04FaCOF24KMxxodb1DZJmlb15gObjicNXVRevZTSSXYrl+aCLMvInhyldusQ1dsG\nyR5tsjjZnVI6cxmldf2UTl9K0uMkvJIkLQRNFTFCCBcDnwO+BXwXKAEvBN4WQnhJjPEbrWuiJD1b\n/a7RwsdUXrWE8iVLnMxPmmVZllF/eHhPj4tsw679HwSwqERp7XLK6/pJT1lCUnHpY0mSFppme2L8\nBfDHMcbLJ24MIfwx8NfAj81wuyRpn7Lh5ib1myg5pGwBQ5olWS2jfv8OarcNUrttiGxwvKnjkuWV\nxlKo/aQnLCYpmWFJkhayZosYxwGfmWL7tcA7Zq45ktScpC8hGytWyEj6/Kut1E7ZeJ36vdup3jZI\n7fanYcc0KwRNkqzq3lu4OLqPJLVwIUmScs0WMb4EvAH4vUnbfxr4jxltkSQ1IT2th9o3hps/oCsh\nPdFJPKVWy0Zr1O7alve4uPNpGG1mSRFIjuylvK6f0lnLSQ7rsdeUJEmaUrNFjB8BvxlCuBC4BagC\nzwXOB64LIfyf3TvGGN+wrxOFENYBHwVOA+4DLo0xfmeK/V5IPlTlJOBB4DdjjDc32V5J81z5xYsK\nFTFKz++1J4bUItmOKrU7hvI5Lu7eBtXmekmlxy/KJ+Zct5z0ECfblSRJ+9dsEWMZ8KnG5/2Nf38E\nfKLx+e4/l+zzp5YQQjdwHfCnwDXA68iLIMfGGIcn7HcY8P+AN8QYPx9CeA3wryGEw2KMTc7+JWk+\nKx3XRekFvdS+1cRKBktSKq9c0vpGSR2mPjhGbf0Q2bYqSSUlPW4R6UmLm+oFUR8ao3b7ELVbh6jf\ntx2a6XCRQhqWUDqrn/Ka5STLKwf/RUiad+qPb6f2g80wWoXeMqVTVpI+x//HJeWaKmLEGH9lf/uE\nEJaQTwC6LxcAtRjj1Y3HHw8hvB14Oc+cc+N1wA0xxs83rv/pEMK9NPcjkqQFoutX+hkbz6h9bx8r\nlSxL6Xn7AOlA0ytKS/NefcsY4//yKLXbh571P2tyaA+VVx5G+ewVzz5u4y5qtw/mhYsHm1zmuJJQ\nOnUppbP6KZ25jGSRWZQ0tfpDQ4x/LlJ/YPAZ26tE0uP7qbw6kB6zfJZaJ2mumMmfJPqAtwBv3cc+\nJwP3TNoWG9snOgt4PITwWeC8xj6/GWNsbipzSQtCUknoeusKat8fpXrTTuo/2NtRK+lPKZ+/iPIF\ni0iWlGaxldLcUt8wyuj7I2ybepLN7KlRxq5+iGzzGOWXriZ7fJTabYNUbxsie6yJnk8APSmlM5dT\nWrec0ulLSbrNoKR9q921kbGP3TbtcLT6A4Ps+uB/0fXmdZROO6TNrZM0l7T7zyGLgMmD2IfJCyAT\nrQAuAl4F/HfgzcD1IYQTY4xPt7yVkjpGkiSUz+6lfHYv2Y462fYaVBKSFSVXNJAmyap1dl1x/7QF\njInGP/s41Rs3kj3d5N8PFpcprV1Oed1y0pOXkFScg0ZSc+qbhxm7Zv3+59Op1hn7u9vp/oNzSQd6\n29M4SXNOu4sYw8Dkd5w+YMekbbuAL8QYb2w8vjKE8LvAOcAX9neREMIAMDBp8+HFmystHPMhN8ni\nlGSxvzipfTotN7Vbh8g2Nj+11P4KGEl/JR8msnY56YmLLRyqKZ2WG7Ve9SuPwFituZ3HatS++gjp\nqyd35J7fzI20V7uLGD8ALpu0LQDXTtoWgeMmbSuxdwLR/Xkb8J7CrZMWNnMjFddRuanesvmgz5Gs\n7s4LF+uWkx7d51KoOhAdlRu1VlatU/v244WOqX77cco/dRJJaUH94cLcSA3tLmLcBHSHEC4DriKf\nwHMV8OVJ+/0j8M0QwkXAl4BfB7qBZpdYvQL45KRthzeuL2lq5kYqrqNyU3+s+WWJJ0qO6qO8Lp/j\nIjmsx8KFDlZH5UatlQ2Owsj+h7g9w85xsqFRkoHJI9LnNXMjNbS1iBFjHGsUJq4CLgfuBy6JMY6E\nEK4EshjjW2OMt4cQXgn8JfBp4D7gFROXYd3PdbYAWyZuCyGMzeTXIs035kYqruNyU9vPePMpVH7u\nCCo/sboFjdFC1XG5UUvUNw9TW7+B2nefPLATHMD7WSczN9qf7Olhaj/cACNj0NtF6cTVJMvmZ6Gv\n7eucxRjvIp/bYvL2Syc9/k/yVUokSdIMSFZ0kT2xjyWJp5AevahFrZG0kGRZRvbkjrxwcfsGsse2\nH/jJ0oRkaffMNU7qYPWN26hefzu19T+C+t7i3niaUFpzFOWL15KuWjqLLZx5M1nE2AXcMIPnkyRJ\nM6j8vAHGP9f82PNkZRfp8RYxJB2YLMvIfrSN2u1P5YWLjQc2pG2y0prVJD1t/1usNOfUHtrE2Edv\nhJEpJuKuZ9Rue4TavU/Q9WsXUjp2/ixN3HT6QwgXAz8GVJg0wWaM8fdjjEPky6JKkqQ5qHzOAOPX\nPwlj9eb2P3+VK45IKiSr1ak/MEjt9g3U128kGyrW+6sZpfOPmvFzSp0m2zbC2NU3T13AmGhknLGr\nb6bnXZeQLJ0fSxM3VcQIIXyQfEbc9cC2SU8vrAFpkiR1qGRpha5fPpqxv3tov/97p6cupfziVe1p\nmKSOlo3Xqcct+VCROzbAjv38UtWQHNJHae1qSmtXU/3+k9RuemS/x5R/8lhKJ6w42CZLHa96S4Sd\nTS6bvnMX1VsilYvXtrZRbdJsT4zXA6+PMf5TC9siSZJarPxjK6CUMPaPj8DO2pT7lF6wgq5fOpqk\nbC8MSVPLRqvU79mcDxW5exOMTv1+MllyxBJKa/LCRXLY4j2rHVWOXkbS10X1S/dDdYoqazmh/PIT\nKL/kuJn8MqSOVK/WqH79vkLHVL/5Q8oXnUmSdv7SxM0WMerAt1vZEEmS1B7ls/opnbaM2ne3Ur11\nkGxblaSSkB63mPJ5K0lX98x2EyXNQdnOMWp3bsqHivxgM1SbG5qWHrectFG4SFdOvVpCkiRULjqe\n8rlHUP3mY9Tv3UI2UiXpLZOespLyC44gWdI1k1+ONGdl4zWyoZ1kWxsfg42PrTv2PJ44iWdTto+S\nDQ2TrFjcmka3UbNFjH8AfiuE8LYYY3NlVkmSNGcl3Snlc1dSPnflbDdF0hyWDY1Su2NjXrj44dbm\nfnFKE9KTVuQ9LtasIlnWfGE0WdJN5aXHw0uPP4hWS3NbNjxGNri3ILG7WFFvFCvYNtKaC4/Pj1/l\nmy1iHAH8FPBzIYSHgWesSRxj/PGZbZYkSZKk2VDfNExt/Qbqt2+g/tBQcwdVUtJTVuZzXJx+CMki\ne01oYcrqGWwbyQsSE3pO7ClWDO6E0ebmjZlRCSRLFtDEnsDdjQ9JkiRJ80iWZWRP7KB2+wZq6zeQ\nPb69uQN7ypROP4TSmtWkp6502VMtCNl47VlFiWzrjr2Ph4ah1txQq3ZKT34OSd/8KC429U4TY3xv\nqxsiSZIkqT2yekb2yNP5iiK3byDbNNzcgYsrlM5szG9x0gBJpfMnCZR2y7IMRsaeMcRj9+f1wR1k\ng8OtG+oxWSklWd5H0r+IZMUikhWLSfr7Gv8uov7kIOPXfK3p05XPCy1sbHtNW8QIIVwO/FmMcbjx\n+bRijL8/4y2TJEmSNGOyWp36A4N7elww1NzyjMnyHtLGUqjpcctJShYu1LysWqN2x6PUbnsEto/m\nQ4+OOYTSC04gbfMkk3uGekzsOTH4zHkp2NWmoR7dlUZxYlFeqJhQrEj7F8HSnn2uJJIcsoT6846n\n9p0H9nup0vOOJz318Jls/azaV0+MFwBdwDDwMmAImGqttYLTokqSJElqh2y8Rv3eLXnh4s6NsLO5\nX9CSVX2U1h6aL4V61NI9S6FKRdTueZyxT37rWb0X6vEpqjfcRekFx1P5mf9GUinNyPWeOdQj7znx\njHkp2jnUY2kvSf8i0j3FiQmFiv7F0Fs5qFwlSULlNc+H7jK1r8Vp9yudF6i86ux5leFpixgxxgsm\nPDwd+AbwBeALMUbnx5AkSZLmoGy0Su3uTdTXb6B21ybY1dyKBMmRS/MVRdauJjl00bz6pUftV7vz\nUcau+er0K9pkGbVv3k/29Ahdv3r+fnv47BnqsXXyfBSNoR5bd+Y9Pdph91CPPcM8JhYoGh8zVJjZ\nl6SU0vWz/436CwPVr99H/d4nyEbGSXorpCc/h/K5J5GuXtbydrRbs7PvrAVe0vh4TwhhM/BF4Hrg\nxhhjmwYGSTMjq2fUNmTURzLSvoTSqoQk9T9qSZLUmbIdY9TubCyFeu8WqDbx1+YE0uP682EiZ64i\nXdnX+oZqQciGdzH2j99oakne+t2PU/3qvZTPPxm2jT57qMfWnY3lSIfbN9SjpzJpmMfiPY/TFYtg\nSe+c+t0hXb2Mrp/5sdluRts0O7HnPcA9wF+HELqAc4BfBT5Pvtyq73jqCPWRjJGbxxm+pUp96943\n1dLKhN4XVeh7UZmke+68IUmSJE0nGxrdMzFn/f7Bpn5hJE1Iw4q8x8WZq0mWdbe+oVpwat95sNAy\notXrbqX6b7e1f6jHs+akaPSqmCereMxXTa+DFEI4AXhh4+M84BhgPfDVlrRMmmHVTXWG/maU2sZn\n/wdf25yx41/HGPnWOP2/0UOp3wmrJEnS3FPfuHPviiIPP93cQZWU9NRDKK1ZRemMVSR9ldY2Ugte\n9bsPFjugnjFjUy2W0mcP7Zg4H8Xy9gz1UOs0VcQIITwFrAS+ST43xm8AX48xbmth26QZUx/Jpi1g\nTFR7ImPow7tY8Xs9JBV7ZEiSpNmVZRnZEzuo3f5UXrh4YkdzB/aUKZ1xSD5U5JSVJN1N/+1SOmjZ\n1ia/Tw9Eb2XqYR6NIsVcG+qhmdfsu9m/A+eTT/A5BGwBNoUQvh9jbFOfH+nAjXxtfL8FjN2qj9UZ\n+VaVvvP8K4UkSWq/rJ7RVhiPAAAZvElEQVRRf3iI+u0bqK3fSLZ5uLkDl3RROnMVpTWrScMASdme\npZolB1NEWNpLsqIx1KM/X8njGT0peh3qsdA1OyfGrwKEEI4ELiAvaLwJODSE8K0Y48ta1kLpIGX1\njJGvVQsdM/JVixiSJKl9slqd+g8H86Ei6zfA07uaOi7p7yFdm68okh7X71+gNSekhy2n/sMNhY7p\nevMFpOEwh3pov4r2K3sC+CFwJHAUcHTjX2lWZVlGNgy1LXVqWzPqW7M9n9c21KltLjbGrvpYnfqO\njHSxPwhIkqTWyMZq1O/dkhcu7twIO5ubCDE5dNHepVCPXOpSqJpzSj9+YqEiRnL0AKXTj2hhizSf\nNDsnxjvIe2CcA9SBm4B/Ad4YY3ykyAVDCOuAjwKnAfcBl8YYv7OP/S8EbgCWxBib7Eun+SarZ9SH\nsrwosTWjvrtA0ShW1LdmZM39waL5a45mYBFDkiRNku2qku0cz/9ivLhSqIiQjVSp3b0pHypy9yYY\nqzV1XHLU0j2Fi/TQxQfadKktSmuOorpyCdnm7U3tX/mJ01vcIs0nzfbE+AXgS8D7gG/EGIv1zW8I\nIXQD1wF/ClwDvA64LoRw7FQFihDC8sZ+mueysd0Fijq1LY2eFBN6U9QHs7x81kZJnwUMSZKUy7KM\n+r1bqH7lEep3b9qzkEKyspfSuUdRPueIaVf9yHaMUbtjI7X1G6jfuxmqTfQQTSA9rj8vWqxZTTrQ\nO4NfjdRaSblE15vOZ9cVN8COff+lsfzSMyitsXO/mtfsnBjrZuh6FwC1GOPVjccfDyG8HXg58Jkp\n9r8S+BTwjhm6vmZBlmVkO8kLFFsz6lsaxYnBjNqWvHCRNVekbZvK8SmpRQxJkkQ+X8X4J++m9u3H\nn/3c5hGqn49Uv/Iw3W89m/TwJQDUB0eor99I7fYN1O/f2tzqkaWENAxQWrs6Xwp1afcMfyVS+6SH\nLaf7ty9i/F+/R/3ux56VgWTFIsovO5Py80+YnQaqY7V7raWTgXsmbYuN7c8QQngtsIx86Mk7W980\nHaisllF/enfPiYx6o1ixu0DRiqEe00l6oTSQkq5IKO3+GEgZf6TG8A3NdyDqPd9JPSVJUm78n38w\nZQHjGYZ2setD/0X5nCOpxS1kjzzd3MkrKelph+RDRU4/ZNreHFInSgeW0P3mC6hv2U5t/aOwbQQq\nJdJjVpKe8hyS1BV0VFy7ixiLgMnDRoaBvokbQghHAe8ln4Ojh+Zq1/NG9ck6o7dVqW/LSLoSKsel\ndJ9RIinNTs+APUM9tkzoSbF175wUbRvqkUC6LKHUn5AOJJRWpJQG8kJFOpDm//ZOfY+615QY/2Gd\n8Yf239CukNJztrMiS5IkqD++ndrXH21u553jVG94cP/79ZYpnbEqHypyykqSLn/u0PyWDiwhffGp\ns90MzRPtLmIMA5MH9PUBO3Y/CCEkwN8D744xbgghHNN4qunf4EMIA8DApM2HF21su1WfrLP9U7sY\ni8/+RTvtT1j8igq9585sdf4ZQz22TNGTYrCNQz3K7Ok9kQ6klPqTvEixu2fF8oSkcmCFnKSSsPzX\nexj6yCjjD05fyOgKKcsu7VmQy5N1am6k2WRupOI6LTfVr/1oZk60pGvvxJwnriAp+xdoNa/TciO1\nUruLGD8ALpu0LQDXTnh8BPA8YG0I4UogJS9gPBpCeEWM8ZtNXOdtwHtmoL1tM/6jGoMfHCWbZv2V\n+mDGtn8co7Y1Y/Eru5o+756hHlsmrerRKFDUtmQwNkNfxH4kfVBaMWGoR6P3RGkgIV2RkC5JWlo8\nSBcn9P9OD6PfqzHy1XHGH2gUMxKonJjSd36F7nWlBVnAaOi43EhzgLmRiuuo3NTv2XTAxyYDvZTW\nrCZdu5r02OUL+WcMHbyOyo3USu0uYtwEdIcQLgOuIl+dZBXw5d07xBgfJR92AkAI4WjgIeDwGONI\nk9e5AvjkpG2HN64/52RjGUMf2TVtAWOindePUz4qpWdtec+xu+ee2LuqR31v0WKozUM9VjSGevQ3\nhno0hn2k+xjq0U5JKaH3eWV6n1cmG8uoj0LaA0nX7LdtDuio3EhzhLmRiuuo3GTD44WPSc84hMrF\nJ5IcsaTQ8qvSPnRUbqRWamsRI8Y4FkK4iLyAcTlwP3BJjHGk0esiizG+dYpDMwoMJ4kxbgG2TNwW\nQmhTf4PiRv6rmhcbmrTtE7vYef14vqrHjv3vPyN2D/UYSEhX7O1BsadnRX9CUu6s/6STroRS851a\n5r1Oy400F5gbqbhOy03SUyEbrRU6pvyCI0iPXNqiFmkh6rTcSK3U7p4YxBjvIp+wc/L2S6fZ/xFg\nXs92NPr15lfNAMh2QnXnzHav2D3UY/fQjsmTZqaLsQukJElacNKTB/a/MslE5ZT0+P7WNUiSFri2\nFzH0bNUnWzzeY/dQjykKFHNpqIckSdJcUz7vqEJFjNJZh5IstqunJLWKRYy54GAXkK1MWNVjUoGi\nNJCQLu+8oR6SJElzQXr0MkpnH0bte0/uf+e+CuWXn9D6RknSAmYRYw4oDSRUnyhWyVj8qgpdoZQP\n9ViCk0ZJkiS1SOWXTicbq1G/Y+P0Oy2q0H3pc0kP6WtfwyRpAbKIMQf0PL/Mjs82P/N16bCEvpdW\nLFxIkiS1QVIp0fWmddRufZLaV39E/cGhvU8urlD+8SMov+hokuU9s9dISVogLGLMAb3nVNj5hXGy\n0eb273uxBQxJkqR2StKE8tnPoXz2c8ieHiXbNgZdKcnKPpJSOtvNk6QFw3fcOSBdnLD0Dd1NvRrd\nzy3Re661J0mSpNmSLOshPXIp6erFFjAkqc18150jetaUWf7r3aTLp+lhUYK+C8sse2O3S51KkiRJ\nkhYk/6Q/h3SfVmbl5SV2ra+x69Yq9W0ZdCV0HZ/S8+NlSsusOUmSJEmSFi6LGHNMUkroOatMz1m+\nNJIkSZIkTeSf9iVJkiRJUkewiCFJkiRJkjqCRQxJkiRJktQRLGJIkiRJkqSOYBFDkiRJkiR1BIsY\nkiRJkiSpI1jEkCRJkiRJHcEihiRJkiRJ6ggWMSRJkiRJUkewiCFJkiRJkjpCud0XDCGsAz4KnAbc\nB1waY/zOFPu9CfhdYBUQgd+OMX69nW2VJEmSJElzR1t7YoQQuoHrgGuAZcAVwHUhhL5J+50P/C/g\nZ2KMy4GPAP8WQuhvZ3slSZIkSdLc0e7hJBcAtRjj1THGWozx48AG4OWT9jsC+MsY450AMcZPADXy\n3huSJEmSJGkBavdwkpOBeyZti43tezfE+E8TH4cQzgEWT3GsJEmSJElaINrdE2MRMDxp2zDQN8W+\nAIQQTgU+A/xhjHFrC9smSZIkSZLmsHb3xBgGeidt6wN2TLVzCOElwKeB98cY39/sRUIIA8DApM2H\nF2intOCYG6k4cyMVZ26k4syNtFe7ixg/AC6btC0A107eMYTwK8AHgTfHGP+54HXeBrzngFooLVzm\nRirO3EjFmRupOHMjNbS7iHET0B1CuAy4Cngd+RKqX564UwjhQvIVSX4yxviNA7jOFcAnJ207vHF9\nSVMzN1Jx5kYqztxIxZkbqaGtRYwY41gI4SLyAsblwP3AJTHGkRDClUAWY3wr8A6gAnwxhACQABnw\nszHGG5q4zhZgy8RtIYSxGf1ipHnG3EjFmRupOHMjFWdupL3a3RODGONdwDlTbL90wucvbWujJEmS\nJEnSnNfu1UkkSZIkSZIOiEUMSZIkSZLUESxiSJIkSZKkjmARQ5IkSZIkdQSLGJIkSZIkqSNYxJAk\nSZIkSR3BIoYkSZIkSeoIFjEkSZIkSVJHsIghSZIkSZI6gkUMSZIkSZLUESxiSJIkSZKkjmARQ5Ik\nSZIkdQSLGJIkSZIkqSNYxJAkSZIkSR3BIoYkSZIkSeoIFjEkSZIkSVJHsIghSZIkSZI6gkUMSZIk\nSZLUESxiSJIkSZKkjmARQ5IkSZIkdYRyuy8YQlgHfBQ4DbgPuDTG+J0p9vsF4M+AVcDNwK/GGDe2\ns62SJEmSJGnuaGtPjBBCN3AdcA2wDLgCuC6E0DdpvzOBK4GfB1YCG4CPt7OtkiRJkiRpbmn3cJIL\ngFqM8eoYYy3G+HHyAsXLJ+33i8DnY4zfizHuAt4JvCyEcEib2ytJkiRJkuaIdhcxTgbumbQtNrZP\nu1+McSuwFQgtbZ0kSZIkSZqz2j0nxiJgeNK2YaDvAPebUghhABiYtPlIgKeeeqqphkpz1YUXXngM\n8FiMsTqT5zU3ms/MjVScuZGKMzdScUVz0+4ixjDQO2lbH7DjAPebztuA90z1xGtf+9omTyHNWQ8B\nxwIPz/B5zY3mM3MjFWdupOLMjVRcody0u4jxA+CySdsCcO0U++0ZOhJCWAn0N7Y34wrgk5O2dQFH\nkQ9fqTV5ntl2LHAT8GLyF1Yzq5Pv72MtOKe5UTM6+f6am+l18uvaCTr5/pqb6XXy69oJOvn+mpvp\ndfLr2ik69R43nZsky7JWNuQZQghdwAPA+4CrgNcBlwPHxhhHJuy3BvgKcDFwK3loV8cYX9m2xs4B\nIYSTyN+UQozxvtluz3zj/Z2ffF1by/s7P/m6tpb3d37ydW0t7+/85OvaegvhHrd1Ys8Y4xhwEfnq\nI1vIe2VcEmMcCSFcGUL428Z+64E3kS+r+hRwKPCGdrZVkiRJkiTNLe0eTkKM8S7gnCm2Xzrp8WeA\nz7SrXZIkSZIkaW5r9xKrkiRJkiRJB8Qixty2BXhv41/NPO/v/OTr2lre3/nJ17W1vL/zk69ra3l/\n5ydf19ab9/e4rRN7SpIkSZIkHSh7YkiSJEmSpI5gEUOSJEmSJHUEixiSJEmSJKkjWMSQJEmSJEkd\nwSKGJEmSJEnqCBYxJEmSJElSR7CIIUmSJEmSOoJFjA4UQjhmttuwEIQQDg8hmJF5wty0h7mZX8xN\ne5ib+cXctIe5mV/MTXvMl9yUZ7sBKiaEsBb4AvCc2W7LwQohHA08BCyOMQ7PdnsmCiGsAiKwCphT\nbVNx5qY9zM38Ym7aw9zML+amPczN/GJu2mM+5abjqzAL0HLmV/Epm+0GTKMP6AWS2W6IZoS5aQ9z\nM7+Ym/YwN/OLuWkPczO/mJv2mDe5SbJsrt7juSGE8Brgd4Bjyb8h/wUYARbFGN/S2OcbwCMxxl9s\nPP4S8Cng/wJ/BfwkcBjwOPC7McbrQgg3Av8ZY/zzxjH9jeePjTFumKYthwCPAD3ADuDoRlv+Enh1\nY7dPAe+KMVZDCD37uP6LGs/9J/CmxvneClwIvB4YBN4YY7z5oG7gPkyoVP4h8AZgBXBNjPF3Qggn\nAB8EzgG2AlfFGN/fOO5m4AbgNcDxjc8/AFwJHANcD7w2xpg17uvfAC8BdjbO8xdNtG1zoz07gBcC\ndwJ/APwKefj/HXh7jHF7CCEB/gT4WeBw8nv3v2KMVze+xu8BlwO/R/6m8XvkFdDfAqrAb8cYP3Ug\n93CuMjfmBnNTmLkxN5ibwsyNucHcFGZuzA0dnht7YuxD4wW6GnhLjHGA/MX+BeDfgJ9o7LMIOA14\nUeNxH/k35vXkbw4BWAcsAf4euKJx+muBn5twuf8O3DJdwAFijJuAi4DNMcalMcZB4H8DJwGnA2uA\n5wLvbhyyr+vT2P5UjHEF8A/A58hDtxL4NPC+Zu7TDDgUOBk4H7gshHAeeXDvIg/DxcBbQghvnnDM\nLwMvJQ/1i4CPNh6fRv6m9rLGfv9EHqSjG+d/bQjhl5to03PJ39RXxxjXA78N/DT5a3s8eSVz9718\nLfAq4LwY41LgXcBfN74XAAaAI8m7yP0+cFVj22Hkbw4faqI9HcPcmBvMTWHmxtxgbgozN+YGc1OY\nuTE3zIPcWMTYt8eB02OM3w8hrCB/YQbJX7CBkE9Acx5wI1APIZwEXADcGWPcDHyYvHo1DBwFbCev\nZAF8BjipcQzkbx7XHkAbXw+8M8Y4FGPcArwX2B2GfV0fYIy932A3A9UY49/EGGvAf5AHo9Uy4M9j\njOONMEXy4C4D3h1jrMYYI3k19vUTjrs2xvhU4z7fDXy68fgx4B7g6BDCavKw/1aMcTTG+CPyiubE\nN4v92d3d6g3Ae2OMT8QYd5IH+ZdCCF3A54EXxxg3hRAOB3YB3eSVzt1f41817utN5Lnb/fjL5N9L\nPQXaNNeZm9YzN+bG3BRnbsyNuSnO3Jgbc1OcuWlxbubT2KNWqJFXyN5AHpBbgUrjuRvIK2KB/IUb\nJQ/4GeSVTMjHd/0t8DzgfvIqYAIQY9wWQrge+PkQwjXA2cAlRRrX6H7VC3wlhLB7XFACVBrffNNe\nv2F7jLE+4WvdPuG5Ou0rcg1N+HycvKL3+IS2Qd7N7IgJj7dO+Lw26Ry7234U+df7QKNLVNbYvuUA\n2ngU8IkQQq3xOCEP81GNtnw4hHBho53rG/tMvH+DE9oK8PSEtk7et9OZm/YwN+bG3BRnbsyNuSnO\n3Jgbc1OcuWnhvZ5PgWyF15B3gzozxnhSjPE15C8s5N2pLiTv6vMV8krfBeRdfv69sc9VwL3Ayhjj\n84CPTDr/teSVxFcD18cYdxRs35ZGe9bFGFfEvNvUYcBpMcaxJq4/VydESYHnhGcu/3McMLErWjNt\nf5L8TWNVjLG/cX+OIu8216zd13kC+KkJ93kAOBN4EPjzxj6HxhjPAv5oH+dZCMzN7DA3nc3czA5z\n09nMzewwN53N3MwOczODLGLs21Lyb5LxEEJ3COEd5F2BKsAXyceNHR5jvJu8WvkKoBxjvHPC8SMx\nn4DlSPLxQYQQSo3nv0De/emNNN/VahfQE0IoNyp51wJ/EUJY1hij9DHgE01efy6YanbcDY2PPwsh\ndIUQTiYf//ZPRU7c6Hp1C/D+EEJPo8vcZ9kbyn3Z/Wa+rPHvJ4A/DiEcGkKoNM7x5cZzS8kr1fUQ\nwgB5ly7YW9We/DXu73GnMzetZ27MjbkpztyYG3NTnLkxN+amOHPT4txYxNi3fyAfj/QwcAf55DEf\nA06JMW4k78J0C0CM8UFgE3urlABvBy4JIWwln8n3L8i7NJ3SOGacfDbgI8nfNJpxB/mYqK0hhOOA\n3wR2j5t6tNHGn2/m+nPE5ApeRv7Gegn5RD5PkY9f+1iM8UP7OGa6x78ArCZ/DSPwGHDZ/hoVY3yK\n/DX5YQjhfPLZd28Bvg1sJO8ed3HjjfaPgBPJX4f/IB9Ddg9773OR9s4H5qb1zI25MTfFmRtzY26K\nMzfmxtwUZ25anBuXWJ1lIYR3k1c73zrbbZE6hbmRijM3UnHmRirO3KjVnNhzloQQVpIvZfNm9q6B\nLGkfzI1UnLmRijM3UnHmRu1iEWP2vJB8HNKHY4zf370xhPAdpu8OdUuM8eJ2NG6+CyH8M/ma1JO7\nIiXAwzHGM9rfKjXB3Mwic9OxzM0sMjcdy9zMInPTsczNLFpIuXE4iSRJkiRJ6ghO7ClJkiRJkjqC\nRQxJkiRJktQRLGJIkiRJkqSOYBFDkiRJkiR1BIsYC0QIoR5CeMkMnOfmEMLlM9Emaa4zN1Jx5kYq\nztxIxZmbhcslVheOQ4Gts90IqcOYG6k4cyMVZ26k4szNAmURY4GIMW6c7TZIncbcSMWZG6k4cyMV\nZ24WLosYC0QIoQ68LMZ4QwjhPOCvgFOBTcDfxRj/tMDpDg0hfB54CbAReHeM8drGdbqAPwT+B7AK\n+BbwP2OMdzWevxn4EnAucCHwYGPfi4C3A3Xg8hjjhxr7l4E/b+zTDXwd+I0Y40MHei+kZpkbqThz\nIxVnbqTizM3C5ZwYC0wIIQU+C1wPBODXgHeGEC4pcJpfAr5I/ibxr8A1IYT+xnMfAX4ReCNwFvA4\ncEMIYfGE4/8A+DRwBjAE3AicApwDfBj4QAjhsMa+lwPnAz8NPB94ArgphNBdoL3SQTE3UnHmRirO\n3EjFmZuFxyLGwrMMWAFsiDE+GmP8IvATwHcLnOO6GONVMcaHgT8BuoDTQgjLgNeTVxJvjDHeSx72\namP7bv8ZY7w2xvgAcC2wFPi1GON9wPuBEnBSCKEHeFvjuW/HGCNwKXkPop85sC9fOiDmRirO3EjF\nmRupOHOzwFjEWGBijIPAFcCHQwhPhBA+BnTHGJ8qcJoHJpzv6canvcBJ5N9T/zXh+XHyN5BTJxx/\n/4TPh4HNMcadjf1HG9u7geMb/34lhLA9hLAdeJp8Ep9QoL3SQTE3UnHmRirO3EjFmZuFxyLGAhRj\n/J/kIfkr4ATgxhDCmwucojbFtgQYnWI75JXH0oTH45Oer09z3O45W84H1kz4CMCHmmmoNFPMjVSc\nuZGKMzdSceZmYbGIscCEEI4OIVwJPBZj/ECM8QLgY8DPz8DpHyDvWvX8CdfrAs4G7j2A893fON/q\nGOODMcYHgUeA9wFnHnxzpeaYG6k4cyMVZ26k4szNwuPqJAvPFuDngEoI4X1AP3Ae8O8He+IY43AI\n4W+Bvw4hjJBPUvMuoId8bFjR8+1snO8jIYS3AA8Bvw+8mHwsmdQu5kYqztxIxZkbqThzs8BYxFg4\nMoAY444QwiuADwC3kY/Z+mfgj4qcZx/b3tl4fC3QB3wDOC/uXcd5quP3db53kHfv+gdgMfB94Cdj\njBuabK90MMyNVJy5kYozN1Jx5maBSrKsmXsuSZIkSZI0u+yJoT1CCAPs+3tie4xxuF3tkTqBuZGK\nMzdSceZGKs7czE8WMTTR18mXEZrOu4C/bFNbpE5hbqTizI1UnLmRijM385DDSSRJkiRJUkdwiVVJ\nkiRJktQRLGJIkiRJkqSOYBFDkiRJkiR1BIsYkiRJkiSpI1jEkCRJkiRJHcEihiRJkiRJ6gj/H2k3\nTUqoXtqNAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115d4d400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.FacetGrid(wins.reset_index(), col='team', hue='team', col_wrap=5)\n",
    "g.map(sns.pointplot, 'is_home', 'win_pct');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Those two graphs show that most teams have a higher win-percent at home than away. So we can continue to investigate.\n",
    "Let's aggregate over home / away to get an overall win percent per team."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "team\n",
       "Atlanta Hawks        0.585366\n",
       "Boston Celtics       0.585366\n",
       "Brooklyn Nets        0.256098\n",
       "Charlotte Hornets    0.585366\n",
       "Chicago Bulls        0.512195\n",
       "dtype: float64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "win_percent = (\n",
    "    # Use sum(games) / sum(games) since I don't\n",
    "    # know if teams play the same number of games at\n",
    "    # home as away\n",
    "    wins.groupby(level='team', as_index=True)\n",
    "        .apply(lambda x: x.n_wins.sum() / x.n_games.sum())\n",
    ")\n",
    "win_percent.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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37t3buxrtLgJU6BKGDx8e9+ILHcZ8uCdehxRdfCGEEEopAlQIIYRSigAVQgihlCJAhRBC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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115ef76a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "win_percent.sort_values().plot.barh(figsize=(6, 12), width=.85, color='k')\n",
    "plt.tight_layout()\n",
    "sns.despine()\n",
    "plt.xlabel(\"Win Percent\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Is there a relationship between overall team strength and their home-court advantage?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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MgYnJ7IxrSAMHqy9pvrq3bWqGtL2/h819VtLcNId5f0tFZA3wsKq+UkReAVzv\n39z6PismaExtZbL5EzY2HKmypHl3R2wqIBWX7bqtpLlpUnNtnPht4PPAWmBMRP5YVT8HnCMiFwCf\nEpFhXLB6tDHDNUGx2BxwtchD1+zy+QIH/MzfxWtJB49OUKiipnkiHmHL+u6pzN9b+6rL/G3/Dibo\n5ppJ3Qj8OS6P3cuBe0Tkn1Q1par/BvybiPwOrlT7r9d/qCZIFpsDrhZ56JqJ53kc9kuaF5fsFlTS\nfF1Z5u/Viytpvtz+HUzzmStIdQHP+jn1BnD58uLA1E0VqvoN4Bv1HKAJpsXmT2v1/GvHx9Izluz2\nDY6SrCLzdwhYv7pj+jpSnUqat/q/g2l+cwWp9wNfF5FjwCrgY6o62phhmaBbbP60Vsq/lkxl2Tc4\nxr6Do+z1t38fH6su8/fKnsT0DbL9PWzp62lISfNW+ndodsXaZaVFR8s/pgqVEjqhrlrxc2n72Wqv\nFZ+bKsRZKLiiqR5M1Qzwy9WEZkljVaxKUIsKBZWYawv6zSLyZeAFwH5VPVj30Zimsdj8ac2afy2T\nzfPc4fEZs6RDx8qLQc+tsy064+bYrf099HbNnfm7XoL+71B8M53xRg0V1yeb8WZcXp262GchX3zf\nJxxiRgHOEEwVsywtcjnzZ8w9htJq1iG/oGexmnXxeDgUIhKPTLcFQuHIVAFQ933hGYEon8+7++A8\nzy/C6Qbixh8hFApRyOfJ5fPk/QAYAsKREKFQmGg0SjQSnqqUXayZBtOVpPP5mbc1FAruZ+F55AsF\nCoWsOz/+8YLn2hTHEgqFGD+2f2Lef6i5zt/JylmbaSKyDdh7x11309cfrP/Epn6KJc33HRxj4OAI\nAwfHeP7I+MJKmvf3sLW/m20belmzzEqa53I5ctkMnpcnGg5PVV0Oh6YLVpaanhm463DRaNT91e6/\nYQNkszmyuRz5gp+O/ST9RPzqzu6NODTjuUZVejaz/etUzm6UMAa/pPlIym1qODDKwMGR6kuah0Js\nXNfFtv5utvX3LouS5lN/0WezUMgTDkMkEibiB6JoJEx3V5z2tk6i0agFAlO1QAUpEdmB2y14KvAU\ncOVc92KJyDuBl6vqZSXHrsEVPEwzXRDxolmq+JplbHQizcDBsRlZGyYmq8v8vX5Vh7sXqc/VSNq8\nvn6Zv4Mik05TyGdJxCNEI2Fi0TCx9hhtiQ5isZgFIVNzgQlSIpLA5QG8HrgVV/p9t4hsV9VkWdsO\n4APANcBjK3cYAAAfHklEQVS/lHW1A3iXqn6q7oM2TWEynePZwdEZQenYaHWZv0tLmhcDU2lJ81aT\nyWQo5LKEQ97UzCgaCbNiZTsdHassGJmGCUyQAs4F8qp6i//4Nn+mdDHw5bK2XwHGcbOutWXP7QA+\nW8+BmuDK5go8d3jmDKnqkuaJ6IxsDZWUNG92LihlSMQjxKJhenvb6OhY0ZDdW8bMpaIgJSIvAD4G\nnIm7X2rGn1GqWovdBKcAT5QdU/94uStUdVBErqMkSIlIOyDA1SJyO3AM+ISq3laD8ZmAKRQ8Bo9N\nTGX9Hjg4xnOHxtzF9AqVljQvBqW1K9tbPvN3oVAgm04RCXnEYmHW9HbQ1bnSZkgmcCqdSd2GCwZ/\nDdTrXqlOoHwvbxLoKG+oqoMn6WM98J+4bBmvAc4C7haRA6r67RqO1TSY53kcG02V3SBbXUnzUAg2\nrOmaUaxv49pOIssk83cmncbzryd1JKL0rl5FNBqkxRRjTlTpb+iZwJmq+uM6jiUJtJcd68At61VE\nVQdwy4ZFD4jIF4BX46oJz0tEVgOryw5bnpgGG/dLmpemEaq2pPmaFe0l9yJ1s2V9D4l4a29sKCoU\nCmTSKUJegWg0TDwWYV0NricVCh57HnmWgcFRtvX1cP6ZWyzXn6mrSoPUPqCnngMBnsTVqyolwO2V\nduDXv3qlqn6s5HAbUM3NZFcB11XR3ixSKpNjf1nm76MLKGm+1a+NVFy661pGJc1zuRy5dMoPSGHa\n4zHWr1xBPF7b7Od7HnmWex7aC8ATzwwBcMFLt9b0ZxhTqtIg9W7gRhH5IPAzYEYxG1V9qgZjuQ9I\niMhO4Gbc7r51VDgD8o0C7xORp3CbK84DXgu8ooo+bsAl1S210R+fWaR8saR5ycaGg0cn5r1rv1Rb\nPDIVkIqfVy6zkuaFQoFMKkUk7BGPRVjZmaBr/bq6b3QYGByd87ExtVZpkPqXss8wfZ+3Byx6DcVP\nZHsRLkB9FHgauERVJ0VkF+Cp6tvn6eNpEbkUt8njc8B+3CaLx6oYxxAwVHrMr59lqlRa0nw683e1\nJc1DbFznNjZs92dI61cvv5LmuVyObDpFLBIiFovQmYjRvwTXlLb19UzNoIqPjamnitIiicic83lV\n3VezEQWQpUWan+d5J2T+Hqi2pDmupHnp1u8Ndcj83Qyy2Sy5TJqYv3zX0Ranq6uzonx19WTXpMwC\n1D8tUqsHIVO9icmsv+17dGoL+Mh4dRPOVT1tU9eQtvX3sGV9N20NyPwdVLlcjlwmRVs8wqrudro6\newN3n1I4HLJrUKah5qrMewA4TVWHROQgnPx+yBrdJ2UCKpPNs//Q2IzrSEeGqytp3tUeOyHzd0+n\nlTQHSKdSREJ5VnS309O3flldWzNmPnP92fpuprd/v5s5gpRpHflCgQNHJmYs2x04UmVJ81iELX3d\nM4JSNSXNlwPP88ikJolFPPrX9NLe3rbUQzImkOYKUof959Oq+o+NGY5pJM/zOHJ80s/6vfCS5i7z\n9/QMqX+RJc1bWTabxculaUtE2dy/klhs+WyTN2Yh5gpSdwN5Efkv4H7cFuyHVLW6dR4TGCPj6Rk7\n7QYOVlfSHKBvdYfb9u1nbdi0rotYdHncILsY6XSKCHlWdrfT02NLesZUaq4gtQp4OfAy//NVQFxE\nfoALWvfjgpZtzw6gyVRuemODH5iGqyxpvqJ7ZknzrX09tLct340N1SoUCqQnk7TFw/St6qajozyh\nijFmPnOVjx8FvuV/ICJh4FdwQess4H8Dm0Tk+6p6fgPGak4im8uz/9D4zMzfVZY072iLzliy27aE\nJc2bWWl+vM62OBvWrF3ybePGNLOK/yxW1YKIDANjwCQwjMvEsKpOYzOzKBQ8Dg6VZP4+MMpzVZY0\nj0XDbPEL9RU/1qxoD9QSVKHg8b3HD/D8kXE2ru3iZadtCOR1Ls/zSE8miUagLR5l1eoO2tsbN2Nq\nhfuWWuE1LLVWPodzBikRWYdLLXS+/3kbLsfed4C/Ar7rZ2gwdeB5HkMjMzN/Pzs4Rjpb+Q2y4VCI\njWv9G2Q39LCtr4f+tZ2BL2n+vccP8N1HnwPg6f3HATj7V4KT5zeXy1HIpuhoi9G3cfWSZRNvhVx6\nrfAallorn8O57pN6HHgRLj3Rd4D3Aver6qHGDG35GZ3IzFiy23dwlPEqS5qvW9k+Y+t3s5Y0f/7I\n+JyPl0I6lSLk5YjHo/R2xOkNwAaIVsil1wqvYam18jmc68+/U4EDwDdxmyS+o6ojDRnVMpBK59g3\nODYja0O1Jc17u07M/N3ZIiXNN67tmppBFR8vlVRygngsRP+a7oYu5VWiFXLptcJrWGqtfA7nClJr\ncLWZzsct7f2CiPwItxX9fuA/VLW6q/PLVDZXkvnbv5Y0eHSiqruj2/2S5tv6u0syf7fuDaAvO80l\nMSm9JtVInueRmUzSlgizuX9lzUte1Mr5Z24BmHEtotm0wmtYaq18DitKMAsgIpuYvjZ1DtAHPALs\nUdWWrr9UTYLZgudxaCg5I4XQ84fHyOUrD0nRSJjN67tm7LRbt2r5Zf5eCrlcjnxmks6OOGtWrbCd\necYsXv0TzAKo6nPA50TkbuDXgf8JvAG3Jb2lg9TJeJ7H8OjMzN/7BkdJLaCk+db+6d12G9d2LZuS\n5kGRz+fJZybp7W5nZV/fkl9rMsY48+3uiwE7gJeWfPwC8HPgP4C3A9+t8xgDYyKV5SfPDDFwYISB\ng2MMHBxZYEnz7qmsDZv7ummL2w2yS6VQKJBLJ+npSrBq/dJvhDDGzDTX7r4fAKcBCUBxwej9uG3n\nB+oxGBHZAdyE27TxFHClqj48R/t3Ai9X1csW2kc1PnrbD4h1VH5bWHdHbPpepA29bO3rpqsjmNc2\nlpviFvLuzgSr1ta/oq0xZmHm+hP+B8DHcRsk6r7tXEQSwG7geuBWXPn43SKyvXyDhoh0AB8ArqGk\nWnA1fdRaW3xm5u/t/b2s7FleJc2bQSo1STRUoLe7nRW9fUs9HGPMPOZKi/SORg4Et5Mwr6q3+I9v\n82dKFwNfLmv7FVwZkZuAtQvsY8Ei4RCb1nX5W7972drfTd8qy/wdVMWsEIl4mP7VXZZDz5gmEqSL\nIacAT5QdU/94uStUdVBErmNmkKqmj6pd8hvbOf20F7JxmZY0bzalO/X6N62xnXrGNKEgBalOoHxJ\nLgl0lDdU1cHF9nEyIrIaWF12eCPAWadtoK+/dW6Sa1XZTIZQIUNvTwe9tlPPmKYWpCCVBMrXYTqY\nrg7cqD6uosm21DdLMtZ6y6TThL0sq1d00d1d+7zHzZDEsxnGaEw1Kg5S/qaE1wAC/C3wEuDJGm6q\neBLYWf5jgdsb3McNwB1lxzbiMm0EUtCTsdZbatKVYV+zopPurvJJcO00QxLPZhijMdWoKEiJyHbc\nm3QUl2nic7h7pM4TkQtU9b9rMJb7gISI7ARuxu3MWwd8u5F9+FndZ2R2F5FAF3YMYjLWeituhmiL\nh9m4rpu2tvqniGqGJJ7NMEZjqlHp1f+/A+4FtgLFLKiX40rMf6oWA/Er/F4EvA4XJHYCl6jqpIjs\nEpEbF9NHLcYYVOXJV5cyGWu9FQoFUslxIl6arRtXs7F/bUMCFJyYtDOISTybYYzGVKOi3H1+scOz\nVFVFZAz4FVV9RkR+CXhUVbvrPdClVE3uvqWwHK5JZTMZyGfo6kywamXvktx82wzXe5phjGbZaUju\nvjSwcpbj26luU4Kpg3A41LLXoNKTSSJhj1U9HfT0LG0R6HA4FPjrO80wRmOqUWmQ+gJwg4j8kf94\npYhcDHyGEzcZGLMo+XyeXHqStkSEjet7SSQSSz0kY8wSqTRIvRv4KPAALpffI0AOuNF/zphFKy7p\n9XS3s9KSvRpjqDBIqWoOuFZE3g+8wP++p1V1op6DM8tDMZ9eEJb0jDHBUs19Uv3AC3EzKYD1IgKA\nqt5b+6GZVpdKTpCIhdiwpof29tatMmyMWbhK75O6GvgEMFvyM+8kx405QaFQIJNK0p6IsGXDKmKx\n2FIPyRgTYJXOpN4DfAj4uKqm5mtsTLli5dvOjjgbN1v9JmNMZSoNUmHgnyxAmWoVg1N3Z4LVLbYZ\nIpcr8Om7fsTegyNs7+/lHZedTrTB2fHtvijT6ioNUp8C3icif2SbJUwlctkshVy6pcuyf/quH/HA\nY65I9fOH3X+LP7n8jIaOwXL1mVZXaZD6JvCnwIiIHAUKpU+qavDSMJglkU6niJBnRXc7vS1e+Xbv\nwZE5HzeC5eozra6am3mfwGUTr2sZdtOc0pNJ4lFYv7KLzs6Ky3c1te39vVMzqOLjRtvW1zM1gyo+\nNqaVVBqkfgE4TVV/Xs/BmObieR7p5ATtbRE29a0gHo8v9ZAa6h2XnQ4w45pUo51/5haAGdekjGkl\nlQapPcBZgAUpM7UZoqM9Rv/mtcu2LHs0Gm74NahylqvPtLpKg9QDwE0icinwNJAtfVJV31PrgZng\nyWWzeLk0Pd1tlrbIGNMQlQapC4EfAiuAXyt7bv5aH6apZTJpwoUsK3s76emZLRm+McbUR6W5+86t\n90AARGQHcBNwKvAUcKWqPjxLu8uBD+Oq7t4PvEVVD/vPXYNLhpvG1THxgItU9cFGvIZWkk6liIYL\nrF3RRVdn/cqyG2PMyVSTu68L+D/Ai3BpkH4K3F4MDoslIglgN3A9cCuu9PtuEdmuqsmSdi8BdgG/\nBTwOfBq4Dfgdv8kO4F2qWpOKwctRejJJLOLRv6bXcuoZY5ZURbfHi8iLcTOba4H1/sc1wBMi8qIa\njeVcIK+qt6hqXlVvAw4BF5e1ex3wVVX9oaqmgT8HLhSRtf7zO4DHajSmZcPzPFLJCchNsqlvBZs3\nrrcAZYxZcpXmcPlb4N+BF6jqa1T11bht6d8EPlmjsZyCuxerlPrHT9pOVY8BxwARkXZAgKtF5KCI\n/ERE3lSj8bUkz/NITYwTLqTYunE1G/vXLrut5MaY4Kp0ue9lwBmqOrWrT1UzIvKXwAnXjBaokxNv\nFE4C5XeGztVuPfCfuGKMr8Ftm79bRA6o6rcrGYSIrAbKL8C0XG32YjbyrmW+jdwYE2yVBqnDuDfq\nn5Yd30DtMlAkgfayYx3AeKXtVHUAt2xY9ICIfAF4NVBRkAKuAq6rsG3TKZZm7+q0bOTGmOCrJi3S\nLSLyx8AP/GNnAX+DS5VUC08CO8uOySz9P+kfdw1E1gArgSdF5Azglar6sZL2bUA1SXFvAO4oO7YR\nuK+KPgInl8uRz0zS09XWctnIjTGtq9IgdT3QB3yV6etYOdyy2rtqNJb7gISI7ARuxu3uW8eJM6A7\nge+IyGeBR4G/BO5R1WF/qe59IvIU8BXgPOC1wCsqHYSqDgFDpcdEJLOwl7T0pm/AbWdlX58FJ2NM\nU6lorUdVM6r6VmANbgZ1OrBSVd+pqjV5A/f7uQi3e28IN6u6RFUnRWSXiNzot3sMeCtu2/kgLnj+\ngf/c08CluOW6Udys6Ar/e5aVbCZDdnKc3s4I27b0sWplrwUoY0zTCXne7AkjRKTiTJWq+mzNRhRA\nIrIN2HvHXXfT1x/sqiTpdIqIl2PVii66u7uWejjGGLOov47nWu4bYP6UR8WMDrY1bImlUykioTzr\nVnbTtUxKZRhjWt9cQeqXyx6HcPn7/j+gpWdOzaRYx6l/TY/dfGuMaTknDVKqquXHRMQDfq6qz9R1\nVGZeqeQEiViIjet7SSQSSz0cY4ypi4pz95ml53ke6ckk7Ykwm/tXWmYIY0zLsyDVBFxwmqCjLcrW\njauJRu2fzRizPNi7XYAVCgWyqSSdHTH6N1nqImPM8nPSICUib5vlcAS4XESOlB5U1VtqPbDlrDQ7\nhKUuMsYsZ3PNpN49y7FDwFvKjnmABakacHn1kqzosewQxhgDc+/u297IgSxnxYzkPV0J1qy34GSM\nMUV2TWoJTZXL6IjZsp4xxszCgtQSKJbL6LTgZIwxc7Ig1UCZdJqQl6Wnq52VVi7DGGPmZUGqAVKT\nk0TDBdas6KK7q7zorzHGmJOxIFVH6ckk8ViIjeu6aWuzvHrGGFMtC1I1Vpq6aFPfCktdZIwxixCo\nICUiO4CbgFOBp4ArVfXhWdpdDnwYV7n3fuAtqnq4mj5qzfM80skJ2tsilrrIGGNqJDDbykQkAewG\nbgV6cVV1d4tIR1m7lwC7cGXh1+BuML6tmj5qqVAokEqOEyPDts1r2dC31gKUMcbUSJDeTc8F8iUp\nlm4TkXcCFwNfLmn3OuCrqvpDABH5c+CIiKwFfq3CPhatuI28qzNu28iNMaZOgvTOegrwRNkx9Y+f\ntJ2qHgOGAPE/KuljwXK5HOnkGB2xAtu3rGfdmlUWoIwxpk6CNJPqBJJlx5JA+VLdbO0m/XaV9nFS\nIrIaKN8nvhEgm5qguy1kefWMMaZBghSkkkB72bEOYLyKdpX2MZergOtme2LThrWsWtlbRVfGGGMW\nI0jrVE/ilutKzbZ8N6OdiKwBVvrHK+1jLjcwvXRY/Diviu83xhhTI0GaSd0HJERkJ3Az8EbcFvNv\nl7W7E/iOiHwWeBT4S+AeVR0WkUr7OClVHcJd45oiIpmFvSRjjDGLEZiZlKpmgItwu/eGgJ3AJao6\nKSK7RORGv91jwFtx284HgT7gD+bro8EvxxhjTA2EPM9b6jEEnohsA/bu2bOHTZs2LfVwjDGmmSxq\nl1lgZlLGGGNMOQtSxhhjAsuClDHGmMCyIGWMMSawLEgZY4wJrCDdJ2VMQxUKHnseeZaBwVG29fVw\n/plbCIct3ZUxQWJByixbex55lnse2gvAE8+4+7cveOnWpRySMaaMLfeZZWtgcHTOx8aYpWdByixb\n2/p65nxsjFl6ttxnlq3zz9wCMOOalDEmWCxImWUrHA7ZNShjAs6W+4wxxgSWBSljjDGBZUHKGGNM\nYAXqmpSI/Anwp0AXsBv4w9lqQYlIHNgFvBrIADeo6kdLnv8xsB3I49LED6jqafV/BcYYY2opMEFK\nRF4FXAP8D+Aw8CXgE7jCheU+CmwGtuKKHt4rIk+p6pdFpA14IbBeVYcbMnhjjDF1EaTlvjcAt6rq\nz1V1DHgf8PsiMluemjcAH1HVcVV9Gvg08H/8514CDFqAMsaY5tfQmZSIRHBLeeU84BTgX0uOqd92\nI/BcSR8rgHXAk2Vt3+5/fTqQE5GHgF8EHgX+RFV/WqOXYYwxpkEaPZM6BxgGjpV9/AjoAJIlbYtf\nd5T10YkLauVtS9v9AHgtbknwv4B7RCRRk1dgjDGmYRo6k1LVPZwkMIrIY0B7yaFi0Bkva1oMTu0l\nz3UUv1bVW4BbStq/V0R24mZYD883RhFZDawuO7wZYHBwcL5vN8YYU+L888/fBjynqrmFfH9gNk7g\nlu+k5PEpwLCqHihtpKrDInLYb3vEPyzAEwAi8jbg535ARESiQAxIVTiOq4DrZnvi9a9/fYVdGGOM\n8e0FduBWzKoWpCD1RWCXiPwr7hrUB4HbT9L2duADInIZsAZ4B27rOsB64CoRuQgYAv4f8KSqPlbh\nOG4A7ig79ovAN4DfAn5eYT+tajtwH3Ae7pdvObNzMc3OxTQ7F9OK5yK90A4CE6RU9esisg0XDHqB\nrwPXFp8XkTHgQlV9EPgL4JPAT4EC8DeqWtx08RGgG3ddqhP4LvA/qxjHEC64TRGZmuDtV9WBKl9a\nS/HvUQN43s6FnYsiOxfT7FxMKzkX+YX2EZggBaCqn8ZtJ5/tue6Sr1O43Xxvn6VdARfcri1/zhhj\nTHMJ0n1SxhhjzAwWpIwxxgSWBanKDOE2cgzN13AZsHMxzc7FNDsX0+xcTFv0uQh5nle74RhjjDE1\nZDMpY4wxgWVByhhjTGBZkDLGGBNYFqSMMcYElgUpY4wxgWVByhhjTGBZkDLGGBNYgcrdt9REZAdw\nE3Aq8BRwpaqeUINKRC4HPoyrEHw/8BZVPdzIsdZbFefircCf4c6FAteo6gONHGu9VXouStqfD9wL\ndKtq8mTtmlEVvxe/CfwN8ELgGVx17PsbOdZ6q+JcvBu4Epf4+sfA1ar6aCPH2ggi8uvAV1R140me\nX9D7ps2kfH7l3t3Arbgs7DcAu0Wko6zdS4BduMq/a4BDwG2NHW19VXEuzsFlnX+Nqq4APgPcLSIr\nGzvi+qn0XJS0X+G3bTlV/F70A18DrvcTQ/8l8C+tVB27inNxLq6M0LmquhJX3eGuBg+37kTkD4Bv\n42r3zfb8gt83LUhNOxfIq+otqppX1dtwJ/LisnavA76qqj9U1TTw58CFIrK2weOtp0rPxSbgr1T1\ncQBV/TwuJf+pDR1tfVV6Lop2AXc2bHSNVem5eCNwr6p+FUBVv4SrrVRo6Gjrq9JzMQF4QFxEIrhz\n0Gqz6/fgisV+eI5mC37ftCA17RT86r4l1D9+0naqegw4xsyqws2uonOhql9U1U8UH4vI2UDXLN/b\nzCr9vUBEXo/7q/omIFT/oTVcpefiDOCAiPyriBwVkQeBmKpmGzHIBqn0/8gPcCsMP8FVB38X0Gol\nvm9V1R3AD+dos+D3TQtS0zo58S+cJFC+rFNpu2ZW9WsUkRcBXwbe5/8CtoqKzoWIbMEl0nyTf6gV\nk2JW+nuxCngL7s15Pa7q9jdEpLfuI2ycSn8vLgXeBvyq/z1/C3yllZY+VfVQBc0W/L5pQWpaEmgv\nO9YBjC+wXTOr6jWKyCuBB4C/U9WP13lsjTbvuRCREPCPwHv9/7DFWVSrzaYq/b1IA/eo6h5/KWyX\n3+bsBoyxUSo9F68HblbV/1bVjKp+CIgDv9WAMQbJgt83LUhNe5ITp57CiVP6Ge1EZA2w0j/eKio9\nF4jIm4B/Bv5IVf+yAWNrtErOxSbgpcAuETkG/AgXoPaLyMsbMsrGqPT3QoHymUKE1gralZ6LFCee\nizyQq9O4gmrB75u2BX3afUBCRHYCN+Mu/q7D7VgpdSfwHRH5LPAobufSPao63MjB1llF58Lfav0Z\n4AJVfbDho2yMec+Fqu7HLWcAICJbgb3ARlWdbOxw66rS/yNfAB4SkYuAbwHvwL1Rt9IW9ErPxZeA\nfxCRfwIeB67GTQ5a6jaNCiz4fdNmUj5VzQAX4XahDAE7gUtUdVJEdonIjX67x4C34rZPDgJ9wB8s\nzajro9JzAVyL23L6TREZFZEx//Mrl2bktVfFuSjn0Vozh2r+j/wI+F3c7QnHcW/gr2qle8aqOBdf\nA96L23Z+GPgd4EJVnViakTdOrd43reihMcaYwLKZlDHGmMCyIGWMMSawLEgZY4wJLAtSxhhjAsuC\nlDHGmMCyIGWMMSawLEgZY4wJLAtSxhhjAsvSIhlTY37hu3fjCrxtxtUZugf4iKo+v0RjugL4mKr2\n+8Uq7wPa/MwJ5W1/F/g07v3hXX6dsOJzfw3sVdVPN2bkZrmzmZQxNeQHqP/ApQX6v7jy6W8AtgCP\niMgLl3B4XsnnWVPN+Bnd/wF4Dy6d0a5ipWW/4u7v4HLVGdMQNpMyprY+BPQAO0rys+0HXiUi3wA+\nC/zGUg2uAmuB1cCdqpoXkRHgBbiCdu8BPtVixQtNwFmQMqZGRCQMvBlXV2q2BKLXAQ+LyKm4pcDf\nVtWXlnz/FcCHVXWziERxmaJ/H5dB/AHgj1V1r9+2AFwP/BFu+e0sEbkY+ADwYlw5iAeAN6vqgSpe\nxlFcyfOXishhXDmF/X5Rx98C3llFX8Ysmi33GVM7L8SVj394tidV9Ye4+kJnAXcAv+a/+Rddhitp\nAPBR4Bzg1X77A8D9ZRVd/xfwCuAtIrIN+ArwOVyp7guB7cD7q3kBqloA/gxXVuMnuKB5CPgL4K9U\ndbnVQTJLzIKUMbWzCnetZ64aOSPAGlX9KfAYcCmAX1r9AuBOEWkDrsIVkvy+qipwJa5w4GtK+rpZ\nnR/jVkWuVtXPqOqzfn2vu4BTq30Rqnozbga1WlU/IiIvwC1Rfk5EPiAiAyLyteK1KmPqyZb7jKmd\nY7gaUv3AM+VP+kt4a3H1h8DNpi4DPgn8Hm7Z7r/95cAErkhcaRdtuNla0d7iF6r6tIgkReRa4DTg\nl4GX4K4lVa2s9tP7cDO7XwOu8Pv/MPBB4I8X0r8xlbKZlDG18zNcAPr1kzz/q7j/c8XlwDtxS36b\ncTOq4lJf8Y/Hc4BfKfkQ4O9K+puq+isipwE/9X/G93EzsU8s6tW4fk/x+7wdOBv4vqqOAd/0HxtT\nVxakjKkRVc0Dfw9c6y/flbse9yb/uN/+edzmhjcA5+FmVgBPA1lgvao+o6rPAPuAj+FmR7N5K/Cw\nqr7WX/L7HvCLLL468HW461IeUGD6PSNag76NmZct9xlTWx8CfhP4TxF5D+660ybgWtyuu/9R1v5O\n3IznJ6r6MwBVnRCRXcBnROQPcct678EFsqtO8nMPAK8RkZfhbh6+HHgVbna1IP7s7EWqerl/6BHg\nPSJyOq5s+vcW2rcxlbKZlDE1pKop4Hxc8Pl/uCDxJVwQ+dViICpxFxDHLaeVuhb4V9xuvUdxO/Uu\n8HfawYk34/4d7ibie3DLiRtx17te6N9gvBAfwF13Kr62h4B/xGWrWOc/b0xdhTxv1hvPjTHGmCVn\nMyljjDGBZUHKGGNMYFmQMsYYE1gWpIwxxgSWBSljjDGBZUHKGGNMYFmQMsYYE1gWpIwxxgTW/w94\nc1puBIDncwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x119bbba58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(wins.win_pct\n",
    "    .unstack()\n",
    "    .assign(**{'Home Win % - Away %': lambda x: x.home_team - x.away_team,\n",
    "               'Overall %': lambda x: (x.home_team + x.away_team) / 2})\n",
    "     .pipe((sns.regplot, 'data'), x='Overall %', y='Home Win % - Away %')\n",
    ")\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And get that back into `df`.\n",
    "You could you `pd.merge`, but I prefer `.map` when joining a `Series`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"0\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>away_team</th>\n",
       "      <th>away_points</th>\n",
       "      <th>home_team</th>\n",
       "      <th>home_points</th>\n",
       "      <th>away_rest</th>\n",
       "      <th>home_rest</th>\n",
       "      <th>home_win</th>\n",
       "      <th>rest_spread</th>\n",
       "      <th>away_strength</th>\n",
       "      <th>home_strength</th>\n",
       "      <th>point_diff</th>\n",
       "      <th>rest_diff</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>game_id</th>\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>1</th>\n",
       "      <th>2015-10-27</th>\n",
       "      <td>Detroit Pistons</td>\n",
       "      <td>106.0</td>\n",
       "      <td>Atlanta Hawks</td>\n",
       "      <td>94.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.536585</td>\n",
       "      <td>0.585366</td>\n",
       "      <td>-12.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <th>2015-10-27</th>\n",
       "      <td>Cleveland Cavaliers</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Chicago Bulls</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.695122</td>\n",
       "      <td>0.512195</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <th>2015-10-27</th>\n",
       "      <td>New Orleans Pelicans</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Golden State Warriors</td>\n",
       "      <td>111.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.365854</td>\n",
       "      <td>0.890244</td>\n",
       "      <td>16.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <th>2015-10-28</th>\n",
       "      <td>Philadelphia 76ers</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Boston Celtics</td>\n",
       "      <td>112.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.121951</td>\n",
       "      <td>0.585366</td>\n",
       "      <td>17.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <th>2015-10-28</th>\n",
       "      <td>Chicago Bulls</td>\n",
       "      <td>115.0</td>\n",
       "      <td>Brooklyn Nets</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.512195</td>\n",
       "      <td>0.256098</td>\n",
       "      <td>-15.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               away_team  away_points              home_team  \\\n",
       "game_id date                                                                   \n",
       "1       2015-10-27       Detroit Pistons        106.0          Atlanta Hawks   \n",
       "2       2015-10-27   Cleveland Cavaliers         95.0          Chicago Bulls   \n",
       "3       2015-10-27  New Orleans Pelicans         95.0  Golden State Warriors   \n",
       "4       2015-10-28    Philadelphia 76ers         95.0         Boston Celtics   \n",
       "5       2015-10-28         Chicago Bulls        115.0          Brooklyn Nets   \n",
       "\n",
       "                    home_points  away_rest  home_rest  home_win  rest_spread  \\\n",
       "game_id date                                                                   \n",
       "1       2015-10-27         94.0        NaN        NaN         0          NaN   \n",
       "2       2015-10-27         97.0        NaN        NaN         1          NaN   \n",
       "3       2015-10-27        111.0        NaN        NaN         1          NaN   \n",
       "4       2015-10-28        112.0        NaN        NaN         1          NaN   \n",
       "5       2015-10-28        100.0        0.0        NaN         0          NaN   \n",
       "\n",
       "                    away_strength  home_strength  point_diff  rest_diff  \n",
       "game_id date                                                             \n",
       "1       2015-10-27       0.536585       0.585366       -12.0        NaN  \n",
       "2       2015-10-27       0.695122       0.512195         2.0        NaN  \n",
       "3       2015-10-27       0.365854       0.890244        16.0        NaN  \n",
       "4       2015-10-28       0.121951       0.585366        17.0        NaN  \n",
       "5       2015-10-28       0.512195       0.256098       -15.0        NaN  "
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.assign(away_strength=df['away_team'].map(win_percent),\n",
    "               home_strength=df['home_team'].map(win_percent),\n",
    "               point_diff=df['home_points'] - df['away_points'],\n",
    "               rest_diff=df['home_rest'] - df['away_rest'])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import statsmodels.formula.api as sm\n",
    "\n",
    "df['home_win'] = df.home_win.astype(int)  # for statsmodels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.\n",
      "         Current function value: 0.552792\n",
      "         Iterations 6\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>Logit Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>     <td>home_win</td>     <th>  No. Observations:  </th>  <td>  1213</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>               <td>Logit</td>      <th>  Df Residuals:      </th>  <td>  1208</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>               <td>MLE</td>       <th>  Df Model:          </th>  <td>     4</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>          <td>Thu, 21 Apr 2016</td> <th>  Pseudo R-squ.:     </th>  <td>0.1832</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>              <td>07:01:39</td>     <th>  Log-Likelihood:    </th> <td> -670.54</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>converged:</th>           <td>True</td>       <th>  LL-Null:           </th> <td> -820.91</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th> </th>                      <td> </td>        <th>  LLR p-value:       </th> <td>7.479e-64</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "        <td></td>           <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th> <th>[95.0% Conf. Int.]</th> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th>     <td>    0.0707</td> <td>    0.314</td> <td>    0.225</td> <td> 0.822</td> <td>   -0.546     0.687</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>home_strength</th> <td>    5.4204</td> <td>    0.465</td> <td>   11.647</td> <td> 0.000</td> <td>    4.508     6.333</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>away_strength</th> <td>   -4.7445</td> <td>    0.452</td> <td>  -10.506</td> <td> 0.000</td> <td>   -5.630    -3.859</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>home_rest</th>     <td>    0.0894</td> <td>    0.079</td> <td>    1.137</td> <td> 0.255</td> <td>   -0.065     0.243</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>away_rest</th>     <td>   -0.0422</td> <td>    0.067</td> <td>   -0.629</td> <td> 0.529</td> <td>   -0.174     0.089</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                           Logit Regression Results                           \n",
       "==============================================================================\n",
       "Dep. Variable:               home_win   No. Observations:                 1213\n",
       "Model:                          Logit   Df Residuals:                     1208\n",
       "Method:                           MLE   Df Model:                            4\n",
       "Date:                Thu, 21 Apr 2016   Pseudo R-squ.:                  0.1832\n",
       "Time:                        07:01:39   Log-Likelihood:                -670.54\n",
       "converged:                       True   LL-Null:                       -820.91\n",
       "                                        LLR p-value:                 7.479e-64\n",
       "=================================================================================\n",
       "                    coef    std err          z      P>|z|      [95.0% Conf. Int.]\n",
       "---------------------------------------------------------------------------------\n",
       "Intercept         0.0707      0.314      0.225      0.822        -0.546     0.687\n",
       "home_strength     5.4204      0.465     11.647      0.000         4.508     6.333\n",
       "away_strength    -4.7445      0.452    -10.506      0.000        -5.630    -3.859\n",
       "home_rest         0.0894      0.079      1.137      0.255        -0.065     0.243\n",
       "away_rest        -0.0422      0.067     -0.629      0.529        -0.174     0.089\n",
       "=================================================================================\n",
       "\"\"\""
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mod = sm.logit('home_win ~ home_strength + away_strength + home_rest + away_rest', df)\n",
    "res = mod.fit()\n",
    "res.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The strength variables both have large coefficeints (really we should be using some independent measure of team strength here, `win_percent` is showing up on the left and right side of the equation). The rest variables don't seem to matter as much.\n",
    "\n",
    "It's easy to explore variations in formula."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.\n",
      "         Current function value: 0.553499\n",
      "         Iterations 6\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>Logit Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>     <td>home_win</td>     <th>  No. Observations:  </th>  <td>  1213</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>               <td>Logit</td>      <th>  Df Residuals:      </th>  <td>  1210</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>               <td>MLE</td>       <th>  Df Model:          </th>  <td>     2</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>          <td>Thu, 21 Apr 2016</td> <th>  Pseudo R-squ.:     </th>  <td>0.1821</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>              <td>07:02:58</td>     <th>  Log-Likelihood:    </th> <td> -671.39</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>converged:</th>           <td>True</td>       <th>  LL-Null:           </th> <td> -820.91</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th> </th>                      <td> </td>        <th>  LLR p-value:       </th> <td>1.165e-65</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "        <td></td>           <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th> <th>[95.0% Conf. Int.]</th> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th>     <td>    0.4610</td> <td>    0.068</td> <td>    6.756</td> <td> 0.000</td> <td>    0.327     0.595</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>strength_diff</th> <td>    5.0671</td> <td>    0.349</td> <td>   14.521</td> <td> 0.000</td> <td>    4.383     5.751</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>rest_spread</th>   <td>    0.0566</td> <td>    0.062</td> <td>    0.912</td> <td> 0.362</td> <td>   -0.065     0.178</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                           Logit Regression Results                           \n",
       "==============================================================================\n",
       "Dep. Variable:               home_win   No. Observations:                 1213\n",
       "Model:                          Logit   Df Residuals:                     1210\n",
       "Method:                           MLE   Df Model:                            2\n",
       "Date:                Thu, 21 Apr 2016   Pseudo R-squ.:                  0.1821\n",
       "Time:                        07:02:58   Log-Likelihood:                -671.39\n",
       "converged:                       True   LL-Null:                       -820.91\n",
       "                                        LLR p-value:                 1.165e-65\n",
       "=================================================================================\n",
       "                    coef    std err          z      P>|z|      [95.0% Conf. Int.]\n",
       "---------------------------------------------------------------------------------\n",
       "Intercept         0.4610      0.068      6.756      0.000         0.327     0.595\n",
       "strength_diff     5.0671      0.349     14.521      0.000         4.383     5.751\n",
       "rest_spread       0.0566      0.062      0.912      0.362        -0.065     0.178\n",
       "=================================================================================\n",
       "\"\"\""
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(sm.Logit.from_formula('home_win ~ strength_diff + rest_spread',\n",
    "                       df.assign(strength_diff=df.home_strength - df.away_strength))\n",
    "    .fit().summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.\n",
      "         Current function value: 0.676549\n",
      "         Iterations 4\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>Logit Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>     <td>home_win</td>     <th>  No. Observations:  </th>  <td>  1213</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>               <td>Logit</td>      <th>  Df Residuals:      </th>  <td>  1210</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>               <td>MLE</td>       <th>  Df Model:          </th>  <td>     2</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>          <td>Thu, 21 Apr 2016</td> <th>  Pseudo R-squ.:     </th> <td>0.0003107</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>              <td>07:03:09</td>     <th>  Log-Likelihood:    </th> <td> -820.65</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>converged:</th>           <td>True</td>       <th>  LL-Null:           </th> <td> -820.91</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th> </th>                      <td> </td>        <th>  LLR p-value:       </th>  <td>0.7749</td>  \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th> <th>[95.0% Conf. Int.]</th> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>    0.3667</td> <td>    0.094</td> <td>    3.889</td> <td> 0.000</td> <td>    0.182     0.552</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>home_rest</th> <td>    0.0338</td> <td>    0.069</td> <td>    0.486</td> <td> 0.627</td> <td>   -0.102     0.170</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>away_rest</th> <td>   -0.0420</td> <td>    0.061</td> <td>   -0.693</td> <td> 0.488</td> <td>   -0.161     0.077</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                           Logit Regression Results                           \n",
       "==============================================================================\n",
       "Dep. Variable:               home_win   No. Observations:                 1213\n",
       "Model:                          Logit   Df Residuals:                     1210\n",
       "Method:                           MLE   Df Model:                            2\n",
       "Date:                Thu, 21 Apr 2016   Pseudo R-squ.:               0.0003107\n",
       "Time:                        07:03:09   Log-Likelihood:                -820.65\n",
       "converged:                       True   LL-Null:                       -820.91\n",
       "                                        LLR p-value:                    0.7749\n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [95.0% Conf. Int.]\n",
       "------------------------------------------------------------------------------\n",
       "Intercept      0.3667      0.094      3.889      0.000         0.182     0.552\n",
       "home_rest      0.0338      0.069      0.486      0.627        -0.102     0.170\n",
       "away_rest     -0.0420      0.061     -0.693      0.488        -0.161     0.077\n",
       "==============================================================================\n",
       "\"\"\""
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mod = sm.Logit.from_formula('home_win ~ home_rest + away_rest', df)\n",
    "res = mod.fit()\n",
    "res.summary()"
   ]
  }
 ],
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