image-captioning.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5"
   },
   "outputs": [],
   "source": [
    "# This Python 3 environment comes with many helpful analytics libraries installed\n",
    "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n",
    "# For example, here's several helpful packages to load in \n",
    "\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "\n",
    "# Input data files are available in the \"../input/\" directory.\n",
    "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
    "\n",
    "import os\n",
    "# Any results you write to the current directory are saved as output."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0",
    "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running.....\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "from keras.preprocessing.sequence import pad_sequences\n",
    "from keras.preprocessing.text import Tokenizer\n",
    "from keras.models import Model\n",
    "from keras.layers import Flatten, Dense, LSTM, Dropout, Embedding, Activation\n",
    "from keras.layers import concatenate, BatchNormalization, Input\n",
    "from keras.layers.merge import add\n",
    "from keras.utils import to_categorical\n",
    "from keras.applications.inception_v3 import InceptionV3, preprocess_input\n",
    "from keras.utils import plot_model\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import cv2\n",
    "import string\n",
    "import time\n",
    "print(\"Running.....\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000268201_693b08cb0e.jpg#0\tA child in a pink dress is climbing up a set of stairs in an entry way .\n",
      "1000268201_693b08cb0e.jpg#1\tA girl going into a wooden building .\n",
      "1000268201_693b08cb0e.jpg#2\tA little girl climbing into a wooden playhouse .\n",
      "1000268201_693b08cb0e.jpg#3\tA little girl climbing the stairs to her playhouse .\n",
      "1000268201_693b08cb0e.jpg#4\tA little girl in a pink dress going into a wooden cabin .\n",
      "1001773457_577c3a7d70.jpg#0\tA black dog and a spotted dog are fighting\n",
      "1001773457_577c3a7\n"
     ]
    }
   ],
   "source": [
    "token_path = '/kaggle/input/flickr8k/flickr_data/Flickr_Data/Flickr_TextData/Flickr8k.token.txt'\n",
    "text = open(token_path, 'r', encoding = 'utf-8').read()\n",
    "print(text[:500])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of items: 8092\n"
     ]
    }
   ],
   "source": [
    "def load_description(text):\n",
    "    mapping = dict()\n",
    "    for line in text.split(\"\\n\"):\n",
    "        token = line.split(\"\\t\")\n",
    "        if len(line) < 2:\n",
    "            continue\n",
    "        img_id = token[0].split('.')[0]\n",
    "        img_des = token[1]\n",
    "        if img_id not in mapping:\n",
    "            mapping[img_id] = list()\n",
    "        mapping[img_id].append(img_des)\n",
    "    return mapping\n",
    "\n",
    "descriptions = load_description(text)\n",
    "print(\"Number of items: \" + str(len(descriptions)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['A child in a pink dress is climbing up a set of stairs in an entry way .',\n",
       " 'A girl going into a wooden building .',\n",
       " 'A little girl climbing into a wooden playhouse .',\n",
       " 'A little girl climbing the stairs to her playhouse .',\n",
       " 'A little girl in a pink dress going into a wooden cabin .']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "descriptions['1000268201_693b08cb0e']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['child in pink dress is climbing up set of stairs in an entry way',\n",
       " 'girl going into wooden building',\n",
       " 'little girl climbing into wooden playhouse',\n",
       " 'little girl climbing the stairs to her playhouse',\n",
       " 'little girl in pink dress going into wooden cabin']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def clean_description(desc):\n",
    "    for key, des_list in desc.items():\n",
    "        for i in range(len(des_list)):\n",
    "            caption = des_list[i]\n",
    "            caption = [ch for ch in caption if ch not in string.punctuation]\n",
    "            caption = ''.join(caption)\n",
    "            caption = caption.split(' ')\n",
    "            caption = [word.lower() for word in caption if len(word)>1 and word.isalpha()]\n",
    "            caption = ' '.join(caption)\n",
    "            des_list[i] = caption\n",
    "\n",
    "clean_description(descriptions)\n",
    "descriptions['1000268201_693b08cb0e']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8763"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def to_vocab(desc):\n",
    "    words = set()\n",
    "    for key in desc.keys():\n",
    "        for line in desc[key]:\n",
    "            words.update(line.split())\n",
    "    return words\n",
    "vocab = to_vocab(descriptions)\n",
    "len(vocab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8091"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import glob\n",
    "images = '/kaggle/input/flickr8k/flickr_data/Flickr_Data/Images/'\n",
    "# Create a list of all image names in the directory\n",
    "img = glob.glob(images + '*.jpg')\n",
    "len(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_path = '/kaggle/input/flickr8k/flickr_data/Flickr_Data/Flickr_TextData/Flickr_8k.trainImages.txt'\n",
    "train_images = open(train_path, 'r', encoding = 'utf-8').read().split(\"\\n\")\n",
    "train_img = []\n",
    "\n",
    "for im in img:\n",
    "    if(im[len(images):] in train_images):\n",
    "        train_img.append(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_path = '/kaggle/input/flickr8k/flickr_data/Flickr_Data/Flickr_TextData/Flickr_8k.testImages.txt'\n",
    "test_images = open(test_path, 'r', encoding = 'utf-8').read().split(\"\\n\")\n",
    "test_img = []\n",
    "\n",
    "for im in img:\n",
    "    if(im[len(images): ] in test_images):\n",
    "        test_img.append(im)\n",
    "len(test_img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Descriptions: train=6000\n"
     ]
    }
   ],
   "source": [
    "#load descriptions of train and test set separately\n",
    "def load_clean_descriptions(des, dataset):\n",
    "    dataset_des = dict()\n",
    "    for key, des_list in des.items():\n",
    "        if key+'.jpg' in dataset:\n",
    "            if key not in dataset_des:\n",
    "                dataset_des[key] = list()\n",
    "            for line in des_list:\n",
    "                desc = 'startseq ' + line + ' endseq'\n",
    "                dataset_des[key].append(desc)\n",
    "    return dataset_des\n",
    "\n",
    "train_descriptions = load_clean_descriptions(descriptions, train_images)\n",
    "print('Descriptions: train=%d' % len(train_descriptions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['startseq child in pink dress is climbing up set of stairs in an entry way endseq',\n",
       " 'startseq girl going into wooden building endseq',\n",
       " 'startseq little girl climbing into wooden playhouse endseq',\n",
       " 'startseq little girl climbing the stairs to her playhouse endseq',\n",
       " 'startseq little girl in pink dress going into wooden cabin endseq']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_descriptions['1000268201_693b08cb0e']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.preprocessing.image import load_img, img_to_array\n",
    "def preprocess_img(img_path):\n",
    "    #inception v3 excepts img in 299*299\n",
    "    img = load_img(img_path, target_size = (299, 299))\n",
    "    x = img_to_array(img)\n",
    "    # Add one more dimension\n",
    "    x = np.expand_dims(x, axis = 0)\n",
    "    x = preprocess_input(x)\n",
    "    return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://github.com/fchollet/deep-learning-models/releases/download/v0.5/inception_v3_weights_tf_dim_ordering_tf_kernels.h5\n",
      "96116736/96112376 [==============================] - 2s 0us/step\n",
      "Model: \"inception_v3\"\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            (None, 299, 299, 3)  0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_1 (Conv2D)               (None, 149, 149, 32) 864         input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_1 (BatchNor (None, 149, 149, 32) 96          conv2d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_1 (Activation)       (None, 149, 149, 32) 0           batch_normalization_1[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_2 (Conv2D)               (None, 147, 147, 32) 9216        activation_1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_2 (BatchNor (None, 147, 147, 32) 96          conv2d_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_2 (Activation)       (None, 147, 147, 32) 0           batch_normalization_2[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_3 (Conv2D)               (None, 147, 147, 64) 18432       activation_2[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_3 (BatchNor (None, 147, 147, 64) 192         conv2d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_3 (Activation)       (None, 147, 147, 64) 0           batch_normalization_3[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2D)  (None, 73, 73, 64)   0           activation_3[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_4 (Conv2D)               (None, 73, 73, 80)   5120        max_pooling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_4 (BatchNor (None, 73, 73, 80)   240         conv2d_4[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_4 (Activation)       (None, 73, 73, 80)   0           batch_normalization_4[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_5 (Conv2D)               (None, 71, 71, 192)  138240      activation_4[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_5 (BatchNor (None, 71, 71, 192)  576         conv2d_5[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_5 (Activation)       (None, 71, 71, 192)  0           batch_normalization_5[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2D)  (None, 35, 35, 192)  0           activation_5[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_9 (Conv2D)               (None, 35, 35, 64)   12288       max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_9 (BatchNor (None, 35, 35, 64)   192         conv2d_9[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_9 (Activation)       (None, 35, 35, 64)   0           batch_normalization_9[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_7 (Conv2D)               (None, 35, 35, 48)   9216        max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_10 (Conv2D)              (None, 35, 35, 96)   55296       activation_9[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_7 (BatchNor (None, 35, 35, 48)   144         conv2d_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_10 (BatchNo (None, 35, 35, 96)   288         conv2d_10[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_7 (Activation)       (None, 35, 35, 48)   0           batch_normalization_7[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_10 (Activation)      (None, 35, 35, 96)   0           batch_normalization_10[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_1 (AveragePoo (None, 35, 35, 192)  0           max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_6 (Conv2D)               (None, 35, 35, 64)   12288       max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_8 (Conv2D)               (None, 35, 35, 64)   76800       activation_7[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_11 (Conv2D)              (None, 35, 35, 96)   82944       activation_10[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_12 (Conv2D)              (None, 35, 35, 32)   6144        average_pooling2d_1[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_6 (BatchNor (None, 35, 35, 64)   192         conv2d_6[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_8 (BatchNor (None, 35, 35, 64)   192         conv2d_8[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_11 (BatchNo (None, 35, 35, 96)   288         conv2d_11[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_12 (BatchNo (None, 35, 35, 32)   96          conv2d_12[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_6 (Activation)       (None, 35, 35, 64)   0           batch_normalization_6[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_8 (Activation)       (None, 35, 35, 64)   0           batch_normalization_8[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_11 (Activation)      (None, 35, 35, 96)   0           batch_normalization_11[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_12 (Activation)      (None, 35, 35, 32)   0           batch_normalization_12[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed0 (Concatenate)            (None, 35, 35, 256)  0           activation_6[0][0]               \n",
      "                                                                 activation_8[0][0]               \n",
      "                                                                 activation_11[0][0]              \n",
      "                                                                 activation_12[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_16 (Conv2D)              (None, 35, 35, 64)   16384       mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_16 (BatchNo (None, 35, 35, 64)   192         conv2d_16[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_16 (Activation)      (None, 35, 35, 64)   0           batch_normalization_16[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_14 (Conv2D)              (None, 35, 35, 48)   12288       mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_17 (Conv2D)              (None, 35, 35, 96)   55296       activation_16[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_14 (BatchNo (None, 35, 35, 48)   144         conv2d_14[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_17 (BatchNo (None, 35, 35, 96)   288         conv2d_17[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_14 (Activation)      (None, 35, 35, 48)   0           batch_normalization_14[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_17 (Activation)      (None, 35, 35, 96)   0           batch_normalization_17[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_2 (AveragePoo (None, 35, 35, 256)  0           mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_13 (Conv2D)              (None, 35, 35, 64)   16384       mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_15 (Conv2D)              (None, 35, 35, 64)   76800       activation_14[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_18 (Conv2D)              (None, 35, 35, 96)   82944       activation_17[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_19 (Conv2D)              (None, 35, 35, 64)   16384       average_pooling2d_2[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_13 (BatchNo (None, 35, 35, 64)   192         conv2d_13[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_15 (BatchNo (None, 35, 35, 64)   192         conv2d_15[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_18 (BatchNo (None, 35, 35, 96)   288         conv2d_18[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_19 (BatchNo (None, 35, 35, 64)   192         conv2d_19[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_13 (Activation)      (None, 35, 35, 64)   0           batch_normalization_13[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_15 (Activation)      (None, 35, 35, 64)   0           batch_normalization_15[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_18 (Activation)      (None, 35, 35, 96)   0           batch_normalization_18[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_19 (Activation)      (None, 35, 35, 64)   0           batch_normalization_19[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed1 (Concatenate)            (None, 35, 35, 288)  0           activation_13[0][0]              \n",
      "                                                                 activation_15[0][0]              \n",
      "                                                                 activation_18[0][0]              \n",
      "                                                                 activation_19[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_23 (Conv2D)              (None, 35, 35, 64)   18432       mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_23 (BatchNo (None, 35, 35, 64)   192         conv2d_23[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_23 (Activation)      (None, 35, 35, 64)   0           batch_normalization_23[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_21 (Conv2D)              (None, 35, 35, 48)   13824       mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_24 (Conv2D)              (None, 35, 35, 96)   55296       activation_23[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_21 (BatchNo (None, 35, 35, 48)   144         conv2d_21[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_24 (BatchNo (None, 35, 35, 96)   288         conv2d_24[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_21 (Activation)      (None, 35, 35, 48)   0           batch_normalization_21[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_24 (Activation)      (None, 35, 35, 96)   0           batch_normalization_24[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_3 (AveragePoo (None, 35, 35, 288)  0           mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_20 (Conv2D)              (None, 35, 35, 64)   18432       mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_22 (Conv2D)              (None, 35, 35, 64)   76800       activation_21[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_25 (Conv2D)              (None, 35, 35, 96)   82944       activation_24[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_26 (Conv2D)              (None, 35, 35, 64)   18432       average_pooling2d_3[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_20 (BatchNo (None, 35, 35, 64)   192         conv2d_20[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_22 (BatchNo (None, 35, 35, 64)   192         conv2d_22[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_25 (BatchNo (None, 35, 35, 96)   288         conv2d_25[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_26 (BatchNo (None, 35, 35, 64)   192         conv2d_26[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_20 (Activation)      (None, 35, 35, 64)   0           batch_normalization_20[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_22 (Activation)      (None, 35, 35, 64)   0           batch_normalization_22[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_25 (Activation)      (None, 35, 35, 96)   0           batch_normalization_25[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_26 (Activation)      (None, 35, 35, 64)   0           batch_normalization_26[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed2 (Concatenate)            (None, 35, 35, 288)  0           activation_20[0][0]              \n",
      "                                                                 activation_22[0][0]              \n",
      "                                                                 activation_25[0][0]              \n",
      "                                                                 activation_26[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_28 (Conv2D)              (None, 35, 35, 64)   18432       mixed2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_28 (BatchNo (None, 35, 35, 64)   192         conv2d_28[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_28 (Activation)      (None, 35, 35, 64)   0           batch_normalization_28[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_29 (Conv2D)              (None, 35, 35, 96)   55296       activation_28[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_29 (BatchNo (None, 35, 35, 96)   288         conv2d_29[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_29 (Activation)      (None, 35, 35, 96)   0           batch_normalization_29[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_27 (Conv2D)              (None, 17, 17, 384)  995328      mixed2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_30 (Conv2D)              (None, 17, 17, 96)   82944       activation_29[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_27 (BatchNo (None, 17, 17, 384)  1152        conv2d_27[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_30 (BatchNo (None, 17, 17, 96)   288         conv2d_30[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_27 (Activation)      (None, 17, 17, 384)  0           batch_normalization_27[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_30 (Activation)      (None, 17, 17, 96)   0           batch_normalization_30[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_3 (MaxPooling2D)  (None, 17, 17, 288)  0           mixed2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "mixed3 (Concatenate)            (None, 17, 17, 768)  0           activation_27[0][0]              \n",
      "                                                                 activation_30[0][0]              \n",
      "                                                                 max_pooling2d_3[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_35 (Conv2D)              (None, 17, 17, 128)  98304       mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_35 (BatchNo (None, 17, 17, 128)  384         conv2d_35[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_35 (Activation)      (None, 17, 17, 128)  0           batch_normalization_35[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_36 (Conv2D)              (None, 17, 17, 128)  114688      activation_35[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_36 (BatchNo (None, 17, 17, 128)  384         conv2d_36[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_36 (Activation)      (None, 17, 17, 128)  0           batch_normalization_36[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_32 (Conv2D)              (None, 17, 17, 128)  98304       mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_37 (Conv2D)              (None, 17, 17, 128)  114688      activation_36[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_32 (BatchNo (None, 17, 17, 128)  384         conv2d_32[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_37 (BatchNo (None, 17, 17, 128)  384         conv2d_37[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_32 (Activation)      (None, 17, 17, 128)  0           batch_normalization_32[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_37 (Activation)      (None, 17, 17, 128)  0           batch_normalization_37[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_33 (Conv2D)              (None, 17, 17, 128)  114688      activation_32[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_38 (Conv2D)              (None, 17, 17, 128)  114688      activation_37[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_33 (BatchNo (None, 17, 17, 128)  384         conv2d_33[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_38 (BatchNo (None, 17, 17, 128)  384         conv2d_38[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_33 (Activation)      (None, 17, 17, 128)  0           batch_normalization_33[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_38 (Activation)      (None, 17, 17, 128)  0           batch_normalization_38[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_4 (AveragePoo (None, 17, 17, 768)  0           mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_31 (Conv2D)              (None, 17, 17, 192)  147456      mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_34 (Conv2D)              (None, 17, 17, 192)  172032      activation_33[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_39 (Conv2D)              (None, 17, 17, 192)  172032      activation_38[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_40 (Conv2D)              (None, 17, 17, 192)  147456      average_pooling2d_4[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_31 (BatchNo (None, 17, 17, 192)  576         conv2d_31[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_34 (BatchNo (None, 17, 17, 192)  576         conv2d_34[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_39 (BatchNo (None, 17, 17, 192)  576         conv2d_39[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_40 (BatchNo (None, 17, 17, 192)  576         conv2d_40[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_31 (Activation)      (None, 17, 17, 192)  0           batch_normalization_31[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_34 (Activation)      (None, 17, 17, 192)  0           batch_normalization_34[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_39 (Activation)      (None, 17, 17, 192)  0           batch_normalization_39[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_40 (Activation)      (None, 17, 17, 192)  0           batch_normalization_40[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed4 (Concatenate)            (None, 17, 17, 768)  0           activation_31[0][0]              \n",
      "                                                                 activation_34[0][0]              \n",
      "                                                                 activation_39[0][0]              \n",
      "                                                                 activation_40[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_45 (Conv2D)              (None, 17, 17, 160)  122880      mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_45 (BatchNo (None, 17, 17, 160)  480         conv2d_45[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_45 (Activation)      (None, 17, 17, 160)  0           batch_normalization_45[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_46 (Conv2D)              (None, 17, 17, 160)  179200      activation_45[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_46 (BatchNo (None, 17, 17, 160)  480         conv2d_46[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_46 (Activation)      (None, 17, 17, 160)  0           batch_normalization_46[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_42 (Conv2D)              (None, 17, 17, 160)  122880      mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_47 (Conv2D)              (None, 17, 17, 160)  179200      activation_46[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_42 (BatchNo (None, 17, 17, 160)  480         conv2d_42[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_47 (BatchNo (None, 17, 17, 160)  480         conv2d_47[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_42 (Activation)      (None, 17, 17, 160)  0           batch_normalization_42[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_47 (Activation)      (None, 17, 17, 160)  0           batch_normalization_47[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_43 (Conv2D)              (None, 17, 17, 160)  179200      activation_42[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_48 (Conv2D)              (None, 17, 17, 160)  179200      activation_47[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_43 (BatchNo (None, 17, 17, 160)  480         conv2d_43[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_48 (BatchNo (None, 17, 17, 160)  480         conv2d_48[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_43 (Activation)      (None, 17, 17, 160)  0           batch_normalization_43[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_48 (Activation)      (None, 17, 17, 160)  0           batch_normalization_48[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_5 (AveragePoo (None, 17, 17, 768)  0           mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_41 (Conv2D)              (None, 17, 17, 192)  147456      mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_44 (Conv2D)              (None, 17, 17, 192)  215040      activation_43[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_49 (Conv2D)              (None, 17, 17, 192)  215040      activation_48[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_50 (Conv2D)              (None, 17, 17, 192)  147456      average_pooling2d_5[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_41 (BatchNo (None, 17, 17, 192)  576         conv2d_41[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_44 (BatchNo (None, 17, 17, 192)  576         conv2d_44[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_49 (BatchNo (None, 17, 17, 192)  576         conv2d_49[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_50 (BatchNo (None, 17, 17, 192)  576         conv2d_50[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_41 (Activation)      (None, 17, 17, 192)  0           batch_normalization_41[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_44 (Activation)      (None, 17, 17, 192)  0           batch_normalization_44[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_49 (Activation)      (None, 17, 17, 192)  0           batch_normalization_49[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_50 (Activation)      (None, 17, 17, 192)  0           batch_normalization_50[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed5 (Concatenate)            (None, 17, 17, 768)  0           activation_41[0][0]              \n",
      "                                                                 activation_44[0][0]              \n",
      "                                                                 activation_49[0][0]              \n",
      "                                                                 activation_50[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_55 (Conv2D)              (None, 17, 17, 160)  122880      mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_55 (BatchNo (None, 17, 17, 160)  480         conv2d_55[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_55 (Activation)      (None, 17, 17, 160)  0           batch_normalization_55[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_56 (Conv2D)              (None, 17, 17, 160)  179200      activation_55[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_56 (BatchNo (None, 17, 17, 160)  480         conv2d_56[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_56 (Activation)      (None, 17, 17, 160)  0           batch_normalization_56[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_52 (Conv2D)              (None, 17, 17, 160)  122880      mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_57 (Conv2D)              (None, 17, 17, 160)  179200      activation_56[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_52 (BatchNo (None, 17, 17, 160)  480         conv2d_52[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_57 (BatchNo (None, 17, 17, 160)  480         conv2d_57[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_52 (Activation)      (None, 17, 17, 160)  0           batch_normalization_52[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_57 (Activation)      (None, 17, 17, 160)  0           batch_normalization_57[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_53 (Conv2D)              (None, 17, 17, 160)  179200      activation_52[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_58 (Conv2D)              (None, 17, 17, 160)  179200      activation_57[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_53 (BatchNo (None, 17, 17, 160)  480         conv2d_53[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_58 (BatchNo (None, 17, 17, 160)  480         conv2d_58[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_53 (Activation)      (None, 17, 17, 160)  0           batch_normalization_53[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_58 (Activation)      (None, 17, 17, 160)  0           batch_normalization_58[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_6 (AveragePoo (None, 17, 17, 768)  0           mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_51 (Conv2D)              (None, 17, 17, 192)  147456      mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_54 (Conv2D)              (None, 17, 17, 192)  215040      activation_53[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_59 (Conv2D)              (None, 17, 17, 192)  215040      activation_58[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_60 (Conv2D)              (None, 17, 17, 192)  147456      average_pooling2d_6[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_51 (BatchNo (None, 17, 17, 192)  576         conv2d_51[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_54 (BatchNo (None, 17, 17, 192)  576         conv2d_54[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_59 (BatchNo (None, 17, 17, 192)  576         conv2d_59[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_60 (BatchNo (None, 17, 17, 192)  576         conv2d_60[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_51 (Activation)      (None, 17, 17, 192)  0           batch_normalization_51[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_54 (Activation)      (None, 17, 17, 192)  0           batch_normalization_54[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_59 (Activation)      (None, 17, 17, 192)  0           batch_normalization_59[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_60 (Activation)      (None, 17, 17, 192)  0           batch_normalization_60[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed6 (Concatenate)            (None, 17, 17, 768)  0           activation_51[0][0]              \n",
      "                                                                 activation_54[0][0]              \n",
      "                                                                 activation_59[0][0]              \n",
      "                                                                 activation_60[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_65 (Conv2D)              (None, 17, 17, 192)  147456      mixed6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_65 (BatchNo (None, 17, 17, 192)  576         conv2d_65[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_65 (Activation)      (None, 17, 17, 192)  0           batch_normalization_65[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_66 (Conv2D)              (None, 17, 17, 192)  258048      activation_65[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_66 (BatchNo (None, 17, 17, 192)  576         conv2d_66[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_66 (Activation)      (None, 17, 17, 192)  0           batch_normalization_66[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_62 (Conv2D)              (None, 17, 17, 192)  147456      mixed6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_67 (Conv2D)              (None, 17, 17, 192)  258048      activation_66[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_62 (BatchNo (None, 17, 17, 192)  576         conv2d_62[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_67 (BatchNo (None, 17, 17, 192)  576         conv2d_67[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_62 (Activation)      (None, 17, 17, 192)  0           batch_normalization_62[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_67 (Activation)      (None, 17, 17, 192)  0           batch_normalization_67[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_63 (Conv2D)              (None, 17, 17, 192)  258048      activation_62[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_68 (Conv2D)              (None, 17, 17, 192)  258048      activation_67[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_63 (BatchNo (None, 17, 17, 192)  576         conv2d_63[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_68 (BatchNo (None, 17, 17, 192)  576         conv2d_68[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_63 (Activation)      (None, 17, 17, 192)  0           batch_normalization_63[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_68 (Activation)      (None, 17, 17, 192)  0           batch_normalization_68[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_7 (AveragePoo (None, 17, 17, 768)  0           mixed6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_61 (Conv2D)              (None, 17, 17, 192)  147456      mixed6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_64 (Conv2D)              (None, 17, 17, 192)  258048      activation_63[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_69 (Conv2D)              (None, 17, 17, 192)  258048      activation_68[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_70 (Conv2D)              (None, 17, 17, 192)  147456      average_pooling2d_7[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_61 (BatchNo (None, 17, 17, 192)  576         conv2d_61[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_64 (BatchNo (None, 17, 17, 192)  576         conv2d_64[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_69 (BatchNo (None, 17, 17, 192)  576         conv2d_69[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_70 (BatchNo (None, 17, 17, 192)  576         conv2d_70[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_61 (Activation)      (None, 17, 17, 192)  0           batch_normalization_61[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_64 (Activation)      (None, 17, 17, 192)  0           batch_normalization_64[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_69 (Activation)      (None, 17, 17, 192)  0           batch_normalization_69[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_70 (Activation)      (None, 17, 17, 192)  0           batch_normalization_70[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed7 (Concatenate)            (None, 17, 17, 768)  0           activation_61[0][0]              \n",
      "                                                                 activation_64[0][0]              \n",
      "                                                                 activation_69[0][0]              \n",
      "                                                                 activation_70[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_73 (Conv2D)              (None, 17, 17, 192)  147456      mixed7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_73 (BatchNo (None, 17, 17, 192)  576         conv2d_73[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_73 (Activation)      (None, 17, 17, 192)  0           batch_normalization_73[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_74 (Conv2D)              (None, 17, 17, 192)  258048      activation_73[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_74 (BatchNo (None, 17, 17, 192)  576         conv2d_74[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_74 (Activation)      (None, 17, 17, 192)  0           batch_normalization_74[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_71 (Conv2D)              (None, 17, 17, 192)  147456      mixed7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_75 (Conv2D)              (None, 17, 17, 192)  258048      activation_74[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_71 (BatchNo (None, 17, 17, 192)  576         conv2d_71[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_75 (BatchNo (None, 17, 17, 192)  576         conv2d_75[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_71 (Activation)      (None, 17, 17, 192)  0           batch_normalization_71[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_75 (Activation)      (None, 17, 17, 192)  0           batch_normalization_75[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_72 (Conv2D)              (None, 8, 8, 320)    552960      activation_71[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_76 (Conv2D)              (None, 8, 8, 192)    331776      activation_75[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_72 (BatchNo (None, 8, 8, 320)    960         conv2d_72[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_76 (BatchNo (None, 8, 8, 192)    576         conv2d_76[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_72 (Activation)      (None, 8, 8, 320)    0           batch_normalization_72[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_76 (Activation)      (None, 8, 8, 192)    0           batch_normalization_76[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_4 (MaxPooling2D)  (None, 8, 8, 768)    0           mixed7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "mixed8 (Concatenate)            (None, 8, 8, 1280)   0           activation_72[0][0]              \n",
      "                                                                 activation_76[0][0]              \n",
      "                                                                 max_pooling2d_4[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_81 (Conv2D)              (None, 8, 8, 448)    573440      mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_81 (BatchNo (None, 8, 8, 448)    1344        conv2d_81[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_81 (Activation)      (None, 8, 8, 448)    0           batch_normalization_81[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_78 (Conv2D)              (None, 8, 8, 384)    491520      mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_82 (Conv2D)              (None, 8, 8, 384)    1548288     activation_81[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_78 (BatchNo (None, 8, 8, 384)    1152        conv2d_78[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_82 (BatchNo (None, 8, 8, 384)    1152        conv2d_82[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_78 (Activation)      (None, 8, 8, 384)    0           batch_normalization_78[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_82 (Activation)      (None, 8, 8, 384)    0           batch_normalization_82[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_79 (Conv2D)              (None, 8, 8, 384)    442368      activation_78[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_80 (Conv2D)              (None, 8, 8, 384)    442368      activation_78[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_83 (Conv2D)              (None, 8, 8, 384)    442368      activation_82[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_84 (Conv2D)              (None, 8, 8, 384)    442368      activation_82[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_8 (AveragePoo (None, 8, 8, 1280)   0           mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_77 (Conv2D)              (None, 8, 8, 320)    409600      mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_79 (BatchNo (None, 8, 8, 384)    1152        conv2d_79[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_80 (BatchNo (None, 8, 8, 384)    1152        conv2d_80[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_83 (BatchNo (None, 8, 8, 384)    1152        conv2d_83[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_84 (BatchNo (None, 8, 8, 384)    1152        conv2d_84[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_85 (Conv2D)              (None, 8, 8, 192)    245760      average_pooling2d_8[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_77 (BatchNo (None, 8, 8, 320)    960         conv2d_77[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_79 (Activation)      (None, 8, 8, 384)    0           batch_normalization_79[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_80 (Activation)      (None, 8, 8, 384)    0           batch_normalization_80[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_83 (Activation)      (None, 8, 8, 384)    0           batch_normalization_83[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_84 (Activation)      (None, 8, 8, 384)    0           batch_normalization_84[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_85 (BatchNo (None, 8, 8, 192)    576         conv2d_85[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_77 (Activation)      (None, 8, 8, 320)    0           batch_normalization_77[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed9_0 (Concatenate)          (None, 8, 8, 768)    0           activation_79[0][0]              \n",
      "                                                                 activation_80[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_1 (Concatenate)     (None, 8, 8, 768)    0           activation_83[0][0]              \n",
      "                                                                 activation_84[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_85 (Activation)      (None, 8, 8, 192)    0           batch_normalization_85[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed9 (Concatenate)            (None, 8, 8, 2048)   0           activation_77[0][0]              \n",
      "                                                                 mixed9_0[0][0]                   \n",
      "                                                                 concatenate_1[0][0]              \n",
      "                                                                 activation_85[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_90 (Conv2D)              (None, 8, 8, 448)    917504      mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_90 (BatchNo (None, 8, 8, 448)    1344        conv2d_90[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_90 (Activation)      (None, 8, 8, 448)    0           batch_normalization_90[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_87 (Conv2D)              (None, 8, 8, 384)    786432      mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_91 (Conv2D)              (None, 8, 8, 384)    1548288     activation_90[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_87 (BatchNo (None, 8, 8, 384)    1152        conv2d_87[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_91 (BatchNo (None, 8, 8, 384)    1152        conv2d_91[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_87 (Activation)      (None, 8, 8, 384)    0           batch_normalization_87[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_91 (Activation)      (None, 8, 8, 384)    0           batch_normalization_91[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_88 (Conv2D)              (None, 8, 8, 384)    442368      activation_87[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_89 (Conv2D)              (None, 8, 8, 384)    442368      activation_87[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_92 (Conv2D)              (None, 8, 8, 384)    442368      activation_91[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_93 (Conv2D)              (None, 8, 8, 384)    442368      activation_91[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_9 (AveragePoo (None, 8, 8, 2048)   0           mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_86 (Conv2D)              (None, 8, 8, 320)    655360      mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_88 (BatchNo (None, 8, 8, 384)    1152        conv2d_88[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_89 (BatchNo (None, 8, 8, 384)    1152        conv2d_89[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_92 (BatchNo (None, 8, 8, 384)    1152        conv2d_92[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_93 (BatchNo (None, 8, 8, 384)    1152        conv2d_93[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_94 (Conv2D)              (None, 8, 8, 192)    393216      average_pooling2d_9[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_86 (BatchNo (None, 8, 8, 320)    960         conv2d_86[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_88 (Activation)      (None, 8, 8, 384)    0           batch_normalization_88[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_89 (Activation)      (None, 8, 8, 384)    0           batch_normalization_89[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_92 (Activation)      (None, 8, 8, 384)    0           batch_normalization_92[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_93 (Activation)      (None, 8, 8, 384)    0           batch_normalization_93[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_94 (BatchNo (None, 8, 8, 192)    576         conv2d_94[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_86 (Activation)      (None, 8, 8, 320)    0           batch_normalization_86[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed9_1 (Concatenate)          (None, 8, 8, 768)    0           activation_88[0][0]              \n",
      "                                                                 activation_89[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_2 (Concatenate)     (None, 8, 8, 768)    0           activation_92[0][0]              \n",
      "                                                                 activation_93[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_94 (Activation)      (None, 8, 8, 192)    0           batch_normalization_94[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed10 (Concatenate)           (None, 8, 8, 2048)   0           activation_86[0][0]              \n",
      "                                                                 mixed9_1[0][0]                   \n",
      "                                                                 concatenate_2[0][0]              \n",
      "                                                                 activation_94[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "avg_pool (GlobalAveragePooling2 (None, 2048)         0           mixed10[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "predictions (Dense)             (None, 1000)         2049000     avg_pool[0][0]                   \n",
      "==================================================================================================\n",
      "Total params: 23,851,784\n",
      "Trainable params: 23,817,352\n",
      "Non-trainable params: 34,432\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "base_model = InceptionV3(weights = 'imagenet')\n",
    "base_model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = Model(base_model.input, base_model.layers[-2].output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#function to encode an image into a vector using inception v3\n",
    "def encode(image):\n",
    "    image = preprocess_img(image)\n",
    "    vec = model.predict(image)\n",
    "    vec = np.reshape(vec, (vec.shape[1]))\n",
    "    return vec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time Taken is: 219.64522123336792\n"
     ]
    }
   ],
   "source": [
    "#run the encode function on all train images\n",
    "start = time.time()\n",
    "encoding_train = {}\n",
    "for img in train_img:\n",
    "    encoding_train[img[len(images):]] = encode(img)\n",
    "print(\"Time Taken is: \" + str(time.time() - start))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time taken is: 34.9825165271759\n"
     ]
    }
   ],
   "source": [
    "#Encode all the test images\n",
    "start = time.time()\n",
    "encoding_test = {}\n",
    "for img in test_img:\n",
    "    encoding_test[img[len(images):]] = encode(img)\n",
    "print(\"Time taken is: \" + str(time.time() - start))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train image encodings: 6000\n",
      "Test image encodings: 1000\n"
     ]
    }
   ],
   "source": [
    "train_features = encoding_train\n",
    "test_features = encoding_test\n",
    "print(\"Train image encodings: \" + str(len(train_features)))\n",
    "print(\"Test image encodings: \" + str(len(test_features)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2048,)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_features['1000268201_693b08cb0e.jpg'].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30000"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#list of all training captions\n",
    "all_train_captions = []\n",
    "for key, val in train_descriptions.items():\n",
    "    for caption in val:\n",
    "        all_train_captions.append(caption)\n",
    "len(all_train_captions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unique words: 7578\n",
      "our Vocabulary: 1651\n"
     ]
    }
   ],
   "source": [
    "#onsider only words which occur atleast 10 times\n",
    "vocabulary = vocab\n",
    "threshold = 10\n",
    "word_counts = {}\n",
    "for cap in all_train_captions:\n",
    "    for word in cap.split(' '):\n",
    "        word_counts[word] = word_counts.get(word, 0) + 1\n",
    "\n",
    "vocab = [word for word in word_counts if word_counts[word] >= threshold]\n",
    "print(\"Unique words: \" + str(len(word_counts)))\n",
    "print(\"our Vocabulary: \" + str(len(vocab)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "#word mapping to integers\n",
    "ixtoword = {}\n",
    "wordtoix = {}\n",
    "\n",
    "ix = 1\n",
    "for word in vocab:\n",
    "    wordtoix[word] = ix\n",
    "    ixtoword[ix] = word\n",
    "    ix += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1652"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vocab_size = len(ixtoword) + 1  #1 for appended zeros\n",
    "vocab_size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "34"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#find the maximum length of a description in a dataset\n",
    "max_length = max(len(des.split()) for des in all_train_captions)\n",
    "max_length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(292328, 2048)\n"
     ]
    }
   ],
   "source": [
    "#since there are almost 30000 descriptions to process we will use datagenerator\n",
    "X1, X2, y = list(), list(), list()\n",
    "for key, des_list in train_descriptions.items():\n",
    "    pic = train_features[key + '.jpg']\n",
    "    for cap in des_list:\n",
    "        seq = [wordtoix[word] for word in cap.split(' ') if word in wordtoix]\n",
    "        for i in range(1, len(seq)):\n",
    "            in_seq, out_seq = seq[:i], seq[i]\n",
    "            in_seq = pad_sequences([in_seq], maxlen = max_length)[0]\n",
    "            out_seq = to_categorical([out_seq], num_classes = vocab_size)[0]\n",
    "            #store\n",
    "            X1.append(pic)\n",
    "            X2.append(in_seq)\n",
    "            y.append(out_seq)\n",
    "\n",
    "X2 = np.array(X2)\n",
    "X1 = np.array(X1)\n",
    "y = np.array(y)\n",
    "print(X1.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total word vectors: 400001\n"
     ]
    }
   ],
   "source": [
    "#load glove vectors for embedding layer\n",
    "embeddings_index = {}\n",
    "glove = open('/kaggle/input/glove-global-vectors-for-word-representation/glove.6B.200d.txt', 'r', encoding = 'utf-8').read()\n",
    "for line in glove.split(\"\\n\"):\n",
    "    values = line.split(\" \")\n",
    "    word = values[0]\n",
    "    indices = np.asarray(values[1: ], dtype = 'float32')\n",
    "    embeddings_index[word] = indices\n",
    "print('Total word vectors: ' + str(len(embeddings_index)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1652, 200)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "emb_dim = 200\n",
    "emb_matrix = np.zeros((vocab_size, emb_dim))\n",
    "for word, i in wordtoix.items():\n",
    "    emb_vec = embeddings_index.get(word)\n",
    "    if emb_vec is not None:\n",
    "        emb_matrix[i] = emb_vec\n",
    "emb_matrix.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model_2\"\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_3 (InputLayer)            (None, 34)           0                                            \n",
      "__________________________________________________________________________________________________\n",
      "input_2 (InputLayer)            (None, 2048)         0                                            \n",
      "__________________________________________________________________________________________________\n",
      "embedding_1 (Embedding)         (None, 34, 200)      330400      input_3[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dropout_1 (Dropout)             (None, 2048)         0           input_2[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dropout_2 (Dropout)             (None, 34, 200)      0           embedding_1[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "dense_1 (Dense)                 (None, 256)          524544      dropout_1[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "lstm_1 (LSTM)                   (None, 256)          467968      dropout_2[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "add_1 (Add)                     (None, 256)          0           dense_1[0][0]                    \n",
      "                                                                 lstm_1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "dense_2 (Dense)                 (None, 256)          65792       add_1[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "dense_3 (Dense)                 (None, 1652)         424564      dense_2[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 1,813,268\n",
      "Trainable params: 1,813,268\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "# define the model\n",
    "ip1 = Input(shape = (2048, ))\n",
    "fe1 = Dropout(0.2)(ip1)\n",
    "fe2 = Dense(256, activation = 'relu')(fe1)\n",
    "ip2 = Input(shape = (max_length, ))\n",
    "se1 = Embedding(vocab_size, emb_dim, mask_zero = True)(ip2)\n",
    "se2 = Dropout(0.2)(se1)\n",
    "se3 = LSTM(256)(se2)\n",
    "decoder1 = add([fe2, se3])\n",
    "decoder2 = Dense(256, activation = 'relu')(decoder1)\n",
    "outputs = Dense(vocab_size, activation = 'softmax')(decoder2)\n",
    "model = Model(inputs = [ip1, ip2], outputs = outputs)\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.layers.embeddings.Embedding at 0x7fb67c17d8d0>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.layers[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.layers[2].set_weights([emb_matrix])\n",
    "model.layers[2].trainable = False\n",
    "model.compile(loss = 'categorical_crossentropy', optimizer = 'adam')\n",
    "plot_model(model, to_file = 'model.png', show_shapes = True, show_layer_names = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 55s 189us/step - loss: 3.8895\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 55s 187us/step - loss: 3.1549\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 54s 186us/step - loss: 2.9185\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 54s 186us/step - loss: 2.7652\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 54s 184us/step - loss: 2.6496\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 54s 183us/step - loss: 2.5559\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 54s 184us/step - loss: 2.4748\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 53s 183us/step - loss: 2.4086\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 54s 184us/step - loss: 2.3477\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 53s 182us/step - loss: 2.2957\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 53s 182us/step - loss: 2.2490\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 53s 182us/step - loss: 2.2049\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 53s 181us/step - loss: 2.1670\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 54s 184us/step - loss: 2.0737\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 54s 183us/step - loss: 2.0440\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 53s 181us/step - loss: 2.0219\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 53s 183us/step - loss: 1.9995\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 54s 184us/step - loss: 1.9785\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 54s 184us/step - loss: 1.9599\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 53s 183us/step - loss: 1.9442\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 53s 183us/step - loss: 1.9274\n",
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 53s 183us/step - loss: 1.9118\n",
      "Epoch 1/1\n",
      "208384/292328 [====================>.........] - ETA: 15s - loss: 1.8688"
     ]
    }
   ],
   "source": [
    "for i in range(30):\n",
    "    model.fit([X1, X2], y, epochs = 1, batch_size = 256)\n",
    "    if(i%2 == 0):\n",
    "        model.save_weights(\"image-caption-weights\" + str(i) + \".h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def greedy_search(pic):\n",
    "    start = 'startseq'\n",
    "    for i in range(max_length):\n",
    "        seq = [wordtoix[word] for word in start.split() if word in wordtoix]\n",
    "        seq = pad_sequences([seq], maxlen = max_length)\n",
    "        yhat = model.predict([pic, seq])\n",
    "        yhat = np.argmax(yhat)\n",
    "        word = ixtoword[yhat]\n",
    "        start += ' ' + word\n",
    "        if word == 'endseq':\n",
    "            break\n",
    "    final = start.split()\n",
    "    final = final[1:-1]\n",
    "    final = ' '.join(final)\n",
    "    return final"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "four girls are sitting on wooden floor\n"
     ]
    }
   ],
   "source": [
    "pic = list(encoding_test.keys())[250]\n",
    "img = encoding_test[pic].reshape(1, 2048)\n",
    "x = plt.imread(images + pic)\n",
    "plt.imshow(x)\n",
    "plt.show()\n",
    "print(greedy_search(img))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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cPdtIcOET1LQOEQobrBTU6oJdCrVTW+HU2awBvMy9631fnisOKHwxEgCn6me0q+Dotcx1ze49VoRypSqlGy98PYsBB0VoxTTDqPZeOWdImRDNiyrOgLLo60PIaraLrIU6MQAhdRNwjr0Y2nv2B1Tdc8UFfpmf2e4JQchtIgZF3H5gQLEIoq4frteHlP7DtSoirY9HVNfyMRouEWr7C5irNjJ/ZopvYIrmD1qKECs9JPX/isFLaXQWudPbqYGq1thuWhaNC+cqTMsdJtj6hk3sMfa5bta+o/Q8bDqOP1UBXDahfgmq5BlBWyZbD/V6iXSf60bXayl14ykbXJkqvdrrxOsWcgz2rL4XSNea1KkI9f0LmiwuqmH2594zbGIW7tHbZVzWTF9lMVcyeou9eJQgVMRtSC/QffRFl9vaD0X4N+reKcwKoApui6BSqBqcc55lIxARUs7EHhLeXqrtoYyDmNYlwQREMWCq9HzY/b/oe0A1rmZD96FnTygUXOkXfFSzb0RCNDgsUxvzPEDC1Pu/J1Gqy0HnEgrYhrBtrplikVzb6u1820ofIHXjaRvwNCcCHVBRR+Ym/O2eRm0zVDqjdewjXr9f3SAaHCfEQvMUjFf8+oPRd6VNdULVDc7HMYAk+75QM51xtJMNjsyqsOmDzCxU+0zBEJmuj+qcqIZZ7dTMmZJdYQ0YovLNPfsmMLOunAoVG99wnTH5g5Y3joAPLrCyI/NwrSdJECPhCw+uPgghyzY0CX3Xu+oNYr/YAlepY9sfl+oZQqdSC2a4Q7KLvejovQWNqEKSPLMIpIeErqcWdyqkv1tvoxExT4jaJlzpFojBCARzOwxci8h0RoBUI6e3p1vs2d5B3Ijoboz9hmlPw5kxHlVhVoRUQU+GwnC+scYSSGMeIGRi090XijqmakZIhMHQfLSLN4IAIQ4c7bpIj0Bq2d6bIsE2BJSk5sXR3wNDLBSCecE0CARDWaIwcMuoutwUFaZkIkIDbhsKxEz1hygb80SyU0vBDJspk1JrxkbfBJoQqusddAa9Yh8RgZS0c/cTgTylWKcCoDEjWryn/F2yk0o1hqMYhsOMj3/RCM1rp9ATHpfhnLItLdsozUtLq+1HFVJyaq0a09U9k+jmLwaIgmrHelbBbnMqpDLHgDaheVrnZ3JUbU4N3QaZHETZuwjFxzwCSQtVm4wb90fmlKw++sCsTvKeITPXd0hJSUG7tettiNJplzn79T2uvL8UcwERFQC4r7zPnBAaUt4iJXMQME3B1oDm5rqa1tdS3jgCvsdvRXqoztGA4GgOE6ZRzQ1SwUhREWIOdeLG6J4CPVe+RgJFlGpwgZzdCFsnfGmQ+V4HNatmpmUoA0QzSbRivqDmARKKAQuq0aQghaDqrpMdFq+CU20jKQLd1PRUqSJz6UoMmqZObBExI5PojACrQri6aVr/CS0aomk4PR9xe93oMt/VxOgo1AVEcQk1xCcUI3Ux0JbJXVwPjdfPFd3Yg9qKeLQIMMENWYJKdqSl5PF61XAECE1jrnjjKSlkmuxaQRA33nYUVhGeA7NkoJLJdO6iBdw2CNMgDBqh3WqZDyNSnqINiDaoGNoOKEMGZEkMJKDZxn7SQFQPWgm2sTQ5MZDI1KkmaaK7DGZy0w1S8XJSgay5em0h4n7u3p/inh/udljpIIUkNvcrR+1eJn13PjNKu/FZrG+DG+ojjWsv7qoZlIFGMtnWWzRpnqMi2byOkqqB46ZBkm1mKRvHHcQMxrYhF08w12qKoMPsCTE0pJzpmL5sQVxbWzCao8lKKzbPM8WWYKsr03oAnBmVyWY7yUXz8c3bPtl6zL7hB9cCUs/nHDGEr8k2nuCAMjnowu0GWS1gqslWV9YCJsuw9OwqAdP2c0BpzfDr9Ez2daBkVKZoFsKgQVtvsSg5tyQttitec3njCPgehdInKProt/LIpS8Vi97ULmhF1DjsvnDv6J9uAlTl88vslAGpFvtiTGmzod6CZRvcu0CTIdZ+G3vtdj3CBKh2KB1mefny/pq1k9WBSoHU/ulDopl+Usx1MDuH2ZXCJfa1dXN1c9XWqZbaj15f7Z56X67t7/dd0Zbotb3TwLYjJ6+w5KdQelyptamg/EwL10T7YjxlzxBW2lapid7Xrbu4lT6fpgSamWw1xDhkUzagCcTpkDTMtJMJcxqROEAl1fEOEsmSMYNxMOFb0DNd9CTq89Dn53ZVuxj2IlLBQFviEcq8ce1lO3Vi9QdnVrp32j6NO6pSqFyYGLVlLqChN4YBZNqLM4kElKn/FDD0rIJ5nPR47UK/qPbnTAequM5a3tZQ67/Cp2u3vmyum9HdUVkd4wLGWnLP+dj6RCWjqePkQ2/t91F89dHPTr94W7JAKPESRUuluFbODMZsfxckXidfcJbA7pbeOpAydjn5PBLvw0gTTIv5Q5DvbyABXxCkz4nK2RWqxLCY7+fiSqu4ILAObmLxYTUXp+gdHcS4cO3zr+V/hRSkcNTdxBRS5y5JRGNxw+poCshotFWQsponTaeM+Ly0hWAePX1hbG0PkV7QVWbQhF7ATfI1kl2D7e6VXuCNS0l/34g44jYeMTBw9RY6wS5FSyKaEVJD3TdmaZ4OJeJoqXumj0jhL430pYv6zR3SDv0pm40CUuuXIBb5mdz1LYQSMAaaWpogIKGG7JfIxVywWvC5Q66aU8aou0FqjfpQ9QChTGKeHNYRAs2WI+3RhPnUQByikgk9baf4zEeEJjQ9jw93ew2RVpQo0QQ7RruWeYoa8sviAETMcB0UcgzEGAwZQ6UUwOk7BQrNIsEpSqnfUUZCXCKXiSXigMlcHgtxYf9vYU1Ul4BBN6/UYzF6wVnBHxIkoGVyqmluqW9XcCEXXDBn56aDb/T9qM1KG0kipSkDUad11Ds8O4Vkqye4qM4Y0i1UXutzx+a6/aFujJ0RwnTUSU9VN24/WCRy5wEVnEXoNstKMhTPOhVSCahyYGagI4Ik1zAqlKztCb5BRQ9YTKklEE3rUXOq7I/taylvDAHvcib03qdM7M67xTlhp21E1NU0rSH8M/e6HLTByXV3Lrx1YTf6QmfGs4UiwK1my40jBCxHRsEHfYRU+cdtdfVec+ZZ0IHTlKa+SUWf+O7Tj1SvC7vPesPqc8QeZp9TkLcEW9ytJgaFhqII9n5but6rxuhqrCvGp6JJZN9YTaLawr6eLaBXfzWc9jWcSCz8Z9mopKOIKp+Mbc5O8NS+CxpIxWAl4j7Lsygx4H77gxEhZ1JKtkgzkAKT4cColzYxv3cX65sbrAfI05bFEGkb8VxBudI7KWViCGY834YIG+1Qc3IbUUGA/ZJSF21dqUGlQ6Lqc1shm0d3b6xmtdF+n/itXdGCSjOdQ3CHLiGbrQtFJJUcZFTCnZ4NqeRYod/nbsQHpy161c+gfK0qVb+/yt8R815RTeTQs/r0QEb9rwpXoz5Rm9/WE7NBdrP9Hro54XUVGdBP+VH7WXvvVNsb6gbW/d57nxktBu97o1gxTtK7KKK0qFpOohIjEVyOaFL3uHntGP4NIeCFTiiXQQzZEYhfU9Ta4Mg6u9AR6QRZQfJl5zWuV6vffB+915K7QSmIW3xXR6ROei1ISBzZQA11t9lV+FIX3MGMYmXzMTXW2hxCL6K1cPhN8LYnCKGXCMsmVBM6dTxTkJq/T1lbYny2qmDeF8adD53LLX4xfU7dmt9DVf1BKZW7TDG10tCKBQJ55Ggw7SvnRIwBdd7WFkVDwiIBbQMvwlyrYHevf1SVgW8EmRID4aNVFo92SJ2sSOMUmLpZbRtIMODamokyevIqEa6wyfHnL7CVAmONXHniNAcWprzpyGFGw8hanBLGkcnmhD27Ftg1dK3EBXPP4uLPcsFe5m8Sc/sLgRTd7pAVUWUYGxJKUrcRiFlcsgcgFcOe5Mw1RGxxVAc3YPY3hd57e5s66iSY3zg+nq595UorDWfEScSCy7TMFx+r0GtSX3uoIKts5Ckb+HbXU7XdisJtl3ZmVZoYmU6n9ozQ/T5N5bqiyfZSH0hwrSpVG0FxHjb7Qkni5fOtCuJrKcbgdI0m08AViio5M5dUXZsQr8/nQc7qEcV+DdniGHAffQCNiHtzddcmd3mGnMzl1MBSESqzbfhayhtCwM+Ajj6ipjdZHcHjkzpDDeSxCdBVlJIZxXLUGlYd82ydWqiGnvV/1mvHd2dPGWBRjtlVJ5yYCExzYhgtqrAE01SEsA3Ba+iQppVMFEOIFW0Irqk0vhgEFXdp83aWHulKz8OlgLq6qJUmZpL0DF7Sn/jF2yjP1DmDZrah1e77aNkSVa+xJfR5WPOIcopNBMS2wdSL4Ov6vSCcnrCWjhILjgzNzz136L63eVTtyDWBsTZkFdbHLZPJhKurqzz+0gqj0LDeJq5OMgeWFri4mXn6/Jj1q1d4y333cGHlEmHjEs0gsNSMTGORBgkRTe0MGi1eJdmRRvD2zwAULTlRzB6SxYPjCjXgEZaURU83L6MIbY8uS163Cc4SwyBFxatjrNldhOjGL8sUUeN9re/MILh97BqNnkZCKrWRs0WJlxxI+FqSNs8ieW+DNaNM3mvnlYggWUmeAE3VNjrJgsQeGFDcdoC/g/eiBCQlf27PBqPd2PQ3qL7MrMFfvVzlfW1we3+U3zVr3YxjmcOefkN16mtqSN8OCBE7GiNSvJlwUJPcYyyEIRBo2wkzk+c1lDeEgBfcIIUnOxKpk9xcz7qJDS4oMS48FH5bO544RoGcaAwPW0ZIEaRQzNqpjKEpKLgIEadkNHSuYJJpSiqmXBaKQoCBdi6BgmehKZRDeT8Rmv4GourGWzMIBRFnGC3jXxLbLEqUrIjQ5Ogh0u7xHASm9l6tu28a3+OugKIuSAVN5p4X3T6RpfPhlcK7h9ipAuBOeV1ADqHwtz4xgwVeibiKqYZEGw3Offv7BjNzNX3VvFJMuY53RslSxExLwAJl+g7RAZhEo+SG2edKLj0txCbTtCO2cmR5YcJ4M/LKFqyeukxqJ1zdv4eTJ65y6Oh+7n7zLWxtbfHK8yd40+03sxwHvHD+FBuTRNx1gKeeO8WuvUs0aw1PXDnLTe8+StwcIMPGUuVKQ9ZpzfDYtpYALKpTbKJoCBaYk22jDdEMcEksC2JINrczijSBJlt65+If3WyjKJrg3iyau7AyFV8PHfXoXyMSPQOjo/nqlxLt3ypsSxBd+dRtuoVuKkhfY0/qBCDnmZiEzruMzqTj6y0CbQ/8VPdHgThNhCaCe0umkCzgjALoC0DJ1fgZHAUTGiTnnjaiHg2MoX5VaFtKfqO+gRWyBfEBKRjdIyoepOjpgtuyDtz7qaQp6L1D6Wd7aUP21ieuNeIZ47ISYnFbNTlXU1TkaV0zdtNrl/BvCAFfAefMpLNic9yFBX1E37tmhtebRQlRpEpazSaE+hWYnC+LIBMcZRaqZ8ZDIPRmspfiSVD+Nk1jFpX227kdLQffVGpEp0SjocTfKxSjsmf4c+FoWSMby5hZk1E5N5ut7TFBjkKKFOV1G4rv2mlj4AK/9ou/VxCKk3B9px5SlG1/i1u81Gmu4DYQQz+26RQaZjvvWYQaVY31jdARaKPU+7dz25obsrbo3JhHX9rgjhv2sboyYWNujouXJhx/9gSSEldeTAzWz/L+9zzM5fOXWJlc4dy0Zc++JYbzy6xcusrCwWWWhktsjNcY5sjxUxvcc2wPeXWKNJmUlMFgRArr5NSa7aRPm7mQVgnODWeCROuT/OVV7+jaqaiNe3YCLYhUZ5hcOXp1d8ji9b1drZdemofODdccdr32XGxbXSqKfikovK/hzmhdviyK5lJTi8TiPeZjo7izgUeNsm3dOIonS5fLqN5oV2ZTEQzcBvdQkYas5uBg95Q2mtaY1Z00sgEem+edA0Dl1mdQeqdxVY3avCg6yrUQpSU9RpHJszOSTnaVDbbQxbYm2wzia6K0IPgavMZr52sobwgB3xfc9P4uGeuQTNNTxfvqfP+eMkgmxLuurkIdU8uCmE+9SuHlY7XwlsjTIeJoPZuvLybbQ+XC1dS+rMTSproYusXUUSrb37F4DbmPvxjy16A0vmBFzN89q6GLmpY2Z09yNq31RwVJ7nniz29jwRAFTQdyO8OtAAAgAElEQVSfvMU8G6u2Ie4D3QlwRdQSn0k23+v+OyjFTGFYsm8fMJW4aAGFPfEJHEIdmWuid0VoffMLhY8lMGgT2RNXDVR8vduGX1JAG5EfiEvw+CePc/jO2/ncqTFnLp5hfTxhKopsJITIkUOL3PXWY2ykVY4e2M3Tr55hfSuxuT4lyGVgjtHiiDMbqywuHGZuIfHo0y/x6Scu8Pb757j/5juYi1PG4y1GC/Ns5SlRpihzpOxuviGY504WkGSeE/2839IzYzuYKKHz1UlFIKYe5y3Fm0fqZ9OebDQV6YyQpR1ls3VaDB8zAyGmtYn4/O8l9TIDsc3pkhu9KS6LiLmEOo2QxLl5H2dwmkV669Vxls3nfgCd0oAFFoUAkjBPTE+FUQS3FpXWgtmq8BPz1a9AQ13jwa4tcEsGkUCDpn6K6pIMTUtVdr9nhC3PFZ/s2bWXmM2nR1VptauvjF1d/+V+sfHAc+AkzFgdNc1E5mptVxcJ/VpL+P0v+S9TjAsz4V793UNxxfNFIeZlErQIG/sckSqIr+GNgSI8Z6JHtefFAJiockOkr7jCn85uLCV4KvSQcK/emXeyvd9QtyIuGANyTVv7uerDNkFYkPgwC4Ocq/OoBcd4TnxNNN4y9dw0JfK3cPV9r6XZ+ql9vH3jNROStaqGXROp6Qm0eCt0pTy3RAHWvulpW9E3swaLGo1im0vUbP7y2VwQk3Sn97BtbGMr5GlAlxp+9/NnWBw2HD1yG4k52rxMijDRxFTm+NSzL7DRLpAO38Hi3D6WmwUKHSFxi7MXx2xcnXD2wnnOr6yxhrAZ4LNPbfGRzzzHZrvF/EJDO24ZxGZmvvX/CyJEP0mszJHtGs9XKr3ZVfsy9u4PiLvtXbuUu77Wa8ax/1mLT3bv9zInoUOSs95c187ZUooG0m9HQf+2Jvpt7c+33vyrXLqv1RDcddZkQdM0xGguqSWNd8mSOfPuAToM8JURcWlfBYoUTz6PX48WvKYVFBnAMKfk1J0hoLOxALUtvvmUuIhcpdHsfd2m83WC4KFPXwBZaQqacSt8qkYUTyXr3Lz4wQfQCW9NmUSuPsolwQBivqcRqYmczLDl5y9ppvEovy7oo6h+xb96dlMoExN8E9IuxHlGSPcCl8zn39TZSOOnTjmqCaZVhG2uW/PZ+Fd1It6i6wagFrMa1ZCciDKtWRw9aZT7KSefqI2UFGlO24hrMZQF1QmEabR6BiU8vjfnxP9X+8NUMV+cRh2ISB1LcS2iX4rG0/lbu/bmFE0QYYIykkhKmTSKZmg1e3sXLxED07zGF09PucIN3P7Afh77wkusbK5y75GDXLiwysEb9rN3N7xy8ipbaYPzF84glxIP3HcLJ188wXNnrnLohoOkSeK2O2/jxAsv8cxLJ1mazEMYsrK1ydZwwMaVCXddHXPnkUiThqQ0Bp1DQ2vZG3OhBqJ7NU27fhau69JZDbQi9Qg6RGzM1EL7VbFYDPHUAD1B1HqcRMUCha6jC/pTR6eSzYtKnUYKsYxX7o2H1IR3iAs59/WvLoFqmqMqtP4+ZTNoJNDSzSMDplr5/LJ+FHNuym1iMpkQ2s5gLYIFqHlAWTmpKaBo27rmavYgXMvOwfpy6HMqpWTrsoCLIldQShbVRLZoUymnpDWmATgfPqhHBxpanxS7kDgAccuGOhgREUiFLnY0HgJtEEhTsw9qQGlopcWVZ2MV6hr/wylvGAFfQt2jNEgIJGmduzH3uuiCw3bY4l4kdWFYvveuvoBAoqNj3FCHZJIbJAsvJmI55CWESseghSfOPZTQBWoUVKFJHTypBUGFAhmMHzXNIBq3HVqfuCVBV2OKrmSzxgc/b7WQrXRIJImg/vxqfCSZPy6Qg+XYNtfNPHNvCAFJBU16grUAmgMxmMBJ2rqb2sD6199xoNgBBw00yagisOPEWiJB1TyUBISGEBJTtQCeWNJAJuNBC/q3KtR9nsURqQuTUIxS7muM0iRTDCQGmFqCNI2Z3A4YNlPWUstyO+T4lXke/dJJDhy5mcsX1tlIW8yNRgz27GXXaJ7VqxMuvpoYb6wyWNrF+voqqsKzZze4/75v4PHnP8LZCxfZ2tri4oVL7N+3m6M37ePM2UvIwA4nSeMpaW7I409fRvI8xw6NGQzm0ekmCUFzctqg8BZCCSIqueY7zcNTMYsL4d7pWhEhp2yeRoIZ0oPZKIoffRnjpF3a4q5m6YSkmMZnWkSsJxEVmkt1SpLCaVsmUwqFSDR3TSKalQZzw20dWaeijYqdDDUo3jYCuHaZxbJHZtTBm/nZJ99AWgJkIcbGNpVgYCuH0KFeBCQjwfISTadTBy2gSclkJsav2JGVeWz5XkgOBnJHf2mxQJicDtHyHyV3U5QQ0ZDQ1uI9kth5Ee61ac4K3q6WcmZwOcyjJaXMQNyDLSs5QFLPnSQC7nVnWrb6pmh9Ii67jFL9yjLzqylvCAEvQIzlqLaSY9yFaKVObPrmbH6zlVYJwbMNygzCLFSG1ieAxGLKUMrpKQ0NSK48vXl9OGdGUbMxoaJqiaR66leI3VF43fsUH3NHbGKsmyXaExppOpXV0YydDFVUge2UjAnhIvcbibM5xf3+4NcN6ruXa+xw5+qaVeiDphjuuoRsWTPB48IsB5nQxEDMZqwdZkgSUU3GEQpoYx4wWdpZe4T6q3iCb+2PTRRGWjQxKBTD7Gu5itx0h58UNNVoIA8S03bIggy4FJVHXj5BDpEXXzxFbITbDh5CstJkmIwTW1fOsEjgTQ++jc2XTxIXFonTKTftGvE7H/11jtx6kN1zAy6cPc+4jZw5dYYbbrmRxfl5rq5uAhDmGzYl0S7v5okXL7K4tMyBXQ0DYOipDPDNeNK65uTIuKQ/7tMQVYVX9TXQqeoxFuHqY6wKyTb4COQatKdVuBdPko5uKFtqJ/5l++HGYF5iIoi21RBYMkEW1Gu7AXXe2jrQWpVEszuEgtZjN76N2yCSZ5vUYvwU11qDJRyz+RhREUbO48eyScUB65t2VGDTNPWUqSGWWjn6fFc/FjCoRdSa3cpz00Qz9FsfJzQEJI9nctTknMkEm8tASObrLj421QPH67d7PImYbzATsdO7su1LZlPQ7HmBfJmrL1p3Iy6nkzU+3n8YfvBvGA6+qHzADEUgIuYyeR1O3Txc0sx3dhiEzlzb58W3F3Pp6nf6dh/2WXW6b20vqL58Uzn2SnuUNpuKHJQ6CSlubUErt2muote2s/QBvZOPZrhcnT3PtbTbqJ/Q2SwKJ5+lhtrP9JO6BhEEJNKohYglwdRguikXpCEH48RV7czXYc84XGmq3vvE8n3dtPXa9/H3VLENu1Aw2f8u16WkJG3QaWYzZz734lVyO2Jj3VRcEWFt/RKHb9rPybOnuHrlIg8+/DCH77uTYRAefu87mVsQbrzzGOM8QJd3cenSJSbrWzQh8uA3PsRocZFLayvoIDKaGxIEFkYjFoZzrG5ssbBrD48/dZqtHNDUxQMUqqL8HZBtwKPryW5+dEChXBN84y2b73beO9DRgeaa2WmW/fXUPavngldmic5+7lwkPfuhFiojdjnl61m63tZ+riQXWEFhSLDEb2qaX67h5Z3WaxpeIBIZ+PUD/7sYk5PCOLdsTSc0IRGlRbSFPCVKdi7bArmiNMQ4IDZKHAC0JiMiDu2nRM0EbYkoAylJ2gIi0TzTQlMDC+u62XaWQ1cCEKpNrZRyHsXAtYWGUO0IIQSihHq4TdmwmkK/RSWF3KWEeA3ldTl0+w9a5hrRW3Z33hhSQ+CL4OovBne/Eq3RkqX0BYrVg1ujCwEuhHokW3SBY/VHXw1FiMwc6A3Vz72iU5lFY90i9DS4/gwJnXAvCyRKg2qyHDTqRiPPp0HoJlShj/pCcIZ2KX7CAmUjMoHYTcC68H0TsAARe1aWVIVQRwVZDp+IZVW0U34y44H44RdS2zzIVEFshidTTQu9Ur1BtqVSuN73fcNW+TzDUde8+37dcMh0c5Vn1+HJL73Mvn1HuTyecunSFVY2xiyN4JsefogxUyYb61y+fJnxdIBOMqt5hckVYYWWI7feyDvuuY2LF67w8c88xZGD+zhy6Aaefvpp5paWSZtriERWx1OWd+9CohACDFJkYaSMxmMOLgTe/cBBRKIlMvPRz9mdU3K21AUuLAsffI2bpwvUrJ1LcD38WnvzM2tNhVDGOmc7IrB/ljAw87mLgO76e6buGhzUze8CBOr1np8n9QOJspLCNhDkeWgKxaJiNEcJpypuz5b7ZULMgV23HLUkX6VDpqVt1mfEgDAEEaepIrlNTL1PKX2WcwV+01QolM7/3Z6dPZdRIHhK5q5PUu0rUdcIZHZO1rO9S84nLQeMOI0ajbosfeAV23pVc3EmK7Gxw8hn5n9NepP59Evrb7xDt7/WUtFH6FzF6hyW2UM7rkWszAj32e/KBhE6n936TJ2hDopLmOg2dNnjf663KXZKb3ADTHbhbkFMxbimko0j90gmyR2dUYxwRYWdAfMedi29iVxsEJVL7V1evIqSdH2o2bjMJO6J4UnHVKnv1jhtnAIM1YxOKdhEkRz8OMsSkNblyxAP4CiJsSivsm0DBttEvKeu2SgLaqs+8h7QVLWwYO6r02nDwuKIj//Gsxy8YTeLy/s4efppssJNu/dw9OgRLo+nXDhxmrbdIo0nNMtLjLc2uOu2W1lbPsultci54ycIb30rlzbOMRcjZ86dZ//eZZYX51nd2OCtd93J5njKK2cvMGlb0rhl9+5lDuzdx0giF86/yNm1KRpGRE2es0htDLOhVfFNMwkUn/OZd6595IZS7fqqToGeZhbEsw1qmW6Fo+7mTv/+3x/EWfyHRYpHp3V8vvlCrC6epW2V+unNOW+t0R3FfbM39h3LY5Si16VEc8rCsnyWWmPosjMmFG2VLGOfF7lGzQ56kahNY04Sw8EyAJevXiGpMj+at40pBNq2Nd4+Q8pux5LeaWYhECTXM18l2O+5phAwo37Xr+rva/cWCgv3uBNwl+xy+pVYRmaxqPsQAkUwqaoFRf0hlTeEgBeg8YAmNFkeDxeOlUdWNSGvJkyIYseDSXdKTCckikta2RtCnZQhNK5UKWbeaezw+DJA0Z5Zk5KBe3543b3nRI+CLVkrTfQpEiNZW0strH4QX7CBW9DAFokQRjRpjma4xbQdE8I8NJHcjolhxDgk5hSmZEYyIE+U4WIg5TGNDpiK2fBk0DAleRvE1tzUcVJc8ux8awzClMl0N6mZmlcNkeE00S64nUMW2JysM2pGdsADGc0NEgMTnRJkRGKLZjAkTIUkQ7biJrs0Ws6QZo6sLUkSkzaw0LTErEwHI8J4QjPXsJGmDAYDdDohRrdlDAbElGhzS5TIQBaZbF1kOJgDEuOoRB1ZMFdOjJohWyEx0jVyG5hrIjcfPMqXzp9iVZXl5UUWl5Y4ffEce/btIyzNc+7kFZtLF9e45dhRjtx6M4996hzHDoxYG4+47aabGF9aYePEi5wgcvHKZd5271t46sUXeP7ECd7/ng8y2n+G3dMJT7zyCocP7Gdtdcx6HDB/5BjLBE5fUm451DAcWwqGlBLatMQcmDjGiBrJwfyfE5A0IrGkHDbBn1IiRBMOBb0aAu1oPHqbe+e7bVx8VAuC2s7ednlrCgXZP9Q92kHbwYyEtimYj3jZgIMfyF1KrJk2PepWbRMoDgAZkNStlaxKG20dpdRLDSyYY0MOpI2WwWgIbUsOwiT3hWjZOIuQDBXRpLY1HhEYT+zUpE1dQxU0mdPERju2qPGkHtlu6DsCaDkIu4tGTdIQnVdvc3BPNSghTh7cyhDLKGl59sU9dhRcU2hiQ/Axzil1Ed3ZNkJVi6MxW7A6jVqOC+zSR3yt5Q0h4FXK+DjPK13DrsfRdm6R5p4kVcB2fvLgvuRSfEqduyX5InE+TBWKKiVmCDPjYDGClnb4AtEeiq5I29sTDF0J7hudATzFLZmGObaalsVBZGNlgeXDNzM/HLCxuYLkEcO5BmSNtfE6u3fPc+LUGcIY3nr3EU698hybi/s5mPZzcbrCKCsHDh3h7NUrHFjcTRg0bEzWWQqRFy9e4NTpV3jbfTexxByrk0X2HT7Mp598nIfvvZUzF1uWG7isLXs1sjAccX46YX60zGIM5DBkqx1zbv0y+5dvYHL2PKfSeRZWE3fcchvTJtOSuLq1xNEj+/nYM8/x7rt38dy5wJ7lOZrpGi9NEvftP8zW5bOcTVMW0oCjowU2Nja4mCMHF5aYrl1BN9ZZPnSQrQuXUGl5NZ0jNkOayxdYWFgixSFpeoU9zLMlGQaC5JbYKutRef/7HubGe+/iuZ/7TfbNDRCdcv7cado2s7a2AmSGc0OaJrCxusb6xQuMtm7lwbc+QFxf4Vs/+C4+/B9/g72L61wJgV3jIYshcmlthYM3HuaBe45x/NRFjj/+WQ4cuwMmEy6uTIghszQMyKbCKPHYS2dZHu5n/7zgLkqITRejEgUkJcuCqYo0jXknedrbnJUo6nS2RWIWUIMbJAv6KweDKDhit3mGa1eJYnh1/aoH4PuaYSe8pXq0dGtulobMuaXEOphzAeSs9QCOYng0DcQSEefQtTE49ZDVqNVWc5cKJJsWmXNCNXva3I6m2k5nzVB3xWZGR29lyTVIyDR0qeu1QDugJh9sNbsdIVQqx6RLl75Bs9b8Vd7b7oVjCD+oyYqs2byNnMrN00TS7sjJbjAy5MxAYs1dj9qhNZrKqU+85vKGEPBA530Bpsr1ggnKv3WQpRPuVbgWbp6OLikTtTt7NHbX9QwYNSJQuu7fbtDtLuzIGAieSXG7ClzUTE8Y5lGEk8k6S4yYTuH7f/Qfs5GV8+dO0TBi7+IS7TDz2Gc+xaUTLzPejIQ9+4nzY978XX+K3/77P8b9DzzEaH43w+k6RxeXeOylF3nPBz7IhY1VTr34Ivfc840s33KYz/yzD3P7m7+NP/mnfpAXxldYOX+CJ558mktzd/DLlyKrryZ+4Hu+mb3s4q4330HOmfXVTBMSE4WP/dZv8OBddyEvHueZz3+B/eEAOc1x/9sf5Hv+4p/j//zXP8XHPvpp3v3A3azc/hae+8xlvumOD/KRz32BNky4855bGeYB4c5beOehw6x/+tOkfYe4/b3vpd3Y4pGf+jDxpptIZy7yrne9k5WhcnhumRv2H2A6nfI3//aP8MN//m+w59Bebj50iBNnzzNc3oUorK1eYdgE0uoaV7cyn/q5D3PDBDbXV9m3a8TW1ha7F5YgDLi0vkqbMmmyhYwGHN5/kCtXrrDrpsM88olP8d3veZi5hXnu3LPA2nRKnmaYG7I+abhpeUQDvHjxEmfOXuTOB97C2VOnGe7exblzJ1haXETIzM0vsfuGvRx/+lnO7B1y8NZdlo9fBE2ZbImBKDm+cYHTF16idHYbZYZP9j+qIO7z8/TWRAn+KjYYo3GlksXXcxIo33ceXZ0wVUeTeHtEytzvhJx9ZwdWCF3Dy7oLJfCoZ+MR52k6rbezQ2W3KxgTUkRoYSe7Ouo7FOHudqBCdQLVpdEcVYTgPuxJPHd9r65qg+p5781mk1C359maL7bCciShjZv299FZmsxlSaudq2aXdITa/urs0WyTO6+hvGEEfHJZ3QUHaf3/fhBUOZ3dkIEiqf+b3+FSvnBZ5f6IUk5fL52ZsV3TBt2NWCFYNrvQoZjQp4u25e6w73MvmMk41ljRmGWPCzRMgxB0zOqFy6xNVlgezvGl45/nV774EmThwrlzHD60hxtkgYV98xy+5UZyGvPKdI3vuf8eVs+8xNxc5PP/4bd44I9/gJdf+gLrJ0/xzd/4TiaLC6yePs8VGbP5xJP86MX/je/5M3+Gf/Pzv8IXn32RK+fPIcMBh3bdCJNFQmj4zV/6Jd50/wMMm708deI4b7rpKA8evZsTz7/EbUdv5233v40b7j7Cx/7z5/jdT3ycX/mzP8hdt97L3qO7+Lc/9+/5c39+nge+6Y9yfjXw43/3O/kPv/soD735Xn7ldx7lR/70t/PLn/g0t997K2dfPM3v/frPc+7ECU587BGOhHdx6x23084p9990G6vrK1w9c4JzJ17h4YfuYIM13nPHQzzz8gvcfOQQG2N46eQpdu1Z5uyp83zssU/xpd/+CJdS5MLZFfbtXeLw7iWeO36cybywvrnBrj272draQlNmMIiMc8v8riV+4yMf5eDigH/+L3+OY/fezvve98d48vH/zNqp8xxjRLs4Iq2uI8PIS8dfIE8bXr6wyQ2HbuOZl7/IQIzfvXDhApnLvPDC8wwFTlxseeudbmRLrefWadwtD/fvxpPgZWLAg5Ys6jiLmr86eDrszngXelx7DqGXE8UFSNI69W1eFuHYM5gWoePrpB9QY3+ZF5QvBctLHhS1TL1AqDRG39hvRlRLf9BpAQbashZ3WzvIZBgjbbY4lpw6A3ISM4jOiXlQRcw1sdc43/x66N3lgG0i6itTqx2iGE4TqQOIQj0QCNznPrc1BxPgbtd29KRx4qaB19QbqnUDKdqUOC1meWVce1H14wQxm4FrNEkgYH7yqrmeCSzqB8KokPUPh4d/TUqAiLwkIl8Qkc+LyGP+3T4R+aiIPOf/7v2q6qqBu7Xua1BHpGd8lV7Is3RBAX0qZ6b03QV7qmiQLtUBdP+WVm3fhTsXzu7wYcJs9GfhTS3NbUEYwmjY0IQR4xzYXJ9yy74D/Pyv/iL/+XeeZrwyZn19nbtuuw3ZSLzvW7+RPFLavEC7OeaHvuv72Lh4icePv8wrn/wi9z30DRw9dAs3Lh/h3d/13Zze2mKUp9x8aC8fese3sPe+Ozi3OeXH/p+f5JOfeowrl8/R7HorBw5/P1O9wlTHxPYC5y5c5bknnmQwWOdD73grP/1T/5rFxcy3fev7WR0NePz8K0zWp/zSL/0ix44eo4kjtiab3Lp7L3/vf/p7fNcHP8Tnj3+JV85cYahzvPnwHfzaY8f59re9nd995FFWXniRY0cO8f5veQfDYeCD3/o+bju6lw9+89sJQ+HyiVc4+coLnDzxIruXFnjom76Zb7n3XlbOX+Ff/MIv8O9+4xH+6U//a6YiLO1a5PSV84SFAScf/wy3HTnIwjBwee0Kjbasb2ywtLTESCJzzYBpakkhs7A8Yn5+hEwmtFdXecdb3sJtD9zHkdv3sWsU+cTH/z9ePbfKTc0c+285zNH5hvG+ZV66usFUA29734PcePOtTKeXmR/ewOimebIK83OLTMZjQogMFgacvbRCFmjbCU3TMBwOfd6a503xODKw0SHSpucbXdFoj0UvLo+dBttLL+0lRzOG52h5XcrnQA9NOkrernCax8l2LbSnVRRDq1qglBD9oPbZFAfbS5KSQ8neq8FiIQT7sqQRMFuaC/TQj6i+dh1f8969dZdnfp9tW/HC6ou8svGoRIspkGiaxDWvJPRdQft1bH9/EQ+icn69uMjaJtujm7J2akavVOcRvnLffrXlNblJishLwMOqeqH33Y8Bl1T1H4rIDwN7VfXvfKV65gait+2bfaHyojEaB2mh0sXN0K4JntK3qk2hp+64ilnyyUQiUS3YpwhrVYhlAumsn7H2NApVpQmRVBIoeS6XQZT62XLmREQiUZK5QdV0w8lz0nvo/eYm8fZ3kQYD7rr3Vh75/NMM1jf5zj/yAcY6YeXyOk0TWNq9zIXTZ9l94CCf+fXfZN9tN/KtH/gW4r4bee6xR5g7cAO6MWbfDUeYxDGf+uxTLB48zD/+8f+DyeUxkTEpwTc88L284+3fwkPvnGN5OfADf/p/4Ed/5G8Q5gcsM+HqdMpSs5etPOEnfvUTrFxd5Xs/+BDtJLOaMpvtOl/8/Cneff8R1vbdys/+y3/D3/tf/yqP/tYn+PY338mLo13cecdtXH3+RZaXAn/zxz/M//3Df535PQtsrm8xP9cwl4S4uMRjv/Ur3HHfw/zKL/8aD7zrLZw5e4GDe49xYGmOK+stv/job9DqAe5+8EMsygpbm7s5f+5RPvVbx/mR/+UHGRL45KO/za/91L9gbW2Ng4vzNAsLXN6acmxuwI037+N3njhBGEZ0ailid8+NGE8S973tQbJkHrj7Dj77mc/xxPPPMZ1OWVrcRVgaMlof8+0f+iOcOH2WzbUtttav8sVzLzG9OmH/4Zu4ac8+Lm1cZnV1nYsXrrAwN2C4e45dGc5eXmExZv7ye+8hN1tklknTLbf74EjQhPbUDwIpaLjGMmVLYCfZOO+S+iL30KgBuy5gpniSVGolmHAp9eesJvBzrgmy3B7ZRWVrqHO7RJRb3T3k7xx19x2YyuDv4IBTnQO30z4aeydH8S3ZbGhZq4tvwtMGAOvjMUu7lpmfn2PYDIzjr1pBZ38otJaqBUhOkxsjs1oSNAmeQsDalXqEiPpB4/331Dzw21sPcDQPoSxUTr541Rl6n+3zusF4ymIRe8c+0q9FLCw7pVzPXg19wQ8d6gcee2XymtwkX49Apz8BfNj//jDw3b/fDYVT7CcNK8FB9bdeEEgJFgBqbmihQzqheBz0/MjLBlFKmTRlgczs9oXqoUME2VXX4t0TQvCdv4v47JDX7NFhxYsnR5tsu3fv4dZjd/Ded7+PX/vo77J55iL3vukYZ858kZjmmaxu0Q6V9Y1NVgmsXLnE0v693HP0fj775BP8zi//e+5+8GHmmoa1lU3G4RJracy/++hv8g9+5J8yubQKmmni/Xz/n/g7/LW/+iEefPuUBXaxZ+FGttImuj7h1PMv8PKk4Z/93CfZdXQfnzp5godvPMBf+L4P8dQL6zzywgm+8OiXuPzcq+w5eoz73/kwV55/icFwif/5L/4YH3jP+zlw7z20Swv8rb/+T7gwGrK++x62Fu/m109e4Jlzr/LkU8+yNJhnPIjE4SLv+5Pfy8WrK9x684188dNfJKy3XL36ChvhEvBiGCwAACAASURBVL/66Ef5xC98hEP7HuDciadoVFg8vMXyvnt5+/d9H3/rR/8vttIp8qsXaJrAKDTs3b+Phbl5wmZiLQTm9x9g73AOacdkHbM8Em648UYevO9NfOHzn+LE88/wxOc/h6ZAWsmkzcj65atwdpOVzXW2Gnjm+eM8eepFFo8cZqjL7Nm1j7FuckWnrE8yk3Fiz9IyaxtTLpxf5cyVRBgO2JgqW6FhIytbeYMmFr/rPDOfBuIJ1RRPrqaWtCJINRKWc3xt/nQprPuHh1eh3gNp1/DUtY4e511Q4gyY6fPnHYIuWm6/zmJM3Y4wjUoKFqm9LZBORGbOK+5bfmu9Otv+ap8IASmnOanTGzFCENrcURkdH25baXLKA+/rWDn07j9V07RL8JYh+B7YlI7q6mtQ20s/sK8yBSVBWq//s4rLkpJV9VqU3m/hay2vlYNX4CNiW+E/V9WfAA6p6qsAqvqqiNxwvRtF5IeAHwIYBEMvlMmgbpzCD4vO2yzqvU4sCDo4T4kj96QgQQjanWaOdLxaF+CD1VeQvAv3wtuXaVg4f5Tec3DLuvm6C9ToVkSINScMhBRQSZZvIwif+NxjyGc/y3d8ywPoaJ7NV4/zucfP8d3/zVs5Gm5inTF7miG33HiIfUdv4dldT3LDsWN86ePP8x0f+m6Of+kJdu/by8uM+ds/8PdJIRPDPMN2L//j3/0n3HlsxMlXn+E9734f48kKC4tv4vMvPcVP/9Qvc8PhQ5yfazjzSuDVs09y880H+bf/9mOci4tcPnMVBlc4ekvk+UdW2J/g+77jj/HS2YtsXV7jz33/H2fulgN8+nc+xaVLF5gORvze06dJF5/gH/21R9g/WuThd72fT/zCr/IfV87wZ7//v+Wv/KP/nTuP3MB3ftt7GLdTLl6+Cgf2c2MYcPSmI6y+epyf/sXH+L2Pfpxv+zM/SHMAptO7eObShGc/+RJHDjTcfMdt3H3zYa5sDPnJn/lJbjqyxPyuBaZzQ06ePksSZWvc8tnfe5LYBBZknvF0wupWS1xZ4eTJk7zpjtvYuLLCy1/4ArvmlvjGd7+ZE8dPM7egrG2t8+a7HuLVEydZv3qJ2Ix44rHPMtq7yME9Bzjz/AluvH03ly9fYvdwnjNXL7J3714uXz1PnE/cdGCJrZXE2ZVNbtkH0i6woVuEaAI9OYxVXNsXcT95yG6ridlyI1niK0vWNXNUGVCDAd3YaQqubQwxRrRtiZ6vJhbh7SeGa+HtHQUTOk22cPzGzfuczy1VcxDjobuI3GJ/8s9+bGZqPUV1M0DbZNqCUMFbVq20jfoRhq1mmhBoJJAnLWEpUJLhqSqksgkFt2fkSuiqawRugqhCsS+CSxzFNvlT38GiXalsgLlxekrumXv6dgzTavo2ieLZNLtJUf8WiWjuzuNVDM3XDa7X+NfCrMy852ukaG5S1dMuxD8K/GXgP6rqnt41l1X1K/Lw8wPRO/a5iPSISPXkWQPPQS2Rakgpmd/KfxmD7pW68QyTjU+Q7tSk6GpZP5XBtvDvnvdO/3tLGWo5WCwC1YxkuLFV1BOiiRmcRISmdwqASCRpy3A4ZLyxwQPf+xd48tHPc9c99xJzyyOf/jjveeibSEuLLA7nuOnQPGvjCf/p1z/Be9/9Xg4cWCAPFnn22ePEhcihQeQf/quf58WXTzLZSozSHv7sf/Vfs7J+lg985zexa7jM0g3LnLu8zp03H+Ynf+5nObS0j3e9+5v5K3/pL7KwfzcHDxzlxLlEs3uekV7lobvv48ZbDnNw9zwrL5zilVHgzXsP8753PsR//zO/yHtu3s1thw7x+HPP0Y4bvuPbHubDP/kzPPKlM1w5/hR7D97C3rsP8ewnHuPme2/l2+/7Bn7pP32MN73zm9l74x5+4Lv/GOK+zV985mnuOnaMtbWWe952jIfe+QH+u7/148wd2sdvf/IpmqUBWxenHNk3z+jWowyaJT79r/4u03HL8t5NePkKS/v288rlc8zJiPE4cct9d3Ly+P/P3XuH2XVVd/+fvfc5t03vM5pR75IlWbIkW7axZWxwsI2NO9h0QkKxAUPeBEhCDCSE0EuAAAnFAWywsXHBYONeZMuSLEuyehtpRhpNH0275Zyz9++Pvc+9d2SSvInzPD8/73keadq9p+y799prfdd3fdcB5s1opvtYDzmt8VJJBvsnmd/RShCOM6ejmSWNdTRU1vGLxzYTAscLBebU1FHf0URtTR1jwyPs2rUHP5mmypcMZg3KTFA3fTYn9u8mryqob/BRkWJocIJB4+GlciytaWdWU5Zz5jaTzecdGyQqJvRDJ2YVVz/G0EzoKIbScaNxRsR6e7GBneqxT/XaY3EqW8QjhOXNCyEITNyaQhQrXaVLGsZFajbZWsL1S9BRDEla+mAsFuZWmYOdptqPmOOulCIKYyEtF5ljny8UJbjDGEOorYGPQo3wFLWNdcW/x1CMMcZp3ZT01yNjIyRZHFuKmk3F8dJx0x5r/oWOpoxdLN53ahRkoZoSTIP75OJ7tvuuLF4/NvxFCMlVoUXluRNkSbMmNgyuA1jRiOjSmBpj2NQV/P9XyWqMOe6+9gkh7gHWAr1CiDbnvbcBff835xLO641LNHxTgj9spyVRFPYRZUkphCk16HYQSSyGazkBpph5j5tslCdPnQ6W+68UME0x+i4zL0Vom3IIe85IWK+rFEJbbFHGKoqu1NmycSCRSBEEIblcjuGxcTIqSSYJhdBw2umrGE1kWdAykyCc5IWXO1m+cCmXXngBze2tdA8Mku/qoro5zY/ueICtG3dSoav58A0f46wrlvCB972f2+/5DkFg+NDH38Ftd99HTW094fgoH7zpXr7yub/mwUc3ka7ew+GuE7zvTe/gty/s4OpzZzGeF5x31gVM5BXJ0YiFy5YxMK2dZFcvtz21iVs+cyvnnPlGGte8hZs+/vesP30Bg3ObaOwLaZ+9gr7fPU5z/ULq2itpr4DjNc2sWrSG7/3mIa54y5t59ukNNPY20PHR93G4p5dtT25iCI+OdAP1DYYz17yeK9/zSXpEBrG7m+YZi3l508MMdB2g168h98Qx8p07qW9oZujkJGKswLnrzyPRUId4cRO5MKK6pYPqsED9goXMmuylOZ3mQD5AjgtmLphORRDRMWMG9Smfm666msqWFJe/9Uru/OYPGKuo5ERXPzu6DlPf3Ez3iV7S9VUo3+NI1xhrVi+gL5tlxbxZdB/r44y1i9ixdTtSeTz/zquYtXYhhw4c5s77H+MhWcue7m7m1TUTJEOIFLHqpycdgOd6ocZlLF5MRyTOCQmIYt61a8/nPPWiFr7zYSNXbWkVU0u6TFJ51hgKjUIVcXCb5XS8cdfU2/nmUJb4La5JHK6uYy/TWMNmX4DQJag0jowBwsDCTDLGwmMJC1mqdrYbBPjKGTklLcPGQTk2wBFFCqKJawtMaSOJLYENqmVZzsJ51o6majcMXZRktpuXKkYAQJmchMLIVyayS028S/UMU6iO7nkMVgyu3IOPo5ESVIPz+GObZG/ZgJVzNqaEPLyK438M8wghKoSwfDEhRAXwRuBl4D7gXe5l7wLu/a9PRnEXLcf54n6dpQx4PNn0K17nGeEEf2KhfofDO+Na7Jsy5Rp/5PHLuLzxRIt/1qZAVEwLSYT0irzdWNciTs7aKC7G+WzorXMFhIEw0gzlcoxFmqGTA+QDw6zmZmrwUaQRpoqFM9rJ5UYQ6TSDo6PMbW5h+sr53PypL7Dz+b14WvLoI/dw9YffSPexHkbHC8zMNFBbUUFX/wCPPvIUrRUtVGZ8lp+7hp/cvYF93ZvQBYMnfbygj5UzFYd37mH1ylWM9o6yoK6WhasWAzn++b4HOHDkCMePjVI14wwSdWkO7NnLO6+/mGNCcE7rCu68/Yc88exGMl7IorlJZKaevqMTdLSmGRoco3nW6+jrzXDVpevp7upk694TbH75CPNXLeL0uR30bNtASiYIJUxbtJhUdpjJlmaOdnYxtPmX5A+/QP+Bhwi6dvOpHz3EmuveBtEkUV07QRDxwjMbaMpUUyuT7NjwPEEhpK6ujltuupGbr38jF7UnuWp5M6+vS3H5ylm85fSFvOeKi5m5YiEVopHqsVHe+eG3c/raRTTMrKG1vgG/oGlubKJK+chsQF2dofv4AD2HD7D90FGWVSoefeRZkqFmqHeAOVddR1+QJFE/m0//3c307D+AyswiyESIKP1KpVETEQlJJCSB0YQYQikI4rUsxZSmEgozZS1MhSaLQW35uix+LeLoumRclDOm5cbm1K+vWJ5iapRbXCplOLuUytKDnZCddGyYKfhz+bXK7jsugiouP21K0h3Fe6D4/BIXaTsc2wiF0LIoYieEldjQxTEUTuhPlKmbqtI6Lm6kliFUjovHSdapxv6Pm83i/Uox5Xfl/4o8f0qNVKaMq9uMyvOMr+Z4NR58C3CPuzkP+IUx5vdCiE3Ar4QQ7wOOAtf+VyeywlQuTD1FL0ZqJ0trHMVKSISCYj2rYx4YNJ6JPyyQ+Lg2BLbKTNi+KyXP3WKbcQMK6SaQdS5KZdxCAcZWnIUyaRdaGR/eduux9xz3rY75siXOpUBIiVI+2kSkMJy/7hyeCTcyry3NhPbpH5tkbtsSMjUp6jM1dB4YJ6Wr6fMm+drX/52+vYfJE/HZD36Wcy9YwQf/6ma+edHFZCsTdC2eTyQV2UwlKdnM0c7DzJp2OjsOHeLMtrnc9M7VnByZJJudR2tlM7XVCTo6Opg+rY6L17+Jzp5D1M9bzcZjXVxUV0vvyS5eemQbu2qncfPb13JscphwtIaGOe18+eZvcPMH/pSGGvjM+2/m89//GRV1s0lqn+TkENdfuZ4Hd+9C9o+wuGGM55+7n9bWW/Dqp9OaytGyeC7jwRhNM2ZzcGyQ119yCemaRTz777+htsmnZ8sWWmd0UEgsJl81yGXTX8fdR1/gc3/xAVSun/OvvAK/cjpP3vMDFkyfxWNbtpHJVCA8RVV1htktGYSBmQtm8MlVH2F8fJxUZQ2FXIFZy5YSVmRgTCHmNNKxdC4jR7tYWhAEA1lqa5ro83xSdRmeePwoUWSorGnF5APmdsxiWpVHP7V87q1voPOpp7h89VWEJ3poXrIAc3gn48cNnzlrHT/e9Cyzzl1gJXCNBulblgrWC/WRGG1IyPJaCpvPMcZVlQJKSgo6wr3R1nBIy52OedsyXsHaeoOxQJ3REUoKtJboMrpkrMduDI4NYueoErYmxDards4UtnoVIx033jUJsTPa4faRWwmAAM+3sEUUhUgjS5LGcbRrYnjGrmGFbSQihIQocgwj5ZaPEyx2fQN0pEvROJbubM8VFS2Z1kVtSTeuDmZxw+TFGxAQSwGEWPw8NAEogQyx/Dvhkgfu9UX2DBausbpM9n5ib14Ju1lFQiJFyZO37mZUluC2cguxrnzRFgqB+CPRw//0+B8beGPMIWDFH/n9IHDhf/d8xR3O2OkTG3w3m9xrYs14UfY7h9uXZVUsHn5qqBk33BXFoof4+yn34f4WJ1njejqNE70yETErpnQJRwtjqqrd1NyYLSLP6xwAe46coKK5nlBJqtLV1FcWCDBEUUCQNeSkoC/q4W8/9nV3gjbOWXsOK87vIKmy7Os+RpfU3LhkJc/t2Y3Sht6BHnyvkosWrWHt6qX4XoaR48MM9I6izRD33P8i77pmAfUNdbQ1NXPaink8//JmTpu7kEe3PEXvsOKZwGNmbQVJaVi0Yj4zpi/nl//8r3Q0eNz269u54G3X8vz+/bylfQY7977Ige37eeulb2brwZ3s3fR7cmGOXVu20zpzLucsb2blquUc69nMjIY2+oMKcmMTeIHiWNcu7vznn2CCgAW1tSyQE5w1kOHj2SEOdQ5T1XYO46M+OweHaaptJ900nyPP38byc/+Ep3aM0FhRje9JMgkPEYXoCLq2Pcclb7uO+qoMvq9QyQTNHW2YQCKETyGdJhGlCKc1oxpaoOswFcKjrrGBJcuWsHnDi+zbc4ie3j78fIQ2Eb1DvVQ3tDDe38vAUIo6P+KFTQdZ1Tqdw4cPoP7mw5juScJkO17VAKuWLub27RvxMBScvrnNuxs3P2JAxBbCG+0SedImXctnZCRccwystlLkckmYksojJkbTS7mlKWwXSglRHBwQN5KPX1PE5U81NCaBZZiEFp4w0pERbHEWxkI2Fk4o46+jioWBCmtA/8gqs9/JMrpm2ZoykX4FB16IsmJDXZJhiM/+x42iLuUoRKymWtLYBxBaQVwY5ogURhZvsej4xYMmpHH2pvSiYrNxbaYke+OjPGFrcwuxm2jxent/TrIhUmXvLPyRZ/q/P14blayiFKYU+6nG1WfKYl+lalbnQTtsG0C4bkz2+3iw436n0ml4lIVL8WXLQ93y7ylNNiFtVGGEY81IFyUYF0MIQMRMHbsblVPM4u+llHiRIK0UoqoGESnyfQM0rjmDXBjgC8lgTy8PvbSLu3/3DJMnRqmrWMbt3/4XVpy9mM0btzN/VhOf/cr3GD98FC8xl3Z6uf2F5wkTHhEQaoVUEX/z3W9xxaXX8PM7vsxomKKqtpr1i0/j8596N5BgZkMD56ydw20/+SVtpy/h3R//DNUVjaw8bQmdyX7u+u19vPvdV9F/coK/+IdvsPy06Qz0nuD7f/tpqrVm3vrVXPv+j3Nk91Euu+h8Xtyzk+Wzp9M7fRqjR/t4z4c/x+joCM/94WEmR4ZpWhiRzU9w70N3MdlbYO2611PZe4ju/ojWxrlM9zKsPDHEV4afYe2yxezduY3l4RiLEhX01tYwbTDHY8/+gvMvuojnP/c5kq0zmTZ9GrPntxEmFCMnTnC0t48vvOOt1NVXIVMJhO8Tak1orOATyQx+bRtUNYFqRGcqCZPd+NOaSb94gtaaSm5cu4z9HU3s2LGT41t2o9LVbA0UdamQfKKJtvo6egeO0Xm8G9WruOy02Rx78HfMmLec7FAXqqoRvyrNaK9CJAx+5BUTlVI4iVtpcXOlQIRWdVG6GgvlvN1TFU8B0LaGIxIGqUvcenDeallUKcoNOBplpGOeOW/TeesRJYizpCXj7tOAlDaiMNpWpRgR2KYUKJfIlJhYEEyUjHQRr4/XtGPwlH7n/u7WsXYOFZTUFY2JXbKpR+wBx46UVQ8xr7imcMlqq0eFq7iCgIjyFpE2oYrtHmXjBIxTL7QBuMA2IXKQkAndOMXncL55Edq1/xVh9XjzctWqpmiLbDQny7RxLIxgEMVE7avH4F8bBp6S12w7E2m0iemIxN3FpsrAuGNqBZ6TKXUhYBGGIU7AnvreqV6LgbKNRCOER7kbbjvp2KQPpqxIyu3kpQ1IFJ8p/qCMcQGuFgQ6ojqhaWxr4cTgMYLxCQoyYlt3Fz/78WMYcnQ0nc+vbv8MT7+0gd339lLI9rJx/x4efvxJEnikGpbTN7CfGY3tnBjoZd6sORw8PsL4ZJa9e/awpeUpqjItvH7VSrLpiO1Hcvzy03fQt+84775iPqMFRfPMDjpfOsxXbv00L7x8EFXI0l4lOdI4j3OXLOXweJYffe/bPHZwE5dffS2nn/UG/vDMIyR7s+x7fgNpknQfPMj+l15g1Rm3QkEzqSMe/f73aGqfToXIkqlOsYx6+rPj7LpvmIrKBHc98VOCseMsmd5KiojJukqeSUyy8nWX8fKGZznznNeRen6IvZmQY0cGmZSaNzYvZcn2w+xum8VEbQZdVUn/wAhRBFWVNaRO9mGqPdtFKBehEmk0IZ6WBBM5ZKqCcCKPXwWiMg3RJPnCBNpkqaxMIUdH8UyORp3lkkUzWXblRdTUVPHVL/6IO3ceZSCp6enrxeRz1FdUsWJRB+euO49Dh7uY0dCB6mhGFFKkGusYCSO0EoRBVPI6jeVcK2F1/i1tsWTCigJ5huKCt+G6ozYWF7xNZEY6Iu4IFb8WShFocU2hyvgyU+e+dH2Ai3IHbrbH6yxmr9iKbFGESU1sJEtnK17PkiU00iljlh9xIxK7OLFdkox1mkxZbsEY4wqv4lX5ysUbs2TisSt3pv6YcSxW8E7pqGTcurbZTeEoqbZYSU1Z+44K55LTU53EuD2hcTTY8qKoYoMcYyP48pzcqc9h4S67aUJpk341x2vGwJc3zDAiru5zBRXuNae2GrO6NNpRsGLv3MEo+Nhmx4AoVa3G3jku7FLFatMy3ruJvfXSYlMG26A7NHixDo3rx3VqsrY8IVzeUCNSAiMU+fGA2a0+B/cNs2n3Qe74xe+BZlKpmTz8m7v43h0/QUrJ+z76aW645k3s3X2Izv5uXnr8MXQqTWQikpMjVIoUk80NZAcG6BrsJhfkOLfjNJ47upexoIlUS4qf/+I+uo6FpNqXkM2+gA6GuOK8D3Bwby9zFyxn9mr46ie/RF55qMlqbvjYhYxtPMxNf/Mbjh05AiLJyvaF3HfX3Tx1552EqhIvneA9t3yWu267D08afD/FHT/4DFUVVdTNvpC2ypALgkGeCydY6rfy6FA3iZxBqBGErmVlWy0vN9eyOEgzFvbx0q596IymZ+dm5lRV8/yGjXzgvFVcd+Y0Pvb9LRzyKznQnuKBipWIQ0cpjGRIjz/OujPnUNPg0VbTQdfwcSq0j9KSrAARFEh6PmGgIZNG5Q0iCpAnhwgnc/hKQXacBBG6Lk1ThaKxtQaxZgUUDOFEHqk8PvnVv+H6A4e456GHSVRWsu9QJ4MFaG3rQFZLlk9bxomxEVrmzSR38AgbX3iRdFKTH5UkUx6ayFWWlhX8KJ8wDItl+TrUeEISEGKURBedCAuFaClASSKtEY6qGzsT8VGUunXzT7q1Eq8jS+1z19d2zkau6lUhCGJjSVn3oqKRdTi3w8ttT9fQeqHa9jwWxgOBi1IEoQ7xHJNHCOGQVWH70oqyFpHaQjFh6NgzStp/tqt4ce1MccRcTgJMsVXlVO55ic1SNOIxUSOyAIp9roiY0mhcD1Vh7FgXdNx6MHKeZgzPKrtdGhBCYyL7WUkhrS1wG3QonGcu7BaqjbE6EsWHUMW9xhi7+dkNMUK6RLh8BdDz3z9eMwbeAEpLtLSFDJ7Te5bGgoaeEoTaTV6Bo5BJlFGOCmUTGLbhggQRgoi1tF+5IKxzYAWPrNyn28WFTcgiQerA6lMIiZIRRBApG+oGwtgGD7j7JKY8/ccQjbbV2yhp8FJV/PqJZ9nw7EsIk0JULuSC8xfyu82P85unj+MN7eLs119AMl2FTlbiKUFTXRPdw6MEqkBOjuOrAuNjOfLkqU83MTqeY9SfpKIqQRSOcmDnC7znqou59ds/Jp+VpIaPMSkKzDp9Lid2beW05Sv5zD9+hZv+/F30kaXz2En+6i+/wuTwMBjX9Nzk2dq9HaU8fFXNaFSgya/ix1//LCA5IhswqWouWPkudvbsJayeQ27gDnb4TeTqTqOXLPm8h0rUsqCQJ+NH3Dc6Tn74ZU5O6+DCjvlw9Djdg2mWznwdYxxkcWomG7bt4OyVs1g1awZpb4wdL3VSmcyw5opFPP3EM6QmT3Lk+ZfpFx65BUvp6Z1gUkLS2LJzKZKIfAGdFvhhSGRCwnxIQuXwEoJIJUgoD/IFEtpVGBqNnAgIRYQvNVGQh0SChoYGZi+Yg6cyqLpGDh04yIkTJ1hwztkwOM6Wh35H85LVCDVK1+Eu8p7mxESe9lQJotFCI6Xt7BTpwDVHkZjIJTbReK6hRBgj6kI4Zoq2CTsNERHaavW6CGCqxxrrM9lErIUvZVzq7bxnjWVwaJfARBs8KQldqT2xV6njBCmYYrTg5I0j3xVKWc/T9vgo4ebSyCL0Gp9DAXlKbRvjqNzTtvxfSMuGEwYn4uVCd0PRAYuMnrKmoigsFU2Vw60u2Ro/iyw9PqBtM+6i3otCmogwvncdkBQSE4ERilDHNExbTBkZ580bXBaVol5/rEyr3AYU8+9jKxcLpAlpIJKEsmCjqOLzlklYTCnX+p8drw0D7+AUYWJxLtvw1sQ4u4oNa1ikQcWt8HCDLR2sEmEna7kxV65JN0ARAHNHrF9TChNUMUtuE7gxjqfsB2xK4Z5tq8cUiVctSg1ITj2kiogiQyGIuPPe37Ph6YNseeZhHtv6HP/6ndsRFVXcf/deGlumk1IhqXwlq+a3cdm5azjv+ncxPDpEQnhk0tPIV08j1dsHEXi+j6iopHpokO2HehFkWdDcxt984l/4zm0/wMh+mvKTVM+fwbve9VGe37KN/aHha+vfQl1dA2/90W20VjYzONFHUKlARZzdMINduWHGCwayBUyoGQknmZesZ9poDRWVPv2RYGKiHwqSXOfzLMvMYt3xl3kiPZNtx8eZ551A0cT602dyz8YXOG3Vcnb07uOCxgbu7png0jev56Vn9pENIUhXM1jo5Y3L5tE9NM5icy6D9w8y64wK1nuSjSOadH2O5v7nGBwfY9+oh1IhM5KG0b0vk8hUsaPzBKfPbKc+m6eAJEgnicYnSNTUgQ5RukCQ1SQqPFTeR6fSiIlJpEoSRBGKCmRoUNJDVElkBJHOUdNUR5NOMBqE9B84TLXns+PoUcaODiIqYOYZq9C5MVLzZnLvxv1kqyVpWUCZBCkJudAySoSShJFGCbvsNI4CrK0BKrg8j40gLevEQccWRhbYJtKUmmwXLWVRGTJmYDiPVlleuNFWhRIMIqQUoVos07IUXYQbSwLERhV3T9ZYOyMqIxdNCHsiWc75tmsqNGGxziQ2ymmjio0uYspg5NQl4/UjhCg1t9emyKIxxuYfHHqPjjSedAlSEW9sJXE/d9ule3KRujHG1QaYsu9tPYKruLHGVbj7UXFkIIr2xZioSOmMHbv4+rr4iblKHGOT5EYY4mZZdtwNCh9TbCNqufpSuvyB+X/Eg/9jqYR4kIp/MxpRdrulD86Gc6aIxZviCa0XzVSDHn8QlLMbXonzRFZadAAAIABJREFUxWiQchil/ZAc5naKATciho9KPxf1tIv3a5N9WhdIpyV33/cEF5x3CV/9hx8ya+1CmqsbyBYMJBrwwjRts6bx2Vuupzs7xne/+wPCRC1EhzEiQqcF+fERChG0VTczcPwwvSe6CUNNa2UFK5as5JobLmdGXTUtFTV88x++SMuy03huZzdfub2TWbVH2fbSY7y1qZ2TkwGJigxffNNl/GHbNjYPHGGuSPNg71GMAmE81yg8gaDA3LNWsHPvPo4P9THNr+ZINsv1Z53BXVt3Mkdm2ZHt4gPnXcKTxzZwVM/kZNUEdUd3Mzc9h679u8mOjtJZJWj2Qr73w19w4XkXcUbrfMItXfR5Kc6aBseURo6O0FGRZKShknt6MwTjfRRUjtVL2hlRSSY5iGltonKyj4Yoye7JcfZ09TOruYpcoYlUUpP0FYQ+ejKPwcOLIrTwiLIFZEUKNESeRCowMk04EaHCABAUjDUIvqggCkNmzGpBpDKcDPN0j46yaOESRsOI+qymsaqRMAghBX35Sfy0ZHQyoKFBkI0AL2XhidAgIpBeUGRmxUwTAF9TpPRpGbNbnHGRFgrRrh2edEU7Tmm+5Ck7w2xM5DxoWWJ2GCfuFecFdPnaKM3fUtK2jN2Ccdd2wn7OocKUNcUoi1y188iLZ3eGOTbusZKjXa7SEhmKXq+2BtYZ5FPXWnytuBhoCnwTf180jtGUnyO0va+ypKwp17MxBu2a+sQ5j3jtS+kV+72WH6XKWZejOOW24/MIN65GlOoZysf01Hwg/6948HZO2g9XxcGUOCXEM9idDYgbaEic54+aMrnsTh1P5NI1ZFkiqZRMLWF3MXNGGhDK7eYmQgpDhERJt4CUtA11XZVgeXJXGGNxfV1KGsWHNnmk8RHGZ3RsjDecdyZ5Ctz50AO0VjVTmRnjwrYalr0hxy2fPsKjt36Jmvdex6Lp9XTtS7HpsAQPRvt7aO1YTzh2gCFZxfSkhwg8JlM+/eMDrLz4Q6y5aDVr1p3P1se3E1bMI5P9KbNXnYZ/9GGq5/8j/smNnDOvlX8cP8mfnn8lGzc/z+jIcY5JxZ7RY0jl28UUBVavWmd51xsuJ93YypIFcxmcFNz383/lk+e/gYfHBmhJVbAuLbhtMsveFx7lmdwQjZ29hI11LF22go9/7EYO/9tv2dlqWN/cxHPTq9k2kiQz2s2C8y7h/gf+jrcsW8ngI72IHKRaKhheN4u/+MZtXHv1G7no1k+Tz/Zz17e/xjEvxxq/htR4jj7tU60E6+p87n9kC+2tdbTX5TEIKjhJKlGLDDWZigQIO7u0kYhsBEESr3kWA8d7OLJjJzUpaG6pJyVTGOWTqKqiMDFGlDe0NXWgEpLzVixkwwubuK+nmw/d8lF+8sUvMJQdIykkLzx/Px+68XXsPzJC/9AxPIHTWgltaz5ZwAgNKKv7XrQGjonhcjsYkNo2bY4kJKSykgNG40sbBUgp0XExnygxV6yKozMPxhoyUeKHWJVFaVkwyri6bwcBxcwVKaY6JvH6K60Xa6zLm1sbYs36Uu4pVnK1xt2ydrR0m46xcgDClLByY6yeDuAgzVJrv+L9xAYekJ4iLNNjL1/H9jZLsKtNbEtLdT5F30crxxYyGiG0c+AU2sFR0pEj4gg+jgJiw1+6x1L+wkRhUfHz1EOUefFWnsVeP5ZM167xiPkjomb/3eM1YeBxu7mFXuwvlEtICIQdEZcoBYOHb3F3ACOQIsQou+vGCddS5j/eqaVb3OUbgS4muoCifg2iVJWKk0nQ0i2USBNJY7FCKSE0RYhtCsvH/VBOP9MIPOVjGzCGLF/YzOMbNpJMzWBe+xihyrFhOM+vv/A8ibo5XPyPH+K7D/yOFx/pZ+vLm6mtqGFkYgykonXBKl4e3MSMSHM4ymKMYE1tDV+64YP89PnDiGAa2440EIlGrllbT0v7cqJ0mnlv/3u++MV/IDQBdwz3sKa9lXVD43zxxBhvmT+N/Lhhuy/Ij2ly2QAamqiqquIzS8+gs5Anvf8wx8fGuW3vRj5444f58s+/zbU3XE/Xtq1sN418YvE60ulmVk0cYnNnPx9+5/v4zlc/T9eT++hevIDhQh+bHx8n7Xnsbaqh1TcMvPQcb7r0TwhyWb7c08UbL30Tb2pKcNem53jPO6/kyY072LTlr7j0uuuZsewMnrzzHs5770VsevwpKkYMo5MTBKGiWnp8+1ePcdHs6eRFNVW1bQS5k+SUjUJSiQxSJji+v5PuiWGe3fwifjbk7HVnUFWZIK08RqNxtBHU1reRDyOSgcEEBl2dRE5OkqmuYdHSFeh0FQvnzuPEUB9JIxhrqODMy9bQvreSiZFnaJq/gH27D2FSdfT1Hqe+Os3pC6dhogKT406vJU4MooiISGhb6VjASvoa6eC+SCM9JwkQxQqJFkg8lQlWjsVbKl/swVojK3D4vABhXGIRVxIobMXnqcycGBO2tGDrrhqU88OsUXSKacS8cwG2j65xzpoHQgsSTjjMNgIRp6zRkhyJrzy0UkVqpzEabUJMWNLdiTlIcRW8hVQtJiTNVATbGmRbuGXctWPqktAKbQTK9aPFbS6ekDZXoV2Vq7EQWcFETnLBPki5o6h1uXcfA2mxTg6UiiiVq961xZjxKYwx+LEAz//C8Zow8AKBcvVLJX0upzUh48y/Ad8yCCJCJKooT6DjatQIEBrtKZSZWiothBUk8lRs0OPChgBbe2q9/UjF73G7KRKpBSmnme1JHxW5jSi0kYftEW7jMoEslvVZr0aWcH6TIAjyKJUGUrzcNcbT+/tR6TRbXt5LfWMa4QWkkq2YuhYue8+3ONHVR6I+Q0JIxrWmWqYYMxOsqI4Yq29j7OQh/FQHOjtMV9TKp+77HQ//7Dtsu+Fi3v+ez3HGspV84hM3sOvIUU4eH2bwZCdNHTM5d9FsliUT7Bj3uas6YGZbmrA/y760z+hoQG4yR31DHScnBukdPkHHB9/N0qZq3vneT/Dtj/wVQxUJmrq6uPyq66isrWNty1qqxzpJD0+iBgXbendwZuVsHn3yfv5p6YVkMrUcOXqI1rDAw69bS3pONe2H9zIxOcz2RzdRXRhkzRsuYH77DA4f2sfR1jeQ297P8b4kB/fv5dprrud7X/4q1569mDNWr+WOF3ppa1nM4WPbOBoYZpmQipQHhYjBQkBHpImCHFIJolSKfBAQ9R1HJVMcPN7F0/sOER7Zxxkr11KVDtFBSF/fKDP8aVTV14CAhEpDVUjehHi5EJ2wDcSrKpOsWrGUqlSGnsExCqFmcF8nYtY0qiqamTG9nRPZUebNnM7mbd1s7S1Q12PoO7GX5ppq5i+ppkomGA0LmNAQBQJEREEFDhi3kYbCEBkP7XuISCO0JlIQCpvEk9om6oRRGGnfqx0UIgRoHVjFQ+d1CK3ACe4VsWpACGWrWLGXD2ODqx1HXdq5b2c1GDTaFIpdntx2gjEKYyZQUqG1ZyMIJ6YlpXW6IorLw65ZF8BE0l5HRtB55Dg5Y6hKZVBKWcYRkKmsoJCzIm5GGnzfJ51IImUIkaYQ2WbdWhuSLi8X20np+8VnipO4kbEed1gIXEs+YyF/NNL4oCM8EbNZBEaFaK0QOiIiSSAgIcIpLJ+4wlg7MR0pSrh+iEUDiulABVp7CCKMEUhjadmhCtCR+CPFEP/94zVh4IvhkohxdxeiYPMnJqYiOqlQX2BDKWnxLKmx2h2yBMHExRPlWtYqDp9cOGVhnGQZvGMvaIyd6DGn17bYAi0NIZETHLNX8o203rwQKOMy7PF14mSKKyNXPvhaIEKob27hqa1bCfMQDOxnYmSc7sFKLnvfOzjc20//Y/ezv28nrdOnMRlUMGE0QmQRvkHpFD+99+vUtC2nMHGUYHwU4/lkJ7uZ7J/gua0vc/sfDrNsVQuFiT1c+r4PM9x3nKXTl/Bn73oPezYfpOnsFu43gnMXBVQ2z+T+YxFy1VuYeOIOKqsyGF8xcHIMpUMwmqVXXE730WNcee1b2e4bPnPrh/n8p77Pez72Ae578F6OH9/KZLqWjmQbhWCYRYmZdI2PsmQn/HX2JV43fwlPTfYRjo2x4kBEbbfHVXMXEnlpdl21iqceuoPmVBVbezfzhtmv55Ff30b96bXUVlTy3rnn8f4lIeOnNbH9UDdzlyyhrjqgbTzDiNGkDTQkUhzK5aj2Krj15/fwieveyrJMEi/hk/QkJ7Pj9OcLPPHMNja++CIXr5zPnPUXUJ0QzF51LsH4SZ584FFWnjkNbSLy+Ty+Mph8gZSfIMpnGR05iV9RQX19Pcd6exkRmkRSMTB6EuV5nBw6SXOmgjlzZlMx0k9hcpT6ymouzk6wqbuHP3TD9HdeyKIFM9D9g2z/8V0M9SSYNSdBbY3CI4HWmkI+RCMIEXgiQEWGQILwwQsikkGCUGoCIqTvPNPASmEX9cuNQAgfQ2A97qJQlsSYcAosIoQtRrJiW2WJyqKOvSgRCWIaSBm0WVy7xuq4xHCHNeJl8lvGQwrtdJucQQS074qwJJjQoKIIL9IEUZZ83LwEQ35isni9+B6HtS3ZEsIlTeP1XrBfy9UnhRAEUVByji0ZqRg1xAwgy8Mvg1ucx52XeaIQPKmorYBMSsWYVLExUIn5btDKRUvaWCZUWWWujaxEMYKyDbftMHrBVCf01Rzq1ltvfdUnebXHFz7/2VubKmwZdLwDxoUX9gdXtCRizmkcLoIRxurBUPoQi0wb956itrvLZksR82DjSU/Z4FuXIv5w418rBFIoFBLnBzmcrCRqhBClitr4fsuexYaWIBMSf/qZTOuYwf7jmj27OnnHOy9i/MQou45uZ/sDP2NCpjDJiBkz2pkYERRyQwRRRBBERDJhNTPy40QmjTE5jOehCgajPFTzTJ69byPXrF/KTX/+XjKhZtWypbzhwit49Og2Fs4/kzmrZ7GkJsGMjGbVmtXc/cD9rDpzLS89/wRDI8PovEbogGR1iqAQ8MYz38DsGW08+4sH0L7ih88+g68jrr7uzbz/I/+HN1NPKpmnc3SMaOIE5yVSHPcDNIYbr7iOluWrePa5F0l4CXrHuqmsqKd5bJTqXA3/tudpzr34TYzuO8is5Wu5tDlFfYNPSibJkuGsOdXMXH0aDSMh1974ZoL8BPOrW9ADB0njMyvTQC4MGAoLSA19+Tz7e7tZPr+d+kwlRJqJ8YCnd25i/7aNfPiyK6huVvQdH6e9qYn+8YCnn34BjzyzprfhJ3xEOkNU8JBBDqE1upAjCkOk7xNqQ1jIk6iqYGJsggIh+SCkIu1TncmQLxQYHBymrbEBX0kmC3nmNSdoCHPsuONpRioVx/uyXPPRt/HY3Q8wMlLB4MkcoTFoo6jI+CR8iaKAlCkiKRGRREaKghFEGoRne6BGUeRCfWWTsCawTAyUywN5GFfdKkSEEJYeSJnjE1d62xc5dMBOWDuvHWyKy3fZF2nHfHHn0YJSwtVyxW2BVwxDWcwpEhbHLkoSCMuGEXH3Kh0SRXaDCnUIwhDpqAgraR0V9wyLV5sy7RbjPELX3U0ajDJWT0rZ5JovPTwvged5CCPwPctuEbL4iPZujbaevBMiE0RkdAoVgBSGIFvABCEVqaRzKssgFRnbGoo2QJrYeaX4+mKuoPheixyoeMSkoXM46rn11lt/8J/Zz//seFV68P9bR0VCmKXNNpiQIm7WZ5xH7sq3Bc7oapRwyQlhCao+PkXIJcYtyxIvRV0ZWar8s38oJY+Uivky9jzF3ohuw1Au1Cqq+jksSTqaJlialY0k3Pnj0vNiPGr7byakoat+PYvXrWPnzjykJqlUmqeeeoa5s5voPZ7l5st9vvjznRzLDhL2wfq5dWzY003oS1J+yPI1l7Bl0x+IdDupqItcIGlTimEC6qc3MzfVTn5OBwe3bGbFgtn0j/Sz9+BOCpOCJ37+U7Y+cT+1jQvJZQU1Ha3s2/IHDkxm+f1z2ymYgAISbZK01NXR23WEe3/7K/7521/G6AJPPbWZ2dNn8+bl53H9x69m2erzudSbznUNNTw+0scbW6bxw+NHGAxgnzfK33/rLj77ub/m+iWLWTlzNUsuOZ1777yDe39/L/2jIySSVVy/7EzOndnO4UVVvLh/P8cfepF1ixdzeGKS+17egSZPdU0Vo+NjeF6SKAc+eaqFYlpthvbK2fQFJ+kc6+XkRIHI95hXkWTx9DpWL5zJW2+4jPkV1ZCpIQoLjCC557vf5K4nd7KovYPT5nbw7ve9G1VVjTCaMJNEJqvQg/0oowkmR5nMZclGAQVt8zAFAbnJLIVCyNhoHqXyzGxuY3x0nEOHOpk3ZyYTE2NMnBxiKBhEjEF39iQ/+912/vajb2ZiTPPl799LVU01o9pDmQJSCBJOftqqGwYklSSdFnhSU6V8UpWSusoEQucJcxqNIig6MG4duPBeG4nVkomKXq/WpSrUco84LFL87PoLHSyDKS82KuH61mN2kERc5IG2nHgZOcimLJmJRBbb6jnHJyzx2kNhDfxkLqKQDxHKc0ZfFx20uLVgHFFY/jgE7jLKxFCvrRwu6bNbcbSCiGwFrSj1TpWmJIhmmUnKMeWn2kbhip/CSCJRRDqgo7V26jMWdenLx0cXx640bnHrwZJAonCJ4VgETQjJUwdfXcu+1whEA5g4wVr8seTBu6Nco8NWnmG74DicLJK66DEbSkki574Uz1OkcVHy+u1JZfGicV9E5e7FqkbY0m7pirCEsAVPQsVJWztB/qNBtV69xEvAg/fexTMvbSbVcAaz5i3jzIWHeLIwgclOkMs28dzhHrp6Blg6Yy3jeh8tFS0UOISQBp8KNm54BB8QvjU8DZkKBvIjFJJ1dHce588+cAnf+N2jzJ3TTODlOXR0H7nJAE+upFBdR/WKtfT99G7mfugDbN/8Ij974Hn8qgJ9/b14BtafvooXDuznyLFuVK7AX978cb72f27hpZFBGtNN3H73fTSJDAt2rcBT8GByjLenZ5I2gwyMD3BjVS0P5BRhheDQgZcYGzjB+is+zDRRSXikl2uvuYHLL7yAWr+a3b+9n3f/+sf8Ymea9l9X86UP/jkbL5qDP6Odq5cs5E/3HGLX3u2EE/300MxQ10HWnjGNfMGnpW4hy89ZwsHdL/PME48zvWeSTtHPoVyBzpMhq9cu4un9B9nzxZ/y41veT1RTQ9pP01BdxUUXXUZ1po45s+ezcNl8ZLIKsqNoE+F1LMUUBMIl9aIoLj5x80sbiDS5Qt7iz8p2JMrlcmRSSevDeoKKTIqkriJZSNMb9dNSUcWshgYe236IOc31jE1GNDQlyARJsrkIIyWTMnQGIYc0AlkAnbcTMxEF+EbR1ByQSWmm1aXxDASFyFaZhqWEpTYhRZqKdVPcvLVMm1ON/JR5ahfBK5dpnLR157WbiipeI6b8UaRZltaWkIZQ2lxZTEgIhW0CIoWtkA3dnuJJSR7jPHv7WiElKqLoIePyA7ac1Tg6qERHmsizUKuQDrqx6j14xio4YnDsGEDpIqwLoI1l0sSbV0wJ1VoipI8gj5Q+JoyNsyGuDyiOk4C4dsYYQSQdayi2RUa6zyF+hx036cYxfr5Xe7x2IJqMzfqD4wcISQzS2HBLEEmbcfadl68EFsNyIj1KxOEPCCOQShWTtPERG38lpUsNKYjxRmOKZcnK+Ahs+GfFyyQo5TRy7IXiTLyFlkBqC/1oTyKkREYOmxOAJ0lEPkpKhrND/PrBp/nlL/+d+R3TeeyBB4jUGBX+UrzJTtZfdxk/+eZP+eCb/5THdz5KbuQ4L/UcI+knqQoKjOLz1kWzOdrTi45G+cd/+wndvcNce/U17N+zjcvPvYAb/vzP+JdvfR1VVUFv13EuOGc9WRkxr16RMQ14z22neckCNux/jP1Hh5i2qJbk9HM5uHsLSMPBvh7CvCElQgoIzlu3jvu37+Ff//mbVNdUMWPJQt674nw+8Y0vMjY2QZ2XZu+CNI/v7mRZWMduUcWOiYMsu/B87vjNg4S5Pu793dP84qWj3PbUE3gJQePcVpqXtHBy2iy+/OW/47ndI+w8sZfalau5+dPvZ05rmpOhpnrFbPYf383yC85n5VtWsvScFfgtM6hfvoBFr1/DuMoR1rbSsnQGUSQZ6D7IvEoPP5AUPMPIYMhl58+jtaOF5ubZFPwI5VWQrK3l9DPOomXOPBJRQDDUDcpHJWoxTW1oo1H5HMZooigPSnJyYhxjNGP5AuPZcZKJNIVCxORkjqq0oCqdsXMkKJDPT9Da1ESU8KiuriSVgtpkHaYwwfH+kM6BIXqG8/gqQTJRQCLxpSDpe0gJUkmUNijlgbBVINIECC8iNxkxOmnoGpikeyBPc00lKeWhZUSkwAt8fBNhlEAL4SJjXXSSSvUgcaQqy9g5wkmvmGLVuC4WFJbWKCKmJwMiwrIOHJQSSStXbGz+TEcGJaxnjHA67tI6RMr1W0WApyyjJV8IkNIrrm+tNR6WGmpwzayFIHSstqKevMNujHYbW9GzNy6Zi+OiG5vPFvEYlGBdT3h4EjwMCeVZOwAoJSxrSNoIPhKamkwGHRlQVtRQGoEUHqEAiIqFXkKb4mYDdoMTdpdx9O3IVTRotDCOoCHoHNavCqJ59aVS/ytHyQiXl/jbY+ouFmNi8b9TaWLFc0ib4Cjnq8bGfcprZemaFnZx3dY999XYpgDxUJWLm5kyLm/5BJGR/X0oIYzzN5Fh3MuTVwXSiRpmrVpL5+FeXnx+Hx+86c/Ys1sx6+zTOW2ux5bN25k2ey1HomEWLFhCKpFgmQeNhQkavSRCjFPVvgCPEJOAn/zqLrxEmr7eY2gpWH/uOVS31CM9xZy2aYyODPPIow9yZPc+Lr3xcn71+KP0HDzIjt3dmFQTM1YvYUzUUCGPIIVPBXZ40ykoBD6pCO659x6e+d09gOTpDc/x3BO/R5zWRv9AH4paRsJhbrj+BkaVpiejeDwxzE40Rzt7OePMZSgDCcaJTmwicfIo3/+3r/HA03v4xh1P0VaXIDAZqmYt4HVnn8NffvK9HBvp5UQqTdX0BoaGezjv8ovw2irZf7CXivoG6mfMob29BYxH44J5FIZGyZJk195OvLRPosJn5rSAdk/iU+D0xQvY93InZG1TlfzoJMn2ViZ9hRifJAgCpFeNTKUwyhAVxtDBODqXJ8oXABtWT0xMMD4+jg4LGGOYnJwk5kpnvJTlu4cFRCZJMplmNJ/FV7YZRiqZRiU9qhrqyDTVsXvvIWoz1eBpQhSeZ3XXoyhCGoEnPaRSeJ5HUnq2vsL3CVEIP0EYGWtkBWw/OETnWA4RQSLrEaQmySWS5AuhtejaIBXkdUj5IZyxj6tGpzBCRNmcjmGRsr+XCp6w8Ez8L24lXkzWmpKscJyTjeFTbH2I8ks2IAxgbDQgNxlQyGp0JBB4CBJ245OglEQpSdL3SCqPRPk/T9nf+x6+r0h6Cj/hkUz4+Moj6fkkPR/P8/B9H89T7p+HUspdo9RwI4Z3y8ejaI/i3xvKChv1lNeVG/UpYx/nIoqFU1YO2teQMAL/lKjgf3K8diAaKYq23E6o+A+imFCxfVVLD23iJE8xkVN6P5QGVmK5r3HJ4NTBdyJHMVfVvS+K8oDtEC+Esju38xric3hCgFZ2547vyRiM53rCRjatorEl576uRukC+XCMT9/8SS47ewUf+up3OX/1SRqrpyPE/Tx0pJ55K3xOHPQZGcjy4vOb6Zg1nU9cdQ0XvvO9zDt9LrPqpiHntZFPNXLjRz7IgcE+1i5bwlduuRlQnLX2TH7x298QiIhNzzzDZCGHp2DZqpX85Ke3kYs62HfeSi5cO5cXNj7Nkz/7OZ3digWtzSxdupT9E+OI40cQXgVehSAYHEWLgNlzVjE4PkkwPkJ2so8bP/rn1FU1ctfXv8FHvvR1vvvVH7Dhyae57urrSMx7E+bZH3Hehev4p29/BylhweyzGMnnONq9lVRSseH5Z+nc8SI/+cY49ekGFpy5jq5dO9i5bR9RYZyJsXH2T46S7J/gxh/9nKQOCPLgVYQMdE1y1vq38YEbzqDqSMi2ni7WzJzHitmncdeBXTS0ekzPTCM7NMSewRx7dvaRrhGMdG2l6uJrSHYfhTCFjBRSBah8DhkJCjmJ7xvU0ROIhKKQH0PrkMAE5AkwAvL5PEJ55IMA5XuMnxykvrYKmUpZXNeTpFIJskEeT0HaU4TaUFPTjh8N8a3fvMB9T32Lh9fuorEjS8GkMdpHqjwIgQ7A8zyQCuMLwoI1ytLziBBIz2c0n0dIzybvImtIu7pH6fGT1NYnmZdSyEKEl/SJQklEQCEISCQriMKgtIaKGdU4x1oGN2KrSuPaEgtVuvdRMvL2zeWKkyHS01ZmOE5aChtbKyOs9w3FRj+aFEEhwk8otA5JJSPa2jKEuiRyFrkIWxivaC9sP9TY+y/TfHf3ZXN3rmCymC82xXsvFodR2uSEEEVKqInToafYF+NYM7ZJSoQm1qSK9eYNUpexhRyuH+fjYkKTJdxZzZt4/Ir3XDI1r+p4jXjwr8QByw9rkK03HeN8cYVcjH1N9Sz+8/NNfa1NxsSda4rnlAqlfNfhJgQTFRM2+hXnoHgucH1YdRz4uSQuAp+QSAT4vs/ggS5yvk9bu+Tf732Yz3/1RXbvCWlsqWegez/rzj6Xp5/5PWsvWkfP4b3sba3ljt//kpvedxNvueG9jI8Jpk+fTpD1qU37nMydRKBIGMGDjz1KdUU1JtSW4SMFoYSezn287dp30NO5hbHOk+x7YTezmGDZ7GWsXzmfFYl66seGuFJ5tNdMZ3x8gnxYsAo/xmPCi1jWe4xscAJpDB2NS5g4OcrPnj7Czj272d91kC9+44d095/k5NHtSKF56MHnEJFCoXj/266mvqqWdHMzuUItqa6XeM97/4Rvv/tKPvKmBZwmRvmT1TP5A/1RAAAgAElEQVQ5cXgPh/tzvNQ9xD0PPcXvN+8l13OY/iN7GDmxh/6DB1i9cBF/f8tVPPPkLsaGsvzywcfo7+9n5WXruOHy11ORn0DrcaiOaPBDntv5MimgPwdBTTW6rgozniPhKwpjY+R1wNYdnUzk8uSjSbL5AXKTw/SPD9Hd38NodgwjIJ1OE0WafD5PEAQ2KTg5QcJTJDJppKdIp9MklIdEUMjniYQgUe0TSc3MGW2suXgd/X17mDGjGqnSyKCAryzDSxmJUgrlWTojxqB8D60sjdFHEgb5Yus9hCISikBrAqkQOsdI3yS94xKT8dBBweaoPEXC89FByKlHOR0y5nxr4uj3P8Hop5zEB5PA+ozWk5/Ct4+pyAZOpf8JWXA6TY7hY3wKeQOhREee3fxMEkGibP1axl0soqkpadvY1zhYNb49S64pq8h1X13Bkk1LmOL7ipo7ZV67Ifov7dR/9DubWC3dH2irp2+Eg4lc9yskRhaDrld9vDY8eEGR2mh/jpVcLGRiHNYtXZGGECWmi4j5TZTCzXgMixz4OJQsufhlxCQXTpVFBgJAG7QIUa6sW+CDDBDKJn20wYkURPYDMbH3YxChASEoKIvXe5GdajnGyCAZNYb209r5+F9+lvPf/m5+9K1/ZWzgCWaveSuHH/0ql918C1evm8s7LvkZCxbNpE98idWLliPSad58xnl8/of/xNuv/0tmnvF6Xj5ygpsuW8iWLVuZNXsah48co3Z6G0cPHgZPkc/nAQMhDJ6c4Atf+gdu+rMPcOX5r2PLk7ez+cgQew4NkGxbSEVuK2eedi4PHT5K9+Au/m7B2Xx23wYaapoYGu1nYP8OVlTNg2yEnww4fmIX6cZ2fvvEI2RmLaPQ9QKPPPgrLln3RvLpet705ssY8ZNs3fcigTHs7BygrXEha1ZpPnTDpSxumUsi1YBRBQpjwwSTOY70nGTazGkcPPwyh3uO8bV77iQPeFXTmXv6lYwZhRjt4qN/8X4WLZ/D2Qda+PzXv8KRQwf40+3bueWa96Lap7GpL+SyeW1UEnJxcy1P7NzHpz70Nrbteon5e/ZCYy2hmiA8PoiIUsh8jqVLZzJZyNF5opsX9+wjWVHNueevpq6qjiCfIwgCgkij/CQT2TGEkgwNDZJKJaisriIpDclUhvxYFplMUqUgUorJwv/H3JmHyXFVZ/93762q3nv2kUYaabRYmyV5X2UHgxcw4DiGAA4QlhBCIE5C2GI+wk4WCGFNAgQnbGYJYTOxDQaMsbGNsS3LmyRrX0fSSLMvvVXVvff741Z198hKgOR7vselp59R1/RUVVfde+4573nPeyIyGRha2sctdz/I6964iZc/672sXDeEh08moxAehBZX16ElOjZoY0C5hJsnpMOqraboBzSwKAkmcoJbRliE8ZgQFmM18cgUe0ZynL2yiB81wHrEOsJXMklkptRJB8qnNENrE4y6zbMHl3Bspz0250pakSl1G/vD8ctFMl/nwazSefHOK3fMNBs7cEMqEpGvCKm002whYcZY1wYvJTdYHIPOJlou6WKSGtJmgrjpuqe2oAU/kS46wh1fJQvbyQ1B0uRrkxdvHEnDAhLlWoqKhBaq2xOpyblI6mZEghi0o89WJ3RKk7QgbH3fUy6kv+H2zDDwza1FKZIyNbqtYFBImxj99CG5fij6FDej/b3zdJwux8ltwNzvU83n9MGnPOFEN0Q4/9vYkMSlaS4ITckEWrKokXJdpTwLwkDsADoCkyc0lqhygvM3bmDN0uV86/vf5CNvfh3//Pl/508uP58v33YLT95zN98r9nD0yE7yA93cecudSKuw1Qb/ed+PeP/ou1i/ehE2P83lL3ohb7j+d7Bk+eQ//DVvffs7+No3vs5zLtiE8CUiitxdFGC1z9CyJWz+0SNcNd2ga0MXzzltkHPWVNgdFQn2jrB7y8O8ddEqXqslYxkJPghZwBNjhNYViqwVgkmb4XnlNdw2s4cT1Scorr4MO95PGGlWbLyEf73lu/zxxWfxyJYnKHUtYnZ6mDNWDLL5l3fxd+++nujQFN7KTmpGk4sMmWIXQblGx/Qk1akpNqxaR7GY51N/dg033baP4ZWXc2DPbuLDd0JxkE9++l/I5QOeGt7PngO7gQyUQ6aPPUrG9LGip5tKXeOHAlmocsH6hXzqllu58rTTYG6UqFhAeUkT6nKJXHeBqeG9qGyJ3oEhVvoetbjBnl27WbVyOd2dXUxOz7hnrCRzlQqdfT2YKU1dx1SrdboW9VOfqCJ8j6zIUPddubyIYxp1g44FP314F4fuuJ3e3l6EqiPjHPhQrVqUMqgkqRfHzquOtcXDIlNVDaWwiTyGJyTKk0nxXYDWmnycp2ZraCvJ0+DYhGF5Oeuof54i1hHptHfzom2upPOoHR7FyXWlY6hJfGB+9Oy89mTAu0YKIF1TEpPoz1uT5LmcdKX7WwHKMwml0UkQKJkF22ga56bWfbIgtcMo4PrTWtpglpRV07QUJE2DBEYzn61nbVPTJ6VkW6FbhI/mPWkXAxNJH+gWDRMh2pqySFeciXPDXVCQcOBty/BjwZPp/XO2zWnlJPP1FLbqN92eETz4YiDt6Qu9to4vwmXgcZLAafLCS4uPXEDjpEJxHnr6gCGBRaRsVpc1GxgkD6r1OZU0/NCtpIpNJRLS5t8u2apMgBDahXQplp/cOi9R7EO6B68cPyv5jGxqSPsqII5jZkdH2b/oQg4+tZ1X33AD//LxTzM9WyUbKCIdIpQHngIZ0JHpws9l6RhYy4FD2+goZhndu5VvfvZf+Ldb72DVsqX85M7b8YMsF110EY89toXHNm/hja9/HV/98f1EtSkqE+MuH+BblvUvY9GZ6zl3X4XlNHj0wjPIR4bDk0/ynIEO1q89hz//6FfYNTqMFIbFZzyXwzseYlNxAfeNHyJbLFKfm+K3Cn3sDyI+3b+Wf9k5yl45wURfie7FC5kMh1gWjXLti5/Pt+9/iCP7HmF8eJjv/tsbWe53c8YFFyGrc0RzdeSShdiGRvkSWwuZPLqXXLab/KIuauNTqOWLiQ6O8W8f+jj6F1kqhaNcnOnlhcOPQc+F5GTI0MqNPP7zz9ARS6655koaIwfIBlkazCGsZLyqsTpkaKCL7/3kcSbv+TK1zmXkqiH1vCXaN8zh3TsJB7rwKqACy56JCapb97Pi/CGOHTvGmRedT7VaZ/T4KFoJanNzSCkZGx2lp6ubFcsG6ciVsKZBIVNmujJBZAwNIfCikHxvB6/54/fz5Jhgw9IelO/h+5I4ihIan4s4dWwwxr38wKkXhlGMrzxH6/NE0qAjSVIKXIJYuAYS1arzoo1tIIRHUYUsXthJXwHCeoTwfHRS+t+eLDVtXHcjWjQGi2kZ2DaD3uTLp+yVhOdtsM1GOADW+AnnWyNMxkkqpMfQbs6GyZxTwjW9MMbQiEIMqtmQJL0ubWNXDGlb/Y+VkMQYZ0w1zYpb2wYFCdFSw0yZQ3Ebn58UG0++t5ecG1oLh3vpJF/oFoMFvSWnR9OUhDBgI6zx0TZGSbA2h9FVhPKc/hUOQkqbG7XyAy7Pp4iS8yp+tKf+v+LBP2MweIl4WpY53e9+tm2imUZpPpR0rTtV9rp9EUubA8u2dO3JNMr0vaa1IjuWjXEeiHX0yrQUxeFosrnipo0DXDFGC07yjEEpQa6rgy0Pb2VkbI5PfuyTTM/NcNHFF9LZtRAhA+Iwom/BaZy27kxOP3MNI0d3QqzJ+oJFC5cT9A7y0U9/knMvOpfPfe4zPOfZV1Ds7ODgwYN0dnYCsHnrDvAVstiH0jFWKqJYs2T1IEcOT1HrWMDMmuVsWNzFeQsGOLIPJswKJg+e4KIehZXgdxQZ2/EApjHDXgzZrj50dYwbupaSzUou6hxgKgyZO7uLqV7JqtPWIBolJvcf4h0vfyWyp8BTu7YQmxw5Ip69aAmnDS6m3pHD+EUXFmuLVQqhfGQmR+3EBBSz2OkKGaEQOY9Cb4mXvu336L/WJz8V8sDIfs6sV2gcu5PK+BM8fs8/Ishz1Xn9mKnHCTOCaT2JlxoiXceTHlNj4/zO8y5h8479+NPDRLaCbBh2HtrLDiOYPDhCuQvKnSWODk9y2QuuZOmCPnJZj0rUQCRddyId4/s+1nOJNQ9BvV7F2Boqm8fLQ0AWpSS+1hQXFukMCtz4+Xexsi+fMC8ss7Oz+H5LPdFaSxSHzqglmkmBkgSBj/JSFodCSRA4CqOf6sknx/R8SZDxnNyE1WRyBfYcmmKq5hwTE8WnCP1lU2m1OQ9sMr/a9rWTOk5mw6ReKtAmnZ0uDC0hsnn4d/PsLYZOeqy0cUlaWJjO45TW3OwHAc0F0QqQnnIdoRImjFDSXZdUIBVSKHevpUAohVWKQPn4UjmdKeHhoTgZAWjx/1XThgghwIiktr11P0TCbPKkooFCyxgpfRrW0LA2ebn/13VEPQ5paE09ttS0pWItc8ZQ0U/Pl/ym2zMDohEnv01ClnZPWLSSNIo0jDwpC04rpGpVr8nmYGkO17aCpnSz1mK1IVVsNc1FQTpoR1kn42mEuz6RGm/VLH5Jr1tq6Zr4qqQsO8Hkasqg8FFlycrly/HyWQ7sfJB8Xy+NusTP+6zpW8fR48Pk83lmR6vs27qXnq7FLBkoMztVZvWqJUxMTVOrHeGpbY9z3XXXMTFXpTpbp5QpEWcCtIJ9+4bpX7eW6ug0amAFXjRDvtDJyJFh3vJ7b2b1VasBw7aHD/Ouf/gIV69fxdgDjzApBM9duoFv7N1P52yGipfjkgWLedSWqU1sR1jFf1SGeUfnEKNjR3n43Is4sH8PoxPjxAe3Mzmt+drb3s1ZL9vIjS//AHJkF5uWncYPfvoJZtddQtGXRBZER4MgKhHPzSAyJfB8dMYSGs3E9BQLO7qhnMGvahrFIl3rL+GVf7OJr6u/513f+TlHjSbvWb77hbfQvTgPvuWxRw+y8/6tbH3gENlOj8lIEAtNuVymWq0yqQ1Tx4a55sa/5+5PvJ21SzaAHeW7D9/DDS9+Gdt27KR61qXc/c0f8bprrqI2OwPSsOG0lTy+by+F7m601YhIY7DEkcFmfSpCI40h6ym6ij2EkcAWLPVqRBAI3vPxO1hz1Xq+/O4vsGL1EDIQVCoVero7CcPQMbKUItQa3/ebEafWGi/jodCEscUqF1VqKV1OSkqU8sjkFNrEeJ4ijmI8JfE9SSEPVWPoKhXZMzzL+atLTSkDNyTdoqKNgxZ1kqZKWR5eArmnHm/qRbdgGjenxMmLg0gLkTwQIUL4WO2DCpNEbEsfBhLZYhfCON0Z7c4V6QS2EY7x4lgpTuzLOrQea8G3EAmXLBbGNf1RzTyCbEUlNq30bXcXDTPJVG9n6DltG002k3HCZFondOn5uu2xiQg8H5JiLZt46HMeWCLCaoaFGUuIR2BT2JfErhkiofC81O45Rl82qQ9zOcT/nZF/ZnjwbW5Cu2fQvoqmZcOn1EgWrcrVNLHa3gvVYmgPD9oHYztHtRmipvvk0zm/zesSrWq9+dea6uEkUYZwnpBxawFhrMllA4yx1Ot1VKGIZxWHJ45y9NgB/GwHmhxRFFEqd/G7v/tCyv0D7Nx9gK6OTp7atZOJE0/QERSYGBvnkUceYdv27Wx94km6OrtpWMOiviHyPb3s+cUvicMGi5YuYWpsglf90dupG6iNTzC0bC1D3Ss5ffEizjhjNT/Y/ARnrV5N35mrKXUM8tziMlb0daAz0/xidA9q4iHOWjaIkopQKJapgIv8fu46vJeiJ/DxueScS6AScsHvrGf73iMceGIzK9dvpDwQMTo2RqE6CaYLIUJE9wDR3BwmCsG6CYTv42czxBOzhNkAUSqANWQ8RdYTTGc9rn7583jlqiLXP+8KvvXv76Jw2nJqfpmqznLOpWdz/V9ezwXPW09tThPrCjJ2fVHzuQ60jlBIckrwmR8/RhxE/OtPf8ZHvvEgZ7767cz+5DGefN+HuXz4KHNjkwS+dR24anX6unvI+kGieW5BetRqNbL5HFNTU/T39BLakEatgS81PpaOfECY8+g7o58jj29h4fJ+jJ2mEdWJogZhGLpkZMKyOlWTaqV8hBA0GhFKegmrqwUdtP+01hLrCM9XBIHjoWcDH+tnyAU+e040UH5b05yk6fc89lnb5DhlfYkQrkhIPP2zJycGLRGQSRyqRmLcaXr0JxdbzYN+gDiOieOYSMfERjc9dY1trUInXacQAl8mUg9KNaFX3/fxlMIL/CY3PlCSjPTIBz453yMTBAS+T+D7eF7KZkrzFY7wLE46n6Notupykr3kjcTXEh075lNEUp3clgw2aT9p65xaZUEaTQ1LXUCD//32Kz14IcQXgGuAE9baDcm+buCbwDLgAPAya+2kcE/sU8ALgCrwWmvtll/rShJtgpPDx1TLAUBbV63adnWAIE647Moyz9DSfN8afOkDajfK7fubaZQkK65sUmlno0TnxsOVILvr0sq6piCJyp6VwuFs7ZPPOkGjXAwNPGQUMT0xweCyheyZrnH6kvWEWeiQOcZGjrN8YDlbD/0SrWHXvgewUZ2rXvASfvzDW8h29FDsWU7noiK3330XCwo9TM5Ms+6sdVz2nMv4i/e9h76BFRzYupmB01YwfvwYG4d6+fMv/yvvfNOHueSy9dzyi50Uvvof3PnwDq5cdTqrjyiWnnYmm+94lN7LevnW3Q+zV8acZYdAznF11zoyXYKhapapguQPrvp9/vPWb3HtxZezijw/fOBmeldcwfG65mPvvBFyRXIZBb7lrNJi3vueN4DIIUMfyyhSKUw2T73aoGg9TKdAFfI04ga9vf1k/E5soYici4mDCC/IQj0i8BSNbJZ1m85l3UXrmKlXaBzbh9QF4lqDeDCmkC9yzRuu57f/5BV88W8+w+7Nu5mu5OkbhJ58B3Ma1i/oZMsj9xM86yecvjji9zatY3xqllVXXkpfPkM26GDSVti9a5ShhVnqUYzKO08aaTk6O0asFZVKBb+qufbKKzFhlQCoehUascRmS3zwptvZ9PyVfPOff8TKwQIq7xMLH4WkWCwijGNtuOYWptla0hiDTCCaRqzJ+gGImGrUIOvH5Pw82oDVBuW5cWZwnmCxWMT3febmZsgEeaQ1+B7MKA89V+HB6YjzlmZamHJyfmldXjL14Nsj4bTLlJtJbR7607YE407yXkYHoBoYDVIGaB0iRcvI20RXRidgUMpmk1LgSZ9CxhEoEAmjCLDECUSa+IXC4e5+6gYb24RMtXZ9mq11bDflubkppEqcrqRXsyWxEW3Kk7hqdKO1k1JQCpsUibnyG/c9Y4uDbYQg0f91TV6MwBOKqaiC8TsJtGvxJ4XEKHejLQI8A8YxaSQKhdeEnjxOdY9/s+3X8eC/BFx90r53Aj+11q4Cfpq8B3g+sCp5vQH47K9zEZb5mW1wNCvrpOZIZb5kkkghqR5NvW5XN5dyVZPjGYMz0U7uV7ctHCm+6QaxTjLncj6GKAwCg5XC0bOk5x6qTISCZIxRrusO1kNb5ZohC4VOeKxWuOSqEQbhCRpCYk2dKNIU+3qwuTyBbnB85iiVWkjkZxge28NY3UOTwZM+It+F9TvY8dB+CALqM1OMT+yjdnSOXLHA1Mw4YXWSHY8+SWdfFyuWDFGvzSKI6VlxNkuXr6RiMtx2670859pNbHlkL5/6+z9n8Ny1vOZ1L8Iu9jngVzmydS8vfOH53P3EAa59/oV0Zpexsr+bV3ScxRvX9nD8yC46yz7nmyX87S03ky30c/f9j/P6P/g9dARd3YPMjExx8PgR7rpnGx/855uR2vKmj13LKi9P79ACGk/tQNScJyYbs2g/wHTkkNbDSEtGWJTsZK4ygc51IyoG5eeSMKiOCGfIGY/OVYvo8CS5TJGsLFAsZehZ2snkaI1DB0/ge6Bo8Jq3vZaBi5bilwUzo1PgC4zOUJeCnsJCrji9lzNXbaRmQGQ9Pr/5h/xyeoQfT+zkB9sfZuuR3aAkvmeoVwzZoINqo049jKnNTPDoA9u57trLqEYV6hGEcYPugS4yvb287SOf4ZxrFvDhd3yFZUs6MdKDSDA3WSMQKoEDnNendYRG43kSiPE8z1WxCouUzggWAolvNNbmiGyKISfj3/OIY50Y0YhsNosxEk8KYgvGCgJfobIlpA6JM4nEADFCO5GvhmfQSVW3xMmGSOl6lcqkwskpsaa4jcFq02KInOQwuYKdCLRC4rtKWhRCNRwjBd0kK3iecnMymdsWg/Ws62KFa6EHHtYEjq6MTIyqkyAWntN6t7oFv1htEqK1SORFXPEhUqGTJt9WeGjrLIuUEiVcCtZpxccgLbGJcMqc7tjGOkPu7h/EGpRy8I0lciCOFGRlSIyEKOHPi4RmGWu0EZioijQa6hFYi9aRy4/IGKU1ORUh/38YeGvtz4GJk3b/DvDl5P9fBq5r2/8V67ZfAp1CiIFfdQ4HpzuL2IRMkuSIS6aIZoY5LU5I/wRoPsT0b6VwhT2pYp3CdWtPver2ENd1tSGRB3UQj0Ql+2UbHOMWF9FUO3MlIZEEKyP3YKzGSxg57kQtBlAaXiqlmuyBqfEJQtlgIp5lRW+BwSUDFDJFsoU6QQhKFdB2DmSNuVydrPQJip2IOQ29BTZddAmhEISNDG+84QZueMub6Qgsk/v20b/sbN71xhdweMcufF+x/aGHyZPjbz/6IR7cuZvtO/byne9uYfbQCGJgMa/+zFu4b+QY//j1LxGMLWBDT8i3hh9jv6nxgaf2sYxVPHRsnOd0DfG3PWcxPFVh+xKf7275ER6KpauKHNj7KD/b8TjfvPXHDB8+zEf/7ne5NFNGnnMmutRPZs0A0aF9yEYV3QBUgI0VRM4Li60kKDTw6xFUx9HROLZaI6yOYkdPICfGqVUn6O4uUuotoPKCfGeGXMlHKR9j6/R0l9m1aw+TEzMgDG/809fT2ZMnRJD1inTl6ljfZ7w6i/VgfGqaQAqiuTqPb53kTR/7d+655x6eO7CS37/gIrJBDnoHyZS7qIgGT+4dQc1F/NXn7uNEaQl/+42f8JOtu/nOQzv4yiPb+PAdd/LTkT1s2badL7z3Dro7CxSLOaxx+Hp/Ty+kXrOU+FLh+z6+76O1xvczADTCOkEQoIykUa+TzeTJZrPUalWMtsRxjJQevpchiiIC30MYTT6TddBMNovvq1ZBFBLpe5TKZR7fVmVOSzAFjB+QiSFjXGm81wZgtncjS8d0SqhR0nPVtklRUDt82Yyik/lrRZrYlViTRL/NxhgGG2vQpqXUKlzWTNhEuVLEjsHWxoppsVpc7sx1VlJN2qJjxLVF6JYWpRFn+FK8PLampTApE7uDakJmsYmS67IJK6bVLMUY3ZaEdZAtwiCk53j1WuAJiS/AKkOmfwH5JavIDp2Lt+gsgqEN+IMbUIs24C/ZSHbZWYjF6zB9GxB9K36V6fyV2/80ybrAWnsMwFp7TAjRn+xfDBxu+9xwsu/Yrzpg+lCa/HLrblYaGrY3sG7xTGl2pZ83sGzSijh5q3GCRQqadDSS/6edxpI8aCJrkAgDC/cXacikmuEcpJJ00spES9qJOhkr3ZEFzeYDKlloMjKAMCZSlrGxUdafvpqujhdBJebI5EHM+Bg6ChgdHqcrX2bxqrOoTU6yc8fDeD0+yweHeGrb4wghueu++9i9Zx+7d22n0JXjE//0Vfq7FrJj+15s0OC556zhNS/5Uwyz3H/vPZyx7kzO2bSRP33zG/nk37yPA9v3c2TPY/zWS1/GCy5czbe/dj+XXftCPvHca7jXzBCuWsXZa1fy4GPb6Mn0kl3WSWbvCT5XeZhnLVqN7hR87VvfYOn5F4KEn9z8eYwXsf3+GS58zksY3vIjLn7XP/PYD+5j41vXI4ICppgjmt2HPzqBKcZEuZgosngZjfF8fJGlbiS/uOdOVg+PsGRwBbPHj1AaXIjGJ9BQDUMmRk6w/IJ1LBQ+mx9+gv7+XpSnWb9hNTNzFRiXzM7UyOZ8gqzkbZ94A9/+1x+w7Wdb6enqZ2L2OFIqivksU5MVokKE9Hx6OnIs6uvgnq2HuO7KcbYeH2No+SCV2QlmqXGk1uA9n72TfDbL6kVFTuw+xNxwyKO/3Mvs6AlCk6Hga24rZOksd1BUAbE11Kt1isUi6BhrI7R2TTqaHq+xWKPJeD4CgZdxsrtRpBHC4nsBsdEUcnlymSwTkzPkSnnqUcORDoQT9hIWlO9RqVRQymH6vlRoHTXP5WWyZMsxe4/B2Ws1ciZCZxU6dgJcyeSjHdbU7VRjM9+4plOuVfafOGipXGS6V7gIwJJ2OWoZ2JO3pqEVofsLkejBy/TYsnn+1B4YY1vcd2sdlzy5PleV6+yDsa6Yq2kqmnBt63slb9wCh2rus2Z+Qtlap8ffKgpzUZlNBNGw0NAOyvWFQRqBMCHGxFjjNOZN5NQ0s0GOxx58mN6+LvoGOjkxPMmKoc5T3p/fZPt/nWQVp9h3yjhDCPEGIcRmIcTmqCmjmQIsyUp4iktsPdj5hQit/dZFcMzLqzZ/nxr3dMA7v70F2ZzqnO7z86lQaViqErpkKkpmBSiTvGzySt5HUeSMvrEsWbKYXD7Aj6qMmhka1Tq1MMIW8uS6S4RRhTgOCVWMkTEZMgwNrQRr8JRrTv7Tu3/Ge973fj77+VvZtnu/m+AFiYoF09WYSMxx8aYrWdKX5/EtD/KqF7+C9Wev4ZGndnD7T75PecFSfvjVH7OiYwHTDz1C/fgE0eoNvOlDH2Hk6BSP7xxnVf8Sfi8Y4kcH9qPL/dg4Q6MW85bP/CN/d9cDdJ59DWUjyXT24dsALWqsOPtSWPNSLj5vBSxZiTp0DGyMLubJrFpJIwwxJiTr5VF10IU8tlSCXAG1tI9zrriUwqXnYa66HE2Anqwgchl0KUe5p4MF2RLZbJbYhCxY2CpVxsMAACAASURBVMHI8WEqc5qZuQqlUokorjFXmWFutkIYGoTOc/m1FyON83bzXkCj2kAIQRRqLJrYaKwInebOsgH2zU4QFGocnzqI8Dz+4+6n+LN338ymNd1cPBSgZBbf1Jirz9EwVfoGSwwszpNf0IkqFujOFZmuTVOtVslkMmitmxh7SgBo9zallGgEUZJ89zwPKRS+n6EexfOMSWdXBwjhmlakiU9rUZ4giqJmglGptog48aDRhjCMyZY9JifBz4HWqgm1pFGxRDSva/78as2BptE/ecKfhM+nQmXphDzZIDTvh5j/986Y+lgdgFU4xcr2OTmfiPFf1fS0KkcTAkablUpzdM33KSVaCFSTwddGiwRSJo0QAmsk1kgEAanQGtZBRtKCNk5XP1WmjRNdfmt8rPGQIkApFy2cedZGFvYvoidfpq+0iBOHR075fX6T7X9q4I+n0Evy80SyfxhY0va5QeDoqQ5grf28tfY8a+15vnJFCfMebDNUS5OUT1dza8lVJ5WvnmyWdlvlOLBCuLDTt22DwbSgHOmwHVcpaNzATpsGWJtWxtmEHqmaEqfuIQmMp+czCkRbWGvn83jdDXf4/czsBHf++Fb6CnkuPPcclq1YzZSdpTvfR5fM4Mss5WyJRmMarGXp+gGe3HeIoQ2XIbwC2hc85/T1fP0bX2bjun52b9nKxPFxqFhKp11AfWIMrGX/vsfJ+3284o9uYMnGjZy+ci1HDh3hJZf9NrahefM/3Mj3b7qVZS+9mPsff5TRHTt55/vfybsvOIPB+lFmykXuWF3A8yP2z+5hN8e5afQxvvqtb/PZG/+MsUN38crSReRnZuhYchZKBfTm4G+et5pGb5aznr2JseHD6IeexK9GyFI3uqHwpmLyxQxjE6PIxgzewX3YcALfW0z5jDMpdSxE1mcprz8T1dmJXLII4XvosSnKxhI2anhKsWhggBXLh8gXBYcOD3NsZIS1a9eycOFCwjBmfHycCM2ChWsZV3M0Qk1pYSd+IUcmlyWTyTjPOYYo0nSWB5ANy+3/eT9v/et/5+1//S1e9Y5PMnngCNdv2kC9UaUSFIjqs3jFHAU/Q2AyhKGgVo8gcs/dUGFhZw9dvSWiuE4YhtRrEXEkaESGyFisdONJY4lt3DTYDot3pau6HqIQZPI5Gmi0NJg4IoobhHHk1CuNwfd9wigik8kQx6ETRYujVmRsXJWkRJDLF2nMRRybqLHtqCET1x08k7za5qjD+KWrGMfoRLobl9xMSqHESYtDOocd37EFx4iE8iekbfLYVWLYmxLGSTtMA0hrsKTwiKLVMcrNpPbrFCp5bwVKqGaTn+a12PmJ4Xbnz30d28wB6NjRm33p9NwlwtU/SldBq5Q7vkqS4/MXUQMihqQQMzaS2GinXGklKmygTIiwDde+0EiCIGBsbIxGrc7sTI3Z2Qr79x2l1NlzKtP5G23/UwP/n8Brkv+/Bvh+2/5XC7ddBEynUM6v2lKueltbXsAlKR2nVrbtc5hXakBtgq+hXf9DcLBNZA0xjvZohG2FF2l7sJPoYelLCxxfVsQIYV1ZstQYYVDWnccI0J51EUCa8MW1T3M+YVJ51+YdWKsJlSVQeWIEPR1d7Jma5Pv/+R/sOnwUMz1DrmcBYyYk05mnGs0xeWQSYSUTR0Y5cehJpg4eZu3G88FoLn/JdXzn5u9z+eWXsWrtWlQ+whYMjcoMB6aGXbIsVoSFDu65+6esW7ucb3zle/zsh99l44a1PPe3r+I7X7udXlvm8I5RnnvdVdz4yY/xqRe9lUtvfBdXX/EqDu86xKBf5pz1l/Fkw3Dx6jN5x9V/SJQfQgvNb1VDJuMRosBQnRpBe5pzzxpi1YY+/EqOOGvJ5ruoCbBjxxB6Cm/RII36OKq3h3xvBmsFMuMT1wxVCaLQj95/GDp6kQv6MRtOh9kZZMPihx4lLMfnppDayTHnVBFrNYVcmcpsDUtMqZRjbm4O38tjwgbV2Rkynk/gK4J6SGfOh0iTzwkakcAKhac9quEs+EA2y8Z1Szl/4zLO27iKmWqdahzTUe5iZmKSRf29jI2OUu7qpVRy0rMd5QxZ3yCNJmo49NMzkPM9cp6HVII4jjEGjLZEYUwcm8SREKBDPAFC+FirsISorEcm4zM7O4uwEi9yTksxkyObUCiV7yWFUm6xSBtJSxlgpRuH9ahObA0REHgBwvco5zpo1GIIAodR6wYunSnIqASylC3D6Mrzk/jaugbVIk3A2qRxfRJda21RnkTLGINLsFoRuKKgVJbYKKyRTkM9mSYiiXo9RKujlLHOaCaesfucSWiLJkk2O7thMWirmyQHrGPEGGFa3XuSxchJAzpteW1dctQKCMApiOL6PhvV6sCkVMLAsdYxe6x27BnZcNCLFPg2izSuul15wjVhsQrpQR4BQcKP0RYd1KjONZBhTK6/SM9QFxOTFVafWyLT2ffrmM7/dvuVBl4I8Q3gAWCNEGJYCPGHwIeBq4QQu4GrkvcAPwD2AXuAm4A/+bUvJAnjlHHJy3Q1VaKV6EwHmifbhH9sK2EFLbw+zf7Lln1tG5jz6ZBt37W1Iqfl0FY0X1pYTALNeEK6qMC48odmMritLeDJIWTgZZDG4gvBkYMH2XD6eqZnp5FzFc7duI6+vjVYO8fEyChzs4rx6UmijgALHJk8itaaFWesZPv2PSxddCYTdcV7PvhuLj7/Wdx3++cZOzzC717xGnLFbkxnP8ePneClN7yB04e6uP6KZ9NZzBOHIQsWDbL/+Cgf/at3MrhkgOFdO5FSctf37+WNH3gvX370Xp7/gufxox/fTF5pzuzNs3rNcqZmN+MPncaCZ5/H97/+YfqGlrNqYBXVQsxMxyC16SOcf/5VTIeHefDACJIMc9E02QvOpvTsCzn6xKPEWx4jWLEcMbgeKlXKGy7GGkGoG8isIU8WK8pk13bBlscxueVItZJ6fiEQ0lh7Ogueex3PHl9B6YHDIMH6MZMTcxQKOTIZn4nxSYwxlMudnDhxAmkDYl1l3ZmrGBmfYrqh8XxFqA1BLusMgI3JBhlMI8KzgqzKEIWWmUqVaqOOxnL8xBi5XI5yqcBUPeK0wT4OHD7ByNwc3eUC2khqjZi5at2pPypLjEBIiZ/xyOV8sjmfTFbiBxLXx8MCzpFQKjVgBs+TeFIhjMOCizlHeYxtq/AlhXy01kmC1m9rb5dEkEmS1fNa7e+yXkQpowh9S6mzg9FQoDIK4WexyhXpNWL/JGjGkRXmJyrbE6vtYz6lSbocFRisDEE0cIor6ZyOQUT/NRZPBkEGlAYbIL0wtRbOSCeiJSljRolW5WpzUUpzBbSSru1wk0MJ3JGsdZGElg4JSEskvYSp306+SG2OsSKBYFTTg3esGYOQhmwgaFhLoAyBFHhW4yWNxIUQZEMB0lLu7iCq1PDxKHXm6Ch1EoX1/8Zi/nrbr8Oiebm1dsBa61trB621/2atHbfWXmGtXZX8nEg+a621N1hrV1prN1prN/9mlyOaOhitXa1CgtRYtkItO+99EyVpM6rpXjHv7572HVufPim0m7cAJJWsqWdubauBQXNAidb5DfZpk0EKp/BYLJcZn5ji6IEnCONJth06wMzUGB1eN72dAYW+XqYqMVkCsrki1bpGxrD7qd1kix3MVEJMoRMtDKD52c8eIJaWex99EN+M4Tdm2XjRJj7xoQ/y1J5D3HLfY2jRYGhJP3uHhxk+ups1azcwt3MPZ199FYf3bmZ5p+UPLryC0xeW+eI//DUXv/yF7L73dq5/11/iewEP3PMwz95wJm9/10dYtvFc1FzAzUcfZ0e1TrB4DYVCFzsPjPG9z9xB5/oLaDzyAJ35flSkkfTQIYscHT5CPLYPf/kQpj4DZho72I89MIKaq0M4hSnENHoWY3wHCVRUhCqvoJ7pIWPqyIaBtf10GQgmQmwpQ97PuEImpQjDkDAMyWaz6NiC8lBKUurME4YxnnKMlVgblO8Rx7H7O5F0tlfSdf5Ji12UopDNIXCdwBSCfLbA1EyDfAaiumZ6epp8OcAPoFDOMj09y+xknXpNU61rohDiGGILnnASAxnPdx2DjEBaSZREf9Y6VolMpIPBVbUKYTG0Cn5SaCOFN1IPUyQ0TEefdJ+VUhJFUfNYnrI0IocvHxudJTIKHcY4gr1jr5wsHdI+T2RbDuzkeZWySuZBNolxRGhaUiOyCbOmbLfmMWgVC1pzco6s7VzCJZlPNtoplRphm4KAKW7+X83zec5gel1pZCFSqDatH3BxukvwMu847ceWwlKPDMK63rEeFpUk2I2AOq4PbSAlMsgwMnyE/U/sZXjfMEqd2l79JtszQ6qANmkAgdONMElCxcqmgZfSbyVScdl0aDUTaM+ltOW6SSlNTfpU29Yy4POZOGlZs8JpfAjhsHlwMJKbUMq1E7NuAMdWJz3nW0nYVkUGCR/fEmQ8vEyRctdCugcj5g7twFQmqI8d5om8RIzMkuuaJaCLYgCHazMsWbKSIyP7seEExe4iOZOlL9vB8SVnUjm4gx989/tg4fCubWx64e8yvPsAx0ce5qwznsWhgzsJwx3s3Wp47Z++mRcVfG7+0md5oSmT+/l29inBtoUBE9sPUTlxiKkYvvmLO4n9PN/51u3EMfz+819P/y/2s27jaSzp11Rthksnj3PN8qt4/4DPwP5d/NHKc/jYzgf4+dhBopsFX33gTn75ubdTfsGLqapxgmuvY8H+fcRbdmL6hvEH12Aee5JwzRD5K64iOvwUYuwAcqaA39cHazcSjmwnu/AMDDGZZZuwv7gJUavCzAIOjx6BygAibjBhKvQ0JMZItBZMT89SKnUQBFliJTANCHKlZiVo1vc4MVVloNRN9cSUE7EyOTCWjOfwbB8PpTwKXsDY2AQLevswxtBdLmJtiCnkWVToZmJ2mukpQ5CHnJ+nUChQKuYIozmX85cQx4mGu7GOHmodr1opiZROVCwyUVK9GjjMXAhirZG+lxg/hZ/NENUjt08IavUQz/MJtTMaImkiEcdxon2kiOOQIMhijOtCFYkCnqhTn47Jl3MUcz3sPDDFuqUllwzXFi/QRLEbu0IIYpMUI7VZ7XkOl7HtQ71lPJM5bIRAWA8jaoCXRBipaFjLOCtcn2MjLEKGGCsQZBEidsnWVMTM2laeLOkPm0xcwCECJ5vHdBFMv4Npq4qfdwg0otmYPCVxiKY2lWg/trFOYz9w0ZdIcgjSOiHDAJiowYaSyxOoOCI0EQ0hEFJQwKcmBNoYJo6N0t3dzYLLuskHJY6NHuJ/uz0zpAratqbBTcSBgCb+bm3aPM9ptDuc+ySIZZ5HY+at7Cl80u4JNJXyaHVWT5M6afY8bQJgTqrGOpml8999JyEcwyFQnvMwY0PgF1i0ZA2hjehdtAjj5RCzU3QuLGFiQWdHH7bYh1UBZ5xxBlp4kMtxfO8ODu17jFxvH36hxAK/g49/4h/A+jSoc3RinD1P3Y8NKzy2YwcTYcxcJcTQyb6tjyCnK1QmI4pXX03ujS9hzQ2v48pzNjC8ezfTqoSN5tAySyYQ+OUhLl27kTe8/qU06qN8/c4nGB3xWFprcE5uAUeqY/ScexmbQkH1QIVVLGCgo4RnF1MZ8vjzz3yP+NBh8o1p/IYgWH4ajTlNZWIC0VVmzsuRV2BGD6N680yNHEYyQ0QdQu28ptFd+CZChBbWX0yoA+769q08sXc/OaXQEw2CWBPHhiiKiKNEfMoIoijGVwpjSJKbEbpNMbReryOlw7BjJdCeIPYsoTCuMMo4jxclqUehy8MoRRRFFHzF6NQUXV0doODE5CwNYxiZGkcIQUbl8DzpyuKDNokA2zIlLjJ1CUdftsZbKnFhk85FIimuiXTc9OqFUAkfXjavSUjXG1QpRWxN06NvNBrN0v2YROdFxFSjiEzOI1QOp9Y6wtiYsMlgEK2Iut0l/xVjnYRRJizNhKoQNoEyWoJdCNPy4tvujYNJfcCxZ6y1CDk/qhBNh+vp0gnp8U6Owp/+DFpfzXWYArDIxMCnMFD736UEi+YxTqZpQxJ9GAJPEFuJp8AXEk+ASgkf0kFAVgqyXkBoDKMzk5iGYc+uA/R2l3/l/f5V2zPGwKeYlEzke9PB36JtubZ5RhhMWhlmLaIZqorE2AuM0WBdFapRTsK3ffDI5J+wwmnbtBn11OAraVzW33ogfLQIm0kfh80pQKLTUE20VdEZgTAOw0sLLLTVKN8QxmA9H58qJ8b3sP3RO1mxdCOV6RnwM0iRY3xsAt/3qdWOkw08enq7ue27XwUM9dFRiuVOcrkS235xG+N7fsl3b/sCX9yxi84la1l01qUsnT7IB/7olXzgTX/Ma377WXi1WfpPv4jnX/1i3vlHN2LvfYrPvOVD1G/7IfeOnSC3bCErb93G1eU+bsoP8d78cv747PP48nvex6Pf/Ce++LWb+D+f/ihyQR+brlhLfsMiju57nIHVZ7Ku7LH5c3/H4mwXq/IWFc+x89huFm0ocv8d3+Bguc5Dd9/DxC/ux0QhGkv5Bc+imO8jfuoJ8su72Hb7XVS3bGHsF9vwS4vZ+cBW/B07MI/ei/IMYmo/RsZYJYj9pahLXsQlf/hafutlr2DZWetY2tdNKd+HUFCpVKg3YsYmKxw9epyx0SkaM1NYDYd2HiLnB2Bd8whLnWq1jp/N4HsBJmwQ1huY2LoeqK5WEd+TdBRLTEzPoTIBVmlqcUgsNJ2lMuNzDXrKkpwEpWMW9/QzNz6DzeYoFDvJ5TOonKScK5HP5PFi4Rq0qwCUhzGgAh+UY1QEyjVsR3lIC17SSUgIhYdFx6HTMDEWozVYSyaTwaLQJkKqhLQgLVEUUW84JcwUbgqExpeCQi6gETcI65rerjwjM67QStgQP86ghePAC+uiiXaP3enRuFZ67foxVrsKV2ENVtP8nbWamFRsDMc2ky4Sjknkx4SbrxhLYNLEafJx4ZpxG4nDtxMHLC1+TLFxay1Wt67PWX6Hj6fsH4MF6RYunSZiW5Q8vCbrx3HvZQLLieaaZFEyYQdJS2wswsZYqzEGJDFSK8KgTmeQwaDIeJq855HxLCVTxQoP31rqSuNrD6Nh2bJFFLI+mUKR3v5OhA7+VzYVnikG3rbwsXacDFJj6jZjTs3FTXU00tc8VbhkIqSfn4epywQb59RJHnd7koXGQoAklo5S5WnXVFsmutQW2WICSIsmRidaG1YKrJXUtSXOCGQY0miEDB86jB9XGB47yoUrVnHhWeeSzyr8jGZuZpapqSlGj48wfnyaRUvXo6xhycq1NGYrdPYvIju4ELIZOhcM8LWbbmLh4FJUw/CnN7yG/iULyfb24lGjq1TkxNaH0FGVD37uI/w4k+FAfQ8bX/UKvv3tW/mnr3yVB5ZlUZedyZ2HfsaGYhdRRycX/db5/J9/u5k/+PSXuO/ee3nnjZ9i82O7mRgxnN7ZzYOH9rD3yCEo9fK9yjH+6thmht79AWrDBziydYwoM871r7qOP3n/Rzl8bAQ1uY8onAMb4G88B7F/BH9kmvWvfAX7J47h9foUihnE4kGmdu9F6AayFqNlB4YSghA/V8bYmMySQfysT3RiggVLl6In5xwGLX10ZPCk5NixoxTyAToW+NkMu3fsJZfLOZNjI9ACX3ogNLl8NoEz0q5E8w2a53nkC1lmZubwVICPpGEkeCGmXscrlOkslZmqznGicoyBoTInnjzMlod2cmzvJGN7Y47um2B4/xizYoZMXuLLCGMtgRcQx+E8/NYL/GZOoVlFKmjq1KQJ0yAIEmaOE2yrVRvNJGA6n3zfJwgCrLVNjz8V4HJdjCw2VkzNxEwbCTLjmtuc1DPuVJ5wO8HhVHMsvY604rV9/qbvM9axdYwSqER8LVLiaV52YgWS/a3opwnXJJG7aIvUHSTTiuRT6rUrEEtg15PE05rChm3RfppzOzl5mz6H+d/LgnKa8koJaqEhIz18GyGVjxUCz9fUyJC1HrEfEmUslbEaejYiatTQccjk5OR/YZd+/e2ZYeCZf8OAJu/dQTKp/KhshngppKKbxK3W5rBviScUnnW6GjRb+6Vxo8PsWwMySeIKhU01JwjcCi4ilPUxwtHeYiFpKPCMk0+IJWjpfids4hWkWfZ0YEiLb3xEo0okFKuGzmBg0XK83vUsHljFLT+5jYc3b0GgUaKMlxPUqhOUs710FvoZHx/HAMPDU0S2xsTEFI04IpAet3zvdv7i5dezf3ICP5dl/7Ex9lZDPv65L1Ihw3OefQUXX3geC5d2s2fHTky8j/d/6qscHg3Z1L+Yg08+yf5wmjt/+O90LT2Lvz+ynZ9NTzJ06ZX87NYfYu/7AQ9tfoi+TVfx8wd2UlaHedPKTVzWmaPS2YWaOMALX3QFl33su+x8ci+Da9dxz4++yFe/OcaGxf2c/oILOfv1f8OxR+4ju/lBYunkfdXVLyBcsoSRb36PFYOnU6j1svcHD1J5+Enu2HGIY1FAFOdhYRfexA6QAaGYxs8PgtdNbu0KfBRiKuKcBcuIGjEqG5DJZFBWsHzFEjq6CxwdGacuDPFMTBB4aGmo1RpYKwjDkChqUK810AYqlRpxbNoiSg+BQkoo5XLUKw0qVU1HuYhvDVLn6OkuMXF4kuf+4Yf4/IHjvOGm+/iLrz3OzZOTfPiX+1j5pvdy7T//K+98ZA+3HznGV+4/yMW//7ccPdjASkHYiAlkDpA0Gg3iOG4aZs+TKC9o0W21G/+OMRNTLBabhTIpdCOlJAzDxKCHCGmJ4gZR1HDFT7GmUqmQzfgoD7xshoaAcrnM/mN1pG/wPI9ASnyVjmOax07vjRBOIluQSvm2O1KqydyxCZfckz5CzufGk1ARJQYROz0cZEtbSloS/RuXZJaiJTiYGvb/buFpJjtp89JTXnOaiAUsBiEdXCKEwKr5CVl3jJaWfLrfSEWkk/aCKYNIgJURfuSR9Q2T1RpFqZCBosPL0ZiGffvG8GyDyA9ZXD1Iz8xTeKU5ehblUOEseVmjLzv1G9nQU23PjCRrG70whWiEFNCkOLVlvG3LMFvpkqytTLz7abEnaTs7TDPF15qJoF/j0iwtLM+LLaGfRAkW4tTICwG2XWfalU7HpDIFjs4plEL6Pp4JIJtj1eDp7PzpXfSuPY2puX5qtYPYSoZSZ5npWUWhwyc0FaqNKYq9fdi6wMsLpCqgdQSRE2Lb/+RTLD59JQWrmD5yDCNLdA4MYJVmbGySe37+cz7y7j/jrR+4lfWrSrzwuc/mBdcs5ODubUzWKixffToPHn6EZf1LGBs5RrU/z95H7ufCwaVcef5LOO+qS7jj7p8yfvAA+RXLGKxZHt+1la5CB5cvXMv7Rkf45OdvYuGmP2bmye/w43sPceNfvJxv3T3FbT8Z5YNvfxFHjh3lU1/4IR9+22sRx49Q6xQEuV68RatY+OplNJQlwLCmO0N9/DhHb72Xh37+ANctWQy5BcQnRpHdawgoYOIGNttN1kRQcFzywaFl6F/uxOYEcUItrIYRJo45PjqG9gXZINv0Yuu1EJQrjmvUInzfMaRoowYa4/RemkJRRARBwMz0HKXBEuiYhvLoyhnWvvaveMUNL+O686+BuMHgBRsZu2cr9ep2vOw42ybg28VFBN4yXv2lL/Hy1z+ffbv2cd83v8SiVZpadRpFPimiceMoNholPQdVSMed94RL9injjHCjUSMIsoRhPVGRrJPJZPA8jyhyi5jn+S6qTCLgGANJLigbZIiMRliDlwnwPJdrUjQg4aynEKZjj5inTZx57JWm8SUR6EoMPsIJonmiKWvgjomDS3RCNxbOu7b/RcdpaxInDenmu3ValM3kb4IGOKmANlZOuwPZ+ug8G+Fa5bV9F5LvoyRJk6WnHQ/SznPJImDT++BaCfrSMa98AZH0ELICkaaXxeTDcfLVSQQaH8nA3CS+gCCp2PVPLQLwG23PmJZ9Gxc6kSWpnDctpdPjcBibQgmN3xw8bqV0ht01JIaUVePCPQ3zVmDnDZyaJuV0L0yid5Os/NY0a5rdAA2x0sfXECvnq/i4qEIqXHQhXBtuKWyTRdOe4FVCgPDQJuKHhxcwPnGU4sA6xnfcz5J1FzB+YA+qbKlO1VGFPLoOPd0LGD8+QqHTMDc6zvIN57Nn28PgKQqBh65oZqaO8/Fv3cIHPvI5+koF5OQ+pMpwxopFlAo5Dk/OMjUFx08c5QN/91Eeuu0WXv3S3+Hv//JGFrz4Fax/ci/fnhyBiTl+uf8hzs0vYuXzr+H8cy7gbe9+Cz2LhyisPJeS6GDi/3L33mGWXNW592/vXVUnn07TPT05jzQaaTQoooBAQiCMCbZABGOC7yWZbCMMGPOBsTEWNhgTDRhsMAaJIJKEhJBAaFAepVGeoEnd0zOd++RTVXvv+8euOuf0SPZnX777PPru5mlGfUJVddXea6/1rne9K55h5u6b+IvBMvniCioz+2nmV/B3YzvJZ7K87n++hWeedhb1Yo53vOoyBpflmT82xfJiAaEMR+c073vpBWxcs5JXv+Z3CZYNokUeL6xArHnkttv5yU/u4saxGfaN7UPNVvFszBf/8kNc9P43EoUr8ZVwzSlETBxOkA1bRI0KRx56mAdmDnKs3cCTPo1YIyNDdiDLvb++hwdv2e0qEkWIslDsKzndFgSxEWgTJfiqYKBcwvPSUN9xrI0xVFoth59mAkq+x+TsDMsGlnJ0coyFI23e9I//wvat2/n6l7/Bz6/6J0bKbVauH6Go8lR8ja8Eoh0Tzxxlw5v/gSve9gdcuOZsBkerGB83b2IX8sfC5QKiSDttmWSuu+bTTmem0XaGPTYakwhkxe3Qef8ZRdRw+vApzOR5kumZOQqFAgHufC0LOSShCF17yWaTtaM+Okyuw/RAHDI1oAnsolMddAdndiJWlzVD20QH3Xp09GBMT0e2hHweJ8bMMiTQgwAAIABJREFUtcmESMe0mml7P4GVrrDIFYH1QiUpHTOxARawohtN2MWJW4PtZGePp9/3wjGuc5P7e/xMjla9gZdAY0LYTovDOMmRrBwuo1OYWLg2Hc7meNxxsM6fnJEljHyapkZoJF6sqMgAL24n+aCIjO/+ViWTGoRY8/m7K79Vy76nhwefDOe9Gyc7kOZH0g2brrpd6ld3sL/jcPvOSDH9//CMouP1Oy8cSISJpHBQjrWO+Ihw5cuxdLoyALEH0kiUcZCSFukWEbtkk5RI4RT3jLZEMiLwAgJfMjG5n/O2b+f2vfuwEg6N76FISH0hAh1RLqxk9YaN3LPz56xbdyoTY/vQUnB43368vjKy1qbeaKLwuemBu3jwgUc59aSTOTy2H4NitK+ImZnnTX96OS/7wz9mzekXkJuFVWsHKL3sd7jiyn/l+oNP8If7H2bab/Onl13C9QfHeV32xaw5eTN/8U9/y727dkJB0FiYZn7Hv/KhN/wJH//6DuyARcZ9mCO7aXtFjPB4XukkTv3Lv+SS55zEHXc9wik5y+CGTcwcvJ9l5QybNgzz6EMHGOpT/M1Pb0RZ+PL117N13XIuPm07gdfkltt386833kPDV9hIIcsapKY/X+Z9X/tn7vkfL8IbXkMkQqRVeCKD8rM0ZURGlFgzuoJZ0aI6P0GzFlKv1Mngo/oibv3lDlRcJOvnMaEmmwtoN0LidoQRMX5QoNkKyfoBOm0sodOSet/NCel6qGaLGXQjQpcDTOTR8EM2nfdiVjz3dznpJS+mKuHPv/I+zvqDl7Dz369k989/xKw3TYCbA8PLR2iVBrn6r17D9HiL897yRm78yt+zdKUzmH7C6/a9jItuIzfvlQQhFehEBEy7EvgUf3cCXrZb9p+smSjqQk7WisTD9xE6Busaa0R+gCXEp0g7rtOigGcrXWxZCicb3GmTJ1w0bdMY1yaRamJErSsolEkOyiSl/l3P3OW1wAUJKikt1SqJlq1CiLR3LAk0m1SUGvd9V1cCIXTc8V5ypE2jfXqiDIsDlXp+74WW3DGeWqi3EwUkQmrO2MsOwiBFUvgoBXGkIbAEsUVZgxaGKLYI66HwHJMroUtKK1EiR9hsks36yNiCMfiB/xRX8d8bTw8PPiPttmWZLhZuuxV4zpu2HUVGoKMql+6WHGfchUi8B5VgeAh61IK7D0OIJCMveqryEgpaYuzTClWkRZoUa3OfUQntq3te0fl86hx05FelQOGhAglS8sUd8/govOUFmlPHCKxGGQiyI9RFnc0rNjIxbmhUHufUbadzrFbh4O77KPRtpTX3KFpafvzDn/CFL3yVs1/4fD73iS/gBQOUB7NMVg7wZ899JrWBZXzzG9/iaNRimcyyZsVaPvCaC3nFB/6Wqz77D0z9cAefnnicXOCT6zuBnKxx0113kFu6mXjhEIW5YyyzA5S9MoWsor5ukLvHY5Zkj/EX2dVUFibZsnQpj9YGyPVbvrvrZu6UGt9rceaLP8ue2z7Bms3n8OhdP2Dr5jW88vW/x/U/u5n7b9+Fn4Uwcs/baIUUmmLWY65pwBNEUQLXqZiRAPbPwx9f8nw+891voHJ9SJt136XpytajBXRthni6yU33XcdYq8H+sUmu+9EtzB5t0Rw/BoP9rFk6yJAfU6mEeIWAVqPN8qX9VOtNms0WvpfBxCFDgwP4UqAC34lGaZ14n7BQqzLbqtNXGGSkr8SuBx/lvpk655z7Oj78/W8y2Ae5TERjzyRHWjCyYgXZPLStZXupzSWrns3GdWshX6Zx9B6+fMtt7Nl7iC++52U0sSjhIVtNIukT0I0GlXD8dqEcxm5Ed50AxO0Qg0+j1SSfC8j6kmayOfjC6d9EsSETBCglOhBUvd4kk1GgwfckM5U6gWyzbjjT2UhIq1h7snaLKY2ig4n3vpdMfue1G4HtePqaTpV4R+ZXI4RyjUe0pR63iMI4YRo52muHyZBECem5nJFOqM49p+5cYweXMd3rtKmulHGaOCmkhHTOnQEjJEEmQ6PRwBdy0TFdb3FNG9i8tEwYCTzlIik/tiAidC7Pg+MBb9q6wGTdoRQaTWQtocVpwtOT7xGWTIosKMFnbp35v6PpdjpE0h1FJPSs1Euwx/13OizQO5e6WCEJ3tg76Vj8PehJ+CTKFJ1dmkW/Y9NEU/eWHc+9cRTOhE9LIi9Ml0kglKua9DMBtOoYHeI3WyA8TBigA5/S4CBxQ2Dbc5xz5kZWLl3BXLvN5JHDYHJksi3AoITkyPRRCvk8m4bybNp2OvmBURqtFgV/BXsm5/jGlV9n6epnwPwCkwsLBEs2MxUKBi0sWb+KaOkUr3z2i3nhBedyxrbl3Pyba9mwahX5jMcfBQWslWw79ySODoeM1w5xwSmnY8wsrVqb/UenaTdyXPfoQaIw5ODBcV45cjavGRohp8rMHLmRKJwnig06honJBR7c9TCbN69ylaKRh2gZ4jY00QilaIWQCQyB0mjpUWtrclKy0BAUvDz//qtfYv32YtaT9RDCB6+AzJfw8prz1p/I9P4qP7zi37D3TDB25BiZjGBufp6944e482CVtp+hUmuQy2QxsSaXy2OBWDs6bBxpNAIbO8PRhRYMQeAxOlyiVqkzEBhqMuLhA9PM3Hkj89OHmRibwAifFVtWsO0ZowivzsL4BENZwa93TfK5e27jozdfxaev/xIve/8/8Ldf+iannraZ6myINA5iQUmEJzG+JBZOkTAWFuO7+ZfKFLTbbSIdExpNEARoGxMbk/RuhXa7jY5DvEyAlNKpVB5X7BcnkYAK/I5wWbURIaXqVMEaoLedmjU4o56kWZ96pOuqd921MYiELpmy1FIGnPuspofi2DPSCKR3fYODaTqV4k9KEHTpMYtqYuhi5tBdyw4yevK5pXjqv9FK0Un0puf3rKCSsbQyHrQaRPUmGVUm52kywkkV2BB0y1KLfObbMNPQHJtvMDnbZP9s3f1MVf+D+/pfH08LD74UOA/edT93NzIgoU4mHrKSrnjAJUwTrnqnds5BLR09GiG7xU4keZL0gfZohaY0S2CR+lz6nvs3hX9MB6dXiM6Dxdie8yY0rER4qZf2BmB9H6U1Ku9xw15Jux3hFzJE1QaHqnWoVtm4/QUUrWLjCUt4bPcY1vcJlKGgMswtHCY0A+zd/Rts2OKDH7icUBc48/Q1fO+WXdx79xPsf+SXrFxzAtXZaTZt2MjO+29FWI1tBFx9/ff5/peuZ/WKNnrO0L9hGUfv2clCU3PiyZs4eft2vnftTxjYNUH77GUsH23w+O0Z9MQE/evX8MD+Se6YPcClEbzktHPx0ITritxy3T2cVFzOWHWSJ1pt9m5fyuZtr+BnX3oHhdHTaczeidYgNOTzim2nrEBoy5EnjjCzAEoYyFo0Pu12xGmnrOJFLz2XhVqLr335x8xVPAZLMVM1sFP30xIewcBG92St14nEDBFeu0Lz4P1kC/1sWXk+hVU+9x1p4EtBGFvwsqzv14xNWcJszMZSmXXLl1A3TgnSlfMb8rmAXMYn7zvMN9WJaccuARZqSQkPPzDUc4ajRxZYt34NbHkeF73idUzedQ9vfcdLuOamXZx74akcm1NUxveRX7uCtcUCn/7AJ3jnJz9IJrRcUl7CtxYO845Np7NxldMusTaDFIa21ASeh7DGiZRhkdp2RMW0NcRxTDOKyRnJQtii0YpZ3j9Aw4bunmczaGtotZrk83lkWnafwCfVZpuc72NFjG7FkMnQarVZXjDksxarNUYkdEC6xnLRSJgOpsPZ7xrj9PNa6wTb9hNny5X8p7rr6WFST7rZahNFGpJKX4lxePVxlMSOU+cytskbi416x173JG91pyLddgy8Em5T17J77CCTIwrDjkxBep3WumfRRLN52SBRbFFSA4oglmjPEtkGPgHNMAeyTcrtt0mbUdnLPrKJ7k3qGArLTx9t/v/fg7e9htUapDFoK9xPovrQSd4c58EDCW0pmUwmZUC5m++ZxTSqRRn/46+j97jG8We71CfnxVvRfbhpAjj18FKu7yId7Z4HaKMYfLfV7Nm3h8OHDlAsr+Lw2ASqMk+hXObkVXm2bB1mxYkb2T3+KGecexqt0LLQVqzdsp18/yhWGXwUsRriwBO7+PRff4pXPOdcNqxdyvCqdfSX+6g0NO1ZzSvf8A76Vp7CCaedx9eueoDf3LmD2Qd2c8cjv+Gu73+Xb/76N9x876186vOf41dXf5+Tz9zM1redR388RnDgUbafu4arDj7A4cw67p3Zw2vbBd512aUgPMJghDga4vfe9QFGXvsKhtstXr9yI2N33sxPvvw2cqVh1p6w3pW8a4VW0GhoHtt5hLt3HqZFkfVb17Pu7A0MLh9g7doRzj73TJatOZHIH2DJ2g18+FMf49Nf+iCve+ereNbZK/jC+z9ONuNhTQts7BwC4QpdlM1AsAS54TR0TvDY4V/yybe9FoICQijKAQRRzOFZwZpCnryFubbmkYlZYhFgrU6oiQFaG1rNEE8pMoErOBFJRapSgqjWQKsmjx2ZQ7VDSkITFVfRuPZLXPMXH2b1Bc/ivnqGdRecQUVKlmdbDK4ZQTSzNGhxx493ULJweGqGob4WP/r6d/GGRmgaR7P1fEHbajwEJk6MoHAtIqOkl2gURU41EkGQCHD1F0rosE2l0US3Y1dJm3VceZJq19T7FxZsrMl4Hs1qC6SHFR6lXEB/McvEgmShaQlS8oDnYKJe58WtWRw2LsziSlPRNVYChUjaECbtPnqMb9LWLlGEhRR+7XG60orXjoHuRtxuP5AdRyxl+3R+ehuBCDqOZCpL7GicjqGntXatC43tMGJcwyBvkXHv/I3KkStSu+COa6n72lVG6wxVAUrOE0iRKGVapNZIHRFqiY0VNlaIWKBjMJHExED425vnp02S1SaMpBTeSLswiU4yI02CdsOh9L000SMTapPrDJUwcOiGYb3jKZOyi97vydLbFPd3+tBWdnE+53ks1oR22FySkRc4lo8FX3lEcUw+mwMF0sATT+xFCIW2UK+F/OgnVyEsLF2xliUlj4M772TTqpV4fgHPV/T1ewyPrGXu4OO0oknmqzG5JUuJ7Sz7dh9i6vGHya3ZytK1K6h6ITt++lM2LF3H0q0bmT0yS1hQTLWatPaNMRn4nPyM1dz3wG4+duHzuffQGCv3Lyfavp7zz3kdes8hvnDrPSBC7rnvevr78tBazi/vu5utqzdwrH6MdWe8kHu+/j3Ov/ylFFetA2I8qUB51KszHDv6cJKEdt7bSEYyKCwzgUdjboFdswtooZweNwtYOQ4Wrv7hL9z9BzJBgUzWJx8o/v6Ra3nzm1+BPGMpnSI0nDGwtk1MDqSP6ttEa+J2LnrdK7Af+jKxKbB98yAHxiepa59Wu8JoEHC4WmemCqbdYNVwP0Hg+pAaDTGWZqNNPp/HCAuJ4JcQllzeY6YWUxQZmrOKwGpsWKOqPAoHf04w+O9EVfCzFp2VNA2Uszn2L9R4jujjWW+4lCUCfnjNzfj9AblKjZFla+HwFKo/RocW6Ycom03goRilZJJMdUyfXqhFYYlMjCcFhZybX8KA1jFaR4TaacXnswE6isG4aNR5y4J8Pk+U9HNttur4UtEMnWa91hHSl0Q6donWRQvXJDzgp15ji2BRm2jHi9hx53HwiVvLdOmYSZKWxB6IBPp03ptzpLoRtkrw/+6mIYR7vQPtJse01nTKJtMCpU4+zuLsiRRE1tFRkxMcd/2L/34jEoVa49r+2YSkkTOu45yRkI81LT+Djlsdho4WvovATIRAJPk9d75YGqS1rp7mtxxPCw+ehMfqpAMkRip8kex0yY6HsZ0dVxiXrU61aLxUUtg6YlNs4s6EiSUORrEkD76H02t7cLkURrFpklQkxVY92hki7iR4U0/Apvr1Mk0AGZTBSSR4LtlrhEF7Fm1jAhWAbyHy8HMFfB1irEYIjUfTUdqUZHL8KIP55dzzWI3rrv01V1/971x91RfYv/N7nDg6xKUvfxUHdj1OebCP226+icZCllw+AzbmyNijDHmKA/f+Bmmq3LNzB2OP7GH3o7dQyJ7ODXsCtlz6ImbxODVexqtPupCP7rydg1PTNPeHzP3ND6ntnmFXa5YLpifpG9pAxBomZ4/yPz70es761AdZ+/pXsvyyi1l+4QZGn72WfVf/kupIPwvnrUWWy5x96f+DHVxJOPYoBH0YoRBWk9URR9qGfKwYDSSbA8nmjKYoDTZIONZJ5IOSKAltVUe3ayzUFpiotgnOuQzVOEJUnUckkICLrgIUGt+WEKpMdt1WIlVCP/wj3v3qU7lz7yQZX9FsRRz2oCUVMuhDCTjWirCqTBQbFhohnoQIQTWOaRuDLyCj3PNURhLkPEqBx/K1/cw25ikvX8n87pt59tv/nnpY5hMbfMojrs/s1EKbx2bg9mvv4fOvfSdnnnwGd/z4u1x06nO4/it/Sn3BsnbFaqYmjiBLFkMB7RmU9hJD5SIUrS2xJ/CVh4mTMv/Y1QFExnYgkb6+IvOVBVrWle3PVxYIshnyiYqmlKBNmxCBDPJE2klIKBSIiPpsxNR8mw987nIuef0rHe3YCApBHqtSLXVnFKVyzei7EWvX+B4fLbu757vkaLquhEhaYUoQPV2dPPd7LCzapp3T/E6S1ibKn04xIN14u0WQqf8ukE4HIdGFBzDWYQJ+WiWcbFpODBC8FDmQifugE+qzkp3ovWu5JJ41REYgraGtBbFQzEuPWkZgtIcJ+siKLFL4BCoPsXY5OiuRKAySSHhEeERWIYyrfP8PSgH+W+NpYuDdSI3rol1SdPVoQPZoRkgn+GO6Xrx9kgHvFjWZHminF+ZJcXhXnOB+TM91dAXHuh798enVNNyVaeu/xNY/Gad02iDNZpOtJ59EFLeZn59HJRV/cRxjtMYnoG/JMAcnDhO2p4mYYctJ29FikLGjDXbceS/3PbiHRx7bw6MP7mL9hnX84OpvM1LOMNg/RByHPLxrJwKYGBvDFzFHDu4jG9V5/dtfyrrV65idHuaiF76QLW97NatPewZnn3YBz/6jN3D+67ay9OJNtLYLtq7MMHjaJgZm96GWReQbbW792Oep37qb6ekx+vMx3/vst9h0yVn0r97CCR+4jJVnnsfs/AxTUzN4QYaFVjZ5jJpBL8OSQkDLGio6Yq4tmAwNA75gicmQC7s6+0iPQCdeTARGGVphTKw0wkDl5lvJ+FO0dBsrXCIXqxMoQBOjITNIMLCMusryyfe/m5HyEo4uaE5dUaJoCywfkJw0FOEbidVZjlZqYAT5fI44ch2R4ihJuEYxYauN73mJPICrwFQIhoYKzC80Wb5kHc9/1athaAMnPGsL733Nm1BFKMkcB/bv4ct/+3EKszewpb/KYPt+hrOHCPIlIs9n9MzTUe0F8JTTUjKgtejMN20ddTPldUdR5CCaVGDNRGgb02q3CcMIkK4i13OebCCddxpHhkarTtMmVZm2TiZXJBtY8gXXbm74pBW85x/fwtTsBOXhYapxBWEl1VYN28NC6UCPpLh4t9Bv8b/HrfGU1NDpudBdl2nki3EVoQrb3QDo6rAv+k7StyFdiwBOHqrbgCTVquld/9ZalBEY4eaZBFRMpyhykRT4U0T8LvIwSJmwmaTTy4lRDK9Yw7LVGxhevoTlq0apN2JaXt5VTidOq+6xVZ3jCYHDL0IQ0ZPO+d8dTxMDLxBKIJTTkRbWkJZPdLLTUiKJEVInXWoSISD1ZK8cHPaklSt5dt60ePLmQa+apBu95c297wvpEr4SH2E9N1lsinAtDhk7kycJ+dyBrKNKKkU24/P4Y4+Qz2Z40xtfyYmbV3WOAz6xNFSmDxMuTDE0sI0gu46jx/YnnXs0SkkmjtWJJex9+H4OHJ1mxx23sOPnVzE7P4fvw+hwjqF8gWefeT6rBnzKhZj1a7YwfqTC7oMHGeqfgdwAA7c+xEmjZT78J2/m4gvP4/bDhokN57NuzUv40M2HGK32c9HIep65/w7+5XdfxrlvewF+q4WYPoYolnnR857D1a96H5UjE9z/xSuZ2/FtMvnV9AnFCVtfQmZoHUZXyQdFaEfsqkIZt3iWeB5KwYGaoqnaKGEpaIPwDWu1RnoWmQhKRa0CFhjQPqs8nxNe/1b6C2ezsOOnqIW9NL1ZhAgw1oD18fAxMsB4o5TWboIVJ/KDT7yV73zkE9w3XueNb3sDO8daPDADy5YUsXGTVnsBLyMw7RrSl5Q9n9jCXL1OiMNbwyhyiU7pUSznmDw2xdBAgdnZCnNtzR9v3cAVt11HPAmrDvyaty4fAFPnlG0n8cHPf4oxvZKFrEcpO0LsF8lkfU57+Vu5aPMoBa8CUpERCmU1+KIDJaQqqWjT0a/3PA/f9x2vXQTY2LWRs0azdKgfETeZqzUp5Mu0Ki1q1TqZTJasKlASikw+i8ajX/g0NJRWDfPOT7+dV7z5hQhjaNbaRDRYdfIzk05mTvxMYBOHxkUWvcZQCq+7fjoGVXcUJTvrxS42Pb3OUAf/xtWQOAMbY4mSDS7Vk3EFVr26OyZpttGRIxDWZfeTH2FBJKJrVrv6ASW60ghGORKFpxZfXyoDASy2I0KBUNRiSy0yzDZjKm3D7EIFraFpizw+Poc3PMDKVcsYXb2cFavXEaKwNnbRWRJ5dCAlAoTNgs3w246niYF30EYn8fMUzJ40+7yY6eK+m77W2ybPSOF0YxLWgTTdHb/7/eOSr8mPOO6940enz2rPMTv0K0tHz8IN17ghpYDFcdypgqtW63z3O99jamqaV77yMl7+it/HmAgbh0ghMabJkUM/Y2gwjyc8lg7lwbSxugVUqc/PY32PwJYIbD9WZVwfyAimjjWYadT55d23UVN5jh6tMBsd5dien2AbglUbn89rX3Q+hTPOYMHLMRlpTCBZs3IVg0sGMf4x/NY4j020mW8OsnpwO78Y28OjD43jrRhkz65pjt51FLVhPef87fuYG4zxqjX61i8F3ebxB25lJqoRl/sRhSz1sMUz15bpJ2Q08Bj0LU3RZqmQtKSipGGt8jBSsNwIQmUpShCxxkowopUk0CPiOGJZACtGfdZf+Do+9Y6/pEiMNrorKWtISv4lyH5McYjzf+ccSiNNXvr7L8c0nadU8iTj0zU8T9Kf91hohklOJCbrewm27zjXQnqJ1+wEuxqNBrE1NFoxHprKdJVVQw0+fukfcdAqMqUSnmlQHCpABKs3DjNcGkHFPr6J8RAoHfO+P7+cByYXKJWzrhJVQiwjsnSbPadzLGWHpU0/FnmjSnXmnZKCocEBKvUa83M1hFAUyyV0FCMDg8r5tCsVylnF3skZYuHxro+8DqErzkMOM2RyWeq1eZZtPgHpSQrZXNJivlfMK1F8TKWOOX6ddh2oboRuu7h7z1pMN7G073H6etegmg6fvrNXWNHB0h0DL33mT2axdSrTO7Cs7PRytSkrBldB3HHsRM/xe0bH604SsSm0bIXEIEFqIiJ+c/ej3HbffqardYTRxEITYIicCuKiSERbF6no5H+GxU3G/3fG0yTJKrDGYW5pzr13Yjj4S2Dwk0Yc3SYf0jqyFfTSJF0zbZ0YebcrL4aA0kUjhcAas0iBrpu8Mt3JaDyMiHrwRLBSke6R1rpzOOpZulGkYmkOQYxxuuLGGIJMjmazxlythmjAVVf9AInggnPPoV6b4+RTTuOxffezb3+DqUN7iO1RlAXt50AGhLU6sWxgdIzNRwle6ESSMFAq51iYbxMEHgsz04TEPHb/Dh59TKF0xMc/diN/jU/ZH+LU0zdycfw7DOf7OPt5Z3Hld+7gFz+7mmJ+Hbcu72fVeZfyi2tv5NQz38KSc0pMTM0yfVKR2DRY60lUNk+z4FNpHWb/3gI2miGam2b+gSkKXhttB6iISS46Ywul4hFueegwI32W8SoIKyjaNrNCEJuY2MBRH1bFimmrWedLvKzHZBSysiCImgEio/GNYi5soAoBn/vRNVy55i7uPHA3xuQRMukPigcywtKPspJo6TO4+KWD5DJZ/uBDX+QH3/sxL3v5S1m5cRljT0wgqlUebjTZsnIJfcJnLmzQny0QWpirVBgolsl5AU5yVpKRWcK8YHK6zcqlfeyZmWGwvJLh8AHOeeef8+vPfITtp23hXWc/h+de/iEue/VzuOQD7+WBz/0FC8oys3c38dn/g2tu2clP/uzP6F9VpxB7GO0RqRijQWYkaMeastYZH6ttT6RpkFLhZwXGOOEyhCBOvNNszkuYaJpYNxHaoIIsKvaYimq8+s1/SHEkSz6bY3qySqQDjIqxtkl52GfmCShvHqT5Y/BVCCopSsKpu7qerU53RSQ7q028bCFtkoPtgVWJwMokqZ5KH3QtQVceXIBy8uCyA+m4zlzWuqSzQDhRQKtdpNzTr8Ho4zYFXBLVYJBGdHrVIkF2uj+lVsc157DauHUsFitmdq7VWjycFLg1EcJapNB40qBEQNyAM04dJVPOUz9yjEcOTbJyaZ5TBos8vK+N9APnyGHSlLO7JtvBL/6L9vM/Hk8TA+9CXiNihI2T7H4mSWi6hEpsAOlugkogOdnZ/RKjnrJpLOhErCxOkibpDXSfT54mCYteJAXOyUQ0xnQqZ63BGWUJQgRoG4FwmLlUAh0bVIoLGouV0ul9S0msXMWeFDoRcIqxWmHqIeeccz7KtPjFr28GjVP5s5ail4MRyy2372TJUB/PPXsVqlDizjt3Mjs7y3y1BjoiFAGecZBUHAk8KZDKYnQ/sMBCteIKd2JX8SgAqbLkVZZWaQkFJRFmkjotdtz1G3bccTeKNs8960KWrFnOP3/u7zn7/Is56ZWnc9tN93PF59/OF774A4rFl9M3MEL/0T7qRIiFGrMLIWXVz/qtp/GlR+9H+ZKmEJjmPIWt59J44DpQGc7dtoZ8NMv+1hJqBxasLVm8AAAgAElEQVRYk2sjShqz4IGxTLadHHPbaqY8QdPCgJVIHbIpk3Ht2cqSjO9h2nVG2zBahljAg4cPoOYnaRYK5PxlWBmgcRPcWgEqjxAaOzjCuRefzp/csonSaB4hBMf2TbB6xQmU2kcQCw3m5xr4Sz0yQtDUmkxW0qpqGrHBUxGelkhp0YkeTNu2kF6O0WCQZrvBmAi442NvYf3WbcTNKUpzD7Pz65/mrOc/j+3nn8VNH2+yfI3PgnwJX/3xF/jdTc9k4/KIZmxoakEuE+HHPrGvEYlUhtGx6/2pul5lauS11rRb8eKq1tg5I0vL/cy1NF42R91IsgHMTszh5wPe8ldvYvm6IY7tnkIMQC6bxRLjCYFRHnEcUugrk1E+Q8tWMn7gMUq5EhiRdMZKNxsPKyJH27ESEFihXV8E4ap/k9YWIBTWKqw0HTwfpFvriU8ncbCPtiCVj45jhLF40iNKBGSMBCMs0rZBBhirk53Cve8JhTa648mn615KmTBdElVKhwP38O8FUngYDF7SrS2ymmyvcJkRSaRuCRPdLJPYoCV9A9RCx37SMSwZHGZsvMbj04KcXyNLgbHQEiCxSjrn1KRW0LGOXBc5hXN3f7u+rE8TA+92ZFSC4QFCxG5KJN6By7o7Q6WtcZlxJbqQSI8XoCUd0aIuNu5unuy0+fvPr8gKibGOcQCOUqaNRvVMGGNMR/kPXBm3wKClwgiL1QYlFco4/kAceGA0mYFhbr3hLgaGhnnzG99KrVLl4T2PMjs7y3W3/BLwGBnqp6YMrZFh1FyVw2Nj5LJZnnnWOTzw6MO0q3WGBkc4NjlJHNYJbRtLROBDaIyTlUU55T4Zgy0Q6ZBqFCNzdXSYRdCg1LeaSj3LwHAOJSw3PXQf3gO/4sofXks2o7npX64gNnk+8u6H0V6BzdtPYGamxU9vvJJLLr6QZZtXs2//DNkVa3joDnjs4M8QNoBGjfUveDNH7vwaJ/7O+3jgzp9x7d2HWRIuY/PeKUZGTuJYrsGBuUmWZHNMZltcumQtE3MVGs0FbFhFtgKOBR4yJ6k1DS1paWFpWMWGDauwtRZzKGYX5ilLEMNbueGL/8B5//MN5K0G4RFKn8BahAhAlUHlkMsyvOvv/oqf/vOPsMJy3Q23sfHUYV5+6etZYR/mcKXJBjlIrAMC3yCswlMhc3NTFEZHMcT4RiBlgI7qlAfyVBsRQ0M57to3xkoVsGHzSdQnqqjh5QgiMgcf4hObB7Drns3RQ3lWXPwG/u4zl3HpaS9m04oaUVOR9bNEQCPUeCqDIUbpbiSrSJppK4UxLpFqTErjBYRrRGFJ0UZXAduYr5D1LVu3ncSpzz6Bc579DA6PH2F2vkq7kiObcxtFFLlNwW0UMVIqCiXB3HyDzRefTXhNi2ZlCqQl1tbJGJsITYQwDi9HhAhhkSYDMu5IPFjjMPjOMrWJwe/hV6Y23lEak/Z9xjFokAbdC4tIhZewraw1dGnNJNeRQjZ01n9aH/OUSpP0sH2sQYuENimSq+yInQlSTv5i9p0rWko32LZoYk0WE4d4QlPItFHWQ3o+C5UGUnkuIk+VNXuuRyc2Rf3fA9G44WqJUnpQMikSA+s4rso5AaL7fDreNz2/C+e9y3Smd7qspzfxuAffg9MdT/HqftAkvHvjEnmQSBqnoZTsOZ4l5eS619yEimJDJukEs3R4CdlyH9/5zncIPJ/B0RFGRkZp11vMzx3j2Nw00/Nz7H/iMP3FHCtWLWfdqg3c98AuMhmfdiXiWc/Zzg9/8DPWrVtNHEUcODBBqDW+DDC2jU7EelzTqjrSL4DRxKElk/EgzFOvj2OMpVqpUSwMopshQVDE6HnacZaD9RZnn7mNJ/Y/TmO2zhV//lFOPeM8DIq5mZj3ve+rfOBdl3BwYoZpmacV5giogu8zsWcH9bkjHNv7MCLT5oxTtrL71j1c/KzTyYc5Hpo4zAlL1jOQy7DjyCGes+Z0jopjjBfnGLEttm/Yxs9vvBtVzjKmZ2hmPfY1GwSBx/yhCUaGh5Cxoa/Yhxdq5qsRl73z/cy98eUY4eHJDKFbuclDdEZIyyKib5Tfe9Wz+NzsYb7ytX+iXYm54iMf5a2/fwkZ4WEENCQEWqPw8H2PdiRotCJKxQAdaTJegNUxEYZ61VAulBkZGCKzbj3zjz+IIMPW13+YDWqUmSf2cOjwg6w+ZTsveedr2RcZ/ujEi9jct5/IFhAexChQGk96xGFExkuKbHrkdWOtkdJh31p356jnuaXcSxqw1uknZQdGePUHLmPLxmVU2rBn/wGksXgqoK0Tdo5xkWjvepAWYhvSrrXJFXMMrV3F+INThGGE5wWdKCI11NaGXeKBCDtronftieR5dNYGyuH2titboHCe3JNwbyERqXaLTTeCZL11bLbsCIg9FW89OVDXVtjEVvR4iI6ZIzobTpoXNIKO8lS6NXU0rRJj38mH+BIZObw/G3hk80XChQpSeGgRP2nzsdjOS0abhKDx5Fzkf3c8bQy8kKYLiQCIECvBEx5COtaKJXTFT6kxTrSq6UgT0PHy06QNkDwYAfRMLHFc6Nbz34sZMW5zEQlu6NgADgcUiTdghe11CJykgnWIo8UQC1wWPzl/2Kpy5PA4cWwoFPMYIWnXY2YbFQb7V5Avj5KzlkIx4Nj8ONWFGkf3jXFw32GEkhT6+jEGPJMln+3j4IEnkFhe+IIL2XzCOqqVBvv2H+ahh/dSmV8gl5VUmg2MDcgEAZZ60kA4pKCG8IeyzMzspeV5BMrHEDr6WhRSLPVxx87fEJTLxLLNVTf8lO/9/CYqYZ0vt/+OTEHROLaLVZs3cnBshkrzGI3QsRtKdcvotlex9qSNHP3hLuZnDP5ohkpYxtTKPH7PbTxmK7zm1G2s8rMsVMfJ/N55nFHop2V2c9/Dj9JcqehfvYwV5UHqYZPaoXEakzW8bI6xSoWwEbF6/RrivMQcnqKB5dZvXcWZl70AmV+PEhKbtImTieKckQFCrEIvV7z1T/PoT/4r7/nB1Tzndy9m24W/w8Gf/Iz9s9NsHl1CHAqMZ5xsQX6Yo8dm0bbEQDFLGLsiqHYUk8kIJmcmGTUhC4fG+cSdB/nRWz7M7mvv4F9+/n1OXl4gjPq578ZbuPYz72N4sMj6dTlazRxL115E1K5RPXwvSgqqrQgZgBYZRNJMOzKO7+/7fifJ6wys82GM6Rr3tPmHtRZkgK4d5btfvZG3vfcicvEo+bKHjjwa4TwZmaXq5wgEZLNZoijCRFEChUrIBdTmxxkeXsvqM09m9x23USqVXAWtBRPpTqLStbeMk6hbdXT0je5NFLvcmfv/JLlIr2QfaEzCosHVI+jEkxVp4jPxwkkpk7qTJHUxtCUl0nR8OZMyVLoxgzPKxgkI2q5Xb0TyOdtlCzlbaxzCYCEUtqNnk1Kcg6wTZ5NSuqCZEKMCgpyPmg3IBD5RFCGtdLCVdJtVp0LWdp3cWFjk/wccmKeNgXd7pershCl7wUHvadLS4XtdPMa58ikcA4mxtmCkWGSsF+/mtoPb/0dj8XvugSAczpeGkN1ppoDeRI2XlFrYzveFEOR8hYkMgfIIcmWGSwWa7TZ+EKCCDKVSiYX5KgqJVygx1WhTGNjAkmWK+vwEY4fGaTabVOZnyPgB9z5wL7XGPJ6naEean99wC4fGJhjMFdi2aQMGS1MI9t71KEsG+5mcnSFT8IhqIbGtUSyOoiPLfH0MaQUDg8uoNarU56fJ4BOJNpHQeLksUdTGVwHN0DBQ8lHCkvN96m2Pm3bcgL75JkqDfTxj0wkcnplFENDOZdA5mJpaQLQmyfa1OWHwBCIvS4E1vGXrMHvv3c2e+iSbBkcZDwT7brmbV7zmRdz2k10Mjw6x/KIl7D96jF/9+n6qjTpZGWGNpr/cRzYWLF+3gmxW0r9qLQcnZinZkPf+1We489zzaW+o4stSUkgmcJXIEiE8IIYgj5dfzbvf/VoOH3icZnWe8869iB/+9GdUF0LqSwVKW1Qc4yvPJSiVoFqtU8pl8IUFbVDCA9EmVpb+JUs4OjXHV/76M/zTlZ8gG8Mb32k58stvMjywgFGGvv61TDXmCYxjVFz+9c8SGMMfX3AKot0mm82jTRMZeVhFUpzkEo1hGHfYMx1qYKIr09s+T6bdnYRlxaql3L1zFy37YsL6NP3lLFqGTmo4EgihkdLH6N7KT7dmlBEUykUnBoUhm3Oyyr6X2k6VODzduZ74tiSq6J31l66r3uBYSIfj03G4ejzpdN12GPcyUYG0x6laJp5dz3fTe5M494uGTI/YgXWS43dsiEvR28SG6GQTSsqkSAMSje2oxR4f8RspsKHBsx6tqEGtOkWhmO255uQ+J9F95/sWJ5PivFR+2/G0EBsrZqTdviLnJimLDbKXPMgOhVJ06ZRKdGljaacbIQReUjyhJfgku2HauzWJg9KH58tuYspJE4sO5YyUQSMSfr60HbExI0BIDxLj0VHBFCIBE92xRYoJAlrGeCKgWPT46v2u9VchyONl80QihxRZCrlBVClDNqoyP3eUTGuOjKeotTVh1OSUrRtptuo8tucxZKtNrDWTswsgXH4hTWrZJOGklGLp0qVIP0/cbPL2t76Fb1/1bRqtOgfH5ghkAS/XQEfDjIzkiRoV8sUBnjj0COWBPirzDYQwZIplbLOJlc6jNLhK4kAK1yA6oREKGxEZtzHrKCLwfJb2lbDFLBeOnMCJG7Zw4vOfz903386mcsCNd0/yomeeyuS6PM88/3Su++zlFGWTCnkmpufZ98jDWBSVVot6w4CJiImJRIacbZPPlahHbaaqIVtOWk1YDzk6NkO9FjPTeAx0BvKjIHxiYfDwnIdnk1Jy28TO74HZSb589YMcbs/xyY/+DUZAvyxxyvo+jPIYyGfBRGjPozIzT76vRDEAoXIQRbSMIdYh2aKlqPs571PfIBdkePgHP+OBX9zE5f/+z3zuPX/MP1/7Ax4bX6CyYOiLZ/jqd37En737nQyU81y2ZROjq3PErSaelti8hwnbCfZu3X2VAmlEovMeIRM+PCJG4hNHrkoz9eBjEREIn0B57G15vP19L2fpEvdeo9liaGiQdrtNNpvFSxgyrVYrKQx0NrBabbKw0KRQ6GNy314euuZXqGyMjQzSZNEZDXHUWadu00mdJI3RyvV4tVmsjbD4ICKscf6lIMLgtKfAOeoSQWhjwiimGUadjcsaV2WeDiclkmZLAdntV0tSAZx+Lh3dRuC2A+eIxH4AWCRKSrRN+vMajyCbodGouQjegjVuA42FTYqWDP2DA3hW4eUyeMV+KpV5nrHlBBoLdR55bDfFvoC+QhGJ4NjYhIPchOlu0KkpTiA5qQQ79tX+z4qNCSG+LoSYFEI81PPaR4UQ40KI+5OfF/a890EhxF4hxONCiEv+qxfSm7hMf38ST723glQsLlDqblTuO5FwhUZpgw5lWHS8VEio17NYdC3iyRvf8V59t3rvuNuofZTMEVs3AayviWSIVBaESzzpWOCLDO22oFFvEVeOYqpPEE7tpPHwr2FuH0HjGAuNCpO1KnGrQf/AEL+4+0HueHCMwfxS7t65k/e893KuueYaLnruczvcaCEsKatLa83ExARjY08wOXuUf7vym0wdG+fiZz+Ls5bmCb0aYU3SDsrM1ueYj2oUAuettWfmOO9ZZyN0SLkQoImJhEAbiYo9giCbtFBzDZzDMAQhyGazZLNZisUi2WyWI3XNsWNTfGPnDj5+zbf5xBV/hinG5JZkecZ5TaZW9bH7V7dx/ZevION7DI2soWGqqLkxlJfBK5apmzZGapQnGCj30e95DJZztGyDbEYwMljg8UcPM1OpUyr6RJ7Fjs/RNLVE4dAgrXEl/riydgtI6aOyRVRpgHM2WvpKS9my5mQA5qlCgku3Wq2kKXfIwMAA0zNz1CMIVIL3mpis8AgrOTxl2fm1f2P3I/s5//3vYeV5Z1KrzlPe9jxGQ8PtO/YxsrGPPcdqbD/vTH5ww8185d++RSGjwITkVAGZMdBw1wmujZ7nea5CM/HWleo2phQWRx1MkqQdaWDl1DAr9Qb7HnyEX99yF9VKK3GSPIe7J05NJpNBSkkURa43rNWEcYhSgiDj06gvMLJiFf0rR11NgvKwSmMi07lOEsE9rKs077bnS7sh+Q6Oxf2L0IsMdrKaF62/Xvqz+1sXU6h731u0nhPHrJcenWLpnYhfdCEYZUhqZvQij9yy+PfuyU3n2jpdqpLmKzZ2FOVatYExbp75ysdTGaLI9Z6NpAsF3LVLJ09te5LDx+v+/G+M/1cPXghxAVADvmmtPTl57aNAzVr798d99iTgO8BZwHLgRmCz7d0+n2KUMsqesizoTNq04ADclEk9e0nckUl15RZm0UZgEnzeQxBbg5GCwAqHl0mJsnS46l1jnSaVkvMcl3RNC7Dc5uIMn2MqSEcPs1FXPVLaRdculPNQbIIVegK0tgz2BXzyl3MUi3mKKqDZbDoDGTmt92whT6XaRGmnYmdiTd53bcyKfQbPzxE2swQZp0VijCGXy3HqtpNRSnF0coIdt9xCKsbmeR4itmic7ENalRfHgkJRsHX9ZkZHlxLGcwyUVrLnaIX7770Z35dEUYaztp/IA3sOObpaIIlaTaQOWbpiI1OTx5AmSppAuz6hsdFd7BVQ+MSeIJBtrNYUB9YQ1zV9fTk8lWFF9XF+7w8vJGqHlPuGoDXDHXfv4uiU5uGZaYaEj1au1+pCveHCeTTLBwqotsQPYLzRQMQexrYp5nKEus2RaZ/fXP8vbDr/AoxfRpLDWIO0vsN9ZUxsLFLECF3Bjj/GDdf9mD/6yLeZnD2Gp31OO2kVOg7py3gITEemoNGOmVpYYMvaZQTKIwxjWk3Ngm1SwGdlf5nb7trD9ndcztGJCb71+Y/z6j/5R77yr3/NCwLJFTc9xD+89uVsPPMUPvK9q1gOvOCZZ7MkrmCUwQ8NLU+6Go0Os8WSkZIoofkJY2nHiTqkdLRE1zRCOKaZlRgbE4eaWqvFzPgx5InbeM2rzmbryRtpNasMDAwhZAvPz4G1NBoNwjBEeZ7joANxqJ0UhFEcHJ8l41vu+fqVePmAWIdI43XglLTQKZUg6CZQSbx6hU6TsUmhj9GpwU09+CSXgKUdRrRjZ2Bda8V0VfbYLSM6RIrUmKcNRXqJKClOfzycq9MUQjcBSCoD7mBiSybI0Wy2ET34PDjGi4frO1HuL+HjkSnm0WScquTcDCPDA/hZhZ8toZsRC7NztGpVrIkcNVJ2q1idHXXPViL4zf7/wx68tfYWYPa/eLyXAldaa9vW2v3AXpyx/8/Pge14HVqneslP3ng6tMenKHN+EtYuBH4ivRpYQfCfbDHHn6u3OhCe7OmnnWS6iaPFBVRGe2AD17ZPGzypETYEnDcSxzE2DjFxSKO+QH9fiempKcdqaGmmj02T7wioRaxcNUK+NEh5qEzbltCiHxFYvCCHUAH5fIFyuY89e/dz7327OGHzVt75zj9l2fKVFMslJ0gljNM0t4I4NsTa4AXQqhnu3fUQP7l5Bzf8+l62Ltec019hcGQprYYkjptMTM/TbC2QzXr09feD9fC8ElE7JJ/JLro/cZxAOMkilVKCZ5G2gW37+LZAuz5NsZRj+YlrIFC87o0vpFgehEjhE+MZGF+oI0r9DGYCygN52vUG9WqNIAjIZrOsHh5gSV+B0IZgI/LaUvZjRAC0nQZLO2xz+cf+EV2ZJW5XsCQNpxPmhCt5V0iRAZXHloqcvf1srvnsX7mkpdXMVasEQRatDZ6fQWuL50lK+Qx5z8PIAB2HWKnwvBhfKogUszrktO1LuP1TVxBMTPGjG+9n/3U/Zs9jUwyX1nPo4H14WY/x3U9w1T9ew+lrL2JU5bFao70MzYxG4voSW6sxJsaYGIvucT4ceaDXw+2dj27RWDzlk81mWblymMfvewSt21Sr1QTLj5xXDczPz9NqtZxDIASe8MA4JyLSMdKXLBksIjxFO26jJGjrWum5rGZaGGgTAC+5VhH3ROBxJxlLjz5Mev0dxFyYRX9TOqdSWeK0j4dzchdH8081elk10tKRQ4BuhO8ZnBNonsJ57qk6XfTyonuuOr+3wxrZrIcVkiBTwPcLiGYLEYZEYYvIGkLZjTLSeh+SzTuVSP9tx38JgxdCrAWuOc6DfwNQAXYC77XWzgkhPg/cYa39VvK5rwHXWWu//58dv5hRdlviwTscvPueSnDwdJdMu55a4RT+MEnVmRRYJRHG4gt3jBCDb5PWfQndIJUB7a1M6/XY08y1kIvfsx1OfPIaOJ45uhsOJ5NQKYcBSs93/AAjUMonNlUywf9i7s2jLUvP8r7fN+zpTPfcqepWVVd19ahuqbvVmkeMQBIzxCwwZgnDcpK1GJLYCnZsrCxWEpI4EGIHjCEMJiFLjlCYbDAIMQhLaGwh0epBPamn6q6qrvkOZ9rTN+SPb+99zq1uw7Jk4t5r3VV17z3Dvmd/+/3e93mf93l6SF/wG08OmezvYWxBrBQ3n7qRvb19itxBD7AN46ZySKWbIDNFGEesekhRoZIE7z29NAUvmRVlcOWpSrTWJJFiOBzwrq99J48+/Sgf/tDvU+V5qIAJjTgrHcJ4Yp1SUqC9xMoU70qyfg9fhKpFR4I0jri6f43x5jqJTphMgmenbjKQkN0GhoeKdJcFCVeioyG5tWQRyKoiL2u+4w138nXf/CpM7djun8AenMPpiiceeYb7nrlGv6y4yJTL+wY9zTmy1Wc2yxEohmua0VofXcd8+9e8lQ/89u9wJXdYmQQOc+khhbO7ho/+4e9w6pbjuNFxnIxRoocQS7cifNAvEabAHjyO273A+37md/k3H32Es8/8GXecPE5KyJTXBwOsN6G3YwzPX77CsZ2jjOOIUpaUhaMsYGMgWUsGTOoFT+/mDFPBN/7wT7BmjzCXu3zh/rN863d9K+efPsstr7uHT332z9mUBb//Y3+f8U6KrjVOLoLfqPNY20oR+O6z7TjmTXBpm6/L6U2J145EDZjOroIwPPLYLt/wfd/Ad37XN2LdgqwPVelxvu5gGoBFXrBYLKirksFwSO09dVXRT1N66YAP/cpvMH3mLJGWoaruGpYNI8RBmK2O8NQ4H+FchSSoYzpsCPQ+qKy2iVvLbAGoraeqTWeyIpwPvscrNMjWJtax3AgOwblWHgqUh6GXplJoWDThcQLrwxBUECKD2kMaxZRl2fXhvAv0ToMgEgE96A36+MoQ9xOKWjHaXMfkOYvZjN6oz+7BjPVeSjGfEftgzVj5OmxUTVnRYBFdxfLpZ+f/UQw/fh64BbgXuAD80+bnLwUaveQOIoT4fiHE54UQn6/tUh6gvQCBOHO4Kx6svNqfvzhArwbqVmjMqiCyH+CZF5/e9c9rf7b6b/c4QOAOwTgdrLPymtYo8HFQIjQGJ2oqO0eKiLrypGnK/sFlpK5RNbzilts4e+EC1+Y5ezjKqWW2yOknKetrGf1UEGEYDjZZoChjUP0BQkJtKuI4QmhBb9hrDB0CpDQajrl6ZY8PfvDXOffE87z5dW/hTW96O697/RsRMsjPKuvBS0pTENUKKTxxtSBWHncwpfRTrJ8RJ/BVb3o9r7v7HhZ7C/YmOVVVkGWBGhZFUfdvEHIKk5VRFGHjjKqYoJRAJSk7p+/irr/2Xbz7a1/BTv8UDz1+Bl9PiTJDphK2b7mNo1ueu990E/Nrkj49XnnqFLftbHDPzTdw0/Y6PZmwFvXYObrN+pF17rrtFk6ONoh0xYkkYzTsMRxtcseW5sd/4p9AVSFchRYeJ4JGegemiSAk57TA93tEyVG++213su1nODyTgxlax2gdU1chGFU2WNv1spSrB3M0lkSvEck+kffszyVORiTRgJ6PEZXk6kNfRA08X/0tb+c1b/4qvuUttyCjAU986j6Orm9w5guPEfcSJJra14GjIRrYxUJdGYz1wYbP2iaZUA08GEDMKIqI47gTI5NKUVUVaRKRZBm3HjvCB97/B/zRH3yC2hVUNVR2hnMG3aia7u7tceXSZWpn2NjcbIT2PForkl6CFIatG07inETikDLucOQlG0SCW2340zVfg1yBDv9iloFi5XHX3/tdltwm+L79WsaBVeOgTnRgtfJuNG58MwXrIARz64IRR5vJrxA9Xupclm8om+qqmZ5txN+01ihtsbYkihK8k3zpyfNgFPmiRmqFU4LK27AGXcDe2woAXjpWfTnHl5XB/7t+J4R4H4D3/seb3/0h8D947z/zF73+IFH+1ceTDmsPg0LN4mHZdJAsd/cgC+u7nV/iGj0KQSwVBh92CZbZuvS+oXuFi+gJbJpWT14KsZxW8+2m4zrMuuUdSxGeq1QU+Og6ULW6x7cNziYzUSL4YEqrkComiw0/9dGLJIMUUctOzMhLQW0NSoVsoCgKiqIIDct+xnxWsjPuIwY9zlzYJbEWV4YKIpaCOBLINEJZiYoEk1lOP8344R/8z/nTP3uQJ888hVZwYnuTOI04d/EKX3jgcyHTtoIkigIlzNpumCtNeuHvVo7aVrzjXe/mxM4J4rIg6jnOXdjl45/4AgeTCdvbfSKlcI0KXhRnzOczTp7eQcUDdi+eQYsIkRf8vb/99bzunlfy8CMPsbmxwa2bnvmiZjJzPP/s86Q7MY88fIbHn7zMurR84ze8kQ36XM73WVy4zIGFg2LOw489xw9+57fjR30+c/8nOXvmCv/Ze/4mn/3c/Twzm3DzLbfx07/0e5y+6UY+/OkPk+oRPlrDxRHKxY3JQqCqOV+ipMO7Ge6ph3jh3EVuf9f3YiLFW288iUk8I68xuiZLemANSkXkVYkVgmGWkSgoyprJomBt1CcRAmUM09rz1JmLvOm/eB93334z93/4T3nn3/0BfvsXf4W//Z7v44/ve4B73/5mfvcf/yPs5PXU18oAACAASURBVFGoQMaqY3+0PPcu4AiB0mHN+WZYSTa9IWstqmmWKqWwDQdcyeDh+uBzFzgo4Xc+/s8pr1xERBEex3w+p65r+v1+oO52vRpDmsUkUcxkusCaElvHfP43/5C9F84gfJguX4WHgozLkt0iAGdb6CP0Z5pY0d1PxjukX8r3CutxtWFmDA5BXHvqVnOpxdGNR0jXsbpUy6hvGsemdWVz/tD5tO8dpl5tGGhq8X0llrz55m+RkaauLcpBpAR18/eKMEpPZR0bG2OMszgLcRSSPxVnFEXBQMGkqNBC4ptmOMuo9mJYGNCCrziD/3IhmmPe+wvN/38YeJP3/ruFEK8CfpVlk/VPgNv+siZrG+BbiqQQS1OBFqIJqm0KMM1QlFyOR4gw+YUKH5bwEqmagOyXu7dyQNQG+/BUL0W3W3YwTbshyDDoJBUBqyQJGXzTfJEqAr+EaNrS0PvrKwrZwEw1xkUMRyn/++9/iWgwQDcr3QsNUiBVAsYjtKCqKjaGa+G5yRplvUcUp8xnM3bGfXxecfr0afbmM65d22O8tc6z554njWKUkuxPpwwH69Szgt5GRiY1/X6P+XxOrCT5osLI0LzdGG8ynR5w9vnHsRaSOHDG4zgNWugiNHN/5Af/Dsd3jvK7f/xvuDaZMspu5DVvvJmjR7f5+CfuI58YJvkeu/szZosppqrJZIrBcfz4GucvvMDPvfe7OfvMExw5diOvetU96Po5Br0xl/Ydi91djm17nnj6Clcv7uITz123nebOU6+k/03fyN6HP8a1S1d57KGPU9gD9hYSu5C87d1v5+yzjyAXkptf/UoSnfDUs+fJxkM++eB9fOxP7ucX/8VvcPM9J3AbOzi1hnDJIdwUJMYvUEKh3EXMped59P6H+bv/6H+kjoeoSY4bpgxtTa0FQsF61Accj1+4TCwSbj51FOqgzX5594BskLG9voFZLLhUzUhLxxefucCNx44xsIYojrn3m7+X+PStfP6Tn8RdeI7F7mMoGRNLiUzUynRq079pgr3UqnEsFCRJRJ7nwXjbhilXIQS1MUhCtSa1YrZYcLSn+cOHz/Mvfu/HYDKhvzbCOEtVBbqkVCAlpHGgLusoYW9vL5AB0gSN4NzT17hy6SrnP/onOB02mdZwpE26Aoxiu+Deesh2j2umWL0Fmnu0bWqG5qundAZXhi5sLfxyqrRrjIpGXvxwVW/9Uu8dApsthArRGLP5br6g6xeF4BE8CJrKI7guBWJC7WzA7pv733i6ZNRYy9p4GL5vdOiFCiohWqXUUQR1jjEVkVQdlNni7Ydi0krV8WdfYZP1Lx10EkJ8EHgHsCWEOAf898A7hBD3EuCXM8APNCf2iBDi14FHCbXXf/mXBffwJnSBMJTLYmVIqB12WNnxvG3eOjxGC4CG+9pk4q7ZuV3zuFZX4i8qfFbLr9UPWTQd/rBYl5uBUoq6KtE6xTlQqs1aWpOQtlEUXrPGkSqBsBXaQ11WOBGGN9I0QqqIJEmpqdEOokQytXO00PRri7Eli3xBHGfsTi22KkgOppw7f4HBaI0nnjkHSLS3XLh8nje/7e088IUvcmzrKEI7FkXNrJpTOrBVjRJBhc85YG/GfLqA+AhZpMkPrgGWspqCh1gnWGP58X/209xx6ka+9XWvZ+/WmF4y5vHHHuGhByse+PPL3HnP7Sxyy02nTvP0k19ksDFiezygrkvuuOMU24OIKxefo/Zw4tQRKlcySCJMPKZW+6Q9x/rGGr2LC9Y3am6+4xRxblh72zspjWZwxyleeOpZbrnlJi5deZ7jN63zwBeeJkkjdk6fYhAd4dT2GJWusShK5Hidt6d/jd0Le/zD9/0Yv/av/jeUP473BiGjJqVU7TJEB6krap0RbeywvXaOH33v9/JD//jXObUhmJcKow2JTvBSUrig6X3TzibPnL1CbQyq68tElKXB1TOiuMdYOExScsP2MfarkqO33ID3NX/62/83eSXYWDPkC8dMarSv2RgmpE1fqixLXMNOWh3jb9dpqyPT4vJaK2pj0JEMUKEziNoE/wRtOb02QHhJmmUICba2xHGAWuI4IooUsU5wzrG/v89sNiNNU7I4IV8smE0XbB4/zvPGo2LZ0CHFEktnmYmu3luivW0bLRqPDxOchEnj1WAhhCDyglwKrABlG9ES0RVddBWC5xCTJrDZlvey5PAwpFvJ5FffzzdBfhWmFQ0srEWQ8vV+OZG7Gi+srdFSNdZ9BuECK9AIy7VpwXYvTFR3E/ZuyQK8Hgo61Cj/Co6XyaBTA9E0ObwQS35qKyLUCvIvaYs0EE1YGEIQpEx94xgjg/AShEDbfVgyvEuLs9nmZuk03lnSJdsx6HanVc0gSKCsBbzZ2AWCpHnMciAjvMaSstVmijEZqhfxy3/4BLI/IrGLgJc2G8awPyCOHXEz4ZUkAboaZ2ss6hl9oVGRROuKI+M1pFbUVRGwbwTr/SFGGITwJP0BSmn62jGfGvpb6xRFFeCcNCYhpaYKZby1RHEMScBsrYHRYC0wTJDYxOGoiekha0lFSW0cXlqqUjHqDxgNUw7ykl4y4mDvClnWx1pLJXJSGWNNQTW5xhc/9XHW+vDV3/Y97B9c4TWvuJ2HzpxjPBpz69qEpx+9wOadt3Hh8Wd529vuxVuBvvdrKL70JH0Bi3NPMZvusXnzKzj/7KeY1o4Td76BlIx44zhysc+1y1e5ePUsk7OXuWIcV6dTfvYXP8g0WuPJh+/DZBGytw0iQYqoWYkO7zTeF6Fx7wrYf5LLj53jf/rJ/5U/+uyj3HC0TzGPGfRDGZ/2UhaLBb04ot/v88z5F9ja2qKnQEpNnucc5J5jI4VVnoODKePxiPNnrjKPJEmkOLG1jtQ1ly+VCGk41hsiYjh/dYYXkihSrI36gZ1Rlk1AWEKC7Zpskw7nHPNF0QzrBSXWoDcTsui6yhlmmnve863cfetR4iQIh0VRRNJUAMaY7r2MtWRpmMJ0xmKc5bFHzzEebfKp97+ftNHPb4/rg1UbyILMsAwZe4PXO+8RWgUIxRmskJ2GVO09tXeYvO7sCsV1We7yPZv7uaU6tl4NbfPVd1c4+OsS4sZqBt35KLdkirb69wG6TXVEaZvhJ0JVIhr579pZ1oYZaRwM2xER3joi5ZkXJVFvjTqfIFWD+ze4gfNL2ubq5yU9RAI+c2bxV5vB//91tPh7q0ERCruVRULYQVnJ5IVwCEGXVbcXPXgPiJWSh87Or8W72l1EyObn7jDVsX1X0QX6dmiizUZWN4NGF0S04kMJAh8UMqVHyRghJbUqqI0hLuZ8/9fdhhU1kbwBAK3CTaG9QOsYqz1aNpx+Z8m9YZidQESeurIoF1HZBWiFWtvA4HFo5ouSKFW4GkQe2CGlipA4Lu0d0E8zzKRgkdeYVOBtQZakgSe/WBBHPYzxVK4iryaoOGRxQyS1d8zlLDhkGU2aScbrRymTHG8N8+kBvcE6k73nSJIMHYUKQamU/NoEMe7z7MXHQBri/hbPP/88N506her1yCc5/ThlnwPS9R2uXbjE+mgLpRTV5u0ol0It8XGNH6dsyk381jZH9zfxLkfpiDg9gotiqCJ6MkH01hj25nz+sT8nMoq/9uqT/J8fPYuPPb6uCLruNjh0CQG2UQSVKdbMkMoi+8fYuSnn+/7Wf8KlSxWXiqtEqUfoMBOLqRlkikUJSV1irGdvb0G6kRJpx2AgmdQFl4uam4cbpIOIBRXHT53g3IVdysJiFhLVy1hfy5hUcwqbopRg2PMczAvyvAQfmtZZllFVVbNOFbIx2jDOosTS2ahNSIzxLPIcgCyKw2bkI+zYce7MRe66eYdIRVgsWmdIKcnzHLwgiVOUlkil8M0AjxQegyWvSoa1Ier18NMFIloKu4fssw3yhymcgWK+kh2392OTsSrRCIg1pAiJpFKikX6WKxn+8n9t5u29p3VOW2b0dD010cWZFcaP82glmyDfxoDrK3jZRaJQzAe/iVaIDOgsOmUTbwQGpMTKQPgwRUk/SajqsPF6s3x9OLwhahEqICNeXGX8+x4viwx+mCh/7w0ZELL2lv4EQWogLATXNVtFg31JtSxlVgNze5HEigGAbDIFbDt9dhh3X0Ixy4VHE9xFIz3QLtJV+642Y28zp1bVr13gYbRZdpuLFAG79U5hnTj0/Pa9OzxfBWwvSRJMHYaJIilDxiMVSgqMsYgoxhrP+tqQ+XyOihXO1GTpgDzPUUqQDYZIEZOXM3ScUVcz4iQjjTOMcQipSPsZUiqKoiDPczY3N8PmZixJf8x0Mufozib7+/tEukeSeLyNiQeBr51Pa7Ty6LSPUpqiKlAC+mmf+cGExx76GJdfeJbNbMTtd92KYI03vOU1fO7T9yGilK++5zY++/gjzF7Y5+5Xv5obb72J8cnTyN4m7F9GnHmOeuM4fuyIto7hRIpeXCL/3Mc5ayS33/tOqs0RUVlS57tcvP9B5kXJb/36B5gtPHe/67VMDyb86f0TPvhr/xw7OgZO4dUQrTTeKzr2BZbA2yqQ5ZzZI3/Gxd1d3vND/x3DZI3STxkO+qgGS7Va4itPf5TxwsUrjNbH9HBEWlM5z3yeoxCMR0Ou7l5BEKNTxcF0wmTmSNKItX5CEsdkccDTD6YLto9sYes5Ve6pasekmuOdQEcSrZtMXkT04giEJyy/oCfeoqPGOIqyxLiQ4fcjj9Wa3cUB3/ne/5SdtYThOGGQriGUQ0aAl5w7d4GqqiiKgiQJ7JAsSRmO+1w6s8/zL1ymbw0P/8GfQmKQNmTpFo92rgmwh2GTNrgD3e8csguQHVbefG+9Y54XeHQYlFqZYvWHNHDCsaqmGQyzWXn8YaZO97gV6KZNCp0M/YFWt8bZUE0vFosg6dBsXrKRQC5NTZqmDLOl3ozwjkVukdkA6eZoGVEawDkSYalih6uXNE7lQqNZN34TQng+d+Y/Dk3yr+RojXwdnsOZNE2X3OJEOxBwfZnWgXvNhTpc97h/x8Vd3akPHV20XxmL7rRplrozS6xsOabdUqdCZrJchEKudBZk2LmlFMjr7MWca3oM1hI3tnFa6650NsZ01nGtcmAURVgCayDLMhxB37v921xVYm0NTlF7x6C/AVZTVxAnPdJkQCRSrPWkaY/hcA1jHN544jilrnOynmIy3cW6ACXUtUK5ivmioioFrsrpjdbRWpPnC45tb9HPMgSOLEvYv3gRM8sZDYPRhi0OmuEVULLi0tkLPHfmPDecvokkS5lc2UVvrCO1JH/6KfzWOBglnL+IjCO0V3DsLrI73kBvPaWKInQWUT9/mdkTl9jbPeDqCxdRa+vMqZhOKo5v7fBbH/kUn/hXH0FOc5QUaBXjV7RUlitKIl0EUcrgxhvZGa/x6lfeyu61CUrEQUNEK2QUbsg0FkxmCzbX1tjfn2AROAuR8gx7CWVRMZ3P2FwfgvCMRiOOrK+T6ghjYVZUzOc2QD+ZJutnXL5ylcpIen3NaBQzTocMej28sdS1paoq8rykKC1FaTC2YX0oRZQETD2KFKPhkNEgI0vCFK+1wH7N7gtTdKzo93rB/clavvT4ee7/84epy4Isibnt1ps4ecNRjh/bCuqnzqC0oNdLOXrDDvSjLrgLQNhwTd1LJaBeBw65U+BVAEtXPnPZAbUNxu7DvRUIFxyKCy+FU1/fm1i17gu/X0oqtF/Cu4Zl47t7CJbZeXducnmusoFg20nYYKTmA5GDNo4JvNIsygInPLmxyMhjYkGOR+Z1x+DrkkfES8apL/d42UA0IRg2cEuHfbWUsFZgLLRfwyIIbJlmnKPbGFoxMNvqRl+/IBqmTbv62hI3LJbDA1CHzk+AdXUY3PCNIYHy3YCF9zZUDX5ZaXTn3VQCYSBENTZmTeBtqJSm+ZuVVFjniKMYYwItSylBbW2zGYTFLkVgLiRag6mRUmPKiiRJAnbqPEpLdJyAcBRlTSI8o7WjLPID6lJy5Og200nQV0c45rN9kizFlHXHpTbGkCR9IisbymafJPb0s34I9FGfYV0ilCXdGJPGkmJRkkWSyWSCjlPK+YTBqE89O2A+mTEYptSVJ/I5933y4zz+1Bne9/d/iDLK6N//JZK1dXppxvbmJounz9HrrVOrBf0i4sLznyYZZUT3P0p19yuJfYZ9xes5Pt/nwU9/hCNbRzl65Bjrt59m4x1vhasTPv3Fh7Fzw/Fbb+K3fvsP2BmnfPX3/wjuO95NmRviXoTRKcq1SUITYoSjlJZEKFx/h+yOIT/x376X3/nIv+X/+tUPsbs/Y2dzDVuVDNM+lZ2zkYzIqxlDIuZ1jdSO2GVo6djYHDIvShZVxGAAF54/R5L1OHlyk8nehL28YmpyJhcPWB/2GWUxo96Y0jnOXp4w7GeMhh4hY/ywT10Zah+mRPPKYl1NNa8ahzAVNGTiqGkABmcgASSJIvaO3o1DPvnL/y8PvuEOXn3XCYZrRxmvD7nn1Sdx9mbquuxEzYRQDTvHMRgOmC12iaIE0pRb3vIGnvvYpxFKgDUBhkEe6n2FmYMXT5wHfDxoWvhGZGxpphFuI+kD+yYw42hgGBXkugUNHOq6+z08KcAyL46Rjfz3StbeatSvbjOsVB0eie1kUVQH4XjvsUIQGU8hBbq22H4Q32vxe9lUEdKCtDXOK1JCUrbQQ2JbIzrl2zYWHZZH/kqOl00G35Zkq7uX9x4v/cruG9ThWn0aALWyg6/uuKtlV3jNF2f01+/+179/eGDzvQtWXssmaoP34wmLJny1Rrkdm+BQV181X825N9o7IWg7tAz4W6w0rjZEMjj2WGvoJUnXCJZSoqSg3+uF5qhUOFuTxgnrgxEYixSQpBHGVggBvV4v/C3ekEUxG5tjrMsZrWV4V+NsTn8QuM5JFDdqnZIsyzDGoJUniSVlMUMKS1lMEE5T2hlZ0iNf1ESpYj6boIXshMbaz3K6mFKZHOsgUmDKCrMoKBYz9s9fgqzHxz7+CW655w5mly8Ra8Xw6DZpHGHKA7L+DgvhSBLLmsxQ4y1i61B+gdTDsDlsJVy9eB7nMryLmDz8GMQRr7v7bnqDmAc/+SnOfOFx4rhmM4bnPvMokcpxEqSzdIyMhvrmnUC5GOdlqLKimOFwxNd+1Vuoipx+L1QicZxSFAW1lFTOEPX7jNYH7E2nFNZS1SawrLQgyzIOFhOcVZw4scViMcEYx3i9h/JB2kImilk5xxhJ7cKk8Nb6AGtKDgpHVQI4ohjSSJLFEcNexDBL6GcxaRp39L+qqromp9aaONZoHcy9ay85sbnFH3/oczz6yAWkjhFKMV9MKcu8mR03SLXMMAeDAbPpnCRJyLKMoqoYHzmKMQ6J6qpvKcR191cbrEoQFQgDokZIE0gRPkyjd4dcueeFPxSoVs1+Vp5w6AGiCQAW1xlnLOmwK88VgcWzep8u18FLD0Be30Ruz8m54AQFQaPGeMc8z9FxitIpqUjRqcDFmot7FtlMD7/k6/0Hgs5fFgHeE6AyLwC9dDpffqDh5nPIZsmFRo/BUnvTGHqE0BmoVqGJ2oE2zQconD+kpX39xWsXgHOumd5rmqxBogxoue6Gdpw44La6wxMhYJ4d9kiQOBBCIF0NziB88GlVyhMJRaIiIqECRc87tIBICiLlSSKBlib8TEu0avoRQFmWZGmKkoJUa0y5YDHdRwOJkpTzOWkUESkBVRWGu8qrrG+eZDI5z6LI0aqPIiON+ngvcCYEN61jQJJEKd5CURdEaUR/OMB5QZzF1NKyHg0pNfTW+gzSPnHSx0qJ9eBsSUzJKBvy+JeeYLg2CI3a/Ws8+8STPH72AtcunOdv/M3v5Pd+6yP81j/7FcZjicn32N45yuzsZcTxbdjZQI1Po6xhkm7z+ad3KW85hUo2cItL6LJEHL2ZI8OjHBkJ4te9k2//Oz/HH33s3/KT/80/YPvm45zfv8wDD3yJNHXcccM6t2xpbv/m7+Fn3vcLmNlllA86L6uaI4FdVSFFj1pnkPYRN5zg9Mkb+d7v/HbKyZwLl66SO4NIIzKbBoGu3OLMjGO9NS5cmeFkjXU5tgqbx5GNMbNqQm4U21tb2Krk6eevccvpo9x8wxBKSVXEPLd3mcW8pKoqslixsTZiIxtglGd/VnDtICevapwzpFrRT2KGWcx4kLK50Wdjo8f6sEccKdIkItUC4SwH8xmFiVBFTN4TDIn5/d/7M9Y2MrZ2UvK5ZDafspiXHOzP2N87WAriVVUYhBOQ9WO0FmztbFGLIGMc/G811L4xI/Ed3NneB0oEZ61wjzT3nRSHgppzDmdbOYaAR7dc+rbftQyMsmMRdSSaFVXagPO3ry1XYBqWnstKdESMJTlDHHqNVqPH+WV8EV5SK0XkFEZItJPU7ZyMlAx6PerasnuwYJGOuHLQ58okYrydYfyIKEuJoqiRcPDUzgZoT4Qxz6/0eFkEeGgokU7gjQ8feuuugscKHcK3Dxm7INi1SBFkCGC54zkBvvmdbxdB8x7XN1NC5z2UbC3s0h1edQshaMFXBL9JQbs4pdTNIrbdBRVCoCLdnY9E4RqalZcqeDsqhW82BUdoFkdR1GjxBO3pYBcisc4F42EbSrj2cUKFMrwsy25owroO+0EIxaA/xHuojEdFiriXUfuYRXGNwdo2dS7Y37uC8xVlZcnSAV6WgCMvC2QERTlHCIWKUqQIipG9fsqidEhXM61ysjgi0hJf+5Dx13O0DNK6pakpZIUvJuzP56QyZlKDKxf04xQZxQzXNZ/+yJ9wyw0blFZz4elnyacThBY4GyGeu0pRFDy3u8eXLk84e2UfruzDC+eR85yiuEi61uf5M09Quppzn/oQH/jZ/5o3v+HtvOevfw/ORkTJAO8Ma70j7GQL3vrGk9w6hH/yC7+EtHO8ycNUimt0XfB44XAixdnGEMP3UekafvsIX/cNb+bmG48Txz32ZobUepAeaRsN9qRPlAjWBzGTRcWiBqkcvjaIumZjMGJv7xroiCxLuGG7z/nLU7RKObqWkkpJJhOmuWEyXTAv8qCLomKGccog1QyziKr07E8N+/OaaeEojcJ4ifaKCE1g2gSYzyKonSe2oFOBiCWmzsmiioHX/PZvfgpRJxhXE8UZSkt6/YzBsM9oNEKpiLK0VJUjSTVZLybrJZTlAWs727iyRGqBdTVoFZqsTuBtCKrOB4Ex6wk8+EZS2Dq3HCAKVLQAMUlBJAQGgVUK3UzteuuQBE1/1QTvlh7ZetPKqLkXfYB4hCdM/Lb8RoLrWtzQNVvnJiAEfOzK5JEllivWfCGIBO4+Dul80z9sNiNv0Q1UvKhK0hgy4bg6OUdeLjhx4yYHexFnr+1ycSF4YbdiUji8kkSRQEcepV1gaX2Fx8sEgw/WdrTsw4Yh2fVYXJhcE82HGspnQEiEAOddQ6NqsnIBdsVjMrwDBIRfIL3vBqFenMW339gm4Afz6gAQanxXvoUmkfNLo+JQCjfN2Cb7b8GhJU1siaO3C6sqDVKr7gxbRT8lJKrhJSvhscZQNdIJwYicDitvudBAJ/o1W4RSuteIktXG0kv75PMF4/EGWS8O8r4NA6Cqc5QM6pBJEoaAlFYkiQ4ZhWvMx61FSwVVxebRMYVxVM5T1wV+DllvhLGe8fpR5nmOkJZqb4pblAw3N6mKkmmZE0WSyfNnmc0tx7ZT3njX63nuoS9w06nTjI+9imp7nfyzH+fJp56lp2qOv+pebrvhGzFvqIjqAfUxhbh4HlUUuI1tNkY7nH3qMfKnPsD24E5u//ZvIqlieldGfMff+D5++V/+CjJJ+NADe0jxDKe3h4yKgl//qV/gPe/9ewHXjRTWBsxZeIFv4AaPCh0enYEQ3Hbb7fzDf/BefuRH/2emecG8ikgHEdQWraPgnRrFrA8VF6/uUksJJibLkgBTacnWeI3ZbEq/PyRO+hwfKC5f26esanZuGDHZz5ks5uQ1uDyhqirWspJSKXQU7oMs62N8aIbXzlNVJd7DfhXUS3EeHWucq5osV5FmYEXIjvEaLSVzX/OZTzzIN3/b61jvrVFMZ6S9hChWRLHA2IYTbwqSRKFjgXN1AwXBzs038tT5F4jRDa1SYG2FEBohJM4FqKdzsWalsm4h2BYODdzJcPqtppQLHg8rk1PhfpIC0WjkIxoevADsChHDN68pBLpxf/KE6VbX3OGrhBvvfbArbCOTVKxW/X61RygU1ttGaDBIKwgpsK5CyhgnYi7vTzl5/Aj9yjGZ7PKJzz4ZNh4huXaQ0zm9Nv3G1td2Sc788o+XTQbfHi/qih/6Gx3yRVoSK79dwmovGh5oHx825YatIugEiLr3g6U/6/Wv0ZVsDU63MvHWaoEENcwXbx7NE5s+gutgJ6DT+g54PN0GENgylihqB6k83gZzhbYEPbzw2hHvMM3YHw0w3lLkC5yzHYdaS8lsNmkqkBC4jQnNOhXFVFVFXZcoGVGWdcAWq/BvkiQYE4Y91HBALUQw0TCOxbV9pHLgPEmsg8hVmnLh4mXiOKZc5PQGfRaTKbPZjHE2YmtjnYe/+CBHjowZHzvC7oXz3PLq1+JSg33mi1RVzWv++rcw2N5geNu9uGMjdLbOYhCj9iboCnQyoK4W7Nz2Kk6cvB0XWR4981kS6anMgp4TnNg5Sj9J6KeeTHqcSLgyDWyn/+Un38/5Bx4Eu+hMM4BOUTRsxDLok0gFOkbqlFM3nqAoFqRaMWuGgpRSuEYLRjhPpDS9NKOuayyCPC9DxtnwykfDIdeuXQtUVVGzOY7wTnHmuT3W1tZYS3ton1CbnMItmJQOYyW1bZgoyJChCk+iGygmiVkfD9lYHzHoZWilAv0yjcnSqIFJwt82X1SsDUcIBflshrECLT2JjrAuxzc4sVIRUkQkSdZAmA4hHHVlcVaydXwHnyYIH7Rrgh67bGCvKtBOXXRI2fEl7xHalCp86Uby26ggBia5TgakzE9e4QAAIABJREFU3RSux7EbLWGx2nhtHyeW7/NSz12y4prvnT+0Ga2ed2fM6ZY8ewAlNc4axlmEsI7nLk25/MIlxlkWNhMZJtsjQHkbYFt80+M3IE3Xz/tKjpdVgD9McVo2O1Q3TWAPFS1COuyKGt3qoYU8dOHawsDiu8De4m1iZZFY5wLG5sMSC2cRxLZ8g72vBvUOilnRtLj+b+p49W5lsKP5XZt9DwaDYMEml+ettUZrSVEsQtasg750kiQ4T6MaGabhlNaAwBnX2K15bFU3QxPh782LgiiJkZEkTjTehX6B1nHAQmUYeImS8H1dFfT7/eYxOuic+KCiqIVERJrSBMbNsNdnc7xOXS2QHubTa8wmB7iqJooSSi+JooTKGq6ev8jbvupr2N/f57bX3sVs9yqXHv8SJ7a2eMfr38HNb38b5e4+Jhuy8fa386Vf/VW23/b1VLKCakJZ7dO7/CRmMaO+/WZ8kpAkGYzGnHr9a6kuVIwGjsWz54jTAdbV3LC1TrVnkLXmdXef5PYbj1JJxTU0G8cq7n7Xd6GqCukXCJnjqQJ8FqhVQexCCLyPgpnDcIP145v00z79QUplK164cJlIxWipUN4FpRVXM+xFbI1HQTogicO1sUEawHvP9uYW3lv29yzODrnhaMZtp7a4tLvLwtZsbCWMkx52DnlVMsvneOGoXU1VL3C+ChVaXaLwxAqUN2hnSGIYZDHDXoIWIAKhG+HaAT7YGffpiwy85oP/z4eZLhYsCosnpigM1oSExGMQMsCB164U7F0r0RHEiWPz9Alufe3duBZTx+IbhligRGqsdx27RMiVgCpbM/vV+z8cRoJ0ganipEB6iXJBqRLXkC5WKvWX2jTaSll4cMrj2p3bLdkuq4f1LlgLNQVHCwW3/QKlRQfftNAshKCOCpaQha2xUmNNwemdAbdsSW48mrK5XjFOJGmikUJTe4kVKiSaLc7gm2glX7z5/fseL5sA35Vb133YkuUF916E4QbRcM6vG1ZqXyfsD/5Qk1X6JaQWHgfXM2sO787X7eheruzsoUm0pE21eP2Lq4rrMwPfwUwrrw2d202noS4Cj73D9pWkrAMN0lpLr5d1DeHVc4+iqJPuDb/3yChq/l6N9QFqKKsw+9o2sdoKQscaoSO8F40UcBCF6vWCFHFRFHjv6Y+G2LwkVRHWWhZ1CWlEb9BHRhoVR6yvb5KmKZEXbB05ymA0ZjAaBhMSCTunjqCimPF4gyM7O8wm17j5rnswRY1UMfHVnLMf+zgnT92Ccgq1O8WXNSau8cdvQtx1F+rqPvKFiwE3XUtYDAeI4RYqHvDs/feB1sT9IeP+Grmo6A8H4C3UOdLWFFPDpWuWk5tw7osPYYsCbwxKLD3t26yvG5TxEhOnoMPnIoQnVgorJIu6PGSZp6OIJNIksaYoCqz14C11VeEsmNqhtGDQz5DCUeYTpM7wSrM9SHC15YVzB8gU1rcTfBmoq3UVHIuEihonp3C2xjhKYwMfvun/lMaSVzWVddTOY1aUFdM0RYiaVBYgPG95y2uorMGI4CmQ9XoMBoMA+c1m7O9N2ds7oN/POLqz1cA2hqTfY7C5ifVhTZmqxpMQctwq/OviF933UrxUEGvTscMBu63MVyvu9pp0Xw1G30b0F8GwbtlsRYqgHPkSRwPld0OVh9pz1zNcVph3bZbfa8xhZJQxLxyL3GG8JlUpm6lmPIxxwiCEA9+ImDUxXXmPcn7lXL/842WCwYdSChswLykkDoegLSUdyjfyQJ3JdeDECxkumoBOOTI8YyXoidYyzHa895C9exCyyWSCQiW012ulHKPtqC/1aUIAtY1t32Es0SFQaHyXZYcGK94tF3S7IJXAWzCmamAbhXEWbx29NMPZ0EtwVoQstTn3fDYlihXGhMze1HXI3FWw1IuSFOMlKtZI5ZEWkn6PvKwZjdaYzg4QtQ2yDsaTxhmRF5SVQQhFnCR4NNbUxLHuRKziLCaKEhZFSapD09XhiXVEP06ZVwQYSDcmxUIwWutx5hmLGo2xheHmW29hOjvg5PF1BrXiSi/hpte/hacvXeTOt3wb9aSimE1Z2znC1laP6PSdKCthuIVXhsxY/CAmujyjKvaJd8bkUY8svQmhLvD6172N+x7+OL/5mz/NYDzkxBvfip9KemspxSLnhs0ex3c22fvMF/FZBpVnMFS88m3fwf6FL+DrGtYslVPEPgraF14FPD6MeVKKmEin3HTbaT730MOkChKhOL875ejakLXYUdUCrQRWaxSCo+MxVw4O2NraINK+gwONK8FqBqMMaz2T/TlpGuiqx7bXAZguShZ5QVCJh0VZIqVkJPoBplAgo5B4BLmBOa4wIUPEd+taIfB5hdaKWMQIDHEW8+Y7djjydW/h7W++CacCDNfLwkZ1+epl8mJOlmXsHDuKMRVFUeHcAms9SdInn+5z8pUnefBfG1SmkV7hrQ9DTUKF+1lWgQ/fbJI08EZrduGlwFqHbCmSrpEvkQSrPi+wIsAWUigEAu+ClLBrMPY29kovGpnrwHQxLqxf51p2W8Dq2+FKRJgkRQZpYaeWujbCy3C6yoXGfwUIBcKjROjnIQXSmqCsWVoWBG6/tCWRamKPdxQOhn3PuWt1GA5rr00Xd+DFOMCXf7xMMvgmUDfDZQ6H9kHeNwTP0ElvKYn4CO8V3kmcXQbs9ngRJt1AKS2MsgqtBGOxFTGy67L6F/FmgVYoafX9Vo/w/WGcHee7pq9gOQnbSiCsvo4Qgki1Zg/N5uRtkBptjTWSFI/svg9wTjPinCRULkAA0vmAYzYLqaoq5nkRtqDxADnIqCOJyyL26xwpUmxpQdYYl+MsaNVDoDC1I5IRZVkyHA6pPcRpRl1bkIrJfEFZlqS9jNF4LUA9ArJejyPHdgKWXxuSJOHa1T02t29ipmJu3LmRk6+4g97ROzH7F0AIlHfM9i+QjLeRRUW13sdtbyLSLfx4C392l8V4RLyr8DNH9uwLVG6Cjx1PPPQEt7/5rQx6Qx7844+gowRfG9aHI7zyeAXaOfZzwWRuUVFGlhDck4oCVdUUVU0sVSjnm+pNIkKp5S2pBEvEMEkQBSRpD5lEYGoOZlOQUcd0ggDn9ft9hr0+B/uzYAojLToOLBPQaCVQSpD2Eub5ggpJHMfEUUQWR2ysj4m1pMoN81lJVRoOphOsdHjTZIHegTX00z694Yg0icgiTaJ0NyXpnKUsS+Z5RW08Xqb4KGZzfAxXKfLco53E2JqizIm05tjOCTbWtzDGdFo4sqlapQgJQJaFBEQ3A3LdvbOSiHZJk1yZD2nX+Eo12t6bh+5FAZEXqIZ9ZhogbTn46Lv5VN/0yJz1S9nwFZu+tuJuD8VSY77r5V2X/YeeVeOz7C2rZh9h86DpkYkOMWgrjvY1jTGkadpNmf9VHy+TAC86qtNqQBVCNPKgQS5USocQNgxHyJrQPrc4ZBOow5ixaUaPu9cQYbG0GYyUcrnYCWPVLTbfndHKJoFY+rAuj6UDVQe9dBDPcmG2bk+iUf3zrllIQoFQOBNG011jS2a9Qbrw/qHZWSOURMuwaRjT/Kxp6EoZgnxtDM4F2zztw7BUbUpq78hd85i6ZDjshww7TrDzEgpLikLmNSOVEClLnGhsLVEiRaeS2ufsHuyzsbERhp6EZHFwgBdQLHLSOBh8CBX044WKcEhG62O8FCwKw/qRYwhg1B9w+fJV7rjtFUx3DyimEyYvPIqzCnvwGB/+1+9ncvkMk3yPsw98Fil7yMWC+KDA7M+oE4+YHqBuu4dMDOENt+OPHoPTO/CpjzL7/U/whne/mxtPvor1jU0eOfN5mC2YFSWTvX02NkakccK8Krj11BqpLtifXeXtr72Tioj3//wvcvlLj5BYB+U8NAupcb7E+RIhA32uBmTsWExypHJI4VFJyvZwgPeevUVNJAN84WuDVoq6LlkbheGoK1dnFLamthVaxSgZhqHwwfO1Nxwwn+fsT2fMZjP6acIwiTi2vcapnQ221nvEWjJZlLxwccLV6YJFFXx3A8Zfo/D04sCPH2Qpa6Mho8GQLA3c6+C16jmYl1yeG37mR3+O+x45SzmbUBgVtFWGQ0ajUWCJNC5SWsedf3IL2zklQoPeBggvioMhTzuNKQl4ufe2gz7ahKd2gVffctm7XpZsWGjthiAcpjH3UD5ICfcaSbI2228HJoVYbhwtBbK9LTVtAJZIK4Ky48qm0kFxLnwtadXNvQ6HegariVj7WCFEN7gVfuVCHDOeQIGSuOuSyb+K42UC0fhu8ux66z5EaARJEWQ2QwYsGp56+xga2uDhD/36LNsSsmjvHQYQQgYxMy/wvtnl21qpkYVbbfzIlf8vX781zaUxCGmwM9Hs6r6lTAYDDVYwQwClwiK31qN0tPR9VWFcOooC5h4pSaxj6romjlO8c0RJuEmtcygVLqW1gU+Ld/TTAc65wJVXGq0VzlSsra2TF8HcwTpDbW1YCUrgakmaxnimqMihZIz1gqLcp3aWKI2o65rR+pi9vT2iWKCUZD6fsT7epMoLitk0lK5Gc2xrh/3ZHOqcfDKhjjSvfvVdjLd38Eojk4hnv/AUg8f+hOLMee586zfx4P2f4dh4h/VTt1KLPVyaEhUFynt8eYC/XOKqF5CRAlfgNnaw8wP06+9lXSvElSvg4cjGNgeLA37vA79EdPxGdicz4jOXuPGWk6wPK44e2STWCT/wt97Fz/78+/n6N97BW9/9Th547EG+7thxzNoIPSRgta2khQ3XO756gUvPX0CkEuWCvoryFYU1jOKMS3vXGMY7CBUCiPe+a6rubA+YzUsO9gqGowEyMuArPDF1aUgzjXCWzWHG/qICKdlfFERSkCUpChVgkAH0ewlZv8ezZy8zme0x6aUMBz16sQzBVUXYMgwnlS7w0OMo6L0PBhEgKE1FVAnefe8p/uVP/Rr/9P/4YZLYHNIyCjIFtquIBa2EtiCOY+Z1zcHujMGoj61NR0t0ziEO3YfqEGYd7oGGYtxk2G1g7KSB7ZIn3zp9LE20JV74TgYhuFd1xEPaOZjQR3tplp4Xga/iWPWdePHhXHBbC43jQA+NhAsuaG7pj1s7i22w/QAdS7TQ1BgEoklAGxr1Vw6z/4XHyyaDRwRczIftFqPCF4RSR/kVeiIGCJrnQrQNI4JipDu8eFaP1cyg3UhsM/naBfLm/VePwwF9+bNVqOb636/+rGUWtF2UsOOHnb3VohFKdhBS2/C0dkmTMi401bTW1HXd/dtVKc2CaRt8vsk4gmtN2Nh0Y0VmqjJ83taBhUhpZEMDzAYhw2+nFouiQDjPeG0jvL6OEVKzWBQoFVGUNVJF9AcjJpMZZZU3jbvQ8L22t4u1jitXriC8JdEapWAxnzIQMUc314mymGefuMhzVy5RSMHOydMcTK6ytXEEIyW6tAhvgm/o1QXEEiLLrA/uyBpohzYGOXNUl/fYf/Isk3OXUP0+fZnwwIOf4ZkvPkxZe3TaY23rKLEesr05YPfqnPs+/yB//pTmv/qeb2atn3L6ppuZHOwh8xKsxVuLMzW+LhHFATLfJ790AWdq8oMDqiJHaoWxQZe/LEtGWcLuvGhUB0PiUpk6XA8Uo2EfYwzT2by5TlEIIJEOE5sqQkWaYS8DHKO1NaI0YT6bkJemu7be1Ex3dxn3U7I4oigqZvOSsnKUtccYRxyn9Pt90jhBKijKknm+YD5fMMsXwaBCRyD77PQ8lXXEKrCsfKMh3zbvW8/RoiiaZEMjhMcZz2R/ymi8hq3azSCQEroG9cqUMLAMvHZZcbcsso4GTODCuwZ8scJ3XhESiXLiEAQkvUB1wn8+TMi2RiDS45qKooVNvDgMyYA85PO6er+3RIhltb7SsO1OQAR/XC+biiUE9FZfR3oaS8WXjlH/oY+XSQZP2DulDDpCHmRjsWdUCOnSCZSXOGnAJ2Hn9jWCGPX/MffmwZamd33f51ne7Wx36X2Znp4ZzUij0WLJSEjIsgSSiAHHQPCCQzBgY2wD8UYqzh8xlarYjmPHdkwWDBiq7MJ2iMuOjQ0EkIQFsoRYRvvsmrV7eu9771nf5Vnyx+95zzndGoyIoGreqtP39rlnP+/ze37Ld9FC6vBpONoz0pI714bc0GfUabCilKhnpDMN2OqDa7O5WoVeKoneAAQgKo+J2brnHoJKWZpKvUW1VntUGKSFmzDkxqyNQ9AmbVReMhSzUagMIQg8sXP4TkrwPFd0voZoRUdDi26Mcx0heLIsx6BoXEP/wegIbRKNWq1WlOUAk+XErsa1HZPJgMWyZrmcC6mqkdeZVwU6s1SlwTU1RkeIio6WLBqC0cwPjiDLGFYjWhxN51g6x8A5YiaktDxT2NGE42eG3J41vOWBN3P00lM89Ia34t/6Wv7F//WLmHrGLp6Xrl3iwumTdNpSrgoUDaxq/EBDNyW77x4OfvIjDE8NiXZCLBbw/v+M9nO/jj27i10e8NSnb3D61IOslnNuf/oZPvmpDzMsjjFvD3n8c59n78QOD509xUPfdoZ//wufoqha7r1wlq5pOX38FNeu3mC5ajiRa8wgx+oIjcPdvE0XPPnOmImac+mll3hxOuf46QG5GYKOrDLN/qDi6q1DZquce09P0FGyZu89rTcUSrG/UzJddkyXDms1kyrHtx3ey3kTukhuNFVmObp1nVXbsTvexVpYLUQ8bDwaAdB0NfuTfW4cTJkvV7y8rNFaM6wMe+Mh1iaWdGbJbMCYESjZKDofqV3Hsok8cOost4+WjMcZNkC3aumm3XrWU1XCyRiPx6xWK7rOo3XOqDKsiFR7J2hevE5pDZGwCWRRJ2E+v15rUhELkYzUygzrFofGGYX20tZUyhCUZL799EyqYYVzSUQwijk4USQLBLqxGWISe7ijJ+r+9kgFppKelEq6tVsa8DIVjPhaeB1zpVFpA2r7JA5RFhV11LgWQotEYtTEEAi6wFhQwfG6i8f5zHOHEF8Z5v27dbxqAnx/qJiQNFHhDOhAkuQMmKjW2HT6Ek3fKfzfX3yM2LSzOkFEYRHKMn7Tn/uS2mCp/SOnST/G6cu7flMw/Xm7Ljl7JE4IARdiYqv2pgwqyQ/Iffrs3doMH7uk4lisy+OeACVoFovNc4HZOUeRbQbKPRFJKTmpJBOXUtu5wGBQ0kWpCPxqgbGi1Ne0rUgSh44sy+k62VhUMg8OXSAqw8q1VNUQ7SPkkbaeU+YFKnQEOnSA0XjCcrmkXawYjEfo1Jo4e/IEg6JksnuSmzeuURWB5y89jY45DoP3lg/+ws/w8OsfoD7cp6p2cKbBmgG0GtNBdnafL/y7X+KB978Zju9wsOy4vjjgIhr1+vN8+Jc+R3fzWU7fbDn77nehgJefeYZzasgnL91mf/8sX3jhJd42yTmaHzF7uWUxn/M1b394rXUSQmA8Hkvf+fYRZlXStjW+aVEkslfb0q5qrt08QhshozlabLQMC1g6x7GdCbfmC1qnsaojS4pJMQW9YTUiUjNb1ZTlBJIGkEukMpNZsiLDxgyUouwEBaZUYLwzoWtaVssGYxVFnlM3Lft7O+S5aMlHpXFeUdctOjqK0QCVGVQXiWuiHKigyTOHDzWdz8htQ55bRqPRWpUyBNE+6rpGoJhNQ/ARa3PqekXKU7BaMltrNV0QI51+kUnmu6W5r2RJ9YF0jUST8vOLSI4xRnLsesAalcbryJogu660v4Q1vXV47e4gYMWkJkmahUnFwLoK7weyX0Su6mPCduhI70WySkfnInkmQ+i1cM7v4fGqCfBrFnLqozstLDaQMssCHo8KOahOdkmVye/BrIkTd5CIEnzKEYkhEpN5R1QJfhk3H8DdKJyN1KmccJIb3C1t0J+sUs5qI0O1LJMHj69Q6m0/Rz8kda5duwopBUZnqUKJ695tm2z5VMrqCcKUG1QVMSTiTJHTNIJfJkq2r42hKCpcEL2bxaph79hxyfxDh80ylBHD77auycuKoijofCQbVCxnc6qqoA6W3Gi6lcfGmnI8BGA03MVay42XrzLKMqq84NqNq0xGY+yo4vr16wzKnPl8zn4Jy+kRO7vnycKK6wc1p0+X7J44zsXTx6jKHW4f1PzmC0d83QdKmrggdztQdLQOsAV+tM9g/yI/8Mf+W86cLnnu6g2GD+9x3g+59fQL/OG/+md45IF38MQXPsr4/gfIzj2E/vmfpFQGrQe01Dz8wDmuXr9JYAJE3v6G1/FHv+UbpL2QNPfzzJBlhs7XhEWLzQzZToVX0HWO1csHLOaHXJ4uOH1ywmzVMhpY6oUni56DRc3pyYRT44pLV26ztz9kr5DvoKlnoAsMhr2RsFwPbt0mTsaE4BgNhthMNvOmjWTWkhuLNYbFsma2XHDs2DFpNVqDV9B2EmyD81SZZXzmOG3bSmYaIk3jWMxbTFaQGWhWS3wQA2+tcnRhKKmYoTh3/CxNt2I+l3PdGEVRFBijidGSZYbpdCoJR+vYP7ZH23XEEFjNF4m2z1qGN+Ih6sTUVInHImtbqPl3Idf6nynD1snrWANOa0QtMiTF0yhChUmDft1D7wecoQ+y6TGVFtkTAjG1TkzYQtEEWbfBbHxbtdQFtAQKo9e5ntiDJlnyu2JZSJIMCiMwShXAR6w1tF1Hbgp2S8Nh/Xsb5F81AT4ZYN0xCIlxk+EC8k2EJOwVU58t9KXenTupCeDTu8sC6z6c3i69VOpvyH/ugEXdNYuRk2Rt2LG5z/rvanO7DXkpCVcFl0rAfkPon0c0rHurtV46wEeRDhgkOVrpued0nUPrmPRjWopCggNR+t19O6iXPpDbOQyarusYDyqyQqqLznmqQtPUjbSjjDyGirCcL1BoLJbJZMLs6JD9k+doVjPG4yEudLRtjVGWLnjGxnLxwQc4vH1AWDZ0ixX5ZJcr166zMxpjjaJpGnToGO+MqQaGZnXEqVNnmAw8wVrC9CbTo458uM/F11xkdWMBF6CdNBSrirwo6IzFBDjz7jfytj/xHs7tjHnTdMmbxqfZvWePg6e/wOTiBW7bmtx7/DAnXr9EUe5w+eASebZDDBrlYFQN8CVE7Xno/vPs7e2Q5yXeBYLr0NYSo7CGTcrcfBD4rnVwfTrncHqDmBsybTk8mjMudlC5xa8aTuzsoQ3oWJEXNYcHcyanxmgvQT64iNJi7lIUGXXrBQXWeTrvKG22+e4T7NDmGZPJhGJQcfXqVfb29mR+hKFxDmsFR+6cY5BJwlCoipUNlEVFhSJ0jhWGvNRAb0yjCUr6wqvpElsKD6Isy5QwhbXRzGw2o2kaikISgX5W47xHo1kua6zJZW0ov0m4tFQNX4xGSwRErTYM7P/EZNBEadmIjoz01bXfaFD1YIt4Vzx4paOfkXmtk0JkACMtHH2XxIGs542C5fZFKVnH29dtVy0SKQzGeDonmlFN23L2zCmOnr/8e9qLf9UEeL2NS42KzAWcitggWW1nlJSqOqKCSdNzx1rCNyqUTtIGaLH+6oeqqb9nUSifsLJrU470lHchbuQPdyJnNBKslb2z5PTRrQebPbwxz3O03kC+8jzH+a1hblpYWIHYCQEjEEIrlnxqw2SV4akiScCs20vL1QprZVPQ1qCRrC+ETRVjraVdrhiMd1ksVuzs7OBdRwyRuolrdcrMZizrFVVWkec5q3rBYnlElhUcO3GS+ewAk2cw0ISVYmAqohG7wKwQQbQ2NgwHY84cv5cIHDt9klVdY7Oc8aiiOH4MPTlOnpfcnM+49Pivcf70CZqXb6BNRLVgfc3jv/xRbu6f5uTZ89xTTYhjUDGgnSXqXaLO+BP/5bcz+/CnyP/Qm7BDRag6znzDu5hfe5Hr/+DfcK4cM94b0x0UdCbDUXHubMkTz97E7Y4JwxUnxpHi/W/kHbsPUo7G5DaTkt+YJPnsmU7nksFmOT44fN3Sti03Zrf4Dx/+GJiMXBkuL6foA83JyRBVlDTNghuzJcf29zm1M2DROA5rz05pKWyJysTXlE4xqMQL9cbtI6qqQllD7TwmSpus7TqyVJ1pLdIBJ04cI4TAbLZkMBgxHFbUdU1uLIXNaOuW+XyOJ1JWA5wL3FyuxNc4k/Miy2xKAiJGWVaxQ7WRT33+BY7vjThzxpMXGXkuMhXWWopCevCSwZvEzhXEeqYN89kRmTGEJCGyycaVzIx0wJAQZX2LQrNmnHs2rRmfZmjrx1DQKtHd0SFiYoRO4ZIMMQEx1I795hnWiJ2+9bMWCwySTEralYR51/aC4gHbz+qkXaTR3mGIOCX9f/HwlflB7yC33hQSO1zeYq+gFVP7s8NYxfjYCPNShnPtbxkXv9zjVRLgN25MkCbWSkgNnZFgbL2UPdoITxQ0qC5BJvV6oq1TDz8YRRZk0OqVvNGg0t3UhtRgXwE61ZMvtts9crKkB5BnSmNX0m3ky1QRTCYfay9A1ot5KS16MT3UUyVZVO9aFIayzIhRYFf9Cd9n4V0nYlZFUazJG7bMcU1LlmkReEqCYi5h6lerFUopyqJYk1PatkVbS5kX1K7FOcdkMhHY5HAEWPGFtEK1V9bw0pWrnDq5jyWnUAaHoRpPuHX7BrkzzEPLuCrRWUnTiH55XpW4+YqyKFHWYC1Mdvdp8jHLVUPrDa6OPP/sDV73hgs0xnDPmZLLt2r2T5zk0kvP8KnPfZazp+8nFsdF8rYy1KqjzCzNxDB539vpPv4oEUXedKADYXmDN++dY3raQF1z5eg2eWn43Bfm7LxmzPjEAJqG+87fx7Oz27zlwFFcGDBoK0whPqbSZitkcOcDrotQd0TnqX3LsmuYLg54+gvP4zowVnw1D5ZLzk3G1FE0T3Z2drl9eIsze7sMSs2l6zV5UOQDSzTSH1SdSu01zWAwYDafU1TCYs2zHJfgiTqz63PSGLM2wqmqiqOjA1SYkGfZej0VmWVw/AQ35yu6WgLKiVPHxK+37TBJYgLyfZnjAAAgAElEQVRgtayJtGQDw9lTE168fIN779knz3PKQoy3nduYU/QoK63tGjppc4MO0HUNVmWCcNuCMvdM8HX/fQsqGVKy5dnCkMeYzDNCaqvKOzNp5CaonOTvFsMdJiDbndE14oWEpdgk1+vD66RPlRRqQwhrGXKBRG4Y7a8UK/rXHtNccHseIDcXhzlrNN6JAF23bev5e3i8SgK80IPVFrEhpt6aiQrthORgNPQU4Rg7NJoQfa9aAQgkSkWSRrNFAXnS3YgKgVX1WbTetHaU6tUCZRoeU3axrRIZEt5dRIdImYIWjfqk+S6OOXatuNiXuNpkoguDEqlik8hRQWOsDCFb14LSWNMPcDzC3gWlJPhrIiE6stzi2gZrLCpCZg1tF6jrRgxAqsFaUM3FiPItWVmxaleM7ZhMG5w2RAXLVQtEQuPxumYwGGJMSdu2FHj2hkOC1xSTgjy3VFEGWePxmNVyyk45JgRR+7M2o6oqrl27xu7ehLpe0MxbDl9+mRefeJTJ7ph8eJJnXrrEuWrBW9/+PsrdSGgVn31uxTd+01fz9GNP8fV/4o9w4sHX89gXnuL1D2f44gQETTZfgAtkuiTsgH7/2wlK4Q5vY2YLqngRM4gMXrzG7aef5EM/9mNcunqN4swJDuuG2Eb2hoqjGzf4e//9X6db1uztnyBWCqU0WdIRV1onlx6FzuS77UJktWqYTadcv3SLT3/i82Q13BxbBkSaJrJKELhCD/C+Y2c8IURDZg2n9nMOpzMGVUloPXmeEUxCVoXA/mTIeFBx7eYtEXAbD9kdDcmsRUWNt9C0LcYAQYL97qhiVBYczKYczqZYU2GtZX93jHMtoxxM0i8qlCJ0HmM8znU0TlqU5ShnVI2YHc5ZdA3HVU47W1EPhZBTVtkattt1PiUTAe8FKmutxURpfSoD2itqZeRcbjvavMB4R4wLVMiJKQOWuZasAUjqjqonHYoZToiCgpP5m0XHgF9zXMWsUyRGAkqDT2tUZnpRbASjtHRSl5We6wpsNs24tVZJsSjpyCsFUQWWOnCSAXlUON+R6YJlbDAu4oxAiCM2QXoTMkgh87wYCFF8HHz0YBQqNNx7Yo/nbtwketAq9OKYac1/MfT6d3q8SnDwqUTjzh3ybupwQNAxQvgTg5B+p90a26x3zqh6lmrvcbjxe9xmra4VJrfaNf0lpMt2b11u49eONT0G/YulEBLaRt3pQNNDIOP67xtcPtzZ6+s3GKFFO+kFx8TmMxuZhi5RoEXKVdM0NcbIidx2DdqKRnxhpSUzX80hKnKbUZZl0r8WFE/bOqHbG42tCsb7uwyGJV3rmc8cy2VN3RxxdHRAXdesmpq6aUQS1wsN/uTJk4zGYwbDIc7NyUrL9Ru3ufziNXYqw6D0vOXt78KUkV/8l/8vw8kF7n37m/n8o59iVXsuvXCdWy+8wAtXn+Ozjz+KbTp026EyKZmjDsRcYawlC6BGJX5/gj6zR6sisap44uO/zrybsnKaZ1+4wan943TtgmAK7nvgfo7tn2CxWMn35pycO2I7JOdQREwczOa7cc7TrmquXrlBu4LWi075qdPHCSow7VppW+neBUhTe4/SliLTVEXOraMjXNJjN1YyxBAlG81tRm40oWvpOs9svkzCYltWkLDmU3Qu0DnH7mjM/s4u3nvmixWXb9xi2rR0EdoYidbiQqRpOhYzWK4UKmTEqOnqjitXrtB1HbvjEYvDqbQRknx1jFJFiP2fnGdZlqXBqxFOhm9lCNt4gurIfYfpwBtF7gSKaUMv0pdkjhG3tBjvXHOyntUd/1dh0165G6set6qCNZu1F5pZc2RkA1ERdAxScd+l1njn+t4QGGPCzpfe0+gV89ChswGuzsmMwhcW04p+lKsb0MJR3V7DRguKLTgvNJ4WcGLuI1VFkA1IW3kP8GUHd/gSMnil1D3APwVOI/XVj8YY/6FSah/4KeAi8Dzwx2OMB0o+pX8IfD2wBL4zxvjol/Ji1l/uFlGnj9w+KnIl7ZgYBS4uG79JC5Ek8ytDE6JkAUptaUJ4wbBHpdYqlZJnCz5XRMmUAOq1vmPQGuKW3rNOipUqTcyJOL8hJxnESzXPTQr4Djmx5XxTWoEyaLUhX1lrJcNPm0Y/LF3LBKd2jeCObVIQFObqcFBSt/XWohSyU9vICZrZnM4HikGBa1qarqMcVCwXonzYrGqyXNO1gcwLmSWvRM89ZIFFsyAoBLapRRmwWTnKIiOGnBg9y+WMGBWT0Q7WWpqm4fbhAXt7e4wGZ7h96RZ5lXE4n/MrH/55zp+7yC/94gfZPXGKvbMnOXtsl2WIHNghH3jfH+Cqt3zmyWcIt2bceOYxrn/u87zjA1/H5OyDkK9Q+3vo3V3aoiAfZoTaEoceO12iDlaUZ05y6ZknODbUfPjZloW1vPzSTWIw/Onv+gu8411vx1rLpBxIPzovcZ2/4xwUSQuT2MJCy18sFjSu4yf+7QfJzpzk6uXr7NewnNWMi4KDwyNUhGNVKWim4JlNF+Aio1IxyC2HruPGwRGnju3hmwaFQVkZVhIiJ47v07SOo/kCa8fgHUqbFExzXOJAaK2xWsxYVLTkVc7pkQxGF/MG5zxHs5nAdhVrvZiiKIjeM10ssJkWSYLBEBUNt+ZTXn70Md70lvuJ0dO5SFGO1pVpXdfrRKbruqRumlo3yxmT/T3iao41ljYECCPatsGojqAzghe2aD+vYotkuM0O34o/64uOCq9jWq/xrvv0QUTan5F4V8KW4L5m0xYxPllrqlfQvemrdDa3r4NiErTIj7SeUC05mGYUOlCMcmzd0I4tZcgSqUv0hpSC6IXMqAi4tiMfTbi5mPHSpQNZ72tTka365LeQIP+dHF9KBu+AH4gxPgy8A/g+pdTrgf8O+FCM8UHgQ+n/AF8HPJgu3wP88G//FHftVFsA2G1J4LUSXXrpPkpGvqEt970yaT30+hHwyruhvuuqu424t+/SS/j2pI2+0RfiJrD3J23orfNgnd2v31rfHkoIBkkYN96TPm1CfSWg0oTfe5Et6MvjPntDaRarZRoMynYlUL+w3hhc68lTAMnKIg1vlUgV+A1xK8ukFG/bluAEkZNlGWU5oCxLmqZDq1ICTSYLfHd3F6JnPByhESTOarVitVoxHI5FR36UM5tNqcg4d+wip+85y/nXnOOee47xxjeeZnVjxVPPPUdbZBy2K55+8RrF7jEuXLiXRz/9CT72H3+dn/7pf8MP/49/g9n0Gu30KtFG2k6cr1onej15UcCkolnVUMDzX3iKYndMdWrC/WeO85r7jvPA/pi3/r43Q9okh4Nxgp2mucvWYG77u4tRKieVqPmPX5sSBhUBw9wF6rolz0tMzFjOFvg0a9HKMqxKZrMZ0ViUjoyGg0Q889i+1x/VeljeORmuVlWVzg+F8xHvxGkos8X6HKnrJEPglxij6NqIUTlFrtnfH3D82D5a6zXipWkabt9cMD2UmY4MTyXBWSxrms7hXWQ4GlEUBXmeE0JgOp0yn8/X59QajgvUtZx/B7MVt5jwoWdm/PwzLR96ac6/e+k53KREa8ucxD9R0lfvq+O0MtYZ790eDVsrdA1/3KzRV85y79aV6m/bV9Y9y1a98t3v2HQ2MSCgcCgfWQGfuQ6rRcdRHTi81bIsc0wbCSYXwtZaRA2MLbEYTMwo84qjg0POnTpF62QD6dehrPPsdyW4w5eQwccYrwBX0u8zpdTjwDngG4H3ppv9E+A/AH8tXf9Po3ySv6qU2lVKnUmP8588lDKSHd+FbIkpVRbi06aHrgHrBTEjPqxmUxYpoSzbNNyJKtyBiNmAl5KgWYz0+jExRhEa0neeGL08gHzwChWlhA0hYI0h+oDNzLpN1BOTsuxO5ToQ5qnSvYTxpidojFicWWvonMNYDyiszlgsxIJPcO6SnVtr1/IEmxNCysvgWrRRaKNEJqBMdnFZyXLRUA0HYte2WDCZjFDK0MaOcljifYvrpFVTFBW74xG3bh2IM1NTE71hNBrx0kuXOX3mOEe3b2HNgOn8SMSyRgWr5ZzgG25efooPfvBneM8j53nq8cf4I9/8tYyO3cOZfM4vfeyXOfPI2+gOr/C6MwOe/PiCD//sz/G1+wMef/w5qmKELz2q0ey/9iL/xz/8n3jve76O0W9+hke++qtRFwqs8zSLqUAWyRm98X5++Yd+lEfe+zbM4pC//YM/SLWn+dyvf4pmoZjsn4bdDJqWnb1d2tihWoexQiiKMVKvliIfoQTR5JzDe8/h0RE3rl+ljfDo85dBeS5ND3jdmfu4NJ1hnKIoSm4vZuzlIzCGwdCjsh2mzjMuCwof0Xu7XL91yCrPOHViH53lhE48bGPUtN4xyOT1LOoVVTVEGeE+iBtUXA/dG+fJVI5rHAZH2zoyXRAaQ557Tp08RoyK5WyOQqN2exP5hFzpHF3rsGaIzQoqFRlVeZJ9lsx9MBitq1HZMLKEpLHiFbDs+MITz3Dm4j38zIc+jcojylY49viXH36WbLDHH32dolu3IrQAHqIWfZ/tIel/qjXhUsWb+ugxgtO9VIcWzDmpat96nJBQLTaI325QQoAkJYL98/aJYki9+hA9YtRjyJxi5T15axk+fD8/8lfezc758/zAn/qbHOmcG7fm7BSB05MjiiJp4UdP1Ipnnr/JgWedGCoVefb6EygdMYjDoHPSogm+QysoMs2q+/KC/O9oyKqUugi8BfgEcKoP2jHGK0qpk+lm54CXtu52KV13R4BXSn0PkuFTGJVUF4OwxxLFzZokJBSF2Wpc0qvooU6IkbBAnCQoayXBTAs0deOSgkbrjeojJLxtlH6fjRp8xCtRttvsvkJOUEoRvbDQlJYsFxUxWDRZetw+65O6o+lqbG4I6ym8F0pzNJvsMKh+IgSwFjzrOqGHy3WKqKUHb+wQ5z2ZtRjFOtP23mON4KqNKcBoXPTgBTYacxk8KyIB8cdsuxlFMUSbCDHQtAtMJtZ61aiiXdQUuwPyXAvefVCRG40pSoqiYL44Ym9/zGLZUo52yHLAZ2itKHRGm8v84yMf/Qi72nP50lV2jo958bmrXCh2+PiLT3DlZcXJB6aUp/cIruDS4ohhVvHCf/wUD7zzbQwC/NonP8u4mdEsb1E0nuPHhjz53DWu/sy/5/3f8M3o3QlVlmYeYcGH/9bf4ZnnP8fe+T3uuXgv9ZXPcuGd34z66K+idoYwNviswnjBoKMMXd1RGsGwa62FHNc5Mh3AKVZ+StfAytV87GOP8pZzBV9xoeSwG/PRJy+h88CJQc6Vrsb6QNlEuhEU3q/ZizdvHFGdOEZmMirrKIylbkW217qOXBmssokYY+liQ3Cyic8OD2A8FhVIFdFlUiLtHIUxdHjJ/htP7Dwxi7ShIbMZne8k+aiyRMsTdEvbOhlANhBjjs5XmJBhq4ZYCqSvbxdCILNCqHIucHg4x5iM0UgqINdpSj3k3IMn6YKGJmKaOR6HzTK6dsUq209EokCmciKenMBKbeS8AVwQrXa7pQgbtaKnOwK4FMhjj24LSXBsa43L+kpQZqnzRVo5Csxyo0VjpAceIvTzgOTqIN0ASQgXxrEbLU3lePRXH+c3fvVJLAGd5zRxRhnBBIfKJ0Sj8M4RMBBalDEo72WtkUDYscMH0aQyGgweFwVdZZSiioHV7yRAv8LxJQd4pdQI+FfAX44xTu+GC23f9BWu+6ItOcb4o8CPAowKHfusWhAMEljjFoIFSLtq+uhTUIzRo1Pm3Ss3aq1kEBc9PdtUodaBtn+Z23ZdXzxE7cW7kiiZ95g0LA1e6PxKCw6zL696PZneOGTbEUYpQcLcUWGGKIYfCR6mjcDtlPPk1uI6l8y3ZSPrlSWVUjR1S17IxtLLGnRdK733thXj5wDDUYVS0NQ1RSlZfjkomS8XQuwxogy4WEpLJSrABRbLmtwWNK1DBwclcraogA8dXllyO8Z1ot1RLyPBlegwJ1ot4lVECq14/nNPcOHESXxsyFxDaG/z9OO/QTf3vOeb3s3Ll69z7sQDXJ1exwxP8swz17h0+fPc/9xz/Off9Z0czpc885uf5uDSDS68/fdx9fnnePtXvJMIPPPkr3Fw8wZVnjE6tUc5qviaP/91/P4XHmHnxFluPX2JF158il/8G3+X+77m/cQuEmMBNoeqwlYVcbEgywo67wg4fOdlBgMsosNExexgSb1c8Zlf+yT/6Kc/zpkdzWO3So7vl+zrCm0KIp7KGtENKivoQBc5NsFaB4OS6zdvcM+ZU2jtOXPqOIvFEbcPFmS5YjKWvr1N51mWVejQCYR2klG3DVlWYJU4dRljsH32GiLNSlpWGNbyuwDBI7ICWYZRitg5US/ttY4sdLbBNSNs2XLwzA1+7Ic+wl/5b95LnufJxcunGY+0D/b397FWWNjed5iqIhtK++h//+f/mmm+Q6Vycmv5vm96J1gYNy1Xp0eMBkOqgaKNivou16IYt230tlFuCu8dPcx404MXuPIa1pxa+HHrfn11rlWSMYiiaKkTVzX2ejAKGV5H1m267Wpi0Fpav8TpEY+cW+BNzuXrNYNhpCwGAsX2DbkSg3vTQ6cBm4xAQjIniiTNLdUHe0QUMDUPUNAZC92Xp1XzJQV4pVSGBPd/FmP81+nqa33rRSl1Brierr8E3LN19/PAy7/NM6z/VcSUwf+WrwW9HnCGFMg3/TKdUDJW6eTyIqJi/YfaP7Kw5+4cQay/zLuGPj2SRdhyYtXbD1N1asXIya/WPcvtjQNSoNdh67VKtkFU6OQiQ0j0aK1ROoj+NgafkAzGmHSSRmxmcK7FZgVNU7O7uyvKj0phEyM2t9JnLgfCLFwtluzs7TKbzRiPx+LKVGmikd5u07VkyuAzjXGBUGSChMiRLLHrmC7mSTqhpSgyVDBoXRGMg1Cj8yG3prc5sX8MpRVPPfEYe5M9dHQY04LJePLpq+zs7fLQ687ymgfv5cT4JL/4oY/ypofOsTOw/MJLU77iYsWigbe95Sv5+V/4IF/xzrfx7Ocf5eyJU2SDCfvnLtDVDbtdx4VT58kfOAN5Du2S7jOfZWe8T1vmHDt3nmOP3M/iyjWee/k6F+55AFVK1h6Mgtyipk5aJE40uwGCa2XxB08bLVpB7Tw//yufx0d4bqp5tq3ZuT3ncKl5oM6wmWZUFhzOFzgKFtMFcRwpMk0ITjZkNcBFhw0Z3i3JTE6WL3FB3LRCVGSZlgE60sprO0dW5Izygi54YucgCZdpZei8k6E8MojFGLyPSe9EoLx5nlOvGpGkSJwIaXIGrDVYSsg74kpx8kTJpz7+G2TZB6SSxKKMSv33hNrqOpyTc7ZrHW23wPuMwQT+8T/+YV58ecyFeyfsDSre/MjbCGqOO15w9vyIxa1rTOe3yTSozApqjA2pqD96xJvSCfkSBUa9vb5C7G2v7xy+bq9pgRenRA2Zfym13ardvkMSIYubtml6NcTc4NsIfkmnM7qm4fxxqYmX9RLnDaoo6bAk+xhZ7zEKG3or/vRhJmn3bRmRCNyYEFmFL1+I7LcdsiZUzI8Dj8cY//7Wn34a+I70+3cA/3br+j+l5HgHcPTb99/lgw4xab4oaZtsB0khH8ilv27zJmTXNXEDh3JxYz69dnTqe/fprjHGtXu71EhysUmDPiRtadLU38eA8x6rTeqqhLVOdp7na7mAfuh75yfdbxYicxzxuNBJW6n/cqMEWqOknZJrI5tYEN3tplkRgls/Rh/w++GZVBwWZaT3T3BE37FYLOX9G2k9mRSsc2vQRk5QH1qGgyIxYWXAa4xZy8HGGOm6jtFoJEOgCK4DlCOyYrmaUuRDrA6c2d9FdR2lVfzmx36F9mhO00RuHXQcHnXcrlteujVnf3CWm4cKm8/45KOfBwODyYD7z5Uot8Lpmv/1f/mb3Ftazr71Dezs7fL6t76Fh9/4JsLYUpzfwzxwGn3/aUEeLBfEbkW2M6Hd2SXbPQUPXIRVzvDBN3Ju/zTlax+gKw26yolKoQZiVhKCI3QtR9NbTBeHrFYz6mZJ5x1dU3N0cEh3+zqffeIF7jHw1844/trYU7oZf+pbv4UbixvEoBiPKrTyLJdL8iqX9khUWJtTWEVVZtw+WDJbLjC6Ii80+7t77O+UNI3j6GjKsm5wwQMO5yM2z1g2okEzm89BG4FdFtVGZjoFibZ1dE7Oy0zJ+2rqWsTB0vda2ZwMDV2HjQpXN9Rdh/cWPYoMizEnj5fYrECbjP39fUajCbu7++ztjRmPKwaDUshSQWGzkma+JM9G6LzjWH6V7/iW+/j2972en/u3P4LLFSf3T/Btf/4vc+41r+dP/pnv5/D2kZihNB0msHZw69fjJuBt2iw9EkZ04VOqq7aq8rv8ILZi2NbvdxrzGLWBJKcd5Y4Wz8awB7xqCAq6aAnpfm2oqDtLlRdkeST6BaVt7nhupQx54lf0USFu7WUGCeymh0dKyOF3Q2fyS0HRvAv4duBrlFKfSpevB/428AGl1NPAB9L/AX4WeBZ4Bvgx4Ht/uyfoiUmm/5laKXqrHBMGsl8PSAIJ4prcyGXAKNThXp+jz7r7zLuf0G8HX7UV7PvN4JWQL33ZaEwiWiV9jt4AoNe/7kvFbQzv2k0X1icq0dJbwfmE5PXpPp2Si9OBaHoqtsGYbPN+euVB59bIFXnJgnDoa9UQ/DoriTEyn8/Xba/c5OuyXiklf8stOSK2FNuWTksv2jUtg8GAxWJBu6pxzjE9OKSuWw4ODhiNRsxmCw5WHYsmsOoCt6cLzly4n8n+gIP5IZPJHnlWYa2iGmquLq7x1FOPcevmEd3KsaPHrOaOQawZ5Za9yZDv/At/mtP3X+TcufO862vfy4n9PSmv85LgFcppiBZTFLS6QzkPexPyE8cJWYG3GexU+NWc3XPncc6T2QqiFj0jZdB5AQiCpUlQyMVszmq+YLZY0LUtymj+yU/9LLaCq8DOruY1JzTDcodbT16ShCIo5oulyAUYafnkmSF46VvLZ24pCsuq9ijtUZSo2JLrgnEpLZq67ag7gdZmWUb0gTLLmQxHjMqKVSM6/e2WlAVakZXFGi3TG1/3Wu5aa/IiI8sszipCromFYRk6WgVWWbK8oV3BZKeEtk6DP8fh0ZTDw0MODw9ZrRraVjwMRIJYpwq2IdrAlctLHnnT2zh5+hj2xIjHf/OXeetrL3L23DE+9NFf5OUrVzh73/0UeYXJM6pisHZj80ThB2hwdwRrfefPrTW7PRzdXtf97+sZXN8u3Uqo5IaKHpff+0v0Cc3dj5lpqZoymxO9S17FDagG5xt8zNAhg64HVfQkLL3Wh5IehRx++2VsvSaTSIPmS4nOv83xpaBoPsor99UB3vcKt4/A9/1OXkQEMHqt1d7T9SUz3/TkYrSoqJJDTJ/de6LVYBReabm9SvBFtvvj8lWvMaZKSFIeiKmnqbUm3wrQ8pyCmImwNiWIPqKNEDZc8NKmURvdmTud4rVoZIQoJFwFxqo1BDIql7IQgzYZvdCRC1JW5rpXstjANBvvqKwhqiDQQOTxyrIQg26jE65esnCiwCaV1pg8E2E772lDS65zuqalGA4IbUfdLBhWu9L7VRl0HUEV6EIzO5iRD3Ks1XinGNgcbRTDnQleQVkO8BZ08GLM0LVkVjE9mLJ3ap/lwW0cmuVccfNoyamTU9qnf4Mrpwb8xe/5k5z5yodxH/owb3nrGxjMjnj+8IhjiytUw3NkNy9zYrfkkx/9Nb7yW78N7zoJ0lVJiB2hXmKzIT7kmJ2SRmsKFwjLFfXsgMXllzn2lndT5gWNMRTR4pQhZDn5iZOEtmN164Cq3CHLWqbzI1QMON8RO/jW//oHOZwHnIbXmpxh3vL6C3u88Q3v5cXPP441Gd53jEdDmqA4uTvg2tXbKCJGe3wMjFQpaKbcUhhN3XgGgww8+FBTDSryQvT6m6YhsyXGKrTNIHZoHcgyQ5ENRJ/ce+a1yAbYIEN1mylcK3IO0WYo5ak7lzDYsj5c3aCUocpzqiyn9p5S5xg3R5c5y/mSc0XO1SsHTHaGDIYFWSa68/P5EucCi8VKEpzkUWrygr2xpe1q3I0jPvuJX+PHf/Jfg4Jv/NZv5rnHn6R8tuJbvvEPsRrs8tZ3vY8XnvkYdZ30cfqed9hAJ5UVnscm4Ypr3glKE5MPk1TTKhlohzSbi2u0TvQi3R1jTJAMgVv2a16nddsnWCgjkaLHzsc+1gRi2xCjQWFxCRthoqVTkUgn6pYmYkIUoFuQdpjNQh8gheuSokNa2eIBEQVRE63Chy3rwi/jeHVIFagNSamHqZl1fzwmGdAep56QJkn2V6HWHqbE3h5PoVSQDJn+y1aw/ttG60In899c9+bIEYy+s0TcvEzZVhLtWZ5TNo9++AOsyUrS5nGb/v1a/MyiUk89hESLT0Faq4BpNZmWnqr26cQiiHWZgVwbdBD9GY1okWfG4roOnUtWX1VVmh0YqWhcRGWarpZBnes68rIgywrmywVZISJIk2rIcjFnvDukXrWU44LFssE2it2dHVauJnpQ1tAYx7FqQld3otlvajSCsNFRs6gVX/VV78bPj5jOZzS6IB+VXL99BXfbs7h0i7/9z/5n3vv7vovXnN/j6Fc63vvWN/LEs7+BP/Vm8vAiP/TD/4oH3/mVfOpXnyOo2/zpv/uTOFOhdUP0ELoG8EQrrvZklqgsBRldN8cOCuLhkmP3vw6XG1SmKFQmwTCAV5YwzNC5Z5gXVGdPorXBTY9YHR7y8sHL3Lp8lRvzwDELe97wDRdb7rtnl7o54ru//wf47j/+DdyzX0G5oHaWncpw+eggoTO0eOpGaJx46Son39lqtcJFx6gaABrvuzVmPc8jR9ND9neHaCRLXq0kMCsV6TqB3+V5TlO3TJsaFx3asGYrR2VwbUP0YU1yskpTWotCEzKFDpG9PMdVFS8/dhDdzoAAACAASURBVJ3x/oDv+h++hywWXLpxCaM9N1XDZDLB2N7bt1tnpFVZMRgMmLc1mc4YVQOUijz00Jt54rEXePbaZf79v/h/+Cs/8JeYLWZM9k5zeO0KX/m1X8fzT38cpT0ubKWqijXD1MDWek0Veuyb1qwRLz1yJm71PVTqfRO3YNdpbfouJW1bYoC9q5tSYvuXKb3m4Kyz63Wmr0T8LvZezzrpxWu88nTBb+SHk+SB7SWSFevNKkYogFaB9tDYNGz1UkX8bhyvGqkCRfoy2WTAcYtF1h+yw26uv3se2xMczBZB6rfqx8FmYNOTXTB3tli20TXrcpD1sP6LXltPb06PTi+uJPfPQGVIbZLJRRm2Hd6VkhPDKSlXpVVD6sluXnMIAbOlGd92DT2ihiiCUL1sgBCg1HoWkRmNJuDcRpa4zIV2Pm9WjPd2WDU1eW5xq4bd4ZCgFdPlAt2JyqcOEdUG5vM5bezIBiXBRXyMTOcLGsRsxOUZ1f4JsknGtZtTfuPTz/LZZ1fEkPOBr30vwxMlX/2O1/DCS4dMrzzNe772bZwcnuGv/+C3819827sYn97hcHpE10ypZzXhxEnZKLWVBYvCWoO2GcoWuNwiuj0RW2XExZJibxfKIS6Ttp2LiUDmnVRl1uCtJaBl2IpUPlU1ZLSzw+eeeIZxYcHDxZFht4KlX9HEmp/6iR9n7/xxbnWBWVOBh6KomF6bcnxnxHS+pKpKyjJf94t7Y2wxrG6Zr2rqrk1SACngeI9G7PO6IHZxPWy27hxNsv/rFUebppPMer7i6GjGYt7QdTIbmoyGjHfGoGVQqjKLHuToxmGyjIPbc2498Rxf8+1fz3f9ne9i0S45am5z/NgxBoMBw+FYzD+0XbcxrRWFya7rWC6XGGXxLnL82G4yCIl8z5/7bq5dvsYf/MD7OXfhXj76y79CiAZi4Pj5C0LaU5vz/m5C0oYHk26zRrbcJdvwJRzbiZ1Y920ev4dF9+9tnQCmtlH/mvqf2wNTrYWdGqMXOYWtwW3fSg6KJAWyOWLcGqym97gWIVeby5d7vDoy+LhFSkiYIaPunIj3LNN+Y9P0wxctVl70dxdrMB2DtEW2TxoNev08KpVLOmXOgrkP3q0fRymVYOrpREhfvrS6NzDOzRfRD4Al19dbJiQxRpQJ8rqVYt0wShKXfVCKKeOwPQmrz/qtBS1UemOMGPu2Lumo+MSe1bhU0oqRiJCs1q2jTHqB/RDYoPDRETvP7KgFNBZFPZ3T+CV6kGFyTRv9Gm8fY5CWj4fhYIe2mRF8ZDb1kA2wwTEcDjmaHwmi5GDJbLHk8596gvv3J3zVW+7n4Xf/Ib7w5OdQ9grve+RP8s6HTvD4Z2/TnDvHT/3zX8HunuCP/+HvwQxz3nz+JFUIvHTziHvuewRuTVHDMbpriBh8txIEki5oo6bAEmqRXGY+hcWcMNyB4YQyWNCFCNHRooN4rXoFOupEHsqkEoySrcXFET/xf/8yzjnaAF/9QMuZ/QkndkrK2Zz9Ew/R3Ph5BmdOcvnyi8yWBcNJQ8zE9erY3g6z6RStYTCQTL0nTe3s7KC1Fo31uqXMhW0cY+/MFbhx/RClFGWZozSUqU/fO3cJEQlOlwVd6HBBqrksyVXUnaMLHYXNMEXOqmspSkM3WzCdBS48cIq/9EN/lmaluf7iZbrZjN1lwfd+/9/jb/7IX0TpQNVl3L59W+YB6fzLsuwOIb5xrXlheomLWGa3Ok4ejyz8iu/7q9/HhXMXiHXN//YP/j4vvnwdXy8Y3HOBW5cPOXXvcequlco8wRj7Nd4PMvt16NN6lWrYb2XYd4EaorrzOrV1m21Rw5D8IZL72jbR0W+pGSfvDnQUIpUxSqCnMXURlGLDzklztuDRUSCcRNCZSXDuTXUPffYeCRqsT7gmeXtfjPD5/3G8KjJ46WPJF6y3d7atXf2OLDzCHZlxMozuN4B+990+BJ/+W7PkglYEs5nS351REGNqpWyOtTfrOuNQ9BToL3qPSqGiJUYDMSeGjBiyO96fUioF/KSYt/VaXddhlOzHzjlBzxR5MoIw60XXuI6iLOk6J5Z7W0OoPtCLpZpdD420gSxZszkb0cNSqoi2w/iI6QKDPKNdrugItIsVHY5Vu6LpHK6LlFkObUsWI8F1jDKZJ5Taculgxq8/GVjEJZ/85GeYNpGnvvAo/+bnPsHJ42d48gs3qIaa4bEJ9775Ak9fusaDp0aczCN5GXn2sWvc/xV/gPNveCO60JiswKf+qDIajEHbXDKrTlyMfOqdU1SQl2As0VhimnPELsm1Oo+qO3AdWV6AVmhjIG2Ut64d8OTLN3EezlrYm2jGA8O1ZYtTkQ9+4iN85/f+OVaHtzDVkKlW3AywyvZRecsgzxmNBgwGA0LniGlAGVOV1XWNaP/kOZ6IMZKlL5dL8jzn2LE9BoMSHwNt0zGfLUQPp2nWiKeu6yBIL7jMBlhTEINoCxljyNAi2WwMFZbrz90i5BXf+4++mz/z17+R1XXP0Y0bnL73DBeOD/nMY1POXpxwdDRjZ2cHazXj0QijxYu1LKr1Oun1ebqw5PjxCcuVZ7WSavLkseNceeklXnv/RXZGI6bTKYvZIVZpFrMZJhhUFASQJ4n6ba2Zvgq/2xS7v6zbNVvx4e6Kfb1+ZcVKtexZ67dvZ+Z97OllErYPjZK28B1VxcYUpEfs0StQxg26TxEgMVa3jx75FLdQQ4DAprXkdF/u8arI4CORoAVdEpWTgWNMdPzYYqxKGVX/gUCI8oHrCDaK9G1vA58RaVEYnaaaSUo0OiGw6LiZGru0cxPTjhuk552lnvzajEuxJhn1KXuvJZOKNbmZ2hhzxyiVhZwYIW0IogypjCLEDqtkQYs0MGibKguT4QQJLe0GY3BBJJKttXjv8J0YKddtg9GW5XzBZDik84Ks8USatkGbTMpI7wlaE22OJ4BboGyGd5HO1RTDAbSe2NQUtiKqyHy1ohwqXNPKkDhEOhco0bSuYTIes1o2LOoVPjqCGTAylUDgHLQhohkxGs75j49p/th77uOZX/gpdnXB2VMPc+HtX8Wn/8NHePLxF9l/zRlufeQpZteW7Jy4n/e+5w9w/8MP8poH72P55Mvos3scfeKz7PzBt4uui+/QweGw0LQyoNIGozNwHb4spAWW50SrUdVAFnLQOBWIscOsFvgsRxe7dJkQhyKBmCmsKXjq2hFHUfMVpeEbH/Y8dM8ey1pD13LlWuTPf/9fYDJ/mb2HHuHxzzzOwxcu8MSTT7OzZ5kvKpTqyAtDU3dUuchfu7wkAmXKfms82lgUHh2hyAYyvM80ygcyUzIeDVjVNY1yrGZzVJaCrFEYWxCCRtNA0GgDITMo07GaOuY3FxQ7Iz7w3e/j7GtPcc/uhMXScXS45HYzZ3Iio/nkIf/Vt/2fVPv72NxQDM+Q2YIi8+Ta4toMY30yqol0Tgy7TZBql7Gi6gKLo5t0oeFtv//NuAB/9ju+g8Fkh9HuLllUlOOKQVahVUfc3WG6XFIkQMA2lKNPRgQjHtHBgzYEv+nF65Q1S6wO69cmQT4D/B1y4lErondJSz8B2yQmS7oYgiQJmYIkipZejbBk04BWdOrTEKCTv6hEVgwqgG+ET7HuwUeMhkor5lGlOSFUETCKVUhESCk1ZECLxvlXagT/zo5XRYAHDdElNEoGwaGyZZJQzXDKoOmEABAR7LYMnlEx0mmHMR6iJSpDoyNZkteNILjhqNeZeUBOmqjVHX0wgrD76GGRbM45pZAB2V39fGG8bvbmGDesur6dI7/3anHp9hHucCbojzWKIGnUxL4NJMihXpagt/eTk0cGX2VRrg0Y+jbOzs4OIUZWsxl5soETy7WCqDU2KIw1dFYn2Kfo7WS54MMdrFtFRXr8vOwNRAyzxUp8QbuOndGYRb3icNVgVKQcDvj/uHvzWNvS9Lzr9w1r2MPZZ7hT1a25q3r20I0H2bGNhwQDjiNkIQgk/MEgLKIgcBhCIiEECRESEPAfxCCQIiVisIkTsME2xLac2E7sTrfb3V3u6qm6uqvq1r11p3POPntYwzfxx/uttfe5VT25pajEuto695y999prr7W+93u/533e57Ea5lXDdHGEurthsTjk/d/zx/iFn/t5/qO/8JM8+33fz70vv8q/9uf+PPObV3jxU7/Hw4cP+cAL72FelVwr5zx87TYHswnzo0Pu33rAYecxRQXBEJ1BpywfOyzpkwwQnWmlyRYkU+xO8WDoEETZj7oWmmFREVyHyfeIAg4nNSYFvvfdJ3zwxhaXSmKhmRjRzn/PM4dsHp5TvHmfD7z7ed744udYLDSEmjfO3+SF+irWdkzLKQpLqCPebUTPv5OkQ1mF82KBaIyl98IOCU6kJsqy5HzdiBicg1k1w9iKED0mBrFZjJpJVTObzGk257jznq5do68u+FN/5U/y+LPHPHZYsbz/kHtvLNH1nOtPzbC+4b/79/4mv/mJBxw/8QTetWxaz9HVCT/93/wcf/4v/Ks8/3xF788pmdA0W1GxtHLPh+QhQn+hiLpkeuUxpvY1/v4v/Qr95gzfbundltBeENdrLC22qIh9x4fnHa7o+PJ2clnMD/bG0G6sjWNOKYaeqJT58CprOw0r6ZibhAanuJAiMcWdrHjKkMxQl82Zv3S2MhqCj8e0v5p/dMgOIPr+/aUL9j2cRb5Kja9Tanf8wy6lI5dMKkkk/82DNO+IAJ9SROmCkDxedxhVopw07PjQonAcVAUUWbKAhFaJEo1J0KkSj0I7sBoUHb2qRM4AUIP+c1KEfNGGmofO0I4eTv5QcR+ie8blYu6a1XswjdQJdgqXKfPaR6w++7/ubtSYX7+rGAxUrLwuYXCNGm7UnPPnFYDoaYuE8K4oNJlM5G+FaORU9YTT01Pq2XTUaBc1yJ5SKazWxOAwweAL8L5D9Z5yMRfkXylC9DRNQ11NRBgtq1UKm6Ohqgq6zrOo5/jk8N5xfn4OwTNbHOJiwPuei+WS+RPP8oH3rvj5Nz7O/bue6Yuf46d/5q9RLA4wneen/uu/QnPnARvX8f5nXiDcfJqm3XBxsaQ6MizqKfOTI0xEJqzb9+DJJ4hJYU1BVCJYpUsrbCTytStyYbOYklT27x2ejwHtHa7pqG4+RlS5o9gYUQIsS3Ad73r3+/mXv/U6f/RZhdET1ucrfNJ0XWBxMOGn/oP/hKevbDhtG7qLh1y/eo2L0GFWG9zkgI/euseP/1PfwSuf+AL6PEIZOVgcoQtFOYGoJTMsVSVG2z5hSpuhhMjN9z3Na698iUmhUSawDT2ui9CuiSGIfK8xTG9cwxzNed8Pf5Cnnr/Gk09fwznH+Z0zJrMpEw2FstT1lF/9td/gYx+/y+urGXZWUMTrXP3AEasHW+rZEWrzkFuv3ON9/8R7ePr5q2zbJUbXdP0WqwV7T62weHwUCmhpodMzSJ7jG9eY/tZfxzHY01mavqNWhqBaKmdoXGD+WGRqS77weU+VbR+HInhKjMyTQTYkhox9ZMMZyIFfMRIIpJlIoY0MYhEHlWAuTU06Z/w5ERggAbg0Lkf32D0IZyz2svvsAQre1ebA9QEzLVFkrD4myrLAFFYguryjTstiwWYXqYSAEKY0dH3YVV+/ie0dEeCVVvRhi1IG4ytScqCk5d4WBhcir28iD5bSIRbEaZtaawqleepKwdwWxCrRpQg+oXUkGiPL1XyRCpWGyzbqu4PKdlsDfifHNOTkgy7FGP/3Mvj0do7wSZQtDZc1q2MUSuZQZBn+/uhNM56TnDmorPmuAR/9yIwYpIGttVxcXADi9iPZlWU+n1NNJzRNI9l822aJgY7pdEbfdnTaYL2cI1VVbDYbrClzITabcCtpgCqKamzWGvxm57NCaKAqMalK+s4xqWe4PlBMCk7PzrCm5Mb0GvaZE64kw8or/vk/+2eY1CWqKMRuLcJUK+ykwpcVLZFK1xACat3S21Joay4yPz7BNz02BAYD9kRCWT2eRaUUyWhIBrQFUwzsZ7lGUYlMRIjoFKGs0EFqGybJCkpbA1FTHS947ok5tX+dVReoIujOUDtFm3o+/3u/zhfrKY/dfJxCRx7ef8AGx9z1tCri2hk/9Me/j3/rL/4rvPrqfU7fOOdjv/pRTk/PeOONU5RPWBewhRYWjwYfHUbLwL97+4zSFjgn9Ds1KbG14tozV5kdT3nu297FY8/e5ObNm2g8h/OKvgsYbbF15Oi5GQ/feI07t+/wMz/7Sb7w+Te511mwmqvHNbgGpyrCOqFqsNozuTqn7QI/+s9+NyFdZIbVVPo3ksmmGfk+FqF53LZhakqSjhSzQxY1BO1xzgsrKTlS39F5su59zcXFlqXRaD172/rYPiMu5ME4sgfHcRdzXrYTE0wxElRExaGJacDIZbyOpInxM4fMLisUwgjj7sX/cQLZ3waviZGmfel7ZNhJRVARvQfCG0TbPoYM6zCwbcD5IE26ZuDw/+G3d0SAl8p5TUoBM7VsWsNn7m7wrh9n1Ui4HFwRNocCbq86NIouKayFb725YFZ6plqL+iGDfK4nKJMvmJElXb4wQ9Y9iIsNhUmdr0oaiqz7zJ4oRtxy4ZPohWNytX0I6EORU7ISycTl/XJTBJJSIoc2FmkT5JVCSANzx5BixOTKi0ARom1TVpNcsHPUdY33Phe+hGMdQiBpoeVZa0c6XmVKmBb4tkU3LaCwhWY6mbBtW4qioG068ebM+51MJpyePoCUmM8nwvU2wlyZlAVrt6Uspvhtx7wWnLg8gJvTD/NHfxxw55zdehl94yY36inBbdFMSTZSJDGmmE2mnC8b6tmU+8sli61m0R5SmTlpMcdYQ2obuXGsldWXsTJ5K0hRJJZRhqCysOzAxhjOe0wE16ELSyhLjJe2deUFHnApoH1i4h0f/JEf5/y130WbAjOvmRUaqwMYzU9sP8Hv3Dvi6s2bxG3Dq2dfAtXR2jkpNlS14r/4z36e84uGh2enqOC4caC5fu2In/gXfoB3v/cJvuv7voXF8QK7OJRr68O42sT3kqT0Ha7raNcbOnfOg/tn9B3cu71Bbzf8vb/1i7z8hbu8+OkH3H6zIygoqxmFsVy7csh8YelIbKtjnn5mQWkNrBTQ8nD9gKIqac4869Ki/BqDom0eormB91tceMjEHIzewGrojnZCNS3SVFajVcX1q5ZPnB9xdMVS1gmtFbOrJaWCY+84LCd8/KVX+Z5/8UcJD0/5+K98Tmwlx9WvzuMlwzX7BVR2ek4pxey2JNZ9MeySJ63Ft3ZgxWk9jJuQyRCJAUdXceDKC2QbUrzEUUwZ8lPErG+1K/7qKHtRQIiRpGTsX9q/UvgYKbVltBhK0rEah0WJIMOYrKybktCRv1mQ5h0R4AGqKtCnxKdfP+eiyxD1cI404BkpR8BYwCCByzOwUZB85BOvnZNUQak2TAvFM8c1BxPL9bmmh3wBhiDJHgdfjRX0MMg+6jEvxLILFEoL7ifHMyC2+dCUytSrPamFgQI2QkCRwWh8nDQyFjjycbXGx0Bh9syNM3OhKAwmyxbHpCjLijLT7EBxfHzMpt3inBvZPkoPxgISSLsU0BuZFJwPGF0SgmO1WqGy01NdT1ht1oSQqOua5XKJ0RpjNJtuQ2mm2FBQ2BKvFQZD9D1VVdFuN0wmM46Uow2eH/mBD/PJj3yc8+V9SrPgarnFzEuatmfiYR0dM2vZbFaglfiPokghQGHQhSVqjbeaEogM7KlMqx2WyUNAsKUMbL0Po2WK6CDZZ0ucUZiQsdNH2BghGubTiu/44e+guWhFlC1tUarGdY6XNhPag4h2hm0yPPfeb+H0/gPOL15nzpRNkWg6qOyEF567iSlnrLG8er7kP/+rf5fQbTk4MFy9dsyzV+c8/vgVTo4L6nnF7KBkverZrls+/Qev0kZFsFNs2PL63fs0neb0TLoqZwfHgOHo2pSnP3CdsFnhGkOxmIC29JRU05LFlRnNcklvIKTcrcwRNk1Q05cpNbhoSK7n+fc+S9evqHTJbHpI260oCjvChwZN6j0pRHrlROZgGmj6wAeejdRR0fcOl8C3gW2WTogu4Z2mWyV0rCEHdpvvfaHv7mXDGcJMSSR9U9aKQkkin4LIOgz+CzD0FO6g2JGGvRv8As9I5JDfk+DhRmk6fBYCUyPMeqkIPISHxA4SzNsQ3AVWYpQcN6ofXyNNUpkxo7J2FuB94vhwykO3gbdh83yj2zsiwLuY+J1XOsLARGEPetrvFdr/vnvne5DokRMtht1KORyw9IkX721lV1HC9MxGvvOFBVdqy6YNpDJRBhH56umobYV2PVYVbK3ChESBmIgARJXQgTG4D/RMwQMTMThAE6PKq4C8ohxdakJmuavdTZb3FQc+LoL5G6XFEcbIZCbdjpLp98GNhh9KZZVAnTBGs91uqDNXOvqIKQbpAmlp3/ltKpptjyk0SgW0Fl0bW5XM5nP60FOVBUbnLsAs4mZKsSYzVuNdS9t64hZmixkgy/C2dxRVoJofUR9FPvKPXmR58ZD/9//5KH/kexPl1LKIC+bFlItetFU2my1d34qGTkxMFwtsWUgdIAVS8lgMaJ1rLNIJPDCahLdUyjnNpuIKnbsdFaiANh3RgDKWMNMU0YAF7YRppJTCxiRUSh+Yzg8pmnvE/gF9r1m4locXkVQrTteBal6zPbuHKgxbn7j6+A2eePZpbn3pS1ybVpydrYiFJjVgO0dZea7OZlx97gXatmW2EHbPG6ctL9++TTk/Ybv8MjFpUl3gmi3vf+FpXr9zn7qqMb6mSyWzwwmLmUcXFkrLYrGgMBZjChp7QDeVldrh0YKmaSAmNstzVPBstmuUrjHG4905TrUcHtyEpscuAuvzlpd+86MsNoEPPvUYi8MZx/WUhSroOsfr925z4RrM8RHnqy0vrlZcOZqTaLn62A22m0NuFA29Ehg1qIQpCowuCJViUljMzNK3Lhfua5KTTl/RUEXM6ccVcMbIhwlYDyt/QBk8CbXXZKgGUUJlSCmIaXfOjKU5SZgvAFHnsQaEoW6nZPYIQyIAwu6L2W81KhKBfle1ReXamdozCgJkJUHAGNApitZkHvdWiVubAopJSXCO1Ldcm1W80XT7bPA/1PbOCPABYGA5CN4c3uZ1X61zbUeP2nWb7rJl+VkoTbSRbVL89mfPOZ5pvveFBZYJbeHpo2MSC9rYo4sZnkjpBPevzIwOB+x4+o9iciNvXsmicXiNTP77SnI7LH7UtyE3bWVf1rduAvEMXYQCJ2UP2CKK2JFPYwPMjvMuRSjvd/xrg0ghBBKTsmLdbNGpoG0ajBFRsWQsy+WKxWIh3ZK2oveBFAI+OHQKUNfEIHo47apjPl+wXl6IA1A94/DwkLZtoW8pJxU/8H3fyyuPHfHKpz/P67du8/TTT1LXNRc+m0poI1zkqAV+U9J5OTTYiIJgzHpDUvhWIpE5ZpUpKZTVqJhGzZLMSJZCag4ISYGyZqSmoQZTifFiklJim7ZcuXLEd/zpv4EpYXUuhbCLKIKwH/4j3487O+VO65gFz8HhlL7pibFnMj+gqCw3Jod4Eudv3sWrBKEUhlfcCJ00ipvWOm7YeMehUixuXOXN+w+5erjg5Jln2CwfUNYVM2O5e3aGKg1lXVCYCUlBVU8pSrFjDMnJeQdm8xmr5RoVE32UlWFpLNtNz2ReUFpDUdSUi2Om1hBiy73mTWazGb/4f/99/uOf+JO86/Gr3IglLkaqo4rGKN534wbnZ2eQKh74hl/7jc/yC6+9yr/xl/5NXnr1Nh+e9Kiks8KrQqskQEqMqKDHTB32mvkexbeHfpSYVV+V2CbuxlUOvsOYSQMhYsdXH1oKdYYEEoDaZev5gzN8JwiBigIrpXFlPsBFu4E5rMgHDF6wetGPGtEBpUDF3OEacpd8XnWkXOcTRRVsUqw3vYjTtQG9MMwCrN4uFHwD2zsiwAOoDLSgIcT9klh+/m2KMOP5HnV88kXVw++XX+5UFN6fAiw8bCO/+OISZVree5J4z2Mz0Z7GUIRAkRSbIjvIqA4dd5X9YdsP8iPOm/n2g9LkfvFv/335f5e/Um59lh4Ak7OBweYsO0slhffZA9QoCltlfLykbzuK0lJXFZvNNhtlR0JWMwwhMJvNaJoWWxXilTqZEJDiabftiKUsg8uyZrtuxPndQope8mNbZugk0vU9wYrnq+8ds8lUzrUTz866rrMW+ZrN6oLpfMqq2fLiZ1/ig+97L6TE0fEV+k6acvqUSFZTFVMqGDV1hrZ8U1SQ5XCV0UStQGkRWUsKZS1KW9CgbSHLeWVGKl3SChU0BKTxiUT0HRQVKIMSnE/qHyRc5+nOLvgv/8Of5MAG5kfHhP6MUhdcv7bgh/7cz3Pt+Wd5+sEprq5o1iusKtlcNGCmdJsL5idXKWJiNrWkEIk0lJWlb2Eym9Jtz/De8/S7P8B2c8F23fDkY9dIdsrZa68xo6QPikpNeLhcE1PPwfQE5SNGg+sdijX3798lWos2BVVZkkIUm8eiFCG9usJYS3txwY0bh6y2Hev1lvl8DjhCMvhyy6Sfsbro+dk/86dIfaTbbGmuV5T1nMZ7XFWw3azoiRwvFrxy6w1+4gffzx9bP8Xf/em/xp/4sW/BBUdEEVUS5loWE4wIGa4oDSE4eie1FLUnMqZlIORO0iSa70kEASV9vmzKEfPfRvT2kXE2sFtSEmp02JsclFIQsrsTe0SLkQixe92uTmdQyudVgFCuAwITSiK3iwkjNTtFSruDlpQShLlHlCO9hoUxlClwPIO66nn88QUffeOCb2Z7R3SyAhmN1qi4y34f3YYMfeTEJilMvqXr9JFt7H3LwJlRiugtMWi0sujQ8tn7if/rxQuUNhwX4H1Pk3pMKrGp5OARTupXWk1Ik5Mdq/f7XaT7OPC+8NnuvemRfe1rcgyXakePNCp3Eq7Xvh08sgAAIABJREFUAHRtI7hxCGKwXRQYk02alWI2nZJGOWT5DtPpVAyUS0vbtszn84xxCkRSliWRRH9xQeg6yrqkdT2xKgnOU9qCGDyFNVmnXj7fGMN6fYH3nmYrejjNesPy7JzlcjkWgpv1hqbZoHSia1uS0ZjCojPsBIwrFpXdcMaaglLAYJy8132stWCnSg8WnmOCsKOwGrFRU9L8MqwYRJFwh/9677nwHVcnikMb8efn1K3hYtNz+84pVpW4dk0XeyAyqycYI/rvvu+IQdNuWty2I/qE0RWT6gRSSUyyGgJL2yR86/G9Y2JLVPBMyprjq9c4OlpQ2Mj6/C46NHgVSCmMQSkBbdvifZ81dCYcn5wwnc8oy5LZwZxqUrPdbum7hvlB5uT3ibK0AtX1a1rvCQ5MOUPE+ixmNsOqAtdDu+nQQRyhBgniJvRMrx3y5JPP4xO879lnOWsTdTIopdHoLPyl8tiOpCBSDag0Yu0jX3xYdY8BNuu/m70elKH4qNW4Oo974lxfxS8o71MzSA+nvRer/LkjK4ZBTOyt/g5qb/W9P14Hnajd63bPPSoglksB8jkxURq4MjVcs4b2nubJ+df4Il/H9g7K4KXbNA5Fx71zMWbvg6b63knb33bWfrmhIddnhpcplTJOm8gyjYKrBzC6JyX4Pz55SkLxoScOeddjBc4tIdVcFBYbZF01fG5A4I60N9sPePyQdaAVBptvhIBSO8EmraUAA4zqfIqd2cbwHQfWAkkoVWVpSdHTt2uqsiYkqbwHOsGgY42xmq7f0vdGfDN94OLiYlQDlOWjpmlaUoqC0WaWSR9ako/UtgRtCEr45gBdsyWGntImNtuIC17Wp07gI7+Vwe98TzUR5g3Gs1ktOT66TtTHvPz5L7GoP8j/+cu/zI/+yA9iJyVK9RRFRZUsWlum9YRBcKLQIsUwQFIqRbTdX+Zn7ropZJFsTF4H73S4BYXR4m8bItGWmKLGxI7kPUk5UlWIflCSwKGUot08RLmaZnNBKEus05xNPROv6LAs3ZbZxrI1CrW9QKkJRalou8BsIV3F2iroeqIJeBPZrJfYwmBsgTaGrfOYumCzWlJNS1zbsV6v2TZSLL939pCJttiDI+7ffsi0giKKzomtaoq6oktwdHyN6ASeu3f/TbSGClGtnMxqVIpMi4oYIrN5zaZZS4kratZ+wpHbcrZd06Y1P/yt74LY50wZ+rpAO02Kik5ZNCVW1WxO15SpZL18yAvPPsPi4ClePf0EVw4SRKFISmFziNwyFsqipqwnTGbzcTwMWxqKoDAqPgr9mDETJ0Occu8laX4cipLZjUmgWqFUp6HRaD9gJytNfLmgCkKdjEnMgZJC2EJqVwQUmDR38SqNDyGrX5q8AtmbsJKwgUiidVWozPJKcog+SrOmU2CwbBrPzYnl+mJKWUXOm38Mjk7/uLZELoJmvPptM+TBxYW3ZvOwy3hVbnCAoZFIiExp/KChOKPAZ/sueTlaR4wOfOLWGb/+B29yVF7hwEzBi5mIk9mAGAImlZCiGBUgq5CUcvPDmF1qIoEoNfOd3AFD8M6iVikLnyVFVPIzqdyyrQ0u9LgkMJbrPAmLw9AGKcx2XUOKBqMrtJKi0fHRVYwRWYNIwlQlCSizUFTse3SRJ5JeJry2bYldwDtFHxT9dkPpHfW0wlQVWhdMiwndRct0JrouMjjlu5eFpXUtKVq2qzUKhw6KyeKEzWZF6gP14SEvvXyb93/nt/GRj34M74Tu6oEQBXIiQKlLarszOQkhZZpoxka1YJxEL5lYYRCdb01CmsLGLMvsJuKotbCXTIHXMolpFIQOCkXMDU/KGkIogZauN1hbEQswvafvDNPQ0FvL1nuqqJhNF1ijEJ9ehzKy+jA9kApKe4CJhoOpYV4qSm3oGmEKXTs6oW0b1lvpW/BUtBdL1k1L33lcDNKcVmqiLehVEP0kAp3zVCZhQk9otqSuxzqN2kbKg5or80NoRAbhwdkpDx484P7phs2qJXaRRMuk6zh1S4KuqecHfMvjJbEsKYoJzI6oYk3Sim3vqIMhJk85q0mTKWdNT+taTD1D644r5Q2U0TiidIxbEeRTSaN8RyTiWNO6SLNpsKEENMSWInQ5MBtR/RxWboOhz7CqHRk0yH2Q+YZRJzBROOakvHLYaVxphF5sFKAiHlG0HB77sWRwiNNJC6c+xx6txdEpaMSVI+kx6VQ6omMk4HDREYzCqUTQnmSkFhSQ41YJIZYoQ0yRzsDWGRrtmc4Vj1XffP79jgnww3YZltgtlR4N6EODSyK9JdDDLpu/vK+3fp7Wuyx/KI6klMAWNMHwP3/0Fv/r79/D6sTERlIfiC6RbA200jAVd+YiIcZLnwmMAmjDNlAeJXPxDHAN7DQ4Bms+cavyIk2AIsVeViJkTYssbau1JSWFc2HEq09PTxlYA2VZUhfiF9s2HcZYYqaUDSyc+WQKKlJWFk0kZCEs5xy+dzSbLU3XoCtDo3o2m0aMRXwgOA8xse2WaK3ZdqcYawkemUSdTGxFVfL8e57nrDln2ge+7wf/SX7vYx9jfbEE5UBrotaYusRWpdDLshRD0glVWlRRoSgkuwoIdm6L3ExmRnhnvKaSROX7JBddlUEZyfCJiRScyF60nTTCDNfMaJq+o/E9noRLkaAUTGDTOG7euIotSmw95WK9wlpN13WUpuTK8VWC69l2KzAebR2JBlvPKOo5vY9MZlO5Jt0WiGzXK2LouFidC0e/7zAalufntI00slVG0263aCKrpcBgvgmc3j+lbVs2fUt5MOH45jX6tuPW/dus3RYqSyoMB4sJSjtm8wXzw5o7t0954DqOjq5wPD1g4VZ8+D3v4mB2RFQFxoNVhioVHC2OWbYtB9MDJmVNMa8ITQsB5vMpk+mUJ596F196LZcHkyH6jhANwUacKaAX6eOpFlbKg/tnLO/fp10HlqueqDVdkpWb7/pMY9YwOL1l1tQ45pOSehUWFQ3JK3SGbgd3KGfEaCnmUROSUCfj3rjc/z1kmvJ+z8oA18QYSVFl3n0WFc4F/hgLfDLoWGK1ljpJ1NKZrzLUKl9I0hSt8ywViRHOWkfrAz1iLvPNbu8YiObr2S4Far0XsEe+6C6CX2KRjO+/tLdLs9uASQ+fUYZOmBRGYYj8nU+doULix953FVNGOt9xqCxORXFz8gFtL08qas+0hCQkyBFGkggyipntsOGdJLIc1+WJQmnh4McgipAAfd9SFKLnLooK2VLNKKwxbDYbZtPpyKxQSuG6npgCVS4eGa1p25Yu9ITgqU2JystjEbiMLOYH9O0WFTwHtuBstcYaxXQyp2maXJit0DqiVIHrG9CGVYwczg9EM2Wz5n3PPs353bvEouDB7Td5c9Pw3ZMD2ranLnZXJ5IocrGtLCvMpCKWJaqoc/ugHs9diqCNzRCV7ENnakXYm2ClNhfy+TYZaw6kIMqSVhlUjEQn2kh1UeJ7R+h7NAqfRNJgOiv4nU/dYpIi2wBdzE1muW5RVhPa3nHt5AanqyXz+Zxm3RBNQed6Nr2j7TtWmwuhrgYgFagUOH/wgGo24+TkGg/vvsnTT97klYv7lMUEw4TotxS5ua1zQb7HrGB6dEShFdpKt+n6bEk5kyJ1YSyx9/jVhn42Yzad8ebFHVat5frVI5pNS9NsiU7zp3/wu7g5O5IMU3sqXWJ1wVRXXLSOZ248xR98/iVC1zM5mHG8OKSwkYtVz/L8nOOTGVcXH2J58ToH83NMmgO9CK0pT0oWtGTh6y7wl/6H/4q1W3F24Tk/P+el3/o4p7e+iPct1hZjQqSiyOoqJXae0iuicrfnrnlJ7TUIjSqNCUiRhMiLyJ+GmljIP3exQms7cuqHPNigLilbDjAPuaYmmLB0r3axp7CamDxoiw/s9dHsRaGU7UgBpUq2JtKqkgcXHQ/S/48gmq+0PZrN77NSvuJ71P5r9/+u8mOPQjni85df6zT0UdqaA9KiXhXwSy93lDFyvYi00RHzzTeoxr1dkXe3SfY4UL2++vd9lK2Ts/6oGLqXQ3QSmFIag1bI2f7APBl48k3TjFTJorQkIrPZjL7vR3u/mJuq6qKk7dssQ5vwXc9qteT8/JT1+oK+7Vgul9SVFNrabjsWV0mOrguo5AXSCIrFZEa3bXJtQbE4OmB+fAAxUU1qPvyt386rn3sZrXb5xlBAjUroi6awKFtIhr8vpZzx0UfITfn67t07ejijaWxVl9ftoBu9R8EbBnBhrRDlQtgZTkTFrDC8cucc3/b5vKaszS6PbdeiNTTtium0lIlaJepJxbSeUNmCuiyw1uJ7T9t09M1WfveBuixYnj1ku77gjTducXx8ONAQMEUxHudsdsDBwQHHszmzokBrKbhODxYU0xqVNAWaZr1hfb6ksgVFqVhtzjk+uMKktihTURmNUYbDw0OevLKgSIrZbMa0rFBEQv6e2ntC2/PCt3+Qx9/7bu7ff8B8OiP5RFUUPH79GibVHF+Z4tsarRU+49bBBUwCnyAFj61KprMDvvyZW3zxC3d4/ZXXuPfmGyydwyvJ5HuVcARiYUj2sp2m2h+76nKw3vWcpN3vjww7nbLR9eDUBONjf4UwjD0Asyf6uz/WZWRLsofaJZjDPRp1LmawSzyFkZePVwEp0HSeB2eRTZrxZvvNh+d3RAavFBhLXvJ8ZTYMlxoI1N4F203Tg/TAbkZ/e8bLLrAPvw+FuPz6mEgqkiiAhDce5cGw4X9/cUX08Mc/8DhXj0rWzRaMEYXClKTIhyz59N5njMeSdhV3beQSxNwdbYwRaz5LXvYBRGwhKzmtKlKCEDpqXUpHbMwOQFmWODhES4VI1zVYWxIyDc0aw2a1RlvDdr3BlIUs8Z3oyPfBZ69N6RLdbrfYssBmyQaPJmiw0xrf9hgjgV3ZApPNRULsUGaK69ZEAiuv8NsttlCACEy9513PSXajHG5zzm9/8qP8kFVMv/3bST4bbiQF2mK0zw0rCl2VknmFDJCqJCYuCcHO1a7zcJj4lDKS/UXkJCaPTikX0KQ2AlEgqzypx6y1XlYVSmuc9/ShJymhrm7OznjxtSVFfQVNwqcW3ASiR+0pGM4PrtD0DYUpuHJUcra+YH50QlE36E3B8aSmbVtUgrM7b3BxccHxbMZmteHo6JCmKLh//z7TWrPpE1cXj9FlpcyyLGXCi5GgAqt2LZm6D5zfe4jvndx7Sgr6ZloSFMSgiV5Rzi2tq1Cpg3qKIZK2jm9/+iZnr9zi3R/6NibG8pkvvczVk6tgC45SounOSQ80E605OV5gfIfqW84fvsHJ4eO8cv8PeOa5b2NmJ9xfP6RLDyAsKJNB+8hWRSZFydn9O6jU8Su/+bOcPP9ursWaoAKfff0Bz88SeE0MMU96nuj93njJpjYxoMJuPa5MlusOkaRFTjhKvVMMgPbqY7k18lLmDtKHMTg+ScAWn4aULUBVbnISlF+KAQlQyUIQOz/lwVgrMSVqVAjYMscAyMVXoY8SpM6mQwAD3//8hFvLDeuq4NayeWsc/Aa2d0QGL8VnwZD3RfVhN6OmlCRbDXEU1Iehkp5pcQlpelCP7n/PzSUJvXL3ZL7AWmhzgtlm9Wel0QR0iigsUdnckSrY7S+9dIfffekus6mINgUgIDBJ0D4LJPX4kFDaEpLHeQ9Biq8aQ4hDxhhIyeXi3GXNmxACzseMEfbZyd3Q+oDzQ1t2zFi4dK2GELJDkWG92QiigRhJDNZtCYO1gm/bQmQOou+JyeNJtKGntAp8TyIQlacuFKuzU9xqiyKbTQC+a6HtcH1Ap4LgekJSxGApto5JXZH0RIp2dZTskgJURWknPP/cC/z+5z/LJnZ0yon2kMm4a7IknaUKXCRFIzWQVIqERUqiQBjcblJPw0MonzE40uaCsLrAZM2bpNMYKEBjfIIklEkbNbjsFKYSnfeCpyZPcJ6LZsPnz1p8NWFmFfODG5wcHcu5V5GqqmhWDeebM4iBEBxBa2bzBb4TLH0+neG3W0oX0H2LtjWzsubOw/usNmte+uynWW+3FEXByZVrzOdTzluHzx3QgSA1JKOxaOqyImKIQVEUGmUD1CX1fMa271gcHaNthZ2VzK8eYudz7LQGXaON5eBgBlUkbFtmpsb1nr694Pbrn6c7e0h/tqGazqirA3zb4dYrymrC/OSE6+UJmzdWXLl6zFU1ZdU5TlenbPsNZZygY6LzHUF7ahWJumA6PUAlT9IFs3KO15o+WTRbUixJPqAx6CCd41oXhBTFvjK7lxGGBC6OSVNKimD0rni6pzQJg0S4EAOkgLoH3wG9DlJEJeFR9FHsM4eCqScRg87ZvJbCPpqgICiHsVFgVAJRJ1y22xwou6SsMmsURVLY3KwV0YQo/hbX5hNuVH+YaHp5e0cE+MKWXLt+RFUbFAZjd1n3cNLfbhsKLoOc6K6TVZ4f7MQuP7ffxSYzr9AVB6s7w6DjvB9kY67iSzAQD0at4eWLlr/5D+/wq5/ZcH1qqUuPUh1FmGJsxIUKa0QoTCXQKo261SC/P+oxuc+0Gf4evCIlM1r8DZduoH6GIJhmUUhGPnR/9n2PNYYu4+9lKRK6vXPoSrPaXmALTddu8V27W1kkKIoS7wd8UozJvffU1ZRqUgsmmTn3Son9n0oOjfxMOFCezjcSZPuG89OHbJYrrp+c0K02xK5Fmch3f+hDUrPoAt22QSEmGSklEd/ShpA0GIu2tdDidNq7bnosFu9qIEkKqXjidoNuOkzvSaGTQR52BfCRmRE8se9IrieliPc9VVUQglDjAgkXPL/zyVvYySGhaegimORl8swF89lsxmRScTA54OHDh9y9e5ftesV6eQ6uxTdrCBHXB8rpAU0P12/coJhPefbmE8xJHF+Z8twzzzCbWvo2oINGxYYriyNUANf0qJjompb7907Ztg4XeqLyNL5nfnRIXRim0ylXr14VbaGyYmZnVFSkrqPWUOpEoRIXrufw2jU+8vKXqW5eYWIqqvIA+9kld2NHGXoeEAhVzfHVY5qHDyi1YqYLrh4d8ODOa6yaFlfVRBt56vEnqKpaOqAVVNbQRo/L3aXL5ZLlcklygbqwEJNQYuOgMZR7F5Tw3GMUy0udhc6M0qN8t/Q/jEW5kXG3g2EeXcXv4J74yFMj4yYH/9Hf2QWxe4xegro2YyKxq/EY4j63Pu1sBq3acfkls0+5SCurigEEQm84mdacHB9/hcj39W/viAAfYuDwaMKknmHLQArl22Low7bPtBmKFoP63FfHwC+zcsYmCaQJYWxXZu+CPbLPwXlJ/i+TT6k8m97zv/3eA16948GUOfB4dAEx7IL4uJ/hkcLe5+zdoAyZveB2j56LoQC0P4kZUwg9zXvath154ykFjBGjj8HqrcgZezHIHZjMKtEF1pSAGimGxhhpknEOnGCtZythbxCkQDsUfF3f0bWtMEM2EvCiijTdFkzkYDHDlgWawHa7zaJLYt79vg9+kL7tCE7MwocBrlLmthci/zsIPV+6njGN98Cue1DOe8hWean3MkDzam44r2ksksmAxDvU2JgWR7PrpAR/9xE+9cU7KG0xWUU0+k6K1J2TRrroKaqSlBLVZMrRyTGd62n7brTcu1ids16v83Ekmqbh7OFDunbN0fGMWWFYnr1JURr60KNNwZXjOV306LKgmNREY0haMSknlLZgPp1QFTVai3FL7x3aij+rSaJg2DQNTbMRRk5RUBQVZWEotBjAf+KzX2Q6nbKMHnzg17/4CW7/1qdYXtzFbTpSYbEotlkLaUmg8x12Yrl/sSQUBe955jlKIx3W2hixJPTCtNJkW0ytxWrRKkk8YPReHa6RztdW5WCtGTxZLzcQRt4+Vqi3DQd7lNmhMvOWuHE5NOoE6MsWol85Pu0lk3uzx8Dvh10VMSWBj4b7ERKVq/DaMEnffAr/NQO8UuoppdRvKKU+o5T6tFLq381//0+VUm8opT6RHz+2956/qJR6WSn1OaXUP/21DyNx9+4G5zVVVYCWrkAJul/Hu4PALloPzInhBEfBuvYw+nx88mu2ysosJYgZAlIK2HWe7S7msNTL3o4oFFNcFOxv2bZ87NaSX/ndN+mKBhPnBBfQuifGkjQaEIR8ZYegLoJiMWaxMa2y3+aAw2fmTPTE5AVPNeLfuZvo1OjxaXNzD5AFxVKGUmKWNrCiEx9S/u6KhKbrfYZ2Aq7vaNtmPGeVtSwfnhJ0pHEtlsSmFc42IdC1DUbLEjglkVGezQ4odCGdshhS14jDz6ol9S1v3LlNHxOVkSLv49ev8/sf/RgqRC4267EobAo7djIOj/1l96DIeWnVo6VpTCmFsSW2rknGZN2QKJz3JG5IBNELUS6gul6yfOdRIWKNweoc/BKoFKjLklubkoOTBSH0qELgHhf8KMeckqJtW3rvWBwd0Ll+lHR+uFpxsW1Yr9e4fsu9e7domiUqRKqk0XXJMnimi8dxrWM+PUBRY8oKZSfYCNOyot82mBA4nMzYrh7gmi3rsw2FNqQ+sF31mJBYny2pqgmN63FEWrfF4el7jy1rWh9AK8po2K4bvnDngvuv36YqpyRTcPjss/w7v/85/sGLd5hOa7qu5c52yfT4GJdgPp1xr++or17heHZA6HoWszn1RIJ28D430hkqW0FWfjR1STmp5f+FJSpNl1evWkutJ+k0Qi1Jqx0NWaDvPD7NGPDHmKC49Jrx77lPZcjKxyamNPa7yz734n0g5YlHWDQ+hBEuvpyU7QqrIQnCn/Q+apAuRaKQH8O7Bj2dX3j1IcsHax7ELd/s9vVk8B7491NK7we+B/izSqkP5Of+25TSh/LjlwHyc/8S8EHgnwF+Ru172r3NlgDnGhSWx28+yZUrRzsLLwVvAdXfbh97zJO3a1Ue9jU21I03wzCD7wqvl6lMMrOmFLKuiR7b2aVZshEalIYUNA7DEsPZSuH6LaTs1qIviyBdPvYMuzzStSeBLGPsSfxXZX8CyQyiYjtxMTGbHqCKwRREdGt2BtzeeyZ1TcrFt5QCKUph1Tk3yhxU2VikaRqigvpwLp2SbY+xeXmsczYWE9uVSCY45+j6hs36gtXygsXhIVEbMGLEMT08YNO1FGUp1E2XPXBdz70370rgc46u68Zztxsggqsohkn2rdf50vXNNn66KggWkgFSyJNszJX9kEkMkVwUkYARGSeTYYUSQsAouH8uqxNT1FRVQevFC6CwFWVR5xVUgTIQnKcwVhhKpmI2mVMUVVYktPQu0naeTdMRSdSqYxK2HBSBo6M5621ATRTaRkKzGiWdU0qcnp6yujjHljORl04e7wPeO3zc0HpH1znWywtC7yQL1jazq2SynMxqfARVaHrnOG96TjdrlHVs254PnNzkytE1/sYf/ANU11EU4gHQA77tsUGRioJoJ5lKuyai2TTit6pRImmhkIatzFAJLhK8J7psnZgz9ZRZUiZK9m5StueMew1OowDY7lrv1+XGoDz2Q+fRvl+7yz8T+lLMePsxmrVmstzw/gSSlM4Fn3w/xQFZyE2EqEvHsZuY8k8QUbQoUsWvXsAr5543Hizfchzf6PY1A3xK6U5K6eP5/yvgM8ATX+Ut/xzwsymlLqX0JeBl4Lu/xmfQuUQX1nz5S3doW5hMLVVVsetBfeuhDoN+gClGyCZlnrmk9NlQIxvbDnY0ebIeKVdq10QhUI085P35kSSIKiXdcGrIwFVEB4XKUsFJJ/7ep++hK4smkMwRMXViHqI0Ie50USSm5AkkCMYYA0S/001JKRB8Lzg2acTolUpjxq2UsEQ0Bc1mKwFMBzbNFm0q+q4hRY/rJMtfry/yMr7DR5cHjZyalJuhQtzt33c9selwvkVbjd900qXoA61zRKWwtiBGkUX1fSMSAMHhNg2h2eC2Drdu6Ldr+m2DVkrYObqmMNJla46O+N3f/m0u3JoQe7a9dHEaH9FepPdShJiL8SqvPqJ3pJADRJBGlBDk/+QCfVFZdCFQDimifCR0LdpF6DzJ9eg+QefxsaOPHZ6eqGM2eO9pe898cUhTzlnUU0ozhVgxmR8wOThkMq2opjMmh0dUJdTKYpSmtIXoxMwnzMoSdEIbqI5nFOWc+vAaxbRkfvWE+yto7BW+8No5X7z9gLund3n44Jx7pxf0xrJtOpyPGJv59p3DR0/nA0oXbF1LMZXn5otD5tdOSEXB4soxfXLUSqG7iIuKTdPStD2xqOmMpd+cc9drPnLnVfqHLYujgmceu8Z0XvCFWw1VjHTbjrTuMMYwOzqmmtVsto7ORa4dHzOtE14FVqtACJFkEn3fgk6oGHCuI9hEbDradktlICor1n+FsI8SPqsuJnoiMUHQWXpgaPRLEsKCjqLPowQWJaZcmE3YpPJEIdi9R9hkfkC8tZa6WMbtVZ4AY54gItKpqpMmIGN7iMwx59+SLAhVRymTY43JSZew+qzSuHG1HkeMRhKsHWQbkkcry0fvrjicfB3wxdfYviEMXin1LPBh4CP5T/+2UupTSqm/rpQaKgJPAK/vve0WX31CuISeiRaK5/HHn8zYp8UYgSS+0vZWnPytr93vbJTfd5TIt8PS3u7v46+PCPHvF+oA0IGkSkoLxmtCbNCpI8aAdJYOk8nus4af4s0YRux9EPAa/Fj3i8X76nZiil3RdR11LctelaAqShRSXBVJXkVVSVNU224xxgijJonP7QCLDBPJMAEOVLUU1VhUBViv17KczpS85APRRcFUjR5pmCEE6RbNx7/ZbDg/u5DuWSIhRfq+570vvJuXXnpJskKjJbvzgxwCwpTJ0MtomJ7/E4KwZZQOYkM41FWiv9RINhRlI2nsipQCHuOxDkVbURYFbIEPhqKy1CpyeOWE84ul0Nu0xnUeEyJ9FIhtgkYXJZ2XFdGwEuqbFteuUdFRaoUJgUVdcnIw4fhgQWVkVbNcXaArw3R+yOHihJM4IDVaAAAgAElEQVSTEx67fgOVEkZrEZIrC1RVoGfSUXp05YTF0YLj42NmZc3x/IjgekqrRc8fRfQOnwRuGGo8wffoGOg2W+r5IXVVcf/+irM37+GWPZPK4GxB/dh1YUulRN95EhrficCZdx1VETlbrdC+ZtYpVpu7wswKZCXTATbUbx1badd9PiZcaffcOLYjJJ9yQ99uzJlHMHhvLj+clofe+9y4h+EnqXruQZt6tCWUQmwc4dKhKqvSDtIBci3g7WPP221DPBqYguNxEfEK/uGr35ySJHwDPHil1Bz428BPpZQulFL/PfCXkYnnLwN/FfjXHznWYXvLt1ZK/STwk8PvY2OAVoTQ8+Uv3+PmzRt03Rtoo8Wp6O1E4tlbou2fyJhI+x+rGDtLL1W9dRyflwPN74m7oDv8FC72/lcZRIsuL/msh+96Zs7Z1qO0ooolhTkkpm68YUJ2fVc6O+SwW9YNrkKD6FhEnJyGczTABQqf96epqoq+b6mnFU3XZjZNxFpN8C1poHgCbdvngJ9wLmCirE5CkhqAc13mFRtCFJu+vnO7YmNKeOfRUSwOrVJ0KdI00lZeFAXeRfq80jC6ABUprcV7h3aK6Dzn6y1v3j/l+Pp1ABbljCtP3+AfPXmdcH9JO7H4ArQRiKRSGl15oMM7gyWB8iQXwSDaQCSS6/Lly/WLEEZDlZQSKSS8EyGtGAI2F7lC38k+NbhOVgdGaabWCuuoqLl5/ZBf/bXfYX4wAa/xvhfDDedpwppFPKHtO5oycayvsYqNmIKnBNrQeE/nRPo2OIUOimZ7QftAJua2bZlWcwqrITpsOcVmU/GytlSzOWUx3dFT+x76SDSK9eaCSTWVlaA1UvRtN1RVRQoRUxWYokQVJXWpiZWm1EZqB0UinbW0xnL16gl/67c+zp/4tvczfeqQg2rC+qzhsfKIbrnEzS1RFzzcrrg2PRBfgbmie6XhC6+s+NlP3uLnfv0n+a5vfRJrE2AFatGl6CllCGwgCqgEXSfmFiE6VNRYBX3yMrbIkFkagqpcS3F0U+h0WXIgKdFX343LDG7D6LGafxMAdhiLSklvBhotpqhYDS6KXLfBSF2MKB+f1SzFyHtXPB1IAD4GNHmiyP80Q7NlyvTvXeI4foUYUWjcfrPUH3L7ujJ4Jb5efxv4X1JKf0cOJt1NKYUkuMX/xA6GuQU8tff2J4Hbj+4zpfQ/ppS+M6X0nexlyyqBRdrBl8sl1x87IEWDd3tysF9h27Fq3vqakTnxaDEmvf0jf++3nos9DG+oiu/vTymFwnK0OMAkqE0iakXbOpE2Js/YWjxEB1xZsnJ16ad8jsoFoDg+Uq4Kiw6MmGUMWWLbtmNGPvzdGJWt/IZN+OtN04wZrNYa773IAw/MhDzBnJ+eZXiKkX3jg3D2ATYbMa6w1lKUJSFKNl4Xon8zrB66rmUymYyf7VLkzfv3d8Gq6Tl7+IAn3vUMD+4+oFkuiSZk5o8nBY9yjhgchZLvEZyTAREF4lJRmpRSSOgIKuRW8FxnIAqWalGo4LFoYu8IXS+CVurR4BNwBgwJlEPHxO9+/jYlUmSbzkrm8zm2kEKhqGuKfs1qtRpXS9ZaprMZh1dO/j/u3jxIsuw67/vd5S25VHV19TLdPdOzYrARGCzERoAQTEokTBCiRYo0HLYlWgRlR4j6Rw6HwiHLdtg0FRTC2kyRJmWRCpmyRJO0SVEiQBMgYBIQFyzEMsQsBDAzmG50Ty9VXZWVmW+5m/8492Vm9TQ2QcGY8I3Ima6qXF6+d9+5537nO9/H9MQ2k8mUrRPbYmxuDdPplD4GyqrCJzhazOm6Dt8v6bqG1rUsu5blsuXw1i2WbcPB7JBOJ5bIdx9VNa7rCb2j7zo5D8qwbDu8F7/Qre0dOVcpUNc1RVmjTMFR37KzexKrNKdOnWQvRLZToDvcg2LM2ckJvvDs0yz6JdF5vEqURc1isSCkiAsTfJjzskfO8lf+9CtoxlOKElBDg5wHFVZQKrAiNKSUhOmUWSfDjupOrLiY24tiXrwHw+pjSZ7K+LvOD7UO6l9ud3/s/lVq1Tj1vOfqIZGTe3FTBhxY1dlWDLBcHN48xtvHesEZPgQShofPFnd8/tczvhYWjQJ+Fng8pfR3N35/fuNp3wv8Uf73rwH/kVKqUko9ADwMfPQrfgZ3gERUn+lciosX72Y6rb/Gr7Q6vmP/3vx5s6q9ETfX+vLp+QtJzFnE5uSTNzv+uSlJ1+v7HvsSl2+2nIglhJaq8qvVYXPirjP6/DkxSpV+c6GKAh0Mrxlw8b7zmTKmqIqaGMEUNkM2fgXveAe2LFYF2QHXt7bMBtzC7vDZ8T6EIEXYGOnbbiVd7L2naRciRqbluSn61bG5vs2uUHnBCR1dv8S3Db7pCN5zcGsPgLbtuHD3Oa7s7/Ps5y+zaHqW3jOfz3nR2Xv5yV/4Ra5euUZzMOPw8EAWhK4ndh3a9wS/JMVezBo6j3IdKXQk16IDmJCgb0ldQwodKvYk14PvoXcE10thKzhUCmgV0cYQ3JKmFaEsoyNJKQpjUcHjW4eOHbGY0HYNXTKo0tD2DtcsmNgR9bZl+8SEiRox2ipQRLYnY07tnKCyhkopRsYwUYpKR8roUER0CJQ52/O+ZTIZMW8bKcyWI4qiou07gjHErZrR6R227zrNzulT7O7uUo4nqKJkNBmjC8tkuk1Vj5lsySJSVZVg31Ey6D4bePfNknFVUyeLqTW4hht7+7z2W97EF+sxNxrDyckWfucE9faYRoFftvS+w+3tMWsWdE3P3M2ZbF3EL2Z8/P1/yP3nDHVd50ShhyQYO2H98LmuZKyirItVUjJAjmvjnjX0IbDb0LAohVeiQmNWRuBk3N34hPFiuWmjzIlIVmpNAoGqDebLQHZIST2f/RLFKCSGNcFiFVvSai+AImf2KWUmnMSKocA6sNrItXy9AdEMUhQSJhL3nyi/Wpj7quNryeDfAvwF4Ntvo0S+Ryn1qFLqM8C3AX8tX4zPAr8IPAb8BvAj6XYS+B2GSus1M+kkHZ060Swk2wyxv/Prbgvk+Rju+Jw7ZQR3eh9YNz4NGcOXe93w2s3X2wDg+cSlQxZeYWNJ3Nhaqlxx32zCWmlfJIU25Ow4s1yIbNIplTIYU6wcmkKQLLcoCrSytO1ylZELxLPOiqy1Kz14ybr1KqgXxuaCtdAonXNYXQiOrxQhin+m4O6sdgo267VUVUX0gbZpqMqSzjlc1sNJKVHXJaPRSIJNDJw7c4b5okFry63ZIfvzOTf3b3H1qcv84RNf5I+ffpr5wUwYNU2Ldw6CdOyK3Ktg6DYrQiq8zJuYbdKCR6uQ6ZJrZtTA+48p5bkmGP0xhlW+3hHFWGtciFhbk/BUiLJkn6+Z914kqpMiLVtMijigUtkrt2lZHs2ZH9xifnCL/b1D5kcNh0cLUlJsnTxFUU05d+E8WyemTKqa2hacHE/pOof3gcnWlOn2FhcvXmS3mlBGRaHEelFZhVWGYtBJMZpFdNitMVrDcn5Et1yQgmc2O1hh4W27pG+X+G6JbpzAI0F2OdE55g3svuzVLA736XvP2d1TXH7umkhlKwmYTdPQLRv0UqFtw7/8p/83/91HP8FYQ98LpTeZhKg9mhXMeDusOszXgUAgO9t8PTZvzbzDkhJVLqJvGG8M7+tVEiXJ/HAqCdNtM4fMV5jMyFolWyFkaYLj+P6AwafBwCTTM1efGzd7c26HeM3qe24OzbqxyiixJUxG4kfj7xzzvp7xVTH4lNJHuDOu/t6v8JofA37s6zmQY+qPARQVLgSimnPtuuPC+fu4fPkyMfWkqPE+og3EIKhX/tzNYxBJ0vEYtHCSfe82FOLWY5hQwAqyWP0tbRQ/V5Vv/bwLufk+Tit0gGgUv/bpy/zZN5wlYIa5CUoLKig8PFISw4KYt3SESFlWx5qZrLW3sWc60IZkFMqQC7fCBkh58gn+CdZqwdqNJbhIzHRKHxP0hfDglafxHhNlShS2yufC430EK+5N3nsxOohJunOVwjnBj5dtQ1kbYtR5pxAwRUnbHRGionOOEBJTa3CtBJTXvvqb+NTnHkU9JgtBqQrCuGR7a4u/9r/+Er/504/gZwFjHF4FxjaiYklMU0JhMdqgFGLX55wYNUhSlwuIIdPPFCqImxAxCLTlHSCdxTFGlGvy4qEJoafrespU0rhAnxSLtuPo8ev87jP77Nxzli1rme9Jtt/6RJ08TR9QNlD4xPywY9H2UATpiJ1MaZoOqxWmtIyTFK7b/X1ijOy1R3jnmM0Pgci0HtE0R0y2xiznh8TkOTAFhMhoukW3XGK1IsZEnzpUn8CJpHK/PJKg1rRyjZCu2RBgdGpC2y6h9biQ6GNPJNIuHHY0ZXlwwGT3FAfXnkbtX+An/vn/hbrwCkprOD2+yPXYc/kPPs2l5QH//lvext6tA0JzyLVPf46//oknucsqTp+eomLKTCYFxpGcQqWCGB0petoGXA/WRDSl4NgqYax4ovZBdIaMUjg0lohDCyyTu5hVFAqiynIASa/ZNQBm2PUOcUGizerfUjSVjHy4r3VMJBVWEikxh5gh+05ZOGrg50vh1kBaC9nFBKoI6FjjSRgCLiUKHXFKkjWdAkFpNFmxVQnWL4HG8MT1bxyDf0GIjW2OTSzeJPDBY4uKg4MZRWEI0dIOTie5cHanoTOn+/DwkO2dE4zHY1otrfgrVkeMqNvWrjvLDKdji8CXxdKG30eFNiWJni7BqCqZLTzGymZMtpzyfC0gXe54G7KadaeqBHVxhpeNkCFGCWKlHTpV06pZJKVEbaS5SBlwbU9VVTC0axud8zxZGApt0UbjomM8HQuGGwKmlPMXtXBzQSCaYVcg0sWapmlW7J2yruicWNMNlm7B9RkmUuAd1opH62LeQFTM53MefvhhFkfzTMf0KCLPHh2hdMny2g30hbsJy56uWrBsdphEhbK90GetLJQmy8YqpVBG9r9Di5sVLQpizk61NaictWuVd2vBobxk+8YYnO/o+5bkjjBb4kK0vTXiSrfA5J1OOapp5iLVYKxFpcBkWuGCw+Fx2tA3B1R6m0m5zeGt/bw4O5mfMQiBwEEyUnty3ovpeQqEmOhCYr5sBcvHMD+4xfZ0zNHBLWIUMbl6OoZOmE9Rd7j5jGp0gvlRR2lU9gKNlKMJR/M5KSDaPT5QFoZl8CRriW3PIiyptyaMphP+4b/8IPZzX+Kfliewe0/xA/efw40dsWn59MFN7rp4nu5gjy9dbfiFX/oAH1gc8R0PV7z5m84xSWPa3Kgz7FQDOfPOmdIAYRRFtar5WCUJVt/3q+rjMds8NSRXALm4mTJkkv1TU1IiNp02usMzDs8GmLB+zzWpYbj3N5k7QpGU4C0fq0iiQS2v0Xqtl3UMWq2QbDVArEhpozs7s/juGEnyruBG81WBj686XhABfpPtklYroOC6trI0/ZJu1nPPxbMcHR2BWtIsW4ErNNxJfXczQM8ODqmqino6yYGoXkMWmUMfQqBtW1mdOR7EN4P77cd5pyxeYfGpxVIRdMeV6y1nT2mcyyqTUaiSd/oc+Z1aM2BSxB7Tppbj09rmLbBAKl3nsBGUNcS+k+w7eKqqyqJjGTNPg468MEuc9bk5StE1rQRAJcFSNG0MPgVMUnS9X8kPD5CQaN4E0axphTlglMX7SNv2KGWoKlmUjFU0TUN7taGuaw5uHTLZmnK4t09tS3RSzJsFN27sEYDK9PzlH/0J/ocf+Q952ctfjtOeSkEzmbLLCZKx6J0TwpqJETWZippo9AIj6EKye9cKsySuF02jQBHwvUfHgE3i7KU2uoBjjLhCE49afuGjl9j/+BzbNtjde6mLUpg90zGqF834WdtA49k5cQKbFH4p2PPR0SFlabEFdC6LWDULyqLAKkOpDFoXWCsYfLOcr4r39128hyuXrlCcPY0nUVjFwWxOHxOjUlrZfevpXaTUoHWi8R0jremWHWFkKHTCdZ3IPPjA9Ws3qEcVdlRyuGyoTcUyebbHY7Q1eBLXb+5x36veyj/W+zx07928e+cmu/dcZLH3LE8/dZM3fPMrGNHx9/7Ze3n/rRl1qXDA6+/d5uREsdBLCo/IPedAqFUiJJ3nciHwihIhMYFDBe7SSaMKi3L+WHE0bujH3GlkCkKmz24UPlUOvqx1q2Bd+1s7/R2nH6eocq9MvueSOC8FFVHa5O+k1ouEWlOxNZEQI0EXRAqILRqT61k+3+ci06G4U6CPHLV3/Jpf13hBBPjNb7eZLSel8C5HbwPXntvj/PnzLJdLjBb52MSdRfE34Q3JdCTDrMtylfWajcBd11LEXcEszuXMbq0FvcYG7xzshxFTjzIQfSQZuHLYc9fp0QbEsoYRbKZwHcMkk1oVmCTjOZ4ZDBnA8P0GLrwxBp/58M51q92KMQXOdZRlvWLGhBAxGHrnKCqL7wU6QIsrfNu2FJXomA/iZQITOUR73tN1gm0LS0SjraEIZvU9RqMRoPHRobIJSF0nvnTlBqdOn6SqS0LwVGXNfD5HKcXMLXjsyasUQJE0e07x2//m41y4736U0SybOV7DVjXCForkOmFgdB22HuUTtu5wVciNNxTnSAkdIzGJcJSWsttqDiqtSQODBjCdsJ0euvcezulTdK7js5/9LF0t7BellXDSlUa1HY5In3sDsAZbJZpFoO813XLB9sltXChRZaLUNnfrelIy9N2C3jv6vhVIyRh8TJzcPbEqkJe6hKLEeM+ya8G7rCUD0XtirxmVJ+j7JcXYUtdjQnCUZc3oxAnSbEa/aCEpbFliQoCksT0sfY/qE1tVRec8+/46pZ2wUAt2J6fQ8znPPnPA+596jLf2ng89+hj/71GkzPRODBSnKiZGoVpLp7z0fgSBN6VWI/M4hIBXAWMNldXoqI/d+33fr0XC0oZu+uZ9uEqywkYY0SQt1MXVRVzh+ceTt9tlglcwbSJ3tw6ER3mvweRcsfZL3rwvB3/lVV9MsKAlg1dYoUnq49o3K3gRYeAMR7RWxfrGxgsjwKvbAntKGCNZbNJWKtSxx/kRe3sHTCcjjkKka0VbxX+FU7GJpx/NZpRVRZUfm4wY51wuBNYSiHMlv7R2tUhYbURHvW1pFotjNC9YZ+DWgPcWcBAsj1894JV3bwE9Maa8iithE+QrsJk1yhQasneToZwCHxxKSYD2vqesRpBvBoVGG+HZxiiFSJ1rB4FcVPQOpQxd12AKi1cIB74NGKtxKaCTxmQ5BoGyHGVZ4pxbiUQN9EhltKgvRjEXUXHdYRii+MfasqKwNb2/RXTbFFXLZLzDxXvPEkJi0fX4LhKtpW1bnvzjG3xsb59SgxpXVMuG//NjX+B73n6TRd8yMpaDdkmN4fTJU+g4whpFt2iJaR9GNerECVTQK35zit2KKokLEDwmRXybdzoG6YdwCb3RqWiMoZ3dAm14+5//Pr7jHf8Jb33LmymryHwmu0Lv5Hmx76i3JnSLOUHBYj5nNJ2gkqMsLdPRhFnwxD6g+gA6cRQaoZ12DaPRhGXsccljy0IKh6VFEdjfu0LUhu1Tp2jbhq3piHJckoJjNus4nN+iqEpsMhSmFAE0lQCPC54YABfort/EKk1RFSxcR9UZtmzFoXNUdcXQcGbKAtU1BD1h4R37177Ee2eGX3n88/jtMRfPn+P3P/ssVFtcqAuY7PDK6SXe9foX0fVLltFTpI4Q9cqQZuCkh1XCtM589UA0IK0SuqFRTzLptStXzC5HRin8sHU3UvNSUeFV5sTftgisgrCSwH57lj88Ryd5P0lMpHOa4d7UucCaXxeiSGwIwy4XUGPKO4KIMoXAZgGMEm77sHOXnb7sKPRGDNEaQtRoJdn9NzpeGAF+qIgPtCil8EgGo5HGlAjYUtgiW1unGF8Ys3fzgPlscazoCXeGVIbP6duOvu2YTqcURUFE1AJVipS2ou9apKoOVVHgOuGVz5eNNChEuQFMJRSmQklBccD8pSiTsCbgExR4XIRnbs7Z3S0Zp0QxQoKqKYgpEXLGrmLEaIjBoFMkKC2rvwkkvVZJJPcJ+NBLRq4LtE70vVAaXdb1MIVQ00yU7SdKjAqMMQQnDAdp4EroIIVfoxQhDswXea4E+4g1itDKDRZRaN/mRi0RdtMp0LkOYwqqSqziuqYl2YQtJ7i4xHnLS178AKPxlKPlgvFWwc39GenoiMpYPvyFZ6kTvOaRuyn0hI8+/hQ6Rj76icd5+csvErZ3MeOSpmtZLBaySzAKRiXNfEHhPYWRLb7MAWlFl/1wxmVdT+h7UEihPi+GQ9/4ANMZa/FWlC6vPv4F3J9+B74NlKMtko0sl3Oq0YQQO5Jy9DFRW8OiWZC0Zjwec3Qknb1HfkHTLDCmoPWysBRVjbYWOx5DYTGtYNFFYeh7z2S0w/zwBk3TYQrN/MY+5dZJmnaB0QVbW1tY02JsNpU2YAsAQ3Ke5BKdz6qiuaAfSJSqoEyAsaSqZOoiTecYjUuC84Qo3r4nd2tMEzj94hfxtDK84uxDXH3mGeYHc7bGE5yLtAnKdskb3nIfpe5YWoNtlwQMxA1GjEKahFQQ2AZNaAPaRupih5CW0jUcvfQoxLSCZpKSrmKXHClKkAi5m3kI2JG0poIoJQVPWPHw1SAUmNIx6ROdc2X5G3lhUCvXtUGDCsjGMgEf08r3d6A/BhVZ9Uxq8H2irCJaFaQo5iCBwKjMhMgEXsleICoNyVMCNkGjhJKplCF9ue7Or3G8IOSCgWOCYiqlY5SjtWCblM1ms5kUMKKiLO2xLB2+fBF0c4i0a7ei8MUY6V27wpSliUYKhE2T2RV5DiXnib3Ddz3NQgpJvffYsqSsa8iaQ/Jd5LvtN57lwZJbR45Lj17n0qzl5nwJRjOuNDY5CeqhINETlaZPreB5Q7frahFba9cUphT3oRCyYJFfLTjHKGdprSszFLdU1qKXSRyJBHHIGbbQmd8enD/O/89SCwL1uKxuKf8u8vkcIC5rreC6g/BZ7xiNp7gAxhQYI4bgy97x5FNPoyg4f0Jx5u5dKqO55557GI0mfPCTj3F0MKd1oi+SgtBnvXP4vqcsC1zwNMslqWlRnbTf62yriJNzFL3w3sX0RA8ALyqI8JWKshCALH5FNSb0nqNrX+KpJ5+maecYZYlB52K/SCyHsBYkq6pKCstdT0w9qI4QOwINIUam9QSdNNGLMJUJiTKArUrqaowxBWQ9lP39fWH1+CjQjVU457LUxPGfi6IgKTCFeIEaK3IYPsqOy+T6wnAtA0mayFKkHFf03kmzlu9RWjOqa+q6Zj5bEILAduPJFj5KPcdFLxRenfjYEzPKUUHf9BSFzXWZtRjeII6XkmDkmxxxcWbPO6GstjqYsIRMS/QxHiMbRCVUyJj550OXMqyx9SEWSOZ/5+alTSBkM8s//ruYw098fmzJC4ne+HW+Q1eYPlmg7E6NmgmDzjvNXllaSjQJo0Cr/58UWYFVYUNn3C0O2FZMxFwYiQGUbeh7xeHBPqMJOGfQOj4vyN9prCvYasUIGVbq0ahCxTVX1disF6Msk8mEG3v7q+eqYYXVIiIVUryNxqiISqOVSP5C4qn9JU9cD5Sp4KFTmms3ApM0Yrs3RN8SZzc4uzXivpNgRyVdCtBHnFX0XaQ0+fzoQf9CrPqKQq1u3IHfnpKYE6eQVk0jMXO/YcAehWo6SCIPx77JnxcKpFtBVAor1yIkqmqEcx0as+JVxzjUBGThcM6vji0pcE3HyI44ubVLlxJN0zGbH3J0dMSo1LzjO76N737jYzQm8fGnt/jclz6ENie5+757+aPHn+B3Hv08W+UJHnr1wyKfEBxt2zKqKqLyol3jA/18gVosKSYjMAlty1zYliJq9JBCzEymIdgpCmVWHZWEKLs1ArYY8c63vJT3/4u/QxHHqInGNuJ9q7Qwm7QtcV6YS8Qo1zSUxC6hKLAFjMqTQKQJkpHrKGJnwSQ6G4nLJstNjCD2jEtD8D1Wm0xx9WL+bQq863KNRGodQ83JhcB0PJb56DwRB0ljjDASDHJPVVUFXgKpyASIxHFd12gSW+MRN29ely7kquBoPqcPgfFoTFmN0EETu6UIc0V43xOeV93jOF8luqMoFFlT5OOSjFUbvQrs0UPfecqpRmspEjdNQx0TZWUIXdZ/YR0YU9x0Zlr1Da7mV4K1fsyg3b7xnONc+XVE9nFoVFoH93VjlcrwUhhWjmOOcApNignF2l8ipUSli5VJuLaGgIbVwiXEkpQgqYjJn16hMCbSBKkJ1VbTfINyBS+cDJ7jzJR1R9fxv2ujUCrSdC27J89uaMB/fe8/TJohsHWNmE8rJeYDg0IlIMJP+W/DsFpTWmlN32xUGo5klQ2gQIHzEV1r+rHnc3uB/Vszri1ucdRAdddLedl3/RAH0/t44saMZ6/eAhL1dEJyM7TqjrVup7x9Wxd34qp4KiJZBcGvF7K4Udganr/JFlhJM2e9+qHxA4Sho7VdvffwXb3vAS3aJvmcKWVWsgNWGyk8Jsnaow/MZgte/NCLGZUVlS2oqoJJsc3Ozi5v/5a3sLVY8v1/9k3s3Tok9NICj5UCeEJx9cacx55+gubWPGO20DuHj2GVxQ4mJytxswTR9+BdxgjSyhVrcPsZinmbAWR4FJVlXBaU9ZTXvPxBHnlwyq39GTrjiWpQrUxmtSgCmLJYwS0hiIKiD4GISCakEMSSLrESInOuO0ZFNQq+73vfyXe+/c+A8lijODy4iTYK7/vVdx7O93BtyHM3xuxvoNfBqiiKVc2ka1pc12NKw6iq0UjXrjGG6PyqThVCyH0FAmdYW65gUaUURlsm0fGvH5cicSoq0d9R6wx68/5TSq147ILJu5VcBoj8gMIIffiYnIfEBVg3B+m0Yl2uIZuBDXPb5z6PDJF57ErLghA33mfz3pLfbRbu1/HkWOPUxttvitv5DZrfavPHyXMAACAASURBVG5t0LNjimzbyLecjbz+DLzj7Jh3np/wjrNjvtHxggnwq9VYcWwlHLAxjSKZgPdjfBB9lUuX9rnrwhnKslwLcN22BXre56xYLPLevne0y0Zokr1j2Xa0vSN5jesD+weHuJBQxkJVQFWgCgvWiIHxoOHuxCQi+kDIHZYaRVTZhz0pUldQdonXnB/z7jdd4B2vGXFhvODoi5/kV3/+n/Doo09yM+3w8Pf/VfTD38EHP/UUV/YCSW2vYRMXsoy5bAQH6QGV9Y+dC6sMZgjURhdsBu1BG8XYtdaFUXp18wxwzrBwDPTKoeNVa+l+7b3IvTon/w/JS7aSKafDDWxDoLQV3/Ty13DhrnuZVDXTsmQaLKfGJQ91h/yDv/sP+e//0S8S2jnT1KHPTdB6Fx86vE2c3N7mY898iXMXT/HB3/kwTdcyb5Yso2O2XKLRVEqaTRZdI3DNfEFctKiuRTlH6n2uPVhsPSIkRQgRFSLa+ZW6pBT5BfJQQTM6scV0Z8r9F8/yX/+l7+Jv/sU34JxfOXUlHEo7SCVGV/QerKlxLmFGFWZcEExFnxxJTygocSGRpmPsyZMUlJROGDM7p8/QZiOOS5e+xNvf8WY+8+jHeM///Dd58UvugxS4/twVfHBo0rFdI5DlJzyul92jj7Jz04XFR0frWzCi4990LT4GklEsl3Oh/pHw0TGaSsHYtw2joiJ0PSYlotVUWxOK0QhblfTO42NiXJV8/krgrl1L8AswGpciFGZ1PzvncDHgYpa4ttKR7Xwv94eK+XgVffBSpI3Closh+yBoTVRrv1XxBhCbvE3BsUETJmwos6Kez7jbDPopL/4iZbBWFIX1YjY8zwwaOymKMckKRpb3a5yn845uuRC5Yn9cv37NxKt45LTiux/coSpqtu2EmTbc7B1d+SegRfMnNrRaZXxiQJtWGcDwd6ssihYfIy4kYnS0S3HSIRWrTrOvFOOfx6PVUofpfU/XNcLN9ZG27ygLTYoWUoUOmjIWDK3KPsEYRVGPJCuqLKYq8dGLxZyGEBPWxMzljaA6oir5xNWW/aZm5CteumN5y0NbvPNNp3jti6c8c/kqP/Oev82fe+SN/MzP/Q4//O638qUn/xhtjFC0dCTGOb6wpCATuXcuZ3Uek7ftJom2tI8izqVM7r5LaZVJxiAYckrZdm7DX2bI7Ae7P6F9RVTS9K2TLC5KgdJ76Z6tyxHJiZvToKmtjAYDTbPgxM5JkrHEYHGxQvdHLD77GD/3ax/hqFa8/PUvYT6PeGu56+RJ2vmMN7zljei5I5ZyQ9V1SVFpCTiQdxPSodz7HkjY7B2rtKVzgdArtEsiNgbS65ICKNHflzmjMSGiNmA4FRNlVVFaQ1WMqast6smYV959H707IulAE3tccOjeEP0SH9qsTukJcYlJER0dlUqMbUmBxyuHUYGJUaTFHKUDjV9SW4NrluhxRSoN48JwdnuL++4/x4XpKf7Ku/+CsDWUNEH5mCTIp7Qyaq+MJrgObCRoT6kM0SlwSeoQvUchLktKS/3DotFREWLPwcE+OMHb2wBeWXyCSMDWBcr3WFXT9l0mKWj61JOMYnc78UxTMq4MLiZKLaqhRJlfSmVt9hTxSdM56UHQRnSaTAIfxVowsdZpD7nuZLSVeYssEISICxG8I+VkZMWEyddw8EE1WozulTJ5dy67t0IbtLKyj9NW5itS9yIqUgABYDQxyUNpWbQ0GhNBByncJrWOWYWCAlHd9Eq0/0kWrUT3SCSvI9BBENZULEockZGC8ye2GW3Qff9txwsGg5fVNq0w+KGCvvn3oeJdGMnUXOjYv3WTM2dOcfPmdXz7fKmBrzQGCpbSa0TOOUefekZFyc7ZM+ztPY0KiuCFca8mmrrv6EtDHy10DbqoqJQmOM+J7V1R3BNNggyHgLbSUh5MT9KKX/nUU0w0fM9bHuDwaMaWKnhwWvHqN57BFAX/08/+V3z6iSP+m2/b5wOXT/Ktj0wwB3DvS85ifSQtDyjrLbxzaCMBLSGyq7UtZGvosu55rgMMXZsD9DTg8ymFY1tS2S2st80iWlaANrIIaJEUXp3n6AlBs1wupdBaFCtmQiShC0uz13DX7lma1nPz6jO0/R4/9TP/jFc+8gj7quen/up/yWPPtmxt7XGhHPPULPGt3/lnmF89oHWe0zsnqKqCX/n1T/JD3/s2nnzySR580cNURYWyhtl8RllUGGNzcc/TLOd59wI9UCaL6h0UGt9Fkhc2xlCLsDKtcu1FFrhRXa8sEH0IxKBZliV/7z9/Jz/z6x/n1iKxiIpy2+D6bPyNIyXF7LDB0Kx2PT46bKFQzlCORsxmc6IPdF0DwKHvGI+2mFJhfcSeHfPYpUPuv/Ay/vj6Ne45tc1LX3SaZy4fsDy6SVVb5q2mIhArUQK1ZYG2ZtXG74goelLSmKIihrUqqNaaxeKIne0T+FEJi5ZSafoUiL2j0gnnWhoUdTFGecXCNZTFBB9hdzrFtQeoqIgm4TvFT3/gkP/x26ekdJSpwnJP9i77GmSTGpMtGEMIuFbMWkII9L1DDQbbRhMYIB25V73L925Swi/RmpCZaIAEfCWm8XGgYq5iCKDjCi0IKdcHhsx8mM5DNBhgUavE4AdNCBGfEDcsrdD5c+MKhhlqcNKsOco9AkkLDVVrKXzH7NppgUvznvO7hrCsaVAQeroQ2ZqMvqY49pXGCyeD53jle/P/wxj43SuDhrydrqoCW6iVR+lXcQj8sp8b4xpza1xHClPQkZ2dknpqueeeUzD3LJImeY23nrIe45GM3lpL5510k66KNGa1qhsgOaAwFPWYRdIcXGrZtQWLClJvuakbbrWJbz15Fz/81od5z2/dy8vGP80HP7KPfvXrsJ3BVSVFGGfFxnAMm9dJcOkuwypaiVlH8BtNGSkJlHQbrj/g8gMDZi1mtmbgAMcYOkMTlHMdg8HGUCwfcOEiBLAw0iPi0hGV46kvXOJPvenNvPt7f4BqNELvHbG88Xlc23MY4cGXvYRvftPrqe6/B5WgGBuKlPj0F65x7eCAp596huVySbOYs1gcoZQwQoSpkZlAUXYlIXk84mbVtw2da3HO0Waf1K7rsqBdQmuzelhrKHRBXdQZKhTqY12UnNo5w/e++WGaaKnQJJNrEZUVfZJcG3Kr4meGB0Jka+sEQt+0K1hIa82J8RY70wmt8iyT58UXH+ITv/1enrz8OX7rZ3+Vv/XX/zZPPzOjazyudRze2qeoapxeX8fhHFhrpUCqNCp4oRv7IJTZICqhVkvBNYRAcgFVFXTBkzontZSY8D6urr3zfT6/0ji4aDtU/sxBs+i5meHSoceHNRR6/J7O/O/IihMfXD43OZkYxMMG8+1Nsb/B+m7I1IemIj3sPDfoxCbPx+H8bnLrh5+NWSs4Ki0Po4Svro3CWClMqwxgGq0ocvY/FHRvHymllQm8SREj7V0bMWHjuVgOHTy3MJRVoo9Q1YZ6bJhMv3E1yRdMBg8DNsUqCA1jhZsraa5RKWeiRuy9rl/f59TuWa5113OQ+uo0yc0hrfzrZgspVikKbvCKe+/CLw954IG7mTW3OPfwXVy4MOYPH7/My+5/mMcuX+PS9ZuS3epACpqiLGXCWCNO8kq460FHwGA6TzTSGPS+a4fwzJLveeldFCcDI07ikueojbR6xrvedoZp9R4m534EiPwX/+Sf84P/2bv5kbc9yLXuQCzv+h5tBr4vqyYPa6ToGXwUMbMNfRtrLSnLCefOpNX5GLL+IfOM2Udz5eqUkjg2IYua+I/mrDGB6/oVjp1SYt+UaG+4+bnP4LTlN37r9/hP3/Uu3ve+93H4xWc4unXIw+MT/Nwnn+DPvfP1TEcl7//7P4pSMG8gnH0A1cq1XxD5/Ue/wMN37/L+3/oA3/89/4FkRNFzYvs0Xd/inDQQKS3872Uzk4Yin0TGoBPWTPQOozWl1qigiHqU/TXXqoFGF2iVmFQGnyLORxgrynLBQ/c/wItPPs6Tsyl6doA3FucSGk+IUNUljXMU2lCogna5pOuEC29Q+Fz0DK5HG+Ged67DpkBsPJ/67BM0fSNNPV2iqizluCZ1gb5NdIuW6qSjjaJXJB2xwnBSKXvBVpblvKO0lkU7p6xrJkY6mukcZVJ0iyWqrvFLkQ5OVlOkhGsDtrAorVEENIntaooPnt3ds7TLGZGAKQqS74k6UdvEz39qyV9+7YioIq7rh1nJIAGcYiS5hPfgfW4O8mvD94GVJSm1XmWhMUZKrXI3aQAtOHyRVSqHtErkCIa5LD+LAmSuyubu8Zg7mHMvOUMjzrCwyGJgiHHoME05yOfCr/QkPh/HT4KIVUbR9T2mLGmiSBYroymMlnmkkJgQNJ9+bs7OA1tY23Gjq4lN5Kkbe19XHLvTeEFl8Jvj9pMG4DfYH5Cz7Sj2Yc0yCPfXGAYc+Wv5jM1dg1ABpSni4oWT7CyOMGNHmxJ6eUQ4PES3DZ/9zCVefmqKa69zttKc2d2iVnIs2hh8Lw1PyhgRIsp0T2UK2ZtlhoEtDMVyiTbwr564xm9+9CaXbnRsFZZb9EQs81szDg4O+L5vvQuzBR/51d/gf/vZf8QfPvtFQoKu67N9mWxbh69+jPcexQgE1oyjIVBvns/bs/n1NdCr5w0t5851KxMRay2D/ryPTjw1FdkIwuNnM3ZPn+HZK1d57/t+k+9/53dzb+lZ+MDEWPwy0c6WfObyAUUr4lPP1jVf9IbnzJhRvUVVWqyRBrjPPnud0+fPcvXGdZbzBW23xHtPn49pkKYY+NcpKXwvHH+XIPlcXM+9EE3TrArJKxmLwqJNgSkzIySJbeLQdVgZTaEK3vaa+6nDAmWk63jgfRuladuWUhmaxVLUTL0nxrx78j0hDh3BshOaTsc45yEkXNvQzK7i1R56uUfBLfxijykLdq3UDxKwmB9QZmrrsOvqe1GQtNaiozhT+T5IfSF6FqHHV4beQKMjvVWEbPaStKLtO3zv6L3D+R6tpFmOkFtRkCJ/s+wYnLpCsiRE6/7qTFEql88lx+dXvF1qYMh20wozHzLwIbMeWF9aa+km1aKWalAUUepQwwNygjg8hp+JK7L67XN8ZdCdUsb7Oc6OGZjJWtg/Sa31bDbHUPgVCRKwWWhYB4XyccXZF1LE8CJJnJKCR2/O2U+aURE5WSbecO/u1xTHvtJ4QWXwwxgu9kBDGk6mzn9bSRugpPgYFQdHc06eOsH+3tGxreHxMTgjbXxWTmALrQgxsT0tee3FmtmVQ252nm9SUJw5ySef3efKPPKtL+/Zsoq2mbF/3WHqCd98fpvuxIRLfkG8FbmaOprDQESDhcKA6kppIrKFNG0kKcJisxSBVhymxO99cZ/feVbx5196lmgjYdzT+CnxCN71orN84JO/ws/+yv/Oj//UT/Kvfvxv8NADF5jP9wmukIISHlKiKEs6taZu6k6x1A14EQNLWmFz8UprjcsZTGESfe+xtiSltKLiDfCL7yMBjy0svV9iY4W1cj38iqQQUQZUBK0NbXSE527w7FHH9zzyJvaf/AyPnd6lmM/p96/TEHnlT/wtbhzAU/OW0rSYoFiagI9LSt/SBbBWce89d/PFy5d45MF7GNcl/+ZTn+AVL3pAqI+2wmpDoUQqwVQBbY0ErpBQXlbCQMIUY7arqcBVsScZWLYd08k2Pkh+52LAqESlLX2lMUHRE6htxbS2FIx58T3nefd3jfmZD1xCuQYzqilbRVGNoC6oqKCOHC3EOk9rjTIiR+xiT6EN+EjykcPFkmoU6btIDLc4X0KKlmQjfRBM+uAwEDEUNuC8Yu9gn9NGY8oJwYmkc9c2NKaly+qZ1ip632GqGq1KwmJJORoxqka4KMX2Qe3Fty2TaoyLgcpkSCQEKTRqhQ4dfe+whaWsLDiD7xaEYkQRswTGEZysC55dBlToMWaLqKQoXGYpgZA09D0hGlLQzF3LsjnicNazfeIU+7cOUVaSNdHuj4QY1jvNzKYRPvkdnN4y53EdqNe57LBBGLpciTrrwIS8i1fomE23lSxAQ1zSSqHyoiJ1gQ0KZKZsKgXJCMNGaUNM4FygLuVYTabnq1wj8Fn3fX8O+/OOu2uHsSWfeu65rxIpv/p4QQb4r2VopOiSUiSmhJD86tyG777Mq56f2auoSKagjz2YglffZXji8pwbRxGnLfO9moPLt3BmQqgcH3oscGHiOKc85TnDM1fmPHD2JL935Spb9ZRXvuQM3ZN7PPiaCY8+fYvFQtE7A2WHzo1URYYugvOkAU5Sw8X2jC18/NlD3vjQLqkXqd+olhxGz1vOncNQ8Oivf4jfuXRIO6p55V0aZSEpTXSaHsEilRO1zOA9vVkQlyX1ZEL0HuMTSeucYflV1uPz7N+k3wm3XYqR0umbVhmVHHMW51JZ8Mx7VESEu1Ki9TU3woTLlz/Pq85eRKcZfq9mWtb8H+//IPudYMave+A0y/kh9XhECiUxdBijcE3H5MRpnNdE7em0IgbH/Rcv8P4nvsC17RNMxluyc1Iem5lEru1IWlEVJYWxOO9JyaMUFEY09mPyqGCECx0DPvSQ1nx/E5OwIILCpYhF0SlF1AXKeupqm3O7lrT8DKrOLCJr6btGGqdSossNaINdYdd1KAU2m0xEcoPYpIQQUS5BmqB2LK++5yJBBe65ewdjek5uTajLEeeqyM//8of5f56JLJtDxqZeBTnJ3jV9iFRlRd82IvWhFG0nRutN1xJzjURLK7LAcKaiR6i+xIQtJClSauDWa0aTLZbLFlvWiBtYh8kF/eQ1xShy6AyF8vQoMWAhQYwoY7L8b57zUVHFxOTc3ZyanIQTng9/5EOMqxF9kMC3uZtccdC5Hf++c/J2OxIgRA698Uy9TvbjGibWSqFV7lwf+PEMuwNyc9Nw6x6vHQ7HR274UwqMDvhkMViU8qgNg+/N4wO42gSSav4dKNGAunOm+yc7lFJpoCetxgaOvtlgM/x8rGmCiDEFW9OT1GO4cX2PvvfPO4F3GkbJTf7qB3aZzWZ8YS9iiWgzxcc5SVWk5LEpgFH4WFDlm2e3DiyWgfNbmrdd3OZjXckYQ11ErrQa2x9y60AzGjUsG8O+k3Z4nQO8UhvO8WrdCWejp1Mlrzk54cF7KnQVme0H5tpy0DZ0s5bPL3oqr9GFpg/CcjGi8IFJiaKwmCRm3SNbUhSBl9+1w/bpsXRPpkihK4zVq3Mo51bW/BWmPmTufuhKVRlfVwxtJ9K5uu48HmQnholflpbLl27wq08ccX/f8NN/8Qf5g0/9PubEDn//d/8APx5xV9fwt//Sqzl5zxluhSX/7U9+jKg9sY+48YjkSto4xxM4XMLf+aF38uD9D3Dl4JBLz17hpffey5kzZxiPx0y2pEHEO0fwidFkTEqJE1s7GKUpK2mlR2frQhREgXDkuxdU5Yio5DygDCaIqJ3rGjrvOJzNWSwPaZae5XLB+/7gY3zwj/YpyymdDvSuo2s91UjqMS43JqUIXScCbkeLGWUpUsPee06WOyzcHov2kB/94ddxOm4xpiXpAlOXGBUlaIYS3c1IyfD9/+C3cabg3Nlz+Cg6/FVuZirqEtd4gh4gDktdVnhS9t+t6fueyWQidoYhMh6P6fKC7ZLPvr891pb4CKXV+Aht75jPDtmqFDeuP4ctRlR2gvMdTHrecm6Lt9+74NYi5m50D8rkxDoSg+bwMLBz1nD9+oR//PHLnD8Dd09KapXoe73Splrt5lEsBm/hjYx9cGPKgUP+e1t0XHWoBlbhPaTM0Y+D3ozsrGNmwgwxSHRuBMNPyE5nKPCKZgxZE4fVahAj1GPRFrJaWGU+aXQBy0ZxbX8mi8eXiUkDVz4RP5FSet2Xj2BfebzgM3h17EI+f6Ucfo4xslgsqUdTnHdobe7o3jSMYZGISWH1iL3rM662GvB4C/g5BrBFoO9FtTlGBamn86BUxUGTsKXmIRv5pcfm7NaGnQk8s4icOn+GG3PHmTNTZsuSNL3FpN8GRAen7zrRLoe1ap7KlLJgwfRc6wu2jzRXLjV8fn9JSkL18zpy9swu3dGMqhBDBwOEZEEXRJOkOAgQRQc7JM0fXl9y36zn4n2WgkrobXFQxByokj4H63RsQYWh6GpX9DYYGAuiiidFq4TJ7lVDm7nWJd5aKt9wydS855f/BYcx8br7HkIrw2Te4BV0xmLNhHGZm65ixCooY4tRcKIS2lydCg4OOxaLhjOnt5nP5/Quii5N6GkateY+Ewm+z9rwgp+KrEQS13stXYUJjdbr7+y9B6Ol/yIqXJLegqgFJzamR6XIaFRDjLz0wXt49Au36MsJi6MboKCsRtjsFmWMwbUdWomUA+SaDbJD6vuepW7pteLesuTB8S7z6zf5YutoFw1fvLzHwdzxzM05B1TcPOpxXY5iAdpmQVmNcv2gwC2XKO8FJ2PAwT0pWbSSLmxCpDQW3/WE7P4VQ08wQIiE3mGUaDHVtRLJB++ExBCl9mKtktqITdgE0USUszx2ZcG33y866CH5HACjFGzTej6FAFtqjz/14AirIovW4auKoMNGj8L6vh+C/WZcuD243x4rhuAuzzsO38o8Pf7aLzdk15ALshusmPUT1G3PzkhDEogrRUfyoHPY1aZYKbNujkEx899F6v3CCfBRtoGrczQYYoBsiUgovb44x2UMsuZ7WLK3D7aUreIdxYFWHycX9PS2o+k9zy4ki1VoihAxBdRVTWUiodKUFUzVCGMjpQuYUc277r/Af/w3vo+mK/m9D3yCn/zN3+WPri44c+oM7WxJNa2lc485qUkslvMVhGHqSlqq215W6jhkFYnaWkKAm2HB4vICV5RUlaUnUOjECVXwuhc/xCc+80ms1niXiKUwdqxXKOvxsUVhhbFhNT556tGY52zJ0ZMLXveKu2i7meiOK8VKQ10ZtFln5PqY2QgyWZOYhsQgk1dsEzNGm/nNMUWK3CmbkuMLz10hAK+9WPN7zxywZQse/fyzvPXeHT538wgTevom0rolKXXcPOgplCYE8FWkTA3BwqhWpKLgxuEh2zcPeO1dL4Vzib3DOfW4oq5r6rrEWs3R0RHOOZpmwfb2Nm1XUJZiNF6WZa7jpPV8U1pce3JQ0FlDZZgvKSWC9yJ9ECK20DSdo6ws53cv8B3fPOPXr49Z3HgOg8dOFE0TVjdxUhptzErlc9D90SRKa+jjjJgMBybwv3z4c7x0u+D8mW1GO5Z7QuLWY3/MSx44TXt0i/2tQHSBZw7h+syxPNgnbW1TjLdZNO2K6dF0opzqkmSibd8B5BrLWuQrdJFRUeLbHlOXhF5UHX3v0IVFWUXfLpmMarpmiVeWqDSHiwXVdAvlA003RxUl1keenvV86NmKV40TwSRQpWjfAN51Kxgs+MTc1hy2C7aUBlUSWxFKG9hwMUYJkClfLaVWi4TEiLBxnx/XWx/YMHKtBff2yq50aySwr/2SV/9PdhVgU/7P8BE2rXfbWgsMF5PEpxVt00DrRDeIpHAp0HUCzfTOCYPmDsF9c3y5DP/rGS+cAM+6cHo7drb5dzgOZ0jBVYR8lBJWyXRnzPLw+XYog97KACkYo2jmljY6KptQhRHoISKF275HOdm26aOCL9kFJ0+eI6mOdBD4sQ8/zS//0C/x429+FfUk4uaWf+/ee3iu79kvax6eWn7/8cuU4xqrworjG1NExYg2FmWt6JIMHZRa0yqHAmyrmQdQXY81ikoZmkIoeO/9yMeYGChHgI7orsNqQ9CgVS1KibmphNhjTUXTLRn7yNXZjOtHB2wViBn4hiaNdAiy0pI3WfIAFda4dKZfGp2DpFrfQC74zCbZwPF7w71nd7nrvOWld5/iM88suWEdW73DK8eoNNQHJV0/w/tdGn/AD/zgdzIpNdPtk+xY2KoU1aSiVlBMTvKLv/CvWXQtqYfKVvh0gM+CamVZUhTSsdi5nqef/Bxaa6pRTYyWohCdE61Fj4ZcjE4MTIwNdlGIeJOwURMU6BjoiPgoNotVVRP6hqoYsTMd87oXfwu3rtwgLffpY48ta1wjsIK2Bl0W6OjxfqCgxhVzp1KGmJZ896texDvfeIHF/IBClXTtkmecmG8/t3eAMwWpcyRTcapwzMpIdNAsjqimO6KymSK1Ga20akBULvu+x6eIVpG+F9hNW4vTiUorolZgFEFBjaXzHVRZvkFp5vM548mUm/MGbS3ewbgeEWdzuhTBG6wNlKOCz11reMX9GkWB94kiHQ+8IURCUFRKEduedmzpywLd/3/cvWmwJNl13/c7997MrHpVr1+/3nt6NswAg2VASgAVJAQJJAWCtEXRBm2ZkiyFrXDYkv1BYUU4vHxySHY4bMmWLIdl0QrZ+iBRCtGUZJomKQYFUgTADSCxcQQMBrNhMN3T2+t+/ZbaMvPee/zh3Kx63egBsTAUCGdET/e8qleVlZX33HP+53/+f6XJJ9lwX52tD6P+pkWjJx7T+553cu3bzzNIhQBZk23oIqU7egLHH1g28pDNgk3gXbNxTm4HAjkHlm2kVxNx6zBnNmP7lMr4YVWA3Sj2noUE8a0c30YBvmBXZTAYvhqeOXmhh8MuuiuuKDYldn73UZbNbfZum4N8xiA0nxUqLbxek5xdZttN2wikVAZUYEs9tRpVS1FGQcx04O5NtEByLsDrt6/xZ37+KjHDcVI+c/2AqvL0vXArKBfPnOX86S0aMnl0i3TkmVcOlktiVUO0TFtF0AbcMlLVEEbWnBpy54QiLlN1oDGxUwWqkelb166CYfhChswnQWXBzqRLlcaNaBNo4/nCSzd437sur7MkRypaXPbhTCTNkbIFJxsis3suRiMA9yninRCzZYUuVcWw2uiipjSYmcfIE+ceAY1IJ/yJH3qKZnKKL3zpNS7sjGnzbdpWmbc9SR3LWeZH332O3G0j7oiEEFxAnBJUcf0xufcsAlICJAAAIABJREFU+hV3jg7YntZIFBbHC8b1mO3tCSHUbE8nLI5nvO997+PV164xjKnHZAqGonbdc+zszlNBqkDKlqWrmlInfU8q92KXe+ObuxYJimiLb8b46g6PXrrM0fnzPPOuZ5ndu8FLv/Mc1GaDGOqKxWzOKCaWqxV1cRar6sCyhWY04riNxFZ46tKEvXsr+pVQVT3ZhuLxCuPg8TnSe0+XWra3PI+5wJf2EpWD1M1ppjvkmEl9ZDwerwe5VOw+curIfSbHDi8VWR0jdZAjASUkq6aTGN11Wm9ZT8Zn2pnp5Iwrs3OcLYSKQO89tcss84xlhG0/4oW9Fdtvyxx2duMkB1kFCMQcSQoiFUqRKcmOqjXoL5I2MynFWCfnTVarBXpKQhGPsxgyVF8i3rTfB7VUFMSbQgUbkgA4Y8kUDF3FmVezkeNL1j8w4Fkz+NKG52ixoNg9DU5S4mxzcGr7hio4TcUgRIhd5IR3yP2RMKcTG8a3dnwbBXg7Bou6kwMED6M93oexlcecCCl27N28wSNXzrJ/9xhVc31yzpE6oDesOFOubfkiRx4qHCMEl4VZti9gRdlDY1em2aQMRVDMeB2jLuJyZuwdW0FZ5USShmUlxDNXeOnONaZ9y7NXLnNwNvA7X/oyEJgs56TkiBXU3pG7SA6sRb8AqspM5SoVJHjcxNOMx4TJiPkb13CAJLse4oNh4L40swa8UgVxrmQLgnjH0aK361U4yAiGQeuJoQ4p2Tt5nY3f933o/UwFzZk2dmYNmMxFHgzKVkqmlGHbCyyPeM9bzkHK7O0JbYGrJB9yuq74jU9c53B+SHd8zFGfuXfrmKNFy42DJTMVfv87zvOW+Cjz5QI3BgnWa4gxEpzZC0qG6WRCu+o4Nd3amK2r0qeML42zAS5JqUN7U3OUAkWNRiNiqVpUdd2IpYdGFVxtbJQUaPsl452zHB3e4oM/+H28/PwX1syLdrnCQQm2CVHT7F8t203tn1bEBDvThmgRAY2JVKonh0kM9IsWEbtLnMBWJVTeqHvzw31G423j7KeNnMTA8XdVKHaXGylpq2SGa1fUKUPAe4MtY+yoqolVb1VN23drMa+276gqM3lXNf0enGWmPlXEsCCvMr16Gt9BqizpymVKSDwulPvdl2rSuxNdy816X1e55WebmPBgQqjritLMQMpLOWPdWeB2myBaNovyEFCm5tdwsJDJqJP7dN+HHLw8qUgdlHPBI2JCZ16ELkNvP4UBGPwaJJA3p3p/Y8e3XYDf0KFOZO/l71xcaYYG3uZx20WTJnO+WR3x8pdmpCH/zSY36hyMPVSlYSYKh2qUrS5Di3Ks5Q3VBGpsKEGpnNBpum9fTVhK0TvAO1YJxqFi209oRsd0+zB74Ysc0XNUOx5/6nv4gWffylP/9H/iN9qKW1cjPoCGnj558DZ9anCTsQiiZmtguuLq2HasVnNkz0aaBypj0kxXxLSkBGOfPN45xqFCnbOsqVD2usR9jVTFLMg238MgugVO3FdtthudmrJplMar99Va4XKgnEk1QjXhNILaTKRzZknYtjYIMss9qw7muaJ2PdX2hO3Tc3bd41A7tvC44JgEh1fPP/iZX+Po6IiD/btsNTVVM+be8RE4YftwznYGN2movGPSNFx4+ik++dnn8BdqmtgzHm+tB7VEPF3XoiQEMwaJxYqw61c4hapqyn1UNjMHsAV1oOsjfVzgJPDpf/KPePn5q/zqz/73PPGet3Lz5RfY2tqy6ciU6LqWatSQcrfWoBmNTK9+RGSZMhWRVTSVcJGAl6Jfkm2DsM3IKq02Jrwk3nImcHU/ElW5ee01HnnqGZIENEZiTuueQxBH266ofNjQXFtjyZjIn6mHNk2DKDRVTd+29Cxo+x4fKrrVEsmJbrFg1NSsFnO6rmNra4soCc1CLz3npoHX24qzIVL3kTZKEeErf3SA8QbtIku9nNpn1SFQD/efCcyUHk+BWSWQ78vSwaug5E1zNW8Skvs2gZzXVYIlORtc3+z11oEHJ1LW4rA+pLzG/fFrqBhcTtQR2gDZZbbE0yt0GtEsv2cB/Hc7vm0C/IZrer+X4vrxoXOuD9ndrGbDY0MJQRyNz3QJXOWIBtLQ9cIc1rALgKjt5LLOXG0b16LT4YfkKr/Z0K9Doy0M5xsWbeLS+ZZ7y8jpsyNylWlvw7gLfP4XfpqP/5zyS3/9C/xo938wfuV5/srvfIF714Qv33qdpqrQ2JvAUsHFfYGMUI9GY4EgwnR7BJUJnNln9oQyji2DepoXxAudzzDofpTgJS5YplUycNMNt6zQIK2BKmY3tvMbxo2IrJvFztmQyOCrmco08CBtgCZivzJedmypqjG5iHuldAydZZFVpSzampBnLP2U5BeMWsc8An6G9o7shQPJSFXTNvDyF1/i8oUdrt7e4+zOhIPZAi/C4fTIuOactnuhdqzu3rHK5eiIUKZMvff2ub0jxg7NHZ5ETJmu3Cc4SDGt9VJ8CRA7W7tkepZHHT4L12eBz92d8ZFPvYhUPU9/4N18z7O/j5dOjfniF79o8svJ2CRSgtRkMmG5XKIqpK4jxkDtF/RdJiul0dsX5k+NqjVE+wSqnQVrl8gK21XkibOeF/cSITju3bpKM91lMtpiPN1msbBpX1NBHETwrFkeUyLGlfUmMlSVwUddMkmKmCH3venpJKtmvGajZYYRXWsbSIydrS3n6FNPG5Tf+bLjh97mOOqUoL5MBSdOslkGD4FcMJiUkt3vw1pHwJmrk+ZBt92M6wffUl2v3wfwcYrAjFAokEND1lkQB5ungTWJQ0scUB0g4CJFfIIkM9AolQ3N2BIf841KorReWHZl81HrbWVP6QGa5k16cIc4ce6/F8fvGuBFZAR8HGjK8/+Jqv4lEXkL8JPAGeAzwL+nqp2INMDfB74LuAv8SVV97Xc9k3WGeKI7PgT1E///sH87Ae8VItTeMtgFglQNbYwF8SmSnu5EY0M3dYDam0MJ5L7cOKNxYFZ8SB+ExWxAwhYjoSKnlqmD6bjm9T1h0jjqhWlHL6VjCZzeHvED/8W7OfydBbenL/D7Pvh+XrngeONgxKpdgVY46deOUt5L4aJnHDCuGiQIO6Mt9g8OTd7YmwpHX6iBDIJJCpKs+kgB2jYajimCFm50LsB6Vi0DKcOiKvS+glvnAk082AexRbmBy2yhGOhologmnZcz5jGrmdwt8Q6ir8A5ovekCF4dnXi03WOHy6xaT1MtWGZP60CDxwmMVJg2E67u30Z8MHGs2FJ5z+zomNXpJV4cx8dzxnVFqEa0q+UGZokRfCYlX+CTmdE9c4c6M03WsllpgbCCmGaKCwEfHF1OBvNMG+4cR/75S6/w6V/+Iltve4Sj23scXNvnN1cv8UPf9wf4wgtftGnhLq0NN1SEPie6LtLUwe575xiFqmDNFrpSNnlcS2qgKmqZ3rmiMQ6o9V22nBKAZYQclzjfEEPNVgg0TbNmQw2mKEMiZaQFt9Yakq4vZisVkpLZ+PWtTfY6w6g1q2m592ndq1itWtQHfAggnhQdN+eRVnskCm3dE7Lcdw/ZeWzMdWy9CyLuPnhJyqaU2SR5Q9P/Qfq02WQO0qCuSHmYmqoWcH3I6Id72BLyr04qN2t9g+8PImP2rkYRHsKUFFzd+wrXRVoSiFj/z/thdy9VyMNp3L9X+Dt8fRl8C3xQVWciUgG/JiK/APxnwN9Q1Z8Ukb8N/IfA/17+vqeqbxWRPwX8VeBPfq03EGem05qsTLvvOpcv14kr1n0lo6UY8xYcOGcrmxdDwyQJly8VGeEIDDfWA0Jkm/KM9U4sDt5Zwecj/PC5GtdGfvIuPOh/qwrqAkJEY4930GXH1cPMI+cn3JnNWPagyRG8oNlzMFtRq+OpH2o4feMv8fLejHgOHqmEdz37BB//l2+QPah6tI34yhE6heDJZBapJQTPESvUe9QJsZyLQ0k5Epw1CqtQr9khkjFvMk0Fkipeq11Ei7lvEE+MveHXwRd8BvocSwPaITrc6GrkmnJnx/KlBe/XUI9l92WAJJtUbO5aoDTFe8uWnbb4BPurY9JyF1819L2jE+NtWxWV0d4Mm5fScXY85o3pOW5fe50Lj53ncKXEeY1zcO32babTKefzaU6dOrWG6mLXkpJylATxEFyFeOtN5Lhaw3h2fkucC9QLwY8cXaWoOoJ4wJrF8wX81z/xc7z85Zs8/j3fy9l3Zw5mc6489jh3bx4wO77FJ37tLod3jzl75hTboy1WqafXhCC2AVYVMUcUZbFY8gNvn9LFlWXSuSLXJn7mtEUczGLLSjOjqMxLYPJAlxxVyLzljOfWceJedMTZAd10i9t3bnN6esq0aYqJRYxx89lzpioBKqEEJ/jskJzplwvLnmOkDgFfB+KyJTsbpuuJ1MnRVBPadlkmzDM5KSPXszeH+cJiqURBQ/FR1YG+CORClEi2xtQBkpEh8RCPpoh4iH1NqG2ADVeT8wqHL5NNQioG3DlSZleMKZOzkS163cCNKQ/Z9YDlbIYpBzDW4ovFmVjO1yqL4VfSQ7H0SlsUbN1bwQB5w+3XE5n7w+Z73qT/+g0fv2uAV3vX2XDe5Y8CHwT+dPn53wP+MhbgP1z+DfBPgP9NRES/Rs2hWTnJM60qT+xLtsGg8mg3csam0WwoqIAqWddUVt28qCkpfo1hJztMhcNmTwQROD8dc5A933kp8it7kbsrRyWO/iGUJZ9AS0MlZwiTzNHhiursFvPC1BQgJhMM9UDnPPM9hTP/DRfOn+Ev/Ngf4w/9yX+Dn/2HP8vbnnmEF1+9TuMDmqHvI1Wg6MYYRu9wdLPFeq9ylUmaDq5WlCDsyjUSgZw24mJS+g9rOzJNlpU5GFWNLaqENaOTUSWzOKzbYT6ZTtz6fdaXXJVe4xqusRcvsM66QtP7sjURKUYLyRQes1FIhwzTzrFkXTlbIw7wekR96jyrWNMfO3bP1MzHwvz4mGqWyN2K6djgA3bG9p4Jcp9ZxjnVeFRyZCHUwcwgsg22kZSVC7jkcKEiRoEgSO5wCbR3fOSFO/z6K6/zyu05Z579fcyvv8brV29z/tGL3HltnzNvvcDs7hHX3rjG7pkdYkxkelKK1M0WOSZCcY3q+x4FqnHiHVcusnv6NH3bsermdKkm9Us0BzqFahnIlbIUpRWQ1oJRRonJMwmJ3RHsH9n3vlzOUamYL5eIDzjnUQbIzcJYVoheGPuwbvB3Oa7vkeCr+6bJDSbqzV1MlZSUZWwJoSY7MZZV8CSFPjv2+8iuKL4PmOmWLfbh+xUpdphDw17FTDWINjughnl7gZfvJJCEOgcai3hZWt9P2ZYJvlApBq+zdU0uluDosDABXwK401xwfPNdHejYQxW3xuQBV7B2b5nheh24ggV1mLRwGH7fpOcZvF+dmOIkwloPa6gIeDh58ps6vi4MXkxg/dPAW4G/BbwCHOgwKQHXgCvl31eAqwCqGkXkEDgL3HnT13cDdkzhXbO+mGamW7imfkOVWpvXahEkQ9YMnIECtVgsmE6nHB0d4weO90NPoPRvtMiixo4bC8f1peM7LkUeaZXn7ny13RdAkgg10Nd46Wh6z5VHd/nKrbsMXOtMBO8t04gKvidGuHswpvL/FX/tF/8i6cjxX/6Fv8xf/7v/LZfGDUdEVn20ycespKrchMFTNQ1BhMViYRWPiGXQ2Ur5UHjsLoFkEzKLRdnRXOozORsjJEFpmG5MVoL3dMMG60z+l7pCcybI/ZaHJ3H5dSZCqYyMd4mKrKGfoWGmqmQSuUBiKo5V29vUqbeBIii02ZLx5GwwFSKcu3KBe5+4irz/z7A3u8VlPaautqnO7HI4bzluV8jdG3iBrj13H+e8aUb4GE3oCwi9BbZ61JO6xvoDuSanTLOdGKtw86Dnrkz4hV9+kZvXbnEjKn5nDMnz4mdf4EMf/l5yE7h90HLuyV3mN+7h/Yw+NYxGyuzoGHUGDzWNmczUPlCHyiZJY6RvK3784y+iH3u+ZDPCO85ucX7k+eDTlxkF4TZz4gzmWYgdFujIuABO7TpPt+Bsr9zqPOngkN0LF1m2S0aTLWLMjOoRTe3XCqM5JkQTs8UcdULqesbNiFCF9ZTtIB09nU5ZrBZs7WzTzxZWgTnHYtWzc2qH5fEBkOj6zDEdxJqrR4HzkyU+VMTUW6Ze3I9yzgydyqTmMCaUqWkcqpFYNvUOh0rE+SE5sWBQOS2MIl278iVfxMjUmraWPsBIC39CN/IFAzHbBQhaIJKS7EHpx5X4og4yzqoD1SIPImsmjiuQWaWZCoPMxFOq8kEwUUzfaJimz0piSE5/LxRoNsfXFeDVuiK/X0ROAz8NvPNhTyt/y9d4bH2IyJ8H/vzw/wNLICbDgtcvcyJorPlOzq2DjKgFM/SBxkRxVW+aBvIxroKHxfc1lgxQ8PSjVWJC4lItfPmGcHHbg4sPv/ZqWZSKklxNlC1evnYHrayfIDnajGhMJJcQKogmKyCSianl+BgemQT+h7/1l3n/936Q537ro7zl/AVey3tkcYQEfTJmTb/q6ZadBcswaHBYAByE9nJVfNrdppRMahMGCSt7zfu2lLBrmCWbPGx2ayekLBnX2PTngI+e+A7Xfz8Y7DeDGoCYoJMvGeDGWV7IJzaHlIZs3fTnzR+TQkUbTMHtPcZ4Lp2/wK/+s1/kve//o3xltmTXH+Dqhkkzok+edhUZ1Q2zxZyqqhiNRmbnlyxz9WHQObLkou07pqNdXCe4nSXTZsK1f7nHYVXz/3z2RQ6OVlw9WrFynmefeZJXfvu3uBNrnv7Od/DcL3+cWwcr3veDf5hu74DV+Jjp1nmuv/Eqi9kBwRvzZTo9xWq1MiZMb8Yafd+jTvGuRbaFiYNlttvtS4dzXrgHn7h+RN3DpZ0xkyaaTaGDkVdSKvFFo5nNxMTl01vMbs+ZC0gsVVjOVN4G63Abb17owW20kfqYSFXE4ddBeMDqu67De28MJDUxMtVBMtq49yJiomlVwHvl7jHIWIh0GzSj8MWNw66bpEA3az8W5Uk3YPZZGWFQS5njY5B5H3jszvqx1FoyZzmhJw/oIBmMDsPyZREXggcDdK88GLZceWp2mTiwI6Ugmbp+JcByPoc5P+WspiDpHEOJISVR9dh8gCtrM+XNCvtXAtGcPFT1QEQ+CrwPOC0ioWTxjwLXy9OuAY8B10QkADvA/kNe6+8AfwdARPQkNP4gQ8Y4wGUHFcPjwTrilC/ajsKOEcjF2Hfv1h12drY5Pj5+k0+VCyuy0BOBuQYq4KUlqI8cHVblqn91Fr+eE5SeBhiHjq6tiTFRSzb9ce/Xu4uVfYIQyWXTaPBc7zvGruH5X/8NZrniVruiWiTmTebIgPByI4ktDtGijw/ihshu5WfTWtCejCF4c8mJMdPljBIGaJ3c9fhsCxNvG2X0ZoW2ajuCczSVSRWEIfM+wTlOqS+Uvbz5bOrKIi0wjILKhkf+MME4+86FvksFv3cG0RWa6MBkGoawVDNbVUDqwOvLyP5vfZa/8Od+mJ/6qV/kQx94D6fiNZq6ZX5wSLdqkJ3T4Dx1ssXlnKPPEYmJUdOAZEKoCPVl3rh5wN39GT/16ef47g9+N29/+m381b/59xmffivzm3v0y32oxnzucz3nH3sbz6SOwzs3eOcf+n7emRZ88nOf473f+TbiDUe1e4Yf/KNP8lsf/yj7d28yneyaM1Jvw1KSjcWizjxVHRVp3nLYOhgrYUsJEkgu03eZdz55mevHN3j1VsWogke2AlEj0RU1HQ++T2Qv+LzgXTvKc/tw7+4eO7tnSRLJ3hNDj3MQU0SJxprRvDbDbkY1bdtCCPTJPFybqqaqKrOXHG8VCC0j4sFlaufpu0iXoyVVdUW96sl14vVDR3vJQ17gXGMwa87ERKngNlUdGOnFZK09gsdlk9l1KLXzxJCpOjXxP4X6RFsye/v9IMM9qZvh1BNQilGLBzZLCf5ivJqAKYcOzxvuPaNGWmY+DRbY+1yoppw4d8C5gIrN24h3SEqFSz8kfplKxSjWatWHLwtzreiqbzLp+g0cXw+L5jzQl+A+Bj6ENU5/Bfh3MCbNnwV+pvzK/1v+/zfL4//ia+Hv6+NNnuHYZOcb0aC8fnRY9OSTN0gwLYjF0mz02p561NAuOx52KlYdpM2/NbJWiUgA7ZueXxpoUprQUcW9ZQ/0iCrdkMCumSbezAIKBugyuNrT50yFkFxHJ45dEk11kdEF4awPvHZvj60gxQvSjA5SH/ElsIfK9PFSMneqLlImeCMiSt0YtOWkRrsO7xzHBU1faiQ4cDmiPkBvN/VW8ICWiU7FhRrxFiBTsilDX9g7A+1PVYnaG+OkwGpS+O65UDkpWVLGdOklJlwScB19v4WqTQzHrIiPEK2RnKNDXMQniA0mqLZU2hB44syYn/vHn+Czn/sit67d5I988P3sTHe58uhjuPYYYYVvI6mZMap2rGFWB24czKlmPTuTU9xzPV96+Ut8/Lc/x91V5OKZhqPXrvKr1xI/+sf/BH/7r/0vLGJHc+4sZ8cjHnvkEdq2o5nsMOojR9de4/nbt/jgdz3Dq1+5xlI8i+M7LMKCpgo4XxMlsugWliZo4YSX6+QUvuM738oP/8j38X//zMe5cePL3LvVInVEmgo62B4F3l+PuDdRPnl9wquHS951usJpD8kRAwSXUYpZemPb7Baeg+U+j8ijtFWkkcAqJSTbWnI+4kJAYqQJFZrN8cvHbN6nbqDMZvwAlyU1qY1oFM6YMl3b4rLDZYeSSEHYykv24xYjehbZfEnRXCZKHRo9PhgdOGpGpCYnqwL6YrotJV/IURlJImZwVWDQoPFQpmQts3eKvb7Yxid+c38mM0tFCnwyYOBhXSlCFKjLBlCWNrCBWUxFEmt+l1R86A+myJp6jGoZbCo68CVbV7WwHcQo2evKG0Ud68pCxCz8vpXj68ngLwN/r+DwDvgpVf05EXke+EkR+e+AzwJ/tzz/7wI/ISIvY5n7n/qmzmxooA7d15ONuwePE+m/Ne0KXl2gAOccLggt3Td1Km92WGDPPPbYOY6OZhweGIZIadqsP0rZ1VNpWVSVWFkthnFXwVzdYzTcvZOKdPMaRylzOgjjCKeffMsG+sAaQ2Sb0G3bpeHpUU1rJKzwOTMajTk8PGTVK94p3icqgTxkJcnKd3UOcYEcB6U+c88ammpJFUnm3hPElVFwYyw4ryVYeVQTocA+lt0V6IayBxfXK8rkaC8RTclgBYVltCnSWv1gfFXaq4ncz/BhTK8rfDsiRSVdPM07JzUX3nKelz/3PGcuXeTMW57mH3/qXxKPjpkQiDFzur9JEvjQv/XvcmN1l2ufe417+8dcevoJrt64yvjiNiN1HF29zdPvfifx1Zd46cVbvPrabZqdU/hfH9OMM2meOD85x7mLl4jLI/bfuEE92eXm8W1+/w+8m6CBT37+NqGeEGdvsJeE977n3fz2Zz/LKAS61dI+d5wzbcZsb01ISbl3sAcaSQn6+ZI/+yMf4LVXHudjn/gMt1Zz7t46hmya4rM5XJkE/rULLdVO4Max425KLA8yLgZyk5GcONfssjVqee8T8GtXF0xWNfuTI5p2bD0OR5kDUKNiOoMIvDcMvKoCy+VqDXOKCH3O+Loi5oKfo3Sxpy4bgDpha3vKfDbDiUd8IDKBnEjBmRprts1Hi9lGlkjOZq0YBYaK2m5QqxhVQXLBwaVk5WCNe4Wlh5AgOEGTWvOy/L7HflfKfV2JkoPB/vlNwBCnrIenYANzNgUhKKoEpW84VKxWCUg19Kesmu6H1/GWuFTJhiwVpcPOafAdcSXUrc9LvvrcvtHj62HRPAe85yE/fxX47of8fAX82Dd7QpsgVtLcNexrpdZJhyfYwDP3ZeZ5aLxurOmmzeSbPaWveThx3L59h64FxUx8T/JirZ1QgrJzpJjpOy2j4N6CnQQbiY8R2RJCqFndu8NYge0pcXFMtzhec6hzzkQyfd4YDIsIVW1s//Onr9C2S/Zu3WZ7e5uDg6MCdSm2BWnJ3syseGj8DOjfwGcfbtRhSAQ1DFPWN6IZM4dQl+nVjHPeStB1tWU46iB6paUsHiYHT27ZJ7nZOWdc+XebMj4EsmaceFKKfH5vyicOD/jux55CDmdcvXGIm9Tsfeo3ePLpp7idMs3lXZq+48ZBz2iyw6vXXufWa6+SH38SGSfy4pgrj1/h3vNXkccukcOKV7/0MtFH+maMVsrRV77ClceeZNWPSLsTnn33Wzk4XPLytX1uHS34ke9/F++vnuQjv/QCIUTc9i5ZEpUTfJ7SeUejgTa1SLLrM6pscjXGbLZ+obIhoQCnxhV//yd+hi+/cYMf+PAf418/f4F//HO/yBs3rtPFxNntU/zW9T3efnlKFzsuThouLFYsnrzI3Zt3mHtjbrTdDGLPmekWowzJd6RFoN8SfN7C43A50TQNi25FiKAxgc9r027vPQ4LSLHYP9ZVUxye7k+qVJUmVLiS7lbBEfuI1DWQDNNO95u8ZzViQ/BGkfQBFE/KcQ3pAWUIcujbYNWJM70jUcPDs1Oi9ZuNxaWbJGuw4ZOSTQ8N/zW2/5AYOtzv1ry9/2cb9g1F9GS41+29tTxZC3kkY/0A78ykaN13yoOcwhBLKIQP3fQWvsXj22aSdTg2GBn3tWtVh4xZN/3XUiat6X4nAr/RBDcDFPP5/KHwzDd7rBuDmkmrAGTEW6OzCn59Tt6z0bV2SjUKVHW9Lvu08HKXyyXGoxJiP6fb3kGOD2n3j1mFQLx7j6qq8JVh5hZkNwYV62Csyu2lTWleunSJpmlYrTqb3CyXL6mw7T1dzuVnm81iYEv4YqIQi0DH0Pfok5bReUGyIY85x/K8MhEsJhBlw0OKejvnkoSRsmWNUpgfJnEg9F0mJaXPPV3KjIYhkpgQX6NxSS8enOdlmfBvvvuX4S47AAAgAElEQVQ0H//0dd7+rkdYze9wrj1NHG/zlWvXuXB6h/7oEB2NmVYj0uEhy7tjsla89+bzxMN7nH3no3zoL/4nyNVf4iIjPvzXzuPvHLDqDhg/9ShBM488/gxNO+Le8T5uIewf3ubMxZoPnHs7t28t+cxvvka7OGJreorx9uO0x2/gvTAbjUhuwRd/9VPEKoAfEVeJvo1WtqeM5lgqJGP3VFXFp557kZsLoW88P/+RX+TJC5e5euMNa8ynRH2q4sZqRHtdedKdZTY9InRjHhvN+dAHH+P//MjrqChS9Sg195aeP/POwE+/EJm1K3LfUp8b0aaI+grnhLGv6HKCrMSVCcflmKxZ6T2aEimadWPftgwTy3afGDayWq0IwbD87Z0pXj3zPLeKQJTc9ki2+zsb4G1N82SERidCTJjuTmkI+4EUICXr1YQTZ5m6Kjlm+gx1VSR8U/FWFcWrI8km0TNyr9LnoUFrjU/hfmwejAwgJZDfJ0sutq0FWFexrsSjpENAtjWV1BIp76Tw8A027cWqA1Vs49QN3dugnM2G8mZiZN/I8Wbz9//KjwfhF1HHSRdbKQ2OtVkCptFycmDADi3Pk3W2a56ibwLvfJPHuimkMIgKaTKaZ5+TqT/6gK9q6vEWo8mUra0tqqoixrymnw1fvDFEIpDpY0T6RNuM2fIeii6KjXA7nAQyigsV4Igxb15Dha7vabuOa9eu88YbN2jblW0cydQp+5QYVYGUHQPZJasYLIJJ6fZJCyXVGl0ppfKzTMyZlHoGL8w+qbGD1H5Xs6z/JHTNiPmqJivlJhYjm5nWxyaDVzVctvWJu92C6D2uEmYpMLu+zz/71FXG4y0+9fM/z7Pvfobm8Sk5dGxtjzm4s8e9e3dxswUhKlEq7syOYTolLZZ84H/+X1l85hYf+4e/wl/5q8/x4f/804zoOQ4LONWws4jceOEVTq1GjLdHPPL0WS5cqbjoal755A0+/skXefHGdaIqOppw4fLjkA+ZbFVkbamrMU7P8NL11+kXHU++9W0sDo4ImAm2c4H5fE7XrdA8GHorzzz7BEd3b/G+73gvf/pHf5D+7hEBRxg7Qu1JC2g0QrfglfYWL11f8Ws3e0QdjUzsOxI1DnrqUE1cvFDxHWdByYSo9CniFGo1VcN5NsmJqrLJYgqlVMS+v55smHeJPAN8N8A0VVWZlWOy+9o5x6pb4qraBqd8bdaY6snJDMyHKk5VC8NrU51rGYQ7WScMgmsDrRCMoVJV0GYb3MtiwTqLSRhISbldwdu9DjTFgpeXADvAN8OfgXpNOaf1nyE2saknHBsIZ8NYo3y+DURJAbhdOQ/7TKyvYS7soOF9fq9S0W+bDN4g/sRAxxoCgT02QAfl7/zwjz/8LoVxk8v/932/GQL6Oo8B+vjdBqWM3lnwvco8SZtQspNyG6SoKJFMjWJYvDhjA5nEsSvn7stAhGl9TFSYBzjbCXedZVXaGCySEVyKxl/XvL6ZhmupIvgq0MWeZjwm9x25T6TKYKLdXWs29RIMey2Zeh7gMFfmP9XZd1PSCRFvtK+qJqYlOVtQz7nDAU6MGreQRKNC7jPOezrtwFtZexRgHIXK1XSa1+YUixjJOdJ1nnbVM5rW1FGQbJINGiNjdbx+OGeujrHf4darr3P2qffQ+HMsj19n3Jzm/M4Oeuo0R+mQauyY7R9QBziYKW995FE+fRU+8x//p0wfeYbbv/kacZ6Y+3vUlfDs23c4NYb2TmT6tsfYvrDDl169Rjy8wQfcnPa938Xrv/HbTM5coHITtk6f5s7dPV596QWq1Qp37hSnppc5vHubnVPb7Ezfwed/57eZ7x+jvaOaVCxja2PzVZnrcEqfI19++XUOFx0//KHvJjTw6quvc7zKxCwQE32XYSocr3refXGXeep5YT4DmdJpjxLX7JCMZyyJVV7Q9Nt84NktPvPxBT3K4t4dxtvb9CIETTRVYwElGHtpVFUsl0uqql6rS+bSNyE4ct+jKePUGXRGLpmuDUV519C292iaMX3n0LHh820PFdnE5lImOaXNpiogGOMMl8gqjCWT1JfM3e7rCqESG9LSRBkO8oxIhTlnvamRmABgVgtwg+56zyYIq7KGSrScvy/+AHkYeBq0aVIJ6MFkGoaIILmsF2VdVagCTgrJYc05u68XBdZ7kyy0pXm8jiViVe0g7fytHt82GXzOcR2gH4RS1ljcCSrVw46TWfpJ2ObkEM7Xfz75vk3ma71nVXlCvVHnM9efBANeLokkpckqptthhcgJ5s/Q5U8JXyiJ2dlnXnjF50zMidh2qEDtvN2ApRw8yUEHTERLhLqumU6nVgGUnwM0hQEzMDiGJpndEg5bGrY8hs3H/th7xKLxo1nW310isdCOed+y7Ff0uadqAqmCZjwCXxOqLZpuzBbb62uccyZ7MSZEzjZVWz5HSonedfTLY7wmVkl4dCzsXT/mj374uwi7Y/ZvXef7/uAuvo9UVcUbfccrhzO6ecXsRs/8APQwshVmLO7eZOexd1A//i5euX6VVX+HrS3hiUcvcnpRcfvVfX7z16/xS68teXlecfPaG1y+dBqtzvLRvZ7l9UP27uyjdUVdN8TFikY8W9Mxd6Sj65YcH+wRJNNMHV27JAS/blbGGOmLoufgfztcg0VacFojX3zlVa5/ZY8nT59m1h5BbcGsdjW5tQZpFcacOXfeMtGJ6cisZ0OkXEeELRoOpSVL4ImznhbFRZjPbPJ63mW6aDLJPhvU4RUqGQbQNvdWxkw6BsMX83VtLFB6x+CrvFqtiqyyQ11Pk4X9Lmys+oqmzHCv1uU9fYY6ewIWwKOD3m/+RAe9GMNKscrXkW1tWf/WmsXO4cThRUq2rkV7/gTeXWAaTdnWTzmviJLLjEDOw3ChQ708QAd+SD9QZF0ByBre2Tx+MtgOvHmfLenx5fmSLWHMWR+QJv7mjm+bDB4KplVwtwePbwU/zzmvpWG/keNh7ylijvXOuU1AL1lGVAV1JnymCoVDnH1RbRRFc0TUra3y8gMQk3hH160IdUPKGR8aehJnu8xdIrGLOAn0vlszEbxz5bXvb3ylHIkRjo6ODCKRQJUTLijnJyNWucPTI5pNj2bIbrIg2a1pZk4zsSx4cfnETR1s4ZTpWOehyS1976ndCN05y2q6RX35PHQJSZHZ4T26/dvk1ZxQjyz7V6hP7UDXkvpMVXnTqlFHchmXdxiPWu62B0zU4XLkO77zMT760/+c06fOkK88xd/8R59mNNrC+4Z474hp8LQ+ojXshF0WsUPDmHt3V/yxH3kbV6/f5StfWHK8EmR3h/msRWYLuw5bU7b7I2Z7t/n8wZTvGkfGuzWX3/4hPvbZF3niPd/FwetfYj/D1nQX7yt2d3eZhjESPTlkur07zEVYHR1CyvadNjVeIiHYfdOvYgnyptJ4bvs8zZVtnlmd4+Ybb3Dq4jYf/pEf4Kd//pfBQ+8iC6+4XPH84T7njke0AZpVou+saRmzUmWxYJiURVI0C8tF5IPfeYorn5/x0YOIiwtWrTAeTRAROpSYOnzwLHNE6kC/6tbwZuUNthmq4VCZzlHMRf2xKHKiynLZ4kJNHyMuRIiBn74GP3appxcQb99vF3u8F4L2ZCdoVaHJ1lH2BR9XLZpTlgFHLDinVOiPQI2AO8GlT5lIgVycrAeKMtZTyDmZAJmA846YcwF9DR0QUVyCMKirFpx9GMYcAvgQI04mpUPzdA3n3LcRFEqnbiicvlCMjb1pjw8vrvKtR/hvkwBvNDtzyikmyN9CQL9/gOb+DPmbPsOCOVZ1jakjDn6vbrNJF59Jo9TntSZLKDdTIpnmiQyd9VyyjPszeYpUsaBEgaqHNkXG3jFXxWUl1Sb85ThRrZw8VzVhI8sUHYkeg1iESdg8z+7Ek7lFXqtBDv+fZfMerqhpeO/JOky3lmGVLIylZnZhh/GFS1x64m1sjaac3rnAbDZjfriP7i54LUGWJRrn6+9IgzPsNWeGiVWrOpQgM+aLBduVMHItXzlouXbrDfbu3uHi41POpxWXzp/G5YbJqW2iRiRFfOo4PjwgpYDmFd3kMpXO+cKvPcdHXztkZ2vK1qlTzJb7zG7OefzKOY7v3iM4x6LaRfMWvS6ZHXf0c3jHH38f21ducu3F17jTRrJzdKmjqQOH7ZFRIGd3uLlccPrMY9QVpNoa7in3dN2KprarWvtA7jN9SrgyRYqDy27Mc/v7hO0d5ofC+e1tTm9NuHc0pxFPLZArWMUVr2gHCVo6fDVe6/BnAUFpxo05N7XgG5NGfudjFf9iD7zr6RYrnCREdhi7gMZMKBWbc4KWqsBhE6zDfXpycnlj85ip65p2sQLEfAH6lsYF5nT0i0AVevrs6JLitYzqC4iMSTmyXCUq9fQ4NCfjrD8wOT1tesRB2xbtPArEUrT6B+IFYhueL0lP5W2s2+WElM2gz0qKut5wc7bp1gHmSikXpVq/3mC8HyqZTZD/6lgxUC0f+LmyTqLsvi8r7IHnrWPBw1/+Gzq+TQK8IkS8g/HWiMVi9U0F44cOMZ2Ad77RQwqcgpM1Jt91ndmLiSu+mvZcGy+xzYk1x7ewecoQlXNFMMt5yxJE1rSuk3dLFnOmMvVGh4qwbDyhK0JJjaNfdDYeLkJVVUaBjIOg2EYuQBRySraQcqR3jrfsBpY5I5rI4tfhXdh0klSyNRDLaw3PGXDGnOOa1oVs9H/uSU1f7zL1OywOF2gnTPwdxgjH/Yzj2Rx1E15+/SpvvzQ2vLJg9V0XSb0Su56opg8TpWKGBaikiRf2jvnZl2siB5w9/QQHd+/i5gtWqaaulsR+yc7ONvP5ElHl9O4lQs4czI+498Z1qODO3iHf/71/hM/86r9gvmhBe0Z1ze29m9T+HIeaubS7TeUq1DXsLRbQ3+GJZszWY49w7do+Iw/eeQ7vHnDEIVfe8hYeeeY8F9zjLGdzXn7pBjde+CTh8acZj7boV+3a8EP8tPQ1eqv8opKT0s1XHC7n7FY1YTLmuF2xe3GMmzTQLeiIQM3YT/jus1M+tXeT733yMl/am9OmxKo3M4kYDaeez1uz06sgygpWU3TU8f0XIs/dhnuqLOcrxn5CX9m93sYeH0LRKS8Ycsk5Us5UIRCLi1POuu5RpT7Sxc7E8Xywx+OKlANel1Su4o7WbKeI5Q/F8hFH1CWVg0mgiNt5qgQUEbHEQK0tbU0tsIza2sl+4/ZklbEyUU8a+PJZ6Yu0cghi/SbAFamPPg4qtbYGczStIBVrwva9rfMgRV8J1hWNKqAnZMfL5lj2a5uWHdY1m5Eds06UtU7UOuas//P/owDvHZwfV+SotLMFY2B5suT6V3m4DWY/dPhdEmIcxLc252UQTZEgoPTr141eSrjfBHwddF8GbzCXzQNy6MmrKdZpFkLdmOJgCCVQV7QucQHP7cWSU37EMqe1XdpgnpxTsjFpNqYKzjmyBDwdKTtOjRu6fkV2QlWAvpQGB5yMLwIMNrqd0QgxOLwJ9pClLBTqtYCWDxWqidz1HC+W7LolnYc2dsznx9QxMlelO2p55Ss32R0J4hJtyoiHdj6n6IvRtUK7XJD8LrlV1Dva5Q7/y698mjNXrjDameDyFqtuye5km4iyffYU9/bvkFc9d+/dwWWQ0hjUotoo9QipHNFFPv/CZ1i6HvHgkqBSsbu1jZtss+UCqpkutVSxY7GcsTPd4sd//Mf5t3/0w/zhZy9yOT9L13Xcu32Hw9mc2f4b3Jjf5rYISECmE/Sxp8sCj7iwbbo/1RaVhzbNaZNJ8P65/+jf573vfS97h4dIynSu5fjOPt0SPvHZT3Lp0mXCdMpBymTf03aRj9y6xkThTlqx7JbkBI4xGiAET9aMusCySPCKVGYuHyve+lTg8XM9/+ALpm6q/YIoY8SNEOeoB4VL72hXHZNmZIQF5/Au4ENl2vBVKCwS659o8DQiBHFm8D7aou97air6kfKpayM+9OQKXSZWTgtbBjoxmCp2lrDk3KOuRooC6jBEJwrRmVaNsdSKdU8ylkwQq46TCDibo3DqwEvB3IchIllDOQLURSs5RgvGLgghG6VymHQ1jN6YZb4833nM6D7pfW5PD5JEBuaOsIF5MgbdDv0vbOnZunP3D0p+K8e3RYBXhdUy2tCMSFE8/NY+4aAe+PUe64v8VXRN1mStkxvOyb9lGEWD+zaH4RiC/n1N0ILX64OkqNLYSckkfHOhnQFsTabE46VN5wVPXJnnZl1b3a8pG2NA4xqaUVViSsZgcUKKkZR62pRofF0yiQ2v1yziPF3qS9am5mmLaXknr2gPbmaYcOha1HlaIkJmevos+0dHnNreZXLQMx6P6aqaLvUsux5NyuzwLs9cOE1MVqm5oeRPvli4KY2f4npPnU24ae4jPmQmztMtVlQXzpHmM2btEu0iW82YRx59hMXBEavxGGkqZvv36GOkn89LwyoTVtBsT8i9EvvMqA7kHAm1Z+w9i1VHrz1VHRg3I/aODgjA4nBBzpn/6yf+KZUKt2c32RpNaLbHZOfZmuywckLsO5Iqq6NjqrrhVB2Yz5dr9yvABp4E/GhEGyOXLlzm2quvc357wic+9hsGqUzHPHrlNP/Bj3yYcTMlT7dovGOlK7Tt+B//xt/i+edfYhwmXJiOgDtrhUVVh3eOUFmVmbPNJ6ybdm3C1TBFOcwwXyzZIuB8tW6gp5RATIysK+dehcqamzHianOCMm58j6yxf8PzfTaqbewSPgSWqwVZHXdXnhERnxxdFiiyvqqw1iQo6yMWDV0Rm2gVV6i7smF7aVaqYnM5ZNfkDeyh5I2tXkmuBjx8IBAM18W5YgWIkgt2bwVqqVqx01OFmMzrOea88TEW0GRwZpKBdimD2LVRONlQMlU3UhUno8BJx7lv9fi2CPDGSAo4yWRNuFKSPSxYfj3HsIM++PsPb5oOf9tjWTeX+eTvnAzOG/oT9wX34fkPe7+TFM7ym1ZWDs3LARpB8KKkWLL9rKQUcb6ibXvanDjrG263c4I3PvxytcSJ8Zht+lDXfpOD207qlvQJLo8bFmnF2E/piuaHGz5XTjhfs+hW1N5DEmo34nj/iO7Y43KmJlmjyIMkzywk6miKfS2Z9uYNzjjP/KW7TL7n3dwMsJuUnBP0kcPuiGd2xjTSggtUqqj25KzFcSoTY2LVr+gl07pMDWyfEsYBjpc9KhXx4Ih2vuT8pfN0OTHvltx+7QDayPb5M7SzBSOpmJzZ5XC6MMG0Zc+ya9menOJgfogmpV311KMJPjSsWDFrW6rRhNlqSRLh4sWLnN4+RRboo01NOuBpeYrZYkVcLBBV5jmwXM5oxDD3gBDnLdXErOzWUEZKxKqi6yNBPantuXDhAp///OeZtyvS6R1+4eMf4Q++9w9w+9UZP/WRj/Hil18i1BX9vAcNjAl8+Md+iFe/8BK/fn2P2lc8I36NwZttotB1CfA2yanFwrJs6DEJH3qm4WMvt9xrGpaLGc3WmBAqgyFDoF8aYysLuAhVCiZk5j2xtQYsKdM0FW27JDtwSdGY6L3BjHVheFW+ptXEb17LfN8VhZRIONO2icowNGgzLKWalWGielhFgUojWZVKDPIcBaEtwnTIELCHNVtWmmMNfg9reDAct7AqGzaZOxF4i5yIK7CPOE/MhcrthayOqMm47SViiJf1Ws/ZcKU1PXLAZ8RolTlZn+BBIvbA838zjP8bOb5taJIp92RNJwLu/Z3pr+c4GYSdc+tx64dBPQ9SJweMb/24ZuQBRTl73rfW/L3/993afOPBx+WBDvpQjURn+Ddl4Qw8ZZXibZmHIaFi7DFscjZoakqGJ15PSjoxtHVs2Kroa1PxxpcP6GcZn3schtm3CMdJ8E9fYhQBMitnTlgiEHJiJZnj33qBc23xnVRlFQ1euDTdIhdJYJMnSOvPqLlC8whNDkcm5NoMXvolj144hWssq5xsjXHBMzucMcZs4kbNFu7UlFPTHS5degR36hRHx0vOnjrLqcn2ulF+NDs0qmlTMRptsTWeMBptsWx76mYETqiamsl0Cn1icTTjaG+f7uiY+a2bLG/e4upLr7J/8ybHi2P63ONHgeCdUVlzYhmXuNqvIbKhf6Mkq7DIoOafujUZ4Zxjmf+/9s4txrKsrOO/b6219z636uqpqu4Z5kLGkZaAt9EQhWAMEjVI0CceIEZ4IOHFB0xMDEii8dEXISbGaMSQGKOGiBHhAQlgDCYCIgM0AzM9AzMw9FjVdb+cs29rfT6stU+dbnoAnZqppmr/k5Nz9jq7dq39nb2+tdZ3+X/Cyto9/Nj9V8gGY/b2Sp65/m1MgHGIRbClEGZSYqSgAV577xpXBsnnQ0rQSSvHebFpJIWzxueiosVozmRYc3kEZRmpAYwx1HW0rwMMh0OccynT2M7NGvUsFiLXNmY9dzVVO3S+K209XjwWpW1rChH2SshxVBpt461fyAoVixibIouETCAXcMTayOJbajukImcaYOYNR6mQhleZJ8rFa0UjukZus/mOthtwmsogish8/HXOUaPR3GMT8ZdqKuOomrLSozln0UKwOBEZY+bBxvF3iQ7hTtF3E1g3Ri1xkdVRHZ+EYu9wZ6zgAWNtjH/utis3mUC+/0q+G7wdNNysnJ97wri9NG8Xi9/FAgtdpZeYLXfrKv650P2oXehZVOLRjt+t8LoIkugAihElcTvT4CshGw84KEtsG683GAzIikjvGlpPWVfYtMoSiSaDqg1gHZOxYXPacoURB6FmJPk8GqBj0utkcrjfsL0zpUDwIfa1RNlXz0xgW4FvXO+41TASkztGVhiqshRgw7XMdjdZXl4miHA4nbJ+7Tr3XLYEW5AZJWAIJq4+fa14M6X1SjUbsbm5GRlA2ynbU0NVLXNpaY027HGwtcPqcEIzzDjIod6bMbY5ozwnK2MBjUme49YKNtfXMc5Sec9AMgajMZu7Wzix5NZRVjOYHXJxOODG/j7D0RLWQXV4iPFKpVBLoDUwGAwgwMXhRaqqobEBLNSHu+QYgjdMyxnDYRYrSKVJzBhDNiiQ3GDKKGsv0PiWelbzwb/6AHWAS5cv044muMGYBx5Y5TP/WUIBK3ffxe43D8krT4OhLWd4cfzHNza4d2IIktF6me8wmhAY5o76KNJnBIlc4z5AowqU2AA/elm4+hQYUbbWNxgvX4gK3TmmzYyiKBhkx6UfrREyWzCbzVKt1gY10YRng9IgkGdkbUDyIcZAXU4ZuCxqr1w4CJpKBKYQ4yBUjXJUh2SX92jLnGZA0mo9KFg3Q33kexeJ91Yq5Db6u1p0nl8iKQIGwtwhah3RNBoiK2bM/0g78rkCEcQnKgOJNQtiNJekCLKOciFmkLchMlCKxB2MaArhNIIViUyTIe7+5pQGCmCieUqOV/2Luuck7PB3jIJvk4JzYuZZcR0Wb/4Hgh6Hcn2vyJpFfL/rP1cfYltI58hN7d89SUSvTbxWXFndbLa5+f9FG3rKVE22vs6+VzihamE6nbJ2+RLWWg729tPWEEi2vnkfPBBacAUhGIqUZDNfxXT9UoNBOKjqaIMn2jGfUCGy5QgDhGWiozhTUGOIyXjKkc8oTc3dGOoLI/Jv71AaR7F6ka0bm1zIxtRMcYkJM47H9lhmPsd7z6PfuMF429GKxwbHkTXU2QTjwWcTmsEB6/U+Y8YsM8atrrG5t01Vt5TVjMlwBCYV6x5l1BqQUtAiA29YWbub2eZ3sNaSiZIbw6ycMhxPqJuKYTagbhoy5xguLeGrislgwOxwhhsMqESRSUHe1Jgm0HioM5BMIOQEZ8lthrWOmP2bniEia6Y1MboqI0ZJveVtv8VULQ/eey+zZo/N9S0+/5lHwDsmgwk6rRCgEWGgpHKDMabeWB8ZGX0y68USRjiXAykibcGObAKYgdIeGIo8Ov+DCFmRcXRwwPJdq3G3IS5x1weKokjPYyDgcXkWo7ZSEfuA4kVjkXeBGSGaF+sWLwYLlIAxnv224bKQsngtxsXolNYrGIN13BwqrWEeEtx6i/g4EcSav/V89TyvViDH1Zi6hVNMwo3PW2fC1fTM3hQV3D2HhpRX0hUGERKXR2Si9Im62xXQNNQmxO80+QhItSLSNZwImgnahoX/JQu+gq7lZHFHKPhORQpQabgtqe/3M43Ehzhd75aZ8Af+e+KDNe9VCptSOoUdnWOkVGKxZr7b6FY48+uRHER68/WhM4+YtBJQUEESIReJ5N+GVG3JurhaUIsDmmkNRphgqUy0WW/8zzpFUSRisTLKsyswQtz6BWk5msHaiuerN2b85H2GahZpBeK9RUU/dAWb1RE7QVErDHyMjllGWUaQlNatEqmCXQtLQRlgmeBoUR4TeNoGXnbYEjKlufo0G/o4yy+9n4HbpqlBwxQZD+bmhKaOK2WPZxoaigm4cUHmY0Ho7XrIYVMxWjLUg8BascpsNqMsa27s7eD2dlm5a402j6aFg909QlNDG3BE4qopivEVjTMMjMGP15ge7mGyEdYdgoyorTAsRogIhcu4OJrQVDUDk3FweER5dER1sB/JwQYFWV4QrMEWWZxQm4aiyKinJdUwRq/kebTDG5MchlohdkDjFCkrtGzY3LjBpYuXafYOqacznn36Oj/+iiusrE7Y2dlhaWmJb65vAJ4ZcNBMQRwPLS+zFA7InInFuAFtwGVQNjVKoG0N1gdm3jB0Busz/EyotGXgCpZkxiGRY2Y0mbC3u0leDBmPC1rvCRLJxESELIsqw7kMV8TJODOWRmLijjeKqCe3jjaUeKNkxiBtwASllcCXbhhes+oQ02B8LOpeDA25d1QpOc8GG4uSzHM8NCp59clt5VGJ5GPZAofR4o5dkjUgjh+ogkZzj6SggS7EORXYEBN5grxJDKtxPkimc537y4ym4hzBE4LHGcElcr6aWPwj+ouPo2lyByaR+1mbeBert7kAAAi5SURBVHBSgZ7jBMWFBKm0e3m+vtY7QsFD5+o4oWs9Tzs5ROW9yDOvRHZKTfurGP54synpViya0W/dUXSJIs6kBIyOIU8jm97cnNNFEvgQU8KJStsb0BaMjTHUZTmjk6DCfG8bJ6dEOiAwnSlTD/tlRqaB3EYFrhILOGztzjhsG5Z9xjM0FOrJjbCq0Q7qutBPBXfhAmHnEK9Q4nlWWmZp+5kLHNYlGY6DuqV1MPvOOi+/5y6wNZmNBZgXyeBaYlx128QBG1CsjyaQfTvG5Yb9vS2G5gKzskTEMFlaoqoq9rZ3WN94Fs0MqysrseCxyyhDRWh8/D2tQX1NnmdoqMASS/m5Kb/+pof58L88TpY5jFhyY3BiuLG9RZMYFlsDaoSiyHEoxWBIlwgEMBoO2J5Gh25exIiUrd2dY/NhaFOBi2jXNrlDgclkwnA4pK2ibfubz3wLLKx/6zvUWrN9Y5OtzR0uXLjAtJzhm4a8bLhsW7baJq7MVVM1rJDir5mzjvoQEBvrgDbJtxSITkb1LRMHR03cVdbllEGR0YaWqqrI8jw67SXaizvWy86UCvH/GElFWoziTEaV6rhaJFaO8olY1wgHwbPdFNyV12gAL4JIYDAwaA2zGgSfMqSPbdKqumC2OV7h+/S4Kyw4WFM1JKFb3qfty82m3JvG660ZR/Ox+73X13FnFmI1KKMpASv5lJLppg3d5HPcv2g8Oql4mdvjjlDwSjR/PQeH2Kmg29bOnbEi85m2Y6nrHLMd58TxQE7mpQU+j3gGiBwXf+5W8iQOmK4wSeQRSQ9v4kgXonJZXl5CVZmVRzgxND4wzmOc915ZI17IbCBzMB5aMqNcmmQMQmC3Ub6+2ZIpXFuv+Il7ou0bAjZz7O3XlHsNGbFCzkqAIxsovcZkIwEncRAZgeJgRquBFoncMQpDDIPgccaQE6hrzwUM2iqNh6tPb/DQS0fkRy122VG4jKCRYEqI8raSkp9CYJhlbAZFshFD2yKjnPWtbUYyYDweM3AFI5fjMsO0rmiqmq0bG2jTxvyCzDJyDh8gzzPaqmR5OGR7Y5/9qsHamkHT8KG/+XfCpfvQw4q6aTj0LdlowPLqChdXVyK9r4lFw8VH3p1BMWQ2m6XIlZbpwWH8oYNS+5K2LjkqjxiNlxdMbiTHpMdqJK/a29nlYx/5GIVYpnj+8L2/z6OPPsoN2eH6k9eYrKxw7do1fNNy/733sXV0SFNNuXsAS24fMxwTvEd8YOgiK2VjPJnLqKuaLiXeNDHnpGo9XgSLpa4b7r1o2LgRYh1ea6h85Mpp25ppecTa5XtiCT+Yl25smhqX0nKrqsKa6Pdp2pZ6No00uNaQ24x61gKCI6DBEWzBo9sVv7isTDOhCAYrnqW8xZkYXinhOPrEGDnOMiWaSJCO153j2qxp7BqExodkQ09jNA3HIN8dWWLmPrU0vgOk2nqRiI/jqJhbzbSdoiaZlefMlTbuGto5hTFzO5CkScuIkpvkAEfniZELC/rnDXnRE4lu1wmRG8ARsHnafTllrNHLoJdBL4MOvRzg5aq69P/94ztjBa96SUT+S1Vfddp9OU30MuhlAL0MOvRyiDJ4Pn9/x8TB9+jRo0ePk0Wv4Hv06NHjjOJOUvB/edoduAPQy6CXAfQy6NDL4XnK4I5wsvbo0aNHj5PHnbSC79GjR48eJ4hTV/Ai8gYReUxEnhCRd592f15IiMhfi8iGiFxdaFsRkU+IyLX0fldqFxH50ySXL4vIz55ez08GIvKAiHxaRL4mIl8VkXel9nMjAwARGYjI50TkS0kOf5Taf0REPpvk8A8ikqf2Ih0/kb5/8DT7f5IQESsiXxSRj6bjcyUDEXlKRL4iIo90ETMnOR5OVcFLZOn6M+DXgFcCbxWRV55mn15gfBB4wy1t7wY+qapXgE+mY4gyuZJe7wT+/EXq4wuJFvhdVX0F8Grgt9PvfZ5kAFABr1fVnwYeBt4gIq8G/hh4X5LDDvCOdP47gB1VfRnwvnTeWcG7gK8tHJ9HGfySqj68EBJ6cuOhS4k/jRfwGuDjC8fvAd5zmn16Ee75QeDqwvFjwEvS55cAj6XPfwG89XbnnZUX8M/Ar5xzGYyA/wZ+npjU41L7fGwAHwdekz67dJ6cdt9P4N7vTwrs9cBHiQmn500GTwFrt7Sd2Hg4bRPNfcC3F46fSW3nCXer6rMA6f1yaj/Tsklb7J8BPss5lEEyTTwCbACfAJ4EdlUTtebN9zqXQ/p+D1h9cXv8guD9wO9xTB27yvmTgQL/KiJfEJF3prYTGw+nncl6O/aePqwn4szKRkQmwD8Cv6Oq+7fyeyyeepu2MyEDjVVOHhaRi8A/Aa+43Wnp/czJQUTeBGyo6hdE5HVd821OPbMySHitql4XkcvAJ0Tk69/j3P+zDE57Bf8M8MDC8f3A9VPqy2lhXUReApDeN1L7mZSNiGRE5f63qvrh1HyuZLAIVd0F/o3ok7goIt2ia/Fe53JI3y8D2y9uT08crwV+Q0SeAv6eaKZ5P+dLBqjq9fS+QZzof44THA+nreA/D1xJnvMceAvwkVPu04uNjwBvT5/fTrRLd+1vS57zVwN73bbthxUSl+ofAL6mqn+y8NW5kQGAiFxKK3dEZAj8MtHR+Gngzem0W+XQyefNwKc0GWF/WKGq71HV+1X1QeK4/5Sq/ibnSAYiMhaRpe4z8KvAVU5yPNwBToY3Ao8TbZDvPe3+vMD3+nfAs0BDnI3fQbQjfhK4lt5X0rlCjDB6EvgK8KrT7v8J3P8vELeUXwYeSa83nicZpPv6KeCLSQ5XgT9I7Q8BnwOeAD4EFKl9kI6fSN8/dNr3cMLyeB3w0fMmg3SvX0qvr3b67yTHQ5/J2qNHjx5nFKdtounRo0ePHi8QegXfo0ePHmcUvYLv0aNHjzOKXsH36NGjxxlFr+B79OjR44yiV/A9evTocUbRK/gePXr0OKPoFXyPHj16nFH8LxkV5ERuFwTlAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "woman and two young girls are gathered around each other\n"
     ]
    }
   ],
   "source": [
    "pic = list(encoding_test.keys())[570]\n",
    "img = encoding_test[pic].reshape(1, 2048)\n",
    "x = plt.imread(images + pic)\n",
    "plt.imshow(x)\n",
    "plt.show()\n",
    "print(greedy_search(img))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.save(\"my_model.h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1\n",
      "292328/292328 [==============================] - 197s 674us/step - loss: 2.2044\n"
     ]
    }
   ],
   "source": [
    "#train it for some more time\n",
    "model.fit([X1, X2], y, epochs = 1, batch_size = 64)\n",
    "model.save(\"my_model_\"+str(i)+\".h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "white dog with red collar is running in the snow\n"
     ]
    }
   ],
   "source": [
    "pic = list(encoding_test.keys())[888]\n",
    "img = encoding_test[pic].reshape(1, 2048)\n",
    "x = plt.imread(images + pic)\n",
    "plt.imshow(x)\n",
    "plt.show()\n",
    "print(greedy_search(img))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.save(\"my-cap.h5\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}