Trading Strategies Using Python.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Trading Strategies for Apple(AAPL) stock using Python."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# JatinNanda (https://www.linkedin.com/in/iamjatinnanda)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading the Required Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from datetime import datetime\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('fivethirtyeight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting yfinance\n",
      "  Downloading yfinance-0.1.55.tar.gz (23 kB)\n",
      "Requirement already satisfied: pandas>=0.24 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from yfinance) (1.1.3)\n",
      "Requirement already satisfied: numpy>=1.15 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from yfinance) (1.19.2)\n",
      "Requirement already satisfied: requests>=2.20 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from yfinance) (2.24.0)\n",
      "Collecting multitasking>=0.0.7\n",
      "  Downloading multitasking-0.0.9.tar.gz (8.1 kB)\n",
      "Collecting lxml>=4.5.1\n",
      "  Downloading lxml-4.6.1-cp37-cp37m-manylinux1_x86_64.whl (5.5 MB)\n",
      "\u001b[K     |████████████████████████████████| 5.5 MB 4.3 MB/s eta 0:00:01\n",
      "\u001b[?25hRequirement already satisfied: python-dateutil>=2.7.3 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from pandas>=0.24->yfinance) (2.8.1)\n",
      "Requirement already satisfied: pytz>=2017.2 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from pandas>=0.24->yfinance) (2020.1)\n",
      "Requirement already satisfied: idna<3,>=2.5 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from requests>=2.20->yfinance) (2.10)\n",
      "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from requests>=2.20->yfinance) (1.25.10)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from requests>=2.20->yfinance) (2020.6.20)\n",
      "Requirement already satisfied: chardet<4,>=3.0.2 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from requests>=2.20->yfinance) (3.0.4)\n",
      "Requirement already satisfied: six>=1.5 in /srv/conda/envs/notebook/lib/python3.7/site-packages (from python-dateutil>=2.7.3->pandas>=0.24->yfinance) (1.15.0)\n",
      "Building wheels for collected packages: yfinance, multitasking\n",
      "  Building wheel for yfinance (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for yfinance: filename=yfinance-0.1.55-py2.py3-none-any.whl size=22616 sha256=b58526cef3d6c97830f8eb5d0249dbcd1ee5bd698038680b947223858cb71f8f\n",
      "  Stored in directory: /home/jovyan/.cache/pip/wheels/aa/8a/36/59ed4f6fbcb6100967618eeb0696046bf9777a41ac2ff1f9b9\n",
      "  Building wheel for multitasking (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for multitasking: filename=multitasking-0.0.9-py3-none-any.whl size=8366 sha256=6faa2abd39df9a96d6caae58ab2fad7bc96c1f4006b86e5453f4cd871a56fec2\n",
      "  Stored in directory: /home/jovyan/.cache/pip/wheels/ae/25/47/4d68431a7ec1b6c4b5233365934b74c1d4e665bf5f968d363a\n",
      "Successfully built yfinance multitasking\n",
      "Installing collected packages: multitasking, lxml, yfinance\n",
      "Successfully installed lxml-4.6.1 multitasking-0.0.9 yfinance-0.1.55\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install yfinance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    }
   ],
   "source": [
    "import yfinance as yf\n",
    "AAPL = yf.download('AAPL','2019-07-14', '2020-07-15')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-07-15</th>\n",
       "      <td>51.022499</td>\n",
       "      <td>51.467499</td>\n",
       "      <td>51.000000</td>\n",
       "      <td>51.302502</td>\n",
       "      <td>50.606209</td>\n",
       "      <td>67789600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-16</th>\n",
       "      <td>51.147499</td>\n",
       "      <td>51.527500</td>\n",
       "      <td>50.875000</td>\n",
       "      <td>51.125000</td>\n",
       "      <td>50.431118</td>\n",
       "      <td>67467200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-17</th>\n",
       "      <td>51.012501</td>\n",
       "      <td>51.272499</td>\n",
       "      <td>50.817501</td>\n",
       "      <td>50.837502</td>\n",
       "      <td>50.147518</td>\n",
       "      <td>56430000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-18</th>\n",
       "      <td>51.000000</td>\n",
       "      <td>51.470001</td>\n",
       "      <td>50.924999</td>\n",
       "      <td>51.415001</td>\n",
       "      <td>50.717182</td>\n",
       "      <td>74162400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-19</th>\n",
       "      <td>51.447498</td>\n",
       "      <td>51.625000</td>\n",
       "      <td>50.590000</td>\n",
       "      <td>50.647499</td>\n",
       "      <td>49.960094</td>\n",
       "      <td>83717200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-08</th>\n",
       "      <td>94.180000</td>\n",
       "      <td>95.375000</td>\n",
       "      <td>94.089996</td>\n",
       "      <td>95.342499</td>\n",
       "      <td>95.170906</td>\n",
       "      <td>117092000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-09</th>\n",
       "      <td>96.262497</td>\n",
       "      <td>96.317497</td>\n",
       "      <td>94.672501</td>\n",
       "      <td>95.752502</td>\n",
       "      <td>95.580170</td>\n",
       "      <td>125642800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-10</th>\n",
       "      <td>95.334999</td>\n",
       "      <td>95.980003</td>\n",
       "      <td>94.705002</td>\n",
       "      <td>95.919998</td>\n",
       "      <td>95.747368</td>\n",
       "      <td>90257200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-13</th>\n",
       "      <td>97.264999</td>\n",
       "      <td>99.955002</td>\n",
       "      <td>95.257500</td>\n",
       "      <td>95.477501</td>\n",
       "      <td>95.305664</td>\n",
       "      <td>191649200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-14</th>\n",
       "      <td>94.839996</td>\n",
       "      <td>97.254997</td>\n",
       "      <td>93.877502</td>\n",
       "      <td>97.057503</td>\n",
       "      <td>96.882820</td>\n",
       "      <td>170989200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>253 rows × 6 columns</p>\n",
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      "text/plain": [
       "                 Open       High        Low      Close  Adj Close     Volume\n",
       "Date                                                                        \n",
       "2019-07-15  51.022499  51.467499  51.000000  51.302502  50.606209   67789600\n",
       "2019-07-16  51.147499  51.527500  50.875000  51.125000  50.431118   67467200\n",
       "2019-07-17  51.012501  51.272499  50.817501  50.837502  50.147518   56430000\n",
       "2019-07-18  51.000000  51.470001  50.924999  51.415001  50.717182   74162400\n",
       "2019-07-19  51.447498  51.625000  50.590000  50.647499  49.960094   83717200\n",
       "...               ...        ...        ...        ...        ...        ...\n",
       "2020-07-08  94.180000  95.375000  94.089996  95.342499  95.170906  117092000\n",
       "2020-07-09  96.262497  96.317497  94.672501  95.752502  95.580170  125642800\n",
       "2020-07-10  95.334999  95.980003  94.705002  95.919998  95.747368   90257200\n",
       "2020-07-13  97.264999  99.955002  95.257500  95.477501  95.305664  191649200\n",
       "2020-07-14  94.839996  97.254997  93.877502  97.057503  96.882820  170989200\n",
       "\n",
       "[253 rows x 6 columns]"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AAPL"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualisaiton of the share "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x324 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#visualize the data\n",
    "plt.figure(figsize=(12.5,4.5))\n",
    "plt.plot(AAPL['Adj Close'], label='AAPL')\n",
    "plt.title('Apple Adj.Close Price History')\n",
    "plt.xlabel('July.14,2019-July.15,2020')\n",
    "plt.ylabel('Adj.Close Price USD($)')\n",
    "plt.legend(loc='upper left')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the simple moving average with 30 day moving window"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Adj Close SMA30</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-07-15</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-16</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-17</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-18</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-19</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-08</th>\n",
       "      <td>86.661830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-09</th>\n",
       "      <td>87.201690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-10</th>\n",
       "      <td>87.745959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-13</th>\n",
       "      <td>88.278083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-14</th>\n",
       "      <td>88.830254</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>253 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Adj Close SMA30\n",
       "Date                       \n",
       "2019-07-15              NaN\n",
       "2019-07-16              NaN\n",
       "2019-07-17              NaN\n",
       "2019-07-18              NaN\n",
       "2019-07-19              NaN\n",
       "...                     ...\n",
       "2020-07-08        86.661830\n",
       "2020-07-09        87.201690\n",
       "2020-07-10        87.745959\n",
       "2020-07-13        88.278083\n",
       "2020-07-14        88.830254\n",
       "\n",
       "[253 rows x 1 columns]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SMA30 = pd.DataFrame()\n",
    "SMA30['Adj Close SMA30'] = AAPL['Adj Close'].rolling(window =30).mean()\n",
    "SMA30"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Create simple moving 100 day moving ay average "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Adj Close SMA100</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-07-15</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-16</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-17</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-18</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-19</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-08</th>\n",
       "      <td>75.216789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-09</th>\n",
       "      <td>75.363867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-10</th>\n",
       "      <td>75.527425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-13</th>\n",
       "      <td>75.675068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-14</th>\n",
       "      <td>75.846746</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>253 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Adj Close SMA100\n",
       "Date                        \n",
       "2019-07-15               NaN\n",
       "2019-07-16               NaN\n",
       "2019-07-17               NaN\n",
       "2019-07-18               NaN\n",
       "2019-07-19               NaN\n",
       "...                      ...\n",
       "2020-07-08         75.216789\n",
       "2020-07-09         75.363867\n",
       "2020-07-10         75.527425\n",
       "2020-07-13         75.675068\n",
       "2020-07-14         75.846746\n",
       "\n",
       "[253 rows x 1 columns]"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SMA100= pd.DataFrame()\n",
    "SMA100['Adj Close SMA100'] = AAPL['Adj Close'].rolling(window=100).mean()\n",
    "SMA100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x324 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#visualize the data\n",
    "plt.figure(figsize=(12.5,4.5))\n",
    "plt.plot(AAPL['Adj Close'], label='AAPL')\n",
    "\n",
    "plt.plot(SMA30['Adj Close SMA30'], label='SMA30')\n",
    "plt.plot(SMA100['Adj Close SMA100'], label='SMA100')\n",
    "\n",
    "plt.title('Apple Adj.Close Price History')\n",
    "plt.xlabel('July.14,2019-July.15,2020')\n",
    "plt.ylabel('Adj.Close Price USD($)')\n",
    "plt.legend(loc='upper left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#create a new DtatFrame to store all the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>SMA30</th>\n",
       "      <th>SMA100</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-07-15</th>\n",
       "      <td>50.606209</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-16</th>\n",
       "      <td>50.431118</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-17</th>\n",
       "      <td>50.147518</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-18</th>\n",
       "      <td>50.717182</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-19</th>\n",
       "      <td>49.960094</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-08</th>\n",
       "      <td>95.170906</td>\n",
       "      <td>86.661830</td>\n",
       "      <td>75.216789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-09</th>\n",
       "      <td>95.580170</td>\n",
       "      <td>87.201690</td>\n",
       "      <td>75.363867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-10</th>\n",
       "      <td>95.747368</td>\n",
       "      <td>87.745959</td>\n",
       "      <td>75.527425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-13</th>\n",
       "      <td>95.305664</td>\n",
       "      <td>88.278083</td>\n",
       "      <td>75.675068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-14</th>\n",
       "      <td>96.882820</td>\n",
       "      <td>88.830254</td>\n",
       "      <td>75.846746</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>253 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 AAPL      SMA30     SMA100\n",
       "Date                                       \n",
       "2019-07-15  50.606209        NaN        NaN\n",
       "2019-07-16  50.431118        NaN        NaN\n",
       "2019-07-17  50.147518        NaN        NaN\n",
       "2019-07-18  50.717182        NaN        NaN\n",
       "2019-07-19  49.960094        NaN        NaN\n",
       "...               ...        ...        ...\n",
       "2020-07-08  95.170906  86.661830  75.216789\n",
       "2020-07-09  95.580170  87.201690  75.363867\n",
       "2020-07-10  95.747368  87.745959  75.527425\n",
       "2020-07-13  95.305664  88.278083  75.675068\n",
       "2020-07-14  96.882820  88.830254  75.846746\n",
       "\n",
       "[253 rows x 3 columns]"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data= pd.DataFrame()\n",
    "data['AAPL'] = AAPL['Adj Close']\n",
    "data['SMA30'] = SMA30['Adj Close SMA30']\n",
    "data['SMA100'] = SMA100['Adj Close SMA100']\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CReate a signal to buy and sell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "def buy_sell(data):\n",
    "    sigPriceBuy = []\n",
    "    sigPriceSell= []\n",
    "    flag = -1\n",
    "    \n",
    "    for i in range(len(data)):\n",
    "        if data['SMA30'][i]> data['SMA100'][i]:\n",
    "            if flag !=1:\n",
    "                sigPriceBuy.append(data['AAPL'][i])\n",
    "                sigPriceSell.append(np.nan)\n",
    "                flag=1\n",
    "            else:\n",
    "                sigPriceBuy.append(np.nan)\n",
    "                sigPriceSell.append(np.nan)\n",
    "        elif data ['SMA30'][i] < data['SMA100'][i]:\n",
    "            if flag!=0:\n",
    "                sigPriceBuy.append(np.nan)\n",
    "                sigPriceSell.append(data['AAPL'][i])\n",
    "                flag = 0\n",
    "            else:\n",
    "                sigPriceBuy.append(np.nan)\n",
    "                sigPriceSell.append(np.nan)\n",
    "        else:\n",
    "            sigPriceBuy.append(np.nan)\n",
    "            sigPriceSell.append(np.nan)\n",
    "                    \n",
    "    return (sigPriceBuy, sigPriceSell)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Store the buy and sell data into the variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "buy_sell= buy_sell(data)\n",
    "data['Buy_Signal_Price'] = buy_sell[0]\n",
    "data['Sell_Signal_Price']=  buy_sell[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>SMA30</th>\n",
       "      <th>SMA100</th>\n",
       "      <th>Buy_Signal_Price</th>\n",
       "      <th>Sell_Signal_Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-07-15</th>\n",
       "      <td>50.606209</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-16</th>\n",
       "      <td>50.431118</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-17</th>\n",
       "      <td>50.147518</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-18</th>\n",
       "      <td>50.717182</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-07-19</th>\n",
       "      <td>49.960094</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-08</th>\n",
       "      <td>95.170906</td>\n",
       "      <td>86.661830</td>\n",
       "      <td>75.216789</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-09</th>\n",
       "      <td>95.580170</td>\n",
       "      <td>87.201690</td>\n",
       "      <td>75.363867</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-10</th>\n",
       "      <td>95.747368</td>\n",
       "      <td>87.745959</td>\n",
       "      <td>75.527425</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-13</th>\n",
       "      <td>95.305664</td>\n",
       "      <td>88.278083</td>\n",
       "      <td>75.675068</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-14</th>\n",
       "      <td>96.882820</td>\n",
       "      <td>88.830254</td>\n",
       "      <td>75.846746</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>253 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 AAPL      SMA30     SMA100  Buy_Signal_Price  \\\n",
       "Date                                                            \n",
       "2019-07-15  50.606209        NaN        NaN               NaN   \n",
       "2019-07-16  50.431118        NaN        NaN               NaN   \n",
       "2019-07-17  50.147518        NaN        NaN               NaN   \n",
       "2019-07-18  50.717182        NaN        NaN               NaN   \n",
       "2019-07-19  49.960094        NaN        NaN               NaN   \n",
       "...               ...        ...        ...               ...   \n",
       "2020-07-08  95.170906  86.661830  75.216789               NaN   \n",
       "2020-07-09  95.580170  87.201690  75.363867               NaN   \n",
       "2020-07-10  95.747368  87.745959  75.527425               NaN   \n",
       "2020-07-13  95.305664  88.278083  75.675068               NaN   \n",
       "2020-07-14  96.882820  88.830254  75.846746               NaN   \n",
       "\n",
       "            Sell_Signal_Price  \n",
       "Date                           \n",
       "2019-07-15                NaN  \n",
       "2019-07-16                NaN  \n",
       "2019-07-17                NaN  \n",
       "2019-07-18                NaN  \n",
       "2019-07-19                NaN  \n",
       "...                       ...  \n",
       "2020-07-08                NaN  \n",
       "2020-07-09                NaN  \n",
       "2020-07-10                NaN  \n",
       "2020-07-13                NaN  \n",
       "2020-07-14                NaN  \n",
       "\n",
       "[253 rows x 5 columns]"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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eeQalFI8++mjESdGsWbMYN24c7733XliGqDXbtm3jvvvu47777uPOO+/krLPO4tprrwWCwWXTE5qTTz65zcFNcXExr7/+OqmpqTz44INhwQ2Ay+UKZQQsy+KZZ54hLS2N++67LxTcQPB3dPfdd6NpGvPmzWvzcwO4/PLLI4K0Cy+8EAgWlmiNruvY7faIscO+K91tsWDBAsrKypg+fXpYcANwwQUXcMghh7B69WqWLl0acd/mfuennnoqWVlZvPTSS2HFEerq6pg3bx7p6ektTmGL5qWXXuKBBx7ggQce4NFHH+WNN95A0zTOPvtsxo4d265jRXPeeefhcrlC03cbNExfHTduXJsLsURb86Hreiir0VwlwLa+J5YsWcL69es58sgjw4IbCAZhQ4YMadM4G9x2221ceOGFlJeX8+CDDzJ9+nQGDRrE+PHjuemmmyKm45aXl/PSSy8xbty4sJN5CH433HHHHQDt/ky0RtM0nn/+eY455hhWrVrF7373O44//njy8vL4yU9+woMPPkhZWVmbjvXyyy+jaRp33XVX2NrL7OzsVi9UzJw5M2I92EUXXQREfnazs7OjZtdPOOEERo4cKVUhRa8gGRzR533xxResXbuWo48+OuyP8KmnnkpCQgL/+c9/+POf/0xiYmLEfSdNmhR1Ef5RRx3FkiVLWLlyJRMnTgy77eijj47Y32azceSRR1JYWMjKlStbPIFvCJq+/PLLqNNkiouLAVi3bh2jRo1q9jgNGqag/OIXvyA+Pj60fdasWdx7773MmTOHm2++OfQ8Gx4z2vOIj49n3LhxoavKna1hDntL07Lao+G5ND2JBUhPT2f06NEsW7aM9evXM3r0aE4++WT+9Kc/cfPNN/Pf//6X448/nsMPP5wxY8ZEvA+WLFmCzWbj7bff5u233444vs/nwzRNNm3axCGHHNKm8W7fvp0HHngAAMMwSElJ4cQTT+SSSy7hhBNOiNi/ucxjNN9++y2WZTFp0qRWg9QNGzZQWlrK4MGD+ctf/hJ1H7fbzfr169v8+EDU30NOTg5Am9Z5nH322TzzzDMcccQRzJgxg0mTJnHkkUcyYMCAdo2jpfcFwJQpU1i+fDkrVqzgyCOPDLutud+5zWbjwgsv5P777+c///lP6GLK66+/TlVVFZdeemnU9WQtefvtt0MnlX6/n23btvH000/z8MMP88knn/DBBx9EDfbaKjk5mTPPPDOUKTrmmGOA4AUh0zTblXEqKyvj8ccf58MPP2Tr1q3U1taG3d5cWfq2vida+l7SdZ2JEye2a32i0+nkscce4w9/+AP//e9/+e6771i5ciXLli3j2Wef5fnnn+evf/1r6ELYsmXLCAQC6LoedZ1Tw3TN9n4m2iIvL4933nmHtWvXsmjRIlasWMHy5ctDP//85z957bXXOPjgg5s9RlVVFVu2bCEzMzNqMNr0fd5Uez67SileeeUVXnzxRX744QcqKirC1mE5HI4WH0uI7iABjujzGhYfN87eQPAE7ayzzuK5557jlVdeiVqCNz09Peox09LSAKJene/IfRpruBr35JNPtrhf0xOI5jT3/HNycpg6dSoff/wxH330USjr1DC+hvE21dzz6wyZmZkAnTZHu+G5NDfmhoW5Dfvl5eWxcOFCHnjgAT766CPefffd0P0vu+wyfv3rX4eyGWVlZQQCgVBA0pz2zJs/+uijQ4/ZFu15LSorK4G2Zcca3oObN29u9fm1R7TAquH3GW0helP33nsvQ4YMYe7cuTz++OM89thj6LrOlClTuPvuu9vc2LC974vGWvqdX3TRRTz88MM899xzoc9bw1SghqxER9ntdoYOHcpDDz3EDz/8wFdffcUbb7zB2WefvV/HvfTSS3nxxRd57rnnOOaYYwgEAsydO5eEhARmzpzZpmNUVFQwdepUtm7dyoQJE5g1axYDBgzAMAwqKyt55plnml1j1db3RFd9L6Wnp3PuueeGXq+KigruuOMOZs+ezY033sgJJ5xAenp66DPREFQ0Z3/XybRkxIgRjBgxIvTvDRs2cNVVV7F06VKuvfbaFqctNxRU6ejvL9rr1BBcN/3s/v73v+fpp58mMzOT448/nqysrFC1vxdffFEKDYheQQIc0aeVl5czf/58AK6++uqIdRUNnnvuuagBzp49e6Lu35BFifal35H7NNZw++bNm9t9ZbqpNWvWhBaOn3baac3u99xzz4UCnIbHbxhvU809v84wadIkIHgSUVFRsd/rcBqey549e6Ieq2FKXOPXpKCggGeffRbTNPnxxx/59NNPefbZZ7nnnnuwLCvUOyghIQG/39+jf6zbk+lqyFC2pcFrw+/jpJNOCi3e7w0Mw+Cyyy7jsssuo6ysjMWLF/P2228zb948zjjjDJYuXUpycnKrx2n8vogm2vuiQUu/88zMTE499VT+85//8P3332NZVmjtREM/m84wYcIEvvrqK7799ttQgNOQYWwuUGwIcJs69NBDmTBhAm+//TYlJSUsXryYXbt2cckll0Ssc2rOnDlz2Lp1a9SSy0uXLuWZZ55p61NrVnd9LyUlJfHXv/6VhQsXUlhYyFdffcXpp58eevzLLruMBx98sFMea38NGzaMZ555hvHjx7Ny5UrKysqaff83ZO+7+vdXXFzM3//+d0aPHs0HH3wQNmsAghlNIXoDWYMj+rQXX3wRr9fLQQcdxPnnnx/1Jzc3l1WrVvH1119H3P+rr77CsqyI7V9++SUA48aNi7jtiy++iNgWCARCU8+i3aexhoW4DY+xPxrWF02aNKnZ55+YmMhHH30Uypo0THOI9jyqq6vbXcGtPfLz85k6dSr19fU89thjre7fWuWthufy2WefRdxWUlLC6tWriY2NpaCgIOJ2wzAYN24c11xzTahz/DvvvBO6/fDDD6e6uprvv/++1XH2BhMmTEDXdRYvXhy1PHZjw4cPJzExkWXLlnW4HHRXS05O5pRTTuGZZ57hrLPOoqSkJKwKXEuZoZbeF0DoSnhbpxY2dskllwDBz17D5+///u//2n2cljRMCWpclrghgC8sLIzYv7KyssVqYZdccgk+n4+5c+eGxnzxxRe3eTwNU8NOP/30iNuifY90REvfS5Zlhb32+0vX9VBw1/A7Puyww0Kfn96kaQDRnISEBAYNGkRRUVHUlgUdKbUdzZYtW7Asi6lTp0aMbceOHVFLsAvREyTAEX1aw/SsBx54gCeeeCLqzzXXXANELzawceNG/vWvf4Vtmz9/PkuWLKGgoCDqvOVPP/2UDz74IGzb008/TWFhIVOnTm11itBll12Gw+Hgtttui1py1jTNZk/MGquvr2fevHnous7f//73Zp//L3/5y7BiAz/72c9ISkrijTfe4Jtvvgk75oMPPtiuRfN1dXWsW7euXT2AHnzwQRISEnjsscf461//GrUUcXFxMTfddFOrVwPPO+88AB555JGwvjRKKe644w7q6ur4xS9+EVobsWzZsqj9axq2NW6q2JANvOGGG6JOqauvr+9VJ0OpqanMnDmT4uJifve730Wc+Hu93lC5V5vNxhVXXBH6PdfV1UUcr7S0tEuD3aa8Xi+ffPJJxAUHpVToqnTj16eh6EC0DNspp5xCcnIy8+fPjzhhfuGFF/juu+8YNWpU1KpfrTn66KMZPXo0r776Kq+99hq5ubn89Kc/bfdxmrN169bQmq+GNTMQDEoTEhJYsGBB2Hs4EAhw6623hhU+aOrMM88kOTmZp59+mkWLFjFx4kTGjBnT5jE1ZKeafi+tWLGi06plHXnkkRQUFLBkyZJQVr7Bv/71r3b3B7v//vubLXk/f/581q1bh81m44gjjgCCn59zzjmH77//nvvuuy/q99KOHTv2u89RU1u2bOGZZ56JmoFTSoUqQI4cObLV7OWsWbNQSvHHP/4x7HO0c+fOTsmywb73wldffRX2HVNTU8P111/f7tLyQnQVmaIm+qwvvviCdevWMXz4cI466qhm95s1axZ33XUXb775Jvfdd19YsYFp06Zx22238d///pcxY8awceNG3n77bdxuN0888UTU6Sonn3wyv/zlLzn99NMZNGgQK1eu5L///S/JycmhP0YtKSgo4G9/+xtXX301kyZNYtq0aQwdOhTTNNmxYwdLlizB6/Wybdu2Fo/TUFxg2rRpLU6Pueiii/jb3/7G3Llzufnmm4mLi+Oxxx7j4osv5pRTTuGMM84gOzubxYsXs2rVKo466qg2Z5eWLVvGaaedRl5eXpszHQUFBbz55ptccMEF3HXXXfz9739nypQpZGdnU19fz5o1a/jyyy/x+Xwcf/zxLR7riCOO4De/+Q2PPPIIkyZNYsaMGSQkJIQW6o4ePZrbb789tP+rr77Ks88+GyqjnZyczPbt21mwYAG6rnPdddeF9p08eTJ/+tOfuPPOO5kwYUKor0h9fT3bt2/nyy+/ZODAgV1WkKEjHnzwQdasWcMLL7zA4sWLOf7444mNjaWwsJCFCxfypz/9KbSo+uabb2bVqlXMnj2bDz/8kMmTJ5OTk0NJSQmbN2/mq6++4pJLLmk1I9lZPB4PM2bMIDc3l8MPP5y8vDz8fj+ff/4533//PYcddlhY0YCpU6eybNkyzj//fH7605/icrnIy8tj1qxZxMbG8re//Y0LLriAGTNmhD6rP/zwAx9++CGJiYk8/fTTHS528atf/SrUff6GG26IWqikLRqXiQ4EAmzfvp13332X2tpaTjrppLCqbHa7nWuvvZZ7772XyZMnh6akfvbZZyilGDt2LD/88EPUx3E6nZx//vmhrGl7M06zZs3i8ccf5/e//z2ff/45Q4cOZePGjXzwwQecdtpprZbGbwtN03jiiSc444wzuPjiiznttNMYOnQoP/74I4sWLWLatGktNi5u6m9/+xv3338/48aN49BDDyU1NZWqqipWrFgRqp539913h1VffPDBB9m0aRMPPPAA8+bN46ijjiIjI4OioiI2bNjA119/zb333rvfvY4aq6qq4ne/+x133HEHRxxxBKNHjyY+Pp7i4mI+/fRTtmzZQlxcXJsCyeuvvz5U7nnjxo0cd9xx1NTU8J///IdJkybx7rvvdvi92iAjI4OzzjqL119/nWOPPTbUp6qhv9lBBx3UZ7Leon+TAEf0WQ2lTy+44IIW90tKSuL000/nlVdeYd68eVx22WWh2yZMmMBvf/tb7rnnHv7xj38AwROn22+/vdnpK6eeeioXXXQRDz30EO+//z52u53p06dz5513trmU6cyZMxk7dixPPfUU//vf/0J/HDIzM5k2bVpEmdT9ef7Dhw9n0qRJLF68mI8++oiTTjqJ6dOn8/rrr/PAAw8wf/58HA4HRx11FB999BGPPvpop0yfa8n48eNZunQpc+bMYcGCBXz88cdUVFTgdDrJz8/noosu4sILL2xTFbk77riDcePG8Y9//INXX30Vr9dLfn4+N910E9dff33YNIqZM2fi9/tDV4nr6urIyMjgxBNP5Oqrr44omXvttdcyceJEnnnmGRYvXsz7779PXFwcWVlZ/PznP2+1r0t3S0pK4oMPPuDvf/87r7/+Oi+88AIAWVlZnHbaaaE1UBDM4syePTu030cffURNTQ3Jycnk5eXx61//mlmzZnXb2GNjY7n77rv57LPP+Prrr3nvvfdwu93k5+dzzz33hJqQNrjxxhupqqpiwYIFPPbYYwQCAY4++ujQmE866SQ+/PBDHnnkEf73v/8xf/580tLS+MUvfsFvf/tbBg0a1OGxnnPOOfzud78D4Pzzz+/wcV566aXQ/2uaRkJCAuPGjeOcc87h/PPPjwjAbrrpJtxuN8899xzPP/98aBrf7bffHspmNue8887jscceIyUlpU3fL41lZWXx3nvvcdddd/HVV1+xcOFCCgoKePjhh5kyZUqnBDgAEydO5L333uNPf/oTH3/8MR9//DETJkzgnXfe4eOPP25XgDNv3jw+/vhjvvjiCz7++GOKi4vRNI2srCzOOeccfvWrX4WyNw3i4+N55513mDNnDq+++irvvPMO9fX1pKWlMXDgQO64446wUvydYcSIEbzwwgt88sknLF26lPnz51NaWorb7WbgwIFcddVVXHnlleTl5bV6LLfbzdtvv82f//xn3nrrLZ5++mny8/P59a9/zVFHHcW7777bKW0AnnjiCQYNGsQbb7zBs88+S2pqKieffDK///3v9+vzIERn0ioqKlTruwnRv7zwwgtcffXVURfNNue+++7jgQce4KmnngpdBT9Q1NfXk5mZyXHHHddpJzNC9FVLlizhxBNPZMaMGRE9ZnqrV199lUsvvZTrrruOu+++u6eHI7rZ888/z/XXX89vfvObUE8fIfozWYMjhGhVQ++Hhr4IQhzIHnnkEYColRl7I9M0efzxxzEMo9MLIojeJVoVxcLCwlC/q2iFIoToj2SKmhCiWVu3buXf//53qLpYe6e2CNFf/PDDDyxYsICVK1fywQcfcNxxx0VtStmbfPHFF3z22Wd8+eWXfP/991x88cX7NTVP9H7/93//h8fj4ZBDDiExMZFt27bxwQcfUFdXx+WXX96hyoFC9EUS4AghmtXQWX3IkCE88cQTTJs2raeHJESPWLFiBX/+859JSEjg9NNP5+GHH+7pIbXq008/5YEHHmDAgAFccMEF3HvvvT09JNHFzjnnHObNm8e7775LRUUFbrebgw8+mAsuuIBf/OIXPT08IbqNrMERQgghhBBC9BuyBkcIIYQQQgjRb0iAI4QQQgghhOg3JMARQgghhBBC9Bu9MsBpKEkr+jd5nfs3eX37N3l9+x95Tfs3eX37N3l9w/XKAEcIIYQQQgghOkICHCGEEEIIIUS/IQGOEEIIIYQQot+QAEcIIYQQQgjRb9h6egBNBQIBHA4HlZWVPT0U0YLY2Fhstl739hFCCCGEEAe4XnWGGggEqK6uJj09Hbfb3dPDEc1QSlFRUUF8fLwEOUIIIYQQolfpVVPUamtrSUpKQtO0nh6KaIGmaSQlJVFbW9vTQxFCCCGEECJMrwpwAAlu+gh5nYQQQgghRG/U6wIcIYQQQgghRO9gWoq6gNXTw2gXWUAhhBBCCCGEiKrIY/FlkZdYm0aa2yAn1iArxujpYbVIAhwhhBBCCCFEVMX1JgC1AUVtdQBDo9cHODJFrROtWLGC5ORkTjzxxA7vk5SUFPrJzc3lJz/5CW+99Vbo9vvuu49JkyZ1+tiFEEIIIYRoqtgTPj0tzdX7w4feP8I+ZPbs2fzqV79i9erVrF27tsP7PP7446xdu5aFCxcyduxYLrroIpYuXdqVQxdCCCGEEAcwn6nwWypiW4WvSYDj7t3ZG5AAp9N4PB5effVVLrzwQk4//XTmzJnToX0AEhMTycjIYPjw4Tz66KO4XC7ee++9rn4KQgghhBDiAFNUZ/LFbi9vbfXw1hYPn+3ysq0mgGkpSurDg5sEu47T6P2VdPvEGpzXNtV16+PNHBLT7vvMnz+fvLw8xo4dyznnnMPFF1/MnXfeid1ub9c+Tdntdmw2G36/v0PPRQghhBBCiKaUUnxb4mdzdWDfNqDIY1LkMbHrGq4mwUy6u2/kRvrGKPuA2bNnM2vWLACOOeYY3G43CxYsaPc+jXm9Xv7yl79QVVXFlClTum7wQgghhBDigBEtuGnKbymq/eEZnNQ+sP4GJMDpFJs2bWLJkiXMnDkTCDbBPPvss8OmoLVlnwaXX345OTk5ZGVl8dRTT/GnP/2JE044oXuejBBCCCGE6NfWVgZaDG6a0xfW30AfmaLW282ePRvTNBk7dmxom1LBRVqFhYXk5ua2aZ8Gd999N9OmTSM+Pp60tLRuehZCCCGEEKK/U0qxtiI8uHEZGhMzHNg0ja01AbbVmHjN8IIDyc6+sf4G+kiA05E1Md0lEAjw0ksvceedd0aUfr788st54YUXuPHGG1vd55Zbbglty8jIYMiQId0yfiGEEEIIceCoDYRXS7NpGpOznCQ4ghO7kpwOxiUrdnsstlYHKPJYOHQ4JKX5NeO9TZ8IcHqzDz74gNLSUi688EKSk5PDbjvrrLP417/+xdixY1vd5+abb0bX2zZjsL6+npUrV4Zti4mJYdiwYfv3ZIQQQgghRL9W4Q1fVzPAqYWCmwaappEVY/T6hp7NkTU4+2nOnDkce+yxEYELwIwZM9i+fTuXXHJJq/t88sknbX7MzZs3M3ny5LCfSy65ZH+ehhBCCCGEOABU+sKnniU6+l84IBmc/fTyyy83e9ugQYOoqKho8f5N92lt/1tvvZVbb721HSMUQgghhBAiqLJJ484kZ/8LcPrfMxJCCCGEEEJEVdEkwOmPGZz+94yEEEIIIYQQEfyWoi6wb4qaBiTY+0ZltPaQAEcIIYQQQogDQNPpaXF2HUPvfwGOrMERQgghhBCiH6vwWnxd7Itcf+Pof8ENSIAjhBBCCCFEv+W3FJ/v9lLfpHEnQGI/LDAAMkVNCCGEEEKIfmtlqT9qcAOQ1A8LDIAEOEIIIYQQQvRLezwmm6sDzd7eHyuogQQ4QgghhBBC9DsBS7Gs2Nfs7XmxBm6brMERQgghhBBC9AE/lPmpDYRPTftJthMAnwlZMf03zyEBjhBCCCGEEP1Iab3JhqrwqWnDEmykuoweGlH36r+hWzcrKSnhxhtv5KCDDiI9PZ2CggJOP/10Fi1aBMApp5xCUlISf/nLXyLue9FFF5GUlMTNN98ccduKFStITk7mxBNPjLjNsixmzZrF2LFjycjIYMSIEVx22WXs3LkzbL/t27dzzjnnkJ2dzZAhQ/jtb3+Lz9d8ylIIIYQQQvRNllJ8U+wP2xZj0xibbO+hEXU/CXA6yfnnn8+yZct48skn+eabb5g3bx4nnHACZWVloX1yc3N54YUXUGpfurCsrIz33nuP3NzcqMedPXs2v/rVr1i9ejVr166NuH3y5Mk899xzfP3118yePZstW7Zw3nnnhW43TZNzzjmHmpoaFixYwL/+9S/eeust/vCHP3TisxdCCCGEEL3BqvIA1f7wfjcTUh3Y+mFDz+bIFLVOUFFRweLFi3nzzTeZMmUKAAMHDmT8+PFh+02bNo13332Xzz77jMmTJwMwb948JkyYgKZFvuk8Hg+vvvoqCxYswOPxMGfOHO65557Q7bquc9VVV4X+PXDgQG644QbOPfdc6uvrcblcLFy4kNWrV/P999+Hgqg//vGPXHfdddx+++0kJCR0+u9DCCGEEEK0zQ9lfgprA2S4DQ5JsUc9J2yrCq/F2orw7M3geBsZMQfG1LQGfSLAsS3+uFsfLzDp+HbtHxcXR1xcHAsWLGDixIm4XK6o+9ntdmbNmsXcuXNDAc7cuXO55pprmDt3bsT+8+fPJy8vj7Fjx3LOOedw8cUXc+edd2K3R08xlpeX8+qrr3LYYYeFxrB06VJGjBgRliE6/vjj8Xq9LF++PDQOIYQQQgjRvXbVmazZG5DU+AMk2HWGJnbs9Dw4Nc1H47ICLkPjoANoaloDmaLWCWw2G0899RSvvPIK+fn5nHDCCdx222188803Efued955vPPOO1RVVfHdd9+xfft2pk+fHvW4s2fPZtasWQAcc8wxuN1uFixYELHfnXfeSXZ2NoMHD6awsJB58+aFbtuzZw9paWlh+6ekpGAYBnv27Nmfpy2EEEIIIfbDuorwQgAry3ysqfDzyc561jXJxDRmKcWKUh+f7vKypsKPz4J1lQEqfOFT08anOnAYB87UtAYS4HSS6dOns2bNGl5++WWmTZvG0qVLmTZtGg8//HDYfiNGjGDs2LG8/vrrzJkzhzPPPJOYmJiI423atIklS5Ywc+ZMADRN4+yzz2bOnDkR+1533XV8+umn/Oc//8EwDC677LKwdT7NpTr3JwUqhBBCCCH2T9OAxFTBKWsl9RYry/zsrjOj3m9lqZ/1lQH2eEx+KPOzqNTgh7LwgCgv1iA79sCamtagT0xR6ytcLhdTp05l6tSp3HLLLVx77bXcf//9XHvttWH7nXfeeTz77LNs2bKFN954I+qxZs+ejWmajB07NrStIWgpLCwMm3KWkpJCSkoKw4YNY/jw4YwZM4bFixdz1FFHkZ6ezpIlS8KOXVpaimmaEZkdIYQQQgjRPSylMC3V4j7bagJkNlk/U+O32NSkBHRTDl3jkFTHfo+xr2pTgFNdXc29997LO++8Q0lJCePGjeP+++8PLaJXSnH//ffz/PPPU1FRwYQJE3jooYcYNWpUpwyyvWtieosRI0YQCASor68P237GGWdw6623MnDgQA477LCI+wUCAV566SXuvPPOiPLQl19+OS+88AK33HJL1Me0rOCVgIYy0EcccQQPPfQQO3bsICcnB4BFixbhdDo55JBD9vcpCiGEEEKIDqj0KaxW9in3RgZAq8sDrd7vkFQ7zgNwalqDNgU41113HT/++CNPP/00OTk5zJs3jxkzZvDVV1+RnZ3NY489xlNPPcVTTz1FQUEBDz74IGeccQZff/018fHxXf0celxZWRkXXngh5513HmPGjCEuLo7ly5fz+OOPM2XKlIhKZfHx8axatQrDiJ42/OCDDygtLeXCCy8kOTk57LazzjqLf/3rX9x888188803rFixgokTJ5KYmMjmzZv585//zMCBA5k4cSIAxx13HKNGjeKKK67gnnvuoby8nDvuuIMLLrhAKqgJIYQQQvSQsvrWwpRIlT6LrTXNZ290oCDJzsC4A3uSVqvP3uPx8NZbbzF79myOPfZYAG699Vbef/99/v3vf/OHP/yBp59+mhtuuCG0WP7pp5+moKCA1157jYsvvrhrn0EvEBsby+GHH84zzzzDpk2b8Pl8ZGVlMXPmzKjNOwESExObPd6cOXM49thjI4IbgBkzZnDXXXfxySefkJqayvz58/nzn/9MbW0tmZmZTJs2jX//+9+hKmqGYTBv3jxuuukmTjrpJFwuFzNnzgwrNy2EEEIIIbpXua/1AKfWb6GUCq2bXlkavs4mwa5zQq6TNX6TYYPcGBrossa69QAnEAhgmmZE6WO3283ixYvZunUrRUVFHHfccWG3HXXUUSxZsuSACHCcTid33HEHd9xxR7P7vPvuuy0eo/HtL7/8crP7DRo0iIqKitC/33nnnVbHl5eXF1ZZTQghhBBC9Ky2ZHAsoC6giLVr7Kw1KfKEFx0Ykxzsm2PTwX4ANfJsTasBTnx8fGgdx6hRo8jIyOC1115j6dKlDBkyhKKiIoCIBetpaWns2rWr2eOuX78+YpvL5cLpdAJErFsRvU9VVdV+l5qO9j4Q/Ye8vv2bvL79j7ym/Zu8vr1HQMH6EoOWSwwErfSYJNvh8zIDT6OYaIBdUWdaNLyqB9rrW1BQ0OxtbZqg9/e//52rr76a0aNHYxgGBx98MDNnzmTFihWhfZqWHG6cTmvroCorK3G5XNTX1zfbLFP0HgkJCeTl5XX4/uvXr2/xzSn6Nnl9+zd5ffsfeU37N3l9e5dij0mGzdumfTNSHfgsRaLNT8MCBw04PsdFkjPY8UVe33Bt6oMzePBgFixYwI4dO/jxxx9ZuHAhfr+f/Px8MjIyACKu5JeUlEgZYiGEEEIIIZpoWuY5N9YgJ9aIemJe7DFZUx6+/5AEWyi4EZHa9ZuJjY0lMzOTiooKPv74Y372s5+FgpxFixaF9quvr2fx4sUceeSRnT5gIYQQQggh+qoKr8X22vC1NLmxBpMynJwx2M0R6eH9a7bXmgQaNXC36xqjB9i7Zax9VZumqH388cdYlkVBQQGbN2/m9ttvp6CggF/+8pdomsaVV17Jww8/TEFBAcOGDeOhhx4iNjaWmTNndvX4hRBCCCGE6DN+LA+vhJbo0MmJDbYO0TSNOFvLxQLGDjiwe9y0RZsCnKqqKv74xz+yc+dOBgwYwOmnn85tt92G3R6MHq+//no8Hg8333xzqNHnG2+8cUD0wBFCCCGEEKItyupNdtU1qYQ2wB62bj3O3vwEq0SHzpCE6H0Uu0xtNcamNZjDRoM7tnsfu4PaFOCcccYZnHHGGc3ermkat956K7feemunDUwIIYQQQoj+5Icma2mSnTrZseEBi8PQsOsafiuyxtohKfYWi3h1OjOAsf57NI8H28qlmIOGozJyuu/xO0hWJwkhhBBCCNHF9nhM9jTpYzM2Ofpamnh7ZBCTG2uQ5u6+7I1WWYaxZjmaxxPcYFkYm9ZAdUW3jaGj2pTBEUIIIYQQ4kBSVGfybYkPgPGpDjJi9i+4+LEsfO1NmssgvZmAJdamUdaoirShwbiUbigsYFlopUXoO7eh1dVE3pyRA/FJXT+O/SQBjhBCCCGEEE0sK/FRFwhOE/u2xMfJA90t7r+mws+qMj82XSPDreOyaZgWJDl1XIZGqdcK239scvOn4akuI6zS2ogkOzG2Lpx4ZVlou7ah796O5vNF3UW5Y7Dyh3XdGDqRTFHrJCUlJdx4440cdNBBpKenU1BQwOmnnx4qn33KKaeQlJTEX/7yl4j7XnTRRSQlJXHzzTdH3LZixQqSk5M58cQToz7uQw89xIknnkh2djZJSUlR99m+fTvnnHMO2dnZDBkyhN/+9rf4mrx5f/zxR372s5+RmZnJqFGjeOCBB1CqLf11hRBCCCH6l1q/FQpuAGoDKuqamAZ1AYsfy/xYgM9SbK81WV8ZYFN1gG9LfHxZFN7UMyvGIMXVfEZoUHywL45d1xgUb2NkUhfmJJTCWLsCY9vG5oObhETMUYeA0TdyI31jlH3A+eefj8fj4cknn2Tw4MGUlJTwxRdfUFZWFtonNzeXF154gZtuuim0QKysrIz33nuP3NzcqMedPXs2v/rVr5g3bx5r165lxIgRYbd7vV5OPfVUjjnmGB5++OGI+5umyTnnnMOAAQNYsGAB5eXlXHnllSilQsFWVVUVZ5xxBkcddRQLFy5k/fr1XH311cTExHDttdd21q9ICCGEEKJPqPRFBjP1psKuR1/gX1pv0Z7LwmNa6WNj6BqTMpztOGLH6YWb0SrKot5mpaRhZQ3sE9PSGpMApxNUVFSwePFi3nzzTaZMmQLAwIEDGT9+fNh+06ZN49133+Wzzz5j8uTJAMybN48JEyZErYjh8Xh49dVXWbBgAR6Phzlz5nDPPfeE7fOHP/wBgPnz50cd28KFC1m9ejXff/99KIj64x//yHXXXcftt99OQkICr776Kh6Ph6effhq3283o0aNZt24df/vb37jmmmu6t1qHEEIIIUQPq/RZEdvqA4r4ZuKSqigBUXNyYw2SnL1jEpVWVY6+Y3PYNmUYqLQsrKw8cMX00Mj2T58IcAK7F3Xr49kyp7Zr/7i4OOLi4liwYAETJ07E5XJF3c9utzNr1izmzp0bCnDmzp3LNddcw9y5cyP2nz9/Pnl5eYwdO5ZzzjmHiy++mDvvvDPUf6gtli5dyogRI8IyRMcffzxer5fly5czefJkli5dyqRJk3C73WH73HvvvWzdupVBgwa1+fGEEEIIIfq6qAGO2XwQ03T/WJtGklNnR2141TQNGN1K9qbb+H3o63+gcepJ2R2Y444AR/dkj7pK7wgf+zibzcZTTz3FK6+8Qn5+PieccAK33XYb33zzTcS+5513Hu+88w5VVVV89913bN++nenTp0c97uzZs5k1axYAxxxzDG63mwULFrRrbHv27CEtLS1sW0pKCoZhsGfPnmb3afh3wz5CCCGEEAeKaFPUvO0IcCZmOJmU4eSIdEfY9kHxNhIcveP0W9+4OmLNjTVsdJ8PbkACnE4zffp01qxZw8svv8y0adNYunQp06ZNi1gXM2LECMaOHcvrr7/OnDlzOPPMM4mJiUz/bdq0iSVLljBz5kwg2Ez17LPPZs6cOe0eW3NTzBpvb7pPQ4EBmZ4mhBBCiAOJaSlq/JEZnCYtbEIClqI2EB78JOztYzMwzsaR6Q5SXTpDE2wcmto7sjfarm3o5SVh26ycfFRSSg+NqHP1iSlqfYXL5WLq1KlMnTqVW265hWuvvZb7778/YqH+eeedx7PPPsuWLVt44403oh5r9uzZmKbJ2LFjQ9sago7CwsJmixI0lZ6ezpIlS8K2lZaWYppmKEuTnp4ekakpKQm+6ZtmdoQQQggh+rMqv4paMKC5DE5Vk+xNnF3DaFSMIC/ORl5cLzrlrqnC2LYhbJOKT8TKHdJDA+p8vei33bz2ronpLUaMGEEgEKC+vj5s+xlnnMGtt97KwIEDOeywwyLuFwgEeOmll7jzzjsjykNffvnlvPDCC9xyyy1tGsMRRxzBQw89xI4dO8jJyQFg0aJFOJ1ODjnkkNA+d911F/X19aH1Q4sWLSIrK4v8/Pz2Pm0hhBBCiD4r2vobAE8geoDTdDpbgr0XT5AKBDA2/ACNSl4rm4FZMAb0Xjzuduo/z6QHlZWVcdpppzFv3jx++OEHtmzZwptvvsnjjz/OlClTSEhICNs/Pj6eVatW8dFHH0U93gcffEBpaSkXXngho0ePDvs566yzmDt3LpYV/PBt376dlStXsm3bNgBWrlzJypUrqakJdp897rjjGDVqFFdccQUrVqzgk08+4Y477uCCCy4IjWvmzJm43W6uuuoqVq1axVtvvcVf//pXrrrqKpmiJoQQQogDSoU3eoDTXAanaUCU2EvW2ERQCn3TKjSPJ2yzNWQ0OFtuYtrX9IkMTm8XGxvL4YcfzjPPPMOmTZvw+XxkZWUxc+bMqM07ARITE5s93pw5czj22GNJTk6OuG3GjBncddddfPLJJxx33HH8+c9/5qWXXgrd3lCd7e233+bYY4/FMAzmzZvHTTfdxEknnYTL5WLmzJlh5aYTExP5z3/+w0033cTUqVNJSkri6quv5pprrunor0QIIYQQok+KVmAAmq+i1nT/REfvvDisb12PXlocts3KyEGlpPfQiLqOVlFR0Wva1VdWVpKYmBg2VUr0Xg2vV0etX7+egoKCThyR6E3k9e3f5PXtf+Q17d/k9W27t7Z48FmRp8cacOZgd8Tslre3esKyOz/NdXV7pbSor69SaNUVaOUlwR9PXfjNMbGYBx0OutGNI+0eksERQgghhBCC4DS0aMENBNvFeE1wNTp7Xl/pDwtudCDe3oMZnIAfraI0GNBUlKIFAlF3Uw4H5siD+2VwAxLgCCGEEEIIARC1PHRj9abCZdNQSrGi1M+GqvAAItml98j6Zc3vQ1+7Er28mKgl4BpRhoE58pB+t+6mMQlwhBBCCCGEAKr9LUcHXlNhWoqlxT521IY3xtGAMQN6oM+Nz0v8ltXoAwa0vJ8GKjEZc+AwiI3vnrH1EAlwhBBCCCGEoPUAp9JnsarcT2mTSms2TWNShoM0dzdP+fJ5MVZ9i+Gtj3qzsttRSSmoAamoxBSwHRin/gfGsxRCCCGEEKIVTaeoOXQtbE3OyjJ/xH1chsYxmU6SnN1cHtrnxVj9XWTxALcblZyOlZQK8YlwALb8kABHCCGEEEIIoLpJyedUl87OOrOZvYNNPY/JchBj6+bgxu/DWL0cra42bLM1IBVr+EH9qmlnRxzYz14IIYQQQghAKRWRwUlzN3+qnObS+Um2s/uDm4A/mLmpqwnbbA1IkeBmL8ngCCGEEEKIA15tQNE4vHHoGgn26MFCdozBxAwHendO/7IstIoS9O2bI4Ibf1ySBDeNSIAjhBBCCCEOeDVNCgwkODScRmQAY9M0xqd2Y3BTW41evAutZDeaP3INkEpKpiY5pt/2tOkICXCEEEIIIcQBr7rJ9LQ4u44rSoAzPMmGy9b1wY1WvAt91za02ppm91EJSZgjxsHGTV0+nr5E8lhdYOvWrSQlJYV+0tPTmTBhAk888UTYfldeeSXnnHNOxP0/++wzkpKSKC0tZfbs2eTm5rJly5awffbs2cPQoUP561//2oXPRAghhBDiwNA0gxNn13AaENsomHEaGsMTuzg/oBT65rUYG1a1GNxYA1IxRx4smZsoJIPThV5//XXGjh2L1+vl008/5YYbbiAnJ4czzzyzzce44IILWLBgAVdeeSXvvvsu+t65lb/+9a8pKCjguuuu66rhCyGEEEIcEKr9FiX14RmceLuOpmkcluZgRakfXYPxqQ5sehdmb5RC37gKvXh39JttNlRqBlZaNsQldN04+jjJ4HSh5ORkMjIyGDhwIOeddx5jx45lxYoV7T7O448/zrp163jqqacAePnll/nf//7HM888Ewp4hBBCCCFE2yml2FFr8ukuLx9sr6fS1zTACQYyaW6DabkujstxdXmvG33TmqjBjUpKxhw+FnPCMViDR0pw04p+e3aslOLW/92KUi13pO2usXz11VesW7eOCRMmtPv+6enpPProo9x777188skn3HLLLdx7770MGjSo8wcrhBBCCNGPKaVYU+Hn3W31LC7ysscT2efGoWvE2bu3Qaa+bSP6np1h25TdQWDcEZijDkWlZMh0tDbqt1PU5q+fz5wf5jAxeyLTC6b3yBh+9rOfoes6Pp8Pv9/PlVdeyemnn96hY51++um8++67nHnmmUybNo0LL7ywk0crhBBCCNH/rSzzs74y0OztDj04La07S0Bru7ej79gStk05nZijx4MrptvG0V/0ywyOUoonv32SGn8NTyx7oseyOP/85z/57LPP+Pzzz3nuued4/fXXueeeezp8vFtuuQXLsrj55ps7cZRCCCGEEAeOwprIjA1AilPn8DQHpwx0kR3bfZkSrWQ3xuZ1YduU3Y456lAJbjqoX2Zw5q+fz6qSVQCsKlnFWxve6pEsTk5ODkOGDAFgxIgRbNmyhXvvvZebbroJl8tFfHx8RHU0gMrKSnRdJy4uLmy7YQQ/bDZbv3zZhBBCCCG6lN9SeMzwC99D4m0MSbB1+fqaaLSKUoyNq8I36nqwOpo7ttvH01/0uwxOQ/amLlAHQF2grkezOI0ZhkEgEMDn8wFQUFDAmjVr8Hg8YfutWLGCvLw8nE5nTwxTCCGEEKJfqoooJKAzPs3RI8ENNVXo674Hq9E5qkawr01cYvePpx/pdwFO4+xNg4YsTncrKyujqKiIHTt28NFHH/HMM89w7LHHkpAQrHxx9tlnY7PZuOKKK1i+fDmbNm1i7ty5PPPMM1L+WQghhBCik1X6wi94Jzq6t5AAfh9aUSHGj8uwff81mhk+Xc4cOhqVlNK9Y+qH+t1cp88KP+OQjEPQ2PeGVSg+2/5Zt09TO+uss4Bg5iYzM5MTTjiB22+/PXR7YmIi7733HnfddRe/+MUvqKqqYvDgwdx7772cf/753TpWIYQQ3ctnKhTBxoFCiO7RNIOT4OiGa/2WiVZShF5ahFZZBs1MKjIHFaDSsrp+PAeAfhfgPHzcwz09BPLz86moqGjTvsOGDWPu3LmdflwhhBC917aaAMuKfZgKxgywM2qAvaeHJMQBoWmvm8SuDnC89Rirv0Pz1LW4m5WTj8oa2LVjOYD0uwBHCCGE6O2+L/XTsM75x3I/SU6drBjpbyFEVzAtxbrKAHUBRXF90wxOF2ZQvR6MH79F89Y3u4uKjcPKGiiZm04mAY4QQgjRjeoCVkQVpy92exmbbCferpMdo6N1Y/8NIfozSym+KPJFbeZpaBBn66LPms/bbHCjYmJRKRlYKRngljLQXUECHCGEEGI/WUrxfZmfar9iWIKNzBayMWVNriA3+KHMD0C62+CoDAc2XYIcIfbXN8XRgxsIrr/pkosJgQDG6uURwY2VnIaVNwRi4pq5o+gsEuAIIYQQwPaaADtrTWLsOlkxOinOtp/8rCz1s6Eq2Bm92GNyQq6LOHv0uf1l3ugBToM9HpNPd3k5JtOJo0kBgtJ6k3WVAVyGxthkO3YJgoSISinFdyV+tjXT1BO6aP2NZWGsW4lWVxO+OTUDa9gYkOxst2j1lTVNk3vuuYdx48aRkZHBuHHjuOeeewgEAqF9lFLcd999jBw5kszMTE455RRWr17dpQMXQgghOktpvcmSPT6215qsrfDzyU4vi3Z68Zmt91DzmSoU3ACYCrZUN39SVd5KgAPBIOiTnV48gX2P7zMVX+z2saPWZGNVgK/3+Fo9jhAHIksplu7xsak60OJ+CfZODjaUQt+4Cq2yPHw8A1IluOlmrQY4f/3rX3n22Wd54IEHWLp0Kffffz///Oc/eeSRR0L7PPbYYzz11FM88MADLFy4kLS0NM444wyqq6u7dPBCCCFEZ9ge5SpvmddiW03LJ0gAW6KcRG2Nsq0+oKjxW5R7w4Om3FgjaoGBKr/FJzvrqfEHA6KddSa+Rg0Bd9aZVLQhWBLiQOI1FZ/u8rK9tvmLDA06u0S0vm0DeklR2DYVn4g1fKwEN92s1SlqS5cu5aSTTuLkk08GgqWKTz75ZJYtWwYEszdPP/00N9xwA9OnB/vMPP300xQUFPDaa69x8cUXd+HwhRBCiP1X0sy6mCpfyxkcpRQbqyKDGY+pKKk3sesaO2pNdtaaVPgiH8Oha0zMcALgtxRf7vaGVXmqDSg+2enl2Cxn1Kk2ayr8ofsLcaCr8Fp8WeSlLhD+uXUZGsdmOVlT7g8FPg5dI9XVeQGOVrwLfee2sG3K7cYcMQ50qZDY3Vp9ZSdOnMjnn3/OunXrAFizZg2fffYZJ5xwAgBbt26lqKiI4447LnQft9vNUUcdxZIlS7po2EIIIUTn8FsqojdGg9pAywHOrjqr2X0+2+Xlo8J6VpX7owY3AMmNTrDsusYxmc6IbE69GQxyiqMslC6sNSMaFwrRF/gtxdZqP79ZeBdKtT4VtDWFNQEW7ayPCG7i7BpTs50kOnQOS3MwIslOXqzBsVnOTivkoVWVY2wKX5qh7A7MUYeC3dEpjyHap9UMzg033EBNTQ1HHnkkhmEQCAS46aabuOSSSwAoKgqm4tLS0sLul5aWxq5du5o97vr16yO2uVwunM7glaj6+uZrhoveoaqqij179uzXMaK9D0T/Ia9v/9ZfXt8SH+yqjH6FtcZQZNZEDyCUgi/LdWrMjp8kxcZYrK8OPyFLVbC7WmeXt23HXVihGBPfOUFOf3lNRXS95fW19n52lpT8yH+2bSFVzeXg5EkU1us4dUWGU5HpVMQ1c5YasMBrgQm4ddjq0dhYF3nNPtmuyEuw2Lll3zbX3p+SKijZj+egmQEclaU4youxeWrDblO6TvXg0ZjbCvfjEdqvt7y+3aWgoKDZ21oNcN544w1efvllnn32WUaOHMn333/P7373OwYOHMgFF1wQ2q9ppRmlVIvVZ6INqrKyEpfLRX19PS6Xq7Wh9Stbt27l4IMPZtGiRRx66KER/+6NEhISyMvL6/D9169f3+KbU/Rt8vr2b33h9TUtxc46kzi7zgBn8xMW6sv8ZLr9UW+z6xoFg9xRb1tX4SfO5md/Cr4eEiVjAzBcKZaX+qNOf4sYo6FRkB99jO3RF15T0XG96fXdXhMgzvCyZP1zeC0fr+5aS8GgM0lJDJ431gIbCVY5y401yIsziLPreAKKb0t87Kprks20Q2ZC+KZhCTbGpdjRO3nti1ZZhrZnJ3plMVgWJCYEfxoxh40mrZsbd/am17c3aDXAueOOO7jmmms466yzABgzZgzbt2/n0Ucf5YILLiAjIwOAPXv2kJubG7pfSUlJRFanPyspKeG+++7jww8/pKioiMTEREaNGsWvf/1rpk6d2tPDE0KIPq/Ca/FjuR8FZLkNcmINXM006av2W3y2a99c/DSXwcEpdpKiBDql9c0vRvZbioClIqay1AUsVpWHBx8D4wxibTqrK/YFSzqQ5jbIjTVwGhpfFXmxGt2W3EzgpWkah6Y6sOsaayqiB18AKItArQdPlR+3yxmcDiOLmUUvV+yxWLZ7GTuqgxmOHdWFLCv6lsMyJ4TtV+mzqPQFP/cDnDr1ARXRJLcpDTg01cGQhE7uhGJZ6BtXRRQRiNgteyCqm4MbEanVV7+urg7DCL+6ZBgGlhX8is7PzycjI4NFixYxfvx4IDi9bPHixdx9991dMOTe6fzzz8fj8fDkk08yePBgSkpK+OKLLygrK+vpoQkhRJ9nKcUXu72hk5vddSbLSyHVZTAwziB7bwABwZOiT3d58TY6ESquN1m4w+SYLCfp7n1/00xLRTTe1IDGp1B1AUWCIzxoWF8ZINBo3YBd1xiX7MBhgMOAWr8i2aWTFWOE9ao5PN3BsmI/plKMTraHxtycscl2HDqsLNsX5KQ5dZzluzF378TpqUKzLHx7bMQ7g89L2QywOcBmD1ZwyswFl3RLF71Hkcfkg80f4rOCpc59lo8PNn3AhIzxzc7+aUt5dYeuMSnDQZq7kxf1Wxb6hh/QS4ub3UUlJWNl5KCS0zv3sUWHtBrgnHTSSfz1r38lPz+fkSNHsnLlSp566ilmzZoFBK8yXXnllTz88MMUFBQwbNgwHnroIWJjY5k5c2aXP4HeoKKigsWLF/Pmm28yZcoUAAYOHBgK+AB8Ph/33nsvr776KhUVFYwYMYLbbruN448/vqeGLYQQvYppKdZXBfBbMDTBIMa2L7uxtdqMuHKrCAYuxfUm35ZAuttggFNnQ5Pgo4EFfFvi48RcV+gkqsxr0fi0KcamEWPTwqqqeQKKhCbrhJuWZx4zwBbKJhUk2pt9jnlxNrJiDCxFRBPP5gxPshNj01hb7iOxcg+HlBVSVF7L7kbTdGr8ipS9xdS0gAkBD+BBq6lC370dKyUDKzsfYuPb9JhCtMRrKnSNdjeaDVjBDMz/tn8dyt402FFdyLdFyzh/1CRK6i2KPSatlR6Is2vU+hWKYDb0yHQHsc002O0wy0Jf/wN6WWRwo5wuVHoWVlo2OA+spRW9XasBzoMPPsi9997LjTfeSElJCRkZGVx44YX89re/De1z/fXX4/F4uPnmm6moqGDChAm88cYbxMd3/xep68YbMVavDk/RK4U5ejT1Dz3UJY8ZFxdHXFwcCxYsYOLEiVHXD1199dVs3ryZf/7zn+Tk5PDhhx8ya9YsFi5cyEEHHdQl4xJCiL5CKcUXRT727K0UtrvOZFqOE03TUEqxrrLltSiK4FXhoiiVxhqr8Su21pgMig/++StrEqikunSaxkbRpsRU+cO3ZURZR9OcFis3KQU+L/jq0bz14POieesZ6K0nv64azesFgid2jdX6W7i6rUAvKUIvKcJKScMaPFIqO4kOW1PhZ1WZHws4NMXB0MS2TQVbXuILNcRdU7aG/MRBNH4XK6C4+jNGD5gMBPtG7ag1KawNhJVOBxiaYOOQFDuapmFaCq+lwi6IdJpmghvlcmMNGYlKGCBTQnupVt+V8fHx3H///dx///3N7qNpGrfeeiu33nprpw6uIwLHHovjpZfQ6upC21RMDN7LL++yx7TZbDz11FNcf/31PP/884wbN44jjzySGTNmcNhhh7F582Zee+01Vq5cGVqUf9lll/HJJ5/w//7f/+Phhx/usrEJIURfsLYyEApuIDjNrMhjkRljsKvOorrRCbxGsEFfc6WdGxuaYMNU4c04V5X7GRhnoGtaxDGSnXpEmdmm//aZKmz6mw7ENbMWqE2UCi5a3l2I5qmh1cvWhAc4ps1BhW5gGRq62XKAp5cWo9VUYQ4fB3EJLe4rRFOryv2sKt83XXJ5qY/sWAN3K+//LdWBUHADcN6Y80L/PyTeRqJDJ8GhhU0tc9k0hibaGJpowxNQ7KgNUOVTpLt1chuVVzN0jZhOKvfclL5pddTgxhw9XjI2vVwnr8DqeYHp0zGffBLbN9+EtpmjRxM4/fQufdzp06dz4oknsnjxYpYuXcrHH3/Mk08+ye23387QoUNRSjFx4sSw+3i9XiZPntyl4xJCiN6urN7kx7LIhfRbqgNkxhisqwy/LTfW4MgMJ1U+i8Jak8Iak6omGQxDg4NTgguNa/0W26oDoalodQHFlmqTIQk2Kps08kx06ED4sTxNApzqJo8VZ9dbrBraEq2yDH3zWjRPXes7N+I0dLyp2RQn5+J3BtfXFOS4GODQIOCHgD84PW3Hlohja14vth+/wRwyShZDizZbUxEe3EAwFt9YFWBscvPTMj0BxYrS5gtlDIw3SHW1nAF12zSGtTD1syto5SXoxbvDtim3G3OUBDd9Qb8LcNA0vNdcg3HVVWh1dcHszbXXdksK0eVyMXXqVKZOncott9zCtddey/3338/f//53NE1j4cKF2O32iPsIIcSBym8pluzxRU1a7Kw1KfaYYethAEYkBb9HExw6ox06owfYqfRZFNYE1+O4DI0xyXbi987Fj7XrDE6whZVcXlXuJy/OiGiSmejQaZoYaprBqW4yPS3e0YG/L2YAfesG9KId7bufrmGlZWPl5KNV6Phr92VsSutNBjjtwelndgfKHYuZmolWXoxeuBmttmbfcSyFsWEVqngXyhUDDgeO8mK0imSU0w1uKUog9llX4eeHKBchADZVBRiVZMNoJovybYkPvxU9LWlozVcS7FFmAH3zmrBNyu3GHD0BHM4eGpRoj/4X4BCexemO7E1zRowYQSAQYPjw4SilKCoqkoyNEEI08m2xj9pA9JMfC/h0lzdsW5rLiFrqOdGhk5isA9Gv8o5MsrO5al8Wp94MXlVu/MhuQ8NhBIsMNNY0g9M0KIpv76LmuhqMdd83m7VRdjs4nMFAw+FEOV3gdKEcTnDHgS34pzvF6WdHWIBjMSyxycE0DZWcjpmUir5tA/qu7eE3V5ajVZYDELt7F4bpCY4hJg5r8PDgGgNxQNtQ6Q+r4teUz1Jsr923rq2xbTWByJ41jaS7jU7vU9MZ9G0bQ+vdANDALDhIgps+pF8GOKEszjXXdEv2pqysjAsvvJDzzjuPMWPGEBcXx/Lly3n88ceZMmUKY8eO5eyzz+aqq67i3nvv5eCDD6a8vJzPP/+c/Px8Tu+hAEwIIXrSluoA22vDT35chkZ9o/UtTUOfoQkdK//qtmkMSbCFrQNovC4HCAVO7ibVzZoWGYjI4Njb+DdGKbSiQoytG4INApuw0rOwcoe0efpLsis8sNrtsbCUin7CqOtYg4ajYuMxNq2J+viNaXU1GD9+i0pIRCWmYKVlgnP/m4mKvmVTVYDlTaaXGVqwPHvjgh4bKgMRAU59QPFdSfh9k53BprsbqwLE2rQWp7b1FK20CH13eIU3K2ugVCDsY/pngEMwi+NdsqRbsjexsbEcfvjhPPPMM2zatAmfz0dWVhYzZ87k5ptvBuCpp57ioYce4o477mDnzp0MGDCA8ePHc+yxx3b5+IQQorep9lssb3Lyk2DXmZjh4MPC+qj3cRoa2bEd728xMsnO5uoAzfUJDK6/AacRLBzQEAI0bfbZdA1OgqOFDE4ggFZTiVZdiVZeHD5NbC/ldmMOGQ0JSe16PslOHbuuhab/+C1FscdqsaKbSssiEBOHsf6HNq370aoq0aoq0Qs3BafG5Q6W9QcHiB21Jt+W+MK2GRocnekkxqbx/vZ9AU6Fz2KPx8RnBj8nmTEG35WGT03TgcPSHCQ4dA5OsaNBh9eudQnLCq672bg6bLNyubHyhvTQoERH9dsAB03De9993fJQTqeTO+64gzvuuKPZfex2e4uV5vLz86moqGj230II0V9YSrF0jy+sV42hwZEZwZOfnFgjbOpVg8Hxtv2azuKyaQxNsDVbcjpx71oaTdNw27SwqXMNzT4tpahtJYOjlZcEf6or0OpqWxyTlZ6FNXgE6O0P3HRNIyfWCMtE7awzWy9ZHRuPefBEqKtB83qCpah9Xrz1flRCIlpVZeR9FOh7dqKX7MbMG4LKzAO9F66dEJ2maeEPHTgqY1+j3OwYg52Npp81nk5qaERcSBidbA9dDOg109KUgupK9JLdaKVFaIEm3w26hlkwpkOfT9Gz+m+AI4QQoldRSrG+MsC6ykDYNDQIVjxryKBMSHXgM71hvS80YEgHp6c1NiLJzqYqM2oj0MZre5oGOBU+i3i7Rs3epoKh/QxtX1+bQAB906oWu503UDYDK384Kj27w88FgieZjQOcwlqTQ1JU61fGNQ1i41F7p90ooM6rMAsKoLoCY8t6tJqqyPtZFsbWDaidW1EpGcGpa3FNF/6Ivs5rqrDKhBowKdMZFjwPS7SFBTiNNQ1uBjh1RrSxX063sCz0nVvR9uwM9ptqhpk/XN7ffVQvercJIYToz1aVB1hdEblYOTvGYEjCvj9HDkPj2Cwny0v8bNp78j5qgL1TGvk5DY1hiTbWVESuK2jcy6bpOpyle3ws04JrhBqLb5ieVleDsW4lmsfT6his5DSsQcM7ZapXhlvHpmmhgM1rKsq8FimtlN1tUXwS5kGHg9eDVl6KvntbxPPS/H603YXouwtRLjcqNRMrNVOqr/UTTRvgJjp0sppkBtPdBgl2PaJEe1M6wYsWvWY6mlLo675HLy9pcTcrKw+VmdtNgxKdTQIcIYQQ3WJbTeTUsFibxoQ0R8R2XdMYn+ZgRFLwz1RseyuVtWB4YrBkdOP1AYmO8F42MXYdCL86bSoiKr4l2LVgL5t1K9EC0a9mq5hYVFwiKj4RFZ/UqUGAoWtkxugUNprSV1hr7l+A08DpRmXmYmbkoO3ZEaws1XQKD6DVe9AKN6MXbkYlJWPmDG73eiLRu5Q2Kc2e4or++StItLGsyTqdpkYOsEetfNhT9G0bmg1ulN2OSknHSsuSzE0fJwGOEEKILlcXsCKCg8HxNsYm23EazV/Z7czApoHD0BieaOPHRk0Lm/biGBhnsK7CH7U/T2MpFbsxStZHlHtTsXFYA4eh4hLA1rWVonJijbAAZ0etycEpnfgAmobKyMVMTg/20ynZHTXQAdAqyrBVlGGlZmANHSVrF/qophmcAc0EKAPjDH4s1yKmnDZIdOiMTOo9p5ra7kL0ndvCN+o61oBUVGomKilF1pb1E73nXSeEEKLfKvaEnzAlOfSomZvuMjzRxh6PSXG9hdvQKGiyPiDRoTMt18XmqgCVPkWlz8LXuFmhUqTu3kQORdCkwaGVno01eHi3ndxnxRhhVd/qAooKr9X5V83tjmBBhPwCtIoStJLdwSvhUZo46iVFaN56zBHjgo1HRZ+hlKLc27YMjqFrHJPpZEWpH02Dccl2FMFGunYdxiU7ek1BAW33dozN68K2KYcDc+zhUhmwH+p1AY6KsvBT9D7yOgkh2qOkyZSXzNYqfXUxQ9eYnOWkNqCIsWlRT8ISHTqHpO47OfcEFFU+i0qPH9emH8mwynA0WRdk5g9DZed3+fgbs+kaGTFGWEPFwlqz66YF6ToqOR2VnI4V8KOV7kEv3oVWHV59TauuxFj9XfAEUq6K9xlVfhU2fdOuay02s01y6kzJDm+AeXRm72qIqRXtiAhu0HXMEQdLcNNGKuAB3YHWR7KyvSrAiY2NpaKiApdL3my9mVKKiooK4uOl6ZUQom2K68PXp6Q1c0W4O2maRlxbmnQGAmh11cTUVBFbW012dQVawAuNgxtdxxw2BpWS3nUDbkFObHiAs6PW7J4mijY7KiMHMyMHqiowNq0O66+j1dag7dqGyhnU9WMRnaKsjetv+gqtqhxj85rwjbqGOfwgiEvomUH1YkpZYHrBqkeZ9WDWo/w1KF8penwBWkxOTw+xTXpVgGOz2YiPj2fHjh0kJSX19HBEC+Lj47HZetXbRwjRS3kCippGvWM0+sBJkxlA37kt2BujlYaYyuEIXgnuwZOl7BgDjX1Lgar9FlU+q+UmpJ0tIQlz7GEYa1eiVVWENhuFmwgkp0uFtT6i6fqblF5UIKDdPHXoa1eGr5HTdcwR44LrbQQAyvShPDux6osg0Pz3nVVXiObO7j0V8VrQ685QbTYbPp+PxESpXiGEEP1B0+xNslPf1zumF9LK9qBvWYfm9ba6r4qN6xXTXByGRprbYI8nPIuzPwFOfUCxZI+PCp9FfpwRNl2vWTY75vCDMFZ8hebfW8TBUhgbfsQcdSjIhbFeLWCpiCa7TQtw9BmeOoxVyyIKYpjDxkhwAyhlorxlKM9ulK802PS0NYE6lK8Mzdn7f3/yTSOEEKJLlTQpMJDq7r1zuLVd2zC2rG/DjmClZQX72Ri9409pbmxkgDNqQMenqW2oCoSC0w1VAXLjDFLbUn7a7sDKL8DYsCq0Saupwli1DHPkIeDoXeszxD7rKwNhxTRsmtb7s62NBQJolWXBn7I9+4Lsvay8IT02jbQ3UJYf5a9EeUtR9XvAil4NsVn2OII5+N6vd3wrCyGE6JeUUhHdznvD+ptotB1bMLZtjHqbcseg4hJQsfGo2ASIjes1gU2D7BiDbxv9u8JnUeu3Olxqu2kz1LUVAVIz2xacqrQsVMlutIqy0Dattgbbd19gpWVjZQ2UKWu9jM9UrKsMP+EtSLT16mwrEJyGVlqEVlkaLHTRTCLCSs/Cyh3cvWPrTsrE8pYGsyyWD/b+KMu/9//9oFpuyhpiONEMFxgu0F1ohgvNHodm7ztrlnrXt7MQQog+QSmo8VvE2rQW52OXeq2wHhk2TeuVAY5euAl9++bwjRpYWQOxcgZ1eS+bzuCyaaS69LCKdTvrTAoSO+f3XRdoX/VMs2AsxpoV4dXVLIVetAO9aAdWShpW9iBZ6N1LrK8MRFRPa1o+vVexLPSdW9ALNzcb1IR2Tc/CGjKqe8bVTZRSEKgJZmN85bg8a7HKMzp+QFssekw2misDTe/933et6cXvXCGEEL1RfUDxRblOvK2eRIfOlCwnjkbNOpVS7PZY1PitiP43WTE6Ri+7Iqxv24C+Y2uTjX1zIXJOrBEW4OyoNSlIbPvJiqUUXhOizUQz29sewGbHHHVIsOhAZXnEzXppMXppMSpxAOaQkeCSjE5P8ZqK9U2yN8MTbWGf617FU4ux4Ue0muqW99N1rOz8YOamDyyMb0oFPKhATTD7YvkaZWb8qEBtcPteWkfad+h2NHcGuisTzd6/KuNKgCOEEKJdVpX7qTU14oFKn8WP5X4OTXWglGJ7rcnq8gDV/uhTIXLjetefHX3LOvRd28O2KcPAGnkwKmFAD42q47JjDFaU7jvpKam38AQUblvrJ3f1JnxU6KXab0Xte1Lfzun6ABg2zJGHoO3Zib5zK5q3PmIXrbIcY9W3wX45sj6nR6yt8BNodILs6K3ZG6XQigoxtm4AK/p3jHLHoJJSgj8JSd3WcLczKKXAX4HlKQou/Dd9nfsAugG6E82RjOZMRnMMQNN6X0a9M/TCd68QQojeyhNQbKoOP9PdWBUg1qaxqToQVg66KZumkenuBX9MvR60ijL0sj1ha0QAlM0ILoSPT+qRoe2vWLvOAKce1ol+Z63J0DacrG7zaHgcwftFC1ADSlEXsIixtfM11HVUZi5mRg5aaRH6jq1odTVhu2heL8aa5ZhjJvS6tU39nSeg2FgV/pkemdQL1954ajE2r42aDVR2B1beYFRSao9XNGwvZZkoX1lwqpm3JCwr0262GDRHEpruBN0BhgNNd4Bm71NNOjuDfIsIIYRos3WV0f/4rixr/Y9yj01PUwqtrHhfdaV6T/TdbLZgKeM+viYkJ9YIC3D21LctwKkMaLRWCLrKp4jp6JmDpqFSMzFTM9EqStF3bEar2rc+R6utQd+0BqtgbAcfQHTE2go/jZbJ4TI0hib08OmhZUFdNVpVBVp1ZfDHHz2bYaWkYQ0eCfY2lDHvAcryofzV4K8OLvhX/uAUM8sfmnrW5sX/Ten2YEDjSKa+Mg1bqnx2GkiAI4QQok28pmJTVdvmKTWEMY3zOT0yPc3vw1izvNW5+spuDwY3sX1/HnrTIg7VvrbNza8OaLS24qjab5HJ/l8FVkkpmInJ6GtXoJeXhrbrJUWolHRU8oFbyrc7WUqxtSa8yuGoJHvPXIjwedF3F6JVV6DVVDU7Ba2BshlYg0ag0rK6aYBto0wfKlCF8lWifGXgr2n9Ts3RDTRbPBjuvRmYvZkYw7E3QxMTKvKi9NpOegb9gwQ4Qggh2mRDZSDsSm80GpAfb2NEko1qn2JZiQ+vqciOMciO6ebpaYFA24KbmFjMgrEQE9dNA+taTdfP1PgtlFItVrurC1i0MLswpKqNwVKbaBpWwVi0H5aFTVnTN6/FTBjQJyrX9XW76qyIymmDE3pgGlNNFcbqb9ECZuv7QrAwxdDR3TodTSkTzHqU6dmbeQmAMlEq+N/gwv8aCETPELeZbkNzpqC5MveukellUwX7CAlwhBBCtMpvKTY0yd7kxRrsrDMxVTCwGbQ3sInbe4Idb4fMGBf1pmr/uo39ZZkYa1dED250DRWXiEpMxkocAHGJfbLCUnMchobT0PDujUYtoCagiLc3/xwrvG3M8jRTPKLDDBvmsNHYvl8aSvdpPh/61g1YQ/tXWd/eaFtN+Gd6YJyB3t2fBU9t8EJEK8GNMgyIS8BKzQxmbbpwnMGGmMEsDP5KlFnX+Qv+G7O50Rwp6K5UsCf224X/3UkCHCGEEK3aVNWkR4YGE9IcjDUVZV6LFJceNYjRNY2YNlTw6lSWFSxNXFURtlklJGHlDELFJ/b7hewJdo3iRum2ap8ivoWESIWvbYFLZWdmcBrExmNlD0LfsSW0Sd+zE5WagUpM7vzHO0CYlmJpsY+SeouBcQZNi3D7TMWu2vCgYmBcN2dvvPUYq79D80eu4VMOByo+CZWQhIpPCmZYOxjUKMsfzL5Y3mCg0lByWQXAMsMzMcoCM7LaX4dpGtji0OzxaEYM6PZglkaz7/1/e7/oO9Pb9O9veCGEEPvNtCI7nA90W9h0DZuuERulpHCPUQp9w4+R1dHiEzFHHtzvA5sG8Xad4kb9cAprA1T6LNLcOqlRmtxUeNsW4PgtRX1A4erkoNXKHYxWtgfNUxfapm9agznuiAPmNetsaysD7NgbwKyvDJDh1ShodPuW6gCNX/VYm0ZKtAZIXcXvCwY3Xm/YZiszFyt7IDjdzd5VKQWWd9+UMdMbnEIWmi4W/P/gQn5vcDpZdwkFNIlojsTgNDMJYLqdfGsIIYRo0Q/l/tB0JwiWe853d8GV/P1lWegbfkAvLQ7brGLiDqjgBiDeER6AbKsxARPKYUqWkzR3+IlsZRszOBDM9mTaOvlEWNcxh47C9sOy0Cat3oNeuBkrv6CFO4rmrK0Iz4psrNU4du//ry7382N5+O0Du7MIiGUGp6XtDWiVMlF4sZKTsNJjwF+E8lnA3oxKQ2bFCqCs+mCGpSONLfeHpoHhQtNdYARLL2u6AZpt74+BZrjAHoemHTjlmHurA+fbXgghRLvtrDUjOpwPTjCwlzVzh+62t6eNVlUeLAHdZKqLcrsxRx1ywC1Yj9aos8H2GjMswPGZitpA208Wt1YHyIzpghO4+CSszFz03YWhTfruQqysgdIAtJ18poooCFJjBtdlfV/mZ0uTXlY6kB/fPSflyqxHW/8tVtU2lPKiqEcpPyo+HpUUB9UbumUcrbLvzcLYE9DsCcHgRtbG9BkS4AghhAgTsBQ7ak221Zjs8YTP0XcbGqOS7GztqQAn4EerLEer2tvTxtN8xSLlcgdLPx+AJ8ctFRTYVB1gfNq+niHtyd4A7Kg1u2SaGoA1cGhwqppv74Juy0LfsQVr8IhOf6z+rOnntsF/C+vxNIl8dOCwdEeoOMj+UAHP3kpiNcE1LlZg31QxFQhWHyvfg168K/yOsbGojLz9fvxmaQYYzmCGRXfsLbnsCK6B0Qw0PZiB2fdjP6CaYvZHEuAIIcQBzLQUJfUWpgp2qt9dZ7Kz1iIQZfqHBkzMcOAweqbimFZUiLFlfav9MWBvcDN6fJ/rat5ZYmwahkbUst5JjvAT2dYKDKS7DeoCFjX+fVXZttQEGJnUBVkxw4aVMxhj89rQJn3PDqycQQdkoNpRjddfNdY0uLHrGkdlOCKmLLZGKQVmHcpfHQxo/DXB/1qtNPytrY4MbhwOrMyB7S8goNvBcAeDFsO1N0jZF6iE/q07g31jxAFFAhwhhDhABSzF/3Z5w7ret+SgZHv3LkJuRCstwti0ttX9lM1ADUjDGjjsgD4h1jSNeLseNXhpGry2VhnNUooh8TZWlu07ed1UFWBEoq1LenSo9GzUzi37Fp9bCmP1csxho/tFI9buUNRMBqexWJvG0ZlOEhyRmRtlBSBQHWxWadYHAxfl37to3996IBNNXQ367m3h3X8NPVhQwDCCwYo9PlhVTDMAvVFGRQ/9N5iFcUmGRbRIAhwhhDhAra0ItCm4SXToDE+0kR/fQ38yqiswNvwY/bZQT5sBWInJ/a6nzf6ItWtURGnd4W1y7ttaBbXMGIP8eBs/lPlDVbfqAopSrxW1Itt+03WsnEFhAa1WV4Pt+6VYuYOxsgeBLmshmtM429acVJfOpAwnTkMLBi2BmlA2RvmrIVDX4v3bxVuPVlqEVhts5qppOhpO0FyoweMwUgeBLUYW5otOJQGOEEIcgOoCFusqm78K6zI0BsYZDIyzkeTswZNJrwdj7ffQqAcPuoaVkYtKSjkgetp0lLuZqYR+S2Epha5pWEpR1STLc0S6g6V7gpGRTdMYFGfDaWjkxBpsb9Q3pay+iwIcQKVlo4p2hE6KgxtB374Zraw42MW+D2Rz6gOKdZV+DE1jRJINm65RF7AwtGAz1q6wxxN8PXXLi92qxWbVYSgvlrWbZE8x6S4Ybge9zCSgzM4toazb0GyxYItHC4C+eyd6hQ9IRTMyCK74MdA0DXPISMjI6bzHFqIR+asghBAHoB/K/BHrMxIdOslOnbw4gzSX3iXTj9olEMBYswLNH56GMIeMCnYyFy3KjjXYUBX95NVrgtsGVT4V1gvFbWgMjLMRY9Moq7fIijVCxQRSXHp4gNPGqY0douuYo8ejb16LXlIUdpNW2yibkzO4V2fsvtrjpWTvepjiepMkh86GqgA6cHi6g7w2lmZWSu3t77K3SaVqXD654f/9qICH+rIqMmtr0VTwtcqONVDANr2M4TE66W4dWp/B1jrDgWaLCwYz9rjg/xtuNL8PfdsG9JLdweloWlzEXc38YSgJbkQXkgBHCCEOMOVea29flH3GpzoYktCL/iQEAhhrV6DV1YZttnLyJbhpo3S3wdAEG1uqAxHBrNdUuG1axBqdhmxdqsuIyM4kN8nkNQ1wlFJsrTHxmYpB8bY2FaMInrgHgifuygr+oFDKQtMMzCHDsJJTMDZvCA9092ZzUGDlDWn1cXqC11Sh4AagxBOgvM6Lw6rHpjxs2OkjK0NHwwoLVlTjvi+N/9vWx/X60Rqts4qzawxw6DhirGBw01a2mL1lkuP3Vh2z7606Zg9maqKVTA4EMFYta7a6oYpPxBo4FJUwoO3jEKIDetFfMyGEEN1hRWl4RiTBrjO4m3pgtEkgEGwCWF0ZttlKScPKG9pDg+qbDk11cEiKnU93+Siu33eS3NC4ten6m8QoC84bJDl1dAhbh9O4XPSP5QHW7G0uWVhZxZR0E00FUP5KlK8iGMSgOtSgMZAVQCvZg15dBexdgA6wbROmtg1crr3Htfb+t+ljNAm2NK1RqWBn8P/3Nm/cR4X/N2zcjW4LPV7j56bw+CwSvTUYewMao+H5N1JaYSOlk6eANq0vENNaOW9NA1ssWigTEw+2uA4t4tc3rYoa3KjYOKyBw1BJKe0+phAdIQGOEEIcIPyW4scyf9hVZYCDU+w9Px2tQcCPsfo7tJrqsM0qLgFr2JhePR2pt9I0DWeTc9X6vQFO0x44SY7mf7+6ppHo1MMKU5T7LDINHZSfzSV7SDRLcZrlGJaXKt3WYsPRdjFsqIxszLg49KIdYO4dgwJ914aOBb6mj2ghS2fxeS1i/C2vb9njMTs1wPFaCnPvejWlGSgjFldcMprhwlfuRh9QEFzMr9kg1Pulc6rhabu3o5cWh21T7hisvKGolPT9Pr4Q7dFqgHPQQQexffv2iO0//elPeeWVV1BKcf/99/P8889TUVHBhAkTeOihhxg1alSXDFgIIUT7KKX4sTzA+srIdTdZMQYZXdGVvr2UQquuQN+8Dq2uJvymuHjMUYeAlIXtsKYL2n17T4IrmpSIbq6ghFIK/JVkmbvQPFXoyo9OgPrdYMYEj5FcH54ZrAtAfGe3yolNwMoAfWej85L6eqgogaTUTn6w/eOzWg+ZqnyKOlMR05aCA5pBjalT5LXjVQYBZWCiBf+r9FAzyzK3k4DmxtKdpDh1jIRgLyjT5kN3dlEGpa4GY+v6sE0qNg5z7GHyuRU9otUAZ9GiRZjmvnzn7t27+clPfsKMGTMAeOyxx3jqqad46qmnKCgo4MEHH+SMM87g66+/Jj6+91c4EUKI/kwpxTfFfrbWRF5J1gj2tukxSkFNJXpJEVrpnohiAhCcs2+OPARsMuFgfzQNcLwm1Pot/I1Owm1asDdKY8r0ojy7sDy7wKxngGVRbu57L9X6dIixEe1cvi0n+EDwBFh3BLMKaHuzCTpKBcDygmWGr0GJTUDFx6NV78vy6aV7sGITwN57Gjp6o3RZNTUHpu7C1FwEdBeW5mAzDg5KcgV7vETp+wLB/3pMxaLt9fsuUmhN/gvBNFSjeKKlKYedxrKCZdwbvd7KZmAWHCTBjegxrf7FSE0NvyIyZ84c4uPjmTFjBkopnn76aW644QamT58OwNNPP01BQQGvvfYaF198cdeMWgghRKsspViyx8eO2ugLlAsSbVGb/HU5y0TfsRWteOe+Zo5RqMQBmCPGSRnoTuDUmwY4KiJ7E2dToalKKuDBqtuG8uzeu/A/KNYefpzaQPAY/ibrapSmU60lornj0QwXmiMJ7PEEz8aDx2jPtKhQFTFlBosSxB+E8eM3aAEzdExVnYQ54pC90xgb3tdRJqEpAAssP8rygukDy4uyfPtKJoeNbd+Yo27XGu+j7d1Fo8rrp9KpY2ouTN1FvMvN0EQnukaoDDfAei8k+h0MaqXP1PaayGIRrUloYcphZ9ELN4eX8waswSPBHdPljy1Ec9r1V0MpxZw5czjnnHOIiYlhy5YtFBUVcdxxx4X2cbvdHHXUUSxZskQCHCGE6CGmpfiyyBe1o3lOrEGG2+iZwgKBAMba5WhVlS3uZg1IwRouV4A7S9M1OF5ThRUY0JWfFL0Kq24nyluC8pZGPY7b0DA0DXNvQBOwFPWmIoCNgG7DayThNZLxGonU2e2MS3R1yvg1Tdub4bEBTrDFovIPQt+0Zt8+lTWo0lJUenbbDmq40Oi6mSYVlfXU2ff9jselOElzG1hK8aNNCwWHAN8W+0iwayS30FeoLU15m+rqDI5Wsht9x5awbVZKOio1s0sfV4jWtCvAWbRoEVu3buX8888HoKgoWJs+LS0tbL+0tDR27drV4rHWr1+/X7eL/kFe5/5NXt+uoRSU+aHYp6GALKci0QZeC4y9F5S/rdIp94dfvXXpcHiSSYwJZhVsKIp6+DZr7+urBfzEbV2LzVMb9XZl2PDFJ+FLTCFgxMLGTfs3QBFS5oPdlcGTZ1350Y0KaqhG93uxU49OgGyXYue6Nc0eQ2k6lpHEzrpkSgIuLAwsbFho2Az4vqrh5NwHFFMEDPKYXVoXIq66Fntt1b4xFhdTNXQMlqNzAqv9saHUoHFMstNnUrH3V5Tmh80VRlgPotf3wMQkk+ZinB9LDTyN7jAyziLeUBga/FijUx2I/EXv8ZtUNIpxOvM72airJn7zGrRGGT7L7qAqKQsl3/094kD7m1tQUNDsbe0KcJ5//nnGjx/PuHHjwrY3TTMrpVpNPbc0qPXr17d4u+gf5HXu3+T17Rp7PCbfFPuosylwB7dtjbKfMwUaX0ONs2tMznISY+ucK7rtfn3r64KlnxMTIDFh33ZdxxqQikrNCJaQlYxNl6iq91K6dTuuQClOsxKXLbhkIta0AcFGjG5/GZmZUa6829zoMblorgw03U5lqQ+rct86nIREG0kOnR3FkWuosvJcnVdJLZrcHGwrl4C17yQ7Ey/msLE9WnHPUooVRni55IMGu9EbjSmtOsDXTX5nxU6dKVlOjCZTCn2mItHwkLj33xowdZA7tF9ipZ8Vpf6w+7gMjTH57tC/O/U7ub4O44dv0DIy9m3TNcxRh5IuPW56hPzNDdfmb53i4mIWLFjAhRdeGNqWsfeNvWfPnrB9S0pKIrI6Qggh9s/OWpPPd3mpC7RvIn6iQ+cnWa5OC27araYK44fI5n8qPpHAhGOwhh+ESk6X4KYLqEAdZtU67OVfkejdiNOsAIL9a3yNFnRoEJk5sMejJ47CSDkyGODowYIUA5pUWqvwWlEX1EOwShjAjlqT7TWB4FqazuSOwcwPP6nTqirRdkdWf+1OniafUaehhQU3APnxNoYnhl9nLvNafFsSHqgAEQ1ZExx6WBCUGxt5vbothdk6xO/DWLMCzR8+TnPIKGngKXqNNmdwXnzxRZxOJ2eeeWZoW35+PhkZGSxatIjx48cDUF9fz+LFi7n77rs7f7RCCHGA2lFrsqTIS3tn4Q9w6hyb6WxTV/muoFWUoq/7Hs0MXwskBQQ6n1IWmB5UoA7MOpSvAuUtA4IV0jSa7/Xishvgd6O50tFsMWjOFDR7QtR9k5sEOGVeq9ny0tV+i+UlJhuqghmfnbEGR2Y4O/T8mqMyc1HlxWgVZaFt+vZNmMnp4OyZqWqeJgFfc802D0q2U+lTYWvlttYESHJqFCTuq3BY1mT9TdMg023TsOtaWFW8DHcnXzDwedF3b0crKtxb3GEfK3cwKi2rcx9PiP3Qpr8sSilmz57NmWeeGVb6WdM0rrzySh5++GEKCgoYNmwYDz30ELGxscycObPLBi2EEAeSwpoAS/b4Ik5O01w6AdX84uNUl87RmU7seg8FNzu3YmzbEHFWbaVmYA0dDXoPZZT6EeUrDxYGCNSA6Qku0IpCA2yNToD9eiz1thR8egKm7iYnPgZv1XaMpNanuMTadRy6FioDbSoimsc2qPJZ7Krbd9v2WpPxlur096Q5dDTGisWhE2/NNNG3rMMaMa6Ve3aNWn/bAhxN0zgy3cHCnfXUNLrPylI/A5w6qS4Dr6kiPuMDohQPmJBq56tG1dkGdlYREa8HfedW9D27wqYCNrBSM7DyhnTOYwnRSdoU4Hz22Wds3LiRf/zjHxG3XX/99Xg8Hm6++eZQo8833nhDeuAIIUQn2F4TYGmU4GZCqoPBCcGv8IClCFjgsmlU+y2K6kxsusbAOCNiWkyX89SiVZajl+1BqyyPuNnKHog1cFiPro/oD5Tpw6rZgPK0vVKEbjiptmXisaVi6u6w25KalllrRbJLZ3fdvqv4zQXZVT4VllWA4Ml/krOTX3+HE2vgMIxNa0Ob9LJitO+/xsoZhEru3mnzTTM47hYyqA5D46gMJ4t2ekO/KwWsrQiwSQ+wrSayEmK0319unI1DTdjtMcmJNUhtoSJbmwT86FvXoxfvajb1pxISsYZKY3fR+7QpwJk8eTIVFRVRb9M0jVtvvZVbb721M8clhBAHvK3VAb4pjgxuDksL75lh0zUaltfE23XiE7sxM+LzopWXoFWVB398kQvNG5iDh6My87pvbP2U5dmFVb0RrMi1GlHZE9Bjcqg1E6nxRj9TTXLqtFy4O1yyMzzAaU7TtSMANf7mp7TtD5WegyrejVa975loNVUYa1eiYuOwcgYHA51uCK6brsFp2j+oqQSHzmFpDhYX7esLtauZ368GJDVT/nlooo2hiZ0w7TMQwFj1bUR/mwbKbkdl5mFlD5S1c6JXksnPQgjRC+2oNSMqLGkEg5v8VhoCdgul0HZtw9i2Meq0lbBdbTasoaO7/Sp6f6MCtVhV61C+iuZ3MpxoRgzYYoJraexJaPZglTSnzQve6CfNiY72BzgdVdvOIhltpmmYg0dgrFoWsUZEq63BWPc9KiYWK78gWLGvCzV9ji1lcBpkx+gYGq0282xaYKDTWSbGupVRgxvldGJl5wd7DUlgI3qxXvBXUgghRGNKKVaURgY3h6c7GBjXw1/bXg9aSREJG3/ASEpsdXcVn4g5bDS4pKt5W4UVCwjUosy60P+jogST9jj0uKFo9gQ0vfn3h7OZk2y3oTV7W3OaLnJvj6brUzpVbDzmmMPQt21ELy+JuFmrq8VYvRxzxLguDbibZnCaW4PTmKZpJDj0Vht6prq6NkOrb1wdMb1Uud1Y2YOCDTxl7ZzoAyTAEUKIXmZHrRlWCloDjkh3kNdTwY1SwY7lRTtC03+M+jogMsBRhgHxiVgJA1CJyRAXvRKXCKcCtVi121H+qr3FAtpQL08z0OMGocXkommtn3Q2F8R0ZLqY09CItWkdysbUdFUGp0FMHNbIg7Fqq9F3bEYvLY7YRd+4CjP2yC6pslZab1LjD3/93G0s0Z7USoATZ9cYmWRv9vb9pe3Ygl4Svq5LxSVgjj5UKh6KPkXerUII0ctsrAqE/XtQvK37gxuloN6DVluFvmsbWk1187vaDFTmQKyGgEau8LaZUgpVV4hVs6ltQc1emjMZPX44ms3d+s57JTSzDqSj2ZgBTp3aQOvrcJqq9be32HkHxcZjDR+HVVeDvmMLemlRaLG8FghgbPgBc/SETl2Ts6U6wLfFvrBy7oYWpcdQM5pbW2PTNE4e6MKhRzZX7yxaWXFwymkjyh2DOfJgCW5EnyPvWCGE6EV21ZkUNym5OzShG76qAwG0ylK0miq0miqoq45YxxBBAys5HWvQcHB0bm+TA4EK1GFVrUH52rH6xeZGjx2M7s5ofd8msmMNBsYZbK8xQ4UrYm0aQzq4pivZqVNY2/4Apy6gUEp12Yl6hJg4rIKxqNh4jK0bQpsbGoKqrIH7/RBKKVaW+VlfGYi4bXC8rc3PNbGZ6nJJzvZPI2yX6gqM9T+EbVI2G+aIg8Hu6LrHFaKLSIAjhBBdbFNVgJJ6k5xYGzmx0S/l+i3F8hI/W2vCT5DSXEaXVJwKCQTQ9uxA37EFLRB5chaNik+kTnMQGH+EBDYdsC9rsxlUMwFCWLGAWDRbDBixaEbHTzZ1TeOIdCcTUhX1piKgIM6mdXjBenIH14IogkFOa5XFOpvKGoiqLAtvCFq4GTM1c79O4v2WYskeX9SqciOS7Iwd0PZTrcRmMjjNZXY6hacOY+3K8GIhGljDDwK3rJ0TfZMEOEII0YW2Vgf4tiRYMGBbjcngeBuHpNgjTiq/KvKFdTNvMKwzSr425alFKy9BryhFqypvvr19E1ZKGlbeMHDH4F2/XoKbDlCBWszKNeCvirxRt6PHD0NzpqDpXbfOwtA1YjuhCleSQ0ejzW+fMLUBRWzXPcXoNC2yIWgggF64CWvwyA4dstpv8eVuH9VNpt3pwGEdKApi16OvbepoMNkqpTA2/IjmDy85bg4eEVxDJ0QfJQGOEEJ0oU1N1tNsrg5Q4bOYlOEgZu/C442VgajBTapLJzumk05sAn60qvLgepqqtk2JUjYbxCWgYuOxBqRCfFLnjOUAo5QJ/hosbymqbnvUtTaaMwU9YQSa0XeCRpserPpVGaXXTWtq/Qravnyo8zicWDmDw6aq6UU7sNJzILZ9Dcr3eEwWF/kiGpm6DI2jM50dXtuU6Ihc27Q/Vetaou3aFpyS2oiVMwiVkdsljydEd5EARwghWuDd25SiI/Pf6wOK0igVkcq9Fv8t9DIpw4HD0FhZFl4SOtamMSLJzqB4o2PrFGqq0Gqr0Ty1aJ5aqKtpsQFnA2UzUGnZqPhEVGy8lHbuIGV6Ub4ylL86WBUtUBMs2hCNbkOPG4oek929g+wkA5yRAY5D1/BZLed1urySWgtUZh6qaAdavWfvBjA2rsIce3ibC2Rsqwnw9Z7IJrwDnDpHZThxt6EsdHPsUbJr8fZODnCUQistwti+KWyzlZyGNXBo5z6WED1AAhwhRL+jlKLSFzz16Oj6FaUUS/f42L53EbXL0Eh06CQ5g1mVlDaURWquEzmAz1J8usuLTdfCGvvZdY3JWU5i23tCYwbQineh7y5E89S1667KHYNKTsfKypMFxftBKROrZiuqblvzAU0jmisNPb6gT2Vtmkp26mxpUmAv3q5R6m35+XdbJbVodB0rvyC47mQvrbYGbdc2VM6gVu9eWm/yTZTgJi/W4LA0x3434cyNM8LW4qW7O7GhZsOau93b0bzesJuUzYY1eETnPZYQPUgCHCFEv+AJKIo8JrvrTIo8VmjaSIpTZ0yyvU0nCZZSFHks3IZGld8KBTcA9aai3mNS5DFZWxE8mTkk1dFiZmdHkwDHaWihjBAE1y40nd5ycIq9fcFNIIBWVBicetZkHn1LVOIArOQ0VGKKLCTuBMpXiVm1BgJtCC4NB3r8cHRX1zWa7C7JUS4gxNo1Sr1Rdm6kI/1zOpNKTsNKzQjr+WIUbiKQnAbu2GbvVxew+LIovAw0wNhke6f1p8l06wxw7uuHM7odRQqa5fXg3rUVo3wHmhn9wotUQxT9iQQ4Qog+K2Ap1lUG2FFrNrsOoNRr8ekuL+OS7Qxv4QSkLmDx+S4fVW28sry91qTIU8/BKXbyo5TZDViKPU0CnGMzneysM1lVHj0QGRJvY1BbS/YG/MGrsLu2t636ma6hXDGouESszNx2rzcQ0SkrgFWzGVVX2PKONjeaPSH448ro0iIC3SnBoaFD2Al/nF0HWi4fXePv2QAHgif0WmXZvgsDlsLYtLrF3jgrS/1hFykADk9zRP0O6ChN05ia7aTYY5Hg0PdruhuAVrYHY/2PuEp3o2VmRd3HyslHpUW/TYi+SAIcIUSf9U2xr819OL4v85Mda+w9+QpX47f4bJe33VeVfZbi62If22pMJqTZQ0UDAHbXmWEnfbE2jSRncIrbAKfO0j3hi5OHJgSrqzWrofGmpwatuhJtz47m+9RoYA1Ig9g4lDsOFRMLTrc04OxkVv0erOoNYEZJVxhOdHcW2BPQ7PFoev+c+qdrGikug+L6vVXJiJ7VacpvKXymwtGVvV1aY3dgDRqOsf7H0CatqhJ9x2aszIFgCz9FspSKmHY6Min6BY79pWsaGTH7PzVNK9mNseHH6KXudB0rLSs4NbWFrJUQfZEEOEKIPqPSZ7GkyIfHVGS6W24yaNM0Aip8Otiqcj9HpIdPwajyBTM89WbzwU1WjMGYAXYqfRbrKgMR2aIij8mH2y0OSbWHMjBba8yIYzT+/+NynCwv8VPttxiSYIuc3mJZaMW70KorgsUC6mrD+1REoWwGKiMvmKGRqSZdQikFgRqsmk0ob1nUfbSYbPS4If0mS9OacSl2FhdZeAKKMcn2Nve3qQv0cIADqNRMrJLd6OWloW369s3ohZtRsQmohCRUYjIqLpGKQPh6OaehMaYzpo91Ea1oB8amNRHbld2ByszFysiRNXei3+q9n0whhGjEtBRf7t6XZdkeJbhJdupkuA0yY/S9i59NlpXsqx62rcZkRJIVaqZX4bX4bLc3YspJU8MTbaHsS16cwdqKAKvL/WEZmoBSfFPsw21oxNm1iCu9eXHhV2Pj7TrHZkUPQrSyYvSt6/dVeWqFstlQWXlYmXlgOzBOqrtDQzCj/NWoQDXKXx1cY9Ncc06bGyNhBJpjQPcOtIcNcOqcnOcKVfxr7fPUoMZvdW0T2zayBo9Eq/4qPCOqQKupQqupon77FvwKauIyMGLyMO3Bz22aS+9YlcNuoO3ejrF5Xdg2pWmYgwqCJaAlmyv6OQlwhBC9mtdUeAKKDVWBFqeQHZPpJLPJlI5B8QbrK/WwdTVf7/ExMcOB34JPd3kjFvk3bbI3wKmT1qhAga5pjBpgJyfW4NsSHyX14VmVDVUBEpp0HU9ytK3qGp5ajC3rwjqtt0TZ7VhZA4MnLDb5Ou9MyleBWbW2bUUDNB0tJg89Nh9N78SKV31I4xP9ttbI6MlS0WGcLqz84RgbV0fcVO61WF/pD87wKiskV99FRXo+lam5pLp64cUEy0TfvA59z87w7RrU5gxFZQ3smXEJ0c3kL6IQolcqqTdZXxlgZ63Zaqf0VJceEdxA8KRr9AAbX+3Zl8Wp8Fm8v70+6nEGx9s4NNXOtyV+tlQHcOgah6VFn8KR4NCZkuVkY1WA5aX7igbsqgtWcmtsaEIrX7WBAPqOzei7t0ML/UOU3Q7uWFRMHCo2HpWSDoZ8jXcmZZnB6WetFQ3YS3MMQE8oQLPJGoYGuqZhaNBaIqeuFxQaaKDSszGdLrSyPWiV5aFS6zvrAmHfP7plkrx7E4klhWQPzkCvcLV8XJsdFZ8EcQldnzXx1GKs+z44nbUxXcMsGIu/tG0NfoXoD+QvoxCi17CUYluNyYbKABXt6I4+ZkDzV1JzYg3SXDrF9S0fb1iCjYNT7GhaMKg5KNmOQ6fFKSiapjEs0c6GqkBYVajGJ0R2XWNgXJSr+pYF9XXopXvQigqjl3jWwErPQaWko9yxsq6miwWzNmsg0MrUQMOBZotHc2eiu9K7Z3B9jE3XMFuJcHpNBmcvlZiMSkwO/sPnxawsZ+fa3biry7H7wt8TDstPfGURWmXbp6g1XKCwktNQyWnBwh/tFfCjlZeA34dmWcHvEcsE00Qv2R25Tk/XMUeMQyWlgAQ44gAiAY4QosfVBxQbqwJsqg60af5+XqzB7r29bgoSbWFTyJrSNI1JGU6+LvY123hzRJKdg5LDg6SW+ttEjsfG6opggKKUYt6aeZwz8hw0TSM/zsDwetAqS9E8dWj1dcFqaF5P9MpGe6mEJMxBw6WcczdoLWujOVPR7PFgj0ezxfXpxpzdxa6Dt5UChz3a7LM1DidlcWmUZieAUiSU7WBA0RZ0M1iSPd6uodG+9Tea3w/+CoyqCtiyHmV3QExs8L82O9gdwSDI7gh+N1gmOJyo2Hiw2dFKdqNvXtN89cQmlNuNWXCQfIeIA5IEOEKIHqOUYmWZn42VgYjGeY3pBNtS6JrGiKRgxTGfqVC0LRBxGBpHZzrZWBlgdYU/VDFNA8Z0QoO+3DgjFOAs272Mz7Z/zrABBRyVNo7R5Vuwrd/V5mMppxMrvwCVkrFfYxJt0+JaG5sbI2EkmiOp28fV19l1jaYRvEPX8DWaglkXUFhKoXfSQn2fqSj1WiQ6tLCS7R0VWl+naVSl5FKTmMGAPZtJKNtFfBsrxbVE8/ug0tfOMKltrNQMrMEjZW2eOGDJO18I0WN+LA+wvrL5JpVZMQYFiTbS3QZKqbDpYh0pLzs00cbQRBv1AUVtwMJlaMS2dUV0CxIdOgl2nUqfyQebPwS/h60rXufm0V5iHG0bZ6jEc06+rKvpQsoKoPxV4K9C+StbKPWcu7fU84FZNGB/BQOccG6bhmbuq7KmCAY5cZ0QLPgtxUeF9XhMhaHB1GzXfldoK/WGX3axbHZKs4dTkT6IoYk+TPxgttBkVym0uppgqXdvlF5JXUHXMQcNR2XkdM/jCdFLyV9RIUSP8AQU6ysj153Y9eC0rmGJtrCmnJ1ZjtVl03DZOvfENS/OYPF3/yN750YOq6/HySq2l2WRkXlYs/dRTmdwTv6ANFRqplxt7SLKX43l2YnyVUKgtuWdJWvTKaJdN7Drwf5Ujaeh1voVcZ1QjGxbtYln73FNBWsq/EzM6PhUQqUUpc2s20uOc5GUkdRq8RNolMOyLPDWo5UXo5cXo9VUt9rXqlm6hpWWHfy+0HWUboBugGEE19pIbxshJMARQnQ9Syn2eCyq/cGsSZJT59tiX1iVJbsebJqXH2+LevW3V7IsqKtBq61iZPFurG9fILfeA6oWv7mJDzYHmJA5AQ0N5XajUrNQ7liUyw0ut2RquphSFqp2C1btNlCtn45qMTnocUMla9MJon2GDU3DaYPSRsmMlkq/t8em6vBMSktNgNui2q/CSsjbdY3JWU48AUVmTAcyQ7oO7hiUOx8zOz/43eGpDU5T2/ujBfx7/98fnJOracF1e56aYKSkgUoYgJlfIOtqhGiF/HUVQnQJpYKlnrdVmxTWmmFz76M5KNnOkNbKKfe0+jq0ijK02mq02iq0uprQJdrvdn9Nee2SvVNWgidXO6p3sLRkBYcd9nNprtfNVKAWs3I1+Ktb39kWg5Ew/IBr0NmVbFGuUdh1iLXpNHw+oPMCnM6+JlLWZHpaslNngFNnQGfVl9B1iI0PywK1+JtoCNB7aWNRIXqbXn42IYToa+oCFhsqAywtM0iytW3eeZxdY1B8L71q7q1HK9uDXlKEVlPV7G5rSteSn5gfqqzkscHWWI2X3TuZIM31upVVV4hVvYn/3959x0lVnY8f/9w7fets3wV2WcpSBJVIEbHEFhFLrISYGPNFFIP+jCUoGv1aMBELtigSjdj1G0ExatRoEokBFcWKKL0sbQtbZuv0e35/zO64szOzjV3YXZ7368ULuHPLmTmzs/eZ55znoOJ8i29ORLOmhko9W1JC/5cbx24Va46cRddIbDXfpr6bKqnF6j2/ocKZJEMp1lX52ecxSDRrDEw0MTDRFLfAQevhaRn2g/zlhLw/hegUCXCEEN3GE1D8c7cXv6FoZ9mZCIenW7utklK3CfjRd2xC31faod0vHnMxECrvbOTlo9Ky5KbkAFFKQdCDCtSj3HtjFw4wWdGTi9Cs6Wi6/OrrabHm4Jh1ogoKNHTTYp+NMTJB9X5Fmi10vW+r/OGCJtXe0BC2FIvOyQNtmGOkfypaBzj7WbBACHFgyae8EKLb7KwPRIxbb8miazitOoZS1PkVZh3sJo3CZDMDE3tX9karrUbf8l2HKh8pmw2VmAKJyRhpmTI2vocpIwCB+lAwE2iAQAMqUB9aMyQOzZ6FnjICTZfJ1wdKrDk4Fl1rGqL2g4aAImgo9jQGseoaOQ6909k0Q6lw6feW6vwGaTadCk8wZrXGWr/B7oYghcmRt0K+oKKuRWZJA9IPdgZHCNEpEuAIIbpN67KqJg0GJJjITzKTm6D3vixNS4YBjXXopbvbzNqolFQMZyiQUYnJUrHoAFHKwKjfgWrcBaqD6UHdjJ5chO7I7dnGiSjx5uDYTaHPheZ4xG8oVpV62deUMRnttDAmvXNl1eLN46n3KwKG4vN9vrjH1vqi30utP8dSrHrfKXwihAAkwBFCdKPWwzp+nGcj3d67sjNhXk9ofYr62tCfhlqIk31SjgSM7AGhxTdt9gPcUNGpggFNNKsTPXU0mkn662CINQfHrGloWmgRzpYZkn0tPjfWu/yMTjN36ssQd5wAp85nsK7KT30bw+BiHdt6/k2mZG+E6HMkwBFCdIsGvxGxvoUO+73QXo9wN6Dv3Ipeta9DuxsDCjDyh0kFtIPEaNyDUbc1fsGAZroFzZwA5iQ0axqaLVMKBxxEsTIezaPTkiwaddFLYIVVeQ0yO/HFSLx5PKVuI2rIbLIlMriKNXendYCT3hs/x4QQbZIARwjRLVoP60i1qN41JM0Iou/ahl6ys516rCEqIZHgkFGQ4uzxpoloKtCIUbsJ5auOftBkDQUx5sRQQGNOlExNL2OOudBn6PMgMdb4tRbK3Z0McOJkcFoHN4lmjaOzrfxrjyfusUopqryRwfRBr6AmhOg0CXCEEN2i9beeaZbuqY7ULRrqMG35Dq2x7VXslc2GSkpBpWagsvIka3MQhBbn3InRUBxzro1mz24qGNC5eRriwLLE+HKjubJa61LRre1zByGt4/3bGOjYnKyJ2VZSrJHX9gQVhvrhyxiXT0UsQGwzaSTFKgknhOjVJMARQnSa31CYNCIyNK0DHGcv+XTRyvZg2rEx5vwalZiESk1HJaeiklLB2l2r+InOUEEPyleD8teifJUQcEfvJAUD+hRrjASMSWvO4LQdMFR6DIKGwtTBif2xhpm1VpRqDmeFbCYtYjhtY0CFy1dXeiKzNzL/Roi+qZfcgggh+oJ97iDfVfup8Bg4TBrH5dlIteoEDEWNL3qI2kGlFPr2jehle6IfstkwBo9AZWQfhIYJpQyUuxTlq0L5ayHYdjluzZaOnjwCzew4QC0U+yvW8NTmTe1lcAxCQ16zHfGHqdl/9ztM69cT1HSCeUdgM1tBgTFwIP6Lfxmxb7JFZ2yLjFCiOTLAcQcUSU0PRy3wKfNvhOiTJMARQrSr0hNkXVWAfS2+3XQHQyuDH5tro8prRExrSbboWNuZE96j3I3oxZvRqyuiHjKy8zAGjwCzfPwdDMpfS7BmAwTaHi4IgG5BTx4uWZs+yqJrEfNgmufeJLUzBwdC83DaCnD8xx3PF6vWUZzghK07MAHKZsV/yikR+2nAxCxLRDYowaxR1SKmbggospr+HbXAp2RwhOiT5De8ECKuam+ozGqZO3a0Uu4OEjQUpY0xJuV6Yh7SM4wgWk01mqsSraYSzR1riJNOcOio0NwaccApI4jRsA3VsLv9nTUNzZGHnjRU5tr0YT/KtPB5uQ8DGJNmwdwUZJh0DbtJi7k4Z7PiugBFqWZsMcpNA5Sdfhbb/v45pm3bwtuMgYMwxh8Vsd8IpyWqVL2jVYDVPMStMWDgblUJMk0yOEL0SRLgCCFiWl/t57vqNmq5Elqsr8JjUNoY+a1njkPH4+rBxjVzN6Lv3ILuqoi7hg2EhqQFRx4JickHoFGiNcNbgVG7GYJxol7NhGZJAosTzZKMZk1F02UB1b6uIMlMjsOEoaKDiiRL2wGOO6j4pMzLCXm2mMPd6gPgn3oa+tNPo3l9oezN1Kmk200UJpvZVR8ky6EzOsZkwNZV3L6v9tPgV7Se8pNm6+WLEwsh4pIARwgRpcITjBvctB52sq0uQG2LdSU0IMdhoriH26i5KtE3r0MLBNrcTyUkERw9TgoIHAQq6MGo24LyxF5zSHPkoCfkgzkRTZNvyvujeBmYhA4MU6vwGGxwBTgsRkU1X1BhjB+P8d77mLZtC2dvEswaQ1PMDE2Jf3uTEKPIQXF99OdIugxPE6LPkgBHCBFlXVV0cJNp1xmTZsETVHxa7gtv39MQXXUo1irm3Ukr24Np+4b469noGirZiZGWicoZCHrH19QQ+0cFvahAPfhrMBp3gxFjeKPJjp4yEt2WfuAbKHqFUOnlyPfGEekWShqNiLl+u+qDMQMcrwFoWiiL88yz+KdOBU0jP6n925qOBFdAp9biEUL0Lh36eqK0tJTf/OY3DBs2jJycHI4++mhWrVoVflwpxYIFCxg1ahS5ubmceeaZrF+/vscaLYToOZtc/qiJtpOyrZw4wE6Ww0SOw0Rbtwe5CT17U6Dt2YFpW3Rwo2x2jJyBBEceQWD8CQQPOwqVVyDBTQ9T/jqCddsIVn9DYN9HBPd9jFG9FqO+ODq40TS0xHxMGZMkuDnExVrsM8WqMyk7cmhivDVu/E3D24zx4/EffxyWSeM5LtfGwMT2f947GuBIBTUh+q52v+pwuVxMnTqVyZMns3TpUjIyMiguLiYrKyu8zyOPPMKiRYtYtGgRRUVF3HfffZx33nmsWbOG5GQZ8y5EX7CnIcjXFb6ISbYQClgKWnwrajVppNt0Kr2xbzx6MsDRizej790ZtT04eDhqwOAeu66IwfARrPke5S7r2P6WFEwpI9As8jtBxC4VnWTRcJg1TBrhxTaDKrTulqXVBBlf8zBZTSPw859zVKa1w589VpOGWdMIqPhzgBLNGvYOBkJCiN6n3QDnT3/6E7m5uTzxxBPhbYWFheF/K6VYvHgx1157Leeccw4AixcvpqioiFdffZWZM2d2f6uFEN3KE1B8Vu4l1pzfsTGGh+QkmGIGOA6TRqq1B771VAp923r08pLI7bpOsGgMKl3WszkQVMCN8lagvBXYPRtR7pz2D9LNoWpojgFoMmFbNIm12GdzVsdu0mgIRK5TY7FGvne8rZKDtg4uCtpM14g/xBWpniZEX9fuT/Dbb7/N+PHjmTlzJsOHD+e4447jySefRDV981FcXExZWRknn3xy+BiHw8GUKVP49NNPe67lQohus8HljxncDEk244zxi35gYuxhaoOSeiB74/dhWv9VVHCjzCaCo8dJcHMAKH8dwaqvCVasDhUN8LnQ4n37rZnAkoyWMAA9ZSSmzKPREwZKcCMiOMxaxBCwQYmm8HukdcU1dyD6veZvVTWxs/P+2ns7trUGjxCi92s3g7Njxw6WLFnClVdeybXXXsu3337LvHnzAJg9ezZlZaHhCS2HrDX/v6SkJOp8zTZv3tzmddt7XPQP0s8HjycIxW4Nr6FR4o38ba8Bo5IMkgKKza7Yx6e5NXa4NXyGhgakWxTWgMHmqh/26Wr/asEA5voaLPW1WOqq0QORRQ8Ms4X6wSMJllVAWfRinmI/KIWmPOiGG81oQDcaMQXrYu5aWloKgKE7CFhyMPRElGZvcffY0PRH9BUH8jM52wC3O/T5kepXbK4Nba+o1Slt8Zm0vsGg1h4Z0OyoNNFyquBOX5CKTsQkWr1GqfuHACvBpGgMhq5p1qDRH2RzB0df9iXyO7d/O9T6t6ioKO5j7QY4hmHwox/9iNtvvx2AI488km3btvHUU08xe/bs8H6tv51TSrX5jV1bjdq8eXObj4v+Qfr54Kn0BPmo1IfPGrppaLlOvN2kMS3fHrHydyzt9Vyn+7exHr2iLLRQZ33TDbXNBLbMiN2UzUZw9FFkOxI6fm7RJqUUylOKcpeEKqCFiwNoQGLTn0ilpaXk5g9Hd+Q1DT+TIT193cH4TB4TY1tDhQ9qfyjbnJtuocgZOVT2e4s7IoszerCjU1mcAX6DFXu9eIKKdJvOj/Ns7G4I4vIZDE6Knbnu6+R3bv8m/Rup3QAnJyeHkSNHRmwbMWIEu3fvDj8OUF5ezqBBg8L7VFRURGV1hBAH3876QHh18VhGOc3tBjfdTduzA9POre3up1KcBIvGypo23UQZAZSvGqOhGPyxszStadZUNFsWnposzBlje7iF4lDUusqZp9UQNUOpiOBGAyydjEcSLTrT8u00BBTJFg1N0xicbEZKlQjRP7Qb4EyePJktW7ZEbNuyZQv5+fkADB48mJycHFasWMFRRx0FgMfj4ZNPPmH+/Pk90GQhRFetr/bHXcATQtmbIckHcHksI4i+dT16RTtjQXQdIy8fY9BQ0PvfN6sHkjICKE85yrsP5XOBihfqtmJORE8ehm7LCJ1H9/RcI8UhrXX1staVHX2tCgxYdK1Lc7xMukaKVeaGCdEftXsnc+WVV3LaaaexcOFCzj//fNauXcuTTz7J//7v/wKhoWlz5szhgQceoKioiOHDh7Nw4UISExO58MILe/wJCCHaZyjF5/t87KyPsegiodXGzRpMyLIeuOyNz4tp4zc/DEdrRSUkoZzpqNR0VIpT1rPZD8oIQLAR5a1qWnwzfpALgG4JlXM2J6NZktDMSWhmGRIoDgyHqe0Mji+qwECPN0kI0ce0G+AcddRRvPTSS8yfP5/777+fQYMG8fvf/57LLrssvM8111yD2+3mhhtuwOVyMX78eJYvXy5r4AjRzWp8Bi6vgVnXsOqhykHWpn/HC0y8QcXqMi/7Wi3eqQPjs6wMPpAZm2b1NZg2rkXz+SI2K7MZY3ARypkhw9C6SBn+UClnf30oqAk0QrBj2RbNnoWeNATNHD3nRogDpXUGp7G9AOcAD6kVQvR+HbqzmTp1KlOnTo37uKZp3Hzzzdx8883d1jAhRKTSxiAflXrjLt1g0TVyHTr5SWbyEnQ0TaO0MciafT68rYZ4WHSNKTlWsg5CKVRtXwmmbeuh1U2KciQQHHUk2CVT0BUq0IDRuDu08KaKnamLyexAs2Wg23PQLCk910AhOqh1BscbVBGFi1oPUetsiWghRP93EL66FUJ0xaaaQFvr0uE3FLsaguxqCGLRQ6uBe2IsbpNk0Tg210ZyZ2fl7i+l0HduQd+7M+ohIy0DY/hYMMtHUmcpnwujYRfK24ly2boltDaNPVuyNaLXMesaFl0LFxIwCC3saW/6eIjO4BzgBgohej25mxCiDwgaikpPx7+V9xuKWLMssuw6k3Ns2A7UN55KQUMduqsSrXpfzPk2xsDBGPnD2l95T4QppVDeCoyGneCvbf8ATQOTA82ciGZJQXPkoemW9o8T4iCxm7SISmmeoAoPXYta5FOGqAkhWpEAR4g+oNJr0DIZY9E1Uq0a3mDo20x/UMUt+wxNC3c6LYxOM6P3dCAR8KNVlpG4czMm1160QCD2frpGcOhoVFZez7anj1NBX3gujQo2QKARFWiAoDf+QSYbuiM3VCTAnBAKbmSdGtGH2E0adS2+pXEHFc6mf3tliJoQoh0S4AjRB5S7I8OXAQkmJmZbw/9XSlHpNdhWG4iqlJZq1Tkq00KGvefn22g1Veib16H5/Vhrq9ASYhcKUFYrwZFHQFJqj7epL1JBL8pdguEu6XCBAAAsyegJ+Wj2LAloRJ/maHV30rKSWnQG50C0SAjRl0iAI0QfsM8dGbRkOyJ/o2uaRqbdRKbdxLCUIBtdAXyGYnCSmcJkU5fWiOgUw0DfW4y+exttThQCVGoaweFjpEpaDMrnwmjcg/LuCw3v6yDNloGeWIBmdfZc44Q4gBxmHfjhc6/lWji+GEVThBCiJQlwhOjl/IaiyhuZwcluo/pZht3ElNwDVB1NKbSqcvRdW9Hc7ti7mM2o1LTQejap6VIlrZXQwpulGI17INDY8QM1Hc2eg56YL4UCRL/T+iOuZQan1cfhgZtTKIToMyTAEaKX2+c2IpIiyRYdh/kg/0IPBND27UUv2YXmjT2EypOZR+DwiZCYLAUEAKWCEPSggp6mv92hv31VYLRRQELTwZyIZk5AMyVA+G8HmiYrHIr+yd4qaKmXIWpCiE6QAEeIXq6kse3haQeEz4vWWI9WXwP1dWh11WiB2DflymzGKBqLe18VJB3a66ooZaA8+1DuPShfTecONic0lXLORdPlo1ocWlp/iVPuDrLB5WeU0xI9RE0yOEKIVuS3phC9WL3fYEddZBWytoandSetthqtdDdafQ2at42KXeEDwMgeiJE/FCxW2FfV843spZS/HsNTElp004hVsDsOTUOzZYUCG5lPIw5h6TadRLNGQ4vMzboqPzrgaz1ETebgCCFakQBHiIPEF1QElKJ5tIUiNK/cpEFi0yKc31f7I4anJZo18hJ6OIPTWI++ezt6ZXnH9tc1jMw8jLx8SEjq2bb1csrwE6z+BvzR6/20yWRDdwwIrU9jkuILQmiaxqRsKytLfARaFNxYWxX9hcGBXrNYCNH7SYAjxAGmlOKTMh97G+PPu8iw6RyRYYkq+XxYmqVn1rExDLTqCvTSXWi1rg4doiwWVM4gjJyBUhGtSWjxzDaqn5nsaCZ7aF0ak73p/w6wJEtZZyFaybCbODbXyqpSL8E4P1YWXev5KpFCiD5HAhwhDrDi+mCbwQ2EFvZcsTdyWFiKRacgqZuHpwUCaOV70Et2ovl88ffTNVRCEioxBZWYjEpKAUci6HJT3ppuz8Xwb2mxwYxmzw0NOzNLBTkhOiPLYeLYXBsfxQlypMCAECIWCXCE6GF+Q2HWCH/L2LpoQEeNSbfs3zeVRhDcjWgNdaGCAY310FAbt1gAgEpKxigYjkp2SjDTQZo9B+q3oVmdoQIB9kypdibEfsh2mJiSEwpyWk2/wSoFBoQQMUiAI0QP8BuK7bUBttcFqfMbJFk0js+1kWDWKHdH/op2mDR0LVRJ2RuMLoEKoV/wAxO7cJNsGGiVZaGhZw117S7C2UylODFyB6HSs6XEcydpJiumrClNw9WEEN0hJ8HElFwbH7cKcqxSYEAIEYMEOKJP8xuKryp8uLyKVKvGgMRQINAj81Q6qDFg8OFeb0T1n3q/Yr0rwPAUc0QAY9E1ziiwhzMzpY1BVpVGDk3TgB9ldvJmORhA21eCvre4YxXQAGUyoTJzQ3NqEpM7dz0RQYIbIbpfboKJyTk2Vpf9EOT0eNEVIUSfJAGO6NM2ugLhifi1ftjVECTNpnPSAFubQU6tz+DrSj8BQzEmzUJOQvcMIfIEFP8tiQxumu1tCJJiiWxTll2PGHaWm2BiQIIpYo7OSKeF5I6WCTKCaKW7Q4GNv2PlicPFAnIHhco7CyFELzUg0cTJA+3sqAuQYtUZkizDP4UQ0STAEX1aaYz5LNVeg131QQYnx357e4OKlSVe3E0zVleVejku17bfQY7fUKwq9VLvjz0OzGcoNta0XtMmOnAZn2XFV+al0mMwKNHEaGfHfky1yjL0HZvaLBagbHZUQhIkJoeKBiQkgd0hw9CEEH2G06YzziZfxggh4pMAR/RZfkNR03rFtybFcQIcpRSflvvCwQ2EpqWsLvfx4zwbTlvbmRKX12CDy4/NpDEi1RxeryZoKD4q9eKK055m3lZlgLJiLNppM2mcOMDe5nlQCjxutMa6UNGAWhdaXU3sfXUdIzsPI68A7FLFSwghhBD9mwQ4os+q8hhx58yXu4M0BgwSzKEAxG8oyt0GG11+qrzRQYjfUHxS5mVqvj3u0DZfMDT8zNc0h2ZnfZAjMywUJJn4uMxHhSfyvDmO0HCzrypjZ1RsJo3UztQ4DQTQS3eiuaqgsR4t2HY1NmU2NQ09y5d1aoQQQghxyJAAR/RZrQOK1tZV+bHqGhUegxpf/GCoWUNAUVwXZEhK7B+LrbWBcHADoaDo830+vqvSIjJCEFqo85gcKz5D8VVl7Otl2zs6r8ZAK9+Lvntbx+bV6BpGbj7GgMEyp0YIIYQQhxwJcESf1TrASbPpVLfIzjQXH4jH3pRBKXP/sN96l5+8BBM1PoMqr0G1NxQc6ZpGnT92QNU6uEm16hyba8Osa5j10DViDaWLF0iFGUG08hL0vTs6XgktNY3gkJGhRTiFEEIIIQ5BEuCIPslQiipvZADzowwLK/Z6O7TUS16CiXEZFjQN/rEzGC452hhQ/H2nO8YRHVtApnm9m5aLz+U4ogOc0U4L2THm3wDg86JVlKKX7Gy7YIDFAglJqOaCAUkpEtgIIYQQ4pAnAY7ok2p8ipaJE5tJI91uYkCiiT0NsTM3yRadLLvO0BRzRDGBwmQz2+oCMY+JpzDZTG1TlqeZ3RQKbuzmyDk8BUlmNrWonlaQZGJMetM6KV4PmrshNKfG3YDW2IDWUBs/ntJ1jIGDMbIGgK2dQgRCCCGEEIcgCXBEn7TPHRnEZDbNZzk83UKDX1HrM0i16WTYdLIcJjLtOjZT7OIBo9LM7KgL0PaMnh+YtNB1rDpsrAmwvTZAglnjqCxruKpaS06bztHZVopr/WThZYSqR99QiVbnQgt0MLDSdYzsARgDC6VggBBCCCFEGyTAEX2OLxi9nkxzgJNk0Tl1UOcyGwlmnSMyLHxdGZrArwEpVp10m06aTcdh1viuyh8uAX14uiUcLI1yWhjljLNqvc+L5qpEq62msKGeIZ4GMDo21C1M1zFyB4VKPEtgI4QQQgjRLglwRJ8SNBRrq/wR68nowID9XKRzeKqFAYkmvEFIsWiY9MhsT65Dp8prhIsG/NCgAFpNNXjdaF5PaMiZ1x36u6PZmRhUQiJGVh4qM1cCGyGEEEKITpAAR/Q6SimqvQZBBUEFNT4Dl9fA5VPU+6PLPY90WmIODeusBLNOQpyfCE3TyLA3BVGGgVZTFSoEULUPjI4OboumTCZwJKISElGOxFDRgIQkCWqEEEIIIbpIAhwRl1KKPQ1BPEGF3aSRZtO7JZBoiy+oWLHXG7ckc2vJFp1RzgPwNvZ50ar3odVUo9VWd2w9mhiU1RoKYpJTMdKyICEJ4iwsKoQQQgghOk8CnINke22A9S4/iWaNSdk2HObed5P7+T4/xfU/DLPSCM0/GRFvzkk32FQT6HBwowHjsyxRw8n2i88LPk/EcDPN3YhWW93RStERDVSJyai0TFRKWihDIwtvCiGEEEL0KAlwDoJan8GXFT4UoXVXvqrwMSW3dw1J2lEXiAhuIHR//311gOGpZvQeyDoopdjRgXLNSRYNp1VnSLKZTPv+zb1BqVBmpmofWnVFl+bNKJsN5cxE2exgszf97QgFM5KdEUIIIYQ4oCTAOQi21QYikgF7G4N4Aipq/ZQDzRcMBRi7G4IR67u0FFCKOr8i1dr9bS11G3iCkWkSp1XHadNxWjWcNp1Uq46lOzI2hoG2by/63p1onlgLe7ZNmc2o9GxUVi4q2SmBjBBCCCFELyEBzgGmlGJXjIUodzcEGJ7ac0O/2lPjM/i41EtDoP1xWLU+I7KSWDfZXhuZPSlMNjMhq/uHdGlV+9B3bkZzdy6wUQlJqIxsDGc6JKZIUCOEEEII0QtJgHMAuAOhzMjexiDVcTIjO+uD3R7g+A3F5/t8VHsNhqWYGRln7szu+gCf7/MTULGDGx0iFsGs9XVsMsrWmtA8o6CCVKtGpt3EsBRzzPlG7oCipDEy8BuSvJ/Dz1oK+MHdgGn3djRXVdzdlMkENkfUcDOVkAiOxO5rjxBCCCGE6BES4HRRjc/g2yp/eGhZikVjRKolPMxMKUWZ22BbbYCSxmC789OrvAZ1foPkbqxSttEVYE9TtujbKj9Zdp30FnNWlFKsqw6w0RW/Ilh+oolsh4kvKnzhbR0pAlDtNfiq8odjKjyKCo/BJpefwclmRrSqfNZ62F6KRf+hLHNHGQY01qPVudAaG9B8nlDRAK8HLRidNQvTNYzMXFRWngw3E0IIIYTo4yTA6YIqT5CVpT78zavS+6AU2NMQ5JgcG6XuINtrAx0a7tXSrvogh6V1X4CzoVXgsqkmwOSmoMEXVHxa7qPMHX3jn+0wUZhsItGskW7TqWyVdepIBide0GQA2+sC7KgLoGp1srwGSRaNLa2Gpw1J6WBw01iPXlUeKt9cX9u5NWk0MLIGYOQPlXVnhBBCCCH6CQlwOqnCE+SjlsFNCw0Bxb/2eLp87p31AQ5L655hairGcLPm4XHugOI/ez1RAZgOjMu0MjQl8m2R0iqrVO83UEqhNWU6iusCbKoJYNHhqEwrukY4cxS3fUCpV+NfezykWPSI19OqDApNHrQqVygDEwyEMjBGEIIBCAbR/D5wN4b+7gKVmkZwcBEkJnfpeCGEEEII0TtJgNMJ+9yh4CbeXJW2pFh0CpJN7G2qUKYDE7OtrCn3hee31PsVVZ5gxDCyrqr1R7exMaDwG4pvKn1RwY3NpDElxxpzWJjVpGEzaXiDCpTC4q6lodJNogm+r/JRXOdHUwZBpfiqXJFh1Uhu8KMH/JgCfux+D8OtfvY2+PEEFVrTYLTkahdpLicAzuaLKcUgm4GjvJvfmroeKudsT0RlD0ClZ3Xv+YUQQgghRK8gAQ7gDSpsplA2ojFg8MU+P+6AYlSamYKk0EtU1hjk4zIvraoYk+0w4QsqXL7ooVEmDQYlmhmSYgqv1zLKaaHeb2AzaVh0jV31Qfa2mFy/s757AhxXjGIGCihpDLK3VXYlw6YzOaftxUZTLDr7gkE0ZTBg61f4ys3s9QTx+BU5rfb1Ahkt/j80xUyWyURuSmgeTklDEHdQYQ76MLXKwGhArrPrldOU1YpKTkUlpYLdgbI5QsPPZIFNIYQQQohDQrsBzoIFC7j33nsjtmVnZ7Np0yYgNBTqnnvu4bnnnsPlcjF+/HgWLlzI6NGje6bF3czlNfhgj4dBSSZGpFpYs89HTVOw8lm5j2SLjieo+KTUS+uQYUyahdFpFgylWF3mCwcqDpNGUaqZwmQzVlN00JDUYshXQZIpIsDZ1RDkyIwfhn91+XnFCLgAvq7wRzyPRLPGjwfY2l24M8Wqsc8Dqmm/7R1YkBPAqmtk2EPPV0Mjy24i067j8iq+q4veP9NhwtqZdW50DZWShpGejXKmhxbYFEIIIYQQh6wOZXCKior4+9//Hv6/yfRDhuGRRx5h0aJFLFq0iKKiIu677z7OO+881qxZQ3Jy75/fsKkmdMO/sz7IzvroeSOflfto8BtRwc3h6ZZw2WVd05iSa2OfO4imQbpNbzdgaJaXYMKia+E5KN5gqPpabkLbWRylFA0BRaJZixkMubyxh9H5Ws0dyk8yd6it4Xk4WueKIBQkm9CJPL+GRppNY3iiQUKahb0NQWp9BskWjYJEE2igrPamDIwdzBYwmVC6CUxmMJnAbAllZ+wOqXomhBBCCCHCOhTgmM1mcnJaD0QK3WQvXryYa6+9lnPOOQeAxYsXU1RUxKuvvsrMmTO7t7XdzB1Q7I4R1LQUqyTyuAxLzDVrshydH1pm0jUGJprY0SIjsqMu0GaA4zcUK/Z4qfUbpFh0JudYSWm18GZNnAxOa4MSO9bmFOsPQYQnMRXQQtkcTSPFZqYgxcLaqgCGpqE0HV2DMVkJOFMdBK22UDBijnzNXFu3kDm8iOEQUbQgYLFK0CKEEEIIIbqkQwHOjh07GD16NBaLhQkTJnDbbbdRWFhIcXExZWVlnHzyyeF9HQ4HU6ZM4dNPP+31AU5jwCDBolEfY0J+PEfFqDK2vwqSIgOcPQ1BGvwGiXHWxNngClDbFHjV+g3+W+LlhDxbOMhpDBhRmZpYki06TlvHMjIt1+cpGfqj8L+LUs0cnm5B0zSGNQT5rsqPzQRHZFhJs+ltrv+jLLZweWYJZ4QQQgghRHdo9059woQJPP744xQVFVFRUcH999/PaaedxurVqykrKwMgKyuyIlVWVhYlJSU90+JulGE3MXWQneL6IN9U+mOWfm5pQpaVwuTur8uQ7TCRYtHDQYsCNtcEGJcZPTFeKcXOVvNfPEHF+7s96IDdrGHuYPajo9kbms6batXDmSGTBuOzrOEiDAADE00M7MQ5hRBCCCGE6G7t3q3/5Cc/ifj/hAkTGDduHC+//DITJ04EiJoD0nK4UTybN2/er8e7W2EQNjfoNAah0KEo9WqU+0LPQQMOTzbwBxWbS3vm+haPRmndD1mSfWVgrQzSOolT6YPtNZ0LIgbZFVZdsb3xh4yKBgzzBtlc2fHzZAWgpjHUoMEJBt4S2N9eOtD9LA4s6d/+Tfq3/5E+7d+kf/u3Q61/i4qK4j7W6XREUlISo0aNYtu2bZx11lkAlJeXM2jQoPA+FRUVUVmdzjRq8+bNbT7eU45s8e+Aofi2yk9jQDEi1dyl+TWdMUwp6nd6QmvNNDGlWyhytpq3Uu4j19GxCmbNjsy0MiTFjMtrsN7lp8GvKEo1M7gL2ahxnT4ivoPVz+LAkP7t36R/+x/p0/5N+rd/k/6N1LmSWIDH42Hz5s3k5OQwePBgcnJyWLFiRcTjn3zyCUcffXS3NvRAM+saP8q0cmyurceDGwhVYhveam7P5poARotFRQOGYk+rNWzSbTopFh1LnNLK1qYiBgBOm84xOTZOHWTvUnAjhBBCCCFEb9fuXe6tt97K6aefzqBBg8JzcBobG7nooovQNI05c+bwwAMPUFRUxPDhw1m4cCGJiYlceOGFB6L9/crQFDMbXP7wYqKeoGJnfTA872eDK0CgRcBjN2mcNMD2Q/UxQ9EYUHiCob+VgtwEU8y1eIQQQgghhOiP2g1w9u7dy2WXXUZlZSWZmZlMmDCBf/7znxQUFABwzTXX4Ha7ueGGG8ILfS5fvrxPrIHT29hMGkOSzWyp/WEI2uaaAIXJZvY2BNng8kfsX5BkipjrZNY1UqwaKQesxUIIIYQQQvQu7QY4Tz/9dJuPa5rGzTffzM0339xtjTqUDU+NDHBqfAY76gJ8UxkZ3NhMGiNirMUjhBBCCCHEoazTc3BEz0qy6FGllj/f54soYa0Bk7Ot2M0y9EwIIYQQQoiWJMDphUaktp1YG5tuOSCFD4QQQgghhOhrJMDphTLsJjLtsbvGZoqutiaEEEIIIYQIkQCnlyqKM79mWIoZU5yS0EIIIYQQQhzqJMDppQYk6NhilHceKuvXCCGEEEIIEZcEOL2Upmkc5ozM4hQmm6WwgBBCCCGEEG2QAKcXG5piYlBTRTWnVefwdCkLLYQQQgghRFtkvFMvpmkak3NsBA0l826EEEIIIYToAMng9AES3AghhBBCCNExEuAIIYQQQggh+g0JcIQQQgghhBD9hgQ4QgghhBBCiH5DAhwhhBBCCCFEvyEBjhBCCCGEEKLfkABHCCGEEEII0W9IgCOEEEIIIYToNzSXy6UOdiOEEEIIIYQQojtIBkcIIYQQQgjRb0iAI4QQQgghhOg3JMARQgghhBBC9BsS4AghhBBCCCH6DQlwhBBCCCGEEP1GhwKcBx98kJNOOon8/HyGDRvGjBkz+P777yP2UUqxYMECRo0aRW5uLmeeeSbr16+P2OfZZ5/lrLPOoqCgAKfTSXFxcdS1vv76a84991wKCgoYMmQI11xzDfX19e228bvvvuOMM84gNzeX0aNHc++996LUDwXi5syZg9PpjPozYMCAjrwEh4T+0M8Af/nLX5g0aRK5ublMmDCB//u//+vCq9H/9Pb+9Xg8zJkzhylTppCZmcmZZ54ZtU9paSmXXXYZEydOJD09nTlz5nThleh/uqNvq6urueGGG5g4cSK5ubmMGTOG66+/nqqqqojzuFwuZs+eTUFBAQUFBcyePRuXy9VuG9v72ZW+jdYf+nXVqlWcdtppDBkyhNzcXCZOnMijjz66fy9MP9Ef+nflypUx7602bdq0fy9OP9Af+rcv3zt3KMBZtWoVs2bN4r333uPNN9/EbDZz7rnnUl1dHd7nkUceYdGiRdx777188MEHZGVlcd5551FXVxfep7GxkZNPPpmbbrop5nVKSko499xzKSws5N///jevvfYaGzZs4Morr2yzfbW1tZx33nlkZ2fzwQcfcM899/Doo4/y2GOPhfe555572LhxY8SfwsJCzj333I68BIeE/tDPS5Ys4Y477uDGG29k9erV3Hzzzdxwww28++67+/nq9H29vX+DwSB2u53Zs2dz2mmnxdzH6/WSnp7Otddey4QJE7rwKvRP3dG3JSUllJSUcOedd/Lxxx/zxBNP8PHHHzNr1qyIa1122WWsXbuWZcuW8eqrr7J27VquuOKKNtvXkZ9d6dto/aFfk5KSuOKKK3jnnXdYvXo1c+fOZcGCBTz11FPd+Er1Tf2hf5utXr064v5q2LBh3fAK9W39oX/78r1zl9bBqa+vp6CggJdeeolp06ahlGLUqFFcfvnlzJ07FwC3201RURF33XUXM2fOjDj+q6++4qSTTuKbb75h8ODB4e3PPvss8+fPZ/PmzZhMJiAUXR577LF8+eWXDB06NGZ7mm9qN23ahMPhAOD+++/n6aef5vvvv0fTtKhjVq9ezemnn857773H0Ucf3dmX4JDQF/v5tNNOY/z48SxYsCB83C233MIXX3zBP/7xj259ffq63ta/Ld1www18//33vP3223H3mTFjBunp6SxevLgrT79f29++bfb+++8zY8YMiouLSUlJYePGjRx99NH84x//YPLkyQB88sknTJs2jTVr1lBUVBTzPJ39jJa+ja2v92uziy++GJvNxpIlS/b3JelX+mL/rly5krPPPputW7eSkZHRA69K/9EX+7e1vnTv3KU5OPX19RiGgdPpBKC4uJiysjJOPvnk8D4Oh4MpU6bw6aefdvi8Xq8Xi8USvilqPg+EOiuezz77jGOOOSa8L8App5xCSUlJzOEzAM899xyjR4/u9R10MPXFfvZ6vdjt9ojjHA4HX3zxBX6/v8NtPBT0tv4V3ae7+raurg6bzUZCQgIQ+hlMSkqK+NycPHkyiYmJbZ6nK5/RIlp/6NdvvvmGzz77jGOPPbZDz/lQ0pf798QTT2TkyJH89Kc/5b///W+nnvehoi/3b7O+dO/cpQDnpptu4vDDD2fSpEkAlJWVAZCVlRWxX1ZWFuXl5R0+7wknnEBlZSUPPfQQPp8Pl8vFHXfcEXGNWMrLy2Neu/mx1mpqanjjjTe45JJLOty2Q1Ff7OdTTjmFF198kS+//BKlFF999RXPP/88fr+fysrKDrfxUNDb+ld0n+7oW5fLxR//+EcuueQSzGYzEPo5y8jIiPhmT9M0MjMz23yPdPYzWsTWl/v1sMMOIzs7m5NOOolZs2Zx6aWXduQpH1L6Yv/m5uby4IMP8sILL/DCCy9QVFTEOeecw0cffdSZp35I6Iv921Jfu3fudIDz+9//ntWrV/PCCy9EfEMLRKWzlFJxU9SxjB49msWLF7N48WLy8vIYMWIEgwcPJjs7O3ytyZMnM3DgQAYOHMiFF17Y5rVjbQdYunQpwWCQn//85x1u26Gmr/bzDTfcwGmnncZpp51GZmYmv/jFL7jooosAop7Hoay39q/Yf93Rtw0NDVx00UXk5eUxf/78Ns/R+jzd8RktovX1fn3nnXdYsWIFDz30EIsXL+avf/1re0/5kNJX+7eoqIhLL72UcePGMWnSJB544AFOPfVUKSTRSl/t35b62r2zuTM733zzzSxfvpy33nqLwsLC8PacnBwgFPENGjQovL2ioiIqOmzP9OnTmT59OuXl5SQkJKBpGosWLQqP8V+6dCmBQAAgPBQpOzs7KtqsqKgAoiNjCKXYfvrTn5KWltapth0q+nI/OxwOFi1axMMPP0x5eTm5ubk8++yzJCcny/jgJr21f8X+646+ra+vZ/r06QC88sorEf2TnZ1NRUVFxC9OpRSVlZXh83THZ7SI1B/6tbndY8aMoby8nHvuuafP3Cj1tP7Qvy2NHz+e5cuXd/wF6Of6S//2tXvnDmdw5s2bx6uvvsqbb77JiBEjIh4bPHgwOTk5rFixIrzN4/HwySefdHmcXnZ2NklJSSxfvhy73c6JJ54IQEFBAUOHDmXo0KHhMnWTJk3ik08+wePxhI9fsWIFeXl5EZOfAb744gvWrVvXZ1JsB1p/6WeLxcLAgQMxmUy89tprTJ06FV2XZZ96c/+K/dMdfVtXV8eFF16IYRgsXbqUpKSkiPNMmjSJ+vp6Pvvss/C2zz77jIaGhvB59vdnV0Tqj/1qGAY+n68Lr0b/0x/799tvvw3fvB/q+kv/9sV75w5lcObOncsrr7zCiy++iNPpDI8bTExMJCkpCU3TmDNnDg888ABFRUUMHz6chQsXkpiYGJEKKysro6ysjC1btgCwceNGampqyM/PD0eETz75JJMmTSIpKYkVK1Zw2223cfvtt4cnZcVy4YUXcu+993LllVcyd+5ctmzZwsMPP8yNN94YlWZ79tlnGTZsGMcdd1ynXqhDQX/o5y1btvD5558zceJEXC4XixYtYv369VKNid7fvwAbNmzA5/NRWVlJQ0MDa9euBeCII44I79O8rba2Fk3TWLt2LVarlVGjRnXba9XXdEff1tXVcf7551NXV8dLL71EY2MjjY2NAKSlpWG1Whk5ciSnnnoq1113HY888ghKKa677jqmTp0at1IPdPwzWvo2Un/o1yeeeILBgweHz/PRRx/x2GOPRZW5PRT1h/59/PHHKSgoYPTo0fh8PpYuXcrbb7/N888/38OvXu/XH/q3WV+8d+5Qmeh4NyXz5s3j5ptvBkLpsHvuuYdnn30Wl8vF+PHjWbhwIYcddlh4/wULFnDvvfdGnWfRokX88pe/BOCKK67g/fffp6GhgaKiIq6++uoOpbG/++475s6dy5dffonT6WTmzJnMmzcvopPq6uoYNWoUN954I9dcc0275zzU9Id+3rhxI5dddhlbtmzBYrFw3HHHceedd7b5Q36o6Av9e/jhh7Nr166o7S0XLIv1PPLz8/n222/bPX9/1R1921zuNZa33nqL448/HggtPDdv3rzw2lLTpk3jvvvuazd47chntPRtpP7Qr48//jjPP/88O3fuxGw2U1hYyCWXXMKll156yGfV+0P/PvLIIzz77LOUlJRgt9sZPXo01113Xdy1zA4l/aF/oe/eO3dpHRwhhBBCCCGE6I0O7a9PhBBCCCGEEP2KBDhCCCGEEEKIfkMCHCGEEEIIIUS/IQGOEEIIIYQQot+QAEcIIYQQQgjRb0iAI4QQQgghhOg3JMARQgghhBBC9BsS4AghepWXXnoJp9PJmjVrDnZTumTp0qVMmTKFnJwcxo4dy913343f74/YZ86cOTidzrh/Vq9e3enrNjY2smTJEi644AJGjx7NgAEDmDJlCgsXLsTtdne5rfX19dx9991Mnz6dYcOG4XQ6eeihh+K244033uCkk04iNzeXwsJCLr30Unbv3t3p59MRTqeT6667rkfOfSBs27aNiy66iIKCAvLz87nooovYvn17xD4rV65s873y29/+tkvX/vDDD7n66quZOHEieXl5jB07lpkzZ7Jly5Yut7W6uppHH32UM888k6KiIvLz8znhhBNYsmQJwWAw6pxKKRYvXsz48ePJzs5m/Pjx/PnPf0YpWZ5PCLF/zAe7AUII0V+8/PLLXHnllUydOpUrrriC7777joULF7Jnzx4WLVoU3m/mzJmceOKJUcffeuut+P1+jjrqqE5fe8eOHcydO5cf//jH/OY3v8HpdPLZZ59x9913869//Yu3334bk8nU6bZWVlZy3333MXDgQI444ghWrFgRtw3PPPMM1113HVOmTGH+/PlUVVXxxBNPcPrpp/Phhx+SkZHR6efVX5WVlTFt2jQsFgs33ngjAH/+85+ZNm0a//3vf8nOzgZg5MiRPPHEE1HHv/3227z55puccsopXbr+7bffTnV1Neeccw7Dhw+ntLSUp556ihNOOIF3332XI488stNt/fTTT7nzzjv5yU9+wrXXXovD4WDFihX87ne/4+OPP2bJkiURbbj33nu55557mDFjBtdccw2rVq3ipptuoqamhnnz5nXpeQkhBIDmcrnkqxIhRK/x0ksvcdVVV/HPf/6TiRMnHuzmdJjX62XMmDGMGTOGN954I7x9wYIF3HvvvXz44YcRN42tbdq0iUmTJjFz5sw2MyTxVFZWUl5ezujRoyO2P/zww9xxxx28/PLLnHHGGZ1uq9frpaqqiry8PIqLiznyyCO5/fbbozInPp+PoqIiRowYwXvvvYeuhwYIfP3115x88slcddVV3HXXXZ1+Xm1xOp1dfr0Otnnz5vHMM8/w6aefMmTIEAC2bt3K5MmTmTVrFvfcc0+bx59yyils3ryZTZs2YbfbO339jz76iGOOOSbcTxAKko855hhOOeUUXnzxxU63dceOHei6TkFBQcS1rr/+ep5++mlWrVrF2LFjASgtLeXII49k+vTpPPbYY+F958yZw/Lly1m7di05OTmdfl5CCAEyRE0I0cudeeaZnHnmmVHbFyxYgNPpjNjWPGTpn//8J8cffzw5OTkcddRRvPrqq1HH19bWcuutt3L44YeTnZ3N2LFjueOOO/B6vV1q58qVK6moqODyyy+P2H755ZejaRp/+9vf2jz+lVdeAeBnP/tZl66fkZERFdwAnH322QBs3LixS2212Wzk5eW1e/3vv/+empoazj///Iib5nHjxjFy5MiYfdDdmoc3FhcXR2wvLi7G6XTy0ksvhbfNmTOHnJwcysvLmTlzJvn5+QwePJhrrrkGj8cTde7XXnuNU045hby8PAoKCpgxYwYbNmzoclv/9re/ceqpp4YDBoBhw4Zx8skn8/rrr7d57NatW/niiy8455xzuhTcABx77LER/QRQWFjIEUccEfFe6UxbCwsLo4IbiP0efOedd/B6vcyePTti3yuuuAKv18s777zTpeclhBAgAY4Qop9Zs2YNV111FWeccQZ33XUXCQkJzJ49O+Lmyu12c9ZZZ/HCCy9w/vnnc9999zF16lQee+wxZs6c2aXrfvPNNwCMHz8+YntmZiaFhYXhx2NRSrFs2TIKCgqYPHlyl64fT0lJCUDE8LD9aWs8zXN3EhISoh5zOByUlJRQVlbW6fP2JMMwOO+887BYLNx5552ceeaZPPfcc9x3330R+z388MPMmjWLAQMGMH/+fK6//nq+++47pk6dyo4dOzp93ebXovXrDzBhwgTKysooLS2Ne/z+BsNtKS0tjXiv7G9bm88B0e9Bm80Wzug0O+KII7BarV16DwohRDOZgyOE6Fc2bNjARx99xMiRIwE499xzGTt2LC+++GJ4iNTjjz/O5s2b+c9//hPeD2D06NHMnTuXjz/+mClTpnTqus03ebGG1eTm5rZ5E7h69Wp27tzJ3Llz0TStU9dtz4MPPkhCQgKnn356t7Q1nmHDhqHrOh9//DG//vWvw9srKyvDwWVJSUmvGnbk9/uZNm0at956KwCXXnopLpeL5557jttuuw2AXbt28Yc//IF58+Zx8803h4/9+c9/zqRJk1i4cGHEEKuOaO/1b96n+d+tvfrqqwwaNIjjjjuuU9dtz7JlyyguLubKK6/strb6fD4effRR8vLyOOaYYyLOm5WVFZVF0nWd7OzscFAkhBBdIRkcIUS/cvzxx0cELdnZ2RQVFUV80/76669z9NFHk5mZSWVlZfhP88T///73v52+rtvtxmKxRN2wAdjt9riVzCBUzQxgxowZnb5uWx566CE++OADbr/99vBE8P1tazzp6elccMEFLFu2jAcffJDt27fz5Zdfcskll+Dz+cLX7W1mzZoV8f9jjz2WyspK6urqAHjrrbcIBAJccMEFEe8Vi8XChAkTuvxegdDwv9aah5zFe63WrFnDtm3bmD59ercGw5s3b+Z3v/sd48ePj3hN9qetEJq/s379eh544IGIc7jd7pjnbL5WrGGCQgjRUZLBEUL0K/n5+VHbnE4n1dXV4f9v3bqVdevWMWzYsJjnqKio6PR1HQ4Hfr8fpVTUjafH48HhcMQ8zufz8be//Y0f/ehHFBUVdfq68SxdupT58+fz61//miuuuKJb2tqeBx98EK/Xy/z585k/fz4Ap556KhdffDHPPPMMSUlJcY/1+XwRfQShIXMtK791N4vFEjW/qHleV3V1NcnJyWzduhWASZMmxTxHrCF57Wl+fWPN92q+sY/XB83BcHcOTyspKeGCCy4gNTWVF198EbP5h1uD/WnrAw88wDPPPMOtt94aLnDR8rzx5rt5vd4uzy0SQgiQAEcI0ctpmhZzXYxY62oAcW+IW57DMAxOOOEErr/++pj7DhgwoNPtbB7CU1paGnXTXFpaGjFBu6X333+f6urqcPnd7vDuu+9y5ZVXcvbZZ/Pggw92W1vbk5yczPPPP8/evXvZvn07ubm5DBs2jFmzZqHrepvn/fTTT8OT0Zt98803DB48uMPXj5fRMAwj5vZYGaxmze+X5mNfffXViBv/jpwjnubXP9acpOYhYbGGfAUCAV5//XUOP/zwmAUluqKqqorzzjsPt9vNu+++G/V+6GpblyxZwl133cWcOXOYO3du1OM5OTn85z//wTCMiNfQMAzKy8s59dRT9+t5CSEObRLgCCF6NafTGXMi986dO7t8ziFDhlBfXx9zLZquGjduHABffPEFZ511Vnh7ZWUlO3bs4Nxzz4153LJlyzCbzVx44YXd0o4PP/yQ//mf/+HYY4/lL3/5S8yAr6tt7agBAwaEg8RAIMDKlSuZNGlSmxmcww8/PKrSXGfn6zRnX2pqaiK27+97BWDQoEGMGjWqy+dpacCAAWRnZ/PFF19EPfb555+Tk5MTM2j497//TUVFBddee223tKO2tpbzzz+fvXv38tZbbzF8+PBuaetf//pX5s6dy4wZM7j77rtjXnvcuHE8//zzrFu3jiOOOCK8fe3atfh8vjZLqgshRHtkDo4QolcbOnQomzZtory8PLxt7969+1VG9vzzz+fLL7+MeQ632019fX34/7t27WLTpk3tnvO4444jIyODp556KmL7k08+iVKKc845J+qYmpoa3nvvPU466SSysrK68EwirVmzhl/84heMHTuWl156Ke4ch660tasefvhhysvL+X//7/+1uZ/T6eTEE0+M+NPZYUpDhw4FQmWwW/rLX/7SuUa38NOf/hSz2cyCBQtiZoJaDmesqalh06ZNUQFWLOeccw7/+te/2L59e3jb1q1b+eCDD+K+/kuXLsVkMnVLMOx2u8Olrl9++eU2A4rOtPXvf/87V111FaeffjqLFi2Km1U744wzsFqtUX3zxBNPYLVamTZt2n48OyHEoU4yOEKIXu2SSy7hscce47zzzuPXv/41NTU1PP300wwbNqzLpWSvvvpq3n//fX71q1/xs5/9jPHjx+P1etmyZQuvv/46y5YtCy8y+pvf/IaPPvoIl8vV5jntdjt33HEHV199NTNmzODMM89k3bp1PPXUU/z85z8PZ01aeuONN/B4PG3Op1i5ciVnn312VBWv1nbu3Mn06dPx+/1ceOGFvP322xGPjxkzJlySt7NtffLJJ6mpqQnfuK9cuZJAIADA7NmzSU1NBUJFDb777jvGjx+P3W7n3//+N3//+9+ZNWtWRKaop4waNYpjjjmGP/zhD1RXV5Odnc27774bNbenMwoLC7nzzju55ZZbOPXUUzn77LNJS0tj165dvP/++0yYMCG80Gjzzf2iRYv45S9/2eZ5f/e73/HGG29w9tlnM2fOHAAWL15MWlpazKGT9fX1vPvuu5xwwglxK5ZBKBMG8O2337Z5/csvv5xPPvmE6dOns2fPnnDpaYDExMSI/upoW7/88ktmzZpFUlIS06ZN47XXXou45tFHH01hYSEQGtZ2zTXXcP/99+P3+5kyZQofffQRr7zyCjfeeGObz1EIIdojAY4QoldpnvvQPLRq+PDhLFmyhD/84Q/ccsstDBkyhLvuuovNmzd3OcBxOBy8+eabPPLIIyxfvpzXXnuNxMRECgsLmTNnTpcn+//qV7/CYrHwpz/9iblz55KVlcX1118fd37NsmXLSEpKirmQabOGhgYg9jyHloqLi8NBWKxAaN68eRFrjnSmrY8++ii7du0K//+DDz7ggw8+AEKT3ZsDnDFjxvD222/z/vvv4/f7GTVqFI899li7N/td0fp90uyJJ57g+uuvZ9GiRTgcDs4//3xmzZoVUaK4s6666iqGDx/Oo48+yoMPPkggECAvL4/Jkyfzq1/9qkvnzM3N5Z133uGWW27hnnvuAWDKlCncfffdMfv6rbfeorGxsd3iAo2NjeFMVluaf3aWLVvGsmXLIh7Lz8+PCHA62tb169fj9Xrxer389re/jbrmokWLwgEOwO9//3ucTidPPfUUy5cvZ+DAgfzxj3+MKFMthBBdoblcrujZu0IIcZD8+c9/5qabbmLNmjXdWlWsr7rtttt47bXX+OKLL6SyVAu1tbUUFBRw3XXXcfvttx/s5vQKGzZsYPLkybzyyitMnTr1YDdHCCEOGpmDI4ToVb788kscDkenqmf1ZytXruSGG26Q4KaVr776CiBizaNDXXMxBwluhBCHOsngCCF6hTfeeINVq1bx1FNP8Ytf/IJFixYd7CaJXmjdunX85z//4fHHH6exsZGvv/46XD1NCCGEAJmDI4ToJf73f/+X+vp6Lr74YhYsWHCwmyN6qbfeeouHH36YcePG8cc//lGCGyGEEFEkgyOEEEIIIYToN2QOjhBCCCGEEKLfkABHCCGEEEII0W9IgCOEEEIIIYToNyTAEUIIIYQQQvQbEuAIIYQQQggh+g0JcIQQQgghhBD9xv8HrmcM+qYCQtkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 907.2x331.2 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12.6,4.6))\n",
    "plt.plot (data['AAPL'], label = 'AAPL',alpha=0.35)\n",
    "plt.plot(data['SMA30'], label= 'SMA30',alpha=0.35)\n",
    "plt.plot(data['SMA100'], label = 'SMA100',alpha=0.35)\n",
    "\n",
    "plt.scatter(data.index, data['Buy_Signal_Price'], label = ' BUY' ,marker='^', color = 'green')\n",
    "plt.scatter(data.index,data['Sell_Signal_Price'],label = 'Sell', marker = 'v', color = 'red')\n",
    "plt.title('Apple Adj. Close Price history Buy and Sell Signal')\n",
    "plt.xlabel('June. 07, 2019 - June. 07, 2020')\n",
    "plt.legend(loc='upper left')\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.7.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}