Demand_Forecast_Model_Comparison.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pylab as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df = pd.read_csv('J:\\MMM_Data\\customer_orders_df.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "33696"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(co_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df.rename(columns={'Requested Date': 'Requested_Date', 'Creation Date': 'Creation_Date', 'Shipped Date':'Shipped_Date'}, inplace=True)\n",
    "co_df.rename(columns={'Order Number': 'Order_Number', 'Order Line': 'Order_Line', 'Requested Quantity':'Requested_Quantity', 'Shipped Quantity':'Shipped_Quantity'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df['Creation_Date'] =pd.to_datetime(co_df.Creation_Date, format='%d.%m.%Y %H:%M')\n",
    "co_df['Requested_Date'] =pd.to_datetime(co_df.Requested_Date, format='%d.%m.%Y')\n",
    "co_df['Shipped_Date'] =pd.to_datetime(co_df.Shipped_Date, format='%d.%m.%Y')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Questions to be asked\n",
    "1. what about the floating point values in Requested Quantity\n",
    "2. what about negative values in Requested Quantity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df['Delay']=(co_df['Shipped_Date']-co_df['Requested_Date']).dt.days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df[\"Deficit\"]=co_df[\"Requested_Quantity\"]-co_df[\"Shipped_Quantity\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order_Number</th>\n",
       "      <th>Order_Line</th>\n",
       "      <th>Outlet</th>\n",
       "      <th>Part</th>\n",
       "      <th>Creation_Date</th>\n",
       "      <th>Requested_Date</th>\n",
       "      <th>Shipped_Date</th>\n",
       "      <th>Requested_Quantity</th>\n",
       "      <th>Shipped_Quantity</th>\n",
       "      <th>Delay</th>\n",
       "      <th>Deficit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Order_01</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8WW91511052540M</td>\n",
       "      <td>2017-01-14</td>\n",
       "      <td>2017-01-14</td>\n",
       "      <td>2017-01-14</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Order_02</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>6YX87639578537D</td>\n",
       "      <td>2017-01-07</td>\n",
       "      <td>2017-01-07</td>\n",
       "      <td>2017-01-09</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Order_02</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>4RQ12578481053J</td>\n",
       "      <td>2016-12-30</td>\n",
       "      <td>2016-12-30</td>\n",
       "      <td>2016-12-30</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Order_03</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2DS35615142379C</td>\n",
       "      <td>2016-12-29</td>\n",
       "      <td>2016-12-29</td>\n",
       "      <td>2016-12-29</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Order_03</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5DG98783853149R</td>\n",
       "      <td>2016-12-27</td>\n",
       "      <td>2016-12-27</td>\n",
       "      <td>2017-01-06</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>10</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Order_Number  Order_Line  Outlet             Part Creation_Date  \\\n",
       "0     Order_01           1       1  8WW91511052540M    2017-01-14   \n",
       "1     Order_02           3       1  6YX87639578537D    2017-01-07   \n",
       "2     Order_02           7       1  4RQ12578481053J    2016-12-30   \n",
       "3     Order_03           1       1  2DS35615142379C    2016-12-29   \n",
       "4     Order_03           2       1  5DG98783853149R    2016-12-27   \n",
       "\n",
       "  Requested_Date Shipped_Date  Requested_Quantity  Shipped_Quantity  Delay  \\\n",
       "0     2017-01-14   2017-01-14                -1.0              -1.0      0   \n",
       "1     2017-01-07   2017-01-09                12.0              12.0      2   \n",
       "2     2016-12-30   2016-12-30                 2.0               2.0      0   \n",
       "3     2016-12-29   2016-12-29                 3.0               3.0      0   \n",
       "4     2016-12-27   2017-01-06                 8.0               8.0     10   \n",
       "\n",
       "   Deficit  \n",
       "0      0.0  \n",
       "1      0.0  \n",
       "2      0.0  \n",
       "3      0.0  \n",
       "4      0.0  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df_delay=co_df.loc[co_df[\"Delay\"]<0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(co_df_delay)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "drop_Req_Quant=co_df.index[co_df[\"Requested_Quantity\"] <= 0].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df=co_df.drop(co_df.index[drop_Req_Quant])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df.sort_values(by=['Requested_Date'], inplace=True, ascending=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order_Number</th>\n",
       "      <th>Order_Line</th>\n",
       "      <th>Outlet</th>\n",
       "      <th>Part</th>\n",
       "      <th>Creation_Date</th>\n",
       "      <th>Requested_Date</th>\n",
       "      <th>Shipped_Date</th>\n",
       "      <th>Requested_Quantity</th>\n",
       "      <th>Shipped_Quantity</th>\n",
       "      <th>Delay</th>\n",
       "      <th>Deficit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>7602</td>\n",
       "      <td>Order_4838</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>7WT30850004924P</td>\n",
       "      <td>2016-12-26</td>\n",
       "      <td>2016-12-26</td>\n",
       "      <td>2017-03-08</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>72</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Order_05</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>10LT38882262598Q</td>\n",
       "      <td>2016-12-26</td>\n",
       "      <td>2016-12-26</td>\n",
       "      <td>2016-12-26</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Order_06</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>9DG12017945528Y</td>\n",
       "      <td>2016-12-26</td>\n",
       "      <td>2016-12-26</td>\n",
       "      <td>2016-12-26</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9935</td>\n",
       "      <td>Order_6706</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>9TZ23479641614Z</td>\n",
       "      <td>2017-01-13</td>\n",
       "      <td>2016-12-27</td>\n",
       "      <td>2016-12-27</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Order_03</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5DG98783853149R</td>\n",
       "      <td>2016-12-27</td>\n",
       "      <td>2016-12-27</td>\n",
       "      <td>2017-01-06</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>10</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Order_Number  Order_Line  Outlet              Part Creation_Date  \\\n",
       "7602   Order_4838           1       2   7WT30850004924P    2016-12-26   \n",
       "8        Order_05           1       1  10LT38882262598Q    2016-12-26   \n",
       "9        Order_06           1       1   9DG12017945528Y    2016-12-26   \n",
       "9935   Order_6706           9       2   9TZ23479641614Z    2017-01-13   \n",
       "4        Order_03           2       1   5DG98783853149R    2016-12-27   \n",
       "\n",
       "     Requested_Date Shipped_Date  Requested_Quantity  Shipped_Quantity  Delay  \\\n",
       "7602     2016-12-26   2017-03-08                 2.0               2.0     72   \n",
       "8        2016-12-26   2016-12-26                 1.0               1.0      0   \n",
       "9        2016-12-26   2016-12-26                 2.0               2.0      0   \n",
       "9935     2016-12-27   2016-12-27                 7.0               7.0      0   \n",
       "4        2016-12-27   2017-01-06                 8.0               8.0     10   \n",
       "\n",
       "      Deficit  \n",
       "7602      0.0  \n",
       "8         0.0  \n",
       "9         0.0  \n",
       "9935      0.0  \n",
       "4         0.0  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#co_df.to_excel(\"Barkawi.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n"
     ]
    }
   ],
   "source": [
    "demand_part1 = co_df[\"Requested_Quantity\"].values.tolist()\n",
    "neg_demand1=[]\n",
    "for x in demand_part1:\n",
    "    if x <=0:\n",
    "        neg_demand1.append(x)\n",
    "print(len(neg_demand1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df[\"Indexdate\"]=co_df[\"Requested_Date\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df_indexed=co_df.set_index([\"Indexdate\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df_part = co_df.loc[co_df[\"Part\"]==\"8YE32821942352L\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order_Number</th>\n",
       "      <th>Order_Line</th>\n",
       "      <th>Outlet</th>\n",
       "      <th>Part</th>\n",
       "      <th>Creation_Date</th>\n",
       "      <th>Requested_Date</th>\n",
       "      <th>Shipped_Date</th>\n",
       "      <th>Requested_Quantity</th>\n",
       "      <th>Shipped_Quantity</th>\n",
       "      <th>Delay</th>\n",
       "      <th>Deficit</th>\n",
       "      <th>Indexdate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>18852</td>\n",
       "      <td>Order_13012</td>\n",
       "      <td>21</td>\n",
       "      <td>5</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2016-12-29</td>\n",
       "      <td>2016-12-29</td>\n",
       "      <td>2016-12-29</td>\n",
       "      <td>24.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2016-12-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16731</td>\n",
       "      <td>Order_11556</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-01-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3783</td>\n",
       "      <td>Order_3037</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-01-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>27482</td>\n",
       "      <td>Order_19193</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-01-05</td>\n",
       "      <td>2017-01-05</td>\n",
       "      <td>2017-01-05</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-01-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9909</td>\n",
       "      <td>Order_6699</td>\n",
       "      <td>50</td>\n",
       "      <td>2</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-02-09</td>\n",
       "      <td>2017-01-06</td>\n",
       "      <td>2017-01-06</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-01-06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Order_Number  Order_Line  Outlet             Part Creation_Date  \\\n",
       "18852  Order_13012          21       5  8YE32821942352L    2016-12-29   \n",
       "16731  Order_11556           2       4  8YE32821942352L    2017-01-04   \n",
       "3783    Order_3037          14       1  8YE32821942352L    2017-01-03   \n",
       "27482  Order_19193           7       8  8YE32821942352L    2017-01-05   \n",
       "9909    Order_6699          50       2  8YE32821942352L    2017-02-09   \n",
       "\n",
       "      Requested_Date Shipped_Date  Requested_Quantity  Shipped_Quantity  \\\n",
       "18852     2016-12-29   2016-12-29                24.0              24.0   \n",
       "16731     2017-01-04   2017-01-04                 3.0               3.0   \n",
       "3783      2017-01-04   2017-01-04                 1.0               1.0   \n",
       "27482     2017-01-05   2017-01-05                 7.0               7.0   \n",
       "9909      2017-01-06   2017-01-06                10.0              10.0   \n",
       "\n",
       "       Delay  Deficit  Indexdate  \n",
       "18852      0      0.0 2016-12-29  \n",
       "16731      0      0.0 2017-01-04  \n",
       "3783       0      0.0 2017-01-04  \n",
       "27482      0      0.0 2017-01-05  \n",
       "9909       0      0.0 2017-01-06  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co_df_part.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df_part_1 = co_df_part.loc[co_df_part[\"Outlet\"]==1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order_Number</th>\n",
       "      <th>Order_Line</th>\n",
       "      <th>Outlet</th>\n",
       "      <th>Part</th>\n",
       "      <th>Creation_Date</th>\n",
       "      <th>Requested_Date</th>\n",
       "      <th>Shipped_Date</th>\n",
       "      <th>Requested_Quantity</th>\n",
       "      <th>Shipped_Quantity</th>\n",
       "      <th>Delay</th>\n",
       "      <th>Deficit</th>\n",
       "      <th>Indexdate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>3783</td>\n",
       "      <td>Order_3037</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-01-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3784</td>\n",
       "      <td>Order_3038</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-01-09</td>\n",
       "      <td>2017-01-09</td>\n",
       "      <td>2017-01-09</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-01-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3753</td>\n",
       "      <td>Order_3024</td>\n",
       "      <td>52</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-01-23</td>\n",
       "      <td>2017-01-13</td>\n",
       "      <td>2017-01-14</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-01-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3711</td>\n",
       "      <td>Order_3017</td>\n",
       "      <td>57</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-01-11</td>\n",
       "      <td>2017-01-13</td>\n",
       "      <td>2017-01-13</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-01-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3703</td>\n",
       "      <td>Order_3015</td>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-02-01</td>\n",
       "      <td>2017-01-21</td>\n",
       "      <td>2017-01-21</td>\n",
       "      <td>6.7</td>\n",
       "      <td>6.7</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-01-21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3815</td>\n",
       "      <td>Order_3055</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-01-26</td>\n",
       "      <td>2017-01-22</td>\n",
       "      <td>2017-01-29</td>\n",
       "      <td>26.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-01-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3794</td>\n",
       "      <td>Order_3045</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-01-25</td>\n",
       "      <td>2017-01-25</td>\n",
       "      <td>2017-01-25</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-01-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3705</td>\n",
       "      <td>Order_3015</td>\n",
       "      <td>111</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-02-01</td>\n",
       "      <td>2017-02-01</td>\n",
       "      <td>2017-02-01</td>\n",
       "      <td>27.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-02-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3841</td>\n",
       "      <td>Order_3061</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-02-02</td>\n",
       "      <td>2017-02-02</td>\n",
       "      <td>2017-02-02</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-02-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3888</td>\n",
       "      <td>Order_3084</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-02-27</td>\n",
       "      <td>2017-02-27</td>\n",
       "      <td>2017-03-07</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-02-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3884</td>\n",
       "      <td>Order_3082</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-02-26</td>\n",
       "      <td>2017-03-02</td>\n",
       "      <td>2017-03-06</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-03-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3963</td>\n",
       "      <td>Order_3113</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-03-07</td>\n",
       "      <td>2017-03-07</td>\n",
       "      <td>2017-03-07</td>\n",
       "      <td>19.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-03-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3905</td>\n",
       "      <td>Order_3092</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-06-11</td>\n",
       "      <td>2017-03-20</td>\n",
       "      <td>2017-03-20</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-03-20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4033</td>\n",
       "      <td>Order_3151</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-03-26</td>\n",
       "      <td>2017-03-26</td>\n",
       "      <td>2017-03-27</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-03-26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3955</td>\n",
       "      <td>Order_3111</td>\n",
       "      <td>21</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-03-28</td>\n",
       "      <td>2017-03-28</td>\n",
       "      <td>2017-03-28</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-03-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3965</td>\n",
       "      <td>Order_3114</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-03-30</td>\n",
       "      <td>2017-03-30</td>\n",
       "      <td>2017-03-30</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-03-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4061</td>\n",
       "      <td>Order_3166</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-04-12</td>\n",
       "      <td>2017-04-15</td>\n",
       "      <td>2017-04-15</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-04-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4025</td>\n",
       "      <td>Order_3148</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-04-05</td>\n",
       "      <td>2017-04-18</td>\n",
       "      <td>2017-04-20</td>\n",
       "      <td>8.5</td>\n",
       "      <td>8.5</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-04-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4128</td>\n",
       "      <td>Order_3198</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-04-15</td>\n",
       "      <td>2017-04-18</td>\n",
       "      <td>2017-04-18</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-04-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4199</td>\n",
       "      <td>Order_3225</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-05-06</td>\n",
       "      <td>2017-05-06</td>\n",
       "      <td>2017-05-06</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-05-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4117</td>\n",
       "      <td>Order_3192</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-04-07</td>\n",
       "      <td>2017-05-06</td>\n",
       "      <td>2017-05-06</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-05-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4174</td>\n",
       "      <td>Order_3219</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-04-25</td>\n",
       "      <td>2017-05-09</td>\n",
       "      <td>2017-05-16</td>\n",
       "      <td>17.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-05-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4214</td>\n",
       "      <td>Order_3235</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-05-10</td>\n",
       "      <td>2017-05-10</td>\n",
       "      <td>2017-05-10</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-05-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4219</td>\n",
       "      <td>Order_3236</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-05-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4236</td>\n",
       "      <td>Order_3247</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-05-13</td>\n",
       "      <td>2017-05-16</td>\n",
       "      <td>2017-05-16</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-05-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4175</td>\n",
       "      <td>Order_3220</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-05-18</td>\n",
       "      <td>2017-05-18</td>\n",
       "      <td>2017-05-18</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-05-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4235</td>\n",
       "      <td>Order_3246</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-05-22</td>\n",
       "      <td>2017-05-22</td>\n",
       "      <td>2017-05-22</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-05-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4202</td>\n",
       "      <td>Order_3228</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-05-23</td>\n",
       "      <td>2017-05-23</td>\n",
       "      <td>2017-05-23</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-05-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4282</td>\n",
       "      <td>Order_3268</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-06-02</td>\n",
       "      <td>2017-06-02</td>\n",
       "      <td>2017-06-05</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-06-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4226</td>\n",
       "      <td>Order_3239</td>\n",
       "      <td>72</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-05-28</td>\n",
       "      <td>2017-06-06</td>\n",
       "      <td>2017-06-06</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-06-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4208</td>\n",
       "      <td>Order_3231</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-05-06</td>\n",
       "      <td>2017-06-07</td>\n",
       "      <td>2017-06-09</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-06-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4232</td>\n",
       "      <td>Order_3243</td>\n",
       "      <td>5000</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-05-27</td>\n",
       "      <td>2017-06-15</td>\n",
       "      <td>2017-06-15</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-06-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4322</td>\n",
       "      <td>Order_3285</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-06-18</td>\n",
       "      <td>2017-06-18</td>\n",
       "      <td>2017-06-18</td>\n",
       "      <td>20.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-06-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4373</td>\n",
       "      <td>Order_3303</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-06-18</td>\n",
       "      <td>2017-06-22</td>\n",
       "      <td>2017-06-22</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-06-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4148</td>\n",
       "      <td>Order_3206</td>\n",
       "      <td>42</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-04-27</td>\n",
       "      <td>2017-06-24</td>\n",
       "      <td>2017-06-24</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-06-24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4425</td>\n",
       "      <td>Order_3330</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-06-23</td>\n",
       "      <td>2017-07-04</td>\n",
       "      <td>2017-07-07</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-07-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4409</td>\n",
       "      <td>Order_3321</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-06-21</td>\n",
       "      <td>2017-07-04</td>\n",
       "      <td>2017-07-04</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-07-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4529</td>\n",
       "      <td>Order_3376</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-07-13</td>\n",
       "      <td>2017-07-13</td>\n",
       "      <td>2017-07-13</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-07-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4417</td>\n",
       "      <td>Order_3324</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-07-02</td>\n",
       "      <td>2017-07-14</td>\n",
       "      <td>2017-07-14</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-07-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4411</td>\n",
       "      <td>Order_3322</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-07-14</td>\n",
       "      <td>2017-07-22</td>\n",
       "      <td>2017-07-22</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-07-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4477</td>\n",
       "      <td>Order_3342</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-07-10</td>\n",
       "      <td>2017-07-23</td>\n",
       "      <td>2017-07-23</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-07-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4481</td>\n",
       "      <td>Order_3345</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-07-26</td>\n",
       "      <td>2017-07-26</td>\n",
       "      <td>2017-08-05</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-07-26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4522</td>\n",
       "      <td>Order_3370</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-07-17</td>\n",
       "      <td>2017-07-27</td>\n",
       "      <td>2017-08-05</td>\n",
       "      <td>16.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-07-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4591</td>\n",
       "      <td>Order_3404</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-08-01</td>\n",
       "      <td>2017-08-01</td>\n",
       "      <td>2017-08-07</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-08-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4543</td>\n",
       "      <td>Order_3385</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-08-02</td>\n",
       "      <td>2017-08-13</td>\n",
       "      <td>2017-08-13</td>\n",
       "      <td>12.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-08-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4595</td>\n",
       "      <td>Order_3406</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-08-10</td>\n",
       "      <td>2017-08-14</td>\n",
       "      <td>2017-08-14</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-08-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4519</td>\n",
       "      <td>Order_3369</td>\n",
       "      <td>44</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-07-31</td>\n",
       "      <td>2017-08-16</td>\n",
       "      <td>2017-08-16</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-08-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4588</td>\n",
       "      <td>Order_3402</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-08-18</td>\n",
       "      <td>2017-08-18</td>\n",
       "      <td>2017-08-18</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-08-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4657</td>\n",
       "      <td>Order_3431</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-08-21</td>\n",
       "      <td>2017-08-24</td>\n",
       "      <td>2017-08-24</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-08-24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4563</td>\n",
       "      <td>Order_3391</td>\n",
       "      <td>61</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-08-21</td>\n",
       "      <td>2017-08-28</td>\n",
       "      <td>2017-08-28</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-08-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4603</td>\n",
       "      <td>Order_3410</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-08-12</td>\n",
       "      <td>2017-08-28</td>\n",
       "      <td>2017-09-06</td>\n",
       "      <td>24.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-08-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4663</td>\n",
       "      <td>Order_3434</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>8YE32821942352L</td>\n",
       "      <td>2017-08-16</td>\n",
       "      <td>2017-08-28</td>\n",
       "      <td>2017-08-28</td>\n",
       "      <td>27.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2017-08-28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Order_Number  Order_Line  Outlet             Part Creation_Date  \\\n",
       "3783   Order_3037          14       1  8YE32821942352L    2017-01-03   \n",
       "3784   Order_3038           3       1  8YE32821942352L    2017-01-09   \n",
       "3753   Order_3024          52       1  8YE32821942352L    2017-01-23   \n",
       "3711   Order_3017          57       1  8YE32821942352L    2017-01-11   \n",
       "3703   Order_3015          63       1  8YE32821942352L    2017-02-01   \n",
       "3815   Order_3055          22       1  8YE32821942352L    2017-01-26   \n",
       "3794   Order_3045          13       1  8YE32821942352L    2017-01-25   \n",
       "3705   Order_3015         111       1  8YE32821942352L    2017-02-01   \n",
       "3841   Order_3061          15       1  8YE32821942352L    2017-02-02   \n",
       "3888   Order_3084          11       1  8YE32821942352L    2017-02-27   \n",
       "3884   Order_3082          15       1  8YE32821942352L    2017-02-26   \n",
       "3963   Order_3113           2       1  8YE32821942352L    2017-03-07   \n",
       "3905   Order_3092          19       1  8YE32821942352L    2017-06-11   \n",
       "4033   Order_3151           1       1  8YE32821942352L    2017-03-26   \n",
       "3955   Order_3111          21       1  8YE32821942352L    2017-03-28   \n",
       "3965   Order_3114          15       1  8YE32821942352L    2017-03-30   \n",
       "4061   Order_3166          27       1  8YE32821942352L    2017-04-12   \n",
       "4025   Order_3148          17       1  8YE32821942352L    2017-04-05   \n",
       "4128   Order_3198          13       1  8YE32821942352L    2017-04-15   \n",
       "4199   Order_3225           2       1  8YE32821942352L    2017-05-06   \n",
       "4117   Order_3192           9       1  8YE32821942352L    2017-04-07   \n",
       "4174   Order_3219           8       1  8YE32821942352L    2017-04-25   \n",
       "4214   Order_3235           2       1  8YE32821942352L    2017-05-10   \n",
       "4219   Order_3236           2       1  8YE32821942352L    2017-05-14   \n",
       "4236   Order_3247           6       1  8YE32821942352L    2017-05-13   \n",
       "4175   Order_3220           2       1  8YE32821942352L    2017-05-18   \n",
       "4235   Order_3246           2       1  8YE32821942352L    2017-05-22   \n",
       "4202   Order_3228           9       1  8YE32821942352L    2017-05-23   \n",
       "4282   Order_3268           3       1  8YE32821942352L    2017-06-02   \n",
       "4226   Order_3239          72       1  8YE32821942352L    2017-05-28   \n",
       "4208   Order_3231          12       1  8YE32821942352L    2017-05-06   \n",
       "4232   Order_3243        5000       1  8YE32821942352L    2017-05-27   \n",
       "4322   Order_3285           8       1  8YE32821942352L    2017-06-18   \n",
       "4373   Order_3303           8       1  8YE32821942352L    2017-06-18   \n",
       "4148   Order_3206          42       1  8YE32821942352L    2017-04-27   \n",
       "4425   Order_3330           7       1  8YE32821942352L    2017-06-23   \n",
       "4409   Order_3321          10       1  8YE32821942352L    2017-06-21   \n",
       "4529   Order_3376           7       1  8YE32821942352L    2017-07-13   \n",
       "4417   Order_3324           9       1  8YE32821942352L    2017-07-02   \n",
       "4411   Order_3322           3       1  8YE32821942352L    2017-07-14   \n",
       "4477   Order_3342           9       1  8YE32821942352L    2017-07-10   \n",
       "4481   Order_3345           2       1  8YE32821942352L    2017-07-26   \n",
       "4522   Order_3370          10       1  8YE32821942352L    2017-07-17   \n",
       "4591   Order_3404           2       1  8YE32821942352L    2017-08-01   \n",
       "4543   Order_3385           9       1  8YE32821942352L    2017-08-02   \n",
       "4595   Order_3406           5       1  8YE32821942352L    2017-08-10   \n",
       "4519   Order_3369          44       1  8YE32821942352L    2017-07-31   \n",
       "4588   Order_3402          12       1  8YE32821942352L    2017-08-18   \n",
       "4657   Order_3431          15       1  8YE32821942352L    2017-08-21   \n",
       "4563   Order_3391          61       1  8YE32821942352L    2017-08-21   \n",
       "4603   Order_3410          19       1  8YE32821942352L    2017-08-12   \n",
       "4663   Order_3434          16       1  8YE32821942352L    2017-08-16   \n",
       "\n",
       "     Requested_Date Shipped_Date  Requested_Quantity  Shipped_Quantity  Delay  \\\n",
       "3783     2017-01-04   2017-01-04                 1.0               1.0      0   \n",
       "3784     2017-01-09   2017-01-09                 6.0               6.0      0   \n",
       "3753     2017-01-13   2017-01-14                 4.5               4.5      1   \n",
       "3711     2017-01-13   2017-01-13                10.0              10.0      0   \n",
       "3703     2017-01-21   2017-01-21                 6.7               6.7      0   \n",
       "3815     2017-01-22   2017-01-29                26.0              26.0      7   \n",
       "3794     2017-01-25   2017-01-25                14.0              14.0      0   \n",
       "3705     2017-02-01   2017-02-01                27.0              27.0      0   \n",
       "3841     2017-02-02   2017-02-02                14.0              14.0      0   \n",
       "3888     2017-02-27   2017-03-07                 1.0               1.0      8   \n",
       "3884     2017-03-02   2017-03-06                 6.0               6.0      4   \n",
       "3963     2017-03-07   2017-03-07                19.0              19.0      0   \n",
       "3905     2017-03-20   2017-03-20                 2.0               2.0      0   \n",
       "4033     2017-03-26   2017-03-27                15.0              15.0      1   \n",
       "3955     2017-03-28   2017-03-28                11.0              11.0      0   \n",
       "3965     2017-03-30   2017-03-30                 4.0               4.0      0   \n",
       "4061     2017-04-15   2017-04-15                 4.5               4.5      0   \n",
       "4025     2017-04-18   2017-04-20                 8.5               8.5      2   \n",
       "4128     2017-04-18   2017-04-18                 2.0               2.0      0   \n",
       "4199     2017-05-06   2017-05-06                 7.0               7.0      0   \n",
       "4117     2017-05-06   2017-05-06                10.0              10.0      0   \n",
       "4174     2017-05-09   2017-05-16                17.0              17.0      7   \n",
       "4214     2017-05-10   2017-05-10                11.0              11.0      0   \n",
       "4219     2017-05-14   2017-05-14                 6.0               6.0      0   \n",
       "4236     2017-05-16   2017-05-16                 5.0               5.0      0   \n",
       "4175     2017-05-18   2017-05-18                 3.0               3.0      0   \n",
       "4235     2017-05-22   2017-05-22                 3.0               3.0      0   \n",
       "4202     2017-05-23   2017-05-23                12.0              12.0      0   \n",
       "4282     2017-06-02   2017-06-05                 3.0               3.0      3   \n",
       "4226     2017-06-06   2017-06-06                 7.0               7.0      0   \n",
       "4208     2017-06-07   2017-06-09                 5.0               5.0      2   \n",
       "4232     2017-06-15   2017-06-15                 3.0               3.0      0   \n",
       "4322     2017-06-18   2017-06-18                20.0              20.0      0   \n",
       "4373     2017-06-22   2017-06-22                 7.0               7.0      0   \n",
       "4148     2017-06-24   2017-06-24                15.0              15.0      0   \n",
       "4425     2017-07-04   2017-07-07                 9.0               9.0      3   \n",
       "4409     2017-07-04   2017-07-04                 2.0               2.0      0   \n",
       "4529     2017-07-13   2017-07-13                 8.0               8.0      0   \n",
       "4417     2017-07-14   2017-07-14                 5.0               5.0      0   \n",
       "4411     2017-07-22   2017-07-22                 6.0               6.0      0   \n",
       "4477     2017-07-23   2017-07-23                15.0              15.0      0   \n",
       "4481     2017-07-26   2017-08-05                 7.0               7.0     10   \n",
       "4522     2017-07-27   2017-08-05                16.0              16.0      9   \n",
       "4591     2017-08-01   2017-08-07                10.0              10.0      6   \n",
       "4543     2017-08-13   2017-08-13                12.0              12.0      0   \n",
       "4595     2017-08-14   2017-08-14                 4.0               4.0      0   \n",
       "4519     2017-08-16   2017-08-16                14.0              14.0      0   \n",
       "4588     2017-08-18   2017-08-18                10.0              10.0      0   \n",
       "4657     2017-08-24   2017-08-24                11.0              11.0      0   \n",
       "4563     2017-08-28   2017-08-28                25.0              25.0      0   \n",
       "4603     2017-08-28   2017-09-06                24.0              24.0      9   \n",
       "4663     2017-08-28   2017-08-28                27.0              27.0      0   \n",
       "\n",
       "      Deficit  Indexdate  \n",
       "3783      0.0 2017-01-04  \n",
       "3784      0.0 2017-01-09  \n",
       "3753      0.0 2017-01-13  \n",
       "3711      0.0 2017-01-13  \n",
       "3703      0.0 2017-01-21  \n",
       "3815      0.0 2017-01-22  \n",
       "3794      0.0 2017-01-25  \n",
       "3705      0.0 2017-02-01  \n",
       "3841      0.0 2017-02-02  \n",
       "3888      0.0 2017-02-27  \n",
       "3884      0.0 2017-03-02  \n",
       "3963      0.0 2017-03-07  \n",
       "3905      0.0 2017-03-20  \n",
       "4033      0.0 2017-03-26  \n",
       "3955      0.0 2017-03-28  \n",
       "3965      0.0 2017-03-30  \n",
       "4061      0.0 2017-04-15  \n",
       "4025      0.0 2017-04-18  \n",
       "4128      0.0 2017-04-18  \n",
       "4199      0.0 2017-05-06  \n",
       "4117      0.0 2017-05-06  \n",
       "4174      0.0 2017-05-09  \n",
       "4214      0.0 2017-05-10  \n",
       "4219      0.0 2017-05-14  \n",
       "4236      0.0 2017-05-16  \n",
       "4175      0.0 2017-05-18  \n",
       "4235      0.0 2017-05-22  \n",
       "4202      0.0 2017-05-23  \n",
       "4282      0.0 2017-06-02  \n",
       "4226      0.0 2017-06-06  \n",
       "4208      0.0 2017-06-07  \n",
       "4232      0.0 2017-06-15  \n",
       "4322      0.0 2017-06-18  \n",
       "4373      0.0 2017-06-22  \n",
       "4148      0.0 2017-06-24  \n",
       "4425      0.0 2017-07-04  \n",
       "4409      0.0 2017-07-04  \n",
       "4529      0.0 2017-07-13  \n",
       "4417      0.0 2017-07-14  \n",
       "4411      0.0 2017-07-22  \n",
       "4477      0.0 2017-07-23  \n",
       "4481      0.0 2017-07-26  \n",
       "4522      0.0 2017-07-27  \n",
       "4591      0.0 2017-08-01  \n",
       "4543      0.0 2017-08-13  \n",
       "4595      0.0 2017-08-14  \n",
       "4519      0.0 2017-08-16  \n",
       "4588      0.0 2017-08-18  \n",
       "4657      0.0 2017-08-24  \n",
       "4563      0.0 2017-08-28  \n",
       "4603      0.0 2017-08-28  \n",
       "4663      0.0 2017-08-28  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co_df_part_1.head(52)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\sattwik\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "co_df_part_1[\"Indexdate\"]=co_df_part_1[\"Requested_Date\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df_part_1 = co_df_part_1.set_index([\"Indexdate\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df_part_1_weekly = co_df_part_1.resample('W').sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order_Line</th>\n",
       "      <th>Outlet</th>\n",
       "      <th>Requested_Quantity</th>\n",
       "      <th>Shipped_Quantity</th>\n",
       "      <th>Delay</th>\n",
       "      <th>Deficit</th>\n",
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       "    <tr>\n",
       "      <th>Indexdate</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
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       "      <td>2017-01-08</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <td>2017-01-15</td>\n",
       "      <td>112</td>\n",
       "      <td>3</td>\n",
       "      <td>20.5</td>\n",
       "      <td>20.5</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2017-01-22</td>\n",
       "      <td>85</td>\n",
       "      <td>2</td>\n",
       "      <td>32.7</td>\n",
       "      <td>32.7</td>\n",
       "      <td>7</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2017-01-29</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2017-02-05</td>\n",
       "      <td>126</td>\n",
       "      <td>2</td>\n",
       "      <td>41.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Order_Line  Outlet  Requested_Quantity  Shipped_Quantity  Delay  \\\n",
       "Indexdate                                                                     \n",
       "2017-01-08          14       1                 1.0               1.0      0   \n",
       "2017-01-15         112       3                20.5              20.5      1   \n",
       "2017-01-22          85       2                32.7              32.7      7   \n",
       "2017-01-29          13       1                14.0              14.0      0   \n",
       "2017-02-05         126       2                41.0              41.0      0   \n",
       "\n",
       "            Deficit  \n",
       "Indexdate            \n",
       "2017-01-08      0.0  \n",
       "2017-01-15      0.0  \n",
       "2017-01-22      0.0  \n",
       "2017-01-29      0.0  \n",
       "2017-02-05      0.0  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co_df_part_1_weekly.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order_Line</th>\n",
       "      <th>Outlet</th>\n",
       "      <th>Requested_Quantity</th>\n",
       "      <th>Shipped_Quantity</th>\n",
       "      <th>Delay</th>\n",
       "      <th>Deficit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>157.000000</td>\n",
       "      <td>157.000000</td>\n",
       "      <td>157.000000</td>\n",
       "      <td>157.000000</td>\n",
       "      <td>157.000000</td>\n",
       "      <td>157.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>60.808917</td>\n",
       "      <td>1.617834</td>\n",
       "      <td>16.185987</td>\n",
       "      <td>16.185987</td>\n",
       "      <td>2.369427</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>399.554097</td>\n",
       "      <td>1.327882</td>\n",
       "      <td>17.476029</td>\n",
       "      <td>17.476029</td>\n",
       "      <td>8.328424</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>5008.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Order_Line      Outlet  Requested_Quantity  Shipped_Quantity  \\\n",
       "count   157.000000  157.000000          157.000000        157.000000   \n",
       "mean     60.808917    1.617834           16.185987         16.185987   \n",
       "std     399.554097    1.327882           17.476029         17.476029   \n",
       "min       0.000000    0.000000            0.000000          0.000000   \n",
       "25%       2.000000    1.000000            3.000000          3.000000   \n",
       "50%      13.000000    1.000000           11.000000         11.000000   \n",
       "75%      37.000000    2.000000           23.000000         23.000000   \n",
       "max    5008.000000    6.000000           89.000000         89.000000   \n",
       "\n",
       "            Delay  Deficit  \n",
       "count  157.000000    157.0  \n",
       "mean     2.369427      0.0  \n",
       "std      8.328424      0.0  \n",
       "min      0.000000      0.0  \n",
       "25%      0.000000      0.0  \n",
       "50%      0.000000      0.0  \n",
       "75%      2.000000      0.0  \n",
       "max     97.000000      0.0  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co_df_part_1_weekly.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 157 entries, 2017-01-08 to 2020-01-05\n",
      "Freq: W-SUN\n",
      "Data columns (total 7 columns):\n",
      "Order_Line             157 non-null int64\n",
      "Outlet                 157 non-null int64\n",
      "Requested_Quantity     157 non-null float64\n",
      "Shipped_Quantity       157 non-null float64\n",
      "Delay                  157 non-null int64\n",
      "Deficit                157 non-null float64\n",
      "Seasonal_Difference    105 non-null float64\n",
      "dtypes: float64(4), int64(3)\n",
      "memory usage: 9.8 KB\n"
     ]
    }
   ],
   "source": [
    "co_df_part_1_weekly.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "157"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(co_df_part_1_weekly)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x268d168d548>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1800x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "co_df_part_1_weekly[\"Requested_Quantity\"].plot(figsize = (25,15))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "31\n"
     ]
    }
   ],
   "source": [
    "demand_part2 = co_df_part_1_weekly[\"Requested_Quantity\"].values.tolist()\n",
    "neg_demand2=[]\n",
    "for x in demand_part2:\n",
    "    if x <=0:\n",
    "        neg_demand2.append(x)\n",
    "print(len(neg_demand2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.tsa.seasonal import seasonal_decompose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x268d3e6f2c8>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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VEButhNgoxcdEKz42KvA+JrDtB8+uUkkN0yYAQH9W1dCkZr9tZ8rBJDX5/Cp1uTUkLdGh6HqHloamjftcPZbQ2lxWJ7+VfnTWeGUPiG+93re97ifERunZZXt0/3tb1dDUrKS4kE5YAQDoRcpdHg1J+/xzvSQVVzZKo5yIqvdoudZv2OfqsTL313lUWd+kC47O06yRmcFrfLTiY6IOuO7vrmzQVf9cqr3Vbk3N67HwAAA9oNtPcNbaVZKOamf7NgXW0wL6lJYRWjmpn++1/e6mMllrGdJ+CNWNgZter89q+/56jT1oOqdwqar3alhmki6eMeyQ++VlJGr5rqoeiQkAEJlaO6+kHtTI1dJru7KRhNZhVDd4JUkb9tXquDFZPVJmVUPgHuPyY0coMS66w/1G5wR6kZfVejQii4QWAPRXZS6PCvPTDtg2JD1BUYb1sTujuuGzzis9V2bg/uKMSYN0+qTBHe6Xnhgr6bMlIwAAfUfPDI0A+pAyl1vxMVFKiT+wASQ/M0lur7+1EQzta7kBlXq2J1dVQ5MykuMOu19OSrzKXR5Z27NTIgIAIkdH0wvnZQSSWMU0ch1WlQONXFX1TUqIjTpkMktS68g77tkAoP9q9vlVUe9R9oADr/Wx0VEakpao4irWxz6cquCzfU9e61tGhR3u2X7ggHhFmcAoPABA30JCCzhC5S6PclLjPzcKKz+zpZGLG99DqWoz1/XGfbU9V25DkzKTDp/Qyk6Jl9sbmBYRANA/lblaphc+sJErNz1wrd9dybX+UKy1nzVylfZk5xVvp6/10meJSwBA/1NZ3yRrpeyDRmNLgQ4suyvpvHI4LSO0SmrcqmnTcTWcWjrMZBzmeh8dZZSZHN96TwcA6DtIaAFHqMzl+dz6WdJnc21z43toLQ1cMVGmx3pyWWtVVe9VenLsYfdt+W9LIxcA9F8tvXkPHqGVEButQanxTEN0GI1en5qa/YqJMtpU6pLP3zOjnqvqm5TeiYRWS6KyjGmIAKDf6qjzihSYfYVr/eFVNXgVExXo6NtTHVhaOshmJHXm2Z6EFgD0RSS0gCNU5vr8tASSlJvBCK3OaOnFVZif3mNTDjY0+dTk83eq13brNETc+AJAv1XmcmtAfIyS4j6/vlJ+RhKdVw6jpfNKYX663F6/dvXQ76uqoUmZnZheOCMpTjFRhms9APRjLZ0aDu68IgVGaJXWeuT2+no6rF6lqqFJhfnpknpu9pXKBq+MkdISO5HQSo3nWg8AfRAJLeAItUw5eLCkuBhlDYijkeswKoMJrVkjM1Vc1ai6Hpjar3We7SOZhohe2wDQbwVGY3/+Wi8FGrnovHJoLb2nZ43MlNRzjVxVDV6ld6LHdlSUUdYAem0DQH9WfqgRWsHZV/ZWc70/lKr6Jk0YkqKUhJge66xa3dCk1IRYxUQfvjkze0A8z/UA0AeR0AKOgNvrU02j9xCNXEk0ch1GdYNX8TFRKsxr6ckV/hvf1nm2O9Fru2XKQXpyAUD/Ve7ytNtjWwpMQ1RS0yivz9/DUfUeLdfdY0Zkyhj1WCNXZX3nRmhJgV7bJLQAoP9qmWK+vet9fmZwOQGe7Tvk91vVNHqVkRSn8f+fvTcPcus8z3yfg31HA91Ao8leyG6STVKyZImStdiOvFtJnLKTTGWSyk3iijNOfDN3cidzb5K521QldSe5qdQsf0zk6MbOpMZxZiaxbxYnEeNF1krKWixZJCWy2U12c2k00Nj3A+B894+DD71hOefgAAdAv78ql6TeALMJvN/3vs/7PBHvwOIE1Nb67bw4MOtjgiAIYjDQQIsgVNAuU4NDXtvdSRXExqHXB2BQAy3Z+kiJz7bPaYHNYqKBFkEQxCGm40Ar4ILEgM00KX7bwevu0Qkn5oOugdT6Wl1CtlxVlKEFyIp8qvUEQRCHl1iuAr/TCrvFfOBzc0E5ToDcV9qTLVchMWDCZcNyxIurWzkw1v/BUVrhNjYgi1XrEmsKbQiCIIjxgAZaBKGCeJ7bEjhafn424MTddIkUQB3gdkCzASdcNvNAbIiawbEKlFyCIFB4LEEQxCEnli23r/VBnplJTa528LzMCZcNy9ODUW1nSlUwBgQVNrlCXgfiZENEEARxaIl3sBcOex2wmgVyX+nAbtHocsSHXLmGu5n+19VkQVSUjQ3s2EnybTyCIAhiPKCBFkGooJMtASCrtqt1hmiWGiTtSDcC200mAaemvQOxIWpaDio8+Ia85LVNEARxWClUaiiI9ZZ5mcBOrgZtZLcnVZCbXBMuK05HvLiZKKBcrff3MXljTaENUchrR6IgokbWkQRBEIeSWK7cttabTQKOTjip1ndgt63/6YgXwGAyM9NFUfE2NuVjEwRBjCc00CIIFXAlbzslF7cmuK3BmoAxdiisb1JFsTlYOj0ga4JUQYQgAH6nUmsCsiEiCII4rDTthT2ta/2M3wGzScCtpDbVdjxXGYglj5GkiiK8DgusZhOWIz5IDFjZyvf9MQHl4pWw1w7GgESBbIgIgiAOI7FcpW2tB+Q4AS33ekDeGu63kMNo0rvq7qlpeaA1CLFqsigi6FZuOQhQPjZBEMS4QQMtglBBPFeBSQAm2xx8ZwPaw2O/9sYdvP//+U7THm9cSe3yvF6OeJEuVvtu75cqVuF3WmE2CYq+Pux1kOUgQRDEIYW//7dTbVvMJsz4HZpU27dTRTz+e9/G+ctbPT3HYWe3eGU5wptc/VVtN+2FyYaIIAiC6AIXk4Z9re2FATlOQMu9HgB+6osX8DvfuKL16Y0EycKO5aDfacURv6PvFsMlsY5yVVK1jQ2A7vYEQRBjBg20CEIFsVwFkx5728HIkQkHBEFbeOyzV2MQaxI2xjh4VpIY0i2bXP09+CaLyn22Afngmy5WUamNt6qOIAiCOEisuY3dvsk1F3BpytV46fo2qnWG67H+K5iNJFWsItAQrxybdMFmMfW9ybVjfaQ0Q4tsiAiCIA4r2XINlZrU1nkFkMWqyYKIQqWm6mffSZdwdSuHlVh/N5ONZndeJiDf7QdW6xXe7Z02M7x2C21oEQRBjBk00CIIFXSzJbBbzIj41Ku2GWN4ZS0BANgcQJCqUeTKNUgMzQ2t0xEfgP57baeLomIVF7Cj2t7Oj/e23GHh//67K/gP37pm9NMgCGJEaFoOdmxyOTWJVy6uJQGMd60H9uZbWMwmnAx7cHWr300uWSkeVFjvuSqfmlzjwTOXovi5L70y9naeBEHoA48S6FTr54Ky+4paAQu/10fHvNaniiLMJgE+hwUAsBzxYTWeR7WP2ZRqB1oAEPJRnMC4EM2U8cP/8QVNZ3CCIMYLGmgRhAo6BcdytKi2V+P55vAkmtFmazAK7D+ABt02hLz2/m9oFXaU4krgv+NYdrwvIYeF85e38I9jbu9FEIR+xHIVWM1Cx7oxF3QhlquoysdgjOHC6uFpcu3+81uOePte61MFETaLCU6rWdHXT3nkswjZEI0HL6zE8cLKdnOwSRAE0QluN9txoBWQ87HVNs+btT5bHushe6pYxYTTCkGQ3WtOR7yo1hnW4oX+PeYum0OlhL122sYeE968lcY7m1m8sZEy+qkQBGEwNNAiCBXEc5WOtgSArNpWGx7LD70AEB3jLIdWdkCnB2BNsNvmUAkhj6zapibX6MMYQzRT1pR1QxDE4SSWlbexeYOmFXNBucl1J61chLKeKCLaEEpEx1wwkS5UmxtagFzr47kKkn3MCU017IU7/d52Y7eYMeGyUpNrTOBDYlJtEwShhHi+kZfZwV6Y52PfVnmPuHhDvtuLNWmsh+z7XVAGkZmZbPQTlG5jA0CI8rHHBi7+plpPEAQNtAhCIXWJYTsvdlRxAcBs0IXNbBliTfmq/cW1JI74HZgNOMd6Qytd5IqqXQffaS9WYnnU+mhNkCyotBz0UXjsuJAsiBDrElIJWyUAACAASURBVHLlGjKl8b1QEgShH/F8pWutn2s0udRcqC82LIgeOR4c6w2tal1CrlLb02xablgM97XJVag2LY2VEvbamyp9YrThNp5asu0Igjh8KNnQmvLY4LSacUvF+8rtVBG3kiU8cjwIANgc47t9ap8LylLIA4tJ6KtYdX9ulxJ4rR/nbbnDwmaWaj1BEDI00CIIhSQLIuoS66jiAmRrAsaAuwpV24wxXFxL4NHFScz4HWOdq8GV2XsGWhEvxJqEm4n+qGxKYh2VmqRqQ2vSbYMgUK7GOLB7C0KtupIgiMNJLFtGqEut56ptNU2ui2sJTHnseP+JKSQKoiq7wlFix1547zY2gL43udQotgFZmc9V+sRos9VsclGtJwiiO7FcGXaLqZn/1ApBEFRnZr7SyMr8zANHAYy3xXBqV14mANgsJiyG3H2t9byfoEbAEvbaUarWURDH89x1mNgi8QpBEA1ooEUQCuHDjW6Wg2rDY6/H8kgURDy6OImI3znWNkStQlxPN1Tb/Tr4Jls01rphMZsw6bY1w4KJ0WX3JZIOvgRBKCGeq3TNywx77bBZTIothmXxShKPLgYR8Tdsbcd0M4hvY+9ucoW9dky4rP1tcqm0FwZkZf64/h4OE+VqHYlGk5NqPUEQSuC1vptN7VzQpVq8MuGy4olTIQDjbTG8Py8TkDey+5mZmS5W4XVYYDUrb2XyLTzKxx59draxSbxCEIcdGmgRhEJ4xkJXy0EeHquwyHILIr6hFc2Mb3hsuliFSQC8u5RwJ6c9MAnA1T7ZEKX4VphK1XbI66Am1xiwSQMtgiBUUK1LSBZFhDyda73JJGB2wqn4fYXnZ/FaD4xvkyvVYhtbEAQsT3v72uRKFcQ9GZ1KCHvtiOfIhmjU2X1eoyYXQRBKiOUqXWs90MjHVvG+cvFGAo8cD2La54DZJIzthhZjDKli9YCQ5HTEizvpEnLl/li9JwvatrEBihMYB/jZ+U66BEmisxtBHGZ6HmgJgjAnCMKzgiC8IwjCZUEQfq3x8aAgCN8UBGGl8c9A70+XIIwjluseHAsAM34nLCZBsTUBz8+aCzox7XOgUpOa6uZxg9sSmEw7SjiH1Yxjk+6+NblabYUpIey1kw3RGBDNlGESAJfNTE0ugiC6ksiLYAxdN7QAOTNTqXjlwi7xSsQnnyPGNVcj1dzQ2jtcOh3x4tpWri8NiLrEkCkdbKx1I+S1Q6xLyJZquj8nYnDw15LXYSHxCkEQiojlKl3v9YCcmZkr15BRcD/n+VmPLk7CbBIQ8tjHNk6gVK1DrEkHsqyWp2WL4Wtb/bvbq77XN850FCcw2jDGsJkpw+uwoFpnNKAkiEOOHhtaNQD/ijF2BsCjAH5VEISzAH4LwLcZYycBfLvx3wQxsvADULcNLbNJwBGFqu1mftbSJARBaKq2x/Xgmy62DmxfjnhxtU+HXu6zHVSp2iYbovFgM1PGtM+BuYCLmlwEQXSFb2MraXKpydW4uJZAyGvHUsjdtBwcV9U2D2zfvxm9HPGhKNb78l6cLVUhMfXilaYNEVkMjzRcsX1uIYDbqRJt3BEE0RUl9sIAMBdU7r5ysZGf9djSJAAg0nBfGUe4eGX/HXu5kZnZT7GqmigBAM1NPBqAjDapYhViTcK5BXlXQqmojCCI8aTngRZjbJMx9kbj33MA3gFwFMCnAfxp48v+FMBnen0sgjCSeK4Cr90Cp83c9WtnA05FBXZ3fhaAZpNra1xtiIoigi2aTcsRLzaSRRRF/RXSrbI8lBD22rGdr9Aq+4gTzZYQaWxAqgl0JgjicKJUvALIqu1UsYp8pXPtaopXFmXxitdhhcduGV/LQd7k2q/abja59LcYbm5jq7YcJBuicYALwR4+FkRpV54WQRBEK8rVOjKlqkLLQTkfW8k94uJaAgGXFafCcr2b8TvGt9Y33mf337FnA0547Ja+ZWamClXVUQITLitsZhOJV0Ycvo398LEgALIYJojDjq4ZWoIgHAPwAIBXAEwzxjYBeegFINzmez4vCMJrgiC8Fo/H9Xw6BKErsVwZIQUqLkBuct1KdlcgcwuixxoDrXHf0EoVqy0HS6cjXjAGXNvK6/6YfENrwqk+V6MmsWaTjBhNNjNlzPgdmA24cIdU2wRBdGHHXli5arvbhfpmooitbAWPLgabHxtn1Xa6KMJuMR0QAPGBVj+aXJrthcmGaCyIZsrw2i043fg7RhvZBEF0gr/nK9rQagy0lLyvXFxL4JHjk017/fGu9bJ4ZX/dFQQBp6Y9fd7QUlfrBUFAqJGZSYwu/LXEN7RuK+i3EQQxvug20BIEwQPgawD+Z8aYYuklY+xpxthDjLGHQqGQXk+HIHQnnqsoanABcpNrO19BSax3/LqLawkcnXBiNiA3xUIeO0wCEB3XXI1Ca4uA5YgPAHC1D6rtdFGE32mFxazu7S5Equ2RhzGGaKaMiE9+jeUqNcpJIQiiI9xqdkqVartzzb64Kz+LE/E5xla8kiy0bjZ57BbMBpx4tw8Ww6kCtz4iy8HDyGZG3saebTaeSbVNEER7eE6yEnthv8sKr8PS1X3lVrKI26nSXvGKz4F8pYZcefzysZNNIUnru/3VaE53IWG5WkdRrKuu9QAwRQOtkYefm49PuRHy2km8QhCHHF0GWoIgWCEPs/6MMfb1xoe3BEGYaXx+BkBMj8ciCKOI5SrNIUc35oLyhfpOuv3BV7YgSuKRxSAEQVZxWcwmhLzjGx6bKootLQLmgy44rKa+KLmSxapqn21gR7FHA63RJVepoSjWGxtayv3vCYI4vMTzZQRcVtgs3Y/Ic/x9pYsNEc/PWpxyNz82zqrtVJu8TEDeyO7HhlZS44aW126Bw2qizMwRJ5qtIOJ34GiAb01Sk4sgiPbw93wl9sIAd1/pXOtfuSHnZz26tEu8MsZxAjwvs537SqZUxZbOtXUnSkDD3Z7ysUeerWwZZpOAKY8dswEnbnfotREEMf70PNAS5E78lwC8wxj7d7s+9TcAfqHx778A4K97fSyCMArGGGJZ5RtazeZ5B9X2SiyP5K78LE7E7xxLr+2SWEelJrU8gJpNAk5N96fJlW4zROsG/12Tkmt04c3i6T2qbWpyEQTRHrnWKxOvBN02uGzmju8r+/OzODN+B+L5Cmp1qefnPGykO9gBLUe8uLFdQKXWeYNdy2MCUF3vBUFA2OtoqvWJ0SSaKWHG74DHbkHAZaUNLYIgOhJvbOWqudt3u0Psz88CgBm/3BMYR7Eq34xudbfvV2YmjxJolcndjbDXTrV+xNnMlBH22mE2CZgNuOheTxCHHD02tN4P4OcAfEQQhDcb//sRAL8H4OOCIKwA+HjjvwliJCmIdZSqdeWWg9yGqMOF+uK+/CxOxGcfS9V2t3yL5T4NtNpZH3WDbIhGH3553L2hRU0ugiA6EctVFGVqAPIwZC7g6ljrb2wXsJWtHKj10z4H6hLDdn78chrlbezW6unliA91ieF6TN/MzGShCqtZgHtfbpcSQqTaHmmqdQmxXAURnzyInlWYY0sQxOElnqvAJACTCuyFAdl95XaXLN4Lq7J4hednAWi+L43lQKsowuuwwNrC1v90nzIzO22FdSPktSNZECHWxk9IdFiIZsrNrcfZgBN30yXUJcrHJojDSs8DLcbYi4wxgTF2H2PsvY3//T1jLMEY+yhj7GTjn0k9njBBGEGssTGl1JYg5LXDbjF1tCbg+VncnpAz43eO+UCrXZPLi0RB1H0jKl2sahpouWwWeOwWanKNMDyLLuJzwO+0wmO3kJKLIIiOxHMVhBQ2uAD5Qt251jcsiHZlagDyoB2Qs3/GjXSx2rbZ1M8mV8Bl27MFp5Sw107ilREmnquAMdnhAOCbFCReIQiiPbFcBUG3vOmhhLmAE6Vqva0I5VayiDvp0gHnFS6QGce7fadt7AmXDdM+u+61ntsLa8nQ4tv327SlNbJsNraxAVlAXq2zsbTzJAhCGbpkaBHEuMNzlJTaEAmCgKMdrAl4ftb+Qy8ge23nKjXkKzXtT3gI4Z7X7Q6+pyM+APo3ueQNLfU+2wBZE4w6XA057XNAEARqchEE0RHGmDzQUrihBXRXbV9cSyDsteP4rvwsYHxzNSSJIV2qtrUDOj7lhtUs9KnWq29wAY1aT/bCI8vubWxA2SYFQRCHm1hOeZQAgKZ1ebuNbO68sv9u77CaMem2jWWcQKpLTvVyxKd7PnaK9xPabIF3guIERhvGGDYzZUR8O+IVgOIECOIwQwMtglAAP/gotSEC0NGG6NoWz88KHvgcv5CPm5KLe163y7foh9d2uSpbRWrJ0ALkTbs4bWiNLNFMGVMeO2wWudSR1zZBEJ3IlKoQ65Ji8QogX6jzlRoypeqBz7XLzwLGN1cjV66hLrG2ge1WswlLIU8fmlztbQ67EfY5kC3XUK7qm+tFDAZ+Xt5tQ1SpSWNp50kQhD7EVdgLA2g6qrS7R1xcSyLotuFk2HPgcxG/Y+zu9YBcdztZ/52OeHE9ntc1KzTV6CdMODVsaPl4nADd7UeRXKWGolhv9sooToAgCBpoEYQC+MFHjQ3RXNDZ1sO/nYoLkLdJgPEbaO14XrduOIW8dky6bbqqtrvldnUjRDZEI81mptw89AI7gc6k2iYIohVcvKLUXhjYaXK1qvc3tguI5Sota33AZYXNYhq7Wq+k7p6O6J+ZmdJoLwzsnO1ItT2acNtOanIRBKGUWK6s2l4YQFuL4YtrCTxyPLgnP4sT8TnGTrwCNIQknTa0pr0QaxJuJgq6PqbXbmmKFdVA+dijzX7xypEJ2tAiiMMODbQIQgGxXBk2s6ntMKYVcwEXMqUqsuWDqu12+VnA+OZqcIuAToqq5YgXV7f0a3LxrbCgVtW210ENrhFmd3As0HmTgiAIYsdeWEOTq0XzvF1+FiBbE49jk6s50OpQd5cjPkSzZWSK+r0Xpwqi9m1sUm2PNNFMGQ6rCX6n/HeOW4NRk4sgiFbUJYbtvKhqQ8ttt2DSbWs5KG+Xn8WJ+B1jZy8MAOlC+7xMYLf7io5i1YKICY33+imPHYJA4pVRZb+9sMNqRthrJ/EKQRxiaKBFEAqI5yoIee2qwsabF+p9qm1JYnjlRuv8LGBnQ2vcDr6poghPF0XVcsSLa1s51CV9Nmh4blenw3Ynwj47CmIdhTHLMzss7A6OBajJRRBEZ7hqV81Aa8eG6OCF+kKb/CxOxO8Yu1wNJXX3tM4Wwzy3q5e8TACIk2p7JNnMljHjdzbP6Ecn2g+ZCYIgUkURdYmpshcGdpwe9nOhg/MKIDfgkwVxrGxtq3UJuUoNwQ5CkhNhD8wmfTMzU8X2GZ3dsJpNCLpsJF4ZUaINsfd+sWo7RySCIMYfGmgRQ080U0ZRNHagEM9VMKWiwQXIloPAwQv1SkzOz3psqfWh12E1I+Cyjp1qO12sdt1wOx3xolyVsNHGzkEtOxtavdkQ0cF39CiKNWTLtQOHXmB8bYjqEsN33t2CpNNAmCAGSbZcNdwGRovloM9hhd9pPXCh5vlZjy0dzM/iRHzjl6uhxHKQq7b12sjmuV292AsDVOtHla1MGRHfTq132y0Ium1jLV557WayecYliFFCkhhubutnQaeFWFZ9rQeA2aCrpeXgxbUEgm4bTk0fzM8CxlOsysUrnYQkDqsZxyZd+m5odcnt6kbIa2/+/onRIpqpQBCwZxA9F3Thdno87/UAcHO7gGs6uhcRxLhBAy1iqKnU6vjh//g8/sO3Vgx9HrFsRZViG5AtB4GDXts8P+uR4wctiDgRv3Msm1zdBkvLER8A4KpOqu10jxla3IqCrAlGj6bPtm/voRdonXUzDvy3V2/hF//za3hpddvop0IQqvmNv/gBfv5L3zP0OcSyFTitZnjsFlXfNxd0HhCvrG0XEG+Tn8WZaQTFj1OuH7cX7qSgnvE74HVYdGty8SGaVvHKpNsOE9kQjSz78zIBYK7NJsU4cHO7gJ/6owv44nOrRj8VglDNn7+6gY/+u+cMtdbXso0NyHf7O+nSHicRxhheWUvi0cVgW/HKjF8W1I2TWHUnG7tz3T0d8em6oZUsdO8ndCLktSOep1o/ikSzJUy67XvcfmYDTmymy6jVJQOfWX+oSwy/+Kev4tf+65tGPxWCGFpooEUMNS+vJpAqVnH5bsbQ5xHPqx9oTbis8NgtBy7UF9cSmA20zs/izPh7z9W4HssjMUQHtlShu6Lq1LQHgqCf13aywK2PtGdoARQeO4rsD44FAL/TCq/DMpYbWnWJ4Y+el5tb17byBj8bglBHvlLDd67GsBLLo1IzzpInlqsg7FNnLwwAsxMHVdsXu1gQAfL7k1iXetq0SOQruB4bntd8qiDCJABeR/uhoCAIOB3x6tbkSvYoXjGbBEx5SLU9ikgSw1Z2b14mIFsMj2OtB4CnX1iDxECqbWIk+cZbm6hLTNchh1rizbxMdZaDc0EnqnW2Z9PqdqrUMT8L2LmL9LKhVatLeH09qfn79YafW7rV3eWIFxvJom72/UocXzoR9joQH6NNucNEK/HKbMCFmsSwNYaCpG9eiWItXsBqLK9bHAdBjBs00CKGmvOXogCA1Zhx1gRiTW42qbUlEASh4bW9c6Hulp/F0SM89n/441fwO9+40tPP0JNUsXu+hctmwXzQpdslJ1UU4XVYYDVre6tr2hBRk2vk2AmOde75uNzkGj/V9j9c2sR6Qn6vWY0PT3ObIJTw3asxiDUJdYlhI2FcEzqWKzetZtUwF5S3QXZvWl1cS2LaZ8exyc7iFQA95Wj93j+8i59++sLQbHlxOyCTqfNQcDnixbVoTpfn3dzG7lG1TeKV0WO7UEFNYi0GWk7c2feaHAdiuTL+8vXbAKjWE6NHsiDilRuy2GM1btzdPqbBXhhoncXbLT8L2Blo9SJW/ftLUfzkUxcMF/lyUkVlolFuMazHAF6sSchXapoztICdDa1xqw2HgWimlXilESegU1zFsMAYw1PflYWqYl0aW4EOQfQKDbSIoaUuMXzzyhZMgtzsyeuk7FHLdl6biguQD7677c2uxXJIFsTuAy2fA4kewmMzxSqi2TK+d2N4lFypoqhIPb08rZ9qW+ljtiPgssJqFihXYwThDeLdloNA+0DnUYYxhi8+t4rFKTcemJ/A6hBtaxCEEs5flms9YGyTK97Y0FLLXNCFSk1q2tjw/KxHF9vnZwE7uRq9WAxf3cphOy9izeBMEo5S9fRyxIdcpYY76d7fj/k2djfRTCfCXjvV+hGklb0wINf63a/JceFPXrqJWl3CTzxwFLdTJc33BIIwgm+9swWJASYBWDNwIBvPVeC1W+C0mVV931yjeb57I5vnZ50Mt87PAgCP3QKv3dJbrW/Y8b86JHd7pUKS0zwzU4e7fdPmsAfxSthrR7XOmgM5YnRot6EFYOzu9hfWEnjrdgb/5NwsABKwEEQ7aKBFDC2v3UwiURDxo/cdAQDcMKjJtWNLoE21fStVbKqALq5yFVf7/CxgR8mldTNodVsuenczZdzVoVnUK7W6hFy5pqjJdTrixc1EQZdLeqpY7UmxLQgCQh475WqMIJuZEiZc1gOXVb41OU7KvBevb+PSnSx++YlFnAp76dBLjBSVWh3PvhvDj7xnBoCxl7ZYrqJJvLKTmSnXWyX5WUDvuRqMMaw1zkavr6c0/Qy9USok6UeTq5d6H/Y6qNaPIJ22sYHxyszMlqv4yoV1/PB7ZvCRM2EwhubrnyBGgX+8HMXRCSfeOzdhaK2P5yoIaRCvHOUDrca2hJL8LE6kkZmplWat30hr/hl6wgdC3YQkcwEXXDazLnEC3F64lw0tysceTYpiDZlS9cCG1pEJBwQBB3JsR52nvruKKY8dv/HJZQAYKmtxghgmaKBFDC3nL2/BZjHhcx84DsC4JpdWWwJAvlAXxXrz0HdxLYm5oLN50W5HrzZEuy+4b2wY3+RKl/ihV8GGVsQHiQErOuQApQpiT4ptgGyIRpVopnxAsQ3Ir8mCWEd6jJR5T313FdM+Oz7zwFEshd3YzovNBi9BDDsvX08gX6nhJx+cRcTnMKzWl6t15Mo1jbW+YXnSuFBfaIhXHusy0Ap57TCbBM0Ww/Fcpbm9/sbQDLS62wsDwKlpeaClS5OrIMJiEuC1t8/t6kbIa8d2vkI5BSNGq7xM4OBrchz4s4sbyFVq+MITS1gKydsgJGAhRoV8pYbnV7bxiXumsRTyGGw5qM1e2G4xY9pnbw7KbyXl/KxutR6Q36M2e7AX5nf7Yan16aIIu8UEp7XzlpvJJOCkTu4rKb6N7dZ+t+e/d7rbjxbRpnhlb623W8yY9jrGakPr0p0MXljZxuc+cBxhnwNTHpuh8SsEMczQQIsYShhjOH85ig+emMKZGS/MJsEwawJ+4NFkQ7TLmkDOz0rg0ePdD70zTa9tbcV5LZ6H2STAYTUNhWpbjXqae22/27BW6IVUUexJxQUAIVJtjyStbAmAnSbXuCi53rqVxsurCXzuA8dht5h3Nbno4EuMBucvR+GxW/D4iUkshd2GbRzEexSvADuWJxfXEoj4HFjokJ8FAGaTgLDXrnlDi7/OvXYLXhuCWg/I9V6JeMXvtOKI36FPk6tYxYTL1lUh34mwzw6JAYkC1ftRYjNThtUsYHLf+fJoc6A1Hk2ucrWOL790Ax88OYV7j/pxfMoNQaCBFjE6PHc1DrEm4ZP3RLAU9iCeqyBbNkZcFstVEG4helPCXMDVHJRfVJCfxZnxOxDVeK+vSww3EgV47RbcSZc09wf0hG9jK6m7p6e9uLrVe2ZmivcTetrQ6s0FhzCGHXth54HP7c+sH3W++NwqvHYLfvbReQDAYshDtZ4g2kADLWIouXw3izvpEj55bwR2ixnzQZdhDVre5JrSFBTfsDxJFXEtlkOqWFV06O01V+PGdgELQRfun50YioGWmnyLY5Mu2CwmnZRccjh9L4R9ZDk4imxly4j4Dx5658bMa/uLz63C57DgZ94nH3pJtU2MEjwr88Onw82B7Go8b4glaFO8omGg5bSZMeWx41ay2MjPUmZBBMj1vpdaDwCfuv8IrsfyQ7GZmSyIiq3/liN6qbZ738bmv3eq96PFVraMaZ8DJtPe15rLZsGUxzY2tf7rb9xBPFfBF55YAgA4rGbMBpwkXiFGhmcuRzHptuHhY8HmWdVIAYuWWg/Id/vd4pVJtw0nOuRncSI+WSBZq0uqH/NuugSxJuFT98sxDMNyt1cSJQDItT5ZEHvONOQDrWCPGVoAxi5fcdzhrkXtxKrjUutvbhfw929v4mcfXYDPIb++lmigRRBtoYEWMZScvxyFSQA+dmYaALA45TbUcjDotsFqVv9yaW6DJEvN/KxHuuRnAYDXYYXHbtGs2l6LF3B8yo2HjgVw+W4WRbGm6efohRpFlcVswsmwB1e3emtyVWp1FMQ6gj3YEgCyNUGiIKKq4QJCGEOlVsd2Xmx56D06RjZEq/E8nrkcxc89tgBv49A7G3DCZjbRwZcYCXhW5ifv2an1uXLNkEYDV+tq2dACdjIzV+MFbOe752dxZvyOnrax7RYTfux+OX/s+wZna5TEOio1SUWTy4fVeB5irbf6miwqH6K1g//eYzTQGik2M6WWtR4Aju7apBhl6hLD08+v4r5ZPx5b2nlfWQp5sEq5GsQIwLMyP3ZmGmaTgMWQGwAM+fubr9RQFOvaa33Aic1MCdW6hItrCTy6OKlIvBLxOyExbYOUNS5euW9mqNxXlG5K6ZWZmSrI/QSlZ4xWuO0WuGxm2tAaMTbb2AsDskvCZqasaVg8bDz9whosZhN+8f3Hmh9bCrmRKlaRLBgvWiOIYYMGWsRQ8sylKN53PNhU4CyFPbixXTAk2yCW1a7i8jqsmHBZcTtVVJyfxYn4HZpyNbgtwWLIjXMLAdQlhh/czqj+OXrCVeNqlFy95mrwjCQ9NrQAYJuUXCMDv6S0ytDyO63wOSxjoeT6f59fg81swmcfP978mMVswrEpF3ltEyMBz8r80HIYgFzrAWNU27zJFPZqsyGaDciqbTUWRACv9drqy9q2LF55YC4As0kwvMml1g7odMSLmsSwtt1bU1NurPW6oSX/3uPU5BopopnW29iALPC4Mwa1/plLUdxMFPGFJ5b2NM6XQh6sbechUe4bMeS8vCpnZX7yXlm8Mh90wWISen7v10Isq30bG5BrvcSAV9aSuJsp41EFQlVgd5yA+rs9j104Ne3F/bMTQ5GjlSqKirOslvUaaBWrcNvMsFs653Z1I0z52CNHNFPGhMsKR4vMttmAE3WJac6eHxZiuTL+8vXb+CfnZvdYovK7EYlVCeIgNNAiho7VeB4rsTyevCfS/NjilBuVmoS76cFfTOP5imYVFyBbnG0ki4rzszgRn0PToZfbEiyGPHhgLgDAeGuCVJFbDipvcsVzlZ6UKPx7e7ElAHY1uUi1PTJ0UnEBO43nUSaaKeNrb9zGTz00d+D96UTYY1jmIEEoZXdWpsduASD7xAPGXNpi2QrMJkFzzZgLOHE3XcLLq9uK8rM4EZ8D+UoNOQ1ZImvxPBZDbjhtZtxzxDcEtZ4PtAbb5EoWqj3X+hDZEI0cjLG2eZnAjg3RKA98GGN46rnrWJxy4xO77kWAXOvLVQl3hyBPhyA6cf5SIytzaQoAYDWbMD9pjPiK3+c0i1eC8gD9L16/BUC5eKWXOIG1eAFeh2yjem5Bdl8piXXVP0dP0o3sSiVMeuyY8th7FqvqESUAyL97utePFpuZckuhKrCTY3srOdq18E9euolaXcLnP7i45+Mn+N2INrIJ4gA00CKGjvOXowCw5+LGlQnXDWhyxbPl3gZaQSe+dyOJVLG6xyqkGxG/tlwN3ghcnHIj4LZhKeQ2XMmVKoqwmU1w2ZQpqpYjPgDAu9FsT48J9BYcC+yyISLV9sjA7bs6bDGq0QAAIABJREFUN7lG24boyy/dQF1i+Gf7Dr2ArNpeTxZ7tvEiiH7SzMrcVetnfA44rWZDmlyxXBmTbhvMpu7WQa2YC7pQrTN8+50YHltSZkEE7Aze1dZ7sSbhVqqExSn5fPTgfABv3kobarmidjN6KeSBxST01ORijKmyPmqHw2qG12FpqveJ4SddrKJSk5qN4v3MBlwQ69JIDylfvL6NS3ey+PwPLR54b9rJzKSNbGJ44VmZH1oO7dmuMCoXhtvKarcclJvnz1yKYsqjLD8L2LmTaBpobeexGPJAEAScWwigJjH84LZxFsOMMaRLVQRV1N3TOmRmJotiz+IVQP7d00BrtIhm29sLzwVHP04gW67iKxfW8cPvmcGxKfeezx2dcMJuMeE6DbQI4gA00CKGjvOXt3D/rB9HJnYsRIwKj2WMIZ6vaFZxAfLBt9JoLD+iUMUFyAffeF59eCz/M+JK93MLAby+kQJjxilU043gWKUNPj28tlOFxlZYjxlaYcrVGDmiCje0jHxN9EKmWMWfXVzHp+47gvkWWyBLIQ/qEsN6gppcxPDyzKVGVubZ6ebHTI1sDSNsiOK5StNiVgs8M7NSkxRbEAHATMMuTa1VykZStmHmWSTnFgIoVes9K6B7Qa2QxGYxYTHk7qnW5yo11CTW80AL4DZEVOtHBb6N3Um8Aox2k+uLz60i7LXjxx88euBzS43XPjW5iGGGZ2U+ee/eDcOlkAfrieLARRix5oaWtno/43fAbBJQqUl4RGF+FiDb7tstJk22aGvxApYaTe4H5hvuKxvGiVWz5RrqElOVZbUc8eLaVq6n+IhUsdpTfhYnRLV+5OhkLzzjd0IQMNLuK199ZQO5Sg1feGLpwOfku5ExAgCCGHZ0GWgJgvBlQRBigiBc2vWxoCAI3xQEYaXxz4Aej0X0h2cubeLmtvHNz81MCW/dSh+w1Qi6bZhwWQf+Rp4uVlGtM82HXmDnQj0fdOHoROtC3IqI34G6xLCdV2e7d2N7x5YAkJtc6WK1GShrBGoVVWGvHRMua28DrUZjTY16rBVTnoYNER18R4bNTBkeuwVeR+tLz1zQiaJYH9lw1a+8so6CWMevtDj0ArtV23TwJfby9u0MXlzZNvppAJC3sXdnZXKMurTFcr2LVzhKLYgA7bkarcQrgLEWwzywXY2QZDni66nWp5viFbIhOmxEs3Lzqp14hb8mR7XJ9datNF66nsAvffB4y8wYo+5GxPCTKoj4b69uDIVwa39WJmcx5IZYlwb++oznKrCZTZoHIxazqVm31dR6QRAw41cfJ1AUa9jMlJvilaDbhkWD3VeatV7FHXs54kWlJvUktksV9NnQCvvsyFdqKIq1nn8W0X8qtTq282Jb8YrNYkLE5xjZWl+u1vGlF2/ggyencO9Rf8uvWQq5aRubIFqg14bWfwbw5L6P/RaAbzPGTgL4duO/iSGkWpfwz7/6ffzxi2tGPxX84+UtANhjQcRZCnkG7h3bVHH1otoOyhdqNYptAE2f4E2V3vi7bQmA4WhypYuiqouDIAhYnvb2pDTnh+1evbZtFhMCLiuFx44QsoqrfWN6doSbXOVqHV9+8QaeOBXC2SO+ll/DL7108CX28/vn38X//ldvG/00mlmZrWu9G7dTJZSrg82HkAda2mv9kQlZITrjd2A+qCw/C9g5X6i1IeIileMN1faRCSdm/A68ZmSTi1sOOtXZEN1Jl5DVkCEGyIIZQHluVydItT1aKN/QGr1aD8jbWV6HBT/zvvmWnxcEwZC7ETH8/OXrt/GbX3vb8EwZnpX5gV1ZmZym+8qAN7JjOTlKQOlmVSv4sPwxlXf7aZ8DWz2KVwDg3HwAr68b577S3MZWIV7RxX1FB3thAAiRWHWk4LEPne/2oxsn8PU37iCeq7TczuIshTy4lSoO/G5EEMOOLgMtxtjzAJL7PvxpAH/a+Pc/BfAZPR6L0J+76RJqEsPdtPEN+/OXozgR9rT0o14KuQe+ZcSHGPzgo4WTYQ9MAvDEqXD3L96F1lyNtXgBi7u8dxenPPA7rcYquYpV1QfQ0w1rAq1h3qliFR67BTZL729zYa+DmlwjRDTbPiQeGO0m11+8fhuJgogvfKj9oddtt2DG76AmF3GA9UQRm+my5vdVveBZme3EK4wBNwdomVmXGBL5Sk95mTaLCUshD544FVLVKLNbzJh02zRsaOUx5bHB79xpKD24EDC41ouq6+7ytNzkuqaxybXTWNPLcrA8FFsNRHe2MmWYhPZndIfVjCmPfSSbXGvxPJ65HMXPP7bQdtscINU20RpeP++kjT3n8qzMJ9uIVwAMPDMznqtgqodaD8jbRkcnnM2hnFJm/A5sZtX9Tm7sE68Aslg1Vaw2Pzdo1OZlAsDJsBeCAM1i1WpdQq5c08deuCEaprv9aMBtOjvf7V0jea+vSwxPP7+K+2b9eGyp/cbnUnjwdyOCGAX6maE1zRjbBIDGP1t28wVB+LwgCK8JgvBaPB7v49Mh2rGekC96dw0+9KYKIl65kcQn75lu+fnFkAfxXAWZkjYVrxbizQ0t7TZEswEXXvjNj+BH3nPwMN8JLbkaTVuCXYdek0nAg/MThqq25Q0tdQfQ5YgPRbGu+XCSUrkV1omwj8JjR4loptzccGzF0RHN1ajVJTz9/CoemJ/AI8c7q0KNCtsmhpdqXcKddAliXULCYLvN85e3cN++rEzOogFNrkShAolpz9Tg/Pdffgz/5sfuUf19Eb8DWypzNWTxyt5m2rn5AO6kS6o3u/UirSHfYrmh2tba5NJifdSOsM+OclVCvkI2RKPAZqaMsNcBi7n9dXY24DR8S0ULTz+/BpvZhM8+frzj1y2FPNjOV5ApDu5uRAw/G0n5fGtULeCcvyxnZX70zME20ITLhkm3beBn1XiP29gA8JtPnsbf/PP3q97yivid2MpUVImK1uIFCMLegdZDx2T3FaPu9mrzMgHAaTPj2KT2zEw+RAv2mI0N7Jz16G4/GnTbxgbkWr+ZKaE64Ey+XnnmUhQ3E0V84Ymlju8nRgkACGLY6edASxGMsacZYw8xxh4KhUJGP51DCfcyVqsO1ptvvbOFusTw5D0zLT/ftCYY4MG31+BYztEJp+pDb8Blhc1iUrWh1cqWAJCVXNdjeaSLg29iMsaQLlZV2wHtNLmymh43pTK3qxMhDw20RoVaXUIs19ly0Oewwu+0jpyS6+/e3sStZKnroRfYUW3TpgHBuZMqNcO4jWxy8azMVttZAJpDmoHW+oadSaiHDC1AzrZw2g5m3XQj4lOfq7G2XWgO/zjcYviN9bTq56AHWuyAZgNOeOwWzU0ubnPYa14mgOaGHqm2R4NotnOtB0bThmgrW8bX37iDn3poruvWaDMzc8C2bcRwc3NI7vbPXJKzMifbbFEuhTzNu+ug6NVeGJCHM+3+P3Ui4rNDrEtNq1wlrG3nccTvhMO6c7Yw2n1Fa91dnvbi6lZv29i9RgkAu2q9SiERYQzRxp1luoNYdS7ggsTUOxsZCWMMTz13HYtTbnyizZ2IszjlgSBQPjZB7KefA60tQRBmAKDxz1gfH4voAb6hlSlVDQ3HPH85iqMTTtx7tHUuDFcmDPLgG8tW4LKZ4d7n+z0IBEFQ3eTilowHm1zyNsf3Nwbf5MpVaqhJTHWT6+S0fEnXaqeQKqjfCmtHqLGhRcOB4Seelzctxq3JxRjDF59bw4mwBx8703qLdTcnwh7kKzVqzBJN1pM7f9+NtBjulJUJyI2ioxPOgV7a4nk+0OqtyaWViN/RvLArIV0UkSyIB2r92SM+OKwmwzIzUxo2tARBwFLY01OtNwmA19H7OS3cGGjyAScx3GxmOtsLA7JLwp10yXCbVTV8+cUbqEkS/tkHF7t+LbdoJ4thglOtS80ab6T7ylqHrEzOUtg90Fov1iQkC6KBtb7hvqJSrLq/1nP3FaNqfbqore6enPZgI1nUtEXDt7H1EKsGXTZYTALdkUaEzUwZHrulo/0ujxO4NUJ3+5euJ3DpThaf/6FFmE2dhar8bnSdaj1B7KGfA62/AfALjX//BQB/3cfHInpgGJpchUoNz69s4+Nnp9tuHswFXbCYhIE3uXpVcfWC3ORSc+jNH7AlAID75/wwmwRDDr7pgqziUptv4XNYMeGyNm0z1JIsigjqZTnodUCsS32zu/yTl27gp5++0JeffdhQYksA8IHW6GxoPXctjnc2s/jlH1qEqcuhF9il2qaDL9FgY5fvupEbWucvR7EUcrfMyuQsDjgXJp7VZxtbKzN+B1LFquKwZ/5ns99y0Go24f7ZCby+YVyTS0uzaT7o6qnWB1w2Re+L3WjaEOX70+S6fDeDx3/324bbgI0L0YyyDa1qnY1M4zJTrOIrF9fxqfuOYH7S1fXrZwNO2MwmytEimuzdxjZOvHK+IV7ptHmwOOVBoiAOzEEkUeC1vrdtbK3MqMzHZoxhLZ5vmdV1biGAlVjeELvRVCNKQG3dnQu6UJcYNjX0m3Y2tHq/25tMAqb66L4i1iR84t8/h79/e7MvP/+woazWy/VylO72Tz13HWGvHT/+4FFFX09xAgRxEF0GWoIg/DmACwCWBUG4LQjC5wD8HoCPC4KwAuDjjf8mhpD1RKF5ODDqkv3ctTjEmoQn721/6LWaTViYdA30jTyWLRt26AXkg6+aDK0b24UDtgQA4LJZcHbGZ8hAK9n02VZ/AO2lyZUuVHXb0Ar32Ybom1e2cHEtaYgl5LjBL4kR38Fsnt3MNcJjR2Xr7qnvrmLG78Cn36vw0MtV23TwJRrcTBThsJpgs5gMa3LxrMxOtR7gNkT5gb0+Yzn5z8No1bbSHK0bbbaxAbnJdflORvFwTE+SBfWWgwAwH3TiTrqEmgbVdlrPvMzmhlZ/Xh/PX9vG3UwZr940LtN0XMiVq8hXal3FK3NB3uQaDdX2V15ZR0Gs41eeWFL09RazCcemBns3IoYbbjc44bIauqH1zOUo7pv142iLrEzOUriRCzOggWxsCMQrALCpsMbEchUUxHrLWv8gtxi+Nfh6kiqo38YG5Hs9AE13+2SBZ2jpdLf32ft2r7+2lcO1rTyefZcMqvRAyTZ2xO+ASRidgdYPbqfx0vUEfumDx2G3KLMq5xato7RxThD9RpeBFmPsZxhjM4wxK2NsljH2JcZYgjH2UcbYycY/k3o8FqEvjDFsJIt45LhsSadFMaMHz1yKIui24eFjwY5ftzhgr+14rmJYgwuQczWimbLipl4rWwLOuYUA3ryV1tQw6oVePK/ngi7c0nDoFWsScpWafhlaTa9t/Q++jDFc2ZRzwvg/Ce2o2dAqVetIFIZ/iJgpVvHKjSR+5n3zsFmUle2w1w6P3ULWBEST9UQRC0E3ZvwOw5pcPCuzkwURIFsMF8Q6tgZk/RbPVeBzWA6IQQZFpJELoHTQuBbPw2ISms363ZxbCKAmMbx1a7AWw7W6hFy5prnJVZeYpkFrsqBfXqbPaYHNYuqbapvX+Heo1vcMF690ytQAdmyIRqXJdf5yFA8fC+Dskdb2661YCnloG5towocFjxwPGiZeiWbKHbMyOXzLeFADWT7AMOpuP+mxw2wSsKXw98L/XPZvYwPA/bMTMJsEQ3K0tORlAr0NtFJNgax++dj9Gmg1a73GHHBiL9FMuXlObofNYkLE5xgZ8cr5y1GYTQJ+5n3zir9nKexGqVpXPBAniMNAPy0HiREglqugXJXwvuOTAIC7BmxoVWp1PPtuDB8/M93VP3Yp5MHNRGFgQxnDB1p+2eouqaDpzm0JFqdaD7QeXAigVK3jXY3B61pJ97ihdXuXdYbixyw1HlMvFVfThkj/A8Rmpox0wy7inc3B/m7GkWimBLvF1LWpOkrWBCsx+e9Fu3zBVgiCgKUB27YRw81GsoD5SRdm/OqyGfXk/OUtHPE78J6j/o5f17TMHGCTK9zlstxPIiptiNbiBcwHXbCaDx7jH5iXVduDth1MNyx5tTSb5npocqWLVd0aXIIgINRHG6IrdzMAaKClBzvilc7b2Hw7ZBSaXJLEcD2Wxz1HOr8/7mcp5MF6sgixNljBGjGcrCeKcFrNuG92wrB87H+8EgXQPiuTs2OZOZhaz9/bwz5j7vZmk4Bpr12FeEU+wx9vIVZ12y04M+M1xH0lVaxqutdP+xywmU3aBloFEU6rWTfhUdjXz1ov1/hrW/mBC4nHjVpdQizXfUMLkO/2o3CvB4CVrTyOTbo65oLth+IECOIgNNA65Nxs2NacDHsw5bEbsqH18moCuUoNn7x3uuvXLoXcqNYZbg2gWJXEOnKVmmGHXmCX17YCJcaOLUHrXJJzDWuCQR98UwXtTa75oAs1iam2wtx5TJ1siHz9C4rnh16Amlx6wG0J2mXxcWaDo9PkurYlH1xPhr2qvo+8tgmOJDGsJ4o4NunCEb8TmwZsaMlZmXF84p5I19cnt8xcG+RAy2DxCqCs1gPA2na+7TZ20G3DYsg9cNV2uod8i95siLQpxdvRLxuioljDWuPMTbW+d6IKt7EdVjNCXjtuJYe/yXUnXUJRrOPUtMpaH3ajLjFsJEnAQshRAguTLhyZkF8bRuRjP3Ope1YmsGOZOSj3FW4vPOUxOB87q+z96MZ2AQ6rCTNtBDfn5o1xX0lr3NAymwTMBpya3FdSxapu29gAEPI6kChU+vJnxze0xJrUrPuENuL5CiS2Y83didmgE7c1RlUMmpVYXn2tH7DYjyBGARpoHXLWG2/6/OBrxIbWP16Owm0z4/Glqa5fy4c1g2hyNTM1DD30ysVbiWq7aUvQpsl1xO9AxOcY+EArXRQhCIDPObgmF7clCOrU5HLbzHBazX1pcl3ZzEIQgAfnJ/AuWRP0zFa2e3AssFu1PfxNrpVYDk6ruWMOQSuWwh5sZsrIVwavziWGi1iugkpNwvykGzMTDmzlKqo3X3uFZ2V2U2wD8las22Ye2Iah0dvYHrsFXodFUa2vSww3E8W24hVAbnK9vp4aaEZgqqhdvDLjd8JiElTXesaYvKGlZ5PLY2+e//TkajQHxoCHjwWwla0o2rwn2sOHv0pEZ7MBJ26nh7/JxS2CT053HgLshze5rseocUrIG1rzQVdze3HQ+dg8K1NJrQdkO71BbmMH3baW282DYsbvVGUvfHzKA1MbB5tzx4IoioN3X0kVRc11d05jPnZKx7xMQLadZAy6W89LEsM7d7N4+JgsJCYBS28oFa8A8oZWNFse+m3lcrWO9UQBJ7sM/Pcz5bHB57DQQIsgdkEDrUPORqIIs0nAkQmnITZEdYnhm1e28OHTYUUr5EshHh7b/zfyHVsCA22IVORqcHVbuyaXIAg4txAY/IZWsQq/09rVTrIVfKClVsmVKmjP7WqFIAh9U21fvpvB8Uk3HjoWJGsCHZA3tLoPfrwOKyZc1pHY0FrZyuPkdPsLbTv4++WNMbMdFGsS/uatu3hlLWH0UxkZ1hsh8QuNJlddYn1p2ndiJysz0PVrBUHAUngwTS7G5D8LIze0ALneK2k83kmVINaktvbCgLyRnSpWcWOAymBed3tRbattchXEOsS6pNs2NtC/Da3LjW3sn3xwFgDwLjW5emIzU8aUx6YoTH1UbIiubclNabVNrsUxVW0zxvC9G0l87fXbRj+VkUGS5GzshcY2NjD4fGyelfnkvcoGWkthNzYSRVQHcP+JG7yNDci2e0rzsde222djA8a4r5TEOspVSfNwab6HgZaeG1rhPuVj306VkKvU8GP3H4HVLFCcQI/wgZYSsepswAmJKbfvNoq1eAESA06q3NDid6NxzMfeSBTx5RdvGGKRS4w2NNA65Kwni5gNOGE1m2TFULo0UEXv6+spbOdFxSquCZcNUx4bVgegQuQNDSMPviGvHB6rpDCvxTvbEgByjtaddGmgar1kUdS8KTXjd8CsQbXNleJ6H3zjfWgAX9nM4swRH87MeMmaoEckiWErW+4aEs+ZC7hGwoZoJZbratvSCv4949LkShdF/OF3r+ODv/8d/Is//z7+t//vbaOf0sjAt7GPTboNsSESaxKefTeGj50Jw6JQGb0U8gzEhihXqaFclRD2GideARo2REq2sbf5NnaHDS0DmlzNwHa3tibXXNClWbyi54ZW2OtAulhFpVbX7WcCcq33OSz46Jnp5n8T2olmSooaXAAwF3Diblp9HuugWYnlEfLaVYuxPHYLZvyOsan11bqEv37zDj79n17CT/3RBfyrv3gLdw2wyR1F+Db2wqQb0375/jpo9xWlWZmcpZAHtcYgrt/EDN7GBuS7bbERa9CJSq2OW8kiljqIV4xwX2nWeo13+/mgC5lSFZnGXV3x4xZE3YSqQP/ysa9sylmZ989O4ETYSxtaPcJF3REFd/vZwGjECfBsbLXb2ABwIuQZq3zs19eT+MJXXseH/uBZ/PY3ruBv37pr9FMiRgwaaB1y1hOF5hbMkQkHCmId2fLgJuPnL0dhM5vw4dNhxd+zOOXB2vYALAcbdiZGHnzNJgFhr11RrsaN7c62BMBOk+uN9bRuz7Eb6R4sAixmE45OOLGhcuiQ6iHLox0hr/6q7UypilvJEs7O+HBmxgeArAl6IVEQUa0zRbYEQMOGaMgPvZlSFVvZimqfbQCYD7phNgkj3+RaTxTwb/76Eh773e/g95+5ilPTXnz87DRuJoooV/VtOo8r64kCLCYBRyYchtgQvby6jVylplixDQCLU+5Gpkx/zyR8G3sYmlyKan1zG7t9k2sp5IHPYcEbG4Nscmm3HAS0qbZ7bay1gv892M7ra0N05W4WZ4/4EPLaMeWxk2q7RzYzZUR8ymx4ZwMuVOuD30pVy8pWDqc0NLgAnpk52k2ubLmKp59fxRO//yx+7b++iXylhs8+fgwAcHWLXi9KuMm3sSddsFvMA8/HLlRqeEFhVianuWE4gK2DeLZseK1vZmZ2EbBsJIqQWGfxihHuKzt1V7t4BQBuqbx/pYpVBHW+1wP6b2hduZuFSQCWI16cidBAq1ei2TLsFpOins5cQP67Newb2StbeZhNAo53GFa3YynsQTxXQaakbiA8TNTqEv7uB5v48T98CT/51AW8vJrArzyxBKfVjKvR0e5ZEIOHBlqHnPWEbEsAYOBNLsYYnrkUxQdOTsFjtyj+vqWweyCXtni+AotJ0C2HSSvcmqAb3WwJAODsjA92i2mwB99Ctadmk6YmV0GEy2ZWZGOplLDXgbjOh15uOXT2iA+LUx5YzQKptntAjS0BwAdag91KVcv1mDYLIgCwWUxYCLpGcqDFGMOrN5P45f/yGj70B9/FV7+3gR+9bwb/8GsfxH/53CP49HuPoC6xkfz/ZgTriSKOBpywmE2G2BCdV5GVyVlq/J3vt20eb2YYbUMU8TkQy1W62i6tbefhc1gw2WEryWQS8KABTS6b2QSXTVvdnQ+6kC5WVV3Sd7axdbQcbDa59Ht91CWGd6NZnJ2RNxbOzFCTq1ei2bIq8Qow3E0uxhhWYnmcDKsXrwCyxfBaLD/U55l23EoW8dt/ewWP/dtv49/+/btYmHTjS7/wEL71L5/Av/zYKQByBh3RnY1EIxs7KN8HB52P/dy1OCoKszI5/O7ab4cKxhji+cpQbGMD3QdaqwrEK8CO+8qgbNbSjbqrdVtKSz52rS4hU6rquqHVHGjpLFa9fDeLpZAHDqsZZ2Z8iOUqSOT1tzE+LMhRAg5FA/KI3wGTMBobWlx0oBaembk2gvfffKWGL714Ax/6g+/iV7/6BpIFEb/96Xtw4V9/BL/x5Gmcmvbg6hadjQl1KJ8iEGNHuigiU6ri2OTOoReQm1ynI76+P/7lu1ncSZfwLz56QtX3LYU8SBZuIVXQHkiqhFi2gimPXXVujd7M+B1NX/12cFuCT99/pOPX2Swm3D83gdcHqNpOF8Xm9pEW5oIunL8cVfU9yaKoq2IbkA++uUoNJbEOp8aG3X54psY9R3ywWUwNawK6tGuFD+OVN7lcqNQkbOdFwxWb7bi2JR9YtWxoAbKyc5S8tiWJ4e/e3sQfv3gDb91KY8Jlxa9+6AR+/rGFPXmGy40/j6vRHO45oszW5jAjZ2rItd7ntMBlMw+sycWzMj+kMCuTs9TMhSn09XfMtzbCPqNV204wJm+MHZlov3myFi9gMeTperl/aCGAP7gaR6ZYhV9HVXM70oUqJlxWxar8/ezOzPQrtKrSOy8TQLPZGdexyXVjO49yVcI9R+Sz0NkZH/7kpZuo1iVYFVpwEjuUxDrSxaoq8Qog/916+Fiwn09NM/I2al2TBREgCwBylRpiuYpi22WjeetWGk8/v4Z/uLQJkyDgx+4/gs994Dju3fX697usiPgcNNBSyHpyZxsbQMOKcnCbe+cvRxFwWRVlZXJ8DivCXnvfN7TSxSqqdTYU4hWg+0CLu9F02+Jouq9spPAj75nR4Rl2hm9oabX1nwvK78dqBlpc6KJnlIDdYsaEy6prrQdkO+FHjst1hvc/3o3m8P4Tw3nPHHbU2AvzCJVbQyxeAeQNLa33ep6PvRov4IF55e+zRhLNlPHll27gz1/ZQK5Sw/uOBfF/fuosPnZmGuZdfdZT0148ezVm4DMlRhG6RR1i1hsqLt5E4Bta/W5ylat1vHozif/07HWYBOBjjTwBpewoufp78B0Gn21AVptsddkM4rYEx7uouAD54Hv5TmZgVl2pYrWnwPb5oAvJgohcWblqO12sas7xaAf/u6DnwffKZhZTHnuzgXZmxktB8T3A7brUNrmGWcm1spWH02rG0Q4N7k4shd24uV1EbQBh23rw1e9t4H/68+8jW6ridz5zLy781kfxv3xyec8wCwCOTblhM5vIhkghN7cLWGjUekEQMON39H1DS5IYrkZz+MNnr2M7L+JJFYptQLZMEoT+2xA1LQc9xjaB+SC+m+3gWryARQU2JQ+i7kEOAAAgAElEQVTyJtetwQhYUj0KSeZ2DbTUPCYAXTfp+6Ha5uKVs42B1pkZH8S6NJCMuHGEv0aUilf4gHiYN7RWGu9z2je0Bmfbpger8Tx+4qmX8cJKHJ//oSW88Jsfxr//p+/dM8ziLEe8NNBSyM2EnI3NsyoHlY+9mSnhb9+6i++8E8PHz04rzsrkLIbcfd+4jw2JvTAfOG92GWjdiBcQ8trhdXS+zw7afSXV3NDSds/2OqwIum2qBlr9iBIAgJDHrqsVbbIgYjNT3lXr5fdz2sjWjryhpfwOPOxxApVaHTcTBc3ilbmgC1bz6MQJMMbwT5++gC+9eANPLIfwV7/6fvz3X3kMn7wnsmeYBci1fjsvYps2GgkV0IbWIYaHxHPVdthrh0nQ34YoWRDx+noKr91M4rX1FN6+nYHYaK7+9MNzmPSoO1juXNoKOLfQP6VlPFdRfFnuJzN+B/KVGnLlattDbdOWYKp7cTw3H8BTEsMPbmfwvuP9VaqWq3WUqvWeNul2VNslnD2i7CCbLOi/odW0IcqVMd+w6ewVnqnBOTvjw9ffuINEvqL6dUHIh16LScCUW9mf3ewur+1hVTmtxHI4Ee6cjdeJpZAHYl3C7VQJxzR4dQ+a19dTmPE78O1ff6Lj/2er2YTFkJuaXApIF0Vky7WmvTAgN3j1thcuV+t461YarzXq/evrqWYm5/K0V1VWJgA4rGbMBVx9tyGK5yqwWUzwOY09EiuxISpUaohmy10tiAA5kNxsEvDGegofXlb3Z6+FdLHaU7OJ11VVTa6CCEEAfE79mlxTHhsEQd+B1pXNLGxmU/P8ujszczmibYBxmOHvXUpC4gH5vSTstQ91k2tlS7u9MLB7ozWPx08ot3Y1ijc30qhLDH/5hce7KtWXI15cWEugVpdUD0oOGxuJIuYnd+rD7nxsv07vk3WJ4dpWrlnrX7uZwp20/Jr02i342UcWVP/MpZAH3/jBJhhjmrd8u8HFK0ZvaNksJkx57IhmO5/B1raViVdsFhPun50Y2EArzTejnb0JWNSIV5IF/Te0AHkzX89azwdX3F540mNH2GunOAGNSBLDVrasWKgKyHf7l1e3+/isemMtXoDEgJMaN7SsZhMWJt0jI16J5ytYTxTxf/zoGfzSBxc7fi0/D1+L5jBFG42EQmigdYjZaATH8oGBxWzCtK93r+1ytY5v/GATr95I4rX1ZHPYYjULeM9RPz77/mN4aCGAcwsBTU372YALNrNpIEqu++eMt7Ka3mVN0G6gxbfVlDS5uGr79fVU3wdaegS27/ba3j386fa4/Pv0Qm8bIrEmYSWWww+dCjU/ttPkyuEDJ6mQq2UrU8a0z6F4+DMKuRorW3k8vjSp+ft3N7lGYaB1bSuHU9NeRb/D0xEvvncjOYBnpY6tbBliTWpunBjN/m1sQBZKvKvDMPC7V2N4eTWBV28mcelOBtW6rAI/EfbgR94zg4eOBfHQQqCxbaW+SbUU6v+lLZarIOy1962JppSIAtU2zxPrFBLPcdstODPjHViTK1kUNTfjAdl2asJlVTXQShZFTDitB1SevWAxmzDptum7jX03i5PTHtgscjN+MSRvmL6zmcVnHjiq2+McFrZUbmMDO5mZw8rKVh5THrtmAdi0zw63zTxQe7leuBbLwWoWFDXsl6e9EGsSbiaKONHDe4zelKt1XI/lW26VGQFjDDcTBbx3bqL5sd352L0MtK5Gc/jmlShevZnCGxsp5BpilZDXjoePBfC5DxzHQ8cCODPj02SjuhTyIFOqIlkQ+ybo27EXNl6sGvHbu1sOxvN48l5lFoLnjgXwxy+soVyt65of3YpkUYTHbmnWMy3MB134we204q/Xo5/QirDXgVdv6nePuHw3A2BnMwsATs/4KE5AI8miiGqdqRKYzwaciDbuYb38He0XO9vY2mvZUsg9MnECK43oBCXxI3ygdXUrN3TCnDc2Uk2hIDFc0EDrEHMzUcS0z74nD0gPG6I/e2UDv/ONK/A5LHjoWBA/8eAsHj4WxH2zfl0OWWaTgGNTrr5e2mp1CYlCBaEh2JLZuYyU26o51hTaEgCyumlxyj2QJleqoajq1XIQUGlDVBB7esxW6G1DtBLLoVpne4Z0pyM71gQfODlchXwU4MGxSnHbLQi6bbg1pKrtTKmKaLb9614JJ3YNtD6q0t510NQlhuuxPB5bVDbAOxXx4q/evItMqaqb8lgPfutrP8D1eB7P/68fNnxIAgA3G+KV3QPNGb8T2/lKTxe+la0cPvsnr8JmNuG+WT9+8QPH8fBCEOcWArrlWy6GPLiwloAksb7lWcZyZcMtiADZSsduMSHaQVTEhTxKxCuAvJH9F6/fHshmQ7oo9pxlNR90qbQhqure4AKAKY8dcZ1siBhjuHI3i4/s2lC0mk04EfbgHdow1QQf+qoZaM0FXfj+hvIG6qC5FsvjlEYLIkC2kl0Ke0bGhuj6Vh6LUx5F70vNJlc0N1QDra++soHf+bsr+NavP9EUDxlJulhF7sA2tj752D//5Vewla3gZNiDT913BA8tBPDwsSDmgk5dzjmLu3Jh+jfQGg7LQQCI+DrboqUKIlLFajMvpxvn5gN4qs7w9p1M33MCe93GBoD5oBP/8Pam4rMJz8vUOzs95JU3tPTaDLxyN4uIz7Hn7/CZGS8urG5TZqYG+NBX6TY2IA+0GJOH+AuTwyfkXNnKwSQoP8e3YinkwbffiY3E3yk12+chjx0Bl3Xo3FdWtnL4iT98Gb/96Xvw848dM/rpEPsY7lcA0Vc2EkUsBPe+mc7oYEN0PZZD0G3Dm//XJ/Dlzz6MX/3wCbzveFBXxdBSyIO1Pl7akgURjAGhIVBxKcnVuKHQloDz4EIAb2yk+u6pni72Htjud1nhdypXbdfqErLlmu6H3km3DWaToJvX9pVGpsY9uwZa3JqAvLa1Ec2WMa3SJnSYVdvXdVBx+V1WTHnsWI0Nv2r7dqqISk1SHJTLB8ArQ5aj9fadDG4lS3hjYzCbMd3YaLGhdWTCAcZ2Nh20wFWGX/8fH8dffuFx/OsfPoOPnZ3W9b13KeRBuSphs4fn2Y14Y0PLaHi2WbRDZuaN7QIEATim8JL+4EIARbGuyzZeJxhjcnZlz00udTZEqYKoe60HZAW/XuKVWK6CREHcU+sBWa1KtV4b0UwZfqcVLptyXeZswIm76RLqUn/PvVpgjOH6Vq6nWg/IApZRsSG6FsspzhA5EfbAJGDoMjPfvpMBY8DfvHnX6KcC4GCUAKBPPnamVMVWtoLfeHIZ3/z1J/C7P/Ee/OS5Wcxr3LxuBR8I9vNuH89V4LKZ4bEbr+eWa337c40a5xVgx33ltZsDEKv2mJcJAAtBN2oS65ojtvOYDcvBPsQJiDUJ2VJNl593ZTN7oNafnfGhWmcjIzYYJrSIV3bHCQwjK1t5HJt0w27R3hc9EfagJrGmA8cwcy2Wh99pVSQkEARBzswcslr/g9vy5uVfff+Owc+EaAUNtA4x68nCgSygI34HNjPlngYda/ECjk+5+6amBuQD3kayiGoji0tvYkPisw3I/s5A51yNtXhekQUR59xCAMmC2LQv6hf8ABpw997kUjrQSpf647NtMgmY8uhnQ3RlMwun1XygMXlmxkeqbQ0wxrCZKWFG5RB6mMNjr8caqqYeVNtAw7ZtBC5S1xq2BEr///LBV7+b9WqI5crYzsuD/GFqck377HtEJc0mV1r7hY/Xj+N9tLJsqrb72KSVLQeNF68AssVwpw2ttXgBRyecigVC5xpNrn4PV3OVGmoS67nJNR904XZK+dChXxtaYa9dv1rfEK+cPbLXluzMjBfxXIXCrzWgdhsbkJtcNYl1bCIbxd1MGQWxjhM9bGMDwFLYI/+sij7N2X5RFGu4lSwpFq84Gmflq9HhGgDzgfTfvnW37wJBJaw3trF3b2jpkY99c1t5TrNWjk44Ybf0N04gNiTiFUBu0KeLVZSr9ZafV5ONDQzYfaVY7VlI8v+z950Bbp1V2s9V75rRNGl6L+4pdhLHaXZ6cVgILQlhKWEpG7LLLiGhfNtIgLCwEELbZWEXsoT1kpBiOyGk207ikuKxPePpfTTqo951vx9XVzOeUblVkvE8v8AZ6Uoz0j3nPecpTSzdVzyhGJQyyRmuQkKAHrI7AvzrQiSexJgjuCoeYXlm5hrYge6H2amxqfMNG3JUMTFs5680Xh4nUO4YsfnRXadjTH7oqdNjeMGPVBmRj+jv7jvTi2X7uTqXsbbQOkcRjiVh80XRumKhZTGqEU2k4E5Lu7lg0hVkzB7mio4acZkJtAqnHGwJlDIpqrSKnCwmtrYEwNKQS+zGVyjPazasbdqWgK/1UTbQ1gRCYGDeh16LfpUXb5/FgFG7H7GEOMvaP1d4w3FE4ilWTS9ADbnmPOGyGEasxLAtAJVckmGbccXZYkM0nGZkMW30GyrU0CtlmceVA+jhdb1RhX1pO5VSY8oVXGW7kbEhYsiOzYYJZxC1eiW0IrKdxT60RRNJLIbiZVHrgbTtcz7yipMdeaWhQo06g1J01vZi2l6Yvw2RJs3aZrZoFcNeGKBqvcMfFeRATYfB91rOHN6vWxtyccaCl11IPLAsM7MMhxG0yrib95CLus+LTVbjCy7q8x6zPkN6KQdEE1R+Vr1RhXFnECfnSv89zpaXKUQ+Nm1bLCZ5RSIh0FatFTVOwO4rD3thYMlCLRdZddwRhFxKZO5bTFBM9xXeauyqpXxsJvAEY4ITVYFlcQJ5lPFMMbTgRzJFZmo7jfZqOjOzfM4qZwus3ghkEgLVWubfW7NBBamEKEuFVjSRxJQrxJjMkQtLFq3lUxOzgSRJDNsC6Kxl/n57zAYEY0nM8SBcCo0Bqy9DonrmeHmQVdewhLWF1jkKuoFoFnjIFYwmYPNFefnCMoHYQy5HGSm0AIqZkou1TdsSsDlodNbooFfJRGdtL1kO8mt8m1iwtsWyJQCo8Fghml6SJDFg9a1qegGKtb1mTcAe9D2LVp4wRWMltcR3lCFLfsQeQEeNjncAaUeNDp5QHK4yfI/LQQ+HmGQBApQ1QbdZX1YKLfrA+jdXd8MZiOGNMVeJXxE15GoxrSavAPxsiCadQVEHXABQrVPAoJJhXKQhF62mK59ar4bNF8m6SCFJEhMOdvbCBEHggpbKs4q8AjAbcpEkCU9InCFXrV6JRIrMvC8+GJj3odmkgWHFfa13baHFGVwVWkB52hCNZNTJPBVa6bNRuYfFc3m/PWY9Jl1BhGPZFS3FxogtgESKxOev6oRcSuCZ46W3IppyhWA2qFYpePnmY9NWty1V/MhVhdBRK26cgCNQPmps+v6Va94y7gig2aRhlX1Ju69MimxDRhFJ+NVds0EFuZRgvtASIKMzG+jPgxBkVZq8slKhJZNK0FWnW6v1HLDgjaDOoGLl+iSTSmAxqsrSfWXCGUQyRfJ2XtGr5KgzlH+cgCMQhTccZ5UPujwzsxxAkiQGrT5c3lWD85sr8OzaQqvssLbQOkeRsSXINeTiuBXPhM+LrNCiF2ZiDbnopUW5MLny5WpkbAlYsLYlEgLnN4s/5HIH49AopLx8ggFqyBVLphjlvbiDwizRsqFWrxRk8THrCcMfSWD9CgsiYI21zRULHHy2gWWs7bIccvl5s7iAJda2mMxXITBs87Me6HXX6TFs85eNwm7Q6kNDhRq7t9RDr5Th6RLbDoZiCdj90VWDKK1SBoNKxnvIJfZCiyAItNeIpzC0p2sKbe1baliMKsSTJNxZFik2XxTBWJI1Yej85krMLYbz2hbzBf16+doLs7EhCseTiCZSog65hKj3p+a9qzI1AMoiqs6gxOk11jYrxBIpOANRmA3syCv1FSoQRJnWersf1ToF7+Vsc5UGUglR9oSoYbsfCqlklUtIPvTU6UGS5bOso3v0SzqqcEV3DZ49bi25RdJ0ligBgH8+9oQziHojc6tbruiopuIEoglxlpYOX7RszvXmTD529r/LhDPI6lwPFMd9hc6p5nvGlkoINFYyjxPwhOIw8ewvsoHu/YSwGB6Y90GvlKEpi6sGlZm5VuvZggt5BSjffOwMmYOFYikXOkQ8GwkF+v2ymWXQy69yydGy+aLwhOLos+hx65YGnF7wl82ybQ0U1hZa5yhoW4KViycLT4XWpDP9vNXisrj0Kjlq9Urxhlz+KIxqOe9FjFDIl6tB2xI0sbAlAIALWyoxbAvAm86cEgOLAgTHAuxY27QqTCxrAlcgyjtU/NR8dhYXQCntFDJJURZa5bIEEAJLCi12jW9TmbK2/ZE4rN4Ib59t4Ozw2k6mSIzaA6xYXADQa9ZjMRQXzAqULwatPvRZ9FDJpbhugxkvnFrImZFQDExnCYmnUc9jyOWLxOEKxtAq8kILoD6/opFX0p+bGl15sLbr8tgQ0cx1tjkmF7aaAIibo7UokELLYlRBJmHG2s6osUUYcgllQxSIJjDpCmVVYwPUkGtgrdazAk1sYlvrlTIp6vTlydqmLHn413qlTIpmk6asaz1ADbnaa7Ss1Cc0a/t0meRoDVr9UMklaK3S4pbN9VjwRXBk0l3S1zTpCmVdEvLNx550BkU/1wOUQitFAtMiKIzCsST80UT5LbS8q2tMMh2pwJa80lmjg0ElE3WhRedUC3G2b2IZJyAGeUWvlEEpk2SiJvhgwOpDn8WQVU3UZzHAGYgKls2ZCyRJ/lnV+wUfe3thgFJkl9u5HqCIqhICgjhZ0Qutcv5705EAbBRpepUcDRXqslka0fO4PosBN260QEKgLBTZa1iC6AstgiCuJwhiiCCIUYIg7hf7emtghil3EEa1HMYVDJtqrRJyKcHZhqhYCi1AXGbCiN2Phgp2CyIxYTGq4MkRHsvFlgBYYnK9K+KQyxOK8WZsA+wWWm6BBmvZUKtXIkWCt3XbgNUHCUExTldCJpWgu04nuo3ay6dt2PGdVzBqL4+GgS8WfBFICPaqyobK8gyPHbGzZzXlQiZsu0yYzdkw4w4hmkixZq3Rv59yaHwj8STGncFMAPStW+rhjybw6pC9ZK+JJq9kswqyGFWY56jQokPixVZoAUBHrRYLvggC0YTgz02z/Wm75VIjnw3RmJNWY7P7na+zGKCUSUQdcnmCwgy5ZFIJGirVmHYX7kHFzMukLSj5LspP57AgotFnMWDMERA1M9Pmi+DKf30Vv397VrRrFBP0Qqvuz4S1TZI0mYN/rQcoRXa52xCN2P2sF3gtVVooZZKyycwctPrQYzZAKiFwzbo6qOXSkmZrhGIJOPzRrOQVPvnYJEkWRY0NiEu+GkmfddhkUokJjYJSyWcjq856QoglU+hgSV6RSAgqR0vMhZZAUQIA0GxSM1ZouUMxUaIECIJArYF/PnYyRdmS5a711P1dTLJqKkXi7l8fw9/tOS7aNYoJkiSxwEOhZfNHRFN7csWIPYCWKq0gateOGi38kYToS1I+GLEHYFTLUaNjN5uhMjPLo9Yv5eAaUKNX4tLOajx73FrWi8RzDaIutAiCkAL4MYAbAKwD8FGCINaJec01MMOUK5R1wCWREDDz8NoedwRRZxA3JJ5Ge40W446g4DcUuz+CIxNuXL2uTtDn5QNz2goym+UeF1sCANjcVAEJAVEbX08oLshiyVJBBXwyWToshuJQySVQK4RX19UI5LU9MO9De40u52vsMxtEbXq9oTi+8sQJzC2G8YMXR0S7TjGx4A2jRq+EnOViV6OQoUqrKLsh16iNfWh6Lkgk4tq2CQF6gcfWV7ycvLZHbAEkU2RmoXVJexWqdYqS2g7STOcWU5YhFw+F1kQRF1q0IkmMbI19/Vac11yBKpaHLbFgydgQZan1jiDUcmkmTJ4pFDIJNjdWiMvaDsVAEIBBLQyBhZlCS1w1NsDfhihXpgaNPosB8SQpmo0aSZL42h9OYsoVwsPPny6pWlQocFVjA9SQa6bMFFpWL7WsF6LWA9RSgM7pKEeEYgnMuMOsF3hSCYGuIpC9mIAkSQwu+LAuPaTWKGS4Zl0d9p+wirqczodMNrYpi0KLh/uKOxiDL5IoClGV7ifEsMfed8IKmYTAFd01gj83V1iM6qx/k3EHN/IKAFzQXIlhu18095UlZbQw7iueUBy+SP7XmkyR8IbjqBQhSgCgLIb51vopVxChWDK3GtssfpzAY4en8OKgHU++O4fjM4uiXadY8IUTCMeTmRkYGzRVakCS4EzaEwvDNvZkjlzoSD/PaDmf7W1+dNfpQBDsssB7zHqMOQKIJ0tTT5eDjhIwps83uzfXY9odwnt/Bt+xPxeIrdDaBmCUJMlxkiRjAH4H4FaRr7kGBqAWWtkbJarB4q7QKkbTC1CHNm+Ysj0SEs+fXECKBG7eZBH0efmAHmCtbHy52hIAVIZKn8WAt0W2IRKCPS2XSlBfoWKm0BIgrDYXBBty5cjUoEFZE8QEsUDIhgf3D8AdjOGadXXYd8L6Z6HSsnojnJpegGZtl9eQa9jmh1ImyWTK8EVnra6sM7SWbAnYDblMWgVq9MqyGHIttyUAKLXJzZvq8dJpO/wFDuxiYdIVRIVmtRoboGyIPKE4wjH2Q246JD7b8ExodNaKk5k57ghgwOrDzZvqBX1ePqjSKSGVEFlZ2+POANqqtazCsWmc31KJU/Ne0RYanlAcRrUcUg6vbSWY2hDRagMxhlxapQxahZR3DT4154NJq8i5hOwzi8va3ttvxYuDNtywwQy7P4r/PTojynWKCa55mQBlQ2T1RpAogyEJjSUyh0AKrVodYslU2fU0NEYz6nP2Q73uOn1ZkFcWfBEshuKZWg9QiuzFUBwHRx0leU0Zy/8cCi2AWz427bxSDPKKVimDxagSnHxFkiT29Vuxo6taFEUvV9QZVVmJqvT750JWvaClEiQJ0YatnqBwLijNDDMzveE4SBKoFIG8AgA1Ov4KrULklcp0HyBWrZ/1hPCd507jkvYqVGjk+NHLZz9Z1ZrOl+NKXgFQVnUwlkhh0hXiVPuygV6MlevZniRJDNsCnHqbnjo94klSNLt5NhhMW4nSuG6DGQqZpOQZ2WtYgtgLrQYAy09Ps+l/W0MJEU+mMLcYRkuOQVQ9TxsiIXxhmYBmJghto7X3uBXddTrB7D+EwJLX9pl/F662BDQuaKnEu9OLoh3uKYWWMMMmxqxtERdaSzZE3IdcnmAM895IThYXsDQQFyNA9sCIA3uOzeIzl7fjOx/YBLVcih+9PCr4dYqNBW8EZgM3lUVjpQZzZabQGrEH0FGjE2RADFDWBDOeUNky9EdsftQbVdBxUPf2lok1wYDVB41CekZtvWVzPWKJFP54ylaS1zTtDuWs9fSQiwuBZbJIIfEA0GzSQiohBB9y7e23AgBu3GgW9Hn5QCohUKdX5mRtc+2vLmipRDxJ4sScl+9LzAqPQHmZAFXr3cFYwSWwkIO1bKg1qAQZcq2zGHKyU+nMTDFygdzBGP7xmVPY3GjEjz56Hra1mvDTV8fKzoKHLazeCLQKKfQcakVjpRrJFJlVAVkqjNBkDgEVWkD5ZmbSIfGdLO2FAarW2/3RzHe/VBigc3CX9fGXddXAqJaXbMg17aYGf83Z7IV5KLQm0ouyYiy0ADpOQNgh5nszi5j1hHHTxvIhqgKAxaDKXuudFBGJiwqKdl95W6Q8t8W0QksIy8EmhgstMdXYACjLQZ41YWDeB1laRZoLfRa9KOQ7kiTx1T+cBAng4ds24VOXtuHFQTtOitTvFQv0d6OOpSsBADSayi8fm1ZOs7XWzwWzQQWNQlq2cQKOQBTecJxTb5NxXynx2T4ST2LCGTxjUW1QybGzpxZ7+61lq4Q/1yD2QivbCe6MvzxBEJ8hCOIYQRDHHI7SsJrONcwvhpFMkVmbXoCyIbL5Iqy/pLRaqlgKrfZ0cz3uFK7xXfBGcHTKXVaMbWBpobWy8aWZC208hlyhWBK/PDSBvf3zeOHUAl4ZsuPQqBNHJ914b2YRp+a9GLX7WedGJZIpeMNxwdhwzQxZ20LldmWDEAqtwQIsLkA8r+1gNIEHnjyB9mot7t3VBZNWgY9d0oJnj8+X7fCDKSifbR4KrcUwUmXUmNAyfaHQUaMDSS6xbcsNI3ZuLC6AYm0P2/wlbywHrD70mvVnKGjOb65AY6W6ZNkaU64QmnOpsXkNuYqTqQFQlnnNJo3g96h9/VZsba3kfN8QC2ajahV5JZpIYtYTyvQ9bHF+cwUA4PHD03j2+DyeP7mAl0/bcHDEicPjLrwz7cHJOS+GbX7MuEOsrZw9oZggAy5gOWs7/yCCtj4yCmBzmA01eiWvWh9PpjBk8+et9TKpBD11elHIK//87Cn4InE8fNtmyKQS3Ht1FxZ8Eew5dnZnaS34wjAbVawtbACKvAKU15BrxBZAlVYhmO1pR/o8UK45WsN2PxRSCVpznEHzIZOZWeIh1+CyTA0aCpkEN240408DNk6qZ76YcoUoNXaW+yGffOwJZwBSCSGYW0AhtNdoMW4PCBonsK/fCoVUgmvXlw95BaBqvSMQXWWrNe4IcO6vaPeVl07b8fR7c3juhBUvDdrw+rADb4658PaUBydmvTi94MM4B0svIXOqmxjmY4uZlwlQZFVfJMGL8Hdq3ofOWh2Ustwkrz6LAaP2gOCkkiffmcPrww585fpeNJk0+PilrTCoZHjkpbNbpbXAw164Tq+ETEKUlUKLzvFja62fCwRBpAkA5Tm/ockrXAQC7TUUkXFIBLIXGwwt+JEikbEXprF7Sz2cgSjeHHOV6JWtYTnEDjqaBdC07P83AjhjqkOS5L8D+HcAuPDCC8tnmvhnjElXblsCgFJoJVIknIEoK1ZEMUPiAaChQg2lTCIoM2H/CSvIMrMbBACdUga9SrbKmiBjS8Dxd35RWxXkUgIP7T9d8GflUgIHv7KT8WeC9u82CTTkajJp4AzEEIwm8see8hwAACAASURBVGa0eUJx1FeIM6BUyaUwquW8WNsZW4I8Cq0KjQIWo/DWBN/94xDmFsPY81eXZJQVd1/Wjl+/MYUfvzyK7394i6DXKxb8kTj80QQnCyKAWmjFEik4A1HUcmCCCQ1/JI55b0QwCyJgibU9ag+g15z7s1cKJFNUhsz2jipOj+8x6xFNpDDtDnGqPwveCD7966P44UfOy/ye2IIkqUDo3ZvPJEMQBIHdm+vx89fH4QxEUV3ErCZajX3rluwEjXqONkR0SPytW4onuO9IZ2YKhRGbH0M2P/5p93rBnlMoWIxqDK44xE25QkiR3CyIAMrKcJ3FgCffncOT784V/PkffmQLq7+vJxjnNHTIhuZlQ658yyBPKAajWg4Zy9xEpqjVK3FqnnsNHncEEUuk8tZ6gCKwvDRoB0mSnJY02fDyaRueem8e9+7qyjBdt3dU4YKWSvz0lVF86MLGvIO3coaVJ3kFKK+F1rBduEwNgOofq3UK0XLZ+GLEFkB7jZbT95buXYZtflzczr5fIEkSf/Wbt3HdejM+cEEj68fTGLT60WzSrFKU797cgMePzODFQRtu2VxcYmS+KAE++diTzhCaKtWs82m5oqNGB380AUcgilo9/5qSSpHYd8KKy7urRSM/cIXFqAJJUiTJ5efWcUcQl3Vxz/ra0VWNn782jnt/917Bn73tgkb86wc3M35uTygGhVQCjQA51QaVHJUaeeGFFp3bJdpCi/qcOfxRzovbAasPl3VV5/2ZPosBifR5Z329kdN1VsLuj+Cf9w7gwpZKfOziFgDU7/WTO9rwgxdHMDDvy9tHlTOs3ggkxBKZmA1kUgksFaryqvW2ACQEOJ8zs6GjRoujk+JFh/DBUpQA+/erlEnRXq3F0AL3PubfXx/DhDOEb71/I+fnGFgRJUBjZ28tdEoZnjk+hx0FvvdrEB9iL7SOAugiCKINwByAjwC4XeRrrqEAptMM/ZZcCq1lQy42C61ihsQDVIPeLjAzYW//PNZZDJyHRmLCbFCtsoYadwZhVHOzJQAodtiRr16NxXAc8WQKsUQKsWQK8UQK8SSJWDKJWILEtDuIh/afxjtTHtzA0LKBbkCF8rxePuRaWVjOvG5MNFsCgGqs7D7uC61T8z6YDaqCbNw+iwGnBWRtvz3lxn+/OYm7Lm7B1lZT5t+rdUrceXEz/vPgBO7Z1VW076+QoBe9XAeqtDXBjCdUFgstehAllAURQN2XCaI8Wdsz7hCiiRRnG4YemrW94OP0+f3TwAJOzvnw/MkFfOGqTk6vYW4xDH8kkfXetHtLPX7y6hj2n7DirktaOT0/p9fkSauxcxzQcyl/CyETEl/Ee0VHjQ6vjziRTJGC2HA+228FQQA3lJHdII06gwqvDJ254BjPZGpw/50/8bntsPkiVK1PUjU+W92//8l+vDXuZrXQWgzF8tZlNlhibee/V3lC8SLUeu42RKfmKbuffHmZAFXr9xybhcMvDKHCH4njq0+eRE+d/oz7GUEQuHdXF+765RH8/u1Z3HFRC+9rlQIL3ggu7eQ2QKivUIMgyidXgyRJjNoCeN95wpIDhD4bCYlhmx9bmio4PbbOoIRBJeNs2zXlCuGFARv8kQTPhZYv46SwHNvaTKgzKPH0e/PFX2i5gzivqTLnf+eajz3hDBa91gNUryrEQuudaQ+s3gi+cn0v7+cSGnXLejB6oRWIJmD3R3nV+q9c14s7trWk63zqzDqfJBFP/+//OjSJt8bZKQwWg3FUaOSCkS+aTRpMuZgqtMR1X7FzXGjZ/RE4/NGCS6rlcQJCLbT+8ZlTCMeT+M5tm85wh/jEpW34zwMTeOSlEfzsYxcIcq1iY8EbRo1eyXmZ3lihKauF1qidIkIIadXeUaPDU+/NIxRLQKMQe6zPDsO2AIxqOWo4Ejm7zXr0z3LPAvzNW1OwLkbw/25eBzXHBfyg1QetQoqmyjPvCyq5FNeur8NzJxfwL+/bcNYSxP5cICrdhiTJBIC/BvBHAIMA9pAkeUrMa66hMKZcIajkkkwe0EpwtSGiQ+KLZUsApK0JBLIcnFsM453pRdxUZuosGtlsiCbSmRp8GstKrQJt1Vp01+mxocGI85srcVF7FXZ0VWNnbx2u32DGx7e3Qi4lcHyWuR/zYkhYi4BmBtYEyRQpqM1hNtTqlbwytJiypfoseow5hLEmiMSTuO/3/ag3qvHlLIe6uy9vh1wqwaNnaZYWfa8ycxwGNpUZa1vokHgAUCukaKhQl+WQiw+LC6DsDAgCnJlcB0acAIAjE9wzB2jLsGxD/V6zAT11ejxT5GyNqfS9MhdrWyWXokqrYD3kWgqJL26tjyVSgmTdkSSJvf3zuKjNJMjATGhYjCqEYkn4IonMv40LQBhSK6Rordaiq06P9fVGbGmqwNZWEy7trMZVPbW4dr0ZN22yYHNjBetDpJB5mUY1ZZvFxIZIrAEXQLG2g7EkgtFE4R/OgoF5H5QyScG/Ga06GRBIkf2t507D7o/gO7dtgkJ25jHvsq5qbGmqwE9eGUMsIU52qphIJFOw+6OcySsKmQRmg6qgnWWxsOCLwB9NCGZBRKNcbYhCsQRmPWHOGcUEQaDXbMAwx4XWgVGq1r8z7eH8+Q/FEphwBbPWeqmEwC2b6vHasB3eUP4MQCFB18ZcRFWAWz42SZKYdAWLFiUALJE2hPr87u23QiGTYFdfrSDPJyQsWfKxJ9JK9A4eCy2JhEBzlQadtTr0WQzY1FiBC1tN2N5RjSu6a3D1ujrcuNGCnX21mPWEWUUKCE0abWIQJyB2htZSnAC3sz3d/xdSY7dWaaCUSQRzX3n+pBX7Tyzg3l1dq1Q/RrUcn7i0Fc+fWhAlo7MYsHojMPOwBG8yqRlFVRQLw7YAp+zIfOhIE1+FdLAQCqN2KjqB64yyt06PGXeYUw8+5Qpixh1GIkXi3WnuCrZBqw+9FsMZy2IauzfXwx9J4NWhtcikUkN0/ThJkvtJkuwmSbKDJMkHxb7eGgpj0hVCs0mT8wbD1YZo0hVEQ0VxQuJpdNToMOMO8fI9prGvnxo23lJm+Vk0LEbVqiDrcWcA7dXiq8mUMil6zQZWQ66MQkvwXI3czYk3HAdJCmdzmA21eiUcLPPEaETiSYw6AgWbXmDJmoD2IOaDR18exZgjiIfev3GVRQpADe7uuKgFT703h6kyzVjKB2vGZ5tb49tQUV65GiM2fyY3SEiU65CL7wJPrZCixaTBkI39oS2RTOHNNEP17SkP5xyuQasPBEGF1mfD7i31ODblKaoyYKqAGhugCCxsh1xLIfHFUzJnWNtO/p/f0wt+jDuCZZeVSYNWzi23GB53BFGrV0KvEt8yaVOjEUMLfsZ9VSSeRDieFEyNDVD1frpghlZMNAsiABnSF9ccLTpTr5C1Gt0PCBEW/+aYC789PI1PXtqWVQVDEATuvboLc4thPPnO2Zel5QzEkEyRnO2FgXRmZpkotOj+TqiQeBodNVp4QnG408qGcgGtPueTD9pj1mPI5ueUsXQoTV6JJlI4McecoLccQwt+kGR28gpA1fp4ksRzJ62cnp8L5hbDSJHI2zNyyce2+6MIxZK81EJsYTaooFFIBRnQJlMk9p+w4qqemqLUTrawGKgzy3JS0biTVmOL319taqRUQv0svguLobigRJJmE6Wiyfe5dAtoc5gNtQZ+tZ5WYxc628ukEvSY9YIsmLyhOL7+1Cmssxjwmcvbs/7MJ3e0QaeU4UcvnZ1k1QVvBBYeqvXGSg3s/qggM0K+iCVSmHQGBc3GBpadjcrsbE+SJIZt3LOxAWTssoc5ZGYeTJNXAODIJDeyKkmSOG31Z1VjA8ClndWo0ipKlpG9hiUUxxB5DWWFaXcwJ2MboCTdKrmEk0Kr2HZlHTVapEgUlKszwb5+KzY1GtHMIai4GDAb1bD7l8JjA9EEbD5+tgRssKnRiBNzXqQYHoY8AgbHAhTbSK+S5WVt04d3IQdrK0FbDnI5TI/YAkimSIYKLdqagF/je2rei5++NoYPnN+IK7pze7J/9op2SCUEfvzK2df42tL3KvpQwhZqhRTVOkX5DLnsAXTU6ASxVluOjhodxh1Bxt/hYmHE5kdDhTrrspUpuuv0GOIwEO6f88IfSeDqvjoEognO37dBqw8tJk3OfD86W+vZ48UbchVSYwPcbIjokHg6j6YYaM/YEPE/tO3tn4dUQuCGDeVnNwgssbaX92DjjkARa30FEimS8XdhMU1eEXrIVZC1HYyJqsZebkPEFiRJYsDKTI1t1MhRL0BmZjiWxP1P9qPZpMHfXduT8+eu7K7B5kYjfvzqaKafPFuwwNNeGKCGXGVDXsmQOQQectWW55Br2MZffd5t1sMfSbA+oyZTJN4Yc+LqtFKHqyK7kBpjY4MRbdXaog65aPJKPmvA5fnYTEFHCRRToSWREGir1gry2T066YbdHy1b8opBLYNaLj2DvDLmCEJC5CciCYWNDUYQBHCChfuKJxQT7FwPULU+kSLz9qGLwTgqtcLZHK5ElVYJCcGt1gOUGruhQg0jgx6oz2zAoJXbQn45/mXfADyhGB6+bVNOS74KjQJ/ub0V+09aOS0FSo0FX4Q3eQVgT9AXA1OuIBIpUvBa31qtgYQQ5mwkJBz+KLzhOLp5RCfwWmiNOGExqrDOYuBc62c9Yfij2aMEAEAuleDGjRa8NGhDgKOTwxqEwdpC6xxDKkVi2h1CSx4WF0EQqGc55KJD4ovZ9AJLzIRxno3vtCuE47Ne3FymdoMAxVqjw2MBYWwJ2GBToxH+SCJjN1UIS5aDwgy5CIJIs7ZzD7kWBV6iZUOtXoVoInWGHRRTDFiZZWoA1AFSJZdkDs9ckEimcN/v+1GpUeAbN/fl/dlagwq3b2vGk+/MlVSiP+4I4JGXRnD3r48xtna0+iKo0ip4qUMbymnIZQsIzuICgM5aHcLxJKw8cmHEAGXDwO/99pr1mHSxV+vSjO2/vaYLAJ8hly9vhlCTSYPzmiuKPOQKocWU35K2nkNQfLFD4gHKaqZSI8cYT9Y2ZTdoxfaOqoI5hqUCnV26cAZrO1i0bM8Ma5vhkEto8gpAfV9mPaG8rG0qQ0tENbaBXmixv19avREshuJYxzAno89i4L3Q+rcXhzHlCuHbH9iYNy+AIAh8cVcXZtxh/OHdOV7X5AN3MIbfHp7Gp//7GN5YxqbNB/o7wSbfdyUaK9VY8EWQKINl3ojND5NWgWqB70WdAhIAhMSI3Q+FVJL3DFoItAqaLYHlxJwXvkgCu7c0oLNWh6McWduDVh/0SllOQgdBELhlcz3eHHfxyuBjA/pclO/3auHgvlLsbGwaQrkJ7O2fh0pennaDAPVZMRtVq8grjZWaomSy6FVytFdrWbuvCEkkYRIn4BZ4ibYSUgmBKh33fOwBq4/RuR6g4gTcwRjn5RkAvD7swO/fnsVfXd6ODQ35e4xP7WiDRi7Fj0oYKRBNJPGnARu+9L/v4eevjTF6TCCagD+S4E1eAcrDfWVYJDW2UiZFs0nD+2wkNISITmiq1EAtl7J2L6DIKy7s6KzGRe0mzhbDtA14vrP97i31iMRT+NPAAuvnX4NwWFtonWOgpLepgswftjZE7mAM/kii6E0vfT2+je/eE9SQ8caN5bvQWsnapm0JimX7tKmRsq9hOuRyB+OQSwleqouVKLTQyii0xFxo8bAmODXvg04pWxUumQ1SCYGeOn7WBP9+YByn5n34l1vXMzqAfPaKDkgIAj95tbiN74w7hJ+8Ooobf3gAO7/3Gv7txWG8NGjD9/44zOjxC15+LC6AtiEqfdMbjCYwtxhGF88FTzbQy+9yGnIlUyTGHPwXeN1mfea52ODAqBPr6w1YX29EY6Wa00IrEE1g0hXK2/QClEpr0OrDSJGYklOuYEHFsaVCDX80AX+Eed5HKdTYAK0w5PfZPTXvw5QrhJvKuNbTw3q61ruDMSyG4mgv0u/cYlShWqfEcYZDLo8IdbfZpEE8Sa6yWaZB2xyKm5dJ/R241nqgsAURjT6LAWOOIGdrnOMzi/jFgXF8dFsztndUF/z5nb212NBgwI9fGS3qYscbjmPPsRnc9csj2Prgi/jqH07g1SE7HvjDCUZ5oXzthQGq1idTJGuFjxgYsfMnc2RDQ4UaSpmk7BRaIzZKaVrIhjMfutMDwSGWdfTgCJVzsb2jCltbTTg66eZkMTxg9aHXos9LFNm9uR4kCTzbXxxF9qQzBLVcmlGVZgOXfOxJZxAKqQT1FcVTYwNUrZ9bDPOyCkskU3j+5AJ29dZBoxDuHCo0zIYz87HHHcXtrzY1VuD4rJeRYogkSSyGYoJFCQBLuev5iJSeoLgLLYB7nEAolsCEM8hIjQ0sDce5ZmYGowk88OQJtNdo8cVdXQV/vlKrwF3bW7G3fx6j9uKptOLJFF4ZsuPv9hzHhd98EXf/+hieOT6P7zx/mhEZgf5OCKHQKoez/YjdD4LAqqwzIVCOcQJ8s7EBSq3bXadjrdA6OeeFNxzHjq5qbGs1IRJP4eQ8e4vhQlECAHBBcyUaKtRFz8hew5lYW2idY1jK1MjfLLG1ISoVi0urlMFiVPFmJuw9bsV5zRUZNkc5YmWuxpgjCKJItgQA0FWrg0ouYTzkWgxRdkBCWgQ0mzSYdYdzWqbR1keVIrK2a3TcWdsD8z70WfRZwyWzgWZtc7EmGHME8IMXR3D9ejNuYDi8NRtV+PDWJvzfsVnR7ffmF8P4j9fHceujB3HZw6/g4eeHoJRL8I2b1+HN+3fhk5e2Yc/bMxiYL9z0W70RmHkwtgGKCTTnyf3ZKhZGBWA15UI52hDNuEOIJlK83y8X1nYwmsC70x7s6KIGwNvaqCEX2+/b0AKz4fVNmyyQECiKSotWY7cWWmhlsbfLh0xIfAkWWu01Wt61/tn+ecgkBK4vU7tBAFDIJKjWKTO1nl7iFctykCAIbG40slBoCV93M6ztHHbSYofEA0CFWg6ZhODEpB6YL3wQXo5eC7WQH+VANoglKCV2rV6FB27sZfQYgiDwxZ1dmHKF8LTIB/FANIGn3p3Dp//7KLZ+80Xc9/t+jDsCuPuyduy9Zwd+8fELMeUK4TdvThV8rgVvBAqZhNdAtalMWNtUxoRfFDW2REKgvUZXdqztYZufd603auSwGFWsFVoHR51YZzGgWqfERW0m+CMJ1s+RSpE4bfUVrPWdtTqsrzcUTZFNRQnkzsYGuOVjTzgpUozQ9teF0F6jBUkuzRa44PCEG85ArKydV4Az87FTKcrtppiZZZsajXD4oznJI8vhjyaQSJGCLpcsRhVkEiIvWdUTiola64F0nACHcz1lH8icvNJr5hcn8N0/DmHeG8bDH9jE2JXk0zvaoJJJ8ajIKq1EMoVDo0488GQ/tj74Ij7xq6N44dQCrl1nxn99YiveeGAndEoZHtw/WPC5MgstHmf7OoMKcilRFnECI7YAmk2avOp5ruio1WHcGeScAS0Ghm0BVGjkmZkZV/SY2ccJ0PlZ2zuqsbXNBAA4yoGsOmj1oa1Km5cQIZEQuHmzBQdGnGWXWXouYW2hdY5hirYlKDDkqjeqzshrKoSMz/ZZyNoedwQwYPWVrcc2DfMK1jZlS6DmZbPGBjKpBBvq2Qy5hGVxARSTK5ZMwZaj6XQXw3KQo0Irlc4kYdr0AtRCyxOKw8bSBiGVInH/E/1QyST45/etZ/XYz13ZAYIAfvoqM1sAtnjynVl84KdvYPu3X8aD+weRJEncf0MvDtx3Ff7w+UvxqR1tMBtVuGdnF4xqOR7cP1BwwbDgDQui0IolU7xsIIRAhtUkAmu7SquAUS0vq4WWUO+3pUoLhVTCqvE9MuFGPEliR2d6odVqgisYYz0EHEjbgvYVYGjW6lXY3lGNp9+b5+2fXwh2fxTRRArNBcgrNPOa6ZCLDokvlULLGaB82bmAJEns67diR1e1qMoeIWA2KpfVeurz2F4kNTZAsbbHHAFGvvBiWA42F2BtL6mxxSOvSCREJjOTLQasXrRVaXNm6q0En8zMn746hiGbH9983wYYVMx/H9esq8M6iwGPiqTSenfag8/+5m1c8C9/wt/873s4OefDxy5pwVNfuBQH7rsK99/Qiw0NRlzZU4vLu2vwyEsjGbVfLli9EViMKl5EKZq4NlPiIZfdH4U/khDcgohGR40wOURCIRRLYNYjjPq8u07PyoYoFEvg7akl8go95Doy4WJ13RlPCMFYsqAaG6BUWsdnFjHJYynDFFOuUOaemQtc8rFLESUALI8T4P6729s/D41Ciqt6y9NukEadUQWbL4JUioTNH0E4niyavTCw5L5yfKbw2X4xSJNXhKv1MqkEDZVqTLtz96CUzaF4tR6gFFrcan2a0MZQoWXUyNFQocZpDnECxybd+O83J/HxS1pxYauJ8eOqdErcdUkLnjk+z9vlIBsc/ii+8dRJXPytl3DHLw7j6ffmcUV3Df7jrgtx7BtX43sf2owre2pRq1fhi7u68PqwA68O2fM+J02q56PGlkoI1FeoMVMmCi0xzvUAVetjiRTmyuB90hhNv1++pPbuOj2cgRir7MeDI070mvWo0StRrVOivUbLyX1l0OpnVOtv3dyARIrE/hPFy8hew5lYW2idY5h2hTI3+HywVKhBkjgjqDQfJl1ByIocEk+jI83a5jog3Je2hLhxY/kytgHqMKKUSTIZAhPOYFEHXADV+J6a9zIafgjtsw0wY20rZBJoRGDA0KjhaEM07aYOwusZZmoA3Idcjx2ewtFJD75x87qMbRJT1Feo8aELm7Dn2IzgQaon57z40p7j8Ibj+LtruvHK31+Jvfdchs9e0ZGxnaBh1Mhx764uHBp14ZU8jW8knoQnFOflsw0styYo7ZBr1B6AQiYpOJzgAoIg0FGj5aQCEAtC+GwDVDhrR62OlQ3RwVEnFDIJtqYPhttoJhfLbI1Bqw8GlQz1DD6Du7fUY9pNZTaKiYwau8DniK1Cq1RqbIB/ZubxWS9mPeGythukYTaoMwzVcWcQcmlx+6tNTUaQJLOweKHzMgHKHkuah7WdUWOXqQ3RgNXHeMAFcM/MHFrw49FXRrB7cz2uXlfH6rF0ltaEM4i9AlujxZMpfOY3b+PIpBsf2dqE//vsJXjj/p34xs3rsKWpYtWQ42s39iEQTeCHL43kfd4FAdTYZqMKEqL0Ci0hLHnyoaNGhxk3+1xJsUD3HUIo0nrNeozZA4wXsSvJKw0VajRUqHGEQ60H8mdq0LhlM0WSfFZklVYmG7sAUZVtPnYqRWLKHSqqWohGW7UWBMHdTSCethu8uq+uaKRPrrAYVYgnSbiCscwCr6OI/dX6egNkEoJRjtYSeUXY5VK+OIFUirI5FFuhVatXwRWMsVa5DMz7YFRTSyqm6LPoWZ/rI/Ek7nuiH/VGNb58XQ+rxwLA3Ze3QyGT4NFXhFdp/cveAfzu6DS2tZnwkzvOx9tfvwY//Mh5uGZd3aosuI9d0oKWKg0e2j+Y9/5N9780iZgrqDiB0p7r48kUJpxBUZxXgKWzUbkQWCj1eUCQ90srGocZEljCsSTenvLgsq4l6+2L0u4rbBx4/JE4pt0h9FkKv4c+ix6dtbqiZmSv4UysLbTOMUy6gmhkEObOZcjVZNIUNSSeRnuNDoFogrOyYm+/FVtbK3mxQIoBgiBgSYfHkmTxbQkAYHOTEZF4KjOEzgehfbaBwuGxlM+2XFCbw5UwqGRQyCSsP2+ZTA0WQ66etF0RG69tmy+C7zx3Gpd1VeO2CxpZvUYan7uyA4DwKq3H3pqCSi7BE5/bjnt2dRUcit9xUQvaqrV4cN9gTrXoks82v+9vubC2h21+tFfzy5jIh44ysyEasfnRUKEWJGuvp07HSqF1cMSJra2VmYFHW7UW1ToFaybXoNWHPouB0X3nuvVmKKQS0f22p9JL/0Ls6jqDCgQBWBkurzNq7BKwtul6x/Xzu/f4PBRSCa5dX97kFQCZWg9QC7yWKvHuCdmwOc3aPjHHZMgVh0YhFTTEXi6VoL5ClbPWZxRaxbAhYkjsouENxzHjDrOq9VIJgR6zgdWQiyRJPPBkP/QqOf7hlnWsXiONa9fVodesxyMvjwhqV/PCKRsc/ij+9YOb8E+3bsDWVlNeq+Uesx4f3tqMx96ayruwtvrCvMkrCpkEZoMKs3ksroqBEZFC4ml01OqQIqlzXzlg2CacnXJ3nR6xZIrxezs44oRCukReASgCy5EJDysy5IDVDwmx1JvnQ32FGttaTXj6uLiKbJs/gmgiVTBKAGCXjz3vDSOWSJWk1qsVUtQb1ZwHtG+MueAJxcvebhBYcl9Z8EaW2QsXj6yqkkvRXafHibnC5BVPhrwibN1tMmlyqrF9kThSpPDXXIkavRLJFMnaNmwg7bzCZu7QZzFg3MkuM/Onr45h3BHEt96/kbHyezmqdUrceVELnn5vXlDVqDMQxXMnrbjjohb85I4LcONGS15bPaVMivuv78WwLYA9x2Zz/pzVF0GVVsF7Id1YocGMOyy6K0Y+TLmCiCdJERVa1POWC1nV4aecNLqFUGObqedgqsg+MulGLJnCpZ1LC62trSb4IglWhFf6ekzIKwRBYPfmehyZcAtOBF8DM6wttM4xTLsL2xIA7G2IJpyFszrEAh9mwojNjyGbv+ztBmmY09YEC74IQrHi2hIAS9YEzJhcccHZ0/UVakiIfDZEwl9zJQiCSFsTsBtyDVi9kEkIVgHgNOuLjbXK914YQiyZwjfft4HzYq+xUoPbLmjE/x6dOSOsmA98kTiefm8euzfXw6hmtuhUyCR44IZejDmC+N2R6aw/sxQSz1+hpVfK8LU/nMT/e/pkyRrDEXsA3SKxuABqyEU3m+WAYVuA1XciH3rMBli9EUbvze6PYMjmx47Omsy/EQSRHnIxX2ilUiSGFpjZEgDUd/qquMCREwAAIABJREFU3ho82z8vqt/5lJtSTddX5P9eyKUS1OqVmGf4PS9VSDyANGmG4KTQSqVI7DthxeXd1YzvP6WE2aiCNxxHOJbEuDOI9iIr4kxaBRor1YyUhJS9sPB1Nx9rWwybw2yo0atYq7HppRQbe2Hq5/UYXGCembm334p3phfxlet7UMUxp0AioVRa444g9glol/LYW1NoqFDjim7mdl9fuqYbSpkE33rudNb/TpIkbN4ob/IKQA0p/vAelet1cMRZkmHXiN2PSo0c1TpxPsMdNAHAXh4LrRGbHwqppKBqmAl6MpmZzGrBwVEnLmytPGPQuq3NBGcgyiqnadDqQ1u1lvGQdfeWeozaA6yVl2xAk1eY5CmzycdeihIo0dm+VsfZcnDv8XnolTJc0VNT+IdLDJpMu+CLYMwRhFYhRR1PVQpbbG6i4gQK3QeXlNHCk1XdwRj8kdW9O53RaRIxGxug1NgAu3zsRDJFZeqxIK8AVP1JpsgMqaEQrN4wfv76GG7aZMHl3dw/05+5oh0yCYEfC6jS2nNsBvEkiTsvbmb8mOs3mLG1tRLf/9NQ1r85kFZj8zzXA5R6xhmI4sZHDmLP0ZmSKJZpModYZ/tKrQImraJsFFpCkldqdEqYtIqMor0QDo1S5BXacQVYcl9hc7Zno8YGKIthgLK6XUPxsbbQOscw5SpsSwCwU2iRJIlJZxBtRba/o9FRy521vbffCoIAbihzu0EaZgPF2i6FLQFA2VfpVbKCQy6SJOEJxgRnVClkEliM6jw2ROLbEgDcbIgG5n3orNWxZhv1WZiztk/Ne/F/b8/iL7e3MmJr5sPnr+xEiiTxs9eEUWk9+fYswvEk7ry4hdXjrllXh4vaTPi3F0fgy9L40raofBtflVyK//vcJbhhgwW/OzKDq7//Gu765RG8ctrOSqbOB8GocBkTucDXtk1IJFMkxhwBQSyIAKAnzeRi0vgeSofG7ljG4gIoJtfcYhhzDMkcU+4QQrEkq+H17s0NcPijODzOLr+DDaZcITRUqhmpetgOuVpKEBIPUMu3lipuuTDvTHtg9UbOHvJKmrU9txjClCtYdPIKQIXFMyKvBGOi5Fs052Fte9JZHsXI1XCHYozzZAGq1gPs1NgAZa2yyDAzMxJP4tvPnUafxYDbLmhidZ2VuH69Gd11OvzopRFBat2oPYA3x124/aJmVveJGr0Sn7+qE38asOHNsdX3RncwhlgyxZu8AgDf/eBm3LOzC+/NLOLO/zyMa//tdTz21hRCscKZcUJhxBZAV61eNEcB2pK8XIZcI/YA2muEUZp21uogIYChhcK9scMfxekF/xmMbQAZtRYbi2Fajc0UN260QCYhRLUioi3YW0yFe342+di0iqPY1vY06Aw4tsvmWCKFP55awDXrV9udlSPqjNQiZcEbxrgziLYaraguI9mwqbEC3nA8sxzNhaXsSnHiBGay5GjR1xRbocUlH3vCGUQ0kWJNXulNL+QHGdy/AOC7fxxCigTuv76X1XVWolavwu0XNePJd+dyRjewQTJF4reHp3FxuwmdLJTGBEHg6zetgzMQyzljWEjnZfLFnRe34Nvv3wiSJHHfE/245Fsv4eHnTxdVSTNiC4Agls7fYqCcMjNH7MLZKRMEge46HWNi94ERJ85vqYBGsaRibKzUoN6oYmUxPGilrESZfgZbq7XY3Ghcsx0sEdYWWucQFkMxeMNxRvYBepUceqWMkQ2RzRdFOJ5EW4lYXGaDChqFFGMsFRUkSWJv/zwuajOxzhkqFcxGNWy+SKZoFXvIJZEQjIZcgWgCiRQpCqMqH2vbLRJTfCW4BMWzzdSgsc6ix7gjUJBVRJIkHtw3iAq1HH+9s4v1dVaiyaTB+89vwG+PTDPO0sv32h47PI1NjcaMyo8pCILAN25eB08olpVVRi/d+eZqANRA8Xsf2ow3HtiJv7umG6etPnziv45i5/dexa8OTeRkkgkF+nstVqYGsIy1XQa2gzPuEKKJlGC+4j1pr20mtoMHR1yo1MixfsV3MpOjxZDJxZbFBQC7+mqhVUjxtIi2gxR5hdlSu75CBStDG6IJZxCtJcjPotFereVMXlHIJNjVV94B8TToQ9SxSQ/iSbIkOSabGisw4w4XtODxhOKiEEmaTBq4gjEEoquXDJ5QDHqVTHSb6xq9EiQJuALMbYgGrD7U6JWs+0o2mZm/OjSJucUwvn5TH+/lskRC4J6dXRixB7D/JH+V1v8cnoJcSuDDW9kv2j61ow31RhUe3D+warmWqfUCDLlMWgW+dE03Dt2/E9/74Gao5FJ8/amTuPihl/DgvoGci1ShQGVM+NEpYq1XK6RoqOBu2yY0hm1+wWq9Si5Fa7WWkYXQG2MUeWV5pgZA9UJVWgUOM6z13nAcs54wq1pv0ipwWVc1nj0+Lxoxis6wLqTGBtjlY084Q1DLi68WotFeo0MolsQCy/PHwVEHfJHEWWE3CADVWiVkEiJNVg2UZIG4sYHKdj5e4Gy/GIqBIACDwCr3fHECdEanSWw1to76/rCJE6DjANY3sDvbt1RpoZZLGdX6E7NePPnOHD55aduqrGku+OwVHZAKpNJ6fdiBWU+YNVEVADY3VeB9W+rxiwMTWQmECz5hFFoyqQQf2daM5+69DI/ffTG2tZnws9fGcNnDr+AL//MOjk66RVdoD9v9aKxU57Vi5ItyihMYtgVQoZGjhqNzwEr0mg0YsfkL1lBnIIpBqw+Xda1WMdLuK0z/1gNWP/os7AhHu7c04OScr2x6rnMJawutcwg084aJ5SCQ9tpmoNBasiUozZCLIAi012gxztIT+PSCH2OO4FnD2AaWwmOPTnqgKYEtAUANuU5b/XkXLLQtgRiMKmqhlX3RuhiKo1JkWwKAYjmxaXqdgShsvihrFhdADblSZGHVycun7XhjzIV7d3UJZqn1has6kUyR+Plr47ye5/CEG6P2AKemFwA2NBjxF+c14FcHJ1cNmha8YRhUMk6e4rlQrVPinl1dOHT/Tjzy0fNg0irwT88O4OKHXsI/PH1StGZFSJl+LjSnbdvKoeGiP9NCKdLqjSrolbKCCy2SJHFw1IHtndWrcl16zQbolTLGQ66BeR+kEoLVElIll+K69WY8d9KKaEIc+4spV5CxtZPFqMa8t7DHfDIdEl8o+05MdNTqMOUK5g2TXolkisT+E1Zc1VMDvar87QaBpaH9obRSpdiWgwCl0AIKWwwvhoRXYwPLWdurh1yeIqqxAXY2RAPzPk61vtfCLDPTGYjiJ6+MYldv7SrVCVfcuNGCzlodfvTSKK/BeziWxBNvz+L6DRZUcxhmqORS3Hd9L07O+fCHd+fO+G8LApJXaChlUnzggkY889eX4onPXYLLu2vwy0OTuPy7r+DuXx/DoVFx7Agd/ih8kYQgGRP50FmrK4taL4b6vNesZ0ReOTDiRIVGjvX1xjP+nSAIbG01MVZoneZoJbp7Sz3mFsN4Z9rD6nFMMeUOoZGxGpu5+8qEM4CWKk3R1UI0aPIVW9vBvcetMKrlZ9hJlzMkEgJ1BhWmXCHMLYZL0l/1mPVQyiToL+C+4gnFUaGWC67Qb8pT68VSha0EF4XWwLwPCqmEtfKGyszUF1xokSSJb+4bQJVWgc9f1cHqGrlQZ1Dh9m3NeOKdWd7EjcfemkK1Tolr13FzOfpyWnH23efPtBmOxJNwB2OCZtsTBIFLOqrw849diNe+fBU+vaMNB0Yc+ODP3sTNPzqIPcfEsyMctQXQLVJWJo3OWh3cwRjrDDgxMGLzo6tWJ1jt6DHrEYwlCzqn5HJeAYCtbSY4/NGCKlSAOjMOLbBTYwPAzZssIAiInpG9htVYW2idQ5hy0z7bzJolpjZE9EKrpEOuGh1rhda+fiskBHDDhrPDbhCgGhEAeHPMibbq4tsSAMDmRiMSKTJvIyZmvkVzlQbOQHSVNUwqRWKxSAqtWr0S3nCc8TCaqwURwIy1HU+m8OD+QbRXa3EHx6VRNrRUafG+LQ34n8NTvOT5j701BYNKhlt4LI+/fF0PJBLgOysaX6tAPtvZIJdKsHtzPZ78/KV4+guX4rr1Zvz2yDSu+f5rePm0TfDrjdiFy5jIBZlUgtYqLev7pRgYsQu7wCMIAt1mfUHW9pgjAJsvmrXplUoIXNhayXjINWj1oZ1FpgaNW7bUwxdJ4LUhB6vHMcFiKAZfJMHIXhighlyReCpDRMiF+UUqJL7UtT6eJDHjYX4/Ojrpht0fPavIK/Q97c20uqAUloMbG4wgCDAacgmdqQHkZ227RbA0zobadM/FdMgVS6QwYvdzqvUGlRyNleqCQ64fvDiMUDyJB27sY32NXJBKCNyzsxNDNj+e5ZEB8OzxefgiCXyMRx+ye3M9Njca8d0/DiEcW+qxrD5h8jKzgSAIXNBiwqO3n4+DX7kKX7iyE29PeXDHLw7jwX2Dgl+vGOQVgD4bBYtmm5wL9FJNKHth6rn0mHKHzviMrARJkjg06sT2jqqsQ/htbSbMuMOMzrpc1NgAcM06M5QyiWiK7GlXCM2M1djM87EnXaGSKINpdHLIx47Ek3hhwIbr1tdBITt7RlxmowqHJ1wgSZTkdy6XSrCu3lCQvCJWXqZRLYdRLc9a6zPzBJHJqiq5FHqVjNVC69S8D91mHSelOBUn4M9LmHhhwIbDE278zTXdMAhIxvrsFR2QSAj88KURzs8x4w7h5SE7PrqtifN3raFCjU9f1oan3pvHezNLnz1aQVonIHllOZpMGjxwYx/e+uouPPQXGxFPpnDf7/vxwZ+9KfhSK55MYdwZEFWNDZRPnABJkhixBwTtbejssUIElkOjThjVcmxoMK76bxexyNGadAURiadY1/o6gwoXt1XhmePzJcllPZdx9lT7NfDGVHrxxFShxdSGaNIVhEImQb2ATAq2aK/WYW4xnPdgsxy03eD2jmrOYdqlAH2QdwZiJRlwAchYxp2Yyz3k8ogUHAssZ3KdeSDzReJIkeKzuADKhghgPuQa4MjsBKjvq0YhzRsq/fiRaYw7gvjqjX2CWzD97TVdIAH86wtDnB5v90fw/MkF3HZBEy+5vcWoxmcua8fefivenlpiulK2BOLfezY3VeD7H96CQ/fvRI/ZgC/tOc44d4gpRmzCZUzkA2VNUPqF1rDNj4YKNXQCqut60qztfM3kgZHcLC4A2NZWhVF7AC4GOXmDHK1Ed3RWo1qnwP8cnmb92EKYdLEjr2SGXAU+z5OutBqbZz4fH9DDHjYL2X39VqjkEuzsPTvsBgFAo5DBoJLBGaDyqYqhRloJvUqO9mpt3oVWMkXCF4kXXaG1GIrDJHJ+FrBU65kqskfsfsSTJKdaDxTOzByx+fHbw9O486JmdAqs7rllUz3WWQx4+PkhzkOd37w1he46Hba2VnJ+HRIJga/fvA4Lvgj+48CSOnzBG4ZMQojes1uMavz9dT144/6d+Oi2Zvzi4AT+eGpB0GsImTGRDx21WoTj7G3bhIYYC7xesx4kufS7zIYxRxBWbySnWodNWPyg1Q+TVsHaGUOnlOHa9WY8/d6c4LbVJEli0hVEKwvyClBYoRVPpjDjDpW01tfoldApZaxq/evDDgSiCdx0FpFXAGqh5Uzb2oqZs5MPmxsrcHLOh2Se5fdiKC5abmWuOAFPKA6ZhBD0nJALNXolYzU2SZJUlADHWr/Oooc3HM/5XYwlUvjW/kF01urwUQ72vflgNqrwie2teOKd2Qzhli0ePzINAsBHtzXzei2fu7IT1ToFHtw3kDm30b8TMcgry6FRyHD7Rc34499cjh98eAtOzHnx0H5hCSxTrhDiSVJ0hVYHBwKAGHD4o/CG44Kqz2kiTD6yKkmSODiSm7zSUaODSatglKM1yGNm9xfnNWDCGcyaA7sG8bC20DqHMOUOoc6gZDxUthjVcAVjBQ+2E06qmV5p3VRMdNRqM6+FCU7N+zDpCp01Hts0lhf3UlgQ0a+hWqfE8ZncQy7a81rMIdfKxjdjS1AMy0EDuyHXwLwPDRVqTr8PSQFrAm84jn/70zAuaa8SJR+msVKDT17ahj+8O4eTeZaYubDn6AwSKRJ3XMyv6QWAv7qiAzV6Jb65ovG1iMTiyoZavQo/vv08xBIpfPHxd1lZnxXCiN0v+JAyG3rMekw4g/j1m5MlZRGN2AKCD/R66qhDYr7v5qFRJ1qqNDn96Le1UcPYo5P5LYIWQzHMeyOsWVwAxYj9xKVteG3Ywel7lQ9T6cUTG4UWgIIElkxIfAlZ2x3pfIlxJ7NDWyKZwnMnrdjVWyeoLWkxQNutlKrWA9SQKx9r2xuOgyTFIa8Y1XLoVbKcCq2ikFfSyxOmmZn0cGhlNh9T9KXvzbn67of2D0KrlOHeq7s5PX8+SCQEvn5TH+YWw/j1m5OsH398ZhEn5ry48+IW3u4BW1tNuGGDGT97bQz29DLG6o2gzqAS3O4qF1RyKf5x9zpsaDDgy/93HLMe4XK1hm0BGNXCZUzkQq+ZGqI9/PzpVa4GxcSITXj1ORPWdj4LIoBaIOuUMmYLrQUf60wNGndf1gZfJCE4gWUxFIc/kmBMVGWajz3rCSORIkuqxiYIAh0s4wT29ltRqZFje0eViK9MeCw/w5Tqd76p0YhwPInRPAtEsRRaAHW2z2ovHIyhUqsoiiNNLYt8bJsvCncwtsrKlCl60+eG0wvZz/aPvTWFSVcIX7upTxSS4+ev6oRRLcdD+wdZnwNjiRT2HJvBzt66DCGOK3RKGb50TQ+OTnrw/EmKOLIgYF4mExAEgfed14BP72jDr9+cwnMn+GeJ0hixFYe80lCphlYhxa8OTWbOaqUATV7pFpC8olfJ0VChzlvrJ5xBzHsjOW24KYvhSobkFR9kLKMEaOzeUo8avRI/fpV/Rt0amGNtoXUOYdoVQouJeaNED7kWCjC5qIVW6ZpegNqiEwRw7+/excE0+z4fnu2fh0xC4PqzyG4QAKp0VHgsULqhIkEQ2NRozDvkWvK8Lp4N0ZIqrBiWg+xsiAY4qjho0KztbE3nj18ZxWI4jq/d1Cdaw//5qzpQoZbjwX3sGt9kisTjR2awvaNKENahVinD31/bjXenF7HvhBWxRArOQLRoTS+N9hodHvqLjTg66cEPXuRu2bAcoRiVMSFkE5gLn7y0DZd31+D/PX0Kn3vsHXjDwrKGmSCZIjHmCAiaqQFQyzqAykjMhngyhbfG3TkHXACwsaECSpmkYONLqya5LLQA4GOXtECvlOEnAje+0yzzMukDaSHF4bgzCI1CmskVKgWMGjmaTGo8+vIo/vuNyYIL5cMTbjgDsbOOvAIsHeZLpcYGgI2NRtj90Zx9oJj5FgRB5GRtL4aoIZfYUMgkqNTI4QgwY20PWH3QKKSM1ZErkS8z8/VhB14ZcuCenZ2iKfa2d1bjqp4a/OjlUXhYZjE89tYUNAop/uK8BkFey/039CKeTOF7LwwDoM4ixa71SpkUj370fKRI4IuPv4u4QASWUbsf3XXCZUzkwvnNlfjizk48fXweux89lHN4KjZG7MKrz1uqtFDKJHmHXAdGnGg2adCcg9whlRC4oKWwxXAimcLQgh99Zm61flNjBS7rqsYvDkwIamnFNkoAYJaPPVkGUQIAsL7BiEOjTnzjqZMF70fhWBIvDtpw/QaL4E4VYoO+r5kNqpIRb2j3leN5zvYeEa1+m0wazHrCqxRinlAMpiKc6wHqbO9g4MwAAANWiojG9WxPkw2yua8shmL44UsjuKyrGld2i5MFZ1TL8cWdXTg46sRrw+ysz58/tQBnIIY7BSCqAsCHLmxEd50O337+NKKJZEahJWReJhPcd30vNjcacd8T/bzzxWjQ1vpik1WlEgKPfPQ8zC+GcfOPDuLZ46XJcaIV00JbLBbKzDyYJq9c1pX7bL+11YRpd6jgXHvQ6kdHjQ5KGXtXIZVcirsva8OhURfeFSk3cw2rcXZV/DXwwqQryJixDTCzIUqmSEy7ShsSD1ADn1/cdSGiiRTu/M/D+KvfHMtZjEiSxL5+K3Z0VRclg0FISCVEZphYKlsCgGJyjToCCESzMz49oTgIgmqYhEalRg6dUrbq7+spUnAsQH03pBICP3l1rGDTE44lMe4IcLYlAKghly+SWHUInXaF8F+HJnHb+Y1ZPYOFgkElx727uvDmuAuvDNkZP+6V03bMLYZ55WmsxG0XNKHXrMe3nzuNWU8IJCm+LUE2vO+8Bnzowkb8+NVRHBjhn4M0Zg+CJCH4gicbjBo5fvnxrfjqjb14cdCGmx45UPTGa9odQjSREjxDpCfD2s4+uHtvZhGBaCLvQkshk+C85oqCQ66lTA1u78GgkuOu7S147uRCXlYsW0y6QjAbVIxzvarTRAkmQ66WqtJkNy7Hr/5yGzY1VuAfnjmFmx45iDfGcpNY9vbPQ6OQ4qqzyG6QBn2YL6UirtCQazGTbyEea3vlQiuaSCIYS4pCmMn1Gp47sYDXGQx9Ts370GvWc1YR5crMTKZIPLhvEE0mNT6+vZXTczPFAzf2IRhN4JGXmZM1vKE4nu2fx61bGqAXKOujpUqLj1/Sij1vz2Bg3leShRYAtFZr8dD7N+Kd6cXMco0PSJLEsC2ATpEtiABqKfyla3vw2KcuwmIojlsfPYTHj0wXXZk9bPMLXuulaQZ1LhsiirziysnYprGtzYRhWyDvwmTSFUQ0wT5TYzm+cFUnnIEo9hyb4fwcKzGVsQFmfrZnko9Nu520lvhsf/8Nvbjrklb89sg0rvreq/jNW1M5LfFeGbIjFEvilrOavFJCO+dqLXRKWV6yqlh5mQBVZ2PJVCY/KXPNoHg2h9lew4w7hJ+9NlYwd/DUHFWj6cUUW+hVFDlrIIv7yiMvjcIfEZeoCgB3XtyClioNHto/yMpt5LG3ptBs0uDyLmGWbTKpBF+7aR2mXCH85s0pLHjDMKhkRV/uKmQSPHr7+QCAv378XcQS/AkswzY/GivV0CjEfy+7+uqw/97L0F2nwz2Pv4sHnjwheCZYIQzbAqjQCK8+7zbrMeYI5PybHBhxorFSnZfIeVEbpdwtZDs4MO/jfK4HgNsvaoFRLcdPXh3j/BxrYIe1hdY5gnAsCbs/ymqhxcSGaH4xjFiytCHxNHb11eGFv70cX76uB68PO7Hr+6/h+y8MrcrVOj7rxawnjJs2nn1NL7DU+Jbyd765sQIkiZxWWYuhGAwquSgyeYIg0JRlyEUHxxYja8SkVeCHH9mCcXsAN/zwAJ56dy7nz55e8CFFcmdxAZTXNgAMrvC6/s7zpyGVEPj763o4PzdT3H5RC9qqtXho/2nGje9jh6dQq1fi6nV1gr0OqYTA129ah1lPGN967jSA4tkSrMQ/7l6Pzhod/vZ/32Psu54LS5ka4g+5AMpe6jOXd2DPZy8BSQIf/Nmb+I/Xx4sWHk/bMAitSKvUKlCrV2JoIfuC6OCIEwQBbO8oNOSqwql5b97Mi0GrD9U6RUaxyQWfvLQNSpkEP3tNuMZ32h3MyUjPBqmEQJ1BVdCGaNIVKqn9HY3OWh1+86lt+PnHLkAwlsDt/3EYn/+ft1dZgsWTKTx/cgFX99UxXu6VEzJDrurSkVfW1xsgkxA5h1xi5mUC1IBp1h0+4760SF+zSLliD9+2GSatAnf98gi+uXcA0UT2AQFJkhic56fGbjZpoM2Smbnn2AyGbH7cf/3/Z+++49uq7v6Bf44ky7I8JO89E68MZzsJZJKQhBAI0BYoo0ChwANllofdX0tb2lJauoBSCoW2bPpAW5owwgwJJCGBJGTaTjzjvW15yLbO7w8Ny7Fsy9q2P+/X677iSPLVtXOie+8535HvUtToeOTEh+OSRWn4x+flTpfx/ueXVejpM3ksYtvqlrOyoQsJwsNbj6C23bflhe2dPycJ3y5Mw1OfnMDH4wjqcaSh09JjwssliOydOT0Gb9+2HIsyonDfG1/j1lf2e7yf00gMvZbscy8E6+TGR4wYtX2wyhy8MlrENjDYR2u0AJYjbmZjA+am9AvTI/HnT056LNOv3JKNPVL5ZEec6Y9d2mhAuEaFaD/0brQXoQnCj8+fia23Lkd+QgR++K9DOPcPn2LXyeH9SbYcrEFMmNr27zmRJAbAgpZCITArOWLEnpk9fQPo7hvwavAK4Kj6itFnPUS/tyIL62cm4JdvH8MVz+4eNZPjSE070qO1bgVw5CcM75lpLQd/yaJU5LmYEeostUqBezfkoaiuE//cV+XU9xTVdWBPaTMuW5zm0VYjK3NisSInFn/4oBhHaztsJbd9LTVKi0e+UYADla149N1jbu+vpL7TJ5VXrFIitXj1hqW4ceU0vLynAhc8sRMlo/SZ9LTiug7kxLlWmnc0eQnh6DdJh9ek/QMm7DrRhOXZMaO+b35iOELVSnwxSvWVFoMRte2utRKwCgtW4ZozM7DtSN2oWWXkOVzQmiKsFwhp4ylLoBu7DFGgRHFZaYKUuHn1dHx410qcMysBf/iwBGt+8zHeOlBti0j874FqqJUKrJs5scoNWqVGaZGsD/FrP5CCFHM20GiTXN6Mnk6LChlxQctXkVybCpKw9bblyEsIx+2v7sftr3yFdgcTBNboK1d7agBAbsLwqO29Zc3Y8nUNbliZhXgfTPKoVQrcsyEPJfWdeNWJCNPK5i58UtSASwvTPF7+Y1l2DM7Ki8O2I3UA4LcLX61ahScun4/O3n7c/sr+UZspj6WorhNBSjGuoANPmJ8Wia23Lsea/Dg8vPUorvv7XlsZMW/yZhmG3IRwHK9znKG1o6QRBck66Mb4nCjMiIJJAl9WjBytau6p4d4NZ3RYML5dmIZ/fXXKYz1aypu6xt2rJGmMMkR9AyZUNHchI8a343MkQgisn5mA9+9ciR+cnYMPj9VjzW8+wW+3FdmCWD470YSWrr4JWW4QGJyk9EVfvZFogpRZbMM6AAAgAElEQVTIiQ8fcZLLet71VmZ0qjVq2y5gwJtlDh3JTQjHf76/DFcuScczO0px4ROfOZwgqGrpRkdvv8s9NYDBnpn2Ududvf34zXtFWJAeiY2zfXPdesfZ2VCrFPjVO2NP6Egp8eLucsxL07v1szui05qzw3eWNKHLOOC34BUA+NF5M5AbH447XzswLItgPIotPSayfZChZS82PBh//24h/nd9LrYcrMamP+7weP9GR6zZx97oIZKbEIb6jl6H2VWfWoJXlmaN3k+pIEUH9Rglho/WtCNIKdz6LBZC4ObV03GqtXvUILjxKB9nNjbgXH/ssiYDMmP8n41tlZsQjpe+txh/unw+Onr6cenTu/D9l75EtSUIx9Dbjw+O1eGcWYleCaT0tmS9+Vzv68+E081J0eNoTbvDoI1WL5f1H21By1fVdHQhQXjy8vl45Buz8VVFKzb8frutr9PpjtS0u3VfD5gXyMsaDUMCr3/59lEEqxS442zP98l0ZMOsBCxIj8RvthXBMELVHXsv7iqHWqnAtxakePxYHtiYj87efuwpbfbruX7j7ERcuSQdf/m0FB8crXN5P/0DJpxsMPik8oq9IKUC956Th+evWYT6jl6c98edTi9YusOcfd7h8XKDwGDwq6OyyQeq2tDR2z9mNrZKqcCCjKgxz/WAe8ErAHD1GRnQqpUebylAjk28sz65pMzaJH4ck1whaiUitUGjTnJZ9xsIGVr2EnUh+P2l8/D6jUuh16pxy8tf4ZKnd+FwdRu2fF2DFTkxXimH5wt3b8jD099Z4NdjiA4LRrI+BAdGmORq9fIFqLUsgH3UdktXH4KUAmE+XOhLjdLileuX4I61OXjrYA02/v5T7CsfeqI8Ut2OCI0KyW40Tg0LViEtSmvrC2QySfx0y1HERwTj+hVZbv0M47F+ZjwWZUTit9uKRyw3afXi7goohMC3C1O9ciz3b8yzlXXy54VvTnw4Hjp/Jj470YQnP3L9wqWkvgNZMWF+qf2v0wbhqSsW4KHzZ2JHcSM2/v5TpxqnuqOorgPJ+hCv/H/NjQ9HcV3nsAXGjp4+7K9sxbIxIrYBYH66HiqFwJ7S4ZHAgHmBp6i20+2LXgD43vIsCAE8vf2k2/vqMvaPOxsbGLsMkbW3gb/7ZZ5OE6TELWuy8eEPVuHsGfH4/QfFWPvYJ9j6dQ3+e6Aa4cEqrMz1Tg8CbztvTiL+/t1Cvy5oAcCcVB0OVrU5LFPW6uVAEtskV9PgJJe3F9EcCVEr8dMLZuEv31mI2vYebPrjDrywq3zI7+SwJYPanfLCgLlZ/DG7nplPfXwCjZ29eNDL5YfsxYVrcOPKaXj7UC32jlGe5fMTTTjZYMAViz1XWtje5ZbscMB/wSuA+bPmicvnods4gFtf/srlAJbB7GTf/79WKMyLKq9cvxS9fSZc9ORneH5nqVdLEBbbFrQ8P1lvDfZyVHZwZ0kjZifrxswoCVYpMTdVP2oZoiPV7ZgWGwa1yr3rs1W5schPjMCfPjnhVgCUVXnT+LKxAef6YwdCb+zTCSFwzuxEvH/nSty+NhvbjtThrN98jD98UIytX9egp880YYNXEnQavHDtYly80Dv3S84qSNGjb0DimIO+ToPnXe+c6xP1GigVYkgZfyklWrr6EBXqu/kaIQQuWZSGLbcuQ2qkFje+sA/3vXEQXcbBe96Onj6UN3W5fa7PTwwf0jNz18kmvHu4Dv+zappblR/GQwiB+zfmo6Gjd8x7EENvP9748hQ2zk5AtIdLygHmhetLFpmzvP3RSsDeA+fmIz8xAj94/cCYJVpHUt7cBeOA50vrO2tVbhzevm05ClJ0uOv1A7jztf1OLVq6qqGjF+09/V7Jxp4WGwaVQjjsL7uzxLnKKwBQmBGJ43UdI5YYPuKhBS29Vo0rlqTjrQPVttLA5D1uXZkJIb4lhDgshDAJIRae9tx9QogSIcRxIcR69w6T3GWdDBjvBWqiLmTUMkSlAdAkfjSLMqLw1i3L8PCFs1Bc14Fz/7ADNW092FSQ5O9Dc1myPsTjUbCumJOqw9ejRG17N0NLi95+05DmrS0GIyK1ap9HFKqUCty2Nhuv3bAUAHDxn3fhd+8X2cryHbaUIHL3uPITw22RI28drMaBylbctS7XJ3WZrawXvo2dvXh6lBJpvf0DeG1vJdbkxXltAmp6XDiuWpqBhAgNIjT+y1YEgIsXpmLz3CT89v0i7HZQCsUZRXWdXolqcpYQAledkYE3bjoDmiAFLn36czz+YbFHJl0cKarr9ErENmCutd3bbxp2EbnrZDMGTHLMKC7AnH03M1k34sLeyQYDjAMmt+psWyXpQ3DRvBS88kWl26UrK1xoEg+YJxNq23pGLDlpbRLvz5I4o0nSh+Dxy+bjleuXIFyjwk0vfonX91Xh7JnxXi/R5i3BKiVWeKkh+HgUpOjR1t03LHIaMAeSqBTeCyRxFLXdYjBHivuqDJG9s2fE4x1L6bYH/3UI1/9jny1j7Eh1GxTCPCnjDvuemdWt3fjLpydx/pwkzEuL9MSP4LTrlmciPiIYP9tydNQFjxd2l0OvDcK5XppMVqsUePDcfCgVwi+LQPamx4XjpxfMwu7SZvzhA+d7jNkrqu9EhEaFWD/eNxVmRmHrbcuxLDsGP37rCG74xz60dXmnBGFxXQfUSsW4s4adMdgzc+gkV2dvP76qaHXqXA+YywEerm4fMVDraE2725PXgDVLaxpONhjw7mHHmR/jUd7cNa7+WcDY/bF7+gZwqrU74AJVrULUSty+Ngcf/GAl1uTF47FtRfjffx5EXHgwFmVMvHKDVsuyYxCi9u+1iq36ioPMzcEqKN457wYpFUjSa4ac69t7+jFgkj4NXrHKig3D//3PGbhhZRZe+aJySEartSSwO+WFgaE9M00miZ9tOYIknQbXLfddoCoALEiPxLmzE/H09pOjZh//50A1Onr7ceVS7wSvAMCdZ+cgUhvk0zJ9jmiClHjisnkw9ptw68tfjavHmJU1eMXXGVr24iM0eOl7S3Dbmmy8+dUpnPf4jmFlLj2lyJJ97o1/O7VKgcyYUIcl/HYUN2JmUoRT9wSFlj5ae8sd9w0/WtOBmLBgj1yfXbcsEyqlAk994n6wKo3O3VDwQwAuArDd/kEhxAwAlwKYCWADgCeFEBNzRmGSKG82QBcSNGaZpdMl6TWocSKKK1DKEjiiVAhcvjgdH9+1GlefkYGCFJ1He/pMVbOT9aho7nIY5dBi6PPqBWiqg0muZsuClr8sSI/E1tuW47yCRPzu/WJc+vQulDcZcKy2HTMS3V+AzE+MQGmTAS0GI371znHMTIrAN+Z7PuV/LPPSInHenCQ8/enJESM83zlUi2aDEVcs8d5FLwD8cFM+Prprld8/f4QQePjC2UiL0uK2V/aPu2Rft3EAlS1dyPFzuREAmJWsw1u3LMO5BUn49XtFWPnoR7j2+S/w861H8eoXFfiirNntkoQDJokTDZ1eu8i3Nmk+PZJrZ0kjNEEKLEh3bmJ4cWYUDlS2OSzN46myBFY3rpqG/gETnt1R6tZ+rD01xpuhlaQLQd+ARKOh1+HzJ63lhQMsavt0S7Ki8d9bluGnF8zCtNhQr38GTQWzk83nL0cZ2S0Gcza2tz6Dk/QhUAgMidpu9nKk+FjiIjT42zWFePDcfHxyvAEbfrcdO4obcaTGnMXhbr82+56Zj757HBLA3Ru83yfzdFq1Cj9Yl4v9la3Y8nWNw9fUt/fgvcN1uHhhqlf71K3Jj8fXP17nt0hne99ckIKL5ifjDx8W47MTjeP+/pI6c08Nf1+3RIWq8exVC/Hgufn48Fg9Vjz6ES77yy48+K+v8dzOUmwvakBVS5fbfTWL6jqQFRvqlVJw8RHB0IUEDcvQ2n2yCf0mieVOLmgtyojCgEniSweTXE2dvajv6PXYuf6cWYnIignFEx+VuJUZ12XsR0NH7/iDV8boj13Z3AUpA6/yyulSIrV44vL5eOl7izE/TY/rlmd6tKfPVJQSGYKoUDUOVg4vtW0NJIn0YrZU2mn9sVv9kI1tT61S4L5z8vHitYth6O3HhU/uxNPbT9gWtty9t0+NtPbMbMe/9p/CoVPtuHtDnl96vt69IRf9JhMee6/I4fNSSrywqxx5CeGY78XgmtjwYHx27xpcc2aG197DWVmxYfj5hbPxRVkLfu9CAIu1vLC/qywoFQJ3nJ2DF69djI6efmx+fCcueGIn7nxtP574qATvHKpFcV0HjP3u9Xa03nN7KzjX3E5g6Lne0NuPLytasGy6c8F/BSk6qJWKEauvHK1p90igKmC+V7h4YQr+b1/VqBnR5D63QiqllEcBOLoo3wzgFSllL4BSIUQJgEIAn7vzfuS68qYul3qzJOpCRi09VdZoCIhsIWfotObmsuQZc+wiuVaeFkXu7ZrX9mWIrBF5rV19Xr3QdkaEJgi/u3QeVuXG4cF/HcL6321HT5/J7TrbgHniXErg3jcO4lRrNx79VoHfbt7uXp+Ldw/V4jfvHcej35oz7PkXdpUjI1qLZU5OJrhKCOH3iEarsGAVHr9sPi568jPc9foBPPOdhU7/+5xo6ISU3ukx4YpwTRD+cOlcnJUXi/cO1+FkgwGfFjfCaBehptcGYVpsGKbFhmJabBguXpjqdLPoiuYuGPu9V4YhOy4cQgDHajuwYdZg1sCnxQ0ozIx2OmOnMCMKT28/iQOVrVh8Wh+OozXtUCsVmBbrmX+zzJhQnFuQhBc+L8dNK6ePO/jEqtxWXtj1SS5HpU7KLE3i/ZEVM14qpQJXLknHlVzM8ojchHAEqxQ4WNmK8+cMzW73dja2WqVAom5oz8xWg3cjxZ2hUAhctzwLS6dF49aXv8IVz+6GWqXAxlnu97iyllF7dW8lth2pw02rpiEl0j+9674xPwV/3VGKR945hrNnDM92fOWLSvSbJC4rTPP6sfgyG30sP908C/srW3H7K/ux9bbliHGy/JKUEkX1HTjHA+PEE4Qwj+NFGVH4++flONHQiX/vr0ZHz2CmkiZIgcwY87k+KzYM58xKGNfiTnF9p9eyC4Uw95w7PWr70+JGBKsUmO9k8Mr89EgoFQJflDUPy4r1VDaGlVIhcOOqabj7nwfxcVEDVufGubQfa/BK2jgz38bqjx1ovbHHcsa0GLxxk3fvNaYKIQQKUnQOe2b6otRvWpTW1hsZsOuX6ed7+zOmx+Cd21bg3jcO4udbj0ETpEB0qBrxEe5lcSgUAnmJEfiqshXvHq7DnBTdsGssX0mPDsV3lmbgrztLcc2yDOQlDP2821/ZisPV7fjZBbO8HowRKPf1AHDBvGR8dqIRj39UgsWZ0U6VrLcqqu/0e897e2dMj8Hbty3HEx+V4FhNB3aWNOKNLwf7OSoVAqmRIeZ7+7gwFGZEjSsBoLi+E3ptEGK9UI4SMAer/vdgDTp7+21VIXaXmoNXnJ1v0gRZSwwPD17pGzChpL4Ty3MyPHbMN6yYhpf3VOIvn57EDzfN8Nh+aShvNetIBlBp9/cqy2PDCCGuF0LsFULsbWho8NLhkHlBa/wXp4l6Ddp7+h3WXO0bMKGyJXDLEpB3zbIuaJ0WydXbP4Au44BXa14nR4ZAiNMytLr8m6Fl74J5yXj7tuWYkRgBIYA5qXq392ktd/Lu4TqszY93qlawt6RGaXHVGen455dVOFI9NHX9WG07vihrweWL06dctOSsZB0e3GSOdh5Ppk1xvf96aoxECIEL56XgT1cswLt3rMDRn27A9v9djeeuXoQHz803N99WCHx4rAG/ePsY7nxtv9P7LrL1EPHOglaIWon0KO2QDK2atm6caDA4HbENAAszzJNhXzjorXGkph3Z8Z7teXbTqmkwGAfwt8/LXN5HeVMX9FpXsrFHn+QqazIgK4CaxJPvBCkVmJEUMcIkV5/TC9muOj1qu7nLiLBgldv9bDxhZpIO/71lOS5fnAZjv8npCfTRhAWrkB5tntiLCVPjf1ZN88CRukapMJcZrmzuxj8+Lx/yXP+ACS/trsDy7JgJM/ntKaHBKjxx2Xy0dvfhztcOOJ3F1NhpRGtXH7IDIBvb3pxUPX5z8Rz86+YzcfBH67DngTV45folePjCWbh8cTriI4JxsKoNf/ywGJf9ZRfaup0rT2jo7UdVS7dXempY5caHo6i2Y0i2086SRhRmRjmd6RAWrMLMpAjsdhDA6elsbAC4YG4yknQat/qulrvYSmCs/tjWBa3MAM/GJu8oSNGjuL5jSM8owPv9MgHzvWVjp9E25+SPfpkjiQxV46krFuAXF82GgMC8tEiPXA/nJ4bjYFUbatt78OCmGX69b77lrOkID1bhF1uPDXvuH7vKEapW4oJ5DqdzJ7Ufnz8T02PDcPur+8dVFr64riOg7usBICYsGD86byZevn4Jdt+/Fl//eB3+8/0z8dtL5uCmVdMwIykCp1q78fxnZbju73vHlYVeXNeBnDjvZZ9b5wyK7e7tdxQ3IVilsN2vO2NRZiQOnWobNrd9oqETxgGTR8oLW6VGabF5ThJe2l3hdnUbGtmYd4NCiPeFEIccbJtH+zYHjzm82pdSPi2lXCilXBgb6/9eAZNR34AJp1q7XapfnjRKJFdlc5e5SfwUu5ElswhNELJiQ4eVIWq11OH3ZvR0sEqJxAjNkDJErV1Gr0+sjUdqlBav3bAUH/1glUfSzZP1IQgLVkGlELhvY54HjtA931+djQhNEH7x9tEhj7+wqxxqlQLfXOD7coiB4Mol6dgwMwGPvHMMX1U4rtF8uqK6TgQphUtBB76iVAikRWuxOi8O1y3Pwi8umo1Xb1iKvQ+uxX3n5OGj4w34rMS5C9+Seu+XYchNCMexWvuLXvOxOdtTAzB/huUlhI8wydXh0QkuwDxhtjY/Dn/dWepy496K5i6XzvXWDK3qEcoQnWww8Fw/hc1J0eNQdduwnnqtXs7QAqwLWoPXoIGQjW0vRK3EwxfOxkd3rfJYppK1bOodZ+cgXOPfn3VFTixW5MTijx+W2CY1AeCDY/Wobe+ZsmU98xMj8KPzZmB7UQP+vN25Hgm2nhoBNsllTwiBuHANlmRF4/LF6fjhphl4/ppCbL97Nd76/jK0dvfhTx+P3EPVnvVc781SkbkJ4ejo7bct0NS29aC4vnPcFQIKM6Kwv7IVvf1DSwwfrWlHfESwR7OT1SoFblg5DV+UtYxaBWU0Fc3mhac0F6uvjNQfu6zJgKhQtctZ4jSxFSTrYJLAoVNDgxVbuvoQqlZ6tSepNduwssV8b+/PfpmOCCHw7cI0fHrPavz6WwUe2ac1E+qcWQl+7wGn16px65psfFLUgO1Fg0kGLQYj/nuwBhfOT/Zav9RAplWr8MTl89HZ24c7Xt3vVG/p/gETTjYYAqJM8mjCNUEoSNHjwnkp+MG6XDx5+QK8c/sKHPzROiTrQ/DzrUedCtiRUqKorsOr1zbW/yv2Gdk7ShqwKMP54BXA3EdrwCTxVcXQgHxvBK8AwE2rp6GnfwDP7XSvpQCNbMwFLSnlWinlLAfbv0f5tioAqXZ/TwFQ7e7BkmtOtXRjwCRdvOgdeZKrzFLaKDPGP6VQyP/mpOhxsGroCcFXEVWpdlHbUkpzpHiA3YCplAqPTQIrFAKXLU7DD9bleqzMmTt02iDcuiYbnxY34hPLhW9nbz/e/PIUNhUkBtTioi8JIfDINwuQoNPgxhf2DbkpGElxXScyY0I9mu3jS1edkYFkfQgedvLCt6iuw7ZA6y258eEoazTY+l/tLGlETJjaNlHsrEUZUfiyvGVIQ+CGjl40dnqup4a9m1ZPR2tXH17eU+HS95c1GZDmwsJoVKgawSqFw+CVnr4BVLd1B3z/LPKeghQduowDtglqK/N518sZWtFaNHb22iLG/d0vcySZMZ7rE7R5bjI2zk7AJQtTx36xD9y/MQ8dPX14/MPBjJIXdpUjUafBmjzXSqZNBpcVpuHcgkT8+r3j+Mv2k2M2ji+u917TdF+YlazDhXOT8dedpTg1woKIvWLbgpZ3g1cAoMgyybXTElgzntJQALAoMwrGftOwTNQjNe1eOddfsigVMWFqPO5illaZNRs7ZPz3PaP1xzb3xuZ9/VRVkGqpvuLg3t7bZX7t2wlY3xPwb3lhR2LCgj12TCtzYlGYGYX7N+Z7ZH/uunJpOlKjzAsZ1oWbf+6rgrHfNGWDVwDzOfuh82diZ0kT7nxtv8P+8fYqmrtgHDB5rVe0t2mClLhrfQ4OnWrHfw6MPYXf0NGL9p5+r/68KZEh0KqVtj5a9e09KKrrHPe5fn6aHgqBYX20jtZ0QK1SIMvDwZvT48KxfkYCnv+sDB09zmW30/h4a/bsPwAuFUIECyEyAWQD2OOl96IxlDe7VpYAGL0MUWmjeb+ZMRPzw5rcV5CiQ31HL+raB2+MbI1jfRK1bR6D7T39GDDJgJzk8qT7N+b7tfzQ6a5cko70aC1+vsV84fuvr07BYByY0he9AKALCcJfvrMQocEqfOeve3DHq/vR1Nk74uuL6zsCrgTReGiClPjf9bk4XN2Ofx84Nebri+o6vR6hnpsQAZM0R4hLKbGjpAlnTIsZdzmPwswoGIwDOFIzGK06GMXl+X+z+WmRWJoVjae3nxwWKT6WvgETqlt7XJqMEkIgSR/isAyRtUl8ViwXtKaqghRz2Vz7SS4pJVp9MMmVao3atmRptQZQeWFv2Tg7EU9evsBjC2TuykuIwLcWpOJvn5ehoqkLZY3mvoqXLkoLmGP0ByEEfnnRbKzOjcXDW4/iwic/w6FTw0tzWhXVdSBco0JcuHd6TPjCnetyAAC/eff4mK8truuAWqlwKWvYWdbFQWtG9o6SRkSHqpGfML5FKGt2hH3GlLHfhBMNnV5Z0NIEKfHdZZnYXtSArx2Ucx1LhYutBABzhlb1CAuSpY0G3tdPYXHhGiTqNMMWdn2RGW1b0GoeXNBSKgQiNJM3K8hazSXVi5+R4xGsUuLu9Xk4VtuB//uyCiaTxIu7y7EwPXJYX62p5uKFqbh9bTa2HKzB2sc+wb/3nxpS6tZeUZ33s5O9bfOcZMxMisCj7x63BYeOxPrzejNYR6EQyI4f7Jm5wxq8Ms5s7HBNEGYm6bDntHYCR6rbkRMf5pVr2ptXT0dHTz9e2OVasCqNzq1/MSHEhUKIKgBLAWwRQrwLAFLKwwBeA3AEwDsAbpZSjm9mhjymwtok3oVJrgSdBkI4ztAqbexEhEYVcFkx5DsFlj5aB+z6aPkqoiotSov6jl50GwdskTKTfZIr0KhVCtyzIQ/H6zrw+t5KvLCrHDMSIzDPAz3DJrr8xAhsvXU5bl2Tjf8erMaaxz7BP/dVDbv47ekbQEVzV0CXIHLG+XOSMCs5Ar9+t2jUC98Bk8SJhk6vR6jnJph/n8drO3C8rgONnb3jjuICzAtawNBJLuvilifrbNu7efV01Hf04v/2jb04aM+Wje3ijXGiTuOwDNFJa5N4ZmhNWVkxoQgLVg2Z5Ors7UffgPRJ8AowOMnV7IMyhzTcnetyoFIo8Mi7x/DSngqoFAKXFgZGBpk/hWvMASxPXDYfNW092PzETvx869FhPWgAc8ZSTrz3ekz4QkqkFtecmYE3958adfEOMC/gZcV6LnPREV1IEBJ1GhyvbbcErzTijOnjD16JClUjJz5syLm+uL4DfQPSKwtaAHDFknSEa1R48uPxZ2mVNxtcXigcqT92l7Efde29rLwyxRWk6IZlaPkiM1oXEoRwjcrWTqDZYK68MpE/LyeiTQWJmJuqx2/eO473j9ahrKkLVy6d2oGqgDmA5fa1OXjrlmVIidLitlf24+rnvhjS/sKqxNIb25ul9b1NYemheqq1G3/7rGzU1xbZyil7+d4+PmzIglakNsile/HCzCh8VTFYYlhKiaM17eMOhHHW7BQdVuTE4tkdJ8dcHKTxc+sKU0r5ppQyRUoZLKWMl1Kut3vuYSnlNCllrpTybfcPlVxV1tQFTZDCpYjAIKUCsWHBDjO0yhq7kMkm8VPajEQdlAoxZJLLVnLQ25FclgXaqpYu23sGSp3tqeScWQmYn6bHT/97BMdqO3Dl0nR+JlhogpS48+wcbL11OabFhuGu1w/gimd3o9wSZABYM4gwoTO0gKEXvs+PcuFb0dwFY7/J6xf5GdGhUCsVKKrrsPXPGm8UFwDER2iQHq0dMsl1tKYdiTqN1xbtz5wejTmpejz1yYkxS1jZK7MFr7gete2oDFGZdUGLPbSmLIVCYFZyxJBJLmu/TK+XHDxtQavV0DdlS9r6U3yEBtevyMKWgzV4YVc51s2MR3yExt+HFRCEEDi3IBEf3LkSFy9MwdPbT2L977YPKzlcUt85YUsQ2btp1XToQ8w9VEeKUAes2djev7bJTQjH8bpOFNV1oqGjF8umR7u0n0UZUdhX3mIrtXW0xjxxNsML2diAuRfx1Wdk4J3DtbYJUGcY+0041dLtUqAqMHJ/7DJL5RWe66e2ghQ9ypq60NY1WB7LF9nYQogh1VemQjZ2IBJC4IFz81HX3os7Xt2P6FA1NsxK8PdhBYz8xAi88T9n4MfnzcDesmas++32YSWHi+s7vV5a3xfOnB6DVbmxePyjklHLLBbXd0CvDUJMmHf/v+YmRKDJYERDRy92FLsWvAKYz/W9/SZbUE5DRy+aDEavBa8AwM2rpqGx04hXv6j02ntMVVO3TsQUUt7UhfQo1xeeEvWOJ7nMZQl40TuVhaiVyIkPxwE/THKl2k1yDWaFMWrb18wXvjNgMA4gPFiFzXOT/H1IASc7Phyv37AUP7tgFg5WtmHdb7fjTx+fQN+AydaTJmeCZ2gBwBnTYnBWXhyeGOXC1xrF5e0MLZVSgWlxYThW24EdJY3Iig21ldAdr0UZUfiirNk2cXfUSz01rIQQuHnVNFQ0d+G/B2uc/vW1hOQAACAASURBVL4KW3lhFye59BrUtfcMW0QrbTQgOlTtUq8OmjzmpOhxtKYDxn7z+BgMXvHuuT5SG4SwYHPUtrHfhI7efk5y+cn1K7IQGx6MLuMArljMiO3T6bRB+MVFBXj1+iUIUiqGlBxu7OxFs8E4oUsQWelCgnDLWdnYWdKEj0foE2ro7cep1m7k+GABLzc+HCfqO/Hx8XoAwLLsWJf2U5gZhc7efltZ4aM17QhWKbyanXzNmZnQqJR48uMTTn/PqdZumKQ7wSuO+2OXNlp7Y/PefiqbYy0xfMq++opv+lTbL2gFar/MqWBRRhQ2zEyAwTiAby1MRbBK6e9DCihKhcDVZ2Zi250rcca06GElh31RWt9X7jsnH4befvzxw5EziYvrOpET5/3s81zL9dOWg9Wo7+jFchcCVQFgUUYkAGC3JVj1iK2VgPfu7Qszo7AwPRJ//uSE7T6KPIMLWlNARbPBls3iiiSdZlitbVuTeF70TnlzUnT4+lSbbbK3xWBESJASmiDvXvzYR21b+3YxQ8s/FqRH4ubV0/CDdTnQqid2NJK3KBQCVyxJx7Y7V2J1bhweeecYzvvjDrx9qAYqhXB5YiLQ3HdOHgy9/fjDh8UOny+u810ZhryEcByubsfuk80uZWdZFWZGoaWrDyX1nejpG8CJBoNX+mfZW5sfj5z4MDz5cQlMppEj4O2VN3UhJEiJWBf7syTqQmCSQH3H0H5vpY0GnusJBSl6GAdMOFZrvvFr6fJNv0whBFItk1yt3b5ZRCPHQoNV+NkFs3DR/GQsneZaFsxUsDgrekjJ4bWPfYLHLZNBkyFDCzCXy0uP1uKXW4/ZMprsWYN1fJWhZRww4aU9FciMCUWyi8Er1hLD1kmuozXtyE0I92rJxKhQNb5dmIZ/7692WLrKkXI3WgkAI/fHtmZ5s7zw1DY72dxOwFp9ZcAk0d7T55PFpbQoLSpbumEySZ/07aKR3b8xH6tyY3H1GRn+PpSAlaQPwTNXDS85fKJhcmRjA+bz67cWpOIfu8qGVJixklKiqK7DJwt4uQnm64nnLJVgznTx3j46LBjT4wZLDA9mY3s5WPWs6ahu68G/9o+vpQCNjgtak5zJJC0ZWq4vaFnLENmXlaiwNIlnFBcVpOjR2tVn18TVN1Fc0aFqaNXKIRlanOTyn/9dn4erz8z092EEvASdBk9duQB/vnIBWrv68O7hOmTGhEKtmhyn4+z4cFyyKBUv7Cp3eOHryzIMOfHhaOzsRXffgHsLWtZm8WXNKKnvxIBJYkaizlOH6ZBCIXDz6ukoquvEtqN1Tn1PeZMBaVFaN7KxzVHbjia5eK4nW89MyyRXq4/6ZQJAWlTI0OAVRm37zfqZCXjs4rksLTwGa8nhLbcuR1ZsmK0Ur7ezk31FrVLg7vXmHqr/3De8hM5gTw3vT3JZf6flTV1unesTdSFIjQrBF6XNtp4a3pzgsrp+RRYUAvjzdueytMqbzPdbrt7bx0c47o9d2mhAfEQwQid4mSxyj04bhIxora0/dlt3H6T0fvAKYK6+Yuw3ob6j19Ivk+d6f0mL1uL5awqRoGNp4dE4Kjls7DdNimxsK2sP1V+9e3zYc/UdvWjv6ffJAl5MmBpRoWqUN3UhI1prq9bkisLMKOwrM5cYPlrTjmR9CHRe/oxblROLGYkReOrjEw4Dgcg1k2MGbQrq6RtwKl2xvqMXvf0mpLsxGZWk16DLOID27sHmsScbWJaAzKyTXAftJrl8McFlrbVd2dyFZoMRKoVAOG/CaIJYPzMB2+5cgRtWZuF7y7P8fTgedcfakS98fVmGIc8SyaVUCCxxI5sgPVqLuPBg7ClttitL4P0blXNnJyItSosnPyoZtU+JVXlTl8sR28BgXw37SS5Dr7VJPM/1U11KZAiiQtX42lJi2FpW1FdliCqbu9Bk6PXZexJ5Qo6l5PDDF87Cd8/MRHyEaxm0gWjj7ATMS9PjsW1F6DL2D3mupL4TaqXCrYBKZ02PC4PS0kdjWbbrC1rAYInh2vYetHT1ebUEkVWCToNvLkjBa3urUN8+vMT/6dzNxlarFIhx0B+7tNHA7CwCYA5W/dpSPs2XQaPW6ivlTQZzDy0GqtIEYV9yePPcJKzOjfP3IXlMfIQG31ueiS0Ha/BVRcuQ54rrrK0TvH9fLISwlR1091xfmBGFDkuJYXMrAd8c/82rp+NkowHvHKr1+vtNFVzQmqBe31uJhT/bhjtf3Y/3Dteip2/A4etsZQnczNACgGq7C19bWQJOck15uQnhUKsUtmbxLV1Gn5UIsJYhaunqg16rZsQwTSjhmiDcd04+Ll6U6u9D8ai4CA2+tyJr2IXvgEniREOnzyLUraUJ5qToEKFx/TNJCIHCzCjsKW3G0Zp2hAQpfVIiUqVU4MaV03Cgqg1XPrsHL+2uQMNp5QCtTCaJimb3FrQcZWixBBFZCSEwO1lnC16xlhz0RW+1tCgtevtNKKo1Z31wkosmEoVC4PLF6fh/582YVNepQgg8sDEfde29ePbT0iHPFdV1ICs21Kvl+qw0QUpkRGuhEMCSLPdKYS7OjEKTwYgtlv6VvljQAoAbVkxD/4AJ3/7LLvzhg2JbeWZHKpoNSI92PRsbMLcTOL0/dhl7Y5NFQYoONW09qO/o8XE2tvka9mhNO/oGJLOxacJZnBWN3186z+WAg0B1/cppiAlT4xdbjw0JshzMxvbtvb072djAYInhHSWNONlo8Nm5fsOsBGTFhuJxJ4NVaWxc0JqgZiTpsG5mAj44Vo/r/7EP83+6DTe/+CX+c6Aanb2DUXLlljJwHp/kajQgJkzt1iQhTQ5BSgVmJEbYyhBZF5d8wdo8ttnQy4htogByw4osxIQF4+dbj9ou2MqbDDD2m3zSPwswNz7PSwjH+XOS3N5XYWYUatp68MHReuQmhNuiwb3tWwtTcOuabFS2dOH+N7/G4p+/j4v//Dme21k6pLelNRs7zY2FpwhNEMKCVUMytMoazdcQnOQiwLw4XFTXgS5jP1q6jIjQqHwyYW0tK2K9zmAZIqLAsDAjCutnxuOpT04MCbgwZ2P7ruTSypw4rMmPd3uBfZGlxPDfPy8HAOT5IGobMAeI/u7SedBr1XhsWxHO/u12rPnNx3j03WM4ZNenGDBnaKW5mfmWqAsZcg3R1t2HJoOR53oCAMxJ1QMADla2odngm36ZgLknkUIMnuv1vLcnCghhwSrcvjYHe8qase3IYCn84voO6LVBiAnzzXX5sukxSIjQYOk09xa0kvQhSNaH4KXdFRgwSZ8taCkVAnevz8Nli9NYdtBDWJ9rglqQHokF6ZHoGzBh98lmvH2oBu8ersOWr2ugVimwfHoMNsxKwKFTbVAqhK0BrCsclSE6ybIEZGdOig6v76vCgEmipcvos4iqtCgtevpMKK7vREzY5IqEIZrIQoNVuOPsbDzw5iG8d6QO62cmoLjed2UJAHP0+Du3r/DIvqyRXBXNXS43oXVFkFKBO8/OwR1rs3GstgNvH6rFu4dq8dBbR/DQW0cwJ1WPDTMTbDcS7pZ3StRphgSvlDaa/80yYrxfNooCX0GKHiYJHK5uR0tXH6J8lCmVZlvQMmeCc5KLKHDcsyEP7x/djt9/UISfXTAbht5+nGrtxqU+zD7/f+fN8Mh+MmNCERMWjIrmLqREhvg0cPP8OUk4f04S6tp78N7hWrx9qBZPfXIST3x0AimRIdgwMwHrZyWgorkLq3Jj3XqvRL0G24sbIKWEEAJljay8QoNmJkVAIYCDVa1IsZx/fRFIolYpkKgLsZ3rfXWNQURju3RRKv66sxS/fOcYVufFIUipQHFdJ3Liwn2Wfb52RjzWzoj3yL4WZ0bhja9OAfBdNjZgztIiz+GC1gQXpFRgWXYMlmXH4CebZ+HLiha8/XUt3j1ciw+O1QMwZ2cFuRFBGxseDJVCDMvQWpHj3sU0TR4FKXr87fNyFNd3oK27z2fZUtZJrpMNBp80oyQi512yMBXP7SzDI28fw1l5cbYSOhPx/2pOXDh0IUFo6+7DDB9FbNsTQiA/MQL5iRG48+wcnGzoxDuHa/HOoVo88s4x2+vcDTRJ1IcMKUNU2tiF+IhgaNW8XCSgINXcM/NAZavP+mUCQHJkCIQwn+u1aiU0QUqfvC8RjS0rNgyXFabhpT0VuPqMTBgslUJ8maHlKeYSw5HY+nWtTye47MVHaHDl0gxcuTQDzQYj3j9Sh7cP1eBvn5fhmR3m0o7ulj1O0oXY+mPrtEG28sLM0CIA0KpVyIkPx4GqNoRpzNd/vir1mxalxecnmwD4pswhETlHpVTg3g15uP4f+/DKF5W4YnEaiuo6cJ4HKqH4wyLLgpZWrfRJv0/yDs5QTCJKhcCijCgsyojCDzfl4+tTbXj3cC2y49y7oVAqBOIjNKixZGgZevtR38Em8TRojmWSa0dxI6T03QVoml0pTUZxEQUW64XvdX/fi1f2VKCorhPJ+hCEBk+8Sw+FQmBRRiTeP1rvt0kue1mxYbhp1XTctGo6qlq68O7hOjQbepES6Xo2NmDuq3Gkut3297Im9tSgQXHhGiTqNDhY1YaWLiNifZQZHaxSIkkXglOt3Sw3SBSAblubjTe/OoVH3jmGdZbo6Zz4iRe8ApibxftzQcteVKgaFy9KxcWLUtHe04ePjtXji7JmrJvpXoS6tZ1AdVs3dNognGwwQAi4XcqQJo+CFB22HanDjKQIBCkFQtW+CSRJjx5c0OK9PVFgOXtGPAozovD794twxrRotPf0+6zyiqdZq6/kJoRD4aNWAuR5E29WiZwihEBBih4FKXqP7C9Rp0G1JUOrtJFRXDRUVkwYQtVKfFLUAACIDPVNhlay3hy17ctFNCJy3pr8OBRmRuF37xcjXKNC9gSd4AKAlblx2HWyGXkBMMllLyVSi2uXZXpkX4m6EDR29qK3fwDBKiVKGw1Y7+bEGU0uBSk6HKxqRd+ARI6bAVPjkRplWdDy0fUFETkvJiwYN67Mwq/fK0KLwQi1UjFhF0eWZcdCqRAotPTTChQRmiBsnpuMzXOT3d5XoqWdQE1bN/ITI1DWZECSLoTZr2QzO0WP1/ZW4dCpNui1ap+VFEu1+9xgf2yiwCKEwP3n5uOCJ3binn8eBDAxK68AQFZMKNKitAF3rqfx8X4nZ5oU7MsQWcsSsIcWWSkUArOSddhd2gzAd4tLmiAlEiLMUYa+6ttFRM4TQuCBjfloMhhR1tQ1YaO4AODywjTsvOcshE3ADDNnWaO269p60dbdh2aDked6GqIgRY+ypi7Ud/T4NJAkzYd9PIho/K5dloWECA32lrcgKzYUKjfK3fvT9Lgw7H1gLZZl+65fpq8lWTO0LNVXyhqZjU1DzUkxV1/ZXdrs04Ul67leIeDTHnZE5Jy5qXpsKkjE3vIWABOzvDBgnqPYcusy/GBdrr8PhdwwMa80yeeSdBrUtPVASmnXOHZiRt6Rd8xJ1cPYbwLg2wknayQXm8QTBaY5qXpbfe2JGsUFmBfudZP8cybJErVd3dZtO9dzkovsFVgmufoGpF8mubigRRSYQtRK3LkuBwAmdPAK4Lt+Qf4SF66B0tIfW0qJk1zQotPkJURArVTA2G/yS/CKXqtmGTCiAHX3+jwEKQUitUGICZu458twTRDUKi6JTGSTN8yYPCpRp4Gx34QmgxEnGw1IiNCwSTwNYZ3kAnxbIiAtSos9pc2ss00UwO49Jw8dPX1Ynh3r70OhUVgztGrauiFgnkjgJBfZK0geLGWt9+F51xq8wnM9UeD6xvwU7DrZhHNnJ/r7UGgUSoVAfHgwalp70GwwoqOnHxk815MdtUqB/MRwHKhq81PwyuQOICOayNKitbjvnHy0dff5rBwpkSNckSCnJOottbZbe1DWaGB2Fg0zx65fmy8jG+0juYgoMCXrQ/D8NYX+Pgwagy1Dq7UHxn4ThBjaz4BIpw1CRrQWZU1dPi31m8ZsbKKAp1QIPHbxXH8fBjkhUR9izsZusmZj81xPQxWk6HGgqs2ngSR6bRDCg1XMxiYKcN/1UP9mIncwv46cMqQMUVMXMmMmbtko8o6UyBBEaoOgUgiE+7DHzIzECKgUAimRIT57TyKiyShErYReG4QayyRXsp5N4mm4AksAiy8jqLNiwqAJUrCnGxGRByRa2gmcbLAuaPHenoayVl/xZdCoEAL5SRFI57meiIjGwAwtcoq1DNGxmg40G4yM4qJhhBAoSNHjcHWbT1OP1+TH4bP7zkJcuMZn70lENFkl6kJQ09qDhs5elhskhwpSdPjPgWqfTnLptEHYcc9ZPs0KIyKarJL0IXjvSB1KGw1QMjCQHJiT6vvgFQB49qqFUCkYd09ERKPjghY5JTpUDbVKgc9ONAIAI2TJoVvXZKOyucun7ymE4GIWEZGHJOk0qG7rQVVLFy6Ym+zvw6EAdNH8FBh6B5CbEO7T940JC/bp+xERTVbW/tj7yluQGhmCICUXEGio7Lgw3HtOHjYVJPn0fcM1LC1MRERj44IWOUUIgUSdBl9VtAIAsmK5oEXDLUiPxIL0SH8fBhERuShRr8GnxY0wDpiYoUUORYWqcdvabH8fBhERuSjR0k7gq4pWnDk92s9HQ4FICIEbV07z92EQERE5xFAcclqiTgPjgAkKNoknIiKalBJ1ITAOmACAC1pERESTUJKlnYBxwIQMnuuJiIhognFrQUsI8agQ4pgQ4qAQ4k0hhN7uufuEECVCiONCiPXuHyr5W5Ilkis5MgTBKjaJJyIimmysk1wAF7SIiIgmI2uGFgBk8VxPREREE4y7GVrbAMySUhYAKAJwHwAIIWYAuBTATAAbADwphOAKyASXaJnkYv8sIiKiyck6yaVik3giIqJJKTpUDbWlbxYztIiIiGiicWtBS0r5npSy3/LXXQBSLF9vBvCKlLJXSlkKoARAoTvvRf5nneRixDYREdHkZM3GTo3SQsUm8URERJOOQiGQoGOwKhEREU1Mnpyp+C6Aty1fJwOotHuuyvLYMEKI64UQe4UQexsaGjx4OORp1jJEXNAiIiKanOJ1wQB4riciIprMEnUaqFUKJOmZjU1EREQTi2qsFwgh3geQ4OCpB6SU/7a85gEA/QBetH6bg9dLR/uXUj4N4GkAWLhwocPXUGDIS4hAWLAKC9Ij/X0oRERE5AXBKiVmJ+uwKCPK34dCREREXjI/PRJBSgWUCkdTN0RERESBa8wFLSnl2tGeF0JcBWATgDVSSuuCVBWAVLuXpQCodvUgKTAk6UNw6KH1/j4MIiIi8qK3blnm70MgIiIiL7pnQ56/D4GIiIjIJW6VHBRCbABwD4DzpZRddk/9B8ClQohgIUQmgGwAe9x5LyIiIiIiIiIiIiIiIpqaxszQGsPjAIIBbBNCAMAuKeWNUsrDQojXAByBuRThzVLKATffi4iIiIiIiIiIiIiIiKYgtxa0pJTTR3nuYQAPu7N/IiIiIiIiIiIiIiIiIrdKDhIRERERERERERERERF5Gxe0iIiIiIiIiIiIiIiIKKBxQYuIiIiIiIiIiIiIiIgCmpBS+vsYbIQQDQDK/X0cASIGQKO/D4LIAY5Nmig4Vmki4DilQMWxSRMJxytNBBynFKg4Nmki4XiliYDj1H3pUspYR08E1IIWDRJC7JVSLvT3cRCdjmOTJgqOVZoIOE4pUHFs0kTC8UoTAccpBSqOTZpIOF5pIuA49S6WHCQiIiIiIiIiIiIiIqKAxgUtIiIiIiIiIiIiIiIiCmhc0ApcT/v7AIhGwLFJEwXHKk0EHKcUqDg2aSLheKWJgOOUAhXHJk0kHK80EXCcehF7aBEREREREREREREREVFAY4YWERERERERERERERERBTQuaBEREREREREREREREVFA44KWBwghUoUQHwkhjgohDgshbrM8HiWE2CaEKLb8GWl5PE8I8bkQolcIcZfdfnKFEPvttnYhxO0jvOcGIcRxIUSJEOJeu8e/b3lMCiFivP2zU+ALsPH5vBCi1G4fc73989PEEWBj9SwhxJdCiENCiL8JIVTe/vlpYvDUOLU8d4dlH4eEEC8LITQjvOdVlv0WCyGusnv8YSFEpRCi05s/M00MATY2P7Z8tlo/h+O8+bPTxBNg4/USIcRByz5+5c2fmyYWD4/T2yxj9PBI16WW1/E+n8YUYGOT9/g0ogAbq7zHpxG5MFYvt1w/HhRCfCaEmGO3L4dj0MF78j7fVVJKbm5uABIBzLd8HQ6gCMAMAL8CcK/l8XsBPGL5Og7AIgAPA7hrhH0qAdQCSB/huRMAsgCoARwAMMPy3DwAGQDKAMT4+3fDzf9bgI3P5wF809+/E26BuQXKWIU52KMSQI7ldT8BcK2/fz/cAmPz1DgFkAygFECI5e+vAbjawftFAThp+TPS8nWk5bklluPp9PfvhZv/twAbmx8DWOjv3wm3wN0CZbwCiAZQASDW8rq/AVjj798Pt8DYPDhOZwE4BEALQAXgfQDZDt6P9/ncnNoCbGw+D97jcxthC5SxCt7jcxtjc2GsnoHBe59zAOy2fD3i5+Vp78f7fDc2Zmh5gJSyRkr5peXrDgBHYb652gzzTREsf15geU29lPILAH2j7HYNgBNSynIHzxUCKJFSnpRSGgG8YnkvSCm/klKWuf9T0WQRSOOTaDQBNFajAfRKKYssr9sG4Btu/XA0aXh4nKoAhFiiA7UAqh28Zj2AbVLKZillC8zjcYNl37uklDUe++FoQguksUk0lgAar1kAiqSUDZbXvQ+e88nCg+M0H8AuKWWXlLIfwCcALnTwlrzPJ6cE0tgkGk0AjVXe49OoXBirn1muKQFgF4AUy9fOfl7yPt8NXNDyMCFEBszRU7sBxFsHoOXP8ZRbuRTAyyM8lwxzZIFVleUxolEFyPh82JKS+1shRPA43pOmED+P1UYAQUKIhZbHvwkgdRzvSVOEO+NUSnkKwK9hzgyoAdAmpXzPwUt5zqdxC5Cx+Zyl9NAPhRDCxR+FpgA/j9cSAHlCiAzLgtgF4DmfHHDz2vQQgBVCiGghhBbARjgeZzzn07gFyNjkPT6Nyc9jlff45DQXxuq1AN62fO3suZznfDdwQcuDhBBhAP4PwO1SynY39qMGcD6A10d6iYPHpKvvR1NDgIzP+wDkwZxCHgXgHlePgyYvf49VKaWEeSHst0KIPQA6APS7ehw0Obk7Ti21tzcDyASQBCBUCHGFo5c6eIznfBpRgIzNy6WUswEst2xXjvc4aGrw93i1RMT+D4BXAXwKczk3nvNpCHfHqZTyKIBHYI6+fgfm8kOOxhnP+TQuATI2eY9PY/L3WOU9PjlrvGNVCLEa5gUt62efs+dynvPdwAUtDxFCBME84F+UUr5hebhOCJFoeT4RQL2TuzsHwJdSyjrL96baNdi8EeZVW/tIghQ4Lq1BBCBwxqclhVdKKXsBPAdzKi6RTQCN1c+llMullIUAtgModvdno8nDQ+N0LYBSKWWDlLIPwBsAzhBCLLYbp+eD53wah0AZm5asGWu5jpfA8z05EEDj9S0p5WIp5VIAx8FzPtnx1LWplPJZKeV8KeUKAM0AinmfT+4IlLHJe3waSwCNVd7j06jGO1aFEAUAngGwWUrZZHnY4Rjkfb5nqfx9AJOBpYzKswCOSikfs3vqPwCuAvBLy5//dnKX34ZdiSwpZSWAuXbvpwKQLYTIBHAK5iiDy9z5GWjyCqTxKYRIlFLWWI7pApjTxokABNxYjZNS1ltKZtwDc1NaIk+O0woASywlM7ph7ve2V0q5G0PHaRSAn1uyEABgHcyRsERDBMrYtHy26qWUjZabwk0w9yUisgmU8Wp5znrOjwRwE4CL3f35aHLw5LWp3ThLA3ARgKWWDEHe59O4BdLY5D0+jSbAxirv8WlE4x2rlnH4BoAr5WBvNgD4Ag7GoJTyMHif7zlSSm5ubgCWwZwWeBDAfsu2Eeamgx/AvOr/AYAoy+sTYF6JbQfQavk6wvKcFkATAN0Y77kRQBGAEwAesHv8Vsv++mFe2X3G378fbv7dAmx8fgjga5gvcl8AEObv3w+3wNkCbKw+CnMT0OMwp5r7/ffDLTA2D4/ThwAcs3wm/gNA8Ajv+V2Y+7yUALjG7vFfWfZnsvz5Y3//frj5bwuUsQkgFMA+y3EcBvB7AEp//364BdYWKOPV8vjLAI5Ytkv9/bvhFjibh8fpp5YxdgDAmlHek/f53MbcAmxs8h6f24hbgI1V3uNzG3FzYaw+A6DF7rV77fblcAw6eE/e57u4CcsvioiIiIiIiIiIiIiIiCggsYcWERERERERERERERERBTQuaBEREREREREREREREVFA44IWERERERERERERERERBTQuaBEREREREREREREREVFA44IWERERERERERERERERBTQuaBEREREREREREREREVFA44IWERERERERERERERERBTQuaBEREREREREREREREVFA44IWERERERERERERERERBTQuaBEREREREREREREREVFA44IWERERERERERERERERBTQuaBEREREREREREREREVFA44IWERERERERERERERERBTQuaBEREREREREREREREVFA44IWERERERERERERERERBTQuaBEREREREREREREREVFA44IWERERERERERERERERBTQuaBEREREREREREREREVFA44IWERERERERERERERERBTSVvw/AXkxMjMzIyPD3YRAREREREREREREREZGP7du3r1FKGevouYBa0MrIyMDevXv9fRhERERERERERERERETkY0KI8pGeY8lBIiIiIiIiIiIiIiIiCmhc0CIiIiIiIiIiIiIiIqKAxgUtIiIiIiIiIiIiIiIiCmgB1UOLiIiIiIiIiIiIiIhooujr60NVVRV6enr8fSgTikajQUpKCoKCQ7c77AAAIABJREFUgpz+Hi5oERERERERERERERERuaCqqgrh4eHIyMiAEMLfhzMhSCnR1NSEqqoqZGZmOv19LDlIFCC6jQP4pKjB34dBRERERERERERE5DWtXUZc8ufPUVLf4e9D8Yienh5ER0dzMWschBCIjo4ed1YbF7SIAsRLeypw1V/3oLK5y9+HQkREREREREREROQVO0oasbu0Gf/eX+3vQ/EYLmaNnyu/My5oEQWIA5WtAIDiSRKZQERERERERERERHS6vWUtAMwLW0TjwQUtogDx9ak2AEBJfaefj4SIiIiIiIiIiIjIO76sMC9oHahsRXtPn5+PZnJQKpWYO3cuZs2ahfPOOw+tra0u7ee6667DkSNHhj3+/PPP4/vf/77LxxcWFuby99rjghZRAGjv6UNpowEAcKLe4OejISIiIiIiIiIiIvK8LmM/Dle3Y1FGJEwS2HWiyd+HNCmEhIRg//79OHToEKKiovDEE0+4tJ9nnnkGM2bM8PDReY7K3wdARMAhS3aWWqnAiQZmaBEREREREREREdHks7+yFQMmieuWZ+HQqf3YWdKIdTMT/H1YHvPQW4dxpLrdo/uckRSBH5030+nXL126FAcPHrT9/dFHH8Vrr72G3t5eXHjhhXjooYdgMBhw8cUXo6qqCgMDA/jhD3+ISy65BKtWrcKvf/1rLFy4EM899xx+8YtfIDExETk5OQgODgYAXH311di0aRO++c1vAjBnX3V2dqKzsxObN29GS0sL+vr68LOf/QybN2/26O/CYwtaQgglgL0ATkkpNwkhMgG8AiAKwJcArpRSGj31fkSTiXVB66y8OOwqbYKUko0EiYiIiIiIiIiIaFL5stxcbnBJZjQKM6PYR8vDBgYG8MEHH+Daa68FALz33nsoLi7Gnj17IKXE+eefj+3bt6OhoQFJSUnYsmULAKCtrW3IfmpqavCjH/0I+/btg06nw+rVqzFv3rxR31uj0eDNN99EREQEGhsbsWTJEpx//vkenef2ZIbWbQCOAoiw/P0RAL+VUr4ihHgKwLUA/uTB9yOaNA5WtSFZH4JFmVF453Atmg1GRIcF+/uwiIiIiIiIiIiIiDxmb3kLcuLDoNMGYdn0GDy89Shq23qQoNP4+9A8YjyZVJ7U3d2NuXPnoqysDAsWLMDZZ58NwLyg9d5779kWozo7O1FcXIzly5fjrrvuwj333INNmzZh+fLlQ/a3e/durFq1CrGxsQCASy65BEVFRaMeg5QS999/P7Zv3w6FQoFTp06hrq4OCQmey8DzSA8tIUQKgHMBPGP5uwBwFoB/Wl7yNwAXeOK9iCajQ6faMCs5AtPjzM3xTjSwjxYRERERERERERFNHiaTxJflLViQHgkAOHN6DABgJ7O03GbtoVVeXg6j0WjroSWlxH333Yf9+/dj//79KCkpwbXXXoucnBzs27cPs2fPxn333Yef/OQnw/Y5UmaVSqWCyWSy7d9oNBfme/HFF9HQ0IB9+/Zh//79iI+PR09Pj0d/To8saAH4HYC7AZj+P3v3HRf1fT9w/PW9Y3NwbERAUKYDJxq3xhWzR5vVqGmapkmbpNmrI01/bUbTNHvvmG2mSZqlxoXiAAeoyJSNbI55cNx9f38ANirKugH4fj4eeVS5u+/3I4W77/fzXp1/9wfqVFVt7/x7MRDa3QsVRfmdoigpiqKkVFZWWmk5QgwdhhYT+dXNTAzzISrQE0DmaAkhhBBCCCGEEEIIIYaVnMpG6o3tTIvwAyB+hBf+ni4S0LIivV7Ps88+yxNPPIHJZOKcc87hzTffpLGxY7+5pKSEiooKSktL8fDwYMWKFdx9993s2bPnuOOcddZZbNq0ierqakwmE5988smxxyIjI0lNTQVg7dq1mEwmoKNtYVBQEM7OzmzcuJGCggKr//sG3HJQUZQLgApVVVMVRVnY9eVunqp293pVVV8FXgVITEzs9jlCDGcHO+dnTQjVM1LvjruzlpwKCWgJIYQQQgghhBBCCCGGj5T8jvlZiZ0VWhqNwuzoAJJyqlBV1aqzls5kU6ZMYdKkSXz00UesXLmSjIwMZs2aBYBOp+O9994jJyeHe+65B41Gg7OzMy+9dPy0qJCQEB566CFmzZpFSEgIU6dOxWw2A3DDDTdw8cUXM2PGDBYvXoynZ0eRxjXXXMOFF15IYmIikydPJj4+3ur/NkVVBxZDUhTlUWAl0A640TFD6wvgHGCEqqrtiqLMAh5SVfWc0x0rMTFRTUlJGdB6hBhqXtmcy6PfHWbPX5fi5+nC+c9uJdDLlbevm+HopQkhhBBCCCGEEEIIIYRV3LlmH5szK0n5y5JjwauPdhVy/+fprLtjPjHBXg5eYf9kZGQwduxYRy9jSOrue6coSqqqqondPX/ALQdVVX1AVdUwVVUjgauAn1RVvQbYCPyy82nXAmsHei4hhqO0EgOhPu74eboAEBWok5aDQgghhBBCCCGEEEKIYaVrftbPK7G65mglSdtB0QvWmqHVnfuAOxVFyaFjptYbNjyXEEPWgRIDE8P0x/4eFaijuLYFo8nswFUJIYQQQgghhBBCCCGEdVQ2tJJf3UxipO9xXw/38yDC34NtOdUOWpkYSqwa0FJVdZOqqhd0/jlPVdUZqqpGq6p6uaqqrdY8lxDDgaHZREF1MxNCfxbQCvJEVSGvssmBKxNCCCGEEEIIIYQQQgjrSC3omJ81LcL3pMfmRAewI6+adrPF3suymoGOdjoT9ed7ZssKLSFEDw6UGgBI+FlAKzpIByBtB4UQQgghhBBCCCGEEMPCnsJaXJw0xyX2d5kbHUBjazv7iw0OWNnAubm5UV1dLUGtPlBVlerqatzc3Pr0OicbrUcI0QtpxScHtCL9PVEUCWgJIYQQQgghhBBCCCGGh5T8GiaG6nF10p702Kwx/igKbMup6raCa7ALCwujuLiYyspKRy9lSHFzcyMsLKxPr5GAlhAOdKDEQJivO76eLse+5uasJdzXg5wKCWgJIYQQQgghhBBCCCGGNqPJzIGSeq6bE9nt476eLowf6U1SThV/XBxj38VZgbOzM6NHj3b0Ms4I0nJQCAdKLzEwMezkMtvoIB25MkNLCCGEEEIIIYQQQggxxB0oMdBmtpy2+mpOdAB7C2tpbmu348rEUCMBLSEcpK65jcKa5m77xkYFepJX2YjFIn1XhRBCCCGEEEIIIYQQQ1dKQS3AaQNac6MDMJlVdh2psdeyxBAkAS0hHORAST0AE0N9TnosKlBHa7uFkroWey9LCCGEEEIIIYQQQgghrCYlv5bRAZ7461xP+ZzpkX64OGnYllNlx5WJoUYCWkI4SFpJHQATQr1PeiwqSAdATqXM0RJCCCGEEEIIIYQQQgxNqqqyp7D2tNVZAG7OWhIjfEnKqbbTysRQJAEtIRzkQImBUX4e+Hi4nPRYdGBHQCu3QgJaQgghhBBCCCGEEEKIoelIVRM1TW0k9hDQgo45Whll9VQ1ttphZWIokoCWEA6SVmwgoZv5WQC+ni74ebqQW9lk51UJIYQQQgghhBBCCCGEdfRmflaXOdEBAGzPlSot0T0JaAnhALVNbRTXtpAQ1n1ACyAq0FMqtIQQQgghhBBCCCGEEEPWnoJa9O7ORHV2pDqdhFA9Xm5ObMuWOVqiexLQEsIB0ksMAKes0AKIDtKRKzO0hBBCCCGEEEIIIYQQQ1RKQcf8LI1G6fG5Wo3C7Ch/knKqUFXVDqsTQ40EtIRwgK6A1oSRp6vQ0lHd1EZtU5u9liWEEEIIIYQQQgghhBBWUdfcRk5FY6/aDXaZGx1ASV0LhTXNNlyZGKokoCWEAxwoMRDh74Hew/mUz+kqw5UqLSGEEEIIIYQQQgghxFCzp7D387O6dM3RSsqRtoPiZBLQEsIB0ooNTDhNu0GQgJYQQgghhBBCCCGEEGLoSsmvxUmjMCnMp9evGR3gSYjejW0S0BLdkICWEHZW09RGSV0LE3sIaIX6uuPqpCG3sslOKxNCCCGEEEIIIYQQQgjrSC2oZfxIb9xdtL1+jaIozIkOYHtuNWaLzNESx5OAlhB21jU/K6GHgJZWozA6wJPcCqnQEkIIIYQQQgghhBBCDB0ms4X9xXVMi/Dr82vnRgdQ12ziUGm9DVYmhjIJaAlhZwc6A1rjewhoAUQF6ciRloNCCCGEEEIIIYQQQogh5GBpPUaTpU/zs7rMjvYHYFuutB0Ux5OAlhB2llZcR6S/B3p35x6fGx2oo6imGaPJbIeVCSGEEEIIIYQQQgghxMClFtQCkBjZ94BWkJcbccFeMkdLnEQCWkLY2YGSehJ6OQgxKkiHRYWC6mYbr0oIIYQQQgghhBBCiNP76XA5v30nRWYbiR6lFtQQ5utOsLdbv14/JzqAXUdqJNFfHEcCWkLYUXVjKyV1LSSEevfq+VGBngDkyBwtIYQQQgghhBBCCOFg36YfZX1GOfuKah29FDGIqapKSn5tv9oNdpkT7U9ru4U9BfKzJv7HydELEOJMkt45PyshtHcVWmMCdCgK5MocLSGEEEKc4Kv9pazeno+nqxM6Nye8XJ3Qdf5Z5+qEl5sTOlfnE/7e8binixNajeLof4IQQgghhBhissobAPjxYDnTIvwcvBoxWBXXtlDR0EriAAJaZ43xR6tRSMqpYnZ0gBVXJ4YyCWgJYUfpxR0BrfG9rNByd9ES6uMuAS0hhBBCnOSlTblU1BsJ83WnqLaZRmM7ja3tNLf13JJDo8DDlyZw9YxRdlipEEIIIYQYDiwWlezyjj2qHw+Vc/+58SiKJEmJk3XNzxpI0FPn6sSUcB+ZoyWOIwEtIewovcTAmABPvN2ce/2aqECdtBwUQgghxHFK6lrIKKvngXPjuXFB1HGPtZstNLWZaWxt7wxymWjoDHZ1Bb1WJxfw+Z5iCWgJIYQQQoheK6lrocVkZvxIbw6W1pNb2Uh0kJejlyUGoZSCGnSuTsSNGNjPx5zoAJ77KRtDswm9R+/3U8XwJQEtIezoQImBxMi+ZSZEBerYdaQGi0VFI62BhBBCCAH8lFEOwOKxwSc95qTVoHfXoHc/9Q1fXbOJlzbnYmgxnfZ5QgghhBBCdMk82tFu8A8Lo7n5gz38cLBcAlqiW6kFdUwZ5TPgNudzYwJ4ZkM2yXnVLJ8wwkqrE0OZxtELEOJMUdXYSqnByMQwfZ9eFx2ko8VkpqzeaKOVCSGEEGKoWZ9RQaS/B1GBnv16/cK4QMwWlaRsad8hhBBCCCF6J6uiI6A1NyaASWF61h0qd/CKxGDUYDSRebSeaQOYn9VlcrgPni5aaTsojpGAlhB2kl7SMT9rQmjfAlpdG1W50nZQCCGEEEBTazvJudUsHhvc75kFk8N98HZzYmNmhZVXJ4QQQgghhqvs8kZC9G7o3Z1ZNn4E+4rqKJcEbHGCvYV1WFSsEtBy1mqYMdpPAlriGAloCWEn6cUdAa3xI7379LqoIB2AzNESQgjhMA1GExaL6uhliE5JOVW0mS0sHhvU72M4aTXMjw1kc1al/H8rhBACgLZ2C8W1zezOr+Gr/aW8vjWPrPIGRy9LCDGIZB5tICa4o8Xg0nEdra+lSkucKLWgFo0CU0YNPKAFHXO08qqaKKlrscrxxNAmM7SEsJP0EgNjAj3xcuvbnAp/Txf07s7kVkpASwghhP1VNBhZ9MRm/nz+WK6eMcrRyxHAhoxyvNycmN7HuZwnWhgXxDdpZRwqq+9zBbkQQoihpbXdTLmhlTJDC0frjZTWGTlqaKHMYORovZEyg5GqxlbUE3IconcX8f1t83DSSj60EGc6s0Ult7KR2VH+AMQE6Yj092DdoXJWzIxw8OrEYJJaUEv8CG90rtYJPcyNCQBgW04VVySGW+WYYuga8E+VoijhwGpgBGABXlVV9RlFUfyAj4FIIB+4QlXV2oGeT4ihKr3YwFlj+r7xpCgK0UE6CWgJIYRwiI92FdHY2s6egloJaA0CFovKT4crWRAbiPMANxcXxAYCsCmzQgJaQggxTH2XXsZf1x6kqrH1pMe83JwI0bsRondnXIg3I/Rux/4eonfjUFk9t320j492F8lmtRhSDpYauO6t3Xz+h9mE+Xo4ejnDRmFNM63tFmJHdFRoKYrCsvEjeGvbERqMpj4ncIvhqd1sYW9hLZdNDbPaMeOCvQjQubBdAloC61RotQN3qaq6R1EULyBVUZR1wK+BDaqqPqYoyv3A/cB9VjifEENORUNH1ltCPzeLogI9+elwpZVXJYQQQpxeu9nCBzsLAaTl0CCxv7iOqsZWlowNHvCxAr1cSQjVsymzklsWxVhhdUIIIQYTk9nCP/+bgd7diVWzIhihd2Ok3p0RejdG6N16zJyPDtLx/s5CnlqXxcWTR8pmtRgyNmVWUtHQypasKn51liRkWUvm0Y77gdjOloPQ0Xbw1S15bMqs5MJJIx21NDGIZJY30NRmJjHSOu0GoSN4Oic6gKScalRV7fccYTE8DLhmXFXVMlVV93T+uQHIAEKBi4F3Op/2DnDJQM8lxFB1oKRjflb/A1o6qhpbMTSbrLksIYQQ4rTWHSrnaL2RMQGeZFc0yqylQWBDRgVajcLCuECrHG9hXCB7CmvlGkMIIYahb9JKKalr4U/njeWPi2O4IjGcuTEBRAfpetUGSlEU/nL+WKqb2nhxU64dViyEdaQV1wGQkl/j4JUML9mdCW4xnbPeAaaO8sXf00XmaIljUgs6GrRNi7BeQAs65mhVNbaSVS4drM50Vm2CrChKJDAF2AkEq6paBh1BL6D/U6uFGOLSi+tRFBjfz4BWdOfFQm6VvGkLIYSwn9XJBYT6uHPd3NE0t5llCO8gsD6jnGkRvvh4uFjleAvjArGosCVbKsGFEGI4UVWVVzbnERus4+y4/m/HTAzz4dIpobyRdITi2mYrrlAI20kr7kgq3l0gAS1ryqpoJMzXHc+fBcS1GoXFY4PYeLiCtnaLA1cnBouU/FqCvV0J9XG36nHnRHfM0UrKqbLqccXQY7WAlqIoOuAz4HZVVev78LrfKYqSoihKSmWl3EiL4Sm9xMCYAM9+D0OMCuwMaFVIQEsIIbpzqLReNlmsLLu8geS8albMjGBcSEdbEWk76FjFtc0cPtrAkrHWyxObHO6Lj4czmzLlOlwIIYaTTVmVHD7awO/mR6HRDKw10z3nxKEA//4h0zqLE8KGKhqMlBmMhPm6U1TTQnm90dFLGjayjjYc126wy7JxI2hobWdHXrUDViUGm9SCWhIj/KzeFjDUx53RAZ5sk4DWGc8qAS1FUZzpCGa9r6rq551fLlcUJaTz8RCgorvXqqr6qqqqiaqqJgYGWqd1ihCDTXpJHRPDfPr9+jBfd1y0GnIqJaAlhBAnMrSYuPLVZB766qCjlzKsrE4uwMVJw5XTw4kO6gpoyeeQI/10uONyerEV5md10WoU5sUEsjmrUlpKCiHEMPLyplxC9G5cZIWZNiN93Llh3hjW7itlX1GdFVYnhO2kFXVUZ/16diTQUS0iBs5ktpBX1UhMsO6kx+bGBODurJW2g4KjBiMldS1WbzfYZU60PzvzqjGZpRrwTDbggJbSEW59A8hQVfXJnz30FXBt55+vBdYO9FxCDEUV9UbK61uZ0M92gwBOWg2RAR7kVjRZcWVCCDE8vJl0hAZjO3sL61BV2ZC3hgajic/3FHPBxBD8PF3QuzszwtvtWN984RjrMyoYHeB5rHLbWhbGBlLV2MrB0l43WRBCCDGI7S2sZeeRGq6fOxoXJ+s05rlpYRQBOlce/u8hud4Sg1pacR0aBS5PDMfNWcNumaNlFQXVTZjMKnHdVGi5OWuZHxvAukPl8v5whkvpbPNpq4DW3OgAmtrM7JfkijOaNa5s5gArgUWKouzr/O884DFgqaIo2cDSzr8LccZJL+nIDpoY1v+AFnTM0cqTCi0hhDiOocXEm9uO4O6spbqpjVKDtBSxhi/2ltDUZmbVrMhjX4sd4UWmBLQcpqm1nR251SyOt/5Y2gVxHV0SNmV221BBCCHEEPPK5jy83Zy4asYoqx1T5+rEnUtj2Z1fy/cHjlrtuEJY2/5iA7HBXujdnZkS7ntsg10MTObRjv2o7loOQkfbwaP1xmN7YOLMlFpQi7uzlnEjvW1y/FljAlAUmaN1phtwQEtV1SRVVRVVVSeqqjq5879vVVWtVlV1saqqMZ3/K58g4oyUXmJAUWBcyMDezKMCdRTUNMuQTSGE+Jm3t+XTYGznwQvHAZAmmVoDpqoqq5MLmBimZ3L4/9rlxgbpyKloxCxt6Rxia3YVbWaLVdsNdgnQuTIxTM+mLJmjJYQQQ11uZSM/HDrKylkR/Z7hfCpXJIYRG6zjse8Py32pGJRUVSWtuO5YQvH0SF8OldbT2Nru4JUNfVnlDSgKp+wUsCg+CK1G4ceD0nbwTJZaUMukcD3OWutUB59I7+HMxFC9zNE6w9nmp0uIIS6/qonUAuv0WU4vNhAdqMNzgDcTUYE6zBaVgmppOyiEEAD1RhNvJOWxdFwwl00NxVmrsL9YMgIHKjmvmpyKxuOqs6AjG7O13UJRTbNjFnaG25BRjrebE4mRtmnfsTA2kL2FtdQ1t9nk+EIIIezj9a15OGs1/Hr2aKsf20mr4U/njaWgupnVyflWP74QA1Vc20Jts+nYDPNpkX5YVNhXKElvA5Vd0UCEnwfuLtpuH/f1dGF6pC8/HpIKzjNVc1s7B0vrbdZusMvs6AD2FtZJoPoMJgEtIU7Q1m7h2rd2cfWrOzh8dOCzJNJLDCQMYH5Wl+igjiyYXGk7KIQQALyzLZ96Yzu3LY7B1UlL/Ahv0orlZnWg3k0uwNfDmQsmhhz39dgRHe1FpO2g/VksKhszK1gQF2SzbMeF8UFYVNiSLdmOQggxVFXUG/kstYTLp4UR6OVqk3MsjAtifmwgz/2UI0kQYtBJ60xum9QZ0Jo6ygeNgszRsoLMow3EnKLdYJdl40aQVd5IfpUkYp+J9hcZMFtUEiP8bHqeudEBtFtUdh2ptul5xOAlAS1hFzkVjazdVzIkhkO+v7OAgupmnLUKt3+0D6PJ3O9jldcbqWhoZYIVAlqjAzwByK2UCwMhhGgwmng96QhLxgYde49NCNOTXmzAIi3x+q3M0MKPh8q5Yno4bs7HZ1/GdCZWZEtAy+72FddR1djGkrHWn5/VZVKYD74ezjJHSwghhrC3tufTbrFww7wxNj3Pn88bS4PRxLMbcmx6HiH6Kq24DhethrjORCwvN2fiR3jLHK0Bam03k1/dTGxw9+0Guywd19Eae90haTt4Jkrt/D2bOsq2FVrTInxxddKQlC0BrTOVBLSEzZXUtXD1azu47aN93PbRPlra+h8gsjVDi4lnN2QzJ9qf56+ZyuGjDTzxQ2a/j5femR3U1b95IDxdnRipdyOnQiq0hBC2l1vZSE7F4A1crE4uwNBi4rbFsce+NilMT0NrO0fs1JrVaDJTUW+0y7ns5YOdhVhUlRVnRZz0mKerE6E+7mSVy+eQvW3IKEerUVgYa7uAllajMC8mkM2ZlRIUFkKIIajBaOK9HQWcOyGEyM5kSFuJG+HFldPDWZ2czxGpxBCDyP7iOsaGeOHi9L/tzumRvuwtrKPdLHPf+utIVRNmi0psDxVa4X4ejA3xlraDZ6iUglpignToPZxteh43Zy3TI/1kjtYZTAJawqYajCauf3s3RpOZ384dzddppVz+ynZK61ocvbRuvbw5l9pmEw+cO5az44JYOTOC15OO9PtNMr3EgEaBcSO9rbK+qCCdVVsOGk1m/vxFutyECCGOU9fcxhUvJ3PFKzuoN5ocvZyTNLa289rWPBbFB5Hws4SBrl759mo7+Pj3mcz510+8m5w/JCqQe9LWbuHDXUUsigsi3M+j2+fEjfAiSyq07G5DRgWJEb42vzk8Oz6Q6qY2DpTKLDohhBhqPthZSIOxnRsX2LY6q8sdS2NxddLw2HcZdjmfED2xWFQOlNQfuyfokhjpR3ObmYwyuYbtr8yjHd+7ngJaAMvGBZNaUEtVY6utlyUGEYtFZU9Brc3m/Z5oUXwQmeUNHJT7ljOSBLSEzbSbLdzywV5yKhp56Zpp/OWCcby2MpH8qmYuen4bKYOsh3FpXQtvJh3h0imhx9pX/em8sYwJ9OSuNfv71R88vcRAdJAODxcnq6wxKlBHbkWj1TZOv00v4/2dhTz830NWOZ4QYnj41/eHqWsxUdvcxvM/Db5WMquT86lrNnHb4pjjvh4TpMPNWcP+Ivtc1CblVALw17UHuWvN/kFdgdwb3x0oo6qxlZWzTq7O6hITrCOvskkyXO2ouLaZw0cbWDI22Obnmh8TiKLApsxKm59LCCEcLa+ycdh8nrW2m3lz2xFmR/mftJlvK0Febty0IIofDpazM0/aPgnHy6tqpLG1/aQOOV0b7DJHq/+yyxvRahTGBPZc/bl0XDAWFX7KkDbWZ5Kcykbqje1Ms/H8rC6/mBqGm7OGd5ML7HI+MbhIQEvYhKqqPPT1QTZnVfLPSyYwNyYAgCXjgvniD7PRuWq5+rUdfLy70MEr/Z///JiFCty17H/tq9xdtDxz5RSqGlv585cH+hRIUlWV9BKDVeZndYkK0tHUZuaolVpcfbSrCEWB9RkV7C2stcoxhRBD2+78Gj7cVcT1c0dz+bQw3tp2ZFAN9W1qbee1LXksjAtkUvjxGzZOWg0TRurtUqFV19xGVnkjty6K4c6lsXyxr4RLX9xGgZ3aHdrCu8kFRPp7MD8m8JTPiQ3yos1sIb+62Y4rO7Nt6NwMWGzD+Vld/HWuTAzVyxwtIcSwtju/hl+9toNF/9nM0+uzHb0cq1i7t5Ty+lZuWhBl1/P+dt4YRni78fC3GdKuVjhcV1LbifcIIXp3Qn3cZY7WAGSVNxDp74Grk7bH544f6U2oj7u0HTzDpOR37ClOi7BPhZY/FTsaAAAgAElEQVTew5lLp4Ty5b4SDM2Dr6uMsC0JaAmbeCPpCO/tKOSmBVFcNWPUcY/FBHux9ua5zBzjz32fpfPQVwcxOTgz7lBpPZ/vLea62ZGE+R7fZikhTM8dS2P5b1oZX+4r6fUxy+tbqWxoZaI1A1qd2TC5FQPfMM2paGRXfg23nh2Nn6cLT67LGvAxhRDdK6pp5obVKdywOmVQt6Zra7fw5y/SCfVx5/YlMdy9LA5nrYZHB1ErmXd3FFDbTXVWl4lhPhwsrbd5xnVqQccF+4zRfvxxcQxv/Xo6ZQYjFzyXxIaMoTcE+WCpgZSCWlbMjECjUU75vK4B29J20H7WZ5QzJsCTMYGnH8JtLQvjgthbVEdtU98r04UQoj+Ssqu48d0U3t1RQIMNWx2nFtSy8o2dXP5yMlnlDYwL8ead7fkYWob2RpjFovLKllzGhXgzrzOR1F7cXbTcuzyOtGIDX+0vteu5hThRWnEdHi5aorq5Zpoe6cvu/NpBfS82mGWVN/Sq3SCAoigsHRfM1uwqmtvabbwyMVikFtTi7+lCpH/3rettYeXMSIwmC5+kFtntnGJwkICWsLofDh7l4W8zOC9hBPeeE9ftc/Qezrz16+lcP3c0b2/P59o3dzl04+TR7zLwdnPmDwuju338pgVRTI/05cEvD1JU07us9PSSjuyghDDrBbSigzouzKwxR2tNShFOGoWVsyL5w8IotmZXsUNaRQhhVe1mC69uyWXZU1tYn1HOukPl7Cuyz3yn/ng9KY+s8kb+ftF4PFycCPJ24+azo/nhYDnbcx0/cLW5raM6a35sIFNGdZ/5NSlcT2u7haxy680b7M7u/FqctQqTOtv6LIwL4ptb5zLKz4Pr30nhyXVZmIdQpvK7yQW4OWu4fFr4aZ8XFahDUSSgZS+Nre3szKuxS3VWl4VxgagqbMmWtoNCCNtSVZXXtuSx6s2dbMup5q9fHuCsRzbwwOdpHCixXvvgfUV1XPvmLn7x0nYOldbzp/Pi2XLv2Tz+y4k0tLbzbnK+1c7lCOszysmtbOLGBWNQlFMnpdjKJZNDSQjV8/j3hzGahnb7ZTG07S/u6JCj7SY5KzHSj8qGVopqBuc898HMaDJTUNPc64AWdMzRam23sCXL8feQwj5SC2qYGuFr18+hcSO9mR7py+rkAqkSPsNIQEtYVXqxgds/2sfEMB+evGLyabO8nbQa/nrBOJ64fBIp+bVc9ELSsUGT9rQlq5Kt2VXcuij6lMPWtRqFJ6+Y3NGScM3+Xm1SphfXoVFgXIj1AlqBOle83JwGHNBqa7fwWWoxS8YGE+jlyoqZEQR5ufKfHzMlY0kIK9lfVMeFz2/jkW8PMyfanx9vn4/O1Yl3dwzOHs+F1c08sz6b5eNHsGTc/2b1XD93NKE+7vzjmwyHB2je21FAdVPbKauzgGNzI2zddjAlv4YJoXrcXf7XdiPcz4PPfj+by6eF8eyGbH7z9u5+zV+0N0OziS/3lXDJ5NBTfg52cXfRMsrPg2wbBwxFh6TsStrMFhbbYX5Wl4lhPvh6OLNZ5mgJIWyopc3M7R/v4+FvM1g2bgQ7/7SYL2+ew/kJIXyxt4QLnkvi4ueTWLO7qN8Z/unFBn7z9m4ueWEbacV13Le8I5D1u/lReLg4MSFUz9lxgbyRdGTIVhGoqsrLm3MJ83Xn/IQQh6xBo1H48/ljKTUYeSPpiEPWIERbu4VDZfVMOkVCsczR6r+cikZUlT4FtKaP9kPv7sy6Q0Ovc4Xou8qGVvKrm0m0U7vBn1s1K5LCmmY2Z8m9y5lEAlrCakrqWvjNO7vx83Th9VWJuDn33FsX4JfTwvj4xpm0mixc9uI2fjhovz67ZovKo98dJtzPnZWzIk773HA/D/5+0Xh25dfwypbcHo+dXmIgJsjruM3OgVIUhahAHTkVA9tIXJ9RTnVTG1fN6MjEd3PWcuuiaHbn17IlWzJohBiIBqOJh746yCUvbqOmqZWXV0zltVWJxAR7cdnUUL5JK6NmkLXyUlWVv649gJNG4W8XjTvuMTdnLQ+cF09GWT2fpDiulL+lzcyrW/KYFxNw2r7ckf4eeLs5sb/YepndJzKazKQVG7q9YHdz1vL4LyfyyKUJJOdWc8FzSVbNMreFT1KLMJosPX4OdokN9iJTKrTsYn1GBd5uTna9OdRqFBbEBrI5q1IyHYUQNlFc28wvX97OV/tLuXtZLC+tmIqnqxOTw3349+WT2PnAEv524Tia28zc+1kaZz2ygYe+Otjr6uADJQZ++85uLnw+idSCWu45J46t9y3i9wuj8HR1Ou65tyyKprbZxAc7B89s575IKahlT2EdN8wbg5PWcds7M8f4s3RcMC9uzKGyodVh6xBnrqzyBtraLceS204UG+SFl5uTzNHqh6733tjg3re/dtZqWBwfxIbD5TZvBS8cb09hRzv+rsCxPZ0zfgSBXq6sTs63+7mF40hAS1hFg9HE9W/vxthm5u3rphPo5dqn108Z5cvXt84lOkjHje+m8sz6bLtsonyxt4SMsnruOSe+V8MtL5sayvkJITz5Y9ZpNyhVVSW9xGDVdoNdogJ1A67Q+nBXIaE+7syLCTz2tSunjyLUx12qtIQYgB8OHmXpk1t4JzmfVTMjWHfnApZPCDlWdr9iZgRt7RbWODAw1J3/ppexOauSu5bFEaJ3P+nx8xNCSIzw5YkfM2062+J03t9ZQFXj6auzoCPwPzHMx6YVWgdKDLSZLSRG+p1yDb86axRrbpqFxaLyi5e2D7r/z7tYLCrv7ShgWoQv40f27jMrNlhHflUTbe1yc2pLZovKxsMVLIwLsvsm5cK4IKqb2o61TxZCCGtJzq3moue3UVjdzOurErllUcxJ7Yn0Hs5cN2c0P94xnzU3zmJRfBAf7Cxk2VNbuOLlZL7cW9Jta7tDpfX8bnUKFzyXxK4jNdy1NJak+87m5rOj0Z0QyOoyLcKPs0b78drWPFrbh167vJc35eLr4czliWGOXgoPnBtPa7uFp9bLbGZhf2mdyWyTThHQ0mgUEiM65miJvskqb8RZqxAZ4Nmn1y0dF0xds0m+52eA1IJaXLSaXt9PWpOLk4ZfzRjFpqxK8qua7H5+4RgS0BID1m62cMsHe8muaOTFFVOJ6UMZ8s8Fe7vx8Y2zuGxKKE+tz+LmD/bYtPWD0WTmPz9mMjFMzwW9bM+gKAoPXzoBf50Lt320l5a27m96jtYbqWpsIyHU+m/m0UE6yutb+72pXFTTTFJOFZcnhh3XW9rFScNtS2JIKzZIWbgQfVRa18INq1O48d1UfDyc+fz3s/n7xRPwdju+fVtssBdnjfbj/Z0FDm/f18XQYuLvXx8iIVTPtbMju32Ooig8eOE4qhrbeGFjzxWq1tbSZublzXnMifY/ZRDp5yaG6ck82mCzOQ5dN2U9Vc1MDvfh61vnkhjpy72fpvHA5+mDbrNsa04V+dXNrOpldRZ0/By3W1SOyA2DTe0rqqO6qc2u87O6zI8NRFFgk7QdFEJYiaqqvLM9nxVv7MTHw5kvb5nTYztVRVGYMdqPZ66aQvIDi3jg3HjKG4zc/vE+Zj26gUe+zeBIVROZRxv4/XupnPfsVpLzqrl9SQxJ9y/i1sUxeLmdvpUudFRplde38llqibX+uXaRVd7AhsMVXDs7Eg+X7gN29jQmUMeKmRF8tKtQZm0Ku0srrsPHw5lwv5OT87okRvqRU9Ho0PntQ1F2eQNjAnQ49zHBan5sIC5OGtlfGuYOlhr4Zn8pCWH6XnfqsrZfnTUKraLw3iAd7yCsTwJaYkBUVeWhrw+yOauSf14y4biKn/5wc9bynysm8efzxvLDwaNc9uJ2imqarbTa4721LZ8yg5EHzh172llfJ/LxcOGJyyeRW9nEY99ldPucruwg21RodWTF5Fb2byOxq2XY5YnhJz122ZRQxgR48uS6LGkzJEQvmC0qb207wtInN7M1u5L7z43n61vnMmXUqQMdq2ZFUlTTwpZB0uP5iR8yqW5s5ZFLE7odoNxlYpgPv5gaxptJRyists378ql0VGe1ctvi2F49f2KYnnaLyqGyepusJyW/hjGBnvjreq5G9te58s51M/j9wig+3FXIFS8nU1o3eIZRr96eT4DOlXMn9H7uRlf//OHYdnB/UR3/+TFzUHwGbsgoR6tRWBhr/4CWn6cLk8J82JhZYfdzCyGGH6PJzL2fpvG3rw5ydlwgX948h6jA3reugo7P0xsXRLHxroW8e/0MZo7x542kI5z9xCaWP7OFrdlV/HFRNEn3LuL2JbEnJRWdztzoACaF6Xl5c+6Qao31yuY83J21XDsr0tFLOea2xTHoXJ145Nvu75OFsJX9xQYSQvUnVXz+3PTOxLjUAqkY6ovM8gZi+tBusIunqxPzogP48dBR6QI0DFksKq9uyeWSF7bRblH503nxDltLsLcb50wYwZqUolMWHojhRQJaYkDeSDrCezsKuXHBGK6eMcoqx1QUhRvmj+Gt62ZQUtfCxS9sY2detVWO3aWmqY0XN+awOD6IWVH+fX79vJhAfjNnNO8kF3S72XOgxIBWozAuxNsayz1OVFDHhURuP+ZomS0qa1KKWRAbSKjPyZlLTloNty+N5fDRBr5JLxvwWoUYzg6UGLj0xW38/etDJEb6se6OBdy0IKrHzLVl44MJ9HLl3UGQPbS3sJb3dhawalZkrwLw9y6PQ6tReOx7+21SGE1mXtmSx6wx/swY3XN1FnCsd35akfXbDlosKqmFtX2aaeSk1XDf8nheXjGN3MomLnguiW05jp9XWFTTzE+ZFVw9IxwXp95fEo4J9ESrUcgeZgEts0Xlrk/289xPOXyaWuzo5bAho4Lpkb7oPXq/KWtNC+MC2V9cN+hm/gkhhpajBiNXvrqDT1KL+ePiGF5dmdinYNOJNBqFeTGBvLRiGtvvX8Q958Rx55KO1oJ3Lovr13umoij84exoCmua+SZtaNwDlda1sHZfCVdOD8fX08XRyznG19OFWxfFsCmzctAkb4nhr6XNTFZ5wynbDXaZGKbHWauwW+Zo9VpTazvFtS3E9bMT09JxwRTXtpBRNrzuG850pXUtXPP6Th759jCL44P54fb5TIvo3b26rVw7K5J6Yztr9w2tamvRPxLQEv3248GjPPxtBudOGMF951g/Er8gNpC1N8/Bx8OZlW/ssuqb0nM/ZdPU1s795/Z/3fcujyM2WMe9n6ZR3Xj84Nv0EgMxQTqblNuO8vPAWav0a47W5qwKjtYbuWr6qYOPFySEEBfsxdPrsoZUhqIQ9tLc1s7D/z3ExS9so7TOyLNXT+Ht66YT7ufRq9c7azVcPWMUGzMrbFaB2hvtZgt/+uIAQV6u3LWsd5VPwd5u/H5hFN+mH7V6osGpfLCzkMqGVm5bcvrZWT8XoncjQOd6rFrWmnIrG6lrNvWq9eGJlk8YwVe3zMHf04WVb+zknk/2sy2nymHtJ9/bWYCmc95XX7g6aYn09xh27YS+2l9CTkUjAToXHvv+MIZmx8yLg45gY2Z5A0t6aMdlSwvjglBV2JotG5JCOIrRZMY0hK/HU/JruOC5JHLKG3h5xTTuXBrbp84YPQn2duPms6O5dXEMPh4DC+osHRtMbLCOFzbmDIoq3Z68mXQEFbh+7mhHL+Ukq2ZHMMrPg0e+zRg0LbYHI0OLiSteSebzPY5PohnqDpUZMFtUJvaQoOfmrCUhVE+KzHTqtZzOROr+jhZZPDYYRcFqbQeH8mficPH1/lKWP72FtOI6Hv/lRF5aMXVQJFZMj/QlfoQXq5MLbFYRmFPRyA2rUyiuddw+juggAa0hqqqxlR122kzsTnqxgds+2sfEMB+evGKyVW9Mfm5MoI7Pfz+byaN8uO2jfby0KXfAb0wF1U28t6OAK6eH9/tDGTouhp6+cgqGZhMPfJ5+bF2qqpLeWe5uC85aDRH+nv0KaH24q4gAnetp53FoNAp3Loslr6qJz/dKZoMQP5dX2cjSJ7fw2tYjXJEYzoY7F3DRpJGnbW3RnatnhKNRFN7b6bgqrbe25ZNRVs/fLxrfq/kSXW6YN4aRejf+75tDNt+kMJrMvLw5l7NG+zFzTO+raRVFYVKYnrQS6we0uuZnTe9HQAs6Pte+vHkOvzprFN+ml3HN6zuZ9egG/u/rQ+wrqrNbOw6jycya3UUsHRtMiP7UswZOJTbYi6zyvn8ODVYms4Wn1mUzLsSbt6+bQV1zG/9Zl+mw9WzI6Ljp72m+jC1NDNXj7+nCxsPSdlAIR7nylWTu/yzd0cvolw92FnL1azvQuWr54uY5LJ8wwtFLOi2NRuHms6PJrmjkx0E+78XQbOLDXYVcMDGk1wlV9uTqpOX+c+M5fLSBt7YdcfRyBq3PUovZdaSGuz/Zz1f7Sx29nCFtf1HHNf+k8NNXaEHHNXx6scFms3aHm64W47H9aDkIEOjlyrRRvvx46OiA1qGqKs9tyGb8334gKdvxnS7ORPVGE3d8vI9bP9xLVJCOb2+bxxWJ4X3eC7EVRVFYNSuSQ2X1Nmkrarao3PPpftYdKpe2uoOABLSGqLe2HeGqV3ew6s1dHLDBht3plNa1cP07u/HzdOG1VdNwd7Ht0D8fDxfevX4GF00ayb++P8yfvzwwoMqhx3/IxEmj4Y4lvatIOJ1xI725+5xYfjxUzprO2VRlBiPVTW02mZ/VJSrQ81imTG9V1Bv56XAFv5wW1nNLtHHBTAzT88z6bNraJQNGCOiozPr9e3toMZn55KZZPHpZQr9bgYXo3Vk6Npg1u4sccjNVXNvMk+uyWBwfxDnj+7bB5O6i5b5z4zlYWs9nNs4o/WhXIRV9rM7qMjHMh9zKRhpb2626ppT8GgJ0LkT6938DydPViX9ekkDqX5fywq+mMmWUD+/tKOCSF7ax8IlNPPljJjkVtq1++iatjNpmE6tmRfTr9THBXhRUNw2bzYBPUooprGnm7nNimRCqZ8XMCN7bUcDBUvteY3XZcLiCMYGejA7wdMj5oWNzd35sIFuyq4ZEtYIQw01bu4UDpfV8tb9kSLX+bGu38Kcv0vnTF+nMjgpg7c1zj81eHOzOTwhhlJ8HL27KGdTzXt7bWUBTm5kb50c5eimndO6EESwZG8zjP9j+mmYoUlWV93YUMDFMT2KEH3d8vI8fDg5sw/9MllZcR7C3K8Hebj0+NzHSjzazhXQ776MNVdnlDbg4dSRV99fSccEcLK3vd1WL0WTm9o/38Z91Waiqyr++Pzyo36OHo11Hajj36a18tb+U25fE8MmNswb0M2Erl0wZiZebE+8kWz9x+L0dBewtrCMxwteuHWtE9ySgNUTduiiGP583lvTiOi54Lomb39/Tr4qdvmowmvjN27tpaTPz1nXTCfLq+YLBGlydtDx95WT+sDCKD3YWcsPqFJr6sUm5t7CW/6aVccP8MQT14mKnN347dwyzxvjz968PUVDddKzFla0qtACiAnUUVDf3qdz6k9RizBaVK6eH9/hcRVG4a1kcJXUtfNwZqBPiTKaqKn/54gBZFQ08c9Xkflfn/NzKWRHUNpv41s7z6lRV5aGvDgLw94vH9yuj6qJJI5kyyod//5Bp9YBRF6PJzEubc5kR6cesPlRndZkYrkdVOyqKrWl3QQ2JEX5WyURzc9Zy/sQQXlmZyO6/LOHxX0wk3NeD5zfmsOTJLZz3zFZe2ZxLaV2LFVZ+vNXJ+UQH6fo1RxIgLtgLi4pdrj1szWgy89xP2Uwd5cPZcR0VzHctjcPXw4UH1x60ezCnsbWdHXnVDm032GVhXCA1TW02qXYUQpxeQXUTZouKyawOmZZkFQ1GfvXaDj7YWchNC6J489fTHTYHsD+ctBp+vzCKtGIDWwdpBYDRZOatbUeYHxvIuJHWn9dsLYqi8MhlE/Bw0XLXmv3Syv4E23Oryatq4ro5kbzx60QmhOq59YO9bOpmPrfoWVqx4dgM3Z5M65yDuztf5mj1RlZ5I9GBOrQD6Mq0rDOBcn0/ql8rGoxc9eoO1u4r5Z5z4njk0gTSSwz8cHBwV9IOF23tFv79w2GuejUZJ63CJzfN4vYlsTj1kCTvKB4uTlw+LZzv0suoqDda7bildS08/v1h5sUE8O71Z9mtY404tcH5Eyh65Oas5Yb5Y9hy79n8cXEMmzIrWPbUFu77NM0mG18AJXUt3PzBXrIrGnlxxVS7Z9ppNAr3Lo/n4UsnsDmrkitfTe7TG5Sqqjz67WECdC78bv4Yq67rP1dMQqtRuP3jfewrqkOrURgbYrsbjOggHe0WlcJezt+xWFTWpBQxc4xfr7O958cEMD3Sl+d/yh42GfhC9NeHu4r4fG8Jty+OZV5MoFWOOTvKnzGBnry7w75tB384WM76jAruWBpDmG//qowUReHBC8ZR2dDKS5tyrLzCDmtSiiiv76jO6k/wqGsodFpxndXWVF5vpKimhcRIX6sds4ve3Zkrpofz3m/PYscDi3nwgnG4OGl49LvDzH7sJ654OZl3dxRYJUt/X1EdacUGVs2K6HdgrqvtyHCYo/X+zkLKDEbuXhZ37Puh93DmvuXxpBbU2r397tasSkxmlcXxp24PbC/zYwJRFM7YtoMvbMzhw12Fjl6GOEN1JQz4ebrw0e6iQZ2NnlPRyD+/OcSyp7ZwoNTAc1dP4f5z4we0Aeool00NZYS3G89vtM31zUB9mlpMVWMbNy2w3v2srQR5ufGPiyewv9jAK1vyHL2cQWV1cj5+ni6cOyEELzdnVl83g+ggHTe+m0pyrmT994WhxUReVROTetkhx8/ThahAT5mj1UtZ5Q39bjfYZXSAJ9FBuj63cz1UWs8lz2/j8NF6XrpmKjefHc1lU8OICvTkyXWZdgsm7C2sJb+qyS7nGkxyKxv5xUvbeWFjLpdPC+e/f5zH1FHWvw+2tpWzImi3qHy4yzrJ+aqq8uDag5hVlYcvSbBrxxpxahLQGuK83Jy5c2ksm+89m2tnRfLF3hIW/nsT//f1IaobWwd8/JK6Fl7fmselL25jzmM/sSWrkn9eMsFqG7r9cc1ZEbxx7XTyKpu49MXtvd5MW3eonF35Ndy+JBadq5NV1zTSx52HL01gb2Edb247QmywF27OtmvFGBXYcUHR27aDO/KqKahu5qrpo3p9jq4qrfL6Vt6z84a7EL2xZncRK9/YaZX3utNJLzbw0FcHmR8byK2Loq12XEVRWDkzgr2FdXZrHdvY2s5DXx0kfoQX180Z2BDxKaN8uXRKKK9tPUJRL4PrvdXabualTbkkRvgyu58VRH6eLoT5uh+rmrWGrhvfRCtU6J1OkLcbv5k7mi9vnsPmexZy19JYaprb+OuXB5jx8Hp+/dYuPtxV2O+ss9XJ+Xi6aLl0Smi/1xgZ4ImzVhnyc7SaWtt5aVMOs6P8mR0dcNxjv5wWxuRwHx77LgNDi8lua1qfUYHe3flYBrEj+Xq6MDnch01ZlY5eit2V1rXw5LosHlx7YFgEbsXQk1vZsXl266JocioabTIPYiCMJjOf7ynm8pe3s+TJzby9PZ/ZUf58efMcLpw00tHL6zdXp47E0V1HagZdBYfZovLa1jwmhen7Vb3uCBdOGsn5CSE8vT6LjLJ6Ry9nUCgztLDuUDlXJIYf2zPQezjz7vUzCPfz4Pp3dg+63/fBrOs+qrcVWtAxRyslv0ZaKveg3miizGAkdsTAk9mXjQtm55EaDM29u6Zed6icX768HYsKn940m3MTQgDQahTuWBpLVnkjX9th9tyh0np+8dJ2Fj6xiV+9toNv0kqH/ViOrpao5z+7laLaZl5eMZV//XKi1fdRbWV0gCcLYgN5f2dBn7pancp3B46yPqOcO5fGMqpz7IA9OtaI05OA1jARoHPlwQvHsfGehVwyZSRvbz/C/Mc38uS6LBqMfduEOTGI9c//ZtDWbuHe5XFsvmchV8/ofVDEVs6OD2LNjbNoM1v4xUvb2Z5z+pYQ7WYLj31/mDGBnr1qudcfF00aycWTR9LWbiEh1LbtH8YEdlRZ9bbV00e7i9C7O/d5GPPMMf7MiwngxU25/WrxeKZLLzZw7jNb+euXB9iSVTnsL3zsKaeigb+sPcDW7CpWvrGr1xfGfWVoNvH791MJ0Lnw9JWT0Vg50/iyqWG4O2t51wY9nrvznx8zKW8w8shlCT3O0uuNe5fHoVHgX98ftsLq/mdNSjFlBiO3L4kdUGu/SWE+7Ldihdbu/BrcnDWMt2OLnwh/T25dHMO6O+bz7R/n8dt5Y8ipaOSBz9OZ8cgGLnlhGy9szCGrvKFX2fs1TW18k1bGZVPD8HLrfxsoZ62GMQE6sof4Rv/b2/Opamzj7nPiTnpMo1H4x8UTqG5q46l1WXZZj9misjGzgoVxgYOmlcfC2CDSiutsnjww2HywsxCLquLurOX+z9Jk00vYXU5FIyP1blyRGI6ni5aPdg+ONuCHj9bz0FcHmfHweu5cs5/KhlYeODeeHX9azIvXTCN+xOBtg9dbV88Ix8/ThRcGWZXW9weOUlDdzI0LoqzS+the/nHJBPTuzty1Zr/cDwEf7ixEBa456/h9FX+dKx/89iyCvFz59Zu7rN42e7jqutaf2IcZ5omRftQb28kZBq2zbSm7M3EtNsgKAa3xIzBbVH7KPH2VlqqqvLw5l9+9m0J0kI61t8xhwgnjPM6bEMLYEG+eWp9llYDF6dbyt68OoHd35o4lsRRUN3PLB3uZ9egGHv0uY1hWbVU1tvLbd1L4y5cHmB7pxw+3z2f5hBBHL6vPVs2KoKKhlR8H2JrS0Gzib18dZEKoN7/5WUKwoij81cYda8TpDY47ZWE1oT7uPP7LSfx4xwIWxAXy7IZs5j++kde25J22bdzpglib7l7If/84jz8sjB5UQ/8mhOr54g+zGeHtxrVv7eKLvacu9fxodxF5lU3cvzzeKpu4p/J/FyuCyu0AACAASURBVE9gdpQ/5yXY9g3fy82ZEd5u5Fb0/AFa29TG9weOcumU0H5Vjd25NJaapjbe3p7fj5We2f79YyYF1U18mlrMqjd3Me0f67j1w718vb+0z4Fm8T/tZgt3rdmPp4uW/1w+iZyKRla9tcvq31OLReXONfsorzfywjVT8fN0serxoaPN3CVTRrJ2f4nNgnJdDpQYeGd7Pr+aMcpqrQJC9O7ctCCKb9LKSLFSFnNru5mXNuYwLcKXOdEDyz6eGKanuLbFahvxKQU1TAn3tennyKkoisK4kd7cf248W+89m+9vn8ddS2NRVZV//5DJsqe2sODfm/jHN4dIzq0+5ayKj3cX0dZuYeWsiAGvKSZYR+YQDmgZWky8sjmXxfFBp/ydSAjT86sZo1idnG+XzPJ9RbXUNLWxeBDMz+pydnwgqsqgnSdjC63tZj7aXcji+CD+duF49hTW8f5OqVYX9pVb2UhUkA5PVycumhzKN2ml1Dvo+rG5rZ01u4u49MVtLH96Kx/sLGRhXBAf3jCTjXcv5MYFUQToXB2yNlvwcHHi+rmj2ZRZabcq+p6oqsorW3KJ9PfgnPF9S1J0ND9PFx65NIFDZfU8/1O2zc5T2dDKitd38mnq4G0B1dZu4cPdRZwdF0S438mtv4O83Xj/hpl4uzuz8s2dZB4dutdZ9pJebGCUnwc+Hr2/V5seKXO0eqOrQt0a40YmhuoJ8nI9bYChtd3MPZ+m8dh3hzlvQggf/24Wwd5uJz1Po1G4e1lHgMmWv+9f7C1hd34t9y2P57YlMWy592zevm460yJ8eX3rERY+sYlrXh8+VVsZZfUsf3oLW3Oq+NuF43jnuhndfv+HgoVxQYT7ufNOcv6AjvPY9xnUNLXx2GUTT0o2nDrKl0smj7RJxxrRMwloDVPRQTpevGYaX98ylwmheh7+NoOF/97Eh7sKj21y9TaIFdnLmUuOEObrwae/n01ihB93fLyfZzdkn5Sh3tjaztPrs5ge6cvScbbdINK7O/PBDTNZGGf7uRdRQZ69qtD6Ym8JbWZLvyvTpozyZcnYIF7ZnGvXlktDXXqxgS1Zldy6KIa9Dy7l9VWJnJswgu05Vdz64V6m/mMdq97cxXs7Cii34rDKM8HLm3PZX2zgH5dM4BfTwnj+V1M4WGLg+rdTaG6zXiXhy1ty2XC4gr+cP44pNuwVvWJmBEaThU9t2H/ZbFF54PN0/DxduXd5vFWPfeP8KEI6h6Jao4Lh09RiSg1Gblvcv9lZP5fQmamZZoXNqMbWdg6V1ttkflZfKYpC/Ahvbl0cw9pb5rLjgcU8fOmEjplsyQVc/doOpv1zPXd8vI//ppUdC/aaLR3tI2aO8bPKjWlssBdFNS1W/b2zp9e35lFvbOfOZbGnfd4958Shd3fmwbUHbD7DZn1GBU4ahQWxjmvtfKIJI/UE6FzYeAYNqv8u/ShVjW2smhXJZVNDmRcTwL++z6TMYJs5tUKcSFVVcisaj7UZv3pGOEaTha/22b690s8dKDHw5y/SmfHwBu79LI0GYzt/OX8sO/60mGevnsKsKP8hVSnUFytmRuDl6sSLgyDzOqeigate3UFasYEbF0QNydlky8aP4LIpobywKdeq80271DS1seL1nSTlVPHA52nsK7L+Oazhx0NHqWxoPW1iUaiPOx/ccBauThqueX1nr7uynKnSig19qs4CGOXnQYDOVeZo9SCrvAF3Zy1hvu4DPpZGo7B0XDCbsyq7Tbavbmxl5eu7+DS1mNsWx/Dc1VNwdzl1Qvai+CAmh/vw7AbbzHyvN5p45NvDTAr34YrEjr00rUZhYVwQr65KZPv9i7h7WSz5VcOnamt1cgEtbWa+vmUu180ZbfXuNPak1XSMd9h1pIbDR/uXlLgjr5oPdxVx/dzRJ1UJdrl3ebxNOtaInklAa5hLCNPz7vVn8eENMwnxceOBz9NZ+tSWIR3EOpHe3Zl3fjODy6aE8uS6LO77LO24suNXt+RR1djGn84bO6xuuKICdeRWNJ52c01VVT7aXcikcB/GhvS//ccdS2OpN7bz+lYZ5ttbL2zMwdvNiRUzR+HmrGXJuGAe/+Ukdv15CZ/cNIvr5oymsLqJv3x5gLMe2cDFnW3DsnvZNuxMdai0nmc2ZHP+xBAumNgxn2HZ+BE8deVkUgpq+N3qVKtc0G7PreKJHzK5cNJIVlmhkuV0xo/UM3WUD+/tKLBZS6vVyfmklxh48MJx6N3732auO+4uWu5dHkdasYEv9pYM6Fht7RZe3JjLlFE+zIsJ6PkFPUgI1aMokFY08IDWvsI6LKrt52f1xwi9G9ecFcHb181g74NLeXnFVBaPDWJjZgU3f7CHaf9Yz6o3d/F/Xx+kpK6FVbMirXLerqBYb+c5DibVja28mXSE8xNCGD/y9JsgPh4u3Ls8nt35tXy5b2A/4z3ZkFHO9Eg/q/+eDoRGozA/JpAtWZV2G77taO8k5zM6wJO50QEoisLDlyTQbrHw4NqD8hkt7KK8vpWmNjNRQR0BrYRQPWNDvPlod6HNz200mXl/ZwEXPpfEBc8l8WlqMcvGB/PJTbNYd8d8fjtvjE2q1gcbvbszq2ZH8N2Bo+RUOKZKxmgy88QPmZz7zFYyyup5+NIJXGWj9vn28LcLxxOgc+GuNfutugFtaDGx8o2dHKlu4sVrphLs7cbN7++htqnNauewlneTCwj3c2dBDzPJI/w9ef+3M1FVlWte2ynZ/6dQ1dhKSV0Lk/owPws6ksOmR/pKhVYPsssbiQnWWS2wsWz8CJrbzGzPPb7qP6u8gUte3Ma+4jqevXoKdyyN7fGciqJwzzlxlBmMfLjL+p+NT6/LprqplX9cPL7btQR7u3HLolNXbf03rWxIVW2pqsqmzP9n7zwDo6rWLvycmUnvIb33BkmAFDqhg4hSlF5EFFTEXrFdr1cUG4oKV0QFEUXQC4JSpIYaSggkgfSE9E56SJ3M9yOED4GElJlkEs7zM3Nyzk5m5py99/uutfIZ6m6GpxIy09SBGYH2aMkkbGpHvEN1nZw3tkdjb6rDC2Oab360MdbhieHKdawRaR1iQeseYZBrL7Y/NZj1CwIx0JZRJ+/eRaxb0ZRJ+GyGP8+OcmNbeCaLNp6jvLqO/LJq1h9L4X5fa5UqLLoCV3N9ymvqKShv3korIr2EhLwKZndw4dPbxoj7/az54cSVey5Doz0k5pWz73IuCwc73ZZRI5UIBDmZ8sZEb468PIIDLwznlevZLZ/8Hc/Yz48x8tNQPtgTKwYn30JtfQMv/RaJkY4m/5nc5x+vPeBvw8cP+3MiqZClP0d0aPKYV1bNs1su4Gymx8ppvp1SCJ8/yJErhZWcSr6q9HPnllbz2f4Ehrmb8YCfauxQJ/vb4m9vzMd/x7U5b0+hUJCUX8F3x1OY9/0ZskqqlKLOgkZ7VhczPaKzOt6ley61CIkA/R3atmDubPS0ZEzoY82qGX0Jf3MMW5cM5JHBjqRfreTHsDSsjbSVplb2sGzcaO2OdjjfHE2mqk7OC2NbVmc1MTPQHn87Iz7YE6cyy9iMomsk5FUw2lv1Ku+2MsLLguJrdSrpqlc3ojNLuZBewvyBjjc2MBx66fLCGA8OxOSx71JuF49Q5F6gqVHA9XpuriAIzA6251JWmcot8F79PYo3d1yiTt7Avx/szdk3xrBqRl+CnEx7VHNga1g0xBktmYS1ocmdfu3Q+HzGfX6Mr48k8YCfDYdfHsHcAY7d+j0w0tXgo4f8SMyv4PODysmmrKipZ+GGsyTklbNufgATfa1ZO7c/BeU1PL/1olrlH8bnlnPmShHzBji2qkDgZqHP5scHUFUnZ/b606JK+A5EtSM/q4lAJ1Myi6vILRXdUpojPq8cdyXkZzUx0MUUfS3ZP2wHj8Tn89DaU1TVNrB1yUAe9Ldp9fmGuJkxyKUXa44kKdUxIi63jB/DUpkV5IDfXYqlt6q2XhrbqNp6+pcIBq88xOcHEtTqPtQcCXkV5JRWd4rbVGdhrKvJ5L427IjIarPb1JojSaQUVvLBVN8WlYIAT4S4YGWoPMcakdYhFrTuIQShUeK7a9lQ/nqm+xexbkUQBF4c58nHD/kRlnyV6d+E8e6fl6lvaCze9TTcrndsthRkuvVcOrqaUia1YVLQHC+McaeqTs66Y6JK626sDU1GV1PKozeFRt4JQRBwtzTg6ZFu7Hx6CGfeGM37U/rg2EuPDSevMPHL4/xr56Uuy0tQN74+nEhsThkfTvO9Y2fwwwF2rJjah8Nx+Ty75UKzGUItUSdv4JlfLlBZI+ebeQHoacmUMfS7MtHXGlM9TTaFpSr93P/+8zJ18gben9JHZZsgEonAO5N8yCurYd3Ru2/6XKut52BMHm/9Ec2wj48wZtVR3t/d6E/98jgPpdqt+dsZE5lZ2mFVRXhaEV5WhrcVqdUZmVTCAJdevHm/D0deHsHBF4ez7YlBSssAc+ylh6ZMQmI3U2jllVWzKSyNqf3sbjxL74ZEIvDe5D4UVtTwxUHV5H8cjG1c3I9Ro/ysJoa7myER4Eh8QVcPReVsCktFV1PKQwF2//j5Y0Od6W1jyDu7LosWzCIqp8lizM38/+9Rk/1t0ZJJVKrSupxdyq7IbJ4McWXvc8N4ZLATRrrd57mnbHrpazE72IGdF7M7TSGTV1bN0z9HsHDDOWRSgV8WD2DVzL49JqNshKcFs4Pt+fZYCufTOtbNXlUrZ9HGc0RllvLV7P6MvL4R62dnzDsP+HA0oYCvj3S9ZWQTm0+noSmTMD2w9c2m3taG/PRYMKXX6pi7/gz55WLx5WYiM0qRCDRrB9YSTTla4R38HPZUSq7VUlBeg6dV6+bKrUFLJmWEpzkHY/OQNyj44cQVHtt4DjtTXXYtG9KuJvSXx3tQWKG8zHeFQsE7Oy9joC3j1fFt20e0NNTmmdGNqq0NjwbRx9aI1YcSOZGk/jm0odetxUd4qo/tuTJYMMiJqjp5m7LW4nPL+W9oMtP62TLsLmpaaMzdfO0+5TjWiLQesaAl0uOYEWTPDwuDyCyuYk90LnMHOOLYq+cU7ppo8tRPbmYjsby6jj8jc3jQ3wZ9JWzKu1kYMKWfLT+eShUzn1og/eo1dkVmMyfYAZM22rFYGmozb6AjPy4KJvzNsTwyyIlNp9MY89lR/orKvqdtjiIzSlgTmsy0/rYtqkvmDnDknUk+7Lucy0u/RbbZHuuTv+M5m1rEyod8cVdCxlBr0ZJJmRlkz8HYPLJLlNd9ueNCJnsv5fLsaHeV3wcDHE140N+GdcdSyLrlb2hUYZU3qrC+O0Pffx/g8U3hbI/IwsvKkPen9OH4qyM5+GIIy0YpR53VhJ+dEQXlNeR24L5VL2/gQnrJjYVvd0QQBNwsDO4YQN5epBIBN3P9G4HR3YWvDicib1Dw/Bj3Nv2ev70xs4Ls2XgqVSWqtEOx+bia66lls5GxriZ97Y052sNztIora9kVmc2Ufra32T7KpBJWTvPjakUNK/eKPvkiqiW5oAIDbRnmBv9fxDDS1eB+X2t2XshWWXbh5wcSMNSW8dQI126tBFImS4a7IBFg3THVqrTkDQo2nLzC6M+OciA2j5fGerD3uWEMdu24BbO68eb9PtgY6fDyb1FU1bbPerC6Ts6Sn8IJTy3i85l9mdDH6h+vzx3gwNR+tnx+MIETiV2/mVxRU8/2iEwm+Vm32bLTz86YDY8GkVNazfzvzlKkhlaKXUVUZgluFvrtakL0tjZER0Mq5mg1Q0Je4z6TstfE43pbUVhRy8INZ3nvrxhGe1vy+5ODsDFuX05XgKMpIz3NWXc0RSkNR7siszl7pYhXxnu2eT+nCalEYKSnBd/MC0BbQ8Kh2Ly7/1IXcyQ+Hy8rA6yNOp6Xpk70sW1bvIO8QcHr26Mw1NHgrUk+rb5ORxxrRNqHWNAS6ZEM9zBn2xODmDvAoc0bVt0FS0Mt9LVkJBfcOXTyz8gcqurkzFSiz/rzoz2QNyhYo0adburGN8eSkQoCi4e7dOg8RroavPtgb3Y+PaTRn/mXCzyy4RxpV7tvyGh7qa6T89JvkZjra/GvB3rf9fhFQ515dYInOy9ms3x7VKtl3/su5fLtsRTmD3Rkcl/bjg67zcwJdkABSvMA33cpl5d/iyLY2ZTFwzr2eWwtr93nBcDH+xoncgdi8nhzRzRDPzrCmFXHeH93LHll1Twy2JGfHx/AhXfG8t0jgcwb6KjUQsvN+Nk32kREdiBHKzannGu1cgLUMD+rq/Gw1CehG1kOZhRd49ezGcwMsm/XZ+6V8V4YaMt4Z+clpTYZlFfXcebKVbVUZzUx0tOCqKxSCnuw9fC28Axq6huazU70tTPisaHObDmbzpkU5VvEQmNjzPaITKU2N4h0P5LyK3A117+tqDQzyJ7ymnr2RCvf+vJCejEHY/N5IsRVrXL8uhprIx0eDrBjW3gm+Spq6ovKLGHymhP8+88Y+jkYs//54Twz2h0tWcs2R90VfS0Zn0z340phJR/ta3uDQG19A0//HMHxxEI+esjvjhZlgiCwYmof3C30efbXC11u17fjQhaVtXLmD2xfNm+gkynfPxLIlauVLPjhTJcohbNLqpj+zSle/18U+y7lqMyCubUoFAqiMkvvagnXHBpSCf0cjMUcrWaIv96w5qHkgtYIT3M0pALHEwt5MsSVdUpwRXlpnCelVXV8f+JKh85TXl3Hit2x+NoaMSvIoUPnAtDWkDLUzYyDsflq3ZxcXl1HeGoxIT1MndXEI4OduFJYyfFWKOU2n07jQnoJb0/yblPzQVsda0Q6jsoLWoIgTBAEIV4QhCRBEF5X9fVERJrwsTFkxVRfjHV7ZmixIAi4muvdsCS5lV/PpeNlZUBfe+XlvTj00mVGkD1bzqaTWSwG095Kbmk1v4dnMj3QDktDbaWc08/OmD+eHsK/H+xNRFoxYz8/xleHEqmpV16Qsrrz+YEEkvIr+Ohhv1ZvsCwd4XYjU+/dPy/fdQKZWljJK79F4m9nxFuTvJUx7DZjb6rLKE8LtpzN6HCAbGh8Ps9sicDX1ogfFgahKeuc/hVbYx2eGO7CzovZ9HvvAIs3hfPHhazr9+M+nHx9FAdeDOHN+30Y4mbWKRs1PtaGyCRCh7J/mha63VmhpSrcLQ3ILq1WyabGT6fTWBuapFQv8tWHEpFKBJ4Z1b5mF1M9TV4e58mZK0XsisxW2riOJxZSJ1cwWo0LWiM8LVAo4FhCz7QdlDco+Ol0GgOcTfGyMmz2uBfGemBnosPyHdFU1yn3WXwxo4QH15zgxW2RDF55mImrj7PqQAJRmSWiJ/89RnJBxQ03hpsJdjbFxUyPX5XU/HIzn+1PoJeeJgsHOyn93N2dJ4a7Ui9v4LsObpbeSll1Hf/aeYnJa06SV1bDV7P7sWlRsFoqdZXNYFczHhnkyMZTqYS1IUO2Xt7A81svcCgun/9M6dOifZ+upoz/zgugpk7O0z9HUNcOO3JloFAo2ByWhq+tUYfW5oPdzFg3L4D43HIWbjhLRSerAFbujSMyo5TdUTk8uTmCfu8dYOa6MP4bmkxsTlmnb9hnlVRxtbIW/3bkZzUR6GRKbE5Zp/8vuwOJeeXoa8mwMVLOvkYThtoa/GdyH9bM6c/r93m1Kk/ubvSxNWKirxXfH0/pkILxy0OJ5JfX8N7k3kiVMC6A0d6WZJVU3SgQqiMnk65S36C4Ydva05jQxwozfU023cWWMrukio/3xTHcw5wp7WhwbsmxRkT5qHSHSxAEKbAGuA/wAWYLgtB6zZ6IiEiLuJrr39Fy8HJ2KVGZpcwKsle6Xcgzo9wQBIGvDokqrVv57ngKcoWCJ0NclXpeqUTgkcFOHHophLE+lnx2IIH7Vh/nVHLX22eomvNpRXx7PIXZwQ5tzlV6YawHS4a7sCksjQ/3xjW7yKquk/PUzxFIpQJr5vbv0m7YeYMcKayo4e/L7e+8PpVcyBM/ncfD0oAfFwUrxXK0LTwR4soD/jY8OsSJXxYP4MI741i/IJC5AxyxbaeVREfQ1pDiaWVAVGb7FVrhaUXYGuv0OAsGZeB5vWtT2TlaNfVyPtobx8f74nli83mlWDck5VewPSKT+QMdserA4nx2sAO+tkZ8sCdWaRsgB2PzMNbVoL+D8ppQlE1vG0PM9DUJ7aE5WqHx+WQWV7FgkFOLx+lqylgx1ZeUgkrWKlGxfiq5kLnrT2OgLeOXxQNYfp8XelpSvj6cyINfn2TQykMs3x7Nodg8pRfSuhsHY/JY+vP5HpsxWl5dR15ZzR0z/gRBYGaQPeFpxSTlK29zLCz5KieSCnlqhGun5Yd2J5zM9HjA34bNp9MoVoLdm0Kh4M/IbEZ/dpRNp9N4ZFDjPP8Bf5t7yurxtfu8cOqlyyu/R7bqeSpvUPDK71Hsic7lrfu9W6V2cjXX56OH/YhIL+HDPV1jF3v2ShHxeeXMH+jY4fd3pJcFX83uR1RmKYt/DG9XZnB7OJ9WdD1fz4WId8aydclAFg93oay6no/2xXHf6uMM/PAQr/4eyZ7onE5RkDXN7dur0ILGZrUGRaNCVeSfJOSV4255u1JYGcwKduB+P2ulnvPFsR5U1cn5pp3qmMS8cjacTGVmoH27sryaY7RXY5HoUKz62naHxudjoCUjwLFnNm9qyaTMDnbgcHx+s3mYTdlpcoWCFR3IHm9yrPlItCdXOapu2Q4GkhQKRYpCoagFfgUmq/iaIiL3DK4W+mSXVt+20bf1XAaaMglT+infNs3aSIe5Axz4PSKTK4X3nv1dcxRV1vLzmXQm+9uozDrN0lCbNXP6s/HRIOrlCuasP8OLWy/2WPuna7X1vLQtEltjHd68v+2qKUEQWH6fF48McuTbYyl8fiDhjse9s/MSsTllfD6zL3YmqnnvWkuIuzkOprr8FJbWrt8/n1bE4z+GN57jsQFdYhmkpyXjq9n9WD7Rm8GuZp2mDmsJPztjojJL2tU5qlAoOJdaLKqzmqHJhkTZtoNhyVepqKnnAX8bDsXm8fA3YR3udPv8YAI6GlKeGtGxpgOpROC9yb3JK6vhy0OJHToXNG7QhcYXMMLDHJm0678vzSGRCIR4WHAssaDN+YTdgR/D0rA01GJc77ur5EI8zJnS14b/Hk1WSobcwZg8Fm44h62JDr8/OZjBrmY8EeLKb08OJvytsXw23Z8ARxP+jMzmsR/D6fvefh7/MZyt59LJL7+3ck1/PJXKkp/C2ROdyzehPdPSpclO3NX8ziqdhwLs0JAK/Ho2QynXUygUrDoQj6WhFvPaaYd2L7B0hBvXauVsuEuH991IyCtnwQ9neWbLBSwNtdj59BDefbA3htr3ns2jrqaMT6f7k1VSxYrdsS0e29Cg4M0d0ey4kMUr4z15vA122pP8bFg42IkfTl5hT3ROR4fdZn46nYahtowH7mCN2B4m9LHmw2m+hKVcZWMHP4+toaFBwXt/xWJpqMUTIa5oSCUMcOnFaxO82PvcMM68MZqPH/Yj0NGUvZdyWfpzBP3/c4AZ34Sx5kgSl7JKVaLeiswsQUMq4GXdfku8fg4mSAQ4J+Zo3UZCXgUeFp2XKd1R3CwMmNK3fZnvTcUMXU0pr07wVOq4LAy18bMz4qCa5mgpFI3rkCFuZmio8Tqko8wZ4IBEENh8+s77LHsv5XIwNo8Xx3p0aD/P1liHJcNd2BWZzfk00c5Ulaj602oL3DzTzrz+sxsIgrBEEIRwQRDCCwp6ZseniIiqaFroptyUo1VdJ2fHhSwm9rFSmd3i0hFuaEolfLwv7p6yvmuJDSevUF0vZ+lI5aqz7sQITwv2vzCcZ0a58WdUY3fnL2fSe5wd0cf74km9eo2PH/Zrt8pIEAT+9UBvZgba8+XhpNvy37ady2BbeCbPjHJTC4m9RCIwb6ADZ1OLiMsta9PvRmeWsvCHc1gaavPz4wPaHDjdk/G3M6Ksup7Uq223Ss0oqqKgvEbMz2oGOxMddDSkN4KjlcWBmDx0NaV88rAfPywMIrPoGpO/PklEOztoL2c3WuQsGupML32tDo+vn4MJMwPt+eHEFRLbWdCorW/gr6hs5n53mqLKWsb4qK/dYBMjPM0puVbHxYz2W3iqIykFFRxLKGDuAMdWL+bfnuSDvpaM5dujO/T8/eNCFk9sPo+3lQFblwy6zbLYVE+ThwLsWDs3gPNvj2HTomBmBtoTm1PGa/+LJnjFISavOcnXhxO7xPKps2hoULBidwz/2nWZUV6WjdZCJ650eS6OKmhyX3C9g0ILwExfi7E+lmy/kKWUefixxELOpRazbJQ72ho9M7NJGXhaGTDWx5KNJ6+0SZ3b0KAgIr2Yj/bFMfqzUMZ9fowL6SW8+4APO58e2iF1SU8g0Kkx63XL2XSONmNpq1AoeO+vGH49l8GykW48PdKtzdd5Y6I3/RyMefX3KFKasexXBfnl1ey7lMv0QHt0NJX3/ZoeYMdIT3NWHUhQeebizsgsIjNKeHW81x0VnJaG2swItGfN3P5ceHssvz05iCdDXKisreeTv+OZ9NUJgj84xKr98UodV3RmKV5Whh1y19DXkuFtbUh4N87RqqmXczyxQKmf68KKGooqa/Gw6j4FLYDnxzRmvn99uG0K+r+icghLucor4z2Vsk64ldFellzMKFHLRuT4vHJyy6oZ6dUz87OasDbSYZyPJVvDM25zOii9Vse/dl2mj60hi4Y4d/haT4a4YmGgxXt/xfa4PTp1QtUFrTtp9P7xbioUim8VCkWgQqEINDfv2V8gERFl02RFcnOO1p7oHMqr65mphBDL5jA30GLxcBf2Xspl0IeHWbE7ptksr3uB8uo6Np5KZbyPFW6d1MWkrSHlpXGe7H1uON7WBryxI5qHvzlFTHbbiiDqyqnkQjaeSmXhYCcGu5p16FwSicAH03yZ3NeGT/6OvxEWezm7lLd3XmKI+jxlEgAAIABJREFUWy+eH+OhjGErhekB9mjKJM12D92JuNwy5v9wBkMdDX5+fAAWSspw6yk0bRa1J0dLzM9qGYlEwN1Sn0QlWl81NCg4EJNHiIc52hpSRnhasH3pYHQ1pcz69jQ7L2a1+Zyr9idgqC1rU0f33Xh1gie6mlLe2Xn3nL6bSS2s5MO9sQz68BDLfrlARlEVr03wYmIf5VqvqIJh7mZIBDgar762Ke1h8+l0NKQCs4Kbz2K5lV76Wrx1vw/n04r5+Uz7VLU/haXywraLBDuZ8vPigZjcpRFBSyZluIc5/57chxOvjWTvc8N4aWzj8+vT/Y12xCGfhPLRvjiVdcR3BdV1cpZtiWD98Ss8MsiRdfMDWH6fNwpF43e7p5FcUIFMIuDQQofwzCAHiiprORDTsY5vhULBZ/vjsTPRYWYLWUQijTw90o2y6vq7ztFq6uUcic9n+fZoBnx4iGlrT/HtsRSsjLR59wEfjrw8goVDnJWW0dLdeXGsB24W+rz2e9RtVnUKhYKV++LYeCqVx4c689K49s3ZNWUS1szpj4ZU4KnNEVyr7ZzMpK1nM6hvUDB3gHLX5oIg8N7kPjQoFLy767JSz30z12rr+WhvPH52RkxthfuLTCohyMmUV8Z7sfvZYZx9czSfTvfHy8qALw8n3ZhXd5SGBgXRmaX4dSA/q4kgJ1MuZpR0WcZaeyi5VsuOC5k8/XMEAf85yPzvz/LYj+FK2zxvUp97WN65sUJdacp8//VcerPWcrdSWVPPit2x9LYxZM4A1aiUR3s35tAejlO/+fORuMZGghCPrm/uVTULBjlRcq3uthzklftiKaqsZeU0P6W4ZehpyXh1gheRGSXsjGz7ulWkdai6oJUJ3DwztgOUl6AtInKP42Cqh1QikHRTdsmvZzNw6qXLQBfVqgmeH+3Oj4uCGeBsyoaTqYz+7Cgz1oWx40LmPZft8NPpNMqr69vVLdhR3Cz02bJ4IKtm+JN29RoPfH2CFbtjuvV7UFFTzyu/ReFspsdrE7yUck6pROCz6f7c18eK//wVw7fHkln6cwQmupqsntVPrTYUTPQ0ecDPhh0RWZS3Ih8kuaCCed+dQUsmYcvigdh0QU6VuuNuqY+WTNKuHK3wtCIMtGXdynKjs3G3MCBeiZaDkZkl5JfX/MP6zd3SgD+eHkJfO2Oe+/Uiq/bHt3rRHpFezKG4fJ4IcVWqDWcvfS1eGe9JWMpV/opq2cKoSY01Z/1pRnwaynfHrxDoZMKPi4I5/upInhrhqpRQbFVjrKtJfwcTQpvpou+OVNbU89v5DO7rY42FQduaAab1t2WYuxkf7Ytvs1JozZEk3t55mdFeFmx4NKjNSmRBEPC2NuSZ0e7sfHoIZ98YzYfTfHEy0+PbYylM+upEjyhuFVXWMmf9afZeaszMeffBxqB2e1NdHhnsyO8RmcTm9IxmniaSCypwMtNrUS04zM0MW2Mdtp7rmO3g/pg8ojJLeW60u1pYBKs7fe2NGepmxnfHr9yxw/uPC1k8/XME/d87wKMbzrHrYhZBTiZ8MbMvEW+N5efHB7JwiDPmBspXAHRntDWkfDbdn4KKGt77M+Yfr31xMJF1R1OYP9CRN+/37lCej42xDqtn9SMhv5y3dlxS+X2xXt7AL2fTGeZuhou58gsD9qa6PDfag/0xeezvQP5uS6w7mkJuWTXvTPJp1zzFwkCbhwPs+HZ+IGb6mqw+2HGrZoArVyspr6nHXwkKx0AnE67VytX+WZJ+9RrfHU9h1rdhBLx/kBe2RnI2tYgH/G14YrgLVworOZGknIztJivxJmvx7kRT5ntrbcG/PJxIblk1703uo7I9gd42hlgbaXNYDXO0QuPz8bIy6FC+cHdhoIspHpb6bApLvXH/P51ylS1nM3hsqDN9bDteIG9iWj9bfG2N+GhvfKc1UNxrqHrWeg5wFwTBWRAETWAWsEvF1xQRuWfQlElwNNW9oY5KLqjgbGoRM4McVB4o3JilYc5/5wVwavkoXpvgRV5ZNS9sjWTAB4d4d9dlpW5wqitVtXK+P36FEA9zfJXQIdYeBEFgWn87Dr0UwoxAe9Yfv8JqJeS6dBUrdseQU1rFp9P9lGrNIZNKWD2rH6O9LPhgTxxZxVV8PacfZiqwFego8wc5Ulkr548LLXf0pF+9xtz1ZwD4+fGBOPTq2gwwdUVDKqG3jWE7FVrFBDqadItiQ1fhYalPfnkNpdeUEwB+ICYPqURglOc/LfhM9TTZ/PgApgfY8eXhJJ7ZcoGq2rsX7z/bH4+ZviYLBzspZXw3M2eAI71tDFmxO/a2PEu4XY2VdvUaL4/zIOz1UaybH0iIh3m3+2yN8DQnKrOUQ2qaBdBW/riYRXl1PY8MbntXriAIrJjiS31DQ6uVegqFgpV74/jk7/jGHK55AUqxebMw1GZ2sAObFgUT/uYYPnqo+xe3Ugsrmbb2JJeyy1gzpz+PD3P5x/x22Uh3DLU1WNnDgreT8iuazc9qQiIRmBFoz/HEwlZ3od9KQ4OCVfsTcDHTa5XyQqSRp0e6UVhRw7bwDLJLqvjxVCpzvztNwPsHeH7rRc5cKeLBvrZsWBjE+bfHsnZuAFP62WKke+9lZLUFf3tjngpx5X8RmTeUh/8NTWb1oUSmB9jx7wd7K2V9O9zDnOdGu7P9QhZblJRD1xwHY/PJKa1mvgqz6R4f5oynpQHv7rp8x3lIR8guqWLdsWQm+VkT2EHrbR1NKUuGu3AiqVApuTJNc3o/+46vvwMdG/82dcvRamhQcCG9mE/+jmPc50cZ/skR3t8dS3FlHU+GuPDH00M4s7yxmeXFcR700tNkUztzmG8lIb8CIx0NLLph8d3aSId5Axz5X0TmXV2EkvIr+P74FR4OsCPAUXVuHIIgMMrLguOJBWoV2VFeXcf5tGJGevV8dRY0vg/zBzlxKauMCxklVNfJeWN7NPamOrygZMceiUTgnQd8yC2r5ttjKUo9t0gjKi1oKRSKemAZ8DcQC2xTKBSq00OLiNyDuFro33hQbz2XgUwi8FBA5y5KLQy0eWqEK0deGsEvjw9guIc5v5xJZ/wXx5i69iTbwjN6bFfC1nPpXK2s7RJ11q0Y62ry4TRf7vezZnNYWqvUPepGaHw+W85msHiYCwGOylcZasokrJnbn1lB9qx8yK/DizNV4W9nhK+tEZvC0prdeMwuqWLOd6eprpfz02MDbliQitwZPztjLmWVUd8GO5HiylqS8ivU9nOiLjT56ycoyXZwf0weA5xN77j5pymT8PHDfrw50Zs9l3KYsS6M3NLmg59PJRdyMukqT41wu2PuQ0eRShotf3LLqvnycGMjwc3ZWHdSYy0b5d6tbUFnBNnjZWXAYz+G89Yf0a0qKqorCoWCn8LS8LE2pL9D+zYyHHrp8sIYDw7E5LHvUssd8vIGBW/+cYlvjiYzb6ADq2b0VUkAt4meJjODundx63xaMdP+e4rSqjq2LB7ARN/bLTmNdDVYNtKNowkFnEhUTld6c6QWVjLy01DCkq+q9Dp18gbSrl7DtRVqjumBdkgE2Bbevk35P6Oyic8r5/mxHkqx2LlXGOhiSoCjCe//FcvglYf5167L5JZWs3i4C9uXDr6hlhzpZSFmkrWRZ0e742VlwPLt0Xx5KJGP9sXxoL8NKx/yU2rzxzOj3Bnmbsa7uy4T3Q71fmvZfDoNGyNtRqlws1hDKuGDaX3ILq3m8wPKtWD9eF8cDQp4/T7lOGbMG+hILz1NvlCCSisyoxQdDSluSlC+WRlpY2eioxY5WtV1cg7H5bF8exQDPjzE1LWn+OZoCr30tHh7kg9HXxnB3y8M55XxXvS1N77xvdCSSZkVbM/huDwyi9vX5HAziXnleFjqq7xJWlUsHemKtoa0xe+E4rpdp46mVGmf8ZYY421JZa2c0yld/zlr4mRSIfUNCkZ43DvxP9P62WKgJWPTqVTWHEkipbCSD6b6KrWRuokgJ1Pu97Pmm6PJPTLztatR+cxVoVDsUSgUHgqFwlWhUKxQ9fVERO41XM31SS28RnWdnP+dz2S0t0WbLXOUhUQiMNjNjK9m9+P0G6N5635vSqvqePX3KAasOMRbf0RzKUt1i4bOpra+gXXHUgh2MiXYWX02vJ8c7kp5TT2/nEnv6qG0idKqOl7/XzTuFvq8MFZ1mVbaGlJWPuTHwwF2KrtGRxEEgfkDHUnMr+DMldsnvfnl1cz97gyl1+rYtCgYb2vDLhhl98Lf3oiqOjlJbcj7O5/W2KkZqMKOvZ5Akx2JMlS5KQUVJOVXMM7HstljBEFg8XAX1s8PJKWggslrTtxxQ0qhUPDp3/FYGWorPbviZgIcTXg4wI7vj1/h3V2Xb6ixUgu7vxrrTlgYaLNz2RCWDHdh8+l07v/quEo3BFXJ2StFxOWW88hgxw5t2jw21JneNoa8s+vybfkvTdTJG3h+60V+OZPO0hGu/Gdyn075PLS2uKVOGZx7o3OYs/40htoyti8d0mKDy4LBjtiZ6PDBHtUFb9dff++uFFYSquL8uPSia9Q3KFrVpGJjrEOIhznbwjPa1KwBjX/TFwcT8bIyYNIdioUizSMIAm9M9Gagay9ev8+LQy+FcOilEbw2wYv+DqKiuyNoyiSsmtGX0qpaVh1IYHxvSz6b4a90GzCpRGD1rH700tfkqZ/PK01hfjPJBRWcSCpkzgAHlReMAxxNmR3swIZTqUpba0ekF/PHxWyWDHPBzkQ5DhC6mjKWDHfheGIhEekdU0NFZZbQx9ZQaf/bICdTwtOKu6TJo7a+gQMxeSz7JYJ+7x1g0cZwdl3MJtjJlC9m9uX8W2PYsmQgjw11xrFX8+rdpvynnzu4B6BQKEjIq8C9G9oNNmGmr8WjQ5z4KyqnWSvJvZdyOZFUyEtjPTrFsWWQay90NKRq5XBwJK4AAy0Z/e+hta6eloyHAuzYHZ3DN0eTmdbPlmHuqivovT7BiwYFfLwvXmXXuFcRW7FERLo5ruZ61Mob+OHkFa5W1jIrWHWbdm3BVE+Tx4e5cOjFELY9MYixPpb8Fp7JpK9O8MBXJzgcpz4P8vay40ImOaXVLB3p2tVD+Qe+dkYMcevF9yeuqJWk/W78+8/LFFTUsGpGX7GjFXjA3wYjHQ1+uiV4vKiylnnfnSGvrJqNi4LwU4J3/L1A0/8pKqP1C/1zaUVoSAX87cX/cUvYGGmjryUjMa/jBa0mm6Gxva3ueuwYH0t+f2owMomE6etOsSf6nzlWR+LziUgv4ZnRbiq/p7x+nxe6mlJ+Op1GoJMJGx8N4lgPUGM1h5ZMyhsTvfnl8QFcq5Ezde1J1hxJQq6igoKq2BSWhpGOBg/6d0zZLpNKWDnNj6sVNXe0v6uuk/PET+f5MzKb1+/z4tUJXl3S9dxScWvil8fZ1sE8JmXw/YkrLP0lgt42hvzvqcE4m7Vsvaclk/LKeE9icsr446Jqgre/PpLExYwS9LVk7cpibAtNubitUWgBzAp2IK+shqNtzLXbfiGLK4WVvDjWQyzAtIMARxM2LQrmyRDXVr9XIq3Dx8aQ96f0Yc4AB76a3V8lKlZoXKuumdufvLJqXtx2UekF8Z9Pp6MhFZgRZH/3g5XA6xO8MNHV4M0d0R1+FisUCt77MwZzAy2eGqHcde78QY6Y6nUsS6tO3sDl7DKlroECnUwoKK8hvZ0Wrm1F3qDgVHIhr/8viqAVB1m8KZyTSYVM7W/Lj4uCiXhnLGvm9mdKP1uMdTVbdU5bYx3G+liy9VxGh/K088trKK2qw7MbF7QAlgxzxUBbxmf7b1dpXaut5/2/YvCyMmCeCi1Bb0ZbQ8oQNzMOxearhTpeoVBwNKGAYR5mKrvPqivzBzlSJ1dgoK3BW5N8VHote1NdFg9zZseFLC50sJAv8k/urU+tiEgPxPV6B+d/jyRjY6TNcBV2F7QHQRAIdjZl1cy+nH1jDO8+4ENlbT2LNobzxcEElXXTqpp6eQP/DU3G19aIEDWUaD8Z4kp+eQ07L2R39VBaxf7LuWyPyOLpEa5dlkWmbuhoSpkeYMffl3LJL2u0VCutqmP+92dIu3qN7xYEqsSWsafi3EsPAy0ZkW3I0QpPLcbX1kgssN4FQRBwt9QnXgkFrf0xefS2McTWWKdVx3tbG/LH00PwsTZk6c8RfHUoEYVCQUODgs/2J+BgqsuMQNVvJpnpa7H72WE31FgjPC1UFiytTgx2M2Pf88MY38eKT/6OZ/a3p9ud59PZ5JZW8/flXGYE2inFZsTXzojHhjqz5Ww6Z1L+35auvLqOBT+c5Uh8Ph9M9eXJEPVogrm1uDXM3Yw3dkRzSkmB8m1F3tBo/fOfv2KY0NuKXxYPpFcrO6Yf8LPB19aIT/+O79Am3p2ISC/mq8NJTO1ny4N9bbiUXarSuWuTjbjLXTK0mhjlZYGZvlabsoBq6xtYfTARPzsjxraghhUR6SpmBjnwwVRfNGWq3a7q72DCmxO9ORSXzzfHkpV23mu19fx2PoMJfaw7zTnFSFeDtyf5EJlZys9nOpajtCsym4sZJbw63lPpds26mjIWD3PhaEJBuzd3E/LKqalvwE+Ja8YgJ9XnaCkUCqIyS/jPXzEMXnmIOevPsCsym1FeFmxYGMTZN8fwwVRfQjzM0ZK1b16yYJATRZW17I7KufvBzZBwfT7vbtm9i/VGuhosGebCwdi82z5rXx9OIru0mv9M6dOplrtjvC3IKqkiTg2y5uNyy8ktq2aEx72Rn3Uzrub6vDnRm9Wz+mKq17qCcUd4aoQb5gZavPdXjFoUM3sKYkFLRKSb09QVWF5Tz/RAe7XeQDPS1WDhEGf2PDuMaf1t+eJgIk9sPt8ts572XMol9eo1nh7pqpbe0kPdzOhtY8g3x5LVvmhYVFnLGzui8bE2ZNko964ejloxd6Aj9Q0Kfj2XQUVNPQs3nCUhr5xv5gcw2M2sq4fXrZBIBHztjFrdXV9dJyc6s/TGAlekZTwsDEjMa72d450oKK8hIr2YcT53V2fdjLmBFr8sHsiUvjZ8diCB57deZGdkFpezy3h+jHundR3am+r2SDXW3TDW1eTr2f34bLo/MTllTFx9nB0XMtV+wfbL2XTkCoVSO3NfGOuBnYkOy3dEU10np6iyljnrzxCRVszqWf2Yo0Lry45gcl2p4GKuxxObz5OkpDy81lJVK+fJzefZeCqVx4c6s2ZO/zY1EkgkAssnepFdWs3GU6lKG1dlTT0vbL2IlaE2/57cGz9bI8qr60lTYdE2Ob8SS0MtDLRvzxC8ExpSCdMD7TgSn09eWfN5gjez9Vw6WSVVvDTOUy3nsCIinckjg52438+aT/+OV1pG3q6L2ZRX1zO/k5QfTTzob8NQNzM+2Rff6vvBrVTVyvlobxx9bA15qL9q7NkXDHLERFeD1Yfap9JqmssrU6HlZq6PkY6GSnK0kvIrWHUggZGfhvLg1yfZFJaKn50xX8/px/m3xvL5zL6M9LJQynx1sGsvXM312HS6/UXNhOvzeY9urtACeHSoM6Z6mv9QaaUUVLD+eArT+tl2+jqvKU9PHWwHj1y3UA7xVL/m7M5g8XAXlVoN3oy+loxXxntyIb2EXZHdo+G8OyAWtEREujlGOhqYG2ghCI3h0N0BbQ0pn033551JPhyOy2fq2lOktCHXpqtpaFCw9kgSbhb6bd547SwEQeCJEFdSCio5qAYTppZ4e+clSqvq+GyGv8o7MbsbzmZ6DHM345cz6Ty28RxRmaV8Nbs/Iz3vvU4qZeBnZ0xcblmrrDijs0qplTcQcA95incEd0t9rlbWUlhR0+5zHIrNQ6GAcb3brhjQ1pDy+cy+vDLek50Xs3lhayTuFvpM7tsxKzmR1iEIAg8F2LH3uWF4WhnwwtZInv31okpySZRBbX0Dv5xJZ4SHeYt5FG1FV1PGiqm+pBRU8v7uGGasCyMhr5z1CwJ50N9GaddRBYbaGvywMAgtmZRHN57r0He5LRRW1DBr/WkOxubx7gM+vDXJp10WeINdzRjlZcGaI0kUV9YqZWzv744hvegaq2b4Y6itQR/bRjVAtArzYJMKKlqVn3UzMwPtkTco+P185l2Pra6T89XhJIKdTBnuLjbGiIgIgsBHD/nhbKbHM1siONlBlapCoWBTWBpeVgYEOXXuHFIQBN6f0ocaeQPv/RnTrnOsP55Cdmk1b9/fvntxa9DTkvH4MBdC4wu4mNF654QmojJLMNSW4dRLOdle0NgYEeBowjklFbRySqv49lgy9395nDGrjvLV4URsjHX46CFfwt8cy/oFgUzys1GKQvxmmnKYIzNKiGqDK8XNJOSW00tPs1NypVSNvpaMpSNcOZFUSFjyVRQKBe/+GYO2TMrrE706fTwWhtr42xlxMFa1eZytITS+AB9rQyzvwWa8ruDh/nb0tjHko71x1Na3LfdU5M6IO4ciIj2AQS69mOhrrbTA1s5AEAQWDXXmp0XBXK2oYfKakxyJ6/oHe2s4FJdPXG45S0e4qnXuwMQ+Vtib6vDN0WS17ZQ/EpfP7qgcnhvtjre1YVcPRy2ZP9CR3LJqzqYWsWqGPxP6qGcRtTvgb2dEnVxBbM7d1QdNC1qxoNU6PK0auzgTOmA7uD8mDzsTHbys2tcRKggCT49045t5/bEw0OKNid5qrVruidib6vLrkoG8PM6DvdE53Lf6mNI63pXJvsu5FFbUsGCwk9LPHeJhzpS+Nmw+nU5uaTWbFgUz0qt7NCHYmejy3SOBFJTXsGRTuNLt+24luaCCqWtPEp9bxrp5ASwc4tyh871+nxeVNfV8dTipw2PbfzmXLWczeDLElQEuvYDGbnVNmYTodm4S3g2FQkFKfkWbM5mczPQY5NKLX8+l31WVv/l0GvnlNbw0zkNUZ4mIXEdfS8a6+QHoa8mY+90ZXtx2kavtLOpfyCghJqeMeQMdu+Q75mSmxzMj3dgdnXNDgdFackur+W9oMhN9rW7c91TFI4OdMNbV4Mt2qLSiMkvxszNW+v830MmE5IJKijrQFJFVUsX8788weOVhPtgTh0wi8PYkH04vH80viwcyM8gBI93WKXDby7QAO3Q1pWwKa59KKyG/vNvbDd7MvIGOWBpq8dn+eP6+nMexhAKeH+vRaXagtzLa25LIzBIKyjuncehOlFXXcT6tmBH3qDqrK5BIBFZM9eWLWf3EJm4lIf4XRUR6AF/O7sfXs/t19TDaxWA3M3YtG4qdiS6LfjzH2tAktS2+QONmw9dHkrAz0VH7bmuZVMLiYS5EpJcQnqZ+AZT18gZW7InFqZcuS4arR6aIOjLKy4Kp/Wz5YmZfUW3SQfzsG61JWrMZGZ5ajKu5XqszXO51mmxJ2ms7WFlTz4mkQsb5WHV4g2JCH2vOvjmm2xQRehoyqYRlo9z531OD0dKQMue703y4J7ZVysjOYtOpVBx76RKiIquRdx7ozcMBdmxZPFDlm4LKpq+9MZ/P6EtEegkv/RapMtvik0mFTFt7iqpaOb8uGcS43h1v1vCwNGBGoD0/nU4l/Wr7bQHzy6t5fXs0vW0MeWGMx42fa8okeFsZqEyhVVBeQ3lNfZsLWgCzgu3JKKoiLKX5AnJFTT1rQ5MZ5m7W7T6XIiKqxs3CgH3PD2fZSDd2XcxmzKqj/Bae0eZ16eawNPS1ZEzp13Vz9iUhLria6/H2H5eoqm39s/fjv+OQNyhYfp+3CkfXiL6WjMeHOnM4Lr9NSqLqOjnxueVKzc9qosl+7nw7180nEguZ9OVxLqSX8PxoD0JfHsHOZUN5bKhzp6pgDLU1mNrPlj8js9usWFYoFCTmVfQIu8EmtDWkLBvlTnhaMa/8FomnpQGPDOpcO9CbGe1tgUJBlzZzn0gsRN6gYITo+tKp9LU3JthZjDNQFmJBS0Skh9CduyztTXXZ/tRgJvnZ8PG+eJb9coFrtfVKO3/a1UpW7o1j+fboDudCnEq+SmRGCU+GuHZqgGh7mR5gj6meJt+EKi/oWFn8ei6DpPwKlk/0FrtUWkAmlfC5WMxSCjZG2pjpaxJ5lxythgYF4alFYn5WG7Aw0MJQW9ZuhdaxhAJq6xsY69N2u0ER9cTf3pjdzw5lVpAD646lMHXNKRI7oOBTFpezSwlPK2b+QEeVqaxN9TT5dLo/virYcOsM7vO1Zvl9XuyOyuGzA/FKPbdCoWDDySss+OEsloZabH9qCH3tlZeD8sJYD2QSCZ/sb9+4FQoFr/4eRWVNPatn9b1tfuJrZ8SlrDKVFPqSrttvt9VyEGB8byuMdTXYcja92WM2nrxCUWUtL43zbPcYRUR6MtoaUl4e78me54bhYq7PK79HMXv96VZb4xdV1vJXVA7T+tuiryVT8WibR0smZcVUXzKLq/jycOsUUJEZJWyPyOKxYc7Ym3aO68sjg50w0mmbSismp4z6BoVS87Oa8LU1QlMqaXOOVkODgjVHkljwwxnMDbTYtWwIz41xx8lMeZbGbWXBICdq6hvYFp7Rpt/LLq2moqa+RxW0oNGa185Eh/Kaet6b3LtL93F8rA2xMdLmUFzXxUKExudjoC2jv4Pyv0ciIp2FuIMoIiKiFuhoSvlyVl+W3+fF3ks5TFt7qkPdtXXyBvZdymH+92cI+SSU9cdT+ONCFmM/P8bzv15od2bX14eTsDDQ4uGA7pFXpqMp5ZFBThyKyyc+t+s3Epsor67j8wMJBDubMk7cwBbpJARBwNfW6K6doIn5FZRV1xMoFrRajSAIeFoZtLugtT8mD2NdjU7PmxBRLbqaMj6c5sv6BYHkllUz6asT/HEhq0vH9FNYGtoaEqYH2HfpONSdJcNdmB1sz5ojyW3eEGuOmno5r/0vin//GcMoLwu2Lx2CgxIzUAAsDbVZPMyZPyOziWxHNsvm02mExhfwxkRv3Cxu39DztTWioqae1KuVyhjuP0jOb5ybtkehpa0hZWo/W/aQX8vNAAAgAElEQVRfzrujXVbptTrWHUthjLelUguIIiI9EQ9LA357YhArpvbhcnYZE744zuqDiXdVGm8Lz6BW3sC8gV2n/mhioEsvpgfYsf5Yyl3XgAqFgvf+isFMX4ulIzrPNcNAW4PHhjpzMDafS61UvkZdv6/72yu/YURbQ4qvnVGbcrTKqut4YvN5Pvk7nom+1uxYOgSXdtzDlY2nlQEDnE356XQa8jY0YDTN43taQUtTJmHNnP58/LBflyuUBUFglLcFxxMLVW7tfCcUCgWh8QUMdzfvFg3aIiLNIX56RURE1AZBEHgixJUNjwaTXVLFg2tOcCKxbcG8WSVVrNofz5CVh3lycwRJ+RW8ONaDU6+P4sRrI1ky3IW/L+cxZtVRXtx2kdTC1m9InE8rJizlKkuGu6CtodwAV1WyYJAjOhpSvj2W0tVDucHa0GSuVtby1v3e3VpdKNL98LMzJim/gsqa5lWg4WmNC9lAMT+rTbhbGpCQV9Fme546eQOH4/IZ7WUpLqx6KGN9LNn3/DA8LA345G/lKn7aQum1Ov64mMXUfrYqz7Do7giCwHuT+zDM3Yw3tkdzKqlt87FbyS+vZva3p9kWnsmzo9xYNy9AZQqGJSGumOlr8sGe2Dbdj5LyK1ixJ5YQD3MWNGNH1Me2cRNVFbaDyQWV6GvJsDRsn9XtrCAHauUNbI/IvO21706kUF5dz4tjPe7wmyIiIrcikQjMHeDIoZdCGNfbks8PJjBx9XHOXrlzsUPeoGDz6TQGupiqTTFg+URvDLRlvLEjukVV6V9ROZxPK+aV8R4YaHfus3HhECcMtWWsbqVKKyqzFHMDLaxUZOEX6GRCdFZpqwoN8bnlTP76JIfj8nl7kg9fze6HXhcq825lwSAnMourCG1DllrijYJW1xfllI2/vTEzAtWjmWm0tyXXauWcbsEmWFXE5JSRX15DiJifJdLNEXcNRERE1I4QD3N2LRuKhYEWC344w3fHU1rckJA3KDgcl8djG88x7KPDfHUkid42hny3IJDjr47k2dHuWBpq00tfi+X3eXP8tZE8NtSZPdE5jF51lJd/i2yVGmztkSSMdTWYHeygzD9X5ZjoaTIr2J6dF7PILqnq6uGQWXyN709cYWo/W5XYRYiItIS/vRENClrsBA1PLcZMXwtHJSsHejoeFvqUVtW1OeT43JUiSqvqRLvBHo6FgTZT+9mSVVJFTmnXPIt+O59BdV0D8wc6dcn1uxsaUglr5vbH2UyPJzefJym/fer2qMwSJn99kticctbM6c+L4zxVZvcIjdksz43x4MyVIg7Ftm4jr7a+gee3XkBHQ8onD/s122zjYWmApkxC9F2sa9tDckEFruZ67W708bQyoJ+DMVvP/TP352pFDT+cuML9ftb42Bgqa7giIvcEFgbafD2nPxseDaK6roEZ68J47fcoSq79Uwl5NCGfzOIqtXq+mOpp8sZEb86nFbO1GaVtdZ2clXvj8LE25OEuUC4bamuwaKgzB2LyuJx99/tqZGYJ/nZGKmuIDHI0pU6uIOou9/idF7OYsuYkFTX1bFk8kMeGOqtdk+a43pZYGmqxKSyt1b8Tn1uBhYEWxrqaKhyZyCCXXuhoSFs9R1EmofEFAIzwEAtaIt0bsaAlIiKiljiZ6bFj6RDG+Vjx/u5YXth68bZOqfyyar4+nMjwj4+waGM4kZmlLB3hxrFXRrLh0WDG+Ny5299MX4s37/fh2KsjWTjYiT8jsxn1WSiv/R5FRtGdC1sx2WUcistn0RBnteq8ai2PDXVGAfxw4kpXD4VP/o5HAF4ZL2Y4iHQ+TUXUlhaq51KLCHIyUbuFqbrjYdXYkRzfRtvB/TF5aMkkDPcwU8WwRNSIwOuWkuGp7Qtc7wgNDQo2haUR5GQibuq3AUNtDX5YGISmTMKjG89ytaJtBeudF7OY/k0YEkHg96cGcb+ftYpG+k9mBdnjYqbHyn1x1Msb7nr86kMJXMoq48Npfli00PmvIZXgbW2oEoVWUn5Fu+wGb2ZWkD2J+RVEpP//d+ybo8lU1cl5YYyozhIRaS8jPS048OJwnhjuwu8RmYxZdZSdF7NuFI9/CkvD3ECLcb3Vqznn4QA7Bjib8uGe2Ds2HH13PIWskirenuSDVIWNBi3x6BBnDLRld83SKq+uI6WwUqUNkQHX3Rmasx2skzfw7z8v89yvF+ltY8juZ4YS7KyeFuUaUgmzgx04mlDQaleaxPxytVEY9mS0NaQMdTfjUGxem50tOsrR+AJ62xi2ONcREekOiAUtERERtUVPS8Z/5/Xn5XEe7IzM5uFvTpFZfI0TiYUs/fk8g1ce5tP9CTiZ6bJ2bn/Clo/i5fGerQ6ytTDQ5u1JPhx/dSTzBjqy42IWIz8NZfn2aLJuUTKtDU1CX0vGI4OcVPCXqh47E10e9Ldhy9l0Sq/Vddk4LmaUsPNiNouHuWBjrNNl4xC5dzHT18LWWIfIZnK0ckqryCyuEvOz2kHTAjghr/UqDoVCwYGYPIa5m6Or2f2aBUTahre1IToaUs6ndX5B62hCAelF11jQTZ/jXYm9qS7rFwSSX1bD4k3hrbJikjco+HBvLM/9ehF/e2N2LRtCbxvlZ540h4ZUwqsTvEjKr2Bb+O0WfDdz9koRa0OTmRFox4Q+Vnc9t5+tEZezy1q08GorFTX15JRW42rRsYLWJD8b9DSl/Hq2UY2RV1bNprA0pvazw62D5xYRudfR1ZSxfKI3u5YNwdZYh+d+vciCH85yIrGQ0IQCZgc7oKFm1smCILBiqi9VdXJW7I75x2t5ZdWsDU1mQm8rBrl2Xa6QkY4Gjw5x5u/LecTmlDV7XHRWKQoF+Nmp7llioqeJu4U+4XcoaOWXVTNn/Wk2nExl4WAntiwZqPZFgTnBDsgkAptP312l1dCgIDGvAvceaDeojozxtiC7tJrYnM7LOS+tquN8ejEjRLtBkR6Aej1tRURERG5BEASWjXLnuwWBpBVeY/jHR5j3/RnCkq+yaKgzR14ewc+PD2Sir3W7FxAWhtq8+2Bvjr0ykjkDHPjf+UxGfHKEt/6IJqe0ipSCCnZH5zBvoGO3ztxYMtyFylo5P51O7ZLrKxQK3r8eOPxkJwYOi4jcip+dUbMKrSbliJif1XbM9LUw1dO84b/fGi5nl5FVUsU40W7wnkBDKsHf3qhLClqbwlIxN9BifO+7FyxEbqefgwlfzOxLRHoJL/8W2WIxp6y6jsd/PMe6oynMHeDA5scG0Eu/fblQHWF8b0sCHU34/GBCs7mJZdV1vLD1IvYmurzzQO9WndfX1oiKmnquXG19DuvduFLQeC5Xc70OnUdPS8aDfW35KyqH8uo61hxJQt6g4LnR7soYpoiICNDbxojtS4fw7wd7cyG9hHnfn0EiCMwOVo98nltxs9DnqRBX/riY/Y986k/+jqdermD5RK8uHF0jjw1xxkCrZZVW09xd1Zb1gU4mnE8r/sdz7lxqEfd/dYJLWWWsntWXdx/srXbFyzthYajNhD5WbAvPoKq25WaUzOIqqurkeIoKrU5hpJcFAIdi8zrtmicSC5E3KBjpadFp1xQRURXqfwcWERERoTE4849lQ5gzwIEvZvYlbPlo3pjojbNZxxb+N2NlpM17k/sQ+soIZgTas/VcBiEfh7J4UziaUgmPDXVW2rW6Am9rQ0Z4mrPxVGqruquVzb5LuYSnFfPiWA+VBcGLiLQGPztj0ouuUVxZe9tr59OK0dGQipZk7cTDUr9NloP7Y/KQCDDaW1xY3SsEOpoSk1PWbIFBFaQWVhKaUMCcYAc0ZeLyp73c52vN6/d58VdUDqsOJNzxmJSCCqasOcnxxELen9KHFVN9u+x/LggCyyd6U1Bew/rjKXc85t1dl8kpreLzmX1bPTfxva4OUGaOVlJB431TGSqqWUH2VNXJWRuazJaz6cwIssdBzIQUEVEqUonAI4OdOPDicCb3tWHJcBesjdTXfWLpSDeceuny1h/RVNfJic4s5ffzmTw61AnHXspbT7cXI10NHh3ixN5LucTl3lmlFZVZgp2JDqZ6qs13CnQ0pay6nsT8ChQKBT+cuMLsb0+jpyllx9ODmdzXVqXXVzYLBjlRVl3PzotZLR6XcH3+7i4WtDoFCwNt/O2NORjXeTlaofH5GGrL6Gsv5piLdH/EFZ2IiEi3wdVcn/en+DKlny3aGlKVXcfGWIcVU3058vIIHgqwJe3qNeYPdMTcoPO7i5XNkyGuFFbU8vv5lu13lE1tfQMr98XhYanPjEC7Tr22iMit+DdtRt4hA+VcahH9HIy7RdelOuJhaUBSXkWr/eAPxOQR6GjaJeoNka4hwNEEeYOiWdtPVbD5dBpSQWDOAIdOu2ZP5YnhLswKsufrI0lsC8/4x2uh8flMXnOSkmt1bH58APMGOnbRKP+fAEcTJvpa8e2xFPLLq//x2u6oHLZHZLFslPuN3JTW4G6hj5ZMotQcreT8SqQSAQfTjm8s+9kZ4W1tyH9DkxEEgWdGuSlhhCIiInfC2kiH1bP68dqErlc5tYS2hpT3p/iSevUaa48k8Z+/Yuilp8mykepzf1g01Bl9LRlfHUq64+uRGaX4q1idBRB03Xb8aEI+z/56kff+imGklwW7nhmKl1X3a3gLcjLBy8qATWFpLc7PE/KbClqi5WBnMcbLgsiMktvmJ6pAoVAQmlDAMA/zO+bMi4h0N8RPsYiIiEgz2Jno8uE0P86/PZblE727ejhKYYCzKf72xqw/noJcidkPd2NTWCppV6/xxkRvcQIl0uX0uV7QirplQ728uo7YnDIxP6sDeFgaUH49C+ZuZBRdIzanjLGi3eA9RX+HxsLB+dTOsR2sqpWzLTyD8X2ssFTzrIvugCAI/GdKH4a6mfHG9mhOJReiUCj49lgyizaew9ZYh51PD2GgS9flsdzKK+O9/o+9O4+P667v/f/+ahYtI2m0e5Fs2ZZkx47tONjEWZyQYBKWC01KWUIbCqWFS0spt6U7/Bru7Q8Kt/1d6KWFX6HQwn1QCoQCaUkpWQiNnQ0nIV4Te+R4kTfNaJ8ZSbN97x8zI8u2ZC0zozkavZ6PRx62zsyc8x3nPOyZ8z6fz0exREqfe+RiK6vzQ2P60+8d0HWr6uYc+LhdZdq0sjavFVrdwbDaG6ryUs1mjNG9r063PrtvZ7ujq0YALJxdXU26Z9tKff4nAT17ol8fvWuDaiqc006/rsqr9968Rg8dPDdRLZTVFx7XmcHRgs7PylrVUKmWmnJ96qGX9MP9Z/UHr9+gv7tvu2od9Gc1F8YYvfumdh0+N6znT03/2evo+RGt9Fcs2ve5GO3emP4O9JMFqNI6dHZYwZFx2g2iZHBVEQBm4K/0yFVmir2MvDDG6Ddfs04n+6L60cHzC3LMwWhMn38soNvWN+t2PkDBAWorPFrX7NOLl12MfOHUoFI2fScj5md9pk3JbNoO/vhwumc8gdbS4q/yaP2yau1boDla/7b/rIbHEnrPTWsW5HhLgcdVpr/9lVdpbZNPH/w/z+lD//S8PvXQS3rD5uX6l9+6WasanNXebm2TT/fd2K5v/ey0Ar0jSqWsfv87L6ZDrndum1dF7pZWvw6dHbrqLLG56A6G1ZGHdoNZb9/Rpg+/tlO/s9s51RcAiu/jb96k2gqPrlleo3e+2nkzv35911pVeVxXzNLaf2Zh5mdJ6e/Ld2xoUX2VR1973w360B2dKlvk1wLu2daqmnK3vv7UyWmfc/RCmHaDC2zjihqt9Ffo0SOFD7R+ejQoSXrN+uaCHwtYCARaALDE3LlpudY2+fT//7R71m3BcvG/Hw1oZCyuj5VIlRtKw9ZW/xUVWvtODqjMSNevJtCar/WZNiXHZhFoPXz4vDYsq9GaPM5CxOKwvb1ez58ayFsYcDWPHw1qeW0FQXWe+Ss9+up7Xy2vu0wPHTiv37tzvf72l1+lKq8zZ2R++LWdqvK49Ol/f1n/8OQJ7QmE9P+8edO8Z7FuafUrEkvqeCiS89oSyZReCUXU0Zy/QKvK69ZH79qguqrCzpoBsLg0VZfr3z68S998/42OvGGz3ufVe25eox8eOHfJZ8n9p4dkzMUZhoX2P+65Vk//6W7d2lUaF/995W69bUebHjpwTsGR8SseT6asAsHwxOd4LAxjjHZvXKYnjoUKPuP88Zd7tbm1tiTGaAASgRYALDmuMqMP3LZOB84M6anuvoIe65VQRF9/6oTe+epV2rCcO77gHFvb6nRheFwXhi+2xtt3ol8bV9SqutyZF2QXg7oqr1pqynX0QviqzxuIxPTsK/1UZy1R29sbNJIZuF5IqZTVk4GQbulskjHOu3C32K1qqNIDH7xZD3zwJv3O7i5H/xk3Vpfrg7d36JEjF/QXDx3R6za26F03zL86YcvELMbcZ8GdHhhVPGnV0Uy4D6DwVjVUqd7n3LD7N25dp0qPS59/7OIsrf09g+porl6wz+jlbpfK3YWb2V0M776xXfGk1bd+duqKx072RRRLpCY6LWDh7N7YotF4Uk8dL9x1maFoXM+dHKDdIEoKgRYALEG/eH2rmqrL9cWfdhf0OJ/+9yMqd5fpd+9cX9DjAHN13ar0xcgXT6cvRsaTKb1wanBiEDTmb/2ymitmH1zu0Zd6lbLSXdcSaC1FO9rT1VL7TvYX9DiHzw1rIBrXri7nzHMqNWuafItm7uD7blmr5bUVqqvy6NO/tDWnAK6zuVoVnjId6BnOeV3dmWA3ny0HAWCxavB59as3rdG/7j+rQG9Y1lq92DO0IPOzStm65mrd2tWkbzxzSolk6pLHsjeiEWgtvBvXNarK69KjRy4U7BhPBIJKWen2DaVRcQhIBFoAsCRVeFx63641euJYSIfO5m+o+WTPHO/Tfxy6oA++pkMtNRUFOQYwX5tW+OUqM9qfmaN1+OywRuNJ7aAtWc66llXr2IXwVdvJPXz4vJbXVmhLKxcnlqL2xio1+rx6rsBztPYGQpKkWzqaCnocLA6VXpce+M2b9P0P3aKm6txa7rhdZdq0ojYvFVqBYCbQymPLQQBYzN5/61pVuF36m8eO6dzQmELhcV23APOzSt27b2zXuaExPXJZeJJt79jJjRULrsLj0q1dTXrsSG/BxkE8/nJQ/kqPtq3iey5KB4EWACxRv7KzXdXlbv3dT4/nfd+plNUnHzqiFf4K/cat6/K+fyBXlV6X1i+r0YuZOVo/O5GuFNnRvjgqDZxsw7IajcaTOjM4OuXjo7Gkfno0qDs3LXN0izIUjjFG29vrCx5o7QmEtH5ZtVpquakCaW31VWqrr8rLvra0+nXo7LCSOc6C6+4Nq7mmXP5KT17WBQCLXWN1uX71pnY9+OJZff/nZyQt3PysUrZ74zK11lXq60+dvGT7yxdGtKqhUj7arhfF7muW6ezQmA6fy73q+3KplNXjLwd12/pmR87NA+aLQAsAlih/pUe/vHO1fnjgnE73R/O67wdfPKv9PUP6g9dvUKW3tPqPo3Rc1+bXgTNDstbquZMDaquv1HI/F75z1ZVpV/Ly+anbDu4JhDQWT9FucInbsaZeJ/uiUw4nz4fxRFI/O9Gvm6nOQoFsaatTNJbU8WBus+C6g2HmZwHAZd5/2zqVu1367MNH5S4z2rSitthLWvRcZUa/vHO1nuzuU6D34uf0YxfCWt9Cu8FiueOaFhkjPXqkN+/7PnxuWKHwuG5fT7tBlBYCLQBYwt53y1qVGenvn8hfldZYPKn/+aOXtKXVr3u2teZtv0C+bW2r02A0rlP9Uf3sxADzs/Kka1m6XcnR3qkDrYcPn1dNhVs71zLXaCnbnpmjVagqredPDmosntKuTgItFEa2ZeqBM/Nv3WytVXcwQpsnALhMU3W57rtxteJJqw3La1Th4SbJfLj31avkdZXp/2SqtOLJlI6HwhM3pGHhNdeU67q2uoLM0Xr85XRIdhuBFkoMgRYALGHL/RW6Z1urvrXvtPojsbzs8yt7XtHZoTF97L9sVBll7XCw7HDpf33xrELhceZn5UlthUcr/RU6duHKqoVkyuqRI726Y0OLvG4+hi5lm1v98rrL9NzJ/oLsf28gJFeZ0c51BNUojI5mnyo9rolZjPMRCsc0NBpnfhYATOEDt3Wo0uOauAkGuWusLtebt67Qd58/o/B4QidCkUxoyL9DxfS6jS16sWdIvcNjed3vT14OamubX801uc0OBZyGKwkAsMT919es01g8pa89eSLnfQVHxvWFnwR056ZlunEd1Rdwtg3La1TuLpvoI0+FVv50LauZsuXgcycH1B+J0W4QKne7tLXVr30FqtDaEwhp26o61VQwlwiF4XaVadPKWh3MoUKrO9OukEALAK7UXFOuhz5yq37/9RuKvZSS8u6b2hUeT+h7z/foaOYGtC5aDhbV7o3p70aPvZS/toOD0ZheODVAu0GUJAItAFjiOltqdOemZfraUycUjSVy2tdnHzmq8URKf/LGa/KzOKCAPJmLkb0j46qtcKuTC4p5s35ZtbqDYSVT9pLtDx8+L6+rTK/hixWUbjt48MyQxuLJvO53aDSu/T2DuoV2gyiwLa1+HTo7fMXfdbM1EWjRchAAprS2yadabk7Jq22r6rSl1a+vP3VSL18YUZkRrW+L7JrlNWqtq9SjeQy0njgWUspKr9nQkrd9Ak5BoAUA0Adfs06D0bi+/bPT897H0Qsj+udnT+m+G9u1jmAAi8R1bXWSpB1rGmiRmUfrl9VoPJHSqf7oxDZrrX58+IJu6mikagaS0oFWPGlzmkE0laeP9yllxfwsFNyWVr9G48mJYGquAr1hVXldWlFbkeeVAQAwNWOM3n1Tu471hvXAvtNqb/Qxo6zIjDHavbFFe46F8naj1+MvB1VX5dG2VXV52R/gJDkFWsaYvzTGvGSM2W+M+Z4xpm7SY39ijAkYY142xrw+96UCAAple3uDXr2mXn/zk4A+/v0D+tufBPTd53r0ZCCkV0IRjcZm/lD1qYeOqLrcrY/s7lqAFQP5saU1PUeL+Vn5tT4zWHpy28GjF8I62Rel3SAmZGdi7DuR37aDTwZCqvS4+AKPgsvOYjwwzzla3cGI1jX7uKECALCgfuG6laqr8ujs0Ji6qM5yhN0bl2k0ntRT3X057yuVsvrp0V7d1tUsF58xUILcOb7+YUl/Yq1NGGM+I+lPJP2RMWaTpHslXStppaRHjDHrrbX57ScCAMibj/+XTfr49w/qh/vPaSAav+LxuiqPltdWaIW/QivqKrWitkLL/RVa4a9U78iYHn85qI+9aaPqfd4irB6Yn1u7mrRpRa3u2rS82EspKdm2JccujOgNm9N/tg8fPi9JunMjgRbSGqvLtbbJp+fyPEdrTyCknesa5HXTjAKFta65WlVelw6cGdIvbW+b8+u7e8PcUAEAWHAVHpfeuWOV/u4/j0/ciIbiunFdg3xelx45ckF3XJNbm8BDZ4cVCsd0+wbavKM05RRoWWt/POnHpyW9LfP7uyX9s7V2XNIrxpiApBskPZXL8QAAhXPdqjr964d3SZLG4kmdGxrTuaFRnR8a07mhsYlfzw2Nan/PkPoisUtev7qhSr96c3sxlg7MW0tthR76yK3FXkbJ8ZW7taqhUkd7L7bh+vHhC9q2qk4ttNbCJNvb6/XYS72y1sqY3O8gPTc0qu5gRO+6YXUeVgdcnavM6NqVtfNqmxmNJXRmcFT3Nq8qwMoAALi6+25s1z89e0o71zUUeymQVO526dau5rx8Ln785V4ZI93G3GKUqFwrtCZ7n6RvZX7fqnTAldWT2XYFY8wHJH1Aklav5osnADhBhceltU0+rW3yTfucsXhSvcPj6dBreEybW/0qd9N7G0Da+pYaHc20HMwG4X/4hg1FXhWcZkd7vR54rkfHQxF15GH+4t5Auk3LLczPwgLZ3OrXN589pUQyJbdr9lWBx4MRSVIHrZ4AAEWwqqFKL/7ZXbS9dZDXbmzRjw6d16Gzw9qcaY0/Hz95uVdbW/1qqi7P4+oA55jxE7cx5hFjzMEp/rt70nM+Jikh6RvZTVPsyk61f2vtl6y1O6y1O5qbSY4BYLGo8Li0urFKO9c16u5trXm5EAmgdHQtq9HxUFjxZEqPHL4gSbR2xBWyc7Ty1XZwbyCkpmqvNtA+Bwtka5tfY/GUujMB1Wx1B9MVrHx+AgAUC2GWs7z2mhYZIz16pHfe+xiMxvTz04N6zYbc2hYCTjZjoGWtfZ21dvMU//1Akowx75H0Zkm/Yq3NhlY9kib3TmiTdDbfiwcAAIAzbVherXjS6mRfRD8+fEHrmnwTs7WArI7mavkrPXruRO6BlrVWewMh3dTRxAUaLJgtmTuo9/cMzul13cGIyoy0pqmqEMsCAACLTFN1ubatqtOjL12Y9z7+81hIKSvdwfwslLCcJiUbY94g6Y8k/YK1NjrpoQcl3WuMKTfGrJXUJenZXI4FAACAxaOrJV0hs+/EgJ7q7tOd1y4r8orgRGVlRtvb67XvZH/O+wr0htU7Mq5dnY15WBkwO2ubqlXldengHOdodfeGtbqhinbNAABgwus2LtP+niFdGB6b1+sff6lX9VUebW2ry/PKAOfIdYbW30gql/RwZljd09baD1prDxljvi3psNKtCD9krU3meCwAAAAsEp0t1Soz0pefOK5EytJuENPa3l6vx17q1UAkpnqfd9772RMISWJ+FhaWq8xo80q/Dsw10AqGaTcIAAAusXtji/7yP17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\n",
      "text/plain": [
       "<Figure size 2160x1080 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "decomposition = seasonal_decompose(co_df_part_1_weekly[\"Requested_Quantity\"])\n",
    "\n",
    "trend = decomposition.trend\n",
    "seasonal = decomposition.seasonal\n",
    "residual = decomposition.resid\n",
    "\n",
    "f = plt.figure(figsize=(30,15))\n",
    "ax1 = f.add_subplot(411)\n",
    "ax2 = f.add_subplot(412)\n",
    "ax3 = f.add_subplot(413)\n",
    "ax4 = f.add_subplot(414)\n",
    "\n",
    "ax1.plot(trend, label = 'Trend')\n",
    "ax1.legend(loc='best')\n",
    "\n",
    "ax2.plot(seasonal, label = 'Seasonal')\n",
    "ax2.legend(loc='best')\n",
    "\n",
    "ax3.plot(residual, label= 'Residual')\n",
    "ax3.legend(loc='best')\n",
    "\n",
    "ax4.plot(co_df_part_1_weekly.index, co_df_part_1_weekly['Requested_Quantity'], label= 'Original')\n",
    "ax4.legend(loc='best')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_pacf(co_df_part_1_weekly['Requested_Quantity'], lags=55)\n",
    "plot_acf(co_df_part_1_weekly['Requested_Quantity'], lags=55)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df_part_1_weekly['Seasonal_Difference']= co_df_part_1_weekly['Requested_Quantity'] - co_df_part_1_weekly['Requested_Quantity'].shift(52)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Verifying acf and pacf with seasonal difference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_pacf(co_df_part_1_weekly['Seasonal_Difference'].dropna(), lags=55)\n",
    "plot_acf(co_df_part_1_weekly['Seasonal_Difference'].dropna(), lags=55)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.tsa.stattools import adfuller"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test Statistic                  -3.706467\n",
      "p-value                          0.004023\n",
      "#lags used                       5.000000\n",
      "number of obserbations used    151.000000\n",
      "Critical Values (1%)            -3.474416\n",
      "Critical Values (5%)            -2.880878\n",
      "Critical Values (10%)           -2.577081\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "dftest = adfuller(co_df_part_1_weekly[\"Requested_Quantity\"], autolag='AIC')\n",
    "\n",
    "dftest_output = pd.Series(dftest[0:4], index=['Test Statistic', 'p-value', '#lags used', 'number of obserbations used'])\n",
    "for key, value in dftest[4].items():\n",
    "    dftest_output['Critical Values (%s)' %key]=value\n",
    "    \n",
    "print(dftest_output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test Statistic                -8.789154e+00\n",
      "p-value                        2.265286e-14\n",
      "#lags used                     0.000000e+00\n",
      "number of obserbations used    1.040000e+02\n",
      "Critical Values (1%)          -3.494850e+00\n",
      "Critical Values (5%)          -2.889758e+00\n",
      "Critical Values (10%)         -2.581822e+00\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "dftest_seasonal = adfuller(co_df_part_1_weekly[\"Seasonal_Difference\"].dropna(), autolag='AIC')\n",
    "\n",
    "dftest_seasonal_output = pd.Series(dftest_seasonal[0:4], index=['Test Statistic', 'p-value', '#lags used', 'number of obserbations used'])\n",
    "for key, value in dftest_seasonal[4].items():\n",
    "    dftest_seasonal_output['Critical Values (%s)' %key]=value\n",
    "    \n",
    "print(dftest_seasonal_output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x268d624e988>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2160x1080 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "decomposition_s = seasonal_decompose(co_df_part_1_weekly[\"Seasonal_Difference\"].dropna())\n",
    "\n",
    "trend_s = decomposition_s.trend\n",
    "seasonal_s = decomposition_s.seasonal\n",
    "residual_s = decomposition_s.resid\n",
    "\n",
    "f = plt.figure(figsize=(30,15))\n",
    "ax1 = f.add_subplot(411)\n",
    "ax2 = f.add_subplot(412)\n",
    "ax3 = f.add_subplot(413)\n",
    "ax4 = f.add_subplot(414)\n",
    "\n",
    "ax1.plot(trend_s, label = 'Trend')\n",
    "ax1.legend(loc='best')\n",
    "\n",
    "ax2.plot(seasonal_s, label = 'Seasonal')\n",
    "ax2.legend(loc='best')\n",
    "\n",
    "ax3.plot(residual_s, label= 'Residual')\n",
    "ax3.legend(loc='best')\n",
    "\n",
    "ax4.plot(co_df_part_1_weekly.index, co_df_part_1_weekly['Seasonal_Difference'], label= 'Original')\n",
    "ax4.legend(loc='best')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Observations:\n",
    "1. p-value< 0.05 and Test statistic < Critical Value (1%) => Data is stationary. <br>\n",
    "2. But, we have seen from PACF and ACF that there are intervals such as d=6, d=50, d=52 and d=54 where there is a significant value of PACF and ACF. This implies there is a correlation between timeseries shifted by these intervals.<br>\n",
    "3. From seasonal decompose it can be seen that we have a seasonality as the patterns repeat yearly.<br>\n",
    "4. Based on the above observations, it can be inferred that we need to Fit a Seasonal ARIMA model. <br>\n",
    "5. We will do a grid search to determine the parameters based on the best AIC value. <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "import itertools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Examples of parameter combinations for Seasonal ARIMA...\n",
      "SARIMAX: (0, 0, 1) x (0, 0, 1, 52)\n",
      "SARIMAX: (0, 0, 1) x (0, 1, 0, 52)\n",
      "SARIMAX: (0, 1, 0) x (0, 1, 1, 52)\n",
      "SARIMAX: (0, 1, 0) x (1, 0, 0, 52)\n"
     ]
    }
   ],
   "source": [
    "p = d = q = range(0,2)\n",
    "pdq = list(itertools.product(p, d, q))\n",
    "seasonal_pdq = [(x[0], x[1], x[2], 52) for x in list(itertools.product(p, d, q))]\n",
    "print('Examples of parameter combinations for Seasonal ARIMA...')\n",
    "print('SARIMAX: {} x {}'.format(pdq[1], seasonal_pdq[1]))\n",
    "print('SARIMAX: {} x {}'.format(pdq[1], seasonal_pdq[2]))\n",
    "print('SARIMAX: {} x {}'.format(pdq[2], seasonal_pdq[3]))\n",
    "print('SARIMAX: {} x {}'.format(pdq[2], seasonal_pdq[4]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "import statsmodels.api as sm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ARIMA(0, 0, 0)x(0, 0, 0, 52)52 - AIC:1434.3735713623619\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\sattwik\\Anaconda3\\lib\\site-packages\\statsmodels\\tsa\\statespace\\sarimax.py:887: RuntimeWarning: Mean of empty slice.\n",
      "  params_variance = (residuals[k_params_ma:]**2).mean()\n",
      "C:\\Users\\sattwik\\Anaconda3\\lib\\site-packages\\numpy\\core\\_methods.py:85: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  ret = ret.dtype.type(ret / rcount)\n",
      "C:\\Users\\sattwik\\Anaconda3\\lib\\site-packages\\statsmodels\\tsa\\statespace\\sarimax.py:1014: RuntimeWarning: invalid value encountered in less\n",
      "  params_variance = np.atleast_1d(max(np.array(params_variance), 1e-10))\n",
      "C:\\Users\\sattwik\\Anaconda3\\lib\\site-packages\\statsmodels\\base\\model.py:512: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  \"Check mle_retvals\", ConvergenceWarning)\n",
      "C:\\Users\\sattwik\\Anaconda3\\lib\\site-packages\\numpy\\linalg\\linalg.py:1855: RuntimeWarning: invalid value encountered in greater\n",
      "  return count_nonzero(S > tol, axis=-1)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ARIMA(0, 0, 0)x(0, 0, 1, 52)52 - AIC:nan\n",
      "ARIMA(0, 0, 0)x(0, 1, 0, 52)52 - AIC:963.2115304985961\n",
      "ARIMA(0, 0, 0)x(1, 0, 0, 52)52 - AIC:952.2502953441237\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\sattwik\\Anaconda3\\lib\\site-packages\\statsmodels\\base\\model.py:512: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  \"Check mle_retvals\", ConvergenceWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ARIMA(0, 0, 0)x(1, 0, 1, 52)52 - AIC:nan\n",
      "ARIMA(0, 0, 0)x(1, 1, 0, 52)52 - AIC:481.2627241463121\n",
      "ARIMA(0, 0, 1)x(0, 0, 0, 52)52 - AIC:1400.919591693042\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\sattwik\\Anaconda3\\lib\\site-packages\\statsmodels\\base\\model.py:512: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  \"Check mle_retvals\", ConvergenceWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ARIMA(0, 0, 1)x(0, 0, 1, 52)52 - AIC:4191.847881696883\n",
      "ARIMA(0, 0, 1)x(0, 1, 0, 52)52 - AIC:955.0213169769079\n",
      "ARIMA(0, 0, 1)x(1, 0, 0, 52)52 - AIC:947.8500077585626\n",
      "ARIMA(0, 0, 1)x(1, 0, 1, 52)52 - AIC:933.1210723884057\n",
      "ARIMA(0, 0, 1)x(1, 1, 0, 52)52 - AIC:482.8469107763049\n",
      "ARIMA(0, 1, 0)x(0, 0, 0, 52)52 - AIC:1423.5249004196705\n",
      "ARIMA(0, 1, 0)x(0, 1, 0, 52)52 - AIC:1010.8108363100304\n",
      "ARIMA(0, 1, 0)x(1, 0, 0, 52)52 - AIC:966.9297539941458\n",
      "ARIMA(0, 1, 0)x(1, 1, 0, 52)52 - AIC:504.26199062795143\n",
      "ARIMA(0, 1, 1)x(0, 0, 0, 52)52 - AIC:1326.890894417746\n",
      "ARIMA(0, 1, 1)x(0, 1, 0, 52)52 - AIC:949.7956407636462\n",
      "ARIMA(0, 1, 1)x(1, 0, 0, 52)52 - AIC:911.5987422228484\n",
      "ARIMA(0, 1, 1)x(1, 1, 0, 52)52 - AIC:478.85885637082396\n",
      "ARIMA(1, 0, 0)x(0, 0, 0, 52)52 - AIC:1390.1562939315152\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\sattwik\\Anaconda3\\lib\\site-packages\\statsmodels\\base\\model.py:512: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  \"Check mle_retvals\", ConvergenceWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ARIMA(1, 0, 0)x(0, 0, 1, 52)52 - AIC:4311.741793033698\n",
      "ARIMA(1, 0, 0)x(0, 1, 0, 52)52 - AIC:963.2128688236286\n",
      "ARIMA(1, 0, 0)x(1, 0, 0, 52)52 - AIC:935.7005697150435\n",
      "ARIMA(1, 0, 0)x(1, 0, 1, 52)52 - AIC:937.7002810264667\n",
      "ARIMA(1, 0, 0)x(1, 1, 0, 52)52 - AIC:474.49128577012516\n",
      "ARIMA(1, 0, 1)x(0, 0, 0, 52)52 - AIC:1336.8667719163045\n",
      "ARIMA(1, 0, 1)x(0, 0, 1, 52)52 - AIC:5655.105338234904\n",
      "ARIMA(1, 0, 1)x(0, 1, 0, 52)52 - AIC:956.0621195206874\n",
      "ARIMA(1, 0, 1)x(1, 0, 0, 52)52 - AIC:913.0120727853111\n",
      "ARIMA(1, 0, 1)x(1, 0, 1, 52)52 - AIC:905.3640203629012\n",
      "ARIMA(1, 0, 1)x(1, 1, 0, 52)52 - AIC:476.4821178046721\n",
      "ARIMA(1, 1, 0)x(0, 0, 0, 52)52 - AIC:1383.9675408365915\n",
      "ARIMA(1, 1, 0)x(0, 1, 0, 52)52 - AIC:985.3366175894603\n",
      "ARIMA(1, 1, 0)x(1, 0, 0, 52)52 - AIC:937.4622949685684\n",
      "ARIMA(1, 1, 0)x(1, 1, 0, 52)52 - AIC:486.05977052830934\n",
      "ARIMA(1, 1, 1)x(0, 0, 0, 52)52 - AIC:1328.6788745042618\n",
      "ARIMA(1, 1, 1)x(0, 1, 0, 52)52 - AIC:950.6214531158242\n",
      "ARIMA(1, 1, 1)x(1, 0, 0, 52)52 - AIC:906.4165439114367\n",
      "ARIMA(1, 1, 1)x(1, 1, 0, 52)52 - AIC:471.29536938840727\n"
     ]
    }
   ],
   "source": [
    "for param in pdq:\n",
    "    for param_seasonal in seasonal_pdq:\n",
    "        try:\n",
    "            mod = sm.tsa.statespace.SARIMAX(co_df_part_1_weekly['Requested_Quantity'],\n",
    "                                            order=param,\n",
    "                                            seasonal_order=param_seasonal,\n",
    "                                            enforce_stationarity=False,\n",
    "                                            enforce_invertibility=False)\n",
    "\n",
    "            results=mod.fit()\n",
    "            print('ARIMA{}x{}52 - AIC:{}'.format(param, param_seasonal, results.aic))\n",
    "        except:\n",
    "            continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "test01 = co_df_part_1_weekly['Requested_Quantity'][-6:]\n",
    "train01 = co_df_part_1_weekly['Requested_Quantity'][:-6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Indexdate\n",
       "2019-12-01     0.0\n",
       "2019-12-08     0.0\n",
       "2019-12-15    17.0\n",
       "2019-12-22    19.0\n",
       "2019-12-29     7.0\n",
       "2020-01-05     2.0\n",
       "Freq: W-SUN, Name: Requested_Quantity, dtype: float64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test01"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                 Statespace Model Results                                 \n",
      "==========================================================================================\n",
      "Dep. Variable:                 Requested_Quantity   No. Observations:                  151\n",
      "Model:             SARIMAX(0, 1, 1)x(1, 1, 0, 52)   Log Likelihood                -211.620\n",
      "Date:                            Tue, 28 Apr 2020   AIC                            429.240\n",
      "Time:                                    10:24:09   BIC                            434.726\n",
      "Sample:                                01-08-2017   HQIC                           431.295\n",
      "                                     - 11-24-2019                                         \n",
      "Covariance Type:                              opg                                         \n",
      "==============================================================================\n",
      "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "ma.L1         -0.9457      0.144     -6.556      0.000      -1.228      -0.663\n",
      "ar.S.L52      -0.5022      0.113     -4.461      0.000      -0.723      -0.282\n",
      "sigma2       552.8625     90.103      6.136      0.000     376.264     729.461\n",
      "===================================================================================\n",
      "Ljung-Box (Q):                       31.29   Jarque-Bera (JB):                18.29\n",
      "Prob(Q):                              0.84   Prob(JB):                         0.00\n",
      "Heteroskedasticity (H):               0.58   Skew:                             1.22\n",
      "Prob(H) (two-sided):                  0.31   Kurtosis:                         4.91\n",
      "===================================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n"
     ]
    }
   ],
   "source": [
    "mod01 = sm.tsa.statespace.SARIMAX(train01,\n",
    "                                order=(0, 1, 1),\n",
    "                                seasonal_order=(1, 1, 0, 52),\n",
    "                                enforce_stationarity=False,\n",
    "                                enforce_invertibility=False)\n",
    "results01 = mod01.fit()\n",
    "print(results01.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "results01.plot_diagnostics(figsize=(16, 8))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pred01 = results01.predict(start = test01.index[0], end = test01.index[-1], dynamic = True)\n",
    "plt.figure(figsize = (20, 10))\n",
    "plt.plot(train01.index, train01, label='Train')\n",
    "plt.plot(test01.index, test01, label='Test')\n",
    "plt.plot(pred01.index, pred01, label='SARIMA')\n",
    "plt.legend(loc='best');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                 Statespace Model Results                                 \n",
      "==========================================================================================\n",
      "Dep. Variable:                 Requested_Quantity   No. Observations:                  157\n",
      "Model:             SARIMAX(0, 1, 1)x(1, 1, 0, 52)   Log Likelihood                -236.429\n",
      "Date:                            Tue, 28 Apr 2020   AIC                            478.859\n",
      "Time:                                    12:24:26   BIC                            484.713\n",
      "Sample:                                01-08-2017   HQIC                           481.103\n",
      "                                     - 01-05-2020                                         \n",
      "Covariance Type:                              opg                                         \n",
      "==============================================================================\n",
      "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "ma.L1         -0.9477      0.117     -8.095      0.000      -1.177      -0.718\n",
      "ar.S.L52      -0.4881      0.103     -4.743      0.000      -0.690      -0.286\n",
      "sigma2       498.9550     72.709      6.862      0.000     356.448     641.462\n",
      "===================================================================================\n",
      "Ljung-Box (Q):                       30.96   Jarque-Bera (JB):                25.71\n",
      "Prob(Q):                              0.85   Prob(JB):                         0.00\n",
      "Heteroskedasticity (H):               0.40   Skew:                             1.26\n",
      "Prob(H) (two-sided):                  0.06   Kurtosis:                         5.35\n",
      "===================================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n"
     ]
    }
   ],
   "source": [
    "mod02 = sm.tsa.statespace.SARIMAX(co_df_part_1_weekly['Requested_Quantity'],\n",
    "                                order=(0, 1, 1),\n",
    "                                seasonal_order=(1, 1, 0, 52),\n",
    "                                enforce_stationarity=False,\n",
    "                                enforce_invertibility=False)\n",
    "results02 = mod02.fit()\n",
    "print(results02.summary()) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "forecast02 = results02.forecast(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-01-12     1.709484\n",
      "2020-01-19    26.912418\n",
      "2020-01-26    -3.754868\n",
      "2020-02-02    20.197601\n",
      "Freq: W-SUN, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(forecast02)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'mean_squared_error' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-50-3a664bfe6ffc>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mforecast01\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mresults01\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mforecast\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m6\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mrmse_s\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msqrt\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmean_squared_error\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtest01\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mforecast01\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrmse_s\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'mean_squared_error' is not defined"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "forecast01 = results01.forecast(6)\n",
    "rmse_s = np.sqrt(mean_squared_error(test01, forecast01))\n",
    "print(rmse_s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(co_df_part_1_weekly)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred001 = results01.get_prediction(start=130, dynamic=True)\n",
    "pred001_ci = pred001.conf_int()\n",
    "ax = co_df_part_1_weekly.Requested_Quantity[:].plot(label='observed', figsize=(25,10))\n",
    "pred001.predicted_mean.plot(ax=ax, label='One-step ahead Forecast', alpha=.9, figsize=(25,10))\n",
    "ax.fill_between(pred001_ci.index,\n",
    "                pred001_ci.iloc[:, 0],\n",
    "                pred001_ci.iloc[:, 1], color='k', alpha=.1)\n",
    "ax.set_xlabel('Date')\n",
    "ax.set_ylabel('Requested Quantity')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred001_ci"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "pred = results01.get_prediction(start=105, dynamic=True)\n",
    "pred_ci = pred.conf_int()\n",
    "ax = co_df_part_1_weekly.Requested_Quantity[:].plot(label='observed', figsize=(25,10))\n",
    "pred.predicted_mean.plot(ax=ax, label='One-step ahead Forecast', alpha=.9, figsize=(25,10))\n",
    "ax.fill_between(pred_ci.index,\n",
    "                pred_ci.iloc[:, 0],\n",
    "                pred_ci.iloc[:, 1], color='k', alpha=.1)\n",
    "ax.set_xlabel('Date')\n",
    "ax.set_ylabel('Requested Quantity')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Trying out normalisation:\n",
    "log transform is not possible because we have zero values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import MinMaxScaler\n",
    "\n",
    "# prepare data for normalization\n",
    "demand = co_df_part_1_weekly['Requested_Quantity'].values\n",
    "demand = demand.reshape((len(demand), 1))\n",
    "\n",
    "\n",
    "# train the normalization\n",
    "scaler = MinMaxScaler(feature_range=(0, 1))\n",
    "scaler = scaler.fit(demand)\n",
    "print('Min: %f, Max: %f' % (scaler.data_min_, scaler.data_max_))\n",
    "\n",
    "# normalize the dataset and print the first 5 rows\n",
    "co_df_part_1_weekly['Normalised_Quantity'] = scaler.transform(demand)\n",
    "\n",
    "'''\n",
    "# inverse transform and print the first 5 rows\n",
    "inversed = scaler.inverse_transform(normalized)\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df_part_1_weekly.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "demand_part = co_df_part_1_weekly[\"Normalised_Quantity\"].values.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "neg_demand=[]\n",
    "for x in demand_part:\n",
    "    if x == 0:\n",
    "        neg_demand.append(x)\n",
    "print(len(neg_demand))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "decomposition_n = seasonal_decompose(co_df_part_1_weekly[\"Normalised_Quantity\"].dropna())\n",
    "\n",
    "trend_n = decomposition_n.trend\n",
    "seasonal_n = decomposition_n.seasonal\n",
    "residual_n = decomposition_n.resid\n",
    "\n",
    "f = plt.figure(figsize=(30,15))\n",
    "ax1 = f.add_subplot(411)\n",
    "ax2 = f.add_subplot(412)\n",
    "ax3 = f.add_subplot(413)\n",
    "ax4 = f.add_subplot(414)\n",
    "\n",
    "ax1.plot(trend_n, label = 'Trend')\n",
    "ax1.legend(loc='best')\n",
    "\n",
    "ax2.plot(seasonal_n, label = 'Seasonal')\n",
    "ax2.legend(loc='best')\n",
    "\n",
    "ax3.plot(residual_n, label= 'Residual')\n",
    "ax3.legend(loc='best')\n",
    "\n",
    "ax4.plot(co_df_part_1_weekly.index, co_df_part_1_weekly['Normalised_Quantity'], label= 'Original')\n",
    "ax4.legend(loc='best')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "mod02 = sm.tsa.statespace.SARIMAX(co_df_part_1_weekly['Normalised_Quantity'],\n",
    "                                order=(1, 0, 1),\n",
    "                                seasonal_order=(1, 1, 0, 52),\n",
    "                                enforce_stationarity=False,\n",
    "                                enforce_invertibility=False)\n",
    "results02 = mod02.fit()\n",
    "print(results02.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "results02.plot_diagnostics(figsize=(16, 8))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df_part_1_weekly['Normalised_Forecast']=results01.predict(start=105, end = 157, dynamic = True)\n",
    "co_df_part_1_weekly[['Normalised_Quantity','Normalised_Forecast']].plot(figsize=(25,10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Trying forecasting on monthly sampled data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df_part_1_monthly = co_df_part_1.resample('M').sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df_part_1_monthly.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(co_df_part_1_monthly)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df_part_1_monthly['Requested_Quantity'].plot(figsize=(20,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "decomposition_m = seasonal_decompose(co_df_part_1_monthly[\"Requested_Quantity\"])\n",
    "\n",
    "trend_m = decomposition_m.trend\n",
    "seasonal_m = decomposition_m.seasonal\n",
    "residual_m = decomposition_m.resid\n",
    "\n",
    "f = plt.figure(figsize=(30,15))\n",
    "ax1 = f.add_subplot(411)\n",
    "ax2 = f.add_subplot(412)\n",
    "ax3 = f.add_subplot(413)\n",
    "ax4 = f.add_subplot(414)\n",
    "\n",
    "ax1.plot(trend_m, label = 'Trend')\n",
    "ax1.legend(loc='best')\n",
    "\n",
    "ax2.plot(seasonal_m, label = 'Seasonal')\n",
    "ax2.legend(loc='best')\n",
    "\n",
    "ax3.plot(residual_m, label= 'Residual')\n",
    "ax3.legend(loc='best')\n",
    "\n",
    "ax4.plot(co_df_part_1_monthly.index, co_df_part_1_monthly['Requested_Quantity'], label= 'Original')\n",
    "ax4.legend(loc='best')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot_pacf(co_df_part_1_monthly['Requested_Quantity'], lags=16)\n",
    "plot_acf(co_df_part_1_monthly['Requested_Quantity'], lags=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dftest = adfuller(co_df_part_1_monthly[\"Requested_Quantity\"], autolag='AIC')\n",
    "\n",
    "dftest_output = pd.Series(dftest[0:4], index=['Test Statistic', 'p-value', '#lags used', 'number of obserbations used'])\n",
    "for key, value in dftest[4].items():\n",
    "    dftest_output['Critical Values (%s)' %key]=value\n",
    "    \n",
    "print(dftest_output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = co_df_part_1_monthly['Requested_Quantity'][:-3]\n",
    "test = co_df_part_1_monthly['Requested_Quantity'][-5:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "p = d = q = range(0,2)\n",
    "pdq = list(itertools.product(p, d, q))\n",
    "seasonal_pdq = [(x[0], x[1], x[2], 12) for x in list(itertools.product(p, d, q))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for param in pdq:\n",
    "    for param_seasonal in seasonal_pdq:\n",
    "        try:\n",
    "            mod = sm.tsa.statespace.SARIMAX(train,\n",
    "                                            order=param,\n",
    "                                            seasonal_order=param_seasonal,\n",
    "                                            enforce_stationarity=False,\n",
    "                                            enforce_invertibility=False)\n",
    "\n",
    "            results=mod.fit()\n",
    "            print('ARIMA{}x{}12 - AIC:{}'.format(param, param_seasonal, results.aic))\n",
    "        except:\n",
    "            continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "mod04 = sm.tsa.statespace.SARIMAX(train,\n",
    "                                order=(1, 1, 1),\n",
    "                                seasonal_order=(1, 1, 0, 12),\n",
    "                                enforce_stationarity=False,\n",
    "                                enforce_invertibility=False)\n",
    "results04 = mod04.fit()\n",
    "print(results04.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "co_df_part_1_monthly['Monthly_Forecast']=results04.predict(start = test.index[0], end = test.index[-1], dynamic = True)\n",
    "co_df_part_1_monthly[['Requested_Quantity','Monthly_Forecast']].plot(figsize=(25,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred = results04.predict(start = test.index[0], end = test.index[-1], dynamic = True)\n",
    "plt.plot(train.index, train, label='Train')\n",
    "plt.plot(test.index, test, label='Test')\n",
    "plt.plot(pred.index, pred, label='SARIMA')\n",
    "plt.legend(loc='best');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df_part_1_monthly[['Requested_Quantity', 'Monthly_Forecast']][25:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "rmse_SARIMA = np.sqrt(mean_squared_error(test,pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Holt Winter's Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.tsa.holtwinters import ExponentialSmoothing\n",
    "from sklearn.metrics import mean_squared_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "co_df_part_1_monthly.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def exp_smoothing_configs(seasonal=[None]):\n",
    "    models = list()\n",
    "    # define config lists\n",
    "    t_params = ['add', 'mul', None]\n",
    "    d_params = [True, False]\n",
    "    s_params = ['add', 'mul', None]\n",
    "    p_params = seasonal\n",
    "    b_params = [True, False]\n",
    "    r_params = [True, False]\n",
    "    # create config instances\n",
    "    for t in t_params:\n",
    "        for d in d_params:\n",
    "            for s in s_params:\n",
    "                for p in p_params:\n",
    "                    for b in b_params:\n",
    "                        for r in r_params:\n",
    "                            cfg = [t,d,s,p,b,r]\n",
    "                            models.append(cfg)\n",
    "    return models\n",
    "\n",
    "cfg_list = exp_smoothing_configs(seasonal=[12])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = co_df_part_1_monthly['Requested_Quantity'][:-5]\n",
    "test = co_df_part_1_monthly['Requested_Quantity'][-6:]\n",
    "#ind = train.index[34:]  # this will select last 12 months' indexes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Holt's Winter Model\")\n",
    "best_RMSE = np.inf\n",
    "best_config = []\n",
    "t1 = d1 = s1 = p1 = b1 = r1 = ''\n",
    "for j in range(len(cfg_list)):\n",
    "    print(j)\n",
    "    try:\n",
    "        cg = cfg_list[j]\n",
    "        print(cg)\n",
    "        t,d,s,p,b,r = cg\n",
    "        # define model\n",
    "        if not t:\n",
    "            model = ExponentialSmoothing(train, trend=t, seasonal=s, seasonal_periods=p)\n",
    "        else:\n",
    "            model = ExponentialSmoothing(train, trend=t, damped=d, seasonal=s, seasonal_periods=p)\n",
    "            \n",
    "        # fit model\n",
    "        model_fit = model.fit(optimized=True, use_boxcox=b, remove_bias=r)\n",
    "        # make one step forecast\n",
    "        y_forecast = model_fit.forecast(5)\n",
    "        rmse = np.sqrt(mean_squared_error(test,y_forecast))\n",
    "        print(rmse)\n",
    "        if rmse < best_RMSE:\n",
    "            best_RMSE = rmse\n",
    "            best_config = cfg_list[j]\n",
    "    except:\n",
    "       continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(best_RMSE, best_config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "t1,d1,s1,p1,b1,r1 = best_config\n",
    "\n",
    "if not t1:\n",
    "    hw_model1 = ExponentialSmoothing(train, trend=t1, seasonal=s1, seasonal_periods=p1)\n",
    "else:\n",
    "    hw_model1 = ExponentialSmoothing(train, trend=t1, seasonal=s1, seasonal_periods=p1, damped=d1)\n",
    "\n",
    "fit2 = hw_model1.fit(optimized=True, use_boxcox=b1, remove_bias=r1)\n",
    "\n",
    "pred_HW = fit2.predict(start=test.index[0], end = test.index[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(train.index, train, label='Train')\n",
    "plt.plot(test.index, test, label='Test')\n",
    "plt.plot(pred_HW.index, pred_HW, label=\"Holt Winter's\")\n",
    "plt.legend(loc='best');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rmse_HW = np.sqrt(mean_squared_error(test,y_forecast))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(f\"RMSE_SARIMA = {rmse_SARIMA} \\nRMSE_HW = {rmse_HW}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_w = co_df_part_1_weekly['Requested_Quantity'][:-6]\n",
    "test_w = co_df_part_1_weekly['Requested_Quantity'][-6:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cfg_list = exp_smoothing_configs(seasonal=[52])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cfg_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Holt's Winter Model\")\n",
    "best_RMSE = np.inf\n",
    "best_config = []\n",
    "t1 = d1 = s1 = p1 = b1 = r1 = ''\n",
    "for j in range(len(cfg_list)):\n",
    "    print(j)\n",
    "    try:\n",
    "        cg = cfg_list[j]\n",
    "        print(cg)\n",
    "        t,d,s,p,b,r = cg\n",
    "        # define model\n",
    "        if not t:\n",
    "            wmodel = ExponentialSmoothing(train_w, trend=t, seasonal=s, seasonal_periods=p)\n",
    "        else:\n",
    "            wmodel = ExponentialSmoothing(train_w, trend=t, damped=d, seasonal=s, seasonal_periods=p)\n",
    "        # fit model\n",
    "        print(\"inside\")\n",
    "        wmodel_fit = wmodel.fit(optimized=True, use_boxcox=b, remove_bias=r)\n",
    "        # make one step forecast\n",
    "        w_forecast = wmodel_fit.forecast(6)\n",
    "        rmse = np.sqrt(mean_squared_error(test_w, w_forecast))\n",
    "        \n",
    "        print(rmse)\n",
    "        if rmse < best_RMSE:\n",
    "            best_RMSE = rmse\n",
    "            best_config = cfg_list[j]\n",
    "    except:\n",
    "       continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(best_RMSE, best_config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "t1,d1,s1,p1,b1,r1 = best_config\n",
    "\n",
    "if not t1:\n",
    "    hw_modelw = ExponentialSmoothing(train_w, trend=t1, seasonal=s1, seasonal_periods=p1)\n",
    "else:\n",
    "    hw_modelw = ExponentialSmoothing(train_w, trend=t1, seasonal=s1, seasonal_periods=p1, damped=d1)\n",
    "\n",
    "fitw = hw_modelw.fit(optimized=True, use_boxcox=b1, remove_bias=r1)\n",
    "\n",
    "wpred_HW = fitw.predict(start=test_w.index[0], end = test_w.index[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "print(fitw.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fitw.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(30, 15))\n",
    "plt.plot(train_w.index, train_w, label='Train')\n",
    "plt.plot(test_w.index, test_w, label='Test')\n",
    "plt.plot(wpred_HW.index, wpred_HW, label=\"Holt Winter's\")\n",
    "plt.legend(loc='best');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hw_forecast = fitw.forecast(6)\n",
    "rmse = np.sqrt(mean_squared_error(test_w, hw_forecast))\n",
    "print(rmse)"
   ]
  }
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