t81_558_class_10_4_captioning.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "DFIHVQqnPgVN"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/jeffheaton/t81_558_deep_learning/blob/master/t81_558_class_10_4_captioning.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "LXSZ9CRGevw0"
   },
   "source": [
    "# T81-558: Applications of Deep Neural Networks\n",
    "**Module 10: Time Series in Keras**\n",
    "* Instructor: [Jeff Heaton](https://sites.wustl.edu/jeffheaton/), McKelvey School of Engineering, [Washington University in St. Louis](https://engineering.wustl.edu/Programs/Pages/default.aspx)\n",
    "* For more information visit the [class website](https://sites.wustl.edu/jeffheaton/t81-558/)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "3LFASLt5evw2"
   },
   "source": [
    "# Module 10 Material\n",
    "\n",
    "* Part 10.1: Time Series Data Encoding for Deep Learning [[Video]](https://www.youtube.com/watch?v=dMUmHsktl04&list=PLjy4p-07OYzulelvJ5KVaT2pDlxivl_BN) [[Notebook]](t81_558_class_10_1_timeseries.ipynb)\n",
    "* Part 10.2: Programming LSTM with Keras and TensorFlow [[Video]](https://www.youtube.com/watch?v=wY0dyFgNCgY&list=PLjy4p-07OYzulelvJ5KVaT2pDlxivl_BN) [[Notebook]](t81_558_class_10_2_lstm.ipynb)\n",
    "* Part 10.3: Text Generation with Keras and TensorFlow [[Video]](https://www.youtube.com/watch?v=6ORnRAz3gnA&list=PLjy4p-07OYzulelvJ5KVaT2pDlxivl_BN) [[Notebook]](t81_558_class_10_3_text_generation.ipynb)\n",
    "* **Part 10.4: Image Captioning with Keras and TensorFlow** [[Video]](https://www.youtube.com/watch?v=NmoW_AYWkb4&list=PLjy4p-07OYzulelvJ5KVaT2pDlxivl_BN) [[Notebook]](t81_558_class_10_4_captioning.ipynb)\n",
    "* Part 10.5: Temporal CNN in Keras and TensorFlow [[Video]](https://www.youtube.com/watch?v=i390g8acZwk&list=PLjy4p-07OYzulelvJ5KVaT2pDlxivl_BN) [[Notebook]](t81_558_class_10_5_temporal_cnn.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Google CoLab Instructions\n",
    "\n",
    "The following code ensures that Google CoLab is running the correct version of TensorFlow.\n",
    "  Running the following code will map your GDrive to ```/content/drive```."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Note: not using Google CoLab\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    from google.colab import drive\n",
    "    drive.mount('/content/drive', force_remount=True)\n",
    "    COLAB = True\n",
    "    print(\"Note: using Google CoLab\")\n",
    "    %tensorflow_version 2.x\n",
    "except:\n",
    "    print(\"Note: not using Google CoLab\")\n",
    "    COLAB = False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "7xH2XSZmevxx"
   },
   "source": [
    "# Part 10.4: Image Captioning with Keras and TensorFlow\n",
    "\n",
    "Image captioning is a new technology that combines LSTM text generation with the computer vision powers of a convolutional neural network.  I first saw this technology in Andrej Karpathy's Dissertation. [[Cite:karpathy2016connecting]](https://cs.stanford.edu/people/karpathy/main.pdf) Figure 10.ACAP shows images from his work.\n",
    "\n",
    "**Figure 10.ACAP: Andrej Karpathy's Dissertation**\n",
    "![Captioning](https://raw.githubusercontent.com/jeffheaton/t81_558_deep_learning/master/images/karpathy_thesis.jpg \"Captioning\")\n",
    "\n",
    "In this part, we will use LSTM and CNN to create a basic image captioning system. We will use transfer learning to utilize these two projects:\n",
    "\n",
    "* [InceptionV3](https://arxiv.org/abs/1512.00567)\n",
    "* [Glove](https://nlp.stanford.edu/projects/glove/)\n",
    "\n",
    "We use inception to extract features from the images.  Glove is a set of Natural Language Processing (NLP) vectors for common words. Figure 10.CAP-FLOW gives a high-level overview of captioning.\n",
    "\n",
    "**Figure 10.CAP-FLOW: Captioning with a Neural Network**\n",
    "![Captioning with a Neural Network](https://raw.githubusercontent.com/jeffheaton/t81_558_deep_learning/master/images/caption-1.png \"Captioning with a Neural Network\")\n",
    "\n",
    "We begin by importing the needed libraries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 64
    },
    "colab_type": "code",
    "id": "m2p8iXQygqRN",
    "outputId": "9048a577-a759-4b13-e65f-f4d5e428e0c4"
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import string\n",
    "import glob\n",
    "from tensorflow.keras.applications import MobileNet\n",
    "import tensorflow.keras.applications.mobilenet  \n",
    "\n",
    "from tensorflow.keras.applications.inception_v3 import InceptionV3\n",
    "import tensorflow.keras.applications.inception_v3\n",
    "\n",
    "\n",
    "from tqdm import tqdm\n",
    "import tensorflow.keras.preprocessing.image\n",
    "import pickle\n",
    "from time import time\n",
    "import numpy as np\n",
    "from PIL import Image\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import (LSTM, Embedding, \n",
    "    TimeDistributed, Dense, RepeatVector, \n",
    "    Activation, Flatten, Reshape, concatenate,  \n",
    "    Dropout, BatchNormalization)\n",
    "from tensorflow.keras.optimizers import Adam, RMSprop\n",
    "from tensorflow.keras import Input, layers\n",
    "from tensorflow.keras import optimizers\n",
    "\n",
    "from tensorflow.keras.models import Model\n",
    "\n",
    "from tensorflow.keras.layers import add\n",
    "from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
    "from tensorflow.keras.utils import to_categorical\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "START = \"startseq\"\n",
    "STOP = \"endseq\"\n",
    "EPOCHS = 10\n",
    "USE_INCEPTION = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "kEMwH956gaOG"
   },
   "source": [
    "We use the following function to nicely format elapsed times."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "mGt4swcqIFKR"
   },
   "outputs": [],
   "source": [
    "# Nicely formatted time string\n",
    "def hms_string(sec_elapsed):\n",
    "    h = int(sec_elapsed / (60 * 60))\n",
    "    m = int((sec_elapsed % (60 * 60)) / 60)\n",
    "    s = sec_elapsed % 60\n",
    "    return f\"{h}:{m:>02}:{s:>05.2f}\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "TgTP26RygaOe"
   },
   "source": [
    "### Needed Data\n",
    "\n",
    "You will need to download the following data and place it in a folder for this example.  Point the *root_captioning* string at the folder that you are using for the caption generation. This folder should have the following sub-folders.\n",
    "\n",
    "* data - Create this directory to hold saved models.\n",
    "* [glove.6B](https://nlp.stanford.edu/projects/glove/) - Glove embeddings.\n",
    "* [Flicker8k_Dataset](https://github.com/jbrownlee/Datasets/releases/download/Flickr8k/Flickr8k_Dataset.zip) - Flicker dataset.\n",
    "* [Flicker8k_Text](https://github.com/jbrownlee/Datasets/releases/download/Flickr8k/Flickr8k_text.zip)\n",
    "\n",
    "Note, the original Flickr datasets are no longer available, but you can download them from a location specified by [this article](https://machinelearningmastery.com/prepare-photo-caption-dataset-training-deep-learning-model/). \n",
    "\n",
    "### Running Locally\n",
    "\n",
    "You will need to modify the following code to reflect the folder's location that you will store files required by this captions example.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "hj4K-WHafser"
   },
   "outputs": [],
   "source": [
    "if COLAB:\n",
    "    root_captioning = \"/content/drive/My Drive/projects/captions\"\n",
    "else:\n",
    "    root_captioning = \"./data/captions\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "VlBS8URRgaOo"
   },
   "source": [
    "### Clean/Build Dataset From Flickr8k\n",
    "\n",
    "We must pull in the Flickr dataset captions and clean them of extra whitespace, punctuation, and other distractions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Ra-d7BLlf1nC"
   },
   "outputs": [],
   "source": [
    "null_punct = str.maketrans('', '', string.punctuation)\n",
    "lookup = dict()\n",
    "\n",
    "with open( os.path.join(root_captioning,'Flickr8k_text',\\\n",
    "                        'Flickr8k.token.txt'), 'r') as fp:\n",
    "  \n",
    "  max_length = 0\n",
    "  for line in fp.read().split('\\n'):\n",
    "    tok = line.split()\n",
    "    if len(line) >= 2:\n",
    "      id = tok[0].split('.')[0]\n",
    "      desc = tok[1:]\n",
    "      \n",
    "      # Cleanup description\n",
    "      desc = [word.lower() for word in desc]\n",
    "      desc = [w.translate(null_punct) for w in desc]\n",
    "      desc = [word for word in desc if len(word)>1]\n",
    "      desc = [word for word in desc if word.isalpha()]\n",
    "      max_length = max(max_length,len(desc))\n",
    "      \n",
    "      if id not in lookup:\n",
    "        lookup[id] = list()\n",
    "      lookup[id].append(' '.join(desc))\n",
    "      \n",
    "lex = set()\n",
    "for key in lookup:\n",
    "  [lex.update(d.split()) for d in lookup[key]]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "xdFUtyIPgaOy"
   },
   "source": [
    "The following code displays stats on the data downloaded and processed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 69
    },
    "colab_type": "code",
    "id": "Gnq3ZjaSU79-",
    "outputId": "abca1d2b-293d-48c2-8acb-f8808e2254c5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8092\n",
      "8763\n",
      "32\n"
     ]
    }
   ],
   "source": [
    "print(len(lookup)) # How many unique words\n",
    "print(len(lex)) # The dictionary\n",
    "print(max_length) # Maximum length of a caption (in words)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Jk1ts5ZfgaO5"
   },
   "source": [
    "Next, we load the Glove embeddings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "JYVZ83DLsb1r"
   },
   "outputs": [],
   "source": [
    "# Warning, running this too soon on GDrive can sometimes not work.\n",
    "# Just rerun if len(img) = 0\n",
    "img = glob.glob(os.path.join(root_captioning,'Flicker8k_Dataset', '*.jpg'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "vzVqUkNGgaPG"
   },
   "source": [
    "Display the count of how many Glove embeddings we have."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "colab_type": "code",
    "id": "DosvCz6bVZA7",
    "outputId": "2a6cda6d-6fca-42bd-ecdd-05ea4e02fc62"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8091"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(img)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "EXpBd3PrgaPL"
   },
   "source": [
    "Read all image names and use the predefined train/test sets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "lhJSo7czkW03"
   },
   "outputs": [],
   "source": [
    "train_images_path = os.path.join(root_captioning,\\\n",
    "            'Flickr8k_text','Flickr_8k.trainImages.txt') \n",
    "train_images = set(open(train_images_path, 'r').read().strip().split('\\n'))\n",
    "test_images_path = os.path.join(root_captioning,\n",
    "            'Flickr8k_text','Flickr_8k.testImages.txt') \n",
    "test_images = set(open(test_images_path, 'r').read().strip().split('\\n'))\n",
    "\n",
    "train_img = []\n",
    "test_img = []\n",
    "\n",
    "for i in img:\n",
    "  f = os.path.split(i)[-1]\n",
    "  if f in train_images: \n",
    "    train_img.append(f) \n",
    "  elif f in test_images:\n",
    "    test_img.append(f) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "aP2-k6XfgaPT"
   },
   "source": [
    "Display the size of the train and test sets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 52
    },
    "colab_type": "code",
    "id": "ZZQZkT8X_qNt",
    "outputId": "c3bed225-6672-4935-e328-633b9b2fffc9"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6000\n",
      "1000\n"
     ]
    }
   ],
   "source": [
    "print(len(train_images))\n",
    "print(len(test_images))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "iawCdtU4gaPa"
   },
   "source": [
    "Build the sequences.  We include a **start** and **stop** token at the beginning/end.  We will later use the **start** token to begin the process of generating a caption.  Encountering the **stop** token in the generated text will let us know the process is complete."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "cBX6TJbPF0nD"
   },
   "outputs": [],
   "source": [
    "train_descriptions = {k:v for k,v in lookup.items() if f'{k}.jpg' \\\n",
    "                      in train_images}\n",
    "for n,v in train_descriptions.items(): \n",
    "  for d in range(len(v)):\n",
    "    v[d] = f'{START} {v[d]} {STOP}'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "XHD6IZ3HgaPk"
   },
   "source": [
    "See how many discriptions were extracted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "colab_type": "code",
    "id": "v3_PCjddHcUe",
    "outputId": "20a7b7b0-dc56-4ec2-ebb0-dbf49543e57b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6000"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(train_descriptions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "SAYpvjpogaPs"
   },
   "source": [
    "### Choosing a Computer Vision Neural Network to Transfer\n",
    "\n",
    "This example provides two neural networks that we can use via transfer learning.  In this example, I use Glove for the text embedding and InceptionV3 to extract features from the images.  Both of these transfers serve to extract features from the raw text and the images.  Without this prior knowledge transferred in, this example would take considerably more training.\n",
    "\n",
    "I made it so you can interchange the neural network used for the images.  By setting the values **WIDTH**, **HEIGHT**, and **OUTPUT_DIM**, you can interchange images.  One characteristic that you are seeking for the image neural network is that it does not have too many outputs (once you strip the 1000-class imagenet classifier, as is common in transfer learning).  InceptionV3 has 2,048 features below the classifier, and MobileNet has over 50K.  If the additional dimensions truly capture aspects of the images, then they are worthwhile.  However, having 50K features increases the processing needed and the complexity of the neural network we are constructing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 89
    },
    "colab_type": "code",
    "id": "DWOP58lrtGwt",
    "outputId": "7e88d00b-5685-46bc-fb0c-e1abba438650"
   },
   "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 [==============================] - 28s 0us/step\n"
     ]
    }
   ],
   "source": [
    "if USE_INCEPTION:\n",
    "  encode_model = InceptionV3(weights='imagenet')\n",
    "  encode_model = Model(encode_model.input, encode_model.layers[-2].output)\n",
    "  WIDTH = 299\n",
    "  HEIGHT = 299\n",
    "  OUTPUT_DIM = 2048\n",
    "  preprocess_input = \\\n",
    "    tensorflow.keras.applications.inception_v3.preprocess_input\n",
    "else:\n",
    "  encode_model = MobileNet(weights='imagenet',include_top=False)\n",
    "  WIDTH = 224\n",
    "  HEIGHT = 224\n",
    "  OUTPUT_DIM = 50176\n",
    "  preprocess_input = tensorflow.keras.applications.mobilenet.preprocess_input"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Wz8_Fu2lgaP3"
   },
   "source": [
    "The summary of the chosen image neural network to be transferred is displayed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "_QQ-D9Rq9SwF",
    "outputId": "51391967-5e66-4037-dcd6-b82941261396"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model\"\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            [(None, 299, 299, 3) 0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d (Conv2D)                 (None, 149, 149, 32) 864         input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization (BatchNorma (None, 149, 149, 32) 96          conv2d[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "activation (Activation)         (None, 149, 149, 32) 0           batch_normalization[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_1 (Conv2D)               (None, 147, 147, 32) 9216        activation[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_1 (BatchNor (None, 147, 147, 32) 96          conv2d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_1 (Activation)       (None, 147, 147, 32) 0           batch_normalization_1[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_2 (Conv2D)               (None, 147, 147, 64) 18432       activation_1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_2 (BatchNor (None, 147, 147, 64) 192         conv2d_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_2 (Activation)       (None, 147, 147, 64) 0           batch_normalization_2[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d (MaxPooling2D)    (None, 73, 73, 64)   0           activation_2[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_3 (Conv2D)               (None, 73, 73, 80)   5120        max_pooling2d[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_3 (BatchNor (None, 73, 73, 80)   240         conv2d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_3 (Activation)       (None, 73, 73, 80)   0           batch_normalization_3[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_4 (Conv2D)               (None, 71, 71, 192)  138240      activation_3[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_4 (BatchNor (None, 71, 71, 192)  576         conv2d_4[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_4 (Activation)       (None, 71, 71, 192)  0           batch_normalization_4[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2D)  (None, 35, 35, 192)  0           activation_4[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_8 (Conv2D)               (None, 35, 35, 64)   12288       max_pooling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_8 (BatchNor (None, 35, 35, 64)   192         conv2d_8[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_8 (Activation)       (None, 35, 35, 64)   0           batch_normalization_8[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_6 (Conv2D)               (None, 35, 35, 48)   9216        max_pooling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_9 (Conv2D)               (None, 35, 35, 96)   55296       activation_8[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_6 (BatchNor (None, 35, 35, 48)   144         conv2d_6[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_9 (BatchNor (None, 35, 35, 96)   288         conv2d_9[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_6 (Activation)       (None, 35, 35, 48)   0           batch_normalization_6[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_9 (Activation)       (None, 35, 35, 96)   0           batch_normalization_9[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d (AveragePooli (None, 35, 35, 192)  0           max_pooling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_5 (Conv2D)               (None, 35, 35, 64)   12288       max_pooling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_7 (Conv2D)               (None, 35, 35, 64)   76800       activation_6[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_10 (Conv2D)              (None, 35, 35, 96)   82944       activation_9[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_11 (Conv2D)              (None, 35, 35, 32)   6144        average_pooling2d[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_5 (BatchNor (None, 35, 35, 64)   192         conv2d_5[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_7 (BatchNor (None, 35, 35, 64)   192         conv2d_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_10 (BatchNo (None, 35, 35, 96)   288         conv2d_10[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_11 (BatchNo (None, 35, 35, 32)   96          conv2d_11[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_5 (Activation)       (None, 35, 35, 64)   0           batch_normalization_5[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_7 (Activation)       (None, 35, 35, 64)   0           batch_normalization_7[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_10 (Activation)      (None, 35, 35, 96)   0           batch_normalization_10[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_11 (Activation)      (None, 35, 35, 32)   0           batch_normalization_11[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed0 (Concatenate)            (None, 35, 35, 256)  0           activation_5[0][0]               \n",
      "                                                                 activation_7[0][0]               \n",
      "                                                                 activation_10[0][0]              \n",
      "                                                                 activation_11[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_15 (Conv2D)              (None, 35, 35, 64)   16384       mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_15 (BatchNo (None, 35, 35, 64)   192         conv2d_15[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_15 (Activation)      (None, 35, 35, 64)   0           batch_normalization_15[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_13 (Conv2D)              (None, 35, 35, 48)   12288       mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_16 (Conv2D)              (None, 35, 35, 96)   55296       activation_15[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_13 (BatchNo (None, 35, 35, 48)   144         conv2d_13[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_16 (BatchNo (None, 35, 35, 96)   288         conv2d_16[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_13 (Activation)      (None, 35, 35, 48)   0           batch_normalization_13[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_16 (Activation)      (None, 35, 35, 96)   0           batch_normalization_16[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_1 (AveragePoo (None, 35, 35, 256)  0           mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_12 (Conv2D)              (None, 35, 35, 64)   16384       mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_14 (Conv2D)              (None, 35, 35, 64)   76800       activation_13[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_17 (Conv2D)              (None, 35, 35, 96)   82944       activation_16[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_18 (Conv2D)              (None, 35, 35, 64)   16384       average_pooling2d_1[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_12 (BatchNo (None, 35, 35, 64)   192         conv2d_12[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_14 (BatchNo (None, 35, 35, 64)   192         conv2d_14[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_17 (BatchNo (None, 35, 35, 96)   288         conv2d_17[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_18 (BatchNo (None, 35, 35, 64)   192         conv2d_18[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_12 (Activation)      (None, 35, 35, 64)   0           batch_normalization_12[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_14 (Activation)      (None, 35, 35, 64)   0           batch_normalization_14[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_17 (Activation)      (None, 35, 35, 96)   0           batch_normalization_17[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_18 (Activation)      (None, 35, 35, 64)   0           batch_normalization_18[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed1 (Concatenate)            (None, 35, 35, 288)  0           activation_12[0][0]              \n",
      "                                                                 activation_14[0][0]              \n",
      "                                                                 activation_17[0][0]              \n",
      "                                                                 activation_18[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_22 (Conv2D)              (None, 35, 35, 64)   18432       mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_22 (BatchNo (None, 35, 35, 64)   192         conv2d_22[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_22 (Activation)      (None, 35, 35, 64)   0           batch_normalization_22[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_20 (Conv2D)              (None, 35, 35, 48)   13824       mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_23 (Conv2D)              (None, 35, 35, 96)   55296       activation_22[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_20 (BatchNo (None, 35, 35, 48)   144         conv2d_20[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_23 (BatchNo (None, 35, 35, 96)   288         conv2d_23[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_20 (Activation)      (None, 35, 35, 48)   0           batch_normalization_20[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_23 (Activation)      (None, 35, 35, 96)   0           batch_normalization_23[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_2 (AveragePoo (None, 35, 35, 288)  0           mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_19 (Conv2D)              (None, 35, 35, 64)   18432       mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_21 (Conv2D)              (None, 35, 35, 64)   76800       activation_20[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_24 (Conv2D)              (None, 35, 35, 96)   82944       activation_23[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_25 (Conv2D)              (None, 35, 35, 64)   18432       average_pooling2d_2[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_19 (BatchNo (None, 35, 35, 64)   192         conv2d_19[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_21 (BatchNo (None, 35, 35, 64)   192         conv2d_21[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_24 (BatchNo (None, 35, 35, 96)   288         conv2d_24[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_25 (BatchNo (None, 35, 35, 64)   192         conv2d_25[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_19 (Activation)      (None, 35, 35, 64)   0           batch_normalization_19[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_21 (Activation)      (None, 35, 35, 64)   0           batch_normalization_21[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_24 (Activation)      (None, 35, 35, 96)   0           batch_normalization_24[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_25 (Activation)      (None, 35, 35, 64)   0           batch_normalization_25[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed2 (Concatenate)            (None, 35, 35, 288)  0           activation_19[0][0]              \n",
      "                                                                 activation_21[0][0]              \n",
      "                                                                 activation_24[0][0]              \n",
      "                                                                 activation_25[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_27 (Conv2D)              (None, 35, 35, 64)   18432       mixed2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_27 (BatchNo (None, 35, 35, 64)   192         conv2d_27[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_27 (Activation)      (None, 35, 35, 64)   0           batch_normalization_27[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_28 (Conv2D)              (None, 35, 35, 96)   55296       activation_27[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_28 (BatchNo (None, 35, 35, 96)   288         conv2d_28[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_28 (Activation)      (None, 35, 35, 96)   0           batch_normalization_28[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_26 (Conv2D)              (None, 17, 17, 384)  995328      mixed2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_29 (Conv2D)              (None, 17, 17, 96)   82944       activation_28[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_26 (BatchNo (None, 17, 17, 384)  1152        conv2d_26[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_29 (BatchNo (None, 17, 17, 96)   288         conv2d_29[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_26 (Activation)      (None, 17, 17, 384)  0           batch_normalization_26[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_29 (Activation)      (None, 17, 17, 96)   0           batch_normalization_29[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2D)  (None, 17, 17, 288)  0           mixed2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "mixed3 (Concatenate)            (None, 17, 17, 768)  0           activation_26[0][0]              \n",
      "                                                                 activation_29[0][0]              \n",
      "                                                                 max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_34 (Conv2D)              (None, 17, 17, 128)  98304       mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_34 (BatchNo (None, 17, 17, 128)  384         conv2d_34[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_34 (Activation)      (None, 17, 17, 128)  0           batch_normalization_34[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_35 (Conv2D)              (None, 17, 17, 128)  114688      activation_34[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_31 (Conv2D)              (None, 17, 17, 128)  98304       mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_36 (Conv2D)              (None, 17, 17, 128)  114688      activation_35[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_31 (BatchNo (None, 17, 17, 128)  384         conv2d_31[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_36 (BatchNo (None, 17, 17, 128)  384         conv2d_36[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_31 (Activation)      (None, 17, 17, 128)  0           batch_normalization_31[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)  114688      activation_31[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",
      "average_pooling2d_3 (AveragePoo (None, 17, 17, 768)  0           mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_30 (Conv2D)              (None, 17, 17, 192)  147456      mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_33 (Conv2D)              (None, 17, 17, 192)  172032      activation_32[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_38 (Conv2D)              (None, 17, 17, 192)  172032      activation_37[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_39 (Conv2D)              (None, 17, 17, 192)  147456      average_pooling2d_3[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_30 (BatchNo (None, 17, 17, 192)  576         conv2d_30[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_33 (BatchNo (None, 17, 17, 192)  576         conv2d_33[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_38 (BatchNo (None, 17, 17, 192)  576         conv2d_38[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_39 (BatchNo (None, 17, 17, 192)  576         conv2d_39[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_30 (Activation)      (None, 17, 17, 192)  0           batch_normalization_30[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_33 (Activation)      (None, 17, 17, 192)  0           batch_normalization_33[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_38 (Activation)      (None, 17, 17, 192)  0           batch_normalization_38[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_39 (Activation)      (None, 17, 17, 192)  0           batch_normalization_39[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed4 (Concatenate)            (None, 17, 17, 768)  0           activation_30[0][0]              \n",
      "                                                                 activation_33[0][0]              \n",
      "                                                                 activation_38[0][0]              \n",
      "                                                                 activation_39[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_44 (Conv2D)              (None, 17, 17, 160)  122880      mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_44 (BatchNo (None, 17, 17, 160)  480         conv2d_44[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_44 (Activation)      (None, 17, 17, 160)  0           batch_normalization_44[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_45 (Conv2D)              (None, 17, 17, 160)  179200      activation_44[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_41 (Conv2D)              (None, 17, 17, 160)  122880      mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_46 (Conv2D)              (None, 17, 17, 160)  179200      activation_45[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_41 (BatchNo (None, 17, 17, 160)  480         conv2d_41[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_46 (BatchNo (None, 17, 17, 160)  480         conv2d_46[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_41 (Activation)      (None, 17, 17, 160)  0           batch_normalization_41[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)  179200      activation_41[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",
      "average_pooling2d_4 (AveragePoo (None, 17, 17, 768)  0           mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_40 (Conv2D)              (None, 17, 17, 192)  147456      mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_43 (Conv2D)              (None, 17, 17, 192)  215040      activation_42[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_48 (Conv2D)              (None, 17, 17, 192)  215040      activation_47[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_49 (Conv2D)              (None, 17, 17, 192)  147456      average_pooling2d_4[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_40 (BatchNo (None, 17, 17, 192)  576         conv2d_40[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_43 (BatchNo (None, 17, 17, 192)  576         conv2d_43[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_48 (BatchNo (None, 17, 17, 192)  576         conv2d_48[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_49 (BatchNo (None, 17, 17, 192)  576         conv2d_49[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_40 (Activation)      (None, 17, 17, 192)  0           batch_normalization_40[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_43 (Activation)      (None, 17, 17, 192)  0           batch_normalization_43[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_48 (Activation)      (None, 17, 17, 192)  0           batch_normalization_48[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_49 (Activation)      (None, 17, 17, 192)  0           batch_normalization_49[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed5 (Concatenate)            (None, 17, 17, 768)  0           activation_40[0][0]              \n",
      "                                                                 activation_43[0][0]              \n",
      "                                                                 activation_48[0][0]              \n",
      "                                                                 activation_49[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_54 (Conv2D)              (None, 17, 17, 160)  122880      mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_54 (BatchNo (None, 17, 17, 160)  480         conv2d_54[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_54 (Activation)      (None, 17, 17, 160)  0           batch_normalization_54[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_55 (Conv2D)              (None, 17, 17, 160)  179200      activation_54[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_51 (Conv2D)              (None, 17, 17, 160)  122880      mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_56 (Conv2D)              (None, 17, 17, 160)  179200      activation_55[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_51 (BatchNo (None, 17, 17, 160)  480         conv2d_51[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_56 (BatchNo (None, 17, 17, 160)  480         conv2d_56[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_51 (Activation)      (None, 17, 17, 160)  0           batch_normalization_51[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)  179200      activation_51[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",
      "average_pooling2d_5 (AveragePoo (None, 17, 17, 768)  0           mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_50 (Conv2D)              (None, 17, 17, 192)  147456      mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_53 (Conv2D)              (None, 17, 17, 192)  215040      activation_52[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_58 (Conv2D)              (None, 17, 17, 192)  215040      activation_57[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_59 (Conv2D)              (None, 17, 17, 192)  147456      average_pooling2d_5[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_50 (BatchNo (None, 17, 17, 192)  576         conv2d_50[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_53 (BatchNo (None, 17, 17, 192)  576         conv2d_53[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_58 (BatchNo (None, 17, 17, 192)  576         conv2d_58[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_59 (BatchNo (None, 17, 17, 192)  576         conv2d_59[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_50 (Activation)      (None, 17, 17, 192)  0           batch_normalization_50[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_53 (Activation)      (None, 17, 17, 192)  0           batch_normalization_53[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_58 (Activation)      (None, 17, 17, 192)  0           batch_normalization_58[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_59 (Activation)      (None, 17, 17, 192)  0           batch_normalization_59[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed6 (Concatenate)            (None, 17, 17, 768)  0           activation_50[0][0]              \n",
      "                                                                 activation_53[0][0]              \n",
      "                                                                 activation_58[0][0]              \n",
      "                                                                 activation_59[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_64 (Conv2D)              (None, 17, 17, 192)  147456      mixed6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_64 (BatchNo (None, 17, 17, 192)  576         conv2d_64[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_64 (Activation)      (None, 17, 17, 192)  0           batch_normalization_64[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_65 (Conv2D)              (None, 17, 17, 192)  258048      activation_64[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_61 (Conv2D)              (None, 17, 17, 192)  147456      mixed6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_66 (Conv2D)              (None, 17, 17, 192)  258048      activation_65[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_61 (BatchNo (None, 17, 17, 192)  576         conv2d_61[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_66 (BatchNo (None, 17, 17, 192)  576         conv2d_66[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_61 (Activation)      (None, 17, 17, 192)  0           batch_normalization_61[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)  258048      activation_61[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",
      "average_pooling2d_6 (AveragePoo (None, 17, 17, 768)  0           mixed6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_60 (Conv2D)              (None, 17, 17, 192)  147456      mixed6[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",
      "conv2d_69 (Conv2D)              (None, 17, 17, 192)  147456      average_pooling2d_6[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_60 (BatchNo (None, 17, 17, 192)  576         conv2d_60[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",
      "batch_normalization_69 (BatchNo (None, 17, 17, 192)  576         conv2d_69[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_60 (Activation)      (None, 17, 17, 192)  0           batch_normalization_60[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",
      "activation_69 (Activation)      (None, 17, 17, 192)  0           batch_normalization_69[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed7 (Concatenate)            (None, 17, 17, 768)  0           activation_60[0][0]              \n",
      "                                                                 activation_63[0][0]              \n",
      "                                                                 activation_68[0][0]              \n",
      "                                                                 activation_69[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_72 (Conv2D)              (None, 17, 17, 192)  147456      mixed7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_72 (BatchNo (None, 17, 17, 192)  576         conv2d_72[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_72 (Activation)      (None, 17, 17, 192)  0           batch_normalization_72[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_73 (Conv2D)              (None, 17, 17, 192)  258048      activation_72[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_70 (Conv2D)              (None, 17, 17, 192)  147456      mixed7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_74 (Conv2D)              (None, 17, 17, 192)  258048      activation_73[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_70 (BatchNo (None, 17, 17, 192)  576         conv2d_70[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_74 (BatchNo (None, 17, 17, 192)  576         conv2d_74[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_70 (Activation)      (None, 17, 17, 192)  0           batch_normalization_70[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_74 (Activation)      (None, 17, 17, 192)  0           batch_normalization_74[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_71 (Conv2D)              (None, 8, 8, 320)    552960      activation_70[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_75 (Conv2D)              (None, 8, 8, 192)    331776      activation_74[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_71 (BatchNo (None, 8, 8, 320)    960         conv2d_71[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_75 (BatchNo (None, 8, 8, 192)    576         conv2d_75[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_71 (Activation)      (None, 8, 8, 320)    0           batch_normalization_71[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_75 (Activation)      (None, 8, 8, 192)    0           batch_normalization_75[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_3 (MaxPooling2D)  (None, 8, 8, 768)    0           mixed7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "mixed8 (Concatenate)            (None, 8, 8, 1280)   0           activation_71[0][0]              \n",
      "                                                                 activation_75[0][0]              \n",
      "                                                                 max_pooling2d_3[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_80 (Conv2D)              (None, 8, 8, 448)    573440      mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_80 (BatchNo (None, 8, 8, 448)    1344        conv2d_80[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_80 (Activation)      (None, 8, 8, 448)    0           batch_normalization_80[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_77 (Conv2D)              (None, 8, 8, 384)    491520      mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_81 (Conv2D)              (None, 8, 8, 384)    1548288     activation_80[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_77 (BatchNo (None, 8, 8, 384)    1152        conv2d_77[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_81 (BatchNo (None, 8, 8, 384)    1152        conv2d_81[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_77 (Activation)      (None, 8, 8, 384)    0           batch_normalization_77[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_81 (Activation)      (None, 8, 8, 384)    0           batch_normalization_81[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_78 (Conv2D)              (None, 8, 8, 384)    442368      activation_77[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_79 (Conv2D)              (None, 8, 8, 384)    442368      activation_77[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_82 (Conv2D)              (None, 8, 8, 384)    442368      activation_81[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_83 (Conv2D)              (None, 8, 8, 384)    442368      activation_81[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_7 (AveragePoo (None, 8, 8, 1280)   0           mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_76 (Conv2D)              (None, 8, 8, 320)    409600      mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_78 (BatchNo (None, 8, 8, 384)    1152        conv2d_78[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_79 (BatchNo (None, 8, 8, 384)    1152        conv2d_79[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_82 (BatchNo (None, 8, 8, 384)    1152        conv2d_82[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_83 (BatchNo (None, 8, 8, 384)    1152        conv2d_83[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_84 (Conv2D)              (None, 8, 8, 192)    245760      average_pooling2d_7[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_76 (BatchNo (None, 8, 8, 320)    960         conv2d_76[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_78 (Activation)      (None, 8, 8, 384)    0           batch_normalization_78[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_79 (Activation)      (None, 8, 8, 384)    0           batch_normalization_79[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_82 (Activation)      (None, 8, 8, 384)    0           batch_normalization_82[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_83 (Activation)      (None, 8, 8, 384)    0           batch_normalization_83[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_84 (BatchNo (None, 8, 8, 192)    576         conv2d_84[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_76 (Activation)      (None, 8, 8, 320)    0           batch_normalization_76[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed9_0 (Concatenate)          (None, 8, 8, 768)    0           activation_78[0][0]              \n",
      "                                                                 activation_79[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "concatenate (Concatenate)       (None, 8, 8, 768)    0           activation_82[0][0]              \n",
      "                                                                 activation_83[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_84 (Activation)      (None, 8, 8, 192)    0           batch_normalization_84[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed9 (Concatenate)            (None, 8, 8, 2048)   0           activation_76[0][0]              \n",
      "                                                                 mixed9_0[0][0]                   \n",
      "                                                                 concatenate[0][0]                \n",
      "                                                                 activation_84[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_89 (Conv2D)              (None, 8, 8, 448)    917504      mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_89 (BatchNo (None, 8, 8, 448)    1344        conv2d_89[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_89 (Activation)      (None, 8, 8, 448)    0           batch_normalization_89[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_86 (Conv2D)              (None, 8, 8, 384)    786432      mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_90 (Conv2D)              (None, 8, 8, 384)    1548288     activation_89[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_86 (BatchNo (None, 8, 8, 384)    1152        conv2d_86[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_90 (BatchNo (None, 8, 8, 384)    1152        conv2d_90[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_86 (Activation)      (None, 8, 8, 384)    0           batch_normalization_86[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_90 (Activation)      (None, 8, 8, 384)    0           batch_normalization_90[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_87 (Conv2D)              (None, 8, 8, 384)    442368      activation_86[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_88 (Conv2D)              (None, 8, 8, 384)    442368      activation_86[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_91 (Conv2D)              (None, 8, 8, 384)    442368      activation_90[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_92 (Conv2D)              (None, 8, 8, 384)    442368      activation_90[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_8 (AveragePoo (None, 8, 8, 2048)   0           mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_85 (Conv2D)              (None, 8, 8, 320)    655360      mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_87 (BatchNo (None, 8, 8, 384)    1152        conv2d_87[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_88 (BatchNo (None, 8, 8, 384)    1152        conv2d_88[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_91 (BatchNo (None, 8, 8, 384)    1152        conv2d_91[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_92 (BatchNo (None, 8, 8, 384)    1152        conv2d_92[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_93 (Conv2D)              (None, 8, 8, 192)    393216      average_pooling2d_8[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_85 (BatchNo (None, 8, 8, 320)    960         conv2d_85[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_87 (Activation)      (None, 8, 8, 384)    0           batch_normalization_87[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_88 (Activation)      (None, 8, 8, 384)    0           batch_normalization_88[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_91 (Activation)      (None, 8, 8, 384)    0           batch_normalization_91[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_92 (Activation)      (None, 8, 8, 384)    0           batch_normalization_92[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_93 (BatchNo (None, 8, 8, 192)    576         conv2d_93[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_85 (Activation)      (None, 8, 8, 320)    0           batch_normalization_85[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed9_1 (Concatenate)          (None, 8, 8, 768)    0           activation_87[0][0]              \n",
      "                                                                 activation_88[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_1 (Concatenate)     (None, 8, 8, 768)    0           activation_91[0][0]              \n",
      "                                                                 activation_92[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_93 (Activation)      (None, 8, 8, 192)    0           batch_normalization_93[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed10 (Concatenate)           (None, 8, 8, 2048)   0           activation_85[0][0]              \n",
      "                                                                 mixed9_1[0][0]                   \n",
      "                                                                 concatenate_1[0][0]              \n",
      "                                                                 activation_93[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "avg_pool (GlobalAveragePooling2 (None, 2048)         0           mixed10[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 21,802,784\n",
      "Trainable params: 21,768,352\n",
      "Non-trainable params: 34,432\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "encode_model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "FZCQH7nvhNdc"
   },
   "source": [
    "### Creating the Training Set\n",
    "\n",
    "We need to encode the images to create the training set.  Later we will encode new images to present them for captioning."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "SeT4zJ8l9Ps9"
   },
   "outputs": [],
   "source": [
    "def encodeImage(img):\n",
    "  # Resize all images to a standard size (specified bythe image \n",
    "  # encoding network)\n",
    "  img = img.resize((WIDTH, HEIGHT), Image.ANTIALIAS)\n",
    "  # Convert a PIL image to a numpy array\n",
    "  x = tensorflow.keras.preprocessing.image.img_to_array(img)\n",
    "  # Expand to 2D array\n",
    "  x = np.expand_dims(x, axis=0)\n",
    "  # Perform any preprocessing needed by InceptionV3 or others\n",
    "  x = preprocess_input(x)\n",
    "  # Call InceptionV3 (or other) to extract the smaller feature set for \n",
    "  # the image.\n",
    "  x = encode_model.predict(x) # Get the encoding vector for the image\n",
    "  # Shape to correct form to be accepted by LSTM captioning network.\n",
    "  x = np.reshape(x, OUTPUT_DIM )\n",
    "  return x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Ni6VXDiVgaQe"
   },
   "source": [
    "We can how to generate the training set, which will involve looping over every JPG that we provided.  Because this can take a while to perform, we will save it to a pickle file.  This saved file prevents the considerable time needed to reprocess all of the images again.  Because the images are processed differently by different transferred neural networks, the filename contains the output dimensions. We follow this naming convention because if you changed from InceptionV3 to MobileNet, the number of output dimensions would change, and you must reprocess the images."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "OfusVb6uKREw"
   },
   "outputs": [],
   "source": [
    "train_path = os.path.join(root_captioning,\"data\",f'train{OUTPUT_DIM}.pkl')\n",
    "if not os.path.exists(train_path):\n",
    "  start = time()\n",
    "  encoding_train = {}\n",
    "  for id in tqdm(train_img):\n",
    "    image_path = os.path.join(root_captioning,'Flicker8k_Dataset', id)\n",
    "    img = tensorflow.keras.preprocessing.image.load_img(image_path, \\\n",
    "            target_size=(HEIGHT, WIDTH))\n",
    "    encoding_train[id] = encodeImage(img)\n",
    "  with open(train_path, \"wb\") as fp:\n",
    "    pickle.dump(encoding_train, fp)\n",
    "  print(f\"\\nGenerating training set took: {hms_string(time()-start)}\")\n",
    "else:\n",
    "  with open(train_path, \"rb\") as fp:\n",
    "    encoding_train = pickle.load(fp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "0sM7abSfgaQo"
   },
   "source": [
    "We must also perform a similar process for the test images."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "4mO2cNDOP64-"
   },
   "outputs": [],
   "source": [
    "test_path = os.path.join(root_captioning,\"data\",f'test{OUTPUT_DIM}.pkl')\n",
    "if not os.path.exists(test_path):\n",
    "  start = time()\n",
    "  encoding_test = {}\n",
    "  for id in tqdm(test_img):\n",
    "    image_path = os.path.join(root_captioning,'Flicker8k_Dataset', id)\n",
    "    img = tensorflow.keras.preprocessing.image.load_img(image_path, \\\n",
    "                target_size=(HEIGHT, WIDTH))\n",
    "    encoding_test[id] = encodeImage(img)\n",
    "  with open(test_path, \"wb\") as fp:\n",
    "    pickle.dump(encoding_test, fp)\n",
    "  print(f\"\\nGenerating testing set took: {hms_string(time()-start)}\")\n",
    "else:\n",
    "  with open(test_path, \"rb\") as fp:\n",
    "    encoding_test = pickle.load(fp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "0Ao7N4JngaQv"
   },
   "source": [
    "Next, we separate the captions that we will use for training.  There are two sides to this training, the images, and the captions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "colab_type": "code",
    "id": "C8DFzzPmXg-n",
    "outputId": "5e13badb-7d6b-43ad-c6eb-10269c023a1f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30000"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_train_captions = []\n",
    "for key, val in train_descriptions.items():\n",
    "    for cap in val:\n",
    "        all_train_captions.append(cap)\n",
    "len(all_train_captions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "KiTjOC_9x1_x"
   },
   "source": [
    "Words that do not occur very often can be misleading to neural network training.  It is better to remove such words.  Here we remove any words that occur less than ten times.  We display the new reduced size of the vocabulary shrunk."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "colab_type": "code",
    "id": "-HxHSgLgYUUE",
    "outputId": "5ca662de-6c95-43e9-a3c4-47411fa8ed31"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "preprocessed words 7578 ==> 1651\n"
     ]
    }
   ],
   "source": [
    "word_count_threshold = 10\n",
    "word_counts = {}\n",
    "nsents = 0\n",
    "for sent in all_train_captions:\n",
    "    nsents += 1\n",
    "    for w in sent.split(' '):\n",
    "        word_counts[w] = word_counts.get(w, 0) + 1\n",
    "\n",
    "vocab = [w for w in word_counts if word_counts[w] >= word_count_threshold]\n",
    "print('preprocessed words %d ==> %d' % (len(word_counts), len(vocab)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "E3vQYH860N8J"
   },
   "source": [
    "Next, we build two lookup tables for this vocabulary. The table **idxtoword** converts index numbers to actual words to index values.  The **wordtoidx** lookup table performs the opposite."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "colab_type": "code",
    "id": "Oi3zqAUhYcNP",
    "outputId": "f8de8619-8aa8-4428-fac6-5dae7c0d4e86"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1652"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "idxtoword = {}\n",
    "wordtoidx = {}\n",
    "\n",
    "ix = 1\n",
    "for w in vocab:\n",
    "    wordtoidx[w] = ix\n",
    "    idxtoword[ix] = w\n",
    "    ix += 1\n",
    "    \n",
    "vocab_size = len(idxtoword) + 1 \n",
    "vocab_size"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Rxs9sfOq0Xxz"
   },
   "source": [
    "Previously we added a start and stop token to all sentences.  We must account for this in the maximum length of captions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "colab_type": "code",
    "id": "KSohY53bYjTi",
    "outputId": "624663a9-7134-407f-867c-c3c153643785"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "34\n"
     ]
    }
   ],
   "source": [
    "max_length +=2\n",
    "print(max_length)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "YOLTDiQC0i_r"
   },
   "source": [
    "### Using a Data Generator\n",
    "\n",
    "Up to this point, we've always generated training data ahead of time and fit the neural network to it.  It is not always practical to create all of the training data ahead of time.  The memory demands can be considerable.  If we generate the training data as the neural network needs it, it is possible to use a Keras generator.  The generator will create new data as it is needed.  The generator provided here creates the training data for the caption neural network, as it is needed.\n",
    "\n",
    "If we were to build all needed training data ahead of time, it would look like Figure 10.CAP-WORK.\n",
    "\n",
    "**Figure 10.CAP-WORK: Captioning Training Data**\n",
    "![Captioning](https://raw.githubusercontent.com/jeffheaton/t81_558_deep_learning/master/images/caption-2.png \"Captioning\")\n",
    "\n",
    "Here we are just training on two captions.  However, we would have to duplicate the image for each of these partial captions that we have.  Additionally, the Flikr8K data set has five captions for each picture.  Those would all require duplication of data as well.  It is much more efficient to generate the data as needed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "gZsbbCx6d04X"
   },
   "outputs": [],
   "source": [
    "def data_generator(descriptions, photos, wordtoidx, \\\n",
    "                   max_length, num_photos_per_batch):\n",
    "  # x1 - Training data for photos\n",
    "  # x2 - The caption that goes with each photo\n",
    "  # y - The predicted rest of the caption\n",
    "  x1, x2, y = [], [], []\n",
    "  n=0\n",
    "  while True:\n",
    "    for key, desc_list in descriptions.items():\n",
    "      n+=1\n",
    "      photo = photos[key+'.jpg']\n",
    "      # Each photo has 5 descriptions\n",
    "      for desc in desc_list:\n",
    "        # Convert each word into a list of sequences.\n",
    "        seq = [wordtoidx[word] for word in desc.split(' ') \\\n",
    "               if word in wordtoidx]\n",
    "        # Generate a training case for every possible sequence and outcome\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",
    "          x1.append(photo)\n",
    "          x2.append(in_seq)\n",
    "          y.append(out_seq)\n",
    "      if n==num_photos_per_batch:\n",
    "        yield ([np.array(x1), np.array(x2)], np.array(y))\n",
    "        x1, x2, y = [], [], []\n",
    "        n=0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "vtIIFt4m6pTv"
   },
   "source": [
    "### Loading Glove Embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 52
    },
    "colab_type": "code",
    "id": "IY_9XZ4Hec73",
    "outputId": "e012f280-24a3-4a76-a3d9-e0976769f6a8",
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "400000it [00:22, 17942.21it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 400000 word vectors.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "glove_dir = os.path.join(root_captioning,'glove.6B')\n",
    "embeddings_index = {} \n",
    "f = open(os.path.join(glove_dir, 'glove.6B.200d.txt'), encoding=\"utf-8\")\n",
    "\n",
    "for line in tqdm(f):\n",
    "    values = line.split()\n",
    "    word = values[0]\n",
    "    coefs = np.asarray(values[1:], dtype='float32')\n",
    "    embeddings_index[word] = coefs\n",
    "\n",
    "f.close()\n",
    "print(f'Found {len(embeddings_index)} word vectors.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "kYH3-S2n82MN"
   },
   "source": [
    "### Building the Neural Network\n",
    "\n",
    "We build an embedding matrix from Glove.  We will directly copy this matrix to the weight matrix of the neural network."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "adEmnYFEfog6"
   },
   "outputs": [],
   "source": [
    "embedding_dim = 200\n",
    "\n",
    "# Get 200-dim dense vector for each of the 10000 words in out vocabulary\n",
    "embedding_matrix = np.zeros((vocab_size, embedding_dim))\n",
    "\n",
    "for word, i in wordtoidx.items():\n",
    "    #if i < max_words:\n",
    "    embedding_vector = embeddings_index.get(word)\n",
    "    if embedding_vector is not None:\n",
    "        # Words not found in the embedding index will be all zeros\n",
    "        embedding_matrix[i] = embedding_vector"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "GpuNLhoaCf5N"
   },
   "source": [
    "The matrix dimensions make sense.  It is 1652 (the size of the vocabulary) by 200 (the number of features Glove generates for each word)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "colab_type": "code",
    "id": "86hPHHjSfx8p",
    "outputId": "8bda8cb8-7edb-4381-f8cf-b03055cccf25"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1652, 200)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "embedding_matrix.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 141
    },
    "colab_type": "code",
    "id": "2homy6Znf7wL",
    "outputId": "42ba0f60-fa39-4583-efcb-0662aab97a23"
   },
   "outputs": [],
   "source": [
    "inputs1 = Input(shape=(OUTPUT_DIM,))\n",
    "fe1 = Dropout(0.5)(inputs1)\n",
    "fe2 = Dense(256, activation='relu')(fe1)\n",
    "inputs2 = Input(shape=(max_length,))\n",
    "se1 = Embedding(vocab_size, embedding_dim, mask_zero=True)(inputs2)\n",
    "se2 = Dropout(0.5)(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",
    "caption_model = Model(inputs=[inputs1, inputs2], outputs=outputs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "colab_type": "code",
    "id": "UcCe2n5pnGfo",
    "outputId": "1970d918-4445-4632-ace0-c3905023c8ac"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "embedding_dim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 520
    },
    "colab_type": "code",
    "id": "asGo7TqRfgJp",
    "outputId": "5349e27e-5e2f-46cb-ff93-4d189800651e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model_1\"\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 (Embedding)           (None, 34, 200)      330400      input_3[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dropout (Dropout)               (None, 2048)         0           input_2[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dropout_1 (Dropout)             (None, 34, 200)      0           embedding[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dense (Dense)                   (None, 256)          524544      dropout[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "lstm (LSTM)                     (None, 256)          467968      dropout_1[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "add (Add)                       (None, 256)          0           dense[0][0]                      \n",
      "                                                                 lstm[0][0]                       \n",
      "__________________________________________________________________________________________________\n",
      "dense_1 (Dense)                 (None, 256)          65792       add[0][0]                        \n",
      "__________________________________________________________________________________________________\n",
      "dense_2 (Dense)                 (None, 1652)         424564      dense_1[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 1,813,268\n",
      "Trainable params: 1,813,268\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "caption_model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "gze36nMIfoEg"
   },
   "outputs": [],
   "source": [
    "caption_model.layers[2].set_weights([embedding_matrix])\n",
    "caption_model.layers[2].trainable = False\n",
    "caption_model.compile(loss='categorical_crossentropy', optimizer='adam')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "wCSzCGtB8-KM"
   },
   "source": [
    "### Train the Neural Network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "0LXG3PE5fxzU"
   },
   "outputs": [],
   "source": [
    "number_pics_per_bath = 3\n",
    "steps = len(train_descriptions)//number_pics_per_bath"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "dyCHBbjnf2b1"
   },
   "outputs": [],
   "source": [
    "model_path = os.path.join(root_captioning,\"data\",f'caption-model.hdf5')\n",
    "if not os.path.exists(model_path):\n",
    "  for i in tqdm(range(EPOCHS*2)):\n",
    "      generator = data_generator(train_descriptions, encoding_train, \n",
    "                    wordtoidx, max_length, number_pics_per_bath)\n",
    "      caption_model.fit_generator(generator, epochs=1,\n",
    "                    steps_per_epoch=steps, verbose=1)\n",
    "\n",
    "  caption_model.optimizer.lr = 1e-4\n",
    "  number_pics_per_bath = 6\n",
    "  steps = len(train_descriptions)//number_pics_per_bath\n",
    "\n",
    "  for i in range(EPOCHS):\n",
    "      generator = data_generator(train_descriptions, encoding_train, \n",
    "                    wordtoidx, max_length, number_pics_per_bath)\n",
    "      caption_model.fit_generator(generator, epochs=1, \n",
    "                            steps_per_epoch=steps, verbose=1)  \n",
    "  caption_model.save_weights(model_path)\n",
    "  print(f\"\\Training took: {hms_string(time()-start)}\")\n",
    "else:\n",
    "  caption_model.load_weights(model_path)\n",
    "    \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Ymx07aUHpHMZ"
   },
   "source": [
    "### Generating Captions\n",
    "\n",
    "It is essential to understand that we do not generate a caption with one single call to the neural network's predict function.  Neural networks output a fixed-length tensor.  To get a variable-length output, such as free-form text, requires multiple calls to the neural network.\n",
    "\n",
    "The neural network accepts two objects (which we map to the input neurons).  The first input is the photo, and the second input is an ever-growing caption.  The caption begins with just the starting token.  The neural network's output is the prediction of the next word in the caption.  The caption continues to grow until the neural network predicts an end token, or we reach the maximum length of a caption.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "JPKINJ3JMbSy"
   },
   "outputs": [],
   "source": [
    "def generateCaption(photo):\n",
    "    in_text = START\n",
    "    for i in range(max_length):\n",
    "        sequence = [wordtoidx[w] for w in in_text.split() if w in wordtoidx]\n",
    "        sequence = pad_sequences([sequence], maxlen=max_length)\n",
    "        yhat = caption_model.predict([photo,sequence], verbose=0)\n",
    "        yhat = np.argmax(yhat)\n",
    "        word = idxtoword[yhat]\n",
    "        in_text += ' ' + word\n",
    "        if word == STOP:\n",
    "            break\n",
    "    final = in_text.split()\n",
    "    final = final[1:-1]\n",
    "    final = ' '.join(final)\n",
    "    return final"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "MAv_Bab17WeD"
   },
   "source": [
    "### Evaluate Performance on Test Data from Flicker8k\n",
    "\n",
    "The caption model performs relatively well on images that are similar to the training set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "TtaaQI8wMsst",
    "outputId": "4819cd3e-f4c0-4a7a-b609-92635e877297"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./data/captions\\Flicker8k_Dataset\\3485425825_c2f3446e73.jpg\n"
     ]
    },
    {
     "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": [
      "Caption: man in white shirt is standing by woman with blue hat\n",
      "_____________________________________\n",
      "./data/captions\\Flicker8k_Dataset\\3490736665_38710f4b91.jpg\n"
     ]
    },
    {
     "data": {
      "image/png": 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qEO4n9KeUtUEzUch1PKBmc2oM8wTPABcMS18Zkt4BygESrVNGFAxHPV5/87ucf+hJvvuXv8cbr3+Fc099lh8mHxq4//+RGkhkBQSBYpl8N20G13bvoSAhVO7dFDjVQOZrIKvdpfDAautWeFUZwII6QaEGQu/Hz2FsxU9L/aymQf4993bkc19Hf6dbqS5YY/0hm6Du/6Rnh0xxP6aWarSu+jk1gaY9Dy8ER3ta00By2hM4YpnUmQlKSbzwJJFmdrbN7GwbU5ZgPU4HjpFKOSqpwDuU1IEPjyyvvvA1+ru73O8p3t10jLxkuPAkC50Bjf1dBt0ug/VV+rubzM/NIN1BsAxVoAyiOEFVbm7d92AYltjS4b1F+gZeCPLSkWUZcTvFW4MpcrYebHEwKukPRpxabtPKwKFotloUo5KyzOl2+1jvOffwHPfvXmNnY5OiyHF+G+lStu/lzJ+1tHJIG4oiGzKz2Obc2Vm270m0clVGToJA4gUYY5BSAw5cWVmGYF1w812gmYPl7MEYj/Aaax3OuqDwVQAoKTTeOrTweOkQHgojcc4SKYXHhrXgQeIxhaE0Fo9DouhVE9C7wFM7PMp7cAKHoPAC4Su+WIUAvVcSHSmSWJCmTeI0DuAfx7RbDbJmiyyOaDRiokZMEsdkcTxWDLGOAlDKoNmUFkgRgXRVVhS0ZudYuPAI/dGIXrfLg3u3GfWucvaRp7jz5l8hRMTHn//PaDc74Eus0XhfMhp1QQmanTbWQWdxkSiOsUJS9PdBabK4RSQFe3vbtGdmmV1uce/+GlnU4PI7b3Lm7DynTi2TpW0snlQrosqTwrkxICilgkdara/KYayww1eWdzBy6nVV00++Wnn1Ops2KgMuhCBvMIyCd7q5vcKXv/q/cOfdW3z+M3+HP/k//zlP//RP8w+f+yxf+9ZX3hdzavlIgDsiuDThpawovyOcc/XXCY9ETvHUwdqvkbkeQMFEm07+gRJUaXCiSpub7kbtCh+Oik/QtO7j4T4dlaCc3wv4gXaq09am3JIacCtPogZkP55AYux9BE/jCCD7yjbyckwpVfZzvYzfV/kcDab6mpM8AuzeB6tZCvDegtcIL7hx4ypz80tEccrag1ucOHWS2WabKI7QUob2dOiHRrK6/i73rr/F6voWr1+7i2rtcOnZ52m3M2yRotMGWafL1u0rRCnEsSRVTU4szFOaEVKAMQ5rPdZajDF4HxSOVpo4TkB4mi1Jbj173RGddgswJNJjyphRb59+UaJERCI0cSyImx0azYRimCNEQi9LkVqSF0O6D7bZXz+gtID3aDnElE1G/R5OHmDLGO8USu7gtaXRapCmkjjRKGGRKJwj0BrOIqSgHJXj+eoIVr101bwTIR4QgqgeYy3OhskTsmSC92StxXpPaRzCSWItKFyOEIJIRIDH+ZBJ5a2kdA6hPd5Z6tRRUQX5hFIETggsIXPHOoGKJFJU3ofxGAe28PR7u1jrMVWmTwgEEgK5OApvUUKhlQQtETpC6Zg41iitacSKKIrQUYpQcOrcMicX5zmtZjGdeba3uuztrPLJz3ye3Y2cy6/9AbOnznP27MeZb81gfImUMSoWDIY98rxPo9nGjAaUxQBTGuJ4jr2tVXzZJe20UVETYxw6a7KxeZe17fssLZ6nkIakFfHVr/4ZPh/SWlgm63T44he+yEI2O7GuAKnkJIbnfeU9Bwo5xJTkGKxBTNI1q2M9frym6+CyHGft1PGYgBHOhbUZyQbnZh/noZ97nkcf+wTf+PrXuPXGFRo/d4aLz/4EVU7K+8pHAtwFhNQ0L8eDOaYemIBoHcaQ3h+iZRATYJ6A6nQ2yDQ0e/AOQeDkJUE7T6sSVT+QcV/CeVPP+RCwHw5uTrtcU6BataOqjozB3E9okAn5MvEeghHux5Z9bVxPK48axL2fcPp12h2eimT3h4B80q3pz0I7w8GAOI6JIz2mjob5AGNywDI3swhC89xzz7H6YJvtrT0evngBS8mDzU0W5hdoZJpYJ1X6m8dHOa9/66/IdzaZXWhjnWHn7k12dre59OgTRM0ORb/H6vW32N9Z4XyziSlyyAT73QPmF2bCs3Iht2PMSbvAYbrSU9qCfSMRZU5pHUmjwcmlefIyh2KEiDVmcRGnBmi5j/MFjUaTKI2Z6bQp4xjvDErmIX0vV+z1c3q7FTVSKWRrPb0DT2QNvgDj+6RYGmmEbsWMRgP2+wZb5kjhSVNNM0vQUUwcKdqtDCWCJ2KtxTqLtSGe4DxYU6W6eULw2IY0TudtpVzBC1kF9hTGOExuMbKJKQukl1hfYJ0DJ8FbElSgfpzFTHm53jsQYEWEt9V+Ah1VikwAEQBWOoSwgX/HIWKJ9Xo8Wb1zCBH6rYlwXiKcB+sZDoc4P6IsLWiNFwpjS0pA6Yhfff4/4ud/7dfZW99mb2uPhZlTMBjx1b/4F1z42C+ytn3A7MVFFpdOQ+TxOaxsvky7tYAtUrJmQrPRoLu/i7eCuc4Cd+7cQmk4c/o8+/v3GYp1omwBK+Hezg42TvnOS19jaX6Rg+37LF96goPVdc6cOcude7f44y//a372536JSwvLIQVXyrD+feDHQwC/itOJQPtMpzpOUiTFGLfqJT+93mqGQHiJrKgj4RWqoi8a7YSf/5v/gFvXL/Ol3/nfSOaaqNkmX/rtf0az2eSHyUcG3LVUUzTIZEAOZ414NIet8aO0iBeTQQz0TQV2h6zvCaCNQaLqSM2118dIWedPH3kwTL0eg/tkM4mvCKSjVw3gezgQMs4Kmj7f17b39EAdniD1uV7K8Zj5inqpx5XDt/O+MrEuYJSPKPKcNE0RQqCUpihKBv0BO7ubXLv2DmfPnePcuQvMzy+xuDhPJCWddpvhqM++2mFl7R2sMZw/8zjz87MkseDaO5fZuX0d40sebA/o7e4AHru7yp0X10AphLPkgxwGBXErI4kUaZayvHwWGfmwmclBlfaBcy5kYjiPSy2mELz85jbeKoYHPc4sxmSpoNGcob/v0F7RamdEacRCJyGNE2SSYowja0QkkUf6DCEdHs3ogaNMFaMeCBtmidSCPC/wDspCQGEoZU4LOHNykYWzc7iyxBrPfnfI5tYOqIiNnV1KJ7DGE0mJdQalIUk0jSymncUkabBu8YGqKB2UxmKLEu8C7ValpGO8wxmLsZbcWvpeUFjF4lxccdgeb4MFWFqH8wpXWnw5xCFCZlM1hkoH69F7gXHBe5bOIkRo3zuBQ4dsEwJ14zzEKlBBQnq8kxMQEwJXex3Ok6YCY8A4KJzFGhM8WCGQxiCEYHZhmVbnFKeGhoPRBhce+pus/PEd3nntWyycuUgzm6WVJNy+cZN0psH61l1ev/IlYrnEp575Fe6vbXJycZksadMfDlg8fYqFhVl6e6sUdp+Va29zMJDcvLNCrkt2tm4RlwMWs2d4561XKERMszmLbjVZ3djm9tWXWFu7y9/7lf+CJy5erJJrCYq2To8WIuyxOcyUToB9bJ5ODK8aF2pTtc6xF0KGOItUUMVppFAoHfHqW9/m7VuvcOITT+DWH/Ds058jGca0Lp3jhd//4LDmRwPcRYA7X7k2tfnqfZ0tUBPfdUgmQOUYwmoTd4pbrr4ZBzdEHaSsgNU7j5Nhw1PdVjCk/TjVqbroIYrkKNiKWov4WplMHp2vHv4h8fKIEjncaL2ZKqSfuSooU43LeAyONOnD577aH+AIwdYJfSUmiqXizuvc4EOpnFIyGAzJ0gSlBN5bBoMS4y1ZI+GxExd56MLjPHiwwtbWPvdXd2lmTeYW2mzu77N6b4X93l3uXX+TJ5/6OFEzRiDo9na4/J1vYIY9TNLm1e//AG9LfGlItEZGDjMc0O0NGPYGNIQgTqDZyIijiChJ0IkKVpKDkM4XNgk566rgo0TmBbvFLuu7PVy/x0xnHiEMiW7gmk1EOSIpGmSpJhcjGu02uS8ohgOyOMFKgZIpZZmjVEqx7ohPz1AO95FlpUClpSgtNpdks46RBxErTK9JYiVpK8HFMc47dBSxub7Kk49cROQDFpdO0Oq0Obl8hv6woNvPWV/bYHNjk40CBg/2cc4ghKeRRjSziDTRJFFCmkTEUYh3eCpQKT2F8Wx3e/SGBSuruzzy8WWkCEFhYS0GWNscsvJgnycePYMmQ4uQr10agyktRVFgrUdW8QCvPELGKKVD8Nr5sDGKMKd8RRvZatJbW4bNQuM5phCVZ+FtiC0MRoay8IyMw0oQTiMJXsXW+hrDUQ9tY4SGRDeIcPztv/Wf85U//WP6xnLx1EXurz9gZmGetZ3r/OCN79LutDh38VmG/QFzMzNcv/Yd0qhB2lmk3Z7n6pVXuXnl33D+ib/FiZNPMrx/FVO8S//OW+Q7fc49NMe9qy9ifYfZ2WVW7rzIaKgxdo9LFy4wf+YUJ5ZPEscxvizDqlFBuVEDu/Vj4+ywIRooqjE4jCEjeGx1Nk1Y1/WaVCip2O9toiJFHLe4fOUVvvv136RntznY8Dz0+C/xrT//V7z26pdg+MPh+yMC7mH33KHBEcGACTSUDOBcAdWh/yuQrK1452v7eTKoFSsRUqeqqLVDBLe1GmBBoGOoKB8PYVPEFKj7SdcOAfI4c2a6b3W/mOK1qa3ycN6EWpnk148DuDV346m4uIru8eNWxmlTNWXkZbWNq1YKNbc6pYAg0EVUXkt4GVwm7yzdg22Gg5i1tbs0W5rTpx7F5H0erN3j3r1rXHr6WeYWFnh04QR9U7B6f5Pt/S5znQ7nL56jEZ3lZ37ip7l86yYvvfJVPvOpz/HmS99kd+02EsnVO+uM9rsIBFo7Ymk46A4YdgvK/ogs8qQSOs2ELNbsbW9T2oJWs0GaZSRpRrPRJI6SYOUCRWkwtiQBEuVotlsMen2sc3gV0W4lSGfJZY7OJZ32LHYubH6yOwNIYnQFyFJ74jRFS4UWCVn+KOvFNkYMEM7jrcAOHUTghhqnDVm+DLuLpFGXJI3CQi0dynkeeugsrU7Gk08/ho5iitLQSDRxrJhppyy0JL3TGQtLSzihGIwsd969h5Qxb12/zc72FkpBFEsUgkamabZTWo2YTrNJ2sw41cgo7A7ifpdSRCx0glJwpsB46OWS7r19EJJWq0FDq0AriGDBO2sDyJdFiGM4wAussxhl8Q68kxSFwZqCRqMR1qIUIQOlUCit8IJxXCHQF2H/gSktTkJaOA7Kyj0XrjLo4MG9O5hyyO7+AYtLczSzDBlrWkmDT/7kz3L5rVfp5l2kNmQzbUS/xdPP/CxicIuFZslsq0PRLbD9TYp4kfWdVTIhWL7wONnsLAvziwy2rvD2q/+K7TsPMO1HWJrdJO+tMfKnWTz5Y5w6+xSbt67R27zLo5/8Ka688S16l3/ACw99ly8+/wVaOsWYHCFVoHQJQWAX9vPiKs9qQnNS7cmoN0IFPJCC8a5VxjhRGZgCpJNc+cF3ub3yKosnHuVb3/nnJPqA9S3Pwukn6A3vs9Vd43Nf/CV2HnyPb17f+wBU/ciAuyDRKgyW95Mt+1Xeep03WqeG1UHEcfkJMYFdD1XKUzWHxp9OqIfpoIi1fpIuPkXTTNIupyxbjnD9lVJRh4zpCuLlezciBeCdRNHrPoiKe6/rlojptsbOyKQfHpikPk4cwjrdSlb8oPOu2hnnKqXAIQWJr8dO4fDs7+8wHA144vFLPHiwyksvfZ0nHi9ZPHmS+dPLzCzM8Vd/+tvMnXqMCxc/weXLf8bFR3+GVnOelfUVsiQjzw9oNIbcufGnbD7ocm7xLPcvv4YflBRzbW7e+D5eWbw1ZEJhSks5KimKIUo4kiiilSnarSZRJDlzcpHZpVmEswzzEb3dHhsrKxjn0FoTRZpWu43SEV4QgonGkaaS2/ue//UvrnJ6YYFLiwmn2xFN3SFKYiIZnm27M8vB3i6x9KA0SkUkiUXgiaKI2J3m4dnnuL3/BjlDpPAkVTkLZ2DOX2Rh72lk2SBLe8Q6QqmIki5SaNqdFmkWE6cxUZywu7uPTjXCeqwFpRRJHKO1QsUJzQz8qE273aa/s8G8cpy7MMfC4im6ewfcurHO2t0dxPIS91YfMBqVSBGRlzkWxcrOHrONFsQdZloNCuPpZA4ZpQBkcUynkzrIpg0AACAASURBVIJzSAHWeUpjkYJQmsAHOscUBusctqopg4O8KMFDaQ3OOYyzAdBijRQypAIIpoKEgeYpjSMqS0qj2Br2cTbkSVpAE/Hg3g229lZJEsXdW1d56NKnGQz3KUY558+e4s3XPYszEbdXr7G5f5Vr715mfeUlnj7/KZAtFk8skqqMbn6TpflHSDe3UFHMjWtfYnfnHu+K36fYv8VMq036zDlGW5eZS/cxOubU2c/Qmj3HbCvm+kNPIru7vPm9b5HNzeAw3Fu5w7dffZGf/NgnaTWa1GUluoMBcdYI+ec+CimfR+jSeolNb3CSU8Ber8kaJZQUeGF5/qf/E37Kf5Hb166z8ejf5vuv/RGSESt3t7H5GucvPYkWESHS/sHy0QB3QqK+rK1qPwXWU/TFxKWprPxqv4wknOMIlqpE4GQVACUEQOom3RQFM02UHQ3ICny1A7YuahCuo6qdprX5Pq4RM82Hj1miSYB4TIdMNgaOxTtCgacqoBr0igt2/zTBPtW/Q15E5X1MpzOGolETRTWOUfjp1Ml6TMKxzdY8F863iXTM8vJ5Tp38VcpRzq21u1y9+jbLJ0/zmZ/+u7z1xp+xvu557a1vUkZLNITi4sVHOXf6Ya7fG/CDt67guglZ1mT9xvcpert0Tpzk6++8Q2+3R+kMkbBIoRjkI0xe4K0j1pIkChtr4igGKSmKEZESZI2MTruBl5XdZD2ltZSmoCxKBsMhvcGIYjjClAKMx6WOnYHkYNDn7VtrSC1oNdssdhRnZlMuLs0y11BYpcnas6TWYoocY1TIaZYaoSPm5WO4SNBljf1yD5kVUDaYj5Y4I55BlzFWSqSstsOLHCEUcazJi5w4jTDWESURSRYC1UaDLD1ZI8O7gijSKKURotr4ogQXLpzmQaSZmW0yN99mdjZBK42QAx57aJHFkx9je7/PcOjY6B7gb68hXMruQcT99Q1+5Rc+zcraFq3MIL0j0pp2s42SniRWIXNMxwzznCRWeOcwFfA6Gyxsa6u4hnU4F3Ly8WBNVa2nioMYW9W2qTdBVR63RWKsRZeCohConT7WSlzQpUjpKXsjXnjxD7nwyJOcnVvmxo23cKbHs899FqUky0+c4Pq7f83VG/8H0nfYWY/I/AFxmhFFip37V1l98Bb37r/IwvO/wX5vFWkdt9/6OksnltEy4fqdO8wvXWKp1Wenu4NTGXkesX/5e0SNF3jkuS/w8UfOc/edHP/wRc5feIpTp89x58E9LpxYZpAXKKVophEy1ty8cpU0bXD2zCWiSCG0QhyhOafp3Qm41+tzskGtXr8Oj0ThTc5v/6t/gUjgzq1vktse3sQg+8yfOkfrxBnyvU1EcZJQ6eX95SMB7jC5ee+BaQAUHAK4utDRdN65rwZtenCln7acQ85oAP66WTEF7MESnqRGChB+vMMS6gBpSHUKAHwYdEVNg9TNiimSZnxsVTPH+5AZFIjwseKpqxCG7J1J6YQPGLFw7lRfpJQURYFzjjRNMN4Tq4iJbVCLrHbbWYwPqXFRFGGKPhsb6+zuNDh16jRZ1iLNMn5sfolHHnqc3f1ttvd2uLuTw/4KbrhAf5iz9mCFSGcIfYJYSD759OfplwNGG7fYuvI6Ugm2ZcSVt69VPXfESjAajciLHFsaYilII0kkJe12k2arTVFYMh2xt79PX0K70wneTRVsEgLSSKKlotWKOSnnmL15wE4xwCuB9BIlQQmPVx0MloGR3NlyvLvV5zvv7KOFoZkolt7JOXeiwbnFlI4WtOOYrNFESYUSil6+yMkTl3DCUeYDpIsweUEmFKUqiURKFGtUFLaxS2sARxJHVVxHIgXEkUaKUMfFO0OcxJhCIzAonSClRkURSSNj6cQMsRJILYjjBoiIpTOKrJ2xtXqHVluztDDPcGjIkpKPXXgam8bMttq89MLbpO0m88MRM3NNnu+PuLg8T6ZA6zhsnvKe3v4+Oo6xJgBOFCVQpegJWRkvgDUlQgj293eJVAwejDUURUE+zGk10zCdXVoZGYH68VJjjKEoR+AMWu5SYKp89wgVeWxZcPXl7zAqrnOw9AlmOw+TJAn/1x/9zygtKUc9dvdfAb3O6bmEj3/sGfb2L/LUE1+kMAe8u3KNZvscilu89uKXsLZB7+AGsyc/wZnHfo57K6+xZdrMphe59uYfMtfxyGSRyLU4/4lnuPD4j2MNXD34Hqo54DNPf4HeQDB/6hRPPfEsve01mGkQRW0GA8ur3/82lx55kpHJKYUhhLAVTkws6UmSRL2haWJk1d9P1i1VuQGPEpLtgx4//qkvkGaCf/n2v8HrkzzY3qWROJyUXHnlr/nYp3+M+aWfAF79QIT4yIB7Ld4zrqvw3u/qCHOF/pWVLP3EMpVSVpx5tT291orj1KQJ+EKgQqQPwB68gupa1T9nQXoftkpz2AqeIsjHCmJiFE9y1311Y3VqZAi2hquEHbQSZ+sCZVM1MKqOjHeuTVndE4pp+jtBHEfs7+9hbUkcx+iqxG09fnWaaOBaS8pySL+3T5EPieIMnKbdbpIkGiFKEJqDgw3WVq+z/MjHufPu97hwRrGxP+InfvHX6fd3WXpogS989ucZFTA/N8dsK+blN77H6t13GHb3SZpzfOv1y7i8xHpPjEe5UD+kGJY440kzSRpLmo2Yk6cWWFhchLyLNZb52QWkcEgdhQ0+ZVnFUCR4Rf+gH7bWJ8FzSZIGeb+Hd4JEe/A5RjTQQuJtWU0cR266qKzJwEbc2hpyeyvHO0sj9rSbmpPtiNOLHZYX2mivmRMNGqnGRy2K/pA+FudTFCGgKGVUKROJjjQegxiGeai0qgpBgSkLIq2RUiGjQC8ppYPxIBVRFFe1YjyzCx2GwxxkyO9vtRsI4bDlAlGziYg0c0mTu3fusLAwR9xoEQkZgp1xRKITdAq/+JmnEAL63QO8UugoodFscdDdI01jjIXRMGd9fYMkSbDOVDVhPEmSEscRSaQ4cfIkXqoQfxA+FOYqDd6ZkIHjPMaELJmyLPEiVK5MogRjYiIV7gtASodzGpV6muJdxM42RfNRWudOsrO9jdm/xt7mG2xu75DGEZ2Tnq3RXXa2Bixf+Em2N7/JtStf4qd+/p/SzxNOPPwpbl75Ks1mh1IskKaCxx5/nqt3rmO7MS+8+Mc8tNAlLwUiy7n01KfImjHvXP59nn387/Dp536Zd5e26O+s8KmP/yxru1s432fh9BLNqEGkYhozkieeeYarN77D4sxj3N/f5LFLT2OrlNJpqc3PurSJFGJSMLDaqFRXnZUiZGihPf3RgNKU2HzE2Yeex9x5hSyJsCZnd+Me5y7Os7v+Fg+G7/xQLP1IgPskBXLygfNHdkxCzVcEwKwscV+5gGL8rwoW1uDqZUXnBA465JGKSSyWKXdpfLkpd0oSsk7G7la9ucmPX1MDuxDj/GWYoooI/Jpwrsp7rZSPrxWWqx7yNL/PJBg61c/Q1mSDVQgiu2Bh+pBN0Wi22NreZHa2w8raOieXlsniZEIpyWBBilTTEG3mZs9QuJzu7i4z8zPkecFrb3yP82cfIy+HxKkgtzF/+ZU/QaWarfUVovwNBvYOjYVL3Hz7OjtPP8KjT/8YzghkBHE5YrS9SSQ1K92Sd9+9i7AWrCWOPUWe0x8WlKWhEUlakSaNNSdOLNBIG8x2Woz2CwYH2+zs7NBstUgArVOiqB7/QAu0ZtsUhUFFGZEK28mNV0Q+Z97FdIWkKA8ImyNVqKonJIlu4K3E6/DMwiZBReEk2z1Y2+zx5r0RyHW0NMw2Vllqp5w71eTMTItMOVJRkqgYvCVSIYCuKgCzRhLJsPVfCRBKBUrRGZwp0CrBehV234qwa1NFCik8cRaBaCKdQ2CJpUDoFBkpBr0D0jSm3WwQJQm2hIX5DlEiSJXDS0VETiIEw8ihZISIdUjUGki0FuhYIbUgjRPSNEFFKTMzYWa22y2McygVc/P6DeZnZhmOcnZ3uvS6B4gkItYxadogbSjazRZShRostTHirKMsDWVe0BsOGQ2HaDWgyotDItEKTp6O+ewvzuHTAwalo1hZ5frl36bVSmjNDMhLQ79nGUjHQININM1kiF5/mTuv3Wbh3CP8+R/9YxqLpxiONBu3b/DUJ2eYO/EIm+9+h72DNdaufx1vVzi51GHY2yaZjcEY3rn6XfR8ikzmYeksD9be5d273+T00lO4qE8zKsh7fUbdAaefXAKr+fZLf8RrV/+SEUO++FP/LY9deAZvVDCE8AipJoXFBOPfF6hz4F3lrWsZVYaaCQvSa6x2vHPtNkmmmZ9v84d/9tuU3TUawnN+fhE916Ex3yRxewx2t+kOez8UVz8S4B6yPSYBxvGnU6/HGSlHgpTAmKYZ7zAdD+aEEanTCRV+XHbUVTnhogLZ8Y7O2iCfom1q7VG7V9NuVtC8Ib0p1JAOOtu5kOtbW+pSyFBi1IcdzXVg1OGPKv1xH47udJ3edDS+syogW1NCkVI0G032dve5dfsmnfY8w2GPpfkFpBAYm+OMx7mSUdHH+ZI0mSUXW2xu3WVv8xZzs0/ioxG+v8GtO28gs1k+8exz3F95m8WnzrO/sc3KrW9z+8YLfO4X/we+98r/g0lTZuOUZivi7pXXcdYRz5zg9a+9wmhwgPKGRHnwITsjH43QQKohUjAz06DdyUizGB1LnClpNhsIZ7BFTr/o42y3iiVUNYGkItIJcRIjfKBxTGFAJSw1PL/+S58E5en1uvS7JaurmyTNGUbGMSxKesOc++vrxNkMeVEyLEuGzmGEQBZgSiBKsEqznhvWdg54816XWFqUKzk7P8cvf+4CC+20KjwXFIVzHqEYV6OUtREgJaY0OFEGi73ao4AK9yIQeFtvWJNIPEqHZRpFEUJJGtUGrySJEVpji5L5+Rna7TblqGQ4GjIaFVhjUUrjvUPHAifCTl6pBFGk0VohtUTqUHNG4Im0QisVarRHEYuLcywuzgUrx3t2t3dwQrCxvkk+GNLrDulFMcY7hJKhsFmkydKUJE1odtp0lhYRDt545a2q6mdEY15z5pLmuc+0GJl1ygPLwkIbE69y5vxT6FIy7K5zdX2HvCzoJA1u3+6TZSUzcwWm3IL9HtnsKv3BDnsr23zu8/8V37hxhXvXvsKwaCFExJ//xT8l371J3HBok9O3hpGcRUU5w+GA0YM7+OZp/vjP/wn769dZasXMNOZ45+1/y9ziIzTn5rFOUHpDf3AbKRKa2WkiMyAf9sFYGkJRSgJAu5ARU29Im+w6rZgFJcGbKrqmUD4B7ekOeqyu7DDo9jl9+hG+/u2v0cvX2Nq6Sewlc7NzaG3xB5v0hhu0508wYx2w80Gg+lEB9/eXaWDz3o+t9DFFTZ1JVNVB9gEkpZQhjZFQpyZUawtWd/iRA1kVKGPiSlXn1jRKTbGEa0w08VgLVwWCVMVLqqrYfhSpcRGzkG5W0TvOVzVCwg4/KQXCVZsVpvIUQ5cm3P2h2EDtoozTM+v7qnbK+XrHHCzMzbM0d5LTp5fZ3tngzp1rLPzk59EiuMZSRYE+0DG33/0+3Z2XGPavk49GdE5+kpHdZnVrja2Vr5M1BqzffJeVG39E2shYubNBa2YBEZ9Cu12uXf8q3Y2bJHqPhVMnGKwMMF1F1mxz7cEuq6v3UM6CsySRYDjMGQwKMJ4slqSJpNFIOHlqkVYrJU0jimJEUVpamaLRDEARxwopolDfBj9O4ytLx2AwoiwL5GiXOW3ZK3dxuSJOHTONNqc6CaV1nD8d02x3QMbEOibPS+7eXeHRS4+SlwVFYdjbPWBUFqgoITeGUWl59+59krTFMM/p9vqUuaTbL5D5DkVxCmvTagHXE6sCZyWJoqhe6URKk2UphTEYUxJrXf2og8KVA3q7I8q8j5ILCKED7kcKoeS49rpUKlA6UiGEQGtJHFc17IVnptOh05lBCI3SClUVEwseW8jsAE8UKbSuindpBc4TRxFSygr4NUkahxz2KilBSRFAw1q2N7Y4/9Ays7NzRLGmNCXOOcqyxBhDd2+f7cJSuBwlIpwTNDsRrZOCrGVZPDtkY31ILDVLpxKamSGWW+z1/pq4jPHS8fSnnubtV+/TRBArQaJyTp5q0h94Fk+22Vt9Fz07w2yj5ObVb4GOyPcHHOyvY31Jc3Yu8Pqjku2+RaWzjAZdMD1U1sDkEjPcxMQHJM0WIx3zYPVlmq1lLi2f4IWv/iY7O+vEsaV9/glUegaXtrhw4lmevPgsnbhJjiPyEukEJSVIGbK5phIqass9GHo6AI9zoAXd/ggnYnYHPR599in+9E9+l3vrr3L35j2KwpBQUjhNHOWcmpunkS3jC0lLneAjH1AN4Oem8rbfa7XXAQo39Zmov3OTH+moz/XOjzmucMLkvAo7xxksNYDW28sFhIVUY6mg+i8Aq1Q1tx/4tOBSS3T1GVTKYYqeCVsaVKhFYSvNXpXOduP0m0PcFNNlAiafTcckBFTbnsPn4a+qog5ClMSRBy9I04ivfeMPePZjn0ahWT77GN4VxHGT8w99nO78WTyf4pUXfxfUkGt3v8mnP/4f04yf54W//p8wxT6btqCwi5x/+u+SRJpYaNTmm7C3wu3rV5H5fRr+i7jiLLY8gJkFXrv8BrgcYX0IIlpDPjLkQ0MkJK0kopEpFk/M02g0SJOUQa+PWBTEaUJhRmSNNihBnCWByqp+aSjSqqrBDS0viLzgxIkldntD7t5aYWVzF4nDS4G3Kih+L5HoqmiXwduCRhpjozCHEik4daJN6Qxpqx1AzzvOzWtm5xeIIk1pCwaDPoO9A+aWTiO1Y2enG4LU1qOUpre/R+lKmlEGhJTH3nBUATM0mhnD3IZt+4ArCrY2N9jZ3SDSKZFS5JjxmpgUphJEOgpBS6XHwBzpOHxuHUkSE0dJAOlI4a0d/ypSlMQob4jiGCHk2Fix3hKrUFbZOwMiWOBhPVZ1UFQIFmdpwvLZ0yRJE+9Ltne2OHv2DFrHISkgTZFKUBaGUS9HJJ4iN5jCMX+ywV7UI0lihns5LnZsDQ2ltng14pGzHfqb+wyHA04tn2dze41W2mPgHZ1+wsJpQVvsE0UJUdpgWEbMywGmLLjx8l8zMJYsgzyNaAiNjDSN1LO94SCNcUKytlswMxMzl0pSN2RnN8KJLr5xijNnTtLrrpCyywtfeZU79xSDWNNZGvHgRkEcrdDrHZA//DRPXHiO5okWsTMIofBCEKkIaw2Jqsau2ltTU7SCkORnUVUtEkuz3eDLX/8qe8Mer13+Ni9+4/cY9u+D8sQJKN2gO8xx+wX9XkFzRtGMG4zy97IY0/KRAHeBeA+/Xv+Cz3T9lGChV7nuYpKv7tQkYFq3OK7S4g+h4+FUQGrrV4yplNparuu5TFIIJ+fjPdLXxYKCxxp0Rl1/ZnJObf+Hn0QD4QI95KpqgJZQK4f66lM5jkfpmKMUjbVlyI9WurpKtbEJCEWMQh2Phx+6RD5YY/XuNjubd3nw4Cbt9gxJ0iSJU5qtJmka8fb1bxDpATff+gPsUPOOLZC6RWf5s2xv7RKVffK9Vfbvfhk9I9jbXSfJDCqzCBGzuzNHXJ6gP+wxv7jEv/3BbXbWNxDG44VFCcFoVNAf5HhraaYxaQQLcy0W51u0mxlFUTA/v0DSSJBlyqA3pNVu0ezMYl1R/dBGiZQa79z4XyTChpokESwmEe30EktbO5WlX3lsSoYsGwRaR+GHD+IwtrEI2Q5SqlB/3Qu8CdUQhfMhnlEUuEobJzJGNFOiRONxLC7McbB7gJCh9G5ndgbnDGZQjMvE9gdDOu1OSI/4f6l7kxjLsvPO73eGO7z5xRyRc1bWXCWKIkVSIylRFA1Bcgu23G3ZMNwLA90Le+Gde+ONV70xIBhtNNyA0ZAN2JB7UEuttqmBIiVO4jzUkFmVlZVTZMzDm+90Bi/OvS+CLYlqWBbAfoXKjIx4ceO+ePd+5zv/7z9IwWKREcmgAt3d32UymnJ8nrGyFqGjmKo0KCSxqou5lkhVX0cEfYZQGoELxcXXnuWi2eFatBJYF163ShIoSkwAfgOBQNTxkUoF9pU1TEYLBuvrSy1FsCeoh/I4VKJZ6azT7g452H/C2sYauvaDrzlnOGeZTGZ4b2lFLbSMGQ4di6kj155ut8IA2UhiRML4uEL7jL29JySxZ2VD8ODRfYbrXV58NULINtOjCt1xJLrN93ZPiY+nXF1vM5pPkK1VeptXmJ/nPHz6lLidcDSekcpDtq8IfFvibMXhfoFqRaSlZZSNmBg4Oiu4fTVmND9gsjel5Qv2M0O7/zLD4TPKfMb1qz/H+fwZB3vvc3K2YGvjOf748/+Cv/sf/31kkoDQFPkCpWJAI7ytVd61xUDNgpMIvFAoJSit5enBAffeeZsn77/Nk/vfZXhlm9n8HGs0sVb4EmbnJUJKcldgTUHS63M8mjM+nf/AuvrDUdxF2O4tse4a6vi3FasQhpvhey7EPkoGw3/rXcA6oenHlx1PM+jBB966vEA7lsVdirrj9bU8Xyw5LxdPRtbapjAclUJevIEiYPiyXhjqH3vpdYpltmTDJ6bG5eo5y6UzZ+lZcQEThVAHlrsCR1WVKBECF0SduBMoVQ6kx0mNqQquXXmBTneL85PHZPMj3r77BTrdFZyM2Nm5wnw+Z/fh9zg4G7MwG9y+fpOf/8Svs1i0Kcoxf/SV/52jJ3e5/drHqfK72OI+K4Mhp2djmO3z2ktDVts/jZcxOtYcV4o33riLr4rAsVYSZwvyoqIqKjqRIo6g1UpYX19l0OuCt/T6HeJWHKCIJGI2doymc0Sc0u/HKK0Root3gqI0dSaowdocgSJSCeejCQ4YrvaJdIRWEaayoDwIV9t3OBQaLyXeGjyBEirCVgxbBe8X70xwT1RQutq2V0ik1eBDpysFeCFRUQil0FGE9TXAJpodqWJ7a4M8KwJ7JopppS1AMJ+OWdvaYm3rOlulZTEdY60nL/KwsMhwcThnKBYGrWWN10corSl9VV+ZCuvL2hpZ14QMiRMSpXRohurs1kTpIMGury8hQr5qUZScnpyyur6B9KDrnakjJBKpQAdCxQmxU8wXOeLkmLjdItItWmmEVDFREjFcXUHX1/DZ6Yg0iYlVwvw8ZzEv2NjQpIliMp1jRIuzh44bO21KMh6971hf9XQXDvoVMKckx84KygSe22oxK1ocz+YoIk6PT4lbbZ4+mtMZ3OTHfuJTPH77q5jJdxBGMZsULOYVaUfQFYZ2Al4LhFGIynE0yYhaMQszx1QtWu0OqcqZxzPaKuP88AtUZcb0cExnuI1xAz71yf+Mg5Mpuwd/zGhywtbWq6wPr7CzuhlmGCKMjpueTRKG6tN5yYPdxzw72OXZk4d86MM/Cvp1bly/yb/83X/MfDZB+wiNJ5M2DOOzmG4qiRODyxzeeLpRm3P+8qHqD0VxhyYl6YI2sxxicqmu1v9ammrVHbgQYbsqvAoFti6S/nKhXA5t5aWieyH/9/5ii9rAIQHebpxswsOL+jxrfMgDOL9kofi6g6whThomzXKhkMGuVQC6SbYOd1f98/xStlwDEDWmXp8TOhxfhCSe3BoO9p+yvX092CdIT6zbaC1wwqOFrJkPLZL2lLRrEOocpWZE7Rbf+fZn+NZXR+xcv4X3LZ5/6Zc5Hc052XuLe+9+jQ996NN89iv3efub97m6/TqHj47RqWUxKbi+PWewMqaalmx2XmFndYvTozFb11/gTz73dcx8jHQV0luUF+RZSbbISAS0I0krkaxtDun2OugowjtHv9/DI0iilDkztE74yle+hxCarfUerX6HVprQ63XoDtvBf0YrWp21oDg2ls2tNg7PkyfPwu9faZSOcL6qnSVDpqetB+llkZNli7BQSxlk92XB7uNHbG1fJW6ndR5rgNeskKACwylE2JmwU5ISrL0QvYmAg8umy/AucODra7vVTuoMUsVgdY04bYPUHDx5jLWGbrdNVVqEC1oAayx5VpG2QyxcnhXEgBAqBHA3UYbOo+OYqqiIE40QdmkxLKVEA1WeEUUpSksiFeZEcRrR7rUZbqwSddqYUM2XWcb5Ysbk/Dx45LcllYror/RZH/TJbUWZGcb5BO81yKDATaJgTdDtd8gXBUkk8UVBpyWYnXvMCszmksWoQEaCfpQjY8vMeJI0ojtImZ/PMGXGYhojhGA98iTKkPamjBYlJwdBZatMwmJ6wic/+TM8fXwPES24cyfijbdzsrlj62qLjvPEA4vJPTOglQg6bcvESjoWWlFMVYHPjnkwOeNsVLF2RePiEUVhcbLHj3/413hykPN//8m/5Jc//Z/wxW9/lk/9/K/i84j9vYdc39rGaYW2FqwJnllKUGQV+4cnzLMRca9DZ9HjE5/8NI+e7PLtb32e0cmb2PkRLS2xVHjRwhlBPsnQTtJPPTqJIUoQ3iD0X6CIvPT4oSjugsbK9gL+aCASoBYoXRpuXqK0CLGcX4X7RzUdsw9Oes33i4vB6AUVpe6mgZqnsISItLoI82149Y0StVbs1wk7wRdm6QK5VLg2EA51YQ+vx9bwUROau4SdLsFS3jmsDZmTjehJCrF8foj7DDdxt90juaqZTKb0ex2kl5ycPqPTHrC6MkQRYtaENNy9/5Cnz+6Sjcd86xv/iOt3foxEnbPWHXB+vkuSXGUgp+SzQzZv/RTn+YzPf+5z9BLFr/+X/zXXtp/HmDFv3PsaJ/sb/OlnP8/GesatGwPWB6+Rn5Wsrm5x/+CY9997F2cLhDfESlGUCxaTEl9Z+mlEO9FsbAxYWw1e6kWRs7W5TbvdZjKZ1XFyEiUtz93a4vjomGFPsrUzxNiglBwdnXNizjBlFeAS4Yh1RJImpK2UfJHB6hAda1xV4k3goEuCPTD1Ds1ag3cWLxwIHfJOpeDkYJ+11TXSTmv5PqlI40y4YEUzhiEMzpqA4wtKIMrnxwAAIABJREFUq1pK8YNjhsL7UGiV1vgKokjS6/bCkNjbml0TVNVRHCE8VJnFVAUISSxdCAYXgVdtrEVpSVHk+JpBpOq0pflijo56SCkpypIoFhcCpSghdx7iGOKETr9LJBW9wQrSC2KhQdUxlTYU+TRt0W61qWwWCAtVwdlsjtAJG2tD0tggRRul02BVjMDaIlAircHYkiiWxMOYdk/hXYWINZ2BIlYdzicnTI1HOagKwf4zxZOjOVIV3LnSwfqC/Bw2+wky9UxOc05ODIaIzjBhfrbLlXVJ1I35hV/8FX77f/vvKeMciaWVSBbzAusVceyR1qK0AK+YzhUuVeiBRccRIzLWogG//Ldf5uXXrrCyvoX1BfP5iGd7BxyffYnjo5L7b8A/euN3eXKyC7Lkpz72d7h162UKU+FLSyw1QinOZxkHB3scnB8j0oSzw2d0B+uc7u/y5OldpOpwe/M2bx7d5c5Lr/PWu18j8gZTefr9NotYoB1IkZGmA7LKoFQC/z4U9z//aNzSlv+ksdEU8vu915vB6JIG6QM8IpGBKrP8OnWRvfg+72tlqvDLwh4gItCqLr41fujqNBYBIMWykFehIbs4vxobt5egILH8L/xgpSQaUTMZQpFo8iCtcxhTc2IviZmWr1EGCEgSvu69R1iJp+Ld+19nddjhxvUf5fD4DCEcGxsbWAtpDC+//DqHR/eIV1/kp3/+NeZnE54+fcKheZvRuGSw8gHS1g5Hu/t0V25jphkf/8gv8OLLd/jsF3+PN9/5Anv7f8JsIcgWZ3z0F/4Wf/jPf5vbay+i/QZWVehBjy/80Vco5jPwFik9xlWURcm8KEglJLEK7JjNDQbdTgjKXhnS7rRRUvL44UO2NndwNnjL375znfVhn4O9hyymLXrDITqKUbJT/+5CMpOQApygKCvyvMSUFapmlEil8FV4T6oyhGU4L6BhniyvoTrQwlu2tjZCcHHj3V1T/awIM4RGoLGkQCpVZ/kKbDNzkfX7ZC1CqjpYJAyCfZ2sdKGbCNej1ir4vFu1pOgeHZ3grGJ1tRX8gpyj3WmhooiyNHTSFG8rlBJoIYmVoJWEJKQyt0gXclC1CIPRd/cX/KvP/xlRt0OrnbLaT1kZ9NDesdbv0EkzNlaHzI2mJeLlbKc96OHLkrPDEaao+KMvvIvrrvFLH77Oq89fqSEuj1AKLVSgVkYeJRWZmpGmEf01R1V4qtKhTYnTkmTF0Kok5syRRYLcepJFTiYcvbTDw6ygsyLYaGvmZcXZ3CC1p9vtsLe7oMgUq5uSTjrg8P1/w9GTz2DshMOzoJY9mhjWhKfdkmQnjo31BLRh79gyGxlaPTAzz86dFp/+Wy/y8z/zE2xu7CCcwXiLp8SvDbh98zpZkfH6K0/59lee8t3vHlJWEUX2Fn/65f+V967+BF5k3Nr5ST7+kY8ynS544/GbVGXJ2eycjhvw4Vc/wnfu36O0JcPeGnNjmBvL/rNzcnEfHTlMpVHaQ2xZXe+xkgw5eHLAeJ4RRw2EVvzAKvpDUdwbqmCj0PyL8GpgSSi5PFxsBqKXn9JANxeF3y8ZB2GXIJfmY3yfWMpfwDIEqCiE6qo6FOKy8CiwXFQwSsV5++eZPpcw+0soE5FUgTopg4eIkuGGFgjysgpq2OYcgaqqgolVHOO9xdZzd1/f5JFqs5hPkTjef/AtVnrXef75F/Gu4P7973J15yYHx0+YZkdc3+5wfjrl4OBbTEaWrNI8e1zR7cVQzNi6cpNP/syv89aDexwfHbL35CnP3XkO9BpXrqbMj/4Zj+7fY/dJzvjGXXaupDx3/cNk84r1a9f40puPOXj8FEyOtB6tBVmWM5lkKOlJI0ESK7a21un12sRRhBKCXq9Pkqbcv3ePG9dv1JYSim63Q1llDAcrRPoGUkd4JJWzNF46YVBlMKVFCUkUaZJWBxEJjKlwNrz/zlYYWyKdDJ7rzpP2+gjhLmAVEfZhQsDW1R2SVg+ECh2/EBhjEPU+T8kLyK4JTXaBoB4wVsmlRaOG1VRoFhoRXGChhIU+fE8twPOgpMbYEu89o/GcLPMMhylxnTEQLkaHVqC1RkcRCIeONGnaFGQVVLetLtYLbBkGyzc2O3z8A7d4eDbj8cGIR0+nVO4IlEZqiVKBNhkBsXZ0WjGdRBNJTztSCH+Cs56TuSOrDGcTQ9pu40q73IpXxoATxFoxHo1oJxFpmpAfSNZvtzg9G6N1jM+hyEvKhWA0Nbh+hE9SinJO2g8CNWuDDbTXkFWW85FDeUlRZLz22jZvfO+Ux49mXL9taCURpYuwSBaxp7sG7VNNmlg2NxVlpYgSwbsPPGfnOUpr4p7kV/6j1/jkL9xka6tLFEvm5hBnLY4KnMTaAkNGLNvcvjVkZUWhe4bf+b0HPH46YTF9zL03v8kLr73O3e98l6/+/m/R2ox5/OgRzlTIeJ2PffI/5DAfc+fmLeT12zybPqGf9Lh7uo+KOyx230f32siVlPlsRke1KKeWt999SDnNuLLTJy/GRO2E7nrrB9bVH4riHi79Cyy8oTbCpRsGLjorLopoMwxawjji4qhLrNxDE28XbhyH8Bfp6aIeGMkakgksArnsxpUMN9+FdD+YKIW5XJCFNyZAy3OlwdwvKJtBUn5xTkKA1qrOqgx+Lz74qwbWRi3OMlXF2ekpQgo219ZJWgm+Udn6wCDa2NihKk45O32Lz3/5H/Ph6j8nkhFnR+8wnTxEacV48pDjk6d84KO/zuSrYyJ1ytn4PZKWZrB2jUf33uWNz/1PbCYLpqNztq++zO6zu+yevMJsusvdN/4po6NvsnX9OmvbAlNMuP38x2m1EkwlOJlbvv3N7+KqLNzUQmDKPIRSV45uIummis21Aasr3cAYMIbrV6+Sttvs7e/T7XQY9PthR5PE+FbK+toqoGh1OmitsXhkFKL+hFRBFWgdQio8nrwsEdZRlSVREgcZfGUoipxsMUdriSsLJuMJZVURR03nH7ipvmZOWRGG7wqBrotkMK2TNMrn5lrTKgq7g/ozrs7G83UUnVIBhxYCvLXh/4b9VOOKqrGkxqNUVLOfQKuI9Y0N5guQOkLIEEqdZRmqDIEmQklUHIUpjRII5XHU5+scRa0b6KQtXGnotxSf/KlXqCrDfJpTGsfTwzO+e3+XvfOchZFUhaOUktHcEBVheFz7AYMzpERMjaLbixhNptx96y2k16TthFa3S5oktJKIKIrZ3trCmozhShf/xDA6m9FLEvK5CVzzUlCd12E8xmGqjE6nRSQ0QltM5Tk5tPQ7EdXc44SkXISoQaENq8MO79y37JYF+TWLMQvK3KBiyaQUbF5RDPoReek4HXvOC5DKM+hrZkrzU//BHZ5/ZZWFn1F4Q56dgSswvgpDcSIkHcCTVTNmC/BiwU994ibzheNf/fMHtGNFWY7Yvf81TL7KIslYL/qcPD1hnBtefPkXefu73+Fo64RXX/goG72U3//t/5G8OGOr+6NMjw5xuYPIYkYLkpUIQdglCe+4frXL889v8OBhxXRm8Db7gXX1h6K4e76/KDZK0aZDv1Cvhuc3BbKxzxTCLSX/Tde+jLfylzJHlz8hoPcXxwDhLhg4znusd7VS0ONVs20PeZ1K1d24CFtxIxyuLrLWhXACfC0o4qJjb86jySMViJCQLJpOrMHfPeCWGPug16Xdijk5PeH09IRZMWFne4d8MeHgZJetK89zbfs6z7/wo7T6K3zpy/+Md773O9x87iZRMkN7z5vf+EMWxuPMhDe+lnNyekCxsER6jc3tEZPDh9x6/mOczcd87o//TzppQWQfcPb4s3yDUwr7EFs85um+xT/dJe0Ynlu/ybW1W0zGGZvXb/EvPvdVjk9O0K7ESoF3BXlWMZ+VRAI6kaDXTdjeXqPfbeO8ZWVtlaTTJl/kTEcjXnzpRUbjCS3frynCnmeP9ljkOdaU9Pod2r0uaaezNPaKdYSPBMZZYh0xn2VBpYzB2xxbzNjdPeTdu/e5tdWjO+hRlY6nz0ZUT0Zsbg9DYRUXkJ8UCoUEC146rIDIg9QaZ2yAXRrWktSh81cSGaB/lJBhR9AcTzXMiRCXp4SkxKFFCGiwxuIj0KS1H7pDS43RCu8iNtaG3LizgvCeIluEXWUkcKVDqQgpPVpqnAxDYekDDdYJ8BLiOFrqM5wQuPrchZIkqWdlsMa1Wzu8/sI2VVkxN4Kq9Hznrfc4zj2HZ1NGWUWRe2aFIUliFtKBlNiqZDBc59r6OnluWBQZ4+MTzsqqvrw1OBhsDrCVxDqNmHpOjkqsUEiCeZhQktxXdKKYWDrKPCfLCtrdFJtXtIYx46mBWQiyaSXglOZkNqO3mfDcArobLY4mFt3pk8oxk1NPNfNEsUPgGG52SZwgrTKcVsxzy0s/cpVr19bZPXrG9o1VZvkcW5XgDc5WUGfXIoJuQMk+UdRikeW00oSf+NlbfONr+xQnU/RGj7Q3YDFaMD7PuPe+YbAhUeOE86NHjI+f8PAbC76sfpONvuPsdJ9rL20Tp/usrMZoJ3G6Yjq1dNOYfkty7oFE0olTFvmU29dWaMWS3E1+gITph6S4A99fuZefusxdb74sLrFHGoxcLjHpZpDZLBYXsqJQzmWNb6tlOO0FRfHyz1wOcL2speDNcy4ZANfPUSrYfUovkTIMQ90SFpKXintNhby02BhncaYZsCq00jSc4mBGFT5OW106nTanZ8ecPtzl219/l1ZL8Wzvq+w+mLC78TLRyvNgFS+/9rM8/O7/zJvf+C1yt83tmz/N7dc+xt3vfYbJdJfzt0+RnVXWNl9iNvP8zM/+p7z1jS+TGc/Wtef4xEd+hffe+yKT8ZvsHe3xbPxbrA497373gKM9T5IKXJWw8/xPUuUlw7VtHu6PuPfW29hqhhQaZXOqyrCYF2jnGbQU3XbElZ1Nev0uQni01vT7fQSCB++/z3N37mCso9PuMD4fs9broWJNt5Vw8O4RGxvbbG5v4nFU1jA+G4Wtvw8zGh1rYq2D50maUmkHTqBQtGLNrZs32Ry0idMOadJnu5Ac7B+SzbPlddMMvhuxmhB+qW0I0I3G1SHlSwaTEBhb1Qp9hzEmyMxdGKoKESiqTaX3we6tjlLzDTUMms+pC/pcM6htZkDSO6xWwVJAR+g4CernesAedgugkw5FZYIvEirgGTLw34VUJGkLqRQah1MCKR3GFgjpUdIxHLbpJm3a6hrdXgfhBTMjufvOY85mGaenGSeTjLvHBh3FYdcrBHEsQUZI5emtrvBkd5+d7TWkg6TbwWSG4qwikyC0w+Pwc/AyQkaWOBLYUYGPNJXyCOXJJhbtYibnFQ7JlU0FWtNdsyjAGIHuddl5tcfJ2QnxVo+012JdR7z95SNEVzPLS9IKquOcPLNEwrLIoL+ywSsfuMrJ6R5reoYQbaaTKbYKVsbe5phiisCTpG1KKXFiTJz0qKqYPC8YrO7woR/d4k9/b4LuGYrC0Bt62r0tKA9pu4JWO2Vv723WVxTbaUKrmyBSyejIkVQnVPmE4apjOOyxttJB6IjeiuPw2TErXUElFSvXFZurkudvrbP/bAxyBzj5S0vqD09xrx+NeKj5+HJxXwp0uFzkWQqTVFPcuTDs+T40Xnx/cRcN86UBxJc7hXpnIC7ETQ3WvjSkFJf5PBdcZ+mbYaurF4V6+15vwS/jsAEFuFChSilIlQ5RefWNuvyaUFTes7a2xfb6DijJyfSY8/kpB/vfYDx+h1H1NtXc8OGf/EUqqZjNHfnsXb7y8D18a4B3C8YTQ0xGdbLL3qM5qxs9Htz9A6bVCdXogJ0f+2/YO3iIi844mT1l/ygjq8bsa8HVjS4vv7TCfFSws3GD66s3mM1yOjur/Okf/GvK2RzlTOhQK8tsnpMXFcNU0U48a2t9BsNe8DnPc9ZXNuj1erz51ttcvX6NoizodFc53D+iKiyrvTZJ0qK0FS+88hrbW9t4V4aBeT2T8LVJj7GOsixw1lDkC+bZjPEkZ3N9kzhO6XdjOp0UUQUfeRklXLm6w9XrVzh8+hjvLUJonLfL3ZwSMrj4CVAyFNSLJsI3wyKQDu8t3rsLnyMvQCgQYWCLuLgyPTJ0zc0WdInJyyVODhc7V2OroGeoSryplnBe+B0oUBJR2ziLeuAeJ23weSAHSEGUxIGeaxxeByhLah2YQt7WpycQhBmIJHT+SdrGeIlSkmFL84Hn12n1WkjdxlnBb/zmH3DvxBDFLdrdAYsiQ/uEuGWJVMTzL9zBupJiEcLCW2koOT73uCTsjBAO1bL4ChYziCJBJ43QUlCUDq8sSSflbLwgbkVsbK7R7Rpm8xkt5Uj6Ka0rOzx9ekC7Ixm0HFIcYyaCjY0IG1uKLASJL3JDy3vStsaS8NGPPU+endFdz3jllTUmozNcVSCweLvAlTmUBqxk7ifIRBF1W1SFR+oUoQZMpye89sFrvPuNfbwQTM8nLJRjbS3hQ69WlDNFXkk2epqkLZHaI2XJ0Znjtdci7Ewwmk1Rccpg4OjHFQen51ROc+X2gGRYcrhfcHJ8DKJHUZWMxgYV/3sAywC16CM8JLCssMshav3FxokRlh0wzfOXBbTmvviLYasQ1HCIrKOuLrr9ZhFpuvNmSWi6ZlfH8TXmT/WJcFH0m0IefkhjBnU5gUUgLlSqIlDMliZktcJVSxkENjRc/gvFq/eQtBKEd0ynM/YOT5lkU7y4yp1XX2Ry+pCT97/EtSs3mZwc4/wVTD4kbglwktMjz+jIoLttIpmz2h+iiwRZZOy9/5jz6YLNjR5f+uJvsbkCo/GIyWSEsRG7D8fgPQ8FrK4V3Nhu86HXPsh4smD7+g2+ffceT588BFugkZRVji0qskVFJD1pLBgM22xtrTPodwHP+uYGg8GAZ8/2aKUpg8EA5xzz+Zy03SFKwDhDpCMG/TU6gx5KgRDhkrUmCJhcrXlAStJOG5yj3emBkrQ7c7xxtcw7vGMqUugAmQf1pihxrnb0EzWU5prOXOHqKbwQ1MWzXrjx9bUYmgovwtyk8S5yps4cuDxkr4+/9Or3oRhzmWlVX3fe2cDO0QpnA1/eWsdsOkWpwP4RXLbrCGwe6oXJmpL3332bjnwZoVxtbQ3SujBLcB5Vz5jCtVbPC4TDyzIsGCIBQElPpOUyRs+aEIwdtVN6sWOlOsHM+2TlgMo5uu0OqQp3kTEhdByrKMoCoT2tFU1HRxwd5gjlaa+3KK2lyKugZo4Cw6iYGpwD0XY4ATpNUCrmvQfn3HkOuj2LlorSTDj83lsscoPSlnI2p90SzCaeqzc6ZCZmNnEcHWVBB9JLaKURhpgsqnh6/xkf3YqwxRlVNcWWjiovUcIi8bgMysJhcSQ9TyxylHKISBOnksooVBQ0CINBysZmxtlYsd7JyKcVRwcdXGTJpxXlmWeSe3pCk7QFxgjaSZukq8kWYS4yx9BflYgo5v67x6y2h3REi2goGfYTzs8WnJ0VzPO/QbaMEOIRMCWsv8Z7/+NCiFXgt4BbwCPg73jvz3/QcZpU8ItP1H/UxfFyVmhTkOWlz4eaG76m6qGYqzHvpjuSsoY+hLx0jIuBbeCSU3Orw2b24saUf/6cw1QgBG3X0E1zzEsrQBj/1oeSUqJr90jZMC3qHYQkdIdKNoNSt3SaDOcQjqdURK/bZn2tj7Ge7a0Nzidz3p7ts7axxSKfs33jdd7+8lso91HOj9/C+YqyrJCRJBELrFAcjWYMuwX7zzLWt9qsraY8fnJGK4Z1AaupYLjeYzHP6CHIqwqpPbPMcGP9Q3TFOlW7Ymw9n/vKN6kWM6QPnt6uqMKFV3l6HUWnpdjc2qTXbiG9J2m1GA6HOOs5Oz3jpZdfwuOp8oKiKLjx3PMsCkt+ckS7H9MbdugM+uHYphlEGpxqwhHsknaqkJjKcnByQq/TwroCh0WpCC0V1pYgPFKrWvQVUnQCXCFwtt6FNe/wpbmJq4eJ3lugGboHKwklBL5OrlcqorIOZwMFsJn9BCtgcN7U9NvwnlMXWVfHpiklwVYIJaHm3KdpStpp00oivPCc7h8G7xd/ASchAmgo8UTSk49nvPPmPV7+kRfQWnN6cMLo2SE7z9+oFxCPsa5eKEJkXgjglkAcKAayuSFFiNxTCocjUuEa/uBz2/zyx18HD/PRhIqIcmEhEjhj6nQpSFREq91CKUVlBccnc3xboo3AlhYztggLXnl8blgUluF6n+6gReUKCluSpsGvRSrJaGFZoCh9GjjhRcGiclxdj5jkjvlcM1gXSAXH+4bzmaHbT9ncUvRWOuy+M2fr2ipJmtNJKjqxJ59muHKBqySLcUUkFUI4qjLM8NACX0iqiSFtCWyZ4+ljS1CUdLoGU8zJpWJtW1Iu5kymkq1ritG45PzEc3quEM6xupEQOYisIdIz0kgRK0/hHIfjgp0NRXZmGEQtXOnIKk/sDKcHBYeHGbNJhWui6P6Sx/8fnfvPe+8vAz//APis9/4fCiH+Qf3v/+6vOkiDUUtPUHQBDZNFyMuUx8BekUKEmDABovbIaLpgEJf816kNvkLAMLAUBV3G95fHayhryy69CeYLzJSGoNksHIE1U6til7iqW2K0zZLV7CiUurRrIBQUhQhUOxnOX9XnppbnF7jUQjaOlI5uO0IKTWXWODk5ImoPOZ9K1jpbJGqN/+LX/ltmZszdB1/m4NlXePWFn+NodMzZ3pd48PgdTk8sewczJJ5OLqgYsbPVZq2v2N5w9NoJBQsSHWGN5NlRwaRQ+Mk2P/bax5iezNi6/Rz/z1ffYHr0LND7EBRFRp4ZikVJL5Z0YsXmxgorwx5JFGwF+oM+nU6XN954k9u3b+OcI9KKbDHnyu2bZPMZutOlPejgneGbX/8emzvbdDuSdq9Lu9Wtja+i4I3uQpH2Hqxz6Cjm2o2bLOYjnC1RUhNFcUAArMeLMCBHSSIZBRjEXzQToU7K5WLhCF20LSpwoZtrVJt4X4vODEjB6dkYqyLWV3ooQeAiS0m7P8TZ4IFjvAjBykLimsQvEQzHpAwWvM4WgaklFE5W4ffrg9pWYBHUOwQnUSKYskk8QmokCqRAS8vqWh/wOFORtlJ6m6tURUHSMpRFxsnJCd1UBzqprRcgF/j4SkhUpNHCIrQKthqO2h8p7ASipI2TllbSobXSDywiqBuswFyKoxhjCmxR0hEJ5WkVFqRMILqCOI4xugDrUZHi+Q/ukJU5z928ydHuKXvPZsi2gNgh0hRjBKdnJfmzCi9zMAWgaQ3h3rtl2IP4ilYc83Qv52QKMhUk6xWzeUUsSj704dfZem6D73z7W3zoI5pOz1LkBdXCUGYCXwkqbxEyzDCE8EgnMLmnqkIgiUwdUuRgFUq2iCKJcZaqipgeVFSlwRoYzyZMR4KTE1DW8+qrbdqdkt5Qs/u04mjf0O1FFLni8MSxvpFQ5J7OQFHlhje/OcIIyfDFhKcPHed5xWarTxx5Dn5ATf2bgGV+Ffi5+uPfBD7Pv0NxX/a7NT7NEo8MX5WiNkVqVHjLLjncXK4u7g0PPtTFht9+EVl3OehiabXcwCdSLf2XnXf1tlfWWHvjWePrn+GXGH3ol+ptdvNimufWj8YywddPVfWALMwJ3HLBkrIWOYlgEuV9ECxpVXdRYcqLklAWFXYxR2HZ1B0+/KlfR0YJJJr7732TP/naP6U33OTZe495dPc3aPU8ndTS60QoaTjymvlEcXwgWNnsQZVRlZJFBW7iWF/vsHcwZu4Mu8eO/T3Jr/70pzCFYXV7i0ejBd/75tdwpkQ5T5nN8UXJPCtRHjqJoNdrsbO9yWq/T1WWrK+u0uv1ePLoMZsbG6TtFnjP2dkZg5UVlJQk3RTjIO31KSbH7OyskbZiqjznYHyEtUfYmmIoRIBXoiglSSPiJCZJNGnSQkcdMhdwSaUVrubGhzfE1YK45rpq1NFhN3ZBu71gajnr6iYj4DoBX/e1V80FhjiejImkZdjv45xlPB3T6oUQFOk91pi6CfFLfYe3FrwO77dSte1EUD47Fxg2DXQU4MYwqNVRjLflcrcXrHvDS1xbX6HVSUM2p1S02m2iOGZydhz8S6LWkvkV0KGgLUCGXeMS/69pm0FgJZp5P0iBAVZWVpFe15z64HckHSHftsgC777TQskWMjlGuJqcoDzGeMpFhbMW1RP0NjR5OUM7wXtvPub8ZEb7ikTrhFiU2LzAtTQus2hnSZRjWsTsH+S0ZglKeaR1JG3H3pFhNgu+QN2WZ77vGQ6g8pbj0wdk8gAvRnS74IqKvPCYQlLmfrmQmRx0pDA2KIJ1DFELqsqhKoGvSrRUjMcZJ4eBeprPS8pc019xgUYpYtqppN+vmJ06xllJ4UsqHGiF1AqIKRahUZQk7D7N0DLHFWCQ3HpB8fSp4fCgotONmGYLum3zA2vqX7e4e+APRMjN+l+89/8E2PLe74cbwu8LITb/om8UQvw94O8BrG3thBurgUEIMEvTaS+/h4vnLLFWlrYZQRm6XBdqTrH3eBmyOUUtRGkGpU2HLmXwshYXP/zSy2sGuxfxfhf8ZC7wkvr5F66T1G6RIRdVEEKHnSCEd9fnHcsLO9UAzYiAvcsgJPH1QtKckhCNcWjg3t+4ssWNqzt1TJ/BOM2To13snde5t/shRlnC6x/7Eb71rX/D7sEug35JZ7iCUIYrV9okN7ooOrz86gd59O6/5uBowmlmYZHQ7QheeqXH/HRGPi25s/EqOxtXsbMcsbPGn/zeZ5idT6kKh8JiioqisAhr6caKTjtmc3uFwaCHNYZuv0ur1WZ0PsIaw/rGBkIKJuMx7U67LtaSw7194qRFNOwj8MSRpZ1YRJow1L1AratnGM7X4jKjqKqCbFZwdnxOmZfMioLtjWFdIG1tvhawcpprRNZ+6yIUzHDc2l2zxsOluhCUCQQNZTUAGKJmtIBQkrXVIcOtjeBRhiVOIjrtIUXlK37WAAAgAElEQVSREycpwlnKMq+HoaLx3QgaB+fRUobBppDL0HRZz3Ccd8uRrNIxWiUIITFeLZehcK1ajDW0ux2Ga6t1rkDA6SUerYKNsQR67Q7OFJjKUSwy0k6bsjI1/h52kM45pAuDZrxbQqBShZap3WqTtvqUVVXbLIQgFkpFnKZIFZHNFriqIPIaHQeoysfgcVgH7WGL/iDCmpLRUwvKMlhLufHygEoZOl1FmeUcPDJEA8n29SH7TycMBoqz8wIzjXCpYbDhEU7jhWR05pmMPFQOXWqEdky84+zU0x4U/NJHtticnWGyHOcc+Rw8iqo0UIEvA3SFC3ewrxdjZ8FJQWw8psho9zRHz3rsPRFsXoNZZijnIIiQiSWKPNaWdHqadhQxn1YsppL93YrSKIbrEUcPM65cjel0ehweGibTCl94ZNtzZUdTFgLpHIlSWFORrMakq3+zsMxPe+/36gL+h0KIHxzqd+lRLwT/BODWS6/5y6rO5tEISPDBQMs6t+w0nPdLVagnBMuK71sM6s7Lh86nAjR1t76MymMJdSxXiOa76/uuGWxS/7n0XveXa/tydbn0t69v0ssqxpDOI6xDK4fQoYComh4Z/GMC7i5kA/+I73tdnkZ0VYc2eId3nrPZOfcevQU24/FZSWwEkVgnJmOWFVy/9irWtHj8znfobIwQhSfSc+Io5/pGwZtv/z7dOOL29QElnrfvTXjweMKDx5pbrygi2ecTH/oU1XzO+pVbfO39Jzx4626APXDkRc4id2S5YaAl3USystpnY2M1cINVxGB1BSUVBweHvPTKqwgpKIoC6z0bK2tMRmMmszmHz/Z45QOv47zBGSiKimJxzubWRjAiw2J8uIkVAuMMQge6Y6cXgegR6YRFXjAbnQMB8nBOIIWqhWIhJUtHuu6MQ2H1Lvxew7sa3rkLGuzFWw01Xi7qhUOCt4441nT7HcpFETB3pZBKkMStQBpYNhXh+EprSimJ6kSkRnVb1dYTZ6MZvV47eM4IiRNhiFgZS1UWRFGCELr2+A/KWWsqvLVEaUra6bKYTblQbEsirVFxTBzFCK3IFiH8+sH7D3n5lZcDJKgCxNAsGI2/E9aCMzjjUD7w8b/+Z39G0moTRZp2p0W7HQzdkqSN0hIVRXQHbaRzvLt/TnsYEXUSRmdFaHxaGpRjpgyy1UGpiuy04Ph0xtHcst2PkV1JZ6BZ3TKYzJHljkXmmc8Np3sGrQSJVsxOHc47ZBx2v2lbIdsx42xKpGB6LsidYNWXRNJSmYTZkUbKktm8QOl6h14JfBUatKoIi6oToCMwTqAThzCCvHTEccS9752TxJrJyDE69/RSSTaH8YFnfUvjS4i6EVHiyacwm3rKTNPtxey+XZG0I46etZmNxxQLi4wkd+70eXRvRt6JyDo5qzcTdEdxNspRPcdiEv3AGvvXKu7e+7367yMhxG8DHwUOhRA7dde+Axz9uxxriblzgczUCMQydzA0XapmmVx01I273xKvpmnALwVee09lzcUg1btwK8iAZauG5eIv+Mve137MPhRV512IzVveKBeil2URrz8XtvYXa1Vwkq0ZM0oQK4kWje98KCKewEbwhPmAbnx0ar5mM4cI50htw+oZT2Ycj6cc7k95/+GXmGNZLJ5gK83Kygs8uPdF0sSxM5iQ3lxnXuYsvGU8TsFKKluwuX6L6ckjRpMFC2B0pLm2KRmPPd/6guHTP/dztFp9JIqpbPPtr34Fl81x1oDNMUVOWRo0nk4rZlY4et0uK50uUkp2rl0jkvDeO+9y9dq1ZVDwdDrn+s0bWONwxvNs7zGvvvpqGNpFLQzQ63dJYxlSDmQSJPJLW06P9jEIDT7Y0lpXMR5PQxfsLMI33vo1o6T+fTeq1IvGYnllh/dYKoRSyx2FaDp+IZYDdGddGMjSXCsBYtORxggbhpUXQP7SIpqaJhvcHNWSwthAfY1vkNYREPj1QHh9Ne3SVCVKqPD7kBFCSKqypMhCeIW3glZnwHw2DRCfazpuhY4TRBQRxRHZIuwYX3n5ZagHu6q+Xq2r77t6d0tthtbMwjqdNtdf2ibWLYwxlGWJtZbZKOOsHONtSW4MSEkSSbSGZEVjUok6y5EoKldiI8+VTg9TWI7GCyIUiXdYFFWWUEwUSX/GlRsdHtyv8MCNW22ePZwTpxFKG3prmqO9ChUpLCUi0UjtkAtLfibJhcMrkIni7KTk4Tsjnr8dk80rysziC4ktGi6TR0mPcypAgDXxwZYeL8G7MITWqeXsIOJ4b0akSzwhMrIoKspcMJ872h3HrVuKRQmTExhuChwKrUHIEMjRbUn2n81o9zw7NyXzmcBHC378E32e7k6prGC+UExmGa1uCjLg/j/o8f+5uAshOoD03k/rjz8N/A/A7wJ/F/iH9d+/81cezF9OK2JZJF2Nb6v6ZjQubDlVDWE0ODb1gMtDHWhdd/cEEcvSFbJmxTQh2YFi6y66KCnDRW3l8gJuLA68h6oyNJlPy0JbP5ru7jI3fwml1K9HquA22U5SUi3rjV4YPIkmVKQ+T+fANIPUprBfhotqNg1KsjIY0B32uLq1yf0X7/CHn/kNHu3/Gdb2aMdtkvYWoqrYe/Y9Xn3+Gu3WFtPJmPefnLEoMpLIUpWntIe3KeQ7nBwusNbTaQGioM0mH7zzUYrxmLVbL/DZr3+b/SdP8a5COcm8CMMjb0uGicI4z9xLNtbXkcKxvrZJpCOOnj2j1+2StFN0pDk5OebKlasoFXDyB+++xwvP3WFR5cQyCXx0Cdl8QiQ6IWA6CX7sWjQ+noF90giNPJJIpRTFGJ2myyIaVllX02RZQh2yhuWWrBNxyZn0ctBLXaAb1hM+NAYegpLUGnSdkETjk1Q7KzrrEImoIx/DXCdYHQSeuveADPh501w4FxhA/cEAU5XLwu9McJXM5nOkPmFtLaCeUilMZdg/PKTXTVBSk2UWGUUoFdU7RxlYOkIhpMbW23zvPY7gSYMQFNYxn81otbrBy12E2YSUwWZa6uAjj5DICCbTMb2uJIkjVBSjo0Dd1Cohilt4oDIWVyw4evM+i2JGnLZZW21hSsXUVkhZcnY8pZ1qhAMrCkqZwNzRvjHk5GTE7bWU/f0JZdJiWlnWOy2EXzDYIShf84o0iTFVRWcQkQgJ84RFviCRmmyUo7uC7gqUaJ48cbz2coW1Y5yRJLGnzKDMg/e9j0tQLgzTa2jLeXBOYo3DFoLOxpB37y3QacHkEECys9lj90lGt+/ZuBoRkXC454m7ktU1ODnNwWvKwpHlOYO1mPk0R1jYvhGzviY4PjXMC0e7zDAyRg/bHD2dcnOrx/HpAjOKOD6e/sCy+tfp3LeA3655thr4P7z3nxFCfB34v4QQ/xXwBPjbf9WBPBdpJUtxSo1nXvjKcAGdWLfUiQanmQbn9hgCe6B5qgOoQ2sv0JN/e9DZHLZ2/6uZKxeWBheWBA7Qze7A+5oed3HwJa++/j4p62T7mtImCH7ursYrvfN44bCuYQEFPE8igiBK1jsaEcQoslnEaidCD1hfcDrK+eIb3+HxwfuMxTX6279GcX7ML/3i3+f901PuPXxAJWDjWkw2fYv+4IxXXpLcfVywOuhh3YLx+Ij93RnHh1DMKp7JFjdeSHjllU8QRRIZrbA3yfjOt75JOS8RxpNVWZCcZ4a2lKRaczwr8FEwOWv1enS6HcqqZDqZcvP2dbwUnJ6csjJcI0lb6CTi/tvvsLG5gY4VwkTEUUxdmUl0F2Mk1SxjNpnRwGRNiLOKYuJIEcUpSRwDcP3qlcB+KMowJJcSYX3tAxBYKMYFHrVUdb6lCI3EMu5FSMAihUbWQdO4S8VdBL8gayxS1+6SqmbB2ApvXY1Ly2XHL9GhOZE1pu6D66Pzlqg+t8sMMRpfIxl2HRFxvUOxnBzuE0eaTm8dpTXSOspsjh606Q465LNxGIAuIUqFFAalIowx9d0Rin0Tw+ecR0uBc4LZeExVVcQRS3xdKokXkhB1GFTV7TQmjsNA1TmFM+CwCOFwZREaqxrq0VKQn3paaY5QfU5Oxgjt0IlAaUd7XWFJEfMWM7Wg3WpRmgVWz/Fmhel5AcJxXBSMqpJ55tjelvR6PUYnjqPTCa+82uf8OOf4kaOVCnRfkEYSY2KsqJAVdKIEb25xfPQ+3W6dulVZtJZYZfAmwlQK6Syi4Uu4sJOJYh8o04niyXua99+eoyPBzrWIJPZc3YT5yDHPwKSOV3+kz3e/dcx0EjPKPbOFpswrylyyOvh/qXuzX9nO88zv9w1rrGFX7eHs4Yw8hxRFihQlqy1PbevC6Ia70zHSQJAOYHRfxVcJkNwlSK4CBMgfkJvkroFcpdPtbiTptJ04liVZsmiZIilRnHnIM58917hqDd+Qi2+t2vtoMJDABugCyH12Ve2qVau+9X7v+7zP+zx9ElmRbOowHawcT08bqjKiHynuf7ZCkTA5OmXneszDBxa8ZGkabhzs8sHdX8yX+f8d3L33d4HXfs79p8Bv/398tXUj8rJ2umtxaNvSEYULwyIhuF2wXjpsxLp2wER2LccwiUqrHCjw606/d11QDjexzqMD+yXIBNg1b/1SYs1F17WlVF58dgA6t3vRHr/WYVF3h9pYizTdlOzFsUjbQkKy3RRc0CeBsDFYqVDthGsolcE0jvNlyadPjpmeTthKh6S7z/PuZ3/G9dsv8gd/+D8wmx9i0ht8dvIJx09OmE+P6PczJBFX9jeoy4aHxxXnpyfcuJ6hV7DQ0B9HvPTcDb76ha9QLUuSvQO+/e++ycnJMbgK7y1lFdyVlLP085SittQeIiTD8YhBfwMQ3P3kU174wvPhmKuaSGrGm7vISPDwwWdIrej3+zgT8F/TGESaYwAVCVQiGW9eIVIK5wRCRXgPVbXCOUNT1SxnM2bWrhvlVRNkeS8PpnX01TBU9FNyzN1aEN1GfKkKa7M2j6RpVjx9esjWoEe1WjGZLbh68xqXPUmlDGs1NL4DZOLw62aOD18y0A4yEdb+arUijvQFM6fdbNYm7S102O/3GSVj4iRFacXk7AxTloy3xkRpSqLHnD5+gHeuPR6Jsb5lg3nSNAl0TCkw1gRVSseaaZOkKbIJw11KtdikuDg/3RS2QFAWq/D3OkHpeA1XIRVeOLx1FGWJKwvwnshLVoVFqCZQClWA4Dau9JguC4R1FJXD5xIjGk5PGnRs8XJFrCVags1TrmSCk7lkvloyHqUYYeinEU+eVAyv77CZO5rzGflA0B86hrOUx48DtLRY1rz9l2+RoPjVX09JkiXlTIJTKAwqr9dQmfMh9qhIEglAWdCShyeav/jeOdqFfkQTW8bjlK0dyS/98pCzSU0jIs4nM4QT1IslUaaJIsnqXJBoR29cc3bcCqDFnqbOOH7oGF/VNKrBIigmnnygqArBYlVCI6hmDYX8m8vc/9pua9yctiT1BK0WGXZ82XIAfVs6d0B2p8HnWRMgWtyzM93w4MPE4Zods+55ip8+ivUPQcjivRR4Fe68mFq94NxflhZYH8f64u7eJwiJ+bWKYKhGamPQSrVVSvi8rmUhCA/SSWy7uYg2a3DSYy8NbkkXQP1Rr89LtxISDQ+OHpEVc3r2CYvD1zHlA2xhmT58mxtpxNbVlOnkOjrKKGqLihZUpcHZbXrxIUp6fuU3JWWdsKoluxu/jrGWwdYuP7p/xCfvfYw0DXjDol5h6gZvDLkWNI1hWpuwsSpBmudkec7Dh485uHoVISU60pyfTNjb38NSUS4Np8cT7jz/PNY0pFnG3U8+4eDgGsKBaxzEQVXRNsE4IrTXXYBp0lD2JknerpMQnZxz1Kbh/PQcD21WGc6nb6tD2wYy3Wm1KLleiCFANQgZ0/mC4sVaOXQ0GiKcwXpHkqZBkdKF79u6jrZ4oe8v20qha1B2Zi1rgw2l6AhY+Fb4rq0k1SW2Du3a05Ei7/VQcYIXnlgrVBox2NxEJwl1rS4lGe3aVfKZfpGkrSDaqWgIlahxjlhJYpmEythW62qi61kE+D1Mrkppkd5Sr5bU9YyqaTCNxTpDkkZEUpH0crSUJFlClilq4ViZmmwUg/RUZUMyzClPSrT06FxTNzaM6guBF5Kjxw1JP0Ioi4wMJvbMFyX1IubDozlilJNf3UWakt6mY9Tb5N5xQVHUnB07pC8wC09RN3itiDLJe+94tnYjrl3XZKMwgGcNIIIUs5AKh0E0GqcDxu1IePd9xVtvG4rGEmPZUTHTRc3ppODsMOLa7ZjS1ggBJ2dgEWxuZszOahZnDelQMNzQeGHCwNtKI63g4SPH/lgzP2uYFZaBBmNqTs4gOm8oJ4LRjkL3ExZnzV8ZVz8XwR2CNkg3kBTgh45fHkwy1gbW7RVwIRHcNcPWrc11Yh12XPDSo3x7ia6D+4WLyVrCoL2t83L/rI9ruCDEumLoLh5/KbjT8t6F70rxcDFbF9QfhffYlgfkWzOLy28vfIBnvAyGul62g13txiTbHoFS8mIzQBDpiGtXrxMP+rz75ncR5QOWy3s0wuIauHFlkyRakOWO3nCD3vi3mM1P+cm736MSVzk5eUrGNczGEz64t+LxoeVXb/8Ke7vXA7VNJ3z7O9+nKqb4ukTgsEWNqWp6ChKtOS8aGnHByU/ihMl0jtIx481tvK85PT7hxq1bID3W1Lz/3oe8/PKr1NWSJEm4d/8zDq4eEMURKtYoodB4BnlKx3mSUiO8RLhLbll0zW25rvoE3Zh/t3V3jdQLSEW0zU/nTCsf4OnKO+/cmtLdyUpLFTT+e70BppijopTBuHfRsG11ZNYVQkuDlTLoDnXspyBH0UoItLo11gbqZCcHjAx4PT6wfbTSrbxB4O3TYuCBWaPIBgOMcwjrcG1lRdtAlVJ2GGW4T+t1whGpCCkV1pv1uXHeE0URkY9pivKZ/pMUBMw98D8DzOggTlPyPMI6R7kq8d5T1ytMVVPVBu8ast6A+aLB1oJ8YIgHsJpGmFnN6rQhVgm+hsatSHNPPa8YZDnZVkptDakSGDKWRcnOaIRYGTb2M9LtGzx+64i41yBSx/RkwexeTRRZylmEpUJogVSOqoRooBBOEuWSd96yHD5KuPOiZ9gviVOPcK0MReh8YbSjqiUnRxHvfGw4K4IGVFRAPhB4Z5ieK6yAYTzgk48Mj48cxq6oC4ltLP1+wiCPuPV8w7IUqNRjl5K9Pcl0pqnnhiiC88KQCE+ykLz0q1d495MThlKDl4x2NJubGU8enmK9/CvpKp+b4B5I4W3m7cALG3C69Tj+RRYU/t1msF5cZDywfg0A2uZpd4F6EaZQf14wX2Od7Yu0b/tMcJdCXkT+y4cO4YIG6IZUO2edNtN27RtJ3+GcIfMMQb+DB1h/prVEmu9+hAjv2ijihW3zybaLbz1NWZPJiCtXv8KL/r/mR2/+L0yPfoCpKo6qFVt7/4Bf/trvMFsVfP/NPyZOMs4nktHuNq985QXy7AazySGnn72OXk359V/+Bqul5erVG/zRW+9yeO9TXFOiIsFsXrBsDLHzbGYR55WhdShFxHGgFXrPbDLluee/iBCS2WTOeDRCxZIoivnxmz/h1o2bWF8Rx5onTx6xublJmmbM50vyvIfDMV/OGW316A+H6CjFI1vlTRuqPmuR7dRmEPdSLOYzTB0yp24wTWmNrer2u7749qUMph6BISMQPjRrtdZBo11c0vNvRcucc0gVtR6jXbbfZsLd99jBZwSmlWxlLSRdj6ljawXeeRc8Vet6JIXCK906Q9FWri3jWtA2ZDVKeEQU47xFx0EPRqvQaA5OUBZrg8mIajXvQ+UaWEDOtaYnXrXc+/aaEAKhVWuc0vbBOtpua8auVIKwCVZGDAYbOOuxdU3Sk4FemkbYqkbIAEfMjGC0rYnTAYeH5/gIhK0RwPz0mHy7z2goST2oTLOUgnq5QhmPFBFxZBnEGbJImC9LNIKDL/eJt0ccPnrCYnLGxlYahqtezlB1j/l7h6RC4K0nH2hMY+ltQz2vqSpNU0Q8+rTh0UPJ3p5mZ1Oxs+MQosHYmLJUzIqYj96rOZ8a9FbG6qxkIxP4NOH0SYO66hHOYZqIux9MkZGAWJIkir2B4vH9kmnh2HjeUyw9Sgls4SF2oCPM0qBjz3NXJQ/uCXoHOc6uqKhRDvZv5Dx9uCSWgo/ePCHeEMSDn0Yfnr19LoJ7WEjrKNZmPrK9WMG2DdHuIg37wIWpdZeZdRfss8E+vG6X3XVwz+UA70UnGHVRGbg2aOLafK8dmAlQ7UWztXPgUeJZTnpAYC42BghQgVAK4fxaPXB9mOKSEFr7t+HfQe+jO1Pet03X0FdhPeCkYDjMSU0czDs2f50Xbr/Cv/nm/8YP//L7/Morv8kvvfYb3Lg6pDcMrjyT5Ql9dri6ucfrH/0Zjz79ATe+9CXe+PMn/OPf/F16eZ8kzbg7XfDdP/surlkEqMBamqrBlYY8VZRWMGtaGCJKESImy4Ysasn1/R08DlMVIeMdbpDEKe+/+y5Xtsf0eilowfnpCUoqtrZ2WCzmrOZT9N42aM3R05Ljs8+Ci1OiyXspkY6IYkWWZ8RxjE4CZTCKNFJ4dnbH4ODJ/QfBTLj97pWQNKbCCIckjOx7JXG1wRYrVNYDT9CDb5ksCoEUGuHjLgdBRRG2qVAd1RIXzLVbnD5ovCisCEIGwoc1EjxxHc7WeK9QQpNEEbYJcrZRkiBcWNuhk6fwtENF2PD9ExFJjZIaITTSVWFC27f+Ao1Da7nWhUeI4CesfGDbWEPoHnTTr+Dw+FayWrTJDb4jJqiglqk0Qmm8a9lhQiKUIe9tsLG9BR60JFQY1mCdx/oIGyUU84KiLhBxFjRiegukl5RnFhWBcIJIeTJdYYQm0pJyVuEE9LYUjfFsjAWLhaW3bbm+36PyEL0Uk2jJ8vwheRbR3xkxfXqMzGIW789IBoLtvQ00Kw5u77FcaT7+yYfUhSDXGbNZSTM11B5Wnxnu3dVkuqa/JajmEPcsK6MwRYWMIUoizt9fsHNLIY2nqlNoLLGL0ZslYmUQ/YjlqcNZwfSwYf8rgit5xHJiWNkYbx3DXHB+JBmMFZOnlq3dlHxDc1QuIdccn8zZGMU8fbzi2vURs3mBcT5Y3vYEKhL46m8BLCPgAu6ANij6trT2LYOBdXZN+7vDt7FbrPH2NXTDTwV5wmPPstu657XZ/Rq3EV2adJGpd1VF+zR8kD2QUqBamYKA64c/6KD4n6kSvG8HTnjGI/XiTIS39M8ceYCkOukD7zscvmvQtY0f51pnnTnvffABXgrMpKTvxrz20ms0dsl3vvcOcM4nn74LOsE1nr/393+XWWzY3T3jo4/f4JdefJnXvvIqdbEi39rjW//uTylPTii9J5OCcl6wWjYMYk8SaQ7nVchClUZFIev8u//4n/LyqxtM772N91CuCq7s7SJ1xJPHj5FS0tvcwALNYkVV1PQ3NjC2IY0D1KCkRnjDzevbHFzdR7RB13uJNQZjLNY6lkVFc76kWFWYuqFpmqDzLi29JGL/Zsg6kX7taRoGiBTem9aaL8Zaw+nDh2yPxgiVgE6BbuOvqOu6TSQuxOfC+gm01k4Aruv/dIR25+wzEk/WB0hqNSvRkaY4P0FEEcPNneA01TQBUkSidURjQh9DiQ7zbsFIEd5b6YhGhDF4KWVwmnKexrh1xu2dBaVD30BJOs/Wtr/bXnKhryXXCU7LDOos/ZwN5uw0wc0MQRqnPLz3KUdHj9ces2kSqJhp2iPNM6QWbG5tIKXkdFZRGRB1YKZ4b9rrS5BkgrRvaWo4OQ2N8Z2dlLK2RMZQLBxRlDBdCFZ1xWgj4bWv7HD30wnFdEE8gLRfkEQJJDEPKXBOoNWKZGB5+uCQs/slvTxDCcH8tED1YyplUJFDjyWikuA0Z09LaDTzpUOlNcp7lHcUc4XoweLMs3zo2T8Y0h/1eHT/KflMsL2vmBaebJRyflShifjoJ4YodWjrcdozutKjXixwwrMqFImWzCY1URyxOFdMJjV7w4heLokTifc1cRw0hh49aEiR1AvDeFsBv1iC4HMR3OEC/uigkMAfCavPeh/wyk6hLghvAGHAaX3htIF4zX3ofv8FmDp0j3XaMs8G2sBUeNZhfD0E1WH9XUD2HQzz00H54u+64/Cs27fPwE0ddEOrlWNloIOKrqJpy+Lu3AgITbwWc3VeoHXCzZs3uXXjOkrAL732y8ymS+7c3mM6XzF//kVmxYIXb/8dfCR47+4bfPP7f8jjw0dsjp/j1S99jTv9BFfWbO3t88bdx3zwwzepjSHC4+uKyXyF9jBIFLOiom6HW+JUI1TCK3/nt/jN3/0PKd7/P9FRwvnZOfvX91FaUpZLjo+OuHHzRsCWnefk+JRbd+5QuYZIa15//XskaYr3FlvXrJqSx/cfsr1/pZ0eDZO+kYJESqTqI+QIIXQ4J9bSGEtZLJiengJtQ9XYQHdULfzQSvgG3XZBlg84enLE/aNj9m7fBERo2tuah/c+YjmdrBMM1zVUWljHe9EmKRcSF8a7daIitWgFqEJfxVtHXZc4p4niBNV65AohMC0mjmqJmU7SqUbW9arNoNW6cvNItNYI1w3YBWVKay9kgZVSgaGjuJTRh+GrtuO/noDtoE/vu0Z0MPi2xrCcToiSCKENsQCE5ebNfQbDjfVmu1jMaRrDZHJOffIkiPapGOcM/dF2wOV1xdYVRbWUKKlp4orpNKJ2noOrCjcwTM4EtvEUdU0vCgNdo62M80NLLMbMl5Zv/+lHzKYNVQkbo4jP3guKjaWZsbM7pFk2HD8sYUOydyVhcW7wK0svi+lvZFgpKXEYHDQxWsJq4tjY3sD4GuUDrCWdpRYKX3mUVcxOgorlaHeLeFEzPzskiiRxHHOlt8VyssSbknhDkCYpp0cVtjEkjSVNK67fSbgpJXc/WiEyxcBrqrKhWljGA8nVOz5U7xEAACAASURBVBuszpZ4oSlxzMuSF17e5I0/Ocb2FDf2RlTqbwFbBriUtV8igHWNL3/x+C9CmS6RaNYB8/KT1wG+ex3xU4217vf1e3R/3I6rX2wZbYnP+tjWTT3XDohcrhwuB/Wu8ep9awPX3Q/QXVAisHREcOCTLY4r17EkZPDrs9Rmh7Y1rQBaznzYBLbHPfZ3NrHOMxjkDAYJz/kx5s4N5ouCLIl4451v8YXhV/n6l3+DTz74MbJ4SJRY5jLlz7/zPVxdIrDE3jOfLalry04eUxrDvAnfVaRDwOmNrvAPfu8/wUpIk4zj6YzecNQ24CSfvP8ht5+/gyP4ZT54/JjrN28Gu7co5b2fvEukY7bGm+A1widIYdjZ3kRFCqE00Pp5EpJK5xp8U+F9Dc5gTZDLjWKJ0hfMJSUjoJVSDmc8VIZSsmoMmdTs7u/zpPgQUxdMTg5JkhSBRStJlqU8u5lL8IEvLoRvBehCydb5sYq2n6KkpHFm3QPwDtI0Q8YxsZBYU2FNs9acCVh/u16lwJoaaxRNtUKIiCiKwgqQBKynaye3azGwPALurZQk0jEmXGDt1GlHRJB0VpR+vcov/z+sO60U1homkwmj7QG58ngfuiwnxyc0piLLcry3JKkiywM8qKMRQqQoIowpaACFZjaHWDh29ns8ujsjTTTNwpIkQRAPYGM7QEuDUYYvDFrHHB3PyWXM6dFTDl7KubaZ8cHHjv3nU57/4haUV/jOv/oJ1incqkbHHi88zaHj/pMZSIVbGRoMbDZYY4l7El9I3Nxi0wCbFXWNspbFqiGJFApL3IPtmxEUCZ8ezhBIzk5PuX7jJrOjjM2tjKb0lNOCp5+d0R/kCNlw/GBFkkO2odje0sSx58HHNXEOIpZ4C70rNX4i2bspGA1jzo4blueGVWlQOYhewspGjG/kCGs4XSzI+hFQ/oKI+DkK7nCRzbaAdcDHRTdN6FuzDcFaY5tOrqAL3Bev0mUwlwP8elK1ve8y86VrfnZiZc8Yc3i5hkku5+treLzN2C+C+EVgf+bzef9MsHdwMZnafWxYa51AkPeVVq5fT0u7fqJvIamwSdigxe1b1yDnkGtt7gYlNJGXWKECPqtgvDnklfQVajnkw49/yL/9t/+Sl3c3cE1Dun2dP3z9hxzev4utGyJlWS5nTJcVuYRYOZ4sPU5JIiGQsSZRff7RP/vPGBxcxZqaqq5AwNbmFkkS86M3fsy169fAe+JIc//hQ/avHhDHwf3n7sefImTEi6++wtnRIcbWCGXxpiFOYqIoDdzslo4XNkmDIIUYGutx1pDGKWdnZ8H0vFVP9N60+LFo5XNb5XMfMmlJcDjKRkO++NVXOD85AQ1xopE6Zb+fcfLwEOfDQNF6CtWHYSrnukZ/mDj2XbbsW1aXD6qSSocmaqhA6m61rX13rWnQkcbaJrBdEJhyxfTshLzOKJclVSOIs4zB5mZozgroWKBrVzKlw8QsgaXVftxWI0a214NaK6Fe9lQI/Z8wrS0IDevaNGgp2d8/oKxWTM/OiZYF9WpOL4vJ0hSloDFho1NSEXhOHoTFWMuTJw/Y3r1KVTicVMQDSbMqiFKFEhAlilvPpZyfe+LcsygqyrnFaNgdx9T1iqryiJ5heCVlOVkR7Spu3Rgxo+F7f3RE+dkDXCypF5YnpcF6QYygKSDfCT2N4sjQyzVlVXLruZxYxTx6XHA2lzR1iUegjSVOoV4JNvoJWQpG1tgaHt9dkvQFXknmywkfv1fwxS98gU8+e4JKz5k3Buc1plqRDjXxUCKMZVV4lmnFfAneKcxUUjcNW9uax59BlFuaCtLEUsxKjs4tUaoZxX0iITl6uGRv36KaHm+/M+HGbvzzwuj69vkI7m3gku2ARtegFNAKavFMEBbtRRoa++KZgNk1GLtgeOG1Kp55ry7wXwxDXejaXOYHd9j5ZX59uF28jxQXQ0sXFUA7FLVm91w6hku3NYbPRfbVBS5B2zjtjJYFQbu8O/b1z7V1yJodEfjYl7D5VsY1VAgEiqiXaBWxERk++/g99lJJZJYkvU0ez0re/MFf4kyNwCBMw2JR4qynn0vOC4MREUmukY1ASs2r3/hdnv/lr1OVNUoGXfWNjSFpnvHZJ58wHOYkWUSkIo4Oj9kcb9Lr5cRJyvGTE2aLOS+//BLWNPR6OUG2SjOZnHH/vqfX6+G9JM00UZqioz46ipBaobUKDBGXgPDs7mU0pubRvU/x+MB28aBEF+Qt+LYCUx6pEuIkBJDGAc6TpUlogHuBVFHw+RQSLzyqIzl6vw7CQX8kcNeV1BgB3nW8J4lWLXAjFF4G6CVSwTTENAJPkBZwCKSpoTEUZcH7P3oPX8548ctfZD5r+PT+If2e5Asbw4D/d30m2R6D69adwwuJFgorbHsUUQsdyjaBsAjken2v8yPXaqh0wKAgWPPFGm0kXmhMVbI4X1BXc9IspTGdJ0HY7NI4RkYa4x1WeLZ2dqhWS2QE9aziuFFkWnDriwOmpwGCqEzFleuK2ZnB145mJRB9ydmkYjmB4UhBpEEGSuhqCVkiOHx7iSlSrv3aAeMty9GHc44/WmAleCk5eGUctN9Fgmsscey59oJmPPTMJhacZPzCBstThznOEE5QTQ3aCow3FD5jaydnlGeMNhwqKzl/aFFiRNkUvP2j9yGu6Wea3iBF15ZiYSkfGmSkEUj6A4mtRJB+1o6msfQ2Ekxj0FLTNJ7iKPgOOyWI05jnXu6hnULVCYvihNWi4WBnRCYUCX8LgrtAoFWgPfp1cBdtLPXPBGjZRVRY67RfxG1/Kbj6Nf79THYugnbehWKLX28CF4Yfzwbr8Nrrgw1/Q5tNI0D4dUWx3ixoSwTRjdVcBHm6i6XbL0SH4V/apC6VHOuNxXd2hH79uS7/7M6B7FgbNjR4vQxj9Er4VsLBIdvsLY5jvvrSl7i69ft894/+JWa1Qg23+H/+1R+wODtEOBfU9M7mlMuGYSLQUmGsJ84idBzjvefKrS/xO7/3T9FCYJRvG3eavN/n6PApVVVycHUfnOX09IQoidja2kJpxdnJKfce3OfLr72CcQ2xVlRKkWiNdw1b25vcvvNCUAI1hqYxmMazWi0QeIypg0omAqkt6AghW+elukJ63wrFdewmiSbFCsOidNx/2vD4+Bz34TFf/sIBu5t9ZJIiZZA2EB6klnhXI51tG41BVMwbGSo7b9dwX5eqB6q6whuHEJLHjx5x9ebz64lRraO1xkzoZwYcXKowA4G3VE1Bb2OI6sVEeZ+d/RyRjLD1hG4ldiYB1lqitjKRwuF9TStiHDYcodcyBkFvp72+pEIStNmF6JhgYb0qGfB8pRWCoD0udETW26AxNfnQ4BeGug4UzaauAwSnFROzwNY1CEHW74NzNGVJvfL00phCWGIl0P0F21nK/Y9LojTBlg3zCVDH9AaCZVVRVIIYhW0sG6amqSXzyrC1PeS9Pz+jf72PHNTgzjl8tybJFNlA8OWv3+Dw/pKnn5yR39CkWpJlDp06VBoxnzk++XHB8VFDfyLZvHOb+XxK5AxR33Iys5ycWGTiKMWIc7dgGA8R8QaDzYaT83MUK3qbhtppSutZnZTYlSPvxSQ6uJg1FiyGKwcxp4cSYSOW5xXFrEYr0JEhGiniTGFqSS0so3HC/GkJStEfCE4eG7ZuC4rqHBk1FKu/WT33v5abEBBJdRGMYY2ZXx7pbnPWEKB8m1Osx/EvgqO4FJgvB0DRZvo/A8esNxNxiafcZfFcbC6Xj4tL1EXEejO4jKv79vk/nZmvYRt5gZn/osz+p7P+X6SLsz6XdBORz24OzosWF24PvIOZrMMqxwdvfZ/V7IzR7k3e+uBjHrz/LpGzgKNeFUznFamU9GNBf5hSNhVqtIVXEStt+J3f+33iNA+cc+URThC3uPCje/e58+ILOGuoyxV1XXP1+m7Akq3n/fc/4JVXX6FpKuI45tH9B5imoT8YMjk/Z2sj4fD4hMFwxGDQI3ISqTU6khSrGrxhkPUoqxIvFHVVoKzFeEkcZ3CpLyKdQArLk+mSN955n7KUrFaO6WKBMZbD+5/x7/+936CXZa2iYwigQirK1ZJ6NUfGKUhNS50JsxbetWs1fMtSdibX3bfgGI/H4Fvl0o5JJcS6kS+Vwku1hh2lCOYb125dxxRzaucRWnD1+hWWMx2sJFU4h1KpMMJOy+4RgGtwzqynqsNRhEEsLq3pbkFGOsLW7uIaXOP4IRXqhgyFCFVHrDVpb4XxOUJrkjQjlmFTSJMEgaCuqrCZKc18PifOeww3EqZFiVk0bBxsIsWUVeUZ7QdWz+mJ5uj+CjDIFK5claxKiU49WzsxOpaUK83mGJLIkl5RLI5n7H/5OlW5oBFg5o7GeBp7RJrB9hWN72k2nCZ9+Qpnp4d8+oGgmtYsFgrZg/6BoK6eEKcxWtUsphVCWCIkqXJU5zVZEvPoySGzDyqGmwlXbtzi5OEDVoXF1oZ05PErTzIQFHNDbQVN40Pvp6c5m1RMjxxmFaiSRA6VJcE0flKSbWtsYdBKYquKNMs4fjqHVOISixYZx2cV+7dgY1Dzyc9EgIvb5yO4I1rrObgc6J4Ndi0GvYZUWtihgzIuZ6/iQi4g/N5l/SJkcfLZ4N4t5Z85rssVgxQt7fHZx4C1GqQQXYMrMFjcz8Ten32Py+91+Sc8y6RZ/xce+PlZe3tuLqoDsT5z3gdZBgWhadtydpT0vP+TN3l89x2S4ZBp7fn2n3yHoqqIsdDUnJ/Pqa1gNxHsX9kkyiWLhSPq9SllzNd+++9z+9VXaeoGpyK8aVAiUDPf+cmPeOH5FwliV47JZML1524htcZYy4/e+jGvfeWrKBkC2XI+5fz8nJs3bzEYbyAijTGS/f1rxFmMkBHWekQk+e5fvMf//L/+X6gk4aXb1/j6L73Ewe4mgzwmTjWxsMRnKpieuFZR0VuWdcP/8Sd/wdki0FmNCVZ4eKgrz7/4o+/yja/e4fkXb7cbfFBRrMqKo6OnDLc2idMeCIdSUJUrolitobNwzn27eUMYUvPESfzMegqsHbVOKqBNNFqZAJwnT3sY63E6aP0LbPCBJWT6UqkgAuY6lcvA/HGEv2+aZp2MdEvQtccWqsuLNTSfz8mSKGT27QQ0hAJUSkGzKqmrBc424AwIjY4gTVN0lrMxGodKiTDX6YQnT2Ok98znBUma0uv1wWnyUcr83DAYe67eGPH6D6YI7akah/We/eckZ0eCzb2cKPMkNxrmxw2T85LnXtjibDFHFg3DqwNu3vwi9771DrOTOVlkmZwuUEYy2tS4osRrjVIRbulx10vklZzn79zhnT9+gNM5Oy84+irm0VENdclqZvHGoVNQsWSwKfBesZzPOSygP8hRJjCjlicFzsRUiyXCSWZPbVCV1eCNoCwBF5y2XK2YHAqUTMlGjtnMsHk1wWLJc8FmEjMrDE47vFJU1qBdRdMolI5IegmPP64glWxdgWb1NyT5+9d961xnuuz48n8/q7d9kYmLnxswW8zj591aJspFdt5CJ4K1kuTFm12Sf23vuwy9PPPIGipqJ22FCLjlz8muu9uzjk4/dR8Xm8bl51+mQf68918/F7+ePKTN6AIMFH6Xrc1TXa/44J03UAhGoz3+4Fuvc3T4IKjhCZjMliwLQ6YFo2HKlZ0hUmqepiUyTti++gX+7j/8D8Lxt0bLQgVu9Ww2Z297h6gNak+enLJ/9SrBMCLhzTff4vadO0SRRviGpq44OTnludu3mc0X3Mz67F7ZQdUVWZ4j0gzvBOerFe+8d8i33npI0cQcPznm3uMzPno052BvxCsvPEcuIU0kmRSMVpZhL221ZASDKOHf+8aX+OGP7/PktKSwMY9Pjjk8PqOuDFLBg4dP+f2NTW7e2AsSE3j6/T67e3vEvT7OQlUtscZQ4UnSAbRDUi0/db12vAuTcF2TXojQpOyG8ML37FopC9bN2ZDoKKIIfBWwbKVk0M3XCa5atetFBY2KFgp0zrXeBSpINWjduoJ166hlVonO3Sn0dLIkaSWB2+pDqQsIVErKYsnk5JDReIA3BqE13jmSOOX2c3cCw8tbrLXYxmKNbU2/HaPNHBzUVQUWVtWC8Q1J5Wf4OMJ7i1tJGqkRaLave577UszxEcwmK/COspFEuePB4zmrRUN/X5JlMXbpsHWNrioynbIzCm5mwjsOjxTDmyOqiSXLEuIrOcw8oplSGcuNO5pVAWUlSSMQo+C1K0tHPlb0NyzzE8NolHLz5td4/73XMQ6k9DRNTT19QnFSk+SS4ShnMV+SxLBaQJJorDLUpSWKNab2pJlCZZY4BiMFOhZIJymLmlURtN11qnDSgoE4DTIFvnDUc6jriOEIslwxn1a/MLbA5yi4r9OeZ2CVVs9DdPg2reNS91SxVm1s89OwGcD69+71wnt0QPf60TWMIdavE7aYjpa4Lk67bFy0TSsuNoiAibeVcHshg1iPqcMluOZnPzRdFLjcs70M9wSmWyuURduwW0NRF+duDWq113nH4OlgJ9ket+oCvvCBG10s6G1f4Z1PH/HuG2+jmhLtDcuy4HRWIoVkGAsODrbZ2hrjmmAdlgx3+cY/+ieoLKYyFo9AeQsieIAOBn1Ev4dSko8/usutmzfJsh46jvjx2z/h+rUbjLc2gwBXA48ePOLW7duUqwprHbZuUFJwPpvy8OicSTXjnbvHPD1bMpusmBeO0ju+8Nqv4lVMMT/ibGb50UcPuHPzgMwaZON58P175JliexSxtZmS+ZgrmxG/9uoWUTaiUmP+i//2f+T4bI5shbxOT+b8T//8X/Nf/ef/jPHGMPgNKBnG+4XGexPWp4DRxhghWxmEVn9fa81kfkachYapb2GbTmbXe7t2fOoWxnqCmXYCVLFWMXXtxuEFRDowbcyiCph6FNEgQOr1e0gpQUZ0A1dhTcl1H8C1bCohgpuUNTVSJS2E59tjDjTCbqn1h0OiSLKYnmCnZ8TJkKYxfPzBh5wcH9HvD8h7OWmWEKcZOk6IkgQdBRkH166RSCtWc9h8zmOl57zQbO5IynlFnij0yPHkrqe55qlrSKOESCv29lKWzZJqoRFLRTmpaaaC+z/+CeVJQ+Izjg4rXAzxwCF9RLmoKCbnXHl5h9nRguatCuZgtxtSa3l0v8R4xfYoQSUqeDxEhsG4x8bBDR5/+gl5LpmdV1TVCc1C4twKvEf3JJvXEibSMZ3VLFdN6EmkAje1GFMjteba86+yOHvAbDJh1IswK8fRE09vR7GYl+hYkQ8VdSnY2FCcHlXkPU/icw4fF/hlxOFiRm+kcTR4PEWhf3EC294+H8FdhBKny2pUG6DXDVN5ATnI7kntLSzWEKguD0KFidHu311WfdFI7TD8IBx5sQGEzNivsYxwqQQGghDgRRjb7mRaZacC41mLe3XVhvi5J/9ZZT7n/bo0Dhtat9F4fCfBwMW+JH1n9uyQSl9AU160I+R+3ZcIQb0bqulGxsWF/LAQWDy9/oAax7dff4NyPkF4gTGG82nITLdyyZXtPrs7m9iqJB/0iaTki69+jd1bz2GaMP4ehq8kIsh6YpwlixTz8wm7u7skeYaONB+//yFpnrOzt4Otw7TjgwcPuXbjJiqK6UURZV2hFCzqiHvTiB98813OZwUySkmzAc42JFqRqRS7WrCzt0MyvkYaCY6ePuaHb77PIIvY3xmz0c9I0ojlSiCnmuOmpHowZ7Es+f4b3+R8ZZhMZ3gPFojaTvdHj+a8/9Gn/MbXv4JDthLNErxF0OqDyFAl4cP3RStjERIEhyIhyAaEBmuYZArfCZ0K5XrVdiuk3dAdIetu6ZaBDaXC8BeepimZnZ+R530Cf0dRLQuiJMYriYoysAbVMqS8FAgLUmqkd4ESStT2rGzQppFh2nqdvLRaM3iJU4Kot0G8WrBczJieTpiXntGgx8HeDtZ5nLUUi4LFbIGzNviNtjBQ0zTkaY8si4kd+FoxONjCWsfG1oqr+wlvvn7OeCuiKj3V0pCnmkVds7mb8OTRhMoF8+ooU+Q9xfx0ThIXCKdoGoNSltW55ParQ6azFXtX+zz+tGb64Ji6AL8JOy/GyMrRUwJzFpOKGikqNraGOCcwqyVF44mnoBvF8syynDQI8Qn9nmK4l3P0ZMZyYmiWEhF7dKRYLRvSRGIaSzQAYwR1YxhdT1lOK6JEY6wkThPyPFQ3cSLRwrBaCFLVMD2TJLHGlA1Ihy9j7ry0xacfHiK0I849O3vBxNy5y0OXP3v7fAR3CBrsopP3DUFunZG2WXwIUn6Ns69xw3bQqDPD6B6DDpZwF3j0Tw84tUl/x0jpNF+cAOn8enrR02a+zmI9SBeOywnfSqeKNfxBS8dse7zt27SZeMt5th1tkQvE/5lmMEFWNWRu7YbUQleOAGN1jlQdRhtkYtsBJynaZvAlLLfdJCMd8n8AJyXZaItvf/8HPLn7EY1twJWUy4piXpNKwbifcHBlTJ7EIMLAktKaOAkGFgIfzL/pTM0FeEe/16d6bPBSBJ1xpfjs4SNqlfHC7VsYY9CR4JMPH3JwcJ0062OF5ng659FZzTufvcnTh0/CuHraY1kJUmcRriCNU6Jexv6vfZXz0yOK5SGTlWH3yjbXd4foCI7PZpyeH1OXGcfHkKUZsZakeYTWMYtVw3Gx4sPPHmMtdFRS2264jbH8mz96nTvPP8/+lSGRkljXEImordQCbNE1a31nf2cbpDP0B4PwfRlD+5JtgtENzXUa78GopnOT6jL/9spAtFOvztlwXXiHEhKtYoSQvPvWWxzcvIGxhtPJlBsvvohwLiA1zmOtRccxyMA7r8uK+fEZg+1tyNPwORC4xnI6PWWYp+BDlu0vDccppZBeEqcZMu5xfn6KKyqk8JRFycZ4HGQwAKU68/JO0TWI5llj0cozO3PMCkPeq4lJePqw4OaNPr3NIJGQxAKdxywmhiiLqErY2lHMJoraSOrMoBTsbQ2oiyXDA8vkccPwuQ309oqzkwWbOwpISPor0sjy6EixMjM2+yn5fs5wa4uNezPcTFLWmpPHDSdnBRuDFNSKxdldhvuax8cVOIuXEelGjlARRlbEscPUoWE9HifEscFKwcZYYIXj9AFUpeDk9A1qrYm3JFLW9Hoxo7Hi3icN9cLTHwuQngZJnCimq4YsjZFJxWBX8fDuIWVpSKqEG8/FNJWnbGqS7OdB0he3z0VwDxm5Wo/1h0DXNproKtNWqAvWMA0d60SFK0d2lil0AVOgRWA6BIjEr/H2cGuz4jZL79gtFwfWvqcPUdb7FjbiwrsgSMk4On140abw60btGjm5yNZ9+xrCsx6a6o5mHRzpdMcdRbFAIYiUbg2RA8PCOhcGli71lLv/LmiiHcsBdDvpqkRw2+lop8eLmrfeept6tcJhcc2K2bQgcp5xP+VgZ8xgmBKnEb08p2xq4khhTEUY2ukwfrdmfnjvWVUWYz2be3sIHXF2csJqsuTFV76E9StiFB+9/zEHz3+NeDjiw/c/4OMPP+Lk9BzjBauqwliJQ3Fje4PVcoF3BlCcnZ8gJeSJIsYRC4dKGppqivIZpoZMZ0hcyPLjCJ2Guk0BmYbda3s8enLCh3ePQNowVNChXd5jnOTjz874F//6/+a//E//I6SKgkppt2q76k+0ZtJtT8M7j2kpm3Gs1989rf4PbdC9AAe778+vE41uNM073wrWObxtUDoKtMzaIuOIpJeztb1NtZyT9BJGowFCBEMUY5sWRlRt1RfgmmKxYHZ6ymh3B9ve55xDqZj5ZMJq6siHQ/obm+vVqBAYa6E1GkkHfUZSkw8MZ0dPiLMeXidoqS7YPwKKxQykCDCbqUkiDY0OcrXG8fiTKZESCF8xmUbkOWxmQ47vnzA/rdEy4uykoa7Ceen1I0gkvgbrJGVZ8OiBp5hYJAGq6d8aMJ0WpOeWuLdkZRUD1WN7BPGGY3MDHn02ZTwtA2W+71gcrtA9yUBGNAuP85ZmUSMdJHkcDE0awdHDBSrTYKFWFiFjfGlYKkchPMnYMluGnpNRksGWRtQGEAyHmmKqkVGDswGSs86jUkFTSCZTQxpb4rFCCcX2WHLuDBujiD0Xc+Ug58mTFaulYV7ClUEMrH5hXP18BHcpgl6FuMheQybc2d51FMUuZLO+sMIG0JbFHSzTwhmi5XV3m4GSF5TFLpS2iAbApb+/BPuEOy6ojfh10Ay/eawH4S4fW/fB3AUsJLqcW60/00Vx0mVwIU/rtMuauuC/++//G4rlgkgr6qbiV77+2/yT//j3sC7APtY7hOuy/UvZv2yPdY25d5+fNVxlnWPVNHz3L/6C80f3w+tVBcVkRVPXjDLJwU6Pna0RQnnGm2OqsqQsysCGMVUovS81jq0NwUtK0EnG6OAAhKJeNXz24DFf+cprVE1JL0u4f3/Cq7/1exQo/uw7f8zH77yNrVbkeY6rLUk6QFuHs4aTpw/J8wRjHE1dksQwW86RRAitWJaWumzwvsDYmjQNQ1ASGA832B1vYJqG+argfLbEND2EcOxv93jti1cpDSyXKx4/PWVV1WETdobSek4OT2h8pzPUqTVe9HdCUqDAmbVQl5KSe/fukWURV7Y2gtZMU4Hq1EV9q/7oEUKv110Q9eoke4MwnWtMi9nrNeSGljRNjVSSnav7lMsZ5XLO5n4430JYdKxZrgrSJMaaBqU0XniyLGHzhTskeR6mabvrTML1mzd48OknpEkSWEBpGqrX7vpqJY9VFNMfpCwXC4TUxGlKpFTbGA7VZF02rFY1+wd7oCIePbxP3ktoLIgSqrlj1bfEfc/8XJH3Sq5uJWwOBuDnxMqTb8Qs65LFQrF3kLCcN/Q3Y2aVI5cNaS/li69e4Yd//hChLawa6o9mlFXD4dBx5UZC1HgObkY8PV8w3NE8fFRRG8mTpyV9oVgWBq89kXYor2iKkqaR9HPH6Mm6WQAAIABJREFU2WGFNII8TyDS+GnBxthRF1BWYIsGKxzpUCOd5+wuRLFD5sEyr8BQzxyDXc9qVlMvoUgU27uKKHFsX9XU3qKkIBt4ojhie0dx/Mjy/rsN4+saEVvm5w1PHq7QWgczlTSiPvurw/fnIrjPzo/51v/+zwPcISOSOEVEMUpHZGlCnudE7cCHEII4ilEqUNc6J3cpVXDEEe3QhdKo1hsziqLgfKMUSoZGhBCXqGjer7ONDjMXbSNz3Yh0HqkEumMlcJERd4NVa/+PlvXwDJa+ztAuMts1rdP7dhqzBWBc2Eh0lFCVFdWqoJGQ93OePHqMbRwoRVd5hEK+23SepZKuaZwiHGcrFYVzjtl8wR9+809564c/wFcNztY0qxXLpSHWivE4ZmdnSJ5lbIx7aCE5mswZj8dk8SMUDu881gmst3SqlSDa+OepmhrpJB/+5ENe/eqrAcpqLGd2wPjFL/Ph8YIffO9PaGYL6tIwn86Yz5c4L4myFCE0kY6pqhW1aUiThFEvQwhHFIOtDcVqSdkUJGlEWQUWivcFeT7EIZjMligM/SzFmgbjJPceH3PVjRimCXd2NxEaVNzn4fGS7/7l29RNw+Z4QL+XEsVJCOxS4KwJG8qlBny3mR8fnzDupYBBq4jn7zyPaQqkbzg7OcFawyhL18qU3aCeaKG0QFFtV0nbF+kgvpCPOIQLQbhxFuEcCoHVijjPsdUKqwTKe0SL/w2HQ5xpaKzB4XDWhkQqjXEy+L1K1fZ4vEcowXh7q2XwCMpiibNBuVG0/R0lBNiQMMQ6RcsYaxxFswQc1hqcC3pHWksmkzOkiunnObb1VBXCoayHSqA2YbwnefmlhGzQ5/DolN1bEpk3LJaGrJeC9TgrKUpDugomNkUBy0XBcmnY3EmojKVeWbauxQzdVqCpzmbcuhVRiAVx5mgWFldKTh4Zkhjq1LC9HxMLixVw+iCIQqieRA1SBrJCCIcWDV5blNTkQ02SZ2TNhLqE2SkIb/9f6t4kxrI0Pc97/uFM99z5xhw5Z2VN3dUTm7NI0aQMwzYNSxAo0CvLoCXYFuAFvRDtjReyAC1swwvBCy1ky4ZkWQMEUbAlgqZIdpNiN9lsdje7umvIrMo5Y7zzPeM/ePHfyKom2E2B1oKOTWacvBE3MiLud77/+973eZGZJ9oIejuKqnZ09zTWGvzGk6URi5WhOwoj0bPna4YjjdRQzyFPLFppdKIwtuX4dcn5cygXnpVSyMajfcS1GxEXy4Y0UUR/QJ7xB9/+RBR3U2949vZvgq1JoxSjPNPLKe2qAgE6EuSdEbIT5nFFUdAfTJDWU5QhJaaoVuzu7tDasABK4ozaGrpZgvYwXy6x1qCzDkpHKJkEabPXDMZjmtZgmpbOsE/kPY0pyTsZbWtpq5rxcMhmU1K3LVmWkHd76DimLGoa09Dv5iRJjFIKhKSTdUniZDv/ljjhA2tcSyKdBvu8A1TgXcRR/DKqLc0StBKkUtDPuzRVBQikUwgraH2L9uolwxvvgqb6ahQEL28aXN1Atu96CRaHawz/7Au/xn//P/9N7HSOceBbw2bdoJylP0jYHXXp5h3GkwG9fpeLywuu3TxGeEeSEMZRgPctDoVSAuUbrIjx1qCTBOnhd3/vbb7vc58mko5SDjgREy4LBw+f8eTDR/SGu8zWBeVmiTEGU7c4HEoJ8n4HYz060hhrME1NqwTjvXF4YaiGxlZ0RAptQ5Z3kFIQRxIhDMLA4+fP+fr8ktdfucfR4QGxtuR5gtSSy8WC1hmK+YraL6md5taNPZQQTM/OWG4Er//oZ4hVOCE41yJ8ivcCjUA6u+3YFUfHB2wuL9CxIoo0jfZ4IpqyojfKkURh6S0EnnaLNvCgdDhZKQXe4Im3IdSgkRgZlDZKBFiZJNxkAgJhqyZTEVESo0WE9w6tFUkk8M6idEJdVtsOfBv47QUYj4wDO95ZGxjhQgc1jQiFSbiw+MNbpJc4KfFKgWvxKkXFGpkEB2ued4OL2IMQOnyvtm1LaxzGGJyFGEGcRqR9SbXytIVn/7pitYGL1YKdXc3swlOUirqoWa4M40nCk4cbIi2ZGkvcVZRFwrNnhv6kQccxUaqIDnoU64qDN1KK8w3SChoMy5llfea5edMw3lG0CNpSEecGHTtirTCuxcaC4aTL7KSkXVlULugPgtHNO0c+jOnu3GbYz3nnq1+nLBuQkuXM0B8qfGxJe57GKeq1oT+OMJnl2cOWTh/WRSCZCquY3I5YXDqGA9g5UrRL0Knn/AzKAsDT6yqK2tOZREgvKdqadW1QUctbnxrxrS+vv2td/RNR3PGCQa+L9TECT+wNvcMxHAZWemMtqY5Dt+FhXSboOCNKEvaSBFAob4kEFHWN1ArrPFVdY6qC4WRCkkKxnGPsBteCjjOSOMMYD01BjCSNBL7Z0NQ1zWYFK41OUy6fPaedZcgkAh+xagXSVWAtRWtp25ZiGhHFMcZVeELGaCR0kExphXUGax3eEop7EkPThAWeVCRphtYR63WB91DXLTpOuTw/Jc3yEHSRxEEP7CxKB9/KS/frdi7j2Bp4t0vZK2nbld0rnDskj5895e/97/8IsW7ZVDWUa5rakPQOwb/gYJAxGQ0Y9DMGwwHTizlxmjEcDKiLgkhpnAmqES8Vdjnj3a/8MnknYu/6PfLhDkIUfP3Lv8/rb71BGqfUDv7Rv/xVvvZ736ZaF+wfHHH73qdI1ITLszOs9eg4pi7WWNdSriGKQ5CzNS1qS54s25aT8wuUkgjj6GY9fGSIJFtdtUdLqOqGy7MZUsaoKONsuUTFYYcwHu2ipaLa1CjZIlVGVbRczKfMViuiKKLxip/9c3+GP/uTn6NtKxIRNkAfjf14+X0XgqD82Y5qkB+N7qRURHGMba52IkHXDh+NF6/uvlcHArHN1r0aCX58yRTm+1dZsYENE7gyobF4eTLVEmMa0jQwSAIkzCLUlXfkI1fty7neNmNAKYknFG25JUIKIRA+3FysdSANQumQCdw6ulKDd+gtkTQiCSlSSqITQbffpS4KhFQsLxqyTlCWTO5kdMeSsm7IR5J3v1Vx7WhE6+DDb09JVUTdtvi1p45BJjFl1RALxXiU0RpDthPTvz1GrTeMX7nGpqhRbFisNYtTh0wsN19RxImkKSXH4xTbxqyrElvXGAeLZcTeIdTLllxAMa2wl5JZ1DKYJAwPwDaK+fw5Jw+WtMZhVeAW+caz3ngGw4hy1dJUktEwZnpSMchTqpVjc9mSZp7SBDLnw/stk92YuKMoKgs+jDVdo8BZZnPYu2OJGsH504pspJikOb4tiVPPs9P59yyrfyKKe1GUfPHXfivIGkVE1otDyk7qWa8tcRQTSUkUxyAFKkrp9iSGddC9K1ACcDZgWWVw2CVpRtJNaZEYIdE6Q4ma1jlcU9Ei6HQnpGlGEic4ZzHeQKQYjYcIFxxgo09NcN5SFxu6+Yja1nQ7fUxdkTqPV2F0EEcxdbWmqTdEsUZHUSh+zlFXwYgRRkia7bYMZyxRkmCdwTuD8xV1ZZAiohMrTB2S5bXKcK7FOosxBhFtfStyW1z4aKQUWCdX2PugEHq52LUCrx39Xpfr127y5IN3sdbQNJY/82//+/zF/+yv8N/9/F9iJNd00w6j4ZDNZkNrDHfu3sY7Q9PUxFEUUox86Ph++wu/yPNvfoH+cMI3vvRrtK3lpz59jztv3GU0yYGab/zefX7zX3wB56BpWp7Vnt2DGwhvqDdL1usNIg5OQO9blKrpj8Z08oyyClFxy8UaYQ1ewHA4oN/JqU3LarkgjQIi1llLJ9asNyXWbbXa20Dqpm1Zriu8N4wGPfqDPkVVUjUVxhnwUK5aFqak28l47SBHU+NtHE5K299Z59w2PB24kg6KrVb9is4orwxKYQTXbjX0WmvES0WVfylhDY8LualSyIAOEJ4rPXPr7JahvkUCCP8yESlEDUuk0ljX4r0jihTOGTzuJY4iFHOJkIECeaUya21LJLZafO/wAtabDePxCK0VRblBS0kn7tGWJUK3gETFCtvA3tFeOGkI8ZJOGQ6VgV2PF8zOF2RJzHAvJksFQnru/WAXUZSkieTi3PPgvZq21Yh2yXLmifKERFcoCdlhh/WmJVGSOI0Bx/nUUnrBeFSR2nOenS85v5yjlaOZw/kHhvzQMcwEy5Xl/F1H2pccjWp29xP2r41ojOF8Nuda06FcNbywS3IXYZ2gvx9RV+F7PT8VeGMo65JIabo9RyITpmWFyCxxrChLi5QRtjVsZi3CRZy9qGmroF4rKkPeTVFphCthfubpXxcoB6tVSxQLaue5dTshm6WsypJMw3AQs6lanj9c0RtHxFFEWQM037Wu/oko7iCwNSSdFKcint3/kLgzxFEBKa5tieOI+XJFJ5FY5zHWI3C0ztOJJMY6WiyxinDGESmJjzQQqIHOt6itYNzjr2oiOg6AKJzddvwBqatVeAEqFbQ8UoVDsJQa15rwgpYhDBqCztU6T9O2WzlbSKWJorAEq+oSb4KUTcitqYPwNUilUTLI7KzxgOJHfuTHmOwk1E0Zlie1J9VdHJ7W2NClyS1m4WNh39/BiBdXdnS/LXICqzzawng85i/8zJ/lS7/7BfRaotMh/8V/+p9zdH2fVHmyNKXX66FVxNnFGXdu38a0JdPLKWmWEkU6uBQ9gKKTdemkXYSMieMIa0riOGJn0Ec6yWw+5b37D6jrBpVIdCKJMazOnrCZajbzc4qyhDrwrZ0TCA3T6ZSRknR7XaxxSO+RNsLiMU1NCQgtiGNN3klQEsqyxDqDa1vKpkIoRRprBmnGZrNmvlgx6neI0pgoUhgEVdNQlgYtHDcOelzOVuwMImbPH7LY6TM4uI5SGuMtid+OULBcOUyt2UKctjsHCGYhraElqImkvDo9XRVyhZTu5V7k6kOvunlnw07Db53GEvVShRXAX9+ZRSBVCPRQW3WMQG0lntvV/8djJJ3/WJ6wf4nOFkqitEYKQZ7nLwFjSRLT1i3eOpbzS5yI2D3K0TJiNV/y/u+/TZplYT8Wa9IsC2MipYmSFCskWbdLsV4z2a353E8ecvZiTZQGu/78DOoSkkhz+3afFx9WJDmM9g3zqaKtNdNZCQpM6djNu5RFAZEh0hM2NUy/NUXImOWLip2Jpq09/UmKKSu6BzHPnjdkY0m/J3j8pOb8bEFTJ6wr8LLL+cmKzaamLWDvMOx04tzjWkHVevo9x+7ObU6eL5ltZjQW6qrCVw6nJLSenaMOjW/oKMX6siXKBHEWE2lBta7wTlKsGsRKsHeQMZsVqAswDnbHKW3j6B8YTl940rSl0/GYSjIYQ/04oqkb8txgasjy/x9QIbNen9uf/Txv3LzD0jp+45/9E3783/kPmNYV1fSS8d4hl6ePeetHf4qvfvHX2dkZI7OU5ckJt9/6NO99/XcxtSONJcfXr/P+N36P9WpDPujR3z1mPNmlaQpmsyVts6ab9FlvlkidMBgMuDx/wuXzp/RGfeqqwQlJEneo6hLRrIlUjJeaoilDTqWOERaEtRTrDXXTMB7vBGelqREY6qYJWFTrcAiMbUPSjnNh/CAFcScB46jrZitJC11d0zjWmzWOfbAtq9k5WidEgJc9yrrAibDgw7mP6snWhHNFmFTh5L0tFj7McK445Aheu3eLvePbVJdzDvfHfPbzn2U+O2Ocp+z0JJOdAaen59y8eYxWjvWqoJN3iSKN0iFpSAiJdQKd5lgBHS2wThJFGXariZ6en7CcLvmJH/thzlaSr33tq3jriVTEcnqOlppNsaRtQ8foyhqpNU5aNm5NnKRUdYXwAtta2rqisS3jYT8UPgR5t4Otwk5EKk1ZVpR1g8Rj6xKVJpxNz2laS7fXo7aGF2czBIIoSsnzIRezZ/RSQS9VjLtdRnnMaNSn0+0SxWLLKI8QUnF+8oLdyTB8t6/8DfCSEfNy4equbsDBM2G4UoB95BwNyhu/9XBcaeYJTH7Cj9lsn8MZ9/IxAolQEsFVwHYYiXh7hSGOcDYEbVvbbk8XISTbbk0YV+RHbwxaaVprt/kdLpjdtiC9OE5Jok5IrMpyBjsH6E6X1jh2D0Zcu34baz1NU2CaiunmlE1RvAyRcV5gTJDQzs5TXLqg3zcU65okVtg2Is49N68LtDPEueZ0WbLcSLTSlKXBFJ7ebk5lDFI3DMaO8aTL+UnN+WVL3QbpYX83YXVZsblsGRwpukOYv6ipLiHrCWYvYLg74MMHCy6KmmYhSHxBWVsG+4reAJo6pqwrRjuGmQ04gclkD9Up+fSPZjx4b8PZiworLPFQYmuFKR2XzypUz+CcxDQCmXiEajFViK71zuMVDHc0g11PWXdQsmE4EZimBaUp1pLZhUF1PFEERdGi9wVeSDp5wmRHolLP+dl3D+qAf43iLoT428BPA2fe+09ur42B/xO4BTwE/oL3frb9t/8a+DlCnfkvvfe/9Ec9h5KKfr+P1jHXbt3hsz9VkAz2ubkzZPbgA9LxPkJLeqMjDm69Rpq1xFEfGkUUdRhfu0PkJa2z3Hr1Hk/e/Ra33/oMm1XBa5/9AeLemHI9ZTgvGXVTaBwqUahOl1R5Tk6fc3k+o6sVja04uPkqtm24OHtOvZzRn+xycO0WD779Nv2dXaxrMa3HbxbowYSTp4/ZPbyFNyXNuqBpl6ymSyYHB6yKkrtvfZqn3/4WcT9neXLO3tEeX/mVf874+DaiNbRxxDDvg5QU83MQgqTT3ZIcJd1OTpymgd3RWOqNZbl6gU76JFHQFuvoOxOgIHRmklAwr9DIgjCrD4tnQX8wQWd99g72iDoJUZFwfG2fVNZcTi8Y7wzp9nLWywWmqtjd3WexXhBphdnOe7VwKBHSiqSKIfHEOJSSrFczzs5OObp1m95wwE/+Wz/CN772NawEJSyb+QKhIlphwsINQaTAWIuwirLdUJ826DghjRPy7oAWTd20PHtxxv7ehD4588WKTqyxxmKrmiSJaNoGByRJgnWO1gbLf9u2FMUGrRUHB3uYtgGl0cKSRSlNU9HNI1KpuLw4RSefxrYmGIlMg3WG3fEwKK22AkkvHAiHEx7tzdXVl94J4yzCeuxVt7810wXyZBQKvArpSYqgYlHeBVcpW3Ofty9/roHZfoW2+GiWb93WMGUtCBlu9lLhtkY+s6XZKXElHwbvw+jOuRCyEaSUfjveC0x462wIAFGKtNtFaA1ChZu8MyyWF/QGQ9Kog+jlCD8h2yyJopgoSrDWgPDU6xVSPeW9bzwjVYLJYcpwF+bTlm5HECeW+aOIqvIMxhmxNyRdjZ45okFGaWvyCGzj6OSe2jga1yJzTdTEgS4bCXY+O+RwPGH5/AShLE47GlVg1y39ScR6UZBKGUxW1tBKQzqU9IYpzm2Yz2pMo3l830Ds6fUlZ08uWJxKTg8czuV0hjm2rVkuChItkEIRa4mpFTqFFkG1AWHBmWAAE9IzOs6pTMHZokWnA/q9nCSdM92AToKr99brEUVhOX1hGe5oSgu1aRn2YxpjMJuPFH5/7OIO/K/A3wT+t49d+wXgV7z3f0MI8Qvb9/+qEOJN4GeBTwBHwP8jhHjVhzbiu38RWoNt8dLTHQ6Z7E5I0oTucAA7O5TUdDoCsz4l95Zrt1/j5OEjrl2/zuuf+TyrXz3FN567n/wMVbFgd3efW/de4cu/+kV0GuG9Ic9TvGu5fvc2T999j7iTcXjtkGI6ZW9vxK079/jwvXfYycfsHh7w4J1v0+2N6He6xFnK+PiY1XpGnPU5efyYn/h3f5p3f+eL7N68x73X36DcNJTNHErIBwnPHz/l3puf4MmzZ+z195C3S2pruXZwTJznfPKHSnaObjGdPiFOxxzdvk1bLXnwlS9gfJdP//hP8fCbv413gqqqEBH0u0OcaPjiv/oVvvRL/5xe3iUfZcQqotvt0ul0UErR7faJkhiZJnR7PbrdHlnWYTAY0YlSkjQOqoNNhYxiojhkR1ZthcfQyRPq+ZJIaw4Pd9lsNpRlzd7uHpuy5emTMyINpWuxzmGkxwmNFDHCWqSw1G1LXRWcXzQcXzsOYQ5ljZKWncmE1XyGbAUbX9KKgo5QgWZowErItCYC1hvDxhdhNBDFZMsVo/GEJFI0IubF+Ywqb+jmKU1rOT05QWDY3dshS2NaZ2mtwTSGtNMhTTOch9aD0AmzxZI8DcqpvNNhb5Lj6ZJnCfuDDlJIHj14wr1PfGJbrENxbZ3FK4XzFu/agBFwIfnKs12sOhdStax96QNQWoEF09ZY0+BRxGmgXRq3zUKVMrhJXc0WTRTMT86G+ERr+IiHtPVHuO2qPKgUEUKE0ZkL4yIhtrca73jJFdoObJTS2GYbpn0l32V7+njZMGyRIDJQKxHgbIuOY4SDTqcbuEfOYUwb0L0nzxmOJ8hcIrVgXZQI78k6kvVMILoRy3mDjjV5D4rCkOqEqmgwtaKqa/IhtIUj9glNIxmNPVXV0skE64UgaizCxBQvCuo1lF2HLR36qWS517BaFjhjGU80kpAz3JYCUxqcF/SSmM6e5PxRTb2yFBdr8rEk7Qbde9rRzGctthTsv5Yz2Tvg4TsP2T3MOT+d0xYVysSkWYSNDGXhmOxLpucGao/qhLQr1beYdchYWC0L4oFguba4akrc7XI83ufFhyfYXBNrw2ptUZMOO37D0aTHt98u2TuCXlcyP9PMbU2efO/C/UcWd+/9F4QQt/7A5f8Q+Int3/8O8GvAX91e//ve+xr4UAhxH/gB4Le+55NIhdApl6slExcCElws0G1YnCkPs7MZe/st0/Pn3Ml+gLx3QZp1aY0lTlKcKRFmzYuHH3Dzrc+Spj0mgw7jyS6zsxcgHBeP3uPu7dfRCoSDPImReY+H73+Dz3//bTZ7EzbTOTQlN64f8+D+2xxdu8vs4X3y+LOksUbiefUTn6SuKgb9HsI1CBXT73VwqyXVYk13tId+/Iw865APMqJM0u1nvHbtJtPpkvnlC77vT/0YWmguzh6ROeiM+nzwW9/k+JXP4UzFhw/eI0sSlAIdBXV6WzegHd/6ym9wdOsOJ4/e596tI4QiuA43C5aLJYvlMkS8udD5xUlCp9Ol08lp6xarNZH0iME+Zmttf/7kIX/37/wvYDes5zOa9ZJ7916hWC3YrDaMxruUjeXZ2Tl37r7Ggwe/j5QQRxJUiEhrXEtca7xtadZL2nbC3v4e+OA7+PKXv8TBvc/S3+lTlStsA7vdnN2dLq5a8/Riw8JYbl0/pG1qBv2U++sC2247YNvi6gXlakmSJvQGu2gZ0bQ1SmQ01YZBN6euS3AQR5piXbOpg5mGTUNrLxBKk6YZtYGDyYhEesbjHeqyptdT5ImiFZq032XYzciyDpt1iUOCN3BF29z6FyR+m3erwEuc3SIDlER7hVWKSGk8EidDIW6ahrqqUDrGNCWmWROLLrYuaJxlPZ8yGXXhyqDnHN/BV/8DFFXvxXb84ZFSY1wd/Bc2FHfv/FZFJXAi6Oz1Fgp2pakPHKWP3LRh1CcDm/6lS3urudoinHEOY5rgeLZt0MwLh7U1vW6H4WQXj0YoT0cobFXR1h6tBZuVY7Wy9HcFi4UnizI+/GaNs4K6aKkbMBtP1ld0BhBlNV6CKRXTxrJ/E5Rw9HTM/GlJubFIFX4mzRxON3M6E8VkT+M2MVWzRsWa42sxDy49w12N1p7NxpP1Ioa9hNZUrFvHemXoRJLl2tPpSSqrqKYV7z24T3ciePzNC4RtSRA0wuK0YrwToY1EqJpZC0kmaY0L+QaVQ3nNYG+I6RrqTYkqHNIIkBXfes8xOdjn8mJK2gWnwslNpBEu69I9apCJoDDhdOrXsPje+dh/7Jn7vvf+BYD3/oUQYm97/Rj40sce93R77Xu+SSnpZcGYUk4fEYkEqzTF4oK83+f88hyhYmSUo7TCSEdtBRGW9XrO6OCAi2+9w87hMdPHzzk/O6c76mOqNc2mxtYbLuZTkijDmxa0JG4N52fPWL04ozscYuuG3qCPdY6qrOhkHd5485PIKKe4fMrph+9jNmuu3dwn3dnDtWFNFimBdS0xOb3BgJO3v82tN19hMBrRSTMiG7o82VriNGVTPqOTRSwvF0x2Jtx98y3KsyWR91ilWS2n3Hr1VaSD5cVDpDBEUYc07aGEoy03mLLGZX10FrPYrHHNhl43Z9jpM5kMeX7ygvF4B2w4pjtnUJEOvJ1YoZIO+IaN1ghvkNLg6orH732b1ew5xeUJt27so6TjcjZjPN4jihKePn/Em2+8SVnM0ULSnn/Au7/8tzEqYXFxBm7rvnSWREco7/EGdKL43d/7OsfXrjMZKK7tjjl/9AiPoNuJWV8s2T1IKU82WC/44HSG8oZEK8ajiPW5wQNH+xmrjaMuG6qqodeDfjcLHVYaMxnuEWnB2dkZDkXbNhgrKEsTknBsi1SSTpIy6A8Y9btIYVFacjm9QCjJwyeXvHH3iOenG8oGagNHtzssiw1SxERKhTm32y4yUWEhn4SZvC7aEOixnWfjPHZbnP1Wq6pUWHiGnNQgf6uKDa5xzOfnoCSx0ggvtqHrwfFp2zBXRwqkVttRjdvKptgig8N4SEmF1hJnQzLSFYxMCB9Y+lW9VVeGmY7bqnW8E0GjTvvRKG8rxxQ+aOKvNEPhROKwxrCYn1GVFVpHGGOoy4Ll9DLo2rMOkQ6LWo2jl6UkceC9q1hzeWJRMaxMhcPTGfVYzJckUUzRVMRWML0sSJKIddFweC3GCTCuBa/5zOdShgc1H3ywIY9z3v7KmsFIkvTCyHC5qEkSQd5JMKLlybM1vf2Y2raUtSFJcnq3PVmkOH8kEE4QZQoZC0zpmZ8LTG1xLUxenWBWG/oTi1aK2QvYu5aQT1JaY9HphsGOoI4UyxV0rWA1tTih8T1PthsRqZyT2YoohzQNC9vGespyw/WDCaq35OGFNydcAAAgAElEQVSzBXZpSHtjsnREXZ1DA8qCMQ1ZLL9HNHZ4+ze9UBV/yLU/1EYlhPjLwF8G6I8mWN+QZH2c6FCsThkfHNKcPMfEUDdLLC11NcVUJamOAU+1WVNvavJswLNiA1lKbWp6o10uL5ekgxHT8+fEWRaWSIlmXSxQWczpe/e5Pvksi+k5R595C+sd2WDAYr0MssaOpigt8+kF+/fe4OLZObvHdzFt+KW3xjDc2UXomLIoqWlIkhShFZ3ugLJ6l6iXMRqOWBUtJDFGCCbjXU5OPuDm4TEHt45ZvVOz88Y+s+kF40GPTdnS0SmnZ0/o9fpIocMcE42UHi2CCsQYixaaf/gP/zF1VTEZ75ClKVIJ2rah08kRUpGmCq0EcRKRpglapnSyDnEa4Xoa6aLtMk+yXq/xXnOwu0snTVjMZ6Hjz3u88/59bt25RRyBjQReKlxbsT55zLPnM1qtkIRfeB91qJxBSEV/MOArv/P73LhzEyU8pin4se//JN98+1028yWX04LMC4TJaFtHVwmq2qBpmS8WjMYpiQpO5GJdUxaWvZ19ai9IuzlVsUJ2QxHo5j2klsRZxmJVsFxumG8K1puKSCv6eUbayYjimP1xDyk83hlaa7i8XOKcwWwqhIq4c/c6ZdNQmIyvvv2AO7dvkCY5qYhwPgrmHBeWkQFIF8K4ld521NuMVGdcSD5yfmtAcFwxZa7cy2ma4sf7xDoi6eaoJGMzmyII2nK3RV9477Z5qw1Chvl3UNJsX2L+oySm1lqECJ210EEzH1C+CncleSR8bvEyu1i+JIc6DyLoi8OJYSvtvJJhhqcL/wcdadIspd8fEUUpHrDGUOzMyfpDPLCZz9hsLtFYokjS7UuiRGCMom4dOEVZWNKOYj6vETJFGA8N7O3lCGm4mAksivOThnwYAHAw5Jd+cYFXJZvSo48d+69I8jjlclpQVNBayPaDGq1qLElXsXMkOH+acrpYkuqC1UahZYGKFb6xtCuJyiHtQGslO3uOooBVsUKVDVVhyDJNb0fSHcYokfL0vRPa2hKlVxGL0DuQbFYgJoJsEFFXC2TRZ2+vw2oBrSk4vHGbQX+HcW/E9OwhSeeIuX4P0dmwf3idzYuYvh4ireSVV25SFS3nF88hcsw/+DfPljkVQhxuu/ZD4Gx7/Slw/WOPuwY8/8M+gff+bwF/C2Cyu+enF0vyriKezCmXl5iq5cX5lNGwi2s9VeE5e/KYolxDVbLYLBiOjljMV+S9iGVb4OYtm6riYGcHYT3u2h0uL56zc/0VNuuSVjs++PYD9l69w4sXLxjf+RRqtEtTO54tXrB3fMTzhx9y6/g1fORoWsOjb77L5/70D+NpaJWnmq7pHAiePHrCeJDRioYGiOwGooSoP8S2njSWPHv/PVopKNcVi9k5WdZnOp8hZMbJ5ZLJseX0xSM4OGIzPWexajg4GtPpZJSXZwxuHBFFGZ1uHxVHCGcoaEFs0K1luHeTv/hf/TWa2rJaLZhfXHD/vXe4dbDHxeUFvU7KbHrBZrlBSY8SJcvls3BUV5p7n43Jdw6RUvH02SkPT36NSBj+/I/eod40SC3pDfo8fPyE3d1dhoM+CMlqWSCFQ/igOe4NBswbjy8XCNfQthZnPJUxfOOb73D9xvUwEmoLnG1xmxU/++d+mn/8i7/Mi7MLFJ68VvSHI6bTKd2tgWazbknilF63y6Ys8TJhOIzYmeyycZK8l+PTGO9bEJLatDStxYtgomlNCI4YDrp0kog01tTGEEcJm9WUnckuXggupjOyNEa4iMI1PHx6Qre/ZLbccLh/E6UH3H90yc7Ic+PaDpezgt1hymo9xzYVUduAcyzmSx58+JjdUQryCg5xpUkPHbDd0iuuqJ5XRfJqLhIlGSJK0HEUFsNS4bbSy6twjKtFbLA5XBFA5TYf9iNHctDdty/dyUKGnUZ4TuBq6r41VfmtgkYqhQz7WCAwbgKbSPIRDpvAwZFhIdtaS5SA1wGGJWJBPuwHlY8Q5FnM/GQBWpJ1NDK2NEaCsKzmIHwLNqapbVCblQ7TCJJMY1wDQjOZRDS9iM1sRRQLOlnM+fMl02lJs3aoyPN0WSJTx9HrAq80ZaG4eGQ5/bBictfRySTnTx1njwy+bZFxhJWCLHU4K1lsDP1ejjSO9bqlPxFUC8vGK5JOgy1adK+DqyIiJ9FScvGkJc5KrIMkiqgWhqhjycYCIxSNsKStpH1cM7t0XL87ItX7JHrK8fAuvaTH6cNTimHFK6+9wnvvfJvDvZtcXDzHrFoaX7Cz3+XW8A54xxuv36UpP8HX3v4a8OK7Fuk/bnH/ReA/Bv7G9s9/+rHrf08I8T8SFqr3gN/+oz6Zd47J9SPMbM5wMObUVHRUQv/wAOqSvWu3yaSGtqY73qWoWlIduuJqvkBnPYwBY1pMuSIi5b33vsrR0TEvHj/lzps9lr2cTjygi2S6WhL3hpw9fkDWz0minLI+I01z5tMF2Z0YE2VEkWDn6JBsNOLyy79JvnuMUDFaCqy0OCfJugnNqiDNMpxIMFZycnJCb9Anyrs0bYuKKl574w2siOlaQ5alLJcrsihhNByRdrr0d/aI+w2ZbDHVEqVafFujdERrDanu0DQNymx5IsIx6fW5cfM2ad5ncXmJaRs+/+M/xu5ozIvpBeuzc4bdHhvlEK7D0TDj/QfvIRxknTFNR/H1r/8ueBhOJnzmJ36Gca6pH/wSZdNw/fAGj58/I0kz+v0us4szqrZl2B+gLy/ZNC0ffOs+e9du402LaCqsFiAkcRRjasvxGzfpdDvYpqUpW07OXvDqq29QVC2/8PM/x9//J/8Xv/mlb/LB2QKtFE7AwhukhwgoL1dIJSmMo59EpGnOZVnRH0+oyg3jfsZivqGxnk2xRokW23jKukJi2Bv38a7BmhqQaCR5EpGlMU9Pz4lVRJ7HHB5OsGXFs2rDybyAyw1xN6W3qUjzDj6xrMqC+bIKp8ckIc1HlO0KYS1eCTp5wvUbRwhTojwoGeGUDWgItrm2KiwxhQocoGBYCkoLLwRSRYFXJBVeAltqo7VBm64lIWbQBWmrcwbvAoLYXjHNdJAwRkmGaTdBOolHeI9FggwOW+Ms8dXzbG8GfpvMdFXBpfd4KXDGYLXZBm/I0NV7GUZxrsPh8a2XwTTOO5xxGGFQzuBsS2tqLqZn3L77KkmxoNuJEQLOzluaUhB3RODHNCIAyJxHJwLdE7SmQTSOKBW0rUWnMJvVXLsRM95PeP6oRHpBs9kukyvBhx+2tK0hjwTeNICkWASgnjU6TLNiR6I8bWuwsaKYG3b3MuqmplgFZpIUMTqqMIUl60rSJGbTOqyw1K3g4rSmN+6SZUOuvTJCW8f9tz/AohASNqeGLE7pjhSi0+G1m0fUbcvu7pjdN9+i08l4/4NH3L13nfFgAE3BqJ9z7XCPO3f2MC7i0fNH7A32WJ7PidKEkydPGY0P2O0ffM+6+q8jhfw/CMvTHSHEU+C/3Rb1fyCE+DngMfAzAN77t4UQ/wD4FmCAv/JHKWUAtFL0+xMW8wWJcPjKkEaSPO0wn16Sd7rkvR6WLBzblyv2j64TacdyM6c3uMvk2nW88xwdXafT6zIZ9Bjtjpmf5aRJhyzNAhRpvEemJG40IslziHRgzagYrwVNs8HULTKNyIZjHpdrIq/ReY9ys+Rgd598kKKTiHKzYrK/g1MxdVWRKMErr72K1ClJ2kN6DSLCxSXVpgRXM7u4YPDmm9iLc+bnU9J+D9MalucnPPzgPp/+oR9mM7sgzWKEs3SyDq6tcGbL4m4b2roGHHWxZr1c4GVCksRk3ZRAM3Fc3xnxO+8/5PbRDXqx5/2vfYM3b/wgURSRxZrh/g7rrebdG8vB8avcfPU2/cxx/z3PzmTMi9MzTCO4c+eQqiy4vDjj+MZ1vAoGMh1HpL0EYw0eS9vU+CQiTjo4PDoJphbnHKa1nJ6cc/fea6hYo9sG1xR8/s1X+VM/9H3MLmd0koyzxYov/9ZXuVyumS5XSAcKx7XDAw5Gh8xaQ9bLg6u2rZguGurW4JylbSo6aVCjvGT/2xZrBXXdsN60DMZ9qs2GxfmaMlG8cfsWuWzR3pN1U/YPx2gtqNYlTSu4uDxnXc45PLpGtJPw61/+Kol0dLpvcSPbQ6kePlXBIeo9/SxisawCg4WPNOkv4xKvxht/ACznfUAZSxFtZYtXWnmAgP1tmoa4w7bYW65IqEpseZXiir8eunulFE25pYxemaEEYdm7HcF4t3WqBm7zd6hwvHMI6dFCY22zPQmEEOurr8/hMKbg/rffQUcRSZxs3eUdhJckKkJozUZWXL/5CvvHN/j2ybvUpWC4Zxg5zeLS4BtQsqU3TomyBHcimJ8WWCuRbUTeh7QvGewknF20DPY7NG3C6gyaVfg/eh/yV2UtmD6pwEk2aYNEk6dBIlktHVSe4d4upq1o7SV1oSkWjkSlzM8byjL8bEY7mulZQWcUgINOCYh6cFJhFi39e30Obo74Sz//19jrjPgf/qf/hvXZKeO9EToX+LZhlGTQTSkXBd1Y8NYb15F6xJMnDxh1B1zMLnj/nXe5dWOPXKitcSxmejmlPxpijKKcFohsD2trKA0LtyBK+lTt/8eYPe/9f/Rd/umnvsvj/zrw1/+oz/sdHyOgk/eRhwdEUYxU4JQnjSIGoxGx1hRlQzzJWDw+5eb1V0jzHsbW1HWQoR1cu87FckoUJ8SRxCcS6yFVMVlHc/rB+9x49U1a07K3e8iik5PlHY6vX+fi5JS832GzWnJ8dB0RgyYijSImexPSKGZ3Z4+zDz9E1oqkn9ONOzTVJbYOc9GejigWc9pII5oidG3Fiv7uLufPV4xu32F9OePanVu4zYY4TllUS/Ksg2wV52nKjXtvcP7oMR0dURQFwkniSDO9PCGJoLaesliHRHklEDjOnj7ixmAMpiLRCVrH5P0+q2LF3vEuqhcRI/B1RW0anGmIuwOcsTjhQ7fkGg6uHUJZc3y0w4vUUVQFF+cL3vrMa1hXs5hPGY0mZEnObL1AIVDCk2YRiZbIxhFHIcRDRpooVuhIInG0dc3J6TnHN64jtSJNEh5++JBHH5zxfT/wKbJM4a/vkcSK89PnfN/r/x6t7/IbX/kaaX/Mr//Lf8Xr14+ZrWrGO7s01rFcXGLrNa1WwShmG4xpUU7QSVOE8HihmS9q0rxL1t3h1v5B4LJIx+Sgyw/+6Z9kfvKIk/tfR8QJ1mkWizVZpul3U5IoZ7pcILSmXFc8b08oG4OTggfPLhgOx2gZoWUcEF6tp5Up3s/RIkQbWu8/wkNwpVkXW1FlKPjWBSdqQBoEvfnVm1IK04axjdqOYoIi5irTIEgb2SIOvLfIq/elxJrwuEAF3XbwsNXIXzFrtolg4dXIFRbBC4+VV8EyCtO0KGUw1pA4u2XXOLTS9Lrxdj/QYlvDrChB6nDT8Q7pLQ7Bk6dP8aJFKcHlqSPOBAfHKWcnDdlYcXizy/pMcrKqGU7C6VlKgzMCnSoWK8NyavHO0FUDJgfXePzBe1SLZTifKPDCk2hBUztMKxgOE0xrOMo7xLdGFJsKsbigsIbKRuQdjymhN1YBQdJYdCTRWhH1Iqx3RDanO8xRjaRQS165e43huM/l+TN+9V/8Xcqp4/zpCz599yafeuOTvPPhB/RiRa/TpZaaR88+JNWOR+89YrzfknVSVosZ8/maqCPYnexQlRVlUTEYZ5SLS2zZUtuYnfEeVWVIux3qTWjoOt1dlIy+Z139E+FQtaal2VwigW6aQBTCZ3WkMc5gvUfoiLTTo93UpElKJBVOSAbjAcIY4rzD7GKG3RTMzs7YmxxRC03lak4e32ezWlOvSwZjjXAOIRSb5ZI077A4+ybj12/w5P59hqM9lqtzjg+PKTYr9GBI1VhUluBFTXfUx9We0reISLOpK1Z1w3jUxxSGbtyjWC7Z2d3hbPWUQT9n8eI5t155nWen51z/1BvMnp2SD0ds5guSvMfOwQGLdsn89IJ7n/1+nrzzO4wPb6NMzWY1Zb1ekqZRYLKUxVa+qCiLNSfTGXt3X0U1FTqKiNOIeVFhvefkwbvIumK8t4vIEmoXlq2ewKawzRrtPBjB4Y07DCcDnPAIpXn08AVvfPJVmrpgtaoZ7xzgTMvlxYzZchZgaG1D227Isy5i20W2xgSZnAoEQm8Nz5484ea919mUJVoJnjx5wfn5hk9/7pMI4airliiSPHr4mCQZcuPuK1yePOE/+fM/yc6tu9w4OOb+l79KdrhHISPOZxd409LWNdYFx6j34QSYZRHWtLRtiUDz2puv8yM//iMoqUjTiKKo6Y332T08oKprvvh//0OacsX+ZIhXisFoRNtUqChkve5MtktCByKOKIqSpWm5OL3gWwJsZ8CP7r2JdmcIucJ7ifIK1wbmx8dD0P3HijBcFdurLt5/zD0c4huvEvgEAVdt9UdGNa2jYKLaatG9dyHXwLmPFp9K4J18uXC90rpLPlK8XLGpPx7MjgjIjRCho1DK420bUPY6BHRbO0dS4qOItmnAtrgtO0lpRZzESBmED1KDUhH76TGtaXgyK5EyqITqShAnnt1dTW9HM5+uMBuBVYb+LcWr93Luf2OBc7C8rFiuDLu7A7pSsSpX/L/Uvdmvpdl5n/es4Zv3vPeZhxq7qyd2N0lNlpSQMmXZhh0YSJzEgO5zkf/Dd0mA3OQihhMkV7KcBI6lyIglBZIlkRIpqkWyp6qurq6uOvM5e97f/K21cvGdoiIgInKTgDl/QFdX1al3r/O+v9/zBOIaoQ1eojHGYGtH4Gn82KO2BWGiCYaaXj+iLOFnvvYt/vj3/w2VqFgsIOlIjh/5nH5ZkFYNncSxsxsxn1UsznOCnkeRCYhS8nXF6w9eI04Ul5cbDsJdJu/8PKcvn7LT22F/mDCMRmhPkShNL44IdcCkt02RXrWI7KlkNZ+SNg1qotBSMhz2WC8W+H5AmVnwE+Igpio2NNKjqiq8SFMWJVmRgVex2lyRxP2fOFd/csXp/6MvBxTzBdFwB1dbDl//CuliRWfQa7/RPYXu90BodOCxXm6QqmWQXF1do7THpipJpEdnOCQMQjpRl0hriqqmNzzi+K2vcvriGet0gw7a16Wzls6wT5atCb0QaQ3K02hj8eKAfFNhi4q6SAmjmAoNShCFPuliSTIYs1lcky6WNEoQDfvtPyalSMuaSkhmqxWqG+IpH+uBqw152WBdQ1WU1I2lakpiP2Zx+iWd/oTNzQ3nL8+RfkgSBni+R9UYXF1CY+hPJjgnybMU12TkyzVlUWOQCN0q5ExRsCrWPHvyBV43bv9xIvGSLmmxQSjL7HqKERZFwybNKKoFSnlcni85Pt4lChQ3l1OSJCSOO6w2FfP1irtHRxjaWJ66LcEIWipiU9bY2mCqhqKuubq8Ym/3ECVai9Ozz19weTHn3XffxLkSKSyh9jj94oQk2ebg3h2kKwmjGJTm8x/+JQdJyDtvvM3WzoROp894OKY/GFPWhqyosLflFAtY6UjzjNpa9g/u8Ct/+xtMJiO6icYTlsmgQ7/vI29TG0UjmS9z8rImyxtW64qyhmcnF5yczynLkk4SMBiFbE06vPHaAaOO4/z0lO99csLdr/w97r7/Lb6Y9xCdOz9ujgrt/VWGnNtXu+DH73VrWrKQuD2IKtW+s5y1rTVJqNtHeYukaMXbEqRCKg+HuEUH8+Os+6t1SltQbnlH7bal/buy1mCNwZjq9oBq21KWai1orz6AXvFyXom0sZCtUy5PTlhNp3hak60WXJ+dUKRrcKZNBQnRehM8hRd4+H6b1NKq7Wks50uWN1NQOekKqjwgzyBdQZFb5jcVwgX0tj3uP4qhMWyynCKDKPLpJdsMR4rDQxht+aQbyYunM5zM6ewL7r69QxD7lKUlSwtU1EIF80VKtsi4ma/5/X/zm4Rjw3qpsAWkswZP+tx75JP0G7zAMd5tGO60Yp31osbUgk7YY7J1zPXFDTvxNu8+eBtPKAKh2I33KWcrtsdHXF/d4GqDLSXL5YrzL895+flzQhFjc4E/SCirBuEkxTpja2vI3tYRSZiglabIc1aLDb7XZb0pmQwTtKcosg3lusQ0Cj9KqJsaxP8P2DJ1VXP58gX+YJ+T6pLCOpYvnxEMhqzzElPPsF4HY9csN2uKbMUyW5F4MZ3dbebrNU0tmC9uCDsx4WpOJiXh1hApFSWCrKrojUacff6M3YMjNqZhOb/mxZenbQmm1+f8+hJnHIlzbL3ZsLh8QTgaU+Q1prKQFVyfnGCbgjjs8uXj53THEbV1nH38hN72BGfaY9jJ1TVivSLqD+mMd3ny+DEGw8unX6DjDpt1CvgYIbi6bD8gvF7E809+hFOa+dVLtjs+fpgQBj79fh9nDWWRIa3FyIaqMcSdCetsgcgd/mRCeT3DCwPOPv2UTVHxzsNHnF9c0xnfYTGf4wlJNrvgRZ2xLBuMbRBeTBR2+OxHP0DUDfffeYPYLbm8uCH0Q7pJxOxmyfRmxqO3XkPKNjqppUZ7uv10lo5a1LjSopSHCzyKImey8wbOGrSCL5++IN/kPHrjAXWTIq1FI3jy2VMOj48YjUdIWiDXepPxv/3+D0n8HtIFWM9nvsqYphuMK+h0I+7cf8iL589xTUlTGwJfUOUGYWF3e5tv/d1vop0hm11juEWqehXOlNTeks7WDv/wP/4n/MHv/h46v+DoaI+Pn50ReIok9HFKUDSa+bpgvDVgnZecnFywSS333/gG3/zW3+XgcIff/u3foLaW+WeWh3uvYbwNGHBW4GQLCHPOgfSQ7jauIkBrRVW3jlN7e7w0pkGroD1iWtPaVSxAq7eTDhwGhI+QfsuT53Y/72xbsHK3zJkGBBXCytsPk9azK2gpku1VUbVOAIBbjHFbkJIIBw0Gi2J6cYmnK4KdMcI6ev0BfmjY3j9muWkIQt3iMWyDbGSb0tGttL2pG3xP4SsNKkAZKFIHoaMbabJMI3zN1j7Uad0KV5Rk9tLgax9LQ1kCwTn+yHB5Ywj8kt3jfaq04OpaU24c25N90rlkdXND6PuYoKbMKzapIGxq0Ir0sqAuU4KRQktL4IdcpxBkluHYUWwUhfUwKPbvx2RphXUFm/WKY3XIsjSMBmPuP7iPr0K+/73v0Ov2GB7eJ0xGfPzdPyacKvZ3+lxeX2GoqKoNoR8RBC38DidakFhtqLINTV6zdTAmXTZsH43Imku8ZMjmxTm+CugPJkwv50i/wZUWCEAaTP03xyDhp2S4SyFIuj38UGKVglJy+vIpr731bvtjf/eAQmjCRLXZ19JSZQWD7R46jEmXC3zjKNI1RbphcBy18KqmwSJZzG8o8wzP71I1OTeLGbowjMf70Ji2LVgaTJrR3d+nvL5iuD3h2Y8q7HpNfzTBNxGNbMsuQbfPYGtAYxuy6QWdrX2sdfhhhyrPibsJNzc3xFGE1orxeIsqM9SFIowjVJiwmN/g9xJwBj+JCHsTGt1gak1v+wApJWWxIYw9lssl0gvwfUV/PGS9sdTGIrRia3+P8faYzdUarRRaKuJeh7IqqJdLOoHj6vqSeHBEU1XEkWY9dUjalqoxFqkMRZHSGexS6j7d/hbpy1O0DukPIxbzjBcnZ7zx1usEniDPMjwpb19qiqqpqUqDawRWG+qmQCto0hIhBUEk+eSjjylKePDaXYqqIPAkeV3w9OSE1998iyAMwSrwHFma8cF3/pzaDbhcrNjkJc7TeDok9DU0miCKefja65RVyc3lWZszt4Iokjjp8fX3fwbbFCzXm9YN625NVUiquqSqC/YO7/Ha+z9P95/8p/x3/9U/ZWe3QGKJwpjAawUTi7Tmej1nus6xVjPcecQv/b1f4NGbD3jyox/wu7/1z+nEHvePHzLNap6HIUN/G5RCyduUeGMxtUF7oIRq4V2qBXgp2RaOmlc1/1fFIdkWwoRrj5jylSAeS9nU6DBufwKwoK1E3LIn+fEL3CC4lVTTHlrrsiAIO+2LvzHIqkEECoL2WP9XKySBdQbhWmiXw5JmGw4PtwnCqKWiSk038lvOunBcnc0QwiPsJEhKmnoNWrcDNd0wGrTo4LLM8XTJzkBiOoqyrIl6FiMqmsprX/KpI4o9PK89hMvYUIVtYmcYeJy8bNB+w2jnmnTtePfNd3j/5/4jvvenf8rrb++xnq/59Pt/gikcQaTw+z6RJ1CdMTeXV9hZ29yWPkSTgMurgmpaMxpLqsLQm3igMnRYcrgDzka4usv0+oSt4R6L6ZKP1h8RejGbRUq5KRB6CfIU07SS8v6oT74qSeIEYxxFWiCUo6kaamPp6xilBHVtsabElBAFMY2rsZXCv6Wunp5d4oddmjpHO0voW+qsoDENia5/4lz9qRjuWmt0EqEkVHVNokIG/YRytcLVrcdRaAmmYLS9TWpqOkmEqSsSq0nLNW0+FyI/oCgKeuMtAhWytb1L7EmqzYrtR3exTUG+TOnujMnnC2ZnV2zdv0NtDJPtCV6nj7m+wVUVvWGfl5895/jePR4//ZxBv8fNxQX64A7KQeQF1Emf2A8xXvsCKouc3mSEqAp01MGVBc5a5ukaHwtNTTWbEfsB4ahPOZsyX8w52t/Gw8NKR9zfIejFXP/oe2ivQxwkNI0h8D2CuJUTNFbRiUPS9Zph3SA9iasqhBdRZilxr0dvskdjHJdfPOf1d7doXE0v8gniBLSHh70tZFnOX7zk5375b3F1fU1YO6rSsLs1oihTzs4XvPHW621lPF2Rrtb4nof2fLT0aZzDNBXWFCit6UQ9Rv0eX3/vkFALPvzwOVIH3Lk3wjQVnoZ0veTs/Io33/oKURJjbI0UlscfPkN4MXuP3uPb/+vvgaNtNgYBg+EEQp9OLyKOQoaTAY/eesT56XOqomQw6KMDzdvvvcfO4TamKcnTDdl6g5KSTqeL5/mk66DhFoIAACAASURBVA1N3fD5J5+SVw0P3vsqh3cf8fiLL+mFmroukFrTH4xIpCIvLb7f55d/5dco6oq6XPFf/xf/FFOu2JtMaErJZ+WH+HHM+dmX9Cf73D16gCC9ZafrdpgrRVlapHoF/Hr1mm5+zG8Xsl2tvEqycIsVEFLirMFUBU2e4vsdtGhJgULwY61h4yyea/+bQiicNTS2HfCmLPjyxQmHd44p10vAEGqNenX0Fa/0kA4lWhOWATxPsL27zXBnFyFb4XcjwUkBsl3HdCY9ispRSdgaj2/F5A4pPSbjCeCoq6oV4awrgmFErjJEA92OYJ1JFpc1aWZbjlSW0x2E6NhQryTzc4dUBmkg8CWNlmRlQVl5XM4McjTm0dd+he2Rz3e+/V3MX3wXYwqqXBB3akTYJ6tqhLN07vTwpKBcr/CKBrVu8RDVpsPufkhjcpZLmBzF9JMttPC4OS149/UHrJdzfKVZz1ds3BpTGzar9S1a2+KsRDjHepmCUKw2S3CSvKgYjAcEUUIv9EjXKxLtk242hP4tWkS0xqsycwhhiWOHDFOCcITyfOqiIggDPE+xXM5b/8BPmqv/L87s/8dfUkiapmZ2fUNnMAIBSnvM10uUbm3tMvRx0hAnXaJJn2y1IepJdBhQZdeEUQfn+yxvLtjZ3cdpiZIelanBGvLNiqLMCQOPy5fP2D+8g9/poJSPKRVlXuG0R55neEnCerbC6/SxQrKabYj7A1wGXhiwXM0Z3DlChxl+7bO6Pqd3cMDi5ooo8NB+QFOVZChYGuJOH09YlDVo5bFM50Sqj0ZSNAabG0wtWG8WrJdTRpNjup0QayxKaTwVECUdMKY14OAIghhbp1yfnrBzdJ/+oI+rapQfoaUk6XQZTLZJ+hOOjguqYo3fbQXX2g+Ieh2msxJX1fheyNHRAWF/SH16ipO2fXkUJSdnU9546xFSOlarNUI6+sMh86spytN0OwNm6xyBQQhN5Pc42OrxtXcfIMo53//+h3T6A0bDhLoqiaOA2dUNWZ5z/+GDdu3gBNo6vvf9D3D+FiLq8T/9z79BU1Vsd3vcO9jFWrjZzMlucg4evMak18M3Fa8f7dD5tW9yfXPN0f4BSeTj+xJrCkzRkGUFUmrC0Ed7Cu1p+v0xZVGyTFdcnb6g1wn5O//g7/M7//q3CIobnJDQCGazOYPRLgcHd/jW3/9H/OEf/R/U+Zxnn31KEgY0NiLPCsoyZ7aAKOjx9tuPKOo1EkODQ0mNVn57pLzdwbdC6lcij7pdv9iW1eKswSLb5Iy4XZO426KSENR5xuxiymKZY6uc7U5CY6u/ErXQ/hpa3ar0RCvjAIenNXWRs7o44+WXX/Da++9jrMNH/Vj6Lm5BZMAtTrglWA4nY0QQ3XoC2oikuI2bIhTCVYyGA8JOv/19NAaHxbi6Ze4gkJ5H0usR93c4O/8BTjVEwzauubhwhKFEKcFq3uBKRbzVEPkVUazp90KurhxNDXnZJozuv/0aSX9Ip7fPix/+KZ89u2Tx7GMusjnOs3QSRRAp1o2kt+8hppB5mrg/wAsNLEKaTcXOgz43F5dEOgCvxfcGro8oA14/eBtnJG8cxHzx+QtiX7PaLMnzjG7SReqA2WKBor0NBnGMUBbhHIGnWJaWThThBzFCCtJig60FQRjhlMMUBVGntVkJARaD7/tYZwiihGbTgtZCBQuT4dEhXabgapbL6584V38qhruTgk5vBIrWdzq/IYw76CBi5DlqU0ANZZnT7/QpsgU9v0O+ymCSsPj4kp39gNHOHl8+fYJ2gjLLmeXtnlXKgMF4mzZhJrF5iqkc8WSAchK7nJGtU4K4R95U+N0hi/UClEQlHpvVFKUlJTXOKuq6YLPeUE3nVDaHhh/LMTarJVvKY76YMxj4BDpuOeVN00KJZhV13RCEAdl8iVOWTb6hvm0W2sqQ5xsm4z1AtdAhZ9tollI4Y2iqnCTukM4WBIHHarlmcnjA9PyGuNtnk6eoMGlXL6HfHuzCgEAHFGVDGAbk6yV5mqKEw1eyJS12+vT3j1l89AFj5Xjx8gVvvf0Oni9YrzOssWxvbWHqCiksTVVSrFdEXoz2fIQMGPRivv7OIaZYc3FyycM7R+C3mN3ID7k4v8RTkjt376OjhEArynzGd7/7IfeOH5DsbvHf/LPfxFYFD3pDjre3iKXA9wN24pZg2d/ZQvUidKRI84z9vSFHe2M8pTBNTl3n5GlOmZd0uiEaxXI6ZzldMNnepzsY44UNUmnKqmQ1X2PMGd/65jf5k9/7HTwlWGcZ3dEeew/e52s/+3P8xr/47/ny88+IfZ+t7S3yMqMsa7pRSCf0EbbhsxcnOFPyS197i6ePn3C43Wc1XVJlOaOdIVoqKufalYeAV1O0TSG6vxaRfEVhfJWRt7bNx1e15XqWEyaGUFQ/Xo1ZIZCqhbYJaxFOtUPdWaBlwEit256Cqbnz4B69fo+iAWfNX4OEvHrBOwso8Wr0o7SHq+pbK2p7SxBWIISPDnx6w1HbsBWvopUC8X/5/WV5RlPXbO8f41mP1GaUc8PuQOCHlgqBU4a4G5PrmsY0rGaCuGvZPejTHQacPVvTSNBdwfkLy/HxXX7wp3/IR+WS9cJgbInwfHwFzkrqgYdeVSib41V9Dgb7FJ+vcAqO7hxQlxEvXn7K+6/fQ/k1vt5leXPDa+8dEfiazWyJqT2STkNV1HS2E66n19jakm42xP0uUrWyaqk0fuBTZBu6/Q6ebMVCSRRTFBVlWRB2PERTo/HYrDbEcUyWVfjNpi3m1RJfStbTGZfXK7odzWpzTWNrwjhBKofn+TS2Zl0sf+Jc/akY7sZa6iyH2KPMCpbZEpOXBHGHJm+QdUEy3qIoSpaLOd3RFvgeVV7hmQjhJPPpnO7uNkW2RhhAS+Jhl1U+Y54tkVGMF8aUeUbWtMeeRkGz2KA9nxcnz9ga7hKGIc1iQ17UdLsJftDl6Sff5+5rX0e4208f4Qg8j9wLcbahTCuulhlNviZSPoW1oDVF2tB1jlWa4yUhNIrL80s8C4vNnHxd4LRlfjNjNV/S297l8mZKfnHOYGdCWmSYOqYscmLbQwmPqrYtW1y1XlatAtZ5ysXlFVWWsclSsiqlTGuqumRTFixvZlCU9MMCbzigyksWqwVZ2X4qNXVNXVds1is63R6zTUa+uOTOw2OCSJCmGXVRs727jfY8Lk/OaJfBFU2R43sJrrEMegG/8ovvU6dTZjc5bz56jarKW7a4NXz+7CXj/T0O9o6w1uArWM2nfO+7H/HonTeYbI8QQvHr//g/4H//nd/nUHsoU5OlJS4IMcLR6+xhXENdLFldzwFLjWBrNEK7jLouKcuSbJNR1RYvDNr9MhbfD9pDsNIIBzruIAcDOpMBZVWRLaa8+zM/zx/9uz8Cp/n3f/FXCeKQf/2//I9cnD7D1wqnJFHkob2IUS/m5uoK7Xk0RjE+OEB6AR99OccY+Nk3DXfHHZY3c6qqZHZxQ+Vy+uNRO9aFa7kzr+KItK1TdyvCxlqsu/XiYhFCk/RH7N/1kMpSLW/ax4unae+04rasZFAIkB68OsLeJmO8qIOjJi8KqrpBah8hb9dEtC9OrMP92PR0Cwm7VTWKWwBZCwxu+fPCWS7O51S1IYwCPK1QvocXRmgZEQQ+YBgM+jjg6uIxcQzCD7g8r6nimu5IUZSQdD2ur2AwiKizDOV7dDsJn3x0xmDkcfe1mMvnBXklWd5c8p0f/UvytFVx1nmJ5yusyvEmAZGI8GrwhhF7h8dM3nqTLz74gPLcsrt9yCgIOLr3AF3nPLp/zPR6wcHRG/xw8QEnL84ZDAZMb+Zsb4/Jc0uaLYhSgbWCxpj2+6FuCDyFr1u0r4ejsm3RzHmayqzpy5gyzxFBa3rzb2U/GoWjzeMLV5ClKxAhWMdms6AsVigS1qzYbDZ0Oj1Mk9JUjiiM6A67fMjp3zhXfyqGOwhOL89JBj3kIGIzXbJeLujtTlnnM8QqZb8zwTrL1emXjLbvcvrkM5LBgF4vZJMVTPojVqsVRlvWed4eFI2lKmry5Yb1/AbhdxBKk29Srq/OGHghq+kFfhiTZWuuSkE46rOaz6h0SKUU03VOmm5Yr9acnH6O5wqqxqBPTpnf3IAr8IwEP6JazcgJGS7XFFVDnV4QjjXrZYVwFi8IKLIc5xRXN1OqoqGbRBhrCDs95jcX+EmMsA4ZJnhhiJKKKIppakMjFc4JPO21MgepKbKcSS/BNU1LvJQS3wsoyox0dsHsZkAQR7y8vmET5nRMg6kavKiDqOc4W1PWBZ8++ZQH3R18bbi4vuRnXtujk4Tkm4rVas3u3i7OSZ48/ox+nLSybyER0iMvK0ZJwN/+5Z/FpNfMpyveePNtmjpvizTWcnZ2wWTvgJ3tPZwz+Mry2WdPePL4hL/1C19DBf5teadkf5LwzW/8PF9+8DFVmuFw5KZEKEFmNtwZTbj34IheIFjMLpktZuweTBh0+yA9jPL4t3/45/zOH/0lYbUkL2veevSQ7iBmmS4o6opud4CvNav5nMVsThBF9MY7mCjkl37tP+Rwf58///53acoply8/Y28yRiDISsNiOiUONKlxVI2j2+8Rd3v0e2Pm8znT5RLfD/nB4zndr0YcPNijLFPCTkCg/LbcVNc/HriiDbbjaodoQGpBae3tn0ebmmnqHGssYdxhdzfG7/S4OdXUZU1ob3V9SmAKiVVgMHjabw1ItmlXI8K2SSd8fHkLM3PtyxvAGHOrCrldGZkaRKtnbOOatGUiFI0tQbYpnzhyDDpbeGFMntZ8+uQxQeRzePeQPM2Z3tzQH3QRXiv4yPMlVSUZjCOqCjqThmxjyOYCaQOUav8/ur0eeVpQFAbPC+gmIIKMwV5ER2lOnq7ZLCsmh/vgAlR6Rhx55JWlmVpGDyOSXofp5YpJ1mHYseSjIfd399FegCmWvPziGXf29nGlolwabvQFZZ5TZxlNY6jLiqIoKKqGLMtZLhTWSLzAJytLlNYkndajkGc5Wkv8sJXD+FogfUHtDLU1aCcJwwBbOtDgpGw1fc6RZSXS87E2u5WON0wmCZvUUDUNTra/nvUa1nmGVu6v/bT1f/f1UzLcHYPumNHRMdZKelGIUAOcqWjqGiUVMgrxsg3aE6gkJs48wm4HKTSBVsgwopjPqWzDarVmcLCHrQ2d7ohUrnGbG6rlkqA3IglDRBxRrDYo5ePj6PW3KFZr6nRO3OviS8Py4ozd4we8vP6CvFpz7/X7vPzh99A6YjAY4kmfptkwv7hgGIbkZYypWlRtEvdwfk4YdUjLNYNuHwusb86Jeh2E32G83ccVBUK1jsnFxZek85TjO/fIluvb1qLBuy0wWXFrVxKt6xKhcNRIB2Wa40sPhIcwFU5BVTcUecp4bx+SPqYs2SwX7N5/g7zIUesllprhzjHlJqdaz+gc7rB/eJcwseR5TlU5dvf2kZ7k8UdP6fYS+uMRi5tLpNQURcFk0ufrb92lmF6wSTMevf0InCMIPBZ5xtX1NYfH9+j2hihp8CV8/4PHrNYZ7733Bk7VOKfQypGnKSdnnzPZ2mP7V77C/GrOeroi6nbpDXocHE8Yb42QzjA/e8bps894+PBNer0xzosQpkJR4bRiVvqEdYASjo+fPuXRG++QBAGLizPSdcrWeML27j5Rr4/qRuiohwq6bG3t8lv/6l+SUPPDjz+hP0xoipLaWawFpTRFWmOVxvNDNqsNVdFyWpJQMuiOGfZHFKsNJ9MNiTcgCXyUL3Cm1ey92qG3W+7WuKWVRtFKmAVtXr4lMAqyNCeKfIRwrLMVw26M8AVl3q4HG6fpReA8cRsnTdDaQ1gNt6U3h4+zGudLhKexLkc5v7VIYVqkr5BkeYanLE3ToLRCijYvb53DKYk1GiUdUns4Z9o4rfbQYYAvHVv7I3b29giSLt2B4eje/dvv1zbx//zxE4xnKVxJp1MjpE/dFOweBEwva8JEsVnkdLoa1xjwK+7e77OezlltGqKOZr6AYdJjpWf4YQs2e+3Om3z+5AWDkUYIj3484f3XHzLdSrk+fcn2eJ+u8phsjUjzkovrFVHYJV3PCbz+rTsWkrjLdJMzmy4QWOIkptvrE0UheVHgnEBKje87GmuxtUE51yoFadvA6XqJ6sZ4gU/ZVARB2+BdTJf0Oj2MsxRlged5baGrcWipyJsSJSR11d4Xl/WcwW6f9OKEUW+LxaZdV7Ux059MdvmpGO5SCKLAh1Bh1wXaEwz8mG6vh9KS+clzHI5OmKCkwA9DgtinrgoiY5DKIn3NoNdjkYwRKKJegisMJowIbUUv6babQpMirCSKEorZDd3dQ1zeVpeFMnTDHjLqc/niMbozJuiM8D0P2xiE10EIj07SoakbpO+BdXQmE1xVkQQJKzZUjUFoH+lp6rzG5BViAOnllKbcIIVHti5Q2pKXFZ0woahyVvOXqDzEHww4++jPKLIUXw2omwrTNPgBSK9FyjrbSro938fVhrpxiEEH11jWqzmGhuHWDkW6RuwdgyowtWNzc42584CirhG0lMIoDEEKLIq8cCTJkGJ9inWGrf09lPZ4/MkTxltbHB8fslrNb3kxJaMk5quPtpidnaKVz/H9e+0QqDcsNzmrVcb9h2+BsGjfYqqaP/jzD5mMtnn3+JDGFSgLUaS4OD+nLiuO7t2jqQ22LkgShWx8fuFbv4CnJZj2wOhcTZD0ef0rX2Mw2sZqvy3e6JZhrwyYsmBeWe7s7VHdnPDkyWPu3jmmn7RHP+ssmzIjXVl0kXJwfxeE5kcffJtIlXzx9AnduEOaZSyrjNKBdIbtnW38xAcLW90u1jRIESBMialLlFF0twf0dnpMlwue3RTcP4rpCmiRS69KQ+1Ql7QwLuNSinyBc4I4GSBdm5iRSjIYDqjKnMY1dAcjlANfRaTFhs9OzvjTD57wn//6N/B1jMCjQSCNo67bB4JU7fAQDqgNzkmkDNrSlHEIJxF4OCuIkw7Pn3xMHHfpjQOcdu3B1gmauqGucpyzLDYz+oMRQgYYJWiamlArdrf3iZOExkksNcY1CAN5UbBazLESlJGtEKMHs8sMp3zOrwo8KelE0BSWThLQSJ/NZsNZMePe2yGXL0E1kq4HvZ2YQO9xtDdidzzAmIrjnV2yfolLHDvZhHKeMUoGXHHN2dkLPCRVmiOBQId0uh2axpAkPW6mK8KmRimN1D6+FGjdrk6cc/haYW1LDMqzHE9rqsbc9k18sqIAHOPRmPk0Jd2sqZsa4SSmae8aNTVN3WCbkjIvMHWFHwQYa6htg3OSui5wTYUyffb27+B7CVuTQ/K0YNDbQQceSihWi+wnztWfiuFujKEWDWF+q2q3OX44YFOsENbiNTWuqNCdBCUE5XKBRlKmGXRrTF3hHDTFhqA7pKpm4PaYXc8Y7x2xWMyJhGJtSvy6QYU+2guoTN7yOqKAoFAUUpNulkQqZLBzhBEOp9vLvxf0SeIh3dGYqimRWFCOfLnE7w1Z3lwwHI7asohz6BCq2uKaCicciAAvTPC9iLoW2MrRDRPyxZxktANouv0tpospnghJby7ANNR1Q+MEVVmT3A5hLaGuMrQQCE8xm17j+wNEv0NjS+qqQIYdmianvJmTbt/F8z1ST6F9D+ks3IqUhRNo36c/HrKZnRONJjQ6pl6V7BzsYJ3gyZPPGI/G9PptZDHfbBBKsbO9xZ3je1y9/IJ+f4ujB8fkVY4n4fRyigEOjo7adYBWTKczPvnkGa/ffUhv5JOXJVoosILnT5+R9Icc3rmHsA6jHLJsSYbpYtGCwbIGL1R4ocY2ksFkD+V5GNOghAfC4ETb4FRhgAz61GXB6briYLDN8uqEZ89e8ODB6/R6XUQYUDWOxjS8/vpXWSyvefn8c+oyZ+/wPkcP3+SD7/0xwXyFrSrKqqIxFlMZVuUGaR0+4PvQ7QUgbkmhQURdVewdDtnZnrBKc16el9zZsUQanOK24n/bLHUgPY+yMCyub8iznOFOTVW3NX2tNU1eggNPt6wTuC0bCccnT7/k4ibnR0++5LWf+4d0Hr6DKBsaYzjqfZWm62GyLi6QWJOhbIOTyxb/KwuU7iE8jfIABEoJ/CRga3tMXtZUrsHScGuFZ3l5RbcTMZxsY5xhvkr5V3/0Q37hvbf4xs8+QPkCfIhkSOhChGqbtsqL8D2fm6sTwlBydtowP4fRRGEc6CDCU2v6vZC93SEff3pOv9MlCRKigaYfh/T3Y7qdhKrI2J48ZDx6SLnZcPb5Cw6OjymyJW57xPOrM/JNhmsMoqgJwoRys0JHCdOb2e3h18PzAopyg7OCMI5RGvzAZ7yzRb5ZEkXRbYCg5SZba2ka0+bQHfi+j6FNBAV+RFUWONGSNIuqYtAbkKY1m2yFkgoRto/ZFt1RkST92+OzJC9ywjAgim5FP0ry8J33+PAHH3F4dJ/nnz+naWreeP0tyqzG7ir+4i+e/I1z9adiuEshiKOQUCmMhPkmZevhu1Tpgny1wUYBEtNq3ZIEoSwm8FF1iTEFeVGyG4WojUN5kuXpJ5zZnM7RQ1TYwquqbEU4GFItppRVQaR9ut0engSjA3RjieOYOlvhSdOug6yBYsnq5hQbJxx4h9S2JA5Dqs0ckcTIuiRSkqt0yt7+mGxjiLTAVRmh8MEY/CYjioP2k1aUDMY7ZOsK26zZnH9MfxijfEtjHEZumJ8/Zjjs4MsetYUo6aNVQ2MqhG2jdJvFDE3LDNfKITR4UlG4hrKqGAw6GJOT52ussviez+L8nCDsYGtDXmRIJVCNxY8c1jlMXiEdRN2EruzisDx//Jzx3g7dQYIpK64uztBO4gcRDx68xumLFwyHE/aO9mhsQSAEV6dXIBR3ju8ilEN6iqvLOU8+/YJ333oTLxIY4/ClxjnHly+fs394TGcwagXNGkRR0lhIi4K6Kfn4ox/g8gpFQBRLlGro9Sd4YQzS4QcxSisiz0doheckBCGmrPmlr3T5yt0dvvMDy/l03dq8qoqqduzdO2aye8DTJ4+5unxGoD229w8Z7+8QdQa8VZR8+md/QNzrkGcZlTNUeU0vDEFLyjpl1O1RplM6gyGjrQOqWnC1WDPPThl2Q3Z3tki6ARUOX2jSLEMK1cK/sBR5RhgE1A3sH7/G9cUpTZFjTdNigW8Z7kLItoRqFdaTOCnxtCYKIhZmzV9++JJ15xM2yX32dg9xrqAm5E8+/ojtnQfo/g5C1YTlmu3JfdLLj5jeLJkWS6bTiqXZIAR4niKzMeezhsa2DdqqMNS+awmb8YTNZgXllKYRfPjRcz76cgHNx7x/d4CpDUI3KKdwwiF9nyBMcEiEsjSlo8gdWkmUgGId41SO8sGYkOVMUhc11IIiy9je3aIsSt4e/xxVIsjtDQ0JsR/zxccfMdm5w9VshpAN2Tynvx7gFhsW9Zq408EUDdJZDJrStMUwYR2gKcuqNV4Z8DzdDt6m7Rs4a6irHC011tj2YKo8miZrX+F1SZluMDiMbYjDiPl6SVlUGGdbxo4MsIFiJdrbSXxLp7WVa2XtxmAaQxBEhCqg2xnQWGicZL1O+e6ffIdslZKuZlRZQVkXPPu0pK5qwugnS1R/Koa7koJAVJTTLwi7QwaDDunyjDpdUWQbtiY76OyKcnPOuNuF9Iok8rAYVJazFzfUlx/jNQ27icDGu8S6pp5+wdPPf8j6+pS6cfi9AR2vZqe7Q372l3TjAGYbpHR4tSOwBSbdYGRKV4UYH/RyyoM7E2oxJz39IXe3+zRVhV19hs58umIDyxU7SUF1/QRdl5x+vMAvi9a5KSS+yJk/voI6o6Mc+eWHeNKjqCVHe0PSix+Sf1FjK8v6+oqZyXjva1/HTzo0pkR3B7x4/hxMSRSFpFWJqGtc4OOXDS+ePubw0dcxszkyGDCdrVD6EkfApqpYz5aMjvZZ3ZygkhH98RbL6RV+EmPt7bAaBpTGsF6e4l+csNWDz55+wfbuLknsUWUZN5dX7B8dYw1kqw2r1TnbBzsMhiOcMyhhOb24pj/YJopipGeJwi5/+Rcfkm8yfvbr71CZAmsg1AFXFzekWcbR4TFR0kWLlhOuhOPLL8/oDyOCIOLw7j4P7x+jdIgpShbTa5zTWFOxXqxRSlBqiTOGmVXUwuPm8oSkPGNRVbx5t8O3fv4Ob7yxx3/7P/wuQdgliAK277zBtNjww9//t+zu79Hr9EFIJnt3GQz2iDsxwZs/wwd/8sdgM5T2KFYZm6wC4ahWGUr7XNc52zuTVmbharYmYw4OD1hlFVm64ukXLxgPh9w73CWIfTxvzGp2jcADd/vTQNOQxAkiiVG9Id04oj6pkDicgflySq+TYI1hs17RFTGirqiNYVNWzNYpT77YcPi+4uTslE26xDlD4EVcnZySiBkrs6ZenTE9m9HvKd7a6/Obv/eH/PEPXqDDLpV1qNuMvKc1jRA4z+KbVpjR2FcMm5YtKUyFH3qsb2YYKch9Rdjr4kmN8BTSGsqmBtF2L4xt2pWDrUkSRSQVZWa4e6fHYuHjRYbVUlNTUBaCr797zKrMMaViGG9x+skFzg/RPU06m+O0z2x6Q78/pq4KqjKhomGVromiiE21psoqUA1aSvB9tCewTrTrn8kQa0qSTkSQ+MgNCOfjyRrhDFL5WOPaB5T22mSSkvjaZ5Nv2rCDH7Bcr3DOMez36PZ6rFYpVrQr1LQocMYSRh2KakMUxCRJH6UL+uMRs5vZrQFLEScRZVpQ25r1siHuRHSSGM9XrNYLvFBTojGmIe4kt52Xv/nrp2K4SwGesvhossU5lbAE8wVBqAhGXSIJQhkiBcO9EWWZIZ1AhA3CVextDyhMQSMFYTdGqAib50hT0k9qdjr3mU5n+KGg39sh6fRRfoBBoG2DqUqU1PQDn+5kQNNYlCtwRYPnBWztbOMDs2xB0hkiOiHpMiXUNVUksLaiUTU4bSXHHAAAIABJREFUQSxANAbPKRoJhakoqxphazypKG2JyyzCDwjiLpuswBkf5/t0OzEHyQDfH/P5yysae8GWZzm7Ome+WhB7AYINICnrglCr1q8pFEkcoj0f15RsbY1pjG3XLaMdmk16mzzY0PEC8qokChKapsFhyb0QHfco5yfM//LfMbBzXt6s2T3eJ0m6KKG4uDpnsjMhCHzSTcrJyxe89fZbCK3AGoRUXJxds7O9TdLrU5Y1UgR8+9t/xrDXZ3I0wtRFu7LSitOTFyjtc3TnHtbQvoqigDrP+NEHHyIU9AcRnpZoA6askEbhex79QZ+mLvCUh1YS7d9KnFWA1grbGP7OL77DV++NefzFS/qBoq5yxt0+73/ta5TBmNFkyI9+8G0mkxE74z62Lok7PYaTHfyoQ9Ib4GmPZH/Ee//er/KDP/htmnyFa9qV2E0xY9Lp0InA8zV1bdqdeFWxWaeYvAI8oiCgF+9gmprLmzl5EtDrhPhRl9pJnBTEid/6Zm1DU5X0e702r35Le1RKMBgMcKZBQJs8UbcCbglfe+s+j5+vePtewqin2RvHvHzxOVjN9vEuD+/d5w9+87/k1/+TX+b49bc5jRz/7J//C+7+Z/+If/yr7/Fr33iXL558SeHgaplxvSiZTlcUphVT4Cy1abDCR+s2WeNcjZUhhYGaEOVqqDKMKalsjQxaIJz0Dc7kCB2irU8Yxcz+T+re5NfSLc3Pelbz9d9uTxPnxIn2tpFdVabTVKpcLgvbQiXMAHAJyRISSEh4xAxhiRH8AUhMGCNAIIFUgEBCLiNTZapUVVmVfXMzbx83mtM3u/3a1TH49r2VApG2MIP0lmIQO05EnGbvd631rt/7PLc3CB+YpCmLpsOajumopOtaHh0UuLChSKe4WvNgb0yzTug2gc8uX5HnY0pT0lYd5V6LtR13t3copelMT98ZUJJiXOKCIgiIogG0hglEkSR4gTEdiU+RQeCNo+86qnpoNxpnaNoGIQNlWbK8W9B0HQ5PXW0oyxEpOcF66mpFkeZ0tmd1tyBJU3Qy0GyjSCFDIE5z0nyC6Ua88847nF9fsdlUtPVmaNVEgtZ2dNaiZEy92aD0YHkaWEMRZTEiUQnb6govh7mX4QLl//3xK1HcO2P48NPnRERM9ucYr+lEhluvaeqOySTi7rPXpOkILRX13RWj/WOkq2m3FZ0I3Dt+RNVUGNvRVTWhW6HjjOnxPV5d3DCaHNIpyeXdFvPhB8yePgNriRNNZxyiq5lNZnz26iXZaEY+m7J4dUk5LTi/fMF8fI98ep+ffPwJq3WFc5aj48fcre84enKflz99zfEb7+Lanm/99b/Bzd0pH3/8CXlZYrqSbdNysH/AzfKM5fkND548ZD67z88++QnvfOmbtGbD2jju7j7j3sMDPv3JHyG15jdONKMip7EB32+x3UDxc/2WfDzGmI7Z/hwrerIkx4WWJM0YlWPs8iUmScD2ICMme/dIR2OUiknLiNXqBh8cWRozH0fYFxcoX+MVlJMhHeCtY7lYcXh4iIoUpu94/eolT994TBRFoCRd33K9WPPw0RskeYzUirvlmp/9xfd5+uQJo0JTbxu8HXylr1/fcO/oiDwv8CEQFzFxJHj+/kecn1/x1psPEMLtuCqOrm2Iooi7xZL53pQoTYYXd4BEq93YfoRUGqkCSieoSLB3f8pf3S+5O7vEScVZqzF5yvX1Cy7PP2Q2mdFuN6zdiqyYoJTGOoc3Pa+ef0IaZYhEsTeKeesr3+Di/BRbXeG8wXaBpqlJ9GDm8qbDuZT1piPpa4pJwXSSszefUxYFbVPT9wMO4bqtydIMVWsiDUUaAx0iBARhN5k84AZCGC5UTW2Idkf7NM2woUNFEcFbtGto+55mo/je//rf0f8v/y3WBpzIWHeeOBjq9Rnf/RPBw8dvMy40/9E/+PcoIoFYLjhJBPeTE8Z7c3Sa4pzi6tULJIpls6VqBc9fnWFkzrrqudo0XF3e0VrwoQQsHZ7eW9Ijz9FbJxzeP4bIIq2gXt9RrRvOP2q4Pr2kiHJcJwjS8NVHD2i2LXtHe8RRimtbRNjHe1je3hJFgqvzJcLFWCXYbFbMD2e0RFSrDqViqmZNXmQ4BwhF1/YkmUfpIedvncV7qOqK2CqyvCRKB1Sx1hrnA3VdoSNFYBgy01oiZYp1hul8hjMWrRVV1WOcwXuPMx6UwnhLkma0bQtSkMcxiYyZT6cURU5AcHF2jVKKD9//gNoY8jwnuAa7o3UmacZiuWA8mtJ2HUlQ9E1NNJpyfn5OWabDXYbtcEJyd3NHmv0LQIXsO8P2zuDMiu/84EdMi5xnf/PfRDSem8s74tEJbeUJaU6kI7qoRyc5hRyxXj7n9vaOJ9/4V+gXlwMmdex54/GMD/70e9SdQE0nSD2mVxJcwqI+ZzI6xrdrQOLLiCw1RPfukfeAhXh6n2kPIYo4Gt2nbyxyNEbdXZPnEVmZEk3mzMdz2m41EPqyMZOjEp/mPHzzbW4XNYnqkOMx8yhDK+jbDaNHJYf3T0jGJZMsosgU82TMTdMxG4/ZG+U0jx4ymUxoFp9S5Al+taHre6SIB86I7eiqiiiOwUDkJbGICFoTHGy7nsZJxvv3WN/egTWMxlNCnlGvFsyfnnCzOEO4wNS2LH70hzhTo+IxqTZkaYLpejbbivnePnGaUNc115dXHB4ekhc5SKjrmuW64unTN0jzIe51+vqCD99/zrN33iRNh5RFmiRcX9/gBDx6/JQoSUEIIg14x3f//HsUacK77z7ABXBmZxOSim3b471gfjBkzb0zODfQDwkSJeNhsMYZbAChNV5E9M3wRo2VR0cj/vAPfsjl2Sm3VeCtL3+JzbZGOEdSlGzXK6I4QRJotmscimSSsLm85P0f/Bmr2qGA2nj29ubcXLY4KTChJnEpQibcLVbEteXpk4KDccFkktNUK1y3ZTIagQ0YLcnzCVoprm+W6Cjm5mbNW4+m2N4QiQAyIKVCa40PDoKi6zriPNt5WC3ee4aouuPtx/f5xqMP+SvvHlBGBaNyzs3dmmrb8hc/fYXyHXcq8OFPP6PaXpMVh9yefsK27oYsdjoBtRlaJnqIPaZZTBRHJNMEpVMOxoK9o2Os8Tjrubu+JCpy+qB5dbbgv/79P+J3//1v8q2//ZuMsylCONphIovRWND7mvlDxeknOa++/ZrDw5xl4zhIj7iuzljf3JCP5vjWk+oeETu09GyXLXGs2NwtKLMRvbes7hb0waGbFKU1BIezAq1isjyj71tkgFhHaDmw8Ou6ITgITuBdwNgO4QLFeIqKI6QKu8FAv5OgBNzubmp/b4+ma3DODRCwumE8GnOxvUZoie0d4zyjLEdcXV0yLsfkWYo3lsXdku1mQ1mM2W5rlJb41uLsICzxXtD3DmcNXdfjip6ua0iiAmsc1bZGSElVbVneLpnPxtwuV2R5Tt/9C8CW6fuO7//gLxDCQSzJCRTSkuzNabqKSAdmR/eI84ymNZwcP2Td3TC7/wbN9Skbb9FSk4/mRN0WERTtxlDVC0b7R7j6jvzkKZvVLeNxiTo6RvlAolOs1BSRwzhDyEqm0ymbm0vc+ook1chizrbqiNQCtzpHK8mjt96gWm+QWCZHD1i9uObhySGRlpSRxvYdYjQe2NKrNZN7Ka2zCGspyoLtsqF3Fldvuf/gBOEsPpGIjSWIgJcgdUZ9/QIlJC44lGQ4EqsIoRIibfBBQpySqghcQ1ffEnpNmWZoFTEf5xA8fqSh3TCajXHBDK5RFYEF6Q39zcdkRwesb9bkqRzGm01D1/fsH+6TZAmbTcXLl69549GTHUdccLdY4gM8efqEOB0K+/vvfcR2VfHVZ4/xvsfZ4c13dnHOeDrn4PCYQEDHEOmYs1cXfPzRpzx8fMzebITre4IdJii1SkmUoqkNbdURG4cXFvA01ZZqWzGZTIes8G5kXqcjvAtESjHbO6SrKzbLBd5bHu4VfPXxr/M//P5PCECaZUOx6g3T6ZTRaITtDeV4xt7RY6SOUKnm7K7CbJc8fnjIg4MnrFe3qOgRfdNhN9f0NrC8XCKQvPvWhMOpwnRbzs83dMaRJQllmjAZj1hvatIkxbuBnLnZ1qzWC8okcDAphtiiUCDUjgUfQEomk6F1FIKj73qsrUl1QkDhveHf/ju/RVWtEKGkGGekucIaz0UFI1o+efEp3tb8o9/7hxRlxpiWx2++QTKfAzHomCAVIAeM8w4kpoRCCUUsI3wQICU+sqSZwHnLbDqhsmv+wX/yt/l3/+7vYjH07hVeWlTYx8sSYzsSKciKnOxrx2y2nzL+RyU3t1tetq9wbY/Vht51pHoM3jMpc6TS1E2HzBKMUPRtP6jukMR5glYKpSDWJY3rcN4SRdEQX3RDGzQATdN88bV4G1Be4lyPCop2WzGeTfC2RylFkua0bTdMbfcO3zvWyyVpmlD1luAEXdsRzyPKMmO9WfH0wQNMP5BaizTFdB118ERJTBzFjMvdya1rSPIUJaBptkgtUUKhpabe1FgPzljSJKOpO2znmO7HLO8WHB3tYboWZweRiwyK8/OrX1pXfyWKuxCCKFUoC956QjDcPf8ZJ+98nTQfRBEmSbHdhvXFa974xm+zeHWKSjKyUUEaSerNHaO9+6xtzWQ0pd+uKfZm7B8d8frjO/IiY9TnyDhBYxCmJk4TFqcvmTw5ASmYRBl1s6JvDUXac3t5xrvfepNsZHn98SV921COx8goRqcZOkqQriGKEmy7pV+vsbMZ1c2C+YM5RRHTbBUoiauuEb1icXHNm8++Tm0bvA3E+d4gYtAJzt6Bhur8U9JxytmLS5L9OciUvuuII42WESI4hIgpJzMmh/cAgSEgQo+pVqyWHdLVxErgek8wntfvN8NEoumIhGS1XBALxTpAmB6wikZE85RKerquQQvH4b09lNIsl2uur254cP8BQgm0gsurCybTQ+a7Pnxwhu9896eU5Zg33nqE6bcoBaZtubq65eD+fYrZDI8niTQBwXe+8xNwjmfvPkEI6JuOYHu0ligRhl5221GUOflkhFYx3g++VCFT4mSEkgLvLC4YnLO0fQsIggv0zuG7Dmd6UPDbv36fj15f0/Qt2iuatiLe7eyq7QapI6IkRaiI3nRksWKyd8S/8bt/jz/9/f+Je3v7FGXGw7e+xuGjL2Oc4/Llp3z7T34frl8xn5Z423F+djUUiiJnsW6YTvd4efqa8XjEfH+P1XJJGknKIqM3WyId8+JiTRInTCOFlZqI4S4KBkeq2xWqEIbJ0zhKMb0B25Gn0TCAJDP6bUesI0KUgHZMRyUH0z2skrTNLdJ0pF6Tj0oCDOLt4FFC4sOQ4cZZpBQDHkEIlB5ew1JAUJIoRLQiIYkCUji+/FvH/Nq/9Da1v6Hxrwl+BUKg5QVVf49IpSDvEEAkNW9//U2+9Fsf8/HHV9R+jXTD1ylkxrZp0C7Q9W4YfMLjWksW5SA8sRj8QjoE2rojK1KyLGWzasnyDOsMcZQQKU3bddRtRRzHCKlIs5SmrulMh1QR1jUop7Ae8APga93WdHUFwQ8WOBmo6y1FkdN2PUkyDG5FsSaWEVGsuH+4z/e//x4qS0BC29TE2R59Nwi49/Kc9y6uqW1LEIK6blBJhO8tWE+RDljgarMeBOBKUOQj2tWGutri3bCrV0qRFRlt21Nva5T45eX7V6K4A2gVYa3BqoDRjlDdUH/2A1zniN6ZU28uyIo9tPdo5ZgXc4J1jOYFo4MpWZYMYgLn8X1F5B1aROTFjKN33sEhhqNQmpIfP6ZXgXicUDblkA5wil57OuuYP7rPbDTi+vw5QQhM0zCZHiC9o9pcEwSoSKHjBJwgy2fcbh12sWbyzTmby5pISarlBtf0eALLmzvK2T5JMUaNcq7ef8lkOsL2PSLLqa8WWNsTkaNjhfOSd776m9R3V4RgaaoVRkSUhcBj2W4bkBdkZUbVVZhegi5w9CQS+t6RKkGoG3xUsFlXxCqitR4tAsb3uDAo8ayV1PWAQzWmZxQks6MZURxxc33Htmo4uneMtT1CJCyWKyaTMYdH+wgdU9cV7/3o5zw4OSLLC0LoUQiuL29QUcrjd95C6fiL6NvFq0s+e37G/tGM/b0SZx1aawQCu0MzGGN58GQf4zwyJEgJUgRkEhGIUInG2wi8RcoUgiA4h1IaHQ39d+sNKgSef7BFeIFyjuWi4jf/5b/FdDRmub7DtDWxjkkiTZRmpFmGDwPRMIojkqwgzGY8eecZj998m/2jJ8zmB1gtEDLw4I0n3H/jGZ989AM+++4/4fmLT2ndGW89fsw9FRFpTdc1NO2Gq9sl8ekNaRJxuD9nPB3hxJo4idBEnJ5fcTC7Tx8cQg76QBiy/vyC4/RzLZ4LDslOZr1LdHilkUoNcnCtGI0K9u5NkVrR1gmjYkSRpMTJgK9QUv2lKYq/pEpKOZAcYfivxW5xgQEvHOtAFJeE3PDkaw+pwwbjz7BuhZAG7zzBX2FNhA6OLrxEqzGxvEdRFPy1f+0r/OPf+4TN7XCSMaZlvdqSF8PJS6mItEjZNgZrPFJAnGiEAWMMNliiOKXvLMlBhtbV8F6SoKNBMi6lHAgLIRDriKYZ/AK7VRMnJEoOmO5UC1xvEM4TCcVytSQdTQgCjHNUTUMUa7QQgEYCUaJ5OD7m4599yGq9JfJDPLLMEowzWGMoDFzfVpgANoD1bpCbO0mcJARvcdbhfSBLc1zXEyeaTEKrA8Jb0kiSJQmddFTbCqU9vmmZTPJfXlP/f63Q/18fgR2CDoQF3zq2tUFkNdXdiu7991BJRjo63HGcO6yKub06xwZPW1VUbUseD6mTTbXFVlskCus9xnSIXXFZn56y9+iEzeU5t13N5YvPOPzmPtu2YdZbTGtYXH+KOLpPIMGsN7i6ptksCEi63jCJomHwyrQIowb4kkh4+5tfJUKz2d7yo+/8OZnQXGzWHGjNtJiw3TaoKIIoIkkyijRiu6xQ5YjQbbl374iuCYwnEdvbFZPphK5aYvuKVKVEaYnUguAsRZayursiS2Nuq4b3PzjlyTtfI5lOMNs1Rmi+8Ve+xY9+/l1m2SGuXfLg/mPOfvBtbl6+4Ev3n+Kcx9iW93/6CQqw1iBF4OnRGP3kDc7OLghecO/eIc45goDlesnBwT28F2gluLg85/XLS9548gghAoIeZwPnpxfM9/YY7+0RxFC4g7F874fvITy8+eYRQnq89YOOTUv63vH67ILZfE6pB8VbmqYY2xICfPL8Ocf3j4jjaLhsdBZne9jhUgUDhc9698XC5F0/JD1CQEWKoDIOjh8xTUtmx8d4awjGoaXA4YmyjKQoSNJ853/cUhQlf+13/i5JHDEui2Ga10uMcYTMcPLkAZaOb//vv0dwit5YXp5fILXk+P4xAU+cFLx8dY1xFXE86PI+O7+k6wwnx8fEStF3EXXTEUUar+OdMG8o5gMueHifiJ2qTwr5BT1SiGH4CMFgbFISpCTSAh0pJuOcIp0wKkpEkCi5y87/QkEf+PF88e/hA0KFnfBjWFCGEGQgOIH1PdOHGT5bsuqv6f0niODB+Z2R29HWe0T5DW3zffL0IWm0IZPHPHlwzOhQYDYZOI9WCXGRo+OY3jZINXBXlJZfrGvOWzR6yKELSSIlXdsTRyliF+Hs2wadFVgv6OoaYx1aKpy0WGuHjVOAar0gyjICPVFQdI0jK4thbiDNqJOELMuJ05SlNcRxirMeyQBh22w3RIlCWkfb9pgwTFSXRYYg0HVrijwlEYFF0w0IZw/eBoILpHFG33UIH/B4tJKYvqdttkzzOevVCqck2+2W6XRKtd3Q9oGTB0esF4Zot4D9ssevRHFXSvJXv/ou53e3XF8tkWZgJhjb44QgtGuqbkl8anny6Et0dc3h0ydc/fznzA9m1Eikh/lkxnVjycqYZV1z//FjjNni10smj4+QsaBqbzg4fLCLUu1hVyv6EEjLlNF4zPxgznQ8xoeOvePHFOOUYj7CXhqkypiGfSajCSZp6NqKvjWoOCbPIh4++wrBVZyffkguYqK9GQf+Pso7sukEXzX02y1llJOkGt+2jGdjgmBAhCrBlp6iKHj+8zP25jOqzZI0M1hrhsldkaNVTBIrNpsG4TyPHr7L6fmCdJwxPzji9eKWZ7/+DYppweOHT6iXDQcP36J6/VO2Fx9ybzpHiXgQQeAo48AoKdlULVobikTy+tU5aTlhb2+MVJa2M/TG8/jJ/cHh6QXv/+wTuq7njSf3AU8UDQM611d33D95TFoWBN+RJ5KrqwXvv/+c46P73DseDQtj2O2ypeL8/HLYrT96+AXzXO3cor0QIBRvP3sGOMJusCZIPcgjhq0nUg0FUUiB1JJ79x8ipOCTzd0gmPCC1iUUeYbWCXGs0VIMp70dyFYnCWlWAoKuqkBBWZREAiIhUAHwgb6pETLCB0nwkh/+k/8N125YrQwH98fkccKmqlm9/yHz+YTZdEpbN1zerJnuTemev2ZTtxR5ibFXjMqUOIqxIUd5jwpuaIN4jxeegQ05FFgpwPqA1ArPjiBJQIow+GylIniPVIo8lkSxIpEZfdtQFCneBIQchCA+DBgGISTO2i8okGG3YBIGGYeUEu/cIM35fNGJHNl9y9X2ezh/Sdue4XuL9y1ZMaLrc9z2iDL6Mb1dI81zGndKl36DUr7L/hszFp9conWE8Y5gwhDzU4q+7/E+EJRHSIn3PZPplPVNDVZAECSpxTvLer2m7TuKIsH2ZmDipDFSCCI9sNJ7Y+i6ljItCVoxmUzQUhCUIs8zaFpkCAQ/7K7LsmS9WTGbjZlMx8Q6RiLoGoOnBwGRlnSbGq8147Kk846m6Ui1pu8N82yEbQ2d9WipCX1LlEaQSapNRZIlqFjjOoMMASUsCsHybonMcpRUVN2WuulBDjTOzhhG0zl1VXNzc/NL6+qvRHEXUjK9f0zIU25XFa2t8cKQ5XvI3lOWEaoD1a5or98n3XuI0gnTvRHB1yjhqK7P4dFj8mmOlAq5FEidkuc52dEAETs8GjHPOib7kk9+vqJgjj55yGw6p+p6+u2S6bjE9IaXL8+Yjh6QZzFxlLCUKaNyRO0FeZJilaBZ3yCRKDngWU/295idPOT5e98dYlZxoEgSusWKtMjY+jWpDoS+Zm8+w20XGGsROiXSEd44Egmnn32CVpLeVdRVxf4oR8QJAoUzBq31TqcWMNbStSumec6jByeYEEh1QNLTr1vme4cU8prbD/4Yf3NFKQIyiuldQDBIIqRQu10cu8udltGTA4pJThxpqqpC6YT92QRQOGt4771Pmc3m7O3PMLYjzwrOz86I4ozHT58QaU2QPWlU8tH7n3B7e8u77z4hTSTGWLROidQAxLq6vmM2m5Hv5yg9FOvNeo3SgdnhlPr2AlwHTiCjQUCexAlCyC+mN5FqmOAU4gvxhHM9WickSQbBs23hBz//jHfSI9589ytDW0IEnO9QUhEnMSqKUcGQRxFeDBrCpl5j2y2+mNKbDhEsOkrougapI168+JCr189JkpIgtrx4dcbBbA+tthR5QbxpyNOUvb0xTW/ZbLZUzZD9Xpxe0LcNe9OnEFrabkQSxwRrkX6YTpXCDb2RnSVpoEV+8Vs8HoEiBLd7XcghaQPEu5fKoG2L0DrC4Rlkv2K3ww/DJKyzO2/fcCJw1iIUO3qkR4nd7l4A0qOinEbdUq+fg9lguy2bVUukA13dU21jJuULmu0pSiW03YIgNd58iI5zgpEIpQhCoYUEN/gM2qahKPIdakEQggVhSTPNVnq62uE8ZKYD7+m6ijhJBgps39O0DZESKDG0M3prSLKUzvSURYHTEbLtGQnHbdtCOYa2232fMnql2G5q2qbFTTLiOML3hjjWNG2PFJJYR/Sb7dAjzzP2kpjPzs4ICvKopExTpLEsty02yhDBEGmNVJoiy+huDVlW0JiWtEhpNxV5kiGdJ6QJIdLkSTakwpTE2B4pFHVVsfFb4jglzrJfWld/JYo7kef64AN8AidpTTIq2Dt8zHxvyuojA7VHbQTpyRSjt9SHH7NMPZfJS07KMaN7c6I0JU0KlqtbpvkEW47wQjApZ9x2C/ZGJUE1mBBQpiaPBcauKfcjVKHZOzkm+EA0HXHx8x9T5iVZGqGjFGM31IsFD08OyUnJtETKnHpzR9tapHE8efaMRDrmozFxnJBlGd5LkiwnPxyBcbTNBmMa2tUNZT6hzzoWr0+ZPZwgAnR1S5mXXNy2JDqjtop3v/otRPOSYnyH9hJrO7y3WOPonKP3Hm0aCBBHI7ypKYrpcOs+K1m9/imbj36CvX1Fnu0hJhJbTgbrizN4OzhDvfCMJhmJ1oPYQEu861kuWybTfZI0J2B4/foVVxdrHjx8QFYMOe1q63h+8Sn7+8ccHR/R9R1aC9bLmh9/8B7jyZQvf/UdnO0J3pHGKT4EXr14iRSKRw8fYZ1FR2ooNg4ipbFuIBNa77i7uR4KuxAIoXYtCbn7GobLVD4XVuy4485B7wTr6zvuP9jnJz97wYuLG/auznnz3XeRQdB3HXgzFDvbkaQJl3e3nJqa+w+f4IOgkZo8zTFhTaQT4igjeEvTthjjOf/slKfvfh2VxHz3j/+Qu6ue04sFRZmwrYcjuY415agkijWFjLhdLzHeMCoKkliD6ziYDwLlprWkesg/CwJC7mxM7CQau4aNQqCUHFqaUu++LwoAJSMgEEfDkJmMI7RUKD3MB4QdTtg5N0i2d7wT780QMRUSKQLOO5QfiPLW9kj1lyclQqDaLNj6W8xmhW0NwYDVgcXZmCyPaKIf0HSWtttQpAqhJEkZCJMp66sKqTVKaVxncWbYvZve0emepu7Ji4y6aZjNE7zvUJHAeU/fDt9/aQxtXROlU7xpmR0cYrqhtbVqG8azCaENpGXB3WpFXdVEoxFRpBF1RRnpHbxJffZkAAAgAElEQVRNII1F6iGGmucZvTXoOCFWKcvt7XAyigSbRUUsIbSWuuuJyoyRzkhUzLLeYNOM0XREt6loQiDKYmIiRqMxdV3T1s2AJkhT2r4ljmPILIVM2NQNi82aYlySJQnWGUxnmEzLIcPf12TFiKraDHMmv+TxK1HcVaJ4/fFnPH4ncHjfk4/e4qZasK4/ZvS4ot940nBMl23YugVd3bB8+ZzFS0P+7jfInp4wD3ssuiWJSiBK0ElGvVoh8GzvXjAaa8rckObvYrgjObI0+s+42JzyJP632B89YXtVUY4yzN2S8eEDbi9fMT15RBkndLYjjSP69QaXZVjnyEYFgR7vO7K0wPnApEgQypPHGU5puN2SRCmyCIgLy3SyT1OtSUYzxvfucfriY/q6YjqL2FYNddfipCRYRzae4qoVdtGiAxg7cLkFg0Hde0E+GpGOZuw/yInKlPXrU1SwtM0d/k5z+cM/oUgSpI7pgqFnMLlEO/lypBUYT1GUJDpiuVmj4ojeQbOuOLp/QlYWBCzvv/cC5wVPn57gfU+sMxaLJZvliuOTh4xnBd4OCOIP3/+E5WLFo4fHJLEmuB5wSBlxc31NVVXM53tkWYFUA6ZWoPHOcHV1Sb217B8eIKUkL0vKyZzJdIz3FqRAhEBwDm9bvOsRaISOB8kEkqF5EPBC8sPzT+iN44NPblAi8OFHP+edLz2jyAuazYpEC7x1REmM7WOEGy5i66oCqYmjmJ6hRWJ7S8gDbT9Mlzpvefr227jHj1jdXVDXK0ZlhI41y21L13Yo3WLsHULcEicJ1gciFXOzWFFttqRin0+ft2h/yOzJGzgExg2LmoBBt8fn+ruhReOs3cmrw4AIVgoZDQM5AknQKTJYpAQVPFEc4zZuuBcRn2OGBVLsFgckwRokAe8+PyW4gRTpLIGAUtDWzTAdi0RY2L5oqKc1Zm1xlUcHzc11RFFOSfLXrG87QOAs+CwQRRavO4yA1WVDALxzWDsMbCEFSmq8FXjvMZ0jiQrapkcJi0fj6Ih0TNcbyjgheEee59xeLMjvHSPXKzIkbjoGOVBP4zglSfKhbTIaQGmt9Sg3YHeN0GANyvXEEoySO8SxxrtAnOW41R3kKXGagTEoNHVf805WsqqGDU0ca7z3+LaHSJHlOTJWbNY1Gku13RIn0W6grRoSREFwb/8ed+stt9sNcRqhgSRNiCOJUwrjespyhA0Jo7zEdY6u639pXZX/tMIrhPgvhRBXQoif/sJz/6kQ4lQI8cPdr7/zC3/2HwshPhZCfCCE+J1/luKelxlvPdsnSwzFOLBpzgj9J1BfEAhkI0utznl+/gGmH+Jcwi5RWctP3v9j1slzRtOEWCiKccH29hKpY3SUYYsV7/xWRnHwJ6joR3z6/Ie8Pv02p83/yOnVH7JdfYZZbwhqzKZeo3NNNC5Iy4JydkCnFF7nFOMxXdeyvF2wrmt6Z2gWK9LxCGcDtTf09QZft0RpjPEBEo1IJBoFwRGcJ84K8rKkmI7J8gy8ZzYuKbIR+WROUY45Oj7h7WfPePzgmJPDA1QkwQW63tD3FhcCzvR0dUXXGWzVcO/4PkfHe4yLnHISweqMq+/+MbmzREISgqBuW+qugyjB4wnWkMZDXni5XlH1LaumpnUG6z1HR0fESYrzlp/+9FOkjjk5mUPo0Urx6uVrnPM8fuPJMMAkE1brJX/x59/D9nZow6SgBGgV8NZwcXaB8IJHDx6Q5QlKS1Ss0Kmkrte8+OwSrfd499e+QVrkQ6vA9khvuLm6ghB2vVE/9J9lhFKaIC0Bg8Ag6Al0+DCQDKMIXl5sOLte4IPj6PAYgcIaw6jI6OsKaS2YDmxPpIai17cdwQesGyTT3nsQAdsPeXNrzNC39oHNasG3/49/SB7LYYbgc5NRpHl9ecWrq2vW2y2xjhA+0LfdDhY2kCyrumdd1Xzw0cecnV8RZEKUDMmR4P3ustoCdijKSg2LnBS7acnhc83LMV5o4nxM7zzGWrzf9dfdMPXr3KDd+zzIENzQc7++ud21gXYF1w2nh7Br1/iBE4GWg8mKIDFnc7aXgnoB7SpidS3Q7hClL2irhq4C2wjwAmMcHo8UKd/7gzXdYlik+rrFi8FXgNhZo5wnjWOsseAF9caxuGvoO0GaFJSjEaCI0xHGO0a7Abo0TwlKkQpNORrtJO6Kvm5Io+G1EmmNkBl90Ii2JfQdtq6xztFt7mirNanSeOtY7WYkklgPoQPTk+UJzXJJ1VTszeYcTO6x2BiEUKRacm88xzQtcVlSNw13dwvUrrWitERGEbGOkCKQCMnTo4d0neX1xQVSK4w1VJuKs1enxFGEsxaQeC8IFrarLc548qT4pXX1n2Xn/l8B/wXw3/zfnv/PQwj/2S8+IYT4MvD3gK8A94F/LIR4J4TwS6nyXdvQ9JZpDmcfBoxYUk5jSPdwcYxoX6B7wXziiVPHZgvaJ/jeUCpBffcTXk+2uIvH7I2/AWXAKs+L939AOv4NzrsF22vD4eNA8MeMRMLDyRybv4eXN8joluXdFXdnZ4ymI65enlKUhyyqimRzi99IEqU4v75js9kwPz6hahbUTUMK1MstxaHnxz//ERfXp8yLEbd3LeNxTpmO6JqafDpBao3MU6rLVxzzlL42HJ88gGBI0hlH5f6g24sTsrigbyt81ZLmOVJohB8kHFIoetfhbY+3DtNuqU8/4Tf+1t+kPR7T3r7ErK7IspyNj+hDIMlL2u2W+WRKmo/ovUOKQNe3jPIYaQTT2ZjGdiSpYDIZE0Wazbris5fX7B/MSLMhqVNXHW1nmO3vM5nOML0lThUffvg+i+uKp08fEsUCISxJnBK85+5muF+Y7U1JkmynJBuIoN46Xr6+JIoK3vrSl4nioQXQ94Z2t2PVcYxMFUoPmW6hIIjh9CJlggopLoCSGhAoLbm4viIrcqIo4oMPz+jMUNS+9rWvs39wjLMdvquYTPfZLG6G3DEBHaVEQuJNT7m3D0IP4otfwPRqJYlijQsB7zTX5xecfvYZxrX0BhpryfMUZw3B9xgjKYs5SnjSWGNtQ5mmGCOo2pr9yWSQYrjAYrlmOhmRqXgYWFHD8I0IYpe6CF9cfH6uDQwh0PY965tr7j94TL3ZYu2wIHnnkASUBHa5dYnCuaF3L8IgDylGJdZaIm0hONIsw3hNFCds12u8tYMiTnoCjmAdE3Wf1y9P2LoPobcIVzCeWEzb4yzoVODlMPXpnCD0CnGZ8eL/rDHtEBOelWNW2w1CCoTUxHGEEIpsVGI2W5wTSDSjbIR3gBxEJtPRlCwr8aHH9i3BOWKlidMUJ0EZR28NuOHElaQxVd/shuhyFsaimpaxcAgstgsEYWiDBN8yH+dU1mCEJ3QWkaYkPqBCwGpJOip48403WSxXxFqw8pDphMgbquCgGxZc03ak0bCJQiuUEMRpTLCGbzz7GsvNlufXF8h4uCC3nSFP4yGOKtSwWUDgrBvuPXC0Xf3Pz5YJIfyREOLJP+3jdo9/HfjvQwgd8FwI8THwG8Cf/bK/1Dc91coy30vBt5zcl+TTmNttx+oamktPjGLdehafCR59SbH3qGAyf4qpzzg6GbN38g52I7h4+X2yWcz26pbpo4f028DB8W+jxAX9OmVyGLG9uuPw4FucXU5JkhKXTjh4Ouc5HVkSgRLsHT7EyXNUVXF+cc6Dt95hurfP+u4HiDxipEvuXjVEypEVmjzOyCZTFufn7D+cYa6bofASmGURWmVY0yO8wZqe25trRpMx66rmXpRxt1mSlYLeVExGE27ubpBdy5OHT7i+9EgfCMIhwm5HKAV5nmC7CpmOscGxPD3l/Pt/Sqi2pFmMT2ISBIt+GLOvt1v2ZvtEcT4Iuf1gBZKRJFEJ3tthmjKPiHTM67NrFsstDx+d7ABlkrpZ4cywqxeRxAdP02z54IMLsnzEu88eIgEpB+DRdluxvLtlNN5jMp/jGC6IlJJUVc1qsaFqLI/eeIPZwZiuN0P0zQeiSJMkMXYLznpG8/Egc2aXItm1D4IQIIfLYKF2l8NS8uD4MUILXgvN66srXLDUbY2IJAFDoEPI4USVFzlVtaFersjSgf0RCfDGkBTZkNsOEJDYXSJHeIdUGnzg5K1nHL7xFa4vXpIEz4NJycFsxns//gFqNMEiOH11TjUpEXK4vNzUht5LpLPcmxS74TSN0prttiKflwThh1CTlOCHE4VkiAUKFErI3c8wItYJW2+oVlfUreHg6B5N3YNj2KGLQd0XrEdEA4FzgJMNxXIynRFCwLQV4FgvV8TZlJfnl/RNw4PiACH8Fwx6giGi5IBvcnV+i5B3ZIVgvWqQjWc0UUgd8Ax1KIoFyozh4m3E7RV1M8wYVG27i3Jq0jSj7TriNEFqjY4jgg3EcUwap9RNM3Ds5WC16roGEQJ9Mwz5VOs1eTFme3PKJC5oqoYsyYgTSdd2FGVJ2/bEowgnAl2AsLohk45F74gjwXg85e7ygspsefPp21xs12RJjrIGIcGbDu8c43JCmZdcr1coNcwizEYTmnaLnkyxPgyvrSzfyejFzj2siLXmm8++wsXijvdfvcBbN7SBgkdHg2i72tZku+SWNZbgauIoRUUaJwJo8UuL8T9Pz/0/EEL8O8B3gf8whLAAToBv/8LHvN499/94CCH+PvD3AeJCc/M6oiiGT3i16ehFS6kjlo1ieRUY7wU2F4JmI6gXituyY3H9Me12zfs/WjJ5tOSdB/eYPXhGtTxD0WHqBeerhtHJ36AoS0K/xZmMZDIb+ofLO3SRgw60rWV6MkfeK9h/9wgpetaXl4x/7avIi0uMC9jekOT5oCrrA+P9Aza3C8xyS+96MpUQ4gyCYLO8YTot8cFgeo83Y0bTkvXdHXExYXywx4sff590lGF6R6wzsIJIJ2hissmU0+/+GV999hXSsgDh8bZD6xhnDWmekWcJ3nUEJWjPr/jZH/zPCFoa50l9oPEtQgoSIUiLgru7Fc47oiQdLiCdJYtjnG/QUUpvHEUxwvQVnz5/SV5kPH56H0FASc3t1S15mTAqc5x3ZHHK6dklF2c3PDi5x2yvwPYdaZbjnOTs9BQlYb53SJLEeOGIpERLwenrK27uljx94wkP356jopi+7cE5ZBwjIk0UCaQcYnnVdoPpO6QazEIwHN2NMTjXE0kFYkhffB6vVELi9RCra62nagxaF1TbBhyYrgXXE3qHdIEkTqnrjk1V4wVMIk1bbQexQ5CEMEC9pAxDGiqKhktPEdBa8td/519le32F6St+9MPv8PHHHxFsh8LQdA4PrDZbiixlXCRUdUuwA0dHSU+sBId7e8RFiXMtHoVSMUJ4XBgww967YffO53ean/fQJX3XMRnnBGGY7I1wwSGE2Alkdqmi3QzP5zn23QTTbmc9/HyUDHgBrq24vLylMgEhBwuRVJ8bpBQwTAYfju5xF3+d6/VPicsWKz1dF5gnA789IJBekfQHhOWXiVcPSZI1yECaphBLpIvouv+Lujf9sTS77/s+Z3nWu9ba1Xv39MxwOOIqUmIkShRjx6adBZIcS4oSIQYMAXkR+G9IAsN5FyMbEFuBjSxekryIJUFyYhtmFFmSKVLkiDOc4aw9vdZedddnPVtenNs9EmBRQQIB1AN0V9Wtqttdt87zO7/z/X0Xg+h6kiSh7zqyNEOh0JnA9Aad5kyLMV3bUrUtvelRKTTrlsl4Apuf1XqP7Dp8USI3tNnVekVZ5IQQw1mM6Wltx3Qw5PLwMbtbe/TGUQiLCI6AwKcpy+UlA6FYXl6yvzNhfXJOVy9RAe7dfpGq7tEyQyhNoSHXgrXP6L1HIEizDI+gXSxJNvmqQQS+8AOf4snJCfdPjlAe2q4nzXP6viVPU/rO4D20bRWFV8TRSIQjIdEZ1fpPJonpvwP+OhG1++vAfwH8VZ5J2v7w9a88O4QQfgn4JYB8kgbfeY7esZQ7irNjx8VTxWhiGO9bJrsJsxOLsYp7n9rCmSXVyZKtwZAPPpCcn65Yn9S4yxVf3LrJYHwFay5o1PtIn6ObH2FRHaJp6FYlPRc0a89o7x6IQPHyFLfV8eLdVzChZ/+HbuHPo0GVTBIWixk3ByWrZkXoA9ZYZocPGV8/4PRoxu4rH6NftTTFkN51ODem6dcEkTA/fYLe36ewHV4nFKMdZg8foYohk719VssV+WhMmmeUOmO9rnBBYNc1yLAJ2h3ipY0MEaWw1pKmijRN8daiQ8B0C4xJSZJoT6CKBC9ip4lQ9FiSLKFa1+TOIaXGOEvbRfOxVMaF5WxLvV7z4t4O08mQREpW6zVdZ9m5cgDEwWgIkm//3rsMJyUvvniNREmSDXyyWiyZzVdsT7dJM4l1BqEEhU45PV/w6PEDdvb2+NwPfw6/sVx2XQNSkySRBnh6coxOoNjdJtGKYjLlytUbsbA/w9y93TgnugjvhI+GhZ5YgLROefrwMdPJmvJ4xUsv3+X2retY01OvG4JpSHUSNxXh2JpO6YxFbVgUIjhMvSLNB5FqGQy261FaP+eYSySp8AySFDcYMLs8pjo7x1cLnOupu5jes701BK9xQeCtYpSXdK5lvjzj7XdahvoGN/ZH7O9cZbz9AudnxyybhqlSJHg6AdJ7AnEthODRkniaERIpA34j2ZdC4W0Xlb0xmxAXBDJ4vBZ4KRDW4k2HVBqFIvg+BmiLqHItipy27SiGJeOdHax3aBQ+bAavQeFwZAh2iy2u732JTs5Z2UNCUlIKS4ZGhy0G/gXS/g4y2SIMGvJCo1RBmkiElOSDIaenFxRFSdcb4l6twDZopdm+cZ1usWa8O2C9viTLFa4VFOmAta/ouw7bdQgsKlF0FtKmJktTKgfSC5QODJKCqmlx1ZJkNEDJBHN5yqptIaTx67oWZxzLao6pOm5e2SV0axK9gwZa69jd26ccFBzOV0ghyDRs5wn1oqLLk5gABRxcvcrR4Tk+gA2WsSz48c/8EPcfH/H24w9JiwLvDRvEBi3i/Q0qxu+5nkSWKAmT8YTz0zOE9BSJwtR/AsZhIYSTZ+8LIf574Nc2Hz4Bbv6BL70BHP7xT+jIS8VgMiUda3pZ4bqKdqEoU0gyT98EUqkISKTIsbYHk6KEZfuq4votwWDScvjeu5SMqJsTLs6P2JtsMz99g3S0i+scKrGEVpOUjna9xvqGtHXoSnL8ziMme7d5/OBb7IcfQpUF3eUJuAWma6iamp2dnHZ9ybrqmNiCLGuoVktC52PQglJ4C+2qIktydDHAi8hICTYQbEt1foZfr8iLjGqxgCKhnjcwchwePqQcvsp8dsGy7lh5R1aUdE2HUEkcnm3YBd7H9CahJH3wXCxXZFmB8xbbBpqmQeuMuqkRBHpjMe2abSmxNsp2AoKqqrC9IRBwtichwgYKwfnJJcWw5ODaLsZbFJqTwzXz2QlXDsaMJ5O4kHRclJfnF6RJzpXdPYRwJDoBCdZ73n3zIVk54tVPfoIsFbhugTUdzgeGwylSp1xeRGx+PJ7EwaixBC8QPvD22+9z88YVxKabF88Hqx6hkjhslQIhFVIqnAx4FVBZRu8cdVvz2u/+FlvDjM989vP89m9+lcPHj/mLf+4rjIYlaaoRwjMqy2iexSZazVqCs0idxqEqceAoE2LLGwIJEpEkmCxla2uHVz75ad59/TXmhw/xnpgR7G3MzMwzkjxHpkN058mUwrYds8s5rXG4INBpzsG1m3zw/ju0nSFPIGyKNAScswhkpCUSYrF/LmiK5lqeuIkHH6mywbkIZRExdu8cng6VxBkIz17TZ10+grwsUDKjrWqSLHnu0xP/hXiSCTpgGwcWrNeMi3v4/jaid6A0gQE1A3rpCZwjrUEimU5HmLYh1QqCxxlD20QowgYoy5K2aUErlnWDqyv8pYgpSL2LQjyh6PsOhCfXnrrpCLqnzwaslqdc2b3Fh+dnpGVKMJbJJKVbnROMYpKOWTRLUpHRmh5kiu8NIg/YIAhGYKTn9OyUg4MrpEn6PE95MBiyWK3x3lOvluRC0hhHG8A5j/KCrEgxxkCwFGWBqdf82Gd/mOOzU9558AGNj2shTRO0jF44zhq0jpmrwYGSgUQ7nBM0XYvTirq3FHm+EZT90df/p+IuhLgaQjjafPjTwDMmza8C/0AI8TeJA9WXgK//cc+XJAnTSYmxsDxusLZj51pCng0xbYO2OWXaoZRjfrJiWGjG21v42lGWiu3rA7audNizHeZHlrOzFa2r0PmAy4sBefcuavQhtg/I9AHzVYK+N6bJv8NwdJMX713l+k5Af/pH+PpvfJWivU8++BwqS+j6jmp9yfzskOHVfar+gts7+yzqHbquw4YWv6xIJtssD0+ZXr9GKwJd1XJxcczRw8eIGzepm565daSLBjsYcnJ2iUglHYLzi0uGwxFCKEzXkucZTdOifRSNDNMc23QElSASFV1AhNwkp0tUCEwGQ7YnUwSCro9mW9Z5BoMBSilkADWSOAdpOSBU9aZjiAukHEoQKU0tKaSkqS0nJyfcvH2TNM/xAdqq5fT4EonkxZeuEXyHFgFEwuJyhrUtk/GINM1jV6klCDh8OsM4yd2XX2AwyjBtw3I2o8gShEhQOuX8co6zgen2LpO8oO0afFuj06g6dUFw/fr1SN2UgojksuF+R0FWCM/ogjEtSFqPVoJEZrgenDFsDQZ8+NZ3aNcruqri0cOn/M7v/C4//qUvAHlkMWBjwRGRZuhEj5EyRq2p6LkSvKdr25gNqvXmyGwps4wwmeL66/AD0FrD6dMnFIkiTwRJnmGNpa9XuAA7O1NG5YCX711nPMgwasq6DYSzM9IsZzDeZXb2kBtXRkjZ4kKzgYccSonN3hJZPPF1IMYnKhWDu6XCeBN57M7GuUFwSKvp6hZSTZJZhMo2535iBqiPdhNpUaBCSt12CBn9lCIdVUaPFK2weLJhwcH+lY2+wGO8IXhHKtPYNDi3MVIAs+lqm7ZmmBUEKRiUsTGK0NI20nvapiGEOOjdu36PN772L0iL6CNkTEdrLVv7E7KiYL5YMsgTlG0Zio5Zs4JeIM6POBhv83h+wUBHn5vZ7JKxlTRY2jZmEc8WFVtbA5y1ONeysz1mtrqMdEwTGI2HZElOWzfgPcVwzMn5DJmkNMsFdDWdMayMZ297D6UTVl0VWTK9xTQtX/mJL3N8dsY7D+4jpCRDkasEZz2r1TrOoqQgz3PatiXNUgIe6w1aRTHWdCsG8aSpZjsfwNsP/si6+scWdyHEPwS+DOwKIZ4A/wnwZSHEZza/qwfAfwQQQnhTCPG/AW8RY97/4z+OKQPQ1xa70NQtdK1gdtGQFYpGtnivOW0aBiOJyBJuv/Aye1s79GbGbP2U67dLBhPQvUGEG8xWax69+y5pliKCQusFH97/Bm1nkcqRyyFJonn4mqANCwa7l9y9MuG4mfLea2/yT//3r9K6Brn6nxkPM3Qa6GvDYv0v2L49QaaO+slTHp8umYyvszUZEKymHKT064o00xiZcvvFl6ibJbc+9gLr+ZrhoGAgMwZZhroiEMKTiZSlNeRZSV4o2taSpAXzywt29va5qFdUq41zYZ5gfWSBWGtjdyUV3sRUdaUUvTMkSseMRrGhv1lLW9eUeYF3PS5IGmciV95brO1ItCZLClyALIvmSFkuOLi2i9QS7w0XFwsOn15w/cYuRZ7hbMegHLBYLlmvGkbDAdOdnTjoU6Ck4vT0lItZx5WDG+ztbyN1IBiPtxHXVDJnNp9jg2Br7yp5MSRJC7z3KJXgpMTHNp00y9jaGsNmAOg3w2CxUWx6HELGYAYhJInSzOeXGOtonWCxbrEb4Y6Wmjdf/zbFaAuB5MP7D/nUZz9O8BaflUipaRtPXhQgQREwXbSNlZHjEzdYpZFa0fUdvY20vkxLBvkAuavQRNn8673l4uQh3kq0jFBRkqUMhmPy6RXu3rrFjWt7FEVKUWYMJkP6ruFitmQ4HDKd7gKxU9dSE11vxXNVaSAQQsT+n2HoPo4xUVrQ9bFoCwRJoug7i+sb7n9wn7sffyUy58UzYdMG2gob4ZSUURgmLUEK0jShbU1kKoVAImX8fwTHkycPog+R9UgVgzKM8FjTIwWxcFrIdGQadb0l03FesVqtCT4gRIS7ynKAkAl9b8izlJ2dKQJYLhdMx1t4b5EqNhC72ztM85JHx8fk3nHSNwwTjek1pyfHvLC9RaEi/CGCpEgG9POn7O9tcX/lEPmAdj4nOENjLBLHx166wzsfvosUKUFHG2SBYLlYIwN4ITHOIGxN19R0qwUyT6mqOQcy/qze20inFYYvfvZzPDk85cHZ05j01DuQgbrvSTOFBTIhSbP42ig9jHOtchi1I0KSZym260BAXdWb39cfff2/Ycv8/L/i4b/zPb7+bwB/44973j94eR+gL3j/G09jNmZQ4KPc2YUOoTLmwSETz9Ebb1HkKVZoBrrnz/3cCyghOHuvR1hwFxayIWniyZOMVCrOFmv6VrBdljEGK9HIILl3+zPs3/kYv/sbax68/y3OH72P7Dyr2jPIz5gwxPqAsY7V0THfec3FhakTCgFCC66/eI/P/xs/gxSB9eKCG+olFrMFg50dVosFtvOMJhOGw5JgHWtT0TQVhdAU16+jixIjLG9941/yyud+hOn2FZZVxXQ0YXxwFW8DyXQbF2KHHalQfhORFzaFPkq4274jKTZwgoiYfNN2eGIgtcDjlaK1kcYmfSDRCbZ3ECRZoqnWSxwBlU5Q0lOvGg6PLsjLkhdfvh2teHXA2sDTp8dkWcH+3k50ElQanWbMFxXHJ+dsb+/y6ifuYJ3B+QbpEryLx9S2ccwvL9je3mI0HUNaILXGBkuqFJnS2FqBh94aHj++T12vSVUsqgIZC68ICOEJIUruA5CkKUZENWZwjqqqadqOdMM1ni8XFIliNT8jSwLWVHzn91/npRfvsrO9QwYTeN0AACAASURBVKYThNJ0TUOW51jTE4TE9j1SR8GP1gld15LIMvqcI2IqjwuMiyhZz7MMpQIKzeP7Yy5OHmKNZdl5ruxdY/faDcBz5/ouN67vUg7HdH3P5WxGmuYYZ5gvZiS2Qk1TpIjsJALRoOuZ/8DmzzP7hahAFdEgTDicCSgVLQWMqfHOEbxnb2+fyfY+nXPI6EoWlctsNk4JQgaCiOZu0hlWF2e4YMnTDInEd1G0hjXcuH6dQHzdvXPP1a5CZvGUKBRVtcKlgiTRNK2jyCzT0Tbr2RIfoDeG2WzB9s6IJIm+611d8/D+e2ilCFIghKPpDGVW8ujBIfV6yac/9iJf+NwP8s3X3oyBGr4iyzXDyYjDD9/n3iuf5YOnh7EL1imj7Sn12RkvX7nJcu1IlOB0ds4oTVGrmt9/7fdRUmGNIylTgo9zmKZp2JmOWK4qvFQ08zldXeGkQqQlZdkxnYx4crag6S24jh985VWOzk546/599q7skWiPSzQqiwHZRZIznkxwpqM3NT6k9NZvmEIGZwHtMcYyHo25uFiQFRle/SkwDsvzkitXX+WLX36J5aoiAH3bYjpDU9U4Z6OQxBqMD/SdiQKcaU575FG5ZJAmSFVwrFdMr70c5R5a4ZynHN1ANhVXpjv87C/8h9x+6QZkOWLrGmfzjrqpqZYV65MH3H/9Wzz+8B3ef/338NkEIRSJ65l1EZ/cHhYMswKVKOqmYmcwwblAnqa46hSpRRxwSkWZl7HjXtbIaYmwbRSabI3ozhcMkluMBzmL+RpPRm8sQWtc31KvV6h8iEpy2m6BdZZgAy7VSKk2aLmIsXDBxSJoLI3qIwdaQJCRMpflKU3fUg4yLs6WHHiJcAFvHX1vaeqKnZ0pUqpIE1MaGVLOjuesqjVXb1xnMIxFTOO5vIjxfMNhSVmMkAK0lnS94+GjxxTDES++8jGKPKdrqmirW5ZAYHYxZ12tGA4HHGxvo1WCEJo0LfAykCQKYT2PPnxE29XcuXsbrSVmtWDv5Zfwtnue/SqIxlchOII1WG9iBmbrEEJiTQ82sFjOyLOEruvYmZQ40+OcZ5CnkU/fGY6ePqBZXvKpT3+WYTlE5s+cHw2ZivF23sUADQhYK0iSFG/6TaBKFP9IrfBSIoIiyXK2tq+Ak5Sp5lGuOTx8TJoM2T64CbokwRBQpFLhTc94uLVJufKURcaDD97DdzMyOWJ7WMZ5i7M4Z5BBYQNkm/tIhLD5f2yMgKXESwG+QEmNCBY8SCnRac72XhZ575shLJvGAR+pnsHHx1Ax9q+ZndGbwHh3Gr1lPDgRED7Q9T0XFxfkeY7USYTLfAARM3ODEMg8qjudswzKBc5bVosFWiu61uKDJ08HcZbUW6TokDKGY1zMP4zziM7iTU9TdXS1Ic8ytEr54PEpyWDIv/1v/ll+5Vf+MTrRnM8rXploFpXl6YfvcPP2y7SrNVIJ9vb3eLJckfc9F3WF0pqqqRmlOcYGOudIdEbnG4bTEX0bmK2PCc4zmWxhJSjjaVbraNU93sIrhZaKIi85PntAmgs+9+rHWC4rvvvgIV3XgfN0rQEUpjPIVNE0LWmSUjcrsjS6kU63t2m7jnZdkRcDAoY0SzHGkuqEerliPP3/L2L6E79CEFQzQ5nlDK9OQEa3tOA8gohDSS1I0oSm6xAhdnbBtUhhCcqQbClMDwcvDqm6iDubugELjQ385X//Z/iFX/g5jIS2FXgPs/Wal6+OOdi/wwePTpnd3md0cJsfHwx4/MFb/PI//J8IxkTD/1tXuVMm0HlaIckkZInivHXccQGRFmR5QW83eLiS9KFhcTFDJ4qjD+/jsPStYnpwQL5XoIPASk3V9Xz6x7/MolojXUM1O8MlQ8qtLS7OP6C6OCRXQyq7itCCEHR9T6JSCAEXYrHrjIPOkicJddMTbPTFbo2hMoYim7B7bYzSCV6C8w5PhDxWdUMSAhBNkU4vL7m2VXLn1k2SLEHJGDIwW1UUeU6eaoQIJNpT1R1nh0vaznDrzk22d7ZxPuBdDyF6vyznc+qmYzAac/3qzThYVAqZKaRW0Wyq6zk7W/H00RN2piOmkwlCePIswVtPtVrR9y2DsogQBAKtFIIEkcQhKxAZLFJG+bYsIu95+V2yNMFaS9f12K4nyxRFosmkwhjHer2maVr63pKnAZVGn5Zuw47Be9QGk7bOYbEkCNqujp2b1AQZ6IwhTzIWi3OWyxkXiwusdQwG2wzHLZO96Hvf+IDOMxZ1y8WyYzoVVGeP2d4a88Hb7/LGG2+TpZo7N/aj70pwQIR2gncIb3HWRvtfuTFMU9EiNzbiAiUjv1spQdikPAVBZMgoj9/AWPH6yGI4iHhfBi9p+p40LTg5OmT34Ao60Tjvo5e8VFjnyNKC5aKirQ1hoxpWWhJwceYjNca3WOcJfUvbNPQmGpi1TU/d1DGkJZG0nWFVNVB3mN7S5g0OjfNgO8Pag0w0fd+yP55iuxZjWt5890PWy5q//LM/yf/9G19n9ug9ni56rhQD6m7N2fkxd6/e4Wy9JNE524Nt7GqJkAGRZwjTYl0UcA0GQxZdi840W/tX6I1idvoQoWA4mVJ7Qd821KslxnsmZcmy6/FBYJ1hua750r1XmS0qHp4cUQ5z8jJByEBSZLRNHz1jBuM4G1Ebx08SurpB5T3WOJROMNYAjrqu8c6zNd7FWUOqM77X9X1R3Nu64e3XvkWaxYGNkHF3DxtcVUnQaUKabaTmYSNYIYCS6ADoSPuTUmN7w7paopVG6oztrX2ePnyPv/3f/jeMtrY5uHqT7Z1dJle2OT1ZYXrDYFCyalquXtnj7Picz37+C1y9skMaFG+++Xv8g7/392gXCpkOcSIgXUc+mOLTFIuLbBFvkTaglKCXIuLSozF2tiTdO6BdL1kuzlifndKNJnSLimADbbVGND2maanqNa03hOUl5x++gTY1rV0xzDJoY0HzPuBt2Ei5BX3fQ4CmjcwCYwyFgFxLbHA0bUNVN/izGBSeK0VvDIHooqe1YrGYs6W2MdawsD0fOzhgulUiZHQEXFxe4n1gMhkhcMjgUCrh8ZNTlrXj4NpVXtiPC9XZnhBi1N3ZxSXVumJ3d5e9vSlIhceic02MPXAs52c8ftBiLEwnI27f3kMrycVsxc7OaGMWJsnyHKFkHLJ6Q3AxQUiIyIx55mfFxuMcD9b3lGlGQMa0oiDxLnaaSZKTyOitIjf+KkprpIoKSR88Mojo1eLBW4PXGpVk0bRLbgREIg4Xn+HMfR/l4mYjOhpkgtl8xXo1Y3t7i73r17EyY4RG41nXjsenFwxH18EaXv/mN3n3/vtIBVk2YLVa4gxsTxK8l/jgog+9NQQXaZBK6ljwhXpuIClEDN1wrqc37bNZM945IKC0ej67ie6+buMzE9krQkqCkDhnEFKitGQwLmPRDx9tppH3btnbHZKkGUJl+BCJEmEDF0mhCULifcC0a45PZqwry7RQnF/MwXlGwzzeCyrF9g6lPa5rsSHFiIo0RF1B33l0Jgm9oV5ccvPaderec3pxydvvvs+iWvGTf+EvMHxtyNe+/tsk2yUTAefnRyxHQ27s7dO0lsF0m4vZMcNizNo1+CBYNx3DrESGgFYSt+wps4yHx6eYRUWRKGSaEtaGulqAiJYPKklxVY0DPnx8xMfv3CZLMr77+CG6SMH2NFVNIiVZWZL5FG8dzmwCczBIBEoIGhvpvl3bkqiYn5skkjSJgrm6XZOkCZeX8+9ZV78virtzlrOLOQLwG4l3/OBZJyYQchMoEL2F0BvTo7DBChOt0EqS5wXeGnobmSBSSs6PHvHkvW+TJooQBAKN1Amj0YCsnDDd2qMcj/BJxouvvsqNOy+wuJSMpntoqfnFv/bX+OSnXuXv/Nf/JW9/5w2MF4S+RgSBunmb9eFTHnjDxWpJu5rRuY5kMqUYFJxeXJA6T45HZzn1xSHtcsAL0ynSVJSTLarhCdkI9PmMnTLj/I23IAlI6yi291DrQOLt87iwZ0ENEeZV0TNEgPeOcpCjYtnGeoHQHqUDMhgyEWialgkBSUB4z9Z4zGBYspxfkmsYFpq+ben7CkdK27RY6xiNxpvknkAIkvWq5fD4kK29fT7x2TtIEcBbwGB7Q70yrFdL8jxlf3+fPM/xoUfqeOryneVytuLJ8Yw0H3Lzxj6DUYq1ZlOwYTQqI+REpH9mWRZVfsTTi5eCjWAXFdhI8sXGc0bSdp62m6FVYLo95vzsklVjSbIUmcSBXlLkgCXRgnJYgghxIKw1QYhoSRut1LHGIISkTLMIyTjw3se1JxMCApUm+A29VCmBqeZcPnyP1eUpq/WKvekL5IMxHoHG0q4XFIOS9armw8dHXNkb8dvffINHT54yGozJs5RBlvLyvR3u3NgjBIv3MbCiq3raxjB0LhZ2JVEhwT3D34lVPkkUUsbX9JkvjSCangnnIswXYucYd4VnRTtG/JV5hpKS0WQbnZT4EGLX7h1CB4TSBCSnpxdMhiPyIvrfdI1HpunGojhSLJ1zeOvRCqxzGOOZjAdU6x5jowo7iBbnHXmimU6GyKygWq1YzWeIfIBpW1AKnaW01vPg6Qmf+eSnUEnBk4ePODw64W/93b/Lv/tTf4l7L/w8/+ev/xOQKaldMLs85NreTUhSbBAYFK7qSXVOlguWFzPSgUEZxyAfcHx4TJ4q2nqOa2t2trZZrCpCD+vZJclwhNqY8V2u1kgFWmTkWcJbhw9J0tgY2F4gQkJbb04vPs6I6q5mMCwxfYvW0VYkz3Oc6UiUIM+KaBKnNdbGzAQhAwgf336P6/uiuAME/PP5EMQGIs6GogMgHqwLEEScvEd5DkIKrBc0QaCFZy3WKBVwqLgJEAuhFwGRCHTIote1tNSLFKuexKKloonqa7/5a2RFSZqOSLOE27df4hvXb/Lv/Ny/x3/+t36Jv/mf/af8s1/9FYIIlBJeffEOk+vXmGwPePp2SzHIkRb2J5o+H9DVJ3Suol+uyfIx+xNJXV+yPHqDveu38bMziu6M5YMa01yi7YCbd/fZ3drHNC1WpRBukCWak5OnXBwdkShNZ3tAYlyPCIEii9z/WPocSkkynRJSRV13JEKjEKTlKN7MzoE3eNMTbIIxHc5njMqSynmCECzmKwaDgq3pBCk1IFkt15yenpMXA1546UWyMiX4DqFiUPPickVT1WR5yu7+NiGEeLLYbMCZzDl8csaT4wsm2xPuvniH4aiMXaiPQiKhNFqVJF0fF4IU9LanqapoGrYpFD5YHNEZT0iJUtEvWypFkFCWGcnkgNfvX9K3HSJR9E2HCR25SpAhYIxFCM8gS3G9Yb1a0fcGP5KkSRJZI3GEgTUOgcF7RyI2nvE2qkDTVKOTFOthsVpGOKRZ8OTBO7hqjk4Sbt5+keGVK1T1jNWqIsvi8Hs1q0i0pj6aI3XOJz71BU7O/jFeGOrOcv3GPi5IjBVowNvokVOte5bzluleR5rniBAFXEU5JCiwzkRPHhW9cZCSgMc7j1cb6wkZefof0Ug3alai3YTDbzaGQJolccMjhqk8O1nHGDtNOd0iS5J4agpRSdl3ZjOUthhjsabHW0Oi0k1DEtiaTvAirptCSu7evcPZ+Sm97Vm3lleu7uAnE05GE06PjkllgustOomspbbt+do3vsGXf+wnGKVDvvX2a5Rpxj/69V/mC5/+HL/4V/8KX/2N3+To21/D+TMGxYC9/Rv0DorBLsfHT+gSjVCaPgSqtiFJCpJigM6iHYRrOkII6DzHhkBfL3EBBsMh9D1t39E1DT/08Vd4cDnjgwcPuLK3DXiWqwWpTp9bC2glWTctSZqytT0lTRTrvseE+PswxiF9hNmUFKSJJsviaygQ2E2mw2j4pwBzh02zsLFeUELi8fgQHQWFFFgXJ8NyM9EPYeOL4ePNjoD+Gc/Xxg2gD37znBs/DANaVPjNTaCo8DJK3LUUSJmiNCTVikQtESpwevwQ0zX8+i//Q77yUz/Lj375z/Ct3/jnmHpN0IrDwzOmV96mCFPu3R2yevhVQmt57wOH9xqhe3QnUEbi6zVXrmzjHVFOvnhCludMphLfrCjRSGMoU8X84gIrUgg1prFY65hfntPU6yi196Bk5Dn3pqPMSrROmE62ODp6GjNc+zXpaMB60ZCl0YEw24hzwiYOrSxLkJGlYPuebFjiEwkeBmVBohOUiJj0k6dHGB946ZWXCaFDioA3McKuMpbL8xllmXH12kEUYRBZGForfAis5zXH50dMt8d8/JN30UpFyMUZetOTaoGSapM7uqKpa8pRidxwf8UGa46NoMA7gQgRYhAELJF/zcZfJiC5f7zmN7/xDqv5mqIsaDtPriWpgmAdbVsxGuRsT7ZZ1g3rZU1VN4wnEe8ssuwjsZSPb9t1RaIznPHgIckynDU0TUPvYpCElDA/P+fh/UcMUs9wOmU02cVaTWMdP/ijXyaVip39A+68+HEWiwVvffNfktlzbu7d4+23b/H48AH7u7tIoWjqlrPzGdd2sk3cHaTFgCAWOGPx1sT7CMF8dokLnun2hNZ08fHN5vzs1LNp6oFNkZYCgohNlWJT8Hn+2gYsQkqc39gPexcFN2EDYXnLqmro0gznwYcI5+lE01QRi57PZhR5hncN1ibIDYvr6PCYJBXsjAfkqeby6WPSJGVrNKZ2hiePHjFA8sKtPXQz4Om8AiFoTYeXEf5JVcbXvvUN/uyPfYl8+EXefOt1BqOU199+i4ePH/IzP/0zfL1xvP/dr/PBO+/hrWA03cE4SZqm1K4lyzKyMqXpWoZZRzmZMCoLpJPIRkCIKVcez2J+zpWbt1is14zHAx4+PeWFa/s0PvD44UOGkzFdE/3oB5MxwRr6tqPrDd57siyhbhsOn665uruNRhFSjXPxmGiNY5AXeOuQMuYO5JsGTgqBcybSmb7H9X1T3BHPKbobUcbGrW5zVIwdqUABmYhciVTGT6wMH6nzgo/2oZvuA4gy8c1qtv6joZEjcpitDTgBQbTxyBkalFzFE6qKzIFqWfP3//Z/xc0XXgQMWgds8Dx59C7zyyP+/Fe+EGXZbY/xHb3zrPsA9PheYtseE6I4KEiivTCe6e6Ui+M5k60Mt+qZjHeYrRfUNtC1jhtXC5ZPZmzvjKk6Sz7IcZubWydJdJoLgfAsz1hpqqanSCRlqcnyFOkCyTRFeJAi4ZlA33UGMkmRJqg8JUhFkuTsXi1x9QVy4/n+9Okx1sHWdIdsmCCFjwZXUjBbzLHWUhQle3vTOBPxPjpCZiXGGM5O5xgT2N6bcufeDbIsw3QdSsQkIO8sqYwe9Yv5kr43pEkefXw28xUXLJPt3cgU8RFrFsgNthw3dYKK72uJUDmLSvD45NvUdYxsy7KEokiQNtr1ahkoi4REBHrTsn9wQOPgzTe/w87OzvM1GG1X42nIO09btwwGPaaLnZQgUJuOuu8j9uoMs7MTTp48RmLJspzWGsa7e3RWsTOd8sUv/euRry0lozznxrWYCLa+eMTy9BE+BI5O5izna04Pz/ihT9wiL6KXf6IVQowoDwb0WPA9AY9zBhUktl2i0oJg+g311EQaZHRkQ4R4Z/ggEN4SRNzsxeboHHzctIKI94xzDpU4CBsoRii887jgUNYi0jRqJSYTkkSTpjnWe5yNSureOpyF4XSH0WiAsz3dxRytNJ21JEHiek9TVRQDQZFlSGfZF5Jre9uIckyzWHH04JArE83+7jWOlx0PD4/wDiwGITzKBH7tn/wf/Ac/+9Nsj77IN779TYaDgqrp+B/+l7/P7d0bWKcYFwXHDz6g+IEhCEfVWLrQMB1NWCUZK1NRtTWFd0zHY6SQmK4mzxQORegMKtGMdq9QLRdkaQLWcufGPd549IRP3t3nwUWP8x1epNgeCpVTu5jJkOgcZ3uKLMG5lHVTRZDOG7I05jMnqUImgroyJGlMPyNEIzKdJjjvcN8blfk+Ku6bzj3IZ5DfZgFuPheIG5UO0ZFOELvzIMImXZI/gOnAZqTG8zeb7/EiQjvPPuVd3CCEJ1qJbv5psRn+CBdwvcfIqMV6+O5b5Dp6lwRpcKrgC3/x3+LdB/cRmWJ1+RCjVgzLCavTS1RZsDi/ZHXWEQikSsfjKY7t6YiWHls3iHFJIhVrVcOgR6zA+yVBK1RhmeyMmISUs9klcbuKrol5nuGdIxEQguV8fsaVWweA52JxwSfu3ubhoyNyKRAO1q1lKAXO93hp8InmcrUg4FhVNXXTM9waMUo1i5VhvZ5x89YN0izFOY8ghkmvliuWyyVKJezs7hKdKkEqj5KaprY8PTqk6zuuXr3KcDgguChvd6YlS+SmKHtM27JeLDHWMppM2b2+T9f1dDaqGX3XYm3HxdkpUidkeYnWimebNGwWhw8IqWlNzumZ492HT3j85JCtYU691gSp2BqOmV+cYY0haMnWeITvehZ1hR7WHJ2dE7zk//rn/5Sf+Ik/AxvjKZ1qZGDDB48/fwxlTnCOmKvatSQE6sWMb//ubzHKM3QCvTDkeclLL7/Itdsv8/TRhxy9/x3M9i4Iyzobkk/iZiLzIUkxYn//Ch+7e4tbe0M++cl7XN8fgQPp27guN1vbZFhi655kcyJr1hVpqinHAwJRyCY33vJxMCyec+XZYOfxHotwjHcxlUluZjhhY0tgN6pSCJuEqIjf+xCQPrKsVqs1WZaQplmEFNIUrS1JiKcGKSR1vaaralLtKXLBzVsvUS3nXFzOccHSrxS9qdFZyuCluyTnC15/csmtF+9w7+5L2BA4e/KAfd1ycOMaretZu0DVw2U7R6ucX/3lX+Uv/dRP8sP/2o/yra/9FtZbOut4a/kew3FBbzzTyQ5vvvUBr9y5SmVqglas53MykbESit71tOuKYjwkVQmdrZhuXUVqzez0jCtXb9FWPaMyBy+4d/s6As3BQGFqQWVi1F/mHKbtUDpDJyXGttgQrVTKrGS+qjEqkGcJoe2RWhNkDOROko1OQkVtjVKKvMxxxpAl0T3ze13fN8VdiY9qM8TiHPHAWOCjq2uEIWKyWCzpSily6TcT+/idYnOQDHzke/3s8vDcSU9ubhHPs8FtrBHBReGGEPEbpBJ4ASrRG98VgZUOYQXD8RCdrhgOFOtugVY1yXBIX6+ZTgvmfcdoOmCcD1mcL8jKAts7dJbiXEePQaUC4STrvsauwZiWPMkZb5V0WMorA0SWEVroTU/wkOUpXReTfrKihEQx3ZqQKYXvehKtuLp1QLtomE63ydJo8kQ+wHqH8z35oEAkARkKhlphuh6Ep+lqKu84GBTcun2TNEs2r0+grmpWiyVZmsQc2ODxvqfIojjs8nLJ0fElSqXsH+wymuRxCOgMIgQSqeMg3HkWywXrak1ZlIy2tqJn+ib1vu96+t4yHmwTpCQgSMsy4ttZtlFQxs040RlpJnA4ji487z285OzslIuTM3IpuKgrjPNkKtC2FVorjPERp9ZJ5FTLjLPTM/q2ZjQcc3n2lHfffotPfeYHma+X5FnOuCzJdfqciRJtByKdMJESJWL2a1tVzOYz1lpgOoOxgVc+eY3l2RlmteTs/Iz7v3/Jrat7lKMxEk02HHHt9itoOmy14M4Ld9meCD5zd8poMo4BIbbDtZGr3rse52raaoUOMX7QeodOJLbbQFViM20moKSK4dnPiAhhE+H3/FQbA0GkBB/cZtYQi3fwPp6RNkPrZ/C83PjqEDweTz4aMRpvIbMcgf/D9sQiCpuGaUKWlfSzGVKkPLj/iK1pzsdeOCAfTjg5XXJ09ISr44Kv/JU/z3v/7A2633mbb797n3ffeoesHDLd3uHa1lW2bUM7O+XOeMhRXTOa3OTgxm0uT075H//XX+YXf/7nUZ/6Er/z2lfJJKyDIJQ5ozRSrXcHW7z/ztvgA1IkBC/xtkcER28FdVsx3ptyfHKMV1CMcuqmpm7WjLb2uLw8Z1KOuFitGE3H5DjGQvJbT2d4GQegwUdHVesDaZ6Tec+wHHF+eYnf6BKENcisREjIingydwHapiMdpti+fx4K37Y1yQa6NP33TmL6vijucbAjn3tjfPSYiK6kIXbbPkTtXCIlWQJaR6c7Ez6CdNg8hxBx4PrsRPAM2xFSRFn1ZpELBFpusH0RB3NxR9kk4CBQQuE2gcJOgBeeRIISmuk45eLslG55hnE9vge/sBhv6FyHzDQOjfeGvCzZGo/pe0NQEtPD9nSHvpozmYyx45yursiTPNI40/gz+tpF62APSRIDu5NEU9ctRTFkMt1jMpmys3MVoVMcAoUkzXOarufeCxPadkHfGex4EjnizuNdjk4mpNpT1xWq7BEi0PeWolAMRzlaR2y/qmpW6zVZVnKwf8C6XmwgFYEUmvPzOScnM4ajMTfv3KAcpDhrNyHYkdOuZVR5LlYrjDGMJxNu3riFx9NbCzoyp5wxpFrirY9FQic430TWhoobstCazjTUdcP50yPefOc9Pnh6yJPHc25cuc1wmOP7luVyxmK52JxuNOPdKW3T4dwA6z3L9RrTGQZ5TggihosER1mkvPGdb3M+u+Tlj/8A0+kWkkA60h+xS3ycKXjv8cHhbE9drTk/u6BqLKt6zu54ghCCw6cP+c63PPQdj44OKXPF6niXZDBCB1iua2SSUZbRr9tIzfnpnI9fTSmKDKUiJdEHRyI1mY7ZqEkiwMjnDYsQPLflJYDaBA7O5jO8dzgf4axoGxy78AjLuKhc/YgkHxssRLSAQH5EfdzYzjrnIufeWbAWIS1sTMq0ylEy2RitRb1KFEYFOgS+8+yWGYu1pe0tjy97hotL7t7a5eWrEz4/TLny3Qtmn7vG5z/9Ccw/+iq//8F3qecXzBYXfOAEX/j8J7jz6g/y4LWvs51pZrML3ry84N6tu3zlx3+Et7/7Fl/4/BdYVZ/mu29+G1OvOW8hyWryXLF7/R7Z9es8SjsX6gAAIABJREFUfPQEYx2D0RBRV2wNC84vK0zf0SzmHJ1dkAlJlqVcHF5ycPMmp5fnpBjWNXjXsVNmXJyf8u3Hh6xdQ5EMEcZhehNP+X3L7s4EfMHlYkHbtZRpSm8NhYJcJ3R95NkbZ9BKc3kxY+faDohA8EQ/+1WDSKNmYTT4UzJQxYeN3agkeB+HhUQWjZIKEWJnEq1lA4kSpImg6iN2/sz0CIjY1PMn/sPA1DO4Jv7tnj/6HKj5AyeIZ0dPhaXMUnKtyRKFLiTSCHSq2dkeIU1HkWQMs4RViOnoJvRImcUuxUjW3YxkkJFKQVLmrNs6biqtIRMJVlr6Vb2higUGo+jbUkyGlOWIJ8eX7I52KIshIcByudycPnrWVYXDo1MFShO1ISHyrlVkvQjfYjpLnh+gfIDgaLo1/D/UvUesrtl1pvfs9KU/n3jPjRVZrEAWMylSlFqUZMk2HGAYRkNo2IYDDHhgDwy72/DEnnna8MxAD2yju2UPbHU3rFZLFtmSGCRSLFYVK7DSTXXTiX/88g4e7P/eEgyb7SH1D2pQhVP3nHO/vb6113rf590EXN+yWZWxU3M93jn2REHwWwSxW5EkGdPJLBaEYMnzjLbrOT5Z0raW4XDA1euXmEyGMf0mQJ5mSNGTSE+9aaiqhjRNGA4HpHmOD562b+PfnQ/xRS4hTTQiBOqmZryVxnprufnu22jjUWbEYtPzwe2PaXrBz967xen5MVIoVuuSvlqTZxnOxhudMYrxMI9dv1EMMkOqDMdnF1y0Hb21WKdwAcrt91g1HZ31vP/+eyyWa371W99C4Bnk+ZMrckSzxoZgU1eE4EkkTIYFRZFTlWsuFqt4U3ANbzcrJqMBy+UF9+6vuXXnLnmRIIOgsVC1lsko5ZnrNwgqhkl4IWO4x+M801DHwA0iQiOa2NpPdlZCbJfNIS6sVby95lnGRoknz3ikl8bbryDE+TrRnCVETLT1LoD65ExFN/Bj9szj2MG4I5Nasykr2m6BVJvty2+7fCXmuradpelaghUsVxc46fAiMEgTLl2+TDHOsEHxGR2YZYZ7N+9wpd/nJw8fsDcouJIkXKwrHrSWRGu+992fMP/0c3zhG7/Oe2/8JRPm7BcJy9WSd5enzAZDfvCn32Y422d3Z4pJ4LzpcEozPz6hGM+Z7s7QD09o6obzckWhJa5uSA3UbUtSlqyXNdPJkKOnnua92/d5ZveId955mxsHU5yHQZFwcXbGD352i0VfkbmUal1GFdtoiAg9uyNNQsfxqoGkQLUW6SXSRRFBVKBGSat6/PcUgM7jrMeYlL73hCCw3lM2NTs7Oz+3pP7CFPdogP7k4bMCEiHIiFFmPR4pAlYEZKrQMmZpKiUwUkXAlXNR/eKJAQVbNGxsxKPr7hOVwF/5U5/EVX0ywnn8aglEZNNsf4cbl3eYDoa0XUXZeEwajQUvXL3CerGkMIoez/J8jUrGLNYNVy5f5/T4AY0iOkqFR+JJ0MhUMsxz0mzA7NKMpVwjfcvxeUMiNLt6TKpHECSzzCCkprcN2miyLOPs7AytU85PP2bczVg3K37yxk1294fbeLWew+u7dJWjrloO92f05XUydwTAZn1C6yDP9DYXNGV+sWBnd0C56VktEpIsYTQekiQpfe/AOlzvOD2fsy4rxpMxh0cHaBVDHqQMZFrFgtG3nC/mbDYbJrMZl44u4bseJ8D2FuvaGKqhFM7baMGu6oj9dTG0WweHEz2DyYArN66z3PR8eP+COzcfIlXAdRUutGjpGeSGIhkwGGRkicIkIzrn8d4yzFOmkwlIxWazxloXZZxKIZyn6zzzznOx6iiUY3/HoIUmzRRtueDk0T2OLl9nMV8ym023fJa4ZHTOsV6vYy5t8GijOLh0ifligXM9nbP0VU/ddSyWDU9dO+DZ55+jbHratkEg2U00ZdUyzhStD2zKDbPpiK5ukIzx22c4jlviPdWLHsTW4xAej2GiqStIH+mODvogUAoIOipUrCNIHUFdIUKw8GxfGFtVkGRrGPQEfJzdR+0isYt3iO2J9SGes+lsjE5NDJJvmnhD3o5GhQDrA94LcJbjhz2rxnFR95S2ZF59gDGGZ2YDnnnlWZK0oPSGm29/yN7RFW4y56kXnudTneX2pmHjOtIko2xK3nr3Db71W7/Bmz96jcXt22TdGSs8fm+f/etXEbblMlPUQ8WNKykoeL8qubh3inwaSDTU4JueOi8QymNExHO4rufpVz7F/OExOM+kGFKXHZKeQTZguTpFBMmpHbOsOjKTUOGQQmN9h1EtV3dmhAAP5zVWKrAdaEnZViS5QSjFploBkR2VyDS+DIMlIDBpHm9Itme8O0EQ2DQtyiQ/t6b+4hR3pfAyPNEVI4mONrZzPxc7eE1ABk9mErT09L1nPMp44ZXr1MuKICXDNKGtG8azGcv5kiLLWVcblNFY62JhsQ6pJNZHIwXExVPbdrRdh7MxACJ4gfMwmeQUI4ERgZ3DPW59fEKeFXjrsE2L1op8MMQ1LUHWjCYjGrvApAnjyYRHZ/Nox/bbm4GUXLtxFes6hlnKJBtQqxaTGgQdUkqSfIiUGtcH9nd2OF8125eVQ8iANtF9mGcZidbsTCZMhwWTUYHRiuA6ruztkqqc27fu8plnn+U4mYLf5l/mA1xoOJrusbRrlpuG/Wmx/dkV41EG2zAKrQ2LxYKTR3Mm0xmDYcHe/i4+WKSMhzw1CfjAarXCuVgQ8jRheOkSUin6rsXiEFIgvSVRUZte1h3nZ2ckaU6aZVy58RQmMayXF/FB8Ck2SP7yrbvcunfM8cUc4TzTQUK9XpMlhrvrhra2jEcFWZYwLorYVTY9OzszdmdTnA9UVUuaT5k/eARAJmHhPU9fO+Dr1/f4B7//Y6reg0ojMAxJX9V89LP3mE5m5BPFZr0gz3OkUAiiUc5bS297gohjxCQx0RAlIDE6eitCwPrApqrobUtnBYv1ijTJ8XievX5AlmScnG/wgFSG5WLNtWuXtg+N+ERIQKB3frsQjWNEpN9ukba3nS1uwLttwEnwUXUhdAzCllspXYhjE+d8BHzpJOJ84z0tfr19/P9wPDaKEaKJS+hoLNzMS+59/ICXX/o0ITQo/VjoEP9hvUcIQ9U2tG3Dc09dobGO3jtEiLjrbzz/LLVLac9LhkWGSGbMXMFhdc7HtuX+ssXojLpqmV6ZQD/n6a+8xIfrc04byy/9xq9w5833Wd/8gOrBHb5//JC6DwySlK9/6bOUS8u9e7fQaUJdtmyqJUVhWC8CFo/btOhRTlnWFMkQlSr29y4xP37Ix3cfcXT5Ercf3GVnYlhdPKTxgcs3XuT73/0hyEDddXQhYimClDx3Y5e+1nx05x4mH9BZi1QxJlNJjTFZbCmFR5vIMlIqOnuLNMH2DVqk0U2sYq6B73pc3dKU9c+tqb8QxT0AjbNEybJ48m9b4Z502TJApiSJlCRGEvvp+DBnMjAdaYyXeKd57toBWZ6yWNWMM831q1d49Og+o8mEQEBJw8XZKXv7u/TObW3aguGgoCwrfIjBy1mqCK5ByIz5sqQsN/S2j+dIBTpro5tSQhCCsuk4Pl9Qr0qKQUqwnjs373D56BKGOCvvrEVKiWs66qZBacHOdJfIqHbkeYoPHtvFsYAOgc2yJFMxQzN4HylxAvI8BnNUVUuW5lRlietr9mZHCAKjfA8ZYDoYMMgMN2/eJH3+WbT3SBdwfc/h4R7VpmQwyljXJdPJmNPzi+2cOxDoqRYVF7fuomTOzsEuh4d79F1D2IKoIOBcy/l6Rd/H/NGdnRnW9jFBfrlkOI6AMTpHYgbUdc+DkxOElBSDnMtHRyR5DkJh0gTvHdok9Gh6mfLRg2MeXmxoe7BCkWvF+cWc/dmQ4/mGum6Z7Aw53N9lb2+EEQakYHdnRqoNtm3xQtEFz+nJOcv1hta1BOEZj6b8p7/zNR59fML3j0Y8PLuIXPHRkNP1CtHD+dkF3/+zf84vfe1rzKYzjFExLFoIJJL93V1W6yVd39G0llGRo6VE6gSlIjJCBEEQlvFoGLX/ZQ/CoBPN0e6I2bDg5sMFq3XN0f6I+dmcdm+2FQ/4rUoldtCesJUKyycBG8EJHncPMfQ6/BUVjI2//y2eV2HwwSG9I8T/EJnrXuCdReuEzjfbXVbYLo7ddon9eLQZtqqyGJhdlSuODvaYn58wmWYINMErHmsapFB4Lzm+vwLruTg7597xIr6kRODSZEQuU1aLNQejKRcn58x2Z4xnO/hnd1HinOG6IC0zZibjYr7mm9/6VZKBYbmq6foV//xPfsyv/fIvc/TUi7z+g+8yND3PPPdpbj045gevvcYrz71MSHL2Lx2xPj1FdJLhZMjxwwtCABs8wgbGuzvUi5KyCrz91hvs7e4TSQ8C064JXY0Y7zLcnfDR6ZzTizNGqaGRAuEiovjLrzzHyckJdx+eo5MBTdMgpY5OVBvTnow02BBx1d5vw0+Mj+hu25PpEZ21BB39CMF6bFvjfcdqffFz6+ovRHGHOP1+bGR6AoBCPDFSaCm2wcsCpQJSg9YaZT2iD9g2Rr8JNM6FLYNaIU2KDeCDRKqoMFG5xmQZdV0hTYJte2zfk2c52ysDZdkgMRS5pO1b2q5lPJ2yWVVsyoZsMKB3ASF9XLIi2ZQ1bdOB83HcoA1FlvL+rVs4BKfLBVopunYLBVIKERzrTUMqNFIJikFB8JbpeCdmJCrJcDhkNMop2wYhNda57RhEoyS0dYUQgtQUHO7vM8gLNusVh7u7nK/nXLt2DYzi7scPSNLiyWG/dOUS3tYMx1NEiAqbRGoyE3XH9x/NcdYynY64fPkIZSQOh5IeaRTr1SoujLZh1qPRKPK/pcDZnr7rcH1PnqYoqairmtNHxyTFCGUy9g8PyVONSXRk31QbtEkQeHSSodMJyzZwsW44XpZIpfFNQ8BiveLg6IjdnYI337vPtcsHPH3lCqkJHB3uM8gKzrZFf9VUeB9YbEoenl9QrivqpqNzG8ra8x//W19jfxhYZ5YvvfAcf1C/hvdsX9yCoCVV3yE2nrt37lAMBjRNjSpk5IojUUoxHgyoW0kIltl0zHPPPcOdO7dp22iQcX3PZByj5Zq2IwRPniYUueHwYIfFxZK+qbhyaReAxfKCorgM4ZOxSNyLWMJj8mPYFtnt2fHB47zdHuz4UpFCbCWOUeIr2PoLPFtDjN3m0gqstQyKrZs1uO1LIQakxPzWyM3ZEu2BeF6NSDk5PuXqlSt47+k6Qd/3eN/EAy7iotY7waW9Mav1kt73NLaPMDalePXKIevFBYfjXRrnGQwzXDVHes9z0+e4vXyEPPBMiilXi1eYZrssuxW+OWdTzfmVb7xA4Q95cHqGFwmf+xvfZP7ohNdff4PxwQ6j3T1aX3HjxlX+9E//nML0UDuaNiIYXNeRTUYoK9jZmXLnYk4hUlKt6K2nK9f4DoytGF26zMYGLhUTfvzam6SJoPWWvoPnn7rES89c4a33blPWDWXfk/qACmAShUBFFpCwdH1NmqXRh9B0qCwyZ7KioBOSclWSbJPB6u1uT6Q5LYqu+2uA/P2rnycbeR4vNuPcLjGaBE+iJULERY3wHi01Pnga62idp8gMnY2J8ULCYrVCiIBKDb2zdFWPxxJCDG0oyxJpElCCuqlZrjc0rcP20PSKYZ9QNz1l1ZIVGXVTs1nVeAkIRZZJLk4v6PqAwtPUJZf2Djg9P0Mpw+H+HutyRVutCQSKokBJhTORz7y/M2FQFBSFxA5T+q7BeajqmjxTnC83pKZgXa7wwhBwOG+jjVBG0FDVxiAKa+M8djlfM5tN6G2D63uCizPng9193CCj7RoIlp2dKfduzbF9x5WjfZZpRZZktG2gU57BIGc6GaGUJ0sVTdchUVTrinKzxvURuJbmGX4r1QreRuNPkkRFjvVcLBd0fkGaFtx44WWM0diuhuBpXMDrAeQFtq9IdELbB+abDete0DvBowdnDLKCsl6TGEtAMcwG1I3lnbduI3BcOtglyyST0YjVsuH+vWOWZUvT9zRth3eORyfnKJNSlnPwktxk/Cu//gJfe3mXtncoUr75lV3+4u33cVKiCs2gS+jqPiYOCYkNgd476raJz6RUOBcIKJx19G2DEQIrBFeOLvPw0SPmyxX5IGea51zam+K7Hu88JtGEsuZgNsHbwPmm5mB/n4Dg7vE50+kYo4muXC+2hkSP9XbrToxKmL+i9v+k5G5ha1JFPa/zPcEHvOcJzjd46G2PUBprewQB7wLL1YZsmCOkoK9ahNQorUCCCzHM27sYmBK8QxpF5zyvfOGLSGVwwGQ0euLo/eSlsMVF9Q5lFONBjghzQhB85ZV9/t3feYV/+ntv8M69JTfGA66NxihSlsf3efpgypeHL/Fm9TGmGPH1X/8NQoAffvtNfvCdP+SlzzzNBz+9T9V+hBQ5WsJ7y5r9vX1e/vyXef31n7Be1awmS6Y7Gz77xVc4vneLFIlXsFptoBe4viMfTbj70R1m4ymuqyhXa9A5drPifHPGaDyhCpJBmnD7dM78YoFQhmJY8PkblzEYfv+7r6OCY3dvwlCltOUKF3zMOPagVULQkbXTdTHGMUsynHOINOXk4gJhG3IRwBu6vsWGQNv1uK5DmwjP+3mfX5jiLh8vU2EbOBCljGEradTCI7zHqLjE1NiINyUQhKSz0HtBWW7YaI02oE2CMYqqisYOpRTrak2uJU3b0HWB4XAYxwfek2Y5alNH7goeLX207fcCbTRqq5LQRoHWJElCnkhm4wlCgOu3duNigHU14+EY71qevnqF2809/NIzLIbUVRuDJVzAKInrOvoq0DUlBwf7ZElKMRiQJdBur8qWQNe3dH0d3WkkcaFsDMEFXIhmLmUMeT5AClCJZmcy4/TkEciUumxjV173OOe489F9MmNI05Tbt084X624MZ0ipEFlMCgCIrQoGdPYq02D9R2TyZgizxHFEGstfdtvnaEGHwJd17JcLvF91PbmwxG7gyFJmpElkq7Z0DUNcnjEs5/5Bi98/kvUTc13fv93+d4Pf4InoJKU5fKcvekOwkNbtaxWK3b39plMcoT3fO/Pf4ztWp66cQQh8OD4mA9u3mO5qaJShEhMrLuWtmuYjkYcTDMOn3uRg90Bzz91xLW9FG9bMAOEtDx/acKXXrzMD96+DyIwGxUs+zVtCGyampOzc57te5zRLFZLBiYlNQYpA8429F2FSbKIjpWgdQzZSA3s743jTFtqTJJQ9y3jcYY2ivWmJh8O6ULg7HTB+cWcpw6fIk/ifPwxeiGE6ORVW2Qz28StJ54OGYu9EtuhpZQ4TyRibjv/mAfgt1TI7Z7LB3rboy0Uw2yLAFGs1jVaSEZax/n747MqXAzz2J7ViAAJDMajeGv2HoLFExOH4ubWo5WmamOsX5pEueRAB7701Iw3f/wGm6pkmh0xLfZofMCFimp5wtg27EvHV77xDb73nR/zj/7h36NTLaP8RepQ8H/8kz/nYH/G7lCjjOe8sSQiYbGcIw8Cn/7sc7z70/dY3Dzl7v37HF6+wtX9HU7uHdP4ElKBrCRVVbEsa4ZpSrmpCK5lbHKW8zlys0KKnsFoSqMgH6TcevsmPZKvfPEVPnXjGm+98TZ/8bN3sEqgnaOuWwqVo5UBFZVmUinapkMITd/HlCUC8bYrPNIlpEnKcrViPByjTYKUAqMU67JES/Cd3aIK/r8/vzDFvcgynnr6gDwreOf927R1w+c/+zLaCGzX8+jOPVxbb7f3W0OGUghp8YDrHb6zZOOoX06znKZrmU7HuN5S5CnT2YQiSwlSxzFPCNRly87ulLKKCUnj8RDroyxwPDRMZyOq6hQlFWkSqYXD0YDFusR5xyAb0jc2RmX1FiMVVVmSmTReZXGI4EkzTVhGi3jwgSTXsYtRMai6brqo3W5iGEXbdQjnGOQJy6XFbjM6pTT01qKkjy+hRJOmMbEFNAjFumxpOoW1FZ3v6VyPEAlV3XPDBnDQucB6U7NRAr9q8N5hhWax2tDVNXq6A05Td1HCmGU5eVHgnMIoGaVwziNlQEhF2/asLxaE4BkMh4wmUxKTECQQHFJYmmqJCAW90Ow+91Ve+fpvcXTtGfoeLm6+y2LZ8unPf4OyK7l/6yYmyVnVNdO0oGsrkjShbRwfndzC40iKjKefu065WFBuzjmcTtnbSRgORuxOBixP7iGCYDQQPP30NWaTAaPxCJ1omtUF0oetf0GijEEZiXcd3/rmF/jLd+/TVh2zYU43SGnLhr2dHUbDARdn5wyvX8falsp24FOkKGI6krfUTYkyCtta1us1o2HGzjgjTyVpOqBpLcfHc6SEybhgUzY0TY1IEo4fLanbnslkyMFsQGbi0vYTJddWq+sF3tttVx9NRt47hPfbZad/YrYKGHy/LcAhbBetAnzMSfBS44JAmoJUQ6o1bVtzdnzK6ekFzz79dISp+RARyE9UD+EJ3E9JQV1usL1jd//gSdpT3PU6lJRxth8CfdcgrKNpGnCe3emMd3/4gE0XaZEX6gO8XTGZHlDIwERAMjaYg0vcPrvHiT5lYgqe2X+V1c/u8OXnrvD8lV3unyypm4bVxQW7O2N023B+suDs4QOGezt88atfZHGx5P13fkauDcenF5RNh5bRVOcdDEYT6qZhsrvD5nS+hZv12MohbM1kd4YPkAnJoobal/xrv/U1MpPzj//gOyw3GwKQbqcHtrdgYm6CMRolBG3bbpVPPCGYeh9ouxZdZAQhSNKCbLxDMCleSEIf6NoOk6VRYhoE+eCvi1pGwtHRDGMyivs5rmkZ5pJsYKirnsQImoatFkBur6hROYD35KlhkEjSRKKFiHmD3oIVKBODFrq2xQVPV9c4a6mbGm0SkFENMixylJJUbY+3nsloQJYajAYjLZkKJKnG6Bih1jvL2fkZO+MhXesZDAvatmFdloyGY9IkxQtLU9eYRNF1TQy4MBGYJZUmH425f/cRu9Mh050Z0nnGkwllWaPGGetly70Hx+wf7Md5at3FzEsV6HvHIFVbHbVFacG6XKO6GKaw2VR439F3cQMrk1HMAPUB7y2bZkNWJHEMtFyhTcrCQ+8sVgjqqo1RZaNBXG7aAC6u2JQyLNdrNpuSIAImTRiNpxRFHscufQdq20FaUAiEVBDg6rOf58UvfJN6teb03j1sWnBy8pBXP/USz7zwMitreXDvAXfufciDm+9z98Ofslyu6VqL3S4PdyYjvvq5F7iyO+XKwQGTnSGjYfEEg1CvznnjuyWtT7h6fR8VKtLU4fsS5yVaSs7nC8azSDKURI9F07RcP9jlyuEOJ/MNddORZQlp39M1NXt7n+Lo6AglRUy0rzfYvqbbLuV76yjbFpMV3L19G+E7BoXicG+GUpqqdZwv15R1zf7eHn0fcK4nHxYcny8JJEjlmIwKBkn8Pp13KBl151F6+FhVJqPpzjrwHqkUCLEFi4VtR+iRQWL7EAtsAK00wUfjUsxITTHZmIv5fRbNBU8/fx3vO4o84dXPf5ZiMORiNaepS1R0L8WAixCLuxPbTFsBh4f7MXVJma1sMmDd49l+9DNMd2aU53O0VKAl/8Hf+lukpy233/4zqrAi0ZJUtIh6zuVXXmEnHXB+seJH773O7Ft/g7OfvMVuKZnffJ3jj97j6cN9ZqMBYzq09KjhgEcPT1DBsz/OeeVzn2d2cJlUpTT7JU9fv8z5ySOW65KubxFtoFlF/4BWhoP9Mcv1Gm0MXVkivMXXntEsJxvssFpsuHpjl7fu3uSrrz5LuVrzT3/4ffq2By3RUsT4PG2iOCIuN3icM+Btv52qSYSOub9JktJ1UalUFEOcA2kSpJE44RkOZiAkSapiA+gDJst/bk39hSnueIFWaQQQZQlLD7GISNJMwXaJqqR44iKVIgYmKBlQMpBqHROQ2pa+70mSFNu3VGXJ/t5OZH8kOYSeQZrS54reO3rb0zQ9cqZp2oqu75BomtbjaRkUQ4SPm3+5LVDBR95GapII+dlqjWc7OzSdp2ktSnu0icN/oQxCSgQxl7HfBmwIJFJHyVuSBqpNTd2U9LbBi5JXv/Ic/92//be5dHCV3m744+/8Kb/7D/93fBO54x0tKkkARZJk4DzOdyTG4H3HoMhppceFQFIM8V2Daxv6vsdkQwKBwSBlnBVMd4cE2xFCj04E+SBFyDhmQSoCirp1rMs5zlkSk7FzsE+apYQQl7xSEN2lPcg4FUGEyB2p6obZwRUKLfjuP/oHvP/Ou1x78Qs89bkv4l1F1y35J//L/8Tu9ad4+ktf4GvP/SZ/dH7CycU52gWm013e+PAmOkAmBb/xq7/EdJw/2dO40CGIREgXBM+++irp5JC+aVk8eBvhk4ihdS5KKcfTyD13MbTbh1ggE9Hz6gtX+faP3icIhZCC8aigLDveeeenpIngxtVrgKTvOoQxNF2EztkQzWOnZ6ecHJ8QgiVLEoIP1L3l0cmSqndk2TAeZilIMsXFoqKsAk1dcrg/JvSeKwd7WFvG581Fh5d4XLTZ7qS2nfhjDMCT34VzBCeQKhZ7Z3ueuDcCSJlgXYe1DoLj/q0HgGc0SmjrDVmeURQZvW+oW4U2ZstwD08kjmELB/M6LpQjviFm9m7RrWgZc1+fdPHO03oLVU+eCkZKcHVgmH76VW5dPMI9eIf9UYKSOeyPmd8/wWkDjWJ6OOVTL73ML6173vzDbxPaClsI/uSnH3B1Z8oz164wyoekvWc6HFAUgtA7mk3FO+dvszyfc3h0wHLVcHq6wnjLYJDjVMFu0BwfP6JuSoSOJsLzBycYr/AdIDzeS3SuSHrNerlmnBecHZf89P3bBGfROjabVoJ0AqkNxgiMSbkoK4ZSYLYoD2ujPwEhEFqR5AVetBR5EW/GrqMvF/hsgveaPEtwraGtG9blijQv4u7t53x+YYp73/UB3G1EAAAgAElEQVQUWR5NMGmKB/JBwXA0oG0hSQxWVkROhnzCwBAi5ndKKSPvfcufds5iVEbUryu6rqezHUOdxwPedyRGMy5GeBewfZzZt9bR9T192zIcxFzT8XhC2zmcEASpaZr48uisxQiJE5rFck1wlnXZ8vDhKYPhlKZbMB5lrDclbe+pyobz83Pqqo0/586M5fw8vnS2B7DrO7y3jIZDXvzcPv/5f/k3KQoROxlK/r3f+WVeeWmf/+a/+h+QRPOJ7y21LdGDIXq8y+7OLjdu3KDZ1HQInNb0TU9VN9x+/w1cU9HUHTYUdHXPctOTKUhHARU60kRiJLR9i1YaHxybah4j1XrHbGdEolVcCOIj/lcatI6sau88XdvRNBGWplVUB+wfHpAMCt548/t8+MFd7j045dFqztvvvIZJFEezHb7z3e+ze+0qH957n2/+9r/OyWLOrCj4lVefYXh4g/duPQDb8pUvvYh0JYuzKubLuhZEZMY7G2i7GnqJX61YnZ2jvcMTsyuVjshULVUcm0kJQkUchYhLw5eeOeCf/eCn9L1ikCXxcBnPYrXm4aNHXL98BaEUSEndNhhtCNvxxoNHx7z3wQcQIvRpUAzo+sDpYsPZfI0PgbzISLTE4mnLEtcL2rYnyxXe2uh9GKe4Oro9hfexSBJRHBEREB3W4nEYxvYsPUYjBCmR0qCUwPYVfWNRPpoD67ah3NTMdoacHd8my2YMD2ekXqPTBKk1zsdFX7VZkeV5nLk/DkTxfovc9qita3I6mTAajZ84dxFiix+I3w9IXG8ZBkHZzlE+8OLOiOt7h3iT8mu/+dv8xfcSqvV9TtYbVj98g9005YVPf4rZtUvk45L7b33Ikcm4P9vh5IM5xgwYjHuWVcmdWx9w9WiH1AxITMZgNMQ6uHd6TrASnY/YLGtufvARLs0o10vM/S4C5aZDBoOcxoeonPEeT6wp3sU9Q1k5rg1zupVl4S33LjY8fHRMj0dLgXCBoASJ12Ta4KwlzzLsFsYWkE9w454eI/RWAaVo+5h5IEKUvSZGI50nuJgI1bc1dVVGw6X3pFoTrOPnfX5hinsQ8YdS5onfmfVmiUmjQUQLFRGxUiKV2hpnFFbGpYJ1US4ppEYIGAxGlFVD23RPuuwkzQjOxdmVMZRVw3JVMywy5vMVTdegDWw2FW0bSJI1qVYslw/pXEDXNo46utjl1XWFbySL1WrbGUGaafYPpnQ2xt9pUzCeTmhaS5alzGYTCEukCBzsz5iOUzbrhtlozGigsT0MR440l3z1t69Q5W/SIBiKp5CcoMh44XNTvvwrn+VPvv0+enjI4NIhSTFAm4wXrglEX7MpK5aLc46PL1gs57RlTdfVdJ1FC2idpbM+psJsLegffqiZTnNeeflZTC5Zrkq8i4nro+mYJDVRAqjiofUdSJWgjcI6y3q9wTuH1pFQOJqMeAKY2s6Fja/54KO7vPH+TYyUzG+uWa9rslRw9eplbFhz/9Z73PnoIz66e4fNeslvvHKDq7sZl57a4+/+t/8JIQSGhcSHhmAsg4EBOcTZlr5qML2gyEe0XY0yCRcXkraGwdAjhYYgkGEbVyhlhIrFhgrvPNYHnrq6z9HBLg9Pl6w2JWkyic7XPOPRo2MePHjAM09dI8sz5vMYe+a9Z7Wpefudd0mSBI9jOByCkFwsNjw6meOFRosQC7u1VE1DHzyJ1HjXM53sYivP7iwqqDbNJ1gBIbeQuxDiWdguSMMWHxDZTOEJZC9swV9aCZyP5p+2XIBtabrY/PR1jXI1RZLjhEIogzRqu5iNf47tW9oQOTouPJ7jixiOIiLj3XuBdZa2a7eI5Dij7/p+a6dnm9QVjVwhB6USnr02Yd1AJhYcTkb89r/xb9LUGy4ennD84G2c67noN/xo/jGz4Us8ev0ebXvOdG/Kq1/6j3jvZ+9y6/2fcfzoPXqfERY9L9xImY6G2MpyfHaBl4qu9azKNanSDMc7rJfHyDSl7QO67+nrlrpusDIaG63Q1E1P6h217RAelo3j/GzO5RtX+cl3f8xF26ESHXcizkWDXh+VZvGGFBsb52yE4gkVR1NbJZPYGiedc3jXkycJXd9R6DFd25MkBbbzyDwyf3rbAoFMp/RNj7V/DUxMEC3SD44rZBJYrau4lZfRLp3lE7R+FCPWQiziSmpwDpTCuobNuqIoUkLQeNfy4PiYsmqwdSBN4ox+c37BYDiibiq0zgjYWIwSg+1bMj2gbx1polguSgSeohjGGW7rYr5hqmmBPIlv5AjDcowGGdZ5PAFrLTpoUJKgQHhFXS5Ik4yuifF/XRet59oM0Upxvlqg9QjrBFmeInRPn9zi7uItdqYjNk2F0h8zUBnIKS//8jVuHu9w9+MzLh6ccnH+U+rViq5a07YbbGtj56UTfG9jHmeS0NY9SkukSem7Dp2k2L4Gpehby2pVsl5uGCG5fmnIZDyk7zq8s3R92ILXwEiJsw22BzqFUJrUGLJRXFjWdR3lc97TNjVamwiHQ/CVz32aSwd7vPbmzzg5mzOZFaRasypLuqBY1zWL1Ybedfzmr32Zy5fGeFfibEthCryr2SwuKA6HvPCVb7Gz9ywqDPBCsdrc5fZrf0J5fIFODBcXZwwGhmrZ4YPCBY8WGicEPI5iVGo7qoiLYuk8w0HC556/zPl8TUiH3D9eMBsn7IwH+NQAAakURhimxQQvPEJrys0G23UUSUJQ0fF84X18qRqDkDAbT+l7S91blpsaZVKE6bh2dMh8uWRnOmaSBxIht8Y+Sy/kVosemx8vLCHEpWVMptoepOAJvt+GZUTwl5Sepu2jqWo7k8/SBClAKkma5fTOE2SDCh5BSvBiW9gdYiv3lMqQmgwhY+dv257BMELNglA421FXAj0eIzXgojvX9h1GqfhiUoLF+QpjIJWeG9de4ObxCXtGs3swoxWwaVouyjOyl58hyTP2yvhcvvf+Q6hLzs4eUUwSfud3vs7H927z9PMv0DQrsk5DnvKzs5Lsw2P+1S/8Mr5MOfYX7Owd8PxwRL1Zc+vuXQaDCTsSlgEu1o6+C0z3DkFDvV6RGUN+qWBzPKf3is+8cp11Z/jw5of80q98nd0P7vDUeMjhOGW+3NALycV8zWJVcnGx3O5FBLaNOQ5GBGTTInK9RWfH0QwyNq3BRWFC3TXoqkYBKonc/OACTdcRnCB4u11OR4Xcz/v8whR35x0//NFrW6dW/OEv5itMklJX53S2Q6jo1IgT94DfzrZUAOUlvpXsHx1xcnwLT8/h4S7VuiN4y97eDmq+RGvNcJSTphlVtabvHMNBQt9l5IMEox27BxPqzccUeYYIUY8eAixW65gF6tutWUduZ9YZu7tTmqpBSkeiNcYk9M7HN3XwmFSTDzOkAJMYmrZHaUOwDiE9Whm0NlTzDSpLwSt+8ue32Tsvcb3hs19w4FdkhWNQzPjRDw2/9/d/gOt6fN+j0hxnW0LwDKc79H6DEjkmT/FNQ5rG+Dnr62iNVwZvLUmeR2JlnrHp14xHY4bjES6UcVTV9nhrkVpgZEq1KSPTJE9JkgSTJFHAQcBoE2esNj6AhDgLTpMUpQ1CJmwqy3x+Sr0qeebogE89dZVskAEepRK+94M3aAh86ZVn+OJLL7C3O0RIjwomvjC1Q5uc8e4uL37zl8nSGV7cB1KkzxgNNS988TO8+8M/I1ykHExz5ssLHBaFiPN19QmPxVqHDgKL3dIdo8PTW8vzT1/lez/5gE3bg4Bl2eBcIEkSbt2+zeHBHpPhDJEkpCKAUBzMxnz1S5/FGMW7H9ymaTus7Z6MjPb39wkBTi8WmDQlywzOduxOdzg7PWU4GiK848Vrewj6uIzzEo3Ghh7rbFSJ8Vc6eiLb/bEa5nF0HsTuUWlDlsWdTLeyoOJyW8q4kE3yjN49+ZInunkXHA6HCwGlEjabJXXVkSeSNM0IMganSFUQrKVvO2bTna2+HXCBttzgvMdq88T0NCwGlHXFpSu7yKszykFgNh1Q9x13Vwvqakm5Kzg/P2fPwY2LHrOXY9I5jW8p+wXjbJf33v4zzu6/RluvOJpocDPuPPwAHzzX9YBvv/UTsr0jyrWjT+fMdiakO2N2yylLHPcfPWI6HfHitcsxqEYoRtMh0+kBjx4d88HDu6iRwQbJq59/iXx4mbsnx/z5T17naH+PRw8esjiN1MdBphmqgCo0SiS0TlHXjt5FR3BQgaAS2taiJIjE4LxH2oATAZSk8wFro/x6s16zs7PDxckJJkm2zuC4mHXyMYLi53/+hcVdCHEN+J+BmAAB/2MI4e8KIXaA/xV4CrgN/DshhPn2a/5r4D8kDgX/sxDCP/sXVncRYrdhATxSCIyW7B5M6buczcWC2oNWYjtz37pXg0V6wHuE8KxXi8ipsT3OdWgdqKuWqqpAxM21RkFwDIuEZdvgbUBKzWZTY5QkSwRZIrFdz6X9GWVV0/aOplY0bUPTtFj3+EoU4rXUdnR1TTHK0MqQGE3XN2xz5RkPB6xXLXVdxQOLoGoanM3pOovrJM4FiiInSMHde6csvm9wr3sWF2csTjyffjFjtjvhvNb847//Gt7Gzqv3CpMNkN5EdrQzKJWSpBFlkKUJOklo2qiaEUIjhN6CNLcqFuKyuqnb2MUZTVN3eFuTpQnJ9vqYpIbJZBJNKSEgiRpsF+IuJKom4mK13nTx91U3WA9ap5g0YVBkTEYFAsFgPKZrm4hcNpKjf/mrVGXLeLaHp0M6R9vGUY+TivlZzeFRxvDTE9bmNnX4GNdpElWRSgFeQpYwfXrMW6//BXTgZMQPe+fiqDoOLXDWIpXGOfeEs+JdRFq0TcuNox0uH8x4eF5imx6hFHXvWaxXyD3NnY/v8ZmXdyKjv60xxjCdjRmMBpyenUZGD1ENYYxgNp2Q6ISHx6e0XaRyShHIU03f9exOhyw2PVd3C3J6fvr2bR48uODXvzXDe4vAbVnsj7HW8gm6mq2OPSKvP/GJCCmi1l5Hz4GtzTaeMeIGtNIIKUiUwnpBsFvkx+PNq4/zfqECeWaoyxKVD1FKAYpys2SoBkipkCqh6yVpYQhdyqY8Yb1acXDpCGlSXPDbWbYjeM2qvcPHrMiTQ8rlOYkLzP2C7GqLTBI2P/yY67ND2v0he89PyY5G3Ln1HuNkQr2o+OP/8++he0NfG46PT1lv7iGtYN1YjpXljjvnaib5rV/7Jnduf8wfvf42JxcbQlXx7NEun3rxZRabNSJLKTLJpml5/4N7lN1HJJOCo9kObjihrRYYlTEdF1y9cR3va1brOQ/PThnPhtjes1mVKCxaOHKh2B2PGF7f4d7xKWeLJb2w5FKT6JREBcoucohSIRA6whGlByMUrrMxWhS/NQi6bbMUCDLeGIVUZEX6c0vq/5/O3QL/RQjhNSHECPixEOKPgH8f+OMQwn8vhPg7wN8B/rYQ4iXgbwIvA5eB/0sI8akQiUP/r58sS3j+09dQLrCzd8CDh6e8/95NggjU9Tp2UiEg0EitcGK7oNkCxoQS6ESgtENKS6IN1y5fYbPZUIyyGGIsFUpLus5SVZZBltFtwy4iA9tglCFNJMiAUJH1IrYjILGdn7r1BmOixdv5Di1htViyNx1StS3CxCJtlKHaLDk8PGS9jkwaKTVdb2maGG7dVBVC7lJWDdIrlssVq3LF3u4uzgde/4sFsqh57lNT/uh/m/PRs2M+87mC3/vdN3l4a4lSQ0SSIkUbD6CQJHlK03YoJUiVpOkcyhjazhGIWv3gYm8mlUSpLTxKKFAKpQfMl2uGuxkm0eR5SpGnGJOS5gVltUZIorwyBETQ4Dy9i0qfpq6pq5gQUxQZxhh292YkWRpfLFojgsf1HX3Xx7BzH4usCYoOz2CcokWg73scjwuyB1txMB3grKXSp/j2XZzwZOJZyuUGWTTkxqB8QX5wFRd61mdLVDomOLDeY0S00eMcwUeNsdwibLUQeGujiklqhqnhmRtPcbF6n+l4wLrakGQ5vYXzxZL2vYa6ttx46gqjPMN6aNuOs/M5t27fxZhYQJVW5EVOEJL7Dx+xLCustYyHA7xtmI0HFHlB11v2dgYcTDIG030OBhohRzF+TSf0NoZeiP/HUQp8wpN5vFoNOB5nGwQEXe8YCLDWolKD7fvYBEXLKlLJrUT2Sa4ZIUT0tu0DuJ7UCNLZEJOk8U/oPQrFyYP7ZOMdtB7QdrDYnDPKp3hgdnhIOhpHhpP3qAB9J+jtnNMHpyRXf8bhtQmzg69weroh8QMObuRs3r3Lv5Te4NJgnz88Oebs+AyFwq1GuDJlefIQX7a0fcfO5csc7u9x785f0geBFh6fBz7zlc/xa1/5PP/oD77D6XKFF8n/Td2bxNqaXud5z9f83e5Of/uu+o5kkSWRFhUplC1YsBwBGcRBMgkMJIAnmWQWIHMDGXkeAxkESGzBQBIlcSLBNCGKokmKVLFY/a1iVd267Tn3tPvs5u++LoP13yvGkUoOnAG9gUJd7Hu6u8/+17++td73edmyPd/4919ltQ68+e5trl3Z4+q0oq07lvtLLl/dYbJRcn5yzid3HnFwds7VC5uMtjcoqwnX9i7ww7ff5MVbF3n+6lfJxxNCyjh8fMKj/Ucs1y1N12JDw3p9yLMXNrm0ucmn9+6hUVSTEt9KpnHnHEmL5JEwhKJoJYC94Ok7mRDYLBu08YO3RAWyLOOv693/2uKeUtoH9oc/L5VSHwJXgf8Q+K3hw/4H4LvAfz08//sppQ64o5T6BPgG8MO/6nsYq9jbmaJcj806RuNcnNUY2rWjLDJhqdghJeZJtxIlQCMZqCYlzjlA07cdBo1rPaNSGBohJRaLc0ajCQbhu1gryomsELWEShqjM3yQpU+QGiAddgh4J0HComhhOMYn+rbndH5G5wPdYkW7WKO1YrFuODw5JfiemALdkMoDwl7Z2dmh957Z1hZ+vaaocjayTbI842y+4tGjI7yHgzs1G3tjzg4z/vk/vYPKJlBOiU1DXk4pskoA/zYjoOlDx6ycQEy4FKmynOhr9BA8njBy+jGKzjtJdw+QFxWrJnDv/gGb+S6jK5fJjQQ+qJiwGiya+emcCAJCUkoucpNRljmjasrGbBtUwlroOvmduCGtPtMZMSoiRgiYBrJciwlHCEM0647zfiXB2JOSkcpJRJwHdEtSmrS6y3H/FsoqsvRTivwapt0hxgl5UdA3H7F19SYbZc3J8ZzWNaK1f8JaYYjMSxGlrdAOY6CtW0bjDUxlBQyXFVTjqTBXxiMWqwalAyTNat3xzru3+eijj7hycZfp5owYA/VqzeJ8ye7eBnmW0fWRxfKck/kZSVmSgumkYlRqimzMxqQgEVj5xJVS8Td/41cYTTbYtRlV1hO6IIlZGKSfGzhMUZaoMYZBIZMGA1MaRmKD/NAnCH4IpxFBpDFa2OE2A6WFv8Qw5knpqaQyInuWhDhdjVYSkm0kBTwvRuhmznx+zGKu2Lu0Q1GNyGxgtLFBANqmJSlIXgJBlsua/YMDoodxk1h8+DMuT7Z57Svf4nh+Tr8+59LWJvX+h/yPP/gR3/n4I2bbF7j57AsoU3B03uEp8LEkAFeeu8ZqpbBvvkPnW8ZbG/zd3/sW0/GYP/wX/5IYYWs85vUvPceV3SmfPao5OvyMX/3Ky2hrhWOzscGzk5LT4zPu/fwxZ41n6TuyTHP1+jVWXeDa5ohROcJqy1nToWzGRGt0adnc22A0LZiWGctVzd17+yxX5yxXj7m6u8s3vvwsn947pBpPOFqv8G2PzixRKequZ2O6DclTZGJbMAhcMMRIlmf0QYyZ6/USdBpGauZfL6X/34r7Lz6UUreArwF/BlwcCj8ppX2l1IXhw64CP/qFT3swPPevf61/APwDgKLIBrCRobAWlRmsFUaM9wkqg0eBir+gvkiyjACSlmzUcqJwqSMfaeqmRllF3Xes6ppAILMlZTmiWzdyMa06kZ9NKtp1je89anuL2gcigeV6zf37j+SiRDMaVYQ+4FuPyTNSgDYFNmcGg+LqlR0Oj05olUUZRVUVbM7GjCe7PNg/BNOSohDfyBJ122BNz/Z0wuO+ISk4P28oxpoLW2O2NypOF56k4PQ00LY9XUzY2KFshUsdNhmsga5boWxO8gkTChIaF3vQOd0T4p+WhdiyWZJlOdolPAmSJkXRSQdXs172nByP8c8ntIokbzARDu4csl6t0AbGk4rZbIK1cjPN8pKqKkSHrcVopLFURYnJDHbA3ho0SWsCPfV6Sd8sh5ukRllFnhWMZ5tM8gJij2vqIctTk08nlCNhmy8PPuPYHIDycvPJPqP3uyg7IzQ9t0avMh39DR4//JBu3aCNcFCCtagoHa2PAeVFCplSQCdDVImjg8fsmgKnCwgem2sm1YRHZwdMqkr47auGGAbJmlYsVkuC7wWVqzWzSYW1hvliSe9Eaqs1XLu6g3fycTmJqpCl88m6wwDf+sbXGBUW52pZVodAVMITMirhNSQvGvOk5Gf3nqcETz0UbwnsCBA6UgTvusHFLHP4mCLEQAw9XlmyohDFS/JAICYtCU2SSznE7WkiHh0tIMoPZWCysYGbL0G17OztMJlO6LsVyfUYhIYZhnFPJGEMhBBZNYGPPzhlYioefPqH/PrvbbF9+Qp3D0947+3bfO/b/yePT+ZkBs7Pzrh39w6723tce+EZUYRFjW81k2rG5t4GdqNiJ434T/+j3+PBz3/Ojz/7PqPZmEs7G/z6N77Kn731Pn/+sw8IKXLr8jbPXb3Aw4MjilHOg4NDlifnHO8fMneepXQSPHvrKvcfPOLRwVVeffU1di7tsewdp58f8Oa8BpWTV5qLF7bY2hhxpgzbGxV/85tfYVRmvPPRXe4+PGR5vuLi3oSsqjg8TDhtsAmCj+RW4X1HaS0qaULfSI2zGVlRMdqYMkoG33uSzbBAYQt0lv3/U9yVUhPgfwb+q5TSQj3heP4lH/qXPPf/Oj+klP4x8I8BRlWRTk5WgostC1YOXnjxJS5dnNKvl/SdHBkNQ2IJ/IUDLwpUfzFfMZrmKOOIsWftexZ1zfnhEb5NdH1P38mb2ypN2zpiEga3jyLh8l2g63pmW2Om44o69djMsr27zaef3md7extPT5qK6kKta8oiZzyp0EZRFBmZzWnqpZh8csu9u4e89Mot8jzHqhKjW4zS6Bz6vofRCKM1o6rCWHFXjkcbTKcNN25d4fTtT8mqTSY7u8xPF2ztXWV+/Biby8ssiFANOhPziO9FBaENPkSmpoQknVlmLCjBjIagyG2J7wNFnlO3DSKaFzv74ck5J6drChvxfkFmYTyt2NoaM9uYkWWWvm/RKmG0YlRaoTla6SZS1LKwDA6TIs45UhKed0L+nSjDaDqV5RxqCMweohWtoVlLp2dHAiHLbE5bd1SjglHzEqH5Lgt3TJFpzlaat/58AfkJu+WIa7/yrHTkecGtV7/E5x/9hOADBi1IixCJPmAKNexrAKvZurhDpMI3He/c3edsfo4lMW9ayqxivVxTFNlTFVFZ5PRtR90GyjINi2dDWeQsly3eBaoiZ2tzJJJEJ5b7caYpMkvSlrNVi8XyjS/f4vrlHYgekwwBL5iHNLg8gwRpRB8I9NINpzB06XJdaa0I4rKT2EgS2iR82w3AuaF3V4LijSEJ6TMTxU0I8j0VZqB8Pble5dTKE6398F9MAW0s08mEphXs7+npY9QQXCJuWdmP+Rjw3rNa1BweHmGsQeUlF29c5nf/k7/PzsUX+aM/+H1e/MoL/MHbb5NSxuXL13DOY0xC2RKjI/P9B7RZSR0DTdPw7T/8Nt/623+HV154lq+//iX++be/w507j3hmd8ZvfP0Frly/xne//xanywUpJK7sbPLGG1/h808esTFK3D064rPP9zk8PCFXmqhhOirpes/exR3u3Tmg7ta0fcf1a9eJSbNa12gdafqatVMcnyzYGucURUE1KfnoowOKacXrz1/htZdv8fn+grt3H7A42ue1W9f46O4+jU9URpHpjMLk8v4IHlIkJghR4dtIvbRYU7A4XwroTUeyIsc+Gan+FY9/o+KulMqQwv4/pZT+l+Hpx0qpy0PXfhk4HJ5/AFz/hU+/Bjz6wq+vLcZMcK7h0dE5k9Emmxe2aJoF9WJOCAXWgIsQtRwTdZICoZWoZ7I8w2YFLkWCSpyuT/Ax0bg1s/EWF7ZnpKDJSwlE7vsaay2jaQUqElKkrCoBekW5IH0bmcwmNF1HVY3I85x23dC6Hh8daCTOLSiaRtCoMQW2d8Y451jVjr72PH58gsmVdJk2kGWGtg2yA0iJ2jd4hGo53drCecX2hYuM967xaH+OtxvYYkK1Ybh8/QbL+RnaKkw2KFLISTphTQSv0NrinGRZRiumIqM1QQWU9lgDySTAoFMPdsDsJkUHAphCEfBMZ1NSAKMCWWZJJLp2RZFPEbNFJSOClPAx0PX9U/edMYJ1sFZRFLLg1VlBDJHoetYxkhcVLoanag81mEhU9EQX8M7hk5XuMSQ65xgxpogb3Mr/Hu8d/iGreMC7b2uOjxK3rmzyrZf/A3bzGyQ0u9eelS4VjTKiMlApDa+JEBMHbi4AvfNMZpZyY5OffedDkoZJVXKn2WdrY4P1usYnqDLNuBqTYqAsRvS9Y77sKYziwlaOthq/DuztbqIIQKDvHXmekRdyI160jrZr0NowKRPfePVZkncEZVHKE1wnM9go/o3oHCpCCoEAQrIccmelk3/iXJVRjRmi8/JMUSv/lNKITiQvfzY2o13XQ+j4UPgTRGSJF32U6D0jo6wUwyDGHLgySaGVwehEnmnKDEblWPTdSQKgGW7YznuhHirFaFSh9YoXXr3CKy++xNHhAT999y0u37jIz372DuPNnEd3W25eu0kgsTpfYvNArg2f3z9gOikpdy6hysiFvZLdHctXXn2e7/zxn3J4cMLLN1l0SHAAACAASURBVC/wO7/5dbp6xbe/813O+4APiVs3dnjtla/yx997i69+6RnufvJQiu5qTTSaTikKY6iqgqQU/brm9dee5/lnXyaGxGRScvPiHuuRZmM2QVBNGSEp9o8eU9eeet2jM0VZWO5+fsT7H3zOeDzmtWdusFhf5OPPPuOFa5dZtA11uyJlFaFvaVuFtQaljPD/lUaliE6QWZmxF9mwGzMa33dfWLf/TdQyCvjvgQ9TSv/oF/7qfwf+PvDfDv//337h+X+ilPpHyEL1BeDHX/Q9siLnjV/7dR7eu8Ppn/8MnSzKWozWzDamVFXGernCx0huC4nvGmA7KMEPONeSB2Ev5CM5Tscg9ue9nU2ic2ilyAvL6dkpRid8cgSfOF+fsDXbQ8dBYqbEwWozTZYZlnXPcjnnbD5CG40y4oodG5HZXb64SZFLpzUaj5lOLU3TsndxkxgSZTWmGlVMJntykYdIXozIspxAoGlWTIvAeLxFno1Yr85YtWe0rkXZkqQt6+WKtu/56KP3hyIYycoC17RYbSltDkGJwQiF94FSiWi0C4FqsMCHmERVgULZnJhWgkAwWsYzqRW7+/C78b5hXFVYnWF0Ruu6IXRAUmNSFMywC4HRaIS2mtEkl+Ku5O+88xgtmaMqJQiJ4HqC6zEK6qYm0xpjjThike8/HlcsfUPwAYsEmV+4ehnlIynmbPhX+OaNK5x0n/DMtEMz4/LWdQomOC/BEtYWtH2H0XJxCO88yGuoJfRCK03yUcwmEXIcd85qHq8CVQFXr91g9PAIMGR5Tt/1NMGjU06eZ4zKitL2GO3p1jWYnPmyJs81mQVrMto2YmxBUoaTxVIuTKUp8hHL8yWv3XqB7c2CpqvBWEIv+OREpKzGLFYNBQGDQKi62uGjJddpcGaLgUlY14MUcmDQyNJczDMxCfFUadD50MiU+VCs9TCy+QtZ5ZOOXRsFvdxgGcY+Kqrh9DB4BKInhZ7eB9zQsYcUxSwWhTXfth2LxQrnVgTnWC9r1ss1R6e3mV24wp1H9zDG8OqXv8ZHP32PR5+8hVcFz966ScDw8P4+oypjsVqi1z0xKl770lcxDj67d8TjoyN+7fVX+ObXv8xPf/JT6nrBle0J16e7jCclX//G67zzwR1+91tv8PDRI0azkm987Q1ykzBZibY5ZS6yTa8ENbIxHTHJC/SQ6/xbf+NXmJQFk1FFApquZdV2KBzjUcH25pQ8FiyXDSF0KJNz++P7vPnzd/nqa9f5e3/3t3nrnQ9YrM/YHpc0wbJKntW6YXNjSop6cABrkk2smxXVbEa1MaZZzjFoMqNZrJb/dsUd+PeA/wx4Vyn1s+G5/2Yo6v9MKfVfAPeA/xggpfS+UuqfAR8gSpv/8ouUMk8eJ/v7LOZHbF7cJkvFUz6FAoqyGsA7RtKI0pO38nBATBo7JMJbY4iuIbiECjlb0wl721scHOxTtz26UiidaF3P7u4GJydnTEYTRmVJ9Im8zFBGs7W7w3K+pmsbxtWIF198gbLKhR+hLSkKWyUR2ZyOKfMCLMw2L+N9JMvGBOUIfcCaAtC4IAoT2paUNPWqp+4aFosVfXNKUa1YLWuiazg6mVN3PevO49Ua3Qd8EHVOTBEdAJURY4OopDSuC5gSMq2o20RfJuzA/jZlIdwPBzEqbEx0KRCTwiQzZHQCPMm8TGTGDjLNFbk1lGVJUpoiL8nzgrIsyYsC571wqpUitxkheAmdVhE92Pr7vsNk2UBOTHjn2drcolmt0UkRfERjaNoWHxJ5NaJ3Nb3zVMqiIvz89gdkZYEdln7mCRjLZmQJVOw4Ov6EoCJJZSQsJEfbyM+T6bEk7QwehSgpKyhtiIidXqlEryvevP2YrJpw+eI2Dx8eEzvHvaNDEp7NjQ2atqZVQZbuDvLMsDUtWRBYNR3BB3Y3Rlibcb5cobRluVrRO0eeGSZFic0yVnXLc7eu8ru//avi/kyGFDQptKQgy+isqJiNJqR6IXpyFzlfNBzsr7j+zJaon1IakBwyupH2OkLSKJWkE8Sgkvw7hUo4GKOUIqaItbmc3JIo0KTrHnTzAokXJRFPcAJhyGE1T5uB09MTxpORnICHrpPhpBRDIDrP+nxNs/b4BB9/vM/e9hXeef8zTk7+hOOTc4gGW0Y2x4bO51y7foM+OJre8+rrX+X+3buMxzscnz3mxs1LVFWJzQQd8caXX+T5m9f43r/6IWOreeWVFxlVU8ZZyXnf8H99+895+foe61VPCImvvvgKxWRKnhcit33Cv+kdPgFeRk3L9YJddQGLJqumLNuePgVsplA6Zzyq6NdrHh7Meev927xy6xmu3bzGeq04eLSPmZRcuXyZn7x1m/bFwMVru8z29rj94WfY0FDagrVuSCqgjTRnMQrCuchzVvWKkCDL8sFQ2FOW/5ZSyJTS9/nL5+gAv/1XfM4/BP7hX/e1nzxUgsXZEd16xeLknJ3dK8QUMcowmYypm0bivLRIt7SxkhQ+bPV1YsiENBRZho+BPgXG4xJlEutuwWhjTJU0eWUoyhFtuybPcm7e3CaFQFlUVEVF23XUrUfnitnOLmUms+N8NCPPDBuTQnCr3mGMZdW2LFcdi9SBjtTNEX3vWa0iTdvioqfKFKdn55yerui6ll42YNy4egnXt0w2ZlzczlnOD/jszue8+twzGDomkwJ33IBOdHUNFpyPgxY7IxuNUaZF+DmK4Fsys4FKGk1LkRf4PkEvSgmCSOliaolBChwq4FwHXmiVTmm0TuxsTtAqYpRlOp5ijcJmhs45Oa6HgFKG9XqFQro4pRGKoXNiGFJI7q2xdH0niT8Yoo8sF0vOF2v8cFQ3VhNiQg9ml7JuyHJhXOd2g4zEZDJm98JVfHQE1w6MclGAYITT0dUrjDJU4ylJRXTy9J3n45O7UtSTaNyJCd/L0izLEuQ52gdc8Di9zZ1Hn1LlFt/17D96zPzkDBKUeUm7rqnGFb3v0ckOHWqiaT1lOWK5XrK7OWE6rli3Dq0M66Ymyy3jUYnvG0JMnB7N2ZxNuHl5j9j3kI0G+WIQvYDK0Hiaek1eCTrDaLGtjydTLlydMJ6WzJsVvyiCBLkuQkpYROsenEJLCrZo72PARzewmaxA7czwFVKU+L5fvOwTqKeIA54ifVMUU1hCiJOTyUx+/hhFXZZEXRNioO2ccJWUka+tNfcenPDVuuX44ID1+QqbBHLXLaSJuvbCNR49PmQ9X6LLjOlkk3Iy5vTwCEPC9x3vv3MbWk998pDZxhaffPYZ1y9O2d6c0PQtMRgOFocEZ3nxxoz7Bwcc7B+SZQUPHh1JYhhRXhcvu4LeeQk2iZGuXfIb3/wGL738EqB46913+fi9D9AmSXBQTHKCMYncVnRdw5+/+RZ5bnju1gvcuH6Jw/mKd29/zOJ0TrT3mE13KSrLS196lnuPjuhOT5lSkQj0TnTuIQSSUwQrApK+bSmsISVFlomg44sevxQOVUXC9zWjakQ18jILjRGcZzYqWODxfS9jGDkpSYcygJlsXvHGV7+OLQq0TuQkMIbetahM0zjHuJzie0cf1nS+Y1k7+hw28wm9D2iT6LrFYPyRUOiT00YKXxIo1dlZzWpR4/pAWzegEsu6pTCQ53D5ygW6puN8vuboWNCl127usn1hl355hvaRyih848iKnGpkmU022NyacWEjY1NlnBwfMS5ztqYVD4/XFFaMUyk5UhBsqlWgQ09mxnQpoFIQaZ8d4ERRDC0xaHxoUVbRJU/0iWRkpt53jrzMyZQR9KtSMk/VlqLQbO7s0vaB0mh5DZSlWzVEZbDakmfl4I6MAs2KEKOk+Li+I3Q9YTiaKzRGC1YhKsWoGjHdGIv1XyvKokSh6XygnEzFgNa1KBWZn7e43pNnCqM0zntIQdQXQS4CUCTnICSOHz/Ge8eNZ54loFiv1uSlxTkvISchkrIMpQ37B2dcvbaHDz1GlRRVwSrtcPvOOR7Pa8/d5J03f8b58ZE4Oa0mz2Tx1fUteZERomAZQtB0eKbjEWVmyG1G03YslxLavrM9o2k6zk6FeR6Tx/WOCzuW7dkEbTIiEa2lIdFapLjR93RdQ5FrQhCna0qGK9euyKw29LTLM3kNkozBAH4xizjphOsNSkdSUjzBscchg/hJ2LVCun7RzQcZvSg5yYUEMCxIhyVvjAP2ICZJp0xirDLKkFBYy3DPiRgSISm6Vpa6RWYpbEbyHbff/pAUBIMb+0SRaUodmU4y5ocP2Bpbnrm6TTYyzAoJvG8uluTFlOXK04UCt7jLczf26CO8884xH3ywxBq4dmGTF597jhQtV69e5LNPPuXh4yP29/eRU4kGJWMQ+9SEJwYa7wMms8QwmCO1Jg74Bte3aAvagJIuBnykcWtAURUVMSXe/+QOH316h2s3rvC3/tY3OXpwxI/e+YCty5e5+/CUdn3Kl7/yGtXdgvPFkmV9ymy8zcnJY1QURlPjAluTgtB2eNcTUbSto6nbL6yrvxTFPQSPNZrzdcv5fMFsugUqEboV1mj2dqc8fjQsw5S8ObUxEvWVICTPw4NjNre2MCpSWce68zRtT1COZdsSgma9cKzXNU27YDadUK9XFIVltrlDvVyhg2MxXzAZT7hx8zI/+eknKGPYnGpeeuk5losF86Mj1uuOhBJzjxL36aUL2xSlwecGo0AnOQ187UvPEaPm6OiUopTTRlEZQV1HT4iJerVkfPkKs3JMVeb44MiyjLquuXThMvfu3xeZXZTuy6uEQeaoWSFJ6SgDaJyXm6DKDEPFfZq8E5MnV1YkbzGKsxc5kitreBLw4EOi7QKdgz63qN7RBzH3hBjx/ZrFckmWZxJhaIY7roJqXGFsRmYzsswwmc7EjEEiL3KSyoe59QpFGkJXNEpprBJ0s80tfVBPbAzDWEAMNg/u3+fC7jYCcjTS6Rojsj2d2Lt0ibatZa8QGQJFzFPXbEIAZi4JkiIvDSRFig43usB5fZGT5T5fe/lF3v3Jjzl48IAiz7CDu1kRyfNK+ETGkpcy6jBackUJAZMgeM+q7umcZ3Nrk7puOT6aU+YTTAbrrkEZw9l8wdHRKfrLr+CNx7qWpDIpGGLBJjMKTcCqJLA6NG2zRIeetm0IoSfGAqNz+Z2HSFJRTjbBobGkKEUsxOFGPszjQ4wYI9LKJxLKlJ4c1YdOfVClESENne1wS5XXUw0ZTVpTjiaolNDW4r2XU2YKQ4yfkkI6cMxVEiPitOrZnFqsFXT0ZARFHrEWxnlJbjIUBhMzSJpoFZ6SFC369JSLz1xj3Sg+u/MpXa9JR0fkKZJvTrl4eY/VcsHrr7/Ee+9/xun8hHW9pCgyrLEyNrTio1EwuN8tTyIMMSIuMNpKGIqybE7GXLx8BVvmwws1GMhifOofiEFe3z5IVu5iXvPmj9/i+RuX+Z3f/FU+fXzEG6+9yO//r3+Ic45Xv/w6LvasFpYu1Vy/cZ2D+/tEbdBImP2T5suQ6NqGPPvi8v1LUdxTkuP4qp7LIiNGvHPU85rbTY1KhsVpR9CGqIRD8ySwICVF17X88Ic/ISmL0YqtTUUXAvXSUVWGclyiyVmc1mQVTGY5KjVMJwUoT7M+Is8yRtOcUbFDWWRMR4ZXX7rCsnGEtuPxo8fs7W0zsRn7j48xxpBZg7IGqxV7e3us1gvQmlE1xU0judYYW9LWa1SRo/HCpx+PKbOCrY0R8/kSpRRZOUJZKby2HJEHuHblAu9+9IC+8cMbT465pqrwXcT3TpZvnROsrjWgEsZKKIBSgmPVyuB9EJtQEsNR71qRJGYZfedJ2gJRZq3Bc3JyTNzdoXc9KWpsptnZ2mG1XjObzJhNZzRtQyLKkhTZ9JejSkLA23aAhUmR6rsWYzRZVdL3wreR47tgC4y1aJXItMI7J52vcxAjmTFYHcms5vr1q+IODn5wtwY0YOQFIgYYlTmZEU52ubtD61oyK7P/pIzsLLQizxwqKLQtifkGZ+kCP394hk2JT957h/v37oJW+AHhUKgneIJE9JG6aSnyCU8YL0ZpcmVxSjg7jeuZbcxY1y0nx3O2Nvboup4+NuTGgspYr2re+/kBz7/W8syzF0j15+hkCQxOaeTob7RU3Koq8CmC6kghkFwD+P/HuMToYewxFJwnMXwoubaedKfW2qc00ydb9BRl7IfWfzGUedrZyyPGOFx7cUhnkvi4GCPL9QqrFePxmBi9LHBjQqUgssyhMHnv0dFR5ord0lFkRoKya0dxlijJGemSUoOXMCP5nWpILtK4Hp8crs6ZqW3uf/IxYTqiXZ6RN5BGJS4YLlzc4frFXdbLyNHxQ65cvcnj41OqsexDirxEDbjqPMuE7hl4qhzS6i9ucCk4jC2ZTcYUI2ErqaSfnnyVBmvVIEE1eB9x0dP3DhcceWY5Pl2TTpZ0LrA9zdi5sMWnj05o0wd8/Ve/RugjB0cHHB4fsXNhm+OjE/AK5xpC8oKLQJzUJv93oLgDdM6zbqQgRDQhetq2pgmJ5fGSkS2ICjxGONVEGVP4QKYiVCVJD6z3PFLZAqMyfN+Di3RuxfbGlK0LY4oiR2sJGJjPz0jJDyHSM8hKZhslKXhmVcaFS1scPp5zflaTXMQUmrxUVEVGkecs25bOyazWe0fEsGoaRuMKO0j8ysyytbHB+bHobNES+jHbmDGvG6rJjPNVS9efy6K17mmbnu3NCUWWWC3DcEGLcy0vK1rtic6jCgldMEmhbU7XN2S5pNe72GFVhtYFXb/GmoQ2itbJ+sulhI6KpCHPMnznZCZPYlWvKIpLbG6MKKyoSsaTCm0TVikyA03ywt4fikWeZxJfqKJciCah8BSFQWPJC0tVWZq6J7dCxlQgnJqgZC7b1oJG9U6MO1YTQkfnvMy2AwTnhgIjcjyQwhNiQCcx/Nh8KdLAqPEI5jmRCMmDyjC6wKiGhMHbCX15i4f757Rtw/s/e4dHd24zm23QOC85sb1jNhnTpx6DzDzrtmOd52RKiyNzNMKiISlcjJiiwAWYz1dkpiC6gOs6jLWiXPI92ljuPDzg29/9IX87+y2evTCDQSUjmIin0nTZZ0ZQUcYfKYL3UVKPgBhlXGW0khFPehLsIQRxceQyLFCT3BCR2fqw95Rl7NPtenqq2pDUFUiEoWMfHokh1UnGNVVVUOQSAp1bOzi5E11wIsOMkYnJ6U3J2NbQOGZ1ySwmUuPQIWNWlmgSRktADgmiUoSohojHQK5zfFJcef4Ktw8O6GY554/XzIAHBKyFxdk5oe/ZnF3iB9//I7Z2dnh8cMpoNH6KhTCZIKBlEpUgSHoYw2sip7VE1zmaZs3mdEZmRKKognDcMVZuXFZyJJJKZFkmS94ogDbaSFkIR0ppzZvvvM21m7d445Xn2T86JMXI9/7kX/Glr7yCsoq7dx6wWC+4ePki67olH1Wk0QitJNRova4xRfmFNfWXorgrpXiw/5jT0xOSN+xcuSqLO5XY2BnL8rSJ0AkMnyFQ9olJw5oMUxSUI0u77hmXI1Ztw2Q0ptM5yiR2ZlvkJqMqcrTOMVYLnXDd8ezzN3CtZzoucY0h9j0pwsZsxmhqKapNVus1zbrD5CXjasZ0XGGzDB8M6yg8lfWqI+icvou43lGVBeNJwYcfH3FweEauc5q+ww1JSKtFRWlHEBVN26KVpMbnWU60juB6rl3bo+726b0gEmLwBOfJqxLV9KRcYvKiMrJUjTUG6dZd31MVBqUiiYhRBSEghSZ5NJqkBHqm8gJIWC25qVub22zMJhjlKfICBn14kWVYpBvf2tyU+aNzspBTomdOIUkogQuE2A0/F6zWLc4nfO9YL9eDlhdsHtDWolNEGdH4SgyhJstE466JFHlGNR0Np5BBLTN0nDHGp91/SpJLmymFxtIHx/H9YSYtrgiUieKLUBkhu8CjM8el7T1+8v03uf3zj9kqS/CJXGe4KGYqgOlEQsFHVUkXRdNstWE6KQhJD3uBQHQRTEHXeWJUbMxmRO8YlzkuJurUknSUnydpjo4k9u1wMmO3TJgk0DGlFM7HpwtInbTcDAFtLXVdP9W151kORhO8J2mJm4wRlNFkVg/UxwGQFmVfJYVb/UJn/tTjihqWpGkYz6AE4yE3VvX0455II1NSnJ6cURYWneRznXeEGOj7jnrdslrUrOs169YTlAS/JyfTf5NV2KogVCNG0xl2YwsbNcfvvoMpoRhiG73OcCqg2pZ7+/eJ5ZhMlVi9ZjGvycsSVRTsbu/yzM3n+N6f/jHORfp5jXOBFKSZKfNC0sN0RggJFzw66eEkmUECEwxKCT3U9T0pJSzmqXjDWgvWYpSMY4IWEFuIkaLIhxGNpbAywokEgtcUo5KNrRl/9O0/ZXuz4MXnnqWrHD/+s7d548svcuXiNp/cfUBAUeZj8qzCey97w7gSPbxOfNHjl6K4JySJaWdjhnOa1DtSLvP0zUlO8FNOVickZeWtFxD05bBUDVoxnhYYFGUV6V2gsgW991TTAqsL1vM11U5GNSo5OzknkCjKMWU2YjKacN4uSMFgMkNe5FiTc75cMN26xOY0cf0Zx/H+gq5eEXwkYOnrjrpZ40Ogq3sWywZtAl3foK2hiJ7xaIxre8o8Y1xWRBVpFivyyQZN59jd2eJkfk7wFlOUZNqgwpq6dfS+o9IZLz17mU/vH7FYe+yQ7FLqDJ/W0hVoycMEocURpLMjWZxS6BhJxqJMelo4jQ70pKfzbm8CyUeUhFexXNScL1tUHkguSJC3Fxmhdw6jDWWeD8u2KBAyawcJ3LBGNWYYCcThtGQp8gI9mmAzS1vLWMdkljwvcF03aKoNvnf4vqFrHXo69J5RoTFYlQjRScc16LCt1cNeQWNsgYoRjeJsdUqVlRgjrkydPCFCZjWYnEZf4LOjQGFavv2dP+FHP/oxm1WJQYibKUZKqxiPKkpjmOSWYGVkcb6s6UKkS4mT+ZIqn3NhZ4PNaYVG4VzEtx0XtzZBKfqoMDrH1S0qClwu+kBlLY8Pj/jovbcpp98kBsvFLCe5hjgglKITBUuMiRSErqiVZ2NzxOJ4KZrzQT78JFRDEBACRYvK4xKoGIb3hjQAkUiKYIwRZUsSeWOMkb+A2AyvnfIiHcXItD3FIQtKSI8h5Xz8qGF3arm8WeCHG4aKCeUTFk1hDT6vGPU1fRehyNi4dovCKq498zzVxi5BF+R9T5xus7z9c6rSUpWSztb1sOgbnNa0uQXfMh1tcHz+mEsXL3Bed2QEus1dfvXXXudHP/gJZVXi0wrfx6fOcTP8blOQG9YT1G5mClkoRzFzGS3NZNAi47SFxuYSmZmUGjhXT/YjYDMrQS1RfkeSXtbJPitB6iPaGr7y4rPorKTpW07XkQ8/uc/rX77F9NTyZz/5Gb/5W99kuWhpcTS+Z5QC+IBzPVonRuVIGp8vePxSFPeu6zmfRzQRm1VihnCOEC02m1BlAasMQcvc1ChDCA6N5DPGqBiNRiQnQHuUpus7tBmhjZG0nNMlnsRyUVOUOVmZMZ8vUA4+v3uH6BLZ3iWhAoZAyBLHpwv6GLh8a5vptCILGW2nmc/P0LGnmk5wMRJ8y3x+Jp2QlcKbFWMMUWSSyxplNcYorNYiY1KKiKVpOhSayWRG6yT8WpkcF1rwgRihMjlWaWJI6JTjQo+xOV5pdIzkNkMh4Q1oQ0AWr2bgzaPkOEsMqN5BZlCZvIZKaUltwxAUAyVR0zQt9bpnu8jJ8/xpl5mSEievMZRFQUpRSIPGDClZ8vnO9aJBR2bc0fUkFfAa8kxT12vq1ZrJeCTLYg2urWVJiyW6Xrj9w25lONHzaP8xFy7toc1AmVQD/hmLTp5EEJ2+tSRlKIsxeE/0DhfBmIQ3sqRdu5I3H67ZvDjmO9/9ET/+yZuMS0tVllhrBmqmET6/tuTGMiqr4ZSQs390zM7WFnlWcnB0SAqOddtSVAVGKaqypJzmFDanbhpyk9M0rSieTCZRaTaKpTzAux98AuUGF69dYfvFHVK8J4HkoR8SkJ4AvQYXaQikYQeQGDrqAWhntMYMqhcdFUoXKJORVAYo5ucLdrc3hytwYI4PDlYpVqKUMUoTvARtpDTA9NITr4nM9o3KUCbjvOn5p//yNi9e3+Q//51nyUIaxks9Non00hLxbYNvHZOxJV9rCpujm5rHtz+B+HN2ty5x+OABbfJsakuRa1yMNL0IJYpqRK5z2q6m8Jqj81PiYkk+0WTjEsYWB3znO9/nmYsz1m0z1InByzAoYfLMSPj4E3lCDPR9KwKDwYerAG0lRKNtahk3JrnB+hBwzsmuK8UBe2zouk7GPsbIyThEsiyj61q0Ednsl16+yU9/9hbWWEZ2St2tUD6n94GdvT0+fv82L7/0Mu+9f5tEZL1uyK2lmk5Yns/Js0JmdF/w+KUo7ikltnY2aZtOzDjDm7RrHc26xzktI8AQSVoRkIKSiINsK7Jer8SFmhSKDK0kAcaYwHnXsbk9IyqP0rmYcbQhkdG2a5595gbNusEDk/FYlneVYbwYMR2NSE6O8H3sGI0rxuU287OFxIp1HVmR0TcteWWZTkuqouTx0Zwsz/nBD35K10c2JzPpipLMzWNyNJ1nVOVoApmVUOcsg8m4wPUdmdVkNmd5NhdlSWblTTRs6KMygvq1hq5tGY/H5MajSagowcUueJLS2MyS+oQjYXXCBEMVwOicXjnpyKwlRCkeKSV6F1AqiRTSyEWhlJa0+xBgWPZ5H1BOZu65znHeyZIcBSng+05uUlU1uBUVfR/k2Jo8WllRcCjEwPHEQao0Xe9IyGgiobh58yZJDZb7wVEpNxQp8CmKKkiZRL3scTFntYqcNYrrCbTKsVi0qrjvch4t9nl49Ii33/tQdNrjEqMsNrMYa1EJMU0pnrotCyNhLK+99CKH50vO5ks2ZuIF6H3PsnEUmSbFlllR0bUdKQo6IYZEVVYyKtGGlDxRlVRVjGbFDgAAIABJREFUxdlqxaN79+h8T6UcL+yVFNaTuoQ2EDxPXaf6iRFpcJT6EGjOl0wm48ENHPDBkgjkpeV7H875ycOG3355REyKyWwLbTNcW2M1w3uzIQFapSGIxhKUpXMMQLSMPuasasPaedZt4HTRsGzP6ELk0/sL1l1N50YoZdGmk0QHo8CIWtBaxWhSgdYUbUB1DUeff4Jp14zyHKsND44+R3c9tiqoGWOSpgsOlGJnMiWfTZmnRHi8IlOafrnEuMjZncf0eUdz5Jm7SJsb6llGXuYyxjNi6Ao+SdwisrcIKQgT6ambVnZ3aTB89X1P6HuW6yUGjyS4OZwXLn50kcxK1KR++jWGm4lhyOZVrNZrUkrsXrrA4+Ml773/KcoKn4bY8fb775HnI5rFKVcuXuSzO/d4443X+f6f/fipaqxv1iSjWLtWjJNf8PilKO4wSLJsQQiiRQ4p0vUt56fnmHKCJ5ErgSKFFInqCXtaCoFWCpvlqGRQNqOuG6xRFFYgWeNRyXQ2FodcXXN6fk41GrO1NSVET+c7XAzkNidqTZ5bytIyzkpsNHRRUc02mIxLVo9b8rIgNHJEwgiwzBgzmA06MfOkROsSNsuJKbFqGpyPTEYl29tT5guH1lLAXZ9YLjo0GXlWyJjCew5PD4nOUeQG00ZC7FFG0XUNSWn6vqesxsQmJzmwmejSrS1kft17ErIE7VPEk8R6HiwkL8sga8RxOKgqtB7kkUaRVCImTXSJPNcYbZ7yQWKQ1z74MIDKEql3MmcbVm5W5aALmfsrLQuqAH1IbExLou9kCR4jyTlMWYjm2Bhi0mR5IUdgIn3XMj8+HPTaiZT0U3dlGGR3ISm8N9St57/7P37AWdPTLFq+8eIGX3l+j4DCWMOn5xmfHzZ05yua9ZwQWqoiwwzZljYrQEs0oev6YZE37AKG/YLrexaLOeu6YTQecXHvIufLpZywgmcyKoSfHxOx66DvRWlRVsNOSWNtCUNx3d6cUo5HjE3CpZyD2nB9mohxjjaiGpGQmkHPHuVU9gQ3obTsK0IQnkvCo1NG37ekbMLnh2u6m4EwGpOUkpQghPkSk8VTcVx7Hq08Z3XNw/0zfEo8OjiXCMN6yXLlCWjavhcViPcCqBtvsm47WdJGP9zYFVELsdLHRBiuX5MCOjnBQ+SaGy9fYmOWkdma2K+JsaPIJrh14rOf1rioUVpRGIsnMFomFsA0z2m6jlgZdke7hNEjTheWetWjYhoQCE+sXVKwgxdlUdv3mDCQSo1CB0X0AW3kPeqVf4qEZgh9Pzg8guQ4OZ+TCDjfopV4YpzvZf+XZU/VNdrop7uoNFwTZZWzubPHP/mDf0HdNIK7LkQ+u+xqiigTif3DEwyGjYMDnnv2GR4fHguxM0ZwPX3bkNl/B8YywUfOTueQLHmmmUwmRN+hbYW2I+GuGwnBKAZNdQoSqA2Qa0OVV/jeybE+1yQqNjZGrJcNZT5itVyRFRXB1WS54+azF3n8cE7dwGzHs7U5ZnHWoIxnWbfoakRU0HjPzI453n9Es/bkL12k9VDmI0yVc3h6ikqB2ayk7WtiyuhaR1EJ8vX8vBYedspIDMWt77l6ZYeTk3s41xPxLNcrjk/npJi4eUOwsC7IyiovMybFmMPTA8gqFAnXy2im79YYKoLyWCXLQhd6tAWrlRwbs5zCGLoEI5vhdMQrJSOMGMm0po0tWCOKAfV/U/cmv7ql2ZnX7+128zWnu03cG32Gs3FW2mkqjeWiCiFUKlUJmMCgECAGSAiJkSeMQELiD0ACS8UEiQkSQjVBQkUjqhWGomSoqnSm7XRmOCMjo7lx495zT/c1u3m7xWDtc7OQcDIApPQ3jDj3NN+399rrXet5fo8qBaaYuboZ6WyL855UiipQBIL3xLQww9HvZYzK6twCNlL99IyIwTvLHLXbjrcTMVdub2+XRWmvD4gq7I57ikGlnaYwzVGt8cEzjUe69QZv1e5uQ4NzAWsF7xS7oIYcSxHLOGeOY+Zqv2OsKySsKClyKA/5B3/wKS9fveSjn/6UB9stZ+sVxji8dXingR6rplXIWNUbPFi99pzzFATvHaHxrDY9zhiCMzx94zHXr2656Lc8vriglsowzUzzxOl6Rde0iHd47zSAxmhGwaZf8+L6Fbt5IpaK2OccH1wQirCuomMS+7MioSMSdVGyEEBDF8hViaC1Lvm+xWNSZn71Kc9e7Ch/9qtgYZoj1nYghq5p+C/+5kf8zvc/4zhMGBH1GWDBqK7dSaBvHbnG13sWETXwONdxt9uBFFwfmKthmic11iGUioogxYIJiMtY1yN2ZkbwZ57SCMiE2APeGKZY2Wx7tlvHuT0lOEtrW2Zn2JnMOlbSdMQaw2qzoXdrjBcOFdKlUI0+5OqiDgJe6+51OSyq+a+WWhPVKkVTsrpr793M1giSVWL8448+0fdALIfjRNNavDUUDFkU1yGpLlm8QiXjvCP4BjGFrg9stj0vrq847BWdTYU4RLrW0jlHFvCuWdQ3LR/99FPefPIEZw3DNHB2dk66S7gF2fHzXr8Qxd1YQ9d1mCVQdnd5idjKHDPPX8CjR6c42zCXSPN6wviz7X0WoWbIFYIYnHNMKbFKsD+MdI2lyIQsFL1aK0Yc3jekmGjalrPzHjsL6zYQY6Jrel4MV1gJPHzS8sbjJ4zjQNv1uFXieDfQN4HzzQnX+yOmcRjbMoyRGCM2FX0gUThMmVQz3lqGUThbB1ad5XTbY60S33zb8PjxA17dvMI1nr5fM9zuWHVrtr0ltJ71quUuVjrXMJWIWa2wQ1Exm9dNvJcGg0oVXQVDQIwwZ9EFWo7k7JEAJsqyy6iQwNqA1BnrAywpVJv1hsYGZboEs8y/K33bcXF+zjAMOKcPA4zHWGgar4jmJYnIKnWf4D02eDBOERJGU6xWfYdzvLbWu+BVhhY1M5SqkXFYy6PHj8g1q1LK+sUhqYur+5SikiIWdULGJDTW8eMvEr/9N37Ed77xHudPLD/86GPmeeBwONLUStvoXF2qmqOCt0tXpiQ+75wuu5e/v2nUqFVrxQVDnWcOxyMbY6lp5uFbb6iTNauZaN22NCHgnEeMJYSGOUeKLFr/EGjalv048fwnH3OcZs6Gid1l5M9/pVGjVFlgVqhJSqWhOv8VYxjGGQTaoNC9PFYyA70LdH2DSMA4la62bQfVIuJJGf7sB2d8/Z0HvHx5iTeQkp6Qd3uVplrfIFi+fPGCbrWmSF3SgjI4h3FrjkPl4xd7Yiw02xNczpRaScYhRiXJYiCLZZxHnINUCvvxiGGlk+/iqUTmKbPqA8ZEKFsSQikjOcLqwTkmHthbw3GKlMkxNDO+eiqzmtVEcRbjMNKt9NooOZKlUqt25XlxxUqFYtUEqKEnGe89uSzAtKKGquMwcHv3kpQLpSi+ojo1OCFCkbLch/qyZkn9WvwRXdcvOQ8nGO5VZRVvVFkUYyS0HaWMFBPAJjZ9zyeff8b5xYVmr+RK367wNjDudj+3rv5CFPdSCrvbu6UrUSeqpuUIuXSIqOTqPgQiF52/3rMIXAWKFiOMQEp0zhJah/GFUoWuW2NsZbvdMhzh8uU1zq2wTrh6uWe97slZcL4DmfHiaUOL6QI3xz03hwN2TtiThsOkQLFhlzi/eMjV3Z5SoaRM8I6+DcxzpWk7Tra63A3es2oCUmbOtmtW/Vo1xNZQUmYovO5uY65M48xbbz1iHDJWItkI3brldp6pBpBKsLo4qrkQnM78ktHZZIxZc0mdJ9eJmjQ/NYRAKgmxLcZbYo3LxZmw1mkcmlPbcymVWguhaTTFPkdlcFsNIqk1UWvSEJOiTBBjNedWRMmVjfc46zgcDgtWwuGdYCTRNC0hgNQEodFsyGW+re7Je2ej7mW89/zkww958sZjmrbFtFroqlTsvcJDKlJ07+CNUI3htPe8Okb2P73m61/5gN/9m3+Pw/HIcb8jWI93lpPNBimVFCMs8s7gvNIqnaNtG7z1TDmDtzgVhNJYx/mpjvtWqzW1FM7PTgiLgzqnjAVWrY4cQWewKatbGqddtpiRp288YvryJUbWdH3gbn9kd72nvP8mqRRevrjk5GxDZdFfu8Dd4fj64VaKykXtQrsMYul8R3GVdx+seXIWWNJtEBFyrSpXzYW3zz1nF+fcvuHY9AGsowmW434POPWeYLh62fHo7AxjDXOMTFPCNy3OeJ7dFf7af/sPscwcdns6DFIyKWViSozjxDQVUloCtKtBqiGNjnbV4KTDmUoZHWuE/GrLyszEOlHxGBy2a9i/fEUeRibv2NVITJ4QHfaswfWWyBFrHaHoKfw0dlTR+bjHUrynVg06VxCXKvOkCj4onPBe9VVFaNuGagpGGj774pKua7HO0vVhWZwqosB7t7ipl5/ltElxSyefc+XB2WO++4NPXl8HIkLTeWpO4Ftq0SB16wK5ZKoETk5OGI5HZe/ngg9BR6nz/wc89/+/XwYwdrH7yoIUWCR7JSkBDasdvs52y+utvhHDjIA3xGkiSeasW2OcpqcbYzmOA9b3jPGI2UWohTjNGK/RZOOh8OLLF4yHiF2yDe+u7gjGcRwPbE7XrC/OGb+84fzRI2wNfHH8jDefvsnN9Y71ekWtiWAtRoS+60ASxWhYRZHKpuuY40TXGs7O1pQsCgSLunyrFXKdKUkU9yrCOI/EIvRdw93VHd4KphTmkhHj8LVqqlFV+mItkeK0Oyp6jAELznjq4q4rkvAigCPWipDwodH3ZNxTU4RS8AhiFOu7z5G+ZqzVi7iUzLw4TEtO5OS1MIvuLCxaONTerR1wTgnbd4tV3y2i6sqqb5gnRQfr0fjeaKOLvaZRMBeiaUKNa/nh97/PV776Aeuzc1zTEqweZxU7W6g1I0ChIBLVZZorj7uWV5fPeXVzxZS0g3NWoWuHw4FV2wAZ51SnfZhGNl3H2WqtbkQ0WjCmiLcW75bksFy42J4iWPbTwNnpKRTIKam5K7Q46xjHQdkrwTEcjtQlsnGeJqo09F3D+XbL6bpHbODV9S1rX8iiC9KT05NFx69FUQycnp1zuN2rwc0pw8dZVJRgKnMeCS5wtg780tcec7iJKkYQp3yeqkacfrXG2bDY5hXGV0QU9HYvPa6io0VRPXipFTGCGB1zIJHfeP+MX/36G6y8RkbVhVVTF+SwcZaahWoBArUYPvzBS66aF7hs8FLwJdA1Qop7XK/c/Q1rTqolHiaCQPaOOSc6p74B33ia/oJmKli5U+kisB8jIpZa9PqVZZSVc1k4OxnQnZMxBim6z7gfrUitqn/3mkP75asB1ziqZHJROSWoYqnUQqkKYgtBC78iOgwpzRgbuLo+8OEf/xhF8ujfNk2RLngslq5bQS3LbkWbWGs93mZ8G4gl47qWbrVWTs/Pef1CFPe2b/ilr71J17YaJj0nvvzyBovh6ZMHbM/WvBxHatG5nQ8NNUMtWeVhFYbDwCTqJiwxaqHMFu8XDbjpaJue5y8/59u//E3FGFhNtwl43nr7MZ/+9BnYuuS1BtbWY8uETJlMZZgm+vWauBqhCg8ePeD5i5esVj3TrGHRMc7LAhBlrhuVPlmE4Bxf++BdvKladBvDMA54t6IJLUag6zqOw0S3bhnGmVfXRx5enDBPmU270DCxVONJUU1VqWSapsPYhHNo1zirLt15R4wVbypiO6Y54atd+iCPZMCjHVMpyoNfMMGlQNu2dN7Q9R19vyHnSs4ayBFndYpOU1wWmxBjWgiVy/voHMZZUikcDgdCaMgx4Lwj10JN+qC1ouYfY/V04Z0lzQlng2Jl0Xlov+15/PQNSqkMwxGfst6Uy1JdccKRXDKuii7IUyQX4eF5zzQf8MEx7naERcMsoqlMxWXaJjCnQtdtSONhoWjqctg5hzOOmjK1qeopcJZhngjW0XY9J6ue09WaNE0I0DQNzno1wADbkxMInlgqJU5ESfjOIkbYD0fGVFlv1jy72nF1e8WbH7ylYgOjTkhqoWLwS+5piQUqzDmzXm9Uvy8VZDnxWCV0hkZza3WspvNoWaSvxkBoA77REPmyMIaM6O4jV3VHh+VhpiweXj+4LYZSE63LfPuDU9560LE7DmQDNWbSrPrscYjMs3CYsxIiY6FSiblwsOqeboJ+zhRHs04YmxEapjjiLEw5EaUSqzDnuqB0EiUYbo93DHHC2Iozes8dRv051lYdm8Brd7qzyhVSZUtZeO36sJ/nqAqpUgAVFBjg7/zPv0voVAp8P/OuNePD0rWjC/6ctfAaY6hVdPFcK9cvd0wxce/x/ZnXV3DOkHMCqfgKzulYcz/ObFad1rtFLLLu15yd3UtZ/+9fvxDF3QCUymF/QGrh0aOHXF0fKXPEkgiNuvPMwpYBFjGG0uqKQH+y4nh9TfOVt3A3O05cz36IGJuoppBJHOZb/Krh6uaKVd9xdbhlHRpSSozTAY8hT4lxGjg/21Lmwqpt2e0PtLan61p80zIOR0wWdnc3NI2Gh8RJcydzqcxJzThSCjUn+qBRbMFZXly+4o0HF5SaaduWOFdlWQQhzoU5TgxDYo5HpAr7uyNnZxuOxwPrtc6mKYXiPKlkunbFdNzRuB7xjjRM9F1PrII3FW8bhqoSS4yOSqpol2FNJUsB3y9zQkOVxcEIas6KBlctIVSORzVN5ZzZnqxeuza9c/imATR0G4TiNF/UWINzQefNC6/E+XsXn2Cs1Tm0VErS75djwnvP4TjoR210xzJOEXOc8I1q/OcxEorBWV1m6mpXg0ParscCMVtaDI01tDYyTZmUEt462qZZ7Poe6/SYrsvKymHS97+KMOdMEVHpmdUZq7GO4zgr97tmJj/TdC1n21NMLcxppm07nF8IiW1L6x02BFzwPHz4iMvba6o17PZ3pBz1/XFO5ZTHkW69omtV9WRYbvbld0qlLhkHS0FasBFzTsr8zwWTCk3jCcZBqaTjTJTImv7+9tHuFJZ0rIwVxRs4vwTXcG/QMYvcFKqxi89VH+il6D4nmAYXEndHg5dE2zd43+KM4H1AqsY8Fg9RLH6+5yo47ILcrdVhXcE6dPFqPa7oeMc7hzeFsRYMjr5faY2YB6TMTLudRhyKw+MpZA4lc70/8OhsQ0kqk8WYxRMglCILR1/HJ9XIonBZkrqsOm/VDV0YxhkXE9547gu5sWZx4lqaptFQGqtO11QyCobX+2l/GJjn+LqIGaNOU+uVJRSCynmNKBiiZkUnD+NIv251Lu9bxnHE/2kwMelHnGh9g+BYb1c0oSFmnWN2XaDtPNN+0m5PuteUv1QLVgwthm69ohknYp2QtuGf/uda/tJf+Tbf+c6v45znBz/8Kf/1f/UP+fQHt5yaU2oSYq3UIrTtmtOt5fZ2VEuxVIZpwLc6o+5rQ0ozeZ4JbUfbdZw/uODFi1tC4/j6197njz78DErG0RAlEUuhX/UY69gfj5w8eMzt3R7nB0xQXsk0Rqyx3B2OxGHm/PEpL169wjvD2emWz58fePzghLvrW0otrNqGIc4Yi/LEcZQ0sb9L+KbT4zoW4x21FPLCuqjAa0qkW5gs3iJlJhad2Z6cPNDdQR5I00xMFWvD0pEXVeA4eT2HT/OsIzKEnBMlZ9abNffwN8P9TQPzFPFNSzWCpSBisU6XmOQlEMLqnNJYS7sUtXGaKCynoLbl9OQU0AXk2cNHVAy1ZHIpWKt6+ZU1iiJYrfDDyN3tzAePH/P1x6f86NPn1KoLN1ERMlPMbDt9+MwxAsuDx6AuRO+IS7KVbx2mFrIIqRRyKsRaKGuUBZ9mUsp4b6lU5pzIKWOcxzmPC545RoZpJjQrGrH0uSKzcm6MVUWV9ZaSltjCek8/XcZgdVFk3J9WrNH4PRTFULJGB8YyEaSlwYK1yudJLEYoFEVhVBFTKhQs4iypZn2QUHQhuIgXZBmlUZUVL8ICKYNiCkUyXSjklLk63vJue4bFK889JVKeVGFTNAdWFpMTNdGbFkkZl9Q74U2lNR2NdThb2PQ9NqvwYm3W+H7DrlbczR2t86zefoc5T4QwMz+L3I6V+/D0m7uRs81Km0ijYDxjLLlmRReLxYqO/qoIooYCqtOUOGMXZoyoPTDVjFhDExpdbNeKdQq20O+tHei9Ae8+qyCXwu1u/1rKau45ycu831bRkR9QbcCJPjwwkHKhNxrcwZJq9Zrq/Ce8fiGKO9awXq0Yh4Lvtij/W/uwUh1WHHah3rlls2yMYG1Fsmres4FSM9uu4e5Y+Jf/6nv86//Wt7g4v8CYFUY8bzz5TX79O7/Cf/qf/Td87+89Z9M0lOpIcUQqmgDPRN+viHPEOsPd7sjpWcc0HTDOcvvFCxKW4gwv9jvmOWO9p0rB9IFxd4cMGimXspqcun5Fipm+X/Pyy5eEQ8AZtdx3vSeXzINHj7l68YLtqudwOHDSn4KrnD99yEnn6TrLcKjY5VhuMUjOzPGW0LVk9NjedPr9RDKFQps1jzThX8/os0AnI7NR1dASp8rhcEQwOJcopS7o30i1jnGeX6fCSK2Yqx1dG0gxKXYgeLBmWVQFGlH7vkGI80icRz26GgNGC4IVoZZEKQmszhxLTVjCYhAbGfZ7tpuLZXdy4Orqmm7V8cb5+aJm0NGIs1XNIs6pIzd4+uDxArZ6Vr1fWEAL2dFapnlWxUupNK2yP3wIuKokyPvlbskZU7XAeR+gGMY4cxwHDscD7XaFGMvxeKR3AVsr677nOA4ariK62HXOk6TqglEqTSjEeWacDqQUaWvLzdWBsF4TcyUOGesF5wOlqtZfFR2FXOqiJV+CIqQSvNcHCY5aE04g4ChSCCFgQ8em8aQ8U3HEJIg1tF5RxsqNkddSW/08NUS7ogWsVlV4mEXwUKXgraNmHYNUPKt+w6ura3Z3A6cnG6Y5Liqyunx/dW8WiQgqce5dQ+tWlKJo6M4HTC24acSIIU0ZrCVOOr9PuzumKuDdMlryvPj8SH/i2cWJfYURyySVNGUu5sS2sQuX3lDFLLP3vKCg7dKo3DOr0JOkkdfN0P17g3OohkMffLKMXgpFsbxeu++y8GbUdAfjFLk77DA/Sz3U+7hWdbNWHQ8mKRjvIWds0yyUjUrNFcqso7XUkPlTslC11RHawiAqgfTOAzMuZHwQ0gw1e6ToO1OL/mnWeopZ3GC5QDZ88M0z/qV/8wzOPmHHFxjxWNPQuW+wOdvwW//uX+Q/fPbfky89L65uaXyLuiDV4BCzLijHFBVjensgNIHgO55//gX7lNk/v+Tk/ae0pydMw57DZHjv7TeZdkdEDI0LhL5FquJfxSc++8lHPDg/4e2332DcH+lXQeO0MMiy3CtZJZPBBqQazrenvPvN3+TFYHn+4Ue89+YFHz275ZgKjWuZGclSCK7DVoE+0Hct491u0WgLDg+lYm0BoxKwUpQFU8mUHMFaJGu6EqJh0iYYfOeVIWO9hl3bgAChaRRk5dUynbLa1w/7UQuJsTSNW1jqUMXpEtmB8epEdc6S5vk1pz8E/xpFW2VhrxSdq1rrkGq42e155+wM4wNZKk5UvXM/KLhP6oox8c13zrlYN1y+LDx5vOZ6v2OKM1IqcZpwFrquZd1YGu8xy/jAYBeDHMs8X7vWm/0djQt0baAQsbZQrEra0lzUWl8TFmFMMwUUFbF0W3OK1ONOO3jnGQ7XKilMulRvg8cauLm6xnYrRAovLi8Z5jcRdInnXMCmrOwcb8lJM1R909N2PaXs8daSEgsCWpVL1mqAiJFl9Fah8S1xOtI3AesCw5A0M2DRB0qxVDHElBdcsvoHqm4DVSFVtFgrV8yRy4hvZr7xra8w73bMMVGzwv1G9MRTciUXSxH9TI8xEU7POLt4QJnTgrHwyOFIHgYaDFkggT7UqsGHnpUxjHlmdzwyXV2yHwqDOSVmT66RIm6RKFZe3QxsH22Xym0WFLJeMxazFO/yekaO6GkypYrEEet0nGitV+XNPUYZoFRw5vUs3xjzmu3jne7fijG8ur1doHc6YkNAljl9tpXaOCiBlKDFUeqsuwOrgqgYM33bIVI4Hg86Yfg5r1+I4g6C9ULJDSKGElp801BlYIrw/MtbsghiIyItxvjFRFEXJobTXrYWXnz5Bf/Gb32H1FxxnA6EJSszhIbJ3WLre9jzI1/91hN+7398QXCGy+MdP/rxxMOTC+I86ZwsNAtcKGOt6pxPzraUFNnvDwTvOL14hHdrdp98SqFy3jvefPyQy8sbhjmCgZPTc2IcsQHatmOzbbk7XuOSQ0zDME+cbLdMaSLVCLbgGthNt6Rqudl5uvVDNiePePutzPPnnxG8x0jGime9OcdYaNseYw272xuO44gLgZoSYvXGdmIwpeCCo1ZLKkLrPa5xau12akUyzlCiYh40Sk2PjQjL0lHnr6YuRqWgs0UfVBkTGtXZiyj693VaD4bj8UgVh9RR5Zo5EbzDG+j6htVqRWgCzgeshaYNdF1PrZY5RYx3fO2Db3ByekrTdTTtapHECnOcFjehX2RnhX/lL/85Sp758tkzfvLshj/46FPVXVelT/bB03rPqm+xdnmAiM6Zay10XUeclVNeUWWVs5UxR0qdVLkQlhNBFQ7HA9YIJ6sVRjLGW4pkXLXEmBc53r2ZpmBqZD8cmaslJaG2QhM8Ta7sjypx3O8s06xSwmA9KR25x+uqhEyDvneT4CO0q1NIM8KEdV7rTl3m5VWWWS40znF5eUXNidP1BWmOzFG4z1VNKelIri7a9KKO0ooag+5Dr1lSl3LJFIEUhWlKHOcD+5sjbWv1usk6w06lEqvVrtNpFkIS4er2jul2RzDQrLY472mdQ3zLcdQ0K1MTlkqyumdLqaq71lquDjdE13L96ksOVThgyFT6pTs+DhNzXtMG+3qkdN9IGFmWw1ZR49Ys2vdFYCBSyalQaiF4i3F+UQ6pQslUHYuVotmyxmmAS138OHFZHl/vdoslwbvlAAAgAElEQVTQAoyV5UGiGbbTlOit1wasJrBqpipFoXw5arDNPE/qgl0wIT/v9QtR3AVhtx+4bZ9iSbTTTJp13mdN4N333+Xq6h/pAmmZ597Hhem+fWZ/OFAkMwyFmC95+Sri/A0dFVMzTbfG+FeI3WGD0G6Vd/70jSc46WlOA64E+qbimkDjHc7pXM3YSiax2gT2VyO9MfjtmunuimwdZt0y43l2MPDwPearO/o2KOL0bo/vHZFIQZjsKWf9hqv9S9zsqQhJEnf7HbUUDsNIEcv65AmfffQFb71xyvf+wd/lcjxy8fQJlz/8Y9ISiFxbIcWRxvfcHW9ZbVYLJdGRs0AUaERDDUTdgj57TGNpl44x1YrPDnGOVCK+1RvXOkOcIsMBbKr4oDeC69QgQ610wXMfUWYAH5x2KyEsNm9omsA0TXRdy2az1oeA0zFPt+pJcWI+RlIyXF0P5KwYBLsstXIc2J71VCrHIfLRx5/S9bqotL597cZ0BprgqcsF3waPCxDnQtttqPYW4xuCc5QS8d7SBceq8azbgHMwzjNmifLzC+IB48nLTWYMxFpIxxnjjS7HxgFnoO07Qhs4DGoLlyCaQ2ruIyEz85zIOaiuXTLeGtq2Yx4nsB4fDMUYmuKJd3um6UBnz/js8+d89ckHWOepFl6Hw1cNSgkucHNzzdXVNY8uzrjYrrDWqVnMN9rF1kLOkdY15MXMd3ayIqfMPEVSyWxOHnAcBvKUCS5Q7mfr1qr6aTEAKnuoLnsJdWzmqj1A2/acnJxxGAcePnpEaBwlqbFvjgkbE9UW0nHEOT0hHKvhaBLri0dcbM5xGZwLpHFiHy8Vty4QjFaLXGCIM0MuRDHU7ZaHv/JnWN9lTl89Z3j+ki9vrjiUwk1JGDHsauHzqzvef3xCRdk5WlhFTUk54b1DqobY36dGzSktyAkwIqQ8463Bodeddf61c9gvI0Gd4GlXP+VELYbruz3HKSm++f40tdQ/79Q1MU2JVVMRKwzDgRBaShbqgkIouei12wZqKveEjz/x9QtR3I1x0DWEeY/NhcOUGI4jzgg5jvz4ww81CKMo/7lKVlMBBhGHD2su3rjg8lVi4wwf/+gZ508a2v6A9TMOjw9H2qbVm7i2vPjMMCTD3fWRGgt59kiugNcFnneUmvBNwzxPiEkgmd0wYYp2lcPVF8x9S+ouuHp2p3ruszV++xC5uyKXxOrklCizjo6k8Oow060uaNqgkrbOU3JkHmbKXEEmhlm4rFekeebTLz5ld/X7zNUuG61EQqg5aB5qrJSgl1KJkWoWM4Z1VOcQKzovzouWxInO6kul7VbazdWKcy3FV4yzOne3S2SfBKxXKmCuootVU0lTAhGc06LuBWzTYr1bkMDazWMEH5ZZejFUqzI6I4bgGygFuzJ0BozpND6xajdqTODqxUuqqPSvawPnDx6w2m5o2pa2X+Oc/oy64Cic0zSuWpZ5bpqJw0hOX3B7p9dUCOqPOFn39N7iTSXGBAjjrAvRVR90l1MygiWlQhO8dpGlkqMwzpk2NNgg1Hhkvdqw38+khQFixOlOwqmPoUghzoVmUUbEJBhbFtyBzq+NEUpJdG2L84L1sDseiVn5QkX+yXv6PiXIsGkMXb9l2O85UDBe8LUljZGmXezwNVMX1rhdrgUj2k3nGPU6nI94AwZLLgs6oDrivCRf5fp6iV4xOOsWQ5ShlEStcNgPECreViRm6jLulLrw5aVwul3x6uYAGI7Fcns7E8otw/Wes/UGezwQd3c0rmHIWhSDazDegAnYZs3paYd3DZPztMWwH29J1nI7HJjmmbFkZoQ9UIxlPyUO88yqXZQuSxgMsERELPJEWRaj1pFFVP5aq6pabEFmiziD85YYy/KvNMJQyfvKL4JKMUKM8OLyegHxLbsTo+7Xe2mqeN2oTBmaboVIVKWMqKyzbVumacLajLeQaibNfwoyVIfDxA+/99lyxF7IidbSh4A3M+vNCfsbT3YRfMH7hlz1ZjRSadqWJ08ecbO7wtfCj38v8/RtS3eSaNcVpoSpltXpgO2f8+Kzp3zvf00cbwJ3cY+xwkVzStsYkhuQbGjFEtqGy6trvv6Vd/nkk59Qs4ZwTKnwcNtyjFsO7Yb68ho/XPPeGw/50e0zfJzZD0dcaBgOd0Dg4fYNYp04Hl7y6XBJnRtyfMk8ZYwX+tBgxRJ9JaUD3u1ZnzSsulPWvVrL4yQUB4cXSZkfzlCsx2plJ9WAKYHqZ2RCbc/G4kyFmjEhqPV6wcLWMlJjJDhPGg5IyuQ4UXNmLoZxsyaXTOMCiQJ1iflyjrYJNMGo3lcg5sR8e6fETSk03mFoljxVr/FltSxdkC4X9zdXNE1QdokN2q0Ly8xdl+a+CTgcw3DAYmm9xdSMqY6aRnK0uBAwVUl9xuksXlk3jnmcGIeRTz//gt04chxmdoeRTdPjQmC7adTIZRpMrIw2AsIwJKLkZW9hkGUxOU8j282azhYen57oyKIWuuCopbJuzqi1kqMW7YIwTIlt32BKJotK/myxhHalkDdnqNXqDLvqyGGOmaZpebhteHi6eV0EqixAEnGK3rW6f/JWWPcNwVXllGc47ifSLDx80pOLFpJU6lKYVW3m0Azc4gJxSsxjQhqLk/vlLWQRjYA0S8Evip+eYyGWCbOESMfqoRxZrU50v7B0/tpbiP7tVhHNVhyZQLXw4jCxsQVxQjAts205F8PK2sVz0lMMiGsXE1zACByHI/vxC9y3foXrKbFzLYcmw9c+wHxxyfzsE+UaISQquRheHSbeCRtqTRjrSDlryHUtqk03lsoCGyuZyhJ2I0tgSqk4O2JMQ41OZb3OvZam6hxfde1lyZp9cXVkXB4CIlrYi+ippyJIKZAM3gvWBmIaNWxHEq01NCEoJqNzy35OFUR/OsI6DFRbaWxDwek82SqMqu16hfhYMFIVoLQcawAwGjD9R7//4RK6a/n4h5nNReKb327p1wWJQp4q3dZyN3j+/t+55YtPLa2PlKzabGOhyIBIYbPtKWWCUpjTxJQnCpYxJuJcKdYTug2XU8/h1YB79hmnXcOz5y+42x/oQuAQEytvWG96NqenkAq2CGEvbE5WmK5hvX5CrYZSJoxU2qZjihNtdJQpMh4m9hKR0moBtiONa3l0Xvny6kiOmfshXvWC89qlGzE0XcNcJkIRshRM4ygx0m3PSHFGSsaUjCuFVGZSUTOM7hG1+3h1NfJHpSJ0PH20xbugC7W4dGUhkIvO9HvfYJv7bsQq0gDLNA/qGB0sysjWxWnTtj9bXqEgOEUOqAu3Aj40iwkrEkLAiOU4DMS7Ox49frzwuS3ewn6/p2nUcWitp+SMNYXj4cB+GPSzuR1IWZdkplUpXKlenc4IyVWmY2EbLI8fbhWLcRi5O0QKhcZV3nnrhF/96vu89+SUi9OeIsIwJ8p0pFutqbZnN0x8+uxLPn5+ye1QSbeZ4TBRDazXp0iayTkhPoMzhLZT1UZoKfNMzJFxmhlm2LaZeToSsEjS6L2a1BFprBqTiqkkUTok1mNshVLVldw45qipTTiPN0KuLO5c3RdUwBU1ExnbMMyZBMQpEufEcYqMs2IxSq2Mz58zTZlhFm6HiSlXYhGOSfjnf+Up77/XQWgoSbEQo2SmGJmKMI2Z2yFze0hcHY60rSNZw25MxPGavvFc7W44X/e88/CcVbHI7oD1S/6AaED7LJHqLMMcefcb3+Sjj19ye7himg5kMsYvCGljcBWcGJJYdofMfKKQObucaq21lMVrYb3XXZVREqUTu2x1VM6IKDRPRGtGRU++97RQQZcaBiVN5mK42w8oKkURIG4B3OlYRzMSvLUghVIym02vISJFZb61akNkcfStIrVXm55pHH5uXf2FKO591/K1b7+rdl4JuHTLbp/ZPb8hG08qghehGKu6XPlZcb+HiFkxlBTBGVJ0/OP/pTBdnXH+sGW1GRgHy+2N5bOfGHI9wdRp4dRMeNuRcialga7ZYo2QqnC4PTIcEj/9+CXHYeLu8CmShRgrf3y4w0jgYrOCzZp1G9huVpyebzFG4OlDalE65NXdjkcPHxAa1buXIjgn9N2WcThCsbhmzdN33ufLTz7law9POV7f8c4/81U+/v3v8Z4k/vDmQPfrf55/9a/+JX73//guv/3X/jqSBe8FSTPeOijqbpM0M5aEDYb5OOMaj20DpRYOd9fUonPFsqhUrLV46/HB0raBtlVJJcDnL3d89o8+5+K05Y3HFzw9X3Fx0uEaYWUshkI1hdkIoTqCUdu19XqRN82S8yiLLrgWSq1M40hKC/fdWrz3WGtpmlZpfF7n+SEEcpoX1ovj7TceEdoOu6gbpAr73S0/+tFH/Oqv/rLO/hfDm7PC+fkF4lQqV3LkuK8k6whNIKaIsWvKsuAq88S33rzgX/gL3+LsbI0YnbMfh0lv+lJwCNTKq+sbYnJgwduM8w19o5LYk0drnpx/hQ/eOOP07JRXNzv2x4mXd3d89w9/SjQahu49zENmLoARgm+oYplnZdxYI9jZc9KdcJgTq8V0FBFMitiizCU9UY6k2FG517Drw7rpgprprOF3/+CKPM9qtMuFcUwMc2Y/R+YpMsTClApziqSsu4JchVT0NCH3+u1F6w6LLhwtZoIhWMf3P75iSIUpFqYpMc6FmAu5FJzoqSEbeOPRim7TEioMt4baOCbJGh6+3vL0G9/k3W//Oi+/+yE33/3fKR5eDoVT31Clg6Zl9plnP/yIE9PiaibFqGNAI5ytt3wxjuxQfECIChm8vBt4fL5FFhdqXR54RQyyqHVUq66mJw2ltkvLY7BOR5XGKKTwnomkqWgLG79oMPkwJWJJywJcxTpUlXSXKouMF7g/sd67h6uqlEKjWBZvHQYhp8R0ONCvW9XA/5zXL0Rx1xT1ia7ZkLNB0mIocIY5FeI4MomGKJvGL1pUPZ5KVbclCP1qxXgcsM6QUmB3teWzj2cyLYdDJvjAyaqnxEyeE6ebE4IvpJi5eXXAu8yBHZcvM7UYUp5om/XCXRa6PtB3G7xRlcWUEk3f4kT10cVaVuGcSuG9t9/mJz/+hOvbG548eZvOOwqVlx9/wpMnT9mebTCm46efv2B/t+Mv/uV/kX/qN77Dq89/jNzt+cPr7/PyxSuejZGf3u354nqHG7/L22+v+cEP/oA3n6zAdTq7r4aU8oIeUDv9YTdwc3vg4vEpjx6e44OhX/eUnNSNWBVNIMYQvCM4TdXxQRUd4zQyjhPbk5bry8TN7oYv//gZ3xPDybrlwemadx6d8M7DLW8+3HB20qnDUnWtVKOqihLVMKQGkojznsY3Onbr+/+L5DAl9QWkXBTZ4FvmeaJxYHKm+Mp+d8DakVort3e35BRp25azs1O+fPGSkjVLtFah6wyVwH6YEGNo25aUyqIHT0i17IeB9WaFsdAHx2/86lfYbmDMM2IDtmTyNHFyekYxhikmFPSnI0FvOywNUzno0hVNphf1EdEE4cGp5+HZKW89OaOzDf/d7/weoVuxaldUZ4gp0TpPnAdKbcgJ2sZxehL46vunPD4FiTMleJxR2adUFMlrA4lKkZYkLTFXcoVhnBEL+VjBTHxxF/nrf/cHjPOk6F2pBIR141itGsQarvYzY9KxjbX3aUvyM94PP8tStUuhN4tnQRCcVD58dr34MBY1z/LvBc0/7dqG4LWx8AYkRsQ4Jmt4tRupYmiDQa6f8UcfP+cHP/6UX3/ylPN1z6Zr+cYDi+96Vs2WbrXhOEVyG7jZT1xhORD4/OU11/ORm5K5XLwdBn3Qdd5irLqdvVE2jhFDLjpKcVbHmPeKKWOFLJqEZZ2eRu8ffCEEUs6QszYhtbx2JFf0FLwblHePsa+1LcYuSbWG14W9pEKwDTnN2myw4J3FklPBO08piYvTM6YxMg8RKT+/rv4/FndjzDvAfwk8QV3p/7mI/LYx5j8C/h3gcvnS/0BE/ofl3/z7wL+N5rD8loj8Tz/vZzhrWVtHnCdKLlASZZ71zS0VD68TTfRopIlAssytcJ4pZmpnmKu2Gc5bXl290nAJk1mve1rn8I1n082cnW3pugZjqnYoszp5YpyJSejWK7Z+TZo1Z/Sdd9/Be8s8DVjjODk9JwwDtjrVNIcNz4+J+eNP2fYNT998hyQz5xcbnjy90Jg5C7/2a7+MIJRqCa3hz/2Frys/Jd/y+//b38JU0WCS9x8y18JXfu2XmI+Rp7WwXXXsh4F33/sl3v/KB4i1TOOIt2pewSg7I6ayLK/qwtCwWkDaFuc0OFubr0JMEed1w5/TfQiHsGoazPaUkmfeeQSH+QHXNztubyf2dzs++/KKT5/fYAxsWs/DkxXvvnnBu0/PeHDac7Zd32s67qXFy0WcEfuzjqOUsqifdGkUrKd3ymvHNEzTkeGww4r+jrv9gdV6jWBZn5wRQqBtAiKZ0ASsccsRuWKsZxwSvkn0XYfZH+h6GFKm70/o+56+75jGkdZ5zlcdvRdiRkdZruXudsc8D5igqIIYI0UqqeqOWkrW3QaJlAAcJQnGBkrJlJKZpowPnhQTX33vTf7Z34S//fe/y6r3zAWkFhrr8GHFzeU1rrGkQ+SsbTHdKd//EuzLA0X23B2O3BwGpBpKgd2YuL49cphG/WyXDrlm0cX4soBNdaGpGjBGTVwFIfQNZ+crxDtGMUx3oy6JnVVe/dKhNkFHAutVjzWw2azo+pYmNMscXb/eAMEbGh/YnmwwVGXke1VVbVZrXNuocicE5nHCGKPKl2nC1IpvGw77UfMCrDBgmD54zC45xnlgmA64MrFKt9zsBoYcORZBWiFtBbZnrNwJoWROxom+XZOJ5Awpqos4jjPjoJ27NYacNKLSqSRIl6IuYJ2FonN5a3URa62GcJRa1Zxm1BylChyUTotnnCeGw4GwaODta1274I3FGaMQQFiwA0LTBozajRdEtM7oh2Hk/GKLMQ4fGq6ubthu+/93xR3IwL8nIv/YGLMF/pEx5m8t/+8/EZH/+J/8YmPMnwH+NeBbwJvA3zbGfF3kT37OeGt46+ycHDxTyuyHkVevnuMQ4vGI+KJHS03GJhbleeeib6S3Cj7a9J7TzQbvlIynISot1p2Tkzr4Tk43nJydMafIcNwzDjskBdpVg/cNW+dZb87woaXxDSKafuOCXug1nWAWR2x/ekaJkS0tTd+zOhHMhadrPONwzRuPz2lDg5Hy2v24ftAtyh8WDkWCoj6IUoU5jhj3s0OgF0t70tE4hzOWuagEqmn0Btx2Pc46nPXErJKzmNRW3SwStvsQbBFhu93inD4MrF0i9Kxlmma89bSh0eKAkHKibzvcYnwSA8dhzyefPePl5Y7Ll3dcX99xjJHD5cyzq1u++0PL6apn3Xc8Ou148uScd54+5GTdqhHM1QWlqvPKarQjEimUHIllRL2OnhR3zHHm5vaG7WbNtl1xcXHK7dUdpw/PcQg2eGqa8UFZ69apAUlDnC0+WDp6zh+c8fmLV5S8WOsl4a0ahSrC3TDwwbtPSbWQigHJCJHt6QVhWnN1eyS0HmM96TAxFkM9ZhDVzc9DZU4Dh6kwVeE4R47HkfDhFVc3d8xZXvPPb8bM9SicJqGkxLpfM+cRcss0T+QEjx70dJsz/sbv/IibY9aCzNLM3BsPRBUrejJa/tvirlTzleagLjB8ulZxwJtVx8XZOV2wXGx7njw6ZXWyxjVrrm/3XJyfsdms6doG5wSRQgie4Dx9t14Ijyx5xkr89F6xEVIyITjmmKnoqXBeIGrGGIIPxHmmSqAUYXPaIbWwqkJz8ZBcC4XK2anmFNhFjTPFmVyFrUGRG5JUo18s1mvMYsmRaYoappLTMmqt5FpJKTKNE+M8M82ZaZy5vrljGAfmSd24MWWmedTf2y4x4OLUU2MMlbyMV7RYd63eK+7/pO5NYm1d0/uu39t+3Wr2Pvucc8+9t6pulatc5cQuYju4XOkIzQDRSAaUCYOAxCARggFjplGGBDFCBCExCUJIMEAIS0wicBJCghLHVXaV7YqrcdVtTrf3Xmt93dsyeL69XRJ2EXASFUu6uvs0e6911vq+933e5/n/f/8Ndte0EvIe1gC6Muz3vPfsQNs/w1jDPM3cPLmSM822qVSEvmmNOLRFBF85Hq54+/qWWiJDP3A+jYzzSKqR/aFnfTUR1vUPt7jXWj8CPtq+PiulvgG8/yO+5ZeA/7bWugLfVkp9C/gK8L//gS/COZ6+eE5KK/fnM++/92mWKfOtb36XP/mnf5HjzZ5f/l/+N6bllqrZ3mhxhZVa0KqKvVyY+Tjb4JzlchlZ10DfNwy7Hbv9nmfPnhByRfuKMS3H41NevvyEJzdPqUoxL4FxzdRpQqsJoyUoWSnRo5ZQKTXCBrwqmyFC34uBJebEfZF4Nt9YrF0wxrDf7SS822i0clgnx611rSzLLGEQvmHfHvHebelTXljt1gnbo4qyoWm9yA2NRSHkuBSFCmjsxpDewrhrVY/RhXo7DyrEZRjWmRA9x8ORZV3wVgaRKcVHzkvJQrMMMbCuC0M38N6LT8tgc124P418/OoVt29PvH5z5vb2npfjjJomPnyt+Aff/hijNJ3zPL058N7zGz714oabQ8PVzqOcx/uOrhlwnTBDmn6Psw0ogTpNl0Uq9xDJfuHFpw7M8z1KW4zzGGVo2kbAYUqjjfTjqSJZa1B8+Yuf4Wtf/022UCVySszTTGNbMRgpxcdvJm5fncjKEhKc1sw0z4Q1knNlDAu1RMoSuQ9wCZW8DTJrTY8sETECyfBMoR5NM3VbfzHQW837zzOKhFIrOhtevX2D1pWhLRz7lu9+dGIKha6zNI3ZqmOPVoqu9Vjjpc3lFU+OB3ItDL1k+Da+Yb8b6IeWtnXsdnv6rscYRde1OGsF7FYLOUdyQq4Ra8gxkbNgp60VU1qIIulcwyLuaUR+arzFO09F8odTSlhraGJCb6fErutZQ0ABQ79jWVdiEnhWDAGjtPSaS6b3g5x4asFvTudSCs0q7TcUxDWxhEm49Xm7L5xcu9dbv1ypjQcDWGfx2graeR6xRvrYIUZC3D7beWKeVuY5iN+BSomJdQ1UpUj590xJvpGELlHrQde3lFrY7YZtQ1L4xm8O7Iy1Gy9ok19WVbdZVJX7dcsqEFOVuGpTTOgvfoG28ZsbOLOEgDIajcy1Ukr8p//FX/v/vrj/8EMp9Vng54D/A/hTwH+olPp3gP8Tqe5vkYX/b//Qt32f32czUEr9BeAvAAxDSyyBw2HP4WrPFAPGax5oFd1g2O8PvH55L8oWU7eBjsB3coInN895/u4VIM45ZxxNc8+6RvpBzDMxZ77/4ScUFLnIMMoATXtkWeUYS3V422C8WJQfRMUKAYwpZfBWjC4UqbCt09I/rGU76g90TUsmMQyDHJdjoJZKinUzI0S89xwOB549ffY4kHHOUaoM1IZhxzIvrMtCP/Ria86JHAVgJOECEoahH6b7RjS5RgkD3BqLs06SiSoCEcuFnCSgum09OSZKzFQjKpYHyeJD0RfWQM6ZtmnIqVBixBuF9Y7Du8/54P0XOOepSvHRJ5/w5vaO29sLr9++5QcffUJc4ad+7iu8eO9d+t2Bd54957jb8eLZNfuhl+8tlbouTNPIOI6kVFjGkRgDcV3wThOXkaEpdO/1rFUTF8Xr3/0277/3HN9IOIbeBlzeO5xxVCwmw09/6Qt03f9KruujmiFlcaqmNJKq4Zf/1m9zmQJRV8QtJNeY1dCbwmff2XFz1eKfHvja9+443a+gM1SDLlBV3vpPcsWwadC3X208JOlGoxQxWRojn2UyiSUFVDI8e9byx3/hqxS3pypoO8fVbofREs/XtA274ShHfVVofMMa0hY4Ls+bQmB/uGJeZoFRGYtShpwEPZxTBoyQMBWEZQYkT7Xb98QQZNEvhcPhipRlkaIW5nndHKyapvGEEDbVk8J7zzRNaCstzpSEaW62iMJ5nlFasy4r1sr1Vkulb1th8OSCV81WqYs5LaeMtaLsaduWS72QVUvOEaPUI5K4bVuWeZEqumnQppdUtG0WJAEbHWnN7Pf7R2Z7zoWQ4iZLFXWWUCwrUOi2zFutFDHER316SgljDCFtJ5cqvCKUFFbGKEJJqEfXs/T489aG1Jvs0lpLjEH+nxJGG9qmFWF4rTjnYA3s93vQUhRq5fHNP6aAbKXUDvjvgf+o1npSSv3nwF9Clr+/BPwnwL/H7++J/b8JMmutfxX4qwDPnh5rVcLeqBqKKqzLQs6Fj1++JqnA5XxCqyIAsc0RybY7X10d+d53P+ajj17zqQ8+hTUKaxOoZjMTeNZFuBylZMEHs1UGSFxWLgXfSI8t5yT6WmfR+gFMVGgaj6qKppF4t7AmOa56AZvp7WhXCjSNJ1cjkKgQt+AKYapY4+Ri3RQh8MCULoSwYrQs0PM4Ya2l61pxYRqDMXJDhjXgrBw/S8nijqPijabo3wuK0FqO/kZrlmXeJvoGY6CUuF3gEppRlHxM19dPtueWIatSGmO0vLaHtJn6MMFXKLMpC7LmatiDyszLTEmKNa7c319Q2bAsK9Pr7/DtD7+JMfCrOVCy4np/zXvPbjjsd4Lr9T3rHLCN9CmNyVvmJ4RcaKzj2f7Am9PCmCu3U+S03KKNJ6TCtEaWNXBZEvM0cjrPfPL2wv2UGZxmCSvTmrAKYIfWcLokxjULImBTgGi5KwGJY+j3Bw7XB5yzHE+VJc10vWRkCjYBht7T+Jaua2i95+p4pGs9x8Me7yzX1wdKhaurPX/zr/9tvv2tv0fVlul+JqyJZy8Uf/Jf/qP88//6LzCHiEWRl8r4xpFXaYN41wv+WAHKkLIRfHOUa5sirsvb21sqMncpuRBTwHkrmzzQNR6AGAPDMJByZufELOO8oncDzhsu04lUMlRPChLR1zRyTaaUca6h7zumaUYbS9v1OHTDoRcAACAASURBVOdY15XdXk6ZthOY3rIsWGt5550X1ArrKj33sunIvW+Y5wVnLKnCfr8npcww7IgxknPi+sk1qWQ5yRgxlu36gXmaiLtIzllcxs5vWnKRUccYqUVxfzmzxCAJYinRNC0pFozpxGxn5N5sOhEgWGNxjScsAd3orVWr0SpSUXjvtjYLGGcfB9DOajotRVItwgAyVpNS4CFAO6b0CBorOUvRqSVcRNWC9n77WSIJt9YyThfZ5P9xLO5KKbct7H+t1vo/bIvzJz/05/8l8D9tv/w+8Okf+vZPAR/+qJ+fcuEyZsZR+s3WWkoC5xU/+OgV3/3wY27vThidhULnHkD5WzKTGpmWCzt7lGBlvTnnSqFte0qpj9XhQ1q5MhpnDY1zRJ3Q1kiYrXPEsMrCpjVKSUqLNRZyxji3veoNCUslhoRRUh2sa8S7FqUMm+qVmDa3ZBE6H1vCi9icxcbtNmiUtXLD5SybjzOWGCU6r1A3cJBYl7UC1/qN8yEGkRgjzlnJe20aMpW+7zYwl9naA4ppnmla4UI33uO9Y5oXGQDOM33fUVURrbJWW4ShJAAp6ygpsSwzzjuWJWKMDKfXMAuC1rZoFemaHucafvs3fgtnjARZNw2NcSzTiGo13mtijqQ1S/SarVQNyyx9U6s1dXNFXkrlP/uvf5lpXbmbFs73ZxKFEArrGlhjJqZC3I7RD0NdUFwNlv0zCVqYlkSIiaqga1vi6YwfGgya60PP8xtJebJWc3N1xWHouTm0PH/nmr5t+RPWY7Rn6CT71BuzmUo0fbfHecc0XUAL49so4dRro9DKY53hV/LfwBjPOZxYDwu/+Kef8K/+uS/y0z/181ztd1Tl0bVhmVamaeX+deL1d1fmuzNaNXjTEnOUGVB5COz2hBDxbSuQt43B5FyDjgFrDb7ryCGSkoRoaCWB1lpL1dq2rVxzctSj8Q06Z4wy5JpIKW9/B3KWeMacs8yBtGGeV6z1kjM6r3RNQ615q/SbR2CX3L9WmPPOSQDLONF3HUoLt6U+SCydmNxytsS40HU7SQSbZ3JIXPIFECZ/zhXfKqx1GCVhKl3jyUFmUdo14p6ukut7uUxYLy0u61tSWDeHtcM6T1gXWt+gtvfHPsLBZDBdkBOjM04GsdZtpxk5taQk71HrDTGt+GY7hRdp5QjETDEv66Puvm7FYIzCljGNfnzfGt/Ie6R+vzr69x7/KGoZBfxXwDdqrX/lh37/3a0fD/BvAl/fvv4fgf9GKfVXkIHqTwJ/50c9xzQt/J2/+/Xt4xZDy5oKT59fc7pMxKJJVeE35+ISgxAUc0YrzTwLQGldIuN5pGkaihM4fllkocaJSaEWJFiiVtIaID1QBFc8XnTiyNGpJMGnNt5LH08raoaqNzTqxrqQ7psYarx3eG+IccFYS993lCJKC4rZAPvSmnFaqshh2Ekm5bpsvXaDs04yXDepiXOWGBNN4yQMoGuxxmwcaeGPG2MkHzUXrq6ucU76s03TSI6rMzS+I+WMb1pSjljb0LRCpzz6hhQiCkMhbze4Zppn2qZFOyM29SABwto7ilL4rpWj/Rw25+rGylYNqQRa72icxyqDN/JcuSZ0a4R2twaSiwQjMXRlSqLzLaIPFnW5WLEXFL/6G79FyYVzyUxj2vT0lv0w0DfbQmA0nVVo64HCYd8yXDXsFHzrG99CK0VImWVNdM7wb/wr/xI//bNfxlb5WbbxEh5Ri/BTYhaXojGooglpkc3yAfFRNU0rOQNKKZZ1RSF5nGGJdG23aaBlOFgmzWV6jR80Tz8w/Gv/7s/y8z/301ztP4UzBzRHBvN5Un5D6U8stfLsmebps8yH34ncfj8xr4G2kVlD0xi8E+1+5xtSSqSSHjpLLNMF6ywlVZbbO5Zllfads7RdQ4wBUsY72fDneaYbei73I/0wiPqmFq6ujsQoUKuUE1dXV7x9+1beG6XRpmJ9i3MtbTcwTaMUIc4TY5CTZ+OJMaGQStQaKUpiSOyG3eOGVJW8X8ZYxnF83EC89yzLilLQNi1t2+E3A6CkgFXBA4eVmKNgqmvFODlhH/dX5JwoJW0L7B5nDHMQGaIxLSUmphQYdjsgsiwCkGua/lFh03ZiqNTWPBrqZLStqUptYfAa4zzeNRJrqMvGbno4dUsrKgRBEzgPKIV3LTEkvJdNAETdppWmcR6KktPUH2ZxR3rrfx74mlLqV7ff+4+Bf1sp9bPItf0d4C8C1Fp/XSn13wG/gSht/oMfpZQByTN8/eZ2G14KmD4slRAi/aHB+4aat4pHO4FVaY3rpF3wvH3GNF04HnbEFCRpx4nRIK2BrusIIXC6v+fm+om4vdSDcUZRUhTXWS6bIUGCLpwTHvO6zpvMbtPkV4uzdjMDiZ26ai2niO3ol0vFa0cKgaZxDF0r2FTETpxzpHGeA3uBX1UJ4s05k0LkeJBjctrSjlKVft0cgmwMzm2McEcIsqDP8yoLk/OStgRbb1eOzjFlxmXZjCcCh4rrSoyVcRxphowbCjkaatb4/oi1HT6diGtljaukL5XMtEwYY+n7HZ2TEA6lLN7IZ6hq3lgyhmUMGOuoCXKMaAXLum43r0jnqoHzPOEbyVnViLkjZ2GuLGvg7u5MNYrPvv+cpDTv/8TnsMbhrebqOPDO0xv6vqPxEu6iG0vOgcYb5nTL1773K3z2+c9z+/otLz96ibZwuay4fcOu33PcHXjoWeRUttSv35td5Cz905S3QI8sxMG49WhjzBSJLCfHsrXQxDw2r/M2D8nkmrm7v/D27Wu+9Kcsv/Tnv8qX/ujP0LvrbZYSsGpHqStz+Qamepxy2Nbg3u3QXSHmyO13YR5lw8klU/MFaxTThvhNSTZxpWV+EJdAzpW2a7HO07eNAMWQRUNbKYBSknlQLYrD/oplGbdTrieGLdZQQTf0xJxEgWUtznusccSUaduOaTzhnbQ4jDZCUixl64NLAfNQJBkrqUh64/CsS0IbjfMNy7xQtWJ/Jeq0XOT+9k3Dus5oDNMSUcawxoB3raCIldsqfum3Xy4XFArnO9rGk3Mk5W2BVVsiVZKvUVXu07hsztPfkxajpLBky5ZIQUKr52XZNkwvku0CSSWWeeG4NzhnuExhA9wVQoyM68TxeNwyh6X4W5aFqCIFySS2utueLzNeZhovyjjj/B9uca+1/g1+/z76//wjvucvA3/5/+lnP/59qqS3VyUDxyI74WVcWePKkycHDvtBeomhEpYg/XEqMQecgf1xwNqGWhTGVNZlpGlbGm9xRuOc5zB0WyCyQWn5p3svx7MHU481oiXz3mONGA9iFA210nUbskDTOJwz29eN8J6N5ubJkZQL1jjCGrcL1D8eqR6QAaUWSo1bP06Od7HkTWXTcjqfafvucdcOs7RmxPosG6KiYJ0n5sL5dMY7S9N3YAzzOGKtEA2jkgtzXldhUiuDd5YYC5iMvZr5ma9qrt9x23E3cns78vL7r3j7bQelwfmGUheM67Yjedh43pmQEsYacklkVYmpoJ2l8S3zxqCOcSUsic5ZUpSh3kPlmGOhJEuJgfvzW87LTAbuJwlH3+93GKt4/70X/OTnP+Crf+YXZBO2sjFbLbm6OYthJG+D5jGdOXHh40vm7e33efWR4tNX8KnPPOfNqzekVFliIGYnbPsi/BZnLMYY5mUWuiJswR4Waw390Mtn+ZCTqYW14r0DDYWC2wl90VqD3tJ54sMQ01m+9Vt/n2df1Py5v/gVPvXpF9S8ktQtxgqrxqsPuI9/nVR+AEqj6Sl1oO2ecv3EkX4yU0MivO1QGcJWrXZtJ0NLVbciRv5boqQLiSdC5jTns2xKc5gZul4q60e1SUWrwrqM2zxH47teQlxSlrSgmpkvM7thJ8C3Kkyctm2ZpgsxJY7HgyAM5nkbto6sITIMjnFeN2OZKLFCiEzzzP5w5PrpU16+eklWmiVKbN35Ii1ElEJZiZlcYyAsAYVi2O3RSsikkg629dNTxAJd2zNNI69ffSKzrL7fmO2BtusxzhGWhaEfmOeZWMFvBiwJJqlcpkl4Sc5uhYnFarknh2HPusqgONvCNAkeoO/7bUBs6bqeeV4gikt8v99tQTigyFC20BBVUKpymc7EJO3lh5Swog2ubR5jLv+gx4+FQ1Urof6VIsO7Wh5MLgqF4XxaKEmYDFqJrjcsCdM1rGugOI2zirbzdN7TdyIzEjmUtBfWJXI87jFG+nxK2e0oWTeVgbQ1tNYbolXYHY1z9H1PpRCCQJK6rn/sdxkjm8O6LgxX/eMAsiKT+bABlIzR2+6rUMZg0UKGU0peC9AgvUelJGFIaUNVWy8zi8EobZyVUgq5ZO7u7zDW0fTiEM21bCYu82jtdw9zAi0cHW8aclm51Lc8+0zin/mFA8+fXeNsL7MDIu9fX3H5zB0ffzDz63/3lvH1EWskLxZkNtA0osDou16cplvFo7UoV6zSKCdu4+tnN3zn29/l9SVSgOurK6Z55v72FZfLyBd+4vN8/nMf0HvHPiee3tywb93mPr3a4GOWJQbWNZKLmIeWUvH9TnT9TYdJWYI+nMEumkNzgKHi3/0S8YsK3zg+/uZLvq6+jnUNRm3hzm1L3U5zIj1VOC8Sv1oRKeCmVpLYPEkdiTFiTYNxkp+rNsnjGiUAZRknQdvyIGUVXfaHH3+Lf+7f+hzvvnfDMt6ycqG0DhM986pQ7RNC/VWsbogxMS8ZbVuqvoDacbw58vxzmd/8ZMRnT9PIMT5typJaZUaxrCtt19F0LUpBCIGu85tTVY72++OR3rViYjOKlCMhrmKj3+R+KUQ++fhjaYs0Pb5txFHZC7hPGU2KiWmamOdZTrvOMk0Lp/MZ7z1v3r7F+4ZhOJJz4u3dHcPQi+DASRzffncg5szL128ECIdINTWGcVwosQUD0+2EMQbrHGtIDH0nubuXC0pXmqbFeUOtmaZxzPMiVEejuX5yhdaOlLMY57bCYFmk/bguK4337Hc7QHIIUgiCw/CibQ8xyca4rjhTsJt35HQ60XWdpJY1DSlmlmVhGAb6XoqCw+G4oQvAu4ZYqoR91Mo8rxwPlXm+cBlP27zB8/Tpc5YQmOeF3WEv7/H5IYv193/8WCzuoCQ42BrWsJC2GzfHStzCaWutlFx5yKjSCpZxQmvNdFkZ+p7Wa7xTomrZdnBpWfdCvssJY4Vx8hBK0DR+G+bIwCdtVag2llLE4JJjQCnF1ZMnj/3GkjNKa7pGdMApJS7naQNiyTEuxBWtpAf8wxwVkZGJbMwY6cGXKtFmSqvHDFGjDU3Xcj6fHxf0tm1ZFtHOC9dcLtKH55kuF+rDPGI7CjulN/2xE/BQWNBN5d3PDXzx5yrPnnV4NLYmqJIkpFVB+wE+46mm47t/7wq9eoxGrNYpkZKolmoVw1jbtYQY8a4RjamqdPuBsCx85au/yM//4i9ijRhOzLY5hpRoO9Fmx5Qec2FVhSUH6aFSiHGlhlWULCXTec+aEofdFU3TEmKAkmXxVFBrRnUHrK1Cyiwr2nuGfuAzn/48jfsVkqq4xlBrs7kEPSEk5tNZMmFz5jKOPH0uUtWitZxQqgCn6hZWkbcIPtdYSNKjR0mwdtM01CzO4bwhid+8eU1p3/DHf/ErXO4/psY7qIowit4+hWfU4RPW8iHeNqRSmeZC0zVUJnwzoHjO7qZl/3zP+JGlronGCYFTPpvKsO9ZQyZHKRCsE5FAjEKcxMqiZLycMnzTsKwBaz3LNljV2mzmmhVXrYQ8n8+Uu7tNd66YSqVppWUDm8eAsskMM/vdjhADh+OR/e5ACJH70x3vvf8el/OZYScbj8hp5dSstBEDVs08e/qEXOR9VRUyibZ1SK3k8K5l6D0xSPsx5YUYZeZxf7oXdVlc0VrRDwMURT90oDS3d3doFN5bnt7cbAPhhVIy0zSx/tB9229FoK5VksiUojWG8XKGIIai3W6g61pCTOx2h+0aOqO04nI507Yt42XE+i3LIUamaZHs4QLTJCfutm3ZH2+opTDPk7SAsgxrU8yUXLD+/wdJTN47PvP+M0qu5LKyLDOlGtalEta8CfalF9q2lsZpusaxG3pJJdKaw3Ev3ArnNleb2rStMgjVSuObXswlCrpNZfKgVb1cLjRtg28kAMJvHPe+66Wv6y0pS7/Ye79pU1dKDJQqlajRBmNFibOsC6XIQHWdl23DUdsmIwYEbTSH42ELMlipSISdNSIbS1Ve6363h61t1LY967pK1eI9xsnrXOcJChyP1ygFy7IQUtyO22njbhdSSbT9Ab0b+ckvDzy9fgH1+2TuhCdO3V6HplaLVYpnLwofX91z9zsth/2RxncYnallkROOUWg2y3uV1CFSxrcNYYmoKkoh4zwxi3Z5CUESZZRijZGwBFEVWEOIkYeQbb0RQYWeJwx/XaGkhK6IWiJupjINMWbEplk27rXgUWvV1By5u3/L4Xqg6VrCBKU2FAxv3r4R+ZGCJzc3xCADx8P1FWxqkpefvOLm6RVtK5Vy41rmad4Wbri/e8N+2JNTwrWNOJuVmJjmeaZpW0qCb3z9H/DOFzRuPzHevpK2ynJhvohazJk9aX5FKCu7faTUwuWiWNdMjuD8irYr7fCE63cd8X7AxFY012GWgbvSnO/PONeSQ2KJK76VQGfxWQhryQBxXqRoUga0YVkDRjvCksQxSaVpLTGKz+Oq6x45QKUUnNXM44UYMzlVdocDlSzY2hBl43NybaMU4+UixpwUaHwj+vstWzauKzkmQghUJe7Yq6O4OhvnmS6SULWEmVyhbaXYSyVinEcbxXISQ+FuOLDf75imRa5ZZwnbzOB8uYgJkoK1rQDS1pUcZSZArewOe3QW5MSwk2zjrmu3jdIRUgKl6PpenKubUUlUPYXz+cyyzMIt8h2H4zUpJpFFVglYf/LkKY0/431DWMVpvTvIa759deJwOGA2FlLOWeCIKT2qbX7U48dicbdWczxeYwGrMtZ7bOtFO4qGaok54rxmvz9IPNzmoLTWMa0LKWWRVdmHSTz0Q0dMkf1xJ3jMWjcjSEPXirKg6Toa53nx4oUMpbYTQqqJYedQqWC9YX8cZMCHVKkSDtFSa8G7bhvAWsZpIi6ywJQkAcht5zFajvqqSBUn+vWey/kESir/q+MVb9+8IRRJtfeNZxh2G79DZFhhTVgrPXCzwb4Mhl2/2wY+mhgD3nuGYWBZZprGP2Y7OmeJpTA8megOZwrvcQkXvFvQ9RpUQpPJZRFWeQ1gIu9+/sD68ZEUEnfhLMqFRlgc3jWYVvwBJotqIBvpfaeUZGOkiOalilrAeU9JwjePUYwqSiGZqBuIRm3aYY2iRnnfHowdqUTKJgWJ6yqtLMWj9rkURSxRNgYrMlJjJA82riINzHoCo7jEyCev36KUw+pNLmscvnPMs0DKuqbjC5//PON8S86RznaMyy0fvv0uWcN4OfHi6tM4Y/BG88DaWuZ5S6WqTOOINZ5f/+bX+KV//5plfE1YFkq4I4bIPEec21HthWUtjPNMrS3aFuY5sqyVu/OMbx1d94ZrFuwuY7prxvuTDC7ROCty3sZ5QokYryVwIhWMNoS04hsxr42rIJK1VlzGs3yejSVs5FBrWkzjqTUzTwu7fodxLS/ffMxuv6Px4gydQ2Boe0JeCdMIpuIavzHKPdMYMC7y6uVLrJEh5/l85tnTd8Qpuq70Qwu1xVTFbBwYiEHu7TWErdCrHHYdyoicV6tMs93Lirq1C4V/UxWUouh6yRiQlq5iSQkTK5qM0xalsiSDtZtqaENvTOOFw9WBXHaUFOi7BmulVThNI/Yhmq9alrCSs2Smvr27Zb8/iA+liMfEAG9ev6JpOp49fYcPP/qInDKvX72S5w0ztZRNnrygK1wfDhhtSSkzTgvKKvq+5Xy6YIzGbfOgP3Bd/Se3ZP+jP7TStCbTNi3G9NvCN+C83SbpMoXPReLPoMiFbAwhZoz2YJO4Hb1nmma8c1hnGWxH0zZ0bcM0jsR1pdbE/WVhN/SUnJnyLD2/nGjbjmWdcN7Rdx1UsSDnkpnnla7fyaKjeWz9OOfJSkJGnGtFzoTaFAKJtm2gaqZpEj26MXjfCC1u69Hvhj3Oena7A1pLSpG1ksYjrSWFsw1Zx623naUqqqB0ffzZ1oo1/KF6cK4RmBGWdQ1QDb7vsMMrpvpNTueR8/0tw5Bo9JfwTaL1Z1SRXNXMmZDOtIefwHXvEWcZ2qUgp5i4RHFzIqoWWdLkuVFSEIawbqYPhWtb1mmWBRkeue7VFKk4q8xcnNsWWmsYL+PjCe2B9YPRwtHWBtNKa+shdg6kYACRWoqpJVLWBWc9v/1b36RtLH7R5LRSsua3fvN3OJ3ucbriDIRUOJ3uMcaK2SRE4rrSND3aWOZ5ZV0SvX2Cso7r589YzyvneMs0joRYeP7ihWxIWrMbBpTSjONITJqb5w3LfCKsJ1QRc5l3arv24HT7klevJ2IqHK8VIWZiFtqjcYabJw0pfCzySwKlNjTNVmQ0nrhZ60PO+MYJHtqIoadpO7SWk18IAWM187wwLwHfSCvNhEi362Bj9KzhgXxYePv2DU9ubri9vaUrUuAY41jWwBIXdNXcXN0wzyvLOrLGC+saOR6u6PtnVKqEPXcDb97ebVLkwOUyoSoMrahwdNUcdgdKjkiRnMhx5fZ+pG07cgksayYX8W+IWkU+f+88reolp9cZGYCmKrOpknHakMOKdV5InyUzjiNd1z4GT5circ01JhmeZzFCXsYRydi15Fy4eXrD6XxmGAZqrYzjhZykuOm6AQnKNgy9ZZplBvFgSFzXlWkapYBT4NsGUyqnu3tM1LStREqmkpkvK1POlFp4crhhnucfua7+WCzuKSVe3b6GEmmUoxkGhv7I1fU1rnWM44IzDq0Ux6vjhonVGCspNdNlppSE0oUQZnZDTy4Z6wWIlVIU7bhzjwvM4ETuuM6LTOCpdF2LsZbj9RUpJqxzUNWmBKhY37AscSMYtuKiS0kuUGVo25am6cg1M40jw7CTC0ULEdBYR2Ptpo+X3n8ymt1uT9uKKaHvB0JYpdUSRjytaGS3gWpIadPyyozAaLdFuTm61qM2d11VSnrn2mCt9OsPm7ErlAR64sOPP+Kbv/1tvvethS//3BV9N7IbFO/cLAzNhaoTOSVRw6ieor+AUh3n8z1Wy0wiJzHQ+FZOUyEIZuEBo6JQYuBJkRwjyhpKyuhtgL1MExhN3/QoVfBeFqaUJPNTa8EJoBUhJ7wVuWgIC9YKeXEcJ2oVA8syz+z6buN1uG0YGmi6hrQG0VRvVnvnpRIbw8rLl28ZLyeuj4Po/7WhOxweTwdWiwPYanE5ZyJN09J6cQ6CJu4X0ho4HhuaVpKeQgyUmBgXsezvhh3/7C98lWn6NfwQWdcRXSOkzDwnzpOlaSwxvSSGxEcfvabWQThEoZByJSQFKXB1DUZHKJV3nj2n1Mo6zfIe7HrafkdGcXv3ZiuSrBhymoZpWqklisUrZryx3Dy/AbS0qIiM84hSlnWJdJ2opJZ1ZV1XlBnZ73fCo9FbCLZKDIeBEANvXr/BuY7Xry40vaXvD2htub17K3mszoidPhb6oefq+ih4gLble9/5LnNY6JsDb8cFo2DYX5FypHWOMF9Y1knyeLUQE4XxVB/v9WWFvt/TtZ7z5YyxA/f399QKuSb2uyONawgps9sPGKsx1rEsM8tG2AQxE07TiNEabx3aOA6D/BtTFgbPhx/+gLZpuQuBpu9BG2HnFHGsdn3PZaOZNm1Pzpnr62vOlzN2wzTULbR9XQO+adnv97RNQ4jr45C28Za4FhrbsMzCvfpRjx+LxV0pReOPzONbistYbVmXmZKPKBxXx4O4OmtFact+1zGOowyhlkCukf1+EEnVAiEI+a8+amidcFFyRlmDcQaM/j3qI9LPKzkT0krdjvC3dyea1uK0Y77M0ju0nmVemaYFozXOOxrfEEJkWRap3r3AsNaQ2R0OON+AWsgxUtOK2lonRmuccSzzIiYGozed68put9vYHBFlGkoQlU/T7TGI0UvUPZa2G2ibloe0dGPNFvIsCp26pTOllMgpoq1jmd7yre98wt/6mxGlNamcKfW75Kj5s3+243Pvb5gBNCnDur7hcr5HL8KtqVZmGm5DMZQsyAFrtaQF5YLvWjkK57rptwsaIwO7aaJ3DU5rcs3cn24J6yqtk7bd2jktShtyiiilZYBbk7iQjYCW0sb8aNuOaZk5HI/UnElhxblGNnQrUWm7vuf29i3aWa6fvcMn3/4+uUo77513rnl285TGW27v7oXH00nox+l8kRmHtSKX1YZcCuuSaJ1H68IaxaXr9ztZ/EuAXDbWi7ThnHOsYeVnvvwltPqHhPnMPF3QpbLOgVI1pzvFoc/UcmLoFMtamE4rl9OC8Yr9ocVoiU1c58B9nqEqlnmklsq6ro98F2UsS4is60rNhWCMZB7MEyjFZRrZ7QfZJGPm7u6OeVq4fnKFMh5rjYQ29x63zZxqKVgvi+B4OfPs+XOWZaXvGnK1xJJFHaY11sI77z5BKcPt3T3zDNfHG6ZxZhwvKAWn8wmlI+eLJuaC946ma3jy9Am393fUGEg1o3cN5Mj59lYYTv3Auq7SHrSieW/allJEMVSLYpkXjKr0XUvfdtQD8j0qk0rmyX7Pui4sy8STJzfUDfqlNunwsoggwhjNk+trvLHc3d1RiuAN9vs9QQWurp4wT9Mj6iGGuDniJXqvlMLx+kpmDbAxYerWQo3ijN0EEtpYbu/uyFuP/fmz5+x2R169/EiUbLpIeLb1W1HxBz9+LBb3tm34I1/4gMt4RYwL93dnliXw/d+VN+zm5gnW79gNT2h8J5gCZVlipmKY14VUCkO/43C1EwJdkequaVpQijXEzTqsSUnccE3TkVJkN3Ri2qiV8Xxhv98L3McVlLJMoyAFtNPEVRyl5yp1FQAAIABJREFU87ps7Aq2doi80c7pR/WIUvDq5St2uwPWKBpvwcrCPuz2KOWouXK8ukIZwzQvDLs9fX/Ae79lcS4sy0K/GzDGbaaOC2GWYWYu0o9c5ocL0WCyIWUBUT086mbOKXlBaY/uLB9+O3B6XTC+0liLNpW728gPvht5upfKQIh4ijQVWo4oZzf8gfy8+HC0naRizkUY8YfDgZgSbdNyGSfKtgCnlIk5kSpM60pYZuH4GMPhcEQStiQRKlcBwzkrrsR1iWgrJEHn5ebp246cE/N0kf5kiNQi9nitJHChZkEuO+948/I1YQ2EdRVFQz+Agn/xX/gz5JAIWQNesBIpo43CNQ0hZoZ2YDgeJTg5rIR0y2UZKaUwni90Q4dzmePhirvbiXUbGqcQCJdA13fEsBLqxD49ZTx9m8sp0ThNCJoYCq3vCeGlYHKLRlOYLoF1qfTakMNC21ac0SxjIgVHl1vWKMPmfn9knmZR/mzAN2sMx+snhJAYpwmK5ng8stvtWTdpbdKRrjM01tA4C1pG6+tyoWn7zYEJbNx9ReGwO5LiSsqBaQ0sa6BUmYw0XSMsG2dJObDfdTgrGnxvC/7Yo7TieNxJ4HpOrEtAq4ayVnSJ5GVi6HuWZWGaJvqu5+p4w7II7bVWaNtO5igpMs8j+/2eabqXE7dSXKZJ7PvGsD8cuHZWqmol3Ke68YPevn0D1VBqemz/CT+nMgwiYmgGz34v6Wn7ncAISy1baHpmf9hzuYyEJTCvC27789w0LOvM4bBnnRe6tiHEQM4JKEzTTN8LJuX27o3A+7Ko8l69fAVGiiythCh7dbUjp4Rv/pAmpn8aD6M17zy94cnVFZfzheMhcH++ZRov1LIyja959Z3vMAw3tK3nj/z0H+Plm1dcP92xRssSLuiQSetzTkqhTKZrOiTFpBBywFhD37W0XoYmpkScNrhOpG23d/c44zDGM8+rJMRbzTwHnHVig0az2+9lUa0O33gUAmra7Xq8l2l8jCID69uO/f5KQPw1451jWRa8N48o3qEfZBH0DcZYLqcL3jvGy0XMJFWRYmEab8k1opUnrgvW6sceKmiM1pQstm1t9IYRFq5JRQwVXSc6/JoC6faAo2XfLdyfE9OdIqwQU+Xuk8z5U6BrAge5ergcUCjavmOeJnHiUmnajnle8I0jV4Sb71pJIiqFV69eEYtwSdZlESWJc7SN6JLbrVWWcqRWWBZxFKckQ+lxHjd5Y5Uh2cbhsdbg/UDJmRhXrq+vSUmgbc514kg8jRiLAOZSIawnvv71b/DyB59wP14w2jB0LdYoPv/5z8p7acy2mK2sIZPS+uhQvD+feP32DU3rN0OTZo0RZ7wEOShNVYVXb16iFeyPe96+uafvhHg4ThNd2+NRzKcdi3G8eVloHVQyOWmOe8vp7gfy3KuE5klQDYQ14j1YZxhPgTXBzfEKEOPZuo54L9WfsiL9jTGgrSaEQAyikPGtQxnF3e0JpdiYR1bmC1aiA9cYaJqW/eEgVey6oBVcX9/Qti33t68F9Ffh+vqaab6w840gibXhfD7Rdh3n8xlrNPMyYfTIuiyCHW4HYqzcne/Z9Q0pKZq2o3UNaV2ZxxmrNdPlwhJWemVIrnC8OlJvM4fDgfvzCWsNaUMM9LuB8+UsBdCyEGKkH3q0cRjfUhSczxdKEVia3UJe2qalpoxSltNlQWvY7a/QWjOeR2zruFwuzOMEGppN/mh9I20ga9DbaVkpHmWXxipykrZg2ZznAiaUDSPHSExBnO7A5XzGGkNcZ0rOj8iC0+nC0LUYq9Hak1Ao5/7wDtV/Gg9rLFf7K0KMXF9d4xpP3YZg1jhyXrg/v+G3/+F3mKYLv/Zrf4em2xPiiRwUH/zEZ3CNRtdMxtHte/JS0MVI9YLo0k/LyuoaaUNEYT03VvTVy7iwf3YQel7OGOM2tYDCOqkIrdZSSTrDfrcnhEgpcDgc0Epxvpy2IabH5MxlnOir5u7uLU3jGfo98zThfLO1KTKn01sqGnV3+2jgesB/1lrQym6YBFClsqwjiorvejGabKChdQ4YLUPTmCNd35JzYVmyGLW822SOiphGbPgM7119gfX93+DVS8XuUFmXyuUMra5c3hSUrijboMtP0ISfwjctd/dnkXwasyXQzzJ4ClCNWPJzipSUWeJC23X01j7a9E3jNxZLoWbprZeNJWK0efQd1Foljs9ISg1IRNvDwGxZV5nFWMOy9dC1NpxOp8fWjtKKcb5grcxHPvr4Qz75+BUxRVKSdCGj4Kt/4it47xnnmYxmHCeMlv5644Q3tISVXOFw3PP29g1UthBwxSVMTNMFv0hP2nvJob1MZ1S15MKmly7cX+7xnadXH7DE3+T09ttcgmjNnbXoNBHiLKyhpdL2Gu0K4JjPiV2vSUumKE3jr3D5M6RF9P3X11eyyC8LKWt2ux3GOuZlRhnDvIzUmqUwOV7z/Plzpnnk/v4WbfZYq1DWoJ1h17aUAufLhb5rabyn7Xo+efmKmleoiX53pB8Gbt/c8/T5c96+eU1xi5j1KNzf328EVEfjZUi+311hnRQixlqevXhOzRs3Xsngei6Kbic89LvTSQx9FV598orpcsI3LWsIEryiHE9unpGj5PJ616F8Q9dWUJHLWRRABcXt3ZkwzzTeSZspLgxDT0qR8XQhhIJvPfMysdsdmaeRUiOnuxFjHfvjfjtZFkrK9EPP/enMuqU7xXCHNSKGmJcZ5w05ZdYUcZsk9nSasNbx6tUrrJUZxDDsGC8jxgn6pHGG427H/f1I03na0uEaj1Ea7VtCzKgqLJofua7+E1ux/988FDjjMcqSS6KEgNUyyNS60Psdh+7I0ycvmMLCR598wu39PTlXpnDhm9/4Gu9++l1ujk94c/sKc2r41IvPMJ1Hcsq0Xct+GDZwWNmGGnLxoSJt2+L3lnE8i/rCOEDTtS2pSLKMaSUxRgZrMsTx28796tUrHgICoG4GIrVJ9yrOys6/LIGudSgF67KwhoXdrhOWSRa9/RLFki1oVIO1og564MbEuNJ2LeN0QW+aeeEHFawB3Tl2ToY2ZqP1pSC0OacN95czjbf05gW1fAX14szT/fdQppASXC6KQ18JkwI6vP0cef5ZanzCEk/4diBEQZ12jfBq+rbfFA2RnAt936GVovd7fNOIo7NuxMua6DrJMpUQ6O0CsKIWQME8jwCEWiXOLFfGaZQhl1bUnDfbt7S4HtQrtVb6fqBscC7jNNb3GOV48+ZjvvHrX+Pt25dcH1oqjq5R5JL48pf/GMP+SDndEULAe0fXe2qqpBA57AdKzYzTxPd/93u0Q4dRhst43k5LEsoRVyEGxq39l2tmWS5cLmf6nQQ6DLsdqSTms6Ufvkijf4fzeEJPluRhur9QEPy0MiLpVVlRQ8GZSlpF0tdftfTtB8Q3T5nejhz2PbkUXONFIZWjRA46zd451jXS9h3ruhKWlVGPQiyNknegUJxP91u/OVPKjNGW/bCn6xpAcXd3z/vvvsc83pHyTEyasC589rOf5e5OtNqH48Dr168oJQvxMCO6eeMYhiPONozThZIzTWuETuoGUsrc3b+hazvatmFZJnLKDLs9xmqsdbzzjuFyuse1LahCrZq+3xNC5u3ta+o224CJGAJt17E/HFi20GvfOJyGXd9wmUbmZUbY9pFhf+BJ07OGmZ3qqFtEYtdLgpg2fjv9dmIoNIZxmtHakkIWd73RGKdxThOizLi6rud0vn3EpVgD++OO82kil8IHH3yW0/mMtZb98UBMBa/FlbrbG0JaiClTRqFrTuMdRht67x9Dyv+gx4/H4g7EKBzzh0VdRPoVrRucE6NCXmCZRw6HluGouTu/AacxccC5yte+9nVUcuz7nqNp2V1ds8wzrbFYbTbbeqYuC23b8847L1CiJWToW9ZVYFgxSphF1zZcxiQDkr7DeY9RjmWV9sJpWsil0Le9DHsloBJdC1ZbIhFU/r+oe5NfS7v9vuuz1nr6ZnenqapTp+ptbuf4XvteE9txsB1FRCgKQkKKRZgEsHCISBQSJJo4SIAnKIhR/gYmERIDJqA4SgIhIcaY2L5ur6/9dtWfbndP/6yOwdrvCwN8BwTQ5UxKKqmqTu29z3rW+q3v9/NhGodAc0tCJEuepBqr1RJwjMMUHKhxjDUGLQTFCbs6T2PY6UsRdgNxjDU64ErjhKIoED7siiUeZzRD3zNrgzrJEaqqgNNNfJ5G4QesbSnKLxMnMWX668zuM4xrKPMZ5VJ0e0YSPUVGH+Dna4RI0c7hx5HkRK50VlMVGdM0Eydp4HD4YKqZ9EzfDwipwAVpxee+VN0Fop+2Fmds2GmnCV3XoFQQQGitmccxyEjihDQr0EYzTzNKCYokwRnPZrNitpqu6ZnmiUnrEzguQkU5wku++53f57d/51c57PaBozLHzEaTSsVP/fRPYZ3gcDxirQ8s8zji4eGI0Q4hBO9u34WL8zRFKMEwhJlvnuV0fRuaxoTMcxYnNPNI17aM48ByuWSeZ/oB+r6na3uUjBGRIbcXPL38Y7z1v0R/OAQpRVB2MjtHXki89mjtiIUnq0JiR6mEJHqMGr+FMQllET4bkYtASqx2ZFEQPrT9GLAZQpAXAaBnrcNow6w1ZVWQZgnOhkhyaGnbUyEwYhwHbm8PWBs47uMw0vcjXjlWyzXH5oGH7R1Shs2RsRNpmrFenXF3dwMERPd6vWaeDffbLXmWkKYFSiVEsWCchxCYwNMNHZ13FFmKiARZnnP3cE9eFqcZtafbH8jzcFl+PB64vXvH2aMzLi6e8NknLyjKhLIuiOOctunxzlNuSvr2CM6SpUuch7PLR8yzxsyGedK8vXmHjARpFB5qVVFhvEdKT9+PHA57xrHn4uwcAQxdF5qqzjBMI5cXF8QRdG3Ler0my3K6tufx2SVOjxz3e64fP8XGEZuzR8zjxDgNnJ2dsd3uyOKUwCVz9PPI4dgyTSP1YsnxcEAKy6KqiNOcuqj45OOPv+ea+n2xuEshKeoiSGNVdLqIkjRdwzgdmWwEaU/1/sTluadYGuJMoF3Gbpvwybc7tu8mLlYrElKOuuV3f/+7fOmDr3D56DGxTBBELDcbrAkpgzROKaqc/f4BM1vGvgsbSBVGG0kS0bRHAJRSJ850yf1hR13XpEkObqSIEwQh6pcXCXqeSbMcEIgiMN7rusZ5R5KEUUvXdfRdWLiSOMLZzzEJguy0050nTVHmIYHjLJLgP+27EeEVSRYQAPvdDm08etIsypwoChcvRZazrCq6vidJYrwIl7x6HhEikM53xyNx8oRILpDiLZPZU6aCSFU4t6FIn4BTmCgGHHEl0EPIEscRpwSLDVwWQsoA59kfmlOFOkUIj7Ea4wNGuaqXZFmGs6GF2LUtbddjfeD0SCmI4xQhImbmsKCbgSzLGYaJOE7Cg2AYiVTCy9dv8T6cxhAK5wVJGmb2Q9Ny++4Vv/Xrv8ru2PDRi1eoSHImJD4WRFHCh1/5Kk0/BC6PDRjasR8Z9UCWFYzjRNP1LFTN2DQn1n0BXjD0I2dn5/R9j5k1aRRxPB7JijxcssdxcII6h9CeSKXM80SkBMtySX/ckxZPeXT+Te7sr6PNASkMKg7yZRWB0+C9DDJuASqRlNFz5sOPMnQL8kgSRSnGDggh6NoOgcTMnnYYQYTTb993VLZms1kzTTlGhzx8ksREKuLQtaRpSH5JEXNsG/qhCy3wJGKZl19cQC5WZzhpmY1mUa+QSlDkFc7bIJywjt1uj5SKNMspq8XpVCy4evKYYxtwC+OoGaeJ5aLCWUdRBohWmiZkScJhv6PtOtIspx/6wIwSUNcVQkLb9YzzRJzGDL3mo48/oi4rymJN1zQIMYUU1jgz6SlwleKEdpzI0ozXr14RRXEADnqBE46yWNLsW+ZpF8iTSRruMJRksVyyXBSMw8j2YcvFxWWgQU4jeZqx3x9IolC8dE4yDBqfRJSrJWPfc3V+GSCCQvLm9RuyNODBjfGURUHTdRzbniJPKYqYy8tz8IEHJKkoyxwpFG03MsUJWfnPLsj+f/3LOcfd3T3GhssNUMSRpKoXSDOQXe54+nXDkw8zijIhTRbEosI7wWSOfPPHDrx63fKb/2CkeeEo2gy3UfzWb/82zS//Ks+vn1Mva47tkUWZ842v/iB1kQcP68kAE8wxYV5dFhlFGWBh0xQsNdaG8cr5+TkQSJBpEhynQknGZsB6Q5Ilp8apxVhDkSUndVawm09ziPudnZ3xuebrc+6NdSbMpaMIoy19H3ZcURzMTeM0YuaQgxVIsjQLuyttePP6NZvVh4FMGM4jzCfccT8O5EWIvCVJjLOQZnBeXzBNE23vSaKvguuQxhOrgtlK9AjgcW7CWIsQKox6vMFLhbaWcRjQTRv8nCeDFARcgIoE8zwyjzrscKRgu30IBhxrwgMVyIscGSXM84jThmEYsSbAz4oi+4Lzok6ze+fBI+jGgThN0fNMPwRzVEDdGtIs5dPf+11u3n3C48slH3/yKV7GTKNmtVnx9tNX/HNf/wb7fXdyWob30mjLPE9Yr2lO81EpFbvdnixJMdpx2LekaYIxlnG6/2Ik108txhh2TRvMRjqINEBw2D+QZRmL5YKiLri/3wMzfRuTZk/JkgPj9FsUtf/i/+e9OJV3BFmxYrn+gKtHP8HNzYydLzCzweHo9ZY4CfKKOE7ou4F6UdK1PUVRoKRksajRs+b25obFeoV1oQQXKYUV4f4pOaVOvLVYYynyjGkOl4PGzKfxCGhrUCrBTAO4iNVqQdO0jKPGmJAUqauaIgunuuPxLUVVoueZw/5N2MhFgnEI1fx+GMnTIpw2VULbjujUIlUQyLddT10VSOews0VVoT9QVTWRCuCvaRy4WC+JVcyyLhjaA/NsWK4qplGHtNxgGPqJRZ2zWlTEUQgexHXGw3aLSmA2lqJccH/7iigO7PmH7Z4ojkIRsj+SpQXnl5e0bYdxnmGacN6RJfGJuurRpqfvQ6Ju7AYkgvtxAiXIs+zUXB4DmiAr0WamXi5ZLNccD1ukh+N+G2LVccp6tSROUvp2YrM+Q0WCL334wfdcV78vFnchBWUdiktxLJHSYZyk72fKJzu+8idmLq8WrJINygsiWaCo8CrFJRuW2ZGzVUtVb/mtv9fDu6d4IXn/gw942O64vbvH2gnhNF2j+c5vfZtYfZOkqiiyJbMYcMqzvFihTqUbpRTmBBgSIiD4hZCh6WZNmNf74GsVUpLEgTuvJ4uzOgCwZJA8REJgvMM5FaQFo8GJkMaRSpLnOeM4YKZQqQ/xu4R6saTZH0jTgm7oiVTKYpVQluEyV8/h8i6KJd/65g+GmWuUhUucaURbQ6oEXohgJhKeSCUIYYkp2D5sycqColqHkZN6hBTQ9wPWjbTdhGAGAp9byhikAxsQqHp2FGXJrEecMxRZFnYaOnCyrfN4A3lRBmyDd8y6JTaBax5/frmqgnnGekGe50xjTywVWV6ipzHcLRAuj6w36G7COotQIZ3jrCXLEpyX2HmmO3ZcXJ9x/uQJf/pf+Rm+/d3v8p2XO17+xu9ytkg5NA3LYsmHX/tSSCpIyc3NHV3f46xBQsA2JCn2xNlPophmDNFSB9iTNyBJM8Z5Djl3EYiidV3StfvTJSFM44Q1hv1+y6xnbm7eUZUZ+31DXS8Zxoqy+mHMaLhtv8N6U5KXBc4YqvQxaX3B9Yf/AudnP0ySbqize37j279MkqQc2j3r9YY0Ldjvd0xDS5plgCSKZZhNS8U0jTjjSeKE7ng4GZCSsAEpa1YnVnukYmSsvhgnPRx2SCexdqLVIxebMx4Oe87OLsNcu47ZHbZEKmboW5arJTKNsY4TOz5FRSGE4GxYLPM0p+9Hirym6zu08Wz3bwNMznuun10RpYHbk9oESegKJFlJVEUBK4BAT5ppnri9e+B8WZOqBGM9L1+8xOPYrNe0fUuex2jbkUcZegravKYdgmc3L5idYVWWaOfQo0H7iQ8+fJ+mOSCEZLVaM04jQ/95+S3HaBdMazak0xbVkjwr2R8aFmVGe9xS1zX39zviNGG9WlNVBW3fIpwhyyKWmzWHQ4e1guVySde1TG1PlKasLp/idgfGbkuz33H95CnjYMmLnGkcaI4jVn9v5K/w/nsP5f+/+Lp6fOH//J/7MzgbbtSKIqcbOtZPe77+J/Z86Rvn5MmGhBTvJxJRIihAZCcuu0R7TWuO/M7vPfDp/xCRzCXWObQJ4KJ5CrLeNzd3PLy9CZeS08x+d+T80SOun1zz7PqK27s3fO2P/OAXY5N+akMCRkYkUUQ/9NT1kqoomaaQammOB4ybg25LhpLLOE5oaynL/HSZGNqSHoiVYtYTWZYTxwEhal1Akwa+tT798GVMwxQeAlIyjxP90KNOlMno5EJVSpzE1g49zYzTGJytSiKkRMqIcTaBtOdnFtWCrmlPM9eSNMtDPMxoyrII1WelQvIjTqirIjCmT9x7j0cKFeKa0rBYFPTdwKw9WocFRGtNUZWM/RAuUK3m9u4Ga2C92RArBVisCYWPNE5Is4xxCnE9rScQoVE7jtOJt2450XNxPohMlAjjn2mcGJ3DTiHienb5iKRe8q0f/eN8+uojxtnwt/7mf86f/Zf/DH//7/8id3cHvvXNrzOOgWneHBu8dOR5ijeWLC9II4W25guiZxrFCBWhtSXOQhzTu8DKGSdNEgV0s4oUWRJjtGO337Je1sxzSNzESYrVlr5vCGfGIGMsqwyl4JPP/ikiaslyiD380Ac/xMX7P0FZXHNW1myHI8us4m73jihSNMOExHJ9/SHGGl69esHm7Ix+6HHOU5UVQc5sSLOwYKpIUlYFwzDQdz3TOJEUCy4vz5F4xmFgni3OhVPp7v4eiSXJYuqyZnaSvCgDM33u6dsGYwEX2t/d0GOMoWuPbNYBp7Hb74mjhKura8qyQhHRDR2znoiimEPbUFc1WZYxDN3JVOSwOpw+IxWdJDNQZhVGT+wOW/quDZ8Nq4nTYH9q25auORIpwdnlGccm3EGdnZ2FlvdoAMs8aVSUcmgOKGvIipJ+CndXcRyxWq/Z3T+glGK5WnJ3cxPYLuMY8MjWcXa+pqrW7HZHZj3ihUYSsTm/oOmPZEnK4XAgiQORdX88MJ7STdfPnobPtpK8ef2CsigQXiLjmO3DkSQuSAtJFAvu7+5YlEv2+z1pEoVSVRTxr/87/8E/9d7/6P/Vuvp9sXMPMbcKpYI81vmZ5ZnlKz/2wOb6iJQFxhq8DIkVryz4HuEjpMgRPsUIR6YKnn1Zs/1uz/hpKFtEJwyqyx1lWXJ5eYH8oa+HuJ2UdN3A3f2ObdNzfvWYX/v2/8qbm3v6CX7kh7+ONRNpEhNlUYiIRRVd39A0x5Bf7kz4Ef0cWUrQ3mVJQh7FQUZxEvY6Ey6lpBJEXoVcvJ7puoGg3ovpug7vPXlesNseAs0yD3lXRYhTtYcDURRRrFZM04C1YYG3NsCaHBYlgwFI63A0NSbkxRHh3+iGMYwS+vBrmia0Q4uewnjDWhswpX2HdYHMiXc4F1AH3p/SB3FIUjRtR5SE6jVCoGSY/adZhrGGeZ5Y1DVVuQgLahwhREyaFSRxhJmGgBsQUWBmiKAAVEp+cQntVWikqiiiiIPIpO8Ghr4Pth6VkGYR3eHI7lby41//Jt/97d8my2K63ZFvvP8VMhlzv+uQSvHm7Q1CeOqqYrnImYxFOBHAWXNPmS2wJhy366oKAgdryYuYoiqx1rC737FZb4gjhSRczEqRBWuYiqjygr7ryPKCOqnpuhbvHNWiREUR02jY7w+8+/gN4zjy7u5A03SMvaMqcl588jE+3ZM6WEWSn/5Tf5Jfe/OSH/+pn8QrxUVZctzveXjYoSJJvVjQtM0XHJskSmiPDSqC+SG87hcXF3TdgDGOcRxJ04DafvHZZ9RlzjxN9MPIxcUj8jynvL7m3dtX4ZMtFDdv3+IRLFcLpHes6iXjbBjGgb49sN6EVuo+Cqq7siw425xxdnaONY5pGKnKmr5r0afxSl2VzLPm4WFLWZZIGcD4fdcGLpALHHTnHS9fvWC7f+Di4ozV5oxIhgd82/Xsmw5tHGeXj3A2lKIkhrP1Oc3xiLEzU6+ZTQ/On3hNhs1yzTDOxNLjrSVLCrYPOxZ1TT+OIUwgFTJJMV1PVqSU+YKHh3uazrLd3fLs2RX4hOOx5fXbVzx5+oS6qALt1ujAJ5oNICiLkofbe7z0XFycs754hFIZ2+09sbKsLmqmbqTvAlZlf9gxThN5kmIl9GYmqcrvvap+P+zcnz658H/l5/7V8MbPGpTl/INbvvITL1hcGLIiIY4XCLVAuIRIrfBeBCCPzEDEeGKcy7ER/M7/dsvtL9XMY2hFRioOiNI+IFWTU45aa4OKE5xyRCIc/47tgUPb8cu/8mtUZc4f+fJXuXpyhROOvMqY+ylEo2SYnVkzA5KmbUIFOslx1pz464JjG1jO1p741lqTpjH4kPM1NjQLkyT9gicfJzFDP5xMPnEQTktBGgUm9+fya6nU6Z4iZRpDRb8oU/AOazlFKRX73ZYoikOO2FnE6S3/vEgVuDsRUkjsyS6kzYx17hRlDBX2LEsp8jQgUQlJBmscZRWq4OMcAEuKkKs/NC1ZnlJXFQJomw5rNXVV040T0akmj/cURcZhv8c5iJTE+RmrHUmWnx4UPkTNZELf9VRlgZ5n5lnTNC1SCZyPyUvFm5evuXn9lq98+Rs8vXqEc5aDVXz3V/8JJBm/+XvfpcwkH3zwIaCp8lCoSfKQRpFCUZU1HheofWnKerViGEbGeSRJE7qhZ540ZV4GTLSCiIgsz2mHjjzL8Db8X7qupawqnBRfANNipYjSOIzLnMD5ieY40rYNi3XCbnfk5Sc3WCGZ9Rx8u/3M82cXONPxoz/208gs52K1xtnwEN3v93R9S11u3Vx5AAAgAElEQVRXTPNA0xx49OgJdzf3LNc1HhvatTrU/PGBIiq8J83LgLMQBG8CgmPbM0/BMdD3DZvVChXFqEjQdWMQgliLEoLlas1swxw/VjHjPDKMA/ViwTQOJ99xRJrlLBeLYEiyhn7owHlmozHGkSQ5u8OeJ0+uuLl5x6LOsS6ceLuuY71ao+KKsT9i9EBV5vTjxLKsORyOZGVJ2/doHaKDeZJSL5YYa2nbhsNui/MzcZqFRNswc388sC6KcIrNc0KfO9i9YhVGqbv9gTiO2e62tF1HkkcsFmuaY8/r1284v1wRRYK6XOB9TD80VHVCJDOECJaxy4szJmMZTaBgCu8ZupYkitEO+ik89JJE4Z1ld7/F2EC1tc5xOBzJk5SiWrBerdHTzJ//uX/3D925f18s7s+ePvJ/6d/8mVDtHQe0b1l+5Xe5+uqnrNaWrI4QUUaSbIAcJc/xIaOCFBkOT+RSbLTAovjs45nf/28VyiU0XUueF4FVogJTuh8HhJBfXAAOw0ScpkzGoKeAFl6vK+7v7vjOdz/mD37/JT/9kz9OligeX12TZjlt21NVNYuqDDxzAfvtHiEU0zwRRZIiCx7UvAhmlkNzpEjisICdyHNSEvAI4+dclfwk1ggM5+VigfZBHKA8RHEUaszTSD+E3ZeKJHGU0jY9jx6fczw2SJGgVOC/ZHl6Un559GzRZmbWUyBnRiG2aEw4XVhtQi18USO8YzZzGKvMmuykLEvi9FSHcgz9RFbUqJPl3RuL0TNZkhBnGQ/7B8w8k53adLMxxEloAWdp+oVj9uzsnLuHHdrNeG+4OHsM1tJ0HZPumYeRJCsCesILVssaAcxGM2vDNE4Y5/AEtsf//I/+AUbH/MgPfcDr17fYuOT48BJVVnzp+XtcP1qDzJCRwPuQ/OnGlqosQhlsDjnx9957zvF4oGta8LBcB15+pBRv373l/PKcfujpu5EsCp+3rMzDQ9ILIiFQKiLJMo7dgWEcOF9fMPUD4NhcXtBPhuZ4QOJIVMpys6DtZrqh5emTJygsWb5ksjOHh4eT/FlTlmloR3pBFBeMw4Rznu32jtWqIokjzs4eMWnHzd071psletZYq4miiCSOaZsjRZGSxxm39w+cXT4my3I4ieT1aXGf9UgsI5ph5PrZcw67I2kSY+wUPKpVSTf0NIcjRZJjnCXNc6JI0DZHpmE4+RTCbHKaNUmWoE+9Dmtm4jhjsdzQj8ES1Xc9eZGyXq9p+z6QUVXM7W4gU1AkMpTYtObsfMPYd+z3O6qqCrPvesHbl68D5toG9G6WpFSLnGH2SGdJY3j38EAZZeR1RTfPX4ABozhht9+TnApmdRX6HMfmwLEZmM3M2A9sVisEEev1GdM8c/Nwi4gEwniiyFOWK/bbB+qqYLae7cOWvKwwwiEkbBZrDscjF+driiTn9u4WrQ3WONIkyHuiJKMoKsa+QyrBp598TFUW/I1f+Fvf72MZEMKHWXEkUREk2cxhD14MLGSEjDXGChANUh3wSKSMEZwIiELhzRpvc4TMieMFCSmr1RLvQrJE67AgblZL0jQNTJpJkz/JyfKccZpoDkcGMwfx9vkjHj++4oPnb9gf3vCw3fGP/smvUFdn/It/+k8RJRmfvHhHlcVkmUB4iJUkLUuiOOj03EwgK049y7IgihPMHIiTszYs1yumsSc/ORE9jqLMMMYjXWB6q1OVXCpF2/W0bQ/eYXy46PRWUG8W7PZ73rx9yzyfKJhSoG3QrkUyAJDadqCsa2QUgQDnxvAAyFJiI6BIEF7gjIHTnHaxXPJwe0fXdCCDaEPGCUmUsjq7oO8amC3TOIfZKB6DRbdHkkiRxQVSSHCEuT9wtlyG701JrNPcbx9wBCyyd5Z3+obkFI0sTtiEvCiJspJESZzWNF2HnjXnZ2uyx4/4+OOPUXg2j1b8sT/+47x49Yq75oHFZc1qecbFj3wVGUeUZY3TlrZpiVWEUJ5pHCmyIG2I04g6TlmsVhyaPfMUpMerZc3x0OG8I04jIhVx3DeM88yqrjBah5FH31EUeehMzIbZWPpxIisWPLp6RiShUZJ5mmmbjrpeEi0l89QSyxhnwonq+fVzuq4ljhQPb14zm4m6zjBahxZsUgQS5zQwTm1g0Kcpi1WFTBT1YoV3Du8MURx2g8JpsjScDGMVoPNdO5Bt8vAAOuxDHHmaiOaMKIJmd0Abj7UzZV3z7u6OVCju7w+cn5+TJSl9N1Mvz5knx2G7BSFJ8xJrBOvVY3QRLsZfvXzDelmQZhn9PFDWJYf7B+q8oMxyrNV4O1OWS96+ucF7TxZPxFHKbB2dc4zDgWK1pJ87ShWSOsOsiVXE2E+4WbPd3jONHY+fbpgnTZptSJMsfL68J40U290dvs54+vQ9pEgYh5b++IDzgoPvkLFknGfaw4E8TXj27Jo0SUmzipKYSjrUuUI4yTAMvHz9kjiWKOFYLc/57NMX5HlEmo5cPrrAaAtac/X0kiLPieKaNzevef/Dr/HqxSu2D28Zc8M8W/Q8cnf7jmKxBiERqmEa3pDFIZ1UL1cslv8/GMtcX136v/yzP0MUxyzqkkm8Ibv+FbQYqVeabHkkqzxJFvR5QkV4IVEqZEaDD1UgVYbxGQ8fPeeTv7uiygKAy1uoFzVChMZj37ZAMJlEQpJEEdpotHUgQePZH7tgsI8CYKisU7phx/bY8vrFLWOnGYeGIqv50ofv8+EHXybLAkkvLxLmyQTWCA5nNDiH9YGvniYpMo7R1pzqzB57EhgrGUiX/TQhov9jxgwShQzf56SxdiYvixDTNA6tQ1QwNFvDnFrPBm0NVVnSNUest8RRSlEWHI8H0iQw8aWKmIYZj6eoSgTgZo2MEvSpPRuf+C9ZlgZjkwieVG8CX6RaLAGL84ZxmEJB5QRT887y8PBAFKfBjAVkeUmU5AxDTxwJmqZjmg1XV09Is4woihn7AKXyXtMeDxg903QTZV4AjmkOD7w4Cn2CVV3jnWWcNHGWg3BU5ZL7u1u0mTGTDXozb9CTYbVcgoBDc2C9XjHPOjyQHXCCsnkXoqpN0+C9Z1kvkEpybI4B7mSCpDyJg1haW0dRFEhnKcqKJM/ohyGke071+mW9wFrDPI8kWUqaZ9ze3qOUYL3c0DQd+8OOzSogOaZpIk0ChkLFKV3Xs1qsiKPAxmmaAy/evuRsc36SqCTMZkZFMVWxIIpz8qLEWYedRqwLEmiBYBxnijLIl8cxRG/n+XPgl2C52dC3OyIV0bcjUlmcD+RP42bq1Rm4lDc3L8mlI1eCxWbJw6Hlk89ekiUxH37w5RNoTrDft6zOQhMzL/IwkksCUOx+/0CSZ6yqBUVe8O72npv7O957/5rVcs3+YY/VM303cHd3x/MPn+JlRlzmTG2L6SciJSnyUIBKs4Khm7l7eEdZ5Yz9zKJaU5Y5zlve3r1imge+8tVvcvvuhsP2BuEMRZ7SDQOL9QqVpAxtzzSOrM42WK/Y3t0ipWKzWTOPDoelKoNHQkZp+CwPY0CYxzFCeYxxzEbTtEfWmzVVlVDXj/ns5UeUiwVDN5ElMe0wI6Ti2fP30LNmGnoOx5blqub29l2gqJ4irI8fP+Iv/OWf//7euSulqOsFRs8M/USxiXH2iPWGSSf4QTEbS1ZMyEgEjZ5QCBUcm8G5KXFC4yPNeC9Zlusvbtl3ux37vQnWeu9Zn7RdCBEWMQRZnuEJdpg4iZgTQ2saQJIVildvXpMXKednlzx7+gEKycP9G37j179N0xz57/77v0NVlXzw4WPM7Pjgy98gKWusPaL8TJZk2NGQnlCrWZEzTzP4QFFUKiCHvQ8wsRzP8XhgGoMN3jlHWS2ZTqafOCrQLpSvojgJrc7ZnBguQaRhdCjS6NmEbLyAsiw5HHco74iFoK5qptmwOF9inAvGm3kgjhTGB3P7/HmCIAkL3zxOVEUBsYIkFGKmcSLLY9qmx2jDahksUHmWsFyvEECal4zTEP4N62jbhqFvyNOwcK1WF1hjGfqBftyhVExRZkQq/gKXulktgj0eUJEkzRIipZDCh3GDlEzzxKA1zrpgwkoiYhUxRzNxpLAuQkWGfh6JVMxqeU7bNlyendMOPY4wmkriGLxi6IPDdhjGk4lOsF6vSZKE7cOO47EBkbDZbMiLGuc9RZqwXK5puhbjHE0TAGJlViCVP0lhBm5vtzx99ownV+9RVTV/8NFHDF3Harlm1hNf/vLXuL+/4XC4I8sKZi1Yr8+pioTDbou1GhXnXF5ckeclfd+h55kkztlsNicdpGF7/444Cncqn4s1irxkta4Yp5G7+3uun16Dkhz2B+qyxDh48eIzkkRSZCld13F+sWK5XNIce+4eNJ99+oK22/KVL32VxCv2ux2rqOC9Z+dcXV6j4ujUfbB0XcP6vKKslqRpMKApCW0bmp7OGSLhA8phHCkzyeWm5nB3z/7uARVnvL255+rZY86vHgXUc5pSlyW37YG0ClKcZuhYrlbEacqnr16hhGD/sA9FvsgjkhWxirg8e4JzmubhjiJLkJtL/uD3vsP19QXrsw3ex3in8F5RL9YolVJkBXM/Y3SD0x1RlNMOhn50nJ2dYX0QaqepYBwMwzjR9T1lveCrX/0BhmEkz0qsn8jyFc+vw9qzO+7p+plZjyyWOa9efBL0lHbm/Q+ekxcrzjdB/zj1Pdbq093XH/71fbFzf+/6sf9P/v2/GEQX2pLWA+/mv82s3rJ8lOOVw1tJnA7ExUSUxAHLeYqSCanAx4gowU5PaH/zj7L9SJGd6IJFES5JPodPRVKR5QVxHAUK3SnyJREnf6NGxBHaBVbKdn/Pw8OOsqqIZIxSMSoKF7Ly5CvV2rM9vAOvWS83/N2/84+5enpNVZb84A99i4vLS4axY1EFf+c49JhxBgE3D7eB1heFeN2sNf2oydKcMs9x3jGMI+2xYbNZkycqxBJPkm9t5hAJ9SqgVucZYzVOE1ySdRlalHo+WXpmsBbp4fr5ezTDGOb0URxeJwHOO4SMkc6SpSm7/Q7nZoRQQeGWJAiVEKcpeZYwtj3OB1iVkB47jySnNp62mmPTnC6VZUDMes84jwhhqYqwUy/zEhWn7Pd7xnEIXPKxQ0rFo8tHDH2LMZqmaVjUS+Y56OKM80QnOQnOY/HBzTpbYhUhHURJRNO1YcEWAi84naKCsNjokUQqLA4ZKZq2DVApHR4am/WGvh+RUWDkPDxsWa6WgMBZS1UW3Nze4pAUZU2eJiyqAJrSZkRJQd80rFYrvFK0TYMUYXbe9T3rzQUqjtkftlgzIb2n7yeclxRFSllIDoeG3a7l+ul1gNctFoyTJS1q+uOWoqqCfWnsqbIC4y0qSlguV7x8/ZKqSknimK4PFMVFVXE4HBn1TCwEzgWv59n5Jd573rx6jdYDm/MzoijB+5lY5Wgz0rRH4igmkir0QGRC27Wnn0iFNY71ZkWSxFR1hYgi8II4DjC/aZqZ+g4lPQ+7LVmWEUlBWdbIKOX+7oZIORwQZzVEcDwcaNuJerHh/uYGPbdsNpccuj0X5xuunz7DI7nf3oeTiQ+JIaEIp9WmZbvdk8WS1bomiUuc04zzxHp1hp00SkDXN/SzZtJwbA6cbzbgNX3fURYVUVwwTwfyJOHFy7c4AWVdB0SAM8xzx/Xz5xzbiUeP3+Pu9h3GDCzrmjhKydMcGQfxB87StR3t1LBcPWLoWvDhpL+93/Lq3VuqsqSuF1xerkEIyiqc/Jwx/Oy//YdHIb8vFvfnTx/7n/+rP4vRFik8i3XBVv9Dju5/obywqFRgZ4HHkBSeJBOo8Fk5RQ8liBzJJVH3I+jXX8J2kjgOCFJPuLiwxhGriGW9ZJonuv/TTb22hkhFLIoQUUMKIpVgTWjdWWsCZz0LWN+m7YLbcGgZJ33ifxuSRKJHw+sXHzMPB97d3bJrDE7VPH58xaPNkosnF4x9x9SPzMD68pIiSdhUJVIE/spsYHc44rRBRoqqDlaZPA2m9/3+ECh2SYRUQUIgZMRisWTWBmM0x+2WRAXVX5qnAbMbK+IkDQZ1E8ZOkwlZb/AMbZA8kMTESc7x4V3IbFtPdEKYOmco8pwsLbi5v6EucqSHerXmcGwwZj4JNWCcDDJOaJoGnMMYG3b90lOUJXVdBsdkFHFojozDzKPLC9r2gNGGrIiRMkLJmHE4IpSkaSfWqzVDewwL/WqNNpqqKJmn+fQ+JNzd78BJyqJgs1kyjKdC1MmVK6XkeDyGprHWAZ+gQkpCqXDZHh5k+UlbN1JU9YliGFJM4NHTyDwHablQocwmcJR1ycsXL04R0IooUgGYpjVCeqYxIAOUkgyjRmvHxcWaKAoSaSlilutNgMoJwXK14tXr1yfGiqBtOpbrNWmao/XAan1BWVW0xx3SGvbNAakiDoeW7f5IkkS8//w59TLU882sQQiyKmceBpyx8DmPqK6Y5wEpIY4LPIKLiw1jP6KtZn84MI4d0jm2D0e085yfr0jzHCtjrIGb12/Js5SLy3OWyxXeWZyZiFVMO4w0+z1lFkOsiJNgtZrnmUN7JEsi7m/uUUnMxZMrzi+vuL+9IZYWc/oenR9xTpEmgddujcUYx2K5xIkYREQSgbeW++2Bl3dHZpGQoVgsYL1cYOYO6WAaZ+a5QQoXClmzZXtsePr0Cu8cN+9es1wu8E5yvz+yXCyosgrvRhbLkv2hD43ieWS1Krm926JtjPUOiSPLEqoitMM9CVZKhMiYuy3H4wMqlqRZOCkKBJePLhFeMcwd0zgQywhjAvsoiiVaW7yDn/9P/8v/+4u7ECID/icgJYxx/hvv/X8mhNgA/zXwPvAp8Oe897vTn/kbwM8RfNJ/1Xv/i99zcb9+4v/6X/k3GPuBLI1Ii4JGf0QvfgUdvSDJDVJJ5tkilSTJBSqxCCVwNiii0+SSUvwEafdNXJ9w3B24vn5GFEUcjoETsVysaNs+8NUJLxTek6QRQgqiKGLoOoZhCDsSJHmWksQJ1upAH5wt9iRnjiPFOI9s90fabkRIRZrkxMrjnMY6zTxOfPejz/jok5cIAW9e3SDSmC9/6Us8u37Os6/8AMvzRxzvbhn273i0rhjGCestm80Zh12LsY6iCqeQ2VouNgv0rBkny6Ku8X6mrAq0sQynUo6UEIkgaHY27GallCA8Wgc3pDWaNElDVM2FSGUapxzagayuOTYdVRZ26pFKENKRJBld0xLJiKLImMcOYzQOSLIMqSRlWfFwv8U7i0ozZuvIswyFJ4oipmEI+Xzng3fSOdI8wwpC4SNSdMcDzsNiUZ74JzHOjcyzo1ysQ+tTzyRxQtP3OCzOCI6HI1IIrq6uUFGMMTNZmjH0I4uyoO0HZhuQrWmanNq19hS7TFBxiIyWRYHzYM1E1w5fvHbGhKhkkec4gtTbaI2ZRharJXfbHUmSs1osIRK0TcP5KffthWAeBt6+/Iyzy3OSLOX+/gHnQnN4GDrKMkepmIuLp4xDw7HZkRclRbGgOR6JEhnihMsLDrs9WaqYpp4sLfjo01eIKOby/Iw6S5inPjCLEMgoxHXzvGDfjJR5Tp5nIULZhALRPA4ob4mVoh8HVOQDX2dwODy7/Z7Hl5dEaY02HUkk0MOA8w49zux3e47jjCwKNssVyhqObcPV1bOAWZ5nnLHEp0byPI14O5OXNUIm7HZ7hmFgnnsWdcGzqytEFLPd77AuCg7bTGB1wH/MeqBebOiHLjRwrTm5DEbSvGCcLDJWmHlmuagZJk3XDUxTy3pdI0UaYGd6RMqY1aqkaXZgFdOs6YaWul4TR9EJiJcxzYYXr18ileJ8c8b2/jV/4if/edK04t3NHdtDMDU9f/Y+x/3AobmlaxviWIbXsrdsd0f2/Z66vOD66SqcKo89q8WSt2/eYazn6fU14zBw7B7YLNfURUy93GCs57jbkqiEfdPy7/1Hv/DPtLgLoPTet0KIGPjHwF8D/iyw9d7/F0KInwfW3vu/LoT4QeBvAz8OXAF/D/iq9/4P7cq+//zK/8d/7S9gpukUoUqJU4XKb2j0b3Acfx/jDyeFlkDFEKWBwOhsSp4+xZsrMvs1XLtEiiQgM6tQkBEiNESNsbRtF1RpScLUz9RVTZzEaD1zPB5Cdl5IFnXJOHasFkuMCZAr6wLcqOs6xmkCPFpPFEWJiuIgG1aKMstQMlStj8dD0N9hmY1hfzhytz3y9uaOoR/Yd5q7h5YkUvzwD7zH5fkSJWMuLlcoqejGkKyZ+g60wUg4WyxCyUMpcCGT7vAsV2uapmNRVzTtAXWS+15sLjkcjvS6J0/DaabIgwt17MP4JMvisJg58ARwVdccqOviJCQJ/aSmPXwxmrLWkiURaZYxGcM8TSwWC7wXzHomErDcrLl7uMcYTZkX9MPA8jSuaNoWFUcIHzgyszaUZUHfB1RzFIcEEbhwqZsEfvrnzdqyLDkcGow2THri0cUTBJ62Db/XjyNlUQQn66wDKrWo2DUNAM+ur9jvd5RlgZ41xgV94tnZBVJKDvsjZRky/KvFitVmE4o29/fMegpUzLrisD+Sne4o0ixo7I6HHe9/6cv0Xbi/0HpmnCeqouT+7Q1EgdIYRwHHOw0zKgbnDc55VusLDocDZZ6SJSnNENCv69Wa2/sjCMWTyxVxFC5q62rB/W6HI+xg9TAyzUF7mKcpZxfn9H0wGqVZioxEEGEME0QRkRMUdUGaJBz2B6yAJFEUKuHs/AkoQT/0HPdHummmyFLqokDKwNEfpom0KDgcD+GzIsMldKIUF2dndOMEOLzRLJfnIB0vXn7KenPG9uFAe2yo65wnjx4zjZpjd6BeFjSHkc3ZBTLySAk37+7ByzBejUIJ8PzikiTJkTJimEZevv4MbWes1egpuIzXyw3dPOGN5e7hBnwSqJ2LnA+ev880BQVnFEcUaYmUks9efMzjy0c4a9gdDkwmUDTLouTmfhvQI2bmfBNOyy9evGO1XrFc1UFjeBwQOKapByx5XjIbh3aa4z48wK6fPmW/7ZmMRLsBKT1dPwSstgsxYa81du7ZXFzzsG8oE8HlxTnGO/6tv/gf/j8zlhFCFKfF/S8B/xXwJ733b4UQT4D/0Xv/tdOuHe/93zz9mV8EfsF7/0t/2N979ejC/+y/9i9R5AXLZR1GDEKS5oKZe1z0Fu3vsL5lmrtgeE8SElWDq4jlc7L4OYoVfdfinEAJSV3lKBVIk9ZYhnFCnJRVbRMwvJvNGWki6YcOYwI/O41iiiJHSM/QDxRlRVXXIY+rDdMUlHbTNOKdoS4XCCnD6McapqlHqojlYh3kCM5wOHY07UBRRszjDMrjlOW4a/n408/4znc+Is0yPvvsLWlWUdcJP/5Hv8XbmxtA8eEH77NZVyTFgiypOR5vMEafTgoJKlIIEaBTAd3lcMYgRExyaulOekBPmr4PbJa8SKmKEu8l1hn2hwPOEZgc7TFklPsw806jNOzougNn5+eM2mK9Zx4nlAAZSR7utqRJSpwE4QZe4kR4j6NI0hyPYf6Z58Htig9WpiTBGkPTdeFEFEdkaZASDEOAd+V5hrWWYRhI0yD81kbjnSdLs5BFTlKsCemSPMuZT5dOzfFIluanenvBME887LYsqoqyKJjmKdxHRIokTqkXK6zzPDzcBQ+mgEUdCjx6HkGECKcUit3+yG63xwmDdxGXZ4+Ypw5nO/J6xTRprp48xjvPx59+Rnwybk1Dz3q1oswLjscj2/09V9dPSeKEm5sbkJLl+hyMBm3wImLz6BF3D3eM48D5+SVZEiMRjKOh6XaAC9YwY2mOLVkRxgJJknFsgzZxvVjSHPchFWQd11dX7A47sjSlqhcMQ3Cj9nPP2eacRbEgjsKJbOwHhq4jr3IggP36oed43JNXJU3bYrQJp6IoxuE5Pz8/cdEr+r5jHvsvlH3eSdIkx7gJ6aGqK0atmWcXLGPecuxaNqslUoSCn5SCOl+w2x/Q1jKMPf3QMRvLo/+9vTeLtW1L77t+Y4zZd6vb3eluU43b2LHzEJBAgFABiRM5RCJSCCBLVKgHEGDyYDlYQuIxPCAQ4sUiSJZoIkuAiCwhJQpEPAA2JG5ip3zr1r23bnPOblc/+znmGDyMWfdeoqJSSpVzru9Zf2npzDX32vvM9e21vznG933////qMSDY7h4IQifRMZ8lCBlw82KNkT1pKKmbmqIowEqUkPR9ix41cTrjxYsbhDWkccxoLFkaM+iRrFgglE9VHol8j0dPnvKwXrPfrhEWnjx+yjAMvPvOe2RF8jGprMgLhHSCdmW1RyqnkdOWR4LYRw+Ktm7oMXRtz9A1XD165HoFWGfyonuyyMNIt6tezpJJVC/hq1/7he9vWkYIoYC/A3wJ+C+ttb8uhLi01l5PifxaCHExvfwJ8H996ts/ms79gz/za8DXAGZFRprFiClhpqljiqVpRDMUlPUZgW1phzW+X4FnUTIgCZdIkyKIGAdXikhC5z2aRAlZmjjigx/geQHBZJbcD5rNZsdms6Zv9yySJfli5urmfe+6+1bTt8627eFhTVO3KM9jHDsnCRA47fXA92nammI+d7XTxo2KjcPIw3oDFqRSeEoxnyVoazFSI4Uk9lLUPOMnfjTjjdfepKxrXnt2TxiF1PWeb733FpEwBF6C6Edu7w90wy1CJIy24+nTK451R9cdmRUZAkvT9LS9Jgh9Fvk0Xw5sdxtmxYxDc0BKNXm2OsOA8lBxOB4Io4g0ccbcXVtjwgAr3OpfCNDaucvvthuOTQdSMSsKhB1JkpDwySVN0+JNZtJl2eBNSnl6GEjSCANT2UgyGqfl3jQdvpKcn1/SD25HtF6v6Xt3k5dS0HUdvu+RZTn7/Q6lpFPxHHrmszlmtBg9ae/7Pl7gUx86wiAkOj9HD4PTbxEKa32Wsxl66B0VPs84HDWBF9DVLfvtB4wW0sSZtXR9yzh2jpymQpIkBTRKSprmyGwWYV66qo8AACAASURBVL0ADHRtSVtXGKtZXMSkWcbN7Q1FMaMoMsAtNuLQRwjL/foe5SnOr845lkesBRX4jMbQDx1WuxHZY1myro689uQxoYK+qTgetKuxlzUSJtG3o9vNDS1F4CQT4ihB+QFtU/PwcE2WxviRI8UoX5LlIZ5yXqWj7kmTgPPzM4ZRsC8rkthOvrmC5WoJSmCMYL3Z4HkCo3uUyVnMV1zfXDvZiThGWMFufcAIwYfP7wnDkLOzJWPfOTvEUPKwvmW5XBEnubsRqYC0CNGjxgiJ8AOKImccRqSUfOuDbzHM4XZ7j7WC9fqOwBOM48BhL7m7uyOMI8zOmahEwROE6umGmigpOB42zNOEsRs5VgcG3VPMZszn52wPJY+fvcb24QHlS+ZZxmp+zjAOVG1HVVUUsxzdNHzrvXcIwgBrNI+fPqPXPbvdjsdPH7FYLDiWpfN4jT022yOjEVRVzaOrc/d5TyNn4lNVyNAnwXB8eCBNExJfEs9zbm/v0AgnR5LkWC9msD77yhnXpMXZd83b31Nyn0oqPyWEmAP/kxDij3yXl4vv9CO+w8/8ZeCXwTFUiywliRO6fuBYlewPDcPYT1rdIVGckgcFUeRqhX3Xwyg+duBJo9BZbQ0Q+QG+M4fEAp1u2LVbjmVFGISkiZMIKBKnDY7v7MWEBYmlaxqqytUx4zgkCJzu9XazwQvcRMtoFGEcUzcNh9bw/s17WCyeUpTHCm0N0ldIoYijEOxAFCqeXjxCxZLj8cj2UDEaxyANvIR5EXG2vITRUFZrXgjBYXdL3z3wm//H/+IIW77Puqx5/NqX2N7fcra64Md/8o9yd39DXdeOpXr5iFmR4+FKJaOStH2FLJUjVA3NJGmAWwWnMUIa+nGk0x3jvicMFE3b0Xaa2SwjjgOM1q6ubgVeb8hns0nrvqTbHAjD2N3YDGRxglQBgx7ZHQ74vitbJUlCVddEgWOsioltGWQpVVWjx57FYs585nZhWZ4jhKJpnYqflB6LxRIhmG6sTutdD4bR9GRF/rHLlpI+SZwSBB5NU7HZbFAqwPcC7OgazkhJr3vK4x65XNGPHXkRs35Y09Yj8+Wc2SxH647AlxgDo27wAkUU5zx7+kXeeuv3UcKSFzmd35KkEU3VYEZHElLKcyv9SUckiTL0qCmrI1ZYlJQgJMa25FkxaaIDo3HepkGAkR6hFzgROhVyLLcIX3Iod4R+jB0NURg5VUYEQ685liWXl1cc9ns2uzVnZ2esikdIIdkca/phRDJgjETQ4yuPUTsv0NvbHUmaoHXPYRx4/uKW87MlxhRuR9X2zOdzPE9x9fgxm7s11+/f8v6HH3B+dkbb5MznM1ozUNYtvnKGAi+ef8Dq/BzlRfiRz6MnT2ials12QzEv3PsJQ6y27HYHwjiia1xPaLfbYIzlYbeZPgOCJ0+foDDOpk6EvP7am/R9zdnqjKHveX77gmHoyNIYKzxaK5yEtdGslgtG64T7XIkmxErLfLXEDCNNN/Dhi+dU1R6lfDwvQIcheb4gTg1d11LMfO7XOwY9oKTThP/GO+8yy3O6viUprnj02spJj/QDsR/inSlqfWTsBfHjc2SQcnfzDpfPHjkhQSx+EHH2+Jkz39YaPRpnsSkFfuC8mB/W999/cv9UQt4JIf428CeAWyHEo0+VZe6ml30EPPvUtz0FXvxDf7aB6lihfJ8sK+j7jtgGzipMWawBZSKGWtNVB8eENAYhDEp69K0bi/Ok53TShaXvOwZjXBlFKcIocD6dUYgZFWZyDRqGgeOhYhj0NDrlZumN7eiHgTgK6bqGLEtp+4FBWwwjZbPHjFB3PaMZCQIPPEE6d7K746AJAkGgNKHv3I82uy15HON5Pn6isHWLAKSUCDuCGel7Z068uriiWJ0z9CWPXh/oy44k9LmrtvzG3/0GVki+8pV/kTTOCJQPccwsL4hCH08MDH3LMHRUXUvdVujBoIwlDlwZZ7Qj1f5AMSvwfYEVEj+I6JsapQTS03hSo6xgffuAmqZoMJY8n7E7HPEDHzM5+gyDZrFY0DQlbdfQ1J0z8bWgvIBFPiOOAu6unztp3KLAm6RmLy4fuV1Euef25pYodKYRaTxjtBYpfZarOW3bcjyWKOF8cM1o2O72LOZL/EnaVgj3GWjbCjM6ww8hHMkoCD0O1YFZmlAUGbPlko+ub+h6y839liDwSNKM+XzF0Pd0bUeSJOzWR2bFHBX6JEXCw+aOpql5WN/hBwLdDdSHEj+M6IYWK0f0UJFEEZHvM7QDF6vHBH5E1w+fqDZmGX3TAoJZ5rx4DcI1Bz05JXTF2WyFMSP90DLakTzPqZqWrqp57QuPaLuWzW5H0zqHqK5u8AOfvmvxPEGWxHhKsd1uWc5mbrwyjRm7HmkFgwClIs7OLzns70hTVzLT2qPrBt54/XUO+w0fPf8W88U5XdtRlgqpFNuDYRw6/CTi2RfeJPJ9hIUkyihyj0ePQ9p2cNo8hx2397fESUT5/EgcZyjlcXF+ST8YZvNzqrrm+e0taRyxKHKE8nl+8wHnl0s3VGE9urYljALHMk4iDIZ333ubJE1ZLZfc3jywmC15dPEUa50fwObYY9FcXv0w/dCy2W0xZqSqjxR5ihQeH12/wA8Exaxgv6+QUiKBKJAoJTFjz/XtNRbJYj6jrGqarqXXI4tZ7kp62rpx1Cwimxcslo/RA7z19d/mm8//Hq+/+SU2Dzu3a8pmjOUGKSSH2uB7A48vzjjs99ytN5R1y3KWEcQeAkNVHsGCHg3H3e675tTvpaF6DgxTYo+BvwH8FeCfBdafaqgurbW/IIT4ceC/45OG6t8CvvzdGqqvPX1k/8Of/6prngnn6PNtGVc1rey6vsPiND2C0FlsKaXo2ha33jYY67ZuzinIc8bLxpkdSOHueF3bOilcMZn0KgVKOv3wMMILA6wxNFWDNgZnKu18IEcD7aBpuw6tNVEQfpyYszjEUxJtnZpdEkfOOFoKvh1jJV2NTxvn5SqFoKobvNCj7QdGA2Cd8JhyjuptXaE8WG/u2azXeMpH6448y9ns7mmqhCj1OVsVGCH58o/8FNY2jL27Ti/xUVKySjNaPdKUPXHiGqq77Q7lCedLGaZO2a+pmRWZq7E2NQrBLC+omg4DzBcFL56/cAqUQUgQRZOb1ICxjpDy+rMnE+vXMUjTNGPQI3XVEIQBx8PBeWzO5oRhzPWLa+q65PziHF8JjvsdEoUKQqpDQ5RENN2Rs8XCTZwMA/PZnG+99y083+nAZGmOsT0C4comYsR0A13nGpnfnsoRQtJ0HXEYcf3iA7I8g0nQSgiB8tRk3NLSHI+cXV6hx5GHmxviKEZbg1CC7f4eYQ1ni3PMAMJXYF2pyTDSD4YsjkiSmDSbYYxEegqtO9dkH0fOz8+o6ho9DMRJQhjG1GWJMRqL8+IVysNYgacEkR+w2W7IigQ9jOx3By4vrzgejwjl07bV5BIWoYfeebamGVhLHGekecb9/R15mlHWFV3T0/euGd00Ox49fobvhWTFnK4+oLVFKZ+6KhFIZrOc+4dbivmC+/WO7f0N2+ORn/ypn4a+p1cenR4oHx5YzZekeQHWorserKWsa7pxJM8DQs/DSI9RSA7bHeNoWc7nSAvFbM7dZksYhSyLgt//vd9lsZxBEFGXB9raGXHo3ukTxVlCFGVkScqoNb4fEkUxx6PjNRg70FZH+r4jTBPOzp6yP+wYdU0UZAy6xyqLwaM8lG7cOC/QFrqqpjysyYuIw7FktTgnjDPatuewP5LlBX7oTc5Qe/bbAzc3dxRFgu/7tE3NF774JfAy50hW1ygh2KzvmS/nRFnGoWzI4hQ9QtkekEh0N9DpkovVEl9JxtGwXJ1znEaNrRXEYcS/8hf+re+r5v4I+JWp7i6BX7XW/poQ4v8EflUI8VXgA+DPAVhrf08I8avA3wc08O98t8QOoLWrgUshGA1IIfCCGuVJ6saNoSkEYRhirP1YH0IIQZamDF3vrsz1SunbFj/NGLVTXEyzzCVLKZ2mg+cxzYihpLsJ9I0jmuy2G7c10sP0f7hr7JoaqXwizyOPcgQCz/ewSJqmJU1cU7CttHO/EZIo9N12zVNI4WZx27Z1BCBwkqPzkNGM+EHIMI4fN46ssVitubp4hPIki/mKu/iW/e6W7aZle39HVkj2Dw+EquB+veEn/ug/QT/s2Nb3HKqaMM/YfrDhR57+OFWvmBczuvoFTd+wLQ/c3625WKzIswXt5AlaZBlh6LPd7wkCV5KySqIChbSWNImcRECQIJWPFyjqsmR/2LNczPEmiePeWvqhp+/cis3zA6RSbDZrdpst+aygaVsetjv6wVGuj/sjUlmGYWCZpRybhpGBEUWez6jrlvlixmhGHtb3aKNRKNI0wdqRwA9o6pr9fufo80M/NZMV5XFPkiSMGLftt3B+fkkYBSBdczHwA+LE3fT61umI+54TgiuKmZNxaGqM1eRxivLc77RIE7QR9L1TmLQSyqpFCUdwGoYOz3Pkss12TRwn1H3H9fU1y+WSMAioajcnvd3tGYaBKAlRvo/uLXGYYYwmiGLiJGboNKvVGYEfEoWRkz3QozNfR1AeDoRhgMFyLA/kWUFZldRNy7EqGbqeIEmJ0wDPa+gPJW88e4Nj3WC14a7umWUJXasZ9BHpG5aLJVXdYoSzwSyylDx9ky9ICAKf9OwxeTFz5a8kJY3caG43dPiexBMj9bFCGYs0AZ4XMRpojgeKNMT3IxbLFVXVOB6FJ0h8xbvvvs35xYpZkbEpG+qy5Itf/hIP6x1xEJBFKU3d8u6773JxcYYSgpv9DV/88pfxlaKrapQnKPIFox0JkoTD/uCcp8KY8lhx/eI5P/xjP4Qf54SRs/y7uX1BnERcXD7l7OKcuqkJ0zMO+x3r3fXHNorvffA2UsLZ2QVKSaIo5LWnT0AM9J0mX16AHtntPuRY99zfb3jtyRXnl1doYwGP1XxOW1cMneH2xXOyOKUqK86uVswWl1THHcq3PL++Jokjwjjl3fc+pP+HGGR/NkhMTx/ZX/pLf5G26ZxGilJEcUjbd9RtTRSGDG2PhKmpOSKEIM9z+rZjNNB1LZ6vUMpz2+/gE+MLTyk8KcE6r8JDeUR5jvLuyCyKcRgmtqOhamqGQeNJ5eRWfafNrUenM+Km5A2jMYxCYCaDaoElDBOshTCKCcLATZT0A6N2ZtC97gl8RRqHhMqViLQekZ4z1tjudvh+SN/1eNLRq6UnAYnRI52u8JTgWD/w4uYthsGy2+85evdks0t+6OqPcNQ7Xuy39K0m0nNm4YrlMmNRnKMInH5N39K2JfGkYHg4lERRQhS6aZckmzmtEuumWtb393hSIIRj8JaHlihJiGJX6nI2gLXTfQeGfsDiZsDDIMILfJCgtZMqCAPngzqbLZBCYgGDoW9rAinJihlN21FXe4IwxFoJxhIEirrpJjMIZ0S83W7p24anT13fvuu6iWUcuB3EJJHcNC0at2vK84LQ8+gGZ1KshFOHXC5WWGM/MScR7iYVhfHHjV0lhXPGkk5104yGKEgYho5+1GwPR9I0J/R9Rt27yQ3tJJ7n3959NC3D0CMniz7P92mamqKYc3t3T5rFKC+g6QxdO7CYpZihnmz73KSExXJ7d4sfBKwWS/q+o64qsixzNn+j4cWL51ycXwAKzwtAGIzRjAQEYURfH8mykPrY0o+jm6SRijgIiLOcJIvp+pGuH2jaI+++8wFf+uKXeOP119kfKmZxQNu2fP39a86KgsSX7A4PRH5AEvrIIKBpe5IwQMiAUViGbsTPIhg1oVD4YUKcZ3z4wXvs93uW8wXDYPH8gKZrsWaga2uOVc/5qiBSAYvzS5DOjHpWzDDjwHazRmtNkqYYBHf39+i2I0tTgtA1888vzthud9R9i8VgteVstWS/PeCHieuVYQlCHwR89Pya42FPlqacrc7I0oztYUtVVywWc6SUXF+/oMjnzGYFUezEyTzpSol61GzXW7quphtgFIY3X3/Tael3PUpKhDHc3tzQdi3Pnj6mKHLM1JQ+lh1ddSRNIjo9MGqNHTV//6236MaR/+I//6ufcYbqs0f2F//dn3MOMHoqhVingT5iCH2foeuw1iUHp7dssRbatpumYdQk9mRIk4Q8S1G+M35IEje/63seCohitwXXWruRuslpx/MVbdOyr0qCOJlIVSHjaD6u2apJD96MIwbQ1uAFEcqLJt3qlmEYaTpDbwzGuqRtjSUOQqepbUfiQJHHIXmWIoWg7dwW0wJxknDY7502unSJb7QWJSR2lHg+SGVpmordYcO+vOXDwzd4vr4hrQu+8PqSF7pmrHzeuPoJnj37Ec6KgofdPXYcaHvNxdUVSirSKKVrK9qmJAzc6hLpUyxWtHWFkBI9ah7u7pBSsJjnE408xAqBtSNZVlDVLavlHK0HHh7uUJ6bgokiN8vtJoBqp4fuuRn5NE0pjxVVVfP6m1+ga1s2+40jNfkhSEEUKjbrNVL6ZGmCHgaapsNY98ffNc7opK5L3nj9DXa7DVVTM18sQUpCT/Higw9IkoRhHLHAYjF3c/TCsVWVJ7DGybxK4cp6yvPohxFjBvQ4gvRopl5EHMdYa2jqBimdNVzsObGutu/wghCtNWmaT8l0RErP0fuNxvMDMCNRELo/ACG4u7klSROE9CnLmvk8AyEpq8pJ8oYKYQSe7/S867rm4eGe0YzkRYGwFmGhyHOqusT3nT9A27XOa9eLGEfDMPYYO9L2gqoqOVvM3ERRGHF3f0cUe+jR4CvBfPmIobf0umG5WnHz/J7zi4K79RrfC52kMc6mrxw0PoZICQwjx/2OOAxIiwtkmHI8HjncP5DGlmJ5Sdlbdus1kbLMljnH/R6DwIsSLi6vuL+5Y/PwgPQ8wjgiDX2CMAOrGYeOY9UQBCFdXcII0neKmIPu8QIfPwwRSlEdj4x9j5iKFH1fOQa2JxDS47jfEYU+s9mKh4cH2uqApxTFYsm+qvClR9WWPHn8CKMtx2NDN3QEgccsz+j7gbbtKRYrPN9JRBwOJbM8Rionk3Iot4QeFOmCm7s1V48ec/tw68YZgxBlJfvDkfX6lsVsQZTE+FGI5zvZYdO1aD1wfnHFbrcnCj02+y1CSb76F/+Dz3Zyf3J1YX/+a/8qwzDQ9oNrigEgJpW61tVvhWAcDMYagtCRbqIoZjFzpBglJWVZMptm0pVS+GFIUbgJBKTgcDzSdR16GIiCkKLI8eTEUJ0aqfuqwgsCwiCgbVqkEBNDzf0xWgNZUaC1pmkqkjhGeb4TbWoakiynat01d1pTlhWeVCznMzwpnaqitU7RUkoQzpxYSncDORwPNE1NmuQIaxkxFEWBFHJqGLo5cmPdnLdUHlX7QNPVvHj+EZvNc6qy5Tf/3nMODbTVkR/5oR/lp3/6x3jy+AI9SrzAx/MEQ6epjiUCy9X5iixL2BwOqCAiUI4JWJZOM6TrB5IoIk4S2q51q6zlEoSHUAGH/Z4o8OkHx4yczc4/3rmkaUp1PNK1Fcv53NGyPcUwDJjR1Xb1aJz1mtYkYUIY+3jCiYIZ63Y/fedGVZVy44Jd13Lc71kUC549e42mLanqiiBKEcpD960zHBaCMIwIw4imKbGjo/tHUUwYOoKbNW4XJz3FoEeiMKYpdyAE9WCcU5R0v7c4iiZNfsGoR8LARyqBNjjzhb5mFG413nUNaZq5RqkxBL5H37ZYHNmn63u6pmG2yKjqBt+L8H1noNI0A57vkyWuRFTVDUniSo7WjmjtVEOthMP2QOB5aNM7Jq3y8TyJ5ymqsnUCdHYkjhLiNKNrj2BG2tZJR9+v70nikOXZBdv1mmqygIuiBIwg9H2q45bz80uCOEEBXacdG9oPsHZECYWnApQnGMaB0SiMHjjsb5kV5zzsbkjCkDidc319TXnckSczrq4u3U5vtGRZ7jwH2obBGA5Vw2p2RtN2bLcfMcsytrsjgx65vFiipIcXeIRB4Ppdac52Xzod/UCihKDtRoI4pGv2HPflpI0T0fU1aZ5Q5Ate3NxweXWJHtxnYTQWKT23Gj/u8bGEkY/2Qo77HfVhh7Gw3u4JooA8jSnyJV2rqdsDcZwggoBm6Lk8f4y0Iy+evw9CEWc5AkkgFLd3t24kM/HpGuiMJsljsmSGtoaxqxn6nkdPnqKHwfUUfZ80SfhTf/YvfLZVIY01dIOmbVqMsQipJlu6gcBXhKFH4AuSOKVtekYsYRJzv95QH/bUTc2syJmlGU+ePCWOXcN1u3Xbp+12xzgajDH4cUCWZWRZxtB29FrjxW42fjCwWsyRXkA3dOhhJE4yZ6KMpWmcpV3Tu+13niQUeUHbNrRtRxRH+NMc/TAMBL5HnucUSYoZNVEUIiaN8qZpAIEXRJhxYLQGoWEUMMtnJEmK7wVT49gx8ZxUbuF6AVikCCeJXw8hZ1xdPONi9QVu728Q48CP/vCO3/q9t3n7m+/zrfc/oB97/vTPfIUwUOw3G4w1aC1YLjOGvsdKSdn1WKVo2hoR+Oh+wBhDHDt3+sNhx1vfeItHTx5zefmIopjz/vvv0vWai/MVfWeY5UvavmW73ZAkKXHsWJtNU+J7EuW76SNpDWEYU5V7et0hUKyWS4TyOJQNXdfSGwh9Qdc35JkT6nrYbAh8p+Z5fn7Gs2ev07cdm90GKT3ibAZY9vstuu9cyajtaesDcaKJs5CmHgmjEE95Tj97GNx4ZSAmMxWFHloQ4AU+sWfZ7SrybE6aJkRRRFu3dH3rFA2t4XAsWSxWbDcbfGXJ5464AxalJH07MI6aoWtd6cAY+rYDO3J2cY6SYEZoWs2bb/4Qxg7c3d/RND3DCH7kc2y31MPAqphNRDxBWR7xptHSs4sLDvsD2WzB8XCgbSvSNMVTkRNAWy7YrPfc3N7y2htPGZoW5fmMFnwvoCgWXL+4RgnL2cJp7rf9QFNXxKsF52dnCGHxpWIcemaLHN31E2diZDk/o+s1TdPR1gdsP3Bx9Zgofszd3T1JkjLLCpK0YL5c8OH778GgabuWbhjYrB9Ik4ggCPGDCKTi6uLM+efqgavLR5ix50d//DXefudd0nxBFPno0eedt38fqXtWqyUGyeawJ89i0iRjs92hPEkc+mRZzmK5wlqPbjSU5YFd2TFbnDN2I13fuUVAVbJcztGDRnkhbddgEXjWEvkR22Hg7PySKMsYB0sSe6zXG7S2XF1dYrAo36MfLLfXd4ShR9k0ZEmMNJo8c9NffiCJ04w8SVF+z/FhTTJa7u+fE8Yhq7MLHjYHPvzofUyv3cx+WnBx/ui75tXPxMr92eNL+2//m3+O9YMbt+snJ6LAc7ZfWZa4pNl2SM/jYbvBCkGSZggpiQKnny2sZTBuAiaJI5TncSxLoihiPluwWa8JEiealcYxmBHl+2AdazKKnAJjW9WEcYTyQ47HGisMUkqCICIKAsq2wgwdSRBihNMnHwbtrLgChZI+xliKIqPrnCznt+e8he+5iR/fx+iRqmnRw4DnKUKlyJdz5HQD0XpktTpnVrgPATjt8KZx3pOg8HxHEmq7nmN5ZNQazxPc3l3Tdy1GuP7Ezd011zfvc/ei4emzJ1xcPqEocq4uLzG0DN3otHTSlLKu6Pues0VBUzXUde2S0ainvgRUdcXZ8pxxMOz2t0RJDMJydfmMDz/6gMD3GHpDUcwJ4xSpBE3pvDyDICNOY47HA9XhyKxIEVIydJr94YCVimPdkEY+F2cX+J7z1gVJVdeMxhIE7vPRtB1hmEwaMCXD4Iw1BJpumqaIwpD7h/W0oh7wo5AgcPH3hKQbeqSnWMxmKOXExNI8Q6HwfQWTSUqWppP0sEWPbhECThJg0JrN9oGqrMjTnK6t8cOY5WrFbr+edGzcWK4nFavVmbNU9N2Or+8tZmzJi4SsWFBX2snRHnaUZYPvewSR76zgkozb6xckUUwSRJTlgTAKnTxGGIOFXXnk/v6BOA5J04TZbEFZHhlG5zC12W6x0qK0xeJxdnlJXR5d30LA7c21s8jr3ECAGUfSJGe1OMcKQ1W2WD0SZhGR8hGKaax1pOucefVilhMpn812h/R9kixD9z11XROlGauLS6zuWd/eOOmAvsMYw2pRYEdLECeMxrLfub5LHDt/V2tGpOdh7Mg73/gmnq9I5wuUMvR1RZHm9OPIiGAc3G4ijGIEFj1odvudEwcUPlE+w5dgdMfusCUG+rEjSjLaukcbSz9oijyjqkqMssyKOR4KPXYcypo0jYjCgrrakeczV4La7wnThCiJsdZju9mjlCDJYwLlxngtcHFxjlKK/eFAFETsDgeE55H6PnVXIqRgd6gYNJi+xlM+vi+IogwhPb76tX/vs12Wefr40n7t3/hZsBCFIf0w4EoykMQRYGm7DjFa0izGCItUTmpUjwatIVKKOI4pG1cHjaKI0Vja3tl4xWHE0Hf0o2HQI75020ypFFEYY6d6bD90zPKcvh8wQlFWDZ7vIaUiimIOuzVImM8LEj9kvds6ITIL2owYC1K451maOFJTWSGEoO1ainnhSCtTp3uz2bra8dBxNpszSlDGEkQRcZziqQBj7NQc7olSp3nTta1zJvI87GhBCrqhx4yacRzc877jxfVH9J1rYB73G8rjgapv+PXf+DpZPuNPfuVfYHHmJgRGPU4rtY7t+oE4cvIESkn80PUZ5vMzHvYVZb0nDQICL2CxnJNmK0Tg4/sxNy8+IA4Uh8MGJX3CJGWz27C5v+NsNWfoQfmKPE8x2hCFPnbE/c5GTdO3dIPGji1ZuiCOIh7W9yjfxxqmOmdDmkRTI3dAG9eAHnqn4dG2JfPZHN8PWG82BFOJ7dnTp+yPB/p+AGvwpcKPArR2Eyht07ldizB0dU8Q+AjPY384UhQFke8Rhj5VM9C2A9IbMcZQtwNJ5GPGAWskfhAyny1J0ojbm+cgIAxjJ013LgAABStJREFUpPLYrDcopbi6uuLu7m6a7vFRSKIootMjxjpSjERhYRqnNQxaI7yApu2YzeaczReYfmC9e0BIwTxLSZOUpu+opqZtEDgt9jiOnZ+vHpx0AwZ6Q9tpiuWSJAzZ7XfM5wuCwKfte/pBc3l27ohmgSOL+YFHkuRUZYnwJc3hSJan6HFieI+a0YykWUbf9rz/ztuszs8YRksYxixmM/zEWd0ZPYB2XALlK8qypG9qPD9gHC1B6CaERu0a+cYYdruHSTPd+ZtqK4iSAiEtddnw+mtv8ju/8zvMFzM8H6pDydXVFdvtFj1oVsslVV1RVS3rfclylrKc51TNEVNVCE+yP5YU+RyhQtbbNX0/4AeKIA5Ikpyz5Tl9W9N1A3Vd4vkpYSDZb3YTh0RTjz1jP1BWzmDk8vKCYj5ns16jhw5rDUIKxxRWPr7vM4xu5DhAECXOZKVqGm6v77i/u+bqyevM84y+63jjzdf52T/7r322k7sQ4h6ogIeXfS2fEZxxisW3cYrFJzjFwuEUh0/wurX2/Dt94TOR3AGEEP/P/98d6FXDKRaf4BSLT3CKhcMpDt8b5Mu+gBNOOOGEE37wOCX3E0444YTPIT5Lyf2XX/YFfIZwisUnOMXiE5xi4XCKw/eAz0zN/YQTTjjhhB8cPksr9xNOOOGEE35AeOnJXQjxJ4QQbwkhvjlJB3+uIYT4r4UQd0KI3/3UuaUQ4m8KId6e/l186mt/eYrNW0KIf+nlXPUfDIQQz4QQ/5sQ4utCiN8TQvz70/lXLh5CiEgI8RtCiN+eYvEfT+dfuViAc38TQvymEOLXpuevZBy+L1hrX9oDUMA7wBeAAPht4Mde5jX9Y3jP/wzwx4Df/dS5/wT4xen4F4G/Mh3/2BSTEHhzipV62e/hBxiLR8Afm45z4BvTe37l4oETrM6mYx/4deCffBVjMb2/v4Tzhfi16fkrGYfv5/GyV+5/HPimtfZda20P/DXgz7zka/oDhbX2fwc2/8DpPwP8ynT8K8C//Knzf81a21lr3wO+iYvZ5wLW2mtr7d+djo/A13F+u69cPKxDOT31p4flFYyFEOIp8KeA/+pTp1+5OHy/eNnJ/Qnw4aeef0cz7VcA/x+zceDTZuOvRHyEEG8AP41bsb6S8ZhKEb+Fs6z8m9baVzUW/xnwC4D51LlXMQ7fF152cv+ezLRfYbwS8RFCZMD/APy8tfbw3V76Hc59buJhrR2ttT+F8x3+4z8II/o/bBBC/Gngzlr7d77Xb/kO5/7Qx+EHgZed3P+RzLQ/h7idTMb5QZiN/2GCEMLHJfb/1lr7P06nX9l4gDOiB/42nzKih1cmFv8U8LNCiG/hyrT/vBDiv+HVi8P3jZed3P9v4MtCiDeFEAHw54G//pKv6WXgrwM/Nx3/HPA/f+r8nxdChEKIN4EvA7/xEq7vDwRCCAH8VeDr1tr/9FNfeuXiIYQ4F0LMp+MY+Arw+7xisbDW/mVr7VNr7Ru4fPC/Wmv/dV6xOPxA8LI7usDP4KYk3gF+6WVfzz+G9/vfA9fAgFt1fBVYAX8LeHv6d/mp1//SFJu3gD/5sq//BxyLfxq3hf4d4Lemx8+8ivEAfhL4zSkWvwv8R9P5Vy4Wn3p//xyfTMu8snH4R32cGKonnHDCCZ9DvOyyzAknnHDCCX8AOCX3E0444YTPIU7J/YQTTjjhc4hTcj/hhBNO+BzilNxPOOGEEz6HOCX3E0444YTPIU7J/YQTTjjhc4hTcj/hhBNO+Bzi/wWFfulcT9L95QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Caption: dog is chasing ball\n",
      "_____________________________________\n"
     ]
    }
   ],
   "source": [
    "for z in range(2): # set higher to see more examples\n",
    "  pic = list(encoding_test.keys())[z]\n",
    "  image = encoding_test[pic].reshape((1,OUTPUT_DIM))\n",
    "  print(os.path.join(root_captioning,'Flicker8k_Dataset', pic))\n",
    "  x=plt.imread(os.path.join(root_captioning,'Flicker8k_Dataset', pic))\n",
    "  plt.imshow(x)\n",
    "  plt.show()\n",
    "  print(\"Caption:\",generateCaption(image))\n",
    "  print(\"_____________________________________\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "colab_type": "code",
    "id": "a1mncR2JPno-",
    "outputId": "c2a1a559-6e7f-4d95-eba1-50c9cfc8f742"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2048,)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "encoding_test[pic].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "HmPT4uNu7hgN"
   },
   "source": [
    "### Evaluate Performance on My Photos \n",
    "\n",
    "In the \"photos\" folder of this GitHub repository, I keep a collection of personal photos that I like to use for testing neural networks.  These are entirely separate from the Flicker8K dataset, and as a result, the caption neural network does not perform nearly as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "-jl0BUNIMxGv",
    "outputId": "6a02490f-4729-495b-c8eb-d0a0d406c3e9"
   },
   "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": [
      "(1, 2048)\n",
      "Caption: two dogs are fighting in the grass\n",
      "_____________________________________\n"
     ]
    },
    {
     "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": [
      "(1, 2048)\n",
      "Caption: two workers are sitting on the curb in front of building\n",
      "_____________________________________\n"
     ]
    },
    {
     "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": [
      "(1, 2048)\n",
      "Caption: two dogs are fighting over bone\n",
      "_____________________________________\n"
     ]
    }
   ],
   "source": [
    "from PIL import Image, ImageFile\n",
    "from matplotlib.pyplot import imshow\n",
    "import requests\n",
    "from io import BytesIO\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "ROOT = \"https://github.com/jeffheaton/\" + \\\n",
    "        \"t81_558_deep_learning/blob/master/photos/\"\n",
    "urls = [\n",
    "  ROOT+\"annie_dog.jpg?raw=true\",\n",
    "  ROOT+\"landscape.jpg?raw=true\",\n",
    "  ROOT+\"hickory_coat.jpg?raw=true\"\n",
    "]\n",
    "\n",
    "for url in urls:\n",
    "  response = requests.get(url)\n",
    "  img = Image.open(BytesIO(response.content))\n",
    "  img.load()\n",
    "\n",
    "  plt.imshow(img)\n",
    "  plt.show()\n",
    "  \n",
    "  response = requests.get(url)\n",
    "\n",
    "  img = encodeImage(img).reshape((1,OUTPUT_DIM))\n",
    "  print(img.shape)\n",
    "  print(\"Caption:\",generateCaption(img))\n",
    "  print(\"_____________________________________\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "zFZpd0AZevxz"
   },
   "source": [
    "# Module 10 Assignment\n",
    "\n",
    "You can find the first assignment here: [assignment 10](https://github.com/jeffheaton/t81_558_deep_learning/blob/master/assignments/assignment_yourname_class10.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "0QMn6sx1PgWy"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3.6 (tensorflow)",
   "language": "python",
   "name": "tensorflow"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}