dog_app.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Convolutional Neural Networks\n",
    "\n",
    "## Project: Write an Algorithm for a Dog Identification App \n",
    "\n",
    "---\n",
    "\n",
    "In this notebook, some template code has already been provided for you, and you will need to implement additional functionality to successfully complete this project. You will not need to modify the included code beyond what is requested. Sections that begin with **'(IMPLEMENTATION)'** in the header indicate that the following block of code will require additional functionality which you must provide. Instructions will be provided for each section, and the specifics of the implementation are marked in the code block with a 'TODO' statement. Please be sure to read the instructions carefully! \n",
    "\n",
    "> **Note**: Once you have completed all of the code implementations, you need to finalize your work by exporting the Jupyter Notebook as an HTML document. Before exporting the notebook to html, all of the code cells need to have been run so that reviewers can see the final implementation and output. You can then export the notebook by using the menu above and navigating to **File -> Download as -> HTML (.html)**. Include the finished document along with this notebook as your submission.\n",
    "\n",
    "In addition to implementing code, there will be questions that you must answer which relate to the project and your implementation. Each section where you will answer a question is preceded by a **'Question X'** header. Carefully read each question and provide thorough answers in the following text boxes that begin with **'Answer:'**. Your project submission will be evaluated based on your answers to each of the questions and the implementation you provide.\n",
    "\n",
    ">**Note:** Code and Markdown cells can be executed using the **Shift + Enter** keyboard shortcut.  Markdown cells can be edited by double-clicking the cell to enter edit mode.\n",
    "\n",
    "The rubric contains _optional_ \"Stand Out Suggestions\" for enhancing the project beyond the minimum requirements. If you decide to pursue the \"Stand Out Suggestions\", you should include the code in this Jupyter notebook.\n",
    "\n",
    "\n",
    "\n",
    "---\n",
    "### Why We're Here \n",
    "\n",
    "In this notebook, you will make the first steps towards developing an algorithm that could be used as part of a mobile or web app.  At the end of this project, your code will accept any user-supplied image as input.  If a dog is detected in the image, it will provide an estimate of the dog's breed.  If a human is detected, it will provide an estimate of the dog breed that is most resembling.  The image below displays potential sample output of your finished project (... but we expect that each student's algorithm will behave differently!). \n",
    "\n",
    "![Sample Dog Output](images/sample_dog_output.png)\n",
    "\n",
    "In this real-world setting, you will need to piece together a series of models to perform different tasks; for instance, the algorithm that detects humans in an image will be different from the CNN that infers dog breed.  There are many points of possible failure, and no perfect algorithm exists.  Your imperfect solution will nonetheless create a fun user experience!\n",
    "\n",
    "### The Road Ahead\n",
    "\n",
    "We break the notebook into separate steps.  Feel free to use the links below to navigate the notebook.\n",
    "\n",
    "* [Step 0](#step0): Import Datasets\n",
    "* [Step 1](#step1): Detect Humans\n",
    "* [Step 2](#step2): Detect Dogs\n",
    "* [Step 3](#step3): Create a CNN to Classify Dog Breeds (from Scratch)\n",
    "* [Step 4](#step4): Create a CNN to Classify Dog Breeds (using Transfer Learning)\n",
    "* [Step 5](#step5): Write your Algorithm\n",
    "* [Step 6](#step6): Test Your Algorithm\n",
    "\n",
    "---\n",
    "<a id='step0'></a>\n",
    "## Step 0: Import Datasets\n",
    "\n",
    "Make sure that you've downloaded the required human and dog datasets:\n",
    "\n",
    "**Note: if you are using the Udacity workspace, you *DO NOT* need to re-download these - they can be found in the `/data` folder as noted in the cell below.**\n",
    "\n",
    "* Download the [dog dataset](https://s3-us-west-1.amazonaws.com/udacity-aind/dog-project/dogImages.zip).  Unzip the folder and place it in this project's home directory, at the location `/dog_images`. \n",
    "\n",
    "* Download the [human dataset](https://s3-us-west-1.amazonaws.com/udacity-aind/dog-project/lfw.zip).  Unzip the folder and place it in the home directory, at location `/lfw`.  \n",
    "\n",
    "*Note: If you are using a Windows machine, you are encouraged to use [7zip](http://www.7-zip.org/) to extract the folder.*\n",
    "\n",
    "In the code cell below, we save the file paths for both the human (LFW) dataset and dog dataset in the numpy arrays `human_files` and `dog_files`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 13233 total human images.\n",
      "There are 8351 total dog images.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from glob import glob\n",
    "\n",
    "# load filenames for human and dog images\n",
    "human_files = np.array(glob(\"/data/lfw/*/*\"))\n",
    "dog_files = np.array(glob(\"/data/dog_images/*/*/*\"))\n",
    "\n",
    "# print number of images in each dataset\n",
    "print('There are %d total human images.' % len(human_files))\n",
    "print('There are %d total dog images.' % len(dog_files))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='step1'></a>\n",
    "## Step 1: Detect Humans\n",
    "\n",
    "In this section, we use OpenCV's implementation of [Haar feature-based cascade classifiers](http://docs.opencv.org/trunk/d7/d8b/tutorial_py_face_detection.html) to detect human faces in images.  \n",
    "\n",
    "OpenCV provides many pre-trained face detectors, stored as XML files on [github](https://github.com/opencv/opencv/tree/master/data/haarcascades).  We have downloaded one of these detectors and stored it in the `haarcascades` directory.  In the next code cell, we demonstrate how to use this detector to find human faces in a sample image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of faces detected: 1\n"
     ]
    },
    {
     "data": {
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KRMlN1clxaPc4jonj8djAZrNZo10geatnt7/n/v6e29tbdvcPHHZ7hmFovEaMCYkF+BTMqppQZwO763wBVQUyOcHxGA1YxpE37o4QYL1Z8fL6ipcvX3B9dUEcrrm+umC97s3PQjzO1UjXicCs6kEdO8UVDJyZP9VZ2xJaHExdW5zGnJAYUTxZEhSrU8JZ9KwD77v2jB+Nhhn5+RwYfAhv8dyxp3Uv1MmTdpzjZn5s+STAIufE8fgAnEHqXDD/hB8w85a2B3x67rLT3Ml35/VYETM56uz3eaenspyICJKrS45AVluV64p9Ml58ub6WHzxQtC4ydbWfqVgATnBFzcqSiuRSrAZSLAXZ+u5wGLh/u+P+7oH9/sjx6BmOIA5ycgxRGYbI/nBgGAbuH+4MWBIMw2Amz+NIGiPrjZkWU0rEaA5YVWJ5d/u2+VnEaEAzjkAqPgkCIdgEm1sT7GX9UC0kIsJhvyfnRBwz+3jkcH/kt7/+FnHw6mbN1eWGm5trvvziJa9evWS9Xlud1eVdPDmPpo5KxrtMIpI1W995EO/Aq4GaF47jyP1+R7jriJrpVj0aOvAO53xZiQXRqmI+TYyeG3d1bCbi2Ymqqs1E+1w5d+6zE7/kTKn8kyuOcN77jwYYnwRYGBNeRCZ/ojLkJbKeQ9NWx/ewxU89gInZnqkmZ+pIMrbz5lKFFOvKKVhM13OLk+aShPiy0pX7WuZYsHDwHJXQ/ABSa2OvHt8lcj7wcFD63Ug3ZMCx3+8Y44HjIbE7jOx2B97d3/Pw8MBufz/dZxZikRKGYWC73VoCmDQ20TarDfx6TM5AnojHVNwdVB9HD0/PzTXLhvfmELXd+Bb16UikNBLHIzFm3r07cNiZhyhZ6bqOruvYbDakfLQFQFPpEwpxm0AV1Tg5aKFEzayCEIIj9N7q6j2h7wjBkYOg4nDVeU61qRxVYhSkGVnqPTUOYfas6z0nnVTP0/E3VyfO9dUPKTEux3J1Z6/j5mPQFp8EWDgnbLd9u9GnJrecdmjLYvT0OfW75fcTn3FqNTkXTd7Uh5kWMonWINVpSs8TTE5qYphJMjKwyA0s4iwXRXupJyfQLtP7mnchE2NkzImHuwOH48hxjAzHyOE4cjiM3N3t+c1vvmO3H9nvRh72Aw8PD9y9e+Bw3DGOoxGFrsR0qJQkNhYTIZLMr6EMOMWRRot+NeIQEHNmEhFIEKvVIGXibMCPowHstNpN0sVmtcVLwHtHcB0hBDofyDqSxgMxwm635/Xr1/hgvfriRaJfWT9YmIk344NYdKuooOoRCz5BNRGzsA4GDpvtiourC65vXnB9fUm36olFSqljSzRBTjigm88QnZy2VI3Pmf14OmhmE3/JHbUzzqgVp0DyFHicgkvMZZHRJWjEKhmdreXDyicDFpdXm5Nvl0TlvNQOcvp08+edXkVk+1ziKOAROD1V2vUegUVtaVEXVG2S6fIhN6dqMUtP5SzAXKxNsjCJQEpjRQSJlpSFrIxAEEfKiTFlHh4O/Oo33/Lu/sD9w8Dr2x3fvX7L3f2B33x75Fe//IbdfuR4jByGyH5/5OHhgYyRmV4cOQRC6Ns9ei8cj0ecm3gYLcluhqHEhKhr/VCT8mSnpiBl8xad33tS8GIkY0qZKBMZnEaKxODpvBCCEHxH5z3ZK+gIqtzf7xpI7vd7fud3foY4LTEe4J1HXAbx5g1qDvF4STZps127+nxstisuL7dcX1/Tr1dk50kqk6qbI+SEF8W7aUGq/TSZutezMWYKZHuuLe3H+SC908/zY09/PyX253W29uhSomsyrRYjwV8UyWLRyXnuO/BEVGLpmMhkLjp9KM8x5vW7ZdDU0kFpYXqtaoiODbnhhO6sbHTKExlbLSPzgUZqlpbMfFIV/wiZ1BCnAVFlHBIh9DjnOBwmf4df/Opb9ofE/qjc3w+8vn3Hw8Oe33535JvvXjMOyjCMHEctYODRqLgKbsVTk2SkYXQDOZpo3/WeEEJbPQ+HA5qFzhcpSWdu6VIT3kBGiwmyWnfMwkXhAqw/CvE7puLbIaxWHVvXI70n+IDvHN5lVBO73QO3tzuqGfzm5so8QJv5Ulrfu2Ben1kHmyTO+Iys2YLoxPqhqjUhBKJ6xE8TUdQXySLjXTo7fqbx4hZjpI6fUaaxOX8/reNcmfvJPGVNmb+blNUt6s05oymjMZ1dcH9I+STAIsbIt9+9Buokn6bh/P8F8qprk7J1zhnQOFdOGeY5eTpH4VMAqeg9j9WcTKXJhmyqnpRxVodNrKi5cQ6ZGbABMWvRqmaE6hiL6jH1xW63Y7fbcfv2HW8fjuTcMSbHw/3Am9t7drsDr+9G3t6+A0yNyYhFnOYlw54zkEbLCB4j1cIbAuTco72g3TRgg6tkmVu4lc/vxfrKHplrg3zS7a1PKL4MiqjgcagKUTMhKqKRbu1KSkHjK5QjwxC5vb3l7vbCyDtZAQ4VqydrxiWl+kpNk8z8HVQzMQ7FXX1HCD3dEFHfmeN4WwQsAM1pBnc4qWsai957aL4+J5Y69xgk5mCilWg5MybtWqdgMpHz83cA55QQlmDRXsmsYO7p6fDe5ZMAi8PhyN//e/+o2eVbYBOQdVrlU1oCQUoTWMw/Lzt56f5sxFRYnDeXZlKJvCQvgcckms2iTtPdy7nVTyRbCPg8x8RQRGC7TmqTS7U4ZGXhOFQQsWAwI6iMW4iF0HBSgsQ0m4UiOlR6hhHu70fevr3nfjdw+zDy7t2uOKN1liM7m44tQiMVfemPnEwaoI1faQCXTZJnHMwiI+JPANr6A7SZT9UV1a/pbdKuQ+3TLHRSCNG6amYDDFFhTEoo4fehNwsNkjmOke++fVOiRkFk3RykVJOZSKGAg/l4iDiyGon78G7Ht7xmOEbe3r6jX69R16POI86XADItDlwZ38UFB9AmPL6NFeeqtDWNlexOJ//jCOVTns1C8lO7Vq0TSu6SmZfvqcTRolSKpFUtgN4Jwf8FsoZ8880b/tZ/9t9RSSNVIVVzaaodVsyaepJk9rRIfvTbJHXY4E4zFtMm9pzlnnEcp5yV9rh6joCTuupq8TTMONW2YFQJxQVpx0Fz9iypND0pKfuD+UbMI1v7NSVqsysMvqkiWSDGzP6YGSKmiuwi+6OSYuYwRIYRhETOqd2vpeYvVgsFkWT3gUck4DpHjAMxgR4GhuOIYipKCI6+7wluSvZbV7OEreZpJmF47xAfANuCIKdMFiVrRtXyRSRN5JRJmkg4kkYSnuRNqhhyMpOoF1adb0B1d3dHSomHhwdevnzBi+tL+t43s7OixU3c2covinc9x13i7s1veXj3J9zf79gfjgwxkfzG+A6pkpNtP+ABxMSthZWqSBhVuvCuW4w3ESGdhIzMz23RtieT3jmHD6lZMuYgslqtZiH+7tHLy9JsGkKgD4Gu687Pkx9QPgmwiDHz228eyJmy0tv3qvasze+B5oE300RaWVo8Hud3MBLI6slZZ+cUm/cZbqSZQuuKkEY7Vsy12AfovMN5Q36nQpKIr7xG9aA0zwryLKZB6x8x3wmtrH6a1JbDMRuB520ajDmR80jSTFbhOMIY4TjCcRRiUnIOaI7Fy9SRcyJrTfCSyMkIx9q/ZIilw12w9og4XHAEN/VfKjrKJPFlfAn77qSYeKFJTeItZ8QYzQOzbQugDpNCPGVBNn8ZcpGAbKIJAddJIY8zMWPciGoLWqvu4MELQS5YrwNg1gyHVLNNmUjFXSsq+/3A29t77u4HDkc45kNJuOMLL2Ju9l6gGLJmYv+MX0tGzlfSfEFOnslhMp/8p+N2ssYdHkkNIhafM0/WM4+idc7hdCl11AQ/ITzOTv5DyycBFpqF4WhiVhxdE29NrJ3S4KcZqQY8MnNOnXLGzZbUQCKlyQFWZscvygxQ6oPReDDJw4GGYhFpiG5XceKMjZ/Rz3XjnIqCzQ05g0oip3pfk89FzoovC+MQS3avXMBNHOMQOY5qDlejMIzZJmZKOBdI1TKRBYTi2TlJTROuTn0WixctIaPq7ZolxwQqS5VNBQkO75xZLxrHaKnpJHi8C8SiHuaciYVINavPjBQU5TSPZRYKGHkDuVzVARhzMgmURHBC13vWXWC7vUDzWIhN8C0/qUOzs+C77MjJkZKQzOhhfiK4tpgUYcSe8zAfX/Y0KyaYv2Adj7l9r0rjTU6pM5Hz3019kdt3y+seZsfaq1mlRB7HJLVjZAFOP6Z8EmCRFcbBGPacvE2aAhQpTpaRpBl0huAz9J5Q3QbHImWaTKu16ctLHRPKhJdlfc3yoTVDFdQgJTvHJAofXBnsRdUQ09+rZJJPMnC3Cjw26RxF7ATEkaMlbhkieA9BHTFlI0/LIMgijCmTkhrYVB9PJ+Q0NJXN2mkrUM7R1JBcBno2stb7ulJ5QFu0qfWmNBJvYWFiyjKFCUXWnxS1xPS0MxLeNBEsstXcuJOY2bnuO7IknRMpjjPeICPZfDj2+z273Y7h6hK4KOdmXDRAnxQThULypqTEMRNHSBEU2+6xcjtV4nKZ5iwoUuJFxLfn1/KXFom3fm9S7FMk+xmfhyrYiix8ceqEz+V5TeBwSnQuVenpe8q4PJ9b40PLJwEWqsqYhqIi2HfVElnGtKF9EwhKevqZWN+kkao6FKcamYUU14fnYmp1NygS69Layd6BeCnirInIqWybEbxNYucohFQ00tAtfTHmapIycRgyu05OigtC0mSxCNls9DmWVwaXq3ksgPOkZJvlxNogSWg6kMt9hcEbaVkGrakiQoe0oC8TBSqjaXkZxqB4MZVJUbyaLqzOE7xnzCPN+uEyySWyS1zgbJI7tfR5mLlUNaIu0TJWFdB2mux6HjPVCnTOkztHioCH6AKhC4UzsSTFmjKIkNcd4iJZlWM+cBwf2I93OH+NIsRoGcerE1vOiW2xnFkSHY+4FQSbYZIt0lUonA6zcdRWCEO5avA2otwAOvuJPK9jUPMSEiaVYhrj89LIUU4GTSlOHTku86bOpeeYRk7Lgpw/rfAHlE8CLKq4ZGV5Q87ZwAPzhKxxG2binFYskfKQZ3XOX3MgKQvohNCOFsZexcBGGM1EAlfAoO/Ms6/vHF0nBG8IblaGWc6LsrJq2QBokrTrEmTBSognqenjWieGJnwBzxhzCZlOuK5YI/I0OHPOpKzEmpG6qjNllcxCI4WNv6Ck17N+D8HhfUe3EdadedJ6cQQTykr/KkMMDCkyjoOpGzmTU4JQPDOlBMkJ5AIgwUFyM4LQWYNkYYA+MffpXOo7SfSrxZpVLEspaQmGGxmH1PrVQmiKumMhZbbKeocLHt8ZCZhyJrWU/nWFL6IF5nNx6uOQc/GQmcX61JFbjBHk2R4q7Vet0hiL+pb3ObkK1Ot6xBIXy6SSL87NSheWmyEt667lMaB8SPlkwKLvzNXap3kU5qROKJPuldT04qqi2ISRxknMLRqVgGqIr9o21TJfgLCM9Czii3cFALQcKDZBxcF65emCEAL0AVNDiGUFLW7DMz00pSlIzNqnhUsQtIq2GA+gzhVnILNApGj+iJqV5I23ULW0+zk7csqMydx9c0lyO8RMzNqEzyatMRdPTf3pQmC1WtF1HX7rubq8pPehuGVPoraIcDjs2R8PPOzNZVxF6HCGQCUNHlI5GVfUNHB+7jxndZppc6mbz8EiRSUG8Ewgp4IF8GWTNFOCAdjvBh7ujzzcD6zWHbbtYF39Ban9h4HwZPo1a5Hz/dQGqTxH6R9ZRp3mwsnknBsALwYyxX+E5QZHpqYYnNT+rFxF48y0a6pXMzrPpAdbIA0oJg28jtvalqnuOhc+VvkkwCKEwM9+/somj1bRuKyIOTeSM1WyDZvULk3oOffNSM0Xf0ZOzolRneUFOLFQNK6jEHCVqKymV+ccm5Xp2d6ZRUTEAr2Q6kthJOVkV9/aijLTViufkEre+ywH8yORQvT6iIs9yVkei5jsPasQk3AcEw+7kXFMxDGV8PTSn5oNKGoWc3GlT8reHYDzynYdeHFzyatXN1xfXnF1dcXFxQWd93hxJaeFgVxKiX3xHn1z95a7uzuOYw11Lw5oladwDt93dP2aN2/viUOihdsXSc4744IWwXe57teqHI92fOhKEJQrWx1mrJbTAAAgAElEQVT4bGREduS055iUuzSSx3t69y1ff/UFNy8vcaE8bx2BTJTEmDOHeOCQ9ox5RDz43kOepACTQUz5tc3Ya+Ki0s7yqiboNilnfMJ8XM0lplOJYbn6G3hJWKrMlQ13IiU+ZuZ82BIucUL2Twhxytv/mPJJgEXXBb786quZblU6eZbwRFUZ4+RDISL4U7BgKXqpLCNK27ElItAm0lOpQXIjtyaAUhPPO4u2rCuDEyMFVZdOXlXKqIFkS1a6DgoTx7t+z2GIRaweURlwKTAQzcOyiMfifHEJtzYlxbYUdKZ1A2QZIbtWt914BShltfZs1x1X11u+eHXDV199wdX1JS8urum7zjJpl6Av2zbRgG+73rBZr+m7jpUPPOx2xBh5ODwYoVqsHRIgiNAFR9cHi/YMgRRqmn5zmAqINblsmqRZ0JRJqgxRLLxcvInhZa8Uy3BuUaJoIOfIMSk5Hbl7u2e7PlgOjI0niJlBxSWSK1nMq2Tlyz0i+BBam6atFhUktwVpMa7a++PJOPnQzD07K8FdUhwsFBd7r6peoYpn/jxVsnCzcVjiazztt5iXJOZSrfs44sUnAhYdv/u7v9smZpqZp2pRaOTcBBaTeDt3OZ7UmAoIS5v1fH+MuvHt4lpV8lhIFalYLLR5xBlPUR2c7LuagEZ1JkKezVU0rTwZR79+MGZ/fyA/PCBjZMxVYjIVS7wUS0a2Fdx3eG9qRtWXDTiLeuPkJIAo0wfPV1/c8OLmkpsXF7x8dc0XNy+4vNqyCtu2y5sXU0Vyzmi0iRZcb5YSzWgyU+YwDGSNHIahkNSZHBMaOwtYQ/AidE7IvTe1KmZTK5iyibX8poXd1xgbuJofhTPyte41qEbyqli2Lz0mbm/vCZ35vVy/WHF5GQhdQohGQooQ+sB6u2FUR+iTmVDTFHFqHrlTVvUwt6KVsXkuY1cjE6uKoxMQwAQuQAn5Z/FdEzrLw5w/T1EtfJlbcGiL8RXnY1Xb+Vn1x/KarXwSYOFDx8svv2x6WUt/xhIcqvmzebzN0DTNEHSevAZAvFuAhcwiPKfVvgQE+QkcYFI/VBXnDdFrVOZ8C7tKBMaYm4j4yNdjgYB2XdNvHeI6nO/J6jgeR3ADY4zEpFBACpGSNTsX+s32G62Je00Hz7g8ibzT9ntmXN2u13z5xSu++PKKVzdXXL/YcnV1wWa9wmXfwu2D9yYR5UwcC+nrAzln1us1XdexWq0swKzkldgPCuNoMTDZcm+a+7v1U+c8zls4fs6xEdRTwJ02VYqUGVMqnFPAOwM/A0mPTwL0ePXkmEh55O27e0JwdJ3Dh0tWq605zDlzPBPn6VZrLl/09OtMipCyb3k26zM1Ja6QjXUszsy5pyv2xIHM1dAaGyRnj50+s6i77SU7C3OAAhTI7FoziVpHfKiLT+XwyoIrM0D6keWTAAvnHP3qAjiZUEURPJdjAlg6PlU0nRFRQNtlaj5puxlPMV/1MzWhSW4DBwyImiv3rDR2H1pqja6bD4jqEnwa2eoaAZpzRvCs1omH3cAYM8chMg4K3tF3a8vUpyXQTA38SBb8lfLY/CWEXKwEFlzknBC8cQ+rdcfFdsXVxZbf/72veXF9wfaiZ73pWAdHcNaOEByuxKY4J0gOhFBWODzqnG3z55R+FXi437M/7ozD8cI9OygZv4+HnUneWUlxYBzNhIs4QufNF0IVS4EnzTElqhGYxCkuI4krGayEusVhnVS+Czj1xMMDD4c963ee1Qr6leK8peUzK5J5pm7Cms2mQ9Wj2YH2s3FWHVDM5Fod5ioQnMvmfu6V8vDouDouVR8DTE2H6JBH12kpFc6cV4FDZrzc/LWs6935ifSe5ZMAC2OejXWei1lQeemnPNAmPqN8WIpz2Pp66jpbPi2rUtfWevCoUyjmVFf1z5kk0/iVatYNdjUj1aSs7hXExsKM+Qbz0iQbOz7jOY6Zu/s97x4OjGOk6y/sOsVMiQOXjHPJ2TJLpTTahNRiCoWW2KbrPZebLdv1mottz9X1BV99ccPv/+7PWa8D3mlxVbfYlhBsfxDBvDJrzENl/y1BjJu4Gudw3nP1cFV6TlmNwzSZs816hyVdTiWQLARnPiNti8JqQaoBc2Vt12kDpFhGgXpPlOIVWgnvbJ5mWSAm5WF/oH+XTQVxG66ko3e2C1kIPV3YEPwGJz3gSdFNC03xJs1FHUk5PJIoTsfAOW7A6XE5vGaTt0qe5wDDfFGm46oEDCXIcQEY0+d4Ekh5nq/4iwAW4tBuu7ix6fPTrqpzb7dTEseFpW43f3cnD8qpO/Hlr1JJbv8rNEADE1If+9ybq7dAARsrMWWcs9XaomilHe+8I8bIN28f+PPfvObX39xyPB7Np78r8KUecQHvIOuIiGcc9+g4EKDtCJbGSFQLJru+vODF9Zavv3zFF69e8OrmkuurLavecXPdY4nRM6Hz9H1vKeu6S+rGOc45XAiE0FEdwGLMJBXGsS9Jga8Zx5FV33P79i3v7u94e3fHbrfjGC3K83CMsBK8etbDSI3/SSkzioX1u7ZJsdSexkycMI4RTZEoI7Ecl3spGb7KM8RW5KiO3RAZUuQ47NntH9gfr0jphi9/1iMayLlD6XDSE/zGVJyyaXR1yxeX2rCLOplVH42/tNzYuY4xU7mecpJ6srqiIk+pDRbnza41BxAwiSPOFs5TlWc670+evvh7lE8CLIyIMaPUdGPn9PzT8+aTdTlx3RxktB5R7eA0122LcG1cZhGLpbrklC/NB2ROFtZw7PbQdNIZZbqktaU4zGQVy5Qw00ezwjBmvv3ultu394xREdeRVdjvhonMLVGIqRnvLNDNe0/nnenWJLzaHqlfvbzhi1fX/PzrL3j16pIX11uuLlZ4p6z76gNhINGVlH2bbtXMzDUQzJfdwnLfM4zGiXgRYln5us5z8/Il3apjs12zWq142O04Ho8cxoE3t28NHDpfwqyVw3Ek5yMp5eIYaY5WVepzoriq62NCokgmVz8G7Y2LESznhBRXbN8hGlFNjBEOR+WwtwhcVY/5f4tFMnsjSJ0EcjY/l0wxTRYD6jkHqYXFrvjhzCdkkzbIj84RaFLaaWk8nM5/m0jwRGq5Uxa+GUwWuXrsOX7kY5RPAiwAajZDmZkXba15usydYvzpKq8ztK9AUOc1M0/BAiELziNB9qYqqGRE5jmeGvVFdb01NVzKwGGRTQvA+d4eeCoOVq4EZRU2an8cefP2Hbv9ES1ivqqyP4wNKEKw5DOqZuD3EqxdakAhqvhCaK27nq9fveSrr2/46ssbrq/XXG47NuuAI7FedQTn227i1Y+lE0fwwbgbCTgfCD4gzjWyORfLQcg2kaL3pEuh6825q+97tvt7DocDx8NombqOI8NgSXRxdh9RJqVv9kQLiPkS3FWIZZ2AvhxFVvMypez5mikh86XCmBOHY+JhHznsjTSX4qnqfV88dg0wLDgPnGrZAsA8cVUEKbHmMpuclHHiS9DgfOjV9irBxsLJxKbyYnrq+wOImcBVpw2668B1QnMVraA6gZAnacmjsliqtI2lj1E+CbCoEw6W4HDGhX5Rlig/MRuilIcoU5AJlGS00qzdk+ZRB4RREFkskAtnZqmqjtTckVosfM1Ls7XBKqjPRopFpW4NmCmDO1mzLJ3+kbt3Dzw87NkPIxonXmSMZad0TPdXXwaJTn4Q5sgUIZtj2Hrdc3X1kp99/SVffHnNi+sNF2vHykPA0sz1QSzfga85OB0xZwMLV0K5xdh3NwPcII4c6i5q1efFs9Ie52tYtLDZrNgfbVf1wzgieLzcsT8MlpK/U7xsOMSheLfWl7SH4LxQo3CdVitU8f3IkJP5GbjSB5FEUPNt8WVQxZjY70bu3j4wjtd03dpA0BWza5YSIuOaybayZArF7f7MRKskZh09BRRsslKCyOoYrbTWJDFXn4myVpxWjalj0ykT7zaLlp6rIfX46hN08v6xZIsfBRYi8qcYa5KAqKr/soi8Av4b4J8F/hT4a6r65tl6mDr71LHqVDc7uf5T7VrqkHlZVxMVhSLuzqSA6l4ukJmceJZlikBVBXXSvBhda+c8QlOLB6Vg/gG28o0p8e5hz+3tLQ+7shKPh+YUlbRHVZAM0TxNLFVdViNkXUDTQIrmzxBWKy62W7766iu+/PILXt5ccrENBB/xbsR5CM7RByP7vK9Wj0AAfHJT6vtZ3I0WHwjvfcmuFVr/uuQYSidZ0hZhvV6zOpgLeYoQfI/3HW/v7tnvD0UdgTcHGzrNNF7B1zmkmFtPwUKYCFdxznxKNJOjKY7eAcGC0zUnjofIw/2Rw+FA161YrwRXeArvO9BgZveSns9I6qKK1Oss1IglD+CRaXIuR+FsfC4lkmrFqepkHZPnQslbv2S3GNPz66Vn5e/n99r9kPIxJIt/Q1W/nf3/R8D/pqp/U0T+qPz/17+vEj/b4m9eND+Ni7Iwgc7FVNqGPuoypz5ReUGaurJ6Fsa5yh1qOSksT0B1wrEH5U/IJI3a1KBpgExi5lgGhyORk6kWa5/Z392S9jt2774lj/ekeE8cRsayZG3WG1Q9KXdkF0ihQ7wv/gYZ1dFYewHphNXlmldff8nPf/YFX7x6xXod6ILQhRV9gH5l2wGKExTPmMzd3JfMTDmEKXW8a0tiuw9xAt6xCp6Mmu+CetYIgyRUhN4FoodAR+82dFqkk3HAa2YfPPuDbVq0DT27uEedmtrnMQuHaFnbzVxa9wuVkibAFT+ZmHOJkcmknAnOUxQMA9s4oIMlu3l3j+W9WAeCC8SmJmRCWBHjQE4ZdWqJgnNCJdP5ZdZ5W/iLU3hORaV9vHBpUJ5a059SC8x3dDlYXVtzMkhj8mjmfYpkE1YlwG3Jn4jwaUgWT5S/Cvzr5fN/AfzvvAdYPFWekh6AxzLc/DwA8vmekom4mowWFTCm3Jp2/crOT5vKNJHzPSQbAFIultPHFpq7uzt2Dw/EwXwTHOA618Krx5SQzrNedXT9ipwSw3EgjUfb8jFDCMLFdsvNi2tubl5wc3NNVwjFrvP0ndB5JTjLt+F9TRFnkkXwXXH6WWZgqvxRELG9QIyJtqDOmhRDy/4ZabLnVymk6zqurjpiLlYNHH1/ZLU2S8m74YhqZkzTpkDeeyR4hmEo21baY/GYaiLiLYOXN9Wzxgs186JmhmREoXMBL6bL397e0ndrNutLum5N0LpHR8b3q0fPsnr+Pvdsz57D93MEz43p02wXc2VjWW/xZKX4Ep255sckN+HHg4UC/4vYjPpbqvrHwM9U9VcAqvorEfn63Iki8ofAHwK8vLnCnwvy5/tueC4h1OMKv/BMdiD1NUuGBX/VHcWmxk31VOAQmR6cam6DG51yUrZ26PLlxfarGIdEPJqzToyZd2/e8ebbN3z3zWse3j2UhMTmfRdzJHuHeMfF5TWr9QbnHMfDgZwTcRgJIvRrz8vrF/z85z/n66+/5quvvuLrL3/GxdbyZa7WHV2A4AwsVBMh+GJd8Q0cnARC0+cLP+BKhm0RQkpELUldUs2r4MgOXlysmaQvcxYbhsGS23Q91zevePHihm+/e8PbQuTGmEgivFlvuH33lv3xYPENzoja3nlTA0sqAuOJzOfF+YALHhfsXdXiaXb3O8sQNkSyy2w6z6rfMEblz375DcchgQS6fsuql9bfLo8Gfk6Rso2hkkBTCwhcjB8oqscS/GfsGM8lnHkOLNx8J6sFa+cadmmVduep/Gbq0ccGiVp+LFj8a6r6ywII/6uI/L33PbEAyx8D/P7v/ewH3d2y02vHnnkQsgSiifuoEsYTv5ddrWZtfvL9qVVFREjVm3QWwKZq+48+PDzwcL8jZ/OXECzqdMwjMSc6FxaRszFG0jjiRVltV1ysem5eXvPFqxte3lxzdbll1Qe63vgFy8tRImgdULwz6/8tY7XkSaJY0vvTfSXrD1dWXSkMsYRV83xNKTHI0Hii9WZD6NegnpikpbA7Hgcutxcc90aE7vd7cixOR8UBy0nxf8la0vthwWrOmVu6U/rOfFBEhB274uyGhe6TOIjSB3ARHvZHbt/dc/WwZ726LKBAC0IUse0KnbMs48Vx9oxZtI6eGYfwSIR9mp5/bi7LIrBx/jkv2qFtgVtWdg4oHkm6P7D8KLBQ1V+W99+KyN8G/grwGxH5S0Wq+EvAb9+nrqew9lk1RGylfKJt5ZjHqsjcmatKBovfTz6cA4L55+eAwkymY9vxvRJrx6NtOLzfHYgx03frRkTFmMHZihoV0oy3iTFyOOzonbLdbrm+2PLi6pKXN1dcX12wWfe2w1cXCM6S9HgU54v64RTvZhKFmzJNF6+vdi/z1PM5WQ5TAxkBJzPQCZZQCLcYmN57QrcmeCVt4ars1J6SqXQ319cMhwP39/d0zhOJbUc3U4OKxaCK2Vkn87cmtCSmCcFiVrzvikt4huiI6Ug+RDQI240jJmG3P/LwsOfqamS9tlD8+aTPlXNUFttQnE6408/PjtMPKScc3SS8TGSolWSJhsp/FVaeAoaP0b4fDBYicgE4VX1XPv/bwH8K/A/Afwj8zfL+379PfU/h3vM3+T3GVTn/+2kkppXJAeb0uhMghcUx8+POOebUz947vHfFTFh9KA68fnPL/jigOFabLSkljuNgKgiK61a2/2dJ555TQpPZXZ0Tri+3XF9f8fLmBS9fXPHi8pL1xZZ+ZdsBOmfh/15M7fLemcPTSRr5yUpk2b7mwTjze3Il65QlxpkkFJ1nflLb9tD1PV23IpfNfUJJsnNxccEYs/lSjIn9xSX3F/cch0MxEydLFiG5mRgtWMrcxmmWJl8S4di91fotOtWh48BhnxkPe8jCRXF0G46Jh92ew/HIqt8gneVHNHOwtr1UUpEoGpCcjgkmCWGpgtCO/xhlnqtishiadDZvhLjzi9XHLD9GsvgZ8LdLgwLwX6nq/yQifxf4b0XkPwL+MfDvfl9FCk+YKOuvz5ST85Yd9sS5ek5lOc0H4Gah55MD0TmgEJGZL//yN4DQe3wXYMxkMimO3O92vH7zlv1hICP4rmOMkcMwNqKw7zrWmws2m43p5WWl71eBlXdcXV6YW/fVBdfX11xebVmvbbMREcU7KUl6vKm4MmVQqm2cqx110EsD0CmlXCgqgUkgBTCKlSLmKYajSiPOO4IEjiWS0ovQB89qtWK7LuHtuyPr9ZqLzYbj0eJgYhxKkFhq/Ro1mnXi5BnPg6RCCPR9j3cdvfMkHxjHgUEPxKSMCUKCISYOxVEsXiSCdMUNv2x1oArMYi+Kv85TYvzHnpCn4Q16suCprTaLNp2Cybl2PSWBf0j5wWChqn8C/Etnvv8O+Dc/uMIz+yyU+p47iUfSxUIlOPM7RWR7IpR1bhvPbukl6hZ1nz/vrNThLGtzzEaY3d7v+NN//Atev71jfxxZb7eMKXKII/txICXoe8/aWxj4vL7gAO/YbtdcX17w6uaaL17ecLFZs+47ghNcsM2C8F2z9tRcHKDNv2K+QXRtq3Ou5WRwgkkQysLSYQnMy5qrDi9SWHwhFSuDy86cyNrqaxLNqus5ro7E5HDeomJXfc+q6xmGAY2jkYozXkWka8BR+9iSE2dS8qiuTYILgRwzo5rk1fcruLyCZBsqQ6BfWzrG/WFgGCJdlwjBEYszXHVCsw1/XNn0SheAOnvqZ8fQubKUVJ8b0yfjdUa+1+k+nS7NRaAR8ifj0Kxq590SPrR8Eh6cQNlF/HF53nQKCySeB5a1T/X32W9pecSiSp0S50xLWZEs5CTKlcdm1KWNu0G+mbeC57A/8N3r1/z22294e3dP6FfgAsM4mOgrDvHZ2P4iHg/DQE6J8Xgk50zXdVxsNrx8+ZIvX73ixc0V24s1fR/KKgmheFO6oo5I8VgVCWhxRJsMOJYPk5LlPqm2XjNuYLkbV7u3bG7RWVIhGjJebO8USqIWFaEvF8q9cS598MRQMnIV6c07V9QcbINj51r8RwOJOiEwslhT8YxNiexsk+c4WPrd4Mxxo+tXaA4McUeXTKiMarzQcRhYrTr6PiyklWnovO8EPz+OTv9/H9Pq4zWstEfds+dV/mL+Aswd8CMJP58IWEhLPXdanu+gUzPTLBpv0UGTXwXUzWeWv9cEwVonirp2jrH+riU0Mae9CQhEytaKULJw20ZA9bfDOJCPGbTjze0d//Af/im/+OVviSnT+UBMyjAmnPesLramQngPWTns9oS+tzD1ZHEdLy9e8Jd/50v+uT/4Z7i82LBd9XROShZoR3COEDrLoenM+9EX1UGrf4G6peuzGp9SYyCEMnDVgph8DSNX80Zt/gA66fNS0wu6koy2iPAZZ4mNBbxs6Z2wXffk4YgPysXlipfXV3z75oLvvvuOdw/3hN78NPDT/iBjidOITO7UlUBGbNeuGDOHw5E0jjiUvg8E7yD1jINw/zDSdfd4Z16c/SpwcbEhdCVdn05baAbxqC5X5aWU8eTQLFs3TueUrpqNp/Mlxad4uFne2LnJ9uQaZ9vykVSlTwQslHORePB+nVB5BZFKDz9OUrKss070ChL1vEJSWn5+qp3k1FGmtqtKFfPP5x5M5zwxC4chsd/tuL+/57jbg+tIYya7REomDvc+NP3yeDgiImyds+zboqyDsF73XG629H2g9zOiMpQJVgi/OlmdmDnQO9vMdzKR2o5fTdetUgFmfWigoYq6KXtTywhSwHDuNWjF9jPVkmPC+AxLuOwFVl0AWbFe92yHTeM7Hg4WiBaOtg2h9b3HuYQ4hysSTqzZ0p3iZ/kfUsk3YgAFw3AkxoGuD3QipJgZhmjbBpQkx1XNACMJbUBMKfffRxo4O8ZmSYDnwAbgngELd0rKn5Uo6v8n/MYZH4uPaan5RMBCHjtGlXKaDGde2kNutbSzlr4ST1bglseUiM66YXGFCij275OmzB9CjVWo5BPlpVA8M4XD7oF3t3fs7vekUfEB4phxLpJjIrsaPVu2MKzbYJQ6gw+sVoHNamVmydl+liEEXPm/tV7mAVgWhl1NnXM1ybqx2AuZiE7zp6DsRD6Z7ur9VV5BNVL3MIUpbBuXi8VCyanGzphr+QpKuy2exBWJyDnw4kiUFIFz57oawVf7hFmSZBX2+4OlACx6ZEqJcUyMeeSis82TRIRxs25AMRwjYzRHuRDCYhSllGwdmfuanHn2T5X5AjJ/f6oO1aW3ht1jKo/m8fww61DNefK0Wm3l+8Iyv798ImDxNCg891Cq8CAIVH23FN8G2RmnKybrixQzXP1BBZyUtPMtGKiCysxqcObhnNre6yvFSPA9d7fveP36NcfdHhHoQ4fDyEcdlTiOttmvsw17ui5AccryYrkjtusNl5eXrNdmVq0b4HrvW2q1ulcKM7XC2lQlsJkZLpcJLmJkjjytG0+SxJnnInmhcNvmPo4sFkuTa9o3C9lCUfpVx2rdM6Y1x+ORruvaPQnOnqkUsPO+TTiZEXbNH0TNijSOoz2vwj2lZG1LjejLHA6H9joejwzD0HJcOh9K3ywlig/1XZCTsXLu2CVgV/GDxf/TVVMDBpFZ7jjJZ4HkpyifDFg8NUCfUydql02isYHG4/rmDypPcQ7l/0U7il9AFbW1Zb2x78+1ef6+MGnNmXXvub+/5+72rWXCEqHve3CeLgT2UPYnBQkB3wc2G3PxlpKcJoRgpsaLC66ursxU6CcHK04HHssBOXeysnaCzqI7RZ52FbbfMzoTfZsKVnffKoAxXdOsJDYRl1mvVZW+79lsNqDCOI4tEbD3Hu+ETCoRqB0hxAKEDikp5Go9tmmyZfwajrZjWlWfEhb/YxKIEbaHw8B+f+R4PJasXSUlnQ9IeV56xtfkcd88t5A9L0HU/p++s5c0KXd5fTk5vwnOIk0y/lBV6UPLpwEWCjpzbV3qXsuOXoj+c8tD4R2kSBIqpw9bGz8xZdFSU39a0JiUp+ZKngMhl53IIE3bKDJNSrP1a8lZkXGhbkJcE+c6NrIm0LN7d+D+fsfhMLLabAh9h4q3fUFxjJHCW6zoQocLWwMaRjqBjXdcX/S8vNpwebHBdw6/6ixa040EbwRj1p7s6316m+DiCN6I2M7ZFoW5gl+xSKgcJtVOZFrJnLSdyXwBF+tKOz/GsmeJYCzmbDulDuNJRDJRLQ4nqYFOD0jX0W2UeFhz33dc9oF9EJKDrI7QBxJKzL3Fcjgh+N4iVSlZ1F1PCB2hM+sIO7O6GIhmYiobIIvFCw8pMGjHIfccRle4qUzWA0pCvG07kcXhNSykg+nlF5Pz0XYPfto9Xk98cNqYLePW+JcCrnnVyOY6xqSqQm1I24InRWW1Z4epvXXuiAEjRSP+GF5inwZY8DQqnqLyXLyb/7awY5eIvPnAzxhbDzQSD/PpRSQseYvS8VlqRqLqlDWJhiYOMyMLSz6CM+RVHMx9+2Fv6ebMo7OzPUaYEsGaF2LXMk65GuhW4kY2mw3b9Yb1em0E5qwvJo9MKaRgEauZtU9Mwulc11bptvFOBQehcRpm1ix9VbxGjXWQIoVM0bh1gIqEpZhcncHaM5pWwbmKUT1VqyqSNeGLNOUE/GCTPxaASyk1c7sryYAqh+MKd2T9Wp6BmvenK1m/qoXlWMzRaLbsXS6WRMUVMM+PO4u3ORPIqFN/SRlryjTRmzTWFjcKaVTaOztuXuZ9dzrzl0AyL2Xh1Lkx9YeXTwIsYkq8efNmgd5gHZTKhkC1zDtxntSj6tKLIhOizxWIZh61/+xQpSVfseMLV1EnvzrLoDXTP+cDvrZh2qtSGsuvw47Qd/z2m++4Pxz59i7B3Q/qqs/lB5aHeWb+e/jTXy9//xt//a9ZQJrlIkfF0gmS4nLiVs4Gx2IT7PZzMeHPJWUm/soAYiZRzDglBDSP9SSqVWyuNtZyGlSdnyBRK5gjZ9Hkg8qnARbjyK9/85v2/zxeoZa53l07vlj6MIQAACAASURBVEY/1t/P6YYwOVOdfi8izfqwLOZMNN8HtZrj5iupqhLKythUj5Tb6lbDtdPwgJPAmBN+liH8c/l0SkoKvWVfT0lLciHb9e4RWYlj4WszKza2EvPkR+fMmU8VVyUv0w3nJ1GXsflbrW90y2tNn7NFC3+E8kmAxTCO/Pmf/znAI8li/t288+01/33JODdwkSU4AM39tYnn5Zy5FGJb400gUY+fg0U17YUQ6Ly3JDBZm8SjqmY61NH2voiZ0C/B4vJqA+LZbtd0ISzGx8Z7tus1X716wcvra15eb7m5vuLF9QUXmxWvXl7R94UQDNKu63xX7ssci+o+InX7u8cidV3ZqlnVF15mWiFF3OP0hOUeYzw2EXohdZGRsvVhzFOUZNTImCL7nakCu4OFqD88PPCbb7/h17/5hj/79S9JWZFgVp4xK2Mxv/rQk3NuOTNSSX9XU/Y5FyxUfrCMXHE0h7YxmcS/Wnm2F2s2m55/9GevATiOSt/bbmmqingFD16lEI+WO3OuduaTCbt8P+/tWxeWeT/O68jTwZwt587RupObkRM2N6YAyQYaP7J8EmARY+Tbb1+fFaGeUkFgUkOmAT/lzJzHEZyWpLmRlNUC0PaoLPUxC92u39UUbiEEyNpUpK7rCM4xjmPR5wWNqQEJkhjHyHEYTvRcC4P2zgbeMAzFYmHS1boPkDucatl82dMFTx8C637FuuttUyApE7uqRJXDwMLJjcd4HDRWjz39TmZp7GSeY937FmuianuM5rLzuRaROhdBHrBdvucktGCqYbR9MKyfpfVTv1mz3W7ZbC1/p46j7WOaM0mnybVarRjHsfENFRwna482c3IbO+JxzjZdTppLcNnkFXn79o5x3Nh4EGxbAe/oZwuL5QCd5wN52mS5zEsx3X8+E9awlEBMX3Ju2vz6tB57X0oQoe8X9dWpbf3yFyg2JOfMw2EPLDtuDhZN9Zgh+3Ok6CnoLEoZ8cu9I029aQOs+Co08IAFWNiKGm1X9RBwmFtycN62FhxHQjDzZ1LL4zAMsXAhy7bW9o7jUFh8oQ8d0lm8xKoPbFYdm1VvyXALAdp1JWKy+iNIwDtfErnU4K56IbXYCgnN/cp079O21Ezbbno1s95kqs5ZiWpek5JNZK7Zxw2KJ3FcJJvrtEDC4SURRRA/kZuqZq1ar9fNhBpTIuZcNso2C0oFFlWzjGix1Jw+9xY+P1sEcIJmtY2ScqKL04T+9tvX7NYr6ycB3/UgHp+nLRRPJYJleL/gZJIafHBnz4FpU6j5+Kxj0MvQgOjcWBe3nAPTPY6PxvopsPzY8kmABZyaS3ncSbOOPwWS+l0tp74ZcwISmMJ+dXnMog06iYWt0/2SS5nzKCnZLuu9C+wOD6Qxslmt2a43DHngsB/Mo/BEf6yh1cMwMI6mrvTFMakLnnXXcXFhIegX2y0XmxV9mCZYSgm8s2Q3ZTMj7/zkwapSfB9cYeZzkzwmyqdS/vWkzMLm5vykvuTlM7HPBg72uT4n+36ejUzVnLG0uFQ7ZxagcRwNNNTR94GLi4sSbSqkHIlF/Yk5lXgRh+jECwkly1dW64czk9FJsH4qkzJFJa2mZ/ndt2+566eEPqYyOaoSek51OwWD5evU1HoecE5/c3J8EiyamunO1DufyvMNu59SZ35A+STAohl2ZmDQyjM32+bDbJJPJrp5FScdJ1Jya4INZG36eIs4LRMniDzS9s4Cm3Mlx4NJBc53XKw3bLsVve/Y746ktw+cxglJ8GQxFURzxjlTa/q+Z90H+lVgu+7Zrles1ytL8BICOkvW6rCVf5nG56TNjXB3i8FmJ9R3LScbUEgxkUoL3FLrl4IjHme+C7FIgrXfVMtWAvP4GSlANZsgiz7UluS3782M6o5FrcvmoxELeXy6gIgYUV2J5erl4Zkmmrpya8WfQUXmW9dy97Cj208LUBZQcScbFD9trn806d3yQT8HFvXdJOd4Us/jFIin9agmOrd6si1/oTgL6gr5oac5ad55jVgCc6aa51+YbdwjIugsgs/OX0oskC33ozuRXsrnVCdXNskjx1j4AeX+uONyteFnX3/FzfULvPf84rtfE48Dw+FIOsG+NIxEFxnHI6vefCnWq46u8wSvXF6sePXymqvrLZvVihD+X/LeJNaWZFnT+szdo1nNbk6TefNm3VvviXqIRohpTZEQQoWQ3qiQGAFCqgnMqRnTmiIhIdUAQU1oxAQGzJAQE5pBPSEVAyQQqOrWuzfzZp485+y9mohwd2Ng7hGx1t7nZPPylY4unkqtfVYTK1aEu7nZb7/95mZXFG/1FOKdCdcWN1jzsqupVNxiEauRutqvd7ySP5YqmUft2GUutlbwT8z1d97jQyCOaQY4AduNc+nMNU1Qla7KdfPealdSniyMc6a14dUTt1uSZm5v95yGM/lUANIUmcZoJfqn0yVzNRsW0a7iduccfd8TNaP5xHGMRgbLlTAXSdMSyx8PA22w+N6MiwcRklhNSZ0f81xYebbz48pKO+Kz2ZA1znHtLVfMpaZM11SCy89dnoeqzlXB18eeOTA/w/gkjIVFtz/+B4mWwt2Csi8LXy8urrHAL1fp0gKgqCbndarKU2tNKgHLGH7lJiyRygz0hcYmahon2t0Ndze33N/eGcYhjiDGp5yusCYR24Vr7O7cGreBUNSlGm86lxazL+I14nwpiV9CBVfi+GXCWHWpkdGKi3q1cy07W+056lcFZyU1fDX5q1KVeIOLq5KWU5jbrmUtehdF3xITrolTXqjWpJlEFRy0jWfT93N3NDClrhFr/jxN03zu1rAoz5tNNQSVtDansQsBDy1EtAxOVptG1c9wJYwVqzqu9wEqVnspnDs/zpOx3NdVKvOj+NnVsBCtgJNlkqku2U9x61BvOWbVeF3OzT7s3M+n9v1JGIsP5ay/b1xfhDw3y70+3gL1qerKUJRXtRiFQphRmaPsEo1fuqL10WL4fEGIyTHRti33t3fc395yPp9nJSjgiUJ80zTknOn6liY08zlWZanWB9o24ENdHMsCoO4czrIO1qO0LPTiRbjS4k/EMg+i3vq3Xly34miowzqmVY/Czx5GQsnzgi+fQ0hqoRq+tA6o1yc6lAhNwBWRGjDtiVj5JynOVOg51Vp+0wziOk8yqiwiUlLQsWSZpBiC0jtEIcdEUvN0QghzSLL2BKoS+cV9cA3OaREmto5kJmyZloxOPU6dSyVzxdposADA9vf88WKQL6bljDDPRkmv5lf9rkqzz89gEarzcdZPmxfNR/Uzfsz4NIyFPuVC/JCxxMOLNZ1d5NmzkHkizZ+rIYtK8ShYBfXVo1jlzWck+lLU1zmHK6BTniI5WMHXtjcVq/vbWx7fP3B/c8vpdKJvO7IOMC3nUs+z3+ysYXAcoQB2m82GzXbJfMwVmSUjMOfsRWahmutsgBNXTOUKV9A6aZMJ2ZTiL5fDqsBWzEBkq00w7+Qpl8XCj6J0tcpAmGEyLCenpZ6kpmJretYVrGfe0ctx+75ns9kYRjGWdKJCzJbJCDE+deFVZhB57VWYK24TzXuoCsPXWQJVJceqheKp2c/ncQotGaJLQNOOUzYd/XBZ+vrc6+NFOKHLFmcGSi7TVysjU27pEzyjvh7jjw/xnxufhrHgw+7Zx4zHpbFYSq9xbt6lq7FYG4yaMgWHpmyxuKxcRtOixyNz8Zl9jkKAWXQWDFxzxBLrtiGw3W65v7UwhKy8fPmSYRjY79+gzvHdcfkN1X3ebrcEJxyPeW5xuN9v2e128y5buQPOOUJJm1JDgAomfujaqWVCLt3iPO9YAAGPaiKLI+dkeKez1Ke56eECoEzZznPmtNSdcg7Tys68GjV0cM4EfQFyNjxkncRqmmYGc+09y7nX8KV+dzUWroYYMZGDHayGdzkvFOkZA1idW8555s6klJEgBOfgioi2TqE5MfzI5t2lUM662HC+BVcbos01mY24wqwYp6rWunMuWahzdikgY30/awjowrwOqrei+uE19GPGJ2MsJBeLeB1CfDTcynWfQjXj1BBwjy7pNHnqCkpepRZL9WCd8NZwxjqe26IAkYCKxbmiKwZnjDhnC1i9sR5D03B3d0fTdWz3O4Zh4OWLPafjlvvbnqzj5S9II7UlX/CeJjiQhk3bsWk31nJvs2G721kf1FLQlZLSttUzyoRyrs6VBj21sEzBWHwguSlxcEHHneB0IWxVQpnTEso9SdHp7M1Y4sRIWoecCLJUpuaymOfb54ymtZCrPG3bc5pi8ZJa3BStXeGUkNhw7zY8uJ5daDmokMaIEyWguJyI0wTqmFIhWomQJJOChY9ZcpH/83gCIZSMkSrOGTEvxWVyDXHAU/qX5gQRIovDuQYb1+HMc7v5erHa/FsqQS83v+rt1TDC8B2bwRUTq17gyhixOrHyfbU4UpM+2TCea234U8YnYyzgMq78IWPt4l0gyzBP6mt3D0BYLL+UXH01AOYuOwRTj55jwYJlrI81eyxZCd5wgtZ79vs9N7vdTDAKg4UUL1+9MFzlN8tvcCJkTUzjiLQtkk3ZumJ7cz+MEMwLKgpS62tloe6Cy1xO3qeJVHttATkvcZjioq8+JyJkLFux/neuYZ/l9ZbzWV2nlNKsnFUlBapX5lKoqDS4S4JW5Z90RUt0EJmbBBsfxfgaKeW53+k6JTyHJsXV+ZD7X0fFVFhf17Ljf2hOPhdeLKMqh1G+/9kjlOfX7zMw/anK7kqkCai7nW2wC662Dp8rRvJT8MDnxidhLISPU2c/PNzVxRbsJjnTabwyPvXmejW9C6uBuJw03vuigu3n/hUV1PMF/U+kIuVWCD5lY4jjyObuBa9fvmK/3ZXaDFtENzc3/PrXvzZm4D9Yvi/GsbiOSuOEsO1oQ8N+v+P2bs/LV/dmyArHIDSNNdJZK0f5Zs6kADMGAYv77iXMQJftiGFODc87Jd7cWUqPEJyxVlWQBMkl/CQzdqFqxXZN081Gwyl41xBdRFOGZHT+rEpORWIvl3i/eCfeOTR4GrFUcNM0vMwwJeV4OnMYBk7jwDja3T0eB3I+IYSSRTOwt9+083XJKTMMJ5y01oqwitHk0pYwXeEVMZFF5z6wirUwvAYHn+XYyJpq/nS+fd9Yeyozr0MyzMzVAp7rqqht6UE2iw9d/1+Pvaa9/0XGJ2EskGW3ub4ZP3Rc7/bTNK16Vlxb1iXmAy7Sqrb41hCnw5W4vrI51/9bXG/p1Ay0bcu2tz4WaZwgW/4/pYR7fJrzNuS/YVvaDpKFprFdNYRgepQp4cXhQyFs+TBXtOIdzdwVfRGaXXCassuKziHU4g1YaFF/ty1g65cic0pIyK6AvslS3JIX0V+7mmsG4sI+zNGMqq8TWBYwUlXNZS6G1j4f5r4oXZdMEWy/Z9P1NK7hxGjtBqO1QBSXEPFETZeeoYhBt0lRN81CRLbLKpS+qU4ucyLzYq/g7MxiXebYNQbxXEiyno/fN5ZwRZ49/vp9lx+sSvMFp5JFA3XtyVhk/wcGcP7UsTYSsOyk9bm5b+ZFyLLKaqxSVfVRtIqkLHoCzhWWZ3Wly32Z6xKyfVfXtLShgZQNKFsZlhjHohG5jE3XsNl0c31JLr03vBQ+QrQdWlrF+0Djln4iUXVuiiNSCt20SP+khKrgVKmqTnkFZprWqJRrUftx1OtizWtcNRRqalLrbEUubr+lZv0MpKn3hTmpkAXvG0iFaSpLmrZ6g66g/g4x3ZiyC4YQ2HYbdrsd225rXlVVIi/X1hVgOudMckKbG2YcQHXOsq2zZeu5cj3qHEkpUcvQccu8WXCE+u8lbNEirjPPtedSnM+NK9BzPU8tvCyhsFvm3nL1dN7S5OI3rn+f8oGf+6PHp2Es9Omi//goaknlhtb05npnqccyF/yyYe8FAewZpFhEEJdmY2E75Qqj4PJ2iC76ln1Jc5LtvU0IbH0PmCFp2stLPhdNjSPJqfECQgJNqCamaSBrRMTovHN7QOdofenE5auXUCeqWsNztbRmKNciqZ2sOHAXu5hlfZyalJwAmoXoMpI9c61B7Zq+8iTWitv13HwBXFQsrMshzyHcXIOTM8blSCu6wSIoI2LhSN+W1LEPtCEgtfw/KUkMZ7BUqZKmiPiVS16PK8aH0NV6K47VTPmuZLecS6bFyyyAXOfSh8Zzry1dzp+GJs+FKst5VTOQZkMA1Zhceh3LZxNuVWV6baB+iqf+3PgkjIWyUF0/Pj7Mb0/oTP2+NhY4cCtKd7ryIi48kbrgUNa023q91y4jWush7LXg3AzKGZkJOh9obl5zPJ55+3Di9uHh4rzb4lEM48nwjeBQ9YhmUyhfue2kXBaIlWmHri3nStmbjYJNiksPUGnMEOQF9LPFat7DuvtarjgHOhOQtP4tQm0rIBXVlwUkXYO9dbdXtexJSgm9KowSMTwnC0bGgkKOK6laXdKsoWScgjN6eXCOqMlAVs0l3DBj5XD2XL2XxtCbDUUNe7xzBIFKQfAzDpTRrHM4FVcFJM+mPlev/dgQZD0ujMYz7Svs0OvjV0xjKVEwcJ4nxuhaaPqnjk/CWAAzSLjm169vQI2p16+tn5gr8vTpZ2ENgV5ZXbu6dryy8FRyYT0uJ1ONWc5LMVPbtnhxjKfzXKq+7TdsNht22+3M0c3bht3uht/89vc07hJsUtUimpPILtF0G+5ubnl5f8d2u10yH1kZ4zhneWYasy7lzUmN9hzPxvnYtBsUK1KLUwmpsrK7vbGGPVnwoZCWwBS4Rc0zcB6nMmcw1oI+FfNZwqs4/9bJ5cXDEMc4jRdGeB3jV0RWi+p21jz38wBKYZ3j/sUtL9/dz8xNTRFfcJVKGssK05QIQc0rWHmSS7VmvehPwfQ5/CjX1gyPv5hD15vZc8Zh7d0t3sB1qPw8LlHxpgsB6fL4nMr9RYYnr49x+bv+oLIh1VUz0IuLtNDa1bq+cc8Z8LpTOj5wgYSFvi2gs7VevUVlluKTq52lnpMRfYzU1Jc6hjyanH3XmO6EUyArQzPNJey77f7idIbTiZwjwQv9dsOLu1u+/PxzPv/8Na92G0SEb7/+iun2xP39/czcHIYBlxOhaVBxTKOpTp3HkdPDI999966kLe3aNs7jvVWzvnr1aiZ8abDWiCklWh/oNhYyxZiIOeEkENpmrgNRVSgGM4SAeDNAORWj5gFx+LBUgKpi7RdW43pSV0WzXP5TB+KNybnf79nvtxwOHVngZtMzpcwwKTqM5Ij1MI0RVW/VsPXwWnqXyHKPK5a1zipLMci5djhTo89/TApiZlheP6eX+rAXGMTaM+XKC6D4DlVVHaGqwa43OQuFzQtaFTJ8+ER/pvGJGItl2MVc/rbxfIjyMVGPJ/mPC9dsfZNzqSlZGaK5Q3ia06cOQBfsQ0TmfhN9qftQoWgx2G7dOG/sTmefjdGk4K6HQwjO03pTwNrtdtzu99ze7BARTieTndtsNrNnU3ur1hkfY+Q0DJzPZw6nI9++ecPxcCDFTPCetukX5WwgZqus3aD4qhTuHefz2cIFX/gdvsUFb8BsFlJOiyixlIK1fIkXzVkiZa7lqKzLlNITaXxximZIqzCzHq9tGzZFQavrOo7DmbZrCEkQJuKUSvtH0Ggok9Hy7X4mKotxFYbUMOojC2zetX/IGrzAE8tOvtpkZPWoLLjX+rfW19f8lsJoW6je83HMiLAKrT+0N/6c45MxFhc4Q74MR56+72PKDfUleVIwthykhAf186uYzrIKgqhVSpLTjP5XJK5iI7nMvqgZl5Subfniiy/oum5eNHUHrgv88fHx8lQUEJkb7vR9z7Yvili9SeNv3m+Yponz+czpdLAq1KYhFb2FMU4cTieOx2PRtLSsyzhNTFMs4UCR+XMe3wTGODFMI/f3t9ze3rLZbQ1oJpEUvCZUfSGBFT+fmmUwgDJnE4OVXLMazEai3svaNyMXI4EucXYuTFtdXfssoE7I2UhxtQXCbr+l61sOw5HGOwgBxTFMhecSk9HFUy4p1dK5PsOih2n/LzKDH5hfylxr8VPi/csMzNOsyMcAzw8d7wlomf36DRjfdG2W6ms/+vQ/OD4ZY1HHclH0YhdfXlvfvA/fSBE3V49ej1zTpag5ec9gG1AMhrOFYmnsYtDc5XnFGNExcrvf8+WXX9K2rT1HQn1GeqFt+7nL93rURsW7fsPtzQ33N7dsNhu6xghGjQ/c391xOBzQnHl8fKRte25f3EOG49mMxMPhwOFgfTCGaaTd9Khz5Mk6glu60XptvHv3jvP5zOPxwGk4owKhbSx82mxQXao7Y4xolhmnqUbCeqlGC/vSImQ8X0etFbCXi2d9n0VMFm/uwDdvxktja+ehbQP7/d46tL19W4xvQ87QeMfoHCLJKtALeczkBl3xZBaAs363E4e/2iR+rvHcb73GNT4Gll4ebMmqPD1+zdb8E3Ar+MSMxcUNk+W5D97HQob6qd+T0eJVuJnWW18R0bkcGFdvyApsLSreAkVERdntdrx8+RIy1kwIIbkI25auc2y3RgFfjwoGbjZWqfry5UtudntruOPt9tzdWavC49GaFD0+PhK6lqzC+8cHHh4eOI9F5zNacdd2v6NtO8MtsoGQ42hg4+l04nA68nB45Hw+k3PkNA589uIFtzd3c8MfcLNWRErpglOSSWiymplUirBQV/ojV13MjJYUsBn2cl2rSHJt1FM4CrlkoGbAtpjuEALbrdXImOAPOG/d1WvVqhRMwnABE0DOYvUfemEUrH6oyvDVURfdNeD4Qe/04zNsxsWWWbN+dXly/r55j1yKHC9GwSnWn1nCGbFQ+jnP4md0LT4hY/FUYwCW2PJDln9uRXr9fLmgidqZfHVMp+ZdVHdZst0IMZd4FrdxghQhlPmmFIQ+abKu3yLEcaLvOlOm3mw4H46G6Bfp+DiOVm6+2bDdbp/8PlFLhe73e25ubthsNhehy83NDU1jbe1OpaHv4+Mj4gKPj48cDotc3zr0cWWxo45Q2vmllDgcDgwF35hSIkvmOJx5+O477m7vubu748WLVwV/KWK6K4KZQhG1MUMiadXLpZTPAwunQlcp29VinFWc1p6dMDM9K81ZSpjWdc3ccX3NIJ2vY2EmzFkHtTDHXufie5/jItTYv3I06nF/7HjqDX94XHsd9px/8lztFrc8/0/Gm1iP7zUWIvKfAv868LWq/gvluZfAfwX8MfD/Av+Gqn4ndmX+I+BfA47Av62qf//7T0NRTJ/AlYa4ywnU1+sNWEIRpSkYw2LF5y5O5ZqaPuXKBVQgh0u7bbOftXy76qVLrUD2Ct6jPuDFkxN4H2gd7Not+36PxIzTzM2uh5zQNOFcwzic2HUd+93m4pdbuCE0wdF5IbiMk4kutKh4Nrst4h29XzIS337zHefzmRcvXuFVOB9POGfewKbb4EPHOEQk2GfGKYH3tPsN4zgRhkR0Z/M2suPbt0feHybavmO3ecf9/T1/9CvlxYtEEwJdaJhSxInxR5IT8yLEEbPiou3q2RvW5KKiJFxSk9yPRQagZIdc4YNIApVk9PLkluyUZlxONN4zpsh4OBBy5rbf0ok3mf7iuTStEJLAyUJFq0A2UR4VE/y1itcyH+q8EMX55R7HkPGd1QORBC9L0dz3jXVK+LmQ60lq9clC16u/8vzXbHjKRnbhkVwZj+tMy3Pf/xcZP8Sz+M+A/xj4e6vn/jbwP6jq3xGRv13+/R8AfwP4p8v/fx34T8rjR0dN7dWL5HFFPux6KOsLm0mg5im4K4NbY2VYHLrlog3Pn8jVV84TZX4ocWYeS12D+b7KhA/KZtfPhNBNv2XTd+SceZcPtL6l7zZ8+YsvL75jv9kSGsfrFy949eoVNzc72lJ5Sc4GSBbef9d13NzcMI0GlE7TxH6/h1Lw5b1J8J3OEylaUVTb9qaV6T3eW1e0zz//3IDQ45Fz8TJijDw8PPDVb3/HOI787+2fcXd3xy8+/5zPXr7iiy++4PXLV4SCXXi3FLNNaZjrVKJaQVaDGZbTOJCKDF7wHpVmNr6VjGeyAOa4m2aom4v1AELrkejY7TZ88cXnfPf/vCfliPN2sZ2DthXGUXHB4ZtARphSZIqRnK1e05f3ChmPt1oc60DBtjOjnXM2HQtvSmEf6ixfjcKcVZnX/zMVputMhiyA6/Lk+vX6fTq/v87FS6NTDUl5nL2lZ93sp8/9hPG9xkJV/ycR+eOrp/8U+JfK3/858D9ixuJPgb+n9qv+FxG5F5Ffqupvv+97nCwxoylK19RV9TIuRVvKizMhZZ2ys9eACpDqOr67JMV8bOeQKyadr0icGhdAxJkGgqh12SqNb4bR8IommDx/53urFi0pzMvvMPJS13X0bbc0PM7WRYuc0CglFSu4fkO6mWa3fixhiQt+DgPapoetI3QtXbcp8f1Ssj9ttpw3Z06bLcfNhtPpRIqRIUVELaZPKfH48IATYTydDe9Imb7rTMWr7eZrl8hkUVz1/pwU/KF4fMGbBumK6q2qJFl4MYt4iyOuUoKLzuZEaBy3+y1t2zLlxEZ6pjGSojK1ip8Gu+eZWWrPXELbMETKtMiWbltXHHuHoaNa2aR5XnfrKbLMwZodmu/kxeuX82q9WD+woOdxGSJ9KKRZexHmeawNzPX7PvJ1P2L8VMziF9UAqOpvReTz8vxfAf7R6n2/Kc991FgIrIAknQ21UEuL60XIC56giner4h0u3bvlQlJCGGaj4f33/+znUl0+Hy0lR0QQWyBezZ1W5TyeGOLAOI64JATXsO2VsCsd0dU9sfK1U/im72m7YJTvep5SOpYbCdpwjM527CZ0DDFxHs1LqpTogtdaDxMfnuh1Vixkpk87oW0apmmiGQbyFNn1GysrT4lpmnjz5g2Hw4EcE7cFU7nb39j5r8hHzpnKeL32F7ob3gRxcy0RnxeBNZw2CqkZmiqEVDtpORRRlkfuPwAAIABJREFUA0f7vmW77RnHiHaemDJTykxZCSESsexUQgup1G583cwVrAhNJmCRz3dqWiEOXWUg8jPLetnxLxfhpSdwDaquw4WPL1598vj8+y/fJ2sj9TN5Etfj5wY4n/tZz565iPwt4G8BhLASWpkfS+pshq2wKsOZwFKUq1aGwoxFsczKU4ad1EzG+jye0q/r58t5zn+7ej7Fa3HOQFBL9SXGcZgbBY3pzMlbKz/XeaYccbrItNXRN1bSfrPbs2k7E70p5+B9xWfc7EV57+nbjrGJuNI1a9tNNH2H86Hszp6pLMSUEjkpIVjBmaizJkUlvPECjfNMYbLmPKqzAM04jpwPRw6HA8fjka+//ppxGLi9vSWUQq+u69Bs2aAlMyFzCX09Z1+qUctFJukigyxSi7YCImn2gNY7pzgI3tF3Lfvdhgc9gmvZ7jLncWKM4NyIS8pUNEZqjL+urFUtiZtn0pu2kOs52nVPT/p//DAM4NobWf79PbyKq8LGtVfx3PfO18g9BXJ/7vFTjcVXNbwQkV8CX5fnfwP8evW+XwF//twBVPXvAn8XYNM3dl8vwB+ZmZR+teiXzIfDSZyNhCOU3V6eXNjl5lSUa30ml7X+cuUmqi6fV2msIAqILs87YRaYknUcS7kUcTkHKTOczkTNDHGy3foqXG3blu2mY7/f0vc93pnhCc68hUqGQpQUoylrZaXvOtQHmqab8QJfPIlxskrOGEfyaHU3TdPQ91uaBrzvaLzgu47ghK4xvY3jNKA507btnDmJ+xsOhwOHw4FxHDkej2awmnYmnwUU8R7nzPALJhI7DaOlgItgz5rQ5ZwrxWxlkZaFWu9vkBIkqOKKQetCg3Y9u92Ox8cjaKJvrSlRGKaSdl274DJnR2ppvNMS+ujTjMgFUJmvjMfV++DSaDwffizv/9jrF+/Lz7/+fUCrX7EYPxTG/EXHTzUW/x3wbwF/pzz+t6vn/30R+S8xYPPdD8Er4NKCwuXFr2BlZTvW15+kzqSI7D77DauWbu6yecf1xX2u0MhebFBf4vHasITKD9CiepbxInRtg/eOlCLffXfgfD7ju5581TjEie3ktYEQqvhVyFB/U6VOi1gnrZQyaUqMKXI8HpmmiSzQdT1SuoinpJyHiRgTwbf0/dk6nfW9hSOOGSdwztHmhMeqQYMPhK7H7W/Y7/e8ffuWr3/31cwkPR6P9EXkZ993eKDxnlD1NtVo4U2hsdt5JzPNpZ/I7EFkWJenwyq9WaTxvDia4NA20LeNhSiiONfOHeJTMuk575x9RVrdJ1c9xMuQZ33fn1tT12n5izm3KmF/6lNfCR098TSe+bIrb/jCwKxfU33y93Nh84f+/VPHD0md/hcYmPlaRH4D/IeYkfivReTfBf4h8DfL2/97LG36f2Gp03/nh57IWrHJxgIwzVmN4Od4XlWtOtQtYQe1v8WKE7Acc/k7yzT/vc6pgysyapcal3Ysh2hDRkkp4nxTnIdMCI4uNIgm+iYQ2kCDY9O0TMNIOia+/vprvvjyV09qQ3JM7LY9bWsNi33waCouvJr4bZSqqWHVkCG04BJ5zNa5Xax+5Hw2L0YVmtCh4vCuoSm1K6fTiWkyWrSQC95gOJD3nqTJQpxpmq95KGrlKSUe3r030d2UGIaB0+lECIHbvrcmSIXBmaaJaRhmqnwoVZwxWhewGpq4ZJ3Ck1x1kGNJW4ozjYlpMlC38YG+7wvzVRinAR8cm66BbM0NxAc6H8ga54ZBIrV0XWiDwzXNZQjqrQm11vCotDm8zGR82Gt4ukCf7wRWQdvnPN+1avx1CnbtnazfUx/9M+BmeeLJOfzU8UOyIf/mB176l595rwL/3o89CRElhFICHmuLe5AgaExzJ66a0XBlJ4l5CTlmEZPitdeGNyKKbV1111ISq8a5skj6A8tEnXed6j6b+xp8wHvQHEsKLoEomyDc7nprPegD+97YmtN54r1muu2GlCeUS6Wsv/KrX/D555/Rdc1cQq1Fdfvt+/eYEnY7pz5bJ6gzL2tTpPgMyBQeHx/nBsvjMJAUEiODDITQ4kPLSGI8V2NQ6jZy6eCVE912Q06JYUpMw0TTtahC32/4/PNfmPFLCe+CxdcZFEdWYRwsI3Qex5ktuicxxoE0RYZhWCQCvfV4tX5kWnZ+47DklHFth/dGU9c4mmJVts5it/sbfvHZa949HImngcYHtluhaQUicyjqxZFdOb9swsGN93RNw7Zr2WyWedB23ryVMl20GC8v6wW7nrMy4xcVQK/PmxecP2gs1nhYnZMVBK6SAIvi9/q7Lz2hWZwXE4x+blTj9HOMT4PBqQo6YDhFKpa6dNVqpEjj6QxQ1nyY9/ViCwSLgXMqrfByLHZAgERNx5pru6QvnVv6NNTHi8o/lgyGhBFSRPKIQwnCrCjdiOI0opoIoSc7ISYlonTbDbe3+0Khvhy7nXVGr8bQcA8zKC5VkLP+jssdp0rzt21g13ekNOG9sOs7hjbxeDzx/t2R43kAZ5hFaDqmQk+vug1ajEUjmfZ8RoIZqJqOVV3Uth1SvBk3h4e1+CthTXrGmJiSeRCVOzHqxOH0SIyRrrGiuVR2fecbskY0W9cznDApRMWUq9TKpJIY2N00DfvNnsPjuXhFQu+tWncYM5NCVodLRQoRoSu/1dtUIXihCcvia5zhXTlbmfyk5qEG9xR8r3/XmVixlZqJsNcuF/vywWtPZHafAfCusDdnLPg6O8K8aVZjJfJhB8Le8wekwSkCm8Z+bRJQrZ2+oSu6ESldKhHlouUwDxWTXHNCckLWOKs6UXZR54zsFVfxsi8svkW7c91C4Ao/8cUrkIR3QiMGYmbN+CxMBTvQDYxT4jydTSeia7i7v+U8jHM6sI7tdktb6kWSWnVmTGZ0urCxXqY+sJ4RWSPBt9YyAAiN8TRuVIltV4C/qrlRgT7rUN61HW/efMc4jogIMS5aGze9p+t7k7HrO3xjgGkYG3a7HaIwFgKXOj/zSsR5sjduxjiNDONAjHb8x+EAA5wOB96+fcs0nOcsyrbrcU1g1gjNkSRKDp4owjla+JHGiVzqS3zJuPR9f6W8ZcV4yGiK4mt6umYazCMz7EPog7BplunvXalB9s4kCYuKmH+m9d/FQi+gbZ3HM+bClcf6ARxhnWK2I+Z54a9JV+vN7HrtiMhSt/OM1fiD6kjmBFpfysbnH12a6cTBcvMpzZLzZlkzmobSO8JUnpsCpHmnkMCTEZSkEdGi9ajCQrYSRAIVXDMfdK1aXWNne7fXwQBJMTEVycoUE3mISLclDlYivt3doS6RculFmia6rmMYR9r20ru4udmx3fVWr5IzSeO884Qi8Y9bskRZFU0JN0vFm7CvkhCnhMaVtKaj77fc3rxgjLbTinimBF///g2nODBOp7k4zXsP+458W3CQcUB8kQncFLXyKTINhrmE7aLbkRxoTAzTaOnjOKFqu/d3D+84PDzy9u0b3r9/z3A+z4vj9YuXVkka2pmjUVsajDlyjJHT8cQ4ndGYmPu/qmVsDKzNxKwM0bCknDOykhDMOZNVmZJpkoRWaV2gbRxrOVTNE+LMaHonVmzsBK7Zllwv2Nm3uOD6+NWavTYYF1kXVVJRCbPFcBkyzPhcNRgXhqQaymWOrsOhZfwhhSFkNJ+pLr+INypSXb8o3pkRqLJyqkpMyeL7Ur3YzF6CQoq4wtIQEirJyE3i2PbTvCGE0p/UmIWyUt++lHYHaLJ5K03dN0TxXgmNsNs07LqWmCamojClPqAukNKAC9bu77qQ7Pb2lu12O3tLqmr07CD4tpmbIJnGxqJ1OcahnLedcxynWYyn9Z6m7XC+w/kW7zpUAlk9b96948WLF3jvLR06RM66LOBpmixdLeCyYxLBBW/SfONkLM6iXnV7e0vXdUyaicM4F6hpDY984PT+kW+++YY333zNw8MDw3AmTpZG/u7t25KmDbNhamumJgjTNJLGiSkO5DgVsDJzW4rbmqZhu3UMU2RMleOSZ4NvncwTa900lzMBaASa1RoKYtiTr5WwWPj0pEZILaxZdvqFEVwXrYG0z2Edy2cWyUbzemcNTf8czlGdlzUloBqecvwZB+HJvP0hJMQfMj4JY+GcY7fpi7Ws2Y16MVe9METMkNQQIjTzDfRiXoUW1iGbDi/gg4N8BvKsNxn9dytBWZ1DETMY7Xxe6+8SEbqxSMUpqwZCDjSgEnj58tXMT8jOFr9TywaISAlJLi/5ZrOhbVtyGoqHZAutaZbGx2kyI6WyNKFZaNDGbFwmHIzjwL7f2vO6KJQLnu12yxdffMFd0cjouo537zYgmU5M0cp5T1fL1KueR81g+MDNdsfNjaVUQwhM4himkYfDI6fTCVB829CnluF84jQcOZxPHM4nYpzmrmun04nH44EYjdUZQqDpSr8Ub5WmTbCMTdaEVqWt8WCAbOGPWL+gYT5HnMcqbRMhWYVxW+pMGm/Ubu/ArzALIwZazYsKBIUcZO7Hug4Dnv5/6TEYX+Sph7D+WwqoaUm8whVyroQh1yHFWkLysr9INRZp9jQuItZ5Y/05xidhLDY+88/fn0x1u9mSRIg4kgQSGBkKx/E8zSGHCDQum2fQrIqHpoloKXi8QB88u87jGXEkvEDiS8gRyHSNJVzJCYdlBnww/CO0ZoymZO5vowkDrdsCwLaI7xHXkXJLt7ml64XQ2Hw1gC6SshKCUaqvkeltH3CaGYrQTAieEFqa0NE3bSFyVcjMoYVMlCZH4z1pymhyBNcRI4zjGRpPmDLBWZPlnN/Rdlu6zQ190/DZL15bifrpxHbX8+67t6bpOTxwGge67Ya276xEX6xCVJPVTey2O272O3ZdRx9MBvCsE64JjK3j8d2Bdw8HM679juB74tjh5NbYrIzc3e3puob3jwN5GFBJVpsSM2400d1GYNNBasxz1BiJkxnU9+OZrm+IRNuXZcI1kSQT4syr6rXBT5l+iGhKeG3xLtJopuPEzide75aCwrv7R8QbWJqjWvGZgMtGCX/eSGTWG/2CNUCYlkVaSbvmUXBBzLsOcuK1ANZqFPz04n8Ri1zcyrO4/vzPYyo+EWNxd3/Pn/7Nf4UkwikJkyoPh4G37488HgfO48ThNPB4OM86lnHKTOPI+XRGj4prQtlli/6lD7Rdx+3tll9+fsN+27Dbdey3G/ZtW+jOCacjwSveJRyJrJHGO7LEhTegJXNQ1rnkBtQDAZENyIaUG45nB+3eZOtK+0TvA6hpSKS06FeuR9WorFWjtRvZXHUZwhKaaRHlkcxwHIi6yP6bgyGcHw7kU6YLHV3b0zYb8hR5GL8DFwih4ZQicRy53e+56Te8e/eOeFQ2qWd3s2ez2+GCL63/qnix0rcd+23PzX5L35vYb9d1uCZwm29nZaqvv33D7776hu3+ni503NzccXNzgxOl6xo7WfeesYQXqYRTw3AixkjbBU7DiXfvj4zDkTgOaDIhndYJ/a6361XwlJxLK0jfkaaRYTogCJ+93ht35OEbcspsN/DrX9/zJ3/yS/7qr1/x3/zPdg/+xr/612cdkJQSOVr4kqJ/1lCAbQTPGxEljJdAo6rO13Kt7XHhsQhEPvx9H3peRNBYz+n54wPwv33NX2R8EsbCBU+z30HMnN498HAaePvuwPvHE2/emZs6TplptNTiONoufD6Pc+4+ZQPmLLQwrkPXN7x923E87bi73fD65S2n2wnZbdj0JqbSOMvPBy94VZxvaANkTZbnL0xEdZlYSTxaQC0t3TqccBqUrJPpVwSFrBY/a0RT5HA42G/9QM5bxArFQuk5Uq6MtRz0Yn1IwcC7dTycF6BsdsOzkqeRKQnBBRqvOLGu72M8Q9cRR8tkdKHBFddcmgbfGOlpu93SdC2U1ohd1zGdBxzCrjR9bnxgKmlejYnhdOZwMLaqKW0rwzBxPo90oSmAZEvTdEDm1WevzcBTOBfJmirFGDk+vmNsPINXgodBII5nUlLG8YQPIEVJ3XqanCBlYh7QPEIlcHVbXr3ccfOFhzyw3wf+6K++5q/9tV/yy1/ezdfxj371elYIyyuGaYqXKev1/9WI1scLklR0z34uaX7yfP23OZDdjzIU61GNxIUS+8X4AzAWCjyOI8fTwD/++hu+/uYt794fOI+Zh8cTKgHBo9mRkjJNkTRlTufMOCqpAIPjmMgJnJsYfeY8JI6HM4fTe3bbhq/f7Li9u+H9rUnL39/e8Nl9XxrgCM4HXMjgFWLC+WxiPBkQy26IeCTnIpiqiLOSeic2weIQcS6b65kgZquaHKezgZdXxqLGuLUa1BVl6pQSAQ8ieKm3yRiPlaJd3++SlbjV44sa8SpNA4MKHm8kJ+dxTtFsWZOuqQxOKwpzdLi2mT2LpjMyWOVdjKFB1LqotbN3JgwoMY2cTiceHh44nU40TcOLF684nCZOxzPTGNli0v7ONyCZTbux723CHFvnQhL77tuvOR0fOT4GDo+WITk7hWkijVanIt7C0cqF8M4xDRYaBA/BTzRN4sV9yz/3xy9pPNzctHzxxS2//OKOu7slM3V/2+FKU2SyFuk9z5SeX6zA7Pmtd/g62tzMv+fCwKzSq88teJHNhYH40OOTz3r35PvWc8zG//qhJfiDxidhLMaY+Edff8vh8cQ//PPf8/U33/F4GMjqGCY1MMoLOUnJu5uY7GlKpEnJ2aGaiDFY1y4gigF/g8+cYub98cTb44n+zQNvd3tu91tevLjl/OvX3N903GxbthuhV0dDJqZEOzm8V2p9ZC6ZGbKSUzRuh4tAImfr93k+jyQ9mxydtHj14M/A85Nj9gicnw1J1eVMufZKsUlp5smAV4e3LMJq4jnfkrzSecfD9MCYYtmtJ1pvizI4IYrSNwHddIVWjvVbbTPtpmez3dL2LRKKcpQmKL1NQqlURdNMlpuGgfE8MJ7P9jiOuFJoFpodTTBD2XWVeu6IU6QJuRi9ZjF8xZZuuoaH99/xtl2AXhHBDycYLRsiWolQpftb1zJNZ3KGvoW+g75L3O0Df/JPfUbfeW5vOm5vWvY7T9su96PxybJqmqiqbEE82T2/UA2kXMYCLtqzTa7ex1XIcLFZPJNSva4pWR3/Q8bDJsdl1mb9uZ9rfBLG4ng882f/4P/mNIy8efPI4TQxjgklkJPDuYh3nhQzcUyMo3XRtpoCX1x+geyK4Vjt4Bma4IgRpqNyGAce30Pbnrn99sRxzNzftLy43XB32/LqfsN262h9yxQzPqVCwc2202NcDS0AhvWtVcZhQrJjOJ0ZhgOhdYTW4bwjlwKw65oAYMYqrvn+NjkEMkSNeDzZZcv6lNfJxjatXoadm5JxK5zD1J5SmkDAhwYXglWptn7uJCaAH3poPE3b4ptQ6mys2VDO2Xq1BlvY0zSRiZCVcTxbyrSc+zSODI9HxB95/Ytfzeli55xpfh4Oc53KMExI8LPkv/V+9aUmZW8uvVj2oO6aMRhnpOuMh3IezkzTxLZvS6hihuJmG7jZN9zdNbx63bHf9Gy3gcZH4EyMC/U+5YlcGjJpygRxTM7NihbPhwTLQlRqSULBuYq3+2ThX1W7XnMvNE/PEz9X1dCrJMnqDas+Je7qmM8Yn58yPg1jcR74P/7P3xBjZopq2Y/sqKLRhg0ke26CaRJSykSxPHpKmRxzSWXaIpuBKhFyMAFIFzPilEE8ekq8P57JvOF2Z0bi1f2Gh2Pk1f2G1y8bQjCXtupHdqmmtbLtagjiRpwEYnKI9KQ0MY6PNEnoVPBNJmJEJufcEwZnbQWg2SDttbHw4lDUWg2K4RbLDuzmYzpavGQmsboN1LHdWlrTSSClzJjNiIxpJDQeROn6lrCqjdnsWsZpsqKq4HC5iA/lxBQndm1L1wa8mJDx7AFNEY+y3254/fIlMStv3z0wRuXh3Tt805l3kJWUjWNxODzy1Vdfz0a06zr2t7fc39+z7Tucz1Y+HzpSf8O5PeFdmBdoxRecc6Q4Mp7ONN7RNMbHaVvYbITbvWO/D3S9o98KbSdoikzTCbdqBBRjxEko2QoTI7Zpk551/+1xMfCCtyI2KSpgaxnZK+Mwt4JcPfeE/s3lxvHcvy9G+S3r9C2ylOj/HOOTMBbjqPz5V2fb+ZwVVClF70DFZNgS5FSAmyTk7BhlNH2CbGXbo+YiHwfDFEFMVIVkhevKRCJzjBnRTBsmND/wftNwPAy8ezhyPE8MQ2S7+4wQ0+yW5qxoMRaNr3R0S+llPTDFwDgNhHbPeJx4OJx4PL1DvLUXrDesKl/X0TRNAWWNiFV3ghp/et+gOeEKXdsKvphVp6yobqk3yC5zypndzYa+6YuepdHPp5yICtHXBsdLi0GAJmakFVLOpdzbYvdcDVTxZrw3UDepkqeI88w8EhEzGsN5Yhje8+bNG16/+pz7e9MY/dWvv+TP/uzvk6aJ92/f8/79e47nE03ouL+/58XLO3a7HXe3OzYby7w0TUPb9oiYd6lOaDc99y9f473neDzy/v1bXNdYKOFg2zte3G25v9uy33qcy6Q0MU0JJRoBbmW4h7GGe3Y9hGzNo+Tp4p0fL4SM9OLRr4DnXOUfKanTtAIfnVwYC32STF3Gx0IKzZeiQev3/0EZC3BE3UIWYgrkBKqLsYgxkWLlVxhrUdUxaiqluQ41lUWcCqJLfwVxikwBr5SwJsGQCM6j2SNjy5iUb05n3v3+yPuvHvnqrmM6jtzsO7Z9oGkd3jtOzhryBjeiOs3FPM55kIZEILsDYRM4Pj7w29/9ntN55OXLf3HuMepce/HL+763Xc05mkJ7zjmTYqbJpsYVmr4IznTF2JjiVkZnafyUEuIMq2nbHu8bomYKY4mm8TS+w7cNGoygNQNiZfJ2TkmnEzlFpMjtdV07d+eSpLYrpzR3ZdOcOT4+8u7hLY/HA+fJKjc//+wFX375JeI6pslCreH4wDe/+3NaJ9zte77+3cQ0nBkOByZ3wpPIw4n3TcPhds9uv+HuZk/TBs5Hq1zVBC9efs7dzS193/P+/QOPx4PFgxppGthvHb/85Qs+e7nhs9db7m4853FgnM6A4RIi6QJsfngUZtaumtvv1BbIstiqSz/zQT88o/M1yEi5jlDLDaqBF5HZaGT5sLH42JA0PQlp6t9/UMZCEeJk3oGyigUL8SRlyEgp6rGGsFkVJ2Fmo0jRoKgtCTWbC2Y3rVyw7C2lhuA047KDWBORQlY4HRPCwO9++x3nuy03txtuthvaroEw0QZHDhbLK3FuWKMy4VyLIvgAmQOH4xsejyf2+3GmlT9XUFRl59aFUTZMBs85RxA/ewNiWVtrFVhgz5lhqQ4fAilGUqGAO+dwTcCHEltLY+nYWgxX+1TEMxRg2HmHD3Ihl299Tk2kNqvVpOSciePZrkfKjKcj5yniQ0O/zbx8dUMbdDZomiOvX9xyt9+gmnh1f8fj4yM15a1qlPPz6YDXSCDTNJ5hPKEp0Xih63p80zBME4fTEVVls9kwxCNd57m72/Pibsdua2GTw9LtNWvl1LyPNdY4Rj+zhh3ZuqmVEHQxDj984ZlD8vReL20RzehcewPrroTX42PfHXhqKOzfT8ldP3V8EsYChThpyblbA59stc2l3sGk61rfIpLJ5X8pQrS1aZBNZHu/wUHGScgx2U5BRrLOAkk5Z6aYkJKajFlImhhTZvPtiSk7puxJdPQZfJOIDfQ4UDHdBXTGEMQ5Uo6kpAzDiSmOpGmcX3+OY1HB2FnVm5UByW5G5WsdCFlLRmRF+7VuwLOXgXecHg9kbNJqMrXrFAcYR9y0yj7IoogespbO6B4XPK5UZaZ1Ok4t9ZpjtHqUKTKOZ1KaiGlkHM+czgNN2+ObjtPhkRgzNzc33N/d8Or+jqYNjONI1zgeXr+0JknRQszj4cThcODx4b0xzePEpBNxHHAofdfimx7xDbESuNqWRGZ6PLLtt9zd79nvd2w2nhAcion1mKixdQvTqOiq3YTpHluY6dRqO0QzWa9W7w9sgXfdyWI2BmITfln4ernA3U+rEFX/NPxYwpCfdMgn45MwFgvBpYi9psw4RmrrPArar2K8A5WMSsa7YGGG81Y7gIFTWqtHcy4AqAUqdTfOri4UR8RDgkktk6CaCB76YyY1CQ1K8pltVjqfGbuy++NNOctl053AMg8pwvE4cTxENDvadjtzKJ6LOVV1fr2OagjW3gZg/UrVXncS5utm52M8Ee/Fdug200hDDkuP01yxlyla3CxSDGqZWD4bSOjEuA/OMeXS/TxG8hQt9CrGYpoG4jjNzMthOJHiSBDou4bdpmN/s2M4nNE4EccTh0czasN4Yr9vadsb9ruOyhMZzhOHw4Hff1V5A2aUyJlNFwihp73ZIc7aMKoqoWvoXeb9Q6brm1lIyDkQzUzDSI4t2liomnOZJ6u+s2mGL0r2RcuVebLQ3PcYjHLMfC3hX3AOucQ+1vUcdiIfWykfHlqzWleG4uccn4SxWFI8lq2g9Mc0OfWMODHVa4kFJChEqKKgJd6hYjdfozNBWIoTqEZSIkthKjqy96Z94T0TkLIUuTi7pT4pzSEyuYlRzpxp2EZhHyb6tiouWePf4BzOwzSBc0pMwvt3Z46HieA39O2iu1AX9vVvr6nPtZu5ZgVaytA0OqqhCr5wLly+vIYuWB+SpiXjiiy+fXcW0wtNZe6GknGpqtwlD7xqWLN8fzUYqDV0qmGHeWcDwzAwDaZh0XVtUfdyxOFM04YSrkyM4cyma9hveiKm4NUFT0qFJi0g2sJnrzgPJ06nEzJmQGb9UDZbNEX6fiC0PS6O87XtOutWFmPE4YsEYEJ1Z9dgMj2QnC7d+hjz6jdnpAS01w2Blvt3xZB81oDohaG4eEUrlHnpWfhnSuKffvfTESU+ed8fKMDJEtNWklJxqWPMSCFlmTNN8RzU/pJaom5/Z0mzaIk4S//VXcIXVz06jzgPYulLXg7cAAAgAElEQVTVGe/IAIExT3z3eGbIlnKMOPZJUX9k6JrSa0NpfKYJ1qg3RtO6UNdyeBw5nxIiHV23XVzQZ4zFOhV6jbbPqUkrpyskKLE+GvUAV+k0EeE4ngtmMTCN46xDiXeMcZrj5uA8bTD1be9Avc6qT6zOod6XVFXIlFl2DiztmGOcz9d5+9z5dKJr91ZXExNRR8ZzRpPVwIR2MgXzcm9VBR8cTfB0bWOq3t4RU0PKGR8sJX7OmaZtuL295XQ68Hh4x+Pjo0kMFmXyS0Ng5QGkTHZuNhbrexFjnDELX1XPUKbrcGIVXzyvQFXuh16FF2VknoKOaz5E/onGIpOeGImfe3wSxkLEobS2cyIgHu8tlp8VkUJDnDLjNJErbz9MeBoUTxozOmU8jqbs1tX6D5IheKQJJOdwRGIc5qIn4zQUy+4F71uCBPIUOB0cmhKnw5mxPeHcidN5oms9bch0faDvW4JrTfMyTzxMkWNKVuLd9zgXcM5Uq67vY9NsitdhVG4Ttk2l6MzOLWVF1ErjRZ1l9MfJdDVrSbYIMSrDeSDmyMP7R4bB2JQxRlIpegLwBXBsGk/fd7PGZ9v4uYOZarRUawExVTMS7TpZqtURc4QMvbRMNEQdUOcINDR4Gt/SqOBipnXeOCjngXHIHB4fTbRnbkpbFhdGrtkEYdt0ID3qPFmV4/nE4+nM19/8Y969e4dz8O23v+ebb3/P6fDAP/vP/FVe3e252fd4lyycdQHXdZymdrWYyrRfZR6qkLKIXKik+njJi7mct88+Wx4WUtYFg1PEGjY/42ECs2jw+rn69+x98NRzeK5A8ecen4SxyKqMZXe60K9QS51WPoAt/iXWW/MR4NJizxWjJZYrAY31ai+7pXXdKmSp4npXTU5xgYydVzodOY8ebY7m8Xila4S2gc3Ulb6iAbwnp4nTOTJMGfEsmRjgOZCzhiE1ZZozxk5NihS156x59ipEDZMJPpBUidOESAJnrvc0TUzR2gPM/y7K2D6UGhBZyEaudDKza6WM04RLqRR25blSVkRMll9MBVtW5x5Km8YK0krJ7jQuWKFdSUVKMWo5F63RcWJMkUzGOeOctI15O6HrZw8hpsRQOC4eNUzj918xDANv375hPA80Lez21qm+aYrYjSbL3JQQ09bWU+8OFszi+qUcP7bTf8C9L3VCQBHQgWpEbO6uqNlX3+dWPIv1ucgqXKmtRerrWry9v+zxSRgLKClShUB1yRfmXIy2g9VJO3e48lxceDcveEfblN4Slg+hyr5nZO61uXz3YnDOOdNog5tM7wImavFWakaaxhD1thGa1shOwxRnRuEUHQ/HE2NMdASkqDrV81sDmfW5et7V1Z/l4PKiL1nFhsWX9oYU/CEnI/Ik2x2Pw9nUpYp2Rv1OIza19JsOVasXCU1Rp2q78n3luwtgWq9lvUZ1mAcA3jfAYiwab5wMFwKNt+da365AWisgyzmSfWRCYKAoi5lIUN8Y3XvTtKgq52lEYyTFEc2mTdp6x7brOR8fydFo7H0frNExRigTIuJMIl9VSNHCVjv/5XfUUZnf18ZC8kdW4Uc4EdZucTnYzAZQcOswRJkXv6paWFaPUT2Icr8FAb0MOWW1ef5lj0/CWNh1KxPbhdIdu5lrAVJKTOM474JL9kCXWBoKgFn4DB5kNtuXE35dviu1Wk9XvUKSwHlxHytDUcbJ6hYaR9c4uuiISRgmCCHStplxgsfjgEgDoUH9oub1Ic9i7SVVw2XnWN5b2g6KOGuBCMRkQjxZsxlAVYYcmVJknEasB4o1RA5l4XZdQ7/ZENNU5PcdKp6MszSiODMUqiUl7XDicaJMcWBRPS/Vr+W3NL6dsZeMWpWrCzQh0HfdDN7mkp0S71C81dqoI6QRHDS+McBVrPQ/akTjxDSeGYazpWjjSL9pef3ZS4bxyHl4IOfIzX5L1wQQExsSYpFZNEZqTOuuYE/5CNMHPIvnNDjX987G0/c4vWJmusWzUL3EVHQ1N+OKgl6w/Plz6/lS7sJynGeEhX/u8YkYi7qYlqa9ALnw7O1+mSqWbwKhTM6Ux3lhwXIhRYyfEVOViaNQo4tS+Kx4vdRF1PAGYErZiqiKUVl2fyXkTHvMpFaJGVKOTFFpm4YxWmHUGJ1VcTb9hWdRvaL1WFeaPld4tBSZ2cRXXWU2sul45Gw78DCYDqXGTNc1MxYhIrPn0zQeiZCSaUpUQ+pdQypCOoJN9gtSkVoYuGyR1YurHt3CmlU1CX6nrrQYsGsQdbJaFzGdVV+Iaim1pa7CzkajEomWDq81KGqErpwj5Mx209K1jq6keDfbhrZ1pnNRGlfPoGG2dorr+3BNkIvxw5mLq9k6/7V8/JmFqsWTqYYpr96bVlmvlccBluJfPAcummrNz5XPeFYen///ibGAZSGp81zSaFMB46w+wK90H6TyMLBwpN5sZXHltaQCLVZeuBxQL3Tpt+kWHMRJ5R+UQpzyd0zWFu/xnJiyY4t1LR9jZpgiTSNMU8L5Bt9tafoNuJaUaperK9ogNaZVYjZWqoq3NHA57zk1nKwhD4X3ICKcChYxTpHz+WyZDlU637DZWe/UttSH1DYIYC0HQmmxYN6UJ4TGQpto54GUbow4wOjaaJ3MhgmYO71iH2bIyRZ68HaeRIXG3uvFQ8E8IBO6hiY3dr/me5YMa0gGquZsyuwOY5x6J0xxMMmCHAnO2JheMkjCiSt3TFCsFkayMqYF4BV86Tmz3AeDJp668x9LO1689SokqT1L7T1LCLTc9w8cVBfPB6pnITOoX48pIsTympZ09l/2+GSMhQ9tqZJ0NktLvUKMlmMPoaVpmnkBOWc05UW49lIhaL17hOBm65yyNRw2w2GL2K3eG/NChrLwZDmWjiNJlWG0yk5nZh+fhZhMAyNnpWs8TejwoTPjUDzL51JplX+Ri7ezzrs7cTPnIRdPJyedVahOw4BifSHGOBE1lzCtpdv8f+y9S4wl3Xbn9Vt774jzyqys+qq+172+9rXNZyy3jWmEYQaWGIGQLCYIJqgFwgxACKkHdDMBybRgQDdqgdSSEYj2gJfEBCEkBEiIATQt6EHb7Re2ue77+F5VWZl5XhGxXwzW3hFxTmbV/V73UtftXUrlyVNx4pwTsffaa/3Xf/3XhsVSi7DGis+oLQOUWGRIORJixoeEcYl2sSTnUmqei0ByztoGsRiLqmFhxGh9CFnjP2ZpVgyxksFixBm9b86AnkSNdmMsuakGORYWqCcFSGEgRCVkpRBVuaxS64PXTuhRi9hyVo8j+F4/V2FpUuoz1LBMnpsZPdDJy5vKzc9Tna/ZsecL9Lw/bv17dsw8NZ5nBuFkPpQXqZelxXp6bfNoJPT/ps0N1DP6QY83wlhIKVFu2xZSpu/7sTFKs1ipZ9FqDr3m25umIUZbXMwwSuoBVPZjrdKEzDAMo95jiLqztssV64vVqJJdtTBjmkhRbnZDkoUcIoNPGLHQZfyQEJNorcHaRLNquHBrXLPUBsbhfsZmPkwpu7Z2Ul6yVuX1WuNwTVM0R8NEziJxHHq60iLQuobV5cVYsr12S1abtfJUkhoS0IXe971S0b1n8F1p1FxSqeuWx48fq4cQtDBp1S5Yrzcs2pbU98rkTEGBv6yFZMHHQqoSvXZZazFi2LNoOljKaIDbRtswphyIWVEQEQFjkGRJcVCpgr5nGDoO3YFu6Ig5EMkqwrxoePHiOULAEnCt8OhigbMJcirp98JMNcpKGcIAxQuKhNJoalaiHh+6P6qZUu7UK72MBxd98SweUsYaj8+neAUw9iydzl2FX22lFp2/U/nvr6Y3yOvGm2EsAIyUjlyKXSyXmoarcbdrys0q/pYvvSeqoQhn+fARLMzqpk5otKZlxThcs2CzvsQYg/ceYSDFnqpJoGnPSddQonY4z1kIPmr3kIK4h0Z3p41paZvl2HvyBEx9hWcx4RgTTmCMoXUTwShk7XxWmYc5Z8SakkVwJ4VqYg0xBy3OKxjEyMIshWVt2yIm02U1pNEP5KHD2oblcqnVuQi50c9lxNIsVgQ7EENpexi8GosQtNnSiO9YYknniQjGqWchhXKvt9sRs1f2rEAumhkhhFFsp3p01loVEEI9ECuG3faW436HcZmmcaxWDSKa+Yoxj16nXmM79hAdwYHEiWcR4in4WcOKNHocaZw7dR7Nw4LzkeKJ2zE9EjDm1HiMrxFOwg0Ac25g5nNn/g4/eJrFm2Es6iWri6BtmrJLMuIVxqK1B1GVsoahx4+77RyE1EsYQlDXt3gZuRSmGbG4tmZUtNy7gobV+GiGJZeYeeIa2BjBaXNiKQQpsu6kZNXKtLZRcdpiMHJKYKZeH+fZkPrZa1w6Tw9jdCHV3zEnYjnGOKsVo1DidB0iisFomft0vhgjoaZTrYYATbkOKrDrOfYdu91Oa27KnfFeazVa1yBGRgk8Abx36m3kKpYM4hzG2lICD26xpF0tsQgxerSXXLnrImCkdKZPhJQIBZNRYDbTpIaUoxq/GEgxklKkP+xJYWC9WrFeNlyslzijuE7OmUyA5BDryDmhvXsKfyfVazUt1kr3rgCi7uipNBuY369Jd3PqK3M2nwuo+sr5nh/Kn5TPxLxHyHScSffxlPmI+dXv91WNN8JYwGy3LBMIKHF8LMQk3QF9DPR9Vyb45EY2TXPi7sVC865jvlM1pV4jZeHY9RhRjkLfKz9B89ea085R9R5S1FYB6spO70XRnkgmY5dal+GsZdnqbj8MgwKWr7iZFays4yTdVnGWGfdiRM1n9SZ5pp0wktGyqj1lkzE1Le1cOWcBfsWUlOqCptGuYPvdgZ1sp1299H7d7Xaa4bDComlpW0cq1znGPGZoGmtxtiWUDERNwWqatXBejKi3V/EnMhL0+4ZokRS1/sVAkxtCCthkyaUvqyn329glm82K1VqbNot4aruEev00VFIAu4KOIEW4ZmYsRk4LVMxAwe/7HsDkKdbQ5TSzcs7aPHltMdzzcXL/X7Hms0gBmB8e6e81YwGMYFQfelIKo94jkghhII7MQ4Nzp8BVXXiZ0zixegug+W41QnmseYBEDL60LlQ3utaqTICpoS1AnynBZhx8cbdVZ8EitIWg1LqmAFCFup3DGAbMRw0LamyqhCcLpSw/pcRQBGc0W6KLr5bu64KYkXREGEKPS81kUEpT6JElGksrQJIa1fK6RbukM93Y42TZLFm1KzarNYdDh++OimOsl9oFPXq6ruN4PNL5oaSnDSl7YswEn0o6NxYpkaRYqDUYazFNOV5Agn6XNrdEhDh0RDS0nHuMqh5mefLkCTAoGatFQ5ycMZKUQi7F60taT2R8TRPnoip1msKeU/H1vdJ47R6ap3pcJdPNCFjZUGwUzAwXVPzidN7XtL1+UdVZed36mJLdZ0N+8Ev5jTEWoUy0pm2K3P9AjGHCIkQpwbWWQLOhdlwA9WbFsqgqEagalpCVxWmS7rqmVrKWUZsTjexQMfgM2aTSKVNojPLyDUIMnhBiaZRcGgg3LRcXF1ys1lhrCWHQ+gf3sEQ7TOnbMXszNmO+797WrImIlMIofexsowg/KIYQI6nQp02eql0b05TrODFGlT6s+IfNwmq1YrvdEkMmiNLGndFr6YNXwR07hXqHw4GXt7dst3vtXG+tMjuNw5iGIQY6P2CisnLbbHBO8QvDxDMAlHxmVKgn9GpsKuhccaP6+K0nT8gMIAPG1v8valHVsJBVy0OKbAG5BPdGQ41Z1F/FksbNxugiDg+xNKtxPinom7ANoMgdTPc7FQrHvMhtzGZUgd2soeZnlMw4+0h/j9SGUHf5ksGASLAGSTIW+BirBKWUVeNg7pLXhTZnfOpp87hz6SIrF7ScyzlHuygp0ugxZurhIbngHmNa1WDyMKJKigmoPL5tG9ZLVaZ+dHGpncEzpDLRcQ8DVPWzj6lSc1JPqiF9qb0IvqaSp65myZdUqZ0aE01GKQLNicfljBkl/Fxxs2sKGiAG7S7WHQdN/eWszYyPXanmLLcLxSi6TjGO7XbLbrcjxAExhqZZsFhtWK3acUGEkkXJ2ZTmTZlklLiV4V63tvq5Q6gGI4/GMgye9WYF4jQzZQWYsI5qLKrnVdkVlX+h/2lOtvnKF8klNVxDlnxGYBDuY07VY5nf03koUg3FdPzssRbqnL6Gh8OR0bvivncRzjzWH8R4I4yFGEOzWGKahoAQJZEtpGwgmTEFGoaeEDI5O6xpFFB0NS2HqlwNgzagGRehIWWLbRqaomG5WqrydbNssM4wDB3dcCT5HqGAbKHX+NpqvlsETF6UTt0RZxuazYJ/+B/6s7z33nss2oYUBqxJNG6hwrLBcbG4Ug5ACIQ44OLpJa8CvsYYyGZ0e40xZSJpR3YrXsueY8BklRS82e25vdvivWex3nB1pWK360drQgwYPJvVikXWfirGGFLMtK0amCzMFmNkuVrpgpaGw+HA/rDldrvjcDgQY2S9XuNa7f3Z9z277YH9fk9KRxaLBavLKxbtikXTsFysWZVmRJIiKQxkH5DGaigVgUGFjGLyxOhJ0ROD9iZNPpODqPcUMrnvSYcd8Xhg6XokdojNrNqsKmASaAq1nqShnMlWwesAg2jdSu2bS2lcVUfMmnY1lfkp6g3E8LB0/8n8vffUBHDms3RnmnkV5YnxNSIC6eFFb7Kc4BLnRw00J3/XKmryq1O+n3e8GcZCtD2eiBSAcaI5L0vq1FpLz9QPREROjIW1QkhhNBLTBRIWzYrGLVRDwbUsF5uRq5EkkrMlJgPZEUfhU6V3a2igu0Ct3kxJm/G8//77/NIv/RIXFxds72558enHWJOKKxvHGhY/6K7pvadxp7c5lUrOXFKNo9tanp+POdnMWa2d2e/33N7e4twtfd/z5MkTEpHVUhd1LShzVhdpW65zSFMvk6nnCKVATPUmKs5iYPQi4FAEZQoWkRKrRcvFesPFxYWWuBuDs1O/1iCqWZpipM9xvD+uKLGH6BWPin7EdaZa4ek61R8jWTMuJhWSmQ6DkI0UoecCNCbFEFJOIFYFcUXrimI+Pb/eNxVCrgVe6p1M87Smg0/vC2dzbgI5P8s4wUHGz3RODish9XjomW9Rvb5yrjALi16XRfk84/saCxH5z4B/Gvgk5/zz5bl/B/iXgU/LYf9Wzvl/KP/3F4F/CTV+/3rO+X/8vu9RSFkhBIbuOFZIigjr5XLkUSwWuuCnSTOBXllmaVZjZjdLWCyXtK1Sn+cSdzmnMbevC3G6werOmoms5SNhCCXrknjy7Cm/+Iu/yM///D/Ah9/7Dh8fDmy3W772zlN0g/CEs5DIe09s7xsLaxmNRR0555HFWv+ui7v+qPhLx+FwYBg8vuuJg2f38hZzdYkTw4BiF8ulKoS3rRqZ2E99Ya0YxCg3IGcNhKwxLNsF5kJYtnpvrm9e0ncenzLStKwXpZbHxdEQj2Fg8pAzvvXkCBTyHKVeJ4Sg4ZrRQq+kfpxybQo2EXLSMvycCDno32REEmI0tZoKDmERktQ+sDORYVSfNZK0crmCnzJxPgBi1vL3SCF1UYDK71srcnbPxscTZ+b0mHHWj6+ZG6OaAhU5D0VKer3yVM4+1jkD9avyJubjs3gW/znwHwO/cfb8f5hz/g/mT4jIzwH/HPBngK8B/7OI/Ex+WFJoHEbKLl8W5rz4SYHCuph1gsBMRaq058uSWCzasWBqyjroZHdtW+oBNKRISSdsP+xLpiFQJdSsCIEJT8g542NArBqPzfqSn/zmT/MLv/ALPH78mN/57d9id3tH3/csl8sCzlYBm0BTUpajYtNszElb8/HQzlT5FxWnePJkSYzqsRz2HVdXVzx58gQjhWhVsIrFeqUdyJIlkmmMNiLOUQu0pFxvawxxSEQfCN4TY8BKMRrLFW3bcjho9zFN2ZbdVDTsy7GUh4tgnJCzxfte+45AMRIen/SeGVe9mlNwLuZE7wcG35deHyrio9fVYysmI1FfK5rZyTkphpkzZEtUkgqQSZEis69eRcozDKte71L3kjOlE9k5rvF672K+UMco4IF7+CqgO+c8VUoXoHV8XQ1TCo38VXDmPaJXZm6hvtT4vsYi5/y/icg3P+P5fgX4r3LOPfD/isgfAP8I8H+87kVqGAze6+NqNACOaYrhYyFhTeCmIv8+BEXijYzA5Um44gTJiRx156jI+kjCSqotKXUhJe1wVjEPbVxkMBgOxyMffPD38/M///P89E9/wDAM7HY7bQZslXUaCq5Rd+lyHR9Mnc7rWc49i4e8ihqiqYdjtSHPlWIFV4+ueHL1mCdXl/zd735bOR5GQ7vdbkfKmbZtudpcjJNyJLVplE8OkRwiyat2hCkcCecca1NaEyDFEBaeiNHFSFlEZhQanpXcQ9m38yjB5w6Hcq8oNR4ZH5NyafzA0PeE2BVMqcfHQMypVPRoWlONRlJPIaknWa+Z8inm9R2VfVkPMyfXW9kdmp4Gc8KxuG8cHiZJTYu1nvt8ocrJc1P4+arXz85S5rzul6f/f95vRMuMZHr8FYwvg1n8ayLyLwD/F/Dnc84vga8Df2N2zHfKc/eGiPwq8KsA7UIb79QwIqU07oxDntiZo54kpzfPGEPwaSRUVe+kvk6zGnG0yiJTQ5amsaQkJcMyLdKaz7emIRlwNmnvChF+7ud+jl/4hV/kvffe4/d/93fY7XZ0XcdmvcSgxk6rJO2JjH51r+djzuWYx77nP6OxyEzehTgu1xvilWdr9trR/HhELi/42jvvMiRV9T70Hbv9vuzOHiPC0i1wSPEuCqAqU5/YpilAIJX7odemdE9VDyILi0LlDoSSkjY4qwSvSrDLAqSs7MqC/vsY2B1VeUzFc/R4HwL9EOj7nq7vCKFj8ApA+xDIRFUgK97EvNrTQOG91B9lh+ZkiMhkJequP1tEKWtxljaNqAYHOHk8/jl6GOdjXPSvCF/On6+Gor5urEXJ6QSAnZuGfP7hx/POvJFiXbKAYF/T5+yzjy9qLP4a8GvlI/0a8JeBf5GHgrT7plWfzPnXgV8H2Fxc5JEL0DSlkKykHefptFmxjx47VZ3iGTMV1VOp1GQNa2YNfKrOQtOwaIrydGCkkuekN8qaphSZgUjAh8R6dcE3f+qn+bEf/waXl5fc3Nxwc3Oj2YSlYiLOWFIB905SaGnS3qjjlH9xygKc/67fu1ZMGmNYtAuWS9XwjF7BzuuuR7zn537hz7BYr+iD56MXnzL4CTzsug7TClkMJCk8EhA3FXzlnEeAc055b5pGsaVSxFZL30V0aku5H+eFTTEHJZWh8zySyd4jMdPkRBY3Fr6FFNl3R7ruSIgdIR7p/UCMA2JyEeqZQgdroCrBQ1USq0bXkIoB12ZKqewZFknnS0hxhgmruC9U9PpQpCzYB0KM+vr5b/2/dGIsqi9aKmnGzxDPXmfGz1uub6miPjl3MRRfFRX8CxmLnPPH9bGI/CfAf1/+/A7wjdmhPwZ87/uer3xJ5xzNRqm7oxufZwzMseTYluyJ/u1DT9dP+EVKadypnHMsl8sTcLBtl2RUUWkhWnUavScMA5K1hD3azDAEbm52mv1oW1x7wU/9zM/wj/3j/wRP33rKx59+xG//9u8yHDuePH7MxWrN0HdAonWOQCLHScNiNFan1/JED/T8/0AxFF+OM02jQG+74GK9wYhl1S5YuiWffvopdzc3PP/wY34rRZ48e8rVk8e8/fgtfuz9ryHOcnt7y4ff+S7HQ8fglb9gxaiBW6toz5SRscgM++j7nqEI7Mzp5s6omlYfPc6o1xAH9WrcYmqeVD0TKOh+gQSMwJAiKfhRZLgLnj4FXQ/OYqWBVMIOE0mSMQWz0AUXyTFibUs0mRwSMRlVyUpCKszKJFltilUR5DriuGAL56HUDM3m+b17dz8MmYOWr1b+Pg9D6mtz1iwP1K6rE1/k7GVTxrUaNFsKH2fnTVmL1tIDhu+LjC9kLETk/Zzzh+XPfwb4rfL4vwP+CxH5KyjA+QHwNz/jOXVBV6IQheZbjEWMccQsqjfhnCn8BSm6DWbG+JuyEClpPxJl6RnIDSllcgrE1o3vrzhAiWtxeH/UcChknG25evyEn/77foZnz55hGsvhcORwOIyp34olRG/pS1xurQU7EaYeqguoBqMai/kONGlyKEg6iuOWa1SVpBprudxsFJxdLtmX0Ojm5ob3vv413vv611g3C+zVY5IPbG+3dPuDlpL7QEyJm9tbYt5MGaOciVlFi4dhYL/f6/Ejo1K/03rRalVsSgwhkn1WrgqRhSwmIV8RZWmK4MSRg+pk1lAlCyUrogYnQ2mh6JDYIjGccQ10MyGrToemStPMq5jS0XUh5VysUzpNN1TylHolJfNA0cWgmIEznOJVUECmZFz4DFmJucGZPzwBOEt4OPca5iSwsYXl9H6pvMb7WLCXL0/a+iyp0/8S+GXgmYh8B/i3gV8WkX8QtXXfAv4VgJzz3xGR/wb4bSAA/+r3y4RAze2XBZInQ2ELil6zG8d0oKakUoLeD0p4mi3AkeVWjEpGMx21AYQSX6a4PEav8m9GaBYLXGkoHEOvDM9mSRd7Ykw8fftdfuInvsliuR51B6qnIiI4K6wXS3ypjiVlFm1LNIyAamWk1jGlcU8rFWvmo+IFozE9q5MgQQ668y/bhZZvh0Dc+jEsO15d0e8PJB+4vLzk6+9/jePlgbu7O+7udtzeat+NEODlzc1o+DJqoKsMQO8HzSJY3fOSV4D5OHhyjkU/UtPYoTREGrwno+QzAfJYC1OAZ1GRnWym3VJ3xUJBb7SXCDGQvNWMSwH5ctIu95K190vKEcmmpEr13kesGqEa1jEDCWa6lTV1SqnL0XtSVNQ4zYRM8+yhMERn9Pzx5xm1Vy95kvzX95szU/O9s1a8iPK5a2ltjBHbuK+khP2zZEP++Qee/k9fc/xfAv7S5/kQIp1ZB0cAACAASURBVAVQy5kUToG9CVmXsR9mXUSmtOpTZmLEl36pWgQ2e4OUC9W4utfaH7NpVEFKTKZtF7TtkkW7ZL8/8vx4hx9i2ckjxlneffdd3v/6N/Q9cxgrNk2KrNrFuCOrkdO8v9LN9X1DCAxyaiyqFzV9tin7IzlrVetYzDalcufYghLUDK11mAzHkhGKJQIejh23z6/VCL77Dk+fPWOz2ZRwboVxDuMcx6Pn+fNPOA59CY1mn7VmqPLUl7UK6wxFsQtJGCdj5kNK9kZmfVPVwOk9cq0W20nW14oIkYxPkWwE6xxNA2KCsnlBsx5ZS9rJCclBiUw5TCmD8yxGsQ2psM7GbubnSy6bcW2fwqanIYecGZDp/s0ff36coBqoOuLsPc2JITqtMj39bJaUarMuS9tafIj3UvZfZLwhDM7ZF5Y4koNijJhCzqrgI0zsztV6fZZqnS5gSnaGU0B15cSAMAM4l0pNXixWNM1ilK27ubnBh6SaF2JZry545733ee+99/TzBG1Q1LgF2Q1cXl5ipIjLoGFDOOs5oWzG+zwLmOoSTjIgZbc4B0bnBoJCMkomjyXfV1dXDL4fPYvD3Za+6wghsL/bKh9ksaJdLrh49IjVZsM777zD9z78lLvdrR53PNB1h/H9QunIntLkDXmvYOnKtSQyxoBbKJ8lFe3UbKHNDSLtieaIGqpSO1LqOmo/1phrqClaTCmqzRGJhJRoapiRtDE1xFk+tAKdk4Aw1GtaKfT3u9nnXB17M1u0ZpaSnIOU83CkuhrTedRY3QczP8t4UOymeDgpZ+3Ze5YlIxvEKYg/D3WtVXX23XaP9z+EMOSHM2SqxlM640kmoV64OXsRGFOl812k/tTdz5ipaEzMlHZcLBas2gWXl5eslhvImaHvud3uuL5+WUKGgDGRpl1ydXXF+++/z1vP3tb4PCSq4lQcSsZlNqG01H4KqeY3eD7UyFVMYsqOiMxEbCrYO8M3YtRqVinnb63gnfIlvGTW67UyXwev4jRdD8B+t+PTjz9hsVyxubxgc3lFu1zQLFqePHvKN7JnGAZubm44HHYMw8Bxt1cQuBR2jT1OSwOj5x9/wvF4JElitVrRLhuc0+rRp8/eGq+/oxkNRdM0NMuFpmFLtegoMVBCBOO0N4wS5s40O2q9d93d5TwLkQqoqQzQuojrqGDm9Lf2gLW5sELRTMtDmY3XGYDzOft9MYvzc1MzdlA3kZN0LareJTUUySBGmZ0qjqRcllqCfzgcCmj8J8izqAVVOEcwqVQpptG1N8awXq+BafENQ38Chlaqt3OOvj9Sy7GttZgxn+9K16qGxliWyyWNc2y3W148f8nt7Zab213R+1QxXBFhs9nw9tvvcnFxQQwJRLGU1WqF73RRLVpzgkGMuIOdYQxnIxb5Ov1Op+y+hyZlStpJvRoQayzG6YQyxhBNwB8H/V7W4a3ThZw0lLIIx+NRZfDIxCwsg9ZzLNcbvvmTPwk5c3d3R98f2e12fPrpp2p4MwxDKEJBPYe9Us0P252Cn3Eo2qYNtlWKedO2NG2LaxqapsUgI52/Er5MUi9qDOFm2SOMht8V+qqGAWOQPDVD4uxanfNU7pGcCi4y/3u+wOvpxurT+T154P2m8xRD9Aq5bbln1Kb3B134AJiJ7zFtlrWtROIE/jSGcCaBUNfI3d0d2+32T46xMGJ4vH5UhG4igx1KEx11BauXsGg3hU1Zd1g1KEMc6LoDPvSlICliC9FLROtLFo124F4sllxstE4ihswf//Efs73RC3o89qWc2ICJtAvFUR5dbfjmT36Dn/rx98m+Y9k+QlLL5mLFW2+9RRwONI3qWXTbHTYa2tBgbEuDY28s2h3NEs/k1g5lYSNWGyORiSFgROglF/3RFolKKnPW0hgLxmkvUin8RAsRT8gBt2wwrUWiei7r1SW1BLuWqIOQtp7bm0/4pChQSbvg2bNnLFetdofHYpoly2dvj95B33Vst1tub7aYwSPOsFoJrbtks9nw5NEVq4sNm82G5WZNs16qi1yzOsUYWITVUunVoddamsNxT7/fMvQ7Li8XrDZLIonb2x2fvNxyc/uSlBJPHy9YrBLWRlojNK6lEYP02jqAPKjuhlgyLSm1xKSeJRFyKTiccZ5IrgCto/sRgTgCnCdhR93hz4z/3NjkV6QqFRe9j3+M71qrVdMUPtXjZKbbkmUSgTbZ4KQtWEWVJITDoePjT67Z7Q6k+PnCoYfGG2EsaupRqb9qAaVoSYCZ+oTIFPMq0FlSSskRwkCu/S1IRYFKd/bLzYZF0xbNTfAh0Xee4/HI8+cvuL29xXfKz2gWpVFxzmOn7eVyyeXl5ejZ1G5o7WLB5dUjtjdLrNGQpw/aRUs9HIuR15cI19RuJTjV63E+VIrfjKQvM8+ilO3spHKyCMZa2yALi0gR9PF+pDEPMRBCGsv6/XaPHwbathbbFQ5IVKwo5czxeOTu7o7dbsfh0KkcQIZVu2Cz1F6j68WycEFalus1sbyfMdpWcgSoTcnWDD2744F9d+Q49PS959mzt1guFnT9nr733N1sefHimpgCJm/YeMtymaDJOFptfC0K8ElKJ+IzCno73a0L2JzNqbhQKn1DKkZRKdVJ4kl4W6/568IRnaN2vO/nYfKrlN7P18Sr3kPODJiGrFa5FklTytFHDn1Xrqk/ExD+YuONMRY1XGiaIpXHBBIpTmERUXXr2pPTNQWfMLqgXXBoybIai6YI/64XSwRGCbjj8aB6Ddsd2+1OSV9G8/l1YqWciGiOWoldK42xi+HyQTMqV48v+fSjhWo2kEupvGCaSXFLOFWnmo956fXJzpQzrmRDsPUaTRR2EZl4AbPJK6JpyD4NSuUuamJtZbJaQzcEfOwLq1FwTaO/bQYf6b2yMxOx1M8MZRH3dH1f9E/DCKRdXVzSNg0XFxesVysWbcvCNbNmyVMq2zpHW/RSw9Bz7Dr2uwPbO9XNCF7v22Kh5LDjsePm5o6bmztub3fkDNYkBm/YrC1hZSFZpM20GExOhKwamykBEVKUieRUVdDNaefxXBXKSiPuGg44O83P+cKt2NH879mMhlfgHfePPf1/k6b3OTcTZsZCzmgWT/kXppQqKNjpw1CM+o5hCAQfeSAC/tzjjTAWwJjaMUYnmCpi1R1JJ3zjFjPdzOk1kYxzJWuSIEbFSStott1uCd6Pik6Hw17LuruhyO/VANUQYsA5Q0XFBcHWJr+tVrV2fkBSYr1ec3V1VdKciRA8pnE0KJ+AXLn5p30vz8ercIrRCFAMZvGs1EhMClhSjq3CORWYq1XSVcjFGME1LdkHQlGeykYwjcMItChoPJSy/Rg9fdCqz94PbA97ff5sZ3y03qhHsV4X8d8GV3CKtm1JZpL2G1sqAjvv2R2P7I8HDl2vXd3aRkV2mhX7wy0vXt5y/eIld3c7jgctOLvbDngPfQ9haJBosKsG2zpyNqphkYSUhCEoMemYNPwyYaKozzGLbkiliVEROqrGwmhqv/J7Rm8ulU73o4GfjIC+Np5co/k9feg+P/T7/HWvOlfOGe9DyZxF+s6PoeLx2KsQU7L3zvl5xxthLGrhWAiBtl2WiaVIeAX/nG0xrVEh2LKrDX4/Mx4l3RryqFFR063dfkfwvjTY6UdKOEao/U9rOq3yNrTvRKklKAuzbVuwhmEYWLaG1cWGi0ePcG2DP6rK08Y5JS4ZQ5y9z6uMxSmodipGY1BG6wj8Fen5es1iUb8CIKYxa0Cobraqb+l/qxUV47Q83QiIwZb3zAL4knWIiRSiNhQKg5K+MkjSBcUsnZtzprGORdPSWDdRlEs6O5dQUDMbpVo2q6Hves/h2LPvAyFpQ6mLiwsuLzdghf3Rc3uz5257pOu10M8YGIbCm8ggOeAk4Ii00mhbBGlIkvAh0h0j+z6zD72yRWs4YfJIwwc47PtZtk29DyeGMPPY5pyYyZubCFp5JG5NhuV8oxizWieToPzOebxf8w2kcjjm/xQXKZ63VHBcyYrDEDjsO3a7A0MfsNYx52980fFGGIv5hazeQu3J4IpKthHtzA2TZ9FKq+m7odeioxDGblu73Q4ftM6gPxxVOLfcqFTUmE0pXjKjMnLNrDgy2qxHgpAiowZm/ZzGOIyzLNcbLq8e8aI/qkpT2f3bxYJBhKHritHJ1M5n8zHHLPS9J2NRr81YDIcphq3Qw31Q/MIYJGkneD3pnOxVxZBVv9L3XaHIV6UsSsiXsWPV7yQGZIuC+uA9OQZ8mgrLKNTp9XLFarGkbQqXwjmatoVm1vjIzPRJBjXchyFyGCL9EBDXcHlxyeXlJW3bst3dcnu35/Zuz+HoiVE7pKdsCLFUsOoHR2JP8o5WHI0TxGaGmDgcAte3ge0+sR2K9pbMRITctIBubvfl2utmYYs0gbH+JAyZG/waWs1DlPHcdvr7/s/pvJ/OKUiaewz1uMrq1PoWpHJy6u1Wwx9iousGtrsD2/2BYzeor5ngdX1MPut4I4yFc4633nqLruvwvqC5xo0WGygCsVv63vPy5Uuur6/ph51WUfqhaEGmMcU27riFQCsjTTyPKaiUJ6XvCqaCItLG2JI20xjWp0zXe5pFS7tYIVYIMXPx6BE/9uPfZOiOHO7AFK2FpmmU8+ADttEK1Ha5wLhTd7AbepqcsI0Dr266ccppkDxhGmJUHbsW03V9j0mZLEW0t/auSBkpximG0sZxsSyGNJTf/RimpL7yJXpyyKzaBdI6rBVMEEXRk2L72bWa0iaBmSp6aypa06YL1hcb7KIlGLBNA0bG8nSfIrv9juvraz69vSMMgeSWmkl59nYR2DnwW7/3h3zrW99SRunxSAiGyArJQj94BM9eoN3BtvE8Wh/I3rFaG3BwHHqudwMffdrxycvM0W/VG6FkPg3Tjg787b/zB1PPWyx29CbSyaKe/8wB6WowxlqextwzMpWXAxPfZ6T0j+8dxw1jAvZP378+rvPcOYfvBo7HPTc3N7y8eTG2czC2Yei1veSXXqdf+gxf0ahuVy19TlmLf9SABPb7PS+vb8f6iq7ryGjqtJJudBfWm6HgU9WxPFWjmkue5VHnshR7xYyMO7su0CEG/KAVrWSjhWHGkI3g2pb1xYblekN3PGJiBFNSZ6aU3M8Yf+ehyLxE/R5QWZzVlHNh9pUKwurKFhIOqEdtChXapNLasKm7+kRmG4FWBTr0WodICsqcTKVTuWpDRO3ZKVr56oxFbBq1KY3oDmwbd/KD1Wtka8WjVEOdRrEgrUVJuFYxjov1BtNoU6a7uzs++vATPvn4OS/vbk/i9UQi4vRK5EgQ8EDfJbb7jojFLQxdTAxB6KNiWHOaQRZUL2d2K4bieRgi4BUYzmf8Dk4X7HxO3fMezEQirGPOBZrfi/m5G/ewsTg3TvPnnHOkMJRru+V4UH3UnCj4W2mGfU/m9/ONN8JYeO/56KOP6Pue/V6LsHwhZR2P/bgb7nb7E4CzglBITS3qTRKRInhTG75UgksBAAVVgK43HaMLEFXXtrPnUmJslnPsB5QZJ+PObaxltblkffGIu5uXSpZJEw7StktM6sfveg5eTfJ797Mi9fgpfi2Lu4RRKas6lHJHBWyhgIN2KC80YUFDLucm0Hf8SbMUYwFDMTLNK9HrppPztCZFJ7yGa8ZppiUbIUop7LRCyAlT4uXee7Z3d2PhGk3LatGyXq9ZLtcQEzc3N3z88cd8/PHHXF9fc+g7nCu1QyWrkkTrZkQofAcYep0rxjpao7hRSpCyJeYwxvcVMNZ5MF3nqGJbxJHoeb6w8tnvCfKY39K5AVI8Y/63nPakrZvCDJ8w+BNDcO6xnP+M7FhJxOjHNHgM+vly2XS/ivFGGIu+7/mjP/oj1ZI8dOoWF4BSEd7p2Ao4jvRwyoSJ93dn3YznKaxiwbNhvOm1eChLKfiak2nUeFSgtO98aTqcyAFSGrAZFqsV64sNzmkXeBGIKZaGPA0GP55xZKqWMReXqXUg8zRrFayVSkGexbsicuJKa0EWGm9ji3aDkI3iETVtWHGheh1todjXc8ao23HFR5DSS9Po6qwpvDqZszUo5yeTcyrtB/V1KSVtcxgj+/2em5cv2e12RB9YbzZsVguWi4YUe27utnz04ff47ne+x257S8oBZ6brNH5Poxoc1gg2R0hKdQ4hE6PS7GuImZIKAdfQUxdvOqk4hbLxpBmeMAKN9yuap8k4wxc4xRkeHpkYIsY8nNnQNGj1ZLj325wB5fWxc47GTanUJIAtVTIxat+c132szzjeGGPx7W9/G5gorWlmbUdqc2Gm1fRWbWbLK1xDfaJiEWeS6CKaATEFyRbG48imFEwpuJRSpu819BGU+ZlFtSRbZ2nbls3mksVqrRkEk5BkyKLpU+fcPeLV+PHyVDRXb3wFOOP8/6yZzJgRpJDVkCIPn3ShZqARO4nMiFZ11grUXAvXoHRgt0jbkpwDa8kxEmMgJl8KtdRri6KZDZAiwz+5yql4FMmKOiUCtryfD4EhBo7HI9ubW+5ub4mDp7GOy9WCdesgBba3t3z80Ud899vf4cPvfY/+uKNxGurEoP1kQaUMDBoqNaJelUkZm0FSJodIDJDEQkrKaowULZOaWlbPSWaU7JQovXHvF5nN75W+/ovH/yknUlV8O2NSvO68Ou91w9DPMn8+sliU0ghXDYp6xX6IJ4D5lxlvhLHIWRe+7lSpVMtNKUJTUqhV/SqVSVAZmarrWBlvduZhzHYFlNmpxqWkJmcA6liVOuMAS+kdEkKZ7NsdMSZ16yzEUECrxYrles1qtWK/25aFrKsm5zT2z3ioNmTOSK2KWdW1rEIwIUWyV0zCGIOtrqm1ugBiTWMqKBqNMjarYdJwBUJO+CFos+fyUUSk0MctYh0xD3ipndFkDDWMs5iond2lZjlcaRhUStCdc8rZcKoiTlJ25uGg2hm72zv6rmPhlHTV2Ez0R2XSfvIxH3/4XZ5/8l1ur18Qw0DTWBU0yol6K4WMpKheBQmblU7VOGHpjOoMVZyhhBzj7owtRWLFaMx7J+ZSlVpCPVPmQXrtAn54g3qVsTkfo79bN7ucRw4LnHkXopIH9f3ymA1S7VAXwVqlz9eSiBpK6Vr4TB/pteONMBbWGi4uLgoAVtiBeQIl52rdwFjxOBqUWOO+6WKqu18MBFCrEyvgV0e17mPc+ABoVXt6brfa/SvRsrAtPkYwFicZ5xraZslt2aGapkVswg8Dzk3vce5ZzI0FnAr41lGfM6Lfqxo5Ed1ls9SmegqKeu8JXl3tXBq6ptm1GWPixEkHdkp5fVsMRyoKVPVz0hRtTVeaNmuzVayowbZtg2sbkiiPwofEvjtwt71jt9UyeSMyErhif2Rf1Lw+/vBDrj95TrfbkUPPqlEdECFhGkvjCgCbNBWci/6yMbBwjs3SsVk7bBtIRlW2xOgMsILiKTkXGvccE6oPZuDhCQbx6oX/Oibm5xnz483c2yhztupxMBqLs3Cn1DJhqteXyVFng3GZGBJfQeb0zTAWKWe64ag30xTG5Az8GZHwmdV1zhGqIEqqC0D/rBkQ/Vuw5pS3MArUikBltqXimhtLignXKjJvW1Xpur6+5vnHH7K7fcl7bz1RUFEactDfbbPmydN3+N63v4WxGZaqaxl6j8tGqxAdJ0Qg0L9jzjgEiZnQDcQsNFlwbkEsu7OCWYoh5JhZNI0Cl8aowRMgW1LIpNgTvIZMFZOoHldTsIZsDSFDSJlQCvKir4bWsGxaggSGkIgxFAKbKjEJWvMSM6SQCKuEWWT6NnIk40Ni6D0+Jra3O7pDR45wsdmwWTUs2wZjA9/9g9/n+Scfsb2+4bjbMhx2LELkaQN+AX2EIIAkQs70gxKynIBJuj4a41g3jqu14/GjhJiEF0s8QuwC0VcP8Yxqf+55jhYilwxZurd5/DDGPU9mNv9PkdTJkGnGaQHGgWkUvDKBFHukqSX/BvpT4aXPO94IY6E7vxk9gNGKjmGCjMfVG/jV4Lv3xznltk4yX+jilWlau5VFMs5aLi4u6C4udHFiFVCkeBK5yvine5+7GsBs8rhzKDCXxu87gl9zULe4liklxSyyIc87ijmHMVW5a+qDWXfXigHNAWHVJVUBGim4kYhmO1KMJ6CgaiboHIxZwyexhoTBB0/fe7pBmyfnnGlbx3q1pG0EH3r67YEXL15wd3fHUDYKJa1FUobGWbAJh6g8f8wkmzAtDJ5SVXqayjTGkI0rnsGUNVNdzYdChYfl/H8Ux3madu5pa7Nxy2H/J8BYVOLTKReiPj/HFQDmwqRf7E5nYXQ18/nZC+o/r39IKdJ1R25ubrSIKifsjGtvrWW9vuCiGovy+UJUJqQVSxZDEvNgw5dUFqhSqfWAkFQyLhLHwjqT8+heiyj4R1b2pjpRtZCsdBhzjqZZjABXZYtWjEPQrIk2IY+4jFbv5kwInpC0xSFStGaoknnF4AiIUSGWirnErGnm/eHA8dABhuVywapxLBpDDB031y+4fvmc588/od/vMCnjnGClxQAmBg1+SotCooK3rSl4dRHGMokCyAopFYavrcYva31ILKK9Y2HX1PbyR8VQzL3rOuZ/T4SuqS3nuAlknQfneh5fZLwhxgKqYTg3GDUFOk8XjRfvSygWT9kPNRhjLVlOWCmFbKLszhhzUcq+43DoRost2MKLMDhnlMloNWc1UdeVzZfLLn7uZv7Ff+8/+sLf4U9HGVu06+4ffbbDv7zA3Js4pj4pqhg0bbRGNHv2ZceXP8NXNbIZf2Tse1Uo19nc+10BqS/9tg/FM4YxzVbBRx8Du+2e7XZbdtE8Aq29116fi8WKRbsCUMKWcWN3eFdTjfLmXPI/HT864xw0Pd1UqwzlaYZHmIrizoH1LzLekJlbuRAqGlIfw1RNVx/Pn/+iQyVdzdiRuvasqD/1mJFhJ5qWPB6P3N7cjWlaUD6GCuNqpmKxXhFjHsWFndMY2qAGwxjDb/yVf/cLf/Y/HV/9kB8RAz5nep7/HeOkW8sDRuLzZmgeGm9MGDLPWZ9fkIeO+XJjloY9B5pF294rH0MrEUABpOPxyPX1NZUl56q+RFRi2cI5rq6ecPviOcMQaXLDXOXZYsAogPnX//KvqQZmVDn9/fFY+m6gmhhNQ7NQzKFpmrGXaxXMXTYLHq0ucaYZpfZsqZ61iZER6ooIjTHqjg6DFhzlHLU4LFeBm0Dqo9Laj3t8GFSSPxcqOsoEnIdssRjNYw4McRg/v9aFaKHZ7fUtL6+fc/P8Y25vXjB0O6zJNK3lsoFGtD+GTQmT8hhahgKoZiNjLD5NipYYE/0Q6PwAkmlbw5O3V7jWYtySgxeeX/d8+OmBm23gZThNG1fq+I/imIPv9W81FA3Kjambq5twqj8pqdM8lzMrlOKRa1DAQq1vMKcU589wr8/Tr/Wc9fFYMyDTZIo54KzFuQY/dFgDbWM5HA783u/9Hl1/ZL15i9APLJZL/KCtAJfLlp/64AMg8dH3vkN/PLA7dlwt25GhSdIQx4rgxBCLwfExIjGMnb2OfcfRZxaLgcuLK4wztNJqqXnQStsw3LBerFk0LYM4rNVeJktxmgJOaVbyr02QB9+Tg7L6rBNyttOEMgoMtm0LkslDJqaIWKvl8AtNI2cMPgb2exUqvstaz9AuG8RZ/HEghAN3dzv+8Pf/H7Yvr0mxp7XgbMRYQ/KZaDK2CNPagv3U+2RzBlOTYrGUjLsS0kWyWEJ0Km6TYkE7B8gNpIF1u+TttzYcu0B3GGhxY7uILDJ2XDdG6fvjfJktKlMA3R/ueMjLedWnmG2qGMXZyOSkHq+uoaqp8eU/2RthLOA+4jsHO88Lq76yIXZKx1JRZai075yrBoai6F1/5HDcj3UK2UxZgKZ1hBRZX17w9Nk77Pf70smrLx28tLqzvo8kpf5aY0rtgsGUzAYouzTmoGI+3mtWwyiQGjP40imsNi1yJuJoVQaQade0aSamElUwRzMEgVRSqN5rRW0uxXvza17l/60tWhRFfKgf+oLXeLIVTFEX84OGa/vjgZvr27HDvKC1MgJYSUg25BRIWEyapWKL0Y6Fvi0y59AUtSspdRBkXGYkjkkM2GxRemrGmsyqFZYLyLswpr5MHjmcr5hPP1oeh8gpcXEqSoSaPZSv4Cu9QcZCJfE1ftS06CiuOuMWnIYi1QqfC6jOzWjxnU9Ye1XFqMyfMT07b/hTL3jAikBKdN2B/X5L3x+JUYvDIlq3kUXwIbFZX/DWu29zOO449gf6l55DN2CMYdkudbdKk0iucjCExjQqIyiq/QDq7cSooYHBYkvDpRqLDmngOBzxKeLE4JxK8dvmgtqBXqXk/KiNAZBiQJLgYjEWwRfhXk+ahRLiLNp7UdPJuYjvHPuOQ9fR9171Oi5X5JTZFyOx36uor8rhbUlDxKmeLJK1biSaiScSEWUbltRwLfiqSgKC6nZUyo0I2o2uptDFkLM2HJKccNX7dJaL9YLNeg+7qT2wigXFcTGNO3Q2VRTgC87iH9QoNUuzUWlI8+rTubGorF8RwVnzlWRD3gxjcYZTzA3COU5x8ruGGF/irfX81UBNIUvOGVKAolNZO3V33YHjcc8wdIXw1NK0RftAQJzl0dVjnr33PvvjgSFEhu3LUZtSQ5FJrWkYhnJD7YzmncgF48g5E4bIIIOSrGYVnxoyJQgDUWzhf0RsmLwJyXVCWUytjSky89Goox0ShLK711i+am0mowX7gQzBcxh6tvuj6nTmRJRM6xzd8cChO3J3t2W/33P9QgWKhj7gmOocYlT7E3wktRTtDwCld+cSpinOPWl6YERbJRjUcJTvYozgtE+X9sUVQ2OEZLSo7WKz5HKzpDFdWTyM3oqRGVXrLLv2gyL9fZVjpO0b7bpX520u80i5NBZpqkTDlxtvhrEYsyH1N6hnIbPH09G6oGoKdaLpTrf4zLO499x06SUVjQAAIABJREFUnoe4/3OPwxgpJd+iO3m359jtGWLPwq7IJmnbw1KhmcTQrJe89c7bHLojfQzc9UeMdfiku6dkra5dNnZscWhFS5dNZrzZ2TjFc0IkDJ6BfmqkJIZgpeTVdYGFlIg58KLrWK83WJk6oZmiMSq5Vm5qAZKIMiQjGZwl+KT9S4eBWOT1cvHOjv3Aru/Z9UdSzljrSKICRbd3W3wYOHRHDseO2+0d+72W8GdLASkzIlrEVqvfU5YZMdQokJrANjI6hFEAScRZ2BjL/XbGjHuuNdCKxZpGSXDWsVnB5cUS51SlPOYHQtmvKA3/wxzqleVRs0LV1DIkM5LkdLNQYPxPjmcBPGQsJgDnPMyo3oX6pRWs+qzGwhQgSHdZIRdMYnyFZKwUVXGmndz7I7vdlkNRuW7bSIymtI0LYCwxZ1rbsL644MnTp3TDQPf8+Sg0I6ZM+JTISY9VvQqDFS1K029ewMXyPb2PiHgsghSXU6tZ81itWnubOlnQpgXiWlLOeD8Qg16zxioACiBloSqPRD2nIQb66AlZl6OxyjodhoHt8cDheKTzHrGWTKaPgXDwXF9fk8js9/uihHUgaBeDkY2bxRTpOkrNSsAaO2pTGBQAThJJWUgyLwLUcMSTSvakKHGj+h1SmLKSTdHRUq+kbVo2mzXLtnSVD6WnSpkylfT35oxJDvJ8PERajDGTC7U9FY9RmDwLdQgj8hWAFm+QsZjGvB7ioXGvKOgLjBo2zN/z5HHWvqGjGleOEBP7w7aAl1N/zoqyxxiJTkvBnTFcPHrEOzmR7l7y4sULjrdbmoVWjYao6tnOOSQq5pDEkIt+po9VCg2IpeXB4BkyY2sCHdrfxMdIX3qPLpzh7rDHOW0AVBsamwwYwdHo9ylfOcZI9B6fe3zfE0LUik8jhByJIbI77Lnbbel9oI9BXf2sjWx8SOyPB1YrbYMYEWIE51C3gtLDAwVo20Y1PmtjJil0f1UaaHBGGHIYfUURZV3mnFTJGq1+NUX6LlVt0phAYvldBIcbYb1acHG5Li0OOqocpd7yuUf6ozUqbmGtFIOh2ivkqXL5devo8443w1gI975Q/ft1ufCqOZlrvqt6HvPQQrSEez4f5oSrcaKV9zNGtTUWzaSSpfiAaltIyrx4ec1+f+Cdd9/jbn8Al1Rot2nog8dkp9JyiwuevX/Jk3fe4tvf+mP+9v/+NzncbFk7x6PlGtc05BDp+8DSOKwxHIaeICqCE30pDXeli3xIDGEgZ82wVFEd4yyryw3teknf99ze7Pnu9XNqBzPlamjHN5czq8KfIEdEVE1JGwl5YhhUqaxXxbK+7/GhZD4GzZbYpiWYTN/1HI+eHHsuL6/45k//FBebR/zu7/8ed9sjx+OelCO2MeTW4nPCNS3NZlnqTHqGAjJ6hKaI6uRsENqJc1EMmzMOZwzeZbAOcU7vS0wapvmEiY6mBxsS1iSaGHmM8OxqpSrgsWffa/5ElTAqsK0z480xG/dBzZNSdsOY/taq4iL0M8PwtCSiGNCv4BO9GcZi9k3mXsMJ2PjQyx4wMOfp11f933gMjM1maiXn/PixDDhC27YqDXf9UhsCHw5jJWjtIWpySZFaivKStmZ8+vQpT5484TYk8CoZaI1VaX0pbrkIC9eMgje1x2tNhdlCGMs5Q0wEwnh9vNfsjLWWy8tLOq+4gyp3R4zpsFab/vRGyDkW3WHV6xh67fMaw1D6qxx1AQ4DIQ5qtGd9S9RbUY9nuWx59OgxH3zwAUYc3/ned/WalQTGaPiBkCJDH0AS60WplsSAWCJmpmgey73QDBUma/ovCs7Uzm+qZlYl/KPvJ3c8Z4IEQsqlwbV+Dj02EhMK9H4VBIQfyPiMYcNZn5FcMkrqkcmDc/6LjjfDWJTxKj7F5zEYD53r/NiTV5x1yda0qoJHKlBrRoZcu1yw3x95/vw5+/2e4/HIZnOJKyrXTgxZNJNgx25VCefgyZMnPH37Gf7QsX95y647smpaXBG8FTJOhOQcTU5a1Vm6qlXPR0QgarNedTO1DUCO84VgWV20PAqXHI8d3XEoKU79GQYtGZcUdVcSw1BaE8acIOWx30ouVbMKpqlcAjADzxRg22w2vP/++/zsz/4sL2/uxnDEGAMlRelDhHk1pAh9Y3Biizygw5bUbAqJGDW8qNkhALHl+4ZE9InlYkGDUwVrG4vMIpAtCa9d1zDaLqJzyiV5gLvzozbqR58MBCeUg3qQEZWNNON3/RNRon6aLj33Al4Xc72udPezv+9D56ihiYXS89N67Z364sUL9tudCs2UXPbY7FeM8gCquGoW/OBZLRreevaMw92O43bH9u6A957L1VqZSKVS1WZojcU5IZdzRxNprFNOhwgSI0OeRGuIcvIZovcsl8vSM3TgcOwZhjB6QHHwSErkkAmAL5yPoTR0jsEXdF1oCmtSRAhpkgbMMumFPn36lPe+/jXeffddbm63pbcIuLYl+l5l8YoWv8oSqnbFMVhsNrikcnhjOXo09ENPDp6a+AK9FdYmJGRioz09lo1mWkBDxCQJTyAmQ+8jMQk+ZY7HSN8PDEMiJkro+vq58v8P7vnZPIrKUQEQccxbFpy0GihY7leR7/m+xkJEvgH8BvAe+k1+Pef8V0XkLeC/Br4JfAv4Z3POL0VX2l8F/ingAPy5nPPf+j5vMrn7M0m5udjLKz7bK/9+nfExMpdhB21deKZ9OAtH6s9ut+Pq6oq7lze8fPmSEAeGrmfZLog+QMo0Tj2MtmlxVrGGlD0pweO3ntIfj+xu77Tvan8kkVm6htZZZW+mjMuCGIcXDS2cYSxGo8jJOQODD0oTF8G1jWYzho6IsGhXONeAGMQY2jaWrIontoPStqNmT1LjWEA5RyYaS0wK4FqZJiB+vjMZalvGr3/96/z4j/84m82mNJ4+TvfAGjVKlWgVIUukRbjttam1SNY6G7QZQ46JoZ818y1AXlN62HaofV1FrT4eF4615KA6lkPMdCEp2zUJISbtGh/rcjQFH3ntzHzjhswmZ/3eMWrWrGJrlW2rnt0PF+AMwJ/POf8tEbkE/m8R+Z+APwf8Lznnf19E/gLwF4B/E/gngQ/Kzz8K/LXy+7VjJJRUXoC537X6da+d/56fb/76BzGLalROXpeKxZi0PY0x+K5nuVyy3W41u7E/sHDL0cIbBGk0m1ENkgoOq3u9XK958vRtdl/bsu+O3F2/ZNdr28WnV48xBKIG11iExmohkKf0BTEGV65Pqtcnq6JV9IGEYhfZ2AJuxrGJUhXAsbYlOasehq/9VTT8qZkdZVnODXjAxzB6L6eduBxvv/cu77zzDhntVN+Vkv3aO0WbQ0fEaOPe4CER8D3YAk5rc8aivVDJRPW+R43DgwGXBZczxiRWPtINSV9X7tGQPYNXQ9GFTMiGQKmBSdr0KHOaCftRHBO2pqrfzroxnd40pVucmXrSyldgL76vscg5fwh8WB5vReR3gK8DvwL8cjnsrwP/K2osfgX4jawr9W+IyGMReb+c57XjHNw8f+6LjM/8+myoBHo1Dupqh9LQR1yDtdqc9+5uy/OPP+H6+ponj58SfcA0DblI0099QJTCbUXZkbZxbK4e8bVvfhOM8L2/+x2ef/Tx2DRITOlZ6gOpKnznhFNJKjUZM39y4ZSgVZsyhVrbYaDniPeqkBSzEqH0WmhBWcphnEiVAFfDFHLWnp+2go2m4CNmZKGKSAlzFrz99tsqK9h19H2vYsFoLw+EUqSn8gMB7ZRlkiGURjjKuUqF/KaktbaxRWE7EfKgqdhCxYkOMo4+Zg5dD8mydCpWmxjooucwJLpAMbSOIWoPlhp0ZjRRMI9E5vbjzXI4zkMT9cZy5Z8Uo62hh0P7BNuRTDdqtH7J8bkwCxH5JvBngf8TeLcagJzzhyLyTjns68C3Zy/7TnnutcbinOJdd6a51/BZPIX5/7/quXOPZXweizGqT7FYLHRHHTQrsb5YkXNmu93SdwO/+Zu/yU/8xE/wwU99wNB15BhZr9dUinVO02eMMdM0iiesL1suHj/irXfe5r0f+wZ//Id/wM3za3Yff0prtAfJ0QdCP5BMpSULDVq3EK0KAbcujy0GfNSWjsdS3BUTHO92uotmDYVy0nJvbSCUxu9+omRtMuvlasruiGGxbEhZMz3L5RJrLb5gIo8ePeLtt9/mg5/5WXIWnj9/TjcENRrek1IeM01IwWBMg7SorL1tGBv25owvWQyTE4PX7uzGaqm1SMS2C5brNU+fXbBeNdAfudle83Lbc7la8uzpE5xpEDnig9bM+GwZYsYHKTomNUFawhDyKyzDq8lRP7xx/72neS8FG9P5rBmvXFpqhPth+A/Ds6hDRC6A/xb4N3LOd69ZqA/9x72PKiK/Cvyq/mE+9+L/omj293uP+jZVeag+H3zEGjd6DbvdjufPrzkej6zX6xFrSUljbiV2qZxZtfzaZV3Vo9vlgtVmw5O3nxF94OZ7HyIx4Yp+BcayGwZ1JxFqA77G2FFqf9E0ZOdoUkNTq0KbwLH3GpYkjdklU5oZg8WRC8MvV8B0XM/C5eWF4jOHPTFkFosF6/UT/r/23i1Wkiw7z/vW3nHJy7nVtbu6ukrT3cPhXEGxqRnInLEIkBxbnBfaDwbkB5m2CVEPFGzD9gNFvRDQi21YMm3YEDAGBUi2YEKwZGhASLIuJE1bnhlqyO6Zmgtnurq7erq7um7nnDrXzIyIvbcf1t6RkVl5LnXprtPjswqFzJMZEbkjYsfaa/1rrX8VvZKtrS2MzVnqDbh48SLPPHuB8+fPU5Z99vf3IxO4m2nj0IXWAsTVMFIlNm6qTFLEB+X7SD1cczKSOeUxuCBU3mMmNW5SUTkwYrVJUt5DvIGswZYeazSXwlU1ftTgI16RiAl0jB+8DXG4tXu0cpp9VtSa8EzB9u73H7iyEJEcVRR/L4TwD+PHt5N7ISKXgDvx83eAK53dnwduzh8zhPBl4MsAxuYhfnboOI5SKMc4D4C2VFpYwMcYzAywam2OMWqOp1XV5hk7Ozu8/fbbbG5utlGBxFnhUjZn4rBIdRmd4xqb0xv0OXPuAvVozFsCtfcMrEGKTDtrVXF/I9ptK4bBjAhkWWvmG2PI2vRvR24rzclwjsZPO7r5GOFxMc8jxHElfML5GiuBrOyRZRnjakJm87bze+r3UZYlly5d4sqVK5w5cwZMxqROJDqujXikepB517J7P1tLLHW5DyG6W5nmfQTfaplQNwSZsLkdyI0nNFrot9QryfrLLJ89TzaaUEtJLXv4yiFNYFx7GlfTdH4+9VE5HLx4MDHqacqiHKQEPjs3bUmZZHptPyCAM0Y3fgv4Xgjhb3a++grwS8B/FV//UefzvyIiv40Cm1vHwSseVR43Xm5FaOYms4koeWoELDJtIehibsN4PObmzXe4ffs2y8vL9Ho9VSSxetQF5e0sigJfR5A03uy2n6lV0743GGCLHGk8ZNp2r/YVvbKMoGAsstATBtTCaKqmJW4REYosgyzDkmOxVKkfiPdt/YByYIBz04mnae1KVei9B6/jVsxkSvx69sIFLly4wGAw4OrVq1y4cIGiKLi/u0NdKzlxG80KWgmJTz3AppZGmrva9yz50937aMGq9dEQ2xN4j3Xak8S5SawlaSitIS8stZSMGkMVLI3NIetjfY0DbBbwfjS1FNs+IvrX/K+/32yTTxqDE4nNpjoBgrSNf0KKAo5nWXwe+IvANRF5NX7266iS+Psi8svAD4F/L373j9Gw6XU0dPofHf0Tj3ZCx1EURyXhLEr+Egw+NBr3j0xOznslafEoUNdox+93332bK1cuE8Iyde3JsiJWVKr/WBRTS6Wp9aFN0QQjlrIs6Q2G5EWPxo+o8fig/UgGvWEb4TBBxxKCAnXBB6Rtew4SyXMwQm49LrZ29OLx0tCk8KKxBDttV5B4QRWw7GvGowsKJmYFYjKyIifLcs6fu8iV569y5swZLj9/iSzL2N3dZX80AbEYm9O40JLGppUPiGNN6fmz36VEuNAJWTexgMPEfAgjGU6dKapGC/00UuTwVEi2z9JKg4Z0+2SZxeEINBhTae5dmKb6/6iJcr9oy4Tp6zRq8iTkONGQ/4eDsdSfW7B9AH71YQdylIvRnVxp+4c9xqLtQbAypU9Lv6Mr3jR82z1uoqobjSa89dZb/MRP/ISWAct0ZU3vvffksQ2A8x7EtynORVEgRc7y8jL9pSF7rtYKVgmQ5XGFnuaJpDMOTgvHJCgPaAsIA3jt05nFzuhNUEXiG61yNeh4SElkRsjMtIq1dg218wyWlhCbaz1IgHLQ5yMvvsCVK1cYDAYMhssKZFZNBHA1SlJVVVtPk67bvEIWiEohsVAkRaGUA9qjRPdxaGhUy8osQsAGrWDFC41vqPcrGnYoe5vkeRGbJwGSqRKVQo+dUsY711K11KLZ8XTK1o8zf+efg26H+e42T8r9SHJiMjgXyaIkKzi+GXfYdu0D2PH9ugrJGptSXwB1TTwgEZswxtA0DW+++Sbr6+ucPXuWsiw1dNg09IdDfNNQNU3b69TYiMJLZBewFivCcDjk3IXz4Bua0STmSsBkrG0L20K7AC5lUab4uUg02UMLEhoMNlicOHV9Yv6Cjw9em20a08OTZSFGeS/6Rcny8jIeAzIhiPDss8/ysY99jLW1NepaE7yappnya2Q5de3Y3d2P5fQRWwmBIFro9KCV17k/wbSEwGAINjKZBacJXQkYxeO8iT1aBUT7tIwmgdfefJteoQBxnpcMyl7bjWv25ptp5t0TfqCSvJ9g/fz2zrlogTEFbsM0yvOkTvFkKItO1GFRWDM9xN3JdpDmPOxGtElGnR8OJABtdpspGDo1030T6OU9/W0fqCYN11+7wbVvfY+V5bNcvXoV18ROWLUnt6U+4E6tjix1HxfN31C0IJCVA37sk59mZfUst27epNnYYG9vj8IqZtJUCh6WWU5uMqqmApOxU+1TO48XTXgK0U1pZDulHgFembOB3OZYhCyz2vm8s3gGgb61hH6GFAVFr6QJlvMXnuHKn/pTXLp8hV5vwP3726o4vdekMQfGeib1PnfX77C5tcH2/h5ODA5ogkFwLY6oiVcG52u8lDP3ynR1RxsdkRbX0HticbF8XbWodnL3tfKE7k9q/GiCyJ4qjWjVNbbU7m7BtQkWOocin2qnT4yIj5wQmh8yK3P0dnPfThmpukBj5/ukp2YkLlyiV2gGEA5hqtgSJttOVn1xuKk6VDw9lg/EEaX9HlNrnAxlEU/mONr4KAxi5rAHWCbz28wjyAd91z1G4tEMIXDv3r3Ys1OrPJPVAbMp6yFS5weZNXJtnrG8vEx1/lyk+9cEK2qtmExRjGRJpGNaa9Fi62hWOwVWg43cDj4yb4kmLAGRq1OVRaKXSw9ybi1ODGIteVbSK3usnT3LubMX6A8HTCK5DmguSmrNHUKgqpq2uC71gzUmi4i84YG4UzBHJgodbEqb2Dl+WpjmAB8rbyUqAOcctbUxH6GYAf5a100SDV1naF3w5IhoiDqyR0s62oPbmvab5LrqGDpWz/w16Ooj4cFBxL8lAscfWDTkg5EHS2kXKYf3O9fiIKVxEBaS2Klu3rzJxsZG64L0ej1lrIqMy97X7Wos0Uf2IhgCjaY/UA6GrK01hMbFCtGGZqLJVsF7giipToqqNEGxj1wEG4LyYYaA9eqG+JSwE893im3E1G8bq0LN9NxsCPigpDJFUTBcWWFt7Qz9pSFgYr+RQGFMWxKfiHwnkwk7Ozvs7ysPhveQZQZfJysgMqZ3FoZHncKtZanUv0gCTjvFJAbfKl1rLabozdzTKaaiNkWbIzOzOBxvPK0i6JzTA/u2z/38PE65ETHfpW2N2dku1S2F2WNNBzr/UXyeIjj8I6YsZqW7AqS/u69JcRzWku0gi2CRzCeydMfQTW4hav7k5ydwaX19nbt37zIajVqFMO0OpQuDdjvXXpTtwiCxM0W0G8vegNWznnGtVaDbe/vUrsFV+tuJTNdDZO9WNisrWt2aBYO3gImFRdHPTyS/YqbnEYzmbxiDMnmLYBqPr5XNvNcbsLKy1malNk3TXnMR5dUgMoiHEBiNRrEX7L42QoqWTxOvnWInJrrSjzd5Z8Fuiw8eIz6yjDktuJOs5TKFBy2K6TEiqOpVcczOu+MOiFnQNH3Wvo9csdGq1IN3ktUi2KuSFJ6ZOcfptgsGFWLSnQ4DLVdX8Hr6nGjZ/+PIiVEWMw/lAnm/rYp5rKKrsLq/3eZIyDQhZnt7m9u3b7O1tTVNgErVgCJYphreh4ANVn1X9Mb64BAMJs8oh0usrikrFduaFVlPGjJFrgh+2gk9uJqU8GVAqeZi5aExBhvHaUIi5o0me/CRBFfzJ3RiqvvhxzV52WO4sszKmTUGS0M9V2vpDfp6fjHMGUJgUo9pmobd3X02NzcZ7U+mxUttK8pZwuUpm/rh9+nAuZD4WkXxppQjIolajogdGC0wC35xxGCRAnnADT0wHZypQpifUxFU7n7eOjZeSDc/WX3d8Zg05zoYioqZHluY6WkKTK2quCi0neK799k9npI+McriOPKwodGDMIvDJmK398L8fmkM3eQtay27u7vcvXuX9fX1VlEky0Pp2D0Yg/VMF4mOn+lRPkoJGTYzlIM+S6sryPnzWvOxu0cg8obSQCwKkxBBwRDQ7hsGKxnWWHKTxehL3C+EaQGVUkLjfNBoZUzcIhgkyxkMl1leWWNleZWiP8BpAUK0KHwMIgS8OG0X4GF/f5/trV3tcRLAYslkGj6NdLyaHCZdIPDh72X7kMcWAIhXsx2rCs83qgIjF0cIgSpGsLr3t72PrbKYA31jFObAR2zRXJx5uDu5JISYpBOVVkALB4U2oYoOliVtfnabnB7nnt73qeo7ePFTDCRt+fjZqCdGWSyyHA6yJmbN0MVyHHCz62p0J9GilSZt212N0uTb39/nzTff5PU3XuPzX/g3GI2FwWCA8zXO1+RW2add8IhXLs9gpOUzJ2g2p/eBxmu69erZc5yTEpsVbGxsUo3GGIQ8K7Vbj2vo59pHxIcps7dpPIU3sXfotO6jBUkJ5HmGt4IJnonzVDETdBQMz3/kBV786Ec5f/FZ8l6JMwbnArVrGE80pJvnOSEbUXtPFWrqynF/c5s7d+6wtzeiaXx8GMEYG/ukKGdI8EZXRZFIO3jYpJj67tNFXDlVAxC8m6lrCSE2oraGajxBvHKjihFwml2beEunIKxBrHTmwJSmTs+h6TyOZlZxhKT540PY9jTwQIZ2aU2n4rQuSNcN8gyyzJNZaYmSAg6r5KBxDMmF1VqZdLl8wj5DAs+NWooAJmCMQ4wqPyXx9UzV0KPLyVAW8cbArCKYd00WuQXd7Y6KpnT3n/VbH7Qk5iMfoPcw8UJ0x2GMYXdvm3feeaf9bjxW+rqVlZWWni6BgsaYdmVtvJZeB6YPtAtCEEs56LO2tkavP8QEaKo6thqweO+mCotC1+08cloGyONDEfCxz4hEbk9PHb/HB1yleRGIUAz6fOzjH+fMuQv0l5bZn4zZ39vH9gpNbsoznKvZ3rkf62GE/f3A9p5aFKkepmkayrJHVVVkxupD0sE7pqXxs/ewe+0PtSLb71NERZf/hBUBZHmpWItTzCKl4acIlojEHAy0lYT4B+aVjrdoj5ksFd8BQzObtX8bifk4XpR13Dk8MQs1OMDTK3S4RQH90pDlhtxajFVa/zxFzEJolUHjPeNRJJP2TLGH4AliaGpHXqTPQDKDNRaMZXt3FAvomsXX8iHkZCgLOT4G8ahYxaPKot+bR819aNje3ubmzZsRs9CWg0VRKKntgiG3Hcw63yk2YBCvSVVZXrJ65hxrZ8+w7hzOBQwBm+ex3kNdGJGAsXkLXtJRYopHxJ6lXslwmhBoRhNGdcPY1eRFj8HSkHOXLvPM5ecRk9GEiA1YtQQSRtGtriWyn08mE/bGIyaTyQytQHAeOQSEfpISEvj/ENLeW4HY4YQHmoKGaZ6CulKCBHV7smipaG6Ei/wfjbKRO5DoLJgAxkKWCatLOUWZUeSGPBcyA8aqInV1wM7ldSSFNykrgheaAE0dcA60da4n6xUEW0fLFFzjCX5CCEKZG5x4miBtCv2jyslQFgtCp09T5le1Rf4yzLosdV1z69YtxuN9lpa0ZD2FTtvq0/YYnhDMbBIS6juHiINI0LqOYtint7SM3N+mMSNo1AXxooQ8tW8iS5QmGIXgKawl2AyJZDwhKON47Tw2N/gA40nN3niCFDkrZ8/y7LPP8uyVj9DrDxnX6tbUPsTqzE54McYyXGiiJdEwGo3aBshtLgizluBMlCGG+h69bDrwQLDwIY71gPXYDefOV6GayKsaFiwcrsHTIEHT+INHSYYCFOIUaDRQFBm9MqPXKzh7ZkgR+UPF+Jgr4hACLs8pjJ0dG1A7R1UZxZiCUFeBcVVRV3rSg0GBl0SC5BnXDtfodTYGJiEQHI9tW5wQZTErB4GPx3E3nqQclfsRQsBY9cuN0VyDmzdvsra2NkM/l7aVaDJP8Q+J5e/6eQpzBtH8B59lmADlcMBgdVlJbiYjLbXOA3lRqqlbN0oiI+qfVk4zU40YGq+uQe0bGu90hYlUc1IWDFfXuHDpOZ67+hHWLlxgc2cXL2aa8GUMYjNNdDKCeHV9fGjwkZlrMhkxHo8je7Y74D5NMZPHvi8P6oqHP0YX/zIHA95JgShuounmJkKO1kAmWvgnQf+WXN3KQaHXsCgz+v0evV7BsF8yHOTaAd5XNE2t5fyuidetoTBTPCyNMc+E3KDh4CBUpaescupK826K0uC8AFolPHDKY9J4w95YG03VNUweU1ucSGXxNOWoiMs89pHmWLq5f/Inf8Lly5c5e/ZsfJAmSGYWKp7QJuDMQu7JWnECdfAM1tZYrieM6wqAq9UoAAAgAElEQVRvBGuUUm91OKCuKvb29qijC4DzOOuwVklufBAa8YTcIFlP+5gaobeyzNmVVc5efIYLzz3LYHUVspzJaESWG4zNKKyFmF/h3dT1EhGkw5OhyU/VDA4xxSD0yZ5PRIq21CPepScjiyJkB0W/QggKrAaHMWCN0CtyitxgxGFw5LnVBzu3LJVJWSj1YFFklLmytnunvVwCFbhJ67paCQQXYpRE09yDaNf5YGJDKEy8/xm+L3iv2Ihz2m5TNVZBQDvDZbsGYY+6DmyPH+96nThlcVi22dN2VbrRkba6NEZEtKO68Nprr/GpT32K8+fPYYzgXIO1WpGZQuOpra/G8O2Bv+Uyg8UyWFuhX43pjfaRXsGg12NpMKSfZ+zv7lEjjH1DPXHK/I2ltuiKaAIhTKtKM9Nn0BuwfOYMF569xNqFCxS9AT4IVV3TGw71HI1gjCUDRqMRdaN1FYlJOgGZzqWM05rU90o6IboHlOuDdENPTQ5bGNKYna87n2lmqLGGzBpWhiWry0P6PYuxgTIX8kyjPr1sMqXjl0BuPcZ4gm+01UJd4asJodHEthbfME6bLmEg4rde2y/hfRN7gWRkRYGIpXae/f0x1ihJr1gDRtnFxGYUvZyi1KK/Wxujx7peJ0NZdKIh8CBG8DSUxKIM0gTWzYdwk8uxv7/PN77xDdbWVrl48QJXrlyZPiCCmp84QtDiJnxAYiMh04bJfGTyEkKvR1VPePvuLXb3dsmWhqxeuMDS0oBhv89oZ49+ntNkghn2Wpwkw2sfVYHMWnIjsRIzZ+3ceZ5/4SWcGPYmFZPGEYzVsnWPFrAVPbwL1FVMsIrRBLzDN0qoUkWLZlKNtK3B7i5VNW5N6IAj+KlFpeCrf2z3AVQZhS5I8Qhd0GeSr5gNkU9fBbGRtT0Rq7pG69CMEJwwGCxz/uwKeebVqrCByXhENdqAkGlRYVAVabzENglGu9ZBy0QWYuTDUGtI2TeKM8R5EUTdWMkcuTVYq02mcDWTUUUmFaYoMGTU1YQqaHHh0pkzDJdW8aHh2g9+FJQFDz6c837vwyqM+RyJ7mfdCZxwhe426e95RWVE2rBdjEOQmZwyL9jb28FaSzUZ89aNG9y5fZtzsWw9Cxbjjb4KOlF8ICtznGvIbEbtPZlVEtnR/oQ8zxlXI9bX17l1+y4hKK1dIYaxF9y4wduMMBhSljn56hrWRqVQTzkl8l7ZsnAbkzEcDtkLHu8aGl/Hc3I01YTaCWWvQCQS7gjYTMhsjnM1zajB+TqSGmubw8Y1+NBw//59BXq9U+4Jr20Nm6qe5qy0eR/TnqIz9zVGcxbdi9l5IockdXXIiDv7SJiC0VP3x8QEs04EpL23cXw+NuyRlACWEXxDVXvGVeDWrU3G4zFnV5ZYGuZUOKrJiLqqMUYbX+eZKoLaVRqZqjQ/xApY77He4j2YkFGZTBPk0nz1mj9TlKqwCnpYl9PUQl0JrsmRkaGWQHA5uc/w0uBdTRMqerubZDZlET+enBhlcZQymJ9A74fMJ10d5Mfq59oDI5nhab/d3V1u3rzJjRs3eP755xkOh61vn3z4aXadWgLjyZg8L2mcjwVYmiNx8533uHbtGltbW/R6/Zbqf2tri/3dPTY21tUtMKr0ykyZt0po3Y7l5WUuP/88q2tnyfOcqlL+fWOUCDjlEFhrldxXNNvSxorRgG/zIloMRqbp03Vds7c7Gw0JIeCDb3uStNe3vX9JCRx8Lxbd58Nc1EX7L97+QSukq5S644MpHeB8NEcCjKsJwYF3E+rxmP3lgl6ZkRmvYVaxWtQXAWyCwbnYYjGGzU1mVfU5g0ZcpyCwDWl86X7GlHyUm9SjYfA6ZmmGusbjCEbZ1FyAqqpxolwljysnRlnA0UlVx932KDnI0gDaMKeZcznSft2ELtAHvs0EjMdbX1/n9ddf5xOf+ATPPPPMjIsVQoj4hnbw1v6jDVlWMBqNVGk0DTdv3uSVb77C7/7u7zIYDFlZWWnJcne39rh1+ybvvfcezulvp27a1lqYTBgMBhRFwcWLF/nJn/xJbNbj0qVLeBMp+UQwWY/GVzFZTGtJNA25m6wWYhNk314f75v2OjWNWhWpRB9omcC895qU1b1mM5bd3H3hoOTl+H0KcR4677vK4Hj4yIPzYNba8YQ2zK2KIraJbGr260BVe6q6pqpzlpd6DPoFy3lJZrIY7YpFeCLEtq4aYkUI4nHB4CUgVnBuGl2JPP9a6GcttlAswjmtMq59wHmhcQ4Ri3fgJCA24EXTuyd1wMQm2I8rJ0NZHJGUdZCL8qTkqBVrHtTsKoZ5N2nQV4Dw7bff5t133+XKlSssLS21tSIh+LZrVAiaXFOWNloZBWWZsbGxwbe//W1+7/d+n6997essDYYsLy9rqjewtbXF7u4u2zv342/rQ5zAuPHumMFggDGGCxcu8O6te+xPHD/zMz/DcLjUEgv3+znGZvjoKmTWttZLNwqgCmJaRds0WjqfiuU2NrQlgnOdzNj4ZM+HSgPM5DXMfM5iC3JaqXmMm9kRTXeOULLEC9Uey8xvPP39mYivFvR0x+CFSMVowCuDelXDaNIgtiZgWLIFRnIM4HygcTXGCCaDLIukzo2m0QfvINb1zGa3av6MEUtWaEzWe0/lPbVzNMHijNBIwESqA2MFBcL03jW1x2oY5eEv4JycDGURjs6teD/dkK7J2k72OYtifvtU3ZneO6cgbVGohfDO2+9y/fp1XnrpJVZXV2PTohQy1GNYoyuzUvgHssyyubnNH//RK/zB//V/881XXmV3e4ftzR16vfttu4Fu8pPNdDWqqkmLU3hrGDU1VVUxcYFJ/Sq9wTIvfvTHefHFF2lcoGpqyv6QrOiROT2HjGkp+vx/5xyTSlstjsdj9vf3WwW4vr7eWhXqXk2vm6Ytd+pqxEdo4mg+i0dVEkfKA1mSh/+IsmnFqFVUOj6IWk9BY0CVAyaBhoq6CaxmPazNKEqrwLZrNJENVTRBlHhHS0ECIl4tAjqkwsYgmURgU7N7Q/B4HHXwcVtLEyvLMoFCLMZYPA7nDI1vKIygvVceLxJ1MpQFR6/u8xGIx5GDsjO7xz8oIau7jTGziiwxZI3HY+7cucPr19/gvc/c4oWPvEg2zKLprhPVORdR8BA5MjK2t7f5+tf+kK985Sv8q6/+v+zs7Cmvp6/jNjnGCIPBUkvVFwTqZoINOVlRqMUSXQBkhAtw884dXv3WNT756jc5f/EZ1tbW1BJID60k10FzH+YVRTrHyWQS3aaq7UoGcP/+fWDat8R7j2S27XzWtS6SNZaAyoPkoHYeiqMcfv9nQGo0eiMLLQqZex/P1Qtt2nd7jztbBhNT7TMCjiYo1uRr7f1SNzU7ZQ5ZgCxDTAnWEfyYEBoqH7GcGOUkaJha+9NOM36TaynClH7AmrZZVWzwgItWBWIRm0dWNIMNnqpucGLiXP0RURaLkO/575+UVXGYsujSmqVJ3R1Tl8vCe9fS4PX7fUQsGxv3KQptOnTt2jVWV1e5evUqL+QvkBcZvV4vZnvWiLH0eiVV7fmjP36F3/md3+Gf/tN/xhtvvMF4PIagvUVXVlbweDxKkKv5GrliDSZgJNPuWyFE01YVSVn2SR3Svv/97/Obv/mbrK+v85f/0q+AD9STClcbJqMxoSh08kXgMrkjjau19mNvh9FoWv9RFCXGWDbW77O+vtlWNqaSaMFQew3zAR0OjM5170Y/525t90/tIqDuwVG4xnRnaZPCQwtaChw6h6LC6ICc81G1YGzcTCNhqfE0Eqh8g69r9ht4K4zo7TQMl8YMBzlFz5KZgkHf4nyFiXZBitpYMRhrKDqFa9bGuhTRe+gF8B4rASMBH1NZjYAttGCv8ZqnIVmOBOVG9Y0nZIvzeR5Gnm4K3Zx0FcLU1JeZB/QgpXGYJXDYdt3P53+n65p0x9LFLlIValIy6iJohWLTeN56621+8IMfsLe3N9NUeDKZYAxUtR7r+9//Pl//+r/m5s2bLaZRZCWTSU0IQlH02irJbgTGSkZqhktE4K1AU00wBIrMYgi4uuLtt27wnWvfYnP9LitLA5pqTFONKXOLwbfnlRRFAm+bRis1g49dzhrfukR37tyN+00jK91rvCirM1lTrQJZcEtENIktJbLNY0Pzlk9nTxarE/18Zr9gpv8fkNmQOqDsYtAOuPFa9ekRnIdARpb3MbZkrwpsTRo2dkbc2dplc3fMuAGTl+TlEGMLjag5kCDkxlKIjX1sc4osJzOxk7zzWEkeUAw/O2XkzYwaQcZCXqSGWHULqhIS583jL7QnzrI46H1XSXRX/YMe/sPcmkXg5HzYdH67+VCcvp9mRiaux6IoWoXSNA2bm5u89tprvPzyy1NMwXuyXDusV1XFrVu3cS5w9vx5xFpGeyOyrMA4Icuytqw6WSzd80hmv6sb6tTCzit+sLe7refiPK6uCK7m2jdf4a0332B1eYlhzNacgpjpIXRt2DSds/Jqeq18bBqWl5fZ2Nhga2uH8bhqLawUeg0xfOBBF/QwGzY9StyhQIVHxBygKB6UBxaYpBwWbj51Rw6TxMSd8jR8iFhEpMCqvFA7TzVxlB5qb4CCleUeZaZs6xgQmRChSazNsSafVjVHfMcTu6sEVVCapwM4hw+a/m+MRySxqE8XJWM65txjyolRFosSqJIswhUO2v84UZXDAMx5pTBv0UyjGolt22Ktb/34oiiii6KRgu3tbV577TU2Nzc1dOknZFlGUZbUdcPurjJi/9RnP8vy6ipV1fDVr36Vra0tlvrL5ISWhwE8ZVmqPyuCZHaG61OCug9FrEWpxxNym2njHSNk1vDO2z/k9p1bjMYfZWVpyO7enuZolCXjWKPQVSCJlLjLVu6aQL83ZOv+W9y5fa8l3qnrmjwrQGYzcoG2TQEi7dydrwaHqSWR1vpF96ZllGuVedq43Yl0lBD/2XDEHApm8YDSdzOjmo5NsVFVMB51JyDgTQ54vKtxPij/iKlY26+xg5JMLJk1hMwiIWBNSVH0EBctV7Q3i48d8IwJMRnOadPo6GMF11BYyHJtvO0iN0ciAhaRtp/M48qJckO6Mg+uPcp+R20zbykc9JtpYnUb8iRloA+rYG3e3ti0b0quun37Nq+//noMZU3p3XZ399ja2iKEwNraGh//+Cf5+Mc/zsrKGtVo0gKi+vsRLPSexlUEHJmhbWqcXJcsy7TKcFJRVxOdwjJtI2Ct5Rtf/0PeeO16tHQU7W+aKuYE+JY0xzlHVY1jijJRMeakVfDevQ3u3l2fumOdB3KGzIgHc1bmpetydO8JMMUe9CAz2xx8TDOzTTr+9L/p/I+fxavc3UabO8uB/xePRVrXUCQnBGFSw/6eY2NzxM5ezaQKeJ9jTB9je2BybJa39yg12zbGtEl3yY01QVMwjNEFIi8Mea40hkY0Pd3Ee+Bjot88Z+ejyIlQFoHZh3URGv/APnOfH0dJHBTl6FoK3dejJCmMLuem7g8aHdBin52dHV555ZV2EmQ2ZzQac+/ePQUL+8oqVRQFly5d4tyF8/SWl2YUUvvfT/uKeO+1J6tX3opMjFL+h4CEQCYWXGC8t894b78N01777ne48fYP2R3ttg9GMvudb1r3w/umLRJLom5XwWg04fbtu2xv72KtJc+KGRcpXe9F79N17z6885JW7UV3oas8H1b0AT4I7DvscZjlH5GgdouEpGJoOTyUr2SayOUdNDWMR3B/c8zGvT3u3x+zP3ZUHpAcbIE3FpNnZGWhhWLWxsjHNOFO/xusFazVKEee52pNBYf4KVm0q2qaWpm13GMS38AJc0OOwh8WafJFFsKibY/z+/PHTm5H+nvetJ7ff37bBBY2jeX69esAlGVJ7RTLuHv3LisrK/Tz5RgWDQyXV5RCv2koyiKWfgdEAtY5jFusWIHIsWBig+bYGNl76rrBI5RZwd7eHk3TxAjHiF5PO6whFqFp3ZoQXPs+rXb63jIYDFi/t8Gd23cZjyY0tWtXwiRJeXbv0VELwMz1POy7FEg5ELLoPPQJfzq02OwwMtvjradWEqNW0Lof0ZIAvEeCQYIjeKgmcN+PtaRcBAYleZ5hipKsV1JEC9B75UWVmANjYp6FtapQcvGIsZrQJTl11bm2PuCbEFsyEHGVHxGAU5iyarefzaHf81bBYsDx8NXsgd/tAJfzx+v2AU3H70ZC5o8TQmizMhPwmLqT7ezs8NZbb/Hd736Xq1evcnf9Hs45tTTKguFwyP7+mMYHLl68qH1Ti17rEpSlHrdyFdQp+9PRVHU0NV10gaYFW9s7OzpuIxEMbNja2uLCMxf587/wJT7+iU9Q1TV5USgHQvCI04naNJU2PZ5MAK/kw5EzIQRPr+zzB6/+K65d+w7r6xvs7+0xXFqiKIpo8aRoUDNVsJ2oRjtvDzEOjlL60sE+jpSHrUo9hKPPhNlhKxnONKSODwTxSK2Fh8bk2LLAxhLzyWSfegLOaQi6QSgHfbLBkKWza5jxHvWkYjwaM2lqghGKskc5yPC+Ie/lDI3gvOBdRt0PBJ8z2dew6aRucF6rVfFCkWkv2jIvgJ2Huw5zciKURWBKUdd+1sEOuhTuSXsuWrEWmbpHhVQP8jsPC9HOkwt3w4GJGDaFFr33WNGuWTdu3KAsy9YdGQ6XAaPgpQk0VUVZ5hpfNxpN8TggYhHeYo0ls4U2Om55FU1b8CWZxYvHFpGgdjJpFV9RFLz0wov8m1/4PM8//7yCmE0DDeSSLIGpGaulCVkMiXrqekRZ9tnd3eW9Wz9kUu2DOHr94UxjoaKwNE2FtVo4lfj0Ja62LeWeLMaPZhaKEGbuhR4jKfa0z7Qxj97kub8PFT/3yoyiWISjpGnRtSZ9tCrECiFYyJXiEDzSpMO61CieKhi296H2NUE8Zb/HyuoZeqFWAmAKmjDGETTaZjOwGWDJcrAOmtqTe2VaG3un3K3W4qoGP6nJrEPKBmsFTM3jyolQFkkOegjTg3iQHBQdmbcWFsmikCnMJl8d5/fmjzfbUsCzu7vL66+/zuXLl7l48aLyYcYKQmMMmRGsVeWSgEpd2TvAKp1Wg1EZpfGEENnD65rxaNQqtfRaFAVXrlzh5Zdf5sUXX6TX67UJVsldSpM/uRxVVbXuxWQyoSxLnHPcvXuX+/fvt1WzafsZst5juhsfNjmue9td7HwItHzukZBII1we52qsNfR6Baury4hRBneJ2ZhKAaKAsipgq7UlDoxoCBkHvcZRVQ11PWqfFWstxgpZZlCd9nhUWSdCWbSRrwWTa9EDv8gFOWybeYsl/d19oLvbJaxinuviMNN4/jfmlcVkMuH69et8+tOf5vLly4iNK2a0QvLM0jR6k3u9nlaX7u4utLZSp7H0cCeFkIq7JpMJ/X5/pk/GpUuX+Pmf/3l++qd/mqWlpdZFSuBlXWvWZ57b1v1JSipZSP1+n83NLd555x3W19fbSbmoQneRHKbAu58fhl89WTkoVHqwG9KVRefSnSPz0TUvYKzS4hECDo+vYWt7B4ywtLREM6jJc4vNMwqG1M0IsRZMRuMrsiynzEqcCzhxZFlBaAJFNYkg5jT/RJVFLG1/AiXqJyIaAtMHFKbhuynYdnCYc/7z+YrJ+e2POkYax0HWStqmq2QOW0G7E399fZ13332XqtIErhSSBChiXYeINijq9Xqdxspeke24+neVmtYOTEvlE06QmugAnDt3js985jP83M/9HJ/73Odai2UwGLTnWxRFe+1TElhZlm3CWbome3t73Lx5k52dnQie1u2Y5i2zeddx/hp2r/n8ZydBDruvh415Hvua/x/QKg0fOTarBjbvb/PDd97l5u173N8ZE6SkN1imv7xG2VsCyXDeYG2JLUqyLMdmBXlWYrKCPC9bizRFTbIsaxeedH8fR06GsuiEhrrl313SlUUuSvp70efzk7MrCyMJC/afVz4HHe/g05rmQBhj2N3a5a233ub+/fsUWc4ougsAmZmGxspSb7wxRtm+O2PtXossyxS76IRwQwgdQNKxtLTET/3UT/HFL36RT3/60zz33HOt1ZDGlcaoisG3CiR5fkmJhaDK4vbt2+zu7s9cn+41m7/Wh70/iYoihEA4BHxN2yQ5SmGISCxIM7iYaNU4r8laCC7A/gRu3dvgvTubbGztMq4cJu/R76/SH6wSyAhEMgzJwBSa8ZkXZFlBURTtgpPZvHUnh8MhZS+nKPLHvi4nxg1Job6u2dt9UNMqOrPfAROtO4kfZhLOm/yLJv5hOMgicFRElJSkCWxubvLuu++ysbHBSy+9xHA4bC2HtG2bWDW/SkvsnB40szLP8xZLSBmW3XEVRcHS0hKf+MQn+OIXv8jP/uzPcu7cOUajURvWTBZGit7MYxP7+/vkuU648XhMVVVsbW3FNoV7HWtwWny3WMkuBqBPvITYGHlOZsHWxXOhe0/bwwHBx1R1o+n0EiCVs9SNZ2PLY/JdBisjsl6fpeUeRZljfEOW1SAWQgbiMVlOnvUQPNa6GH43M89MUWSx38gH0JFMRK4Afxd4Fp0VXw4h/Pci8hvAXwLuxk1/PYTwj+M+fxX4ZdTa+k9CCP/nEb/Rrl4w+7CnmoSUG9B1EZLyeJxJ2LUoFgGr3W3S2Ob3nx/D/DbeB3q9Hrdu3cJay+///u/zzDPPcPHiRSZ1xWQ0our1kABLS0uRL1NJXZumATft3E7H7QghsL+vrQN92xHLU9eez372s3zpS1/iC1/4AlevXuX8+fNMJpP22mZZRl3X9Pv9lswmKZwmkslqJa0wHlcURY/r169z/fp17ty5NxP50XOcdo2fv4bhgGV60UN3HFD68eSwfIoHw+LHcUXmJYSAzaQ99+A7LpqxOO8xxiKS0XglABYRgrXsNzV3NkdMwk229isuP3eBS89dYLh0RovPIpOWkRxjDSbrEVyNMRnG1BR5ydLSbHPusiyOLOs/jhzHsmiA/yKE8Mcisgz8kYj88/jdfxdC+G+7G4vIJ4G/AHwKeA74FyLysaAMIotlDifoPpgJ9e+CcfPbzE/S7vdpm+5rAh/nf7OLm3T3PcgFOcqETg8mHpZWlhmPK3Z29njjjRtcv/4GzzxzCcEyGVcMBktsb9/HEJSAN0+ZhrPdvtss0Fhg1uI8jTbDLcsSV1d85jOf4bOf/Syf+tSnlKR3T7kxxuNxe021vaJvJ1aKmij5bqAoCiXQmUyw1rK+vs6NGzfaornUCsDarPN+qkDaa9cJNc5fu/nredC17lomi6y+o2WuVuWAscwvFI/yjD2g8GSW6EcibhHQqlUx2myqbjxZgMoHdvbGcG+DssxZWlpi6dIapffUk4rQOIIIIhYxGWVhGWVjbUuRKatWcjHrZp/aNfR6H4AbEkJ4D3gvvt8Rke8Blw/Z5ReB3w4hTIA3ReQ68Dngq4f9Tnc16l7sBOClbR4VP1j0W/MK5v0SY4zS/ouoKb+xycbGBjs7O2QxkSttZ61t8YvOEZiHl7QtoZuxwkzQc7l69Sof/ehHee655xgMBu02h52niDBbK/4gnLW7u8v29i6j0Wjq9gR5pAfqZMphmZzvg4QH2auC116mo1AhEtjd3Wc0Gcd5P6vUjER3NbG65wVFocdLlroPkxgReXzEQR4SsPsI8AfAp4H/HPgPgW3gG6j1sSki/yPwtRDC/xr3+S3gn4QQ/ve5Y/0K8Cvxzx8H1oF7j3EuH6Sc58MzVvhwjffDNFb4cI33x0MIy4+687HVjYgsAf8A+M9CCNsi8reAv47iNn8d+BvAf8zideYBjRRC+DLw5c7xvxFC+DMPN/ynIx+mscKHa7wfprHCh2u8IvKNx9n/WKFTEclRRfH3Qgj/ECCEcDuE4IKiV/8z6moAvANc6ez+PHDzcQZ5KqdyKk9fjlQWoo7ubwHfCyH8zc7nlzqb/bvAt+P7rwB/QURKEXkB+DHgD5/ckE/lVE7lachx3JDPA38RuCYir8bPfh3490XkT6Muxg3gLwOEEL4jIn8f+C4aSfnVQyMhU/ny0ZucGPkwjRU+XOP9MI0VPlzjfayxPhTAeSqncir//5WTke59KqdyKidenrqyEJE/LyLfF5HrIvJrT3s8i0REbojINRF5NSHKInJWRP65iLwWX888pbH9bRG5IyLf7ny2cGyi8j/Ea/0tEXn5hIz3N0Tk3Xh9XxWRL3W++6txvN8XkX/7Ax7rFRH5PRH5noh8R0T+0/j5ibu+h4z1yV3b+aKqD/I/2hPudeBFoAC+CXzyaY7pgHHeAM7PffbfAL8W3/8a8F8/pbH9OeBl4NtHjQ34EvBP0PD2nwW+fkLG+xvAf7lg20/GOVECL8S5Yj/AsV4CXo7vl4EfxDGduOt7yFif2LV92pbF54DrIYQ3QggV8NtoBuiHQX4R+Dvx/d8B/p2nMYgQwh8AG3MfHzS2XwT+blD5GrA2F9V63+WA8R4kbTZwCOFNIGUDfyASQngvhPDH8f0OkLKXT9z1PWSsB8lDX9unrSwuA293/n6Hw0/waUkA/pmI/FHMPAV4JmgqPPH14lMb3YNy0NhO8vX+K9F0/9sdl+7EjDdmL/8k8HVO+PWdGys8oWv7tJXFsbI9T4B8PoTwMvALwK+KyJ972gN6RDmp1/tvAS8BfxqtQ/ob8fMTMd757OXDNl3w2Qc63gVjfWLX9mkriw9FtmcI4WZ8vQP8H6i5djuZmPH1ztMb4QNy0NhO5PUOJzgbeFH2Mif0+r7fmdZPW1n8a+DHROQFESnQ0vavPOUxzYiIDEVL8xGRIfBvodmqXwF+KW72S8A/ejojXCgHje0rwH8QUfs/C2wlc/ppyknNBj4oe5kTeH0/kEzrDwqtPQTF/RKK3L4O/LWnPZ4F43sRRY2/CXwnjRE4B/xL4LX4evYpje9/Q83LGl0tfvmgsaGm5/8Ur/U14M+ckPH+L3E834qT+DnVUBYAAAB6SURBVFJn+78Wx/t94Bc+4LF+ATXNvwW8Gv9/6SRe30PG+sSu7WkG56mcyqkcS562G3Iqp3IqHxI5VRanciqnciw5VRanciqnciw5VRanciqnciw5VRanciqnciw5VRanciqnciw5VRanciqnciw5VRanciqnciz5/wALAj/Xp5FT4wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f56bbd2df98>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import cv2                \n",
    "import matplotlib.pyplot as plt                        \n",
    "%matplotlib inline                               \n",
    "\n",
    "# extract pre-trained face detector\n",
    "face_cascade = cv2.CascadeClassifier('haarcascades/haarcascade_frontalface_alt.xml')\n",
    "\n",
    "# load color (BGR) image\n",
    "img = cv2.imread(human_files[0])\n",
    "# convert BGR image to grayscale\n",
    "gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "# find faces in image\n",
    "faces = face_cascade.detectMultiScale(gray)\n",
    "\n",
    "# print number of faces detected in the image\n",
    "print('Number of faces detected:', len(faces))\n",
    "\n",
    "# get bounding box for each detected face\n",
    "for (x,y,w,h) in faces:\n",
    "    # add bounding box to color image\n",
    "    cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)\n",
    "    \n",
    "# convert BGR image to RGB for plotting\n",
    "cv_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n",
    "\n",
    "# display the image, along with bounding box\n",
    "plt.imshow(cv_rgb)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before using any of the face detectors, it is standard procedure to convert the images to grayscale.  The `detectMultiScale` function executes the classifier stored in `face_cascade` and takes the grayscale image as a parameter.  \n",
    "\n",
    "In the above code, `faces` is a numpy array of detected faces, where each row corresponds to a detected face.  Each detected face is a 1D array with four entries that specifies the bounding box of the detected face.  The first two entries in the array (extracted in the above code as `x` and `y`) specify the horizontal and vertical positions of the top left corner of the bounding box.  The last two entries in the array (extracted here as `w` and `h`) specify the width and height of the box.\n",
    "\n",
    "### Write a Human Face Detector\n",
    "\n",
    "We can use this procedure to write a function that returns `True` if a human face is detected in an image and `False` otherwise.  This function, aptly named `face_detector`, takes a string-valued file path to an image as input and appears in the code block below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# returns \"True\" if face is detected in image stored at img_path\n",
    "def face_detector(img_path):\n",
    "    img = cv2.imread(img_path)\n",
    "    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
    "    faces = face_cascade.detectMultiScale(gray)\n",
    "    return len(faces) > 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (IMPLEMENTATION) Assess the Human Face Detector\n",
    "\n",
    "__Question 1:__ Use the code cell below to test the performance of the `face_detector` function.  \n",
    "- What percentage of the first 100 images in `human_files` have a detected human face?  \n",
    "- What percentage of the first 100 images in `dog_files` have a detected human face? \n",
    "\n",
    "Ideally, we would like 100% of human images with a detected face and 0% of dog images with a detected face.  You will see that our algorithm falls short of this goal, but still gives acceptable performance.  We extract the file paths for the first 100 images from each of the datasets and store them in the numpy arrays `human_files_short` and `dog_files_short`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Answer:__ \n",
    "- human faces detected in `human_files_short`: 98/100\n",
    "- human faces detected in `dog_files_short`: 17/100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [00:02<00:00, 33.83it/s]\n",
      "100%|██████████| 100/100 [00:30<00:00,  3.32it/s]\n"
     ]
    }
   ],
   "source": [
    "from tqdm import tqdm\n",
    "\n",
    "human_files_short = human_files[:100]\n",
    "dog_files_short = dog_files[:100]\n",
    "\n",
    "#-#-# Do NOT modify the code above this line. #-#-#\n",
    "\n",
    "## TODO: Test the performance of the face_detector algorithm \n",
    "## on the images in human_files_short and dog_files_short.\n",
    "human_count = 0\n",
    "dog_count = 0\n",
    "for human in tqdm(human_files_short):\n",
    "    if face_detector(human):\n",
    "        human_count += 1   \n",
    "for dog in tqdm(dog_files_short):\n",
    "    if face_detector(dog):\n",
    "        dog_count += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(98, 17)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "human_count, dog_count"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We suggest the face detector from OpenCV as a potential way to detect human images in your algorithm, but you are free to explore other approaches, especially approaches that make use of deep learning :).  Please use the code cell below to design and test your own face detection algorithm.  If you decide to pursue this _optional_ task, report performance on `human_files_short` and `dog_files_short`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "### (Optional) \n",
    "### TODO: Test performance of anotherface detection algorithm.\n",
    "### Feel free to use as many code cells as needed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "<a id='step2'></a>\n",
    "## Step 2: Detect Dogs\n",
    "\n",
    "In this section, we use a [pre-trained model](http://pytorch.org/docs/master/torchvision/models.html) to detect dogs in images.  \n",
    "\n",
    "### Obtain Pre-trained VGG-16 Model\n",
    "\n",
    "The code cell below downloads the VGG-16 model, along with weights that have been trained on [ImageNet](http://www.image-net.org/), a very large, very popular dataset used for image classification and other vision tasks.  ImageNet contains over 10 million URLs, each linking to an image containing an object from one of [1000 categories](https://gist.github.com/yrevar/942d3a0ac09ec9e5eb3a).  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading: \"https://download.pytorch.org/models/vgg16-397923af.pth\" to /root/.torch/models/vgg16-397923af.pth\n",
      "100%|██████████| 553433881/553433881 [00:05<00:00, 94981102.18it/s] \n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "import torchvision.models as models\n",
    "\n",
    "# define VGG16 model\n",
    "VGG16 = models.vgg16(pretrained=True)\n",
    "\n",
    "# check if CUDA is available\n",
    "use_cuda = torch.cuda.is_available()\n",
    "\n",
    "# move model to GPU if CUDA is available\n",
    "if use_cuda:\n",
    "    VGG16 = VGG16.cuda()    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Given an image, this pre-trained VGG-16 model returns a prediction (derived from the 1000 possible categories in ImageNet) for the object that is contained in the image."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (IMPLEMENTATION) Making Predictions with a Pre-trained Model\n",
    "\n",
    "In the next code cell, you will write a function that accepts a path to an image (such as `'dogImages/train/001.Affenpinscher/Affenpinscher_00001.jpg'`) as input and returns the index corresponding to the ImageNet class that is predicted by the pre-trained VGG-16 model.  The output should always be an integer between 0 and 999, inclusive.\n",
    "\n",
    "Before writing the function, make sure that you take the time to learn  how to appropriately pre-process tensors for pre-trained models in the [PyTorch documentation](http://pytorch.org/docs/stable/torchvision/models.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CUDA is available!  Training on GPU ...\n"
     ]
    }
   ],
   "source": [
    "from PIL import Image\n",
    "import torchvision.transforms as transforms\n",
    "from torch.autograd import Variable\n",
    "\n",
    "train_on_gpu = torch.cuda.is_available()\n",
    "\n",
    "if not train_on_gpu:\n",
    "    print('CUDA is not available.  Training on CPU ...')\n",
    "else:\n",
    "    print('CUDA is available!  Training on GPU ...')\n",
    "\n",
    "def VGG16_predict(img_path):\n",
    "    '''\n",
    "    Use pre-trained VGG-16 model to obtain index corresponding to \n",
    "    predicted ImageNet class for image at specified path\n",
    "    \n",
    "    Args:\n",
    "        img_path: path to an image\n",
    "        \n",
    "    Returns:\n",
    "        Index corresponding to VGG-16 model's prediction\n",
    "    '''\n",
    "    \n",
    "    ## TODO: Complete the function.\n",
    "    ## Load and pre-process an image from the given img_path\n",
    "    img = Image.open(img_path)\n",
    "    \n",
    "    ### PROCESSING IMAGE IN PYTORCH ###\n",
    "    \n",
    "    ## 1. resize img, min size in PyTorch pretrained models document, is 224 px.\n",
    "    ## 2. convert to PyTorch Tensor.\n",
    "    ## 3. normalize it, noted in PyTorch pretrained models document,\n",
    "    ##    mean = [0.485, 0.456, 0.406] and std = [0.229, 0.224, 0.225].\n",
    "    \n",
    "    min_img_size = 256      \n",
    "    transform = transforms.Compose([transforms.Resize(min_img_size),\n",
    "                                    transforms.CenterCrop(size=224),\n",
    "                                    transforms.ToTensor(),\n",
    "                                    transforms.Normalize(mean=[0.485, 0.456, 0.406],\n",
    "                                                         std=[0.229, 0.224, 0.225])])\n",
    "    \n",
    "    img_t = transform(img).unsqueeze(0)\n",
    "    \n",
    " \n",
    "    ## model inference\n",
    "    output = VGG16(img_t.cuda())\n",
    "    _, preds_tensor = torch.max(output, 1)\n",
    "    preds = np.squeeze(preds_tensor.numpy()) if not train_on_gpu else np.squeeze(preds_tensor.cpu().numpy())\n",
    "    return preds_tensor\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tensor([ 243], device='cuda:0')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "VGG16_predict(dog_files_short[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (IMPLEMENTATION) Write a Dog Detector\n",
    "\n",
    "While looking at the [dictionary](https://gist.github.com/yrevar/942d3a0ac09ec9e5eb3a), you will notice that the categories corresponding to dogs appear in an uninterrupted sequence and correspond to dictionary keys 151-268, inclusive, to include all categories from `'Chihuahua'` to `'Mexican hairless'`.  Thus, in order to check to see if an image is predicted to contain a dog by the pre-trained VGG-16 model, we need only check if the pre-trained model predicts an index between 151 and 268 (inclusive).\n",
    "\n",
    "Use these ideas to complete the `dog_detector` function below, which returns `True` if a dog is detected in an image (and `False` if not)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "### returns \"True\" if a dog is detected in the image stored at img_path\n",
    "def dog_detector(img_path):\n",
    "    ## TODO: Complete the function.\n",
    "    if (VGG16_predict(img_path) >= 151) and (VGG16_predict(img_path) <= 268):\n",
    "        return True\n",
    "    else:\n",
    "        return False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (IMPLEMENTATION) Assess the Dog Detector\n",
    "\n",
    "__Question 2:__ Use the code cell below to test the performance of your `dog_detector` function.  \n",
    "- What percentage of the images in `human_files_short` have a detected dog?  \n",
    "- What percentage of the images in `dog_files_short` have a detected dog?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Answer:__ \n",
    "- dog faces detected in `human_files_short`: 0/100\n",
    "- dog faces detected in `dog_files_short`: 100/100"
   ]
  },
  {
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
    {
     "name": "stderr",
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     ]
    },
    {
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     "output_type": "stream",
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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     "name": "stderr",
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     ]
    },
    {
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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    {
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      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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     ]
    },
    {
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     "output_type": "stream",
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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    },
    {
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     "output_type": "stream",
     "text": [
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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     ]
    },
    {
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     "output_type": "stream",
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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    {
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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    {
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     ]
    },
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    {
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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     ]
    },
    {
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "### TODO: Test the performance of the dog_detector function\n",
    "### on the images in human_files_short and dog_files_short.\n",
    "dog_human = 0\n",
    "for human in tqdm(human_files_short):\n",
    "    if dog_detector(human):\n",
    "        dog_human += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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      "CUDA is available!  Training on GPU ...\n"
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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     ]
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
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    {
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
    {
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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     ]
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    {
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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    {
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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    {
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
    {
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    {
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n"
     ]
    },
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      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
      "CUDA is available!  Training on GPU ...\n",
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   ],
   "source": [
    "dog_dog = 0\n",
    "for dog in tqdm(dog_files_short):\n",
    "    if dog_detector(dog):\n",
    "        dog_dog += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 100)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dog_human, dog_dog"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We suggest VGG-16 as a potential network to detect dog images in your algorithm, but you are free to explore other pre-trained networks (such as [Inception-v3](http://pytorch.org/docs/master/torchvision/models.html#inception-v3), [ResNet-50](http://pytorch.org/docs/master/torchvision/models.html#id3), etc).  Please use the code cell below to test other pre-trained PyTorch models.  If you decide to pursue this _optional_ task, report performance on `human_files_short` and `dog_files_short`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "### (Optional) \n",
    "### TODO: Report the performance of another pre-trained network.\n",
    "### Feel free to use as many code cells as needed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "<a id='step3'></a>\n",
    "## Step 3: Create a CNN to Classify Dog Breeds (from Scratch)\n",
    "\n",
    "Now that we have functions for detecting humans and dogs in images, we need a way to predict breed from images.  In this step, you will create a CNN that classifies dog breeds.  You must create your CNN _from scratch_ (so, you can't use transfer learning _yet_!), and you must attain a test accuracy of at least 10%.  In Step 4 of this notebook, you will have the opportunity to use transfer learning to create a CNN that attains greatly improved accuracy.\n",
    "\n",
    "We mention that the task of assigning breed to dogs from images is considered exceptionally challenging.  To see why, consider that *even a human* would have trouble distinguishing between a Brittany and a Welsh Springer Spaniel.  \n",
    "\n",
    "Brittany | Welsh Springer Spaniel\n",
    "- | - \n",
    "<img src=\"images/Brittany_02625.jpg\" width=\"100\"> | <img src=\"images/Welsh_springer_spaniel_08203.jpg\" width=\"200\">\n",
    "\n",
    "It is not difficult to find other dog breed pairs with minimal inter-class variation (for instance, Curly-Coated Retrievers and American Water Spaniels).  \n",
    "\n",
    "Curly-Coated Retriever | American Water Spaniel\n",
    "- | -\n",
    "<img src=\"images/Curly-coated_retriever_03896.jpg\" width=\"200\"> | <img src=\"images/American_water_spaniel_00648.jpg\" width=\"200\">\n",
    "\n",
    "\n",
    "Likewise, recall that labradors come in yellow, chocolate, and black.  Your vision-based algorithm will have to conquer this high intra-class variation to determine how to classify all of these different shades as the same breed.  \n",
    "\n",
    "Yellow Labrador | Chocolate Labrador | Black Labrador\n",
    "- | -\n",
    "<img src=\"images/Labrador_retriever_06457.jpg\" width=\"150\"> | <img src=\"images/Labrador_retriever_06455.jpg\" width=\"240\"> | <img src=\"images/Labrador_retriever_06449.jpg\" width=\"220\">\n",
    "\n",
    "We also mention that random chance presents an exceptionally low bar: setting aside the fact that the classes are slightly imabalanced, a random guess will provide a correct answer roughly 1 in 133 times, which corresponds to an accuracy of less than 1%.  \n",
    "\n",
    "Remember that the practice is far ahead of the theory in deep learning.  Experiment with many different architectures, and trust your intuition.  And, of course, have fun!\n",
    "\n",
    "### (IMPLEMENTATION) Specify Data Loaders for the Dog Dataset\n",
    "\n",
    "Use the code cell below to write three separate [data loaders](http://pytorch.org/docs/stable/data.html#torch.utils.data.DataLoader) for the training, validation, and test datasets of dog images (located at `dog_images/train`, `dog_images/valid`, and `dog_images/test`, respectively).  You may find [this documentation on custom datasets](http://pytorch.org/docs/stable/torchvision/datasets.html) to be a useful resource.  If you are interested in augmenting your training and/or validation data, check out the wide variety of [transforms](http://pytorch.org/docs/stable/torchvision/transforms.html?highlight=transform)!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from torchvision import datasets\n",
    "from PIL import ImageFile\n",
    "\n",
    "ImageFile.LOAD_TRUNCATED_IMAGES = True\n",
    "\n",
    "### TODO: Write data loaders for training, validation, and test sets\n",
    "## Specify appropriate transforms, and batch_sizes\n",
    "num_workers = 0\n",
    "batch_size = 20\n",
    "\n",
    "\n",
    "transform = {\n",
    "    'train': transforms.Compose([\n",
    "                     transforms.Resize(256),\n",
    "                     transforms.RandomResizedCrop(224),\n",
    "                     transforms.RandomHorizontalFlip(),\n",
    "                     transforms.RandomRotation(10),\n",
    "                     transforms.ToTensor(),\n",
    "                     transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])]),\n",
    "\n",
    "    'valid': transforms.Compose([\n",
    "                     transforms.Resize(256),\n",
    "                     transforms.CenterCrop(224),\n",
    "                     transforms.ToTensor(),\n",
    "                     transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])]),\n",
    "\n",
    "    'test': transforms.Compose([\n",
    "                     transforms.Resize(256),\n",
    "                     transforms.CenterCrop(224),\n",
    "                     transforms.ToTensor(),\n",
    "                     transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])])\n",
    "\n",
    "}\n",
    "    \n",
    "image_datasets = {\n",
    "    'train': datasets.ImageFolder('/data/dog_images/train', transform=transform['train']),\n",
    "    'valid': datasets.ImageFolder('/data/dog_images/valid', transform = transform['valid']),\n",
    "    'test': datasets.ImageFolder('/data/dog_images/test', transform = transform['test'])\n",
    "}\n",
    "\n",
    "data_loaders = {\n",
    "    'train': torch.utils.data.DataLoader(image_datasets['train'], batch_size = batch_size, shuffle = True,  num_workers = num_workers),\n",
    "    'valid': torch.utils.data.DataLoader(image_datasets['valid'], batch_size = batch_size, shuffle = True, num_workers = num_workers),\n",
    "    'test': torch.utils.data.DataLoader(image_datasets['test'], batch_size = batch_size, shuffle = True, num_workers = num_workers)\n",
    "}\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's first analyze the data we'll be working with"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are 6680 entries in the training set\n",
      "there are 835 entries in the validation set\n",
      "there are 836 entries in the test set\n",
      "there are 133 categorized dog breeds\n"
     ]
    }
   ],
   "source": [
    "print('there are {} entries in the training set'.format(len(image_datasets['train'])))\n",
    "print('there are {} entries in the validation set'.format(len(image_datasets['valid'])))\n",
    "print('there are {} entries in the test set'.format(len(image_datasets['test'])))\n",
    "print('there are {} categorized dog breeds'.format(len(image_datasets['train'].classes)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Question 3:** Describe your chosen procedure for preprocessing the data. \n",
    "- How does your code resize the images (by cropping, stretching, etc)?  What size did you pick for the input tensor, and why?\n",
    "- Did you decide to augment the dataset?  If so, how (through translations, flips, rotations, etc)?  If not, why not?\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Answer**:\n",
    "\n",
    "- I chose to resize the image to 256 and then cropping the image to 224 to reduce run time\n",
    "- My augmentation of the training data includes random horizontal flips and random rotations of 10 degrees"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (IMPLEMENTATION) Model Architecture\n",
    "\n",
    "Create a CNN to classify dog breed.  Use the template in the code cell below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Net(\n",
      "  (conv1): Conv2d(3, 32, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
      "  (conv2): Conv2d(32, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "  (conv3): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "  (conv4): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "  (pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "  (fc1): Linear(in_features=12544, out_features=1024, bias=True)\n",
      "  (fc2): Linear(in_features=1024, out_features=512, bias=True)\n",
      "  (fc3): Linear(in_features=512, out_features=133, bias=True)\n",
      "  (dropout): Dropout(p=0.2)\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "\n",
    "# define the CNN architecture\n",
    "class Net(nn.Module):\n",
    "    ### TODO: choose an architecture, and complete the class\n",
    "    def __init__(self):\n",
    "        super(Net, self).__init__()\n",
    "        ## Define layers of a CNN\n",
    "        self.conv1 = nn.Conv2d(3, 32, 3, stride=2, padding=1)      \n",
    "        self.conv2 = nn.Conv2d(32, 64, 3, padding=1)\n",
    "        self.conv3 = nn.Conv2d(64, 128, 3, padding=1)\n",
    "        self.conv4 = nn.Conv2d(128, 256, 3, padding=1)\n",
    "        \n",
    "        self.pool = nn.MaxPool2d(2,2)\n",
    "        \n",
    "        self.fc1 = nn.Linear(7*7*256, 1024)\n",
    "        self.fc2 = nn.Linear(1024, 512)\n",
    "        self.fc3 = nn.Linear(512, 133)\n",
    "        \n",
    "        self.dropout = nn.Dropout(p=0.20)\n",
    "    def forward(self, x):\n",
    "        ## Define forward behavior\n",
    "        x = self.pool(F.relu(self.conv1(x)))\n",
    "        x = self.pool(F.relu(self.conv2(x)))\n",
    "        x = self.pool(F.relu(self.conv3(x)))\n",
    "        x = self.pool(F.relu(self.conv4(x)))\n",
    "        x = x.view(x.size(0), -1)\n",
    "        x = F.relu(self.fc1(self.dropout(x)))\n",
    "        x = F.relu(self.fc2(self.dropout(x)))\n",
    "        x = self.fc3(self.dropout(x))\n",
    "        return x\n",
    "\n",
    "#-#-# You so NOT have to modify the code below this line. #-#-#\n",
    "\n",
    "# instantiate the CNN\n",
    "model_scratch = Net()\n",
    "print(model_scratch)\n",
    "\n",
    "# move tensors to GPU if CUDA is available\n",
    "if use_cuda:\n",
    "    model_scratch.cuda()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Question 4:__ Outline the steps you took to get to your final CNN architecture and your reasoning at each step.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Answer:__ \n",
    "\n",
    "**My resulting architecture is based partly on what we've done in class so far, as well as some trial and error to produce the highest prediction**\n",
    "\n",
    "I decided to implement my model with 4 convolution layers followed by 3 fully connected layers. More convolution layers may lead to more sophisticated predictions as it picks up more detail in the deeper layers, however, too many layers may result in overfitting and lengthy computations. I decided to go with 4 in my model. The fully connected layers are used to map the inputs to one of the 133 possible dog breeds. \n",
    "\n",
    "To help with overfitting and better predictions, I've also added maxpool layers inbetween convolution layers to downsample the image by a factor of 2, as well as dropout layers inbetween fully connected layers for more randomness.\n",
    "\n",
    "Lastly, relu activation was used for the outputs of each conv. and fc. layers."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (IMPLEMENTATION) Specify Loss Function and Optimizer\n",
    "\n",
    "Use the next code cell to specify a [loss function](http://pytorch.org/docs/stable/nn.html#loss-functions) and [optimizer](http://pytorch.org/docs/stable/optim.html).  Save the chosen loss function as `criterion_scratch`, and the optimizer as `optimizer_scratch` below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch.optim as optim\n",
    "\n",
    "### TODO: select loss function\n",
    "criterion_scratch = nn.CrossEntropyLoss()\n",
    "\n",
    "### TODO: select optimizer\n",
    "optimizer_scratch = optim.SGD(model_scratch.parameters(), lr = 0.05)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (IMPLEMENTATION) Train and Validate the Model\n",
    "\n",
    "Train and validate your model in the code cell below.  [Save the final model parameters](http://pytorch.org/docs/master/notes/serialization.html) at filepath `'model_scratch.pt'`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "def train(n_epochs, loaders, model, optimizer, criterion, use_cuda, save_path):\n",
    "    \"\"\"returns trained model\"\"\"\n",
    "    # initialize tracker for minimum validation loss\n",
    "    valid_loss_min = np.Inf \n",
    "    \n",
    "    for epoch in tqdm(range(1, n_epochs+1)):\n",
    "        # initialize variables to monitor training and validation loss\n",
    "        train_loss = 0.0\n",
    "        valid_loss = 0.0\n",
    "        \n",
    "        ###################\n",
    "        # train the model #\n",
    "        ###################\n",
    "        model.train()\n",
    "        for batch_idx, (data, target) in enumerate(loaders['train']):\n",
    "            # move to GPU\n",
    "            if use_cuda:\n",
    "                data, target = data.cuda(), target.cuda()\n",
    "            ## find the loss and update the model parameters accordingly\n",
    "            ## record the average training loss, using something like\n",
    "            ## train_loss = train_loss + ((1 / (batch_idx + 1)) * (loss.data - train_loss))\n",
    "            # clear the gradients of all optimized variables\n",
    "            optimizer.zero_grad()\n",
    "            # forward pass: compute predicted outputs by passing inputs to the model\n",
    "            output = model(data)\n",
    "            # calculate the loss\n",
    "            loss = criterion(output, target)\n",
    "            # backward pass: compute gradient of the loss with respect to model parameters\n",
    "            loss.backward()\n",
    "            # perform a single optimization step (parameter update)\n",
    "            optimizer.step()\n",
    "            # update running training loss\n",
    "            train_loss += ((1 / (batch_idx + 1)) * (loss.data - train_loss))\n",
    "        ######################    \n",
    "        # validate the model #\n",
    "        ######################\n",
    "        model.eval()\n",
    "        for batch_idx, (data, target) in enumerate(loaders['valid']):\n",
    "            # move to GPU\n",
    "            if use_cuda:\n",
    "                data, target = data.cuda(), target.cuda()\n",
    "            ## update the average validation loss\n",
    "                    # forward pass: compute predicted outputs by passing inputs to the model\n",
    "            output = model(data)\n",
    "            # calculate the loss\n",
    "            loss = criterion(output, target)\n",
    "            # update running validation loss \n",
    "            valid_loss += loss.item()*data.size(0)\n",
    "        \n",
    "        # print training/validation statistics \n",
    "        # calculate average loss over an epoch\n",
    "        train_loss = train_loss/len(loaders['train'].dataset)\n",
    "        valid_loss = valid_loss/len(loaders['valid'].dataset)\n",
    " \n",
    "\n",
    "            \n",
    "        # print training/validation statistics \n",
    "        print('Epoch: {} \\tTraining Loss: {:.6f} \\tValidation Loss: {:.6f}'.format(\n",
    "            epoch, \n",
    "            train_loss,\n",
    "            valid_loss\n",
    "            ))\n",
    "        \n",
    "        ## TODO: save the model if validation loss has decreased\n",
    "        if valid_loss <= valid_loss_min:\n",
    "            print('Validation loss decreased ({:.6f} --> {:.6f}).  Saving model ...'.format(\n",
    "            valid_loss_min,\n",
    "            valid_loss))\n",
    "            torch.save(model.state_dict(), save_path)\n",
    "            valid_loss_min = valid_loss    \n",
    "    # return trained model\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  0%|          | 0/20 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 1 \tTraining Loss: 0.000732 \tValidation Loss: 4.873596\n",
      "Validation loss decreased (inf --> 4.873596).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 10%|█         | 2/20 [03:41<34:26, 114.80s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 2 \tTraining Loss: 0.000729 \tValidation Loss: 4.861164\n",
      "Validation loss decreased (4.873596 --> 4.861164).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 15%|█▌        | 3/20 [05:22<31:19, 110.56s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 3 \tTraining Loss: 0.000723 \tValidation Loss: 4.747886\n",
      "Validation loss decreased (4.861164 --> 4.747886).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 20%|██        | 4/20 [07:03<28:44, 107.76s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 4 \tTraining Loss: 0.000711 \tValidation Loss: 4.653239\n",
      "Validation loss decreased (4.747886 --> 4.653239).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 25%|██▌       | 5/20 [08:44<26:25, 105.68s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 5 \tTraining Loss: 0.000705 \tValidation Loss: 4.544545\n",
      "Validation loss decreased (4.653239 --> 4.544545).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 30%|███       | 6/20 [10:25<24:19, 104.26s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 6 \tTraining Loss: 0.000689 \tValidation Loss: 4.438749\n",
      "Validation loss decreased (4.544545 --> 4.438749).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 35%|███▌      | 7/20 [12:06<22:23, 103.36s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 7 \tTraining Loss: 0.000681 \tValidation Loss: 4.400323\n",
      "Validation loss decreased (4.438749 --> 4.400323).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 40%|████      | 8/20 [13:47<20:31, 102.62s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 8 \tTraining Loss: 0.000673 \tValidation Loss: 4.316474\n",
      "Validation loss decreased (4.400323 --> 4.316474).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 45%|████▌     | 9/20 [15:28<18:42, 102.03s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 9 \tTraining Loss: 0.000666 \tValidation Loss: 4.234505\n",
      "Validation loss decreased (4.316474 --> 4.234505).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 50%|█████     | 10/20 [17:09<16:57, 101.79s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 10 \tTraining Loss: 0.000657 \tValidation Loss: 4.163637\n",
      "Validation loss decreased (4.234505 --> 4.163637).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 55%|█████▌    | 11/20 [18:50<15:14, 101.65s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 11 \tTraining Loss: 0.000649 \tValidation Loss: 4.142303\n",
      "Validation loss decreased (4.163637 --> 4.142303).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 60%|██████    | 12/20 [20:31<13:31, 101.48s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 12 \tTraining Loss: 0.000642 \tValidation Loss: 4.080663\n",
      "Validation loss decreased (4.142303 --> 4.080663).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 65%|██████▌   | 13/20 [22:13<11:50, 101.48s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 13 \tTraining Loss: 0.000636 \tValidation Loss: 4.033627\n",
      "Validation loss decreased (4.080663 --> 4.033627).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 70%|███████   | 14/20 [23:54<10:08, 101.40s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 14 \tTraining Loss: 0.000627 \tValidation Loss: 3.988966\n",
      "Validation loss decreased (4.033627 --> 3.988966).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 75%|███████▌  | 15/20 [25:34<08:25, 101.09s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 15 \tTraining Loss: 0.000620 \tValidation Loss: 3.910948\n",
      "Validation loss decreased (3.988966 --> 3.910948).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 80%|████████  | 16/20 [27:15<06:43, 100.88s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 16 \tTraining Loss: 0.000615 \tValidation Loss: 3.905368\n",
      "Validation loss decreased (3.910948 --> 3.905368).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 85%|████████▌ | 17/20 [28:55<05:02, 100.73s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 17 \tTraining Loss: 0.000607 \tValidation Loss: 3.947918\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 90%|█████████ | 18/20 [30:35<03:21, 100.61s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 18 \tTraining Loss: 0.000601 \tValidation Loss: 3.769850\n",
      "Validation loss decreased (3.905368 --> 3.769850).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 95%|█████████▌| 19/20 [32:15<01:40, 100.38s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 19 \tTraining Loss: 0.000592 \tValidation Loss: 3.915660\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 20/20 [33:55<00:00, 100.23s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 20 \tTraining Loss: 0.000585 \tValidation Loss: 3.753124\n",
      "Validation loss decreased (3.769850 --> 3.753124).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "# train the model\n",
    "model_scratch = train(20, data_loaders, model_scratch, optimizer_scratch, criterion_scratch, use_cuda, 'model_scratch.pt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load the model that got the best validation accuracy\n",
    "model_scratch.load_state_dict(torch.load('model_scratch.pt'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (IMPLEMENTATION) Test the Model\n",
    "\n",
    "Try out your model on the test dataset of dog images.  Use the code cell below to calculate and print the test loss and accuracy.  Ensure that your test accuracy is greater than 10%."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test Loss: 3.703781\n",
      "\n",
      "\n",
      "Test Accuracy: 10% (86/836)\n"
     ]
    }
   ],
   "source": [
    "def test(loaders, model, criterion, use_cuda):\n",
    "\n",
    "    # monitor test loss and accuracy\n",
    "    test_loss = 0.\n",
    "    correct = 0.\n",
    "    total = 0.\n",
    "\n",
    "    model.eval()\n",
    "    for batch_idx, (data, target) in enumerate(loaders['test']):\n",
    "        # move to GPU\n",
    "        if use_cuda:\n",
    "            data, target = data.cuda(), target.cuda()\n",
    "        # forward pass: compute predicted outputs by passing inputs to the model\n",
    "        output = model(data)\n",
    "        # calculate the loss\n",
    "        loss = criterion(output, target)\n",
    "        # update average test loss \n",
    "        test_loss = test_loss + ((1 / (batch_idx + 1)) * (loss.data - test_loss))\n",
    "        # convert output probabilities to predicted class\n",
    "        pred = output.data.max(1, keepdim=True)[1]\n",
    "        # compare predictions to true label\n",
    "        correct += np.sum(np.squeeze(pred.eq(target.data.view_as(pred))).cpu().numpy())\n",
    "        total += data.size(0)\n",
    "            \n",
    "    print('Test Loss: {:.6f}\\n'.format(test_loss))\n",
    "\n",
    "    print('\\nTest Accuracy: %2d%% (%2d/%2d)' % (\n",
    "        100. * correct / total, correct, total))\n",
    "\n",
    "# call test function    \n",
    "test(data_loaders, model_scratch, criterion_scratch, use_cuda)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "<a id='step4'></a>\n",
    "## Step 4: Create a CNN to Classify Dog Breeds (using Transfer Learning)\n",
    "\n",
    "You will now use transfer learning to create a CNN that can identify dog breed from images.  Your CNN must attain at least 60% accuracy on the test set.\n",
    "\n",
    "### (IMPLEMENTATION) Specify Data Loaders for the Dog Dataset\n",
    "\n",
    "Use the code cell below to write three separate [data loaders](http://pytorch.org/docs/master/data.html#torch.utils.data.DataLoader) for the training, validation, and test datasets of dog images (located at `dogImages/train`, `dogImages/valid`, and `dogImages/test`, respectively). \n",
    "\n",
    "If you like, **you are welcome to use the same data loaders from the previous step**, when you created a CNN from scratch."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "## TODO: Specify data loaders\n",
    "loaders_transfer= {\n",
    "    'train': torch.utils.data.DataLoader(image_datasets['train'], batch_size = batch_size, shuffle = True,  num_workers = num_workers),\n",
    "    'valid': torch.utils.data.DataLoader(image_datasets['valid'], batch_size = batch_size, shuffle = True, num_workers = num_workers),\n",
    "    'test': torch.utils.data.DataLoader(image_datasets['test'], batch_size = batch_size, shuffle = True, num_workers = num_workers)\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (IMPLEMENTATION) Model Architecture\n",
    "\n",
    "Use transfer learning to create a CNN to classify dog breed.  Use the code cell below, and save your initialized model as the variable `model_transfer`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VGG(\n",
      "  (features): Sequential(\n",
      "    (0): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (1): ReLU(inplace)\n",
      "    (2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (3): ReLU(inplace)\n",
      "    (4): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "    (5): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (6): ReLU(inplace)\n",
      "    (7): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (8): ReLU(inplace)\n",
      "    (9): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "    (10): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (11): ReLU(inplace)\n",
      "    (12): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (13): ReLU(inplace)\n",
      "    (14): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (15): ReLU(inplace)\n",
      "    (16): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "    (17): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (18): ReLU(inplace)\n",
      "    (19): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (20): ReLU(inplace)\n",
      "    (21): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (22): ReLU(inplace)\n",
      "    (23): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "    (24): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (25): ReLU(inplace)\n",
      "    (26): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (27): ReLU(inplace)\n",
      "    (28): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
      "    (29): ReLU(inplace)\n",
      "    (30): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "  )\n",
      "  (classifier): Sequential(\n",
      "    (0): Linear(in_features=25088, out_features=4096, bias=True)\n",
      "    (1): ReLU(inplace)\n",
      "    (2): Dropout(p=0.5)\n",
      "    (3): Linear(in_features=4096, out_features=4096, bias=True)\n",
      "    (4): ReLU(inplace)\n",
      "    (5): Dropout(p=0.5)\n",
      "    (6): Linear(in_features=4096, out_features=133, bias=True)\n",
      "  )\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "import torchvision.models as models\n",
    "import torch.nn as nn\n",
    "\n",
    "## TODO: Specify model architecture \n",
    "model_transfer = models.vgg16(pretrained=True)\n",
    "\n",
    "# Freeze training for all \"features\" layers\n",
    "for param in model_transfer.features.parameters():\n",
    "    param.requires_grad = False\n",
    "\n",
    "# replace the last layer with our own to specify 133 output classes\n",
    "model_transfer.classifier[6] = nn.Linear(4096, 133)\n",
    "\n",
    "if use_cuda:\n",
    "    model_transfer = model_transfer.cuda()\n",
    "\n",
    "print(model_transfer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Question 5:__ Outline the steps you took to get to your final CNN architecture and your reasoning at each step.  Describe why you think the architecture is suitable for the current problem."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Answer:__ \n",
    "I decided to use the VGG16 model as my transfer model as it has been proven to be quite successful for image classification tasks, however I do acknowledge that other models are also available (such as ResNet). I began by loading in the vgg16 model as pretrained, and then freezing all training in the feature layers. \n",
    "\n",
    "After specifying the model, I changed the final output layer (the third fully connected layer) so that I can specify my output parameter for this project, 133 output dog breeds in this case. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (IMPLEMENTATION) Specify Loss Function and Optimizer\n",
    "\n",
    "Use the next code cell to specify a [loss function](http://pytorch.org/docs/master/nn.html#loss-functions) and [optimizer](http://pytorch.org/docs/master/optim.html).  Save the chosen loss function as `criterion_transfer`, and the optimizer as `optimizer_transfer` below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "criterion_transfer = nn.CrossEntropyLoss()\n",
    "optimizer_transfer = optim.SGD(model_transfer.classifier.parameters(), lr = 0.01)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (IMPLEMENTATION) Train and Validate the Model\n",
    "\n",
    "Train and validate your model in the code cell below.  [Save the final model parameters](http://pytorch.org/docs/master/notes/serialization.html) at filepath `'model_transfer.pt'`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  0%|          | 0/10 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 1 \tTraining Loss: 0.000351 \tValidation Loss: 0.668810\n",
      "Validation loss decreased (inf --> 0.668810).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 10%|█         | 1/10 [02:58<26:45, 178.41s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 2 \tTraining Loss: 0.000218 \tValidation Loss: 0.580686\n",
      "Validation loss decreased (0.668810 --> 0.580686).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 20%|██        | 2/10 [05:56<23:46, 178.35s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 3 \tTraining Loss: 0.000194 \tValidation Loss: 0.570502\n",
      "Validation loss decreased (0.580686 --> 0.570502).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 30%|███       | 3/10 [08:54<20:47, 178.19s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 4 \tTraining Loss: 0.000182 \tValidation Loss: 0.526614\n",
      "Validation loss decreased (0.570502 --> 0.526614).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 40%|████      | 4/10 [11:52<17:49, 178.30s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 5 \tTraining Loss: 0.000176 \tValidation Loss: 0.475319\n",
      "Validation loss decreased (0.526614 --> 0.475319).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 50%|█████     | 5/10 [14:51<14:52, 178.41s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 6 \tTraining Loss: 0.000166 \tValidation Loss: 0.430776\n",
      "Validation loss decreased (0.475319 --> 0.430776).  Saving model ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 70%|███████   | 7/10 [20:47<08:54, 178.04s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 7 \tTraining Loss: 0.000162 \tValidation Loss: 0.445767\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 80%|████████  | 8/10 [23:44<05:55, 177.81s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 8 \tTraining Loss: 0.000154 \tValidation Loss: 0.483813\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 90%|█████████ | 9/10 [26:41<02:57, 177.55s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 9 \tTraining Loss: 0.000156 \tValidation Loss: 0.435903\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 10/10 [29:38<00:00, 177.49s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 10 \tTraining Loss: 0.000150 \tValidation Loss: 0.435255\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "# train the model\n",
    "model_transfer = train(10, loaders_transfer, model_transfer, optimizer_transfer, criterion_transfer, use_cuda, 'model_transfer.pt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load the model that got the best validation accuracy (uncomment the line below)\n",
    "model_transfer.load_state_dict(torch.load('model_transfer.pt'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (IMPLEMENTATION) Test the Model\n",
    "\n",
    "Try out your model on the test dataset of dog images. Use the code cell below to calculate and print the test loss and accuracy.  Ensure that your test accuracy is greater than 60%."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test Loss: 0.468442\n",
      "\n",
      "\n",
      "Test Accuracy: 84% (707/836)\n"
     ]
    }
   ],
   "source": [
    "test(loaders_transfer, model_transfer, criterion_transfer, use_cuda)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### (IMPLEMENTATION) Predict Dog Breed with the Model\n",
    "\n",
    "Write a function that takes an image path as input and returns the dog breed (`Affenpinscher`, `Afghan hound`, etc) that is predicted by your model.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "### TODO: Write a function that takes a path to an image as input\n",
    "### and returns the dog breed that is predicted by the model.\n",
    "\n",
    "# list of class names by index, i.e. a name can be accessed like class_names[0]\n",
    "class_names = [item[4:].replace(\"_\", \" \") for item in loaders_transfer['train'].dataset.classes]\n",
    "\n",
    "def predict_breed_transfer(img_path):\n",
    "    # load the image and return the predicted breed\n",
    "    image = Image.open(img_path).convert('RGB')\n",
    "    prediction_transform = transforms.Compose([transforms.Resize(size=(224, 224)),\n",
    "                                     transforms.ToTensor(), \n",
    "                                     transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])])\n",
    "\n",
    "    # discard the transparent, alpha channel (that's the :3) and add the batch dimension\n",
    "    image = prediction_transform(image)[:3,:,:].unsqueeze(0)\n",
    "    image = image.cuda()\n",
    "    \n",
    "    \n",
    "    \n",
    "    model_transfer.eval()\n",
    "    idx = torch.argmax(model_transfer(image))\n",
    "    return class_names[idx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Mastiff'"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predict_breed_transfer(dog_files[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "<a id='step5'></a>\n",
    "## Step 5: Write your Algorithm\n",
    "\n",
    "Write an algorithm that accepts a file path to an image and first determines whether the image contains a human, dog, or neither.  Then,\n",
    "- if a __dog__ is detected in the image, return the predicted breed.\n",
    "- if a __human__ is detected in the image, return the resembling dog breed.\n",
    "- if __neither__ is detected in the image, provide output that indicates an error.\n",
    "\n",
    "You are welcome to write your own functions for detecting humans and dogs in images, but feel free to use the `face_detector` and `human_detector` functions developed above.  You are __required__ to use your CNN from Step 4 to predict dog breed.  \n",
    "\n",
    "Some sample output for our algorithm is provided below, but feel free to design your own user experience!\n",
    "\n",
    "![Sample Human Output](images/sample_human_output.png)\n",
    "\n",
    "\n",
    "### (IMPLEMENTATION) Write your Algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "### TODO: Write your algorithm.\n",
    "### Feel free to use as many code cells as needed.\n",
    "\n",
    "def run_app(img_path):\n",
    "    img = Image.open(img_path)\n",
    "    plt.imshow(img)\n",
    "    plt.show()\n",
    "    ## handle cases for a human face, dog, and neither\n",
    "    if dog_detector(img_path):\n",
    "        prediction = predict_breed_transfer(img_path)\n",
    "        print(\"dog detected, this looks to be a {}\".format(prediction))\n",
    "    elif face_detector(img_path):\n",
    "        prediction = predict_breed_transfer(img_path)\n",
    "        print(\"human detected, as a dog you'd be a {}\".format(prediction))\n",
    "    else:\n",
    "        print(\"what are you..?\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "<a id='step6'></a>\n",
    "## Step 6: Test Your Algorithm\n",
    "\n",
    "In this section, you will take your new algorithm for a spin!  What kind of dog does the algorithm think that _you_ look like?  If you have a dog, does it predict your dog's breed accurately?  If you have a cat, does it mistakenly think that your cat is a dog?\n",
    "\n",
    "### (IMPLEMENTATION) Test Your Algorithm on Sample Images!\n",
    "\n",
    "Test your algorithm at least six images on your computer.  Feel free to use any images you like.  Use at least two human and two dog images.  \n",
    "\n",
    "__Question 6:__ Is the output better than you expected :) ?  Or worse :( ?  Provide at least three possible points of improvement for your algorithm."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Answer:__ \n",
    "\n",
    "The model predicted all pictures correctly! If the picture was a human, the model detected human and provided a prediction of dog breed, if the picture was a dog, the model predicted the appropriate dog breed\n",
    "\n",
    "Areas of improvement includes:\n",
    "\n",
    "- hyperparameter tuning to obtain higher prediction accruacy\n",
    "- experimenting with other models to see if more accurate/efficient\n",
    "- maybe use functions for some repetitive codes (image transformations for example)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f569969d400>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "human detected, as a dog you'd be a Beagle\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f56abbf3c88>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "human detected, as a dog you'd be a Dachshund\n"
     ]
    },
    {
     "data": {
      "image/png": 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32FSjAtR9g/eRfthNmt7hY6BMEpIslfkcA9vthnKRAgHvBcZ3RhNigzEK71NCAKsNWZYNJNkxchGCgxDo+w7neswwNt57gfROoidZluBcOxnX0EeapmGz2bLdbumbPW1X0/UNy9CjVMQkghoyo+ldinWJbBTGCviOI8k97vTHEOyDxRmkL51zoAJnlyeoGLnszgnec7/ZCVSPnru7O3lP9OJSBS9cjFFYJXoUH4YoiImogWBXA8pQcYiMDbyXPMzMDZ7mTcQFP7nZ43eI8ai6GHURIahhwUdUVCh93MxGVKG1m2QF6K/zbMfrzUT0/y7t22Es4hFZPA6LzsNFIxkpdER8EJZCjSIVZkTRaNXFNwzOowwSRQGCOg7AsYOFoxiNxZyXGI3FyGaPYSmtJSRoUBidYK2Qc9F5uuBIU4tWmkSJn6uDF5gZIokx1L3DagPGDlyDZlnkE+JZlCVJkuCCI2qo6loWgRbNSNO1GO0BzXK5JCmWFIsFdSuG5urJE15++gnn5+eUZYlNBsjue3zfUVV7AJpmi3c9eZ4Tg/RrkeekSY4xhiJLCM7TdR2+7wafG5Q1EC0KQ4iK3jv6vscYQ9u2+BjwTtym7WHP7e0tm82G0NW0fU/TdfgYUUZLxKSpWRsDNgGjSRVYBQFN7x2gJxc1GZCPdx3edQSjwGoY0AzBieYlS0S7UQQ0Ynyb+kBV7bm5+UDsPaGPoquInsQokXy5nhA8IQawQ8QmxCOXMU06sQ1qiMjpMbIxkObjZuOcuLTGRKxlQg8hDsiDMfoxkvSCqHWci63jRG5KX4g7+XC9HH8XNPZPXJuz9q0wFscIxqDGjPHIIEwGQeLtg90dFqlAsOAH5OAH1yMe+Y8x1CQdPxJDblj8Go0QQCOaGBWRfecnURaD9kPCXaIz0MpijRWuYghPGW0I3uOiRkfZmfMsJ0sSluWCsyzHuIiJgVQpVIh09YF6d09f11gUy3Ihockofm+C5uzpJZvthq9ev6Yn0HuPMobLJ1dUTYdznlevPuWzT7/DD37wA569+kQWlVbkWSmuRy7IZLO5xfmGpq54/+Y1+8OGtm6wiQEc6+UCnWf46On7QPCOVtW0bcvl5SV1XfP6zVccDgeurq5Yr9fiRiiFSTN0lnE4HNg2DR/ud4NrYGm7jpvbW969e8eHDx/YbrcE31OWJevlgsZ5ksWCdZaT5hk2TfAxsN1u8bv9FC0BRexuxJAVC1arFQDb62vu7+8o85zFomS5LCUaUFX0bUt5skJrhQvCBy2XSz558ZJFvmCRL9jsNtzc3eIrJwRoFJ3HKLDTWoMxBMB5jw9eCFulJ1dYiPYo0V4dB3I8EPxRzNd13eReW+snEVYcDW8YEdOIlseInZ/m8XHTtEA36CyS2WvqwXXf6tDpP6WNbsQYj5YwtZog5hgNeaiIG02HDJLnCANHRDHnLcbPmcJa8WGYNYRA8ODdKMAZoyrjewfp84MBE8NklcYoC2FANkqTpinr5ZL1csV6uWKpDbFpUL0nM0aUm65HhUhT7QWdBBFypWnKYrEmTe1ECFZtQ9O19N5j05QuKLK04Lt/+n1++MM/5/nz5zx//pIA1HVNsSgpVyXL9YIQAm1bc3Z2Rt1uITryIkWbNayW5HlKkac8e/aMLC3o+56uc0L4OUddB5qmoaoO1E1DVdccqoo0yyiKgjzPycoFZdvTtD1df2C3F54lSXNsAkFpDk3L+5tbbm5u0DFwdnZGXizQaUqxWHJ+ecVyvSYploQIh7bD9Y6udUTlBXt2PUmSoIpcVJPe4/uWZr8H5zA6kg7c1WG3p2krjIY8K4d5ZsF70jTn/PycJEm4vd9QliXvPrzlw41nX1f43mELgw6KPgb64PAu4JRwKkYnEkpFNFGPZ9rcHRiJ8nG+yWPLdi+b1bCg58rOYQ2E4Ca+4vi5aiI64+DqTL9HPbnk8wjM79q+NcZibKMxMEY6z09x5Ychp3lUIqqI804GYvDh5tbUe//IssrOHSJ47b82qOPPDN/IMwxWY+5+TKw0R5GNHtjyJEkoioL1es0qL4mHiq5p8W2HGkhO13bUh4r7uw2pTXBpS5GWrFYrTldrbGb56v1bdrvdEILs2DcNpmtx0bBan/Gd73yHzz77jNXqhCRJaL0jyzKyLJNFlaYYINURpSPWW4oi4/z8FKIguizLKIuExWIpk7qV0Gjv3MBD9MIz9B1aizEbBT910xCBNM0oFkuKtuN2c8+hbkjzgnK5wlpLFwJv372jd47N/T1pmvEkKzm7vOLq6UvOLq5YnZyxOjkBkxBQ6NRj245dXVMfGtq+I+lbiqIglgtC39HWDdV+T3U4EPzI+YjR3t7f0TUt1qTEoEh0QrQRYxLKPGVRLCjLBTbNhqmhQCs8XhSgvp+QbwziQqhR2dr3YKzMj3DU+hAR0nHkvob5pONDbcV8IxuNxYgs4oCux0iH934iRcXNdg9k4T6EB3N+fN/x8/9YOAvGDpDfj+Ei/TUhy/g6gBl0DUEFgh7fH9F6loQU4tfQhYZBmiyLZxJ5eT/jJ4BRSjt81hg+ewwF9VwNohRGa0m8spbEZkJUes92s+Fwd4dvGrpigdFQ7w9sNhvu7+8pspzOWsyJplzknJycoBPN4Rc/p+s6siwDrWnblti1ZOWaoig4OzujKApMkqCtZVUWrE9PjkawbdFmJIbBWo1dLLAajJady2jIcyEXR9FUcLKjHw6HgbxsUUok5coasrLAZimtc/imwRhLXhYs3YrkfULf94KuTk9YLpcoo3nz/h1ZWYrGJBXtx7PnL3j27BknJ2dkWQHaSvjcJhRpjkpS6r6n7Tt2uwOpF7l621RYo9htD2zv79nv90TXk2jRQzjn2G7u6fuexWpNHSMHD2masywXmLwAICsKiqZhsVhwHs6HMKpsMtd378SAcIw0KKPxrhfV5jCjVAgQAipGTADvJcdpJHcf6B9CeLBBHWclJDqZonlqQsFq4iTm0cDRfU7T9GHEJYRJOj6+54/LDTGCCnSiRLA37NqptUcSUke8U7MvH4lKC11hFTEaPBEfBiXokHA2Wt0xC3T0PbXW+KjxfiSu9VHnoYSFNtpM8nDsILTS6ZDlKHyFGXQROkISFTYoCp2SxxTTeIokotqa7u7A/nZLXzWsny3YV3vq/QHlFKvVCUVRCHGZZdweDqTLDVnIuL7fcne/BWvYHWrqTpGkOWcXL/j8Oz/g8skLzi+fSMgSiekTA01T0XcRFQqSRHJlfHCYROODl905Ruo6UB0a6spxv9nR9/2wkyXUregkmtazWCxIi5xlkmBTQ1mWGGNwneR0qCSlC4G6g2hLVufPePn593ny8hXapujijP/y5AkvvvtnfPXVV7z95a8lHGxK6l7TOoN1Cus1WieDRYc8KC7SBS45UDc37G6uKZ8paqNYath/eE1z/w7VtkTt6Q7grCEoKIoVJ6cFdetpukbmTt3Qup41QRIPY0Kap5xenKOsfI8kW2DTgq8Oe/q+p20bXAjoTIPzBBcIymMSMcC+d0QfMGowNEGiaB5xe6IK+OBF7DeIrQhxitDpAVF4HGpwf485roAy9P7ozgAYE0gCRDWGW83EVzxuf1TIYmxHOevDXXx2wcxYDDJtJdl6YejMgIeoCMEzl4k/Dr0+vt9DV+foVsyfbUIOY6qzMUKAoTARbAATjrHuEAL7fYXvWt68ecNuu0U5x9lqjes7DocDbdtirYRekwHe7/d7tkVBXpTCHzjJOUmTDG0zUIqLiwtevXrF5eUlWZbhvacdwpZqgOHO9QOsTUEFrJVnjYMxFj6iZr/f49qO6w+3Q8jOUpYlgYi1lkVZcnFxQbFckKYpaHFdQgj0duQ2OvpW4Pd6tSSxRp4tL4YoS8qrxXNOT9c8f3LFP6YZTdNgraFraw6He2LsUVEMmTFmWghJakmsQUW4vb0lzYZNJERubm64vdnQdR1dJ32VZgXlak1RJGR5yfXdrRDYzgFMxGuapiKMivI9y7JEJ5aiKMTlSQQhjYvU96DtPKU+iHo2BMEBWk2EZ4xj+oF/EE07zjvhGiTqdeTHJjfk0aIfP2MKRQ+bqDFmcgnnhOaIMv7okMW48INncCmOi/WBtkLNF/g4YGCtMPfSOXoK/cXIAzJy9PHGz55b3HmHjov9AVw0x/cZY0jsEA1RWtSaERInJOsomOn7nn3dUO32fPnll9RVxSLNqeuaxFi6ztG2ohTUxpLnIuw6NDXXN7csTxxpnrEEsqLERyT1PMt59vwlV0+fkJeFhCfHdP0QMFZJolfoB8NmMHaYkNpiogetUV2P63qaqqbaHri9vkYZQ5YVpGkq2pGiwJqUk5MTysViUFJ6MAbjHIlKaJuGpq7p+pbEai5OT4gna7I0wTU1dVuhlMKWJYsyQ12ds392xf39nbhVvqWpdhB6gmsJYYWIlyxpXg6Q29O7RvJkqgpjDH3fc317y93dhu12S14sODk5IS+XnF5csj45wRjD2+uhbwb+ShLZBg3LoCVhyL+wWUqxKNlXB1KbUA/jLa5JIBoh4eMoCJwMA5NLOi3seEz6eqzTkaS0o2EQI20mN+Kb2txlHt83GsBx3s43w8f3/F3at8hYyOIfychR3jr/8jFGjIUY9NQBYajfkiQJCjPUQUBYa+dwThSPo6GYZ+F9k0GaW+9xJxoHSJNAYidDkaap1KxQWoRYIWL7gEWTJQmFFZTQ13uapmW3O9DWDekq4X5Xc7Y+YX16zmFf07qeRYCgDdFYfIB93+MPFWdPn/K8XFKu16ANaVawXC7RNuV2u+Pwt/8XZVmS5znOOfLMkOUJMUayxJJnKVmaCjdhE7r9gb4XxNF1HX3dgZNCMqvFWpK70pRlsSQtchaLBWVZUpaldHbvGOLU+L7HJKlEH3xHu7uX5KUYCc7z9te/GFwZUSl6LxENYwx9s2e5LMlLRZFH2sMNXQWVtdzfJngfMWnCyfqMJMu5fv+Ot69/xe3mBpsm7A41h0PNu7cfuL6+JkZ4/vwZJxdPSNKSpMhpXc+Xv/w5v/ryDev1mtPTU8pckv1skpDluQjIilwWIZHY9yilKcuSxUIiSUkiLtnt9p7gAiaxKIMQ8VrRe4/repwaeYMhFD+ginF+H38fOIgAo1pZGxGWzzmxcX6O/x95ivlrY72VkQAfk/PGIj/fxPv9U9q3xlhIBCOi1OO/P1zI8scgoaEwWnHPKJKS9HWIwQ2dfkQWj6HY3AI/LjTymLWerotHCJskCZmVTEkTQBmwUZNqS5nl8prWqLQjTVPKcoGKCq0Mu90eFWC1XJDkBWW2Yrk+IQBN5+h9xNqEpnc44yjTlMVqjTYJ+aLkxfNXvL++4ebmhhCCRFxWKwnDJorVekGSGIoslfR5AtF5mt2Ow0788JFsUy6QaUtSrlDKyIKeJ+mNkzNqCVNOIcBI27aUxZCQVdVsN3dU+wM+9BDiQJYeqKqK3rsjPCbiXcOzJ0/JshSrInVzwFo7Gb0QISWwP2wJ2y1v373m3XtJOd/tdjR1x3a75+bujtu7LRcXF5ycXvDk2XMWqzXOBZruwN39ZtqttRZhV9t3tH035BgFlNGT8Y8xEpUU/Dk/OZX37XY0XTvUM5ENJCmSaS6Nu72PYVCGRkJ0hDDf1SNjda3JaDDWRokDZ+bQzAWFD0OgX5cCHD9rRBvjfB7H9/eVefrtMBbTTm8mK6swDwwFME3aaVErUbeNLP/x/8fOGn3Rx67HY85iLngBSZ2ek0lfj4Ic3RozCMYUoEN4UOUIhkH0AWtS0jSglGF7v6eru8FlSFis1qS5QN+mbeijJzQ1PsDV6oSTs1Mur64waUa5WHF2cc77uzv2laCEGOO0u5SZkmQzlU6TJfSik9jv7umbdkIWwfnJJ0+STEK59aDlsJYsy0iNnWp5jPC96zpAPvPuw3sO+x23H66539zSt92gkZWIRdM07HY79tUB5xz9YHASAzbCer3Gaqj2ewnJoojKEAeX07nAoW65vb5hu7lnX1dwe0uMhvvNls1my25/4PM/+T7PXr7i5SefojXcb7dsdxv2+z2L9Zp8URK1oqoq2rYlTVPJykzke5pUDH+SJEQFRVFMfBAwGZe6lyxfOyDV+QYTZ4UswjXvAAAgAElEQVRpQgiE6CVnROsHix8Y6k4MS2CWDY0KoCRUf1zk5mFY/5GGYj6P5z/z+fu7tm+FsVBIZStRq80yTr8Bhj1wF6YMvuHvkhs8/W0coDlPATzw8R4Tm3OkMbot0+cNnzPkrooQJwS0VhhrReZLxCg122ki1aGhqppp4AKRfXWYMjEXiwURRe88TddSdbL49wfx8z9bLzl/8pSr5y9k510sSdOU5XJJ0zTgg0x2a2XnC54YZffvXUdVKULfUdc1m7sbQu9E7+E9bdvT1g0hBMrlgq5z7KsDAEVRcnZhyLKcvhOoW1UVVbWnbSUVvWka7q7fcfvhmt12Q/SBPLEkA5o5bHf0rsX3Le1BUEBdS5bsYlFwcX5Okef4PtC3kvputcEhm4d3Eilrq5a+92htMTalc56mrtlXNW3nUNpyfnnBk6fPubx4wmZ7x939G25uPrA77Dm5ekqSSKm+QyOK1HnClVIypnFM8NKKPM85PTnBDOHqruvQ1pC1FW3X4ZQXWfegshzFVTFGgnNHfYU+8mvfyB+oMSUhwDdsknJNYCo1OZuz41z9TdzE1zVG//T2rTAWcVh0Rhkk1VZNZCd2FoWYL1wtkM1gAKljobUSSXgMKH1Me0+SoajKYGmttZPBGTmJ+QDNMwLHAZfQ63HAR05j3FmcE5kw3tN6qUeplSROuV4ETVIrQ+OcoIuu69lXDZ0LFCcrDt0GpRTlcsnbt29pB8n26fklz1++4OrZU7KsQBlNXdesBtfDOUei5Tl291vylGk3bJpGQqFdS3U4cHu7IVWKtu2p9geur6+FLFSKrFigjKZqahblchJeCVEa2NzfAXB/fzelzNeHHb/+4hdsbm6JwUGInJ+sSRMz1Aq9GUKPPdc3t3z48AHnpB7merGk2tb0q47Ddk/oI1Vd07Uem2YkWUHbtcTQ4YIHH0mTjKJA0E8vRt8YQ1aUXD15xun5GYvVkrv7W5qmHYxbRZIkrE7WvH//XlL7m4aT5QrvvahMB+SktcYOv1fqQJFm9LkoRpfLJcv1it1hy/Xmjh4xoJN6UlRU6HgkHcf5EYaKVpN2aFz4BLQa62mC+g2c2rjp8Whzm6+JOfIdIyHjHP59tG+FsYBR5xAnQzGPQhw7bf6OMW8jDqq38ZrIKGqRfx/JzTlDPP5/DumUOhKsjzt+QjeRB88WnMcbCZT4EInOAVJUtwO6RorTyH2UKCAjKAw20dxttuIyvEtI84RytSQJAZ0m9PuGIl9wcXXJ1dPnPHnyhN4Hdrsdh8OBp0+fcnZ6ilKR0Dt2ux3X1mCNI7EJfd8N93a4tqNtGqzShCAy6JubG968ecP93R3eRVanJ4QodT3Xq5Opj5qm4fXbt1zffBCfv2+lNof3bHcb7q5v2Gw2WCMp+d459lVNVe25u70dKlp1bDYb9vsKKb7saVvP4dByd3ugbfzkTqVFTpZHimggajrnQBnSpOT5k4K02nF7s6Gpe5TWFIvlRF4mWUYfJA9DkrIMRouSNssy0jSdduLOO4oZic5IKioldUGHaBY+kCYJZZbjYiDPcxZlyYe7a1w4KjRlHo/RkdEYzN2LKHyblvka41CLVY05IGbICRnnuhRsmguxtAGl7Ne4tWOphCMxOr7+R2YsRuNwTP6SGggePSSHiQWduwthdr0MwrGW5qjDf+hejAZjnJTf1MaBf5BROkMaSqkB6ss9HBJXdyai/SABVhpnHAro+37iB0bmeswg1FoY90Nd4YInTwQ1FKsFP/78UxarFWdnZ/z0pz/l4uJCZMidTM6yLMmLFGvFLYpaqm5rFDHUtHVN1x0JRtd2uL6nOVREH/jwQSIIm82W/VYUmnGQDY/JYVpLfdK+81RVxfv373HO0bY1ePn+TStqSj346mNty/u6YnO74cO7a/peDEFVt7heFKQxaLo2sr0/ELwiSexUNzVflFxepaSJ1OPYH2pAUy6WnJ+f8+JP/gRQdL2nqiRvpveRq2dSbPj2VhDMbrcjKFierDk/P+fs7EzQ4ECGr0pJRMuyTLJ+x90oBHwnOTuX5xdstvdSv3O7ZbPb0vZS9tA5N0U7QpzXzhxm9aCzUI+KNh8X88i7zVIXeDwvw7SJTtHBAUU+1gV90+b2m0Kw/5T2rTAWMULwoJQww4ImpJpRHArVONdP1z+EaYoQA95rvHP0XaDrHH3viYM4anQX5ot/HLQ5QQVHonNK+JnBwbHgL0D0ouDzA3+hrCVGQRpBRbz1GNRUhj1PE9TpKVmSooKaSvX1fQ9JwuXTJ3z+3T/h0+98ymeffcKf/+gvSNMUpQzZegVB0bUNSsUpnFdkOXhHOxg/qzSn6yVtE9lvt7RtS1Xt2e/39E1LDIHFYsHrX/2aX/zql3x4dz1FFowxmCRnsVqilKHvPe8/fKCqa3bVgX/4h3/g9duvMFpJVundLc45zs7O+O7nr8jLkrauqasWHTW3N1vev7/l/dsbFosVp+dPOL1IOewrmk4iMYcqUDc1N7cVNhGRW1FkrLzGuVs+3Oxompb7rVQKy4sFr1694l/+6/+K58+fc3p2JkZtKLRzqCuur6/52c9+zuvXX9J1HYvFgmdPnnB2dsZyLfL4y/ML7u/v0RHKsiQbamjETpSro5vSdR1aKRlr56l2e67fvcdmg6y9LGn7XjJ8vbizGHFWR5FcH0aC8aFQbyzHEGLgWCvFgxkNzpEgH43FGIWz1kxzdETe8/k9XydzYvV3bd8KYwHDIvUivBkL7GoNwQuPcYx2HBfwuNCVMgQvhVMf5/7Nkca8zXeA0eJPfiE8gJVz5lnNck3G5wgq0FQ1KkRsjMOhN4Oqc4iWOGRHFUWgp28GZr1ryfOc733/B/zlT3/MJ59/wsXVJeurS5EDuzDOtOl5nOvR2lJVe3zXS31MBaTpxFU456SwTNdNSEkNCsWma2majqaTHJDdbk+WZXRdx0prwsABWWunQsBRwWazQSF1Kfb7PU3TSEQhCDRXEVzXTWUIjbFom4t02mRAQsTRO+m/HifwW0VSnxJTMNrSJB292xG1oqk76rZhv6+4vdvR956rT1+SZyWLoRiwSlPwPdvthuvr99zcfKDrxnB1yXq9HqqMMY1xkcpiVhGqw2FCnjFGvHNTWrnWeirtGONQyGb+mtYYDD7KWSJqjLSp8GBuHQnIY56J/PsozBKubYzWRaTW9Tc0dSRCHyOK8Z6Pf34f7dthLOJxRyf6WXLXsCDjSF4+RAfHhR0JRk1EE4w+Isfdm68bgDlXMbbHIdXH8e4xFDkx6RFcAviAVQPSCUHuGSJdLTC5rmvw0FSyUKtdJTF+Iienp/zFX/wFP/jzP2N9ukInmnq3Q0chyFQMQ73NfiJk+7Ya6icEDJE+BNqmGSanJH/d399T7WUhLAsRbZ2cnEyhz67rqJqaw0GiHyMpN6bEL+sWZQ1pnrFaSeZoVR3oB4Mw7sD7/Z5FIS5UN3A2CqkwvlisSNKMqu6p2gN11UoBGDSpGRdUxAeGgrmigShLCXO6Xs7jACYj5dysAtQwZ/qu48P1ezb3d/jgOD8/F+3JYsFqeSK7/EHOGRkXbgjSr/0gZJoT3zFGMfhaP1CylmVJHMo7zqXjorUxhODF2Aapkq5Qj+bRQz5NMS5oMSQPyfbjYUUxHuf/9N6Zq/FNiGL+8/to3wpjEZHOkA4OKI4k5RhlkJDqQxJn7vvNkQcMxE4MD0Qpj2tXzMOq85DsYwMyNxjee9TMWIxVvIs0kxyRPuB6R+U8fdtx2O7Y3t4KI68T+tZR1y31oZbITJby/PlzPvnkEy4uLshWJa5veP36NXmSCswOspu7QRPR9z0qQnOoJCVbNPCTgXKh4357x2YjZ2qUZUmyFjZfKXEjqqY+RoK0Jh3IvxE+77YHysUOm6WsTpa8ePGCm5vP+PDhPZu7Ow6HHVVVcXt7y+HwTLQsQ/9gk2lX79pBV7I9cLvZ4pxHmwSlDEmZcKxm3eGDom0V1jaCbIxkU5pEFqsPEtkanzPLMikqHCPtUEvUGMPV1RVPnzzj5OQE38nnb4YShL6XsdNDGrmK4Id8msfktrWWlV0I1+QlrN0Hz3Z/z26odxG0QluDVRbtnbii8Uiaj7L/h+jioRxA5t8w2dQ3SwUez/vRyMyvexxO/aM0FgAuIjBeKqCizGDh8Ug9QghhLKkW0ZoHxsL7FuckRKW1oA05JeqYeKO11LxkFnGZD8Z4zbxQybigQgh4zXBamNTTjAqUl/d3WlP3jovFkhADWhuK1OKCgw+Ruqm4rTp6J5xKCIGz80u+853v8L0f/5B8XbKvduyaPRAk3fokx3jDMjFkRqH7AH2H7uW4vAg4JWrVQMSrgIsOfGB7v5fDfIYSfiZT9LHl+vo9H7a3NLElPSm5PF1x+elLrq6e8PzqiSCGpmV/2HDWrkj1ObnWLM7P0X/+F9Rty1dffcUXX/6avFiy3++5r2tsXhCdp3URR0+iE3Re4k1D4+H9focj0A21srMkI+Q5RkHXt2wPO1xXYa2myDNMbtC6xqYJq8xSLJc8zTLOz8/5sx/9CWeXC8qlgkTqgUZaslyRFytOlqc8ffqUpum4rQWhbb76MISuo0SirJUSh1qLS9L1hN5hjJpC7RKSXZMlqZytohTLZckvvvgV/voDleuI0UnIdDC4fbAQHKoWJahi7m4EcTWUGpSbgxgrSkl/Ywwuhq9tVmJQhvNuQaqdD6daKCVVt4L/Osd2NER/TG4IDOHPKIfuwOCCzDmD2bmmU6hKeIjpaAD/UMH22G0wxhBRGG2/0Z+bk0bz+xw/b0g7toOsNkg+hVdCovqup7UtCZo8TeXMkNJxcnLCfr/n7nY7QerlcsmrT17wve99j+9+97uEELi7uxPNRD6c8xlmug+liTYIVI5HvYjGDDkKY6KT53C/HcjCgqLMWK+XaK3Z7/d88cUX1HVNWUpk4fziisVCjggok4K/+7u/ozo0xCgEcxhqkqZZyvn5OSZJuLq64tmL55ydnfGLX/yCGAJVJeFh3/X4PhBSICpsmtPXrfQhGpPIjp0NOSdag240bXugbjx93dL1LcUiF9ifpixPRE9ydnrBs2fPuLq8FHdABgTvWpxzgqCMZbVakaYph0NNXde4VsK2TLu9FRm+UmQ2gUWYsoin7E1lSRJLNJKKr4yW82R1ZHvYU/cdm3qL9wofwpHbiUfEOg/9fy057BsWcAjhWDuaryPlsT0WZc1/f3z974vchG+RsfimFmNEYxiPY5svZHEDHp4j4txoUIRhnrsOk9uBhvhQQzFvv8lYSGhxyGtwXvQdBuENdKDayzkY/VB0V+eKMi9IbULcHNivT2nqXvIVBri8Xq745NOXPH/6VI7Y6xti9JRqOYUgx91PoXDGY2yKUh4TLSlCZiaZnYjNzvcoL+FPVJiqbEsK+IF3795RliUnJ2d8/p3v8urVJ8NhwZdU9zv+9m//VgyvUjRtS9u2NG2LBLIj6zLjxYtXfPadP+Hly084Oflr/u7v/5a+F0jvQsT7ngBkSY62CSF2RC3krrGDC1EuWJ+tSBIrJ4ophws9dbWj7XswkC9yTi/OefLkCecXF1xdPeXZs2cslyVJJjs30VPXosjMEvnscpFjrCUER1vVbLdb3r97N/RFRmolSU2FSJ7npHaoJpakJOZYASwGNSk9lRLEsShXnJ6esqsrkpu39DHgvcMj0u7RuM+jEKOhmHNfDOekzud6jHGSuB/Dpce5OX7G3AhN7vXMJswNxTyv6Xdt3w5jEccsvBFGjQlgg++nj3BKJMpjbsMwqHEcgGOniGUPRM0UEVBKYayoEaZ6FPYhyphHTx5bcLwU6DERDOpY1j8qkiRlvVhifaTZV+zcBjpHnqSoqMjTlLP1CS6K9iKiOT095cmTJ8QY+fD+LcVQaNYqTZpYUpWig6HvhEhzIUJiSAvRBVh7FBG5tuH6vWgnuq6jXOS0bcvt7bWUh6tr+r7n9OyCf/Wv/jUXF5cYkwjvcLPlV7/8irev3/F3f/9zqqoiuI7Xr9/yxRdfcnl5ybNnz/jH//RzQnD89D//z/jJT37CX/3VX/Hs2TNQRhDLoaLtAtXhgLWe5SJleXpG1fXoxJIWGYtyRblcsFqd8JMffZ9Xr16wXi0IwbG9l2jG3d0NWmsuLi548uQJl5eXUhS4XFAUBXW1I0lPsMbQVgfefPklbdvy6rNPybKMYrGQquX7Le/ev+FnP/sZ12/f8+LFC168eEVRLtlu9wMygSRJMcYiyYiWLMlRs9Pp2kEnsxiyVfPbHA3kSUogglOo4KhaCaMGJZW/Y5BT4kTZaYYyeU5gMw8l4BOCjlGieoYJZYuITU8GLA5I5jg/5UyTeU0Led/XD/z+Xdq3w1gMhXYVTFWtR0spPAMYc6zLCWNHjVbzIVkknAXTdcfrI9GFoTDOkWx6zCSPVl2MEIyFelWM6KF+p5xEFkB5Iop0sZDzS31gtVhQJhl5mqGHHZUQ2e/3WCtl5szgJhhjcG5IKx6rhQ/p7xqJ8Us0R9OHIVyXWExi0FYKt9A23N9t+Oqrr3j39i3e96R5xn6/5+3b11xfXwuSWZ/yp3/6pzx79pwkybi92fDll1/x5s07Xr9+zfX1Le/fv59EZPuqQWuLtSmnp6dTNOL1V2+5vPyS9XqNUkrqR+Q51f4gRGwf5IRHPxTE6aWcvjFSLvDi4oyLiwueP7/i009f8eTqgjRNaJuKDx/ecX19Td0cprDncrkQRJAlwilYg9UK73t22w1NfaD3jtTqISIFvuuHaE3FZnPLfr+fNpmRqyrLkpP1Cefn5w/yduTIbU1ACiipEDGppUgWJNFR5gVFlpMmCX3wclRhgCQkRBVwEdBHDuyhjkfSFOZzcz739GxjlAOHjvLvGCSVAeZKYlk/88+YcxUj8vh9tG+JsRiaCrNFGsBHtDHT6V5C8hy/+Dz99+t+20NmWK4XMcy88x6fAymDI8cMPL5urrRTIRKQ07P7ENh3jpB3lNqyLBeUeUGeZUJ+DqHGs7Mznjx/xg9/+OfYwfcvCjEoZ2dnpKmd8hSyJMWSYJWVgkAM5ecHObuxVmyk69hvt7x//573795xc/NhMEqWQ13x7t077u7uJIy4PmWxXHN7d099aAYj8Zabmxu+/PJL3r59Ox24Uw71KUEERmdnZ2RZJu5e37O523J7e4sxhjwVw0iMuL6XQ4m9oWkkQgGBk/WSJ8+e8Pz5c548e8bV1RWffvKSi/MTlouSLEtYlClWB7LEsN+LUCxNU9SI9ILkV+RpiiZQ1Q277WbYRBIJTxeQuJS+7yZOiXCE921bU3ctHikTeHZxzupkTdcOeR5aSQ1QLRSyayXpTceIjoo8Ee7mk77hrrpH328Iu3t65yZOzccgHJOSc0DmJsGFMNvIhjkn+v9hbunpR5aE8HjBMxmK4wKQv8kZskdZwWgo5olyv4/2rTEWI6qIMQjjGyTi4ZwbwpODzzZo5ueIYg7jps+buRbzvJA4DN9RSTe2sUTfEaHAUf9xjHvLORJizAQO+giJSYjeczjIeaX0nsTIWQ4SUVGcn5/z+eef85d/+ZdoI/oFyVewLE/Wk1sRhozRJBWk0YV+uJ/DDydkBe/xfU1T1dy8/8D7d2+4u7uhOVST/qHp2kkLkKQ5q9UJu92em+uv2Gy2vHv7ge39PU3dsrm7p2k7urYfjEWJcz2HQ81ue+DNmzdkpRi/vu/Z73ZsNhsJxw6nd+mhT/ABFxtiL6eVL/OM9arg889e8ezF88m1WC5KcD37+w1NojEK2qbG9R1FYqfoVQwO5RUmJlgCWskh011d0dUVRVGKZqJpsdoQM08cdA4jUksSOdKxHbJvY4zYLCUvS6JSKGvQCpTR2DSRU+W9JvUS7dBI+DTJLGenpySpoTeBL9+85os3XxI2d3SuJ0aPjoG2fygCHOfnvObE9Jo/nm53TH04zlEVFd48zh6dEfMRtHloJObz/48OWYyCFRUj0YvfNnXYYEQk3KWl1sGMvBmTcpwbio1E/SAvZOys0b9XPLS0888YoyZHlaaZnk8rOR/EWitKPiT/Y5J1B3mGyldYbXFGTua622zZ7fecXV1ydnbG+eUZSSoIIkmksGxi5PQv0YRISrSjJxpHXuY0XUcfIyp4uq5FE2mqA3fXN/zs5//IuzdvcW0HCAqq6xo9uAhJmnN2dkbX9bx9854vvnjNzfUd9/f3NFVD2wrxKqhOiUvQSS5JjJG7uzvSzFI2JUpFupOTKRrkup6+rujrSo5aJBC6lnYornN5ecnZ6ZKXL1/y9OkTrp4+4erqQoxiV7NrqyEM7OkHQtX5jiJLUWmC8kjdiCif2xNolMiyq7ajLAqMNWidEXzAdXJOad9KMZ7gHUWesdXSp9572r7j/PycLM/JioyqqQlDGcbEGjlOwhqSRJPY5VQgx8RI33ZkNiG7uMBp2dWbvmVfV8TdVuaklnNix/uNbTTcjze3uRGYUhjCODclDUJFkTQf0cfjFaSmH6U0SZJOqQ6/r4DIt8ZYqOCHSseDys0H0HEQbMFjS6o4SqBhDFsNwpRHCOMx6pjDsiNsG5HFaJHNMCCzzxoOb9H/N3fv8iPLsqV5/ZaZ+SMi8rFf55x7S1VFtdRNM0BCQqiFxASExAAhMaKnICH1v0CPGfWUYfcAiQlSM2nBCIGQmCMxbiigb/WtW7fOa+fOR4S/zGwxWGbuHnlOPbrOgd4q30pl7szIyAh382Vrfetb3ydCluqKbVwQF8xg+d2H99x0B4790eYLijbkx8dPfBgHYyjOs/2uU7KE8typ7NozaTER3dGfjdykmUzG5WxeJzrydDnz2z/+Dd9+8w2/+fUfc356NvCt29iW9toc928yfX8gY1L8f/rNNzw9PHE+X5imhWWaV1akCmVuJa4q38/h2Rb/7YT35ub1/OmBp4dPzH3P+fmJ4fzCPIzkaUJTtGEt53n/9g0f3r3jw5s77k9HegcaR5ac+f63z9YBSpmcE5qWQoZy5Jsj/fEAXWemxN4jqUFzQ/CG9RzbxgyrEVI09W5yxotwfr5wfnrm5fGJ6TLQNNs8hfdibeWDlVrDMBhO4T3qwaunq2bTbUsoAHkmMczKEiOaFS8OTZk4LcRpti5ZAhUh1VkReLX+ZJdB5PV79eMa38hXGYLHFbO9Lcj8GHj5Omt+XWr/VY/PI1iUkxkQgjcRHHVqbE4pnZEqPLOfAF3Lie1zKhToij2IvNKk8JsGQH2+ENo1ulvg8OuOsO4C2chEGeur63oxbLESIy8M3Bxvuf3wjt/56pe0oWGaFj589Ts8PDzwe3/we/yNv/U3Ob2543K58PzpAbCBsLubE3MRva30cJeTUY27jqb1K8twnmculwt/9Ed/ZCPoMXHojZfw5s0bnPd8+9E0J5wP3Nzd8vRy4fHxmV//899wuUzgHF13YBxnXs4D8zSRVRG1HVgUlEQXGuZpYhzOpGhamsEXq4Qipf/4/ddMw8W8NOJC8J67uzve3b/j3d09DY7h8ZnfPD3wR7FkBZcXvvvOFLe70NC0nr5tuL295f7NLfO7e/rDYX3ffW+M0LbvaB2ErsOL53IZePz0zGWcyGo7eox5Hb//1a9+xcPDA3/wt/9V3ty/46svvuD9+/e8u3/LoQmkaWaeRsbJSrama7m9veV0d8vx2OObzuoEUbxAGxxpSTyfL/zh//WH/Oo3f8Sf/MlvGM4DbWgJbcuS0zqc13hPihlFaUIgspH8chkNELyZH9twSfGnYf2owSFX93b/Q1xi3yLdi/nuS/CfenwewYIaV21ABtj8L+rPf6SPLNQSAkJQa1VlXXf81/XfD1lx7gf1Xc0y1t54Ntp4ZYMCLIotIGwBiXM0zhh+z8OZ9uEjfX/gyy+/5O2XHzgcTgzDwJe/+ILf/d3f5c37d2SBy3QhLxE5WtA6XwaTn3t8YhxHjoeGnCPn8zPBUW4EUwMfx5E8T3QuIMeu2A3OPDw88Pxy4Q//6f/BOC+EtuHd+y8Y5oVxmJnjgvOexrcsstA2PSFciMsCags652jWfWUepwrD5CWiJOI0Mw8Xhpcz3nuezy9cLoaVII4mBKNqizAMA/M0Mo0XNC2M48WwkMszz082k3I6GkErODM4nseBeT5YVys5cvKIHIr5V2J4aZguA0tWnp9eeHx+YVoSvmlZ5sT5fOb777/n++8/8vz4zDRM+AxNEVYOztqYOSUik+mLpEyKM06UFDvyMhNnCHm77jjBFyHfOUamcWQpwOhKoCpzQavwtLwG0PekqW048Afrujx+v27rmnRZLdPc8S7YPX6v0fJ6g/0px2cTLGCfPhV3J6kKWEXTotkyAhFZz2iNoNnXzKJmG0bO2hNlnJd11LxSevd96XoBnTOB2oqdiMjqD5HK8JYT1nauawJBHDFnXi5nHl+eefvuA03bEm4Dt3d33L+7R4LhCefhhefnZ0SEUzY2Yh3+enqwOQbvbhBR4jyjBRPZD29VncyYTLfiUjQWNAtff/0NGUxxqj1ymUZisp7eXrawaZrVLMh2OdAUGbMRnqqj2zJOaLA2drXTq1L6j4/PPDx+YpoWgg+0bUdSeH4+M14uBCccupaYRobhTE5WZqWy+K2LsKC5WYPhMg6IJLJ6snpEMpoXLhfHx+8fSUlZYmYcJ8bZxHFc0/L8ZOfw4cG0N+O84MXBougcSeNMnhZYEjpHssvoYs7prfNG7Q7epnizuaqv5URSnG8I7Taf0jQNngAJ4hwZ07LOnGhSEps6fC4lsoH5DoqymC0+AN02yBp83A+DgZbOzH4j3POD1tbrz5hVwGcWLHLOEBUtakKQUbfVZTFei+eKr9jDnphlRy1LrKuyBQdxrDJmmzXAD2f+TTD4WtBkuzBl2M2VmRXURpRzxqljWhbGZWbKhqQfb28IIVjnwDkuw2CZAbqqhTvnTMy2SMHFeUGYaby33TFqXZ0AACAASURBVGqamceR8/mZaRhtvqTQiJ9fLozzxJxM1WqZkylXtT1tCTAvzxfmuNA0nfFMoq4L63A4EEJgKbV527aIKjHOllEtkSnF4hzf2vDVEhkuJprz/acHHp/PqMKpb8gqTONCXBb6JtC1ocycnLmcnwHTBg1Ng/OsgadtPPNskgTni2fODX40fs35HOyxOTOeM9MSyQlcCPY+257x8cx3Hz/y+PjE4+NjaduWjGyc1o/5MjCEJyRlVMQk+4DQOCuxshp+kh351SAYRZ+kDdbu/vj0yOl04mW8XFlHNE27tlL3u/+are7Ywfs1drW+RRA1ub7aidsHB7cz0Hrd8XhN0Po5jp8ULETkV8AzNqQRVfXfEpF3wD8G/gD4FfB3VfXhL3qurWzgKmMQZ+7R9WLFuAGUsgOIUjIE2S5AVd3aiDFV4dsyC79+r4qsbq/h6v1dfV4fo6aAZDlQrRNtJkKjPcc8Gxlpigs3fakvvWEhVRfTOcfpYN4UXdcRygXOxbn806cXusbIWuNl4Pz8yPPj08rGFB8Yppnvvi9tO2fcBs2OqmFRzZlfLiPTYgK7TrwlDTkbIPeqRFs1IihmwKolUIf1HMyzuanN88zz83OhRXumuKDZk5bIPEfoWjRn5jlzfn7i5fkBVwhLp9sTzls2sSzCNBmhLuXA0wuEyYBAw6ysco9p5uM3BswinpubW27v3tD0By7DwsP33/P46YnHF7NhPLQd/nDgcrlwPJq723gZABhHy4xcWQet2gDZaKw7nHN0zeHqRswlIIS24f379zw8P/Htw0eeLi+8jAOSFrxztKG1zs7Od6Zek7wrFfbBQsT0XK6ChSHq7IHR1/fNa0Dz9Rj754RZ/Huq+t3u/38f+F9U9R+IyN8v//8v/vynMHZaNvYVDoeKA1FC4VaICEJAEVIuQaAsZM1CXKxdmqNY+ZByUQ231lvwnqb07pEdOOSsXZizpYkOCBVZqrUk5hfik2kmRjJJSsroPNkJbWhwQZjOBkyel4nn4QUXhHwQmsbz9PIM2YJBS0fX99zcHDn1JyQn+qC4NNDLwjx8wjlFaAkaSZcHPn39W7799tuSiQRCdyTPkRQjDs80RTQq58vEHBfa/oauPRVVbKvXZ1149/atsQF3pc00LQwNaMo0jTCNI86ZhqhlYoFDf8uhbxE1Vuc0Rh4fH/HRcQydLdpx5JIvdr5cQNWzRIgx83JOvFycmQf5QNMK3jV4acipIcbAvHiyCpfzgjgLwiJK46vA8sJ33z+Ts6l+qSrLOBGnmctlZnx6YXh+IU3R8IQRkjbEWSF7RB1JrQPy8PRIzpGbuxtC2xBSoJkbDvOBxC2ugUPT4AtXZprm1fkNHJ1rOTYHfA7MzzNpSHRqY/WP82hjBWqgdE7mAGc+p0XBLS/r3FPAkZaIhGrqXYKDmOaFas0QDIC3bpxlHjkbw7m2vm3TvGYx/xwB4/+LMuQ/Bv7d8vV/A/yv/IXBoiDA7CbtZEeV3ZUBNbCqKnF1lhaSYhEbV4xk64g720eJHm4fLMQuzDr3r4WDz/Z3VgDKOwQrNWoAq0csDL4cF5IPKwg5F7xBmh4tZLLD4UDjLLu5uT1yOBxI42Uti3Iu3hxxom0aYhNWkd7L5YJzjuPxptSoBqjFpMwxkZOdt/v7e96+fcuHD+948+49h9OJYagkLRMUzphAbDXWEX/kdDiyzKbDcXk5cxGjUHsnnI7GtGzbFk2ZqQB5e5LbllpXEdrKKgQXPM4ZgKqqxLx5ndSyUgVChHkxzMoVzErVdvR5GXl6Gtcx8hBavAT6/sjz8zMfP37k4dMjSypSdN4eV71CpmkyF/RkuiDqlJjNO6RtA/3paBnFYrM1z/GJuXRwEmrMTCcM40wSo4x/8f4t33x3z6fnJ8ZpICubJqfu1/Sr8YO8KyvKinPKtjnW31MzSa7nyo6Ntfl6vqk+/37i+nMIFgr8T2JKNf9QVf8R8JWq/hZAVX8rIl/+2C+KyN8D/h5Ad7B2qTjzDfHeFy3CTcS3yo+RTfZNS71SI2mMqTiUVb78Tn4vOEJj1OEQAs2uVQrmwl6PFI0YNqUJLRfaiwOn+MaTc6lxFTIFTF22adSubej7jtAYYDgWZetjf0LUkaNNjt7e3nJ3a65hopmPgylaNa2VKo9PDzw+GvX6zc1pK12AZVz4OH7i7TvTWfB4M/H1DafbE1989Qv+1r/2t80q4M1bbu/u7EZUM9j51T+zMfUcy+h9SYmPxyNv7+757rvv+M2v/5hP33/k3J/xTrg5njjdHMqsx8R33z1yPp9REp4SOBVSCSDZBVSltD2PiAhdd6Dvj8VzJCONYxFBo5jWRZ5xw4KQuQxPiGSOfU8Iu5ubRONbbm7uTKhniYh4MzIeZitBHp4siISWvEy8JOX50wPxw3ucg7BuGAFxkCWT08I0FcvKyUqrpmnofFip4Ma7aHA+0PQdpzdvOXUt/8rv/T4SPHd3N3zz/Uc+PT0Sn75fwXApU84552JCtDNKXkqgLdqbGWwY1ZUPgVSyDytHQJ3gVyvEbBIFa8kMBkAXTU/yGkx+6vFTg8W/o6p/UgLC/ywi//Qv+4slsPwjgLs3vVqgKCO3km1gq56AIp1u/y9IMFgWoWaqY4t+CwAWyLcMou7aIVxHYnDmb1mzh7IzmtN4fb6CSywziULZBRDzxgTwVJNaiJrxIeBbv76enAxom6NNzU7jyNK3eFFSisR5ZInFTi9trt3jOBIw31DVOjZtP1/mSNs3eHE0zhNWzckbfvnLXxYF8AOha2jaHu89p9MJshb1dGDfLVJTjRovA11oCkCfEbUdbBxHxvHCNFmLdxitddoWSnWdZ9hzUyoeJAVUbprGfGg14sQjmEmPZiUtCdFEKsQ1w69nqimyc4HQtNzdnLi7u6MNDTHaGH5ORfkKzKS6zBTFnBExsaGYZsiZpvWE0BGjGUerE5u9SYlhnHh+eURV8a7hza0FWuccPlkL2R88HiHHGWla+q7hw9s3aws1pYXvXp7IaYESGGrW7BCyVklGR8KtQDqqlOFrG0pQXW9+I43VdavrB+6Hqm6wEbb2A5M/9fhJwUJV/6R8/kZE/gnwd4CvReSXJav4JfDNX/hEUtuhlnJKNVxZ0zcTrbUUbHNf0uzJKZGTZQRaJvBE8u753HUq7By+0r4LqORU17boNTiE6WkUkscSKW3ZbMM91HQvsqipay/zhBfHcDxZKbKMKyLeNi1ZrEvw8vJEEFj6BocBovMwrqAYZDQtTMOZs2a8hJJytjg3cbmYJeChALtd13M8Hrk53nJzPPHm1kyNu0MP6uh6a/Udjje8ubtHi4dpSsk2MQlIyvz61782fkV1htM6gDWxTAPDcGaJE8s8lxkQxWvRq/RiHAbvjJOwGuZcWymUNUPMxkpdrzHZAmU1tA4CGglNXtPtrj1wf/uG0+GmTOxal8bKvomcwPsGL6GQzEqbUkxvcxgGbuYjIVjXZVkWmr6BZGn+XMrHJRWj4WFctTe7g0BuzJGucC7EwcF33N6YalhoXMGH/NrGFkpHQ9MqyAt77Uy3WilkrYZWWCnttrL8z+qY1PP5Y9nDzxUo4CcECxE5AU5Vn8vX/wHwXwL/A/CfAv+gfP7v/3LPaNmD9x7xnup8bi1UXzCIa3prYm3DENVyt4pNItiF8Za2ZWH9UDWmIn7LXrya1H+u7nWVIYeU7kp9bC6Bxv5ODVwWEMxZvHYIPn36xOPjI++OX5DvKGi3Lco0283XNQ1d3zANA+fzM+fz86qCVbsODk/jM8fORHeXJTFcluL3IaBC3xv20TUNSubl+YluRw4KjcO1HS/Pj4Aj1MGlsC2By8PAH//zX/ObX/8x33/7nfmKlgnWHGfO52eboM3LOpy1LAuu2fRBpBhTWzbXmLCMbK1CVUUMYyanvGVmJSDnmImpuHypjWg3zkb2j4eevjBVVycu/EpIm+d57X455yApUrgTqsowDDw+PtB1gZucmOLEOF3oc8dQ7AnNNIjCKs4kl1Y2bxsa+kNL33Ycuh7ftjZIWJAyI2Uposa8zQVlTCXTiirkdD0TsrKJ63zRStS67n78WIdjCxT5B/NOV3fWDnf7KcdPySy+Av5JecEB+G9V9X8Ukf8N+O9E5D8H/jnwn/xln1DEqKzey9rqrErfqKWrexo22GJB87p7/Xlgzj49RnQd/923SK8WG6zCqFu2soFVsgM5pXRPQrn5bGE+8vT0xPx+Xqcxc0rmVjYNnF8izomJv0STgJvHiazxiiy2LAuaoGkS1WHr9vaO7x+emcbFamnvccU89+nTI7/+9a9p25bbu3vjUCwLuYjleu/JzuFlU7POOXM5P/Onv/0N33z9WxsyG+usxWYuHULAYyBtcMbQbDxmnhwaW+DqwG8SdWQro3I0g+iqV+JQM4yxE2iYlSi+jHg3ztOHhr6UV6eTuYqtVpRRIWdizgyXydiweQMQgTWI5ZgYBvNI6fuOrJE5WYDxjWMpimCu0OBdsPUU1FsGVVqgDsuCvDj6pmGIM2leDMQm47AStuu6bcyglJRkOwdVfXPb3OqmhA1S7taVKyA0YtmHiAku7df0a8m+1+v/51LL+isHC1X9f4B/40e+/z3w7/8LP5+Tdaffk6jqDptzLu5PUqKuJ8+g2Ry+gphepMYEtQZHVwNjyYpk499nyVfstj15RcRIQk3TlAGnvAUZ1bX2Nv55/f5mQdf6zuTml8jd7S0vLy+2iMUk2jw2ch1jJM4TiDKNL3RBjCOhpl1QF1rXdYwXQ/DPLwNd6Li9vaNrI0syV66c1RarKNNw4dPzxHfffWc2hG/uVw3Qx7sH7t6+oesOa1BLycRdnHM8PDzy8PDAeL6QFst8albgvefmdCIls1Woa/N4PCIatwzNe5rQ4b3JAhojdDFQsQ04cmEuCvM8bbskibQkE7tVxTub8G2DL4N5HX1juqZxmtcpUYBpmjifB6JmEwZSCnO3dAwkoGJBdxgGuyYaTY1KLYhUinZltZ5OJ1xocKW7VDtYVrYVQDvZzQ+WGQRnep23tyeeYiK1hqVJsaLwWoLOLlt4zbJMKV11BZ1zSMmOfSnv9tiQZEXCNalwn7m8Ft/5Kcdnw+CsN9s1xnBtnLLqcTpnXQup8nuxBJFNN7MY+Rl349W73J+81ymdc1t2UTsx1hHZTrwUtfFtYMWVVLA+hyvzB44Uc1GPWtY61hac0nYN0+XMHCcWyTafUV5fSqkIyzZonpmzYQsigYDjdHfPGJUwTVb7FwZojHGV0gtdy/39PW/eveXt27fc3txxut0Mj1U3b9cQAvE88/L4iZzNNGhlCpb33fc93h9KtrCJvaDmK2+ZR2NyhTVYSDXuLUFVMzl6yKZpmnNcz1sjCt4jwZiUXddxaBu6NtC5QFNqeVPe2oJFjHHn/FWp/SZFUF/7siy0hUlqRs2Ca9xq/NQ0DTcu0HQdp9Mtp5PZGjbGb7/K9HI2U6nn8WIU7sbK5K7ruLu55XK58JuHT7hCKPNeSIDLgDO1tddrsHY7nG4ZggWKovz2KjGoWbGqWra2G1tfyw4RspqEAvIvMbP4OY+6WLeORbv+335uiw0U1ENKiMvgLSR4cWgwUZbkLGCE0Kxpc3DBHNqTI6lCERJxzvwjrllu127pte5UVbrQMRNNFYkMMa0TrxTqsMdxvLvn/Zu3fPXFl7x/+45D33K5vBATNq2pmTZ4ckzMwHC+8Pz40TxU02JuYeOMa1raNqEyMA/RgqEGkIklwul0w+n2FmM5Wv8/JM/7d+9M1OblTJoXhpcz3/32a5yz1l89t6n04UMwha5D0zMuM03fcGpPnO5OhsWUDk6MM4f2ZEHD7XaubLJ/qloIXEVK3zWEwsC1GyKxzBOX1nG5CAMzIoHqEVOFZ30QTocjbdusZsaGhwguZ5aUbHcWI8V5703N6907xnHmfB5Y5oQpnoVC7rKsdE6Rx5dnzuMm8VeDRXcwbVALFicO/Ynbu5Nlg7qZR728vPD08sJ5GsgCERMzTs5Uxe7u7oh5AaeEYCWZJNPJiDkxp23ytCghA2as7XcZRQXla9lLIWGRzetFkrWrEUjl/tiv49rF+5dehvysR023duUAbLt6ldrbmK512GvPlWftZe+fayW1ZBswr7/vik6nc6VWXAkzCdUMmsgaC8MuUa9K7WeTi/pytlau+IYmBI79kTc3t3zx/ku+/PDVqlO5THP5XSsZckrMy7gRlGIkzkuhSc9rGziLdSpCa69TVZnGhYnIzd3tGthijMRSDjjnuLm5McwB0JzNB1Yj8Xw2QlPbrLMMdS5k6WL5nv0d742/4JyjHUbOL0+lDZjxvrEJzhAQ11KDBSoE2QJ/G5oVd5KcmYOUuj4i2kPeyeardSDaULgqIdAV8tU+ywwScNnmhsQ7cnY0ahaISaFZkgkTVcAcT3aGbZh4czJcrHGkIt0/LQncRN8XT90ioDQOZoPYeLcGrXmeCc7hMCPpmCPjMhNFUe9WMlRdv4IgXvEqBtyrW2/gfYmbc8LtXO0MEC8lx9Xt4kpL2p7L5ATqhleDwg9nTn7q8VkEi32NZjoUm2UbVI/JejO7DWw0YUVTO9aIpmw3cS4j5aVtplJH3zd9z+w3tqFj65I4fogc1xOek/EcRE10tb4esEylaRpOhxtubu64vzes4ObmhiZ7Ex0Wj8Zl1YesSuWV8VhvXrAWqc15COocvhjuGk5qcyVWBtiCnNPmaXrqT7x/83ad3ciVoCamvgElNS1A4b7syzkXSb7FdEBL1+N0OiFkWh9o2y1QeO9p2q3ccLm0o52zce6+LdlHIudIE0CIODnYQFpedgu6LYGix/vasdlKu7o+OidF9KYoZ5ef55L2t22Lc6FgAuYEPxc+iWETkaYL9hwprS7sbdtiBsSmezrOM/1UdDTalr41Ml+KmXlaCnZlRL05RRuvX0xrJJfArYJhZZQ5J+8MwHXeqP+2A4Cqlc21/Y+tU1+LtFJOCAV/qwA7avM9Toz+eXVXbRPTf20yC+UalKlkKdh1MLQGj+r/qFf4wr7fvKZ4ACS8axA2ab19K2klrojNRVRV5rVe18Id/cHJdqu6FXg0b+BYFaH54osvuL+5R6eJFCNpHInzTJwXEJvmzIs5iK2tRy1svLxZK9Z5Fu8q5mE3+DzPdh6aooqlCVdqbDPhsV2o7mKpvFepwQHTpjUJuYbu0JIHNc/RxUyDuqW3TOVw5M2bNyYr6GUNFo3zdCe7OQ28tXPjCoX+2LcE78jZbqYYA21jortVzGd/3dq25dgfVvBOd9etBqcFG7dfsonjLivWUxzFW3tPzgW8C4BDF7MWnBebOfFNUQFPiWGeCqgMTTPShDMxWUkR+76cQ0VKS7hS+X3f4rynazqiZoY4F7D1vK1lQFZLzp1uimx40NU6T9fToytmxo+rYq0ZihRgo3SV7O9vG++VIMxf8fgsgkU9fqyHDGB2g3XewALF606G957k9Ed/f3/zr4zC3bmzzEULsGgXa2W+7YGoH3u99TmytSJDCGvd+sUXX/Hh7TtePn7k6fGRp7P5Y+qy4MjlZrcjhABtZ+5mUobN+s7cwNoZ1OjT3oeidC2FV5AJhc+qZUx+mia6ri875RYYKysUrlvMdeqyZlrVYGl/TbTMhhghyTgHh9b0HLpTi/eNCRlnWJ3UREwbovFoiqS8GO7RtUx94SkUgLX+Xe89h67fAn7KdnP7ja5/WWBJEb/YlOvizbXdOWuve63DWh7vPODQaO8/LhHnlZzbtfwT9VRZxnEcEWdGR313pP3QrOejnrvV2nKaCNLhQrN2NerPti5Pbauz3sQqRu67LhsqNnG9yrbnuQ4WdS2vv+K2zRZ1VEZ0JSf+HNXIZxIsMknKolGb/qwnU1e9U0spne6yEIXghQUhL9nSVt+QSAYqiRgPYyXaFwmyxZSGsjdv1ayxLJZNQXmJsdwwbj3TSSLiTP7PiTdSWKl51QcQzyLCeYkkMZ8PbTwh9PRd4lP+xlSOSsbisTo1eCGFYLW1CsuSWHA04UjqHKEZtx3EC5Jst5gmNZHaGGl9QMSTZkVcZMoDmjNtobanlFnyQucDS8zEuZzvEmiSSzShBKlgZKq283iXOfaBrhGOvRkUd40Rk6pr2k1vbcXgPK6uylISOm/pdxYrFZfYEbsDXV7w7aEEkLgFMYw5asvCWJ2VJl5vyNwccPOM6ggxIzHjcjIKdsplMliZxwFpe7rDkVbNKW6YJ7x3RFGmHBmmifvTzQr89sHTOpvITSw0XWPGxyEYmDlNCNCHhmGY0DiTF5s1CblhnjIvwwLBF6q5QHAQiwWAq0I4mbQK3xiAmV0ta1mBTiiBgU0nVpPxLkpObpILaq/BS9FscVaiiMuF0PjTFb4/i2BRW5Q5Z5JmJKW1j1/ZlvtMYu3pi6HLQSCEyq9PZSesDD93BST94O+ltErv1wGfutPpNaq6HlevpewMUur9moY+PDzw+OYt9/f3BGfg2M3NDWkYGM5xpfWGEKAMp+kr0GtfhogY9ZpgpLV1J2Z7LfX3TN2p2c6VbuKw3num2cyEK3uS1nbLZZqM4+A9oTHD4EPbrY7od3c2vNU1FjDqDdyHhrbI1Tkx0Ne6SMa+sjmaTFSPL9KASQOirkzMztuOvFL2KynpOljAtrNXRznvt+wEVVJlYbJlU4fDgbYNNEuHambJ8/qzvrcsrG3tc2g61Ae64uHStg3iHcu8GAELCF2LmxbbLJaF6LCyqLSTf4zf8Dpz3kD1PdenXE+2jMSCxXWZort1WTth6/NIaQig5KSrkNRPPT6LYAHbSUvZ5Of92u6RQqU19/RqqOIraJeEGN215HquwaU6oi9r+QFG9kkp4VK01hZbdlFBQlm7MteMQOBqIdTAE3PmfD6Tc+bTxwfmy8Cn7z9yuVz4m7/4fW5PN4Qvv+Tp4/fGWsyJnAIxL4SUwAlLafsu00xuEtN8IefMsdjm1TTX2IKepbdJTHS7uVSVNNpAWv2dZVlI00JOia5pSMEzxwVJyXwyMG0QcqINntPBKNV9b9qYNzc33N3d8bu/+KWJ9JR2ZR2zb8tntwPgarAQV/e/RMzZMokyK9O3mzgMu0lMy6LKuYaV0VvfXzzHrVQqjmkueJYk6zCYiNC2R+Y5Mg0Xvrh/z+29GUTPaeHT8wMiNlDXdC03pxuOxxt8CLSHI6FrCV2PbwIxJ4aXJ9PznGz259QfuH/7lmmZWTTTNA7tG2YykyYeP16YdS6ZG2TnCjC5wy0K5rZuPt6jshG3pWBXRtTL2/zIjqWayzp0bBucp1phZFIG8T9PR+TzCBayaWTa/zMqZgq8YhJSh8t203arwXGtr3WNn6pVgzMXafsNr9DSeZCcyGUYRNnqdHg98lsynKuXfI2J2Pix0aJTkdGvmprPp2f6tlsDmt1wwjyPNGpU7CVFktOVHSgixHkhzouZ/R5NZyGWGQhj+jUFNa/EsQKWOduxvffWgs1KctEUpBUOXWs4QjaNibpr5wInVjDRdtWWY99zc7TZk2rJGKqOqTNadjF3uX4tZezaAkbAayRmj3OzjW4DuYgB2/nc62GU7Eo2S8pKVvNDg5MF7zJNY9cs5oT3W7km4gjeE51le5fhhbYLtF23tmfrbjuOY2kBB9pDTyOU/zvmFJniwjRNDOPFhtWiEbu++vAVjReCE3LjCaJEB+dlonn8U6JzaEprx0byNdZWl9B+LbldMBEFdVrc73R9XyIbq9g6KpiQER7ncpm7LFiT5r3/8k86PotgIYCK2Ec9CS6DYBYA4hAn6wDSFp11za5EpIDBddHVrohRf7eywqKuc85YhFrNlXVtdwFrx+DPOvbdlIpqh2C8hOittTmOo5Ujp7ccuh5XPEQtlQ+E4IhpxjnHy+W83ig1MNX32XUdp8J3GMtuM8ZkLNHA2v5sXJny9J7F26W11nBAtCvydQt9d6BTW4AhhNI5cIzTjHNC4z1tCLSF59B1Zk/YeOt+GOFqoyq7zKoxIqvi2CvgDhvU86rkcl5dEd2BbVCqloL29dYJqVkVLFcl14ZfubVz6ESood2VSWMbrx9RUUJbndKNEDZPkdHPOBnBO/qUjDpewNdaWkjweO+Yx9HUzNNsWU0T0DYQvHAjmZuzTcR6MeZmnYW5er0/klkYqW2bP6qZBAlkLZF3ZbChXoXBaVl4RpHskWYjdNWS5Kcen0WwqMe+5Wl1WN2Z1FSlSwtDS3IXs036p/IPoHqN7Gu0625ItPmQnA01luubHjAuhQvldbzi3F89125mZNc2TaHh2PWICOfzmY8fjZ151wZL+cvzmR6jqUPlnNd6tN6IXdcBrCDl/jGi0DSetogWe+8JzsoOpwsptaQlkpISfaD1lsGMztMfe7sBdMvoVCCFRGgaDodj8WrtOXQ9x/5A17QbPkJZ7GpfVwEdG5oqabfuBGbL+81FxMVpKVhk1yFYa+7Nz7ZiRvugvWcj7ssWKMK8aoLDKZvOidkSeGKe1vO2ZSvu6m/VQB2LgLBvcjHlLl2uvmcpg2zLZG1S31gGloNHCkW975o1WIpuUgZroMjbsNh+mtRKCL8GCqn4j5hFps27aNHEkJUOcH0+BEg4MuIFDT+PShZ8NsFiGz9fUsJLtsRCFA1rBWePE1lNbqt82TbsVXr2bF0NkUzNw/bZABRmY7IFc3Xji+zS2T+b0LL/nRQjjVq3wLUdd8fTanX48eNH0hLxb+/pg2dWJecAOZHKUFmtwV0BPZ0CffWeKLvbUlzCymBaFxq822TfK4bg6SDlVRsj54ZlaYuAbaTpDkxLKWX8DgBuWis1TkeOx0MhIhmg2TetaVaUIOGMHFPSwpIdaOG5KlCEiazjY98U3ApA27XZn9+83jyWJW7eF/vTb8BvUwbVUpm/CHifaTvrWIRgsyDjtIGg42yEshoct7L3etSg4lExRsu8Q88oQQAAIABJREFU2pam8xy6DsHbdXae8/PLakfoQ5VT2PgnHlnb8683lnXV795vPX8i/qoUrWMOWngxOWfUezzscLqqz7L9vYprhOig+YvvwL/M8VkEC2WncuyUlISZTCcNOTvEe7O9L7L9YBoBUl5+bRXZhbbaLe06ANsOstHB95yC7TDSV/3+PvLX0oacf3Dxay1dPS/evXnL7e0tbeFELLPNE5zbQPTOZPu8mFxcXla+RV3Eh7aDtiMUevk4jiyTqYUvk93kQRxd2xZGZbsCjM45uiAs00JTqMkpJbo2g55sgTuhWZr1hqjnom+DqY0fTrRdR9/33BwP9K1R2UPR4zRPjIw62z9doaNo3RGdgctSQDZXz1EdZFDDK4L3q52D7Yh5DXzr0J5cu27Vm7ppGrtxopCzlXJd15kQTlGschLWUuv+cEfXtbR9j4qxIZcYbVjtcLhqzQql48ImiWDdkhay0jfGNL28XMjRSpTQBBKWWbWlVHO1/CjCyHsnPJvt2nW6sllLiOr6/SAOFctEXQZ81QVhXZ++vEdESuaRrfzQbRCSmNe//VOOzyJYgHH8LTqabiB40x4sS0xdrbpqe0lRybuPKjUmV9nE/qg39hooXvWeazTPmXVk2aTSSsahFt3Ra1R7BSRjNMn5/kA63eBbm284BBNgARunzjHixajJ4nQNAjldlzrjONoNXQC1faBoGist2tCstGzvLBVvRIhiuEUNWJu6WI86oU+mRpV25ySJ0rUHDm1HKDdEGxqC87S+6Ivo9hqzqgkeJzPf3cRpPU5zYebuwDiuJd6yy2tJpoVFK6WMtFmHDdSsu2UuN10VGa6+MvWmrljAmjlomSrtrcNl58BeQ+MsG6vUqIq5wJYlGZu2zpSUcYJCHgvBrBfmuNAeD3Q3R/MdQYmL8UdIW1brZFMPU70e7lqDJBtdPlQ/Gyc4KhPXA5uqPc5Mkys3ScmoupJsVELX5yHY+7MclW+w1l6UrkfRUakahSpClmIVhxRPi0wdxsrrv61dl3NdbELWMq1YGHsp75mKvlyw8hriZg9XkXjKHEntOuwzj6bMJkzTVEaorXbu+55b6TgdjtwEx3B+YXx5YZwH0jytmcVwvpjxz1yNiiOhAFzzPDMNIxpNgelw6Lm/ueXNrQFpfdMW3YZSwqRMcoHU5rXEqecgpVR2IeMFqO6Q9nKDdV1H23dFYLenazva4ri28j3KhXJl9iZnNXGfEhRqvrZ2mFbgcg+0hVWysGJOmhw5QOgClaqcs2VAOME3puTtXKBpZsI0rMGiyx3BK74oZ03RWKN5ylbF10DlHS4UlaqsXJ4va2v20Tna/oFw6OiPB9rg11Z32/bW+VHT27g7nqzcmSdePn0ixsjN23s+3N5z7A9Mw8ikilIc85zQu8Ik1arKy0o09NU2U01BHrGWqFaMRSuju1wvl1h0Y3KaLKHJPCpiwj1NwDXuBzaKf5XjswgWyJ5sZVlDFUk1k+SdpB2g6ozUpFs5Uf0XagmhXCPmdZ3UCF+/tmOTL4tRcS6bQtHqJ1lepm11Vy3WGjBSSqScVp3HYRiYjpOlrwfTv/Riu6JvAi46EpvIjXlL6BV+EdpuzSiWZbFUFVtcwV/jFHVnrOIs3odVtSmJIzvTr8iNlgnczXfFTsFmZxhKkLPx8H6dWbFdV3e4BGuarKULUgPC1qXYSEXrxd5xVype4jCWJ+WcSFbWtEM8Qlp35f0UasW6LPO7xgGcNRJQkhke2QUrrN6ioVmer96ocVmYMK2NrutW/CrGSOMXUsFq4rIQ1EqNZZp5fH5imEazNuxa3t2/sWs2XIgpkRxkJ0xa3ofmcpOLBdls4+qe7fWvmZra5pjYMjcbjLdgXaepTZjJOkqmSRvpugZfBi5/6vF5BAsgl0uo7C0KNxXjLBmPL4uwpGE4Q9ivMqw//6Tsg459/WNKQnXqtabopT2KodtVEVtE1kBXHz/Ps6lSdT23xxOHw2H9ea25D4cDTXDMXcM0DbTzjEOIcyKFhtyZ0E2OaV2oVQEMNpWqSkzbcINCbqKIv9RF9+qmymrBwmdP1A1Y9F5oun6tz5umwe2UnNYgmWv7z+M0EYnk9MMgevW1+l1pKEVW7/VwVMEpCsFI8gYu19VhXiIbJ+cH7UivuHwNGuacGeNQNpWi+xHc2m06NC2ukbXMcFpVukxMOS0LY4zM44gXh8Mbz8QHLueRh+++59tPHwl9h28bbt++5e7ujpfhQkZZYiSKsmgmpHLLlWBhg4p2PvKuNLFzVq9pPY9+xeGkBD3nMiGbnoaII5UyRNUGDlNK+NfKOX/F4/MIFuWCZhTvtlR15T8UUFLFVJlgq5vtqACO8SZUMal7KVlK+byWFVqUvtEtunONztff0QKU2oKUNVjUx1cvB0sTLcMYhoGnpyeeb245Ho9M3WQcharK1HegB+Z5JKVToVnDKBMRIbuEF+F5fFqNkPMSaQsIV8VaXOlOWACozEfbRfZl3ZaxFXBt1fHYpiGtw6B0bYPfgX2umCpZDb+9d4/9HaV2pPY37XZp5fo/WwlTCUnKNmZevy5aIbuUbnsv6osZ9C67KDeDlWKAViB0A0Yr/pQ0Fz5PTwhWWqaUflBaOhHiZBaNy7KsGqYiQt92vLl9A77h08MD3377LR8fP0EwYtub8wXferrQsLQdznvIkZwTbdOQytBazlyxOp1z7DVEtzHFGhT/4ltpDcIiUNZGigrhhxjev+jxeQQLtvTVAkP5ruxGcLXOGKSyy2yH1W8A3sxyXd3lroHIurvug8XrzOK6bKm995Kuyw+DxVbJbC3IeTZNg5eXF25ubpgP9yxNC6ErN7tpLOQcyTmS1JSnnx6fi/5lLDuaAabDMNgYu3P40urrOgNPUcVV0DamNchda4zargyUtmwBcmswdL4I8uZVC2IdY3euCLKU0mPd6Y1NCKyau6+PFVsq5QayX/5//vE6M9lLC+z1N/at7bUNWYKyPTaVsXZjtMacEO9XNfTDweY/mtBsz49R5JcY+fj8yBwXpmFcR+FvTzfEDwsf3rzl6emJ88uL+c+maPjFcOH2b/zuisVlgZgUV+ZZNMa1pNsfBshuDNQtsNYb/8c7ca/X7nou3LbZys+QXXwmwaLy2jPqizs5CzEutF0DYk5OUevCLV4XRWdTMDVoEdMUcVlovOk9Ljmu6ayYMIUNMYWET25NnWtjxIkJzXhn9HLDEgwDkNpmTZvwiooHZ2KtWYW4mADuvKRiF5hhUTRab8c7YVxGRBPTNDANA5fnFz59fOS7775jPI9lV/F0lK7MnNb6tap4OwyDEBWiKk49OCMUNdIQo81U1HTdA9mBkxbnLSOq92MtV5qmpS1dG6fgstHsg/dU06caNPdlQOVCVCxI1FidtgmY4rXFGWHvfxEz12m1dwUwrR0JV+KyaXCst4VqqeMdgrOJS3XEbBOWNk/ijfAlJsHYeUfX9ogLSNPSNO3KTD01DRoXNEdUMqKBOCeGOPPp+cEo3jmTk5Why3mgydBmyMNMPI8cJZCCx2Vl/P6B29//Eq/m1lbFnV1wSDTSneaMFDheKB09oJFCf0fK8JhlWHXor2q6kO0RqH2t5mWx8ivapsEH6wxW3OWnHp9FsDDMaEeKyqDO0n5bnH77OhnlNVeVrFe52ZpFrKWML7iHQ50W1mHdqdJahqgouuPUr69txS22Nl+WDdDLZFDPEqOh7GUHSIVabU5iRUnLebxYVydFcxubxpHz+czz8yPj+cI4zuvCbE8n4HpwbZ9SR2euW07reHN57I7eXrkbeV9iOWfBorIm3Q9tFOoZqJ+3oCBr1lEXYaCxxV5AxlqLa8nCruDNK4LVK7cs1atzX//uHlTeg6L7axNjZEkb4auaKNWfmSWm4QyuzLzUDsi0zEiMprbmFJlg1sTLcOHh0ydziBd7bOtbHpcnnDpOwWwlUxHdcd7hQ4DG9EclNEjcXNHZAbCV67OWICK2ztXQu302XB33LDbUki+xHyj7MbKXK4rgNcD/1OOzCBa24AOqS1HONn1DhyDZrX1izZl6y2rOzMsmHiMlIpMFL6YlYHC6iebYY0xRyLPXdNzowuK3DkkdXtpf1EpJVqGQmbR8Xsr78PRdjwTPsWm5OfS8vb3h7e0N796+4cv3b3BeWIYXnj595HGa+PbrrxnOFzSasdDpUF3HHORIJDLrgqbMEltruTlZW5RIyX5iXpl/MacVhHUurCxGJwEhGRmq5CfV8UrEl+6S4REl1JbOyQr/2LlRCoW5BggD23x5rqrqpKpEXSxUiJi2hWzkK/PjLM/pBPFSMu6NzyFqaurrvpjF+CiYlJ+xN+39aJrLS8yQM0GNFp1itk5LLlOYSZnmpdyIEUkJL6kwKBUJBuwmhThmhpeJw42xW3/x1e/w8eNHXi4Tf/jP/hkvz8/mRXI48O6rL/jwO7/g9t09U0rMS2RM9jHnIugcmtWFzWVHzJGYo3EkCk+mgpdQhIZLUE45lVGFRFIlabKsArPA3AJt7Q6Wrk8Q4K9L65S6ewZzzbaKmCC+0IqNiOWuwE2Pc35blDGay5gW9uCaGgeybE5P9vsJ1R+PtPvW2+tgnEo9mdcSpHBCEHBmWde3HYem5f54w5fvP/Dm7p7T4cihN9FXyEw5ry5aKc4s04AWERwtO5jJ+s9MhQwkxVXN0nkt/q8FA1hBzioYtJkuVSJUbS/X4OdECg17a1evO10Jrl72bbkt4NYsq2JKTrespM42UHpVWsf9V5KQ4UTWs/E7nssPqfXmrbPv6NichfhA45Xko2l2tgdit5CLanbaGxmJcSK8eCR41AeiCvOyMMVCutNoamPZhJS993T9sZQpJ14YiUsmNYBztG1nbmbjzMt5YBhn5pTh0NLeneje3CLBkb1hDSbhswoE1lSaqiVbr4mXnbmV6CbavAP8K/SwZppmMrA7f/vBtEzOWwb5U4/PI1iI7XOUmtZmDyp46K0GFredNHUG7HnLJnLOxb3bsgmr04yZ51z+wU2fC7i0b6PWYz8q/xpIinX2pKTXedvHCM7mQI59z5vTLb9494Ev3n/g/f0b+s7Mi5fJrP8uL09cXl6Yp4HxfOHp6YnLebCBJQlM08DlPJK9EufFNDzqQhIj9FSila8TnNTSa++n8ko8pzBla8tYpHQnxJfwLJbZXQHCspr1ghQjqPIB22fEgNPaHSrZiffecIA6AVnLJU2WNawFSv28TQHvg8cGPrKWD23u1/OwxIllmc30R+2m1xxXB7RaT7nyXMuSGKYCWmqk8WLAdY602tErBNfQNJY5TdNMVsfjp+fCR+l4+PjEshhRTr1jmiMfnx45jm+58x9sfXrLXNBcAOVMrhlZKT8cVp4awzRfvV8tmI1NqAqQSsDYlXBr0Clgtly3YH8OvAI+l2BRU06xVrwi5OzwyTIKLVORUmXR1UqSitJ7cUiV8K/t0FclyDZlus8YNnDuNU5Rf34dLOrE565WLAs6pUQUs/O7aUzktvOhlFJKnEdelkycRp6fHhnOF9K8rHL5dErTtCvGoKo8nl8smynzEOK315lrNhWC8T/Ke/DlXFnQC+tnCzSmY+ldS3Xfdm5zlFfZrA72I+ZX52RPlirfr23UmuFs/InS7i6Py5JNkZ3rbKL8h6oXiZFXtr+3si9tA3EuEJyiTUPOhxWXmMeRJM6Yu0skZi1WDeamrnMmkhljZIyRJS7EnGg7Kzu8ZshNGThryEtkukycXwamZcaFAVXhyy+/pGvaFZPqjweksQGlYZh4Or9wSJE5RWJKxGwj70oFKK9OINUcy2jb8VWQrFFObPTUTkoZhDBGshkT2Xlau06yZXt/iY7rX+r4PIIFistS7usSXctorjl5O0h7Ao/1/eOSdtiDsT0LIF4APtYUvAJEwKu2ouCcrhdlPwK9b21JBaCAnHZsQKt1VrxgGkamfiCnBRHFizIvIzE5XI4s08j5/MI4XYqATS5ivXa/1RmHpmlMJ8EJLBtIpm4rk1ZAWJyl69QhpcJKrH6jta4XbwGpeJxS9C+MAbo7J7srU7sw9eYHsTq5lgVFJsD0Q8E7WbsZ9cg525CVFnMct2ulrml3fV9+nffY/qbuODX11HucM5ynbVu6Alh6ETR5UjkfZRFwvpyJSRnnyJAiczahGvGOqJG+Op+Fhr7r6dseiZlpGIlTZJpmCInw/MxXX/2S2+Mtw91bLvJkRs19S+4cszOMZRgmxmFmmheW0gnbd6DWla+6+roYYG5r2peMUNlAUCt9tzkbyy6MKl+d4qsz3ooNOcefZ5r8L3J8JsGiLkYTsPVKaRWZwEutm1fwTSM5Q8yKc3sjIutE2ECWZRWr6M3OFs5YotvATio+oeBWb1WjXBdKbZ16rCkihvrjLMBZjLMbaJknlsko30shVLWhSN7HmWW+MJwvTPO00qsPXeRxmAsul1mmhWWey3h5NnJyyQKA9fVVQ5uErjhPzhnvqjZlwAXz+qzBwhZiRdv91fOuK7kGIb3GEq52vFQHv6QMLBTko2QAtXZ24lDn8SoFTlKsJtFVURwovheF3yG1C7Cl2levoUxfriWWgh4zy3jDEmdUE8s0r9dtmiaenp4YLhOXeWFBieJIDlwTkNYxNoFT39GcbldyVKpepqWbNVwudF2HpkgTAr/3i18w3t3x9PRkQevmhhiE4B1PT09XKul18xIpDV+FlDZlMCuNFrKYcFL2nqBFd9QpMZo5kqoF54qZrVmaM8DYrqcF3hAsgNTz91OPzyRYGBqlmspCrd92VDcyU4Jy5UYpGhDRrQNIdXS3Li4tFNic2XQeAVMXqjVhnfSsJ3IDQlfex25Hq1Fd1KYdXdkNbbfHfDOlY44L3377NY0qaZ6YT3c0bUDTRFpmKCliXIpbemjxfiSmyDxHhmFiGAbGZYacabyzHVMVr1ZWiJo1nys7k2XrFSCzHVq8w7umlDbNbrL39c1fa1q/7eC5zIDkre2Wq+L6ThwWChMW7GaXSjMvWlXeuBoqmVTaq4m0Zn2mhBbWc1lWA1LO73Wes7VOjUQG0BLbjrYLNE6Yl2lV9Qov1gFCHX03kjJMxck+pUyaM5dhQHqzMmxbx5ItI+x6T+ha5vGG4fyMDBecb2kDEBfe3Rz5t//Nv0PjPBoTuYGBxMfxzHOc+L/jhTZceBkHJM7k2crYrAVZ2gVCF8z20uVSYteWLwtJI5qFmBe7xmtWYWU7ZfBRvKyUAO8F31gbdw94/tTjMwkWcD2vsbtB151KCL6a6ZS+e7W92wUKS+t2/fmdOI7VbxHKRal8BjuuU7UfY8ihmw7n1a7rnImiOqFtGzwWoIZp5GW4cNcfcdkxz5E8TzbCnKIJ0MR8tUvWD+89TGVBJcii5LgXtC2lD27F2S1TqM9hN0oNFC74dad/nSWspYY9yRoo6rlfA3ANuFnWliuYz6ZldxEnzpixal2ASuG2zpGQNbPkTZsCjGmI1Od0a+tVhKu/fc0lKOtCjYhXyxERIR3TuqtXPKM79Cwp08yJlBfIM+RYSFPCsT+Yg1zf41vjZLQucOhaDo3nPGYa5zg0DYfW7AJ673h3c0vfH6BtGOPI/XTm0zLw9cPXhmNlm12KKaHRZA+yiNG/NVFJatVkapPIu+b4rBlYKXuN6Ump0Lbr6dwG0tvX4a9fsLAIWGGa7abR9ecFiU9bDVdFYuvJ3KetNWDoK5DS0OG6AOvH60X44zb1VWGv4gbOOSP67OOMByfWLqzGwxGlFTPGSTEhGC9ijgvLOBb5Owt4a3ZUPSyzEjWCKrGJ5KiFurt1OBApnQnZAoVzK7hZOyCulB242h61Fmodzljfc93xlLX0+sH1ykJeORpbqbDe1CuuUqnmQioFpbURtRIbIRuzFarilKMpHY/1nO+ux6zzj95IFRhum454sDmQmJVpMh7MWraU5w3O07YNp3cn7t7ecX97om9C8exQkEzbCLc3PVOeGePC6dhz7DsaEb7/7Z8S20f6tqM9HUiNw3fCUQzc7nxgEk8UwyDMsnIxf5Ocr7ILAOc9QbZSc215X63FTSBoU4grA3auYlVV3HovH/jTj88oWEjRY/QrkmusOHaRthBUpAKXZbGkTSBlXaw1nUNX7GHLHrb24io4w7Wcnv296wynft872VL+knKrqtkDopjFeBGZ1Wx2gCkTU2KJ0WZlk42iT3Ehx6I7UT7HJRfviYDkZNaHudgdVmYmBaPBCDxWp+44Ii6sGMVr/sL+sPdVkXq/kqHqmPhWvrHpQdTrlYUkYNzujdG5nRuz6SM7JFDOTy5yiECq3A4lSsa5jPeZ4Pxq6lwX/H502zVunRDNbBmErrV6oGutrTrPM6E1I2i/JLquM+zLewiew+2JD7//Bb5xhGABJBTWr2qiDY53b+9pji1jNI+RU9ciaeZPfvUrfjsuSMr0NydOH97y7vd+Sf/u3rKzaA70mrKVKsn+H+vaWoOBqXKJ2xTa69qux145rLZUbQp148fUDaLS/LcN469RsKgko9o6sxagmQlXdH9LQ4sVgC91sXhEUhnx3ZUoYKmwXkdf2HYwAzdrWbJPd388YKzWBOViaAEVa5p9NS/http+TpFQCEMq1sbLKZHyFoTWrkpZ7DlnOs0sCvM4oTkTo30YhbxQ0MXmZez9WBlyTRcuizJtJCAtY+z12DKu/OPBYh80r66bvb/oNi1Iex9bsKAyTqPxDFIRK7Lu1KZAnpPR4mtAaHxAnK7pebUm8N5DTBSG+vpaVzUtsczPe08TWtqmo2t7+u5obNRsZLAlmzhxf3Pi/vaOyIyIEkp5l1NiiYnToac/HbjnDdHaTbQh8Pz0id/8n78mPl9IU+J4c+L+F+/5PZ35yv8+seiQTOPIlKomybQD3LeWaSy6Iq4JBNlKsP159gFyui5PNh7GTpdjFyj2mcVfG4BT2ep/V1PbNRhc8+rrSaknd+8/qbvWo12QH8cetr9VT+JrjER3r2wLGK/rfamBDF1vcvIPQdGUkqlSua09Wxe4dw2qqYycK7aH2g2SzrXlq2tJU53T1xS1dmR2i+F1oLPG0PV71N17syyhfK+cM9mRh+qUrb2f7bpVpueWgSRUvE3BYmQmLWzXqJmkkVhcu6JGJHk7N2UEvBomVcKRQwiNubmZEI+1R+/uN83M+h4qbrXvrkjwZkvYtZZdzPN68zR1HagN6+EyvilsyphI80KOyofbGwgeCQ2+b1GF6eXC83ef+Pbrb3DjgkvmAjdLpLu/ob+7Yels+nieZ5a4sMSprM0SiNm6WrG24r2D3XvaHzXIV66QAcUGbiu5+Opc4141W///LbMQkf8a+I+Ab1T1Xy/fewf8Y+APgF8Bf1dVH8RW6X8F/IfABfjPVPV//wtfRcUNKpaAlvZQIfms9a+U9AzAYQOflroFGqTw6NW2bONcZKFtuut6WjJCA2qO4LLDNSr1NsbpatcXV6N4eR0FZ/LO0zjz03BZ6ENLEwJN1xGOPbQtdB0xGFNvicI8x7LLzORoNawPHo+iHoLXgiiIScAH0JiZdSLpjAuJxgsSM9k5kvVWcb6xgBYEGo96TyoBzro3gahKoA6glUVUb/a1XMOITbplF/8vd28Ta0t23ff91v6oqnPux+v3ukWKIqXQDqxBEiDwJJkGyChAAI0CJJMEiRFNYmSSQZxMYsATDxxkYsCABoGjSYzMkoGByI7B2DIpKowVMogsQSRNq8nufq/f5/0451TV3ntlsPauqnNfS6TYhP3Aalz0vfedez6qdq291n/91//fMo/WZl3b00DY4kilBooC4q30KlZ+zTmRtBKo5pkynhY/j/F4YppOlLT6zmorrYJf3NGG3Y7H11dGxa72govAL7l2SUK99jNOHZ0P9HLBqBkpJ4wFWczZbT6R7o/WZpwdRcR8U6sD2HSXGPaRvuvxEqxtjueYEjst+FJp8YcTod9x+/Gn3Fw/5ld+9asc0ivmlHh+uqvCxI58OKHRM7mV5NeFnr7r0Ojpu7D4u2hKNG8RW5urh4myZtBdHxcwm9qdKwLeO8RH5Gcg1gs/WWbxt4G/Cfzm5nd/Bfg/VPWvi8hfqT//18C/B/yF+vVvA3+r/v/HHjmnOv3oaorp3totWwpn4FBD/21BxViFZTZptB1rpG1HY3O270tZ/TPHsY4jV13P9fVs1NlS5A5XtA4+tTaiXcyuq8EiRku/UQ7jgZg8Oo9M45E0mWivOYgbkhJjRLzgxXYPquJ3SonTacJpoe8aB0SZcuKq2xNCVynVbm2NOsesBcl2068pqrPspFLqbX5Cl0C9ZW0qNmqfN50kSisjGphcS50pLSVAKYVpzozzxJQSxzTVcf0jh5PJDR4qzfpwe8fhcMfpeGQcR3sPFc3vY50SbXJ/fbd4ku53cbFUfPToEdfX11xcXPD4vfdXTknN0HABXODxpAtN/NXrF8ynsRodKy8+fb687hA8uxjM4zVG0EzKE4xClH7xhum++EWeHIC7ifk08vrNLfM48ublG/bPPuXRX/hXTJYgJXJKtYVrmUSmkLyRqSIG5vZ9T7zYoZqXcXxrXa/AfdNPbWV5q1XMs8afrXNh/XkrhPR5jh8bLFT1H4rIVx/8+teAf6d+/z8BX8OCxa8Bv6mWQ/2OiLwnIl9S1Y9/zGusNfgmUGxrLudsDrVk09BUdz5S7pwNkbUb+PzLv3WySt6WA+fal/b/cNZloVKaW8uy6TbWWaHlM0z5PMjM88QYB3xwSE5ompGS8VV8VlzBq01NGhOzUsvrnIuqkXVElNy4I7UV5y8isdoJFoWsNo16SgmvylbFyxePLy2DKgtAycbeIGzOewUvgDVdL6poTuS5sCUczWVeau/jPHEcT9zeH00IZjwyTRP3h8Mi5NP8TOY5L/iFgKmJVRWw/WClh4t+Qfgbt6Lzwcx35kQaJzMr7s0DtpkSN3CvtVTfe+89U9hKiXE6rhuDuLWGAAAgAElEQVQCyuHO3ODEKRddh7vYM7iAi33VywStbvXOCdFZaXT1wfvoMDHdHZjmzH0azRlddRnR33Yzgjjm2kHLdTYma2auLmtzVXxvpdmWH2QXQmsfqVReUlmu1Rm2VrE/51Zg9Gdx/LSYxRdbAFDVj0XkC/X3XwY+3Dzuh/V3f2qwgDq96K1tCef4hHPOKMoqiG9Zg0NLlcmTNVXeIuItiLxd/wVyWr0+muuY6gNvh+37W1qI1aXKreIy20BkgGmm5ERKM9M0cgpHW7hkvMAQAt4ZHRsvaCqUYsFQtXZQUlo4Evbe6o1fx6dd8EgM+KrElFNmzrOVaMU6EO2QhdFpqXVwRgASVbSJxeZCkrCI2IrTjcZnJRPVoDpPE/OUlwA7l4mxqlzfHg/c3N3y+v6W++OR2+O92QPWcmOaJkqdcehrQNjtduaB0gUjVHWey91u0QJtJj7ta+j9ohbW93EpHed5plHG7ZrY9953XFzY55qnifF0QHNhnE/M80ieMuN0RHNCdj07X3VQm0CxFuNEFEfOtXT1wuX1FeomJue5P5yYD8IchFCJcNud3sYBzFqgNFC2ZFxW5toeMq2TVa9kq3exxZwW4JraIdRMcxLabpJtTf+sjp81wPlZuc5nvlsR+XXg1wH6fagu5v7sw51lF+IMMFPrgMDb6HDjYjhXDWeWjsdW8t/ozd6tRi1QJzg3vestmpyz7QJOCyJu2QFbQFKAreQZMJfVlb2Jr3Qe+uite+KdzWZUrYVpnvHqmJKNrp+mjcO4OLRkcj296jw+9qhUOf+aaaSSSaVehpIXdSWRTNSCL3aTlVQIbLKKKhSTZwMAvWtdqErsqQFXs3mYWHt34nQyAO84HjhNIzeHe97c3/Hq7oZXVe369nioi79CItZZxXu4vLzk6vqCq4tLu/G7OucRIjF4QtiS1Bpr0xE7V02bDfTsoq2HlJIxdGXG+4CqTd56r+CF3TBwdXXFNFlb9vYWcjatkDxb1pd8sAnmKZM742o4bMBu6cz4QCfQSUA0ENQz7O+Ixc5426xiCIs3SVundqNvDK4Klo3UWRXcyh1pj7eA89CrZtvdMyDdILVaptR7qJHC/mV2Q5628kJEvgQ8q7//IfDLm8d9Bfjos55AVX8D+A2Aq8e9llIFxkrCgvHmramx/Ax9bxN2nO3qD4PF1pKu7YDtMd6HOqTWdB3XMd52kVrHpb2O4pBiKa4NLvVWRsiabi6tR6jKR9ZWLVJsscUOFz0SoykqYV2eMivTNEKC+TRzX2v7cc4Lu7O114pWpujQM06JY5nIuTBXNaWiUgMGZFqwWS36uhjpXaBrw2+wiMTKXLO5Wr8bKFcdTtscQ7Kbq8yJ+XTkeDhwe7jnMJ24Odzy5nDHzeGOw+lgDFXNldkq+N7A6BjNEvELX/oCj66u2e+HZRCsr++z5NmMilQRV0w6r1S7Qm09ow0RrJYJgofZRF8ajdwHB2Wy0uHqClHTjkBNrUxUzdDHmZRASTZbkmJ/ZvHYSprOB7oMnYu4EnDq6C8uGbKBxDF0i1/tYiq0WaPeeTyWTRotvq6/nFdpwgcluLJuYq3FvF2vdp31zDjc7otM2aikf57jpw0W/xvwnwB/vf7/f938/i+LyN/BgM03Pw6vaEcLFmurM2OS5g8o1/UQ8fgQ60nYUMX9OWX6nOm2kTFza5mT8xoclrbsg0CkOLya5sYQO2LXEYJfWokNgGrGxapaXcfqTek9oYuE6HEx2NZacYAswphmmJV5tOGz4/FAqVyINtxGLbMQT+gH7l/fcDxaap9SWjCNxt/IVfei8Q68t/e+63qGYC5jXlb/0lgslXXOrAXxdbDOe9MdbUE3z9YqnMwc2OZYjovB0mL9GANDMBZp9ObKHr0BlUPX88GTx+z3+zo2b5BkK/E6F2jGRNoCZbY5Cfx6gyTVCioLXb0GrhQztw7WSaF4kDrNKW7xCDkc7+hirGbJARfVHMqK2TLM88yUZooXwqYz5mtJEWMPeYYixP1ATDMpJ8LQbdbp27R67x1RC1o9bRfv7RAorBPGW/9VxFqx29J62SDh7D45e80HZcnnOX6S1un/jIGZH4jID4H/DgsS/4uI/CXgj4H/oD7872Jt0+9irdP/9Cd9I+2DbjkIW4ZaKcUAzubSXTLN63ThZsgq3NJS1nbSW/pXP9UyGm0XRM+8Tb033Ye1LrSGmSt5IQcFcWeRv5RCcZ5JpyUbqBJSRt3yDglGAy/YIrd3wtI10ZyZy7zwMkLVTwx9Z4In3i9ZQi6Fw/HEm9evubm9txu1DrqkLCv5S230ub3Pvgtc9AMX3cAumnpXqOl1r/azEZoCGmqgDRYsdMMoNFMlE7mdphPjNC7nsOs6pPPsqkqW91ayRW8lRhf6pQNgcn/t+RKShOCELriqdFUzuzSjqsQYyUWYslk5dtS039fR+7DK0Tnn8LEjBMc4TXbjdWLK33nmdDDhof2wJ2cDPsEtzM+c94xpJmkxvQtvQ2MuDvjQMeWJ3kUkOkI3sLtSpGRiv7POyjBQ3thayA/KiK7rkCIEcaabMY5GM1/mYuRsPeaSzjaw8uBnMD5NTgUX1+v9sKv4eY6fpBvyH/0J//TvfsZjFfgvfto3sxKqWrnRdAUT0+Rg6X7U0fJ6UzaG3/ZiNJxgG20bR0DEk5MuiPMigJvSWbACloslzhFkBa5EquxfaAIzcvb3sOpmLIFDPFMpHKcT0dUMBUcYevZXe8ZyIM3CbtfTB89xmimqzKOxDZ33HMaRjz/9lJcv3vDpjz7m7u7AOI6M48hpqiLBCKcaPJo+goTKRUiZq93ALpr8374fuLy4YNcPXMaei93Abrdjv+uZh4E+BYJr8oZWW0/TxDxPpDSTSkK8YQhER9COvYNiJBTGnNfrWYQpwTgeyKnw8iZZ98MHSklV30OrIFCd3QjV7McJMQSGYYAuLpnWUHU2kUicJzoxnCIErfoRRvLqYk+InuDsJt4PHfv9nvfeu+bx40fc3t7y4sVzNGeCE3of8LHndJxJ4z0vnr5EFHofeG9/yZPLa7rHv4gMl8TYE4eeIIrXgr8YiF3H5eUlj06POBzgOE+UaTafW+9RB64UPG7xDjFymJ5tUushVYFeltkjJ3Uj1YxWXZHtoKHdJz+bQAHvCIPTane3TOA9TK1UKxCw0KNtlNwrS/ei1a7bNmYrJ7ZMvyUD2YBM2wnFLbbRDnt9K0Xe6qyo1fzemchMae7eDx5n6bMJ4qZsJVbwlj04MRxEdmakm1QowZExrcisJkunav4iLzNIKrx88Yo02Zh9bjjCPHM6TYZ3aJWa8AWcEa5EgZSZw8wUO/KQ0QxznwgXumQWITr8bHJvBBtD98rC6rRMp5Z60YSAJZc6Jm2ZFE7QKZNKIafmtVoYT6bXgcxLpkZd6F1wdF1grFYOXoQ+2mYwxI4pKf3ltq6fcKEj1GBvG0SzHmiOdmA0+BW0DrJDru37Ux7php5UEvM44UVsqnTYIaLcnhLj/Ug6jYzi6K7gET2pnyhuBhcRMYWyOdm8z64UfAj0+x2djsxaSFXpO+VsZDs1tFd8U2Bf2cMiNqIvtgBtrcmadShWwjo8FcGE2k0rpeGcq+fOz+J4R4JFOzn+QapVKsdAECk265F1ubk9yRZbiVBt7Sj5bPdv7cdt1uH9mklYja1L0Fis7P15Z8aANqnoeqxlzvkMhoixRVsHxJh2a/q+LalQJWVHUlPqGrwn7HZ0LjAFz3wajX05Qpc62sDc/f09x7sjDuF0mkw2zgVCMOwlZiXuOy6A4kx3Q6VhGIoXIajQeSMe7YYdXTfgXeB4PC7knhBNgDgFvy6S6ubtglGjm5FPTBNzMSq3VDqUNVqs2zKdEuNU7fSScqi4TEpWGrTXLJqJ0Xb+631vwZ7CaS7EkDnGQpcKjzbgddjwz8W75csHZ5lEqMrfYkxLXzEtY80aGeGL+iWGYUBEOBzubfYE4XI/sHMRl4V0e+J2PDCPI2MK3OfI2F0zSUcIXSWUBUQSqa6nVop0c8dhtA5MVlMWL14oZBtgE8NWxHbDt8DNdi+gbqGJ60IstO6gJX6yEAwf3lurZslPf7wzwaIdwopTwJoNOOcQdeRi2ok5lXXUd8kgCqb6vSV1VervA5AnzWWZR0ipnJUkdpEezFtUMg1+TentdUxqruEUKz7SJmJNi8J6/JmiibkonsI8O7LOJJwBf8ETkJqeQqqKU1cCU8qc7g3MRMF7KyGcCzVNN7eteZ5tItXbDZLVBH7TJnsiZQKOrovrjEULBG6dHm1ZFnW03FM57m1EPwheHXHo6UTJghn+SiWPqZ1nA0IThTo+7yM+KMdpZsqZpA51iZxnhtKBz1zFHZTMOI+MU0LGCe8num5md7FnFzvDI7qe2A/EfjjrgG1rfuMpmLXEoj0qDnGBWAq73Y6siXGa2O93iyPc1cUlFwRISrob4X4mjUcYE+nuwPH1PTvXMww7vHP0rqPD5nVO87Rwc3LOViaOJ9JkgTWrUKTQhbi6vwHSsLM2IFg7ZpplaWGXapS8zO7gSBtj8NYxVLVs0vt/QZjFv7jDFLEap2Fb90PNPPBrBlDMxtCGh2Rd2M64ECspJy/033YUTQspy9iEaybQ6j3vzwGmNgG7zKk0D5El+7CZkW2JuC15APMsXUDHguSCU5u3KBIMRBUD4JyC6wZr7cWR2/sDR2fkrl0c2PV7fGdOaDF2y3kqpSxU81QKY545zRNzxVNSSuRxglQIzuFdld9zDvL0drDblFSlUtNFrMxwwRNU6XdDnby161BQUsnmlbEJOl0/MOwuuKzl1fxcmKbJBJk1Q/DEYc/u6pL91XukPJFu4Xg4oDnT9waSXl1dcXl5uRC6drvdQgVfge1at1Jwzi8Twu2amMxBXQ8YFXy/3zMMg1H7Fa4uLrjOgXKaKY9OdGNmJNJlCNkx3x2Yhwt0SsShY+gcJ2fdrcPhwOgKY5VWvL+/53R/QFJBvVT4pyy8HJFGDViP802zrSnPqhm7YhSNg4NW4V/A42kGzD+L450IFm0Dt4VZOwmSl0W7YA260rFtYnPFJpYBGxFANsFCFjep9QXLQvdumcUWuwDI2YJDI1/5JlEnn40uiwjNHkArfdmJpbmpkp6m6gGCFDzKWAo7v9KZzWYRfAh0znM5DNwde6aXr9G7e6Zpwqm9p6urK1w0ZmCT/G/s1+iEmWJYwQa83Z6nNE5MqhQ/k3qjNXdl5uJiZ6SsBKm2nTPWUmwBycNCUAKILROpz59KNpGebGpYQQIlFPq+5/LyEh8iKRVe3J2Y0g1ZFZWqQ3FxwdWjxzz5whdJ06muAQDl0fU1jx8/5oNf+AKXl5eV4RltIrXSxA3sXnUcVp6CWzOKDcembQYx9nS72Wja1aSp73v2peNqf8F0eYUeJ46z4saET5XIVVN+771xRPJEUgPPp6DL0FxrbwcVmkesde/WNaS6KrHZBrNqWMC6nu2cbHC9go0/LI9dNS6aLOXP4ngnggW10i1i0ulS8qKWvWg5wsKSNK2Fyq9v3QZmwzSsF3mGUTjXmJpr3daIWHbzrFnFQs7SYm0tbRJzAXP58jj1lapUZ0ZqVqSwgLClovXOe3bZNBTvU2LWTCYThMrwixA8/bAjFGxALVcJ+xgYdFj4AfNppnMRUccQB8TZUFk39BRVDuMJ1cwYPPOcOaSR28PBOiS1lk0pMZ6qDYGDicxpzjAXetchxxPvdZFr51Av4LTyLoQ+tqzDJhlVhKyCKzNd51AXyFlIRXCz4r2wO0COhThnLsPMo77QdUrO8GYo7BJVC8SAzseXkS9cD3xxgNkLu6uO1F+x6yPX19dcXe754uO9BYnBMgobFvMM/W6t9711A9RYcQa61qDjqCP5ZaX4n+aJJrrs8GhOHOeJAcEPHWHoCUPPxaNHpLsD8+FEGiL3QQnMdN1A6goaIznP/HC+Z4h7vDr6WRjwzCKkzko+7xzRRRsKlAydJ0/mA7PJVZcZE1Er0U1FoPmLmMMe3kyXrWOyCiU7gGw5xs8NZmHlhylfzXMGKTT7PTAEf9s3VlWkrFOPzoU1kNRgscUtVN+2+W7MzZQnUjZ1qiXlFhuRTkmsPZgMte/bOLQXfDnHRrag7Fk2JFKHzWq9X7OMhOJyxvUsmgsyZ0g2P9Ao6z7MhM7IUjlncs2SLvcXBOcrH0BJ6URJE/M8cz8n7u7uOU0jx8PIOK/t4XEcK3OzMMSVi2IvcOLOO6KzbsAutjmZQD8MXF5eGkmryNJ1OZ1OHOZhaX2WuqvNtbSTELm4OzDntDA3Y4i4zvHnf+UrK0YUDOi82O/Z7we8g17g0S9+kcv9jotdT6xdkUeP3iP0Hd5FYt/hY2+Wj8GzUml0+Z9NDevCjmxpv2VBNjbvvWe/3xuwnQunwz2nw5GX9wZ4qsAwDExzZvaO7mLH1ZP3iLuBSTPT6Qi+RzqbAH5ze8thGjmmE1kToYv0DGQHU9XibKrymWD/hYArGykFNc0KVzeiVOYF1LQ1LGavILIQ97ZUge16/LkJFrDevFDbjGqpWKvl7OZbcQdrDdlIu/1cA4cPm2wDzrOJdiM//NkChDk5QcsUWjrXUnjRVblpy67bsuq2nP7lfUh7v9adaPRqgDnZWPy9nPBZCQhZHEEd5biOghfWv2lZUpBIUpim0awDpplxGrk7HLk7HMhJ66zJbADb0cbehz4SgqfrhioqUzGSyXxM1snbtd5tNPcYegC8j8a4FSCKyf5tvuaarV2Nk017zrV1qoU5jXgX6aLH9U193BZ8cEJOtVxTc4Q3a8EqK7isCU+TF2hCNjaq3zI7KyUWKUBxS5BoC6CUQsr2nEWtmxZCAKfk0HHCAOU8TkzHI9N4MtczqZICMZC9MOcZkph0f+jwRZlPE9Nx4jCNhsvUtTNVX1xbfxl1rpoLKa7KMaJWwtnkh5W2ro0k1PRVqlm41PaqOHlrk1p0bXWdIfk8x7sRLHQlYtlJqLqQ2rog6xxIs5xf2ZjGXMPbDtjcu7ZtTwPYtsM5q/zdliq+7rJleR/29nJVqjI+/ziuDNEz4tXynGsmZAv3bQZfe815nrkv8GqCQbzdHG3ys1LHp5QQrAW8CL2sEc/IYHMiz6nSxY127V0kRtOcnMa02WXiovvQzIicQhfbtK0Bg1k35yVEQuyJnVGZxRdyc2iLYVPSGS/EZxsHf3R5Rdd15NS6ItZ1QjMB654YP70h+IWcMeFc74jBGWisikdNyKbbmQGTKqFiKaGaKVfo6ExmceHf1KupNbVPTZtDN+rZqstch4iQppnT6cQ8jhQtuODpLi/oQ0T6SPFCQqFOIRcvTBh2c5hH7keT1UuYvKBm4340vIQHLEzxzrLk2gVpBrelUM9T2ywaf6RaJri3Kd+N2ZzzGqA+z/FOBAsFtNgidS7UXbwYV2sD8Gw9FaRyLpw0cOecC788d80QlptLytJKXU+uicY2oZW19aQLIGnPZT83sOohiHYecFhakNIIYGrlTa6DTEWVXDJjKtwcM7OPdD7XdpkidSIspQw+ELpI9P2ykH0LoK19rFBSHT7Dpix9MJu96G246fb21oa5vNkmdp3NitipKWetx1YehAoeti8VDy4RS7V/qixCK3U8vphWhOlHWHcm58xp6gihjqkX0DSvbFl1INaZ8c6xH3YEL4TgGGJP39cR9qqO5ZyjyOo6/vaKevCbFsTrLm5BvAY8ddBajxmcX9v1S1eui+y7niieoetwCHenI8lBCYKPHu0CycE8Z+acOByPHOeRhJpiQJWKzLY4UFjsIpf16UzBrGBkv1Kvi1JqN6phEED9PoizYARna+8zcPjPdbwTwaJFziW1otTdvzLa1Bh4NcdcShTEsVLDz1tNZ9H6LIC87f24vdHt+/VGt9H5soBMYKPQ7e8eBoqu65YsY2nTVaXmVCbToFQTL3EOMh4pymmayaL0zlpfOSmhJk+N2hxDT4hxyWqcM8m4II7kKmEnZdJprKQ14aIf0K7HYQQmScUo3V3PxW7HZW+6Ea5O/A5dz67v6UJc2JUx2uv6LuKjBRYVCKUzu5uSqx5G2pRjjckqC4clhs5YmA1Qns/b1abK3RFj5PJiWPgul3ujoDfMws6JLGbRZplgIkKGZ+lS6j2kTrcNYsko6qa0HTy0152NA7G7oI8D0Qf2Xc++H9gNgyl9ffRDRAvSB8J+D13HqSRup4nDeLK2fEkWQEpCa4YJLJ+5lGIetlqp3+Jr2WqM5pbnGflOKu2+lRiNQ3JOEZcHAejnjsGpxRvdu2ENyrKjt8ziPIA8zCSqe1nGEGH32YCOKV+vJ3Rtoclbu6rVtK2M0UWPsv28VWVqX4vGxSYl1FKqUK2SizEpzS3eUl4thTnbpG0WwzRSSsS6+L04CsFEY11EnOlMNn8I56g+awUt5totRYniGILHu0hQTyzgFYYuErzphfY12IAyDDv6Pp5xFhqd27mAuLCSmrTeWN7mLYpL5uaYNou3SvXNwaY3U0z0ud+ULGs6bkDwOudzsR/sOkthf3HB5W6w1q0Uct0cnHPmCFaZtObMtik9NteMBcNaA8b2JjJWbr1+NAf1nt31NaKw6wcuKqfjYrfncDryyd1rtCRK53EXAykI98eJ14c7pjQyppEslvXOaaZkK1PW9WFjC+2mL2KBoXFZqFmzCR9X3IvWRm2fJdMyjbeCw/L5Wsj5fMc7ESxUYZ6bMhSADclQZwlwYhPdFQQV8XUKMNYTvd7kuWUXjbXpmqx6wzrWHrSI1LmEFU8oNRVvGcI4eusgOEdwtiMcDoezHbHxMWC1SmzBpvEvUjGRVVXTXlBv3qMpZaQ4JCtTNnqz9x7f7cjHmdNpZBxP5hpfYK4mM6lkOu9wux33d3eM48gQO4I4rncXTNOMzDNlSnRDx8XQcxEjVzVrEGdiPhQgJRxC33seXV3Vzo+RlHbD3m7gzlzNfGhDXDaAEEIwEDFBjIIL0WTfyhoIYox0VdW7ObAlLXR+OGNbtoDRMgqbhnXEqgjmQwtU601uZY63kiz4FZiV1hqveIS34LztizWgVLy917koVIVxTVZG/cL7HyxBM8ZIHzskeKKHX/7Vf5VDmriZT7wZDzy/fcPTVy94fvOam/HOxIjEZoqc9xtG51z1M9Zu2tZjd5mRWt7oylJuPB8tsmAvoAvw2w4DQ1cG6c9RsBC0xDYrhjhro7aoW7LWQaRVct85B+ooGaZirU+RKoZAKy0a1pCXBb4CQCBSTEvBr9N5nwVCLhlHff2+3xFCPuPgay2l5tl2zC3oKWoswSJAEVSNORlkIHhPUaXf9/ShZx4Tb97ccHPzio//+CNub28peaZzjt473ru8QFR48t77puDsHB988IQnT94D4Je+9EVOh5GXL19XINHBPNFowZd1kjP4Zm9nN2RwjjjYLEMrp/q+rzL6PS5ExJure8ECoYaAitCJQLCdsu3kJVv5trT06tJPuum0FCtpnK7nPSwEM6w75aq+aPFoqsCdX8lUzjk0F+aUKUfL4BqRrFQTI5wQ8It8wdlRa/tca2GVgBdvcocYeW8cZ+Z8ZJxnxDt2V5fsri+J7z9GpiOn14mnr+/5wbNPePryOYdppAxuaSNnLRRnNPDoIuK785a1t9kQw+5ztW5oncFqUFQS5u72kKFsOIjbgPZrRisoTSjnXCbypzneiWBBvbBaBPW13qzcCBHQsipd2Y4NRRwxrje0nbiCbmrC9Vh1LFpq2/5uldZbBUdgW9u2wFVWRSkMoVdZ+9iWWrIwOF0tL5bWloipfYkJu4RgA0i+ODrxROlJk3J7N/L8xRtev77h9ZsD9/cngoeJxOigj93CPm2Lbbfb4cWhUri42DEOJ8jFnNznbAK7BqcTomOoLMcQbfw7VlHc0FW/Tbcqa50NNDnjENA+b/3yzlS4Va2EKhWwbE7zllJX/RCMSJa1kEbjnbQt1LXFr1bKoK3r0wA9m8NRzbSOFmU1GWqeJLm2xHPbed3Gj+YzAoasrZJ1RdboP9Yu0mkaOY4j0gVKH3B5IOO4nU68uL/h+c1rXh5uuZtOjDnhqz6sPtDObN0LV4OU2uJAWmXdDKmxbo4UG0YEkGoOtfi81q5IkZVesLz3toY5L7c+z/FOBAtB1slQZ227RqayhWaWhqWpSKdUwc3tDmPP1MRgt63VrdSYiI1T27E+xiZIz99VK1mWQKVNTMcMgURWivh6gRq2staiAUXbZCAAHqcRKZ7gO7oQmQ6ZV69uefr0Gc+fP+fu7sA0FxKeIUbQhJa8yOqJs1KpMNswmLPnVSAUGC/3xOAYTzPjOFNmK4+891XCzuTju64jdiv+ADWb2ogHLUECljKvsILIrg68BfHm99KoxrQMz1mGIOBVUMmIOnQsZFgUpFy7WaR2LYSNZcH5zmjlHGRWqn4uM7k01bU1WEgRcvN7Xch9NDcIilg3ZAE5xVUQHfZDb7MjXSTuBiQGuos9Ej2v7m54+voFHz9/xtM3LzmMJ+t8eIFNqVvjgQUFqnBTBTFtKn3dmKRYZ44aQ9tX65q04sTOV/0cC4tYz77s387lFj7P8W4EC3GE0LEM/4hCyTVtbDt7pvHcW5eiXfwQOswj1eYTzjn1Ni0pbj31zm8EbMJq+eb91k9yRZabO7mwgphApZGv7Mj2WZxb5z2cc4S6N5SKaFf1SKNq9z1OPTdvbnn27FOePv2UNzd3xmQtgvie2PdonpF5QsQZxbqWQ9lB8AGhDSWZ9sUwdHhvikzDaV6EeaIPS+kRO1/nKQykNOHf2pnYpLrtyNqYs3VBtp2xda90A70txLMNMi8eFQvwqYCTDAb62zlbHmtA5Vq3FzP/sRNs16ZyBxqxronAlFxLPuyGa2Q2SVuiHja6rxUuV624V82mkMVDNeds7NK+x7kedUISuL+75ZO7l3z84lM+efmcN3e3jDmhwaEKOU9VtbTgDUsAACAASURBVOv8Ri1VzUyKIujZQKKWgpRkn7FmH239llYmsw16WCleA9tyHjZZtT5MmT7H8Y4EC1vUdjQr+k1m6BRXzNN0jZytj7zKoDnnKDS+xpp5rGy3cw6E3fTn4/DtaN+X8qAO1BUMfQvIhCVINFTfe09X5QG1TcaKx4sniM0GHA9HPvroY549e86bm4MFCnUg1Q3bdbXFFigqjOPMaU51F+xwKAupKdnO1PXGiSilkPu8zIcYJgA+NLXq1lFx5GxBenue2mfenvdC281WTsr5Y9fFuixc8YYd4Za8ztfd1ejtVs7YDFe7xU3DRFUhz5TSXtvk7+25a64mNvJt/AnLvtr7KaXgct3VGxZQx9WVtaSzx8I8j4z3B+bjiU4GYt/hOpuHKc7A5cN44tmL57y6ecPd8cBpnpjUaOGl4h9SbMjPzonN/aiwku5q9tVmVoyTs5mFEllkAUTUsjFh2bTaepesaMOKNlmuPevPWbDwIfD4vfdpMxmlJKgEJiVTUvXCTNPaFitaQZ8HtVrlSLS5kS0dvB3W8lznLUpN/dqCac8l4s8IWCaNb0g0DZGuX82DUvDGjnSRUBmXXdWy7MVZm895HB6P53h/4vb1LZ988ozXr24YZ1Oo9l4IvrNhsc0Fb6SwcRyN1ONMUaqRcHLO+BjomvaiCtqtJkpLyu9ZSGhtw7XFynIOz85ZDRT6oKffzrl7sCbbYxapxLaLiq+7upkQB6cIpgMK4MWuhTamZcWsdFOTN53SUu0WgxMTFfZrBtNU1reBbgkKNTthecy6CUx5YjyeuL+54Xh7x/3dTL8bCEOP6yMlOCan3KaRu/t7E/HJeWnZzqXZN9pNv97AWKa8GZMXkbMRL7U3stLS6yFios8N90HWzNhCYOa8narL31nm8fZs1E9zvBPBYr/f8xf/zb+IqpLyTM4zqc4HzGmkRd2UT8u4dc7ZHL7aQsjnC2Ntyb1tOV/cuFzE0+lEruw9VyDlacFFch6XGwynuDCYNJ4HFduFsjpUAjiHimKmQE3azDMMeySYi5UejUkpWbi7O/LJs6d8/NGnvHl1y9NPXliLbQE/A+7iii4GyuENPkGZEqdZOV3OvH594PndkctdoBcIUogedr2Q5t78Umsqq6pmpVdbaA+Ja0sA7otJ53u/yN/b30KQVWG8nkXEW6aSilKQCj86nEQLDDlR5pGsZhhiQaL5WEDUCwtW1SrRJkE3FpU1NS9gDNHa6Rin6eyGGBcxntbxyMvod6k1e8K0NZ23EsSwsApsb0ol5zx93zMa950cHSU4xpLQZFO2p5K4zTOvp4nn45E7zcxBOKVkOiuihL6vM8liiuFi4kJajDcjFYtp4GtBCV5gtZu19y8QFnC82jJKxcXU5kqQYHwMKjDazqHaqLzq+Ybz0x7vRLAIPvDB++/Xm9QCxaIe3UBOlDnZzEOzv2sTnG93MVba9XJDlDXKZzktOEMXT2t2oco8TxtRnESSCgzKxgfChTq8o3VLrROWYkbGFSYEbGcNoSNIQKJQsuPu7p7nz57z0Y+e8aMPP2KaKrnLR7wPJgAbI9oFXCmM40SeJ3wpqLjanq07dgb1ak7cqnWmwltHAmpnSSu12NVS5DxFp+6CrjiiM/c3j1+Mk0UEUcuFlEqXFocXkxosdUoYVWtdq9aWp5ClZSWgKaHVR8R7R6b5rDjLHqy9tASMBtEV1WV+o7R/r2untWVV1fxdRarfCYu5jvETZNk8lp3dOZSakamZLdlacgz9nnKVubh27Pd7ivMklKQQNTOf7rn/9EeMU2aak4nPaKglAng31ACxBjVZI8QKaLZsViwgF5fP1q2IkbVscP6zj5ZVbpnDpVTj5/b9z02wCIEnT54ABgAZsDRvMgsA8w1tKXhKCSlrytXmBVoJAuc751bcJpMW8KroClBqnatIKXE83i+yey199RKMmFQH1ZKm5XXaY47HI9F5dvt+8daU00y4MgLS85cv+dGHH/Hs2QtePn/F4XBA1dHFPT50hDqv0XUdJ5rF4kRQU3Pyztf3aLwS8wVxSy6rwbKJZbZAdbUorMzQrjeWadnWx/U8icpGS0SWgLEQ2WopImAq06JI5SQsabSTSkaqICjnJYGzwt6sKAUWNzdrZVByvXZSlpbg9mvpZrSV0bKI2rKmZZs1qygCoZSzdbFwD8TWnGI3by7FxJeDJ3YDfRfoLy9INZgkwBePlJm5KFMupOLIroAE8z0JQgy7xXRaNdc3q/XzlKo7AVZC1BED7/ChO1u7UsE7xQhlfgk+bD7LGpQMe2oq+bqwXh+WiT/N8U4EC+89jx8/BtaT0E7yONaSQdOCH8yzlQe++ju25wCW3WerjrWoQ9WOgPrzdqfdfNPSXjTn8tMy07AAoBU4XdqHNVhYNmkB4/r6vcUjVFUpsRBQ+tDz6vUNTz9+xocf/pCb17ccDzPaMITg6yyGuV7FGJnnQsozToQueoYu0te69fb21rAUUTR4go8Eh/nBFgPGrDwrlGSmwW1X9pjiV5GmlVlXknhSwyHOQN0VL7BZDMsmWjrsxGpyKxVtiGpKMyVNFDV5f+rNYDMOdSJXqH2HNtiV0UoBD2K7Pu09nLUMK717iXS19HRrVlHqDZlF8dm4Hc7lpZNlsxey8hAs+gFiKbszk6QSoXhlSoVTmknOkVztTjhHEWcCvbrhPpgIac1aXC0hBJvkbaSr2knSyp/wzjK+UI2eNveHqtbuktjnaTae7XzgKL6B9LUlW5XNVRySfza3+TsRLJwIfTtJ7hxd33W7pSSZwrSmoqpmT7cMcrk1W2g7TD2WjKKpYcmqEL7UdyVBWbU4m7PWVmqvFNMyWJ5Pi+1KNcCUlHn06BElJW5ublBVLnZ7OvGcTic++egTXnz6grube+Y5s818wHYkmy2pGVY2g1DvvYnBhIivn+d4mpimRN9HUIfzIPVzebUMwKB+Q+a1mgRFcQT1zZWFtdLFugMpWclQh5q0aoiIt/mQdlr9JidRcWRv7zmVbBoaVTRIZwt2QaxCsQytZj8lGdiYWRifWjN1m5ttz09ty9raaEbWUv+t3TRSRYqpP6tbKdOtcNF6U7fH2N968GoNbWetb7raMetBoyfliZlEERPZCV00LkeemdNoYsW1LYw6ZplxnqUjZmPpjjnNVLiXhrK6Ot5ga/o8a7Kg8CenBa0cDpXAlmvptWipbjbfz3u8E8ECWQe6oEXGLbpbOQpSTL4d1l3NbXxBipw/7QMAr30l3pbRazTltFExauVLe0yWlRS2OGG3QDZNUJSLiwvSOOFdwCH2892Bl8+e84Pv/YCbmxvKXAwwdAXnbHSo68zWL/jOgsF4IicTcOmqxkH7TKVOch4PJy57o0xbWWLzAIL9nZlTWPnhai3gK6ZAcQtvoQXWWWq54bTK0wd8tLmQ0HWI96z6Q+u5dqKQIUl1gK9Bo6DMmvFmQE4sRuCipEWBXEqd7s2Z1lN1+CVzYZPV0PxuNxaRZ9e5rRdaBtJIZecdiKWLo0ozf24tWagUeO/I3uNDpogyp8SYjQOBVh6GlFrGzuCpPA0IroBOrPmBBSh7fqUxiM/KrLIqd5+fXesWNX5K64xs/98+a64DhNvPmrWc3Vuf53g3goWu5UOrJ5eTsP1e4gpYubV9BNVBW1Yh2e1CeriDb3kT9qDzkmTLymz6nIYo2+/nnJbnaZlIzjPBe8bDkew7ri8fLUHsh09f8vzZCz766JP63OCdCcaE0CHYTMZut0Pw3B8PxhupO2kIwbQfBBP3wTxDbu/veP/RFao1WDjTzvBOrP7PxcRW6tp0dYEZhlFTbXxdmYVRbSrWVaDSBY/vIq7riX1nKb486LKoWgACmzilApoiy5xOA1GNoVnLOcUAXDBuRT3HHk+RjKqvuEXFXTZAIe21N1mE/a4s+Ais0gM400LdSq+vwcIe1wDUlqGEtr58HUqrqIENjZuYkvc24BiiIEHYdZ7YWdY2JwO+kdlkDupritMz1bOW54gIrrglWFhpa2BokVKFmeu9oC0r2ra3jfmsmitT3rqAXhxZzjfRn/Z4J4KFiBB9WERsllq7gp02I2CIvFRcWDY7jogQYgsqGKCz2U22KDGAkzWYuA3EvH2+uazg5QKQViBui4+ALbbpNBobstK9Xz1/we///u/zta99jQ//8I949eoVaTKmY/DRlKyiKVYN+x37/R4RYZxMR9M5M8K52l2i47FKeRiCP6fM3eHIqze3/PKXvsTt3YFIYcwT6IwrStBqK+CMnenweFcxgCrZ1kykSwX3kiamnCBGOh8gGieC4JlFCVJ3XlXEeRTTg+jEI64aGoeIv2xyg8rNq1ccb++YDwdKUbQkfDFAemF5boO3x3ZJTaSy7XBtyjVYsAatn0mxDSNX3xKpwcp2YI+rS71g8xbQdm8LbM182a45pn/qDI84nU7MkxlAJxlNu0KUXR/oeocfU+2gnaAI0TvKWQZsHrWCI5e1zW+sYEHLKrJT5rSs2+J0ASYbxSKIw/lKE69cmpLyEghtjbvKQrXDvv+5GSQDqoxdacNAuXUm3hazydrEUirPX8qScm7l7NrR2qvt/ylP6wXZlC7tNYqcC+K0ANF2BCfndojBGyNz1/VEHzje3fOjH/2I/+f3fo/vfPvb3Dx9bqBdE44BVDwlg+8dMfYI3qzvxnHRyRi6nr7rmdNUTY4tmBoQWbg/nrg/nrjsvY2bp0pmmycmhWjQPHgl+rDwChpaLtLKmppNsWZ23tfd2gm4agNYW5AerdiFkZ/ybDepFOMK9G4gdJ4uRtP1nBL340hJczVYBvzKqdiCp0upqJWcpbIEi7J5XBFWNLwGjLIApc3ibwVTS+06rGuiVCBSac5yrrKCHcYmDcHayHOdW7JywcSlE4XjcWSebPd3rmIoZaVwW2ZiGIat2zWzzaj5k4iYonsFyFvQCHUQsYgseMcWJ3p4TzwUgQI2AcX/qbjHT3q8E8HCbvywfA/tAzu8PwcC16/1d6LOmJQb+bt2IwNvZRYNAH2oaLX8be29b3vdLe076wqwtmUfXV7RxYG712/4p//fH/CNf/w7/JNv/R5vXt3gJaxCs75mSTKbpV5leaaSlw6Mw7Hrd1wO1m6dDm0RiN1EqiCem5sbXt+8YXh8TXANCMxW/xerjV3RhQAkVahmCaSb82kLNRPEUHkDVc93I1+zBS8GuJoCeyLXLovUABWjp4sd0QfGEBlDR3KBSRKlnlsvguI3+pfFZiUqSLsocdeBwcaTAUjCkoLbZ9ZlFwW72RXW+Yt2k1YQ0tJ1Z/WPM6vF5s/qFmzBcKW5ZZbJrBeLlyqJKKh04CIhXOK8Pa9X84xR6w3bxuKr2G5SCoWkK5lQsOE7QQgGziHV8Ngh4Kx10jpsDatoceNPwuXamVjW6ueXs3hXgoUz/wdWb4vctAiWx6xWhWu6uII+2wBhNSwLkLTFKsDKEKkFjR0PGI31PYGcP6eu7yNXEpaTQECYxgRl5Dvf+Q5//+/9Pb7z7W/zww8/oguRfufM00MM0Z9zFfqJBmo2ncx5TlCgqw7fF7s9bfCIWntTJztFhNdv3vDq1SueXJnknLRAAZU3UEiuEEqhiO2trYRi+eTrApOKK4Q6r2EXJBmeUExX03xMUz0PVST4NJ5LCIwzszshQDqOmNxY3emK1FrcvjdlM9OcUBUkQyoF51JNrTeLv1L4zX9LFgJHXh6jNRiwUbtuwGlYrvPyydWG30oyinyNgKZjOiebMO063HGsa08IPtINl6AQwh7nR5pyuNlHTPgCKgVRj0iwVjOKShthaP0Qi+Kt72NTtmXhlIpXPNUDpJ6LRsdvR8Nu2mzIdjNtIwyC409kdP0ZjnciWDSQCQy8tynQcwJOCwjLn2wQ320gEZElMsO681svvWIMC7VlM+iEGgJfZzEevlZ7HwshK9kMR9dZ/V1y5uXLl3ztH/yffP23v8Hr168pKeG6juNUeSHOMyXji+wuLrm4uGC3vzSTm5ORz0II9P2OYdjT9z3TNGKtsGiVp3MLOHl3PPDyzWu+Mr7PzhTvqj5HbcUtu/P5zlMT5gXka6l7FIghEkMgOG++paVQ5ok0OlKwTEDUBJXLnJjTxPFwslKtkaUqCUxKtTYYJyO8pWy0cwqzUhW6SwVVhaZQ3fxHpPVMoY7E223l2nXlfMpSHrB2Sy1N2sBZXJ6panWKKYVlqL6tNfCkbHJ5mxZ8KQYiu6jE7EgKx5Mypw7nAt3QIxTmcSTPMzkfUXWU4mpZUkw0yBJmMwUSa3sCC2jpq3C07Q1G1nJOFop4E4Jdg2O9L5Y4eE49cOLrxPXnP96JYKGlcDhUl+m8BZrOuyEPOyQ21t5KDT3LNFYWWz7LUADb0VQr9rGS8a3PbZRmQc66JNvXBczK0DmcYqWDCN//o+/yrW99i2fPnkFdaOPR3MJbPW4WixhLs+8XJ/JSqpxf6DfqXW4Zm85F0WK1vGrBxcDpeM+rV6+4ubtlCLCPtjBdqQNtjkXTtJImF8S/1OSrFBPGsc9e29EIUjIlwVyp86a6pdXDw1p0Oc3M48SYErl1heZEnkyaziN0IaIlM59GUpqq1kVVPKNq3zQQTw2PytmIXHaus3EuZC0Nk9uMpW82Ce9D65nU7NIYoe1zLsHSGV6xdN/MN8Bo66orWFiUcZxI1WQoF2U+ZSa55c2YefrsDXfTbFOpMRK9x/se7zJOurrG1CwO61iAihBcRJ0NSRpStw74WSC2zpVlelWQeFNWP8Tj7KhzIpssWcS6QA30/LzHOxEsclHuT8flZoL15twaI29/1xSzHgYSaIGj4Q1GJFpSsoqOLy1Sus1FsNfOFRjbljYhBMTpMoFq+gaO+TRyOBz43ne/y2/91m/x/e9+r1JsrcMzTWbs07QqRcScuerfw7qQg+8WV/Pt53USSDozpwIYLT36wHGcefPmDTc3N1z1gd4NC8NS/Npaa7tPM+K1kkpaIrxmHaWA2O6f5pk0J4pLK7CrBS+Cr63QXD08749Hjscj97d3HO/uGU8nPKZv+v6jx8vUrZMmVlSvoQSCU+bcUvFqkFzKMplaanKxDRbkVapgOxT3kEtwflOtm1BZbqoKhLfMq9TWI+vwoYuB3W7H1eUj5uI5JuFU4P5w5EcfPeXuNEP0XOxvbQMIgcv9jg9+8bH5nOaJnOeqmFUQ5xFnJZCqw2HljdZO0zbT3QL1D4mGZ5+zbGZJzghnjV7wM6hBeEeCRcmZ29e3y8W3XeJc0m0rJlNcpV07E0B5C4jcoMTbDskabUfWkXK3eVxvgQGQsHqhsih3FYZh4NH1YzRlbm9v+eY/+Qbf+PrX+d1v/C4ff/yxKTwUIYTeZjPmgsSOXKrPRRzY7/fEbiD0PXMqnE4jPkZ8MNJT1sScJ46jSb+HXc+YR+Y5cRozzkGvhRIdn75+wx9/9DF9DOyGgYt+R3KZPM4473Ex4MTjiloZYG0FnDNx47zZne+dQJ7Jb07IaxYrgLmqbmsVMd5S5wE+/vBDnj/7lKdPn/Lm5SvSNLPf77m+vuYrv/LL7HY7Qt+xu9hzdX1N2F8gfQ9Rccnjk1kfGNeiTq1qw+8rL0FzbT8K3miKWB5fs8QCmpr2aaVsV7q14ohJUDUlLe9torSl8Q5BcmLoe8tw+4AymQv8zDIolvBk3zOnQCHA/Jg3zz9lToUPj5/gXOCDJ48J7p5//uFrHj9+zJP332O/3+G9IE4ZpxtOhztKmUn5BDITu0DXBUKAeXpla64GhyYU3HV9/TyhMpebJQKoK2gdV/U0Lc96L4QGaP+cZBalFO7v7wGL8NvAsKhNVaLVeWny2S5fnxUstriDO5PZ85vHrCI2ne9sYGqjd1jmbPJyJfH8xad8/7v/jN/5xjf45te/wfe//wM0G4IdWinUxrKFZcQ4xki/M9tAQZZZDEftEGgd/ErZeCf1HEhtw0nNBpbZBC+8vrvn9v6OOT1h7sKiYJWFOsnq0DlVZqUZHlfltsoIryPMFVSeRrPc88gyp9LFyDSOK4O1YhKqylQd0JxWerOYT2uM0ZTQUS5jtQ3oTQi43w2GLUkG5xaF7ZQqyxGr8rdYU1sfpgtxfmyzwDPS0wbcXjcjw110WQOGDSwiRqWQp7rTy8A0JsZTIaWAjwPTODONyi984cuou+DNzT3j6SkoaAkkFfQ08cknz3j16hVXV1c8fvKI6+sLLi/eo+975nQkpYFcRnKZGE+JUhwumM9r2+BCJVhMY2YYBrOBkDXjNvU1UFomXDtFZ2P4wFtn7M9+/NhgISL/I/DvA89U9d+ov/urwH8OfFof9t+q6t+t//bfAH8Jw43+S1X933/cazRdifr3bwWLBipuOxMPg8VDbGPz/t/6tzb23lK0bebRLsI4Hivtt/X/W2pcePHpc37/2/8vX//61/n2//0tnn3y1LQSXMc4jkjvkRCsz18l9J2z9m7sO3Y7M/bJueBIFvNrp2DZLbMtAOeM7STBIz6ul9wJRHN0vznc8+b+jsM8E3IgOGctQYFZzWxI6w4951Jdy22OIqm5ZZViGAMKmjLT8UTJmTGEZQq2D3GZmdnefKfTCecc+6tL+ko/73srteLQ0w09u/2ey8tL9vs9/c58STIZCZ5QMaSUEkwTpArUasONavYo52XGZ64l1u7C+T/YGShVnrFdf3VNBd4x15KxzQZ5L/huQEtink1e4JQzn754w/PXJ66vnhD6a0L3gpSF4/2B05jZ73rGwx3zPHMnwvHuyHg8cn9zwZMvPGIYOkLY08UBJZHSRMoTqoYLiVY+i/PLZzaBI7O+YClHamnmFPBWRm6Yrm3o0QLm5xfA+Ukyi78N/E3gNx/8/n9Q1b+x/YWI/GvAfwj868AvAX9fRH5VP8vGfHMo52zIJcKfP/dnZA/lrazhxwULOzZiqnLuhu4qGaeUYkrYw0DO1sEw303hD/7gn/KPf/sf8bV/8DU++eQTxnE0iXeBHCylVHGUWRf7P9shbZLRdxEJnpK3O2btxRelVKe1BsK2z2FBs1LOS8bVttlxPHF7PHF3OtLvbMQ5Bk8pZozssMWWxQa2dBEUtlTf9nJTbbJFarfbOI6MozEX+75niN1Cb29H06i8uLrk+vr6LMCHECioObA/umZ3fUm33+FCQL1Ds+LbyH8uJjajxpnIqphIcb0Zzngvbbwb6+bUm0Rlrdntnxp2JRUjaPyFVM+xUdu1fo5pziaCXGSh5Xfe0/c7RN5wOBx5dvOSw8Fk9YaLX2C4jIxT4uLigtvbW549fYoKTKep4k2O4/2J169vEFG++ue+wuMn11xe7tlf7Qgx0ncDPYVxOjDlwpys3ISJEDy7YeDqame6oyrLNK1sAkP7rA+B0IZT/SyOHxssVPUfishXf8Ln+zXg76jqCPwzEfku8G8B3/jT/kg4BzC3OMV5RrCmlO13BnKuaWYLBMtzPwBAzzOSJqu+MjZVlRir81VpCLN1PPqLHdPxxNd/+x/xu7/zTX7w/e/hXbAWdlGoTuAFZZomZjWfz+KFnMB5hw9h7VDUG6NNzYrpwtEIZ9YGDaCCcwEXEhRPzokyZ1xOBJRTMqn62+OBftfhhj1dH8hp5mSilkSpE5mlMGdBqpp1aedOIKpJzoWaTYzjyOl0suA0z4xV03OZ+q1rMHZmKdD1cXEya/oi3X5H7DuGiz3Dxc7eX6hsXYQYrDwpTsxNzTucepwmSpJqEuVYJuGAzWx6u8hn17ud23bog9ahtYxzndfIiBgAO84nK6OKX9q/pSSGfSR2gfvDDT/60cc8/tKv8EH/Ht/53j8HHzmMiS9/+ct85atf5he/9D6qyvf+yLpMKU8cDgfmcaaUzM3N3ZJlFhxdHxaVdTQjfm8ALslsAIpQSofQkdSo9lqlB13t2NlnsqDYPn8peZmQtuv7L5fB+ZdF5D8GvgX8V6r6Cvgy8Dubx/yw/u6tQ0R+Hfh1gPfff9/6yDX1OvecrIHDnSO60lh6bwWSqq+4IeA8zCzaGLxUBFqdVK9Jy1ZUM8ELWWfyPNP1gT5G5unE97/3A373m9/kox/+McF5druBUky+rAmqjvNkdoQCOHPZziT6YO7feFOAbhfQhUAfdlCaJWKgyac5Z45eitX41jGayZpqfepRZqacuDvcs+sjOx/R6p6uKTEjOB/AxLQtVVdH0mJlR+04NKf3vu+shq//Nc/OMrdR/ap6XYebOr8jDD1xGOgHw2Na0NhdX5pPagzEoa/Ct7arhyLgPeocuWTjTVSGZCpVeq5UOv+mE9Dy1E34eCujbCz+NiPkkYXZuT4oL7MlOWfmcUIvl2ckz4mkJ4bugtgps5748KPv8eiXvsAHX/yA/qOPuDve4WPgNL1hnG4Z8xHRwpMnTzZt90qc0sI8j3jXMc+Fw+2RaTK7SCEydI/owo5GJlMyTk2r/P5uJERTRw91/RYxUWBVCw7beyFjxly5VLboZ92Ef8bjpw0Wfwv4a9i1+mvAfw/8Z3w2ivKZ71NVfwP4DYCv/rk/r86FenN4TEo/nGUXbrMbQ6thz3vK5ynYecnRDstGNu02J5W2bLtq512lGztyTohmhu6Ky8tLvvtHf8i3/q9v8kd/8IdMp5E+xP+fu3eJtS3L0rO+Medaa7/OPufcc1/xyMzIdGZUGhlsAyWMhZBLsszDHYsGDRoIEJJpGAkkGlh0aFlyq5DoIBm5ARJgGRkJywKkAgrhonDaVa6HKyMyKyPjkXEj4r7Paz/WWvNFY8y51trn3sjIjEiZK6/Q0T2xX2fvveYac4x//OP/lZjkPC5qgKHYBFRCQOi8w9QVPkWWtaFqVN8yxaRYhDVUlWU2X0CI9H0eYKuqgQpuTZO9T7JylqkJJg8cwQDOtW3Hvu8GC0VNQ4tqtabqkmdw0iSDkZzCJ9Hsp65rTFPjSbgQiEbo+56QdDfTKcz8+MoqdjKrqRYzmuViCBi2W+625wAAIABJREFUqlgcrVREhqTZg1UMJoRAM2uG86EEKuUjGFuRXJv1KEaAuSynm8zlaXmasmL3zVU3ZK4Uwd4JcSnzGIo0YllLMSZ1VDeBqk4Y63n85BMuLp9w9sYbLNcVu36HMcLDxx9z/vw5IsJ8Pufrd785ZGgleGKgbVt27VYzT9/hXaI3DhHDbKZ2kaXEjtEToie4PV1bRKMVvhWrA5b6OKf2EGUwTcJgRBVCVt/8BfC9v1SwSCk9Kr+LyH8N/J38vw+Ar08e+jXg0y96vRACl1dXg8doSWOnnZAiIjLlBEwZm8aYkQ03ASq5QdmWGwsFRuRZf68yYUjFd5t6wdOHT/k/f+1/53vf+x7v/+g99vs9RCFGbd1WdZ1NjDMV2dTKzE4Jj04tphC5c/dsUATbbfaq/hUcR0dr7r/5BjHCdrtlt93jvVcB2iTMGuVPWITkkwaotiNF0QUewLWO6AP7zZ7LdMWimrOoK2Z1g00QXcC7XgfKCqgXxqE5ay00Fts0qrwlwtG8oV6v6Lxjs9ngu34EBsPInGwqS7NYMj8+5uj4mOVyqeWWCDS16nAWPCZkIpIo8YucKWFgtlrqBeI9tJkenWOEDJljopy+ct5KRjTdUEq5NHiIlNuFSYkRSRLV/MhaVqvVIa9BKoiwWKx47f4bfO18y9HRmt/8zd/kd979Q1Z3v8GjZ+d0fcytSosgHK2OefTooZZqRjtDttbvo65VOKeua1YrDaRlfS/mR1T1AtBuTRRPwJFmK1bzExBtm1dG5QhiVNW4rtvSuQ1VZWiaGmsbkumVlyNK1X+hdPsSx5cKFiLyekrps/y//wbwB/n3vw389yLyqyjA+Tbw97/o9bR1utPJzpioa0XArY3DbTEmrD0Ea0IBOFE+giqiFzGbyW6TwkGwqLJojtbrSgaS7GvhnBtS8RQ9rnN89tlnfO/v/QN+8M4P2G63GFPR+x7vtJ2FCL3PZDJjs/YiygSNOhItAst6xrKeqWxfUr0JK4mqUj0LFyJV76gaBSFdUL/wRnQH9kmBzYGmHXTnqGBgk8Y8udr3vVoTKqCjzE+MAqYxl2ISD3bgZARpKsr0ApWlNnNsbPAh0BkzqH+blMlkhYJpRwAxxKgBIatWk8YLVSZs2i5qgUZ+/0UDNSavTNQMeCptQAb7SNAgJ0Z0EjYdBgsNAmUcXb8jl9uNhQ0ZY8TnYC9VxsbyyL5KImTWa6hI3jJrjrh7dp/7d9/g02c/Yv/skrM3lywXgYuLx1xdbfAu4n1gtw2cLOY0uRNk8iYXgiNiafuOqqrYtvux05Szj5iUzFY3DdV8rqzW4HB+R1UbYvSk0ON7R4iRECpqq8Cxfq6cjUSBVGUFMobv+ascP0vr9H8AfgW4IyIPgP8c+BUR+ZO6ovgQ+A8AUkrfF5G/CbyDipr/pS/qhAA473j45DHWWm2tlbZbXauP5wTDmIKgmj3EgSg0BBJRYPHF7okexd9UuzBpkoUYkinmN0LbOj784AN+/3d+jx/94A+5uszEsaDgHNYgTYWL0GfT3DrlE5q0RDAp0ZShnuBx+x2bzYbddkvbezVZFqM7hNOuS0S7KK7zSIqc1DXeJOhM7oSkASRVZasyIKYXbO8d+75j3szwxugOLspGjF53J53AtOUkg4jOfYqluHwpVdiQkme2WGbbRkNttT07zGVE1bacNXPVAq30RzJzM0Qdjqqtpc6vEWMkGkX3rS2AbpbSh0y6U8Hg4cxZHecOL7TQJzNCjKPqI+gNyY48HWAyM5JtDkRraAWdx0wkOEMMqtrd1Cvu3X2dxQef8enTK2azFffOjtjvod0niB7fdbT7yNXzTwDw2fMmCcxmtQ4IrlaaPc9nzOdz5nNtJe92Lcc5M6uspZ7PqSpDCDV06hdjkiVRQcpSCabJzm5Z/S10OBcJ0RKDxcgMHzr+sZCyUkr/1ktu/us/5fF/BfgrP8+bCD7w7Nmzod6bfoHz+XwoS5rMICwlSdXUQyCx9rD9GeLYHkVKey1nGhkXMLWWHDElUiYaWWuRqubi4orr80t++M67/MEfvMOzJ89p+w5jDH2IxCSYusHYmi45dM8QanK3ppCtRFhUtY7g9542XLG9vKQPmmraZoYET7vb0fYenwOZtRWqCh2htlhTU88adTXve5xTfY2YU13JFPYYVQLOx4BDJ05141c8KKQEhsEXBMhyeVbduowMLEAR0cE37wkpKUhpK+18VBXFlNhk6bbZTBf/YqaYhalspjwrFlB2UdCyZNs6CuktBDd4XNjK6HuUkVRkRLRGt0o717U2VXI3efYl5Ta0Dn+VgKHO9nEIKIX+HQVVxs6Bz3mPmepXeH1uVdcs5ivu3XuN9dEx8fEFBFivT7h3J7K57tnbDkuHutvqOL+xFSYmigXAtt2z7zustcP3VVXKyGyaZ8wqq/Ty9QknJyes12uWyyXr9YrVej3I+KlwdU8QzY4CHaaKVHZBZff0rqOLe9ruGibC1l/leCUYnCFGNpsNAPv9fggSBb8oadpisTgIFs18NgSS+Xw29PbB4txYXxcsoxxlarH04IuKdwrqSF4vat7/+FM++uBD3nnnBzz4ySc4F+h7r68vlpgcZNJTTHmnLws7k2UQLY/EaTnhN1tiZYltz6yuSKZCQsRny4Gqqqlncy1lxLLrLT44XMqOVtYoA9LPlfyVORHleyodABdVZdvHgBdtm5LBvxgzCJgvRBFRko/RoTURO0xvRgEJIyg6b2bM6oZ5rWbOAMSId3uqqmI+n7NaHXF0dDRcBM8vLwYAuRFLrdMQkGDe1EM5MFDrRWUAB2lDlCwmg/yfHlNsYQgAcYJVTAbHihRizJdxeV7Izxn0WFOi9hFrfW6BmwGfma1rjtcrbt86G9jEm+019XzF8fER6/UKEcusmgEGF2aZ/VqsG3pCxhgGMd2UsrWFG2aOKnQ2pap0JuXk5BZ3797lW9/+I1jbTtztG6qmRoKS5OazOW27o+t2xFhRmQozr7m6umI2myP/P7dOf2FHjJF9pwxO6y0ueFzw1H2t7lCup+07Nrvt0Eq0VslOJeOYz+fUTZWNfnV4rGQdTTM6gmsbrVCLPWDyjqaKV/P5HO8i7777Lr//u7/HTz74kPPzS/reD9yB2hr6LmDE0odIQsBWg7VfaenaTBFK7R5iQ7vZalsyBGxV44Ojzwt1vjrm5PSI5foYYysigvUz7UK0e3zssw5kmXvQGrBulD6u495p8ALZdS3NXqdX62Y+yOAhQhSD2GwXAEMnxObywOZAMgXolrM5x+u16nNUNbWtkNxyDH0zZg62UQmAoBOk83qut03OWznn19m3BZ9bxlbw2Tmt73vVDxXVDBlk9NJU6Us3g4i6ycGIRxysL4qN4liWhkmp4r3DGJUt8N5r+YShiZGqhhh7RKCuLUfrBatFA+L58Y9/xN3tntt3X4cUCK7H+YB3gXt3XyMRsinWnqKFcXJyQt+PG5kxZvCmMaKKZ973tPstFxcXPHr0iAcPHvDJJ59y6+yM9XrNnTt3uHXrFoujlcoTSuLi6hl9l9hu1JhrsayZzY44Xt/m6uriJT2kn/94JYKFGF1opYtR5yCgF73W4V3XDeBjuV9yllHXGlSq2g7Pq2s73LdaLSaS7MKsmPN4nQBVQHPOcq62A59++hnvvvND3n//fVzb6RxHbnVq/T06uIdS4xq94nSn0zFvcuC4tT7G1srVmM+1s2GqCr/3dN2efdezPNkjt0SHruoGFyJilRi1CQ7ndff0KdI7p+rZUcuJcgGqHKHBNjX7tqOqdjR1zbyZqR8okunQuR4fWJHKiExpnPqllG1Gv2+TdKx+bmsqY9WIOKVBHUuNmfa0bYtcXg6Bq0xLFsR/OubfNfuhdeqCTrAWtbDKqJm1FUMyiUDMHahRcmDojjFmGFPiHjDMf5RW6ACECpPbI8hIyvPekzKLs++1hTv3e2xluXfvDt/+zrf4yZMn+PmcxaLh3r07uF4Fmy4vrtm3O1xYDRlrCCm3ywPb7XbIkEvwHDY/W7Osi2p8ou89fabXP/zsMReX11nvZKalyekJt2/f5q233mJ5dMx8ecTJyS22uyv6Xq0+T0/POD4+fqED+GWOVyNYINmNqxrS13EMXXdDY4QmK2L7oE5lgw6CNZi60gnKXJc2TUPdVMzrhnk28Jk3Cpo28wV1XbOcLzg9XnA0mxO85/lnj/jhD3/I9773Pf7Bb/99RGRI9+t5TXBRux6SWM2WugsH5S80VYOEiDiHiYHsb40BFs2MVbOgjoJc9RjXIpKonGPmPG3nuLx8F//gEbs7d7lz7z4nt844WmtgCbfOcCdrNrtrPg0tu4s959cPmdUJWcxx4tn6PWIXWGrqGLjcXCtYmr+/4/VK26a1qBhuIS2J2kdGk9iHnoaKKtY0tmHWNDRSawfBB64+ecp5UBWpvu8JuZsQc3bW9z2u1U5MmSFZzOdjOTj5V0SoFw11Y8GUqQ29ONt+z62zU46WK2azOVFyySXafpzVs2GEfVqOFIc4k8r4hKhPqAg++ZznqXxflfkWXqCPEVMlTF3joqMKQmMrUtCW8cpY9pstq5MzvvPNt/hzf+bP8NY3vs3jbWC5PmW2POGf+ua3afvAft+x27Zsd9dAxKdI5x1t33G13fCTDz5ke70hRgj9FaD2iMujEwXta6Gx9cEGEGPENjXXV1vl0/SRXX/Np4+fsd9/H+8jx6eWb3/723z3u29z//5dVYo38PDhA7p+/3IG1M95vBrBQuSF7kdZVKVzMaDdubYNRWcSDRaJTKzJZsnK9Tc429FlXUiXgTeyOnhvep48fEQMgYuLC5481JTvxz96jzZjJ1NbgBjBx0Bdj90ZH50OKYU46iSmNLQIU2YC2gS1GGJy1Fl524jFmoS1iV0f8OeXXLtI4xJm2zE7PdJMqbE0jeHYVHSLJe5ojT89pd9dY4PaMSbJ5LIcQItf6263Yz9fsJg3qvIt2m5UsoLqOxbG37SDUARhXFT+Rr/bc3l+he/ag2AAZa4lX6g3OlZ932c/i8nFnc9bL30elIMkIWuoRpJN1FWVRXgg5t9TFXW8/MYxtiXLfMSLHbCyzqa3Tz9vmmRBhcgXY2Q+r1THw6AiRlS07Z7z82e884cfY5o5yTSsj2+xWKwxolyh9TKzdY0ofiSJ12Lk5GhNt2/Zb/acn5+z2ewGvkxECBGqKo7BIo/dn6zmnJxosCzKZ97rEN/z58/Z77b8+L0PePDgAcvlnPv37/PWW1/n3v3bzOfL4fx8leOVCRbj3H5zkKqWVHP62IF0VfruRb8gA4pFRdkkyeQmwQQ1FE6pZ79/qpmHrXj+5Cm77YaLiwsunj3XL36/J0Vhv+vyMJDkbso4JJXzdv37STkCLiaaTDswxmCzOM+80izmaN7gXYejJaVAHwO1VMybmnWTcxGfiJfX7DpHavc4a4k2sVjNmR8tuNMsmd++z3Hd8NFPfox3PTZFqiRUCDEEgsnt4ISK82y3rOYzFlWDbezAOykgbyAhQcV6iwCMwxFcJHaqcrW93nF9fqHZii/go75O27nhtQbz6FJq7FuC04BTyuYy2u6MJ6CtXExCKsN8OWO+nBF6h+8cvek1EGeOhCSDM27wJAEGoWYYSVtTpq8aEk9Kk8m/40agLeADWnm+vWRoTdOwmC9Z5PP43o9/gPOGer7i9PSMZr7CmprZbMF6vc5eK5aQeSjL5ZLvvv1LROe5utpweX7F+fk5j5884/z8EjtvdA1bLbGDUxtIEcuu7Tg5OQEUV/HeU9dpwNH2rWW323F9raXK9fWWq6sr/oXFL2sZfWNc4sscr0SwiFHnD4AB2Z8GjOkxJd9I3gW0hZgVu2moZJxhAAbcowxFNVXD5fkFu92Oj957n6urK9rdjv1+p/MBSS8255wCSFmzMUjKLUertfMEaEtR27MhJHUjM0rKIiZu3VJE+3S1YHd9xVV6DiHSgErQYdRIt6ogaemV9h0kNeLd+5ZuMePoZI1dNTQCx1XNejanS9oYq61VnCREfAqs5gtSHgDbbrcs5zMth5Yn9H2+2KUI9arbuZGYpbOTKjcF6PY93W7P9mrLbrMZAkVpDYvk5D4oE7IMnaVM2jp/9pzYuczctNp6tRWVtezjTlu1tcHORE2Im4bVcslyvsCKyQN6jKK20ROdIYWJzGHudpXzXNi9em5Gc2QjhpgCxeVs6JpMsqpyPsv6MQbE6N/t2h2LZsbx0ZLjowX76wuenm+ZLY44f/4UUoWIZlOz+RE2a5c0+ef09IzVH19w/95rnB7for/nOT8/Z754gMgnXO/3GW22Q/ensoJkbdJPPvlkKNGnrdf5fI4PC9q2zVPCW86fn/Pws8cYU/H222+zWMy+8nX6SgSLkMuAea5vC4A5UrAnO/rkkGQAm0WgFXQs5UhMfhBiqY2ldx1tBuC2F9ecn59zeXnJxfPzYfFr0NJg0TSqoVjX9SCNV3gYhc+QlOuUAbMaSXpRKHvQALpzXmyumR+tMBK5vrrk8uqCCqWUz+qaFCOVQJP1NmNuAfbtXkHSvqNrd/jtBuaWVFt6PKt6xkwsRE9jlChVmRof1R1NxOB8xPeOft/TzvfI2elQppXMQHLJIElVyxRIhegi/W5Pu9MF6LqeFILK4rvRqa0PfdZNYNCvjDEqSNh5fO+RELECddWwnM2Z1w1nJ7d1SG85Y7ZoaFYNq/WS5XKOy3jIgbZJyVZCoIzwF2xCM4hRClE3itEHRTmpKfMwRjDXx6BArzUT1/MxkLS7Hav1GpIKFxsJ/JFvfYMuRP7XX/+/2fcf4kNHt3WAUFcz2u0ea2p839H1e5p2BleG50+f0e72HB8dc+fOPW6f3aWuGr7+5je4des2P/zRezx6/hw3EW82JnNNjGV9cjqI4QxZYVD9zn3rqOuG1a016fQ2p6dnbLdbnj+75LcufmdQz/8qxysTLC4vL9nt1LavBIuyUEp5UjomwzQq40JSPYkisaZzD3WlKHy/b7m8uOL5s2dcX1/TbVo2mw377Y79vlPPjZSGTEIHigxWLJWp8Nnj1CSlHKeDnUyybrMQrVXj4iFoaZvyKnRw8Yzr3SWha2n7lrmtmVlDcJ1iA5lqXlWVkqJSIuaLsCLhY6BrHbEXYg1dClTLmeIkZvweAPUG8QlSxIrOlATn6XZ7dtc7bJUGBmbKhCGZnIvgO6KLuNaz327p9j3tbk9oPSkEXOuG7lTKGUqIE7XtiafLoppTmZqmshzNFpysjjg+WrOaL1jcXQ2Bop7XNPMaO7fY2tCHfsgMCw5USgbnireoReX8cwvV5YwiaClVnptSUnk5dEaicCs0WDiisZhoVdtiCBSqXJWStndduycZw2634ejkjLe/803+9L/4yzRNwwcffszlxTXeR2IKzCx0u2uSCMZZgmsJuXx+EAJHiyN21xva7Y6TW3c5vXWb49MTLq83JNvw/PwpXdcNvKGu6zCmYrGYKYbmfF4fqNq6gabRjbYMIs5nR8xnSzXoJgxmXV/lkF9ES+WrHrPlKn3jl/4YIjKUICXFnGIYJYiUUmVWNyNzcLnIz8+DO1bbeZvNhnf+4Pucn5+z3eq0X+rC8DdqM6akA/diaCHq8NN0pwEG5StIgxp1CG6koKc0LNaUVPtSUtAuSb74bUrYCA1gEzSokHAZpQaDnRBpkgjRKuMwWiEawef7G6vfxTwL1DRGjYIEsChYOK8rmrri9PiEb7z1hmpruo7eOxWUTaO72uXlJZvLDd2+pd3u2G9bXNczs40aGftAcKPTfEoRY7JFn81s2/mSWVVzuj7mZHXE7eNTTo/WzJsZy0bPYVcFbG2QSkuJZBXcTCbh44uKXOUC3/YOn8aWrC1M3Fx+FqAZJhOp1Zg5qBSAG5TWpa6omhl1HjOwtspmSTXH6zXG6qDcbHXE/PiY1ckJy9NTrtvAP/yd3+fv/j//L7/3u3/Ae++9z8WzC816qhU+BoytVQogWzw0sxUkm39fsjw65v5rX+Pe62/w2ptvsukDn3zyCe+//z6b3TZnD/pem6bR5nfSmaNCvRejOqEHUgyipXQpU9brNX/nb/zqb6eUfvnLXqevRGaRR7l0vDZEQii2bdnHkRGrmPbr65y213XNfLnITM45/czRNBW73Y7Hjx/z4MEDfJ+HhpQxNYJXJVuYXuCUHUndqwu4aYrMepq+cx1qSsYSLYhVND5gh9cMQEpGU/GUsEkDhCSoRX+vY8KKuotL0r8mRSUry92BYgtkjKEI13R4OhcIIeGayNGsRupGX2sIhhCCoufeR+oaqkq7Pc4nOtdjrWBms3yBKRYklWW20E5KLXoRWanygFNgcO7O58RWTSbJLWmahrP1CavlkuPFimWjZC4ryp9Q0+CIJGWiFtlC9SwNuEmwkEnA1nmTSZcKvTBM8btl7HqUzVDT9QJkppGvYSRbIIxzI9PDkO+PunlYkg7JecdqseS7v/Rtamu4fXLMej7nBz/4Ac8ePaVPHaFvoZ7R1DNEArFviWKAip4M1tqGi/Nn+BQ5vX2b1eqY01vHHJ8c8ez5k8kQWoBskCwZyAcUIA6JIvFQPkdKCoReXV0NG+1XPV6RYDH20AekOhYEuyDcKrTq+4AxbljQJUMoLM6Ra2/YbDY8evSI50/PB+KWMRabLzL14QgH7ySbEh6k5slo6mqTHSd9o2pAxBxotDuSL2bRi1uBVyEYQxbVVFcwDMSINToLKECTHbtMSjkwhOHvm8zYlJgDRCZjJaOAJjHpvArCLCZIgZigyQHVGEOVBJuEtu8HSn3TVJjqSHGGVvC+p8+mzLOlEodCU+tYvA+YKMzqhkWzUM5GnsOQmDLwVmGqMkWpOqOnR2tmlVohSlL39Bg8Pjpc6klRqMRCrd+Dz8rm6u36IhgZJvMeJVgUe3apmnwaxzKo/BtiIOU2OBNilxH70iBx0FbNI+2D+VBwhL5HxPDNr73O119/jXtnZ8yNYV4JP25+zLsfPIAEFkdtKnzwxNjRh0RdLQgBAhWubrm6eM521/LNb32b5fEJd89uc33nkg8++IC+26tfKnkWhkm2lMFXK5Y0BMjxfp8V6KcNhK9yvBLBAg41JaalUZ2l3KZ8i+Ekej/qNmZzm931hhDUN7RtW7bbLfNcrkjUOl5H0vViZjK+W9qICNjitB5Htiam+FgWYZmircHgcl20qF44xGYLuUgUFWUN+e8bIn3mNUgGCQdjGTRITNdzyruhjpIayLMje+dxIRFcR+8Cs6ZiWc/AzKiqRGUsQYTLzZZkhPV6zWxWM5svMbam7Xa0uy1iDEfrNRwdEZ3XMirbGsxMpRTuKuuNYKmklI4ZPxr8T2pW85mWd67DuT6XeJnZWAWMtQRTEb2Sv1xSIaEw+HxMORH67Stelfkgk9R7IGilUfBoyCxysAghkIIfGJ/VRHKvBCCRMHR2ovOkyiLe411H3+2pu4YkcHy0hOiQELl3dsK//Kf/FG+9+Sa/9fd/i48/+x9pW4+1CWJLdEkpeslh6gZJHok9Ej0pWFzfst1cMb864uzsjLu3z7h3+4zHz56SUsTWVcaDVBXLACEK0ejgYzIK3pZrKREz12aPcx2bzdWXuzAnx6sTLNLQAWNKN5NYtB5l+K88LN7oibu8a+52OgbuvdZx6+PjgUgE0Jh6sPYDMgEaUiq7jVCEX5NYjBhtg+YJv5SZgKX+VUHcLFcXVL4fwvDeE6MTeNH9zAUMUZVgSEmBQl0NY1ZlksaZ6SycAF5FIvR+UXNfHzziPb0kWh9oOks38/Qp6zGSWNcLLrdbXIr4CEfrpQ5GiWZnbbvTGr1uMNkyQJ3PI3HvBu9NsajYSj1jbua5fayhUjC5tHP0XcxchY7OtXlqUjEeasFUFZVU9KkDC0GUqDKa2+fAmacbyjRs6YwZYzBWRu4LY8tcnz6WISmoF2kKcQg0BwNnyRNjMbVikD6wQLDaEjVdR9XtwRja3Zb5XF3sFvOG1+7f5db6mPVsxj965/u8/9GHXF5v6JwHDyKBuk4QesWgvCdFT1MtMXXF+fkzsIbjowVHyxlvfeNNtrsrNrtWW9ZMlMtvBsNh8C5OMouelIq+SfvyC+/nOF6ZYKGp3kvA1pLmAznHGu6qcj0XdRaZrldx1O12Ow7nGKPamAFiZsOFlL0qpIwrl/66GcChkMYx85TDQxF+NaKj0SYvXJOfbyQ7lkcIGXOIMY0OaJKGLKAM9hhEbwctXVKZ3QCw2taLYQgWkkuclIOElcwGTWoonFIk5MBZeRmG8pz3LOqsMUHIE6wtpq+ZZ9f0FBJNMydGfY5NCjhXTU3yAaqgfIrQEz2klEV/VX4HiQkXE8QeySZOrtJswEdH71r60OOjy9+rUKVKu0xeSDZT941odjWwLYUU86xNBmJtYYpaRo9TUxy80nDhlHPrnMuZhR+Zv3KYVZR/Y1TMTLtFkZQnT1M2TA7OE2aO4Hu211m7JMJ6seDseE0t8Of/tT/H3/2N3+BHP36fq92Oi6sdu30iuhafAmK0/dvM51jUkPrq4oIkcHJ8xGwx5/7d23zyyTH7/Z6L68vBxc5a7dIZY0d8Bs1uU8xt6xSIUekD2g35J4TBWY5pnQiT2uwGTbf8bsyoXtzvWx1k2u0IvaM2FlNpV8Rlc5yBQp7ScIGnyQIcX9uguoaRNBHVKcGBnHnYCQipiz8j1ehEZ0hCTLrrpyRqsVmmP7EDek92805MTHIykKnvaTRyLv+KGL04RAfEEmiWExMp9YSoZRLO49OOznfMrCUQuHvrFFNZWtczC54qNYrRpKRlnaYpxGJUE4MaIGXv1xAcvY/Dbqagblayiow7d4JkybMfgc539L7Ti0UECRYbeiQIxlukEkxltNtUV0MmaZIoSzZNSg+j0gPKcXmR2l3S8GF9OAfF7PigW5IOum83aeJTgpZMspDkAxfPnrNYLFicU2BOAAAgAElEQVQujwBht9sgUbAG/uQ/80+z3285PT3ls6dP+cnHD3j89IKrq17LV0mIVMTMxkQ6Uruj2lU8ffyEu/fvcXp6ylvf/DpVY0mfJqYJk5bmnSqVhYiZ1cP7LXYRMUaMBRPNC5O4X+Z4JYKFRsUi2SyZbKUpbZ2FSIw9TLtEEpIVoH3vePzwyQDiaIqqE4opRN0d884DaFqev7wQ+uE5xtjMIk7EZHQXTaMfCeIzHdeqbiMCExczZRWnQd7OR4gSMaE4uVdZQbwkSeOodBGymUrzJ6MLXbKjfLlgACQKxmbB25RRlypjK9lEWUh0STU3uuCwzvF0t6fzgaPdjqPNnuOrDbdOTrl16xah1lFwa2c0tdD1LSE4rKhbWtVUYAIp6uBY4VtsZaddg5R5J147M4UYFdFdrg89PnmqzH+xS4sNFhNyuzXLBxYnOFOZsRwkqBu4kUGxK0kcdlFBkFCCWaDNZadOfUZS8MN51A5aha0bTDWjMjWShCrkVnpMpFTwMEdIAZN0vKDvBLtVnfDFakm3uWJ/qbv+rGnU82O7w8TAP/8n/jh/9Je+w+OnT/nwJx/x4Ucf89u/93021z2bnUNMR3RbQjunMceIS7SupfU7vDjqZcOf/Vf/FXa7HZ89fsLjx0+5vrzi+fPnbDdX7K43Ol/SXiFd8ZUZcYvgvZbmeZ7nqx6vRLAoR6nrKTt9BmpMBtDKLqGpmI6B970qBylbr2QIqoVYFoYaCclQwQQX8sV/OFNQQK8pWHZ4KLeiHIGETfoe67rWnV0YtCJt3oVCDLrLJx0Lz39Q6ccxZofuLMaS3wuTUiVE5YOmm7tDUOOgAraKCNEaqgSQwVLJOAkJrFDbxPOrK86vLpk3FevVEXdv79k7z8m9WyysxWSj3pQSwRc9ywhiib2byBIqQap1e30/URWqkh8FZSCSssN9lJweo5OvszDDGJ3MvVkSTHd7UsaM0HmfMRuk9K4OOiTee92x+57OOUKI2dHrcHZllGY8XAM312Qpf4Ds4xGHtiQoK3UgBGY3sxQ9RI8VOFrOuXf3NjFGLi+3PH5yybPn12w7LYtc30LVYKSm8VZNpjMnyBjD6dkt1qe3eP31N9lvd1xeXvLk8UM+/fgBxhiePHqMsXKAwYAGjLZX8lzB677K8coEi9IJKUyzciJN/rHGDBL3Jgvb+N4NHY8i414WWbnwpyKuwxcZc4Zgys4Vh7YeQRFFyZiFIWm2Axl3zekwY2ZgogyScJUxVNYOLExDIvl40M0AlD4sqI4nWolIUpKXVt0ZnnkZjlNeIoVR6j8HC8lt3NxHUUBYkvJWELrgcM4TAjS9wydDvdrTdC1cbVjcua1/PYyZTIjKaA0EnHdIhMoYUmWzHWJhbqp6t5ZA48yFScVgqWinZixkINnV2KxDcuAgT9YA5bBkHCQSS0s5d44KQa7v++HHO0cMaSAp3ZyKnW4OJQhOO3MxRhUGhtytUuKe7R2p0ud772n3e3pjtHsUowZBiVQmsZjX3Dk9phLh4vklViwESBcbWlcsLAOClk2t62nbfujoVTGwb1VRq2pq7t27x3KhSlwnJydYMXz26CE+s16na7+uZlijnav99Ze+PIFXJFiIUQ9QgISHeOiiDgw6kE1V0WQpdddpqrnb7QZZsnLyp5OPJSMZAsakF60vPw6tDalzhKErk6cWx+OwexJFCD4iKUAWbTFkTxJroLYUeL8s7CFxGXQZhJDnFkonQPL9EjPw+ZJa2uSgU+pwEVEB2pSQAqZKytiGitTZpsGmQBRhEzzx4pJdTJy1O5WNqystY2ylKlYebIViGUmZkjEHTFOZIXMKBIIkoomDmheiWhWV0bkaW6tMYlUb5ovlKGRU2QPOQxETLpmDft8JMMNofOl6Duc2BELGAIrNYgiBFJkEqkNq/BTYnAYMJn/TDKS9LG7kA844ZrUqanunQan4j+j7jhgS1kRmFlJjCcuG0+WM/dGc9mhGcIFtD7GpMBVE6+m8o85U+pKlRBJXV1dYWxNCyKzNiuPjYxaLBc+ePeNqol8ykLiILBYL9nudVfmqxysRLIzR8V2AypbInFWywpgRKFNzNlDA68bmazNSzFdiru0B5VZN2qCifsGoxWiZO8iPLTZwgzxbfgGmgJc2BifvPD9WcZEQcqclBlV4SvpH02ScWtWj0sTGQfEKl4lC6hKmC67JGXLx8EwiBy1Uff/qUYqMzSKDPfS4TGqw60Xp8GZebAgDW+fYXm24bHt67/DGIrUG7iqqkXJE6FxQtmld6Th+p6PqIoJYvTjUVUG//wIgq/2g2hQ2TcO8rqgbnT6dLxaDspkCu+PY/HTnN8kM3ImSqUi84Xc6KQF87wiZH5KCKpcV5u9UgW26QdwMGuPvCt6mOFHVCgFxcoAD2MzvTSlptyR6DInKKng9q4RYV5wdrei2e/rTHqiwu54+WXpRsyBjKlXJ8m7IjmZZXPni4mLYGCWp+fTZ6S2+853vsO87nj17xn6/15K9L8/3Wdz3n5AypAQLEWE+K/XoYWYQXBY0rc3ASNvtdoMMW1lgN2cCXtZZMRIzhTox9cIrJCjIISFlw7v8fsbr1OQ4UgRuzDA8FZJo2mvj0M4rgO3wunFUpfZR9+DAKEFfroLIJHIlKPzP4Zh8timKP3aV8qcxiUE2zhi2XT+kqjGJDsYJVEudf1AthagDZ/WcGCH2e0yeL4mV7uApKOhYm1oVwlOWCxDQEeusWmYts0aVyqrKUFur9PFmMdHllEGHBNSpLYfBjHmIdiMQldibnNsYtWvlu57e5fIjZxc6KTwGi+mI90Gn4yWdkOl95IyiPCaIQDZd0lMqmLx56IBanydltfMRSMwsnKzmtOsVvvOkaIhScemitr3NyP3w3tN3KlUYIlxfX+N9GPAMSSouLUm5QHdu32NzvdOBttAPn13LIpgQV7708UoEi0TRbGLw+7C5C3LA2owq53Z9fc3l5SXnTx6y3W4Hl+/iP1H8Lcd0v6AAusCsLR+7/NXxKM8rfIshSyFiGIk/+mJmEF7RUie3P2PCoXwBk3PlUvpoUMutRhEIah4kQQlkA/YgArEf3hP57URGgtbNQPh5360oIJLLFUPXOSK62I7Wque4XK34xjffolmuaa+v2V5tWTWVyuvNBWeyi5nRS6JeLLBVjZCoA4OjezCTssEIVqCpauaNWgjUdgwW88VqyCpCgiqNG8XEYJ4yjl6IcDEo2JuiBqcQdOcseg6FY1NKIRF5IViU8zy0GG9gGOX7LcEiFVUwQedJStepdLMmOIFS8kJ2UUuk4EnBIUQWTcPp0Yqu83TB0FLh9j3egU9qvRAj2bDI03UdIZK5Q5o5lffqnOPJs6ccH615/c03aPuOkFRDpN1f5WuhUmXxz4e+fubj1QgWKdK7FpIhVIlZVUPmInivxBJNqRTMfPzoEdfX1+yvr5RhZ29cmGkMApK7BWPg0ZOsC2IkYenzSnYhGVQzFL8HQPn3SV+jmBSXhSwiqrDtDSFzNErFnbJi9XSBYhguFJsyLyOqk5finmZkqBYSUf48Rdch+gzKZoUnk8ouR/E7yP6lZeEHNtsdx+tjXn/9de6//hr3798fzJ28GJ5cbHjw/gdcP33K6XLFrfURd2+fsFicQGjZ+45aLPV8gZkrp2AeY85eis3AJBsQqJCBzVobO1DFq2Y2jtUzBgWfXde0ozKuk3E+JBvq5H9dziY2u+2AT1lrqXNwaBotXUuQOAgQkw1pmplOuyshpaGzZQXEvYSPQWb+ZrA5JpUdUAexcf5ouZrjA7hk6dmyZ0srHbudI7qgbWGpaNuezWbHkyfPaJqGJ0+fImKVjenVnCl4T9u2fOtb3+Ltt9/m3r37pJSGcqXd7Xnvvfd4/uQp2+2WTy/e+UrX6SsRLErkJxmaykwAqJSxgIBzHdvNhuvr67yDaLvuJpB583XLUdpxkOv/kj285L2kF3bu8f6hlcbI7jy47+B1So2rNn+FQ1G0McgXlCmAaHlfQGZyHbxeeRshpSFgDMcEB4lmUt9POkLlYlitVurt0cw0FrpA6j3XIeB3O662LbvO4/urgfl3++yYk+UcU1mdZ4ghO6FVNAkFg0ymaZd/0WCmJZ1+ByFFPJqFSfCoAkjhsgCCCsekLl/UhxeuEqz6TEpyB8Fi7JaZQQui/JTzMz1HU0LezbUwBI2X3FeeO2Qdk9csal0xKhdIu2cKzuvIgNXv0FRgrbrbi9NyUGpSFKTSqVzNPOOgEA6aQXVtNwTTvu+5OL/i4cOHWfZvxWK+YrVcE7xntVrz6NPP6LqOT3/06y98jp/neDWCBagCkLyoiqX1W0/wnu12y3a7zcMxDolxCCxT+8IpPjE90UP9OaHImhsnm9JqTDIEAhnuz+O/xCELUegjaLYRlak41XFUywF/MIOQhGHoqry/qqq0iTu0BaEMpR3sYDewmJd+n5KGTk3OUw7q87quWc0XNLYiOq/ksbgn1jXn55dsdi29D+zaFhe8TsY2FcfrI2xlMcGR+h4M2KrBKpKsdGOTR8aJpGTyvEVUkJKEd+rw3dSC+NJ1Kt2NDDxaxXJ8VHLXNFgU2T69gFzGJkY3s9IJm4KZJVgcfkcTESVjXrjop+shL8zBfb2wOW9uTkVJrXBrzJCxTj4DCbE12F6Nl02l8gZRA8s00Nms/FWG+ZxzdH1H13XDew0+cX5+PhgtN43yM5ZZ+Pr27dt8/Y03iRH+t7/1X3zumvlZjlciWDAMWo0iJ4MYjXMK8uQoqnoMmn7KoC49GVeGg4v1ZsAopYN2Dl4k4JSyZZhTSaUU0Z0vovoLAxGIG7sMZSoyzxaECBmAGy/fkRA0tIdTop8sKrLFgEjOOTJu8dJvTzJBqbQSOVz4Y5DU31erNXdfe53bt2+zWCyGxz3b7Xnw4Ud02XSpC2D6QLq+xlSW22fHrGcNYmqkSpnoZAkDIS6XEuiMSoyR4DP/BG3n+qDlUDIWfMTa8dybLDQsWe26KIOX8qT8FJKRc10GE0sHzQwOdlO1NSbWltMgYa3Ffk4gKT+RNGwoZV2oA/1hoCgZzQi6OsV30tjN8zESkpovaSahmIJ6lCRSVMsJneLN7nBJ8ZnglC2rwHLM76sCwuBoVhTnnj5+pqZbdc39+7kxMLkmvuzxSgSLUoYMizovCO/90PFIKbHf73HtXkVuwyjKe7OkmM6BTAHScoy/y0sZe3q/DCXH+D4nO8XwhDC5TfUQSzqtt4dBQDblz5pk/FvTMmo4gpoJY8siPOzwUF5ecpbCYb09dFVyq3fY0bDYquHo9BZn9+5z5+7dIVi0bYuTWuXl+x58wCedXm2vekKM3Ll9TDpec7yYU4vRoJnUAEhQ20GkqGVrvV7IcpqtjbR2iQETE1Ems0AxmwkRaZ12NvyNrCzGSOhaur7Hhz7v7nr+ywVS1zW20Q4Nk++lfIclYNzUdf1pQHF+gOIycthBKefSx6iix/mzkLx+muSJSTVPQxh5P8ZUQK82CdnWdtjwcns4RtVM6bqO6L1uPEmJaS45QlCSou8DRCG4OJAUC9Y3my1e0K/9MscrESystZysj3Map8ST7VbFdXe7naaYPtDt9gPSrS3QokZV6vFpHWoUzGRy5d44Uhq7JC/eLhz6a5oJNyI/ruhgAJGQLxbJQFjS8iTpo0JSZXBK6y1FfAxUmWvpJ0NPOi8SqdKhOCtMSqyXvPNyn4mid2Yl8lQeb7RGPjk74+TsjNlyidQ1YOj3auRTQMUYEsGgRKdeJ0U/efiI5HrM2W2OmwpBTYN1Qk61IE1K2lIe9Cj0rwcJmsZnEpqLAZPP5c33H2McOhtDC3DCwPVdzi6zqK8xY7fD1NVgeD3dLKYX9rT8KN/vy24bMkd9c+NrJBkUyMYADRBIZa4phnxLyIxTPVs+OXzh/8iYSaeUICZ874esNOR2sHOObt+CkaEd2mXQ3Ic0BIXSVt3vFc9TPQsHbL44EP4MxysRLKqq4s6dO5S22fX1NVdXGzabDf1e5/CnAFZZYAftqgk992amcRPYMmYcuFEuwigMq7eX0qCkbubg+TAGinIMU+YpISkQ8wzBlK5tjE5U6u8jxRhUAq20TY0xuEmaeziRUrgiMpCAEmQrwUL5BhGLodTZ4+4nxnLvtTe489rrmOzebesKJ8Lzx08IIVBVFXvnlDPieyKRvvN89ugJNgQWtqJer1lUGrB7q+eoEqGyghGdchFJusBTJIbMUjWabocUEefB+cnnYmBi7nbbg3Ou533kDuhn0e+0zqxQqewLHIqXlR4vmzItWMcBMA3IBMScAqLTNTX+/8SCIBaz5XFDKZ8vpTT0v30e9oo+QVSPkio71KcQh9K7+KP6qF6qIYsO963DL1YAg5aLMld1s6prc/B5vsrxSgSLpqn4xre+RkqJjz74CZ999gkfffQRrh1BK9f3eNcRQ8hdOkOky0ClDB4eQPZZiBR25lQnQ3EFhpOlFzfAWH6IZJERSZNgkpREAESTa3MhD0dpJmOMtjUjDAxxsXHozWvGoYt76MyksVU6jf1T3IWkSuYy/S8p5mKypoTkNB8CfdI2oY/jd9B1HbZusEl47f7XWDRrzi8vSLGndT0XF1c8eLzlahfwTpWZet8STSAlT0yez548wefhpt553rh7m733VP2eGCOVqL6EFZURLAvUJJMJV4dgYttvhnH2Aavyfb4IugPQupLx4o4mZjZok3kThsrY7DYHMcQMuKoYsLWomM8EPFTdDHMQJCTlTtR0F46OSNCNI1miNVo2TBS2DoSJ8u9dlTNeMVltPBOu0InlLiUuuw3Pty2XXU+fhJSnadUGQ4OaaztC3yGuU/5F35OSEt1ctpFMuz2sjthdb2l3LXU09Ns9dd2Q+vBCRvxlj1ciWBhjWa/XdF3H06dPefr0Kfv9XrUBrFWORdakkLwICi5RjoNOSDKfCwb+9OMwG7l5GzBYx9183BhoxjKBya42fX/TOteaF7OW4XNIGFiMhXfy0scVcpmUIbwC4JbAmTKRCJZH6paVJPtmuEjveq6vLwd1Mc1Wsm4EFjFCQP06ttstu90Obt/CWkuInq7Vc+NSwlZFx1RJU6UlroHDDMErpUTv+zzOHsZ03IdBTWsqUhOsOq6JyGALUdnqIFiU44UgcAPcnArr3EzPo765yQnXuZ4kktuh5HJ3sg6mmEi5vSrrQx88fH4sPvrsDatArXfaOTK2Jtk6G1llzkkIwzkJYezAJDJVIClZrXjN9n2Ly1PVjkm29AsIGK9EsLBVxXK5pN3tefDgAU+ePCGFQGWbEdjsRx+Jgk6b4aIbK/iU0s8WKJKBg27IjUBxk1vBBNh8yesfLL6i7jWg/IfiI1PQ9RBBjy+8ZgkSmr0Umnr5tFP5uMnrm6AKUlK0IXSkv65r1us1zawa6lpTG+Z2rrYJu61O0Rq9OJStqUpfBVjb73dq75jB2ehloFZLjIjTrCwlXcjaErZDKQRZEChGQtQyI7hDXIKgsz4DB6VsCtaAMTrfMik9gfFiMDdaojcAzpvBfnocANfT2zL2EmNEkr7uVJYxMhLlxnLUZnA7QTRjC1gM3qsp0Gbbsdn19D4QoqEu3AupdF4oKIOz67uD4ThdNxCDJ6pkGb53OljZ9RTXdhEh/gKwinK8EsHCiOB7x9OnT/n000/ZbDasV6vBYKXPQBfkCyADPVpPfhHK+zIocHLvdBOZ7P6RsTwZHisy4qX5sRa1xruZMZRd0gc3/I0RPNPNyOYFPU3DX8oRiUE/56SjUghPECdiwfp+RRLWCt7o4g5JZeTFCs2sout7+n6HrRvthhhVLffZU7TYMgCq3zDBdGJEyVCuB+Iwbl6whmFEPXpSVKxDd3OrwGB+jSmpKkYFSAdcQPTik7yNjxe/TgmX7yUwWgRoYDQHbWmGUqN0iNIBBlGy0yFYM+4DU7BVRAVx9JyM96cb57zs4AUEJeZzmxIxqEZpTIauj2x3PZfXW/b7jq4PeFOrynlWbQ8p4ZxX4ZquHT1agodkSFF1OlQDNhGDw/lulEqQRofozC8Gr4BCnfsph4h8XUR+XUTeFZHvi8h/lG8/E5FfE5Ef5X9v5dtFRP5LEXlPRH5fRP65L3wXCc7Pz/nwww+5vLzEwLAbF0R8WCADByMM7D4YU8/D4PGyqHqIBQy/3igtSrvx4G1OXm66e01/SqAok36lBVyeM4JNI3noBVvGfLEXZqcecfgZ3bZURUt/1y8ypYSxGVxE23be9/iS6ufP5mIYFndKSScorUFMlcfZx6BXOlAp1/TB64CT8x3WZpOnCa9hAJtTyuSqNOyKLkR8SGqrmDsdAJI7NYPmRAYqC76gohiC2BGkfKGUuFFe/LQf/c4Os4PpOpj+e0Cou/EzUNBvgOiSTNYNVawjiSUkS++h7QPX25bNtqXrA2GYatXPoK1ZlWXo+175FWG0MihEN4JHUsSKZneuG3G9FJWPkWL8Kf3An+/4WTILD/wnKaV/KCJr4LdF5NeAfxf4P1JKf1VE/jLwl4H/FPjXgbfzz58C/qv87+ceIYbBDEhiYjafk1Ia2Gql/iz1Wox+WOQlouuJf3n9r8eNyc98lIti+P/hd+UlRF5sW+ZKYJDt13kOFc8N2ac0+ZDbe2FwsJ6Cewpsjql0VWUNiqnZTSY0Td+Xgrs6vxInpUfpliYU2fBZLNj5mFNgAWMxVU2zWIKpSaJDZYO6kxjtUkTVYogo6zJFJV2V8Nl1Lbv9hq5rma9XauicBwBDdiwr2pb6vRtiSETGXbh0vhRfGan4iUxkK54wwE0DoGl3Qzic6zgICMPtY2t02g2ZBvjpMe14TM+7gqDjuQg3Sss4eR/a5iwZoor4+BDYt47d3rHZ7dntVcsUaYYgEeI4gRxCoPOOPttExqJ5mvR7imqiogzjqMNqyQdsJYN8Y8F9/rFgFimlz4DP8u/XIvIu8CbwF4BfyQ/7b4D/Cw0WfwH4b5N+o39PRE5F5PX8Oi89+r7n448/5vFnj7EZtHLO0Xce79xwgnWRhaG7cVCLJrlx0g96C1/0MT/vs48X92TxTAGtm4+f7kTDX89DboM+w+SiURWnMVhYxr/lpYc8k6szFhldm3y2KGTS1o3MKEZ8UOBMjKWuaparE85u3VPtTiN0bUvn+tyvL5mbYi1NuRhthS8sTFH6eRmhLtmTZH1LZUQKyWp5omWVVRQ/jHMeyvkQbOEkTEqLmEV5JE1SfInKzzCHWYGI2hKYmzjFJFhoIDkUU7qpmBUO8K/D4PyysnAoG6eZxA0ciskaMKYCicQU2bWOq+sNl9c7NvsWHwyptiDavSriPbreOcCDQnA5kOb17pXdKiloMM7gcErFbiJCDEOQ/qrHz4VZiMg3gX8W+B5wvwSAlNJnInIvP+xN4OPJ0x7k2z43WGyuN/zub/8uDx8+JCUtNUwG9YqLue48Y41Z1zoeXY7hJEeGulEDyGFQmdK39dCB4sNAYw4AShGbU8S8gNLk0iygq7XDiazEqD2dyEA/NjIZDmK0/svfq3qU2opC1CkA5AiwvXjCxdaDxoO1lkAieE9MDSkYHfO3FbauOT27x9mtO3znu3+Cjz9+xsXFhc4QZNGh4PWi8SliouorGFPpYjMVyfV5qK/PO7ViFwXIFNG2qTE12KCsQu/xXrOSurKZhq4XVB0gxVHZKcZRur90iRSg1JbrVOGqbprMW1C8yMqL9PlixCQiiH35MBjwwgU/loklAGhAsxiqqh5Ks5Ap1+VxhRYeBazJc8tCPgeq9eFJXG87Hl9e8+Timuv9HqoViDqx+b4FK/S94jN9bo3u93sMHotSCGZ1jes7UqbFpxCJJtJ1rbI8bYXrW4ypCLGjKk5tX/H4mYOFiBwBfwv4j1NKV5/35fPy8uiF2kBE/iLwFwGaphls1qxYVRrKVeS0/QXjxaMX8fQv3KR06247ZAQDPpF0O56ocpeAMf7O8Pif8jmnnyUDdwnCxEDZ6Ai0kcPFOpZOOoJfWwUYnetGlmLoh91JRIZ0u/w45zKlWTGGkHLdLRahwUeYLY84Ob3D+uQWq9UxzWxBSg1Pn1yw3eo4d/C6E7o+4PueShTpDz4gwSNEKjH4G+9/nOHx1MZAGnVGh13fGIwElfPMHQUyT00nMJVYRcmasBTNCislULx43svOa3J5Gm/83QJsljZpef70dUIqKqUcfK6CVWm3zQzN6gG0TqMY8bApCUOAkvK3UuFVaAAPUYX2rnY7Nts9+67HhwQmIFF9SmprVaIxBPp9Swye5FUHgxBxMepIgTTDcJy1lpA8+70jRKeWhkOJHrC2IaugfOE6/qLjZwoWIlKjgeK/Syn9T/nmR6W8EJHXgcf59gfA1ydP/xrw6c3XTCn9NeCvAcxn87TbbCEmbGMHCbDpblIuev3RqU85YGJO25uHdahM+AnD7XlEfPyM9uA54zEGjcKw1L+R782pscnXQh9GMlJlLdYqgj6lEZe/Z4zBdz12JlhrBjA0UfQv8mPR+FZNkfeqxsex5DG2pp7NWM5mXF30LJbH3Lv/Bl/7xre4/9obLBfHYAwf/+STrAGiJUPXqd5Cu+twrsP7HokBCTGrlMtQgoQJE7SAuCEEGqOu7pJLppQUeLWJrMlRGJxKVCrDUVIS5INuUv6+zeHFXX7XIJXPmRnPzbRcmGYZxQd1Wkre9I0pz0MfOZw/vU/LgRghOdUeDZlkVfxmDVbxoIxVTApQQkz0vcclg49wcb3j6npH23vtEItKEEoupawRknd0MQyg5pjx+IG5W95z0yhdv3Mtkj+3rbP1pqiM4ufjeD/f8YXBQvRb/OvAuymlX53c9beBfwf4q/nf/3ly+38oIn8DBTYvfxpeAQoU9X1/I4uQQRzmZlZxcAzIzYtaBSIZjZbxtvyL/hvTgKC/gEsw7hoiugBCHGvbQq0e7PzKYpt0DQbgjdISVRDIMBUAACAASURBVIxi2rEZLvYbfIByHzCUL4Gko975YU29RCqLDzF3HQQT4M69N/juH/1jnJ7dY75c4QM8fPSUq+2OGDRwHTU1TV1hJNHnbk0Kkb7taIxQZ0EhCeqfOjii5e+x4BXee2KVneFSnj7NAQERapOzHqNMWmNEmaWZBl6+5wwxTL6D8bzcBLJv4ggiI56hamCHx/CY/FM+wwvA5mSdvOxcDFnJAGyO57JQ+UtJErGEGPFBQUsXIm0XubzasO8CMRlM3WBMrZte1pwVVMc1+aCAZdTsbmpLWKw4RSyrVZ3B7IithCqXsvr9adA1LyHzfZnjZ8ks/iXg3wb+kYj8br7tP0ODxN8UkX8f+Anwb+b7/hfgzwPvATvg3/uiPxBzsGiaWb7AxiAxntQCGE12glxqHJ74STs0yg0Ogt6fUrl4b05djIs1pZcvnpuL9mYwK6ltuvGaikWU5+fbM1Abgz6mrnNNnHn/EaMysKYg6iVQKYuxD5B8IqGqU8vVmqOjI167903uv/51kJrdvmO/c7S9JwZhNpvRtnngaKctWiERfK+eocaoRqkYJRoFDYgHattJa+XO9TgX1HcVMGVUnThM36ZcaujuqfG5zniSm3wf+tHGTGb4ey/NGnKZYQ81QUqgmJYTg/vYFPgs6+NmVjopZ24eJatRbGXEN8rGM5RdlcWkRO8EH4BkMFVDCo6rzZar6xbnE6QKY002imrA1LkzHjI9fGx/lqA6SBlkMV6MZcGStuvonFOQPDrFnYzREfYQ+AUMnAI/WzfkN/j8Nu2ffcnjE/CXfp43cXPnKBfNzTrz8543Hoc4w81/C3A5XQySpoDoJLswhx/55vNG5H18jyWbuHmMZdS4k5r/r703jbHsTO/7fu9yzrn31l7V1XuT0+zmMpyN5NATaSRZMgIk0SCAEiAKnACJgxhxPthIHCcfZPtDBPhDkCBOkECBAQU2ICdBjCCOooERwVaMQFIESTOcIYfDZUg22d3stdZbVbfq3nvOeZd8eN5z7q3q6mbPcDTdnPQDkFVdd3vvWZ73Wf7P/x9pGbgb4E+TdoU4Ga6KyqC1lRuDyffwAUZlBcrQnZnjxOpJzpw7x8rKKitL59nuD9jqrzE8qDBZwczcHHPzcwyHQ8qyZOQqYnDYJHA8Go2wSlMUGSYGVBMCkzo1TgpszdFu+CbGdUVXy0yD5EsxnYZGxDc5ALnOU+sxFaL1hJVMAi8F6XGtmuN5PIz72Fbp0fPVnONjnnPUUUiL+N42efv41NSraoqoqln44c+JKVUInoRdMVRlyXZ/kBCbTWFVNGIxFmsLQlT4umwWCCHig7RDBQCXJoiNJu8UgMaanGFSHGuId0JoiIWbdvcj6Ib8WZlSitzm5KnaPCkYhkPh31E7esKb94pTvx/OhZsawPQFcfi17XvESZG0fVxPnM0EbpwcQJvhHJ5GlOc2a5gihkUdyY3T85t4P0S0Obwbtjk0iuHwgMXlU8zOL7CwtMzi0gq9uXm0ttxZW2djc5vxqCZqQ64t5bgm+AMpJPuaLI3Lg+TCKvokQZgingRZ1zFOoRcbsmGBIjfzCDG3k+8ZkeIxoJKwj5HZ/Sk6/ShaJlERjwPGhcOTxPBgx3Dvub7XaR+9Rg49lk5zc+4mbfrD1HnT56mJIhr07vTzAxBVIUOGQVGOKzb7fdY2tqjKmhAURJtCL4tWFqMz6bC0hE4JUxEiIU7qFs3nF0UhFNJ5RjXYp/aOrlayphASkE3i3PCTqln8JEwpJZ5Sq5YybNphZNl0IRNA4b1QvEuxcTpHU22O1tYM0q4+CXcbTkbpUxMPO4pApBljD4kWualstxeaIQkCa4EtR48PHq9oBYWj0WAz0p2TxrYtNpPpyEiNQhid6xjB5vjaMawOQGtcHenN9ChroJZjYbWl253h6acv8fznX6TbmxHy4qpk/dY6GxsbQJfZ2Tl6s/PkeQdXB3Y311vGsV43gyLDZoa6HLe8EMGNUT5QuzrtUgqPDItZnaHzGUATNFTRsjEY0pmfJ+pCWseJLUvjIE3DTqcFElhpVAhU3mGaAbN2KrPpZtCqpDc2Sd+S89LNUNq9N0Lr2BDnFVwk2hrFBF3a1KOkuKqJMRBDgzyVFNeHiKeSPk1TrA6R6B1GKzq5cJI6lPCR1JI4Sss3wwXHzrDi4zubfHD1Brc3+uybjKAVwYJ3oKjIbUFeGA52R4SEVlZK6lOexEmiJ9oyAmWH6GuGox1MFuhlOXPzIno0Ho8xVtKPEGrqNIj2ae2xcBbQzApMWLCnATZw725w3O7yoMenPTM8eKe53/scfY/px9ohKCbh8mT9hyMNiZZU+5+8xk52Yp2BCpi8I9wFPqKixhjL/PwSJ0+cYvnEKjHAxsYG/X6fg7EMd1mTo3ROURRUVcVwOBYQlU8t0gTdFv4MTzkaUdVjjFHkWWrF+USC4x1GabS24myTE/bp9XVdUyY+iqgMWglrVZPLNxX5yfE+XHtoZjMCoMPRaOzegi+kBpa+F1dxDyDriDX1rkPpbftYE8EeeX6z9unzbZQolCXoOcqgFVhl0t/EyYaoGI4rdnd32draYmd3V7AzujP5kKkxebn264SWTSlEPLzehrwa0sSpViwsLXLq1Cnm5maZnZ3Fez9Fal0yGo0k+vtpcxbTxDVNSHf0Ajja6nqQ3c/B3O+4TTum9rnTBVV1+PO1nhAFH3UWsm65cCKCXjQ6S99tUh9pYOwxVecahq8Y0xxMhG6nh1aGme4sp0+f5cSJk8zPz3Pt6nW2+jvSlUgXWafTIbcylzAux5SlCDA10PXxeEhme2RZQvklhXZjLEqJItohItoknxiDOBtvNCE46iq0cwsuRLIYkWpyE61NjtNRB9volzSOUo734XNw3HlvYRdHEJtHHUtzPqbP5VFnEWOcKmCnbkeYfLY4PKbas1NjBYl0x+gs8ZTIza1MhtKa2gcORiXb/T3u3N1kbX2L3cE+VR1QeeLbVCbJFWQJGi5ITXw1hRGJbdSrSQRHzXEympmZGS5evMgv/MIvsLy8QFFIg2A0GjEYDISSshy2Mzhv/OnvHn/hP6Q9Hs4iTgqIWSaajM3N19yUcLgQepwdjQKO/u1Br/mk95R6wr3zAk2XZjrfbZTbW6eX6hNaS70heEcMUx2QqhaRHSUU8dpIZOFrTQweazIWFpY4e/Y8K0snICp2d/a4u75BOa7J85yi6B6adRiNRsQwYZuu67IVCq6qMZ1uRhanUJFZhtGRuvJUPtDJEmksIuJjlHQUqOQmr3xNVdtW+CbLRIBJx5hmSybcFdM3fFAPdvbTjmXaCRzSETWHYdvT4wCQEMDp3+17mMkapiML+fdhZ3H4nDedEpVYyyeRj6SpUEeRPjAhYrTUDHYPRmz091jb6tMf7FO5SFCauq6IQaVp3YkYtHcNjV6ZmMmF6Uw1QtkxtumhMYZut8Pq6gmef/55fvEXf5HTZ1bS4J0IiAsLfkntqnYS9b/4z//GA++FT7LHwllM795HwUtHHcQnhVOyi96/EDb9vKNh57GpC8f/ffp1MU5QfU1EMSnOkUJyKbLGAN5JGiI1lzRwhMbaXCIQIxXxohDin7mFFS5cuMDZM+eJEdbXN7nx8S0Uhvn5GUonPfdOR8h3q9pTV56iKMisEVBQchJ5nk24EaoSHxqW7IxOUcjFGKZaku0uLC3nZnQ/AqXzjMuaqvbkLkhhEuFXsDokDbepVE0hbdUpbELrRFVsW8nteWzS0UkGI4+Z41OP6ch0mhxJNcWqqSI0yE591FlMOwp5/yPdESUdmoimctLejihRjlYG7yPl2LO9O2RzZ4+t3X1GYydgbW2oRjXGZAiXsG6duQwdCmKziZ5iWzX3rfBSjAIG63a7rKyscPrsac6eO0OWSySVZYq8yMiLReG6gPQZh2kgfxR7LJwFTPXG25xNtQfyuA7DPS3Qh9ip7o0i7q1jTN77uC6LOrzbpIr1NOnq9EUO0kB0riKihWLNyE+tJgNzURkwFh8lhK1TfQGlWVxa5aWXXmF+foGqqli7u8Hm+haDwQGdmR62yClrgW17lyYVywqT5gEagaYYfWKYsjhfS7v04IAGc9IAv3q9HmqczoVLGrLWpkGmVGtRGhM1rvaMqppxXZPXOdFKy1MHYbnSqkZZy6RnNJXiKYVJBcfJTX7veRbnf/j8NqCo6VT1uHrF9LmIqZB5/DU3cRrTJudat/WLBrugjCYqTe0ThiTLMDZHacu4cuwNhty8s87t9S22d/YZ1Z5ocrCilo6aMFdFPN55ykqg/tZabKaxmXwnFx14Uqoo0aq1oqB+4uQqKysrE0X7VP8hgrZglKXZs2L8KWH3JuXnTaHnOCfQhJQ/1NtO3fzT7zcJWe+VApDlHIPui41mxEQmsSnIulAnJXEpekUQ3L88C6UzjLFUlcOnCU2tPLVLVO9RE6KhqiMRy9LyKZaXl7n83Oc5deoUa2sbfPjRNba2+uwPkop2lrN/MGJvcNBS4I8rCWGLboeiyKmqkmE5bvkQQnBs98ecO3eGlRML3BnvU9dyk/roGA6FDToGhc2MXNwRnKvQ2oioUx7JdIfgR3hfcTCq2BmM0Caj183pWNlpXYgoF9D4tt2qlE5RQaqhRIg+TByGjm2hs4nW8K08dHv+lEo8m+nfbqrg2ZzfhiOkdRhmQsA8vfmE1gnGlB6YQw4L0nySFRkFraUeVPvAuPJoK+JSsawZVyXb/R1u3rzNm+/dZKu/i0OJuDSG6BVoQasIELHEe4dznuGoxGqLlWEFoneEkLp4yVF478EYlpaW+MpXvsLXf/7nePnllykKhQ+eXk8LD0YFNnVmMw0udRA/rT0WziIyiSimi5owYSo6ake7DDBV2JqqgRx1MI3zaC6Io/WQGAWnf/hz0vtpabFJRNKEhf6QA7ImlwvYyUWolExA5LlC2xxtmwtShsGkJSZh/urqKr1el9OnT7NyYomlxRNUVcXNmze5dfNOmkQVfgilfEs2Y4xpgWzj8TgJMlmUNWSZIc+7mMwmIlh4+qmn6Ha7bG9vUu+Wk0jO5szOzVNWIg8Zg7TxjLYEX6edV24Uoww27zKuAsNxSbeUaEWjyY3GNm3OKA5Raz3hlpS3EbyLEULbSUqiDqc/RyPDEO+pPzQR3/Q1MKkXRRSJIWsqPZ12CJNU995iqbImzVxkKSIykiIEUWNzMVKVntF4TH93j42tXdbW++zsDVHGQnIsjahQ+74xte69XCdaTa6lxlG261dKyJaNodPr0ev16HQ6KKWoqoo7d7ZAOQaDbiItnqRjNkHxUfduij+sPRbOAh6uFvFJrz/6lKNpx9GfzUf+MG2le6ruTHbC5sb1CDGNj5HgPXnWaSHdWlvpPCAtUucc+VyHEydOcvasqISdOnWSmZkZ9vb32dja5M7du4yrEmWEy7GqRvQ6M2BkTsQwSTcaFa/e3CJzc3PMzvWYnZtjYXGOmZkZ5ufn6Xa77O8NuH79Knt7ewK8ipEsK3Cuar9fiAqCiA0l3WOhDiDgoyF6h9KRsqop64rCZ1ijsToVQ5Eah46S67cj41rwEUo1EYWClHo1BUTvnKBcmw4TqRsFLaiuPe8Boj6cwkQlqEzVDPWlKc3jrqO2tsFESqD5m/xshtssLoKrHT5oyCy+jozriq3dfe7c3WJ9c5t+f5cQIaQid1DCeRYBFRPrL1LjCUpBcIQgKM2oDg9HNg5GK0WWF+R5gUazv7/P7Zu3AFFYVzHQ6XTodrsT2cZsmrvjp6h1+rBdjvu9djrMms5dj/v9qLOYvMf07w9ej0y++kOvlRxT8nqtDFkmYSFauCKiD4RQARVZJsrei8srzM3N8fzzlzh77jS9Xo8QPJvbW1y7dp1bt26xtrFOr9ej251pd5ydvb4IGyslF4gWmLjNNLaj+dzFpzj/1DlRSz91ktXVVeYX51hdXWVne5e33nqL733/ey2JS+lqbFVJRJQKsCA1l5i4JlCaqAMqJsAaGuU9w6pmpqzp5I5cK7wSDkm0kvqF1hO92Ob4G30o5WhalA2kfTpyjHEy5TsdQRyKPI4UwqfPpfceHaRWNF1Xat60SVm0soeoAQXWnRjMkpxgcI7aB6K22KyDr0sGQ8fG9oDb6302t3YYjkuUypCvKTweISIFXEUiQU56uUnOUUUpCPtmfUwi3ibaaNT5Dg4OGI/HXL16lfn5eYbDIUqp1BUr6HQ6FEUhBe4sI89/PLf5Y+MsPslRfJLDmH5+E24eB+yS3yf/fhCZaYzxEDQ8cm9k0TiWpo4xHgvpSJ4VGCNt4OFYimdaG6wRJvPV1VVWV09x5syptAsASlE7B0oilk63S29mhoWFOUC3NO8+ePJOxsrKMrnNWFxcpDfTIU/vPb80z0uvvMT582dZWlqiO9tpLyClVEJyinZm7R25ldmOcly3EPPmOzeFVu+9kLoohOE6pF0+pQ/jumZUjrE6oLFgFVmIWKsStDu2QkgNMY2eSvdIz1FxKvWcSu+m4fTHjQDoMPn3tCNpal0Sih89b801odt0q1E2U0q1eA6FQTe8GdpgM0M0ObWL7OyPWNvqs7G9y85gyLgGr/LU0BCeEpNEtiOSQRmZ0U/HJBBDI3sQcKluYlLaltwYwUNRdFtA3ebmJnt7e9g8S8LQKWWcaoW3xEs/ZK3vfvZYOYv7dTcexmFMpyHTjuKeHDQ5i09KPQ53Ro5GLbQV9JBk6owxKZyW58mMgEsV7hkJ823BzMwMq6unuHDhAqdOnWJpaYnxeMhwtEee58zOzjI3P4tSijNnznDu/Fm6szPs7OxwcCBw7SzLKGzGc5efZWZmhpXlZXq9DoUVJe2lk0t8/sXnWT6xQlGIHKSLTQE5oA2ijh4D3jtqpQjjEQvdLt1eBxcdpavwUTgpGr6JGEn4CWnfaTKUiqKJWtYU1pJrhUVYz41RhDDBpxxl0z58btLN7Rq272k6gEnROaYIbZrSv607NWPqRIw/fB0YYxIF3738DtNdk+khNbRqow1lLLUPZLkmNwUOzd27O9y4s8b163fZ6O8yHDtCM2ruqhYf4X3ATw0RhuggBqHBm5pkDQFikBaraWkYjaSzIYheS/q+QzdmNBq1zqPZmBpr6Q2O6Ll+GnssnIU6UqA69NgRJ3KcTachh1puUwXO+zmHo5HC5Gds13a/z/RT9PVScTdkNidGhfOBuiypK+Gh7PV6XLr0LBcuXODChQssLy+T5znb29usr6+Dcly6dJFLl5/h7NmzFEXGaDRib2+PZ194XiDD/V1hyDKGM2fO8MXPv8j83BxzM7NYa1BRdDqiDSwuL6TWbEXpxi2hkNaWwXDAcLQPBBmpTpX2EAJ53sGWw4RO1XiVSHCiYEV8O02qMWkWpHaC5BwbRW4h15CbTEiEI20XCaVwMZA1O3tilmpwFjrSdibk8w4f7wkFXyJuZvp8MaWWPokaw1TNQit7+O8JHdlEEjaxi09HFu3ubDOU80SdEXTGaFhy684GN2/d4ebddQ5GDkyGyaSFSlWKQ0jEyUQBbgUVIXphQfO1kPAqaIWYpgbrDm+SMnzYfFdfSVu7DnXbwTnq9IIHrTRVWT/w/nlYeyycBUdObnOQDoFqmqceU8mG4/EU03+fTjeUOtwtmQ5Lp8PVY5eaLsajOXPlHVYpujMFAUUWYGGhQ7czw4XPfYGzZ89y6tQpYpDx7vc+uMKdu7fZ2trizJlT/PX/5K/xwgvPEaJnMNhlMBiwu78LGl588QWUkXHkXqqGW2MobJZEeCBv2LWrmnEcS8QQksq4CthcdszRaMTNmze4decOw3Lcfq/aBcbjKsHGDTalJjFGgnN4PCKXaNFJLR7kZhjXJcFrjIbcaDIVMXiiV2Qqa0fbDUhRtpmKnDpXMnSmIG/SP5KKeECGAKdSkiaCZJJmTLdOp+UCBDatD91Ize9WZQkNKTykRk8QlY2zyArRrzE2I1OKwbBibWOTqx/f4rtvvE1/b0zpFHl3lqhz6gDONa1YT6NlabRBq0AMooSuok81L6EtxGp8FSEVOKuGdCh1Ynq9jjgFBVmWJZV03aJnnRMx6fF4TJ0GA5u6U119ekAWPC7OIlnb7joyFjx9QUyT3MrPpJ6OwiskvyZg9USUJuIFDZcKagbwqVXVOPKoIy4EaCDSqY+f6UadXXRFVczQMYNoE6OyJSiRnnNeMQ5drMnRHcvi6inOnz/PC1/4IqdOnaK/ucZuf4tbNz5m7fYdfHDMzRZ8/We/wpe+/ALj8Zi762sMBgOiUhSZfF8fSlQQfkptenR7BU3LsK4dfuwY65pu0aHTKdCqwHsJTw9G+9S1vM9otM/Vq1f5/nc/4AdvXaW/PkSFAmu72A7MzfTQgFWWTGe4oFAqQKZxyhHcmPagKoVPzr2uK+oQ0N5incH6nCwW6GhxUdbtQ000NdZ4VF4KjUNYQKmMTOXEaIg1mJhTGCsoU1Wj9JBoxig1xseSSC2as0ERvQEn7drMFFgswutpBBdiDDHxWgYKlDY4ZYgavJFryuaWYqYH3mGNkXOnLcFLy9t1ThAzSxk1VVDsMuLj3R3euTPi5r6CbA7btTgjrWtXjihdCcoStSZqn7qWwnjVRhhA1ELH55AahrYQ7RjnIsb2GI1KiqKHsYbewgzLyws8c/miHMvoKYouVekAw3A4YG1tLQmKH7DT3yO4SFUFdKNh8intsXIW03YI9/AJ9YumqMnUY4d2fjXZrQ7bNLYwvU+KZtq5A0yL0NSZ7DhlLWpQRmeoIgnC1E52nyzj5OopTp87z4ULFzh9+jRBaTY21rj+0Yf0tzZYu3ObuhyzuLjIV19+hS984QtYpdvx/KbNV6Uqd6/Xa+c/ur0eWmtmex1G+xW1Uhgjz29o7gajfd5++21u377Nx7duspsmHg8ODtjp7+Irz/7+vmAzpoqF8np5L2stKoIP9ZTIk+BM2rQCKXAq8cjCnlWWjA1kWmGJuBy0bkBRMktBaODZoHUEnWYuTA5OE0LEGouOkaAKKQIigXjECBlMkJssJuh5c9yiCociCaMzMjPpcDTaKM35zrSkHVmekSVHgTIoZUFbqk6B1paDsmSzv8vHN9d4/8pH3L17F2U0IR236JL8YqP10lx/DZsP6b/0t+nByUY0u3Q1M91Z6iZK7XYBzXg85gtf+Dy/8Is/x/MvPIuxEinnmRDgECXC6Pd3OTg44OBgyNZmn3JUMRrVHOwPUUHxG7/REN39aPZ4OIu2q3aYRAQmyM17K9jHO4v71T6mTdpm9z4+zY7QFIZiUMSE1MxsTp518bFmXMpIeNQyjqyNZXZ2nvPnnuLChac5c/4cc3NzaK3Z3ZMx5eFwnxgjc3NzrH7uaZ555hm+9upXefbSZfb399na2mJ/f5/KJeLeylEUBTOdGfJuR2ZHXGSwu09/a4eNO+tCr5bag+PhiNFoxNbuNm+99RZra2tsbGywd7AvN/F4zHhUcmLpBMZk5JkUP+tKZAfLKpDXMiqf2wyHwpf1odRwMlk7ifawFnyN85FxVbGvITMWqxRzsQCtsdZglQPvJYLQGcqmqdwY0Zkit5YYNK4WNuoQZPAsAg6dhskytKmJ0eBMlNA9Stpks1QnwYNSWGUxWpOZnNyalgndBIOPQQrFRUFumpZpRvAQlcVkXUxeUOuMcVmysbnDtRu3uHL1Bjdu3GJ3b1/qFyGKoliU4xSil45PCBAbiYkJZyepA9LWTVrJAoNwgFi0lseaZlHA89wLz3Hp8kUuP3uRvCOk1tbKsF8MClcbxmOhI6jLmt2dAeNxRTWuEyoXfuM3ftgb87A9Hs4CDl2MjYOYvkiPw0ocKuooLTMWyQ7PChiJnJMnaPDzRz8bptpqSkFMOylNt8OgbYdCZwxHNeV4hLIZRbfD/MISKydP8cILL3LmzBl6c7PUlWd/MGRvb4fR6IDZ2VlWlhZYWVrm+Wcvc/Hi05w7c5Y8z7ly5Qr9fp/KT6QaZ4sZ8ryDMRnRRQ6GA3b2Buzv79Pf3OKdd95hb1eKnuVozGAgj23vbLOzt3tIQrFMDqiXy7CZUZqghOU7aFFrD84RvcNmGdGolhSnrecoJaAhURkFJZRxRlnQchNUIVDWgbHz5E4mbqPK0Cm687UnGAWZpuh1RBvVJfSiCWSFxVrdjnHLiL8iixoXDSE4mc5VGa6OuAxA0geTZlgCDf1ehtFZAsIZjBHRpObWtdbSyQu63ZnEX6moYsSYgrw3i9I5O9s7rG9ucfX6DT6+dYe7m32GozE+KrxLsgFH2OSFWNlPbXApqj3U7p1IFUjEI/QC3knLVZTkxnSKHgsLCyyfWGJhaZ6ssBgj5NEu1kRXEUIkU/NCiWgMak4xOzeXjm2a5A733zwf1h4PZ6EmUQVMKt/3tLKm7LjIoXUOR1qn8vyUfyNpw/Tn3fP6VMiYTJIKIa7SHYHuJni2shm9mTkWFxdZPXWapRMrLC4utngGrTWdToenFs8zOzvLi88/x8LsHCvLS+TGMhjscu3aNa5cucK3vvUtfAzkec7MzBzdbpeTJ07S7Xa5kl9hmDgK+v0+e3t79Pt9rnzwgQjQaI1No9HOOVxwuMTDKLuPJs/ztnD3uaeeJoTA2toGdVm1RcNDtKNqoqjVHKvmPIRwxLkqYYYiOlxUVD4wqj3GeEZVpCgUIVp0DMjYrUEjKVswhkhFVIGgazl3mUFbacDKOjQxWkJMFPcM0SojZJrgtdB+ahFnJqiWed1aS25yMi27Niqxltts8ngudI7GZHgVBUyfdQi64GBcc+36bW7cvsW16zdY29phMBpTOsFDuChTp4doCqaBZDF1PkBAbc11q5oOkPzbNdGaNfgISueEVJzO85xTZ05z6tQp5ufnqUONqwPOV4QkGUHUBJUoKaNKjGAJEKYcVT0pZH8aezycBZMb1SUKsKPAoOM6H/e74SfOQqbu2ufEFG0AK8zLhgAAIABJREFUEdf+DcSRxBiFEVkBaAKiOlVYm/LHDvv7+5ROOCRmZudZXl5mZfUEFy48zcLyEhcuXGB+fp6i120RdTMLBbO9GZaXFpmfmWVuNmPj7jbXPrrKt7/9bV5//XV+8IMfCHFN3hG05kyPud6C3FBBKt3D0X6L4nOuZjAY4L3H6sn0ZggBk+lWsKhpBXa7HebnF1leXubrP/cz7OzsMBq+xt2DAWU5ptfpkBsNwaGibrsRAjjTqW6hUWrSyYgIJFyrKXlJFxn5COOa4OFgZoZOFrA60slyCpPTKTIKY/ERtNEUnQzhJw0EJXyg1kqNRE6GENvGaOWmixGlMpm3CBqfqlHROSnmJceWWUOWG/IsRxlHZixZLoQz0vVoahkWoy0Yi9EQsOwdjLm7sc1bP/iA9c0NNrd3OBiWDKuaOiIqbTLylVCwkna0120MU5HE/YF/Lp2zAJgYMXlHOkfGYk3BzNwsp0+f5qmLz5B3ekjdPYCSiC4qEVxSdQCOUiUo0YHRn4wrehh7LJyF4nAL8yg6r7Hp9uc0aEo8Ou3ouNaJNVn+lYpyckmFkOjhok4QxPSe6QZBTQ+vJeJeBcpoRlVNMIqVpROcPn2ac+fPc/r0aRYWFlg5ucr58+f50le+zPz8PFkGVSXq5CoXPkijFIPdPV7/7nv80R/8Id997Ttcu3aNvd1dAPbTzS8dhhqdWntzc7NS9Gx3+4m6fF3XbYeocQxzvTlefPY5zpw5kzAdJ1hcXGRlZYVut8uLz3+Bqx99xN7ODrv9Tfb3RtisINOWqhwLTVyWYYzMajgmuJIG8diohscQyWwuqNNg8HFM9DWu8pQe8q0Bo7HnxPwcp5bnWJibp5NLd2Z/PKCT5/RmCnqdhG2IQYiBokH5xA1CyumTed/DhYgOimgVNgn7aD8mBEckYLWhKAp6nS7dvAvKp9pJRp7nZHmHLJM5CyEc6uAC7O3vc3P9DtdurXHl2g3e/OCacFpmkuZ4I+UurS2V82k4TmDv4luTWpmfisxCnHTdYmydLUqRZSKKTNTUwTPYG9PtdtFa8Bq97jyXnvk8RbYI9DCAyUWLBAUzOdQ1BDUiUzpxlVSTe8MGfAhMSx/9qPZYOAs43G8/Omk67TimafOPw0ZMFzjbajOShsSksKX0pDZCImudRvuFILgJoy0xBMraE4djfJDHLzwtwKpz52T2YmVlhVNnz3Du3DkWF+bRGsqxw1hLp1PgqMB77q6t89GVD3n9O9/he2++zq3bNxjs7VEUBYPBAIBuV0hXh8MhmS3EieKp6iopgEkhzWaGvMjozRTMzswxNzfH/Pw8c3NzLK0u89xzz3Py5EmWl5dZWlpidna+TUUaOHCnm9PtFinXVdRV3R7DZgbFGINJBbmJs7i3QBwhEeAKFsATcFEx8hEzrNDstxiGOD/D7EyPYsZgbCRoqKMmb/ANLqLJ0MZilYUwmVw1xlC7DBNVYtGW/0JweFXLGL3RFDbDWoOPnjKIPmhUCqUtxnYwtsBmHYzOqL1if1yx2R9w9cYt3r/2Mddvr9M/OMCjyDpdPIoyBKnBMBFIkg2s2XA8PuFCaDtGjV7K5Hi1G1xQ6ExjVCaiS0ojjTAtWI1QMxyW3Lhxkz/54+/QnemhGxyIEWhAlmXML87R6zq63a5gcGwPn2j6DB3RgTkibfGj2GPhLJpQbhoo1VyUR4uc052QQz+nHvuk+kZMwJ3YRirNFKSirgVObVUzdSgkqeOqJO8UzM7N8NTTZ3nqqXOcP3++hW2vrKywtLJIjFCWdRIQlpzSZJrdwS7vvvMW77/7Pm+//TYfX7vO5uamqIBVAedEZ1QngZhu3nQLPGWZwDauSjUNSXEuX77M4uIiS0srLC0tsXxihaXFZU6fPcP58+fpzs4ktqxiMiAVNTvbfcZliTGy+zYK7mGKju4QWKqpGcXjEbY+Jg5NJQVESR4MMcCo9oREGReVtFc9Cp13mM8KCZG1x6PxJsMkxm4dM+HZUgaTG0ziHok+YPMifbhBaVEIq8KYTuwQgpFht0Q0hDZEo8BkMr6lc5wyGFXgdZegDIPRARubfT64epV3P/iIK9dvsLm3R9AZ2fwqPgaCcyIXmaoPChGCbuUMg6Ntj6oJSxdMqPibY6dVU0eT+hnOobQlEimyLtYKzqR0Nf2tHX7w7hWcLzA2x9ockxVoK1Fkp5Nz4uQKp0/N0O12mZ2dpZdSYJtp8iTT8KBU6GHtsXAWMPG2R1Gbh+DUUwMxjdcmQcXj1N8n73GYq0IfcjqJMq1xUtoAGmMkaqlS4Q9tWh6G5eVlnnrqPK+++gqnT59mdXWV06dPs5xmM4yBvb2RtLWMoVtkOKfY2N7iw/c/4J/8zjf56KOPuHt7LY0Vy81Y1zXlcEgZEo27ScXKKBR1vdkeRSdnLu+xurzC6skVnrl8mVdeeZWlpSV6s1IQnZudZ2FhgTrSvkc59qhOoCgseW6pa9jdHbC/PxQaOZO1jsQFGU+Xtt1h6PD9Ij2lFAFBKqoksacbZClCkR9q2eVq7xiNx9Qq4q2lu3qSrCgwRom/thaUFqUuLDqlikoDiYHLK4/R+eT6UIByZBiqILoZqgGOpToEJsf25olYKW7aHj7roozIJNzdHnLl+m3e+P57vPfhFda3+4xDoNObIctnUy0ocUukeY2QLr8YHDH4yYxQUp6TDWyiohdjSJgLnQieUrE4YU/E2UjapxMMnRA5ODjgxvWb7OzWdIo5cSpKirkueLRRdGc6dDLBZczNz7C4uMj8/CwzMzPMzc0wNz9zzwb6o9hj4Sym5y+mI4OjBc2jzkLyMvl3iPdGHM1r5fXyXKUmr5X6RXrfKDdJU1AEpAAXI1mWMbcwz6VLF/niF7/IK6+8wvz8PPPz88zOzrYgqoODivF4zG5/h36/z/b2NhsbGwxHB+zs7DDbm+ErX/oyr75StFX4siwZDAZ8+OGHDAa7lKNRS9ePkYr9pUsXOXXqFKurK5xaXWVxcZGFpSWefvoiRdGVHbv2RKUFap7lCHWX7LARw7h0lOPA/HyO81BXMprufaD2Ap3WykCUtlzEt8ep7Sr5qeIyE34KSOG4CgKusoJvsIjAkI+aOtaMvMeNR1Qbm+xWY/S85cLZcywuzpNnDQ0g1N6jVCZ1CA01DoJDK9B5JiS2cdJdiGl6T4q7Bp0Z8TDaELTFm4xxzKg9+Crg/YhAReSAg4OSD97/iPeuvM8P3rvGRr8v+hxaEaqaamuz3VxsJo5V2YCKDednWosKCQeS5BAecHMKoTBoIxGTTylJwKOI+CDvkRmDCwi1QR0pqZOTifgIPgor+Gi4Q2ZyjBmT5wcURZ8sy8hyIf4VEuyfosgCDhctgUM1h/t5xuZiTtcOCjPlbCbvK49NxpHbz2MKZu48TilCiHQ6ncRLoJidW+DSM5d5+eWXeemll7h06VIbwjvn2NnZYbe/w9bWFltbW2xsbLC2tka/32c4HOJdzdLSEi9/5SXpnqysMjMzg9aafr/P7u4uFy6ck7boYJeylE7GzNws3W6Xzz//HGfPnubkyZMszM2RZRm19xTFTGKJMtRGiqKuhnJcUhSFoBfzHK0M5dhTlkN2dw744P2r3Lhxg82NPUbDmhgMXhvyfNIujjEdVz05ziomQpmWSEWOp4uRqAImpXeSsii8hBt4pah9xKtI5RV7ezvc6W9iZ7tk3SVmV86yuHySTBsOBkPGgyE727tYrVia79HtdFDREUMl64lDGZNvzrHMZUlKlWVEq0UKUAgyCcYyDBmjccnecMz+fs1B6SkrGAwOeO+9D7lz5y7r+2NqLKbIiTEwdjXDUhxR0362vmgHzXQjSWBABU2IqZNHuKe93B7DJPOgtUZF6abIVK0SWr3YCGcJsC3PBCA225thOPK44NrWqzYaZTKc91RlRCnPeDTC+0EaE6hR6njR7R/FHgtnMc15OY3cPNoVmQZiSfFtmnuh+V/jdCT3PQoZv6d+EQ9/lkx1WrwXxuWFpUUuX77Mz/7sz/LVV7/CCy+8wMJCj8FgzMbGBndu3ebGjRtcvXqVmzdv8vp3vku/38day+rqKufOXeCrL3+Zy5cv89U/97U03yIFzMFgwNLSEp1Oh4WFOXSKJIpCKvZoQ1FkFFnenvQYG8o1xe7eAKUMWd5BKYNLnI0m64HKiUrjgqFygb29AYOdAa+99hqvf+c19nZ22NrY5GBYYa0MKRnKqcnOxlEfHtOfMD0dNq11UhFruEmd1ISCwlclztdkmcLoyLgcMhod0Lm5SWd2g+7CGYoZTafosjeu6O84rl25TS/PeercKufOrdDr9Yhe1NOUP0Ap4Q7XiTXdh0iRdwWroCFGjdYZOuvgo+bW5h47uwds9ffZ6h+wMxgzKgOjYU1/54BhpdGdebIiJ8Qa50oiAR1l53ch4MsS41xbJO50cwyGDKktxSC1iwbc3RylSCrARzlGxlipV/hmLF0iqDzPUZXMNpnEkWIyQ5ZblIK5mVl8MNQ+MZNrBUq6MA0zuUSBKnXPsrb+8VPjLIDJhGO4FwwEk6jjuC+ttW4Zjo+mLo013hrAO9ERzbKMcjQmBNkljDHYXCY7d/YPOHfuHL/8jX+VX/qlX+JLL32FTq6pqorf/u1/wrvvvstHV2SHbqKJzFhWVlb40pe+wtf/hZ/hpZdk7iPPZG5jZ28v4TwMZVVS13XSdxhR1SkaMA3jUYbJOjhXUVVVOj5u6oKwzM/PEYMwMVVeUg6tDFWtWL+7wcbGBuvrm9y9e5dr165z584dNu6usb83oMgEkJTZnjjJqkLU+zQheFHiJqLReD+R1KPhtpPfUITEWxGp60qiM+ckh4uRqkzSeSqgXMSHkhA8Os+4ub7HzvBdvvfeLWZ783SyGVTQuMpTD/ex1Cwtdnju8gW++IWLnD1zgk7eJQu7BBfBe7RX5FqTZ900qqXwXhF1hrYdSqe5s7HFaz+4ye7ekN39kv1RYGdQMRoHnJcUztUK57VEBEqhdUYInqA8AlhL0Wd0rcRg7cp0U8vErU7O0mhNVBMav+aKnUYey+UpdZ2opf3qqxpqjQ9BZAEUFEK1Rllto1RXwG86BzQ+Ojw12ohjCSHgnUR+jUNzftTihj6tPRbOIrEaMMFgT4hLpzsjx82GSDOrQWuaqZQkIqNHpj3R4kwkZGxnEkyR2qWOunaU1Ygin2FxZok//7O/yC987ef5c19+lcX5DleurXHlw/f55m//LlevfsjW9gYET9HJWVleYGNjg89//uv8hb/wL/L1r/88lz73FMbAzs6Qg4Mxnd4saMVwfEAda2rtcSbgDIRoiJlFFzOYzgy206FnZqALVT2krktQAt4JETqdDrXXdDqzEC06KKrKcbA/Yn1nl9e/833u3F5jfX2T9fUNtjY2Ge0fkNsuHeMorKZjDcSa2o8xOFxVSvcgGKyyqKiITvATWiOwc18TggPlhUymPaYe52p8coKukUn0FUYb8k5CtaLRDUeE6cmNu7eLNTWdosLoglBDHgOhPmCjv4MtDIsrPVZPzmMwUGfkuUPbMd6NsTED3SX4eUaVI+YFUWc4kzGqHZt9zwd3BuztyQSu85rdfcdwVCYk5RDHCKdGwBi80NwRNCYmHhClpb2Zhgrbm94Yqlq4JQS4p6hdpNvpTm1wU0V2ayY7vZYxdqNFYiAERwg64UwEko+HUJZEVaP0Ll6BUjFJGygypVABgtaJmEgljIpBBY1VWQIe/pQ4i8Z+XC2e49/3cO4oEYy0SZWKOCcHs6oqBoNdvv71n+drX/san7v4NEopbt/e5gfvvcObb77JtWsf0d/Zksk/axPPYc7Fixf5xje+waVLzwo3Yikq45kWOPFgcABK0cxQxqCkEo7Gmg5GyxShkPI6lKpSVV1jbEeg20aOUFU5trZ3GQ032drcYWdnn8HeAYPBPv39Ee+88wOGwzExpVNaWWzewVpNVYILnnHtUbHG1QlarBVZnrfDZQAxRVyNAnyjeh5R6eKGOggwzDnXdj4aNKluqv7Ot/BmHWO6YRxEk+pInhhrIEMbBc4BgdqVbPc3uXWry4kTPVZX5lnIPOAg1omQ1wvGwQvRkDaGygcOhvts7uyzsbHJ3vY2B8MRPmbEYKnLMaFyBAORkkAphdPghVq3yRyORLJHu3LQ4D9UQguLAHeWhvSmZRSBFl3ZdFiORtHTkTXIQJPIX4oEZqPaDlHIg5qN1BgamjaljAAP0TSiTvHTZyGPk7P4ZCdxXLfjYeze7ohUm3XivIgRjFV0jMCzx+Mxly5d4vOff54TJ07gg+Pu2h3eeedt3njjdWKMnDtzlqWlBYFoFxkLCws89dRTfO1rX2NhYQljhOlqeDCWSEYrQtS4WnLasQuMxw7nFYqMbq9HJy/I807qShh8bNTewSuPG5aMRgcMRyXb29vcvLHG1s4u62vb7O7uMR5VlGVNf2+X7e0dprlAfVK0atTIiDH1+2UQSjonx+FTmlxYVLhSH0RC5aRFMk7OJjopqgkx8YTWDQRf0TBbteJR4SDxW3bwQVE7lXbanFE9RMcK5cZsbdVcvV6zuJiT5ReZX+5RuzEqhhSPBkwUVKO1FpN1GFXSgbrx8Roff/wx/Y271A60zvDR4EYVdeWkIKsrUDUqljIfEwMKn6C7h6UjRPO0SXUn2CBjbDub0zgUqS2F1IWbOIuJY/A0lY2mFhViRSN9qU1InyWsXs1ofQSijtKuTulhCA3CVZrWze8Ry1FxpR/VHiNncW+d4ehjxzFnNY+pI69v+tsc42BiFPCRtQbnBRmZZRmdTkdOWqh58cUXeOaZZ4gxcufOHd577z2++9p3eOv73+PSpYu88MJzfPnLX+bCU+dZWFig6HbodWe4ePE8WsH2dkl/Z4/RaMTC7CpWW4ajmu0d6XaUTghzUUlham6GotMjt0W7Vh8EELa+2QyPbbG5ucnO3j6bm5t8/PEt+jt7gpsYyMxIXXuK2Q5zswvkeYE1Fu8Dlaup6wrvKqqypJNrjNUYJReewJ49VTWWTohRRJXAWsG1czYkuT6XVL+9c/h6jPfCKdkWlEnAJRItf8JuaGvayM5XI5mBAAFmhRqvCgrbYVwO6GQRrR2DgwPu3h1y48QsqyeX4cQiIVgIOpEB67aoaKxgMKrKsbXV58aNG9y6cZNyMGhbqc6DL70orgWNsQ6lvSAdqZuqt7Qx1cQpNFWaSWR6uKXfTPgaI7KTgrh1h4Bt0+m0TrWKQ1EFXorZJhH46DRvEtMkSkqnmykFlcSTY0yzTklyoEk9AuJ8fhz22DiLo1HDoQr8VI3iHpLX5rd4mLC3maGI8fi20TTWwrmJJmSWZaysrPDCCy+wvNzjxo0NPvzwQ9588w12drc5ffo0v/qrv8rnPvdUOxeSFXnaXQxVmdIE57FZTldpUdHe3eW7b7zOzZs32er3251WeC9zzp9/KkF1c/kuEQ4O5OK7s77BwcEBo5HwVVSVY1yWHByMUlE2o9ObwVhp5QbtW2h3UBrvq6R4PqST53KlNcc5dVnQIdHSNxHGRB+zARgJZ0hsHUjwNc7VIkAUErYxqrYd3WBaiBNNlUYMqXI1IZSpuyIhdPCaWlVoVeHDGBBRpLIq2d0fcfPWHc6cOcMLTz8FGLQyKBQugNGqHWkvy4qdnR3W1ta4e/s2m5ubWGUwyoi2a1WjnMckPIPNFEp5iVKUFAwaxGojUtRGCE0KEoSLVCuNUVpmQbzMpGQ2S2S6/p7ruomqJg5EUpK6ShOkIaBUhqQgaUSuKShLoDNVxPcTpLlKwyLNZyVnIVWlnyZaPXXYIUyHatM3+jRICJqIolEhmw4VaR8PMRxxMIDReKS4FJWCNFW5v7/P0tISFz93iVOnTrG/77h27Rqvv/46b7zxBjv9PpcvX+bVV19lcXERay2zs7NkRSbgQ2Bze0R/e4ft7R1u3rnN+vom22sHbGxscP36dbZ3d9jd3ZUowLtE+55x4+P1xFw1mcuogyIGxXA4pK5dAu7I97Q2pyo92oLNOlijUHnCAnQMdVUTnMy3AGgle68PIpAsLDGGzEqurbQ4gCzLiZE06k6KwKx0MEwkhjSH4SqcE2fR9ABVbOCWAmYTiUKfHMgRwqKo0YR0Q5SiRYJGhRrnHSE6GYDScqE7H9nY2uHmrTvsDUu6OeRNDSdGkYjUGXXt2N0/YG1tg/X1Dba3dhiNSlZPnUQpxf5wzDiUGDzKyE1mtYE0hWwQB4qSeoWaujanUcbN0CIqSuciOcT5+XmKomBjY59JqjutVzJRPmucRQMsm97gmonbZiKhOX5txHzIRIdEnieTbkLHID8bQuBPa5/oLJRSF4B/CJxG/Nhvxhj/O6XUrwP/AbCRnvq3Yoz/V3rN3wT+MuLS/qMY4z/9hM8gy5qQV0lYOQWoOjo30sCPm9xb8t/Q5pOTfDEm5qIsfY4BIt4nhaoobbPMziRpP81TT1/i3/g3/232dkf8zv/5W/z+7/8+b731Fvv7+3z5y1/m5Ze/yoXzF+n1LPv7NcZmVCVsbh5w48Yt/unv/XPefPMtPr5xk8HggP39fXTMcc4xOzsrQ1ap8OV9pCorgq/YH5S0JC2JOLaxug5TO4WSseYI87MLhOBQwTMuRzhXURQFsTRYNN556sTyVY9LkSTMLYaS3GZ0c43WkRhqghMkYlmN0Ik/UiGQYl87bGZkaD966mpMWY6pStEfyXRImiKTtmpM9RCizGbEAL52uEpSwIZVXM6XOL1cwDJEX6E7irI6wEeFNQZtM+6u9+Htj3jh8g3OnJxjaSEjFoa6dOQmUvsRG/09Prp6lbd+8B7Xb99ic2MPFTNeuPQsVT3m9t27VOMBtQ4oAy7UaDMRtxbinIaCL6J9SFHLhODGGJk7sXaCx0HBubPnePHFF+l2u/zuP/v9NhURZLBEVqIbK924JhptagpyHzSSlEnFLAqruk0RSIodEpHTJJKoJzH2pACaIu9MSZTyae1hIgsH/Kcxxu8qpeaA7yilfi899t/GGP/r6ScrpV4E/iLwBeAs8H8rpZ6LD9B8bwpvzcGTm6nJfw+nHtOFM8nxZAdTmkMRR9Pzbna1RlchBNGcaAhHskxu5KLIWF5eZnl5lXPnnuLtt9/lj/7oj7l27WPG4ypdQBatMryH0QhiVAwPAjdu3ODmrTv88be+zWvffp3rNz5mMDigKp2g/Sx0et00inxY4FlF0Eaye51GzE2jPYGT+gHi9BqUqlUaFYRKnuio6ooQKrQKuMqhfGJMihHlPbGuiaHGqgCuwuiIijXeRWwmFXetpdSu1RSfadpZp8FtZTlqdVCNkZpErsV51wkfoNBoK1KNwcv8g1KNWHGKPJSWaEfHVtODqap/UQhuwteOEBXj0pHlPQYHY955932K7FmM7uAqK9omRrRO7t5Z56PrH7O9vc1of0yMkaWlJebm5rh5c5eqqgjRoQ346Ih4gbcHhECXhAqN0rHSLe3B4Z1ZojuLMYqyLMnznLoWjhFJFas2ehBpyboV0m6uZ60tdV23zsImUh5IIKtUI9Ix4ryjoVFQajKcplLKZJIc0aRbkqZivSf8GFiy4CGcRYzxDnAn/T5QSr0LnHvAS34F+EcxxhK4qpS6AnwN+OMHfAoRj1ZTB6tNK452Mqa/uG7ObPp3E7M1bb6EAWgozJpnJaIQgTNbKcQpi9EZK8urFHmX9977gPffv8L29jbOCVvWcCgFRK2sELsMK4YHYz6+cYc//MP/l2+99l2uXv+Ywd4BoFrlrVZ7MoXzTU1CqalcMwo6UrIFn4psTpxdTLeYSm2xphpfV5K3qhqFUMuHIOPs0hI2KMBqKVh6pQiuhuR4pNAuk5sy/WTTTSyM2NP1oOZnc8HHKL2RoATQppTChIBvzpMX6qCQHPbxNo2tac8OqJTbmygSG64m+CC1gaBY39xiY/sERTaHmu3Kzpk79nYr+v0+O1vb7O3tiY5snrMwN4+yGaUTpfOAdL/qWsBnNsr3ncYjhCadUlOp7ZFQvmnVhhCoqoq9vT3W19elNep8cphNEZa2cBpl0oyGGiG2161HtBB0Gilvjo9EZtPp9fQxVEG1NGc6NsTUooMLk/btpzX1oA7EPU9W6nPAHwBfBP4G8O8Be8BrSPTRV0r9BvAnMcb/Ob3m7wO/G2P834+8118B/kr65/PAFrD5Kb7LT9JO8NlZK3y21vtZWit8ttb7fIxx7kd98UMXOJVSs8A/Bv56jHFPKfX3gL+DuL6/A/xd4N9nOhSY2D0eKcb4m8BvTr3/azHGV3+45T8a+yytFT5b6/0srRU+W+tVSr32aV7/UCVSJb2cfwz8LzHG/wMgxrgWY/RRZoX/RyTVALgJXJh6+Xng9qdZ5BN7Yk/s0dsnOgslRYS/D7wbY/xvpv5+Zupp/zrwVvr9m8BfVEoVSqmLwLPAt358S35iT+yJPQp7mDTk54B/B/i+UqqRNPpbwL+llHoJSTGuAf8hQIzxbaXU/wa8g3RS/uqDOiFT9puf/JTHxj5La4XP1no/S2uFz9Z6P9Vaf6gC5xN7Yk/s/7/245kweWJP7In91NsjdxZKqX9FKfWeUuqKUurXHvV6jjOl1DWl1PeVUm80FWWl1LJS6veUUh+kn0uPaG3/QCm1rpR6a+pvx65Nif336Vi/qZR65TFZ768rpW6l4/uGUuobU4/9zbTe95RS//JPeK0XlFL/j1LqXaXU20qp/zj9/bE7vg9Y64/v2DZAp0fxHwLF/xB4BsiB7wEvPso13Wed14ATR/72XwG/ln7/NeC/fERr+/PAK8Bbn7Q24BvA7yLt7Z8B/vQxWe+vA//ZMc99MV0TBXAxXSvmJ7jWM8Ar6fc54P20psfu+D5grT+2Y/uoI4uvAVdijB/FGCvgHyEI0M+C/QrwW+n33wL+tUexiBjjHwDbR/58v7X9CvAPo9ifAItHulp/5nbtobIjAAAB+UlEQVSf9d7PWjRwjPEq0KCBfyIWY7wTY/xu+n0ANOjlx+74PmCt97Mf+tg+amdxDrgx9e+bPPgLPiqLwD9TSn0nIU8BTkWBwpN+nnxkq7vX7re2x/l4/7UUuv+DqZTusVlvQi+/DPwpj/nxPbJW+DEd20ftLB4K7fkY2M/FGF8Bfhn4q0qpP/+oF/Qj2uN6vP8ecAl4CZlD+rvp74/Feo+ilx/01GP+9hNd7zFr/bEd20ftLD4TaM8Y4+30cx34bSRcW2tCzPRz/dGt8B6739oey+MdH2M08HHoZR7T4/tnjbR+1M7i28CzSqmLSqkcGW3/5iNe0yFTSs0oGc1HKTUD/EsIWvWbwF9KT/tLwO88mhUea/db2zeBfzdV7X8G2G3C6Udpjysa+H7oZR7D4/sTQVr/pKq1D6jifgOp3H4I/O1HvZ5j1vcMUjX+HvB2s0ZgBfjnwAfp5/IjWt//ioSXNbJb/OX7rQ0JPf+HdKy/D7z6mKz3f0rreTNdxGemnv+303rfA375J7zWn0dC8zeBN9J/33gcj+8D1vpjO7ZPEJxP7Ik9sYeyR52GPLEn9sQ+I/bEWTyxJ/bEHsqeOIsn9sSe2EPZE2fxxJ7YE3soe+IsntgTe2IPZU+cxRN7Yk/soeyJs3hiT+yJPZQ9cRZP7Ik9sYey/w8S/8u/ZyyxuwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f56abb10278>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "human detected, as a dog you'd be a Portuguese water dog\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f56abb10198>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dog detected, this looks to be a Mastiff\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f56abaf61d0>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dog detected, this looks to be a Mastiff\n"
     ]
    },
    {
     "data": {
      "image/png": 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iE4iNByZAmgCpE5IIXC9PlERIX9ARaxDREiNOnaB2nKA2z1K1yqt//CU4SZUTTx/l/gee4M7HZ5Aiz1o/4e1vuJYn7/kGV196OZt3bWXq9CwHjp3mymt+nLXr11EqKMozZYQ0DA07PPbAIt+6/dvsPz5FID1wPK7bfRlXb5cc31tmbO0WavUlcrLN7NwM9U5Cgo+OYcXYCi654kXMlafYtGUHJ44fY/eVV1Ftdqg0G3zmH/6e7as2cPjxJ5EGZufn2Lf/ScpzM9z6hjcyqIboRILSwAidIKbTCXFdHyM0sYktG0//6I6hWO6MUF0vX9fE169U0UcYzlC6zqddGCA1EMcaKUFmQSL9ds9MRerFgWqRrmqDTBd9VxvthvOJVAwwqZZv6No9U9mzGxGVRKBjtNGAQjo+nURhpELoGN2Zo+jEODrkyT17OHV4L2ODA8xv28z40ADf+u5dfOGLXyGJfN7202/lp974Kqpzs2zespHJ4TFOTJ2g02qzZesGNmxYy9jEGE8++ThSSebm5vne977LA/cfYffu3bztne/ALQ5z6NgpPvupT7JqQDM6Mcov/9J78ByoLDa468772Hv4GLniKFu27mDNyzcyODLM8WOHcCQ0m01mZmb40te+yeDAIAMDdU6eOM2OHbuoP/EUjU6LUydPsmnDZj78l3/BW970ZnZdfjU6EYQCfMdFo23QCVbcMjpjX3125N7/zyQGnNmeDTi77cIAKRAnII1BaBug23M/popQeqalmCIFqQUcSSoaSI3QAim7Hqp0QadKVEqe0+tIdJJGKiXGBhIjMChcmSOMYpQDRieszgcceHoP9zz9GPXyaRanT6ImR9m8fiVHD+7jwx/9LPOL8As/8+9519vfRG3+CMMFj7Ddod5q0mkFrBifQLkOhaLi8JG9nJo6yUMPPsbgyAgTKzZx009ezIa1k6xcUWRobJjhQYcnL97IUrXM+371PUyM56lXFjl5YopicYJff+9bGJ6YxCiPfLHIP3zxH7n+2ms4uG8PrudTrzdR0gUkjaUGWnhUa3XLyqOYZr3GoYN7icOQj37kz3njW97GxbsuZ3L1BqZnF5DKI9HayuJI0PEPBumzme9noTTBhQJSA3EirEtSWKD2/ORdbKVyTRbJZNk/WAOykCC0lWkTbUUFG9VkBXkblNHzp/eijkBrSYLK5K1GY5GRgQGI6gjd5H//7V8xP7uINJKw0cDRsH5yDeXyDHfffy+Vasybbr2Z3/mtX6c1d4yta8aZK59kbHSYylKD7du3s7S0yKo1K3nq6ad4at9BLrn0BbzkhpsplxdotSOma2VG8g4rJoap1yucPnaMqN3glptuIo5jylOHMdqh2Yp47S1votYMuff7jzA8uZZN2y7iFTfexNzMaabLi2zfsplvfet2hobHqNRbXLX7am773n0US0NccskwTz61j6VqlfnZ02zYsIGF2Snuu+t7TK5aSb1WY3L1OoIgDeA2BiUsB+sCMgss+QEgfSYgZmz/WRDUCwKk0DX0ptFPouseldjE05gs+jyVhfqDMZRUvUFLqa+UqQE6EUiVmk/oswHSdfdpnHyJuF0DHeORsGZ0gKnDT1FfOE7YmCFuLlGvLnJ6psqAX8DXAZdf9UK+8Z07+einPseKsZX88rveiYmbjAw4oEPGhgY5XZ5B+Tlmy3NsuGQXx/c/zfTCArf+0ruZP16mHghmK21my1Ue2vMgAyrh2t27mC+Xuf+BhxkeHmVpqYbvFTh96kk++vHP8mu/8V8ol5e46657+MinP836XVfw4le+hk1rJhgZLLF1+8Xcfvu3GSgNMzQyxvFTZebmlzDGEIYh+eIA69esoVwus7i4wCte+lKe3vM4hw7u5Q/+y+/yK+99H/c/8ACvuelmK/5oSSeKQZE6NeQ52frZ8aXLZdFlhnxBT3Y9j3ZBgFTQDRXrRhfpTF406UrGGqmsFq/6wvUkmMzQn6Ryac85IKXI0j1kv/nJQNdR0A4ijI7Ji5DPf/wjjLhw7eW72LF2jIcfPE273qBSqVIYGqPRaCIdWL1uLfPVBWaWDJ/6+B+yed1KPFNB4UEnIWhqioUhcqU8hbWjVMvz1DuaG97wNo4fOMpiPeLe79/Hnqf3881vfZf1K0u84bU3kiuO4eQjDh2fZqBYoDq/iEhiHn7oW3h+kbUbN3H86HGuf9ELIJ/jT//n57jtjt9n49oVvP93fpOThw9y5dXX8eUvfoHRSo0o0Zw4cYLR0RXMzpZxXRfXkQwNDGCEYM/ePaxdv56jR0+QLwzwoT/7IFu3XcyRI0f4lV99H/VmiBKQYM0q3VQXpVLCkIX3nSO45xzUNPNG/WvZSYUQx4A6kACxMeZqIcQo8HlgI3AMuNUYU/nB1wHX6XmTumxZKgs21Rek0C94Z4ENXaFdiNT8YdIQNoNAZ6ylP4FOZkKqIWrWcHWThekDjOdC3LBNTsbUmw20P0DeyeH7OY7PlSmVilx+xS7uu+d7/NUn/ifvetc7ecEl29BhBVXShLU2CkErhqHRcYSMiYxhplLlkhtuYv9DT3Bqpsp//e9/yuN7jlAo5Xjh9dfy7je9lpe8+DqmZ6cwXoH1F+3i+hdcwaCrefS+O/npt76DxdAhSGIKAx5hu0p55gRbtm2n3DlKW7v81z/+c977y7/Ad753L6MrJllaWsT38wyNjTJfqzC5aoKFxSpDg6Ns2LCBx/c8yd3ff5Df/p33cegjH6darTA0Osb+Q3tZu24jP/+un+PTn/osUzOzGHqpL0hhXcSiz7BkzgboMspqT+mBVJ4/v/+XyLt/mTHmCmPM1en/vwPcbozZBtye/v8DmxACz1VZV1LbLkAJcJTtriOy971j4DoyfQXPlbiOwnVEdsxxHBzHxonaVxvArBxrWx0uKgZzsHD6IIOuRuiAeruFOzrJ4UpEbX6Rop8nDDsEnRo/9aabCdtLLJZrXHXZbkZGCxR96DQWcTxFoxMxNLoCg0TlctQ7LbbvvpqZg8d56LGDvOtXfpMjJ+dxBwuMrV5DPY6ozE9z8OB+KvUagRAcOnWSmcU52p0auRyEgSExilanTaO5xNFj+1gxMcwDD3yfThgxt9Si1tH8x//0+yxWG2zYsoU1a9ezsLjI+Pg4ed8jCtqMDA8RBG3Gx8cpDBTxci5f+urXGBoaYWBokFqthjEJs7MzIDRvf8fbGB4eXJa60x943m39JqZ+EeBc2vyzjYJ6LopD3Ax8On3/aeCWH/YFIQyOa3A9UI7G9SSuJ1EOCKkzYElJBjCZsnQpJUJ1UG6M4yU4rsZ3Da4yeI7Ek4K80eQN5Az4WpC3TBlfGHyZELo5hip72HP/XTx8ss7xcgWTK9FamGHzUJ66ErR1h+HSIrI+yPBQgeGJjfzWb/8+L3npNiJZJ5YaYo+gqhkaGCHSIS3HpeGWGJrczPHjU3zhti/xu3/wB0ys2wz+ADqRzE+VCRcWGR4Q3HffPTy+5zAPPXYQ1x+iPL3Irs2XMuSMIqVh6uATjLkCyPPIgSWePN1k5eRqVLBIGFRBxOzYsYOjx6eIIsX07CIbN29jvlLBzResXBhHFF0HHbRYMTSK0oKD+w5zyRW7aXdigtBmSHTadaRpkYRz/Pw7biFoLGGiCCUclPQxWkGiUFriamWDyLFewHP1pO9zIQQ8i2zRfy5IDfBNIcTDwubRA6w0xkwDpK8rfthFhGAZCLugdByJ48hsRXZ7N3r+h/XsPEcu60KCVCLripCJ8UGioINCsGP7LjZt2kSpNEAYBgwUiiRhRBwb3vtr7+Ho0WN89rN/w1VXX47v+8RhhDM8RKvTITdQpNlukh8bo1QaIu8XOLD3CH/3+X/grjvu4aItO2g22hgjWL9mHRMTE5SKJRJ3iKOnyuw/cIhHH32Y48eO4DgOs3NljFTkBgap1pvEGo4ePcqq1ZOcODnF7GKNWPkMDg8TxzFhHLNqcpLbvvQVdl5yKYePHmP1uvW4rp/GlbbI5Xwcx2FwaADXdRFCcPLkScIwxHGcLBHQcRx838d1XT7wgfczV57CmIRWq2EnX9gkyFgnZ83RmZQ1QWQ9NjbB8nzbPxekLzLGXAm8Bni3EOLHz/eLQoh3CiEeEkI8VKsuIRWW/SprkBcyda9JgxEaI7QNKhEaTYImyY5nCXJZiofspYFImZ3Xfx2kQSiQjiDvBkStRYZLOerVGnkvT6cTEkUBq9dNsG7NGsIgIGzAy152HSY2PPzwYTZsXIWUgnyxSGt+nuEV44hSAVXMg+sji0McP3Kahx/aw7e+eSdCFjh+bIpcrsjOHZdSyA/iewWMEfzjtx8gViXuvPMeDu19ist2buW6a64ijBIqjRYHjk9z0c6Lef/7349C8NADD4J0UPkhAnIYI6i32qxev4FYKo5OTfHRT36KkzNl9h89iefniXSC7/vMzs7ieQ7FYhHPdxFoFhYW6HQ6OI5DFEXdOcoUpCRssH/vHnxX4rquLWaR2pZDzs4pO7PrtCdaZ/182z9LcTLGTKWvZSHEF7A1oGaFEJPGmGkhxCRQfobvZsUhtm7fafrjR5ebNchSzM5ce9nKPaN6RleaN2Z5xM65mhAC34nQUYOw3WDDmm0MDw3RbrfZtG0NC/UyvpOjmC/wB//59zl06AnK0wusW5PHdWIcz4EowvM8ZM7F6ITc4BAYxZ6Hn+S2f/wa/vAkazbs4MDhI4xPrme+GTPh53FyHaqNqo1Gil38IObibVu54WXXMjFRYml+llarSTMIqdRbCCH4lV/6RT7+qb+mWBih1tboKKYThHQ6LVzX5Zvf+S4jw4MkYUDtZJ2RkQFWtwPCVSHDpUHCoA3tFsVigUq9wUChSBTG5PN5isUinU6HYrGYafFdSupIxcT4IF/68hf48ZfdSCKczIuHJPXW9c1vanPpulO1UFl6kJ3efwVKKoQoCiFK3ffAq4A9wG3A29PT3g784/ld0TxjP5cA3v+/lD3vUn+3Q6Qzf741OfW6DSNLcJXk0MH9uFIwOjrMcMo677jjTqZmpnn00UfZfdnlXH7ZC4jCRe656z5e/YqX48oOUb1OZX4eJ5+n3WohBgfpxDFRYvhvf/qXqNwwJxdrfOC//XeqYcITh45wdGoaXI+JNZPkSkViYvKu4vqrr+KGF1/L/NRxDu97iiSOGRgc4aWvuJGrrr6OmfICDz30CC+67hoaSwvMHD/CgAtFYsZHRvGUg3QU1VqDyMDIxDitMObk9CxHjp8iMgbXy+H7PkvVReIowJEQRxGdToeBgQEcx9YQ6HKjLlhrS/M8/fRTPPn4E5nNUxtBQkJilpcEyqhn37FuPlq3P5v2z2H3K4G7hRCPAw8AXzHGfB34I+CVQoiD2NKPf/RPufhyUD4TeO1n5zJ99FNljSQx4pxdI2m2NKvXbCRMNI1mjVanTmJiEgT79x1lYuUqLtq5g2YjZmrmEE8/uY/f/PX3MVc+hjs0SLFYxIQhvnSgUsPB4R+++GVOl5f47Be+TKXd4YprrqdcrTE4Pk4sDH7OZXrqFKPDJVxHUJ09zm3/+zN4jmDVqlXs2HU52y99AZt3XMnqzZfSMS67dl+HOzjBviOn2LnrMrZtWIdoVfDCgDjokHMddJwglCRKNFEc4/l5Wq0OGkWz3aHRbuE4kjgO6UaXaZ1QqVQolUr4vp8BytYRsCnafiHP/fffz823vB5HeeikVydAp8U7zgRmPyil0ShM1uWzCIL+J7N7Y8wR4PJzHF8AXvHsr3hGPGjfq3oGziD6znkmzwddX3/mkOr/PP0dNUgUe1x97bXMJcN0giajuXUEnZhmPeY1/+41rFm3mumZBRLdol5t8MQjj3DRjhLJdBlvbJhOvUbOdSDQTJ86yVdu+yqHjp1kdO1WvvXt79AOA4YGB4k6bXJS8sW/+1t+8e1vZu+eRwjrS7g+vPvn38n+/fsZnZzkw3/6VwTa4eLtl5H3CwgnZsO6dQwNrmN8S4mc77ArN8wrXvkqPvwXf8nhJUGUxBBHCEeS83O0Wh1c5eC5OWZm58jlXDasXoF0FGHTxo/qOIJE0263bfp4amrq9xBprWl12ghH0mh3CCOTpk9oW8LImF5qTf88dCOnAGG6ypUd9jNrev2gdkHuZIATAAAgAElEQVR4nGxbXjBgWRDzOVZd5to0YLpZjmlA9LLYRWMwxulzMy+34wFoU8DxSkxNzxEOOqxbNcjBgwc4vO8gvjfApq1bkK4EUWCxMkPO8RkeHKBWKTNSWkUYhQRBQFStURpdgYrhxLGTbNxyEfumF6nMzTFYKFKdX8RoxX96/+8xkM/xmU9+mKInec/Pvo0oqvLQow9xemaJ+2/7Fm//lV9nrtJmfq5OGGniTo3KkVnC8CRSR1y2cxt33PN9fuKGl/Cun/tZPvHFu5Cey4Gjh5kqz6GTbvEIlySKEJ5Hq9VhqVbFV5ooCpA4BEGAMQbf92m325my1NXwu+WDjJAMlkbw3BxhGCMdgZFWX0ckILyzxLJubr8QApl0Y37lss/OFxkXRJMGywZIUEIjSZBG2+oydL1DtvUS9axMKY2CRGBiMHEahJJGSRkBJAkmThC6r+KdFiQa4sSg9Ax6/SVMbt5O++QRmm0HIwfYvGM3F+/aztFDh6kvVNF5xSqGOdFuMVudZWxwnAMzZTzZZPHwU8ycOM7MVJm/+cZ3WJRFHt5/HGKXXKzxpMeOa67mE1/8AodPzmKaHV562Wbe/+430Fl8kOlqxBPHa6zffQOvuvWdlEbXERnBtu0XcdGuiykOTrByzQYGR8cx+QG+99hebnrHr/PdQw0erOTZtHk15blpwiihMDCKmx/GuEVi18cfGsHgMrfU4HR5iThSyMhhbGCUvJ8jkQZDlJqWJFFoiCMBxsnqZjl4tBt1Lr/yErTsgIoRxEgDjlFpMJDJHDCeELiALwQe4CmFK+Wyfr7tAqKkZNTwB5wBnFk7U9NNduq30dluNagkzbfRgqzanUnTJACUI2m0Q9qdkCiKaNVrjK1Yy8LiPBMTKymVSuT8PIv1OmvWrMEBhFR0Oh0GB1dDkDC3sMRCpUNl/xRPHzxOs5Owa9el/OTr30QhanDj627hgx/5MP/f5z5PtFjlC/d9nd/7jZ+jPH0ULz/K0nSDThjTandYsXoSKSWbNqwj7w1w4sRpFhYW8HyHsbExjDBEUcTnPvc56rUm23Zs59BcBalsRL9M2qAkBTcHQLNWJe8XSJKEVqvFYlUwmi9SGCgSJTGe5xKGCUq5gMD3fTqdDoaEJLYy6fDgCPPVJvV6nVwuB8IBIywhEaBT0Kl0jlQfFQUQfUFBz+SJeqZ2gYBUpAHKpDFcNtjEhuWJTN6xp+o+mTKVg3R//OjycjHGmLTcI9jiEFYbtVFTdsACJ0fU0Vx8+VWoOKRSqTCZW0+z06Qwto35hXnmFxZZvfVygiBAKBgaG2dxaYaLLr6K+QNPc/DwSRJV5Pbv7+HwYodOpCjPzPGFv/scV1+9k9Of/BT1xSat+UUmS/CHf/af+fZXb2NsdBThrmKxeZLJDRtZuWYtkTBcculOpqenuf+++6kt1dl/YC/tTp3rrruWU0+cYv/+/VQqS3hujk996lMMOCEjo+PMVZsoKQnDACklvucQK0MQBKAiIm1odzq0hCQIOiRJhNYxWntI6ZDEaSB5Gu2UJAlCGGr1Bm94wxvxXQ+JQ5LYzFyV1iJwlMyCzIFl7wHEGQWEn027MECaxofa9KaukTMt5mDOzNHuz5dJA0rSogak8mgWmS+71fakpaaYtAqzITYGkxZ9EJFHYnzWr9nExNRJyuUyhw4+jZEex05P4WKYGBlmYWGOa3btJFf0uPehR3jxzhVAQnW+BhrmK/O8+CU/zvRX72VyIoevBJXpYzx9UFPMr4DQQbab1DuzLJYPgoIVazbw9W/cz0IYEoYJP7FlE6XBQW666UaarTomMkxMrMQgGBkZ5Lt33M5377gDKSWl0hCdoEVpaIR9hw6x2ThMrlnLkSNHcJRAJyEmisk5ig6aboBuGEe0w4BOFLJp80bmH30Cx7Eypes6BGE7JQbWVOd5Hjr2ecNP3kql3kZHEa5yrZlKSFtJOC3u0cWhNL33QFrtpTvd56h/+gPaBSKTdmM7JRiJTA3FvWPKUtQ00FlrmYJXYLTqvTciO09rLFUw0tb+NLZIbZjEhGmh2iiOCaOEVquDUyix0IrYe+wkys/RajU4ceIER46e4On9hzhw8CBxFDAzM0O1GbLpol1s2roV3awyOz1L0Gxy9WXbqc2d5NTBp9m+ZjWiWeFFl27myKEDTE6Msmp4kKRV4T+89ScJ2jVWr13DE08fph67HDh6gv/rAx9gYXGJY8ePMDY+gqOsbddxJIVCnrHxER566CGCoEWYltjpeoSGRicIwph6vU7YaWN0jKcknuugpEAKGxHW9c7FcUwcdNi8cQOeA0EnyoLEuwHnUkqb62QE23fuYmmpiiMkOc/HdRRKphm50ta0snWtrImpX2cwJsFW2rIdofsS/X54u0BAmkbPa4PQtnqHiY3tkS2pmMRgLSwJOjHopAfGOEp6PdZE6WvWjc6GKAsVy35Zk/cFsU5YChNe9bo3caw8z6rVa6jVlgg6HeYXqjQaLcZGhhkdHSXU8PXb76A4MooUmkcfe5rdu3dTKjpMDCjG84LqqSNsXb2CN7/+JrZOruWRe+5kwI944ZU72LR+PbMziwwOrSQ3MESQxISB5q//+jO0my3+x0c+SjGfw3c9lCM4ceIEK1dN8MgjD5HP+yBsRT/XdWm1WlYzD0KWanXiOGbT5g34jiKKIqRyyOULKKMZKBQoFgrkcjlqtRpKSnwlCdswPDJIs1lHSgjDDqVSCUsgHOII/vD//mN8P2+B60hbwkcYm+J9Rt3VbGRFr3c/7yVR/ivFk/6LNWPQiUmzO7uus4Rudqg2/YXMoGfIT2vHZ897jhI7gmzVaptehjZpPVAMUijiVgWtXJSbY7rR4rJrXsyT37+LaqVCtRZQHJ1kfn6eKAiICHDzHtt2XgxDg3SmT3DPYwd48394O8VcmzBKGMkp5man2b55LWMTo3Tml7j+qsu49XWv4Pihp9nz1D527nohB0/OMzVbxi0qrrzySoZKg3zvjjtwHcVjjz2O4zhI4bF27Wo6nRbz82WUUhQKOUBSrVZJEs309DS5XA4HTdBuoUPB4KANu4uNJooMnpCIJEYaTSFfIPZ8Oq0mtcUFLtu1jiNzEUkS0em0iKKAxcVFotAwMDDEn3zwQ1RrLeLEEIZBGvzjICAtBS9tqjnLK8L041Cc4fb+kWP3BpZ5J6yZCJLYvo8jTRyl72Od1QG1r/2eDfpqhOpeFbc0KAWsmcSI5WDOuZqc7xAYgfYH2Hn5C8kVBykNDBF2AhYqFar1JvPzcwStNrl8gXq7Qzg/T21pkccPTuEUhmm0O+zaeREXbd2CIySVeoPbvvFNisLhRVddQbs1w+q1I3SChDDyaAeGqekZ/BzkfJ/pU6e58ZU3cP/372FooATAqlWr+Iu//DD79++1IXRBq6+2vjXI+75Pd3eLUqlksxJMt3y7wHF9fM+hmM+Tz+UoFgq2krWwaHrhlVdiiFCOsN4jEjzPI5fLs/2inQwNjVCtVlHKJe/n8FwX3bf5hC3DaeX9OBWzku5cGNvjOF5GQZ+Na/SCACnYm44STawViXEIE0lkJKFWhAhCIEwEQaKJYltjPjmjIFaWXaokRgq0MMSiPxc8RsgEpQzST5B+gvBiIi9HIgyeikHHNI3ide94Nx0vz7qt6yn5IZ5xWTp5H0tihNe+9GZ++3d/DpkbJlhoMWYM+DmGChPo/EomijUmh4vkaLBlzUau+bHdNiTPHyNqe1x29fU0jWa+3uDHXv5KhocnKRYGmVw7SWxi3vCGN7NychM3v/ZNfP7zf88f/9H/g+f4REHM0OAYgwMj5Lw8rusipcBV4KSUqrywhHAGEE6BFeMrcXVCUSbkcgVUEjLsaEou5As+zSAkThKiJKS51CCJbHn2ODFo6XLJ5S/kPe/5bYKOh3RcgiimE2vaoSHQkiARhBEEoSHSAUEcECWxjY4ymlhHaBMS6aAXfZbGTTjPQtG/MECamjpIKy9bGTTOatonSYxJdOZZ6grrvcinXgCJMZokia2pKbEszNbD65Xrlkpku4tI2TOdqDSaKuiELFSqvOfX3kdhcJiR0RUUSwO0OyEf+9jH+Pzf/w0kMZ12nVqtxtDwMO1Oh3a7TaE0wPr161mYm8dTDvfecxdbt25l27Yt+Pkco+NjeJ5HGEd0opBqo8kTTzzB3r1PMTQ0xMMPP8zC4jy33HILp0+f5qabbuTQoQPEcUyxWKTdbmOMIZezgSKO49Bo2PjOLgsNw5A4Dq2nKF3Avu/j+z75vAV3N5AkDENarRauY3CVxHNzlAZGePnLXsmb3/LT1FsN2mHbKppJr8dJkvWkW+2antnK7h1kQCd4UuC5Et9TFPMeAwWffM49b3hcEDKpHcae8C3TzDlh0pWXJKnl1KDo24YFkfqB7f/dxDAp+9yeUmc+++6vdUUlZRNzrIykTSpHSUrDIxAEBO06r/6Jn+TrX/4SOQwbtoxzx3cfRZBgajV8V1Kv11mzfi0r1qzClNtoIdiyZQsDhSeIwoAgCtm9+1LmK/PMl8sgJZ0EqvU6jueyd98+iqUBSrkhHFfx5a/8I1JK7r33bjZuXM/u3Zdz9913UywWkVLSaTXxfdm3jU6MECodDet3D6MOrpNDOSJNnXHsTip91ZwdJ3VPKuu9Gx8ZoBNZv0gUwutf/xa0kDTqLbQJ0/gHk8mc9I2mNW0bpOjuP2HAJDjKkPNc/JwN9evfbE08QwXDc7ULgpIK0RtMV6qMMtqEOoPngKsMrhK2HHhapUSqbrXmGCEsG1fKYHPuTWrY1/bcrMvMdZdF+Utpd8tIXzESLV2kO4DxSvzCL76X1RvWsWrtRtavX8/qQZfqfJlGbYGn9x1kz/69NFpNas0GnSAkn89jkoSrLr+M1atWUhzIURoscOkVl5Ir5JmaLeMXijTbbZrNJgkGpQTf/vY3yed9Vq9eRalUZH6hzN333MnQcAnlCDqdDvl8nh07dmRRSo7j4HkeQMo1Ujem45AkCYODg3Q6HXzfZ2hoCM/zcFyV1fbvtm3b1qFEghBW3IoSyVK1QahjcgM5G4FvNBFdVp4QmoQIe1wLxyqlwpqucq7DYDHHQN6l5HsU8w7FnKLgSwq+xPd/xBQnsNqfEHayXHlGCok8MwFP4CiDciXSMXi+i+MKlAOOK3A9heOC46bR/rK3WVhWGUWazIziKYlyBEoIHCUyNqmlQnl5Tp0uI31JaWicW9/0Rj79iT/DiWKefPxBjk3NsPWiLTQ7TcIwxHXdlLW6PPLoA6wYH6aYd1lanOfgwQPEOqHRbLJUbzA/v2g3axAOURRQqy3x6le/mvLcDNddfw2+77Ny5Uqq1QpBEBAnNlvgwIEDaB3j59zMpNP1EEkJURRlaSGe76QeJb0syimKoow4uK5Lwc/hSEWnE6I1jK+YIIo1Xj5HI2hncqbWmkgn1qyXsnqEjcDqbvqmlMBxJZ6S5FzXJkRKgassgUAn5wwaeqZ2QYBUCHBdx2aDurZ7jsBxjU3MU1ggKQtiqbSlosogVV+Jx2cIbu5RZgtOqewWghIbEIFIYx1FghIxjtR2EaQZpZ5bRChNrdHhlp/5aV5w7SUszEwjleB0eYlabSlLV0mShNWrVxPHITt2bGdwqMixQweIO03q1QqVSoXYGE6ePEmr1cKRiiSMWFpaYtu2bXz961/nVa+8kW9+85tMTNi9YaV0luUeTU5OZrvrOa6tgBfHYV/AMkRxgNbamrGkJJ/3cRyZyebGJORyHkoJoijA80u0gxghDHEc8id/8kFyOS+1P/csKP37mSZ91pisbpe06T+uUtnWOEpYAtCf4tPdSeZ82oUBUkiBh01ldnrgdBUpZZS4ymqySsl0T6XefkY/yO7WBWdX2ZJpLVRHSltCRhgQSUpdNZ6yv+07BtcRFAoDhFGTxx9/HHwHdAelLcVIRI51a1czMlTCUw5KKaamphhbMcGNN72an/nZt7J+7SpWrhjDkYJqZYn6UpVirkClUqXdbCOF3YR3ZqbM6Og4+/bt4/rrXkwYWMWxUCgwPDyI1ppcLsfs7PSyXK7MhpxtzSjS3fkscHO5XAYQC3SdiQTdgJyt2y7ByxWRjmJgKMf8whTtTotWq0MU9LxDsk+UtLVaUxmzG71m7FZDy8yCCWnx4Z7XMP6XlEmFEJ8UQpSFEHv6jo0KIb4lhDiYvo6kx4UQ4s+FEIeEEE8IIa487ztBp3GJBpkm4Nme2LrumQGfPu3eZAEnZ0bkL7/ymQVgdd+D96iwFNoOtNAo4jT3X+M5Lp4v+dCHPgLNBkRNqpUl7rjrTrTr4SmH6dNTtrKHlARBwK233kq5PMPxU8f4xpe/zMnjJxgoFBgdHcV1XRYXF8l7abRRYnd2bjQaDA4OUqlUmZ2d49SpU2AkSrrMzMzgODKTS7vyZ1c08TzPJtCJnr251WphjMnk0u6xIAgIQ2tjjaKIdrvN0NBKhobH8X2Xen2JZquG6yocIXGFtcN2rSCOkJniY4w18QmTgE79eul2R6TU08qz1qYdx5ogjAk60Xkj43wo6aeAG8849kwFIF4DbEv7O4GPnNddCED0MgojY1ceWkAs0SZCC2tk1ia227B0P08UsYmJTdxzfQq9LOdb2EDTXhcGLUw35xSZGNDC5uwIiXYUKGXlRQV4J9i29ceYrc4TRFNQmiQyiqHCSnylONCuMehC6ORohYrH982zdu0gm3ZdzWMPPoTvKgYcePrB+6jNTlEqDrJicgOr1q5n5cqVuJ5ksOCS8yRL1XmipIMRMZNrVhHFAc161d5bGtvZarXQ2nqXkihEpNRLGInEukODIMDL+dSbTYIoJF/wieMY4fgEsaDVToh1qgM4AnKK9/7Gb7LUDJB+id/6jx+g1m7SSTq04hqREETCEGOIjEYrMMJghEGjibW1aydCEhlDYDRtDe1E0QgltU5MpRmw1AqptSMaQfLDUJG1H2qCMsbcKYTYeMbhm4GXpu8/DdwB/HZ6/H8ZS66+L4QY7maO/pAfSXNlrHbYlb265gzTRy01IHRfOF43DqX7Hmyh3e7msMaWlOxvZ3k7kl7RAi2seUQCTlpUv95oAIqg3cIV0JiZZmh4lGMnTxCGitn5KlEnQghDvVbhom2bOHb0IFvHVlAoFLjxJ36Ce++6m8VKhd07Lufxw7NUAsnc3By+b6mq8Kw/PY5jXNdlenra7tGUZnHWWk2gVxHb8zwajQae5y3T1G0at5/Wa/JtflI+T7PZJJdzcdKKztVqC2HAdV2GR4YRIkdiHP7fD34IL19kdn4Jx/EzBSw23dLwfXXx7WiCSPcyMAkmgUQYIqxJysR2/6n+6ifP1nf/T5VJn6kAxBrgZN95p9JjP7BpYwijiCCOCKIwq4YRG516RKy7LU7doLG2PTH2WJyYzAPVNS5n+5Qabfc/6utxopd3bTfeDXVqoNYJMYZQGBIl8AtFdl91hWX/RZeBFWMsVpe46uoXWjdrpFgoVxgdGcIkbVwnZuXEMGHQJuflePChR7jsiivxinnKixVGx8eYW1zgou3bGV8xwcWXXMLo6ChBEJDL5di1axfXXXddGjrnZrnw/cEZ3Rz5LquHXj6SECIDrZSSKIoIwzArNOb7PqVSDs/ziOOYxYUFhocnqdcjWi1NFEvy+QF8P28Dx5G4QuAKgSfBkwJX2FdPCnwl8Zw0ElCmSpQwqbs0sveSinDKscqeehYup39pY/65fvmcS0bYiifvBBifWEGQJFmUUrf1KOlyedOKO33RN6JXlKwbZKJTrf2Zb6vvBk03HNVgpK3Tr4zNHNcG4k6bzZs24OoZqqeOMzS8huGRMVYFkyhhiAPI54tUK4vMz5fZumUt3/7at9GVDof3PMz1r7qBx556imuvfzFP7DvGoelZNmzciPLzHDp8gHwaCV+r1ZgcLPHII48gpWRgYIAwDKkvVTPqH8dxphk7jpOZvbqjbMHZszsnSUKUbowhpWRmpsyaybUMDBQsSKOA4ZEirl9k2B+g1ekAMDw8SBxHxEloKa7oVZKxFLHf4ydI0lqyKq104EgruypHZIsnnfd/tSioZyoAcQpY13feWmDqXBfoLw6xaetFJo5jaxSmxxaUkEiDpat9GYymf7CUtIK7EHbbEiRaxxZs6Sa0SZ9L9NxWALv/kEhzqVqtFjqKybkeUkre+trXY1odMB2Gii6t8gwjY6OcnlHoOKJer7Nhx06mjzzO3Nws47KE57uEqX12dm6ehbky27dfTLE4gON1mJubY6FaRynF3r17mZlf5Prrr2f/oYOABePS0hJJHNtEOtlLuYiiKHNvdhUmR9rEDasQKfK5PIAt9pD3EUgczyc/UMxiUDudFiMjIwhtGF85QqVapVAaSp3IAZ4HeWGzQn1y9KePWwLRY+OJ07OaCEPqNBGZXdpJa8haW243YfL82j8VpN0CEH/E8gIQtwHvEUL8LXANUP2h8ihklYNtrGd3SxawwXVkrsvegxl0ultxd5MrI0WmcUoU3ZKQQqSVTbOUknPdgEAJy1bjJKSUK4CTEIUdLt66jZCIgtDQqoFKeOrxR7lo1zXU600mRkb5pV9+PUlzienpaaq1FtWcQ6MRsu/QXjxtUNLl2LETrF69nna7TaPRoBoI6vU69913HxvWr2H9+vUUi0VmZmZYNTlJu91mbGyMRr1OK2n0UoPT54jjOHsvpSRJEqTj4rouURQQhook1/0/gnS/z24MqpSSQj5PFLTxPR/HNeQLDonROEJY17RIkCl1RPe5NLO4CYcu54rSXa675ziil+PUzbg4sx7C+bYfClIhxOewStK4EOIU8HtYcP6dEOLngBPAG9PTvwrcBBwCWsA7zucmLB7t/uiApWjdpDxtrHfC9Ko02/wkkaWMSGUHwiAzFi+MrQGFMWkMwPJEsGXPKBWuq2wekEn+f+rePEiy5K7z/Lj7u+PO+6i7+q5Wq2+pJUBIYhCHUA+HBBLnAmIXmBlmbWYHMf+Ardmu7Q42tsZgoDHE7M7KmEUCNMAgBJKABQm1uqVWq9VnVVe36q7KozIyM853ufv+4RGRkdXdUrWGHSt5mltEvIzIjIj3e+4///n3wGpNNYhoVkPuOHoTHiDJwRSY9cuknS4S5YTMsoyf/yc/w/pLj/MXn/xLfuC9P8POS89TaImUima9SZ7nWCv41Cc/zYm738jczCynnniWpFLloTe8kVuOHWFoJU8/+wxKKeI45ty5c+R5Tr/XI1AeQu0ntk2X1FwR305yTvAnpSlrDJ50ZMRBf0hR9KnHNer1OnmeMzfbwJQ5piyIAo/SMMl1JRopLApBafZ27cZu2O5mbO8+Ts+usUy3ZjSMTMkg8dqgetezun/vq/zqZQIQo1X9L173fx+16ZFUwmSFPX48bmrEs9ej10y4pcY6rMkIR2mtnUz3YPCmdjdekakoJEWhMVpjixyT51ghGexmVDyPYiSAgDRcuXgO35MkUUwSxzTrDaLFBv4lxaOPfREZL/Pd99/L5x99ghMPvY0HX3+Ep186Q6PRQCIp84LVpQPcf09Ia3YOay0Xz59hrb3L5uYmhw4d4ty5c25VHobkWeYsxL39n2F62i1GkozjRZPneejSLZQ86ThheWlI84wyK7CRJY4ilHLFfd9zwGVhXUDa0uJ7HgrlaCcWrD++QKZGQrl3ociRqwtiFJRyPIICIweT6e9dvZrixyu0GwMFZe1ICcNdXdLsR25fm2irEclLWOf9JDy38rFGjNT4cIBe5a56j7Ee+biM5RZjjPK8vNPHDyJK7XHizrs5/9UXuenQCnefOA62ILASbQakRYTcvsLC0u0YD4wW3PngnbCzxcbGgPmFI3Q2r9BYPcB7fvb9KM/j0m6HrVSxUyYkc/M8f26DVRtz+dI5Lq9fpt5oMdSazbV1+t0eRw4dphimBFLRHw7dyt5alHToMCHURFPAaD3COEgQEiXcVqVUPkEYo61EWUgL7WaKQoLx8aQm9FLisEpumiwdvJNQudFW+YwCSoNw/w+cliu4OnZpXdlJ44Kx1AYhg/3Tudm7L4SZWsSy51d6ne2GCFJgyk0EYC+x3puir/1gAiEkwopJUAspESPomBRyxF4U+Iy2/8SIMToq+BvrvsxKo44pDEpZBjtXueu2W5ht1ijyHA+DsCXK9/GjmJ2dHY7deQA/CLjllltYW1sj37qKUoJDhw7xvh9+H7udHl984iscOnKYs+cv8oVnTrK8tMpur02lUiPLC5rNJidffIk0K3jsi19gefUQ73znO3n62WccN8l3U65AjVbI46lcYsc0DaMxxpHmxlO9HKmPBH7ogCRjbK4RBP6IKy8lURQhlY8KfL79bW/HWjfNa1viB/6I9u1cR9z7GP1P63b/x8etGGGA2W8Tfi0YXU5RzeX1xydwAwXpdABee5WNpzc5LiUJRjsso2lFj/T1jUv4LaOV5gj4OE7ojVBgLUoYRkRo9798xSDrUfV9dNrhqS+e5p6772K+dQt5lqFs4Xa5lCSpNwirFYyEKIk5ceJ22lsbNOo1djvbDLKUrzz7LE888xznNnd4/X338ewff5LCBtTrTQaFk+KxDHnooTfT6/dZXl1ho73DxcuX2NzcBOWc+oR0WABhDGrE3BSMmbOGssz3gB0YtAblOQHhsWNgWZZYYyi020qOlGJ2do72xllm52M8PJJKnRxJaTRWSvpZvkeeGyVcxtgJzWes2qy1s3swxjjO3jWBOa7SCCFgNN2PgeXfdDI71gJagBYIIyf3J8csewEKE2q+EGLE71ZgPTcNagCJNXLEKrWOZVpqx5kqDUVu0IVBl84zszfoU00iPFuQ7l7lrW+6l5uPHqS/u4P0A6yQGKkIKxUWVlZhtJCJ61X6gx6Pf+ERKrHPiy++yOEjx3jx3EW2hzmf/Mzn+Z//zb/jcrvL1W6KDCvcfuc9eFFMY2aWIAx5+umnHZDR4wcAACAASURBVMYz9HjksUdZv7rJ/NyiW2V7Ab4f4nkBSob4XkwQRE61OQhcfRTnJiiEQGAwupggpKy1IzqIo9yM0UvSd8FvhWR+aZXPPPKY2+WTcrLrZ3Eku8IaCmvIMeRWk2HIjXYMV6MdhE9YSlvs61mZkuuMwuQUJp+IUJS2xNgSba5/7/7GGEmna6DW7rvKxqh5YIK4wYwMbq2j11lfjjRKpeOWWzOqeY4K4NZO8l0rGC0wmDhgeBI67Tbveec7EGmXahyDzQl8SVkMERZCP6Tfa1OZmaEoNIO8S7q1zh133MJXnnwKKSw6z6k26hileOn8JXoF9NOCIK6RlpZzl9bI8pJf/lf/il//9f+dw0ePcOTYMc5dvMhXz58jDN025vb2Nr4KRoh6H+vZkZyNR6s5Q57n5HkGYUSWDxkO+0gsWgg835/snlgkpR1vI8tRgCqiEea12WzSaM2gheSpZ5/j/vvvRpfaLcb0iP80JjOO/uYYM2pdfjZRg7F2L+hcjXu8SB0t5pQjPUrGqds3mY+TxdGOhRCjqtP+DzAeQ8ejqRUuRxqrOJcmw452VNwIYvZpD5np9MEyQuqAMK6kUg98bnvwfqzRJHEMIx8pTznhNBW2MMUuQZTQ2+5SXW4QpD5+rcb6pYs8/I/fSaUSc/c9d/HCCyfp9/sgnFNIpi3kJV4QsbSyTJ5mvPjSGaK4wvmLl1laWmK3P3BvzWqyLAcNUZgQ+BFBELr3XTgGp2cVcVIn91LKsnD2QaVhUPRBjqb50belFCMeU0EYRXgSsAXtrU2SOCSKIsdvUg3soMeTTz7JbbffTFlkTpVPgM9ol2g0nY+ZSSNYw2jtIJByj7M0XeqbzkOn748pQtfTboggFVgHOpzaZpte3XsTztL4+cAUdC/0HH/Gm/J/mtRcxTVaUhhATXZFhASRpdx69DBgKQZ9hNBIabBFitEZkipSKYrUEEcVkB4YQRJHnN7cQAYxn/70X/Mt3/ImPvCBDzB/6GaHzo8teeryxsMHVxn0+iwvLPKpT32Ktc2r9IcDzpw7zz333cdXvvJlssGQMIhACipxlcgfAzwUVunRVO9TrVYZDvukWR9hNDovSEv3nRQjcI4YLZy0YTTypni1Oqszc+SDLo04JhsOkGmKiEt2d9cosjrJPScYDjPC0MPqva1MLctRqcl9iw7Hunc29q3eX6EercaW2Wa8tX39CiY3RpBKSRSH+xLq6WB13JvRB7dMcq5pBbfx9pscLYjG9TxhQV+TeftyryAOcPy2w5gsQyqPwgpKYwiFBpPi2aGTs5HCaSIB5DlSJiB9apWEc+fO8K3f+q187I8/ThiGnD97llLnZMMBWEUcetx/7z2cP3OWzc0ter0el65cZn5hiVqjxRce/xLb29tIIcjTjJXFAyjpk0QJcVwZ6VU5yket2sDzJbU4YjAI6XkKW+R0886oaG7w/HA0O4nRit8HnYLWYA2VJKLVaNDudhDVlHx3F9/3GQ77PPPUV3j9XSco89TVmsf5/zVbmdaafSLGY7v3awN0grfQ+8Hp6pttJPWkYK4iRwE5RVMe7RQpb09WcBK841qpEFhTTlDq03iWyXQvcHLYFjxczuupgM5giPQ8Fo4cw6DJ0g6hpxjsDgiTECsUMg6h+xzUWmyzxEx1ictPPMbK6x5kV8zQWF6mfe7v0Ttz3H3XPVxe3+HRRx9FdvqsNOc42y7YyuHYbXdg85Tu1jraExw9dJRms86jjz6C70m28z5zUY2GqjIXN/CihDCpo3wfT/qotEe71yOuVzFZgR4OqCiPoTX4SlANq1zdXCNKQkphMX5IUZbEoSUdDPGVoJ4IktBgrCBurrJ+/hSqPiCWuwTxDGvbA2S1y13SIxQZthxCmJAT4Jfs7TQJgRl7tE6C1Oz7zqdOgrudWszBaxPRvSGCVElBPXGACDVSygP2BeP4sZz6YvZGU7Nv5J1uQoz29a1GGfBGgV0ay+xci6M334J2+ywoFEr6VCo1ijxF+Yoiy1x5p9/BbyySD1KsgF6vR+PQYbrbEYuL86ytX+CW2+/j2VPL3HL8PfztZx/h8ecvsjBTY30348UXTtNoNHn93ffy9LPPIbyQ9m6bu++/m0c++1nqQYJIC47ddIB6UiOq1IlrdQaDFKshmV3AT2qgPAqhUTIEqYniOmKQcWBhjjfcez+f/ptP4wc+uZWj/X5BHIbM1utUAkm9XmW+1aTX63H48GGS1gzD3OXvSRSQDQecOXOGm5ebhGFMZgSekpPZa9ymZzzYX32ZPj55vvD2BelraTdOkMbhVHI9PZWYffW2fQn49Kgr9ptcvewLtQ5RpUaAkxIohYAgIBumeGq00PI8BjtdlIA8L6nNNyjTXQoNpF1KBOfOneNND3w7WbdDrVZnxzN0ulvstC/xru95C7/5m7/FT//Euzn42S/xZ3/zCMM45sH77+VX//W/5off80P4UczWzjYbm2tcunIJLwwQ7R733Xk3x+YPMNto0h+kCCwVpdCmdOK4nk+702F5YZHebsdth0YVNnd73Hr4dcwvVtHZX6BVhogUQeCj85w4qnPk4ApZf5datUq91WS3M0CEVQcLUZJ+v4uQMYPOLqdPvcAdh74NXxpXWZHqVfGfk++bYF8AXrs3Px55x6/5pttxkkBF2cl9h8Cxo4D09heFJ6+ZXkHafV/A9PNcnmpgVPxHOtcR6XvUag20zggDH6WgzAvKfkq1FrPTbhNXQpAeXqDQpYK0TVBvsbS6AlmGHG0ORJUqtWqVRhwiy4J3veMfcfe9d7O4tEKv3+EPPvksD3/vd/Gh/+vD/NNf+iUe/r7vZWtnkxdePEmSJGzutjH9gh99z/v4x9/xnXiz89DvQp6j+wNUtc7Fy+v8x9//T/S3hsSmxAC5VGynfQLhMxPXCYWgFkekwqCFw4GWxZDVlSMok1OJQnxfORMH5eOFEYNhTlJvMehvU23E5Jlmc/0qUsZkaZdkROIrp7Yyr91ZAjByP9fsZedYygkE7bWOpjdGkApBMgWgcCno3kKJqfzlZQrCjh/Cfmz1/i9BTfZY3WJiLJ3dXF4CIdBFF4vB6B5CwKDfp7kyh00HmHyIVBF5rkm8HLVyjPjKZfA9fKctQxjPEgQ9TKaptSJuuel2+t0hrXqD+0/cwmcfOYUwIe/5kR9hp5/yiT//Y2ZnWywtLaECn/WtbQSS7/ye78XzAujtkPV7hIFPkfcROykVk/HT736Yaq3ORz/6hzy3dolmrY7EI00CJBk608y3Gnx16yI6D1EKaoliab7OcHedpeUFFhcXWVvfBE8SeD7dTo9eWpDEkkF3B6V8Lly4jIqrYCBLB1idI6JXHinHx8ZWodMBvG9mM6+Ss15HuyGCVAjw1bXTvAOQOL7zNR9saioZg6Kn27VX6v4yqUQI5WglaUYpFaGnKfMeRe548H4Qgi7Y7XaQvqAeRURJiBpcoSwN1eYsRX+IQRBGPiqqsrx8kOee+gqvv+temosHefLZ51laXWKuXuN9D7+DD33kTyiKggceeghjc86ffo6NtXXCOOFyY5tB1kWEPoNhSlKNMJkk1xklpZtdigFmOMAqy3vf9V1sf8ubOXfpMp/83N+zcuet/MIv/Pe0bjrIb8z8NitHV6gtzPPcc89w4OASgZdTeB5JktDrDRBCUa032bh6FayH70dOqG23h1I+YZzwxNPPc2RlmaqSREFAqgGm0yk1+UZHZ2JyLsfA5unHr4g+u852QwQpMNqDFiPY3h6JDmFeRkCZ/qjmlT73NV+G25eaKkxJwfzsAtILJrhU61AThEGAtgHrF9dZ37zK0ZuOknU6ZHEC/S55PENYq6HCAE+XUObIMKQwBSvL81y9usnpi+uIuMbSvfeQhIa1i39FojRB6HP0+M00qiGPxx4Yw9r6Np/93Je5+abjVOo1cmMc5tBX9HsDkjgZlcd8WrMzbGxsUAkiKAtWlxf5mZ/8CY7ceTv4BmxJNYj4zu94mD/6848z11qgnsS06hU8JJWkxuW1K7Rm5vA8j2oSk5YC31f0ex0oM/pZl5mVY1y+us0tt91G2W+jbYkR8ej7u2YAGO9ATXsZiL0cdHLMOJjfNxKoN8TePewpZGi7R/WwI2ziND0Z2LOttvtd2Kb1Tad7afSUCpxhmBUEzdZohJWgPXw/RtkAZIhK6iwevJnB0FJrrhC2FomiJv7cPCJICGYX6KdDSp2DNcQzdar1GM8TPPX04xw+doQvfuVL0NtmmPe567ZjHFpZdFhXAY16i7d9+1v5zre/gxMnXofnhawsLiGrFbIsIx0M8PyA1swMYbWOH0aEtRaF8WjOLZLUG8zOLzC/uMzcwhLg0elsceHkC3h+lSCYYbZ1EE8kJEGVYphSb7bIihxtDVYKR8wrSwJPIo279ZRkptlAKcVur8/Fjavk1u3Vl8ZQGoO2dnK/0HvHjaPdv6yP8RTG2Jf16203zkg6vkLt9NU6QtKMlJpfKeF24Fu1//Er/PXSWhAehZH0i4xVJRE6IwwDTJ5jjEWFFbSRyDSn1+/QH/YY9PsEsUWmu+hCk4hdCI+zufUpjh0z2KsNBjsDapUFekmPA6urPPXIp/n+tz6E3trhageGZoNDhw5BrqjHUEYxUes4B/uCN337W6ktGv7ww3/Lu3/gh/jQv//3hFFE2ung+x6dXpu4WgOGhF5CWZZ4QQCBB6FHMj8DvqKer7Jy5zxEDdbTHnGjhif7NJoVer0tDszUef7USY4cvdmVkzxFEHt0B0OyvMQP6kTNCkY4DtX2pTVeEM+y+Ja76dscVUzx5EfK27BHKSlFsW+UtO5k7J2BMVprjK56DYunb1TB5NeEEJeEEE+O+vdM/e5XhFMwOSWEeMd1vQu7tw883c1IjnGsFmwQ+27H968dSa/tpQWj7WgkmCqFSAFmr8Q1ETZTitrsLG9729t47LHH8GSM1gLVnGH7ahu05plnnnGUl5FOU5ZlE/pxpVLBV4rhsE+SJNx///3Mzc1htSHLNcP+gDQtWFlZ4f3vfz9ffekMvu8TRSHNpTk0lrTIIXRop9IYhKfIi4JavU4URRNqsslyQHDqmWeYbTbxAo9Ca1ZXVx2edKS8NwbujA0h0jQlL5ySiSk1VjtCYavRnLBRtTUjJe39GNFruUrXw1t6pedfb/tGFUwA/g9r7d2j/gkAIcQdwI8AJ0av+W2xl2G/arMwmY6LkStIUZaTx7kxZFqTaU1uDGlZTh6npVMf/lo9yzVpqckLS1aUWKFASKT0HbvSTlUPhALfx+YpVy5fZHF+nsHQEiYzbF9s05pbhrTH8UOHGe7mIGMQAj+JkKFPvdGgPxjwzDNP0e/1UFqzvnmVwJcICmxRkiRVTj5/igvnL/Hxj3+C82cvUalEdAYd3vLmN3Pl6hpxrQKBIlpcIJ6dwWAJk5hclxBHjo1ZqyGrVZ764uO84/u+l36WUm82KHXB4uLCxAIcoN3eJgiiSXo0HGQw4kUhDEpCvVKl2+0yPz9PaQzDYZ/nTj5PXmj2+4e4/jLDDLunC/BKffp3/6By5NbazwDt6/x7DwMfsdZm1tozOELeg1//f0BuBGlpSUtLpnnZ/elj1/bh1+mphqxkFLSWUo8SXClAeajAR6nA0SWkRA8cKmlubo5ms87J585hbEBr8QioECqCA4szFF0NWhJWE9I8w/NDgqTC0uoKa2tryLLk4MI8585fIs16EBiGvV1qcYPPff5RkiShLAwXz17hkS/8PU8+9SVOnn6O+9/wIAdvPs7P/eIv8M6H38VH/uSPkdWYoFUjmGlg0OykfT76ex/mpoMH+MF3/xCl7zHUBYNswJ/+6cfIiwFSgh9GCCFZX19HKUUQxSMailttJ2FEHMe0GlVXyzSCkydPMkz79NMhz518ESHDkZrzqFsnOW7Qo/sl2mq01RjM5Hb6Z3pdYQXXgH6+dvuvyUn/iRDiJ4DHgX9hrd3GqZU8OvWcV1UwEVPiECtLiwzHnp8vKx9ZjPSuQe7v/c79ra893TjWpMBK0MZipcGWJUI5vc5sOCQIPaT0KPIMP44xhSbPC5aXFnjiy3/HzTcdodYIKQcGuudoLDd44lNf4rZjLaKgRVKvM7Al+M4h9ejhI/z1p/+S97z7vRw+eBMHVnb4tV96Pw//+M/zBx/5I378x/47BJqizFAiZHl5kcuXL1NQUqvVSNOU//KpvyBPMz77+GP8c6tJs8x9nlE/uLLCUDrwi5aKoBJT6JzZuRkCT5IPU7a3NTrtUGu0RrbiA+YWGmxs7bLT6RLFVer1Opub69SbM5QG+v0hSysVtM6I4oit7S5z1eja8zc5D9Mo/Fc7B3ulbvf710LE+0ZX9x8EjgN3A1eAfzs6/kr/+RXftbX2d6y191tr7282GgwLTaYtuWH/VK0taV6Sl4a8NGSFntwvtKXQlqx0I2Wuxb6+77ixFKVDkmdlwe7uLsY4yxgvCCgLM2Fb9nd3wVgqccRw2EeJIeubZwGPorQU+Q4f/F9/layXUTKgyHPKvMRYmJmdRwU+WZEShwEnn3mKlQPHeP1dd7AwE1L0dvnDj/4RP/K+H+af/dL/QK0a8eUvPE6tVp1IMW7tbFGYAo1GS0O1VUPUY6K5BrXFWYJGBb+RsDHsMEDTMwWZdlpaWE3a63Ly+WeQCiq1BvWZeTrdPkWh0aWl0+kQBQGVOCEY0U0225soL2SYlpw4cSd5McTYgnw44PTJ0xPZHiHEPm1Rp0fKBODzSn38/MnW9mu0cPyGgtRau26t1dYVND/E3pR+3Qom083Y0XRcWNJiL+jGvdSOUDZ2HRnfnxwzel8fqxLvdVfu13ZUKilK2u02usxHAF8otAbpIaRHpdWi1+8gPElSrfDWt9zLRz/yH9nZ6ROELYzRHD14gM5OxnOnnqZIM3TuaBtWKg4dO8LswjxxEvL4Fz9Plgui0OOuOw5z6pmn+LH3vo+TLz5PrRmSZl08Jen3B87wIc8dflOXZNkAYwoGgy69wYDeYMB2t0NqSgZlTr/IKKxGC0ueFuiydCBtW7J2+RL1eo24krC908HzAiyS+fkFttu7JEmCUopKpQLGcujYcYz0+fjHP8WpU6cQtiDtb2N0QXdnlzAIUFLiKeX4Vp5yXXn4ysOTDo3vSbGv+2qk1C2V2yhR3uT2ets3FKTCSeuM2/cD45X/fwF+RAgRCiGO4iQgv/D1/p7FkltDgX3FrkfyO2Z03zkITHX292urBDCVCgiD73vEoe8QUdaActC9sRJI1u1Sn5kh63fZubpBpCw/9RM/zgd/+/9EUGfjSptWfZHFhSPMLS2SdvtgLb4fkhcFwyyj3qxRrSYoT/Ch3/0wx44c4v577kDZnEGvz8bmRYR0o2+znnD69EuUpSFJEuIwIAoCPCye0NgyJUYRCYWHkx+qJ1WiIEQiJuBkiUBoi6cE+aDP4vwCaV4S1SrMzc0xPz9PpVKZVCOEEOiyxPMkrZk5Xjh9hu/7vu9nYX4JzwMlLcqWUBb4widQnrMOFwJfKteVwFeCQKpX7L6QBFIRKue+NxY4819DTf96SlC/D3weuFUIcVE41ZJ/I4R4WgjxFPBW4H8cBcKzwB8AzwF/CfyitVPV+ets07C76e20aaTTdL921VmMVPJKu18+e1zoz4YpUeAjpEIp51MKjqzn+06aZtjtEtZqNFsN8D1WlpY4fOgW/p/f+2POnrnErbecwOoALwj56ksvYUs9kVKMosQBlGtVbrnlZrKsYG1tjbNnXmRj7QqPPvoo1mre/e7v581vvptmo4oY6Yrq3Ina6iIH4/zkfSlQ2gFupLaYvCCJImI/wB8b0GrwpcKTUKsklDrnvvvuQylFo94kTqq0222ysnBW4OAUW3CU5DTPeP7UC8wvLjmainIGG4Hvkw/TCWVaCAf+VsqpbzselpoIpO25najJcSdHuT8F8Lx/wJHUWvtea+2ytda31h6w1v4Ha+2PW2tfZ629y1r7Ljul92St/V+stcettbdaa//iet6E48mJye5EOcXkdDLW++um04+NsdjCQglCCxwGz/Xx8cwULifVCqMlpc5pLTSxpk867OHbIdKm6GIAGLI8dxyl3a5bipaK7labh//R7Zx68THe+p5f4UpwnLyRozsbrC4nZGmPvIzQzNFNI4yI0Fqze/UKN1c6fObPPsGlC0PuuGmFxs4jvG0u5zO/90ecf/Y0z59bJwoknoBqrUI1qYwuSifOYIxEewVCGaTvFO3SdMBOpwOeQltD4Vlk6CMwxJ7BZ8iZM88iPcXJly5wYa3D8uFb2O6kDIuS/nCIMSWNRhXfE3zk9/+aH/zBd3P27FNodtE6J0s1O70uJrBcWtsk8COqlQhhM2LPEkiJL3x8gsl0roRECbnvsZveAzw5AnALD8n1I/NvkG1R9m1nXru9OV4gvVofj5jOgXmvj48VemSiO/p7eVlgdYlF4vkxyAArnPiD1pYwjBk7lRRFBkmdWmsWz/P4wL/8l3zwt36Lm++4ixevdNlVs6TDXS5dfAlluljdIYoMjbkWc4cPMHf8FpCWZrPBSy88TzX2OHHrLcw061QimK0nxJ6h3+vS3rrKTnubLBuOdtIkTBgHHsixoogkz0vuu+8+hsMUz/MJpIAypxZFCF1y683HOX3qFGfOnKF9dYsgComikM7OVVr1hMCDuFKll2vWd/pEUcjpU88zMzNDq9F027Np6jxLheTc+fMTKvR4ZPRGvLKvt2jac395ZQ7b12s3TJCOxVqnb8dGAOPdpVfrpbEU2pCXmkKbybGx0K42uP3lkQ+mtZo0TZFRTK5BSB8hPJQM8KJkcqEoT6Ckpcw1g8GAbnuDSiL56R97D3/1V3/Dj/7SB4gWbqU9GHJlcx0v9KgkHtZktLc36OeancwwOz9HrV7h+7/vHbzp/rvR5ZC52SZHD8wzUwlYbkU0ajFRIJGUqJHpxPjkSs9DeYFDtyuXjmRpztNPPkUcRphSo0xOJCHyJZGn6LS3aNTqHFw9wAMPPEAYJ+i8gDKn075KJYkxFtqdjM89/gz333sXlUpC6HtcvXoVrJM+MmVBnqesba2PPFotUZhMBeKeFul0V4h9/VpHmDHd/HraDRGk1trJKDd9X4986ccGuBMj3NJObnVp94EexiAIt5of88LHgT/KWk2B50lMaYirNYyRKC8C4VNk+Uh626F2AJSESugxt9CASBM2fL7ru9/Or/1Pv0zcWoDmQagf4EO/9zGMiBB4JHGVPC3w/ZADx27m4JGDDAcdhr1tVleWaNSrLM01qPiWViRoVkJCT+IJZ58o0SN57wI5oscY45DyjkYDeZZi8hwPmKvGRErQTCJa9SrNeoN00CMfptRrNeJKhbTIybKMosjodnt4YcQnPvXXHL/tTjxfsLI8T5YPwVh8qYiiCFMWKGnJ85TN9hZCKfLSSUnuNbPPNvyV+n9NuyGCFMvER3Ts5jvu1hHkcWptLsjGTsLjPg7uaxmKE7apUkicV1PkC+6953UYWyI9n7zQWCGxQpKXTuwL66YpJZy2Uj7ogmfA9Hn093+XT/6Hf0e+cY5/8U/fz+N//3dU5m7i3EZBdfY4F9YHFDog8Gv40mNlboGwNUu1McvyyiJxPeaOO29n+cBB4iSkUYs5ON+kWQlZmqky30hoVSOatYRKFOB7gjwduq1LTxD4Cl8YAmmJlSAUlplqQiUQLM02iEZWQvValX6/j/R9srykVnF5rh9FyCDGi2L+9E/+jIcefAMrS8vMtCp0u7t4UlLmqattWk2pcySGosx49JHPjfwMJFYIrBAYYTDCjYzO/t31/X6v+mU7TvYfcnX/36SJvUWCEGoy1Y/7npnqK3c3Rep9t9NdScdtKouUbNhjca6JMCWmSPF9f7JNt5c/SSaph4WwWoEip3PpHG98w73cfGyVzYunqYWW737LA9x+6x00Gi1KEfJvf/N3IZplqH2CuEm9MYsJqxBFbGxu0t3ZwYtiaq0ZZucXuemmYyzON5irBszWAuabCXOtKktzTQ4uL7A420RJMGVGHEjiSJEEHq1qhCcMc/WEuXpCoxqSRB5RqPA96Pe7RElCUqnQaDXBFFgEKqqRtBb4+8e+zINvfIg4VIh8QFmkBL4kT1OklAz6XaIoolWv0e938YBBrz8ysBB7dWlKCltQYvb1wmpyU5KbksJqMpO/rF9vuzGgenb/lua1SbUa5y/iVVA0aq9E5Ube/RwnUxZIC9XYpxJ5mGKI8iRiZMvj4OOu/qrNKLFHOSkZ6ZFrCKIKNozAKx2PX5R89ZknCAOPvN/mXd/xEL/yq7/OT77//Tx1+hwn7jhC3GjQ29mhUm8x6OxQmpLtzi4LK4fJtCVKYnThctBKLEmiKsNckxWlK1AYqCQRlUihBcw0qwS+Iu0PEFhmGskIQKJp1KtOBlI4c1s/jimHbgTb2tlmaaaFBoYl/Ol//jjve9+Pknb72KKgGUK3LCiznCLLqCYVhLRkgz6NaoWZVpPNdh9VE2TD1Nldek7m3Y2IduQyMjqdrzCr6SkHmenj19NujCC9ZqvtZR/A7hm7TkSgp19uR4E9Kk1du3r0fI9QKrLeNve+6Y2UZZdhmlMLm06qJvQx1uktua1R5RC7jrhBbi1FmtFYXAGvIHvueXS3S6/TZbZRp7N1kc3wMj//cz/Jsy9d5l3v/kGeeepL1GLJ0pHjmHJIHIdsr5VcunCBsDqDF8X0+kP6vQ5JkrDgV9HG0k8zstLSTwuEH5EXmt12m9wYoihgdqaFaZaUWYou3Ap8tjVDGCk8T+FJSRDFbPeGRFEFYwy1Zoso8Pjq5SsY6fFzP//POPX889SjAN8UlIMetdkmZVZSKg+jDe2NDY4fP8rmxjqVSgUlLKbUdLtdwsgnL8vRtu0otZpS4Lh2ILHWUtryZTC/6203RpDi7BcnuaQ0U1ec2bNlmOLf7x9tQ8z3TgAAIABJREFUp2DS0qnoM7VPLKkgvQK/CloOUL4iImKwu0XSqFKWcwSeh9WF8zmSgqzQToLRgF9u4OHR3iqZqUb41RluPXGM3/nND7K8eBOzy4vMJTU8s8Mbb6tz5clPsfXSRY6/+e10OwLfDxgMFCUVNq7usLy4w02rM5xdrNOvh6R5BqmrTqgkpNAW025TrSp2tzuosk+oqsxUEuYaCZgC36vQ6XRQ1BgOM+qVcCJQlpcFlUoFbaEaQGRTNJJAaOqq5PSXP8fS/CKFLkhqMcr3sWmJtJqdrTU8DxYWqqytnaVSqWBsShBItodbXO62yes+qBKMs3a3es/kYXx+xmuK8eN8StDsv5X7yD9ws6MFkWEEzZ9q5mWSLNPqF3uU5Sk+/jVSPR45ipQTtx9DKQ2F21lSWlMMdlHVGrp0QOAkDil1SpbuUo189GCAF/koy+j5Q2696Rae+vwj9LY63PzgYcLZGeIwxJcltshot68yO9PkqS9/gXvuf4jzazsEnuDC+gYb210+9/iXefOb30R1dpFiexvthYRFx9mo2xwlLKvLC6SDIa1Gg8iHUhjqlRCd95mbqZOmQ+aaVTypGA5TglAxGGb4SjFIU4S1eH6M1TlGK/oDj04/5eKFS9x9970M88zl4EHAIMuIpTNKW5qfIS+G2CIjkKCsRugC4YdUkgphHDMsMrJsCFYjjUJrgVW8bPScflwKvQ9P+lrqpDdEkLoVuERKy4TKPJEDdpW2r/XafdqlwqnqjR45ZH+ZYhmQhCvYtIdAYUyBrDXIOju0LzxHozWLkooyL9E6xyNDeYKs3UbJWYwp8UcAiq31Nu3NXR647wG+/MTjUJ3htluPM9uokITO8KHQ2lknioykGnPh/DkWlhY5/ULA6TNf5dRLX6XRmmW320Fry7nTp+j2BsSVBo1Wi7iSIJRClBrPVwSBQ2TVg4qz/k5iLl+6wMLCAkklot2+6mzRfR+kRHmhYy3oDGEU7d2cM2fOcPzYTRNXPWMM6WCIEJANdpC24OraRZSwRFFAGAT4wgm3FUagZUpuC65udyAUWKuRVmG1pPT3KM7TgTi9df1aR9BxuyGCFCxCGayZsvVjj+bxtfGxgnIKHjCWzR7nqAChb3nwgTdg9S5ZXuAphZfUwEBcb6F3XiSSiQM0C4HOnfwiWlAYxWBnl8DzWd+4zM3HjxBWqpy4+37qSczmn/85+AFKeDz//GlsMaDX3eW2224lCiQvnnqKcGaFhWbCV186PXKOk1y5coUvfulLSOk56FxcJ4orbHaGfPnkWZJqhaNHjzIYDFDJDFGlTjcvqXkRG7tDkjggqDQ4d3nN4Q0oybKCrNT4YUS73WaQ5aysHmBzc53TZ9YIpUfW67DZ6xBFEX7k7HSKokAVJUoJWq0qeZ6ihAFT0O8MqVarCGPpdjt0+z1MouilA6wwSDysxi0yR83Zme+5kBjjyH/T6cA33XRvgawc5yx7dOZJoF5TVLv2an1F/Sc7Btcq8mGXVBcIYwmTOtJ4IANQzreoGin0+iW2u0PmDhwhUjGFF6JLRa11AOkXZOmQm24/Tre7i/EV1Zl5NjcuE9UiTp56iZ3tTXa328zPzrDT3mSns4sxmkOHDrB6WLO2dpnOzi55OiRPh8RhwNGDh5CeM+Ha6Cna27sMtOTCVXjLnXew2e1x6dJVFpfm+fyTLxF4cLSfc/7sRVqNkJmZJrrMqVRiAu1sHMM4QWaaaq1BkAjW1jcpCs2h1QXSNCfv77rvxeToFKzV+L7EC6KRSYQgjsJJvbpareJJydXtbeK5JbIiZzi0lIETJXcq3Aqh94JUABg7WSk4a3G7N9/ZqfvX0W6MILUOuTRp0xxu3NYm7C9NTYIUsV8k95q/K4wgLHKCwAPto8KAYqBR5agG63uwfBhz8RxJVPDCk49yy133okqFTOZBK9AFAoMIA8rdkmq1TjHMac7MsrK6xNbVHp7n8e6f/Vk+9rGPcXWnT//SZaI4QHo+X3ryK3Q7Pafg7IfESRVtJBaP/jBnY2ODFy/1UGHEzMIS3/KWB9jtDzl0+DiZFmx3Onzbt7+ZK1eucPbMWe5/4AHiMODZ577C3GyTIKmQdzTaKKQNkAT0U4v0PISf0KxXSPsdh2IKFb7njZDyhiR2uFIVxEgJyvMoi4xKtUaelxQlbG5vESd1PKnodzt48zV3fuxI+dBYEPqa737/ubgWUPJNl5Nqa+nnOeNR1Am07n1oM1o4Xcs4HI+kr8aXGedAqypH6iHSFlCAbyVYgzXOVdhYib+wit9rs5h1ePozn6DWmmVu9TjVhUPoQhIkEbtrl2gtLLN7ZYtQhOjcMNdskGddFhYP8+ijjzC3sEi3n5LU6xRFzotnL9DvdMnKglL4QMCwm7F+dQusJMsyrPWYaTXo9YecfelFwkqdMKpw4cIFpHReSy+cfJ4ojJltzXDx7HkWF+dZXVzE80BYzezSYYwxrG9eZXV1kSiJiaMKaV6wvr5ONa5Qi2M8FRB4nmMlCIvWJUJYkmrNaUfpFD+ukmU5Svn0+j2ECokCp3m6s73N3FyV8fJBGierqa8tC14ThNeqzLzawPJK7YYIUmsNaT7agRDTyhfug2m150t5LRvRvebl6QDsBentdx9HmAJhC0w/Q4oQ8LDaeRd1vISqEngSGkszvM4/yslTp3n0xdPMrBxmdfUeas0YYQqunH6BQNXZ2d7Clj222+vcfsdtpMOMTrdPp5fRaM6wVDnAxuZlSqNRXsQwy+j2h6ggwRrLzHzI9vYutaROmqbsXL6Akj6HV1dJS8Mg1+gsY/nAAYqiYG6mxWAwYLcoKcucTnuL+YUmmByMppfmBEHAbmfA6qEAP0jAC6iEFZqFIQgUUirKvCAdZvjKI8uHBL7C8yRFXmKsRkqBLg0Ixdb2LkIogjhGWsiLnLTfZxEnYAaukqwsaLU/6F4uKb9/JH0ty6cbIkhLDG36I8LcK7x9vX/0nA5UgEI6TSjfuMJ+jkFLlwv5BuZrEVI7GXKkQAuN0T2UF+GrgNlQkXd6lDZCeQJblxy7PSSOX+LcS8/wF49+joWlZeJqk5VDR4iTIeuba2xubnJgdZnZQHKhfwlByW77EkIodtuSNE1Znp1nY+sycVShXokR0nlup7lhbqbB7u4uNCoUImR7t0uvBG0knW6XRnMWXRr6vQH1ehVtDTOLswBcvHgR1Y2Zm5uj3+9TpClhDLOLS5RAjiSIa1irqC3EqLxLWRaYMiPwLEkEtTh2uq1KoBTowpX/BoMBaTZAWku1EhKGPkUJvgoYdlJ8o8hkiZYGKBFWTmTGx+3lk7n+Or9/9XY93qIHgQ8DS7ih7Xestb8hhJgBPgocAc4C77HWbgs3zv8GzmN0APyUtfaJr/U/tDZ0e72vu2U2Pu7Sgb3nFCOZyPHFm+HEFJR0NoleGGF0iQwDpAa8gKyf4vkCpMIWgiCpAzG218ZIHyt8Dh46ShyEqOgCXz1zjmJtjavtLTq9IQ++4SEWFubQWnO1vcO5cxeIY4dH7Q86lKWhUqlQFAX3ve4Ewyzn8to6aV5Sb8wyM7vA+UuXaTQabG1tEUUlYZqz0+lilU8QR3T6PSqVCkm1BkCz2URKSafToVarsbW1hRCCpaUl0qGm2Ww6hJLxCPwEX4ZI6RErn2E5xFDgBRFx6ONL6zC1VqOkwpQ5QkkGgwF5mTl0/siKvNvdBRFSj2agLF6m0myFA6d/zTh6rQ5jU+16RtISR1l+QghRA74khPg08FPAX1tr/zchxAeADwC/DHw3jtt0M86p+YOj21dt1lonevBqvx9//vGtndqdEnvIfY2bRoSnKIwrHgfK0TKiOIbSYqXCakPSbJCnJYG1WKEocyde5AcJCovJM4p+gfIjFhdaNJpV/ub//Qy5zkkqDR753N+xsXGVO+48gScVzWaTtbU1tNbMzs6jtSZJqoRxzIHlBZ566hliX3FgZZXW/BLnL13B8yRR6E9wrkklogT6w5x0mBPHMbVGi3a7TRQlJEkFrTUzM3OARGtLp9Njbe0p0B633HYrjVaTuFLBao3JC7zIR+cFQZwg/QBPOOghpkAGFmNKiiwHnNpJVjqb8jHoHIxbcElvhIBy0phUr6HxfB2o0rVCZ6+lXY8B7hUcbRlrbVcI8TyOS/8wzr0Z4P8G/hYXpA8DH7Yuih4VQjSFEMv2a1mKj6pM14ISpt7DK5aZxreTERiHXSyMdpx6obCFJktz4mYTk6bIIEQYS9rrofyYvChRvnAIfRToFC2GeFFCr7uDDAI8CXk65MQdt3Lm/CXOnX2RrLBU6g3OnTvD+bMXSJKEPC+pVKuEkVsxR0nC4cOH6eyss7y8zOzcApm2rG+0WVlaYnF5lTNnzjBMU4bGY2u3i1Q+Qg0ptUtrdnd3ueeee2hfXWMwTKlWncpIvdEkTtxI3ev12G1vs75+ic3NK8wtzNOcncNXEmMLfC+gtJYwiFGewBQ5QkqKIkcXlmFWUosCsjyfjP66LMnznDAIgD37xmqcUKQZqhLts1+0Xwd79w2qPgKvMScVQhwB7gEeAxbHgWetvSKEWBg9bRW4MPWysUDEviCdFoeozzSc4MGrTPdCiFe9DievES4XscKlA9oYwjhG50Mq1QSbpg57mucUukSqYOQqItFlDr5E65JAKlRcgzJDeRFXO2ukRYlBoDyPJIqoVSKK3R5bG+tOphzpqFBac+XKFS5dusKhI8dYWFqh1+tT9FKSaoUzFy5RqzeZW1wgLTTWCiq1KrOFxqiQnZ0dAl9QTWLa7R0qibP8vnz5Ms1WFel7eGHATDRHp9NxlOEoRGMJfMd0nZlrkSQJQShQnssZ/SAgDFy9E2BYlqAN0vPQ2hBXPIqih/BCpBT4QqFLi1KW4cBtn4YV5ydVZDk77W1mW0sIT2CNc9ATYn/FZfrcubZfVv7/l2K+EKIKfAz459bazteoc12XQIS19neA3wFYPrJqv+ab/jofyMiRlv7osZQSZQT97V1sL8X3HKrJ2hIpHD9cyZEdj1LgC4wuMDqnEALfGogrRHGFJK5QmgKRQad3FaF8mo0ZrPCIopJ+lqNUzPr6OnEcU6nUKK0bAZ955lmWV1dQQrAY1Dh47DbiSgJAU/kgBXElQcpzzC7MM+h3ae8OKaxbCe/u9GjUKuzsdOgHrsLRbCYIIWi3d0a5oaBSqdFcXiJKEvLCAZatdfTv0PcmgmVCCLQpCD2f3X7PIc+kwFc+JT6h5ztl7bxAqRJTGOIkIo4irHIBl0QR3X6fJaXIixzPCxBWINButBxD9ybBOkrLpuBr0/evp11XkAohfFyA/idr7X8eHV4fT+MjHv7G6Pg3JBDxtd6y+DoXnZnOeCzYokQAtSDme37gnQy62+5EjRD+vh+ijabUQzwhwA4xugRhsVZS5Bm6t41nDK16g25e4idOGrIVVlhbWyNQHkNKAuXRHQxotVoOLJzltGqzDAYDp5aSZXzb27+bwWBAXK+TZRlRJWJ2dpYsy6g3ZwiiiI3Llzhxx62cfOEMu/2c2Pc5cPtt7OzsEAU+URzT7XYptSaKIsIoIgxDPM+j0WgQhhWkhOFwSFnmxHEFpXyk52OFwpQFw2xIkiT/H3VvFivflt93fda0pxrP9J/uPPftye4BYuwQYVsRKAicxIIYiwQJBEgE+Y0H8gJSFClRIHlEKBDJQkIG7EQYq5EdI0xiBbsnu+fuO//v/Y9nrmlPa+Jh7ar/0N2378WOdHtLpXNOnTqnqvb+1Vq/4TvQun5A3iff+xgj0ee7c+1kSF4sKiPLNAJJ5zq09Akt5vo09hwcn0WUiMf87HcYjB8QjB+mkQ8frLoXwP8IfCfG+Pce+tVvAv8B8LeHr//7Q/f/50KIXyMVTIv3zUfhR4Kef/TW8OjjtdYE6zg9OeaTL72KvvMVrLXJLCxGog9ImVybg+2RBgguqfs5QaEF0hjaZcvF8TH3zxa89fab2GbNnXdvcuXKFYqiwkdF7yOeLqUOyjArSoiCPE+2iFpr/vmXvspkMuHosGEyGTHSM8pyxPn5Oc45ZrM9hO346T/7r/KHX/4a/9s/+gLPPvc052dLJuMxV45Kbt47RgjJ3bv3GY/HxCjY2ztILSwkXRsoxyXjaTG46InEkHWRrvVkJjEPFosFguQLOp2OdzKQQplkdRkDShqUcnR94jIJoVBSoZV+ABixDp2lVVqiCM49spU/Pq5+0NL+8Nv9B6GP/AzwV4GfE4/qkf5t4M8LIV4H/vzwM8AXgLdIinr/APjPPsgLEfHBjRAeve0kutJNDLvF9lb2kcyn3zoZsa5lYjT//l/6BeJmAZOr+D5iN5tkjqtyYjZF5BOc1IQOtNBkNiLrFXGzAdviY6DaO0D4gGs9q5VHVYccLyxtzKnGe+zP95iNKjIVKUzg+pUZH//Y04wKKDRMSkMhIkfzMTI45uMKGRy///u/l2xpRGS1vuDo2jOslg2zyZRf/nd/kdIoZvMR8/0pXgSuHR4gsJSVpO9bytEUZwVXrlxh/2CKLCRSJ71UH7boME+eBYxuCSLg8ZTjMlFK5vNdWqC1JioFWhEQ9M7ioqOPFisDjbSIrMJFh+sbfNOwX06pRIaJAR1qcqV3iiUPf7+9ZVIOPH2BiZCLDxJ66fgg1f3v88N345//AY+PwF//wK8g/dVjK+lDvxKBx/sbj38Kw/YPRERFyITi4v59PvPxT+M3ayCybmoOj+YgkoVgUA6hdDKY9Z6mXkPwZErjuhoNrFZr2rpm0zk658mqETIrOT8/5+T0nGuHB4xGJSpruDp7AinT+O/4+JgnnniCxWKFVoJrTz7Fk08+SVkm5RCdGf7cz/xrnJ6eMhqNqLuW61eustysedLkTKZz7pye89obb2Nd4M69+4S+5+rhnHvHd8mLGWWesVotKMpDLhYrinLKepXSjhgCWVZQuzSdklLTu0CWlTjfUxQl3tskSb5VJpGC0Pd0w33WWmIUSeKoD0hpGOUVvduCSpK+k9QBot71CX9Yh+bx3VH+aeek/+IP8f159MOGqj+iEbyFPSsiCoEOgb/2S79Et1mRh9SwN1lBu1pRTCcQkwee94nXVNc1RmtMXhGaNSEETs9Pme/vc7dpeOvt91g3lsvlkv39fZ598UWazQZvO+qupxjPmO/NsLajKjIgcnx8jDGK6XTKs09f58aN61SjET4GFpcrvHUcHBywXK4oTE7dtWiTcXb7mMU6adx/+tMTvvPd1/iXP/85fLuhrldMq4y798/p6xXTyR6tbZlMEk2kaRpGoxEiJkXntm2RUuB8z6ia472lMAXr9Zos00QBymgyrQfBtgSvK4oC11tUoQaVmCFX7S3epd6zRGAECCGTicOwjuzQlY9fMvlobSF/3Gb3AOqhVkX61CVKQjre/w1FmaBfGtAhoqzjxSefwvSBrm0opjnj6ZRmeQre4X1EmRKiwodINRql5+oburqB4Lm4uKBrWi6Xa2SWcTieEoQiL8YIqZMn6eEh3rXIPGkv6SxnOt9DKnAx0tUN55cXfOWrf8B3vlthreeVj7/Ks888h5SCtq3JC0nf9Xztj19juak5OVvw6c9+np/66Z9hPtvnZ39uxe/8zu+wuPcek5Hm4vwumsCkKokyIge266gqKbI8rd5aU1Y50wHkYkLSc9Ja0/U9eV4SQr+b3PkY0DrllWHwu098sgQnn84m2M0GoTXE1PQ3SuCkJsqAfHinGzhmjwNI4iMB+mOIghJiR/gE5EM+DT9aL0gIQZAC4QOl0hRR8u/8xV+EpkXlJWo+BRxRaUaTCV27IUiNrh5YinvnCN4SbY9Wgq7tuHLlCkopvv6Nb1E3Fh0Eh1evsV6veeWVVxE45uMxXbummO1x+71bw1aa5BsPDq/RNB3r9ZrxpOAf/uo/5Jd/+Zf5xjf+iC9+8Q+4ev0azz37Au+++y6TyQSpS46uXeeduyfUbcfp2QW291y/fp1/+9/6N1md3ef/+t0vUOY5uemIvicrSoqyICjBxfkpzgakVHRdEtxVWiCVJARPVRX44NAmp+9bnLNY11GNx0htEN7TDgrXtusRQtHbDqSgbXsKY3CuJ4SEILPWgknctIB/BEDyg4Yvjy8zP3agZwHkSsPDXKUf4J++PR4eiQLYGBAxUKmczfE5U5NRVCW0HTEEhJQEJDLGxME3JmnvCE9EYWNISnNGETaW09NThBDcvnUXleW4GLg4OeHGjRu88sorCBG5c/sOR594lcP5dU7XCb1+7do13njrdW488QwnZ+ccXJlR1y33T9/jL//iX2E+v8rHPvYxfvt3/wmbpuOtm+/wxBNPIITg1u1L6uNLbjzxNK2NnJxd0HUJx7q8uOTq1SOEyXj62WdouzdBSAh+oIE4ZpMSF2A+32e13LBYXTKbzQalQE1wLcTIcrXeAZpVlkbGUkpC3ydnE60TYHnQQlBaI3WG7TaomGCDjbMJ/ztMCqWQuB8xu384JuMPuKbvd3wkglQKkQS32CoCRx6sohHxWCX48Bw4aSVJRmVOf7niv/iVX0E6T3N+QZZp2r6jqKbJA74fACoiEoJHZwWIJMAVbItv1zTLVYK+bRryquSNr30TPJRlSdM0zGYz9vfmXL9yiO/rlIdmGW8dnzAej1mvG6yHp595gbq1tM7w6U//NNPplJs3byJUxV/4C3+Za88+yxf+8a9z5eqTvPXWW7z88su8/vYtVq3jM5/7HPfu3WOUJ4T8zZtv88+/+CWef/45zs5OODo64p137zMfTVgtL8lGBVIqCq1ZLC5QyjCZjFivl5SjgigkIbQ45xAyUFZZYqYqQ5YVaG2SJHuWQUjjWK01Qiqk0YAALfB9HHRiPSE4EHp3LX4UwCRutREGnuWHoTp9JIJUwEPKvw/hELfeP/zg6n77aVRGEpynKnOa9YbReExZlPS+Y3R0hG96pNH4YcqUIIEh5RkhQJZRL2psvSbYLkk2LhbUveXZ55/j8mLDarXiiaefom9a7tTvce3wkNXynGefvE5ejLl25Qrz6Yz9/X3G4ynrumNv/wrlKFKYjFvv3eXw6Cmsjego+d7Xv8WnPvU5us7x/Asv8+7NWwgheOmll7h//z5t2+K7Di0Ck8mEayrn3fdukWUZR0dH3Lpzhohgbc8smyXtfQlVVdF1lhATYOXs/Jws18zLtFOVRTKw0FlOHPq5TdemLTqCdW5A3Qucsxitdg17xwM5o0BMVUMI/ACGz/cdD+Mr0mX+sdvuBbkwg/XfoCyydVYWidsNQyM4RBI2J+IYtiVrKLXm488/gYgdbHqCByl1ClAizjqkqWg3a6pJkcDCriWYEd3lPcZFTmdzrIscHZYIMcKJyPlywfMvHOJtz2Jxxp3bNxlPKkZVzv7BVY7PGw6u7nH1xlOgJM+98FISnpiOsX3LwcERy7ZFlJrabnjmmWeQUTLz+5ydXiBQXC46zGgPUZ+wOD8j29Q0TYMyGc453r55k09+7BW+9+0LjDTcuXsbZRTSRK5M9um6HlOOCQHaJqBUTqYylJIczAVKDcxOEwkxqTTHGNFG47seeofwHkkKVKUUIXqiFIQosBFUzOhdg3PJaWQynrHyDd5rUAovH80zv68h8xgI+sMgSj8aQSqSdGAQcshFw9ZldCDipZGbTIlS4ufE5L4cEOADbbviz/xLn6NfnOP9drKRJihd35NpjRRpRMhgNxhEj1YFIkSauiZ6z2azodk0TKdTZG4IUnCwf0T0nqLQZEbS9U0CsQwXZb1acO/eHV7+2CtcrjeD6JngytXrvPbGm+wdJRLctStPcfvWXa5fvcrl5SU+WDabDc45rLX07YboHYvFBeu6SW4hbc9iseDNt9/i+Rdf4Hvf+TajyZR33r2NqaZ0rmbv4IDO+t1kKMZAlmVY15EPUEAl2Ak2CIY8NTiCS4rSQSQ/J+8t3keccxiTk+V5ysvr5aDOHMiNGVKHBz3ROEwNt8H5eHUvxOM//5gFKRFElKgYiDE50kk8kLYVJdODpBgqRwAxEOmIyBCQAhZnp+yPK+jaQdfJI0XEekemNURJNqCGdFlgPQgceZaxvLjk4uSMcVUx39tjVW/omjVN07BYLCiKgvl8jskUhMBqseT8/JyqGiEGyfOLiwtMnrFcr+n8itYGrt14kvV6w2Q04etf/yZ7e3sIIVgsLxiXFW275ubNmygJq3VNax3OR4TJ0W3LyfnFTsv/G9/8Nn3bsVgsmMz3yIoKpKTvHEpBZjRJc0DuVATlgFAKPqGZqsyw2WyIwuOtpWvb4SJ4rHfDIiHw3lPkBSCJzpPnOcJH2r4hoNJj1VY3C0RIoN4dffL7ks7vh19+0OOjoarHVgJCJcHVIHaUBBUEIgYkAhnDDu0kh+xbRMFIS372p/8VciFYnB7jbUu0HbZvIfg0yw8BtE4Fg9a4vsH2NcJb6tWa5eWC2WzGYrVi3dTcuXeXqqo4OjpiMplQlBnleML+3iEgePb555lOp3Rdy9e/8TWCs3RNw+XlJU3TDPoBCfDRdR3L5ZLnX3gRpQ3fe/0NQgh8+9vf5PjkHk29wvYN9WaZeFje0tQr7t+7Q6Yko1HJyckJMUZGkzGdD7gAbduhZFopE9Crx/YtRkv6bpPaat5T5JpMSwiOTb0ieIt3Hda2eNchSJr5zjm89yyXlztF5+D8bjDQti3K6NTeyswDPEQIEOIw0n6Uav7wrP77uGkf8PjIrKTRp7l8YItNhCgFQkhEjCghUjsJwbDIooXCRwFNx7M3bhDaNVVVDGa6CS0U+gZkQvhEmwLWO0dT1yAUjMdkUtNsaozSZFlGjJGjoyMODg64decOvU2F1tnZGQfzPfb2DmmbjqOrV1m89hq98yxWay5WK5TOuFit+YnPfJ5bt97lU5/8DO++/Q7leMRXvvKVZL3Y93z7W98luBZnOwSRi/Pks7RcrcmLCrTBh8hq0bFcQJbJ7YfqAAAgAElEQVTleB84vUiUkrt37zGf7+GsJcZImRkgoqVgcXHKeJxEHpwPiGhQSqVVc2DhNk1DvdkM6UBqSSHSGHQ8HoNUKCWQRtG2LbnJkJXg/PKMZ156LvkKKJFcTHgowxTbRC2tltui/0+yGn40gnQosgNbpigEERFRDvmUJMaAiEkzNAFRRKovJYS2RXuPkBHftQgCUitEXhK7HlWUaKXB9+RZyfriFLxnsj+DtkaiuHp0RNsnysblcklW5JydnSUhWpVkaZ568hnatmWxWFEVhouLS4wxHF25wetvvsF6veTaEzfS1n92ymZV891vf50nn3qKdd2gjeL09DzpKAWPazfUmxVts8b5gHOOum5BLIhRUIwqRqMRUgiCF9SbBtC0bc9kMkmGtdMZeZbT1EuyrECgGFclq8Vlkm/sUmtpvbFMJiOEUNT1GikiJsuRSqX8UmUoBDJX+D7Jjjf1hvF0Qllm9HWToIIx8OLLL2G3mFEeFElB8EiA8tDXx71EfyxzUh8CMYJUiS+TDAwSuCQiiD4i5cBn8oAQqVkVBM8/9SS+bVAyoE3aooSAsF6h8ip5q4uIbS1GghISqRX12Vmyh7EapODtt99GasXp+TmvvPIK62ECs16vmUwmLFZLtNRE71iue6aTCW23QfUCoQybtuP09Jznnn+ee/fu4FxgvbxksTqnrMbEGJnOZ6xWklJrgq2SqoqSnK9qQowIFPWmRshIvVlxGgK5yaj29vAIdDYiz3NOTm7zwnPPQoisV0t0Hjg5uY/3kb7vB7heHIqoPYpqkrClMaJ1sfWMwPY9WZYTPbiup2s6Mm0gRGbzEc6nNMbZYZsWqW3VBUsgpWExPtx5SXlpCMlPNIhtQfXBNfIfPz4SQbr95G0VhInJ9hqZToz0nhBAKY8IkhC3dJJIEIJPvvqxwXDLQZUjQ5/m0FEhx2PYhAfIB5P8NQudaCPGGA5nh1xcXOxew0svvYQyBt+2vP766/zET34ea5OcYqYzfG8pSsOt997m9OyYps/57Oc/z5UrR/zWb/0mZZFRlUe88cYb5FnJarUcLMxzrO14/vnnmRQFMjoy9Un+2e/934h1hzEJg1pVFYKAMYb18hKAs7MTZvND1qsFPkjKPOPk/nECM2826EJw9epVpFBImdIWazsiga5rqCaDHj6gTEazWWNMkluPSIJPRWtVVQTnKcoMay0uWJzvESLDGMPF5SJ5Y5HcBvWws8mhyA0/JEgfJwA9zjh9v+MjEaSpck85qRJi98ZiwubSM0IGi4o9ITp81Pih1xf6mv09SfR1gp62ER80zgWyzEDXoFFEofCjKf3mkoPrR/Snt1mt18jiAJmvadoVzzz7FHXTk+U5q9WKi5NTnr52nW9+57s8/9wLxCC5XKwoq5z37txGGk3rPO+99ybHx8fk5YyXX/kcvV0zm4/5+Cc+xTtvvctquWRUjrh2ZZ9r127Q9Y4XX3mRt995k7Zt+bP/+s/zjS/9Mbdu36ftHDrLCFLiYyArDmjbhnHecHqxSMDly0tG0xmbpkarjOnhDXSWk08PqduG2WRCvb5EiEi7uUTEyOXZHaqqommS/U693uD9wBDtOg7mFXlR4HpPWZYgIq7rcMHTbGrGJllblnv7dNEjhMV4jwgGiQGRxD3UEHtOJBfn1C1M/dntkaZOP2bNfNjq48dE8eABqS5ETxQCFfyOytxHQZA2Vf9JJwfXW4SSeJf0jIQQqfpsuzRWDQolNE4qmO6zePdtzs/PuXJ9TLA5xiRE1I1r1zi7SGzOxdk53/nWNxgdXufWu28TbjyJ6y3rlUiuzgz0ksmCm+/e5uqR4Orhy/St4OWXnuWf/t7/w8eff4LZwSEnJycczcbk0TIZFfze//l/cPvubVarFX3fInXO3v6cO3fO2KxrZJbTWcd0PiPLpjSN4WKxwvrA9954nVdeeZXJZMJ0Mmc2m6GLREOejEtWizPyTNF1G2xXI3A4r7h1cofxeIxzDiUkZZlhtaTKc9o2+QfkeU4IgfOLc4wxtH2ydzR5gevXVFWS2Bla1cOVcsNGlWaeUQSkEjDUFNtC+EFxBeJ9KOyPH38ScYj/GviPgZPhoX8jxviF4W/+S+A/ItXhvxJj/O33fQ6AIAjRp+pwIIzttgwGozC2/PqBmuB7nn3mSaLtkqKzSIxPH3wCNBsFwaUn6AVCFTgP5FOOnnqBs5NTXLPClQX1as1oOuOtN17jxlNP4tqGcZVxdDjn7uKEg/0X6No188mUzWZDvaopi4yuSdSRMs+4d/c93nl9xquvPsf5yW0+/epzvPnaOzTrBfP5nK/+4T/j7OycO3fvJrJgZhJ1Q8B5XbN3cDSs5BNc78nzgq6pB78kxfPPv8DNmzfJ86Qq8pnPfIbj42N624JRyBiwnWM8zji7f4d2fUmwSSZSBJiNNSK2xGBTXrlZ7wAmRTZFxkjwiTZipMLapJU1mc3wUVKUI3SWDWPSADGQqIBbseKUkxIhOJuq/qGSUg8VTpI//cLph4lDAPz9GON/80jACfFx4JeATwA3gN8VQrwcf4THaNreBUJG3A6AG/HOJV32MAxDo0g0hxCIfc8nXnyBrlkl1JOIEBxCaKxrycsSlAHfghNED946sBFMxWQ2J/Yblssl871pok70LZvlgsViQd81ZFry8Vde5qUXX+Tk5ITTk3tcXl7Stx3z+R5N03Dv9Iy6tmw2Hau25fU33+D47jsYAV3t8NHxzjvvYIqc9brGD7yi0XTGarViNpuhdOD43i32Do44Ob6FySqEyqlGY/b29rhoEpL+qaeeYrNZc7i/x3p5wWZ1SQiBzrbkxpDp1D/t1uf0zZp2s6Rew2x6kLyrvKPMkiFaYQKFUfR9T4yWrrX4BprO0nY9KM3R0VG6PgHKckTbO4J1SJUahqn9FCEOlOXtsIWhmCJZ6WTmwbX+sGImfxJxiB92/ALwazHGDnhbCPEGyWr8/32f5yBGjyB5hQoZicHvRmveW2QI9EOe6n2HDJFKBPbHhszJnWOztw5daIwQqbFcb/CuRRdlUmp2DqzDusDe4VUKv8FnU5brmslswlNPPcXe3h7zvSk3336L7OiQVddx/+4dxuMK9se06wUqV7z95muc3D/mMijyrEKYjJvv3kI+d53Da09w9/YtNnXDnfvvsV6v6S5sQhcpiSwMne9QZc6qa7i4uKBpGo6P75OXY/Kix5gCSWCJJ59dpcgMq9WKz3zqk1jXcfOt11ksLrhx4waFKVMDv3HcvvUWoW9xtiHPc8bjEX1b46QkyzRdU6N0mmJlShJch5I9PiakfW4Eo9EeJssRWlMUBb0TNNbjnSOXmih88rrHpNag2Labwq6BLxUPLB4fy0n/hRVOj4lD/AyJFfrXgC+TVtsLUgD/wUN/thWHePx/7cQh9vfnDFkoDCCHOGwlnoAMCZkjQsRFgSCmUaRdo32SiAlti8xzXN+mqlVqcD3OJr13fIBKMBMZdnmJyXJCXhG7DjPfg7qhd4Hp3j6d61ktN0ynU9bLBVcn++R5ztnpCbZryTJ4/bXXGZUl4yrj1q1jetOQ5WOUSlI4CM10OufurfssVg1IjTKC3jui97jWstWdFUKihWY6mnLn/r00BrUWZUq6pqbKn0DFpN2UKciMYL1YsVmcUeWa85M7TNoOJSPv3XyTMtd0bU2epxn78ckFZV4wHo+p6+QX6nyifaN0kuARyW0PKaiykiAVQkIUSYrH2YjwoInMxxMihhSQBoFOo9eBZyKEeGA5KdOKmgnz6PX/EHH3JxGH+O+AvzlE1t8E/lvgP/whz/99C/zD4hDPPvNUVAK8SFuBj46t7r1UIW31AqIQ6JAYjUaBanpKEYguyV8z5D0yywhtS1N3jA726Z3A2hazuKCtW/L5VdBV8h31EbnagMwYz+Y0dU1WlFQTi1GTNPbzmsXyIm2xmxX+rOVzn/k07733HqfHx+yPFG3TsFftIfqG41s3ORY977zxJut1TdtC73tiDFSThEvtrad3yVIyNeAztJFcPTxiVW+omyWRDVoVrBaXvPyZVCDhHSd3b7O4OCO4ltamubptN7z5ztsURrDYLLDWcnnpmEznSK2JKE5OLzg82Kft7QMKiE8wPSUjUqZiMGLITUZrkw1OaiwJJJpRnjGvxgSyxD2LCoFJ2ehu3Jn6p0IIlB6McGP2yPWXHyJM/3+LQ8QY7z/0+38A/Nbw44cXhxhAEAlAAjFKwvCmo/MP3tAgnBUQYKEsMrxrCVtBMu8RMdIulxSjEWUFm7NzNrLioDKsz47p+x5RTMmnc5TOyPf2uVh0HDxxA5Bo4zFKM9/fZ315jrWW+/dOOTo6YL28QMrIbD5hvVyRGYVUkEXHpt3wxre/ThDQ9Su0GYxfg0RSMimmWN/iGouRGdIIMgWJoSbJtMR5y2azIoTEFMizAikz6qbjj7/yVa5fv8rhwT6X56fYvk7YhBho6hUXF+9hBKigKasCKQRGJvsbJQ0np5eURcbde/eRUiTp8iwpPscYqYwj6gyTZYxGJT4IQrSEqIixp2sdSldEC+Oywm0B6uhHgjQOJEelFBG/2/oVxaPX/E8TT/rDxCEeEyH7S8A3h+9/E/ifhRB/j1Q4vQR88X2fZBgjJbheHFbELQtRMXDCEAJ86FFIlHK8+twL9HVDOalouw5CoBqPCF1Nv7hMDe2u5srVMW6zYDyfgMo537TkmcKUJW3nmR1eIQZwrsOURZqbr9Z0vQA1Qpc1y2aDUTlRRjbrhlt3T7GdxflI2wXqpsFkaTufTqd0NqmERCE4qBIutG0D3keyIqfr7A7dFGPEeYfzFlOOCEiqakxRZATrmMzGFJcbzm6/QXNRkecGrTXjIqPrOuq2JteBw8PDRFMe5vBFkdG2NUEpCGIwFO6RApSUNE2HEdkAfFZoMnTM6X3qM8toyGXapp1wKBlwvWVczmmaDi0Tt18qCOSPjD7jMJB5EKQf3kJ8e3yQlXQrDvENIcQfD/f9DeDfE0L8JGkrfwf4T4cX9y0hxP8KfJvUGfjrP6qyhwHZLQVKJHqy8P7BzyEiRaI9CwlSZmjg4OAAJUi67VtIn0i2Lz6wC4Dz42Omo4pgA1LB/tWrxMYiixHFZESoG4TWaKCtW4oi5VVt2yaIn+tYLjY0TcNkMmG5vKTve9548y2WyyXL1tEJOcjblLTOMZonCrExhugTI7OzMdGrhSbKgVFqbeK9m5xROSGrRjtuQmYyyCN911HkBjWfpvcUHLZPebp3LUrA5PCAvCrReZZaR20LQuF8JC9yvF8DOVlmGFVJ5aTrLLa3tMsarRWi7yjKpFVlrWU8muL7dA6rqiIKnZD/NqlKG6MGT1KFe2zq+biKydZdGj5c+wn+ZOIQX3ifv/lbwN/6wK9CQIweFyNSSIRM1ISUlkYyne/stL1IupxaKq5fu4Lya6SUiX4SPfVlAn2YwUy3HE/obMq7eu+xm4bJXobIKlCC6DpkVhFsWhWVySBC13UQHIvVhvu33kUbw2Q8Znl5zun5OWcXlzRdn16Pybh7+y7T6YRca0aj8YDh9EmMNhacX9zhfLFmNJkivKBxgabrE07TGPKsJCuK5GevM5RKBgwQEGpDISLLVYe3PTGKgZ6coIizyZhsNGIymZDlJTFGLi8XWO9o+54oBEWpd4DmotrD9ZYs05RlaotpIcmrkvF4jPd+19TfroZeBPrWolTku9/9Lp/97OcJLkH1iA9o0I/L6Gy/fphq/vHjIzFxEkKgMvMI/hAGqFcICWU6gBii0midEesFZW7wi4Y6WKrJlNha+rYjaI8xOZEUdNam6VSWZQg0lBOIGuc9zkUyBEIaslyD74i2pzzY44ky4/z+XbIXX6C1Pe++e4t103D//gmXixUORRSaerNG64zJZI4WEq0zfN8hg+D+3WNOT+tkPFYW1I3HSw/S8MTTT+FjEqmdjMZIZcirEc4lUd1gHc52BCRlrsg6Q993NE3NaFQyGpVYqzHGMJrNKIoC6xLdeDydYL1H6iy1mjLDer3m8uKMiwuT/qasgMB4XGBkTl6VCRFlJEol0wktdBqdioCQaQL1xS9+kU984lNoKQZh3W1nhh8YpFvk/vb4QZTn9zs+MkFamEEvdADbwgO6gxI6jeKkJiqdHsMIoxQWT2aK1MSXiTJSlnna8kgof2PMDoyb5Rl4T2cjqsiQ0SCjTNWuDHgnUKMRrBYQLHdvv8cb3/sefd9jnef2nXtsup56aHZLlZGrjCuHV9mfzJI8TRdp1omdeXF8yaLxzGbJ6a4ap9VOZobxbL57n3KgJy+XCXKnlCDPDVJ4MjWhFIblcon3Hq2TQklRFMz3pkkGHUnb1oBEKY1QCqSkqiQueKbjMk3t/JwYBEoahBqA5UpR5iVxQDh5IXdKz22bWlZSSqRSbFH7Sim8s0Q8Wv5gyvnDPz9814fNTT8SQSqFpComg/w1GGMeYBS3bSUGPVGdgllnGX3XUC8XHFQT8I6urgnW0dUNQhvK+RRvHXk1BgKbxRrftmTWQtRElwxvQzSY0iTh3Izk+0Kgb2vu3LlNZwO375xwuVpSVmOst2hTpAa2UOxNU/6aXqrk5OyEi4sLqqKktaCLkmo6YzzZYzQZE5CYvEAEgYsB23tkbNM2bgzrxTmz6ZS2SwVewLNYr4gy7TjLiyT3o/OMKAT9oMocEWRZQZZpnI/4EJLkuS5QIrC/f4BSmsViQR4ixITHNXk2QPhM6n6YDOeSbGVukhJKHR1KZTgnaa3jy1/9Kp/9yU8T/TYAH93egUdW1O3vtvdtr/UHOT4SQSqEpMqrXaGjpUqftm2gDs4VQiiENAThKEyJ61pGVUE/zLe7pibLTRI7iJF2s0FpQ+h6TFlSFAWXmw6iJ1MZLnpEcHiRhGBjGBDkfSK/Lc6OURLuHF/QRclkfsgbb71FVuRolSGNRqmIKjTRSS43C27fvc96XTOdzHBZgc97RoMg7/RgD6NzVqsNOQLbWZLCQKLGIAWubZDBE1yLiI5oPbZrMFnOdDZjMp0ynkzQRu78QQOC6BLWoXEWazvy0RQhoKk3FBVkozLN/LMSo3vKaowQIJVgtVqRiZxpZjBa01pLXbeUxYhJNdkFWtf3OCtwIfKlL32JT7z6CkYniJ54rFB6nHb+sECZECLtbh/w+EgEqRQi0Tb8dv7LI22LoOKgqiFBaLQuMbFmvV4zk462rpnO0skc7e2RGHYSdI7zgbrrMFmGGo0YocE60AkgEbwlSAjRgQuo4PBtjXOOIjOMx2MOr97g5s2brC5XTGd79H1P3bWIPol7BRW5XC94991bWBeQUlNMp6w3DcVkyqiqQEmUTHlhVY0GZZGUG9Z1jSAmpqcMCC3TVKpriTJQZBmN7TFDfp1k1PO05Qo7nMOYclCZzqW3aWUVQtDWG7IsQ+oMPdy8jygpaJsepQ1t3XKlKHA+sNlsBoGJCdGlVlL0DqX0wLaN9F1qtS0X5ygl0PL7a4qHt3QZH81Ff+y2+4SgUcSHKsTt/QAGEq+bBMHT0bJXaEa5oioOaM5PEEJQTsb0bcoFq9key4tzRqMJqizpo0S0UEyuQJbjEChdIGKBkpHY98TYEV1PNp4ilktWtmPvxisUl19H5CXeSgKBbOwQ/ZLLi/PkgzTOaNpA3eYUoxlRtFwuLxhXM8bFHiZLvKGu2SBioK2XKGXoXIcSFRKfhgBtQ55pYrBY2xKjwxhD7zt6W1NkOV29xMgwwBYlSINQhtY3mKKkcy7l21qhtUErSV23nJ9fYq1lta5RmUFmOU5pluse6ST7syOsyFNEiI5yMkfmOR0dPjqkmaAJ0DVY5+ldoO0DZTaikGB9QCKH/uhjUuTDFj+sscN9Hzw+PjJs0R0oQcrd7eFPpZRyV1ABA1wtx9ukAX/31nvYvkdJQXCeZrlkeuUKqihTi4RAcClt8NY9WmF6m0APOn1m1+fnxBgxxnD//n1Wm4beeZwXKJORlxUBTUSA1BCT21ye5+zNJrzw7HOMRiOm0zFaS7SWdF1D02xoms3w/khOdLbbWSgKApvVEh8s0bmkyBwSaEMicH1LGPJogiMGR5UX9F2zOy9bxqcQqU2VZVlaWX0cBgh6eG1z8qwgMznBR4pqhJSaum6ZzPYZVWOc9WQmx3l2Ba0QaZpkjOGP/uiPdlqm6SIOgRglRInY2sA/9P3Dtw96fGSC9HE7xoeprw/nOdtP5XicPJJCSKKu0/EErE8gCR+oFwuWd+7iVgsUoLXCGAU6iW5lWepBxpgmXM51NOukTTqeTDg4uoYxhivXb3D9iScTQkgqWhtwUeEijGb7LOsOHwyz6QHj8ZiySBMcJXR6Hc2K8/Nz+kEQTAiR1Olij5CeTb2g6zf0bYO3Pd52iBAwOo1Kg+vp25psoLu0zQajE57TKJFM1IZztxUi2xYl2/OltSYGwXg0JUZBXbdIoVDKEKNgPJ5idEaeFeisZDyeAhIhM4TMMDrfXZ9t7zTGyNe+9kfI1ERItPMHo/thvL29Jer5w7fHrEbf9/jIBCl8f2vi4e+3J2h7FEUBMvXyqrKka1uWy0vOT8+QQlCWJZnStJsarQSbxSXRW7rlJXlZYPuerkte7/V6SXCesqpABM7PzgjB0/QW5xx5UZHlJUIZqvGEtrcgDfsHVzg+vUiW45MZVZ4joqNra1aXK7quY7VasB6C31qLydK8f7FYcH5+RlkW5HmWQCdtTVmWiaa81Qn1DtfbNGXqerRITitSxOQPWm9S3j6067IsfUi2FXRCxm917BN21FmfhIONSeCW0ZS8GnHzvbtU5ZiIROkCKTXWB0aTKXoYMKTrEslzw2J5QZ5nSaoz2iRi5rcffLELbA/ft/j82OWk22M77338Ph8CQmsE6Y3LLSxskKdZ9g3WdkzGU0KMdF2LMamJLaWmb2uqssJ1PXEQSRAYhJCoKDBFgdSa0DUQItPplPv376OU4tr1J4gDGj0EwEWMzlivPU3nuXbjaS6XG4zOiaQxqGsSa1SIROEoy9Gguiwp+oKeZOrlvdutfnmeE5zi4uJiUCLxSJXjhv5p3/cIIeh7m7ogyNRKKioIkGVpjr81dYC0RTdtsxOpsNayXC65cnR1F9QmS9v4pm6Z7+8lPyoX0FmC7YmQzHG9TwIUWZbhEdgu9bQ//dmfZHH3FpcXp5ydXlKUE5yLSDV4W8UwKM48eq3Dj56U746PxEq6baVtA/Tx3HSbCz38CdyuEsYY1vWGoipZb9KqUlQlvU0A47LM03x/UFYu8oxoHVqnUao2KjmNrNeIoeHvnEuVc0iV7nq5GoYBKWC6ztL3DoRI9jRZmZraKhB8z+LykmChqfthNQ7Udb/zqfAuDk15s3uvSEVeptXaZDlCKJCJY69MRt85mrqjGFX03tF1HUoZynJE3abgfPhcdV03nNt0cutmza1btyiKLEmbhqT7VFXVjqozn8+TWp4eSI4k/QPPgzQrhEDf9zvdKNtuyPOMG9cPeOH5Z7B9kkBPI9hkpBlCYie4YHc36/sPHB8fiSB9fKT2cNG07alprXd9wZTXuUFUK5HHRqMRUQaUSc3qrErit/dOjlkuLqkXF+RG47oOoR4bzVlLUea7C5royxMuLha88dbbLBcXzOdzqqLAu56m2STgyKDjeX6e2jBKR5xtkrZoOaXrLHlWkmclwacVSkqdfKRcHNw/AASL5RofYba3T1GNyYsS6wI+ClwAHyEvK/KspGstSEVRjliuN4ynM4AB9GF2ue9ms0kU5RDYbFZ0fbLomU7HICKr9ZLpdEyMHp2pHcZBa4nH77brvu925317HaSUjEYjfvu3fzt1INoNWS6pRjld1xAJWNsTgqPrG7rQ04We1ne0vqMLP3ZByiNB+fhtm4tuqQjbi7B1Ei5HFet6A6TqNq9KFovFbjXpuiQ6ttlsaNsWBpEEIC3jWqfW1fDpnsxmaK15+umnqaqKerUmeMt6udpt21mWsV6v2Ww23Lhxgzt37jAalXzvtdcxUiWnOBLIRSmN1gZnw46VmZ77AVSvKAqkShMfFzxZmTyginJE07UYnTOeThIopawS8wAwJt9t8w9X89euXQPg9PSUrus4Pz9nNpsM1blgs1lxcHAAIqK0TBSRvgcCrU3nIeLxMdA7+1Ahm9KEBD1s+I3f+A1UrskLQ1uvmU8nXF5eslgsiDHS9Q1CxGFltTjX41yPtd0Hjo2PTpCGJOEoI+B9kg4XASUC1nWE4Am+Q+CGWXEAlaOqGWU+pWs908mci8szCC2j0rBantK3G2hhUuY0zQmtW4DQSDVLFAgZCbYly3OyvCLLCs5OzqjrGmst0/GI0fwKZ5crnPAJbyozdDZiVVuq8YjCBEZVhpQZISQNf6SlqjS5Dji/IcSOotQ7FWUpJUoLyrIgRkewLZvlBaWRZFIQrUVF8F2LIe0stvdIZZDKJMwoAW9rjPCEvmM0GqFNSdM7Ti4Wid2pBF29YlJNmI1njIucdr1iNh0nQp1Q5MUIJTRt3SGEQauMECUehVAZphyRZRqpCnQ2wyhNLh0ER+sMGztH2iJhKfwlOm/oQk0bHb1QrEOk89D5QBcjtXPU7sdsJd1SYuFBFR9jmi0LIci0QQxAiDzPIaS5sus6/NC837Z48jyBS9q2paoq8jxnMpkMSKAsraSwo/ISE2ff9v3O2KBpGvq+Z7VaoZRibzbn4OBg4AjVO2ZrstyGrCiRKiHgtz6eJtNoKSgyg/ceY1Jv0XvL2dlZ4rQPq+q2cAJ2qcxyudUDZVAjsY+04Lqu2wk9bM9d23Z0Xcd4PEZKyWazIc9z2r6jd4FVvSEE6DqLVhnleETvPHqYeh1dvbLLZx9uZT08g9+mWEIIxuPx7jyKcsyysShdMp8d8tprr9H7ns51OBybrmbTtcPXmrr/4CvpR6a6F4OUIyIF7VYuXCDxwWKtRyqNkQozfFUChLdywpAAACAASURBVBIEIZiMpziXAMSr1YosyyiLEZ4kjLupL6kmFcV8Tuh7dJkAxHhPNq6g6zCqpF2taTc1jCrquk523psmtVwWC7J8hI/Q2S5V79YhTYbJRzi7xoVAkWskkXGV4UNPXphhiw8Yk9xJusEdZLVapao/z3ZpjbV2qOQT0mnbwtp2AraP6/t+V2yOphMQGqTGB4GInrww9G3SJT27WDDfP2DT9YzHE/oYsS5SjSa0vSMvqyTENh7juh49eI9um/iKkPjzSiRacwg0bTIm+7t/9+/wwovP8rN/7s/gbU3TBYp8zHqzoREdQSW45TZl8N7S/ymLQxTAPwXy4fG/HmP8r4QQzwG/BuwDXwX+aoyxF0LkJDGJzwFnwF+JMb7zvk8SI9EPn0jYrXCD/yCSQKYkLiSqs1aCIssJoUE6n+QHRSK0McD9IHmM5nnJ2eklVZGgajIOc2SfmI1SSrrFKbZL+M3lcpl6lb1lOp6waWrKMq0qRZEjhlXdWovSGYiAdamoWSzP0pYrNcH1ZKYkRAnGoCQEb1FZRlXmED1G5en/ltkgdptWMeccmdH0fY9SYtdtSEWN3q1sSiX3kKIoaJqO6ayk6ywmK+j79P4vNmc0TU1UEp3lKFNQVBN0lie7nBCp+4QLUCaj63p0ZohBJJ2oXbcjMT9ThyJ1VdrO7lSq//Bbb/Plr32Ln3j5OX7q85/j469W/OG3vsLsiRmda9DigS+p9R4f7AcO0g+y3XfAz8UYfwL4SeDfEEL8FPB3SOIQLwEXJMUShq8XMcYXgb8/PO79Y5RUQTpn8d4Rgn+k5bGtJhFJMc5ai3U961UqZJRKFf4WsDEej5FC41ySbLx69SpVVfH0k0+mrXHYWhPDNJIXJblRGC2pipKqKJnP51hruX79Ont7cyaTUQKThICzHh8iQum0WsfEpTw9Pd+9DgDnLGVuQAS0EXjvBn5SKpj6vkdrvQvAYnBMLssSeJCSaK13fdJtKuScoyiK3X1SqCR8AfRtjRSRfqjW1/UGpTN8hHJUYfICxIOuQVWN6ftBYVpqpNA7zKgxZlewbj8YiEDXJfMybdL9lowuaL7y9e/y3/8Pv8qq7tnUHZeLJV1rafqG2qZb52pa/6dYOMV0rIcfzXCLwM8Bvz7c/6vAXxy+/4XhZ4bf/7z4EeOFGAPOt7ubDx3eWxI1Km1zvXc7CR4z5Ggm17t+3DZXXK/XzKZ7Q3BrmqZBDuzFZLPtoO8TKBgQUuLrmuBcEpZQgrbZsLi45PDwkM1mw8nJCav1gr5vU24oSOwAIRHSoIQY5tdp4qOUSkrIgxJLVRV4nxxBNpt1moYNA4KI33l8brfu7eToYZ/6lGtb1uv1LrjbIR9PH4w8Ve4iGbc9jFXQekDvj0ZAauOV5WjgOXWpN6pypEysB4/ARXaIq22RJ4TAB7dbNLYfnNV6gbcdnbWgDX3U/E//yz9CiJzLsxrhVMITxDQ+3WoofNDjAxVOQgg1kPCOgX8CvAlcxhi3icXDAhBPAO+l4IsOWAAHP+B//idCiC8LIb58uVzS2oamr6m7Db3vaV2NjR0uJu63jy6pBgtBIIm8hpgazSEEus4mPKjUrFYrRqPRrjUTY0xgFO9pm4bokqVzdJ4YArZvaeo1ru/wfZJ4nM/nrNdrVqs1B/tzyvz/o+69wyU76zvPz3vyOZXr5s7d6qDulloBJSQMAoEBgUDYBAFOY4+NPTPe3cHjNONdZ4/tYXa8Y6+9Y/uxscHe9WCMDdgegYRIAqRWaKlb6hx0++ZQuU4+590/3lPVgrWh2cHziPM89+m+dfveul31O7/3F77B+aq1XoZUqnS5xBRgCoFnO0r7VFMAiyTL6A79AtmUYmg6Ms8JAx/bMsdNmyLIFmvTopGK4/irHtN1/YoxQzFLzrIMz/NUrSoFSaJ08LMkRmYpYehjmIp1UPI8HEcBostlDykzgiDAMgxM3UAKgRQ6luONywshVAYdzV6jWDV6jqOIfAhVWoVhSB4MsA1BInMiodGc2crZ84usL7bRYhtbM9AyZVBsomFrV98OXVWQSikzKeWNKA79bcDBf+ifjeLv63ztxT/z96WUt0gpb6mWS0SJX3yEhLFPEAUEUYAfDukPlLBWHMcYtkGlUgFNIyu2I5pmUCs4PqMjM0kSKpUKeaY64azIlLZtIxzFAdcMYyw149nO+KgeTQAqlQrT09OsrKzQ6bRf1GHrpElOnkESZ+gCZJ6iF2oduq5TqpSVyRfKD0kFFpim2giNsvpo3guM683R1ggoZpdq4jCaUIy67hcjw67sxNU2LorVUZ+kKZqpXh8hZIGmUtMMTafI0Ep50LJUtrYtd1xqZVlGnqigNQx1MgWBmklbllVwnMDKE6JhT0ki2SaDMMEyS4jU4IUzC5BmBUNfUYGMb6WV+NcEVkcI8VngDqAuhDCKbPliAYiROMSCEMIAakDr6/5cJFKX+LGPZzuEYWFHmOnkmZISFKYGaGz2+whRpWQ5VNwm/X5AJkIcU8HRLNNlc3OdSqWC7/sYhkFiWJS9Eo7MqXpN0A1SkaPrGboWExkWuaao0BqC5sQESZJgCI1Lly6xfXqWeW8eLV/F1E2COEEXElOT5OmQSA6RMlW7bZEpScVkiCDDdRrkEZSsclHbob4P1eVqmERBH3TFIcoSSZrEWLqhwNhZVjSWkBTBLvUco8ismaahWwa6mZLFUlnlaDAY9NAsh9BPIbKpTNQYDoPxiaBAKKp6q5WrZCRjjpk/DJWaiVYEvMzwNAtDN0EWfDESrFzgOEpNOpIZWQ5GLiDykXFMlGb4eULgm+zT95Ek60APx3bIs28hVE8IMSWEqBd/d4HXAieBR4C3F//s+4G/Kf7+8eJziq9/Rn4tM+sfClKZKenCRNVuUaiQ92kWo4mMOOwRhX163TXW1xbo91oILadcUjzzXCgpRcMwmJmZwXEcSqVSgbA3CEJVs7ZaLRh1yLkgz8ApVoejTKzrOq1Wa9zcDAZq7632+cmL6smiqdMhzzNswxw3PbZtF1OEtHgdJSO9pCzLkFk6zlaDwaAgyWXjUZMSckjHnzuOM25mivdi/D1xHBMF4ZgbNhwOC+OGkDxDdfKGhSbURmqMmpIZpqH0AkbN22h2O1pNj0qNkYPL6PMXlz6jZm5UhoyyfpIkBIUjy+nnT+JYNpZlf9OqeleTc+eAR4QQzwJHgU9LKT8J/DTwfqFU8yZQKicUf04Uj78f+Jlv+AyyKPZ1AUI5s6m7OCKOfeKgoyTGkz55OsTvryMISeI+CAUkUR/WuBseBZKQMBz20JB0u216/T7oFkK3VdNj2ORpiud5uAUPSgjBli1bqDQaxc8ymJycwPcHeJ6nZL5lhhASSYYmM7L0yvE5aoAajQaaNgI25+OVZL/fVVungoOkCXV0K0asGAfgaJIxGkslidJw8n1/PH4aNS9BEJBE0ZXgshzSXJJkOUI3STPUrFkzisBSYyU1u9XHTZIYN4FqDT0yxR3dOKObRtO0ceM2wgxYlkUQDMe1s8KaqjX2+bMXSMMcEwtTt76pI/xqxCGeRSnpfe3jF1D16dc+HgLv+CZ+ByBXco5oGLqOEDkmGrkmMHQN17bVC5opMwfHtpGZkiEky9F0hYvM85wkl+i5LIC4qq4M4gFx4uMHQ5zyHAhNWcdkOXpSsFE1jSSK0XMVYJphMH/hAnv37sXxTB7+7OeoVst0um1MtwxZikAddSKL0WUKeYZZZKooirBtj6DTw7CVbaKQGYau41gmlqFjGTb9ThvD88YufYwyU64aM00oadooisYUY6HJ8XgqSRLS1EBIge/7VMo1BBpCaMRJQiYNbMchjnJyibJtNBWdWdM1EBlpEpLmKgMbhkW5VFXeprnK/mEYUnFd0NXN47ou/UH7q2tisvFNpDJtRhwn48XDsNen3x3i2h55HGJ+E2IRL4m1qJSSLElJkgjL0DA0FMROg5Ln4OgelrBxDJuJxiQT9WYxCNcxjBKOozjjecYYaDHalijTAYk/HKh6K4qVDKNWHIGWi+a6UGTgLMvQdJ2VpSXm5uZYWlpidWVFycwUR9qo685y9YZoZKRxgIYszLdSNe6RGfV6lWq5hKlrCAGOY1GtlDANjUa9SrVSwrMtdE0jLTKYZ6st02guOdr3l0qlMeZ2VEEZhhJv0IREZjlBEAAaQjdB0+kHIf0gUnRoXUdKRb/OMrUUyZOYoa+2Xs1mcwyYHnX15XJ5nElHgOperzc+LdScWh+j0tI0JQiG4+mEKlkUYPvs6Qu4VgWZQRQOrzo+XhJBquSrY/RiFagLbcwgVcCKHEOzsA2Xsl2iUqpimR5S6uSaRSZVLaSbalMy7n4R5DJF5hkT9QaO5VIuVUFSjJAyyGLQNPI0LbjzORvrSmG9VXCd2u02q6urDAaDcSeuiGUF7jIJsQ2B59okUTieeSrZSIX8GSGBZK4UP4LhQGmfTjSJQx8dSRZHJGE05ihJKUHT0IqZaJZlYzzBKGONgkdl1isExjSXyn1FtzGtKzX3xsaaek0jhU2IogjXUuO5IAjGN+Do5kgL1+Y0TZWPU5pSr9e/ius0GAzGWIL0RcARTUOZvwmBYVisLK8jU+V7KL+Vw/z/EZda91nj8UiWqcxqaDoyyzEMHcNQ8uRxHBKGPmkaE6YJYapAxXF6BUKm62p4PBwOScIIkUMwDMhSSbc/AFGAqDWpaBljZRBj3KSEYcjy8jKO4/DMseNowiBJMoIgIktzslRJo2eZZGaygWubX5VB8jxF09RQ3XGV9mgu06KsCCl7jpKp9ANEgV63TBOZq5ulUqkAV7L2CGb4YrDHaFaqBuU5SRQXSis5aaIU/DTdIJWSJIvZdc0uOp0OaZ4V/08PU7cKjKsa9o9qy1HTpPCkMVIq0TJQ2XM0LhuN5Ub/51E/IArGaJKoZUsYR7RbfVZWN4mSBOObKEpfEkGqCaWeZ9sucZwWDngC23aVt5FrIHSJYUrSLCIIBwTxAD/sE6dRkVHUGzOaY47qJdd1qdYnqNUauK5HszEBhUGLwquq30HXdUzbxnVdyvU627dv5/rrrycMQ+64405s28FxPDRhIIQ6NjWhI3OBZ1vcfNONNGpVms36uMNX2cseN2TVckkFrqYYpJahE4Y+tVptnH2FUDLqI9GwUZc/CoqRl+eoibFte4xdGJESgyDADwP8KEYzrUIfKkLKHMtRBriWZSFTJSJsG/b/p1sfNU+jE+HFaKvRwmGEJVCZXWXGEYprxLF6MbrND0OeeuppTNNSTfLVxse3Jsz+Oy9NQxglXLdByasThj66iNFkiK1r5JmGnglsaWAXHXIsFYUiDXyGaY8gGRBlISCIgljpuJMxDIcMwxXWNzqFXfc65AZ5qpExJEZiOmU0q0Q8jEmyHCoVcB30soeeZURBiGcZ6MkQU0vIkfipBMvCtgx27buRamOWO++4g6prMFkx0WRMFIfobkXhL001q82iEEuHLBxAEuAYGaaIIexiiQTSAEPP0ERGLjL8KECYBkKzMQ01hkqiuDAFljiFm13sS4SR0w5atAch3YFLmtSQaJh2gmElbHQG9COX84tdIgNyPcI2DYxcI89T5X1le2i6hWE6hfyPhmPYSM0lTGI0EeMYkjSOAA3Hs+n6HcLcQDM8tcK1jIKBm4AmyIWGhkYaSRYur+C6pcJL9irD458s8L6JS+aK416pVMYc8cFgQJKmysQ1TdXwW14RNBtta7JUqjlpnhcipwpOJsQIMSRJk4ypmRk0TZCkERQAFtM0sWwXDAuSTGVH0yD3h+iey/ILl9iyZct4+J3KfDwOKpfLIJUobbVapV6vs2fPHuwiG1tWMRbToNNV6s2tVmc8c0wzZXGuG1c2SGEYKgRWmuL7vnozi+N2hC3NkitwPV3XxxaNmqk488NBQByr1yaX6YuaF8WtGmXBdqsLaGPkvKVb49e12+0XmFV1zPd6vTHeNUkSkvwKzmCEL9URGIY2nrUqDpYxzqaj5m91dVWNzMYW5t/4ekkEqdAEnU6LIEqYmp6lVK7S932VNbKUKAmhsB+MEkWv0HSDJJekEnTNwtDtMQdK13XQ1NgnSWMymTPs99UoSwAih0zVbOSqbkoBw7HRDQuha6TBkLmtW5FSsrq6TK1WQ0qpfDi1YpCexNi6oNfr4ffV9ODQoUNqt60bmJqyQbdtG6EZSkPKcvCDEHSDKE4Jwhg/TL/qmB0xU1dWVhBoYyme0bFuCI1w6I9vTstRARQnGWGcEaZKgNiwreJm1jANpdU/anY2NjpkWY6mQRj11fdHKcFwBCJPsSwH3w8xdGtcaqjjWxsrFZq6ThIFKgEkCVEB3xNCw7DM8Xx1tOsH1ZB+rSHu17teEkEqZU6336PVajG7ZQezs1vJckWHlTIjSiNEIYyV5GqeGKXKvUNoBqAVazwDIUAzBKalZoEj6e80UT7uYeBDYROpIUCzMD0P3XaQuo5mWwjLQgrY3Fzj3MVzmJbO4uJlVQcqTBUl18bQJYHfxjKU9cyxY8fYtWsXU1NT1Go1Sp6DbYgxYiiKU4IoxnI8JIJMamPE0ajhUx02YzHb6elp5TefhGR5Mm7udN0kCSMQOmEQK1n0WJJkBpk0SPOMmbkZdQpYLrpmEccJcZqQZjlLi0qZRdM0NBMsU8co1qCO4yipIs+j5JUxbWesiS/ECL5XQBA1sHWhcAuFe4nQDBB6QZl2xo1sGIb4ka80dr7datJc5piOgr4hdSy7VGAcY5JcUWFzMsIkJEpCoiQmTjKSLENoxhhQ6/sKxhbHIehKlzPLJdVKneFwSLVcwTZ1SBPyPFOZ1HJJMkEiwfDKIARxFNLtdkmimIlGHdd1FNFP6CSFUayUEkOHbTMTHH/2GE8cfQzPcTl58iSe57Fz+1Ym6zXyVG2ByuUylXIZ27YxDINhEOGWPJI0o1SuFCJimXrzudJBD4dDhkUwhXGEY6nadqQ8KKUkzTOkgDiDJDcJkxxhGpRKNr4/wDJNcqEhdIFp6oRhTJzA4sIaUoBt6ySRQoLFgc+wP0BmijQ4Gn3JVGVt3VSlSpqmmLqGIcAf9snjiDgKirGZjm4aBTJLmVVEUTgWgBKaxC15Vx0fL4kg1TSN2dlZao0m5y5cxHI8Zma30B8O0AxBmqe0um2kyJW0jlRZNU5TclHUn7qgP+hhmIxdWE3bpVKbAE1nZmaGMPKJoyEMu1i6gWlYEGfolg3CVPC9XGAIg1qlymSzgWtb+MFgvPXJMxC66sJ1JMPuJsNeFyEE8/OX8Aue1OTkJIYmaFTKJHE4lsbJUzWSKbn2uMvu9XqKLhIl46yTpRJN6CwuLrN79250U8M0VY0tswy9OHalVMDlDEkuTTJpolsuuQDLVavhOEqLbB4iSYsxms7KcmtcVgTDAWQplaqHpueKehKHSpzQ0MZduq4ZDAYKXpznuboJc4W1GGnnKIe+bLzC1YqbSRYSnv3hELMoUa4qPr41Yfbfd+V5zmZ7g6mpKcIgplZtMje3hVq9oWiwpKxvrjEIfNCUw0ec5kSJwlFmWUIY+mxuriN0iJOIJE0wDQeEhWN7ZJmk7HpUPI/25joUChoyV8EhJSAMhTrKJRtr6zzz9DGC/oBaraL4RiWPUrVCmmRKRSUOKHkWjm1iaFCr1bAsi83NTbI0YdeO7Vg6OIaOyFI0UnQhydN4jCtI4kgJVhTjnCAIxmtVIQT1ep2tW7fSGw7GmyC4Qu8e3TCZzEkzSKWO0G0SmVCpVYrxUKa4SdGAIBiqpkZz2NwccvrUeaQmSGIfwxQYuqDkOjiOha5r6JaOZRmYhnreJEkwLAUyKbkOhiaULCQSWeBgoyQjTXOCKBnjEMZjM1TD2Css0q/mekkEqdAEm5ublCpVesMhYZzglVXHvLm5SRyHrG9uIARKy7O4q9PR3l2XGIZOqeSOO8kszRG6gUBHd10sz0NoKPluy0Q4DlkmEaaDZRUgXq7UTpPNJi+7/Q6ajRqPP/4427Zto1Kp0Wq1rwzUhXJFzvOcnTt3juvFarVaIIZ0JpsNJhp1siTGMg2SOEITkGcpXsl9EcJIjvGieQ6lkpLm6Xa7nD59eryuTKIYyzDRCzymai5VcIRxiiZMJRmU59Qb1WK4biNlRiYTWt0N0AySOKNcrnHp4gtIKdANMHRBlqntWJLEGKZSA+wPuuNtXC4Yv16j2WnZc4hfNCfVNGWDfsUVT3sRTSaj2WySyW+zxklDZ6oxydrieaYnXBYWzrC6ukyQ5ySGTmZlDNOQ+tQcXT8mzBKCuE+Y9qnWSuhaiswtKpUaed7HMm2CIKE/XEUzNdCnoKKxnlfRzTpaelkBOjQPDInMi/WHiNH0rPD/tImHIX4Uc+8rXo4MEza7IamwyBMfhusYeUC1XqNUq6r6WAjamy2mJ6ewLYellXWiXKNasrANiSbzMR1D5JIkDGhUPJJggGmBaeQIEiwjp7W5jolBxa2zvtDl7je+hSDP8IMOP/ez/wua9NUsFY1U6rSDCWKRkxJgouGYJo2GDTpoRh3XzZCZT9RzEKIHpsTPNPp6yvllB1JBlgaE/hrLy+eplGw0qaFJDd20IUkwyJVGaZqShEEBZNFxSzVEHiBkiGPr6LrA1A0sw8DQdMglQior9zDwsRyJbn6b8e5HWqMnTpxASskjjzyC7/t0Oi0mJ5ucP3+eUqnEyZMnx+OMVqs1NjrICtOHbdt2UKlVAWW5k6cJMsuQvS5pkig3ZNNiOBzCCKQxokpISIZDdKFh2bbaic/OUqvV6PeHuOUKSaKwpJahI0i5/uB+bjh8LfV6neXlZSoVZaBbLpeJoojp6Wls28ayLEql0hjjOhwOidJkzE8awfsEhScqGuVKDaEbrG6s48c+a2truK5LvTnBR/7qo6xttq6oAvo+QdAvBvLJeJQVRylSGWThVTzSVAlKjFSskyjAMW3OnTlDnisWwOZmm9nZWbRic6RpGjK94mz3tVJIea5ALaZuYOg6w+GQTqczVmYZ/anmrgFSZvQ6XSUVdJXXSyJI4yTh0HXX87JbbuPRRx/lwIEDfOmxL3HHbbdy9txppqcnle1L2RtbG7quevM9T1luD8OEMEpZXV3HK1WoeCVs00TkOcK2xy8sea4QSmlB9MvTgqGqNEFHUjKmpjOYnyeKIjY6PY49c1wNu2MfZEo07PPKO29HlxnrG2uYlkGjWQchWVldZtv2rbwwf4lev6u6dsNCM5UGaKms5G5KpdKYFiykykq6ZpFkgihJuLy8Qq4JMgHLy0uK3m0YfPHLX+FVr3kNpusVpmo5QstpNOpjaaEszUnTXGmQ5oJKrUwUJ+i6hsgNkjjEtgQi07ENnYWlFfwgolarsbG2QhyHStzCcRCaouCMMAOjv49WuUpMIlV4W8dhz64dKJFgY1yTKpCNWrSsr6/jD77NhvlxHPPM8Wc5d/EC93/X2/A8j1e84k42N9ep16tMTk6yddscWZ5Qq5XY2FxFkhX8dBvTKVGrTzL0Y547eYooVAp2MsuRaUqeJkRJzNLSEjjOuAnI81z5X2pybK2dxxGpH6AbWiHvk3Lm7EW279ylRBtkjiZjJuoeg06LLAxoNusYhkan00LTwPcHnDjxLJub64ASURi9sWmu5pCGaWHYaoYoNKOoswVRnNNqDbi8tEFnMGBqboZu0Kfd7fC617+BQZzi1Zu8/+d+gSBUYJw0zXFcjdtuv5lqrVyMyARKa0MnjhMcz1K6qiInTzV0mWIbOTIBTeZcXlrDccu4Tom5uTnSKC6mDFeYrC9Gd40ypOd5CphiKC3VEftVCKG2hkmiRmRSIonYsnWKUsmjXpu86vi4GvqII4R4XAjxjBDiOSHELxaPf1AIcVEIcaz4uLF4XAgh/rMQ4pwQ4lkhxM1X8RyUy2W2bdtGr9dRHXoc8/DDD7O6uorjWDz33HFarU36gy6tlhLh6vV66vtNk8bOPWRSFEINJWyvTBhHCNul2+/R6fV4+OGHYTAsXE1ybMsgL1BHcRwjkBheSdmUhwGh7/Pww5/m4OEjLFxeVIGdxaThkO+859X4wz7lcpntO3ZhOx5hlCiPJt1U4GLLYXVtg1arQ6c/wLIdcjTQDPIcpc6CIM8hjBL6w4iFpVVWNjp0ej5CM2j3e2QatNttjp04TpCk2JUa//7Xfo1Wr4/QDRzbQ5IzNTUxdrLzvCs40CSJwUhJ44yS61AyqzTqFbI0UPpVMiHOBWfOXcKwTBzLRiCxDDW2Mgti4AhkPbrBgbH0UaNaIU8TRJ7Rbm+i6RCG/rhBMm2LKPbZsnUSx7UY9vxvXZDyj4tDAPyklPLG4mPkO/pGlOntPpSf/e99oyeQ5LS7m2x21rA9NRDfuXMnBw4cxCx8hF71qlfiuBZZFjM1NUGvpwxuDdvFdktQ9nArZa45sB/qdWg2acxugXod03ZoTDQ5cuQIvW6XLFHSiXmejbtw09TptjYJNtfRaxUW5i9Tq1TYt28fC4vLSE1HN4R645KwWF8aJJkc848ajUZBr47GELYwVIuFXEIYpwqjKjQMy1Ir3izHLZdIZE6QpASxRDccHLdKnOWsrKzQaNQJopDnT59iz7UHcKpV/ua/Pcj1N92C0A10U9GUc5kyOzs7PpallOiGYDDsKeG2XFB2TVyzzNLCPD//iz+DrjmgQ5YbtNo94jghiWLyNCEOA8izMep+BHA2TZPZ2dmv0jIIgwGOa5GkEYaulhf1iaYKMk0r5CozDly7h25rnV538PVC4psL0q8jDvGPXW8F/rT4vq+gWKVz3+h5nJLFzp07uHDxXAE2qdFud0jijPnLl1hZWSHLEgbDHpNTTUZCDHEQqBngwjxogv3XHmS4sQlxCqUq/bUWjudy5vwF9l97QPkUhT4Utji6rmFaFn6/h2kYuOUyi8+fVGtCQ6Pba+P74Rg6N5K9qdSqCNNiZm4H6+sto/fb6QAAIABJREFU9u49gOuWkVIjyyBJcgzDplSqYjtugQ+FQ9ddXwC0LSxHCar1+gMSAXGWo1sullNR/lOZaiq3bd9CrVZjx87d7Nq7j0uXl6jUJrjv/vuVdLiuBMQGfZ/9+/dj224BmUuQMsH3e1RLDjoatXKZNM554+tfy0/8xPuRQifKIqRmIjWdzY02ErXuHBndjRqkcclSEARfjMrXdLAMnWCo+Ff9Tle9TpXSFcnOLGHn7i0YpiiG/1d3/f8Sh5BSPlZ86VeLI/0/CaUBBS8ShyiuFwtHvPhnjsUhBsOAhcXLPHXsSSUrXqng2C5JnHHowHUsLi6ysDhPq7XBrl27iKKAarVKGPnjTcanHn5IzScFBEkMmo4/9Pnzv/xLjKlJ1tbW6HQ6mKZBFITwIl2lMBhSqtUolz1IEuZmppmcnMRyXXbu3DlGTI268HK5zKc+/TBbt+3ELlWUKVe5xnCggNVRmJAm+fjxWq2G65aoFLaO5XL1RcIPthK61QWZEEzOzKLpJp5b5W1v+25mZ2fx+2qQbzk2H//kJzBcG2FZfPmxo2OmaRyrScHuXde8SJonJIwChAZJ5DPsDPCHfTqtPlPTk9QnSiQp5CIHTTmCzM/Pk8UKI+A4DuQZZFcEdEeaAMvLy2N8gWmalBxlZiYEBfhZ4+DBg2OAie8rZJRlaRimNubrf8uC9GvFIYQQ1wE/C1wL3IoSLfvpUfz9Qz/iH/iZY3EIz3U4sO8GajWT4fAyjtHk9IlTuM46504eQ5eCPXt3IxyNk2dP4Q9T1pa7TE9tJZQxlruVM+fOoE3NEMkJLndTIqfOJx58hn/2z34MvD287r73MbVlGjExjTW5G7Qu+rBHlGU4/jqytaI0SYWB5pYwbYtw0GNtZZU0TlhZXqPd6uK5Dg3X4Lve+Bp+49d/lYWNDkbJIMwigjRks9NWyCzLxnBKeNUGQjfJNaFWvGlMqWQz8IeYrksMJEJHk6qs6Q43SI0huR1jVRzOX1rh8mKXRNZZ6Z+ln3b4off9G7yGzQf/5BN0wg7dnkmv7+O6M0zMlAizDfLcQtMtsqRBbizgOA6vufe1XFy9wLt/9Lv50Ec+SZzMYpgOzaaGrsUIw8JPbM4v9ugME/wgxHPKOMKiVCmTZDFJGpATgEjwhz2VJaUgShNMmeCSkvs+SSJ55tkTBKFPuWQgZIebDh9mqjxH3ZnANv6J1qJSyg7wWeANUsrl4kiPgD/mCnN0JA4xul4sHPEPXo7j8PQTT+L7Ps3mNGEYMn/5EpcXF/DKHoNej5PPnaDbbRPFAYNBj4P7D3D3d7yS2o7dhQtJAHkMeUIc9Tnx3DO84533Y5iSv/iD3yULA+xSGb3awCrVwA/QdB0tz0mSlCRX4I48zxn0emyur+NUylRKZVqdNqapOPWDwYBDBw9Qr1W4702v5//4j7+pxjGy0PPUBIalrMEbjQa6buB4Lo7jIYROqVShWm9w0003jY/BLMvQC2NZz3XZuX0Xruty/Phxwijg1a95FY2mx+ZazM/81E/xR3/8f7K6dplSpcpb33o/w6hDluf4oYI06rrOYNBjfXMdPxySEfP0s8+wZ/c1gMZzzz03LnWklGSpHIeCruusr6+PqSL9fo92Tx3dtmmNOV4jDpQQQskfodi5lq4WIyOh4HqzSa1RxzQdXv+Ge0lljluysOxvIej5HxGHODWqM4WandwPnCi+5ePA9xVd/h1AV0q5/PWew9AN3vfPfxjX9vCDjL3793H81HOUqzVykTM9OclEo6GEDOKYiUaNer2u+EStFlEw4K677iJpb9IfbDJ/+Tw33XgIrWKjVV2qzRJSyxDVKkGSEWk2lOokcYylSTTLxvJKCE1B7solF8cULF84RxoHSmQiT9jYXMPUJQevvYY0HLBr6wz7dm3hTz78IaI0odKsU2vUSbMMt+Th+wG2aWGaigZjWQ6VSg2ZCwJfgVVsy6VcrQPKaMJzy5TLZeIgZGlhkWv37+fyC/NEyQaXzkR84m8+w/HnT/Fv/91PYHs6M7NbQE+J0owgilhYvKQALGUH3UxIZUZjqsRg0OPDH/5z3v2e7+X48eN4nottm/j+oKBQC7JEIbx0XefJJ58kl2rn75Ws8aZsJBkkpZI4sm2HklfBEkrnSiAJ/SF5qixzojjgxPPPceHSPAevO4wUOSkRVulbi8z/x8Qh/kwIcRw4DkwCv1L8+78DLgDngD8A/sU3eoI4Snj0C5/F8zwOHbyRp599mrteeRd+kDC7ZYZquUyeplTLHkkasbAwz5133cGjjz6KZpoIzaHvK138Fy5dYsvsDCJXoq9kknte+x3EWYjMM9yJLfz1f/sMCBPTcsDS0B2PJM2xyiUgJ01CZJogsoTN1RXWNjYKwLNJt9MiSwLyZEhnY4U7brmeNE35+Mf/mtXVVdxSibTAxypVPIHMNXTNKkZFCvs6MTHFlu07kJqOZTk0mxN4nqrxFhcXqVRq6LrO3r17WV1dZf7SEqWS4K67voNf/KX38+XHnmLvoSa/8/u/xWZnSC4lS4srPPHko8RxzPYdM+RaSJxGNKcdbn/5HQRhzFNPHlMmvMMemp4X6tNgaKbS+S/Ic51+j3a3A7raFplGIf+Y55w/f540zRFCJyjGd1IqOXldaMgkYdDvkOUJC0uXQRe84u672LFrO71hH4oFxbcsSKWUz0opb5JSHpFSXiel/KXi8ddIKa8vHvue0QSgKAH+pZTymuLrT3yj5+j1euzes53Ll1/AcetMTk/x6Je/yMHDN7K0vEAYRERRzNTUFN1umzRL2NxcZXp6igtnzxKEOYsLazz04EPMTE4x6HSJwxj8lC89/AWeePLL9Ic90jzni1/4HN/7fd+PjBIQAumrFanQNZIwRGgCkWcYuhKhWF9fV+JjY757RhJHLFyep99rsbG6wvd9z7tpbaxz/PgznDpzknq9SlaU4c1mHUO38EoVhK7juh5CaLjl0higMRwqNxPdsBBCofL37NtLvdlgenaG9c0NHnjXO9mxq8ni8hl+7H3/O7/zn/+O2T2C1U7A3NYDhIkCoywsnWV1aZVeb41OW5lNHLhuB6fOnOS6Izdw8dIihmWhG5JyRQmTWaZDEA4J/eG4mbzpppvUOtqrgCZobWwWEw+Dcrk8htplmcQoKNFSSkxdcZze8d1vo9tuk6cZd999N7v3TjIMNkjSiM32gEZ9y7cuSP9HXI16g0sLZ5nbOgtY2I7DDTdcz6Vzi5S9Cu12n1tvvZ0gCHjFK+5kEPQ4de4ktckqJ06f4PzFC0xMNTlwYB+uY/HK77iL+RdeQMYZ//eH/5K5uTmC4QDTELzi9ltJ/QBkRp6mSvUuiQr6cQpZQp5FJHGM7ysm59LCYqFwXPCpMsnQDxgMfNAN4n6XH3jPA6wvL9LtbOJ4NlImuCWXVqeF7TpjtJMoUOntdpvhsI/nOVTrFXoDnzBJkQJlMuHYrK2vs7q2RpKmPP3kKQwrwqvkNJoaf/D7f8Zdr7qB2a3w5re8lYlGlUG/y+JiB9d2ePO9r8cwFIK/3nA5f2kZr1xhOIiKjtxgMOhgWyZxmFByHWzHREfS6XSwbZt+b0BvMCSXgkqlNOZW7dq1CwDdMtEtkzhNMUwF5hYyx3MMssjHMXRCf8AH//BD7Dswxwf/5L+wsDBPHOWE/rcZEQ8hCKI+R598nKefeZ4gjlhdXWXfnsOcP3mBa/Zdy3PPn0E3baIkxg+HPPHUY1iuRiIDllcuMTNbpzdYZzDcoN9dY3V5HmFofOADH2D3oevJs4y//ehHiNqbGCJBJCGaoZHrOnkSFwa0ksjvo6HIb2fOnufcpcuk6RXim6abNCdmuPbQEaRmM/Rj0kGf7toyb3njd7K8cIkoHDI51WRldQGhyTGo2TAMlDq5iWUZTEw10U1Fb04kJGmK6XoIy+DRL32JxuQE5y5eIJUpTz5+gkE/Znn1HDt3T/Nz//Y/8ZGP/C2HbzjIw4/+FZcX5um2N9i3x2Tf7l383cc/RuB3yZKcLPWxLHj++VNkUkMTBlE8JIyGxVYqp1rzyLIEPxjy2te+hocfeoQozXjuxPPkmcA2TZIkYn19lXZbyWAmcVqYb+jEMiPO1LxUE/Cxv/ooeRyhA6+482Wsr1+mVrOpVVzIUkzt6v3uXxJBmqQJZ84/z8yWWZ548uligyPJY433PPAeWu0+g37A6TPn2Gy32HdgH6utNf78L/6cjc4GTz77JQbBBn6wSbe7zKX5k+Qy4Iuf+zSdzgatFxZor23wqjvuQIt9ks01Er9fcG0MLNsgCn1kFmGXPfSKwmHu3LObtY3NQm3PQ6D4/Tfdciszs1u58aZbufWO72DH7DS2ruH3Otzz6rs5dfp5dF3QnGpiu0ooIYoDkkJpLo5DkiwuQDIGSRJh2haJlLR7XYIopDE9yU0vuxk/VHBAzyuzc/tBPvaxs9z68gMsLXV4y30/wPbtu/jyE0/xjrffx4H9e6lVPfzBkEG/S8m10VE3wY5dWwnCGE0zqNRrBWJqBJcTmKaBqStV6nvuuQchBJ5bZn29jRCKUOdaNr7vj2efwFhULVei/wx9nyxJiQKfTnuTbqvNT/zP/xO33voyarUKr3rVK3nD619Hc6Jy1fHx0gjSxGfnzD5ay/O88hXb2TGzk+XFFqeXv8gTp85QKtmE0ZDmRJ25uVnW19eVfj2CenOSm67Zw+VLj7G03GV+pcNmF/YdafA7v/f/YFbnOHPhSzzy2YfJUx3TigmiBUzNgtgij/pIXUlwo1mKixEEyDSh3+qwY8tWkiCEJFFSPAnQ3IU+fYjtR+5m64Hb2X3Hazh052s5fPNdbJncwS37j/D8k8eU8rNtIWwHw7EZ+j3lnZTb6LLC+oaP5dWwKyXMakDQr1B1alhagJborK0vsOewxz3334LMPM4e3+DeN9SoN2qE3jmeOLrO4sIqr//OBvv3HeLCxdPccsdh7n7jq2n7TXYf2MeWmYQ5YwutM32GmYOXr1B3Bc09Bzh8ZBfICD+pcmD7NobDLlt2bOcHf/hfUSnNIXOHnh9w4vzzhHlKSsIr7rwNS9dwnSqpNPDzjNQWWIFyOzFKFlKLma65fM873sz2XVXOrT7HxuUVKq7F0898kQcf/msWly9cdXy8JILUtmxOnjzJPa97PTMzM2zfvo3+oMvKyhJTUw2C0Ofmm2/E9wccO3aMSqXCrl17SJOM5eVV4nyTyYlruPctd9PpDXnm+ON8+dHH+M3/8Ms0d88wPbWFTrtHGEX4Qcjf//2DYBpgXnHX8EolBeVLU9B1Tpx4nlangxRQr1cVUkpXmyeyjHKjgVaqUC5XmZ7ZiuOV2bvvIPv2H2Lv/mu5/61v5/HHn2Bubq7QxFcqJHGWqnJmfY1ut0un02FhYYHhIKcxZZKJANNskiQmJ0+ewHJMbrzhVmZmpmh1F4kTgzSRbNsBp06fZ252F/v27yCSfRozJZbX2lieTuD30IWG42W0OpusrQ0QWY5huiwvbXLu+VPcdNMB0riDYWhqHW3p/G+/8PPqd05j4oLqvbrZwikANKVSiSSOCQZ9kiikWinhWAamZxPFMZ7n0ajVIZdsndvCe9/7XtUYMsmJp+c5dXyZm468mqnG/quOj5dEkAahz/TsNo49fZKTJ0+ysbnEwWv3EUURn/v8Zzh8+ACnTp/g2gP7CYY+WZLRaXU5fPh6brv95VxceYqNDZ2ILucunCdMBly8sMjG5jl+5ad/lKWVNtOzc/i+j1ef5F3f989BZvibq4rWnGdKM0oIpbKV5Ry58SY2Wh0uzS/hlhzq9Sp5nuG5Nmeef56Tx45x6umn6fd6bHaGJLlJfWYH2/cf4rZXv4HrbnwZP/6v/jWPfuErzM7O0hsOELqSY+wPe5RrVTKZcuHCBVzXxbVmMJwuUd4iDExKpTmaU9PMzMwx6EcMwzbVCdi1/XoWl1Y48rI5FhaWcJwmG611VjvnufWVB2lObeNN991Nt7PKqRPPsu/aKbyKTZzY/Jff/gDl2jQzU7vxbIe77jiCKYZsnZul3d7gtttu4+6778a0DRJSwiwhExp+nDMMYoTQ6LR7mJpOo1LB1XX0LKFiW8yvryBcC98f0tnYpFmq8ImP/TUf/KM/Vt6j0ZCZ6QZHn3iM5eVFwjS46vh4SQSpZmikUvCVrxzDcmzOXjhJkgQcuf469uzeztNPHWXXrp0svDDPju3bcW2HwI84/vxzZFnG7PZpWj2fT/zdp6hPOuiaSbc3wI+Xeev99zLoR2zbsYMgDXnowYdIg4wsDtCNHKvsoSMKXyelrtdpt9hotYmTjNtefiemY5ALSaNZo1Ty2H/DEQ7s28+ObduJoojLS+v0/Zh+L6DXCTj6paMIzaYxMc0P/8j7eO7k82zfvh3TtmlOTVKq1IjiGMcr0Wg2MU2TwM/ASHFLNuVaGdvxKJfm6HUjFpbOEqdtduycYegnXLh4mgsXlzl7/gy/8kt/iKHVKU1pPPrMg3SGCR/809/lu+5/HSKPaU4ZHD12lGEU8ODH/ogok5w9Pc9tN97MFz77Ke6+8xa6fZ8bbjzMu971Tiamp9BMjUzGWI6uZHrM8lii/MTx48gsp72xialJaq7N/W96A3fd80pMx8QtlyiVXAxNxzYtDKEx7PfZubPG7bcfZmrSZu/+Odqdr7uE/Or4+CeMvau+0jSh0xtw4MBNLCwu8olP/iVr68sYQqda9ihXPFZXlti75xp2bN1O5Edcs3s301OznDl/jn4/45Y7DtFpC7xazg033Mn2XVt47OgXOX/hEssrG0zNNjl2/Cle+8b7MOwyeZ5hWRBttpFphmVo5FFAniklj25vwCBM8KOUcrXClq2zmKau1n5DnyQKcT2bekOBRw4evA6JQYrOzj37uHDpMlGckyQZDzzwHh57/Cim7eBHEY3JCZqTk2y0WpSqVc5dvES95mLgkKUg9AHVukkceFw8v8bS0nGaUwb12gxPPPE4jpdx5LpD7Nw1y/RWmGnezFeOfhZhR2CYOBbc/R3X0ah6XJq/iO7q3HHXAZ577JN0+j2qFY9hp8Xv/fbnCLp97r7nO8nykH/3736WZk2RBiFE1zIsw8QybF64vECa5GO3wSxLeNtb76fXafOFRx7i0a88yjD0MW0DoWv4wYBtW7bw7gce4OzJ02yuhkxN7OI9D/woj37+BAf23n7V8fGSCNI4ifjAB36LH/rhf6l459InyxLm5xewDINms0nJq7CwsEA08Cl7FZaWloiTkNX1FbpdQbWuQV6iXK1w8tQLXHt4H1NzO1hcWuWJJ59ko72C1CKWFpbIM2WwkER97HINXVMo/lHHOgyVF+fU3ByGUyKIIrIcdKF4PPPnz2KXHFobK8gsYn15kWDYR9eUol2p0sCrNlheXcO0XfxhyNvf8W4ee/wor3r1PWiWw7XXXc++fQdpNia57bY7aLcuMzUxzY//i5+kOekyDBfYtmUn+3YdYm6mzvVHdjBZnyIKEq4/spssluzaNUejASefWafXCbjuukNouvJL+p3f+jX8/gZb565FuBZzW0w+8HP/miBKMOyAjaUL/PiP3cvFs2d427vexP1vuRfXcbh4/gLvfufb6LdWyOM+WhZRtV10XWA7Jvv27eO+t7yJXq/HRz/6EcrlMrbrsG12hr1799IN+vSSgFSD9c1NDuzZz5njJ7n5lpv57Gc/y+bmOp///OdxnG8zcQjdEPzM//qTnDx1FtuzmZltcPi6g0w0Z1hf32Dh8hK6bhAMfPIc7n7lK6lWqxw4sBfL0cninEcf/TJh1OHyxZByzeb3//AP+MuPPkzL77Nt+xZyGfH5Lz3E3NZZnj1+Er3sYtmCfDhEpsr/SGY5Ms/p9XrEaYZpOQz8ANstMRwqn9FGrc6Oa/YQ97toIseseDz4t3+FWy8TBQN0BJcvX0bTdSq1KidPnUHXLZ588mn2X3sdH/2bT5JjUKlNMH95iYWlVQQGwXCT9773LTz8qUfwhymG6TMcvoDfHzAzsZPrDu+m0TS49aa76LTazM+f5NMPPsH1B6/h3OlL3HrD7QSDhN27pnn+mdOkIYg84Df+/cN0gyF7925l+dRZKtUJhOgyMaFz8sQZ0rRLoC3w4Q/9KQ+84+1UXIe/+auP8Fsf+GXi3gZH9u+hs7TIn//Zh7jxxiMcP/4Mf/Ff/ys7du1EMy2iLCfXdLZPTnH5hYu863veQ3myQXV2ijhP+b9+9/eYrjdp+Rd57tyjXF59jlfdcwOf/vRfXHV8vDSCVBegCQZ+yNzcHDt3buPgwYN0Wh0c00HXDWQqOXTtYfrdAUePHsW1HZoTddbWl9mxfQunn3uB7//B+/G7FT736Kc4cPh60qSE0DMuL13m4vxZ7r3v9Rx79hlKpRJ5GBZmDJaikxS89yiKsC2XJMupNyeoNZo4jodu2rhuiR/8wR/kiw89hBDQmJki7G7w4+/7YT7x4T+m2VD6pNce3E+1WsU0lUf95kabRn2S647cwLPPHifNJY8ffZJtW3dw7ux5yqUqM1NNfvt3fol2u41nTTG3pcncNsHMdIONhYR2a5UTz32BZ5+8yOL8Mtu2e7zmVTdTr2xhONhAlw6VUoNef4N91xzg1375B9i6ZZJDB7fRavt8+dEv8MgnHuE7X3cfQbTOux+4F6FJfvFX/g2t4BT33PNq/vaTnyRLU77rLW/i4tnTXFy5zKtffgd+p8MDD7yTo0cfpzFRV8rSWUqGRAq4+ZbbGGy0cSybD374Q3gTdbrhkAMHDzJRq7NtapYHH/wcs3O7CUOYntzBfW9611XHx0siSJEWndZztPoPcvia11OpWTz97CP0ByFuuURrcZmFCxc4ct0NrG+0qTdmuDC/wKcf+gye59Hqtbn2piZ///DHmdgR8M53fS9Hv7DGj/zQ93P++QvM7i7zxNFnWXvB5+G//3vmtpRBE/S6udLRjGLyNMMSFqbhIqWyCR+GAVGeEGQRzckG5bLHr//6r/GK174Gs1oiGQ6RQcr0jlkqZYtzJ59i0F3g5DNHuXxxHk3UQc4g8hKTk2X+9q8/y0+9/wdIuou8cPIz7N4+yfa5A5hendff9Wp27LyG1fgCrWRVoeBZYb51lNWwzcpA5+V372Q4XOLul/0Ih67fx8W1p9h97RGm9m7yqc9+jpKfUolt1qMXaNkJz59b5nu+/824VRgOQhp338lDf/fb/NZv/Cqf+NKjtJ0O5xcX2TkUnDh3lt2Vvbzz1ttYO/0wSZYyPX0XxvZt7H+NR5gI1jtrOF6dNCuhGQaDaImhn3Nw373smNmKF0gOVK/htut2sPuIw9PnLmOW9/Lmt9/Lyflnue3W65kpNZi2t3Li6MpVh8dLIkjTLOae176TxfUXOPbcMzQaB+kGy/QGsLjWYmpqmltvfzm/+R/+I1NTU2y2W1x77X5c11PiW3HKzp27WV9r0x8M+eIXv8h73/tufuEXfp6f/pmf5MA1N/He9/wQzz5zGsusUK42ieMY17MhCzGswkFDyLFevK7rCm1umMzNbWVycpLQD6jX6/Q7bdaXFonjkMce+zJxP0NIl7m57Xzp0a+we/dOPFdn0F+m055n126H5csJi2tP0d50uGbfNGfPLXDPm9/I7M6clZUBqUhYWF5A1+Htb7+f6elpFlfW6HV9Tp+6yOvuuY/VtR679zR4/PHHuXThIrt3zVGqaEzP1Dhw3Rxx1kNm9f+3vfMOjus67/Zzt3fsLnpfdIAEQAAEe+9FJEWq925ZkWNZtmNZsqxIiWNHsmRLlq0uyrYKJVst6iRl9opCNIIkegcWZSsW28v9/gDsT8kkljLjhFSGz8ydPfc9Z3bOi/3NLbj3/F7U+jBnznTicELfUAMmo5mi2blM+Txs2ryGG67/PpEwpKdnkJaSR1JSCkJApLxCQ/WCfMRQEk8+/gYvvvIQzz39KNnx81mwuIiW5nN4vVG0+ukXUlKSsonhxeFpofVsG7PnFGJO0rBv3wlGRlzEpE6Cop1fPPUcs2dV8vGHH2E0Kfl4zxuYUr9m6+5VaiVP/uYFaurrmAp5UakzmXB7SM3KxZSYxJQ/RpwxgTiTEY9vCpt9DIlEQpzBxJzSSiQSCS2nW+npHmRwwIpCqaKuoQb3VIz3P3if997Zy7+9vYdL1l+BXKaDqIAgSFGpFYgEiUQjKDQqfIEAXq+XsbExfJ6paec6EUaGrNjG7SSYzQjidHnCmpNHCQR9mM1GpFIdVfOW4PPFqK6eR0f7WSLhSfp7W3C5ejl2pIkJdz233vBjjp78ELUym01b1lA9vwSnR8KJM39EVIDDOcXiRVW88spvaGvvJhSOUlRUgEEfj0KjQ21I4myXkwmHncnJKQSCxKIeNm1ezYDVSkQQ0RjMRCQBPttbi0qtYHi0l6BPTsHsPO74u28yONKNVi0jKTENmVRBQ+0Z6utPsm7JEq68ah55s5KYCih4+OEHcDo62LFlI5euvgWjKYJaZWTxolW4vQ7Wb1yHQmVArgpS1/QWUrmMVetXojfKMSVkYRuPklVowB3pYfHS9YxbHdxxx520d5zlO//wDVrbD31lfUgfeeSR/zn1fUVefuW5R2ZX6dGqjeRlV3PZjsvo6uwmGJxk7ty5CDEJn+3ZgyU3B51By+iolb7+frQaHQkJKbjc08YGySkZ2CZcDA1ZybHksm7dEswmAwODVjQKJVqlhmXLlmOMj0cUBIJBHwq5Aolez9H9+5HLJPg8HnQ6PRKplFAkSiAQRKpQYrc78Hu8REMBNmxYjlojw+/3kZCYQFhU4PP5OXHiKJmZGSQlx6PTqrDZrLS0NGAwhZAKmcyqSGFW4TraOo+TmZNHRPBR2/oJGzdfTdQXwZAocKp+kPKyCtp7DuL3iphMmZgSwljHJrHbu0lOjsM6HCK3UIvZlEpjQyOTUw580SBhTwxtnIDVPsn4mIf/+NRHAAAgAElEQVTAVJRAQIM7NoFakNJ31sXCFctQhOPZeu0aUtONKKeUpOfFsWnlCr77vR+w9pJtaBPN/OG99/j4gwMsrF7G0SOHaOuuRxrTMT4xRv9wO65JG9k5WajVAh1dzZQWLwGUKPVytIYEHJ4oN37jUtram/FPKZg/t5jZRSVcd9M3uOW221m4bA2ffnjK+sgjj7z4Zfq4II6kvik/zz/zc3IzCyktzkCCBJ9NJE6joKHmFHqTkYgg0tnbw9DIKAsXL0UqlWK3T1Bz8ihDI4NMeXwEAzFyLIUYDEa0WjXt7efw+4OUlmcyp7qASf8EzkkHUrkMpckMKNm79xDIJCxZsoi4uDh8Ph+Tk9OGvm63G4lEgtfrRxCkCBIRmVxAYdAhl0tpaGhApdZz5MR+7v3+3RTNLsTj9RDwh3C7vJSVziUSgPVrt9Hdd4SG2n5O1u8mxzKX995/i9LyYrZvvYn9h9/kSF0TKxfdiwQnp0/vQUk2V994CZP+JqTROAL+QcoritCa5Fx22TY6z4wSrzPzowd+TGenlfTkZKSikqGRNlzuKRITjHz/vhtITbeQbcmgsLCKyoqF6NVmXnj2aT779EP++Iffs/vzt1FpRD7a/QGbLv0mb3ywB1VSlLwSCz6vnvExPw5PL/fc+WNe+e0zRIRJMi2ZNLTW4/YO4ZkMgD+LhJRkDh44i9sV4uy5RlwuF08+tpPZRXMYtnbQ322lILeMm66+hdtv/RZ79nz1I+lXFunMitFGQRA+ntnPEQShRhCETkEQ/iAIgmImrpzZ75rpt3zZd8fEMA/98DEOHvyIn/zs23zw1h5kcg8piVkU5pXT3n+WTVs3Ulk9F53eSFPTaUwmM5asdNRKUKmn7bojYRHXZIDXXn+bGFGOHDnK8ZM1dPadwe6ysmbDKowJRkSpjN0f70GblsWq9ZvB7SIY8BHy+wgEfSgUsumCtDIpyKafuuh0Onw+H2lpKYz0dDFhdzDpC9DW2UfVvDKKZhfQcvo0NoeToeFxRImaPXsPs2b9Vp546p+wWGZxtu0kYljF2TOnuOaK69i7+3NOnPgTYkSJXGPgjbcf5V9+9ByzcueQkGalu22E/LQlZGd7kIguTrfUoTNIsNutpCUmEPIGaW1pIi0zl3UrFpBvSaa33UpKmpykxEw+33uYYHSEnnYX+3YfYsrlYFb+HHa9/msK8zKonFPBxksW8vTTL3LweAP7aw9x8MQxurqG0Cm1fOubNzJ3bgmXbNnGskXrWLFqCeVVeTin3Nz/0A+pazxONCJDq8zH4fHQ3TMMMSVmk5Ikk5qspALswx4s6WZuu+UOOtv6cTq8TDjH2bp9xd9epMB3mC58+2ceA54URbEAcAK3z8RvB5yiKOYDT86M+6uEwyFWrF7HFddcSnaBhqMnTpKUZmDx8qUcOnSC2qajfLL3Q860naO7ZwiDIZFwIMzQYC8ZGWaksihe/xQDAyPodUZ+88zThMNhHv35o4gxKVddfQvJaXl0dA5z8FAdUn0Cq9duIhYII9fqCPm8xEJB5DIJasV0OXGDMQ65SslUIIAokxAIh9iwaT1Gk4H+wQGSU9NIy8yjp38UvTaBqqrFxJmSQFDhDYZRaTQY4k3IVEpWrFhFODL9boB1dICC/Fze2vUm/3j/Q5Tkz0Yr02KbGibi1/PSiz+lvCwVBekIogSZEKA0ZzX97e2MDDjRqOVkpCXRcdqGfXyQ9/7t92RaUtHLwJKchGtMJD8nmThtPEmJqdgmRkhPLaQwN4uu9lqeffIZVCoHAZ+Hq668kdq6Y1SWbSQ1Iw+3f5SCggzWLtlIyOHAkhzDOX6WifFRnnjiPn7wg7vYvG0zOQWZ/PGdt4kzJKFQqJDJAsQnpyAqbHS0n0EtVyMXHPicY0iCUp576lc885snZ95DjeCyO/D6/mrh7n/HV113nwFcArw8sy8Aq4F3Zob8nunFeDBtDvH7mfY7wBrhz4ai/wWxmIRPD77FgHWCpCwj81cWoTNaqG0+RP6sYm6943rmL56LVq9jybKV+H0RcnLyCIX9+Lx2JuzjLFq8gHGbjU8++YwFCxbgcDh47tkXWLt2I40NfeTnzUOpTua6G+4CUYkgV+CPhPCHfChUaoRIjFg4gt/vJxgMIpPJ8IWCOFxOvD4f8+bN40RNDQajkaamJnbu/C0JiSkIchU6TTLr115KZnohwyN25EotHT3dGMw6nN4JENSY47VIJRoy0k2MW20oJAIP/egh+trHWL18BYGoDaVKQmP9EU431+Kd9GPWp1BWsojdHxzhkjWXUFJYgMvuwjY+zuZNc9FooGphMeVzC2iqrWf3+38iLg78HpFJtx2Y5PLtN2B39rFgXgmpyQp+8P1/4GTtJ2SkpTLc72DE6qa50cbNt9xIOBjE63by6rNPsXXlItbMryArVcdtN29h3HkKp9PJe+98xCVb1+KenMJsymHr1s3INKNYsvOYuzCJ79xzO1s37GDVyrmcaz3ADVdeyV233I0vOMqZcw0sXLCUy3fcxN5PT/xtRQo8BdzHn/2mp6syu8TpWvfw7w0g/mIOMdPvnhn/7/iiOUQgEMNs1jAxeJbdbzTT39HE+OgAe/Z8wvDYSTrre4mTJeDzBIkSJCq4kcoihJxRkhXFpMTr+PjjDxAFCQvmL+Hf3nyHHWs3ML+onKOfHWO0d5zTp+pw2LoxJUhpa2mFqBqtzoi17zSxoBfHpB1kIjK1lJAYxjXpxuPxIkYkxKfpaWo9hVIuweexUVlRQNmcPFweGwWzyjlx6gi73votjokhUpKNePxuGttacQcCTNicWEfH8fptpKdrKZ+9lLHJQYwZCWRlz+WRf/oFPZ19bN1wCc1t50gqWIzMXEJygYHM1BJe+OVzrK7aBsI4I4MxFixfiyfYg6s7HffIENVZW3ntt89Tc6ab1HwD9z18PcOTcirW5xIIS/jwnffISg/R2zrG2iUrOXjsVzz1rzuxtVnpbm7k5w8/RN/kn2gdGMKYnMScuUUEGCOl0MTxs3WcaG7gZ798nOuv/wYjg13kZ6Zy//cepqC4iI7BBp56/jFKS6sZHBvmTJuX4YkpZpVXceXW73DPXf+MKNdy5c13c9mOq1ErjUiiAt+65To2zrf87UQqCMIWYFwUxVNfDP8nQ8Wv0Pf/A18wh1AoYWhggoqqFdx73z0Eww7Wr9qASm4EaZTqeZVEoj56etv5+KN30OmVyBWwaes66uqPM6t0LstXreGW22/jdFsL1YvmcuDIAVKyMhhz2jGY5SjUCvJyZjPcN0Ek6sfrHebd118mNTkTiVyBXmdAkEhRqTSYTPGEw2H0ej0ZmWlo1DpSUlJIS0tj1qxSIuEotrEJujt7yMvOZnx8nKLCEjyeKZx2B0cPHyE9PZ2KinIEESZ9o4QCeiJhKTlF8SQnZrF88Xpq6j/hpZceI9mcS3X1fNKy5PQMnOXY8QaqZ9+By3+W4pLZfHLwGSxppaj149TVtmCxzGH7zaUsW3ItLv8ZcrL1qDQahobtnKhpYHzchlZjwubwsHL1WmJhGf0jtQjqSdQ6kQfv+y56YzLt7WP8/tU9zC2v5unnH0WUQENzB0uXb+VPn9dw9PgJEpINpGbp6e7uZsvmy7l8+5UUFucgkUBvzyBarR5Lfjr5+Rk8/5sn2b37E04ePcqxQ4coKCjgoX98AIkkxtneepIy9TS3N/HaW2+iN/xtF+ItAbYJgtAHvMX0af4ppj2e/lwh8osGEH8xh5jpjwP+6gVIvDGOloYhTtb38uLvXsbvG2Pv+5/iHA3Q2d/DZ3s/oq7hBOmZCejjFBQVZXPs2D5MZg3JmfH09U5w7lwvY7YJgjEfR+uOUNNyitNd7ay5ZCND1i72HzzEslWX0tzURmlZARKpm0jEzacf7gWtGalMQyQsQabQMDRsRSpXzpTGDuL3hxgYHMLnC9DfP8jw8BiLF6wg3hTPyNAgB/cdQqPSoFNryM/J5aorriQ+zsC7f3ybcNCPMT6BaFRLnDGFffs/JRyOkpKSQlFxGoVFqQz3D3D/9/6FlavnkZ2XxtWX38/Hn7xN62kbxtxRUvMzcAx60Ok8JJiM3PSNm3j381dYu+FuesYOkZleQGXlPNRxJhYsXg6xCN2dQ/T0jeALeGltdHHzDT/krXeP0NXv5Kevvc653hbiEmKkFWmZtzyXialBfLEgI+Ne3vrjfjKyK8jKKaRnqI3sfOOM0bAefVwSiQkacvMyufb621CqNHz2+bvUHN3NC88/yazCPN56Y9d06UppjLTMJOTqKGfOjnD3PT/igQf/Gbs7yJjrb+hPKoriA6IoZoiiaAGuAfaLong9cAC4YmbYzcAHM+0PZ/aZ6d8v/tnm7b/AbnNQNquYmlMtuKdCVFdWYVDL+cUTjyFRqNiwcSM2m435c6uprqzgTGszEOPjTz8mFAszOjBJRpKFvu4u9DoFKqXAggXzGBoZZNfbb5GakcO2rdtpP3Oa3p5ORkcGiEVDXH7FDvLycnBbx1CotKi1BnTaOKQSBVNTUxQVFSCTSdGoDaSmphMRY3R0dpMYn0ZdbQPpKano1HIyM7Lp6enD6XSTk5OHz+fDabMzd04F8WYTvb1Blq6cT2p6Cp3nnBQWp7N795usWLwJgnIUKhdJqbD/8z7yc9bz3ke/Iis7Hbe/mf6BGDXtJ/G4xvDaIM4U47sPXs+43cjDv/wOMqWWYWsPtXV1xCUn0dp2jsG+MQRRSnxyEm7POKX5WQyP1zJncS7JWQk8+rNHaOvqY9PGazlxapidz/0Jp8ePTKlCoTMwYnPwyhtvkJKRybzFC9l3cB+f7NmLzyelo60bjVZAJIhcqmPV2rXcfuf1CExy+Y5NHDy0j5tuuoHaU7W8+torPPjjf6C9o4UUcyGrl28hM6OAsVEXx46e+muS+O+J9K/wQ+B7giB0MX3NuXMmvhOIn4l/D7j/y75IKlEwp6wCS0YyqYnZGA0ZnKg7yI23XMrypRv4bO9hBodsWLILUMq1qORqkpPSQFAQjECyPhUVSjISk4nXG4iPMzLQ3c+KpctYvngB0ZCeWExg5ytPoddHiQRDvPj8LqSChoolVcTl5jNms6NUaZj0+FFrdcQnJKHT6ZicciOTKImEpyvyWfJyWX3pZWRlF+B0OrE7RkjLzPhLGcnTp09jNBgYG5ugurqagC9AWnIhDpeLkpISvnHH3/Pa668wMtrL4QPHcLkm0eolqKXJ3HbrvSSnJ7Js5QIcniPMq1qDwztERJRTOCuPeH0egjiJSIC7/u5hJLoBBnoEcnIMLFk6jz7rIHmFuSxckMqnH+1BY1TjC4zjt/t4b9cB3v+4hudffIdzwyNIldDYdIjS+flUzM1BIdOj1hrQG9WM2AeJSnycrK9jYMBBRkY5Tq+XQ0eP8+rrr3Gu7Qznzp0lKysLQRB4881dOGxj/Po3T3HzLTfS2NLIy6/s5MnnniUY9NPX28Wks5XcHDkB7xAmrZ4Fc9Z/ZaH9d72gDoqiuGWm3SOK4nxRFPNFUbxyxhMKURQDM/v5M/1fuuIqEIwiFRWYlBo2L9/CgYMniagiBPBg7RsnGJZQWlrNgf3H6W3vxzbmorHhDJNTQfwhAafdjtM2QV93B0I0hsfhY+OazZh0BkZH+rnyspu54aZb+dbdt6DTScgoKGZ+5QqmPGGa62t49IH7UGlVeP0+unt7UGrUfylFEwj60Kt1GOPi6Orp5E/79vHJe++TU1BAdn4OzedOIUhh2DpE0awSVCoVI6PjLFiwkMaG00TCsHx5OT3tExgT0vnXn/+AWFTO6eYukjNUIPMyag3y6E+e59mXH+Hplx6ksbGGxXMupfb4HooKqli+Zg0jTi/x8XGcqe/mwW//khHrERLjk9CrshFjITyTTnRmAydrj+F3WVEJUnr6uolPkFOaMwuNOoo34CYlJZnZ8+Yhl2moOdyMWpfJyQOdJOktTDn8dLS3oDeCOVnNyIQVhytEQkIhxeVzWLFhBc5JJxs3b2Pd6rUM9HUTC0dw2X0sWrKSto5ujtfWYE5O5Ic/+iE1R49QV1PPqpVrKSvKw2kd4NjBPcypLGdR1aL/GZH+T2EwxTE0YOftN/Zy42VX0dreSI/NSlJ6NnEKNf39ozQ1tXK29RwymQynzcnSpUvR6ePQxhkxJsaBXKRnoBeP38+x4/X8af9ROjq6qKyajVQMQyTGc0+/yMkjtXzy5i4mfU52/v53ZOeW8c27b8cb8HDk+BFC0elis263m4GhQZYtW0ZPdzchv4/Vq1dy1bVXoYmLo29khLrmU1QuLGdgpB8kYHfa8Pi8GIxxREUBq3WUUesErc21lJaUM2V3sGhpOVKJgi3bLmfpyoV093Vzyy1/zz33fBtLYQLlVYX8+qnf8+6u3Yz02ag9eRRjXAKvv/8hxoRE1i+5nnde/YQTR/6IEjPeyQkWll+Od9KLPxBFLldz5fYt2Eej6LQGHLYx5GEtqpicaExBT9cYLee68Hr9KJDw/gcfUWgpwKw2EPb6sY1FqSgvA1FCSkoabreHw0eOoTAYaT5XyweffkRfzxhJCam0NJ9gwjqKbdTPq699wJp1W1m0dDltXW1kZmcgIuCwe6gsX4ASC0mmIq7YcT2//sXjnGmv+8r6uCBEOul1k18wh+tWXkPjsWNk5BoZ80wRZ84m5HGj1anZfvllJCcnMjZqRamSUXvyOGqdmryCXOYsqiAu1Ywu0UzVwsVk5xcz6Q2xdcd2uvo6OX7iU375rz9lyfz1XH3lbfz2dy/S0VXHN+66jT17a4kz6zl27BBZliz8fj/RaBSbzcbQ0BBWqxWJCOFIkILCfOxOGxVVlVgnxpFrFHT0tqNUK3BPubG7HGRkZuJ0uAmGIhQWl7Lj8iuIBlXs2b2L1197iery1dx6+zVI5GG6OtzkWKp4452XyciN4fPIOXVijDdfe59ZxRmUFS5m4/oN9PR0MW/FPPr6pmhvHiU/y0Bl0QqK8nKQyp24RlI4drgbpSqOUaudnvYuigssqFUGVAoVc4rm0985gdPhJzPVQs/AEIcOHKSp/gzz5leSbDYzMdKH2RDH4nmzsWQWEwpKsdkdZGQn09JaT0SQsnhlNW/+8XeMWp289MJOlHKRY0eOUF48n6bTnQTCEuqbmklMSaK+4RShUASJRMHjjz5JRlYG5iQjP3v8EeZUzcYX/hub6P5PY1TpcA+fQzQ72V9/hAXFazG69FjU8YQjU/Q3N3L9pRsQpD6CshBeQSAtpwib1cFAayeJiQX4PTpuvPS7fLrrIBuWraCyOo+db7+CKjubhIxu5s8zYFCcxd3dwaLSciqLlvLbF17FPtZGf0cXCkHJkf1H0KrUIImQlZvK7LJixuwunFN25pRVIAvJsSRY2PvxJxTmZSGNiuiiBiw5yZSUF7Ni/TqkOi2+oIeignTy8tMYsQ9jFUZYte0qBqyD3P/j29m/r54bbn0IrVnL0KiVK7d/F4UhmZOHatm8sJo5JSZ+8oun6By04rPrGD83gVmZR3p+GsPBDrqGRnFZo2TqC0jT5ZFp8WM2w+a5pdhb3ThGk9DoI2hDEeydHuJSekkpKcc3ME52YjwZCiOzV28mZsmhrWEEU3wOOkUCOZZ8kjMSWL1hMRkWI1ffeg267FT+6eVfU5k/hxuv/ibPPP07ZIIBty2EXp3Mpi2X09rZRaoliePHDvDxO+/jnHAxGfTz7GsvITcruOS6Tbz94e8xmNUUFefT19VMWe7XzBxCJpfRNzDIVVdfy7fv+R7xiYlUVFWxZNlyWs+0M7usnNr6JvQ6E4mmBLyuKSbGbKxcsZruvl56elrJy0kjPslIXlEeOqOZQ4dOsG7NBrwOD8dPdHPkaCvJmdnUt9aQmmPiwz1/oPlcA4JCRlt3JyExTFlVOWMOGxMTEyQmJ9HV1UlFRTm+kI/RcSt6o55Pdn/Mlq2bGRuzMjU1xeTkJCqlklyLhVN19fT39xIfb+b4yZO8/+F7RKNREszxGHQaVAol6SlZNJ5q4FdPPIrHPUlJcT5nTjcgV0jIz7FQVl7Kv33wHs31R/npTx6muCiPvNxMhoY7kUrU7Nh+A9bRCfTxauoajxFFzqRHTkFOFiZDMtsvvZp51UsIByNMWG2o5Fr+8NZ7nGtuYePmDZRWzGJkeICAy87khJUrr9hGYpqZguJ0LDmZXHPlzUjRsWDBWpqaWmg93cAdd3ybopJC1FoldqcD16SbO++6G3NCPD/56U85frIWXzCAXClnw6Z1tLW1UDmnlKR4M1F/mCOfH0YZ0xLxihCW0tTSxun2r5k5RCwmEkGg6XQ74zY3+w4cwmhO4IWXdhLwh6lvbOXUqSauveJadmy5DL/by7bNWxBFkbkL52Mb60KhDPH0M0+wYdsWsvIK2bb1Cn79+FO4RoZZtew6vn3vT2jvHyA+O56GtsNcetVacoszUegVHDh5DHWcnlGHjXWb1hMRwoyMDjIVmMLlchCKBCmvnMPho4dISk3m0z2fIsgE3B4XWoOWwZ4Bgv4ALocDjVKFTqdDKhNITk1lwmVjZHiYU6dqCHgDbNywlZycPFxOO7NnlSASwWiS4HDYWL16JQaDjqKifF548Rm8U0662ltYUF2GMUnG0OAw0ZiG0rJKpCqRIdsAMrWet97eh93qobWll/fe+YymU63EfBGISPjXnzyBRhXP/FlFSKQxXD43GWkJKPwhLl25DJUqRljmR2eS8uyzv6GzrYd/fPAxamtO88rO3yERgqSnwl3fuguZWk5uUQEdvd38/b338N6HH3DZFVfwk0d/hlytoqO3k5r6wyhV8NhPHyFJb8AxPMbtV93EDZfeQtOxZgJTEX75wm+R6sxfWR8XhEinvF4KimfzTz/9BXbnFEXFs3C47Hg8Xr77/Qf4+eO/YHhojH/43g+ZGLRRWlhO3YlTtLSeoaunj/HBEUaHhsjIzsA6PsaJulMMW63c9/3vohYCeNxTvPbG69gmJ1EbDdxw480cO3qYaNhPeWUZ1UsWEVVIyci3UNNQh9U2imvKRVpaEsMjA/iDHjo6ztLX1012djoyhXS6SnQ0wpTPi0Grw2mzk56ezuDgIB6fF0EqYfHSxYyOWzHGJxCRhEjJTCccliOVy5CpZEz5/YhSkdqmI8ytnMftt9zN8WM15OcXsWrlGmpqarh8x3bOnG4mFPZQONuCOUHNhGOMoZFByioqkKhULFmxkiRzKl53gOKiMnq7+ygtKUEIhfjHHz9MQnwqqxauIByOYkpJZOWKFVy3bTN5Scn4Jp3Mqixm7+f7WL5sCSGfD41ajtlsJBCAwf4h0kzT5sCTU1PsO7iPtPR08ovyEaQS+oYGeGPXLhpPNzF/0VzUegVGk4Z7/v6byGIxuprPELB7SEvNpnhWGR6fj90ffkjz6favrI8LQqQqtRKt0cCZs2dISk2jvbODHTu2c+edd3DfDx6gv6eXns4etm+5DI/bR2a6hcL8EiZGp0s3CmEVa1dtxO1wo9PpkMikBHw+zrbWUlmaSW/3cZoaDuJw2EhNzuPo/iYS1elUl1XR23WWxLQUXFMe6hsbCMYimOLNBEI+Jr0uAmEfObnZBCN+5s6fS5zJgNlsxu12Ew6HsduduN3TpcRVCuVMaUcZLpeTKe8k0WiE1Ox8isqLWbVhDaPOSVKy0iibN4eqhUswp2RgSDRwtqWDl1/eyexZlRw4cAKvP4ZBn4hSoUOnNaKSK/EFxjjTdhh9nAytxkwsoqS4pICu/lO4bQ40Gh0lpbOZdDnQyGKsXraI/JxcvL4QXneIJUtXU1RYSmZaJjqllnnV1bzw0gt4/D78ITmpSakEfOOEwqP0DZ9m7bqFnG0aQxk1Y7Pb0et106WBpNNOz1lZGYyMDJOckkhubi4DwwOkpaUhk0lxOu0U5OUgi4k019XRYe3hTF8bZ7va8finyMjI+Mr6uCBEKpPLGJsY42xbBzW19YRCAdraW0hONPGtv/s7ctPTeeTHD5BfkIsgk9I7MIBnyktiYhJL5i9BIcTR1tJFviWHBfMqON14Cq1GhVQqsGzVYoz6GEVFWUw4HQTDErZsvop4fSol+bNRKRS0t3VjczgxmcwEgkEiYowoIjKFguycLCTAyPAgB/Z9TjAQoLe3l66uLrxTfqQSOUtXLMfn89E/OEBCQgJNpxowm828/Yc/Mn/eXOrqWrFYLAyPDpOVnYPTY0Mfp2FszENH2yATNgf52blMjNrZd+Ao6zdsJTunEFGm4slnXmDdpq34vCJ9PV34fQ58Hg8quQFpTENqYgI6VRSjTkdyajqzysqZUzWHUNBLRnoqDoebrduvpXLJckymRNw2Fy88/xLP7Hybz4/s56bbb+bjD98nIyMfl8tFalIcl29fz9XXbKNsTilX79hGR1MfRCRIBRkJpgSaG5vIycrEoNexeEE1jQ11bNt6CVs2bSElNRO7ww2CnP379xFn1lBYnE392TrcQQ9KnYply5Z9/awfJRJwT9qprq6mq6uDq6+5jEjEx/PP/YazzS2Y1QoO7vmMOL0O5FK0ZjOhmEhleSViIEpWTi5W6zAe9zhyMciCinIy07IoKqpkz76TzC5eREf3MBGpnN7RIY7VHEZn1NLS2oomLh5BkKKUqQkGoqhUarq7u6eLPsikRMUYdpuNcCBI6azZSEQJG9dvIjvTglFvpjC/iObTLUiUcuJMJgYHBzEajdNld9RKhgeHSNSk4HNOopJI8LkmyU5LxDEyjGciwKKKFcRrU6irOQpE2Lx5I48+8ThHThwngsgPH3qQV9/aRdgvpSR/AUW5C8jNnIXP4UEMBOhs6cSSUsRVV11LZdUCKuYu5LrrbyYSinKqppFNm69Ar0sjqSCL2ro63tm1C6VWznv7XmNP/QFONBzFZhuiZE4RTruNZ556lolxF4VFpej1cQz0dLJs4VyGeseIBmJkpmRIAusAAAWzSURBVGRw5223U11ZSW9nG2qFgFGnRCWT0tTQzJnWDmKiGlNiKimZ6bi8Dlra6nE5xygtKaaksITmU2dZWP01+2e+P+BHKoeEBDMjw4PIZRJSk80o5QImo4HMxASMOg0ff/oRdreLhLQUMiw59Hb3sXrJChKTjBQWZpFrScA+1kdJQT5iUILTGcUbUGN3qli0bDt+YNQzTEjmYdTeS0gMExQlVJVVUjarjIXzF3HrzbehUeuIRGJMTnnoHegnEongtDson11OdmYWJ48dR4gJFBcWo1XpMCcl4wsE0Op1JKYkTz9OdboIB0MYDTry0grw2BzIw1GkoTBGlRy1ICHNkMbCyhXIwwoq5hSxfftGJmwjJKSYqW+pJyCGeOJXT6A1alm+bDUqSSrScAZiQENOVib5uZmoRA1GhYWB/hFGxxxce91tdHb0sWP7VXzv3vvIyS5lz59OUNfWSHFJLuGAh9vvvJnr776RO39wF+k5yVgyk9iwaTHrN6ymvGwe8XEWDh88RSgYITFRj32ih7nlZehVOno6urCkZ3LudAsb165h5wuv8/17v41SLuPAvuMgyrn8imvp7RtCoVHjCbpZuGwu88vnsLh6IdKIjLdefYddr73zpbr4MxfEQrxfPvX4I7MqtTTXdrNyxWp8QTcVpYuRiw6WVhRy4mwTdY1nKJ6TQaKpmvS0TAYH+ghEJvAEHMSnlBGdmiA3IZPklFJUBgM6hYqell5yZiXz9vv7wGSmMF6NLypBF4OE9CKyLQVokDE8HMAXnCApIYf9h98lx1LC4FAXYjSKVJROVw+RyZGIApbcPBzuSVIyMpBKpbgcdhLjE4kFw4T8AYSYSCQUIT4+CZ/Xh4hIdGoCh8NH/uwFxCXH036uk0SzkabGGhz2MbxegXZ3C2N+H0HvFFvmL2W4cwKtKQVBDKKTRlm8cDONjScITkpJMIXJm7sV+9hRrO4IJz76gIS8Jfh8g4SnJli7bBu20ShDYzbcXicqtRS1XgcSBcZUJWGVgXJLOo6gA3+3k/yKTFr212FWOEnLzMEllzHu6aatvoFrtt3KynWXMreqnExzAo0th6leY6TuYBurqouxu6eoPeskLc6PXzJFKDxFftxiamreJaaaIsksY83CpfzupdfQJBcz6Y0Sp5ax44p5/PaNQ19pIZ7wJS8o/a8gCIIH+Oq3exc2CYDtfE/ib8D/Rh7Zoigmftkg2ZcN+F+iXRTF6vM9ib8FgiDU/1/I5ULK44K4Jr3IRf4aF0V6kQueC0WkX3rx/DXi/0ouF0weF8SN00Uu8te4UI6kF7nIf8l5F6kgCBsFQWifseX50vVQ5xNBEF4RBGFcEITWL8TMgiB8PmM39LkgCKaZuCAIwtMzebUIglB1/mb+7xEEIVMQhAOCIJwTBOGMIAjfmYlfmLmIonjeNkAKdAO5gAJoBmadzzl9yXyXA1VA6xdiPwfun2nfDzw2094MfMa0D8FCoOZ8z/8Lc04FqmbaeqADmHWh5nK+/1iLgD1f2H8AeOB8/4hfMmfLfxBpO5D6hR+/fab9AnDtfzbuQtuYXo6+7kLN5Xyf7v9iyTPDF+16vi4ki6JoBZj5TJqJfy1ym3E9rARquEBzOd8i/UqWPF9TLvjcBEHQAe8C94qiOPnXhv4nsf+1XM63SP9iyTPDF+16vi6MCYKQCjDzOT4Tv6BzEwRBzrRA3xBF8b2Z8AWZy/kWaR1QMGPIq2DaxufD8zyn/y5ftBX6j3ZDN83cGS8E3H8+lZ5vZqw4dwLnRFH85Re6LsxcLoCL9s1M3112Aw+e7/l8yVzfBKxAmOmjy+1MWwztAzpnPs0zYwXgmZm8TgPV53v+X8hjKdOn6xagaWbbfKHmcvGJ00UueM736f4iF/lSLor0Ihc8F0V6kQueiyK9yAXPRZFe5ILnokgvcsFzUaQXueC5KNKLXPD8PyJPzyhDRifFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f56abab5470>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dog detected, this looks to be a Mastiff\n"
     ]
    }
   ],
   "source": [
    "## TODO: Execute your algorithm from Step 6 on\n",
    "## at least 6 images on your computer.\n",
    "## Feel free to use as many code cells as needed.\n",
    "\n",
    "## suggested code, below\n",
    "for file in np.hstack((human_files[:3], dog_files[:3])):\n",
    "    run_app(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}