Week_9/Day_2/prophet_exercise.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-29T13:18:58.173612Z",
     "start_time": "2020-04-29T13:18:55.124896Z"
    }
   },
   "outputs": [],
   "source": [
    "# ignore warnings\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "from fbprophet.plot import plot_plotly, plot_components_plotly\n",
    "import datetime as dt\n",
    "\n",
    "# import pandas\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# import prophet\n",
    "from fbprophet import Prophet\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-29T13:18:59.304569Z",
     "start_time": "2020-04-29T13:18:58.198145Z"
    }
   },
   "outputs": [],
   "source": [
    "# load data\n",
    "wmt = pd.read_csv('https://raw.githubusercontent.com/gumdropsteve/intro_to_prophet/master/data/WMT.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Explore the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-29T13:19:25.713918Z",
     "start_time": "2020-04-29T13:19:25.688300Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1972-08-25</td>\n",
       "      <td>0.063477</td>\n",
       "      <td>0.064697</td>\n",
       "      <td>0.063477</td>\n",
       "      <td>0.064453</td>\n",
       "      <td>0.023768</td>\n",
       "      <td>2508800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1972-08-28</td>\n",
       "      <td>0.064453</td>\n",
       "      <td>0.064941</td>\n",
       "      <td>0.064209</td>\n",
       "      <td>0.064209</td>\n",
       "      <td>0.023678</td>\n",
       "      <td>972800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1972-08-29</td>\n",
       "      <td>0.063965</td>\n",
       "      <td>0.063965</td>\n",
       "      <td>0.063477</td>\n",
       "      <td>0.063477</td>\n",
       "      <td>0.023408</td>\n",
       "      <td>1945600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1972-08-30</td>\n",
       "      <td>0.063477</td>\n",
       "      <td>0.063477</td>\n",
       "      <td>0.062988</td>\n",
       "      <td>0.063477</td>\n",
       "      <td>0.023408</td>\n",
       "      <td>409600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1972-08-31</td>\n",
       "      <td>0.062988</td>\n",
       "      <td>0.062988</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>0.023047</td>\n",
       "      <td>870400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11810</th>\n",
       "      <td>2019-06-26</td>\n",
       "      <td>110.849998</td>\n",
       "      <td>111.080002</td>\n",
       "      <td>110.099998</td>\n",
       "      <td>110.160004</td>\n",
       "      <td>110.160004</td>\n",
       "      <td>4161700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11811</th>\n",
       "      <td>2019-06-27</td>\n",
       "      <td>110.059998</td>\n",
       "      <td>110.510002</td>\n",
       "      <td>108.860001</td>\n",
       "      <td>110.099998</td>\n",
       "      <td>110.099998</td>\n",
       "      <td>5481300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11812</th>\n",
       "      <td>2019-06-28</td>\n",
       "      <td>110.550003</td>\n",
       "      <td>111.510002</td>\n",
       "      <td>110.239998</td>\n",
       "      <td>110.489998</td>\n",
       "      <td>110.489998</td>\n",
       "      <td>6506700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11813</th>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>111.300003</td>\n",
       "      <td>111.970001</td>\n",
       "      <td>110.019997</td>\n",
       "      <td>110.620003</td>\n",
       "      <td>110.620003</td>\n",
       "      <td>5514700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11814</th>\n",
       "      <td>2019-07-02</td>\n",
       "      <td>110.830002</td>\n",
       "      <td>111.610001</td>\n",
       "      <td>110.339996</td>\n",
       "      <td>111.599998</td>\n",
       "      <td>111.599998</td>\n",
       "      <td>4062900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11815 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Date        Open        High         Low       Close   Adj Close  \\\n",
       "0      1972-08-25    0.063477    0.064697    0.063477    0.064453    0.023768   \n",
       "1      1972-08-28    0.064453    0.064941    0.064209    0.064209    0.023678   \n",
       "2      1972-08-29    0.063965    0.063965    0.063477    0.063477    0.023408   \n",
       "3      1972-08-30    0.063477    0.063477    0.062988    0.063477    0.023408   \n",
       "4      1972-08-31    0.062988    0.062988    0.062500    0.062500    0.023047   \n",
       "...           ...         ...         ...         ...         ...         ...   \n",
       "11810  2019-06-26  110.849998  111.080002  110.099998  110.160004  110.160004   \n",
       "11811  2019-06-27  110.059998  110.510002  108.860001  110.099998  110.099998   \n",
       "11812  2019-06-28  110.550003  111.510002  110.239998  110.489998  110.489998   \n",
       "11813  2019-07-01  111.300003  111.970001  110.019997  110.620003  110.620003   \n",
       "11814  2019-07-02  110.830002  111.610001  110.339996  111.599998  111.599998   \n",
       "\n",
       "        Volume  \n",
       "0      2508800  \n",
       "1       972800  \n",
       "2      1945600  \n",
       "3       409600  \n",
       "4       870400  \n",
       "...        ...  \n",
       "11810  4161700  \n",
       "11811  5481300  \n",
       "11812  6506700  \n",
       "11813  5514700  \n",
       "11814  4062900  \n",
       "\n",
       "[11815 rows x 7 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wmt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* use only `Date` and `Adj Close` columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-29T13:19:57.356443Z",
     "start_time": "2020-04-29T13:19:57.348689Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Adj Close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1972-08-25</td>\n",
       "      <td>0.023768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1972-08-28</td>\n",
       "      <td>0.023678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1972-08-29</td>\n",
       "      <td>0.023408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1972-08-30</td>\n",
       "      <td>0.023408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1972-08-31</td>\n",
       "      <td>0.023047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11810</th>\n",
       "      <td>2019-06-26</td>\n",
       "      <td>110.160004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11811</th>\n",
       "      <td>2019-06-27</td>\n",
       "      <td>110.099998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11812</th>\n",
       "      <td>2019-06-28</td>\n",
       "      <td>110.489998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11813</th>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>110.620003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11814</th>\n",
       "      <td>2019-07-02</td>\n",
       "      <td>111.599998</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11815 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Date   Adj Close\n",
       "0      1972-08-25    0.023768\n",
       "1      1972-08-28    0.023678\n",
       "2      1972-08-29    0.023408\n",
       "3      1972-08-30    0.023408\n",
       "4      1972-08-31    0.023047\n",
       "...           ...         ...\n",
       "11810  2019-06-26  110.160004\n",
       "11811  2019-06-27  110.099998\n",
       "11812  2019-06-28  110.489998\n",
       "11813  2019-07-01  110.620003\n",
       "11814  2019-07-02  111.599998\n",
       "\n",
       "[11815 rows x 2 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = wmt[['Date','Adj Close']]\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* rename columns to fit Prophet naming convention"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-29T13:19:57.853827Z",
     "start_time": "2020-04-29T13:19:57.847232Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1972-08-25</td>\n",
       "      <td>0.023768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1972-08-28</td>\n",
       "      <td>0.023678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1972-08-29</td>\n",
       "      <td>0.023408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1972-08-30</td>\n",
       "      <td>0.023408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1972-08-31</td>\n",
       "      <td>0.023047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11810</th>\n",
       "      <td>2019-06-26</td>\n",
       "      <td>110.160004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11811</th>\n",
       "      <td>2019-06-27</td>\n",
       "      <td>110.099998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11812</th>\n",
       "      <td>2019-06-28</td>\n",
       "      <td>110.489998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11813</th>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>110.620003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11814</th>\n",
       "      <td>2019-07-02</td>\n",
       "      <td>111.599998</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11815 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               ds           y\n",
       "0      1972-08-25    0.023768\n",
       "1      1972-08-28    0.023678\n",
       "2      1972-08-29    0.023408\n",
       "3      1972-08-30    0.023408\n",
       "4      1972-08-31    0.023047\n",
       "...           ...         ...\n",
       "11810  2019-06-26  110.160004\n",
       "11811  2019-06-27  110.099998\n",
       "11812  2019-06-28  110.489998\n",
       "11813  2019-07-01  110.620003\n",
       "11814  2019-07-02  111.599998\n",
       "\n",
       "[11815 rows x 2 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.rename(columns={'Date':'ds','Adj Close':'y'})\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* convert date to datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-29T13:20:17.263879Z",
     "start_time": "2020-04-29T13:20:17.255117Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ds    datetime64[ns]\n",
       "y            float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1972-08-25</td>\n",
       "      <td>0.023768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1972-08-28</td>\n",
       "      <td>0.023678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1972-08-29</td>\n",
       "      <td>0.023408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1972-08-30</td>\n",
       "      <td>0.023408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1972-08-31</td>\n",
       "      <td>0.023047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11810</th>\n",
       "      <td>2019-06-26</td>\n",
       "      <td>110.160004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11811</th>\n",
       "      <td>2019-06-27</td>\n",
       "      <td>110.099998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11812</th>\n",
       "      <td>2019-06-28</td>\n",
       "      <td>110.489998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11813</th>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>110.620003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11814</th>\n",
       "      <td>2019-07-02</td>\n",
       "      <td>111.599998</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11815 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              ds           y\n",
       "0     1972-08-25    0.023768\n",
       "1     1972-08-28    0.023678\n",
       "2     1972-08-29    0.023408\n",
       "3     1972-08-30    0.023408\n",
       "4     1972-08-31    0.023047\n",
       "...          ...         ...\n",
       "11810 2019-06-26  110.160004\n",
       "11811 2019-06-27  110.099998\n",
       "11812 2019-06-28  110.489998\n",
       "11813 2019-07-01  110.620003\n",
       "11814 2019-07-02  111.599998\n",
       "\n",
       "[11815 rows x 2 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['ds'] = pd.to_datetime(df['ds'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* plot time-series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-29T13:20:45.090219Z",
     "start_time": "2020-04-29T13:20:44.882791Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df.set_index('ds').plot(figsize=(12, 8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* instantiate Prophet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-29T13:21:46.874890Z",
     "start_time": "2020-04-29T13:21:46.869289Z"
    }
   },
   "outputs": [],
   "source": [
    "fb = Prophet()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* fit model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-29T13:22:04.450684Z",
     "start_time": "2020-04-29T13:21:47.349098Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:numexpr.utils:NumExpr defaulting to 6 threads.\n",
      "INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<fbprophet.forecaster.Prophet at 0x7f67a2f1e100>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fb.fit(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* forecast 365 values in future "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-29T13:22:32.376596Z",
     "start_time": "2020-04-29T13:22:04.487074Z"
    }
   },
   "outputs": [],
   "source": [
    "future_dates = fb.make_future_dataframe(periods=365)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>yhat</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12175</th>\n",
       "      <td>2020-06-27</td>\n",
       "      <td>96.535009</td>\n",
       "      <td>91.686258</td>\n",
       "      <td>101.261231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12176</th>\n",
       "      <td>2020-06-28</td>\n",
       "      <td>96.537762</td>\n",
       "      <td>91.676907</td>\n",
       "      <td>101.540859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12177</th>\n",
       "      <td>2020-06-29</td>\n",
       "      <td>96.513977</td>\n",
       "      <td>91.709181</td>\n",
       "      <td>101.598253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12178</th>\n",
       "      <td>2020-06-30</td>\n",
       "      <td>96.534648</td>\n",
       "      <td>91.670613</td>\n",
       "      <td>101.313275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12179</th>\n",
       "      <td>2020-07-01</td>\n",
       "      <td>96.524340</td>\n",
       "      <td>91.615922</td>\n",
       "      <td>101.457854</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              ds       yhat  yhat_lower  yhat_upper\n",
       "12175 2020-06-27  96.535009   91.686258  101.261231\n",
       "12176 2020-06-28  96.537762   91.676907  101.540859\n",
       "12177 2020-06-29  96.513977   91.709181  101.598253\n",
       "12178 2020-06-30  96.534648   91.670613  101.313275\n",
       "12179 2020-07-01  96.524340   91.615922  101.457854"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast = fb.predict(future_dates)\n",
    "forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* plot forecast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-29T13:22:32.968507Z",
     "start_time": "2020-04-29T13:22:32.473323Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fb.plot(forecast,uncertainty=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* plot components"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-29T13:22:34.197258Z",
     "start_time": "2020-04-29T13:22:33.048421Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAoUAAAKACAYAAADq5AJnAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy86wFpkAAAACXBIWXMAAAsTAAALEwEAmpwYAADVs0lEQVR4nOzdd1xV9f/A8deFy97IHoIILkSQIe6ZaZZo5UyTUqNvZUNbfpva+GV72aIssaGVlZgrzTS3hjPFgQqKLNkge5zfH9j9Si5ULocL7+fjwQPOvWe8z+dzufd9P+dzPh+NoigKQgghhBCiVTNSOwAhhBBCCKE+SQqFEEIIIYQkhUIIIYQQQpJCIYQQQgiBJIVCCCGEEAJJCoUQQgghBKBVO4CrmTp1KitWrMDFxYWDBw8CkJeXx/jx40lJScHX15cffvgBBwcHFEXh0UcfZdWqVVhaWrJw4UJCQ0OvegwnJyd8fX31fCaGraqqChMTE7XDENdA6szwSJ0ZHqkzw9Pa6ywlJYWcnJxLPqdp7uMUbtq0CWtra6ZMmaJLCp966ikcHR2ZPXs28+bNIz8/n9dff51Vq1bx4YcfsmrVKnbu3Mmjjz7Kzp07r3qM8PBwEhIS9H0qBi09PR0PDw+1wxDXQOrM8EidGR6pM8PT2uvsSjlPs7983L9/fxwdHes9Fh8fT3R0NADR0dEsW7ZM9/iUKVPQaDT07NmTgoICMjIymjpkIYQQQgiD0+yTwkvJysrC3d0dADc3N7KysgBIS0vD29tbt56XlxdpaWmqxCiEEEIIYUiafZ/Cq9FoNGg0mmveLjY2ltjYWAAyMzNJT09v7NBalOzsbLVDENdI6szwSJ0ZHqkzwyN1dnkGmRS6urqSkZGBu7s7GRkZuLi4AODp6UlqaqpuvTNnzuDp6XnJfcTExBATEwPUXV9vzf0LGkrKyPBInRkeqTPDI3VmeKTOLs0gLx9HRUURFxcHQFxcHKNGjdI9vmjRIhRFYceOHdjZ2ekuMwshhBBCiMtr9i2FEydOZOPGjeTk5ODl5cXcuXOZPXs248aNY8GCBfj4+PDDDz8AMGLECFatWoW/vz+WlpZ89dVXKkcvhBBCCGEYmn1SuHjx4ks+vn79+ose02g0fPTRR/oOSQghhBCiUSiKwhsbjuPfxoo7g9W9rG2Ql4+FEEIIIQxdaWU1E77ezeyVR1iUcEbtcJp/S6EQQgghREtzIqeEUV/9RWJmMXeHefGf3j5qhyRJoRBCCCFEU1p1OIu7vtlDraLw7E0BDO3gTGcXa7XDkqRQCCGEEKIp1NYqvLzuGHPXHcPP0ZLnbgpgcIATXnYWGBld+5jLjU2SQiGEEEIIPcsvreTu7/ay8vBZhnV05oWbAwjzssdMa6x2aDqSFAohhBBC6NGB9CJuX/gXp/PLeGpQex7t1w4POwu1w7qIJIVCCCGEEHry7e4z3PfjfqxNtXw+thvjQjywNG2e6VfzjEoIIYQQwoBVVtfyxK+JfLglmVBPO14b0YmbOjg3i76DlyNJoRBCCCFEI8ooKmdsXAJbU/KZFOrJczcF0MnVRu2wrkqSQiGEEEKIRrI1OY8xcQkUllfxf7d04v7ePjhamqodVoNIUiiEEEIIcYMURWH+lhRmLT+Eh605CyeEMLqrO6Zaw5k8TpJCIYQQQogbUFpZTcyPB/h2TxoD/Nowd3gH+vu1QaNpvv0HL0WSQiGEEEKI63Qip4Q7Fibwd0YRD/T24elB/vg4Wqod1nWRpFAIIYQQ4jqsTMxi8nd7UBT4YHRXoiO8sTE33NTKcCMXQgghhFBBba3CS+uOMXftMTo6W/HGbV0Y0dkFrbHh9B+8FEkKhRBCCCEaKL+0ksnf7WXV4bOM7OLKnJs7EOptr3ZYjUKSQiGEEEKIBrhwurrZg/15tF873GzN1Q6r0UhSKIQQQghxFf9MV2djVjdd3fjunliYGKsdVqOSpFAIIYQQ4jIMcbq66yVJoRBCCCHEJRjqdHXXS5JCIYQQQoh/2XIyl7GLdhvkdHXXS5JCIYQQQojzWsJ0dddLkkIhhBBCCFrOdHXXy6DT3nfffZfAwEC6du3KxIkTKS8vJzk5mcjISPz9/Rk/fjyVlZVqhymEEEKIZu5ETgm9PtjKd3vSeLC3D3ETQxjQ3qnVJIRgwElhWloaH3zwAQkJCRw8eJCamhqWLFnC008/zcyZMzl+/DgODg4sWLBA7VCFEEII0YytTMwi/L1NnMov5YPRXZl3axeDnb/4RhhsUghQXV1NWVkZ1dXVlJaW4u7uzh9//MGYMWMAiI6OZtmyZeoGKYQQQohmqbZWYc5vR7ltwS5crc1YNLE7/+ntY9DzF98Igz1rT09PnnjiCdq2bYuFhQU333wzYWFh2Nvbo9XWnZaXlxdpaWmX3D42NpbY2FgAMjMzSU9Pb7LYDVF2drbaIYhrJHVmeKTODI/UmeH5p84Kyqt5eFUyfyQXMczPlqd6u9PJsZazWZkqR6geg00K8/PziY+PJzk5GXt7e8aOHcuaNWsavH1MTAwxMTEAhIeH4+Hhoa9QWwwpI8MjdWZ4pM4Mj9SZ4cnGijuWJLTY6equl8Emhb///jvt2rXD2dkZgDvuuIOtW7dSUFBAdXU1Wq2WM2fO4OnpqXKkQgghhGgufkrM5enf97bo6equl8H2KWzbti07duygtLQURVFYv349Xbp0YdCgQSxduhSAuLg4Ro0apXKkQgghhFBbZXUtj/xykEdWp9DZxYavJ3ZnSri3JIQXMNikMDIykjFjxhAaGkpQUBC1tbXExMTw+uuv88477+Dv709ubi7Tpk1TO1QhhBBCqCijqJzBn2zjwy3JjOnswHeTu3NzJ5cWOX/xjTDYy8cAc+fOZe7cufUe8/PzY9euXSpFJIQQQojm5N/T1d3uZ0pHl5Y7f/GNMNiWQiGEEEKIy1EUhQ82n2TQJ9sxNTZi4YQQHh/YHltzE7VDa7YMuqVQCCGEEOLfSirqpqv7bm/rnK7ueklSKIQQQogW43hOCXcs/IuDGcU82NuHpwb5t8rZSa6HJIVCCCGEaBFWJmYx6ds9AHwwuivREd6tdnaS6yElJYQQQgiDVlur8NK6Y8xde4yOzla8eVsXbunsgtZYbp24FpIUCiGEEMJg5ZdWMvm7vaw6fJaRXVyZc3MHQr3t1Q7LIElSKIQQQgiDtD+9kDsWynR1jUWSQiGEEEIYnG92nyHmx/0yXV0jkqRQCCGEEAajsrqWx5cfYv7WFEI97XhtRCdu6uAss5M0AkkKhRBCCGEQ0gvLGbsogW0p+UwK9eT5oQEyO0kjkqRQCCGEEM3ev6eru7+3D46WpmqH1aJIUiiEEEKIZktRFD7ckszjyxPxsDVn4YQQRnd1x1Qrw800NkkKhRBCCNEsyXR1TUuSQiGEEEI0OzJdXdOTpFAIIYQQzcqKxCwmy3R1TU5KWAghhBDNQm2twty1x3hpnUxXpwZJCoUQQgihOpmuTn2SFAohhBBCVTJdXfMgSaEQQgghVCPT1TUfkhQKIYQQosnJdHXNjySFQgghhGhSMl1d8yRJoRBCCCGazOaTuYyT6eqaJYO+x7ugoIAxY8bQqVMnOnfuzPbt28nLy2Po0KEEBAQwdOhQ8vPz1Q5TCCGEaPUUReH9TScZ/Ml2TI2NWDghhMcHtpeEsBkx6KTw0UcfZfjw4Rw5coT9+/fTuXNn5s2bx5AhQ0hKSmLIkCHMmzdP7TCFEEKIVq2koprJ3+7lsfhD9PF1ZNFdIYwN9pD5i5sZg62NwsJCNm3axLRp0wAwNTXF3t6e+Ph4oqOjAYiOjmbZsmUqRimEEEK0bsdzSuj14RYW703jwd4+xE0MYUB7J5m/uBky2KQwOTkZZ2dn7r33Xrp378706dMpKSkhKysLd3d3ANzc3MjKylI5UiGEEKJ1WpGYRfi7mzidX8YHo7sy79YuMn9xM2awN5pUV1ezZ88ePvzwQyIjI3n00UcvulSs0Wgu+00kNjaW2NhYADIzM0lPT9d7zIYsOztb7RDENZI6MzxSZ4ZH6uzSahWFd7Zl8O6ODPwdzJgzwIP+7UwpzjtLscqxSZ1dnsEmhV5eXnh5eREZGQnAmDFjmDdvHq6urmRkZODu7k5GRgYuLi6X3D4mJoaYmBgAwsPD8fDwaLLYDZWUkeGROjM8UmeGR+qsvrzSSiZ/u5fVR5rvdHVSZ5dmsJeP3dzc8Pb25ujRowCsX7+eLl26EBUVRVxcHABxcXGMGjVKzTCFEEKIVmNfWiHh725m3bFsZg/2J3Zst2aXEIrLM9iWQoAPP/yQSZMmUVlZiZ+fH1999RW1tbWMGzeOBQsW4OPjww8//KB2mEIIIUSL983uM9z3w35szWW6OkNl0ElhSEgICQkJFz2+fv16FaIRQgghWh+Zrq7lMOikUAghhBDqkenqWhZJCoUQQghxzWS6upZH70nhyJEjrzhA5fLly/UdghBCCCEaiaIofLA5mSd+TcTD1pyFE0IY3dVdZidpAfSeFD7xxBMA/Pzzz2RmZjJ58mQAFi9ejKurq74PL4QQQohGUlJRTcyPB/hubxoD/Nowd3gH+vu1kdlJWgi9J4UDBgwA4PHHH693U8jIkSMJDw/X9+GFEEII0QiO55Rwx8K/OJhRzIO9fXhqkL/MTtLCNFmfwpKSEk6ePImfnx9QN01dSUlJUx1eCCGEENdpRWIWk7/dA8AHo7sSHeGNjbncltDSNFmNvvvuuwwcOBA/Pz8UReHUqVN89tlnTXV4IYQQQlyj2lqFuWuP8dK6Y3R0tuLN27pwS2cXtMbSf7AlarKkcPjw4SQlJXHkyBEAOnXqhJmZWVMdXgghhBDXwBCmqxONq0nbfnfv3k1KSgrV1dXs378fgClTpjRlCEIIIYS4in1phdyxMIHUgjJmD/bn0X7tcLM1VzssoWdNlhTefffdnDhxgpCQEIyN66a90Wg0khQKIYQQzcjXCanE/HhApqtrhZosKUxISCAxMVFuWxdCCCGaocrqWmYtP8RHMl1dq9VkSWHXrl3JzMzE3d29qQ4phBBCiAaQ6eoENGFSmJOTQ5cuXejRo0e9G0xkRhMhhBBCPZtP5jI2bjdFFTJdXWvXZEnhnDlzmupQQgghhLiKi6aru12mq2vtmiwpHDBgAKdOnSIpKYmbbrqJ0tJSampqmurwQgghhDjv39PVvTS8I/38HKXffyvXZF8HPv/8c8aMGcP9998PQFpaGqNHj26qwwshhBCCuunqen24hcV703iwtw9xE0Po317mLxZN2FL40UcfsWvXLiIjIwEICAjg7NmzTXV4IYQQotWT6erElTTZK8HMzAxT0/91XK2urpZvJUIIIUQTqKlVmLv2KC+vS5Lp6sRlNWmfwv/7v/+jrKyMdevW8fHHHzNy5MimOrwQQgjRKsl0daKhmuwrwuuvv46zszNBQUF89tlnjBgxgldeeaWpDi+EEEK0OvvSCgl/dzPrjmUze7A/sWO7SUIoLqtJWgpramoIDAzkyJEj3HfffU1xSCGEEKJVk+nqxLVqkpZCY2NjOnbsyOnTp5vicEIIIUSrVVldy4yf/2bK4n10cbXh64ndmRLuLQmhuKom61OYn59PYGAgPXr0wMrKSve4zGgihBBCNA6Zrk7ciCZLCsvLy1mxYoVuWVEUnn766Rveb01NDeHh4Xh6erJixQqSk5OZMGECubm5hIWF8fXXX9e761kIIYRoiTadyGXcIpmuTly/JrvRpLq6mgEDBuh+Bg4cSFlZ2Q3v9/3336dz58665aeffpqZM2dy/PhxHBwcWLBgwQ0fQwghhGiuFEXhvU0nGfzpdsy0RiycEMLjA9tLQiiumd5bCj/55BM+/vhjTp48Sbdu3XSPFxcX06dPnxva95kzZ1i5ciXPPvss77zzDoqi8Mcff/Ddd98BEB0dzZw5c3jggQdu6DhCCCFEY6uoruGjrSnMW3+cwvIqjI00mBgboTXSoL3M3ybGGkyMjNAa/+/x4opqdp0ukOnqxA3Te1J41113ccstt/Df//6XefPm6R63sbHB0dHxhvb92GOP8cYbb1BcXAxAbm4u9vb2aLV1p+Xl5UVaWtoNHUMIIYS6isqrSMkr41R+Kafyy0jJO/87v5Ss4gqGd3Lh4b7tCHK3VTvUBlEUhZ//zuDpFYc5kVtKz7b2dHKxpkZRqK6t+6k5/1P979+KQk1N3XJFdS3VtdXU1Co80rcdswb44eNoqfbpCQOm96TQzs4OOzs7Fi9e3Kj7XbFiBS4uLoSFhbFx48Zr3j42NpbY2FgAMjMzSU9Pb9T4Wprs7Gy1QxDXSOrM8LTGOlMUhfyyGs4UV3CmqJLUwkrSiio5U1RBalElZ4oqKaqoqbeNiZEGVystrtYmtLUxZuGuVD7fcZowdyumhbpwS4A9pk00U8e11tm+zBLmbjzDrrRz+NqZ8tpgT8YEOmNpem13BiuKggLUKnV/G2k0GJcXkJ5ecE37aY1a4/9ZQxnshIdbt25l+fLlrFq1ivLycoqKinj00UcpKCiguroarVbLmTNn8PT0vOT2MTExxMTEABAeHo6Hh0dThm+QpIwMj9SZ4WlpdVZbq5B1rqJeC9+p/FJS8uqWTxeUUVJZP+mzNDHGzdYMD1sLAt3tz/9tjqedOQFOVvg4WGJnocXCxBiNRsOZgjLe2niCpQcyeHBlMm0sTbi/lw/39/KhrYP+W84aUmep+WU8s/ow3+xOw9HShGeG+PNAbx+87KVlTw0t7f+ssWgURVHUDuJGbdy4kbfeeosVK1YwduxY7rzzTiZMmMB//vMfunXrxoMPPnjF7cPDw0lISGiiaA1Tenq6/BMZGKkzw2OIdVZdU0t6Ufm/Lu+eT/zySzmdX0ZlTf2PGTtzLW42ZrjbmuNua4a7Td1vL3tzOjhb42Vnjo25yTWPq1ddXcs3e9L48q/TbDmZh0YDIzrXXVq+KcAZI6PG72d3tTorLq/m9Q3HeXvjCWoVhUmhXszo60t3Tzvp96cSQ/w/a0xXynkMtqXwcl5//XUmTJjAc889R/fu3Zk2bZraIQkhhMGqqK4htaCcUxf046tr7SsjObeUtKJyamrrJ31tLE1wtzWnnYMlvXwccT/f0udlb0EHJyvcbc2wNtNi3siDKWu1RtzTw5t7enizP62Q9zcns+xgJisSz9LO0YIZfdtxT4R3k9yVW1Or8OWu0zy/+ihZ5yoY3tGZh/r4MqyTCyZNdGlbiGvVIloKb5S0FF5da/9mZYikzgyPGnVWWln9r0u79W/kyCyq4MIPCSMNOFub4W5jVtfKZ2t+/m9zfBws8HeywtnaDBszLaZa9ZOf4vIqPt6WwuK96exPL8JMa8SEEA9m9G1HeCPMAXypOlt3NJvHfz3E3xnFBHvYMrO/H3d2c8farMW1wxik1v7e2KpaCoUQQlzdxuM53PXNHjKKK+o9rjXS4GpjhoetGeFe9rpWPjcbM3wdLWnfxhJHK1NszLQG0eJlY27C04MDeHpwAOuOnuXT7af4YX86cQlnCPW04+G+7Rgd5IadufaGL+cmZhbz5IpEVh0+i6etOfNu7UR0uDdutuaNdDZC6JckhUII0cooisLM+EMowEO9fXG3NcPN1gw/RyvaOdbdxGFtIEnftRja0YWhHV1IKyzj/U3JLD2Qzr3f7+Pe78HUWEMbK1OcrUxxsTbD2doMZ+u6ZScr0/N//+8xB0tTjM/3UTxbXMGctUeJ3XEaC60Rj/Vrx/SePnRxtZZ+g8KgSFIohBCtzPJDWexLL2LOzR14cVhHtcNpcp52Frwxsgv/N6ITS/alkZBaSEFZFfnnf7KKKzhy9hwFZVWc+9ed0f8w0oCDhQkO5sZklVRTWlnNnd3cienlwwC/NmhbWEItWgdJCoUQohVRFIW5a4/iaWfO3eGXHrKrtdAaGzE5zJvJYd71Hq+tVSivrqGsqpbC8irSC8vJKKogu6RClzwWlFWRX1rF2cJzdHS15d4Ib4Z3csFK+g0KAyavXiGEaEVWHj7L3rQinh8agF8ba7XDaZaMjDRYmmqxNIU2Vqb4tbG67Lrp6em4urnrLiULYcikfVsIIVoJXSuhrTlTwrzUDqfFkIRQtBSSFAohRCux+shZElILubeHN/7O0koohKhPkkIhhGgFFEXhpbXHcLcxY7K0EgohLkGSQiGEaAXWHs1m5+kC7onwpoPz5fvICSFaL0kKhRCihavrS3gMVxszpkR4ydh5QohLkqRQCCFauN+P5bD9VD73hnvRUfoSCiEuQ5JCIYRowf6549jF2pS7w72llVAIcVmSFAohRAu24XguW1PyiQ73prOrtBIKIS5PkkIhhGjB5q49irOVKVPCPaWVUAhxRZIUCiFEC/XniRw2ncwjOtyLQDdbtcMRQjRzkhQKIUQLNXftMdpYmnB3uNxxLIS4OkkKhRCiBdp8MpcNx3OZEu5NV2klFEI0gCSFQgjRAulaCcM8MZK5eYUQDSBJoRBCtDBbk/NYn5TD3WFeBHvYqR2OEMJASFIohBAtzEtrj+FgYcLkMC9pJRRCNJgkhUII0YLsOJXP2mPZTA7zpLuntBIKIRpOkkIhhGhBXlp7DHsLLXdLK6EQ4hoZbFKYmprKoEGD6NKlC4GBgbz//vsA5OXlMXToUAICAhg6dCj5+fkqRyqEEE1j1+l8Vh85y+RQL0K97NUORwhhYAw2KdRqtbz99tskJiayY8cOPvroIxITE5k3bx5DhgwhKSmJIUOGMG/ePLVDFUKIJvHS2mPYmWuZHOaJsbQSCiGukcEmhe7u7oSGhgJgY2ND586dSUtLIz4+nujoaACio6NZtmyZilEKIUTTSEgtYOXhs9wV6km4t4Pa4QghDJDBJoUXSklJYe/evURGRpKVlYW7uzsAbm5uZGVlqRydEELo38vrjmFrVteXUFoJhRDXQ6t2ADfq3Llz3Hnnnbz33nvY2tYftV+j0Vx2aqfY2FhiY2MByMzMJD09Xe+xGrLs7Gy1QxDXSOrM8FxvnR3MKmX5oSzu6dYGL22ZvJ81Ifk/MzxSZ5dn0ElhVVUVd955J5MmTeKOO+4AwNXVlYyMDNzd3cnIyMDFxeWS28bExBATEwNAeHg4Hh4eTRa3oZIyMjxSZ4bneursod/+wtrUmGn9OuHt5aiHqMSVyP+Z4ZE6uzSDvXysKArTpk2jc+fOzJo1S/d4VFQUcXFxAMTFxTFq1Ci1QhRCCL3bn17IsoOZTOzuSU8fe7XDEUIYMINtKdy6dStff/01QUFBhISEAPB///d/zJ49m3HjxrFgwQJ8fHz44Ycf1A1UCCH06OV1SViZGjM5zBOtscF+zxdCNAMGmxT27dsXRVEu+dz69eubOBohhGh6f2cU8dOBDKZHetPLVy4bCyFujHytFEIIA/XyumNYmRozKdQLE2klFELcIHkXEUIIA3Qos5ilBzIYF+xBb2klFEI0AkkKhRDCwKTklXLPkr1YaOv6Eppq5a1cCHHjDLZPoRBCtEY/7k/nvh/2U12rMHdYB/q2a6N2SEKIFkKSQiGEMAClldXMjD9E7I7TdHWz4ZVbOjK0g7O0EgohGo0khUII0cwdzChi/Ne7Scw6R3S4FzP6+hLmZX/ZGZuEEOJ6SFIohBDNlKIofLb9FDPjD2Flasz827syLsQDZ2sztUMTQrRAkhQKIUQzlF9ayfQf9vPz35n08nFgzs0dGBTgJEPPCCH0RpJCIYRoZrYm53HXt3tILyzn0X7teLCPLx2crdUOSwjRwklSKIQQzURNrcIr644xZ+0x3GzMWDAumNuD3LExl7dqIYT+yTuNEEI0A2mFZYxfeoztqecY3tGZ2YP96efXBiMjuZlECNE0JCkUQgiVrUjM4p7FeympqObFoR24r2dbPO0t1A5LCNHKSFIohDA4iqKQW1JJYXk1xRXVFJ3//c/Phcu6v8urKSyv0i0XVVQDYGOmxd7cBDsLLXbmJtiaX/hbi625yfnfFz9va669oRs/KqpreHrFYd7fnEwHZyveGuLJhD7+mJsYN1ZRCSFEg0lSKIQwCJXVtWw6mcuKxCx+TcziZG7pVbexMDHC0sQYKzMtVibGWJoa42Bpgpe9OZYmxmg0GkoqazhXWc25ihoyiyvqliuqOVdZQ02t0qBj2JrVJYn2FhcmkZdPJu3MtdTUKjyy7CB704qYEOLB04P8cTEqkYRQCKEaSQqFEM1WVnEFqw5nsSIxi7VHszlXWYOpsYYIb3uiurhib2GCpakxVqbGdS1+FibYW5jgcP7HwtQYU2MjTI2NMDHWXHWw56qaWiqra6msqaWiupbi8mryyqrIK60kv6yKwrKq80ljDSWVdYljyfmE8lxlNSUVNWSfqyQ5r5SSyhpKKqopqazhcqmlnbmWd6K6EB3hjaOlKenpJY1fiEII0UCSFAohmo3aWoW9aYWsPHyWFYmZ/JVaCICLtSk3d3SmXztHhndywd/JCq0exuszMTbCxNgIq/PLbrbXtr2iKFTVKFTW1CWWldW1lFfXUFBWrUssi8rqEsWSqmpCPOwYEuCkl3MRQohrJUmhEEJV5yqq+f1YNisPn2VlYhYZxRVogCB3Gx7o7UO/do4M9nfCxcas2U/rptFoMNVqZD5iIYRBkqRQCNGk/mkNXHcsm3XHctiSnEtljYKVqTG9fRy4v5cPg/zb0N3TXsbnE0KIJiTvuEIIvUvJKz2fBGbzR1IOuaVVAAQ4WTEu2IO+7RwZ6N+Gdo5W0somhBAqkaRQCNHoCsqq+CMph3XHsvk9KYfjOXU3ULhYm9Lb15Eebe3p4W1PkIctrtZmMkCzEEI0A5IUCiFuWGV1LdtP5fH7sbpE8K/UAmoVsDQxJszLjtGBrkT6OBDsYYuXvQUWMuyKEEI0O5IUCiGumaIoHMos5vfzrYF/nsilpLIGYw0EutkwrUdbItvaE9HWHl9HS2zNTdQOWQghxFVIUihEK1RdU0tRRTWFZf+b5aOwvIrC8ur//V1WTVFFlW6dC5/LL63SzQjS1sGCEZ1diPS2p6evI51crHG0NGn2dwoLIYSor0UmhWvWrOHRRx+lpqaG6dOnM3v2bLVDEqJRKIpCWVXN+eTsXwldvQSvmoy8QqqN0usndGV1f5dW1Vz1WFojDdZmxlibarE202JlaoyDhQne9uZYm2kJcLKiZ1t7wrztcZF+gUIIYfBaXFJYU1PDQw89xLp16/Dy8iIiIoKoqCi6dOmidmiilaqsrqW0qm7mi9LKmrq/K87/Pj8jxj+JXNH5BO7C5K6wrIqC88tF5dVUN3DqNUutBlsLU6xN6xI6LztzOrlYY2VqjLWpMdZm2rrnzP63XJf4meJgqcXGzEQ3E4ip9n+zgpgaG0kroBBCtEAtLinctWsX/v7++Pn5ATBhwgTi4+NVTwrTCssoKKtGUeo+0BVAUUA5PwGWolxi+fzvuvWVCx779zpX2Kdu31db59/Pnz+uUnfc3LwCHHI1Vz2ObpuGHucS53f1fVy8zmXL6BqOU12r6Gah+N+MFBfMTlHvOaXedGgV1f9eR6mbMq2mlgbkcDrGGrAy1epa6KzM6qZvc7c10yV3dclc3Xy+FyZ39pYmOFhocbQ0xVxrTGHuWTw93DG5hmnehBBCtF4tLilMS0vD29tbt+zl5cXOnTtVjKjO0ysO8+2eNLXDEFdhrAGtsREmRprzU55pMDEyQmus0f1tYqxBe/63hYkxtmba889fsJ2RBq2xEVojDeYmRphrjbE4/9vcxAiLf36bGGFjVjdfbxtLU2zNjTHTGmOqrduHqbZuH9eTzBmXmeBgaaqHUhJCCNEStbiksKFiY2OJjY0FIDMzk/T0dL0eb3xHawJsPKipVdB9vGtAU/erbvH8B///lv/39/+WNbrt/ln3wnxBg+Yy2124nqbe8oXH+9+ypt5y2bkiLG1sddv9Ow6jf8elgbouZvX38+/jai7YSHM+LqMLxi7W8L/9XHguRhfsRAP8s4muDDX/O46Rbr26B4w0GozPB2OkAWONBiMjMNEYoTU2wkhTt87/jlW3338eMzr/t5Hmf8/dmFqgApQKKINq6n5uVHZ2diPsRTQlqTPDI3VmeKTOLq/FJYWenp6kpqbqls+cOYOnp+dF68XExBATEwNAeHg4Hh4eeo3LwwNG6vUI+pWenq73MhKNT+rM8EidGR6pM8MjdXZpLW4+qYiICJKSkkhOTqayspIlS5YQFRWldlhCCCGEEM1ai2sp1Gq1zJ8/n2HDhlFTU8PUqVMJDAxUOywhhBBCiGatxSWFACNGjGDEiBFqhyGEEEIIYTBa3OVjIYQQQghx7SQpFEIIIYQQaJR/RvltxZycnPD19VU7jGYtOzsbZ2dntcMQ10DqzPBInRkeqTPD09rrLCUlhZycnEs+J0mhaJDw8HASEhLUDkNcA6kzwyN1ZnikzgyP1NnlyeVjIYQQQgghSaEQQgghhJCkUDTQP7O/CMMhdWZ4pM4Mj9SZ4ZE6uzzpUyiEEEIIIaSlUAghhBBCSFIohBBCCCGQpLBVmzp1Ki4uLnTt2lX32P79++nVqxdBQUGMHDmSoqIiAL799ltCQkJ0P0ZGRuzbt4/i4uJ6jzs5OfHYY4+pdEYt37XUWVVVFdHR0QQFBdG5c2dee+01AI4ePVqvzmxtbXnvvffUOJ1W4VrqrLKyknvvvZegoCCCg4PZuHEjgPyfNaHU1FQGDRpEly5dCAwM5P333wcgLy+PoUOHEhAQwNChQ8nPzwdAURQeeeQR/P396datG3v27AFgw4YN9erM3NycZcuWqXVaLdq11tmRI0fo1asXZmZmvPXWW7r9yHsjoIhW688//1R2796tBAYG6h4LDw9XNm7cqCiKoixYsEB57rnnLtruwIEDip+f3yX3GRoaqvz555/6CVhcU519++23yvjx4xVFUZSSkhLFx8dHSU5Orre/6upqxdXVVUlJSWmaE2iFrqXO5s+fr9xzzz2KoihKVlaWEhoaqtTU1Fy0T/k/05/09HRl9+7diqIoSlFRkRIQEKAcOnRIefLJJ5XXXntNURRFee2115SnnnpKURRFWblypTJ8+HCltrZW2b59u9KjR4+L9pmbm6s4ODgoJSUlTXcirci11llWVpaya9cu5ZlnnlHefPPNS+6ztb43SkthK9a/f38cHR3rPXbs2DH69+8PwNChQ/npp58u2m7x4sVMmDDhosePHTvG2bNn6devn34CFtdUZxqNhpKSEqqrqykrK8PU1BRbW9t6265fv5727dvj4+PTNCfQCl1LnSUmJjJ48GAAXFxcsLe3v2iQXfk/0y93d3dCQ0MBsLGxoXPnzqSlpREfH090dDQA0dHRula/+Ph4pkyZgkajoWfPnhQUFJCRkVFvn0uXLuWWW27B0tKySc+ltbjWOnNxcSEiIgITE5PL7rO1vjdKUijqCQwMJD4+HoAff/yR1NTUi9b5/vvvmThx4kWPL1myhPHjx6PRaPQep/ify9XZmDFjsLKywt3dnbZt2/LEE09clJwsWbLkknUp9OtydRYcHMzy5cuprq4mOTmZ3bt3X/Q/KP9nTSclJYW9e/cSGRlJVlYW7u7uALi5uZGVlQVAWloa3t7eum28vLxIS0urtx/5P2s6DamzhmitdSZJoajnyy+/5OOPPyYsLIzi4mJMTU3rPb9z504sLS3r9Y/6R2v9J1Lb5eps165dGBsbk56eTnJyMm+//TYnT57UbVdZWcny5csZO3asWqG3Wpers6lTp+Ll5UV4eDiPPfYYvXv3xtjYuN628n/WNM6dO8edd97Je++9d1ELu0ajaXBSnpGRwd9//82wYcP0Eaa4QGPVWWt+b9SqHYBoXjp16sTatWuBustUK1eurPf85T6Q9u/fT3V1NWFhYU0Sp/ify9XZd999x/DhwzExMcHFxYU+ffqQkJCAn58fAKtXryY0NBRXV1fVYm+tLldnWq2Wd999V7de79696dChg25Z/s+aRlVVFXfeeSeTJk3ijjvuAMDV1ZWMjAzc3d3JyMjAxcUFAE9Pz3qtuWfOnMHT01O3/MMPP3D77bdf8VKluHHXUmdX05rfG6WlUNRz9uxZAGpra3nllVf4z3/+o3uutraWH3744ZL9CRcvXiytFyq5XJ21bduWP/74A4CSkhJ27NhBp06ddNtJnanncnVWWlpKSUkJAOvWrUOr1dKlSxfddlJn+qcoCtOmTaNz587MmjVL93hUVBRxcXEAxMXFMWrUKN3jixYtQlEUduzYgZ2dne6SJUidNYVrrbOradV1pvKNLkJFEyZMUNzc3BStVqt4enoqX3zxhfLee+8pAQEBSkBAgPL0008rtbW1uvU3bNigREZGXnJf7dq1Uw4fPtxUobda11JnxcXFypgxY5QuXboonTt3Vt544w3dfs6dO6c4OjoqBQUFap1Kq3EtdZacnKx06NBB6dSpkzJkyJCL7nyU/zP927x5swIoQUFBSnBwsBIcHKysXLlSycnJUQYPHqz4+/srQ4YMUXJzcxVFUZTa2lrlwQcfVPz8/JSuXbsqf/31l25fycnJioeHxyXvIBeN51rrLCMjQ/H09FRsbGwUOzs7xdPTUyksLFQURd4bZZo7IYQQQgghl4+FEEIIIYQkhUIIIYQQAkkKhRBCCCEEkhQKIYQQQggkKRRCCCGEEEhSKIQQTW7OnDm89dZbaochhBD1SFIohBBCCCEkKRRCiKbw6quv0qFDB/r27cvRo0cB+OCDD+jSpQvdunW75ExBQgjRlGTuYyGE0LPdu3ezZMkS9u3bR3V1NaGhoYSFhTFv3jySk5MxMzOjoKBA7TCFEK2ctBQKIYSebd68mdtvvx1LS0tsbW2JiooCoFu3bkyaNIlvvvkGrVa+owsh1CVJoRBCqGTlypU89NBD7Nmzh4iICKqrq9UOSQjRiklSKIQQeta/f3+WLVtGWVkZxcXF/Prrr9TW1pKamsqgQYN4/fXXKSws5Ny5c2qHKoRoxeR6hRBC6FloaCjjx48nODgYFxcXIiIi0Gg0TJ48mcLCQhRF4ZFHHsHe3l7tUIUQrZhGURRF7SCEEEIIIYS65PKxEEIIIYSQpFAIIYQQQkhSKIQQQgghkKRQCCGEEEIgSaEQQgghhECSQiGEEEIIgSSFQgghhBACSQqFEEIIIQSSFAohhBBCCCQpFEIIIYQQSFIohBBCCCGQpFAIIYQQQqByUrhmzRo6duyIv78/8+bNu+j5iooKxo8fj7+/P5GRkaSkpACwbt06wsLCCAoKIiwsjD/++EO3ze7duwkKCsLf359HHnkERVGa6nSEEEIIIQyWRlEpa6qpqaFDhw6sW7cOLy8vIiIiWLx4MV26dNGt8/HHH3PgwAE+/fRTlixZwi+//ML333/P3r17cXV1xcPDg4MHDzJs2DDS0tIA6NGjBx988AGRkZGMGDGCRx55hFtuueWKsTg5OeHr66vP0wWgqqoKExMTvR+nNZKy1R8pW/2QctUfKVv9kbLVn6Yq25SUFHJyci75nFbvR7+MXbt24e/vj5+fHwATJkwgPj6+XlIYHx/PnDlzABgzZgwzZsxAURS6d++uWycwMJCysjIqKirIy8ujqKiInj17AjBlyhSWLVt21aTQ19eXhISERj7Di6Wnp+Ph4aH347RGUrb6I2WrH1Ku+iNlqz9StvrTVGUbHh5+2edUSwrT0tLw9vbWLXt5ebFz587LrqPVarGzsyM3NxcnJyfdOj/99BOhoaGYmZmRlpaGl5dXvX3+04L4b7GxscTGxgKQmZlJenp6o53b5WRnZ+v9GK2VlK3+SNnqh5Sr/kjZ6o+Urf40h7JVLSlsDIcOHeLpp59m7dq117xtTEwMMTExQF3W3FTffOQblv5I2eqPlK1+SLnqj5St/kjZ6o/aZavajSaenp6kpqbqls+cOYOnp+dl16murqawsJA2bdro1r/99ttZtGgR7du3161/5syZK+5TCCGEEEJcTLWkMCIigqSkJJKTk6msrGTJkiVERUXVWycqKoq4uDgAli5dyuDBg9FoNBQUFHDrrbcyb948+vTpo1vf3d0dW1tbduzYgaIoLFq0iFGjRjXpeQkhhBBCGCLVkkKtVsv8+fMZNmwYnTt3Zty4cQQGBvLCCy+wfPlyAKZNm0Zubi7+/v688847umFr5s+fz/Hjx3nppZcICQkhJCSEs2fPAnV3LE+fPh1/f3/at29/1ZtMmlJlTa3aIQghhBCimalqJvmBakPSNCfh4eF6v/v4ieWH2HEym02PDMDISKPXY7VGckec/kjZ6oeUq/5I2eqPlG3jq6lV6PnBZgZ4WfLWmMvfGdxYrpTzyIwmTaSzqw1bU4t5dvURtUMRQgghRDOxKCGVhNRCzIzUb6OTpLCJTO3hzVA/W97ceIItJ3PVDkcIIYQQKjtXUc0zq44Q5GbDmC5t1A5HksKmotFoeO+WdjhZmTLp270Ul1epHZIQQgghVPT6H8fJLK5g1gA/XG3N1Q5HksKmZG+uZfGkUFILypiyeJ/a4QghhBBCJan5Zby18QTDOjozqqub2uEAkhQ2uUEBTjw+sD3LDmayYOcptcMRQgghhAr+u+owigIP9/HFwdJU7XAASQpV8X8jOhHsYcvM+ERO5pSoHY4QQgghmtCu0/l8uyeNu0I9GdLBWe1wdCQpVIGJsRE/RYdTU6swZlECNbXq33EkhBBCCP1TFIWZ8YdoY2nCfT3bYm5irHZIOpIUqqS9kxXz7+jK3rQinvo1Ue1whBBCCNEEftiXzraUfB7o7UuPtg5qh1OPJIUquifCm9u7uvH+5pNsSMpWOxwhhBBC6FF5VQ1PrzxMBycrosO9MW5mk1lIUqgijUbDVxNCcLUx4+7v9lFYVql2SEIIIYTQk/c2neRUfhkzB/jh72yldjgXkaRQZXYWJnx/dxgZxeVM+nav2uEIIYQQQg+yiiv4v/XH6e/nyJhu7mqHc0mSFDYDff3aMHuwPysPn+WTbSlqhyOEEEKIRvb8miOUVtXwaL92OFmbqR3OJUlS2EzMHdaRMC87nvw1kWPZ59QORwghhBCN5EB6EQt2nmZcsDvDO7moHc5lqZoUrlmzho4dO+Lv78+8efMuer6iooLx48fj7+9PZGQkKSkpAOTm5jJo0CCsra2ZMWNGvW0GDhxIx44dCQkJISQkhLNnzzbFqdwwrbERS6PDARgbl0B1Ta3KEQkhhBDiRimKwqzlh7Ax0xLTsy2Wplq1Q7os1ZLCmpoaHnroIVavXk1iYiKLFy8mMbH+0CwLFizAwcGB48ePM3PmTJ5++mkAzM3Nefnll3nrrbcuue9vv/2Wffv2sW/fPlxcmm9G/m++jpZ8OqYbBzKKmRl/SO1whBBCCHGDVh4+y/qkHO6LbEvfdm3UDueKVEsKd+3ahb+/P35+fpiamjJhwgTi4+PrrRMfH090dDQAY8aMYf369SiKgpWVFX379sXcXP3Joxvb5DAvxgW78/G2FNYeNYxWTiGEEEJcrKqmlieWH8LHwYJ7e3ijNW7evfZUa8NMS0vD29tbt+zl5cXOnTsvu45Wq8XOzo7c3FycnJyuuO97770XY2Nj7rzzTp577jk0movHAYqNjSU2NhaAzMxM0tPTb/SUrio7u2FjEb7c35UtJ3K4+9vdbIjugr2FiZ4jM3wNLVtx7aRs9UPKVX+kbPVHyvbaLNhzlqPZJbwy0AO7mmLS0y9/z0BzKNvme2H7On377bd4enpSXFzMnXfeyddff82UKVMuWi8mJoaYmBgAwsPD8fDwaJL4Gnqcn6da0Wf+Nmb+ns6amJ6XTGxFfU1Vh62RlK1+SLnqj5St/kjZNkxeaSXv7jhAj7b2TO3fBXc7i6tuo3bZqtaO6enpSWpqqm75zJkzeHp6Xnad6upqCgsLadPmytfj/9mHjY0Nd911F7t27WrkyJtGpI8jz90UwNpjOXy4JVntcIQQQghxDV5ed4zC8ipm9vNrUELYHKiWFEZERJCUlERycjKVlZUsWbKEqKioeutERUURFxcHwNKlSxk8ePAVW8yqq6vJyckBoKqqihUrVtC1a1f9nYSePT+0A5Ft7Zm98jCJmcVqhyOEEEKIBjiWfY75W1IYFejGrV1c1Q6nwVS7fKzVapk/fz7Dhg2jpqaGqVOnEhgYyAsvvEB4eDhRUVFMmzaNu+++G39/fxwdHVmyZIlue19fX4qKiqisrGTZsmWsXbsWHx8fhg0bRlVVFTU1Ndx0003cd999ap3iDTM20vDjlHC6vrmRsYsS2Pf4AEyaeSdVIYQQorV78tdEzLRG/KeXDzbmhtNTT9VIR4wYwYgRI+o99tJLL+n+Njc358cff7zktv+MWfhvu3fvbrT4mgNvBwtix3Zjwjd7ePiXv/l0TLDaIQkhhBDiMv5IymH5oSxm9PFloP+Vb4xtbqTZyQCM7+7J5DBPYrefZkViptrhCCGEEOISamrrBqp2tzFjWqQ3plrDSrMMK9pW7NM7u9HWwYJp3+8n51yF2uEIIYQQ4l8W/pXK/vQiHu7bjmAPO7XDuWaSFBoIKzMtS6PDyCutYtzXu1EURe2QhBBCCHFecXk1z646Qjd3W+4O9zTIoeQkKTQg4d4OzBnWgQ3Hc3n7zxNqhyOEEEKI8+b9kUTWuQpmDfDDy95S7XCuiySFBua/gwPo4+vA86uPciC9UO1whBBCiFbvVF4pb/95kls6OTOqq5va4Vw3SQoNjJGRhh+mhGOmNWLcot1UVNeoHZIQQgjRqv131RFQ4KHevgY9Na0khQbIw86chRNCOJpdwoM//a12OEIIIUSrteNUPov3pjE5zJMhHZzVDueGSFJooEYHuXNvD2++3JXKsr8z1A5HCCGEaHUURWFm/CGcrEy5r6cP5ibGaod0QyQpNGDzb++KXxtL7vvxAFlF5WqHI4QQQrQqS/ams+NUPg/29iHC217tcG6YJIUGzNJUy8/3hFNYXsVYGaZGCCGEaDJlVTXMXnmYjs5WREd4Y2RkeEPQ/JskhQYu2MOO/7ulE5tP5vHa+uNqhyOEEEK0Cu/+eZLTBWXM7O+HXxsrtcNpFJIUtgCPD2zPwPZteGntMfacKVA7HCGEEKJFyywq57X1SQxs34YxwR5qh9NoJClsATQaDUvuDsPKzJjxX++mvEqGqRFCCCH05bnVRymvruXRfu1oY2WqdjiNRtWkcM2aNXTs2BF/f3/mzZt30fMVFRWMHz8ef39/IiMjSUlJASA3N5dBgwZhbW3NjBkz6m2ze/dugoKC8Pf355FHHmk1/excbcxYOCGE4zmlxPy4X+1whBBCiBZpf3ohX/51mvEhHtzc0bCHoPk31ZLCmpoaHnroIVavXk1iYiKLFy8mMTGx3joLFizAwcGB48ePM3PmTJ5++mkAzM3Nefnll3nrrbcu2u8DDzzA559/TlJSEklJSaxZs6ZJzqc5GBnoxv29fPh6dxo/7EtXOxwhhBCiRVEUhVnxidiaabkvsi2Wplq1Q2pUqiWFu3btwt/fHz8/P0xNTZkwYQLx8fH11omPjyc6OhqAMWPGsH79ehRFwcrKir59+2Jubl5v/YyMDIqKiujZsycajYYpU6awbNmypjqlZuG9UYF0cLbigZ8OkF4ow9QIIYQQjeXXQ1n8cTyHmJ4+9GnnqHY4jU61FDctLQ1vb2/dspeXFzt37rzsOlqtFjs7O3Jzc3FycrrsPr28vOrtMy0t7ZLrxsbGEhsbC0BmZibp6fpvWcvOztb7MQA+HeHD8G8OM/qLrfw8oRNGGsO/Tf5qmqpsWyMpW/2QctUfKVv9ac1lW1lTy2O/JNLW1pRR7Uw5m5XZqPtvDmXbsto9r0FMTAwxMTEAhIeH4+HRNHcPNcVxPDzgjds0PBZ/iAUHz/HisI56P2Zz0FR12BpJ2eqHlKv+SNnqT2st2/c2nSS5oIL3RgXSp6ufXo6hdtmqdvnY09OT1NRU3fKZM2fw9PS87DrV1dUUFhbSpk2bK+7zzJkzV9xna/FIv3YM7eDEq+uT2HU6X+1whBBCCIOVV1rJS2uP0bOtPeNDWm5SrFpSGBERQVJSEsnJyVRWVrJkyRKioqLqrRMVFUVcXBwAS5cuZfDgwWiucCnU3d0dW1tbduzYgaIoLFq0iFGjRun1PJorjUbDt5NCsTXTMvHrPZRWVqsdkhBCCGGQ5q49RmF5FY/198PN1vzqGxgo1ZJCrVbL/PnzGTZsGJ07d2bcuHEEBgbywgsvsHz5cgCmTZtGbm4u/v7+vPPOO/WGrfH19WXWrFksXLgQLy8v3Z3LH3/8MdOnT8ff35/27dtzyy23qHJ+zYGztRnfTgrlZF4pU7+XYWqEEEKIa3X07Dk+3prC6K5u3NrFVe1w9ErVPoUjRoxgxIgR9R576aWXdH+bm5vz448/XnLbf8Ys/Lfw8HAOHjzYaDEaumGdXJjRx5f5W1MY2cWVSWFeV99ICCGEEAA88WsiZloj/tPLB2uzln0rhsxo0gq8FdWFLq7WPPTz36Tml6kdjhBCCGEQfj+WzYrELKb28Gag/6VHPmlJJClsBcy0xvwUHU55dS1j4hKorW0ds7wIIYQQ16umVuHx5Yl42JoxrYc3JsYtP2Vq+WcoAOjkasM7UV3YlVrA82uOqB2OEEII0ax9ues0BzKKeKRvO7p52KkdTpOQpLAVeaC3LyM6u/DGhhNsTc5VOxwhhBCiWSoqr+K51UcI8bBlUpjnFUc+aUkkKWxFNBoNX9/VHUdLE+76di/nyqvUDkkIIYRodl5bf5yz5yqZ2d8PL3tLtcNpMpIUtjKOlqZ8NymU1PwyopfsUzscIYQQollJySvl3U0nGdHZhVFd3dQOp0lJUtgKDengzGP92/Hz35ks3HVa7XBEM/XX6QLC3tnE/J2ZKIrcnCSEaB1mrzwMwEO9fbGzMFE5mqYlSWEr9fptXQhyt+HRZYdIzi1ROxzRzCxKSKXfR1s5fLaY17akccfCBJkVRwjR4m1LzuP7felMCfNiSIeWPwTNv0lS2EqZGBvx8z0RVNXWMiZuNzUyTI0AqmtqmRl/kOjF+whys2H5vRHMiHAl/mAmEe9t5nR+qdohCiGEXtTWKsxcfghnK1OmR7bFTGusdkhNTpLCVszfyYoPRndlT1oh/z3fXC5ar9ySSobF7uS9TclMDPHgm0nduamjC//t78WSu0M5lV9G93c28ecJuXNdCNHyLNmXxq7TBTzUx5dwb3u1w1GFJIWt3LTItowKdOOdP0+w8XiO2uEIlRxILyL83U1sSc5lzs0d+PCOIDq62OieHxfiybaH+2BtquWmT7czf0uyitEKIUTjKq2sZvbKw3RysWZKuBdGRq1jCJp/k6SwldNoNCycGIKztRmTv9tLUZkMU9Pa/Lg/nV4fbKG0qobYscE8PdifNlamF63XzcOOvbP6EeFtz8O/HGTqkn1U1dSqELEQQjSud/48SWpBObP6+9GujZXa4ahGkkKBvYUJ398dSkZROZMX71U7HNFEamoVnl11mHGLduPvZMWiid25O8wLc5PL96NxtDJj84w+xPRsy1d/pdLnw61kn6towqiFEKJxpReWM++P4wzyb8Md3dzVDkdVqiaFa9asoWPHjvj7+zNv3ryLnq+oqGD8+PH4+/sTGRlJSkqK7rnXXnsNf39/OnbsyG+//aZ73NfXl6CgIEJCQggPD2+K02gR+rd34qlB/vx6KIvY7SlqhyP0rLCsilFf7uL/1h/n9q5ufHNXd4Z1cmnQJRNjIw2fjQ3m0zFBHEgvottbf7L3TIH+gxZCCD14bvURKmtqebRvu0teJWlNVEsKa2pqeOihh1i9ejWJiYksXryYxMTEeussWLAABwcHjh8/zsyZM3n66acBSExMZMmSJRw6dIg1a9bw4IMPUlNTo9tuw4YN7Nu3j4SEhCY9J0P38vCOdPe05fHliSRln1M7HKEnR7KK6fH+ZtYczWb2YH8+HdONIA/ba97P/b18Wf9ATxRFodeHW/l29xk9RCuEEPqz90whCxNSmRDiwc2dXNQOR3WqJYW7du3C398fPz8/TE1NmTBhAvHx8fXWiY+PJzo6GoAxY8awfv16FEUhPj6eCRMmYGZmRrt27fD392fXrl1qnEaLojU24qfoCBRg7KLdVEt/sRbn10OZ9Hh/CzkllXx6ZxDPDw3AxcbsuvfXp10b9szsT0dnayZ/t5fHlx+iVoY3EkIYAEVRmLX8EHbmWqb38MHiCl1nWgutWgdOS0vD29tbt+zl5cXOnTsvu45Wq8XOzo7c3FzS0tLo2bNnvW3T0tKAuhsnbr75ZjQaDffffz8xMTGXPH5sbCyxsbEAZGZmkp6e3qjndynZ2dl6P8aNMgNeHezNY2tSeHDJLuYMaqt2SA1iCGWrplpF4YOdmby1NZ0ARzPmDPCgn7eWgpyzFFxl24aU7bJx7Xl0dTLv/HmShORsYqPaY2Mmb7BXIq9Z/ZGy1Z+WVLZrkgrYeCKXhyNc8LMob5I84EqaQ9k2KCn88MMPmTx5Mg4ODvqO54Zt2bIFT09Pzp49y9ChQ+nUqRP9+/e/aL2YmBhdwhgeHo6Hh0eTxNdUx7kRj3p4sCW9ggV7Mxgb0Z6hHZzVDqlBDKFs1XCuoproxXv5+e9MbunkwivDOxJ6jWNwNaRs42M8ef2P4zy3+gi3fHeM32IiCXC2vs6oWwd5zeqPlK3+tISyrayu5bW4w/g5WvLQ4C54XTAEl5rULtsGXT7OysoiIiKCcePGsWbNmkaZB9XT05PU1FTd8pkzZ/D09LzsOtXV1RQWFtKmTZsrbvvPbxcXF26//Xa5rHydFowPxt3WnOjv9lJQWql2OOI6ncgpodcHW1h2MJPH+rfji3HdrjkhbCiNRsPsIQH8Oq0HeaWVhL27mVWJWXo5lhBC3Ij5W5M5nlPKY/3b1RuTtbVrUFL4yiuvkJSUxLRp01i4cCEBAQE888wznDhx4roPHBERQVJSEsnJyVRWVrJkyRKioqLqrRMVFUVcXBwAS5cuZfDgwWg0GqKioliyZAkVFRUkJyeTlJREjx49KCkpobi4GICSkhLWrl1L165drzvG1szW3IQfp4Rx9lwFE7/Z0yhfBETTWnc0m4j3NpNaUMaHt3fl5eGd8LCz0Ptxb+nsyu6Z/XGzMWPkl7t49fdj8voRQjQbOecqeGntMXr5ODA+xPPqG7QiDb7RRKPR4ObmhpubG1qtlvz8fMaMGcNTTz11XQfWarXMnz+fYcOG0blzZ8aNG0dgYCAvvPACy5cvB2DatGnk5ubi7+/PO++8oxu2JjAwkHHjxtGlSxeGDx/ORx99hLGxMVlZWfTt25fg4GB69OjBrbfeyvDhw68rPgG9fB15ZkgAa45m8/HWFLXDEQ2kKApvbzzB8M930MbKhLiJIcT09MHarOm6ELd3smLvrP4MCXDiudVHGbtoN2VVNVffUAgh9Gzu2mOcq6jmsf7tbuhGu5ZIozTgK/z777/PokWLcHJyYvr06YwePRoTExNqa2sJCAi4oRbD5iA8PLxJhq9JT09Xvb/AtaqpVej1wRYOZRaze1Y/OjXTZnZDLFt9KKuqIebH/XyzO40hAU68MrwTPX1vrC/wjZStoig8veIwb248QaCbDWvui8TLXv+tlYZAXrP6I2WrP4Zetoezigl6609u7+rGVxNCmvTL8tU0VdleKedpUEthXl4eP//8M7/99htjx47FxMSkbmMjI1asWNF4kYpmx9hIw9LoMIw0MDZut0xr1oydzi+l7/ytfLs7jQd6+/DV+OAbTghvlEaj4Y2RXVg8OZTk3FJC3v6TLSdzVY1JCNF6PfFrIhZaI+7v2bZZJYTNxRWTwry8PPLy8nj00UexsbHRLf/zA9C5c+cmCVSop62DJbFju3Ews5hHlx1UOxxxCZtP5hL+7maOnj3HO1FdmHdrZ7wdLNUOS2dCd0+2PtwHCxNjBn2ynU+2pagdkhCilVl79CyrDp9lWmRbBvg7qR1Os3TFNDksLAyNRnPJTuIajYaTJ0/qLTDRvEwM9eLXxCw+3XaKkV1cuaWzq9ohCeouz366/RSP/HIQTztzPrkziKiubpgYN79pzUM87dj3eH9u/WIXD/70N7tTC/hkTLdmGasQomWprqnl8eWJeNqZM61HW3nfuYwrJoXJycmXfU7uJmx9YscGszUln3uX7OPQkwNpYy0ddNVUUV3DjJ8P8sXO0/Rt58irt3Sin58jGs3V5y9WSxsrM7bM6MN/fjrAgp2pHMwsZsW0HjjJa0kIoUcLdp3mYGYxr9/ama7uzbNvfHPQoFT5hRdeqLdcW1vL5MmT9RKQaL6szbT8eHcYOaVVjJdhalSVUVTOoI+388XO00zt4U3chBD6t2/TrBPCf2iNjfhiXAgf3xHE3rRCgt/+k/1phWqHJYRooQrLqnh+9VFCPW2ZFOppEO+TamlQUpiamsprr70GQEVFBbfffjsBAQF6DUw0Tz18HHjx5gDWJ+Xw3ibpPqCGnafyCX93E3vTCpl3ayfejgrEz8lK7bCu2QN9fFn/n15U1Sj0/GAL3+9NUzskIUQL9H/rk8guqWRmfz88ZfSDK2pQUvjll1/y999/89prrzFy5EgGDRrEnDlz9ByaaK6eHdKB3r4OPLPqCAczitQOp1VZuCuV/h9tQ4OGr8aHMLN/e+wtTNQO67r19WvD3ln9CXCyYsI3e3jq10Rqa6UFWgjROJJzS3lvUzK3dnZhZKCb2uE0e1dMCvfs2cOePXvYu3cvjz76KN9//z0BAQH079+fPXv2NFWMopkxMtLww5QwzLRGjFu0m8pqGaZG36pqanl02UHu/X4fIR62xE0MYXx3D0y1ht9Z2tPegr9m9uOOIDfePD/odlF5ldphCSFagKdXJmKkgYf6+GJnwF+gm8oVbzR5/PHH6y07ODiQmJjI448/jkaj4Y8//tBrcKL58rSz4ItxwYxdtJuHfv6bz8cFqx1Si5VzroJxX+9mw/FcJoV68sLNAXRwblkdpc20xiyNDuf/1h/nxTVH6P7OJn6L6Ym/AV4WF0I0D1tO5vLj/gxierZlcIAMQdMQV0wKN2zY0FRxCAM0JtiD6PAsvth5mpGBrkRJ03yj25dWyOiv/iKjqJy5wzrwUJ92tLEyVTssvdBoNDx7UwAhHrZM+nYPYe9s4vu7Qxkuwx8JIa5Rba3CzOWHcLE2ZXqkD2ZaY7VDMggNuvaUlZXFtGnTuOWWWwBITExkwYIFeg1MGIaP7giinaMl07/fz9niCrXDaVG+35tG7w+3UF5VwxfjgnlqkH+LTQgvdGsXV3Y92g8XG1NuXbCLeeuT5E53IcQ1+W5vGgmphTzUx5cwLzu1wzEYDUoK77nnHoYNG0Z6ejoAHTp04L333tNnXMJAWJlp+Sk6nILyKsYt2i0f3o2gplZh9orDTPhmDx2drVk0sTuTQr0wN2k933Q7uFizd9YABvk78d9VRxj/9W7Kq2rUDksIYQBKK6v578rDdHG1Zkq4F0ZGMgRNQzUoKczJyWHcuHEYGdWtrtVqMTZuPR9Q4sq6e9nx8vCO/Hkylzc2nFA7HINWUFbFyAW7eH3Dce4McuPrSd25uZNLq3xTszbTsjamJ7P6+/Hj/gx6vL+ZtMIytcMSQjRzb208yZnCcmb298PXUfolX4sGJYVWVlbk5ubqBnzcsWMHdnY33hy7Zs0aOnbsiL+/P/Pmzbvo+YqKCsaPH4+/vz+RkZGkpKTonnvttdfw9/enY8eO/Pbbbw3ep9CPJwf609/PkRd/O8q+tAK1wzFIiZnF9HhvM+uOZfPMEH8+GdONrm62aoelKiMjDW+PCuSbu7pzIqeUkLc3sS05T+2whBDNVFphGa//cZwhAU7c0c1d7XAMToOSwnfeeYeoqChOnDhBnz59mDJlCh9++OENHbimpoaHHnqI1atXk5iYyOLFi0lMTKy3zoIFC3BwcOD48ePMnDmTp59+Gqjr07hkyRIOHTrEmjVrePDBB6mpqWnQPoV+GBlpWHJ3GBYmRoxftIeKarnUdy3iD2YS+f5m8kor+XRMEM8N7YCzTP2mMynMiy0z+mCmNWLgJ9v4fPsptUMSQjRDz646QlVtLQ/39cXRsuX3wW5sDUoKQ0ND+fPPP9m2bRufffYZhw4dolu3bjd04F27duHv74+fnx+mpqZMmDCB+Pj4euvEx8cTHR0NwJgxY1i/fj2KohAfH8+ECRMwMzOjXbt2+Pv7s2vXrgbtU+iPu605Cyd051hOCff/eEDtcAxCba3C3N+OMvqrv2jrYMGiid25N6ItFq2o/2BDdfeyY//j/enuaUfM0gP858f9VNfIGJlCiDq7UwuISzjDhBBPbu7oonY4BumKQ9L8o7S0lHfeeYdTp07x+eefk5SUxNGjR7ntttuu+8BpaWl4e3vrlr28vNi5c+dl19FqtdjZ2ZGbm0taWho9e/ast21aWt0UWVfb5z9iY2OJjY0FIDMzU3cTjT5lZ2fr/Rhqi3CESUFtiEs4Q193E0Z0cGyS4xpi2Z6rrOHR1SmsOV7AUD9bZvdxp5N9DZmZGWqHVk9zK9sf7/Tj6bUpfLbjNHtO5/LlaH8cLRr0VtasNLdybUmkbPWnuZatoijMWHoMezNjxgWYk5+dRb7aQV2j5lC2DXonvffeewkLC2P79u0AeHp6Mnbs2BtKCtUWExNDTEwMAOHh4Xh4eDTJcZvqOGr6fJIru976k9nrz3BrqD/utuZNclxDKtvjOSXc/s0ujp49x+MD/Hh8gB/uds13Ts7mVraLp3rSZ0sys5YfYvi3R1k9vQdBHoY37ERzK9eWRMpWf5pj2f58IIMdZ84xe7A/t4R1wthAb85Tu2wbdPn4xIkTPPXUU5iY1E0RY2lpecNDj3h6epKamqpbPnPmDJ6enpddp7q6msLCQtq0aXPZbRuyT6F/FibG/HRPOMUV1YyNS5Bhav7ltyNniXhvE2mF5Xx4e1fmDuvYrBPC5mpG33asu78nFdW1RH6whR/36b+1XwjR/FRU1/DkikT82lhybw8vg00Im4MGJYWmpqaUlZXp7j4+ceIEZmY31gk+IiKCpKQkkpOTqaysZMmSJURFRdVbJyoqiri4OACWLl3K4MGD0Wg0REVFsWTJEioqKkhOTiYpKYkePXo0aJ+iaQS52/LaiM5sTcnnlXXH1A6nWVAUhTc3HGfEFztxtjJj0cTuxPTyxcrM8C59NhcD2juxd2Z//BytGPf1bv678jC1tfIlRIjWZP6WFE7mljKrv1+LmwK0qTXo02ju3LkMHz6c1NRUJk2axNatW1m4cOGNHVirZf78+QwbNoyamhqmTp1KYGAgL7zwAuHh4URFRTFt2jTuvvtu/P39cXR0ZMmSJQAEBgYybtw4unTpglar5aOPPtKNm3ipfQp1zBzgx8rDWbzyexK3dHYh3NtB7ZBUU1pZzfQfDrB4bxpDA5x4+ZZORPq03vJoTF4OFiTM7MfEb3Yz74/j7Esr5MfocKwl2Raixcs+V8HL647R29eBcSHN77K2odEoDbi2N3nyZLp164aFhQV+fn5ERkbi5NRyJpcODw8nISFB78dJT09Xvb9AUztbXEGXNzZgZ2HCwScH6u2u2uZctqfySrl94V/sSyvioT6+PD24PV72lmqH1WDNuWwvpCgKL687xty1x/BrY8VvMZH4tWm+A9caSrkaIilb/WluZfvQT3/z2fYUltwdxpjg5hPX9Wiqsr1SztOgy8fTpk2jvLyc5cuX8/DDD3P//ffz/vvvN2qQomVysTHj67u6czK3lOnf71c7nCb354kcwt/bTFJ2Ce+OCuT/RnQ2qITQkGg0Gl64uSPL7o3gbHEFoe9sYu2Rs2qHJYTQk8TMYj7bcYo7urlzSycZgqYxNCgpHDRoEM8++ywvv/wy9913HwkJCXzyySf6jk20ELd0duXB3j58tzeNJXvPqB1Ok1AUhY+2JHPTpzuwNjUmbmIID/XxxcZcLmnq28hAN3Y91pc2VqaM+GInb244Ljc7CdECPf7rISy0Rtzf00f6ZjeSBiWFQ4YMoU+fPnz//fd07NiRv/76iyNHjug7NtGCvDMqkE4uVjzw09+cKWjZ89dWVNcw/Yf9zPjlIL18HVg0sTt3dPNAa9ygfzfRCDq62LBv1gD6+bXhqRWHuesbmWVHiJZkzZGzrDmSzfTItvRv30btcFqMBn1KdevWDVNTUw4ePMiBAwc4ePAgZWUt+4NdNC4zrTE/RUdQVlXL2LiEFnuHaHphOQM+2saXu1KZHunNookh9JM3LFXYmGtZ/59ePNqvHUv2pRP5/hYyisrVDksIcYOqa2p5fPkhvOzMmdqjLSbyhbvRNKgk3333XTZt2sTPP/9MmzZtuPfee7G3t9dzaKKl6eJmw1sju7DjdAFzfjuqdjiNbsepfMLf28SBjCLeuK0zb44MxNex+d7o0BoYGWl4b3RX4iaGcCz7HMFv/cmOlDy1wxJC3IDPd54mMescj/ZrR1d3GYKmMTUoKZw/fz7jx4+ne/fuxMfHM3XqVFavXq3v2EQL9FAfX4Z1dOa1P46zvQV9OC/YeZoBH23DSKPhq/EhPNrPD3sLE7XDEudNCfdm80N9MDHWMODjbSzYcUrtkIQQ16GgrIoX1hwl1NOOu0I9deMni8bRoJ6Z5eXlzJo1i7CwMLRa6cwprp9Go+Gbu7rT5Y2N3PXNHv5+YgDW5oabPFXV1DIz/hAfbU0hsq09/zeiE4P8neSNqhkK87Zn3+MDGPH5Tqb/eIDdaYV8MLqr9PUUwoD83+9J5JZU8t6oQDxkJqhG16B3wyeeeILIyEhJCEWjcLI249tJoZzKL+NeAx6mJvtcBUM/28FHW1OYHOrJ13d1Z3CAsySEzZiztRnbHunLlDAvPtl2ikGfbCOvtFLtsIQQDXAyt4T3NydzWxdXRga6qh1OiyRfkYUqhnZ05pF+7Vh6IINFCalX36CZ2XOmgPB3N7MjJZ+Xh3fk/du7EuBsrXZYogFMjI2Iu6s770Z1YcepAoLf+pODGUVqhyWEuIqnVhzG2Age7O2DrQFfYWrOJCkUqnnjti4EutnwyC8HOZVXqnY4DbZ4Txp952+loqaWBeODeXJQexwtTdUOS1yjxwa0Z+39PSmrqiHy/S38fCBD7ZCEEJex6UQuPx3IIDrcm8EBzmqH02JJUihUY6o14ud7wqmormVMXAI1zXyYmppahad+TeSub/fQ2cWaryeGcFeoJ2Za/UzdJ/RvkL8Te2b2x9fRgjvjEnh+9REZ6FqIZqa2VmHW8kO4WpsyLbItplpJXfRFSlaoqoOzNe+P7krCmUKeXXVY7XAuK7+0khGf7+TNjScYG+zO13d1Z2hHF+k/2AK0dbQkYWZ/RnZx5ZXfkxi5YBfnKqrVDksIcd43e86w+0whD/VpR6inndrhtGiSFArV3dezLbd1ceGtP0+y+USO2uFc5FBmMRHvbeaP4zk8d1MAH98RRBc3W7XDEo3IwsSY+KkRvHhzB1YfOUvYu5tIzjWcLg1CtFQlFdX8d+VhurhaMyXcCyMj+SKuT6okhXl5eQwdOpSAgACGDh1Kfn7+JdeLi4sjICCAgIAA4uLidI/v3r2boKAg/P39eeSRR3SXe+bMmYOnpychISGEhISwatWqJjkfcWM0Gg2LJnbHycqUSd/tpbi8Su2QdH75O4Oe72+moKyK2DHdeOamAJyszdQOS+iBRqNhzrCO/BQdTkZRBd3f+ZPfj2WrHZYQrdqbG0+QXlTBrAF++Dhaqh1Oi6dKUjhv3jyGDBlCUlISQ4YMYd68eRetk5eXx9y5c9m5cye7du1i7ty5uuTxgQce4PPPPycpKYmkpCTWrFmj227mzJns27ePffv2MWLEiCY7J3FjHCxNWTI5lDMF5dz93T61w6G2VuHFNUe5Y2ECPg6WfH1Xd6IjvLEwkf6DLd3oIHd2PtIXR0sThsfu4J2NJ6SfoRAqOFNQxhsbjjM0wIk7gtzVDqdVUCUpjI+PJzo6GoDo6GiWLVt20Tq//fYbQ4cOxdHREQcHB4YOHcqaNWvIyMigqKiInj17otFomDJlyiW3F4ZnoL8Tjw9sT/yhTL5QccaJovIqbl/4Fy+tO8bILq58OymEWzq7ymWLVqSzmw37Hh9An3aOPP5rInd/t5eK6hq1wxKiVXl29RGqaxVm9G2Hg4zw0CRUGY06KysLd/e6rN/NzY2srKyL1klLS8Pb21u37OXlRVpaGmlpaXh5eV30+D/mz5/PokWLCA8P5+2338bBweGSMcTGxhIbGwtAZmYm6enpjXJuV5KdLZeirmZGiB2rD1nw2LKDBNrW4GNv3qDtGqtsT+SVMy3+BCfyy3ko3Jn7w11ooyklPb319i9rza/bb0f7MmeDEQv2pHHgTB6L7gjAxapxxkdrzeWqb1K2+tNUZbs/s4RFCWcYH+hAkG11k3xGq605vG71lhTedNNNZGZmXvT4q6++Wm9Zo9E02h2cDzzwAM8//zwajYbnn3+exx9/nC+//PKS68bExBATEwNAeHg4Hh4ejRLD1TTVcQxZ/HR7ur31Jw+tSeWvx/pj3MAWuhst29WHs5i4+CgAH98RxOQwL6zMZBYfaN2v2y8me9K3YyoPLD3AsG+O8OvUHvTwufSXzWvVmstV36Rs9UffZasoCuN/3oajpQkPD+pMu7Zt9Hq85kTt163eLh///vvvHDx48KKfUaNG4erqSkZG3UCxGRkZuLi4XLS9p6cnqan/m+nizJkzeHp64unpyZkzZy56HMDV1RVjY2OMjIy477772LVrl75OT+hReycr5t/Rlb1pRTz1a6Lej6coCvPWJ3Hrgl242pjx9cTuTO/pIwmh0LknwptND/XGWKOh/0fb+GrXabVDEqLF+ulABluS8/hPLx96+jiqHU6rokqfwqioKN3dxHFxcYwaNeqidYYNG8batWvJz88nPz+ftWvXMmzYMNzd3bG1tWXHjh0oisKiRYt02/+TaAL88ssvdO3atWlOSDS6eyK8uSPIjfc3n+SPJP01qZdUVDPxmz38d9URbgpw4pu7ujOyq1uDWydF6xHR1oF9j/cn0M2Gqd/v5+Gf/272A64LYWjKq2p4asVh/J0suTeirbwXNzFVksLZs2ezbt06AgIC+P3335k9ezYACQkJTJ8+HQBHR0eef/55IiIiiIiI4IUXXsDRse4bw8cff8z06dPx9/enffv23HLLLQA89dRTBAUF0a1bNzZs2MC7776rxumJRqDRaPhyfAiuNmZM+W4fhWWVjX6MlLxS+szfyg/70nm4ry9fjQ8hom3jXBYULZOLjTk7Hu3LpFBP5m9NYcgn28kvbfzXphCt1YdbkknOK+Wxfn74O1upHU6ro1FkrAXCw8NJSEjQ+3HS09NV7y9gaLYm59L/o23c0smFFdMjL7vetZbthuM5jI1LoLJG4dVbOnJPRFtszOVy8aXI6/bS3tl4gqdXHsbD1pzV9/W45gHNpVz1R8pWf/RZtmeLKwiY9wfd3G35+Z5wnFvZmLBN9bq9Us4jM5qIZq1PuzbMHuzPysNn+Xhryg3vT1EUPth8kqGf7cDO3IS4CSE80NtXEkJxzWYNbM+a+yI5V1lNj/e3sOzvjKtvJIS4rBd/O0pJZQ2P9WvX6hLC5kKSQtHszR3WkTAvO55akcjRs+euez/lVTVM/X4/jy47RF9fRxbdFcLt3dzRGsu/gbg+Qzo4s3tmf9raW3DHwgReWHNEBroW4joczCgidscpxnRzZ3ini28+FU1DPg1Fs6c1NuKn6HA0wNi4BKpraq95H2mFZQz4eBsL/0olpmdb4iaG0Kdd6xnmQOiPr6Mlu2f1Z0RnF15el8SoL/+ipKJa7bCEMBiKovD48kSsTLXcF9lWRn5QkSSFwiD4OFryyZhu/J1ZzMz4Q9e07bbkPMLe2czBjGLeuq0zb9zWRebQFI3KwsSYX6f14LmbAliRmEX4e5s5ldd6BzwX4lqsOXKWtceymR7ZlgHt5cu6miQpFAZjcpgX40M8+HhbCr8dOdugbT7fcYqBn2zDVKvhqwnBPNzPDzuLxpmRQogLaTQaXr6lEz9OCedMQRkh7/zJhuM5aoclRLNWVVPL478m0tbegqmR3tKdR2VS+sKgfD42GE87c+5Zsu+KQ4FUVtfy4E8HiPnxAOFe9sRNCGFssAemWnnJC/26M9idHY/2xc7chKGf7eD9TSfUDkmIZit2+ykOZ53jkX7tCHS1UTucVk8+IYVBsTHX8uOUMLJLKhm/aPclO/VnFVdw02fb+WTbKaaEefH1Xd0ZFODcaNMpCnE1gW627H98AL18HHgsPpHo7/ZSWX3tfWGFaMnySyt58bejhHvZcVd3D3mPbgYkKRQGJ9LHkedvCmBdUg4fbE6u99zu1ALC393ErtMFvDK8I++NDqS9kwyAKpqenYUJGx/szYO9fVi0+wy9P9zC2eIKtcMSotl49fck8kqrmNnfD3c7C7XDEUhSKAzUc0M7ENnWnv+uOsyhzGIAvt19hr7zt1Jdq7BgXDBPDGqPg6WpypGK1szYSMNHd3bji3HdOJhZTLe3/2R3aoHaYQmhuuM5JXywJZmRga7cFuiqdjjiPEkKhUEyNtLw45RwTIyMGLcogbkbU5n83V4C3Wz4emIId4V6YqY1VjtMIQCYFunDxgd7AdBn/la+TkhVOSIh1PXUikS0Rhoe7O2Lrbnc/NdcSFIoDJa3gwWfj+tGYtY5YnefZXyIB1/f1Z2bOrpI3xTR7PT0cWT/rP50cbVmyuJ9PPv7KTadyCUp+xznZFxD0YpsPJ7DL39nck+EN4P8ndQOR1xARogUBm1ciCcnc0spLixg5s1dcZKpkUQz5mprzo5H+nHPkr0s3JvOwv3/G7LGytQYNxszPGzN8bQzx93WHHdbs7rfNnW/PezMsTPXypceYbBqahVmLT+Eq40Z03u0lREhmhlJCoXBmz0kgPT0dEkIhUEw1Rrx3eQw7u5sw6kKU7KKK8gpqSS3pJKckkqySyrZkpxHTkkl5Ze4Y9lMa4Tb+STR0+6ChPHCJNLWjDaWphgZSfIompevE86wN62IV4Z3pLuXndrhiH9RJSnMy8tj/PjxpKSk4Ovryw8//ICDg8NF68XFxfHKK68A8NxzzxEdHQ3As88+y6JFi8jPz+fcuf/NhVtRUcGUKVPYvXs3bdq04fvvv8fX17dJzkkIIa5FsLs1t3h4XPK5yupaSiqrOXuuklP5paQWlJNZVE7O+cTxn5/dqQXklFRyrrLmon2YGGlwtjbDw84MT9t/Wh7/lzh6nP/tYm2GsSSPogmcq6jmmdWH6epmw5RwL2nxboZUSQrnzZvHkCFDmD17NvPmzWPevHm8/vrr9dbJy8tj7ty5JCQkoNFoCAsLIyoqCgcHB0aOHMmMGTMICAiot82CBQtwcHDg+PHjLFmyhKeffprvv/++KU9NCCFumKnWCFOtKQ6WpnR0sb7setU1tZRW1ZBTcj55zC8n4xLJ48HMYjaeyKWw/OK+i0YacLIyrWt5PH+J+t+Xrd1tzXCzMZdLfeKGvLHhOBlFFbw6vBPeDjLVaHOkSlIYHx/Pxo0bAYiOjmbgwIEXJYW//fYbQ4cOxdHREYChQ4eyZs0aJk6cSM+ePS+73zlz5gAwZswYZsyYgaIo8m1ECNEiaY2NsDU2wtbcBL82lx+Ps6ZWoayqhoLSKk4VlJGaX0ZaYRnZ/0oeT+SWsPN0PvllVdRePC48bSxNcDt/qdrjgkvVHv9qhbQwkTv/RX2p+WW8tfEEN3dwZnSQm9rhiMtQJSnMysrC3d0dADc3N7Kysi5aJy0tDW9vb92yl5cXaWlpV9zvhdtotVrs7OzIzc3Fyeniu5tiY2OJjY0FIDMzk/T09Os+n4bKzs7W+zFaKylb/ZGy1Q81ytUIaGcG7dw04GYJ1G+tURSFiupazlXWkF5UQVpxJZnFleSWVZNXVnP+dzWnc4vYd6aGvLJqai6RPNqYGuFsZYKbtSlu1ia4WNX9uFqZ4GJd99vV2gRrU/0kj/Ka1Z/rLdvHViVTXaMQ3cWasoIcygoaN66WoDm8bvWWFN50001kZmZe9Pirr75ab1mj0ajSkhcTE0NMTAwA4eHheFymb09ja6rjtEZStvojZasfzblcu13hOUVRKK+u5Vx5NWmF5ZwuKCO1oIzsc5Vkl1Rc0PpYxc60UnJKKqmoufimGUsTY9zOtzR62JrjYWeGu82FN8zU/e1gYXLNnxPNuWwN3bWW7a7T+fx8OI97I7y5o2dnzKUl+bLUft3qLSn8/fffL/ucq6srGRkZuLu7k5GRgYuLy0XreHp66i4xA5w5c4aBAwde8Zienp6kpqbi5eVFdXU1hYWFtGnT5npPQQghxCVoNBosTIyxMDHG2caMkCvcRVpRXUNJRTUZxRWczq9LHrOKK//V77GCHafyySmppLTq4ptmzIyNcLUxw8PW7Hyfx/OJo80FfSBtzHGykjuumxtFUZgVf4g2libc17OtJITNnCqXj6OiooiLi2P27NnExcUxatSoi9YZNmwYzzzzDPn5+QCsXbuW1157rUH77dWrF0uXLmXw4MHSn1AIIVRkpjXGTGuMo5UZgW62l12vqqaW0soasksqOJVXxumCsvM3zVTpksfckkr2pRXx+7Ecii4x4LfWSIOztSle1lpGdC1maAdnerS1x8RYbpBRy4/7M9iaks9zNwXQo+3Fo4yI5kWVpHD27NmMGzeOBQsW4OPjww8//ABAQkICn376KV988QWOjo48//zzREREAPDCCy/objp56qmn+O677ygtLcXLy4vp06czZ84cpk2bxt13342/vz+Ojo4sWbJEjdMTQghxjUyMjbCzMMLOwgR/pyvfcV1WVUtuaSWn8+uSx/TC+ndcJ2UV8vK6Y8xdewwrU2MGtW/DsE4uDO3gTAdnK2ksaCLlVTU8vSKRACcrosO9ZegjA6BRFOUS3YRbl/DwcBISEvR+nPT0dNX7C7RUUrb6I2WrH1Ku+pOenk6luT2//J3BluQ8dp4uIK2wHAAPWzOGdXTh5o7ODAlwwlkGvb8m1/K6ff2P48xeeZiP7+jKA33a6Tkyw9dU7wlXynlkRhMhhBAtjq+jJTMHtGfmgPbU1ir8lZpP/MEsdp7OZ+mBDL76KxWAbu42DD/fiti3naP0eWskWcUVvPp7Ev38HBkbLF9+DIUkhUIIIVo0IyMNkT6ORPrUdUEqq6zht6NnWXssm52nCnjnz5O8seEEZloj+rZzZHhHF4Z2dCLIzVZuXLlOL6w5QmlVDY/1aydTkBoQSQqFEEK0KhamxowOcmd0UN14uRmF5cQfymTTiVx2ni7gyRWJsAKcrEy4KcCZYeeTRE87C5UjNwx/ZxTxxc7TjA/2YHini0cXEc2XJIVCCCFaNXc7c/7T25f/9PZFURT+zihi2d+Z7Didz7pj2SzZVze5QQcnK4Z1cubmji4MbN8GazP5CP23f4agsTbVcl+vtliaShkZEqktIYQQ4jyNRkM3Dzu6edSNvVhVXcOG47msPnKWnacLiN1xmg+3pKA10tCjrT3DO7lwcwdnwr3t5e5aYNXhs/yelMPjA/zo107GCTY0khQKIYQQl2GiNebmTi7cfP4yaF5JBSsSz7LheA47Thfw4pqjvLDmKLbmWgb7t6m71NzBmfZOl5+LuqWqqqnl8eWHaOtgwdQe3mhlfEiDI0mhEEII0UCOVmZMifBmSoQ3AEnZ51h2MJOtyXnsOFXAsoNZALS1t2BYR2du7ujM4AAnHC1N1Qy7SXy67RRHs0t4J6oLnV1t1A5HXAdJCoUQQojrFOBszZOD/HlyUN3A2ttP5bMiMYudpwr4bm8an+88jQbo7mmrG/qmt68jptqW1YqWX1rJnLVHifC2Y0KIhwwQbqAkKRRCCCEagdbYiH5+bejnV9eXrqSiilVHsvn9WDY7ThXw+h/H+b/1x7EwqVtveEdnhnZwJtDNxuCTqJfXJZFfWsXM2/1wl7u0DZYkhUIIIYQeWJmZMDbYQzd48+n8UpYfzGJTct3QN2uPZgPgYm3KzR3rhr65KcAJN1tzNcO+ZknZ55i/NZlRXd24rYub2uGIGyBJoRBCCNEE2jpYMqNfO2b0a0dtrcLetELiD2Wy41Q+vx7K4pvdaQB0cbXWTcXX38+x2Q/r8uSviZgYGfGfXj7YmDfvWMWVSe0JIYQQTczISEOYtz1h3vYAVFTV8PuxbNYczWbX6QI+2prMu5tOYmKsoZePg64/YqinXbOaZWXD8RziD2XxUG9fBvk7qR2OuEGSFAohhBAqMzMx5tZAN24NrLv8era4gl8Ts9h4PIedpwt4ZtURnll1BHsLLUP8nRnWqa4/oq+jpWox19TWDVTtZmPGtEjvFnfzTGukSg3m5eUxdOhQAgICGDp0KPn5+ZdcLy4ujoCAAAICAoiLi9M9/uyzz+Lt7Y21tXW99RcuXIizszMhISGEhITwxRdf6PU8hBBCCH1wsTFjWmRbvp4UytHZg0h8aiCvjuhIX19HNp3MJebHA7R7dT3tX13Pg0sPsOzvDArLqpo0xri/UtmXXsTDfX0J8bRr0mML/VClpXDevHkMGTKE2bNnM2/ePObNm8frr79eb528vDzmzp1LQkICGo2GsLAwoqKicHBwYOTIkcyYMYOAgICL9j1+/Hjmz5/fVKcihBBC6JVGo6Gzq41u7L/qmlo2J+eyMrFulpWFCal8sv0UxhoI87I/f6nZiUgfB0z0NIB0cXk1z64+Qjd3G+4O8zL4u6dFHVWSwvj4eDZu3AhAdHQ0AwcOvCgp/O233xg6dCiOjo4ADB06lDVr1jBx4kR69uzZ1CELIYQQzYLW2IhB/s4M8ncGoLCsilWHs1iflMOOUwW88vsxXlp3DCtTYwa2/2eWFSc6ulg3WvL2+objZBZX8NqITng7qHcJWzQuVZLCrKws3N3dAXBzcyMrK+uiddLS0vD29tYte3l5kZaWdtV9//TTT2zatIkOHTrw7rvv1tvHhWJjY4mNjQUgMzOT9PT06zmVa5Kdna33Y7RWUrb6I2WrH1Ku+tMay3aAmxED3FygnwtnCsv57Xg+u9JK2J2az8rDZwFwszahv48tA3xs6edjQxtLk2s+TnZ2NmlFlby14TiDfG3o5UyTfH62Bs3hdau3pPCmm24iMzPzosdfffXVessajabRvrmMHDmSiRMnYmZmxmeffUZ0dDR//PHHJdeNiYkhJiYGgPDwcDw8PBolhqtpquO0RlK2+iNlqx9SrvrTmsvWwwN6dK77u7ZW4a/UfOIPZrHzdD6rjxfyw6FcAILcbLilc91dzX3bOWJuYtyg/T/5Ryag4fHBnejYTsYlbExqv271lhT+/vvvl33O1dWVjIwM3N3dycjIwMXF5aJ1PD09dZeYAc6cOcPAgQOveMw2bdro/p4+fTpPPfXUNccthBBCtBRGRhoifRyJ9KnrilVWWcNvR8+y9lg2O08V8M6fJ3ljwwnMtEb08f3f0Dfd3G0vOfTNnowSvtubxtQe3gzp4NzUpyP0TJXLx1FRUcTFxTF79mzi4uIYNWrUResMGzaMZ555Rndn8tq1a3nttdeuuN9/Ek2A5cuX07lz58YPXgghhDBQFqbGjA5yZ3RQ3WdlRmE5yw9l8ueJullWnlpxGDhMG0sTburgzLDzU/F52VugKApzNqTSxtKEmJ4+DW5ZFIZDlaRw9uzZjBs3jgULFuDj48MPP/wAQEJCAp9++ilffPEFjo6OPP/880RERADwwgsv6G46eeqpp/juu+8oLS3Fy8uL6dOnM2fOHD744AOWL1+OVqvF0dGRhQsXqnF6QgghhEFwtzPn/t6+3N/bF0VR+DujiGV/Z7LjdD6/H8vm+311/QUDnKwIcrdhd0YJzw8NIOL8oNuiZdEoiqKoHYTawsPDSUhI0Ptx0tPTVe8v0FJJ2eqPlK1+SLnqj5Rt46iqrmHD8VxWH6kb+mZPWiG+diasjOlDeycrtcNrcZrqdXulnEdmNBFCCCHERUy0xtzcyYWbO9X1+88vreB4yhlJCFswmZNGCCGEEFflYGmGp72F2mEIPZKkUAghhBBCSFIohBBCCCEkKRRCCCGEEEhSKIQQQgghkKRQCCGEEEIg4xQC4OTkhK+vr96Pk52djbOzTAukD1K2+iNlqx9SrvojZas/Urb601Rlm5KSQk5OziWfk6SwCTXVINmtkZSt/kjZ6oeUq/5I2eqPlK3+NIeylcvHQgghhBBCkkIhhBBCCCFJYZOKiYlRO4QWS8pWf6Rs9UPKVX+kbPVHylZ/mkPZSp9CIYQQQgghLYVCCCGEEEKSwgZ79dVXCQwMpFu3boSEhLBz584b3uecOXN46623GiE6w6TRaJg8ebJuubq6GmdnZ2677bZG2X9rLN/c3FxCQkIICQnBzc0NT09P3XJlZWWjHWfjxo2NVk/NxcyZM3nvvfd0y8OGDWP69Om65ccff5x33nnnqvtJSUmha9eu+ghRx9raWq/7bwqXe63a29vTpUsXvR9/4cKFzJgxQ+/Haa6MjY115R8SEkJKSspF64wYMYKCgoKLHm+N763/di05wcKFC0lPT7/hY/r6+l52KJnGotXr3luI7du3s2LFCvbs2YOZmRk5OTmN+gHbWllZWXHw4EHKysqwsLBg3bp1eHp6qh2WQWvTpg379u0D6t64ra2teeKJJ9QNykD06dOHH374gccee4za2lpycnIoKirSPb9t2zbeffddFSNsWS73Wk1JSbmhLxzV1dVotfLRdjUWFha68v83RVFQFIVVq1Y1bVAG4lpzgoULF9K1a1c8PDwafAy1XsfSUtgAGRkZODk5YWZmBtQNdu3h4VEva09ISGDgwIFA3Rvc1KlTGThwIH5+fnzwwQe6fb366qt06NCBvn37cvToUd3jn3/+OREREQQHB3PnnXdSWlpKcXEx7dq1o6qqCoCioqJ6yy3BiBEjWLlyJQCLFy9m4sSJuufy8vIYPXo03bp1o2fPnhw4cACQ8r1W99xzD0uXLtUtX9jK9OabbxIREUG3bt148cUXASgpKeHWW28lODiYrl278v333wOwZs0aOnXqRGhoKD///LNuH7t27aJXr150796d3r1768q9f//+9T50+vbty/79+/V5qjekd+/ebN++HYBDhw7RtWtXbGxsyM/Pp6KigsOHD6PRaBgwYABhYWEMGzaMjIwMAHbv3k1wcDDBwcF89NFHun0uXLiQO+64g+HDhxMQEMBTTz2le27t2rX06tWL0NBQxo4dy7lz5wCYPXs2Xbp0oVu3brqEPjk5mV69ehEUFMRzzz2n28e5c+cYMmQIoaGhBAUFER8fD8ALL7xQr9Xz2Wef5f3339dPwelBTU0N9913H4GBgdx8882UlZUBMHDgQN04bjk5ObpJBxYuXEhUVBSDBw9myJAhZGRk0L9/f0JCQujatSubN28G4KuvvqJDhw706NGDrVu36o7366+/EhkZSffu3bnpppvIysqitraWgIAAsrOzAaitrcXf31+33NKkpKTQsWNHpkyZQteuXUlNTa33GSfvrf9zuZzgpZdeIiIigq5duxITE4OiKCxdupSEhAQmTZpESEgIZWVlV8wd7r77bvr06cPdd99Nbm4uN998M4GBgUyfPp0LbwEZPXo0YWFhBAYGEhsbC8CXX37JY489plvn888/Z+bMmdd2coq4quLiYiU4OFgJCAhQHnjgAWXjxo2KoiiKj4+Pkp2drSiKovz111/KgAEDFEVRlBdffFHp1auXUl5ermRnZyuOjo5KZWWlkpCQoHTt2lUpKSlRCgsLlfbt2ytvvvmmoiiKkpOTozves88+q3zwwQeKoijKPffco/zyyy+KoijKZ599psyaNauJzlr/rKyslP379yt33nmnUlZWpgQHBysbNmxQbr31VkVRFGXGjBnKnDlzFEVRlPXr1yvBwcGKokj5NtSLL76ovPnmm0p0dLTy448/6h63srJSFEVRfvvtN+W+++5TamtrlZqaGuXWW29V/vzzT2Xp0qXK9OnTdesXFBQoZWVlipeXl3Ls2DGltrZWGTt2rK6eCgsLlaqqKkVRFGXdunXKHXfcoSiKoixcuFB59NFHFUVRlKNHjyphYWFNcdo3xNfXVzl16pTy6aefKp988ony3HPPKStXrlS2bNmi9OzZU+nVq5dy9uxZRVEUZcmSJcq9996rKIqiBAUFKX/++aeiKIryxBNPKIGBgYqiKMpXX32ltGvXTleGbdu2VU6fPq1kZ2cr/fr1U86dO6coiqLMmzdPmTt3rpKTk6N06NBBqa2tVRRFUfLz8xVFUZSRI0cqcXFxiqIoyvz583V1WFVVpRQWFiqKoijZ2dlK+/btldraWiU5OVnp3r27oiiKUlNTo/j5+dX7H2hu/nmtKoqiJCcnK8bGxsrevXsVRVGUsWPHKl9//bWiKIoyYMAA5a+//lIUpe58fXx8FEWpK2dPT08lNzdXURRFeeutt5RXXnlFURRFqa6uVoqKipT09HTF29tbOXv2rFJRUaH07t1beeihhxRFUZS8vDxdmX/++ee694E5c+Yo7777rqIodf8v/7y2WwIjIyMlODhYCQ4OVkaPHq0kJycrGo1G2b59u26dfz7j5L21vsvlBP+8/hRFUSZPnqwsX75cUZT6r1tFuXLuEBoaqpSWliqKoigPP/ywMnfuXEVRFGXFihUKoNvun2OVlpYqgYGBSk5OjlJcXKz4+fkplZWViqIoSq9evZQDBw5c07lJS2EDWFtbs3v3bmJjY3F2dmb8+PEsXLjwitvceuutmJmZ4eTkhIuLC1lZWWzevJnbb78dS0tLbG1tiYqK0q1/8OBB+vXrR1BQEN9++y2HDh0CYPr06Xz11VdA3bfce++9V2/nqYZu3bqRkpLC4sWLGTFiRL3ntmzZwt133w3A4MGDyc3N1V3Ok/K9cWvXrmXt2rV0796d0NBQjhw5QlJSEkFBQaxbt46nn36azZs3Y2dnx5EjR2jXrh0BAQEX9QUtLCxk7NixdO3alZkzZ+rKduzYsaxYsYKqqiq+/PJL7rnnHpXOtOF69+7Ntm3b2LZtG7169aJXr166ZU9PTw4ePMjQoUMJCQnhlVde4cyZMxQUFFBQUED//v0BdK/ZfwwZMgQ7OzvMzc3p0qULp06dYseOHSQmJtKnTx9CQkKIi4vj1KlTuvWmTZvGzz//jKWlJQBbt27VtaJfuH9FUXjmmWfo1q0bN910E2lpaWRlZeHr60ubNm3Yu3evro7btGnTRKV449q1a0dISAgAYWFhl+zv9m9Dhw7F0dERgIiICL766ivmzJnD33//jY2NDTt37mTgwIE4OztjamrK+PHjddueOXOGYcOGERQUxJtvvql7DU+dOpVFixYBda0wLen94Z/Lx/v27eOXX34BwMfHh549e160rry31ne5nGDDhg1ERkYSFBTEH3/8oSuLaxEVFYWFhQUAmzZt0r3X3nrrrTg4OOjW++CDDwgODqZnz56kpqaSlJSEtbU1gwcPZsWKFRw5coSqqiqCgoKu6fjS8aKBjI2NGThwIAMHDiQoKIi4uDi0Wi21tbUAlJeX11v/n2blf7atrq6+4v7vueceli1bRnBwMAsXLmTjxo1AXT+nlJQUNm7cSE1Njd47sKshKiqKJ554go0bN5Kbm9ugbaR8G+7C12ltba2u74uiKPz3v//l/vvvv2ibPXv2sGrVKp577jmGDBlS70Pg355//nkGDRrEL7/8QkpKiu5SiKWlJUOHDiU+Pp4ffviB3bt3N/7JNbI+ffqwbds2/v77b7p27Yq3tzdvv/02tra2DBw4kLS0NN0l5n9cqiP+hS71WlUUhaFDh7J48eKL1t+1axfr169n6dKlzJ8/nz/++AOouzHr37799luys7PZvXs3JiYm+Pr66t6Lpk+fzsKFC8nMzGTq1KnXWhSq+neZ/XP5+ErvuVZWVrq/+/fvz6ZNm1i5ciX33HMPs2bNwtbW9rLHe/jhh5k1axZRUVFs3LiROXPmAODt7Y2rqyt//PEHu3bt4ttvv22sU2yWLizDhmqt763/zgk+++wzDhw4QEJCAt7e3syZM+ei1+g/Gvo6vpyNGzfy+++/s337diwtLRk4cGC9//v/+7//o1OnTteViEtLYQMcPXqUpKQk3fK+ffvw8fHB19dX90H3008/XXU//fv3Z9myZZSVlVFcXMyvv/6qe664uBh3d3eqqqoueuOZMmUKd911V4v6pnWhqVOn8uKLL170jaZfv366sti4cSNOTk5XfGOX8r20C1+ny5cv1/XrGTZsGF9++aWuL1taWhpnz54lPT0dS0tLJk+ezJNPPsmePXvo1KkTKSkpnDhxAqBeMlNYWKi7QejfLejTp0/nkUceISIiot633Oaqd+/erFixAkdHR4yNjXF0dKSgoIDt27czceJEsrOzdUlhVVUVhw4dwt7eHnt7e7Zs2QLQoMShZ8+ebN26lePHjwN1/TiPHTvGuXPnKCwsZMSIEbz77ru6Pph9+vRhyZIlF+2/sLAQFxcXTExM2LBhA6dOndI9d/vtt7NmzRr++usvhg0b1jgFpLILX8sX9pP9t1OnTuHq6sp9993H9OnT2bNnD5GRkfz555/k5uZSVVXFjz/+qFv/wtdwXFxcvX1Nnz6dyZMnM3bsWIyNjfVwVs2fvLfWd6mcoGPHjkBd/8Jz587Ve33a2NhQXFysW25o7tC/f3++++47AFavXk1+fj5Q93p1cHDA0tKSI0eOsGPHDt02kZGRpKam8t1339Xro99Q0lLYAOfOnePhhx+moKAArVaLv78/sbGxHD58mGnTpvH888/rWkeuJDQ0lPHjxxMcHIyLiwsRERG6515++WUiIyNxdnYmMjKy3gto0qRJPPfcc9dVwYbAy8uLRx555KLH/7mhpFu3blhaWl70Zv1vUr6Xdt999zFq1CiCg4MZPny47pvozTffzOHDh+nVqxdQd0nkm2++4fjx4zz55JMYGRlhYmLCJ598grm5ObGxsdx6661YWlrSr18/XRk+9dRTREdH88orr3DrrbfWO3ZYWBi2trYG86EQFBRETk4Od911V73Hzp07h4uLC0uXLuWRRx6hsLCQ6upqHnvsMQIDA/nqq6+YOnUqGo2Gm2+++arHcXZ2ZuHChUycOJGKigoAXnnlFWxsbBg1ahTl5eUoiqIbAuf999/nrrvu4vXXX2fUqFG6/UyaNImRI0cSFBREeHg4nTp10j1namrKoEGDsLe3bzHJzBNPPMG4ceN0r8XL2bhxI2+++SYmJiZYW1uzaNEi3N3dmTNnDr169cLe3l53eRrq3mvGjh2Lg4MDgwcPJjk5WfdcVFQU9957r8G8hvVB3lvru1xOYG9vT9euXXFzc6tXRvfccw//+c9/sLCwYPv27bz44osNyh1efPFFJk6cSGBgIL1796Zt27YADB8+nE8//ZTOnTvTsWPHiy75jxs3jn379l3XF3GZ0cQALF26lPj4eL7++mu1Q2mRpHz1Jz09nYEDB3LkyBGMjOTCRFOqra0lNDSUH3/8kYCAALXDMVgJCQnMnDlTdwezaDh5b1XHbbfdxsyZMxkyZMg1bysthc3cww8/zOrVq2W8KD2R8tWfRYsW8eyzz/LOO+9IQtjEEhMTue2227j99tslIbwB8+bN45NPPmnxfQn1Qd5bm15BQQE9evQgODj4uhJCkJZCIYQQQgiB3GgihBBCCCGQpFAIIYQQQiBJoRBCCCGEQJJCIYTA2NiYkJAQAgMDCQ4O5u2339YNLqsvTz75JIGBgTz55JN6PU5KSkqLGzhYCKEfcvexEKLV+2fKL4CzZ89y1113UVRUxNy5c/V2zNjYWPLy8lrMGIJCCMMnLYVCCHEBFxcXYmNjmT9/PoqikJKSQr9+/QgNDSU0NJRt27YBdbM1LFu2TLfdpEmTiI+Pr7cvRVF48skn6dq1K0FBQXz//fdA3YDI586dIywsTPfYP4KCgigoKEBRFNq0aaObe3fKlCmsW7eOmpoannzySSIiIujWrRufffaZbts333xT9/iLL7540bmdPHmS7t2789dffzVKWQkhWhZpKRRCiH/x8/OjpqaGs2fP4uLiwrp16zA3NycpKYmJEyeSkJDAtGnTePfddxk9ejSFhYVs27btoll3fv75Z/bt28f+/fvJyckhIiKC/v37s3z5cqytrXWtkxfq06cPW7duxcfHBz8/PzZv3syUKVPYvn07n3zyCQsWLMDOzo6//vqLiooK+vTpw80330xSUhJJSUns2rULRVGIiopi06ZNulkQjh49yoQJE1i4cCHBwcFNUYxCCAMjSaEQQlxBVVUVM2bMYN++fRgbG3Ps2DEABgwYwIMPPkh2djY//fQTd955J1pt/bfULVu2MHHiRIyNjXF1dWXAgAH89ddfREVFXfZ4/fr1Y9OmTfj4+PDAAw8QGxtLWloaDg4OWFlZsXbtWg4cOKCbW7WwsJCkpCTWrl3L2rVr6d69O1A3FVdSUhJt27YlOzubUaNG8fPPP9OlSxc9lZQQwtBJUiiEEP9y8uRJjI2NcXFxYe7cubi6urJ//35qa2sxNzfXrTdlyhS++eYblixZwldffdUox+7fvz8fffQRp0+f5tVXX+WXX35h6dKl9OvXD6i7JP3hhx8ybNiwetv99ttv/Pe//+X++++v93hKSgp2dna0bduWLVu2SFIohLgs6VMohBAXyM7O5j//+Q8zZsxAo9FQWFiIu7s7RkZGfP3119TU1OjWveeee3jvvfcALpls9evXj++//56amhqys7PZtGkTPXr0uOLxvb29ycnJISkpCT8/P/r27ctbb71F//79ARg2bBiffPIJVVVVABw7doySkhKGDRvGl19+yblz5wBIS0vj7NmzAJiamvLLL7+waNEivvvuuxsuIyFEyyQthUKIVq+srIyQkBCqqqrQarXcfffdzJo1C4AHH3yQO++8k0WLFjF8+HCsrKx027m6utK5c2dGjx59yf3efvvtbN++neDgYDQaDW+88QZubm5XjScyMlKXfPbr14///ve/9O3bF/6/vfuOiupoHzj+3aU3QXoHEVRAOvaGIrYYNLHFxJIYNc30aEw37X1NYno3Jool0RSNJiYmYokaC6JiB7Fgo4gIKCBt9/7+8JVfjB3ZBs/nHM9xd+/OPDu73H125s4MMH78eHJycoiNjUVRFNzc3Pj555/p06cP+/fvp1OnTgDY29szf/78utnNdnZ2/PrrryQlJWFvb3/NIWwhRNMkex8LIUQ9VVRUEBERwfbt23F0dDR0OEIIcUtk+FgIIeohNTWV0NBQHn30UUkIhRCNgvQUCiGEEEII6SkUQgghhBCSFAohhBBCCCQpFEIIIYQQSFIohBBCCCGQpFAIIYQQQiBJoRBCCCGEQJJCIYQQQgiBJIVCCCGEEAJJCoUQQgghBJIUCiGEEEIIJCkUQgghhBBIUiiEEEIIIQBzQwdgDFxdXQkMDNR5PTU1NVhYWOi8nqZE2lR3pG11R9pW96SNdUfaVnf00bY5OTmcPn36io9JUggEBgaSnp6u83pyc3Px9vbWeT1NibSp7kjb6o60re5JG+uOtK3u6KNt4+Pjr/qYDB8LIYQQQghJCoUQQgghhCSFQgghhBACSQqFEEIIIQSSFBpcRXUtVbUaQ4chhBBCiCZOZh8bwOGicj79O4cfd+ZxrOQ8AJ4OVgxq68ET3YJo4+Fg4AiFEEII0dRIUqhHGq3C9FXZTPvzALVahW4tnLktzB2ArFNlzNl6glmbj/Fg50Bm3B6GtYWZgSMWxkZRFM7XaCir0lBeraGsuhaNVsHVzhJ3eysszaXzXwghRP1IUqgn52s0PPDLYX4/WEKvYBeeSWhJ9yAX7Kz+/y04VlzBU0v38unfOaw9eJoVEzvi62RjwKhFQ6qu1bLtRAnbTpRyrPg8x0vOU1RRjUaroNEq1CoXfjhotQoa5X/3aRUqajSUV11IACuqNSjXqMPD3oqOgU4MCvfkjggvnGxkgVkhhBA3RpJCPblnwXZWHCzhqe5BTOkVjIeD1WXH+De35cd72/Ht9hNM/GEXHT5cz18PdybYzd4AEYuGsjf/HB+sO8wPO3MprawFwMJMhYe9FU42FpipVZipVJipQa1SYa5WYalWo1ZduG1trsbGwux///7//7b/u61WqyiuqKH4fA1Hi8+z5WgJS/cU8Mji3TzYKZCXkkJobmtp4FYQQghh7CQp1JMXe4cQ42zGE31a42B97Wa/O9aXIGdb+n21hW6fbmTrE13xdbLVU6SioRSVV/PUsr3M23YCa3M1vYJd6R7kQqyvI23c7XG0tsDaQo25WoVKpWqwejUaLb9nneKzv3P4cP1h5qYfZ+awKO6M9GqwOoQQwhjsyTvLisxCDhWVY2tpRtcWzvRt7YatpWmlN1mnyghyMfz3vGm1mgmL9XXCU+153YTwoo6BzqQ+2ImEzzbS47NNbH+yO44yFGgy/j5yhqEp6RSWVzMmzpcx8b50aeGMlbnurxM1M1MzMMyTgWGebDhcxIQfdjEkJZ2negTxzsAw1OqGS0CFEMIQcksreXLpXr7fmQuAo7U5lTVa3vvrMK52Fvx3QCj3d/Bv0B/cupJbWkn3T/8mqZUbb/f0NGgsclW6EYv3c2LxvfEcLT5P8jdpaLXXuppMGIsfd+bS6/NNWJipmHtXNJ8NiaBXiJteEsJ/6xrkQsbT3RkW5cV7fx1m1Lfb5XMkhDBp20+U0O6DdSzdm8+EDv78Pr49WVN7cfSlRObcFY13Mxsm/LCLQd9spaK61tDhXlOtRsvI+ds4W1nLoHAPQ4cjSaGx69Panbdua8O6w2d45pe9hg5HXMeyPfmMnL+dUA97Zo+IZmSsj8GHMazMzVg0Oo4nurXgux25jF24A0WRxFAIYXp2552l5+eb0CowZ0Q0H9/Zln6hHng4WOHhYM3Ydn5kPN2d53oF8+u+Arp8/DdlVcabGM5Ye4h1h88wtVcwg9oa/hIfSQpNwFM9WjIsyosP1h1hUcZJQ4cjrmLb8RKGz9tGKzc7PrmjLYmt3Ixm6EKlUvH+4LY80iWQ+dtO8uqfBwwdkhBC3JTc0kr6f7UFa3M1s4ZFMiLG+4ojMCqViv/cFkrKyOj/JZEbjXKTiCNFFby28gAJLV14uEugUSwpZvgIxHWpVCpSRsbQxt2e8Yt2cuBUmaFDEv9yuqyKO+ek09zGgo8Gt6VrkIuhQ7qijwa3ZUCoO6+vPMDv+wsMHY4QQtwQjVZh1LfbKSqv5qPBbekf6nHdH92j4/2YOSyS9OOljJy33ahGSBRF4dEluwF4pkcQbvaXr0hiCJIUmggbCzOWj++ASqVi8OytRvmrp6lSFIUHftxF3rlK3h4YSq8QV0OHdFVqtYpFo+Pwc7JhzHcZFJytNHRIQghxXe+uPcSag0VM7tmSOyK8bnjC3LgOAUzp2ZIle/L5T2q2jqO8cT/vyWf5/lNM7BhA/1DDX0t4kSSFJqSFiy2z74pi/6ky7l+009DhiP/5PiOXxbvzeaBjAEOjvI1myPhq7K3MWXJvPKWVNYz+boehwxFCiGs6UlTBK39k0bOlCw91CrjpYdb/DgilV7Arr608QPrxEt0EeRPKqmp5dMkegl1tmdKzpVGtCCFJoYkZEunNw50DWLD9JHPSjhk6nCav5HwNjy7ZQ5iHPY92C8TGRLYmjPF14rleIaw8cJq56ccNHY4QQlzVYz/vQaWCZxJa4uV487t8qdUqvhsVi72VOXfP305ljWEnnrz65wFOllYytVcw3vV4PbokSaEJ+mBwW6K8mzFpyR4yC84ZOpwm7Y2VBzhdXs3ziSG0cnMwdDg35cWkENq42zP5l32cq6wxdDhCCHGZP7NO8eu+AiZ2DKB3K7d6l+PuYMWcu6LJPl3OQz/ubsAIb86u3LO8/9dhBrf1ZHScn8HiuBpJCk2QhZmaZePaYa5WMWj2Vipr5PpCQzh4upyPNhwhOdyD241gfambZWGmZtbwKE6VVfPML/sMHY4QQlxCq1V47rdMvJtZcX97/1uenXt7uCf3t/djTvoJftmb30BR3jitVuGhn3bhYG3G84khRjHb+N+MLyJxQ/yb2zLnrmgOFJYzblGGXupUFIUjRRWsP1zE5qPFRr32kz5M+yMLM5WKhzoH0szaNHeb6dLCmaGRXszZepwsmdUuhDAiP+7KY/uJUh7oFEBbr4YZifnojrb4O9nw0E+7KdPzCMk3acfYmFPM412DaOfvpNe6b5QkhSZscIQXj3W9sCDxzE05Oqsn50wFzyzbi/erKwn6zyq6f7qRTh9toPmLK+jz5SbSjhXrrG5jlVlwju92nGR4lDcJwca5/MyNei85HAWYuny/oUMRQgjgQq/aaysPEORsy90xvg02gc/W0py5I6M5WVrJI4v3NEiZN+J0WRXPLt9PjE8zJnUN1Fu9N0uSQhP3bnIY8b6OPLZkL+sPFzVo2Wcra3h08W5C/ruaD9YfoY27PVN7BfPJHW159/Yw7on1YevxEjp8uIHJy/aiaULbp72+MhsrczVj4n0Nsn1dQ/JrbsP4Dv78sjefjJOlhg5HCCFYtjefvfnnuK+9H8Fudg1ado9gV+5v78f87SdYnX26Qcu+mim/7qe0spapvYJxNZI1Ca/EsPtviVtmbqbmtwkdiHlvHYNnb2Xjo11p7W5/y+X+tr+AB37YRe7ZSga39eT+9v50b+mCvdWlH5mSihrGfZ/BjL8Os/9UGUvHtcfMiKbX60LOmQoW7czl7hhvuhnpItU366WkVnyz5Tgvr8hi2f3tDR2OEKIJUxSF/6w6iI+jNcOjdbP123uDwlm+/xQTvt/JvmcTdPrjfv3hImZvPc698b4Mauups3oagvQUNgJu9lasfKAjWkUh4bON5BSV17us02VVjFqwndtmpWFppuab4VGkjIxhQJjHZQkhgJOtBT+NjefF3iEs33+Ke79r/Pvqfrj+MAB3RfsY5YXC9eHVzJqHOgewfH8B24xgHS8hRNO14cgZth4vYXScLyGut97JcSXNrC2YNTyKw2cqeHqZ7ibaVddqeejH3Xg5WPFotxZGP7LUOL7RBKEeDqQ+0Inyag0dPtrAzpscBlQUhfnbThD29loWZuQyoYM/v45vz9j2/ldMBv9JpVLxev82F/bV3X6Sj9cfuZWXYtRKztcwa/Mx+rRyo0fLxtFLeNHUxBAszdS8tCLL0KEIIZqwjzccoZmVOUMjvXS6GcBtYR4Mi/Lii01H2aqja+PfX3eYvQXnmNKzJTE+jjqpoyGZXFK4YsUKWrduTXBwMNOnT7/s8ffee4+wsDAiIyNJTEzk6NGjBojSMOL8nFj7cCcUBbp88vcNL0p8oLCMpC83M/rbHbjbWzF/ZAwf3tGWUI+bm+314eC2dPB3Yupv+9mb3zjXT5y/7QRl1RrujvHG7jrJsqnxcLDikS6BrMg8xY4TJYYOp0EVV1Qza/NRnly6h4d+3MWMNYfILpTZ1kIYm+PF51m8O59BbT2I8m6m8/o+HxKJo7U5Y7/LoFajbdCyD54u59U/s0ho6cI9cQ03WUaXTCop1Gg0PPLII/z+++/s27eP7777jn37Lu32jYmJIT09nV27djF06FCmTJlioGgNI9bXia1PdCPY1Y6x32WQ9MUmth0vueKQ7s7cUsYv2kn422vZcrSYqT1bsuS+eO6K9anXzhxmahU/jInHXK1m3MKMRjeMrCgKX20+Sht3e/q0djd0ODrxTEJLzM1U/Hf1QUOH0iAqazQ8/9t+vF9dyYQfdvHFxqN8t+Mkk3/dR6vpa+g3czM5ZyoMHaYQ4n++2JSDVqswNNIbczPdpygudpZ8emcE+0+VNegoiVarcN/CDMxUKqb0bImbEU8u+SeT6upIS0sjODiYoKAgAO666y6WLl1KWFhY3TE9e/as+3/Hjh2ZP3++3uM0tABnW9Kf6MaLKzL57O+jxH+wniAXWzr6O9Hc1pIzFTVsPV7MwdMVWJqpuDPCk3Ht/ekZ7HrL18j5Nbfhjf6tefznvczacowJHQMa6FUZ3tbjJezKO8fUXsG4O5jGH/jN8mxmzV3RPvywM5fnOrribeiAbsHx4vPc9vUWduedo38bd+6J9aFbC2ea2VhwpKicmZuPkZJ+nNC31jD37hiGRZnyqxXC9FXWaJi5+Rjdg1xIDHHVW70jor2Zm36C9/46xLAoL2J9nW65zI83HGHDkTNM69PqlnZi0TeTSgpPnjyJn9//bwvj6+vLli1brnr8119/Tf/+/a/42MyZM5k5cyYA+fn55ObmNmywV1BYWKjzOv7psRgnRrW2Y/aOAjYcO0fqgVOcr9FiZ6EmqLkV/du5k9jCgUivZliZ13L6VMOs8D64hRWfOFvx4m/7SPRSY63D/YD12aYfrT6KtZmKnl5qvXxeDGVseDPmbTvBu2sP8ba9paHDqZcjxZUM+/4ApVUa3uzpzZ1hrjSzVkNlCRWV4KGGlzq7MjrUgfuXHWTE3G3sTyhgfJx+dqbR97mgKZI21h1dte2iPac5XV7NbS1sKC06hT4XyPpPgic9c4oYOnsLqWPDsb6FDpLDxZVMXb6PDj52DAwwp7Dgxr9bDf25Namk8GbMnz+f9PR0/vrrrys+PnHiRCZOnAhAfHw83t766SXQVz119QHvBl/oravRaDlXVYtapcLO0gwLHXbNfzbMkqQvNzNnfzmv9Wujs3pAP21aVlXL0qwMklq70zMqRKdtZ2je3tAruIDfj5bwpYsbdlamtVtLYVkVY+dsoKJW4athUQyL9r7q++XtDdtC/BgwK41X1p7A282Z8Xrq3db3uaApkjbWHV207YJFBy8sVt25Dd5ONg1e/rV4A/Puseb2r9N4bm0+i8bE16uc6lotQ3/ciLlazSv9w4lrc/M/NA35uTWpbzYfHx+OH///yRMnTpzAx8fnsuNSU1N58803WbZsGVZWjXOYrz4szNQ421riZGOh86QmMcSV9v5OfLHxKBWNYDu8hTtOUlat4Y62no06IbxoSs9gzlRq+HhDjqFDuSm1Gi13zknnREklHwwKZ0SMz3XfL1tLc1ZM6EAHfyce/Gk3qQdO6SlaIcRFO06Usu1EKXdGeuKj54TwooFhHjzerQXf78zjvbWH6lXGM7/sY9PRYp5PDDGpYeOLTOrbrV27dmRnZ3PkyBGqq6tZuHAhycnJlxyzY8cOHnjgAZYtW4a7e+OcDGAKVCoV028LpbC8mulrTH/SwldbjhHkYku/Nqb3R14ffVq70bK5Fd+kHTepCUPT/jzAhiNneCkphJGxPje8kLq1hRl/TOyITzNr7pq3nRPF53UcqRDin2ZvPY6lmYrkMMMu7vxucjjdWjjz7PL9/Lw776ae+/nGHD7ecIS7Y3x4sHOASXYgmFTE5ubmfPLJJ/Tt25fQ0FCGDx9OeHg4L7/8MsuWLQNg8uTJlJWVMWzYMKKjoy9LGoX+JLR0IcanGXO2HkfTwFP99Wl/wTnSjpUwONwTL0fD/ILVN5VKxYPxnmSfLuenXTd3YjSU9YeL+M+qbAaFe/BAp4CbXiTW0caC5ePbU16tYUhKOtomtG2jEIZUWaNh/rYTJLR0pZ2/k0FjMVOr+OX+9rR0seWu+dv5M+vGRg7mbzvBI4t30y3ImVf6htDc1jSvxzappBBgwIABHDhwgEOHDvHCCy8A8Nprr9Ulf6mpqRQUFJCRkUFGRkZdsij0T6VSMbVXCMdLKvk67cbWTDRGC3fkolZB3ybSS3jRHaHONLM254tNxr/WZ2WNhvHf78TLwYqpiSH13lu0rVcz3k0OJ+14Ca+tPNDAUQohrmTpnnyKz9eQHO6h04mJN8rRxoK/HumCTzNrbpuVxsxNR686YqLVKkxflc3ob3cQ6+PIB8nhtHK7uTV+jYnJJYXCtNwZ4YmPozVfmkBicSWKorAw4yRxvo50DGhu6HD0ysZCzfj2/qw9eJqsU8a9GPl/VmVzoLCc5xND6HCLPQ0PdQ4gMcSV6asPkmnkr1uIxuDrtGN4Olhxe7h+Zv/fCA8HK7Y91Z1o72Y88OMu+s7czNZj/7/mr6IorD9cRI/PNvLcb5n0aeXG18MjifVzMmzgt0iSQqFT5mZqHukcyPaTpaTpaBshXdpxspQDheX0aeVGM2vTmoXbEB7pGohWgXfW1O+ia304VlzBO2sO0be1GyNjfW551wCVSsXsEdGoVTDxh10NFKUQ4kqOnqkgNfs0t4d54GegCSZX42RjwebHu/Fi7xA2HDlD+w/X4zntT2Lf+wvPaX/S/dON7M47yytJrfhmRBRRPk6GDvmWSVIodO7e9n6YqeDzv3MMHcpNW7gjFzO1iv6hxvMLVp+CXOzo28aNJXvyqag2zlnkz/+WiaLAo10CcW6g63j8mtvwSp9WrD98htlpxxqkTCHE5VLST4ACt4d5GOU2cGZqFa/3b8PRF3rzYu8QOvg3x8bcjA7+zZnWpxWpD3TixaQQg82YbmiNdp1CYTy8mlnTt7U7v+wr4Hx1LTaWpvGx02ovDB13CmhOrK/xb2SuK092D6LvzC18vvEoTye0NHQ4l9h6rIQF209yXzs/khp468GnerTkm7TjPP9bJkMjvXBogj3FQuiSVqswO+0Y7fydSAjW3w4m9eHmYMXr/XW75q4xkJ5CoRcTOwVQVFHDbBOacLLpaDHHSyrp08qtXntBNxa9Q9xo4WxLylbjeu8UReGpZXtxtrXgwU4Bt7xF479ZmKmZNTyK/HNVPLF0b4OWLYSANQdPk1N8nuQwDxysTaOzoLGTpFDoxYBQd9zsLVm003S2h1u44yRWZuomszbh1ajVKh7v1oLd+edIPWA8W4f9vCefDUfO8EDHAOJ1dHF3tyAX7or2Zt62E2QWyKQTIRrSN2nHcbAyJ7lt07w8xxhJUij0wsJMzX3t/Pj7yBmjn8kKoNEq/LAzjy4tmtPWq5mhwzG4e9v5YWOh5sN1hw0dCnBh2OmlFVkENrfh3va+qG9wker6eOf2MNSoeFJ6C4VoMMUV1fy0O49+bdwIdTfdJVwaG0kKhd7c38EfjQKfmMDWaZtyzlBQVkViiGuTHjq+yNHGgtFxvvx5oJCTJYbf7eOHnbnszT/HhI7+hLja67QuXycbHuveghVZhazONp6eUiFM2aKMXKpqtSSHeWBugjt/NFbyTgi9aeVmTwd/J37PPGX0W6ct2ZOPhZmK3iFNe+j4nx7vFkS1RmHGX4ZdnkajVXj1zwMEOdtyV/StL0FzI15IDKG5jQVTft1v9J9dIUzBnK3HCXa1pVeIcU8waWokKRR6NTrOl0NFFaw9VGToUK5KURR+3p1POz8n2nrJsMZFYZ4OdG3hzMIdudQacNvC7zNy2X+qjAkd/QlytdNLnY42Fkzr24ptJ0qZt+2EXuoUorHaX3COLcdKGBjmgVcza0OHI/5BkkKhV0OjvFGrYIERf7HuzjvH4TMVJLR0wdZEls/Rl6d6BJF/roq5Bnr/NFqF11YeoKWLLSNjfPRa90OdAwlsbsOrfxxAI/siC1FvKVtPYKaC/q3djXJtwqZMkkKhVx4OVvQIcuHPA4VoDNjbdC1LduehAhk6voLbwzzwdLDiy42G2bZwUcZJMv/XSxjgbKvXui3M1Lw9MJTDZyp4z8BD6EKYKo1WYd6243Ru4UzHwKa1dagpkKRQ6N09cb4cL6lkRdYpQ4dyRUv25BPp3Uxny5yYMnMzNZO6BpJ2vIR0PW9bqNEqvPbnAYJdbRkR7a3Xui8aGuVNtHcz3l17yGh3eBHCmKUeKCT3bBW3h3k0ya1DjZ0khULv7ojwxFytYlGG8a1ZeKSogp25Z+nZ0kUWU72KiR0DsDRT8bae90NelHGSrMJyJnQIINBZP9cS/ptKpeL9QeEUlFUz7Y8DBolBCFM2Z+txHK3N6dtKRmKMkSSFQu+cbS3pHeLKnwdOU1NrXEPIP+/JAyChpYuBIzFebvZWDIn04tf9BZwpr9ZLnf/sJRwa5aWXOq8mIdiVXsGufLnpKKfLqgwaixCmpOR8DUv25NO3tRttPGQSnzGSpFAYxD1xvhScq+KXffmGDuUSS/bkE+xqS9cgSQqv5akeLTlfo+V9PS1m/c9ewhZ6vpbwSt4bFMa5qlqeXb7f0KEIYTIWZZykqlbL7WEeDb4tpWgY8q4IgxgU7omVuZrvd+YZOpQ6p85VseHIGXq2dMXFztLQ4Ri1eD8nYnyaMXfbCbQ6non7z17CIZFeRjFbMcrbkaFRXizYdpIjReWGDkcIkzBn6wlautjSQ0ZijJYkhcIgHKzN6dPKjdXZxjOEvGxvPooiQ8c36qkeLTlWfJ6FGSd1Ws8/ewmDXAzfS3jR2wPD0KLI9ndC3IDMgnNsPlrM7WEe+DrZGDoccRWSFAqDGRHtTWF5tdEMIS/Zk493MysSgiUpvBHDorxws7Pkw3VHdFaHMfYSXhTobMuEDgH8sq+A7SdKDB2OEEYtJf3C2oT92sjahMZMkkJhMLeHe2BhpuLHXYYfQj5XWUvqgUISWrrKCvs3yMrcjCk9g0k7XsJv+wp0Uoex9hJe9GrfVthYmPHU0n2GDkUIo6XRKsxNP07nQGc6BsjahMZMkkJhMM2sLUgKuTCEXGvgIeTfM09RrVFIaOkiv2JvwkOdA2huY8FrKxt+eZaqWg0vrcgixNWOYVHG1Ut4kau9FZMTWvLX4SJWGum6m0IY2qrsC2sTDgzzwNFG1iY0ZpIUCoMaEeNNQVk1v2Ua9gt1ye48mttYkCibs98UOytzpvRsyZZjJfzZwEnRJxtyOFxUwePdWtDCxTDrEt6IZxJa4mpryZRf96Mosv2dEP82Z+sJHK3N6d/G3dChiOuQpFAYVHL4hYWsf9hpuIWsq2o1LN9/iu5Bzvg3lwugb9ajXVvgZGPBqw24mPPpsipeX3mAzoHNGRJp2HUJr8fOypxX+7UiI/cs8414T28hDOFMRTWLd+fRp7UbbTzsDR2OuA5JCoVBOdlY0CvYlVXZp9FqDTOEvDr7NOeqaukZ7Iq5mfxJ3Cw7K3MmJ7Rk49Fi/mig3sLXVmZzrqqWx7u1wNMErvGc0DGAFs42vLwii2ojmU0vhDGYl36Cqlotd7T1xELOr0bP5N6hFStW0Lp1a4KDg5k+ffplj1dVVTFixAiCg4Pp0KEDOTk5+g9S3JSRMT7knavij6xCg9T/8558bC3M6BUis47r69GuLXC2tWDKL7c+hJp1qozPN+YwuK0nfVubxnCThZmajwa3Jaf4PC+tyDR0OEIYBUVRmLn5KG09HegVItvamQKTSgo1Gg2PPPIIv//+O/v27eO7775j375LZ/19/fXXNG/enIMHD/Lkk0/y7LPPGihacaOS23pgrlaxcIf+h5A1WoWf9+TTpUVzWrnJ0EZ9OVib89ZtoezKO8snG3LqXY6iKDyyeDdW5moe6BhgUhelDwz3pE8rNz7ecIScMxWGDkcIg9uUU8y+gjIGt/XEw8HK0OGIG2BSSWFaWhrBwcEEBQVhaWnJXXfdxdKlSy85ZunSpYwdOxaAoUOHsmrVKrn428g521rSo6ULqw7qfwh5w5EiTpVVkxjsipW5mV7rbmzGtfcnwtOB11YeoKieewJ/veUYq7JP81jXFvQ0wUk/nw+NQKNVeOCHXYYORQiDm7n5KHaWZgwM8zB0KOIGmRs6gJtx8uRJ/Pz86m77+vqyZcuWqx5jbm6Oo6MjRUVFuLpe+gUzc+ZMZs6cCUB+fj65ubrvpSosNMzwqCno38KOVdmn+WFzFt0CHW/4ebfapnM3HcPSTEVMc0UvnwFTUp+2fbu3D7ctyOSuOZtIubPVTT03p6SKp5buI9LdhiEtrSgsMI5FzW+GNfBgnDsfpRWQsm4vScFXXpNNzgW6J22sOzfStiWVtSzccZKkoGZ4qsvJzT2vh8hMn6E/tyaVFDakiRMnMnHiRADi4+Px9vbWS736qsfUjG3mwrMrj/LHsSpGdL65Nqpvm2q1Cn8c3kvnQGe6hAdhZ9Vk/xyu6mbb1tsbnjlZw9trDrH8WA0TOgbc0POqajXcvuhvVCo1bw5sS1wbz/qEaxSm3+nB4qzVvPRXLkPat8Le+spD4HIu0D1pY925Xtsu3nCEKo3CXe2CCPDz1VNUjYMhP7cmNXzs4+PD8ePH626fOHECHx+fqx5TW1tLaWkpLi4ygcDYudpb0TXIhdTsQr0NIacdL+FkaSW9gl0lIWxAr/drQ5yvI48u2UPaseLrHq/VKoz9LoPtJ0qZ1rcV/Ux8LTMbCzNSRkZzvKSSB3/abehwhNA7RVH4ctNRQt3tZe1XE2NSSWG7du3Izs7myJEjVFdXs3DhQpKTky85Jjk5mZSUFAB+/PFHevXqZZQ7IYjL3R3jw/GSStYeOqOX+n7alYe5WkXPYDlpNSRLczXLx3fAydqc/l9tYceJ0qseW6vR8uBPu1iUkctjXVswrr1/o1gWqFeIGxM7+rNg+0mdbQEohLFae6iIPfnnGBblZRJLSon/Z1JnX3Nzcz755BP69u1LaGgow4cPJzw8nJdffplly5YBcP/991NUVERwcDDvvffeFZetEcZpcFtP1Cr4drvuFwBWFIWfduXR3t+JKO9mOq+vqfFwsGLNQ50xV6tI+Gwj3247cdmEr2PFFQyYtYWvNh/jvnZ+vJgUYlKzja/n/UHh+DvZMP77nZSerzZ0OELozccbjuBobc7gtqZ7GUhTZXJjZgMGDGDAgAGX3Pfaa6/V/d/a2poffvhB32GJBuDuYEXXFs6k/m8ha7Vad79ZMk6e5ciZCu6J9cHB2uT+DExCqKcDGx/tSvI3adzz7Q5m/HWIIZFeOFiZk368lO935qIoCi/2DuGJ7kG42FkaOuQGZWtpzrejYuj+6UZGzt/B8vHtZdRCNHpHz1SwdE8+Y+J8aeslP7hNjUn1FIrG764YH44Wn+evQ0U6reeHXbmYqaCXXO+iUy1d7dj5dA9e6dOKsioNL/6exeM/7+WXffn0be3G4rHxvNA7pNElhBd1aeHCi71b8XvmKV5fmW3ocITQuc83HgVgaKSX7GBignTSRfL0008zbtw4wsPDdVG8aMSGRHjx6OLdzNl6gp46WgFfq1VYsO0kHfybE+d748vfiPoxN1MzrW9rpvVtzZGicgrLqvFwsMLb0bpJfGlM69uKtGPFvPZnFu39HOkXKmu2icbpfI2Gr7YcpUdLF7oGyQRPU6STM3JoaCgTJ06kQ4cOfPHFF5SWXv1CcyH+yd3BiqRWbqzIOkWNjvaQ3XDkDMdKzjMg1J1mV1kuROhGCxc72gc0J8DZtkkkhAAqlYrvx8Tj39yGkQu2c+h0uaFDEkInvtt+kjMVNYyI8m5U1wc3JTo5K48fP56///6buXPnkpOTQ2RkJHfffTdr1qzRRXWikRnXwZ9TZdX8sFM3i0nP334CGws1vVvJXpxCPxyszfl9Qgc0Wuj1+SZOlcnEE9G4aLUK7607TIirHbeFmfayUk2Zzn6qazQaMjMzyczMxNXVlaioKN577z3uuusuXVUpGonbwzxwsDJjwY6TDV52ZY2G7zNy6RnsSoSXQ4OXL8TVtHZ3YPn49pwqq2LIoixOnavfVoBCGKPfM0+xN/8co+N88XWyNXQ4op50khQ++eSTtG7dmt9++43nn3+ebdu28eyzz/LLL7+wY8cOXVQpGhFrCzOGR3mzOvs0xRUN26OyfH8BpZW1DGjjjq2lzDoW+tUtyIWf7o3n5LkaOn60nuPFsvWXaBzeWnMQTwcrhkTKMjSmTCdJYWRkJDt37uTLL7+kffv2lzyWlpamiypFI3NvOz8qa7XM3HysQcudv+0krnaWssq+MJgBoR7MvSOYU2XVxLz3F1uOXn/XFyGM2aacM6w/fIZ7Yn1o4y4jMKasQZPC7du3s337dqKiosjKyqq7ffEfgKOjzPYU19elhTN+TtYs3pXXYGUWlVezfH8B/Vq7Eexq12DlCnGzugY0Y8OkLliaqen26d+8u/YQWq1y/ScKYYTeXnOIZlbmDI30Rq2WtThNWYOOnz399NNXfUylUrF69eqGrE40YiqVivva+fH6ymx25ZYS6X3rPya+23GSGo1C/zbujWIrNWHaon0c2fVMD+6Yk84zv+zj2+0nmTU8ihhZJkmYkMyCcyzdm8+4dn7E+cln19Q1aFK4Zs0atFotmzZtokuXLg1ZtGiC7u/gzxup2bz/12Fmj4y5pbIUReHzjTmEediTKLOOhZFwtbdi3SOd+Wj9YV5bmU38B+sYG+/Hc4nBhLjZGzo8Ia5r+uqDWKrVjIj2bjLLTDVmDf4OqtVqJk2a1NDFiibIv7kt/du48/PefMoqa26prHWHi9hXUMawSG88HKwaKEIhbp1KpeLx7i3JfLYnQyO9mLftBK2nr+G2r7bw2/4Cqmo1hg5RiCs6eLqc+dtPMiTSi26yWHWjoJO0PjExkZ9++glFkWtkxK15vFsQJedr+fR/WyfV16d/59DMypxBbWU3CWGc3OytWDQmnqxnezK+gz+bjhZz26w0XF76gyFztjJz01F25pZSq9HNou5C3Kw3Vh7AXKViTLwv1hZmhg5HNACdrMnx5Zdf8t5772Fubo61tTWKoqBSqTh79qwuqhONWGKIKyGudszacpQpPVuiUt38RcyHTpfz06487omVDdqF8QtytWPm8CjeHxTGtzty+X3/KdYdPsPi3fkA2FioaeNuTxt3B0Jc7WjlZkeImx1Bzra42FnW629EiJt1sZdwRJQ33VtKL2FjoZOk8Ny5c7ooVjRBarWKF3qHcO/CDOZsPc597f1vuowZaw9hplZxd4xc8yJMh52VBRM6BjChYwA1tRq2HCvhr0NF7M0/R07xedYdKmLhjpP8czzG3tKMQGdbgl3tCHa1I8jFlhBXO2J9HXG2tTTYaxGNzz97CW2kl7DR0NnqvcXFxWRnZ1NZWVl3X/fu3XVVnWjE7o714YXfM/lg3WHubed3Uz0heWcrmb31OANDPegRLGsTCtNkYW5G1yAXuv7juq2qWg0FZ6vYW3COzFNlnCip5OTZSk6WVrIzt5Tf9hdQrfn/lNHfyYZ4P0fa+zcnMcSVWB9HWT5E1Mvh4sq6XsIe0kvYqOgkKZw1axYffvghJ06cIDo6ms2bN9OpUydZkkbUi4WZmhd7h/DQT7tvurfw5RVZaLQKY+XXrGhkrMzN8He2xd/Zlv6hl14rqygK5ypryS4qZ8eJUnbmniXzVBlbjpXUDUM721jQt40b98T60qe1m/Siixv29oZcLNRyLWFjpJOk8MMPP2Tr1q107NiRNWvWkJmZyfPPP6+LqkQTMb6DPzPWHmLaHwe4O8YHqxs4Ee3OO8s3accYEe1NUmtZhkY0HSqVimY2FsT5OhHn61R3v1arkHXqHEv3FrD+yBl+23+K73bk0tzGglFxPjzZvSUtXGTfWnF1aceK+eVAMeM7+JEQLL2EjY1OfhpaW1tjbW0NQFVVFW3atCErK0sXVYkmwtxMzUd3tOVYyXme+23/dY/XaBUeWbwbO0tzJnT0l32OheDCNbqhns2YmhjC8vEdOPlyEjOHRRLn68jnG48S/N9VDJ2zlZ25pYYOVRghRVGY8ut+nKzMGBvvh5W59BI2Njr5pvT19aWkpITBgweTlJRE8+bNCQgI0EVVognp38ad5HAPPtqQw5BIL7q0uPqv1BlrD7H+8Bmm9WlFt2scJ0RTZmdlXjeZ5WBhGa+tzGbx7jwW787n7lgfZtwehmcza0OHKYzE8v2n+OtQEY+2c6dDQHNDhyN0QCc9hUuWLMHJyYlp06bx+uuvc//99/Pzzz/roirRhKhUKmbfFY2LrQUj5m3nZMn5Kx73R+YpXlqRSa9gFx7oFCBb2glxA4Ld7Jl7dwxHXkhkdJwvizJyafmf1by9+qDsyyyo1Wh59td9+DvZMCTUWa5BbaR09q5u2LCB2bNn06NHDzp16sTJkyd1VZVoQpxtLVl6XzuKK2ro+snfHDpTecnjS/fkM3j2Vlo42/JyUivp5RDiJrnZW5Fydww7nupOrK8jzy7fT5ePN3CsuMLQoQkDSkk/wb6CMh7pEkiwq1x32ljpJCl89dVXeeutt/jvf/8LQE1NDaNGjdJFVaIJ6hjozK/j23O6vJrElH2M+XYHb6YeoN/MzQyevRX/5jZ8ekdbWYJGiFvQ1qsZ6x7pzHvJ4ezKO0f422tZlCE/7puiiupaXl6RSYSnA0MiPWWB9EZMZ8PHy5Ytw87ODgBvb29Z0Fo0qJ7Brux/NoGEQAeW7snnxd+z2JN3joc7B/DTvfH0bu1u6BCFMHkqlYonewSx46nuBDrbcte87Ty3fJ9sYdrEfLDuCLlnq3isWwtautobOhyhQzqZaGJpeWGrpYu/JsrLy3VRjWjifJ1smXNHCM5u7uScOY+zrSUudpaYyYK8QjSoVu72pD/ZjbvmbWf66kPsyT/HotFxMqu/CSgsq2L66oP0CHJhYJjsHd/Y6aSncPjw4TzwwAOUlJTw1Vdf0bt3byZMmHBLZZ45c4akpCRCQkJISkqiuLj4smMyMjLo1KkT4eHhREZGsmjRoluqU5gGawtz2ng44O5gJQmhEDpiZW7G4nvjeal3CMv3naLHpxs5V1lr6LCEjr2Rmk15dS2TugbKNdpNgE6SQktLS3r37s2QIUPIysritdde49FHH72lMqdPn05iYiLZ2dkkJiYyffr0y46xtbVl7ty57N27lxUrVvDEE09QUlJyS/UKIYS4QKVS8Vr/Nnw9IoodJ0vp/PEGSs7XGDosoSOHTpfz+cYcBoV7ktRKNgBoCnSSFJ46dYrnnnuOo0eP0rt3b3r37n3LZS5dupSxY8cCMHbs2CsucdOqVStCQkKAC9cxuru7U1hYeMt1CyGE+H/3tfdnwahYMk+V0fHD9RSVVxs6JKEDL/yeiZlKxQOdAnC0sTB0OEIPdHJByBtvvMHrr7/On3/+yezZs5k0aRLDhw/n/vvvp2XLlvUqs6CgAC8vLwA8PT0pKCi45vFpaWlUV1dftb6ZM2cyc+ZMAPLz88nNza1XXDdDEtSGJ22qO9K2utMY2rabu4pZtwcx4ZfDdP3oL5aNbIOdpfHscNEY2tiQMvLLWZSRy6gIZ1rbVl/yHSltqzuGbludXSWsUqnw9PTE09MTc3NziouLGTp0KElJSbz99ttXfE7v3r3Jz8+/7P4333zzsrKvNSU+Ly+P0aNHk5KSglp95c7QiRMnMnHiRADi4+Px9va+0Zd2S/RVT1Mibao70ra60xjadqy3NzbNHBk5fztjluaw9pHORrX1WWNoY0NQFIV7ft5EcxsLHuzRhkD/y3eFkrbVHUO2rU6Swg8//JC5c+fi6urK+PHjeeedd7CwsECr1RISEnLVpDA1NfWqZXp4eJCXl4eXlxd5eXm4u195yZGzZ89y22238eabb9KxY8cGeT1CCCGubHi0D8Xna3jwx90kf7OV38Z3kAlfJu73zFOsPVTElJ4t6RjgbOhwhB7p5JrCM2fOsHjxYv744w+GDRuGhcWFaxHUajW//vprvcpMTk4mJSUFgJSUFAYNGnTZMdXV1dxxxx2MGTOGoUOH1v8FCCGEuGEPdArkzf6t+TOrkId+3GXocMQt0GgVnv11P/5ONoyN95UEv4nR2Y4mAQEBV3wsNDS0XmVOnTqVlStXEhISQmpqKlOnTgUgPT2d8ePHA/D999+zbt065syZQ3R0NNHR0WRkZNSrPiGEEDfu+d6tuL+9H19tOcb7aw8ZOhxRT99uP8Ge/AsbAYR6OBg6HKFnJrPyqIuLC6tWrbrs/vj4eGbNmgXAqFGjZDs9IYQwkC+GRnLwdAWTl+8nxM2OgeGehg5J3ITqWi0vr8iijbs9I2N9ZDu7JkgnPYVCCCGaHnMzNUvHtSOwuQ13L9hB1inZ3tSUzNx8lJzi80zqEoh/c1tDhyMMQJJCIYQQDcbRxoKVD3RCrYKBX6dRXiW7npiCsqpaXl95gDhfR4ZFeRk6HGEgkhQKIYRoUC1cbPluVByHTlcwNCUdRVEMHZK4jg/XH+ZUWTWTugTi7iDb2TVVkhQKIYRocP1D3XmlTytWZBUy7Y8sQ4cjrqGovJq3Vx+iR5ALgyOkl7Apk6RQCCGETrzcpxUDQt15MzWb5fuuvQuVMJy3Vh/kXFUtD3UOwEm2s2vSJCkUQgihEyqVioWj4vBvbsvob3eQc6bC0CGJf8ktreTjDUfoH+rOgFAPQ4cjDEySQiGEEDrjYG3O7xM6UK3RctusLVTWaAwdkviHt9ccpEajZWJHfxysTWaVOqEjkhQKIYTQqdbu9qSMjGZfQRn3LNguE0+MRMG5Kr7cdJQBoR70DnEzdDjCCEhSKIQQQueGRHozOaEli3fn89bqg4YORwDvrj1EtUbLfe38sLOSXkIhSaEQQgg9mX5bKL1DXHlxRRZ/Zp0ydDhN2umyKj7bmEOfVm70aS29hOICSQqFEELohVqt4qd74/FztGbEvG0cKSo3dEhN1vvrDlNRrWFce+klFP9PkkIhhBB608zaghUTO1CjUej/1RYqqmXHE30rrqjm4w059Apxpb/MOBb/IEmhEEIIvWrt7sCCe2I5UFjO0JRtMvFEzz5af4RzVbXc394Pe+klFP8gSaEQQgi9G9TWk5f7tOL3zFM8/vMeQ4fTZJytrOGD9YfpHuQs6xKKy8hPBCGEEAbxSp9WHDpdzscbcghobsPTCcGGDqnR+3zjUUrO1zK+gz+OsnuJ+BdJCoUQQhiESqVi9l3R5J6tZMqv+/F2tGFkjI+hw2q0qmo1fLj+MB38naSXUFyRDB8LIYQwGHMzNcvGtSfc04Gx3+1gye48Q4fUaH27/SR5Z6sYHeeLi52locMRRkiSQiGEEAZlZ2XO2oc7E+xix/C52/hxZ66hQ2p0tFqFGWsP0crVjsFtPQ0djjBSkhQKIYQwOGdbSzY+1pU27vbcNX8789KPGzqkRmVF1in2FZQxKs4XHycbQ4cjjJQkhUIIIYyCk40Ffz/ahQhPB8Z8l8GUX/ah0cpyNQ3hnTWH8LC3ZHi0l6FDEUZMkkIhhBBGo5m1BZse68qdEZ68s/YQfb7cTHFFtaHDMmnpx0tYe6iIkTE+tHKzN3Q4wohJUiiEEMKoWFuY8ePYeP47oA3rDhfRevoaluzKk0Wu62nG2kPYWZoxItoblUpl6HCEEZOkUAghhNFRqVRMTQxhzUOdcLQx586UdLp98jd/HTotyeFNOFJUwQ87c7kzwos4PydDhyOMnCSFQgghjFbXIBf2Tu7JS0kh7CsoI+GzTYS9vZb/pGaTfryEGo32hstSFIWqWk2Tuk7xg/WHUalUjIzxxsJMvvLFtZnM4tVnzpxhxIgR5OTkEBgYyPfff0/z5s2veOzZs2cJCwtj8ODBfPLJJ3qOVAghREOyNFfzWr82TE4I5v11h/hpVz4v/J7JC79nolaBVzNrApvbYG9ljqKAgkJpeSXVSjZl1RrKqmqpqNZQXq1BoyioAGdbC4Jd7Wjv35zeIa70beOGlbmZoV9qgyquqObrLcfo29qN7kEuhg5HmACTSQqnT59OYmIiU6dOZfr06UyfPp233nrrise+9NJLdO/eXc8RCiGE0CUHa3Ne7tOal/u0Zl/BOX7dm0/26XLyzlaRd7aKkvOVqFSgAswUDQ62lrjZW2JrYYbN//5ZW6ip1SicLq/maHEFMzcf5eMNR3C0Nmd8R38mJwTj4WBl6JfaIL7cdJTyag2jYn2wszKZr3thQCbzKVm6dClr164FYOzYsSQkJFwxKdy2bRsFBQX069eP9PR0PUcphBBCH8I8HAjzcLjkvlqNFq0CKhWcys/Dx+f6W+aVVFSzeHc+3+04yft/Hebzv4/ycp9WPN0jCHMTHm6trtXy8YYjtPd3ok9rd0OHI0yEyXziCwoK8PK6sL6Sp6cnBQUFlx2j1Wp5+umnmTFjhr7DE0IIYWDmZmoszdVYmKlveJatk60l4zr4s/LBTmx9ojuxvo5MXb6fzh//zfHi8zqOWHcWZpwk92wVo2J9ZEs7ccOMqqewd+/e5OfnX3b/m2++ecltlUp1xT/4zz77jAEDBuDr63vdumbOnMnMmTMByM/PJzdX99sqFRYW6ryOpkbaVHekbXVH2lb36tPGnmpYdGcLUjLseP2vE0TNWMO8O4OJ8TKttf0URWF6ahaBjpZ0clUa/PtNPr+6Y+i2NaqkMDU19aqPeXh4kJeXh5eXF3l5ebi7X94dvmnTJtavX89nn31GWVkZ1dXV2NvbM3369MuOnThxIhMnTgQgPj4eb2/vhnsh16CvepoSaVPdkbbVHWlb3atvGz/n7c2AqBYMmLWFId9n8/N97ejXxnSGYFMPFLK/8DwvJYUQ1yZIJ2sTyudXdwzZtiYzfJycnExKSgoAKSkpDBo06LJjFixYwLFjx8jJyWHGjBmMGTPmigmhEEIIcS1RPo5se7I7fk7WDP5mKysyL79kyVi9+9chXGwtuLOtlyxWLW6KySSFU6dOZeXKlYSEhJCamsrUqVMBSE9PZ/z48QaOTgghRGPj2cyaTY92xdfJmqEp28g4WWrokK5rb/45VmQWMizKm7ZeDtd/ghD/YDJJoYuLC6tWrSI7O5vU1FScnZ2BC0O/s2bNuuz4e++9V9YoFEIIcUtc7a1Y/VAnrM3V9P9qC7klxj355L2/DmFlrmZopJdJz54WhiGfGCGEEOIa/JvbsmJiB0rO15A0czPlVbWGDumK8s9WMn/bSW4P86BT4JU3dxDiWiQpFEIIIa4j3q85C+6JZX9BGfcs2G7ocK7o079zqNFouTvGB1tLo5pHKkyEJIVCCCHEDbgz0ovJPVuydG8BH68/YuhwLlFRXcvnG3PoHuRCQrBsaSfqR5JCIYQQ4ga92b8N7f2deHb5PnblGs/Ek5T0ExRV1DAqzofmtrJYtagfSQqFEEKIG2RupmbxvfEXJnOkbON8jcbQIVGj0fL26oO09XRgQKjprKcojI8khUIIIcRN8HG0Yd7dsWSfLufBH3YZOhy+3X6SnOLz3N/eD29HG0OHI0yYJIVCCCHETRoY5sGEjv7M3XaCZXsu355VXzRahf+uyqaVqx13RHgaLA7ROEhSKIQQQtTDB4PCCXS2YeIPOymuqDZIDD/tyiOrsJz72vsR4GxnkBhE4yFJoRBCCFEPtpbmLBoVx+nyakYt2KH3+hVF4c3UbAKa2zAk0kvv9YvGR5JCIYQQop7aBzRnaq9gfss8xTdbjum17mV7C9iVd5b72vkR7Cq9hOLWSVIohBBC3IJpfVsT6eXAk0v3cry4Qi911mq0PP/bfvydbBge7Y1KpdJLvaJxk6RQCCGEuAXmZmp+GBtPlUbL8HnbUBRF53WmpJ9gX0EZj3QJpI27vc7rE02DJIVCCCHELWrlZs/0AW3YfLSEd9Yc0mldFdW1vLwikwhPB4ZHeUkvoWgwkhQKIYQQDeDx7kF0C3Lm5T+y2Jd/Tmf1fLj+CLlnq3isWwsCXeRaQtFwJCkUQgghGoBKpWLR6DiszdUMm5tOjUbb4HWcLqti+uqDdAtyJjlc1iUUDUuSQiGEEKKBeDWz5rMhEewrKOPZX/c1ePlTft1PebWGR7sE4u5g1eDli6ZNkkIhhBCiAd0d68uQCE8+Wn+E9YeLGqzcdYeKmL31OKNjfbgtzKPByhXiIkkKhRBCiAb29YhoXO2tGDl/O2fKq265vLKqWu7/PgPvZlY80rUFtpbmDRClEJeSpFAIIYRoYI42Fvw4Jo6Cc1UM/HorGu2tLVPz9LK9HDpdwbQ+rYnzdWygKIW4lCSFQgghhA50DXLhg8HhbDpazL3f7aj3+oXzt51g5uZjjI7z5a4YH1mCRuiM9D8LIYQQOvJIlxZkFZTx8d85eDhYMSM5/Kaen3asmPHf7yTO15GpicE4WMvXttAd+XQJIYQQOvTB4Lbkl1Xx7l+HqdEofDA4/IZ6+7afKKHvzM242lry1m2hhHo46CFa0ZRJUiiEEELokFqtYuGoOCzU2/lowxEOFZXz7ahYmllbXPU5y/cVcM+C7dhamPHF0Ah6hbjqMWLRVMk1hUIIIYSOqdUq5t8Ty0tJIfyeeYrg/6xmdtoxKms0lxx3ouQ8E3/YycCv0/B0sGLmsEhuC/OQ6wiFXphMT+GZM2cYMWIEOTk5BAYG8v3339O8efPLjjt27Bjjx4/n+PHjqFQqfvvtNwIDA/UfsBBCCPEPKpWK1/q1IaGlC48s3sO4RTt5cule4v2ccLa14GjxebYeL8FMpWJkjDfP9GhJrJ+TocMWTYjJ9BROnz6dxMREsrOzSUxMZPr06Vc8bsyYMUyePJn9+/eTlpaGu7u7niMVQgghrq5XiBt7Jyew4O4Yuge5kFtayZZjJdRotEzs4M+PY+OYNTxKEkKhdybTU7h06VLWrl0LwNixY0lISOCtt9665Jh9+/ZRW1tLUlISAPb29voOUwghhLgutVrF3XG+3B3ni6IonK/RYK5WY2luMn01ohEymU9fQUEBXl5eAHh6elJQUHDZMQcOHMDJyYk777yTmJgYJk+ejEajuew4IYQQwlioVCpsLc0lIRQGZ1Q9hb179yY/P/+y+998881LbqtUqitedFtbW8v69evZsWMH/v7+jBgxgjlz5nD//fdfduzMmTOZOXMmAPn5+eTm5jbQq7i6wsJCndfR1Eib6o60re5I2+qetLHuSNvqjqHb1qiSwtTU1Ks+5uHhQV5eHl5eXuTl5V3xWkFfX1+io6MJCgoCYPDgwWzevPmKSeHEiROZOHEiAPHx8Xh7ezfQq7g2fdXTlEib6o60re5I2+qetLHuSNvqjiHb1mT6qpOTk0lJSQEgJSWFQYMGXXZMu3btKCkpqcu0V69eTVhYmF7jFEIIIYQwRSaTFE6dOpWVK1cSEhJCamoqU6dOBSA9PZ3x48cDYGZmxowZM0hMTCQiIgJFUZgwYYIhwxZCCCGEMAlGNXx8LS4uLqxateqy++Pj45k1a1bd7aSkJHbt2qXP0IQQQgghTJ5KURTF0EEYmqurq14WuC4sLMTNzU3n9TQl0qa6I22rO9K2uidtrDvStrqjj7bNycnh9OnTV3xMkkI9io+PJz093dBhNCrSprojbas70ra6J22sO9K2umPotjWZawqFEEIIIYTuSFIohBBCCCEkKdSni+siioYjbao70ra6I22re9LGuiNtqzuGblu5plAIIYQQQkhPoRBCCCGEkKTwiuzt7Q0dwjWNGzcOd3d32rZta+hQ6kWlUjFq1Ki627W1tbi5uTFw4MAGKf9G3r/MzEw6deqElZUVM2bMaJB6jZUu27uoqIiePXtib2/PpEmTbrk8U3W9z1xCQsJNzSh84YUX8PPzM/pz0fW8+eabhIeHExkZSXR0NFu2bKlXOWvXrmXjxo0NFldgYOBVl+Soj379+uHk5NRg57AbpVKpePrpp+tuz5gxg2nTpuk1hosa8rNqCucVY//brG+eIEmhkaitrb3hY++9915WrFihw2h0y87Ojj179nD+/HkAVq5ciY+Pz02VcTPtdSXOzs589NFHPPPMM7dUjiloiPa+Gmtra15//fVGn1jr2+23305aWpqhw7glmzZt4tdff2X79u3s2rWL1NRU/Pz86lVWQyeFt+JK557Jkyczb948vcdiZWXF4sWLGzTBNYR/t6mcV65MH3mCJIVXUVZWRmJiIrGxsURERLB06VLgwqKPoaGhTJgwgfDwcPr06VP3ZfvP3oDTp0/XLYidk5NDt27diI2NJTY2tu7ktnbtWrp160ZycjJhYWG8/PLLfPDBB3UxvPDCC3z44YeXxda9e3ecnZ11+Op1b8CAASxfvhyA7777jpEjR9Y9lpaWRqdOnYiJiaFz585kZWUBMGfOHJKTk+nVqxeJiYmUlZVx3333ERERQWRkJD/99FNdGS+88AJRUVF07NiRgoKCy+p3d3enXbt2WFhY6PiVGof6tHf37t3JyMioO65r167s3LnzknLt7Ozo2rUr1tbWun8RRm7t2rWX9BRNmjSJOXPmXHLMN998wxNPPFF3+6uvvuLJJ5+8rKyOHTvi5eWlq1D1Ii8vD1dXV6ysrIALmwR4e3sDsG3bNnr06EFcXBx9+/YlLy8PuHAOffzxx4mOjqZt27akpaWRk5PDF198wfvvv090dDTr16+nsLCQIUOG0K5dO9q1a8fff/8NwLRp0xg7dizdunUjICCAxYsXM2XKFCIiIujXrx81NTV18b399ttERETQvn17Dh48CHDNckePHk2XLl0YPXr0Za81MTERBwcH3TXmVZibmzNx4kTef//9yx7LycmhV69eREZGkpiYyLFjxygtLSUgIACtVgtAeXk5fn5+1NTUcOjQIfr160dcXBzdunUjMzMTuJBcPPTQQ3Ts2JGgoCDWrl3LuHHjCA0N5d57772kzieffJLw8HASExMpLCwEuGa5Dz74IB06dGDKlCmXlGMq55VGmSco4jJ2dnZKTU2NUlpaqiiKohQWFiotW7ZUtFqtcuTIEcXMzEzZsWOHoiiKMmzYMGXevHmKoihKjx49lK1bt9Y9JyAgQFEURSkvL1fOnz+vKIqiHDhwQImLi1MURVHWrFmj2NraKocPH1YURVGOHDmixMTEKIqiKBqNRgkKClJOnz59xRiPHDmihIeHN/yL1wM7Oztl586dypAhQ5Tz588rUVFRypo1a5TbbrtNURRFKS0tVWpqahRFUZSVK1cqd955p6IoijJ79mzFx8dHKSoqUhRFUaZMmaI8/vjjdeWeOXNGURRFAZRly5YpiqIokydPVl5//fWrxvLKK68o77zzToO/RmNS3/aeM2dOXftmZWXVfW6vZPbs2cojjzyi2xdixOzs7C5pU0VRlEceeUSZPXu2oij/f244d+6cEhQUpFRXVyuKoiidOnVSdu3adc1yTdW5c+eUqKgoJSQkRHnooYeUtWvXKoqiKNXV1UqnTp2UU6dOKYqiKAsXLlTuu+8+RVEutNP48eMVRVGUv/76q+4c9++/05EjRyrr169XFEVRjh49qrRp06buuC5duijV1dVKRkaGYmNjo/z222+KoijK4MGDlSVLliiKoigBAQHKG2+8oSiKoqSkpNS9b9cqNzY2VqmoqLjq6/33+68PdnZ2SmlpqRIQEKCUlJQo77zzjvLKK68oiqIoAwcOVObMmaMoiqJ8/fXXyqBBgxRFUZTk5GRl9erViqJcaPv7779fURRF6dWrl3LgwAFFURRl8+bNSs+ePRVFUZSxY8cqI0aMULRarfLzzz8rDg4Oyq5duxSNRqPExsbWfRcCyvz58xVFUZRXX3217nxwrXJvu+02pba29qqvz5jPK401TzCZvY/1TVEUnn/+edatW4darebkyZN1PU4tWrQgOjoagLi4OHJycq5ZVk1NDZMmTSIjIwMzMzMOHDhQ91j79u1p0aIFcOE6FxcXF3bs2EFBQQExMTG4uLjo5PUZWmRkJDk5OXz33XcMGDDgksdKS0sZO3Ys2dnZqFSqS37dJyUl1f36SU1NZeHChXWPNW/eHABLS8u6Hpu4uDhWrlyp65dj9OrT3sOGDeP111/nnXfe4ZtvvrmsV0DcPHt7e3r16sWvv/5KaGgoNTU1REREGDosnbC3t2fbtm2sX7+eNWvWMGLECKZPn058fDx79uwhKSkJAI1Gc0mv6MVe7O7du3P27FlKSkouKzs1NZV9+/bV3T579ixlZWUA9O/fHwsLCyIiItBoNPTr1w+AiIiIS87VF+sZOXJkXW/ttcpNTk7GxsbmVpulwTVr1owxY8bw0UcfXRLfpk2bWLx4MQCjR4+u640bMWIEixYtomfPnixcuJCHH36YsrIyNm7cyLBhw+qeX1VVVff/22+/HZVKRUREBB4eHnWf2fDwcHJycoiOjkatVjNixAgARo0axZ133nndcocNG4aZmZkOWkU/GmOeIEnhVSxYsIDCwkK2bduGhYUFgYGBVFZWAtQNhwCYmZnVdQubm5vXdctfPBbg/fffx8PDg507d6LVai/pErezs7uk3vHjxzNnzhzy8/MZN26czl6fMUhOTuaZZ55h7dq1FBUV1d3/0ksv0bNnT5YsWUJOTg4JCQl1j/27va7EwsIClUoFXHh/bvX6w8biZtvb1taWpKQkli5dyvfff8+2bdsMFLlp+OffP1x6Dvin8ePH85///Ic2bdpw33336Ss8gzAzMyMhIYGEhAQiIiJISUkhLi6O8PBwNm3adMXnXPzbvdptAK1Wy+bNm684vHjx/KxWqy85F6jV6kvOBf8s9+L/r1XujZx7DOWJJ54gNjb2hj5PycnJPP/885w5c4Zt27bRq1cvysvLcXJyuuRykX/6Z5v+8/vv3236TyqVCq1We81yjblNb0RjzBPkmsKrKC0txd3dHQsLC9asWcPRo0ev+5zAwMC6L84ff/zxkrK8vLxQq9XMmzcPjUZz1TLuuOMOVqxYwdatW+nbt++tvxAjNm7cOF555ZXLekpKS0vrJkL8+5qsf0pKSuLTTz+tu11cXKyTOBuL+rT3+PHjeeyxx2jXrl1dT6y4soCAAPbt20dVVRUlJSWsWrXqisd16NCB48eP8+23315ybWdjk5WVRXZ2dt3tjIwMAgICaN26NYWFhXVJYU1NDXv37q07btGiRQBs2LABR0dHHB0dcXBw4Ny5c3XH9OnTh48//viSsm/WxXoWLVpEp06dGqxcQ3B2dmb48OF8/fXXdfd17ty5biRlwYIFdOvWDbjQg9uuXTsef/xxBg4ciJmZGc2aNaNFixb88MMPwIUesH9fP3w9Wq227nvv22+/pWvXrg1SrjFrjHmCJIX/Ultbi5WVFffccw/p6elEREQwd+5c2rRpc93nPvPMM3z++efExMRcMhvs4YcfJiUlhaioKDIzM6/568jS0pKePXsyfPjwq3arjxw5kk6dOpGVlYWvr+8lJwJT4uvry2OPPXbZ/VOmTOG5554jJibmmr18L774IsXFxbRt25aoqCjWrFlzw3Xn5+fj6+vLe++9xxtvvIGvry9nz56t1+swFfVp77i4OJo1a3bNHojAwECeeuop5syZg6+v7yXDb03BxXOGn58fw4cPp23btgwfPpyYmJirPmf48OF06dLlqon2lClT8PX1paKiAl9fX4MtM3IrysrKGDt2LGFhYURGRrJv3z6mTZuGpaUlP/74I88++yxRUVFER0dfMrPY2tqamJgYHnzwwbpz2+23386SJUvqJpp89NFHpKenExkZSVhYGF988cVNx1dcXExkZCQffvhh3USN+pbbrVs3hg0bxqpVq/D19eWPP/646Xhu1dNPP33J987HH3/M7NmziYyMZN68eZdMRhgxYgTz58+vG+6FC4nj119/TVRUFOHh4XWTJm6UnZ0daWlptG3bltWrV/Pyyy/fUrnGfF5pzHmC7GjyLzt37mTChAkGWw5Cq9USGxvLDz/8QEhIiEFiEOKi3NxcEhISyMzMRK2W35BXUp9zxsCBA3nyySdJTEzUYWSmJyEhgRkzZhAfH2/oUIS4qsacJ8hZ/h+++OILRo4cyRtvvGGQ+vft20dwcDCJiYmSEAqDmzt3Lh06dODNN9+UhPAqbvacUVJSQqtWrbCxsZGEUAgT1NjzBOkpFEIIIYQQ0lMohBBCCCEkKRRCCCGEEEhSKIQQQgghkKRQCCHqmJmZER0dTXh4OFFRUbz77ruXLEitC5MnTyY8PJzJkyfrtB4hhLgemWgihBD/Y29vX7et2alTp7j77rvp0qULr776qs7qdHR05MyZM3rZ7qu2thZzc9nISghxZdJTKIQQV+Du7s7MmTP55JNPUBSFnJwcunXrRmxsLLGxsXULLo8ZM4aff/657nn33HPPZQv0KorC5MmTadu2LREREXW7aSQnJ1NWVkZcXFzdfXBhHbKQkBAKCwvrbgcHB1NYWEhhYSFDhgyhXbt2tGvXjr///huAtLQ0OnXqRExMDJ07dyYrKwu4sEtNcnIyvXr1kmVwhBDXpgghhFAURVHs7Owuu8/R0VHJz89XysvLlfPnzyuKoigHDhxQ4uLiFEVRlLVr1yqDBg1SFEVRSkpKlMDAQKWmpuaSMn788Ueld+/eSm1trZKfn6/4+fkpubm5V61TURRl2rRpyvvvv68oiqL88ccfyp133qkoiqKMHDlSWb9+vaIoinL06FGlTZs2iqIoSmlpaV29K1eurDt+9uzZio+Pj1JUVFSvNhFCNB0yjiCEEDegpqaGSZMmkZGRgZmZGQcOHACgR48ePPzwwxQWFvLTTz8xZMiQy4ZoN2zYwMiRIzEzM8PDw4MePXqwdetWkpOTr1rfuHHjGDRoEE888QTffPNN3VaDqampl2z5dfbsWcrKyigtLWXs2LFkZ2ejUqmoqampOyYpKQlnZ+eGbA4hRCMkSaEQQlzF4cOHMTMzw93dnVdffRUPDw927tyJVqvF2tq67rgxY8Ywf/58Fi5cyOzZsxukbj8/Pzw8PFi9ejVpaWksWLAAuDCUvHnz5kvqB5g0aRI9e/ZkyZIl5OTkkJCQUPfYtfZRFUKIi+SaQiGEuILCwkIefPBBJk2ahEqlorS0FC8vL9RqNfPmzUOj0dQde++99/LBBx8AEBYWdllZ3bp1Y9GiRWg0GgoLC1m3bh3t27e/bgzjx49n1KhRDBs2rG4iSp8+ffj444/rjsnIyACgtLQUHx8f4MJ1hEIIcbMkKRRCiP85f/583ZI0vXv3pk+fPrzyyisAPPzww6SkpBAVFUVmZuYlvW8eHh6EhobWDfH+2x133EFkZCRRUVH06tWLt99+G09Pz+vGc3Eiyj/L/eijj0hPTycyMpKwsDC++OILAKZMmcJzzz1HTEwMtbW1t9IMQogmSpakEUKIW1RRUUFERATbt2/H0dGxwcpNT0/nySefZP369Q1WphBCXI30FAohxC1ITU0lNDSURx99tEETwunTpzNkyBD++9//NliZQghxLdJTKIQQQgghpKdQCCGEEEJIUiiEEEIIIZCkUAghhBBCIEmhEEIIIYRAkkIhhBBCCIEkhUIIIYQQAvg/6wufnJZIagIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 648x648 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fb.plot_components(forecast,uncertainty=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Compare the Prophet prediction vs Arima. Use the last 7 values we have in the timeseries as ground truth."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TUTORIAL\n",
    "https://www.digitalocean.com/community/tutorials/a-guide-to-time-series-forecasting-with-arima-in-python-3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### correlogram\n",
    "https://stats.stackexchange.com/questions/182627/interpretation-of-correlogram/182784"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.2"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}