Forecast Future_time series auto ARIMA.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "dd79698c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#https://towardsdatascience.com/time-series-forecasting-with-arima-sarima-and-sarimax-ee61099e78f6"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71821723",
   "metadata": {},
   "source": [
    "- p: The order of the auto-regressive (AR) model (i.e., the number of lag observations). A time series is considered AR when previous values in the time series are very predictive of later values. An AR process will show a very gradual decrease in the ACF plot.\n",
    "- d: The degree of differencing.\n",
    "- q: The order of the moving average (MA) model. This is essentially the size of the “window” function over your time series data. An MA process is a linear combination of past errors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e7b013a7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-15T16:48:18.564262Z",
     "iopub.status.busy": "2022-06-15T16:48:18.562424Z",
     "iopub.status.idle": "2022-06-15T16:48:32.502922Z",
     "shell.execute_reply": "2022-06-15T16:48:32.502074Z",
     "shell.execute_reply.started": "2022-06-15T16:40:42.098111Z"
    },
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     "duration": 13.963706,
     "end_time": "2022-06-15T16:48:32.503095",
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     "start_time": "2022-06-15T16:48:18.539389",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pylab as plt\n",
    "%matplotlib inline\n",
    "from matplotlib.pylab import rcParams\n",
    "from pmdarima.arima import auto_arima\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "import pickle\n",
    "from statsmodels.tsa.stattools import adfuller\n",
    "!pip install pmdarima --quiet\n",
    "import pmdarima as pm\n",
    "\n",
    "import panel as pn\n",
    "from pmdarima.arima import auto_arima\n",
    "from xgboost import XGBRegressor\n",
    "import statsmodels.api as sm\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.tsa.arima_model import ARIMA\n",
    "from statsmodels.tsa.arima_model import ARMA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fbddb3f1",
   "metadata": {},
   "source": [
    "## load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1cd0635b",
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>2007-12-10</td>\n",
       "      <td>9.5908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2007-12-11</td>\n",
       "      <td>8.5196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2007-12-12</td>\n",
       "      <td>8.1837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2007-12-13</td>\n",
       "      <td>8.0725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2007-12-14</td>\n",
       "      <td>7.8936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>500</td>\n",
       "      <td>2009-04-23</td>\n",
       "      <td>7.4742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>501</td>\n",
       "      <td>2009-04-24</td>\n",
       "      <td>7.6718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>502</td>\n",
       "      <td>2009-04-25</td>\n",
       "      <td>7.8423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>503</td>\n",
       "      <td>2009-04-26</td>\n",
       "      <td>7.9241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>504</td>\n",
       "      <td>2009-04-27</td>\n",
       "      <td>7.8284</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      ID          ds       y\n",
       "0      0  2007-12-10  9.5908\n",
       "1      1  2007-12-11  8.5196\n",
       "2      2  2007-12-12  8.1837\n",
       "3      3  2007-12-13  8.0725\n",
       "4      4  2007-12-14  7.8936\n",
       "..   ...         ...     ...\n",
       "495  500  2009-04-23  7.4742\n",
       "496  501  2009-04-24  7.6718\n",
       "497  502  2009-04-25  7.8423\n",
       "498  503  2009-04-26  7.9241\n",
       "499  504  2009-04-27  7.8284\n",
       "\n",
       "[500 rows x 3 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_location = \"C:/Users/hotaha/OneDrive - dormakaba Group/Desktop/Python/Data/\"\n",
    "#df = pd.read_excel(data_location + \"sensordata_ED250_GE10_25-271022.xlsx\")\n",
    "#X, y = df.iloc[:, :-2], df.iloc[:, -1]\n",
    "#df = pd.read_csv(data_location + \"export_ED250_GE10 81122 - 4 wochen.csv\")\n",
    "df = pd.read_csv(data_location + \"export_sensor_data_laks.csv\")\n",
    "df=df[:500]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f51f3b7c",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Month</th>\n",
       "      <th>#y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2007-12-10</td>\n",
       "      <td>9.5908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2007-12-11</td>\n",
       "      <td>8.5196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2007-12-12</td>\n",
       "      <td>8.1837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2007-12-13</td>\n",
       "      <td>8.0725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2007-12-14</td>\n",
       "      <td>7.8936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>500</td>\n",
       "      <td>2009-04-23</td>\n",
       "      <td>7.4742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>501</td>\n",
       "      <td>2009-04-24</td>\n",
       "      <td>7.6718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>502</td>\n",
       "      <td>2009-04-25</td>\n",
       "      <td>7.8423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>503</td>\n",
       "      <td>2009-04-26</td>\n",
       "      <td>7.9241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>504</td>\n",
       "      <td>2009-04-27</td>\n",
       "      <td>7.8284</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      ID       Month      #y\n",
       "0      0  2007-12-10  9.5908\n",
       "1      1  2007-12-11  8.5196\n",
       "2      2  2007-12-12  8.1837\n",
       "3      3  2007-12-13  8.0725\n",
       "4      4  2007-12-14  7.8936\n",
       "..   ...         ...     ...\n",
       "495  500  2009-04-23  7.4742\n",
       "496  501  2009-04-24  7.6718\n",
       "497  502  2009-04-25  7.8423\n",
       "498  503  2009-04-26  7.9241\n",
       "499  504  2009-04-27  7.8284\n",
       "\n",
       "[500 rows x 3 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.rename(columns={\n",
    "    0: \"DT\",\n",
    "    1: \"DT 2\",\n",
    "    2: \"DT 3\",\n",
    "    \n",
    "    3: \"Position\",\n",
    "    \"ds\": \"Month\",\n",
    "   \"Month\": \"#Month\",\n",
    "    \"y\": \"#y\",\n",
    "    7: \"DebugText\",\n",
    "    8: \"TargetAcceleration\",\n",
    "    9: \"GearControl\",\n",
    "   \n",
    "})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6b8f2a10",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df.drop(columns=['ID'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fb8daa17",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Month</th>\n",
       "      <th>#y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2007-12-10</td>\n",
       "      <td>9.5908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007-12-11</td>\n",
       "      <td>8.5196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007-12-12</td>\n",
       "      <td>8.1837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2007-12-13</td>\n",
       "      <td>8.0725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2007-12-14</td>\n",
       "      <td>7.8936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>2009-04-23</td>\n",
       "      <td>7.4742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>2009-04-24</td>\n",
       "      <td>7.6718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>2009-04-25</td>\n",
       "      <td>7.8423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>2009-04-26</td>\n",
       "      <td>7.9241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>2009-04-27</td>\n",
       "      <td>7.8284</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Month      #y\n",
       "0    2007-12-10  9.5908\n",
       "1    2007-12-11  8.5196\n",
       "2    2007-12-12  8.1837\n",
       "3    2007-12-13  8.0725\n",
       "4    2007-12-14  7.8936\n",
       "..          ...     ...\n",
       "495  2009-04-23  7.4742\n",
       "496  2009-04-24  7.6718\n",
       "497  2009-04-25  7.8423\n",
       "498  2009-04-26  7.9241\n",
       "499  2009-04-27  7.8284\n",
       "\n",
       "[500 rows x 2 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b712ad40",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df2=df.groupby(by=[df.index.month, df.index.year])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d96c081d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Month']=pd.to_datetime(df['Month'].astype(str), format='%Y-%m-%d')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "42a20955",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df=df.drop_duplicates(subset=['Month'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "07e1dde9",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df=df.sort_values(by=['Month'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e51d9955",
   "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>#y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2007-12-10</th>\n",
       "      <td>9.5908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-11</th>\n",
       "      <td>8.5196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-12</th>\n",
       "      <td>8.1837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-13</th>\n",
       "      <td>8.0725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-14</th>\n",
       "      <td>7.8936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-23</th>\n",
       "      <td>7.4742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-24</th>\n",
       "      <td>7.6718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-25</th>\n",
       "      <td>7.8423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-26</th>\n",
       "      <td>7.9241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-27</th>\n",
       "      <td>7.8284</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                #y\n",
       "Month             \n",
       "2007-12-10  9.5908\n",
       "2007-12-11  8.5196\n",
       "2007-12-12  8.1837\n",
       "2007-12-13  8.0725\n",
       "2007-12-14  7.8936\n",
       "...            ...\n",
       "2009-04-23  7.4742\n",
       "2009-04-24  7.6718\n",
       "2009-04-25  7.8423\n",
       "2009-04-26  7.9241\n",
       "2009-04-27  7.8284\n",
       "\n",
       "[500 rows x 1 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "df=df.set_index(['Month'])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bfee2793",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df=df.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f69d1682",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "61e5ac7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#X = pd.to_datetime(df['Month'])\n",
    "\n",
    "#X"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8edabbf",
   "metadata": {},
   "source": [
    "## Fill date gaps "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f53edf17",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df['Month'] = pd.to_datetime(df['Month'])\n",
    "\n",
    "df['#y2']= df['#y'].resample('D').mean()\n",
    "\n",
    "#df = df.set_index('Month') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4de16a9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "date_new= df['#y'].resample('D').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ecec5297",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Month']=date_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0ff60873",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2007-12-10</th>\n",
       "      <td>9.5908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-11</th>\n",
       "      <td>8.5196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-12</th>\n",
       "      <td>8.1837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-13</th>\n",
       "      <td>8.0725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-14</th>\n",
       "      <td>7.8936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-23</th>\n",
       "      <td>7.4742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-24</th>\n",
       "      <td>7.6718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-25</th>\n",
       "      <td>7.8423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-26</th>\n",
       "      <td>7.9241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-27</th>\n",
       "      <td>7.8284</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>505 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                #y\n",
       "Month             \n",
       "2007-12-10  9.5908\n",
       "2007-12-11  8.5196\n",
       "2007-12-12  8.1837\n",
       "2007-12-13  8.0725\n",
       "2007-12-14  7.8936\n",
       "...            ...\n",
       "2009-04-23  7.4742\n",
       "2009-04-24  7.6718\n",
       "2009-04-25  7.8423\n",
       "2009-04-26  7.9241\n",
       "2009-04-27  7.8284\n",
       "\n",
       "[505 rows x 1 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2=date_new.to_frame()\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c6deaa46",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d92b6695",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df2=X.resample('D', on=X).mean()\n",
    "#df2=df2.reset_index()\n",
    "\n",
    "#df2.tail(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2fc1d866",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "84ac1181",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df.groupby(pd.Grouper(freq='M')) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8ce64b50",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df['month_index2'] = df.index.month\n",
    "#df['month_index2']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "091d1c45",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df['Month']=pd.to_datetime(df['Month'].astype(str), format='%Y-%m-%d')\n",
    "df=df.sort_values(by=['Month'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ae814b61",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2007-12-10</th>\n",
       "      <td>9.5908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-11</th>\n",
       "      <td>8.5196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-12</th>\n",
       "      <td>8.1837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-13</th>\n",
       "      <td>8.0725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-14</th>\n",
       "      <td>7.8936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-23</th>\n",
       "      <td>7.4742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-24</th>\n",
       "      <td>7.6718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-25</th>\n",
       "      <td>7.8423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-26</th>\n",
       "      <td>7.9241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-27</th>\n",
       "      <td>7.8284</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>505 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                #y\n",
       "Month             \n",
       "2007-12-10  9.5908\n",
       "2007-12-11  8.5196\n",
       "2007-12-12  8.1837\n",
       "2007-12-13  8.0725\n",
       "2007-12-14  7.8936\n",
       "...            ...\n",
       "2009-04-23  7.4742\n",
       "2009-04-24  7.6718\n",
       "2009-04-25  7.8423\n",
       "2009-04-26  7.9241\n",
       "2009-04-27  7.8284\n",
       "\n",
       "[505 rows x 1 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "1e947093",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df=df.drop_duplicates(subset=['Month'])\n",
    "#df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c56116cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "#df=df.set_index(['Month'])\n",
    "#df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ace10fc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2007-12-10</th>\n",
       "      <td>9.5908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-11</th>\n",
       "      <td>8.5196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-12</th>\n",
       "      <td>8.1837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-13</th>\n",
       "      <td>8.0725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-14</th>\n",
       "      <td>7.8936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-23</th>\n",
       "      <td>7.4742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-24</th>\n",
       "      <td>7.6718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-25</th>\n",
       "      <td>7.8423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-26</th>\n",
       "      <td>7.9241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-04-27</th>\n",
       "      <td>7.8284</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>505 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                #y\n",
       "Month             \n",
       "2007-12-10  9.5908\n",
       "2007-12-11  8.5196\n",
       "2007-12-12  8.1837\n",
       "2007-12-13  8.0725\n",
       "2007-12-14  7.8936\n",
       "...            ...\n",
       "2009-04-23  7.4742\n",
       "2009-04-24  7.6718\n",
       "2009-04-25  7.8423\n",
       "2009-04-26  7.9241\n",
       "2009-04-27  7.8284\n",
       "\n",
       "[505 rows x 1 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "f81243bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#y    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "id": "d4462693",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df[\"#Passengers\"]=str(df[\"#Passengers\"])\n",
    "#df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3b4a0de",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-15T16:48:32.586300Z",
     "iopub.status.busy": "2022-06-15T16:48:32.585640Z",
     "iopub.status.idle": "2022-06-15T16:48:32.633446Z",
     "shell.execute_reply": "2022-06-15T16:48:32.633991Z",
     "shell.execute_reply.started": "2022-06-15T16:40:51.994105Z"
    },
    "papermill": {
     "duration": 0.073606,
     "end_time": "2022-06-15T16:48:32.634158",
     "exception": false,
     "start_time": "2022-06-15T16:48:32.560552",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## plot the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "0f4508bf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-15T16:48:32.722323Z",
     "iopub.status.busy": "2022-06-15T16:48:32.721610Z",
     "iopub.status.idle": "2022-06-15T16:48:33.002953Z",
     "shell.execute_reply": "2022-06-15T16:48:33.003468Z",
     "shell.execute_reply.started": "2022-06-15T16:40:52.012450Z"
    },
    "papermill": {
     "duration": 0.310647,
     "end_time": "2022-06-15T16:48:33.003637",
     "exception": false,
     "start_time": "2022-06-15T16:48:32.692990",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,7))\n",
    "plt.title(\"Number of Airline Passengers by Date\")\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('y')\n",
    "plt.plot(df)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "240c9f06",
   "metadata": {
    "papermill": {
     "duration": 0.024952,
     "end_time": "2022-06-15T16:48:33.575586",
     "exception": false,
     "start_time": "2022-06-15T16:48:33.550634",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## <center>ARIMA Model Selection w/ Auto-ARIMA</center>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4334bf0a",
   "metadata": {},
   "source": [
    "## fill values with mean values "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "1f971f1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#y    5\n",
       "dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d038da4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['#y'].fillna(value=df['#y'].mean(), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "2887c11a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#y    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "82bef2bd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-15T16:48:33.102642Z",
     "iopub.status.busy": "2022-06-15T16:48:33.093708Z",
     "iopub.status.idle": "2022-06-15T16:48:33.397417Z",
     "shell.execute_reply": "2022-06-15T16:48:33.397935Z",
     "shell.execute_reply.started": "2022-06-15T16:40:52.215410Z"
    },
    "papermill": {
     "duration": 0.33004,
     "end_time": "2022-06-15T16:48:33.398108",
     "exception": false,
     "start_time": "2022-06-15T16:48:33.068068",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Determine rolling statistics\n",
    "df[\"rolling_avg\"] = df[\"#y\"].rolling(window=12).mean() #window size 12 denotes 12 months, giving rolling mean at yearly level\n",
    "df[\"rolling_std\"] = df[\"#y\"].rolling(window=12).std()\n",
    "\n",
    "#Plot rolling statistics\n",
    "plt.figure(figsize=(15,7))\n",
    "plt.plot(df[\"#y\"], color='#379BDB', label='Original')\n",
    "plt.plot(df[\"rolling_avg\"], color='#D22A0D', label='Rolling Mean')\n",
    "plt.plot(df[\"rolling_std\"], color='#142039', label='Rolling Std')\n",
    "plt.legend(loc='best')\n",
    "plt.title('Rolling Mean & Standard Deviation')\n",
    "plt.show(block=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "64bf4a2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#auto_arima??"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "962b9d01",
   "metadata": {},
   "source": [
    "## ARIMA "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "5e28ac1a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Performing stepwise search to minimize aic\n",
      " ARIMA(1,1,1)(0,0,0)[0] intercept   : AIC=431.001, Time=0.85 sec\n",
      " ARIMA(0,1,0)(0,0,0)[0] intercept   : AIC=507.135, Time=0.17 sec\n",
      " ARIMA(1,1,0)(0,0,0)[0] intercept   : AIC=505.691, Time=0.22 sec\n",
      " ARIMA(0,1,1)(0,0,0)[0] intercept   : AIC=500.314, Time=0.20 sec\n",
      " ARIMA(0,1,0)(0,0,0)[0]             : AIC=505.173, Time=0.10 sec\n",
      " ARIMA(2,1,1)(0,0,0)[0] intercept   : AIC=412.987, Time=1.05 sec\n",
      " ARIMA(2,1,0)(0,0,0)[0] intercept   : AIC=465.732, Time=0.29 sec\n",
      " ARIMA(3,1,1)(0,0,0)[0] intercept   : AIC=414.962, Time=1.04 sec\n",
      " ARIMA(2,1,2)(0,0,0)[0] intercept   : AIC=414.741, Time=1.36 sec\n",
      " ARIMA(1,1,2)(0,0,0)[0] intercept   : AIC=413.379, Time=0.92 sec\n",
      " ARIMA(3,1,0)(0,0,0)[0] intercept   : AIC=458.981, Time=0.32 sec\n",
      " ARIMA(3,1,2)(0,0,0)[0] intercept   : AIC=416.303, Time=1.94 sec\n",
      " ARIMA(2,1,1)(0,0,0)[0]             : AIC=411.166, Time=0.28 sec\n",
      " ARIMA(1,1,1)(0,0,0)[0]             : AIC=429.279, Time=0.21 sec\n",
      " ARIMA(2,1,0)(0,0,0)[0]             : AIC=463.783, Time=0.09 sec\n",
      " ARIMA(3,1,1)(0,0,0)[0]             : AIC=413.145, Time=0.45 sec\n",
      " ARIMA(2,1,2)(0,0,0)[0]             : AIC=412.934, Time=0.64 sec\n",
      " ARIMA(1,1,0)(0,0,0)[0]             : AIC=503.732, Time=0.11 sec\n",
      " ARIMA(1,1,2)(0,0,0)[0]             : AIC=411.592, Time=0.42 sec\n",
      " ARIMA(3,1,0)(0,0,0)[0]             : AIC=457.037, Time=0.16 sec\n",
      " ARIMA(3,1,2)(0,0,0)[0]             : AIC=414.488, Time=0.81 sec\n",
      "\n",
      "Best model:  ARIMA(2,1,1)(0,0,0)[0]          \n",
      "Total fit time: 11.773 seconds\n"
     ]
    }
   ],
   "source": [
    "#Standard ARIMA Model\n",
    "ARIMA_model = auto_arima(df['#y'], \n",
    "                      start_p=1, \n",
    "                      start_q=1,\n",
    "                      test='adf', # use adftest to find optimal 'd'\n",
    "                      max_p=3, max_q=3, # maximum p and q\n",
    "                      m=1, # frequency of series (if m==1, seasonal is set to FALSE automatically)\n",
    "                      d=None,# let model determine 'd'\n",
    "                      seasonal=False, # No Seasonality for standard ARIMA\n",
    "                      trace=True, #logs \n",
    "                      error_action='warn', #shows errors ('ignore' silences these)\n",
    "                      suppress_warnings=True,\n",
    "                      stepwise=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "a099c368",
   "metadata": {},
   "outputs": [],
   "source": [
    "file_name = \"ARIMA_model_reg.pkl\"\n",
    "\n",
    "# save\n",
    "#pickle.dump(ARIMA_model, open(file_name, \"wb\"))\n",
    "\n",
    "# load\n",
    "ARIMA_model = pickle.load(open(file_name, \"rb\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "38521aca",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-15T16:48:33.625892Z",
     "iopub.status.busy": "2022-06-15T16:48:33.625263Z",
     "iopub.status.idle": "2022-06-15T16:48:37.902079Z",
     "shell.execute_reply": "2022-06-15T16:48:37.903162Z",
     "shell.execute_reply.started": "2022-06-15T16:40:52.462306Z"
    },
    "papermill": {
     "duration": 4.304249,
     "end_time": "2022-06-15T16:48:37.903485",
     "exception": false,
     "start_time": "2022-06-15T16:48:33.599236",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>SARIMAX Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>           <td>y</td>        <th>  No. Observations:  </th>    <td>505</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>           <td>SARIMAX(2, 1, 1)</td> <th>  Log Likelihood     </th> <td>-201.583</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>            <td>Sat, 12 Nov 2022</td> <th>  AIC                </th>  <td>411.166</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                <td>17:27:06</td>     <th>  BIC                </th>  <td>428.056</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sample:</th>             <td>12-10-2007</td>    <th>  HQIC               </th>  <td>417.792</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th></th>                   <td>- 04-27-2009</td>   <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>        <td>opg</td>       <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "     <td></td>       <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L1</th>  <td>    0.5674</td> <td>    0.050</td> <td>   11.458</td> <td> 0.000</td> <td>    0.470</td> <td>    0.664</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L2</th>  <td>   -0.2259</td> <td>    0.050</td> <td>   -4.542</td> <td> 0.000</td> <td>   -0.323</td> <td>   -0.128</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L1</th>  <td>   -0.8226</td> <td>    0.044</td> <td>  -18.597</td> <td> 0.000</td> <td>   -0.909</td> <td>   -0.736</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>sigma2</th> <td>    0.1301</td> <td>    0.004</td> <td>   32.180</td> <td> 0.000</td> <td>    0.122</td> <td>    0.138</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Ljung-Box (L1) (Q):</th>     <td>0.03</td> <th>  Jarque-Bera (JB):  </th> <td>2215.45</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Q):</th>                <td>0.87</td> <th>  Prob(JB):          </th>  <td>0.00</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Heteroskedasticity (H):</th> <td>0.60</td> <th>  Skew:              </th>  <td>2.05</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(H) (two-sided):</th>    <td>0.00</td> <th>  Kurtosis:          </th>  <td>12.42</td> \n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Covariance matrix calculated using the outer product of gradients (complex-step)."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                               SARIMAX Results                                \n",
       "==============================================================================\n",
       "Dep. Variable:                      y   No. Observations:                  505\n",
       "Model:               SARIMAX(2, 1, 1)   Log Likelihood                -201.583\n",
       "Date:                Sat, 12 Nov 2022   AIC                            411.166\n",
       "Time:                        17:27:06   BIC                            428.056\n",
       "Sample:                    12-10-2007   HQIC                           417.792\n",
       "                         - 04-27-2009                                         \n",
       "Covariance Type:                  opg                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "ar.L1          0.5674      0.050     11.458      0.000       0.470       0.664\n",
       "ar.L2         -0.2259      0.050     -4.542      0.000      -0.323      -0.128\n",
       "ma.L1         -0.8226      0.044    -18.597      0.000      -0.909      -0.736\n",
       "sigma2         0.1301      0.004     32.180      0.000       0.122       0.138\n",
       "===================================================================================\n",
       "Ljung-Box (L1) (Q):                   0.03   Jarque-Bera (JB):              2215.45\n",
       "Prob(Q):                              0.87   Prob(JB):                         0.00\n",
       "Heteroskedasticity (H):               0.60   Skew:                             2.05\n",
       "Prob(H) (two-sided):                  0.00   Kurtosis:                        12.42\n",
       "===================================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
       "\"\"\""
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "\n",
    "#ARIMA_model = sm.tsa.arima.ARIMA((df['#Passengers']),  order=(3,1,4))\n",
    "\n",
    "(ARIMA_model.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "f783f92b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-15T16:48:38.023222Z",
     "iopub.status.busy": "2022-06-15T16:48:38.022155Z",
     "iopub.status.idle": "2022-06-15T16:48:38.642529Z",
     "shell.execute_reply": "2022-06-15T16:48:38.641988Z",
     "shell.execute_reply.started": "2022-06-15T16:40:55.043759Z"
    },
    "papermill": {
     "duration": 0.6624,
     "end_time": "2022-06-15T16:48:38.642685",
     "exception": false,
     "start_time": "2022-06-15T16:48:37.980285",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1080x864 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ARIMA_model.plot_diagnostics(figsize=(15,12))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "5cefe9ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def forecast(ARIMA_model, periods=356):\n",
    "    # Forecast\n",
    "    n_periods = periods\n",
    "    fitted, confint = ARIMA_model.predict(n_periods=n_periods, return_conf_int=True)\n",
    "    #pred = ARIMA_model.predict(n_periods=len(df[\"#y\"]),dynamic=True)\n",
    "    index_of_fc = pd.date_range(df.index[-1] + pd.DateOffset(days=1), periods = n_periods, freq='D')\n",
    "    \n",
    "    # make series for plotting purpose\n",
    "    fitted_series = pd.Series(fitted, index=index_of_fc)\n",
    "    lower_series = pd.Series(confint[:, 0], index=index_of_fc)\n",
    "    upper_series = pd.Series(confint[:, 1], index=index_of_fc)\n",
    "\n",
    "    # Plot\n",
    "    plt.figure(figsize=(15,7))\n",
    "    plt.plot(df[\"#y\"], color='#1f76b4')\n",
    "    #plt.plot(pred, color='yellow')\n",
    "    plt.plot(fitted_series, color='darkgreen')\n",
    "    plt.fill_between(lower_series.index, \n",
    "                    lower_series, \n",
    "                    upper_series, \n",
    "                    color='k', alpha=.15)\n",
    "\n",
    "    plt.title(\"ARIMA/SARIMA - Forecast\")\n",
    "    plt.show()\n",
    "\n",
    "forecast(ARIMA_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "301b4bab",
   "metadata": {
    "papermill": {
     "duration": 0.029655,
     "end_time": "2022-06-15T16:48:39.089940",
     "exception": false,
     "start_time": "2022-06-15T16:48:39.060285",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## <center>SARIMA Model Selection</center>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "22d74d89",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-15T16:48:39.168443Z",
     "iopub.status.busy": "2022-06-15T16:48:39.160728Z",
     "iopub.status.idle": "2022-06-15T16:48:51.860933Z",
     "shell.execute_reply": "2022-06-15T16:48:51.862062Z",
     "shell.execute_reply.started": "2022-06-15T16:40:55.906288Z"
    },
    "papermill": {
     "duration": 12.742007,
     "end_time": "2022-06-15T16:48:51.862363",
     "exception": false,
     "start_time": "2022-06-15T16:48:39.120356",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Performing stepwise search to minimize aic\n",
      " ARIMA(1,0,1)(0,1,1)[12] intercept   : AIC=inf, Time=8.92 sec\n",
      " ARIMA(0,0,0)(0,1,0)[12] intercept   : AIC=1014.503, Time=0.28 sec\n",
      " ARIMA(1,0,0)(1,1,0)[12] intercept   : AIC=668.208, Time=2.74 sec\n",
      " ARIMA(0,0,1)(0,1,1)[12] intercept   : AIC=621.562, Time=3.19 sec\n",
      " ARIMA(0,0,0)(0,1,0)[12]             : AIC=1012.864, Time=0.13 sec\n",
      " ARIMA(0,0,1)(0,1,0)[12] intercept   : AIC=802.117, Time=0.56 sec\n",
      " ARIMA(0,0,1)(1,1,1)[12] intercept   : AIC=620.541, Time=4.56 sec\n",
      " ARIMA(0,0,1)(1,1,0)[12] intercept   : AIC=700.393, Time=1.60 sec\n",
      " ARIMA(0,0,1)(2,1,1)[12] intercept   : AIC=inf, Time=24.90 sec\n",
      " ARIMA(0,0,1)(1,1,2)[12] intercept   : AIC=inf, Time=28.14 sec\n",
      " ARIMA(0,0,1)(0,1,2)[12] intercept   : AIC=620.873, Time=10.17 sec\n",
      " ARIMA(0,0,1)(2,1,0)[12] intercept   : AIC=666.278, Time=6.22 sec\n",
      " ARIMA(0,0,1)(2,1,2)[12] intercept   : AIC=inf, Time=30.84 sec\n",
      " ARIMA(0,0,0)(1,1,1)[12] intercept   : AIC=876.689, Time=2.56 sec\n",
      " ARIMA(1,0,1)(1,1,1)[12] intercept   : AIC=inf, Time=12.15 sec\n",
      " ARIMA(0,0,2)(1,1,1)[12] intercept   : AIC=inf, Time=14.38 sec\n",
      " ARIMA(1,0,0)(1,1,1)[12] intercept   : AIC=inf, Time=8.82 sec\n",
      " ARIMA(1,0,2)(1,1,1)[12] intercept   : AIC=inf, Time=18.24 sec\n",
      " ARIMA(0,0,1)(1,1,1)[12]             : AIC=624.248, Time=2.66 sec\n",
      "\n",
      "Best model:  ARIMA(0,0,1)(1,1,1)[12] intercept\n",
      "Total fit time: 181.101 seconds\n"
     ]
    }
   ],
   "source": [
    "# Seasonal - fit stepwise auto-ARIMA\n",
    "SARIMA_model = pm.auto_arima(df[\"#y\"], start_p=1, start_q=1,\n",
    "                         test='adf',\n",
    "                         max_p=3, max_q=3, \n",
    "                         m=12, #12 is the frequncy of the cycle\n",
    "                         start_P=0, \n",
    "                         seasonal=True, #set to seasonal\n",
    "                         d=None, \n",
    "                         D=1, #order of the seasonal differencing\n",
    "                         trace=True,\n",
    "                         error_action='ignore',  \n",
    "                         suppress_warnings=True, \n",
    "                         stepwise=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "1fb8ef55",
   "metadata": {},
   "outputs": [],
   "source": [
    "file_name = \"SARIMA_model_reg.pkl\"\n",
    "\n",
    "# save\n",
    "#pickle.dump(SARIMA_model, open(file_name, \"wb\"))\n",
    "\n",
    "# load\n",
    "SARIMA_model = pickle.load(open(file_name, \"rb\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "68fb41d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>SARIMAX Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>                  <td>y</td>               <th>  No. Observations:  </th>    <td>505</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>           <td>SARIMAX(0, 0, 1)x(1, 1, 1, 12)</td> <th>  Log Likelihood     </th> <td>-305.271</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>                   <td>Sat, 12 Nov 2022</td>        <th>  AIC                </th>  <td>620.541</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                       <td>17:28:07</td>            <th>  BIC                </th>  <td>641.544</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sample:</th>                    <td>12-10-2007</td>           <th>  HQIC               </th>  <td>628.787</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th></th>                          <td>- 04-27-2009</td>          <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>               <td>opg</td>              <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>intercept</th> <td>   -0.0167</td> <td>    0.010</td> <td>   -1.753</td> <td> 0.080</td> <td>   -0.035</td> <td>    0.002</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L1</th>     <td>    0.6599</td> <td>    0.031</td> <td>   21.376</td> <td> 0.000</td> <td>    0.599</td> <td>    0.720</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.S.L12</th>  <td>    0.1278</td> <td>    0.047</td> <td>    2.741</td> <td> 0.006</td> <td>    0.036</td> <td>    0.219</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.S.L12</th>  <td>   -0.8154</td> <td>    0.045</td> <td>  -18.208</td> <td> 0.000</td> <td>   -0.903</td> <td>   -0.728</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>sigma2</th>    <td>    0.1975</td> <td>    0.009</td> <td>   21.806</td> <td> 0.000</td> <td>    0.180</td> <td>    0.215</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Ljung-Box (L1) (Q):</th>     <td>21.39</td> <th>  Jarque-Bera (JB):  </th> <td>726.23</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Q):</th>                <td>0.00</td>  <th>  Prob(JB):          </th>  <td>0.00</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Heteroskedasticity (H):</th> <td>0.57</td>  <th>  Skew:              </th>  <td>1.41</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(H) (two-sided):</th>    <td>0.00</td>  <th>  Kurtosis:          </th>  <td>8.23</td> \n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Covariance matrix calculated using the outer product of gradients (complex-step)."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                                     SARIMAX Results                                      \n",
       "==========================================================================================\n",
       "Dep. Variable:                                  y   No. Observations:                  505\n",
       "Model:             SARIMAX(0, 0, 1)x(1, 1, 1, 12)   Log Likelihood                -305.271\n",
       "Date:                            Sat, 12 Nov 2022   AIC                            620.541\n",
       "Time:                                    17:28:07   BIC                            641.544\n",
       "Sample:                                12-10-2007   HQIC                           628.787\n",
       "                                     - 04-27-2009                                         \n",
       "Covariance Type:                              opg                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "intercept     -0.0167      0.010     -1.753      0.080      -0.035       0.002\n",
       "ma.L1          0.6599      0.031     21.376      0.000       0.599       0.720\n",
       "ar.S.L12       0.1278      0.047      2.741      0.006       0.036       0.219\n",
       "ma.S.L12      -0.8154      0.045    -18.208      0.000      -0.903      -0.728\n",
       "sigma2         0.1975      0.009     21.806      0.000       0.180       0.215\n",
       "===================================================================================\n",
       "Ljung-Box (L1) (Q):                  21.39   Jarque-Bera (JB):               726.23\n",
       "Prob(Q):                              0.00   Prob(JB):                         0.00\n",
       "Heteroskedasticity (H):               0.57   Skew:                             1.41\n",
       "Prob(H) (two-sided):                  0.00   Kurtosis:                         8.23\n",
       "===================================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
       "\"\"\""
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(SARIMA_model.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "68787c0d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-15T16:48:52.082961Z",
     "iopub.status.busy": "2022-06-15T16:48:52.066562Z",
     "iopub.status.idle": "2022-06-15T16:48:52.694623Z",
     "shell.execute_reply": "2022-06-15T16:48:52.695214Z",
     "shell.execute_reply.started": "2022-06-15T16:41:03.225749Z"
    },
    "papermill": {
     "duration": 0.685801,
     "end_time": "2022-06-15T16:48:52.695404",
     "exception": false,
     "start_time": "2022-06-15T16:48:52.009603",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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Lly/PthkEQRBEJ8MY25NtG3oS9P1IEATRe0j0HUlhmQRBEARBEARBEDkAiTuCIAiCIAiCIIgcgMQdQRAEQRAEQRBEDtCjcu4IgiAIgiAIgshtIpEI9u/fj7a2tmybklXy8/MxbNgwBAKBlI/JqrhjjJUDeBDANJid7b/EOV+cTZsIgiAIgiAIgsge+/fvR0lJCUaNGgXGWLbNyQqcc9TU1GD//v0YPXp0ysdlOyzzzwBe55xPAnAsgE1ZtocgCIIgCIIgiCzS1taGfv369VphBwCMMfTr1y9t72XWPHeMsTIApwK4CQA452EA4WzZQxAEQRAEQRBE96A3CztBe56DbHruRgOoBvAfxtgqxtiDjLEi906MsZsZY8sZY8urq6u73kqCIAiCIAiCIIgeQDbFnR/ALAD/j3M+E0AzgDvcO3HO/8U5n8M5nzNggLIRO0EQBEEQBEEQRMYoLi62/164cCEmTJiAPXv24K677sLQoUMxY8YMjB8/HldccQU2btxo73v66adj4sSJmDFjBmbMmIGrrrqqS+3OZkGV/QD2c86XWv8/B4W4IwiCIAiCIAiCyAbvvPMObr/9drzxxhsYOXIkAOA73/kOvv/97wMAnn76aZx55plYt24dhCPqySefxJw5c7Jib9Y8d5zzKgD7GGMTrU1nAdiY4BCCIAiCIAiCIIgu4cMPP8RXv/pVzJ8/H2PHjlXu89nPfhaf+cxn8N///reLrVOT7T533wTwJGMsCGAngC9m2Z6k/PvDnSgI+nD93JHZNoUgCIIgCIIgcpvX7gCq1mV2zEHHAOffm3CXUCiEyy67DO+//z4mTZqUcN9Zs2Zh8+bN9v+f//znUVBQAAA455xz8Pvf/77jNqdIVsUd53w1gOz4LNvJPQvNbg0k7giCIAiCIAgiNwkEAjjxxBPx0EMP4c9//nPCfTnnjv+zGZaZbc8dQRAEQRAEkWOMumNB2sccy7ZjEDuKN4zjOsGixOy+98IuPyeRIkk8bJ2Fpml45plncNZZZ+HXv/41fvKTn3juu2rVqqyJOTfZbmJOEARBEARB9HIK0YZ/Bf+Ifwb/hF/4H4UPerZNIggUFhZiwYIFePLJJ/HQQw8p93n++efx5ptv4nOf+1wXW6eGPHcEQRAEQRBEVvmafz4GsjrM1+fii/43MI4dwK2R29GA4uQHE0Qn0rdvX7z++us49dRT7WqYf/rTn/DEE0+gubkZ06ZNw7vvvgu5ZZucc9e/f3+8/fbbXWYviTuCIAiCIAgiawxELW72zcer+lx8M3I7PjCm4x7/Q3gpeCe+Evk+dvIh2TaR6IU0NTXZfw8fPhy7du0CAFxyySW46667PI97//33O9myxFBYJkEQBEEQBJE1fhB4BhoM/DZ6LQDgWf10XBf+KUpZC14K3olTtLVZtpAgeg4k7giCIAiCIIisMJXtwlW+D/Ef/Xzs5xX29uV8Ei4L340DvB8eCfwWN/leB8C9ByIIAgCJO4IgCIIgCCIrcPzM/yRqeAn+Hr007tH9fACuDP8S7xizcFfgMfza/yACiGbBToLoOZC4IwiCIAiCILqcc7QVmOfbiD9Fr0IjCpX7tCAfX4t8B3+LXorr/O/hh/6nuthKguhZkLgjCIIgCIIgupQAovix/7/YZgzF//QzE+7LoeG+6GexUD8el/k+hgaji6wkiJ4HiTuCIAiCIAiiS/m8722M0arw6+h10OFL6ZhX9XkYwOpxgrapk60jiJ4LiTuCIAiCIAiiyyhFE77lfwEf6dPwnjEj5ePeM2agmefhYm1x5xlHED0cEncEQRAEQRBEl/FN/0soQzN+Hf08AJbycW3IwzvGLJznWwYf9M4zkCAAMMbwve99z/7/vvvuc/S3u//++/HYY48BAGpra3HOOedg/PjxOOecc3D06NG48WpqanDGGWeguLgYt912m+Oxs88+W3lMeyBxRxAEQRAEQXQJI1kVbvS9gWf007CJj0z7+Pn6XPRlTThR29AJ1hFEjLy8PLzwwgs4cuRI3GPRaBQPP/wwrrvuOgDAvffei7POOgvbtm3DWWedhXvvvTfumPz8fNx9992477774h77whe+gH/84x8ZsdufkVEIgiAIgiAIIgk/8j+FCPz4Q/Tqdh3/gXEsGngBLtKW4CNjeoatI7ojv132W2yu3ZzRMSf1nYQfHf+jhPv4/X7cfPPN+NOf/oR77rnH8di7776LWbNmwe83pdTLL7+M999/HwBw44034vTTT8dvf/tbxzFFRUU4+eSTsX379rhzXXLJJTjllFPw05/+tANXZUKeO4IgCIIgCKLTmc224ALfMjwQvRjV6NOuMUII4i1jNs7zLaOed0Snc+utt+LJJ59EfX29Y/vHH3+M2bNn2/8fOnQIgwcPBgAMGjQIhw4dSus8ffr0QSgUQk1NTYdtJs8dQRAEQRAE0elc7FuMFp6Hf+sXdmicBfpcXOlbhJO1dXjPmJkh64juSjIPW2dSWlqKG264AX/5y19QUFBgb6+srMTkyZOVxzDGwFjquaSCiooKHDx4EP369Wu3vQB57giCIAiiS2GMnccY28IY284Yu0Px+E2MsWrG2Grr5yvZsJMgMs0J2masMMajDXkdGucjYzrqeSEu8i3JkGUE4c23v/1tPPTQQ2hubra3FRQUoK2tzf5/4MCBqKysBGAKv4qKirTP09bW5hCQ7YXEHUEQBEF0EYwxH4C/AzgfwBQAn2OMTVHs+jTnfIb182CXGkkQnUAZmjCR7cNSQ+3tSIcI/HhDPw7naMuRh3AGrCMIb/r27YtrrrkGDz30kL1t8uTJjty5Sy65BI8++igA4NFHH8Wll14KAFi2bBluuOGGpOfgnKOqqgqjRo3qsL0k7giCIAii6zgewHbO+U7OeRjAUwAuzbJNBNHpHK9thsZ4RsQdAMw35qKUteJUbW1GxiOIRHzve99zVM08//zz8eGHH9r/33HHHXjrrbcwfvx4vP3227jjDjMoY+/evQ5v3KhRo/Dd734XjzzyCIYNG4aNGzcCAFasWIG5c+faBVo6AuXcEQRBEETXMRTAPun//QBOUOx3JWPsVABbAXyHc75PsQ9B9BhO0DYhxANYw8dmZLxPjKmo5cW4yLcEbxlzMjImQcg0NTXZfw8cOBAtLS32/yNHjkS/fv2wbds2jB8/Hv369cM777wTN8bSpUtx66232v/v3r1bea7HH38c3/jGNzJiN3nu0oBznm0TCIIgiNznVQCjOOfTAbwF4FHVToyxmxljyxljy6urq7vUQIJIlxO0TVjFxyGMQEbGi8KP1/XjcLa2gkIziaxw77332nl2Xvz+97/H9OnJW3ZMmzYNZ511VkbsInGXBgZpO4IgCKJjHAAwXPp/mLXNhnNewzkPWf8+CGA2FHDO/8U5n8M5nzNgwIBOMZYgMkEJWjCF7clYSKZgvjEPRSyEM7TVGR2XIFJh4sSJOPXUUzMy1le/+tWMjAOQuEsLndQdQRAE0TE+BTCeMTaaMRYEcC2AV+QdGGODpX8vAbCpC+0jiIwzR9sCH+NYkmFxt9SYjGpeiot8izM6LkH0ZCjnLg0MCsskCIIgOgDnPMoYuw3AGwB8AB7mnG9gjP0KwHLO+SsAbmeMXQIgCqAWwE1ZM5ggMsAJ2iaEuQ+rjHEZHVeHD6/rx+Mq34coRBtakJ/R8QmiJ0KeOwBHm8PYUd2UdD8SdwRBEERH4Zwv5JxP4JyP5ZzfY2270xJ24Jz/mHM+lXN+LOf8DM755uxaTBAdY662CWv42A73t1MxX5+HAhbGmdqqjI9NED0R8twBOOuPH6C2OYzd916YcD+KyiQIgiAIgkidQrRhGtuFB/SLO2X8T/lEHOLluMi3BPONeZ1yDiL7jLpjQUbHSzbnB4Di4mJHxcxHHnkEy5cvx9/+9jc88MADKCws9Oxh9/777yMYDOLEE0/MmM2pQuIOQG1zalWWKOeOIAiCIAgidWZrW+FnRsaLqQgMaFion4DrfO+iGC1oQmGnnIcgZG655ZaEj7///vsoLi7OirijsMw0MEjcEQRBEARBpMwJ2iZEuYYVxoROO8d8fS7yWARnays77RwEIXPXXXfhvvvuAwD85S9/wZQpUzB9+nRce+212L17Nx544AH86U9/wowZM/DRRx91qW3kuUsDyrkjCIIgCIJInRO0TVjHx3RqsZOVfDwO8r64yLcYLxknd9p5iN5Fa2srZsyYYf9fW1uLSy65JG6/e++9F7t27UJeXh7q6upQXl6OW265BcXFxfj+97/fhRabkOcuDXQSdwRBWFTVt+FAXWu2zSAIgui25COEY9mOTgvJFHBoWKDPxanaWpSiuVPPRfQeCgoKsHr1avvnV7/6lXK/6dOn4/Of/zyeeOIJ+P3Z95uRuEsDw8i2BQRBdBfm/uYdnHTvu9k2gyAIotsyU9uOINOxxJjU6edaoM9FkOk4g6pmEl3MggULcOutt2LlypU47rjjEI1Gs2oPibs0oLBMgiAIgiCI1JirbYLOGVYYEzv9XGv5GDTwAhyvben0cxGEwDAM7Nu3D2eccQZ++9vfor6+Hk1NTSgpKUFjY2NWbMq+77AHQdUyCYIgCIIgUuMEbRM28pFo7IIKlgY0rDQmYLa2tdPPRXQ9qbQuyAa6ruP6669HfX09OOe4/fbbUV5ejosvvhhXXXUVXn75Zfz1r3/FKaec0mU2kbhLA3LcEQRBEARBJCcPYcxk2/G4fnaXnfNTYyJ+EHgGpWhCA4q77LxEbiL3uAOAm266CTfddBMAs1qmYNGiRXHHTpgwAWvXru1M8zyhsMw0oIIqBEEQBEEQyZnOdiKPRTq9mIrMCm62W5itbeuycxJEd4PEXRpQWCZBEARBEERyTtA2weAMy7qgmIpgtTEWEe7DcZR3R/RiSNylASfPHUEQBEEQRFJO0DZhCx+O+i4Mj2xDHtbz0ZhD4i4noHl3+54DEndpQGGZBEEQBEEQSdAjmK1tw5IuDMkUfGpMxLFsJ4KIdPm5icyRn5+PmpqaXi3wOOeoqalBfn5+WsdRQZU0oLBMgiAIgiCIJBxchUIW6tJ8O8FyYwJu9i/ANLYLK60cPKLnMWzYMOzfvx/V1dXZNiWr5OfnY9iwYWkdQ+IuDXrx4gFBEARBEERq7DarB3Zlvp1ghWEKuuO0LVipk7jrqQQCAYwePTrbZvRIKCwzDchzRxAEQRAEkYQ9H2OrMRS1KO3yU9egDDuMwZR3R/RaSNylgUGuO4IgCIIgCG/0KLB3SVZCMgXLjYmYo20Fg5E1GwgiW5C4SwMSdwRBEARBEAmoWgOEm7ISkilYziegD2vCGFaZNRsIIluQuEsDnRaACIIgCIIgvNn9MQBkpVKm4FNjIgBQvzuiV0LiLg3Ic0cQBEEQBJGAPZ8AfceiGn2yZsJuPghHeCmJO6JXQuIuDQypoEpv7rtBEARBEAQRh6EDez8BRp2UZUOYmXfHSNwRvQ8Sd2kgF8skbUcQBEEQBCFxeBPQVg+MPDnbluBTYwJGaocxAEezbQpBdCm9Stz984MdeHLpnnYfr0uKjrQdQRAEQRCEROVq8/fQ2Vk1AzArZgLAHG1rli0hiK6lV4m737y2GT99cb3n48lCLeWwTMq/IwiCIAiCkKhcAwSLgb5jsm0JNvBRaOVByrsjeh29StwlI5lekwUdaTuCIAiCIAiJyrXAwGmAlv3pZRR+rDbGUTNzoteR9buPMeZjjK1ijM3Pti3J9JpOnjuCIAiCIIh4DAM4tB4YfGy2LbH5lE/AFLYHhWjLtikE0WVkXdwB+BaATdk2Akgu2EjQEQRBEARBKKjdCYSbgMHTs22JzXJjIvzMwAxte7ZNIYguI6vijjE2DMCFAB7Mph2C5GGZ8t8k9AiCIAiCIADEiqkM6j7ibqUxHjpnOI5aIhC9iGx77u4H8EMAhtcOjLGbGWPLGWPLq6urO9UYniQwUzco544gCIIgCCKOqrWAFgAGTMq2JTZNKMQWPoLy7oheRdbEHWPsIgCHOecrEu3HOf8X53wO53zOgAEDOtWmdAqqkOeOIAiCIAjConItMHAK4A9m2xIHnxoTMEvbBh/0bJtCEF1CNj13JwG4hDG2G8BTAM5kjD2RRXuS4hR3WTSEIAiCIAiiu8C56bnrRiGZguXGRBSxECaxvdk2hSC6hKyJO875jznnwzjnowBcC+Bdzvn12bLHtCnx47ocPErijiAIgiAIAmg4ALTUdKtKmYJPrWbm1O+O6C1kO+euW5FOtUwKyyQIgiAIgoAZkgl0S89dFfphP+9PeXdEr8GfbQMAgHP+PoD3s2xGUmecIRdU6VxTCIIgCIIgegZVawEwYNC0bFuiZLkxAfO0jTBnbyzb5hBEp0KeOwmexBunk+eOIAiCIAjCSeVaoP94IFiUbUuULDcmYiCrw3B2ONumEESnQ+JOIqnnTtqBtB1BEARBEASAyjXdMiRTIPLu5rCtWbaEIDofEncSSVshOPrckbojCIIgCKKX01ILNOwHBndfcbeVD0MDL6SiKkSvgMSdTBp97kjaEQRBEATR66lcY/7uxp47Dg3LjQlUVIXoFZC4k0iWR6cblHNHEARBEARhU2VVyuyGbRBklhsTMEE7gDI0ZdsUguhUSNxJJM+5k8MyO9cWgiAIgiCIbk/lGqBsOFDYN9uWJGQVHw8AOFbbkWVLCKJzIXEnkSyPTi6oQp47giAIgiB6PZVru3VIpmC9MRoAcAzblWVLCKJzIXEnkUyu6QZ57giCIAiCIAAAoSagZnu3LqYiaEQhdhiDyXNH5Dw5K+5qmkJpH5Netcy0hycIgiAIgsgdDm0AwLt9vp1gLR+DYzTy3BG5TU6Ku321LZhzz9tYtfdoWsfxJL47R587qpdJEL0WzqktCkEQRE+olCmzzhiDwawWA5De/JAgehI5Ke5qm8PgHDjSFE7ruGRzNJ3L1TLbYxlBELmAY6GHPguINGGMnccY28IY284YuyPBflcyxjhjbE5X2kcQKVO1BijsB5QOybYlKbHGGAMAmK7tzLIlBNF55KS4E8VO0i16kmx37hB3NKMjiN4K9bwk2gtjzAfg7wDOBzAFwOcYY1MU+5UA+BaApV1rIUGkgSimwli2LUmJDXwUdM5I3BE5TY6KO/N3uuFSyUItqaAKQRCAU9zRQg+RJscD2M4538k5DwN4CsCliv3uBvBbAG1daRxBpEw0DBze1GPy7QCgDXnYyofhWEbijshd/Nk2oHMQnrs0j0ojLJPybAii98IpLJNoP0MB7JP+3w/gBHkHxtgsAMM55wsYYz/wGogxdjOAmwFgxIgRnWAqQSSgehNgRLqwUqYBf+laaIGaBPv4EKmfCR4t89xjrTEWZ/tWwJwr9gyPI0GkQ06Ku5jnLr3jku3umNClNzRBEDmE/FlAnjsikzDGNAB/BHBTsn055/8C8C8AmDNnDr0Ria6lcq35e1Dne+6Yvw75g5+Dv3h70n2D/d5HW9WliDbMgEq8reOj8Vn2PoaxI9jPB2TcVoLINrkp7oz25tylHpZJEzqC6L3Q/U90gAMAhkv/D7O2CUoATAPwPjPzmAYBeIUxdgnnfHmXWUkQyahaCwSLgb5jOvEkHP6yFcgf+CrAONoqL0ekzru+EAvWomDwcygY+jQiJesRqrocXC927LPGGAsAOIbtJHFH5CQ5nXOX+YIqqe9LEETuQjl3RAf4FMB4xthoxlgQwLUAXhEPcs7rOef9OeejOOejACwBQMKO6H5UrgEGHQNonTOVZL5GFAx7DAVDnoPeNgTNO7+FSN0JAHyePzw8AC17voa2Q+fDX7wZhWP+BH/Jese4W/hwhLkPx1JRFSJHyUnPnSiMknZYZrIm5jShIwgC1AqBaD+c8yhj7DYAb8CckT7MOd/AGPsVgOWc81cSj0AQ3QBDB6rWAzOv75Th/SVrkD/oZUALo63qIkSOnojU/REaIrWnQW+ahPwhz6Bg2BOI1M9AW9UlgFGIMALYxEfiGCqqQuQouSnuFJ47d9Nhpijbm05jcprQEUTvhdqiEB2Bc74QwELXtjs99j29K2wiiLSo3QlEmjNfTMXXjPxBLyNQuhZ663C0HrwGPNy+0EkjPBAtu7+BYP/3EOz/LooKd6Kt8krozROx1hiDS30fg8EAz80gNqIXk5PvaDHZ8gqj9KqimU6fO5rPEUTvxeG5y54ZBEEQ2aFyjfl7UAbFHYugcMSD8JdsQOjwuWjZfUu7hV0MH8JHzkbL7lvB9QIUjvgPfEWbsZaPQSlrxWhWlRHTCaI7kaPiTvxWr67rHuouabVMx980pSOI3opjocfIoiEEQRDZoHIN4AsCAyZlbMi8ga/Cl1+J1v1fQLjmDJhRy5nBaBuKlt23QW8bjIIhz2ClZopGCs0kcpGcFHdc4bkzHH+rhVmy8CqnWGy/fQRB9Gycnjv6MCAIopdRtRaomAz4gxkZzl+2AsE+yxA6cgb0pswJRgc8gNb91wNMR+XQ91DPg1RUhchJclTcmb+9PHfeuXipjes+jiCI3gWnhR6CIHornJs97jIUkqnlVSF/0EuINo9BuPrsjIzpBY/0Q1vl1fAV7Mcv+g3FMSTuiBwkJ8WdnXMnbZO1mLNfnXxk4lma/ChN6Aii95JKJABBEERO0nAAaK0FBmegebnWhoKhT4Dr+Wg78DlkMhTTi2jjNIRrTsE7ZToOFlfBB73Tz0kQXUlOirvknjt533Q8d86sO4LobqzaexRHm8PZNiPnMai4EkEQvRVRTKXD4o4jf/DzYMFatB34HLhe0mHTUiV0+DyUtfTBPQNKMTJvXZedlyC6gpwUd2Li5VXRzvDw3CUtqJJCxU2CyCaX/+MTXPPPxdk2I+fxCu0mCILIeSrXAmDAwKkdGibQ5xMEStchdPhc6K1jMmNbyvigHbwCBZyjdeh8gNGiKJE75Ki4M3979aLyzr9LPK5D3JG6I7oZ4v2+7XBTli3JfXgai0IEQRA5RdVaoP94IFjU7iG0/L3IG7gQkcbJiNSemkHjUmdfZCzuPNyIpmAT8ge/SAt1RM6Qk+JO3KCyAJPLlesegi6dapn0EUB0NyI6vSu7inQ+NwiCIHKKDhZTYb5mFAx7EjxShraDVwNgmbMtDTg05DcPx5VHNQTKVuG5bc9lxQ6CyDS5Ke5cvwFvD11anjuP8QiiOxA1qOFaV+H1ubGjugnn3f8h6looxIcgiByk+QjQsL8D+XYG8oc8DeZrRuuBzwNGYUbNS5d1fAzuqNsHo2kcfrP0N9hQsyGr9hBEJshJcafKufNqYp5OY3Kqp0J0ZyJRelN2FV6h3X9/bzs2VzXi7U2Hs2EWQRBE53Jwtfl7yIx2HR7osxj+4q0IHboYRtvQjJnVXtYYY5DPdIysPBH9CvrhRx/+CBE9km2zCKJD5Ki4M3979aJqf84d9bYiui9h3fTc+bTshLj0JpwVd6UH6HOBIIhcpnK1+bs9njutFXn930G0aTwidcdn1Kz2so6bhVxm8QO4c+6d2NOwB89sfSbLVhFEx8hJcWfn3Dly5CRhJkWv8TQi2dLx8hFEVyPCMn2MxF1nk6yFCr0CBEHkJJWrgb5jgPyytA8N9vsA8LUidPg8dJdPyf28P2p4CaaznTh56Mk4YdAJ+Oeaf6IpTIXJiJ5Ljoo787fX6jp57ohcRIRlajl5V3cvnC1UqNASQRC9hINrgMEz0j6M+esR7LsI0YYZMELZD8eMwbDWGINjtJ1gjOE7c76Do6Gj+M+G/2TbMIJoNzk5DRSCzUvQ6R7iLnm1zNjfVDKX6G5ELM+dv4eou/8t24v73tiSbTPahSMSgD4KCILoDbTUAvV725VvFxzwFgCOUPU5GTero6zlYzCB7QfCzZjabyrOH3U+Ht/4OKpbqrNtGkG0i54xC0wTw/bceeTctbeJufw3TeiIbkbEyrnrril37t6QP35hHf723vYsWdMxHKHd9GFAEERv4OAq83ea+XZa8BACZSsQOToPPNK3EwzrGGuNMfAxDlStAwB8c9Y3ETEi+Meaf2TZMoJoHzkp7rjtuZPz7LwEHY87Ltm47uMIojsQtfrc+X3d77Z+a+MhjPnJQmw91JhtUzKC18KRgNIeCYLIOdpZTCWv4jXAyEOo5ozM25QB1hpmURUcWAkAGF4yHJ+d+Fm8uO1F7KzfmUXLCKJ9dL9ZYAZIlnPnaIWQjufO4f1rv30E0RmEbc9dTFnsPtKMz/1rCZpD0WyZBQB4fX0VAGDNvrqMjXm4oQ1PLt2TsfHSwbkOlPoCEUEQRI/l4GqgzyigoE/Kh/gKdsJfshnhmtMBvaizLOsQ1eiDSt435pkEcPP0m5Hvz8efV/w5i5YRRPvISXGnyrlz5si0s6AKFU4gujHCcyc77n73xmYs3lmD97dkN3egMzzdX318BX764nocqGvN+NjJ8PLciT/Jc0cQRM5RuTrNYioceQNfgxEpQ7j2pE4yKjOsM0YDB1fa//fN74svTfsS3t33LlYdXpXgSILofuSouBO/U+lzJx+ZehPzZMVXCKKrETl3qlYIWQ8jtk6vZVD1HGkMAYjP5esK0inERBAE0eNpqQXq0ium4i9ZD1/BPrOICg90nm0ZYI0xFqjZDrTW2duun3w9BhQMwB+X/5GiMogeRU6KOzGR5Z5VMWP7euXiqXB6+ehGJ7oXdhNzX0xAsW7SS0jcO5n0aIkxtSxUkPEK+RZ/d5fnnSAIIiNUrjF/p+i5ixgR5FW8Dr1tIKL1szrPrgyx1mpmbl8ngMJAIb4x4xtYXb0a7+57N0uWEUT65KS4i3nuYttkMeaZc5e0z13q+xJEV2OHZao8d93DcZdRcSfu4+xUByXPHUEQvYg0i6k8t/U5aMEahKrPR0+Yaq4zRpt/SKGZAHDZuMswumw07l9xP6JGdnPXCSJVuv8d1w6EkPPMi/Goepm0WiYAnzWTpN5WRHfDboUgq51u4kASt1YmwzKzeQ96ee4IgiBykoOrgfKRQGHyVgbNkWY8sOYBRJtHQ2+a2Pm2ZYA6lJjFYqSiKgDg1/z49qxvY3fDbryw7YXsGEcQaZKj4s76LW0zPDx3afW54zGvSNZzmAjChRB3/m7Y6K4zvFuGvYiT8aGTn9vD+y+ggioEQeQUlatT9to9suER1LbVInT4AnSbFcZUGDITOBBfPOWM4WdgZsVM/L81/w8tkZYsGEYQ6ZGT4s5QeO6cxVDi93Xvo4JzDk2LH4MgugMRXYQpqgqqZJdYWGYmPXfWfZ6Bm7G+JYJRdyzACyv3p3ju2N9URZcgiJym9ShwdHdKxVRqWmvw6IZH8ZmRn4HRNrzTTcsoQ2YB9XuB5iOOzYwxfHf2d3Gk9Qge3/h4lowjiNTJUXFn/vaqbulVGCWVsEwxcaaCKkR3IyoKqmhyQZVugl1oJDG6wfHKmoMpCTaxTya8gntrzdXYhz/elXTftoiOBz7YEbODPgoIgshl0iim8tSWp9AWbcNtM2/rXJs6g6FW4ZcDK+MemlExA6cNOw3/3fxftEXbutgwgkiPnBR3XLGi7y30pONSGNcOy6QJHdHNiCjEXXfBrmyZxHP3+OLduP1/q/DM8n0pjOn83RHSCbP+14c78cHWWN/AdBaICIIgehxC3A2ZmXC3tmgbnt78NE4bfhpGl43uAsMyzOAZANOAAyuUD9849UbUttViwc4FXWsXQaRJjoo787dX+GV7q2UaPFasgnLuiO5G2G5irqqWmd33q90iIInuPGT1rqtpDicdU9zTegbUXTotDJpDzopp5LkjCCKnObgaKBuRtJjK/J3zcTR0FDdOubFr7Mo0ecVA/4lxFTMFcwbOweS+k/HYxsey/p1KEInISXEnJn0cag+dZ4hmsibmkKplGhkwlCAySFRRUCWTOW5dQTrfl0LUZfJLNpWnK76vHn3JEwSRw1SuBoYkLqZicAOPb3wcU/pNweyBs7vGrs5g6CwzLFPxvcIYww1Tb8DO+p34+ODHWTCOIFIjR8Wd+dszFNNQb//rO9uxp6bZc1zOeSznLjOmEkTGsFshdENBJxZOkkWMiv1SuQSVh769pDOEu48gee4IgshZ2uqB2p1J8+0WHViEnfU7ccOUG3rcoqKDITOBliNAvTo14NyR56KisAKPbni0iw0jiNTJUXGXuFqm7rF92e5a3PSfTz3H5Rzw2dUyaUZHpMbGgw1oDeudfp5E1TKzTUwAJVV31l7JryGTYZmCVJ45t+fOEdpt/e7I58PDi3bhUAMl7BME0Q2w8+1mJNztsY2PoaKwAp8Z9ZnOt6kzSVBUBQACvgCum3QdllQuwZbaLV1oGEGkTtbEHWNsOGPsPcbYRsbYBsbYtzJ9jlSqYronYYkm4Rwxzx257ohUaApFccFfPsK3norvnZNphOdODi8WMiTbaxGp5tzFWibEtm082IA3N1TF7asrFnHe2FCFRduOxO2b3L7UnyC391El5Nobtn2grhW/mr8RX3rEe5GJIAiiyzi42vydwHO3pXYLllYuxecnfx4BLdAlZnUaA6cBWsAz7w4ArppwFQr8BdQWgei2ZNNzFwXwPc75FABzAdzKGJuSiYENOxdH2iZ77gz1diBx3h3nMa8Iee6IVBCLBSv2HO30c0Xt1gCdfqp2kJpXUYgsWUBd8JePcPPj8dXLxC0o34pfe3wFrn9oafvNTMHr6Q7LdHwUWH/f8cJa3PXKhrRPH7AuvLKePHcEQXQDKlcDpcOAov6euzy28TEU+Atw5fgru86uzsKfBww6xtNzBwBleWW4bNxlWLBrAapbqj33I4hskTVxxzmv5JyvtP5uBLAJwNBMjK0qkZ5Kn7vk43K7oEq3nD8T3Y50csg6Sjhqee664cJDqoIznaqVAj0D15vOCPFhmfFHR3SORz7Z3W573BU5CYIgssLB1QlDMqtbqrFw10JcPu5ylOWVdZlZncrQWeZ1JwjBuH7y9dANHU9tearr7CKIFOkWOXeMsVEAZgLowJJ7DDGh9gq/9Opzl3RcLlXL7IYTaKIbYocjdr66E2GZcg5aLIo4260QUqtsqQrLTEYm78VUTutuNZFJT6kYKxSlcrwEQWSZtgagdkfCkMz/bf4fdEPH9ZOv7zq7Opshs4BwI1CzzXOXEaUjcMbwM/DMlmfQGm3tQuMIIjlZF3eMsWIAzwP4Nue8QfH4zYyx5Yyx5dXVqbm/Y547deGURJ67RPNEjli4WPcMfSO6G4btiep8onp8WGZ3Ka0SKzSSeL/2CLVMeCrTGSIuLDODwjkTXkiCIIiMULXW/O3huWuNtuKZrc/gzBFnYnjp8K6zq7NJUlRFcMPUG1AXqsOrO17tAqMIInWyKu4YYwGYwu5JzvkLqn045//inM/hnM8ZMGBASuOKyZ48kXRUy0yQc5dsXHvVniZhRAoIsdIVYZl2QRXFezPTb9enlu3Fn9/2XtX0Or/atvhFmHQ8nXoGnVzt6XPn+JzxEHpHm8MYdccCvL/lcMKxDVo1Igiiu5CkmMqrO15FfageN0y5octM6hL6TwACRQmLqgDArIpZmNpvKh7f+DgMTtEWRPchm9UyGYCHAGzinP8xk2PbTcxTyLlLx1PgLKjSQSOJXoEIkUwnh6y9RBIUVMlkuwAAuOOFdfjT21tT3t++JxWPqW7BdJ6tzIRlpj6Gz2WcSpy6WX+wHgDw4Ee7EltBnysEQXQXKlcDpUOB4viFddG0fFq/aZhZMbPrbetMNJ/prTwQX8hLhjGGG6bcgN0Nu7HowKKusY0gUiCbnruTAHwBwJmMsdXWzwWZGFjlJXA2MfeejCWaW3HE8m26Y9EKovshKlh2iecuqsq5E+/Xzj9/Ktg9KA31vamqlpnqmJmgPS9TKqfXU3wfUFgmQRDdhoOrPb12H+3/CLsbduOGqT28abkXQ2cBVeuAaDjhbueMOgcDCwfisQ2PdZFhBJGcbFbLXMQ5Z5zz6ZzzGdbPwkyMnTznzmGHy65E43KpoEqHzSR6ATHPXecTtSp7qcROtkUDt+9J87fuWHiR9rN+pzNZaG9POZl0np6o6+aXQzG9xhGvibsYi9d+BEEQWSXUCNRsBwYfq3z4sY2PYVDRIJw98uwuNqyLGDIL0MPA4cQtbQJaAJ+f/HksrVqKzbWbu8g4gkhM1guqdAaqnDt50uQ1sUw+ruQJ6ZiJRC8h5rHpfHkX1uPDkd12ZAt3BVvd03Nn/u7qapnpvE7u86UiLsU+7mIsbigigCCIbkHlWgBcWUxlU80mLKtahusnX9/zm5Z7kWJRFQC4csKVKPQXUlNzotuQm+LO9Rtwee48JpapjOuz66nQJIxIjvCmdWVYpvyeFqfNtkfI3XBc9wiNtgvQpDF2Jq4tnaqm7gIuqZxd2OguxuJlBxArkEMQBNHlVK4xfyvCMh/b+BgK/YW4YvwVXWtTV1I+Eijom7SoCgCUBktxxfgrsHDXQhxuSVw0iyC6gpwUd4ZdWCJ5EZX4iaH3VE2ulknajkgF4bHpCnEnBJMqBNNdhXHjwQbUNIU63yiLWFim+UfUy3Mn/lA8YV6VJDMh7hIt1rSEo7js7x9jU2WD8nypnN8Wd8ly7qRrpEbmBEFkjcrVQMlgoGSgY3NNaw1e3/06rhh/BUqCJdmxrStgzPTepeC5A4DrJl8H3dDxzJZnOtkwgkhOboo7ZUGV2ONeXgPV/+7HYtUySd0RybE9d12QdSfO5XhrWqfVXW/XC/7yEc69/8MOn3P9gXpEU/AwibBMOx9WugdlMWqHZSrG8MobTBYWebCuFb98dUPC0NREUavLdtVi9b46/HrhJtMOd86dI2dQPZB4itLJuWtsI3GXqzDGzmOMbWGMbWeM3aF4/BbG2Dqr0NgixtiUbNhJ9GI8iqm8tP0lRI0orp54dZeb1OUMnQ1UbwbCzUl3HV4yHCcNPQkvbnsRUYM+u4nskqPiTlTki23zKleeTgNiDm6LO5J2RCqkWiUxk+dSLTyovF5HmhJXAUuFi/66CPen0O/OveAie+6c7YG87ywvcZasWMz3nlmD/3y8Gyv2HPUeO0E/Qr+mOc7vtuNQQ1vSMG3d9twly7mL/U3iLjdhjPkA/B3A+QCmAPicQrz9l3N+DOd8BoDfAchouyCCSEioCTiyNS7fzuAGnt/2POYMnIMxZWOyY1tXMmSW+QUlQlSTcPWEq3G49TA+2v9RJxtGEInJSXEnMLw8d462CGmMZ8RW3u99bTN2H0m+mkP0brq2WmYCcdeJnmbRwy0hCXLuVAVV0rmGpMIqwfPiHlvlYfVbibZez+8vXtmAZ5bvs2zxGN86NpnnTn5eKOcuZzkewHbO+U7OeRjAUwAulXfgnDdI/xaB1hOJrqRqHQAe57lbVrUM+xr34aoJV2XFrC4njaIqAHDqsFMxoGAAnt36bCcaRRDJyUlxp2qYnGrOXaJvUA5nQYR3Nud24uwDH+zA1kON2TajRyMm68k8Nh2hNayDcx4TMZImEGKlM1shpHJtsbDM+LxApbhTeOm8PHdJC4HaRZAS2JfgQSHIvDx3ALBkZ21CE8QxyaplelX1JXKKoQD2Sf/vt7Y5YIzdyhjbAdNzd3sX2UYQZr4dEOe5e3bLsyjPK8/d9gduiiuA0mEpFVUBAL/mx+XjL8eiA4tQ2VTZycYRhDe5Le5UhRrgrpaZ+ricc7taJgAMLS9or4ndnqhu4N7XNuPCv1B4QUewww87Sds1tEUw+c7X8ae3t6UdlpkpUhF3dlim9b+uq+9Bd26eYwwPR1ayNg/CukQh2MJJdrixDZ/udgq1OHGneH7FU+B1BjssM41qmZ35mhHdH8753znnYwH8CMDPVPswxm5mjC1njC2vrq7uWgOJ3OXgaqB4EFAyyN50pPUI3t37Li4ZewnyfHnZs62rGTozZc8dAFw5/koAwAvbX+gsiwgiKTkq7py/AafQc+T7pLk6LodV5XJRFfEURdyVOIi0sHO5Omn8htYIAODZ5fsSi7tOfBl9KXyKxHpPipw7I+4x82849pPxOibZfchi6s4TMcbumhZc/cBix2PC22aLO8U9ITykXp8nRoqeO/n4bPcmJDqNAwCGS/8Ps7Z58RSAy1QPcM7/xTmfwzmfM2DAgMxZSPRu9n8aC0m0eHn7y4jyKK6ccGWWjMoSQ2YBR3cBLYmjM+zdi4fgpKEn4YWtL1BhFSJr5KS4U00QDY9Jk3v6lEjsGZw7vBS5nBOTy8K1KxFCoLOamIvFhojOpZwwhR2dKBSS5ZHJGMp7M/Y4R/zjAtljJi86JHur2sIrwT7u+74tokv2CUGa3HOXrOhLMs+dfDyFZeYsnwIYzxgbzRgLArgWwCvyDoyx8dK/FwJIXrWIIDJB4yGgdgcw8kR7kyikMnvg7N5RSEVm6Gzzd4qhmQBw1YSrqLAKkVV6nLhLxdMW8xLEtskhXRFdLfqSj2tOZC+dMQQAEI6SuCMSIwRBZ3nuonrMExbLuYv3TDvz2tJ5z3P87vXN2H+0xXOf1HLunOf26nNnKO5d+zHpdnOIICM+DNthnybO7W2f+3z1lkdUtkm3DFCFS8aaxSceP5mX0+szi8gdOOdRALcBeAPAJgDPcM43MMZ+xRi7xNrtNsbYBsbYagDfBXBjdqwleh17PzF/j4iJO1FI5eoJvaD9gRuRd3hgVcqHnDbsNCqsQmSVHiXu1h2ox+/e2JJ0P1XOndNzZ0jbUz8/hzmR/ckFkwHkdsgihYRlBrsKYwfV3bZDjRh1xwLsqG5ybBfe40jUsMMWVWJJJYZSYXNVI/7x/g7c+qT3qmUqnrtYK4R4GxwLCYrHBQ7PneMejr9GmZjnLlHOnfOxupaI9Jhzn0SeO69FESEIk7dCaN/CE9Gz4Jwv5JxP4JyP5ZzfY227k3P+ivX3tzjnUznnMzjnZ3DON2TXYqLXsOcTIFAEDJ5ub3p2y7MoyyvrPYVUZPLLgH7j0/LcUWEVItv0KHEHAI9+sjvpPtw1kXT/7Qzpck6gEk2nDM4BBgSs5ffcDsuM/S2HqBHpEfPcdUzdvbTaTMlZuNb5RSHGj+hStUzZ+8PhuS0VhBZpTfAeSKkSqMuD6AiNVoRlqrxwsscsqgjLTBbGmNhz5xZ34bjHYtUy448Xr6+XIEu1aqp8DRSWSRBEl7NnMTD8OMAXANCLC6nIDJ0FHFiRPAdAggqrENmkx4m7VLwOqrweedU+qlj1t/dLmJhjhl8FfCLPqWeLu0c/2Y2HF+1SPiZPpA83hFDdGMKoOxbg3c2Husq8nEB4iTvquRMvhztny/bcyWGZCoGQqP2HaSfH6+ur4kSVu5iIinTCMsUwXmGZqpBq2UZBVLr3xDV63btelSz/9eEOrNtfrzz2qOS5E/eCndOoCstMknMnPnOSeTmpWiZBEFmjtQ44tN4RkikKqfSa3nYqhswCmg4BDQdTP4QKqxBZpMeJu1RClVR5Ro4m5vLEMg19JsIyhecu3MPF3S9e2YBfzd+ofEx+7g43tmH9AXMS/Ogne7rEtlxBvEU6WlBFvB5uISW80JyrxQdXeMpUAuThRbtwyxMr8KrLMyjEZCKd4U8pLNMZKu3VjkT8nTwsM3HoqQq3cL3vja22R9T9uVLfGvPc6W7PXcKwTPW5xeuUXNy1L3yWIAiiw+xbCoDbxVR6dSEVmXYUVQGosAqRPXqcuEvNcxe/ki+2+TXmDMtM49wG52ByWGY0dydf8gS2Jazbns9O7MWdk9ieuw6OI14OtzZweLBUYZnWw8maYx+sbwUAHG5oU543oecuBXHnDpVOVlAlWVimqk+eozG6tK8QxO4Rdc7tkOPEOXdOcaf2qLEEj8XCSCnnjiCIbsuejwEtAAybAyBWSKVXe+0AYNAxgOZPq98dAJw67FQqrEJkhR4n7lJZzI7l7cQfF/RrLi+G0/uWqJKglXIHn8agMWd4Z64hPw26we3/Sdulh51z19GwTI+cLXmhItYKQRGWKXvzFG9bWwC53v6peMVS63PnPZ6qt5syLNOroIpCdMn72l4116C6we1cQvd11ymrZTrDM2XssEyPz49UPyvkYIAeHhhAEERPY89iM78sUAAgVkjlnJHnZNmwLBPIByqmpO25C2gBKqxCZIUeJ+5SQcy9lu2uxbl/+hBAbAIZ8GmOXLlQGu0MOGJ97gI+rceHZSbCkd8kizty3aWFEBScA82h9sfdG/bz79wuiwZdOpdAvO+X7qrF2v115n4KAaLZeWnxAkgeR0V7cu6c1TLjz6eyUS6iElW0M0kWeuoMxzb/DkXiK4wCTs+deIoT9rlTXItMLHw28epUMg8rQRBEpxBuMcXLiHkAqJBKHENnAQdXpVVUBaDCKkR2yFFxF7v5thxqNLcZMXEnT/LE5E6Q6LY1DNizuKBPy+mwTHfuj/iPpF16CEGwsbIBU3/xhiOMMh3E6/F/Czbhmn8ujo2vxwsaXeEJ21zViEv+9rFjm4wQ7e6HEoktQUriToRbIl6IqfLMVCGJ8jZ5gUYVlimPrymKwojXRXju3NeXKOcuUUEV77BMI84GFY6wTMq5IwiiqziwHDCiwMiTAFAhlTiGzALa6oHanekdRoVViCyQk+JOtToutgR9zpy7dL1vouR5wK/1+GqZiXA3jBbPKTnu0sM9mZebY6fKR9uqsXxPrf3/sl2xv1XvQa9CQqrH3a/r39/bjvvf3mo/7s43U5FKnzt3zp1XUaNElS+9PHOxsMz4cYDYgoQqz681rFv/O8/V2Bb7EjZcz4HqudBscewVlukdbiojv5yUc0cQRJex5xMADBh+PBVSUTF0lvn7wIq0D6XCKkRXk6PiLn6bnHMnh7KF0ujhxjm3w9cCPpbb4k56EqOGgfipMpEKbiFwVOqfliq/XrgZ6w80KB9z538FfRo4V1eMVdkkFjfEokVjWxQfbK2O7ZugNYEgpQq2cHq9vAqqJBJQzvdk/PGGh9dL1WBcjN8W1VHbHMa+2hbHueRw7TjPHeeYOLAE737vtDgbvUSw+KxI9lxRtUyCILLCnk+AQdOAgnIqpKJiwGTAX5B2URWACqsQXU9OijvVBEpMdt0FVUJugZZwEhubKPq1HM+5c4dlWv+S5y493OKrpil9cdca9g7lcC8wiB6M7gImMs7wxniPrDLUM4HQEEKqsS2CX7y83vaGydieO9e44hqW7651bFeLUvU1qPL4nM87i78uyXM37zfv4F8fOkNtVGGfYlFINzjyAhrKC4Nx5/PSbqnkLsZfF4k7giC6AD0C7P/U7m/33NbnqJCKG5/f9N7tW5r2oVRYhehqclTcqbaZG+MKqkSSC7RvPbUKDy/aBQ5ueziCfs0R3plr8DgviSUCsmRPT8Utimqb2yHuEniX3e/BgN+8pW1vluLtLW8LWx4qObIyomivkEjcCaH0rw934tHFe/D4kt1x+4ij7eIn0vvrvje34KoHFmPd/vqEjcKdTczT99ypWiWEooayqFJY2maHfQoRyc0wTM0hiI24c8iI1ymZM87puUu8L0EQREaoXANEWoCRJ+Jo21G8s/cdXDzmYiqk4mbEXPO5CjWlfegV468AB8fLO17uBMMIwklOirtEYZlxBVWihqMJs2rutXhHDVbuPQrOAU0T4zBE0qi02dNweEkUE2UiNeLEXTvCMts8FiCaQlEcrGt1bBM9GHWF4LFtkra9v+UwgFhYpttmI4Enzb2/2Mdt7yMf78L2w03WPuKY2D7r9tcDAGqaQ3FCSsbLq+XOiXNfo7gyVc6eyssIqAWufD6fxhzPmaoNhYzw+iUNy/TIGyQIgug09pjFtjDyRCzctRBRI4rLx1+eXZu6IyNOBLhuFp9Jk6HFQ3HC4BPw0vaXYKj6ERFEBslRcecdihb0OT1u4aiB/IAv4XihqIG2iGFNOGOtEHK5z507v4nmme0jTtwlCctsCkWxZGeNY5uX5+7Cv3yEP7611bEtaIm7RGGZsk3ffWYNth9ucnqhFOGNCT131mN+a+XDXRH0rlc3xv6x7Ikq+vP5NJZQJHmFXaqErK5YkFAd4/XchhU5d/LYPsbANOc2IHkT83Q8d1QtkyCILmHPYqDfOPCiAXhh2wuY2m8qJvSZkG2ruh/DjwPAzOerHVw+7nIcaDqAT6s+zaxdBOEiJ8WdOufO/B1XUCWqIz+gSfvFH9sW0dEW0QFwe6Jo9rnL3cmX28shJriplL0nYsTl3CUJy/z2U6tw7b+W4EhTCID53Ic9PMR7alritomcu1ioYvxx7ve4LieTwuW1SqGJudhdnDuSKD9PITqF8NEYU4ZYum0BnMIn5g10XZOF8LA5jrH2bUtB3Kman2ua815IJt7Ec5os505+mAqqEATR6RgGsHcxMGIeNtZuxNajW3H5OPLaKckvM4vO7P2kXYefNeIslARK8OL2FzNsGEE4yVFxF78t1sScObwG4aiBPL+3545zbnnudDMs09HnLnc9d/IkM2pwe6JJ2i493CIlWbXMjQfNqphCdHiJDy9EWOa593+IUFRPKpIA8zXVPAqqpBKWKR7z+9SeO9W+Tu+gyPtjkgdMcayH544rBGiqnjtVvh0Ax8KN+/NE5yIsM4ZcbEWGu643WVimQ8CSu5wgiM6mehPQVgeMPAkvbnsReb48nD/m/Gxb1X0ZcSKwf7lZhCZN8v35uGDMBXh7z9toCKsrYBNEJshJcaeaEjlbIThz7mTPnRsx+WuNmBPlWJ+73G6F4KyWadgTfkYlVdIi6vLuHm4IpXTcKb97D796dWO7xd2+2lbsq21JWpgEML1Kqvwx+e9ETqRYWKbluUvg0bY9dwrPm8YSV8uMeog31THy36oG48lCHsPR2POuCss0C6rEe+7cnjnxb8RuYp7wtJ6hpWFrgYkgCCKj7DG9UG3DZmHhroU4a8RZKA2WZtmobsyIuWbxmcq17Tr88nGXI6SH8Pqu1zNsGEHEyE1x55pgGQaP5dz5fXGTJtlz557yyR4UDjjCMnNZ3Lmr9lGIWPvQXS6oxTtr8MLK/Z77i2eZc+Dhj3clrJSpIuiP3dJRg6sLk7jetlGdO1shGN4hiaZtirBOxMRdolxU0e/OHa4KAJoW89ypiokYHuJOGeqpCMv0Eocq5DYn8nlfXn0AhvDcKfIU3XbbnkoP8edGNsvg5v5vbqjCeX/+EJN+TpMBgiAyzJ5PgNKheLdhOxrDjbhi/BXZtqh7M9JsF4G97cu7m9JvCib0mYAXt1FoJtF5+LNtQGfgXvXXeWySG9CcHrf4nDvnWKLyX1vEAOexyntmn7vcFTzc7bkTTyA57tJCnuyP6FuIoy1hrNlXhytmDUvp+HS9NaKgCmAuXKQSlhk1DM+wTJXIcm9asK4SpS+sxbiKkrjjvY5ViStdCv9VaSCHN1n6O1lYpnjPykI7WSXKiKLXHwB866nVmDqkFH6XuIt5D53jiP9Tr5bp9D6+tr4K33gy/aa5BEHkHqPuWJDhETmW5L2HpcZk3PH6g9ACffDZPx8GkOnz5BAlg4A+o01xd+JtaR/OGMPl4y7Hbz/9LbYe3UqFa4hOIUc9d87/zSbcpnfC78q5CyXJuXN47jgHY6LPXc8Oy0wWliZfWtTg9uSUtF16yMIgP6ChMOjzzPMC4t+7reH03mMBf+wVagnrShHlFhgRPfa+Nv9XtwEwEnjV/rdsn31cwrBMa4yw4t6RC/ckq5bpEGqqsExp+FgrhHg7vJCFZtxikRWWKYeyimt3jyuObU+fu8a2KHZWp99PiSAIIhVGsMMYxI7ifW0k/EXbEamfjRydFmaWEfNMcdfOvOgLx1wIv+Yn7x3RaeTkXeyejIlS/hpj8GnOnLtw1EBBMIG4i8riLnfCMpN5Lty5P3bOHVVUSQt5IUFjDHn+JOLOFRjcFlV77rzCCgOS5645FFX3fHQdG9W5Z8ij/PeYnyw0j/fq5WbdD4nCMl9dexCvr69Uevfk91kyUeoQajx+m8OzZx+TuucOkASbItTSpzmbmC/dVYsXV+2P21f8m7LnTnr4gQ924L43t3rvTBAE0QGO1zYDABaXhsE5Q6RuTpYt6iGMnAe01ABHtrXr8D75fXDG8DMwf+d8RNpRmIUgkpGj4s75v66bOXcas6plOlohOAuquCfXoUisoApHLH8n4NMShp91d5LlHMmT/S1VjVi9rw4Aee7SRRYRfh9Dnl9DyEOwqfBqst3Ypv5CcIi7sEe1THdBFcNw2Bm1PN3ibxnOubKSJRCrMJlo0eNQQwiPfLJbuY8u5cYqwzIdrQ6knDhlWGbscdW1pJJDKkS429S2iAFNY3ELHd95ek3cuOJ5jeXcJT5nspy83oBhcPzrwx3ZNoMgcp7j2WbU8GI0lm2D3jwOPFqebZN6BiPmmb/b2RIBAK4YfwXqQnV4f//7mbGJICRyUty5J0hRw2xAzhiDX9OgJ2iFEJ9zZ06uDW7uq0meO1VoWU9BVdBCRn74zY2H8MqagwCoFUK6yJN9n6YhL6Bh++Em3D1/o1JgxIVleuTc1bWoxV3Q5blze6h2VjfF59y5PHeAVCXTtT3kkccHxESdlyAVGIZ3WKY474J1lfjrO9tcx3l57uLDJ1U975x98hKaCCDW6859vS3hKHzM6bmL2eL+3yl4k7ZCoMJFWLT9CH69cHO2zSCInOc4bTP+lzcaWqCOvHbp0G8cUDSg3c3MAWDe4HmoKKyg0EyiU8hRcef8X+emJ0Kzcu4iCZqYu2mTQujCumGLm6CvZ+fcJepFBniHrZG2Sw95su7XzLDMrYea8NCiXVh3oD7p8V4FVepavTx3sVdIFZZ55h8+wMJ1lQCAX106FYD5XlAJPiD+faASjLFjzPfUp7uPYtXeowDUniidc0Si8dujhlNk/uEtZ0iiuz2HQOW5W7D2oNSjzzomSaEYN+48ul9cPAUA0BzSrWqZ8XdDUyjq+J8bsWuTbfWCtB2wg/IMCaLTGYCjGK0dwmslQXC9ANGmKdk2qefAmNkSoZ0VMwHAp/lw6dhL8fHBj3Go+VAGjSOIHBV3qgIIokedXyq3DqReUEUgJnQBn4a6lgheX1+FNfvqkoql7kZyzx3NMjOB03NnhmUKVMLN/ax7ecHqPJqhy2GZLR5hmev2m6JS2PK397bjpVUHHftMvvN1rD9QH+dJagnrtmBxI4qGNIWiuPwfZriKV1VMr7DMRO9LVS6gT2Mx8SZd66OL9+CpT/cBiImz97Yctq89FQ+Z8NyJcYuCZnHh1oju6HGXCHcrhFQLqvhUbsFewp6almybQBA5z/HaFtRrDPuKaxGpnwHwQLZN6lmMmAfU7QEaDibf14PLx10Ogxt4ZccrGTSMIHJW3Dn/33WkGVHD8txpDBGd48uPfIqobphhmY6cOyfx4s78HbAmxrc8sQKX/v1jvLmxZ628pJNzJ9Mc1lHdmFojbsIpon3MKe5S6WHn5bmr9/DcyX3umkNR5essbBKLGhsONuBAXWvcfo8t3h13fHPY23OnKhSjEmsG9xB3PD481H2ce9yAj9nHuL2E4n0qjttR3YyL/7Yobiwvwi7PXb5UeMmX4ienOyxz48EGvLz6gPf+rp6BXo/nKpxzLNtVm20zCCLnOV7bhJeKysA1HZG647JtTs9D5N3taX/e3fDS4Thu0HF4cfuLlG9NZJScFHfum+S6fy/Ffz7eDY0x+K1Z2TubD2PLoUZEDY78BJ47UVBFIAqquCe9Rz08Kd2VdHLuZN7aeAjH3fN2J1iUm8iTcbOgSuy91qAQaO7P9xYPcVdV36bc7iyooq6WqdviLvHtrzEWL+5CMW+gW3+EFLaqRFRU5x45d4a6uTmLHeceN+DTpLBM53HiqVDVPUrXc+fTGPKl58unpfbRKU4jrvdAXSt+8cqGpPsHPNRjJJVkwXby+voqbD/c2Gnjp8If39qKjZUNWbWBIHoDx2tb8HRxOfS2ITBCQ7JtTs9j0HQgUATsXdKhYS4fdzn2Ne7DikMrMmQYQeSquPPYnhfQHOFOK/eYeUH5gXhxt3Z/HepbI3Gl6IXnbuNB5wSkLdKzwjL1JJU+qbBDZnB47jTm8BK7vW9/e3cbjjQ5vaINrc4cLsFvXlMXnHB67hJXy8xLkGsKAJoWL+5awlFbsP7q0mk4dcIA+zFV2wYvz526FYI6F06EQKo8d0GfJrVCcB6rWfe6ytuVyAMmRK8QZLpheV0D6XvuxEKTvEiUqDG9uEa/T+2568wKvXe8sBaPLd7TaeOnwtJdtRjetwAj+hZm1Q6CyGVK0QSeV4V9+QYVUmkvPj8w/LgO5d0BwNkjz0ZRoAgvbqfCKkTmyElx5xVy1b84z1FwYtluU9w5PBjWoZf87WOc+Jt34iZiQhtOHFTi2J5owtYdSdSLDKCS7JnCXVBF9hIfbY6JO865sqfZ0WZvj/AVs4bGbZPf3y+uOoBKhYdPt4WRt8da2BtfUEW3xZRPY47wQdUCh0pEiZw7d16ZbhjKRQWxoKJqqB7waVLhFOexPoUoFCTyXIvPg4jlueOcgzE4PXcp59yZx8vtL0JRw/P+EufyGr+zijhxztHUFk17/J+8uA6/enVjxuyoqm/DzOF90KeQ8n8IorOYo23FKyVFYIZm5tsR7WPEicChDUBrXbuHKPAX4PzR5+OtPW+hKUzFpIjMkJvizmN+MqAkD34pnEpU9JM9GPJktjmsY9cRZ3K/CMv84XkTccExg+ztPU3cJfPMJasm2JMrhXYlcQVVpPdaXWsYoaiOpz/d69lWo6Y5jPLCAE6fOCDusbMmDYzb5hXOJxNN1XPHWJw4a5Fy7jQGR2ERd/GXcFQdZinEnTssNGpwtbgTodCqnDs/U1bLBGJFSZRFXRK8v4UnP+a5s8IyJc+dlmLBE4ObRWJkEziPFZ9R2aUx5jm+13EdJawbns9/Iv67dC8e/nhXRmzgnKOqoQ2DyvJRlOfPyJgEQcRzvG8d5hcXIdo4BTDIS95uRs4DwIF9yzo0zOXjLkdrtBWv7349M3YRvZ4eKe445/jRc2vxziZ1EROv6cmA4jxHuJPwisi9wQzOHavq/1u21zGGmMvm+X0YVxHz3vU0cSdPulVehGRzvFSKgRCJq2XWt0Tw57e34UfPr8OrayqVx1fWt6JvYRCPfPF4lLu8GSX58RPgVMRdOjl3bnHWHNZtwacx5ghPbIvqGNanAOdPMxc95BBOx/k5R1jnceePKAqyALF7zlB47vxaLCzT7aETtqt0XKKwTFvcyTl3zCnuUvfcceVng1cje4ObY3uNn8zj3l5aQro1fvY89kdbIghHDQwqJXFHEJ0HR1HxWtT7NITqT8i2MT2boXMAzd+hZuYAcEz/YzCufBz1vCMyRo8Ud6GogaeX78OXH12ufNwr5MntuWu2PA1ynlKiVXUAjt5Wcn+8VHLu6lsiuHv+RnvSmE1UZeVlxOQ36CEWepqYzRbyZNynaY6CKkdbwnZhFK/wy6r6NlvUud/WqlxRr9dLJibukoRl+hSeu1BUKqjCHKGVbREDA0rybC9jc1j39twpWpCo7jvD4FJYJnC4oQ2Lth1B1ODwawyMxbxw7vexyHNTeekSeajEfS33udM05rjfxXUvuP1knD25wnMsztVVRFXbAFMMMubdCkHVHzATNIfN3M5s5tpW1psVWweX5aOExB1BdApj2UEsKo2iIJIPvXlsts3p2QQLgcEzOlxUhTGGy8ZdhrVH1mJH3Y7M2Eb0anqkuNt/1JwEuMuF//b1zRh1xwLPnDtT3MVPmtwTYhGOde1xw+P2lY+W86dS8WQt3lmDhxbtwpaqzFekO+HXb+NnL61LeX950q2az4nnMOjh3WkLZ1+gdga/eW0T3ttyuF3Htob1uEI7sl7xuzx3da0RW3h4eUzMsMyg8jHVaxPwKMQhYxcjSaVaJjdF1PZ7zgdjpmCTe8zJYZltER0Bn4ZC0Q8urG7FYIiwTFdYqOoeksNVdc5x+T8+wfUPLTXDFzXTw8U9xJ0o8KK0IYWwTCHADA7PsMypQ8oSepkMztMTd4YIy1SP11nVMlvC3s9VqjS0RVDT1P42KYcazIWOgRSWSRCdxtzgJ1hckA+9biZ66BSwezFiLnBgBRBRV7BOlYvHXgy/5scL217IkGFEb6ZH3tn7as08uAEleY7t/+99c8XDa37StyiorELnDmUTJd3HVRTH7StHS8mTvVQ8WWLilCyfrT0cagjhiSV7k+9o2xKbJMoT3eZQFA8t2uXoI6YiF8My99a04J8f7MQtj8eXJH5h5X48viRxJcGHP96FC/7yEd7YUGVv0x2eO2fO3dHmsP1ejSbIYSwvEJ475/tG5aULWgsOxwwtwynj+yvHsxtlJwkt1JgpBDXNbCFSEPBZnjvrcVdBldawjoCPodDqB9cc0pViIWqJO7f9qtYQYd2wPZZNbVG7H5+um6JTbtfgvq2E507lyRdPt8pBJhZt5LBMjTkXc+TnTuyn8jYZXN0iQrVN7O8WzTKdlevaHOqY5+7W/67EnLvfxuz/a3+bFFH8Z3BZPooVIccEQXQcXr4GAENt3anZNiU3GHkioIeBgys7NEzf/L44Y/gZeHXHq4jo6j62BJEqPVLc7bXEXUVpvvJxrwmQ36fZfe6c250TKeEt8GsM/3fZNHx2TsyDp3UgLNMrfCwbyCFw8tz3929swd3zN+JNS6B45XDlYljmgnVm3tuEgSVxj333mTX4+Uvr0dDm/aG7t8Z8X9758npbrMml603PXUwg7KltQZ3VH7ExpG55AABlIizTtT2R587dU09GiJFkrdr8mhmWKYRMYdBv5tzJBVXksMyo03PXHI7aiwSfmTIQfYtMD6Qhcu5cnjtVY/avPbbC9nLJhTvCugEfM8My7VYI3MNzpxJ31jaVhyjPDsu0qnBa3rQ8RVimuZ9p36j+RXFjpe254xyJNPf+2lbc8fxaz5y99iKK4STLuXts8W789MX4CIEFayvjmr6ny6H6NmjMzI0uJs8dQWScMtRjeUkbhrSUgEf7ZNuc3GD4XPN3B1siAMAV46/A0dBRvLfvvQ6PRfRueqS4E567CpfnTuCV0za+oljprYgLy7SO9/k0XD93JH5ywWT7MUdYpuS5S2Wy5VWyPRs4cu4ke5oskXG0xZxoe4m7XPTcrdhTCwAoLfCeWL6y+mDcNuEZqrHy5g41hPDOZjO0U57Ea1JYZkHAB86BpTvNcwqRp6KPCMt0vW3y/Bq+/5kJ+PO1M+xt4vUK+DTH4oNMi5Vf5ZXXJaMbsfDnojyfWSRF8vz5FGGZRXnmfdEi9dm7dMZQO3dQNziienzOnUrcLd5Zo7SrLaLD5zNz/rzCMoXnThXJKO5FlYjIsz13sVBFdzEc+bkTr/GIfvFV537/+hZlPqXX4ogQkl6fER9srcZTn+7Dzupm5ePtReQfJxNmd768AU8uTRwhUNWQXnjSY4t34/HFu1FZ32aGzvs0FAUT54MSBJE+04vfQWXAj0jdcdk2JXco6gf0nwjs6bi4mzd4HgYVDaLQTKLD9EhxJzx3XjlDqlXxp26ei8mDS5VePbc3TxwfsCZwPsmz5wzLjB3nLgOvQkw+O7MRcSo23PL4Cny6u9beJk8khTgQk08vAZCL4k7kHakah4uFhIXrnFUt756/EWf98QPc+fJ6vL3pEE6dMAD9i/Pwm4WbcM0/FztEm8ZiXqGZI8oR9Gu2t0OIaRVCFLkn/EG/htvOHI9LZ8T63YnXK+BjyoIr5jjWvknCMiMGh24YtneuMOh3hFoyRUEVMyxT8tzpIj8v5vX2aoUgxF1hChP7UNT03Mlhme7nZ2NlA9YfqI/bPuqOBdh5xBRHKs9dvttzx03b5etVee5GKhpvv76hCn94y+xfKF+vt+fOfJ94pdbVWc+REOiZQoyXiWqZu2vSE553vrwBP395g9kGwYrGKM6nPncEkWn08rUo1Q3sbDw926bkFiPnAfuWAkbH5kU+zYfLxl2GTw5+gsomdQVtgkiFHinuREEV3UMkqTx3Q8sLAKhFiTuvTKz4C9EnT4Id1TIlz0NbCp47r0mo4HBjG9bsq0s6Tkc41NCG1zdU4f63t9nbuPR0iQloMvHmlTOUDq+uOYjDjR1LQs4kQtA2WqGXX3l0Oe59bTMA2OGYS3fV2oJtxZ6jeGjRLuysbsZji818vGF9CnDCmL7YXdOCZbtqHaJNY7FQycKgDxMGxnI66xOIu7ICj7BMhVdVvD3NypxJCqYk8dzpBjfbAFj7leb70dAascN4fVp8PzaH504K4fRpmu31NsVdfCuEmLhLHpLXFtHt89thmS5hsqmyARf9dZHyfnt3s9lGReUhcve5Mzi3Q1jFZ4Ucni1E4OyR6jAnkUtYEJQ9/c7PqKr6Nvz1nW2IGvHN3WXqbXGX2cWV5lB6BVUShWXvqWnxfEywr7YlrvhKVb3Z4w4ARiq8oARBtJ+Arx6bilsxqaEcnKuLdBHtZMSJQKgBOLyxw0NdNu4yAMBLO17q8FhE76VHirtaK8zJa5VZJe7ERFI1KXGHHoZ1cx8RjibnJsnOjjxHQZWO59z9470d+Mpj6vYOmUI1cZTDMoU3NJTkejrquWtsi+Cb/1uFmx7+tEPjZBLxGja2RdHQFsG7mw/h0921CEV1tEUMnDFxAHSDY8nOWuyobsJXHo23fUhZPmaPUE/yGWIFPBhjGFJWYD92VBGWKYSHqJbp1igqz7XYJ6B5e+4EXkU7BBHdgG7E3jMVpfk43Nhmv3/NJubOY+Scu3+8v90WIw7PHecIK8IyYyIo+cdSW8SwCo/EFku87qtEgkXluQv6Nfg0ZnvjdSnvULxHCiSvvfDc9SvOw+57L4wbTwi5QjmM23X//PmdrfjDW1vx+voqsARhmfXW+0SIsUzRkkIrBPmzUxVCK9h9JLnn7sb/LMPvXt/i2La9ugmDrXviuFF9k45BEETqjC5/E1HG0FZHve0yzggr7y4DoZlDi4fihMEn4KVtL8HgyeeVBKGiR4o7MbHwaugbVoReCgGn9typwzJFoRWH507KupM9D2lVy/SYQNU2h5UVAzNJsrLwQZ+3CJZp7WArBBGuJ/InuwPC+9rQFsGynbUwOFBZ14pF244AAKYPKwcAVNW34tYnV8KnMbz3/dPjxpkxotzxvxBH5qTd3KYxYEh5TNzVKV73Ef3MAh3ifcZdvjuluLN++33MM+fOtiuJuIvqZlim2K+iJA+HGkL2YoDsNRPI1TL31bbiuRX7zXNpmtSMHMpWCLbnLpCG504SQl6CKJEzSiXufMy8Brv3m9V2QebMSQPtv8+ZbP49pExd4EksNuUn8Nz1KzLDfo+2RByC1U19J4VlpuK5Ez0ZAXVlU0Gd5IVuaIvE5fG1RXTsOtJs56gKOAcGehTJIgiiI3CEy9ZjWlsYK9tOyrYxuUf5CKB0aEaKqgDAleOvxMHmg1hS2bH+eUTvJavijjF2HmNsC2NsO2PsjlSPEwItnaqTAWsifM2c4Zgzsg9unDfSfsxdLdMWd5bLTvZ2ebdCSC52knkYGtoiCEUNzybsXqSzvyrfT55IiudCPMde8/+OVMt8YeV+3PrflXHnFnz+wSX4zcJN7R7fTW1z2Pb2JqLN8tREdI73t5oFUQ7Wt+HLj5re1FH9CxHwMSzZWYvNVY247YxxGN2/CDedOMpuZH3W5IGYObwcXz1ltD2u8NgwFvOsaYxhSHlsIqsKy/z5RZNRku/HREX1TiC+zyMQey/4fRqCPvO8Z0+uwCXHDonbN1m1zKjh9NwNLM1Da0S3J/YaY3HexIBPcyyW2D3xpH2jhoFINL4VgijqkUyUAlbOndXnzjDM697l4TFS3W/CFlVYpk9jKAr60RKKFRlxC2G5eMqtZ4zD6jvP8azeK4otFQS8xZ18H/gUz6tALAI0ZzgsM5Zz5/05VimJu/rWiOfnjlhc21PTjOl3vYnHFu92PL6vtsVq7q7HjTHYQyATBNF+tPy9qMkLYWpDOVpB91jGYcz03u1dHB9i0w7OHHEmyvLK8OK2FzNgHNEbyZq4Y4z5APwdwPkApgD4HGNsSjpjpFOYROTK9C/Ow3NfPxFD+8S8Jl7VMv2Sx0WgOcRdep47Ya9Xn7vGNnOC5VVswYt0aiComiDL5ggbk+X0dCQsc/GOGnyyw6yCqHoudlU3Y0c7qgHKLRxkZt39Fmbd/VbS49uk5/3NDYfiHi8vCKKiJB+vW+c4y/LY3HXJVDx443HYfe+FmDy4FIwxR5ETkWvFEPMyaRqzQ9AAtbf5xLH9se6uc9HHaiFw6vgBjseZQnkLIRPQGAJ+8/FxFSW4fu7IuH2TVcuM6hyGlHNXUWJOCoQHxxRWztdPLIjcfelUALFwU58me9jM63V77gDz/krWXB2Iee6Y5eV6aNEu/G/ZPuW+qveqCKVUee4YMyuDNlmCR34OFv/4TKz8+TlOmzXm2WjetFWEcnpX122WWmEkCssUXrGWBK0z3Iy6YwHunp84F6Q5hbDMqoZW+++GtkjSsPi/vLMdALB2f73jcVHMpjWsx73vjxlWltBOgiDSp3+fD1BgGGhoOD7bpuQuI+YBjZXA0d0dHiroC+KiMRfhnb3voK6trsPjEb2PbDYTOh7Ads75TgBgjD0F4FIAKWekVtW34tnl+xDRDfzWlb/h5qVVBxw5RhsONNh/v+ESBB9urQZglmF350Kt3V+PZ5ebk8imttgEqyUctbd7sXLvUQDAom3VyrCm/UfNEMWnlu1VTjq9kBtgJ7NBDq0SvLL6gD05XXfAORFr9phErtp7NOm5vNhyqNH+O6Jze5xw1MCO6ibUt0awu6Y57fEfWrQLDy3ahd9fNV35eLLxmtqiZtGQtigON4YwvE8B9h2NTWiX76m1Bf+Akjws2VmDJR6l+uVCMWISvO1wIwaUmM/zgOIgNh6sVx7rZe/pEwdgaHkB/vPJ7rjHL54+GG9vOozFlmjed7TVnqhvOFAPlV56adWBhOffUd0Eg3P7vb39cBMA4J1NpvD9aFs1dh5pchyzs7oJzy7fh/yAD36N2SX7P9xa7cjTiuhcWXgj6NdwuDEUt91NTVMImmYGSRsGx3+l8vz3XnEMHvxoF7ZXm7apWhGIc+yXXl/B9sNNCEUN7DhsXsu+2lbUt0ba/X4PSeG+gqU7ax2LSusPxj6PWiN60oJFy3fX2n0DEyFE4kOLdmHSILUHGAA2Wuc/0hT2vM4PrM9FwFz8qKxTF0PadcS8d9/caH6uHrQ+pwXvbzG94pX1rfif9LodM7QMK/ccxco9R5NeF0EQKcJCiJRuxkXNLXgrQi0QOo2RJ5q/93wC9B2deN8UuHzc5Xhy05OYv3M+rp9yfYfHI3oX2QzLHApAnkXst7Y5YIzdzBhbzhiLqzQiHHc1TeGECf5AfPEIOYfGHXIlxJIvsWPDEc5p8ORholzyXKgQK/xeTdi9SMdzlyhEzXw8tXOHoga2VDWmHUIKOAveyMc/v3I/Hv54N5rDumevQi/kccSxtc1hx/X+4Lm1caF7BufQDQ7OzfL8JfkxUe2uflgQ8KHUqlypKnsvI0/cbQ8wTM/x76+ajqlDyuyxZM6dOjBumyDg01BRqu7teOqEAfjVpVNRaFWq7FcUtL1NUc6VxVOSpNxBN7jdBgAwq2UCwIdWDqLcQFwgewPzA7G8NU2Lr/YZUHgO8/2+lKJaIrp5TRpjMAC0SGJIY05PqMrDJAoGqSqKMmu78KBzj+cvVcTp5fdE1HWPy548jcU/V25S8e7Xt0biFmu8EPdMoh6csje/NaJ7RiBEDQMt4agdieBuE3OkyRTbYT3W4P3SGUPwhbkjUrKVIIjU8ZeuRVQzMKOhBFXol21zcpcBk4HiQcC2NzIy3MS+EzGt3zQ8v+35ds2ziN5NNj13KcE5/xeAfwFA3uDxjnd4eWEAV88ZjlV7j9q9pLy4es5wx/+6wfGi5bm4YvYw/FIKWzp2eB88vXw/zpw8EHPHmB+GP3huLQBg5og+9lhR3cDPX95gH3fRsUOUTZEF1U0hLFhXheNG9cVlM+N0LO56xRzr7CmDMLp/UcLrkWlsi+CnL61XXqeb1fvqcP872xzbzj9mMIZbYmXVvjpge8wbVZIfsCdjMkt21uCjbUdw/2dnKK8lEc9aRTYAcxIrbP7fstgqfmHQl/Ra3t18CMV5ARw/ui9CUR0/fH4dAGBY30KM6V+EU373Hm47Y5zjmOrGEH543iQAwPoD9bjor4tw9exhuOfyY/DD59dhwsASHLA8EndePBUvSU3LrzluOFbvq8e6A/W4dObQhPbVNodxz0KzjUL/4jwcbgxh0uDSuGMmDS7FE4v32E3P7750Gt6wQkJV4+8/2mJ7qVWPX8WHYd6Yfjh78kA8u2I/Xlp9ECP7FuLcaYPwl3e3O/a9Zs4I/PiF9Z7XMKS8wMyNihi4es5wNLRF8Ps3t9oT8jMnDcShhhBWSJ6W6cPKbbse+GAHDlrP5TlTBmHhuipUS165Y4f3wbtbqiEzoCQPBUEf9tYiIT6NoW9REH2LgmgKRXFI8khfc9wIPPzx7oTHiwWUH50/CRWleXhiSey9N3lwKYJ+DQfr2nD1nOGYv7YSQX846ftRID4r3IwZUGx76CYMKnGM98qa2PusJD9gtVfQcf60QVix52icN3NY38Kk9hx/z9uO42aOKMe4CrX3Tpy/OM/vOe6qfXUoKwigvjWCl1cfxI0njlLu17coiKlDYuGVpQUBx5iiyE5AYzh9YgV+89pmfGbKIFw4fXDC6yEIIn0KypdiVDiCfS1zs21KbqNpwMTzgHXPAdEQ4FcvxKbD5eMvx91L7sb6I+txzIBjMmAk0VvIpufuAAB5FjHM2pYyor9UUxr5JwK56ENcnztrFd29HQDkLX6f5ihqkayRuejLp/KeRXXDLpKQbrGSdArLuD0GgHO1PpKix0w89xsrzckqt8L3UkHeT16Q8ksVPpLl/EV0A196ZDmu+adZnapNqt65dl8d3rNCv1btc4Z4yd6Gpz81Hcef7KixK2X2KzY/kKcOKUXfoqCjGmZpfsAuOJEoxA1w5leJHDKV7+eMiRUOb1zQr+GRLx6H33mElvqTVEFhjOG8aYOtgirmvuGooTwuScodIjpH1IhViizJ8+PEsbGVX58W7+kReX6AOakX+W5+jcWtPqpy7ory/Mr3c/9i5xdlW0SH36qWuWpvHQ66wo2TvX+EN29oeQFuO2O84zFNYyjK89vvU0NRLTNd8qz2CjH7Y+/X19ZVYr3kYTM9pqZ91xw3HOMqYv0QBank3LkF4Xn3f4SaphA+3n4Eo+5YgD1Ss3ERfu3ljQPMoj/9i2OhoP/+cKdyv3DUwNZDZkjsuIriuKgK0eS8NaLbnl3hce4tJCsmxhj7LmNsI2NsLWPsHcZYfNIsQSRBCx4GCvfjysYmvKvPyrY5uc/EC4FwE7Dro4wMd8HoC1DgL8AL21/IyHhE7yGb4u5TAOMZY6MZY0EA1wJ4JZ0BRAjh0QQNoL2QQyrj+txZAsenmBC7o7PyAz57W1JxJ6plKiZQskBtjeiobgzZjZaTkY64UxXukI9XPZ4I4Yn554c7MeXON3CkKXm+VItHjy75NUkmFD/efsT+uzkUdRTN2HCwwW5fUORqiC1fq8iB8vuYLainDyvDD86diEe/ZCaej+5fhOe/Pg9fPnk08gM+/OqSafjaaWMwy6OXnUAO97P/9tAHctPugE/D6RMrcI2H9yRZERQZUSE2rMc3xtaYuiCLTNQwrGIi5v+MMdxzeWz1UG7tIJBDD8uksFONsbhQQ1VIZEm+WtzdfOpozJRaTISiBjSrz52KVJt8+zSmfG4Kg340iWqZHQzLBMxrlYeQwzC//uRKx2dYVDekfoWa8jVvT7XMqGFWFJ2/1vTSfSjl0LVIPf28ONoSdhSOUUUplOb7zXzF6ibkBzRMGVxqizvD4Pj3hztxqCFk9hGM6LaoTBTxkGukWExsFYA5nPPpAJ4D8LuutZLIBQLln0LjwLxGP9bxjueBEUkYfSoQKAK2LMjIcMXBYpwz8hy8tus1tES6T9soovuTNXHHOY8CuA3AGwA2AXiGc74h8VEx8gOavfper2gAnYyAIidK4K6WCcREnXuSN7S8ACeP6w8A2FiZOL9FVBZUTaAapeIsbREdX3hoKb70yPKUcs/S89ypWiHE/pbz/UQlwkRssjx3r1phXQfr4gtUuGn2EG5+X2LP3e/f2Iwfv2CGXn60LSbu1uyrc3g71x+sx9JdZlzfAZc9cv6VmHTWNoftHKyCgA+3njHO4SmaPbIvfn6ROfca0a8QPz5/clKRJXt6hOfOSyDIeX7JKkWqvMleBK19I7oR9x5PRazohpmPKC9yyB5Jn6KqoyzYSvNj4s7vU+0b760pCPiU7zmNMcc9GzU4/BqzWwN87dQxjv3njkmtCbaPqcQdQ3Gez9HYO1lPwGTkBXyO5zwUNbCpsgG/e31z3L4RyXPn01jc4hPQ/j53u2ta7J561VK4tbgnE1UgrmuJoE9hAI9/2Vz4UC2q9SkKIhw1cLQljH5FeSgvDNgVPtcfrMc9VouTMf2L0BYx7KJUhYqWFDmMXUyMcx4GIIqJ2XDO3+Oci9ncEpiRLQSRBlEEylbilJYQVkZmgPfMtsY9i0A+MO5MYMtrGWmJAABXjL8CzZFmvLnnzYyMR/QOsnq3c84Xcs4ncM7Hcs7vSefYsoKAPRFpl+fOmtAFfCzOgyFyiuRJlZiYued4L956Iv75hdnI82tYtitxlTfbc6cQY3LoUihi2JUJUxFuXiXJ1fuqWiHEFyMB1JN3wCl6d1Q3gXNuC7NICu0pvDx3coGN1oizB1Ztcxh/f2+HnZdX0xRCn0JTPKzaV2d77o4ZWob9R1vt59Mt7nTJPlGxtLEtVvxB7l2YKfIShGUCTg+XqnedTDqeOyEUw1EjrpejV5jhKeP7239HdMMSNrHHZXGnKVohyILN7blzv/VkISuuuzDoU77nGWNxnj6NMbvi5tyxzkIB9119LJ69ZZ79/3Gj+uAbp491jWk+D+7nlDGGwqAfLWEdtz65ElGdJ+0JmIz8gObwMoYiBr7w0FL84/0d9jZxfRHZc+eLtw9I7pn0+tzYW9Nsf4YdboiFsrZIXkpBVDfwypqD9mtc3xpBWUEQp4wfgEGl+XGVhAGgvDCIsG6gORRFUZ4PZQUBu5G53Nx80uBSAECtNYbbw57jpFRMTOLLAF5TPSAXHKuurlbtQvRS/CWbwfzNuKaxHu8YFJLZZUy8wGyJcHBVRoabVTELo0pHUc87Ii167FJOeUHQnsCoJhnJECFrqlwkEZooT6rEn+5pVmHQj8KgHzNHlGPZbnVZfIEQYSrBJHvu5BDDVMIk0/HcqcSXHCYalh5XTcgBOMLjIlbFOyHM3Dl9z6/YbzUtNsflnCfw3MWeXc6deUl/kgrm6AZHXWsEw/sWYkBJHvbUNNueu/OmDXKMWecS/rJnskF6zg9ZE93OEHfJPHeyCEoWKpks504mIAlu93EqT9SsEeV4/Msn2P9HdeG5kypgBqUFD0XOnSzYSgtiE3aVaJW9kMWW97Ig6FNWf2WID5/2+5jdnH5M/yJH38n8gA/TpZ5pxw4rx1Wznc4P8Ry4bfMxZocJLlhXicONobREtYqgT3N57vS4hd1+VmsD0V8QiM/rFXgtkAi8wqN317TYixo7pcqxtudOevKfXbEft/9vFZ60FlTMsEzzvVqS71e2mOhTGEA4aqA5pKMoz4+yggA4BxpDUftzesrgUkwfar42RxotcdeLwjLTgTF2PYA5AH6vepxz/i/O+RzO+ZwBAwaodiF6KYHyT1Ec8WN2i45FxrRsm9N7GH8uwDTTe5cBGGO4fPzlWHl4JXbWq/OcCcJNjxV3ZQWx4hbuCXwqBKzJrirMLWx77qSwTMQ3NJeZNKgUe44kjokWK+Cq0KdGqQdWW0S385NUBVDcdDgs0wAWbTuCJ5fuQVguya7FvHry5PbYYeWO41vDuv14a0RHVX0bbv/fKtQ2h/G9Z9fglN+9h6m/eAObKhsQihqerRvcAkSEnm2uasDjS/bYk9yjLWHLixDAiL6F2FPTYgtiORduVL/4dgWyiK5vjdiT+IP1poevoFM8d1YTcw99UKZoieBFWjl3oqCKIueOK4rtu7dEDA6dO8WdnFNnNiZ3HiN71+TrkpuYq8YSr0N+QO2501j8vSqLpaHlBXjv+6fj6ZtjFeHy/D77HJrG4kJehfdSmXMnFfg40hRKK+du6pDSuG15fp/jsyMUNeKKiBRaz4HsufNrzBGuLPBaIBFUKvpZAsCemmZ7UUO0BdENbi+kyM+9WAhZuecoQlEdLWHd9paX5Pttr5tAVDANRw00haIotsQdYHrJhRh8/MvH28K/ptkUoUW9q6BKSsXEGGNnA/gpgEs458mTmQnCgvnr4SvaigubWrHEmIY2dLxyI5EiRf2A4XOBLQszNuQlYy+Bj/nIe0ekTI8Vd6UFfluo1Ck8dzfOG4k3v3Oq5/HCS6TKZxECQJ5UiXmZ1xyvNN+PpnA0LkxNRug0ledO9iJ995k19iQrlZDLRPv87d1tdosFc994sfj9Z9fg+oeW4qcvrkez5BHgPJaP9853T8PlVsuDcRXF+PlFU/DNM802A60R3X4+H/1kN06/7z28suYgnpdaHrSEddzxwrqE4WTu0EGx77r9Zi7jd86ZAMAs4lLfYoq7kX0Lsa+2JZYzF/Th3e+dhv9+5QRHoRKBHP7a0BrBSEsAiubu+YoKjh1FCIxUwjKTkSxsU0bkDY4dUBx3nOwVFYjXeuXPz8Ep4/vjUH0bdlY3OcSPLFA0lrgCZkl+YnEXUIi7Ai9xpzEEXTl6fo3ZQsrv0zC4rAAnjHGGZwrRoDHm6b2My0fUmKPAR0tYT0vcPXXzXPzh6mMd2wI+Z/GXUNSIC0UUi0oR3ZA8dyzOvj6FgaRhmav3qkPE99TGPHfit5y/5xR35t97appRby2glVkFVUryA3GLak/fPBflBUHLcxdFUTAm7upbI6htiYAx8/0uPOQ1TWEw1jmLKt2YpMXEGGMzAfwTprA7nAUbiR5MoHwZGDhubDpMIZnZYNIFwKH1wNE9GRmuf0F/nD78dLy8/WWE9fQj1YjeRw8WdwFEDY7NVQ14b0t8rkF+wIcJA73L1YuJpUrcrTtQB8A56RMTXOYxRS/JN8OPmhKsqBsJcu5kz51MTVMY5/7pQ2ypavQcN5Hn7r43t+KRT3bb/6vCMkU7AwCOpsdRqbBDwK/Z5wn4NHz55NF2ifbWiG5PnN/bUm0LB/cEdGtVo10dT0YIYrcHRRy/9VAjgn7N9sodaQqhrjWC8sIAhvctRGVDmy3a8gMaxgwoxonj+qNAUaRB7NcW0RGKGhjVz+wnWFnfeWGZtuBJISwzGemU5B9XUYynbp6LX1w8Bb5UCrFYr3XfoiAKAj5UNbThSFPYU9hoymqZsedPLpLh01hcGGJAzrmz7PMSd2ZYpit8UmN4/usnYt1dn/G8JCHwNRYv3H0enjvG4kNo0/GYluQHMH6gs31BwOesehmK6HFFREQFTYPHPiv8WnxY5mkTBijvo3X76+3nTu7PKFPXEsHe2hbrfIbVwsQ8b2HQh/rWCMb+ZCG+8NBS3G31/tx2uAk7qk0vX3lBzHPnZs6ovgj6NYTsnLuYuKtriaCuJYyyggD8Ps0Wc9sPN2FAcV7ScORcwquYGGPsV4yxS6zdfg+gGMCzjLHVjLG0KkkTvRkdgfJlGNJSjuFRHe/oM7NtUO9j4gXm762vZ2zIayZeg6Oho1RYhUiJHifuvn76WIzsV4iyggB0g+Ohj3Yp90s2WRATRbkvFwBUlOTZPZoc1TKt315zPDHZkcP+3AivmcrT5nXcO5sOYcuhRvzF1XhcRp4M//TFdY4y63E2pNHqwOy3Zf4dkDwv8kQcMMMyVR4lMYkUtEZ0OxRMRhSwcXs9hUdhy6EmjK8oxqCyfADA4YaQHZY5sl8hOIddgEb2AKi8cELciTYIwnNXaYVldqbnzuu9k464S5e5Y/ohP+Dz9Pi9+I0TceoEM1dHfvYDDq+1l7iL90LLnjtHZU0tvhWCHJYpvPBmzp26oIo7T9CnMeQHfA4PoRvxevo0hvLCIN749ql2s2w7j9Y9LmOOvFdz3/TEh3v/QFzOnRGXZ3bDvFH23/Z952NxHu3R/YsRihqO+37Zrlpc/LdFeHjRLhxpCmH1vrq4HEPBNuteAYB3Nx/G/qPmfSqqm+oGd1SjjegGvv20WRxAeDRLPd6zQb8mhWX67NYJ9a0R1DaH0cf6Xyy8bDnUiIlJekbmIqpiYpzzOznnr1h/n805H8g5n2H9XJJ4RIIw8ZdshBZoxNUNzVhnjMIhpFY5mMgg/cYC/ScCmzPTEgEA5g6eixElI/DMlmcyNiaRu/Q4cXfFzKH44AdnIOjTENENtEZ09C/Ow5yRfRz7KRxyDoSnKeAK1ZoxvDy2TwrVMgVigunlgQOksEyFuGtojShDk0Rz7USeA3mS9+TSvXhtXVXcPqPuWIBlu2oRSSM/D4jl3GmS50U8F2KC1iaFZcrsrY0XcrKXUCAm0m6vougbuO1QIyYOLMGAEjPMcE9NM3SDo7wgiKHlBQDMqp2AS9xZYXyyl6E1oiMcNdDQagpHIe4+3m4Ww1GV5+8oAbtapvo19JooZxIvcTJzRB987jgz/UcWVfLrqQp7Bsz3pNvLJgs2OSxW1cQ8KC2siJDEfKkVwkc/PCOh/al402KeO3PfiYNKbO+T1/EaY7jk2CG47Yxx0rmSnsqB21z3/dEW0R1e4s13n4eTxvWHG5/mDCc9e3KFHWoqh1Ou3meGYR6oa8VWy8s/1xWiquLLjy7Hlf9vMQBnARzBqH6FOHlcfxxqMFO+hM1uz51YPBA5lw1tTs9dfWvEbqUAOO/TSb1Q3BFEZxHoswSIlOLG1p0UkplNJp4P7PkYaK3LyHAa03DNxGuw6vAqbKndkpExidylx4k7MWkSE8tw1ED/4mBcCF5xXuIJc8Aj506eaKj63HmHZSb33Nl97jyqZaomVyKXLFGulTuPrkZRxQ4AHlu82+G5E5XvEpEnVXoUk25b3AnPXSS+8h8Au0w9AEwbauZGbTgYL+5EpUt3ZdCWsI5QVEdlfRtG9S9CUdCH/ICG7ZaQKysMoK9VYVCEVebJ4s56T1SUOJPJtx1utD13FaX5+OF5E2PHdEJYpi/JwkBnnNNNnl/D108fi99eeUzcY0LkyK+hLHwONaiLc2iM2WGt9nlkz510T2qK4ityCKd47QsCPtuzHVDkvDrtTv7xlaeoVCret17ijjHzNfn+uRPtvMWOeu6Crs+ZcNRw3Iv5AZ+yqbsczjn/myfjX1+YYwtWOez5YJ35Gg0qy8dmS9zJC1WA8z5Q9VNUeUDl/DggFmor9zA8c1IFXr7tpLjrdIs72XMnjzlxUHwBGoIg0ocFq+Ev2oEJ9QMRYBxv6bOzbVLvZdKFgBEFtr+dsSEvG3cZ8nx55L0jktIDxZ1VBMFnNjEPRQ3k+bU4kVasyAmREfu7V9RLXI2XBSLXybOgilQVzotEfe4aQxHl5Ep47hLlWrnD2Lw8LSX5fke1zL7WRCtuPylc7PGvnIDvnjMBfQoDkrgzH8uXwjJVLRsON8YKvE0bUoaAj2HDwfq4/WKeO+cYzeEoaqxGywNKzLycvoVB7LKqkpYVBNDHFnfx1S6F566iJN/e5tMYXl1Tab9OZQUBfOP0mIemM8IyRWXKTGUV/ei8SY4ebqnAGMOPzpuEeWPivUPifS6/LWWPtvw6ymgaw08vnIy/fi6W0+H03MVeC7XnLrav8NwVBH32Iojj/mPx914qaYR5dlhmbFvMLm/PnaB/sfn+SifX0T0GYH7eyNcfihpx94xKcPm1WEEVv49B05htv5x3J/o5Mpg5qn2Lghjet8AxVnG+HwNLTYE3oDi+el6p4jPT7PkXex2FYJc9d989ZwKmDimLu4biPD/yAxqCPg31rREcbQnb96ss/FXVRQmCSJ9g+RJw7sNXGw9ghzEYG/iobJvUexk6GygakNGqmWV5ZTh31LmYv3M+msJNyQ8gei09T9xZv8WEpzWsI+jX4iZTqomKjFe1TDkPRp7gxsIy2++5E6JOJe4aWqNKm0VxElVfMoG7vUFtcxicc3yy/Yhje3GeHxHJyye8Xm5kYTx2QDFuP2s8mFQ8Q0x0xQStNaLbHkYA+PXl8d6hASV5GFCch3218e0i2jzEXWtYR7UlLIQHJT/gs5svlxcE7BC7Qw2huHL5BVZPtgGSx+LEsf3w7uZDtgdxUKkp/F657STcOG+ko0piRznW8pxw1/PWUb5++lgcN6p9eRQq77AI++MeYZkqrywgipT4cM6Ugfa2PIWXx9xX4bmThEBE8tzF8s0S5/2l4rnLt9tQxI4XCzGtHsWP5JepnyXuEt1/ycYAzOdTvvxQVLcFrUDlufP7NDs8XG70Djg9dweOmuKuNaJjy6FGjK8ojvMWBn2aZx4eoA4PDkUNx4JJgSIsU36vyK9pUZ4fjDGUFgRwqKEN1Y0h23uYT2GZBJFZWBiB8hXwN4zHZ/gWvGrMQ+aWFIm00XzAhPOAbW8B0cxVuLx24rVoibZg/s75GRuTyD16nrhjzgp3zeEo8vy+uMmUPEk/ZmgZ3MSqZToPlPstyZNxrybmgpi4S5RzlygsU+25E16tRNUO3WKxriWCV9dW4roHlzq2F+U5PXezXXmKAi+BIyb/whIx0TMrT8Ymmu4wSMCqwBj0Kat1fumRT/G9Z9bYeW+ClrBuN2MWAi3o1+yw07JCs/KeeO4LAs5eYmJiL/J8ThrXDyP7FeJwYwhPf7oPc8f0xRArZ2/6sHL88tJpGa3a9/TNc7HiZ2d79vXLBqrX1q8Iy0yl5YKqlYAsUApcnrv4VgjqnDvxfvY77j+VuEtqoi025BBMESrY7NFOQN53oCX+021i7n4fBX2a4/pDEcMuJDRzRDkAdb6nw3NniVmxACXEXVtEx84jTdbfBo42hzGwND/OBr+P4fazxuMrJ4/GF+aNjDuXqgJmKKqjQMqdFKJMLgIk5wTmOTx35r7lhQF8uLUaUYNjzijzM0dEDfzkgkm9qlImQXQW/tI1YL42nNoQhMY4XtFPzLZJxMQLgFCDmXuXIab1n4bJfSfj6S1Px0XDEISgx4k7MccSE0Mvz52YxK7/5bl47uvxIWxerRDcvadimON7OQtEDkpDIs+dCMu0BE5bRLdbHDS2RZWTKxF6lTjnznmD1zSHcEQRSsd5zEPy2rdOwVmTB8btA0DZNBmIhe3F5dyFdXuiCjg9ZeJ16FsUjKsOCJjC61BDCM+v3B/3WGtE9tzF5+qI16qvItRL3rcoz49P7jgTD95wHPoUBu1y8BcfO0R5nZkiP+BDv+I8DLJC4VSiV7Dq5+dg9Z3ndKo9gPq1Fdtk8SG/o7y8Pe6FFsDpuZELqvg0Ftcl3em549YxPvv1dPTXQ3y+ayqCS4gN2fOWrDqpLDZGWzmFiSrQqnCbZoZlmn/nBzQzLDNq4DNTBuLFb1j5akrPXaxaps/luWsORfH+lsNYvLPG9vC3WQWDVGMFfBry/D787KIpGDegOO7xUsXiUiji8twFhbiLef0DCTx35r4B1DSHoTGzXYIYZ+evL8DNp46NOydBEOkT7LMUettAfCm8AWuN0djJO/f7jUiBMacD/oKMhmYyxvDZiZ/F9rrtWHV4VcbGJXKLHifuxARPhGSZnjstTnQJL1hxnl+9Iu6L5e7JFObF7wvInjv1hDLPb+aWqMIyX1i5H3fP3xhXUOWO59fi3Ps/RH1LBA1tEZQWBPDqbSc7Vr9Fbliigg5uT+DhxpAy5zAUNRDROYI+DZMHl3p6O73aJYjJvy8uLNNwiLuK0piImTy4BEGfhgkDS+L6egHArVJFQhmNmdUAhedOhGXKz43IpxLl1t2vs7i+oF/DkPICFAR9dkEHALbXrrP5wrxR+MfnZyUMietTFLSvo6uxC6pI20SY7S8unoL7XA253cfJYsjhuZNEAWPxrRDyVAVVgj48dfNc/O7K6Q4hr1pUSUXciTHk2yeZuJPvtVH9TXG33wp7TJW4nDt/7PoLg36EdQNtEd0hhpQFVaQ+d+IzS4imJ5fuxU3/+RRfe3wF8gMaSvP9prjTPcSdFn/vCEry/coCSz+7cLLjvs23xu1TKOcmx8ZyF1QBYs/31CFlDgGZqTBlgujtaPn74CvYj9K6yZih7SKvXXchWAiMPQPY8pp3fkM7OH/0+SgJlOCpLU9lbEwit+h54s6aD4gJT0tIR55fiwvtUXnBZMREJ+gKd/QKSUzWCoExhpJ8vzIs87vPrMFDi3bZHjYRdrZ4pxmG2BrR0WB57o4ZVobJg2MFBoRYVPX+EuiuUMfDDSFlBcZQVEdUN+xJontyJfKL3LlvAuG5E8+BmIyK9gIC2WMzrqIEm+4+D5MHl9rb5aIlqgktYHrlWqycu5J8v309eYr8H7u8uks8RhThfX2KYpNLVVGJzsCnMVxwzOBuG34WC8uMvY9EOLDK2ypQzc3lyb1bfLnfw0KAyDlXBQEfhvctxDVWe4bYuZiioErqnjv5uS9TiJhXbzsZp4zvb+0b2z7aEnfuno3JcIs7vxYrqCLEUlMo6liQUN0LmsaknDvzt3jfi/zVcNTAtCFlKC8MmvmvUSMu3w5w9vSUH//bdTOx8ufnxB2z9f/Ox/nHDLbvq6CU/ycvkgQ8PLfFLnF3wmjqt0UQnUGwzxJwI4jLmhphcIb5+txsm0QIJl4A1O8DqtZlbMjCQCEuGXcJ3trzFmpaa5IfQPQ6eq6488Vy7oJ+Lc6flqwwhlcrBK/JrFfDY5mSfH/CsEzDJe7EXDdshWiJVW15giRK9ruLL8i4wzKbQlGlyAxFDUQNbk/m3RNQEQ6nyouT7ZeLyxQEfHE5d3kub4Q7nEwOfXV7244f1RcLbj8ZBUEftlQ14tHFe5SeAyDmlRH5O+7XTjzPcuEN2TsmxGxvR9xLsvYSr6fqPrLbCyjUXaL7Q5Vzt/Ln59hhiUB8W4hEzp2UWiFY48kLFqrww2OGlWFImenJlU8pPHd1Ld65tCrcT0PQr0HUMhLv/4bWqONel5+7c6fGQqZjOXdOz538/FeU5tn3YtiqIOzGkRsnPc/D+xSaLRekz8KSPL9tmxCT8uKJXHzF4bmTzjvQqlIrxF0qffcIgkgTrQX+0jWI1M/A1WwJlvFJqALda92GCecCYKb3LoNcM+EaRI0oXtz+YkbHJXKDHifuhLAQEx2Dwyqo4vLAJfHc+exQp9Ry7sTEK5GvoKww6NmGAIiFT7onuTXNZuihqJYpT8zqrbDMUAJxp/LqVdbF9yYLRQxEdMMWtO6Jc78i05Pl7psncOf+AOaET+TcnT9tEN7+7qkOwSxfixBpcuirOzxseN9CTB1ShsKgD5/sMFekJgwskfY3j/VrzD5Po5WXeNakCsdYMXEX2yZ7HMT19nbsapnSNpHDpWoNISbw3PstqcT9NvX7NLvQjsDtfRX3dXsLqoj3n1zN1Sssk8cFjsbE7RUzhyY/mYRb+AZ8sYIyov9iWFeLMAD423Wz7BzMU8YPwPVzR9h2i/vIkBZ1BhTnIT+goTViOMIy+xfLuXHq8Ml86Z4SfPOsWLi0OJ8cZit/BsjVMuXrER7SitI8BHys3RVeCYLwJlC+AkyLYkTdCIzVKvEyhWR2L4orgOHHA1sWZHTYMeVjcNyg4/DslmehG+nlhBO5T+bqvncRsSbmztViVQGDxOMwBHwsYbVMGXG6RJFgA4qDCXNzRMl/UbFSTM2EV0CsyMsTLzHJVnnuFm07ggkDi+M8dwBwsD5mxw/Pm4j73tiCtqhuVt/zqSfMkweX4O1Nh3DJsUPw7492xY352yun498f7nSswBcEfHYrhGF9CjCuwhRijJmTeae4M6/P6blzlWv3i3y+2D5/kHK+hOdO9vCM7FsIIL7wh8pzJ+cKqfKSegPLfnqW4/0U63MXex+J92q+Il/1roun4qcvrfPMT/UilZSDfNdrIt6iyrDMNJqYy55lVe6n6pyCbfecn1L1UJm4VgiaZt/v8jV6vQcDPs32Mk8cVIL/uyzWXkR4w+taYwtJA0rykB/woaktAs5jnyGLf3wWfvf6Zvz7o12Oz7o8RWi0CHPtUxhwFDoRYtQtvG1b5c9iX/w+N8wbhTMmVijDYQmC6AgcwfKl0FtG4KroFkR8PrymH59to3oso+7IrAAT3OIbjTsCT2HuHY9l1Kv6z1s+i+9/8H18fPBjnDrs1IyNS/R8etzsVgiSgGu1OFHBES/8mmZPTKYPK8NVs4c58sVU5/UqqAKYE6wjTd6euybLwyQ8eGKyKyZpQtyphKnbc1ffEsENDy/F40v2QFd42g7WxcTdpTOGYuKgUryxvgpPL99ne2rcz9nwPoXY+Ktzcctp6gp2A0vz8bOLpjhW7fMDmuW50x0hlmIPZ/U8y3MnTRLdk1tx7WKf8RXFqCiNNSEXk1JZ3H3/3Il4//unxxVIESXmp0lNkrNVtKQ7UVGSj2F9Cu3/xaReFl9t1vstT5G7eeXsYdh89/lJF1DcJMobFbg96bbHnMFhMwAUJRFpQCzsV75/vEJHvcwL+OJzepPhvreC/lgrBFkkeXnuEiEaix9tjoWK9i82xZ3w9Iv7KuDTYp45D4+6eFzc1+5cyULrcVUerzlufM6d3EOzOM/vyCMmCCIz+Ap3QMs7gsjRE3CxbzE+MKajDtQ3srvxljEbAHC2b2VGxz1zxJnoX9AfT295OqPjEj2fnue5s367y6+3p1hFQCoz/sptJ6d03kQL+P2L81DbHIJucGUlvyZRHMXlaau3PHdC0KhW88OuIief7q6FwYHmkA5V/ZODUlhmUdCHPL9me/gCdkEV5zF5AQ2FQX9afdkKgj40hqJWeGxsQDGELPhsz12eH5ccOwSDy/Ljcu7c4s5dGEd4kuRwwfyAz86Nkrl0xlAcN6qvQ/Qla27fGxFCxBGWKISIx4S+PbSnVph8333t1DEYV1GMrz2+AgAwrG/yaqdiMSDdVgYdxf1xFPAxWzzKz6mq8Ekq79HCoM9RmXdAiZlzJ3J+5c8QsZgjBykEHeLOKtiiCLsGYmK0QBGia44f2194y1W9RQmCyCyBPothRAtxbFMehgRrca9+XbZNIhTs4EOw0xiEc7QVeELPXMujgBbAFeOvwL/X/hv7G/djWIl3RW6id9HjZrrMlXMHiJy79Mf61tkTcOyw1CYhyaplAqa4MzhQ2xx29HoTCM9dLIzS/F3XKsSdFZapEHehiHNyunSXmY8WiuoOz51PY9ANjkopLLM4z+8QQ8wjj0kIrXS8CQWSt0AO9RITWXmbnXMX9OEvn5sJAFi+u9Yxnrh2sW+pKz9KjJeq6HB787prxcpsIp4S2QH8l8/NxBNL9jgqWXaURA1XX//2Kdh6qMnTNsbMqpHnTh1kPza0vDBufzeqnDtP+8Q5E2bWpoaqWqahEMzue33Jj89K6b1thjbHelmaYZlanOcOiIk2Z8sKqUiRdT5hs7sKaWGSsEx53MmDS/CzCycnbPtBEETHYf56+Es2IVJ7Mi7TlqKF5+EtY1a2zSKUMLxlzMYXfa+jGC1oQvLvrlS5esLVeHDdg3hu63P49uxvZ2xcomfT48IyvXPu1JXmEvHlk0fbTXWTESuQ4D3xE73YRG82N+62BnZYZgqeu1X76vD6+kr7/6W7TFEkKmAKivP8KAz6ENE58vwadt97IfxW82KBEJluQWyv4KehlPMDPtRbRWRU/QRlz4SqWqb7WsW5hdAtcVU2FOdINyRQ5vdXTcezt8Q3tidijOxXhJ9eOCWjvcgSeYQnDSrFJYqm8rFw6HiG9UnBc2e9X9pcYc2/vfIY/OaKY1SHJK6alCLxfe40acHDOyxzUFl+Srlp7nzH/sV5KAj67FxK+b4T95RskXxesa9dRTfOc2fei27R2V/RSoQxhq+cMobCnwmikwmUfwrGDPCjs3GhbyneMmajFfnJDySywgJ9LoJMx5W+jzI67qCiQTht2Gl4cfuLCOveaUFE76LniTvrt7tCm5hL/fryY/DPL8zptPMmmusKb52XuBN5P7prlisalQvRowrVCkcN3PKEGa/d2BbB+gP19phymKdPY3aJf3dLAoFok+DluUvHu1UQ8NmeR5UodXruzOtzVMt0CULx3BR4hWUGRN+ylE2M4+o5w6lyn4SYzKeSE5cu3//MBJw9uSL5jh7E7rv4F3xgafKJTGlBfAVaAPjscSPwueNHtNuuZLi9X0FfrIm57EUPKhZEUsGdG9yvOOi4l5yeO1ENSrYn9rjmyrWLC8u0WyE4z7nwWyfjma/RIglBdD06AuXLEG2agJP0g+jDmvCKTvdid2YtH4tPjQn4sm8hNKRZajoJn534WdS21eLNPW9mdFyi59LjxJ27FQLgzLnrjAmqfN5EwkeUHa9uVIs7gd3nzvpfiCMhaJIJl+V7jtpekFBEd3juNMbsvm/yxFH2FogKnHHiziOnJhEFQZ/teVSFc8rV80RBlUTVMsW1iCIO7p5kMQGatqmEBxUleZgwsBi/vtzDk9UBbjtzPB688bh2H2+HECvemqq8VjenT6jAj86bhJ9fNCXpvpn86GAuewO+1MIyU8XOSc3zY9OvzkOe3+dZqMVdERhQ9yj0LKjikXNXUZKP46kxOUF0Of7StdACDQgfnYdLfJ+gjhfhQ+PY5AcSWeXB6IUYoVXjXO3TjI47b8g8jCodhcc2PJYw/YHoPfQ4cRcLy3R67m46cRRK8v04e3JqIZmJePCGOfjnF2Yrz5toOtnPClOqSVAxE5CbmJu/RZ6MED/Jcn5W7jkKn8YwYWAxQlHD4Qn0abEef46KeIpJpFvcqcreJyPZRFW2oSBghXclqJYpwsp81oTU03OXidg5AoApPN78zmk4Y1L7PWydRey+i73eZQUBpWBRoWkMXz99rGdvOxlRUCYT76y4nDufZq/mFCQIy0wVsUCSF4iJunwvz52W2j1ji7s4j74ZGZHJ4joEQbQXjmC/D6GHKhBoGoXPaMuxUD8ekZ5XQqHX8ZYxG7uMgfiafz7aV2JMjcY03DD1Bmyq3YTlh5ZnbFyi59IDxZ1oheAMOZw4qATr7joXg8o6HnN+9pSBjsINgNRMOcEzJiY/bVLxE9Uqiu7aJBqf56fgldpZ3YQd1U0YWl6A8oIgQlGn587HWGzipwrNkq9JUS0zXeTy6Kr+YfKYqXjuIlbpT113VvaM7U+eu+7I1bOH4fazxmd8XFUho6U/OQtrf3Fuxs+VSdyOsaDUxDzR4kaqiHvN2dJA3W8u1Rxau6qma3/GGCYOLMG4iuJ22UoQRObwFW6HL78SkZpTcLa2GkUshFeMk7JtFpECBjQ8pF+AGdoOzGFbMjr2xWMuRt/8vvjP+v9kdFyiZ9IDxZ352+eqltnZ2E3ME6x+CyESkXoTuFsYALCrWwpJVt8aRWHQZ4dKJZqKnfmHD7BwXRWG9SlAXkCL99z5GIrz4qtuRhV2xHnu2rEyL09UixQ9AlUFVRw5d65ziucuqmhAbtoovBBEd+L3Vx+L754zIePjyk3MBfkBn2flxsycM/PVMuWwzLwMhGWKnpjy4okjLFNeqLErjiYeU9xqqnDX1799Kr4wb1S7bCUIInME+30EI1qMSMNMXOr7BFW8D5YZk7JtFpEiz+mnopYX46v+hRkdN9+fj89N+hw+OvARth/dntGxiZ5HjxN3Xjl3XXXeRKqCMYagX0NIN/DXd7bhNws34eVVB+P2+3h7Dd7ZdMjO8alvDTu8Xu58GCHWZIb3KUSeX0Mo4hJ3jNkTP/l5UYlMeQKqMaDYo4F7IuRQrSKFnfJEdmh5IY4f3Rczh/ext7mLx0Qtj13UEsBur4Mt5Ml11yuwa9R2xcudyZw7l71+n2bnyWYiLDPmuYuN5dk/L8Xr8vLcEQTRPdDyKuEv3opI7Uko4204TVuNV/V5MHreVK7X0oY8PKGfjXO0FRjFKpMfkAafnfhZ5Pvy8djGxzI6LtHz6HGfCHa1TM0ZltlV51VV7ZPJ82kIRw384a2t+OeHO/HD59cq9/vyo7G46IjOHdXv3GdQ5RcN71uAPL8vLixT05gy5y4cVYm72N9Pf21eSiXY3RQkCcuUJ5kFQR+e+do8TBlSam8L+JhjIpxvjaHbnjt10ReafvYO7HDoLhTznZFzJzcxL8n347IZQzB7ZB+Mr2hfH0FVWKbcE7I9C17iVu3K55ogiNQJ9v0I3AgifPQEnOf7FEGm42X9xGybRaTJY9FzEYEPX/a9ltFx++T3waXjLsX8nfNR3VKd0bGJnkWPE3e2587RCqHzwzJFqFayaU/QrymFlAq5sqdKGAlUK+kVpfmm587dCoHFwjLlEFJh09mTB+I/XzSrF8oeQndrgPnfPBlvfPvUpNeQH0zmuUv8FmOM2RPU75w9AT8+3wwvuf2s8ThzUgUumeHsfSb2pfln7yDWxLzzz5XJGmNugRT0aXb+rcYY7r92Jp7/+ol2+5R0KVTk1ZZ5iLtUC8UI5346fS4Jgugaqpqr4C9bjUjdHMAoxKXax9hpDMJ6PjrbphFpcgRleFE/GVf7PkAfNGR07Bun3IioEcV/N/83o+MSPYseJ+7EnGlE30J7W9eEZTrP70XAl7q4E03NAZe4c51DJe4GlOTZOXdRV5+7ImussCL37/q5I3DGRLMqYqIV+mlDyzBxUHKvQjLPXSpeVeHdu/2scXbT8sFlBXj4puPiWiEIaPrZW8iC5y4Dp3Lfsn6fZovHTFyJKE4khz07xJ2igJKbh26cg/9+5QT7fxEKncnG9QRBZAZzss4Rrj0Zg1GDudomvGqcCPo27Jk8qF+AfBbB9b63Mzru8NLhOHvk2Xh6y9NoibRkdGyi59BjxV1+BvJW0iHV8LCgX1PmtyVD9nq5i7b4XUVFvnzyaJw+YYAZlhnR7QItwj4xllzYRTxfcvhnJuZwTnGnKKiSwmuTF/A5ehUmQjg7M1H0guj+2Isq2TUjbdzvTzMs0/LcZeDjKpnnTvWZ6L5lzpo8ECeO62//Lz5G3K0QCILILk3hJjy75VlEG48Bj/TFVb4PoDGO5/RTsm0a0U6282F4V5+BG/xvIg+J22ely41Tb0RjuBEvbHsho+MSPYeeJ+6kad4XTxoFINbXrTPROiEsU0YWSe65lXsy+JkpA+1wRrNaZuwxnxYLy4xKPRd+c8Ux+MG5E3HcqFgxk0ys0BcEY8apPIyphMzm+bWUBbp4rUdKnlsid7GrZXaBNynTzV//+YXZtgct6NNw4XQzxLi9eXYyqpw7z7DMFC9Lt3b0p9hDkCCIruH5bc+jKdKEcM0pYDBwte8DfKxPxT7e8b6+RPb4t34hBrAGXOb7OKPjHjvgWMysmInHNz6OqBFNfgCRc/Q8cSfNO+68aAo++uEZ6F/cvryVdp03ybwn6NMcHrNUkT137pXzr54yxvG/CMUS4i4qe+40teeuf3Eebj1jnMOjkIlQt2TtE1IKy0xD3E0aVIoHrp+N/7t8Wkr7Ez0bZodldv657LDJDJ3r3KmDUFFqfjYFfBqumj0M2+85H8MzsDAR89ypw6JVHvNkTcxF4aa+RcEO20cQRGaIGBE8sekJzBk4B0bbcMzVNmGEVo2n9dOzbRrRQRYbU7DeGIWv+haAIf15YyJumnoTDjYfxNt7Mhv2SfQMepy4kwUJYywjE6VUsE+bZBU8aAkuN0VJ+nLJE7ObTxuDq2cPs/+//oSReOjGOfb/QggJkdccijVNv2DaIFvcJQsPzXRYpopUcn/y/L60iuKcN22QMgSU6N5cNH2w/ffJUjhgImLv0a6slpm5cwmvmfBq+1O4H1JB5NzJIk5euJHvO5HH2q84sWibN6YffnbhZPzqUlo4IYjuwhu730BVcxVumnoTAOAa3/to4IV4wzguq3YRmYDhX9ELMU47iNO1NRkd+fThp2Nk6Uj8Z8N/Mh6VQnR/epy4y1bAkBCVRgriThWW2S+Jd1EuY16aH8Dvrz42dm6NOSZx4m8h8p5fuR95fg1r7/oMbj51DEry4z13KjLhuUvWTDqVcLp0wjKJnsv9n52Bjb86Fx/+4Az8+4Y5yQ9ATLD01BofsTy7zF6AKudORhaR508bhHuvOAbfOnt8wjEZY/jKKWMc4Z0EQWQPzjke3fAoRpeNxinDTkEpmnG+tgwv6SchBPKw5wILjRNwkPfFzb4FGR1XYxpumHIDNtZsxPJDy5MfQOQUPW5Gna1cf7HybiRZAcnzKKiSbNU82YQqIE3W8lziDgBCUQOl+QEwR0GVxLZmRNx5eO5eue0ku61BMoJ+rUsqnhLZxe/TUBj0Y0S/wqSLAgI7564LbvzOWNwUi0GZtj5WLTP5faNpDNceP6JLWsYQBJE5llYtxebazbhp6k3QmIZLfJ8gn0XwjH5atk0jMkQUfjwcPR/zfBsxje3M6NiXjL0EffP74pENj2R0XKL70+Nm1NmukphM3Hm1Qkgm3rxK/gtk8SMmaV6TNRECGklS2KUzwzKnDyvH104bm9IYZQWBpNdP9E7sQkY9MOcOAM6ZYhY8yHTRp8JAfM4dQRC5xSMbHkG//H64cMyFAMyQzI3GSOptl2M8rZ+BRl6Ar/oXZnTcfH8+rp10LT7c/yF21O3I6NhE96bHibtsISaZyRb3gx7ibmBJvuN/dxEYlfg7blQfDC0vsMcViNV6r1V74bm77oQRCW3NSEGVFD0wifjFxVPwu6umd3gcIvfoSs9dZ/CLi6dg6U/OyvjiRVGeD/2KghjWpyCj4xIE0T3YenQrPj7wMa6bfB3yfHlA1TpM13ZZXrue+XlIqGlEIZ7Uz8bF2mLM0zZkdOxrJ16LPF8eHt3waEbHJbo3VJUiRYSXy0iSdKfqc/f2d0/Fu5sPO7ZVlOThSFPI/r+0IP6lePaWE+2/8/yJwzIHlMTEYsCnYcv/nZe0mEkm5svJCqqkwrA+1NaAUGMXqe2CucxNJ47Cq2sOYt6Yfhkb0+/TMLA0P/mO7Rj34zvOjLvHH75pDjYebMj4+QiC6Foe3fAoCvwFuGbCNeaGVU8gxP14ST8pu4YRncKfo5fjHG05/hj4fzgvdC/qUZyRcfvk98Fl4y7DC9tewG0zb0NFYUVGxiW6Nz3Kc5fNtap0CqrI4ZCFQR/GVZSgwFXdcWCp03OXbGVfzrkTEzoRkjV9WBmW/eQsx/55fl/SENZMhLgGMlT9jyBUxPpLdv7dP3tkH+y+90JUdIIY6wzyA764Qi1nThqI285MXDiFIIjuza76XViwcwGuHH8lyvPLgWgIWPs03jTmoA4d75NJdD9akY9vRW5Ff9TjnsBDSB4nljo3TrkRBjfw4LoHMzYm0b2hmXmKMJZaQRW3505419ytECpcYZrJcvJUJc+FLX0Kg1nNRTx78kD8+doZWTs/kcPYTcyzawZBEERX8Y/V/0DQF8SXj/myuWHzAqD1KJ6h3nY5zXo+Bn+MXo2LfEtxpfZRxsYdXjocl427DM9ufRYHmg5kbFyi+0JTphQRC+TJKuoFfc4+d8K7VugWd27PXRriTlDfGgEAlBdmtxjJgzfOwaUzhmbVBiI3EUsWPTXnjiAIIh221G7B67tfx/WTr0f/Aqsf6KrHgbLh+NigHpS5zj/1i7DEmIxfBh7BCHYoY+Pecuwt0KDhgTUPZGxMovvSs8RdFud3dkGVVFohyOLOKnqS78pNu37uSIyviMVUlyappqcSd/PG9oNfY/jKyWMSG5+A750zAS9+48TkOxJEFiBRRxBEb+Jvq/6GkkAJbpx6o7mhbi+w4z1gxnUwetiUjUgfAxq+G/46DGi4P/B3+KBnZNxBRYNwzcRr8MqOV7CrfldGxiS6Lz3qk6Ir8m48zy0KqqTSxFwRllko5dydMr4/Bpbm463vxnrV+JPkrqmKowwuK8D2X1+AY4aVJTPfk2+eNR4zR/Rp9/EE0ZloKYZDEwRB9HTWVK/B+/vfxxenfRH/v737DpOyOt84/n12dheWJh2pgg0FRVBU7MaGXew19hBjNEYTosb8bNEExWisUey9ISKxYY8VFQVpiiKCsKDUpS7b5vn98b6Ls8vusmVmp+z9ua65ZuatzyzsztxzznvOZs3C9/UpTwMOA09Pam3SeBbSkb+WnMfOWbO5OPvFuB33/B3Pp1mkGXdPuTtux5TUlFbhLplq+yEzJ5JVoetm7oZwF7Tc7dC9DY+ft3udz7+pkS9FMtGGL1VqnrJRRCTt3fnlnbRv3p7Ttw+DXDQKU56APvtBuy2SW5w0qpeje/BC2d5cHHmRne3buByzQ14Hztj+DCbMncA3y7+JyzElNSkx1FL5qHS1GVAlVvk1d9t3bcPpu/fi3ycPqrB+197tiNRiNvHKo+KJNCUex5HDRERSzcRFE/n0p0/5zY6/oUVOOD3Q3PeDbpk7n5nc4iQprik5m3zvyO05d9OKdXE55tk7nE3r3NbcOfnOuBxPUpPCXS21DQc8KQ9r1ancwlbeLTOSZdx47I5s3bni3CXPX7Ans288LI6VimSOX651TXIhIiIJ4u7c+eWddGnRhRP7nvjLii8fh+abwXZHJq84SZo1tODSkgvpZku5Lic+k5C3yW3DuTucy/sL3mfK4ilxOaaknrQKd8lsu7ry8O342xHbc0i/LjVut3HL3aZ/xMmcxkAklVktR6kVEUlX/1vwP6YuncrvdvodzSLhSNqFK+Dr/8KOJ0FOesy9KfH3hfflrrJjOT7yAUdnfRSXY5623Wm0b96eOybfsclBAiU9pVW4S2a6a5Gbzfn7bLnJ7pGVw11Vo1yKSO1sCHfqlikiGSjqUe6cfCe9Wvfi6K2P/mXFtDFQVgQ7/zp5xUlKuKP0WCZFt2VUzn0ckPVlg4/XIqcFwwcM5/OfPmfioolxqFBSjZJHnFVuqdtUN04RqZ66ZUomMrNDzWyWmc02syuqWL+vmX1pZqVmdkIyapTGMWHuBL5d8S2/H/h7crLCOWvd4YtHYPMdoetOSa1Pkq+MCOcW/5lZ3pN7c27jwKwvGnzME7c9kc1bbs6dk+9U610GSqtwlw6dF6u75i5e1INTmpLubfOAjeeJFElXZhYB7gYOA/oBp5pZv0qb/QicDTzVuNVJYyqNlnL3lLvZpt02HNrn0F9W/PA+/DwddhuevOIkpayiFWcU/5WZvgX/yfk3B2dNatDxciO5/G6n3zFt6TTenf9unKqUVJGUcGdmo8zsGzObamYvmlnbZNSRCDmVw11O/H7E/xuxP5/99aC4HU8k1d18wgDuOHUQfTdvnexSROJlN2C2u89x92LgGeCY2A3cfa67TwU0CUgGG//9eOatmsdFAy8iy2I+K0y8B1p0DK63EwmtoiVnFl/JDO/DPTm3B9dkNsDRWx3NFm224M7JdxJ1/anJJMlquXsT2MHdBwDfAlcmqY64q3yNXctm2dVsWXdbdGhJp9bN4nY8kVTXunkOR+/ULdlliMRTd2B+zPMF4TJpQorLivnPV/9hx4478quev/plxdLZ8O3rsOv5GkhFNhIEvCuY5n3g+bNh5vh6Hys7K5vfD/w9swtm89oPr8WvSEm6pIQ7d3/D3UvDpxOBHsmoIxGyI7/0mzxo+86ct1efJFYjIiKZysyGm9kkM5u0ZMmSZJcjdfDMN8/w09qfuHjQxRVHzJ54D0RyYdfzklecpLTVtODM4iug285BwJsxrt7HGtp7KNu225a7p9xNcVlx3GqU5EqFa+7OBar9yiD2zSsaTf1m49humUO27EDnNvrmTURENsgHesY87xEuqzN3H+3ug919cKdOneJSnCTe4nWLueere9iz254M6TrklxXrlsOUp4LumK06J69ASXlraAG/Hgs9doUx58L0sfU6TpZlcdkulzF/9Xwenv5wnKuUZElYuDOzt8xsehW3Y2K2uQooBZ6s7jixb16RSOoPqpAdM1VClkY/ERGRij4HtjGzPmaWC5wC1L9vlaSdmz67iZKyEq7a/aqKrXZfPAylhbDHhckrTtJHs9ZwxhjouRu8cD5Mebpeh9mr+14cssUhjJ46mh9X/RjnIiUZEhbu3P0gd9+hittLAGZ2NnAkcLpn0DissS13kU3MiSciIk1LeEnCRcAE4GvgOXefYWbXm9nRAGa2q5ktAE4E7jOzGcmrWOLpgwUf8Ma8Nxg+YDi92vT6ZUVpMXx2P2y5P3Tpn7T6JM00aw2nj4Hee8G4C+B/N9dr7qDLd7uc3EguN356o6ZGyADJGi3zUOAvwNHuvi4ZNSRKbLjb1ITnIiLS9Lj7q+6+rbtv5e43hsuudvfx4ePP3b2Hu7d09w7urk/7GaCwtJAbP72RPpv14Zwdzqm4cuY4WL0I9rgoKbVJGmvWCk5/AQacAu/eCOMvgrKSOh2ic4vOXDzoYj5e+DGvz309QYVKY0nWNXd3Aa2BN81sipndm6Q64i52QJWIumWKiIgIMHrqaPLX5PN/Q/6P3EjuLyvc4ZO7oOO2sNWByStQ0ld2Lhx7L+z7F5j8BDx1EqxfVadDnNz3ZPp36M9Nn93EquK67SupJVmjZW7t7j3dfWB4u6A2+6VDVMrJiu2WmcRCREREJCXMXjGbR6Y/wtFbHc2um+9aceW8j2HRVzDkd5ClDw5ST2ZwwFVw9F0w53/w8GGwsvZjNUWyIvzfHv/HiqIV3PHlHQksVBJNf0XiLLblTgOqiIiING1Rj/L3iX+nZW5L/jT4TxtvMPEeyGsfdKsTaaidfw2nPwcr5sIDB8FP02u9a/8O/Tl1u1N5btZzTFsyLXE1SkKlV7hLg6xUoVumrrkTERFp0l6a/RJfLv6Sy3a5jPbN21dcuex7+OYVGHwu5LZIToGSebY+CM55DXB46FD4/p1a73rRwIvolNeJ6ydeT2m0dNM7SMpJq3CXDlGpYrfMdKhYREREEmHF+hXc+sWtDOo8iGFbD9t4g0/vg6xs2O03jV6bZLiuA+D8t6BtL3jyRPjy8Vrt1iq3FZfvdjnfLP+Gp75+KsFFSiKkVbhLB+qWKSIiIgD/mvQv1hSv4eohV5NllT5yFRYEg1/seAK03jwp9UmG26wHnPsa9N4nGEXzresgGt3kbgdvcTD7dN+Hu6bcxU9rf2qEQiWeFO7iTPPciYiIyOc/fc5L37/EWf3PYut2W2+8wZePQslaGKJJyyWBmm8Gpz8PO58JH94KL5wHJetr3MXM+Ovuf8XdGfnZyEYqVOJF4S7OsrPUciciItKUlZSVcMPEG+jeqju/3em3G29QVgKfjg5aVLoOaPwCpWmJ5MBRd8BB18KMsfDY0bB2aY279Gjdg9/u9Fve/vFt3pv/XmNUKXGSVuHO0uCqu9jWOrXciYiIND23f3k7c1bO4a+7/5W87LyNN5j5EqxaAHv8vvGLk6bJDPa+FE58BBZOCUbSXPpdjbuc1f8stm67Ndd9ch1LC2sOg5I60ircpQOz2HCXxEJERESk0b3949s8OvNRTu57Mvv22HfjDcpK4L1/Qse+sM3Qxi9Qmrb+x8LZL0PR6iDgzf2o2k1zsnIYuc9IVhev5or3r6AsWtaIhUp9pVf8SLOGMHXLFBERaTrmr57P/334f/Tv0J+/7PqXqjea9BAsmw0HX69JyyU5eu4WjKTZqjM8dgx89Uy1m/Zt35erdr+KT3/6lHu+uqcRi5T60l+VBMrWH20REZEmoaisiD+99ycwuGW/W8iN5G68UWEBvDcS+uwL26rVTpKofR847w3oNQRe/C28/tegVbkKx25zLMO2HsboqaP5MP/DRi5U6iqt0ke6tYMp24mIiDQNN312E18v/5p/7P0PerTuUfVGH9wChSvgkBuDa6BEkimvHZwxFnb7LUy8Gx4bBmsWV7npX3f/K9u024YrP7hS0yOkuOxkF5DJIvrDLSIikvFenvMyz3/7POfscA7799y/6o2W/xBMWj7wdI2QKQ3W+4pX4ni0/RiWFeGfcx9g5ajd+F3xH5ns22y0leUeTcved3HAY+exbt5w6hoj5o48Ik71Sk3UtpRAGi1TREQks31f8D3Xf3I9O3femT8M+kP1G751LWRlwwF/a7TaRGprXHRvjiu+jiLP4dnc6zkj8ibgFbbx4k6sX3Q8kRY/0qzza8kpVDZJ4S6BshTuREREMta6knVc9t5l5GXnMWq/UWRnVdOS8eOnMHMc7PkHaNO1UWsUqa2vfQuOKr6Bj6I7cEPOw9yScx/NKK6wTenqARQv35PcDh+R3XpakiqVmqRVuEu3Xo7qlikiIpKZ3J3rJ17PDyt/4KZ9b6Jzi87VbQhvXAWtNoe9amjZE0kBq2jFuSUjuL30OE6IvM8LudfSwypeh1f08+GUFfakedcxWI7mv0s1aRXu0o26ZYqIiGSm5799nlfmvMKFAy9kSNch1W84Yyws+DzojpnbsvEKFKknJ4vbSk/g3OI/08sW83ruFZwbeY0I5fPcZVO44DQgi7weT4JVPcqmJIfCXQJpnjsREZHM8/HCjxn52Uj26rYXwwcMr37DkvXBtXZddoCBpzVafSLx8E50Zw4v/iefR/tydc7jvJT7f+xocwDw0nYULjyZSPNFNO/2HKAJzlNFWoW7dItKarkTERHJLJ//9DmXvHMJfTbrw0373kSW1fBR6rP7oOBHOOQGyIo0XpEicbLAO3FOyV+4sPgPdLICxuX+H9dkP0or1lG2ZjvW/3wEOW2m0bzbGCCa7HKFNAt36RbvImn20xUREZHqTVk8hYvevohurbox+uDRbNZss+o3XrsU3r8FthkKW/2q8YoUiTvj1egQDiq6hcfLDuasyBu81WwEh2V9SsnyvSlafAg5m02m2eYvooCXfIofCaRumSIiIplhxtIZ/O6t39ExryP3H3I/HfI61LzDeyOheC0c8vfGKVAkwVbTgmtLz2ZY8fUs9c34T+7tPJhzC92Wb0/R0gPIbfc5zbr8l8pTKEjjUrhLIHXLFBERSX+zls9i+JvD2azZZjw49MHqR8Ys9/NMmPQQ7HI2dOrbKDWKNJapvhXHFP+d60t+zZCsmbyd+2duKfia1st2Irf9JzTr/AoKeMmTVuEu3RrC1HInIiKS3r4v+J7hbw4nLzuPBw55gM1bbl7zDkVr4PmzIa8d7H9lo9Qo0tjKiPBQ2WHsV/Rv7is7il9lTeWjVf9ln4Jm5Hb4kNxObyS7xCYrrcJdulHLnYiISPqat2oe579xPlmWxQOHPECP1j1q3sEd/nsJLPsOTngIWnVqnEJFkmQpm3Fz6SnsVXQHo0pO4rrlP3H8qjU06/gu23Z8ErXgNT6FuwRSuBMREUlPC1Yv4LwJ51EWLeOBQx6g92a9N73T5w/A9DHwq6tgy/0SXqNIqlhFS+4pG8Y+RXfgPx3BgatLWNRpGhd0+ivHZ71PM4qTXWKToXCXQAp3IiIi6Wfakmmc/frZFJYWcv8h97NV2602vdOCSfD6lcHomHtflvgiRVLQeprxaNlhvLLgH2y+enOe7Oj06PI0HzW7CN74Gyyfk+wSM15ahbt0i0oRXXMnIiKSVsZ8O4azXj+LiEV4cOiD9G1fiwFR1i6D586CNl3h2HshK60+XonEXQnN+G7BxRSv2I2H2m7GbzbfnBWf3Qd3DILHj4NvXoGy0mSXmZGyk11AJstSy52IiEhaKCor4p+f/pMXvnuBPbvtyU373ETb5m03vWM0CmN/A2sXw7kToEX7hNcqkh4iFP10HNHCnny3+UucvO0AbttsF/pPHw/PnAZtegQjyg48DTbrnuxiM4bCXQKpW6aIiEhq6n3FKxseW3YBeT2eIJK3gKKlv2LC1wcz4e2PanWcP0TGclnO2/y15DyeunMR8Mom9xFpSkpW7kpZUVd8hzGcufht/u+ofzCsLCe4RvXdG+C9f8BWB8LOv4ZtD4Ps3GSXnNbSq99AmmUldcsUERFJbZEW39Oiz51k5S6hcP6vKV4ylNp+PNonayp/zH6BF8r25qmyAxJbqEgai67vwbNHPsugLoP4v0+u4YaVX1Fy+hi4+EvY+1L4eTo8dybcuj1MuAoWf5PsktNWWoW7jq2aJbuEOlGXexERkVTl5LR/n7xeD+BlLVk79yJK1/Sv9d5dWcbtOXfxrffgbyXnknbfQIs0svbN23PvQfdyzg7n8OysZzl7wtn83LwVHHg1/HE6nPY8bLEHfHov3LM7PHAQTHoYClcku/S0klbxo1Wz9OpFqpY7ERGR1DN35Vzyej5C8y6vUrq6P+vm/h4vrv2cdC1Yzz25t5NDGReWXEIhzRNYrUjmyM7K5rJdLuOW/W7huxXfcdLLJ/Hidy8SzcqCbQ+Bk5+Ay76BQ26A9avg5T/CLdvCs2fA1/+F0qJkv4SUl1bhLl0c0q8LoGvuREREUsma4jX8a9K/OHb8sUTy5rL+p6NYn386RGvfM6gzK3gu93p2tDn8ueS3zPFuCaxYJDMN7T2Up494mp6te3L1x1dz2iunMWXxlGBlq06w58Xw+09h+Huw6/nw46dBwLtlG/jvJTDv42AwI9mIuafPzPGDBw/2SZMmJbuMTSoqLWP52mK6bpaX7FJERNKSmX3h7oOTXUe6SJf3x2SJepTx34/n31/8m2Xrl3Hs1sfy+Kv98LLWdTrONraAR3Jvoi1r+H3JJbwXHZiYgkUy0NyRR2y0zN155YdXuG3SbSwuXMxRWx7FH3f5I51bdK64YVkp/PAeTH0uaMErWQeb9YIdjoP+x0LXnaAJ9Zir6T0yvfo5polm2REFOxERkRQwdclURn42kmlLpzGg0wDuOvAudui4A4/9t26jWu6RNYP7cm5jPbmcVHw1M7xPgioWaTrMjCO3PJIDeh7A/dPu59EZj/LWj28xfMBwzux3JrmRcOTMSDZsfVBwK1oDs16Fqc/Cx3fCR/+Gdn2CkNf/WNh8xyYV9CpTy52IiKQctdzVjd4fN/bjqh+5b+p9jP9+PB3zOnLpLpdy5JZHkmXBFSmxUyFsyrCsD7k55z7m+uacU/wX8qn99XkiUnuWs5RmXV4hp/XXRIs7ULR4KKWr+wORKrdvxyoOiXzBEVkT2TNrBtkWZU50c16JDuHVst352ntR38GOqmppTBVquRMREZGMVxYt48P8D3l61tN8lP8R2VnZnLvDuQwfMJyWOS3rcUTnosg4/pzzPB+X9eOCkktZRX2OIyK14SUdWb/gLEpafkuzLv8lr8dTREs2o2TF7pQU7LpRV+oVtOHZsl/xbNmvaMcqhkYmcUTWRC6MvMTF2eNY4B15p2wQ70QH8Um0H0Vk/hx6CnciIiKS1grWFzB29liem/Uc+Wvy6ZTXid/t9DtO2PaEja/dqaVsSrkh+yFOyX6PsWV7c3nJcEr0sUmkUZSt3ZZ1c/5IdqtvyGn3Cc06v0Fup7cpXbUjxSv2IFq4cYvcCtrwTNkBPFN2AO1ZxSGRSRyYNZkTIu9zZvabFHouH0X78250EO+UDWIRHZLz4hJMf6VEREQk7bg705dO59lZz/L63NcpKitily678Mdd/siBvQ4kJyun3sfeyWbz15yn2D3rG+4sHca/Sk9E89iJNLYIpWv6U7qmP1m5i8lpN5Gczb4gZ7MplK3vSsmKPShZtVOVo90ujwl6zShm96yv+VXWFA7M+pKDciZDDnwT7cmX0W2Y7FvzZXQb5nhXPAMmElC4ExERkbSwrmQdExdN5P0F7/NB/gcsXreYvOw8jtnqGE7e7mS2bbdtg46/vc3jsuwxHBz5gmXemj+X/JYxZfvFqXoRqa9ocWeKfj6aosVDydlsMjntPqF517E02/wlytb2oXTNdpSu2Q4v6bjRvkXk8n50J96P7sR1nMlWtpADsiazT9Y0johM5DR7B4BV3oIp0a2Y7FszObo1rB4MrTqn3eAsCnciIiKSsn5c9SPvL3if9xe8z6SfJ1ESLaFlTkv27LYn+3Tfh4O2OIjWuXWb0qCyrSyfP2a/wFGRiazyFtxSciIPlx3KWjTytUhK8WaUFAyhpGB3InnzyG49k0irb2i++cvAy0SLO2wIemXr+oBXjjrG996d78u6c3/ZkRhRtrRFDMqazSCbzcCs2VyUNY5ItsO/RkFua2jfB9pvCR22Cu7bbwntt0rZ4KdwJyIiIimhYH0BM5fNZObymcH9spnkr8kHoM9mfThtu9PYp8c+7Nx5Z3Ii9e92Wa6HLeaSyFiOi3zAenK5s3QY95cezipaNfjYIpJIRllhb8oKe8Piw7Gc5WS3mhVco9f2U3Lbf4RHcykr7E50fTfK1vcgur470eKOENP10snaEPbGELTSt2A9A7Lm8MwxbWD5HFj2Pfw0Db55GaKlv5QQaQZtukGb7uF9FY9bdoKsxu3qqXAnIiIimxYtg3XLYM3P4W1JcL9uGXi0+v2ysoMPOK26QKvgfk1uS/JL17Jg7UK+X/k9M5fN5OtlX7Nw7cINu/Vo1YN+Hfrx636/Zt8e+9Kzdc+Gv4ayUvjpK5j3MffnvMh+WVNwsnio7DD+U3o0y2nT8HOISKPzkvbBNXgr9gArJtJyDtktvyXSfAE57T4jN+ujYLtoLmXruxJd352y9d3w4vZES9rjpW0oD33raM7EaD/YvdJUCGUlsHJ+GPjmBI9XLQxu8z8N7qMlFffJyobWXYOw17prTPjrCi07B61/LTtB87ZxC4EKdyIiIo3IzA4FbieYuOkBdx9ZaX0z4DFgF2AZcLK7z01oUdEorF0SfFhZOR8K5sPKBb88X/0zrFtadYiLNIOwFc2B1WasyDJWRLJYnmUsJcqCiJGfHSE/J5sF2dmsjFScs2oLy2Wn3A6c0mE3+rXfju06D2KzjtsGH4Ya0kJXsh7yv4B5H8OPH8P8z6B4DQBbWxeeLDuIe0uP4mfa1/8cIpJaPJeyNdtRtma7cEEZWc2WkNU8n0jzfLKa55PTdhK5WcW/7BKN4CXtiJa0C8JecXtenWO0z2tPu2btaN+8PW2btyWnvFvm1lWcNxoNvuxalR/eFv5yW70Qfp4O370BJes23jcrG1p0DL4Aa9kZ8tpBTnPIzqv6vgYKdyIiIo3EzCLA3cDBwALgczMb7+4zYzY7D1jh7lub2SnATcDJtTqBO5Suh+J1ULI2vF8HRauD8LZ2Cb5mMaVrfqZ07VJK1y2hbN1SStYsociLKTajKLwV57aiqFUnilq2Z12HbqzNbcHanGaszc5mbVaEtQZribKmbD0F6wv4evEiLHstZmUb1xWNECltTfPiFrQpzKVnSRZdS6P0Kimhb+latvTldLWptLFPK+xW5sYqWrLa81hNi+DmLVhFHms8j7Xk0ZxiWlFIa1u34b41hbS2Qtqymtywnq+jPfksugefR7fjs+h2LKZdnf/9RCQdRYgWbU60aHNKV+4SLotiOcvJyl1OVs6KCo+zm08jK3sdl3/w2kZH8rLmeGkromUtoSwPjzbDo80gvN/wuKwZ7jngm0G0A+6DwHPwaIRWXkIn1tCRNXTwNXSy1XRiFZ2KV9Nx5Uo62lw2YzrNrYTmFNOcYvKseKNaqqNwJyIi0nh2A2a7+xwAM3sGOAaIDXfHANeGj8cAd5mZubtXd9Dvls7g0Af7EcUpA6IYUYMoUBY+LgVKzSiLHQAgN7y17VTNkQshmg/r8iH8sjliEVrktKBlTkta5bSiRU4LNm+5OdPWtsZLW+Jl4a20VXjfGi9tTXmXp59q+OG0Yh1dbTndbBldw1s71mwIbm1sHd1tKduxjtZZ62jJegrJZU0Y9lbTgpXeigV0ZnU0jxW05svoNnwe7ctKXUcnIhtk4SUdKSvpSBVfR0HWerKyVwZfWEXCW/aa8H4tFlmD5awkK6sYsoqwrCIsq6SqI1VpSXiL5W7gWUAkCIWehWNAsNwAc8Mw4MNqj51W4e6LL75YambzatikI7C0seqJo3StG1R7Mqn+5EnH2tOt5i2SXUCCdAfmxzxfAOxe3TbuXmpmK4EOVPr3M7PhwPDw6ZoJ5389KyEVJ06V/ydnJKGQBki336vK0r1+SP/XkO71Q/q/hnSsv9r3yLQKd+5e3VeLAJjZJHcf3Fj1xEu61g2qPZlUf/KkY+3pWLPUzN1HA6OTXUd9ZcL/yXR/DeleP6T/a0j3+iH9X0O6119Z+k/DLiIikj7ygdhhH3uEy6rcxsyygc0IBlYRERGpkcKdiIhI4/kc2MbM+phZLnAKML7SNuOBs8LHJwDv1HS9nYiISLm06pZZC+naPSVd6wbVnkyqP3nSsfZ0rDnjhNfQXQRMIJgK4SF3n2Fm1wOT3H088CDwuJnNBpYTBMBMlAn/J9P9NaR7/ZD+ryHd64f0fw3pXn8Fpi8DRURERERE0p+6ZYqIiIiIiGQAhTsREREREZEMkNRwZ2Y9zexdM5tpZjPM7JJweXsze9PMvgvv24XLzczuMLPZZjbVzHaOOdbN4TG+Drexas55Zbj/LDMbGrP8ITNbbGbT06VuM2tuZp+Z2VfhMa5Ll9rD5XPNbJqZTTGzSelSu5n1DWsuv60ysz+mS/3h8kvMbHp4jE3Wnoz6zaxDeL41ZnZXpXU3mtl8M1uThNpvCn92083s5BrOeVZ43O/M7KyY5bWqPcVqft1++Ttzr5lFaqpdpLbM7O/h/9cpZvaGmXVLdk11YWajzOyb8DW8aGZtk11TXZnZieHvdtTM0mY4eDM7NHxvm21mVyS7nrqyOnzuTEXVvUelE6vH5+i04O5JuwFdgZ3Dx62Bb4F+wM3AFeHyK4CbwseHA68BBgwBPg2X7wl8RHBxegT4BNi/ivP1A74CmgF9gO+BSLhuX2BnYHq61B0er1W4TQ7wKTAkHWoP180FOqbj/5eYbSLAT8AW6VI/sAMwHWhBMKjSW8DWKVh/S2Bv4ALgrkrrhoT1rGnk/ztHAG+GP7eWBCMftqnifO2BOeF9u/Bxu7rUnmI1twnvDXgBOKW2v7e66VbTLfb/IvAH4N5k11TH+g8BssPHN5X/PqbTDdge6Au8BwxOdj21rDlC8J62JZBL8F7XL9l11fE11PpzZyreqnuPSnZddXwNdf4cnQ63pLbcufsid/8yfLwa+BroDhwDPBpu9igwLHx8DPCYByYCbc2sK+BAc4Jf8GYE/0A/V3HKY4Bn3L3I3X8AZgO7hed/n2BUsrSpOzxe+bf/OeGtxhFyUqX2mmpMs9oPBL5393lpVP/2BB/817l7KfA/4LhUq9/d17r7h8D6KtZNdPdFm6o5AbX3A95391J3XwtMBQ6t4pRDgTfdfbm7ryAIV4fWpfYUq3lVuE02wb+bRuKSuIj5vwXBlw9p9X/L3d8I/44CTCSYtzCtuPvX7j4r2XXU0W7AbHef4+7FwDMEfwPTRl0+d6aiGt6j0kZ9Pkeng5S55s7MegODCFJzl5gPPz8BXcLH3YH5MbstALq7+yfAu8Ci8DbB3b+u4jRV7p/OdZtZxMymAIsJPph9mi61E/wCvWFmX5jZ8NrWnSK1lzsFeLoutadA/dOBfcJujy0IWnx6VrF/sutPiIbUTvDt8KFm1sLMOgK/ouqfXVz/1qRCzWY2geDvzGpgTH1fi0hl5V2VgdOBq5NdTwOcS9B6LokX989zUn+V3qPSSkM+R6eqlAh3ZtaKoKvPHyt9i4e7O5tI0Wa2NUFrRA+CX+4DzGyfBJUbe96k1+3uZe4+MDzGbma2Q7rUDuzt7jsDhwG/N7N906h2LJiA+Gjg+Trul9T6wyB1E/AG8DowBShLl/oboqG1u/sbwKvAxwSh/hPq8LOrj1Sp2d2HEnTDaQYcUNf9pekys7dirvmMvR0D4O5XuXtP4EngouRWu7FN1R9ucxVQSvAaUk5tXoNIfdT0HpUO6vs5OpUlPdyZWQ7Bf4on3X1suPjnsDsR4f3icHk+Fb9x7hEuOxaY6O5rwubV14A9zOxY+2XQi8E17J/2dbt7AUFrSFXdrVKydncvv18MvEgtumumSu2hw4Av3b2qLpEpXb+7P+juu7j7vsAKgr7yqVZ/XMWpdtz9Rncf6O4HE/TX/9bMdo+p/eia9k/nmt19PfASadb9SZLL3Q9y9x2quL1UadMngeOTUWNNNlW/mZ0NHAmcHn7hknLq8G+QLuL2eU7qr5r3qLRUl8/RqS7Zo2Ua8CDwtbvfGrNqPHBW+Pgsgg8T5cvPtMAQYGXYPelHYD8zyw7/o+0XHvPF8APNQHefFO5/ipk1M7M+wDbAZ+lat5l1snBkLjPLAw4GvkmT2luaWeuwppYEF6XXOGJUqtQec95TqUOXzFSq38w6h/e9CK63eyoF64+beNVuQfeNDuExBwADgDfc/dOY2scDE4BDzKydBaNZHhIuS7uazaxVTJjMJhigpca/MyK1ZWbbxDw9hjT7v2VmhwJ/AY5293XJrqcJ+RzYxsz6WNCL5hSCv4HSSGp4j0ob9fkcnRY8uaPU7E3QpWgqQdewKQTX/3QA3ga+IxjJr73/MqrN3QQjJE0jHNWJYNSk+wgu5pwJ3FrDOa8K958FHBaz/GmC639KCPpun5fqdRN8SJsc1jEduDpdfuYEI1x9Fd5mAFelS+3h8pbAMmCzNP3//kG471fAgSlc/1yCC87XEPxe9guX3xw+j4b31zZS7c3DmmcSDJ4wsIZznkswiM1s4JyY5bWqPVVqJrim73N++TtzJ+HogLrp1tAbwbf+08P/X/8luC436XXVof7ZBNd+lf+OptVon+FrODb8W1REMLjVhGTXVMu6DyfodfI9tfgMkWo36vC5MxVv1b1HJbuuOr6GOn+OToebhS9ORERERERE0ljSr7kTERERERGRhlO4ExERERERyQAKdyIiIiIiIhlA4U5ERERERCQDKNyJiIiIiIhkAIU7ERERERGRDKBwJyIiIiIikgEU7kRERERERDKAwp2IiIiIiEgGULgTERERERHJAAp3IiIiIiIiGUDhTkREREREJAMo3ImIiIiIiGQAhTsREREREZEMoHAnIiIiIiKSARTuREREREREMoDCnYiIiIiISAZQuBMREREREckACnciIiIiIiIZQOFOREREREQkAyjciYiIiIiIZACFOxERERERkQygcCciIiIiIpIBFO5EREREREQygMKdiIiIiIhIBlC4ExERERERyQAKdyIiIiIiIhlA4U5EREREUp6ZnW1mHya7DpFUpnAnkobM7D0zOz/ZdYiISNNjZqeZ2SQzW2Nmi8zsNTPbO9l1iYjCnUiVzGyumS02s5Yxy843s/eSWFatmVk/MxtvZivNbLWZvWNmQ2q579lmNs3M1pnZT2Z2j5ltluiaRUQk9ZnZZcC/gX8AXYBewD3AMXU8TnZtljWGZJ1XJBEU7kSqFwEuaehBLNBov2tmthXwETAN6AN0A8YBb5rZbpvY90/ATcAIYDNgCNAbeMPMchJXtYiIpLrwi77rgd+7+1h3X+vuJe7+X3cfYWbNzOzfZrYwvP3bzJqF++5vZgvM7HIz+wl42MyuNbMxZvaEma0CzjazzczswbBFMN/MbjCzSDX17Glmn4dfZH5uZnvGrOtjZu+HX3C+ZWZ3m9kT4breZuZmdp6Z/Qi8Ey5/PvxSc2W4b/+Y4z0Sftn5Wthi+ZGZbR6+xhVm9o2ZDUrYD1+klhTuRKo3CvizmbWtauUm3lTeM7MbzewjYB2wZfhGcqGZfRe+2fzdzLYys4/NbJWZPWdmueH+7czsZTNbEr5pvGxmPWpZ97XAJ+5+lbsvd/fV7n4H8ARBcKuSmbUBrgMudvfXwzfsucBJwJbAabU8v4iIZKY9gObAi9Wsv4rgS8GBwE7AbsDfYtZvDrQHtgCGh8uOAcYAbYEngUeAUmBrYBBwCLDRZQhm1h54BbgD6ADcCrxiZh3CTZ4CPgvXXQv8uop69wO2B4aGz18DtgE6A1+G9cQ6KXw9HYEi4JNwu47ha7i1inOINCqFO5HqTQLeA/5ceUUt3lQgeCMZDrQG5oXLhgK7ELz5/QUYDZwB9AR2AE4Nt8sCHiZ4A+wFFAJ31bLug4Hnq1j+HLCPmTWvZr89Cd60x8YudPc1wKsEb7AiItJ0dQCWuntpNetPB65398XuvoTgC8PYUBUFrnH3IncvDJd94u7j3D0KtAEOB/4YtgouBm4DTqniXEcA37n74+5e6u5PA98AR5lZL2BX4Gp3L3b3D4HxVRzj2vA8hQDu/lD4hWgRQSDcqdJlCS+6+xfuvp4g4K5398fcvQx4liCMiiSVwp1Iza4GLjazTpWWV/umErPNI+4+I1xfEi672d1XufsMYDrwhrvPcfeVBN8YDgJw92Xu/oK7r3P31cCNBN8w1kZHYFEVyxcRdDVtX8N+1b1pLwIq/wxERKRpWQZ0rOEatW788mUm4eNuMc+XhMEo1vyYx1sAOcAiMyswswLgPoKWtE2dq/x83cN1y919XTXn2WiZmUXMbKSZfR92EZ0bruoYs/3PMY8Lq3jeqopziDQqhTuRGrj7dOBl4IpKq2p6UylX1RtJrd4YzKyFmd1nZvPCN5n3gbbVXXdQyVKgaxXLuwIOLDOzfcJrBtaY2YyY/ap70+4arhcRkabrE4LuiMOqWb+QIKCV6xUuK+dV7BO7bH54/I7u3ja8tXH3/lXsV/lc5efLJ/hCsr2ZtYhZ13MT5z6NoIvoQQTXnPcOl1sV+4mkLIU7kU27BvgNFYNbTW8q5ap6E6utPwF9gd3dvQ2wb7i8Nm8ybwEnVrH8JGBi2B3mA3dvFd7K3zTL37SPi93JzFoBhxF0URURkSYq7GVyNXC3mQ0Lv4jMMbPDzOxm4Gngb2bWycw6hts+UYfjLwLeAP5lZm3MLCu8Nr2qniuvAttaMC1DtpmdDPQDXnb3eQSXVlxrZrlmtgcVe9ZUpTXBe+AyoAXBaKAiaUfhTmQT3H02QV/6P8QsrvZNJU6nbU3QklcQXt93TR32vQ7YMxzQpb2ZtTazi4FzCN5oqxS+aV8H3Glmh4Zv2L0JrtVbysYXlouISBPj7v8CLiMYWGQJQWvbRQSjMt9AEKqmEozY/GW4rC7OBHKBmcAKgoFKNuqN4u7LgCMJvgxdRnAd+5HuXt7L5HSCAWCWhTU8SxDeqvMYQQ+c/PDcE+tYt0hKMPeGNC6IZCYzmwuc7+5vhc97At8RtHztHy7bG7idYESv2cAl4UXbWDAf3hPu/kDMMR3YJgyLmNmHwAPu/kj4/AZgc3c/38y6EYz0NZiglfBfwL1AjruXVnX8SvXvAIwkaPFrCawGTnX312rx2s8DLg1fVzPgf8Bp7r6wxh1FRERSlJk9C3zj7nX5slQk7SjciWS4cAqFiQQjlD1Yx33PIZjTaC93/zER9YmIiMSbme0KLAd+IBjteRywh7tPTmZdIommbpkiGc7dFxBcM9c1vH6uLvs+DPyVYJoEEaklM3vIzBab2fRq1puZ3WFms81sqpntHLPurHA+zO/M7KzGq1oko2xOcK34GoJpi36nYCdNgVruRERE4szM9iX4UPmYu+9QxfrDgYsJ5vTaHbjd3XcPr7GdRNAl24EvgF3cfUWjFS8iImlLLXciIiJx5u7vE3QJq84xBMHP3X0iwVQnXYGhwJvuvjwMdG8Chya+YhERyQTVTUKZkjp27Oi9e/dOdhkiIpJgX3zxxVJ375TsOhKoOxXnwlwQLqtu+UbMbDgwHKBly5a7bLfddvUqZPHqIn5eVXleaejSpjmdWzer1zFFRCRxanqPTKtw17t3byZNmpTsMkREJMHMbF6ya0h17j4aGA0wePBgr+/749tf/8zFT09mXXHZhmUtciPceeogDty+S1xqFRGR+KnpPVLdMkVERBpfPtAz5nmPcFl1yxNm/76dGdizLVkWPG+RG2Fgz7bs37dzIk8rIiIJoHAnIiLS+MYDZ4ajZg4BVrr7ImACcIiZtTOzdgRDuE9IZCGRLOPx83Zn686t6NE2jztPHcTj5+1OpDztiYhI2kirbpkiIiLpwMyeBvYHOprZAuAaIAfA3e8FXiUYKXM2sA44J1y33Mz+DnweHup6d69pYJa4iGQZ7Vrk0q4F6oopIpLGFO5ERETizN1P3cR6B35fzbqHgIcSUZeIiGS2pHbLNLO2ZjbGzL4xs6/NbI9k1iMiIiIiIpKukt1ydzvwurufYGa5QIsk1yMiIiIiIpKWkhbuzGwzYF/gbAB3LwaKk1WPiIiIiIhIOktmt8w+wBLgYTObbGYPmFnLyhuZ2XAzm2Rmk5YsWdL4VYqIiIiIiKSBZIa7bGBn4D/uPghYC1xReSN3H+3ug919cKdOVU7ELiIiIiIi0uQl85q7BcACd/80fD6GKsKdiIhklnGT8xk1YRYLCwrp1jaPEUP7MmxQ92SXJSIikvaS1nLn7j8B882sb7joQGBmsuoREZHEGzc5nyvHTiO/oBAH8gsKuXLsNMZNzk92aSIiImkvqVMhABcDT5rZVGAg8I/kliMiIok0asIsCkvKKiwrLClj1IRZSapIREQkcyR1KgR3nwIMTmYNIiLSeBYWFNZpuYiIiNReslvuRESkCenWNq9Oy0VERKT2FO5ERKTRjBjal7ycSIVleTkRRgztW80eIiIiUltJ7ZYpIiJNS/momBotU0REJP4U7kREpFENG9RdYU5ERCQB1C1TREREREQkAyjciYiIiIiIZACFOxERERERkQygcCciIiIiIpIBFO5EREREREQygMKdiIiIiIhIBlC4ExERERERyQAKdyIiIiIiIhlA4U5ERERERCQDKNyJiIiIiIhkAIU7ERERERGRDKBwJyIiIiIikgEU7kRERERERDKAwp2IiIiIiEgGULgTERERERHJAAp3IiIiCWBmh5rZLDObbWZXVLH+NjObEt6+NbOCmHVlMevGN2rhIiKStrKTXYCIiEimMbMIcDdwMLAA+NzMxrv7zPJt3P3SmO0vBgbFHKLQ3Qc2UrkiIpIh1HInIiISf7sBs919jrsXA88Ax9Sw/anA041SmYiIZCy13ImISL2Mm5zPqAmzWFhQSLe2eYwY2pdhg7onu6xU0R2YH/N8AbB7VRua2RZAH+CdmMXNzWwSUAqMdPdxVew3HBgO0KtXr/hULSIiaU3hTkRE6mzc5HyuHDuNwpIyAPILCrly7DQABby6OwUY4+5lMcu2cPd8M9sSeMfMprn797E7uftoYDTA4MGDvfHKFRGRVKVumSIiUmejJszaEOzKFZaUMWrCrCRVlHLygZ4xz3uEy6pyCpW6ZLp7fng/B3iPitfjiYiIVEnhTkRE6mxhQWGdljdBnwPbmFkfM8slCHAbjXppZtsB7YBPYpa1M7Nm4eOOwF7AzMr7ioiIVKZwJyIiddatbV6dljc17l4KXARMAL4GnnP3GWZ2vZkdHbPpKcAz7h7brXJ7YJKZfQW8S3DNncKdiIhskq65ExGRjWxqsJQRQ/tWuOYOIC8nwoihfZNRbkpy91eBVystu7rS82ur2O9jYMeEFiciIhlJ4U5ERCqozWAp5fcaLVNERCR1KNyJiEgFNQ2WEhvehg3qrjAnIiKSQnTNnYiIVKDBUkRERNKTwp2IiFSgwVJERETSk8KdiIhUMGJoX/JyIhWWabAUERGR1Kdr7kREpAINliIiIpKeFO5ERGQjGixFREQk/ahbpoiIiIiISAZQuBMREREREckACnciIiIiIiIZQOFOREREREQkAyjciYiIiIiIZACFOxERERERkQygcCciIiIiIpIBFO5EREREREQygMKdiIiIiIhIBlC4ExERERERyQDZyS5ARESSY9zkfEZNmMXCgkK6tc1jxNC+DBvUPdlliYiISD0p3ImINEHjJudz5dhpFJaUAZBfUMiVY6cBKOCJiIikKXXLFBFpgkZNmLUh2JUrLClj1IRZSapIREREGkrhTkSkCVpYUFin5SIiIpL6FO5ERJqgbm3z6rRcREREUl/Sw52ZRcxsspm9nOxaRESaihFD+5KXE6mwLC8nwoihfZNUkYiIiDRUKgyocgnwNdAm2YWIiDQV5YOmaLRMERGRzJHUcGdmPYAjgBuBy5JZi4hIUzNsUHeFORERkQyS7G6Z/wb+AkSr28DMhpvZJDObtGTJkkYrTEREREREJJ0kLdyZ2ZHAYnf/oqbt3H20uw9298GdOnVqpOpERERERETSSzJb7vYCjjazucAzwAFm9kQS6xEREREREUlbSQt37n6lu/dw997AKcA77n5GsuoRERGJJzM71MxmmdlsM7uiivVnm9kSM5sS3s6PWXeWmX0X3s5q3MpFRCRdpcJomSIiIhnFzCLA3cDBwALgczMb7+4zK236rLtfVGnf9sA1wGDAgS/CfVc0QukiIpLGkj2gCgDu/p67H5nsOkREROJkN2C2u89x92KCyw+OqeW+Q4E33X15GOjeBA5NUJ0iIpJBUiLciYiIZJjuwPyY5wvCZZUdb2ZTzWyMmfWsy74aTVpERCpTuBMREUmO/wK93X0AQevco3XZWaNJi4hIZQp3IiIi8ZcP9Ix53iNctoG7L3P3ovDpA8Autd1XRESkKgp3IiIi8fc5sI2Z9TGzXIJRocfHbmBmXWOeHg18HT6eABxiZu3MrB1wSLhMRESkRhotU0REJM7cvdTMLiIIZRHgIXefYWbXA5PcfTzwBzM7GigFlgNnh/suN7O/EwREgOvdfXmjvwgREUk7CnciIiIJ4O6vAq9WWnZ1zOMrgSur2fch4KGEFigiIhlH4U5EpAkYNzmfURNmsbCgkG5t8xgxtC/DBlU1eKOIiIikK4U7EZEMN25yPleOnUZhSRkA+QWFXDl2GoACnoiISAbRgCoiIhlu1IRZG4JducKSMkZNmJWkikRERCQRFO5ERDLcwoLCOi0XERGR9KRumSIiGa5b2zzyqwhy3drmJaEaERGpjbKo896sxcxYuIr+3dqwf9/ORLIs2WVJilO4ExHJcCOG9q1wzR1AXk6EEUP7JrEqERGpTlnU+fWDnzJlfgGFxWXk5UYY2LMtj5+3uwKe1EjhTkQkA1UeHfP4Xbrz7jdLNFqmiEgaeG/WYqbML2BdcfCl3LriMqbML+C9WYs5cPsuSa5OUpnCnYhIhqlqdMwXvsjnn8ftqEAnIpIGZixcRWFxpYGwisuYuXCVwp3USAOqiIhkGI2OKSKS3vp3a0NebqTCsrzcCP26tUlSRZIuFO5ERDKMRscUEUlv+/ftzMCebSm/vK5FeM3d/n07J7cwSXkKdyIiGaa6UTA1OqaISHqIZBmPn7c7W3duRY+2edx56iANpiK1onAnIpJhRgztS15Ope48Gh1TRCStRLKMdi1y6d4ujwO376JgJ7WiAVVERDJM+aApsaNlanRMERGRzKdwJyKSgYYN6q4wJ1JHmjRaRNKdwp2IiIg0eZo0WkQyga65ExERkSYvdtJop+Kk0SIi6UItdyIiGWDc5HxdYyfSAJo0WkQygcKdiEiaGzc5nyvHTtswcXl+QSFXjp0GoIAnUkvlk0aviwl4mjRaRNKNumWKiKS5URNmbQh25QpLyhg1YVaSKhJJP5o0WkQygcKdiEiaW1hQWKflIrIxTRotIplA3TJFRNJQ7DV2WWaUuW+0Tbe2eUmoTCR9lU8a3a4Fus5ORNKSWu5ERNJM+TV2+QWFOFQZ7PJyIowY2rfxi6uN+fPh0kvhzDOTXYmIiEhGUbgTEUkzVV1jBxAxw4DubfP453E7pt5gKjNnwtlnw5Zbwp13ghmUbfw6REREpH7ULVNEJM1Udy1d1J0fRh7RyNXUwscfw8iR8N//Ql4eXHghXHYZbLFFsisTERHJKGq5ExFJM9VdS5dS19i5wyuvwD77wF57wUcfwTXXwI8/wu23K9iJiIgkgFruRETSRPkgKvkFhRgQe6VdylxjV1ICzzwDN98M06dDz55BmDvvPGjZMtnViYiIZLRNhjsz2wpY4O5FZrY/MAB4zN0LEluaiIhAEOquHT+DgsKSDcscNgS87m3zGDG0b3KvsVu7Fh58EP71r6B1rn9/eOwxOOUUyMlJXl0iIvVQFnXem7WYGQtX0b9bG/bv21nTYkhaqE3L3QvAYDPbGhgNvAQ8BRyeyMJEROSXkTGrGkClPNh9dMUBjV9YuaVL4a67gtuyZbD33nD33XD44ZClnv8i6aipB5uyqPPrBz9lyvwCCovLyAsntNe8h5IOahPuou5eambHAne6+51mNjnRhYmINEWxXS8j1cxfFytpE5XPmwe33goPPADr1sFRR8HllwfX1wkAZnYocDsQAR5w95GV1l8GnA+UAkuAc919XriuDJgWbvqjux/daIVLk6ZgA+/NWsyU+QWsKw6+VFtXXMaU+QW8N2ux5j+UlFebr1VLzOxU4Czg5XCZ+tiIiMRZ7Px1UPX8dZU1+iAq06cH89NttRXccw+ccEKwbPx4BbsYZhYB7gYOA/oBp5pZv0qbTQYGu/sAYAxwc8y6QncfGN4U7KTRxAYbp2KwaSpmLFxFYXHF3hKFxWXMXLgqSRWJ1F5twt05wB7Aje7+g5n1AR5PbFkiIk1PdfPXVadRB1H58MOgdW7HHWHsWLj4Yvj+e3j00eD6OqlsN2C2u89x92LgGeCY2A3c/V13Xxc+nQj0aOQaRTaiYAP9u7UhLzdSYVleboR+3dokqSKR2ttkuHP3mcDlwJfh8x/c/aZEFyYi0tTUpYtluxY5iZ+oPBoN5qbba69gSoNPPoHrrgu6ZN52G/Tqlbhzp7/uwPyY5wvCZdU5D3gt5nlzM5tkZhPNbFhVO5jZ8HCbSUuWLGlwwSKgYAOwf9/ODOzZlvJeqC3Crqn79+2c3MJEaqE2o2UeBdwC5AJ9zGwgcL26iYiIxFe3tnkbumRWp1FGxiwpgaeeCqYzmDkzmJPuzjvh3HOhRYvEnbeJMrMzgMHAfjGLt3D3fDPbEnjHzKa5+/ex+7n7aIKBzhg8ePCm+/CK1EJ5sJk4ZxlRb5rBJpJlPH7e7hx2+/usKyrjumP6N7lBZco19cF10lFtBlS5lqB7yXsA7j4lfLMREZE4GjG0b7UjY+blRBLfUrdmTTBAyq23wvz5QRfMJ56Ak07SdAZ1lw/0jHneI1xWgZkdBFwF7OfuReXL3T0/vJ9jZu8Bg4DvK+8vEm8KNoFIltGuRS7tWtBkB1HR4DrpqVYDqrj7ykrLookoRkSkKRs2qDv/PG5HuoeDpEQsePPs3jYvscFuyRK4+uqgm+Wll0KfPvDKK/DVV3D66Qp29fM5sI2Z9TGzXOAUYHzsBmY2CLgPONrdF8csb2dmzcLHHYG9gJmNVrk0eeXBpnu7PA7cvos+yDdRGlwnPdWm5W6GmZ0GRMxsG+APwMeJLUtEpOkon/5gYUEh3RpzQvK5c4NJxx98EAoL4ZhjgukM9tgj8efOcOEUQhcBEwimQnjI3WeY2fXAJHcfD4wCWgHPWxDky6c82B64z8yiBF/Cjgyvf89o6v4lklpqGlynqbZmpoPahLuLCbqMFAFPE7xR/T2RRYmIZLpxk/O5dvwMCgpLKizPLyjkyrHB9GYJC3hTpwbX0z3zTDDR+Omnw4gR0K/ySP3SEO7+KvBqpWVXxzw+qJr9PgZ2TGx1qUXdv0RST/ngOutiAl5TG1wnHdVmtMx17n6Vu+/q7oPDx+sbozgRkUw0bnI+I57/aqNgV66wpIxRE2bF96Tu8P77cMQRsNNOMG4cXHIJzJkDDz+sYCdJpe5fIqlHo4amp2pb7szsv0C1o29ptEwRkfoZNWEWJdGaBzesy7QINSqfzmDkSJg4ETp1gr//HS68ENq3j885RBpI3b9EUo8G10lPNXXLvKXRqhARaUJqE9y6hYOq1FtxMTz5JIwaBV9/Db17w113wTnnaDoDSTnq/iWSmjRqaPqpNty5+/8asxARkaZg3OR8sswo8+pb7vJyIowY2rd+J1i9Gu6/P5jOID8fBgwI5qw78UTIrs1l1iKNT3OriYjER03dMp9z95PMbBpVdM909wEJrUxEJAOUj4SZX1CIUUNf91C7Fjlcc1T/ug+msnhxMNH4XXdBQQHsv38wZ93QoWDqQiOpTd2/fqFRQ0WkIWr6GveS8P7IxihERCRTxAa6WDUFu3qHuh9+gFtugYcegqIiGDYsmM5g993rXLdIMqn7l0YNFZGGq6lb5qLw4YXufnnsOjO7Cbh8471ERJq2v42bxpMTf9xkC10sAyZffUjdTvTVV3DTTfDcc8F0BmeeGUxn0Lee3TlFJOliRw2FiqOGNtXAKyJ1s8mpEICDq1h2WENPbGY9zexdM5tpZjPM7JJN7yUikrrGTc6vc7CDOgye4g7vvQeHHQYDBwajYF56adB698ADCnYiaa6mUUNFRGqjpmvufgdcCGxpZlNjVrUGPorDuUuBP7n7l2bWGvjCzN5095lxOLaISKMbNWFWnYNdrQZPiUbhpZeC6Qw++ww6d4Ybb4Tf/Q7atat3vSKSWjRqaEDXHYrUX03X3D0FvAb8E7giZvlqd1/e0BOH3T4XhY9Xm9nXQHdA4U5E0lJd56bb5HV2RUXwxBPBdAazZsGWW8I998DZZ0NeA6dKEJGUo1FDdd2hSEPVdM3dSmAlcKqZRYAu4fatzKyVu/8YryLMrDcwCPg0XscUEWks4ybnc+34GbVuteveNo8RQ/tWH+pWrYLRo+G222DhwqAL5jPPwPHHazoDkQymUUN13aFIQ23yU4KZXQRcC/wMRMPFDsRlKgQzawW8APzR3TfqVG5mw4HhAL169YrHKUVE4mbc5HxGPP8VJdGao90mAx3Azz/DHXfA3XfDypVwwAHw8MNw8MGazkCkiWjqo4bWdN1hU/x5iNRVbb4C/iPQ192XxfvkZpZDEOyedPexVW3j7qOB0QCDBw+u6+UsIiIJNWrCrGqDXcSMf52006anN5gz55fpDIqL4bjjgukMdt01ARWLiKQuXXeYGtydsqhT5k7UHQdWry/BCcb2Ku+q4jjuhMt9w3onWFjh+YbH4bblx/Dqj7PhLF71dEJey2TgtehbU+tj1WK76s7XpnkOPdu3qN2J6qk24W4+QffMuDIzAx4Evnb3W+N9fBGRxlDTdXZR95qD3eTJwXQGzz8fdLcsn85g220TUKmISOrTdYf1Ew2DWFk0CGNlUScahdJoNAhoUcL7X0JbWfSXWzRm39IyJ/Y7yzVFpQBMz2+6o7ZGo86U+QXMXbaW3h1aMrBnW7Lq0V06N1KbiQoapjbhbg7wnpm9AhSVL4xDINsL+DUwzcymhMv+6u6vNvC4IiKNplvbvI0mK49dtxF3ePfdINS98Qa0bg1//jNccgl065bgakVEUlu6XXcYjQZtNFH3ii1QzoYWL/cwLMUs29T25cvWlwQtmLMXr9koiJWHtdKo17rVKR3FK1g15Pz/eO1rZi9eQ3FplNzsLLbu3Iq/HrZ9o9ZRW7UJdz+Gt9zwFhfu/iHB3L0iImnrV9t14omJG48vlROxilMclJXBuHHBdAaTJkGXLvDPf8IFF0Dbto1Wr4hIfZWHlA33McHEqbiOKpZVt31V4aZ5ToTmORF6tW/BnCVrgvNvqCOmppjuflRaH9s1rqrws6njlLdYffnjirDGX7oLloezRCsuC4a7WLK6aBNbZqZUCFZT5hcwe/EaikqDf4ui0iizF69hyvwCdt4i9aYj2mS4c/frGqMQEZF0UT46ZkFhSZXrW+ZGuPHYHYMumUVF8NhjwXQG330HW20F994LZ50FzZs3cuUikgzVtbj88viXLnNR9wqtNYGY65PKl/jGgaSqZdS0PUFgqXxccNYUleIOn/2w/JfA1ohKwlCzdE1x4544RjT82RSVRDexpSRKKgSrucvWUlxa8f9AcWmUucvWpme4M7NOwF+A/sCGTyLufkAC6xIRSTnjJudz5dipFG7ijb5ti1yGbdUabr4Z/v1vWLQIdt4ZnnsuGCwlEmmcgkWkShUGc+CXFplgXRCC1haVUuaOh8GrQjirdI1SWZSNwpvHLK+rVGitKQ829alfJF5SIVj17tCS3OysDQETIDc7i94dWjbK+euqNt0ynwSeBY4ELgDOApYksigRkVRS21AH0GnNCk7/3yMw8s1gOoODDgpa7g48UNMZSMb7edX6DcPYVxWaiGk5ih0Nr7y7XvkIiTMWrqy2m13sqHlVHb9iaKu4XW260a0uClrkpy6I+1hyIlJHqRCsBvZsy9adWzFz0SrcoVnYNXRgz7aNVkNd1CbcdXD3B83sEnf/H/A/M/s80YWJiKSCv42bVuU1dZVtsWIhwz8bywnT3iYnWgonnBBMZ7DLLo1QpUhqWLqmiFWFpfXevzQafIBryDFEJHOkQrDKyjL+etj2XD52KkUlZZy9Z59GH9SlLmoT7sovKllkZkcAC4H2iStJRCT5attat8NPs7lg4hgO+/ZjSrOyGDfgYNpfcyUHH7NPI1UqIiKSmVIlWGVlGa2bZ9O6eXZKXmcXqzbh7gYz2wz4E3An0Aa4NKFViYgkSa1CnTt7zfuKCyaOYZ95U1iV24LRux3H2H2O4/en7cvBm5q0XERERGolnYJVKqjNaJkvhw9XAr9KbDkiIskzbnI+I57/ipJqBhDIipZx6LefcMGnYxjw02wWt2zHP/c/m3G7HsmVpw7hTYU6ERERSaLajJb5MLDRJx13PzchFYmIJMl1/51RZbBrVlrMcdPfYfhnL9BnxSLmtOvGFUMvYsLOB3PNibtwpUKdiIiIpIDadMt8OeZxc+BYguvuREQyQnVdMVsXreWMya9y7qSX6LS2gK8234YLhl3JR/334u/HD2SkQp2IiIikkNp0y3wh9rmZPQ18mLCKREQaUVWjYXZas5zzJr3EaZNfo03xOt7vPYg/HHUCn/QawBl7bMG0YTsmqVoRERGR6tWm5a6ybYDO8S5ERKSxjZucz5Mxwa7P8nyGf/oCx814h+xolFf77sW9ux/PjM23pmVuhH8fuyPD1FonIiIiKao219ytJrjmzsL7n4DLE1yXiEjC/G3cNJ6c+OOGi4kHLPqWCyaO4dBvP6Ekks3zOx7M6N2O48d2XTGDf580UKFOREREUl5tumW2boxCREQaw+n3f8JH3y8Hd/aZO5kLPh3DXvOmsqpZS+7Z40Qe2eUolrYMhlo24DYFO6knMzsUuB2IAA+4+8hK65sBjwG7AMuAk919brjuSuA8oAz4g7tPaMTSRUQkTdUY7swsDzgd6BcumgSMcffiRBcmIhJvfxs3jYnfLeHIWR9xwacvsMPP3/NTq/bcuP+5PD3wUNY0a1Fh+9OH9FKwk3oxswhwN3AwsAD43MzGu/vMmM3OA1a4+9ZmdgpwE3CymfUDTgH6A92At8xsW3cva9xXISIi6abacGdmOwLjgfeBL8LFQ4FLzexg4M/u/rfElygi0nDjP5mN/+de3vlsLFsU/MT37Xvwl0P/wLj+v6I4O6fCti1zI9yo6+ukYXYDZrv7HAAzewY4BogNd8cA14aPxwB3mZmFy59x9yLgBzObHR7vk0aqXURE0pS5Vz1Zr5m9C/zD3d+stPwg4BFghrsPTXiFMQYPHuyTJk1qzFOKSLorKGDm30bS+eH76LiugCldt+U/Q07gjW2G4Ja10eZt83KYcs0hSShUYpnZF+4+ONl11JeZnQAc6u7nh89/Dezu7hfFbDM93GZB+Px7YHeCwDfR3Z8Ilz8IvObuY6o7X/sttveD//pQg2qeuWgVAP26tqn3MdYVl1JaxVyRtTVv2ToAtujQYhNbJo5qSI0akn1+1aAaElFDTiSLvJxIg2t57oI9q32PrKlbZtfKwQ7A3d8ysxKC+e5ERFLS6xMmkX/tSE768lX6FRfyvz47858hJzCx545gVuU+ORHj2qP7N3KlIvVjZsOB4QCtum7V4OM1JNTFSzI/uKmG1Koh2edXDaohFWuojZrCXZaZNQu7hWxgZs2BEndfl9jSRETq7q2x/2Pl9f/gqGnvEPEoL2+3D/ftfjwzu2xZ437tWuRwzVH91RVT4iUf6BnzvEe4rKptFphZNrAZwcAqtdkXdx8NjIagZ8uzv90jbsXX14yFK1lVWJrsMkREUlLHVrls06XhY1U+d0H162oKd48BL5jZ7919HoCZ9QbuAB5vcFUiIvH06acsvPJaDnh3AsXZOTyz01Du3+1Y5rfdvMbdzhjSixs0KbnE3+fANmbWhyCYnQKcVmmb8cBZBNfSnQC84+5uZuOBp8zsVoIBVbYBPmu0ykVEJG1VG+7c/QYzuwj4wMzK2yHXAre4+52NUp2ISE3cYcIEuOkmeO89WjZryV17nMSjuxzFspZtN7m7gYKdJIS7l4bvoRMIpkJ4yN1nmNn1wCR3Hw88CDweDpiynCAAEm73HMHgK6XA7zVSpoiI1EaNUyG4+10Eo3e1Dp+vbpSqRERqUloKzz8fhLqvvqKw8+bcesB5PDVgKGub1b5P/OlDeiWwSGnq3P1V4NVKy66OebweOLGafW8EbkxogSIiknE2OYk5KNSJSIooLISHH4ZbboEffoDttmPsRddzefMdKYnkbHr/kBEEO7XaiYiISCapVbgTEUmqFSvg7rvhjjtgyRIYMgRuvZUzfu7Ehz8U1Powmr9OREREMpnCnYikrgUL4Lbb4L77YO1aOPxwuPxy2Gcfxk1ZyIcTp9TqMBo0RURERJqCTYa7cDCVPwG93P03ZrYN0NfdX054dSLSNH39NYwaBU88AdEonHIK/OUvMGDAhk2uenFarQ6lYCciIiJNRVYttnkYKALKJ9DJB25IWEUi0nRNnAjDhkG/fvDMM/Db38Ls2UHIC4PduMn5bPPXV1hbvOnBAxXsREREpCmpTbfMrdz9ZDM7FcDd15mZJbguEWkq3OG114KRL99/H9q1g6uvhosugk6dNmz2t3HTeGLij7U+rIKdiIiINDW1CXfFZpYHOICZbUXQkiciUn+lpfDss3DzzTB1KvToEVxfd/750KpVhU1Pv/8TPvp+ea0P/e+TB2rQFBEREWlyahPurgFeB3qa2ZPAXsDZiSxKRDLYunXw0EPBdAbz5gVdMB95BE49FXJzN9r8b+OmKdiJpIm2LXJplp2Fe/iNMISPHfeKz8sfV7iP3Q5w9wrHIWY/r7B/5e1ERJqmTYY7d3/TzL4EhhBMD3WJuy9NeGUiklmWLQumM7jzTli6FPbcM5ja4MgjIavqy3/r0xVTwU4kebq3zUt2CUAY9iqFxF8ebxwuoWIIjboTjUKZO2VRJxrexz6OuhN1qlxeFg2Wi4g0tmrDnZntXGnRovC+l5n1cvcvE1eWiGSM+fPh1lvh/vuD6QyOPDKYzmDvvavdpa6hDmCvrdrrGjsRAcDMqDg6QHKGCqgc/MrciUZ/CYXVhcayaMUAGtuyWb6sXFXrfmnFrBhq2fCs8nY1bS8i6aSmlrt/1bDOgQPiXIuIZJKZM4Pr6Z58MviUcNppwXQGO+xQ7S7jJudz2bNTiNbxVHtt1Z4nf7PHpjcUEWlEkSwjkpW+Y9B52DpZ3u01GraIVm7ldMDDQFp5e5xgWey6mGOUL4uG3W49dvuYN4Oqgu0vdda8XeWwW3FZhSNVue+G16nAK2mg2nDn7r9qzEJEJEN8/DGMHAn//S+0aAEXXgiXXQZbbFHjbnUdNAWgXYscrjmqv7piiogkgJkRMUhWy2cqig280ZiQW2VYjQ2/m9i+fFnl7aHq7r+/PE/qj0NSUG0mMW8OXAjsTfAFxgfAve6+PsG1iUi6iEbh1VeD6Qw+/BDat4drrgmmM+jYsdrdxk3O58qxUyksqWtbnQZOERGRxpdqgdcrdPmF0mi02utFY7sGb1hfvo+uFc0YtRkt8zFgNXBn+Pw04HHgxEQVJSJpoqQkmGz8pptgxgzo1Qtuvx3OOw9atqxyl4YEunIaOEVERCQIm9kRi/lAH2nwMSuHwSAEeoXurRUGJ4oZvXZDy2TstpVGyv1ltNtfjhNuUWEk3MqtnFTYtuFqc6xfXnXDjhMcC3Kzqx5ALp5qE+52cPd+Mc/fNbOZiSpIRNLA2rXw4IPwr3/Bjz8G19E99hiccgrk5FS5y7jJ+Yx4fgoNyHSAJicXERFJpHS/VrSpq024+9LMhrj7RAAz2x2YlNiyRCQlLV0Kd90V3JYtC0a8vOceOPxwKg1Nt0G8Qp2urxMRERGpWW3C3S7Ax2ZWPi55L2CWmU0D3N0HJKw6EUkN8+YF0xk88EAwCfnRRwfTGey5Z7W71Gc6g6poJEwRERGR2qlNuDs04VWISGqaPj2YzuCpp4KWudNPhxEjoH//Gnfb/cY3+Xl1cYNOnZ1l3HLiTmqpExEREamlTYY7d59nZu2AnrHbaxJzkQz24YfBdAavvBIMjHLxxXDppcGAKTWoz3QGVdF1dSIiIiJ1V5upEP4OnA18T8zgN2gSc5HMEo3Cyy8HI19+/HEwhcF118Hvfw8dOtS4azy6YDbLzuKm4weopU5ERESknmrTLfMkYCt3b1gfKxFJTcXF8PTTQffLmTODycbvvBPOPTeYhLwa8ZjSQIFOREREJH5qE+6mA22BxYktRUQa1Zo1wQAp//oXLFgAO+4ITzwBJ51U7XQG8ep2qevpREREROKvNuHun8BkM5sOFJUvdPejE1aViCTOkiVBy9xdd8GKFbDvvjB6NBx6aJXTGcRrKgMAA07X9XQiIiIiCVGbcPcocBMwDYjDxzsRSYq5c4NWugcfhMJCOOaYYDqDPaqfZuDgW9/ju8VrG3zqLq1z+fSqgxt8HBERERGpXm3C3Tp3vyPhlYhIYkydGlxP98wzkJUFZ5wRTGew/fYbbRqvbpexNPKliIiISOOoTbj7wMz+CYynYrdMTYUgkqrc4YMPgukMXnsNWrWCSy4JpjPo0WPDZvHsclmZQp2IiIhI46pNuBsU3g+JWaapEERSUTQK48cH0xlMnAidOsENN8CFF0K7dhU2jVeXy8r22qo9T/6m+q6eIiIiIpIYtZnE/FeNUYiINEBxMTz5ZND98ptvoHdvuPtuOOccyMsD4jMXXU3UUiciIiKSXLVpucPMjgD6A83Ll7n79YkqSkRqafVquP9+uPVWyM+HnXaCp56CE0+E7OyEBjqFOZGqmVl74FmgNzAXOMndV1TaZiDwH6ANUAbc6O7PhuseAfYDVoabn+3uUxJfuYiIpLtNhjszuxdoAfwKeAA4AfgswXWJSE0WL/5lOoOCAth//2DOuqFDwSwhA6OUU6gT2aQrgLfdfaSZXRE+v7zSNuuAM939OzPrBnxhZhPcvSBcP8LdxzReySIikglq03K3p7sPMLOp7n6dmf0LeC0eJzezQ4HbgQjwgLuPjMdxRTLWnDnBdAYPPQRFRTBsWDCdwe67A4kZ7bKcQp1IrR0D7B8+fhR4j0rhzt2/jXm80MwWA52AgkapUEREMlJtwl1heL8u/HZxGdC1oSc2swhwN3AwsAD43MzGu/vMhh5bJON89VUwSMqzz0IkAmeeyVtHnMnvPl9NyYtL4cVX4n5KhTmReuvi7ovCxz8BXWra2Mx2A3KB72MW32hmVwNvA1e4e1GVO4uIiMSoTbh72czaAqOALwlGyrw/DufeDZjt7nMAzOwZgm87Fe5EIJjO4H//C6YzmDAhmM7gssu4qNM+vLw8Ap+ujvspFehEasfM3gI2r2LVVbFP3N3NzGs4TlfgceAsdy+flORKglCYC4wmaPXb6Dp3MxsODAfo1atXPV6FiIhkmtqMlvn38OELZvYy0NzdV9a0Ty11B+bHPF8A7F55I715SZMTjcJLLwWh7rPPoHNnnh32W27c4lesirSCBPS61PQFInXj7gdVt87Mfjazru6+KAxvi6vZrg3wCnCVu0+MOXZ5q1+RmT0M/LmaGkYThD8GDx5cbYAUEZGmo9pwZ2a7AvPd/afw+ZnA8cA8M7vW3RNzYU8levOSJqOoCJ54AkaNglmzmNd2c0YfciFjdjiQopxmcT1Vs+wsbjp+AMMGdY/rcUUEgPHAWcDI8P6lyhuYWS7wIvBY5YFTYoKhAcOA6QmvWEREMkJNLXf3AQcBmNm+BG9SFwMDCcLWCQ08dz7QM+Z5j3CZSNOyahWMHg233QYLFzK9y1bce/RfeK3vXpRlReJ2mm06t+TNy/aP2/FEpFojgefM7DxgHnASgJkNBi5w9/PDZfsCHczs7HC/8ikPnjSzToABU4ALGrV6ERFJWzWFu0hM69zJwGh3f4Gge+aUOJz7c2AbM+tDEOpOAU6Lw3FF0sPPP8Ptt8M998DKlXy0xQDuPekCPug9CMzidhp1uRRpXO6+DDiwiuWTgPPDx08AT1Sz/wEJLVBERDJWjeHOzLLdvZTgTWp4LferFXcvNbOLgAkEUyE85O4zGnpckZT3/ff8cMV1dHvxGXLKSnmt757cd8zxTO26bVxPo1AnIiIi0rTUFNKeBv5nZksJpkP4AMDMtgbiMaAK7v4q8Go8jiWSisZNzmfE81MoiUL/n7/ngoljOHzWR3TLyuKFHQ7k/t2O44f28bnuTSNdioiIiDRt1YY7d7/RzN4mmNPuDXcvH8wki+DaOxGpQmygw509fpzK7yaOYd+5k1mdm8f9ux3Lg4OPYUmr9g0+l1rnRERERKRcjd0rY4dmjln2beLKEUkvfxs3jScm/rjR8qxoGYd+N5HfTRzDTj99x5KWbblpv7N4cuBhzFfdGgAAHGFJREFUrGreqkHnVKATERERkao0+No5kabo9Ps/4aPvN54NJLe0hOOmv83wz8ay5YqFzG3blSuHXsTYHQ6gKDu3XufKzjJuOXEnTVsgIiIiIjVSuBOphXGT87ly7FQKS6JVrm9dtJbTprzGuZPG02XNcqZuvjUXHnMFr2+7B9F6TmegUCciIiIidaFwJ1KD6lroynVas4JzJ73E6ZNfpU3xOj7YYiCXHnEZH2+xU72nM9AE4yIiIiJSHwp3IpVsKtABbLFiIb/9dCzHT3+b7GgZr227J/cOOYHpm29dr3NqpEsRERERaSiFO2nSqhsQpTo7/DSbCyaO4bBvP6Y0K8KYHQ9k9G7HMa9dt1rtrxAnIiIiIomicCdNUm1a5zZwZ695X3HBxDHsM28Kq3JbcN/ux/HwLsewpFW7Gnc14HQFOhERERFpBAp3kvEqzDtXB1nRMg799hMu+HQMA36azeKW7fjn/mfz1MDDWN2s5Ubb61o5EREREUkmhTvJWHXtclmuWWkxx09/m998NpY+KxYxp103Lj/0Yl7sfwDF2Tkbba9550REREQkFSjcScYZNzmfy56dQh0b6mhdtJYzJr/KuZNeotPaAqZ03YYLhl3JG9sM2Wg6A107JyIiIiKpRuFO0t6m5qDblE5rlnNeOJ1B6+JC3u89iD8cdQKf9BpQYToDBToRERERSWUKd5KWGhroAPosz2f4py9w3Ix3yI5GebXvXtw75ARmdNlqwzYKdCIiIiKSLhTuJK3Ud3CUWAMWfcsFE8dw6LefUBLJ5rkBh3D/rseyrEsPbjx2Rw2IIiIiIiJpSeFO0kJ9B0fZwJ195k7mgk/HsNe8qaxs1pJ79jiRR3Y5ikMP3In31TonIiIiImlO4U5SVjy6XkaiZRw26yMu+PQFdvj5e35u1YHpl/4fO1w3gotat+aiONYrIiIiIpJMCneScuLR9bJZSREnhtMZbFHwE3M69ODLq29h579eRJdmzeJXrIiIiIhIilC4k5QQj1Y6gDbr13DG5Fc5Z9J4Oq0r4Ktu2/LT3/7O7peeC1lZcapWRERERCT1KNxJ0p1+/yd89P3yBh2jy+qlnDtpPGdMeY2WxYVw6KFw+eXstN9+FaYzEBERERHJVAp30uji1UoHsNWy+fzu8xc5bsa7ZEXL4OST4S9/gYEDG16oiIiIiEgaUbiTRhOPa+nKDVw4i99/9gIHffsJ1qwZ/HY4/OlP0KdPww8uIiIiIpKGFO6kUTR4KgMAd/b74Uuu+fpltpz+ObRrB1ddBRdfDJ07x6dQEREREZE0pXAnCRWv6QyO+e4jrpn5Mpt9OxO6d4d//Qt+8xto3TqO1YqIiIiIpC+FO4m7v42bxpMTf8QbeJzmJes565t3+cNX/6Vl/o+w3Xbw8MNw2mmQmxuXWkVEREREMoXCnTTYuMn5XDt+BgWFJXE5XqeStTy6fhL9nn8EliyBIUPg7jvgqKM0nYGIiIiISDUU7qTe4jnqJcCW65czetmHbP3ik7B2LRx+OFx+Oeyzj6YzEBERERHZBIU7qZdg5MuvKIk2rPPlGUN6cUPfbBg1Cp54AqJROOWUYDqDAQPiVK2ISOMxs/bAs0BvYC5wkruvqGK7MmBa+PRHdz86XN4HeAboAHwB/NrdixNfuYiIpDuFO6m1eLbUZRk83LeM/R75P3jpJcjLgwsugMsug969G16siEjyXAG87e4jzeyK8PnlVWxX6O4Dq1h+E3Cbuz9jZvcC5wH/SVi1IiKSMRTupEbxvp4Od47Kn8I1X79Mx5GfQvv2cPXVcNFF0KlTfM4hIpJcxwD7h48fBd6j6nC3ETMz4ADgtJj9r0XhTkREakHhTuIf4KqQ42X8o3gmJ779FEybBj17wm23wfnnQ6tWCTuviEgSdHH3ReHjn4Au1WzX3MwmAaXASHcfR9AVs8DdS8NtFgDdE1msiIhkDoW7JizeA6JU1q5FDtcftCVHffFaMC/dvHnQrx88+iiceirk5CTkvCIiiWZmbwGbV7Hqqtgn7u5mVt3FyVu4e76ZbQm8Y2bTgJV1qGE4MBygV69etd1NREQymMJdE/W3cdN4YuKPcT9uuxY5XHNUf4b1ag533w3HnA5Ll8Jee8Gdd8IRR2g6AxFJe+5+UHXrzOxnM+vq7ovMrCuwuJpj5If3c8zsPWAQ8ALQ1syyw9a7HkB+NfuPBkYDDB48uKFTi4qISAZQuGtCEtn9MidijDphJ4Z1jMKtt8D99wfTGRx5ZDCdwd57x/2cIiIpajxwFjAyvH+p8gZm1g5Y5+5FZtYR2Au4OWzpexc4gWDEzCr3FxERqYrCXQYaNzmfURNmkV9QiAGJ/jq3XYscbumXzYH//is89VSw8NRTg+kMdtghwWcXEUk5I4HnzOw8YB5wEoCZDQYucPfzge2B+8wsCmQRXHM3M9z/cuAZM7sBmAw82NgvQERE0pPCXZrbVJBLRLDb0PVyUHf46CO46Sa45r/QogX8/vfBdAa6/kNEmih3XwYcWMXyScD54eOPgR2r2X8OsFsiaxQRkcykcJfGggFRplFYUgYktoWuQqCLRuHVV+EPp8CHH0KHDnDttcF0Bh06JLAKERERERGpjsJdmho3OZ8/PfcVZR6/SNcyN8KNx+4YBLiqlJTA448HLXUzZgStc7ffDuedBy1bxq0OERERERGpO4W7NFTeYhevYFehVa4qa9fCgw8G0xn8+GNwHd1jj8Epp2g6AxERERGRFKFwl8LKr6dbWFDIZnk5mMGKdfEb6XKTLXVLl8JddwW3Zctgn33gnnvg8MPBLG51iIiIiIhIwyncpaCqpiyIx/QFWQZRh+5t8xgxtG/1oW7ePLj1VnjgAVi3Do4+OpjOYM89G1yDiIiIiIgkhsJdiqk8SEp9bbKrZVWmTYObb4annw5a5k4/PZjOoF+/BtUiIiIiIiKJp3CXRPHsdpmXE+Gfx9XQxbImH34II0fCK68EA6NcfHEwnUHPnvWqRUREREREGp/CXZJUbqFrSLfLiFndg100Ci+/HIx8+fHH0LEjXH99ME9d+/b1rkVERERERJJD4a6RxU46Hg91brErLg66Xd58M8ycCb17w513wrnnBpOQi4iIiIhIWlK4a0QNuZ6uRU4WzXIirFhXQsSMMvdND4wSa80auP/+YKCUBQtgxx3hySfhpJMgW/8NRERERETSnT7VN6JRE2bVOdjVKcBVZcmSoGXurrtgxQrYbz8YPRoOPVTTGYiIiIiIZBCFuwSLHTSlLlOON2iAFIC5c4NJxx98EAoLYdiwYDqDIUPqdzwREREREUlpCndxFBvkurXN41fbdeKFL/Jr1VrXNhwts2BdCd0a0lo3dWpwPd0zz0BWFpxxBowYAdtvX49XJCIiIiIi6ULhrp42FeTyCwp5cuKPm2yta3ALHYA7fPBBMJ3Ba69Bq1ZwySVw6aXQo0f9jysiIiIiImlD4W4TKoe4EUP7AlQYGKW6IFdTsDNoWAsdBNMZjB8fTGcwcSJ06gQ33AAXXgjt2tXvmCIiIiIikpaSEu7MbBRwFFAMfA+c4+4FyailJpVHt8wvKOTKsdNonpO1UVfLulxP171tHh9dcUD9CysuDka6vPlm+OYb6NMH7r4bzjkH8vLqf1wREREREUlbWUk675vADu4+APgWuDJJddSoqtEtC0vKWLGu9hOOVx6PMi8nsqH1r85Wrw4GSdlyy2BeumbNgjnrvv02aK1TsBMRERERabKSEu7c/Q13Lw2fTgRS8sKwhXWcaLyqIHf6kF50b5uHEbTY1ev6usWL4W9/g1694M9/hm22gddfh8mT4ZRTNE+diIiIiIikxDV35wLPVrfSzIYDwwF69erVWDUBwTVx+VUEvLZ5ORSVRiu06uXlRDh+l+68+82SCtfnNWiglDlzgpa6hx6CoiI49thgOoPddqv/MUVEREREJCMlLNyZ2VvA5lWsusrdXwq3uQooBZ6s7jjuPhoYDTB48OC6XNrWYCOG9q1wzR0EIe7ao/sDbDTQSoOCXKyvvgoGSXn2WYhE4Mwzg+kM+tazO6eIiIiIiGS8hIU7dz+opvVmdjZwJHCguzdqaKut8rBWXYiLW5iDYDqD//0vmM5gwgRo3Rr+9Cf44x+hW7f4nUdERERERDJSskbLPBT4C7Cfu69LRg21NWxQ9/iGuMqiURg3Lmip++wz6NwZ/vEP+N3voG3bxJ1XREREREQySrKuubsLaAa8aWYAE939giTVkhxFRfDEE8F0Bt9+G4yA+Z//wFlnadRLERERERGps6SEO3ffOhnnTQmrVsHo0XDbbbBwIQwaBM88A8cfr1EvRURERESk3pQmGsvPP8Ptt8M998DKlXDAAfDII3DQQWCVJ1EQERERERGpG4W7RPv+e7jlFnj4YSguDlro/vIX2HXXZFcmIiIiIiIZROEuUSZPDgZJef75oLvlWWcFE5Bvu22yKxMRERERkQykcBdP7vDOO0Goe/NNaNMmmJ/ukkuga9dkVyciIiIiIhksK9kFZISyMhgzBnbbLbiGburUYL66H38M7hXsRESaDDNrb2Zvmtl34X27Krb5lZlNibmtN7Nh4bpHzOyHmHUDG/s1iIhIelK4a4iiIrj/fth+ezjxRCgogPvug7lz4fLLYbPNkl2hiIg0viuAt919G+Dt8HkF7v6uuw9094HAAcA64I2YTUaUr3f3KY1Qs4iIZAB1y6yPlSuDEHfbbfDTT7DLLvDcc3DccRCJJLs6ERFJrmOA/cPHjwLvAZfXsP0JwGvuvi6xZYmISKZTy11d/PQTXHEF9OoVtMztsAO89RZ8/nnQcqdgJyIi0MXdF4WPfwK6bGL7U4CnKy270cymmtltZtYs7hWKiEhGUstdbcyeDaNGwaOPQkkJnHBCMJ3BLrskuzIREUkCM3sL2LyKVVfFPnF3NzOv4ThdgR2BCTGLryQIhbnAaIJWv+ur2Hc4MBygV69edXwFIiKSiRTuavLFF8HIl2PGQG4unH12MJ3B1lsnuzIREUkidz+ounVm9rOZdXX3RWF4W1zDoU4CXnT3kphjl7f6FZnZw8Cfq6lhNEH4Y/DgwdUGSBERaTrULbMy96Cr5UEHweDBMGFC0AVz7ly4914FOxER2ZTxwFnh47OAl2rY9lQqdckMAyFmZsAwYHr8SxQRkUyklrtyZWXwwgtBS92XXwbTF9x8M/z2t8F8dSIiIrUzEnjOzM4D5hG0zmFmg4EL3P388HlvoCfwv0r7P2lmnQADpgAXNE7ZIiKS7hTu1q8PrqW75Zbg2rpttw2mN/j1r6GZrmEXEZG6cfdlwIFVLJ8EnB/zfC7QvYrtDkhkfSIikrmabrhbuRL+8x/497/h559h112Da+uGDdOolyIiIiIiknaaXrhbtCgIdP/5D6xeDUOHBtfU7b8/mCW7OhERERERkXppOuHu22+D6QweewxKS+Gkk4LpDAYNSnZlIiIiIiIiDZb54e7zz4NBUsaODa6hO+88+NOfYKutkl2ZiIiIiIhI3GRmuHOHN9+EkSPh3XehbVu48kr4wx+gS5dkVyciIiIiIhJ3mRXuSkuDQVFuvhkmT4Zu3YJRMIcPh9atk12diIiIiIhIwmRGuCsshEceCYLcnDnQty88+CCcfrqmMxARERERkSYhK9kFxMXVV8OFF0KnTvDiizBzJpx7roKdiIiIiIg0GZnRcnfxxXDkkbDvvprOQEREREREmqTMCHe9egU3ERERERGRJiozumWKiIiIiIg0cQp3IiIiIiIiGSAzumXW07jJ+YyaMIuFBYV0a5vHiKF9GTaoe7LLEhERERERqbMmG+7GTc7nyrHTKCwpAyC/oJArx04DUMATEREREZG002S7ZY6aMGtDsCtXWFLGqAmzklSRiIiIiIhI/aV9y119u1YuLCis03IREREREZFUltYtd+VdK/MLCnF+6Vo5bnL+Jvft1javTstFRERERERSWVqHu4Z0rRwxtC95OZEKy/JyIowY2jeuNYqIiIiIiDSGtO6W2ZCuleVdNzVapoiIiIiIZIK0Dnfd2uaRX0WQq23XymGDuivMiYiIiIhIRkjrbpnqWikiIiIiIhJI65Y7da0UEREREREJpHW4A3WtFBERERERgTTvlikiIiIiIiIBhTsREREREZEMoHAnIiIiIiKSARTuREREREREMoDCnYiIiIiISAZQuBMREREREckACnciIiJxZGYnmtkMM4ua2eAatjvUzGaZ2WwzuyJmeR8z+zRc/qyZ5TZO5SIiku4U7kREROJrOnAc8H51G5hZBLgbOAzoB5xqZv3C1TcBt7n71sAK4LzElisiIplC4U5ERCSO3P1rd5+1ic12A2a7+xx3LwaeAY4xMwMOAMaE2z0KDEtYsSIiklGyk11AXXzxxRdLzWxesutIko7A0mQXkURN+fU35dcOTfv1N+XXvkWyC0iw7sD8mOcLgN2BDkCBu5fGLO9e1QHMbDgwPHy6xsw2FShroyn/n4uln0NAPwf9DMrp5xBIlZ9Dte+RaRXu3L1TsmtIFjOb5O7VXruR6Zry62/Krx2a9utvyq891ZnZW8DmVay6yt1faowa3H00MDqex9T/uYB+DgH9HPQzKKefQyAdfg5pFe5ERERSgbsf1MBD5AM9Y573CJctA9qaWXbYele+XEREZJN0zZ2IiEjj+xzYJhwZMxc4BRjv7g68C5wQbncW0CgtgSIikv4U7tJHXLvepKGm/Pqb8muHpv36m/JrT1tmdqyZLQD2AF4xswnh8m5m9ipA2Cp3ETAB+Bp4zt1nhIe4HLjMzGYTXIP3YCOWr/9zAf0cAvo56GdQTj+HQMr/HCz4klBERERERETSmVruREREREREMoDCnYiIiIiISAZQuEsjZjbKzL4xs6lm9qKZtU12TY3FzE40sxlmFjWzlB6CNp7M7FAzm2Vms83simTX05jM7CEzW2xm05NdS2Mzs55m9q6ZzQz/31+S7JokszXlvzXl9HtXkZlFzGyymb2c7FqSxczamtmY8LPX12a2R7JrSgYzuzT8nZhuZk+bWfNk19QYqvocYmbtzexNM/suvG+XzBqronCXXt4EdnD3AcC3wJVJrqcxTQeOA95PdiGNxcwiwN3AYUA/4FQz65fcqhrVI8ChyS4iSUqBP7l7P2AI8Psm9m8vjUh/azbQ711FlxAM9tOU3Q687u7bATvRBH8eZtYd+AMw2N13ACIEo/s2BY+w8eeQK4C33X0b4O3weUpRuEsj7v5GOMIawESC+Y+aBHf/2t1nJbuORrYbMNvd57h7MfAMcEySa2o07v4+sDzZdSSDuy9y9y/Dx6sJPlB0T25VksGa9N+acvq9+4WZ9QCOAB5Idi3JYmabAfsSjlbr7sXuXpDUopInG8gzs2ygBbAwyfU0imo+hxwDPBo+fhQY1pg11YbCXfo6F3gt2UVIQnUH5sc8X0AT/aDRlJlZb2AQ8GmSS5HMpb81lej3jn8DfwGiSa4jmfoAS4CHw+6pD5hZy2QX1djcPR+4BfgRWASsdPc3kltVUnVx90Xh45+ALskspioKdynGzN4K+zRXvh0Ts81VBN1HnkxepfFXm9cu0pSYWSvgBeCP7r4q2fWINAVN/ffOzI4EFrv7F8muJcmygZ2B/7j7IGAtKdgFL9HCa8qOIQi73YCWZnZGcqtKDR7MJ5dyc8plJ7sAqcjdD6ppvZmdDRwJHOgZNknhpl57E5QP9Ix53iNcJk2AmeUQfMB80t3HJrseyWj6WxPS7x0AewFHm9nhQHOgjZk94e5N7QP9AmCBu5e33o6hCYY74CDgB3dfAmBmY4E9gSeSWlXy/GxmXd19kZl1BRYnu6DK1HKXRszsUIJuEke7+7pk1yMJ9zmwjZn1MbNcgguYxye5JmkEZmYE13l87e63JrseyXj6W4N+78q5+5Xu3sPdexP8X3inCQY73P0nYL6Z9Q0XHQjMTGJJyfIjMMTMWoS/IwfSBAeWiTEeOCt8fBbwUhJrqZLCXXq5C2gNvGlmU8zs3mQX1FjM7FgzWwDsAbxiZhOSXVOihYPnXARMIPhD+py7z0huVY3HzJ4GPgH6mtkCMzsv2TU1or2AXwMHhL/rU8Jv0UXirqn/rYmh3zup7GLgSTObCgwE/pHcchpf2HI5BvgSmEaQHUYntahGUs3nkJHAwWb2HUGr5shk1lgVy7CefSIiIiIiIk2SWu5EREREREQygMKdiIiIiIhIBlC4ExERERERyQAKdyIiIiIiIhlA4U5ERERERCQDKNxJRjGzDjFDWP9kZvnh4wIza9T5acxsmJn1i3l+vZnVeaJ2M+ttZtOrWdffzN4xs1lm9r2ZXWdmcf+9rum1mNl7ZjY43ucUERERkbpRuJOM4u7L3H2guw8E7gVuCx8PBKLxPp+ZZdewehiwIRC5+9Xu/lYcz51HMJnmSHfvC+wI7AZcEq9zxBhGAl+LiIiIiDScwp00JREzu9/MZpjZG2E4wsy2MrPXzewLM/vAzLYLl/cOW8WmmtnbZtYrXP6Imd1rZp8CN1e1v5ntCRwNjApbDrcK9zshPMauZvaxmX1lZp+ZWevwfB+Y2Zfhbc9NvJ7TgI/c/Q0Ad19HMBHxiPAc15rZn8s3NrPpZtY7fDwurHeGmQ2P2WaNmd0Y1jXRzLps6rXEMrNDzOyTsP7nzaxVuHykmc0Mf5a31P2fTkREREQ2ReFOmpJtgLvdvT9QABwfLh8NXOzuuwB/Bu4Jl98JPOruA4AngTtijtUD2NPdL6tqf3f/mKBVbUTYkvh9+Y5mlgs8C1zi7jsBBwGFwGLgYHffGTi50vmq0h/4InZBeJ48M2u7iX3PDesdDPzBzDqEy1sCE8O63gd+U9NriWVmHYG/AQeFr2EScFl47GOB/uHP8oZN1CYiIiIi9VBTlzKRTPODu08JH38B9A5blvYEnjez8u2ahfd7AMeFjx8Hbo451vPuXraJ/avTF1jk7p8DuPsqADNrCdxlZgOBMmDbur7AOviDmR0bPu5JEHyXAcXAy+HyL4CD63DMIQRdNz8Kfxa5wCfASmA98KCZvRxzfBERERGJI4U7aUqKYh6XAXkErdcF4XV5dbE2vK/v/lW5FPgZ2Ck87vpNbD8T2Dd2gZltCSxz9wIzK6Vi63zzcJv9CVoL93D3dWb2Xvk6oMTdPXxcRt3+RhjwprufutEKs92AA4ETCLqOHlCH44qIiIhILahbpjRpYavZD2Z2IoAFdgpXfwycEj4+HfigjvuvBlpXcdpZQFcz2zXcp3U4MMtmBC16UeDXQGQT5T8J7B0zamUeQVfOa8L1c4Gdw3U7A33C5ZsBK8Jgtx1Bi9umVPdaYk0E9jKzrcNztjSzbcPWzc3c/VWCALtTTQcRERERkfpRuBMJgtt5ZvYVMAM4Jlx+MXCOmU0lCFvVjUJZ3f7PACPMbLKZbVW+sbsXE1xTd2e4z5sELWf3AGeFy7bjl9bBKrl7IcFAJ1eZ2bfAUoIBVp4MN3kBaG9mMwhay74Nl78OZJvZ18BIglC2KVW+lkr1LAHOBp4Of2afhK+jNfByuOxD4LJanE9ERERE6sh+6YElIunMzIYBtwK/cvd5SS5HRERERBqZwp2IiIiIiEgGULdMERERERGRDKBwJyIiIiIikgEU7kRERERERDKAwp2IiIiIiEgGULgTERERERHJAAp3IiIiIiIiGeD/AfLq9M4bAs/wAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1080x864 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "SARIMA_model.plot_diagnostics(figsize=(15,12))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "40a422eb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-15T16:48:52.834594Z",
     "iopub.status.busy": "2022-06-15T16:48:52.833930Z",
     "iopub.status.idle": "2022-06-15T16:48:53.119035Z",
     "shell.execute_reply": "2022-06-15T16:48:53.119543Z",
     "shell.execute_reply.started": "2022-06-15T16:41:03.855230Z"
    },
    "papermill": {
     "duration": 0.324049,
     "end_time": "2022-06-15T16:48:53.119747",
     "exception": false,
     "start_time": "2022-06-15T16:48:52.795698",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "forecast(SARIMA_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "343d53ee",
   "metadata": {
    "papermill": {
     "duration": 0.03634,
     "end_time": "2022-06-15T16:48:53.193382",
     "exception": false,
     "start_time": "2022-06-15T16:48:53.157042",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## <center>SARIMAX Model Selection</center>\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "9a5c426d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Month\n",
       "2007-12-10    12\n",
       "2007-12-11    12\n",
       "2007-12-12    12\n",
       "2007-12-13    12\n",
       "2007-12-14    12\n",
       "              ..\n",
       "2009-04-23     4\n",
       "2009-04-24     4\n",
       "2009-04-25     4\n",
       "2009-04-26     4\n",
       "2009-04-27     4\n",
       "Freq: D, Name: month_index, Length: 505, dtype: int64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['month_index'] = df.index.month\n",
    "df['month_index']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "4159b13d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-15T16:48:53.287947Z",
     "iopub.status.busy": "2022-06-15T16:48:53.286490Z",
     "iopub.status.idle": "2022-06-15T16:49:21.515718Z",
     "shell.execute_reply": "2022-06-15T16:49:21.516215Z",
     "shell.execute_reply.started": "2022-06-15T16:41:04.111095Z"
    },
    "papermill": {
     "duration": 28.285679,
     "end_time": "2022-06-15T16:49:21.516400",
     "exception": false,
     "start_time": "2022-06-15T16:48:53.230721",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Performing stepwise search to minimize aic\n",
      " ARIMA(1,0,1)(0,1,1)[12] intercept   : AIC=inf, Time=8.58 sec\n",
      " ARIMA(0,0,0)(0,1,0)[12] intercept   : AIC=1014.503, Time=0.32 sec\n",
      " ARIMA(1,0,0)(1,1,0)[12] intercept   : AIC=668.208, Time=2.73 sec\n",
      " ARIMA(0,0,1)(0,1,1)[12] intercept   : AIC=621.562, Time=3.05 sec\n",
      " ARIMA(0,0,0)(0,1,0)[12]             : AIC=1012.864, Time=0.11 sec\n",
      " ARIMA(0,0,1)(0,1,0)[12] intercept   : AIC=802.117, Time=0.43 sec\n",
      " ARIMA(0,0,1)(1,1,1)[12] intercept   : AIC=620.541, Time=4.90 sec\n",
      " ARIMA(0,0,1)(1,1,0)[12] intercept   : AIC=700.393, Time=1.89 sec\n",
      " ARIMA(0,0,1)(2,1,1)[12] intercept   : AIC=inf, Time=24.12 sec\n",
      " ARIMA(0,0,1)(1,1,2)[12] intercept   : AIC=inf, Time=27.60 sec\n",
      " ARIMA(0,0,1)(0,1,2)[12] intercept   : AIC=620.873, Time=10.03 sec\n",
      " ARIMA(0,0,1)(2,1,0)[12] intercept   : AIC=666.278, Time=6.11 sec\n",
      " ARIMA(0,0,1)(2,1,2)[12] intercept   : AIC=inf, Time=30.96 sec\n",
      " ARIMA(0,0,0)(1,1,1)[12] intercept   : AIC=876.689, Time=2.59 sec\n",
      " ARIMA(1,0,1)(1,1,1)[12] intercept   : AIC=inf, Time=12.03 sec\n",
      " ARIMA(0,0,2)(1,1,1)[12] intercept   : AIC=inf, Time=14.71 sec\n",
      " ARIMA(1,0,0)(1,1,1)[12] intercept   : AIC=inf, Time=8.63 sec\n",
      " ARIMA(1,0,2)(1,1,1)[12] intercept   : AIC=inf, Time=18.21 sec\n",
      " ARIMA(0,0,1)(1,1,1)[12]             : AIC=624.248, Time=2.59 sec\n",
      "\n",
      "Best model:  ARIMA(0,0,1)(1,1,1)[12] intercept\n",
      "Total fit time: 179.625 seconds\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>SARIMAX Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>                  <td>y</td>               <th>  No. Observations:  </th>    <td>505</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>           <td>SARIMAX(0, 0, 1)x(1, 1, 1, 12)</td> <th>  Log Likelihood     </th> <td>-305.271</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>                   <td>Sat, 12 Nov 2022</td>        <th>  AIC                </th>  <td>620.541</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                       <td>09:07:51</td>            <th>  BIC                </th>  <td>641.544</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sample:</th>                    <td>12-10-2007</td>           <th>  HQIC               </th>  <td>628.787</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th></th>                          <td>- 04-27-2009</td>          <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>               <td>opg</td>              <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>intercept</th> <td>   -0.0167</td> <td>    0.010</td> <td>   -1.753</td> <td> 0.080</td> <td>   -0.035</td> <td>    0.002</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L1</th>     <td>    0.6599</td> <td>    0.031</td> <td>   21.376</td> <td> 0.000</td> <td>    0.599</td> <td>    0.720</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.S.L12</th>  <td>    0.1278</td> <td>    0.047</td> <td>    2.741</td> <td> 0.006</td> <td>    0.036</td> <td>    0.219</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.S.L12</th>  <td>   -0.8154</td> <td>    0.045</td> <td>  -18.208</td> <td> 0.000</td> <td>   -0.903</td> <td>   -0.728</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>sigma2</th>    <td>    0.1975</td> <td>    0.009</td> <td>   21.806</td> <td> 0.000</td> <td>    0.180</td> <td>    0.215</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Ljung-Box (L1) (Q):</th>     <td>21.39</td> <th>  Jarque-Bera (JB):  </th> <td>726.23</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Q):</th>                <td>0.00</td>  <th>  Prob(JB):          </th>  <td>0.00</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Heteroskedasticity (H):</th> <td>0.57</td>  <th>  Skew:              </th>  <td>1.41</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(H) (two-sided):</th>    <td>0.00</td>  <th>  Kurtosis:          </th>  <td>8.23</td> \n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Covariance matrix calculated using the outer product of gradients (complex-step)."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                                     SARIMAX Results                                      \n",
       "==========================================================================================\n",
       "Dep. Variable:                                  y   No. Observations:                  505\n",
       "Model:             SARIMAX(0, 0, 1)x(1, 1, 1, 12)   Log Likelihood                -305.271\n",
       "Date:                            Sat, 12 Nov 2022   AIC                            620.541\n",
       "Time:                                    09:07:51   BIC                            641.544\n",
       "Sample:                                12-10-2007   HQIC                           628.787\n",
       "                                     - 04-27-2009                                         \n",
       "Covariance Type:                              opg                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "intercept     -0.0167      0.010     -1.753      0.080      -0.035       0.002\n",
       "ma.L1          0.6599      0.031     21.376      0.000       0.599       0.720\n",
       "ar.S.L12       0.1278      0.047      2.741      0.006       0.036       0.219\n",
       "ma.S.L12      -0.8154      0.045    -18.208      0.000      -0.903      -0.728\n",
       "sigma2         0.1975      0.009     21.806      0.000       0.180       0.215\n",
       "===================================================================================\n",
       "Ljung-Box (L1) (Q):                  21.39   Jarque-Bera (JB):               726.23\n",
       "Prob(Q):                              0.00   Prob(JB):                         0.00\n",
       "Heteroskedasticity (H):               0.57   Skew:                             1.41\n",
       "Prob(H) (two-sided):                  0.00   Kurtosis:                         8.23\n",
       "===================================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
       "\"\"\""
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#adding exogenous variable\n",
    "df['month_index'] = df.index.month\n",
    "\n",
    "# SARIMAX Model\n",
    "SARIMAX_model = pm.auto_arima(df[['#y']], exogenous=df[['month_index']],\n",
    "                           start_p=1, start_q=1,\n",
    "                           test='adf',\n",
    "                           max_p=3, max_q=3, m=12,\n",
    "                           start_P=0, seasonal=True,\n",
    "                           d=None, D=1, \n",
    "                           trace=True,\n",
    "                           error_action='ignore',  \n",
    "                           suppress_warnings=True, \n",
    "                           stepwise=True)\n",
    "\n",
    "SARIMAX_model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "3c41f066",
   "metadata": {},
   "outputs": [],
   "source": [
    "file_name = \"SARIMAX_model_reg.pkl\"\n",
    "\n",
    "# save\n",
    "#pickle.dump(SARIMAX_model, open(file_name, \"wb\"))\n",
    "\n",
    "# load\n",
    "SARIMAX_model = pickle.load(open(file_name, \"rb\"))\n",
    "\n",
    "#y_pred_load=model_loaded.predict(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "f8960f6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>SARIMAX Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>                  <td>y</td>               <th>  No. Observations:  </th>    <td>505</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>           <td>SARIMAX(0, 0, 1)x(1, 1, 1, 12)</td> <th>  Log Likelihood     </th> <td>-305.271</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>                   <td>Sat, 12 Nov 2022</td>        <th>  AIC                </th>  <td>620.541</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                       <td>17:29:49</td>            <th>  BIC                </th>  <td>641.544</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sample:</th>                    <td>12-10-2007</td>           <th>  HQIC               </th>  <td>628.787</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th></th>                          <td>- 04-27-2009</td>          <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>               <td>opg</td>              <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>intercept</th> <td>   -0.0167</td> <td>    0.010</td> <td>   -1.753</td> <td> 0.080</td> <td>   -0.035</td> <td>    0.002</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L1</th>     <td>    0.6599</td> <td>    0.031</td> <td>   21.376</td> <td> 0.000</td> <td>    0.599</td> <td>    0.720</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.S.L12</th>  <td>    0.1278</td> <td>    0.047</td> <td>    2.741</td> <td> 0.006</td> <td>    0.036</td> <td>    0.219</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.S.L12</th>  <td>   -0.8154</td> <td>    0.045</td> <td>  -18.208</td> <td> 0.000</td> <td>   -0.903</td> <td>   -0.728</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>sigma2</th>    <td>    0.1975</td> <td>    0.009</td> <td>   21.806</td> <td> 0.000</td> <td>    0.180</td> <td>    0.215</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Ljung-Box (L1) (Q):</th>     <td>21.39</td> <th>  Jarque-Bera (JB):  </th> <td>726.23</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Q):</th>                <td>0.00</td>  <th>  Prob(JB):          </th>  <td>0.00</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Heteroskedasticity (H):</th> <td>0.57</td>  <th>  Skew:              </th>  <td>1.41</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(H) (two-sided):</th>    <td>0.00</td>  <th>  Kurtosis:          </th>  <td>8.23</td> \n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Covariance matrix calculated using the outer product of gradients (complex-step)."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                                     SARIMAX Results                                      \n",
       "==========================================================================================\n",
       "Dep. Variable:                                  y   No. Observations:                  505\n",
       "Model:             SARIMAX(0, 0, 1)x(1, 1, 1, 12)   Log Likelihood                -305.271\n",
       "Date:                            Sat, 12 Nov 2022   AIC                            620.541\n",
       "Time:                                    17:29:49   BIC                            641.544\n",
       "Sample:                                12-10-2007   HQIC                           628.787\n",
       "                                     - 04-27-2009                                         \n",
       "Covariance Type:                              opg                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "intercept     -0.0167      0.010     -1.753      0.080      -0.035       0.002\n",
       "ma.L1          0.6599      0.031     21.376      0.000       0.599       0.720\n",
       "ar.S.L12       0.1278      0.047      2.741      0.006       0.036       0.219\n",
       "ma.S.L12      -0.8154      0.045    -18.208      0.000      -0.903      -0.728\n",
       "sigma2         0.1975      0.009     21.806      0.000       0.180       0.215\n",
       "===================================================================================\n",
       "Ljung-Box (L1) (Q):                  21.39   Jarque-Bera (JB):               726.23\n",
       "Prob(Q):                              0.00   Prob(JB):                         0.00\n",
       "Heteroskedasticity (H):               0.57   Skew:                             1.41\n",
       "Prob(H) (two-sided):                  0.00   Kurtosis:                         8.23\n",
       "===================================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
       "\"\"\""
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SARIMAX_model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e507bed",
   "metadata": {
    "papermill": {
     "duration": 0.034857,
     "end_time": "2022-06-15T16:49:21.586022",
     "exception": false,
     "start_time": "2022-06-15T16:49:21.551165",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "We can see that similar to the SARIMA model we are getting some pretty good-looking predictions and the width of the forecasted confidence interval has decreased. This means that the model is more certain of its predictions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "b12775ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "forecast(SARIMAX_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "210d86f1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 74.45524,
   "end_time": "2022-06-15T16:49:22.867492",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2022-06-15T16:48:08.412252",
   "version": "2.3.3"
  }
 },
 "nbformat": 4,
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