05_GRU.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Classification using GRU"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting started\n",
    "\n",
    "Here is handled dependences and imported training/testing data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.metrics import f1_score\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.metrics import f1_score, accuracy_score\n",
    "\n",
    "from src.utils.viz import *\n",
    "\n",
    "plt.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read & split train test\n",
    "filename = './data/clean_entire_corpus.csv'\n",
    "df = pd.read_csv(filename)\n",
    "df_train = df[df['source'] == 'train'].copy()\n",
    "df_test = df[df['source'] == 'test'].copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Tokenize data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Encoding\n",
    "def get_vocabulary(iter_sents):\n",
    "    vocab = set()\n",
    "    max_length = 0\n",
    "    for text in iter_sents:\n",
    "        tokens = text.split(' ')\n",
    "        if len(tokens) > max_length:\n",
    "            max_length = len(tokens)\n",
    "        vocab.update(tokens)\n",
    "    return vocab, max_length\n",
    "\n",
    "vocab, max_length = get_vocabulary(df_train['clean_text'])\n",
    "\n",
    "tokenizer = tf.keras.preprocessing.text.Tokenizer()\n",
    "tokenizer.fit_on_texts(df_train['clean_text'])\n",
    "sequences_train = tokenizer.texts_to_sequences(df_train['clean_text'])\n",
    "sequences_test = tokenizer.texts_to_sequences(df_test['clean_text'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Padding data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Padding\n",
    "padded_seqs_train = tf.keras.preprocessing.sequence.pad_sequences(sequences_train, maxlen=max_length,\n",
    "                                                            padding='post', truncating='post')\n",
    "padded_seqs_test = tf.keras.preprocessing.sequence.pad_sequences(sequences_test, maxlen=max_length,\n",
    "                                                            padding='post', truncating='post')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Convert padded data to tf.data.Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data sets\n",
    "X_train = padded_seqs_train\n",
    "X_test = padded_seqs_test\n",
    "y_train = df_train['target'].values\n",
    "y_test = df_test['target'].values\n",
    "\n",
    "train_ds = tf.data.Dataset.from_tensor_slices((X_train, y_train)).shuffle(1000).batch(100)\n",
    "test_ds = tf.data.Dataset.from_tensor_slices((X_test, y_test)).batch(100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Import GloVe embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading lines\n",
      "Extract embeddings\n",
      "Create embeddings matrix\n"
     ]
    }
   ],
   "source": [
    "# Build an index for embeddings\n",
    "embeddings_index = {}\n",
    "EMBEDDINGS_PATH = '/datascience/embeddings'\n",
    "EMBEDDINGS_LENGTH = 50\n",
    "print('Reading lines')\n",
    "with open(os.path.join(EMBEDDINGS_PATH, 'glove.6B.50d.txt'), encoding='utf-8') as f:\n",
    "    lines = f.readlines()\n",
    "\n",
    "print('Extract embeddings')\n",
    "for line in lines:\n",
    "    values = line.split()\n",
    "    word = values[0]\n",
    "    coefs = np.asarray(values[1:], dtype='float32')\n",
    "    embeddings_index[word] = coefs\n",
    "\n",
    "print('Create embeddings matrix')\n",
    "word_index = tokenizer.word_index\n",
    "embedding_matrix = np.zeros((len(word_index) + 1, EMBEDDINGS_LENGTH))\n",
    "for word, i in word_index.items():\n",
    "    embedding_vector = embeddings_index.get(word)\n",
    "    if embedding_vector is not None:\n",
    "        # words not found in embedding index will be all-zeros.\n",
    "        embedding_matrix[i] = embedding_vector\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Training model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "69/69 [==============================] - 4s 54ms/step - loss: 0.6164 - acc: 0.6728 - val_loss: 0.5249 - val_acc: 0.7490\n",
      "Epoch 2/20\n",
      "69/69 [==============================] - 3s 44ms/step - loss: 0.4757 - acc: 0.7895 - val_loss: 0.4842 - val_acc: 0.7637\n",
      "Epoch 3/20\n",
      "69/69 [==============================] - 3s 43ms/step - loss: 0.4283 - acc: 0.8146 - val_loss: 0.4517 - val_acc: 0.7962\n",
      "Epoch 4/20\n",
      "69/69 [==============================] - 3s 43ms/step - loss: 0.4123 - acc: 0.8279 - val_loss: 0.4610 - val_acc: 0.7830\n",
      "Epoch 5/20\n",
      "69/69 [==============================] - 4s 61ms/step - loss: 0.3825 - acc: 0.8437 - val_loss: 0.4406 - val_acc: 0.8020\n",
      "Epoch 6/20\n",
      "69/69 [==============================] - 6s 92ms/step - loss: 0.3486 - acc: 0.8617 - val_loss: 0.4536 - val_acc: 0.8048\n",
      "Epoch 7/20\n",
      "69/69 [==============================] - 5s 74ms/step - loss: 0.3055 - acc: 0.8804 - val_loss: 0.4618 - val_acc: 0.8057\n",
      "Epoch 8/20\n",
      "69/69 [==============================] - 5s 70ms/step - loss: 0.2865 - acc: 0.8889 - val_loss: 0.5051 - val_acc: 0.8045\n",
      "Epoch 9/20\n",
      "69/69 [==============================] - 5s 79ms/step - loss: 0.2477 - acc: 0.9088 - val_loss: 0.6029 - val_acc: 0.7861\n",
      "Epoch 10/20\n",
      "69/69 [==============================] - 6s 82ms/step - loss: 0.2195 - acc: 0.9190 - val_loss: 0.6568 - val_acc: 0.7922\n",
      "Epoch 11/20\n",
      "69/69 [==============================] - 5s 75ms/step - loss: 0.1866 - acc: 0.9325 - val_loss: 0.7163 - val_acc: 0.7830\n",
      "Epoch 12/20\n",
      "69/69 [==============================] - 5s 71ms/step - loss: 0.1683 - acc: 0.9383 - val_loss: 0.7573 - val_acc: 0.7723\n",
      "Epoch 13/20\n",
      "69/69 [==============================] - 6s 88ms/step - loss: 0.1590 - acc: 0.9401 - val_loss: 0.8217 - val_acc: 0.7659\n",
      "Epoch 14/20\n",
      "69/69 [==============================] - 6s 93ms/step - loss: 0.1471 - acc: 0.9437 - val_loss: 0.9275 - val_acc: 0.7836\n",
      "Epoch 15/20\n",
      "69/69 [==============================] - 4s 60ms/step - loss: 0.1012 - acc: 0.9643 - val_loss: 0.9733 - val_acc: 0.7793\n",
      "Epoch 16/20\n",
      "69/69 [==============================] - 3s 47ms/step - loss: 0.0835 - acc: 0.9699 - val_loss: 1.1357 - val_acc: 0.7797\n",
      "Epoch 17/20\n",
      "69/69 [==============================] - 3s 42ms/step - loss: 0.0923 - acc: 0.9675 - val_loss: 0.9068 - val_acc: 0.7803\n",
      "Epoch 18/20\n",
      "69/69 [==============================] - 3s 42ms/step - loss: 0.0694 - acc: 0.9751 - val_loss: 1.1349 - val_acc: 0.7812\n",
      "Epoch 19/20\n",
      "69/69 [==============================] - 3s 42ms/step - loss: 0.0561 - acc: 0.9810 - val_loss: 1.1000 - val_acc: 0.7885\n",
      "Epoch 20/20\n",
      "69/69 [==============================] - 3s 41ms/step - loss: 0.0624 - acc: 0.9797 - val_loss: 0.9834 - val_acc: 0.7763\n"
     ]
    }
   ],
   "source": [
    "# Model\n",
    "model = tf.keras.Sequential()\n",
    "model.add(a := tf.keras.layers.Embedding(input_dim=len(word_index)+1, output_dim=EMBEDDINGS_LENGTH,\n",
    "                                         input_length=max_length, weights=[embedding_matrix], trainable=False))\n",
    "model.add(b := tf.keras.layers.GRU(128))\n",
    "# model.add(tf.keras.layers.Dropout(0.2))\n",
    "model.add(c := tf.keras.layers.Flatten())\n",
    "model.add(d := tf.keras.layers.Dense(64, activation='relu'))\n",
    "model.add(h := tf.keras.layers.Dense(1, activation='sigmoid'))\n",
    "\n",
    "optimizer = tf.keras.optimizers.Adam(learning_rate=0.005)\n",
    "model.compile(optimizer=optimizer, loss='binary_crossentropy', metrics=['acc'])\n",
    "\n",
    "EPOCHS = 20\n",
    "history = model.fit(train_ds, epochs=EPOCHS, validation_data=test_ds)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model's performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x27b2c596700>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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+d2FhUsXF/70/Kd+3uAB3c7OhF1/0aulSr15+2aNIxKGcHFPHHx/V8cdHdPjhMXl77rEgAAAAIEky2hoU/OwRRQqO3+MiOlJ4srI33Ch/1bNq7sLltZFolbdmmSJFUztFUdyWeaAaR9yn/A+mK+vT21NyYequgvIaAADskUjE0DvvZOj119uL6rfecisUar+QSJ8+CU2YENPYsXGNGxfX8OEJFRZ+/pHCZLK9yK6qcqiqyqnqaqcqKx2qrnaqurr9vg0bXKqpcaqt7asld3b25wX3f8/cLixMfulrc8dZ03V1Di1f3l5Yv/qqR/G4oaKipM48M6Ljj49o/Pi4MjLS970DAAAAOrvgZ4/ISIbUMvCaPX6OlZGraP4x8lU/p+bBN0iOrlk1emuXyWFGFCmaZneUHWL5kxTqc4GC5fMVy5ukWP4kuyPZomvOKAAAkHJ1dQ6tWePesQzIBx9kKJEwZBiWRoxIaOrUiMaNay+r+/RJfu2+nE6pVy9TvXqZGj169+vHmqbU2OjYUWx/Xna3/11V5dSaNW5VVzsVi3215A4GTRUUmNq61SnTNNSvX0Lnndeq44+P6LvfbZODi3YD3Uo3vnzPLvW01wsASB9HvF6B8vmK9jp5r9dYjhRNk6/2BXkaX1Us76jUBEwxX1WZEt5+imePtTvKTpoHz5an8TXlfHS1asa+KNOdb3ektKO8BgAAsixpy5bP16t+4w23Nm5sPzXZ47F00EFxzZwZ0rhxcX33u3Hl5KSmQHE4pLw8U3l5pkaN2n3JbVlSY6PxpYK7/euaGqdOOSWiE0+MaP/9E139ujEAvobD4VAikZDL1f1/rUkkEnLwDhwAIEUCn/1WRjKiloE/3uvnRvOPkenKlq+yrEuW145YpTwNryo04HLJ6GQ/a51eNYx8UL3eOlE5H1+j+tELuvyFMfdW9z/KAwAAX5FISB9+mLGjqP7v2cySlJNjasyYuM46q/3M6gMPjKf9worfxDCk3FxLubkJDR9udxoAdvF6vYpGo4rFYjJS8Iucx+NRLBbr8P3uLcuy5HA45GWBfgBACjjiNQqUL1CkaIoSgf32YQceRXqdJF/VQhmJVlmuQMeHTCFf1WIZMhXuREuGfFEiOFLNQ2Yre8NN8lf8UeE+59gdKa0orwEA6AHCYUNvv52hNWvcev11j956K0PhcPtZBf36JXTYYbEdS4Dst1+C5TUAdAmGYcj3ba7o+g0KCj5fux8AgO4quPVBGWZcLQOu3ud9RIpOV2D7k/LWLlOk+PQOTJd6/qpnFc88WEn/ELuj7FZrn/PlqXtZWRt/qXjORCUCQ+2OlDaU1wAAdGPPPefVI48E9cEHGUom29erHjkyoTPPjGjcuPYLLJaUmHbHBAAAAGADR6xSgfI/KlJ8upL+wfu8n3j2GCW8/eSrKutS5bUr9KEyWtepcehtdkf5eoZDjSN+pV5vlipn3WWqPeR5yeG2O1VaUF4DANANWZZ0//1B3XNPlkaNatNll32+XnVWFhf8AgAAACBlbpknKamWAVd9ux0ZDkWKpiq4ZZ4csUqZnuIOyZdq/qoyWYZL0cJT7Y7yjUxPkRqH36v8f5+nzE13q2XI9XZHSgs+FAwAQDcTj0s//nGO7rknS2ecEdaSJTX62c9aNGlSjOIaAAAAgCTJGS2Xf/v/U7j4LCV9/b/1/sJFU2XIlK96cQekSwMrKV/VYsXyJsl059mdZo/ECiartfd0BT/7rdwNr9odJy0orwEA6Eaamw2dc06+nn7ar2uuadZ99zXK3TM+TQYAAABgLwS3/FqSFBpwZYfsL+kfqnjmQfJXLeyQ/aWap+E1OeOVnfZCjbvTPPQmJXyDlbvuShltDXbHSTnKawAAuonycoemTi3QqlVu3Xdfg37845AMw+5UAAAAADobZ2SL/JV/Ubj3/yrp7dNh+40UTVNGaK1coY86bJ+p4qt6VqYzS9H8Y+2Oslcsp1+Nox6So61OOR//tH3NyG6M8hoAgG7g3/926ZRTemnbNqf+9Kc6nXlmxO5IAAAAADqpzC2/lgyXWgZc3qH7jRSeKktO+arKOnS/Hc1IhuWtWaZI4UmS02t3nL3WlnmAWgb9VL7apfJVPm13nJSivAYAoIt7+WWPpk4tkMNhafHiWh1+eNzuSAAAAAA6KWf4U/kqn1VryQ87/MKKpjtfsbyj2pcOscwO3XdH8tYsk8MMK9LFlgz5olC/mYrlTFT2+hvkDG+yO07KUF4DANCFPfmkXz/6UZ4GDkzq+edrNWJEwu5IAAAAADqxzC33yXK4Fep/WUr2Hy6eJme8Uu7GlSnZf0fwVZUp4emrePY4u6PsO8OhhhH3Sw63ctddLpltdidKCcprAAC6IMuS5s7N1E9/mqMjj4xp4cJaFRd33jMbAAAAANjP1bpevqpFau1znkx3r5SMEc2fLNMZlL+TLh3iiFXJ0/AvRYqmSkbXrkZNbx81Dpsrd8s7ytxyn91xUqJr/xcCAKAHisWkyy/P0bx5mTr77FYtWFCvYLB7X6QDAAAAwLeXufleWU6/WvtdkrpBnD5Fe50ob81SGcnOdy0eX/UiGTIVLu66S4Z8UbTwZIWLz1Jwyzy5G9+wO06Ho7wGAKALaWw0dPbZ+Vq0yK/rrmvWnXc2yeWyOxUAAACAzs4VWidfzfNq7XOBTHdeSscKF02TIxmSp3Z5SsfZF/7KMsUzD1LSP9TuKB2maegtSnr7K2fd5TISzXbH6VCU1wAAdBFbtzp16qkFeusttx56qEGzZoVkGHanAgAAANAVZG6+V6YzU6F+M1I+VjxngpKe3vJXPZvysfaGK7ROGa0fdukLNe6K5QqqYdQ8OWPblf3J9XbH6VCU1wAAdAHvvpuhk08uUG2tU3/+c52mTOl8H78DAAAA0DlltHwgX+0yhfpdLCsjJ/UDGg6FC6fKU/+KHPHa1I+3h/xVZbIMlyKFp9odpcO1ZR2iloFXy1+9UL6qhXbH6TCU1wAAdHLLl3t0+un58vksPfdcrcaPj9sdCQAAAEAXkrn5HpmuHLX2vTBtY0aKp8lQUr7q59I25teykvJVLVIs7yiZ7ny706REqP/limWNVfYns+WMfGZ3nA5BeQ0AQCf2xBN+XXBBnoYPT+j552s1dGjC7kgAAAAAupCM5rflrVuhUL+ZslxZaRs3ERiueHC0fFVlaRvz67gbXpMzXqlwN1syZCcOlxpHzpMk5ay7XDK7/u+PlNcAAHRCpindckuWrr8+R6WlUT3zTJ169TLtjgUAAACgi8ncdK+SGXlq7XN+2seOFE2Vu+U9uVo3pH3sL/NXlcl0Ziqaf6zdUVIq6eunpmG3y9O8RsGtD9od51tzpWugd999VwsWLJBpmjrmmGM0ZcqUnR4PhUL67W9/q6qqKmVkZOiSSy5R//79JUmXXXaZvF6vHA6HnE6n5s6dm67YAACkXSQiXXllrpYs8en880O6+eZmOZ12pwIAAADQ1bib1sjb8E81Df6FLFcg7eNHCqcoa+Nt8lWVqWXwz9I+/n8ZybC8NUvb17p2+mzLkS6Roqny1L2kzM2/UizvCLVlHWJ3pH2WlvLaNE3Nnz9fN9xwg/Lz83XddddpzJgx6tu3745tFi1apIEDB+raa69VeXm55s+frxtvvHHH4zfddJOystL30QYAAOxQX+/Quefm6e23M3TTTU266KJWGYbdqQAAAAB0RZmb7lYyo5fCfX5ky/imp0ix3CPkq16klkHXSoY9i0B4a1+QwwwrUtyNlwz5kqb95sjdtEa5H16umjF/l+UK2h1pn6RlxmzYsEHFxcUqKiqSy+XSxIkTtWbNmp222bZtmw444ABJUp8+fVRTU6PGxsZ0xAMAoFPYtMmpk08u0Nq1GXr44QZdfDHFNQAAAIB9425YKU/jawoNmCXLxrONI0VT5Yp+JnfTmm/eOEV8lWVKePoonn2obRnSzcrIVuPIB+SMblX2hhu/+QmdVFrOvK6vr1d+/udX8czPz9f69et32mbAgAF6/fXXNWLECG3YsEE1NTWqr69XTk6OJGnOnDmSpGOPPValpaW7HGfFihVasWKFJGnu3LkqKChIxcvZJZfLldbx0LMwv5BKzK/OYdUqQ9OmuWQY0t//ntD48UFJXfOd8f9ibgEAAAA2sSxlbr5bSXexWntPtzVKtNfxMj/xy1dVpnhO+stjR6xKnob/U6j/Zbad+W2XeM6hCg24XJlbfq1o3tGKFp5kd6S9lpby2rKsr9xnfOlUsilTpuiJJ57Qtddeq/79+2vQoEFyONon1K233qq8vDw1NTXptttuU0lJiUaNGvWVfZaWlu5UbNfW1nbwK9m9goKCtI6HnoX5hVRiftnvb3/z6oorctW7d1J/+lOdBg1Kqjv8J2FuIVVKSkrsjgAAANCpeRr+JU/TG2rcb47k9NqaxXL6Fe11vHzVz6tp6C1pz+OrXixDpiJFp6d13M6iZcDV8tT/n3I++Zmqsw6R6e1ax9JpebshPz9fdXV1O27X1dUpNzd3p238fr8uvfRS3X333Zo1a5aam5tVWFgoScrLy5MkZWdna+zYsdqwwf4rlAIA8G1ZlvTwwwHNnJmrAw5o0/PP12rQoKTdsQAAAAB0ZZalzE13KeHpo3DvH9idRpIUKZomR7JZ3voX0z62v6pM8czvKBEYmvaxOwVHhhpGzpPMuHI/ulKyTLsT7ZW0lNdDhgzR9u3bVV1drUQioZUrV2rMmDE7bdPa2qpEIiFJevHFFzVy5Ej5/X5Fo1FFIhFJUjQa1fvvv6/+/funIzYAACmTTEq/+EWWbrklWyecENVTT9UqL69rHUQAAAAA6Hw89S/J3fKOQgOulBweu+NIkmK5hynpLpKvsiyt47pCHykjtFaRop5zocZdSfoHqWm/W+VpXKnAZw/bHWevpGXZEKfTqfPPP19z5syRaZqaNGmS+vXrp+XLl0uSJk+erPLycj344INyOBzq27evZs6cKUlqamrSPffcI0lKJpM67LDDdNBBB6UjNgAAKREOG7rsshwtX+7TzJkhXX99sxw9a+k1AAAAAKlgWcrcdI8S3gEKF59pd5rPGU5FCqcoUP64jLZ6WRl5aRnWV1UmS05FCk9Ny3idWaT4LHnrXlTWpjsVzz1MbZkH2B1pjxjWrhak7iYqKirSNhbreiKVmF9IJeZXetXUOPSjH+Xpgw8ydOutTTr33LDdkVKGuYVUYc3rniudx/cS/x9DajG/kErMr57LW/OC8tZeoIYR9ymSgvL628wtV8u/VfjW99W43+0K9/lRByfbBSupolXj1BbcX/UH/iH143UBRluDCteUynQGVDvm77KcPrsj7bC7Y3zO8wIAIE3Wr3fp5JML9MknLs2fX9+ti2sAAAAAaWaZytx8jxK+wYoUTrU7zVckgvurLTBC/qr0LB3iblwpZ7xS4eKevWTIF1kZuWoY+Wu5Ip8qa+Mv7Y6zR9KybAgAAD1ZKGRo5Uq3rroqV263pbKyOn3nO212xwKAlPnNb36jt99+W9nZ2br33nu/8rhlWVqwYIHeeecdeTweXXrppRo8eLANSQEA6D68NUuU0bpODSMflBydsPIzDEWKpinr0zlyRjYr6RuY0uH8lWUynZmK5k9O6ThdTTz3MLX2m6ngZ79VNO9oxQo69/eHM68BAOgApilt2+bUK694NH9+QLNnZ+vMM/P13e8Wafjw3jrvvHwVFib1/PO1FNcAur2jjjpKs2fP3u3j77zzjiorK/XAAw/o4osv1mOPPZbGdAAAdENWUpmbf6U2/zBFCk+xO81uhQunyJIhX9XClI5jJCPy1i5VpNeJUidaGqOzaB50reLB0cr5+Bo5YlV2x/lanfBtGAAAOq/WVkOffurSxo0ubdjw+d+ffupUNPr5e8JZWaaGDEno8MNjGjIkoSFDEjriiJiCwW57qQkA2GHUqFGqrq7e7eNvvvmmjjjiCBmGoWHDhqm1tVUNDQ3Kzc1NY0oAALoPX/VflRH+RPWjficZTrvj7JbpLVE8Z6L8lWUKDbhaMoyUjOOtfUGOZKsiRZ1v+ZROweFR48gHVfDWccr56GrVH/gnyeic5zhTXgMA8CWWJVVUOLRxo2vHnw0bMrRxo1MVFRDHpLUAACAASURBVJ//6HQ4LPXrl9SQIQl973sxDR3aXlIPHZpQQYGZquMwAOjy6uvrVVBQsON2fn6+6uvrv1Jer1ixQitWrJAkzZ07d6fnpIPL5Ur7mOg5mF9IJeZXD2MmlPHm/TKzD1Bw5I8UTGEJ2RFzyzH0XLnevEi9HJ/Kyj+0g5LtzLXur7J8/ZQ19OROW8rarqBAZuJued+5XIWNf5G53+V2J9olymsAQI8ViRjauNH5pZLapU8/dSkc/vwAJxg0NXRoQuPHxzV0aHhHST1wYEJer40vAAC6KMv66qdQjF2841daWqrS0tIdt2tra1Oa68sKCgrSPiZ6DuYXUon51bP4Kp9WbmiDGvafr2hdfUrH6oi5ZXgPV7HDq/jH89U0bEgHJfucI1atoqoVCvW/VC0p/n50eVmnKS//r/K8f73qMw5SIjjStiglJSW7vJ/yGgDQ7UQihurrDTU0OL7yp7bWsWPZj23bPv8xaBiW+vZNaujQhA49NLzTWdSFhZxFDQAdKT8/f6dffOvq6lgyBACAfWG2KXPz/YoHD1C04Pt2p9kjlitTkYLvy1v9VzUNvVlyuDt0/77qxTJkKlI0rUP32y0ZhhqH36tea45R7rpZqjlkieTsXGdoUV4DADqtZFJqatp1Cb27P42NDkWju2+aMzNNDRqU0Nixcf3P/4R3FNSDBiXk4zoeAJAWY8aM0QsvvKDvfe97Wr9+vfx+P+U1AAD7wF/5jFzRLao74PcpWz86FSJFU+Wvfk6e+n8qVjC5Q/ftq1qoePAAJQLDOnS/3ZXpzlfjiPuU/8F0ZX16u5r3u8XuSDuhvAYApJVpSp984tL69a5vLKKbmgxZ1q4PwJxOSzk5pnJz2//065fQgQdaO27v6k9OjimPJ80vGAB6oPvvv18ffvihWlpaNHPmTJ155plKJBKSpMmTJ+vggw/W22+/rSuuuEJut1uXXnqpzYkBAOiCzJiCW+5XPPNgxfKOsTvNXonlHqlkRr78Vc92aHntav1E7tAHahpyc4ftsyeI5U9SqM8FCpbPVyxvkmL5k+yOtAPlNQAgpUxT+ugjl1at8mj1ardWr3arvn7nq1/7/V8smS317dv2tSV0bq6pzExLDq67AQCd0lVXXfW1jxuGoQsvvDBNaQAA6J782/8sV6xcdcPv6VJnXUuSHBmKFE5RoOJPMtqaZGVkd8hufVVlsuRUpGhKh+yvJ2kePFuexteU89HVqhn7okx3vt2RJFFeAwA6WDIprVvn0sqV7WX166971NjY3jL37ZvQMcfENGFCTKNHtyk/v72I5mxoAAAAANgLyagyt8xTLHucYrmH251mn0SKpipYPl++miUKl/zvt9+hZcpXtVCxvCNlunt9+/31NE6vGkY+qF5vnajgll93muVDKK8BAN9KIiGtXZuhVavcWrXKozfecKu5ub2sHjAgoeOOi2j8+LgmTIirb9+kzWkBAAAAoOsLbP+TnPFKNYyc1/XOuv6PtszvqM03RL6qsg4pr92Nq+SKVahl8PUdkK5nSgRHqu47TyqeebDdUXagvAYA7JW2NumDDzK0erVHq1a59cYbboVC7WX1oEEJnXRSRBMmxDV+fEwlJabNaQEAAACgezGSEQW3PKhYzkTFcyfaHWffGYYixdOUtekuOaPblPT2/Va781eVyXQGFS34fgcF7JniORPsjrATymsAwNeKx6X33msvq1evbi+rw+H2snro0DZNmfJ5WV1cTFkNAAAAACljJpS5+V4522rUMOhRu9N8a5HCqcradJd8VQsVGnDFPu/HSEbkrVmiaK8TZDl9HZgQdqO8BgDsJBaT3n3XrVWr3Fq92qM338xQJNJeVg8f3qYzzoho/PiYxo+Pq7CQshoAAAAAUs6y5Kl/SVkb5ygj/LHChVMUzx5rd6pvLenrp1j2ofJVlSnU//J9XgLFU7tcjmRI4aJpHZwQdqO8BoAeLhqVVq50a/Xq9jWr337brWi0/YBh5Mg2/eAHYY0fH9f48XHl51NWAwAAAEA6uVr+reyNt8rT+KoSvoGq3/9RRQuOtztWh4kUTVPOJz9VRugDtWUeuE/78Fc9q6Snt+I5XXgZFewS5TUA9FD//rdLd96Zpddey1AsViDDsDRqVELTp7dqwoS4xo2LKS/PsjsmAAAAAPRIjmj5f5bUKJPpylHT0FvVWjJdcrjtjtahIr1OVPb6G+SrfHafymtHvEae+lcU6jdTMhwpSAg7UV4DQA9TXe3QnXdm6i9/8Ssnx9TMmaYOOqhR48bFlZNDWQ0AAAAAdjISLQpufVDBbY9JlqVQv0sVGjBLlivL7mgpYWXkKJpfKl/1c2oecqPk2Lu60lf9nAwlFSlmyZDuiPIaAHqIaFR69NGg5s0LKh43dPHFrbryyhYNGZKv2tqY3fEAAAAAoGcz2+Tf/qQyN/9KzrY6hYumqmXQz5T09rU7WcpFik+Xr3apPA3/p1j+0Xv1XF9lmeLB0UoEhqcoHexEeQ0A3ZxlSc8/79WcOVnats2l446L6PrrmzV4cNLuaAAAAAAAy5K39u/K+nSOXJFPFcuZoPohN+7z+s9dUTRvkkxXjnxVZXtVXrta18sdel9NQ25KYTrYifIaALqxd9/N0M03Z2nNGo9GjWrT00/X6nvfi9sdCwAAAAAgKaP5HWVtvFWeptfV5h+qutFPKJZfKhmG3dHSy+FWpPAU+SqflpEIyXIF9+hpvqpnZcmhSOGUFAeEXSivAaAb2r7doTvuyFJZmV8FBUndfXejzjorLKfT7mQAAAAAAGdkqzI3zZW/+jklMwrUOGyuwsU/2Ov1nruTcNE0BSr+IG/tUkWKz/zmJ1imfFWLFMs7UqanMPUBYYue+y8CALqhSMTQ734X0EMPBZVMGpo1q0WzZoWUmcmFGAEAAADAbkZbozK3PKBA+QJZhkMtA65SqN8le3ymcXfWlvVdJbwD5a8s26Py2t24Wq5YuVoGX5eGdLAL5TUAdAOmKS1e7NPtt2dp+3anTjqpfV3r/v1Z1xoAAAAAbGfGFSj/vTK33C8j0aRw8VlqGfQTmZ7edifrPAxDkaKpCm65T47Y9m/83viqymQ6A4oWHJemgLAD5TUAdHFvvpmhm2/O1jvvuHXAAXE99FCDDj2Uda0BAAAAwHaWJW/N35T16R1yRbcomnukmodcr0Rwf7uTdUrhoqnK3PIr+aoWq7X/JbvfMBmRr2aJogUnyHL60hcQaUd5DQBdVHm5U7ffnqnFi/0qKkrqvvsadPrpETkcdicDAAAAALib1ihr4y1yN7+ttsBI1R34pGJ5R9kdq1NL+gcpnnWI/FVlX1tee+uWy5FsUbh4WhrTwQ6U1wDQxbS2GnrooaAefrh9TbSrrmrRpZeGFAiwrjUAAAAA2M0Z/lRZn94hX+1SJd3Fahh+ryLFZ0iG0+5oXUK4aJpy1l8vV+hDJYKjdrmNv7JMSXex4jkT05wO6UZ5DQBdhGlKzzzj0513ZqmqyqnTTgvruuta1KcP61oDAAAAgN0c8XoFt9ynQMUfZBluNQ/8iVr7zZDl9NsdrUuJFJ6i7A03yV9VpuZdlNeOeK089f9UqN8M3hDoASivAaALeP11t26+OUvvv+/WwQfH9cgj9Rozps3uWAAAAACAZFTB8scV3PKAjGSrwr3/Vy0Dr5HpKbQ7WZdkZeQpmne0fFWL1Tx49lcKal/1czKUVKSIJUN6AsprAOjEtm516rbbsrRkiU+9eyf14IMNOvVU1rUGAAAAANtZpnzVi5X56Vy5YuWK5peqefD1SgSG2Z2sy4sUTZOvbrncDa8pnnfETo/5qsrUFtxfieAIm9IhnSivAaATamkxNG9eUI8+GpTTaeknP2nWzJmt8vlY1xoAAAAA7GYkWpT//tlyN7+leHC0akf8SvHcw+yO1W1E80tlOrPkryrbqbx2tW6Qu+U9NQ250cZ0SCfKawDoRJJJ6amn/LrrrkzV1jp1+ulh/fznzerd27Q7GgAAAABAkixLOR/9WBnN76ph+K/+czFGPh7boZxeRQpPkq9qsYxhd+xYN9xX9awsORQpnGJzQKQL/7IAoJN49VW3vv/9XvrpT3M0aFBCS5bU6Ne/bqS4BgAAAIBOJPjZb+SrXarmIdcr0vssiusUiRRNk8MMy1v79/Y7LFO+qoWK5R4h01NkbzikDf+6AMBm772XofPPz9VZZxWopcXQ735Xr0WL6nTQQVyQEQAAAAA6E3fDv5T56VxFep2s1r4X2x2nW4tnj1PC01e+qjJJkrvpdbli5YoUc6HGnoRlQwDABm1t0rJlXs2fH9Sbb7oVDJq67rpmXXhhSF6v3ekAAAAAAF/mjJYr98NLlfAPVePweyXDsDtS92Y4FCk6TcGtD8kRq5avskymw69owXF2J0MaUV4DQBrV1xt68smAfv/7gLZvd2rgwIR++csmnXVWWJmZXIwRAAAAADolM6bctRfLMOOqH/2oLFfA7kQ9QqTodGVunSd/5V/kq/mbor1O2LH+NXoGymsASIN161x6/PGAFi70Kxo1dNhhMd1+e6OOOSYmp9PudAAAAACAr5O9/hdyt7yr+v0fU9I/1O44PUYiMFTxzO8oc8v9MsyowkUsGdLTUF4DQIokk9KKFV499lhAK1d65PWamjYtrAsuaNXw4Qm74wEAAAAA9oBv+1MKbH9SLf1nKdrreLvj9DiRoqlyb7hJSXex4rnfszsO0ozyGgA6WFOToaee8uuJJwLautWlkpKEZs9u1v/+b6tyc1kaBAAAAAC6ioyW95XzyWzFcg5Ty8Br7Y7TI0UKpyhr4+0KF58uGXx0uaehvAaADrJhg1MLFgT19NM+hcMOjRsX0/XXN+u446Jy8X9bAAAAAOhSjLZ65f77IiXd+WoY9RvJwS92djDdBaoe95KSnt52R4EN+FcHAN+CaUqvvOLR448H9NJLXrndlk45JaILL2zVAQe02R0PAAAAALAvrKRyP5wlZ7xatQcvkunOtztRj5b0DbQ7AmxCeQ0A+6C11dAzz/j0+OMBbdyYocLCpH7yk2ZNnx5Wr16m3fEAAAAAAN9C5qZ75G14RY3D7lJb1kF2xwF6LMprANgLW7c6tWBBQE895Vdzs0Pf+U5cDzzQoJNPjsjttjsdAAAAAODb8tQuV+bWB9Ra/AOFS862Ow7Qo1FeA8A3sCxp5Uq35s8PaPlyrxwO6cQTo7rggpC++902GYbdCQEAAAAAHcEZ/lS5665QPHigmva7ze44QI9HeQ0AuxGJSIsX+zV/fkDr1mUoNzepyy4L6Uc/alVJCUuDAAAAAEB3YiTDylt7kWQ41TD6UcnptTsS0ONRXgPAl1RUOPT73wf05JN+NTQ4NXJkm+65p1FTpoTl89mdDgAAAADQ4SxL2R9fK1frx6o/8EklvX3tTgRAlNcAsMMnn7h0332ZWrLEK9OUvv/9qM4/v1UTJ8ZZGgQAAAAAurFA+ePyVy9W86CfKZZ3pN1xAPwH5TUASFq+3KPLLsuV0yldcEGrzjuvVf37J+2OBQAAAABIMXfjG8raeIsi+ZMV6j/L7jgAvoDyGkCPZlnSww8HdNttWTrwwDY9/ni9iotZzxoAAAAAegJHrEq5H85Q0ttPjSN/LRkOuyMB+ALKawA9VjwuXXddtp56KqCTToro/vsb5fNZdscCAAAAAKSD2abctTNkJFpUd+CfZbmy7E4E4EsorwH0SPX1hi6+OE+rVnl01VUtuuaaFjl4gx0AAAAAeoysjbfK07xG9SN/o0RwhN1xAOwC5TWAHmfDBpd+9KM8bd/u1Lx5DZo6NWJ3JAAAAABAGvmqFilYPl+hvhcqWnSq3XEA7AblNYAe5f/+z60ZM/Lkdlt6+ulajRnTZnckAAAAAEAauULrlP3xtYplH6rmwTfYHQfA1+BD8gB6jN//3q/p0/NVUpLUkiUU1wAAAADQ0xhtTcpbe6EsV5YaRv1OcmTYHQnA1+DMawDdXiIh/fKXWXr88aCOOSaq3/ymQcEgF2YEAAAAgB7FMpX70ZVyRrep7qBnZXoK7U4E4Bukrbx+9913tWDBApmmqWOOOUZTpkzZ6fFQKKTf/va3qqqqUkZGhi655BL1799/j54LALvT3Gzo0ktz9fLLXl10UUi/+EWznE67UwEAAAAA0i24dZ68df9Q09BbFc8ea3ccAHsgLcuGmKap+fPna/bs2brvvvv02muvadu2bTtts2jRIg0cOFD33HOPZs2apSeeeGKPnwsAu7Jli1Onnlqgf/3Lo7vuatTNN1NcAwAAAEBP5Kn/pzI33a1w4Wlq7XOe3XEA7KG0lNcbNmxQcXGxioqK5HK5NHHiRK1Zs2anbbZt26YDDjhAktSnTx/V1NSosbFxj54LAF/2xhtunXRSgaqrnXryyTqdfXbY7kgAAAAAABs4I58p98PLlAiMUNPwuyTDsDsSgD2UlvK6vr5e+fn5O27n5+ervr5+p20GDBig119/XVJ72V1TU6P6+vo9ei4AfNEzz/h01ln5ysmx9Ne/1uiww+J2RwIAAAAA2CEZUe7aiyTLVP3+j8py+u1OBGAvpGXNa8v66oXRjC+9yzVlyhQ98cQTuvbaa9W/f38NGjRIDodjj577XytWrNCKFSskSXPnzlVBQUEHpN8zLpcrreOhZ2F+7RnTlG680am773bqqKNMPfWUqdzcXLtjdXrML6QKcwsAAAC2sizlrL9e7tAHqhv9hJL+QXYnArCX0lJe5+fnq66ubsfturq6rxRKfr9fl156qaT2snvWrFkqLCxUPB7/xuf+V2lpqUpLS3fcrq2t7ciX8bUKCgrSOh56FubXNwuHDV1xRY6WLXPr7LNbNWdOk5JJiW/bN2N+IVWYW0iVkpISuyMAAIAuwL/9Sfkr/6KWAVcpVnCs3XEA7IO0LBsyZMgQbd++XdXV1UokElq5cqXGjBmz0zatra1KJBKSpBdffFEjR46U3+/fo+cC6Nm2b3fotNPy9fe/e3XzzU26884mZWTYnQoAAAAAYJeM5neUvf4XiuYepZaBP7Y7DoB9lJYzr51Op84//3zNmTNHpmlq0qRJ6tevn5YvXy5Jmjx5ssrLy/Xggw/K4XCob9++mjlz5tc+FwAk6b33MnTeeXlqbTW0YEG9SktjdkcCAAAAANjIEa9T3tqLlPQUqWHUg5LhtDsSgH2UlvJakg455BAdcsghO903efLkHV8PGzZMDzzwwB4/FwD+9jevrrwyRwUFphYvrtPIkQm7IwEAAAAA7GQmlPvhJXK0Naj24MWyMrgOEtCVpWXZEADoSJYl/frXQc2Ykaf9909oyZJaimsAAAAAgDI33SVP42tq3O92tWUeYHccAN9S2s68BoCOEI1K116bo4UL/Zo6Nay7726U12t3KgAAAACA3bw1S5X52UNqLfmhIr3PsjsOgA5AeQ2gy6itdeiCC/L05ptu/fSnzbriipAMw+5UAAAAAAC7uVo3KOejqxTPPFhNQ39pdxwAHYTyGkCXsG6dS+eem6faWocefrheJ50UtTsSAAAAAKATMBIh5a69UJbDq/r9H5EcHrsjAegglNcAOr0VKzy69NJcBYOWFi6s03e+02Z3JAAAAABAZ2BZyvn4x3KFN6ruO3+W6S2xOxGADsQFGwF0WpYlPfJIQOedl6dBgxL6299qKK4BAAAAAO2SUWV//BP5apaoefBsxXMPszsRgA7GmdcAOqW2Nun667P15JMBHX98RA880Ci/37I7FgAAAACgE3BGtip37cVyhz5QS/8r1Npvpt2RAKQA5TWATqehwdCMGXl67TWPZs1q0c9+1iIHnxMBAAAAAEjy1L2k3HWXS5aputELFCuYbHckAClCeQ2g09i40alFi/x66im/amsduv/+Bp1xRsTuWAAAAACAzsAylbn5PgW33KdEYKTqRz+qpG+g3akApBDlNQBb1dY69NxzPi1a5NM777hlGJa+9724fvvbZo0dy/rWAAAAAADJaKtX7ror5K1/WeGiM9Q07A5ZTp/dsQCkGOU1gLQLhw39/e9eLVzo0yuveJRMGtp//zb94hdNOvXUiHr3Nu2OCAAAvoV3331XCxYskGmaOuaYYzRlypSdHg+Hw3rggQdUV1enZDKpk08+WZMmTbIpLQCgs8toeV+5/75Izni1GofNVbj3dMkw7I4FIA0orwGkRSIhvfqqR2VlPr3wglfhsEN9+iR0ySUhTZ0a0fDhCbsjAgCADmCapubPn68bbrhB+fn5uu666zRmzBj17dt3xzYvvPCC+vbtq5///Odqbm7WlVdeqcMPP1wuF7+eAAB25q/4f8pef4OS7nzVHrxIbVkH2R0JQBpxdAggZSxLev/9DC1c6NNzz/lUU+NUdrap006LaOrUiMaNi3MhRgAAupkNGzaouLhYRUVFkqSJEydqzZo1O5XXhmEoGo3KsixFo1EFg0E5OCgAAHxRMqLs9TcoUPmUorlHqHHkQzLdeXanApBmlNcAOtzWrU4tXOjTwoU+bdyYIbfbUmlpVFOnRnT00VF5PHYnBAAAqVJfX6/8/Pwdt/Pz87V+/fqdtjnuuON01113acaMGYpEIrr66qsprwEAOzgjW5S79mK5Q/9Wy4Ar1TLwGslw2h0LgA0orwF0iPp6Q88/337hxTVr2tvp8eNjmjGjUSeeGFFOjmVzQgAAkA6W9dWf+caX1iV97733NGDAAN14442qqqrSrbfeqhEjRsjv9++03YoVK7RixQpJ0ty5c1VQUJC64LvgcrnSPiZ6DuYXUqkrzy9j+zK53j5XktQ2caE8JSeK8586j648t9A1UV4D2GeRiLRiRfuFF19+2au2NkPDhrXpuuuaNWVKRH37Ju2OCAAA0iw/P191dXU7btfV1Sk3N3enbV5++WVNmTJFhmGouLhYhYWFqqio0NChQ3farrS0VKWlpTtu19bWpjb8lxQUFKR9TPQczC+kUpecX1ZSmZvvU+aW+9QWGKX60Y8p6R4gdbXX0c11ybmFLqGkpGSX91NeA9gryaS0apVbCxf6tXSpVy0tDhUXJ3XBBa067bSw9t8/wUWfAQDowYYMGaLt27erurpaeXl5Wrlypa644oqdtikoKNAHH3ygkSNHqrGxURUVFSosLLQpMQDAbkZbvXI/vFzehn8qXHymGve7XXL67I4FoBOgvAawRz780KWFC/1atMinykqngkFTJ5wQ1dSpYU2cGJeT5ccAAIAkp9Op888/X3PmzJFpmpo0aZL69eun5cuXS5ImT56sadOm6Te/+Y2uueYaSdLZZ5+trKwsO2MDAGyS0fyectdeJGe8Ro3D7lS499nijCgA/0V5DWC3yssdWrzYr4ULffroowy5XJYmTYrpppuadOyxUfl4IxwAAOzCIYccokMOOWSn+yZPnrzj67y8PN1www3pjgUA6EwsS/7tTyp7/S+UdPdS7cGL1JZ1kN2pAHQylNcAvsI0pV/9KlP33x+UZRn67nfjmjOnUaecElVenml3PAAAAABAV5aMKGf9bPkrn1Y090g1jnxQpjvP7lQAOiHKawA7aWw0dPnluXrpJa9OPz2sq69u0cCBXHgRAAAAAPDtOSNblLf2ImWE1qplwFVqGfhjyWAdSgC7RnkNYId161y68MI8lZc7dfvtjTrnnDBLjQEAAAAA/j979x0eVZW4D/y90zO9kYQQpEpHEAEFRUXQxY7orguyFhRQinxZQQQBaQrYkCIKSrOCBVdQf8CyKorgipWOhi4JKdOSyfS59/dHkCXSAszMnSTv53l4QiZz77yBk5nLy5lzEkJb8m/Ydo8AALjaLkPY0VPmRESU7lheExEA4OOPdXjsMSvMZgnvv1+CTp2ickciIiIiIiKimkCKw3TgBZgOzkbU2Bru1q8hntFA7lREVA2wvCaq5WIx4JlnzFiwwIhOncJYsMCDrCyua01EREREREQXThFxw7prGHSeDQhk3w3vxU8Dygy5YxFRNcHymqgWc7kUePhhGzZt0uKBB/yYOLEUGo3cqYiIiIiIiKgmUJf+DNuOQVBGiuFt9iwCdfuBa1MS0blgeU1US/38sxoDB9rgdisxa5YHf/tbUO5IREREREREVBNIEvQFb8Hy20TENZkoufRfiJrbyZ2KiKohltdEtdDy5RkYN86KOnXi+Ne/StC2Lde3JiIiIiIiogsnxIOw/DoW+sL3EbJdC0+ruZDUdrljEVE1xfKaqBYJh4GJEy146y0DunULY/58D+x2rm9NREREREREF04ZPAD79oFQl+9EWYORKGs4EhCUcsciomqM5TVRLVFQoMCgQXb8+KMGQ4eWYcyYMih5DUFEREREREQXShKRUbQKll/HAoICrrZvIOzoIXcqIqoBWF4T1QL//a8GgwfbUF4uYMECN265JSR3JCIiIiIiIqrupDh0xZ/AdGA21IE9iBgvgaf1AsQzLpI7GRHVECyviWowSQIWLzZgyhQz6teP4733XGjWLCZ3LCIiIiIiIqrOpDgyilbBeHA21IHfENU3g7vlfIQyb+EyIUSUUCyviWqoYFDAmDEWfPihHjfcEMTs2V6YzZLcsYiIiIiIiKi6EmPIKPq4orQO7kXU0ALuVq8gVOcWQFDInY6IaiCW10Q10KFDSjz0kB07d6owalQpRozwQ8HrCCIiIiIiIjofYgwZRR/BdHA2VMH9iBpawt16IULOG1laE1FSsbwmqmE2bNBiyBAbJAlYtsyNHj3CckciIiIiIiKi6kiMIqNwJUwH50AVOoCosTXcrV9HyPkXltZElBIsr4lqCEkC5s0zYuZME1q0iOG119xo1CgudywiIiIiIiKqbsQo9IUfwHhwDlShQ4gY28LVZgnCjusBQZA7HRHVIiyviWoAv1/AyJFWfPZZBm6/PYDnn/dBr+f61kRERERERHQOxAj0R9+D8eBcqMK/I2JqB1fTKQg7erK0JiJZ2EJhJAAAIABJREFUsLwmquby8pR48EE79u9XYeJEHwYNKuc1BREREREREVWdGIa+YDmMh+ZBFc5HxHQpXM2mI2zvztKaiGTF8pqoGluzRocRI6zQaiW8+64LV14ZkTsSERERERERVRfxEPRHl8N0aB6U4QJEzJfB1fw5hG3XsLQmorTA8pqoGorHgeefN2HOHBPat49g4UI36tUT5Y5FRERERERE1UE8CEPBOzAemg9l5CjCls7wNH8REVs3ltZElFZYXhNVMx6PgOHDbfjiCx369i3HtGk+6HRypyIiIiIiIqJ0J8SD0Oe/BePh+VBGihC2XAFPy9mIWK9kaU1EaYnlNVE1smOHCgMH2pGfr8TMmV7cc0+A1xdERERERER0RkI8AH3+GzAeehXKaDHC1q7wtJqPiLWL3NGIiM6I5TVRNfHRRxkYNcoCq1XChx+W4LLLonJHIiIiIiIiojQmxMorSuvDr0AZdSFsvQqehgsQsV4udzQioipheU2U5qJRYNQoJebOteHyy8N49VUPMjO5vjURERERERGdRrQMxoPzYPh9AZRRN0K2a+BpOBIRSye5kxERnROW10Rp7OhRBYYOteHbb5V48EE/JkwohVotdyoiIiIiIiJKS2IUxt8XQv37q9BE3AjZu8Pd4P8QtXSUOxkR0XlheU2Upr7+WoNhw2woLxewdGkM119fKnckIiIiIiIiSlPK4AHYdg6DpuwniNm9UJIzDFHzpXLHIiK6IAq5AxBRZaIIzJplRN++DthsIj77rAR9+3KZECIiIiIiIjq1jKMfoM73N0AV3Ad3q1cRu+pjFtdEVCNw5jVRGnG5FBg+3IoNG3To0yeAGTN8MBgkuWMRERERERFRGhJipbD8+iT0RSsRtlwOb8u5iOvqwSh3MCKiBGF5TZQmtmzR4OGHbfB4FJg504t77glAEORORUREREREROlI7fsetl3DoQwdQWnD0fA3GA4ISrljERElFMtrIplJErBggQHTp5uRmxvHqlXFaNMmJncsIiIiIiIiSkdSHMaDc2E68CLiuhyUXLqSGzISUY3F8ppIRj6fgJEjrVi7NgM33hjEiy96YTZzmRAiIiIiIiI6mTJ0BNZdw6H1/ReBzDvga/YMJJVZ7lhEREnD8ppIJlu3qjF4sA35+UpMmuTDQw+Vc5kQIiIiIiIiOiVd0WpYfx0DSDF4WsxBMPtOuSMRESUdy2uiFJMk4M039XjqKQscDhEffliCjh2jcsciIiIiIiKiNCTEymHOmwjD0eWImC6Fp9U8xDMayh2LiCglWF4TpVB5uYAxYyz46CM9uncPYc4cL+x2Ue5YRERERERElIbUZVth2zkUyuB+lF00HGUNHwMUarljERGlDMtrohTZvVuFwYNt2LdPhccfL8Xw4X4oFHKnIiIiIiIiorQjiTAcXgjz/hkQ1Q642r2HiK2r3KmIiFKO5TVRCrz/fgaeeMICk0nC8uUuXHllRO5IRERERERElIYU4ULYdo+A1vM1gs6b4G3+LCS1Te5YRESySFl5/fPPP2PJkiUQRRE9evRA7969K309EAhgzpw5cLlciMfjuPXWW9G9e3cAwNChQ6HT6aBQKKBUKjFjxoxUxSa6IMEgMHGiBe+8Y0CXLmG8/LIHWVlcJoSIiIiIiIhOpi1ZB+uexyDEA/A2exaBuv0AQZA7FhGRbFJSXouiiEWLFmH8+PFwOBwYO3YsOnbsiNzc3OP3WbNmDXJzc/HEE0+gtLQUI0aMQLdu3aBSVUR86qmnYDabUxGXKCH27VNi8GA7du5UY/jwMowaVQYV3+tAREREREREfxYPwrJ3Ggz5SxE1toan5XzEDE3lTkVEJLuUVGl5eXnIzs5GVlYWAKBr167YsmVLpfJaEASEQiFIkoRQKASj0QgFFwSmaurTT3X45z+tUKmAN95woUePsNyRiIiIiIiIKA2p/Ltg2zkU6sAe+HMHobTxE4BCK3csIqK0kJLy2u12w+FwHP/c4XDgt99+q3SfXr164dlnn8XgwYMRDAYxcuTISuX1008/DQC4/vrr0bNnz1TEJjpnkQgwbZoZixYZcemlESxY4EG9enG5YxEREREREVG6kSTojyyFZe9UiCozXJe8jbD9WrlTERGllZSU15IknXSb8Kc1m3755Rc0aNAAEydORGFhIaZOnYoWLVpAr9dj6tSpsNvt8Pl8mDZtGnJyctCqVauTzrl+/XqsX78eADBjxgw4nc7kfEOnoFKpUvp4lH4OHQLuuUeF775TYNiwOKZPBzSaxGyqwfFFycTxRcnCsUVERER0aoqIC9Y9/4TOtR4h+3XwtpgFUcPrJiKiP0tJee1wOOByuY5/7nK5YLNVLvW++OIL9O7dG4IgIDs7G5mZmcjPz0fTpk1ht9sBABaLBZ06dUJeXt4py+uePXtWmpVdUlKSpO/oZE6nM6WPR+nlP//R4tFHbYjFgAUL3LjllhBKSxN3fo4vSiaOL0oWji1KlpycHLkjEBERnTet+ytYd4+AIuqDr+lUlNd7gJsyEhGdRkoWlW7SpAkKCgpQVFSEWCyGTZs2oWPHjpXu43Q6sW3bNgCA1+tFfn4+MjMzEQqFEAwGAQChUAhbt27FRRddlIrYRGcViwHTp5tw770O5OTEsWZNMW65JSR3LCIiIiIiIko3YgTmvVPh2NoXosqK4ss+QXnuABbXRERnkJKZ10qlEgMGDMDTTz8NURTRvXt31K9fH+vWrQMA3HDDDbjzzjsxf/58PPbYYwCAe+65B2azGYWFhXj++ecBAPF4HFdddRXat2+fithEZ1RYqMDQoTZs3qxFv37lmDLFh4wMuVMRERERERFRulEG8mDbORQa/3aU59wHX5MJgJL/gCQiOhtBOtWC1H9y8OBBNGjQIBV5Eio/Pz9lj8W3Rtcu33yjwdChNvj9AqZP9+Gvfw0m9fE4viiZOL4oWTi2KFm4bEjtlcrre4DPY5RcHF+1hCRBX/AuzHkTISl08LZ4EWHnDUl/WI4vShaOLUqW013jV2nm9ZQpU2C329GtWzd069btpPWqiWoLUQTmzDHihRdMaNw4hhUrPGjePCZ3LCIiIiIiIkozQtQD657HkVHyGcLWq+BpORuiNlvuWERE1UqVyuuFCxfixx9/xNdff433338fzZs3x9VXX43LL78cWq022RmJ0oLbrcCjj1rxxRc63HFHADNn+mAwnPWNC0RERERERFTLaNxfwbbnn1BEiuFrPB7l9QcDQkq2HSMiqlGqVF4rlUp06tQJnTp1QiAQwObNm7Fq1Sq8/vrr6Ny5M3r27IkWLVokOyuRbL78UovHHrPC7VZg+nQv/vGPAPfUICIiIiIiokqEqA/mvVNgOLocsYzGKLl0FaLmdnLHIiKqts7pv/1CoRC+++47bNq0CS6XC127dkV2djbmzp2L119/PVkZiWRTWipg1CgL7rnHAZNJxKpVJbj3XhbXREREREREVJmueA0yt3SH/uj7KLtoGIo6rmNxTUR0gao08/rHH3/EV199hZ9++gktWrTAddddhzFjxkCj0QAAevXqhUceeQQPPfRQUsMSpdKXX2oxapQVhYUKDB1ahn/+sww6ndypiIiIiIiIKJ0oIsWw/DYeGcWfIGpoBXfbpYiaLpE7FhFRjVCl8vrtt9/GNddcg/vuu++UmzUajUbcf//9ic5GJIuyMgFTppjxzjsGXHxxFAsXutGhQ1TuWERERERERJROJAkZhSthyZsIIR5AaaPH4a8/BFCo5U5GRFRjVKm8fuGFF856nx49elxwGCK5bdigxahRFhw9quRsayIiIiIiIjolZegILL8+AZ37c0TMl8Hb/AXEDBfLHYuIqMap0prXzz//PHbt2lXptl27dlWp1CaqDsrKBIwebUG/fg7o9RI+/rgE48axuCYiIiIiIqITSCL0R5ahzpbu0Hg3w9d0Ckou/YjFNRFRklSpvN65cyeaN29e6bZmzZphx44dSQlFlEobNmhx3XV1sHy5HkOGlGHt2mIuE0JERERERESVKAP74Pj5r7D+Ng5RcwcUd/oc5bkPAoJS7mhERDVWlZYNUavVCIVC0Ov1x28LhUJQKvkETdVXWZmAqVPNePttA5o2jeJf/yrBZZextCYiIiIiIqITiDEYf18I04EXIAkaeJq/gGD23YAgyJ2MiKjGq9LM63bt2mHhwoUIBAIAgEAggEWLFqF9+/ZJDUeULF99pUWPHnXw7rt6PPKIH2vWFLO4JiIiIiIiokpU/p1w/ngrzPueRsh+LYo6f4Fg3b+zuCYiSpEqzby+9957MXfuXAwYMABGoxF+vx/t27fH8OHDk52PKKFOnG3dpAlnWxMREREREdEpiGGYDs6B8dA8iCor3K1eRajOLSytiYhSrErltdFoxNixY+HxeOByueB0OmG1WpOdjSihvvpKg1GjrCgoUOLhh/0YNaoUGRlypyIiIiIiIqJ0ovb9AOueUVAHfkUg6074mk6CpLbLHYuIqFaqUnn9B5vNBqvVCkmSIIoiAEChqNLKI0Sy8fsFTJlSMdu6ceMYPvqoBB07crY1ERERERER/Y8QD8C0fyYMvy9CXFsXrrZvIuy4Tu5YRES1WpXKa7fbjUWLFmHXrl0oLy+v9LUVK1YkJRhRIvwx2zo/X4nBg/0YPZqzrYmIiIiIiKgyjedrWPc8DlXoEMpz7kVp43GQVCa5YxER1XpVmja9cOFCqFQqTJw4ETqdDjNnzkTHjh0xcODAZOcjOi9+v4AxYyzo29cJrRb46KMSTJzI4pqIiIioqrZv346ioiIAgMfjwbx58zB//nx4vV6Zk6XOsf3qiagGE6I+WPaMhvOXvwOCEiXtP4Sv2XQW10REaaJK5fWvv/6KRx55BA0bNoQgCGjYsCEeeeQRfPLJJ8nOR3TOvv5agx496uDtt/UYPNiPdeuK0KkTlwkhIiIiOheLFi06vkTgG2+8gXg8DkEQsGDBApmTpcYbb+jRpo0apaXcnI2optKVrEXmlu7QFyxHWf0hKOr4b0SsV8gdi4iITlClZUMUCgWUSiUAwGAwoLS0FBkZGXC73UkNR3Qu/H4B06aZ8eab/1vbmqU1ERER0flxu91wOp2Ix+P45ZdfMH/+fKhUKgwePFjuaClx6aVR5OcDL75owqRJpXLHIaIEUkRKYPltAjKKVyFqaAl3myWImtvJHYuIiE6hSuV106ZN8dNPP6Fz585o164dZs2aBY1GgyZNmiQ7H1GVbNyowWOPWXHkiBKDBvnx+ONcIoSIiIjoQmRkZMDr9eLw4cPIzc2FTqdDLBZDLBaTO1pKtG0bxYMPiliyxIB+/QJo1qx2fN9ENZokIaPoI5h/mwhFvBylDUfDf9EQQKGROxkREZ1Glcrr4cOHQ5IkAMD999+P1atXIxgM4uabb05qOKKzKS+vmG39xhsGNGoUw0cfudCpU0TuWERERETVXq9evTB27FjEYjHcf//9AIDdu3ejXr16Zz32559/xpIlSyCKInr06IHevXufdJ8dO3Zg6dKliMfjMJlMmDx5cqK/hQs2ZUocH3wgYMIEC5Yvd0HgCiJE1ZYidATWX8dC5/4PIuYOcDV/ATFDM7ljERHRWZy1vBZFEUuWLDn+9kCNRoM777wz6cGIzmbjRg1GjbLi99+VGDjQjzFjypCRIckdi4iIiKhG6N27Nzp37gyFQoHs7GwAgN1ux8MPP3zG40RRxKJFizB+/Hg4HA6MHTsWHTt2RG5u7vH7lJeX4/XXX8eTTz4Jp9MJn8+X1O/lfDkcwOjRpXjySSs++0yHm28OyR2JiM6VJEKf/xbM+54GpDh8TSahPHcAICjlTkZERFVw1g0bFQoFtm7dCoHTDChNlJcLGDfOgrvvdkKpBFaudGHSpFIW10REREQJlpOTc7y43r59O7xeLy666KIzHpOXl4fs7GxkZWVBpVKha9eu2LJlS6X7bNy4EZdffjmcTicAwGKxJOcbSID+/QNo2TKKyZPNCAb5byKiakWKw7ZjMKy/jUXU1B7Fnf6D8voDWVwTEVUjZy2vAeDmm2/Ge++9V2vWt6P0JEnAunVa9OhRB2+8ocdDD/mxfn0xOnfmMiFEREREifbUU09h9+7dAIB//etfmD17NmbPno2VK1ee8Ti32w2Hw3H8c4fDcdJG7wUFBfD7/Zg0aRLGjBmDDRs2JP4bSBCVCpg2zYcjR1SYP98odxwiOgfmvVORUfIZShuPg6vdcsQzGsgdiYiIzlGV1rxes2YNvF4vPv30U5jN5kpfe+WVV5ISjOhE27erMHmyBZs2adGkSRQrV7pYWhMREREl0eHDh9GsWcV6sP/5z3/w1FNPQafTYcKECejTp89pj/tjr5wT/fldnPF4HPv378eECRMQiUQwfvx4XHzxxcjJyal0v/Xr12P9+vUAgBkzZhyfqZ0qKpUKTqcTt9wC3H13HPPnGzF4sBYNG6Y0BtVQf4wvSg7Fvteg+v01xJsOga79U9DJHSjFOL4oWTi2KNWqvGEjkRyOHlXguedMWLFCD6tVxLRpXvTvH4BaLXcyIiIioprtjxL66NGjAHB8zery8vIzHudwOOByuY5/7nK5YLPZTrqPyWSCTqeDTqdDy5YtcfDgwZPK6549e6Jnz57HPy8pKTn/b+g8OJ3O4485apQCq1ZlYuTIOF57zZPSHFQznTi+KLG07q9g3zoCIft1cOeMAWrhnzPHFyULxxYly5+vA/9QpfK6VatWCQ1DdDbBoIBXXzVg/nwjolEBgwaV49FHy2C1cl1rIiIiolRo3rw5Fi9eDI/Hg06dOgGoKLJNJtMZj2vSpAkKCgpQVFQEu92OTZs24dFHH610n44dO2Lx4sWIx+OIxWLIy8vDzTffnLTvJRFyckSMGOHHjBlmfPVVOa6+mu8CJEpHqvLfYNsxGDHDxfC0mg8oqlR7EBFRmqrSs/iKFStO+7W77747YWGIRBFYuTID06ebcfSoEjfdFMSTT5aiYcO43NGIiIiIapWhQ4di9erVMJvNuO222wAA+fn5uOmmm854nFKpxIABA/D0009DFEV0794d9evXx7p16wAAN9xwA3Jzc9G+fXuMGjUKCoUC11133Vk3gkwHgwb5sXy5HhMnWvDvfxfz3YBEaUYRccG+7V5ICi3cbZdBUp35P9uIiCj9Vam8PvFtfwDg9Xqxc+dOdO7cOSmhqHb69lsNJk82Y+tWDdq1i2D+fA8uv5wzWoiIiIjkYDKZ0K9fv0q3dejQoUrHdujQ4aT73nDDDZU+v+22246X4tWFVgtMmuTD/fc7sHixAYMHn3kJFSJKITEM2/YHoYwUoaT9+4jrcuVORERECVCl8nrIkCEn3fbzzz9j48aNCQ9Etc/+/Uo884wZn32Wgbp145gzx4M77ghCoZA7GREREVHtFYvFsHLlSnz11VfweDyw2Wy4+uqr0adPH6hUtfdt+NdfH8Z114Xw4osm3HFHEJmZotyRiEiSYN0zCtrSLXC3egVRc9X+o42IiNLfeV91XnLJJZg1a1Yis1At4/UKmD3bhCVLDFCrJYweXYrBg8uRkcF1rYmIiIjk9tZbb2Hv3r0YOHAg6tSpg+LiYnz44YcIBAK4//775Y4nq8mTfejRIxPTp5sxa5ZX7jhEtZ7x4EvQF65EacPRCGVWr3d0EBHRmVWpvC4sLKz0eTgcxsaNG+F0OpMSimq2aBR4800DXnjBBJ9PQN++AYwaVYasLM5aISIiIkoX3377LZ577rnjGzTm5OSgUaNGGD16dK0vrxs3jmPQID/mzTOhf/9yXHZZVO5IRLWWruhjmA88j0DWnfA3GCF3HCIiSrAqldd/3h1co9GgUaNGGDp0aFJCUc0kScC//63F1KkW7NunwlVXhTFxog+tW8fkjkZEREREfyJJfDfcmTz6qB8ffKDHhAkWfPJJCZe8I5KB2vcDbLtGImzpDG/z5wBBkDsSERElWJXK6xUrViQ7B9Vw27erMGWKBd98o0WTJlEsW+ZCjx5hXlsQERERpakuXbpg5syZuOuuu+B0OlFSUoIPP/wQXbp0kTtaWjAYJIwfX4phw2xYsUKPvn0DckciqlWUwcOwbx+AuLYuPK0XAQqt3JGIiCgJqlReHzhwAEajsdIyISUlJfD7/WjYsGGyslENUFiowLPPmrBihR5Wq4hp07zo3z8AtVruZERERER0Jv3798eHH36IRYsWwePxwG63o2vXrojF+K65P/TuHcQbb+gxfboJN90UhMXC2epEqSDEymDffj8EKQpX22UQNXa5IxERUZJU6c1tc+fORTwer3RbLBbDvHnzkhKKqr9gUMCsWUZcdVUmPvxQj0GDyrFxYxEeeIDFNREREVF1oFKpcPfdd2Pu3Ll46623MGfOHPTp0werV6+WO1raEARg6lQfPB4FXnjBJHccotpBjMG28xGoAnlwt16AmKGp3ImIiCiJqlRel5SUICsrq9Jt2dnZKC4uTkooqr5EEfjggwxcdVUmnn/ejGuvDePLL4swcWIprFbORCEiIiKqzgSu+XaSNm1i6N8/gKVLDdi9u0pvbCWiC2DJewo69xfwXfwMIrZucschIqIkq1J5bbfbsW/fvkq37du3DzabLSmhqHr69lsNbr7ZiREjbMjKimPlyhK89poHDRvGz34wEREREVE1NXp0KUwmCRMmWMB9LomSx/D7Yhjyl8KfOxiBnHvkjkNERClQpakBN998M5577jncdtttyMrKQmFhIVavXo0+ffokOx9VA/v3K/HMM2Z89lkG6taNY+5cD3r3DnLHdSIiIqJqaPv27af9Gte7PjW7XcLjj5di3DgrPvlEh1tvDckdiajG0br+A3PeUwg6bkBpkyfljkNERClSpfK6Z8+eMBgM+Pzzz+FyueBwOHDvvffiiiuuSHY+SmNer4DZs01YssQAtbrign3QoHJkZHC6CREREVF19corr5zx6ydu4k7/079/AG+/bcCUKWb07BnmNTFRAqn8u2DbOQQxY0t4W84DBKXckYiIKEWqvChbly5d0KVLl2RmoWrk4491GDfOCp9PQN++AYwaVYasLFHuWERERER0gV5++WW5I1RLSiUwbZoPd9zhxLx5RoweXSZ3JKIaQREugn3bfZCURrjaLIWkMsgdiYiIUqhKCzssXrwYe/bsqXTbnj17sHTp0mRkojS3erUOw4bZ0LRpDGvXFuO553wsromIiIio1uvcOYI+fQJ45RUjDh7kzFCiCxYPwr59ABRRN9xtl0DU5cidiIiIUqxK5fU333yDJk2aVLqtcePG2LhxY1JCUfr64gsthg+3oWPHCJYvd6F1a657SERERET0h3HjSqFUSpg82Sx3FKLqTRJh2z0S6rKf4W05F1HTJXInIiIiGVSpvBYEAaJYeWatKIqQuJV2rfLf/2rw0EM2tGgRxbJlbq7jR0RERET0J3Xrivi///Nj7doMfPmlVu44RNWW6cDzyChejbLG4xCqc6PccYiISCZVKq9btGiB5cuXHy+wRVHEe++9hxYtWiQ1HKWPrVvVuPdeO3Jz43j7bTfMZhbXRERERESn8tBDfjRqFMPEiWZEInKnIap+Mo5+ANPB2SjP/jv89R+ROw4REcmoSuX1Aw88gG3btmHw4MEYO3YsBg8ejG3btmHAgAHJzkdp4NdfVejXzw6rVcS777rgcHB9ayIiIiKi09FqgcmTfdi7V43Fi7m5HNG50Hi/g3XPaIStXeFrNh0QBLkjERGRjFRVuZPD4cDMmTORl5cHl8sFi8WCLVu2YNy4cViwYEGyM5KMDh1Som9fB9RqYPlyF3JyWFwTEREREZ1Njx5h9OwZwosvmnDHHUFucE5UBcrgAdi2D0Bclwt364WAQiN3JCIiklmVZl4DgN/vR15eHj766CNMnjwZ+/fvx/3335/EaCS3o0cV+PvfHQiFBLz7rguNGsXljkREREREVG1MmuRDNCrgmWe4eSPR2QhRH+zb7oMACa62yyCpbXJHIiKiNHDGmdexWAzff/89vvzyS/zyyy/Izs7GlVdeiZKSEowcORIWiyVVOSnF3G4B/fo5UFKiwIoVLrRoEZM7EhERERFRtdKoURyDBvkxb54J/fuXo1OnqNyRiNKTGIV9xyCoggfhavcu4vrGciciIqI0ccbyeuDAgVAoFLjmmmvwt7/9DY0bV7yArFu3LiXhSB5lZQL693fgwAEV3nrLhUsv5UU2EREREdH5ePRRPz74QI8JEyz49NMSKJVyJyJKM5IEy29PQuvdCE/zFxGxdpE7ERERpZEzLhvSoEEDlJeXIy8vD3v37oXf709VLpJJMAg88IAdO3aosWCBG127cnt0IiIiIqp9lMHDUBx4ExAv7B2IBoOEiRN92LZNg+XL9QlKR1RzGH5fCEPB2yi7aBiCde+WOw4REaWZM868njRpEoqLi7FhwwasXr0aS5YswSWXXIJwOIx4nOsf1zSRCDB4sB3ffqvByy97cP31YbkjUSpJcQjxEAQxCCEehCAGATECSWmApDJCUhohKXTc7ZuIiIhqhYzCD6A68DwydQ3gbzAcgaw7z3vzuNtuC+GNN8KYMcOEm28OwmqVEpyWqHrSlqyDee9UBJ03oazRGLnjEBFRGhIkSaryldPu3buxYcMGbN68GUqlEt27d0f//v2Tme+C5Ofnp+yxnE4nSkpKUvZ4iRaPA8OG2bBqVQZmzvSif/+A3JHoD5IEp90EV9Hh46Vy5Y+hSp8rTvr62T4eO146+39WSFBCUhkhKg0VZbbKCFF5rNhWGiCqTBVlt9II8Y/CW2mEqDp2f6XphN8bAKHKe8ZSElX35y9KXxxblCw5OTlyRyCZpPL6HpKEOtH/Qto2BZqyXxDT1oP/omEI1L0bUGjP+XQ7dqjQq1cd3HdfOaZNK01CYKpuavvrpKpsO5w/3YGY4WK42n8ISZkhd6QapbaPL0oeji0IaQ6uAAAgAElEQVRKltNd459x5vWftWjRAi1atMADDzyA7777Dl999VVCwpG8JAl44gkLVq3KwPjxPhbXqSaGoQwXQBk6AmX4CJShfCjD+Sd8fgQKMYC653haSaGr+KXMgKTIOOGjHnG146Tbcey+YqXb1BDiAQhxPxQxP4S4H0K8HIq4H8KxzxVxP4Tw0WO/L6+4HVV7Z8bxElxpqCjBVQaIShMklQmB7L8iYut27n+eRERERIkgCJBybkGJ+nJo3V/CdPBFWH8bC9PB2Si7aBgCdfsCSl2VT9e6dQz33hvAsmUG3HNPAC1bckN0qr0U4aNwbLsPktoCd5slLK6JiOi0zmnmdXXDmddnJ0nA1KlmLFhgxKOPlmHMmDK5I9UskgRF1FWpiFaGjxwrp/Mrfh8pOumwuNqJuK4e4tp6iOtyoLM2QHlI+lMJfeLHP5fUOvlmNUvSsdncfxTc5VDEyyDEjpXbx25XxP1/+n35sZK8DIpIIRRRD8oajoK/waOcoZ1k1fX5i9IfxxYlC2de114pnXmNPz2PSRI0nq9hOvgStL7/Iq7Jgr/+wwjk/KPKxZvHI6Bbt0y0aBHD+++7uBpbLVdbXyeFeACOn+6EKpCHkg7/QszYWu5INVJtHV+UfBxblCwJmXlNNc/s2UYsWGDEgAF+PP44i+tzJcQD/5spfWI5ffxjwUnLcYiKjOPFdNTYEnFtTsWvP8pqbd2TZvFonE6UV5cXB0GoKNCVGYCmzvmdIlYOy6+Pw3zgOWjKfoKnxWxIamuCgxIRERGdA0FAxH41XParofFuhunALFj2Tobx0MvHSux7IakMZzyFzSZhzJgyPPGEFatW6XD77aEUhSdKE5II664RUPu3wd1mMYtrIiI6q5SV1z///DOWLFkCURTRo0cP9O7du9LXA4EA5syZA5fLhXg8jltvvRXdu3ev0rF0fhYtMuC558y4664AJk8u5cyPM5FEZBR+AHXZtsoFdcxT+W4QIGqyENfVQ9R4CULOGxHT1oOoy0Hs2CxqSWXjpodnIakM8Lach6j5Mpj3TkadH26Cu/VCxExt5I5GREREhIi1C1ztu0Dj/Q7Ggy/Bsm8ajIdeRnn9QSiv9wAklem0x/brF8Dbb+sxdaoF118fhl5fY98IS3QS074ZyCj5DL4mTyHsvEHuOEREVA2kpLwWRRGLFi3C+PHj4XA4MHbsWHTs2BG5ubnH77NmzRrk5ubiiSeeQGlpKUaMGIFu3bpBoVCc9Vg6dytWZGDiRAtuvDGIF17wQsFVGU5LiPlh3T0CGSVrICpNiOtyEdfWRdR86bFlPer976MmC1Co5Y5cMwgCynMHIGJqC/uOh1Hnp9vhbTYdwey/yZ2MiIiICAAQsXaG2/oO1KU/wnTgJZj3z4Tx8Kvw5w5Eeb0BkNSWk45RKoGpU0vRu7cTc+cauWwf1RoZBStgOvwyynP+gfLcgXLHISKiaiIl5XVeXh6ys7ORlZUFAOjatSu2bNlSqYAWBAGhUAiSJCEUCsFoNEKhUFTpWDo3n32mw6hRVlx9dQgvv+yBiovHnJYysA/27Q9CFdgLX9PJKK/3IGdNp1jU0gnFHdfAtvMR2HaPhMb3A3wXTwEUWrmjEREREQEAouYOcF/yBtRlW2E88BLMB56H8fAClOcOgD/3IUhqe6X7d+oUQZ8+Abz6qhF33x1Aw4ZV2+yaqDpSBg/AtP8FZBR9hJDtaviaTuW/qYiIqMpSMt/W7XbD4XAc/9zhcMDtdle6T69evXDkyBEMHjwYjz32GB544AEoFIoqHUtVt2GDFkOG2NChQxSLFnmgZf93WlrX56jzw81QRIrhavcOynMf4kWWTERNHbguWY6y+kNgKHgLzp/6QBk6IncsIiIiokqipkvgabsYRZetRdjWDaaDs5H17RUw7ZsORcRV6b7jx5dCrZYwadLJs7OJagJFuACWPWOQ+d010JV8Bn/9IfC0fo3vVCUionOSkjm3knTyOm7Cn0rAX375BQ0aNMDEiRNRWFiIqVOnokWLFlU69g/r16/H+vXrAQAzZsyA0+lMQPqqUalUKX2887Fpk4AHH1ShVSsJn34KWK2Osx9UG0kSFHueg3L7REjWSxDv8h7MhoayRqoO4yslMmchmnst1FseROaPNyLWeRmk7OvlTlXtcXxRsnBsEVFtFTO1gafNayjz74bx0BwYD70Mw++LEMi5F/76D0PUZiIrS8TIkWWYNs2Czz/X4rrrwmc/MVE1oIi4YTw0D4b8ZYAUR6Buf5Q1eBSiNkvuaEREVA2lpLx2OBxwuf4308DlcsFms1W6zxdffIHevXtDEARkZ2cjMzMT+fn5VTr2Dz179kTPnj2Pf15SUpLg7+T0nE5nSh/vXG3frsJddzlRt24cb7xRglhMRBrHlY0QK4d1z0hoij9FILM3fM2fhxTMAILy/mGl+/hKKe2VUHb4FPYdg6DaeCvKGo6Cv8GjgMCF288XxxclC8cWJUtOTo7cEYiqJGZsAW+r+fA3+CeMh2bD8PtrMOQvQ3nde+C/aAgefDAb77xjwFNPWXDVVUXQaOROTHT+hFgZjIcXwvD7AgjxIILZd6GswT8Rz6gvdzQiIqrGUtL2NGnSBAUFBSgqKkIsFsOmTZvQsWPHSvdxOp3Ytm0bAMDr9SI/Px+ZmZlVOpbOLC9Phb59HTCbRSxfXgKnU5Q7UlpSBg/C+dPt0BX/P/gaT4C35TxIygy5Y9EpxPVNUNJhNYKZvWE+8Bzs2x+AEPXKHYuIiIjolGKGpvC2nIuizhsQzLwdhiNLkfVtV9Q5MA7PT9mBfftUeP11o9wxic6LEA/CcOiViiVyDr6IsP1aFHf6HN4Ws1hcExHRBROkU63LkQQ//vgjli1bBlEU0b17d/Tp0wfr1q0DANxwww1wu92YP38+PB4PAOD222/H1VdffdpjqyI/Pz8538wppOvsssOHlejd24l4HFi5sgSNG3MzmFPRujfAtnMIAMDTaj7C9mtkTlRZuo4v2UkS9EeWwrJ3EuLaenC3XoiYqY3cqaodji9KFo4tShbOvK69Unl9DyTveUwZPAjjoZehP/oeAOCz3f/A6KVP4q2P9MjO5kST2qLav06KEegL3oXp4GwoI4UI2bujrNHjiJoukTsZoQaML0pbHFuULKe7xk9ZeS2H2l5eFxUpcMcdTng8CnzwQQlatYol5sSSBOuuR6H2b0VZo8cRct5UfTcylCQYDi+Aed/TiBmaw93mdcQzGsqd6iTpOL7Sidr3Pew7BkMR88J78TMI1r1b7kjVCscXJQvHFiULy+vaq6aU139Qho7AeOhlZOS/i3hMxFeH+6HN3YMQ1zdK2mNS+qi2r5NSHBmFH8F04AWoQocQtnRGWaMxiFivkDsZnaDaji9KexxblCynu8bnIrE1lMcjoG9fB4qKFHjzTVfiimsA+vw3oS9aCUXUB/uOQXD83Afq0p8Sdv5UEeJBWHcNg2XfVITq3IiSSz9Oy+Kazi5q6YjijmsRMXeAbc8/YdnzOCBy0yMiIiJKb3FdPfiaPYOiLpuwqeQhdK33HjK/u7piokjZNrnjEVUmSdAV/z/U2dITtt0jIKrMcLV9E672K1lcExFR0rC8roH8fgH/+IcD+/apsHixG5ddFk3YuVX+3bDsnYyQ7VoUdtkCb7NnoQrsR50fb4F15xAog4cT9ljJpAwehvOn25FR9DFKG42Fp9UCSCqD3LHoAogaJ1yXvIuy+kNhKHgbzp/ugDL0u9yxiIiIiM5K1NZFvdsmouuMX7Hsv49CV/wZ6vzQC87v/wL9kWUQYqVyR6TaTJKgdW+A88ebYd/xECDF4W71Kkou+38IO66rvu/CJSKiaoHldQ0TCgEPPGDH1q1qvPqqB926RRJ2biEehG3nEIhKI7wtXwIUagRy7kHR5RtR1mAEdCVrkfnd1TDvnQYh6kvY4yaaxrMRzh9uhDJ4GO62b8DfYBgvuGoKhQplTcbB3XoRVIF9qPP9X6B1b5A7FREREdFZ6fUSBv+fAQ/MmYXZB3fCe/HTECQR1t/GIWvTpbDuGgGN9zug5q76SGlI7dsCx89/hWNrPygiJfA0fxHFnT5HKPNWQGCdQEREycdXmxokGgUeftiOzZs1eOklL/7yl1BCz2/eOxnqwB54W86GqKlz/HZJZURZo8dR1Pnrit3TD7+KzP9eCf3vSwAxcbO+L5gkwXD4NTh+6QdR40TxZZ9WzBSgGidUpxeKL/sMcW027FvvgfHALEDi5kdERESU3m69NYQuXcKYMuMiHNQMQHHHdSju8BmCWXdBV7IGzp/vQJ0t18Jw+FUoIi6541INpirbDvvWe1Hnp95QBfLgbToNRZd/XbG3jEIldzwiIqpFWF7XEKIIjBxpxb//rcPTT/vQp08woefXFX8KQ/6b8Nd/GGH7tafOoMuBt+VLKL5sDWLGVrDmjUfmluugK1kr/wyReBDW3SNg2TsJIef1KOnwCeL6xvJmoqSK6xujpMNqBDPvgPnA87Bvux9C1Ct3rP+RJKjKf4P+yFLYtg9Ene+uhXnvVKjK8+RORkRERDIRBGDqVB8CAQHXXpuJpcsMCOrbwdd8Jgq7/AhP8xchqSyw7J2KrM2XwbZjcMW7zPif9JQgysBe2HY8gswf/gJN6fcobTQWRVdsQiD3AUChlTseERHVQoIkyd0qJk8qdyOXc7dVSQLGjrXgzTcNGDu2FMOG+RN6fmXoCOp8fz1iGQ1Rcum/AIWmSqG0rvUw75sGdSAPYUsXlDaZgKi5XUKzVYUydAS27Q9B49+K0oaj4G8wotq9xY27+V4ASYI+fxkseZMQ19aFu/VriJnayBJFGfodGs9GaD3fQOv9BspIIQAgps1FXN8IGu9mCFIMYXMnBOr2RSjzVkhKfdJzcXxRsnBsUbKcbidyqvlSeX0PyPc8tnOnCk89ZcGmTVo0axbFpEmluOaa/21GrSrfA33BO9Af/QCKmBcxbS4Cdf+OQPbdEHX8+agu0ul1Uhk6AuOBWdAffQ+SQovy3Ifgr/8wJLVF7mh0ntJpfFHNwrFFyXK6a3yW1wki1w+vJAHPPGPC/PkmDBtWhrFjyxL7AGIMjl/+CrV/B4ovW4u4vtE5Hh+FvuAdmA68AGXUhUBWH5Q2egKirl5ic56GxrsZth2DIYhheFrORdh5Q0oeN9H44nDh1L4fYN8xCIqYF96Ln6l4y2OSKSLF0Hg2QeutKKxVoYMAgLjaibDtSkSsVyFsuxJx3UWAIEARKUbG0Q+hL3gH6uBeiEojgpm3I1C3L6Km9klbm53ji5KFY4uSheV17VVbymug4jp/7Vodpk4148ABFXr0CGHiRB+aNo3/705iGLqSNTDkvwOtdyMkKBC2d0cg5x6E7NcBCrUs2alq0uF1UhEphvHgXBjy3wQAlNe7F/6LhkPUOGXNRRcuHcYX1UwcW5QsLK+TTK4f3nnzjJg+3Yz77ivH00/7Et5tmfY/D9PBWfC0nItgVp/zPo8QK4Xx0MswHn4NEAT4cx+C/6JhkFSmBKY9gSRBf2QpLHsnIaZrAE+bxYgZmibnsVKALw6JoYiUwLZzCLTeb1Be9x74mk4BlLqEnV+I+qD1fQuN5xtoPRuhDuwBAIhKM8LWLojYrkTYdhVi+mZnLqIlCZrS76EveAe6otVQiEFEDS0QqNsXgaw+kNT2hGUGOL4oeTi2KFlYXtdetam8/kM4DCxZYsBLL5kQDAq4//5yjBxZBqu18j/jlMGD0Be8C/3R96CMFCKuyUQg+28I1O2LeEZDecLTGck5voSoF8bDr8Lw++sQxAgC2X+Dv+FIxFM0yYiSLx2ev6hm4tiiZGF5nWRy/PD6fALatMnGTTeF8MorHigSvBKGxrsZjp//hmBWH3hbzk7IOZWhIzDtmwF90UrE1Q6UNXwMgbr3JHbTj3gI1t/GQX90BUKOnvC0nAtJZU7c+WXAF4cEEmMwHXgOpkPzEDG1g6f1QsR1ued1KiEehMa3pWIpEO83UJdthQARokKHiOXyirLaeiWipraAoDy/x4iVIaPoY+gLlkNT9hMkQYOQsxcCdfsibLsqIUvgcHxRsnBspYgkQhEphKjJTto7NNINy+vaqzaW138oKVHg2WdNePddPcxmCaNHl6J//wBUf76MFmPQuj+HoeAdaF3/gQARYWtXBOreg6CzV0L/454uTErHlxiBIlIMZaQQWs9GGA+/CkXMh0Dm7Shr+Bji+iapyUEpk07PX1SzcGxRsrC8TjI5fni//lqDv//diXfecVVaAy8RhKgbmVuuh6TUofiytZBUxoSeX136C8x7p0Dr+xZR/cUobTIeYXuPC/5HtyKUD/uOQdCU/YSyBv+HsoaPVbv1rU+FLw6JpytZC+uuEYCghKfVfITt15z9IDECTenP0HgrZlZrSn+AIEUhCSpEzB2OLwMSMV+alA1tVP5dFTOqCj+sWN9SVx+B7LsRyP7bBS3Fw/FFycKxlURiGFrPJuhK1kDn+jeUkUKELZejrNEYRKyXy50u6Vhe1161ubz+w44dKkyadPr1sE+kCBdAf/Q96AuWQxU6BFFlRSDrTgTq9kPM2CJ1ocUYlJFCKML5UIbzoQwVVHw8/nk+BDF47HrqCkQsXRAxt6vxGwQmZHyJYSgjxVCECyv+jCNFUIaPQhkpOuG2Qiij7kqHhRw9UdpwtGx7wVDypePzF9UMHFuULCyvk0yOH96XXzbimWfM2LatAHZ7Av8aJQm27Q9C5/4cJR1WIWq6JHHn/tPj6ErWwrxvGlTB/Qhbr4SvycTzvoDS+LbAtn0gBDEAb4vZCNW5McGB5cMXh+RQBvbBvmMQVOW7UdbwsZM385TiUPt3VCwD4v0GGu9/oRADkCAgamx7fBmQiLkTJJUhdcHjIehK1sJw9F1oPV9DgoCw/dqKTR4d11dtU9UTcHxRsnBsJZYQ9UHn/hy6krXQur+AIu6HqDQgbL8WUUNLGPLfhDJSiJDtGpQ1ehxRc3u5IycNy+vai+V1hT+vh92zZwgTJvxpPexKB4jQeDbCUPAudCVrIEgRRMwdEKjbD8E6t13YdYwUr5jRe6yEriikCyoV04pIEQSIlQ4TlUbEtTkVv3Q5gKCExvc91OW7Kk6r0CFi7lCx9JrliorJAcqM88+Zhs44vuKhilI6UlFEK8PHSujwsYI6UlhRTsc8Jx0qQQlRUwdxbRZETSbimqzKv89oVK2XVKSqSdfnL6r+OLYoWVheJ5kcP7yDBtmwbZsamzcXJfS8+iNLYf3tSfiaTER5/cEJPfcpiVEY8t+E8cCLUMS8CGbdhdLGYyBq61b5FPr8N2H5bQLiunpwt1mMmKF5EgOnHl8ckkeIB2D5dQz0hSsRsvdAWcPHoC79EVrvN9B6N0MR8wIAovpmxzZZvBJhaxdIaqvMySsog4egP7oC+oLlUEaOIq52IJh1FwJ1+yJmuLhK5+D4omTh2LpwilA+dK51FYW1dxMEKYa4ug5CzhsQcv4FYeuVx5cAEOJB6POXwXhwHpQxD4LOXihrOAoxY0uZv4vEY3lde7G8riwcBhYvrlgPOxQ6/XrYJ1JE3Mgo/KBig+jAbxCVBgQze596g2hJgiLq+lMxnX9sBnVBxW2RoxCkWKXHEBU6iCcU08dLam0O4tq6iOtyTrusnxB1Q+v9DhrfZmi830Lt3wEBEiRBg4j5UkSsVyBsuQJRS0dISn1C/hxTTYiVQRXYC6vGh0BJ3vEZ0hWF9LFi+tg16IkkQVVRSmuyENdkQdRWlNHisXK64veZEDWO816yjmqOdH/+ouqLY4uSheV1ksnxw3vFFZlo1y6KBQtO/t/286Xy70SdH25B2HYl3G2XpXTJDSHqg+nQXBh+XwRJUKC8/sPw13/kzEuWiGFYfpsAQ8HbCNmvq1jfOk1KxUTii0OSSRL0+ctgyZsEQYoCAGK6+ghbrzq2bnVXiNosmUOehRSH1r0B+oJ3oXOtgyDFEDF3RHndvgjVufWMM6o4vihZOLbOgyRBVb7n2HIg66Ap+wUAEMtojKCzF0LOvyBq7nDG12ch5ofh99dgPLwAQtyP4PH1TBun6rtIOpbXtRfL61MrLlbguedMeOcdPaxWEaNGlZ16PewTSRLUpd9XzMYuWnVsg+iWiBpbnrCsRwEEKVL5MEFTUUBrcxDX1a1cTOsqymlJZUvYGvxC1AeN77uKTbG930Jdtg0C4pAEFaKmdsdmZl+OiKVT8jaDPx+SBEU4H+rAXqgCeSf82gtl5GjluwpqxDWZFTOjtdnHZkif8HttRUEtqu01YklESo3q8vxF1Q/HFiULy+skS/UPr9stoG3bunjyyVIMGeJPyDmFeBDOH26EIupFcaf1EDXOhJz3XCmDh2DeNx0ZxasQV9dBWaPRCGTffdKmjopwIew7BkJT+gPKLhqGskaP19gZBnxxSA2VfwfU/h2IWK5APOMiueOcN0WkBBlHP4D+6LtQB/KOzai6/diMqktP+sckxxclC8dWFUlxaHzfVxTWJWuhCh0EAETMHRBy9kLI8Zfzenu3EPXAePhVGH5fBEGMIJD9V/gbjjzvTWrTCcvr2ovl9Znt2KHCU09ZsHnz2dfDPpEQKz22QfQKKCJFx4to8aRiOkf2AlWI+Ss2zPZ9C613M9Rlv0CQYpCgQNTUFhHLFQhbr0DEcjkktSX5geIhqIL7K5XTf3xUiIHjdxOVZsT0TRDTN634ZbgYpuxL4ApoIaqtLKUp4arb8xdVHxxblCwsr5Ms1T+8GzZo0a+fAytWlOCqqyJnP6AKLHseh6HgbbgueRdh+9UJOeeFUPt+gGXvFGhKv0fU0AKljccj7Oh+/Gv2HQMhxErhbTELocxbZU6bXHxxoPMiSdCUfl8xG/uPGVX65gjU7Ytg1p0QNXYAHF+UPBxbpyfEg9B6vqpYDsT1byijbkiCBmHbVQg5/4KQ4/qEveNDESmG8dA8GI68CUBEeU5/+C8anv7vKDkDlte1F8vrszvn9bCrOSEegNr3/fGZ2ZrSnyBIEUgQEDO2QthyBSLWLghbL4ektp/34ygi7j/NoK74pQwdgoD//ZM6ps09VlCfUFTrm0LU1OEEAkopji9KFo4tShaW10mW6h/eOXOMmDnTjJ07C2CxXPhfoa5oNew7H0ZZ/aEoazIuAQkTRJKgK/4U5n3PQBU6iJDtGkRsV8K0/3n8f/buO7zq+vz/+OvMnJV5EjIYsjcJuwrKkCHUVhSq1NW6Wjc/bR1FsbYqLVY7rVuKo9SJFq36FdA6ClYBIQFBBQRFVkgCZJ39Ob8/DgRTgjJyRpLn47py5YzPybkD75xz8sp97nckrUBV/ecq7Omb7CrjjicHHC9TuEbO8pfl2vG07DWrFDXZ5c89TfWF5yq9x1mqqKz69i+CY2ap36isz2bKZPgVcvdVyNNHYU8/hdy9U+stzs2Mx67GzMEqpVUulqNykdKq3pbZ8MuwZMjvHRebX50z9ptHZR3v/fu3Kf2LP8u181lFTVbVt79YNZ2uOq4wJ1kIr9suwusjdyzzsFuFiE/26lUNndn26o9kMvySpJC798HO7KwTY4Hy1xlhWfxb/6eDen9I/bWNEaNmh8LOLvuD6R4K7Q+rI66uRzWHuyWvL6Q+1hfihbWFeCG8jrNE//Bedlm2PvnEpv/85/g3a7T4v1Le8gkKu7qpYtBLktnWDBU2MyMg97YnlP7Fn2UO75U/e5T29L2/Rf7CfSx4ckBzstaul2vH03LtWiBzeK+inh7aV3Sp6vN/IFmcyS6v1XHu+qcyP7tJUZNdYXdv2erWyRze13B92NFRIXdfhT19FPL0VcjdRxFn51bx9mEeuySL7ws5Kt6Qo+IN2fd9KJMMRdIKY/OrvRMVzDop4c+7Ft8WpW/5g5y7XlTU4lZdh5+qtuNPDrt5WioivG67CK+P3jHNw25NjIDsNWWy741tAGnft7xhnEfI1V3BjKEyh6tjYbVvc6MZ3xFbbpNd1BFH+2YZV9ga1hdSF+sL8cLaQrwQXsdZon94hw1rp+HDg7r//kN3oT4qRli5q6fJWveJdg9dpIjzhOYpME5MoT1K2/tf+b0TDpmB3Zrx5IC4MAJy7n5dmTvnyrznI0VsXtW1v1j1RT9uGCmC4xDxKXPj7XLvmK9gxlBV9X1AhqP9wQ2catfJVrdettr1statk7X+c5lkSJIMs1Nhd+9YmO3pq/D+DbRaUrgotdHHrmhUttq1DfOrbXXrJUkhd5/YOJDc0xTyDGi2jcyOh7XuM6VvvkfOitdkWLNU2+kq1bW/+Ki6BpOF8LrtIrw+dsc6D7vVMUKy1a5R2t7/yr73fdmqVylqy2oIpkOuHvvD6m6K2rLjWkprWl9IPawvxAtrC/FCeB1nifzh3b3brIEDC3Tbbft0xRV1x/W10jf/Tulf/Fl7+twvX/6ZzVQhmhtPDoinXK9X1Zv+Jc/Wh+SoXKKo2aH6gnNU2+Eniri6Jru8FslSv0k5H18hW9262DimLjd+e3dtxCdb3Wey1q3fH2yvk612vczhg3+kDKd1aNShHfL03d+lnZqb1baYxy4jJJPhkyniO8LP/q+d9ze63lr/mayB7YrKrGDm8IbAOpX/OGyrWaP0zb+To+otRWx5qj3hWtUVXSCZ05Jd2mERXrddhNfHp63Nw051rW19IbWwvhAvrC3Ey+Fe47ed1tVWpKwsFoCUlISO6+vY9yyT54u/qL7gHIJroC0zmRTMOklVWSfJWrdB7q8ekWvHM3Jtf0r+3Emq7Xi5QpnDkl1li+EoX6isT2+UTDZVDnhCAe/4I7uhxalQRolCGSXyHbgsGpU5sGN/h/a6hmA7rfLNr3VpOxq6tMPuA8F2b0VtWXH5/pqdEZYpGpKMgExG8ODpaEgmI/gNp4MyRYP7T4dkigb+53TgW0Lnr32Oho+67KjJpqjZqajF+bXPDoXSB9BnSyIAACAASURBVKqm8w0KeCe0mHcwhNIHqKr4Kdn3LVf65ruVufGXcm99SLUnXK/6grNTc5wYgGNiMkmTJvk1dqy/YR72uHHt2s48bAAA0OLQed1MEvmXpz/+0aPf/z5d69fvVHr6sf33mYNVylsxQVGLS7uH/J+iVnczV4nmxF82EU9NrS9zoFzu7Y/Lve0JmcN7FcwYotqOV8ife1rKdvkmXcSvzE2/knv7UwpmDFFV3wdjY0Licl8+2eo3yFq7fn+HduyjcZd2kcIHZmg7OkhRQ5IRC2qjESn6tdOHXB6RouH9l0f2Xx45eFqRQy9v4mtbrWZFgnX7O5uDMkUDDae1P3g+EMI3l6jJrqjZrqjZ8T/B8tc/OxoFzk0f802fHa030I1GZd/7H2V8frfsNasUdnZWTeefy9duSkr97NN53XbRed282vw87CRr7esLycX6QrywthAvjA2Js0T+8F50UY42b7bonXd2H9sXiEaVs/ZipVW9o92DX1E4vX/zFohmx5MD4umb1pcpUi/njmfl+eoRWf1fKuzorNqOP5GvYLqibO7YwFK/WTnrLpet9mPVdrxS1V1uTny4GY3KHNwpW23jLm1r/SaZdGRvB4+arJIsiprMkskqmb52WmZFTZb9l3/tdJOXWyRZZEtzKBg27e9STpPM9iZO2/eftn/DaZtkTms4HTXbJVPa107vP95kS4lZ0q1CNKq0ysXK2HyPbHXrFHL1Uk2XG+TPnZwS/8aE120X4XV8fH0edkaGoX79QurfP6QBA2Kfu3ULE2jHQVtZX0gO1hfihbWFeGFsSCtSVmbTyJHHvrmKe9s8OSoXa1/3XxNcA/hGUYtL9R0uVn37H8mx+3V5tj6krA23Kn3zvapv/2PVtb9Yhj032WUmlaP85f1jQqyq7P+4ArkTklOIySQjrVCBtEIFvKcevDzilzlU2UQY3Tiklsnc7CXl5uaqihe2LZPJpEDuRO32jpdj97+Uvvle5Xz8EwU9xarpcpMCOWNSIsQG0Dz69Qvr+ecrtWRJmt5806G1a2166im3/P7Yz7nDYahPn3CjQLtXr5AcjiQXDgAAWj3C6xZm506zdu2yHPO8a2vtx8rYdKf8OeNU1/7SZq4OQKtlssjf7nvy550u+77lcm99SJ4v/izPlw+qvuAHqu34U0Vc3ZNdZWJF/MrcdIfc259QMGOw9vR9SJF4jQk5HhaHDEsK1oWWwWSWv90Z8ud+V85dC5T+xR/lXXOBApnDVdPlJgWzTkp2hQCaickkTZgQ0IQJsSaZcFjauNGqtWttDR///KdTTz0VGzdotUbVo0fjQLtfv5A8nlb7xl4AAJAEhNctzPFs1miK1Ct73VUybNna2/uPdEwBOHomk4JZwxXMGi5L/UZ5tj4q187n5d4xXz7vRNV1vELBzOGt/vHF4tui7I8vl712rWo7XqHqLr9ovTOQAUkyW+UrnC5f/lly7Xha6V/8RbmrfyB/9ijVdLlJoYxBya4QQDOzWqXevcPq3TusH/wgtpWwYUhffmlpFGi//Xaann/e1XC7Ll1igfbXQ22vt3n3NwAAAG0H4XULU1Zml9kcVb9+Rx9eZ2z4paz1m1RZ8rQMuzcO1QFoSyKu7trX627VdLlR7m2Py7XtcTkrFymYPki1HS+XP++7KbXBW3NxlL+yf0yIRZX95ymQOzHZJQGJY7arvv2PVV9wjtzbn5Tny7/KtfN57SO8BtoEs1nq3Dmizp0j+t73/A2X79pl1po1BwPt1atteuWVg3tjFBZGDgm0i4oirf1v3QAAoBkQXrcwpaU29ewZlst1dG/Hc5QvlHvn06rpdI2C2afEqToAbZFhz1VNlxtU2+lqOXc+J89Xjyhn3RUKOzqptsNP5SucrqjF9e1fKNUZAWVuvEPu7Y8rmD5Ie/o9pIijQ7KrApLD4lRdx8tVX3i+FD22UWYAWo/8fEP5+QGNH39wX549e0z6+GNboy7tJUvSFI3GEuvs7Ij69z8wdiSogQNDOuGEI9tgGAAAtB2E1y1INBobGzJ27NFt1mjxfamsT29WMGOwajrfEKfqALR1UYsz1pFZdIEcFYtimztunKWMLfeqruhHsc0d09olu8xjEhsTcqXstWWq7fBTVXedKZntyS4LSLqo1ZPsEgCkqOzsqE4+OaiTTw42XFZfb9K6dY3naD/2mFuhUOyxpKQkqKlTfZoyxae8PEaNAAAAwusWZft2syoqLCopCX77wQcYIWWvv1qStKfP/cxkBRB/Jov8eZPlz5ss277l8mx9RJ4v75Nn60Oqz5+muo4/VdjdM9lVHjHH7leV9cnPJZNZVf3/Jn/uackuCQBS3urVqzVv3jwZhqFx48bpzDPPbPK4jRs36tZbb9X111+vE088McFVItFcrqiGDg1p6NCD79gIBqXPPrNq6dI0vfiiU7ffnqk77sjQ6NEBTZ3q02mn+Y/6XacAAKD1ILxuQcrKYl1+xcVH/vbc9C2/l736I1X1fUARZ6d4lQYATQplDtOezGGy1G+W56tH5dz5rNw7n5Y/Z5zq2l+kQNZJksX57V8oGYyAMjbNlmfb3NiYkL4PKuLsmOyqACDlGYahuXPnatasWfJ6vZo5c6aGDh2qDh06HHLc/PnzNXDgwCRVilRgt2v/+JCwLr+8Tp9+atWLLzr14otOXXNNttxuQ5Mn+zVtmk8jRwZkaX3baQAAgG9gTnYBOHKlpTZZLFH17Xtk4bV9z3/k+fKvqis4V/52U+JcHQAcXsTVRft6/kblJy5XdecbZKtZLe+aC1W4tL9ySs+V+8uHZK39ODYfKQVYfF8od9VZ8mybq9oOP1HFoBcJrgHgCG3cuFEFBQXKz8+X1WrViBEjtHz58kOOe/311/Wd73xHGRkZSagSqapXr7BmzqzRBx+U64UXKjRlik+LFjl07rleDRuWrzvuyNDatdZUeckAAADijPC6BSkrs6lXr7CcR9CkaA5WKnv9DIWdXVXd4474FwcAR8Cw56i28/XadeKHqhzwlOqKLpAlsEuZn9+pdismKn/ZIGWtv1bOnc/LHNiVlBodu19X3opJsvq2qKrfXFV3/xXzrQHgKFRVVcnr9Tac93q9qqqqOuSYDz/8UBMnTkx0eWghzGbppJOCuueefVq1aqcefrhKAwcG9be/uXXaae00blye7r/fo23b+JUWAIDWjLEhLcSBzRonTfIf0cFZn1wvc2iPKgc8qajFFf8CAeBoWBwKeE9VwHuqJMkc2KG0qneVtuc9pVW9I9euFyVJIXcfBbJPUSBntIKZ31E0niNGjKAyNt21f0zIwP1jQhi3BABHK9pES6zJZGp0/vHHH9f5558vs/mbg8clS5ZoyZIlkqQ5c+YoNze3+Qo9AlarNeH3iaZddFHso7IypBdeMOvppy36zW8y9NvfpmvUqKjOO8/QWWcZysxMdqVHjvWFeGJ9IV5YW0g0wusW4quvLNqzx3JE867d2+bKUfWm9nW/U+H0/gmoDgCOj5FWKF/hdPkKp0tRQ9badXLseVdpVe/Ive1xeb56RFFTmoKZwxTIGS1/9iiFPX0lU/N0W1l8W5W97grZa1artv2lqu42i25rADhGXq9XlZWVDecrKyuVnZ3d6JhNmzbpz3/+sySpurpaq1atktls1vDhwxsdN378eI0fP77hfEVFRRwrP1Rubm7C7xPfbtq02MeWLRa99JJTCxa4dPnlVs2YEdWECX5Nm1avMWMCsqf4UznrC/HE+kK8sLYQL0VFRU1eTnjdQpSW2iRJJSXfHF5ba9YqY9Ns+b0TVNf+4kSUBgDNy2RWOL2/atP7q7bTVTJFfLLv+0BpVe8obc+7yvh8tjI0WxGbV4HsUQrkjFIge5SMtIJjujvH7v9T1qc/k6JRVfV7TP68yc38DQFA29KtWzft2LFD5eXlysnJ0bJlyzRjxoxGx9x///2NTg8ZMuSQ4Br4Np07R3T99bW67rparV5t04IFTi1c6NS//uVUdnZEU6b4NXVqvQYPDul/mv8BAEALQXjdQpSV2WSzRdW79+HDa1O4TjnrrpRhy9HeXn8Qr9AAtAZRi1OBnDEK5IyRJJkDO2PjRfa8q7Sqd+Uqf0mSFHL1agiyg1knfvvIJCOojM9/I89XjyqYXqI9fR9iTAgANAOLxaJLLrlEs2fPlmEYGjt2rDp27KhFixZJEnOu0exMJmnQoJAGDQrp9tur9c47aVqwwKVnnnHp8cfd6tw5rKlTfZo6tV5dukSSXS4AADgKpmhTQ+laie3btyfsvuL9tonp072qrjbp9dcPfx9Zn/xMzp3PqbLkWQWzR8atFiQeb8tBPLXo9RU1ZK1br7Sq95S25x2l7f1ApmhAUZM9NmIke5QCOaMV8vRrNGIkNibkStlrVu0fE3KrZE5L4jfSOrXotYWUdri3FKL1S+Tre4nHsZaupsak115zaMECl5YtsysaNWnw4KCmTavXGWf4lZNjJLU+1hfiifWFeGFtIV4YG9KCHdis8fvf9x32GOeuf8q181nVdJpBcA2g7TCZFfb0U9jTT3WdrpAiPqXtWx4LsqveUcbm30qbf6uILSe28WP2aMlsV+aGW/ePCXlU/rzvJvu7AAAAcZCeHtX06T5Nn+7T9u1mLVwYm499661Zuv32qMaODWjq1HpNnOiXw5HsagEAQFMIr1uALVssqq42H3betcX3hTI/u1nBjCGq6fzzBFcHACnE4oyNDskZJXW7TeZA+f4RI+8obc97cpUvlCQFPcXa0+8hRZwnJLlgAACQCEVFhq68sk5XXlmndeusevFFl156yanFi3OUkxPR9Ok+XXBBnTp3ZqwIAACphPC6BSgrO7BZY/DQK42QstddLcmsPX3ul8z8lwLAAUZaO/kKpslXME2KRmWt+0RW3+fye8czJgQAgDaqb9+w+vat1syZ1Vq6NE1PPeXSI4+49eCDHo0Z49eFF9Zr/Hi/rPxqBQBA0vF03AKUltqVlhZVz57hxldEo8rYfLfsNatU1fchRZwdk1MgALQEJpPCnj4Ke/okuxIAAJACLBZp1KiARo0KaMcOs555xqW//92tSy/NUWFhROefX6dzz61XQUFyZ2MDANCWmb/9ECRbWZlNffuGZLcfvMzi26qcNT+SZ+uDqis8X/52309egQAAAADQghUWGrr++lp98MEuzZ1bpV69Qrr33gwNH56vn/wkW+++a5dBhg0AQMLReZ3iDENas8amadP2b9ZohOT56lF5tvxekln7uv1Sde0vTWqNAAAAANAaWK3SpEl+TZrk15YtFv39724984xTr73mVJcuYV1wQZ3OOadeOTnRZJcKAECbQOd1ivv8c4tqa80qKQnKtm+F8lZOVsbnsxXIHqXdw99WXcfLmXMNAAAAAM2sc+eIZs2q1ooVu3TffXuUmxvRnXdmaujQAs2YkaUVK2yKkmEDABBXpJ4prqzMrizXHp3d+TrlrXpSkbRCVfWbK3/epGSXBgAAAACtnsMhTZ3q09SpPq1fb9VTT7m1YIFTCxa41LdvSD/6UZ3OOssnj4ckGwCA5kbndSqLRpW24yV9cm9vtff9XbUdfqLyYW8TXAMAAABAEvTpE9ZvfrNPH320S3ffvVcmk/SLX2RpyJB8zZyZqfXr6Q8DAKA5EV6nKEv9ZuWUnaef9LtUlb6Oqhjymqq7/0pRqyfZpQEAAABAm+Z2R3XBBfV6443deuWV3Zo82a/nnnNp/Ph2mjIlVwsWOOX3J7tKAABaPsLrVGME5NnyJ7VbPk726o/0s/l/0R8+flOh9AHJrgwAAAAA8DUmkzR4cEh/+tNerVixU7/85T5VVpo1Y0a2hg7N1513ZmjzZkuyywQAoMUivE4h9r3/Vd6KicrYco/8uRP0vnep/vjatRpQbCS7NAAAAADAN8jOjuryy+v03nvleuaZCp10UlCPPurWySfn69xzc/T66w6Fw8muEgCAloWBXCnAHKxSxud3ybXzWYUdHVU54EkFvOO0/DmnJKmkJJTkCgEAAAAAR8Jkkk45JahTTglq506znn7apfnz3brsshwVFER03nn1Ou+8OuXmJrtSAABSH53XyRSNyrnzOeV9OErOXQtU0/Fq7R72bwW84yRJZWU2uVyGunXjz/MAAAAA0NIUFBi6/vpa/fe/uzRvXqX69Anpj3/06DvfydcFF1i0cSP9ZAAAfBOeKZPEWrdRmRt+obS97yuYMVSVPeco7OnT6JjSUrsGDAjJwog0AAAAAGixrFZp4sSAJk4M6IsvLHrqKbeefNKtBQvy9IMf+PSzn9WoY8dIsssEACDl0HmdaBG/0jffo7wV42WrXae9Pe9WxaCXDgmuw2Fp3TqbiosZGQIAAAAArcUJJ0Q0a1a1Pv00pMsuq9PChU6dcko73XJLpnbu5Fd0AAC+jmfGBLJXvat2K8Yp/Ys/yZf3fZUPf0f1RRdIpkP/Gz77zCq/38S8awAAAABohfLypNtvr9Z//rNL06fXa/58l0aOzNedd2aoqopf1QEAkAivE8Ic3K2sddcqt+xcSVJl8dPa2/c+Gfa8w96mrMwmSSouDiakRgAAAABA4hUVGbr77n16991ynX66Tw8/7NZJJ7XT73+frpoaU7LLAwAgqRI283r16tWaN2+eDMPQuHHjdOaZZza6/uWXX9Z7770nSTIMQ1999ZXmzp0rj8ejq6++Wg6HQ2azWRaLRXPmzElU2ccnasi14x/K+Pw3MkXqVXPCdarpdK1kcXzrTUtL7UpPN9SlC3PPAAAAAKC1O+GEiP7yl7265ppa3XNPuv7wh3T97W9uXX11rS6+uE5OZzTZJQIAkHAJCa8Nw9DcuXM1a9Yseb1ezZw5U0OHDlWHDh0ajjnjjDN0xhlnSJJWrFihV199VR6Pp+H622+/XRkZGYkot1lYa9cr67NfyF69QoHMk7Sv5xyF3d2P+PZlZTb17x+Smd54AAAAAGgzevYM69FH96isLBZiz56doUcfdWvGjBqdd1690tKSXSEAAImTkGh048aNKigoUH5+vqxWq0aMGKHly5cf9vilS5dq5MiRiSit2ZkiPqVv+o3yVk6SpX6T9vT6gyoHPn9UwXUwGNuskXnXAAAAANA2FReH9NRTVXrppQp17RrWrFlZOuWUdnrmGafC4WRXBwBAYiQkvK6qqpLX62047/V6VVVV1eSxgUBAq1ev1oknntjo8tmzZ+vmm2/WkiVL4lrr8UirfFN5y8cqfev98uVP0+7h78pXOF0yHd2csk8/tSkYNDHvGgAAAADauOHDg3rhhUr94x+Vyssz9POfZ2vs2HZauNAhw0h2dQAAxFdCxoZEo4fO5jIdJtBduXKlevXq1WhkyJ133qmcnBzt27dPd911l4qKitS3b99DbrtkyZKGcHvOnDnKzc1tpu/gW/i2y/bB+fJufUHR9F4KfWexrHmjlHOMX27TptjfFMaM8Sg31/MtR6MtsFqtiVvPaHNYX4gX1hYAAM3DZJJGjw5o1KiA3njDoXvuSddVV+XovvtCuummak2YEDjanikAAFqEhITXXq9XlZWVDecrKyuVnZ3d5LFLly7VySef3OiynJxYDJyZmalhw4Zp48aNTYbX48eP1/jx4xvOV1RUNEf538q561/K2vaKqjvfqNpOV0qmNOk47nvZskxlZpqVkVFxPF8GrUhubm7C1jPaHtYX4oW1hXgpKipKdgkAkBQmkzRpkl8TJvj18stO3Xtvui6+2KtBg4K6+eZqnXIK794FALQuCRkb0q1bN+3YsUPl5eUKh8NatmyZhg4deshx9fX1WrduXaPr/H6/fD5fw+mysjJ16tQpEWUfMV+7sxSa9LFqO18nmY9/94yyMpuKi0P85RwAAAAAcAiLRTrrLJ/efrtc99yzV7t2mfXDH+bq7LO9WrHCluzyAABoNgnpvLZYLLrkkks0e/ZsGYahsWPHqmPHjlq0aJEkaeLEiZKkDz/8UCUlJXI4HA233bdvn+69915JUiQS0cknn6yBAwcmouwjZzJJro5S/fF3l/n90ief2HT55bXNUBgAAAAAoLWy2aTzzqvX1Kn1mj/frb/8xaMpU/I0bpxfN91Urf792dkRANCymaJNDaRuJbZv356w+2qut0avXm3T6afn6ZFHqnT66f5mqAytAW+9RzyxvhAvrC3EC2ND2q5Evr6XeBxDfMVjfdXXm/S3v7n14IMe7d1r1ve+59ONN9aoe3dC7LaGxy/EC2sL8XK41/gJGRuCI1daGnuLV0lJKMmVAAAAAABaEpcrqmuuqdWyZbv0//5fjf797zSNHZun667L0pdfWpJdHgAAR43wOsWUldmUkxNR+/aRZJcCAAAAAGiBMjOjuummGr3/frkuu6xOL7/s1KhR7XTLLZnauZMYAADQcvCslWJKS+1s1ggAAAAAOG5er6Hbb6/W0qW79MMf1mv+fJeGDcvXaaflatasDP3zn05t20ZHNgAgdSVkw0YcGZ/PpM8+s2rCBGZdAwAAAACaR2GhoTlz9unKK2v13HMurVhh17PPujRvnnn/9RENHRrUsGGxj759Q7KSFgAAUgBPRynk44+tikRMzLsGAAAAADS7E06I6MYbayRJ4bC0fr1NK1bYtHy5XcuX2/XKK05JktNpaNCgkIYNC2ro0KCGDAkqMzOazNIBAG0U4XUKKSuzS5KKi4NJrgQAAAAA0JpZrdKAASENGBDSxRfXS5K2bTNrxQq7Vq6Mhdl//atHkYhJJlNUvXqFNWRIsCHQ7tw5wrhLAEDcEV6nkNJSm/LyIiosNJJdCgAAAACgjWnf3lD79n5NmRIbZVlXZ9Lq1bHO7BUrYp3Z8+e7JUl5ebFRIwc+BgwIKS0tmdUDAFojwusUsmaNjc0aAQAAAAApwe2OauTIoEaOjL072DCkzz6zNoTZK1bY9frrsVEjaWlRFRcfnJs9ZEhIXi+NWQCA40N4nSLq6kzasMGq009ns0YAAAAAQOoxm6XevcPq3TusCy+MjRrZvTs2auRAoP3oox498ECsI6tr13DDmJFhw4Lq3j1MsxYA4KgQXqeIjz+2yTBMzLsGAAAAALQYeXmGJk/2a/LkWCOW3x/bzykWaNu0eHGann3WJUkqKQnq6qtrNWmSXxZLMqsGALQUhNcporTUJkkqLg4luRIAAAAAAI6NwyENHx7U8OGxxqxoVPr8c4veey9Njz3m0U9/mqOuXcO66qpaTZ1az5xsAMA3Mie7AMSUldlUUBBRfj4zwQAAAAAArYPJJHXrFtFFF9XrnXfK9fDDVfJ4DN1wQ5ZGjMjXQw+5VVvLLBEAQNMIr1NEaamNkSEAAAAAgFbLYpG+9z2/XnutQk8/XaHu3cO6885MDR+er7vvTldFBREFAKAxnhlSQE2NSZs22RgZAgAAAABo9UwmadSooJ59tlKvvrpbI0cGdN99Hn3nO/m69dZMbd3KQGwAQAzhdQpYsyY277qkhPAaAAAAANB2DBwY0qOP7tHbb5frrLPqNX++SyNHttO112Zp/Xq26QKAto7wOgWUlbFZIwAAAACg7erePaJ7792n99/fpcsuq9Mbbzg0fnw7/ehHOfrwQ3uyywMAJAnhdQooLbWrffuwcnPZrBEAAAAA0HYVFhr65S+r9cEHu3TjjdVatcqms87K1ZlnerV4cZoMfm0GgDaF8DoFlJXZGBkCAAAAAMB+2dlRXXddrT78sFx33bVXO3ZYdNFFXk2YkKcFC5wK8Ss0ALQJhNdJtnevSVu2WBkZAgAAAADA/3A6o7r44nr95z/l+stf9igalWbMyNbJJ7fTvHku+XymZJcIAIgjwuskY7NGAAAAAAC+mc0mTZvm05Ilu/X445UqLIxo1qwsDR/eTn/6k0d79xJiA0BrRHidZGVlsY0nBgwIJrkSAAAAAABSm9ksTZgQ0D//WamXXqrQoEEh3XNPhoYPz9cdd2Roxw5iDgBoTXhUT7LSUps6dQorOzua7FIAAAAAAGgxhg8P6sknq7R4cblOO82vxx5z66ST8nXDDZnauNGS7PIAAM2A8DrJyspszLsGAAAAAOAY9e0b1n337dV//lOu88+v10svuTRmTDv95CfZWr3aluzyAADHgfA6iaqqzNq61cq8awAAAAAAjlOnThHNnr1PH3ywS9deW6ulS9N0+ul5mjIlV/PmuVReTgQCAC0Nj9xJVFYW+wtwcTHzrgEAAAAAaA65uYZuvrlGH364S7fdtk+1tSbNmpWlIUPydfbZXv397y5VVRGHAEBLwKN1EpWWxsLrAQPovAYAAAAAoDl5PFFdcUWd3nxzt956q1wzZtRq506Lbr45SwMH5uv883P07LNO7dtnSnapAIDDILxOojVrbOrSJazMTDZrBAAAAAAgXnr1CuvGG2v07rvleuONcl1xRa02bbLqZz/L1sCBBbroohy9+KJTtbUE2QCQSqzJLqAtKy21afhwRoYAAAAAAJAIJpPUv39Y/fvXaObMGq1ebdPLLzv1yitOLV7skMMR1amn+nXGGT6NHx+Q00mzGQAkE+F1kuzebdb27VYVF9cluxQAAAAAANock0kaNCikQYNCuu22aq1YYdfLLzv0r3859dprTrlchiZM8OuMM/waM8YvhyPZFQNA20N4nSQHNmssKWHeNQAAAAAAyWQ2S8OHBzV8eFC//nW1/vtfuxYudOq11xxauNCl9HRDp50W68g+5ZSA7PZkVwwAbQPhdZKUldlkMkXVvz/hNQAAAAAAqcJikUaODGrkyKBmz96npUvT9PLLTr3+ukMvvOBSVpah737Xp+9/36cRI4KykqwAQNzwEJskpaV2desWlsfD/CwAAAAAAFKRzSaNGRPQmDEB/fa30jvvpOmVV5xauNCpf/zDrdzciL773VhH9ne+E5TZnOyKAaB1IbxOkrIym0aODCS7DAAAAAAAcATS0qSJEwOaODEgn0966y2H77bczgAAHi1JREFUXn7Zqeeec+rJJ90qKIjo9NN9OuMMn4YMCclkSnbFANDyEV4nwc6dZu3aZWHeNQAAAAAALZDTKZ1+ul+nn+5XXZ1JS5akaeFCp556yq25cz1q3z6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      "text/plain": [
       "<Figure size 1800x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "epochs = range(1, EPOCHS+1)\n",
    "fig, axs = plt.subplots(1, 2, figsize=(25, 8))\n",
    "\n",
    "axs[0].plot(epochs, history.history['acc'], color='blue', label='train')\n",
    "axs[0].plot(epochs, history.history['val_acc'], color='orange', label='test')\n",
    "axs[0].set_xticks(range(1, EPOCHS+1, 5))\n",
    "axs[0].set_xlabel('Epochs')\n",
    "axs[0].set_ylabel('Accuracy')\n",
    "\n",
    "axs[1].plot(epochs, history.history['loss'], color='blue', label='train')\n",
    "axs[1].plot(epochs, history.history['val_loss'], color='orange', label='test')\n",
    "axs[1].set_xticks(range(1, EPOCHS+1, 5))\n",
    "axs[1].set_xlabel('Epochs')\n",
    "axs[1].set_ylabel('Loss')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* The best score reaches 0.80 of accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 432x432 with 2 Axes>,\n",
       " <matplotlib.axes._subplots.AxesSubplot at 0x27b3ae372b0>)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_pred = model.predict(X_test).reshape(1, -1)[0]\n",
    "y_pred = np.around(y_pred).astype(int)\n",
    "\n",
    "plot_confusion_matrix(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x27b3ae09970>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "\n",
    "embed = lambda x: d(c(b(a(x))))\n",
    "embedded_text = embed(X_test)\n",
    "\n",
    "twodim = PCA(2).fit_transform(embedded_text)\n",
    "fig, ax = plt.subplots(1, 1, figsize=(10, 10))\n",
    "ax.scatter(twodim[:,0], twodim[:,1], c=y_test, alpha=.6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model's mistakes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>id</th>\n",
       "      <th>keyword</th>\n",
       "      <th>text</th>\n",
       "      <th>target</th>\n",
       "      <th>source</th>\n",
       "      <th>clean_text</th>\n",
       "      <th>pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6845</th>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>We're shaking...It's an earthquake</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>we are shaking it is an earthquake</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6861</th>\n",
       "      <td>70</td>\n",
       "      <td>ablaze</td>\n",
       "      <td>Burning Man Ablaze! by Turban Diva http://t.co...</td>\n",
       "      <td>0</td>\n",
       "      <td>test</td>\n",
       "      <td>burning man ablaze by turban diva via</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6871</th>\n",
       "      <td>103</td>\n",
       "      <td>accident</td>\n",
       "      <td>I hate badging shit in accident</td>\n",
       "      <td>0</td>\n",
       "      <td>test</td>\n",
       "      <td>i hate badging shit in accident</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6872</th>\n",
       "      <td>106</td>\n",
       "      <td>accident</td>\n",
       "      <td>#3: Car Recorder ZeroEdgeå¨ Dual-lens Car Came...</td>\n",
       "      <td>0</td>\n",
       "      <td>test</td>\n",
       "      <td>car recorder zeroedge dual lens car camera ve...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6876</th>\n",
       "      <td>116</td>\n",
       "      <td>accident</td>\n",
       "      <td>For Legal and Medical Referral Service @1800_I...</td>\n",
       "      <td>0</td>\n",
       "      <td>test</td>\n",
       "      <td>for legal and medical referral service call us...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10083</th>\n",
       "      <td>10796</td>\n",
       "      <td>wrecked</td>\n",
       "      <td>'What manner of human being would parcel out a...</td>\n",
       "      <td>0</td>\n",
       "      <td>test</td>\n",
       "      <td>what manner of human being would parcel out a...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10084</th>\n",
       "      <td>10797</td>\n",
       "      <td>wrecked</td>\n",
       "      <td>@Nathan26_RFC thought you said Saturday night ...</td>\n",
       "      <td>0</td>\n",
       "      <td>test</td>\n",
       "      <td>thought you said saturday night there and nea...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10086</th>\n",
       "      <td>10804</td>\n",
       "      <td>wrecked</td>\n",
       "      <td>@yakubOObs think he deactivated because his no...</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>think he deactivated because his notification...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10087</th>\n",
       "      <td>10806</td>\n",
       "      <td>wrecked</td>\n",
       "      <td>RT CNBC '3 words from Disney CEO Bob Iger wrec...</td>\n",
       "      <td>1</td>\n",
       "      <td>test</td>\n",
       "      <td>rt cnbc words from disney ceo bob iger wrecked...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10098</th>\n",
       "      <td>10861</td>\n",
       "      <td>NaN</td>\n",
       "      <td>EARTHQUAKE SAFETY LOS ANGELES ÛÒ SAFETY FASTE...</td>\n",
       "      <td>0</td>\n",
       "      <td>test</td>\n",
       "      <td>earthquake safety los angeles safety fasteners...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>730 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id   keyword                                               text  \\\n",
       "6845      12       NaN                 We're shaking...It's an earthquake   \n",
       "6861      70    ablaze  Burning Man Ablaze! by Turban Diva http://t.co...   \n",
       "6871     103  accident                    I hate badging shit in accident   \n",
       "6872     106  accident  #3: Car Recorder ZeroEdgeå¨ Dual-lens Car Came...   \n",
       "6876     116  accident  For Legal and Medical Referral Service @1800_I...   \n",
       "...      ...       ...                                                ...   \n",
       "10083  10796   wrecked  'What manner of human being would parcel out a...   \n",
       "10084  10797   wrecked  @Nathan26_RFC thought you said Saturday night ...   \n",
       "10086  10804   wrecked  @yakubOObs think he deactivated because his no...   \n",
       "10087  10806   wrecked  RT CNBC '3 words from Disney CEO Bob Iger wrec...   \n",
       "10098  10861       NaN  EARTHQUAKE SAFETY LOS ANGELES ÛÒ SAFETY FASTE...   \n",
       "\n",
       "       target source                                         clean_text  pred  \n",
       "6845        1   test                 we are shaking it is an earthquake     0  \n",
       "6861        0   test             burning man ablaze by turban diva via      1  \n",
       "6871        0   test                    i hate badging shit in accident     1  \n",
       "6872        0   test   car recorder zeroedge dual lens car camera ve...     1  \n",
       "6876        0   test  for legal and medical referral service call us...     1  \n",
       "...       ...    ...                                                ...   ...  \n",
       "10083       0   test   what manner of human being would parcel out a...     1  \n",
       "10084       0   test   thought you said saturday night there and nea...     1  \n",
       "10086       1   test   think he deactivated because his notification...     0  \n",
       "10087       1   test  rt cnbc words from disney ceo bob iger wrecked...     0  \n",
       "10098       0   test  earthquake safety los angeles safety fasteners...     1  \n",
       "\n",
       "[730 rows x 7 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test['pred'] = y_pred\n",
    "model_errors = df_test[df_test['pred'] != df_test['target']]\n",
    "model_errors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x27b3aecfc70>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_unigrams = get_top_grams(model_errors['clean_text'], 20)\n",
    "fig, ax = plt.subplots(1, 1, figsize=(18, 8))\n",
    "\n",
    "df1 = pd.DataFrame(top_unigrams, columns = ['text' , 'count'])\n",
    "df1['count'] = df1['count'].astype(float)\n",
    "df1.plot(x='text', y='count', kind='bar', ax=ax, title='Unigram frequency')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x27b3b9b7c10>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AH6Zfv35pbm7+SJ9jTaiVHEntZJGjsshReWolixyVRY7KUytZ5KgstZIjqZ0stZ5j4cKFK/Xmu1I0Njau1kMQPij/wIEDC/f/0EMVRowYkTPPPLPdtu222y5jx47NpZdemg022CATJ07s5LgAAABAJfvQ4mDo0KHp1atXu23bb799GhoakiRbbLFF2zEZAAAAQG1Z5XMc3H333Rk+fHjh7VOmTMmUKVOSJGPGjEm/fv069PhvHFD82B+4f4f2fs+AiVM7ca+PVmNjY4e/V5WqVrLIUVnkqDy1kkWOyiJH5amVLHJUllrJkdROllrP8cYbb6SxsbpO+bc65+3atWuH/n5X6ZlvueWWNDQ0ZPfddy/cp6mpKU1NTW1fV+JxMpU4U60cU5TUThY5KoscladWsshRWeSoPLWSRY7KUis5ktrJUus5Fi9e3LaKvhqs7nMcLF68eIXvyyqd46DIvffem8ceeywnnnjih157EgAAACpFfX39an0jXk1aWlpSX9+xKqBTKw6eeOKJ3HbbbTnvvPPStWvXzjwEAAAAlEW3bt2yePHiLFmypCo+CO/atWuWLFmyyo9TKpVSX1+fbt26deh+H1oc/OAHP8gzzzyT+fPn55hjjsmoUaMyceLEtLS05Pzzz0+SDBkyJF/72tc6NzkAAACsQXV1denevXu5x1hp5T505EOLg29961srbNt7770/kmEAAACAytLpcxwAAAAAtU9xAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAocYP22HChAmZNm1aevfunbFjxyZJFixYkMsvvzxz5sxJ//79c9JJJ6VXr14f+bAAAADAmvWhKw5GjBiRM888s922W2+9Ndtuu23GjRuXbbfdNrfeeutHNiAAAABQPh9aHAwdOnSF1QSPPPJI9txzzyTJnnvumUceeeSjmQ4AAAAoqw89VOGDvPXWW+nTp0+SpE+fPnn77bcL950yZUqmTJmSJBkzZkz69evXoed6ozMDdlBHZ1oTGhsbK3KuzqiVLHJUFjkqT61kkaOyyFF5aiWLHJWlVnIktZNFjspS7hydKg46oqmpKU1NTW1fNzc3f9RP2WGVOFO/fv0qcq7OqJUsclQWOSpPrWSRo7LIUXlqJYsclaVWciS1k0WOyrImcgwcOLDwtk5dVaF3796ZN29ekmTevHlZe+21OzcZAAAAUNE6VRzstNNOue+++5Ik9913X3beeefVOhQAAABQGT70UIUf/OAHeeaZZzJ//vwcc8wxGTVqVL74xS/m8ssvz913351+/frl5JNPXhOzAgAAAGvYhxYH3/rWtz5w+9lnn73ahwEAAAAqS6cOVQAAAAA+HhQHAAAAQCHFAQAAAFBIcQAAAAAUUhwAAAAAhRQHAAAAQCHFAQAAAFBIcQAAAAAUUhwAAAAAhRQHAAAAQCHFAQAAAFBIcQAAAAAUUhwAAAAAhRQHAAAAQCHFAQAAAFBIcQAAAAAUUhwAAAAAhRQHAAAAQCHFAQAAAFBIcQAAAAAUUhwAAAAAhRQHAAAAQCHFAQAAAFBIcQAAAAAUUhwAAAAAhRQHAAAAQCHFAQAAAFBIcQAAAAAUUhwAAAAAhRrLPcDHxbKj/7VD+7/RiedouOb2TtwLAAAAillxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFGlflznfeeWfuvvvu1NXVZeONN86xxx6bLl26rK7ZAAAAgDLr9IqDuXPn5re//W3GjBmTsWPHprW1NVOnTl2dswEAAABltkqHKrS2tmbp0qVZtmxZli5dmj59+qyuuQAAAIAKUFcqlUqdvfOkSZPyy1/+Ml26dMn222+fE088cYV9pkyZkilTpiRJxowZk6VLl3boOd44YHhnx1tpAyZ+9Csl5Fh5ayJHZzQ2NqalpaXcY6wyOSpLreRIaieLHJVFjspTK1nkqCy1kiOpnSxyVJY1kePvnXag0+c4WLBgQR555JFceeWV6dGjRy677LLcf//92WOPPdrt19TUlKampravm5ubO/uUH5lKnKkz5Pho9evXr2Jn6wg5Kkut5EhqJ4sclUWOylMrWeSoLLWSI6mdLHJUljWRY+DAgYW3dfpQhaeeeirrrbde1l577TQ2NmaXXXbJ9OnTO/twAAAAQAXqdHHQr1+/vPDCC1myZElKpVKeeuqpbLjhhqtzNgAAAKDMOn2owpAhQ7Lrrrtm9OjRaWhoyGabbdbukAQAAACg+nW6OEiSUaNGZdSoUatrFgAAAKDCrNLlGAEAAIDapjgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKBQ46rc+Z133slVV12VP//5z6mrq8s3vvGNbLHFFqtrNgAAAKDMVqk4uP7667PDDjvklFNOSUtLS5YsWbK65gIAAAAqQKcPVVi4cGGeffbZ7L333kmSxsbG9OzZc7UNBgAAAJRfXalUKnXmjq+++mquvvrqbLTRRnnttdcyaNCgHHHEEenWrVu7/aZMmZIpU6YkScaMGZOlS5d26HneOGB4Z8brkAETp37kzyHHypNj5dVKjs5obGxMS0tLucdYZbWSI6mdLHJUFjkqT61kkaOy1EqOpHayyFFZ1kSOLl26FD9/Zx902bJleeWVV/LVr341Q4YMyfXXX59bb701X/7yl9vt19TUlKampravm5ubO/uUH5lKnKkz5Kgscny0+vXrV7GzdUSt5EhqJ4sclUWOylMrWeSoLLWSI6mdLHJUljWRY+DAgYW3dfpQhXXXXTfrrrtuhgwZkiTZdddd88orr3T24QAAAIAK1OniYJ111sm6666bmTNnJkmeeuqpbLTRRqttMAAAAKD8VumqCl/96lczbty4tLS0ZL311suxxx67uuYCAAAAKsAqFQebbbZZxowZs7pmAQAAACpMpw9VAAAAAGqf4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKCQ4gAAAAAopDgAAAAACikOAAAAgEKKAwAAAKBQY7kHAEiSZUf/a4f2f6MTz9Fwze2duFfHfFxzJB3PIsfKWxM5kjWTBQCoPlYcAAAAAIUUBwAAAEAhxQEAAABQSHEAAAAAFFIcAAAAAIUUBwAAAEAhxQEAAABQSHEAAAAAFFIcAAAAAIUUBwAAAEAhxQEAAABQSHEAAAAAFFIcAAAAAIUUBwAAAEAhxQEAAABQSHEAAAAAFFIcAAAAAIUUBwAAAEAhxQEAAABQSHEAAAAAFFIcAAAAAIUUBwAAAEAhxQEAAABQSHEAAAAAFFIcAAAAAIUUBwAAAEAhxQEAAABQSHEAAAAAFFIcAAAAAIUUBwAAAEChVS4OWltbc/rpp2fMmDGrYx4AAACggqxycTBp0qRsuOGGq2MWAAAAoMKsUnHw5ptvZtq0afnMZz6zuuYBAAAAKkjjqtz5hhtuyKGHHppFixYV7jNlypRMmTIlSTJmzJj069evQ8/xxqoMuJI6OlNnyLHy5Fh5tZIjqZ0scqw8OVbemsiRrKEsBwzv2P6deI4BE6d24l4d83HNkXQ8ixwd83H9t1UrOZLK/LclR8dUYpZy5+h0cfDYY4+ld+/eGTRoUJ5++unC/ZqamtLU1NT2dXNzc2ef8iNTiTN1hhyVRY7KUytZ5KgstZIjqZ0sclQWOSpPrWSRo7LUSo6kdrJ0NMfAgQMLb+t0cfD888/n0UcfzeOPP56lS5dm0aJFGTduXE488cTOPiQAAABQYTpdHBx88ME5+OCDkyRPP/107rjjDqUBAAAA1JhVvqoCAAAAULtW6eSIyw0bNizDhg1bHQ8FAAAAVBArDgAAAIBCigMAAACgkOIAAAAAKKQ4AAAAAAopDgAAAIBCigMAAACgkOIAAAAAKKQ4AAAAAAopDgAAAIBCigMAAACgkOIAAAAAKKQ4AAAAAAopDgAAAIBCigMAAACgkOIAAAAAKKQ4AAAAAAopDgAAAIBCigMAAACgkOIAAAAAKKQ4AAAAAAopDgAAAIBCigMAAACgkOIAAAAAKKQ4AAAAAAopDgAAAIBCigMAAACgkOIAAAAAKKQ4AAAAAAopDgAAAIBCigMAAACgkOIAAAAAKKQ4AAAAAAopDgAAAIBCigMAAACgkOIAAAAAKKQ4AAAAAAopDgAAAIBCigMAAACgkOIAAAAAKKQ4AAAAAAopDgAAAIBCigMAAACgkOIAAAAAKKQ4AAAAAAopDgAAAIBCigMAAACgkOIAAAAAKKQ4AAAAAAopDgAAAIBCigMAAACgkOIAAAAAKKQ4AAAAAAopDgAAAIBCigMAAACgkOIAAAAAKKQ4AAAAAAopDgAAAIBCigMAAACgkOIAAAAAKKQ4AAAAAAo1dvaOzc3NufLKK/PXv/41dXV1aWpqyn777bc6ZwMAAADKrNPFQUNDQ77yla9k0KBBWbRoUc4444xst9122WijjVbnfAAAAEAZdfpQhT59+mTQoEFJku7du2fDDTfM3LlzV9tgAAAAQPl1esXB+82ePTuvvPJKBg8evMJtU6ZMyZQpU5IkY8aMSb9+/Tr02G+sjgE/REdn6gw5Vp4cK69WciS1k0WOlSfHylsTOZLaySLHypNj5fl92DFyrDw5Vp7fhx2zOnOscnGwePHijB07NkcccUR69Oixwu1NTU1pampq+7q5uXlVn3K1q8SZOkOOyiJH5amVLHJUllrJkdROFjkqixyVp1ayyFFZaiVHUjtZOppj4MCBhbet0lUVWlpaMmqR/6cAACAASURBVHbs2Oy+++7ZZZddVuWhAAAAgArU6eKgVCrlqquuyoYbbpj9999/dc4EAAAAVIhOH6rw/PPP5/77788mm2yS0047LUnyf/7P/8mOO+642oYDAAAAyqvTxcFWW22Vm266aXXOAgAAAFSYVTrHAQAAAFDbFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRSHAAAAACFFAcAAABAIcUBAAAAUEhxAAAAABRqXJU7P/HEE7n++uvT2tqaz3zmM/niF7+4uuYCAAAAKkCnVxy0trbmuuuuy5lnnpnLL788Dz74YGbMmLE6ZwMAAADKrNPFwYsvvpj1118/AwYMSGNjY4YPH55HHnlkdc4GAAAAlFldqVQqdeaODz30UJ544okcc8wxSZL7778/L7zwQo488sh2+02ZMiVTpkxJkowZM2YVxwUAAADWpE6vOPigvqGurm6FbU1NTRkzZswaKw3OOOOMNfI8H7VayZHUThY5KoscladWsshRWeSoPLWSRY7KUis5ktrJIkdlKXeOThcH6667bt588822r99888306dNntQwFAAAAVIZOFwebb755Zs2aldmzZ6elpSVTp07NTjvttDpnAwAAAMqs4dxzzz23M3esr6/P+uuvn/Hjx+e///u/s/vuu2fXXXddzeN1zqBBg8o9wmpRKzmS2skiR2WRo/LUShY5KoscladWsshRWWolR1I7WeSoLOXM0emTIwIAAAC1r9OHKgAAAAC1T3EAAAAAFFIcwAdobW3N1KlTyz0GVLTZs2ev1DYAgDWhtbU1zz//fLnHqElVXxxMmjQpCxcuTKlUyo9+9KOMHj06Tz75ZLnH6rCXX355hW2PPvpoGSZZdbXwd1JfX5/JkyeXewze57nnnlupbaw5Y8eOXaltlW7JkiX59a9/nauuuipJMmvWrDz22GNlnqpjWltbc8opp5R7jNXi7rvvXmHbL37xizJMwnILFy7MDTfckDPOOCNnnHFGfvazn2XhwoXlHutja+nSpbnzzjtz6aWX5tJLL82dd96ZpUuXlnusDquFn73L/epXv2r3dWtra8aNG1emaT7e6uvr87Of/azcY9SkxnIPsKruueee7LfffnniiSfy9ttv5xvf+EZ+9KMfZfvtty/3aB1y9dVX57jjjssmm2ySJPn973+fSZMmVeUlLmvl72TbbbfN7bffnuHDh6dbt25t23v16lXGqVbeT37yk797+1e/+tU1NMnqcf311+fiiy/+0G2VbubMmbn99tvT3NycZcuWtW0/55xzyjhVx7z++uv585//nIULF+YPf/hD2/ZFixbl3XffLeNknTNhwoQMGjQoL7zwQpJk3XXXzWWXXZZ//Md/LPNkK6++vj6bbrppmpub069fv3KPs0oeeuihrLXWWtl9992TJNdee21V/rv6+c9/nn/7t39Lly5dctFFF+W1117L4Ycfnj322KPco3XYhAkTsskmm+Skk05Kktx///2ZMGFCTj311DJPtnIOO+yw1NXVrbC9VCqlrq4uP/3pT8swVeddccUV6d69ez73uc8lSR588MFcccUVOfnkk8s8WcfUws/e5ZqbmzNx4sQccMABeffdd3PZZZflE5/4RLnH6rC33347U6ZMyZw5c9q9Rjn22GPLOFXHbb/99nnooYeyyy67fOD//Wrx2GOP5Ve/+lXmzJmT1tbWsv/MqvriYPlFIR5//PHstdde2WyzzVKNF4o4+eSTc9lll+WEE07Ic889l/vvvz9nnXVWucfqlFr5O7nnnnuSpN3Kg7q6ulxxxRXlGqlDll+u5fnnn8+MGTMyfPjwJO+9KK+mX2bTp0/P888/n7fffjt33nln2/aFCxemtbW1jJN1zuWXX5599tknTU1Nqa+vzkVfM2fOzLRp0/LOO++0+3SoW7du+frXv17GyTrnjTfeyEknnZQHH3wwSdKlS5cyT9Q58+bNy8knn5zBgwena9eubdtHjx5dxqk67tRTT83FF1+curq6PPHEE+nVq1eOOuqoco/VYU8++WQOPfTQPPzww+nbt29OPvnknHfeeVVZHLzxxhvtSoKDDjoop512Whkn6pha+/Rx1qxZueSSS9q+3mabbarq72O5WvnZm7z3xnrcuHGZOHFinn766eywww7Zf//9yz1Wh33/+9/PVlttlW233bZqX6MkyZ133pklS5akvr4+Xbp0Kfsb7s664YYbcuqpp2aTTTapiAKk6ouDQYMG5YILLsjs2bNz8MEHZ9GiRRXxje2oAQMG5Jvf/GYuueSS9OvXL2eddVbV/gCtlb+TK6+8stwjrJIRI0YkSe67776cc845aWx877/7PvvskwsvvLCMk3VMS0tLFi9enGXLlmXRokVt23v06FF1n64k730y/M///M/lHmOV7Lzzztl5550zffr0bLHFFuUeZ5U1NjZm6dKlbT+n/vKXv7T9f6kmBx10ULlHWCULFixo+/MxxxyTSy65JFtuuWVGjhyZBQsWVM1qr+WWf1o3bdq07LbbblU3//t16dIlzz33XLbaaqsk7x0mVq2vUZLkrbfeareKpdpW6Wy22Wbtfv6+8MIL2XLLLcs8VcfVws/e9x9qvN9+++XHP/5xttxyywwdOjQvv/xy24c41WLJkiU59NBDyz3GKquVsrBfv37ZeOONK+Z9VF2pGj8Kfp/W1ta8+uqrGTBgQHr27Jn58+dn7ty52XTTTcs92ko55ZRT2v1jeOutt9KjR4+stdZaSZJLL720XKN1WrX/nSy3ZMmS3HnnnWlubs7Xv/71zJo1KzNnzqy6JXTf/OY3c+GFF7a9aF2wYEG+853v5Ic//GGZJ+uYOXPmpH///kne+ze2ePHi9OjRo8xTddxNN92U3r1751Of+lTb//Okeg6BSWrvMJg//vGP+c1vfpMZM2Zk++23z/PPP59jjz02w4YNK/doHTZnzpzMmjUr2223XZYsWZLW1tZ079693GOtlOOOO67d78P3vzypptVey/3iF7/II4880naowsKFCzNmzJhcdNFF5R6tw1599dVceeWVbec16NmzZ4477riq+73+6KOP5mc/+1nmzZuXtddeO83Nzdlwww1z2WWXlXu0DjnppJMyc+bMtsJjeY66urrU1dVVzWvHWvjZe9555/3d26vpMMQk+a//+q9sscUW2XHHHcs9yip79NFH88wzzyRJhg0bVnWv35PkxRdfzK9+9asMHTq03WvGcq1mqfrioFQq5YEHHsjs2bMzcuTINDc3569//WsGDx5c7tFWypw5c/7u7cvfKFWTDzrRY48ePdK/f/80NDSUYaLOufzyyzNo0KDcf//9GTt2bJYuXZrvfOc77ZYHVoN77rknN998c9sv4meeeSYHHXRQ24qEavHDH/4wRx99dOrr63PGGWdk4cKF2X///fOv//qv5R6tQ4477rgVtlXbm6J77733795ebf+2FixYkFKplBdeeCGlUilDhgzJ4sWLs95665V7tA6ZMmVK7rrrrixYsCDjx4/PrFmzcs011+Tss88u92grrbW1NdOnT2/7ZLvaLViwID169Eh9fX0WL16cxYsXZ5111in3WB02e/bsrLfeem3FQY8ePdq2VZPTTjstZ599ds4///x8//vfz5/+9Kc8+OCDVXeIVS29dpw/f367n71rr712uUf6WDvssMOyZMmSNDY2tr1mr8Yl/r/4xS/y0ksvZbfddkvy3nlABg0alEMOOaTMk3XMBRdckG7duq1wqEK5VhhW13qgD3Dttdemrq4uTz/9dEaOHJlu3brluuuuy/e+971yj7ZSquWToI647rrr8vLLL2fTTTdNqVTKn//852y66aaZP39+jj766Ko5SWKtHHu311575ZOf/GTbyYcOOeSQqnzhOmPGjPTo0SMPPPBAPvnJT+aQQw7JGWecUXXFQbUfApNUXzHwYS6++OJ8+9vfbvuEZcaMGbn88sur7goRkydPzve+972ceeaZSZINNtggb731Vpmn6pj6+vrceOONVXU4VZElS5Zk8uTJbavW5s2bV5Wr1pL3rpZy8cUXt1vltXxbNWloaMg//MM/pFQqpbW1Ndtss01VXrGjf//+efXVV9uuLLTVVltls802K+9QnfDcc89ls802y4477pj7778/EydOzH777VdVxcdy//mf/5kvfOEL6dmzZ5L3SsM777wzX/7yl8s8WcfUyhL/xx9/PN///vfbztMwYsSInH766VVXHCxYsKCiznlX9cXBiy++mIsvvjinn356kveW+7a0tJR5qpU3evTo1NXVfeDJA6vtU8jl+vfvn2OOOSYbb7xxkvdehN9+++058MADc+mll1ZNcVDtx9797cqPddddN0kyd+7czJ07t+qOu1u2bFlaWlryyCOP5HOf+1waGxsr5pivjmhpacn//M//5Nlnn03y3vK5pqamqvq3tdzbb7+dW2+9Na+//nq7S4FV29LMAw44oK08mDlzZq644oqceOKJ5R6rw9Zaa612/46WLVtWlf9HauVs2MvPGD99+vQk1XnG+Fq7gkrPnj2zePHibL311hk3blx69+5dVSshl5s0aVLuuuuufOpTn0qSjB8/Pk1NTdl3333LPFnHXHvttbnkkkvy6quv5o477shee+2VK6644kOX/1eiJ554IgcffHDb17169crjjz9edcVBUhtL/JP3TqK9/DDQar187Lbbbpsnn3yyYt47Vd8r1b/R0NCQ1tbWthcXb7/9dlW90KiFTx//1uuvv95WGiTJRhttlFdeeSUDBgwo41Qdd9BBB+XCCy9Mc3Nzxo0b13bsXbW48cYb/+7t1fbmrqmpKccdd1w222yzbL311pkzZ05Vrti59tpr09LSks9+9rNJ3rus2bXXXptjjjmmzJN13Lhx4zJ8+PA8/vjjOfroo3PvvfdW5TLTHXfcMS0tLbnggguyaNGinHbaadlggw3KPVaHDR06NLfcckuWLl2aP/7xj5k8eXJVvuCrlbNh18KqtVq7gsppp52WLl265PDDD88DDzyQhQsXZuTIkeUeq8PuvvvuXHjhhW2Xiv7CF76Qs846q+qKg4aGhtTV1eXRRx/Nvvvum7333jv33XdfucfqlNbW1rz77rttx6EvXbq0Ksu1v13iP2nSpDz33HNV90n9F7/4xZx++ukZNmxYSqVSnn322XbFTrWYPHlybr/99jQ2NqaxsbHsvw+rvjjYd999c8kll+Stt97KL3/5yzz00ENV2e4l7y1H+ctf/tLuk7uhQ4eWcaLOGThwYK655pr80z/9U5Jk6tSp2WCDDfLuu+9W1aeq22+/fdv1hUulUo444oiqelNUbcXAh9lvv/2y3377tX3dv3//qsz40ksv1cRltJL3jk3de++9M2nSpAwdOjRDhw6tqr+Tvz3J46JFi7Leeuvlt7/9bZLqO8njIYcckrvuuiubbLJJfve73+WTn/xkPvOZz5R7rA6rlaWy1b5qLam9K6gsf6OdVPchV6VSqd2l8urr66vystfdunXLxIkT88ADD+S8885La2trVa0afr/dd989//Ef/5G99toryXvnl9pzzz3LPFXH1coS/9122y3Dhg3LSy+9lFKplEMPPbTqDtNtbW3NmWeeWVHn/Kmu32AfYPfdd8+gQYPy1FNPJXmvTd5oo43KPFXH3XXXXZk0aVLmzp3b7jI71fQifLnjjjsukydPzv/9v/83pVIpW221Vb7yla+koaGhqvJcfPHF+ad/+qfstNNO7V5sVIs//elP2WabbdotL32/XXbZZQ1PtGr++te/5pe//GXmzZuXM888MzNmzMj06dOz9957l3u0Dqmvr89f/vKXrL/++kne+1SyWq+VvPxNUJ8+fTJt2rT06dMnc+fOLfNUK+9vD9eptsN33q+1tTWnnXZaxo4dm6ampnKPs8pqoUgfNWpUVa9ae7/1118/t9xyS+bMmdN2mckkVZfnD3/4Q37xi1+0nfuj3J/eddZee+2V73znO9l5552TJI888kjbG9ZqctJJJ+X3v/99jjnmmKyzzjppbm6uuvMWLfeFL3whm266af74xz8mSQ488MDssMMOZZ6qc2phif/y82fstNNOuf/++3PbbbdV3fkzKvGcP1V/VYXp06dn4403bluyvGjRosyYMSNDhgwp82Qdc8opp+R73/te21n7X3/99dx000056aSTyj3ax9YzzzyTqVOnZtq0aRk8eHCGDx+eHXfcsWqWm950000ZNWpUJkyY8IG3V9sLvosuuigjRozIxIkTc8kll2TZsmU5/fTTq+4Edk899VQmTJiQAQMGpFQqpbm5Od/4xjeyzTbblHu0Dnvsscey9dZbp7m5Oddff30WLlyYgw46KDvttFO5R/tYGjduXA4++OCquyb936qlIr1Wzhh/1llnZauttsqgQYPaFZ277rprGafquBNOOCGjR4+uyg+Y/tbLL7/cdnLErbfeOp/4xCfKPFHHtLa25sILL8x3v/vdco+y2vz1r3/Niy++mLq6ugwePDi9e/cu90gd9vvf/z7/+Z//ucIS/+WriKvFqaeemksuuSSvvfZarrzyyuy11175wx/+UHXnz7jpppuyySabVMw5f6p+xcG1117b7qy+Xbt2XWFbNejSpUvbG9J33303G264YWbOnFnmqTrnueeey80335zm5uZ2n0xU24kely+9bm1tzZ/+9KdMmTIlP/rRj6rmk4lRo0Ylqb6CoMj8+fMzfPjw3HrrrUneOzayGj+p33bbbTNu3LjMnDkzpVIpG264Ybtr81aT5cfPb7LJJlX5pu6yyy7LySefnFNOOeUDfyFXy7XQl5s3b15OPvnkDB48OF27dm3bPnr06DJO1XGTJk1qK9LPOeectiK92jz88MPZZptt2q7W8c477+Thhx9uO6FdNVmyZEkOPfTQco+xytZZZ52aKA3Gjx+fE044od0qqeXbqsXyc5gsXLiw3dU6qtXUqVPz85//vG1l1E9+8pN85StfqbpyrRaW+Ce1c/6MSjvnT9UXB8u/gcvV19e3e7NaLfr27Zt33nknO++8cy644IL07Nkzffv2LfdYnXLVVVfl8MMPX+GTiWq0dOnSPProo5k6dWpeeeWVqjxe7YQTTsiQIUOy1VZbZejQoVX7oqlr166ZP39+2//36dOnV9WLjaJDR954440k1XfoSJL8/Oc/z7/927+lS5cuueiii/Laa6/l8MMPzx577FHu0VbKv//7vydJzjjjjDJP8v+1d+dxUZbr/8A/M7LjAsSSGxKZCiKiSCFa4ZIaR/Lk1slyq8zU0/coipCGuYuAuC+RW2qcr+Fy6iiGuSKKKBIu4ICCGwwKBMgywAzM/P7gO8+PESgHzHvux+v9lzy8Xr4+vBhmnue67/u6ng1Wc52fNbEU0mNiYnSKBJaWljhw4ACXhQNPT0+kpKQIRRBeOTs7Y+3atfDy8tIp2PL2/puTk6PztVqtbjBJiQfGxsaYO3cu3N3ddYqdvPWXAYDDhw9j1apVwi6D0tJSLFu2jJvCQW5uLjp27Ci8jrTPILxO4hJL/wxD6/nDfeHAwcEBsbGxGDZsGADg+PHjsLe3Z5xKf9rmaOPHj0d6ejoUCgW3Z6MsLCzQp08f1jFabO3atbh9+zZ69+6NESNGwNXVlctCSGRkJG7dugWZTIa9e/ciNzcXXbp04a4h36RJkxAWFoaHDx8iJCQEpaWlCAgIYB3rqaWnp8PNzU2nM3l9vN24AsDVq1fx8ccf49KlS7CxsUFAQACWLFnCTeHA2toaALg68/hHXF1dUVBQgLy8PLi7u6O6uhpqtZp1LL2JpZDe2ElQHhc2gLpdIIcPH4aRkZEwvpDH3gCVlZUwNTUVzqFr8fL+e/jwYRw+fBhKpRKTJ08GUPc6MzIy4rK3Sd++fbkvRmmp1WqdowmtW7fm6v33yJEjmD59epMTuXjbVSim/hmGNB6T+x4Hjx8/xq5du3Djxg1IJBK4ublhypQp3J0ramyLGW/bzrR++OEHqNVqvPHGGzodpHmrVqampsLd3Z3LYkF9tbW1yMrKQnp6OmQyGcrKytClSxd8/vnnrKM9NbVajdjYWLz77rvCFv8OHTpw16EcAPLz8xsUNxu7xoOAgABERkZi27Zt8Pb2hoeHBwIDA3WmRhiySZMmNXpEgfVWwOY6ceIETp48ifLycmzcuBF5eXn47rvvsGjRItbRmq1+IZ23v/ctW7bA0tISw4cPh0QiwbFjx1BRUYFZs2axjkY4Fx0dzeVoucbU1NQIO4p4/VwH6kZg379/X2eimKOjI3dHfJRKZYNeXo1dI8/Hk+Mxz58/D2dnZ2ZTLvj866ynXbt2mD17NusYLSaWbWcAcPv2bQBokJ+XaqV2S3l1dTUuX77c4Pu8rExoTZ48GY6Ojhg5ciSGDBmCNm3asI6kN6lUiuTkZIwcORKdO3dmHadF1qxZ06AHS2PXeODp6YnZs2fDxMQEn332GUpLS7nq12BoWwBbKi4uDqtWrcKCBQsAAO3btxe6x/NG2/hNIpGge/fuXD5MfPLJJzh48CDWrVsHjUaD3r17czsuGjCsVa/m+v3337Fz505kZGQIr62pU6fipZdeYh1NL3379kVVVRXMzMwQHx+PO3fucNcxHgDS0tKwefNmIXdhYSFmzZrF3QQVAJg4cSIuXryIjIwMaDQaDB06lMtjSSEhIQ3uRxq7ZujEMkHF0MZj8vdJ/H9++uknjBo1qsEcbi1ezkeJbdsZwE+BoCli21L+r3/9CzKZDHFxcTh58iS6d+8OFxcX9OrVi3U0vXTv3h07duyAj4+PzllIXnay5Obm4sGDB1AoFDp9DiorK6FSqRgma76PPvoIo0aNgoWFhdC4Z/78+axjvbCMjY11HrBra2sNoguzvg4cOIDExEThvXbr1q3w9vbGmDFjGCfTj5mZGXezz5vy5KpXbGwsZDIZdz/fli1bMHDgQOGY27lz57BlyxbuOvtv374d4eHhuHv3Ln7++WcMHjwYmzZt4q5j/J49e/D111+jQ4cOAAC5XI7169dz95Cq5e3tzU1PgyeVlJSgqKgISqUSd+7cEY5aVVZWorq6mnE6/e3bt080E1QMaTwmt4WDjh07AuDnoaEp77//Pt5//31RbDuLj4/HW2+9hSNHjjT6/ZEjRz7nRM0zfvx4qNVqeHh4wMfHh3WcFvPy8oKXlxdyc3Px22+/ITY2Fj/99BN++OEH1tH0kpmZCQANuqvzUqiSy+VISUlBRUWFTlHKzMwM06dPZ5isZbQfZkDdz2JmZsYwzYvN1dUVhw4dglKpxLVr1xAXF8flqvD58+exevVqYWvs3//+dwQFBXFTONi9ezemTJmC0NDQRgs3vE25AAxv1au5SktLMWjQIOFrX19fHD16lGGi5qnfMd7Pz4/bjvG1tbVC0QCoO6rAax8Q3le4U1NTcfbsWfz+++86u/HMzMzw4YcfMkzWPGKZoPL3v/8d8+fP1xmPyfL3wW3hQDsnvEuXLtzNrm0M70UDAEJFsrKyknGSlpNKpYiLixNF4SAiIgL37t3Dyy+/jB49euCf//wnunbtyjqW3ngpEDRFW8DRzqQn5FmbMGECTp06BUdHR/z666/o06cPhgwZwjqW3uzs7KBSqXQmKzg4ODBO9fS0zUF5bcTVFENa9Wqutm3bIj4+Xtg5kZCQwOXxPbF0jHd2dsbWrVuFv5lz585xuyDI+wq3r68vfH19cfHiRW53TdQnlgkqhjYek/vmiEuWLEFxcTG8vb0xYMAA7s8/E8Nx4MABmJiYwMfHR2cVtf4KKw9u374titGYCoUCMTExuHnzJoC61dWxY8dyNZIRqGsydOrUKeTk5ECpVArXZ86cyTDVi62qqgomJiaQSqWQy+WQy+VcNuMTi7CwMGRlZcHd3R0SiQTXrl1Djx490LZtWwD8HEW8dOkS+vTpw1Xfj6YkJCQgOjq6waqX9gGcF4WFhdixYwcyMzMhkUjQrVs3TJ06lbveACUlJUhISMCrr74KFxcXFBYWIi0tjbuR0SqVCnFxcZDJZNBoNHBxccHw4cO5/JsJCQnBsmXLWMd4JlJSUvDgwQOdY5Rjx45lmEh/W7ZsafQ6b/daS5cubdDguLFrzwv3hQOg7g30woULSExMhEKhgI+PDzdbGsWkqX4TWrzc7Gk11vlaIpFg06ZNDNKQiIgIODo6CjdG8fHxuHfvHubNm8c4mX4iIyPRoUMHnD9/HmPGjEFCQgI6duyIqVOnso7WLEVFRSgoKNDZXspbY6ugoCAsXboUFRUVWLhwIZydnWFqaor/+Z//YR3tqcydO/cPexlEREQ8xzQtd+bMmT/8vq+v73PJ0VJbtmzBjRs34OLiggEDBqB3797CKEMeFRcXC6ter732GtNVL0IMza5du1BSUsL9CndUVBSUSiXS0tIwePBgXLx4EV27dsWMGTNYR3uhKJVKKJVKLFmyRGfHrUKhwKpVq7B27VomuUSxeDBghAAAIABJREFUnGJlZQU/Pz+4ubnhp59+woEDB7gpHJSXl//h93la3dZuL8vIyEBOTo6wzf/ixYtcHifZvHkz6wiknkePHukUCcaNG4fAwECGiZrn4cOHCAgIQHJyMnx9fTFw4ECsWLGCdaxm2bdvHxITE9GpUyfhwVUikXBXOAAAU1NTnDp1CiNGjMCoUaO4avIYHBwMoG6qAgCdbb/1G4nygpfCwJ+ZOXMmampqkJqaioSEBGzfvh3u7u744osvWEfTm3aFS3tMtP41HoilobbYyGQyxMTEoLCwUKf4zOMCTWVlJUxNTXHt2jWd67wVDjIzMxEREYF58+Zh3Lhx8Pf35674DNT1ldq+fTseP36MNWvW4N69e0hOTubm+fDEiRM4evQoiouLERwcLDSrtLCwwPDhw5nl4r5wkJOTgwsXLiApKQmtW7fGgAEDMGnSJNaxnlpQUBAkEgka2/jB2+q29mbv7Nmz+Oabb4Rtvu+88w63D0a802g0+P3332Fra8s6SouZmJhAJpOhR48eAOpuOHicK6xdcbS0tMT9+/dhZWWFgoICxqma5/Lly1i3bh2X20rr02g0yMzMREJCgvBQx1ODLu0264yMDJ2tsh999BFCQkK422IqJkZGRvDw8ABQt4J0+fJlrgoH2lWvsrIynYUOhUKB4uJihsn0I5aG2mKzbds2TJ48WRTHKSdNmtRgsS8/P59RmubT3leZmpqiqKgIbdq04fLn+PbbbzFx4kRERUUBqOuJt2HDBm4KB35+fvDz88OxY8fw7rvvso4j4L5wsHXrVgwYMAALFy6EjY0N6zh6E+OqdlFREaqqqoQ30KqqKhQVFTFO9WKSSCQIDw/ndrRRfdOmTcPmzZuFplyWlpaNHicxdEOHDkV5eTk++OADhIWFoaqqCuPHj2cdq1kcHBxQW1vLfeFgypQpOHz4MLy8vNC5c2c8evQIPXv2ZB1Lb1VVVTrFtYyMDFRVVTFO9eJKTU3F+fPnkZaWBldXVwwePBhz5sxhHUsvhrrqpS/tTglTU1P0799f53uJiYksIrVIbGws/Pz8/vSaobOwsECfPn1Yx3gmVq9eja+++krou5STk4O1a9dizZo1jJPpp2/fvqioqIC/v7+wuDl48GDWsfSmVCobNALnsThlZWWFyspKmJub4+DBg7hz5w5Gjx7NrAjKdeFArVbDwcGBuzfKppSXl+Phw4c6DdN43PJbf3QIAKSnp2PcuHGMU724XnvtNdy+fZvLSQrA/78ZqqqqQnh4uFA44K0popa2y72rqytXO4oaY2JigsDAQPTq1UunkSBv235tbW11RuQ5ODgI2/15MmPGDGzdulXnb4TOpbJz5swZ+Pj44PPPP+e2uGaoq17N9Z///KdB4aCxa4bu7NmzDe59z5w5w839cHZ2NgCgZ8+e2Lt3L9544w2dzxAed4a8//77QvFALpdj06ZN3PTJqU+7Q83b2xuenp5QqVRc3m+1adMGDx8+FI5RXrx4EdbW1oxT6e/gwYPo378/ZDIZrl69Cn9/f2zfvh0rV65kkofrwoFUKkVZWRlqamq473598uRJxMbGoqioCE5OTsLINh5H0A0aNAh9+vTBrVu3ANRtl+WxiZKhdTJtrrS0NPz666+wt7eHqampMFuYlzNrp0+fhp+fH3bt2oXVq1dz+QEGAEeOHPnD748cOfI5JXl2+vXrp3PmmVdr1qxBUFCQsGstPT0dO3bs4GqlSK1WIz09neviWmho6B82eaxf3DF0arUaZWVleP3111lHeSZ4Lxr89ttv+O2331BUVKTT56CyspKrVciEhAQkJCQgPz9fZydhZWUlV2Ml9+7dq/O1tpCgxeO9b9++fVFTU4Ply5ejsrISgYGBaN++PetYzZKRkdGg6TFvEzs+/fRTREVFITc3F9OnT4e9vT2+/PJL1rH0pn1/SklJwbBhw+Dl5YWYmBhmefh+2kbd2c6QkBB4enrqjMzj7SY8NjYWq1atwsKFC/HNN98gNzcXP/74I+tYennyjf+ll14CUHd0oaioiJsKsljOdGotWLCAdYQW6dixI2bNmoXS0lKd5oi8FUAqKytZR3jmfH19UVNTA7lcDgDo0KEDl0XcadOmITw8HEFBQcjOzsa///1vfPXVV6xj6UUqlSI5ORkjR47krmCg9d5777GO8MxIpVKYmJhAoVBw+/sQE2trazg7OyM5OVnnXsTc3ByTJ09mmEw/3bt3h7W1NcrKyuDv7y9cNzMzQ5cuXRgm0w+PhYGmPNlws7KyEvb29jh27BgA/nbgbdy4EY8ePYKTk5NOUY23woGDgwNCQkJQVVUFjUYDc3Nz1pGaxcbGBlFRUbh+/TpGjRoFlUrVaF+854W/O7wnWFtbw9raGhqNhusbcxMTE6EhiUqlQseOHYWbcV48WUF+Ei8fFPXPdNZf4eLtTKeWnZ0dZDIZ8vLyMGjQIJSWlnJ17nn27NkoKSnBihUruOp0/yQxHtdJS0vD5s2bheZ8hYWFmDVrFndHrLp27YqpU6di+fLlMDY2RkhICNq2bcs6lt66d++OHTt2wMfHR2eaAi9FW95eN3/G2NgYc+fOhbu7u87vg7cHCTFwcnKCk5MTBg4cyGVxU8vOzk5YMDMxMYFUKoVcLodcLoejoyPreC+kJ99feXm/bUp2djYiIyP/cPcXD2JjY+Hr6wtzc3N8++23uHPnDiZMmIDevXuzjqaXOXPmIDU1Ff7+/rC0tERxcTE+/vhjZnkkGpZli2eoqqpKZ8cBb8LDwzFz5kwcPXoUaWlpsLS0RG1tLXerXmIiljOdMTExyMrKQl5eHtavX4+ioiKsXbtWp/s6+euJcRxYUFAQ/vWvf6FDhw4A6sYfrV+/nptmnE9ujc/JyYG1tTUsLS0B8LU1HgCWLFnS6HVeirZaeXl5iI6ORk5ODlQqlXCdt54gZ86cafQ6j+MmZTIZnJycYGZmhvj4eNy5cwd+fn5C0ZAXYnltBQUFYenSpaioqMDChQvh7OwMU1NTLs/UE8MSGRmJqVOnctkPoL7AwECEh4cjNTUVcXFx+OCDD7B161Zu7k8MFb9l1/+TmZmJrVu3oqqqClu3bsXdu3dx4sQJfPbZZ6yj6UU7j378+PFIT0+HQqEQRjjx4saNG3Bzc0NSUlKj3+dllq02v42NTaM/Cy8/h9alS5cQFhYmPATZ2NhwvTuHV2IcB1ZbWysUDYC6owo8jTEU09Z4gL8CQVO2bNmC8ePH4/vvv8eCBQtw+vRp1pGaxdfXF0qlEoWFhTp/Jzzavn07wsPDcffuXfz8888YPHgwNm3a1GSxylCJ5bUF1E2IOHXqFEaMGIFRo0ZxvSOPGI6ysjIEBASga9euOrtzeCuka9fFf/vtNwwaNAhOTk5Mt/iLBfeFg927d2PhwoUICwsDULcd7ebNm4xTNc+T28mLiopgb2/POtZTS09Ph5ubG65cudLo93l54G4qvxYvP4eWkZERJBKJsLLK0zEFMdE2EeRxtbEpzs7O2Lp1qzCB4Ny5c1wVRupvjS8pKUFWVhaAuqML7dq1YxWr2Q4cONDodW2XbF4olUr06tULGo0GdnZ2GD9+PBYtWsTd2NLk5GTs3bsXNTU12Lx5M+7evYv9+/dzdwMOAK1atYJEIkFycjL8/PwwePBgnD17lnUsvYnltaXRaJCZmYmEhAR88cUXAMBV0bapBSYt3u6zxEQsxyqdnZ2xfPly5OfnY8KECaisrOT++IUh4L5wANSN0qqPpw65WvW3kw8aNAg1NTXYuHEjV9vJtR+8M2fOZJykZXjP/6T+/fsjKioKFRUVOHHiBE6fPi2MBCTPn1wux3//+98GHYt5XC2eNm0a4uLicOzYMWg0Gri4uHDZB+TChQvYt2+fUEjYuXMnJk6cCG9vb8bJ9FP/HL1KpcKVK1eEnS48MTExgVqtRvv27fHLL7/AxsYGjx8/Zh1LbzExMVi1ahUWL14MoG5hIz8/n22oZjIzM8Phw4cRHx+PpUuXQq1Wo6amhnUsvYnltTVlyhQcPnwYXl5e6Ny5Mx49eiSMwOaBdoHm8ePHyMzMFLKnpaWhZ8+eVDhgyNXVVRSF9C+++AJ3796Fg4MDTE1NUVZWxuX9/b59+xr0NGjs2vPCfeHgpZdeQkZGBiQSCWpqahAbG8vljZKYtpOLZdULqBt/8uDBA52zkLz9HO+99x6uXbsGc3NzyOVyfPDBB3B3d2cd66mJaUQbAKxduxbvvPMOhgwZwmWRsz5jY2OMHDmSuyk2Tzp8+DBWrVol3ByVlpZi2bJl3BUO6ndZ136t3Y3Hk8mTJ0OpVGLq1KnYv38/bty4gVmzZrGOpbdWrVo1mKjA64rXnDlzkJCQgBkzZsDKygqFhYVcHvURy2vL1dUVrq6uwg5CBwcHrvrkaB/gQkNDERkZKZynLy4uxo4dO1hGaza5XI6ff/4ZhYWFXC8KiKWQLpVKdXZAtmnThquRpVrXr19vcC01NZUKB801bdo07N69G0VFRfjiiy/g7u6OTz/9lHUsvYlpO7lYVr2ioqKgVCqRlpaGwYMH4+LFi+jatSvrWHo7cuQI+vfvz1WxoD4eb07/iFQqxbBhw1jHaJHIyEgEBARg7ty5jT4I8TIiU0utVuusqLRu3RpqtZphomejuroajx49Yh1Db9r3WTMzMy5XiLQ6d+6MhIQEqNVq5OXl4dixY+jWrRvrWM1iZWWFN954A3l5eQDqbsJff/11xqn0J5bXllj6exUUFOg04WvXrp3wGuONdlFg6NChXC8KiKWQzrvjx48jLi4O+fn5OqPIKysr0b17d2a5uC8ctG3bVhRdZMW0nVwsq16ZmZmIiIjAvHnzMG7cOPj7+3P3QATUvcmsWLECrVu3ho+PD7y9vWFlZcU61lMTy4i28vJyAICnpyfi4uLw+uuvw9jYWPh+69atWUXT29SpUwEAwcHBjJM8Gx4eHlixYgUGDBgAoG7FpU+fPoxT6a9+IUetVqO0tJS7HVKAeFbuPvnkExw6dAjGxsZYv349evfujTFjxrCO1SwnTpzAyZMnUV5ejo0bN6KoqAjfffcdFi1axDqaXsTy2hJLfy9XV9cG7708HbmoTwyLAoB4C+m8GThwIDw8PBAdHY2PPvpIuG5ubs70fpH7wsG+ffswevRomJiYYOXKlbh37x4mT54sNOvigUajgY+PD+RyObfbyf8Ir6teJiYmAOp2UBQVFaFNmzZcnk8dN24cxo0bh3v37uHChQtYvHgxXnrpJYSEhLCOphfex2gFBQVBIpEIXX1//vln4XsSiYSbnwOAsEIUFxdnUGfvmmvixIlISkqCTCaDRqPB0KFDuVxNrV/IadWqFdq1a4dWrVoxTNQ8Ylm5MzU1xYcffogPP/wQarUaVVVVwucKb+Li4rBq1SosWLAAANC+fXsuewOI5bUFiKO/16effoqkpCSh6MHrey8gjkUBQDyFdKCuCFJSUqJT+Hjy78ZQWVhYwMLCAv/4xz9gZWUFY2NjpKWl4d69e3j77beFsdHPG/eFg6tXr+Ljjz/GpUuXYGNjg4CAACxZsoSrwoFEIkF4eDhWr14timKBWFa9+vbti4qKCvj7+wsPfYMHD2Ydq9natWsHKysrtGnThssbPt7HaG3evJl1hGfO0M7etUT37t2FzvE8HkkCADs7O5SXl+P3339HbW0tSkpKAPA3AlQsK3fr16/HtGnTIJVKERwcDIVCgZEjR3J5/MrY2FhnNFttbS2X/RrE8toSS38voG6CghiaIWqnjPC8KACIp5B+7NgxHDhwAO3atRPeqyQSCXc7h9esWYPQ0FA8fPgQ27Ztg6enJzZs2ICvvvqKSR7uCwfarWYpKSkYOHAgd5U9rddeew23b9/m9oa1PrGsemmLHd7e3vD09IRKpWrQ6IoHx48fx4ULF1BaWgpvb29Mnz4dnTp1Yh1Lb7yP0bpx4wbc3NyaHEPF042ToZ69ay6xNIP63//9X5w9exYODg46D3W8bcMWy8pdTk4OLCwscO7cOfTp0wcfffQRgoODuSwcuLq64tChQ1Aqlbh27Rri4uLg6enJOpbexPLa4r2/16RJkxotPGk0GkgkEnz//fcMUrWMWBYHtLsG69+T8LiTMDY2FuvWreOyIWJ9UqkUrVq1QlJSEvz8/PDuu+9i/vz5zPJwXzjw9PTE7NmzYWJigs8++wylpaU6Hwa8SEtLw4kTJ2BnZwdTU1PhzZO3yhhQt+qVnZ0NmUwGiUSCHj164JVXXmEdS2+JiYnw8PCAubk5fv75Z9y5cwdjxozh7mcpKCjAlClT4OTkxDpKi/A+Ris9PR1ubm7CGKon8VQ4MNSzd80llmZQiYmJ2Lhxo87KMI/EsnJXW1uLmpoaXL58GSNGjBCaIPNowoQJOHXqFBwdHfHrr7+iT58+XPZhEsNrS61WY/fu3Vz399qzZw/rCM9cTU0Njh8/Lhy76NmzJ4YOHcrd+7FYdhLa2tpyudj3pFatWiEhIQHx8fHCFLH6/VmeN4lGe+CWY+Xl5bCwsIBUKkVVVRWqqqq4av4G1D3cNcbOzu45J2m5AwcOIDExUXgQunz5Mry9vblrCjVv3jxERERAJpMhOjoa/v7+OHz4MFauXMk62lNRKBSwsLAQmvI9ibcHvNu3b6NTp06oqKjA/v37oVAo8N5773HbpVxMHj9+rNN3gpczhFpz587FmjVrhK/VajUCAwN1rvEgIiIC06ZN43LmthjFxsbip59+gpOTE4KDg1FYWIiNGzdi6dKlrKPpTdufQXuOXq1WQ6VS6UxRIs/PihUrEBQUxN1DqZbY7k8AYNu2baipqYGvry8AID4+HlKpFF988QXbYE+p/k5CBwcH4bp2JyFvhaqtW7dCLpejb9++OgvKvI2PzsnJwfHjx9GtWzcMHDgQ+fn5uHDhAv7+978zySOKwgExLHPmzMHq1auFJlBKpRJBQUFYu3Yt42T6mT9/PsLCwhAdHQ1HR0cMHDhQuMaD0NBQBAcHY9asWTpN+QD+VljERKVSISkpCfn5+ToNe3jsA5KcnIw9e/aguLgYbdu2RWFhITp27IjIyEjW0fSyd+9e3L9/X6cZlKOjI3crLFlZWQgLC4Ojo6POA4V2lYIXYlm5e5JGo4Fareby6N7ChQsREhICMzMzAHWFhOXLl2P58uWMk72YoqKicOfOHXh6egq/E4Cfh6L69ydP4vX+JDAwEOHh4X96zVApFAqUl5eLZidhTExMo9fHjRv3nJOIC9+fwsQg2dnZQaVSCYUDlUqlU73khY2NDaKionD9+nWMGjUKKpUKPNXZgoODodFosGTJEu5WgBsjljFaYWFhsLCwgLOzM5fHqurbv38/VqxYgWXLliEsLAw3btzA+fPnWcfS28SJE3Hx4kVkZGRw3Qxq8+bNGDVqFBwdHbnssK61fft21NTUYPjw4QDqVu62b9/OzcpdUyQSCZdFA6BuAaD+A6qZmRmqq6sZJnqxWVtbw9raGhqNBpWVlazj6E3bC0ssfQGAurPoDx8+xMsvvwwAePToEVfvw9ou/rNnz4ZMJkNeXh4GDRqE0tJS5Ofnw97ennVEvWgLBJWVlZBIJDrvXzzRLv49iVVxjQoH5JnZuXMnAMDIyAgBAQFwd3eHRCLBtWvX0KNHD8bp9DdnzhykpqbC398flpaWKC4u5m4Fsv7EDt6JZYxWUVERFi5cyDrGM9GqVSu0adNGWEl1c3PDDz/8wDpWs3h7e3PX0+BJbdq0gZ+fH+sYLZaVlaWzSufm5obAwECGiYiZmRmys7OFCR3Z2dncjpYUA7E8FG3atAk9evSAi4sLt1MhtD7++GMsWbIEDg4O0Gg0KCwsxIwZM1jH0ltMTAyysrKEwkFNTQ02btyIZcuWsY6ml/v372PTpk3CcZg2bdrgn//8Jzp37sw4mX5CQ0OFf6tUKiQmJjZ5xOd54L5wEBERgcGDB8PDw4Prhwkx0N5QODs766zWaTuV88bU1FSnYZ22ws8bsUzsEMsYrW7duuH+/ftwdHRkHaXFLC0tUVVVBRcXF2zYsIG7CSpi6+zt7OyM6Oho9OvXT2dbP4/jGHleufsjKpWKy51GkydPxtq1a4XPwOLiYsyZM4dxquZJTk5Geno6gLr7k379+jFOpD+xPBT5+vpCJpNh586dyM/PR5cuXeDq6splAbRXr17YsGED5HI5NBoNOnbsyOXf+qVLlxAWFiYccbOxseFyV0tUVBQmTZoENzc3AHVN6L/99lvujlc9ORXib3/7G0JCQvDBBx8wycN94WDYsGE4c+YMdu3aBW9vb/j6+nJfteSVtiEMMSximdghljFaMpkMZ86cgb29PYyNjbn9fQB15zdNTEwwefJknDt3DgqFgqteDWLr7H337l0AwK1bt3Su83acRywrd1u2bMHMmTOFr6uqqhAWFoZFixYxTNU8Xbt2xdq1ayGXywEAHTp04LLnRHR0NG7fvo2BAwcCqJv1npmZiQkTJjBOph+xPBS5ubnB1dUVt2/fRlpaGn799Vfk5ORwVThoatTyo0ePAPA1MQmAMP1FW1SvqqpinKh5qqurhb8PoK5XDo/Hq7Kzs4V/azQaZGVlMf2d8Peu/wR3d3e4u7tDoVAgISEBy5cvx0svvYQhQ4bgzTff5PKDjZBnacGCBawjPBNiGKMFiOf3AUBneywVDtnjrUDQFLGs3NnY2OC7777DtGnTUF5ejtDQUO5GGDb1UJSXlweAv4eilJQUhIWFCTtYfH19MX/+fO4KB2J5KFq6dCmqq6vx2muvwcXFRWcsLi/ENGoZAPr374+oqChUVFTgxIkTOH36NHfvWwBgb2+PAwcO4K233gIAnDt3jstJdXv37hX+LZVKYWdnx3S3lyieqsvKynDu3DnEx8fDyckJb775JmQyGc6ePYvFixezjkcIUzy+UTZGLE2U7OzsoFarUVJSojNVgSdi2+JPDIPYVu7+8Y9/YN++fUIH/FGjRnHXR0NsD0VAXfd47U41hULBOE3ziOWhyNHREXfu3MGDBw9gYWEBS0tLmJubc9U/Y/z48QDqJiM92UAwPz+fRaQWee+993Dt2jWYm5tDLpfjgw8+gLu7O+tYepsxYwZ+/PFHrFmzBhqNBi4uLjo7wHhhaAsC3I9jjIiIQG5uLt566y34+vrqnEEPDg7WaSpBCOGXWEa0HTt2DAcOHEC7du2Eh29ejyoQ8iz9+OOPGD9+PLZs2dLo93m56atf+NBoNDh48CC6du0KDw8PAHw+bKvValH0mUhISEB0dDR69uwJjUaDmzdv4sMPPxSOLvCivLwcP/74IzIyMgAALi4uGDt2LHdH97Sqqqpw+vRp/Pe//0VJSQmio6NZR9JbUFBQg0bUjV0j5GkcOXLkD7/PavQqX3fcjRgxYoTOdq36qGjARmhoaIPVSAsLC7z66qsYOnQoV5VkYjjEMqItNjYW69ata9DwhicKhQIWFhZNdvbl9eaVsCWWlbsnV+dfeeUV1NbWCtd5LBzMmjULHh4e8PHxgZubW6M7jngwcOBA9OzZE1lZWdBoNPj4449hZWXFOtZT27hxI7788kvEx8fjk08+YR2nxX755RfcvHkT2dnZsLOzw6BBg+Di4sI6ll5yc3Px4MEDKBQKnaJhZWUlVCoVw2T6aWonoRYvOwl3796NKVOmNPosAkBo+mjotA0p5XI5srKyhCauV65cYfo3wn3hICcnB6+88gosLS0B1FVhz58/LzxckOfPwcEBpaWlGDBgAADgwoULaNeuHeRyOb799lt8+eWXjBMSHollRJutrS0sLCxYx2iRDRs2IDg4GEFBQZBIJKi/cY3HvhNikZiYCA8PD5ibm+PgwYO4c+cORo8ezd1UhTVr1jRYpWvsmqGaOXMm1Go1YmNjma0KPWvr169HcnIy4uLisG3bNvTt2xcDBgzgbtTy0qVLsWjRIp1JCtprPMjOzkZBQQFOnz4tHFOoj7eirVKpxMiRI+Hs7MzVRJ765HI5UlJSUFFRoVM0NDMzw/Tp0xkm04+2WfD+/fthZWWFt956CxqNBgkJCVxNVdD+Xbz33nuMk7SMduTq8uXLsXr1apibmwvXIyMjmeXivnBw8uRJjBgxQvi6devWOHnyJBUOGLp79y6WLFkifN2vXz988803WLJkCQICAhgmIzwTy4g2e3t7LF68GH379tVp+MbTA0ZwcDAA8fSdEIuDBw+if//+kMlkuHr1Kvz9/bF9+3asXLmSdbSnIpaVO6Du/erKlStc/V3/ERMTE/j4+MDHxwfl5eXYvXs3vvnmG+zfv591tKeiVCqhVCpRVlams1NKoVCguLiYYTL9vPPOO1i5ciUePXqE4OBg7ou2vD/cAYCXlxe8vLyQmZmJbt26sY7TYlevXtX5zBg2bBgWLFiAUaNGMUz19LSF8rt37zaYzhEbG8vdiPjCwkKdI7lGRkYoKChglof7woFGoxEacgF15/BqamoYp3qxlZaWorCwELa2tgDqXvSlpaUAwN15dGI4xDKizdbWFra2tqipqRHFe1VRUREKCgpQW1srXOPtg1kstIW0lJQUDBs2DF5eXoiJiWGc6umJZeVOq1u3btixYwd8fHxgamoqXOdtB4hWeno6Lly4gN9++w2vvvoq087e+jpx4gSOHj2K4uJinQduCwsLrhaa/Pz84OfnJ0zrIOz99NNPGDVqFBISEpCQkNDg+7wdKZFKpTh37pywa/j8+fNcLtKcPXu2QeHgzJkzXI36BOp2UCxYsABeXl6QSCS4dOkS3n77bWZ5uG+OuHfvXhQUFOCdd96BRCLB8ePHYWtri0mTJrGO9sJKSUnBd999h5dffhkajQb5+fn47LPP4OrqipMnT+Jvf/sb64iEUyqVivsRbWKyb98+JCYmolOnTjqNHnk5Qyg2oaGhsLGxwfXr1xEaGgoTExMsWLBA54gwQQ4pAAAXwUlEQVQPD8Sycld/5119htYl+2nMmjULTk5O6N+/P/r166czipUnx44dw7vvvss6BhGR5ORk9OvXD2fOnGn0+7yNKs7Pz8fu3buFxpvdu3fHlClTGvSdMVTaAk5GRobOUaqqqipIpVKEhIQwTNc82dnZkMlkAOoaob7yyivMsnBfOFCr1Thx4gSuX78OjUaD3r17Y8iQIVxWx8REpVIhNzcXANChQwdqiEiarakRbVq8NRorLS3FTz/9hJycHCiVSuE6jw8T//rXvxAREUEFHANRXV2N1NRUODo6on379iguLsb9+/fRu3dv1tH0olQqcerUqQZ/I7xMVRAbtVqNQ4cOYezYsayjPBMZGRkNdkmxXMEjhDw7BQUFyM/PR3R0ND766CPhupmZGbp06cJtLw1Dwf2+calUimHDhmHYsGGso5B6tA18amtrce/ePQD0wUyaR2xzxDds2AAfHx+kpKRg2rRpOHPmDNq2bcs6VrM4ODigtraWCgcGori4WOidkZaWhnv37nH5vrtp0yZ06NABV69exZgxY5CQkICOHTuyjtUsKSkpePDggU6PBt4ewKVSKdLS0rjL3ZiNGzfi0aNHcHJy0llg4vHvhBgWuVyO//73vw2KUjwuCvDMzs4OdnZ2WLFiBesoosR94UAmkyEmJgaFhYWora0V+h3w1iBGTOiDmTxLYhnRplVWVobBgwcLTXpcXV25u7HYuXMngLqGaYGBgejVq5dO/xLeznSKxZo1axAaGoqHDx9i27Zt8PT0xIYNG/DVV1+xjqaXhw8fIiAgAMnJyfD19cXAgQO5vAmMioqCUqlEWloaBg8ejIsXL6Jr166sYzWLWPo1ZGdnIzIykttxksRwrV27Fu+88w7tejYQmZmZ2LVrF3JyclBTUwO1Wg0zMzNuxkoaKu4LB9u2bcPkyZPh7OxMf6gGgj6YyV+B9xFtWtoHbGtra6SkpMDa2hpFRUWMU+lH+7Dg7OysM9aMsCWVStGqVSskJSXBz88P7777LubPn886lt60W0ktLS1x//59WFlZMe0i3VyZmZmIiIjAvHnzMG7cOPj7+yMiIoJ1rGbJzMwEAPz4448613krenbu3BklJSWwtrZmHYWIjHYHNO9UKlWDXYTl5eXcjfrcuXMnZs+ejcjISISGhuLs2bN4+PAh61jc475wYGFhgT59+rCOQeqhD2byLIlpRBsAjB49GgqFAhMnTsSuXbugUCgwefJk1rH0wluzpxdFq1atkJCQgPj4eKFBZf0ts7wYOnQoysvL8cEHHyAsLAxVVVXCziOeaHv7mJqaoqioCG3atOFylxTAX4GgKWVlZQgICEDXrl11dklRQ1fSUp6enoiLi8Prr7+u8+DN2wN3REQEAgMDhb+P4uJihIaGcrdIAwAvv/wy1Go1pFIpBg0ahK+//pp1JO5xXzjo2bMn9u7dizfeeEPnQ4C37XNiQh/M5FkS24g2T09PAICjoyO3N+ORkZEICAjA3LlzG91ZxOuqKu9mzpyJ48eP4/3334e9vT3y8/Px5ptvso6ltyFDhgCoG+vJ87HDvn37oqKiAv7+/ggKCoJEIhF+Nt6UlJTg3//+N4qLi7FgwQLk5OQgMzMTgwcPZh1NL+PGjWMdgYjU2bNnAQA///yzcI3Ho9NeXl6IjIzEvHnzUFhYiLCwMEycOJF1LL2ZmpqipqYGTk5O2LdvH6ysrFBdXc06Fve4n6ogpnFHYpGent7odZrtTlpCLCPaxKC4uBjW1tZNbh+3s7N7zomImKhUKiQlJSE/Px9qtVq4znNzPpVKBZVKBQsLC9ZRmmXlypXw9fXF4cOHER4ejtraWsyfPx9r1qxhHU1vJSUlyMrKAgB07doV7dq1Y5yIEMPyyy+/IDU1FQUFBfj888/RvXt31pH0VlBQgHbt2qGmpgZHjx6FQqHA8OHD8fLLL7OOxjXudxxQgcDwUIGA/BWcnJzwyy+/0Ig2A6A9hkQFAsOSl5eH6Oho5OTk6Bzj4W3FKywsDBYWFnB2duZ6YodSqcTx48eF+ds9evTAsGHDuBxPXFZWBh8fH/znP/8BUHcshse+UhcuXMC+ffuE+5SdO3di4sSJ8Pb2ZpyM8K6xkdEWFhZwdHTkojh15MgR4d8ajQa///47nJyccOvWLdy6dQsjR45kmE5/2vsTExMT2mn0DHFfOBDL9jkxCAkJwbJlyzBp0iSd7cvaSRfUyZS0hJhGtIlFUlISfvjhBzx+/BgA/a2ztmXLFowfPx7ff/89FixYgNOnT7OO1CxFRUVYuHAh6xgttmnTJpibm2PEiBEAgPPnz2PTpk0ICAhgnEx/pqamKCsrEz7bMzMzudw9cfjwYaxatUp4kCstLcWyZcuocEBa7NSpU8jMzETPnj0B1O2+fe2115CXl4exY8firbfeYpzwj1VWVup8/frrrzd6nRdPTt3T4q2Qbmi4Lxxs2bJF2D4HAO3bt8fatWupcMDAsmXLAAB79uxhnISIkVhGtJWVlSEmJgYZGRkA6lYhx44dizZt2jBOpr99+/YhKCgInTp1Yh2FoG6Fu1evXtBoNLCzs8P48eOxaNEi7hoLduvWDffv34ejoyPrKC2Sl5eH8PBw4Ws3NzcEBgYyTNR8kyZNQlhYGB4+fIiQkBCUlpZyWQBRq9U6q7+tW7fWOQ5DSHNJJBKsXbsWVlZWAOoWNrdv346VK1fim2++MfjCgdhW5Wnq3l+D+8KBWLbPiY1arUZJSYnOB7KtrS3DRIR3YhnRtm7dOri4uGDu3LkAgHPnzmHdunUICQlhnEx/VlZWVDQwICYmJlCr1Wjfvj1++eUX2NjYCLtBeCKTyXDmzBnY29vD2NhY2MnCW9NNJycnnd4st27d4vKsMFDXcHrx4sWQy+XQaDTo0KGDTvNjXnh4eGDFihUYMGAAgLqjCzSZizwLBQUFQtEAANq1a4e8vDy0bt1auH/hwbJlyxAQEABLS0sAdaMY169fz90uMJq699fg713/CWLZPicmx44dw4EDB9CuXTvh98LjTR8xLGIZ0VZeXq7T5G3MmDG4fPkyw0TN5+zsjLVr18LLy0vnLPobb7zBMNWLa/LkyVAqlZg6dSr279+PGzduYNasWaxj6W3BggWsIzwTt2/fRnx8vFA0LywsRMeOHYVpJDx9JiYmJsLDwwOdO3fGwYMHcefOHYwePZq7CVYTJ05EUlISZDIZNBoNhg4dKmzJJqQlXFxcEBoaKhx7SUpKgouLC6qqqoSHcB6Ulpbq5G3dujWXBWiauvfX4H6qQnZ2Nnbt2iVsa9Run+vSpQvraC+sL7/8EitXruRy6zUhf7U9e/bg1VdfRf/+/QEAFy9eRE5ODpdFkC1btjR6nRpWEoI/3RHFU3PRefPmISIiAjKZDNHR0fD398fhw4excuVK1tH0sm/fPnz88cd/eo0QfWk0GqEoBdQdQ3zjjTcaHVlsyIKCghAYGCgUPAsKChAREYHVq1czTqYfmrr31+B+x4FYts+Jia2tLe36IM+cWEa0nThxAkePHsXGjRsB1N1smJqa4siRI9w1FqQCgWHJysrCoUOHGjSD4mllW0x4Kgz8Ge0R0JSUFAwbNgxeXl6IiYlhnEp/169fb3AtNTWVCgekxSQSCby9vblvtPnhhx8iJCREmDxy8+ZNfP7554xT6Y8KBH8N7p+wnxx/kpeXx9X4EzGyt7fH4sWL0bdvX53ty7yNciGGRSwj2sTUPLS0tBQnTpxAQUGBzoMqFRTY2LBhAyZOnAhHR0fuVrmIYbOxsUFUVBSuX7+OUaNGQaVSgacNq8ePH0dcXBzy8/Mxb9484XplZSW3fSeIYRDbRDEPDw+sXr0at27dAlB3BK5t27aMU+lPoVAgJiYGN2/eBFA3Kn7s2LG0sNlC3B9VWLVqFdfjT8SoqVUIsXVsJc/X3LlzsWbNGtYxnonk5GSkp6cDqDuH5+npyThR83z99dfo0aNHg67FvK+48Ep7A0vIs1ZdXY3U1FQ4Ojqiffv2KC4uxv3799G7d2/W0Z6KQqFAeXk5oqOj8dFHHwnXzc3N0bp1a4bJCDE8YrhHiYiIgKOjI95++20AQHx8PO7du6dTOCT6437HAe/jT8RGrVYjLy8P//M//8M6ChEZsYxo++GHH5CVlYWBAwcCAGJjYyGTyXRuZnlRXV1NW3wNyPjx47Ft2za4ublRs0ryTJmamuq8jqytrWFtbc0wkX4sLCxgYWGB2bNns45CiEFr7B4lIyMDEyZMYJxMP48ePdIpEowbN47bcbiGhPvCgVjGn4iFVCpFWVkZampqqNcEeabEMqLtt99+Q1hYmLBC7+vri/nz53NZOPD09ERKSgr69u3LOgoBcPr0acjlctTU1OjsAKHCASGEkKfR1D0Kb4UDExMTyGQy9OjRA0DdPaSJiQnjVPzj/slOLONPxMTOzg4hISHw9PSEmZmZcJ16HJCWEMuINqBu26x2e6xCoWCcpvliY2Nx+PBhGBkZwcjIiNsznWJx79490RznIYQQwoYY7lGmTZuGzZs3C/ktLS25HE9saLjvcQDUjTPjffyJmFCPA0KalpCQgOjoaPTs2RMajQY3b97Ehx9+KGwLJKS5tm3bhpEjR6JTp06soxBCCOFQY/coEyZMwIABA1hH00t+fj7s7e2FwoGFhYVwjTQf14UDtVqNwMBAWmEhhHCluLgYWVlZ0Gg0eO2113SOW/GmvLwcDx8+hFKpFK5pxziR52vOnDl4+PAh98d5CCGEsCOGe5SgoCCsXr36T68R/XB9VEEqlaJLly4oLCyEra0t6zjk/yxZsqTR6zRTlRBg6dKlWLRoEfr169fgGm9OnjyJ2NhYFBUVwcnJCZmZmejWrRv9rTMipuM8hBBC2NBoNGjTpg1qa2shl8shl8u5WRDIzc3FgwcPoFAokJSUJFyvrKyESqVimEwcuC4cAHVVsYCAAHTt2hWmpqbC9aCgIIapXmwTJ04U/q1UKpGUlESNKskLT6lUQqlUoqysDOXl5cJ1hUKB4uJihsmaLzY2FqtWrcLChQvxzTffIDc3Fz/++CPrWC8sOzs71hEIIYRwbN++fUhMTESnTp2EY98SiYSbwoFcLkdKSgoqKipw5coV4bqZmRmmT5/OMJk4cF84oHPzhsfZ2Vnn6x49etAKJHnhnThxAkePHkVxcTGCg4OhPSVmYWGB4cOHM07XPCYmJkKXYpVKhY4dO0IulzNORQghhJDmuHz5MtatW6cz0pcnXl5e8PLyEnZAkmeL+8KBq6srCgoKkJeXB3d3d1RXV0OtVrOO9UKrv5qqVquRnZ2NkpIShokIYc/Pzw9+fn44duwY3n33XdZxngkbGxtUVFTAy8sLy5cvh6WlJWxsbFjHIoQQQkgzODg4oLa2ltvCgVbr1q2xdOlSPH78GGvWrMG9e/eQnJyMMWPGsI7GNe4LBydOnMDJkydRXl6OjRs3oqioCN999x2X54XFIigoCBKJBBqNBq1atYK9vT1mzJjBOhYhBsHKygqVlZUwNzfHwYMHcefOHYwePbrBTh0eBAYGAgDGjx+P9PR0KBQKeHh4ME5FCCGEkOYwMTFBYGAgevXqBSOj//+Y+MknnzBMpb9vv/0WEydORFRUFACgS5cu2LBhAxUOWoj7wkFcXBxWrVolNIVq3749Hj9+zDjVi23z5s2sIxBisA4ePIj+/ftDJpPh6tWr8Pf3x/bt27Fy5UrW0VqEl/OPhBBCCGlcv379dJo380qpVKJr164616RSKaM04sF94cDY2FinIlZbWys08yBsKJVKHD9+HDKZDEBdj4Nhw4YJZ6EJeZFpP7hSUlIwbNgweHl5ISYmhnEqQgghhLzoHB0dG+yATE5OZpSm+dq0aYOHDx8Kz4QXL16EtbU141T847704urqikOHDkGpVOLatWuIjIyEp6cn61gvtE2bNuHBgwcYMWIERowYgdzcXGzatIl1LEIMgo2NDaKiopCYmIg+ffpApVIJjRIJIYQQQlj59ttvcf/+feHrhIQEHDp0iGGi5vn000/x3XffITc3F9OnT8fRo0fx2WefsY7FPYmG8ztWtVqNU6dO4dq1a9BoNOjduzeGDBlCuw4YCgwMRHh4+J9eI+RFVF1djdTUVDg6OqJ9+/YoLi7G/fv30bt3b9bRCCGEEPICe/ToESIjI/Hll19CJpMhPj4ewcHBsLCwYB2tWaqqqqDRaGBubs46iihwXzgghmfz5s145513hDEot27dwtmzZ6nSRwghhBBCiAGTy+UIDw+Hra0tAgMDuTpqfOTIkT/8/siRI59TEnHivsfBlStXsH//fhQUFECtVkOj0UAikeD7779nHe2FM3fuXEgkEtTW1iI+Ph62trYAgMLCQnTq1IlxOkIIIYQQQsiTtPfwWuXl5VCr1ULz+YiICFbR9FJZWQmgrviRlZUlNHq8cuUKXFxcWEYTBe53HHz55ZeYN28eHB0d6XgCYwUFBX/4fTs7u+eUhBBCCCGEEPI0xHYPv3z5csydO1c4olBZWYnIyEgsXLiQcTK+cb/jwNbWFp07d6aigQHg7U2FEEIIIYSQF53Y7uELCwt1pu4ZGRn9aXGE/Dnudxzcvn0b+/fvh6urK4yNjYXrdIaFEEIIIYQQQl4shw4dQmJiIry8vCCRSHDp0iX4+Pjg/fffZx2Na9wXDpYvXw4zM7MGRxXGjRvHMBUhhBBCCCGEEBays7Mhk8kAAC4uLnjllVcYJ+If90cVysvL8fXXX7OOQQghhBBCCCHEADg7O8PZ2Zl1DFGRsg7QUr169cLVq1dZxyCEEEIIIYQQQkSJ+6MKkyZNQnV1NYyMjGBkZETjGAkhhBBCCCGEkGeI+8IBIYQQQgghhBBC/jrcH1XQaDSIj4/HgQMHANSN37h9+zbjVIQQQgghhBBCiDhwXzjYvn07MjMzcf78eQCAmZkZduzYwTgVIYQQQgghhBAiDtwXDm7fvo3PPvsMxsbGAIDWrVujpqaGcSpCCCGEEEIIIUQcuC8ctGrVCmq1GhKJBABQWloq/JsQQgghhBBCCCEtw31zxHPnzuHChQu4c+cO3n77bVy8eBH/+Mc/0L9/f9bRCCGEEEIIIYQQ7nFfOACA3NxcXL9+HQDg5uaGTp06MU5ECCGEEEIIIYSIgygKB4QQQgghhBBCCPlrcN/jgBBCCCGEEEIIIX8dKhwQQgghhBBCCCGkSVQ4IIQQQgghhBBCSJOocEAIIYQQHbNmzcK1a9cM5v8hhBBCCFtUOCCEEEIIIYQQQkiTaKoCIYQQQgQbN25EQkICjIyMIJVKMXbsWLi4uGDPnj3IycmBnZ0dpkyZgp49eyIjIwNhYWFYvXo1bG1tcffuXSxevBgrVqzAoUOHGvw/o0aNYv3jEUIIIaQZqHBACCGEEB2zZs3C9OnT4e7ujqKiIsybNw///Oc/4eHhgRs3bmDdunVYt24d2rZti3//+9/IzMzEV199hQULFmDo0KEYMWJEg/+HEEIIIfyiowqEEEIIaVJ8fDz69OmDvn37QiqVwt3dHa+++ipSUlIAAOPGjYNCocBXX30Fa2trDB8+nHFiQgghhDxrRqwDEEIIIcRwFRYW4uLFi7hy5Ypwrba2Fj179gQAGBkZwdfXF7t27cLkyZMhkUhYRSWEEELIX4QKB4QQQghp0ksvvYQ333wTX3zxRaPfLyoqwoEDB+Dr64s9e/Zg1apVMDY2fs4pCSGEEPJXoqMKhBBCCNFhZWWF/Px8AMCbb76JK1euIDU1FWq1GkqlEmlpafj999+h0WiwefNmDBo0CDNmzIC1tTX279/f6P9DCCGEEH5Rc0RCCCGE6Lh8+TJ27tyJyspKjB49Gi4uLti3bx/u378PqVSKrl27Ytq0abh06RJOnTqF0NBQGBkZoaioCIGBgZg3bx5cXFwa/D/vvfce6x+NEEIIIc1AhQNCCCGEEEIIIYQ0iY4qEEIIIYQQQgghpElUOCCEEEIIIYQQQkiTqHBACCGEEEIIIYSQJlHhgBBCCCGEEEIIIU2iwgEhhBBCCCGEEEKaRIUDQgghhBBCCCGENIkKB4QQQgghhBBCCGkSFQ4IIYQQQgghhBDSJCocEEIIIYQQQgghpEn/D1DqP9m7dGLrAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1296x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_bigrams = get_top_grams(model_errors['clean_text'], 20, gram=2)\n",
    "fig, ax = plt.subplots(1, 1, figsize=(18, 8))\n",
    "\n",
    "df1 = pd.DataFrame(top_bigrams, columns = ['text' , 'count'])\n",
    "df1['count'] = df1['count'].astype(float)\n",
    "df1.plot(x='text', y='count', kind='bar', ax=ax, title='Bigram frequency')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x27b3adf47f0>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_bigrams = get_top_grams(model_errors['clean_text'], 20, gram=3)\n",
    "fig, ax = plt.subplots(1, 1, figsize=(18, 8))\n",
    "\n",
    "df1 = pd.DataFrame(top_bigrams, columns = ['text' , 'count'])\n",
    "df1['count'] = df1['count'].astype(float)\n",
    "df1.plot(x='text', y='count', kind='bar', ax=ax, title='Trigram frequency')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "nlp",
   "language": "python",
   "name": "nlp"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}