Exam Project AI - Mikkel Madsen & Tobias Dahl - Bitcoin Prediction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bitcoin prediction - Artificial Intelligence Exam Summer 2019\n",
    "## Time series prediction using:\n",
    "* Autoregressive Integrated Moving Average (ARIMA)\n",
    "* Recurrent Neural Networks and Long-Short Term Memory\n",
    "\n",
    "Bitcoin is the largest cryptocurrency in the world. It is a digital currency without need of a central bank or administrator. It is purely based off the peer-to-peer network. Since 2013 the Bitcoin price has been doubled by a 1000. The price is now around 9000 USD.\n",
    "\n",
    "In this notebook we will investigate wether it is possible to predict future Bitcoin prices based on time series data.\n",
    "The dataset is from [CryptoCompare](https://www.cryptocompare.com/).\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "import itertools\n",
    "import numpy as np\n",
    "from math import sqrt\n",
    "import statsmodels.api as sm\n",
    "from datetime import datetime\n",
    "import requests\n",
    "import json\n",
    "\n",
    "# Pandas - data analysis library.\n",
    "import pandas as pd\n",
    "from pandas import Series\n",
    "\n",
    "# Sklearn - supervised and unsupervised learning algorithm library.\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "\n",
    "# Keras - neural-network library running on top of Tensorflow.\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense\n",
    "#from keras.layers import Flatten\n",
    "from keras.layers import LSTM\n",
    "#from keras.layers import CuDNNLSTM\n",
    "#from keras.layers import RepeatVector\n",
    "#from keras.layers import TimeDistributed\n",
    "#from keras.layers import ConvLSTM2D\n",
    "from keras.layers import Dropout\n",
    "\n",
    "# Matplot library - interface for plotting.\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "from pylab import rcParams\n",
    "matplotlib.rcParams['axes.labelsize'] = 14\n",
    "matplotlib.rcParams['xtick.labelsize'] = 12\n",
    "matplotlib.rcParams['ytick.labelsize'] = 12\n",
    "matplotlib.rcParams['text.color'] = 'k'\n",
    "plt.style.use('fivethirtyeight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading data from the Bitcoin API"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>open</th>\n",
       "      <th>volumefrom</th>\n",
       "      <th>volumeto</th>\n",
       "      <th>Weighted_Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-05-24</th>\n",
       "      <td>7996.40</td>\n",
       "      <td>8165.45</td>\n",
       "      <td>7801.57</td>\n",
       "      <td>7876.50</td>\n",
       "      <td>51604.15</td>\n",
       "      <td>4.131627e+08</td>\n",
       "      <td>7959.9800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-25</th>\n",
       "      <td>8059.13</td>\n",
       "      <td>8140.82</td>\n",
       "      <td>7948.68</td>\n",
       "      <td>7996.40</td>\n",
       "      <td>22294.65</td>\n",
       "      <td>1.792063e+08</td>\n",
       "      <td>8036.2575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-26</th>\n",
       "      <td>8726.23</td>\n",
       "      <td>8779.00</td>\n",
       "      <td>7894.53</td>\n",
       "      <td>8059.13</td>\n",
       "      <td>57648.95</td>\n",
       "      <td>4.836637e+08</td>\n",
       "      <td>8364.7225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-27</th>\n",
       "      <td>8785.17</td>\n",
       "      <td>8931.53</td>\n",
       "      <td>8668.46</td>\n",
       "      <td>8726.23</td>\n",
       "      <td>57692.17</td>\n",
       "      <td>5.071647e+08</td>\n",
       "      <td>8777.8475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-05-28</th>\n",
       "      <td>8684.53</td>\n",
       "      <td>8818.71</td>\n",
       "      <td>8562.20</td>\n",
       "      <td>8785.17</td>\n",
       "      <td>37230.58</td>\n",
       "      <td>3.241097e+08</td>\n",
       "      <td>8712.6525</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              close     high      low     open  volumefrom      volumeto  \\\n",
       "time                                                                       \n",
       "2019-05-24  7996.40  8165.45  7801.57  7876.50    51604.15  4.131627e+08   \n",
       "2019-05-25  8059.13  8140.82  7948.68  7996.40    22294.65  1.792063e+08   \n",
       "2019-05-26  8726.23  8779.00  7894.53  8059.13    57648.95  4.836637e+08   \n",
       "2019-05-27  8785.17  8931.53  8668.46  8726.23    57692.17  5.071647e+08   \n",
       "2019-05-28  8684.53  8818.71  8562.20  8785.17    37230.58  3.241097e+08   \n",
       "\n",
       "            Weighted_Price  \n",
       "time                        \n",
       "2019-05-24       7959.9800  \n",
       "2019-05-25       8036.2575  \n",
       "2019-05-26       8364.7225  \n",
       "2019-05-27       8777.8475  \n",
       "2019-05-28       8712.6525  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get request to the API.\n",
    "# The data is from today and 2000 days in the past. The price i calculated in USD.\n",
    "request = requests.get('https://min-api.cryptocompare.com/data/histoday?fsym=BTC&tsym=USD&limit=2000')\n",
    "# Loading the data from the API, which is in JSON format, into a DataFrame.\n",
    "hist = pd.DataFrame(json.loads(request.content)['Data'])\n",
    "# Setting the index of the dataframe to the coloum 'time'.\n",
    "hist = hist.set_index('time')\n",
    "# Converting the time coloum from UNIX timestamp to regular time format.\n",
    "hist.index = pd.to_datetime(hist.index, unit='s')\n",
    "# Creating a new coloum from the mean value of close, high, low and open.\n",
    "hist['Weighted_Price'] = (hist.close + hist.high + hist.low + hist.open)/4\n",
    "hist.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a new array containing the mean of each month\n",
    "month_hist = hist['Weighted_Price'].resample('MS').mean()\n",
    "month_hist.tail()\n",
    "month_hist = month_hist['2016':]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NaN values: \n",
      "\n",
      "close             0\n",
      "high              0\n",
      "low               0\n",
      "open              0\n",
      "volumefrom        0\n",
      "volumeto          0\n",
      "Weighted_Price    0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# Checking if there is any zero values in our dataset.\n",
    "print(f'NaN values: \\n\\n{hist.isna().sum()}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bitcoin graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the price over time i months.\n",
    "month_hist.plot(figsize=(15,6))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ARIMA prediction\n",
    "ARIMA model is a statistical model for analyzing and forecasting time series data.\n",
    "\n",
    "* Auto Regression tries to fit a line based on previous values. This is the 'p' in the ARIMA p-d-q formular. This value is setting how many months backwards we want to use to predict 1 month forward.\n",
    "\n",
    "* Integrated makes the data stationary. This is the 'd' in the ARIMA p-d-q formular. The data must be stationary in order to work with it in the SARIMA model. Stationary is, the mean variance should be constant.\n",
    "\n",
    "* Moving Average is the 'q' in the ARIMA p-d-q formular. It removes random movements and uses errors from previous time to predict current and future values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABZgAAALICAYAAADyhJW9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAIABJREFUeJzs3Xe83FWd//H3mT5z+03vHQhJIBTpIiWASgdBcHXFXV1XVHZ13d/ioquyumJDWcu6uLiIDSyAjZKAooCwCCEJaXATkpCbfnNvbps+3/P7Y2bunZk7t03uvXPL6/l4XOfb55hw8515z2c+x1hrBQAAAAAAAADAYLnKPQAAAAAAAAAAwNhEwAwAAAAAAAAAKAkBMwAAAAAAAACgJATMAAAAAAAAAICSEDADAAAAAAAAAEriKfcARpPW1lZb7jEAAAAAAAAAwGhVU1NjctepYAYAAAAAAAAAlISAGQAAAAAAAABQkhEPmI0xHzHGvGiMiRlj7s3ZPt8YY40xHTk/n87Z7zfGfN8Y02aM2W+M+XjBdS80xmw1xoSNMX8wxswb6LkAAAynhoaGcg8BADDOcG8BAAwH7i8oRTl6MO+V9HlJl0gKFtlfa61NFtn+WUlLJM2TNF3SH4wxm621jxljJkt6UNL7Jf1G0r9LekDSGf2dO1T/pwAAAAAAAABgohnxCmZr7YPW2oclHR7kqe+V9O/W2hZr7RZJ35N0U2bfNZI2WWt/bq2NKh0on2iMOW4A5wIAAABAv47EHK3eHdX+cKrcQwEAABg1ylHB3J9dxhgraY2kf7bWNhlj6iTNkLQ+57j1kq7KLC/L3Wet7TTGbJe0zBhzoJ9zAQAAAKBPjR1JrfrtIe2POPK6pPcdW6F/PrFKU4Lucg8NAACgrEZTwNwk6U2S1kmaJOnbkn6sdCuNyswxrTnHt0qqyixXSjpUcL3s/v7OLYqeMwCAocR9BQDGts+95tP+SPrtU8KR7t7SqR+91qF3z0ror2YlFSpDzsy9BQAwHLi/oJglS5b0um/UBMzW2g5JL2ZWDxhjPiJpnzGmSlJHZnu1pGjOcntmuSOzniu7v79zi+rrDw0AgMFoaGjgvgIAY9jrbUk9+uyBHtvDKaO73/Dp4UMB/cvKKv31MRXyusyIjIl7CwBgOHB/QSlGvAfzINjMo8ta2yJpn6QTc/afKGlTZnlT7j5jTIWkRUr3Ze7vXAAAAADo1ZfXtSlle99/MOLon55r1ekPHtDDOyKyto+DAQAAxpkRD5iNMR5jTECSW5LbGBPIbDvdGHOsMcZljJkk6T8lPWWtzba2uE/Sp4wxdZnJ+z4g6d7MvockLTfGXJu59r9J2mCt3TqAcwEAAACgqG2tCf3s9UjetusXBVXv7/lW6vX2lG56qlkX/vaQnt4XG6khAgAAlFU5Kpg/JSki6VZJ784sf0rSQkmPKd26YqOkmKQbc877jKTtknZJ+qOkr1hrH5Mka+0hSddK+oKkFkmnS7phIOcCAAAAQG++vL5dTk5B8rE1Hv3XOXV6+R3T9IkTqhR092yJsbYpocsfa9J1q5u0sTkxgqMFAAAYeYavb3VrbW3lDwMAMOToYwYAY1NDa0KnP3QwL2C+5y11unZhqGt9XzilL73cph82hIu20TBKVzzfdnK15lYO3RQ43FsAAMOB+wsGoqamJu8T9tHcgxkAAAAAyuYr6/Krl4+r9eiq+cG8Y2aE3PrG2XV67qqpumxuoMc1rKQHtkd06i8P6LYXWtUcTQ3zqAEAAEYWATMAAAAAFHjtSEK/2JHfe/lfVlbJ7erZEkOSjqn16kcXTtLqSyfrzGm+HvvjjvTtTR1a+YsDunNDu8JJZ1jGDQAAMNIImAEAAACgQGHv5aW1Hl1ZUL1czGlT/XrkbZN1/6p6La3t2RKjLWF1+0ttOuWXB3Tfa51KOnTpAwAAYxsBMwAAAADkePVIQr98vbB6uVouU7x6uZAxRm+dE9QzV07Vt86p1ayQu8cx+8KObnn2iM5++KB+tysi5sYBAABjFQEzAAAAAOT48rp25ca9x9d5dMX8nv2V++N2Gb17SYVevHaabj+1WjW+ngH1q61J/dXvm/W2R5r0/IHYUYwaAACgPAiYAQAAACBjS0tCD/bovTzw6uVigh6jW1ZUad07puuW5ZXy9yxo1vMH43rrI01615OHtfVIouTnAgAAGGkEzAAAAACQUVi9vKzOo8vnDb56uZg6v0u3v6lGL14zTe9aHFKxyPqRN6I66+GD+ugzLdrbmRqS5wUAABhOBMwAAAAAIGlzS0IP7xza6uVi5lR69J031+mZK6fqkjk9w2vHSj9sCOvkX+7X515s1ZGYM6TPDwAAMJQImAEAAABAPauXl9d7ddkQVS8Xs6zeqwdWTdJv3zZZp07x9tgfTUlff6VDK3+xX9/c2K5okokAAQDA6EPADAAAAGDC29Tcs3r51pVVQ169XMw50/1ac+kU3Xd+vRZXe3rsPxK3+vRf2nTqgwf0021hpRyCZgAAMHoQMAMAAACY8L60ri1v/YR6ry6dO3zVy4WMMbpiflDPXT1VXz+zVtOCPd+qNXam9KGnW/TmXx/Us80uWUvQDAAAyo+AGQAAAMCE9kpzQr/eFc3bdutJVTIjUL1cyOsyet9xFVp77TR96uRqVXl7jmFzS1L/uDmg69YcVmuc/swAAKC8CJgBAAAATGhfLqhePnGSV28rMvneSKrwuvSJE6v08jum6e+Pr5C3yDu3J/bEdPXjTUwCCAAAyoqAGQAAAMCEteFwXL8prF5eWZ7q5WImB9y64/Ra/eWaabp+YbDH/rVNCV31eJNaCJkBAECZEDADAAAAmLC+tK49b/2kyV69tczVy8XMr/Lo7rfU649XTNHJk715+9YdTuiKx5rUHE2VaXQAAGAiI2AGAAAAMCGtPxzX794orF6uHjXVy8WcOMmnX711slZW54fJrzQndPljTWoiZAYAACOMgBkAAADAhFRYvXzyZK8unu0v02gGrsrr0l3LYjp7ui9v+6aWpK54tEmHIoTMAABg5BAwAwAAAJhw1jXF9cgYq17OFXJLP1s1SW8uCJk3H0nq8seadCBMyAwAAEYGATMAAACACeeOgurlU6d4ddEYqF7OVeF16YGLJum8mfnj3nokqcsea9I+QmYAADACCJgBAAAATCgvN8X12O6xW72cK+Rx6acXTtKFs/JD5obWpC579JD2dhIyAwCA4UXADAAAAGBCKaxeftMUb4+AdiwJeox+fMGkHv2jt7eldOmjh9TYkSzTyAAAwERAwAwAAABgwlh7KK7HC6uXTxqb1cu5Ah6jH14wSW+dE8jbvqM9pUsfbdIbhMwAAGCYEDADAAAAmDDuWNeWt37aFJ8umDl2q5dz+d1G951fr0vn5ofMuzrSIfPOdkJmAAAw9AiYAQAAAEwILx6Ka3VjLG/bJ0+qGvPVy7l8bqN7z6/XFfPyQ+bdHSld9miTdrQRMgMAgKFFwAwAAABgQrjj5fzq5TOm+nTeOKlezuV1Gd1zXr2unh/M297YmQ6ZXydkBgAAQ4iAGQAAAMC495eDcT2xJ796+dZxVr2cy+sy+t5b6vSOhfkh855weuK/ba2JMo0MAACMNwTMAAAAAMa9wt7LZ07z6S0zxl/1ci6Py+i/31yndy7KD5n3hR1d+miTXjtCyAwAAI4eATMAAACAce2FgzE9WVi9vLJ63FYv53K7jL5zTp3etTiUt/1AxNFljzVpSwshMwAAODoEzAAAAADGtS++3J63ftY0n86d4SvTaEae22X0rXNq9Z4l+SHzwYijyx9r0qZmQmYAAFA6AmYAAAAA49bzB2L6w9786uVPnjQxqpdzuYzRXWfX6qZj8kPmpmg6ZH6FkBkAAJSIgBkAAADAuHXHuvzq5bOn+/Tmcd57uTcuY3TnWbV6/3EVedubY46ueOyQ1h+Ol2lkAABgLCNgBgAAADAuPXcgpqeKVC9PZC5j9JUzavTBpfkhc0vM6orHmvRyEyEzAAAYHAJmAAAAAONSYe/lN0/36ZzpE7N6OZcxRnecXqObl+WHzK1xqysfb9JLhwiZAQDAwBEwAwAAABh3nt0f05/25Vcv3zrBq5dzGWP0hTfV6JbllXnb2+JWVz/epBcOxno5EwAAIB8BMwAAAIBx546X2/LWz53h19lUL+cxxuhzp1br4ycUhMwJq2seP6znDxAyAwCA/hEwAwAAABhXntkf09P789s8fPKkqjKNZnQzxujTJ1frEyfm//l0JK2uXX1Yz+4nZAYAAH0jYAYAAAAwrnyxoHr5vJl+nTmN6uXeGGP0qZOrdevK/JC5M2l13ZrDenofITMAAOjdgAJmY8zTxpg/9fczwGt9xBjzojEmZoy5t2DfhcaYrcaYsDHmD8aYeTn7/MaY7xtj2owx+40xHx+qcwEAAACMD3/aF9OzhdXLK6leHohbT6rWbQWV3uGk1fVrDuuPe6NlGhUAABjtBlrB/D+S7sn8PCVpoaSnJf1I0p8kLZD0hwFea6+kz0v6fu5GY8xkSQ9K+rSkekkvSnog55DPSloiaZ6k8yX9P2PMW4/2XAAAAADjg7W2R+/lC2b6dTrVywP2zyur9ZlT8idDjKSs3vnEYf1+DyEzAADoyTOQg6y1P8guG2Oel3SJtXZTzrafKB0Yf2YA13owc86pkmbn7LpG0iZr7c8z+z8rqckYc5y1dquk90q6yVrbIqnFGPM9STdJeuwozwUAAAAwDvxpX1x/PpBfvXwrvZcH7WMnVMljpE+/2B3WR1PSjU8e1o8vmKRVswNlHB0AABhtSunBvFTS9oJtOyQdd5RjWSZpfXbFWtuZeZ5lxpg6STNy92eWlw3BuQAAAADGOGut7liXX7184Sy/TptK9XIpPrqiSl84rSZvWywlvevJw3p8N5XMAACg24AqmAv8UdK9xphPS2qUNEfpFhRPH+VYKiUdKtjWKqkqsy+7XrjvaM8tqqGhYUCDBgBgILivAMDw+r8jLj13IL+y9t2TW9XQ0FKmEQ2/4b63XOyTWhZ69NXXfV3b4o70V0826Y7j4nrLpNSwPj8AoDx474JilixZ0uu+UgLmmyR9R9KmzPkJpfsfv6+Ea+XqkFRdsK1aUntmX3Y9WrDvaM8tqq8/NAAABqOhoYH7CgAMI2utPvpIk6Tu9hgXzfLr6pNnlW9Qw2yk7i2fWiJNn9qhTzzfXa+TtEa3bvXrf8+v1+XzgsM+BgDAyOG9C0ox6BYZ1tpma+0NkgJKt54IWmtvtNY2HeVYNkk6MbtijKmQtEjp3sotkvbl7s8sbxqCcwEAAACMYU/tjen5g4W9lwvrT1Cq9y+t1DfOqs3blrTSTX9o1sM7ImUaFQAAGC1K6cEsY8xxkm6T9GlrrWOMOdYYc8IAz/UYYwKS3JLcxpiAMcYj6SFJy40x12b2/5ukDZlJ+iTpPkmfMsbUZZ7/A5Luzew7mnMBAAAAjFHWWn3x5fwvJ148269Tpvh6OQOluOnYCn3z7FqZnG0pK/3tH5t1+0ut+lFDp57cE9XG5oSaoik51pZtrAAAYGQNukWGMeY6pVtk/FLSuyR9ROl+xndIWjWAS3xK0mdy1t8t6XPW2s8aY66V9C1JP5L0f5JuyDnuM5L+S9IuSRFJX7LWPiZJ1tpDpZ4LAAAAYOz6/d6YXjhUUL28kurl4fCeYyrkNtKHnzmibHycstKdGzp6HOsx0rSgW9NCLk0LujUjlF6eHsx9dGtKwCWPy/Q4HwAAjB3GDvKTZWPMFkk3WGvXG2NarLV1xhivpL3W2inDMsoR0traysfsAIAhRx8zABge1lpd/LtD+suhRNe2S+YE9MCqSWUc1cgo573lge1hfejpFjlD8O7JZaQpgXQIPT0TRk8LuTU96NL0kFvTQ25NC6a3+9wE0QAw3HjvgoGoqanJuymXMsnfVEkbMss255FwFgAAAMCIeXJPLC9clqRPrqwq02gmjncuCsltpA893aKEc3TXcqx0IOLoQMTRhua+j633uzQ96EoH0JkQOh1GuzWzwqUV9T4FPYTQAACMtFIC5pckvUfpvsZZN0h6YUhGBAAAAAD9SPdebsvb9tY5Aa2cTO/lkfCOhSGdNc2vh3dGtLczpQORlPaHUzoQcbQ/klJbfOjrj5pjjppjjjYfSRbdH3QbnTPdp1WzA1o1K6BFNaW83QUAAINVyh33FkmrjTF/K6nCGPO4pGMkXTykIwMAAACAXqxpjOmlpvzq5VupXh5RMyvcunlZZdF94aSjA+F02Nz9mNL+iJN+zCw3x46yBDpHJGW1Zk9Ma/bEJLVqQZVbq2YHdNGsgM6Z4VPIU9Ic9wAAoB+DDpittVuNMcdJukzSbyXtlvRba23PmR0AAAAAYIhZa3XHuvzq5bfPpXp5NAl5XFpQ7dKC6r7fcsZTVgcimcrncLoSel84HUKnq6IdHYikdCjqDLrn8472lL63pVPf29Ipv1s6e5o/HTjP9mtxtUfG0E4DAIChMOiA2RhzldKB8s+GYTwAAAAA0KfVjTGtLahe/heql8ckn9toTqVHc4oXQndJOlZNUSdT+ZzqUR294XBCjZ2pXs+PpaTf743p93tj+tcXpHmV7kwrDb/OneFXhZfqZgAASlVKi4zPSvq+MeZBST+y1j41pCMCAAAAgF4Uq16+dG5AJ06ienk887hMemK/kLvofmutXm1Nak1jVE/uienP+2OK99F9Y1dHSvds7dQ9Wzvlc0lnTffrwll+XTQ7oGNrqG4GAGAwSmmRsdIYc7ykd0m6xxjjl/SApJ9Ya18a6gECAAAAQNZju6N6ubD38knVZRoNRgtjjI6r9eq4Wq8+urxKHQlHT++L6Yk9Ma1pjOqNjt6rm+OO9NTemJ7aG9On/9Km2RVuXTTbr1WzAjp3pl9Vo7S62Vqr5pijNzpSmZ+k3uhIaXdHSi4jrZoV0I2LQwp6CMsBAMPLWHt0s/saY86QdLukC621xT9OHiNaW1uHfqpjAMCE19DQoCVLlpR7GAAw5llrdd5vDmn94e6A+fJ5Af3wgkllHFV5cG8ZOGuttrUltaYxpicao3r2QEyx3vPmPF6XdMZUny6aHdCq2QEtrR256mZrrQ5FMwFye1K7O1OZADnZFSqHk32/hZ0ccOmDSyv0/qWVqvOPzqAcwOjC/QUDUVNTk3czLDlgNsbMkXSD0pXM8yQ9aK19/1GPsIwImAEAw4EXaQAwNB55I6J3Pdmct+2ZK6dqeb23TCMqH+4tpQsnHT2zL641e6J6ojGqHe0DTJslzQq5dWGmuvm8mX5V+0oPbR1rtT/sdAXGuzvTQXJ2eXdHUtGBD61PFR6jvz4mpJuXVWpOZSmdMgFMFNxfMBCFAXMpk/zdrHSofKKkRyR9TtIj1tr4kIwQAAAAAApYa3XHy+15266cH5iQ4TKOTsjj0sVzArp4TkCStL01qTV7onqyMaqn98f6DHX3hFO677Ww7nstLI+RTp/m06pZ6erm5XX51c0px2pvON2yItvCIru8uyOpxs5Un32ih1Jn0uq/Nnfq7i2dunZhULcsr+J3BwAwZAZdwWyMeUTSTyU9ZK3tGJZRlQkVzACA4UAVAAAcvd/uiujdv8+vXn72yqlaNkFDMu4twyOStHp2f7pv8xN7otreNvAS4hkhl06b6tPhTFuLvZ0p9dPB4qhVeIzmVro1p9KtuZWeruV1TQn976udakv0PoCLZvl1y4oqnTPdx6SGALpwf8FAHFUFszHGLSkk6WfW2thQDgwAAAAAinGs1R3r8quXr5ofnLDhMoZP0GO0KtNvWZJ2tCX1RKaVxp/2xRVJ9R7Y7gs7+tXO6JCOp9prusLj9KNbcyo9mpdZrvO7iobDVy+QPn5ile59tVP/talD+yM9S6XX7IlpzZ6YTpns1S0rqnTZ3IDcLoJmAMDgDSpgttamjDELJHHXAQAAADAifvdGVBubuyf2M5L+ZWVV+QaECWNBtUcfqK7UB5ZWKpq0eu5ALNO7OabXWpNHff06v9GcCk/RKuS5lR7VHsXEfDU+l/5hRZX+/vhKPbA9rG9u7FBDkTG/1JTQe//QrEXVbn10eZVuWBRSwMNbfgDAwJXSIuNvJJ0r6TOSGiV1XcBaO0IdpIYHLTIAAMOBr5kBQOkiSatVvz2oTS3dwdg1C4L6/nn1ZRxV+XFvKb9d7dnq5pj+tC+mziL9MCYHXF2Vx3MrPZpT4dbcKrfmVKQrko9mksDBcqzVI29Eddcr7frLoUSvx00NuvTBpZX62+MqjirgBjA2cX/BQBS2yCglYM6GyLknGknWWus+uuGVFwEzAGA48CINAErzl4Nx3fxMS17VpZH03NVTdVztxG6Pwb1ldImlrJ4/ENfuzqSmBdMVyHMq3Krwjr6A1lqr5w/G9Y1XOvT47t5belR6jN57bIU+dHyFZlcO6svPAMYw7i8YiKPqwZyxYIjGAgAAAAA9RJNWX3y5Td/c1CGnoATkmgXBCR8uY/Txu43eMtMvyV/uofTLGKMzp/l15jS/trQk9J8bO/Tz7eEeExJ2JK2+valD/725Q+9YGNQtK6p0fB2/ewCAngb9caq1dpe1dpek3ZLi2fXMNgAAAAAo2dpDcb3l1wd118ae4fL8Kre+cFpNeQYGjENL67z6rzfXaf110/WRZZWqLNJ7OWml+7dHdNbDB/XONU368/6YBvtNaADA+DbogNkYU2uM+YmkqKRtmW1XGGM+P9SDAwAAADAxxFJWt7/UqlW/O6RXi0xE9t5jQvrTFVM1PTSmu/IBo9KsCrc+f1qNNl4/Xf92SrWmBotHBY83xvT2R5t08e8O6Te7InIImgEAKiFglvRdSa2S5kmKZ7Y9J+mdQzUoAAAAABPHy01xnffrg7pzQ8+q5Vkht3558STddXbdiE6IBkxEtX6XPn5ClTa8Y7q+cVatFlUX/0DnL4cSes/vm3Xagwd132udiqUImgFgIiulB/OFkmZaaxPGGCtJ1tpDxpipQzs0AAAAAONZLGX1lXXt+vor7SqWT71nSUifP61GNQTLwIgKeIxuOrZC71kS0u/eiOquV9r1UlOix3Hb2pK65dkj+sLaNn3o+ErddGyFav3D//uadKyaY46aoo4ORRw1RVM6FHXUFHF0qGC5Keoo6UjTQy7NqnBrZoVbsyvcmhlKL8/K/Ezyu2RMzxYhADDRPbU3qh+8Gtb/nl/f6zGlBMytkiZL2pfdYIyZm7sOAAAAAH1Z1xTXzU+3aPORnu0wZoZcuuvsOl00O1CGkQHIcruMrpgf1OXzAnr2QFz/+Uq7VjfGehx3IOLosy+16Wsb2nXTsRX60PGVmlkx8HY21lq1JWzRgLgwLD4UcdQcczTYmukd7SntaE/1ut/vlmaG3ITQAJCx4XBcn32xTb/fm/53/3/7OLaUgPl/JP3SGHObJJcx5kxJ/6F06wwAAAAA6FU8ZfXVDe362vriVcvvWhzSf5xWMyJVkAAGxhijc6b7dc50vzY1J/SfG9v1y9cjShb8DrcnrL65sUPf3dyh6xeF9LfHVsgY6VBBQJy7fDiaXo875fn/lhVLEUIDgCS90ZHU59e26efbIwP+MK+UgPlLkiKSvi3JK+n7kv5b0l0lXAsAAADABLHhcFw3P3NEG5t7ftV+ejBdtXzJHKqWgdFsWb1X/31uvT51clLf2dSh+14Lq7MgaU440o8bwvpxQ7hMoxwepYTQs3KWpwbd8rkkv9vI7zbyuoz8bsnnSq/7XCKcBlA2LTFHX1vfrru3dAz6Q79BB8zWWqt0mEygDAAAAKBfCcfqa+vb9dX17T0qHiXphkVB3XF6LVXLwBgyp9KjL55eq/+3slr3bO3Udzd3qCk6cmXIdX6jKQG3JgdcmhJ05S1PDrg1JWe7MdLezpT2hlPa05n+2Zt9zGxrTwzNRIUDCaH7kg2gfS4jX2747Dbyu5R+zCx7e92XPrdYiJ3+kQKZ5cLHYOa8gNvI7SLsBiaCaNLq7i0d+tqGdrXGi/9beM50X5/XGHTAbIw5X9JOa+0OY8x0pSuaHUmftNbuH+z1AAAAAIxfG5sTuvnpFm0oUrU8LejSN86q1dvmBsswMgBDoc7v0idOrNKHl1Xqp9vC+ubG9pLC1QqP6QqIJ2UD4oBLk4M9lycFXPIOMvys8bm0tM7b6/62uJMXOA9nCN2XuCPFHSsNusv00POYwiA6PQFk8XBaCuau5x2nTHidf96MkEuLqj1UbQNlknKsfvZ6RF9Y26bGzuL/bh9f69FnT63RRbP9fV6rlBYZ35F0SWb5zsxjRNLdkq4o4XoAAAAAxpmEY/WNDe368vp2JYoUNV6/KKgvnV6rOqqWgXEh6DH6m+Mq9N5jQvrNrqi+/2qnXm9LqtbvygmIXUWrjicHXKrwlvffgmqfS9UDCKFzA+hyhdAjJWmljqRVR7GvngyROZVuXTw7oItnB3TuDL+CHsJmYLhZa/Xknpg+82KrNrX0nGxZSk+4/K8nV+vGRaEBfZuhlIB5lrX2DWOMR+mgeZ6kuKS9JVwLAAAAwDizuSWhDz3dovWHe1YtTw269PUza3XpPKqWgfHI7TK6akFQVy0Yf7/j2RD6uNrSQugjcUexlFXCkWIpq7hjFUulJz+NObboh3Hj3e6OlO7Z2ql7tnYq4JbOneFPB85zAppbWUpkBaAv65ri+syLbfrjvljR/dVeo4+dUKW/P75yUB/4lPLb2maMmSZpuaTN1toOY4xP6Qn/AAAAAExQScfqrlc6dMe6tqJByTsWBvXl02tUH3CP/OAAYAQMJITujWOt4ikp5th06JwNo530cuG+eCaozobV8ZQyoXX3sellq5ijnPOsoqn0udHMttzHaFKKpuyIN+mIpqTVjTGtboxJz7dqaa2nK2w+fapPHnpCAyXb2Z7UF9a26eevR4ru97qkDyyt0CdOqCrpdVopAfM3Jf1Fkk/SP2a2nS1pawnXAgAAADAObD2Srlp+ualn1fLkgEt3nlmrK+aPv4pGABgqLmMU8EgBlT9ItTYdbvcMoLuD6XQYnbu/5/GRIufFUladCat1h+OK9tGue8uRpLYc6dBdGztU4zO6cFa6lcZFs/2axAeVwIA0R1NmhAV6AAAgAElEQVT66oZ2/c+WTsV7+ZbEdQuDuu3kas2vKv1bA4M+01r7JWPMQ5JS1trtmc17JL2/5FEAAAAAGJOSjtW3NnboP15uK/rG5er5QX3lzBpNJgwAgDHDGCOfW/K5hy/sDicdPb0vrtWNUT2+O9rrJGOS1Bq3enBHRA/uiMhIOnWKt6u6+YR6LxMFAgUiSavvbu7Q119pV1u8+PcR3jLDr8+dWq2Vk31H/XzG2sF/6cEY45Z0hqSZSvdeft5aO/hpYkeZ1tbW8dONHwAwajQ0NGjJkiXlHgYADLlXjyR089MteqlI1fIkv0t3nlWrK6laHhbcWwCMJ9ZabTmS1OrdUT3eGNULB+NKDTChmRFy6aLMRIHnzfSrsswTRo513F/GtpRj9dPtYX1xbbv2hItHtcvqPLr9TTW6YKa/5A9nampq8k4cdAWzMeYESQ9LCkhqlDRbUtQYc7W1dn1JowIAAAAwZqQcq29v6tAXXm5TrMh7lyvnB/TVM2o1JUjVMgCgf8YYHV/n1fF1Xv3jCVU6EnP05J502PxEY0zNsd5nQNwXdnTfa2Hd91pYPpd09vT0RIGXzAloYTUTBWJisNZqTWNMn32xVZuPJIseM7vCrdtOrtb1C4NyD3FP81J+074v6duS7rTWWpOOuj+W2X7KUA4OAAAAwOjS0JrQh58+ohcOxXvsq/e79LUza3T1glAZRgYAGC9q/S5duzCkaxeGlHKsXmqKa/XumB5vjOqV5p7fmsmKO9If9sb0h70xffKFVi2u9ujiOX5dMjugM6f5h7XlB1Auaw/F9W8vtuqZ/T1fm0lSjc/on06o0t8trVTAMzy/A4NukWGMaZNUl9sSI9Myo8VaWz3E4xtRtMgAAAwHvmYGYDxIOVbf2dyhL6xtKzop02VzA7rzrFpNpWp5RHBvATBR7e1MaU1jurr5j3tj6kwOLMqp9BidN9Ovi+ek22lMD3G/Kob7y9ixoy2pf1/bpgd3RIru97mkv1taqX86sUp1/qFtHXPULTIkPSLpCkkP5Wy7XNLvjmJcAAAAAEapba0JffiZI/q/gz0rY+r8Rl85o1bXLggyyRIAYNjNrHDrvcdW6L3HViiWsnp2f0yP745qdWNUO9p7nx6sI2n12zei+u0bUUnSiZPSEwVeOjcwJJOcASOlKZrSV9a16/uvdipRpHuMkXTdoqBuO6la86pGpk3MgJ7FGPNDSdmPhNySHjDGvChpt6Q5SrfG+NWwjBAAAABAWTjW6rubO3X7S61Fq5bfPjegr59Zq2lUgQEAysDvNrpgVkAXzAroDmu1rS2ZCZtj+vP+mPoqbl5/OKH1hxP6yvp2nTnNp4+tqNJFs0uf9AwYbuGko+9s6tRdr7SrPVH8P+7zZ/r12VOrdeKkkf3QZKAx9raC9Y05y5slPT40wwEAAABQTtZabWpJ6uEdET24I6zXi1SD1fqMvnRGra5fSNUyAGB0MMZoSY1XS2q8+sjyKrXFHT21N6bVjVGtaYzqQKT3iQKfOxDXcwcOa3m9Vx9bUamr5g/9JGhAqZKO1U+2hfXFl9u0L1z8v+MV9V7dfmq1zp8VGOHRpQ2qB7MxxiPp3ZIukjRZUpOkJyX90Frbe5f1wQzImKcknSEpO+XhHmvtsZl975L0xcxzr5H0N9ba5sy+ekn3SLo4M65PWmt/knPdXs/NogczAGA40McMwFiwpSWhB3dE9PDOiBpai88+LklvnRPQN86qpXdlmXFvAYCBc6zVhsMJPd4Y1erdUa1tSqivAGhhlVv/sKJKNywOyT/BJgbk/jJ6HIk5+t0bEX1zY4e2Hin+2mxOpVufPrla71gYlGsEP/Qv7ME84IDZGFMjabWk+ZIelbRP0gxJb5P0hqRV1trWox1gJmD+kbX2fwq2L5P0vKRLJa2VdLckl7X2hsz+n0pySfpbSSuV7gl9lrV2U3/nZhEwAwCGAy/SAIxWrx1J6KGdET20I9LrG5esGp/RHafX6oZFVC2PBtxbAKB0hyLpiQJ/8XpEv98b6/W4GSGXPrysUjcdW6FK79BOkjZacX8pryMxR4/ujurhHWH9fm+saI9lKf1tsk+cWKX3H1epgGfkX5cdTcD8HUnzJF1vre3M2V4p6QFJu6y1Nx/tAPsImP9D0nxr7bsy64skbZE0SZIjqUXScmvta5n9P1S6+vnWvs611rZnn4OAGQAwHHiRBmA02d6azITKYW1q6TtUltIzkF8+L6h/f1ONZlZQtTxacG8BgKGxrimub7zSoV/tjPRa1VznN/q7pZX64NIK1QfG972Q+8vIa407evSNqB7aGdEf9kQV772bi/xu6e+XVupjJ1Sp1l++Dz0KA+bBTCV4laQzcsNlSbLWdhhjPizpOUlHHTBnfNEYc4ekVyXdZq19StIySX/Oed7txpi4pGOUDpiT2XA5Y72kt2SW+zr3pSEaMwAAADAq7WxP6qEd6UrlDc39d7bzuqQLZvp11YKQ3j43oBrfxKjaAgBMPCsn+3Tv+fXa1prQXa906P7t4R5Voy0xqy+ta9e3NnbopmMr9OFllXzoiqPSFnf02O6oHtoR0ZP9hMqSZCTdsDikfz2pSnMqBxPnjozBjKhG0p5e9jVKqj764UiS/kXpiQPjkm6Q9BtjzEpJlZIKW3C0SqqSlJLU1ss+9XNuUQ0NDaWMHQCAorivABhpe6NGTza5tabJrS0d/b8Jdhur02odrZqc1HmTUqr2hCXbooO7pIMjMF4MHvcWABhat0yT3llr9OM9Hj2036Ook996oDNp9e1NHbp7c7sunZrSX89OaE5w/H0ZnvvL8OhMSk83u/VEk1vPtbgVt/23tpgbdLRqckpvm5LU/FBY0X1NKtffTl+V7YMJmLdLukDpCfIKXSjp9cENqzhr7f/lrP7AGHOjpLdL6lDPELtaUrvSFcy97VM/5xbF1wEAAEOFr5kBGCmNHUk9vDM9Ud+Lh/qvVHYZ6dwZfl2zIKjL5gbG/dd+xxPuLQAwPJZIOme59PloSt/d3Km7t3SoNZ4fIies0cMHPPr1QY+umh/Ux06o0op6b3kGPMS4vwytjoSjxzOVymv2RBVL9X/Owiq3rlkQ0lULglpW5xkTc18MJmC+U9J9xpiPSHrIWusYY1ySrpH0TUn/OhwDlGSVrgTfJOnE7EZjzEJJfkmvKR0we4wxS6y12SD/xMw56udcAAAAYMzaF07p4R3pUPn/Dsb7Pd5lpLOn+XTNgpAunx/QZEJlAAB6mBRw67aTq3XLikrdu7VT39rUoQOR/D4GjpUe3BHRgzsiuni2Xx87oUpnTvOXacQYLToSjlbvTvdUXtMYVXQAofKCKreuXhDUVfODWlHvHROhcq4BB8zW2nuNMZMk3Svpp8aYJkmTJcUk3W6t/d+jHYwxplbS6ZL+KCkp6Z2SzpX0D5K8kp4zxrxZ0lpJt0t6MDtJnzHmQUm3G2PeL2mlpCslnZW59I/7OhcAAAAYSw6EU/rVzoge2hnR8wfivU5KlGUknTnNp6sXBHXFvKCmhQiVAQAYiCqvSx9dUaUPLK3UT7eFddfGdu1s75kYrm6MaXVjTGdO8+njJ1Rp1Sz/mAsJUbrOhKM1jTE9tDOs1btjiqT6b50yv8qtq+cHddWCoE4Yg6FyrkF1hbbWfs0Yc7fSwe1kSU2SnrPWFvY/LpVX0uclHad0X+Wtkq7KTt5njPl7pcPiSZKekPS+nHNvlvR9pVvEHZb0IWvtpsy4N/VzLgAAADCqHYqk9Otd6Yn6nt3ff6gsSWdM9emqBUFdOT+oGYTKAACULOAxet9xFXrPMSE9vDOiOze0a3NLssdxzx2I67o1h7Wi3quPrajUlfODcrvGbnCI3oWTmVB5R0SrG6MKJ/t/dTav0q2r5gd19YKgTpw0tkPlXMba8deMvFStra38YQAAhhx9zACU6nA0pd/sSvfte3p/TM4AXq2+aYpXVy0I6cp5Ac0ehbOMY2hwbwGA8rLW6vHGqO5c36EXDvXeompRtVv/sKJK71wUkt89+sNE7i99iySt1jRG9fDOiB7bPbBQeU5lulL56gVBrRwnoXJNTU3e/wlecQIAAAAjyFqrzqTVkZijlrhVS8xRS8zRkZijI3Gna31ne0rP7I9pAN+w1EmTvbpmflBXLghqLqEyAADDzhijt84J6pLZAT17IK6vb2jXk3tiPY7b3pbSLc8e0R0vt+nDy6v03mNCqvS6yjBilCqStHpiT1QP70iHyp0DCJVnV3RXKp88eXyEyn3h1ScAAABQgpRj1ZboDohbCgLirp+4VWvXcvox4fR//f6cUO/VNQvSffvmV/GyHgCAcjDG6Jzpfp0z3a91TXF9/ZV2/XpntEcrq71hR7e90Kqvrm/TB5dW6oPHV6rOT9A8mmSLAFpijpozH/b/dldEj74RVccAQuVZIbeuWpAOlU+ZAKFyLl6JAgAAABnhpKPnDsS1P5zKVBVbtcTT1cW5AXFLzFFb3A6oD/JQWlbn0dULQrp6flCLangpDwDAaLJysk8/OH+SGloT+sYrHXpgW1iFuWRLzOqOde365sYOve/YCn14eSXzJAyxwqA4/Tquez37mq452l0ckN0+2CKAmSGXrsxUKp86xSfXBAqVc/GqFAAAABOaY63+fCCu+7eF9audEbUnRte0HEtrPelqmPlBHVPrLfdwAABAP5bUePXtc+r0yZVV+tamDv3g1bAiBT2vOpNW39rUobu3dOjGxSHduDikQKZHs8ukK6NdkozJrCv30chk9vXYblTkvD6O73q+9HmOTQe0o6H6tpSgOPsTH4Jvi/VmRjZUnh/Um6ZO3FA5F5P85WCSPwDAcGCiDGB02taa0P3bI3pge1i7O1Ij+tx+t1Tvd6nW51Kt36W67I8v/VjrN6rzubSs3qtjCZVRBPcWABg7mqIpfXdzp763pUOt8bETPeWG0rlBdHrddAXVpuhjkf3ZaygdhEvqcYwrs70j04ZsOIPiwZgedOmKTKXy6YTKTPIHAACAiasl5uihHRHdvy3c54zvA1XtNXkBca3PpTq/6QqLs/tqc8LjOr9LQc/EflMCAMBEMjng1qdOrtYtyyt176ud+tamDh2MjJLktA9WUl5dqi3c29/ZY0+2CCD7mm1ZnVdXzg/qjKk+uV28fusNATMAAADGtYRjtaYxqvu3hfXY7mi/lTDTgi6dO8Pf9eaitqC6OBsg1/hc8vBGAwAADFC1z6VbVlTp75ZW6ifbwrrrlXbtGuFvUU0UXUGxz6W6QP4H/bmv8XLD5HqKAEpGwAwAAIBxx1qr9YcT+um2sH7xekSHY32nygG3dNm8oG5YFNJ5M/0ExwAAYNgEPEZ/c1yF/vqYkB7aEdHPtod1KOrIKtMDWek5ImQlR+kq4q5HawuOS1+z2Pb0ebbrfNmC/bJ569nl0SQ3KK4tCIizyz23G4U8rnIPfUIhYAYAAMC4saczpZ9vD+v+7WFtPZLs9/izpvl04+KQrpwfVLWPNyIAAGDkeFxG1y0K6bpFoXIPpUu2x7+13eFztlVG97rNC71t3qPtOicbcucG37YgCFfetW3XtSq86aA46DajYsJB9I2AGQAAAGNaZ8LRb3ZFdf/2sP64N9Zv5c3CKrduWBzS9YtCml/Fy2EAAIBCxhi5e811CXyRj1fUAAAAGHMca/X0vrju3x7Wr3dG1JnsO1au8RlduyCkGxYH9aYpPiphAAAAgCFCwAwAAIAx47UjCd2/PayfbY+osbPvSXE8Rlo1O6AbF4d0yeyAAkzaAgAAAAw5AmYAAACMas3RlH65I6L7t4X1UlOi3+NXTvLqhsUhXbsgqClB9wiMEAAAAJi4CJgBAAAw6sRTVo83RnX/trBWN0aVcPo+fkbIpesXhvTOxSEdX+cdmUECAAAAIGAGAACYaFKO1autSb10KK61TXFtOJxQJGXldxsF3EY+l1HALfndpuBHOfuNfJnj/bnHukzmOj3PD7jVdY7HqEcfZGut1jYldP+2sH6xI6yWWN99lYNuo8vnpVtgnDvDL7eLFhgAAADASCNgBgAAGMestXqjI6W1TXGtbUropUNxrT+c6HdSvOFmpB7hdNKx2hvup1RZ0pun+3TD4pCumB9Uldc1/IMFAAAA0CsCZgAAgHHkcDTVFSRnQ+WmaP+h7UizkiIpq0gqu9a3xdUe3bg4pOsWBTW3kpewAAAAwGjBq3MAAIAxqjPhaP3hRF518q6OVLmHNWRqfUbvWBjSDYtDOmWyt0dLDQAAAADlR8AMAAAwBiQcqy0tibzq5C1HknJK7HQxye/SKVO8OnmyTydP9ml6yKW4I8VSNudHiqas4o5VNGkVc3K2pWzeYyylzP7un2hK3cc53cdFU7bXcXuMdPGcgG5YFNIlcwLyuwmVAQAAgNGMgBkAAGCUsdZqR3sqr83F+sNxRUssTg55jFZOSofJ2VB5bqW7rBXBSacgiM6szwi5Ve2jrzIAAAAwVhAwAwAAlNmBcHoSvpeaElqbCZWPxEsrTfYY6fg6b1518rG1Hnlco6sS2OMy8riMKrzlHgkAAACAo0HADAAAMEKstXqjI6WNzQltbEloY3NCLzcl1NhZet/kRdVunTLZp5My1ckr6n0KekZXmAwAAABg/CJgBgAAGAbhpKMtLcl0mJwJlDc1J9SWKLFpsqRpQVemzYVPp0z26qTJPtX6aScBAAAAoHwImAEAAI6CtVaNnemq5E05gfL2tqRKj5KlKq/RSZN9OnmytytUnhlylbVvMgAAAAAUImAGAAAYoEjSauuRhF5pTlcjZ6uSS+2XnOVzScvrvTplsk8nT0mHyktqPHIRJgMAAAAY5QiYAQAAClhrtS/s5PVK3tScUENbUs7RZcmq9hotq/dqeZ1Xy+u9WlHv1bJ6r/xuwmQAAAAAYw8BMwAAmNCiSatXWxPdvZIzrS6aY85RX3thlTsdJucEynMr3bS5AAAAADBuEDADAIBRybFWCUeKO1ZJR4qnrBJO97aEo8y6VdyREqmC4x2bf67NHmMVc6Rd7el+ya+1JpU6yqrkSo/pCpKX1Xm1vN6j4+u8qvQyAR8AAACA8Y2AGQCAcS6esgonrWKp7sA1kRfQdj8mbSawTUlJJxPKFoS0SSc3yO0+P5kT/CYLAuDcY7oC4ZxwOJl5ztwA+WhD3+Eyr9KdrkjOhMkr6r2aV+WmXzIAAACACYmAGQCAMrLWKpKyiiStOpPpx3CRn/R+p8f+/POcvO3Z5eQoDWpHu5DH6Pg6T1dri+X1Xh1f51W1j6pkAAAAAMgiYAYATCjWpgPXeCpdORvPVPUmHHVV+CZytsdT2apcq1jOcnZ79jrp/d3Vt7nXb273y2w7VCQQTv+g/OZUujOtLdIVycvrvJpf5ZbbRVUyAAAAAPSFgBkAMCwKg9xYqrtFQyyV3h7LCWpjKZvZltmXDXizwW/O8bGc8DeWCXNjqfxj4056X6IgAI4f/bxtJXBLipfjicc8r0vyuYw8mceuZbeR10het5HPJXky+7wuyesy8rnTj97Mtrx9mWvU+11almlzUeunKhkAAAAASkHADIwB2a/QdybSlY+OTU9+5VjJSpl1yckcm91uM9uKHWsLju2+hk2f13W97P78Y62UE+7kBjeZ4Kcg1Cm2zdCvtEv2zzeV/bO3Nm85/ffYvT9lbfffWc65qUy/3NwJzeLZvri5y0X63eZW5eZOmlbYKzc70Vru/uw5udW7sVT6vxOUn8tIFR6jgDv9u5cbxnpyfn9zHz05v699HmPSv9/ZZa/LyJsNd03OddxGHpN/vs+dH/oW7vMY/p0AAAAAgNGOgBkYBknHqiNh1ZFw1JnMLnevd2aWOzL7OnOWc8/pTDjpbZlQebzJC5MKKxMLKw4zVYrZikSfKx1ue0x+6J0NXLvD9fwQNrvNFqznBrm24FrFjit6faUDXpsTAKcKnz+7Tfn7MbH53el+vyG3SyGvUdBtVJF5DHnSP0FP93LI41LQY1TRY7vJ2e7q2u/jAx0AAAAAwDAhYO5FKpP4ZN+PG429N+fW2q7qwWxgZnOXbXd1oc1UrRY7RuquYM3d59jCY/PDOWWPsZnrFzknt5K22Ni6nrdHmJe+Zu66U7DeVcGbU/1ZWA1qeznXyX3ezLWSTrpXakdB+NuZtGpPOJnQOD0JVzQ1LH+l404iUxmbRsqKkePJVN1mK+59uR90uPMr8XOPyX6w4c+pss1+8OF351/D61Jmm9HhA3u1eO7svCC4KzR2G/r8AgAAAADGLALmXkz6wd5+j0mHzt3LvW4zuftN17au43OOy27rPRjOD2KLHwMAo4PLSP5MP1x/JqT1u7tD2J77Mus5QW96W86xXccZ+XMCX79bOcel17PBb2EI7BrhDwwbEo6WzPCP6HMCAAAAADASCJiPQm6Fb48dfZ4FDJ7fLVV4XKrwpttCuEz6AwtX13L6QwqXMXJ1Lat7OXNs9gMPV+bY7uXuY03uNXo5VuquQC7szdvd07f3bUl+FXpwm+4/X3fm78Dlyv4dmK797uzfc87fm9uVPt6dM+lZYWuRrpYjBduyk6FlK3Q9RbZ5Cyp4s313C/tud7cxSQfDHipzAQAAAAAY1yZUwGyMqZd0j6SLJTVJ+qS19iflHRXGIyOp0mtU6TWq8LjSj16jSq9LlR5TZD0dHGf35a+nl73jLKhzrFWyIHSOO93buieQs11BdrzIxHRJR3khe/djfgDrMiYvdHcVCWld2XA975ju0D4b0Oeu5z63O/Mc2QC4MDA2ktyZwNid89xuJjIDAAAAAABj1IQKmCV9W1Jc0jRJKyX9zhiz3lq7qfBAl8nvPzzWZatbTeFyQfuOYscot7JV3VWshce6MudL3ZWvucdkA77u9e7rZ3tcuwrGVqz6NjcwLAwHVST4y57bdX7Rc03eflPkXJeRQplJs7LhcaU3dz0TJGd6qxIY9s1l0lWyPjd/TgAAAAAAAGPVhAmYjTEVkq6VtNxa2yHpGWPMryW9R9Kthcc33zSr6HVsJnUunACv120FE+mp4Jjc43KvkRf89gh9Tc9wuGh4THAHAAAAAAAAYPhMmIBZ0jGSktba13K2rZf0lsFcJBvamq7/GdTZgz0BAAAAAAAAAEatiRQwV0pqK9jWKqmq2MENDQ3DPiAAwMTBfQUAMNS4twAAhgP3FxSzZMmSXvdNpIC5Q1J1wbZqSe3FDu7rDw0AgMFoaGjgvgIAGFLcWwAAw4H7C0phsj2Fx7tMD+YWScustQ2ZbfdJ2mutvVWSWltbJ8YfBgAAAAAAAACUoKamJq8PsKtcAxlp1tpOSQ9Kut0YU2GMOVvSlZJ+WN6RAQAAAAAAAMDYNGEC5oybJQUlHZT0U0kfstZuKu+QAAAAAAAAAGBsmjAtMgAAAAAAAAAAQ2uiVTADAAAAAAAAAIYIATMAAAAAAAAAoCQEzAAAAAAAAACAkhAwAwAAAAAAAABKQsAMAAAAAAAAACgJATMAAAAAAAAAoCQEzAAAAAAAAACAkhAwAwAAAAAAAABKQsAMAAAAAAAAACgJATMAAAAAAAAAoCQEzAAAAAAAAACAkhAwAwAAAAAAAABK4in3AEaT1tZWW+4xAAAAAAAAAMBoVVNTY3LXqWAGAAAAAAAAAJSEgBkAAAAAAAAAUBICZgAAhllDQ0O5hwAAGGe4twAAhgP3F5SCgBkAAAAAAAAAUBICZgAAAAAAAABASTzlHgAAAAAAAKORtVZtCavmqKPmmKPDUUeHY+nl5mhKh7PbY45aoo7ak1ZeI/ncRl6Xkc+Vv+x1Gfnc6ceu/S4jrzvzWOSc7LI3e37hfpeR152z7JIqvS7V+qknAwCMDAJmAAAAAMC4lxsWH445XY+Hoym19AiPu49J2nKPvDRLaz26cFZAq2b7dcZUvwIeU+4hAQDGKQJmAAAAAMCYY61Vc8xRY2dKB8LdYXFzXnjspMPjMR4Wl2LLkaS2HOnQtzZ1KOg2evMMXzpwnhXQwmq3jCFwBgAMDQJmAAAAAMCoYq1VSyY83htOaU9nSns7U2rs7F7eG04pmir3SMeGSMpqdWNMqxtjklo1r9KtVbMDunCWX2+e4VeVl3YaAIDSETADAAAAAEaMtVZH4lZ7csLiPZ0pNXYmtTfsaE9nUns7HUVSo6PcOOQxqve7NCngynvMLk/yu1Sf2VbtcynlSHHHKu5YJRwpnrJKOFbxrmVl9nXv7zrWsUqkep6fXc5eJ1FwTu514ymr/RFHTh9/fLs6Urpna6fu2dopr0s6fapPq2YFdOHsgJbXeahuBoD/z96dh0d21Xcaf09VqUq7et8Xd9ttd7sBg20MhhgMNhibJJglgYEECNgwkEkmk2Uyw5BgQpgkkDDJkLCZPSQMMIONwcbgBTAY4w2wca+y3fuubu1S7Wf+qJJaUkvdalndLanfz/PoqbrnnnPrtjC6Vd976nd0UgyYJUmSJEmTIsZIZzU8Hph5vHtIiDzQ1neGalU0pAKzRwmGB8Pj6vNKnyRzMgnqpmHt4o5cmR/ty3HPniz37M6xp2/sqd6FMvxkf56f7M9z06NdLKxL8PKltVy9NMPLlmSYU5s8jWcuSZqODJglSZIkSePWlS/zZGeRrZ1Fnu4uDpuFvKe3RO9pDI8bU4GlDUkWNySZPxgMV8PjgeC4GhRP17B4ImZlErzmnDpec04dMUY2dxS5e0+We/fkuH9/jnx57LEH+st89ck+vvpkHwG4eF4NVy2rBM6XzEuTTJwdv0NJ0vgZMEuSJEmShinHyK6eEk92FdnaUaS1s0hrZ4HWziL7+4+TTk6i+mp4vLQhyZL6yuOyhiRLqm1LG5I01wTLOZxACIF1s2tYN7uGP3hWE72FMvfvzw8Gzk92FcccG4FH2wo82lbgI7/sZlY6cOWSSu3mq5bWsqTB2c2SJANmSZIkSTpr9RQqs5FbO4u0dhVp7SiytbPA0xZpmRsAACAASURBVF2lU1oDuS5ZCY+HhsVLqyHykmqQ3JI2PD4VGmoSvHJ5La9cXgvA9u4i9+zJcvfuHD/el6PnODPQO/KRW7f3c+v2fgAunJ3iqmo5jRcuzJBJ+r+XJJ2NplzAHEI4B/gEcDmQA/4v8EcxxmII4bnA54B1wCbgnTHGX1bHBeBvgRuqh/os8N9ijLG6f8yxkiRJkjRTxRjZ21emtbNQmY3cVQ2UO4rHrc07UbVJBmccD4TFSxtSLGlIsLQhxbKGJLMMj6eMc5pSvHNtI+9c20i+FHnwYL5Su3lPjl8dKRx37Mb2Ihvbe/j4Ez3UpwJXLM5w1ZIMVy+rZXXzlIsbJEmnyFT8i/8J4CCwGJgF3AW8N4TwKeBbwD9W+7wb+FYIYU2MMQ+8C7geuIjKN3nuArYBnwohpE8wVpIkSZKmtf5i5KmuSimLrZ3FwTrJT3YWJ7UucirAquYUa1pSnNecYkXj8DB5TiZheDxNpZOVkPiKxRluuhT295W4txo237s3S3tu7P+O+oqR7+3K8r1dWXiwk1VNSa5eWsubzqvnkvnp0/ivkCSdbqE6wXfKCCFsAv4kxnhHdfujQDPw/4AvAMuGzEreCbwrxnhnCOGnwBdjjJ+p7nsncGOM8YUhhFceb+zAa3d2dk6tX4YkaUZobW1lzZo1Z/o0JEkzxOFsibt+tZ2+pkVs7SwMBsm7ekpM5geaWenA+S01rJmV4vxqmHz+rBTnNKWocaG3s06pHPnl4QJ378lyz+4cj7TlKY/zP7hL5tXwrgsbuf6cOstoSFOcn100Hi0tLcP+mE/FGcz/CLwphPBDYDZwLfAXwHrg8Tg8EX+82n5n9fGxIfseq7YxjrGSJEmSNKUUy5HWziJPHCmwob3AE0cqP5VF9mqBjmf8GokA5zQmWTOrhjXVAHkgSJ7rTGQNkUwELpmf5pL5af78udCRK/PDvblK4Lwny76+sRd/fLStwLvva+f9D3Xy9gsa+L0LGlwgUJJmkKkYMN9HpdxFF5AEvgTcCrwf6BzRtxNoqj5vHLG/E2is1mYeuW/k2GO0trZO8PQlSTqW1xVJ0vF0FKC1NzHsZ1tfIB8nJ+BtSEbOqStzTn1kZV2ZlXWRc+rLLKuNpBMjOndDeze0T8orayZbD6xfCH+4AJ7qCzzQnuSB9iS/7EpQGOW/3UPZMh99rJuPPd7Fy+aWeOPiIhc1l/E+hjS1+NlFoznezPYpFTCHEBJUZhR/BngRlWD488DfAfuolMoYqhnorj7vGbG/GeiJMcYQwsh9I8cew68DSJImi18zkyQNKJYjT3YV2XDk6IzkDe0F9h5n9ud4BWB5Y5LzWyr1kde01LCmpVLeYkGds5F1ap1P5evHAL2FMj/Ym+OLW3q5e0/umL6lGLi7LcXdbSmePaeGG9c18Fur66lL+d+odKb52UUTMaUCZmAOsAL45xhjDsiFEL4A/DXwx8CfhBDCkFIXzwH+pfp8A5UF/h6qbl9UbRvYd7yxkiRJkjSp2nPlwRD5ifYCG44U2NxRIFt6ZsdNJ2BlXZnnLmyoBsmVMPnc5pQBnaaEhpoEv76yjl9fWceTnQU+u7mXf2/to6twbNHmXx0p8If3d/CBRzp565oG3rmugRWNUy2qkCQdz5T6qx1jbAshbAPeE0L4eyozmN9GpV7yD4ES8IchhE8BN1aH3Vt9/DLwxyGEO4AI/Anw8eq+E42VJEmSpAkplSNPdRWHBclPHCmyp+8ZJsnAwroEz5pTw/rZNTxrTuVnTUuK7U89yZo1yyfh7KVT67yWGv72BbP4Hxc387Un+7h5Uy9bOovH9GvPRf7piR4+vqGHVy2v5d3rGnjJ4owz7yVpGphSAXPV66gs9PfnVELhe4H/EmPMhxCuBz4L/C2wCbg+xpivjvs0sBr4VXX7s9U2xjFWkiRJkk6oI1fmieqCexuqgfKm9mc+K7kmARfMqmH97BTPmlPDs6uh8vw6F0LTzNBUk+CGdY28c20D9+3L8elNvdy5K0t5xKTmcoQ7dma5Y2eWtbNS3LiugTeeW09jzchi4ZKkqSIcrRihzs5OfxmSpElnHTNJmp5K5cjGjiIPH8zz0MEcDx3M83T3M5+VvKAuwbNm17C+OiN5/ewazm9JkU6Of6am1xbNBDu6i3x+cy9fbu2lPTf2x/HmmsCb19Rz49pGzm2ZivPkpJnD64vGo6WlZdibFv8yS5IkSRKV2ckPH8rz4ME8Dx/M8+ihPD3Fic9BSQU4f1Z1RnK1xMX6OTUscFayBMDKphQffH4Lf/68Jv7v0/18ZlMvTxwpHNOvqxD51MZePrWxl1cszfCuCxu5ammGhOUzJGlKMGCWJEmSdNYpx8jWziIPHcwP/mwdpS7seM2rrdRKHjoz+YKTnJUsna3qUwneen4Dv7umngcO5Ll5Uy+37einNMr9nbv25LhrT47VTUluWNfIW9bU05K2fIYknUkGzJIkSZJmvK58mUcP5XnoUCVMfuRQns78yc9OTga4oCU1OBt5IFReUJdwMTLpGQoh8KJFGV60KMPe3hKf39LLl7b0cihbPqbv090l3vdQJx/+eRdvPLeed13YwNpZNWfgrCVJBsySJEmSZpQYI091FQdLXTx0KM+m9iITKXYxJ5PgsgVpLluQ5vnz01w8r4YGFxuTTrklDUnef3Ezf3ZRE7du7+czG3t4tO3Y8hm9xcjnt/Ty+S29vGRxhneta+Da5bUkE97wkaTTxYBZkiRJ0rTWUyjz87bC4GJ8Dx8qcCR37IzHE0kEWDcrVQ2UM1w2P83q5qQzk6UzKJMMvPHcet54bj2PHsrzmU093LKtn/wo/xe/b1+O+/blWNaQ5Ia1Dbz1/Hrm1FrzXJJOtRDjxBetmGk6Ozv9ZUiSJp0rMUvS5IkxsqOndHR28sE8G9oLo9ZqPZFZ6cDz56d5/oI0L1iQ5uL5aZqmyexkry06mx3sL/Gl6qzlfX1j30yqTcIbVtdz47oGLpqbPo1nKE1fXl80Hi0tLcPuvjuDWZIkSdKUVY6Rxw4XuG9fbnAxvtHqsY7H2urs5OfPr5S8WNOSIuHsZGnaWVCX5M+e28wfPaeJ7+zo5zObenngQP6YftkSfKW1j6+09nF+S4pXr6jl1SvruHhejf/fl6RJZMAsSZIkaUo50Ffi3r057t2T5d49OQ5PoNxFU03g0urs5Mvmp7l0fppZmekxO1nS+NQkAq9dVc9rV9Xz+OE8N2/q5RtP95EtHdt3a2eRrb/q4X/9qodFdQmuXVHLq1fUccXiDJmkYbMkPRMGzJIkSZLOqHwp8uDBPPfsyXLPnhy/OnLsQl4ncl5zarDUxfPnp1k7K+UiX9JZ5Dlz03z819J88NJmvtLax82be9nVM0rSDOzvL/OFLX18YUsfTTWBq5fW8uqVtVy9tNYbUZI0AQbMkiRJkk67bV1F7tmT5e49OX6yL0dPcfxFlOtTgUvm1VTKXVQD5bku5CUJmFOb5A+f3cTvr2/kzl1ZPr+llx/tzTHWn5juQuSW7f3csr2fVIArFmd49Yparl1Rx9IG/65I0ngYMEuSJEk65XoKZX68L8e9e3LcsyfL092jzywcTXM6cOXiDFcsznDZgjTrZ9eQcnaypONIJgKvXlnHq1fW0ZErc9fuLLfvzHL37uyYN7SKEX6wN8cP9ub405918rx5Nbx6RR3Xrahl3awUwbrNkjQqA2ZJkiRJky7GyBPtRe7dUwl0fnYwT2GcpZQDcPG8Gl6+tJarlma4dH7aQFnShM3KJPitc+v5rXPryZUi9+3LcfuOfr67K8uB/rH/MP2ircAv2gr89c+7WNWUHAybX7AgbQkeSRrCgFmSJEnSpDicLfGDvTnu2ZPjB3uy7D9OcDPSwroEL19ay9VLM1y5JGPJC0mnRCYZeMWyWl6xrJaPxcijhwrcvrOfO3Zm2dpZHHPctu4S/7yhh3/e0MO82gSvWl7LdStqedmSWupShs2Szm4GzJIkSZImpFiOPHIozz3Vshe/aCsw3krKNQm4fGGGq5ZmuGppLetn+/VzSadXIoRKHfcFaW66tIWtHQXu2Jnljp1ZHjqUH3NcW7bMV1r7+EprH/WpwMuXZLhuRS2vWl7LHG+OSToLGTBLkiRJGrddPcXBOso/3JejKz/+xflWNyW5alml7MWvLcrQWJM4hWcqSSfn/Fk1nD+rhj96ThP7+0rcuSvLHTv7+eHeHPkxvpDRV4x8Z2eW7+zMkgxw+cI011VLaZzTZOQi6ezgXztJkiRJY+ovRn56IMfdu7PcuyfHluN8hXykxlTgisUZrl5WmaVs2CJpulhUn+TtFzTw9gsa6C6UuWd3jjt29nPn7uyYN9ZKEX6yP89P9ud530OdPGtODdetqOXVK2p5zpwav6UhacbyHZ4kSZKkYQZm7n13Zz8/2pcjWxr/2OfMqeGqpRlevrSyEFY6aaAiaXprqklw/ao6rl9VR6EcuX9/jtt3ZrljR5Y9fWP/gXziSIEnjhT4yC+7WdaQ5NrltbxoUZrLFmRY2mApDUkzhwGzJEmSdJaLMbKpo8gdOyuh8qNthXGPnZtJ8PJqHeWXLcmwsN7QRNLMVZMIXLmkliuX1PKRF0QeO1zg9p1Zbt/Zz8b2sb/hsbu3xM2be7l5cy8AS+uTXLYgPfjz7Dk13pCTNG0ZMEuSJElnoUI58sCBPN/d2c8dO7Ps6BnfNOVkgMsWpLlqaS1XL83wnLk1JPzat6SzUAiB585L89x5af7Hxc1s7y5WwuYd/fzsYJ7ycUrU7+krccv2fm7Z3g9AbRKeNy/NZfOPhs7z67xhJ2l6MGCWJEmSzhJd+TL37Mny3Z1Zvr87S8c4F+hb3pjk6mrZi5csztCSdnE+SRrpnKYUv7++kd9f30hbtsT3dmW5fWeWH+zJ0V86/t/bbAkeOJDngQP5wbZVTUmevyDNCxakef78NBfOriGV8IaepKnHgFmSJEmawXb3FLlzV5Y7dmb58f4chfL4xl0yr4brVtRx7Ypa1s1KuTiVJJ2EebVJ3rKmgbesaaCvWOaHe3M8cCDPwwfz/OJwntw4vjSyrbvEtu5+vv5UZZZzYypwcXWG80DoPCvjDT9JZ54BsyRJkjSDxBh5/EiB7+6shMqPHxlfPeVMEq5cnOHaFXW8ankti6ylLEmToj6V4LoVdVy3og6AXCnyqyMFHjyY56GDOR46mGdf34nv/vUUI/fty3Hfvtxg2wUtKZ6/4GjovKYlZdkiSaedAbMkSZI0zeVLkfv35yqL9O3Ksrt3fPWU52YSXLO8lmtX1PLyJRkaapwJJ0mnWiYZuHR+mkvnp/n99Y3EGNndW+Lhg3kePJjn4UN5Hj9coDiOKkZbOots6SzyldY+AFrSgcvmpwdLa1w8P02Tf9slnWIGzJIkSdI01JErc9fuyizle/Zk6SqMr57yec0prltRCZUvm58maT1PSTqjQggsb0yxvDHF61bXA9BXLPOLtsKw0Lkte+JZzp35yF17cty1pzLLORHgwtk1gyU1XrAgzTlNScseSZpUUzJgDiG8CfgAsALYD7w9xvjjEMJVwL9U2x+stu+ojskAnwTeAPQBH4kxfmzIMcccK0mSJE0H27uLfLc6S/mn+3Pjmt0WgBcsSHPtilquW1HLmpaaU36ekqRnpj6V4MWLMrx4UQaolD/a1l3ioYN5HjqY58GDOTZ1FCmf4DpQjvDEkQJPHCnwuc29AMzJJFg3O8XaWTVc0JJi7ewa1s5KMb82YfAsaUKmXMAcQngF8HfAG4GHgMXV9nnAN4EbgG8DHwK+BrywOvQmYA2wElgE/CCEsDHGeOc4xkqSJElTTjlGftlW4I6dWe7Y1c/G9uK4xtUlAy9fmuHaFbVcs6yW+XXWU5ak6SyEwOrmFKubU7zpvMos5658mZ+35QdD54cP5enMn/jO45Fcmfv357l/f35Y+5xMggtmpVg7qxI+DzwuqDN4lnR8Uy5gBj4I/FWM8WfV7T0AIYR3ARtijN+obt8EtIUQ1sYYNwNvozIruR1oDyHcDLwduBN43QnGSpIkSVNCsRz58b4ct+3o57s7s+zvP/FXogEW1CV41fLKLOWXLq6lLmUYIEkzWXM6wZVLarlySS1QuSm5tbM4GDg/dDDP1s7x3ZiESvD8wIE8DxwYHjzPSofBwPmCgeB5dg2LDJ4lVU2pgDmEkAQuBW4LITwJ1AK3An8GrAceG+gbY+wNITwFrA8hHKAy0/mxIYd7DLi++nzMsYABsyRJks6oUjly/4E8t2zr47btWQ7nxhcqr51Vrae8vI5L5teQ8IO+JJ21EmEgCK7hrec3ANCeK/PwwTwPHaoEzo8eytM7nvpKQ3TkIz87mOdnB4cHzy3V4PmCavC8rvq4pN7gWTrbTKmAGVgI1FCpo3wFUAC+BbwfaAQOjejfCTRV9w1sj9zHCcaOqrW19eTPXpKkMXhdkTRSOcIvuxLc3ZbknrYURwon/jCeIPLc5jIvnVviijklltdFoAs64anOEw7XDOO1RdJ4rAJWNcEbm6C0GvZlA0/1JdjWF3i6L8G2vgTb+gO58smFwp35yIPVRQiHakhGVteXWVU/8FhmdV1kYSZi7jw9eH3RaNasWTPmvqkWMPdXHz8eY9wHEEL4GJWA+T6geUT/ZqAb6BmynR2xj+r+scaO6ni/NEmSTkZra6vXFUlA5evLDx/M881t/dy2o599fSeeqdyYCly1LMN1K+p4xdIMc2qtpyyvLZImbi3wshFt5RjZ2VNic0eBze1FNncU2NJZZEtHkb6TnPHcWwr8qjvJr0YkLo2pMGy286rmFAvqEiyoSzKvNkFjTeIZ/bs0Oby+aCKmVMAcY2wPIewGhv71Gni+gUqdZQBCCA3AuVRqK7eHEPYBFwF3VbtcVB1z3LGn4t8hSZIkDYgx8mhbgVu29fOt7f3s7i2dcExLOvAbK+t4zTl1vGRxhkzSKV+SpFMnEQLnNKU4pynFq5YfbS/HyK6eEps7imzpKLC5oxo+dxRPutRGT7FyPXy0rTDq/vpUYF5tggV1CebVJpk/5PlgW12lbXY6QTLhtVGaKqZUwFz1BeAPQgh3UimR8V+A7wC3AB8NIbweuB34S+DxIYv0fRl4fwjhESqlNm4Efq+670RjJUmSpEkTY+Sxw5VQ+Zbt/ezsOXGo3FwTuG5FLa9bVc+VSzKkDZUlSWdYIgRWNqVY2ZTimuW1g+3lGNndW2JLNXAeCKC3dBTpLpxc8Dygr1iZRV25Zo4eQh89L5hXm6gG0pUweuD5sLa6BAtqk9S68K10Sk3FgPlDwDxgK5VyF18HPhxjzFYD4n8GvgI8CLxpyLgPAJ8EdlAptfF3McY7AWKMh04wVpIkSXpGYow80V7klm193LKtn23dJw6VG1OBa1fU8tpVdVy1tNaZypKkaSERAisaU6xoTPGKZUeD5xgje3pLbOkssqm9MBhAb+ko0jXB4Hk05QgH+8sc7C+zsb14wv5NNYH5tQnmDwbQR2dG/86aBuoMoKVnJMQ4ef8Hn+46Ozv9ZUiSJp11zKSZbVN7gW9u6+fW7f20dp74Q259KnDNskqo/IpltX6o1YR4bZE0ncQY2ddXHjbbeW9viUPZMof6yxzKlsifeFmCU2Lf7y7xWjyE1xeNR0tLy7D/00zFGcySJEnSlLa1o8At2/u5ZVs/mztOHCrXJuGV1VD5lctqaXAhI0nSWSSEwJKGJEsakrx86bH7Y4x0FSKH+iuh88H+Mm3ZUjV8Lg+2D4TRnfnJmR/YVBMMl6VJYMAsSZIkjcPTXUW+ua2fW7b1sWEcX8dNJ+DqZbW8blUd1yyvpclQWZKkUYUQaEkHWtIJzms5cf9cKdI2LHg+GkAfzJZoGxFMl8bIo+fXem2WJsMzDphDCNuAE946ijGufqavJUmSJJ1O27uL3FpdqO+xw8dfcAigJgEvX5LhtavquXZFLS1pP7hKkjTZMsnA0oYkSxuSJ+xbjpGOXDVwHgid+8sczJZpdPayNCkmYwbzDUOeXwK8jcpiejuAlcDvA1+ahNeRJEmSTrldPUVurZa/+HnbiUPlZIArl2R47ao6fn1FHbMyhsqSJE0ViRCYU5tkTm2SC870yUgz1DMOmGOM9ww8DyH8I/CqGOOuIW23A7cDH32mryVJkiSdCqVy5Pu7s3xmUy8/2Js7Yf9EgJcszvDac+r49ZW1zK098QwqSZIkaSaa7BrMS4HOEW2dwLJJfh1JkiTpGWvPlfnK1l4+u7mXHT2l4/YNwIsXpXntqjp+c2Ud8+sMlSVJkqTJDphvB24NIXwI2A0sB95XbZckSZKmhCeOFPjMph6+8VQ//WOt/FN1+cI0159Tx2vOqWNRvaGyJEmSNNRkB8zvAj4EfBFYDOwHvg58YJJfR5IkSTophXLk9h1ZPr2phwcO5I/b9+J5NbxhdT2vOaduXAsISZIkSWerSQ2YY4z9wJ9WfyRJkqQz7lB/iS9u6eULW3rZ21ces18mCa9bVc+71jXwvHnp03iGkiRJ0vQ12TOYCSGcC1wENA5tjzF+ebJfS5IkSRrLo4fyfHpTD7du6yc/dq7MsoYk71jbwFvPr2eei/VJkiRJJ2VSA+YQwp8DHwQ2AH1DdkXAgFmSJEmnVK4UuWVbP5/Z1MPP2wrH7XvFojQ3rmvkuhW1pBLhNJ2hJEmSNLNM9gzmPwYujzH+YpKPK0mSJI1pT2+JL2zu5Ytbe2nLjj1duT4VeNO59dywroELZ9ecxjOUJEmSZqbJDpjzwBOTfExJkiTpGDFGfnogz2c29fCdHVlKcey+q5qS3LCukbecV8+sTOL0naQkSZI0w012wPw+4J9CCB+IMR6a5GNLkiRJ9BXLfOOpShmMDe3F4/Z9xdIMN65r5OplGRLBMhiSJEnSZJvsgPlL1cd3h6Nv4AMQY4yumCJJkqQJ295d5LObevnX1l4682NPV26uCbxlTT03rG3k3JZJX9NakiRJ0hCT/Y57zSQfT5IkSWexcoz8cG+OT2/q5fu7shynCgZrZ6W4cV0Dbzy3nsYay2BIkiRJp8OkBswxxqcGnocQFsQYD07m8SVJknR26MqX+eqTfXx2cy+tnWOXwUgEuG55LTeua+Qli9MEy2BIkiRJp9WkBswhhBbg48BvAWWgIYTwG8ClMcYPTOZrSZIkaebZ2lHg5k29fPXJPnqKY89XnpNJ8Lbz6/m9tQ2saLQMhiRJknSmTPa78U8CPcD5wOPVtgeBfwAMmCVJkjSqH+/L8Q+Pd/PDvbnj9nvOnBredWEDr19VT13K2cqSJEnSmTbZAfPVwLIYYz6EEAFijAdDCAsn+XUkSZI0A2w4UuCDj3by/d1jB8upANevquPGtQ1ctsAyGJIkSdJUMtkBcxcwB9g/0BBCWA4cmOTXkSRJ0jS2u6fI//xFN199sm/MhfsW1iV4+wUN/N4FDSyqT57W85MkSZI0PpMdMH8e+EYI4X1AIoTwfOBvgE9P8utIkiRpGurIlfnHX3XzqY09ZEuj93nBgjQ3rmvgN1fWkU46W1mSJEmayiY7YP4bIAd8DqgF/p1KuPyxSX4dSZIkTSO5UuTmTT38w+PdtOdGn7N8+cI0N13SzAsWZk7z2UmSJEmaqEkLmEMISeAtwD/HGP9hso4rSZKk6ascI994up+//nkXu3pGn7J8QUuKD1zazLXLa62vLEmSJE0zick6UIyxBHw8xnj8pb/HKYSwJoSQDSF8ZUjbm0MIO0IIvSGEW0MIc4bsmxNCuKW6b0cI4c0jjjfmWEmSJE2+H+zJ8tLbDvHu+9pHDZcX1SX43y+exf3XL+C6FXWGy5IkSdI0NGkBc9XtIYTrJulY/wI8PLARQlhPpdzG7wILgT7gEyP656v73gJ8sjpmPGMlSZI0SR47nOe132vjtd8/zK+OFI7Z31QTeP/FzTz6+oW89fwGUgmDZUmSJGm6muwazAngmyGEnwC74Oii4DHGd4z3ICGENwEdwE+B86rNbwG+HWO8r9rnL4BNIYQmoAy8HnhWjLEH+EkI4TYqgfJ/O97YGGP3M/kHS5IkqWJHd5EP/7yLrz/dP+r+mgS844IG/uy5TcyrTZ7ms5MkSZJ0Kkx2wNwKfPSZHCCE0Az8FfBy4IYhu9ZTCZwBiDE+FULIA+dTCZiLMcatQ/o/Brx0HGMffSbnK0mSdLY7ki3x949389lNveTLo/d5/ao63n9xM6uaJ/vtpyRJkqQzaVLe4YcQ/kOM8asxxr+YhMN9CPhcjHH3iDp8jUDniL6dQBNQArrG2HeisaNqbW09ubOWJOk4vK5oJsqW4Gv7UnxxVw09pdHLXFzaUuIPzilwYVMfxQOHaT1wmk9SmsG8tkiSTgWvLxrNmjVrxtw3WVNIPg189ZkeJITwXOBq4Hmj7O4Bmke0NQPdVGYwj7XvRGNHdbxfmiRJJ6O1tdXrimaUUjny1af6+JvHutnTd+zifQAXzk7xwUtbuHppxsX7pFPAa4sk6VTw+qKJmKyAebI+NVwJnAPsrH4QaQSSIYQLgTuBiwZfMITVQAbYSiVgToUQ1sQYB26zXARsqD7fcJyxkiRJGocYI3ftznHTI51s7CiO2mdZQ5L3Pa+JN55bT9LF+yRJkqQZb7IC5mQI4WUcJ2iOMd47juN8Bvg/Q7b/lErg/B5gAfBACOEK4OdU6jR/c2CRvhDCN4G/CiHcADwXeA3woupx/u14YyVJknR8Pz+U5y8f6eQn+/Oj7m9JB/7kOU3cuK6RupTBsiRJknS2mKyAOQN8jrED5gisPtFBYox9QN/AdgihB8jGGA8Bh0II/5FKWDwXuBv4vSHD3wt8HjgIHAbeE2PcUD3uhhOMlSRJ0ii2dRX5q0e7uGV7/6j70wl417pG/uSiJmZnEqf57CRJkiSdaZMVMPfGGE8YIJ+sGONNI7b/Hfj3MfoeAa4/zrHGHCtJm9xJMwAAIABJREFUkqThDvWX+Mhj3Xxhcy/FeOz+APz2uXX8j4ubWdE4WW8pJUmSJE03fhqQJEnSoN5CmU9s6OF/P9FDd2GUZBm4ammGmy5t4dlzak7z2UmSJEmaaqbaIn+SJEk6A4rlyFda+/jbX3Sxv788ap+L5tbwV5c289Iltaf57CRJkiRNVZMSMMcYmybjOJIkSTq9YozcsTPLBx/tYmtncdQ+KxqT/MXFzbx+dR2J4LwCSZIkSUdZIkOSJOkslC1G/u+2Pj65oYcN7aMHy3MyCf70oibeubaBTNJgWZIkSdKxDJglSZLOIgf6SnxuSy+f39xLW3b0Uhi1SXjv+kb+87ObaEknTvMZSpIkSZpODJglSZLOAo8fzvPJjb38v6f7yI+eK5MI8Obz6vnvz2tmaUPy9J6gJEmSpGnJgFmSJGmGKpUj392V5ZMbe7h/f37MfokAv76ilv/2vGYunF1zGs9QkiRJ0nRnwCxJkjTDdOXL/FtrH5/e1MP27tKY/ZprAm89v4Eb1zWwssm3hZIkSZJOnp8kJEmSZojt3UU+s6mHr2zto6sQx+y3qinJf7ywkTevqaepxhrLkiRJkibOgFmSJGkaizHywIE8n9jQwx27spTHzpW5YlGa96xv5JpltSQT4fSdpCRJkqQZy4BZkiRpGsqXIt/c1s8nN/bw2OHCmP3SCXjD6nres76RZ8+xvrIkSZKkyWXALEmSNI20ZUt8YXMvn93cy4H+8pj95tcmeOfaBt6xtoEFdcnTeIaSJEmSziYGzJIkSdPAxvYCn9zQw9ef7iM39rp9rJ+d4r3rG3nD6noySctgSJIkSTq1DJglSZKmqHKM3LU7xyc39vDDvbkx+wXgVctree/6Rn5tUZoQDJYlSZIknR4GzJIkSVNMT6HM/3myj09t7OXJruKY/RpTgbesqefdFzayutm3dZIkSZJOPz+JSJIkTRG7eorcvKmXL23tpTMfx+y3vDHJu9c18LvnN9CSTpzGM5QkSZKk4QyYJUmSzrCHDub45IZebtvRT2nsXJnLF6Z5z4WNXLeillTCMhiSJEmSzjwDZkmSpDOgI1fmrt1ZPr2ph0cOFcbslwrwutV1vOfCRp43L30az1CSJEmSTsyAWZIk6TQ42F/ip/vz3H8gx0/359jYXuQ4k5WZk0nwjgsaeOe6BhbXJ0/beUqSJEnSyTBgliRJOgV29RT56YE8P92f46cH8rR2jr1Y31BrZ6V4z4WN/Pa59dSlLIMhSZIkaWozYJYkSXqGYow83VUanJ18/4E8u3pKJ3WMVyzN8N71jVy5JEMIBsuSJEmSpgcDZkmSpJNUjpHNHcXB2ck/3Z9jf3/5pI4RgAtnp3jpkgxvP7+B82fVnJqTlSRJkqRTyIBZkiTpBIrlyBNHCtx/IM/9+3M8cCBHe+54FZSPlQxw0dwaXrwow4sWpnnhwgyzM4lTdMaSJEmSdHoYMEuSJI2QL0V+0Zbnp9VA+cGDeboLJxcopxNwyfw0L16Y4UWL0jx/QZqmGgNlSZIkSTPLlAqYQwgZ4BPA1cAc4Cngv8cYv1vdfxXwL8AK4EHg7THGHUPGfhJ4A9AHfCTG+LEhxx5zrCRJOrv1Fcs8cqjA/fsrNZQfOVSgv3RygXJ9KnDZgjQvWpjmRYsyXDIv7SJ9kiRJkma8KRUwUzmfXcBLgZ3AdcDXQwjPBnqAbwI3AN8GPgR8DXhhdexNwBpgJbAI+EEIYWOM8c4QwrwTjJUkSWeRznyZhw7mB2so/7wtT+HkSijTnA5cvqASJr94UYaL5tZQkzBQliRJknR2mVIBc4yxl0pQPOA7IYRtwCXAXGBDjPEbACGEm4C2EMLaGONm4G1UZiW3A+0hhJuBtwN3Aq87wVhJkjQD9RXLbO0osqmjyKb2Aps7CmxsL7K7t3TSx5qbSfCiRenBGsrrZ9eQNFCWJEmSdJabUgHzSCGEhcD5wAbgPcBjA/tijL0hhKeA9SGEA8Diofurz6+vPl8/1ljAgFmSpGkuV4q0dh4NkQcC5e3dJU6u0MVRS+oT1TC5UkP5/JYUIRgoS5IkSdJQUzZgDiHUAP8GfCnGuDmE0AgcGtGtE2gCGodsj9xHdf9YY0fV2to6wTOXJOlYXlcmR7EMu7KBp/oSPN2b4Km+wNN9CXb1B0o8s/B3WW2Z5zWXeV5Liee1lFmaiYTQU9l5CJ4c+U5Cks4wry2SpFPB64tGs2bNmjH3TcmAOYSQAP4VyAP/qdrcAzSP6NoMdFf3DWxnR+w70dhRHe+XJknSyWhtbfW6cpJK5cj27hKbOgrVWclFNnUUaO0snnSt5NEkA5zfkuLy6uzkFy3MsKQh+cwPLEmnidcWSdKp4PVFEzHlAuZQ+e7p54CFwHUxxkJ11wYqdZYH+jUA51KprdweQtgHXATcVe1yUXXMcceewn+KJEk6gXKM7OopVQLk9kI1UC6ytbNA9uTLJB8jAOc0JVk3u4Z1s1KsnVXDutk1rGlJkUla7kKSJEmSnqkpFzADnwTWAVfHGPuHtN8CfDSE8HrgduAvgceHLNL3ZeD9IYRHqITTNwK/N86xkiTpFCqUK0Hy011FNncUBgPlLR1FeooTrZI83LKGJBfOPhoir5uV4vxZKepTiUk5viRJkiTpWFMqYA4hrATeDeSA/UMW0nl3jPHfqgHxPwNfAR4E3jRk+AeohNM7gH7g72KMdwLEGA+dYKwkSXqGcqXIju4iT3cXebqrxLaugedFdvaUKE1OjsyiugTrZtewdlaqGiTXcMGsFM1pg2RJkiRJOt2mVMAcY9wBY6/QE2O8G1g7xr4c8I7qz0mNlSRJ49NXLLO9uzIT+WiAXOLp7iK7e0pMUoYMwNxMgnWzU6yrzkgeCJRnZwySJUmSJGmqmFIBsyRJOvO6C+VqgFwJjgeC5G1dRfb2TcIKeyO0pEM1RB5e3mJ+nYvuSZIkSdJUZ8AsSdJZqCNXCZEHSlg83VVkW3Vm8qHs5IfIUCltsao5xbnNKdbOSnHh7BrWzqphcX2CIWWxJEmSJEnTiAGzJEkzTDlG2rJl9vaW2NtXYl9fiX29ZXb0FAdD5fbcZBazOGpZQ5JVTUlWN6dY3ZxiVVPl8ZymJI01lraQJEmSpJnGgFmSpGkkW4zs7y+xt7cSHO/tG3heZl9fiT29JQ70lyicmknIJAIsbxgaIB99vrIxRV3KmciSJEmSdDYxYJYkaQqIMdKZj4OB8dGZx9UQua/Mvt4Sh3OnKDkeIhXgnKYUq5uTgzOQVzenWN2UYnljknTSEFmSJEmSVGHALEnSKVaMsGdgxvHIxyEzkPtLp6ZsxWgySVjVlBoSICdZ3ZRiVXOKZQ1JUglDZEmSJEnSiRkwS5J0knKlyOFsmbZsiSO5Mm3ZcnW7XN0ucbjadjhXpq2/jjL7T+s5tqQDS+qTLK5PsqSh8risIcmq5hSrmyptCRfWkyRJkiQ9QwbMkqSz2kBpioHA+HA1MD5SDYwP58ocrgbGAwFyd+FkZxpPXpCbCLCwLjEYHi9uSLJkSIi8pD7B4vokDS6oJ0mSJEk6DQyYJUkzRoyR3mKkPVemPVcJgw8PC4rLR2ceZ8u05SpBcvH0VaY4rrpkYElDohoUHw2NB2YhL6lPsqAuYfkKSZIkSdKUYcAsSZpyYox0FSpBcUc1LB4IjNtzZdrzZdpzI/bnK4+FU78G3oTMzSSqs42rs48HZxwfDY9b0oFg2QpJkiRJ0jRiwCxJOmVK5aNB8cifoWHx0RC5Ghrny5zG9e5OWjLAnEyCebUJ5tRWHudmksytTTB3cDtR3U7SvvtpnnXBmjN92pIkSZIkTToDZkkSUJk1nC1BX7FMTyHSV6yUm+gtlKuP1e1qW1+1racY6SuWj+4vRLoLlcC4Mx+ZwjnxoMZUGBIUHw2G51UD44G2edX2lnQ4qQXy+iyHLEmSJEmaoQyYJWkaiDFSKEO2FMmV4pBHhm33F48Gwz1DQuC+YiUIHgyGBwPj8rD95emQBp9AXTIwOxOYlUkwO3Ps7OK5w2YeJ5mbSVCbsiyFJEmSJEkTYcAsSScwEO7mypUQN1eCfCmSK0eyxUi+XGkbHvxW2rKlSH6M9mP7Dw+M8yP6z4Ds96Q0po6GxJWfwOz00e2BfXOG9JmVTlBnWCxJkiRJ0mljwCxpSokxUoyVALdQhny5ErTmhzw/2k413D0axubLDNvOlath8MBPdXsgwD12+2hYnKu+Xq7EWRfuTqbm9PBgePAnnWBWJgxujwyK00mDYkmSJEmSpjoDZkkT8qO9WX52ME+hGvIODXzz5TjYXihXw+HS0T6Fgf5lKFRD4cJAUFw+0/+ys1s6AQ01gYZUgoZUqD4P1NckaEwF6qttjakE9dV9A30aqm2N1bY5mQQt6QSphEGxJEmSJEkzlQGzpAm5d0+Of3qi50yfxlmlJgG1yUAmGaqPkEkEMqkw2J5JHg1461OVIHjg+dAguGFYOJwY3F9jGCxJkiRJkk6CAbOkCak5y8oXJEMl3E1XQ910NeRNJwOZBKSTgboR4e+wMLgaAqePCYmHPlJ5TI3cV3nNpOGvJEmSJEmaYgyYJU1IOnHqjp0MkE4EagbC3OrzdCJQUw1zB58PC3sr/QeD3+qYoduZZBgMiAdC4HSiEuamqyHvwPbQYxruSpIkSZIkHcuAWdKEXL4ww59eVAmaM8lKaYV0NfwdeF6TOBrQ1lRn71aC4Up7TWIg3D36vCaBYa4kSZIkSdI0YcAsaUKuWJzhisWZM30akiRJkiRJOoNO4ZfcJUmSJEmSJEkzmQGzJEmSJEmSJGlCQozxTJ/DlNHZ2ekvQ5IkSZIkSZLG0NLSMmzxLGcwS5IkSZIkSZImxIBZkiRJkiRJkjQhlsiQJEmSJEmSJE2IM5glSZIkSZIkSRNiwCxJkiRJkiRJmhADZkmSJEmSJEnShBgwS5IkSZIkSZImxIBZkiRJkiRJkjQhBsySJEmSJEmSpAkxYJYkSZIkSZIkTYgBsyRJkiRJkiRpQgyYJUmSJEmSJEkTYsAsSZIkSZIkSZoQA2ZJkiRJkiRJ0oQYMEuSJEmSJEmSJsSAWZIkSZIkSZI0IakzfQJTSWdnZzzT5yBJkiRJkiRJU1VLS0sYuu0MZkmSJEmSJEnShBgwS5IkSZIkSZImxIBZkqRTrLW19UyfgiRphvHaIkk6Fby+aCIMmCVJkiRJkiRJE2LALEmakTa2F/juzn6KZddvlSRNjoP9Jb69o59D/aUzfSqSpBkiW4z8aG+OX7Tlz/SpSBOWOtMnIEnSZPvW9n7e9oMjAFw4K8Wtr5rHgrrkGT4rSdJ0dqCvxEtuO8iB/jL1qcAXr5zDK5fXnunTkiRNYzFG3vPjdm7Z3g/AjWsb+MgLWwghnOEzk06OM5glSTNKjJEPPNI5uL2xo8hrv9dGe658Bs9KkjTdfXJjDwf6K9eSvmLkrT84zH37cmf4rCRJ09ljhwuD4TLAzZt7ef/DXcTotzA1vRgwS5JmlMePFNjePfyryxvai7zh+210FwyZJUknL8bIt4YEAADZEvyHuw/z8EG/0ixJmpiR1xaAf9nQw9/+svsMnI00cQbMkqQZ5dvbs6O2P9pW4E13H6avaMgsSTo5T7QX2dZ9bN3l3mLkDXe18fhhQ2ZJ0skZ7eblgL/7ZTcff8KQWdOHAbMkacaIMfKtHaO/SQO4f3+et917hHzJr5xJksZvrAAAoDMfed33D7O1o3Aaz0iSNN1taC/y9Cg3Lwf8xcNdfGFz72k8I2niDJglSTPG5o4irZ3Fwe1UgOfOrRnW5649OW740RGKZUNmSdL4fHtEwHzZ/PSw7bZsmeu/18b27iKSJI3HbSMmxlw4K0VDavjifn/8QAdfe6rvdJ6WNCEGzJKkGWPkDLMrl2S45Zp5rJ+dGtZ+244s/+kn7ZRdPEOSdAKbOwpsGXHz8muvmMt71zcM67e3rxIy7+sbezaaJEkDbhvx2eW9z2rk36+aSyZ5tC0C7/1xO98+zrc0panAgFmSNGOMnAXwm+fUMTuT4JZr5nFe8/CQ+f881c9//VmnKzRLko5rZADw0iUZZmcSfPj5Lbzt/Pph+7Z3l7j+zjbasobMkqSxbekosLlj+M3LV6+o46VLMnz5ZXMZOpG5FOGdPzzCPXtGX2tGmgqmXMAcQvhKCGFfCKErhLA1hHDDkH1XhRA2hxD6Qgg/CCGsHLIvE0L4fHXc/hDCH4847phjJUnTX2tngY3tR9+kJQO8ekUtAAvqktx6zVyWNyaHjfns5l5ueqTLkFmSNKaR3475zZV1AIQQ+Njls/it1XXD9m/pLPLa7x2mI+eispKk0Y28eXnF4srNS4Brltdy80tnkxgSMufL8Dv3HOH+/bnTeZrSuE25gBn4G+CcGGMz8JvAX4cQLgkhzAO+CfwFMAd4BPjakHE3AWuAlcDLgP8aQngVwDjGSpKmudu2D7+j/2uLMsytPRooL2tM8a1r5rGwbvil75+e6OHvH3OFZknSsZ7qLLJhyM3LRIBXr6wd3E4mAp+4YjbXragdNu5XRwr89l2H6SkYMkuSjvWtHcM/u7zmnOE3K1+7qp7//eJZw9r6S5E33X2Ynx/Kn/Lzk07WlAuYY4wbYowDt2Ri9edc4HXAhhjjN2KMWSqB8kUhhLXVvm8DPhRjbI8xbgJuBt5e3XeisZKkae7Y8hi1x/RZ3Zzi1mvmMScz/PL34V9084kNPaf0/CRJ08/Ia8uLF6aZVzv82zA1icDnXzqHly3JDGt/6FCeN99zhGzRb8lIko56uqvIE0cKg9uJId+8HOp31jTwdy9oGdbWXYi8/q42NrYXjukvnUlTLmAGCCF8IoTQB2wG9gF3AOuBxwb6xBh7gaeA9SGE2cDiofurz9dXn4859hT+MyRJp8n27iKPHT76JisAv76ibtS+62bX8M1XzqW5ZvgKze97qJMvb+09lacpSZpmRpbHGDnDbEBtKvCVl8/h8oXpYe337cvx9h8eoVA2ZJYkVYwsj/GihWnm1yVH7fvuCxv5y0uah7W15yLXf6+Np4YsQCudaakTdzn9YozvDSH8AXA5cCWQAxqBQyO6dgJN1X0D2yP3cYKxo2ptbZ3IqUuSzoB/3Z0Cjn6of25zia49T9M1Rv8G4GPrEvynJzJky0eD5v98fzvdbQd45fzJX5zJ64okTS97s4FfHj4aKAci68v7ON6f8/+5Ct7bm2FTz9Gg4M5dWd58+04+dEGeZBh77ER4bZGk6efrWzLA0evE5fU9tLZ2jNn/N+pg57Iavri7ZrDtYH+Z627fx2efnWNR7eTfxPT6otGsWbNmzH1TMmAGiDGWgJ+EEH4HeA/QAzSP6NYMdFf3DWxnR+zjBGNHdbxfmiRpavnploPA0RnMb1w3hzVrGsceQKVo/7zFWX77rsPkqyUyI4EPbM2wetkcrh1jBvREtLa2el2RpGnmzie6YcityhcuzHD5+mUnHPedVSVe/d02NnccnVl2V1uKRbOb+acXzyIRJidl9toiSdPPzp4iG39yYFjbO56/gsX1o89gHvC/zoukH+zkM5uOfuPyQC7Bf97SyHevm8/CE4w/GV5fNBFTskTGCCkqNZg3ABcNNIYQGgbaY4ztVEppXDRk3EXVMRxv7Ck9c0nSKbe7p8gjh4bXIPuNleMLh69cUssXrpwzbEZZMcLbf3iEH+7Njj1QkjTjfXvE4rHjvbbMrU1y6zXzWNU0/MP+v7b28d8f7CRGy2VI0tnq2yMW93vBgvQJw2WAEAJ/+4IW3nxe/bD2p7tLvPZ7bRzJTv43MKWTMaUC5hDCghDCm0IIjSGEZAjhGuA/APcAtwDPCiG8PoRQC/wl8HiMcXN1+JeB94cQZlcX77sR+GJ134nGSpKmqZFv0p4/v4alDeO/g//qlXV8+iWzGTqfLFeCN99zhJ8dyI05TpI0c+3pLfHQofywtt9YeewCTGNZVJ/kW6+ax9IRocGnN/Xy4Z+P+SVKSdIMN7L+8m+OUdt/NIkQ+PiLZ3H9iDEbO4q8/q7DdA18LVM6A6ZUwAxEKuUwdgPtwN8DfxRjvC3GeAh4PfDh6r4XAG8aMvYDVBbu2wH8CPhojPFOgHGMlSRNU7ftGPEmbZwzzIZ6w+p6/vFFs4a19RUjv33XYX7Zlh9jlCRppvrOiGvLJfNqWN54ctUFVzSm+Nar5jK/dvhHrr9/vJt/fNyQWZLONnt7Szx4cOI3LwGSicBnXjKba5ZlhrX/oq3AG+8+TF/RkFlnxpQKmGOMh2KML40xzooxNscYnx1jvHnI/rtjjGtjjHUxxitjjNuH7MvFGN9RHbcwxvixEccec6wkaXo60FfiZwdGvEk7iVkAQ73tggb+52Utw9q6CpHXff8wmzsKY4ySJM1E3xoxw+w1E7y2nNdSwy3XzGNWenjd5Zse7eLmTT1jjJIkzUQjb15ePK+GFSd58xIgnQx88WVzuWJRelj7Awfy/M49R8iVLMWk0+//s3ff4W1WZ//Av0dbXvJKnMROnITsQfYi7CxKGS2hLZQXOunb0pbS0vZH2HsUKHQPSudbRiGMMEoGhBWyQxLIIM5yYifelmRbWzq/PyRbemTJlm3JWt/PdfnCeuSHnCSOz3nu+z73SakAMxERUV+8fsKO0OXTzBItRuf3//zaG6bm4dZZ+YprLU4fvvBWE45ZPVHuIiKiTNJg92JzWPKyL1uYw00r1mL18lLkaZRB5p9tseCZqo4odxERUaYJ33nZ3+QlABg1As8uLcG8IVrF9XdOOfGtd1vg8THITIOLAWYiIkpbr4YdwDSQAECnn83Ix43T8hTX6uw+XLa2CbUdPDyDiCjTvV7tUCQvzyweWPISAOYM0eG5ZSUwhB0R8INN5m7V0kRElHka7F58FJ687Edrv1B5WhVeWFaK6cXKIPPrJxy44cNW+HioLA0iBpiJiCgtNTm8+LBOeQjfZX3sYRaJEAL3zC3AtyblKq6fbPfi8rea0GBnkJmIKJPFqz1GuLOH6fF/F5ZAG/IE5pPAt99rwbqTjug3EhFR2nuj2oHQouLpxVqMKRhY8hIACvUqvLS8BBNMyv/Xf47YcfNmMySDzDRIGGAmIqK09OYJ5SJtSpEG40za6Df0gRACjy404StnKIMKh60efHFtE1qdPDyDiCgTNUdKXo4eePKy09IKA/5yXjFUId0y3D7guo3N+OC0M/qNRESU1rofTB6/uWWIUY2XV5RiVJ5ym8zfPrPhju1WBplpUDDATEREaSlRFWadVELgd2cXdTvZeV+rB1eua0Kbm0FmIqJM88YJB0LPRppSqMH4OCUvO10+2ojfnV2kuObwAldvaMaORleUu4iIKF21OLx4PyyJGO9nl/JcNdZcVIrhOcow32/3teOR3W1x/bWIImGAmYiI0o7Z6cN7p8LbY8R3kQYAGpXAX84rxtJyveL6ziY3rt7QDLuH1QBERJnktbDk5aVxDgB0unpcDh5baFJca/dIrFzXhE9a3An5NYmIKDnePKlMXk4q1GBCYXyTlwAwOl+DV1aUokSvDPU9vLsNv/2UQWZKLAaYiYgo7bx5wo7Q2O4EkwaTCgfewywSvVrgnxcW46wyneL6h3UuXPdOM1xeBpmJiDKB2enDuwmuMAv17cl5uHdugeKaxSXxxbVNqLIwyExElCnWhCUv43EweTQTC7V4aUUJCnRCcf327Vb8/bOOhP26RAwwExFR2llTrTwM6bJKI4QQUb564HI0Kjy3tASzS5WVButrnbj+/RZ4fAwyExGlu7dOOhDa/WhcgQaTE5S87HTj9Hz8bEa+4lqTw4cvvNWM6jZPQn9tIiJKPIvLh42DsPMy1IwSHV5cVoJcjfL56McfmfGfI7aE/tqUvRhgJiKitGJ1+fBObViAOY4HMEVToFNh9fJSTClSBhtePe7ADzeZ4ePhGUREaa17b39DQpOXnW6dlY/vTclVXKu1eXH52iactnkT/usTEVHihCcvzyhQY2pRYpOXADB/qB7PLCmBPuTcPwngex+04vWwAweJ4oEBZiIiSivrahxwhSzSxuSrMb04/j3MIinSq/DKilKcUaA8ofnZwzb8vy0WntBMRJSm2tw+vHMqPHmZ2AqzTkIIPDjfhOsm5CiuH2/z4otrm9DkYJCZiChdhbfHuHx0YndehjpvhB7/uKAYoYXMXgl8892WbgU7RAPFADMREaWV8AqzRLfHCDfUqMYrK0pRkasMMj91sAP37LQyyExElIbWnXTAGRLHrcxT48xBSl4C/iDzE4sKceVYZVD7oNmDK9Y2w+z0RbmTiIhSVZvbhw3hOy8T3B4j3EUjjfjzuUVQhTwuuXzANW+34KM6Z/QbifqIAWYiIkobHW4fNtQM3gFM0YzM02DNRaUoMyqn0Sc/acfje9sHfTxERDQw3dtjDG7yEgDUKoE/nFOEz41Utn3a2+LGVzY0o8PNIDMRUTpZH5a8HJWnxoySwUtedrpibA5+dVah4prdK/GVDc34uMk16OOhzMQAMxERpY0NtU7YvcEK4YpcNWaVDv4iDQDGFmjw8opSFOmVAYj7d1nxh30MMhMRpYsOtw8basMOYEpC8hIAtCqBv51fjPOG6xXXtza48NW3W+DwcJcMEVG6GOyDyXty7YRcPLzApLjW5pa4Yl0T9re6kzImyiwMMBMRUdro1h5jkA5gimZKkRYvLy9FgVY5hlXbLPjXoY4kjYqIiPpiQ60TNo8yeTknSclLADBoBJ5ZUoyFQ3WK6++dduLr77bA7WOQmYgo1dk8PqyrUQaYk7HzMtR3p+ThjtkFimutTokvrm3CEYsnSaOiTMEAMxERpQW7R2LdyeT2MItkZqkOzy8rgVGtDDLfuMmMl47akjQqIiKK1WvVyuTlJZXJTV4CQK5WheeXlXTbSv3WSQe++34rvAwyExGltLfDkpcjclSYMyR5yctON8/LbrEuAAAgAElEQVTIx4+n5ymu1dt9uHxtE062M8hM/ccAMxERpYV3ah1oD1mkDTOqMD+suitZFpXp8cySYuhCZlUJ4Dvvt+K/J+xR7yMiouRyeCTeOpFaFWadTDoVXlpegkmFGsX11cfsuOkjMxhjJiJKXWvCdl5eWmmEKsnJy053zinA9ZNzFddqOrz4wtom1Nu8Ue4i6hkDzERElBbWVKfuIg0ALig34G/nFyO0kNkjga+/24JtZk63RESpaOMpZfKyzKjCghRJXgJAiUGNl1eUYky+WnH9X1U2PHFMCykZZSYiSjVOr8Rb4TsvUyR5CQBCCDyywISvjstRXD9i9eKLa5tgZktm6gc+8RIRUcpzeSX+m8KLtE6frzTij+cUITTs7fQCN+/XY2u9M+p9RESUHOG9/VMteQkAw3PUeGVFKcpzlEHm505p8cDHbUkaFRERRbPxlANt7mACcKhR1a2vfrKphMCvFxfi8tEGxfX9Zg9u3KeH1eVL0sgoXTHATEREKe+9005YXcFFWqlBhbPKUmuR1ulLZ+TgibMKFdccPoFr3mmB2cmFGhFRqkiX5CUAVOZr8MpFJRhiUD6+PbanDa9XsxUTEVEqWXNcObdcWmmEWpVayUsA0KgEnjq3GMsr9IrrB9rVuHmzOUmjonTFAHMUH9Wx0oyIKFWEV5hdMsqQkou0Tl+fmIv75ylPaG5y+PDwbmuSRkREROHeP+2EJSR5WaJP3eQlAIw3afHSilKYdMr577ZtFjg8bJVBRJQK3D6JN8POYLms0hDlq5NPpxb4xwUlOHuYcv574agdm7kDk/ogpQLMQgi9EOJpIUS1EKJNCLFbCPG5kPeXCCEOCiFsQoiNQojKsHv/KoSwCiHqhBA/Cft/R703klXbLPCxpxkRUdK5fRJvhC3SUuUApp78YFo+fjRNeULzUwc68BmbmhERpYTw3v6XVBqgSeHkJQBML9bixWWlin7/1e1e/H5/e/IGRUREXT447YQ5JHlZrFdh8TB9D3ckn1Ej8OzSEkwpUh4qu2or42IUu5QKMAPQADgJ4DwAJgC3A/iPEGK0EKIUwEsA7gBQDGAHgOdD7r0bwHgAlQAuAPBzIcRFABDDvd3saXbj31W2uP3GiIiofzbVOdHqDC5sCnUCZw9P7UVap1tmFWBUXrBnplcCt26z8FAmIqIk8/gkXq9Oj/YY4eYN1eFbk3IV1x7f04bTNm+SRkRERJ3Cd15+flTqJy8BIF+rwqMLlW3+dje78cxhxsUoNikVYJZSdkgp75ZSHpdS+qSUrwM4BmAOgCsA7JNSviCldMAfUJ4hhJgUuP1rAO6TUrZKKQ8AeArA1wPv9XZvRPfutLKxORFRknVbpFUaoU2DRRrgrwa4b55Jce3tWifW1XC7GRFRMm2qc6IlpC9+oU7g3DRJXgLAqlkFMGmCycoOj8S9O9mGiYgomSIlL9Nh52WnxcP0+ELYeBkXo1ilVIA5nBCiDMAEAPsATAWwp/M9KWUHgCMApgohigAMD30/8PnUwOdR7+3p1290+PD4Hp7MTESULN5IFWaV6bNIA/w912YXKKvKbttmgcvLKmYiomRZEza3fG5U+iQvAaBIr8J3RilbLj172IZdja4kjYiIiD6qd6E5JHlZkGbJSwC4Z24B9Krgc0qD3Ydf7mVcjHqn6f1LkkMIoQXwbwD/kFIeFELkAWgM+zILgHwAeSGvw99D4P1o9/bod/vacK6+EaOMDAQQEQ22nRYVGh3BQzFy1RIVtpOoqkrioPrhJ2MFrtttgA/+4MVhqwcPfnAc15R7kjwyIqLs45XAy0eMAIIB5Xm6FlRVNSVvUP1wxXBgdZ0GR23BmqEfvVeHp890QqRPrJyIKGP884gWgLbr9TmFblQfPZy8AfXT/5Rr8fTJ4O/jd5+24VxdI0YyLpb1xo8fH/W9lAwwCyFUAP4FwAXgB4HL7QAKwr60AEBb4L3O146w93q7t0ceKfCXhiI8u7SkL78FIiKKg6e2mAF0dL3+fGUOpk6sSN6A+quqCtdNyMXfDwV7mP21Ro/vLxiFIUZ1DzcSEVG8fVTnRIs7GEzO1wpcM3cs9Or0ispWVVXhl+cMwRfWNndd+6RNjd3qcnz5jJwkjoyIKPv4pMQHO+sABCuYr5k+FONHpdfuSwD4mrcK/23W45TN/3txS4G/NBbhmSWMi1F0KdciQwghADwNoAzASill596vfQBmhHxdLoAz4O+t3ArgdOj7gc/39XZvLGP670kHNtY6ev9CIiKKG5+UeK1a2X85XQ5giuT2OQUo0AWDF1a3xAO72C+TiGiwhff2v2ikIe2Cy53OH2HAxaMMimt377Cgw81+mUREg2lrgwv19uDP3jyNwIUjDD3ckbqMauDuucpzZN484cC7pxgXo+h6DDALIb4Zy0ecx/QHAJMBXCqlDF39vQxgmhBipRDCAOBOAHullAcD7/8TwO1CiKLA4X3XA/h7jPd2M3+ITvH61m0WeHzcDkBENFh2NLpw2hZcpOVqBJaUp+ciDQBKDWr8fIayM9M/Dtmwt5n9MomIBotPdu/tf2ma9fYPd/88E7QhT3WnbD48+Ul79BuIiCju1oQlL1eMNMCgSc/kJQB8aawR84ZoFddWbWVcjKLrrYL52hg+/idegxFCVAL4XwAzAdQJIdoDH9dIKRsBrATwAIBWAAsAXBVy+13wH9xXDeA9AI9KKd8CgBju7ebhBcpszQGzB3/7rCPKVxMRUby9elwZAFheYYAxjRdpAPCdyXkYVxDsTiUBrNpmgZRcqBERDYadjW7U2oIHr+ZoBJZWpNcBTOHGFmhww5Q8xbXffNqGE+3s809ENBiklHgt/GDyNN55CQBCCDy8oFBx7YDZg78zLkZR9BhgllJeEMPHhfEajJSyWkoppJQGKWVeyMe/A+9vkFJOklIapZTnSymPh9zrlFJ+U0pZIKUsk1L+Muz/HfXeSGYP0eGr45S9yx7YZUWLwxvlDiIiihcpJdaEtce4PM0XaQCgUws8OF+ZwNxU58Kaam43IyIaDOFzy/IKA3I0Kdc1sM9unpGPocbg78PhBe7azjZMRESDYVeTGzUdyuTlsjRPXgLAnCE6XB0eF/vYilYn2zBRd/1aTQk/VedHvAeVKu6cU4C8kGo5s0viod29ngtIREQDtLvZjZPtwUWaQY20rzDrtHykAUvLlb+X27dbYPewipmIKJGklN36L19Wmb6tl0IV6FS4Y7byTPOXj9uxqc6ZpBEREWWP8Lllabk+I5KXgD8ulhsSF2t1Sjz0MROY1F3M3/FCiHIhxMtCiGYAHgDukI+MNCxHjZvD+mX+9WAHDrRm7G+ZiCgldF+kGZCnzYxFGgA8MN+E0G4fJ9u9+N0+9sskIkqkPc1unAhLXi4bmRkBZgC4ZnwOZpZ075fpZb9MIqKEiZS8zISdl52GR4iLPX2wAwfNjIuRUl+e1v8IwAVgCYB2ALMBrAHw3QSMK2V8b0oeKvPUXa+90n/gH/tlEhElhpSy2yEZ6d7DLNzEQi2+PTlXce2Xe9twqoNtmIiIEiW8PcaF5QbkZ1DyUiUEHgo7R2Zvixv/PmxL0oiIiDLf3hY3qkOSl3q1f8diJrkhUlxsK+NipNSXFdVZAL4ppdwNQEop9wD4FoCbEzKyFGHQCNwf1i9z4ykn3jrJfplERInwaasHR9uCizSdyn8Kc6a5ZWYBivXBadjmkbhnpyWJIyIiylyZXmHWaVGZHivHKH9f9+20wuJiv0wiokQIL4y5cERmJS8Bf1zsvnnKuNg7p5xYW8O4GAX15bveC39rDAAwCyGGAOgAUB73UaWYS0YZcO5wZb/M27ZZ4PQyW0NEFG/hi7QLRuhh0mXWIg0ACvUq3B7WL/P5I3Zsb3AlaURERJlrf6sHR6zB5KVWBayoyLzkJQDcPbcARnWwD1Ojw4fH9vAcGSKiePMnL5VB1kzbednp0koDzhmmU1y7dasFLsbFKKAvT+xbAVwc+HwtgOcBvARgR7wHlWqEEHhovgmqkH6ZR9u8+NN+9sskIoq3TG+PEeq6CTmYUqRRXLtlqxk+bjcjIoqrV6u7Jy8L9ZmXvASAkXka3Dg9T3Htj/vbccTiiXIHERH1xwGzB4etwZ+tWhXwuQzceQkE4mILChkXo6j6sqq6FsB7gc9vArARwKcAvhrvQaWiqcVafGOisl/mo3va0GBnv0wiong5aHbjs5AHYI0ALh6VuQFmjUrgofmFims7m9z4zxF7lDuIiKg/XgtLXl5amblzCwD8aHoeynOC/TLdPuC27WzDREQUT+GFMecNz9zkJQBMK9bi6xMYF6PIYv7Ol1KapZQtgc/tUsr7pJT/T0p5OnHDSy23zsqHSRdM17S5Je7baU3iiIiIMkv4Iu3c4XoUZfAiDQDOG6HHJaOUlQ5377Cg3c1+mURE8XDI7MYBczB5qRbA50dlZoVZpxyNCvfMU7ZheuukA+/Usl8mEVG8ZNPOy063zs5HQUhczOqWuH8X42LUhwCzEEInhPiOEOL3Qoh/hn4kcoCppMSgxi0zlQu1/6uyYXcT+2USEcXDmmrlg28mHsAUyf3zTQhtM11n9+HJvdxuRkQUD+Fzy7nD9Sg2qKN8deZYOcaIhUPD+mVus8DtYxsmIqKBqrK4sT/LkpcAUBohLvavQzbsaWZcLNv1pSzsH/C3xmgDcCTsI2t8e3IuJpiC/TIlgFXbLJDsl0lENCBHrR582uLueq0SwOcrM3+RBgCj8zX4wTRlv8zf7GvD8Tb2yyQiGqhXwyvMMrw9RichBB5eYEJIu0wcNHvw14MdSRsTEVGmWBN2uN/Zw/QoyYLkJQBcHyEudstWxsWyXV8CzBcBOCvQFuOe0I9EDS4VaVUCD843Ka5trnfh5WPsl0lENBDhW8wWl+lQmiWLNAD48Zn5KDMGp2WnF7iT/TKJiAbkmNWDT7I0eQkAM0t1+Or4HMW1hz62osXBfplERAOxJuzw2GzZeQn442IPRIiLvXKccbFs1pcA8wkA+kQNJJ0srTBgRYXyj+LOHVbYPOyXSUTUX69WZ18Ps1D5WhXumqPcbram2oEPTjuTNCIiovQXHgBYVKbDUGP2JC8B4M7ZBcjTBOuYzS6Jhz5uS+KIiIjS2/E2D/Y0B5OXAtnRHiPUsgoDlofFxe7YboXdwyrmbNWXAPM/AbwqhLhaCHFh6EeiBpfK7p9vQsg6DTUdXvzmU/bLJCLqj+o2Dz5uUi7SLsmSLcyhrhqXg9mlWsW1Vdss8LJfJhFRv4S3x7g8C+eWshw1fjYzX3Ht6c86sL/VHeUOIiLqSfjOy0VlOpTlZFfyEgAeiBgXYwIzW/UlwPwDAGUAHgTwdMjHXxIwrpQ33qTF/05R9st8cm87atrZL5OIqK9eC6swWzBUh+FZuEhTBfplhvq0xY1/VdmSNCIiovR1ot2DXU3KIGo2Ji8B4LtT8jAmPziv+iSwiv0yiYj6JXx3TLbtvOw03qTFd6bkKq49+Uk7ajvYhikbxRxgllKOifIxNpEDTGU/m5GPEn3wj9DulbhnpzWJIyIiSk/hh2Rk6yINAOYP1ePLY5W///t2WmF2sg0TEVFfvFatnFsWDNVhRG72JS8BQK8WuH+eMoH53mkn3jzhiHIHERFFUtPuwY5GZfLy0ixNXgLAz2cUKOJiNo/EPTt4jkw26ksFM4QQGiHEuYE2GecIITS935W5CvUq3BHWL/OFo3ZsrWe/TCKiWJ3q8GJbo0tx7dIsOoApkrvmmpATst+s2enDL/YwgUlE1BevhW1hzva55eJRBpw3XNkv8/btFji9rGImIopVePJy3hAtyrM0eQn442K3z1bGxf5z1I5tDYyLZZuYA8xCiEkADgB4BsCNAJ4FcFAIMTlBY0sL147PwbRiZb/MW7ZZ4ON2MyKimIS3x5hTqsXIvKzOX6I8V42bpivbMP15fweqLOyXSUQUi9M2L7Y0KJOX2bw7BgCEEHhogQmqkH6Zx9q8+ON+niNDRBQrtsfo7roJOZhapHx+u2Ur42LZpi8VzL8H8GcAI6WUi6SUFQD+GLietdSq7v0yP25y49nD7JdJRBSL8EXa5VykAQB+OC0fFSHVEB4J3LaN282IiGLxetjcMrtUi1FZnrwEgClFWnxrorJf5qO721BvY79MIqLe1Nm82FIflrzM4vYYnfxxsULFtV1NbjzHuFhW6UuAeSaAX0rlSRBPBq5ntbOH6XH5aOWWu3t3WtHmZr9MIqKeNNi9+KiOFWaRGDUC981TbjdbV+PE+hr2yyQi6s2rYe0xGAAIWjUrH4W6YBlzu0fivl1sw0RE1JvXq+0IDYjNLNGiMp/JSwA4Z7gel1UyLpbN+hJgPgXgvLBr5wSuZ71755qgD2m7U2/34Zd72pI3ICKiNPBGtUOxSDuzWIvRXKR1+cJoIxaV6RTXbt1mgdvH7WZERNE02r34KLzCjMnLLsUGNVbNUiYw/11lw8dNrih3EBERAKwJ67/MnZdK985TxsXq7D48sZdxsWzRlwDzrQDWCCGeE0I8IoR4HsCawPW4EUL8QAixQwjhFEL8Pey9JUKIg0IImxBioxCiMuQ9vRDir0IIqxCiTgjxk1jvjYfKfA1+ODVfce13+9pxzOqJ5y9DRJRRXmUPsx4J4W/DFNIuE1UWD5460JG0MRERpbo3TjgQmoebVqzF2AImL0N9c1IuJpqCfyYSwKqtFkj2yyQiiqjJ4cWHdcqD67g7Rml0vgY/mKo8R+a3n7bjeBvjYtkg5gCzlHINgNkAPgWQD+ATAHOklK/GeUynANwP4K+hF4UQpQBeAnAHgGIAOwA8H/IldwMYD6ASwAUAfi6EuCjGe+PipjPzMDwn+Efq8gF3bGe/TCKiSFocXnxwWrlIC283RMCMEh2unZCjuPbwbiuaHOyXSUQUSXh7jMsrObeE06oEHgw7R2ZLgwsvHbNHuYOIKLu9Ua1MXk4t0uAME5OX4X58Zj6GGRkXy0Z9qWCGlPKQlPJ+KeUNAB4HUB3vAUkpX5JSvgKgOeytKwDsk1K+IKV0wB9QniGEmBR4/2sA7pNStkopDwB4CsDXY7w3LvK0Ktw1R7lQe/2EA++dcka5g4goe71xwgFvyCJtcqEG403a5A0ohd0+uwAF2mAds9Ul8eAubjcjIgrX4vDi/bDkJXfHRLak3ICLRiqD73dut8LmYb9MIqJw4QeTc26JLE+rwt1zlXGx16od3eZmyjwxB5iFEI8JIeYHPv88gBYArUKISxM1uDBTAezpfCGl7ABwBMBUIUQRgOGh7wc+n9rbvfEe5JfPMGLuEGWAZNU2Mzzsl0lEpLAm/AAmLtKiGmpU42czlG2Y/n6oA5+2uJM0IiKi1PTmSWXyclKhBhMLmbyM5oF5JmhDnghrbV78+pP25A2IiCgFmZ2+boWD7L8c3ZfPMGJOaVhcbCvjYpmuL/X81wC4M/D5nQD+B4AFwBMAXovzuCLJA9AYds0Cf7uOvJDX4e/1dm9EVVVV/R7o90eo8I3GYDXA/lYPHv3wOK4czr4zREQA0OYBNp4yAiHdhWeKBlRV1SdvUAk2kHkFAJbogKcMBpxw+CMBPgnc9O5p/H6aE0L0cjMRUZZ4bp8eQPCEocX59gH//E1l8fi9fWW4Fv9XGwwEPLHXisWaBgwzMBBARAQAr9er4ZH6rtejjT6oG4+jKjzKlEEGOr98f4QK32wKxsX2tXrw2IfHsZJxsbQ2fvz4qO/1JcCcI6W0CSFKAIyVUq4GgHgflteDdgAFYdcKALQF3ut87Qh7r7d7I+rpD6034wG81d6C548Eq/OeqjHgewvKUKjvU1cSIqKM9NxhGzyytev1uAINLppxBkSGRkqrqqoGNK90esRox9Vvt3S93mFR46CugtXfREQALC4ftn50WnHtG7PLMb44MyuY4zW3PFDpw1ur69Hk8LfGcPoE/t5cjKfPLx7w/5uIKBNsqW5GMNQEXDnBhPHjRyZvQAkWj/llPIC3Olrwn5C42J9rDPgu42IZqy9/q4eEENcA+AGA9UDX4XmDdRLEPgAzOl8IIXIBnAF/b+VWAKdD3w98vq+3exM12LvmmJCrCQZKWpw+PLzbmqhfjogorXTvYWbI2OByPF000oALR+gV1+7YboHDwyozIqK1Jx1wh7QPHpuvxtQiHsDUG5NOhTvnKGtxVh+zY3M9+2USEVldPmysdSiuXcbDY2Ny9xwTcsLiYo8wLpax+hJgvgHA9wFcAOCOwLUVANbFc0BCCI0QwgD/3ja1EMIghNAAeBnANCHEysD7dwLYK6U8GLj1nwBuF0IUBQ7vux7A3wPv9XZv3I3IVePHZyo7cDx1oAOfmdkvk4iyW5vbh7e7LdJYgRsLIQQeXGCCOiQWX93uxe/3s18mEdGrYb39Lx9tZPIyRteMy8GZxeH9Mi3wSSYwiSi7rT3pgCskeTkmX43pGbozJt5G5KrxkwhxsUOMi2WkmAPMUsrtUsqzpJTnSymPBK79W0p5bZzHdDv8VdG3wN/n2Q7gdillI4CVAB4A0ApgAYCrQu67C/6D+6oBvAfgUSnlW4Fx9nZvQnx/ah5G5QV7wHklcOs2CyQXakSUxdafdMDpDb6uzFNjRgkXabGaVKjFtyblKq49vqcNp23eKHcQEWW+9gjJSx7AFDu1SuDhBSbFtd3Nbjxz2JakERERpYbwnZdMXvbN96fmYWRIXMwjgdu2WXq4g9JVnxqfCCF0QojpQogLhBAXdn7Ec0BSyrullCLs4+7AexuklJOklMZAoPt4yH1OKeU3pZQFUsoyKeUvw/6/Ue9NFKNG4L55yoXa27VOrKvhdjMiyl6vdmuPwUVaX62aVYAiffDPrMMjce9Objcjouy1vsYBR0iebRSTl3121jA9vhgWlL93pxXW0NI9IqIs0uH2YUNY/IY7L/vGqBG4Pywutr7WiXUnHVHuoHQVc4BZCHE2gtXB6wG8CGAtgL8kZmiZ4bJKAxYP0ymu3brNDJeXVcxElH1sHh/Why3SWGHWd0V6FW6bpeyX+exhG3Y2upI0IiKi5FpzvHvrJSYv++6eeQUwBAvN0GD34fE9Uc9FJyLKaBtqnbCHxG4qctWYVcrkZV9FjotZGBfLMH2pYH4CwC+klMUA2gL/vQ/A7xMysgwhhMBD801Qhaxvj1i9+PMB9sskouyzocYJW8iBdOU5aszmIq1fvj4xF1MKlYdX3bLVzDZMRJR1bB4f1tWEBZhH8wCm/hiVp8EPpyn7Zf5hfzuOWj1JGhERUfKE9/bnweT90xkXC/2TO2z14KmDHUkbE8VfXwLMEwD8KuzawwB+HL/hZKYzS3S4bnyO4tovdreh0c5+mUSUXcJ7mF062gAVF2n9olEJPBTWL3N7oxsvHLVHuYOIKDO9XetER0jyckSOCnOH6Hq4g3py0/Q8jMgJPia6fMDt29kvk4iyi90jsTasjcPlbI/Rb2eW6PC1Ccq42CO7rWhyMC6WKfoSYLYA6NyPe1oIMQVAEYC8uI8qA90+pwAFumAQxeqWeGAX+2USUfZwRFiksYfZwJw3woCLRymr9O7eYUGHm/0yiSh7vBZWYXZJpZHJywHI1apw91xlAvPNEw68e4r9Mokoe7xT61AkL4fnqDBvKJOXA3Hb7AIUaEPiYi7GxTJJXwLMLwG4OPD5XwFsBLAT/l7M1ItSgxo/n6HcbvaPQzbsbWa/TCLKDhtPOdDmDi7SyowqLOAibcDun2eCLmQ2P2Xz4clP2IaJiLKD0yvxVniFGXv7D9iXxhoxP6wKfNVWCzw+tmEiouwQfjA5k5cDN8Soxs9ndo+LfdLiTtKIKJ5iDjBLKW+SUj4T+PwxACsBXB/4oBh8Z3IexhUE+2VKAKu2Wdgvk4iywppqZQDgkkoj1Cou0gZqbIEGN0xVbib6zadtONHOfplElPnePeWENSR5OcSgwkImLwdMCIGHw9owHTB78PfP2C+TiDJfpOQld17GR3hczCeBVTxHJiP0pYIZACCEGCmEWCil/FBK+V8pJffhxkinFnhgvnKhtqnO1S3oQkSUaVxeiTdPhB2SwUVa3Nw8Ix9DjcEp3eEF7trO7WZElPnCD2C6lMnLuJk9RIerxyn7ZT7wsRWtTj7+EVFme++UE1ZXMOBZalDhrDImL+MhUlzsQ8bFMkLMAWYhxCghxCYABwFsCFy7Ugjxl0QNLhMtr9Bjablece327RbYPczWEFHm+qDOCUvIIq1Er8LiYVykxUu+VoU75xQorr183I5Ndc4kjYiIKPHcvu7Jy8tHG6J8NfXHXXMKkKcJBuxbnRIPfcwEJhFltm4Hk1camLyMo0hxsTu2W+BgXCyt9aWC+U8A3gCQD6CzQcp6AMviPahMJoQ/WxOyTsPJdi9+t4/9Mokoc4VXmH2+0gANF2lx9dVxOZhZolVcW7XVAi/7ZRJRhvrgtBPmkORlsV6FxcP0PdxBfTUsR42fhJ0j8/TBDhw0s18mEWUmt0/iDe68TKjOuJg65HHwBONiaa8vAeb5AB4OtMSQACCltAAw9XgXdTOxUItvT85VXPvl3jac6vAmaURERInj8Um8Uc0DmBJNFaFf5t4WN/592JakERERJdaa8OTlKCYvE+GGKXmozFN3vfZK4NatPEeGiDLTpjonWp3Bn29FeoGzhzN5GW8TC7W4PkJc7LSNcbF01ZcAcz2AcaEXhBBTAJyI64iyxC0zC1CsD/7x2zwS9+y0JHFERESJsanOheaQfo0mncA5rDBLiIVlelw5Vhm8v2+nFRYX+2USUWbx+CRePxF2ABOTlwlh0AjcH9Yv851TTqytYb9MIso84TsvLx5lhJbJy4QIj4t1eCTu2cG4WLrqS4D5MQCvCyG+AUAjhLgawPMAHknIyDJcoV6F22Yrt5s9f8SO7Q2uJI2IiCgxwnuYXTzKCJ2ai7REuXtOAYwhf76NDhD2sFkAACAASURBVB8e29OWxBEREcXfR/UuNDmCybMCncB5rDBLmEtGGXBO2NkJt261wOVlFTMRZQ6vT+L18J2XbI+RMJHiYs8dsWNHI+Ni6SjmALOU8q8AfgbgSwBOArgOwO1Syn8naGwZ72sTcjGlSKO4dstWM3zcbkZEGcK/SAvvYcYDmBKpIk+DH03PU1z74/52HLF4kjQiIqL4ey2swuxzIw1MXiaQEAIPLShEaBHf0TYv/rSf/TKJKHNsbnChMTR5qRU4bwSTl4nEuFjm6DXALISYI4SYBgBSylcBfB3AHgDlAC4WQuT1cDv1QKMSeGh+oeLaziY3/nPEHuUOIqL0srXBhXp7cJGWrxW4YAQDzIl24/Q8VOQG+2W6fcBt27ndjIgyg09KvBaWvGRv/8SbVqzF1yco+2U+uqcNDXb2yySizBDeHuOiUQbombxMqEhxsR2NbrxwlHGxdBNLBfOTAIaFvP4z/L2Y/wRgKoBfJGBcWeO8EXpcMkoZbLl7hwXtbvbLJKL0F94eY8VIAwwaLtISLUejwj1zCxTX3jrpwDu17JdJROlvW4MLdSHJyzyNwIVMXg6KW2fnw6QLzuNWt8T9u6xJHBERUXz4ZKSdl0xeDgbGxTJDLAHmyQA+AAAhRCGAzwP4Hynl7wBcDeDSxA0vO9w/3wRdyN9End2HJ/dyuxkRpTeflHjteNgBTFykDZorxhixcGhYv8xtFrh93G5GROktvMKMycvBU2pQ45aZygTmvw7ZsKeZ/TKJKL1tb3DhtC0Y0MzVCCwpZ/JysITHxU7bfHjyE8bF0kksAWYNgM4Vw0IAp6WUhwBASnkSQGG0Gyk2o/M1+P5UZaeR3+xrw6vH7XB4GAggovS0q8mNWltw22yORmBpBXuYDRYhBB5eYEJoyOWg2YM7tltQZ+N2ZiJKT1JKvBZ2ANNlbI8xqL49ORcTTMF+mRLAjz8yY3eTC5I9M4koTa0Jm1uWVxhgZPJy0ESMi33KuFg6iSXAvA/+g/0A4CoAGzrfEEKUA2BTxzj4yYx8lBmDfx1OL/C1jS2Y8Nxp3PBBK96pdcDDqjMiSiPhFWbLKvTI0cR8tizFwcxSHa4Zn6O49sf9HZjynzpc9lYT/nmoA2Ynt54RUfrY1eRGTUcwSWZUCywtZ/JyMGlVAg/ONymu7Wpy4/zXGjH3pXo8+LEVn5ndSRodEVHfSSm7tfZjb//BFzUu9jzjYukglif9/wfgT0KIFvjbYzwS8t5XAGxKxMCyTb5WhbvmFHS7bnVLPHPYhivWNWPS83X46WYzNtc7eaImEaU0KSXWhAWYL2d7jKS4Y3YB8rXK6gufBN4/7cSNm8wY/9xpfGVDM144YmOfMyJKeeFzy7IKPXK1TF4OtqUVBqyIsCvpiNWLX+xuw4KXG3D2qw14cm8bTrR7kjBCIqLY7W5242R7WPKSOy8HXdS4mItxsXTQ62pMSvkhgFEAlgEYK6X8LOTtNwD8OEFjyzpXjcvBZZXRe/w0OXz4y8EOfO7NJpz5Qj3u2G7hVjQiSkl7mt2oDlmk6dXAspHsYZYMZTlq/GJhIaLt8HP7gLUnHbj+/VZMeK4O33y3BW9U2+H0cm4hotQipcSr4QcwscIsaX6xsBAjcqI/Tn7a4sbdO60484V6LH+9EX/a344GO1s0EVHqCd95uaRcjzwmL5PiqnE5uLQPcbE7t1uwp5lxsVQgsukvQQhRDOBpAMsBNAFYJaV8pvN9i8WS9D8MKSW2Nbjw4jE7XjlmR6Oj92qycQUarBxrxJVjjRhv0g7CKImIenbfTgseDzms9OJRBjyzpCSJI0quqqoqjB8/PqljqGn3YPUxO1YftWNvS+9blwt0ApdWGnHlGCPOGa6HRsUedESUXHubXTh3TWPXa70aqLpqOAp02RkESIW5xebx4b8nHHjxqB0bah3obSOMSgDnDtdj5RgjLq00olCfnX93RJQ6pJSYs7oeR9uCCbCnzi3Cl87I6eGuzJbs+aU/cbHxJg2uGMO42GAymUyKB8RsCzA/C3/V9rcAzIS/AvssKeU+IDUCzKE8PokPTjux+pgda6rtsLp6H970Yi2uHGvEFWOMGJmn6fXriYjiTUqJuS/V44g1uEj74zlFuGocF2mp4pDZ3RVsPmztfevyEIMKXxhjxMoxRswfqoNKMNhMRIPv/p1WPLa3rev1RSMNeG4pk5epwuz04bVqO1Yfs+P900701iZTpwKWlBtw5VgjLhppYKsTIkqKT1rcOOfVhq7XOhVw+OrsTV4CqTW/9CcudmaxFisZF0u4rA0wCyFyAbQCmCalPBS49i8AtVLKW4DUCzCHcnolNtQ4sPqYHf894YA9hq3LC4fqsHKsEZePNmKoUT0IoyQiAva1uLE4ZJGmVfkrzLK5SimVFmmhpJTY0+zGS8fseOmYXXFwVjQVuWqsHGPEyrFGTC/WQjDYTESDQEqJ+S83oMoSTIr94ZwiXM3kZbKHEVG9zYtXjvsTmdsaXb1+fY5G4HMjDVg51ogl5Qbo1ZxbiGhw3L/Lisf2BJOXK0Ya8HwWJy+B1J1fGBdLLdkcYJ4FYJOUMifk2k8BnCelvBRI7QBzqHa3D2+d9G9FezvGrWjnDddj5VgjLhnFrWhElFgPfWzFI7uDi7Rl5Xq8sLw0iSNKvlRdpIXySYmtDS6sPmrHK8ftaIphK9qEkK1o47gVjYgS6ECrG4teCSYvNcJfYZbN69p0mFsAoLrNg5eP2fHiMTs+jaFFk0kncFmlP5F5zjA91GzRREQJtOClenwWkrz83dmFuGZ8bhJHlHzpML8wLpZ82RxgPgfAC1LKYSHXrgdwjZTyfEAZYK6qqhr0MfaHxQ1sbFZjbaMGOy0qSPS8ANMKicVFXiwb4sW5xV4YmMAhojj7yi4DjtqCE/Yd45y4bBgP9UknHgnsMKuwtlGDjc1qdHh7f7iflOvD8iEeLBvixTB9dqwtiGjwPHVCgz+f0HW9XlTkxa+nOpM4IuqPYzaBdY0arGtU44Sj94f7Yq3EslIPlg/xYnq+D9w0Q0TxdNQm8JVdwcNi1UJi7Xw7WDeRXhgXGzyhiYdsDjBHqmC+GcD56VbBHE1d11Y0G7Y39l4dkKsRuHiUAVeM8W9F03ErGhEN0CGzG/NfDlaYqQVQddUwFGf5rJ0OVQDRODwSG2odWH3UjrdOxrYVbVGZDivHGPGFMUaUZvnfPRENnJQSi19twP7WYIXZrxcX4roJrDBL17mls0XTi0ftePmYHbW23hPRI/M6WzTlYFqRhi2aiGjAHtltxUMfB3deXjhCj5dWZPfOSyC955f+xsVWjjXiwhGMi/VFNgeYO3swT5VSVgWu/RPAqXTowdxXx9s8eOmY/x/VvtbeD3Aq1AlcNtqIlWNycPYwHbeiEVHMjrd5sL7GgQ01DnxQ54LNE/xRev4IPV7hIi2tF2mh2tw+/PeEA6uP2vB2rROeXmZNdehWtEojTFl8WAoR9Y3F5cO7p5zYUOPA27UOnLIF976qBXDoqmEoyfIEVqbMLT4psaXehdXH7HjlmB3Nzt5bNE00abByrP/Z5QwTD3Aioth4fRI7Gl1YX+ufX3Y3KwOQvzqrEF+bmN3JSyBz5hfGxRIrawPMACCEeA6ABPBtADMBvAngLCnlPiCzAsyhDpr91QGrj9pwrK336oAyowpfGG3ElWNzMHcID3AiIiWHR2JTvTMQVHbisDX6ZP3EokJ8YxIXaZmySAvV6vRhzXE7Xjxqw4d1LvQ2gerVwLJyf3XAipEG5GgYbCaiICklPm31YEONA+trHNjW4IqaxDpvuB6vXsTkZSbOLW6fxHunnHjxqA1vnHCgzd3749nMEi1WjjXiijE5KM/N7qQDEXXXYPdiQ40DG2qdeKfWAbMr8s8VVSB5yd13mTm/MC4Wf9keYC4G8FcAywA0A7hFSvlM5/uZGmDuJKXE7q6taDZFJUg0E00aPLLQhPNHGAZhhESUqo5ZA1XKtQ58cNoVU5uEEr0KO1aWoYgHKGTkIi3UaZsXLx+z46VjNuyIYStavlbgpun5uHF6HrSsDCDKWp1VyusDVcqnY1ibAsC/LizGpZXG3r8ww2X63OLwSKyrcWD1MRvWnnTAEcNxDpdVGvDwgkKMYKCZKGt5AlXKG2qcWF/rwJ7m3temAHDlWCP+cl5xgkeXHjJ5fmFcLH6yOsDcm0wPMIfySYmP6l146agdrxy3o6WXrWhXj8vBA/MKsr6PKlG2sHskNtU5u4LKR6yxH9I3IkeFZRUG/HBaHsbxhAwAmb1IC3e8zYPVR+1Yfcym6JcayZQiDX69uAhzh+h6/DoiygxSSnzS4saGWmdXlXIM+UoAQI5G4Jzhelw7PgefH2VgJRGya26xunz470l/i6Z3emnRlK8VuGtOAb45KRcqfp8QZYU6mxdv1/p3V75zygFLlCrlSGaVanFppRH/OzkXuVoWxgDZM78wLjYwDDD3IJsCzKHcPol3O7eiVTvQHmXFVqJX4aEFJnxprJGLeqIMdNQa7KX8YV1sVcoAoBHAwjIdllUYsLTcgCk8eKebbFmkhTvQ6sbqo3a8eMyG41G2ogkA10/OxR1zCpDPRT1RxjE7A1XKtQ68XeNAnT22KmUAmGDSYGmFHsvKDVhUpodBw7klVLbOLc0OL9Yc91c2b+qhRdP8ITr8anEhJhcx2U2UaTw+iW0NLmyodWB9jROftMRWpQwARXqBJeX+55Yl5XoMMTJYGC4b5xfGxfqOAeYeZGuAOZQ9sBXtxaM2vF7tiLhgW1Kuxy8XFaIynwdqEKUzu0fiw84q5RoHjsbQi6pTeY4aSyv0WFphwHnD9Sjg4W09ysZFWigpJXY1ubH6mA3PHrah1dl9dqnIVeOxRSZcNJLb3onSmZQSe1vc2FDjxIbavlcpnztcj2UVeiwtN3Ct2Ytsn1sA4FSHFy8ft+OZqo6IBzhpVcBN0/Nx85n5TFAQpbnTts5eyg5sPOWENcYqZQF/lfLSCgOWlRswu1TLw9t6ke3zC+NisWGAuQcMMCtta3DiR5vMOGDuvljL0QismpWP703Jg4Y/nInSxhGLB+trO6uUnTH1MwT8D2gLhwaqlCsMmFzIKuW+yPZFWqgmhxe3bbPg+SP2iO9/cbQRDy8woSyH1SRE6cLs9GHjKX8V2du1DtT3oUp5oknjf+iv0GNRmR56NeeWWHFuCfL6JJ4+2IF7d1ojVp2NN2nw5FmFWDxMn4TREVF/uDurlGscWF/rxKd9qFIu1quwpNxfDLOkXM+D+/qI80sQ42LRMcDcAwaYu3N5JX71SRse3dMGV4RnhZklWvxqcSFmlLB/JlEqsnl8+PC0qyuoHMuJuZ0qctVdVWTnjtCzfcEAcJHW3Tu1Dvz4IzOq27t/T5p0AvfNM+Ha8TlMZBClIJ+U2Nvs76W8ocaB7Y2xVynndlUpG7C0Qo9Redlb+TNQnFu6q2n34KdbLHjrpCPi+1+bkIN75ppQyAOIiVLSqQ4vNgSeW9493bcq5dmdVcoVBswqYZXyQHB+UWJcLDIGmHvAAHN0VRY3bvrIjE11rm7vqQVww9Q8rJqVjxwNF2tEySSlxBGrB+sDW5M/rHPC2Ycq5bPK9P5+lxUGTDSxSjleuEiLrMPtwyO72/C7fe0Rg1OLh+nwq7MKeVgkUQowO314p9ZfRfZ2rQMNfahSnlSowdJyf5XyQlYpxw3nlsiklFhT7cDPt5gjVtOXGVX4xcJCXFbJwyKJks3tk9jaWaVc44jY6iaakpAq5QtZpRxXnF8iY1xMiQHmHjDA3DOflPi/Khvu2G6JeCprZZ4aT55ViAvKDUkYHVF2klKiut2LLfUubG1wYuMpZ9TD1CIZmafGsnJ/Fdm5w/XIY5VyQnCR1rM9zS7cuMmMPc3dtz7q1cDPZhTgxml50DEoRTRozE4ftje6sLXehQ/qnNje6IIvxpVynkbgvBH+ZOWScj1Gsko5ITi39Mzs9OGuHRb845At4vufG2nAowtNqOD3J9GgcfskPml2Y3ODC5vrnHj/tBNWd+xVynOGaAMJSwNmsko5YTi/RMe4WBADzD1ggDk29TYvbtlqwcvHI/fP/MoZRjw434QSZhCJ4s7jk/i0xY0tDf6H/i0NTpy2xV5FplMBZw3TY2m5/8F/AquUBwUXab3z+CT+sL8dD33cBluE/plTCjX41eIizBuaXVvPiAbLyXYPttS7sKXBhS31Tuxv9UQ81CaaKYX+XspLKwxYOFTHhNAg4NwSmw/rnLhpkxmHrd0rI/M0AnfOKcC3JuUyUEWUAFaXDzsaXdhc78LWBhd2NLoirvOiKTUEqpTL/VXKjDEMDs4vvWNcjAHmHjHA3Df/PWHHTzdbUGvrXi1ZrFfhwfkmfOUMI4NXRAPQ7vZhZ8iibHuDK+LhNT0Zlaf297os1+McViknBRdpsTve5sHNm814u9bZ7T0B4NuTc3HnnAL2BCcaAK9PYr/Zgy31zsAOGBdqOmLf/QIA+VqB84YHq5RZBTr4OLfEzuGReHxvG578pA3uCHn5eUO0+NXiIkwpYksmooE41eHFlnonNgeKYT5tdce8+wUAVAKYW6rratk3o0QLFeMJg47zS+yyOS7GAHMPGGDuuza3D/fvtOLPBzoiVrlcOEKPX55ViNH5fOggikWdzYutDS5srndia4MLe5vdMR+c1EmnAhYP8/cjW1aux3hWKScdF2l9I6XEC0ftWLXVgmZn90hAeY4ajy4y4eJRxiSMjij92Dw+7Gx0+wPKgWRlrFuSQ00p0gTaKhmwgFXKSce5pe8OtLrxo01mbGvs3j9TI4CbpufjpzPyYdDwe5uoNz4pcdAc2P0SmF9ORDi8uTdDAlXKyyoMuGCEHsUZXPGZLji/9E2b24f7dlrxVJbFxRhg7gEDzP23o9GFGze1Yn+EpvxGtcCts/Lxval50KTh1jMpJQ5ZPPikxY0zi7WYUMjKBoqPzu+tLfXBgPKxPvRP7mRUC8wZosXCMj0WDtVhUZkOuazuTClcpPVPs8OL27ZZ8NyRyFvPLh9twCMLCjEsJz0fRFocXnxU70JuoF8tK3QoXhrt3kCrC/9D/55mN/q4+QUCwOQiDRYO1WNhmQ6Lh+lRnpue/9YyFeeW/vFJiacPduDenVa0RUi0jCvQ4MnFhTh7mD4Joxs4l1diW6MLTXYfzh+hR6Gea0KKD4dHYldTsJXS1gZXxB60vSkzqrCwTIeFQ/VYVKbDmaxSTjmcX/pne4MLP9rUiv3mzI2LTQyJhzHA3AMGmAfG7ZP49Sft+MUeK5wRYmRnFmvx68WFmFma+v0zHR6JD+ucWFvjwLqTDlSHZGK/PNaIW2cXZFz2iRLP6ZXYHViUba53YVuDCy0RqjN7M8TgX5QtGKrDojI9zizRQpuGk1Q24SJtYN495cBNH5kjHmBZoBO4b64J107ISfmHEyklPm31YN1JB9bVOBSHpk0r1uLuOQVYUq7njgPqEykljlg92BzSP/mIte/JSr0amFOq63ronz9Ux8BUiuPcMjC1HV78bIsZb55wRHz/2vE5uG+eKS3+HTTYvVgXeG7ZeMrZFTg36QR+cmY+vjM5D0ZWZVMfNTv8Oyv9yUoXPm52RWwx05tJhRosGKrDwjJ/QLkyT821Torj/NJ/mR4XM3+jvOt9Bph7wABzfByxeHDTR634oK771jOVAG6YkodVs/JTrsKytsOLdScdWFvjwPunnT0ePqBTAd+alIufzsjP6KbtNDBmpy+wKPNvGdvV5Io4yfRmvEmDhUN1WFCmw6Kheowt4KIs3XCRNnA2jw+PfNyG3+5rj9g25qwyHZ48qzDldpl0uH1477QT6046sL7GGbE/W6hzh+tx79yCtFh0UnK4vBJ7W9zYHNI/ucnR9yf+Yr0qkKj0B5VnlOigZ8uLtMK5ZeCklFhT7cDPt5hRb+/+72ioUYVHFpjwhdGp1T/TJyV2N7n9D/01Dnzc5O7x68tz1Lh1dj6uOiOHhxlSRFJKHGvzdj23bKl34ZClexVmb3QqYHapLhBQ9v+XLS/SD+eXgTtsceOmj8z4MMPiYgwwx4gB5viRUuL/qmy4Y7sF5gjbZkblqfHEWYVYUm5Iwuj8vD6J7Y0urKtxYO1JB/ZFaO/RmwKtwE1n5uO7U3KRo0mtHwyZqN3twyGzBwfMbhw0e3Cw1Y3aDi/UKgGDGtCrRdeHofNzFYKvNQJ6lYBejeD7IV9vUAO6kHsNagGdCjBogq81AhEfMKSUqG73BgPK9S4ciLA1pjdaFTCzxN/uonNhVspFWdrjIi1+9jS78KNNZuxu7v4wrVMBP52Rj5um5ye1N+zxNg/WBqqUP6xz9iuxtHKMEbfPLsCYAu6WSTSPT+JYmwcHWj04GJhfDls88ErZfU5RI2yO6fzcP690m0NC5pvg+wiZY4L3RwtemZ0+bG/0H5a0ucGJnY0uOPrxPTU2X+1vpVSmw8KhOvbnzwCcW+LH7PThnp0W/O0zW8T3V4w04LGFJoxM4mGWVpcPG085sfakAxtqHWiIEBDvzZRCDe6aa8LyCu6WSTQpJRrsPhw0u3Eg8NzymcUDs9MXfU5QB+cE/zOLCHtmifQMg25zVdczjFpETSi4fRKfNLu7dr5saXD163uqUCewINCmb2GZDrNKdOxhngE4v8RHJsbFGGCOEQPM8ddg92LVVgtWH4vcP/PLY414cIFp0AJorU4fNgQy/RtqHWh1xvZXrlMBQ43qqCesD89RYdWsAnx1XE5a9tNJNTZPZyDZvxjrXJj159CIeBNAxGCC1eVDXT8WZQVa0bVlbEGZDrNLtUxWZCAu0uLL45P404EOPLDLGnG3yeRCDX61uBDzhw5O/0y3T2Jzvaur9UVfKn7G5qtxNErvda0K+MbEXPx8Zj4TTXHg9Ukcb/MGk5RmNw60unHY6ulXEiDeQgMKnQECCYmjVm/EA2N6ohbAjBJtoHrM/+Bflqa9yik6zi3x91GdEzd9ZI74czxPI3D7nAJcPyl3UKqApZSosni6tiZvrnfF3Et9iEEFp0/CGqU/7uJhOtw714Q5Q7hbJh4a7d6Q55bOYhh3zM+aiaQR6BbM1qsFTrR7e9yxG01lnrqrldLCMh0mFmpSvkUZ9R3nl/hqsHtxy1YLXsqAuFjD1xhgjgkDzImz9qQDN282RwzQFukFHphnwtXjcuKeSZdSYl+rB+sD/3i2NgT7XfZmRI4KyysMWD7SgHOH62FUC/znqB0P7LJGDTRPNGlw19wCfG6kgVUBMbB7JA5ZgtXIBwIP/NVtfX+YThcVuWosKtN1BZUnF2q4VTELcJGWGNVtHty82YwNtc5u7wn4WxndOacABbr4J20a7N6uuWVjrRPWCAdFRWJU+w/0W1FhwLIKPSryNNjd5MLdO61491T33wcA5GsFfjgtD9+fmpdy2+hSkU9KVIcGkgPzS5XF3a/K33SQpxGY37UdWY+5Q7T8XskCnFsSw+mVeHxvG57Y2xax3+ycUi1+vbgIU4vj35LJ6ZXYVOfEW4GEZaSzB6KZVarF8goDVlQYMLNUC7PTh8f3tuOpA+1wRamBuHy0AXfONuEME3fLxKLZESGQ3OpBcz/OVEkHKgFML9Z2VScvGKrHCB72mhU4vyRGJsTF8kLWlwww94AB5sRqd/vwwC4r/nSgI+I38/kj9HhiUeGAtwPbPD68f9qJdSedWFfjiBoMDqcSwLwhuq5/PNOKIm8ddXgknjrQjsf3tkXc5gAAi8p0uGduwaBVz6U6h0eiyqqsRj7Y6sbxdm/MP9jSkQAwtViLRYH+yQuG6pK6tZKSh4u0xJFSYvUxO27ZaonYh3ZEjgqPLizE5yuNA/p1fFJib7O/3+Xak/5+l7H++BqVp8aKkf6H/rOH6aNuHX2n1oG7dljxSUvkXpplRhVumVmAaydwtwzg/zs50e71t7VoDbZPOmT2wB6pUXcGGZ6jwqLAluQFZTpMLdLyeyILcW5JrINmN360yYytDd37Z2oEcOP0PPxsRsGAD8871eFPWK6tceC9U050xFhVmq8VuGCEHstHGrCs3BB1l0J1mwcPfGzFC0fsEectjQC+HtgtM9TI4CHgr+47oAgi+z9v7Ee/+3SSqxGYO8QfTF5UpsOcITrkM1mZlTi/JE6724f7d1nxp/0dEX8mp0tcDGCAuUcMMA+OXY0u/HBTa8TeLka1wC2z8nHD1Dxo+/CgVN3m6To5+YM6Z8wVSiadwNJyA1aMNGBJub5PB/aZnT48sbcNfzzQHnVr7SWjDLhrbgHGm1Lr0KlEcXn9W/lCg8gHzR4cbfPEJZCsEsCYfDUmFWoxuVCLSUUajAv84HV6JZw+/38dXglX4L9OL8JeB973IfjaI+HySTi8gf9PyNc5A/+Pztc9rfmNaoE5Q/z9kxcO1WHeUB1MCaicpPTDRVritTi8uH27Fc8cjtw/87JKAx5ZWIjhfWgT0Ob2YWOtf1G2vsYR8QCoSNQCWFimw4rAwmxiH3rd+qTEi0ftuH+XNWpboPEmDe6cU4BLRmXHbhkpJWo6vIpq5ANmNw6ZPTEHYnoz1KjCpEItJhVqMLlQi4mFGuTrVBHmFP9c0W1O8ULx2umL7WudXV/b8/imFGq6+icvGKrDqDwe9kqcWwaDT0r87bMO3LPDGnGnyth8NZ5cXIRzh8deVOL1SexscmHdSSfW1jiiJhUjGW/S+B/6KwxYVKbr03kDe5tduGenFW9H2PUD+HdC/GBaHn4wLU9RoZbJzE5fV+/9zoDyQbM75vm+NzkagQkmjX9uKdJiUqEWI3LV8PiU80Los4Yz5Pmj12eYrvejPwP1NEuWGVVd7S4WlekwrZjJSvLj/JJ4OxtduDFF4mKFOoGlgbmlL3ExBph7wADz4HH7JH77aTse2W2N+E0/rViL3ywuxKzSyH3B3D6JrQ3BfpcH+3CY2pRCDZaP9P/jGy0Y4gAAIABJREFUmT9UN+BJtKbdgwc/bsOzh20RJ3C1AK6bkIP/z96dx8dd1fsff53Zs05Wkm4she5QaEuLtIWyLypuqFdEBBdUuG5XvVdRWUW87ooKLhcXcPupVwX1UgotawuFtqxdaCh0b9Ps6+xzfn/MJJnJ0k7SJDNJ3s/HI48k5zvfcFrSOd/v+3vO53zxtGKqx0n9w1g8MSN5a1N6kLyjNcpwTBozwPFdQXKpq/umf4bffdSzRI5WLN4TBqReBFpgepErqxuLSe7SRdroeXx/iM+ua+KNfpYVF3sMty7yc/Ws/AHrBb7WEuGhvSFW7QmyrjbU7/Lo/lT4HFwwxcvF03ycO9lHiffobs5DMcv/bOvgOy+2DlgXbUmlh1sXF3Nm1fhZLXOgM8aWpkjajf6rzVHaMixBciQVPkd3iDw7Ob7MKXFlfYf7uO0JnsMpwUM4BlMKnEf9+yTjk8aW0bO/I8Z/PdPMP3cH+z1+5Yx8bl/sp3SAf6vNoTir9yVmKa/eG8q4pILHAcurvd33LtOHYePXx/cHuWlDKy/2s1kuJOo3f/G0Iq6eVTCoYCOXtUfibGnqGyQf6ByeINnnhJn+xLgyp+thZambYwudWa1PbG1ickzvSTOBqKXIY5hWoIeV0j+NL6Mj27nYxdMSk2EWVw4tF1PAfBgKmEff661RPruumScO9H2S7jDwibkFfHlBMYVuB/XBGA8nb/pX7w8OuGlFb3lOw9mTPN0XZiNVomBzY4RbN7awam//swLyXYbr5xXy6ZMLR6Qe6EhrCSdm8q3cE+DhQVwYH8lxhU5mlyZu8LuC5JklLm10J+OKLtJGVyBq+dYLrdz5Snu/D73OrPLww6UlzCxxE4pZ1h0MdW+iNNCGe/05tTxZ73Kaj4UV7hG5iWwOxbnzlTbu2tw+4CyES6clVsvMLhl7q2ViccuzdWEe2hNk5Z7BXRgfTpnXkTJjzNX9wFKbJcp4orFl9P1jV4D/fLq5342dK30O/vsMP+86IVGSaWtzlFV7EqHys4fCGU/CmJTv4MJkLeUVk70jMps4bi1/eyPAbRtb2TXAapkTi53ctMjP244bm6tldrZFeXB34u9/7cHMHxgfjtcJM/zp9y1zSt0cV+jUnioyrmh8GV1jNRdTwHwYCpizw1rL71/r5KvPtfQ7S2taoZOqPAcb6zKvdzmt0JlYmjzVx1mTvKM66/XJAyFu3tDCpvr+ZwWUex3812lFfGhWQc7Pdn2jNcqDexL1RtceDGW8c3V/phU6+1yMzfS7tAmRTAi6SMuOlxsjfGZtU7/vx12zwtYfCmdcZqHQZThncs9MstFclbK/I8Y3nm/ld6919ltyyGHgAzPy+dJpxTm/AU9LOM6afUEe3BPkkb0hGo/igWWJx6SFyF1BcqXPMSYDEZHB0NiSHS3hOLdtbOWebR39Hj/jGA/7OmIZ17s0wOmV7u56l/PL3KP2/hWOWX75agfffqFtwMkjiyrc3LrYz/Lq3F4tE41bnj3U88Dy1ZahP7D0OOAkf89s5K7JMCcUaXNumRg0voy+rlzsK8+29LvX11BysWOTudiFI5SL5WzAbIz5JHANcArwB2vtNb2Onw/8BDgWWA9cY63dlTzmBe4G3g10At+y1n4vk3NTKWDOrrpAjBuebeEvrwcGfa7TJC7mLk7e9M8uybze5Uiw1nL/ziC3bWwZcDbc8UVOblxYzDtPyMvq0qlU0eQSi64Ls+1DuDCbWuDsudFPLhObWeLSBhEyoekiLXticcvPt3Zw+6bWIdXrPbHY2T1L+cwqL94sPxjc2hThto2tPLin/2XaeU7DdfMK+MwpRTlVA/71lAeW64bwwLLYY3pu9FPKJ1XlKUiWiUtjS3Y9UxviM2ubhxRk+j2G86ck7lsumOrN+uqK1nCcO19p567N7XQO8AZ98VQvN5/uZ25p7qyWaQ4lHliu3BPk4X3BAUtKDcTtgJOKe+5busomTS92qRaxTGgaX7JnuHKxiwe5D8xQ5HLA/C4gDlwM5KUGzMaYCmAH8FHgH8DXgLOstW9KHv8GsBx4G1ANPEoiRF55pHNTKWDODQ/vDfK5p5vZM8ByrS7lXgcXTPVy8VQf5005+nqXIyESt/zm1Q6++ULbgLsOn1bu5tbTi1kx2TfKvUvoqgm3ck9iE6v+npb1x+8xLKrwpFyMJTZFGovlP0RGmi7Ssm93e5QvPN08YBmjLm4HLKv2JkLlqT5O9I9MWaWjte5gYrXMc3X9r5Yp9Rq+cGoxH51dkJVQPBq3PJPywLImwwDGaRLj4txSd1r5pEn5CpJFetPYkn2hmOX7L7XxvZfaCB9hMcacElf3LOUzhmEfmJFwsDPGfz/fyn01nf2W9DDAFSfl8+UFRUwdobKDR7KjJcqDewI8tCfI07XhjB9YnlDkZH65O22z8BOLXeOmzrTIcNL4kn0P7w3yH+uaj7gaJpu5WM4GzF2MMbcDU3sFzB8jERgvTX5fANQDC6y124wx+5PHVyWPfw2YYa1935HOTf1vK2DOHe2RON94vo27t7SnLQWeX+bmommJm/6FFe4xs0SpLRLnx6+08+NX2gecQXf+FC+3nO7nlLKRnxXwWkukeybZ07WZ14Sb4Xdx8VQflxybuDDWBZlIZnSRlhtssubkF9e3pD30q85L1Lu8aJqPcyZ7x8yKC2st/9gV5LaNrbzW2n+Ae2yhk68uLObd00d+tUxzKM4jKQ8sWzJ8YFniMVw41ccl03ycn6MPjEVykcaW3PFqc4TPrmvm6dpwd5vPCWdP8naHysdmKZAdiu3NEW7d2Mq/BtjU0OeEj88p5D/mF434e3YkbnmmNszK5L3LQONdb04DS6sSM/kumebjJH/uzLwWyXUaX3JDeyTOHc+38tMtHTmZi43VgPmHgMdae11K2yvAzcAaoBGottbWJo+9G7jZWnvK4c611v5v6n9bAXPueaUxwj93BZhc4OTCqT4mjWK9y5FQ2xnjWy+28etXOwacFfDeE/P4ysLiYb0IjcQtT9d2zSQLsKM1s5pwLgNLq72JC7Mcnsknkut0kZZbmkJx/vBaJ9G45exJXk4tH716lyMhErfct72T/36hlUP9bDwFiQvRW08v5twpw7daxlpLTUuUh/Yk6imvH8QmVjP9Li5JLt/L1Zl8IrlOY0tuiScf+m1pirCwwsNZkzxjftPq9bUhbt7QyjOHwv0eL/EYPn9qEdfOLsQ3jLU9m0JxHt6bCJQf2Te4B5YXJR9Y5uoKV5GxQONLbsnVXGysBsz3AHXW2i+ltK0FfgGsBnaTKKsRTB67EPiFtfb4w51rrf116n87NWCuqakZgT+dSMKugOHunW5WN/Qf2LqN5b2To1wzNULJEB+2N0dgXZOTpxqdPN3kpD2W2UWf32VZWhpjeVmMM0tjFClTFhEZEzpj8Pt9Lu7b56ZzgPf8M0pifPL4MLMLh3b9F43D860OnmxMjC97gpndvDuNZWFxnOVlMc4qizEtL7euP0VEpH/WwhONTn68083OQP/v+dXeOJ84NsIlx8QYSlUma2FnwPBUo5MnG5282OogTmY/6IS8OGeVJe5dTimOM4p7u4uITDipDx56B8yjEh0ZYx4DVgxweK21dvkRfkQ7UNyrrRhoSx7r+j7Y69iRzh2QntbISJoBXDAfNtSFuem5FtbVps8KiFjD7/a5+Uedh8+dUsTH5xYeccdPay2vJmeSrUzOJItneP8+u6Sn9MXiSs0kExlumgUgo+XU2fCFQIxvv9jGL7d19KlNub7ZyfoX8njP9MRqmeMzeIrYGIyxam+Ih/YEWb0vSGsks8GlzOvgwqleLp2Wx7lTvDm16aDIeKCxRUbLTOCaJZbfv9bJN55v5UBn+mqZgyEHt9R4+XO9i1tO93PBFO8RVwaFY5ana0PdZfveGGBj9N669kq4ODlT+YRizYYRGW4aX2QoxsoM5o8BV1trlyW/LwDqgIUpNZivttY+nDx+GzAzpQbzgOem/rdVIkOywVrLqr0hbtnQwtbm/muKTcl3csPCIq44MT+tvk44ZllXG+LB3UEe2htk5yAuzJZ3lb6Y5ssoYBCRodNFmmTDG61Rvraplb++0f8u1G4HfGR2Af95ahHlvp6ldtZatjX3PLB8ti7zB5ZzSnpKXyyu9IyZvRJExiKNLZINndE4d2/u4Icvtw34wPGsag+3LfazoMKT1t6Q8sByzSAeWJZ3PbA8No9zJ3u1qbjICNP4IpnI2RIZxhgXiRnVNwNTgWuBqLU2aoypBF4DPgz8C7gVWGGtfVPy3P8GzgTeAVQBjwIfstauPNK5qRQwSzbF4pY/7OjkG5va2NfZf1A8p8TFDQuKaY/EeWhvkDX7QrQN4sLsomSgrAszkdGlizTJpk11YW7e0MKTB/uvoVnsNnzmlCIWVLi7N1Ha1Z75A8uzkg8sL9YDS5FRpbFFsqkhmFgtc8+2DiL9l//nXSfk8aFZBWyoS2zS9+yhMJnecM8tcXHJsYlNrE7XA0uRUaXxRTKRywHzLSTC5VS3WmtvSR6/APgxcBywHrjGWrszecwL3A28GwgA37TWfi/lZw94bioFzJILAlHLz7a0872X22jNcEOLgcwtdXFp8qZ/UYUuzESyRRdpkm3WWh7ZF+LmDS1saep/tUymKnyO7k2Uzp3ipcitB5Yi2aCxRXLBzrYoX9/Uyp9f73+1TKY8DjhrUqL0xcXTfBynB5YiWaPxRTKRswFzLlDALLmkKRTnuy+28fOt7YQHmBXQm8cBZ0/qmUl2bKEuzERygS7SJFfE4pY/vR7g65ta2duR2SxlgHmlLi6dlpd4YFnpxnGE2poiMvI0tkgueaE+zC0bW3lsfyjjcyp9ju77lnMm64GlSK7Q+CKZUMB8GAqYJRftbk/MCvjTjkC/S8qOyeuZSXbOZC+FujATyTm6SJNcE4xafrGtne++2EZzP6tlvE44u9rLJcf6uGiqj2l6YCmSczS2SC56dF+Qmza08nJjpN/jp5S5uXiaj0un+VhQoQeWIrlI44tkQgHzYShgllz2cmOEr29q5YkDIU4sTmyidIkuzETGBF2kSa5qDsX5/ktt3FfTic8J50/peWBZoAeWIjlNY4vkqri1/OX1AN97qY19HTHOrPJwybQ8LprqZaoeWIrkPI0vkgkFzIehgFlEREaCLtJERGS4aWwREZGRoPFFMtE7YNbUFBEREREREREREREZEgXMIiIiIiIiIiIiIjIkCphFREREREREREREZEhUgzmFajCLiIiIiIiIiIiIDEw1mEVERERERERERERkWChgFhEREREREREREZEhUYkMERERERERERERERkSzWAWERERERERERERkSFRwCwiIiIiIiIiIiIiQ6KAWURERERERERERESGRAGziIiIiIiIiIiIiAyJAmYRERERERERERERGRIFzCIiIiIiIiIiIiIyJAqYRURERERERERERGRIFDCLiIiIiIiIiIiIyJAoYBYRERERERERERGRIVHALCIiIiIiIiIiIiJDooBZRERERERERERERIZEAbOIiIiIiIiIiIiIDIkr2x3IJS0tLTbbfRARERERERERERHJVX6/36R+rxnMIiIiIiIiIiIiIjIkCphFREREREREREREZEgUMIuIiIywmpqabHdBRETGGY0tIiIyEjS+yFDkbMBsjJlhjAkaY36b0vZ+Y8wuY0yHMebvxpiylGNlxpi/JY/tMsa8v9fPG/BcERERERERERERERm8nA2YgZ8Az3V9Y4yZB/wMuAqoAjqBu3q9Ppw8diVwd/KcTM4VERERERERERERkUHKyYDZGPM+oBlYndJ8JfAPa+0T1tp24EbgXcaYImNMAXA5cKO1tt1a+xTwAIlA+bDnjtafSURERERExq64tXzl2Rbm//kgH328kZ1t0Wx3SURERCQnuLLdgd6MMcXAbcB5wEdTDs0D1nV9Y63dYYwJAzOBOBC11m5Pef2LwIoMzt3YXz9Uc0ZERIaTxhURkbHt9/tc/OQNDwC72wM88EYn10yLcNWUKD5ndvqksUVEREaCxhfpz4wZMwY8lnMBM/A14B5r7V5jTGp7IdDS67UtQBEQA1oHOHakc/t1uL80ERGRwaipqdG4IiIyhtUHY9zzbC1gu9vC1vDz3R5WNeXxzTNKuHiab1T7pLFFRERGgsYXGYqcKpFhjDkNuAD4fj+H24HiXm3FQNsRjh3pXBERERERkQHdsamN1rDt99jOthj/9kgDVzzSoLIZIiIiMiHl2gzmc4Djgd3J2cuFgNMYMxdYCZza9UJjzHTAC2wnUSLDZYyZYa3tmsd/KrA5+fXmw5wrIiIiIiLSr82NEX69vSOtzeuEUCz9dQ/uCfLo/iCfm1/Ep08uwucyiIiIiEwEOTWDGfg5cCJwWvLjp8C/gIuB3wGXGWPOSm7qdxvwV2ttm7W2A/grcJsxpsAYswx4O3Bf8ucOeO5o/uFERERERGTssNby5WdbiKdMXp5e5OSV91TzsTkFOHplyMEY3PF8G2f+vZaH9wZHt7MiIiIiWZJTAbO1ttNae7Drg0Rpi6C1ts5auxn4BImw+BCJ+snXp5x+PZCXPPYH4LrkOWRwroiIiIiISJr/2x3k8QOhtLavLfZTmefkW28q4bHLKllS6elz3httMd7zcANXrm5gd7vKZoiIiMj4Zqztv5bYRNTS0qK/DBERGXbaKENEZOwJxSxv+lstb7T11MJYMcnL3y8uJ3Uz8ri1/OG1Tm7e0Ep9MN7n5+Q5DZ8/tYhPnVyI1zl8ZTM0toiIyEjQ+CKZ8Pv9aRc1OTWDWUREREREJBf8fEt7WrjsMHDHEn9auJxoN1w5o4AN76ri2tl9y2YEYpbbN7Wy9O+1rN6nshkiIiIy/ihgFhERERERSVEXiPHtF9O3a7lmZgHzytwDnlPidfDtM0tY89ZKFlf2fd2O1hiXr2rgg2sa2KOyGSIiIjKOKGAWERERERFJ8fVNrbRGeqrnFXsMX15YlNG5p1V4eOgtlfxoWQnl3r63Ww/sCnLG3w7x/ZfaCMdUoU9ERETGPgXMIiIiIiIiSS83Rri3pjOt7YunFVPhc2b8MxzGcNXMAjZcXsVHZhfQu/JyZ9Ry68ZWlt1/iMf2q2yGiIiIjG0KmEVERERERABrLTesbyaeMrH4pGIX184uGNLPK/U6+O6ZJay5rJJFFX3LZtS0RHnHQw1c82gj+zpi/fwEERERkdyngFlERERERAT45+4gTx0Mp7XdvqQYj7P3HOTBWVDh4eG3VvLDpSWUevv+rL/vDLDkr7X88GWVzRAREZGxRwGziIiIiIhMeKGY5cbnWtLazp3s5eKpvmH5+Q5juHpWARvfVcU1M/P7lM3oiFpu3tDK8vsP8bjKZoiIiMgYooBZREREREQmvJ9uaWdnW0+ZCqeBO5b4MeboZi/3VuZz8oNlpTzy1koW9FM2Y3tLlLc/1MCHH2tkv8pmiIiIyBiggFlERERERCa0Q4EY33mxLa3tw7MKmFPaNwAeLosqPTzylkq+f2YJJZ6+IfZf30iUzfjRy21E4iqbISIiIrlLAbOIiIiIiExot29qpS3SE+L6PYYvLSga8f+u02H40OwCNl5exQdn5vc53h613LihlbPuP8QTB0Ij3h8RERGRoVDALCIiIiIiE9aLDWHu296Z1val04op9zlHrQ/lPid3Livl4bdUcmp531nT25qjvG1lPR99vJEDnSqbISIiIrlFAbOIiIiIiExI1lpuWN9CagGKGX4XH51TkJX+LD7Gw5q3VvLdM/34+ymb8ZfXE2UzfrK5nWg8Cx0UERER6YcCZhERERERmZAe2BVkXW04re3ri/24HcO7sd9gOB2Gj8wuZOPlVXxgRt+yGW0Ry1eebeEDL/h4ulZlM0RERCT7FDCLiIiIiMiEE4xabnyuJa3tgileLprmy1KP0lX4nPx4eSmr3lLBKWV9y2bs6HTwlgfr+evrnf2cLSIiIjJ6FDCLiIiIiMiEc9eWdna399Qzdhr4+hJ/FnvUvyXHeHnsskq+/SY/xb3KZsQtXPtEE/fvDGSpdyIiIiIKmEVEREREZII52Bnjey+2pbV9ZHYBs0r6zhTOBU6H4do5hWx4VxXvPym9bEbMwkcea+RfuxQyi4iISHYoYBYRERERkQnla5taaY/2bO1X4jHcsKA4iz3KzDF5Tu46q5RfnF2KI2VrwqiFax5r5KE9wSz2TkRERCYqBcwiIiIiIjJhvFAf5vc16XWLb1hQTKl37NwavefEfG6aESa1YEYkDletaWD1PoXMIiIiMrrGzlWUiIiIiIjIUbDWcsOzLSlzf2GW38WHZxdkrU9D9ZaqGHcuK0lrC8fhytUNPL5fIbOIiIiMHgXMIiIiIiIyIfx9Z4Cna8NpbXec4cftMAOckduumlnA989MD5mDMXjfI408eSCUpV6JiIjIRKOAWURERERExr1A1HLThta0toumejl/ii9LPRoeH5pdwLff5E9rC8Qs73ukgadrFTKLiIjIyFPALCIiIiIi495PNrezpz3W/b3LwNeX+A9zxthx7ZxC7uj1Z+mIWt6zqoFnDylkFhERkZGlgFlERERERMa1A50xvv9SW1rbtXMKmOF3Z6lHw+/6eYXcdnpxWlt71PLuVQ1srAsPcJaIiIjI0VPALCIiIiIi49ptG1vpiPZs7VfmdfDF04oPc8bY9OlTivjqwvQ/V2vE8q5V9bxQr5BZRERERoYCZhERERERGbc21YX5w2udaW1fXlBEiXd83gp94dQivnhaUVpbS9jyzlX1vNwYyVKvREREZDwbn1dVIiIiIiIy4VlrueHZlrS2OSUurplVkKUejY4vnVbE5+cXprU1hSzvWFnPliaFzCIiIjK8cipgNsZ4jTH3GGN2GWPajDEvGGMuTTl+vjFmmzGm0xjzqDHmuF7n/tIY02qMOWiM+Vyvnz3guSIiIiIiMv789Y0A6w+ll4a4Y4kfl8NkqUejwxjDVxcW8+mT00PmhlCct6+s59VmhcwiIiIyfHIqYAZcwB5gBeAHvgr8yRhzvDGmAvgrcCNQBmwA/l/KubcAM4DjgHOB/zLGXAKQwbkiIiIiIjKOdEbj3LyhNa3tkmk+zp3iy1KPRpcxhltPL+a6uemzteuCcd62sp7XWhQyi4iIyPDIqYDZWtthrb3FWrvTWhu31v4TeANYBLwL2Gyt/bO1NkgiUD7VGDM7efrVwNestU3W2q3AL4BrkseOdK6IiIiIiIwjP36lnb0dse7v3Q64ffH429jvcIwx3LHEz7Vz0kPm2kAiZH6jNZqlnomIiMh4klMBc2/GmCpgJrAZmAe82HXMWtsB7ADmGWNKgUmpx5Nfz0t+PeC5I9l/EREREREZffs7Yvzg5fa0to/NKeQkvztLPcoeYwzfOsPPh2blp7Xv74xz2cp6drYpZBYREZGj48p2BwZijHEDvwN+Y63dZowpBOp6vawFKAIKU77vfYzk8YHO7VdNTc0Qey4iItKXxhURkdFz06seOqM9tzolLsvlRYeoqTmUxV4Nv8GMLZ+ogMZmD/fX9vy97O2I8eZ/HOBnp4So9tmR6KKIiIxBuneR/syYMWPAYzkZMBtjHMB9QBj4ZLK5Hei9pq0YaEse6/o+2OvYkc7t1+H+0kRERAajpqZG44qIyCjZUBfmwbr0uSU3LS5l4eypWerRyBjK2PKrGZbrn2zijzsC3W37Qw4+9Woh/7q0kikFzuHupoiIjDG6d5GhyLkSGcYYA9wDVAGXW2u7dp/YDJya8roC4EQStZWbgAOpx5Nfbz7SuSP0xxARERERkVFmreWG9c1pbXNLXXxwZv4AZ0wsDmP4yfJS3jM9L619Z1uMt62s40BnbIAzRURERAaWcwEzcDcwB7jMWhtIaf8bcLIx5nJjjA+4CXjJWrstefxe4KvGmNLk5n3XAr/O8FwRERERERnj/vJ6gOfqImlt31hSgsthstSj3ON0GO4+q5R3Hp8eMu9ojfH2lfUcCihkFhERkcHJqYDZGHMc8HHgNOCgMaY9+XGltbYOuBz4OtAEnAG8L+X0m0ls3LcLeBz4trV2JUAG54qIiIiIyBjWEYlzy4bWtLY3H+tjxWRvlnqUu1wOw89XlHLZcb609u0tUd62sp76oEJmERERyVxO1WC21u4CBpxeYK19BJg9wLEQ8OHkx6DOFRERERGRse3OV9rZl1Liwe2A2xf7s9ij3OZ2GO5ZUcYHH21k5Z5gd/u25ihvX1nPPy6poMynmswiIiJyZDk1g1lERERERGSw9rZHufPl9rS26+YWMr04p+bT5ByP0/Cbc8u4aGr6LO/NTVHe8VADzaF4lnomIiIiY4kCZhERERERGdNu3dhKIGa7v6/wOfj8qUVZ7NHY4XUa7j23nPN6lRJ5qTHCO1fVK2QWERGRI1LALCIiIiIiY9azh0L8+fVAWtuNC4vxe3Srkymfy/C788s5e1J6yPx8fYR3P1xPa1ghs4iIiAxMV10iIiIiIjImxa3lhvUtaW0nl7n5wIz8LPVo7MpzGf5wfhlLqzxp7RvqIrz34QbaIwqZRUREpH+HLUpmjOl3w7zerLW/HJ7uiIiIiIiIZOZPOwJsrI+ktX1jiR+nY8B9w+UwCtwO/nRhOe9e1cAzh8Ld7c8cCvPehxv484XlFLg1R0lERETSHWnXi6sy+BkWUMAsIiIiIiKjpj0S59aN6bOXLzvOx1m9yjzI4BQmQ+bLV9XzXF1PeL+uNswVqxv54wVl5LsUMouIiEiPwwbM1tpzR6sjIiIiIiIimfrhy+0c6Owp2+BxwNcW+7PYo/Gj2OPgzxdW8M5V9TyfMkP8iQMhrlzdyB/OL8fn0ixxkbEiELW83BhmU32E5+vDNIctHkdik0+3w+B1gNtp8DoMHid4HAaP0+BxJL5OvC7l9V3HnCb52uQ5KV9PG5hTAAAgAElEQVSnnuM0YIzeM0TGsyPNYO6XSbwzdL87WGtVkEtEREREREbF7vYoP3qlLa3t+nmFHF80pNsb6UeJ18FfL6rgbSvrebmxJ2R+dH+Iq9Y08Nvzy/E6FRiJ5Jpo3LK1Ocrz9WE21iVC5a1NEaI2e30ygLd3cO00zPS7+Pd5RayYrJUnImNdxldgxpgpwI+Bs4GSXoedw9kpERERERGRgdy6oZVgrOf7Y/IcfG5+UfY6NE6Veh3cf3E5b11Zz5amaHf7w/tCXP1oI/eeW4ZHIbNI1lhreb01xqb6cPIjwksNEQKxLKbJ/bBAMAbBmIVIT992tsVYtTfEB2fmc9vpfkq8Kr8jMlYN5hH/T4FO4HzgcRJB8y3A/w1/t0RERERERPp6pjbE/74RSGv76sJiij0KJkZCmc/J/RdXcNnKerY194TMK/cE+fBjjfzq3DLc2lRRZFTs70iEyc8nw+RN9WFawrkVJg/Fvds7WbUnyHfOLOGtx+VluzsiMgSDCZiXAsdaazuMMdZa+6Ix5iPAOuAXI9M9ERERERGRhLi1fGl9+sZ+88vcXHlSfpZ6NDFU5iVC5reurKempSdk/ufuIB97vIlfrCjFpZBZZFg1heJpQfLz9eG0uvODdXyRk4UVHhZUuDmhyEXMQjhmCcUtkRjJz5ZQHMJxSzhmk58T34dilkic5GdLKJb6Ovq+PuXnxjPIwA8G4nxgTSNvP97Ht84ooSpfC+VFxpLBBMwxoOtqotkYUwm0AlOGvVcikvNebY5wz7YO5pa6mVPiYnapG79mDomIiMgI+uNrnbzQEElr+8YZfpwKN0dcVb6TBy6p4K0P1rGjtac+yd92BtjSFOGEYheT8h1U5TmZlO+kKt9BdZ6T6nwnlT6H/h+JHEZnNM6LDZHuTfg21YV5vS125BMHUJXnYEGFh4UVbhZVelhQ7qbMl73ANpYMnMMpofSO1ij/+UwL21MeWgHcvzPI4/tr+foSP+8/KV+bA4qMEYMJmNcDbwb+BjwE/D8gAGwYgX6JSI57ri7Mz7d2pLVNLXAyp8TFnFJ34qPExawSN3naZVxERESOUnskzm0bW9Pa3n68j2XV2hxqtEzKd/LAJZW85cE6dqaEX6+2RHm1V0iUymHgGJ+D6nwnVflOJuU5qMp3JgPoRHtXEK2Z0DLeReKWzY0Rnk/OTN5UH2Zbc5Shlk0u9hgWlCfC5AUVHhZVepic78ipYNbpMOQ7DPkpCdTUQhdPvM3Ld15q4wcvtaVtQtgctvz7U8385fUAP1hawnHawFUk5w3mX+lVQNf0xM8CXwAKgR8Md6dEJPdta+p7E7G3I8bejhgP7wt1txnghCJnd+g8NxlAn+R3qV6fiIiIZOz7L7VxMNCzPNzrhNtO92exRxPTlILETOa3PFjPnvbMZljGbWL5+8FAHHrNQE/lMFDp65oFnQyhU4PovERAfUyeQ9eRkjFrLS3hRFmHqE0EvLE4fb6P2kQJiGjy62jyNTEL0XjyWLK9v++jyddF4xDpbk/9uZadbVFeboykbVI6GD4nzC9LlLlYWJkIlU8sduHIoTB5MHwuw1cXFvOO4/P41Nomnq9Pf394dH+IM/9+iBsXFvOxOQVaCSGSw4y1Y78g/HBpaWnRX4ZIhi5fVc/qlCB5sNwOmFGcPtt5bqmb44qcY/YCSWQgNTU1zJgxI9vdEBEZs3a1RVnyt1pCKaHM5+cXcuOiiRswZ3ts2dkW5YpHGtjaPPDM5ZFigIrkjOjqvMTnSQVOFla4edMxXkq8KtsmcKAzxv9sbefe7Z3UBYdeuzhbnAbmlLpZWOHurp08t9Q9bh+uROOWu7e0c8emNgL9TOc+vdLNj5aVMqfUnYXeTSzZHl9kbPD7/WlvRhkHzMaY2wY6Zq296Sj7lRMUMItkbvW+IBvrwmxtirK1OUJNy9CXdaXKdxlmlbiYU+JmTqkrWePZzaQcW+YlMhi6SBMROTrXPNrI33cGur+vynOw4fIqitwTN0jMhbHFWsuu9hgHO2PUBuIc6IxR2xlLfA7EOdgZ42AgRlNo9G6zDHBKmZtl1R6WVXtZVu2lVIHzhPJCfZi7trTztzcCRMZQrjy9yJmol5ysnTy/3E2+a+L97r7RGuXTa5t48mC4zzG3Az4/v4jPzS/C49S94UjJhfFFct/RBMy/6tVUDawA/matvXJ4upddCphFhi4Us7zWkgibtzZF2NIUZVtzhJ1tMYbjH1axxzA3GTonwmc3c0tdlGdxswqRTOkiTURkaGJxyy0bW/nRK+1p7T9ZXsKVMwqy1KvcMJbGlmDUUhuIURuIcaAzTm0yeD7Y2RNC13bGaQiNTBo4t9TFsmovy6u9LK3yUJmn68fxJha3PLgnyF2b21lX2zeYzDWT8h0srPAkPxK1kzXzvoe1lvtqOvnqcy20hvveTc4tcXHn8lJOr/RkoXfj31gaXyR7hhww98cYcwlwhbX26qPtWC5QwCwy/Doicba3RNnSFOme7by1KcL+zuG5gSjzOvA5wQJdb2c2+UGyrd+vsWmv7/6c+jMG/Hm2z2tcDsPxhU5mlLiY4Xczy+9iRvKjYALPrpIEXaSJiAxeSzjOtY83smpvekmu08rdrLmscsKX1BqPY0s4lgiiD3bGkwF0Ing+EIglQ+lEIF1/lOUOZpckAudlVYlZzlX5CpzHqrZInN9u7+RnW9vTNp7szeuEQpcDtyNx3e5ygMsY3I7EBnQuQ88xk/jsdoDTJF7rTmnv+t5pUtt7znU7DM6Uc7q+dxlDiddwarmHSfqdy8iBzhhfeLqZf+0O9jlmgOvmFfCVBcW63xpm43F8keE33AGzA2iy1o6L4mcKmEVGT3Mongybo4kZz80RtjRFRnUJ5WiZWuBkZjJsnpkMoGf6XVTlqezHRKGLNBGRwXm9NVHf99WW9Pq+Pic8+OZKFlRo1tpEHlvCMcuhQEpZjkCMbU1R1h4MsWUINaFPKnalldSYUqDwL9ftaovy860d3Le9g9bIwPcPJxY7uW5uIVeclK8Qcoyy1vLAriBfeLq531raxxU6uXNZCSsm+7LQu/FpIo8vkrmjKZExvVdTPvB+4G3W2pOHp3vZpYBZJLustRwKJILnLcngeWtzhG1NUdqj4++fZ7HHJINnd3cAPavExfFFrnG7ecdEpYs0yWWHAjE21oWpzHNqqankhMf3B7n60Uaaey2Lrs5z8Lvzy1mk31NAY8tAGoIx1h4Ms/ZgiLW1YTY3RgZdru34ImfaDOfjilwj0teREotb4jDuriettTx7KFFf+R+7gsQP8z/27Elerp9XwEVTfRN+tcN40RSK85VnW/j9a539Hv/AjHxuX+xXqZFhoPFFMnE0AXOcxIrwrh/QCTwPfNZau3E4O5ktCphFclPcWva0x3pmPCc/b2+JpO0mP164DEwv7gmcuwLok/wu/B5dMI1FukiTXNIeibPuYJjHDgR5fH+IzU09s/3+7cQ8fri0FJ9LN+My+qy1/GJrBzc829Jn4+AFFW5+d145kzWztJvGlsw0h+Ksqw11h84vNUYOG0z2Z1qhsztsXl7t5fgi56iuQrPW0hax1Afj1AVi1AXj/X5dH4xTF4zTGIpjLcwvd3POJC/nTPZyRpVnzG4YF4lbHtgZ4K7N7Wysjwz4Oo8D3j09n+vmFXJKmXsUeyijac2+IJ9d18zu9r43glV5Dr79phLednxeFno2fmh8kUwMa4mM8UYBs8jYEo0nZjynPvnqutY3vdr6/Rq6bw5S3xl7v77/n2dSfkai1nRNS5TtLdHuz9ubI+xsjw36JuZwqvMczCzpmfE80+9iZombyfkqt5HLdJEm2RSJWzbUhXl8f4jHD4R47lCYwy0KWVTh5nfnl1Ot+pAyisIxy38908yvt/edmfae6XncuayUPD34SKOxZWhawnHW13bNcA7xfH2kzwONI5mc7+gup7Gs2sNJxa5BX4cFo5b6YE8onBoQp37dEIxTF4wd9aQKjwPOOMbDOZN9rJjs5bRyN64cn+HcHIrzm+0d/HxLB/s6B/4LqPA5+PDsAj4yq0D1tCeI9kic2ze18rMtHf2uULjsOB/fflOJrmWGSOOLZEIB82EoYBaR4RaKWV5v7QmcU0PojmEs+1HgMt2B89xSN3NL3cwrU/CcK3SRJqPJWsuWpiiPHQjxxP4gaw+GB11maHJ+ohSB6tzKaGgIxrhqTSPrasNp7Qa4aVExnz2lUGNZPzS2DI+2SJxnDyUD54NhNtWHiQxyD8GqPAdLqxJh84IKD+2RRHhcF4xTH0gExN1hcTI8Plzd4NFQ7DGcVe1lRXKG8wz/4EPykbKjJcpPt7Tz+9c6D3u9PKfExXXzCnnv9HytvJmgnj0U4tNrm9nWT+11v8dw+2I/H5iRnzO/22OFxhfJxKACZmPMHjhyySpr7bFH37XsU8AsIqPFWsu+jli/s54PBo5uZ/RUfo9hXqk78VHmZm6pizmlboq0ycmo0kWajLQ97VEeS85QfuJAiEODeB8xJN4rete79TnhJ8tLuXx6/jD3VqTH5sYIV6xu6LPUudBl+PmKUt58rJY5D0Rjy8jojMZ57lCYp5IlNTbUhQkP36VZzpqc7+DsSd7uGc6TRnnmp7WWJw+GuWtzOw/tCR42hLhoqpfr5hZyzmSvgkMhFLN876U2vvdSW78Ph86Z7OUHS0s4fozVUs8mjS+SicEGzCtSvl0MXA3cCewCjgM+Cdxrrf3u8Hd19ClgFpFc0BKO81p38Bzh1eZEAP16a/Swy9oH47hCZzJwdnNyaSJ4nl7syvmlkmOVLtJkuDWF4jxxIMTj+0M8tj/I622DWzt9UrGLFZMTM9fOmuTFAB95vJHV+0J9Xvv5+YV8ZWGxNkmSYfevXQE+/kRTnxn2xxY6+eMF5cwtVQ3Vw9HYMjqCUcuG+kTY/NSBEM/VhQlmYQ8QnxMq85xU+hxU+hxUJL+u8Dm627u+Lvc6aI3EeWJ/iMcOhHhsf6jferWHM8ufGCfOmZwoBTJS+4CEYpb/fb2Tu7d08HLjwPWV85yGK07K5xNzC5hZovcG6WtLU4RPPdXUb53ufJfhKwuL+cScApy63zkijS+SiaPZ5O8V4GJr7b6UtqnASmvtycPayyxRwCwiuSwSt+xsi7K9OTnbORlAb2+ODssyS58TZpUkZjvPLXVxcjKAPiZPtcuOli7ScksganmhIUxn1CZuxn1OKnwOPM7cveEIRC3P1CZmKD+2P8SLDZEjLzFLcUyeg3MmeTk7GSpPK+w7iycat9y8oZWfbG7vc+zNx/r42dmlWv0gw8Jay/deauf2Ta19fo+XVXu499wyyn0ae45EY0t2hGKWTfXh7k0D1x9KjCeD5TSJ2sH9BcQVXSGyz0llXqK9wGWOarbuzrbkSpfkapfGUObTsp0GFla4WTHZx4pJXpYc48F7lGNmfTDGL7d1cM+2DmoPs+pmUr6Da+cUcs3MfMr0viBHEItbfrq1g69vau333+WiCjc/Wl6qB5hHoPFFMnE0AXMjcIK1tiWlrQR4w1pbOqy9zBIFzCIyFllrqQ3EebU5yqvNEbY0RdjcFGFrU3TQdVf7U+lzJGs6u7pnPM8qcWuzpUHQRVp2dXTX1wyztjbExgGWO/s9hsqUm/mKrpt7nyPZljhW6XNQ6nWM6IzeWNzyQkOku+zF+kOhQW3wVOQ2LK32cs4kLysme5lTknltzd/WdPC5dc19/o7mlrj4/QXlWmIqRyUQtXxqbRN/eT3Q59iHZuXzzTNKcvphTy7R2JIbInHLC/WRZA3nEHs7YpR4ewLiiuS4UZn2tYOSER5HDiduLS83RrpnOK87GCYwiJ0O85yGpdUeViTHmFPK3Bn/WbY2Rbh7Szt/2tF52Jngp5W7uX5eIe84Pk/vCTJoO9uifGZtM48f6Lsyy+2A/5hfxOfnFx31g5LxSuOLZOJoAuZfAycAtwN7gWnADcBua+3Vw9vNkWGMKQPuAS4C6oEbrLW/7zqugFlExpO4texuj7G5MRE4b2mKsrkpwo7WKPGjfLdzGDix2MXcUldyxnNi5vNxRU4to++HLtJGV2s4zvruDZtCPF8fGbbyMl2cBsq7ZpulhNK9A+quQKHwCDPPrLW81pqYXfbY/hBPHQzREs68024HLK70JJYzT/KysNKD+yiWgK6vDfGBNY3UBdNT5nKvg9+cV8byau+Qf7ZMXPs7Yly5poHney1fdhr45hl+PjqnMEs9G5s0tshwCcUsz9WFkzOcg2yqjzCIvJkyb1f95sRH7weRcWtZsy/EXZvbWbO/b+DXxQBvOdbH9fMKObPKo/rKclSstfzutU6+8mxLv9dUs0tc/GhZKYuP0YbGvWl8kUwcTcDsA24B3gNMBg4AfwJutdb2nYKQg4wxfwAcwEeA04B/AUuttZtBAbOITAyBqOXV5kTo3BU8b2mKDGpTsIEUuAxzSl2cWu7ho7MLmKPlZ4Au0kZacyjOM4dC3cuVX2iIHPVDlOHmc5I2A7prZnSZz8G25iiP7w+yv3Nw/wZPLnN3z1A+s8pD4TCXr9jTHuX9qxv71MR0GfjOmSVcM6tgWP97Mr5trAtz5eqGPhvZlngMvzm3jBWTfVnq2dilsUVGSks4ztqDiQeeTxwIsa05Oqjzjy10ck6yJFNbxHL35nZebRn4ZxS6DB+Ymc8n5hZqlYwMu4OdMf7rmWYe2BXsc8wAH59bwFcXFg/7ddRYpvFFMjHkgHmsM8YUAE3Aydba7cm2+4B91tovgQJmEZnY6gIxtjRFeCUZOG9ujLCtOTLkjWxKPIan31k16ruQ5yJdpA2vplC8e3by2oNhXm4cXD1iSGx0eWyhk4ZQnPpg4iPXQuneum7Yz0luzFc5CvXROyJxrn+qift39r0pu3ZOAd9Y4tfmoHJEf9rRyafWNvUp8zLL7+KPF5RzQrECpaHQ2CKj5UBnrLt281AeiA5kWqGTj88p4KqZBSO2iaBIlwd2BvjPZ5r7rfm9pNLDQ2+p0Kz5JI0vkolBBczGmLOttU8kvz5voNdZa9cMWw9HiDFmAbDWWpuf0vYFYIW19jJID5hrampGv5MiIjkmZmFPwLCj00FNh4MdHYaaTgf7gpndBFxeHeFLJw28I7hIJpoi8HyLk00tDja2OHmtc/A3ocf64izwx1noj7HQH6fam379E7fQGoXGiKEpbBKfI12f6f6+61h7bORvQPwuy+KSGItLYiwpiTPVl50EPG7hnj0ufr677xLSxf4Y35gdwq/FCtKPmIW7drm5d2/fX5DlpTG+NitEP/tNikgOsxZ2BQzPNjt5rtnBhhbnoMfE+UUx3j8lyoryGNrSQ0ZTaxR++IaHB2rTB59vzg5xXsUQZ9WITCCpDx4GGzC/Yq09Ofn1GwO8zFprpw9DP0eUMeYs4M/W2uqUtmuBK62154BmMIuIZKotEmdbcqbzK02R7hnPzb3qm7kMPPuuKqZP8NlpmgUwOLWdscTs5NpEyYvBLs0FmOl3sbzay7JqD0urvcM+kz4Us9QH49QFYjSE4tQF4tQFY9QH4tQF49QHY9QFe9oz2aCva9OkcyZ5OXuQmyaNhvt3BrjuyaY+u7JPL3LyhwvKmVWilFl6tIbjXPtEEw/t6Tv7/TMnF3LTomKcmv1+VDS2SC6Ixi0vJjelfWx/kPWH+t9I12ngnSfkcd3cQhZVquatZNdj+4N8Zm0zu9pjvO04H/eeV57tLuUUjS+SiYlcIqO/GcyfB87pbwaziIgMjrWW/Z1x3vpgHW+09aRp756ex/+sKMtiz7JPF2mHt68jllby4rXWwQfKc0tcLKv2sqzay9JqD8eMQvmITFlraY/aZPgcoy6QKMnRFUSXeBwsn+RlcaUn53czf6khzPtXN7K3Iz0xL3Ib7llRxkXTVEdXYGdblPc90tDn4ZDHAXcuK+V9J+UPcKYMhsYWyUWd0Tjra8PdG9YCLK/2cu2cAqZqyYLkkI5InO+82MYn5hZSpZJ+aTS+SCaGLWA2xpwLxLpKaOS6lBrM86y1Ncm2e4H9qsEsIjJ8/ryjk2ufaEpre+Jtlcwvn7izVXSRlm53e7R7Q761B0NpDyQyYUhscLes2pMIlKs8lPt0YzBaDgViXLWmkfWHwmntBrjt9GI+eXKhahhOYE8cCHH1ow00hdIvq6vyHPz2vHIWHzNxx4LhprFFRERGgsYXyUTvgDnjR4jGmMeBL1tr1xpjvgh8DogaY35irb1jmPs57Ky1HcaYvwK3GWM+CpwGvB1Ymt2eiYiML5dPz+MHL7exualn5trtm1r504UVWeyVjIZI3HIoEKe2M8aBzhi1gXjyc4yDnTEOdia+rwsObnMgh4H5Ze7kDGUPS6u8lHi1GVC2HJPn5IFLKvj80838tqazu90CN25oZXNThB8sLcWnwpoTzj3b2vniMy30qqLCaeVufnd+OVMK9CBIREREZDwazBqVk4Fnkl9fC5wLtAFrgZwPmJOuB34JHAIagOustZuz2yURkfHFYQw3LfLzb480dLet2hti3cEQS6u9WeyZDFU4ZqkNJALjRFAc42Dy69rOGAeSoXJ9MM5wLAVyGlhQ4WZZVaLkxRlVHu0un2O8TsOPlpUwt9TNV59rIZ7yP/6POwLsaI1y33nlVGvJ6YQQiVu+tL6Fe7Z19Dn2rhPy+PHyEvJd+jcsIiIiMl4NJmB2ANYYcyKJ0hpbAIwxpSPSsxFgrW0E3pHtfoiIjHcXTfVyZpWHp2t7ltDftrGVB99coaXzOSSUDI67Zhcf7JptnBokd8ZpCA1uxvFguR2wsMLDsmoPy6u9LDnGQ6FbYVSuM8Zw/bxCZpW4+NBjjbSmbPL5XF2E8/5xiN+fX85pFSqJMJ41BmNc/WgjTx4M9zn21YXFfH6+SqaIiIiIjHeDCZifAn4MTAL+BpAMm+tHoF8iIjKGGWO4aVExl/5fzxDxzKEwD+0Ncsm0vCz2bGIKRi2/fLWDlxsj1KbMQG4c4eB4IB4HnF6ZqJ+8vNrD4mM8mt04hp0/xcfqt1ZyxSONaRs07u+Mc+n/1fOT5SW8a7o2dRuPtjZFuGJ1Azt71VEvcBl+enYplx2n93sRERGRiWAwAfM1wOeBOuDbybbZwA+HuU8iIjIOnFnl5eKpXh7aG+puu21jKxdN9eHQbLZR0xGJ856HG1hX23d24Uio9DmoyncyKS/xuTrfSXXy60n5TqryHFTnO3E79Dswnszwu3nkrZV8+LFG1uzv+TcfiFk+/HgTW5qjfHlBkf7tjyMr9wS49vEm2iLphXGmFTr5w/nlnFzmzlLPRERERGS0ZRwwW2sbgC/3avvXsPdIRETGjRsX+Vm191B3Xd4tTVH+8nqA956o2YyjoTMa532PHH24bIBj8hxU5Tmpzk8ExFV5PYHxpHwnVflOjslzKDiewEq8Dv50YTk3bWjhrs3ptXi/82Ib25oi/PTsUpU/GeOstfzw5XZu3djap+b6mVUe7juvjAqfam+LiIiITCQZB8zGGC9wE3AFUG6t9RtjLgJmWmt/PFIdFBGRsevkMjfvnp7Hn18PdLd9fVMr7zg+D49TQeRICkYtV67uvy5qF4eBY3zJwDg50zgx47gnSK7Od1Lpc+BScCwZcDkMdywpYU6Jm8893UwkpQrLP3cHufhfdfz+/HKOKxrMIjrJFcGo5dPrmvjTjkCfYx+cmc933lSi93YRERGRCWgwV/ffB6YAVwIPJts2J9sVMIuISL++vKCYv70RIJqc6rarPca92zv46JzC7HZsHAvFLFetaeDRlFIFAPPL3Hx5YVEyQE4Ex04FxzICrppZwAy/i6vWNFIX7EmZNzdFOe8fddx3XhlLq71Z7KEM1oHOGB9Y3cDG+khau9PAHUv8fGxOgTbzExEREZmgBhMwvxM4yVrbYYyJA1hr9xljpoxM10REZDw4odjFNbMK+J9tPUvmv/ViG1eclE+BlsoPu3DMcvWjjTy8Lz1cnlfq4u8Xl1OmpesySt5U5WXNZZVcsbqRVxp7QsmGUJy3P1TPd88s4YMzC7LYwx6BqGVHa5TXWqJsb4mwqz1GqcfBoko3Cys8HFvonNDh6fP1Yd6/uoEDnekbg/o9ht+cW8Y5k31Z6pmIiIiI5ILBBMzh3q83xlQCDcPaIxERGXe+cGoRv6vpJBBLTGM+FIjzs60dfG5+UZZ7Nr5E4pYPP9bIyj3BtPY5JS7uv6RC4bKMummFLh56cwXXPdnEA7t6fi8jcfj02mY2N0b4+hL/qJRgsdZSG4hT0xJNfkSoaYmyvSXKnvZYn3rCqSp8DhZWJMLmRZUeFla4KR/H/56i8UTg/kpjhBcbIvx8azvBWPprZvhd/PH8ck70q9yJiIiIyEQ3mCvCPwO/Mcb8B4AxZhLwA+CPI9ExEREZP6rznVw3r4DvvdTe3faDl9v40KwCSr2axTwconHLtY838c/d6eHyTH8iXNamW5ItBW4Hvz63jG+90MZ/v9CWduxnWzvY3hLlV+eUUTJM7wXBqOX1tmifIPm1liitkcPFyAOrD8ZZtTfEqr09KwOOL3KyqMLDwkoPiyrczC93k+8ae+9nzaE4LzdG2NwU4ZXGxMe25kifQDnVBVO83HNOGX7P2PvzioiIiMjwM9ZmdqFtjPEA3wSuBfKBTuAXwBettUe3PX2OaGlpGdpdh4iIHFFzKM6pfzlIS7jnrfYzJxdy62J/Fns1OmpqapgxY8aI/fxY3PKJJ5vSNlMEOLHYyb8uraQ6X+Gy5Ib7dwa47skmOqPpl1zTi5z88YJyZpa4M/o51lrqgj2zkbe3RJLlLaLsbo8Rz8IVndPA3FI3iyrcLKz0sLDCw+wSV85skBlLzkpODZI3N0XZ23GYJLkfn5xXyK2nF6t+ew4Y6bFFREQmJo0vkgm/3592MZhxwJx2UqI0Rj1wCnCjtfY9w9O97FLALCIysn7wUi1xJRMAABm8SURBVBu3bGzt/t7nhE2XVzO5YHwHoCN5kRaLW/79qSb+uCM9XD6+KBEuTxnnf7cy9rzUEOb9qxv7BJvFbsM955Rx4dSeer7hWO/ZyD0zklMfVh0tA0wtdDLT7+KkYhcnFLvY1xFjY12YFxoifQLxTOW7DKeWu1lU4RnVes7NoXivIDnC1qZod5miochzGr5zpp8rZ+RG3WxRACAiIiND44tkonfAfMQSGcaYfOAG4DSgBrgFKAJ+BlwI3DvsvRQRkXHpY3ML+OmWdg4GEhtFBWPw7Rdb+f7S0iz3bGyKW8tn1jX3CZePLXTyj0sqFC5LTppf7mHNZZVctaaR9Yd6FsG1Riz/9kgD/3ZiPo2hODXNic32jiIT7aPAZTjJ70oEyd2f3ZxY7BywvEU0bnm1OcrG+jDP14fZWJcIbDPpV2fU8nRtmKdre/6cFT5H2izno6nnHItb3miL8kpjlFdSAuXBzkruT6XPwcllbuaVujm5zM35U7xU5uk9RURERET6OuIMZmPMr4AFwEPApUAtMBv4DfADa239SHdytGgGs4jIyPvltg4+93Rz9/dOA8++s2pcbxQ1ErMArLV87ulmfvVqZ1r71AIn/7q0guOKxu/fp4wPoVjid/h3NZ1HfvEgTS1wMsPv6v7oCpIn5zuGZfZwZzTOyw0RNtZH2FQfZmNdmDfahh7qZlLPuSUcZ3OvWslbm6NDnl3dxWVgZomLk8vcnJwMk+eVuqlSaZ2cpxlmIiIyEjS+SCYGXSLDGLMfOM1ae8gYMxXYDZxjrX1i5LqZHQqYRURGXiRuWfLX2rQw5vIT8rjnnLIs9mpkDfdFmrWW/3rm/7d359F113X+x5/vLE2bpkmapi1SoUAp0EVaQHZEFORHBXR+VJEzygAO6MzozO/8GMaFxTIsziAO4ozjMh4GARkVhCqiMiwCUmGEUpZStooUKlBaWtosbbqkn/kjt/TepG2a9N7ce5Pn45yc5n6+S97fnPPlw33lc9/fNXz/+fac8d1rK/jlrLHsXW+4rPKQUuLbz7ZzyWNr+tw3ubYq2Le+KidIntxQxaT6KkZWD/zD51Z1dLJgS+D81kYeX7GBtzo29+tcW/o5zxhTzar1m3lm1UZebdv1VcnN3VYlT2+qZr+GKmoq7adcjgwAJEmF4PyindHnFhlAXUppOUBK6U8R0TYYw2VJ0sCorgguOriecx98+52x215ex9+9ZwMzxgwrYmXlIaXEhY/2DJd3G1HBHSc1Gy6rrEQEn5tWxwGNVZzzwCpattFXeUJtJZMbq5jcLUzefWQlFQXuZdwXTcMrOeHdlZyQ6SGdUmJpeycLVmzk8cwq553t59yZYOGqjSxctbFftVQG7N9QxbSmrUHytNHVjB+RnxXckiRJUradeRdaFREfoOv5JwB0f51S+k0BapMkDVKn7T2Caxe28UxWeHLF4y3cemJzEasqfSkl5sxv4TvP5obLY4d3hcv7NlQXqTJp1xw/YTjzPjqOH2baZWwJk/dtqKKuCKuR8yEi2LOuij3rqvizvUcAu9bPeXuaaioyIXIV00dXM62pmgMaq12VLEmSpAGzMy0ylgA72imllPbJZ1HFYosMSRo49/ypg4/fszJn7Jezmjl6t5oiVVQ4+fiYWUqJKxa08C9Pt+WMj6mp4M5ZzUwZbbgslaOd7edcGTC5YWuv5C2rk3dzVfKQ5UeYJUmF4PyindHnFhkppb0KVo0kacg6YUINR44fxiNvbnhn7LLHW7jrw82GJdvwz0+29giXR9cEPzvJcFkqZ7VVFRw+vobDx2/949qqjk6eWLmR51dvomFYMH1016rk4VX+t1GSJEmlx0aNkqSiiAjmHFLPSb96652x3y/fwF1LO5i154giVlZ6vv5UK1c92Zoz1jAsmHtiM+9pMlyWBpum4ZUcP6GS4ycUuxJJkiSpd+XZ1E6SNCgcMb6G/7PH8Jyxyx9voXOzHYu2+ObCVq5Y0JIzVl/dFS7PbPahiJIkSZKk4jJgliQV1SUH15P9oe9nV2/ipy+vK1o9peTfF7UxZ35uuDyqOrjtxGYOHmu4LEmSJEkqPgNmSVJRTW+q5uP75LbE+OqCFjZ0Du1VzN97to2LHl2TMzayKrj1Q2M4dJzhsiRJkiSpNBgwS5KK7sKD68l+dtUrbZ3c8GJ78Qoqsv98vp0v/j43XB5RGfzkQ2M4IutBYJIkSZIkFZsBsySp6PYaVcU5+4/MGbv6qVbaN24uUkXFc+OL7Zz/yOqcseGV8OMTmjhmN8NlSZIkSVJpMWCWJJWEC2aMojZrGfPydZv57rNDaxXzfy1u5//9LjdcHlYBNx8/hvfvPnw7R0mSJEmSVDwGzJKkkjC+tpK/npq7ivmbC1tZ1dFZpIoG1q0vreVz81aT3Xm6ugJ++MExHD/BcFmSJEmSVJoMmCVJJeNvp4+icdjWVcwtGxPXLmwrYkUDY+7La/nsQ2/nhMtVATd8oIkT9zBcliRJkiSVrpIImCOiJiKui4hXIqI1Ip6MiFnd9jk+Ip6PiLURcX9ETOx2/H9GREtELIuI83f2WElS6WisqeD/HzgqZ+w/nmvj9fbBu4r5jiXrOPfBt9mclS5XBlx3XBMf3nNE8QqTJEmSJGknlETADFQBS4H3Aw3AxcAtEbEXQEQ0A7cDlwBNwHzgJ1nHXwpMBiYCHwC+EBEn7eSxkqQSct6Ukbyrduv01NEJX3uypYgVFc6vXl3Hpx9YRWdWuFwR8P1jR/PRvQyXJUmSJEmlryQC5pRSe0rp0pTSkpTS5pTSncDLwCGZXU4DFqWUbk0pddAVKM+IiAMy288CLk8pvZ1Seg74PnD2Th4rSSohtVUVfGFGfc7YTYvX8tKaTUWqqDDuXtrBWfevYlNWuBzAd983mtP2qS1aXZIkSZIk9UVJBMzdRcR4YD9gUWZoGvDUlu0ppXbgJWBaRIwG3pW9PfP9tN6OLVT9kqRd86n9atlnVOU7rzsTXPnE4FnF/JvXOjjz/pVs3Lx1LIB/P6aR0ycZLkuSJEmSykdVsQvoLiKqgZuBG1JKz2eG64AV3XZdA4zKbNvyuvu23o7drsWLF/etcElSXv3l7pVc9ELNO69vf3kd/7fhDxxQl3ZwVOnaMq88urqC85+tYf3myNl+0b7rOZTXcfqRJO0s37NIkgrB+UXbMnny5O1uG5CAOSIeoKu/8rb8LqV0TGa/CuAmYAPw+ax92oD6bsfVA62ZbVted3Tb1tux27WjX5okqfAm7Zv48YoVLFy18Z2xG1Y08tODmotYVf8sXryYyZMnM2/Zei54ZCXrN+eG5Ncc2cinDxhZpOokSeVoy9wiSVI+Ob+oPwakRUZK6biUUmzna0u4HMB1wHhgdkppY9YpFgEztryIiJHAJLp6K78NvJG9PfP9ot6OzfuFSpLypiKCOYfk/n3w3tfWM2/Z+iJVtGseeXM9n7hnJes6c8Plrx3eYLgsSZIkSSpbpdSD+TvAFODUlNK6btvmAtMjYnZEDAe+Ajyd1ULjRuDiiBideXjfecAPdvJYSVKJOn5CDUeNH5Yzdtn8FlIqrzYZC1sq+PjdK2nflFv3lYc18Jmpdds5SpIkSZKk0lcSAXNETAQ+C8wElkVEW+brkwAppRXAbOBK4G3gcOCMrFPMoevBfa8ADwJXp5Tu2sljJUklKraxivnRFRv49dKO7RxRehas2MDfLqqhrVu4/I/vredz0wyXJUmSJEnlLcptFVghrVmzxl+GJJWgM+5dyV1ZofKUxirmfXQclRWxg6OK7+6lHZz321Ws2ZA7vVx8cD0XzNjhs2YlSdohe2RKkgrB+UU7o6GhIefNeEmsYJYkaUcuObie7NnrudWbuPWP3bsplY5XWjfxyftWcvq9K3uEy1+cOcpwWZIkSZI0aBgwS5JK3rSmak6fNCJn7KtPtLChs7Q+eLK+M/H1p1o5Yu5yfvlqzzYef39gHV+aabgsSZIkSRo8DJglSWXhywfVU501a73a1skPXmgvXkHd3PdaB0fOfZMrFrSwrlvwXUHiSzNHcfHB9USUdlsPSZIkSZL6woBZklQW9hpVxdn7j8wZu/qpVto2bi5SRV2Wtm3izN+sZPbdK/lja2eP7YeNHcaNMzv40kGGy5IkSZKkwceAWZJUNv5hxihqq7aGtCs6NvOdRW1FqWV9Z+Kap1s57Pbl/OKVnu0wxtRU8K1jGrnr5Gb2ryutVh6SJEmSJOWLAbMkqWyMG1HJ30ytyxn7t2faWNXRc+VwIf3mtQ6O/tlyLnu8ZzuMAP7ygJHMnz2eT00eSYWrliVJkiRJg5gBsySprHx+eh2Nw7aGti0bE99YODCrmP/Utomz7l/JaXev5A8tm3psf+/Yau4/dSz/cmQjo2ucYiVJkiRJg5/vfiVJZaWxpoLzDxyVM/b959p4rb1wq5g3dCaufbqVw+Yu5+dLerbDaKqp4F+PbuTuk8cys3lYweqQJEmSJKnUGDBLksrOeVPqeFft1imsoxO+9mRLQX7Wg693cMzPl3Pp4y2s3dSzHcY5+9cy/7Rx/MV+tsOQJEmSJA09BsySpLIzoir44sz6nLEfLl7LH9ZszNvPeL29k3PuX8VH/3slL67p2Q7joOZq7jtlLN84ajRNwyvz9nMlSZIkSSonBsySpLL0ycm1TKrfGux2JrhyQesun3dDZ+JfF7Zy6O1vMnfJuh7bR9cE1x7VyL0nj+XgsbbDkCRJkiQNbQbMkqSyVF0RXHRQ7irmuUvW8eRbG/p9zt++sZ73/Xw5X5nfQvs22mGctV8t808bz9n7j6SywnYYkiRJkiQZMEuSytaf7T2CA5uqc8YuX9D3XsxvrO3k3AdX8ZG73uKFbbTDmDmmmntOGcs3jx7NGNthSJIkSZL0DgNmSVLZqohgzntzVzHf99p6Hnpj/U4dv3Fz4lvPtHLobW/y0z/2bIfROCy45shG7jtlLO+1HYYkSZIkST0YMEuSytoHd6/h6N1yw9/LHl9DSmk7R3SZt2w9x/58ORc/1kLbpp77njm5lvmzx/PpA2yHIUmSJEnS9hgwS5LKWkQw55DcVcyPrdjIr17t2Ob+y9Z28pkHV3HKr9/iudU922Ec2FTN3Sc382/HjKbZdhiSJEmSJO2QAbMkqewdNq6GWXsMzxm7fEELnZu3rkzetDnx7UVtHHr7m9yyjXYYDcOCq49o4P5Tx3LYuJqC1yxJkiRJ0mBgwCxJGhQuOaSe7EYWz6/e9E6Q/PCy9Rx7x3IufHQNrRt7tsP4831rmX/aeM6bUmc7DEmSJEmS+qCq2AVIkpQPU0dX84lJI/jxS1tXJ3/1iRYeeL2Dn7zUc8UywPSmar5+RANHjHfFsiRJkiRJ/eEKZknSoPHlg+qpzprZlrZ1bjNcrq8Orjq8gQdOHWu4LEmSJEnSLjBgliQNGhNHVXHO/iN3uM8Zk0Ywf/Z4Pju1jirbYUiSJEmStEsMmCVJg8oFM0YxsqpncDx1dBW/mtXMd49tYtyIyiJUJkmSJEnS4GPALEkaVMaNqOTCg+vfeT2qOvinwxr47UfGcdRutsOQJEmSJCmffMifJGnQ+ZupI5naWMXS9k5m7TGcsa5YliRJkiSpIAyYJUmDTkTwgQnDi12GJEmSJEmDni0yJEmSJEmSJEn9YsAsSZIkSZIkSeqXSCkVu4aSsWbNGn8ZkiRJkiRJkrQdDQ0Nkf3aFcySJEmSJEmSpH4xYJYkSZIkSZIk9YstMiRJkiRJkiRJ/eIKZkmSJEmSJElSvxgwS8qbiPhBRFxR7DokSYOHc4skKd+cWyQpv4ZcwBwRD0TEucWuQyon3jfSjnmPSH3nfSP1zvtE6hvvGal33icqhCEXMEuSJEmSJEmS8mPIBswRMToi7oyIFRHxdub7d2dtfyAiLo+I30VEa0TcHRHNxaxZKraIODsi5nUbSxGxb7FqkkqJc4vUd84tUu+cX6S+cW6ReufconwasgEzXdd+PTAR2BNYB3yr2z5/DpwDjAOGARcMZIGSpLLj3CJJKgTnF0lSvjm3KG+qil1AsaSUVgK3bXkdEVcC93fb7fqU0ouZ7bcAHxm4CiVJ5ca5RZJUCM4vkqR8c25RPg3ZgDkiaoFvACcBozPDoyKiMqXUmXm9LOuQtUDdAJYoSSozzi2SpEJwfpEk5Ztzi/JpKLfI+Htgf+DwlFI9cGxmPIpXklTy2oHaLS8iYrci1iKVIucWqe+cW6TeOb9IfePcIvXOuUV5M5QD5lF09ZdZHRFNwJwi1yOVg6eAaRExMyKGA5cWuR6p1Di3SH3n3CL1zvlF6hvnFql3zi3Km6EaMCfgWmAE8BbwP8BdRa1IKn0p03vpMuBeYDEwb8eHSEOKc4vUd84tUu+cX6S+cW6ReufcoryKlFKxaxhQEbEAuCyl9LNi1yKVC+8bace8R6S+876Reud9IvWN94zUO+8TFcKQWsEcEdOAKcATxa5FKhfeN9KOeY9Ifed9I/XO+0TqG+8ZqXfeJyqUIRMwR8RVwN3AF1NKrxS7HqkceN9IO+Y9IvWd943UO+8TqW+8Z6TeeZ+okIZciwxJkiRJkiRJUn4MmRXMkiRJkiRJkqT8MmCWJEmSJEmSJPXLoA2YI6ImIq6LiFciojUinoyIWVnbj4+I5yNibUTcHxETs7adHhEPZ7Y9sI1zV0bEFRHxeubcT0RE4wBdmiSpSAo1t0TE+yKirdtXiojZA3h5kqQiKPD7lg9GxIKIaImIP0bEZwbosiRJRVbg+eXUiHgm877l4YiYOkCXpRI1aANmoApYCrwfaAAuBm6JiL0iohm4HbgEaALmAz/JOnYVcC3wz9s59z8CRwFHAvXAmUBHAa5BklRaCjK3pJQeSinVbfkCTgHagLsKeTGSpJJQkLklIqqBucD3Muf9BHBNRMwo3KVIkkpIoeaXycDNwF8BjcAvgDsioqpwl6JSN6Qe8hcRT9MVDo8Bzk4pHZUZHwm8BRyUUno+a/9zgU+llI7LGhtN1w06I6X00gCWL0kqQfmYW7ZxzusBUkrnFLB0SVKJytP7lvHAMmBkSmltZuwx4JqU0o8G6lokSaUjT/PL54FZKaWTM68rgHbglJTSfQN1LSotg3kFc47M/2DtBywCpgFPbdmWUmoHXsqM9+Y9wCbgYxGxLCJejIjPFaBkSVKJy+Pckn3OkcDHgBvyV6kkqVzka25JKb0J/Ag4J9Pi70hgIjCvEHVLkkpbnt+7RLfvA5ien0pVjoZEwJz5eNjNwA2Zv8TUAWu67bYGGLUTp3s3XR8t2A/Ym64Q4NKI+FD+KpYklbo8zy3ZTqNr9cCDu1ykJKmsFGBu+RHwFWA98BBwUUppaZ7KlSSViTzPL/cC74+I4yJiGHAhMAyozWPJKjODPmDOLNW/CdgAfD4z3EZX7+Rs9UDrTpxyXebfy1JK61JKTwM/Bj6ch3IlSWWgAHNLtrOAG9NQ6mElScr73BIRB9D1PuUv6HrjPw34QkScnK+aJUmlL9/zSyagPgv4FvAG0Aw8C/wpTyWrDA3qgDkiArgOGA/MTiltzGxaBMzI2m8kMCkz3punM/9mv/E3BJCkIaJAc8uWY/YAjgNuzFe9kqTSV6C5ZTrwYkrpv1NKm1NKLwC/BGbltXhJUskq1HuXlNJPU0rTU0pjgDnAXsBjeSxdZWZQB8zAd4ApwKkppXVZ43OB6RExOyKG0/Wxsae3NDLP9CgbTtcTNysiYnjm4wRkHuz3EHBRRNRExBTgDODOgbssSVIR5X1uyXIm8LAPkZWkIacQc8sTwOSI+GB0mQScwtYFM5Kkwa8g710i4pDMPmOB/wDuyH44oIaeGKyfwI2IicASuvqNbcra9NmU0s0RcQJdy/knAr+n6+mZSzLHng1c3+2UN6SUzs5sn0DXX4COAZYDV6WUvleoa5EklYZCzi2ZfZ4Hrk4pXVegS5AklZgCv285na7QYCJdvTVvBr6cUtpcoMuRJJWIAs8v8+haAb0RuBU4P/OgQA1RgzZgliRJkiRJkiQV1mBvkSFJkiRJkiRJKhADZkmSJEmSJElSvxgwS5IkSZIkSZL6xYBZkiRJkiRJktQvBsySJEmSJEmSpH4xYJYkSZIkSZIk9YsBsyRJkjTAImLPiGiLiMpi1yJJkiTtCgNmSZIkaQBExJKIOAEgpfRqSqkupdRZ7LokSZKkXWHALEmSJEmSJEnqFwNmSZIkqcAi4iZgT+AXmdYYX4iIFBFVme0PRMQVEfFwZvsvImJMRNwcES0R8VhE7JV1vgMi4p6IWBURL0TE6cW5MkmSJA11BsySJElSgaWUzgReBU5NKdUBt2xjtzOAM4EJwCTgEeB6oAl4DpgDEBEjgXuA/wLGZY77dkRMLfBlSJIkST0YMEuSJEml4fqU0ksppTXAr4GXUkr3ppQ2AbcCB2X2OwVYklK6PqW0KaX0BHAb8PHilC1JkqShrKrYBUiSJEkC4M2s79dt43Vd5vuJwOERsTprexVwU2HLkyRJknoyYJYkSZIGRsrTeZYCD6aUPpSn80mSJEn9ZosMSZIkaWC8CeyTh/PcCewXEWdGRHXm69CImJKHc0uSJEl9YsAsSZIkDYx/Ai7OtLb4WH9PklJqBU6k6+F+rwPLgKuAmnwUKUmSJPVFpJSvT+pJkiRJkiRJkoYSVzBLkiRJkiRJkvrFgFmSJEmSJEmS1C8GzJIkSZIkSZKkfjFgliRJkiRJkiT1iwGzJEmSJEmSJKlfDJglSZIkSZIkSf1iwCxJkiRJkiRJ6hcDZkmSJEmSJElSvxgwS5IkSZIkSZL65X8BgenoPAthpK8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rcParams['figure.figsize'] = 20, 10\n",
    "\n",
    "# Decomposing to visualize and identify trend, seasonality and residual.\n",
    "# The graphs shows a opward going trend in the bitcoin market late 2016.\n",
    "# There is a possible seasonality pattern at the end of the year with a big increase in price with a following decrease.\n",
    "# Residual is noise. This is what there is left when removing trend and seasonal from the observed graph.\n",
    "decomposition = sm.tsa.seasonal_decompose(month_hist, model='additive')\n",
    "fig = decomposition.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Examples of parameter combinations for Seasonal ARIMA...\n",
      "SARIMAX: (0, 0, 1) x (0, 0, 1, 12)\n",
      "SARIMAX: (0, 0, 1) x (0, 1, 0, 12)\n",
      "SARIMAX: (0, 1, 0) x (0, 1, 1, 12)\n",
      "SARIMAX: (0, 1, 0) x (1, 0, 0, 12)\n"
     ]
    }
   ],
   "source": [
    "# ARIMA model (seasonal ARIMA, SARIMA)\n",
    "# 'p' is the number of autoregressive terms (AR part). It allows to incorporate the effect of past values into our model. Intuitively, this would be similar to stating that it is likely to be warm tomorrow if it has been warm the past 3 days.\n",
    "# 'd' is the number of nonseasonal differences needed for stationarity. Intuitively, this would be similar to stating that it is likely to be same temperature tomorrow if the difference in temperature in the last three days has been very small.\n",
    "# 'q' is the number of lagged forecast errors in the prediction equation (MA part). This allows us to set the error of our model as a linear combination of the error values observed at previous time points in the past.\n",
    "# These are the three integers (p, d, q) that are used to parametrize ARIMA models.\n",
    "p = d = q = range(0, 2)\n",
    "\n",
    "# pdq is an array of tuples. \n",
    "# Generating 2 arrays of tuples with examples of parameter combinations bewtween (0-1).\n",
    "pdq = list(itertools.product(p, d, q))\n",
    "seasonal_pdq = [(x[0], x[1], x[2], 12) for x in list(itertools.product(p, d, q))]\n",
    "\n",
    "print('Examples of parameter combinations for Seasonal ARIMA...')\n",
    "print('SARIMAX: {} x {}'.format(pdq[1], seasonal_pdq[1]))\n",
    "print('SARIMAX: {} x {}'.format(pdq[1], seasonal_pdq[2]))\n",
    "print('SARIMAX: {} x {}'.format(pdq[2], seasonal_pdq[3]))\n",
    "print('SARIMAX: {} x {}'.format(pdq[2], seasonal_pdq[4]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ARIMA(0, 0, 0)x(0, 0, 0, 12)12 - AIC:805.1859181916864\n",
      "ARIMA(0, 0, 0)x(0, 0, 1, 12)12 - AIC:986.4113863537838\n",
      "ARIMA(0, 0, 0)x(0, 1, 0, 12)12 - AIC:568.6390264096334\n",
      "ARIMA(0, 0, 0)x(1, 0, 0, 12)12 - AIC:586.3326658910003\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/tobiaskarentiuskromanndahl/test_jupyter/lib/python3.7/site-packages/statsmodels/base/model.py:508: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  \"Check mle_retvals\", ConvergenceWarning)\n",
      "/Users/tobiaskarentiuskromanndahl/test_jupyter/lib/python3.7/site-packages/statsmodels/base/model.py:508: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  \"Check mle_retvals\", ConvergenceWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ARIMA(0, 0, 0)x(1, 0, 1, 12)12 - AIC:1126.0216077968553\n",
      "ARIMA(0, 0, 0)x(1, 1, 0, 12)12 - AIC:346.00989270109847\n",
      "ARIMA(0, 0, 1)x(0, 0, 0, 12)12 - AIC:743.0161440705207\n",
      "ARIMA(0, 0, 1)x(0, 0, 1, 12)12 - AIC:nan\n",
      "ARIMA(0, 0, 1)x(0, 1, 0, 12)12 - AIC:531.351580913868\n",
      "ARIMA(0, 0, 1)x(1, 0, 0, 12)12 - AIC:558.4155607315777\n",
      "ARIMA(0, 0, 1)x(1, 0, 1, 12)12 - AIC:2235.594229226585\n",
      "ARIMA(0, 0, 1)x(1, 1, 0, 12)12 - AIC:325.84264114266466\n",
      "ARIMA(0, 1, 0)x(0, 0, 0, 12)12 - AIC:684.9061997058849\n",
      "ARIMA(0, 1, 0)x(0, 0, 1, 12)12 - AIC:877.5023684387545\n",
      "ARIMA(0, 1, 0)x(0, 1, 0, 12)12 - AIC:506.3150432852855\n",
      "ARIMA(0, 1, 0)x(1, 0, 0, 12)12 - AIC:502.462905775247\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/tobiaskarentiuskromanndahl/test_jupyter/lib/python3.7/site-packages/statsmodels/base/model.py:508: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  \"Check mle_retvals\", ConvergenceWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ARIMA(0, 1, 0)x(1, 0, 1, 12)12 - AIC:487.1958937587322\n",
      "ARIMA(0, 1, 0)x(1, 1, 0, 12)12 - AIC:274.7479083225138\n",
      "ARIMA(0, 1, 1)x(0, 0, 0, 12)12 - AIC:668.2037276852287\n",
      "ARIMA(0, 1, 1)x(0, 0, 1, 12)12 - AIC:2075.6322514959893\n",
      "ARIMA(0, 1, 1)x(0, 1, 0, 12)12 - AIC:488.76227686650844\n",
      "ARIMA(0, 1, 1)x(1, 0, 0, 12)12 - AIC:502.98660147135286\n",
      "ARIMA(0, 1, 1)x(1, 0, 1, 12)12 - AIC:470.70934910452627\n",
      "ARIMA(0, 1, 1)x(1, 1, 0, 12)12 - AIC:274.95683464941095\n",
      "ARIMA(1, 0, 0)x(0, 0, 0, 12)12 - AIC:703.2450639710698\n",
      "ARIMA(1, 0, 0)x(0, 0, 1, 12)12 - AIC:1220.2182571452104\n",
      "ARIMA(1, 0, 0)x(0, 1, 0, 12)12 - AIC:524.5396547414839\n",
      "ARIMA(1, 0, 0)x(1, 0, 0, 12)12 - AIC:506.06561474690375\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/tobiaskarentiuskromanndahl/test_jupyter/lib/python3.7/site-packages/statsmodels/base/model.py:508: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  \"Check mle_retvals\", ConvergenceWarning)\n",
      "/Users/tobiaskarentiuskromanndahl/test_jupyter/lib/python3.7/site-packages/statsmodels/base/model.py:508: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  \"Check mle_retvals\", ConvergenceWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ARIMA(1, 0, 0)x(1, 0, 1, 12)12 - AIC:1347.5678062244335\n",
      "ARIMA(1, 0, 0)x(1, 1, 0, 12)12 - AIC:271.5940214010443\n",
      "ARIMA(1, 0, 1)x(0, 0, 0, 12)12 - AIC:686.2740704891625\n",
      "ARIMA(1, 0, 1)x(0, 0, 1, 12)12 - AIC:440596568.145677\n",
      "ARIMA(1, 0, 1)x(0, 1, 0, 12)12 - AIC:506.1920800170881\n",
      "ARIMA(1, 0, 1)x(1, 0, 0, 12)12 - AIC:505.8776557519503\n",
      "ARIMA(1, 0, 1)x(1, 0, 1, 12)12 - AIC:2185.7654804762947\n",
      "ARIMA(1, 0, 1)x(1, 1, 0, 12)12 - AIC:263.6275083898073\n",
      "ARIMA(1, 1, 0)x(0, 0, 0, 12)12 - AIC:685.1819389380711\n",
      "ARIMA(1, 1, 0)x(0, 0, 1, 12)12 - AIC:1013.6393233537764\n",
      "ARIMA(1, 1, 0)x(0, 1, 0, 12)12 - AIC:506.81157475082335\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/tobiaskarentiuskromanndahl/test_jupyter/lib/python3.7/site-packages/statsmodels/base/model.py:508: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  \"Check mle_retvals\", ConvergenceWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ARIMA(1, 1, 0)x(1, 0, 0, 12)12 - AIC:486.61320307335535\n",
      "ARIMA(1, 1, 0)x(1, 0, 1, 12)12 - AIC:488.36172061685136\n",
      "ARIMA(1, 1, 0)x(1, 1, 0, 12)12 - AIC:247.2840947617646\n",
      "ARIMA(1, 1, 1)x(0, 0, 0, 12)12 - AIC:670.0626080633131\n",
      "ARIMA(1, 1, 1)x(0, 0, 1, 12)12 - AIC:2076.345696661325\n",
      "ARIMA(1, 1, 1)x(0, 1, 0, 12)12 - AIC:490.6662525832451\n",
      "ARIMA(1, 1, 1)x(1, 0, 0, 12)12 - AIC:487.6554916853118\n",
      "ARIMA(1, 1, 1)x(1, 0, 1, 12)12 - AIC:472.5858894795634\n",
      "ARIMA(1, 1, 1)x(1, 1, 0, 12)12 - AIC:248.4966198476736\n"
     ]
    }
   ],
   "source": [
    "# We are trying to find the combination with the lowest AIC(an estimator to realative quaility of statistical models for a given set of data).\n",
    "for param in pdq:\n",
    "    for param_seasonal in seasonal_pdq:\n",
    "        # Try since not all combinations makes sense, some will throw an error.\n",
    "        try:\n",
    "            # Using Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors model(SARIMAX).\n",
    "            # eXogenous argument is not given, which makes it a SARIMA model.\n",
    "            model = sm.tsa.statespace.SARIMAX(month_hist,\n",
    "                                            order=param,\n",
    "                                            seasonal_order=param_seasonal,\n",
    "                                            enforce_stationarity=False,\n",
    "                                            enforce_invertibility=False)\n",
    "\n",
    "            results = model.fit()\n",
    "\n",
    "            print('ARIMA{}x{}12 - AIC:{}'.format(param, param_seasonal, results.aic))\n",
    "        # If we come across an invalid combination, just skip it and continue.\n",
    "        except:\n",
    "            continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                 Statespace Model Results                                 \n",
      "==========================================================================================\n",
      "Dep. Variable:                     Weighted_Price   No. Observations:                   41\n",
      "Model:             SARIMAX(1, 1, 0)x(1, 1, 0, 12)   Log Likelihood                -120.642\n",
      "Date:                            Tue, 28 May 2019   AIC                            247.284\n",
      "Time:                                    23:43:02   BIC                            249.408\n",
      "Sample:                                01-01-2016   HQIC                           247.261\n",
      "                                     - 05-01-2019                                         \n",
      "Covariance Type:                              opg                                         \n",
      "==========================================================================================\n"
     ]
    }
   ],
   "source": [
    "# After trying our diffrent fits for our model, we pick the one with the lowest AIC.\n",
    "# This what is supposed to make our model the most precise.\n",
    "# Here we insert the order we find above.\n",
    "model = sm.tsa.statespace.SARIMAX(month_hist,\n",
    "                                order=(1, 1, 0),\n",
    "                                seasonal_order=(1, 1, 0, 12),\n",
    "                                enforce_stationarity=False,\n",
    "                                enforce_invertibility=False)\n",
    "\n",
    "results = model.fit()\n",
    "\n",
    "print(results.summary().tables[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting model diagnostics to investigate unusual behavior.\n",
    "# If the graph shows unusual behavior, it is a good sign of need for model improvement.\n",
    "\n",
    "# Top-right shows a plot of standard notation for a normal distribution, N(0,1).\n",
    "# Our model is indicated by the red line, KDE.\n",
    "# This shows an overall normally distributed residuals.\n",
    "\n",
    "# Bottom-left shows a plot of how residuals are distributed when following a trend. The red line shows a normal distribution.\n",
    "# Blue dots idicate our model, which has very few outliers from the normal distribution.\n",
    "# This is overall a pretty good result.\n",
    "\n",
    "# Bottom-right shows a correlogram which plots the autocorrelation, which shows how residuals have correlation to lagged versions of itself.\n",
    "# This result is not totally clear to us, so we can not draw any conclusion from it.\n",
    "# However, it seems like there appear to be no correlation.\n",
    "\n",
    "# Top-left shows residuals over time. In this case, 1 year and 2 months.\n",
    "# The standardized residual seems to be white noise - it is hard to find any seasonality from the diagram.\n",
    "\n",
    "results.plot_diagnostics(figsize=(16, 8))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Making a prediction from 1. Janurary 2017 to now, so we can compare the result with the actual observed graph.\n",
    "pred = results.get_prediction(start=('2017-01-01'), dynamic=False)\n",
    "\n",
    "\n",
    "# Plotting the observed graph and the 'one-step forecasting',\n",
    "ax = month_hist.plot(label='observed')\n",
    "pred.predicted_mean.plot(ax=ax, label='One-step ahead Forecast', alpha=.7, figsize=(14, 7))\n",
    "\n",
    "# Plotting the confidence interval on the forecast.\n",
    "# This is the interval of the forecasts highst and lowest predicted price.\n",
    "# The plotted line is the mean in the confidence interval.\n",
    "pred_ci = pred.conf_int()\n",
    "ax.fill_between(pred_ci.index,\n",
    "                pred_ci.iloc[:, 0],\n",
    "                pred_ci.iloc[:, 1], color='k', alpha=.2)\n",
    "\n",
    "ax.set_xlabel('Date')\n",
    "ax.set_ylabel('Bitcoin price')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            lower Weighted_Price  upper Weighted_Price\n",
      "time                                                  \n",
      "2017-01-01          -2112.253296           3976.896228\n",
      "2017-02-01          -1479.261216           3277.082756\n",
      "2017-03-01          -1311.057539           3442.766873\n",
      "2017-04-01          -1240.836640           3512.985659\n",
      "2017-05-01          -1162.967244           3590.855048\n",
      "2017-06-01           -434.147911           4319.674381\n",
      "2017-07-01            284.842960           5038.665252\n",
      "2017-08-01            111.192676           4865.014968\n",
      "2017-09-01           1539.396543           6293.218835\n",
      "2017-10-01           1734.734859           6488.557150\n",
      "2017-11-01           3010.712399           7764.534559\n",
      "2017-12-01           5489.870674          10243.553035\n",
      "2018-01-01          13045.655140          17867.591274\n",
      "2018-02-01          11366.489931          14323.333937\n",
      "2018-03-01           7639.009159          10590.123241\n",
      "2018-04-01           7538.891487          10490.005569\n",
      "2018-05-01           6346.375604           9297.489686\n",
      "2018-06-01           7075.846003          10026.960085\n",
      "2018-07-01           5232.572021           8183.686103\n",
      "2018-08-01           5257.670936           8208.785018\n",
      "2018-09-01           5202.294275           8153.408357\n",
      "2018-10-01           4898.207155           7849.321237\n",
      "2018-11-01           4597.711371           7548.825453\n",
      "2018-12-01           2467.951808           5419.065889\n",
      "2019-01-01           2757.117381           5708.231463\n",
      "2019-02-01           3135.840722           6086.954804\n",
      "2019-03-01           2299.859076           5250.973158\n",
      "2019-04-01           2792.997415           5744.111497\n",
      "2019-05-01           4451.475448           7402.589530\n"
     ]
    }
   ],
   "source": [
    "# This is the confidence interval.\n",
    "# It shows the difference between lower and upper values of predicted weighted price over time.\n",
    "print(pred_ci)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean absolute error 982.5591385143393\n"
     ]
    }
   ],
   "source": [
    "# Calculating the mean absolute error.\n",
    "y_forecasted = pred.predicted_mean\n",
    "y_truth = month_hist['2017-01-01':]\n",
    "\n",
    "# Sklearn method takes the actual value and the predicted value as parameters.\n",
    "# The mean absolute error is the mean difference between predicted and actual value\n",
    "mae = mean_absolute_error(y_truth, y_forecasted)\n",
    "print('Mean absolute error',mae)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Future prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# We generate a forecast for the furture graph of Bitcoin.\n",
    "# We call the method get_forecast which takes a parameter 'steps', as how many steps into the future do we want to forecast.\n",
    "future_pred = results.get_forecast(steps=10)\n",
    "\n",
    "# We plot the observed graph of Bitcoin prices.\n",
    "ax = month_hist.plot(label='observed', figsize=(20, 15))\n",
    "future_pred.predicted_mean.plot(ax=ax, label='Forecast')\n",
    "\n",
    "# Plotting the confidence interval on the forecast.\n",
    "# This is the interval of the forecasts higest and lowest predicted price.\n",
    "# The plotted line is the mean in the confidence interval.\n",
    "pred_ci = future_pred.conf_int()\n",
    "ax.fill_between(pred_ci.index,\n",
    "                pred_ci.iloc[:, 0],\n",
    "                pred_ci.iloc[:, 1], color='k', alpha=.25)\n",
    "\n",
    "ax.set_xlabel('Date')\n",
    "ax.set_ylabel('Bitcoin price')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2019-06-01     8496.289795\n",
       "2019-07-01     8306.690416\n",
       "2019-08-01    10008.936421\n",
       "2019-09-01    10335.456789\n",
       "2019-10-01    11841.406153\n",
       "2019-11-01    15010.714245\n",
       "2019-12-01    24106.929175\n",
       "2020-01-01    21740.639102\n",
       "2020-02-01    17419.774819\n",
       "2020-03-01    16932.809533\n",
       "Freq: MS, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Plotting the result in USD\n",
    "future_pred.predicted_mean"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "The model does seem to capture the trends and seasonality in the Bitcoin price. However, this also means that in the future it will predict the price to rise dramatically, like it did at some point in the training set. It is difficult to tell whether or not the results are true, because they are predictions of the future."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "attachments": {
    "RNN.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# RNN LSTM Prediction\n",
    "A **reccurent network** is networks with loops in them.\n",
    "A loop allows information to be passed from on node in a network to another.\n",
    "The image below illustrates a recurrent network. The loop to left is equal to the illustration of a loop on the right.\n",
    "The network takes an input but also the output from the previous nodes as input to the current step.\n",
    "\n",
    "![RNN.png](attachment:RNN.png)\n",
    "\n",
    "\n",
    "The idea behind the recurrent network is that it creates a kind of memory, which remembers all information about what has been calculated.\n",
    "\n",
    "The **long-short term memory** comes into place as a hidden layer in the network. It's purpose is to enable RNN to remember inputs over a long period of time. The LSTM network has 3 gates. \n",
    "* Input gate, decides what is relevant to add from the current step.\n",
    "* Forget gate, decides what is relevant to keep from prior steps and deletes information if it isn't important.\n",
    "* Output gate, determines what the next hidden state should be.\n",
    "\n",
    "With the above gates the model output the information to the next node & layer using Sigmoid and tanh layers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1113.4375]\n",
      "Length of the new datframe : 2001\n",
      "[[0.05196624]\n",
      " [0.04434619]\n",
      " [0.03316076]\n",
      " [0.03275506]\n",
      " [0.03938658]]\n"
     ]
    }
   ],
   "source": [
    "# Reshaping numpy.ndarray from 1D array to 2D array\n",
    "values = hist['Weighted_Price'].values.reshape(-1,1)\n",
    "print(values[0])\n",
    "# Converting the values to float.\n",
    "values = values.astype('float32')\n",
    "# Transform values to values between 0 and 1.\n",
    "# This is the type of input LSTM takes.\n",
    "scaler = MinMaxScaler(feature_range=(0, 1))\n",
    "# Fit to data, then transform it.\n",
    "scaled = scaler.fit_transform(values)\n",
    "\n",
    "# Get the length of the new item scaled\n",
    "print(\"Length of the new datframe : \" + str(len(scaled)))\n",
    "\n",
    "# Get the first 5 elements from the scaled dataframe\n",
    "print(scaled[0:5,])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Size : 1600\n",
      "Test Size : 801\n",
      "Length of training data : 1600\n",
      "Length of testing data : 801\n"
     ]
    }
   ],
   "source": [
    "# Divide scaled data into 80% train and 40% test with overlapping.\n",
    "train_size = int(len(scaled) * 0.8)\n",
    "print(\"Train Size : \" + str(train_size))\n",
    "\n",
    "test_size = int(len(scaled) * 0.6)\n",
    "print(\"Test Size : \" + str(len(scaled) - test_size))\n",
    "\n",
    "train, test = scaled[:train_size,:], scaled[test_size:len(scaled),:]\n",
    "print(\"Length of training data : \" + str(len(train)))\n",
    "print(\"Length of testing data : \" + str(len(test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function for creating dataset with look back (y refers to previous x)\n",
    "def create_dataset(dataset, look_back=1):\n",
    "    dataX, dataY = [], []\n",
    "    for i in range(len(dataset) - look_back):\n",
    "        # fx: \n",
    "        # 1st iteration - X:  [0.04680875] , Y:  0.051758032\n",
    "        # 2nd iteration - X:  [0.05175803] , Y:  0.05387902\n",
    "        a = dataset[i:(i + look_back), 0]\n",
    "        dataX.append(a)\n",
    "        dataY.append(dataset[i + look_back, 0])\n",
    "    return np.array(dataX), np.array(dataY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1599, 1)\n",
      "(1599,)\n",
      "(800, 1)\n",
      "(800,)\n"
     ]
    }
   ],
   "source": [
    "# Calling the create_dataset function with loop_back=1.\n",
    "look_back = 1\n",
    "trainX, trainY = create_dataset(train, look_back)\n",
    "testX, testY = create_dataset(test, look_back)\n",
    "\n",
    "print(trainX.shape)\n",
    "print(trainY.shape)\n",
    "print(testX.shape)\n",
    "print(testY.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1599, 1, 1)\n",
      "(800, 1, 1)\n"
     ]
    }
   ],
   "source": [
    "# Transform from 2D array to 3D array\n",
    "trainX = np.reshape(trainX, (trainX.shape[0], 1, trainX.shape[1]))\n",
    "testX = np.reshape(testX, (testX.shape[0], 1, testX.shape[1]))\n",
    "\n",
    "print(trainX.shape)\n",
    "print(testX.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /Users/tobiaskarentiuskromanndahl/test_jupyter/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Colocations handled automatically by placer.\n",
      "WARNING:tensorflow:From /Users/tobiaskarentiuskromanndahl/test_jupyter/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py:3445: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.\n",
      "WARNING:tensorflow:From /Users/tobiaskarentiuskromanndahl/test_jupyter/lib/python3.7/site-packages/tensorflow/python/ops/math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use tf.cast instead.\n",
      "Train on 1599 samples, validate on 800 samples\n",
      "Epoch 1/300\n",
      "1599/1599 [==============================] - 1s 552us/step - loss: 0.0819 - val_loss: 0.2712\n",
      "Epoch 2/300\n",
      "1599/1599 [==============================] - 0s 47us/step - loss: 0.0803 - val_loss: 0.2628\n",
      "Epoch 3/300\n",
      "1599/1599 [==============================] - 0s 47us/step - loss: 0.0767 - val_loss: 0.2575\n",
      "Epoch 4/300\n",
      "1599/1599 [==============================] - 0s 50us/step - loss: 0.0721 - val_loss: 0.2423\n",
      "Epoch 5/300\n",
      "1599/1599 [==============================] - 0s 48us/step - loss: 0.0700 - val_loss: 0.2315\n",
      "Epoch 6/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0665 - val_loss: 0.2203\n",
      "Epoch 7/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0628 - val_loss: 0.2068\n",
      "Epoch 8/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0592 - val_loss: 0.1929\n",
      "Epoch 9/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0546 - val_loss: 0.1762\n",
      "Epoch 10/300\n",
      "1599/1599 [==============================] - 0s 49us/step - loss: 0.0500 - val_loss: 0.1590\n",
      "Epoch 11/300\n",
      "1599/1599 [==============================] - 0s 52us/step - loss: 0.0450 - val_loss: 0.1404\n",
      "Epoch 12/300\n",
      "1599/1599 [==============================] - 0s 48us/step - loss: 0.0388 - val_loss: 0.1184\n",
      "Epoch 13/300\n",
      "1599/1599 [==============================] - 0s 39us/step - loss: 0.0322 - val_loss: 0.0934\n",
      "Epoch 14/300\n",
      "1599/1599 [==============================] - 0s 47us/step - loss: 0.0252 - val_loss: 0.0649\n",
      "Epoch 15/300\n",
      "1599/1599 [==============================] - 0s 49us/step - loss: 0.0173 - val_loss: 0.0357\n",
      "Epoch 16/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0097 - val_loss: 0.0095\n",
      "Epoch 17/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0088 - val_loss: 0.0126\n",
      "Epoch 18/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0077 - val_loss: 0.0102\n",
      "Epoch 19/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0098 - val_loss: 0.0091\n",
      "Epoch 20/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0114 - val_loss: 0.0103\n",
      "Epoch 21/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0063 - val_loss: 0.0092\n",
      "Epoch 22/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0063 - val_loss: 0.0097\n",
      "Epoch 23/300\n",
      "1599/1599 [==============================] - 0s 47us/step - loss: 0.0063 - val_loss: 0.0092\n",
      "Epoch 24/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0091 - val_loss: 0.0091\n",
      "Epoch 25/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0099 - val_loss: 0.0088\n",
      "Epoch 26/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0073 - val_loss: 0.0102\n",
      "Epoch 27/300\n",
      "1599/1599 [==============================] - 0s 51us/step - loss: 0.0077 - val_loss: 0.0098\n",
      "Epoch 28/300\n",
      "1599/1599 [==============================] - 0s 48us/step - loss: 0.0120 - val_loss: 0.0107\n",
      "Epoch 29/300\n",
      "1599/1599 [==============================] - 0s 47us/step - loss: 0.0066 - val_loss: 0.0108\n",
      "Epoch 30/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0068 - val_loss: 0.0089\n",
      "Epoch 31/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0090 - val_loss: 0.0092\n",
      "Epoch 32/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0098 - val_loss: 0.0088\n",
      "Epoch 33/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0060 - val_loss: 0.0087\n",
      "Epoch 34/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0060 - val_loss: 0.0104\n",
      "Epoch 35/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0062 - val_loss: 0.0092\n",
      "Epoch 36/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0073 - val_loss: 0.0097\n",
      "Epoch 37/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0113 - val_loss: 0.0104\n",
      "Epoch 38/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0064 - val_loss: 0.0100\n",
      "Epoch 39/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0057 - val_loss: 0.0089\n",
      "Epoch 40/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0078 - val_loss: 0.0095\n",
      "Epoch 41/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0095 - val_loss: 0.0087\n",
      "Epoch 42/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0069 - val_loss: 0.0100\n",
      "Epoch 43/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0088 - val_loss: 0.0089\n",
      "Epoch 44/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0090 - val_loss: 0.0086\n",
      "Epoch 45/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0064 - val_loss: 0.0089\n",
      "Epoch 46/300\n",
      "1599/1599 [==============================] - 0s 47us/step - loss: 0.0065 - val_loss: 0.0091\n",
      "Epoch 47/300\n",
      "1599/1599 [==============================] - 0s 47us/step - loss: 0.0100 - val_loss: 0.0090\n",
      "Epoch 48/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0075 - val_loss: 0.0106\n",
      "Epoch 49/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0061 - val_loss: 0.0090\n",
      "Epoch 50/300\n",
      "1599/1599 [==============================] - 0s 49us/step - loss: 0.0070 - val_loss: 0.0096\n",
      "Epoch 51/300\n",
      "1599/1599 [==============================] - 0s 49us/step - loss: 0.0100 - val_loss: 0.0098\n",
      "Epoch 52/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0070 - val_loss: 0.0106\n",
      "Epoch 53/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0084 - val_loss: 0.0092\n",
      "Epoch 54/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0090 - val_loss: 0.0086\n",
      "Epoch 55/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0080 - val_loss: 0.0110\n",
      "Epoch 56/300\n",
      "1599/1599 [==============================] - 0s 40us/step - loss: 0.0060 - val_loss: 0.0093\n",
      "Epoch 57/300\n",
      "1599/1599 [==============================] - 0s 40us/step - loss: 0.0060 - val_loss: 0.0088\n",
      "Epoch 58/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0081 - val_loss: 0.0093\n",
      "Epoch 59/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0099 - val_loss: 0.0091\n",
      "Epoch 60/300\n",
      "1599/1599 [==============================] - 0s 38us/step - loss: 0.0049 - val_loss: 0.0089\n",
      "Epoch 61/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0054 - val_loss: 0.0087\n",
      "Epoch 62/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0060 - val_loss: 0.0090\n",
      "Epoch 63/300\n",
      "1599/1599 [==============================] - 0s 40us/step - loss: 0.0069 - val_loss: 0.0099\n",
      "Epoch 64/300\n",
      "1599/1599 [==============================] - 0s 38us/step - loss: 0.0098 - val_loss: 0.0086\n",
      "Epoch 65/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0073 - val_loss: 0.0106\n",
      "Epoch 66/300\n",
      "1599/1599 [==============================] - 0s 38us/step - loss: 0.0071 - val_loss: 0.0093\n",
      "Epoch 67/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0106 - val_loss: 0.0090\n",
      "Epoch 68/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0057 - val_loss: 0.0093\n",
      "Epoch 69/300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0057 - val_loss: 0.0085\n",
      "Epoch 70/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0062 - val_loss: 0.0097\n",
      "Epoch 71/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0063 - val_loss: 0.0090\n",
      "Epoch 72/300\n",
      "1599/1599 [==============================] - 0s 39us/step - loss: 0.0083 - val_loss: 0.0090\n",
      "Epoch 73/300\n",
      "1599/1599 [==============================] - 0s 39us/step - loss: 0.0089 - val_loss: 0.0089\n",
      "Epoch 74/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0071 - val_loss: 0.0109\n",
      "Epoch 75/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0064 - val_loss: 0.0101\n",
      "Epoch 76/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0068 - val_loss: 0.0094\n",
      "Epoch 77/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0095 - val_loss: 0.0084\n",
      "Epoch 78/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0058 - val_loss: 0.0089\n",
      "Epoch 79/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0055 - val_loss: 0.0088\n",
      "Epoch 80/300\n",
      "1599/1599 [==============================] - 0s 38us/step - loss: 0.0082 - val_loss: 0.0094\n",
      "Epoch 81/300\n",
      "1599/1599 [==============================] - 0s 38us/step - loss: 0.0065 - val_loss: 0.0092\n",
      "Epoch 82/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0071 - val_loss: 0.0096\n",
      "Epoch 83/300\n",
      "1599/1599 [==============================] - 0s 40us/step - loss: 0.0099 - val_loss: 0.0086\n",
      "Epoch 84/300\n",
      "1599/1599 [==============================] - 0s 39us/step - loss: 0.0049 - val_loss: 0.0085\n",
      "Epoch 85/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0049 - val_loss: 0.0085\n",
      "Epoch 86/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0058 - val_loss: 0.0089\n",
      "Epoch 87/300\n",
      "1599/1599 [==============================] - 0s 40us/step - loss: 0.0049 - val_loss: 0.0085\n",
      "Epoch 88/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0060 - val_loss: 0.0087\n",
      "Epoch 89/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0053 - val_loss: 0.0086\n",
      "Epoch 90/300\n",
      "1599/1599 [==============================] - 0s 38us/step - loss: 0.0065 - val_loss: 0.0094\n",
      "Epoch 91/300\n",
      "1599/1599 [==============================] - 0s 37us/step - loss: 0.0082 - val_loss: 0.0096\n",
      "Epoch 92/300\n",
      "1599/1599 [==============================] - 0s 40us/step - loss: 0.0099 - val_loss: 0.0100\n",
      "Epoch 93/300\n",
      "1599/1599 [==============================] - 0s 39us/step - loss: 0.0056 - val_loss: 0.0091\n",
      "Epoch 94/300\n",
      "1599/1599 [==============================] - 0s 38us/step - loss: 0.0056 - val_loss: 0.0094\n",
      "Epoch 95/300\n",
      "1599/1599 [==============================] - 0s 40us/step - loss: 0.0076 - val_loss: 0.0106\n",
      "Epoch 96/300\n",
      "1599/1599 [==============================] - 0s 39us/step - loss: 0.0076 - val_loss: 0.0104\n",
      "Epoch 97/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0084 - val_loss: 0.0089\n",
      "Epoch 98/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0064 - val_loss: 0.0089\n",
      "Epoch 99/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0063 - val_loss: 0.0096\n",
      "Epoch 100/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0076 - val_loss: 0.0105\n",
      "Epoch 101/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0066 - val_loss: 0.0093\n",
      "Epoch 102/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0090 - val_loss: 0.0088\n",
      "Epoch 103/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0060 - val_loss: 0.0084\n",
      "Epoch 104/300\n",
      "1599/1599 [==============================] - 0s 39us/step - loss: 0.0057 - val_loss: 0.0103\n",
      "Epoch 105/300\n",
      "1599/1599 [==============================] - 0s 37us/step - loss: 0.0058 - val_loss: 0.0084\n",
      "Epoch 106/300\n",
      "1599/1599 [==============================] - 0s 38us/step - loss: 0.0048 - val_loss: 0.0084\n",
      "Epoch 107/300\n",
      "1599/1599 [==============================] - 0s 40us/step - loss: 0.0057 - val_loss: 0.0091\n",
      "Epoch 108/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0060 - val_loss: 0.0085\n",
      "Epoch 109/300\n",
      "1599/1599 [==============================] - 0s 38us/step - loss: 0.0057 - val_loss: 0.0086\n",
      "Epoch 110/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0052 - val_loss: 0.0085\n",
      "Epoch 111/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0052 - val_loss: 0.0085\n",
      "Epoch 112/300\n",
      "1599/1599 [==============================] - 0s 40us/step - loss: 0.0058 - val_loss: 0.0084\n",
      "Epoch 113/300\n",
      "1599/1599 [==============================] - 0s 40us/step - loss: 0.0052 - val_loss: 0.0085\n",
      "Epoch 114/300\n",
      "1599/1599 [==============================] - 0s 40us/step - loss: 0.0059 - val_loss: 0.0083\n",
      "Epoch 115/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0051 - val_loss: 0.0088\n",
      "Epoch 116/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0060 - val_loss: 0.0092\n",
      "Epoch 117/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0070 - val_loss: 0.0098\n",
      "Epoch 118/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0102 - val_loss: 0.0085\n",
      "Epoch 119/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0049 - val_loss: 0.0090\n",
      "Epoch 120/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0056 - val_loss: 0.0085\n",
      "Epoch 121/300\n",
      "1599/1599 [==============================] - 0s 40us/step - loss: 0.0060 - val_loss: 0.0088\n",
      "Epoch 122/300\n",
      "1599/1599 [==============================] - 0s 47us/step - loss: 0.0057 - val_loss: 0.0085\n",
      "Epoch 123/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0059 - val_loss: 0.0086\n",
      "Epoch 124/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0054 - val_loss: 0.0088\n",
      "Epoch 125/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0054 - val_loss: 0.0084\n",
      "Epoch 126/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0057 - val_loss: 0.0087\n",
      "Epoch 127/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0054 - val_loss: 0.0090\n",
      "Epoch 128/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0062 - val_loss: 0.0084\n",
      "Epoch 129/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0048 - val_loss: 0.0086\n",
      "Epoch 130/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0047 - val_loss: 0.0085\n",
      "Epoch 131/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0054 - val_loss: 0.0084\n",
      "Epoch 132/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0053 - val_loss: 0.0084\n",
      "Epoch 133/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0051 - val_loss: 0.0092\n",
      "Epoch 134/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0048 - val_loss: 0.0085\n",
      "Epoch 135/300\n",
      "1599/1599 [==============================] - 0s 39us/step - loss: 0.0053 - val_loss: 0.0086\n",
      "Epoch 136/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0052 - val_loss: 0.0087\n",
      "Epoch 137/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0055 - val_loss: 0.0089\n",
      "Epoch 138/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0073 - val_loss: 0.0096\n",
      "Epoch 139/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0075 - val_loss: 0.0098\n",
      "Epoch 140/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0100 - val_loss: 0.0093\n",
      "Epoch 141/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0049 - val_loss: 0.0084\n",
      "Epoch 142/300\n",
      "1599/1599 [==============================] - 0s 51us/step - loss: 0.0050 - val_loss: 0.0087\n",
      "Epoch 143/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0072 - val_loss: 0.0101\n",
      "Epoch 144/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0066 - val_loss: 0.0098\n",
      "Epoch 145/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0077 - val_loss: 0.0117\n",
      "Epoch 146/300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0070 - val_loss: 0.0098\n",
      "Epoch 147/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0085 - val_loss: 0.0100\n",
      "Epoch 148/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0068 - val_loss: 0.0097\n",
      "Epoch 149/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0061 - val_loss: 0.0093\n",
      "Epoch 150/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0098 - val_loss: 0.0123\n",
      "Epoch 151/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0061 - val_loss: 0.0087\n",
      "Epoch 152/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0051 - val_loss: 0.0087\n",
      "Epoch 153/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0055 - val_loss: 0.0089\n",
      "Epoch 154/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0047 - val_loss: 0.0085\n",
      "Epoch 155/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0054 - val_loss: 0.0084\n",
      "Epoch 156/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0046 - val_loss: 0.0086\n",
      "Epoch 157/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0051 - val_loss: 0.0085\n",
      "Epoch 158/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0062 - val_loss: 0.0085\n",
      "Epoch 159/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0052 - val_loss: 0.0086\n",
      "Epoch 160/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0062 - val_loss: 0.0085\n",
      "Epoch 161/300\n",
      "1599/1599 [==============================] - 0s 39us/step - loss: 0.0048 - val_loss: 0.0087\n",
      "Epoch 162/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0064 - val_loss: 0.0092\n",
      "Epoch 163/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0067 - val_loss: 0.0100\n",
      "Epoch 164/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0088 - val_loss: 0.0095\n",
      "Epoch 165/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0061 - val_loss: 0.0085\n",
      "Epoch 166/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0055 - val_loss: 0.0089\n",
      "Epoch 167/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0064 - val_loss: 0.0098\n",
      "Epoch 168/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0070 - val_loss: 0.0102\n",
      "Epoch 169/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0088 - val_loss: 0.0089\n",
      "Epoch 170/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0055 - val_loss: 0.0084\n",
      "Epoch 171/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0047 - val_loss: 0.0088\n",
      "Epoch 172/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0052 - val_loss: 0.0084\n",
      "Epoch 173/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0054 - val_loss: 0.0085\n",
      "Epoch 174/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0050 - val_loss: 0.0089\n",
      "Epoch 175/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0070 - val_loss: 0.0100\n",
      "Epoch 176/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0065 - val_loss: 0.0092\n",
      "Epoch 177/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0077 - val_loss: 0.0111\n",
      "Epoch 178/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0061 - val_loss: 0.0100\n",
      "Epoch 179/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0069 - val_loss: 0.0117\n",
      "Epoch 180/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0071 - val_loss: 0.0097\n",
      "Epoch 181/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0076 - val_loss: 0.0096\n",
      "Epoch 182/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0104 - val_loss: 0.0096\n",
      "Epoch 183/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0066 - val_loss: 0.0096\n",
      "Epoch 184/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0066 - val_loss: 0.0102\n",
      "Epoch 185/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0068 - val_loss: 0.0094\n",
      "Epoch 186/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0062 - val_loss: 0.0090\n",
      "Epoch 187/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0060 - val_loss: 0.0083\n",
      "Epoch 188/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0044 - val_loss: 0.0087\n",
      "Epoch 189/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0051 - val_loss: 0.0085\n",
      "Epoch 190/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0056 - val_loss: 0.0092\n",
      "Epoch 191/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0065 - val_loss: 0.0096\n",
      "Epoch 192/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0057 - val_loss: 0.0087\n",
      "Epoch 193/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0069 - val_loss: 0.0111\n",
      "Epoch 194/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0061 - val_loss: 0.0090\n",
      "Epoch 195/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0060 - val_loss: 0.0084\n",
      "Epoch 196/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0054 - val_loss: 0.0084\n",
      "Epoch 197/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0055 - val_loss: 0.0085\n",
      "Epoch 198/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0054 - val_loss: 0.0085\n",
      "Epoch 199/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0055 - val_loss: 0.0085\n",
      "Epoch 200/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0048 - val_loss: 0.0088\n",
      "Epoch 201/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0050 - val_loss: 0.0083\n",
      "Epoch 202/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0052 - val_loss: 0.0086\n",
      "Epoch 203/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0054 - val_loss: 0.0093\n",
      "Epoch 204/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0050 - val_loss: 0.0086\n",
      "Epoch 205/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0048 - val_loss: 0.0085\n",
      "Epoch 206/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0045 - val_loss: 0.0085\n",
      "Epoch 207/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0056 - val_loss: 0.0089\n",
      "Epoch 208/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0055 - val_loss: 0.0086\n",
      "Epoch 209/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0054 - val_loss: 0.0086\n",
      "Epoch 210/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0054 - val_loss: 0.0090\n",
      "Epoch 211/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0048 - val_loss: 0.0087\n",
      "Epoch 212/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0050 - val_loss: 0.0085\n",
      "Epoch 213/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0049 - val_loss: 0.0086\n",
      "Epoch 214/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0051 - val_loss: 0.0088\n",
      "Epoch 215/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0072 - val_loss: 0.0112\n",
      "Epoch 216/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0065 - val_loss: 0.0096\n",
      "Epoch 217/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0063 - val_loss: 0.0104\n",
      "Epoch 218/300\n",
      "1599/1599 [==============================] - 0s 40us/step - loss: 0.0066 - val_loss: 0.0097\n",
      "Epoch 219/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0081 - val_loss: 0.0099\n",
      "Epoch 220/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0055 - val_loss: 0.0084\n",
      "Epoch 221/300\n",
      "1599/1599 [==============================] - 0s 39us/step - loss: 0.0051 - val_loss: 0.0086\n",
      "Epoch 222/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0058 - val_loss: 0.0092\n",
      "Epoch 223/300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0055 - val_loss: 0.0083\n",
      "Epoch 224/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0050 - val_loss: 0.0083\n",
      "Epoch 225/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0047 - val_loss: 0.0083\n",
      "Epoch 226/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0048 - val_loss: 0.0084\n",
      "Epoch 227/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0058 - val_loss: 0.0086\n",
      "Epoch 228/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0057 - val_loss: 0.0089\n",
      "Epoch 229/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0061 - val_loss: 0.0086\n",
      "Epoch 230/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0046 - val_loss: 0.0086\n",
      "Epoch 231/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0057 - val_loss: 0.0086\n",
      "Epoch 232/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0055 - val_loss: 0.0087\n",
      "Epoch 233/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0057 - val_loss: 0.0091\n",
      "Epoch 234/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0055 - val_loss: 0.0086\n",
      "Epoch 235/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0044 - val_loss: 0.0085\n",
      "Epoch 236/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0049 - val_loss: 0.0084\n",
      "Epoch 237/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0055 - val_loss: 0.0085\n",
      "Epoch 238/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0049 - val_loss: 0.0087\n",
      "Epoch 239/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0057 - val_loss: 0.0087\n",
      "Epoch 240/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0053 - val_loss: 0.0092\n",
      "Epoch 241/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0065 - val_loss: 0.0090\n",
      "Epoch 242/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0054 - val_loss: 0.0094\n",
      "Epoch 243/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0075 - val_loss: 0.0114\n",
      "Epoch 244/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0050 - val_loss: 0.0091\n",
      "Epoch 245/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0054 - val_loss: 0.0089\n",
      "Epoch 246/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0054 - val_loss: 0.0084\n",
      "Epoch 247/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0048 - val_loss: 0.0088\n",
      "Epoch 248/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0047 - val_loss: 0.0089\n",
      "Epoch 249/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0055 - val_loss: 0.0084\n",
      "Epoch 250/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0052 - val_loss: 0.0091\n",
      "Epoch 251/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0072 - val_loss: 0.0088\n",
      "Epoch 252/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0074 - val_loss: 0.0115\n",
      "Epoch 253/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0078 - val_loss: 0.0124\n",
      "Epoch 254/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0056 - val_loss: 0.0097\n",
      "Epoch 255/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0079 - val_loss: 0.0103\n",
      "Epoch 256/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0050 - val_loss: 0.0096\n",
      "Epoch 257/300\n",
      "1599/1599 [==============================] - 0s 40us/step - loss: 0.0057 - val_loss: 0.0083\n",
      "Epoch 258/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0052 - val_loss: 0.0086\n",
      "Epoch 259/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0049 - val_loss: 0.0086\n",
      "Epoch 260/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0060 - val_loss: 0.0093\n",
      "Epoch 261/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0045 - val_loss: 0.0087\n",
      "Epoch 262/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0050 - val_loss: 0.0085\n",
      "Epoch 263/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0052 - val_loss: 0.0086\n",
      "Epoch 264/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0049 - val_loss: 0.0087\n",
      "Epoch 265/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0048 - val_loss: 0.0086\n",
      "Epoch 266/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0061 - val_loss: 0.0088\n",
      "Epoch 267/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0050 - val_loss: 0.0087\n",
      "Epoch 268/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0062 - val_loss: 0.0099\n",
      "Epoch 269/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0064 - val_loss: 0.0091\n",
      "Epoch 270/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0073 - val_loss: 0.0120\n",
      "Epoch 271/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0063 - val_loss: 0.0090\n",
      "Epoch 272/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0078 - val_loss: 0.0099\n",
      "Epoch 273/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0070 - val_loss: 0.0101\n",
      "Epoch 274/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0064 - val_loss: 0.0091\n",
      "Epoch 275/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0075 - val_loss: 0.0098\n",
      "Epoch 276/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0062 - val_loss: 0.0095\n",
      "Epoch 277/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0079 - val_loss: 0.0102\n",
      "Epoch 278/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0054 - val_loss: 0.0084\n",
      "Epoch 279/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0048 - val_loss: 0.0086\n",
      "Epoch 280/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0046 - val_loss: 0.0087\n",
      "Epoch 281/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0048 - val_loss: 0.0090\n",
      "Epoch 282/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0052 - val_loss: 0.0083\n",
      "Epoch 283/300\n",
      "1599/1599 [==============================] - 0s 46us/step - loss: 0.0050 - val_loss: 0.0088\n",
      "Epoch 284/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0048 - val_loss: 0.0091\n",
      "Epoch 285/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0052 - val_loss: 0.0083\n",
      "Epoch 286/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0051 - val_loss: 0.0094\n",
      "Epoch 287/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0057 - val_loss: 0.0087\n",
      "Epoch 288/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0065 - val_loss: 0.0094\n",
      "Epoch 289/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0062 - val_loss: 0.0095\n",
      "Epoch 290/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0085 - val_loss: 0.0136\n",
      "Epoch 291/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0052 - val_loss: 0.0086\n",
      "Epoch 292/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0061 - val_loss: 0.0106\n",
      "Epoch 293/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0062 - val_loss: 0.0084\n",
      "Epoch 294/300\n",
      "1599/1599 [==============================] - 0s 41us/step - loss: 0.0060 - val_loss: 0.0085\n",
      "Epoch 295/300\n",
      "1599/1599 [==============================] - 0s 43us/step - loss: 0.0057 - val_loss: 0.0086\n",
      "Epoch 296/300\n",
      "1599/1599 [==============================] - 0s 47us/step - loss: 0.0055 - val_loss: 0.0085\n",
      "Epoch 297/300\n",
      "1599/1599 [==============================] - 0s 45us/step - loss: 0.0057 - val_loss: 0.0085\n",
      "Epoch 298/300\n",
      "1599/1599 [==============================] - 0s 42us/step - loss: 0.0051 - val_loss: 0.0087\n",
      "Epoch 299/300\n",
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0065 - val_loss: 0.0104\n",
      "Epoch 300/300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1599/1599 [==============================] - 0s 44us/step - loss: 0.0064 - val_loss: 0.0094\n"
     ]
    }
   ],
   "source": [
    "# Initialise the sequential model\n",
    "model = Sequential()\n",
    "\n",
    "# Add the LSTM hidden layer with 128 nodes\n",
    "model.add(LSTM(128, input_shape=(trainX.shape[1], trainX.shape[2])))\n",
    "\n",
    "# Adding a dropout layer of 0.2 to prevent overfitting.\n",
    "model.add(Dropout(0.2))\n",
    "\n",
    "# Add the output layer\n",
    "model.add(Dense(1))\n",
    "\n",
    "# Compile the model with Mean Absolute Error as the loss factor and ADAM as the optimiser\n",
    "model.compile(loss='mae', optimizer='adam')\n",
    "\n",
    "# Fit the model using the training and testing data\n",
    "history = model.fit(trainX, trainY, epochs=300, batch_size=100, validation_data=(testX, testY), verbose=1, shuffle=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the training loss vs the test validation loss.\n",
    "plt.plot(history.history['loss'], label='train')\n",
    "plt.plot(history.history['val_loss'], label='test')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# We predict the values from testX.\n",
    "yhat = model.predict(testX)\n",
    "\n",
    "# Plotting the actual graph vs the predicted graph.\n",
    "plt.plot(yhat, label='predict')\n",
    "plt.plot(testY, label='true')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(800, 1)\n",
      "(800, 1)\n",
      "[1169.2621]\n",
      "[1033.165]\n"
     ]
    }
   ],
   "source": [
    "# scaler = MinMaxScaler(feature_range=(0, 1)) as used before for fit_transform and MinMaxScaler\n",
    "yhat_inverse = scaler.inverse_transform(yhat.reshape(-1, 1))\n",
    "testY_inverse = scaler.inverse_transform(testY.reshape(-1, 1))\n",
    "\n",
    "print(yhat_inverse.shape)\n",
    "print(testY_inverse.shape)\n",
    "\n",
    "print(yhat_inverse[0])\n",
    "print(testY_inverse[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean absolute error 180.22182\n"
     ]
    }
   ],
   "source": [
    "# Sklearn method takes the actual value and the predicted value as parameters.\n",
    "# The mean absolute error is the mean difference between predicted and actual value\n",
    "mae = mean_absolute_error(testY_inverse, yhat_inverse)\n",
    "print('Mean absolute error',mae)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting prediction vs actual graph.\n",
    "# This plotting shows the price.\n",
    "plt.plot(yhat_inverse, label='predict')\n",
    "plt.plot(testY_inverse, label='actual', alpha=0.5)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating a new variable containing the testX values.\n",
    "# Just for good measure.\n",
    "Xtest = testX\n",
    "\n",
    "# Predicting the values from Xtest and appending the last preicted value\n",
    "# to the set before predicting again\n",
    "for i in range(30):\n",
    "    future_preds = model.predict(Xtest) # Here yhat is the predicted value from the test set (y_pred)\n",
    "    \n",
    "    y = np.zeros((1,1,1))\n",
    "    y[[0]] = future_preds[len(future_preds)-1][0]\n",
    "    \n",
    "    Xtest = np.append(Xtest, y, axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "future_preds_inverse = scaler.inverse_transform(future_preds.reshape(-1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(future_preds_inverse, label='predict')\n",
    "plt.plot(testY_inverse, label='actual', alpha=0.5)\n",
    "\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Refferences\n",
    "* https://www.geeksforgeeks.org/introduction-to-recurrent-neural-network/ (28/05/2019)\n",
    "* https://colah.github.io/posts/2015-08-Understanding-LSTMs/ (28/05/2019)\n",
    "* https://towardsdatascience.com/recurrent-neural-networks-and-lstm-4b601dd822a5 (28/05/2019)\n",
    "* https://machinelearningmastery.com/sarima-for-time-series-forecasting-in-python/ (28/05/2019)\n",
    "* https://medium.com/fintechexplained/understanding-auto-regressive-model-arima-4bd463b7a1bb (28/05/2019)\n",
    "* https://towardsdatascience.com/arima-sarima-vs-lstm-with-ensemble-learning-insights-for-time-series-data-509a5d87f20a (28/05/2019)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusion\n",
    "\n",
    "By looking at the the plotted predictions compared to the actual values, and by looking at the mean absoluted error (MAE), it is very clear, that the best model on paper is our RNN LSTM model. The MAE of the SARIMA model is significantly higher than the one of the RNN LSTM model. However, the RNN LSTM model seems to have a random behaviour when predicting future values, which suggests the model is overfitted.\n",
    "\n",
    "With this in mind we will save the SARIMA model for future predictions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Saving the model\n",
    "results.save('SARIMA_btc_pred.pkl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Web app for predicting future prices\n",
    "\n",
    "At last we create a wep app for predicting future prices of Bitcoins based on number of months."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting aiwebflask.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile aiwebflask.py\n",
    "\n",
    "# Import libraries\n",
    "import numpy as np\n",
    "from sklearn.externals import joblib\n",
    "from flask import Flask, request, jsonify, render_template\n",
    "import pickle\n",
    "\n",
    "# create an instance (our app)\n",
    "app = Flask(__name__)\n",
    "\n",
    "results = joblib.load('SARIMA_btc_pred.pkl')\n",
    "\n",
    "@app.route('/', methods=['GET', 'POST'])\n",
    "def predict():\n",
    "    return render_template('prediction.html')\n",
    "\n",
    "@app.route('/predicted', methods=['GET', 'POST'])\n",
    "def predicted():\n",
    "    if request.method == 'POST':\n",
    "        months = int(request.form['months'])\n",
    "        predicted = results.get_forecast(steps=months).predicted_mean\n",
    "        \n",
    "        predicted = predicted[len(predicted)-1]\n",
    "\n",
    "        return render_template(\"predicted.html\", months=months, prediction=predicted)\n",
    "\n",
    "@app.route('/bye')\n",
    "def bye():\n",
    "    return render_template('bye.html')\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    app.run(debug=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * Serving Flask app \"aiwebflask\" (lazy loading)\n",
      " * Environment: production\n",
      "\u001b[31m   WARNING: This is a development server. Do not use it in a production deployment.\u001b[0m\n",
      "\u001b[2m   Use a production WSGI server instead.\u001b[0m\n",
      " * Debug mode: on\n",
      " * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)\n",
      " * Restarting with stat\n",
      " * Debugger is active!\n",
      " * Debugger PIN: 127-720-728\n",
      "127.0.0.1 - - [28/May/2019 23:31:41] \"\u001b[37mGET / HTTP/1.1\u001b[0m\" 200 -\n",
      "/Users/tobiaskarentiuskromanndahl/test_jupyter/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:320: FutureWarning: Creating a DatetimeIndex by passing range endpoints is deprecated.  Use `pandas.date_range` instead.\n",
      "  freq=base_index.freq)\n",
      "127.0.0.1 - - [28/May/2019 23:31:46] \"\u001b[37mPOST /predicted HTTP/1.1\u001b[0m\" 200 -\n",
      "127.0.0.1 - - [28/May/2019 23:31:48] \"\u001b[37mGET /?submit=make+another+prediction HTTP/1.1\u001b[0m\" 200 -\n",
      "127.0.0.1 - - [28/May/2019 23:31:52] \"\u001b[37mPOST /predicted HTTP/1.1\u001b[0m\" 200 -\n",
      "127.0.0.1 - - [28/May/2019 23:31:53] \"\u001b[37mGET /?submit=make+another+prediction HTTP/1.1\u001b[0m\" 200 -\n",
      "127.0.0.1 - - [28/May/2019 23:31:57] \"\u001b[37mPOST /predicted HTTP/1.1\u001b[0m\" 200 -\n",
      "127.0.0.1 - - [28/May/2019 23:32:00] \"\u001b[37mGET /?submit=make+another+prediction HTTP/1.1\u001b[0m\" 200 -\n",
      "^C\n"
     ]
    }
   ],
   "source": [
    "!python aiwebflask.py"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Final conclusion\n",
    "\n",
    "Both of these models are based on the assumption that future predictions of time series data is based on the past. This might make more sense when looking into sales or stock price where seasonal fluctuations are not as big. The RNN LSTM model is very well fittet and it might give good short term predictions, while the ARIMA model seems to provide better long term predictions.\n",
    "\n",
    "At last we can conclude that it is theoretically possible to predict Bitcoin prices based on time series data. However, the huge seasonal flunctuations makes it very difficult for the models to find a pattern. With that in mind you might consider using other methods than time series predictions like classification models based on datasets containing data like Google searches or website traffic."
   ]
  }
 ],
 "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": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}