Histogram of Oriented Gradients (HOG).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Histogram of Oriented Gradients (HOG)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The histogram of oriented gradients (HOG) is a feature descriptor used in computer vision and image processing for the purpose of object detection. The technique counts occurrences of gradient orientation in localized portions of an image. This method is similar to that of edge orientation histograms, scale-invariant feature transform descriptors, and shape contexts, but differs in that it is computed on a dense grid of uniformly spaced cells and uses overlapping local contrast normalization for improved accuracy.\n",
    "\n",
    "The essential thought behind the histogram of oriented gradients descriptor is that local object appearance and shape within an image can be described by the distribution of intensity gradients or edge directions. The image is divided into small connected regions called cells, and for the pixels within each cell, a histogram of gradient directions is compiled. The descriptor is the concatenation of these histograms. For improved accuracy, the local histograms can be contrast-normalized by calculating a measure of the intensity across a larger region of the image, called a block, and then using this value to normalize all cells within the block. This normalization results in better invariance to changes in illumination and shadowing.\n",
    "\n",
    "The HOG descriptor has a few key advantages over other descriptors. Since it operates on local cells, it is invariant to geometric and photometric transformations, except for object orientation. Such changes would only appear in larger spatial regions. Moreover, as Dalal and Triggs discovered, coarse spatial sampling, fine orientation sampling, and strong local photometric normalization permits the individual body movement of pedestrians to be ignored so long as they maintain a roughly upright position. The HOG descriptor is thus particularly suited for human detection in images. **(Wikipedia)**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading and Displaying the Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing the libraries\n",
    "import copy\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as patches\n",
    "import cv2 \n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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Dy/3AzzbaOgcf+7IQP443W///cjine3P25Xn4DCxTeLeB59ft4lN23oK/Z+7FD5w3VMra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7csbgbcuamCAUUyKY2jKdz/DGBkuvxmCx4FvdDILSoWyqQ8vJbqT9XCzJ8d7TL0pm1TyArxZP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\ndxEHNyp30X7GWm9uZmu0dGfB2CyOR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CVJEiDr67ygpjGGMAw5cOAAb3nLWzDGsLi4yNTU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hgvPUQn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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110d0ce48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setting the default figure size\n",
    "plt.rcParams['figure.figsize'] = [17.0, 7.0]\n",
    "\n",
    "# Loading the image\n",
    "image = cv2.imread(\"./images/graphic_img.jpg\")\n",
    "\n",
    "# Converting BGR to RGB\n",
    "image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n",
    "\n",
    "# Converting RGB to Gray scale\n",
    "gray_image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)\n",
    "\n",
    "# Visualizing the image\n",
    "plt.subplot(121)\n",
    "plt.title(\"Original Image \" + str(image.shape))\n",
    "plt.imshow(image)\n",
    "plt.xticks([])\n",
    "plt.yticks([])\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.title(\"Gray Scale Image \" + str(gray_image.shape))\n",
    "plt.imshow(gray_image, cmap = 'gray')\n",
    "plt.xticks([])\n",
    "plt.yticks([])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating HOG Descriptor (Feature Vector)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "<figure>\n",
    "  <img src = \"./in_cell_images/HOG Diagram2.png\" width = \"100%\" style = \"border: thin silver solid; padding: 1px\">\n",
    "      <figcaption style = \"text-align:left; font-style:italic\">Fig. 1. - HOG Diagram. (Taken from Udacity)</figcaption>\n",
    "</figure> \n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==========================================\n",
      "| HOG Descriptor Parameters:\n",
      "| \n",
      "| ==> Window size:  (294, 396)\n",
      "| ==> Cell size:  (6, 6)\n",
      "| ==> Block size:  (12, 12)\n",
      "| ==> Block stride of:  (6, 6)\n",
      "| ==> Number of bins:  9\n",
      "==========================================\n",
      "\n",
      "==========================================\n",
      "| ==> HOG Descriptor's shape:  (112320, 1)\n",
      "==========================================\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Parameters for HOG descriptor\n",
    "cell_size = (6, 6)\n",
    "num_cells_per_block = (2, 2)\n",
    "h_stride = 1\n",
    "v_stride = 1\n",
    "num_bins = 9\n",
    "\n",
    "# Setting parameters for HOG descriptor\n",
    "\n",
    "# Block size\n",
    "block_size = (num_cells_per_block[0] * cell_size[0],\n",
    "              num_cells_per_block[1] * cell_size[1])\n",
    "\n",
    "# Total number of cells in image\n",
    "x_cell = gray_image.shape[1] // cell_size[0]\n",
    "y_cell = gray_image.shape[0] // cell_size[1]\n",
    "\n",
    "# Block stride\n",
    "block_stride = (cell_size[0] * h_stride, \n",
    "                cell_size[1] * v_stride)\n",
    "\n",
    "# Window size\n",
    "win_size = (x_cell * cell_size[0],\n",
    "            y_cell * cell_size[1])\n",
    "\n",
    "# Printing the parameters\n",
    "print(\"==========================================\")\n",
    "print(\"| HOG Descriptor Parameters:\")\n",
    "print(\"| \")\n",
    "print(\"| ==> Window size: \", win_size)\n",
    "print(\"| ==> Cell size: \", cell_size)\n",
    "print(\"| ==> Block size: \", block_size)\n",
    "print(\"| ==> Block stride of: \", block_stride)\n",
    "print(\"| ==> Number of bins: \", num_bins)\n",
    "print(\"==========================================\\n\")\n",
    "\n",
    "# Setting the parameters of HOG descriptor\n",
    "HOG = cv2.HOGDescriptor(win_size,                       # Size of detection window in pixels \n",
    "                        block_size,                     # Defines how many cells are in each block. \n",
    "                        block_stride,                   # Defines the distance between adjecent blocks\n",
    "                        cell_size,                      # Determines the size fo your cell\n",
    "                        num_bins)                       # Number of bins for the histograms.\n",
    "                        #win_sigma = DEFAULT_WIN_SIGMA, # Default: Gaussian smoothing window parameter.\n",
    "                        #threshold_L2hys = 0.2,         # Default: L2-Hys (Lowe-style clipped L2 norm) normalization method shrinkage. The L2-Hys method is used to normalize the blocks and it consists of an L2-norm followed by clipping and a renormalization.\n",
    "                        #gamma_correction = True        # Default: Flag to specify whether the gamma correction preprocessing is required or not. \n",
    "                        #nlevels = DEFAULT_NLEVELS)     # Default: Maximum number of detection window increases.\n",
    "\n",
    "# Compute HOG descriptor for gray scale image\n",
    "HOG_descriptor = HOG.compute(gray_image) \n",
    "\n",
    "print(\"==========================================\")\n",
    "print(\"| ==> HOG Descriptor's shape: \", HOG_descriptor.shape)\n",
    "print(\"==========================================\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Number of elements in HOG descriptor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Number of elements in HOG descriptor\n",
    "The HOG descriptor is a long vector containing the normalized histograms from cells and from blocks in detection window. The total size or elemets of HOG feature vector can be calculated by:\n",
    "\n",
    "<span class=\"mathquill\">\n",
    "\\begin{equation}\n",
    "\\mbox{Total elements} = (\\mbox{Number of blocks})\\mbox{ } \\times \\mbox{ } (\\mbox{Number of cells in block})\\mbox{ } \\times \\mbox{ } (\\mbox{Number of bins})\n",
    "\\end{equation}\n",
    "</span>\n",
    "\n",
    "\n",
    "#### Number of blocks in width and height of the detection window\n",
    "\n",
    "The total number of blocks in width or height can be calculated by:\n",
    "\n",
    "<span class=\"mathquill\">\n",
    "\\begin{equation}\n",
    "\\mbox{Total number of blocks}_i = \\left(\\frac{\\mbox{(Total number of cells)}_i - \\mbox{(Number of cells in block)}_i}{Stride_i}\\right) + 1\\mbox{  }; \\mbox{  for  } i = x,y\n",
    "\\end{equation}\n",
    "</span>\n",
    "\n",
    "\n",
    "For example for getting the number of blocks in width of the detection window, we can calculate:\n",
    "\n",
    "\n",
    "<span class=\"mathquill\">\n",
    "\\begin{equation}\n",
    "\\mbox{Total number of blocks}_x = \\left(\\frac{\\mbox{(Total number of cells)}_x - \\mbox{(Number of cells in block)}_x}{Stride_x}\\right) + 1\\mbox{  }\n",
    "\\end{equation}\n",
    "</span>\n",
    "\n",
    "\n",
    "Or for getting the number of blocks in height of the detection window, we can calculate:\n",
    "\n",
    "\n",
    "<span class=\"mathquill\">\n",
    "\\begin{equation}\n",
    "\\mbox{Total number of blocks}_y = \\left(\\frac{\\mbox{(Total number of cells)}_y - \\mbox{(Number of cells in block)}_y}{Stride_y}\\right) + 1\\mbox{  }\n",
    "\\end{equation}\n",
    "</span>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==> Total number of blocks in width of the detection window:  48\n",
      "==> Total number of blocks in height of the detection window:  65\n",
      "==> Total elements:  112320\n"
     ]
    }
   ],
   "source": [
    "# Total number of blocks in width of the detection window\n",
    "total_blocks_x = np.uint32(((x_cell - num_cells_per_block[0]) / h_stride) + 1)\n",
    "print(\"==> Total number of blocks in width of the detection window: \", total_blocks_x)\n",
    "\n",
    "# Total number of blocks in height of the detection window\n",
    "total_blocks_y = np.uint32(((y_cell - num_cells_per_block[1]) / v_stride) + 1)\n",
    "print(\"==> Total number of blocks in height of the detection window: \", total_blocks_y)\n",
    "\n",
    "# Total number of elements in feature vector\n",
    "total_elements = (total_blocks_x) * (total_blocks_y) * num_cells_per_block[0] * num_cells_per_block[1] * num_bins\n",
    "print(\"==> Total elements: \", total_elements)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing the HOG descriptor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setting the default figure size\n",
    "plt.rcParams['figure.figsize'] = [10, 20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==> Shape of the HOG descriptor before reshaping:  (112320, 1)\n",
      "==> Shape of the HOG descriptor after reshaping:  (65, 48, 2, 2, 9)\n"
     ]
    }
   ],
   "source": [
    "# Reshaping the feature vector to: [block_y, block_x, num_cells_block_x, num_cells_per_block_y, num_bins]\n",
    "hog_descriptor_reshaped = HOG_descriptor.reshape(total_blocks_x,\n",
    "                                                 total_blocks_y,\n",
    "                                                 num_cells_per_block[0],\n",
    "                                                 num_cells_per_block[1],\n",
    "                                                 num_bins)\n",
    "\n",
    "\n",
    "# Transposing the blocks_x and blocks_y: the first index (blocks_y) referes to the row number and the second index to the column number.\n",
    "hog_descriptor_reshaped = hog_descriptor_reshaped.transpose((1, 0, 2, 3, 4))\n",
    "\n",
    "print(\"==> Shape of the HOG descriptor before reshaping: \", HOG_descriptor.shape)\n",
    "print(\"==> Shape of the HOG descriptor after reshaping: \", hog_descriptor_reshaped.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==> Shape of the average gradient:  (66, 49, 9)\n"
     ]
    }
   ],
   "source": [
    "# Initializing \"Average Gradient per Cell\" with zeros\n",
    "ave_grad = np.zeros((y_cell, x_cell, num_bins))\n",
    "\n",
    "\n",
    "print(\"==> Shape of the average gradient: \", ave_grad.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==> Shape of the histogram counter:  (66, 49, 1)\n"
     ]
    }
   ],
   "source": [
    "# Initializing an array of zeros for counting the number of histograms per cell\n",
    "hist_counter = np.zeros((y_cell, x_cell, 1))\n",
    "\n",
    "print(\"==> Shape of the histogram counter: \", hist_counter.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Adding up all the histograms for each cell\n",
    "\n",
    "# Iterating through horizontal cells\n",
    "for i in range (num_cells_per_block[0]):\n",
    "    \n",
    "    # Iterating through vertival celss\n",
    "    for j in range(num_cells_per_block[1]):\n",
    "        \n",
    "        # Average gradient per cell\n",
    "        ave_grad[i:total_blocks_y + i,\n",
    "                 j:total_blocks_x + j] += hog_descriptor_reshaped[:, :, i, j, :]\n",
    "        \n",
    "        # Histogram counter\n",
    "        hist_counter[i:total_blocks_y + i,\n",
    "                     j:total_blocks_x + j] += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Average gradient for each cell\n",
    "ave_grad /= hist_counter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==> Total number of vecctors in all cells:  29106\n"
     ]
    }
   ],
   "source": [
    "# Total number of vectors in all cells\n",
    "len_vecs = ave_grad.shape[0] * ave_grad.shape[1] * ave_grad.shape[2]\n",
    "\n",
    "print(\"==> Total number of vecctors in all cells: \", len_vecs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==> Total length of our degrees:  9 \n",
      "\n",
      "==> Degrees (radians):  ['0.00', '0.35', '0.70', '1.05', '1.40', '1.75', '2.09', '2.44', '2.79']\n"
     ]
    }
   ],
   "source": [
    "# Equally spacing degrees between 0-180 degrees radians to the num_bins\n",
    "deg = np.linspace(0, np.pi, num_bins, endpoint = False)\n",
    "\n",
    "print(\"==> Total length of our degrees: \", len(deg), \"\\n\")\n",
    "print(\"==> Degrees (radians): \", [\"{0:.2f}\".format(i) for i in deg])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "\n",
    "Each cell will have a histogram with num_bins. For each cell, plot each bin as a vector so as:\n",
    "\n",
    "- **Height of the bin =** vector's magnitude\n",
    "\n",
    "- **Bins on x axis =** vector's angle\n",
    "\n",
    "For doing so, create rank 1 arrays for holding the **(x,y)-coordinate** of all the vectors in all the cells in the image. and also, create the rank 1 arrays for holding all the **(U,V)-components** of all the vectors in all the cells in the image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating arrays for holding components of vector\n",
    "U = np.zeros((len_vecs))\n",
    "V = np.zeros((len_vecs))\n",
    "\n",
    "# Creating arrays for holding positions of vector\n",
    "X = np.zeros((len_vecs))\n",
    "Y = np.zeros((len_vecs))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set the counter to zero\n",
    "counter = 0\n",
    "\n",
    "# Calculating the positions and components\n",
    "\n",
    "# Iterating thorogh x axis of average_gradients\n",
    "for i in range(ave_grad.shape[0]):\n",
    "    \n",
    "    # Iterating through y axis of average_gradients\n",
    "    for j in range(ave_grad.shape[1]):\n",
    "        \n",
    "        # Iterating through z axis of average_gradients\n",
    "        for k in range(ave_grad.shape[2]):\n",
    "            \n",
    "            # Computing Components\n",
    "            U[counter] = ave_grad[i,j,k] * np.cos(deg[k])\n",
    "            V[counter] = ave_grad[i,j,k] * np.sin(deg[k])\n",
    "        \n",
    "            # Computing positions\n",
    "            X[counter] = (cell_size[0] / 2) + (cell_size[0] * i)\n",
    "            Y[counter] = (cell_size[1] / 2) + (cell_size[1] * j)\n",
    "        \n",
    "            # Incrementing the counter\n",
    "            counter = counter + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==> Total length of our degrees:  9 \n",
      "\n",
      "==> Degrees (before):  ['0.00', '20.00', '40.00', '60.00', '80.00', '100.00', '120.00', '140.00', '160.00'] \n",
      "\n",
      "==> Degrees (after):  ['10.00', '30.00', '50.00', '70.00', '90.00', '110.00', '130.00', '150.00', '170.00']\n"
     ]
    }
   ],
   "source": [
    "# Equally spacing degrees between 0-180 degrees (not radians) to the num_bins\n",
    "angle_axis = np.linspace(0, 180, num_bins, endpoint = False)\n",
    "\n",
    "print(\"==> Total length of our degrees: \", len(angle_axis), \"\\n\")\n",
    "print(\"==> Degrees (before): \", [\"{0:.2f}\".format(i) for i in angle_axis], '\\n')\n",
    "\n",
    "# Adding (half of two degrees = 10) degrees to each\n",
    "angle_axis += ((angle_axis[1] - angle_axis[0]) / 2)\n",
    "\n",
    "print(\"==> Degrees (after): \", [\"{0:.2f}\".format(i) for i in angle_axis])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sometimes you have to run the below cell twice."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<img 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WX1X5GY/xvqnI9tHs+rRa/+sneP/ovuf+dPoYfMvT8OzdJ03PR9xERf//yZsJ+r/o/B5WoqACLzMCbhg+EW6C7ttdI9uTtdWs9OjntlpDiYnj62b5piLv9um2e+7vkX/2AzH9rD/3ZPHtrL8ycn1cOH7XDx5e57+5mCt/eO9LHZEtreyHp57I+v+3LBdyEop3Jhm+Sj7vm9y/w0s75pcn7pYxw7nk5w8cBNLF51h+wVWng43WLqoiv7yjxwKVqPPdX4/EznB3yV81nLWXZx7FD5s/mXj2+HGES6v4fwdkWtuZ/299KX0EfpFdH/+VvrUtpUdfizabmSjSvd3DXt0bP4eo3T/EuXrLpQz9LD5v1A06ZdO7vgmyz+fXPdFjf6WyPZMq+s44PdPTjnhdrb9/cL296yEdpVzWPexLwsPsgzHG76LL98cOR5d/R42HqRvp/sX1vPoaiIgAicxgfhJPHYNXQREYG4JDHC7x+mP0hfRPco8XXOh4K2zvTjsn35+eO3Ui/axY+XUnWy7yHFh78fD5iJkpraKA9Hj0fXprnFxHrYiK1l6KKx+nHVn4WP2fjHdx3I0zS0uYXORPnW7IzzIcrbnzvZ+a7k2Rd9ND8f8Sdajoo/N/W2ctbC7OD3c1s+Jf0X/yOFeEDnPLTM9kf76yDFf9Yiys/hB+mvp/q8dYfMI8NP0Ryd3fI7lj9D9nb35n9/p/gwFB4/ih0fz/V8O/M+EP/u/6H30aPPxRt/HRf10zT+Ds+lP0h+jv0hXEwEROIkJuIAOf4H68huRd/H16LHous6bno24iMvJ9v+R/y/v0bXfpb9A94ieezzPpP8afbrmEcIt9HOnOzjLvgs45uJhuuaR4OvoUcHk57nntULf4BuTzSN/MzUXj2siB6P/PB7ZfchVF6MeNf4AfQndRdKT9Bj9eLZDPXe29/MvC86qlx6Kui7WPVI8XXOhGvZt050wy74/4piL39fMcs7RHvLP14X2vfTfjtzEv1j4n0v/0uPdrRD+rv7nxpv/GfI/L3PV7uRGLsr9Xx1+lP5p+tG2f+HCFXS/x0/Rd9H9z9dV9Oifqd9k23+HzNQ5FDSddzAjcTmYR/jnR1yOL5eQr5YiIAIvQwL/yDvvo/8l/UjE0F9wvv8lHm1ZNlwAuwA6j+7b0fYMG1dEd0TWM6y7deTr9HV0jyq+me6R2l+nh20rK9eGG5PL6L7/w75v0z2Cvpru0cod9LBtZSW8/kbWP0sP2zpWfOxJuts5ynR/jwT9PfQ6/b10bzfQ7/KVado69oX38cM30X/PVyab3+P2cIPl2XS/t7dDPff9nPMU3d/NRfIt9OizbmbbvwS5cI7Tz6JfTT+adg0X7YhceDvrPvawfYgVF5hbwx2Rpe+7NrLtqzfSP+srMzR/j7Mjxy5hvUh34Xkl3Rn5Pt8O++dY/zLdm7/rIN3FvR/35vfzZzqrsK1jJcos3H87K+8NNyaXv8NyK93vm6FH29TxRo8dat2/2Dk//3/Cv4yqiYAInGQE/BesmgiIwMuXwN/y6qvov0B/6AgwfIpz302PRs9KbHvkw9smum+H7XJWPHJ9f7hjytIjp9fSt9Pvo4/S/4TuIsMF0eG2j3DiDvoL9G/R/43u9z7StpELPk6/l+4i/hL63fTj3Q713L9jAP9Nf5z+CN2/cLiwbNC9eZQ2Tff7DNH9/VfSj0dzoR4+93Dv/4OcGEbHwuWyGS5+gv3r6f4F6ifo/uXA93n0Oew+hrfRF9NdiLrQXkf3Lxkj9C/TH6SP0Y+mecT4dPoX6dP9OXqM/eF7+PLP6IfT/M/5R+n+rzj+bmoiIAIiIAIiIAIvEwKf5z2vP8x3dSHzPw7z3Lk8zSO2LsJO1XYdL/biqfpyei8REAEREAEREAEREIHjT8Cjrd9J939dO4/+HP2X6adKy/Ei/kUkSV9N30A/3Kgnp6qJgAiIgAiIgAiIgAiIwMEE1rL5JN3tIjvpbsNwS8Op0vK8yAN0tyT00f+J7n5nNREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQAREQARF4ORGIvZxeVu8qAiLw8iKwpCfWWrs68dKXbpIImGmGcZ9ryErl+YYlaymSA8dtDy7jvZm4xVocivkyxilkivMLDquFv1a5wQJrMbIOtoIUyAtsYIcazniRrNy1EOyhztZxERABETjuBHwmt5oIiIAInJIE1q5J2n1f6Q3erdU6IGhbqZqVy2a5bNNS5byNpov23JVDdnbzQoRyxn7tVavsH7wsh9Ws1UBRJ2oWaxwQ0LHYAS130H0jz/Cro+f59ly3A280/Z19lK0GqZoZb9y/DLBsRgS0jz0cY/Q9wn1+12B/5H2nf9Lx2Zvki463+s13IKA9rbOaCIiACCwMAgf+RlgY49EoREAERGDuCCAQXQBGxWFw80bS8omUNdGW1VTTukoFe/U3LrVccoVla1Tu2LjP3vdC3FLVDPnixq2TAGi0hfecel8XntEeveZ4rLtAnq5HnxVLJCwWjwcMmk3kc4RJVChHr4muB+8zw3Ome/Zs+3j47ON1oR7pdf6G8q4mAiIgAguNgH41LbRPROMRARGYOwKBmiOMGTu4p+sNS7RSFseWkUBI7yuUrZnZZ6mbEvZo9gk7eyhhf/HQVvv+wZrVUzkbW0S4+iRvUWEfrkdfKdznywXTkvwVleAfShfSmBYMHA1EBERgPglIQM8nfT1bBERgXgiU0wmrxhM4npPWaJato9Jh9ULJhi+8z6649XxE9CNWanbZTeuH7ZMbitYxsWRexjkXD11QgvgIXyjTiFmWHmseyqxyhDfW6SIgAiJwjAQkoI8RoC4XARFY4ASaWUODYQVo4HfOWSXZskQdT3CLqDMTBN3bnIiXLcYkwkSjZY34bnv1P51rpYkXrFov2/s2DtrbXthjPa0GPuI6Fmk6lohMo87500xQXAA4gsD75DhCmwmvyqTIIx/cnEamE0xi9HHEWbqdo9VsdxfJPkkzGDhimf1mDSvUU1brG7FWFa+NmgiIgAgsIAIS0Avow9BQREAE5paAi7Jkq2qNZNFSCOWJfMUKldSMD+lsrLbhbNlGX7XHVj6+xoqxESum0vbZ2wZt7V5EXXMxIjxFRLRuVbRzg8mFp3qLeqaP9V0DJw36OO49UMs+sTFhuGmY2kimkwaCmmQb2Tpwd4/a4O4+a9bcfnOsT9b1IiACIjC3BCSg55an7iYCIrCACBBPtnKiQZQZqwY+2jxirDJL0HiMWYWFYsa6xsfJVvGsrfjtlRZLlazUkbW/fiZuV/QNWo37eXq7OBk6Ek39Cp3u454pau2pAcMeXOeR6ElxHMPrnLGUJYk2l/cMEuGnAjvn888E/JCCno6z9omACMwfAf32nz/2erIIiMBxJuAR6KYVLTeetzQugAoiLeGRzhlaZ2PMEpmslVN5IswdVrvuMcuvX2od6aa9Yt+Afe7urXbpcMkyde4ThE1nUeMzPONod4eR4KO9/kReF47Vl9HWSvB5oIX5CmItPot4Mh3YaHIVzhssWmXvkNUGJyzeTFmjTlbuWLJt7Yik3oveT+siIAIiMF8EJKDni7yeKwIicPwJjOFrrnZaLEfkmYwOnlc44ZHNGVorUQoipNl6NVimYgUbzj9s29+NsCsVrbeWt9/e1LR8sWSVRsYsPbMYn+ERL+vdLQ8/I6LdwJFwZ0YFX3mVz6Z/zFqjJXIK4otmv0el6/jMvYUR6mBDP0RABERggRCQgF4gH4SGIQIiMPcEmrvNdry/bKUKgq1VC7y3HgGdqcVqvVbJDFst3om/uWTNRMty1ZSteH+f9b/+ect1xu2tzwzaE98u29lj41hDjt/ktqlR3NAWMdPYF+r+cNy+9EAySC3LvwPERstW27HPmntGKfbifxVhhObDCSYT+sugpN290RbQs3xoC/XFNS4REIFTmoAE9Cn98erlROBlTgABdvbd51ntIyst1VrtHg6CnxPkdh62OhMLk0SjG56dAyFcxE5QS01YutoFtLqlavimEXpxj4QiqM/9y5g1PlWwdGaRLa6V7LZvDdn/fI4KK9yvlSxZDj+0B1iTFCtJMsnwaFogmrmQ2yAgEY1hP5qbzdE1PpZZu+tiDxtjlvGsGgnePxUnyo/6bTEp0Iu3NCHZxDOeb8J777iVt+MlH63Ajs+D6z37ScANb3mTjBzkSfGdgabO81nEveKNmgiIgAgsIAIS0Avow9BQREAE5paAp0sbLVSs+eCYVT/ftPElY9bAelHDmpFBKFdSVYRbAnHXZZ31idkfXllujZVP213xOy3H9csTGfuZoaytGE1bst5Jto4Y3mj39yaZaHjq/2o9OCZMpcNASAdBZJJpUAId9vFsW0hnmnjGx3Gj9w9Skpuy6Fg44nzh8B6oczJxNEhxV/f0HG4r5wtNttaw0/ls4rv67Jy162b/bHRUBERABE4wgVP/t/wJBqrHiYAILBwCm/Jx27gUu8Bwt6X/vNu6vnoRmR4q1jW6xIqZCunSiJw2Mzae28cyN+vAq3nO6anZ6+7ssMqvDyMCU3bVi8P2pYcm7NL+EesoJ6yUIQLrOYx9guEp3oJsGuE7IpY9mtyiNykd7pMEg/LhRdL8DZWtumvYmn2kEiwS2Uc0J7FsBKnsmOQZayWDct0tBDTfZgj+T9iadMxuuPoae/yrX7Yd991t+TTVCNVEQAREYAERkIBeQB+GhiICIjC3BCpUHPz5SxdbMpa3SqxsL/7qFiaqrbVGYbflyKQxkosheBuWb1RwdxxC9Naxb5SINhNdzrx1l90bvx+LQsEu373bfm9zxcYT49aDo6OePLbc0B7Zndrnlsoc3y3q7yCyjIp2hzPReKLSZNRIkdc5zpeNVorMGny5aGDT8DTPbnv2Htg/GjWi+A1b5J7yXXvskx/+XfvdX/kla5QnrFllcqGaCIiACCwwAhLQC+wD0XBEQATmjoB7ip9YnLN3vTZp/ZmE5bpPt01XP2s2cKY1Ug1sHBWrJqtUujsdr3M/lmOXrtO3VhORTeKNFiW+x7nmqttX2cg7d1gsucq+a3fZvrmhasM57klE22ZO9DH9zSf3zvb8WS/k4EzXTk0lF95npv3h8UMtm6168EwnlkAJe6GadJVXL+N53jkS5HI28m7X8EG7cA5SChKdbhJ6DjIAxutudrECYnptLmf1ezfYo//yJZt4+HH7nvMvsJzbOLDEdMQygbf8UOPRcREQARE4kQQkoE8kbT1LBETgxBLAmBunTPetq3rtVy5N2+Lxli1tnWNPv2GTTZBrOIWhw1pZoqT4pImMztbqVB1MMyGunKKEdypp1dSYLf5g3p6tP0bJ6RaR6JL9yramtQop6xnDinCC20yCeCZhPdP+wx42XzaSpAZMwC0F50wrQQ7nUav2D5FAw0ukB9I6uF2QvQ527ndOkP/ZajXLck1vEo67dtnHfvmXrX+g3zrd/lKhxDrR6GDyIWK71OQLzszfaw57uDpRBERABOaSwOx/Y8zlk3QvERABETjRBFBujVTGqulR+8pZp9tnzmraEqKap2UvtWdftxPx10nFu6oNLBq2XHnJS0bnIjPshXKHVcnIkaq71aNlmVrVivFdduHdF9uTHS9aqpS037hvu33kobINL53dT/2SB83hjtmEdPgu0z1uRkEdLYYSZgXxJVaWer1uLcRuefdeG9+11+IlKjnypaTpeZ5jaUtXmsHEShfQbttIE6WOVerWxQTM8oMP262f+6Jtu/8he8drX2f5UplbEp3GB11DSCew1GRScSvk0mjq8nRD1j4REAERmDcCmpkxb+j1YBEQgeNNIBBuPlEQX26a4ic/c8UyG+8o2vueGrJL65fZk5e9YBevX265ylbEMenS8EMTOg2q5SW8Gh5CuR73tHRJKuc1g2qGrXiFiXCYD5IJz1zM+dvt7Fuy9tQV99qa3MX2wSfGLUn57988vxPhh1pPuge4juBOW5l1v//xbDMJ4ZmEdTgWP+68vLUjvtguEMpettxcRPtEQcRygomCcdLOxQdrVkH0xklXl2yTYAJhzEpYO7L4n6vwqmcg5L5mvOhZhHM30fkM13ztnz5jazspcFNHGFfIkMIdmHXIRM4Eoply3lg76rW6bbj9tiCNYKN+bL7y9lvppwiIgAjMHQFFoOeOpe4kAiKwwAgEQhBRnCSPcJ28wjXKdH/89Jbdtna5JWvjdl7tXHvxj4qWL69B440yqQ3h5sKP34w1lnH8zOl6Ft8uQniGNpjut4meIXvN41dYV3Mx0e5h+/EnB+03NxGtzmeMIuJBQZYSIrJFaeqF2njd/c2FtHuWg6Im/rcEwjiGUI7XYxSWiVlzoGjVIGJMpBlfM0cO6s6vnRsa8ZysW4EqjuVtz9qvf//32xNf/7qtyWbwTGOYJlbtqr1F3uwEX1TifGWpVorWt3u73XfXtwMB73m4DyX+9w9cKyIgAiJwgggs3N/mJwiAHiMCInAqEyD6S1SznkRET5AiI5mzbV3d9gOXd9hNsZK9ac+wdf3HOnvsm/fZOeuXInZdKKeCiW4VJgrWExXLUVAlhvVgMjj7ElidiUWWYjIiZl7L3bzENl7bZ6szp9lv3/8MExRX2h+tzViiniPbxyiRbYqzxA6R7eMlTzgxO3jF9ju63zh4WVLNkU3Dqy0miTon8HmXB4ZsHN3r+ZtbWd4FX3MjKLntUf52Fjq/3L98eGGUAhYPw9pxy9f+wy5cvpqsJUVLFMcCYdwMJxdiBYkxQTOXyNtDjzxsE+NjRKAbbPNFBitHnQwdHvxWEwEREIGFRMBjC2oiIAIicEoSiBGCdisG/gsz7ANeHtqjq91EUX/+tJo93r3YCukxe6VdZvn/PsMq9QFrZksIxDqVBZngRkq6CnaMavKAfA5sDRFfsJ9L2JnMEmNWKuy1Cz+/1HIUq25kcnbDI8P2M9uwHxCIbbI3T0nxw23+nLAf7jXHcl7LEzN7LubJnM7Oia8OlsVlUds3ZuX+YV4CsRvHzsLkQc+2wbxKotKc2MD+4hcQ7c8ywTLD8S4E9E+/6a22+4nH7cKuRcwbpGIj969xnnfc00xCTMKaiYJjw/atW75h4yyDeLZPJqR59DmIQB/Li+laERABETgOBBSBPg5QdUsREIGFQaDlYg3dHCfnc53JaSn80G432JUZMFu2zN7SNW5335GzM8j80PX7JYudttJK51NIOjNk2WqHkfmOzBs1MkJg40AFu6D1Fi59fTzFhMLECCncei2eK9r4+X3W8dc52/UTO+z0zGr7w7uGbOyqit10xiobJRIeaxIJP4x2ImwL/h4HPWfSxpGBkVs6in0DgW0jxheGBF9CSK4R+KPdGoN8dms5mpoTEd2xWN16slnbt22rff2T/2hXX3YZ5bpHrFUcJVrNBXyJaHl2DiLOXuI7jR9842MP20D/PsulW9aVSwWTEv3Oh8qIchj4dIoIiIAIHFcChx8OOa7D0M1FQARE4HgQQNyRBs1lc6oWtxrRU49GJz1RM97cRnfBPvzaRba5O29lXBgb37/HCttfQ8jVFWJbbDcoM91qdhwkmqMjzVfdJ53DysD9mPjWjJF27YIXbdUnv8PSRGNjWEj+9+MD9ur+UfzCCy+bRPhlwAVzgiByimV1dMKKu/ssgV2jibfDeUEkKJDigWZvfCfxgHTQOjmyvJG077v4Mtt+14N2xfnnWWVilOKEbT+5R5lTTA5MkRc6yZeYJJHq++65g3Oo4MhHUcUjHQ8yb/hT+IiCrr+eAhj6IQIisCAJtH9bLcihaVAiIAIicIwEertbsXd890E3CSKuTCiMuY8XQe2C7szBEbvl3qYtm8Ca0FOx+FdTNtrxCBaDbvIVlyj+neM8/Ape7pu80k1UJDHZ4L4uPL2FQjSM6LbILZH+2pk2/DEi1KjNZ7oz9qGzOu3uNXkbzlaxLuDtbeC3xlYSRHHdMDFpXWjf8dA/QzE79UyPFIctXJ3UvcHEwMCu4VYNjywjjT3vctLzOA+NkxWDdZ8FSPNxeeSdeDTjZXwegXfPskf26Xk8zo3+fvvcx//E3nTVd1p1BP+y54bmPYIx8AyPNifJsJHAjlGrDtgd69fbou4ua1SqwXnt57RZBg+N/HBR7ff5qV+40TY/uzV8lcgZWhUBERCB+SGgr/jzw11PFQERmEcCcaKlbkNw8exZN55ZVbCPvxIxXW3YQHXMHnnTvdZVenVQYKWG9SBr2DvIyBHDueuiNYGqCyK2YQh2mndpIo4bbxuw9A2IwPq4vXL3uP3/T+yxHGnwsoS7m0zMq1coVR3HY4IXOFsnBD5HzSf5BT1Uzdw37uIXn3PMvc6+PZlVI4MwTlTJl903bLEiCeUQz26h8LzNTcSyMekx2Ga1VisRZccj3qraKkBc2ttrT93yLXv9K19ptZEhwtctSqIfsLq08EYn+IKQycRswz3r7b4N91gug18cwR7YR5DmbqlREwEREIGTjYA80CfbJ6bxioAIHDOBZCNB3meEHQKvScGOVDlhf7OmbudeNGbf/3zezmlebHtf+4It33CalXM7mCOHyA2MIPzKxOsbaFGsGd4mA9DBevRHA79zlgIgxZ/dbunBFTbyLy175XjOvnDfmP3aOTXb3r3C+jpIdVetkSoZMU3J6pnvFr3zgfUgTd+Bzf1rSQS+y+QGQrjlI0Q7t9PKtSPlcaLCKVLSNYoVK44Mot/xURCNjgV2FY+us04lQQ+IeyaO4HsC7+M5nVMjw3bushX20Je+bEVSzrn+bZH7OagwiDAOcncg0j0KncATsv7WWyyT5i4+wTDI2OFzDv18rDE+PsbGE/aPPboiL3SUhtZFQAQWEgEJ6IX0aWgsIiACx52ARz6r/ObL4ciYCDQr0deWC+RO+wB+6A3LK/Z3D4xaId5hW655zs764jm27+xnrdvzFsd6g+wRLnTjcY9IY8XwmXS00LoRbPgP7CGlQtkWE+Uu/X8v2PZ9nXbGI2vs6hdTduuumH3nG3fYcH4pAt4zUdTxFGOmmF5H7r/l4a608zBzNuLUx0HIl+7SliAxnuby8LjhoAgKoyR59xhZSVp+mp/vxV5ccyOAs4zJ34uYsY099Ih97A//2N7/rndZq1SxUawscewazM0M7DBMD7RGMmVlrCnFfX32+KMPk5EjYXmizy6efSyTwW9WJqPOPvmQR3J7NREQARE4qQhM/hY7qcaswYqACIjAsRHAflByzeyNKKjnQHbV2DFetn89o2JfWlEhRVvFVlXX2sPXP0KUuMNSsTxCsTIplD2yiwKfpbVaFLWu4pluFCzZ6LHz/2CJ7Tptm40julupov3lxpadtnsfcxXdh4yCrB9edo5ZHrn/kGcfCbwmvoeocRxF7Wn5bLxu5T1YLYqeeq/GKW7X4BSi8UkguO3DL8VRApZ2UZNuVH1qmPzPO/bYL73jnaSvq1AtkLzQFWLbTLR0LzSGFHI2k/oPv/Sm+x+wZ55+3LoKObKT+P0c7tTeHqpHnmeKPvsZLt5f8sWkfal+ioAIiMC8EpCAnlf8ergIiMD8EHAvs2eEcAtFEJxFMdZsnIh0aqJl77my1z74mqVEqkt2UffFtvOSCcLVKyxJuro45ycbFEfBFx3HejFTS8TwFFOsJR4bR4ymrJjaZqs/Fbf7q/dYoVWxy7cmbP36mK0b2YvdAQsFZVyOtHngdn8nst6a7HHEbIweR+CmPKPICBMhdwxaYl/ZEniz3cKSJOTsYtntGe5GqSF2fd0FbYbw9HKU9S++/Xrb9tWv23Pf+Cbie9iarTJR5qYV8UGnyDiSRIRn+QJQJ3/zhvW32D23/xeTEIcQzghjIvbuEw8i9P5+WFRabhGh+78CBJUN+Qx8omC0haI5EM4uvoMexKmjp2ldBERABOaVgAT0vOLXw0VABOaDQDsqSr07rAR18rbFWviQ3VaQpXBKMms9pYzddBZ5ilesssxwyi5Ycp7Zo6sR0Ys5v2opBGYjnrU6JcJDwTf1PZIIVfc11zxyjd0hRSQa7Wiv23i+PTvxjI11bLMViNi/eATLA37gXOAHrpNGrhZU/iuUUfNkxmhRraRdKntSLBMRdj9zy73Y4UP9N7mrYTzHcbdgEPFNc+/0BCXM9xJxpnygC223djBilrw3kxhbdH/tRIpreH6a91lFufPqc8/ZFz76e/b7P/mTVp1AEFNIpsaxOGyaqOwU755gMmQ+3bStmx+1Z5580Do4J40lIyioEvjD25F9zzLivnGDceBR8W1ai3Pd4zzV5xxk+gjOiP7w0auJgAiIwMIh4L921URABETgZUNgNktAYSzNxDuzgULRKhh233Fp0T5/SZfVS4i+3yjZ6F91W0eL7S4iqOR9TjJp7khbKr3Hzth0mg0PF4n4Dtp12zrtE5t227rBsmXKcatmEd5YRcY7Kohuot3VLJFkj+S2u+tk755aziPOQQuOxziXCDrWChutWGXvcOB1TiB4297jyV/3LmYRsT7NMI3/2oV2vNSwNbGGvfPSS+3uf/6M7X7kEbv4zDOJsbtlBad3lZR86STZRMo8u4qv2eyuu+6y++/dYENDQ+2Iske/g8G0nxNEmT3SHOlHyurA+ZPveWCH1kRABERgXgngdFMTAREQARFwAkV3ZCAu3fpQyyRttNVtv7x2yF69I2/Ly3226N+Wmt2Qt8aSp7Az5C2Tz1rNJxceQauQ0SM9OmTn3XKGbXrXi9ZFJo73PJmx5afvs3df2oMFAosDwrlF1osGkekGWUISCGoGhmBmEXiK/YGupD2a695lCpXgYW6ViaCPYTep+iRHz/Dsp3mkN1j4ViCmPb+zR7ErlYr1xtK276HH7ZNf/LRdddVVVq1gz/ALuXWGZ3v8O5Uikk61Rs+msXXLZtu2dast6uzi+lIQgU9SotsjyYEdY1Iw+7NcPM/2hcXPURMBERCBk5GABPTJ+KlpzCIgAkdNYHqLQPt2rQQ5mqlYWEYwJikaWMXEO9izyN54ddPuua1hhcaQpd+Vscx7L7ah9zxluSKh2Jlt0NOOMUNWjrHuDlscf94uvKXHtrxuGH90zq7avsJ+O1Oxj56dsPFCD9FtF8VVq/Fbuh6EnaO3Q5iSis5zWGTwYARZNRDPMVLTJYk4Nzw6jQhv2ycQ054tw20bNWwUQQnBmq3oydqee261+55/0boRvykmBsaZOOme5kB6k9quwgREz8CRQsg//Oj95K3G000ekg5eu8a5norOh0Yek2BwbgnxKHQonGcTz7MdC69vf0HwG7Zj21ECWhcBERCB+SQgC8d80tezRUAEFhaBdAPxTJQWEVqnKEiqgTcacTmSKtjbX7XSnly8yNCp1vizhC2685U2kBo94vEnmilbXGzaSHfN6umSnXX/IksMpy3Nvl/bXLavPZpBxE9QyIQINMK33oiU//bornuQ6XnukxxnvDsH8Gbjh0Y8h1k1PFIdRKs9kkwFxRTZLJJkz8h5/ufSuF2YzdkLX/oPG96y3XoR6IkM9QYR2F70vE40uYxfuR6I6aZtuOtWu/v2b1mLCDTlZ5h8SBEZ/nOvs084DEVu+MUkXB4xGC4IRXW4PJp76BoREAEROBEEJKBPBGU9QwRE4OQgUCO0imBOkiUjRbGPMh5hV6KVVM0eu3i5ffTcLhvH3jGOH3jLL2y1JY9cMe17zSYi44jTFv7pNKnxfEpfM7bFMn/fQVy3z8aydbvqxUH7iT11W1Svki4uz7zAbBCAjTOOODaNDBaOeKluxT2DlN4ukbaZ4xi3XTy7aEZbB+cHQVsCt/5LvoV47mYGY+m+++2uz33W7rn5K1YbHiS6jKAmT7Rn5Ejj84ghsF0Q59y+MrTH7lv/LSYGelEUn7BIYRSPeQdZNA6E3f1dw/d1aX2slQUlnqf9I6WdIiACC4yALBwL7APRcERABOaPQMwVKK1GFNZb+yd+aFeh40W7eQX2istS9rdUE1ySxg/9C1Tm+/Sl1jhnIyJzxFpVMm3UJ2wiV7B0Y3rbgRdMcYNxEo+FP66RzFv8qhet8zE82G+vWa242v76zr32A6cvsbdchd+6xEn5HKnviApTarvRVw2yaXADtC5ZNpCseWwZtVScjB+1QOQ2yBqXpThKOV6zdaWWDVZGbcud91GGm8IviPdWacJifAmoIrwTZPpoIpzTrfFALD/1xBM2NjKACGeM3KcZFJlxGm4JaS/9ZyiaD153W8mBSHJ4TlQUR9f9Wm9hKrv2sXZuat/veaaDNj3K9jH9FAEREIF5IKAI9DxA1yNFQAROPgKdFB9pYPG4Z3XWPnZZ3rL1rI1VR2zDj91miaFzbIJsGWNYIWrpguWIXs/YXJBGu5+I8PWeuYYJhj1k+2By4uVDo/au54Yt3UmkuEbUe1e/NftGmdxI9gx8yq6+u8pYP5hfWMxWEe6lYF8T//aSvqKV04zhqeftE5/7lO154GGjqLhlSJF3oCGQsYhQV9sKuZRNTIzZbbfdZiMjI8EpHmkOv0L4jlAMBweP8sd04tlv5cLc0+uFAj3MOBLHVuJ98pvMUT5Vl4mACIjA3BNQBHrumeqOIiACpyCB8Qy2iwrFVhJd9qnVNbuAeXM/9egee0XllTb8umet55FlZNDYQzGWBhP5sDu0yxu+hEQLKds2VngpRMShFxLx1HIIyNHf6Lfsu9bYoh+rUBI7bp96pGGLt5ftk2futnSsYNU0UWdS59W8Qgm5lkdyfi1+aNLftVCdKfJAF5pVK5T77c/Tb7R3P/AV0uHVrDnaZ1mOF7ku2aIEOf4OL7aSYRLgMy9stL19uwPbRy7nBWJcnGPWwJphMS+2wjN9fUoL97konk4YR49PuXT/ZnidT1vkhXiuT0f0sU1GsgMDCocUgd7PTCsiIAILg4Ai0Avjc9AoREAEFjgBnzJXo/iHh0nT2C5+Z92EfQZPtGGbtsQKe+Znt7HSzt3s1f5mbBQgsRip7zzqjAEjaEG1PSYmNvNWueBR2/SKIRvEPnH/RL9du7NmV/YjgpnQiKfBFpVJQYf9wycTUqPbkvhLKlQ6LBORLvT3249Wkvbiadfb9dRP2XT9L1kH2TyC2txEvRcRscYgwWRAl+51u/POW22gbwfeZwq9eGETLB4uagPxG4yJUtwR8ezrYW8PfPqf0WvCM0Kx7NvRdd920ez5pg/oZC+VDh2ygHjnqJ+mJgIiIAILhsCBmSALZkgaiAiIgAjMEYF89sbYBWvn5GZp8jfHmGzXpFpJCxGMdLXblnbYGaNxu2yEqPKebisNZS17NSVOGhQg8fCEz+Sb2psFFCQCO9hPpDXuKeAQxD5Zj3LeOx+vWN+rBy2+vNPKG0YJUFftysGUPbqoEYjqiQ5+bXsBF7J0JBhTVy5hawb67aOrLrTPJy+0t+HDJtaMn7lBwZO0TXzuTissXWpj5622YiFjQy9utkcffsD27tgeRJtxQAeVD33yn6elc8tEIJLZbotlhjopnB3kVPHr+6LHw21fepvu/PaRyE9EO2cG58aJejewqMSY3FjGunL62jPty//+X9bXP/DhyBVaFQEREIF5JSALx7zi18NFQAROHgJYJAKzrqd8IzIaJ/RcjtlvnlG0FbFe+84dOy3z34jjJVkrvX8YvzEh5Omai2cEc9u2wYJcGHEyaRQnqrbp8WEmApJZo95je8992p7G2nG2XWiV8rD91AuL7Y/PnLCd9bxZIWWFsaLVsYu8tS9tf7riu613lMwcNk4dlpbh2mCMzD1EBOcQp2Of+LL1nr3UHtu9xcaaY5al3LfHe9tCmS8G/t8Ul4YLehe1R9NmEs1T94fbCSwbHmcmz0hQHj1O9pNMocNWr11mpRLebjUREAERWGAEJKAX2Aei4YiACCxQAojZMr8xWyl+kIPZrRyJZNMGVi+xd3SUbP2+vF00RpaLf8xa8iwydFzbnoz3kreJj7Nr0vfcStuWZ4ZsbLCDSHOaCYhu6UhbKTlmqdFOO+vv47b4ZrzKN8ds3ciYff6h5fb6q2O2eDhmP3725fax/rSl8kwPrFF6nKwfeVfNnjoDAe2TDROU6O4f221PPviUrf2HhPW99VzyR1Ma3AunJDPuCOGF8Dnzn0eivQU/gwqHHlluWyuCA4f4EYphPy26PvWy6LH961hSAncMAjqVStmyVWuCsdWqLqpT3G/qXbQtAiIgAvNLQAJ6fvnr6SIgAicJgVrCPRmISrcuB5HZFpUKPZDcsh4KrVz7xqQ9dGvVVpZHLPN/ltjTX95m6z5VsM6JghUzlLzG9pEw7BXkmEun8/bgA89apeST9LKIRibPJbBdVKlyiB+5WCAW25m1XLNk1euHbZi80Lahx8bqO60//laL5RrW01+xJsVNGkSTc6Sja7lnxAuv1MjZnI9ZsX/A7n3wUcpyY81gxDUmBtbJrFFOZ4Kcz+SnYz/SmWh6hXdLBWra3+1Ac1/y1OZR6/3Cl4PRdT83uu3r0fNjbs2YvGGdqLMfTyaxajSStnhRr3V0dOD1RrR7gJ738XzZnoRj/0WT12ohAiIgAvNNQAJ6vj8BPV8EROCkJtBkMt9ItmyJStZ+7/KE/c49+2zpsNklz15ttqVk5TOeJWEGQrFC5UBS3O3cOWwvPL8NrdtF1gyfgVgnHzM+5ESWKttDViINXVepYGPpAURtl2UQ7BfdsM4q28wuWP0KTmcSYhVB3crRAzWPwGxbMFo1npPJ2i3f+E9sGghwfNpx8k7Xaw3zEuJlJiK6WEe5UnEwYRnmMvpcxCzHoklDXPR6i4rhYMeUfdHj0fXoteF+XwaVC4kyB5k28DrXSaFniPrVq1e3hbYH5iefHT5PSxEQARFYiAQkoBfip6IxiYAInDACocDzBx6NeEsT/W00KUqSKdunl+ftm9/RaxvvGLfiyLDlfzph2R9eZPX3jttjG0kVN4jVwlPFxTpRp+49JsqK39clZaNJqWz25+oZK2LlyBUR1xRDWdF/pnXftcRip/diIWlSIIVKhllsGnilY/t91jGrlsp29913WmemgPeZqDZp7uqkrUvUynZm9xIb/eId9n2Fbrv3jZ2kkGaCIP/V+BugjoDurCKuEdTTtSif6PFwf7j0Y9H1qef6sXY+DfdjUFGRcuIrly6zKl8G4jzbrRvVKoqeY94CD7asGwEL/RABEVh4BNq/qRbeuDQiERABETghBFw0h/1oHtjCcNzAhuC5k/PFpu3t6bA/vjiDJWPcykN4kG9K2JZvk2aumLREuht7QpZsFylLpCjMQjq7GuLVvcaJJFUNEZnxZMmylaJV8yvtyjfcZPu+1oUIXkzSjZolSelWymL7YCJhjGwb8ThZM5Ipu/euu+2hBx+0bAy/MLmq63HuSdGUDNaMi3qWWRfWiXOL+Lb/9r/tVSNEwhHQHWUyUjNsjwpXJrWzi9xon8ojeixcD8/x7anN99UpKuN8fdmEUQOLRs+SXutZvIRn8RWCCLkvXUiH4tnv49cezReaqWPQtgiIgAgcDwKhHe143Fv3FAEREIH5JdDb3Yq947uP6xjcp2seCSYrR6w5gfArWXepw16LfeN/P7DbivG07U0/b5f+abdNZMcN/UijnDZp6Fww1jFSuwj23M7FUbOlZ77dLr72wxQIJC0eUeleEk0/9YYft4vSS0hdR5aPZJl81CjesQl7+KHHrUY5b/cJt/A+Z7mjx7UL2CPWEXXGHIKnumljGLfd4tzd0WV9VFMc/tW3255LVgdeaC9a4oVZkkTEZxLBPmJv0eOHs+7XhOI5nU7bot6VQZq8YMZgcD/+CvIvMH7iNM2v9ee884d/2p7auHmm06a5UrtEQARE4PgSUAT6+PLV3UVABE5BAi7s9nfsG567ItWoUi0wZdmJpI30Ddvtyyv2mbM7cGGM2srq+fbM3/VbJu45mkv4jlGzTB70DBhxJv75xMKJ0aRd95M32wVX/b5Vm4uxO5Ssl/LgI7Uxu+hTf2AtUte109+lbeeOfrtvw91k7qA6opfjRh2nEp6vIma9XT3Wu6jLSg3S3JFDuu4p92INyzJ5cPvYgG3b9oLFi2VLB4mq2x8OmvqQzYVstE93wVRR7dsNouaZTMZWrlyJB5wvGVhW2vMVvaSLzxZ0Fv4NQH8dTcdU+0RABBYmAf/NryYCIiACLysCLuxcAE9tgYYjQhzWPvHjnojCg8bYj/c3P69J3rUW0VsPnyY4qTlSsvpYpR1NZdKgUV77ptOTto/S37+2edDssVfZYz97r13wiaU21Bq2xUSM07lFNpx/lV3zho/bCKW6Rz09nnuAqQjo6eyKzBNMUJ1w9DSzrt96t61/08+QBQSZzIw/F+Nlll7NewmidGknUwaxaniaECSqxVPYJTA4V/BE76ZCoT+zgciOd3RbbKjMZMWmdVSwWGDnqDGRLw2TsIVCOFyG+6NLz6jhLcjfDMsGFpMEKf78Gs+i0SLNX2d3j3V0dTOamFUc1WR6PC/W4ud5fpCYA57cH94//GyaM3xO4XlaioAIiMB8EZCAni/yeq4IiMCCI0CwNmhBDZHJ0QW6GY3nk+2Y/RcIZvc7J6mSl0LAlkexZeA7jtXJpcx+F4MuDckIjQTutJtXpq2BWP2tJwdssHm6PfWBQbvsxldb7o1vtLPP+FkbjeF3rndw7WLEOrmjg0fwVDJUNMrcl8E8eN/ddiaCe6BZtGWNTDDxsEJUeQkide3yFWYlUuAxmTGGGC5XG4j7bJCvesvoXhsbHwtS3TVJt+eB7wSWju3pinUg9ptM3IsjUrP0aBaOqcJ5uu2Wv6eLX2/+jYLou/u5vS1fvjKIOrtdxScsJik17h7o4JtJcEb7RyiUI7uCVX/eTMemnqttERABEZgPAhLQ80FdzxQBEVjQBLzgoLf9+tA3gigpApm8b4F9mcqBpXEizjVELmI5yX/EXvE4E5n2SYEI6hR5nC1eta+tWW7fu22nXZPqtEMzf2wAAEAASURBVPWLl9kr3vxHtu/sM6yfaHIesdtEZDZa/cRj8VITr00Qwk0QxX7q6Sesv7+PwoOcx6BK+K1TlLhO1qu2ZvEKW07kt1aesBLPq5IPuo54TlMgZVupinAeZZIgApkUdSmixf7dIJbm2mbFVj6617ZefaF14qXwCYQeLfa8HFNbVDiHojbc114SeUfsJjyyjR0lg8+5d/kyxD/mDER1DTZJotIunoPrIw84lEAOnxO5RKsiIAIisGAISEAvmI9CAxEBEThRBGYSb6Fw3q8lEYeEQhGIiGMiwAUE7sSeQYsTWq2RWzmGmI0jFP26OiI25n5mfMlJsl/U40WbKGcty3ZqaK/t+uOftZXv+jF7B/cbJkNH1wSRZCRzBYHNhZYmP3OtWLRcJmV33nkrlQLjiFqemY4hzZkEiDBeWYrbWd2LrIdgbhmRWqoXLUXe5xT/NckfvW2438bJDd1gsqGPLYVwJSdH4DvuQkGfRrGS3NCwZe/ayhXrbeL919p4FjtIiQwZPjFxSnNOUSHrfmZvvs+FczywsWAv6VliuVwuyLARTIx0FjBJMiZvwX3Y9i8Y07WZPo+XSvrprtY+ERABETjxBCSgTzxzPVEERGDBEnCfxsHNA8/oQWuMlm2sNEYSDIQzojkQyYjjpotMv8QFIpFhSukhqoklE93t7SnYrkefsnvv/KadV1hJVo1xUs0VPMZM3uU815K6Dj9ws1SxdKJsW7c9b7t2bmPdxTM+Zm4aY73Gfffgv0gv7qVcN/aRdApbSIu0dzmmGiasv1KxfUND2EaQrwjnJqW9PVVeDU+Ke6RXZPO2LJWz1ji5ozsoGc69V9+/3fpit9uOn7vScsmCjTPusEWFcyigfZkgX3MYTU5QBMYzgKxZfXqQv9nT03nEPuj7b9S2dASb/mVk/zeT8IS2uD6wpTUREAERODkISECfHJ+TRikCInACCPhkwKBNBkp94mCjQiYLorZWRdRipagjaF0xJ/Ameylsdzy3G4IX0ZxESOZZDj+1xR7YfYt1jnmRkFpQbdCFaZWsHa0kkePmXsvV0kzyS9qG+2+3rlqJctsUSkkSvUX4xpnY1yS07fHnVowodq7T7nvfa+2Mv3+ISYZk0SgnbC/X7hwcYAQZ4sxEnIlke6HBNLmkG/UJO7+XVHV17sUAa9hJkpzvkwVrrbrtJAf11q/dbss/8D02ikB3r3LYQtHs2+G6Lz0C7e/Q5P1OW3tm29fMOalMe1Kg57P2yYRuSQni2YHtZf9dWTk4yj1T5Dm8QksREAERWKgEJKAX6iejcYmACMwpAY8ie/PsEZ432SfNBZYNF8Tt2W7s83wReJcJ5XZiPxjc228tJvKhnFGl2BYCsexnxJlAiJBkYl6KyXNoXcpSl2wJFQL3bHnG/uXTn7Y3XnCR2XiZB7oXGLHtkWafyGcjQbq7ONHnmo3bvV/7tuWyWYQ1xxDobn3w5gFbXw/cy/ihY1QlbJIib/2bL7K3/OcL9nSp31Ill9dEsjnL09hVSV1XQ9ifg9mka8lSqyK0CVgH9/Loca1St6ElXTa8yyc0klAP/3WWaHnnRNMGC0SQeU4KcVx2QcyEwESdSDoiGLcIT2Af41nUu9QK+Q6rBJlC2mP1n20x3B68JyHxK5xT2PzI5EcweW54xMcXHgnv0z7m94weO3CF1kRABERgfglIQM8vfz1dBETgBBHYH1xGaPokv/1+Z8StK8wMHuBYlegsEefqyIQNsDvuEwaTZLTgeBPBSb0RRCHRXLzFZbzDwQ6iyx3YJkoPPW2PbtyE5xmrBZ0C1cGbtSWl2zFciFati3Rzmzc/bdu3brGOfM5yeXIjM7gk3meP7E4Xlc3grtjebebFBPed0WP/3thpZ6La667cSVvnXwpy3OOcrsXWxReCKpP33GqRYWJfk/er4ace4R2GykUb2jZKJcIk3xlIYQeLNF7uvZ1EvvmeUOYLRJL92RKTErlfCu93GXuIi+9lK1aSdi/Lu5NXmucdqk33HjNdM9254b5wOdO12i8CIiAC80FAAno+qOuZIiACJ5xAKwjnIvxQtIFdwQUyo0gQSU4RJS4NjVtsHE/z5ES5ZCLNRDmP7bplwe0aCFbPb+e2BHRrmtR13Qjg1yxbbJ/4oz+xFXiMPSNHiSwXtU6KpGD5iHmeaIRzAguGUWhl88bHrDbh1Qpb1pnDi1zGwYw4dT3qQjEUi76MRl5rPG8ZotbN2PmKi17GTNYNzNaWIap84eKVlPt2Z7NHtSnhjeD27Bdj7OljYuIwVQtbTIBMMBHRM2bUeUePTGdZZvEx50mZV4FGgkh8HX93mvV2Vo64rTxtbXuM3KHBt44mwtonD/qXjpla+B4zHT/U/mO9/lD313EREAEROFYCEtDHSlDXi4AInBwEQsHnuo/Ubgmixm41SCIIi4PkX0bFxhCIcaKz3hounjke94i1R10D4YzqrFVsEZkvhjY8bH/wT5+2H3rzNdYgQ0ed/e51SGfSrCOcEaXI0aBq9UD/Lntm85OWz5GVgiwZHpVuYo9w8RwjisziJdHnqIhMk4S6Ri5pH2sKeVshHZ1PCFzLhMRlWDUa1XIgvj03s7cqdpE6InfrwIAVuXmVd3JBHOc9fEwZtopEw19XWGGtzX327CV5Ithpy9aTVkSEl7hPPpOneuAq/NKecQMGXN+YjJC38z9PL6Cj4/axTN32Lwbeo/uj69Hjvj/6RcLvpyYCIiACC4GABPRC+BQ0BhEQgeNOwG0OLsiSRJvTeJonRkatQUnrKhaHuKepQxx6aBmtGHQfUIwob5MJdnFsEZgabBW+6JXpRfZPf/7ntqa7m9RzWCRK5aDqX8tFLcIwgXDNYItIpRr2yCMP2xCT/DqwPmR4dqPMuYhbF83e2+Wr3bbBGNCj7sCeruEkIWLMBD7OGMWOsXLZcvuuRN1GG5Ug80f4i7xJZowK7/FMcQC/tH9JcKnMeAIDeBMhXLcl+aydVuimkErNKlmO/f7N9uYPfq89fmbShjB/9/T0WnxNb2DpqMEs8D7zc38LRDqsiFQf7ybxfLwJ6/4iIAJHS+D4/wY82pHpOhEQARGYAwIuml1EesYMyooE0eTxXfs8kbInb0aZtojshmI2cEkE1gu3X7TqNcsSwc3TW48+Zj/3znfat7/0JVvd2UmmCyKzCNhk2rNlEG2mI5GtQjR4eHzI7r3jW1YeG0Ksc38EaAqPdRpbCGp8UpT6r186QtTFc2ANmXzfaETWd7m094wgbuVoksIuc93lNoaA5rtAEClvMoZqKm7PD+6zLcOD5IzGfsIEQSzdViMqnkRUd9DPorT2uljGClUsJaTraOCJbjRrtvcjn7HC3lFb+4qLbMXSZeSP9huHg+HBLprpLuBdiwd6fPLwoRYSwYcipOMiIAInI4EwcHEyjl1jFgEREIFDE8CqkUMQxsgqMbZnALGKkGayXBM7g6dba1Gtr+rFTjybRjOH4CxbK4PAbBFxzqdt14b77e47NtglKxa1rQdlckEjZOvYQFyWN4leuyTOkHruhS2bmBz4ApFpjzC3Pc0pT33nXuhAOAeSGeHrkWZXom2V6lMM/YhHotvNl959Pz95h6RXNuT0IQzO9y9h59uvtMu+tJ6x5uxFrBoVPyeQ6l7iO2ejzQnMGhVbXcjZUiLgcaoUphD9DYRwFdGcaVHdMN1jz5QHbF/e7JwUthSyepTh0FEt2hgMUnUsJx655z9v/k6hIG4Gkehg9/4fwXH/ehCJTvs+L7oSNt+erUWPB/eLXDvbdTomAiIgAieSgAT0iaStZ4mACJxQAjEEcorUceN9RJyDbBuYNIgme+DZZVwcceg61b29Tc+qgU0jjthNM7GuE6vFD77+WvuNf/13S1bcO4xdwk/26wJd63dAGCO4s+RXvuPb/41AZWJeLhlEaNs+4eD0g35EBeJBBw6xUSVMHUxpJK1eGlE+sYg80BessPJDz1oZ4VzgXYoId49UD8f5EkB0/BImF8ZYNhH7SQbdKFctg+AuMXlwB9k79owMEmhmYmI1QXXDpO1h/GTrIzuHsS9OKXBsIEyyjLZQ1LalffRIm+nBe45tKxTrx3YXXS0CIiACc09AAnrumeqOIiACC4RAq4rPd+cAWTDwKiOKk+l0UAzEs3AEUhihmPZ9E1gZSuO2YhF5nJ951r78mS/YFedeaAWEZn1i3EOveJDJIddqR4yRoghwIrnYNR659y5L4ktOY6loBZFm7u0Cvek5ndviM1w6lgNR5jakg0XiwWI1xOj+7SqPdy2bxXpSwZaxuaNlyzPtcuBN3qPBQ5P1svVi3VhJSrx093Ki5FXL8e4xzi8ztgTiefPIsA2Rs9oSOSLD5IbGylFhcuNYV8Y6idI3mORIjZYgxZ1Hn6eTxcH7TBNJDt9TQePwk9NSBETgVCUgAX2qfrJ6LxEQgbYLAs2LDMY2QSYLquR58/zOPjGPFasWRyyLfWFJPWXXnXOBfeQz/2pJL61NmroGlgq3R8fwFxOwDUS3i+csAvXu9bchoCuU5iZ6TRaOBN7kYBKiF2UJLBr+JBfM04vi8NjBAjq4ZPofqNL95waRcyLlRNfHmAjYQSq7ida4vaZnFdYMjCVNsnJUykTEsY9wbp0xjDKmvYN7rUgqO8wZQcXEBBaRBJlHqrzr4om4DWMpiaPSfaJjhqh1tV0RZYbxzBaDDr6eTH+d9oqACIjAKUBAAvoU+BD1CiIgAjMTcOHsLt5A0k0K2yZRVi+c4iKxMThqr7/sAvvc337SkiNDhF4R3OlcEEX2PNAp9G/cq64ka8EExDu+fWugj5m3Zxmyc8QpVsIjsG14Bg/3PuOh4GGxYGbgweNqi+kD4tIFcVRg7xfIXOb7PZIb7GMlz/3rRNErPNcnRXaQyLkUr9v5+JTznRlbkugmr3SR1HwJm8hj5UAIJxn39rFxqg5WrIK/pETUvID32/Neu65vkcruDHzQK9Lkrf7oF23NX99gu8/qRTiTL5r7xPjW4GMIWzi+6JjDY76c6fh050+3L3qv6PrMX0GiZ2ldBERABE4cAQnoE8daTxIBETjhBBChiEVXgUkm+zXxAMcRoUuIKO+96x77q89+zn7kf1xnzUrJWmP92BYmo6ooNp/P51k2YklyI4+P2cMbbsM/jFgl0OwRWgLR7XNIL+eS1icnGgVT2sIQFY4v+XBaKDqnnutVCf2+oYD2HNO+3t4fs3GE9MBlZ9iZm4ass1Qi40bFGh05r9dCy9gLI/024un3sHAksWskyU3dQQaOWKscVCg8v3cN6faquDQqNpEYt0S1ZNmf+xsbu3yVpT7688Gz60CYGoQOhW98lsh6RHP7YI6phc87ppvoYhEQARGYYwKTf1vM8V11OxEQARFYSARQdPVyJUhjZ6RwO7Njke0bK9nbr32jVagMmMC64HMIPXWd9wTe54Qv8TY/selJ2/DY/aStIwsGojXhtg6P4jKRz8Wd63P3NXsRk7a/GfHs6nvG5sJ4pn7wRaG4jkZg/dau1Ytk1LhrRcv6Xr3G5Ts5nRkP+a3HENpPjPYjirFiBCKfY+zzsXohltMWLbdzl6yyVmmCaZEIaL4A5BDmMb5YVJtFK339foqwIN25Nu3fDSLtRIvZE/28yKtqVQREQARmJXB4IZJZb6GDIiACIrBQCRB59gl+TI5L4FP+4A3vtl96z09QsnvEYhMDgSUilSWHMseaRJrb+ZyxSVBi+7FHHrACkeoyQrOHIinNRIES2O33jCFOa3idg4IowUS7tohuCz5UtrcZI7TtX7uhOG6ffODngf0um9u+5ybWk5pHpL1SIs+LkSauUDZbPmF26+UI6IFx6974gm1lwmNXM0smjQwBcuwpiOxWfdzyCOwLl64OIvBkiCaSXYQLd/eoNtHpXUSfd/OFopQp2XBq2M5lFmEGe8cgKTkyrvVp/m7h1wJfP9rUdO27HfqnxPOhGekMERCB+SMgAT1/7PVkERCB400Asbm60Gl7t2+0O/7jq3bu0iWWHh0KJse5AAyEoKtihGmdPMlJPL/bX3zR9uzeSVYNPMcUUkmiNIMyLBFPc6iN28tofPjoXuiAaD5wve870MkU7VFut3AQRXYp69HukTSWjHTeXlzbY4s249euIfQ9Hh3zdHwUb+Hd1vWusCznJ7GpxDxdH5Fmd6DUPXRO2fHnBvtslOwirXQnJbwR0dy9Rvq6uvu+Wfd2osXsiX5e8JL6IQIiIAJHQEAC+ghg6VQREIGTi8AKKu898I//jL93zLLM+mvU8AlnsgjldmmQcnECcWiWI8J8z513WBoBXa8xwRB7RgMbh6e4azFJ0NcDOTmpnI+nwAvFdCienXiwjgh20e/rPhr3XHtxmELvIutupomI162TSofFRM1Wc84ivjgUyNJRIEOHC+ay1YiyI6BjWStyz81De9jOcM94UIkxxxeINPctZ9kXr3C2Z+jgy0NbQx/0wYdjPGjnHG0cT7ZzNETdRgREQAQOc5aLQImACIjASUhg1fJllmWiXMpLcSMmY7G0VWpx/M4xlkymQyjv3fWCbXr6SStQdTDGOSmOtYjIBvMEEc7ePJNHVEBHURyu4JtJdM62P3rM7RP+rJpbOIiGdxS6rIs0dYO8R5N0fD7bL8sXhFWZDluZJMcz0ecEmTc8/7NXDXS7STZbsKf7hqhSWMfnnCNCnSAjB/fEdVJnwmSeiPZblp5m8aGKPd8Rw/pBZUa830fTDpfL0dxb14iACIjAfBNQBHq+PwE9XwRE4LgRaHrhEybJ1YNYAeLY7Q21EpHlmD36yAYr4RlOJZrWTSGRFkVHWnEsEQjKaIaJA75fXwu3jszWEBXC/rIzbYf7w2V4br1OXmpS65X5MrCydzXCOOWuE5vA311HRKdSGXtldjmR9bLlqDNe96qF7s3G49wkKl1GQD89uMMyyYKVKMOIS5poO4d592Zj3NYku2z5kmXk7qAMd5mCMD/8UVt6/Wtt509f52f6MGZscymU5/JeMw5YB0RABERgDghIQM8BRN1CBERgYRJw23IKq0ON+HELz3ADa8I9d/2X5ZgE6NksskwSDNLDkXYixWS6uoedvflBmgtZF3XtGGx7n+8/FqEXiuNw6fcLW7gvuvR1Lz++atUqu/baa23z5heD0uNxosvuU145kbFNlyy1XOfF9uqvbbY6Oa7jJbzb+Jt3Fcdtb3mIaHoGcdxJpcKkdWAAqZLcukbEeWk2Z2sKK/mOUSaAzRcNfNL1DJHnRtw6/+1eW3PVa6zvwjXh8A56bx/XsXDYf9PJlbm819R7a1sEREAE5prA5N8Wc31b3U8EREAE5p9Ay60aCMpsqm7V0T129zf/wwquhr32dRCVxppBBDfmUVtEs0/U8+6nePdIdFs8t0VzIKbZd6g2VQD7+b4v2I/nmFD3/h7sI1LczvPcCPzWPlGQkdCTRJ6xZJx+jlWwXZx/0TlYLcpB9gxmQpJZJE4+aIqnxAr20Pln2lNDrLN/KBMn4txvA1hQ6kSgS4jmGjmqJ/jPrRw99bq9Cn/4OkR4ksi7T5KMs69OAZVUOYM/umYbB0bwWXs6uyCfB29AVg/+S7XnXB4knve/G2cdLiNn4u1Iz29fpZ8iIAIiML8EFIGeX/56ugiIwHEkEEO07nx+k+3Ztcu8Rkou5xUGXSDzn4vjQ4jhg48fiEAfzpADYcyJ4dKvaa+T8SIU0/v3tY/FqY7oUwSTRJw7O7stxYQ+LMxB8RSfyGjE0n/oh37APvOZL1gym7bRfNKWjtRtrJBkwp/Zi7/7Dnv+Q39rK4g2W5zqglziuZ9TPM9/2XcWum0lPuc61VY8GwfOaHI982WCIivVPJHsfTs5K4kAT1g3EwwtThEZRHaWqoZVHuBFVSZwdDAX8SXtcHhOvehgvlOPalsEREAEFi4BRaAX7mejkYmACBwjgfGxURva14ckJG8FgjGJdcNbVOyF69Mtj/Hx+8XzwYLZBbSLYc/H3F732K5n2KhRWtwjxEtXrLR0DgHs4ncyI4in06sxSXB8Ysx+8AffxbVk3Zio4VFhImCNGDIit0SauiK+6DgR7joRay/uUiXncwoX+IXcczlR7RQReS+ckuUc/6/G/XdXy4jnfrzSXu475sFwq5K9w60jWR5BUDu4Z46ItxdX4VEHtaMRwkdzzUEP1YYIiIAIzCMBRaDnEb4eLQIicHwJBJaMOpIQIeiCzYVsUIZ7MgLtTz9YyE0TWp0yRL/HwdcciEP4MW/tRbh+8LJ9fDKnM/FmdD0THRG2RIaXLVsRRJvr2CliRKPRt0Gxlxg5m72Et4toDyvXGyV781teb/d99TYbyCO/STeXw8ftx4Oy3YjrOOn4VqUK1lsoEMWmOmJljHsynZJMJD7xsEKKvr6xcesfGbA4qf3q+J5blDt39ZyvtcjAQbGU+zZZ7LwlFG1p2iiVDmvB85uW4Ry3x6iJgAiIwMuVwIHf/C9XAnpvERCBU5jAwVYNF75h95c+WAgfGkMokKc7MzwWLv2ccN2XYQ/CuxzzSHOC0tsthPLq1WttyZKlVqPMuEedEwjcsLFJC39Vuxh3wUw+ayoFvuKay8jGgdhmUmAWH3MNe0oHEwh7EcAX9i6zRYhev1WKKHWylSCfBhMPYykbRrU/1bfHdpWLVmMMNaLNda+u6LYOotYruNcZ+U4b/uev27kjTRvO1i3Po0P7RsX9MCegeaYR720GJ+CBeoQIiIAIHCYBRaAPE5ROEwEROEkJ4ON1DRqKZV96hDjcPty3CsXw1POj+8P16Za+zzvT9YJlHAG9BJGbSFGshQHW8TgnUbtxouUebZ5JNLp32ceeIg9dqsCkP0Rzq1qzUpboMxHt1HdcZGue2MsEQyLlTX8WEyQZ9DhCfaLWsJ1j+4LJiWTHJuc1EyiJJieJJqeIei9JdXA/s16E/Fi9bIsH6jb4fR+yV/z8O2zjO19jXZV4YBHxCPR+TT8VyCG2j4T7kZx7iMfqsAiIgAjMKYETE0aY0yHrZiIgAiJwmASmRJzDq7wMtkdyX9rDM1669IhxWzW6KHURjsVh0vERimP3NLvX2nvTbRM8w5eNRg3RytWI4wksG5kOSm8vX4FlAnHLuT5BMIl32c8PznWPtBdMcaHvFwZj9SXRaWwWPtnQrSjxnph97zvfbtVqBVHdsn058kNffaVlKkS2yRndIMNGssKkwWbKHhvqs70IX49Vk+man9wNK0gWS0gGX/QZVCjswoOdY0LhBJaROL7qFjHrGtUam3/4FXtFKRtEp+tMIhyLN2wp5QzdG11hRmGW63yZBIhHsMM2VQBP3Q7Pm2kZZAFxBjOdoP0iIAIiME8EJKDnCbweKwIicOIIhMItXB7Nk8OocnhtuB1duqhGPtPJepH0AiTuXcaCQGzYlx0dXdg1VltXV1dwm5nGE94zfNZMyybe5NbgiP3A26+zlUSyM5TjfnJpzG776dfagwWzHcmW3V3us4cqQ7aIiHMVUe7FU2qMsElcupsUd2cSdV7XOmAZiT7Lx5GjsEq1XrPt3/UBO+fu5y3N+unllD3fgwhnUmGhGrexdJzoNMKaxB3TZeiI3nO69Zk4THeu9omACIjAQiAgAb0QPgWNQQRE4LgRCMVZuDzWB7mojArccDtcNjwK60Ia+0TNg9B4jleuXG3LVqy2NKW0w3H40q0aU1v03uExPzfs4T5fltNEnPE370tN2DlveJV1ELjOERa+/zz81G+4ArtGmVzWGeuo4mMmWuz5oHNEvNeQ7/kCqg+uaaSJUleIJM/8V0E9lqPwTMqWc07lQ39nF92+xbZ2UoSFCHSZqHkVi0yGCYwl1tltpem1eHTY066HXKY9qJ0iIAIisMAIzPxbc4ENVMMRAREQgeNNIBTB0y392VFxG57jwi/cX8VjHNo83JbheadXIZ4bgQ3D79D+lRue73uiLdw/nViOnheue7o68otYN17mNOblN33fW6zKxMDSSIXJiVmexsRC7CA+qjyCfi05n1fHc9bFehNbST3msfLZWwvhPMKExRK9ODJkz/3in9rlt++0faSa7i6S1YPvADUYVF3kc6scae+8hYI4fJdwu3304J9T3zu85uCztCUCIiACC4eABPTC+Sw0EhEQgXkkEIq46Ybgx8LuUeNgkl8YiW64xxmRyn7Pm1xHkXZQ5W/ZyhUsu4IsEoSB0c7eDyVXqYwY8Vr7ent7ulEhYMtMPiSy7NUBrVixWnnC3vK277GBNCaNWM2qmQbWjYYtY3LihUSSM6Shw8HNUJhsyOTCJALcewJBPVPL8EJJEj/79Mcaqe9OZ3vgtz5ppz+xzcZSpf2ejXw9ZhOURvdiK0fTpufv4/IuF/TRMNU1IiACx4/AzL81j98zdWcREAEROGkIhMIuFNDRZSim25P/cD9TEnzp0qWWJq+yN5/o5wVN3AV9OG22KO101zfiiHkEZgOh3UQcN5g4mGWC3/9823U2Oj5svZUmuaCz1CVE3Ddrlk4yfdALqNDD5iPDcTJjc8HtJyQaKesqJ2yMSYzZoTF7/odvtPOYUVgqjzMJ0e/SFs913vn/sfcmcJZW1bn37pp6oieGZhZEBRFUkhgVlc8haowDUW/IxUgEIvqpqFc/zc9ZcUw0Jn6oSDTqVeNwc038zI3ROCPiBIg4IiIIiMwz3U3X/K3/rnqqdr39nlPnVJ2qc6p5Nr9Ve797r7322s/prn7OYr17L7QIa813JFpIuDYCRqDXEFj4b7pe24n9MQJGwAi0jAC/+maFl/94jsSGHCRexQkYIVNkefq0jSCdijxP1UGYI5IbZ1ikkfGBdMC9Dkt7xUUofXGzH2kPMT2oJ7nLrDPLUEsCXnUXe6VMnb4RJ2fERSmz/k4RXq4kh6wS8cX9ofB+cqg/DUeke4/Ic37gu1+c9gqd/lh/aGJ1eBkXoOwMIhz60R1P4XtOu+hLqzlsuUGJwPLUhJgU7wymoYhcT4Q8ZGQgXfmQ56YH/vqutCOwmZxcHeQ9Xpbsj2vCY5FtQ5z4ES8sxkuLw+E+R+DNLbP4019HlnVTI0i6GAEjYAR6CYHqb7Re8s2+GAEjYAQ6jkA1yqnnXGciKOJMPZvfPBov2xFRhuiRqjEeic28A7hp06Z08MEH5zSOjjvb1GBj0rs58pBX3X5b2nrGi4Ipj0UayUi6NXKih9KOoLSR9hG/+Ufj4hSIN+/8kQHSbtkWpHvjwJr0vee/Ke0dl7mM9m1PwztHg6ivi5cKIcxTxJ7rv+MelnTb2l1fmNSa7UbeNc+1ETACRqBbCJhAdwt5r2sEjMCyI1CSZdrlM84owkw/r9fpmZrQNHnOvCiI7LvfQVkG10RsN/ozuZ4OlHb8F2txtnIj0BTBzXXcVDjStzFdHJefbP+z30/r99wYV3wPB32Oi1NiH4Ph72BsCSLNPu/ixL02CmuMr96U9hhbkx62c3266vf+PN33+mvTYJzEsWNwXeRCD6RhzquOyDxrAAtR77KU/qqfPhcjYASMwEpAoOO/51fCpu2jETAC9yQESC+AmPHrTjK7/5JEizhzlnM+0xniHKSuL45xG4nLQuLu7XTgvQ5O+x14UJiKKDQR6zCd0yHiRcJsi9yNNovIZONpsfZMgZFOy0zf3MZw/+bIie5PGyKV45ZX/0Xa+T9fFid1RJJHENuJSPMYD6I7NDmW4h3DjMjGkeY+V4kt++wb25HujNsQt8cReQ8a3DcNPOs96YBb7kybt92RI87rto/FFeLx5SJwGiJFpMkLlI32P/sSpYn13E/YT0bACHQbAf41cTECRsAI7LYIlAS53CT9VRFxVj/0cpSI88hI2hr5zfvss29O2yjt1LWr0dZanSDmVWJapzfbB4kuifTsSLXFjYCrg9APB+HfFIkbV+y7OZ2/31DaEmHngbuH03BchjISLx2umozrVPgC0AI/rfraHwQc4j0aRD1Fusb22+5OFz3xxemAm++KLxqB2WDgOzabHBIHebgYASNgBHYbBEygd5uP0hsxAkagDgGRYdWkWyg1o+yrtknXGB4ezjnO+++/f5yssS7BB/vjSDheDiTyPMk5ym0SwzLaWrble12fxubWs7++dyG3fbdGjnPkHo8M5jOc9xhYn/b/3BvT9W84JU1sXJv2iVSOuyMtBN9H4ySP4eDAjUrVtvTG4oIWXnhcF7nhO4YG0kDkWB+xeu+UTvibdN8bhuPc6B1x8+HONB5ujoZ9zovW3hrZlG3XRsAIGIFeR2D2N3Cve2r/jIARMALtIlDJTIAkq4gwq0/PjE9kvbh45JBD0rp1QZwjUstZzwMRtR0dnb4pJGf2Tllrl0Qzq0oiq89Tlqd/Nglp183b2b8mcp3vCIYfOc+rNgWB3ZG2xS2Iv3nGMemi7deH5/FWX1yTGDd9p7XxpWAj6SltlpG4zZDSHxe1RIg+CHk8xM2Ht4/cnT5//AvSkaPhQ5D4oRgmVSRu/3YxAkbACOw2CJhA7zYfpTdiBIxAHQIixrNR5/E5Eeh8+cnY1GUod8c5ygNr1sYlKAfkPGdynON1u0h9jlv94gQObFCmbNKK/OhpgchKGCmLSPpUH792d5V84kf0cw04ElnGMxKnOM+0sQFX5TKUOeQ51ufrAdI/EfoT6+M4ueE01B+3rXDIXZwasudISkdc+OH0yz++XxqMnOSxNYMROV6dbl8dF7ZMf7dghwi22ZtKuQfG1o0P52P0hoNIr+4fijznuHlxYHUaHOlLT4zrW4af+qZ03x2R4jGyI90Yp3SsHuVNRY7jg1Czo6ljACe5YKYGj2YXyGQj/mEEjIAR6CICJtBdBN9LGwEjsLQIZEI5nevMSlPEN4hukD3aEOKx0UjpmCatBx54SNqyZa98RB0RZwppClOUMj/mH3OI62x3Sy3mLmY+izSaX+2ve74tzmre9+/+n3RzYDDGF4e4YCUFBuiW0mgzVZt1eqvvCgp++/b09eOeG9eGp7RnvEzYH0Hv4NapL249HOXLSLRJ7wDbqc9l9lSUOpvuMwJGwAj0EgIm0L30adgXI2AEOowApGxuxFlkLZhjRGm56mNV2nvr/mn/gw+J6G0k666KKGlcPrIqTo8gMMqFJZNxu1+1tEIkq3Oqz81sNCKz5Rz2Ui0aV61xPU8OrUl3jvenQ757drqw/9Y0smY8beyLvO7pYDP/KMz8w5Cjw7LQmLjPaky17hqMK83jC8gxcbnKbx5xerr3tsA54CSVgyvNd8Y4NyjysmN/pMe4GAEjYARWGgIzvydXmuP21wgYASPQCgIimeQuR9A1y0hEQ/vjpcADDjo4yPO+qZ/j3YLH9QV5JirdF1HaKaI9HbUOoi075Zoipeqr02EMPYl0qev0S70pH2ZJcnW98rm0VfaX69HuG4985YGxdNXGVel+F/9T+vn4bWn7ZFyCEpFo5ilNBd3xGoJOPwXa20iww5F5G+L67weNr0u3P+FV6fCdgWuswZF/a+OK8dHQGSNFJB8BQgS87hbGvJR/GAEjYAR6DgET6J77SOyQETACHUNgOn1jIm7jg2CKIG6J4+g27xmpGsFNp8jm9K/C2gtLCM1Oh2cX6NjUGq1NbkSEZWPDu/rTns8dzEK73TIYXyJWRUR9zWiQ+niz7xHnfCxt3rAxcqKn3vJbuzpe/pvl7POaxy/JjHIY6I8cjTtXT79EuP3udPnD/+9075GhfLzdRJxDna8hDx1yvRuVXew2UnS/ETACRmCZEWj8m2uZHfFyRsAIGIGlQEDkGWK6ZcuWdMABB8WRdOsjFBtpBnHpySTpGkEYoXJzo6CQU35FSpbCu3qbVRIt8kw9eGmkPly6KgvtVormozsZ+4ZEbx+Ml/om1qUL91yVhv/phTMkmDOvyyISW9rQeLVPupPxRWQowtN7xPl4kOi1gX3c+p2ue9TL04E7p672Xhep12vimkLOqnYxAkbACKw0BPyba6V9YvbXCBiBlhEIShypzgNpcO3GOFnjXnEYxdo0knOciUhPnQJBIgKETznAGIfAMl4mKYgcVknjXGeYR2LDVLRbc0odyHoZ4SXYyyUj1YtGpnyYDgUTGZ+WWGHGHC3JTGelUefvRHxp4CKU4cHhtCEOab7miEPTxn94UZDcsD40mdZM9qfVpLJM6si+KaOkdLA7pM6ulh6ItwN5YXAsTvpYF+1tMbD38No0tPPW9IMnvTTtFad1rAryfGccDr0xzpCOM0DiqL1I44gzqSej5hmi72IEjIAR6FUETKB79ZOxX0bACCwagYH+/nTggQfnyDPH0E0R2lkCuugFKgZWEc2eTmmoDM08QtRLss4At1yXN13LRpWkQqrHjoij4Y6IHOIQ2tLVAtU56q+rNZf6F48/JN39vGem/i2b0sSasXRXXPmdc5SLie3YLqbNkO2NqzemR1w7nm598AvSXmk0DUZqzfbhkUiDji8543EZS7zciNwd2STBo6e/yCzd51X66LYRMAJGoB0Epg7lbGeGdY2AETACKwSBVRyXRvpyMNa+yLvlRUEuSQm+WFvK1AkUWiOMikMQl2UOzwsnfeWaak/5POX0na+ajQqv4tSQ6SJdPbdbr5kcSjef9kdp8KZr0urPfC2tC7LbNxl5F7x5uYhS+rUzTuAY2rQ2bYirxH/91FemtV97Z7zUGF8GItpMzjQRa24sJMWEI+4IursYASNgBHoRAf3m70Xf7JMRMAJGYJEIcLlISHDPqdMlIi2hyJ8oyV1JnulHlEZRjpUOlf1c/DFrrwFDj8lQ61LQ7Iu1kNn5FfIeF7pETkMWSLOkXF9+0Sf/S3sab1QPxyUn60aG012v+fN02+/dJ20YjDSP/qkXC+ezo/Ua2Vb/UOSpjEXEmfSRe90Y13yfemY6gItY4liUoeHRwHtV5GbHupDosYV/CdF6ro2AETACS4WACfRSIWu7RsAIrHgERAznI5BLsVGIsKTR+o36W/Wn3N+aeKFyZ7xXuMfYULrXJ9+avt13Z9q5867sA/ZmU2DmEv3atTg/elr48iIZ15eX+N8CXIt+1C9uS5ed+o403Deadm6JIwTjBUZSWXixM1KkXYyAETACPYuAf0X17Edjx4yAEVgsAjnSO03gZm11OLIZkeFZIjv/r1RSSnJayaxD+aVCccuie5fm7Dpzhxr1z9WaeipJczk+1j8aWckD6Y54ifC2HeNpv3M+nH6y/rY0ODgVhdbNjOWcdtvj8ZLgqsCrf2IwLkgfSncMb0v3/sl1aegl/5gOjGu/164eTGvHJiIPegoj+druOtY3AkbACCw1AvP/tl9qD2zfCBgBI7BkCARZjsjqXHI6G0GtS4EoyagI3FQfvy7nCheu5EJ6RZSpa79pQdLn6vJMmkd/DCHBo6eEVJFdSD42pkrpT9Vf+Yem2qX+tIk5laLaVVtx/EXoTaTVEfneuXosrY7j5e5/wb+mH/Vdl9YHhkMDQ6kfIINoc2pJs/VQQ2LHcwWcIjId7wnGUuNBovvitI+4CfKiX6dLjn1+Wh8vEw7HdYVj5HDsGEtrI917JHTLFyznbMYPRsAIGIEuITD1W79Li3tZI2AEjEA3ENiFPC7ACRHVXO/ythv0uHOlGVnt1CryOJPfIPXD8aLfjp13p2O/8OH0s4ntaeeq0TizOdjsxNr8RaAT6wrD1cMD6Zjhdem2d3w4bQ7SPDYStyLuMRSnccSZ0bPvTHZiSdswAkbACHQEARPojsBoI0bACPQiAhFrzpHSZr41I6dltLZsz7E3hzw3/5XajLiXfohYzlmnQw/lOqXJHFwmahwyxlnWXHASKRWX7Lsh3fuiD8eRdhNpMMb2CEIb8edy6pxoNPYVUa/W5aRyjztGByN9ZCLt939+kn575F+mwf5Ixo4zqOMelrQzTk+pnpFd2nHbCBgBI9ANBJr/tu+GR17TCBgBI9BBBErCqHYj8yWpq9PR/Ll6U2et0TdFkPm1uuuvVs0Ntkm+xS4S3HROmdGf07u4h7l+z9qq66cPIj0UW7lpj7608V3PT5Pr+tLO9eNpYmw4T27kY7N+JlbXG4wLXMYG16TB0ZF0v037pjXv+3S6O9I5NkauR/9oRKPBy8UIGAEj0EMI7PpbvoecsytGwAgYgcUioMjxYu1M5TeT+wvVhTRLsFy2eW69yD/Vrc7sNKnM0eLpxZVzzBpjA3FjYZzVfNVxh6cNX3l7WrtubRronz+y3+o+0GPtSH0O0rwpcqJH09ZPXpQO/scvpu2T21NaOxBR8erXi3asW9cIGAEj0HkETKA7j6ktGgEj0IMIiKBSL7S0TFqnXypcyDqt+NeyH2040ChNYnAsLjUJzNas3iNdtmYwXfaow9PqLZvnWMafUnTSCPVkvDQomTOpeIjXCtNw3KCyevKutKNvj9Q/PpLS//lB6v/Ut9NwGsnrF+puGgEjYAS6joBvIuz6R2AHjIARWC4EiHRSOB2irlTJK6dmqMyesDGVglDV5XkyR6djBnnR02fViVjO2FFjui7pfEmMsadn1eXUcv1yvGyX+s3a2CKaUp2bn+NKwIGA4fo142njjkDuHc9NQxfclAZf8tY0Gid33B0XnvSPDeS5gxE9nro+sH/m/Ghhjq2JfDoJnnC9zWz8BrgGAgjO5Vg9PpbuHhhMa27ckQ5+/9fS0PiaOP2j/vNqtiePGQEjYASWEoHZ32BLuYptGwEjYARWAAKQvFLkciaSemixlp0W1XdRm29NjavexUAHOqa+FKQgsSltjLTnzeMDQZon0mWP3D+teuUJ0T+QBneMpDVxs2CKUzruXB0vIOarzOsXFyalz+qrm7FtKOx+8Mtp5yVX1Q27zwgYASPQNQRMoLsGvRc2AkZgOREQUSvJ23zra858eo3GW5kvnUZ+NepnzWZjjXxqt58bATkNY1scjHF933BaF0Hm/m3D6VfPemj6/thtaXL9mjirGQI9FtewTMZJHa1Hi6v+V58H44rv4dHt+Xzodv22vhEwAkZgKREwgV5KdG3bCBiBriMAKasSs9KpMhWi7C/nlG105s7h1+i0kPssiXVJz6gK8ynN/NJYdd2pmY1/Sj9HjiMto52iudU50GFe8Ntv+6q0oW8ojcaxHKNxPvPojoF02IUfTDc85vC0c2Is3RXXca8dmUx3DEwd3Kw9YK9quxyrrqdn9jAwHjcWTsRLhHGRi4sRMAJGoJcQMIHupU/DvhgBI9ATCFQJ31zCPL+L1fnNZrRru5mtToxVfedEjrvjbZmdIWMRieZlQ0j1mjireaSvPx34zhekO+Jrwp5ja+JywfG0x6qpq7/lS9Ve9bmRHv2cAX1XEPZJ50ALJtdGwAj0CAIm0D3yQdgNI2AEeg+BdsgtxFDS7k7KdRoRzHZttqIvf7Wm6nIu70UOxkt+8S5hRISnRsbiGLs4uTndEfUNcdnKIRd+JH1t9fY0sHooDXCLYA0W6ittq127bthYG4R8Q5wDXbmLXdNcGwEjYAS6hoAJdNeg98JGwAj0IgJ1ZK7qp8igdFVLr/qs/mY1JHoh85rZbGes0dqkNA8GcSaJYjIIMy8U7hGnzK2OE0rId74zCPPlfSPpyf/5j3GD4EC6K14kXGiRD6oj9pyGh+J0k7z6Qq16nhEwAkag8wiYQHceU1s0AkagRxEgmopAVhX17euLo9lqIqZsQUSONge95cPegjhOBHGU5LHCHs9NS6wVhjMlhJSyBj4gCy3yX/PL56l9YntKNEZdlsnYk0S61JzhPDIY0fVQHg+viUQPRzrH9r6xINYTccRddMSRfZdtCYXPvjFdPDgadsbjxcKJ1BdgD4Td8dBZOwpu4MjeZ6P1+BEqWTjmTm3qcXxkQR5cjIARMAI9hAC/UV2MgBEwArs9AiLMbFQkshOblq0qIe2E7WY2tJ7qRrrzjTeaN1+//vHgSwCR5xRy1YGr04P+5W1p1d5b0qadfUGcV6V+FKJwmod8UT01MvuT/nIM7oxk9j6r5pYRMAJGoOsI6Hdg1x2xA0bACBiBpUCgjDaXJJq1SrLW6bVFBudbY77xOr80R3WdTrUP3fn0qzrN9Enf4IITdIgor9kZker+NenOe++f1r7y2em3k8NpYDCeI6WjPyL024a47rwx5tW1eOYFRl0rXt2Pn42AETAC3UTABLqb6HttI2AElhwBiNiu5Kw/+rhlkF+Bpczvjkh4nV3NFmmXLv3N9DWvlbq6F80p11JfWcunsq9sl3ZLX+v66RuJlBMoMUfcTcRVgqNDU2kWo2Nx0cqT7pu2XnhWHD/Xl/aI06EH47bCNaMTu3wOrF+uVX0enIg865BVTuEAGhcjYAR6CAET6B76MOyKETACS4tASQbbWWmh89pZo5muSGYzP5qNYVs2tM58+tJrVJOaEfw4CjR6Iuc8j0XeM2R6SyRJX712PF3zjAelieHRNLymPw1FLnW1zOcDt6HnG9F3nVo15WcjYASMwLIiYAK9rHB7MSNgBLqFwHxkrZFfC50ne/NFhqXXqbrqL891fYtdb/1I5DgHsSW3eTLyLFbFC4N7jE6mLXGZyq2rIzodZ0SP/PVT0+1H7ps2TK5N24JcyxfV+FD1rfQL2+RRT6dRl0NuGwEjYAS6ioAJdFfh9+JGwAgsNQIlgZ0lblNR06noaekBvxJLmR3TXOp+Ts2IGikLT5I5/RU9xmSv1Ct9LfvbadfbKPcbJ2vklAhOH5lKZZlKZ6lfZVUcnUEecmjO5CTzvD1ymmf32hd5zn1xOsfUxSd9kyNxSnR/EOqNafNHXp++1HdrGoibWMYjjWMo8CUnemz67ULdMig8qFOQb4Qcaz4N1nExAkbACPQSAibQvfRp2BcjYAQ6jsAcYtYh65BUSZ3Jcs1qu05ffZk86mG6ruurqOzyWK65y2B0LMRmnZ1GfQOT/Wl9nBV95+rJdPma4fTA77wv/WxtvFQ4NJiJOC8gcp40X1bGV8UJHi5GwAgYgRWGgAn0CvvA7K4RMALtIdAOWSRVoJFo1V3sETGdFubSzrUmLKDWGqoXYKLhlKWwWV2Mc6L7I6WDQPee4wPpjjgz+iHfen/6/sTNaTKi1JODAzHWF68XRjTf8eUqfH42AkZgBSBgAr0CPiS7aASMwAIRWOT/+68jm/UpEo39q9rgudpXztaY6nKsWXs+u5qryHk7+2jXF25M2Rl5HmvGItVjYDKtnRhKV0XI+cgLP5gu235HGtk5Gq8dTqbbI0IN2S4vs5Gfro2AETACvYyACXQvfzr2zQgYga4g0CoZ7Ypz8yzaNtmtsbdQG8JtXbxdSHSZpOnBOEZjKI6im1w1mIZGhtLWX/5Tumj1jjQxMZH2nhiMOnI9GhTZazDsbiNgBIxA1xAwge4a9F7YCBiBXkNAx6bV1aWvInbUdbr0LUcp/ej0etheaMm3DkYeC9emb4uLVOIW73wj4fY1A+n6u+9KjzjnrLR98+o0ORHXgS90Ec8zAkbACHQRARPoLoLvpY2AEegOAqvixIhZmSJ6kL260yboQ8rCo4RTKupOqhC5LefN126HtDbSnernV/tc0Ykbk3Ees6Qk/1XflOKBznjsFin1hYswK0/pyHNiea7hJo2Ds6HH++Ks6MnRtG7V2nT5uv609d/entKGNWlyPE7sCAw59m71aKS3xGczGmkfnNThYgSMgBHoVQT4DetiBIyAEbhHIcDLbXXSiJQ2A4c5C5nXzOZixkR8F2ODudqT9qfnOrutrjkZRJrLV9ZEiPqydcPp8j88MK3bvHfOgcbGxGB/Pld6zWgcdRf/uRgBI2AEehUBE+he/WTslxEwAsuCQCOC2IwwVh0rbahd1Wn0LP121quz1SqJLSPHZRub8kX2eS51yrZ0VLey/mAcXbdtiOPtUto8uCENvOt5Kf3tc1PfwEBaE5HnuyPOPREXpxA9H+738XbC1rURMAK9h4AJdO99JvbICBiBTiEQWQC6NGRuSkP9AlA3SUycaXNhisgldZUsVp/rrU/1lnZoNyp1Nsu55Tz1l33tthv5UudHne1G80vd0ciTGRybTENxY+F22nGb4Q3HHJzO6789KHNgPDqabzMcHpzKLS/num0EjIAR6CUETKB76dOwL0bACHQWgeCndcRO+cvVutXFS5u0y+dWbdTr8St5SqZuB9Rz/T6ku+uXhLnWG/kn3xuNY4UruqdubCxvM5x7Lffc1Zo99aW1Y5zQMZlGIyc6LifM0ej7f/3/Tdc891Fp3dDatCOu/B4aGYuI9JSdZr41W8ljRsAIGIGlRMAEeinRtW0jYAR2awRaJXetENVGQGlu3Xij6LDmqNZcnhdaZEt1q3akT83pHLlELvRgHGO3Pq72HgxePrpmTdrxwiem3z75iEjniItWhlal8YnRDn4xadVb6xkBI2AEWkNAv85a07aWETACRmCFIlAlmyJ2ddvRmOqqTqP+qp6eWbsqGlMUeaqeG+WdjfzOarfSKk/LaEUfnSo+sqHTO+b62TfnRA5O9ZA+NaUOI67wHot3A8fjFsKJiEPviNzniYi4j0S0eX2cEX3XW09OP733nmErzoyOXOihnRMRqQ5bvPHpYgSMgBHoIQRMoHvow7ArRsAILD0CVWJXfV4KD7QGdTtlPv35xttZq5u6G4dTjk7vEfXe//Sy9IuxO9LwyHjauTal1XEMnvlzNz8dr20EjEAdAibQdai4zwgYgd0GAeU5R0h05uzmRpuTbl3daM58/Qslue3MQ7eUZj61Y7eZnU6O3RUpG0Nxe+H2OMZu1erV6ahvvy+tXrshjQzEZxbpHqt8JnQn4bYtI2AEOoCACXQHQLQJI2AEehsBkUbVpbdKraBPJLQcV1tjdTak00otO3W6ZRpF2S7TJ5RSMVXP/wKj1pPfc+3OeqHx2Z4pPEp8yrFGba3XaJz+urVuWxP3qsSt3iORxfLbofgK879elUZuiEh0Pzkczax5zAgYASOw/AiYQC8/5l7RCBgBI1CLQEksy3atcg92LtRnbh1cN5rS9jgjehNJ0qv60xX7rkp7f/GdaY/+9fn/HPTgdu2SETAC92AETKDvwR++t24Edn8EZiO0CyV3i8Go3TXRl2jddm1oXqfqqj+dslvaGe+LROdV43Fpy2S6e2BiKuc5Llb53X03pYm3nZgm4qpvFyNgBIxALyFgAt1Ln4Z9MQJGoOMIlKdD0ObEiEalqls+N5qzlP1LQZ5FiDttu117pR/9wY/jWOgcaR5ZP5j2Hx6I4+z6050TY+nXjz4k9R2011LCbNtGwAgYgbYR8F2pbUPmCUbACKwkBLh+ek5p8EJaJnRV3ZjYLjFkrfbmcHTdrnNKG2W7zGEu+7OR6R9z9lz5vsCXgroyZ04o8IxqI/3SRrz6N8V+pzu5e6U8OWPGRkSVc0EhXg6cKvGSYOpP4/Gv0SAUeng03TzISPT2DaR1/YNpdMO6aV1XRsAIGIHeQMAEujc+B3thBIzAMiLQiHhWXZAedUlcq3o8S7dubL6+urnlerH8TKnTnRnsUGOxa9SS54pvs/uLK9OL/ZVqqyMX+u6dO4OMB7F2MQJGwAj0EAIm0D30YdgVI2AEeg+BVshkKzqNdraYuaXN0s4sOS01Vl57fGws9fURtW7AsFfeluyxETACuwkCJtC7yQfpbRgBI9A6AiKYJelsNFu6jcZbsdH63NnXUrA739qt2JUN+Vmmaqgv22mDo86Zx+SaAPFM2kYx3DcTaq5MUGpHdmT2x5rxqRcK23BtdrJbRsAIGIElRMAEegnBtWkjYAR6F4FdSGC4WtfXbAft6pe2FjO3tNOL7ZI8N/Jvdv9Bjyt8WnM41q6aT60x10bACBiBbiJgAt1N9L22ETACXUFglrwtbPluz2/H68X62s5atboRdZ6JIDcgyrXzojNOtEv9IWXUvJGu+42AETACy4mACfRyou21jIAR6AoCkMiNT3FUAABAAElEQVRqKkPVkeUimq2sIx3VcRZG4e5smkfRmZvaY980ZdXLfGVEuBEZLXVKu7M+lL1VUts3x8M5/sapJ7IxmcanjASRVl9Ymmu4fIrUjrjhu6WTQMppbhsBI2AElhoBE+ilRtj2jYAR6BkEZknbrEt1fbOju7Z6Rb/OD/og0ePTnFRkWTW7kc6uO1v6njqfl35Vr2AEjIAR6DwCTb76d34xWzQCRsAIdAuBTpC3dm0slX4zu4yRKYGUUeV89PJ0CkWz+Z34fLAv6YQ92zACRsAI9BoCjkD32idif4yAEegoAlWyyDNR2mp/s0Wb6cpes/mNxuRHM/uaKx3ugVGqBmOz/bN7msk5LsbVN82hZ+ZV7fNc2tf4Qmv5V9ot++gvn8u1hc9C1/Y8I2AEjMBSIWACvVTI2q4RMAI9i0BJ2HrWyXkcYw8l2Sz3pJSNsq+a1tHMfDmvmV51bHaeaHpVYy5Z1mi5D/VRz9ore902AkbACHQfARPo7n8G9sAIGAEjsAsCJXkk6txOmbm4bzrsXKZytGOn07rlnjpt2/aMgBEwAsuJgP6v3nKu6bWMgBEwAsuFwE2x0FXLtZjXWTIEDgnL+yyZdRs2AkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAI9CwCnwnPnt6id58LvSe1qLu7qU3Ghu67u23K+zECRsAIGAEjYASMgBFoD4EHhfovQlZNT3tK1OeF3B5yfcg/hWwIUXloNH6ohwY1+v8QcmXI9pCrQ/41hLnLUTbHIh8Nwf+7Qn4V8qqQxZaFEuhTYmEwXenljNjAJ4tNgMdPQ/qKvrdF+2Mhx4Vsmxb+DKCrZ+p7hZwTsjOk7P+PeKY8JmQihDE+w0tDTg2pFv7cXhHCn+G68sfReW4INm4K+VbI8SGvDdG6+DBePP882hR93s+K9pUh+jsSzVwG4ueNIU8NeUyI/JVd6mNDXIyAETACRsAIGIEeRWDfBfp1Vsx7XTH3L6JNhHldyJaQL4X8Y0hZLouHh5QdRXt1tC8I+WrI0SH9IetD/izkjJC6AhHpZPmfYex/h+A/5O7+Iay/2CJC1a6dU2LCee1O6kH9M8KnTxZ+gcctIfyZUXlbND6mh+n60KjRrX7O50TfaSF15THRec30AMT1ySFjIUdM96l6dDQgqpDgP1TndM1nfmcIa2wK4c8C+nwpLMsp8XBe2THdxuf7hqwJ4QvlY0LKAnG+IWQg5DEh14R0oiz073In1rYNI2AEahDgl4eLETACuycCH4ttnR/ywhAisK2WPwlFonIqn47Gf4XsCLktBLLxyJCynBMPRKrryl9G50EhTw/5WQiRPSKQRKDPCFGBnJwectm00H9myG9DID1EuYliUvYLwZ+9eJgufxD1TSGD6ihqiBT7wH+igr8MYX2Vo6Lx1ZBbQyBARCMpRMi/FwJZui7k/SFDIXWFLwrvDrk6BBv/GLI2pJVyZSj9dchPQsDmIyGQJr6sECn9WgjkX+Wz0SCafkfIuSH4rwIm/xECZheEvC3kvBAVvjxor0Rx/1wDHarfFXbeHDLQIXt1Zviz8sUQPq8HVRROjud/D2Gctgqk+x9C3hry4RCw488Cf9afF9JO2RnKfCF7TmUSz58KgdgvtvB39oUh/B3+WIiLETACPYQABJp/GEr5QuEf7XKsbFuvHhvjYlz4e9ILfw6ODz/eEfLEkKtCIJBPCGn2xXl9jN87BGLVqPxfMfDzyuAl8fzgSp8eHx+NL4dADOcrTw+Fh4U8YFoRAnhMyJ4h+P/ZEKJ/kMdzQkryd1I8/6+Q0ZBq+X50vD3k1JD7VQZJL4Gg/lfIASH3Dfl6CAWy//KQvUP4X+9/FPKikLryzug8PAR/sXFgyBtDWi3/LRT5fLDxtBDIM0SetfnMXhqiwhj72BpyUcinQlTOigZY7xcCgSxJJJ8v5BksmfuskA+EHBXSqfK5MAR5P6VTBmvsgAd/vsHm18X4umj/WQh4ICeGDIVQiFQfHFJ+caJ/oeXjMZG19CWJiDaf2ydCFlrY1xNC+Hz4O/vEkHeEsFeVL0SD3zF1wpiK9WYxMi6zWJR/bozL4nDR3zXXRsAI7MYI7B17e2nIRSFXh7w4pK5A+iZDIKl1hX/cieIeXhl8Xjx/o9KnR8jp3+ohaggmv8QhWSVRZ93HhTQrrC2i/t+j/Z1p5f6orw956PRztYLkQEaJYkOwIV1/EkKBRP4ot+b/8bJQ+f8KNXyGLK8KgbTeJ0QFwv0bPVTqU+L5vKLvymg/u3j+t2ifXTy/JNqfL57L5uZ4wI9NIeDA/iCLKm+LhtYCs29rYLr+YNRvqvS1+nhGKH6yUBYeT44+/pwRlWf9j4WU5dB4QHeg7Iz2OSE7QvjzIXlrtCmPCZkIoX84hC83Lwspy0nxcFMIdlkb3WeEUB4ZwpqN/myjo3JKNM7TQ1Frf+q6LBp/Mf3A34EfayDqx4TIX+2Fmi8xdYW/k2DG31H+rvJ31sUIGIEeRaCvR/2yW0bACHQWgVvC3E9CLg7ZEnLvkLrCP/CUDVPVnJ8Pj6dPh/xZyK/mjEzpa25lKOfE7l904sPmkGeGQHLK8tvyIdqvCLkk5I4Q7EMSRSz+PdpEqg8LeUIIOueH1JW7o5NI3h+E7BXyv0M+G7JnCFHJy0PqCl8UvhACOYfwY0PrR3Om7BOtdSE/DMFPhIg2/a2WGwpF/K0+7zE9DknmCwk+49OVIRT8Yj3IY4lj2T4kxh4WIh+pIe5Eq6vluOjYNi0/rw7O8/zFGIcMPn8evbphyOPmQt5QKF073b8x6veGPK4Yo3lyCJ/tWAgk+3Mh9FH4O0Ap/yxO9Sz85ydi6nOmp/9l1ESlyyJ/y/1sLxWKNn8n+bt5cchPQuRvNF2MgBHoNQT6wiH9glT9pcJJ2uqv1tarx8a4GBf+rvTCnwP+Kt8v5K0hvwk5M+SnIYeFQEzrCv+4Q8wOrwz+Xjz/n5C/Cvl6ZYzHI0N+XNNPF/pPDGkUeUNHZVKNqI8LeVXIn4dALCAhd4QQ7aXsDIEsQQD/MuSfQ1opkM53hOAPpAWCeZ+QunJ2dP4yBBwhbUSxtX40Z8rN0bo75KgQkSXIvkhvNDtWiHj+acjjQ1jj0BAKft0UAnk8KETlYDWiZq/fCpGP1Pj4wpBq+XZ0MIawr3bL62PC60L4YtHpAjnmz8YDQ54+bZw9Py7kpBC+8CB/FvLkkL1DLg1h//8tpFPlE2Hoj0KODXl4yKdDFlr4O8nfTf6O8uWAv7NvDeHPXlm+FA/Vf4/1zJiK9WZxMi6zWOjPCrVxWRwu+rvm2ggYgd0MgY/Gfm4OeV/IH7SxN/7xhiiqHB0NoqH/XR01NRHpRukTa2LsopCvhGCrP4S+V4dcGaICeb6vHqKG+Fwbsl/IUMgbQ8ZDII4qj4zG5SF3hRwa0qi8IQb+MAQ7rA2xuy0Ecrgh5LqQl4UQEef5YSGU80NYF3J6/xBI2HkhKqXPZ0bn/w7ZOj14YNR/PN2uVqdER2nnyngu9/XJeD4jROW0aHxt+uFFUV8cAqHnS8AHQko//iWeIXLrQvD56pDzQijs7aqQvwwZnBZw4QvQQsoZMQlfVUo/6PtqyC0hHwspy6HxgO5A2Rntc0LYa115THReUxl4cTzzZ4vympBLQvjzUsoV8fySEMqfhfAl7NQQ8OsLeVTIh0LKcko8nFd2TLer+6P7myFXhvxnSFkeEw9Vf8vx+dr8neXv7s0h/F12MQJGoIcQ4JeHixEwArsnAv8Y2zogBPLwwza2CJl4dgikkfKKkH1CPhKi6MXPo60CAdseAtmsKzuj87Ehvwj5zxAiwBBR5v15SKPy5RggQvKrEEgfdoggluU78TARAom6MqRRgfj8zxDIyLUhTwh5Sgj7gXzz/LSQ60MuC8FfyitD/iIEnX8KgZw2Kq+KgV+HfD+EPUJ4jwjpdPlEGASP34WAKeuVBVJJZJq9/HPIZ0KGQyjs44khJ4aAAzrvDFkdshTl9WF0zzYNvz/09eeMutmfXYjlvUL47E4O4csEeyqFvweMUf415L+H/FUI+78h5G0h/x6y0PLxmHhICJ9LtfD3r9wL7f9WVWrwzL5fEoIN9uBiBIyAETACRsAI9DgCnw7/9L/G53P130LhyfMpLeH4N8L2aUtof6WbhiBD8lyMgBEwAkbACBgBI2AEjECOYt8eOGwwFjMI3D9aDwpZFfLQEKLurX4ZClUXI2AEjIARMAJGwAgYgd0VAaKq5LOesrtucIH7IjWGVJIdIVeGkBsMmXYxAkbACBgBI2AEjIARMAJGwAgYASNgBIyAETACRsAIGAEjYASMgBEwAkbACBgBI2AEjIARMAJGwAgYASOwuyDgvLjd5ZP0PoyAEdgFgU2bNk0ecACngM0tk5OTadWqVVlo33DDDYmaQj0+Pj53wm7yxJ61z5W0pZ07d6bR0VH/e7WSPjT7agR2cwQGdvP9eXtGwAjcgxGAPH/605zIN0WMBUVfX18aHh5Oq1evThMTE1ne8IY3pCDcWWXHjh3p7rvvzmQTwok+eioQUZWSkJY6jDOv20U+4UuVQDMmH6VX9bvU6dZezj//fAh0t5b3ukbACBiBXRDo/m/3XVxyhxEwAkagcwhAcEuSi2WeBwcHMykWGX7zm9+c1qxZkxdeu3ZtWr9+/cy8klxqfp1dyGgp2ViXf8gf9kBknVoi8tzMxVZ0ms0vx6o4lmO0+SxKqY772QgYASPQKwiYQPfKJ2E/jIARWDYEIL8izv393Cw+FS0+9dRT0+23357HINAbNmxIjEO2V3oRkS7rck+N+kud5W6DPX7ps1ru9b2eETACRqARAibQjZBxvxEwArstAiJk1ERlqQcGBjJhfsc73pFJNNHSaiR6JQKiva5E3/EZ/6v/B2Gl7sV+GwEjsPsgYAK9+3yW3okRMALzIKAUAqVfqIakMcYzhPoVr3hFuvPOO3PeLdFnEeyynmepnhleLPlkz5LFboqIsmzps8Bm2eZZnwvRZ/6PwNjYGN0uRsAIGIGeQcAEumc+CjtiBIzAUiMAIWtWIMuQt3322Sf97d/+bSZuED5yoyFxtCHYiyWlzXzotTGR2U7sWbbYoz4LMIVYQ6LBFqFAnK+//nqT54yGfxgBI9BrCDT/16TXvLU/RsAIGIE2EShJ23xTOekBIgdZpn3CCSdkojc0NJS2bt2aCTQ2IH0ujREAH0ljrbk4kkKDgP8tt9wygzHPxrsZih4zAkagGwiYQHcDda9pBIzAsiGgyGYrC0LUIMt6ce1+97tfevWrX52Pu2M+LxZC8ijLTerYB7ISir60VKPWijrTTxsspXvXXXelW2+9NVFT+BJT6q+EfdtHI2AE7jkImEDfcz5r79QI3OMQ4KxnCFq7p2iI+JFaQCT6qKOOSlzmgR3OiobckWrAuEt7CIgUM0s4kq4BvmC6Ur4ktLdraxsBI7C7IeDf/rvbJ+r9GAEjMINARInPgEQ/6EEPaovsEl1WhBkyfe973ztdeeWVmYxD9CDRXLaylAUiqeis/JFPS7lup21XfecZEs1FNSLO+sJCXe5R/USm44vMmzvtm+0ZASNgBBaKgCPQC0XO84yAEVgRCNx8883pi1/8Yk4XIOJZV0TUyjH1QfaIND/3uc9NJ510Uj7aDr2NGzfOkHKRwnL+Qtpl9JV1JQuxtVxzSsKrNZXLzH6IKoMlAo533HFHuvHGG9O2bdukPlNjS7ijix3ZmlFywwgYASPQAwiYQPfAh2AXjIARWDoEIGVEj7///e/n/OaSpGrVOhKoMdXM41zo6667LtshH3rffffNw63Ml53dsa7uH9IM+SefnEKb/xPAy4EjIyNNIcCWCDenn9x2223psMMOazrHg0bACBiB5UbABHq5Efd6RsAILBsCImukXZx77rnpsssuyykCdSR6PqcggRDov/mbv0mPfexjZ+xw5B0F0lclkvPZ3F3G2Tf4UIsAizRv3749E2fO1W70fwDAAX2izujsscce6clPfnL6+te/nn7yk5/MvMS5u+DlfRgBI7DyETCBXvmfoXdgBIxAAwQgZRA3aqKiH/3oR7MmRE1kr8HUXbohyNhg7tFHH51uuOGGTJoh41u2bJlJVdhl4m7eoWhx+QUCbCmkaYAPz3wG6NQV+tEDWyLO73rXu9KrXvWqHLXmJU4XI2AEjECvIeDDTHvtE7E/RsAIdAyBDRs2TD7sYQ/LxAySC5HjxbU3velNOZpMtFNkj0VpNyJ5pVPMIzf3P//zP9Oll146E1m96aabMlGELDaLtpa2OtVu5DvEFH+qpVF/Va/RswhvSZxFhMlzpqBTV8q8Znxbt25dOv/889M111yTjwpkHoI9SPWjHvWo9KMf/cj/XtWB6T4jYAS6gsCuv1W74oYXNQJGwAgsDQIQSyLHkDpIGbnLb3zjGzPBFbFkvJ0CAaQcf/zxiZcURcI3b96c0w3atdfO2o10GxF/7bE6r1F/Va/ZMzhgh/1TgzERZBHgurnM4csF+qTEgN9rXvOafAY0ZJmIM/iJmC/3F5E6n91nBIyAEagi4G/0VUT8bASMwG6DABHoRz7ykZmwcYYzQrQTwsfRaH/3d383J1JMf0lERYwBpOznGZJIgfQR0eaFOZE+cq45pq0bBb/qyHGzveBnde/yvbRX2tA4ZBfSrCKCDC6Q37o5q1evTr/4xS/Sr3/965zvjA52tBZtPitssJcHP/jB6ZJLLvG/VwLZtREwAl1HwBHorn8EdsAIGIGlRAASB7GF1PJCGxFOiBpnOZNnSxtBp0qS1Vfth/BB7BDmvv71r88vykGiOTmCl+AggIwtd6kjz/jQaC/yr7pH+tknJFZtiC0FXfKbiR7zRaQsihijq7mKVIML+Pzrv/5rziHnywwYyS52wBDssHPOOedkkc1yHbeNgBEwAt1EwAS6m+h7bSNgBJYcgZIYQuggfBBDiDRnOX/+85/Pz42I53wOYgeC+N73vnfm2DbmYBuyyBjrSeaz12vj+A02JQHnum2+kNAvklznN+QYHQjw9ddfn57znOekb33rWxmb8nORHjY47o6jAr/zne/MfC6lbt067jMCRsAILDcCJtDLjbjXMwJGYNkREGEm0gmhg0RD/GhztB0RZEjeQogaJBlbEOkXvehFORIt0km+taKrIqDLvvk2F8T3skBu1QdxJuoMyRVx1lg5R21h/S//8i85XeNZz3pWPgeafnBBwIU1+KLxs5/9LH3ve99LV1xxRX5mjM8FfRcjYASMQC8h4N9KvfRp2BcjYASWDAHyblUgfZz4AHEjXWDr1q2Z4HFuNMQQ4laStpIk0mZchTZEkH7kFa94RSZ/EEL6Iw871+izXqtF9qiXo7AOe1bNmrTxmZcDOb2EvdKHsDfGVMtHcCYNg/0/4xnPyF9QwFdncgs7amFNOshXvvKVBEHHtgr+IJqjftdGwAgYgW4jMPubqtueeH0jYASMQIcR4CXChz/84ZnoQcxExERkIX+QO0g0csIJJ+TbBavRVc0tyZ1clU2eGcc2V1W///3vz6kKrMELhURt0dXamt/NWvuS7/JFpJVIPf63UphDTjNfTD71qU8ljg8k55x+CvtWGxzAmEtSiGiXec91a51++ukQcf97VQeO+4yAEegKAo5AdwV2L2oEjMByIQBxQ0qiC5FDOEZNqRsQ3A984AM5txfSWOrjax15ru5Btvbee++czgEpZ23WYb4IZHVeN5/r9gXx5Uxr4SC/VctfPRNthgTzZeXHP/5xvmhmx44dc/YrLDT3u9/9bkKHiDX51BR9cZGOayNgBIxAryJgAt2rn4z9MgJGoGMIiOhhEEIr0ghBJG2AWwXp4xznj3/84zP5t8yD1DEGoa4TOYkORFJz9ttvv/SkJz0pR7axseeee+b5tNGRD+V8tZe6Zm1hQltfMLi1kagzBFpF43pmjxJskH7B9eZclf7a174276vcG7YpYAfeX/va19IPf/jDvKa+cOiLDOMuRsAIGIGVgIAJ9Er4lOyjETACHUVA0WXVREeJQEPgII+ve93rMkmE/NFXEsJWHWHuAx7wgPSIRzwi2+CZaCsEGuKITdakpk++tGq/XT3WkTCX9RBIML6R40yeMm0V/CoL47wsSeHlyYMOOiiflvGQhzwkE2ntg3Uo2KJNdJqI8/e///08b6GYZqP+YQSMgBHoAQSmrtPqAUfsghEwAkagGwhA8EQgeeEPMk3NbYVnnHFGdqkklXSIINJuRHzRgWwee+yxmZRfcMEFOZUDkqkrv4m8YnupI6+lv9ov60KI+cJARLluH/JLEXPmkM9NNP2//uu/cuoF9koiXka22es3vvGNTKDRYR0KXyCq5DwP+IcRMAJGYIUgYAK9Qj4ou2kEjEBnEBDBw5rIH236lYvLy3AQPAj0K1/5ynz9N+P0QSohgyKlqqsEtFzncY97XE4TUZR3n332yS/PSQdiSpu6kwXfyj3KNmkX7AMiS1GtcdUivPh26aWX5psbTzrppEy8mSP/tXftgZsJL7744kycdfqJcMK25qlP87WuayNgBIxAryPgFI5e/4TsnxEwAh1HQMQNw2WbiDFpFeRFQzCJEL/lLW/JhBnyDMEV2VPdinOscfLJJ+cUDqVA8KIhhB2bjDcisa3Yr9PRvuQzpJX1brnllrzHZuuJOBOhps3LfpyW8exnPzv7SZQefGSbGgGjiy66iGu3822MslPnXyt9YNwOzq3YtI4RMAJGoBMImEB3AkXbMAJGYEUhIFJGDREU2YRkQhqJ0EIaKeT5vuY1r8nEET30VWRHz41q7DLvtNNOS7/73e9mItlEoiGeWr/R/Fb6sSFBH98Q7JOmwdF67KuuKCKsMcg1keMTTzwxnXfeeVlI3ZCvfMmgLeywy0uE3DIo0s14WeSb6kbYye9G46VNt42AETAC3ULABLpbyHtdI2AEegIByKPIGhFTkUmitURUIYsHH3xwuvbaa+eQaIggBFKEr9lmRBqxfdZZZ+V0DvR5EY8rv7FBVFeFdVWYO1+RDrXmshbRbtIplJqCnZLYooO+9s0z/rDXM888M73kJS/JXyQUcUYPX6lZi/5f/epX6Re/+EVO18AW/cKz9LvaJ59LHdqN+qt6fjYCRsAIdBMBE+huou+1jYARWHYESgJZXbxMa4DwXXfddZnQQUA/97nPpa9//euZNBKdbUQUqzarz5DUf/iHf8inXkDAsUU6B34hkFP60aNUiafssb7IpnSYz1yixRxHx7F0zYqIMFFj0lUe+chH5n3+8pe/TPe73/2yP9hmnJM0wIdnfCYy/YMf/CAT9NIXrae+staYayNgBIzASkfABHqlf4L23wgYgY4hIHINSVRklpQL+knp+PnPf56juRBKyCQR5HYL80ipeNOb3pRtEiWGZHKyBQXb8oN+iHQzEsqYiiLO+MoeRMI1rpp+hC8G1L/+9a+zP+9617sygYdYI0SYGYcw4xft3/zmN/kEDl60ZC/K6ZZt+cpz6ZvGXRsBI2AEdgcEZn/z7g678R6MgBEwAgUCXOX90Ic+tOhp3hRxhShSSgIIwSUKC6l81KMelY455pg5480t7zoK+YSkc1we0V8IK8T3jjvuyGuwNv6gI79KK0SaKfhDpBkiq75Sj7ZSK1gTYo0e++FovSuvvDLbwA6FtVibOejR1jnOkGgV+hEKNil6plZfHqj50c74i1/8Yl/lXYOhu4yAEegeAo5Adw97r2wEjECPIaCIK25VSSC3FUL6IKGcbayc6IVsATtKn3j729+eI8EQ4PXr1+eXFkWEIfJlhLf0CYLLGC8HEknWnKo/+Ms8agpz9tprr7wHoutE0UWe8QtdbKFH+zvf+U5+OVDP9EnKteijqC7HWm2LVKtudZ71jIARMALLjYAJ9HIj7vWMgBHoWQQUfcVBkTjVvFynSC/jH/rQh3L+L+1qmY9EluMQ21NPPXWG4OLDpk2bcroEkV+IsnygFqnmWDmO24OINyvoEznGFrnNn//859OXv/zlPJcxREWRblI2ePnw29/+dl5f4/gtqfbxXO5L4+3W2mu786xvBIyAEVhOBJzCsZxoey0jYASWFYF2UziaOQfRhNxBEvfYY48cuSV6C/ndvHlzHiNyi0B6GxWRzDqi+L73vS9Hk0XkeRGQ6LKING1SPCj4g15dzRrY1zg51z/60Y8ySdcYtXwVccYWed5aQ75qL+Vz2da4au1NOnpmvGxLX3V1TH699KUvdQqHQHJtBIxATyAwG3roCXfshBEwAkagNxEQGYXkETWGbHLaxTve8Y6c7qD84Gbkeb6dHXnkkYmX87BNZJmaaDBrcv03xLZqXyQTMkxhDkQb8nrNNdekj3/84/mYOY2XPmCL+eRgQ7JJTWmFPJc22mlXCXI5t26MvSAuRsAIGIFeQ8C/mXrtE7E/RsAI9CwCIqGkTkA8IalEn8+IK7/nS6XQpiCKdWSR8cc+9rHplFNOydFtiOOWLVvyi4XcHshaEF75IOIsu4zjAwLBf8QjHpEuv/zydOihh+YLVFiTOdToUqPLqRrf/OY3009/+tNMpFmXcURt1eova9bHVin0oUOhv1Gpzimfy3aj+e43AkbACHQLARPobiHvdY2AEViRCEDseOmOiDAv1om0nn322U3JYiubxS6EPFJPMtnlHGrZhziLPNfZghxzI+B+++2XnvOc5+QLUV73utdlEgwBpojUaj63B/ISInMh5xBv9lfqVds8l32yVdZ149hVKdv08Vzto197rhtj3MUIGAEj0C0EGifqdcsjr2sEjIAR6BACkf5wxoEHHtgha1NmRA4hdaRt8EyaBS8YQmDvf//7z0SnW1lY9qghupzJzMUqvEjILX+QW+xD1lkTQk2fCnnYjB133HE56sz14OhBiBk755xz8qkbW7duzXNJ67jooovyKSKsiaBLoW4l2qy1VctO+ax2O+QXXdZnf9Tge8ghh+QXH+MLy5tl07URMAJGoNsIOALd7U/A6xsBI7CiEIDkIZBGIrZEokVWSZng5Ip2iggsecs//OEP8w2CEEeOtFPOM2PkKUMsabOeSDT9z3jGM3LkGX/ol2Abwv2FL3wh2z3//PPT1VdfnV9KFOmt1vKd/oUWYURdFvWrr3yWLlFnyDO54IcffvhMVFxzXBsBI2AEegGB5ucf9YKH9sEIGAEj0EMIQF5F/GgTHSaqy8UkENfvfve7OeJLJLqVAukmeo1NSKvIMbZe+MIX5ij0hRdemKPMRJc5vg6Seeyxx+YzoxWZpmY+aSAQaeygx3F0nKzB2c9HHHFE1pEea1AakWX6RWzn20upV7ar88qxsi09/CcNhTHtSWOujYARMAK9goAJdK98EvbDCBiBFYEApLQskFVINC8WQnCJnnKaxbe+9a30/Oc/fw4BZQxiyLF0kOLh4eEZ0kt/SShJv4DgHnXUUYlcaF7249SP448/PuuxJmtDckWAsU8fJJQXD4lo04cdkWWe0Wcf5dxyT2qX/qiPOWV/2UanfKZd6pdj+MMzEXJ85gsIxwOqX+vxRcDFCBgBI9BrCJhA99onYn+MgBFYUQhAAiVETEViyWEmJ5oXAikQVsgit/9BhmlDdCkQSJ5LgilyDKH8kz/5k5yGcWicqCH7IsTZQPwQKYacf+lLX5o5Oxq7+EWh5pmCfqOisdIf6ZZ9jdroaqxaa4x9KMJMnrqIttbWeq6NgBEwAr2IgAl0L34q9skIGIFlQ6AkopC6hRTILpFSUjHIUYYQ0v7Upz6Vfv/3fz+nW5BGsWPHjkxgFVWFLIo4QrDL9fFLUWIdR8c81oJ4i5jKX9Y977zzcq40JFlEFH0i4+RmcyzeQQcdlMc0rvnVZ/VX16n2l+NlW3rU9FfHiKCDEySafbEnnaXNHOFC28UIGAEj0GsILOxfi17bhf0xAkbACCwQAUirZCEmILoixBBe2qRaUEjrIJWDWwAhuESHIZLoILQVheUZ0ogv2IFgPvWpT00XX3xxtiUSyjht1qXNPIjzBRdckNvYo6ADkT7ggANyjb2vfOUr2a5sZMXih9ZQXQzlpvrLWjr0VQt9iqRT65l0DYQiHEryTD+6jUg94y5GwAgYgW4i0Pj/4XXTK69tBIyAEegAAp28yruRO4qUQkohtQgFIguBhQiS6/y85z0v92tc5BBiKRLJbYD3ve990+Mf//hsBxsQ35e//OU5eow91qFA0slxVpSamjHsEs3l2Dr6KNTIxo0bc/3Hf/zHad99951DULWPPKH4gf8q7baZh132yJcHjueTj4zNR5Ll04knnshtiv73CtBcjIAR6AkEHIHuiY/BThgBI7CSEIDYSUQqqSHCENVbb701pyNAgHnmhcAvfvGLM4S63GtJnk877bT06Ec/OhNLiDZjEOVXv/rV2QbzWJc8ak77QEckHV3GuIiFEzeI6IqsU+MDLxZeddVVeUxEvPSlWZv9lVKnKywYky7750sAJ2voC4D8KvXr7LnPCBgBI9CrCDgHulc/GftlBIzAkiEAgasjkBBQSivEDl30NIf8ZoRCH1FXSCyRV4gjpPqss85KL3jBC3JEmvU5w1mpGhBNrctcCvMoRI5POOGEdPrpp88QU6LMzKFgA+JcFgg1+8QGZ1XjC37hDy83lkXrqk/PqtVf1hqjxi6+sBbPrEvNC5S8TKk+YcXeNa+0qbb0mulI17URMAJGoBsImEB3A3WvaQSMQE8iAGFrViB+kDsRQnQho0SaFVXVfJF00jdEliG9H/rQh9Kpp56aHvKQh6QHPOABM3NFGsv5OubuBz/4QSbJPENSRUCxx4t4WoO5EGXIM6JrurEtf/AdfxF0VMq9l23GGz2X/ayBTQrpIZB6jeOzvhRkhekf1T1rjHmNxqTj2ggYASPQTQRMoLuJvtc2AkZgxSEAuUMgraRXKAoMqS1JNDp6hjxCLkljYN6TnvSk/BIdZBdyiZ4IrgDB3iWXXJKjx5BR2Rd5hqSSliHSyjzakOrbb789v7RIH35QmCfCTES6LOjUEVbNRVc66itrbCP4qavEGZc/7F/ztW7dehrTeuWz20bACBiBXkLABLqXPg37YgSMwLIgANlrVkTuRPognpBAam4CpEAOpcczBJhxpTKgj7AWqR0nn3xyOuWUU1CdKYxJB+LLSR2Q0HPPPTcTaxR5Zh10sc+LeNQU7DJOYT7EGL+0P/zHL0WtiVbzouJvf/vbvMYf/dEf5bn4UFdYFxsq+rJAH8I61KSPkI5SjjMXnyglTrJV1vONl7puGwEjYAR6AQET6F74FOyDETACPYsABBESCvGEnIokilyW5I8xdBEKL/PF6RHpO9/5To7MQlQhs2UpSfTVV1+dXxCUDrY1TrSaXGjGIKaswTg1aSQcmUcbffyUDWrykLnlj/5169bl5XkR8Zvf/GY+oxryy5iK9sYz+1cNcWcP9OnLAudK45twycpt/Cjxa2OaVY2AETACXUVg7m/yrrrixY2AETAC3UWgSuZ4hhxyKQrkVKQULyGqFPpVRDZ55rbB66+/PhNO5jWK8jJ2/vnnZxPYghyzLvZ5lk9EmrmU5dJLL80EFsKKcLIGOrSxRRsbPBNxVhF5ly7Rbs6oftzjHpf3KD3qch9qU2NT8w877LCZPel8a8ZKPEqbdW30XYyAETACKxEBE+iV+KnZZyNgBBaMAARPKRAYEVGVQZFASKFOr0CnJM/SFaFUZHb9+vXpyiuvTJ/5zGcy2RVpJrqLXUgoIsIJOf/GN76Rc5npFwHGPs+aIx/RP/jgg3OUmhcE6WdtdEWa6dPpF6zLM4Wa/Gsi0OyLNliwBxF1EVp0FWmmXZJiourYwJeyaK765L+ey/GyzTi6KtUx9bs2AkbACPQSAibQvfRp2BcjYASWHAERSi0kAikCSmRWx9FBHOmH4JUkEnIJCYbsQXoRIs5XXHFF7pPtas1akFuiyBBtCDfpExTWEZGtzisJJukY3/ve92YIPT4wDpHmBT78gjjjI3tlDB1F0kW8Re5lm1q6+EmbfUG0sa2XFplXYlH1Vc/tEOF2dGXftREwAkagmwiYQHcTfa9tBIzAsiEgollH1iCKpGlAMiGPFPooEMkqYWQMPQjwIYccks4888zcpg/yWr5Qhw3WxAb50JzcgU2iuCKnIs7yTb4yV0VjzEUg3BTa5CHLb54p+AjZveOOO2a+ENAHGUZXkWXsIvRpXca0HrYV5cZP7IuY54VqfmhuzZC7jIARMAK7BQIm0LvFx+hNGAEjMB8CIpbUEEFIIQWyd9ttt+W2iCwPIqSMq1+kFIL8k5/8JH384x9PT3nKUzJRhTijRwSYubQpzCdlgqgz8+QHOvjAOLXWyJOm51Xb6Ircsh4vBnIqB+0qqWWdG264Ia/HWozLR/ZBe//998+nivBFgIIf6EK8OSKPcezIZ/moZ/lX1vhYluqz7FX7yzlq47NwVJ9rI2AEjEAvIGAC3Qufgn0wAkZgyRGAiEHIEAgkkVlFnEVgq06gC5mkpijl4uyzz84nbBAFxgbzS4GEQqR/9KMf5Zf8mMc4utiCPJYEsmxXfag+Q0BJ1SCVg3QT1tJ8ap4h7NTskz5qChiQQkIeMwQa/7/whS+kpz3taZnc45+uAke/GVFmfKmLyfNSI2z7RsAILBSB5oehLtSq5xkBI2AEegQBCCQCcRUhhmAql7ckoFWXGYNkQobJb372s5+d/uM//iNt2bIlk1KNQ/RENknLIB3k29/+dj5eTiQWAq12dZ3qM/42KtjhFkPWZj+sTR+FUz+IOtNPH2PoUbAJ8YZA4ys6IuCf/OQn8zF4Rx55ZNq6dWvW7xR5FS7ZqH8YASNgBHYTBByB3k0+SG/DCBiBegQgipBHCDMv0FF4FkGE1DImElpGnCGbP/3pT9N5552Xc50hg8pbRk9Elxo7l19+eX45EMJNHwIBZ61SV+2qx4362YOIKDXR40MPPTTnVGMf4qxx1uLIO/ykDdkn1YM2uhBqhLV0Igd+6GQNrSVfZBcd+spn+sqiOdW+ck6dTqlftvEFv12MgBEwAr2GgAl0r30i9scIGIGOISAyeOutt2aSDJGD6FZJGYQSckkp6yc/+cnpy1/+8kwUV45BAkUEmQth5VISbOtUjZI0ah615pV9rbSxhyj1Aj+JKP/qV7/K+2FtCntGB7848o69IvSTooGv1ESfRbz58qAvEPP5gv+N9jbf3HbHq59Tu/OtbwSMgBFYKgRMoJcKWds1Akag6whAJEnXEDkkMkzkuCwQSogahHLPPffMx9F99rOfTUcddVRWw0ZJmMu5jP3gBz/IxJk1RFTRKeeUpLlso9cKGS118J91ZKckmbR5+Y/IOUQeXX1h0JcEUjzYq/zFDjr64oBeuR4+VovWbtQ/3/zqPD8bASNgBFYaAibQK+0Ts79GwAi0hQBkTukWVfJMVJZj5SDWEMo/+IM/yDnOiuBCFNFhDGKpAkk999xzZ14KxC4EFH3WKwlm2dZ81dLXc7MauyKmIs084xs1UWUizrKJTyLJ6OvLBGtoProIc2VbdTNfPGYEjIARuKcjYAJ9T/8T4P0bgd0YAcggBLGuKOWBS1OOOeaY9JGPfCSTafSJSqtAoOlDHxJ9zjnnZFLNs2ygQ0FP66mWHY2Xz1X/SvLKfJ4lIvEQddZDIMLkLkPoqYksMw+/mMc4V32TD00/RJkxbPHMOKd5ELH+t3/7t/RXf/VXaePGjTNkGl9Ln9Rmbl1pNN5Iv85GXd9i59fZdJ8RMAJGYDEImEAvBj3PNQJGYMUgAHGEQIp0/vjHP06f+MQn0tOf/vTcTySaAgkUYYMwQ1S3bduWUzUg1ojIK/rSrdaMtVJEOqu6+ElhHOG5bDNGxPn222+nmS9LgUjjM77oDGjG5C/kGxuMl/nRRKux/+EPfzjnVZ900klMy7q5UfxY6D4LE2018d3FCBgBI9BrCPg3U699IvbHCBiBJUGA6CxkDLLIOch33XVXetKTnjRzSx9RWRVIJoU+bg+86KKL5kRuIalK2YBQLhWplB/yq6whvKRlHHjggXlf+Mr+iDZfd911WVUkHD35yYuHzEGPfVCYiy7YXHDBBbmvbm3tMyssww+T52UA2UsYASOwIAQcgV4QbJ5kBIzASkGgTGd43vOel57//OfnVAcIJIWIMgQTsgZphEgyxiUojClHGl0RUginIr30U0RQp57m/1lHUJlV7ecZ26xHW+Mis6RfECGHNHOqBvul4Ku+MOAvEWci8PQxRh+2qJmvSLai9NjX2tjTemrLDz1Td7KYPHcSTdsyAkag0wiYQHcaUdszAkagZxCA5HEOMuczf+UrX0kHHHBAJs84KHIoYqoo7W9/+9tMRiGiRGSpS/LIXD2rpm8xpSSjskNfKSL4pS7r8wIkNx3qCwHjpV8HHXRQJsnshcJ+RU7ZG8SbvetLgb4kYENrlfbk31LW8m8p17BtI2AEjMBiEDCBXgx6nmsEjEBPI8CxdJ/73OcyEdYRdkq9wHGiyyKhXJYCcYNMogPRZA4kkjZ6IpKql2LzIq3U1bb6qPEVsksEmuixyD5j+E1/6TP9PGve7373u/zlQISZvTAOkS5L3V6xtVTF5HmpkLVdI2AEOomACXQn0bQtI2AEegqB/fbbL5NQIq0QRcggBJlnnUhBBPaSSy7Jp1igo9QGiBzEmSJSV0cm6/rqQGhEOpv1V8dYC6KMj0SdSTFhH/IRfYizbh7UXvQFgJcMr7nmmplUDvS1N/aOvcMOOyz3MUdjdftxnxEwAkbgnoyACfQ9+dP33o3Abo6ASLO2CSGEQFMuvvji/AKhyKgIIyS1jhRX+6rPWqOurhLhRs/qV40t2vgM+YUsk4bCFwAV/CdizpcF9CDBFO2dPdOGOKOnLxAix+wb0k20Xrrvec970u/93u+l4447bpeItNZV3Q4OmtOolk+Nxt1vBIyAEegVBGZ/C/eKR/bDCBgBI9AhBOrI3Xe/+91MJFkCQgm5hESWpFTzIK9qly7V9ZXjzdoix6pLXfWVNW18gzg/4QlPSJdeemn2V74zRp43Eekrrrgi70dEmtQOXhCEmGp/zKOwbyLVzGX/FPKoIeToXnjhhfk2Rk7tUCn3jV/ls3QWWps8LxQ5zzMCRqAbCJhAdwN1r2kEjMCyIQBRJCp766235iPauOK6JH8QRgp9VRJXEsSyPZ/zsk+tUrbVR02/xqjxl7W0Hr5DYkndOPLII9PPf/7zPF2kl5o9QIZJR0EXG9dee23eD3akSz8EGn0i1hTG2LfWpeYMab10KN+wQ1t+qcZGqcNzO6WKeTtzrWsEjIAR6BYCJtDdQt7rGgEjsCwI/OY3v8nEEqIGeRbxo1a7kSPzjTeaR79Ipepqn/rLWmQSgktaBeSZcUQk+FnPela+AIYoMfr004b4Hn/88emTn/xk3ifriRRrr9wyiF0i1OUYZBliDQFHl/V4lj+t4NCKDj6VRfbLPreNgBEwAisBAV+kshI+JftoBIzAghDgshSushYpVLSZZxE+tevqBS1aTCrJcbM2YwhEFj/23XffnPOMKYisSDLEl5SME088cYZUs6dyvpYX4cYmRPWQQw6ZyY9mDn2sRfvOO+9MnMqBHeZBrsm3Fl6y2ajGTrvF5LldxKxvBIxALyFgAt1Ln4Z9MQJGoKMIQOwghBBBorQQRBFHxqrSyuLYaFREZFWjJ/1qHyQVwT/GIMqc2UxqhdIn5D81uuyBNuPcoqh+bCA8K3LMPok2c+sgNy9CiBmnH8EWXzA491oRaWGD37TJt6ZmbXxkvosRMAJGwAjE70iDYASMgBHYnRGA9In4qV0+t7N3keG6ORpTjY7a1BLIKAUfIPbUIrkQWQrktlkRYX7EIx6R1bCDsAZjzMcmLxbShlRT0KFApq+++upMoPWMH8ylkDrCqRxf/epXM4HGLkTaxQgYASNgBKYQaP5b2igZASNgBFYwApBCET/aFGoIoZ5b3R5z6krZr3ZdTR+i9fFr7733niG3Ir6QXJHsuvUYwwakGIKMHebyjH1eNOSCGApjssXYjh07croGY+UcYUSONG3ZhNC/9a1vTU95ylPS0UcfPS+xx+58RWvNp8d4u59RKzatYwSMgBHoBAIOKXQCRdswAkagZxGAhFWJWPW5FefLOSLDJTlVn2qNUSuyCzkm+gvx5bQMEVWRZ/ygLRt1fmFDJHfdunXpmc985kx6BvoQXa0JAcYWz5wDrZsX2QuRafppY49TPGijjw/yGdL97//+7zMvJsrnOt+qfeiWpfpcjrltBIyAEVhJCMz97baSPLevRsAIGIEWERD5Vd3itDlqEMuy6LmsaUuUhgFJpVBDUslzJtJLaeSPbGalJj8g4+QxP/3pT8+knDWY++AHPzhHmxnnOLsbb7wxR6ghxawpPVI1Nm3alG9hrFsGW+hCxF/+8pfnFw15VkpI3ZyF9DXCYSG2PMcIGAEjsBwImEAvB8pewwgYga4hIHKmerGOiCDLjp5Vi5xS61SN/fffP78cyG2C8oManWrBTrWgKynHiOgSkWadY489NkeSGee4vgc+8IH57GtFfVlLUWUi4Js3b865znphsbRbbUOYiXb/8z//c45ky05VbzHPwmUxNjzXCBgBI7BcCJhALxfSXscIGIGeR0AkuK7G+ZLcSgfip369BIguJBMiyw2CGqefUn2e6p3tryPL0qnW6A4NDeWUjKc97Wk5TUO3D0KeRehpQ+Ahz5Bu/GvkR7kG84hks7c77rgjnXnmmfm8aGw0my/iTi0p7ZZt2dG+VZc6bhsBI2AEegkBE+he+jTsixEwAl1DQCSuzgHGJBBSkVL6FNmlhlRSk6LBcXRlqkarpBA9lVbnoA/J3blzZ3rqU5+ayTF+QFzxCSKPL0SSZbOstV5drX0zhi3I+sc+9rF000035b3S14nCOi5GwAgYgZWCgAn0Svmk7KcRMAJdQUDETkSyrCGpCIWILmSSlwPJLaZAYNtJdyjJczbQxg/WIh0DH/70T/80X7iCPc6CJh8bv5WXXZrV/sq+sl31CX1eLOR0DtI6dOJHOWeh7aovIvkLted5RsAIGIGlQsAEeqmQtV0jYARWDAJV4sZzKSLJ1PSrFrmEJB988MGZPENSIbOyKR2BUdpVn2oRRtXqb6VWtBn7tF/ykpdkIk8be9TaR2lvvrW0D+bQRp8aYn766adnMi27RLhZB2m31PnBOuX67dq0vhEwAkZgqRBo/7fcUnliu0bACBiBZUCgSsj0XNa0S8EtcoBFRonyQpohjpxiAXluJ9K81NvEz+3bt6eTTz55hjQ38k+EuF2fwINI+9vf/vac1gFew8PDOQLeri18cDECRsAIrCQETKBX0qdlX42AEVgUAnUkGYPqV2RZ5FnP1JA8aogjQo4zAomkfyFR10VtpjJZEVz5Sc2lKn/4h3+YT9zAP+2jnKq9l33ztbGtaDO51S94wQtyDjbRd8ZaKehJpN/qXOm7NgJGwAh0CwET6G4h73WNgBFYNgSakUSNiTSXtQgnEWdFoIk2c7IGhLScS4RXc9vdWJVItju/qo9vEl4qfOELX5iJPgSXvTAmsqq6aqN8ruqwT0W0eXGRa785nQOMdCwedfWlxdJm2W60/0b95Vy3jYARMALdQMAEuhuoe00jYASWDYGS5JaLiuw2q9GHFHLCxb777ptznCHVnSjLRQ4hzRBZ/OY0Du1HpFj4zLcn6Vf16IdMc8Qdl61gX3sTya7O8bMRMAJGYKUjYAK90j9B+28EjEBTBKoEGSKJlP3ls9rU5PSS48xFKKRqQAiJ4C6miFxio2zLZl2fxhrVzGlUILT4/sY3vjFxTjQnZ3AeNPtrpTSzrTFqcCES/e53vzvjxLqKRmsd9CTqc20EjIARWIkImECvxE/NPhsBI7AgBMpoa0mgMaZntakPOeSQTDghm5BnorlVUojeQorIp+ZWn9U/Xz3fPKWaoHf00Ufnq73ZK/ugD0Gn3VKuiy0wIp2Dlxdf/OIXZ9wWYrddP6xvBIyAEegGAu3/1uyGl17TCBgBI7BABESMIXh1bSKnEEAIMqkaRGt5ObC8QVB5w4rayg4uiYSWddVV9Ocr0iltN5uj9aRTElr1UeO7xiC0Z599drrPfe6T+xlDtHY5r2q/1JE96fPFgkKqCHrgx+kcPIMpUi2yX7UlvUb9GndtBIyAEegmAibQ3UTfaxsBI7CkCIiMivyVz7QhxJBn9R944IFpy5YtmUwrf7eOyNX1tboR5i5mPus0ml/trz4zlz0///nPz9Fi9ihBtxR060qdzaoeqS9cJ846EHRyr/UZVHV5Fv7NdOrmuc8IGAEj0C0ETKC7hbzXNQJGYFkQgJSV0WeRtbJv69at6aCDDsr+iEQSrW1GFpuNtbqxZjbkR1WnfK4jnBpXXfWFaDERYU7NuP322zPB5XruulK1UX2um6M+iDlH3L30pS/Na2gutdrSdW0EjIARWGkImECvtE/M/hoBI9AWAiKZvNQGaUZoQxqJOEOeIZX0Q5pVi2iXdXXhKhHUWnV6dcSxTr/U09qyV12vfC5tlf2aq5r9Uag/+MEPpttuuy3jAeFlnsbRKW3y3GrBDpgSfYZEv+ENb5i5bAWbrKG9aQ3mlNLqWtYzAkbACHQDARPobqDuNY2AEVg2BETYIG0iiPvss08+MYIx+pa6tLOGCCU+lfPU3vzOkbT1r3Zmob2YQvoKOdGcNALZpXBCRzsFvySN5vFyoa4WR7fVlwvns9toPfcbASNgBJYaARPopUbY9o2AEegqAop24gT5zbwcyIuCkDOirioia2WtseWuqyQanyjUQ5dOzJHF+kY0nlxl7bv6wp/65UO5XrVPuqUObcg5Ef9XvOIVOTJdHfezETACRmClIWACvdI+MftrBIxAywhARCHJRFU5y5m0ApFT6ioBlGHGpKc+kcNGc6Snea3qa161rvNBOiNH9CWkEwU/Ob/5tNNOy18sILvK/9ZetE75PB8OmoMtPgNqyDmXreilQn02slVipj7ZcW0EjIAR6CUEOvMbuJd2ZF+MgBEwAtMIQJh5OZDIs0jhUhKzkgAu5kNoZEcEVlFo1pDuYtZj7qGHHpoe97jH5ZxlcKNovfwQPxaL3fr167MN0jk44o5CekejwvpVHxrput8IGAEjsJwImEAvJ9peywgYgWVFoCR8RFZ5bkbIqoRN5LS0M98G2tGts1XO1/qlz4o+U4/ef/ZXeDmvzu58feBz3HHHpcMPPzxfhgKJFsmdb26r4+xjjz32yJHu1772tU7naBU46xkBI9BzCEyFGXrOLTtkBIyAEegsAjpdoiSatEVOVbOqdOr6Sq8Yl67qcrzVdt3cuj7s3fHq1TNm8/ozT4trKM3i+OOPT1dffXU+x5nznPXyZYlFdaVGvlb1eCaNA31yr9///venv/7rv86EnXUg7bLVbL06u+4zAkbACCwnArPhi+Vc1WsZASNgBFYAApA5yXK7C4GUiFRWfWjUX9Vr9ExaSynY4/k1r3lNuvnmm3N6hYhsmQKz2HWxCVm+88470zvf+c5M0smL5lQQFyNgBIzASkDABHolfEr20QgYjE1yPwAAQABJREFUgZ5GYLGEstXNdWKdkjBX14XYEgnevn17eve7351rpXEQoe5kgUBzW+FNN92UPvrRj2bizukoZWG/ndhzadNtI2AEjEAnEDCB7gSKtmEEjEDPIqAIaumgSFmzMfRF4KRf2qANGS1LIz3p1I3X9Umfuhyv87fUbaUNQZbU6SvSDMH90Ic+lG8rxAeINLX8UVvPjWxVCbvmQch14se1116bTj/99ByVFqbV4/Tq7LvPCBgBI9AtBOb+9u+WF17XCBgBI7CMCHSCiIo4ql5K90U6l2Mt9sE65Cjffffd6T3veU9OtYB0q3TKD5FlyPSGDRvSZz7zmfylhLXbvdBFvrk2AkbACCwHAibQy4Gy1zACRqBrCMxH9hiXVJ2EaNdJVa/V52bEXT6obtVmu3rViHDdfMgyfijq/IEPfCBHret0F9on8sx8CDMk+mc/+1k+j5rodzOsFrqm5xkBI2AEOoWACXSnkLQdI2AEeg4BkdFq3chR9JqV0k5Vj7FmpK+cW9eus4deJ0tJWku7deugC5GGzDL+3Oc+N0eFIdXzvewnkl6uQVvrVP0g95l1WG+//fZLX/rSl3KbFA+IteZV7fnZCBgBI9AtBEygu4W81zUCRmDJESijx4tdTCRO9WLtaX7pYzMCLv3lrNkrAmE+5JBD0pvf/Oa0bt26nLu8lH5ccMEF6dxzz82Raa4A7zVclnLvtm0EjMDKQMDnQK+Mz8leGgEjsEgEOkHCOk2e67aEn8uxTt3adX34g5CTzLnQ3OzIM0fQqVQjyuqnXsheiERfeOGFee6jH/1oE+gSULeNgBHoCQRMoHviY7ATRsAILCcCjUgdxLAspV61XdVt9My8cm5pv9ou9bBXPld1Gz03I7ON5sj36no8yw9SKSjPfvaz04033phP6IDocloGdbmu5pXrMY4epapf6tFmPkfpEYUm4l3arur62QgYASPQDQScwtEN1L2mETACPYkAxK0UOUlfu0V22p0n/YWsqbmdqkWsZY/8Z8jvAQcckLixkMILgK0SXPQkstkMJ9b66le/mq666iqpuzYCRsAI9AQCJtA98THYCSNgBJYaARG1doip5izUt1bmS6cdvxbqz2LnkcJB2blzZzrmmGPyJSjlcXPaS6vrVPdcfYbAE+GGuLsYASNgBHoJARPoXvo07IsRMAIdRUCErkrMykWqUVaNlXPKNuON5mgudXVOOabx+XSqc+Z7ViSYyC3STpnPF8Z5oY81OB0DMn3WWWel+9znPvklQ1I8wEWpHujLpvySP+WY+qq1MJaN6rifjYARMALdRMAEupvoe20jYAR6EoEqaROZa9XZ6vxm89q13cxWJ8Za9V1R4ec973k5SswxdJBnSHZZ6shzOa52q+tK37URMAJGoJsImEB3E32vbQSMQE8j0A65hQBK2t1UO+u0a7uZvvwVeVXdbA5j6OEzhJlINxet3HLLLYnznDnyDtIskS2tpeeyrlu3mX45120jYASMQDcQMIHuBupe0wgYgZ5FoI7MVZ0VuZOuaulVn9XfrO4WiZZPrfhc6pDGwTPXfe/YsSOncxCFXkyRfdWLseW5RsAIGIGlRMAEeinRtW0jYAR6EgHIqggrkVIIm6R0uI7I0af5sqHncm6jdnUdPdet1chGtb8a7S2fq7nQjdbTHrQnrSF9nssx2dUNgoy98pWvTNu2bZvJv9Zc7a2cXx2r2tf6ro2AETACvYiACXQvfir2yQgYgY4jUEfeOrFIHRHshN35bECSKaob6c833mheO/3kQ7MOKRxvectb0qZNm/J0EWfZ0rNq9asWlnp2bQSMgBHoVQRMoHv1k7FfRsAILBoBSLMEYyWJ5rkRkWNssUVkcCnWEClW3Yqv8qeZblWnme/SlQ4Radp77rlneuYzn5kvQtGLhuWa0i/7aDfqr+r52QgYASPQCwiYQPfCp2AfjIARWBIEIGWScoG6vnK8WVskvJkNkXbpYq+ZfrP1qmONSLNSKqr6epZPeq7W+KdS+lrXX/YxB9vyi5cIOdruzDPPzOZI8dDa1XkolGvlCf5hBIyAEVgBCJhAr4APyS4aASPQGQTqCFwrlhc6rxXbrehATiWN9EVgG41XiepS7glfINJHH310vqmQFw6RallKH6pr+dkIGAEj0EkETKA7iaZtGQEj0LMILJSsLXSegCij0OpbyrrqL891fZ30QWuoZs+0n/a0p6WtW7fmmwSV4iEd6lbKfF8MWrFhHSNgBIxApxEwge40orZnBIxAzyCg1AE5JPKm53ZqzaWG1Om5FRvoLldphbBLR3to5l+p2+oehDs4vexlL0vXX399jkiPjo7OpHo0ssWcUhrpud8IGAEj0E0ETKC7ib7XNgJGYEkRKAliM5LYrhMiiCKX1fmdXBcy2W4p16+b20ks5rPPld/vf//781nRvFS41GvX+eM+I2AEjECnEWj/N3OnPbA9I2AEjMASItBpwla1x7OEbVTHF7I1kWbVC7HRaE4n/Gtku+zXOrxESD70WWedlW6++eYcXV7shSvlOm4bASNgBLqBgAl0N1D3mkbACKwIBEQCS2cbRZ1LncW0RZpVt2oLX+v8rc6fL3pe1ee5FbvlPK1BH232MjIyks4+++x00003JaLSZWFcUva7bQSMgBHoVQRMoHv1k7FfRsAIdA2BVslo1xxssnC7ZLfO1EJtCLdGNWT6Qx/6ULrrrrvybYVDQ0O7nM1d+iM7ZZ/bRsAIGIFeQMAEuhc+BftgBIzAikJAxI66m2Up/ViKvRFlvvPOO3M6B7cW6mSObmLotY2AETACC0HABHohqHmOETACuy0C7RLHMl2h3blVECGYrZZGazXrZ6yUZmuxL5Vyj+ora9ks++ra4+Pj+Ug7cqJf//rXpzVr1mQSTT82dBlMq/bq1nCfETACRmA5EBhYjkW8hhEwAkZgJSAAcWu3LGROu2u0o18S33bmVXXZF7Za2V+reuUa5EHvt99+uWvbtm15LV4uLEl0p/ZSruu2ETACRqATCLQe7ujEarZhBIyAEegxBCCIktK1Vohjqb/Qtl6eayf6XLdWJ8hmFYd2MGh3/XXr1qWTTz45nXTSSTkqzf6JTLezZh0O7jMCRsAILAcCJtDLgbLXMAJGoGsItEvs5Gg5T8RSdTkm/VbrkjA3I82KxJZ2tX6VZKq/1G23XbWp+a3utdF82aHGloS0Dfa4//77p1tuuWUmhaMTeynXdNsIGAEjsBQImEAvBaq2aQSMQM8g0Aqxa9fZpbBZ9aFKrputOR/JbTSXfkl1fT0vZq5slHXden//93+fHv7whye9WAix1v4brV/adNsIGAEjsNwImEAvN+JezwgYgXscAmXUud3N1xFO2WhEnDVHtfQXQ0ZlS7VszldLv9na5D4//vGPT0cccUTq7+/PohcL57PvcSNgBIxANxAwge4G6l7TCBiBZUegSjZF7Ooc0ZjqOp12+oioVqWd+cuhW8VHa7aCATrVUjevTo95YEM54YQT8skc6OkGwzzgH0bACBiBHkPABLrHPhC7YwSMwNIiUCV21eelWH2hEehGhFM+zjcuvZVU/4//8T/Srbfemm8r9JXfK+mTs69G4J6FgAn0Pevz9m6NwD0WgW6RTeXytgt8O/6iW0qztdqx28zOUo0NDg6m9773vYlTOnrd16XCwHaNgBHofQRMoHv/M7KHRsAILBIBETHVpTlSF5S+wHidTqm/2Lai0XV2lMrAmHyq6snHsq7qlM9VvWZ2y3m0mVviUx2ve9Z6dWPqQ6dRIfd5dHQ0vexlL8uRaPSa6Tey434jYASMwFIiYAK9lOjathEwAkagDQTKaPVKJI2d8JmXCLFD+sZb3vKWNDQ01PDLRBvQWtUIGAEj0FEETKA7CqeNGQEj0GsIiNSpXk7/SkLcyrr4KJF+N/zW2tRVf8qxpWiXEfJNmzalE088ceYlw6VYzzaNgBEwAgtBwAR6Iah5jhEwAisWgW4T0naAWwpfRYg7bbtde438IAea6DOR6JGRkXSve90r7bXXXu3AZl0jYASMwJIjMLDkK3gBI2AEjEAPIVBGOEu32iWA5dxqu93IM/Or65fPZbv0v+yv+rCcz4v1o5xPDjSFPog0hHrNmjXLuR2vZQSMgBGYFwET6HkhsoIRMAK7GwIlYWtlbxDi/5+974Cvo7yyv+q9d7lJ7r134wKY3gmhQxxC2m6S3ZRNdjf735BOygYIIbQABkwzbmBs4957t+QqWb333sv/nGsPeSgyGFuGR7iff1fTZ74586R35/p857gO8OvumAtJmp3zdNefcyXK3e3rnKenpp/GNc51f673wCp0U1OT6yqbNwQMAUPALRCwBNotHoN1whAwBNwVgfNJjM9nn3PdX08lq67ncU1Oz3Xdz8P6tra2Dyy9Pw/9tT4aAobAFwcBS6C/OM/a7tQQMATOIuAkmK5J57nA+bQrz04/2Denn86685263pdzDtd1znm6W+ds+6jpp3Wccx1n+lF9sm2GgCFgCHyaCFgC/WmibdcyBAwBt0GgJ5Iyd6g8uw2gn7AjPYH/J7yk7W4IGAKGQI8hYAl0j0FpJzIEDIHPCwIXm7xdTOJMjC72+p8E50/zWt3167O+fnd9snWGgCFgCFwsApZAXyyCdrwhYAi4PQJM4j6KyvBp3sD5JJTOPs70fPt3Ke7xk/aha1/ZJ+ccTv+4j7Ou6/62bAgYAobA5wEBS6A/D0/J+mgIGAI9gkBPJG2ftPr8Sa95vvt3tx/XuSap3YF2Pvt0d1xPrOuuzz1xXjuHIWAIGAKfNgJmpPJpI27XMwQMgc8EgZ5I3tw5eXZAPZ/7PJ99nPNdyJTnd+JCjrdjDAFDwBBwdwSsAu3uT8j6ZwgYAheFQE8kix+VOPP8H1f1PdcNOPSG8+mjsw+Pcb2e63pn3vV63a3j9q7rXZddz+96rguZ7+68ruu69sX12pzvuu+F9MGOMQQMAUOgpxGwBLqnEbXzGQKGgCHwKSDAxNI12ewu0exu3fl07VIe1925Xe/DtX/d7eu63eYNAUPAEPisELAE+rNC3q5rCBgChsBHIOCaPJ4rwfyIw91yk+s9uWUHrVOGgCFgCJwnAh7nuZ/tZggYAobA5xGBUnQ6+/PYcevzhxDoh6WYD62xBUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBD4OATewA63ftxOZ7cvwfTa89z3i7zbTNz8yS8yAJ/Bvc/DNbddgutuwjkfvgTnvdSnnIcLXAo8LnW/7fyGgCHwGSPg+Rlf3y5vCHweEBiNTo5BvHO2s5djmoKoQpQjliJ6IZz2KGZ+7Sx0M52DdXndrN+Eda5JSDiWn0YUIRoQvOZXEV3b3VixG1GPKDk7/y+YeiC6a5uwsglRi6hB7Ef8J8IP8Wm2rbjYkPO84Bzs1x1m53n4P+zmjTV1iMkuW+7DfGc3606c3ecRTBcg+iJ4rBM8htg7y3wxmI/4FcK1JWGB+/LaTpuOmQ0IPotqxHLEcITT5mFmm7PgMs3C/FzEKoRz3VbMt7gsP4N5a5cWgSycns+BbR6Cz/c/EK4tDwtzEHwezrPic+Lzcpb5HJMQPN5Z50zvwjq2+Qjn+VZgfi1iKKJrm4MVPM+Pu27Asi/iEUQagp/ZLMSLiCTEUYRzzXbMN7ks/zfm5yG2IdhWI36hcx/+cQsW+ffKGzEf4fTXOe9hrLNmCPxTIGAJ9D/FY7SbOE8E4s5zv667fRMrXkPwS4ntGOIaBBPcRAS/jJ5GOG0PZkIRE50VFzDlF906RD/ENEQYgl/MTM5/gHDaDzHzBOIPiHgE7/FbiBkInuNc7TvYEIJIQPAcdyNWIs6VdGNTjzZ+wX6arev12nDxnYjZLp2YhfkT3azb4rIPZ3MQwS7BdXzBctbxxeB8Gp/rGgRfzPg5SkYwwdiO6I84n3YddnKuy8/o712W+Tn4vLWuz+nz1n8mtj9B8Pe/a+PzcJ7VbzD/lssyn6PT+HfF2Y9T7uc05/n2wop8xAvOBpfpVzDPfnDatS3CipsR9yL4N4WfW75AX4kYgXCuy8/wd1yW2V/XNh8LDyC6/r3gOn4O+fvF5vTXOS+v93GN54z5uJ1suyHwWSNgCfRn/QTs+p8mAvNxMSa330bwS+p8G7/cNrvsXIz5ApdlVmsGuixzdhPiBs5cYOMXESudX0ZkIloR7yO+h/gFgl/Q/ALk/L8g+MXIKmYn4iDiPkQz4uNaPXbYhOCXKhM6p8/82/CfiNMIVtkXIiIRbP6IBQiur0LsRTgvJ9znJQTxqUQsQ7DNQeQhmFwUIbjPHATXOS0LM/+F4AsKj+U+vFYQYhWCSaZTyeK8H+JxBK/F4DzXsc1BdL0e17u2LVhg0uy0mZj5HaLrOu53KRqTi1cQfAHis6tA/A9iF+IRxKVqTFCeRFQj+MLA5MlpX8XMcQT7k4H4JsK13YKFQwj+zwU/G9ciurYErDiC+NHZDcmYEkOeky+FTyEWINiSEPzMfg2Rg9iAYOPn8SiiCrEJMQzhNO4/0FnAdD7iV2eX52Cah/ghogRRiOA9OS0KM+8i2P89iAGInmzEbifi+z150m7O1Yh1/J0c22VbIJbvQPwrYhDC9SV+LpavQvAZ8neWSS4/A3weLyA+SVuGnSMR/J1xWgRmbkTwM30hrT8O+jkiE/HQhZzAjjEEPk0EPHEx/oFyjfdcOsB5122u87Zf99gYLu6LC7+Uf4O4GpGNeB3BLxT+HpyrMXlLRpzsskNfLPP3gV9kP0L8HuHa+EU6xnXFJ5xnv1YhmOC6tsVYYFLJZJfBhPEdxMW2HJxgH8L5Qvwe5m9FzEYwWWVCyy9atq8gwhB9EExIvoUgDmyvIvglPgIRi3gM4bR4zPBLtx/iG87KLlMm/tcgmNgMRjChJAZ8iSlAOJUszv8UMRUxFkGsJyO4v9M+7npbsOMMBJ9/NILPmkkJz+OsG4p57tfTjRhNR7zdzYnZBz7/S9Wm4MRMjnnPP0MsQfC5sJUgmASFIph48vmNR7ARl1cQ/4EIR8xCZCFcWxIWNiP+gvgjgu11xB4EPyuPIB5AdG38nDFJ5rPnc38D8e+IGMRKxHKEL+J8Gp87P5+9EEzM+bllcsfG+SYEk/yHzgYmPdr+H872fYSDaY+e/OzJ+Fm9B5He5eRfwnIdgp+r1YgHEU5jAs3nkOusuIgpf9/5OXU9/51YPoE4jDjfFogdeY6NiL2IWMTdCL7IOq0KM+eK/3R2+oh9eKzt1z2GhsvF4eLy8bNZQ+CLgwCTByaJBxA5iO8gumv8Eu5EMGntrvFL8ieIqV02fh3LG7qscxbnYKYD0fVLgRWhhxFs6xCP6tw//ijCqvsQ9yM479p2YIHn5RfcLNcNLvObMO9cx2W1vImF58+uOI7plS4bmXC0IrwRTDx4ndEI18Z9eF9OsuK6bQ4WWhD+Liu5Ls9lOQvz33JZvh7zp88uz8HUdV+u5jbu4zQmX1lnF+Zg2vV6Zzd9MGFfmhBMvm9DvIZg24Vw1mXqmjM/HsFkgcuyM8vPx0Bn4ex0PqY8t+szrsEy9/VG9D47PxTTru1arCDWbPMQ2zjTpWVheW6XdfOx/Ksu67ouzsOKAoSHy4Y9mO8uqeUuyxD/xhm0ZxGP6dw//tiEVX9CZCHuQTitL2b4uWai5LQFmGGwJSGISX+E05iALnQWMPVE5CPmINi64j0f65z7noN5fva9EU4rwQx/P70QxNUV899geRviQlsWDpx79uB5mDrnYv+dJDAP83MQru0RLCxwXYH5JATvzfUzw3m+WLDNRzifKf6eZSK6/g7y78bjCDY+h1KEDxfQ+Lv9ps59/I9N2OXhLrvNw7Jzf9x0GaIaEcAFtO2I7+vcmR/zMXH669zTyy7b/4b5CgRfkJh8+yGsGQKfGwT4h8maIfBFRID0gyOIQwgmfMmI7hr/8LOFnJn8w09+AfBL4R2Et8tW7u8c67L6g1kmMeFdwvXLqQzbmJB2bbwGk39u5z1w3vW6rGryvNz2SX+/e+EY3g9bP8RSBO+BwYS6HRGHeBWxGsEvY97H7xH8ku6D4PGViO4av8z5hfpRLddlYzbmE12Wu85yG/dxWtf9P+567MseBF80GFsRbHwOzrotuubCfrAC6/qMR7uchhgxCeruGXMdny8bk08nAdIVZ39wnZNku64/n/l87MREzWmuuF2HlbsQfI587tcj+Blj4/M9rXPd/7gPq3nuRS6b+Yx4rgaXda7P2Fntuq7rcyVO3M7P5/k0fvaJm9N47WAEq9n8XXG9luvnB5s+1J7BUt3Z+O8Pbfn4hf/FLt9GxH/8rv+wB/F2/dzwd89pzmcqCSv4ojDE2YApn8/liNfOruPfJH/EDWeXiUt3n7ezmz/xhL8n/B27BdEfMQnxOsK1Of117ucrLhtHYr4FcQjBv8XNCGuGwOcGAX7BOn8gnOkql95z3lnfdWr7dY+N4eK+uPCjPQjxSwSrN08gUhD84/9DRHetHiuZNAzubuPZdfxSjkWEuuzDqtFhl+VPOrsOBzCZCepyIP+Lll80THJ2np3nF9jFNn75TkBsPXsiJhm8vvPFxym/jJkgMXH7OWI4YjriRsSDCB7Dijz37a65Jm3dbec69sNpfTHDBJ2tu2O5rZ9uPfPDdX+u6e4Yl911lgnyLMRMhHPvnDrruP1SNH6u+Py+3M3JWY1bf3Z9Dqa8L4+zy5wEIvh5+6jkj/udqzERdT2fgxsrgIsRTHriEHyOKxHOvny+AxDnao9gQxmCSZQXgq0Qwc8E++w012fsrHN9Vl2fK6/PY/jZY2tAuJ7vfJNUJntMrF2vz3s/V/sWNgSfjd+ca6dzrD+B9UsQnzTxPsfp/mE1Pxf/huDfsICzWx/A1BOxHFGEyEDwd/ZBBBv/pkxG9OZCD7VXcB6en9degyhGnG+bih0vR/Dv5wbEHsR3EFEI19Y193BddsXXdX3Xeduv++9lw+XicHH9nNq8IfBPjcCLuDt+wT+JYLJ4vu3P2NH1D83tWB6C4JdVDGIh4gDCtZ3CAr+sumtzsDKvmw2bsO7hs+uZzPCcTGCSED6IaxD8gvoPhNN+jBmuuwPBL3v2aSyCFc45iO7aJqx0rsNEZDaC19qE4PFs30dsQjgJKu/TSdT5pTcKwSSJyRFfFOYh2FYgXkdEINjnWQi2OYiu99x1XRb2SUHwC57n3YpwEpehmG9EhCGc9ivM7ECwb9GIbQiuY5uD6Ho9ru/arsYKfiaIIRM1Nn6BO8nWIF1z5scjmCxwWXZmmfwNdBbOTudj6vTF2ZSEGe7rfXbFZZjWI76HCEEQMx5ThXCuy89BJuK/EEyG+ELFz+NOhNNfzGqbj59dr3lmy99/zsNsG4LJF5/PlxE1CN4z+9COmI3gua9DNCCcc/LzzL5dieDnhIk4nwvbJsTDCF8EP7OvI5zP0i7M/x7BbdMQ1YgFCLYkhCsmXDcEQVx4HfbxR4gMBI9n2454FOGFuBbBz4XTxzmYz0O4tiwszD274i1M30Twcz8cwX23IS60ZeFA59zzMO96rmQs1yKYzM1BuLZHsLDAdQXmkxBdsXDdZT4WfuW6AvP7EHyWbEzaH0HwhcKJmzHPF24+X7Z3EXsRExDeCD7zbyEeQri2TVh42HUF5uchtnVZl4TlFkQegp8l1zYfC79yXfER83yWNyDeRhCzryGsGQJujYDzB86tO2mdMwR6CIFncJ5ExHcR+z/BOZ/DvvchmFSwMXF4H8E/9CmIDsRtCKdNwgwTgD3OiguY8ktvLiIXsRvBJOdPiJ8i/oBwGhOTHyCYSJcgmAg+i/gJYgfiXO0v2MD+c//HEYsRTEZ4L2xPIPhluwbB/XYhpiDY+OW8CME+HUdsRixAsLES1Yo4gWB//h3xSRoTL16TCRPD+QLm+d44u45JHJ8jtzGBOILgc+BLgLM/Zs+rESMm5cSYyQtbOaIUwf6nIS5V24YTX4O4HVGIyEaMQzCxdq7LzwETizmIPAQx4b3fiXD6i9lP1HivTND54vBrxB0I3jOfM5P5hYhKxL0IfgactgczX0U8hmASzOfeD+HaWrDA+4lFvIjgd8x9iGkIXoPP5y0E7+tc7SQ23I94EsE+3nQ2eG42Joxcx88Bz70Mcb7tO9gxGFGEmI94CXGpWiZO/Coi6BNegPfFpNuJH3zE8fxbwN/92YgkxFMI3psTfH7piHsQbHzWKxF8BnyGqYiJiHWIC2lZOIi/Q7xH188KFrWxb859cMrn2V3ji9sKxJcR/EztRFgzBAwBQ8AQ+CdAgIndred5H4ux3/Xnua/t9ncEsjA79++LNvdPigCTt5//k96b3ZYhYAgYAoaAIWAIGAKfKgJZuJol0J8q5J/KxSbhKgMQrEZfi2hCsNJuzRAwBAyBzy0C3p/bnlvHDQFDwBAwBD4PCJDyswQRhchDfBtxEGHNEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAEDAEDAFDwBAwBAwBQ8AQMAQMAUPAELhQBDwu9EA7zhAwBAwBd0cgKiqqMykp6UPdbOtoFS8PDP/AX7+2jjbx8fT50PYLXahvq5cg7yBp62wTb56/m1bbWiMhPqHSjn20D93scyGrOqFo5/GByuL5neFcxzTgPgJxH077qPtx9vmoqXOdruf9qGO6btu/fz/lz2K6rrdlQ8AQMAQMAUPAEDAEDIEeRmDChAmdXdu6/FWdh8r3aZQ1lXbd/ImX29rb9Jh1+St1urlw/YfO0dLeosvtHe2dGwvW6PyWog0f2uejFlrbW7vdnFmTrusPlO3p5D7sh3Otbg/AyqOVR3TTscqUzobWhs6Ojo5O9su1ER/XtqlwnS5WNlfo/q7bPm6+sCG/s7ixSPu2qXDth3bntV2b0zfeS9dt+Fjs6+GPhp3OEDAEDIGLQsCMVC4KPjvYEDAEPm8I5DfkSrRfrFQ0l0uUX7RWoV3vIaP2jIcJEkbX1eecP1FzVLfl1ufolNVltuLGQkGCKIfK9+pydl2G9AtOFiSsiDP76IaP+ME+FjUWfGiP0ib6u8BRpY7+GHATaakUb09vSak6CJ247v+kN7bRrA9uLQ35OuU5A7wDJL32pHR0dmiwgs7GZVbmnebcT0rlIfHw8NB7cra5Ttmv8uYP+2ScqDoKrGMkux73HpSsuxMTNuLB5iw793m06rBeRzfaD0PAEDAE3BSB7v/aumlnrVuGgCFgCFwsAhVI8hIDe39wmp2lWz6Yr2utk7rWWsmtz1YqxoFymu/9PclzTSy5nklffn2uoPIrpGe4tn1luzQR3Fy0XpjAZtdlIoHur8lkEqbn045WHZFYf6rAnWlMNo9V0XTxHxsTfi9Pr3/cgDUplQc0cW/pOGMAiMq7LufUZZ1JvisPSsPZe69oKZOm9kZBxVjPRTzYKprKpKGtQU7XntJl1x/Hq1LlRPVRfSHher48sJG+4enhKek1p6RPUJLwug3tDZqgZ9fTqA+WlTjOtfGlwZohYAgYAu6OgCXQ7v6ErH+GgCHQowh0kC/MSir+MbEtaSiRnSVbpbmtWQ4iYS5pKkbVeJ+cRtKXX5+n80zy0mtOItlL1WS5Hskm29HKw+Lr6avVXyblze3N4FT7anKaVnNCuB+TzpOoUqPOq8kkk9a+qER/VHOqzORr+3r5IqGl94gIq+dxAfEfVG25jvfRXXMqu0xa9+O+GpG4Ztae1l15PzlIYJkosxUh4c1tyNZk1t8zQM95pOLAmUQXiT9bJirePh4+chwYgGYhadXHtR+7SrYpp3tm3OW6H390TYq5bm/ZTklFFdvPw0/PlRjQR8+/q3QbN0tNC52lrRkChoAh8PlAwBLoz8dzsl4aAoZADyAAPq4Eep0ZIFfcUCSbitYiQd4jm4vWoeK6RljxDfAMlDxUlZm8ljWXIBk8LgfK9sqLaU/LlqKNsjjrdVmbv1J7UwBKRF9UVrcWbhRwkOVY5REJ9Q6VI6jokk6xMm+ZJs2HyvZJbUuNXofbWLE+V2Pim4rE3LWl4Bi2NCTxA0IGS15DjvZvXcEqya3L1m0tHS1SCToHKSJnKtWpOp9acViOVOxH8pyBCnCJFDTkgb4RqNc4imo2E30m5r0C++i2IO9g4XnHRU6Wd3MW4YWiCNXncqlrq5MsUDH4srE8d7G+aLyf/65E+8fKyIix2gf+4EuJp3hJdUuVpFefqVaTFkLKRiEq9mUtJZJZcxp0jxIhXSbAKxDYnKn654EG41BJPjihzRgChoAh4IYIdP//fW7YUeuSIWAIGAKfFIHExMRHvvGNb3xw2OKMBVLVWiVend6ysuAdGRIyTNYXrpaJ0VNkT+kOSQzqLavz3pNRSAhX5r8joyPG6XKEbwSSywLZV7oTFIR6WVuwQvw9AmRD/hoJ9QuTFXnvKKd4J6qph8v3SxOqzqWNJRLmEybL85bI3MTrBYPz5M7kB2RN3gppk3Z5P/cdVIUb5eW059G/TtletFn8JUhq2qpkEfp5WdwVsijzdRkeMVoWZrwqsQEJuj4xoLesz39f4oN6IRFvAj3jkFaSl+cslkDPIFmQ/oL2ZX7aszIuYqK8kP5X8fPylzL0pwgvEKyAH6tMlWCfYNzbu+Ln7S+7i7aDYtFP3sleJMkhA2Vl7hIkuOWyA/SWEhwTH9BLNgCn4eEj5eX052VgyCBZmv220j8Olx8AflPl3axFSlFZi/sjnaU/9nk5/Tlc21fmpz0nUf4x8kbGfJkeM1vxa0K1npi3d7Zqot3Y0YSXjzC95ysSr1WqSqx/nP5vwc9//nNyQp774EHajCFgCBgCnzEClkB/xg/ALm8IGAKXDoGuCXRiUB8hN/lLSfdIatUhua73LXKiJhXyc8FaSSZ1Ym7idVLYlC9TomdKXmO2TIqaJh0e7Zpgfrn/fRKDpG4CEsYhYUPFy8tHxkSOl0GhQ+SBgQ/rOchDvm/g16QV/4IhWTcr4Qq5utcN4o9Be8MiRsqkmGkyKnKMTI6ZgWR1gMyOv1Kno6PGSVRglET4RYqHp6cMCB2ENLtdhiFpHYjzlzYXyeCw4RqDwodKI+ghM0ib8BA9/w19bkXiWi13JN0nfYL7IQEulRAk91F+USRxyx3J9+PcETI9bpZuv7Hv7ZKE61+TeJOQG31931vRR3+ZgQQ33D9CpsReJvf3/5pWjh/EvWXVn5a7+j+o/PG5va6XewfMk2mxM2Vm/OUqBRjlH63yfcMiR4FDngXqiZ/EBMTK0LARoJ0kyH0DHkIinojzzpDOjk4J8Q0FjlM06Z4FDJrxMkGJP9JKTtYc08o9q+KUBLQE+tL9jtiZDQFD4MIQsAT6wnCzowwBQ+BzgEDXBPq5k3+WaiSZNaBTrC9cKZWosrKazETvbVAzvtTvHtA19kjvwL6gL7wt46MmyZuomob5RMqOki2gL2yWytZK2VjwvkQiMV1w+iW5AUn4i6eeQnV2jCxHBTfEN0ypHFTlYAW6ADzqcdETZVnWW5qUvpXxiibdizJfkxFnq8ttSLaXZr4FZY3TUoXBgCerj6H6PV4pHy2dLfLSqaeR5LbIqaqTEhUQJStzlkl0QBx42WlSBg73SCTkyzLflAgksY8f/51Mj50tz554XIJBJ3n19AvYN1ZSUCkmdWR/2W7ZjAGCkLGTzQVrJcAnUCvFXkjaIbMn4F/gfv4qwV7Bes+nak/owL8dxZtwzzHyKirck2KmahWc/X8b1fJoVJcfS/2ttHQ2y5HSA6i+l4o3Xi5eRuUZQnmyPGeJDiB8ATj5efrLelBEqtsqZXXuCqV6rMpfJs2tLbKvfKcsznlD/FExHw8KSV1bjcQHJloC/Tn4XbMuGgJfNARQu7BmCBgChsA/JwLUgd637+8SwvUt9bI6fzkSwOnyVubL8q2h35cX0p6Se5Lmgbd8QAfaSaeH0iiifKM1WY73i5fcxhwJRxKdFDwAPOlDqOAmKW843Dtcru59I/jT61ANnq3JKU1IRkaMkUMV+0AFGacV1VAk1WzkJreeHRj4UYhzMCIHJ5LPfLT6sAwOHa6V8+ERo+Qw+MwToqbIqZrjmmSy4s3zqhwdBiqyYsv59YXvK98bW2Qoqti+nn6SgoGBM+LmyAFI642OHCdZ4CUPBKd6Fagc1/e5RfLqcqR3cF+h/FxGXZpcHneNPHXi/+TfR/ynrCtcJdf2uumc3a4Dj5nXHI2K/CpQWr4NbJmIf2XQN+VdvFjcnnw3uOMrULG+UraBS84qPl9gasCVbmhpkG2lm7QKPTB8MIrqXvqSweo7GwZ97sdkoi7YD0PAEDAE3AABq0C7wUOwLhgChsClQaBrBfrFU8+Ay5yrye8GJISUUtuEKqyHp4c8fvS3AgMPeR8JNhPFDRhUODx8lCzMehV0jZE6eJDcZtITWI0OBCWD1VfSIF5Me0Y1nl8F5/dMQr1WYnzjJDG4l+wt3iF9Q5JlS/4GSQrtL9sLN0u/0DPLrtNjFSmoMrdJKKgNOwq36L6b8tdJizTLtkJUf/0jZUPBaukV1BfX34xE9ArJq8mXisYKpX5sK9ik1doXTz4lFS3l4DG/C1k7T3kWVfcJ0ZNx7BpU1CdDC7pAjpYf0j4tynoTyflQWY0qPKvt7+OYweHDUPF+VkJRPT9Qulvy8fLQ0AJaReUxvFBUyE5wtQeEDVbetGv/3zz9MgYA1sl2YHMSAy+rMaCRLxaNHQ3yXs5SfTkhXs0YZLgqd7m+GLyNKnwLll/I+KscKIECSksRuOCb5Hb8T8CEmCkffCiMwvEBFDZjCBgCboKAJdBu8iCsG4aAIdDzCLgm0KzShvqGox7bKYNChigf947k+5SbfG3vm8UH/x4e+l1J9O+tlAcfcHgLG/MlKWigDpbjgEI/SLzFByXIHX3vlyFINOOw7/S4mRiU6CVT4y5DRXgqONKxOuAvMiBS1Sg8YXIS7hcOSoOvJsfnmnrh+qEeoeLj4/PBvnmNuRKOPlNdw9/bD6YkccqJ7h88WIIwCDDEMwSJ7t+PCfEJQdLeD1XgsZoAs28zYufgXhN0EB85xZ7tnjI0ciToHpES799L4gLjFYsY0DMotdcLAymJEU1fhoGiQV7yZfFzkMBHabIdERADHnQvIT5M9nl/rHKT+1HeUipXJ9yA/nvJbf3uVqWOK+KvxrQQnOmHUNzvBPd7OpLramAcjYGYgUr1mBV7pbDyfCX45yPDx4KmEqN9cnStLYHu+d8NO6MhYAhcHALeF3e4HW0IGAKGwOcDAcqrbUYF1wuJ7HpUXIeiqkxTEC9qG1cehZbzIQnNCwPN4bBEVUequsU0cIlzms8YoMD+Wq5IvAYSbytBdciVVnCTT1WfxMC8cFlV8K5Mjp0mW0s2gC4xXCu91Jpm6xeSpNNeUM1gO9eUCbfTEsH7ZaPUWwecDZuhUMHqeCrcBpmM01FwdvxcCQkIdQ5BCtsm1FSmIga1n49UHZCZCZcjAQ5DtTxQEpD0sgWC8+y0pNAknR2IAYuUtyuGzFxpY2/wtnOAzzCVr4sA15tVdzoJcnBhXGCC6jcXY6DlMdBLMMISyXCMZNWma7+2tK1DQi2SW5sFrekMScU+zaCtrAdvfEPOakjYpcnO0u04Xz9U3DHUElGBAY8lDcVI8qNkW8kmmRw3XQc2+nj6qAqH01+bGgKGgCHgLgiYDrS7PAnrhyFgCFwyBJhQkksc4hMu06GuMS5islQ3V0NDORMmI7tBM2iEgkYy1DnuRYIagYqzDyqho1Fx9pUI7ygprM+XsRET5FDZfh3cR+vs4dh+ZeLVMjBsiEyBogZVNvxRlW0Ff3lF9jIpbyjX+3n++J+Vk0z6Alt3U1bHSfFIrzhjz/3okZ/pvjtAZ6jBoMe06hMY/FilRiZMOOsgE0f5um0Y2HcQpi9su4q3yqToafK3E0+q6Yug0kwt5rWQ5WNzrstr8Fqu67gtAVJ1G6GHXYNBktS/PgSudT5eFMjzbmprkSUYZMnEnfvy/tMxoDEpqD9oGquhm52t1xwDjIgLE/EDFXvFE5X5GTFzpBi0kWPVRySvKVv1plntHhg6GJrWA8ErT5YR4eN04OOUqFn6YkCt691IsvkS8lGa2XoT9sMQMAQMgc8AAaNwfAag2yUNAUPg00HAoXBwUN1GcJqp/MCBfUeqzgzwowZ0n8B+oCF4KEeXlVomg02o+LaxpotkFVmgKm4UNOVposzKbiKoENmQdaMcWymcCymJR4m8JlS5L0+4RhJAg8hG9TUGlIu8xjwkuhvlpr53aJJN5Qo212kzZOTKWoqlsDlPQrxD1O2PKhTHILHHyi8HJCbA6bC6pUIl4SZHz1CuMmkWCWer1eRrM7EdBfoGk3pWxKlmMTR8xAfXoytiXFCcBPkGq4FJMirPrPKyL0xW23HXfBlohuLHZbGXg4c9QDJxn1TdGIXBgf5eAcpppmsgDVRqkNQXw2hlBHSzIzHokpSOpJD+GDjZDIrLcCDYISnVB9TRsR1SgPF+CdIJrIeEDAfe9aChhICeUqH45jZmQRO6Q6vo5HBzsOPW4g2acP/2l781HWh9ivbDEDAE3AUBq0C7y5OwfhgChsAlQ4COd6Qe1DTWqs10iE+EtMM58MEB30BV11uGhY7UgXKkMawFRaMBg+F2o6JLM5U00DQghyHRvrFK3egTmAQnQFAaAvtLdgNtrj3UZfAY3AMPwUSFFISV2UuUspAKZ8I9Jdvlivhr5RUYpjCRdyrBrlMmuq2QcYvz7qUDHFNwrhV5S2V/6S6VwmtorVdzF1qL04Xwz8d+J3th6kKHRKcC/fTxxzQJ/vPR3ymOruenFfjC069CwWOfVrnfSn/l7L6P6r5vnX5FrbRL60tUEYMOglUYMLgC91HXVqsDFZ878WeYovjJkTIkxBiI+cyJx9SlcS90tZnYH0LFmU6ClMKj5B2VNlbkLpGCunxUyw/KqLAxktGQjuR5qJqz3N73XmhZN8itfe6EGkeFQO0OqiCnZS+k7Mjr3gSpvVlxV0JLO+SSfS7sxIaAIWAIXCgCVoG+UOTsOEPAEHB7BFiBvuLu2ai2Bsnesh0SGxgHQ5JiJLLtMh7KFNvAWaaKxgFoI9OQ5JZ+d2DiKTf1uUPq2mtBMxgEZYsEHUzXyfqsRxuqwylyB/WiK/eCftAfFegSGRs1HlrS8ThHp4wOHw+6yBFQQvpJEXjCg8AlpsIFDVI4wHAYpOhY7WXVVxNHHJMNm2068Z2qOyYzYEySjyr43cnzVLOaNtk0HZkWO0u5zDf0uU3m9rpOekONg7xmpwLNRJfGLKxmJwcPRAV4hPKLqQByvDpVtaJTyg/KrF6XKy0kHsd24h+dBztwb97ggnt7eauWM6vSXD8a95WJpHYA6Bb17XXqLkjr70BoRPOFhNX8QFSlqYFdAtpGuG+UniMHnGlWwwNAa+kDq/N+wCnMPwyUjSFSC21nXwyIpHZ1OBwewzGYkesqWsqkAIMmE1Fpr8KgyQcHfl3dEvkhs0GEbv+rZh00BL5wCFgF+gv3yO2GDYEvFgKsYB6tOqyqEkcrjkA5A4kutJ5ZIa2Gocpu2EkHQtEiB0nsG5BiW5P/HqTs3oFpyTHl3+5FFXg/5Nw2F26QJZlvyGQ4E65DlXUAlDDywAmmA98y6BxXNJXLcegnbwVdYx8S8nxUXlmR3lKwHlXZ1fL8ySeU7vHUsT+iwt0gzxx/XGXfMmvSJTl0oKRCozkfFVxWkDfjmOew/5ai9bI0501Yhq8GDWSDVp1p/+1Ul1l9dirQWwrXIzGukVMYEMn2p9Rfqz70grQXpa2tDRbZbyCxT5Gt+RuVzpIPzec9JTtVa3pRxms6oJKyc34e/rKhaI1e+830+XquU5UnZF/JbvS3XlIxmLIFyf5CcKE5cHAzeNP7ynaquQv7eKh0n76sUMeaWASDkpJRc0rGhE3EC8tmmZtwHWT0jshRVOdpUrM2bxUGFmbIwbJ9avPN+6HyR2N7g17bfhgChoAh4I4IWAXaHZ+K9ckQMAR6BAFWoH/wrz9U7WQakAyE5jGrrp6oAJOvy6rzVwZ+AzzcMthxD5emzkbQFPzVkbACFIYH+j8s9/SfpyoYlHvj4EIfVGmDUNEubi5Uveg0OPVNxuC9IiyTt9w/bKAO3qOWNF3+qPbByvVXBnxL6QhFTQVaWWXFlxVaKmxwAF8ADFjoYvj1Id+BDF683DNgHmy4o3VKbWnaec+AnJwvVEQc/jSrz04Fmg6LrLInoXLcC06KvBcO5vPy8ELF11duRlWd12ruRGA6O/4qJNSH9Jo0M4nEtdgftecG/7kUAwmJD2kbMXA9TKs9DkrFFVqtJld5BExOONivFdrVtOEOhTpIOKrsA8MG4ZzhOpiQ95EA9RG6CQ6FjXkE1g8JHSFV4KLnQIO7FlV+mszweRA3Xmc6Ku20QB8XPUn7zg+CVaB75NfBTmIIGAI9iIDJ2PUgmHYqQ8AQcE8EPJAJjod7H6u7Xx/0XVR1FyKRGwodYn95DVXnaNAImGCTc7sw81W4DkaoAUozuMNFSEKLGwt1QF5pYzHcC3+AKvW78rUh30XF+iWlVrByOyV2uryRNV+uSrxBFSSQp4MY0Q5jkI3y/ZE/lZ8e/KH8fNyjWN4sN/a+Hdbbb6uZyRFYbBdAbzq/Jk8aOxsgo3cQVuCpkMg7LmlwG+QgwLV5K+SBQV9H1fdVubP/A1qB/nL/+7X63IhqNl8KlqLC/F9jfiWPp/xWzWJolz0perrsAVealIlM8MBza3OQPDerIcoBqI+kVR0HdYOyfqukDbSW91F9D4PqBi3FGzDILw2W4nRfTPNLkyOokL+DSvuS7DegIR2lhipX9bpBNqECfVvfO6W4vkgKQFkZETYKtI80mRt/vbxR8qJSUf57/7+B8pEIg5ZnpBw2329nL5Cp0ZdJeVMZWS9I+Pup0smUqMvkLyf+gPv4Jar/zTrA0T0/UdYrQ8AQ+KIjgPqCNUPAEDAE/jkRcKy8yTV+H0lvgGegJsRtqJqSm1sH7m2Yb6SUNBfIrb3uAq95t9IsboUJyD4MjosAR3cAKr/PnXgCVte3wvb7rzIBZikBPgFI8JpQtR6GZHmbUg/2VexS6+wSqFJQ0u6OvvdBj7kEvOt4yOH5qboE7b5pa81BcgVIzO/u/yCqt02o9HqIv6e/ZIASMQgKGpSqoyU3udIceOjp4alUixaoY7BK7NpOIskdhJcBaloz2V1w+m/KjebAwYlRU6ElXQaJuVM6GJEGKTRbaULFmJzqA2V7FA9WmZn4bypaC5m+cRgQeEDNV6owONAT/6bFzYKz4TIZBbm5VcDRG/bh6TUn0dehMN2GkQqy4GDvYNWfJjfbB9X1WQlz5SQoLeSYL858XZjo+yGR50sFbdFbkMhTzYSKG+RCc6AkudN82eH/AtwBScFYVKTZgINZebs+dJs3BAyBzxwBo3B85o/AOmAIGAKXCgFHxo5JJ+XhHjn4EySz/rKtdKMmakwy86AFHeufoBbehaBXvJvztia+L6U9rfrHi7Nfx2C/cgwILJZVee8ozWBd/kpUsIdpUjkLhiasyo6KHAfL6sUYWDde3s1dDI7vYdlVsg3nWwgpuv7y+ukXNbH9Y+qvpFdwH+E5qGaxOOsNJPZ+8mr634QcbdId1oMXPCpqnLwO/jJpILTY5qC87VC3IH2DHOhhoFAsQ19fw3mpIvK7I/+rMnPPw8qb97uzaJsOFqSayImaYyoJV4JKelljiZTWF8NZMEZ+l/IzDG6MAhf5FaVSPHv8CVR9faH5/JZqTS9D3+taasHl3qf944DCd3IXghLTR9bnv6+Ulb3gUY+JnCD7UOmm7jSx2g3lkXj/RPlt6v+KL+7tRbx4BPoEAZMU7eMhVN2HRYwQqn3Ut9QhCfdSLvUouBC+m7sISfxYdUQkj5qUFaNwXKrfEDuvIWAIXCgCVoG+UOTsOEPAEHB7BJwKNI1K0lGh5SA/8nWpnEErbFZNWfFkdZSV1hZplavjb5Dq9kpphqZztD8qoHDaO1GbqvSOdaA6TIEGMw1MfLx9ZHz4ZFmY84pMi54lu8u2Q7ViApLvIpiPREoOpO5IrfhSv3vhtFempiSenp6qm0y1D8rjsdrc3tGOamyLJshUv2D1eUfJFnCUr0TyvUh1mdOhfNGJfo6ASQnVPJzGYzcXr5M54DOfqD4qw8C33ogBgFdAizqz9rRK3oV6h2p1+tpet8ihSgzUQ+WZVet6SPWVgJJybe+b9OXhalSgN0AXe2bsFTjXMfCYQ0DniJDnT/0Zlewp4FfvVBUOVthptU36RUJAog5cJA87CcoffVHVL2koktKWIlBRjqhWdm+okdS21qKiHQcpwHit9schuS6D+yDvi9bdHIBJPnSf4L5S21yjyfZIvCiMiBijt2oVaOeJ29QQMATcBQGrQLvLk7B+GAKGQI8j4FSgOSBuD6gWj6f+VpUpdiJBZSW2CtQOVkWDkEjT6jsMg9zeg3Yxbbr/DLUMJndPHv+9RIBycBi0hieP/UEl6t4GT5rUiKehhdzc1iSrC9/TAX9Hyg+BzjFLXst4QXqD10t6B01UMurS5dmTj+mguIXQXEYujOr1UpVrY2IahSpwRkUaqrWolPuFyFpUp0cieXw5/Xm5BYP/Xkl/EbJ1vWU5Kty9QJE4AYUQUiVOwqGQltmsWv/68P/IjNg5UNhYi4p6HO71N+Ajj5GlqCaz+kuNZiqQHAbHmpzqHGhY7y7ZodJ6i7Nek6no9xOpj0oh+Ngvnvorzn1cnj31mLogZtVlIKnfLKNRaX4NvO8vJ98nb2cukMvjr1HOOCkXq3Pf031Zsec8+0ct6xCvUKVy8CVjZd67Mi5qoromBsC0JqvmNJL1VB2weAia1nf1fUCeTXtSvjH0uzpo0vlAWAXaQcKmhoAh4C4IWALtLk/C+mEIGAI9joCTQJNHPDJsLLi3UahEn5CZ8VdIuFcklB8Gg9oRKomopGY3ZIOeESt9YZBC7vF1CbchCewjk6Kmo18ewgFzfZAU3onBe6GwBOc5WLWmwsWQELj9wWGPCWobqth9QdkIgypFH7gI+mKQ3iBcZ2bsleAFX6l24jf1u10CPYNUZ9lP/LUC7ecbIHVNNRIXnKDcZOpU59RmyoSYKaicpyonmM6H5E93tMPVLygRA/A81EmRUnrVcAfkQEYU26F77a9V9Slxl4EC4Q+KxXgk1fGqoEEXwIyGNLmu963SgpeGyTHT1SlwXMxk8KELpTeqwOSMx0FBg6oilJSjYkcYLM77oJo8NGyEXIOq9ajwCejbZImDu6C3lw+qzVmKD5epPT0ALoY0nekbmoREfrTUd9ShWl2l+tEd6Df5zQEeQarNHR/QG06OvSUUWtHkbY+Lnvihz4Il0B+CwxYMAUPADRAwFQ43eAjWBUPAELi0CFTDmOOvp/8EGsIupLwesgV6xZ6gZkQ0RSKJC0ZiVwnqRAvc+KqgEV2lfOCtZeslvi4elIi1aqdN3nRBfa54gIaxvmiVjIlgUCUAAEAASURBVG2ZqBzmytZyyfXMkeGgT5xqOK4D6/aX75KbQdOgVnJfVKJTwYfOBtc6vjxBToKP3C8kSakXU+NnInnNxfWofHEK7ntrpE7uVJk50jpOItmnzjIrvO1QyZgQO0XNVBy0ogOinVnwqntr4t8M+TrMQFYuQqkjnUibh8DMhTSWNzNflmK/QiThYaq8EeoVJlmwHGeFnpX346Bd0DacSX9q1UG5vtetMHOpUuk+VooTYb6yB1QVJvXLc5aAhnGFLAdn2QcJdA740eXNRfpyAd6LXAkayer8FXJ/9EOoPC8DPSNZWqGsQUv1qqYKCQZFpAV0lXCofrR0NkP1o1Exo7U6dbJpq27NEDAEDAF3RcCMVNz1yVi/DAFDoMcQIA93auxMcJVnqpLEzOjLQZUIl6mRszSxDfaCMkVrI6gUMUKOLwfS9UZVNAZUiBnRc2QQTFNmoYLcGxXV1nbwlaEywUosrb85DfQKhAxcmwyC014aEuQo2H4fKTskQ4KHqr4zHfsGYhul9FiN7RucBP5wAvjSxVIMzjAVNFiJpj14GKrbp6vTYIe9WSrBDWYySTk7Jp7PHH1M+cTdGalQHo5J8sqcpeA316ryxiDYZudBuu4YTEtehpU47+c4JPJOwGwlKXAAqCCpGBxZCMm8ExgsWCN5TbkyLnIiKCytqKYngiteKv2DBqLKnChjwfe+te9dMjVqtlpus5JPlZE68JuHQbpuWOgo5YdTEWRi5HTlWScCw0ooefD4MO8wvAR0QL5uJqgyEXJj4h2SHDBQroSr4tyEG2UcKtpp6AcVO1IqD/TYs7cTGQKGgCFwKRAwCselQNXOaQgYAm6BACkcDzz0gErScSDfrtLNqIQmgZ6QgMS0Xs0/WKFtgrlIG5JGD8jFDUeCW91WpYP6aJxS3V4lnpBtO1y5X2XtKFEXggGIVLGgScgViddCRSMI4mxtoFFUYrBcb6nB8ckh/SWt7qRMh3TdrrIt0iegHwYjHlUKx0hYX5NjTFm3htY6rfLSUOR4zVEM8putnOVr+9yEfUPk6t436EBCqm5Mi5+lxibdGanQAjsN0nJMWClJRx53P/QhEvxqVr1Z7c2A6kUtLLkxIlFKWgqlBgP2/FHdpnU2758cZ1qW03K7BZjwOuRvN+IYKm9kgzdNV0dWqZmcH69JwfljpA3nHh05FuYyRXJVwvWyp2KH0kVqIBPIgYIlDSW6zJeBYmhFl0O6bi9k/1oxbJMmNLzOQeB7Y9/bJK8xR+28acLiNKNwOEjY1BAwBNwFAatAu8uTsH4YAobAJUHAcde7EhbSQRjQRsUHmoIUwMqaAwlrwR2OgQvfEQyu68A/2k9HQeniYOleVEzbpK6xRivKHGiYicF07dhnPay5AzDgj2YnrOruKtuqHGOem9rJNThnTm2WxPrFQ65uFWy/hyIJbdIKcwYSStpYH0P1l4MTt6LSTEWL1zNelvSqk/IWaBaUy1ua/abkoo+sKq8AXYLNqTw7U1cr718f/in27ZAjsA8nzWJdwUroPTdhIN8y7dseDBg8BTfBWth9H6k8qH1MrT7MXBqa1Hkqw3cEZjLzBnxbpejmxF0NfEolCRVoELzx8rFVClFxz4K6x5y4q7TCPAm25mWNRbBJ748k/bhqSO8HTSbIM0RfKkrritWdsASJNXna6XUn5HvD/wva1u3y32N+oXrRfElZnr0IeByW0zVpoL28rBVq3q81Q8AQMATcFQGrQLvrk7F+GQKGwEUj4AwibAb3thZW16wY0xKbxiB+Pv4YDHcjVCyyIdkWClm7ECSTnVppJe93SPhwreZGgmccH5SgVeKrel2vtt+zMYCQus+NoH10IKUugJ7zEFA5SOOgFF1sYKyqclTCDnw8LKmPVafImKjxoGqcVIe+EzWpcN/rrXSRBsi3cdAd5ek4eO4uOA1OjJ6KAYGXyVjI4nFA40hUd9mcyrMzdbXyTq06Irf1u0uT4et63aw0E1qBs0+893pUuv2VatKKwZIxqG6H6QBEDkYkxaUVPORBsOYugQQdk132j9biOXhpIKWjsb1BTWY4eLIFy5S/ox337f3ukSNVB7Sf1LVm1ZnW6KSApIMTTlvxBkjmVeDFgvSQYFTv6Xo4A5X26/rcojrPE2OmSW59tnwp+W5wsjPVIp337TSrQDtI2NQQMATcBQGrQLvLk7B+GAKGwCVDgE57pGxQ0i214jCk2F6ATnImlt+QNYUroMxxEpXi92Hn4Snvo/pLp7wNsOeO8Y2TfSW7QbNoVFUL8oc7OjpkS+FmXf9G5ktaTS5pKAbVIQ00jwNKb6ARyQpwkdNAmThYehCmK8NlM843AAnqTlRyadyyNPstVF1TMMDwiGwuWKsV3h0475PH/ygL0v+mFWKn0vwWpO/onrgg7QXlHHM96RCsQK+GJB1NW06ib1m1GahAH0AlWmRjwRrVmH4V3Oel2W+jQnxC0lCBpiIJJfmoMJKHhPey2MuVE/1A/6+jP8fAX54m72UvlfWF78syHLe3dIcOdMypy4L5yUjZhPMmQV1kMSrk5Ie/h/scEDRIKhrK1eGwurkSLxQFUAIJQMW6SAci5kLh5N7kebIW54SQiByEZN0WDI58/OijissvD/0E1fYseSXtOeC1TzWqL9mHwU5sCBgChkAPIPD3V/weOJmdwhAwBAwBd0LAMVLprk8NrQ1K2fhjyi/UkpvcYR+4/ZHiQN4wpetI4Qj1iUDl9UxVdiw4wttBuZgVN1dtrxuhHEHFifr2evnR8P8n20s3qd7ytYk3y47SLapm0Q/V5d1l2yTCO1oKmnNVO3lr8XpI5/VB1TUTzOl2uSbhJjmOKjWtuGmGkg1lDFbKyzCILxpc633Qio72j4XqR57yoVnl3lO6XSZFT5eFWQvkruQHYLqyGNJ0N2tCSv7wycrjarG9E/rNHMyXgIpyLsxdWDmnsyB1pqkNzQGOTaguT465TNaC9hEE9QvadtOmm9cL8gqCdvMkNXjRwYUYEEjuc0JALwzAzIDSR7lWz2lF3tzRJMNh9rIQGtG39vuyUkVYWe/l3xd851YpBd2DVXJai18WPwcJdr4m+9StXpX/jtzU90uqtf3Q4H9BP4I+eGyoRpuV9wdo2IwhYAi4AwJG4XCHp2B9MAQMgUuCgEPhcE7Oyi2rwHTcez39JSlrKQX3+CXQCLxVli0GnGUan1Bx49XTz8kEUCneA/94ctQMyajFYLq2Zgwu9JLdxTugixyq+yZhoN72os1qTEK+M01HViABTak4hGr0XnUkHBgyDIPvDqmU29q891S5g8kqTVFW5r4DCWlPNUChIgcdBDcVrcc+w+VnB3+EhHmm/PX4Y6BxjJFlmW9KNLSqNxesgxOiL4xIMrWSS+3kp489JrMT5sovD/23GrO8cOop1YBOBd85rzFX2qEdXQ1KSXLwICEf+sGBD8tLac/IDX1uk2dOPq7a0s/AGIZmMuQiF6GKHO0bA0pIviSDB83K8wxUq2nmMix8hKzCPVLLeTcq1NTRJl+bLyCBXsH6wvDVgd9WQ5kbet8mfzz6K/DBYyHTtxa24kcltewwzpsLl8O/gAaSgf5sA1YHVKVjYcar0IKepgYvDo3DKBzOJ9imhoAh4C4IWAXaXZ6E9cMQMAR6HIHuKtCZSIQTA/uAnrBQebxPn/gTBr+NlyY4Cg6A4UkW9JopMUfZuHAkk/H+vaUKiWeQdwgoDzBbQSLIKuv+it2a6DFJbkZiPW/QN7XCS/3mGL84rW5zXybolG0Lh2xeNigWEeAlF6HyOhSV5jRIwVGjmdbaNCChfnMuDElond2Eam4NquFXw8BlNZLuCTBWKWosgJ33GPSnEtJ0KVoZ94bknhcScFaTqRedUZuGanMiJPBoWgIrclTSqZLBCjYrvvf2/6qqcgxAIs2BjPvLd+K4AFXpaALNJQ7H+nuC8oKqdByoJvVQ4GCVuU9AkipkkMPciOo91/O+vMQble52uCj6IQFuV41pKoxMiJqsBjGU+KOFOPnXHHjJyjZtxK+EekkmnAgbOxpwPX9U4FNlErjQpNlMjJmK6vq0Dz4PVoH+AAqbMQQMATdBwCrQbvIgrBuGgCHQ8wh0V4Fu7GhE4pYBe+xnodEcLM+ceFzVKlYXLFeTlZfSnsYAPG81/4gGteCdnIUwQxmg1eQzSW4njk/XQYJvIjkmn3l++tPgUZ+SRRmvqTLHZlRa95XvVb3kbUUbdQDiclh3z0ZlewdsxGnzvaZghVaZyYVmhfrljOdB+fCTzPp08LFXAgwPWGqjiozEdEn2G+KF6u66/NU6wI/V5eNIoAOQlD5/8ikMCAxVTvUIJPYbwOVmsnoaNInxoF4cgJoIlUIoPcd7j4ZG9erc5ZLVkCHPnfwzrj1UtZfpnLireKsMRkKfXo37841SVY8D4CuHgcbyLnCIDYyXRdBp5iDGNfnvyb1JD6FS/7zMiJkjeXV5eBE4KsmBA6EislQpKC/AEpwDIBdnvgZ3xmSYrizGMM0OVRmh5N5bma8ozYN86DUwXSG1Yzeq0ckhA9UqnfdFy2+rQPf874ad0RAwBC4OAatAXxx+drQhYAi4MQLdVaBJ35gSfZlymKmBfBTqFQ8N+hfZicSWKhvlkKI7Dnk3VkdrYUhCyTUOgpsSNVNCYftNS+qy5lKtSFPzeHf5NpkTe5UUNOVpQku3PraDSKBZqX43ZxF0ma9XebyZ8ZdDE7lIDlTsQYIajfOUofoaAB50s/h5BkoztJepK0d+Mg1dOFCQVturmaz2nycbIJ83GrbczZCnW4/7oLoGedI0L2kCHzvYFwoXHRDaQ5/rUSWeCKvt5tZmGRE5Gslwp/AlIRhSflQF4b3EgCtN9Q1WmqmgEYwqexOSbO7rBbOYepiksKIegheNfFA5aABDvIZBcSSalfiIUUjM96tN+tKcN2Q0zFAqWsuQ7HvpPZMi8p1hP9JE/a7+DyqFYzQ41+RW8x45oJF87CngX5NGMgsKH3Re/NHI/6eqHs5HyyrQDhI2NQQMAXdBwCrQ7vIkrB+GgCHQ4wh0rUAfLUtVjWS69j157PeSGNQbVc+TSBBDdFAeq6TPnXhCK9KstPqCZ0wrb7rx7S/fowMMaZLSjiSVme6+0p2QZQuVZ08+AZ70dFSMnwZ9opdqL9Mem4ni307+BQYkGcqh5mC9tQWrZHzkJNlYvA6GKQFagWUCvDDrVTVb2VC0WvaX7sFAwtOoKi9U+sgyVKk50G4xVEMotcd9D6I/TLY5wHBI+DBwqZfKdYm3yMuorCcHD8Rgx006AJGc4yifKHk09WdaHT8FvWY6ELZhUB8VScZHTwGd5S2ZBqfGTVAKCYMF+AEoj6TDWrwGCTptycmBXoIE+eHB35E/HHkEZi+zwG9+UWgqswYqIPthilIJMxYm6H3h1pgGxY8EDJLchgGMQ0DZeAVKIJH+kbIWHHFW1LegQk9sSKPZWrpBTlUdx8vB+0pZIXd8GnjfwZAVJDeczSrQCoP9MAQMATdCwBJoN3oY1hVDwBDoWQSYQN897y7lBvPMpyEr145/46JgV93epi5/NDOhDrMgWaNOMe25fb18ZXjoaK2k3tb3XghtdMLKeoLkN+VAwq2/eCBxjVYtZWhHe3TInJirpH/YIPHo8BBvDEgsqM/DoLxO8J4jkDD6yNeHfE9CvMIkOXQAksVj0Du+D5rQ6ToQ0Vd8xR+JdG//PtCiDgWFYgSS5VgZioF6c2Ln6sDARKhYDI4YqhQTcoYps0c6xZjw8dKB65NHzYoxE+kkcJu/lHyPDgZkUkz3wVz0OxQvCdS6HhUxQTnfg3BMqFIkApTGQVfAKkjQ0dGwAdXseFSnE6DeUQLljFFR48C/LlKnwKKmArk7+StqtjIMFWgaq4wFVYQ867kJ16qSSH1r/RnnQrwEUCaPFXy6I2bjnmclXAH1jizdTg3scZGTlTLT2FEv9w/4mkryjY+ZotrcVBthswRaYbAfhoAh4EYImA60Gz0M64ohYAj0PALNHc0qz0aObXFLgbyXt0QKkQSOiBqtfN8JsVORgA5X2TVqLcdiACEpGqsKl0kdKBzLct+QXsGoplZs0IF+pF+kQTeausXtoCBUt1RJTmMGqBQlktOUqYYji7JfB7VjuyafpIFw4OIMmLewqkrayOqC9zAgMUPqW+og/dasNIlsSMwF+wbJAQzqi8dAPupF7yzdJluLNsiKgsVI/tOR4FZJavkhJJxeSEZPqylJOWggYd4RchoV4wOgjVC2jtVcbifl4zBMTui8SE41rcaHI0Gn8UlfKIDQgbASAwS3QX7vGKgZpbgHOjFGgP+cCmdAP1SLy1pKZGzERNBZqjXx5YDCDRhgyQGVrILTbnwd+NwjwkcpNSTSP0or7hzQSCUPSvt1kD6SvxyGNL104GGkfwSq9EuA/3DZjv7SqIaKJJTUGxIxHBzrUaoj3fOfBjujIWAIGAI9g4Al0D2Do53FEDAE3BSBaL8Y5eOSh1wHTi/VJ3aXbJc1Oe/Jy6eel7fTX1fOLyXu/L394UyYKV8Z+A1UgEeD5xuDZNUHUm3bZUTYGBiKZCFRHKsW1NRVpoGJai6DgnCs+ggUKbxkDCq8t/e9B9XhCSrF5ucRqFXtH+75pryf/64UNxXL7LgrlaM8BhXvcJ9wVadgNbgM/OthoSPBky6Uy+IuB4XBA4n3HCTIkVLSXKjJ8ICwIVIJFY5IqHnkNuSAXjFAtZ1Hh46RuYnXQY0jG3zlPJWXK8eLAJNX0kpKcN2hSJ5TwO8ej6pvBZJpJtXh0GluhQJJ/5AhqDJDHSR0hLoPDsLAxgo4ClL2zxP3FQ+JP0rrsbpMPez8+nwZHDpMilGZvgcmKaegJBICXvXzJ54UmqmUNhZDbaMeSiaROgAzEpxvSvaRtrEGgyS/M/THeDnYiEpziJq81DTX6DEdoMe0trfKCQxItGYIGAKGgLsiYBQOd30y1i9DwBC4aARI4bjx/uvBe96hg/KuSbxRKRz3Dpgn0+JnwS57hkyOnaYD1qgsQWvuGlRaWQFmtfhKJKQTIqeKl5enKllgeB6qtIWQYhum+sXDUHUtBOWjf/BgHWQXCMWIYCSElJvjAL506ClHoSIbjEF47aBa0ETEBwof5CFT6o7HeoOmEANtZ9qHJwUlSSoS8TmJV2klOAqGLtSVrm6r1AF3VAdpxADCYGgts5+UgxuFQYW0wSbnmpVmX8jaUUaOPBMP0FLiUVH3hoLHCOhIc6DgWCT420o26EDEoqZ8dTykzXYE6CZReGGgCshkGLScqj0GY5ZbVM2D2KRAx5qYMKlmC4XNN5gsGNQ4Tsqhpz0e0nuU9LsOutI0WuEx1HFmFbsTfeE9xvrHq9nKVHCcaWs+FXblHER5ZcLVEod+9kYVmhxxVtVZ0T4NZRPi9Itf/KIQl3qO17VmCBgChoA7IGAVaHd4CtYHQ8AQuGQI9IJlNSuzlHj7Q8ovNcn8U8qv5XeHf640DMcum9N2DK1bkvUmkuRiHXCXXn1SluctgrzcGbWOisYySKzBiAVScbGoyHLAX7xfb9kHTeheqPLm1GSresdJVKQL6wtVF5k24KGoMtejwrq9ZJOapLDyuzTnLVBJ8mUnnA2rm6qh21yBwXWbVPlic/561aCm2Qor3Pl12eAKT1K6yICQQZpYjgb/mS6B20s2qhU5peDIuT5YuRec7iQdkDcWyXU9lDzuZoW46oRW0UnzqEClOym4P2ghJ2UME3Ccf27CDdq/sdDEPgjJO0rkHa88qprTfh4BWhX2h170KQwQRGYM85iNqOhXw7J8GSrogTr4kgod7Ed1U420tDfDUGapKo1sL9okCf695E1Yn49CvxfASp0vAqzss0p9GLSUbaCqbMLAyhTYoQfhhYNOjnRmpKKHNUPAEDAE3A0B+8vkbk/E+mMIGAI9hoCjwkG5NFaPR6IqGgiL6Lv6PwB5uGmanLJSysYpebuBPkHKxfWDAkcfVIQHwFK7tr0KCeZ1UtNeDZm7EsnC4LgYDOJrajtTseagP5qIcN96DIyLDozF4L8rkZhmykRUuHNg2T0SA/GuxkC6GOzbD3Jwd8J+uxcMXaL8o2VryXopaSlUu+yMujRVB0mpOghe9p1qsnILpsehnDEsfCTUMi7T6rMf6CZUtGBVOgf86akYMFiGKvRVvW5SMxYOJGTFeRCoGZGwA49F7IVaxpSYGcp95r2x+h3oE6jGK6xy01Amq+40lDkmQ96uRQaHD0Eh20MGhA8GRzpFrbZJa7mxz+16v9f1uUUHM3Ig4RAMemSCTSlAHwyknIJ+kkIyEOY0Mag8Uz1keuxsVf+g/F1/aD3zXD5ePtIAacASVPapzNEbKh5BvoFyZ9IDeFaB+mxsEKHCYD8MAUPAjRCwCrQbPQzriiFgCFwaBCiHVgquLk1T6OC3C5SOBWkv6MVcK9BckY5KbSqS113F2yDhthu83SWgO7RAxu0tOVV5XJPVbCTGrBhvgsRdGNQ11hWuVC3lxVmvKQ/4ZOUx2Va4EfvmyM6iLRj8VyFbCzdAYu4ZWG7/CQYiC+Qne/8VVtZPylPH/wTFjg51DiSfeFjYKMjY7ZKrEm5U0xLyjJ86/n864HFF3jJ1CNxXtguqG15IlHNUD3ow+Morse26XrfKWxmvyOz4K2FVPh+ScsmodC+Uo5Cr+13Kz6EEEiqdUAdhVXxG7Byt8s6MvULd//r6J6k5SohPGCzCM4Rc5NqmOtAxjgrNVFIqDsqLaX/FPTwH85YnMQhwKSrNVfLU0f/DIMkMVNK36sBDDnpcm7NSLdC3o7ruA5UR9olGMM/hOFp9byiAjF19rizPXqR86HQohRzC+UnbOALXwsuh5sGXHmuGgCFgCLgrAmak4q5PxvplCBgCF41Ad0YqzklpqHJFwjXO4gfTHKhrZKIKSy4xK7h9UallsjoAPOf1Re+Dr3ut0i9IpahoKpOTsOOeCJ50Tn2GqmGwSk23vxaYotSBo/zlpPt1EGFCQC8MuCsA1xnbUXlNrTgCreUTqGI3IEFvRfW4WI1NaI5yGZLbLFStB4IuklmXLtf2uhnW4qsxeG+SHAa9Yk7cVbKuaBUqx721D35efqr5fLzqKKglCTrgsBp61V6dnkhE2zEY0RcqF71BHAF3GQkyZeXIOSZNo62zVRPx2IA4qWuphfNfgDoPUut6XPRE1Z7+3ogfy+Opj8p3h/+HPHHsd6hE364vIuRWF2PAYyTuh/fLSjMl9VblLdeqtieGH5KnTR60p6enUlDowrgDiXWIbygUQCoU28SAROheZ6sxi9JdcMx1vW/G/wj46XMxI5UPPp42YwgYAm6CgFE43ORBWDcMAUOg5xFwKBzOmVltHo4qZw44v7SdHhkxVriO9A1Oh4QOV9e8cdA13ggJOLr7HYRTXjYSag5u4yC9vaU7UJVepvSEd7Lehu6zj6zCMs1LluS8qQoVK/PfkdFh45EsV8JsZYcOivvL8d+D99soj6f8FjJyB+U92Fp7oTLORJktB1Xt+tY6tcBekv2mjI+YAsOTFCSifVDpXqMD+3596KcyMXqamqX4IrkM8goBb3mL3NHvXjVxIR3kVfCLeT/v5SzFwMBI2QWnxEKocqRhYGEdzn8QA/12FG2WiVFTtcJ9TZ+b1TL8nuSvyqaCNeBRR8n7ee9iMOFpOYlqPE1RTsNshnxsVpGXom839b1DHjnwY1XoWJ6zRAcwZmHA5Ab0sxDqHOtgmEKzlT+kPCL39/+6/N+xX8uc+KvkDVTFmXTvAiYtkO9rb2tX9ZIQDEhktX9e/2/KC2l/ke+N+IlqcTvPzSgcDhI2NQQMAXdBwCrQ7vIkrB+GgCHQ4wh0rUBT55nSc2OiJui1mjCQjZVmUjxIh6DpyaGy/TAcCVa9Zsq/cRBiE2TeyOFlVTYIHGlSKMZCgo6DCHvBbCQNg/HIsmb19FTNMYi+eUsgbLWZwFI27wgGxn0JhiwlzUVIio9JVsNpaYAGNK/DAXitMCGhYgUHzdGquxh84P0lu0A12YYqrK88NPB78vzpJ+TKuGshYVem12nA4DtytttxTw1wOCyqL4AxS7jaf1Mto7d/b8lryj17H32h7RyOSnGUStJxYOI6JsToZwQcAk8j+b0OiTRpGExw2W8OpJwTf7W8nb1AqF7yRsb8M30DzaRfcLLK1k2A8sY2DGIkDWQ/9LETgQW1szkIsBF98oEEII1rskDxCPeNUJ1pf6pyAP0WWIiH+UQgqa+RkZAGpMTgsMiRklp5RL6UdPeHPgtWgf4QHLZgCBgCboCAVaDd4CFYFwwBQ+DSIOBage6EHvITR3+npiaFMPjYVrxFrbRfOPEXaUYy9+ejsPZGAjj/9DPq2Lc06y2lXrybswjUh04knKtkQcYLkIGbJO9lL9HBhr898r9KhfgrOMpMAF/PeEm5w/sr92gFOqXyIBjAvmrH/WLa05qE/zH15/JA8tflNVSK+4MGsib/PQxSrNeE9FgF+dlb1RqciiDUSY5Gsrs4+zW5qc+X5JXTzwmTViaZJY0lmtAvz1mMqvpoYdU6Ecn+9sLNEuwXIu/kLtLK9x5Ue6kNvSz7behde2givCjrdR1A+GbGy0q9WI9qOxPft7MWKGf57cxXUSFuhV72VqhjbFKdbCbQHAT45NE/YADmdHnz9MsYQBgnm2H/TQm9wto8fVGge+H7ee/ItOhZ8n9HfgVqSSz42UtBhUmW1ahs0/p8Q/5qVJj9VKu6rr1OKhrL1U6cLxE0XEkOGaBmLuZEeGl+L+yshoAhcPEIWAX64jG0MxgChoCbIsAK9IqtyzUZoz03K8gc+Hc5KqvVcPUL8w/X6jO7vzx7sZqXbCxcK7f0u0NyarMgM5enlt5lraWSiIouk+hZUNdYCqm7Owc8IBuRCHJ5b+lOrQqTD1yOfWvBJSZ/lwPlQr3DlP87LRrax/Wn5PZ+98gW6DCPj5oskTAZqYTpSCMS6KLGQlWiOIrkOAqmI2m1x0HnGCaHK/fLzX2+rLbdPlAGqYFedCDk697NfVspHOQzU9WjsaVRfHx8pbAuX+KC4qQGUnId+MeKMrnJbeBZUzWDyXQyFDBYGa5tqZGogGh5Lf1FNWw5Adm6EL9QifKJkQJUr6fHzJYX059SwxTak4+OhkpH9WkZEz1BVTkmRE+RhaC+zBv0TU3Qx4P6Qjtw0mOoEsJ7GRs1HhJ6JyURbo6eeBWJhhoIeeb3D3gIOtj5eB7rUJ2/R+kv1Oamyc03YX3uKl9nFWg3/QWzbhkCX2AEvL/A9263bggYAl8ABOjYtwN20S0dLeIn/lIFB75dsMgmrYDJHHnHrHy+By4vqRCna07J7NYrZRcSudigWCSwB6GmkSm39b1LK8jNHY2SgYF9RysPgW/8IqrHdbIs8y2lR5DGMB0mIQehJBGDgXXNuGZLWwuSyAny6LGfQVnjBvnqtjtUEm9+2jPy78P/S/6Y+ksZFjJCGjob0Kd0ldZbXblChsLSejXsxydBUu5tqHZ4JHfIfChg3IZkk1rJvA+6I6aCl52E6i5VMS5PvBp23rslvilR0qtPSBIq3Fno68iwcbIble0DVXugRlICObwRGLAYJynlR2R6/EzZW7YT/Y+EmsgqtTVvbG1CAp0nBXV5shaugf2DBqOK/A7k8KJlFSrE0Th2d/F2pY9wIOUbp+er++DrkNpr7GiQTNiO046bxip0UzwMWsxNgXdAB/pluS7xZvT/sA6wDISJSgYk8B6r+40UYxBlQwcq8aC4lILCwepzsHfIBwMJvwAfVbtFQ8AQ+BwhYAn05+hhWVcNAUPgkyPARGx2/Fw98K30V6W+oxbGKF5S01wNreLpqhgxI2629A7up1bVxeASH8LAQXKNh/oMF5qD8L/qGprrocUMLeR+t6u9Ny29x0A3OQID4JJCklXlApZ7Oh0Ey+vSpiIJ8gxRasRUXGdOwlXQTm6TH8U8IrVQyKBcXRg40zf3vgPVVqpldECrOQHKG4NkSPBwGRU9FoPsOqW0pRgqFv5YP1weGvBtyUdiG49qOC2yWUWeCsWONpx3BqrFdPsbBafB5ND+0tbaqkksFT9omhICXvQ1vW9SVY48DKIMA/c5F1V20laoZ02HQXKiWaUPxz0xmS2EasgM0DbIESetIhTKGbH+cepaWEO1ENiNHyzbpw6Fp2vTNPmPwz0QB/aDNJDxkVOQDPvLt4d+X9rb2+XGfrdJKAY4ToAO9y5QRIjz9X0fkndBRekd0Bfc8AbQU2g8KBIG3nSfoH46bz8MAUPAEHAnBIwD7U5Pw/piCBgCPYqAw4FmcnoCtAJKp/lg0ODQsJGw1m5Xuboi0AiYYJJyQCc/cnVLkPwyGU1BlZnGI3vLd6IiPAK0ihNCObrcuhw1BNlbshNV63odgMhksQHV19qWathT+6k7YElLkdSCclHTViOjwsbKkeqDEgBXQ9IT3oEKx0nYZWfUnZI8yOVNAKVjPxwNh4eNlp3lWzDgsATVcKhgwM66FOYt6wpXqKtgIxLb4aGj5WTdURkXMVE506Ngp727fIdSL1gtJ5+5EUkxE+B02Ibn4x5JYTkBi20OAPT08lI3w3gMkqR6SDpstUdEjAE+YaCIVEpcYIJad9+ZfB+q6fthFz4WduJV2HcQ7qVSBwF2IhmmRnQ53BkrYQUeCEm8bNiA9wWdhIoiTR1Neg0/bz9UmU/RvBCDJVuUL83BjDwmEdJ6TLwrmsuBYx1MZWKkA8/l9qR7lFvOgYf83wFT4ejRXws7mSFgCPQAAmak0gMg2ikMAUPAvRFgBXUIqsLk1za0NoCeUCBBHkFaQS5ozFVzlPXgM5PW8duUn8keJKPr81ZD2zkbNIT90htVUNpdZ6Nie7w6Bev2aGKaXndcBxOyGktnvRCYhAwJGwEXvw65Ajzr6xJvhTnIWLmz3wOgUmRKH/++4C4vglJGPQxN2pEsj1ItZhqI1LXUy7jwiXA7hBYzOM4DoAHN5Hlm/BXQiW6Ur4MXzAR0TPgE2Qi5OB/8O1F9TCJ8ovWeqB8d6BukgxlpvlKHpH0qkn/qPs/tda06B7ICvBj87fTKNFUWWQO95gPleySvDmodUAPZA2vtINAm9sPue07cXJXrwwhCVfg4XH4A/WjCAMbDQhvxVYXLcUwAXh4yUXmOU4pMFPSvqWudGNBHpoLzPTB4qDoKJsHQJQAOkKw4R0B5YxlMaXiu4voi5Vf3hfsgK9+tMKw5UXEUmtdrZGvxRilrKnXvD5b1zhAwBL6wCFgF+gv76O3GDYF/fgScCjTvlJXMSaANsKpZhMoslTeYaNI05f6BD6PiGS9zE6/TSior0uNjJitVYRZc/TLBTR4OG+0C6CmHeIdCZq6AZ4QVd2911hsKTnE97KiHwBEwuzFbhoYO1cF7KdWHlPKwpvA9PTa16rDqRlMFZBg4wkzer+9zGyrDR/X6HDBIw5GS+kJUrmtQNfbnZaQfquJM3L86+F9QLT6uVd6aNhquzJaU6gN6b5SEa4H9dhj619TZKPGolBdCDo9V5jRUoaeBm51dn4Xre8sPRv23nMQ1meyTD82K+5jICcoJr2ytAO96KirR1TI17jKtNlOvmnJ6Le3NSNZRcYfDYrhPFOgkMJqBMQoNY4ZE4N5hJjMpeoZsK90o48D7zkY1nPrPnl6eMgs0mlZQTYj7eAw+3A11ENJr+oQkSX9UtstB5fju8B9LZECUGtywUk7bdTarQCsM9sMQMATcCAGrQLvRw7CuGAKGwKVFgGYpMeDwNkLXeRsk4rahynkMA98o2/b7I4+gOvu6GpyQi7yvdI9Wgo/DMZBqGjth7b0DttynQOPYhUottZZPY4DeJEi6HcU+HCDIAXxjMWBvP6yvT0Ibuqa5BuoUC1FNHqLa0VNjLgOdIgfc4TlqaBICSbeVuUtVC5p0iCoog9BJMBNV3XFwHawCzWFoyFAMZNyHRDUJffy5eMBd8C30N8YvXhpbm6UR3OxYqGzsKdkhcTg2HZSIPtj3MAYXhiKZTkHlmJXnVRgEmI3zpqNf8089KwOChsjp6jQk6rVIZrej2p6llt6zoOmcWnFIK8qHcGxK2UEWofX8HIi5q3Qr9KYjQPE4KAn+iUjsj8JmfLAcBF7kU/NcYah654DmklubLYuyX5fnIRVIJ8U3Ml6UQXjJWJz5BrjjkVrt9gTvmtVm6lmvxaDJHYVb1KnwKCzXrRkChoAh4K4IWAXaXZ+M9csQMAQuGgHXCjRPRoc+mqkMBZ0jC057dyU/qG6BDw78huoi39bvLmxvlYFhQ1ClzgPnd4CqQzC59EBlmNJ0rDZTNi7UL0ypHbTaTkIVlQoVo0BtYPW3CjzhcPCtqdYxMWYqqq5NWu2mTTbpHORj35P8FaVoUNqt0wM2LchSqf1MDrbykGG1XdZSgoq0N6q601GZjZZret2g9t0joPtcAbm85NCBUtRcCLOUAOUTV7aWK7+bfRoRPgZJcLP2yxuDJsNxfLh3OPjW2agOT4JcXYhc3/sWvR8axhCbQJ9AJMPD1EiFLwiNrY3i5e2F/qbKaMjR0ZY7wjcGfYjXAYPEgy8kraBfDA4fJjPjrkB1mYl/pdzc70sSH5Qo9/T/CjCukpv7fln7mdOQAc55sg6gnBY7E5zqKnlg0MMq4TcW/SJGVaiCT4OTIS3U2awCrTDYD0PAEHAjBKwC7UYPw7piCBgClxYBVqCrMEjudciu7SzapmYgB0r2wLL6uGwtXK+6xKcg/7avdJe8l7VEK700KGG1tQVV6+2oWjOJ3I3Bg3PirsI5toCuMQKV1Vdkbd4K+cPRX4JHvAMV3MM4x26ZHj1bTUPIbU4DX3kQqB3Pn3oSsnMDUOleiml/KYD1dWljKRLoDvCss9RgZE/ZDnCor0NlOwVV8ABcd5PaiP/0wPdx3p3y6yP/I4dK98vxylTwmU9CDzpY7bP7gE6xFsYsHKS3GvxmXwxm5D654DgfQH8Km/JB7UiA4sUi3MMOeezor+Xx1Edhsf2SuhC+Cy3s6pYqeSd7kWyCQcrqgnfR7zR1Slyc+boOoNxcvBb9Hoj7XamD/qj53IoXhM3Qc16c/YY8ffxxWQaL8wWQ+FuQ9gJ0ol9ViUBup940daKPgedMesZGWIe3t7WpDN7mgvVSi4r9kymPqgmLY6JyaT8RdnZDwBAwBC4MATNSuTDc7ChDwBD4HCDQ1crb6XJ5c5nsAiUjFKoT1HWehQFzNFgZCk7w+3DLa+9shz50jcqvkYtL7jKrvlThoMqEDxSlL4ufI1k1GTIcXOatxRsgcXdEisAlZkJdj0GCgUh8eX5Whykzx8ry/opdGDzYqXrTtAQnLzsBknRaxQbvek/ZdihejFcVC1aFqfYxEpXk1v/P3nnHaVlf6ftM732Y3pkZehGQrogIghTBXlBjTdn0bMomm2TTN5toiiXG3gVsqChIb9J7GZjee+99+F3nGPNx898v4u5k833nYwZn5n3e57nfYfc8t/e5brLNK5JvsPISdYqHhobsXBLIYGtDYAQDswcfTb311qKoOeVIylAaBmqN4BHjGwsVo5eYRD+Othf14tm47NnWhKiRDI1PaLnK8aYjlnFWekcQA65+fZAyFsXtlXQUkdseJ8eIp2gVug72K5NvsjrzhQnXmKuuue1aEHS6MHl96i1wsp+S7078D3jWGyyDva9ut7UZHqUKXUteFI2nHG5F3+2t3SX7G3ab6z8jZg74u+mmj75n6HSUT9M+fv/cZ6eAU8Ap8L+tgONA/2+/A+71nQJOgf8xBdSBnhs3X17If9Kc3+SQVNmN83ys4RAD9T4ZHzkR1/VdlvPmSw4Z3KTgFGIE3jjBJ23o3FqxUVYTN9AClSqiEGsoOLlt5N2yrXKjZIRmWcOeDp0jGFgr+0ohaCyQtSUvynfG/0ieyX1EZjF0H2iCROEfRTb5uIyOHE9xSJ5UQvhoDW+WnVVbDWP3ZvEa+ca47+MEr7NlxFxy2oUQOfSc0uFEnybfHOAdKHF+CQzVp+RHl/xaHsr5mdyQttpc3/mJi6jlflEmR+N8N+VKlV857i5oO4piFM/3Qdm7khU+WpK5OeiD8HGC4/3bxJ/J4+d+x83EAtznLZLItetiYn7rObkh9XbZVPm2DfOqV0pQmmwk6xzrGycby94mR90q6iDrjUIUxTXlnWWiJSm6KPhe+Xp5KvdRyW8+J2+Vr5Nvjft3G5avJeKhDnQYWWjNiR/EWU8PyeCa11pVuN7EeKO9ezgFnAJOgeGogHOgh+O74s7JKeAUuCgK/K0D3UI8IZc8bx+4NF2Im0gRii4Sao22FpP0wnFWnFsPrrQOcP3UX2eGjqIYRORKWv6U1xzBAt12kHfNREGUjJEJbk4jFAN8hPuGg2frIyaRIE09jVIJZUMX+TphHPt4+DEMezL0JkpZd7G0UaPtT4Y40CeYNTofssq8/kAvHOQhYzgn4EDXQOuIC0xgcJ0sMYEM5UQxlJ3cAwKuhAY/zTx3UjzSOtBkVeIaB9GMt4+3t527N26zXqdi8Rpxp7WQJdjro3Y/Hci/NOabsqduh0VN9BwHcLp31WyzxkXVSBf9lEAyMjSbyEUgxJCVFhUJ4pzjWRjUc1R3PpYlRh2iFV9X1VXxl5rvmbjSp2VB/BJZU/KC3J5xtznRVycuM0zd5KhpDNqlRvboxrHX1kaloLxNRfl0Mt/qrn/8cA70x0q4z04Bp8BwUcDd3g+Xd8Kdh1PAKfCZKqBLeg+e+jlM5CWWgdZFPV20exsus/KSD1HvvZK67m0wiG9Mv00+pP47OTDFOMe9VFtX4qq+WbZGbqBc5Amc2tFEN+q7a8HahUhJa7EsSr5GzjSclkC/AGMsn6Ch7xJquNfzHCV17KjYItdl3CQ/PfU9WU4c4wRxCS0ZiYOmoXXhN6TeJk/lPyo/mfygPJ37mNw4cjVZ4nU0AV4uL+KYT42ZIUWthTZ0n6LgJQoXu4k8cZh3mHx/0s/lpye+J4uTlpGtfk0W8Xk7r3dZwhVynmrskbjWBVSU9+A2a8lKH/SOiMAoeSrvEStHuX3PCvnBxJ/Ld498BaTfPXKm8aQNtoMM82VEN6ooYtHik0puIJSOMZfmxheU5BE2mjzzSRYqIyzb7AMiz2PI09zxEhYZla5xrvksMY9N3DA0Qz7ZJae41hPEQKajyYGGvSD6MiyO0ss5Kf1jPS71v074oQ3i2qKYSrTFPZwCTgGnwHBTwDnQw+0dcefjFHAKXDQF/taBPsuAW9iZa4t0Z5tPmWvci8sczTBKNSH11uEg34bkisSrpK2nRfx9A6Syrcwa/SrgO+sQOiFqkhQQuxgJqcNL2MMmx6xtfloocpqSEeVFq3urX/el9fA8S3zjeM6JhqOQLC6R/JbzRp04Vn/Y3OYWWvg8oU2oi32gYY+sTLuZ1yyXWfGXS11XjZE5Ir1jZERgNDGIPOn16DbsnVZzd+OU+3j4WsX2uZazVoutddy92gLI8p/GNPQY0TT8NXU3SpBfMBnnDsgZcbQrHpB5ZL/HRoyVaO84jttDrKWC1xu0KvMkbh7UoT9MqYzeaJykUOYKXPjHch6k1OUrRDa2StuFVhkfPFly2k9LpDfRjZ4SmczCZG77WWtw1MXK+8d8VV4qeBos3zQpbMmXrgudMjd6viSEJkpVe5X0SbdEE3k5QtvjvPirZEPpW3JN6rVG4AjyDrbWRudAX7S/Eu5ATgGnwEVSwDnQF0lIdxingFNgeCugDvTThQ8To/ClDS/SFv9uSLuFzO0aWZpMHpd2v9vSPweh4g0iF23GO55Hm+BbZa9ac6DWWJ9qOg66LgUEXrHh6XaT+50VN082Vr7DEBiNC9tkNIogYhJakrJ65P2yh0hEFk7t3tqdH9V1M7imk5c+R/RBC0imRcyW18tfkkUJy+QERSq6WLeD4bS2r1rqumtkFHi4zv7DtpBY0V5uaLjNle/KbFxgbUn0GvKW2zI/J8/kPwaW7w7ZWPqmzIm/kvrsfBHPC9La02rLg/nUdWucQ51kX4ZuHfCfLfiTtTHWUriiTvCHnKMO3S09zVatrSzqMHB9Z1tPoVmUNTW2gaTbWfuBbKv5gAx1qtS0V1NRftRqxJuIlJxBo1CiLIq+0ybBt2g+PNpwkJsJH753ipsSqr3b8g13p3zthKBkKfIstCVErVPXam+NoUQERA7vXyh3dk4Bp8A/tQJugP6nfvvdxTsF/nkUwMWUVUm3yBkdBsn2Kqs4FfLEyuSb5basu2nWC2conkH5SZNUdJdZwUge6Ln0oCwb/rJgR/cMdFsG+srYq4204UVkQbnFQZ5Bksgg2IG7q/lgfxoENSKihImU0AyiHJdKelUGr5dh9dbjIsZTMlLMAuK9spM8tdI/pkXMoEL7AGzmVXIYSsUYvnYYnN7c2PlS1LLHaB6d5KYvBMfxvQlktf3l8hFXktUegDE9Wq7jOrQifDyNgkG+IcaI1qbBvAtKDhmJL+0ng56DFjmp7q4kuz3K6B8zIV6cbTwtqaFp0oobPppzK20v41zT5AK0j6a+BrSJlDyWCSfDgu6iqnt+3GI5SnFKBtGQXCIiEyImMat7iV+vr0yLmiO1ZLd1kVGxdX244Q09deSv/Yy5HeSbKPXwrZX1rMi8VjjQYKTtvwaUEhfRqIcWyETB1dYK9m1Vm/55fkndlToFnAL/MAo4DvQ/zFvlTtQp4BT4NAqoA13H4Ha+7QxDWzPDXBODYhFucpENgerCthDbKKZ+uhHntIfBrwzShi71dQ52EnsYIb7ePpSAENcgzqFOri4eapNgAwt6OS2nIVckM5TmU04CXQPHNzYAfBz86ONkfj08PWwIDfUPk+ONR2zAfQv3OxjUnTdlKR7enkQvehneyy3S0cwgmRSYzOJiGUuBOny2SlhAOJnncGMoh1FJrq9Tw3kX8FrHmg4bNSOXqu+GnlpKULrM6a2jdvxo00EZ8OgjV1xO/XYZi38nzO3Wm4hNFRtkBpXd/Rf6caw9JRwkHoXbdq1Dngqbu0BMxNvoHdGUpij9o5pMdCzLjeqWK63jOE64LwuRwZTHDHmAAJQO6BrhVIv3UrgSL/EUqlTBoI6izGVGzFxZmnKdVY0vSFpCHOSr8tUJ35b5CQvlHqrKA/2CDMs3BBf74ZzfWMvip3nf3XOdAk4Bp8BnoYAboD8LVd0xnQJOgWGnAF1/UC0qKCi5WkYFj5ME/2RyupfZsHyCgXZ37TaGyiM2dCZRSKLDcQYLbFqTPS5sopTCNu4f6DdChjqykb5R1p6nx6jCsVa020mOowO2OsnhIOCU+qED+kTYzv2DAxa7KOkoNCby/jpwdn6RNtR6XPCQI5SzBJKDVmRec08DNA+G6a4SBtoInOh98KLjGdLPGtlDs9gnG4/KM0QwSmFRa5Sjob/Bzklb/uICEo38oQxrJW8o47m9r0OyqdGOIqscyuJhMsN5UVsBqgzK73N+BZ3knJFBlGPdDeXDm4R3AVELdYOV71zO8J1Dbvxww36c9jaG6AoKVgZgYRfKKtzvAaglIV6hFuFo7myU9yrekrPcVJRA8SjFbQ+AbqKFMXqt68AJKhXkpYKnrD790XMPSgc3L7qs2NLbavi6X5/+sVwRvxAu9uRh97vkTsgp4BRwCrgqb/c74BRwCvyfVeCTVd6KfqsiutAJhSI+KJGSFF+Gvn6qpFsZcguJHsyUvLZzLMxNNhd1bsw8qe+tk6viF8vJlqNWZqJDtS67KbLNF1c4gOhGO89PY0A91nhILo+7Cqb0AaNgaFnLhKjJDM6Kphtk2K6RBQmL7TjasqeNgFp+cln8fOIebXJH5n0Mrp1yF7XiZ1pPWm5az62UvPUCWgmrqRbXJTuNS0yPmY2TO8e4zllkpJuJXkTDX/YnTtJKdKSfrHO0fwzHbZGBwUHpGurk36OlurfCbgj0uOoiazFKMQP+N0b/m5TgvF86YhbOchxnBbePyMvC+GtwkGPhS9/OguQxSllqzDm/Ed50OfXmo8LHGt6OJ8hUiCMeLEPenf0F2Vm3Wb434acUqhSSdZ4utTzvy2P/1Y51ZfzVONFREE9ukmU40UrjmBk9FyRgDo76WCIiHfJi0ZNyadRsXH+WJ/nHVXn/n/0r6i7MKfAPq4BzoP9h3zp34k4Bp8D/jwKap93NQl8kg+aB2j1W032GEpKjVFwrZWJP3XajTpwBs6Zu8jZKPkaHjoe4kSsBHkFQJmIgUuyXWQzWGoFIpEFwY+V6WZxwrbxf9pbE+SfIhso3GUSLqAXfIadwiGNA1BWBc7uKQVRrtcuU1EGBihJA1hQ9bxi3x3J+b663Oq7bec2tVe9LNcuC/vy8VninBKSCz3vVEHTv8TqvlbwiPzn2XXk853fydtlrRq2I9YuXio4KhvIEimF2sOiYhhN8kuvIsFiIxj50oG+ETd0B77kJhzuSgXoLr3Vp5Gx5LO8hc8U/oIXxHK7xHirL1WX+Q85/irYH/ufJH1GI8pZcHb/C3GR1pQtxp5P9U63yOwrcnCL3lLH9K362GTd5I8UrFXCra7hp6e3r5rXes9KVnWAC3ypZKxsr3gYH+EcqzC9Yzvk878Xu6u3yHHi8y2IWWDY6Vm8yGOTdwyngFHAKDDcFnAM93N4Rdz5OAafARVPgkw605oy11ENrtrUauw/3uZ/M8SQKPXTx70Y4zOr2LqchL7ctR0LI89aRJW4iK63OsDf5Z6Y9c3bVddYs8CgWC8/iFquLWt9by3LdVZbfnYaTq86txg+aef7CRAZoL18rZSknV30V1ddKqsiExrEy7UZb+ls98j4c8LM85xI7t6a+RkkNTJdm8tpXxC6U+fGLWOKbZt8fEzZexuNu64B5Q9qtll2OoWFQnd4ZMK3LiX5kUn6iFI8YHGXNInvjevuggeamtTFQa78Xx6+UA427aT+cgFvdKqtA6E2JmkEb4ZX2OsrM7sQRbqGoZXLEpSSje8SP65iPizxE9GMMLGx/yBmXxVwJHSReLsch1zIUff27s75gbv9tI++Rngs9RgjROIq66NckX2tFKTPJQyvyLwskYCWD9olmasKJu+Siw0qqwJXyoQ/nQF+0vxLuQE4Bp8BFUsBROC6SkO4wTgGnwPBXYEv5e7Krbguxg2Bznq9KXGzFHvdnfVleL3lVFicvlzcLX5WZcZdR+rHTIh5B3kG4smdkBeUnH7BwtxDc3ElQbXeN/IJ8/8jXbCDcDilC4xMfVG4A/9ZlZSI5DNY3Z9z5UUaZbPTmsg3W3pcDFzolMMM4yr4+vvJO6RvEJcSc6T285kKa+l6hKvz+bPjJ5U/jil8ChSNP9tXvJoPdLcGwqgvJQE+JmC4HKSJRRzs6MAYneLN8Ifsb8kbpy5TFLMVl3yuXRF0qx6BlxDLcNuM+e9JM2NTdQPnJaasef6fyNctH63UtJ07xXP4TMK1H4jrvMuqHMqY18hITQNkLdd93Z35eDpPVPhF3VPZUbdegh7xX8ib0jlYKV4rl6qTl8kr5M1Yws7boBXOZu6F25MG+ts/N581JP1F/VKbHzqKcppKilHTZX7tL1lGLrvGPdSUvy+9nPCHZoP/cwyngFHAKDFcF3H8bG67vjDsvp4BT4FMr8LdFKrVUdj+V+yjD2RgW1XyIN3QTs4iX/I5zQN78Lc+sZIooiBuaU26h6U8zxq8WPgfu7iar7p6Ou1zIYpxWfGsOWCMhGolQhnGAV6ANhBoBUTLGPBzpp/IeZfD8gjxX8Ge40PfakK1DqbKO/SBXTI6YCld5q0VAlN2cEpKO0+1hg6u6s8lwpzv622Vu3HyJ8h0he6ne1uU9bRXU76uzrl3jirZTMogmHk7TVKjlKTXdVTCgh/gZL8P2eVD8EscyYttAm7nRGk3putBhmDp1vG/DE+ehAABAAElEQVRMvV28vXzIVDdZRrqVDHUQNeDpoSOJnDzHzcJCG95vybgLZvQuO24xJBPNj59rOw0LO8ac+ypaGxcxTO9gqFfnXIkamvfuH+pnsfCkxTaK0HBx0gqG9Z12blokoxn0O2Bnh0ImUcf+44crUvlYCffZKeAUGC4KOAd6uLwT7jycAk6Bz1yB53OftCGub6BP3q9aL9+iMvqxsw/KFUkLZXP5BpYBM8jxnpdYBsjBj/boOCdPKYMi4c3HBxXvmvP8FFXbixNWyAtUbN/Egt2emu1WcEKqQQ5C1wj2DiWKMM0Qdvtrdsv1Kbfhsu6lUjtbHsn5LxuyuxmAleZxquE4yLscuTPtAXLG6+W/pj8mXz3wObkn60sMrc/SFDgBBzePbPQHnIGnNSCuK35RQnxCJStktC0vzoqbK68UPCuXJyzAyX1Rfj3lEW4UHpGFyUvJZ6+XWbGXS21nNYNxs3hGeBrVYxUlMq8yFCv3+UzDmxJF0+GR+v3EK1bIm2SUNV6xnQF4PPnw/soB3OJSSQvK5PgvM65fkA3ksRcQ5dhasdEG4EKy4h1D7ZLgl8T1nIcMcowWxrPcXDRa5vvr479n+t2YsVp+deKHLDu2yD6qvQ82fiiTwqYaVu8r4/5VtlVulOyIMeaef+a/EO4FnAJOAafA36mAc6D/TuHc05wCToHhr8DfOtCDNHa8z/JaJQ7pCL9Yo1O09bbheIZAmGjgc6hh7dQ9nhE9h6z0AAuGE+VQwz7yx1PB0x3CMZ4iRxoOEbVYzLC8z/LPxZ0FsiRxJcNivRWCZFFsooUjAV4B8vuzv5KvjP2OvFDwpIyPmAjF46BRJz7EeU2Do6xlIiEs+WkeW6u/vXCLtYAlNjAepN1pmQbFYlv1Jr7WafnkFBzpQGIlmtdWR1lrxLVmfFrULKODaDZ7E9eodd01MKCHcKB9cJV7oZCoc+3FMmUPZBClWwyCnlM6SARIvmJiIVdCHOka6rLYSEJQkj1X2dSefOiS5XyaGTfRgqgLmcqa7sUBHwEbem7sFdLQXScfEjO5OmGp5DNAzxgx10pm9LdEddfr0oVB/dhTu8PKVo41HZK5LAz2kZG+mmiMZtHVpdbFxXlxC/76C+Yc6L9K4f7gFHAKDBMF3BLhMHkj3Gk4BZwCF1+BTy4R6tFfK3yJLO9RG0DXFr9gRSBvUjU9ieH4dZxVbf17q3StLQrW0KZ3vPEwrq8PA98WuSr2Gnml+DlZlXKzPJv/OIPtbCN56LKgNgYqSm5nzRYJ8g4RdWNzm3JsgVAHZ40kqCMcQvZaXeY+BtnqjkpblgsEhbe7bqtMZ2B/Ou8RWZK00ggbg/zMmpLnLaOtA3s32WrNH+d25PyF4LHP0HLbKzZJQUceWerXbFHwpye/K8uTbpDfnPmZudeaXdbMd0NXHYUxZ1neS8FhfkUu41qf59wUyafuuzeRiV2wsHXBcEP5mwzH3fIyDngn/OgN1Ju/x9cUt/da0YtGxlCShjYu6nOUDb0XwsnJluNSBhe6Ad5zuH8EGpyTNJoYt9G2OJKFyT+e+S8GeC95Ju8xBvJtEugRwrnnSrJfKjcMicQ/QuTF/KfQdoZp9vFvhFsi/FgJ99kp4BQYLgq4CMdweSfceTgFnAKfuQIzYy63VkGt8taBVVnMC6BGBOLazibmkESr3vy4hTIKPnIBUQ6t4J4QfolVcEcERsmtaXcRociW2zPvoTnvqr+QNxbiNGuVd5KMxa0+D8rtithFIO3ekEVRy1jOu54ccxqc5FkcbyYs6hq5NuUGeb30FRYF/90+355+jznMC+OXUUxSIAk0Go4iWnEFMYcsluk6+tqtXjwzcJREBERKRHKkNA02SoxvLPSKCqvJnhA+RTLDs2Rh3DI52LxXvjvux1I/UItDncHQnGgucKJHstWSL0lcJd0XuuQGyCM0mxDNyJBEilWUGb04dYUcrTsAvSNeFuFiR1L2orok4HzflL7acHhKKtGlycugdVRQqBKLC62u8g1QQnSJUikhocRYAr1C7D018gc3BCMggqh+cbQY/uv4H7IE+aEs5Vy8aDqM5Lr0oY2Gei7u4RRwCjgFhrMCboAezu+OOzengFPgoipQ1J5ncYi7M78Ig3mPlYJsg088BrTb+ZYcifKLsZjBzuotRDhmy976HdZCeKRxn4yNnGAcZ20t7IGG0YTjXNVZQY74WVskLCcjfB5ahwcNfkVBeTTw0RDYcAQ6xhbRSEdTT50Utxda/OHV4mdB1GXK4+cfIsc8Rg7VfWgFJwcaOSciGfmteQyS/uSjj1ikobyjBLZzCsNyGbGPdHkDLnR8cKJ80P6OLMAZ1+cpwm57LRlsWgsXJy6XAwzRaaFpRDTqpLa3hibDRKkguuLj4WcufP+FqdZ6GIWDnse1RwaOMEJHbscZuSXtbqmmevtlaCBapqJYuXBiJkcbDtKGeIrYxghyzSdhVQdYY+Kums1EW6axtFgNVu82uyHRN04jGxohOdiwm5bEaKllqfHfDn/NHP6t1RvlAUgjNbxOKkP+xw8tf3Hs54/VcJ+dAk6B4aqAK1IZru+MOy+ngFPgoiugLGStz26GOJGAyzklajrUiwzKUeba1y/FIT7Wcli+OOobECHOy7WQN7r7uxiAx0iEVwTDpzcDMjQJbRdkMOwj5nAXvGPNRjcwqPpA9iAeDJ1Di1AC5HjTYYbGahBvhVRpt1vOt6AtF/f1x6KYu9UZ9zP41hFdCJNOssdavKKlLppznk1FeCJxi5UpN0oY3//y2G9btXUXzvG48AmSxPdWJd0idX3qaN+IGx0jt6TfJdOj5ti1af7an/psT4geumzYCckjC/rICEpPUoJSrT1RneEZtBomB6fJsqRV5qJnMtDvJ8us2LkMlga7YGDH+MZJNIN2JyUsmp9W8kiodwQRkYmQSc7IVTQlHmO4zuZ1dlRulrauNnvvnsx92MggZ5tOkf+eTBX4Sbku9Wajm9yRcZ+8RmxGSSG7K7dbEYwO3Lrs6B5OAaeAU2C4K+Ay0MP9HXLn5xRwCvzdCvxtBrqf8pR3yl43vFw+ZSmxNPdppbU5rP6RUtVVLnNHXCF76rdTQT1DvLw8KAsZT412pcyMncvPnbMq7TLKUJr6GgyF9yFYuUzoGrocp+SN401HZAkki/31O2Ve7FUM1J42gA+A6NCyFR1mDxBdCCKXXEproVZXF3bmMuh68f0aht8EI4HEBBLP4HwaKDzRlkMtftEMs9Zwe5IjnhJ5qbxd8ZomMOQ0zYgdoPE0RzzAEl4s0Yvijnx77ViwdRVdZSzohXAd5Yapa2eYxhu2GwnNVmuzYBcFM0lBydAwjlhBjC4G1vRWySKW+7bXfiDxHFvJHFqsogUxAT4Bkg3iT5cx2wfb5Etjvmls6ZSQNMpfmnCqzxhZI5lB/zToupPNR+WahJWyG20fGPVVmNQe4u/jj3ajLR+9HUda8YHNVJFPpEzmkw+Xgf6kGu7PTgGnwHBQwDnQw+FdcOfgFHAK/I8ooEt4E2m60yW3CobTzOAsuMqUl5A91vrqG+Aga7xi7oj5cprlu5ymM7Kl4n1D2JW0Fv8lvkCpCDXdWcGj5KWCpwlseIN7+wB0XQiRh6clhNzv4zkPUqBSIj1DPVbYMiVyuj1Ha7/3sGynuWSlcCg/uqG71nB2ukCHWSxhPhEMtg0yJ+YKhvRGasCXgIU7Z4O2uuJK99BlvlCfcAbzUQzLiTQJToSiUSDvUu1tVeAM/Odbc6jpnmUOuMY3tFVR6R0Wq2B4HslztdRFB9gWhlYtS1GqSARovX0wnpXzXElEpZ5oSDo69fR3GjJPq76VV7228AXZQfX4axSgZFC+org8fSjW7kzDCbmAQ1/XWYWD3Y0DX0RkJU1+cer7lMkkypPn/8jyYjtZ60NW2HKw9kPO95zFXg6A/dPXVh63ezgFnAJOgeGqgHOgh+s7487LKeAU+NQK/K0DreUiSqNIDkkF3RYpO6BrpBJf8IFAMYsFQ80YX0pRilZYa3GJurPzExYxIG9iqW+M5ad1ce4MjqrWe+uC3xQwc/EBSXKenPCVlIboEtyVCYtxU6MMi+dPlKKxj5iGdxjEifMs8fkR26iWEVRva9Z3KrGRpr56Bub5UtJRYNg8rfnWEpZuXGGts1Z3m+QIiL0Go1h4e3tbUYqylBWvp072yhTiHBx3FRXYGlMJxnEu7Mwz57ihtw6e80Sp0yx0UCLRDn8bUNU5VmZ1KOdWi9s8KnScff+juu9+zjFOruA8TrUckxQaAwvJkE+KnCrXUR+u+LqbMu6w4pSpFKnodZdRLKO14fvr91AZPpY89n5ja2vGXKvC/23SzylWWQjSzhvnOsZuDNSxV/3Pt52RuzIfwDX3YLFzsQ3WH/8COAf6YyXcZ6eAU2C4KOAc6OHyTrjzcAo4BT5TBdR53VT2DqzinbZMt4bCkckMg8dAxPXBOn6+4AnjMB+s3Weu7Uv5T0M/9pKN5e/AS74g3kO+ZJ/7yC6fohRlN+5subxR/Kqcw8V9Kv9ho05somjlKJznUpb+dlB8kuSfbu2FyjbWIdyfpkKt5B4gjqFNfMqgPtVwVHxZ7NPjaN224vC2Vr4vh+o/lG1UhOuy3kmWCYeGLohyk31gRR+rO4gzXI/rXIhLfop8dRuLiHsZyD3lMRYTlfm8oQIKCM76bugYirE7w/JfNIt8Xhe8ZTcueCI56/NEQpRAspMbialwpDezUNna0yqncNh10K9oK+V6TxvjWRcmtZ1xe+Umlh9/L7uqt1JxftZeV53yHVVbLQJztP4gy5IFRuVQFzwPZ/lPOb+zZcMnzz8M8m+/VKOdxjr05zQKo82J7Wjx61M/lkfPPiRvlq6x5UtdwDzD99zDKeAUcAoMNwWcAz3c3hF3Pk4Bp8BFU+BjB1pjD/pIhUlcSGFIpH+0jA4bZ6zi2UQltGhkGk6wVksvoCBF3du+C31kkMtwc6MYUFtkUcpSssk5LNtdZy5pZtgoK0LRjPMl4Nv0eLFg2i6F3jHAQB5AKYg6t5od7mPxLi4wiUF8wOIb+lljFQSf5bK4K+FRZ8nS5JWUsAzKjem3S3lXMTXjvZJG1GP6iNm2wBfiG2w/p2UsWhuuTrBWgYfhNmue+Epc81waDZVTXdJZCHLuDoun6PUo6WJMOGg+CmK02bAQpzuDEpfOvzjcKYHpEu4XgZs9jbbETHvtDD4H85pK1lC9bqBxsYTylvtHfdmc6Ay4zsqKbiZqkR02FjxfmV2rFsD0El35zkQwesQ/bh35ObkiYSF862ttcVFvEDSLPpFCGs18K51jKexrveYfTP4l7nyV3JpxN+7+R/pqtMQ50Pbr6/7HKeAUGEYKuAF6GL0Z7lScAk6Bi6vAxwO0N/QMJWK8TGZZiRlKyzjacIBYwyVUYD9jOWDNMSv3eSuZ59EMm0/m/IEIRIEEegabQ93I4Pda0cs2dL+Y/2dZkXKTPHTmlzi302Vv9Q6JIpJR1IIjjCubx6B9tvkUg3QfDvB24iGXyUbaAS9h8U8/a/RhS8V7xCeCWfYrlnNNxy0Tva7kJRuy1xU9z7CZJR+Uvys+3r4Un6whHlGKc7yV5sJWc8gX0vinFeIaz/CnjKW6o0KCyFFrfnkExIzfnv4pGe9RsrboBZxjP4tsVHSUyqQISmNKX5K7qQp/Kv8RlgSvkee5Hm9iFTvJNCttY2PlOzZoHyIzrtENbW7s7OuyFsMCEHvx3Axo+YoOzntr1dEvwbU+ZuSSXJB4ZxpPGsljN+en1I8NlMco+UMddS2N0YIaHcYPgO/TNsMqFjkVMaiO9Qc0HepyZzvLklE8V8/LDdAX9++FO5pTwCnw6RVwHOhPr6E7glPAKTDMFdCs8aUUmWjBhw62M2LmiOLkRkLPCPcPN9c4IyzTqrc1I6xotpGRo42ykY5Te1jZyknLjYqhVdkPjPq6RS1W45SOIuur1du6VKgxhxHUYvd1dtvQrDnrLL6vA/s1uKwa3ViYuNToHP0M1+rCKiEjHVyc5pa1AXBO7DzRbPNsMtmTWHj0gwetmehRsKQL2vLljsx7iX60mpt8O3/2I8+8r26XDf0a+/g+OeOyrhJzos8RvxiDY61EjkjOS53vpv56jv2R6/5VKsY1g62O72XxV7JUeMoy4KkMzdoYuChxGW67WGY5kOKU1p5mWZS01G4CFiQtkbOg+KZCK7l95D0WSRmisjs9NFPeKH2ZPPPnbbnyyvirZWXaLWjpTaa7RwJ9giSc69EbgXnxCxieKzjXW4iPbCC/fbMNzNfgVjsW9DD/S+VOzynwT66AG6D/yX8B3OU7Bf6ZFHgp/xma8LKsevtN8svfGP99+QP10v864d/lJye+K7dTILKlZiNUiwnS0tMibYMtMkQ7XzODY2FrvqwjN/3s3Nfkzt2r5CtjviObK98j3jBCtpBZVpd2F/XUo0LGEnHIN9zbremfM7f3v6Y8In/K/Z3cm/lleb38Vd0HJNt7ynK+VVSGZ9LO19rbYnlsXdRby+toO9+eqp2yKHmJ1XkrQ3lKxAzpH+jH+f6FLe2Vg9NLDkjHYfYy17tP+uWnXIfGHg417JMFlKCso7J8dcY9sr9utxQR3VAXXF1qXX58Lu9P5JErP8o+Q+LQnLYuR75COcz9I78qr5W/LDemrCaKclSiwdUpKeTt4jUUtGRRz71J5iUskIdzfkOpTAOkjWJD4emCYjNYPCWdFLcV4+5DKyFPfkPGbfKrUz+Sb43/gTx67rfyRbB3z+X92W4cFM9X1l4qlR3lEDh2GzpPFw89dXp3D6eAU8ApMAwV0P877h5OAaeAU+D/pAJTp069cOTIkb9e2wB10lqEoo81xc9RQHIzw+IzuLtj5QDurVI0lIesGd4CstLqIKsD7EcEQjPRHTjNSRSwKA9aoxvHWO4L9Q21hb9p0Du0YAXr1EpUtIzk8rgFMjg4gAN7M3nkHRAtFsru6m1yOc7r+2VvyyQIGj2QPmKpFA+lLOW3p38md2d/0ZB36nzr8qEuOLaQwVYusy5CqjPbwAKh5rE1jtEz1E39d6GsKXnBXGtfD1/x9fbjJmAS17TbnPDW3mZyx7jPxFAui50vm4hJjAN9d5KM9vLk6yxasTDxGjnRBJ4Pp1vxdvFkmRVj1znQJpkg77SpsfdCDwNxtpwFZTcHXnZZd7FEeEfKBXWpWblMIqYxeGGQBcLtZJ5XGBrwMmgmeqOxCOf9bTB7Giupon5c3wYdmJUiovSP3bVbIXRcLX/M+TU3ND/863umf+Caj/Jp2n/7ovsXp4BTwCnwv6iAc6D/F8V3L+0UcAr8zypwuPYAJR8N0jvQJ0/nPs6wNyQv5D9lyLVGXNRwBuYDuLNh/hHiDa1C8XC34Uo/XfiY/HzS7+Sbhz8vd4/6Ao7qk7ir+RA1dslNqXfaMNuE69rGoOqJc6xDdV7LORtSNzKsxjAgH6jdK/XddcZOrsA5VvaxYud2QsTIIPageehdVdskjvzvWlzjf5/4S3mx+ClwdgskzjfJhFJCyMy4OZBB3mUYXyAbyt60cpUGYhllkD+0fVCH3nnEMbZUbpSbU1fLv+y/iyH5Bgpk3sB1nobDu0OONB6wYfcU2esaHPBSbUqELb0dcsjnR39NfnP6xxanWFPyoqT4p7LsV2dV4jEsSdZ0VIufj58dLws3/5Gzv2HBcDUUk8flPyb/FyUx+2BTx0pdV628V/6WkU52VlJnDm96e8UmGT9+srxa+KzltBV8XYwrrkuMLb241rQynqOApZUbhjBiHu7hFHAKOAWGqwJuiXC4vjPuvJwCToFPrcDHS4QfH6gFB1Z5zYvil5p7qnEGLfn4AnGCvoFeiBezjJhxU/pqIhG5ciODYQnf1xiCp5cnLm4ftI0xDJudMj1mlvh7BBIJyZQoSBLjIifaIBgREC43p9xlTX2ryShr/fcluNV1FKZcDnGjA+Tc4pQVomjnWbGXSazWZMNE7uXYyQFUeMfNk8buRrk6aZmMDZ1kBAut4dbFwDZyw/rZD+zdcSrHFyeuoASlSb429nuGsluWdL1RMaL9Y2QiDnQXH3emfd7ORRsJw/zCLQeeGpAh6pjrkt61qTfIIKUnStVID8rga9HUgc/m+ubIVbFLGJb9RdsEQ3GalZ9dTyFLPG2Jes4DREYWxF0DOzoeN/xS0QE7wCOIDHczbYZjDH83napwdbbnxV9lRSl6cxIHgeTOzPt5vSzLo6dRp17XXSNzGfw1CqJkEkXmffxwS4QfK+E+OwWcAsNFAedAD5d3wp2HU8Ap8Jkr4A2uTqkRKUHpokSKIRxoxdR54oS2E1Uo5WuB5Hwfy31Qroi9GpLELko9rpE1hc9b2Uke0Q1/lukqcHv31YnU47JOoHa6lZKQysYKSSbCcLz+sEwInyqtAy0W9dBhdlABdR795rbqIK6kCo2BtAw2Q6mIkzfL1rDI9zljK/fBcO650AXOrcaY0hXdJSz2zTZtxkZOsM+jI8faDYDGRPY17JEQvzDy11tkc/UGy2Bf8BySwcABI3eUtBdyYzAHDvQJmRg1RV4sekp8xU+CmoOt3CWfdkNdbuzg+tXJPl+dI7ooebhpP/XfQUbQ0MFa4ytn2i/AkfZiqdBLEgOSpWuo0+geU6JmmLN9qcyyqnTFAHoSNamkOlxbBbVC/Ciutxa3nGk6IeVQO/K5fi2J0YF8FDSPoq58uaR/mkVmPo7ZfOa/EO4FnAJOAafA36mA29D4O4VzT3MKOAX+8RTIx1XOxhnVgpTOgQ5r+Osno5yKA6rRB+URf0AZyuezv24Lfcpa3g7WTpfZEnCHR/jEyBjyupEB0ZA0rrQB80qa9boG2+UG+M0BXkGWF67qKDOHuYR67dL2IqN6KHJO88WKbBsg21wJKSMAB/vt0nUM0bGyA4xeXlsOS3zdRtbQavDTRCwUFfefJ39ETnmjPHHuDzb0ryl4zpr6Aj0DJZtMcbh3OO50GyzrWQzmOVSTL7HlwAFc7QGuTxsMZ0ZfJiOp5L42+UYY0FlEKrLtpsELjrXGJgIpeTnffJblRF/c4GobjDV60U9uXNsKW8HKzaUtUWvG0xioe8l7h/tGUIDSbsU0WZznmNDxMg33OjUwU3Kbc6SJRUJtIFT6Rg83BicbDn+EBOxusEhHR0+bff8ktel1XTVoflTyW84TB/mz1Ybra7iHU8Ap4BQYjgq4AXo4vivunJwCToGLroAu4KWGpjPIdUticJINupqz1Urtk9RJT4VK8Vb5Glk98l6rotY4wkHwdT6UlujynBaFXPC4YMOtEjIaeutZKEyVPXXbZULYFIbMEBkdMVrighJkZcZNMpN4xvXpt0ks8QYtU9HIhLrckyOn2Z+XJ99EtXee3AZCTqMhGpvQQV4H/BAy1EfgVKeEpDO4JxFzmEsRygQQcstxbs/L6MjxhpLrsfOqBBu3hgXIq1l8PCerWFjU81NnPBA+dAQlKDqIn28/g3vub0P6FSwxNhOzyGAQnhx+KeUumfYci6kw3Iew0Hiy+ahMJjMdxp/HR07CLU6xfPZkFhd1SVBXMTWznBCcSFFLlXQPdVgMRWvJ0yms6cVxTyTyofnmAJ9AYiIDXM9Img+DLHOe035KAv2DjQOdzY3FyNBsWUmcZHbcFdSaz5MpxF60KMY9nAJOAafAcFTADdDD8V1x5+QUcAp8JgocqT2I++zJwloLA92gZIeOwSEukRm4szuqN8vyxOuJILxGpMOLJcECc1gDoHAMkRGOC0i02unogBEWSZgx4jIppmglkgjI9ppNkDMOy3uQNYYY1J/OfVS00vpVcHDFLXmg5/qkGTdW66/fgfW8pep9eTrvUQn2CpF3We5rwiFWPF0Qi4Rar62FIxqr0GPqsY82HJQwnwhZj1uty37vl74tIV4fLSruYglRKR7Kt745/S45S7V3LQ7y+pK1RDfmyu6qLdY46AedQ/nRXAqOcQU4u2ksMdYySDfJCTB1o8HG+ZCtXpZ4nd04hPtEWv235q4P1x+wWu9DDR/KWhjPSuJ4hUXAYO8w8H55UEf8zWVWzXpwmz2GPCWWaEp3XyfovFzc8ApD3ZVSnqIRkD3EaJSIsrdmBw53HyUyu8DYlciLBU/Ky1BRNN6i74dWeVeAB3QPp4BTwCkw3BRwS4TD7R1x5+MUcApcNAU+uUSo+Dd1S083H7fa7mrqrYf4iPSPIptcaEOhVmFrbKB3oNtQcBjOLNdl2+LhbApOjjQeNHrFCP843NRUcsPtLPJda5nhJSkrbblOK8GnUC7S3NdoA7oi3mJY/ONQLNslSzQLh23ko/V4ynFWBvSQx6Bck3ItSLoe0cy0D+17XxjzdbLCpbYoqEOmMpht6MT91Ux011AXOLlTONj38Pr+VkrizeJdSnAaVeTBVkhysGGvxHCumjXWopYgvt7HaygD+nTLcfLdS8hJF1t8I53q7tzWs9LQV0cLYgY5Zx9c4UwZgYP9AGSOC2ilqL2lSavspiGUhURF12kNuZI0FLunx9YIyOy4y3HXz3OeM20AjkDj61NutfMPxI3Wum9dEhzJ4qLmpf91/A/RpFXuoyZcXe17s7/E8TKtKl1f0y0RXrS/Eu5ATgGnwEVSwA3QF0lIdxingFNg+CnwyQFaz07LUwbgIScFpcnWqvfki6O+Kf9x7Ls4tbPlJWq+x9HatwvnM8wvwvjN2gB4vg2sGng6rZc+xfA9OWqa5aNroUbUdtYSX6iUjVXvGAVDK7d1cD4FdWIAh7ulr1kO4x43g8jbRQ235oE3UeWt7u5r1HbXQ+bQohblTpeymFjaWkxTYCP85r0S4hNqzrMymDWXvSBuibxVutYG8TONJ6y5L9YvwQpL/OA+H6k7IMyzhpcLh3TxRsnLMppMslJEdFDWZb4MMtBnmk9IDO5w52CHubzKptZrjwY9p262DtrncLNbOffqzmqG4yKp7aoGv/eB6BLm+qK1Eh0YIxsq3pSliavkD+d+LeOIlxSxrDiCY+S2npME/2SrGO/p7+WmJRke9DYb3tWRD/EJ5/r2EOUIJHdebo76B1SHH6Y2XItetlRusCVFXfTUhU19uAHaZHD/4xRwCgwjBRyFYxi9Ge5UnAJOgc9WgSXJKxluj4OiG2sLdy8XPS0zIFSUMiQqbq0DXNxCqBueXl4S4RNleelJ0VPkOAPxrSPvModWXWcdUO8d9SUjT4wNnyxxYN3Gh0+SrLBRZHdnSNFfSlhGBMZKYGkgbvPlLAf2yF1ZD1g2WYtZ1BUO9g02l1oLU8aFTySffM7KTi5hSNdzUfc7llZBbeXTTLKWkviSCz5GpCIrYoy52dr6pxzp2TGX2XPDUsLkKq5BMXOp5I/LoHgMDPbLZGrDteUwMSiFQdjblijV6dX4hCLz+shTjwkfZ+Uv3lSPj4uYwD+TrC3wtsy7+ZmlVsOt6L/lyddbbORY80FJpFimnXONppFRXfKJkZOtwVEd/4XUfW9iOP7S6G+Z430tld7T0CeI4XlcxGSJ56akiSz5TGrLf3/2V/ItGiG1uOZ2XHV9vns4BZwCToHhqoBzoIfrO+POyyngFPjUCvytA/168UvGKPYY8pLfnvkJTOQJso4GvyQ4x9uqqfDGST1Yv1+Up7ym5HmLZjT2NBp6rW+wT14rfekjVB00iWaKPzST3Mtg/HbpaywItstunNbW/hYc3LPkhvcxeB+m8fB5iBvlONsffW9t4QssDfbDRj5sbOhjxEJ0ifAUVd1aCa4RhzdKXgG1l4rzvIEGwiupAX/IMtAflL8jhxr32SCsvOSKrjLLTA/R/reZchV1uLVuXIfz98haD/B1dcW1rfD9yvWQQTxw1gdF2wqLOwvB8ZUxsAZYC6Ai+N5kGVFpGedbz7CQmEuu+iTYvx1UmTfKq5S7jCSusa7oRQb/UKvj7qC1UX9GlzH3VG+X8aGTWcDcCaUjEye+SQq5kdCBX/PSemPxQt4TEuoXylLjSeNvb+KcNWaiDvXJhmO4/efkeMMh+y8BkfCoP67ydg70p/6r4A7gFHAKXGQF3C3+RRbUHc4p4BQYPgr8bZV3JyzjJ3L/SDFImuS0nmIgzJYC0HZpoSNZfuu2iMIIMsgrUm6gzvoUUQJveMcpDJHbrcp7D0tvWqmtg+uXRn/Tlv106B7kQwfQTgpWNJqgj+ONR8yR/nPuHyxz3clCncYmtHFvFU7sedBx06JmWcmJ/rwWrTyZ97At952npntZ8iriHwfs30vaiqBcdEICqZTVf1ougyc6bYCPnJ4oz3/hTcgh98FZPiRXxl0tO2o3U+M9npjJYUpWmmU8Tq+vpy8D+xFoGyMtFhLuGyWNtAteCvmjsDNPliSskJ1UaY/jhkIH1/cq1jPwTuOGYpJsqnpXrku9WV7j5uP6tNtoTtwiHgzi2nw4IWqyHKJ5cHrkbMtra55Zy1r05kIxgYq7y2k9zfNvNaa2H8uGWkNeT875zqz7pYrlwqL2jxYxDxJbeWD0Vw1hd1fm51WSvz5clfdfpXB/cAo4BYaJAi7CMUzeCHcaTgGnwGevwEv5z1CAskcmhrfJu2R4tbxkA07tDyb/Qp7Je0zuGHm/fFi1y5xazSxroUgIeLrjDJ/fGfsjKwOZHj1b3uU5OnAfY8BdwXC5Gac4FeRcJcSIyVGXEhM5xoDaKIsSryEC8TjRZC/ZSrX2FbTxbYewofQLzT8rE1qpG9ckX8sx3qM8pUpaglvkdONxuTpxGTSPR+SHk34pf87/g8xh6fBAzV65cv9YiTwfJCG4yHUXSuXDa3dC3aiF2HFMTjUelQ/KN8i0WIpTiHwol1pdXiV36PAe559ANEIYkkfIpMgpnP9BGQGu79FzvwWfN05+cvJ7sirlZnmu4E/cWMwHS/eM9LNUWdFeiqO93vLXj5/9vYwC11fUViwTW05KdVcFNI2dVr+tzYjq5Ed6R0sGDY0VHeUM1GHyLMSReKIjLxY8SB57Mfq9YRnpnKbTMLQ7JUoXOeFl9xM1USxgKoO3PtKCMySVf9zDKeAUcAoMNwWcAz3c3hF3Pk4Bp8BFU+BvHehdVdtgJr9iUY1mBtypUCJae1r4PN0KTHSJcH/NbuMunyPGoNSLHIbEQw37ZXXGfbT9bZWvjPm2bCx/W5YkXcvyXy8Oap6E+oQZMUKXBnWw9gUHt5Hsr8Yx1OG+OeNO4zfr8NjN9wNYjtNje+Nwqyuu0QtlRT909pfyL+SFt1dv4hj+tvCnlJAo3xEwpsfZ0t34myLE41S/4d98LwmVN57cK/dkf1F+e/pntuBY3w2bOQjkHtfnTzxDK7w1R+3pofi47eS/x7HI+K7xrn939hfWUqj13VXdFRZpUaZzMnxrddQV53ei5YjMAtm3jqXH1OB0i2xoIUx7X7tlpwvb82UUOMDCtnwpaD9PwcxV8mLhM5A9/I1pXd9Xa3lyde0Xxi+jkKXZGhD7L/RKXWedlHYVWLxDM95KDNGbixUp1/+33wHnQP83Ody/OAWcAsNAAedAD4M3wZ2CU8Ap8NkroDzjZ/Ifs4yyxgx2VW2lRCVWtuD8aib5/cq35aa024ka7LWCk+MNR6S+txZG9FyLJOyo2SybIURkBY+WDbCbEwKTZH/tHtBuoeR497HgdyUkiQ9xd2MsY7yu7EWZM+JyKBgllkmu7qqyxUUlatxIa2FBM4NnJMfC2Z1Pm+EbxWukqr3cohF/PPNrWcqi3ubKd1k6nEoM4qRcEjEdZ/uI3Bd3s6R1JVmjX2dypbxX+qZ487GJfLS2Dm6pfl8WUKpyqHE/aL5RDMGCwxuDU1wl2n7ybtnrIOT87BqU2dxNjrmyv8fKTpRfPYm67z+e/bV8a9wP5XVIHkEUn9QxlD9+7iHOaaXsreYGI3a2If1KyVG30CY4KnwU+e/t9rOvF79CxKWU+MoY+xxAw2FyYIb0U2euFA69UdCbmGvA4a0lH76cvPkPS78pYd4RVJKHCO3qFltRWoo/Q7iSPdzDKeAUcAoMNwXcEuFwe0fc+TgFnAIXTYFPLhEq3SGYymttvdOohuZ4r05czmt52tDoC3nCuMjtxRaXUIyb1VOHTSTP2yY3ptwuhTQH3glJo4ZhdBztfDp4a1tfBJniCRArfBhkR4B40/hGNDEJJXfo0KqoOG1CTATp5jHgyTDZZ+2A6iq393UQcwi1UpUmcHfhFLPogt/3J/6MYbpUVmfewxDsbZGIeMpcai9vl65bfaT2xk4JWhJH7KMGx3yO1JCPVspIJ87wvISriKFckNtHwohmgA30CWIpMROHOEe+Muo7kkfGeibDfQfRjuyIMYbj0ybFSxjWvb195Oq45ZYL1ziK5ql1oVGvfV7cIlF+9ufIKHeR99YhWbUZC7FDc9aRMKPnjVhIXrxX7sr8AjcPhRx/nGHwYmh8HOEXzxjdL1fFX2PLhLMosBkROAKHPdaGfXW9ey50288oD1qRehqj+eXPflnNG/XERfvFcAdyCjgFnAKfUgHnQH9KAd3TnQJOgX8MBdr72mQvEYxwGM+55I4LOs7hHEeKotiaBxoMZZcYkkyBiq/sg1OsFd9lFJl4wGHWgpO2wVZYxiFSQla3pqcaEkY+M+oQOeYKFg2TWDTcKZEM0ptgQk+PmktUgUU64hmTGEqzw8fYP0ryaByslabWBjncdECC/IJtsM5r7bblvYNNH8rlDL8BRC+UTqFEj83wqqvJSvdLL/zmGMltyGEQjZMiWhCVEV3XW2OUj2q41MeaDlHKMsTM7smAP1k0aqE13fvqd1kl+PHmAxLoF8SAOgi7+i1qyQNA4h2iOKaHcwkUj0EPuxk40rRfcjtyrKgljqFXFyP9PQKNMtI90GXnpUOycpu1cEWXHQdA8SkZJCM5iyG7CorJc9xQ+Mq5ltO0LOorDhDpGAv3esBiLykhaZA9npPp0XOMC63H0QKYBhobY4ic6MKiut/u4RRwCjgFhqMCYPfdwyngFHAK/N9XIISoRVJAGhi3IVtYq4QAcVncAqq3B2Vl8k3S1dfFINlrZSJtVH1vBinXQoHKIQo+dBA+3XTCiBFdLOO197ZBrIDb3HKOSvABeZJlv1BqrZ/gs2LhtJEvO3gM7rMHGejzNlw/ePqXkDkOyz5iH6PCRksAMYogr2AG92Krv34m/1FqxYthTedYrGIsXGjNRqeRO67DZR4dOk6OUA+u5I5CssaJAcnm7EYQfVCUXgc/m0JBTEtfixWz7KjaLB9UbZCHzvxConxGsKyYw0AabLljdaeXp9xouDp1tXVQV5RfFUuQXp6e1ISHGaM5BVqJ/pPA9y4wmC9NWmn5ZWU+V3dWMqaLHKjbLY1EPHKaz8ggNxRHGKa1ZjzJP8VIJvr8g9yQJNOQ2NhVawi8FloHNVIzOWIaNw6RvHay3XxE0dLo4+FNnCNM+lhedA+ngFPAKTBcFXAO9HB9Z9x5OQWcAhdVAY1QXJ28VH5+8gcQIRLEh6hCH0uAWud9pPEAZImx0kSL4MSISygmyZJw3wiLD8yhvORP534ntxOlqO2tlqlUdZ8DQacO7JDnkA2NVyVdI1twilNxVSfjOK9gOD1Da+F0SlquTLjarqMIx1orr3spLCloz+VnM6WckpMFfP91GhJvz7jXHOE5MfOsIVA5yuFktUeGjJa5nIOnp4dclbhESnHFx+Mua0Z4Ps/VpsN4HPDFSSugeay0amxF613OzYEXi4MaK9FrzCZuoQ71WCIVY1rHW8RkfOQlUtldZnENPbcxoROIp1RbUUyYXX8AznQI13LKBmwdtLVsRYfuGOq4x/A6QwzNXgy9em6nuMm4eeSdli/Xcpfz7WclSMtieO1irj+CAbm8s4QlzrEM/J0S6h9mQ70uY2pGWn3qkVSbK3lD4xvu4RRwCjgFhqsCzoEeru+MOy+ngFPgoiugRSRDDJ5pgZk4nZSJMDRWd1ZZMcmOqi04sc1yAhRcJ9lg5SZXkyv+z5M/tiKVHx/7juQ259jwfJShVXnG53Bdu4g0vFTwFI18SeYk61D+1PmHJafprLxQ8IR8ed/dsrN6C+7xfokiF63OrQ6p+2BKa45Yj3+25QQLe69KPjXY5SwddrLYl4djrCUuWriiZShtRFBeKXzOaBnKqA7yDDL03lGWBdW1PtJ0kEXEV2VbxUY5zfD+fN6fpbu/y/B5+u9KDvHgJuK9svUctx7Sx2Zzx8fBes5pPGUEjk041koUKaNgRR3uwQFG76Eh3OFI8uMh0tTTYCi/91l81By1P1znXFz4RrLbL4IIVBf81yd+Yq+Z03xa+oiGaExEs9ARPtEUzqyTy6IXyIc1e+y5jcQ1PDy9cLK9CHv4mQutfGyNcLiHU8Ap4BQYzgq4JcLh/O64c3MKOAU+lQKfXCLUamht6DvVfEKywkfDTq6WOTHzcXSLDe02SJRDF9Z0eLsSNzWFn9Xa6pWpNxmu7jsTf2RRB629Vjd5UtRUi0xoDTiMOOlgmW7aiFkyJfpSuYH8bgzLhOoCL0tZZQg5dZ2VPHHB44JVeycGpxi+TRcAc1vPyh2Z94HMO607jSD1umQkLvg4HN5rU26CXJEgi3hddWVHEJ9YBuZtH9EJfa1wvqbnlEUe+trUG6wefGLEVMlvP0cWmg8iGeoQr0y7karw8zjVy/mahyyB2dzOOevxtSmxhEy1LkXWku+eFj1dyiBp+Pv423no1/R6NXettdsLE5da9CXEJxRn3JMsdjbnt5Trny2LkpdxY1II83oBi4cFcv+oL+PsN1he+jZc9gpcd8Xi1YOri+W6Arz9xcfLl9fJtrKY7078idWCf/KNd02En1TD/dkp4BQYDgq4CMdweBfcOTgFnAL/IwpsxIHW7K0uqmmJSTlxiBxqpbPJJOdTI60thOdwTr1ZaDtU/6Etz6UGjTTm8tPnH6OFbzOZ5JFELLZIOhGMJ88/QvwhHae324bZJhzjvTjLLxU8K5FeETI6cpyVjGiBypnGk7Ch19Ne+IFFK3bheE+n8KSoNd+KUPRzMcP4TIbLZrLXWrSiJShal/0O2DzlR+e25cjI4Cx58NTPiGMchPXcROZ4P5GIiXKodp9cCb5ua/lGGUoakmN1h3CJz0tvf6+0D7XZAiBoDnl16Hnp7u20fLcOzs8XPM5C4duyGCKJ5plvTrtLPqh8TybgTJe1l8jk8KkMy2JFLckBqXKQMpcQb/jT1H7fl/llOV5/RIaip5AVP4AmI+UYjYg6uO+v2yuFrXnyCCUtm8rekTlxV8gPT3xD7s/6qjyV94hxqN8te0sWJC6Sk03HZU70PJjcrbKzcqssT7vuf+T3wb2IU8Ap4BT4exVwA/Tfq5x7nlPAKfAPp8C1uLBnYCovSV6BO5or0QHRMi1mltyQervu1cl9Wf9CpfUWa8vTCIe2482PX0TkYJcsTblWGvrrYSj7mFtc3FYgCxOWgGMjp4x7qq6qutxK5Uiide/1klcYSlcw6B4h6xtuGeupUTP5Xqph7ZQjfQmYOC102c5ArnnmfM4pwj+Skpbl5gwr/UMbCX2Jm8TSGBhKq18Dg/V8hk5F4o1isXBu3DxrONQCly1V74uHF0uAOMOjw8dLEi63ur+RZI8Vpac3Cb5efsRNUshuD5DRng3DeSzOdjTIu7slgwH4PDGSCeGTJY9FRc1jawGKtglqNnw/y4Crs++FRFJIi+Ndxr6u7auS5ck32KKgLgXOpeq8pLPIXHNdprwn+18kFmrITRl3SDo3I3Hkz0dD42jqb+CaF1qWew6udiDlMloAsyx11T/c75U7YaeAU+CfTwE3QP/zvefuip0C/7QKrCt6wfK8h8kj12v+lrzEMcgYWpKyqeJtXNkmQ6qdaDhMffdRayw8Q612G1GHDsgb6qQGQ854oeBJmcXQV4WDq67vB1R576vdxYCaxxB9AcJGoMU8lDXdyjKgJx/qWiup40TLMXLOpUb5mBUzV6o6qig6iZT1pa9brrp3sNscWY01aP33pVGzrdXwOxN+JI+efVDqaPZLoeq6lJiE8pO7IITEBsTT/veU3JZxNzXgxyTMN5zM9QFpYelPbwQ0nvJa0UvmEPczOFdS2DI+ahLs6CobsrdWbgLZV2w14OrCNzN0z2YQXl+6VmZznbo8mEtKWWvN3ypZy+A/zX7Ww8NT1peso9a7wBodtVhG+c2dOPJjI8ZbXXoNUZldXPt5Yipbqjbac3Up8fLYBXKgYZfck/klOYreGgFRosnL+c8ypN/zT/s76i7cKeAU+MdQwA3Q/xjvkztLp4BT4CIocHPG5+QlBk2t7D7N4t6kyCnyzfHfl9kj5plrqy6tDnmLcX1zWskjY0tnUVN9gHZCpWvU9FYRghByvV8xisXc2Pm42CMYvFuMWdwDTm4L8YdlydfJ73J+IeMjJpuD24sT++Ux3yLbGyNz4+cT05gLzWOGpAalWz13D0OzLwNzXGAsTvEi2Vu/wxzjOtjOpbi5mZApOgY6JAFO9VifCZz/JPv5yZHTeL33Wd5rl7uy7scRX2pfn88x9NhKADlLrjoDFrRyrfUxODRolA8tLdEcuDYoTiIzPT16NvGQbKNkKAVDXWjNT79OhbdmwZVhrTcGy1OvN1SdanAElvW3xv87uejLLLriT4Y8yCfIhvsVyTeaY/75UV+zXPnnsr5ARnomy4SRssX/fbkmcSVfH2Ekj0pcbh2eA+FAryST7R5OAaeAU2C4K+AG6OH+Drnzcwo4BS6aAo/lPGiYtPy2XNlJBlkHyxfynybfe5xs8vtWsKLu9HFyvHlEGbLIRqsrrfGO/v4+eSLvj7CQVxnlQpf/3oNskc1C4vHGI9RVJ1sDYSecaC0PqcOJLe7IhxH9R2s+3FmzVWYQmdBHXECCbMBxXgD+7vWil0Hi9RkOroMWQa3cPkDxiQ6zL+Q/aS2DlR0VEDrOw6rw4bnxsrV6oyyjAruCr6t7fjWD82O5D0HXaIB08RoD7kFRDrRGOrrIUN+Zeb/sz91Lk+CVEDGKZX3ZOp6/UrZWbeLfi0SpGgepId9e/QHXPIp68TeJtayW9eXrZCxou3c736K8JcaWMGt4zZjgRHmp+GkbvH98/NssMWp+mmw00RGt366Gsa2u/KmmY+b4v1m8FlZ1r7xP5tnP28+G+OPQRTSLnkeuu4prDvQKooWwx/Le16ffctHec3cgp4BTwCnwWSjgBujPQlV3TKeAU2BYKvD1cf8mLxQ+wfB4nTww+isWIzjWcEhmxc6lqS9BJsBFjvNPNEpHb0KvlXloPKKFGIai4j5HPfW3J/5QyttLLcu7ueJ9SQ/9i1tL/lnjDx+yiHdT2mrZU7udUhJv+e6En9iQPS16FvzmieJNnjmciMWlDOCabb4xfTWu9gXDyB1s3EuW+nI7jpIvbiFnrC7yhrI3ZWbsZbT4DcKR7pUvjv6GIfhGhY6VS0fMABXnT3zkvD23lSKVu6jazsY5XwoXuritUJJDUuE4pzE4r7HlvbKuYmrG72aYDTB29Ai/WGnoq5PbAu62ZT9fDz/oHmEM3FfJ+xXrzWHWLLUXyDldYszl5uKb435gw/db87dLY38dQ/xyG46TWDRcW/ICy5YZOOqJRu2oB5s3C5d6ABc7m8x1UVs+GerPUVqz1Vz6UpYV/WiAVF702aZTolGQSyCM6DDuHk4Bp4BTYDgq4Abo4fiuuHNyCjgFLroCWvixmXhFS1+zNQIerz0gM6MvM3Sb5ojfrXjTKrv31+2h5jvX6q2b+xsZrFOhUrxtMQRtx1tXlG513iPDsmR75QfyrQk/NAyccqA126uuazKNh8/m/0nuy/6yRTqU9hHsFUKmery8Vb5WEoOSjMusS4FaF74w7moy1LtZ4su0HPRLhc9KZni2VLaVGYs61j8BpnKvvFm21hYXXyNWoc2BnX0dFi/JihgFFeNVK2hp6Wli6S8cd7rcmgD3ks2eGzvPyB4JuOS5LBJqZnlP3XbZikusDvU68tFjibXkElupoFilBkc41j8eRzmEkpn9crr1uGilt7Y51nXUWgHMBfjQisP76uF77ZzeLntNrk+9VQ4PHjAn+66RD3xEASHWcpg8tupTDl/aj6G4oD1PfnjsWzI2DHcb3dshoyhn+tqUG+Tx3D9wg/BNqz7X0hWtI3cPp4BTwCkw3BRwRSrD7R1x5+MUcAp8Jgp4svAWykAY4RvFMBwvQ9Aq2qiU9qVSex7Z55TAVGgUUZIemA4dYpG196UR8VDixGxoFD+d9KC5qKlUUmseOJmfV250XW8Ni4DloO76JR73egK55144zgvilxjtIgPHdgaNhGUMg0q0qGNxb1T4GHNbtYVwTvTl0k6GOcY33hb+qhgyJ4CluzXtToZNP/nB5F8YTm9B4mK5Lvlm41YnBqQQ++gn5zzSXiOR2uzs4NFyVcI11IcTEfFLQMMLlqVW1rOWvejgeoGbiGj/WKNvKCs6wDvIzjc1JIMBeoK1Hl4Vv5iYSJxlmUf4x8mUyBlyfcqtVhE+MfwSyesApQd1pJ2yGXXSbwN7NyfmClmdfh8RjxT0jZSZUXNhO/tQxpJk0RRdPlRGdqhvGMuCy7mZCJW5PEcbDa+GKT0T110JJprl1gbEUVA6TrLE6Ybnz+SvgjuoU8ApcBEUcAP0RRDRHcIp4BT4x1AgmeFXl9yScGLrGXwPshxY2lloVd66MJfTfJIClQxr6ZvOol8NTYTxDNvhfhFyrPkgrOfpUCSmSwj11lqPHU/so6qzXOJByh1q3Ieb3WdRj3D/KGsM1HKVSdFTiSf4W+HIORze+t46o2xEs9RXw5LgoMeg3Jp5N6i7EHNmz7fnSPeFbvkTTuxPpv5W1OnVaEhDb72kwpzW3r6FyddAuuiQvM4cea30RXmh6AmOM2TlJJfFXsn5EEPBudU4iA702nRYQqmJZqJ1sNZISi2DvA95ZG1bDGK4LgXZpwi9tSUvEp0IMCrHSOq4B7gxUJdc8X0nWo7T2lhgtdyR/tEW4eghUuLJ1L6VKvNCnO2KrhKpZtkywCtQOoc6zJ0P8w/FmT/OAB0qz+U9zjA9HdRdMQuYMbKneqfh8jTm0cWNRzRZa20uVLqJezgFnAJOgeGqgBugh+s7487LKeAUuOgK5FDFPUCO+BSDYJBnCBzlsYaYq6ZUJa/5HEOinzye9wdJ8U+T8xSq3Jv1ZfjL8YauU2v3bONp2VjxDtXeJ0VJFTktp0DEDdFueFSScIVPMyQmB6Xx/eOSSoyjq79LNpdvkDaKUXpxrZcmXod73W811laHzfnsqtomj+T81jB3MTi+k6B9NHTXya+nPgz+batxm0sYbg/X75Pd/LvWge+r3iUdg+2Gw9Nc8kKc50YGbHV/t7BgeLT+EFnvJw2rp0uRel2tPS04zFmyu3ILg26unXspQ7VGJyqpFs8IHSlnuYFYlrBKuvo6ZTxu88uFzzAQ464Twzjfdlam4Fp78/Evo79tpSvq5pezlFjRXW4O86L4ZajkKf5kqNXt1tIaJZ209rbiMs+hzGU7me1ZduOiGe11xS/gVHuTG98JD7rflis1tqGMbHX03cMp4BRwCgxXBVyV93B9Z9x5OQWcAp9agU9WeevBPIkJbK5+j2KPWCntLmIITrPYQCyRhe6hblsaXJa8SgJ9g2R0xDgrD0kJSZcBPgJ8Aol4RFhcQRf8zrSctBiFkjV0aB4C1RHqF2qUjJvS78AFTrIcr1Im2vpbiYu02PCo7GUtLxlDHvqurM/LGHjJZbi2C3BcFUtXQIHJ18f/G/GKAItV6ICshShKuOhjqFTHeCoOrg6do8PGGfM5NTjdzkGLT6Ko+lYcXrou+zH0am45n2Nem3qjdILCm0wlN+Flohla113CNfTacwRHfQZlMLW4x4kg7toGmi26koJGq6kZP8v1Lkm69qOBnkrvWCInESGI/QAAQABJREFUTQMNdhwdejUiEsPrFuEe6/mdbD5uA7tq09jbYC2KGdSTjw4fRwlMCsc7Ra34Cikn1jKfa9cbAC216RvqNfLICKImHz9clffHSrjPTgGnwHBRwDnQw+WdcOfhFHAKfOYKqMM6SCTiPENtQ1cddd0HWN7bI7VdNbi722wY3Q4WTn9mU9m7MJorZHPFe0a0yAjMAk93hpzyUdmDk+oP+SK35aysxUV9Lv9xilnq+NmNVFjvkUfO/ka2lL9vcQXF142HqdwEYu4kJScnG49KXss5ebN4jTyc82t5DPdZYxnHG45YiYg2Fb6c/5xp8SIYuwH4yIrCS6U8pbA1V8ZxrKeoFa+hgKWUfHZNR6VVbR/BaX6t9CXKV96Xis4ycHCvW+W2lqZoJvpp6rNPNB+zApc3il+2tsCzuOx63EMNHxJtCZV3QeDpoH6YenBvilN24HjXEjN5OOc3xFvOEHU5yELlBpkSNUP2Ne2WW9PvhuzxuuXKtXxGIxwFlMl4D3mLHy60EkB0IXEbbG0diI/UH5RAzyB5LvfPEkn74TaWOjUmU8hzCiFzqEuu9d/qbOs1uIdTwCngFBiuCjgKx3B9Z9x5OQWcAhdVgQs4xJNBo+mArEUjWt6xKPEaK0BRasW3J/4Y5zZOFHWnru91aTfb668OvocmvlYp7M1l0U3IItdZ+cgdFJf44xLHkoMuACGnlIlZcXNsMS6URbh3YC2n+aVb5lkX42IDEyhAmUDOdyUurr9MjLpEYsg235Z5L4N6qfTivD4w5qu2OKjEDS080diILgDGQMRQ53nyiGkM296yiAy0tguqY62casW/qbus56Zu9WwW9Dr6Ow1ttyxtFUNspUyPmW1u+wBNhAUd5zmyGPP58rgF9pqjcLP9PQPMNdaYiF5PEXlnReytgI6hvGttX+zmfPIgecyCYHKcFscxPK+2t1oWsgzYgms9nbKUrIjRkt+ZKwvhXKcRDbkv+ytyFUuQmr8+2XJULodHrX++jCrv7VUfUJO+Sip7yimMyZJbRt5lCMDlydfzM+7hFHAKOAWGpwIuwjE83xd3Vk4Bp8BFUOCTEY6mvkZ5OvdhI2Eo9UKLQzzBsD15/mGJZ7j9oPJdayTUSu7xkZOs+lobC98sXUMZSJQUtxbCY14vsUFxshNnto4Yx+slr1gByN7andRmN8m55rN8vVbeojikmcFWaRnbazfbsqE63MXEG7ZQzz0pYooVnujAe4y8cilRipK2IsPsFYJ421+715YL11ObrVXg+ygpaeX4bxevs6ZBKyjBwe0b6MO5PmRRjFcKniGeMY1lvveNDqKvc4FYxr6aXVLdU8WQn8tQTtufZ7Dsqt1hy4XbyEu3kM9+rfgVaeqrt4yyxjEKW/IsY30Y1N8gA7ce672yN6z6+xBOt95IvE3JyriwSeZI30sd9xulL0tm6CjLh/OyRDkK5BDXEckw/nTeo9ae+Mezv+bzZDnI13XhsopSFl0YLG0vZtjPleXJN3AuL8qXwNhdoBLdy+Oj/xflIhwX4S+DO4RTwClwURVQE8I9nAJOAafA/0kFpk6deuHIkSOGXNNlOc0iPwHdYkz4BAxQlgJbT7Hc10PxyANGpdCyE8Xd6UOjE6fJ8WoxiS4Kzgd1d5SGQl16qwRbl0ljXw4RiKSgFGlmyPX28CY7nGzYtpEh2TYMt4PJU2Qbc7pVhCtZog639iYQdTp063MU2dY/1CfpMKCfK3jcSl5212yzXPLp5hOWw9bz1lIRRdLdkHb7X98rddVfKnwazvN8zvWEXMZnHaC1Wvssi449VIjHspgYCHlEr/PDmp243F9nafE39nr6+tel3WLLiupEN0DCaO1vxp2vsIVEzSVnh4whs5zMTcMWuSJ+oQ3tvpSeqHMcCfavgMiF4uh6hrpwjndZ26I/1BGtCdevK+5O89Ga+d5dvd1c7xM0NyoKT7nX2nq4HIdblx0nRE62c9CbiBvTVlsOXC8WxN1RPk3764W7PzgFnAJOgf9lBVyE43/5DXAv7xRwCnz2Cvh4+srOmi2ylwFSUXVDg0NWaPK1sd+Xl4ueEV0cfKXwOegPybi/u+XGjNXyVskaWcHindZpH2jYLR297fLo+d/CMV5q9duX09Kn9I0vjvkWhSTvy5KU5fJywbMW01A022myzrPjrpDfnv85juo3cL5LjTutLjbzuJWLBPkGy/P5fyZGEgparoG4RjfZYX95i1KUu7K/iEu9zqIdOyhs0QE0zCdMQr3DrMhFF/t21G5h+N0mixNWyPrStSwSpsqaohdsaW8XQ/i06BmypvAFi2/oNe+u3wqrOlm0iOWW9LsoOsk19F0BNeEayzhct99uDNr62siDh1kRig738cQ5lIetGha15su8hKtoY6wQrdxeB/ZuIVXiSifR19O8s9aA601GfVetBFMW8375G/KVUd+lJOUhmNuLpAxyx0m0U/e7nxuVIo6tZJOn566Rh05/TR6a+eRfh+fP/rfDvYJTwCngFPj/V8A50P//mrlnOAWcAv8gCnzsQH98uh2wkw/Vf4jL2kKBii9Z3AW2MJcZMsqGTy3zUFdXl+jMPcXxHRgcMKZz12An1dt+VpzSyELg18d9z+ILl8csoA1wD0NwsEaWjcKh5IlDYOcU/abLhd+d8GPZSlxiKgzpoyziLUpcJjuqNluGuR98257abbKSkpTfnfuVfGnUN2UvLYFK09DXUZf3GM73A6O+au62By+i53m4YZ9Mi5plA+zI4GyLkMwecQUM601UeK+yYXd+/CK7dOVdj4+4BPedZUSIHZqbvif7S2Dm2qykRX9Ij7uxfD1LhGG4yd0yNXqmIe4ePvdf8vlRX5dgn2Bz53VQVmze2ZbTlMmk4GrvgqRRgpucZTltXUIs7Sii8jvbEIBaGz4mbLzFP3Q5U13sLSxmjgzLtvdB/8uAfv/J/IcturGOCIdSTD75cA70J9Vwf3YKOAWGgwIuAz0c3gV3Dk4Bp8BnosAnM9D6Aq/kPyMHIU6MDMwwxzSIofCFvCeJE2TBcD5h2Lm3IVHogLq3Zof4UjTydslrVlQS7h0pf879PYNyiDGjW8HSqbvbzjC+rXqzRTOUUFFNsYrGEl4sfIoFw3jLBivG7U0c7SY+r+f4WmWtEQ4dvN8rf4vht4Wc8y6r8w6nzOQ3p39ig/NbJesMM1eA6zszZi6Ujw2GvVvP13XQr++ulW24373kiZ/N+xPlKu1GBdHM87aqTTYI76rYZsfQ/PQO8tgjuVnYRqbZnxbF9zjPKApRNFoxyIfmwbWeW7PdzT2NfH7JYitDLDS+wZ/DaB7cD7VkImzn7x7+F/v35wr+JI1EWN4pfV2Up53PQuWlEXOkqCvPlhLVZdaYh8ZcXi1+TjoG2uV3Ob8yDOA5hvB8tMhvPg/d5DADuhfu+xqucQKtkeG2zKnvm8tAqwru4RRwCgwnBVyEYzi9G+5cnAJOgc9UgeVJN8pSr+twU6n0hgU9K36uTA3HafULltbuFhnCIV0Us0zeqHpF7ki7XwIDAqWpq9HYyUrciPCJkFsy75K91btkceoyCfAIkFVkiHUATQ6B1ewZJsdbD8m08FnybNFjcnPaHTjY/fLVsd+RaZGzZCaUjinh02U6n9t72uVYy0F7ztrS5+WBsT+25b8V0Cc6ejtkZuxsWRq3SiKCIqW/d8AY1FfHLoe20Slzo+bLzobN5qAXQ8q4Lu1WstYhMiv2MhbvfGRe/AJJ9R9pue19RFImRE2WRTw3tPgxuYX89QjfGFmQsFgmhU2V6MAREuudIPUDtbbEp/zrKREzWWLs52fvlpdKnpRbMu6U3KYclisny4SQKVLYnSd3pj9gzYgzoHHcMvJOBug3TNdZVJOfbj1u9dyKstOBPJiIii4p/mjSf3IdkYb100XNo7UHpY+PjKBMyY4YI3Nir5C2nlajhShrWyMp7uEUcAo4Bf4fe98Bb1dZZb/f7f2+3vPyXnohFUIJLSBNQCkWLNgQHcuMzoxtdMaZWMeCjjp2R0VBRem9BQg9QBIgvef1Xm7v5b/Wl1y8/2cQhIAvsL/8dk4/5zvr3Ju7z8761pqKCGgCPRWfivZJEVAEXhEE+uGYZ7XZzMDAZ0LrZRlk4agy4USl2Y8kj1XYW/uul82wvk5l0rIt+qwcFVwqawbvkHbvTHEUnMbw49aea8Vht8uG8XWo5LrkIVST2/3TJZPNS09qvyTTSUjHDcjaoTWG6vDQ0P2oTPeLd8Iju2O7ZGlhBTjPE2ZwX7W1Rpq9rXLP4G3gVD8NjekHwNPeBMOR+ZLOZkwCzQGNrDjTne8mVLIjqQik6HbBgtsn13f/ARXotKztv1fCkJHbimOX1R6Diu+YMT0Zho7z7tAOMyCSNuIbx580SS11qemcOLs4T27pvE6Crkqjb70rtk12gxs9B9fviXabSvCO8DZjpBKXuLQ5OozSyJ0DN0lzaBpsvjvlf7dfAe1nu1S5q+XKfT+F+sg0c71V9WeZezmz8TwZLEBTu/823GsbVD1ulX+Y/c9yXQ9eVGZ+SK7c+zNJQR7PaXXC6OZWmV9zlBnEyPu2WfRn6hX5MuhJFQFF4GUhoEYqLws+PVgRUASOJAT2JfbKLChkFDCKjwNAqLX8zMR6cwt3Dt5seMA9qW64Ap4jhQrwdaG8sQXJ9Apwjc9sPFcmihNQ58iK2+FBknosKsZe6C5PR+U6j4Sv1thR+zHIb8PEOjM4bzq40DNg+U0FjTj41PYKB1QmBo3axm1I1LujXbIdCStNRRYhUV8KiTeqcdR6ak0y/zRoDdtAc/ifnV+F3Ns+uaHvD+BYt4B2UY9BhQuNJvRM9xzwmL0mwc7ALtwknFAYyYDWsRmW5TmBRbavGRzlORgk2ULxEcOBpmzcjb2/h4GKT1JIwBuhZ+13+GG9fQxeJoLGMpz0FPKZB+J9uLc8JPvcciWq2FTYqAc9hZVtqnycDx3nOVAlWQobcvKw3diP7oJM1lfAXfCRkQeMbfo0UGdY/X8DsNwb3y1vbHqz0eF+e9t74Jw40yh2VEIykAMXt4e3CNU4DuhhH0mfMu2rIqAIvB4Q0AT69fCU9R4VAUXAIHA8zESoB92I5G8aEl8vLLvPmnae2UbLbvJ0m5BIPj78EAbbTTfayZSeozrHsQ0nIolMSy+q2Bz4N5DokfmBRbD/zshsSLJR8m45Kr+0op4HxYwAzFk4nQ1qwqLqZfLBuR83MndvmfFuY7t9HDjNI0imR9ODRqGjNdAGK+xmQ9VYjuR8BST1jm04wegnc98t4GjTTIWcaVqQeyweSMLNF4/Lh770itvpwTWDoH6cLLXuWokVIrIO+tENniY4LfbD0KRDFlQulhPrTsE1aoxdth+c5iFYi49n4KKIqnCts15u7b0esnWtmK+VE6Ei4kBV+EwYzgRdAWDTKm3+GSZJT8C4pTvaCQx9Uu9shD52syyBDrUL1fydeCm4F5bpVAR8BmokrJCTez6/agHkAwtisVpM5f/6nj9Ak3qNPBvZIDti2zGw0yltoG2046WD90+JP5raaFMEFAFFYKohoAn0VHsi2h9FQBF4xRCg8oWFChZj64zFdDqflt9Deo5UgbuhLkFFiIdAoXjztLdB9/g+JIp2uAR2G73ofbCaTmQS0gIZOGvRgqS1HwPs1snO8FZQOO6XDs8suWrPL00S2B/rRuV5NgYNjskArLY3wML6i+s/Jc/CBvzKXT9FclpnzFgakTALzsUK9+MDj6AyHDbqHPd03w4bbUrU3Ss0JaG8nAWJZHesS97S9m5oP/8fdKXvkJ/t+J6sH10Hm/BxlNOLsiC4yBizUJ9689gzoF/4DaVjNDUsP93+Pbm5+1rYjv/caETTydCP+21CVZqSc8fVnYTBkHcbZQ/ab48mRozKyGCy1yTid/XeivMFDW4ngavcDSfHGf6Z5vyRTBg4bJMHIXO3GTKBPktAjqs9CdXzLRhI2Wj0stm36/b9TuYFjgLFJQHXx2ZDj2lzt0s8E5MGeyOs0SGlB3v1B4Endaa7Y52msv6KfSD0xIqAIqAIvEQE9NX+JQKnhykCisDUR2CyCgel4XZGtkGL+Axjj7019KxsC282dtw7kAgbu+yao2Uw1WfcCFsh08bq70ODa0wVduP4E9A+fpehIaysP9XYgR+NavECqEaMZUdBWzjLJOEnoXI7lO6XE1DtpWyb0+owlWsauJA+0gxdZUrFseJ9OrZT9ePkptOl2lVlbML7UN1+8/S3ynh2zMjmeSCRt2liI4xSTke1GlVfLNMafC4q0BnqNHubUI1eYM67Hw6A57S+yTgWkl5BwxKK1FGyj1VdStDtj++BrN1SI89H2+42UE3oksjtH5j9EanEQD/SSs6edj4cBXdjEOH7TPK/EvezF8vkY9OYhfbdVVANOb35bMjeHWcoI29tf5c8Nf6YvH/WR6Cf/YhxFDyqerHchQr3e2ZejpeXx1CpXo5+ZxEpQx/hy8lEbhwSej6jfHJc3UqDA1U/iI2qcEz975r2UBF4vSGgCfTr7Ynr/SoCryMEyhNocmlpilLtqoHN9gS0lTegYnuU3AFjk47ALPkDjFTIE/7t3p+LTRygTGwEjzgrHEBH3eh0Lg1Kxy5TeaZZyDDoF3f03ignQQf6t3t+Ae7vKagqs8JtQZLbIykoaYThRHhXz60mwX0M8m9MNtf03QVecg4V5rtMsv00XPmoSU33QWpOB2Bgcl3nAVvsP+25Si5sv0S+vumLcmbTG+W6/b8Tm9UOjrHHJPsJuP/RojsKaTjSNUjteGJ4HWy6lxj5vaCzClbkfzQa0TtDW6UZg/s4SNHYeoNlTZk8DoK8AZbhy0C/4OBF6jhTjo8c6mdGnwIHulNme+fLTaBbUEuahi2LkQCvH33C8LTXozpexGeKMnpMdukyGMvEZWd0m/SiYl5przaSeu+b9VH5w77fgBN9PPr4CMxr3iJ3998ubZ52yPk9gqq+1RjNdMW7IJO31AxOjMKBkQn+V778lQFc4uevo4+u3qoioAhMcQQ0gZ7iD0i7pwgoAi8dgfIEmontstoV0uxsRfqagf7wdgwCdIkV1twx2E3Txttt98rRVccZHWLaYLMSyypvFIYjH57/CWM68vaOS42O86UzP4hBdRi8h8GGlH6jbnG9p9GYo9CtsA2cY1psH1d/orSgks1KN81FyOnl4MQFqEa/Fxbib2g5R2YF5sppzWeZBHJh1WLpjO+XE2DHzQF3rAAvhwFLFBrPefT884u/YqrLe6C3fGztSglBj/qi6e8QKmy8b+aHxe/0m6q3BzrPPN6G63E6j4MOMU8bbr8jIOdOu9BUgE9teIPhdL8HzobTwW9eykGEzoDMCy40snJbQ5skAP4z7cmtFovYcfyFbW83ifcFcGo8tekMrIeyCRRAgkiW3zf7w9Kf6pXLZn8MHGiLBMHLPrflQnl4eA3oGwskkU/g3k6RB1DVX1p1jOFtk6fd7G1BAm6Rzx31X0ZFhDbf1NHmc9MK9Ev/DuiRioAi8MogoPpArwyuelZFQBGYYgiQdvDrXT9GoluFwYA5yMH9SfyzAnIVqtJMAu+FIckp0E/uhK7yu2ZcBqvpjYYSsQcScKPQMF694bNmwN0E+Mb3w1qbg92uR6X4TNAlWFGdCSe+EXCNV8DBj5XoGgzIo+nKAzAt4eDAe+C+1+RqRuX5btBHGmQTBgWSP03jkSVQrxiGKUoYSh2kb9zdcwvoHyfLNzetls8v+bL8Zs/PpRXXC9oqccx2oR14Lwxb7sd1umCD3V/VK9vGNxku9k2oJu+GNTcr3mdh8N9gdED8riB4z5tQ1d1vElg7tKJpHLMX1euNUPqIZ6LG4IQVaFJO7ulDZRi0Duo3743uhFX4ReCI3wZHwk/KvT23yy2w5qbRTBLW47QZp6sgpfImcmOyfWKLoZv0oHL9KDSoz2x+o9zedYN8YuHn5XtbvyY/Wvlb+Y8N/4yXhvm4zm3yrwu/gOr/r6ENvQSVeLtcsfVL8r3jfmlcHafYR0i7owgoAorAcwiolfdzUOiMIqAIvNYQKFl503zEA9oD+cF/2n+1qfj6rQFj+FHjgJEIKqB7Qc+wI4GrgM5bOyqxVOs4rvZEDLJrBV3hcTPIbh+S6yG4/D069KB8ZtF/yq1IJFug0BFDdZjV5ggoB6RXYGSgmbJ6yoSSCfh6UCvSkjL7fmjuP0kW6h3kXJPXTOoDKSa/2v0T+dDcf5Sf7/iBUewgX5qD/SwgldTCMTAO5QtK1s0Cr5mOhh/Geb4F18Jzp10AukQPKuZVUPUYMYPvOnAP9a4mDPrrBd1kGAYrVjPQj/xv2oPjRpEAp8GNPg2UlnFJo+JODGhmwsGOyWwCCiBLZT0GSnLQICkmrITbQTehrTcHGlJqjn0kH7w7th8J/d3m5aQVWs8XTb8E95gFvSRiLND7MRiRknhzkDg/ATt1vqCcDMwSeDZeVP6ZjLMPl3S89y8+hsBnA1Ye8xcbdIUioAgoAn8nBLQC/XcCXi+rCCgCry4Ca6EQQSvsNeAen99ysbHbXtl4svxp+Cr50JxPmAr0vyz8d/nh9m/JBe1vg2X1AWtta4UNsnNt0hXuhDHKvRisNxcKEXcZ3vIaTE8DHWPj2JNQ2kCCnMvIaS1nISEdQ9JrBV/ZKt/f+m15J5z6frfvV3IeEt0dE1vBZf699MKkZFHtUqhu3GsG+I3AeGU/LLvvhBrItUjy3z3rMmMzPiM4G7muRd7c9hZz3Wp3ndBuPIQBiD/LF+TJkcew7a1yNSrp/77s63JX9y3QZ15m1EUoozcQ7wWVosJwmRPgSlPSrh+JOxPpO3pukqPrjsO6QVAtKo0s3YLqo2AIk8HgviQGC1ZABCQrXZF9sCS/Rt47+3JT6V7VgnseXS+XzLhUvvz0541W9bbRTdC03gKaymxgtRfnHMBgzEH5FDC9Zt+VoI645E/7fmsq3MTtbAxAvB2VdL54rB1ZI29texesxu+W27pukvOnX/jqfjj0aoqAIqAI/I0IaAX6bwRMd1cEFIEjB4FSBbrU4wSqqj/f+X3D9a2CYQcrnkx2p3tnQCXiFmMz3eGdDVWJs5Bw7jcydhakwnQr5L6sAFPu7aGh+2RZ9Qqh0Ql1okkPYRWZUybqp4BXTFUP8py/t+0bxmxkC+TdLul4jxmU+Jbp75RHhh4wms2sPJOvTJfBu6FUMTs4T3ow+I7V7NuR4F6A5DgFub0aDH5k9beAivTiquXyeySl/7Tg06bqe2rDGZCQuw8DEAPitLiwP5wQYXYSwIBAB8xbakAZIVeblIl/WvAZoSQdrbx/uP3bcimUMbZD9o6Ogm/CwL4+6FyzTzRkycPaPJmPGzOZ86ZdLNXALAX1DVagw+mQqTZn0De60tzZe7Phepcq6r0YDDgNAwTD4GhXgRtN7jVpIBwkmcqlTPV6GfjWDwMH8r2J3WhqBC8ZFxpnyNIz41Qr0OVo6LwioAhMBQS0Aj0VnoL2QRFQBF5RBJgQUrLu5q7r5PGRh8xAQcrCUSru5s7r5PSWs+VpVFSPhWve7b03GNWKLePPyhioF0xI/RiEZ8WfJyHB9o4Z75Ub9l+D6uv7wGPeIAHwhLsi+2VFw0pUl7dJJB+Sn0Fz+VFc5xLse+Xunxpe9GacL5IJyRgstOuhjfwIKtwrINdGvvPSmhVyJxL4NVCluKTjfUjyf2AG1VHfOQQFkD9CIWR5zXEmYZ2DBJt23qPpUWl1t6Gifie8SZi4rzEJ8A93XGFsuKkDPQ8mLpvGnjYD+eLZOBJTj1yx+SvgTe+XHvChH+i713C1x5C4Min+7PqPQ796FrZBRQQKH36rX3ZATeNd0y6TZ4bXy1lt58nanjVyavPppo98adgD22+n3SXhZNhUlzcOPyFHVx9vKvBff/Y/TDV8HbjQ0wMz5dGBB8yAS2JNJ8f/euYzMgsDKwdh5nJ649ngW+8w+ttnTzv3Ff086MkVAUVAEXi5CGgC/XIR1OMVAUVgyiNA9YnF1cul1tEoC+HGxyrvKfEzZFXzGVCvGJEPzvk4FDk82GcZaBR75by2C6HRPCEn+U4zhh80U5mBQYIOWHJ3gKJwEgYbcrDdAgx8o3JEJTjFlIZr83VA+/ghSMIdZ7i/LjjrXTrjcjmm7ni533OPfGTuJ0AduQlycEtQdfYZy+tjoNJhwzmooFEJ3WMnrsFBeZ9c8DkM1HtQ3jr9XUjinXJ+60Vw97sLCe5MXHcpEs275QxI25G3vbLhVOhM95r7ogTcGc3nGVUQcoxp6ELL8QZHk9w/fLdJ/HdP7JCjapbgpWKzNDqbjbELcmEj3zercjZeJjbgHG80lBVzr6CpPIaEPwq1Etp4W8CnPr+V1epuVO1rTT/u6L1J3trxTjgzZiVrzZp9qDV9TsubDPf6QKVeUFkPQZXjAmmC2+G72y+DpfdOQ1Ghkger+5U28LO1KQKKgCIwxRHQBHqKPyDtniKgCBweBGi5vQNScoMYBMhE7XrwkOeiQksb7NHUkOzHAEHae4+khzAwbzUS5VlIMJ8xVI2roPNMUxUqZsyBrB0T43g2Blm5rMyFnfddkVuR+DoxEG4HBsjBPhuD99bCTS8O+kM/OMhFMInrkGgyAZ0Jzek6V72JAigSWyeeASVkjZxrEuQ7zODDoDVouNLrxx7Hssv0jfrM20ADCYICEU5NmIS+O9VpuMs50D/2RLbL0+Bibw9tMwMfuS+oz4aXXe+Cc2KhV1pgxU06hd1uRxW8wcjEUfaOgyGpgrFu5GG4AN4LbetVpsL8ifmflT2xnRh0WI07zUhPtEseH30QutkzDJ/c5/DDdnsm9JxvNQMaSR3h+Z4eewpV7E4ofDwpLrvb3D954qlcAvfdAKWT/WIHXt/sXi3LQeOgIsk5LefL45FnZWXtqsPzwPUsioAioAi8ggiolfcrCK6eWhFQBKYOAg64AYah50yL6TD4xaRG0KSDZh2sIJNffFLdKsjM3QN95RNNdbYVNtM7YUfd6G6WemcjTFiqUXEWGUuOmco0penIoZ5IjaF6a5OnYC7CyuwOqFO0+2bIkqqjkcTa5E0YAGgt2gyFYyDeL+RiX7vvasMdpo31aeBRPzH8KPjNRehRr5ROuAKyqlwJ62wO8ktCO9lr9ZnjR5PDcFPcbpLxieSoDMUHjJGJBUYk7Df52jFwtcOw167AuhgGDqZhivIsDE6oIrJ1bLNEEhPmwfREO2WOny8EbnkLKt1eVOHf0fF+0EHuAWVkhZHP2wppu0cHH0LCfIfUIemucTYYpY4EXg5OBtebRjDkWtOIhpJ4d/fcJr2Rbmhdn2XcDWf75gqdBmlE8+z40zKGin81NLM9DreR6vPjhWAZ7rEH1uAfgNkKB0fSYl2bIqAIKAJTGQGtQE/lp6N9UwQUgcOKwEUdbzPno/RaI3jIMUiszYasWgoJ6nwYjXx765fl7VCW2BPdZaTs9sR2yAmNJ8l13b+HpfYA6B9LjaHIAtBAaE5CQxLSIGxIzq/p/I28m/rR4EVzuwMVVtI+Lpn5Hpz7KGNMwoF6c3Gd7aiEn9d6sVHVaPVPB//5JjNwj3SLcRiiUEruPtA16mDMkivkQAk51gyso1V4o6cF8nKLkex6zYC+J1Gl5n1YYFqyDaYnbXAjZMJexD1SHq7F22r4zStqTjDXPapusdzavdsM2GsHL5mDBek6SJWQ0zCwkLSMH57wW1PpptX4j7ZfgUGX7RiEmDfJb4buh9CGfgMswUl54QBAvpywrYHm9fRAO1RG/iBFW9EoleQqckY2kJJ+03zTMAByGfjRgr4FxO3zmEGFfeBcU/+aLpGbQhvNQEJQzrUpAoqAIjBlEdAK9JR9NNoxRUARONwImKovTroNVeUQtI8HEn3SDwrHXlRIfwWTlXOa3wzDkWeRVM9DVdYFTnK1sbuuhPnK4zAmWQvJOdI41vTcAbvqqOyCecjiymXQloZFNZwMr+/8g+FOd0X3ibsCySEqyMOJIXMbP93+P0iGs/K/W79lFDZ+vOM7JnmnkQvNWVjhTkMLma59edSUyZOmtTert7f13CAbUN2+es+vDPXk+1u/KU/CQrsbah2DqGh3w7SEOszUcaasHY1d1kNWj7SM9SOPyz7I41277yo4BVZKXwT3DFpJP5LW/ZE9qPhOSCGfR+X8Ynl44H6pwj3/ZOt3hEktZf9cqErThGUcePHes7mswehhqH48M77eDJiMoYpObHOwPu8GzSNgC8I0psVoXj+F61NxhFXxXTB4oRrJA/1rcF975I/o01W7/8/Yi5OWwn7mwKF+bORBoy99uJ+/nk8RUAQUgcOFgFagDxeSeh5FQBGY8gisgjzdU0gsKRuXgM4xK8UnNa6CdfZe+Sfwffdj6nH4YKIyIotQXb2t50Z5E7jJ4VzYDKq7qOMdpsL74+3fRQXVBxfCc+XXe34i50P+rQo0kPOnXSQnNJxiuMUlMGZCx5mtFZXhNm8H1DWmyTiUOGgrTq4wdZ7T4AbnwDI+FYMaB1J9oJQg8YaGMjnZ6UJSLuq4BBSLd5rK81zYYdNi/DdQ93hj65vl6r2/NFXxZTXHoA9VRqJvGegXGcju1bkacX+ny71wFpxbucBI1c2HtB6NYuZXLcKgv3dj/w7I9p0NvnZMvnHsD6BIVyEbfU+YBNplc5sXjbOmnSdbwU9mZZtGLpTAOw/3SgxYFWdF/4Lpb5ef7vgequUrZDDdB575ibIc98iqPCXt3g+Lbw6SpI03K9iUwfvu8T81FXbK2u0CLWVRzVLQRD5rDGZYsdamCCgCisBURUD/k2yqPhntlyKgCLxsBJqbm1d/+MMffu48tLmudtTCWXAdkrpu44x31e5fgnd8vHEovGTGe4Tyb8urjzW23xFoGNM6m5Va6h1vQSWWPGBaT9OB8L83fdEoX5C/TBUJDgqcG1gI1777ofhRL24MoGNltsM/S36w5ZtG9eO7m78GfvMpsOO+EbQIEWvBhkF6taYC7RGn5KHX/BAqwVCVRsX5l1LA8jboNLO/rC6TQ7wDAwXHM6OyGYMc6epHjWgasLBivgk842bQPP4I0xIHeN2/Q1+p0+wBh5oa0ttAORkAb5qD+u4Gh5uJ+uaxDXA6bMDyAUm9W7uvxzlroXP9JLaPGP70bsjVUUGDVelpsBW/v/8eWJAvB13jd4Y+sqbvDsMtp8V4JBUWYvcwlDsGYdpC58YEXhLWYYAl+dIPDKwxBi2PDDwICswmWH9vkCdR4T8Rrojf2/rfJhmnugjbMAZ4XvG1KwYw+3OzQv9SBBQBRWAKIKAJ9BR4CNoFRUAReGUQYAJ92eWXyeaJp80gvCKS0q3hZ+SDcz9uNJUDqIiSp1zrqoMqhB08Y5cZ/Meksgir64/P/7RcCEtq2mKfAum6aD5ieL+7oVdMKTcm3qzSLq0+Wt6HCmsrEssAHP0WQUqO0nkMcpLv6b8NVto2VFm3GTvsDv9MJNGrpB1qFqw607HwZFSKt0UxYBG24sfXnSz9qERT8eM9MDo5DZJ5lM1r8jQbub1joR/NxJNGLaSaLEA1mXzls1rPM3zrs1vPB7e4EkYmbXAhtBiecRKVbHKnOTjx3GlvluPrT0KFu804HPJaxGY4PWhsvinpR6k/ugQOIQH+16P+3VSbL0SV+by2i4z1+dKao2lwgheGBSYpd9qc5iFeOuuDkijEjCX3CJLff4RxC+3FPzrvX4BN0Lguntd6ISruOVTrTzZyf++c8X5xQEt6ZmC2ORfvjxXoLVAooSHML6/4tSbQr8xXRM+qCCgCLxEBTaBfInB6mCKgCEx9BJhAf+QfPgKd43rD132g/27ZDfrA+uF1cgOsqWcF5oIK8XOoSZwuN3VfA9WLavnD/isNl5hqENQ8fnz4YSSKRamy1sl1XeT55uTn279vqrqsulK3mcoXjUhuaVVNU5AHwZXeQz7y6GPyf9t/jET3KOOAuKrhTCTRO0xiekvXn4wE3G3d10ExI2QMT/7UeZWxwv7ixk8ZcGn7fTySyV/s+omcUn86TFl+DtfEDmMI0xXfJz6YuJDj7ELiT5WNKAYTPghzlBDO9+tdP8VAyRZUm/sMPYNyfb2xbmNl/nDfGtmACjT74ANP+37gwgT3zp6bja4075n7/3r3T4DBoOxGFT4GBRPqWbOizkS8NP0FTF+avC0413XGLpzV5O3oN/nR61BVplwdz8+XBnKe+cJCq/Kj8JJxJ2zHq0F9eQR8asoMxiANeG3n1aDCXGyq1V5oZVMN5Etf+pIm0FP/66Y9VAReVwjgP/a0KQKKgCLw2kRg0bKjit+57ZtIJJswoG6pGdRG+gZNVTi4jRVQUiDOhKIEFSSoqsFBbhe0vc0MytsT2wVqRT2qpmeYiuia/juNpFwWA92GUgOQqVsO2gGk70BnoHLGdgxOJL+XsnfH1BxvFC72R/fK9shmySJBPKf1AiNxN8s/11AxSO3YjYF1KfCVFwQXyb39dxywC4ccHRP5DmgsX9h2CVQ6bjacYya21GTmIEgmnjRYoUwdq9tsM/1zkESHpQl6z7QFZ4X8GaiCtMFSexT61nRATGKgItez/RIDJ6kQEkof0JXeAkrI+2Z9GNJ848bWnPvSrvxEVK1LbRgJ9Ra4Os4LLjRW5/eAX70ctuZUH1lRs9JYdu+L7jYVc+JFQ5b7+u8ylX1aoRP7taBwzA0uMPzqHZGtRht6DtRQqE3NY6gnTav0FvDF2dTKu4S+ThUBRWCqIKCDCKfKk9B+KAKKwGFHwIEEk8kx1TZoef0YnP3y+LNx5Eks3wHd5sdNpZSJL5PgWjd0odNRkxz3QNmCTnrj0HjOg7GbzqblV7t/ZGgS16AKe2LdqbJzApVZJIW3dF0vjw0/CKrIs9CZXil7oSZxL3STVzaeIt/f+g2jrLEOyhgWaEE/i8rsF5Z81ah7zKmcL3d032T4xkwut449K5fN+5h8d8tX5T+XfVO+9vQXDBXjhs5rwG3eaLSimQSTT9wKJ78q6Fj3wEa8CVJ1tB5/AyzJaen9H0u/Jk+PbBCX1W10mSlntze8SxbXLIfecpf8cc+V8sbpF4OrHEEV248q/M8MhYQqHOOwCOfgxqPxAsCE/ThUwP2WoAyl+82gyQeR/J7Rcq58b8t/yzGwPr8LvOmNUAihCsjdSKZJ25jrXwAe931mIGIUleubu66VT4EGcmPXHw0l42Zw0TnYcHt4q3x87qfx4nA7kuy75di6E+SH264wSbejwmHkBOch0damCCgCisBUQ0Ar0FPtiWh/FAFF4LAhcPTRRxfXr1//F+crwrCE/N18IW8qy5wvtdK251surafyBGkHdCAkf5icXVIQuGwFP5pqFqXzls7JYyhN57A5oNN8oA/Ueea+5EuzcR+2chUKruNyFjJ43JfazWw8RyqfAi/abZbZnySqt3QrZJWcvG4eU7oWB+aVzmUOOHiOUv/Zl9K5S9s5pbEJ93GBrvJ8jUoavF/eO/vKc5X0oXkMsWZfmczTVIX3y2Ve76+dl8fivBswOYbz2hQBRUARmAoIaAV6KjwF7YMioAi8qgiUEttS0lp+8dK20rrJy6X1TBLJPWZjUsvmg6zboVrpHDyGyTNbad3khJX7TG6ldSVlitJ2nqOUPHMdE9ZS0srkmW3yMaVzmY34i+co9X9yX0r78KXghVoJi9J+pX6Ulom11+I1i6UBhz7LofEqHaNTRUARUASmKgJ/+S/1VO2p9ksRUAQUAUVAEVAEFAFFQBGYAghoAj0FHoJ2QRFQBBQBRUARUAQUAUXgyEFAE+gj51lpTxUBRUARUAQUAUVAEVAEpgACmkBPgYegXVAEFAFFQBFQBBQBRUAROHIQ0AT6yHlW2lNFQBFQBBQBRUARUAQUgSmAwJ+1m6ZAZ7QLioAioAgcZgRGcL6uw3xOPd2rj8B0XLLu1b+sXlERUAQUAUVAEVAEFAFFQBFQBBQBRUARUAQUAUVAEVAEFAFFQBFQBBQBRUARUAQUAUVAEVAEFAFFQBFQBBQBRUARUAQUAUVAEVAEFAFFQBFQBBQBRUARUAQUAUVAEVAEFAFFQBFQBBQBRUARUAQUAUVAEVAEFAFFQBFQBBQBRUARUAQUAUVAEVAEFAFFQBFQBBQBRUARUAQUAUVAEVAEFAFFQBFQBBQBRUARUAQUAUVAEVAEFAFFQBFQBBQBRUARUAQUAUVAEVAEFAFFQBFQBBQBRUARUAQUAUVAEVAEFAFFQBFQBBQBRUARUAQUAUVAEVAEFAFFQBFQBBQBRUARUAQUAUVAEVAEFAFFQBFQBBQBRUARUAQUAUVAEVAEjmwE/oDuX/gib+EG7HfOi9z39bzbybj5na9nACbd+1osXz5p3ctdbMcJigjbyz3R3+H4tbjm4cbj73AbeklFQBE4UhCwHCkd1X4qAkcIAovRzyWImw/29zRMNyNCiDHEjYgWRKl9AzNfKy0cYroK63oPsX4t1pUnDJVY/gliEJFA8JofQExu78CKJxBxxPDB+Y9hWoE4VFuLlSlEFBFBbED8G8KJeDXbw7jY3Bd5wVXY71CYvcjD/2I3G9bEEMeWbXk35plsTl634+A+qzG9GtGG4LGl4DHEvrTMF4MrEV9FlLd2LBypyWz5fRwJ86vQyfLPy1os8zM/DVFqZ2Cm8+BC6dlxWkAkEaV1/FysRmTL1nEbv/+lVv4Z6MPK7yKspY1l0ysxn0M0l60rzc7BzLWIUUQYsQnxr4hTEaW+8HPGa5WWOeXncS3icgT/HeL5ZyImN/47dcXBleX9LZ3rs5MP0GVF4PWGgCbQr7cnrvf7YhFoeLE7TtrvH7D8OwR/dNi2Ic5GMMHlD+FuBBPdUnsSMwHEMaUVL2HqwDFrENMRJyCCiM8gmJzzR7XUPoWZ7yO+jWhE8B4/gjgRwXM8X/tHbPAjmhA8xzsQdyCeL+nGpsPabIf1bC98ssnXY5LxOOLUskNPwTyT5cnrHirbh7PdCF9ZcB1fsErr+GLwWmyTMTzS7pHJ5xefp9OlZ8cpn++bEKV1/O6z/RFRWscpv//lrfQZ4OfnEsRl5Rsx70W8BcHk+N2I8saEly/BPYhFCH7f34bgvyHPIkrXXYh5Nl67tI79LTUm7/ch3lNacXBajem5iN+UrS/1t3Seb5Vte7GzL/Xf1Bd7ft1PEXhVEbC8qlfTiykCRw4CV6KrTG4/ipj844dVz9veiC0Plm0dwnx/2XIe87PKljm7FnEeZ15i4w8gK0v8Ed2PyCLuQnwC8WUEE3T+yHL+Y4jrEKwoFxFPI/gDnUa8UGNSsRbxZgQT9VKf+e/IvyH2IsYQf0LwR5jNhbgawfUhxFOI0g8p9/k1gvhMIG5CsK1C9CI+h2BFnfusQnBdqXVi5vMIvqDwWO7Da3kRdyL4slKqlnHeifgegtdicJ7r2FYhJl+P68vbQ1hg0lxqJ2Pmm4jJ67jfq9WYSPEzyiTrZkQJc8ya6iSx4zb2aSGi1NyY+Q6iC8HtjyC4bnJjAteJOOrghvdiymP4LL+I6EScgWBbjeDn6mpEBPF+xF/DnNt53fLGz+OsgyuuxPRHiNsR/Kw+geD9ltqZmOELDPv/Q0QF4nC2H+Bk70SU+nM4z11+rj1YeBSxtHwl5ol9CPFlxPsQ5e1LWHgM8a+IgYMbdmL6LgSP+Vvab7Az//0ob+/AwlbE5vKVL3HejuMuRPDzyXvVpgi8ZhCw4E74hZsct5XdIecnby8t636HxkZxOfJxYZL4dcRZCCYNv0fwR5vfmedrTN46EPwxK29MbvmdSSI+jfgWorxtx8KS8hV/4zz7xaSRCW55ux4LTCpPOBhMaPhD9nJbN06wHsEkko2J+oWIUxFMVpnQMvlh449/EDENUYP4CII4sF2F8CCY3NUj/gdRao2YYUI4HfHh0spJUyb+ZyOYWM1B/AeCGLwR0Y/wHQzO/zvieMRSBLE+FsH9S+2FrvcQdjwRwedfi+Cz5osCz1NaNw/z3O/VakxoL0MQ8xyCSV+p8fMwG0FcNyJ+hyi1KzBzNGIlghh/FlFAlLcPYOGbiDMQWxALED9GEPMmBJ9pC6K8XYAFJtGVCF7vhTDHLn+1vRNbv4SoQjD5+hqCjfjzs83nx/m9CD6bw9n6cLJfIFYfzpMe4lz8zPB7xPsrb/ze/AFxDYL7LEeUGp8JcT4c7UachBieVHay92D+t2XLL2V2EQ76LoI4fg7BzyP/DSi1f8MM/018vtD9Do2N4jI1cSk9F50qAorAJAT4A8MkkYlIN+IfEYdqTCiKCNehNmIdkxX+mDCRK28fwsL95SvK5ldhnsnN5B+aHNZdjmBbg/iGmfvLvwax6t2ISxGcL2+PYYHnTSJOKd9QNr8W86XrlK02P+xMMNi2I95g5g78xQQri7AhmODxOosR5Y378L6YHE1uq7AigyjHket6EaXWiZmPlBYwPRfBRIptFaJ8X67jNu5Taky8Ow8urMJ08vUObnpuwr6kEEy+L0L8DsG2DlFat9+sOfDXakyuLlsuzfLzMau0cHB6JaY8d/kzjmCZ+9oQh2prsfIbZRuY4PIerGXrSrOVmOG5gggLgs+bfZ7c2rGC+30asQ3Riii1/8QME7pS82CG1zvj4IrVmD50cL40+WuYvx87PVLa8eC0HJsrse7/yrbz2e04uPxeTIl7qVVgphdxeWnF3zhdhf15fKmtxQzPVYcII/iCdwaiEzG5dWIFt5W31VggNuXP84GyHXiffL582eM8cXUiSq0NM/xuLD244m5Mv39wnhN+t84pW36+2XZs4Pltk3ZYi2XeX6kR558fXJiNKfvOF69SK/W3/H7OLm2cND0dy+sRPYivI+YitCkCr0kE+I+pNkVAEfjrCPC/rDchnkEw4WOV+VCNPzBs/gOTv/h7HGt+g7gZUf6jxv1Lx2L2LxorqJWT4pGyvUYxz4R0cuM1mPxzO++B8+XXXYllnpfb/tZ/C1pwDO+HbTriRgTvgcGEOo9oQFyFYAJwDYL38S2EHTENweMnEIdqI1jJpPKvNf5Il1oXZppLC4eYchv3KbXJ+7/Q9diXJxGnHIyHD56Iz6G0bnICeXCXFzW5AnuVP+PJLxyHOsnk+yeufMZWBJNrJrBM1DoRbNzGcCG47fnaZ7DhR4jesh2IX/n1Eljm56a8lW/n+hfCvPzYQ80Plq3k9XwHlyf3hQne5GuXHfoclSeGlUxOX2zjZ+KHiC+/2APK9vsT5suf52ll2zi7HMH7uQRxHMKLKLX3YIbfoWcOruDL2rsQfL5sxP1Q33ez8SX89Rsc83YEPxe89l2IYUR5Y3/L74ff6UM1Jt6zEFsQzyLKv3NY1KYIvHYQ4I8m/1GZHHeW3SLnJ28vLet+h8ZGcTnyceFXYDbiK4j9CFaAyAmcgfgU4lCNFSUmJnMOtfHgOiaw/JEJlO0zH/P8sXmpbQ0OJG2h/EeY53oLIo1Yh3j84PwFmL7cNg0nIAXg4YMnYvLC65f/wPLHuA/BatmXEAsQKxHnI96L4DHVCB5zqMak6IUa+1FqTIyYoLMd6lhum262HvirfH+uOdQxZbubWSbIpyBORpTundPSOm5/Ndvk+yfWowgmW3zOZyCCiHYEWwWC2/kyMBPxfO0sbPgPBD8/pTaAmdbSAqZuRE3ZMmcnY/jXMOd3xVN2fGPZ/AvNsi/l9877Kl+efDwT1VJ0T974AsvfxvbTEPy8H+5GvJho87v5n2Unfy/m+e8MXyAY30XUIvgdY+P3vfzZmJUv4y9+hpmU8zNzKeK3iJfarsGBfJY8xwcR/Az8AsHvDJ9TqX0BM6U84lBT3e/Q+CguUxOX0nPRqSKgCACBXyGYbPwv4m/58fwB9uePQ6ldjJm5CAuiDsEfzI2I8rYLC8eWryibX4X58kpgadNazFx+cMGJKc95B6IdwUrV2YghxGcQpfZZzHDdWxFMKNinpYgJxCrEodparCxdhwnPqQheay2Cx7P9C2ItYjqCjffJH2M2Jh+LEFYEE2a+KLwfwXY74veIKgT7zESUbRVi8j1PXteJfTYjmNTxvEwCvo5gm4dIIpg8ltpXMfMYgn1jMvIIguvYViEmX4/rJ7ezsIKfCWJYSgZqMM9KZQ7BF65SW42Zq0sLZVMmTbPKljl7JaLUFy6ztSO4rw1xqLYWK3sRCxB8LtciiCXbxxDPIAIIvlT9GFF+3R9h+T5EM4LP5QQEP0PtiNI1l2CeydubEWwLEVHESoQD8S0EE/YzEGyrEVdzpqx9FfPPh/kcbOPLHT9/LsRPEeV9vBLLPL7UVmGm9+ACnx/7wu+WDfFJBPG/HPFS2iocVDo3j1+LKD/Xv2OZCWYnYnLrxIozJq1cjeWrJ60rXyy/T67n9yOBYOLJZ8F74Toul+J3mL8ewTYTMY74NoLb2WYheM3yF9J2LJeeJ2afa2sxd/lzSwdm/guTTgTPy89CeZvc3/JtLzTPFxvix3/j9r7QzrpdEVAEFAFF4MhH4FjcAhOFv7UdhQO2IkoJ1j9hfj8ijmBCcg1iOqLUVmDm6dLCIaarsK73EOvXYl35jyCTyJ8hmNwxeWQfyrdj0bR34+8nEfzBHkE8gfgw4vnudS22pRBMWBjsK38QmfSUGhPpf0XsRHAf/lB+HcH2TgTX8/7Ztx8gbAg29vk3CK6fQNyAYFuFmHzPk9d1Yp/PI7YhQgieh4lkqfEFaAzBbUwU2V9ee+BgcL50D6swP/l6WPUXjS8dWcQtk7awD/2T1q3G8tWT1nHxUMnIlVj/VW4sa+2Y5762snXls2ux8N8IPssI4lYEE0s29vNmBJ9FF4IVzfLrurH8PUQfIox4CMF17Yjyax6DZT6bNyLY3o/oRhDXLyJ4/MkIttWIyff71zDnMfwc8YWkB3EporyPV2K5HJNVWO5FlNo5mGFSxv7/EPEg4nLES2mrcFD5uddiufxcxHMY0YmY3Dqx4oxJK1djmZ+T2KSoxzJb+X0eWHNgkN13sPBTxPWllWXTYzGfRlQfXDcX02sRfBbE4FnEPyP4QlRq7Zgpf56l9WsxU35/XN+BKCB+woVJjefg97f8fvj5+VvbSX/rAbq/IqAIKAKKwOsLgd/jdi98kbfMH8tzX+S+utufEejE7OTE5c9bde6VRoBJJSulTLy0KQKKgCKgCCgCioAioAgcAQh0oo+aQL+6D+pNuByr/F4EK6X834gKhDZFQBFQBF53CPC/XrUpAoqAIqAIKAIvhMAF2IFUFcZsxDsQ/O99bYqAIqAIKAKKgCKgCCgCioAioAgoAoqAIqAIKAKKgCKgCCgCioAioAgoAoqAIqAIKAKKgCKgCCgCioAioAgoAorAq42ADgB5tRHX6ykCisCrhkAwGCw66mxSa6+XUG5C/Ba/jOSHxVHhlEIxLy6LWzLFjCRDKSlYcobQW5G3SM6akYqsRYqOghQtBbHkrdheEHvCAbGvCsl5MmJL2yXrSYs1YzPHWXIYUoJ/UfPOnFmXc2XEmrZJwVYQW9IhBXse83mss+N8zz/8JO84cDynlgxUyXDOIs5RgfPzHLxewZHHcoU5tzm/uU4e+9uwf1EqCtgX/eVx3D/jTx7op6UoRZzPgnvjucx+7FMW1+EGNN5HzpXFFPfMbTiefWFj3/PYZkvi3r3AKF+Bc1kPXAd94PnKm7mXLPCpKJhzErO8PYcu4vpWntvO7pp1nOd1iXHOievjXEVuRMtGcpLNZg90sPwCOq8IKAKKwN8JAfxrq00RUAQUgdcmAg2NDXL0d+bJJxu/IFcO/UjOqDpPHgndLzlLXqoLNWK12qTe3SSPh9fKjlv3SrYxLVWhWgjrTkgulRNbwSGhaUMS7K+TUMOouGKQS45bJVudlKZtHdJ77E6p2zJdQi2QCbYXxb0vKIlpYUuU2oAAAEAASURBVKnZ1SQDK/dI66PzZGx2nwS76yXnyCLpTIl/uErGpw+LLxSQcP2YBIdrpJhCoogE1hsNyOCS/dK0caaMzO6V6u4GSQTDkkUCGxitkqEF3dK8aYaMzuiX4FCtpBwxyVSnJNBbJ2Mz+8U/WinR6pD4R6ok7UwjMc1KsK9WBlbskdod0yTSOi6+3krJVMYlFcS97qmX4aVdUrejVUKNo+KN+CWfKUg+kMU5a2R4SZfU7GyRsbn94o54xTbixv1NSOOWduk5bqc0Pd0hYx2D4sW9ZJwJ8e2uE0/eJxMtA1LV3STD6G91Z6PpExNn/3ilDC3qwrZ6GZnTJ/U7WiRXkZdEfVTqdrfKwCLc+zMdMo77q97bIpHaCUnVRGXgZyEm0K/ND6nelSKgCByRCJSLrh+RN6CdVgQUAUXg+RCoq69dPfucDjnWe6L0ZXvFa/GJx+ZBNRqJpN0vE4UxSRUT8gb/ueKd7ZL45rQkHQmxOuGykvRKwhsRz2hAnGE3bBcrpHpfI5JuVE/defEOVKIK7RD/QBWqpVZUcW1SOVAnFShSF50F8Y4FEEEcZxVXyCfuqFfsKZc4Ei4kuJXijLrFP1iNiqtTXHGvOJO4BqquFRUV4opALc5RFEfEjf2gGod5a84m9pxDnCEsI1l3hDxIav0HroU+BnCuClSNXXGP+Hh+JPuZ2qRUoEySR8XaPewTKyrpnnFMsw703Yb+VYoj5RR/f7Vk/SnxDARNgs97sOKeWDGu7KnDtXF/2L+yr+ZAwt5dKzZUjB24RnVXo7jH/bhmtTjyAA7vAhXAyI6quwAH+wTui5j5UFlH5dqecUiwqw5TOzCsElfUI6m6uHhHAmJD/7x4CSi4cuIO+yTnS0vRm5fw+oRkMpkvPd9z1vWKgCKgCLzaCGgF+tVGXK+nCCgCrxoCqUJKhrIDwmlneq+hbayLPSx1oHRE8xHpzfTIB+o/JutCD0m7d6ZsO3WzZG7PSmpaQtzVRdgA2lElHkJltwZV5hFD60hWxiTnzUralZJQ27B4hlFJbhoTDxLbWGVY4lUTUr95ugwv6hF/Tw2qrxHxDgUlUo2qtjct1T2NMjZ9QGq6mlCJHkQlOiixmnEwQ5DkRiol6UmIH4ZzCU9cbA6HxFpHJVkdlwZUfWOBmNhjLnNO0ilijjiOo4EcPJhbByWIBH5o6T5TwY7Uj0sE562NNEmseVxqtjZLqGbE0EfiDWHJ2FDRxS9ABFVwUi/i6GfBiWS1iAo06BWemFcmZuDeu2tkohW0l6RLkv64ZFxJidWHZKJ9UBpDHTI6vV9qu5plvGFEXMNeKdZmZWIaKtBWXNcXk0JzQZKoeOfhu5KvyUt02rihuYRQhQ/4Eoa+kUG1PIz7jLSgL0iiw81jYknZZAxV6iJZLHip0KYIKAKKwFRCQP9VmkpPQ/uiCCgChxWB+fPnFz/ykw/KUu/R8mT0UWlytIrb4pGdqa1ysv8NsiX5jCQLSSSsfnhKj0irbboMZnrl+qtvFHelS3KgHQT2V8pw9aBUhMHvtYB3jOTSUmEBFaJK4s0h8QwGJV4TNpVlZ9wt8fqweIeDSEJRcc3/uUYB9jFq2C/8T25pP05ZFXagUs3E0t9XLcna6AFOMnjWrIqTN1xqpePIfWYlm1P2hdVc8pR5PBNn17jXVMsTdaiuo+qbRhLrjHkk2jiBarvfVLrJ7WZlfHz2gAQ76yRRg+QaVewAKs9R0EBI7/hrLdYQElvKLulAwvCd/b3VMg4aSOX2Rom1j4PSUoekHtcb9CN5t5pzEsdkI/qE6UQ7HMTt4E3jRcWJKvzuq7slGo2+MHh/rVO6TRFQBBSBw4iAUjgOI5h6KkVAEZhaCASq/asrTk2J2+qV20I3gExhk9vD1wuKrLI+9rjcM3GLeK1+eTiyxiTUD4bvkYWuJTLU3CODe4Yl507LKCq7trgDld0uqd7dKMPLuyVjT6NSapFRVEhJPWC1mUll0p6QFKrFnpBfwnVj4gY1g5VZTlPuFAbzRUGZcD+3rrQt6U4iWU+AouGSCXCtuT+nRQ8GHqJQHAM/2Q+KxOCSvVK1r0lC7QOgf+B65rgcjrOb/UnfGENVOwd+cwjcZPKg07VxVJknQIlAhbx2HBVzVLxRDc9goB6ryqNz+sUDuklo5gCm2FaJbS4MjizaZHRurwR7amVsVh9oJKB/V4OPXUQlGRzpSB054V4J1R64z1gVKsspUD8qrOA+dxkMxnB83pWXWN24ZN0Zyfuzhv9tAbFlrHVAMlUpiaDaHKsFx7kyKRPoO6vgIwu7zUDNZE1MYq6IxNfmJJfLfWlqfbq0N4qAIvB6RkAT6Nfz09d7VwRe4wjU1zesPvvN50iHe5b44EC9qvJsmWmfLQ2uJjnBcyr40D65qPodUm2pk2ZnC6rTPhnLDcsM3xyZv2C+7Hlmr7jTqNgiKfRsqhZ3AvzhmE38XVXiIf8YibgPPGLXgEccGfCbs+AAJy3gAkN1AwoSDvB9UQo2CS4SQKlAVZZ/SutKU26D9MdfbMujAmsds0uiJYKEuQpJdkE8E36xxJzPnRPMiOeOs4EnLVDu8I2Cez0OvnTSKZUYYOga8osT/OsK0D6caZcUCuRQu8WBQZK2KPoNLndFlPu7pIiE3ZnFOsxnoSTiHUE1HeodASTStgmXeIEB+du8F+5P+gcTeCbPDgvOg89UKpgyHPAiXjKCqFq7UWkuOovi7auUPBLp2j1NRvSDFBdrAkoc2GYPOUHbwCsOMHNOeMWyH8udDrEPuiW6K6EJ9Gv8u6q3pwgcaQj8+f8Xj7Sea38VAUVAEXgBBHIo344UBmQg3GMk67oy+wTsZWmxtUtXer9Jlp+IP4JBhSHpiuyVftA3OpBgD+T6ZJZzjsxaOUMGHxozgwkzx4Qk86xdQrOHxdtdJRnBwDaoalDpIhvIiCVpFVI4vGmf6ZU3dmDqxuBANjf+lNpz6/7KNgcG+sX94+KvqBKrxSppTxJycfkD14SEHMjS/985HUhik3VR0DAOXDdfDbk58IltYYd4IEVHWocPCTSbBy8FpeZOHOiXN+4z9BRbBSTqkORakdTbU3gBQOMASurN8cWAdJDyc1mtFYaC4RrzSRyVZF9PFSrUqLYjCqCaUJrOhmp2xpcUl9cDDjfuKxiTdBD4oSqfrUyDZpIXp61o7q04XCHJiphYg3axDqEvHaCBKAe69Lh0qggoAlMEgf9ftHOKdEq7oQgoAorA4UCAdIMqqZPjXafIUKofAwfD8kjkPtmc2CBMpotQjJjrXCidqd1Q40iaQYZZS0oabE1Yt0+ObzpR5l88Q1wVqLhCO9kWtIDmgGqqFMQ1AZUIVGiRWUq8KSQpf0IS7gQoDeOm66MdoD2gccAgG+kWpW2ldaVp0h3GIMMDxw3PAO0B3Ouxjn7J23IS92HAH46tgAxyIhgVS9oq5BiT3xyrHsWgxQPHhZpHTOV2aGGXxFomJAn5u6QdSTf+hJohs4dWuh6vxWuWr+M26l2Hwbfm4MYs6CsczJdH0p6zQfMZle3xjiEZbxwy9106V7RmwlS4xyH3FwadI9o2Dmk6cJdHPZDtSyKRToACAmoG/tjACQ9hEGG0fRSDIyfE4sJPEMr4OWhyF/stknTFRfqtoG/kxLUdknpBJPG7MTCRD0qbIqAIKAJTCAGlcEyhh6FdUQQUgcOLgCNgX/35d/2H7MxvkfmeRdKf7UEaV8T8EnCfvaayOd+1SIbzgzLdOROJc6PU2OqNtB01oscKI3KS5wzZm94huT0Y1BcEv8GH5HlLENJrMXGnID83AfpG1Cm+iaChMlhR6aXkXBFSc6zCeiBhZ82CuIEKsetgtdcT9psb5ZRmITlwikkToeFKtiYJeTgXycRmwCB1nskjNgYsqAWTX+0Dj5kydQ5UocmpZuO5TGUYOtMO0DJ8Y6CZRH1I7yug7nGgKm2uh/t34ThbznlgG+TiuE+pTy5wpa0WvigEwBm3ihvqIpSUY5U4MMRzYuAfqBnmDyrb1ICmsQxNW5ygsAS7aqWCx48HoKAB6gcoHF7I7PH+6NVizF3wMmLHvjRr8e2vlpQzLkXk81TeKLhz4ujzGPk9B3SnczUZiW5XCod5yPqXIqAITBkENIGeMo9CO6IIKAKHG4EKl6ze490uCzuOkoeja+St1ZfKA5F7pNnWbCgcI+kB2ZnZLveEbpUoaBwPRu+TbalnJZKNSB5VUfKk10O9Y0nz0bIh+7gEE1Uy5h4SV5VDUrakjFNmDc6EEzOHTPKXDMQx3y8uVKnHaWwCju/Qsk7xDVSbAX3xyqhJolm9ZcJqpkiIMSzPyNflqtJmIB0dBcdnDBinv5w9Yyq+1GsOdQxDX9kJE5JukxSnvFFUipFwI4nmuVzQjB5r70eyjv5BwzpfkcG868B1cD1WxR0ZJ6ghEfCUQamA+sbw/G5wpivNPkyUQ80YvAiONAcIjk8bNprV45CsoxZ1wpmULAYfkvs80YRBloE0+jloXhQi00dAv8aLgOn7oEnwKXWXxUtEuGVUQk2j2B+DBlF9diKBjzoikhsvSCqFgY6VkA3cUyWxRWPi21QjsRNHxDrqkOiSUck2JST9CNwIs1kdRHi4vyB6PkVAEXjJCGgC/ZKh0wMVAUVgqiPg8jhX18+pltHUsPzb0i9JX6JXjvGtlFpHvdgtdpnlnienBc+WWluDXFBzicx0z5aANSiLvcul1dUmQVultDimyab0Brl09gfFXe+S8W1hYzVtL9il7unppoIcxEA9VntRAsYgOFRWwdm1IYn1TgTEB5MSGphMrkCz8syBeizL5sFptqNKzcF2NCEJIOF2wmCEShs+uArawIem9Jsdg/0CMDMJ9NeaRNWR+nMF2oYKd9EKCTtI7LGC7YSSB5NnNnsafaJ9OA1ZYGbiAT87WwmJvAgGDcLshIMCmdBnIJvnx6DIIvjIlKFDIVkccZepeqcDSVOBztRA9g77U6WD1WQm9AG8KHBwIwcq0hjFmUd1fMgNKgqoGag6M/mnq6M3HBTpgzV4CP2MgEsNPrVjHPuGcdwQqvmDGDyIQZO2cfS3CuSTQF4cqPBHNmgFeqp/17R/isDrDQFNoF9vT1zvVxF4HSEAzvLq2iUY1AaFiA2Zx8Rb6ZHfj/1S0sWUPBC6U7Ynt8lQrl/uDd9uULlh7HeoBRdkfeJxGUj1YrhhWu4I3SStzunyZOxROcZ9gtwweA30PEDBcBQkNGtYKkI2SNztxyBCyL4t7pGMA0chyYzCXIVOfUOLO8Ued0oWRimpQNhUX4dhPkIr77E2cIPh0JesjqJiDfk5PyrQqOhSG5nScWlUiSPTRo1piw0JdphydqBRTIDvzISdPOYcJPWYKA+hkszkmpVvD1Q40s4YrodtGAg4DF60bxhVZtiD5z1ZKeZR8QY3mf0bh+YyFT7GUVEu+DDEEk6MUeo44wVhvGMALoMBmWgcwQBCu0RrQpLPg8ICKsrAok5TZR5Z0GuSeVbhi1lUqZvDMjqzF/QYi4RRMc8g8c7BuTHSNCKyG/ewELJ+uwMSnxEWaxSDC9tiGHQIjvU4BmiejOo5XhJCJx6oeFvs4Jc3jktL5ywZGRnRCvTr6Lurt6oITHUENIGe6k9I+6cIKAIvGQGbzb66YSnk12CznRxMS7AqKKfWnCHLPMfKYtcxqDYHpN01Q5psLSZJXuJeIbM8c+VNgbfJTNdcqbTBprsIvq7VIYvdyyViCcvRzSuk3tEog/1DhgvstXvEs77GKFTYIrD2hnNfsA88YMjdeWFxbY3Aqht0CMrHRWG4Qvm7JBz6nKBdVCCBJHea9tw28Khpqc3KdGVXPY63i388KL591YZPbEdl2wGnP0rPSRR9wp9cDoPrDsrfpW2oKOMatlG3uLLgDmNbojYMC3GfpDHAkZxmG6q95FhXJGyYps318hXgHOO4LAYKFmCbbYP1ttUO4xUk1RZI25GmUcxAgi4cEMcYqspQzXCTdoLjPOBW20IO8UUCkPLzSb4qY8xYKvAy4ci7DA3G2ueW4kCFWEKowuN4Wxf6h6oy3ijEs7PSyNRJyiJFuBTShRAjOYWKICtaT5CPve0f5cyZ58pTt2yUwcFBTaBf8jdBD1QEFIHDjYCqcBxuRPV8ioAiMHUQAD3BvdsvKbjtWaAAsfah+6Unv1+iGLH2QOIu5HAZWRu9Vx6J3i+RXFjuitwsw7kBiRVj4EJvkmcT6yFp1ytN9hZ5KL4GlWefdBX3y/GzTpTRIuTs4n6cA1VbSNylwEWOzByReEtIYk0TEpkzLJHp46aiagbZITEuVGEQIpoDfzI+DA5sBCd42hgcDSck1QpOMKy+HaBB2CA357DZUP0FLQKJqB3VX65zIzFmK0niceq0OI38mxWb6O6XQmWXBi9Wj0Uy4A8bOTkYmCTgQsiBfHnQLtKNcbwYwFURVfF0c0yiUN5ItUQxlFAk3Ro19A2qd+RgdEI+dKo5ahL7ZBNMTXB/yaqYFDHYLwU5ulgbrmkHz3nekFmfQsU5DTOZZBXUQyZyUsC1bZCuK9YWoB1tkew8WKFbsD4Ibjf41PFjRyVzVFTS06NSqMxIJDAh5190viw/c4ks9C6W7ZEt5p71L0VAEVAEphICmkBPpaehfVEEFIHDigDGAUoIrnuFLgsc7SbE5wzIDbffCEm7AamD2oanIiAXV75T7DYn3Ao9UOaAIgVUNB4K34vBhndJjbVOBpFQJwsJqbXUg9xRkOnWmfJMdL1cfv6HxN3uEHfRg8F6BQnU+sUB6bYieNC+EIxMcB4nzEom5oCaAa3oJCTucgV0CC1ehcGEIY8k4ExoT6DKi0S+kMKAurq4hCEhNz5vAHSNEUlWxnBcBBXriDluDAML2UoScpSwS8A5sALJcBz70qY7iyGJVkjdRXF8ltfFwMVEIIrkOnSAktELeTgkxUkkvekqyNzFwcEG55mSfAXcRxJJcQhUESbJ8bqQUdvIQ2WDxyd9cVNZJ66xSvQLSiTJKiTVkK7LW8B3BoWDtIykE/cKzHO1GbHtQNUaduIVA9CiRuW7iMp4RU3BvDzkZycF5pDiAF989LGQnHjWifLjz/5Cgg1BWVp5jNw3dLfUOOrMPetfioAioAhMJQSUwjGVnob2RRFQBA4rAjafbXXdYihgwLTDiuRNPEhuE0F5YvPjMnvhbMjZLZTNyWcEQ9hkqfcYc+0GR5OcXnmOjOaHZb57MZJNcJQLcfHbgnArbJWhfJ/M9SyQ3Zkdcuncy+Tmp2+Qqgxstb3QMPYWpW5fC6rRsPOG656TcnRIbr3gJNMlMIOktOCArjK4zh5YgNsTLtAhfJCJ85tBduQwV3Y1GBpEYADUE/CXHeA321GVNnJ00J4ul5zj+qw/g2QcFBBQOchpRpEZduIJ0DPg8oeBfr4R0CQ4WBHlZWsRZi/Yh8Ymbth+e4YDxpbbCvk4C3jXld314h0KCrxUDuxP50QMEkQWLcG9teIDpYSmMQ5wutNVcSNbB/cVcKDtUtVTLzFPWKD8Z0xlOADRNspqOu5hENcH88SKfYvVOclQqm8Y91KNRH5nRt584YXyqX/4tCwNHi394J6fUnu6PDn+GOTwRMLZsOy6bZ9SOA7rN0NPpggoAi8XAU2gXy6CerwioAhMWQSsfstq5+ngCadRgW6cED/k2mgSUpdqlHV7H5OmjkaZyI/LrsQ2Y6Jyf+QOQ3N4NLpWupL7ZbnvOLl67Gey0r9Kno49JVn4XCfyMETJjsOAZYE8GLpPLlx+sdw5cIsEwtWQeQOloQEGIRU2GVzQKcHOOhlDNdkatxm3vnDbmFHXSAQioDbkJNw6ahLV8enDxsXPCVk5Vn8pL8cBhqRcZCtADWkdgxJGwPS9JH9HybkJSNeFpmMbqB7Dc7sxmNAh420DUsQAR5qvRKtD5riReXBiRKIehtQck1jK7eG9AHrVVtA9+iGJ55UQBjGC7m0GM2YhnceEvzSgkRSPHAYfkpoy0TYkefQ92gJ6StgNMxdQT8bykginjDReYF+thBeD3rIdcnSQpbNgcGCqBZQODBYknzy2YNy8PIxU9stHwXFeeupiqawMSqu7Xe4ZuFXeOu3dcm33H2Rp1XLJFjLyFBLpvltHZXR0VDnQU/abph1TBF5/CJDypk0RUAQUgdckAp5aV3H+BbMNLSPpjYFL7JS6dKPRHbbAzCOdyMi57zpHTvWcJYOFPskU01JnbxB3hUe2pzZjsOEKWRd7WFZ4V8oOKHbQUjpTSEu1vQbLW2S2Y75sQQV7seto+e8rvyLVvhpjOJIDkUK6YQoSgZkKaBJ2yLTlfKBI0IwEkm+pyripGhN0co1ZVS412oPTNrsArjJl5bj/yFHdUrelzdAsWJUub9FW2H33InmHkocbFepEfcRQOawYODmBpLhyb4OMzx0QX18VONaoVsNym4kzZelysOzOO3LmGvHGkDjHYKKC45iwsxKdAOfZ31MNBQ04EmIwYQUGDKabMAASUnUJ8MTzoJ0UQN2gIYoljEGN9SlxdvrglmiDXB6S/zpQRGAok22DyyPuyQX8C+mifPyjSJwbj5Ed4c1S52qQAiglfUncIwZnQgNEUpkUXkKsMrxv1Fzn+s/eJrt37/4zSOUA6LwioAgoAn8HBLQC/XcAXS+pCCgCrw4CFVWy2nJ22lRPoxis54OyRPfcXVITrpeRqkEJZIISTUakJ7DPaDdfM3altNrbDf95X2K3VNlr5f+GfyB74ER4e+gGGcr0y1PxR+WeiVvFXuGQe6O3ywL7YtmQWicfPfUTctvIdWKB5TWtp4dm9RjFjP5j9hpedHjGsMTAFy7CGjvUNoKEOg1zkTHQKaySAP0jD94wdZ2NHF1vrTE9oX5zIV+EbXfIyMLRtISayuEaVHGhrhELTmAAYRK0DK/0Hb1LfJC4I4faPRaEeckIqtOQuxvxyQjk9Sr31ksE1W0HaCPh6bDdbh6XgjOHKvawWTeBdaZCHIxIGPJ8BWse8nfdxghlZD4cHLEch0V4vDYi1i0eGV8+IIEttZKYh8GJMD3JY1BgamZE7D1uCZ3eD+tvi5GjY9abc6Fyj3s9Yc4p0nhSrZzdcr6sGbjdVJ1T2ZQ8PPSAtPtnovL8W/HZAnJf792SGkrDQt0lz2bXy+h9ERkfH//Sq/Op0asoAoqAIvDCCOgb/QtjpHsoAorAEYqAp9pdbPsABguC/pCwo0Kbh1FHHNVSd4XYfXbYRWMKhYvMaFYuvuxCmWNfKNUOVIihE81keY53vnQm9kmDq4lOeLItu0nqrQ1yb+R2me2cB/dC0BJAraYutM8GW+5MQX77+6uhN42Bc/iDOrJk9+Ea0FTOwaWPFV8/rLaj1ePijQYlWUTya7eLFVXlmCsqgWRQRlr7pba3ScLYx511wZYbdI72AanpapQYBh1S+SOdh5Qc/qQtaYzBQ7UXtIzx1iGp7m2QVAWUM6qzqBaTOhExBiw8vrazWRKOuNhgUZ7L5KG/jHMNVEq4flyq+uswRdUZUnUc5Beeg8R71IfK87iR4MthECArysmJNDjXKWN0IlA48e5GVdsJ6TtQVDKulOSqYentwj3Xg+MMekeWihx9Bfn85z4v9fV1B/jbFaCL5CdkT2SHLK8+TpKZpATtqHZb4vLk9nViLzqlNwP6jPN4GQNVZoZ1lnz1M1+XXbt26e/VEfo91G4rAq9FBPBPvzZFQBFQBF6bCORRYU02RqH7Bk1kUjgG7JJsiUn1vkYZ8HXL9MhsUCwSUlmsk4GhQRkKDkqbr12ejj5lKASdub2yPbZZlvqPAXUjIxvj62SZ9zgZzgzJOLjTEK2QY/0nSHe6U45znCjrc4/Jpy/5nHzv8W+iKuzE4MOsjK+E9feuoKSmhZF4ukyVN9EQFd+WKinWQ51iAtbaTWFI3o2IbRf0kAM5Q+tgRTcKHrN3AI6FOSdYHRbxxvxG3aMkY+csYIDfwUZdaDYnEtCILyp+qHzEPZCLgxugE4m42ZZB9Xk2Ks7UYQY1PDptXDBK0lBDeL2EBxVyVrxB56CaSBrW21ZU1NMxmK/YC6B+OCTbkETCj4S5Ccn4kAuSeKicd3skMwuUjjpyp6EqUs0kPi/tre1y3sfeJCdUnSS/6/6lvH36pbKm/y5pcDeK2+KV+4fvEgeqzKPxEfHiJWdnfqssd62QEUgE7spvk9Pd5xplFFb0tSkCioAiMJUQwJARbYqAIqAIvDYRIDeXkm7e/gBsqZGIwoKaBiDh2jHoM9tlOA5KBIxHhoJ9snnDZklFwb2FXvQs51xUQh1ylGuZkXZzQeJuU3yjNDvapD/dI33ZLjnWc7yEUUlNgxNtQYLXndov00H/2GfZIW9Z9naJpKICYTwkspXit0BpYwQVaiahUKyge2AetIaUP2740BUJGI3EqGZhk3hNxAzQizVAGg4Z+sS0IYlh0CF5yaMzek1yXS5jRyk7trQD3Gm0kTk9xkKb8nZ5DHos4r6jlSHJOjJC10AXeM6RxjGcM2rcE5M10GBGpTgOl8GUJ2E0s0s24ym8dGRQQU5BccO6A3J9oHFYh2DosgcKGuNWUEBQye5A4tyE+3FnUc13SGJHRubPny/fvOx/ZMmipTLfu0g2h5+WDs8MSYKuwWpzpaNKelJdUhtrlEgX3BQnsrIE9uk+i19Wuk4HB90tC2xL5Znkk7InvsPcl/6lCCgCisBUQkA50FPpaWhfFAFF4LAiYIMKR+P0JvH0BqVohZwcBsYJ/tWzZzEQD0VZd9YjWTjrNfW1SzgwLoNPj8jihYskDKOVhd4lGEi4SRa4lxgjlQAoGm3ODlnkW25MRS6ouQRUCtAZUPl12bxwJ2wwih7T4Wy4T3bLhe1vk6eG18EMxYsBeDAdcSalflebcdqzIHmnygUHCtoTTiP1lg2mYcVdbeTk6GRoA7WksrNeAoM14oMMngtKGV7IyJXL2DngZshg4wDCAvjVlKCryFeAD31gQCPXV1gq8CIB6gbk80DQlqITes24PvtAmb0idKDFinqKtSiB4WrJ2NKSGcDgwDC2AypnxHXApTCHOjccEymVV+DgwI642MdRBa8CjQM7zmqdLV/85H/KgpqFEs5MyNmN58uG0JMHKuqWrHTF90uuCAWPHCrdQxXSCaoGrzmcheU3nBQbbE3Sam3HC0cA9JYEXlJOkg2Fx2XHPXuUA31Yvxl6MkVAEXi5CGgC/XIR1OMVAUVgyiJg81tX287MSsGdl/C0UVMBpmoFDU44MC8B0xB7v1cGq7qlPtlsZOKGto+Ku80JXjEMT/DnntCt4oCV932hu8HdHTeW3X3ZbuPQd3f4FpntmiePxR4UL5LooVy/RAoRabZPk6fzT8jiwHJ5Jv2UuDJeScA8JW6LYNAgKt9LusUzCL4zplmYlIRmDRoVDSpwRJvQTyS0VA3xIGFOgxudCkD5Iuk1BiolGTtOWX3OgubBJHoYgxZzcP0LN48ZukfGFTcqHi4k0IMLu8QNabyROb2maky3wAScAvOBrEQgR0drbToHZsGNTk+kJIlKtHdTjcSXjUvwEfCxlw8J1TWSs8OgeACYBrwQzIHaB15MoqiMX7DyYjn51BPFWluUlfWr5L6Bu+Qt094lf+q6GtrOx8ie2G7ZHtos0zwdcuuuG2VGZq48lLhHVthPlB25TaBxOKXe0iybUk/KUY5lxiUyBX74zsw26c7sk+H7YQKjgwin7PdMO6YIvB4R0EEZr8enrvesCLxOEPAFfMUFF84WL5LVLAbw0UQkCZOTIgbA5WFFHe4YhmIFHASjLrHWVYg/UgW6AmgLsKD+wuVflE2JjXKq70yJVURkKD1gKtFui0e2Jp6VoLUKVI5ume9aJP2ZXtAPfIYe4rMGZHdqm0yzdsj+/G7JbBVZu3sNKso2SYPCQNtreyc4yP6CxO0RqRyrlbw3J2moaQS6a5A8F4wsHF0PLXQweZFtfDak6jAoMAupuiKoH1QcIe2D8nVxuAiS05wKJIw5SxbcZgtUMqiUYXHA3judF6phFPKoOsftqNYXxNnrM9QMx35U6WtT2BdqIdOhBkJDFPzxjVWJs80mX/6Hr8n+zB4J2qrEhhGVY6gmN7laZTQ9gio0dKhtHql218qtm24UkDdgkw5bcPSl0lIjp9rPkFBxQsZlVBY5lj93p8+knzTzixxHy23Ja+WezzysMnbPoaMzioAiMBUQ0Ar0VHgK2gdFQBF4RRCwVMpq5yqMk0OyPA4bbLr2DS3pMklyFPbTlI+jlfZ4x5DY+twyNqNP/GNI8ponZN3aJ2ThUQvl/sidqJA65Lqxq2Se8yh5DCYrd0/cLDW2GrktdB2SRrvcOX6j9OQ6UYleK7vi2w2tozfdJdMcHbLVs1Eai02y3bYJVAo4AToc0rlsm0nixxcMShL6zeH2YVTDQWuAVvLEjCFDx6D2sjuCqq87jEoyJe7Qv2kD4on4ZXwapOpK2+zQWkY+PgazFF9vjYzN6hNbxikZJOphGKDQNXAAUnoVeatM4Dp0QuT5YnWohg+4ZaStTzxPQ+u5fVRsYdAzYLCSmANN6B6vTBzfb9Q3wiuGpYjqdrYmI8mamPgKAVl+6SL55FmfkQfH7pVGVzMq8AG5a+Am6fDNlj92XSUB2KZvmHhSuru6ZXhkRDZmH5czPRfIrck/ySr7OXJP6lZxYSDhTcnfQx0FsngVo7I++Zh0F/bL1tRGY62+LvmIoXsM3D+qFehX5BuiJ1UEFIGXioBWoF8qcnqcIqAITHkEWIFefNIi0C6ckvBFxBuBGoYbyeMMyMj1VEL5YgyW16jQ1oXFkXYJxtyJx+kRn8sn8Yq45FJZ+eSF/yIDjn6Ypfw/9t4DOtLzPu99pveCwaB3YLG7WGxvJJdtSZGiSIqkSXXJtuQut+vYyb1x7Nwb+iTXcc517j2JHBcpVCRLFGmJvXMrt/degQUWfQaY3r9v5ptyn/dVdJyc+CSSTIog+WIOOQtgyvc9Ayz/8/D5/57NKJrJSK5kcaZwAt3OXhnjuDt4H4fmq7Lae9SxERPaNaz2rGcFdUY6176aD/lGDkf3nUApX2CMg8xn1gDmtTwcKbcsNRGLjaJ2W9AtxFDvSxNxxwvLtqXGhrsss9KZUBLBFGvDebE5LdJNFgUqookwweG6eY5LeaE0XORJC3e5QMqGk7zoxNAP3xjoTg3OEktQtBKd6jIscfKbGzVWhZOc4WDJCpcta0aN7nhNZp6NnpKsAS8H2L54PY3PffEL+ORdj6JgcAGRPdsC1acbZTQ7w0iVE2h2tKLIfPNMchrJaApJxOBnBbrH5EOkPosdjnsQry4hSLe6VC3J+EutWufwHJPZ55vaBDrpXp8qHcEaxwaWulhwyXQWf/fPXlQO9LL/bVMHqBT4aCmgHOiP1uutzlYp8JFSwGF3PNnX3seSEuLi6iZmhCsy86u15FERTXwcImtegwxjDqiaHTnmh10ZOq+tcTg4UFeZET6x6zQ2bFuHc/oJ+GlpH87tQ7e1DzcrY4gYC3RKXRjTriBVT3JYbMKiIXLQJGBwKG6yhDBpjHE/z4pGLx3cGw0seudkMyJnSkR7pkkIIYt5ZYyDK2MTXCgstme5eMgBnrELc5URDi75ZYdisPL4RGbZkXPT4bZCa82zIpzHPEhmc4xLd51ZWdettxRQ9mqoicIW8pyrNtI+mPU2cYmywjcEmrkE8ywbBQdzELlmfYR4vYQD1XbGNEgC0UczqKxkzIUXrScPk68hudH/9A//AJ9d9yW8Tpf59padOJM8CZs4Ly4FnkoeR7S8gMu5s6gvmnAwsRcj7rXE+GkcnGdwi+1OFqKcItGkJgdoG/F7Z4j8KzFjbmW+vNTgmwpU5cAtIjBZZs3rXC7kRiWu1S5iZndEOdAfqd9cdbJKgeWvwI8fsFv+56KOUCmgFFAK/HcKiByxwMCZqiak+hc5EpJ57CY5g3XVsl7bUoU1zrY/Zobdcb8kQugmDtYpLtNpBrxE0NXX6fju3z5NvrITpXoRndZeFLgouNa1iWxolofwkqpyeDYFcL10GZP6GHPASVzMn4GbuWiL4DezPMRd92DTJ9dDn6yi4irLYTlQCUn320qyhcaht8CWvwod6KqTrX6BklwC1HyMcJBQIcgauTCbB706YkTVWTUbFyOXYFg5LNu41Octyfvl2DAoht8y68JrJqLlMg4YfINQmeU5Me5hY1RF0DrMcw75PWQ4jpP4YbDopdbENxSs9q5WqnCVPWjvasO/+fKf4bHPPIIWSwfOpk9jyD2MeImlLYyweC0B3CiMocPShfJ8Fbkoi1vqQdjNdoxY1iNWj2Kj7VYkanSnTW3YbNuOiep12CzMXTfqyNZTGC9fQkSbwzgXBveW3kSUefKLBgfxWhUXy+dYtFL6715T9YlSQCmgFFgOCigHejm8CuoYlAJKgfdEAafD+eRgYFg60HU3GcaMKlgNcpjdhnSa3WkfrGwJlDg3Op51d51IOTYUksxmzdtQb/vhEM3yQWwMb4XD6UCmnuHCXIDEjais897muQ1hW6tE3G3z3QoXaRwPBB+R7qoY2Et0YQecK+SynJ8M5PYNLZh/I4ZqawXhbBujExxYLWwoZAtgOVRibMEKR8XNAbpIOoaXmWc/nfAKvLEg67xNMq7RYI5ZLPpZWfVtJlOuIpYCOahXmlhywpx1ja6zvfTDQdmI1mHKWWTroiXNc/LX4J4iDo/0OxHDMBFpZ3SSIW2n4+ttwOZjjGRex+/9yu9j0/BmuVz4ePdnyXI+D5eN7YdsQZzXZnlnyLZGyoGlzCIGHcPImFLwW4Iyy51FBh3WLizW59HLLDifik5zSTrzVg7YJua9Wy2dGLSvZDSmiNtt96JurmGVfR2SjSX0WgepcxCxxiJm90SVA/2e/IaoB1UKKAV+WgXUAP3TKqfupxRQCix7BWwO25O2j1fhyHsQ53KdXXPSkV4k+1lHhU60QMtx8pSNfPYCW/p64qRTsLKaBSfCkTVFbKi16nAWPWwnPCGZx+YWMpdJ4jCZzTic3YcKyngnsxuFWg5T+iTm2UooIglHcwfQ4+jHrvSr8jpjJIiXs6DN0Q7behavnJpHtjcObynApUXi6MoGBB8638fccoJLdSsX+bmFx5ZAMZiT7rhYLPSQCb20hgMsox0CYZcYjjC/7eDCIPF7JIoUmnKo0b0t59ksyD97T4VRXMfM9+lmlDYS4TfJKvBgiQ2CRZg9JhRG03BMe9gkWER3Uxce/NgnERz149Mrvoh3YrvwYNdjeGnmOaxv3oxIaR6nEkexPrwRf3v56+gtD7Ng5gxutd+Fxeo84rU47nc+jJeKz+Iznl/ErtIraLG2YYYLllOVcYxwCfMUFwVFBjpisPCF7v2VygXAMGGsfhHXNWLrGpOYoY4LtXlcLp+h259Hal9BDdDL/rdNHaBS4KOlgFoi/Gi93upslQIfKQV8Pl9j5IkVpFM0IcPh2FF0kbfMoTIehI1V26X2HHwsL6kxyqGHC0TMMQ4RYJU2s7ciG+1kCYpp3g7PKjsdax8pFBqeuP9TWO/dghOFw7in6QHc1G+g2RJGyBaW2grE3ah7A45k97NdbwumypNosoZkflq419e0C2gzd2Ga9zv09AnopFq46qLlj1g9jcNszAsjQEeYRS/e+SC/XufAr8njzJOqITLTpXBeLgEaLEYRMRVbyQYLYxgVcxnVOMdSj0Enm26zaA5MCu4c89ULXpR7GOtwcFOS/Sg1b0XeV2gxW5nGv/mdP4N30AE3w9l1xitEPGXAuwJjuauwMHJR5rJg0BHEmZlTsOSZvbZlaFj70GXuQSsLUOpcRlyoziLPRctKtSwd+VkOzrfY74STdd279dfwoOvn8Jb2Mu523s9s+DhjL0H0ME9+1biELkZjpvi1AetKzFZvolQryse9XD1HjN1BtUT4kfrNVSerFFj+CigHevm/RuoIlQJKgZ9SAZvT9qTj3oZs4ouvm5EYuwpZyGKpsMgqa1GlLSIdsbUzsmQltWpJuqFaR07GKuzkRqdHWCJCpJtgRnt0H06kjqBYKsIb9LFk5RWsd23BD1LfQbu9C8fpOovBWuPw+ULqe2wmTGJ//m1GGAbxdOIbqNdr8Fh8uKidRbe9H8WVKWQuFhAbnIVDd5IFrSM+MA+H4URiDR1aUeU9EkEhkGUDIeg2L3CvzorEqnk66GWWmjSQ7YvDOvVDh918xYniCDMVZEmLpcTSqgycdJy1FXTaA8wcr+P58YHKXXnUOwykZ7PY8Rvb8Cdf+FNcrp+TOLoWxlG+P/sdjATX4hsTX0O3pxdnuTA4tnANetzAocJufNb3FTxV+A/Y4rgNB/S3sViLyOH5gL4HO+w78Wzp28x/u7FQmWGrYwaX9XOsPNeYH+/BG8UX4GPM40TxALJI4yivIxy8K40yXi59HwYd/aMlfq0xhwuVU8hWGQbZX1QO9E/5O6DuphRQCrw3CqgB+r3RVT2qUkApsAwUEBSOtr5W+GJNMBWtaLveA+eMH36WgIhabE/Sz6wwrd4KEXJ1M3xzzVz6s6D5XBdsZCl7F7hE6KSLy6/VFgC/OwBvNoDkfBptnS24O3Q/ws5WhE2tskRE1FR32rvpvoo66gCeCH8Jo8Sx9bkGscKxmkUrBrZ5b0XKSMtFul7rENZuHsX4vikWgtvha/jRku+EpmloOdeLpmgL3JNB+NM83nhAVn43bMw+k10tKrpF1XadldhmjYUoKZZpM8phm3bBO8ZK8JgdzmkfGml+n9nmOl31hs5Kb97OXw7hP/3O13H/jgcw5BtmgsLAKs8aZpzphNN99nE50GvzySKX0gIRdkXGSkxuOsZctGSWeZVjFD7Woqy0r0GLqZ2u8TAdduaqGYfpYd25vxHEfe6HqakV6x1bMexYI93ublufPM8Nji18I2DDNtftWG/ZAt1SQhe/5yLQeofrHlmJvta+EfdbHpXowJt7ZtUAvQx+n9QhKAWUAn+vAP8qVB9KAaWAUuDDqYBYtCv0ZpBmVbaFy3ammhk2h0U2/Zn5Z7lQaCbijrcrN5WQHF1g/KGC1BZeE7mWGY4TB8cqcDrB2roctIKGePMiKRZVvHLiJcSzMWSqKdyoXqWDWsHz6aexL/smLtFhTlRjOJzfB5+NQzq3EgX/eFGP8Pu7kK7GkWdmOl5nHpt55ZX39xNJZ0WBxI2qmY2JXgdit8ygHqwifuss0ix6EfSNbHdClqBUyZFOe+IoRRnZ6CmDuQlUOplr7iiivDrPIpS0PA99lPXcGwvI96dRb+F5Labwud/8LJ79t89h9/wb6GO19mxpGhqZzJcLZ3EsfhCzxZs4ljkAo1jF2enTqNbrklG9RJdZLPiJpb5sLYOJ2nXcZORiujaJI8ZeWE023GTzoliuzNFZFvi+KrU9XT6KPLF+l40zJHCMkcgRxxF9n8yei6x2yZznbY7zMdMo8HJQ383lww5JEhE6e+nYqw+lgFJAKbDcFFAD9HJ7RdTxKAWUAu+aAgLn1uCqmkWzcmEvhtTqKJaG52DY2ajHS6ozRhKFSUY5mq/Qdc6yTKXO/bxqA6W2HFxx1nMTKWdLE1nBWLJu8F5JHcVKEc1aG54681eYzt2ka0vn1dmP+32fRLO5Df22FdAZ43CYnfirpf8Xzya/xezzFRnhuMV3B+YZWbjFeyeDyIRfsOVwdfMafOyLO9FcaoHuYJFK2Q+fQSqHmbXfs+RRkyldYf66zKXB8kwNBeaPLTEHamwGNC2x3TDhoSttg/tCE6oBVnnTcS73F0j44GIiz69uq+H3vvIH+Pzvfxa3dO/AifgRbApsh0HHXNA7fKSKxLQYer0DyCzmEFmKILGQlM8/YBtEopHAKhu5zrUCmhAm0q4NxXoBAzzP+fpN9Jr7sVSLItQIo886wIXCBWpSxS6NS4TmdlziomCdcRM7LzeM62hGK06WD+GEcQj7tV1oo4sd5mNeqZxFr2kQ58unpcO9UGaMhTXj6kMpoBRQCiw3BVSEY7m9Iup4lAJKgXdNAafN9WRvRx+CM63wLzTLGIQ/FuLCnYVRAhtcpHOIhUHReGfXXBJnF+DtAnNEbRDrJgpKRKGHmdEEM2Me1rqdDX0GGw053HYUEIy24uD0Xjyw7iEZP6iYdGz2bUOS3ONWZomHHSP8cxy3++7lPzsRqc3JZUMPK6yjlQUSOTqZSW6g2Cignxi4G2Qkt8x0IxlchFcPwNC50Ei0Xs3NgT/BhUG6wRI/R8QefHWwxwT2hEsAOWAiycLoJMaOC39Vs4EGM87anIZf/9Wv4nN3foHDfwn3tj2IK/kL2Bzchkt0nBOVJVZlZ+kQs1Sl5sTlyctcCuzDdIONgNZulqQQcWcqcygeYpY5hQEi5xJsFwyamyV9pNzQuAQ4xEHcwG3unfI2ax2bJG4vX8tiNR3rpUYEIxy+Law8p/cvy1dE/XkfMXVZLlVuZMTDZiGHmo8xxMc3k24yaFuJdbZNsqRmAmO4uVtFON61Xwr1QEoBpcC7ooByoN8VGdWDKAWUAstRAVFPne6i8zwUxdyt11lakkOiLyIP9UcOtCgZWdrMBUM6zYWWNAtNikgORFg6UkahIyOX9DiR0sFOQOcwWeLyYcwThT3tQaJ5iY5sM/78rT/FjMHoQ/4A0XYHOCZa2Fj4DmaNKUQ4KF8leePp+FM4lzuNPZnX8b3EN5FkxOOl1LO8dwvSegpXCxcxPDCMpk+44as2YbZvHEwyIO/gMbhSEqFnkKJhXrRDW5WFZYkFKQEDeUZUhNucuz0Ok51uek+By5I6eugmb/+lzbij7268PfcaPt/7S/jezFNY592I48nDGE9fR5e7D/vniOCbLeHA7F7SQpq4DDjDYhg6zta1uErnuI0lKVdYaOIxeeWyX7y8yIKUCM7qxzlE6zio7cEMYxy7Cq/iun4Zl7gw+ELhu4xxZHBE24cYIx1n9ZM4XNrL+y3iNDF2rXSc92iv0+pv4Jx2AvtYoNJj6sOB4m6swigu6Kflc7/OhUNRTKM+lAJKAaXAclNAYeyW2yuijkcpoBR41xTw+ryNkcdXSATcjx7UJHkWP/qMMxwvhe40fPMhGCRbmAyWi3ChsGZni5/mQMXBFr+QRuZyWbb7eaJBFPrJUybizmv1w0qWso2UDnuPBQ9/4mFs99yOi6WzbCrcKBsL09U0BlxDEg2XZmOhoHBw5U9yo+dJqRDYuyIbDrnqx5x0BPc1PYynTv0NglMtiLAe21oki5oLjHprQdJAasEKKSJcJGQpSpUDdIPxjBpjG6aElcepo885gLaRFukqhyOdePzXHsWO5p1w8LLAxr8T6UMI2kK4kb+O0oLA4BF7J6IcZhOa662Sfz1jTKLXNsDoRgztLDtJcqDeZN9O/rULZ40TuMNxL2MZ57DRuY2s5nOMq2jYyO8f0ffLc4vXl37oMDfSHMRH0WQO423i68RjiXNtM3cw+jGDtZZNvJ6WGesyGyCF7u0c2EVboXC/RfOj5Gz/4QlMTEyo/179/Y+t+pNSQCnwPiugIhzv8wugnl4poBR47xSw+MxPWh+swplzIzkYlfznVN8i3Fmi3XjJd6bhzntluYqTcY7kYAS2opM55BIS6+dlvCK5mjlcTxUxYuVE1CM/kITmYWMgC1eSHYtommnD0qpZ2OfduGI9h6CPJSHVObyReYnLhzW8nHoGS0YU46XrdKH/M5cLl/Bm6mVWWF/DG6kXuCTnxzX9IoflOTSRJX04vg8bGGuYbLmCcqaCYnsWel8BJo3PfUsMrskAMh+LwJKlEz2Qg74mSxoH4xG317Az+HFM9V+Do+qCzvx0oimKmfNzeCn7DDoCHfiXl34fXfU+ZCZzOJjYi0dcn8XTha9jp+vjLD15lSt8OXSb+rFffxNPeL6EFwtPY6tjB66WL2OqfgMLxiyOavtlq+J5usrlho5DdJab2S4jFgrfKL0gYxtvl16Ek8P2WPkKGc8XMaZfxfXKZUY51uOV0rOy+vuKfoGRD9JISOo4q5/AqG0jfqB9Rw7px/VDKJnI5SZPetE6D/1QHfF4/E/eu58U9chKAaWAUuAnU0C9o//J9FK3VgooBT5ACogilc23bZaZ5x+5zP/Q4VdZfS1qtB0ZN/LdSQQm6cS6SMNgc2G+OcUSFb9sLhTFJa6Ul9GONAQjumLTZQFKOMjMNP82dbMQZXD1EIZW92Olcy3C9jASegxNjjAd1TrxdQnGJJpxqXQO+UYWSSPOgdEj2/Za0IaJyA2i3ywkWrC8perFi3ueR8AIoayRtBFkuclVrkSGeFxFN7SenKzH9jn8GNm4GraGQy4pukteaO4il/ZA8ogZRUsBYa0VI58YRiNlgpPHWKjmZOZYEEKuli/iHu8ncKD0tiwx0fnGQgy7n/V+GefKJ7HNuQPXeJsGc+ArLWtwsLwHO50PYLf2GgRqLmtk0GnrxjWWoRTZGiiqucXgLDB2NyrXWdfdTgebxBCO516zn1+7hlucd+KwvpethY/gVPkYgXgCgWfCTbYVilr0VC2FXg+xdm4nmriY+Ge/+ee4evWq+u/VP/TDq76mFFAKvC8KKAf6fZFdPalSQCnws1DA4XA82dPZw9nWRPybxkpv0jT+gY/MIEtS4n6UWvIoBzRJrSj0pGSMIDOQYLwByLGwRAyRRWaOa8SraZ1Zhh8asLktiHuj8GWCSLYuoXyDueRwFn3+PhRJrThePCxmaxzI7cKZ4gli3hZxNn+SQ7JF5qMXMxFM5SZxvXhVOtYJc0zyoNONJNYMr0GKj2m+4UCOznd9nY66wdbE7gK61nTgzrb7kB6Oore4AguOaYnAmwxep/usIeadx6JjHul6AudZSBLXlpCz5BDlImPZVME54yTJF63Qaxqhc0nZCiha/2513s14xlken5UD9AloJqLx6nSCmSMRfOjrdKP7SOY4w8G329rPx09yqN6NYesanDSOIGQKS5RdqhGnQ13GeeOU5ERfMc6h2yJoHSyG4aBt5RuFKUZFSqR5nK+d4i6liQ2EUwjYmlB2ctwm3u42713Yk3sNM7uiyoH+B35u1ZeUAkqB908BtUT4/mmvnlkpoBR4jxUQNdfJnqjMOZft5NDxI9kXldciwpHsJtOZF+HYNkjD0J0avEtBmEpm1ImyE0xoM51ckc2tcNlQYOEapF0Uwzk0XeuAHsrDPROApWrjylwGpopZPkbqXBZ/uetrMvKQr7LxsKZzca6DzGcuIXKojjZYeb3EmEgsiWCRULdaB7qMXtxnPEoSiAUr6qR3WGNyaXEgtALBPpaosJJblKLcunEHBtYNYJglJnFrFE3Fdpk7NtdMrNYOEB9XQ3OtBSZGPNLXCtCukeTBcwsZrfINwZBlFVKVOJ3dZi4IdsrGv22MaVyqnMFW2w7EKotyuW/YNkKFShyMRzBWvQwvK74vaWcQJaJOONRxusphcyuOlPdhm+N2TFUnUCOfutPSjYtkPveahmQmut8yhJP6YTYKZgg2sWOCfOge8wCRdRfkmwiB6HPVXBgKDAsLHyPNo+wiLOPh4BOIMgO+wr5avl7qX0oBpYBSYDkpoBzo5fRqqGNRCigF3lUFnA7nkx3DbRyAOVzGORjzIhoGq54ynGW27vkqcObdZCyz0rts40Jeg9dWeNlU6E0E2PbnY2SD/7D1z0HMXWC2Fe64D5WwBv90Cyp0q2suLhtWuNDHZUMzFwrF7bLuJIaSa+AYsmCldxW62UwYM5ZQYuNec6kV5ZQoZ6mRhtyBvDULb80ns9C2hk0OqhEzsW3mJP9h5rnhgn/IgyVHBGt9m6A5i+gq9CJOEoiId2RccejWEnQb3xLQLQ40Qrg8dRGYNsMIs+6bzYWB623oGGzDVt+taLIT52fxos3eIRF7PZY+ROpz6GAMI2xlo6LFCuH4HezrAABAAElEQVR+t1jb5BLkKLF0TrLzxDKfQNWJpb8uWy8CrONO1uPotwwLEh+6WNNtI55OZFnaiA8RSD8x/LrYYDhgX8HvOSQr2gkXEnW67GRP54i6a7e1I+VKkAjSzfpvD139GmvR25Ej4q7Z3oIiox9nXjuvHOh39TdDPZhSQCnwj1VADdD/WAXV/ZUCSoFlq4DNZX3Sdg85z7ykexiFYM4235yGs+BGpj2JDBv+aMsizYY/R5JZZNI4arScc51JeTvDX0ZqkC2GZEDn2lJ0mE0sWOFSn79E19ckGw5F+Up6cAl2DuaahZ5tRpc0i3kPIxXjwGn7UQS8QRyO7Ec6m8FabTOOWvbitupOnLAdQE9jAEvmCBYxj4q5jCPmdxAi3G7aNMG8MktUGGaOpWLYnL8VY80XsGXpDlzntShyyZszHKzJkzY6MeG8hvRllqBYZmXVd83NmAmjJGZGJbTRNErTOq6FzmPQNSzbAXN0hL1WHw6wyMRpcXOp8SqzxwmMV64yWjIvec2CtEHWCE7rx6A1SpjQr+FmeRzrOFS/kv873ObYiePaQZa1WCAe7ywz03c67yPG7ml83PUY9hfflvePl+M4VtlP57lflqcM29bgOjPTfU39ciExXUtiBd9o7Mm8ia2sOt+beQMhawvOFk5iTp9BdHdCDdDL9rdMHZhS4KOpgFrK+Gi+7uqslQIfCQXEEuHIE8TYEVEnohoCHyfiDCJvK/B1mQGWgky1cnEwBf88y0GYkzbIjnYnWJTCam+xVFh1GqgKvF3ZwkXDIvxzYaT7yX+eakOuJwFareQxM+pBF7ZM/rItY0e1qwJ/KcjPNQTjrdi8ZSOYrGCMow3TuIm1tU2y3nvJFOWCowk5K2kaxLglscQSEgvxcUtYYVqFSo+Gy8cvY7t2txxgHXRx+V6AbnMJMQ7OJEYja0tj7uo8zDw+gdwzCwQfYxFWuuJwsmglbEUo2oFUB3Pa6Sb870/8C0xyCF5hXc2ARpEIuhJa6RhfqZyXEQ9Bynhdex6Pej6L/aW3sMlxK5sTp8mGjsNBJ9pgZbmTDYtisA9ampiB5sIfs80LJI8Ih79MNrRoNwxZw3JJssCSFlHRrVfp2puDsgzG5XfAaXPDa6O7T4fdbnEgYA3KmIdA12nE4nXau+mUuzGhjeNvf+vv1BLhR+I3Vp2kUuCDo4ByoD84r5U6UqWAUuAnVEBg7Ow7aTLb6eKOzrLRz0C2g5GHtgKyrSlk++OoeivIt6eIqLMh1c2Bltf1GrFpxNZ5F0JIruDyXLQZS2un5WCo+QpIrInItr3oumnWZleRWkGXumBHqTODUnOeiDkrYl3zcI35sbBqAnNHI6gMlTBmuoyWeht2W15BN3Fy37d9k3xoYME8jfPmU/Bqflz3XMCjo4/jguk07my9B5YOE07MH4XNbsXJ9nfQUmnHueBxWTc+McnHNt+UjYniGFwZL8tiMiDyGY0+QxbBCGd8oXcKrqwHsYFZnLx+HFPucYwb17BYn8fu4huI1xZxQjvAaEUCx3g9W7kp88l7S29IlN87hd287RysjJgcZjlKl7UXb5deZmPgMI6XDnK418D3Jzik7cY22+14ofSMZDsfLO+STYZLRPfNNG5iOLAKJ6sH8PHmR/FM7CnJxp6pTONC4bRkUe9P75LV46cLx7FUieIMr2NsS4ztySgH+if82Vc3VwooBd5bBZQD/d7qqx5dKaAUeB8V8Pq9jZWf7peucc1Sk7GLmpmlIbRxTVXGOciB9keaYbB10NJgEQkXBUXMo2ElMo5ubmCebjNjHkFWe4vPyYqDNUcixhDxc8xCl0JEyVlMqJoMIuNY9c2oh0aGtJbVYfITGVd2InCjBdX2Mvx+Pz5/55cwXr2K3jqrsc0pKmNCwrSEKi8VrYJ779tJB9nKYdmG1Z5RLOnkR2eJgkM7jr18AjWjjvngFJKJJBbnF9k8CFhrduk4i0IUi5UIPL8NnroXFYsOO5/fJGLJJQ7UfhaTVFjGcj6Ax778CIa6BjkQ2zFdmcRK1wgulk+jwiXA9bbNeE1/Do95P4e9hTdJ3BjAmHEFd9nvx83qDRD4J+kbEWOOi4wjOK4fxJ32j2HemMYsy1H8JHVMVSaYk+7homFMMqJtPIia32C2uZOD8SIeD30eF4pnsca1VrrOS7UohnkMP4h/m1nsLj5GExKsQN/g2oJJou3++qtPKQf6ffw9Uk+tFFAK/I8KWP/HL6mvKAWUAkqBD4cCAjtXdxI2Z+FAzEXBmoMIuKYCYxYuOOnIcmqWsYyKU4dV5yDqMST/OTAZRmZDHHadbGUnh1uPjnwoy8/tKLt0ZLrjMLw6ir48PKKUhVGNBofbxgIpHJ0l2D021mlX0LhJssf6GbTMdmFh4Ca+9vWvYe2vr8CV2kUu+7HR0M5Kbg69f3THk/jm1F+RG92GF+f+Dqt8a3AqfoxDuQmThQmZ4Q7e1ow397wJz5WAHNgRrsF+043sujha5rpQGszCnfPxzUAFOWeKg7UFmTDPocaMdhuvUy4O+2bYt5SwWFogOQRE2kUYLWnAZwQYt0ggZ8qiu9ErmwdF+ctV4zwCpiYSqjuxW38NW2y34hJxdK2WDkQMZrZ5adBCP0CnucFFzRuNqxjBOmLsFhhRscNiMyPjSHIw1xEtRDDqWo8x7Sr8XCA0ahXMV6aw0bsN54unsco5ypgIb8uISLx6HF12Vnvnd7M1senD8cOozkIpoBT4UCmgMHYfqpdTnYxSQCnw3yog8s5llp2ImIbmLsE/G0ZN4OnsFWQ643JRsOzRZFyjxMa/HBcMK14uAnoLDDSbYM87UKTLLEpVygE6yx0FlLlAKAZyS5HDtYvMiKQJepHO9SztYCLu7AsuuI42w7Jkh/cGs9dRM+kbxOSVeLvhHM69TUIG8w7bBrdjaGgIn974BeQqOdzSdDu/boLb5kG7uwMLpTm0kpSxxrcO5oQNW6s7UNfpout8PPKqidxAhc52a6MdroATNVsVNl40WxGunBeEQsNY5FA/yRVKIu2cUQ7XzHLTQMZF8zlEihHJYr7G7PMc+cuiSTCEMG6Ux4jaK9Ky5v+gZJZ5LRsCDxv7sMa2TpalxDlYC1RepDqLdebN5DyfhE7ec73OjDkRfAE0ocY3HevbNqFur2On/35JIbnFdQebEh/gYNzDMpkQrhQvkCsdlK2MSS4Zityzmc+5M/BxcjoEr7uBRCXG+vHZ//YlVX9WCigFlALLQgGVgV4WL4M6CKWAUuC9UMBpcz65ksQHgZozWU2wcNHOVuGgy4/WiR44Sk74lkJyMc8bI7aOg6eZdd2BaBhGkw5X0iepHMKtFkO4iHbYDbtszTMlrRye6XBba7DFnKgHOcBygVBUfNfCXCrkdZXLhdUuthV6DdSCXE5sdsHiNuPX7v1NyZ5+vItRhtxpdLq6cCl3XjYE1hpVRjcWMeAZwpWFS/ClmpG2JNBm68Dl167D6jDDmfDC2WtDd6UfWT8LX3g+voIfmpWLeloT8pYMjByHbZ5z3VyHVSNmz11B00QHSmwwDLEN8QvdX+bK4gL6rCtYsb2OI32DjrcFt7ruwnR9kjGNXparBHibKAatK2nWWzjWumGz0qnnsCzenMQai1wsdMiCmRAReCVrHiPhUbrIItJiIYHDI9sI13u2IEa3e5tvB/y2AFa6R+HigiC9fdzm3ynJHjEWzFgY9djk3c6BXEMLUXaPNn9G3v7gy4dVBlr+1Kp/KQWUAstFAeVAL5dXQh2HUkAp8K4rIMgbAl8nzNR8II1sXwKpgUXo4SLmN95AZNsEcgJn1xOHqcgylJYU+cwsVvEWUQzmUGZ0I8WFweJAGrmuBOMeBeQKWeQZvahO16F35GCf8EBfkQMypGD06Cj0EXfnqaO0ISnrssvtLFKxlzDasw5d29rw1O9+Fy8mn0HA3oRnpv+LXMi7mBGO8BypFs04lz4NbaGMo+OHEKq0Id6IIlGO4RpjH6mtETjbGcm4awEeDvtFZppF5tpuOLDYzUhF1sC8aQaNBGkj3OsTi5INOu7ZFaSFOHl9VxQmXwM3G+P45um/Rqu5g9nnM5iu3sQB/W3MGlPYx6VCUabSYmrHYZakrLVswkX9LGkbaUwwj3xdu4wsq7aPVw6T4KHJKEfWnIaVDOxIjYuTZDlfKp0l37kTJ0uHwWQ4jucPYLx4Dc8mvoVvRP8jzuSP4YXEM5LkcTl/BtdLl3G7b6ekdghc3pn8CeTJiP7e0jexUJx/138u1AMqBZQCSoF/rALKgf7HKqjurxRQCixbBUSRyrBvNWyaHbYql/OYaRaFKo6cC6GpDtkgGFgIw0ryhk1zSMydM+eWS4YyO0132ZkVn/MSYRNgni42B21Tmd4Dl/Mc0z7YCkSyRbyw5sVKCSMcCRa0eKqwlGzwEdNWuFLC7/3K7+Ou1fdgR/guFGp5fKb3F3GzOAar2QqLxcL8MEv4HORQpxjNYNug2WxBJ5fwsqYk2hyduMfxIItN2hF9KSUzyd2JATrfdbgMj3SG9Sq51ONEyxG552SRi6gaF46xcM7NVjNash1wBOwIR9rJtaNrbq8iNN0JI1vDY72fRr9nkBXcLeQ63wWvOUCsXRvarVzm459LDcZZmHNusXCYN0exyrJWlp30WfvpPjuxKrxGlqo0s6Cl2daCTkc3VrlGcVvgLnisXuygw7zVd5ssSXmo+XGZjb4rcB9CvL1ACbqsHrjpRq/3bkGhkcMW7y3Snd7o2YZN/q3y/w688/JB5UAv298ydWBKgY+mAmqJ8KP5uquzVgp8JBQQDnSij64tWwfjI7MITXQi15uCvchmPZtB53kJroQHxeasHDqTo/NwxPxoOGryay1XehAjzs55NsglRI3DspNV22ZoAzn4rjUj84kIvOeDKPbmZYyj1l6RqDzPzaDMV//2o7+LqewEQgHWdTvb8Y2Jr+H3Vv0hnpr4C2wL78CJxBEO2QGY4mZcKp/Dz/t+A9+pfgO/7PgdLu29TjZ0ieAPO45U/hJ+hx+pT84gN+lBZOUEgkstbEX0Yy48iebL3UitXUDTdAcxdlxMJMmjnqyhMsrWwvkBzAyMIZAKY2lkHqFECx1xDedXH8bVKQ8W9Sl013q53HcFI44Nsn6cgWZWcQ9gV+E1rHGsw9HKO1hXJxGjPoaL9bO43/YI9tRexe92/gu8mHiarYJ+uVB4JLufBSx2HMruwU261edyJ/m9oMw820g5KdULeJ7uu9lkxu7sa1yOtGKFYzXLUqZhajLhavGiHLj3slBlyjXBRcMapks3PhI/q+oklQJKgQ+WAgpj98F6vdTRKgWUAj+BAqJIZfv27TKvm+mNkZccQJmRB4vVCjfzzeJrgcUWUipicgGvzoGt5qN7qzHfHCKwbcGA5inCXiJYmYOzPeqCuWCFaCgUFeAlTwHVQRI4/LxPxAGH147YVBK//0e/h+GBYZS5XLfGuw7X81eRM8hnpuPqtwURdBLTxsW5QjmHubEFyXiOEfk26FqBBJnJA+Qri0IRUVzSY+pDtpFBj6cP39n9bXhLfsxEp5FYTMgGwCKXHwUppMZqcM6lXJA04Cfhw+lxMSJRkai6ipXlJswkl5nrCDSaEC/EYU04YE3b8L/9we9KksZ05SaH2VWs8rbJxcABrMRCeRYGFy4tdO9paTP7TFSe14ywuwUTxXEMuVZCr5WwI3A36oyKXClfxK3+O2QEo9vRi9eTL+BjTQ/R0W7H3vwb+ETwMZxmfGNH8G6cy5/ECqLrnHSxX0o9g0eaPoOj+YO4K/AxzGpTyLCgZUa/KSu/v/HVbyuM3U/wc69uqhRQCrz3CigH+r3XWD2DUkAp8D4qIGICeoD0DG+Jy3R2pFdF0UwnutTEbDKJGuUgXd1wmi19dJmJqBNDov1aAHm6026LH/UmLgAyUlHjcF11cBmRjYIaiRy1dABae44uqg0N1mZnOzL4/37jL3A8dQjberbjVPoYoxFDdHgjRNGNMYrRgQvpM2j2sJRlOo5gsQlV0jzmGlPYYNqKscYlDNZXyKU7vUbsW20BGXYT9lgH2IviYN33MLLOJBcTy7ieugTzKnKml9hEOLyI0IUuFNYyt6x1EJ+no2RmNjvFYpjOGLxZOuQefp51IeNjJXZ9kSkOB8riezeb6NHXkazH6CyfxBpswOul52Tz4JR5gu2CM+ho9LDkhIuSdjM2Brbi1fTzeMT+GZxjzXazLSzLUGLlJRlHqTR0jGvXJKruhn6V9I0eXNUvIG1LYqx0RbKexVDsL/oxxWuxaBi0hHhthcPilHXgY8xYn8weRYxvJCx8R2Cno60+lAJKAaXAclNALREut1dEHY9SQCnwrikghsMYoxtWIudENbdwjUURSrElh1RXDIbVkIQKM3nLDfaaaBUdWCQ9gy6uLeOAe5wM4pIF9kkvSROcnIllM5gfRqhGugULWQKQNdaPfPwxfO23/xpOqxMbfVtZDpLlgl+RsY02zBamsS64CWUOxbVcA45FL782hTZ3JyaMqxii61uul8mr8DIz7GEbYIwFIlvhMrlxt/Pj6DL3ws1iFL2mIeqZl3Xbpc6cJGyUurMw8fhC3U0I1Zu5J8hoiom0D7Kp62xftJTpkSRMku5hZAySQUzwzTXDZJhhowNdDmo4ox8hdWOK7YsmDu3z5ED3YRDDGLKu4huHBra23Mo3CDWs92xFvlrAascotnl3IMhoRqutnSznGbkseblwDpqhw83jThtxrHGvx/XiVdjqdrrV11mo0oYQh+UJfYw58AIH8OPE1MVlVbcojxEYO4M6DLlWIVlL4oGmRzBgX8E4ilrVedd+IdQDKQWUAu+aAupvpndNSvVASgGlwHJTwOFyPNkx1AYTMRwGUXYiM1zldY0DsmgVFEg6S5ktecTRiYiCjQznOuMY9oRT5nRtS8TO0QU1L9FlJr2i4SfrmI9lZa12PBHDL931G7jt47fgofbHcDF7Fmt9GyWJImukiabrwZnUCbq3BqYTrMZeYoMhPWUnR2UxsIuFuWHbaiw1IuhzsBWQLqxoE2wyh6CDsRAO7Fa6r6J0RKDftnvuQOxqHE2mZiweTRKLZ8Bb9yMQ8IF3YzbbAd3NnDaJHFWWqXi1IPcRE3LxkWFqlqhwxVHnmwOyoO15F5F8HOZbrXgi8Auw2xxcImyWLnKDG42LRNcJXnOzN4yKuYJeW7+s917tXoMOezejF6s47PsQogPt5tDvo1MvClGulS/Jz9d5NyNTS8NjdqPfvQJeGxF7yGOVey1i5EjfHbgfFi5QrvGsRweXJEUpS7M1jPHyNb4MVkT5+QrXamwL3IbFagRX3hhTS4TL7ZdLHY9S4COugBqgP+I/AOr0lQIfZgWsbsuT7s0ckjkEpwcX2URYQ74tzQIUZobzdWT6YrCed6KwMQnPmSBKa7KwJkVBShWl7rykc2RviYJYDGj9jGvQcXY4HFh1x0r8+Re/hgumk7g7/HHsX3oLG4JbkKqkMM3mwD73IN5afJVRhRDOR04jWAux6noWJ8uH8bDr04xJ/ADrHFtxpnwCuVoGfZYBPFf8Lh5yfwontSNY49yAscpVEitsuFq5iLLB2AYxdmfLp5BzJbEwNImAK8DoSZKushUdkV4sdDMakW9Cys+WxKUGMhzii4ypeFJ+lDrZUpjwo9iegVcPoDaoo+GqS2f7WOYAbvHdiTdqz2NlYxSXLGfJky7ggfZP4qXks7jFeydez76AsJW5Z/0aZrRpDrULuFq4RF0asm48yiH3GiMagixSQhF/F/8W2tlWeJous4+D9sXCaeSNPFnQS7iQP41cI0v+9SkUmfM+mN1Hl9oqlw5nSpPECDZwoXBWMqJ3p17HpHYD2b0su4nH/+TD/LOqzk0poBT4YCmglgg/WK+XOlqlgFLgJ1DA0+RprPxcH6kbdGfZOGiymeRgphe5XEfnuWqw5puhZkfRDUuMmDoneXJ0a6shNuux9rsWqKLeasDO2MdSZBGPPfE4Htv5BCyGlUWFmmwJPJI8gDybBINcDvTSLS5Uc6hUDERmF+jeluFoOJEijq7D0sWBsYD1ji24VDnHBUE+H89FRDfyyDLzuyjdZhHDGHAMM7KhS+RboZHHSuuIdIlff+N15Mh2btKbMT45LhsBdTYseg0fSs6iHGytSbYSNvP4eV51ZpfNRPRZiOETrYBem1cWwpgszE8XPIi1zaFvejVKehE/f9+XMbxumMdeJg3jEl17DuH1LOMat9E1XsKIay2ilQUuOTJiwmKUt9Ov4g7fvbisncNCZRafC3+FhI2nEbCK6m3i6Vi6IpYfxf1ulicY/8ji44xlHCWpQzQs5sh5Fnp02XvpanehjV+7XDyHtZ5NctFQPIeJTv25win8+a/+B7VE+BP83KubKgWUAu+9AmqJ8L3XWD2DUkAp8D4pULdUkRiOoG28F4nVC7BfYOnJYEFSNqxsD9Q2ZRDc143kvXPwXA9B6yICbs4FU0uNS3ZFNN3oQLx5EZ++7wvweb0Y9K6UTYUvzT+Lfzbyf+HPr/5rfLL3CZyIH2PMwkdChwXH04fwFe9v4nX9BXzK+UXsqbxJtrIX7fZOvFl6CZsdt+LN4ov4sv83cYpuc6Qxj1usd+CQthdP+L6It0uvYHV1FEuVJYQZkWjUTXi99pwsXhnvG0fQFES0iTXf/m7Wac9w0DUjdKgbizsmEbrYhfRAFMFMGGWnRsc5i57JYaRWLqIt0oPF3mkEE2Gkm2KoNdXRlGvFlVUnEZrtwHfNX0fvfJ90rue0GXKc72AByiFEy/OIlBcw4hmVy4H91iEU+SbhdO4oGw1DEllXYvlJZenrOJDbg83kOJ8pHMN69ybMlWcw476JRRazCNh1jkO0eMztvttxpXCBDGyzJI04OW73uPpwic5zh7Mb83z+/c63UajnGVOh7a8+lAJKAaXAMlNAOdDL7AVRh6MUUAq8ewr4A/7GmkdIr6iz2rpWgalOqkPaCQsrt1Hl4qCDmWbWe+suutPDFVRY322LuGTZiF13YvOdm/DQgw9xuc1Ai6MN2XJGRi4E29htcSFdZhyEWWXRmjc/wXZAFocsGDMsQemloxzFJsctWKhxyKUD3MFikmljEvd4HsDFylkM2lZirHyFLm0a97kfxouF7+Fx7xdxXD/EdsIeOrZ5ZqWBftsK3p8FLry8sucVBOh01211Lgw6MTM3g2tzV+Qioch0l4YydNiZnWaOuFqtIhxoocNOV53nanKRRmLW4K35oJl0mPJmFMt8M1Gwwcx68F964pexZXAbi1OKyDCK0u3ox4n8YWz2bMcN7Tr6nUTs0YmerkziY4EH8VryeZl7TlfZ5Milvzv99+E7S3+Dh0JPEEd3ANu9tyNSmcNq5p5dzELvzbwh3eVj/N5K1xq5OCmoHbf67uIQvhe3EH93Ln8KtwbuxHx5Wj5/tV7FFN3rf/mVf6Uc6Hfv10I9klJAKfAuKKAc6HdBRPUQSgGlwPJUoIIy5oYm4LvSjNJoBu4l5ob743BEPERumGG0avBk/Mh1JxjT4FBN57lozePX7v8txJwRfK7v57F38W2MBjYgr+cwXroqcXSHYnsQdrQiVlqCP91EvrKOZCOO7VbmhSsvoJX53zkO0tVGlUuDbqLqbqLf/gVcMM6gs9qD2fIUZqtTMvubIv5jjMt345VrOKMdJxXjKHF5WzFp3EAv2/7GjWuIM94RJkt5smmMXq0HWXsKYdZ851ktngjOwzvbhNxwCp45Lkl2i+iHB0EuGCaCC/Bnm5H2J1ik0gydKL9Clkg/Ej0q/RqcSTcMnrPL5MBU4wa6K914OfF96ZafZ245ZSRJ/agz33xJHrOIXJg5zE/q48TSXcWIe52s3xYxkwV9BmdLdLPZRniG2ecQa8kvMZIhcs+d1m5+7aRE1gnMnZmuuVgm9LCARWDsRCxExEQMXgSNY1KbQJOFTjmH8wOZ3cvzh0sdlVJAKfCRVkBh7D7SL786eaXAh1wBmq+WGResE25i25xsFAzAnCfTWeSb3WwNDNB15pBNMxnuihddri788c//K6ztWo+Nwa1I6RkOmxX0ePs42JUkZcNMJzjsboUpZsFcfJaDXghLtQiJGqOMHGRJbLZjyD4i2cpdth6Omw2sdWySS3Suhhvt5k7M0ZUetKyExmITL/yIGwmO2W4eicYCFeLceClV+WeWlEQr87DVbGg2hZFwLEk3WqeDnLKR6RxYZL9LVZJFRAlMJ+MPIa0FwWyYDnQN7pwXzpILdt0GK6vFiylSOhhdseT5+ZITDg7QNQ+pJDWWoDCXfTT/DpxmJ48oiNvoDFd4LE66xxrz2A5+vcZMdaqcJKYvg7nKNNJ0nmcZ0xARjLgRQ7uti0Uqd/Ez1p+TnS0G4AYf+zBzz7FyBItGhNdR5rO5wMk4h8g+H8zsxUzpJnPXF3A0sw8H03uIvRujAhX5hsVvUhGOD/lvqTo9pcAHUgFF4fhAvmzqoJUCSoEfRwELKRyhXlZlV+ib8m87G+Mb9QDbBjk4m7zE0RUcKHnzGGlswC/89pfwpY2/wva7SWwIbZGDq1h8G/AN40TqMIfZIrnFMeQmCpjOsCHPxMpvgufEotywbQ2mamzmc67iQmCOQ6eL+eVWhilYp81FQoLwsM11G5F1UQxah5Gh6zzkWAmPxSsXBXd47mb0wsAO5z1I1eJ0ngeRM6Xl15qsrAGn++yyeaBNltGh96CzwsW7chcyZdaSJ4jaazGhpd6Ooj0HW8UOPcjFwkwTtKYCSsUitBLfKDC+Yc5ycZJFLM68B9VgGVUOz+F8O+qdBgITrRju4zE5vVjpWSPRdIVGAZ3E2QVtTZLGMerewAjHBJLVhMTZ7SSOjvUy8rLZu52Ujuu4zX+3jK/cE/gEnHxnovNNwqdav4AluujDRNPF6Uh/OvwLsv77Ng7baz0bEbSH2Ga4E3cE78UK9yrZcChc7g3eLbxfFBfeuKwoHD/OD7y6jVJAKfAzU0AN0D8zqdUTKQWUAj9rBVg7/aTjDhPsGRcKO+JosG661MdWPs2J+FICw5/oxz999J8j2RnFbcG7cDi+H5v8W9HE5b0jsXcw4F2BXYuvY5D53+M3jsAocMw1VTFRvYad7gfwUulZbGDc4kTlsHShW9CBQ+V9eNjzOHaVXsN9zkcwU51kXtrLwfMmbjKaEEME53SBcMuzpe+SHMzHylf554uMabTisL4Pw/bVOFk6Qoe6BEfNibP6cdjITb7Mxbu8O4vrwfNIO1KIt0SQdaUQWmpHtHsG/XOrMbPiOprSLYjpi8hZeK5pF0pcjnSmvCi2ZWFj5rnmNmBpN/NNgA/x7giaef+l0By0M1WcrZ6Ax+chdm8G53InCY824UjuHbrjOnaRvHGycEQSN47nDmCzbzuOZQ8xHz2E86RlpIyUHPoPM9Ms7nciexg55s9vlm7IlkEbudbT2qTMZZ/NnZBuuqj7rhqsHyfr+njmIHqdg/jO4jdk1ntP6i0c4/MU91fVAP2z/uVRz6cUUAr8TxVQS4T/U3nUN5UCSoEPsgIul6sxtHoIjWANhVUpcp25XJerI9zRjD/6J38MV82NiD4vGc6nM8dljbefpR8OOsiiOdBgCUo0GkGykICTDXuLJGaIhr4Um/ZCzjCKRoHONlv9GjYZx2gilUJUga90rMHV8kUOwiNyKS9sbpHD8DSH6Vudd2G/9hZG7RvkcqPHREIHEXe7Sq/KwXmJ2WA3M8zTzED3060eM67gE/af46KfCW+++RZqvgqHajfd5qwsOfFFmzCVn5QFJIWuDExxMq9ZnW3V6DbbKxxWuYCY4dAcYmTFWoPf6YOnRia0Lc/oRxnBZCuz1ClJJnEwfFG6qeNv/s+nJAJPVGyLD4GSE8SNi6WzLEfx0n3uwTiruu9reogLhtfYUriZHruF3OdjkrBxMn9EXgsOdLVewTZSN47lD+J23065mHir/065mCgcafHRIDJPIOt+9HEqT8KHpQXnSidIMPHjW7/1PVy5cuXvb/CjG6prpYBSQCnwPimglgjfJ+HV0yoFlALvvQINcx3pR+bgng1AG8hhQ8smjAyPYI1/A9xVN16LvoivrvoneGrir3Bn6z04lzyBy8z4tluJnJt7GV8K/CqezX4Lj9k/jyPVffCzSWW1ZS12lV/FF22/RvTcHuadV9NdTaFsqeB23IO3tJdZhLKej3MW652b8Wb+Bex0fQIFFons1d6EjRnpvYU3ELHPYYpxCBHRGDKvxMHyHqy1b8QL+aex0bFNfu8w3sGIaR3+rf7HWOPYgPM9p5lPDiDliqOtSIyddxp+fwjmtA1zoQkEzreh2JOBKxGA4Smj2JGDf7wZyU1z6M+vRCwQgYnf08mwTrUswVP0YXroOstWfEh0RuBK+lFbUcPfRv4GJVMRsxorx51E+elL8PGNRZalL6IQ5ZPhTzO7vBsi0nEktV9SSsZL1/iGIs/oRwDX85dku+J+OsjtbBq8xtKVJN90iHKXCxzGY8YiJkvjuJORDXG9xXkr+v2DeCP+EktoBvBi4hnp0Ldz+VAsGKoPpYBSQCmw3BRQEY7l9oqo41EKKAXeNQWsFtuTvSNEwi0W8Gdf/vfYtGIzuty9jGiEZNX0uuBG2aRnJ4WCeQKWl5Rh09lcyKxwncO3IGiI5b1e54B0ji0MUntJjnBzsU64y4apglHnRjisLtzrfFAWoIhCkAGi54R72050Xa91gOGHkhyqLWw07CNHOUx3daNrG0tVNnPxrpO11lxMZHwjaGniY3vxMc/DcrnxcfcXWOldxycdn8I29w7kT+p0gH0YSo6gTe9CT3EQA8YwLEUrLO94YE054J9rZl0i8XxVK9xpH8IhLhVqYZiJ8BP/ODVyrtnM6MkH4K0wxz3DkpVCA+4kP78RgnXRhSd/7v/GOhaa3OW/XzYDriPT+VMtX5QV3AIJ+GDzY7J6e6N3K6MXQVnJLXLfzSRwCDKH3eLAAGMvbmL97gx8DBt92+CkRiIzfXvgHqx2jcp8s584wPXMOd+k297l6JElLCIXXiRK77c7/g/S9wx8uf2reOX5V1SE4137rVAPpBRQCrwbCigH+t1QUT2GUkApsCwVCDYHsOnT6/Clnl/GgfgerKqPkufcgtPZ47K44+X559Dh6ZJ5YTD6ICIM0do87nWTc6w9hxHHekxzqZABYLSYOzBdn8B6y2bsq76JIVuCxIwSrpTPM2oxhIvlc9hs3i4XBoUY0doC1mC9vI5Xl2QE5GjpHSzaonRXc7DSiRaLg2fKx/Elz6/hm9rX0GXpYZNhHm8UnicZo4bvV76NbmsfrhuXsaGxlZENHbqliKsdZxkdMSFQbEa2OYGmpVYsrZyFJ+1HoTdNoogH4RiLU0ZZjb0UZOPgPELxNlTsOqMcVQQjLZhuGYd/gW8k2hNcPCSZo2JBcQMjILoZekXH3uIb0I2SdKKjlQgXAp1sFLwBG98YiMbAk4xrWM020jTSmCareZVjHa5VLsFecmBP9nUuQyboLo/JZcxB5zAClqCMaYimRtFW6LZ42NLowKn8MRzO7ZNLhXvTdOj5mD1kUP9F9N/hU+Gfl19flj9c6qCUAkqBj7QCCmP3kX751ckrBT7cCrSEW7gUuJ2LegW0M4rQ6e7CohaVjjL5byRgONBe68LUwk3pLOcbORIvOkQol2xkt4xWWFm53WcfwlJ9HiPW9Yg3luBt+BipWI90PYHHPJ/HIr8nClWmOGxH9QXJhU4wspCsxxEx5phx7pTf04mmW0Vix4QxJgftE/oRrLVuxDXmpe28iNKUseoVPOr6LF3YAtZaNjKn7ZSV45HaHK50niXVQqeTbMGQvhq9tn60FDtgN5zk9TXkY9o5gLZW2mEECggttsnyGE8mwNw0cXZ8i9CYt3CNkWg8Vn6batSAVd8uLhiW/VxYLLvhD/qwL/smmsx0sjmkf77lKzz/QclnFkU0IobRTEZzmYg94bBfyp3h2w4P9ubekFGPNlsHKkT/tdjaZWzFaXL9cPkwfZRM5z14KfYsS1S4kJh8Tbr0lWoFIVMz3X4uS5IVPeraiN3pV+T1zeI4UsXkh/uHVJ2dUkAp8IFUQEU4PpAvmzpopYBS4MdRoKOj48ntn9osucUhkjWu5S6TaVxitXQEtkUnLqbOwqv7GaEwY5612Bud2+SiYJetTw6wZi4IBsxBBjCK6HesIIZuAT32AaSJoRMNf/32FUTZNbjwFmaO9xbSOobhZQQhYG7ikHwNrXStfRY/phhRELEOE6sFrSRRNDPCIcpXVtlHIYb2ftsgWwctsrp6JXnSE7UxurMuLjGWObAzA9wAkuR3eKaCsIVsaDG1I+GKQlQVdhis7zYnEZ5nFMRugb8eRDGQg4sM6EJbCg7djTqXB5MFUkjyJlQcZDtrblSbdVhzTtGwLTF2LWgH0yNMsrDk5GoSUczhc/1f5lOYZbyij3SMMCMaIpMsohtWkw03Ktcx6FqFi9pZ9DoGUOC5jHoZi6G+XkZNulnPfbv/HrYL3oX1/s2kdQzKOIeVLrYgd2RI7ehzDeJ08Sjd7QncHbyPuufxi21flbdb4Vkt4x0HXj6kIhw/zg+8uo1SQCnwM1NAOdA/M6nVEykFlAI/awUqJEBM5SbYHtjOhcHn0eQI4eyNU5iemWKNdRGpRlK6uBcr57HBuQXH9ANYrEZk7fcEmwEHSME4Xz6NW+x34Yp2AZWqQVc1hxv6Nfg5WB8pvsPcdJENgsdYwX0YN1gAsrfwNhaqs2wSHJe137sLr3LQHGNz32UcKu3DOtsmHNX2y8c+p51Eps4FRKOCE9oB9JkH8WbhJT5/FdeMi5isjzEKkcLNxjj6AwPIrouxoMSMa+6zkroRt5CR7D0Os7uBpVunEGq0INo7DV88BC1YRIHnmI1lWMEdg4NDcyGUJW2D+e56HSVfEW4bGdL9QKAaQqRtisSMKiqmMpLeRcQm43hq9j9hT+Z1PLP4LRxhGcpzie9ihouFx3IH8UrqB1wozOKt1AuMo1jlcmFUi2Bv+g0cyO5GtDyP1xLP4aXU9/Fi7BkkSgn58gvnWVA3fhD7W7rz83h68T/jdP4k1rg24O3kq9LtPp09Jm+7L/Um0lrqZ/1jo55PKaAUUAr8LxVQWKD/pUTqBkoBpcAHVYFNmzY1fuvbvwyH3Yl0Lo0b0+PMQLchVo+iw0aKRXUO3XSbCzUWkDCqIZxR4QiLBcEknVYviRJavUj3eCXyXJ4TQ3PIGiaX+YRs7CvU8jLyIWq5RQRhu+sOvFZ8Hg+5HsfJ8mHmnl0ckNMEvFlkYYqgWAgMnGj0C1ta5bDebxliuciibCDUyX0WtIqAle17rLvOIsXj7ELJWUCcJS6faf0FfOfIf0FYb0fSvQR3jYuDjGwUzXms17di9+5dCLY3Yal1FsZCA+WmEupsAhTNgzUfi1OI2LPZrazStsDjpd1s5vJgkU51IIuqpQp72c6lwRpMc3aZhf7nv/qHWPDMSqSfaBic1Mckjm+z9xa8lnoe69wbMccmQjEQi2XBtzOvMNvM1kdqGbI1y6VKkXU26obMNoufI4NvagQP+jSzz2JxcrI8Jpcaxfd2+O7m4iFr1v/rh3jcA9k9+Mtf/4bC2P1IFHWtFFAKLAsFVIRjWbwM6iCUAkqB90KBlraWJy+vPYX1me341tJfsf1vFc5yaU+Ue6yyjOL10nN4wPkYflB4moN0P24SKyeG6xHTerxYeoY0jAfxOjF0Amu3X3ubI7ILmqHh5dz3GeXoxzult/kVN87rp2XDXpo4u6OlA9JVfrXwfc6nZjqxc5ipT2KtaTN+UPw2djoewK7CK+i09mBMvyyX8ESs5BAxdv22IRys7ObCXRMXFsdRMpfYbJjFVWLhbiFL+XzhNB4aeRTfSz0lK8NnPJNcSMxy8LfjlPsIVowM4mDzWzC0GnS7hnxnEu6YH+mVUfgWQygNZeB1eFF3spK7jRi7nB+Rvim4sz4sdsyiVNCQCSaQ7FmElY2GWm8BCWa+d2Vf5WC/JAfkpB7n4L+AV5LP8bkLuMSFwpnKJMa0qxJt18567j2ZN0jwuA/n8qcw5F6Jo+kDzI375dLkU4t/IV/qV1PP4VjxAJcmi4hoc/h865fxCh3rUe8G7Eq8yvutooP9POqsJD//5iUV4XgvfkHUYyoFlAI/tQLKgf6ppVN3VAooBZa7AitWrGjc+f9sYTRiBeboEj/sewIX2ALoMzWhYaljrHwFt7nvZjPgSdzvfhjztRn4zAFJvrhQOU0u8yZEq1y444DaYmnj0psFVVGuwgFSxBYmGNMQ+WWRg543ZrHasZbRDTYBcgHvkn4Wd7sekLGQUesGRFnCotU1dJq7MW5cxe3Oe3GB8ZAGQ8gVZp1NXAx0sfo6w8hGd7gHWUM43k3w2b2w1m1Y7V0r4wxXKhfkEuTbx19n9KJZ0jjE6xCqhHlbP5559hm43C5U6mVUuouyPAVOlsc0M3ddIqbPYkfFwjrv/5qNtjRMfK48NHNR4vDqlhocMVZ9Bwz86Vf+HVJOUdvdyWMnjI/LmKLmW+hwmJGOO4iku1g8ywrzlbK+/Ehuv6z+7nH0sYyG+Wo6yHWWfYtctSiIabW1Mf5xCCuYm74har99LJXJvoU7/Pfy3N2yZEXUe//oQ9xflLL8+1/9j8qB/pEo6lopoBRYFgooB3pZvAzqIJQCSoH3QoHm5uYnS3cn2fq3HpOVcSRqjGU0AjhQeYu55jtw3DhEPF2LHFrnODybeCk3NLRZOjgIj8lFODEYa+QSi6U/gZfzmfxEvL0ph8LZ2rSMUCSIqbvKwVY0Cr5VeplDcg8ilXlkG2mJajtdOYpNlu04ZRzl2G2TUYhUTRA65iHaCR0NJ67XL2FL63bmpPfAw4rtpUqUDvUVSbRIluMc9q8hytsLCke0PIuPDXwCz+e+S4c6hzkHa8Id11FjDGOqOo6Gty4LVfShAvqyw0gORWHTHCh4cqi62U7IsTbblmArYwMRRjRMNRM0p4ZKkw6TwYF6JIaay0CYi4X+sJdO8mk5/D6b/BZLYxj3+P/Zew8gOfPzvPPp6Zzj5IRBzjljgc05MOcgShR9kk7ylc+yy1VyWZB9d3W+Y9GyaFkSsyjucvNiE3LOOccBJufpnHP3Pe9/T3aximXR5O4Si/0PChhgpvvr73u6h3z72ef9PXwTcZ3lKBnWkUeZr5aIRpbDtSwTLnQshY+YOvkYo/tuNdhwKnNE1YFLROZocj/d6mtosjTjXcZApJ1QFjLd5GtPULN2axfSfIwjvF2O+fIi3wicfPu0dqA/iB8QfUytgFbg11ZALxH+2tLpO2oFtAJ3uwI1ursd3JJbwAE6wTzxE45P4FL1LHx0iFPMPUsWWBr++jh0brE9wmhHElOVCQzmB+lYD9JJDjCuMKEG6wG6zXPNCzBdmqLbPKgc1ykuHDrrLlwqnVcO9cXsacVxdnEAHqzewSbzg4oisdi4QmWYa+Uagg0hNfTaG5xqYW+OcSE6g11odrQgZGiGpcGKT7O0xG10Y5V7HRZwua7UUGLxyirmjQeJ23MxvuFQKLun2z+FULERcwoLOZhbkDDF1PIgbHV4XB744yE6wRa44wGYyxbUzVVmnj2oFeooD9ZRjRHBwRx0A4tjGkj0MEftHK4BU9YKbzWAN/pfZqFLiQNtAtWGCpbxHBw1O2u+6yojbiaJ42TyGF3oc7iWuYgqlyEDbFaURUH5uMDlQBmOc2W629S60dTM/HcFq5zr8XrkBUjc43BiP87Hz6jbj+dGlGu9Lfwy7CxmGcz341r6svqe/kMroBXQCtxNCmgH+m56NvS5aAW0Au+rAuRAb93yxGYkSNuYS/7yaTrOgrOTpb5O2wyFmEvVk5jDwbiHSLq51gUKWbfQvgS9pHB0mLtwoXRKDdIhDn83y9e4GDcbeVZhP2B/jMeNKezaAgvb9xjzmM37C7auaqggQGdb0Hg+NhmmDAlWplQQJ4yuRAfZRRdbWvaWB1Yja05jMVv/budv0rkNqDa/DkYgyvxlJqd6MRf1LubPcNGO5SzlMdWCyEQEvGwAnK5PwD7hxKiVCL7CeqTNCbgTPvhyQUXpKPizqpGwbC+oZkVT2Iq4IQpDzIiqrQxYGD5hvEMaCk0FDtEeYvZsRnjzflTNFbgiPlwavsC2wNVYEFpEd/s2fBY/epl3Fh02ern0xyXBp4KfQo9jNodwE5otLcoll/jFjcJlVEgU8fI+F3KnFQ6v1dauSla+1vzPsNazScU5WA+D4UI/+2pKGCJLO1aNKkzeg4HHYWWr4dE3j2sH+n39ydAH0wpoBX5TBbQD/ZsqqO+vFdAK3LUKSLTgeH4//BxM386+zPM0YKo4jkm2DY7lh3EkvV+Vi1wrXFJxhAOZ3TRkDYjmoxguD3BB0E5HOaWiHEeye5TzfCJ9BNdzlyFZ5APZXWhpaMfR7H7cLF0D5z8cJ9punnEx7rCFT+q8zxaPI19hox+JHcKGdlRduFG/iDZvO87TsfYwc92fvYNoiY2AHEAPp/agL9/LyMMhRiCG8W78VSLiEgiXJ9FbvK4y2hdYOCJxk0htGu3r21AvGXDVfo7OcA3xBVNIW1OYahwjYi8PB3nQMV8YyckUop5p2MIOVC1l5DlcG7Nm5EJpGJm/zncnVelKyVpUzYWGbAPSnjiQNOCV3ueRN2fRn7tNNF6amtlwLH0IO2Lb2CR4TOkhi4K5Uk4h886nTmG0NKRKZY7zdrvjbyPG5cMb+atE4v09CsxTvzH9AjW6iZOJo8QDFhgBydJtvkhmd5L3G6XTP4lvD/8HvDP92l37+tInphXQCnx8FdAO9Mf3uddXrhW45xVoCjVtXffkGhWL6CRlY651oUKnLbGuhNlkxVzbfCyzrmI0YTWjDlaWhjALzEU/q8micHZLbCtRNpTgZ1HKbMt8tNORns2FOcn1StRivnkxkXM+us5eLLOswjgbCYXYEatE4LZ5uT5Xhb3uYA22XcVGzDYzOryMa1haWd5iUnnhJXSflzpXqpKSlYxsSHGJYO4kqrHF86gqLbHQhXUy0rHSuQaNdHi7WEgimDjJStdrdQSb/ZgdXYhwbQqL8svR5GlC/HZClahM1Sbh7g+gxqVAa8KJqqfIiIYFVW8J9rKTozCxcxyJHUkP7GkngqMtsOfc6jwsJavKVfunQth9aScemPUQtrQ+ilQ9gc+Fvsa4yzjm2xczB040HvnUEtcQR7pKt32+YzF95Tzm2hfgc41fYwFLGJ8MfQEbfPdhvWczFjmXUXMuOxoK8Fh8ikYiJTPPBD/N9zl1VbTy+eavYZrLh9e339YO9D3/06ovUCvw0VJAD9AfredLn61WQCvwP6GAzW/dGt48yGHXhitccJOh93rpsmrTM9ZMisghQ/LZ7El0WLrxbuo1VmlfwTxi7GTxz2cM4C0i66RV71juACkdg5iF+Xgp+xMV4diRfksN0deKF7kAN8bhO4ejhQOKc3wwvxOdhh7lOhsdJnjtPuU4P+B9DC9Gfoxu60xWV59EL0tZJCv8euwFXlkd2+nqVhjf6CvcxvncKaRLabwU/nsOp3XsTb7LBb4Krucv40HPE3SnX1dLhg6ypSd9o3CEXTjtOAw7WcqjHf0YdvTDmrNjetkQrGEnUmwmbKiaVA46MW8abXd6MLLkFnyTbBhsH0cukEaiJYKSpciIByMnrdPwjzYjPovM6YoLZ3MnMINlL2lrUuWTZ3M4fn76h1jgXKKoHNfTlxQnen9iJx39DE4kD+EO2dEHE3vQm7vONxt+5VrP5JuQfbGduJg7g9OpY0gU4yrWcYIUDwebHM+kjrOMZgQHeJtJ/heDyN6UHqD/J173+qZaAa3AB6+Axth98BrrR9AKaAV+SwrMnTu3/od/9ftYbl2jFgQlLiFDbrleYqGJW9E3pIa7n1XbsuB2gm2AjQ3Nqpr7cvEcnnV9jlzng8w2z1cEDL8hSJd5hKUqKTYJzsZtRjLWWO9TgzDJbly2y8Bjcitn1QEnphsm4HFIKQrgMEhBSB0P+Z9UhAnBtUVI1whaQsq9PZzcp4gUh1K7lUMttI4gq7Mv5s6qDLbNaFOO9irXeowWRlTWWEpJDGRNn80f57LhUgxUb6N3Tx8X/VzIM05x7OgxNQhXuDxYbs2hbieijsSPhrIR2UACHdfmItEchn+ymS2FCVTsJfKi/SrWYcnQHXbmVF24OW1FzVJVyL0qFxCf/cpTWN6+EqPkN0s4O8t4inCxy8ywzHUsVKSNLf6HcZ5vDOSNQiOJG2cyx7HatUHFTASDl+Ji4sHkbsj1SLPhDDsLZciavt/7KJcSLyjn3Uan/2fT38fbf7JXY+x+Sz9D+mG1AlqBX66AdqB/uS76q1oBrcA9oEAgGNg667FutBo7cD5/CkFjI66VL9EVvsXgggPvEEsnyLrLhXMY4BDthZ9EjdNYy6H4bOkEFpmX4VBuj0LYCVf5RPEQZhrmkt9M6gaJGYJtC1dZp10+p1BuQ/U+4vJuYrZrHo6W9qHD0cOWwwRd5puK2nE9f0VFMS5lz6hFw7OZE1ycK5DDHGfm+QAHaaPiKlc4Kku5yuXcOax2bMDO5DakOaQ+5n9GxTv2xN9SeLcdiTcUI1qy0LHcNIZI6Si2spgkOopr3vNIplKKBZ1YPIVAphFZVxoV93tDcnTmBCxE28U7psHUCGKtU6ibakg3Er2XcqjPWVdG3SbSMwrvdAjRGZOMfThwJc3FwuYVKBtLuJq/gJn2Ofhp+HvMLU+o5b/T6aOMXkxxYbKkYjHC0ZZYRsjcRB70uMo7H0rsQrdtNo4z6y3xFFnCPJU6yvZHD25mriqcYKwc5ZuSFK5tv6Ud6Hvg51FfglbgXlJALxHeS8+mvhatgFbgFxSo1irKcRU3N0LucrbOiEI5ppYDx0ojqjjF1uBQld7LLKvVcN1hmkH+8g2YWV5SZMHJOBcO77M+SCrHdcw2ziexwkBv2QkPc89F0jhkiVCcbXGul5pWw251sO3Pw7gI87z+T9J0bsA6132q1rqR1dV2xkkyFS7u8ZwSdGFp6zIO0Yd4Jaqc6uHSoKrvHskPMaO9GNe4sBgyteCrjd9iJOKwqsQukcNsoPO7xL4SUbKtpfBlklnnHvNs4uyMeHj9o4xlhFDykPhR88A33gh32E+qhxn+4SbWdQPWpB22jBOGigGWnA3GAkF4WTsMxQZkXEmVl5YTsuYcXDa08q8GuKZ8qorbMebFf3zt/0CTqwVNZEXPtM3BBtcDWGBbhjZrp6o3b2H5yuHEXmLujuDvp/4Ol+IXuDyYx7bpl8iAbsEkh21ZcpSqcr5foIPdQ0XMWM0ceLIa5xuFGga4iClRFv2hFdAKaAXuNgW0A323PSP6fLQCWoH3TYFGLhF+/RPfEPgGM7XDKrIhy4RXihdUMUiR/m+HuVuxiceqI5hvWUxCx7hC2mXrGVVVHSSObrDah6ChSbmisiAny4IFFq4YOZBm6im0oRMNXgNane0KNTeby4ld1h44zW6FnZvDrHAHC0KGyY8WBnK0GlFDZ76eY8tfJzZ5HmBRynVs4HKdYOCExtFF97rGZcIma4tynmW5sMvWo7SRqMQKouUEyediZESy0jk61hnWfru51Ghh22DT3EZM7A+j0JqBK+5lLCOFao3LiXEfzEUuEbJQpUYGdI3xDm80oLB3MnS7kj40GA0wMitdYZmKmZXeZUY7xK0uO4scz03I+VNoCXfh7Ztv4JEFj8FstnChcAwLvItwNnUSy1yrsMKzls6yi0uBn8FK/j1Ri6rGwixLaWbYZnGIr6vmxW4uRF6i0y7LhwZeo3wOWZoUA7vbMYtvLCLagX7ffiL0gbQCWoH3SwHtQL9fSurjaAW0AnedArVaDW9nXlGRlezA6wAAQABJREFUjfPFU4iTL/xO+hVcKZ1DqpQic3iAhSpsvSPqTmgUR7N7lRtdL9X5tb1cEFzyXi6acY3T+aPkIPdhipGNcfKdPXUfbnAh0WFz4JbpCsaJXkuUopguTqhYxu7EO2QbD+BK5gKuMNO7k7GL8dI4DhJTFy5O40ruPG5mL+MCUXbfnfiPuJW9zsa+o3gx/GOVa76UPseFvAI9WStusrlPPvbE3isoGc4PIM7Yx/n0KbwbeZ3lJY1cLLyIFc61fLzzHDrjCKensekzG+AZDWJy5jCsEScyzVzW65jC5NwhpLxx5HwpJLgoGG2fQLxxCtG2SQwsuY6kK46yrYi8NacG3WRTlLcLY4pRjoQ/DNsUmxKbhuAsufD/7v0/OUCb3ys9iV2Cw2THjuibKoZxNXuR1zyCfdEdmMiPqSH/UuosS2UmcYYFLAXi684mj2OyMMY3Dq0YzN5+Lxsd240D8V343th/Jm5w6K57XekT0gpoBbQC2oHWrwGtgFbgnlUgFAptnf/EHMwzLSIBwquKSbrpDLeZOrHYvpw55LJySWUhMMQh1GcMYqV1HetOwphvWqIiHn4WoZQMRYYZ6kTUtar4hzQZhvyNWOFepZr85joWoW6sYY17IzwsOHk68GkELEH173n8XpoNhw96H1dlKJvdD9M/LuIR71NqSVDcWDm3pXRt59kXqirrRazDXuhcijn2eVzAa1LZYXmSZtnnqudKqBcn0odVmYqTju1D/idU9niiOIZWa7uKSMh5zAjMxEh9AO03ZpMFPQ3vUCMkjmwpWOBK+GEqM9IxxeOPtPFrdjYW+mAr2RDgUqF8zxP3w0m8nYHNLe7pAJwJou5KDmRbEnBlvCjTxe6YmoXXj72KZ9Z9Ag82Pq7iF58JfYVxmYxqHwyZm+miN6tFyR77bAyX+qnbOmIELYoH3U2nvYXnLDrMdS/kNc5TmfMt3kew0feAKmU5+84FnYG+Z39K9YVpBT6aCpg+mqetz1oroBXQCvzTCkixyJnsMXQ0dLJI5VW1FFgjN9lIZrFwn8+z4W+j9SF8J/kXWGfbjGw5hVHjENYat+BHub/EGssWHC8dwEbbFoyU+1hcMoXFvuW4mbqCL7i+gX8z9If4fPCrOJzcz7hHCuaqFde4VCfRiylmfKUc5ETiMBwWh8o5DxT7VZnIufRxDBTv0KW9wlrvNOZbF+NS9iy+zna+XYm30W2ZhbciL6Hd1sUmPgeLRrJY5F6BARauPBn6JHZGt6HZ1oZypYKTHKSlsOWn099TMREpilnp2UC8XQ4t5k6sW7YOE3MmkHwthr4FV9A8MAOjC28Th1eFM01ahyurfmc9SQQnWpl/TmGiewQBLg2Gu8bhjvkQb+aCoaUGY96CiolvOsiJjrSNo+XWDAx230Qw3IK/Pf5f0LilmbSTON7IvcDoihtvxH6umM+CopPil6HiALF1R98bihn16LB08UlsUI50tamCHZFtpHHMxo3cFZxLnyAthdQQ/tIfWgGtgFbgblOAyUD9oRXQCmgF7k0FBGP32Le3YD2H477yTXjpHJcZi7BzCZDdgBCyRpOxBTfKV7go+JCicdjJVI7XIsgRd+c3BDi8kiTBTLDNZSOtwgCf2c+YwXuO8im2Ej5AZ1miGlKzvcSxgpGMM8p5ltuIezxSGFRFI62WDtxiBfYs61xF3BBn+gRb+sQJn2B+eJL3/0LoGzjNZj/hJA9yeU7u087stNA6BAFX4VKklJb083teow92ovGEgmFh5fdNDp1+ut5+uugLHEtU3nlvcjvd3Ta4uUj4g1e/D3+kCamGOOqVOhxlF1KBmFpcFBc6407BUrQy+2zE9Gxi8m53Ito5BVvaofjRoeE2GMoNKPpyaiEx1RgjrcOuSBx1R1XFTnLRHL7+L7+KJZ4ViJTC6HbOREpaFEvTynVf5FimBugN3i24mrvENLUJ87kouT+1A/f7HsNVxl1k0Bbm9RLnSvX3o6l9+K/f+qHG2N2bP6L6qrQCH1kFdITjI/vU6RPXCmgF/ikFPAH3VsdDRsw1L2Rpyjk2CHJA5NB2oXQG99sexfbc6+g2zsIkG/UGy3e4ZJhgzrkXzroLV7lo2MCK6wnjKNrd7VySm1RD7SwuBB6K71b85oupc1zac6OveJsD9IhagBOWseDaevM31H1kyLaSvDFWGkWyFIfZaMaB5C61HCfD+puxl5ldXoNzmVOKH30le14N4zJIyoAvxxJ3ep59EY6nD6rlxAvMPu9IvMVrMdKxfouIuyQd8DRGWJ99M3sNaxkl2cMMtgzTQhuxm9g2OLMB5vYG5IdLmJjfh4aMCcnOMDL+JFwxL6Zn8fzjLmSCSSRbI7z2Bn5tGCVHnm2EVSTbw6jxl3xP8tGR9jFSPvJIMx/tSPmQ7AgrDODZ6CmsnLkakcI03uK1yQD/WuQFnqmBSL80drHWW6q85Zr6WVle4BsZoYsYjawxT+5lnjuIC5mzfAOTZT49QQpHL25t79cRjn/qxa6/rxXQCnyoCuglwg9Vbv1gWgGtwIepgGR3zXUWkhga1dC2wXI/hot9WGlZj+t0bC01K9oY7whzOG4ytHCpLYd5xiVw1728TzOWNC9Hoz2ERnOr4jJv9D7I77k5PDdyOA2obLMMheMsFHFyGE4UY0TgXUc/4xl3iGCbQxqHtBkWWXgyVRxlG+I5DoR3iHAbxzIZmtMnsYhusYGrgjI49pCLPFIYho8kjcEcS1F4rN7cDeLeikq2a3Ros9WMcrkfcD+m6q/l383WVoWZ+1Lo97DcuRp38rfgYs33UKkPax2bIOUsUlve0dyGydQYnCxLqZYqaGYEwxVlNpzRE3POQrWY6iPGzhFxw550MyNOQsd4k4p4mNM2FLlUWKnWVGV3gUQOR8qDirmMtDsKS8SObDEH65gLf/7XfwabzabqvH1sH1zHgd7B82kyt5CH7VDOfLqYZsZ7AW7lbkKWPRv4a7o4xTOwqEVMRs5xkvGXK6mLH+ZLRj+WVkAroBX4lRTQDvSvJJO+kVZAK/BRVKAx1Lh17mMz1aKgje7zYO022k3dpHFE2DzYQuxbivzkMZSrHALrSVjqVmSNzCSHFuFO7RpxdrMwSmc5Up1iNneOaiiUeIGg6xay+c9msGOVZ52KVSxkPEGQbFOVCcy2zUOqniArmsi4BrPK/n4i8AWcy5/kstxM5pqtjH30o8cxG+PlUTYQ3k/MW5y55LLKZm/2PAQb67ilLXE5cXX9pV7Mty9WsYd+OrKLnSv4RqCf0Q/el0O9fMxxzOPg7Vd/N5NBLccaZyxkoHIHK+2rWfgyzZbARVi5fiWG4wNoGLcg2RPh4mAAZROJG94MHAkXi0+MyLTEyYduUCi7mpU55JKdPGgrmoe7UCXazsQadP9Uo2o0NHLZ0MgCGIm3mKwNyPE4nSkWpEwewjPLPwlDqUGxnOe5OCzzDYHwsVe41vL67Kp5UKrN7xRv8vwXsGJ9Co8Fn4XfHMAMaiNRD2l9vLH9tnag1TOr/9AKaAXuFgX0AH23PBP6PLQCWoH3XQGv36siHI/Zn8ObmZfwtP1zOJk9TMbGNJpqLdhX3KlQdceK+9lW2ImavUbHuQlZLu0JOm6T70HsT+7EI56nMcoFOCn/GGBcQ+IVo4xLHE8dVHSOPcl3VPHHEJ3nqfI0e0EqGMr1c6EugWtE1U1ySL6Rv4yr2UssUnFge3ybimZMl9kGyMF+ioNuHxcEa3R8zxNrZ+JS4GRhnNXYJFUzxtGXv01KxwpGIZ5n3GMdkXjb1BKik65ujqUsQVZlH08e4lBKFB8XGmuGGm7nb6qs9HqWuJzhQt7vNf8xlw/fVEN+IZTD7bN9ariPdI7BP9TMuMYo887MRTdGkfNk4Ey5EeUSoYNOdCIUURnnBL+X8iS4tEi3mPezs2Ql0s3bkM6RZCV40VyCK8I4hyMCa9aGbTdexiNLn8Dtwi20NjCLbfbgXPIUYx2t2M5FSDN51adTR/gGpsr4iwO9RPkVmVHfG9/JWEqC5/s2nfg+JPfn9QD9vv906ANqBbQCv4kCeonwN1FP31croBW4qxWYM2dO/Vvf+R1moBfhWukS3Bw4x+napuk8exjTiNbCjE6EYHfYWWNdZ+xBGgTNXDJ04DYruT8f+jrb9PahbChJEzUHRyOWOlZxIB5XA7AsCEq5SYRD8zzbIkyTES3c5pC5kYzpfo7RJRUdGS+NKWydDOOSgc4xdtFJnJ4cVOrFG4l6K3BwvM7WQQMb/7x0ksWNlQYYiWTsjb9LVN2TXBS8ihyLSKLlMJoZK5F2QKkC9zP+0cJ/l/hrtDjE6MgCtgG24GTmCDPT3cxUj6sFRDvJI9N0omWJMmRtxH/40VbMiM2BcJ4rHNdl+JUqbylasRRtSIXiaLndjQSHY3GkPUTfSSbawEXDgiPHApYg4uRDm9hiODlnkHEQH0ruAkKDbch4UvBNkeRhn8Sf/vM/xSzzPGabzygUnyxdJioxbPQ+QHf6loq7fL7p64r9/KD/cdVeKMuSy11r8Abz0y//0dt6ifCu/knTJ6cV+PgpoB3oj99zrq9YK/CxUcDn920tbUlilWUDfpj+KzUY3yhew0hlgENnAKerx7DBtxmHMrvwkPspbIu/yIE3z+iFHwdSu+BirvmdxKuIsQ1vnIzlKQ6iN7JXcCS9n0uAMewh5aJMh/gkFwUTtZgqU9nHrw2SdbyNCLcbdLEvshClv3xLlba8G3tVtQfuS+7gQFvGebUsl8MEMW8H4jvoJDdhNzF2QdI0pHglSDb1AGu+DyR2qoH9lfDfM34SwzXi76bLk2r4vMWlQSPjE9tjbyJPcsjO2DZ1bqPFEQ6ihzlSl+n2vqFiLK9Ffk5E3kzmqq+ikw2M7Ys6cHhoH0x1NglyYdCSt5PAMYysO40audaxtinltoc7xpFtSiBN1F24bQKOnBPjswdgLlsw3jOAWNckKpYyMl7GYEpWRHj75pEOjM8bQDDFa+Li4EOzHsMQr+WtyCuKd/3C9I/UkuRUYQJn6ZALxUTwfLKEeYBFKvImRRCAUr0+vieiHeiPzU+tvlCtwEdDAe1AfzSeJ32WWgGtwK+hgDjQX/72Z9Fq6FALeTaLje5vFma7Ce3OLjWsyZDqafCyOno9B1mSJejptpu6cJr86BZLG5nEl5kLNqmFQKneFnf3cu4skXUrSfWwqfyv8KalaluqssN0juV+4jZ7OYjbDQ41vEpeWRbjVrs34KKg7lwbUa/XWa7yHm3j+fAPuVC4TBE1pHzE0eBklMOostrX2DIYrkxzIdGPZ/7mPlRvZInjK8G+yI/vf/NlPBv4rIpsLHWt5FLeNTraLXAaXDzPcwoJ12OZoxYex0kCmWufz3jKdTrlJg7gvVjiXo4fvvZ9WG95UXUx32wyoiFlVAuEEs9oHuxGlqQOa8YBW9GOeEtYOcviStsZ+Yh3TKCprwvJligI6UAD3WkpZalZKnDGGO0gKs9atqKYL+N3/tVXsMy2Wi0/mrksWECemMCiyojfH3gEB2O7sN63hW86zjCvvZBZ6CCOJQ/gu7//d9qB/jVe//ouWgGtwAengHagPzht9ZG1AlqB37ICkoGObhZChhNny8dhsVmQMsVU1CLEIfN4/CDmORcq59jE6MZVDqoSLXAZPdjH2EQ32/HOZo7zKuq4zUW3KWaWzazyGydRw23ykKpxEROMZ0hpiiy7DRT6iGc7p5b53oj+XOWlLbx9b+GGWjg8njlI1oSB8Yww2i2damFQJJKYSJQudxu5z6czx5i5fgpvRJ8n5q1PDfdvx19RLYoTRNKt+fk8OG+bYIuZiYXL4K379zAnXWBd+HkeyaBqw6/lLqBIcsfPIz9i3rgDF4nIO5c9xfMeVji9C5nTHLDdyNQyaqmyqa0ZJ3KHuBxoxPDcXpTMRSTbIoh2TKpFwlSQvGhjHVVTRbnSwoqWXHSyJcLSmDoRd8TeEYsX65pCwZODOWtG1VxlhTiXFcsmtZRoT7txeHwfNi3crPT72dT3VDvhm9GXmX+2c+mxQirJKZXLFjqJONBluvST1PfKuze0Ay0vFP2hFdAK3DUKaIzdXfNU6BPRCmgF3m8FZJkvACLnGIlw2Zx4zv85OrqteIhLgYusy0izWImVjvVc+qsyLhGCgS2FGS7l9eauY6wygi5LD+o1A3FrC5mKdsHNwXqUy4FJlqTIgHc6eYzLg1XcyFxlLjmiFgcvpk8rBnS8HMWXQ99EtBRRDnSmnESzsZ2EjvnIlXOMd1zBX499W9222dzGYyZUAYpJvGEO8/lqXg3UxXoRnaSBfCb0ZZV5/kWN6spJloFfEHAyIAvdw01HXc5LHHLB7Unxymb3Q8ohF7d8Nd3vQSLuvtb4LTKpdyLoCeK+5ZthtJrgnQjBNUXVhjrgHSXCjzXfDRWjqipPc4GwTpfdUDEgx5hHYLQFZWLsPBNBju6APeaCf7IR0bZJ5bZXmfE2M9JRy9dRaSjDMerFv/7Jv4DZYqLbvgLL7CvxXONn0MQFw+nSJMbyw2Q/x/n395Yr+7I3uUw58YuXrP+lFdAKaAXuAgW0A30XPAn6FLQCWoEPRgFvo3dr8CkH5rkWKYc3XJ3kMDpD4eXY7MGFwhEOckuRr+cRIttZFvyEq9zDOmnB0cWrUcS4aCi54TZbJxf32rDau5FxDXq9jF408C9LOYQ7zU5egAGbPA/gZomLfiwBmWWfp/LUPY5ZuI9YuoXOZWijG9xibcdi17L3HGji7ITP3GxppcN9Q7UNRulOX2NLn7Cmp8mnzpIzLYSKKJf/ynxDsHhonnJr04EsLAu9OLHyAp7yf4pxjJv0yesIWEK8Vp4zlxtlSH7Y95RaMgyYQ3zDsFwh+Mo8Ek8fJQ7nspQo57uycbVcAqYLknuGonEYZZmQA3DVXIG5YENgogkJFqqYmH1uMDagbCnBSKQdgXdoHOtQCDzfdJBIvCzckQAXM6vIhBIKg+fMkhjSmUBwoA37hnfhM6s/rzLp/fl+tNu7lJPfTo0DfLOT4jWv89ynFjAXuJbg8JtHtQP9wfyI6KNqBbQCv6YCeoD+NYXTd9MKaAXufgWcQefW4MMubPY+gn3p7fhS8HfZ4LeN2WOojLBQLUxswJMlPQMzzO/GXlNcZuFBX2F+eD2HOKnWDpKqcSVzCTHyoyeyw+Qy9zMrXcAkl/9yzEVLM6G42KfSx1VN91wyja8wRjHTOlu16nlZjDJVkCbDOxzO52AHl/pmM4t8OL6fFI8ZfPxdzDDf4NA9G89P/0BFR6RsRTLPSfKhezPX4WTj4bHkQYTX57Dj/oO4+cQoDiw7zvjJMBnWaZxKHcVMDu136NrKNUVKUf6eUli4o4n9ytV+N/a6Gq7F7U7REV/mXIULdMyfDHwKB9kC+EjPE3yM/Sj0k0dtsSiX2Z52YnoGEXfMNScawyR2xFQWOto0CRdjGXlXRoLPiLVMI+tKIR9Ic9FwHBbmniPt43SgLWwyrCDti8MTCyHTlIQ358Puge1YOGchLmfOs5yFapJCIpXfsggpOtnJ2JbrrVTK6N2lmwjv/p82fYZagY+XAmI06A+tgFZAK3BPKjBzfk/9X/ztn6jFvUskXoi1WqDbnCwnsIiOsCDfNnse5pB8lLi4NWQ7k0TBzHK3faZiLkv5idRuz7TOUWUqM61z1VKeLAZKBrpKfnGWdSwy7IojPc6MskQwpL46xkjHWvemX9BVsHc5DogT5EJLgYg8frulS2WBd8XehoVc5BSHWylNEXc4TyLIatcG/IxD9Rcbv6EIHc3MbssbAHHEfQ1+0j5e5O2X4A4d6HZrp/qeoPjWu7fgDPPbcg7DZFgL6q6P1dniTj/kfQI/nPouOvjYkmEWR3qBbSkd69vKnd//6kGM24bgGmHbojMOU9FKRrQDFUMFYfKi62ZuCxKh19E7C+lAHPWGGrwRRjdY7+2bauYwPUlHuo0DN/F4xhIcGRcKrhyk6NBUsKDMFkPPUBD2uRZ88bNfxCzjPPVmYpl7pYq2WBg98TZ4lOMu1/WKxtj9wutI/0MroBX47SugHejf/nOgz0AroBX4gBSw+C1bE5smFEHj5chP0WRpYUZ4EAMcFB11J95MvKwQdW/HX1MLf+J4XsidwURhjMt8RxifyCqcXSupGvI9GbDzlTz2Jt9m5OIW3gj/nI71MPbEt+NIah9z0k5+3guXLBhmLyhCx1EuKr5X0T0IGZK77DOIlXtNOdfHEgcwxqbDA4ndXBp8EUvsy3CQf5fGwL3Rd9W5TBPrdoTucIkOrTjVlgYbTqQPY5ALhpLDltvLML8n/o6qG7/NamxBwZ1IHlHXITzlQ/E92Oi5H4d4Wxmg77Bk5XL6vHKlDyf2qhjKa9GfYYVnLc4w1/3F+7+GXQd3INrIOIfRgJFFtySzwrKVEaS8cUhMI0r6hrFiwnTruIppxIJTZELLEmEWkdYxFDkkJ0IsV3GzBKV7FHlbTkU6pjlk+1kPHu7msB0NYXfsHcxrXIiR+gD2RN7lYqWNOm1jbrsP+xM7mCsfQP5ATUc4PqCfEX1YrYBW4NdTgH6A/tAKaAW0AvemAgG6rp8OfQl9pVusvH6AS3ntKrZwLntS1UkXG4oqAz2XaDpxesfJTq7wl1RyNyaaWLH9IOMbIdZ4z8JM22yi4yp0bbuxtLJSDeM3HVfpN1voFBfwhdDXyGpuZpCjQqPbgKqvymHXilXO9bhAbJ2cS5OtRS0KfqrxK1joWMJlxieZWq7hbO4k7Ky2fiL4SVj5eT4HaIlvSIb5EWaYe6wzVSa4i+e12LEcSS7aCarOyuNLBMRpdCsHXIbkDPPDLcxU+8i5NhnM6okt0PUWh3yBc6nKdT/geww9zjnKnX5x+ieMYNTxpabf5ZlX8ZDvCaRyCfzB7/wRfvD//BimmTUsObwRRdZ9+6cbUSXv2Rn3wkqkXWCyBTYyoSvWMgIciiNdY2ga6sJkzyCXCZtVmYo76mXCQwgdEwiNtmN8Zr+q/e4emIe0PQn3nSCjM9vx4Kc3437vo4qz/Y2W/5Us6wjmO5eQxFHCv8K/uTdfoPqqtAJagY+sAtqB/sg+dfrEtQJagX9KgUAosDWzZUotAZ7OHOWyW4NCqMkA7TeGcJnIOYkLHMscQoHUi6v5C+QtTyrG8hnmmTs5nEoF9ywu+kkltwzQUrv9Kt1aS4MFR+k6H87sU7EPQdNV/38UW5VV2m5GECTOMUH28kXWcwvKTiIeRjKlT7ACvMrBWZzgHYk3sNC6lG7zabYcrsbrrOuuCdkje1Xln6V18FLmHF1mL2uvj5FjnSbf+YLiRSeZY97BWm8PHytaiapYyi2Wt8hwLRxpIYpIXfjp1HFmrufSlT6sHOhypcRSk361uHctc1mVtGyn6/sgB+t3eD6bnA/gTO4YvvzkV7H/wEEkO1jlbQWmuodRMZWR86eQYnTDmfEg1jzBdsKCWiiMtU6qBcNkKEpyhwklWwFmlrSIM50JJJHzpZEMRtRiohSwuFMBpJr572EHdoy8hceXPaWKY7ZHXlcYvsPJfZDrmdgd1Q70P/Vi19/XCmgFPlQFNMbuQ5VbP5hWQCvwYSsgfOG1zvvQauxU2LoKMWweLvXFuLA2VWQMgWUlgmaT+u1qtU6ehJk4tQEuCt5mU+ApDrm9Cl+XLMfJTU6g0dgKK7nFFqONUYlpPOf5HO9jRIe5ixg80MUtM/qRwt9M/CccTx9StdTWBjs28ByEIS3LcZlKhlxoG65yEBaneIBLc2l+LcHFv2Zzu3KuHSanaiJMcwjOVXPMbmfJmx6Hx+xn5bhbVXkPFfsUms5t9DKaMqB+RwsROt6n2VZ4iW8QLvIYTSqmUqqX1ZsEyVdXazVV7R2iu27mQD+PpSXL7KuIj5vCbPMcMqNPY4F1Ca7Hr+Av/vjfoz7Jtx5lI/yjTXCwHMUV8bPO24CCM8tK7wI8UT/qzIML8q9sZqE4OdIG/j3RFFaDdp2PZ8wxG36nmzXhVlgLDpjyFrrYNlhTdqSNKTQnO/Cj3d9Hi60Nc6wLsNy7Cve7HsFa1y/myD/s149+PK2AVkAr8MsU0A70L1NFf00roBW4JxRoamzauuqZZWzVq3HotSrCg8/sU813m70P41bpGrz8t3wsca6AnYPxAg6Yq72bVKHKZ0NfRY337SYPWiIQgpVbRpc4XU1wMW+QEQm2+ZV72SrIIY8Lims8m3gMh0LYbeHxpSxltDKoFvWkZVDufz+XB6VMRWIhQXOTwtdJTKOvyAITQwHSWDiHFI8EHeVHfc+yKXCFimqsJRFEMs+y/ChLjvuYD17tWo+yoUws3nK1QLjGsxFLXCtU4YuQQI7RIZ9tX4DrdNF7LLMZE3FgpDSE9f77kK1nsNC+FJPE9c13LCato0iX/CrvO6ny2UIcWe/brCgdn9zyaZw9fQ5FT57kDQ9SrVG4Ej64Yj6FzpPSFHcygCyRdW13ZjER0sChmhGSmlldqyPrQTaYRGiqhdnoPLK+FLyJgPovAlU2FtoSDiTawnDeCuCd62/g6xu+qYb+DBc0H/A/hm2vsuI7HP6Le+JFqS9CK6AVuCcU0AP0PfE06ovQCmgFfpkC3qB3q+3BBsxgdliiACEOrNIUKJXcHoNXoeaE7SwOsAzYuxPvqOrudDGBy2wZdDQ4cIgxAg/jEydSRzgIg4uEQ2ppcB4HVKFpCMWjP39boeOOsFFQ4hYS7/h5+Mdq8JXWP0NDgyJhDNAxzpO5fCi9l+c0i22HO+hXF9FsalNxkNXOTbiZu6Iy0CdTh0nkSPF4Z4nCO02SyEYc5blIxfX3J77LQXecMYcCr+cM89lz6DhfwXL3KrwdeVWVwlzNXWR05DwHehuuM6YhA/Gp9BF1LdL0h2qDYkILGUQqtffzXNqtXbz+K6pifDZz4bcyN9DmaFfV2o/PeBanpo/BWDTDmDYpnJ0j48YE2wbtebrI3iTKjHeQBogYnee6rYqp9lFVpJL2xFX0o+Qiqq5lHP54CJPdgzCypTDrSnOQNjLO4Uc0NIZgpRmXamewqGUx+nK9aDN1Yu+b+zA9Pa0H6F/2Itdf0wpoBX4rCugB+rciu35QrYBW4MNQoKWpZevaZ1ei0zpDZYibuOTnMrrQZG7FSvc6hWx7Lvg5MpZdaoFNaBnS6vdo4FkVt9jIxcNyvcS0coXLf4vRyiVEyUhLVliQbg/7nlQEi6WulWrxUJBxrVaWpZDaka2luZxnUEQOOyMcTwU/zWU/J5nUDytqxkIWuARZeuLlsuAa9wYu95GTTJqGONPrPVvgNwfhYEHLk8FPYJCD9yr3euWgl2pFLjA2q1IWWXZcxFKWNRyujXysOF3r6eqEWiqUWvAcXeYVrrXKbX4m8Fl0O3p47o+jmZi9Fe7VaLV1oMvaQ8d9PYkcJi4sPk0m9CeYm56k886VQv7Osu77Ic8TiFimsGnRfRi9PI6EM4KmkU6UGd+wsmAlNNIOO5cJjXUjcXYhZr9NCmPHuRhNg6wsr1pZCW5G21APTFwobBvtgZllLF5SOJxpL7nSTjrUCTRNdCDF/LS7N4i0I4WNXVuw3L8KL774onagP4wfGP0YWgGtwK+sgKZw/MpS6RtqBbQCHzUFqsw2DxKH9rj3WbrG7+KbzX+C3fwsOWVzzYq3Uy8rR/kykXNjJHBcSJ9i5GEecW97sD+1g7njHN6Nv4GlzAcfKOzGdG0Sy61rcDL9YzzNgfgtur0SARlmZlraCF3w4GLuLD4b/DIGc3140P8ETiQOs+gkoXLPt1gRHmH2Wuqzw74p5bB22rqJqdunSlk8zDLvTrwNO51vwdhJg6KRTvFkcUzRKN6YfhH3+x+hS3xVqHJY4bAiV8kyYsLFxvALeNj/JO5kbuOOsReNDc103a8rEocUxUh+OlaOkcSxhIUlXOorp7DYs5w4vH7mjltxNnEKN9xXMVoYUl9b771P4fL+9/Z/i3+Y/j42Bx/C0fB+BIMhxAthTHQNIBRpQbidVdtE3SWDYeQdeZScBST9UWTpSMf90yRxJFE051Fw55DzpOgyTyHrSSMWmuTg7EDRykXDvBm2ihPhpWOY2bsYw929cJxdgRcafoTZy+YpR/yj9trT56sV0Arc2wroAfrefn711WkFPtYKGBuMzCPPRcjUjA3uzaoE5SuN36Qzm1VsZq/Ni5WOdbjgOIVVxNitcq5TWeBuYuNkiU/cWxlmbWQTS5vgHLYHNtL9DZr/kOaqifddD7/FzyW/rIqGrKaT/Hz4+8pBlsy0kXmGFZ41WOFczWjGNeXuirMsi3wS4ei3c1AkLYOl4HSq3cTK3afca6mx9holq92PSQ7tkq2+ynpvGWrFKRY0n9R/yzlJk5+ZiIxPhD6Hla51dJdblFMuzvbR5AHc530Qsx3zlPNdZ2mKnFe5VlYlLrJMOewY4HWuwWL7Csx1LqCLbMKu+FswGo183I2873zSSHrU0P8E3fDqMzWsSCzDjpd2IRGIoOfafJRtJbQnZ8NCN9pYMsLW7GTroB9ed5DRDJ8ickzOGkJLXzfsPU5V++1N+uGOBRAhxUOQeDVThZ+7ULYTlxdrRNgyAftpN3pNt1XRzMf6hawvXiugFbjrFNAD9F33lOgT0gpoBd4vBUoSv6jXWLtdIlniFMtISsw/5xEyNqpGQEG4yfclt1zk9+J0aP2kYkjT4A1mih2MXEgTobQH+hsCKr7hMwZUhOI9TFxKDZfh0iQXBKdJ0kghXU6rHPF2OtfNjHxInfdrkRfwSf8XuBgXVdGMq8xXyyB+nFg5YTlL46Ag8CR3LG72Yi40Xs1cJCJvL572fUbh59YxHjJGJN4G2xa8FXsF32r63+hmR3A9dxlFcqjPZI4pysZ4aQyDpj51DRdZCmNlHrvIqmzhKZdrFaLxYggXp1X7orxBuM2mP0H4TRbG1fWNsURGsHsSJblSOa9y1oKTkwjJdiLu5pPOkbDEsPmRTdh+YjtGZt1GMNyK4YW32FbohD/chLFZ/WhmxCPnph7E3ZkKVmRcCbYRNiLrTsMaiPHfSYzMvANPhLp2jBFtZ0GloQJ/pIlIvCKCsRaMtwxi7569GBoaer9eEvo4WgGtgFbgfVFAY+zeFxn1QbQCWoG7UQHJ4qbJShb+s8vgYf73CdQqNVwjlWIix0GzeFsxorNEyDXQLR4o3KYzO4wr6QvIcbFOBu0Y0XLfaPpDLGGByXLHGg7SQYW2M7Eu+yh5zkK4OEXGtCDpbqauKUe5w9rNgbiGZ/2fRW/uFskeSzgQn1e/JcM8xpiELDIaSavo5G3XODdAvt5f6OU59fNsDbheuILnfJ9Vgy+Bb4obLWxpWRjsNM/EzeIVYufGic/rZrnKCmLk6irTLTXlLharTBSGkSolmWHOcSgfVM2IPxz7LqMbadSqNcjyYIAYu0kOzJLtTpIsEq/EqFgD5ljm4vOhr5PcMQ9us4cRCiLq6F73mGbBSvzePOsi1NsrKIy9N+h6E0G03uqBb6JJUTp8Uea3Wd8tSLsKKRupQJQxjiJyrgxyjrRC3AkP2hMPsBIcqia8ebQTlrwNdsY6yrytZKq90wFM2IdhNr9XCHM3vsb0OWkFtAIfTwX0EuHH83nXV60V+Fgo0NzUvHXB03OJqFvJ+EaN7nIQJpOZPOcUgtZG5p9HFGd4vDqKRvKSBf2WriWxzL1S0TDOZk9w0a8RMhDLZxk45Vh9rPF+3P8cUrztRvf9qrgkV80wn/wojmcPsVjFioVs/esnmk5iFbJcKI8riAppGOwtXGc0hOSKOnPIRNCJC+0l31kc4Qqd8JOkZbSTK101SN1KjW5wj7pNyNqEAt1qqe7u4SBdM9TpSo+oc5M2wzBdcLfZzWtpxhbfo/AyXrKJi5BF1oBLHMPARcMJFsFwRiYSb0JlpqX2u4M57HFWilfoUEt7YolkEIm/TFRGGG1ZxzhJAFcLF8mgJrrO4sad4k2sdTBOsrIGc8SOeCSONBF2Mvwm6C5bC3Z4ORxbSjaUrYx3jM5kpXdWuctVK5saGSPxxkIsYMkr97rA7zlyLhiJvUv741wwtKLWUIPg76TyO3Eyi3w+rykcH4ufWn2RWoGPhgJ6gP5oPE/6LLUCWoFfQwF3wLXV+5CVFd6d2Jfcwc8duJG+wvhEC13YKt3jSyqycTR9gAUpzdgZe5ND6JQqWDnNSMST/k8RdXeerYVB7CF3WQbdfYl3VWGJ3xzA+dRplaW+lqFjzVy1BTYcpyu9kpni3bF34ONtrjAeIgOjqW6lEyx5XhP5zAc4jDfiWOKAolxcy17CBJcYxUn+u4m/ZG75ISLnjvG2RsWdHqMrHuTtTzLyUWAEZSB/ByFGQMocjMNsKpSYhiD45tsXqfIXiWQcSuylyzyk3iwILm89M+DHk0cYE5lLV7tAh5yuModz+V6dC4mniOkrEIs3Sr61VG/LkH02Sdwdz/1AYhepH+2qZnskN8hFxGVsZrwIM98UGDuAsVOTSHZNw5iywMKvJZmNrptrmGwbha1kR8IXQdlYJmWjHQOzbqJjYBYRd0PwRxuR8saQdsfhyvkw0THIwTuIiW668BUjwk0THKhjKO436AH613j967toBbQCH5wCeoD+4LTVR9YKaAV+ywq0NrdtffiTD2MDsXBVsjek4trEoVQWA9d4Nyryxgb3FqLn2jmQNmEeB9BlrlVCn1NLhXNYQtJm7VToN6FzCOZO0HZ2ZqNDROJJyYoMtk3WVlU+4qL7KxELC5nSy3kcB0tVpIVQ3OY6HVUpUnnU/4wiY2zw3M+Fv1aFz5vFY08RPxerRFQRijjGQbrdX2r6Bof9JvKa01jLRUJxwRv5uEIAER61cK2F7zxaHMJcxirmuOYxk92NpwKfJgHkcYZQskTyPQMbC2LkPKcq41yItCuEn/Co5zgX8hqqyiXvYm35LMccrPSsh9lo4XJkQC02CtlDHPjlfFMgy4ZJ4vbmc9lwjI61VI4/1fRpdK1vw8XtV9Cdm4OCiQ553ovGiVaYia7zxoJcCgyhaqugYi8pl1reUFjLogngzrDIxmSgE90CG51ra8UKZ8rLKImJOehmUkhMiJ9O6wH6t/yzpB9eK6AV+EUF9BLhL+qh/6UV0ArcQwoIbeJ2/ibzxSVIyYnBZ6AzvB1mDtFX6BofSO9CmYP1RZaRSA5ZLfPx31IrOFoaZFnJarVkZ+C/D8Z3o8c+m38z0Mk9hKdCn8b+xHYuDibUACtDbs6WxdnUMdwfeAKX0mffYzgToyeoNlPJjIvMQdfwPRxN7GfN9nm6uJfwgOcxRIoRnGcE43da/wBvRl5hE+FctBjb1ILjnti7CkEnDYh7ojuw1rsBB2N72NGXZuX4MP6B1I8HyKW+yMKV5bXVzD6Poi97W52XuNMBUwivh3+OUqCIc8lTvN4iFw+vKCc+zrjFW+FX6MKHsD36uhrsF9qW0GXfiU82fRHHeJ0VVoBfTV9Gp70LE1xQTJRiCgN4ILEbf9r57/CDob/CM9Ri4ZfmIP5qFlWWqUy3TarilJGeXgSnWpWbLLSNeZdXYHj5bcy/uAp9cy8TJWhjTMOBuDcCV8qNvnlX0TLSzRhImIzpIlxxP1J0oFXN4z30utSXohXQCnz0FaDPoj+0AloBrcC9qcCCBQvq3/ybr6mykzv5W5hFd1iGaqFx+Ex+vEuqxGri685lj+MZLvxJ9KGJeDgZkvsKt+hEG1UFdgObBKVtsMS6aycX9C6zzfBpurwHk7vRzFIWh8FJ19mi3Oo8kXY2Os8SzxDUnDyW3KeNi3oXOKivI6ruNOMZgqqLlsIqz3w8fUgtKA5zgVCQdAuci9XQL42G8nEidYgu+v14N/oGs9VL1DVIEyE9XSYtGhTZY6o0gcdZACNNgnJOkmU+kzrOa56nMsuzGN1IVZLqHOVxyhyMV7EK/Hj6ILpYVZ6sJlmgMqHaFwWrJyUt4myL+3yVbzY2+x+mJ2zG81M/wO+2/pGKiCxiznuMy4oRXkcTYzFsl8F3fvRttGQ7ULNWUXDkYOMyoAzVeWcWjZNtClvnzLkRbZ6CPUMnf7qV7YRjymlO+WII8Tbh1jE4Mx6VpY4Hp3H7r0cRi8X0/1/dmz+m+qq0Ah9JBXSE4yP5tOmT1gpoBX4VBUKNwa2WB+uqwU9IGTaDXbmrA6U7cHLo3cEBusS4hLCPxWmNcAlPqBgyEE4RTScxCqm/jjAXfS1zCVKEkuYC4hkOwFayoS9mz6LT0o1jzFAnK3HmmbN0k6dVHvpk+jAHZxe2RV9ShI0yMXWHOHALGzpajijyxY7oNuxicUq3ZSakuttkNKkIiclg4u3e+5/nEhF0UxxsW83tEDSeNCXeoat+JnMcc6zzcTpzgjxoD8+Z5SjVtBr0p6RJsFbDjtg22E02Dt7bFCYvXo3ReSdCj0uGF+mQmw1mvB19VZE/cpU0894XMcs8l0uMhyUCzXM6wseeRIL4PRmqhwsDKr8tUZjjdPSFr/02kXqb/A/Sjd+Flc41yHbHEZ2OIm1NYrKT2W1i7frmX1UUkaqlzAKWQVSsRUUp4UEVhWN0JlF4HJyn24ZJ7ZD/JlBFnri7Bqn69iWROp7XEY5f5QWvb6MV0Ap8aArI/0bqD62AVkArcE8qUCN6rUg83Foni0nIcfZw+GwytaDT1K2GQRkE17g2cY4zskbbh+nCpHJpG2pGNYA2m9owxKFxhXMtEhw+e8hGtnDYlkhItBxFrpxVA3WC6LgUMXDWmomRj1tc7JvkAt8I4xJlrHauV8uE5jrb9rhIKKUsfdle1T6Yp+P95eA31UKfk4Uqsuz4duQ19Vy8E35dDd69+Rt0w3tV3jhoamQhzBY6xVOqrKVGBNwC20IuCG5R5yRLgJVqBa4GN7Kkgpi41igFKc0mVpfTbb6ZvcamxTlsZ7yDvnwvGwg74G7wqhy2sK430eXOcxnSZwiQ/DEHLRzahcJhqdvoxhsUd7rd3KmGezPfjDTb2rjkuEaVvsw0z6HDfhYL/UuxaNMClPIltEzSiW6oo3GkQ+WgA8w5W/J25qM7UG2owp51IRqYUhg7I5+DKqkizWNdKi9uJdHDyIZCM9F2+kMroBXQCtxtCmgH+m57RvT5aAW0Au+bAo2NjVt7nuhQcQaha0iJyhLnckSr02qRzmq0MarQQ+Tbwypusci1jAuCDlXL7TF7FZFjqNhHPvNttNu66MEa8RCX6m4TY/eg73EMlG8z4jEHrbZ2POB9jIt3jRiku91ibuNjhDGbDvFwZYDouYJCxg2V+jnAt3IBb1jlqdd5N2GkPMRWwpkKjycLixKzkEW/HBcAI8wwy9ckLy0LjZJfHiz1qduLE73E/R4Cr4ntg2m6z3L8dmsXb9OvrmkPyRyd1hlg5Fu501LQIrEPH5F5guKT0hhhXy+mJkFLSMVaFhHTd6d0Sw39DjrootFEeVRFOtb5NtFlT/P2KxHm0qOca4zXKRxpuY3NZFFYvWc7PwfrPFaQXwkTTWdUjYWmCodh/q6ZavAkAqgba8j4EwhwUTAVisOed6BuqaFqrMCd9aFk5yIlv1cj9m76fFQ70O/bT4U+kFZAK/B+KKAH6PdDRX0MrYBW4K5UwBawbrU9CMyjS3ssvR/zbYvxbux15eCqxkCWoAjH+Rgrr6Xyew/Rc/I5lo/hYuoMMW0WnE0fV22D0lpYYNzjQvoEi1iukO7WwHKS8wgQcSfRDskPX2As4g4d6PtdjzFf/Ro2ex7EufRpRa64xtv2Ez8nw+6h5F6eyyLs5YKgxBj6sndwOLVXOc5nGQ+Z4ZiN/fGdHLxzXIK8QaweMXH1OA4zNjHPsZAZ6hN0hldzWB2mk85SFkZHDhJbJ4OsRE2kLlxc5t7cTUXS2E9U3VzHYl7nQVUIM1wcULGN+fzaBZ6f4PZ281wk432YC46juRHFoJ4ojjJMUcVIfkiVs2yLvIS+9G1EqpNsaryshvWTROMJ6m6AjnaQLG2hlOyOvIX5rsVkR59HLlbgImActNBVVEYiHP5oE2TB0E72c8lUQNaZhjfF0pTWYVhI4Qg3jUPc6qIphwrxd+ELcT1A35U/YfqktAIfXwX0UsbH97nXV64VuOcVWLhwYf3J//ygyjVLRMDIbLEsAK52blQFJn1cLFzkWKY4zf8oxiTb/Ya4ZCe3F2zbYKGfnGRGQRiPkIIU4SEfIcd5Kd3ca+RIz7cvVlXf0looKDzhQKe4kOcwuFg84mXsYRoDbDxcSqydVIU/GfgEZBBd497IbDFjIUTjqcrwuLCWOxDm7WXIFkJHi6VNoepkOJeGxKcDn1JlJv94rtIOuJ/EDHHRhSAi2ebrHO7nshK8ifGUF8I/xHOhzzOu8d5CpMfo5aB7Gw8HnsJPJ79HXbp4lSY8RGqIUDyWulaqOImq9mbhCi9boebEaRaXWnLf59OnsNqzQTUTCo5OFhW7rDPZYhjFJCkdkvFOM08tjvgmvoH47rbvoJguo1ogd5oOsxzTQ7RdhEOyK+FHjU2F8VAYM+7Mx9CsW4oDLS60RD1sRTtSwRjO/f1lvUT4j0+6/qwV0ArcFQpoB/queBr0SWgFtAIfhAI2v3VrYtOEikG8FXtZub3lalnxkM1svduX3q0W36Qo5B8daBkUpwpT+Hn0xypL/ML0D1TZiTjCF/JnmZOeYLHITsYnVmFn9E2scq7Druhb6vQlQ/1W7DVF2Hh+6vvMBrN1kO60DOAVFrccTRGlxwFzH/F30ly4j+UsQrjYE38Xl9PnFKd6Z2IbB+dWDqoncZn14HXe75XIz7DQsYRlJ0cVw/pMknQNOuVSyHKQg/cjvmfww8n/Qnd5GXZH32HT4TWFnDuZOMJGQRPReC8r4sbOyBu4we9JxfcOOvHttk5czV5mK+GYWirM0cneFXkTp4nikzcbxxIHEa2E+Xk/rvN2+4muu52+jt78dWybfpFvFFK4lbmOFZ5V+OvRbzMrbVXLl2dTJ3Cf7wGlyx9v+Jf4yZ2/gSln44JgSS0RupI+DMy+iaw3hYIli3gwjCIjGxOtg7BWrRht70eVg3XJksd04zgyx4ragf4gfkD0MbUCWoFfWwHtQP/a0uk7agW0Ane7AuJA/8nf/QGzvQFVn/2M/9OKgCGDoizkeUze/3YJ08TAeYm2y9YyqtJ6gBEIl8mNETbzCe7tLdImHvU+rTLFgn6Txb2TmSOYY5vPfHGS2WmXajqU2wtSboQcaWn/k+ptm8Ghikwu586pYwnZQ+4fLk+rGMYy5yq8SVrHUzw/YVLLcCzMZXGUbxavKJf4Pi+zKKwMlIpt+RiiM95l7XkvDsICGHHN17g2cri9gRZrG2McATUISwFLjAuP8iEO8RgbDwXLV+Jy5VPBT0EWGe0sWikypy0Os3wc4FAuOW55x7GAUYxLdKfFqZ5PvJ4QQsR5PkpM332+BzFN+oeL1y7Li/JGxEVkX5TlLsudq9XQLcUvfksQ3/lLDtghFrQkG5EzZ1A1l+GLNyrHO9kUgSPjUlGO5kgHB+ppmMpmeBjrmGwZxoUfX9MOtHpm9B9aAa3A3aKALlK5W54JfR5aAa3A+65ArV7DWeLelthXolgp0rE9qGITJuLbHvI+QRc4q+IT8sBhIuwm6MTKwCtRi3fjr6sIQoRD7vXcJbSZOiDZ4SzjCQcTe9QQeTFzhtGOPG7R1e2xzsFQQz/eiP0cy91rGBW5oDK/+XqOsQWDyiWPkcwhjYh3cr1qeK6zyc9G+sY1XMK13GXFXN5PV/oOF/waagak6yk85nuWx7+uFhgNUpHID7kuQdu5GMkYLQwqfvVR5qoFpXeDpA2JfrQzD82TRKacZoHKCcxzseY7fYYIvBtsKvwkztEZP285rYbyJa734hlyrUfi+6hRHOM81xFyoIU3LazncWojzGkv33QIvUMY1UIjEd51kdlpwjaYpz6nFjBjpQhylYzKRf9u+x9jR2Qb/vbPfogv/uATMPiBEjF2U40jaB8moq9tBHkW0HSOzEbWloaHld4pewJGhxEFK/F19qy6Zv2HVkAroBW4mxTQGLu76dnQ56IV0Aq8rwrIoLnYukw19QW57He/91G4DF6ym2dgKjuGK6kL6vH2RrcrokS0EGHRyWZ4Gvxs8AuqgfZW/qoiZCToMsvwXKnUVDHKfPsS0D6ls9yEgKGRmLcGVMlednAgnmtdSICcBQWWaefKzCbThS1U2NJH1rSNv9zEzAmZY5SD6VWyl4UdXeYwqmrADTa12Cj131K2cid7C23EyYnruz+2Q53vG+EXFDEjykFVohZCBOlhYUorM9SqYpxjuhA8zqVOcQnyJIfmW+hiTrrCEhkhfpAtRyfZwqF/NvpztxQmbycX/5wNLrSaulCmmyxEkiA1kNz0FF1mKZ4RhvS+6G7Fmk6VUmRnV5RuUpVuZMmKlK6I685otsp8P+h5GjVqNI8148PpQfy7L/17JJIcjnMmtA30wFqyo2m4A83jXSxNcajilYwjxdKVtGowlOMLClB/aAW0AlqBu00B7UDfbc+IPh+tgFbgfVPAxPxvh2OGOp7L4uFiWwoP+B9RQ6d8cQbmqAKVurGOcRItNpDIsT2+TcUylrvW4iYX8h4LPIfNrofV0CyLcrPcs3G+FFARiAaTkYuFFsx2zmeW+By+EPpdXCmeQ4bOsaDipAXQaG/gwN4DH/PQV/IXsJyLifNIv5DB+RE/l/mm/w5Wlp3IucowvNa7kTXiQ3gs+JwqYjG4/nvSbhMjE7ey1xU14wLd5GeDn8XrsX4VzbAYiYnj0G7lZxnY17o3qYXC1e71YkRjnEQNBxF9QtVY6lkJE8/dbwlgvX8LB+UQ895OkjjegZUDvN1sJ92DhSe8rbQpbvBtVhqu8qxTA7kMynMdC9Ti4Wz7PGbBt2Ee4x2VhjJStQS/N5+DdQKROktlChnFlp5pmk2yyVk8/2cv4St/+Xl46l40WBgloRvtynnVwmBTpFUN1UYys3PeJBoTrSh6tQOtxNd/aAW0AneVAnqJ8K56OvTJaAW0Au+nAr6gb2vHoy2kYzRiO2uwhapxnCi3NksHysUKG/eOoIfIuH1EuDVyUJQ4guSj+xmxOESs3GLHcvV3ySdcSV9kRtjCQXQM/YxYpGtJRjsuw02H9lhqP+rMC59lK+BttgRKrbV8biYJ4yi/Z2PGeHv0NfRmrvH4GVxInkPQ1ojzyVNqMK+ihglGJrwcuo/y/GQo3cNzKvLXBQ6dMvyKcyxRiCx/XaJzbjVauaB4Q9VtF+l1n0+eJl4uzPO9zXpwNy5kTiNbyrJi3IoDsV3Eyi0iUu+kKj25RKReppRhbGUSO8JvqmG/N3uTg3YDkXzXVMW41Jlfz15UteSHiciTavDj8YMgGwNJXvvO8Dal1a3MVeU8j+QHuQh5Aeu996kh+yutv4/DdKtbGfcQEom42nOcHLbH38G/fvjfYvvNN1DjcmXSFUPJWEDdVEfMF4YvGWK8YxSWkg2TTcPMRWeQOaqXCN/Pnwt9LK2AVuA3V0AP0L+5hvoIWgGtwF2qQEtTy9Y//so/V4UhMnDOsM3CTDbsmRro1prNzCX71eJcvMoiDy7QrXCvVVEHN/Fznw1+jei2ZRzyauQdd3IQtXAw9bJI5Ql1/4d8T3CublDLeku5BFhkSYvd6FTu8Feafk99XkLU3aP+Z9Sy3zrvZjRbW0m+6OYuYI3YtxiTFBW1XPh44Fk16C5zr+Qw2sUM9WrVejjPsYiLewtVDlmWCqWsZAFpHF32Hmzw3k+cHN1l/lLXwcITQeO12ztUiYoUwsjgvoz4PBlUl5EaItXd9/kewir3OuUyLyNLWggcq3gcWZ6Mc9nQR1d6nnOROsfZdJmfCX1G4fjE1X6u6XOK6tHGoViWBQW35zC5mLWu83G7sNS9gg76fWr5stM2A3N5HMHczQvZ7yEAAEAASURBVOdnGe4FbdfG87uZvYqvrf59HL9JqkjMCVvJgaKroApWXHmvKk/xJAPwZQJwFFwYv8QSnHz+L+7Sl5k+La2AVuBjqIAeoD+GT7q+ZK3Ax0WBYDC41f6AAQFzCG8TLydtfv9YmhLPxfAOv9ZobcJPp/6Ww/VsEi320HW9RJfVqagb6xiDeCH8I8plUEOfNP2N5Idxnu7uSGkAb0VfZeyigUPiMUQqEcwyz8Xx9CGVFxZUnUQq3o29wba+CHF0NVXiIkPra5HnmasmRzpzBYkaF/boap+g+y0D+j6WnpgYYTjC0hQZ9k/QJT8eO4AnQs/xPL+n+M6HuejXS6dYClkOxvYoisY5Fr40k76xP7ZTOeCX6FzvJR7PY/YRdbebC5D9ytUeYTRjoNDHxxzCQr5BeGXyZ8qB3kl83S3i6aaLgunbrQb7syxsEWKHPEaMmeqJwijOciAWsserUz9jvKMFr0//XBWwXKVu8UKUA7WD57CbGXI/vjf6HfUGQ45XrxDlhxKO0sV+PPgsXpr4KWaMzse15rMwpa0qQz7Sc5vLk0ZMh7hY6Ekj4Y6x6psxkCNlPUB/XH5o9XVqBT4iCvz3cN1H5IT1aWoFtAJagV9VAcHY/d8/+b/QYWYNNwfdKIdcGXgFK8fMBS7lzqpmP4lbyHCdpBNtUstwXXg19jN8yv8lNhgeYKa4iVENn3J7xSHeFn0Rnwh+ASdSh5S7LAO1xEMkY52hy7qC+en3KBVFPp6R/OZjyh2WYpOvN/0viv8sCDr5npcDbtDcqO7nNflU3MFMh1yO5WZdd5WLkFLOIi74FEteFjFW8krkH9hy+LDiW0tJiiwYSsmLlLXINbxH/Qjg5emf4mst/0yVn4gjPFwYUNcrg7owpVcxHy0OsXy+Qc6z1IbLG4wgC2EEm3cicRib/A/gEukaSWaaN9BFf3H6J/hq87fU92TRsI8NhAuYf5Y3C+ezJyFOex8XEwPMVfcTBSju9AL7UrzF8pgVnrVqAVEoJwvcS9R9EpEE3nntHWRdzI2PNyHrT6o6b186hIw9RRZ0EWf/4aLG2P2qL3p9O62AVuBDUUA70B+KzPpBtAJagd+GApKBtm8xqEjC9fRlOqZteH7qB2o50EAk26vhn0HQcKq2m/GG0dwwHeGookhsj75OxJwVJ1NH1DLfYK5P4eHOZ05y6DzFKMViVVDiMDlJ2sipchE/qRWH43tRMdBrLRXpKHtwKXEep3PHVFSkN3NDLdrtjL1Jp9aJoXwfox8FOt4OxjNG+DhOFpS8xKzwAuyP7FQlJk2mFvzD9PeY227HTWao7xR70WHsZnX4JFF5rA5nDjpJF3swPwAZvK8lr6C3dJ1c5jJu5q6iTPLHOeajJQs9mR9n/GOGKj+Rqm/Je5+OH2fSuoBb6RssbjmHeCnOSvAOvr+ocanwLcwgqeNU4igXAXMINTSrTLcM4weiu2Bh1fmb4ZdUpEUWBKUSXFjSFxNneEQ55nXmrKcgdJOR8pBy7ifyo3SlgxjNDtMd9+Bi8Swm90aRmhlGyhpHJhDH0IxeZFxJjLcPqs9Z7UD/Nn589GNqBbQC/wMFNMbufyCO/pZWQCvw0VZA8sHtNnGfGQsg51koFD3WuWz1Y3131aAiD+2WTqTqCRWlEPe2Rjaz1HB3WGcwZrGKdAr+nbllcZalQEUiBk4Ov1Ui1hz83hrGPMY5/ApZQ4pPxI2VJUBp65PIR1/pploADDSEOFLmiYXzKVycONlO5oil5OUK2winy1P8OvF2HKgdDQ4EWD6ygKi865lLLG/pwRK6y+KgS523xCrK9RIz0BtJEalyuO5iEUpRDdwRLgbKOcmxXQ1eFSfJsIo7X82pBUZ5RqtEw4mzPZ956gajQRWvSC57o/cB/iaSrm5kjtlDF90Ou8muHG5xrc+Qqd1p7lbRDaPRqOq9hSEdZERG4iPyRkIWHs/wTYZUnMsQPcs2l/evw2lwEiP4mLoWccpLHNvLtQqfi8X4861/jkebnoHZaII7ESTCrgXOohvB8Ra0jfR8tF+E+uy1AlqBe1IBPUDfk0+rviitgFZAFBA03ALnUuW0RmqTLDl5kQOhlaUlF+GxuTnMdXOQrLIdcANms1Gw0JBjzfcUCgYOm0irwXGVdz2xdguwjOg3YSFvIQbPw+FyiBnoFVz2O5rcrzLB8lit/x977wFnV3Xdbe/pXZoZNYS6EAgJJJoQHQbTbWzAxt2JZRu3xE5x3sROnDcmtuMU50tiO06M/RrbgOnFiCI6AwgEKoC6hNqoayRN7+3O919H94ij0R1pRrqaW86z9PvP2Weftvez70jrbq2zdt44N61wunffG0bd5MUrTy06zVuYpCyvXA5ijvci49UjPqS8zae6D436qBcjfOXIa70wjl7N+47IHenNLk8qmOreaV3sJhef4iZpxvf+vb/xMlxYrucCxRm39Da7BoVCDM8tlSNsL/31uJFaXfG8sguVx3qYO634dGXAONmLT44ow4XNuHfrpcW3mxZ7zrO38omeZ222VQZzxcVCQc4oOdsV55ZowZRS5YKereu73NTCU53FTp8zfI4WURnnhWEU5ZQoXKTeTdCXi1lF57rLR3zAzRx2ppzzHq+fFvdtXyZslvvi8gov1jxLbZhaNM0tbloolqXei4i1kf1uY+9a1zOjzVUMu8F1F3W6subRLqsjx3UN63DDW8r5MEMAAhBIOgKEcCTdkNAgCEAgXgSGlZfcnnel00zsMPdC/VPunKK5WkXwOb3M1u32dOxxzzc86U7Ln+lebnjWXVlyrXtLM6xlcpIbuxs1k7rdS1W3TC/S5Wnm+iUtb20zuTZzu1jxw7OVMcPieu3lw3eblynUYapCJhQ+oZX+LF55UcOrXtaNJ/c/IieyVdc2eSv62SqBtsBJg/IlWyo4y/hhi50s16qG5kC/opRxc4svdQ/s+63n0OZp5va52ifcN8b/jdLXLXXmWNtKiFoNRY55vUI3NnuhJSub3/YWinmu5klvpvoV9XNby1blfJ7j1moW+3zNVq/U6oh71e+VSmPX3d3lrXi4VhkxGpWWbpdejrTZ8MfVp+bOJrdJoSLP7X9SOa5P81LdTdZzu7vFTXHYp2t5740t7+m5J2nlwpddj5z3J/c97Gra9mpGO8utVrhMvrKCvKKXDy30402x2Ny60Y3MG+XeanjD/fHYr3jLhV9WfpVepFzumtobFbYy09WNrXZdb2e4rWPec8Vtw1xLVrM3e139zn5eIozXLwX3gQAE4kIABzouGLkJBCCQjATGjB5z+9wPn+e2dm1y5xdfonRuPd7LfZcoVMEWERkuZzlbs8LTC2a6Hs3O5inmea7Om1t6iZzmfHdV6Q3ulILTNeNcoqCHTi/U4cqy61xdpNadpfAOmw22VfhOUbYMW0XQnNtTtYiIzVRnZWZ5IRUW/tGlcI/9kb3eS3qWBs9S41mKvCvLr/fS5s0smuWlqru2/EavjebQWpzxTM2e1ylsw2a1ZyrcokohIacVztSLh8NdmVZW/Ojoz3iLrswqPseb0e7NjOgZ470+WQYPm52eK8fZliC3NjVqxtgWeJkz/CJv4ZPpxTM1M3yS++ioTytE5FylndO+0tVNKpzqLlO6uxzlvT5TIRqWR/t8XTO18DTdo8GbkbYvECdphtteDLTVAm3GeqKus31bcMZm5C3131fH/aW7rPwD7uKyK5Sab5oc+YsUptLmjcN4hYPYvW2pdAWjq7+zXO5pmW73UzWue5hmoltGurH7JrkNGzbgQCfjLxhtgkCICeBAh3jw6ToE0p1AQXne7RsvWK7lrUdpxlMzsnJAdykV2xqtMDhFK+O9VL/A3Vj+UfeQXiY0J/idxiVuTfsKt0Wzpe8qs4Zl5Jhf84CrlRO7Rlkq7MW9Da3rvEwVNlv8bN0TmpHudqu0yIq9ENelF/ferH/F1epFxAeUASNbf16ue8a917Hana7lrJc1v6XsGg1eirpReWO8hVHyFe+8Vc9brpUMLVb7wb13u3F6YfD1hoXKvvGSt+z4G8r2YU7yI3vv0YuNBe4VvahY071PS4FvVYaMpa6i/Bp3X/Wd3uqDbzS84qWua9XS4QuVGs++CFgaO3PoFze8rvR7VUpHt0vp6F7X7HCbe2r/Y1o8ZaV7cf8Ct1oLp7ylc5bWL/JWFLTUdi29LTr2lLc0+Mqm5W6xXijM18qJz9bM9/JKv6CXHc8ddr63OMwi9d3is+/Z/WsFa2R6qxlWd+1yqxqXu216yfEUhYK8qOXI63pq3SN77vVm3K2/ha7Ye7lxlWajJxVOcV1ntLi8t0vcxgmrXUlNqatavxUHOt1/WekfBFKMAGnsUmzAaC4EIDBwApbG7safXq3ls+coBdxuL/fyEoVk2Izz9o4qOdRy6my5bb00ZzO1u7RYSbdifkdlj1ZMsXP75DBHlO7OVgG00AWzUUrxtkIhELZUdtCWKA+zLWSys2ObQjgmerHRmYouXt32rrtC4SG21PYeOZP2op45uRdrIZSOng5vRUFzwi3V3eS8U9xW5Wu2FwzvVwjHaQVnaFb2TIWMvO5uGfUppc17zetLbdd+rUC4zV1VfoOXjs7aslp5mG12eUTWKDnqb3ohG+acfu6k27TCYqW3WMra5hXeLHSFZtFf14qH1oantbrhuZo1rlc8daNCVCw8o72nzZttt3PshchqhX1MKzhNeaefcx/QM3O0fHlnpNPLP93a0+I50hG5wx2RNs0mr3S79SLhVeUf9NLw2cuO9oKjOf6ZirHO0OIz2XpZcEXT296LjeeUnO9+s+t/FVt+lfeFoLW71V1efrVbWf+Ou+sX97gJbrJb8PQCV1NTw79XwQ8cZQhAIKEEmIFOKH4eDgEInEgCheUFt3deWu+6MrqUok4zr907XFd3h1slp/bk7Alycl/0MnK8qgVUMhVysKr53QNLYOvFt6WK1bUZ2qdrH/UyRqzRoicb2te5EXpRb0/rLs2UTtasqJagzoq4zrZOt7Nnq2uRM2lOq4UvPLrvPreq/V1X2Kv468YnvRcK1zSt1Ez3aW5n63Y3RS/Tvac0bxYzbDHRL2jp7iKFirxV/5p7telFNz5zktdec8JtcRRzjtc0rlToxUz3gmaLbeXA3N5cLc+9SPmks3XPbV5oxYuaEV7etkwLlyjPtdLc2TLhllrPnPTX6151rZpRrm+v82aBq7t2uxUNS70X/PYrfrkzo8NtbFrnKhvFQ39s6W6LBd/cvMGru6boRjc8X2Evel5Xe5fLyM5wWxo3u6frHnHNHU3u4Zp7XIkyiaxvXCOn/AKX0ZXh8nMLlFpvuef8W27rZXVverPgdo79A/SHfQ8p60iB4se1MEzd854zb9szNeNeP2Wvc+9lu3Vr1zEDfSJ/Ubg3BCAwaAJk4Rg0Mi6AAARShYDNek6Vw3px8RWKDZ7ovZw3PKvMjcnRktqKvzWH1XIel8spPr/4Yq0YuM+bcc2P5GsGOkNzqhFn55szWdWxwZVmDdfLdtvlLG/30rU90fCQ6je5ypbnlM+5w3UrLZulbBuntHIWP/ylk76hcI597rLhV3mLhnRldCpmeZv3Yl1vb68cVs3iZuS7U/OmK/b4JC893JbOje6m8k9qljbXi68+U7HPtsT4GUVne8trN3TXySnu1IuJzZq91pqJSld3uuKim5WVw1YDVCixt9z3CMUWj8ga7b0YGNGzMnSgRMtuWzhLS0aL07uQXtlirDdoMZQutT/P2iIHPb/X7lvkhZSYI7yre5v3jA3da9ybdQu94f9D/QOupmuvq4lUa3b7Iq3EuM/NyJvtraY4Mn+U5/AvbjtwbltEqfmUGtD6sbVzk7JvFCvbyS5lGVmmFIETFR6y39029pveEuYT8qcoI8oMvSBZ4+aMvNBV3HS5i0TUWAwCEIBAEhFgBjqJBoOmQAAC8SVgLxFW3HyZHOViLec9wnMQi3KLvZhmC9mwmejzSy6SQ9qtsIxlCpmY6S27fUX5td7CJvYCoDnRTZEmOdgXeasGzh52nuKJMz0n9b2ONW6anF+FLrt3W5a4c7UC4eq2d9zW9s1KjXeBlsZe6y7WS4aj9aLe2QpVyJFTfG7JBd5CKdZTi4d+oWGB94Lezq5tXliFhZtE1CJ7QXFd+0rvJb5dndu9sBCbdb542BWa9bZQkpO8lwzt5UbLWW2hIvbioKWis1CMUwqnuVVK13d56dVelo2K0mu9BU8sn/MVZdd4L03O1ouD1d27vVnxHC20sr5ttZeC7h31xV5iHF8wyfuC8JXxfynnvdddVHq5Qke2Ksyl21v2fLrS5+XpS8oLdU+7qxWyYQvI2Ez5DaNu8doxueAUxT5XeS9grpSzfFbJea5Ky4ifXnSG0vWN8haRuWDYpRqPfV6O7hbFbTcrfaAt7GIveG5VhpE5J1/onpn/rKurq/vH+H46uBsEIACBYyfADPSxs+NKCEAgyQm0a+bTlpo+NW+m0sO96M0kL1Zohjmi1W17FOYQ8RYweXD/XTqW5cUta7JWq+Rt914atOW432h8Wa+4lbhKxf+6SKbb37ZfLxsqNCLS4/a27/Ec7mWNi/Wy3yS9mPemZoFXaFnw09yTtQ8rU0apt/peQ1e9VgN807V1NnvEntv/hLe1eGybrX5i3yN6me9RxWafoVURlx3Y6oXDXJenlxCf16z3Di8tnsVAv9H0ilYpfNZ1Kn7aUtbtURsslnp/x36FTwzzXhw0J/eh6ntVt8+tVUzyKqW4sxUVLaWexYJbmEh3pMtrw87WHQrJyNHy2+95S5DX6Jr2rnbvBcA7d/2PZsgL3S+3/6cXs/zSvmfdupbVSvVXrtUT870Z6vt23+l9Mbm/+rfu2X3zvVCVBUrPZ8+x7a7OHbpmldcWy0G9rnmVQkpeco9VP6hY6V0KXXnaNWr1wx06b6FirrN7c9zi2oW6Z57a1+N2Ky49Pz/fays/IAABCCQLgexkaQjtgAAEIBBvAvlaVvqb477j3dYWBenN7HUVWgilyl7UK57g5vRc7C1ffeuoz+plwV5nM6ajlcbt9GEz3Mmt4+SQDnefHPUFbxnsqUWnujMLz/ZmVotbizTvq7R2WlSkSrPNll3iJGXOqFd2iS+P/TMtPtLpvjburxR2cZb3bFusJUvT1F168a5dL9rZS3IWwmGp4DL1tuLq1nf0st+XXZ1e5DtXeZtt+esxuWPdteUf8RYbWdz8urPUe6PqRisc5APeQi6nawW/eoVzmPNsqwXajLOFothCL7aYycUlV3hLgFs6OvsiYLPFljJuolY1LM8eqbCNNV7bJiv13OT8U/SS5E6FX5S460fe7Ebnn+StdHjH6fd61+7tqHYbFf99jmbYN+1RjmYtJDNK54zPm+BuHPMxb2bZlvD2bWz+ePeGXlycVnS6spas9dL7WeiJtd0yh9hYlCj0xBZxuXD4Zcqn/ZD74Mib1Ocx3gz9GUpnZ/c7Y/hs99I+fXHBIAABCCQZAUI4kmxAaA4EIBA/AiNGjLh9xFUlbpIWOVlQ87gX32yzsDYz3dDZ4O6s/rn7QOn17jWtJji78Bw5d9u8BUQ6utvdgrrHvWW9n6x9RLOhuUptt0krEp6upbVXuGfr52v57PHurr2/9GauN7e/5xa3LHSFkRK3SDPEN434uNK1PevO0pLVL9Q85cUlt3U3Kw3dvV46ut/tvsNbcfCB6t9pRvlV3fcMzZA/5y4tvdLLplGWU66Z49Wafd2hRVSedNtbt7j32td49zIn3RZpmSEHeqvqn6l93IuNtoVMbNGSp2r+4HLV3vWtq9x2hU9oQt2bqS7U8uOv1L7oOdE727frpb1VXnjKEzWPKdxkrlui9HU79MLgFs3Yv6oFUE4tnOHe1suNpxef4R7Y9Tsvrd3Kpnfcu0qbZ5lKlmgm38I/LHVdRH/eqHvF5fTmy7Ee7Z7c+7BCOcrdisa3vfCXaqXNe0ezz/bS4is1L3gvZ67SvXZ0btWiKyu1omK9t6rhw3vudrVdNe73e36jRWhOckvrFnsZSPY+X+f27dtHCEf8fjW4EwQgcJwESAt0nAC5HAIQSF4Clsbu3vvu9WJ239LqgeM0M5qvkIR2OZpbtbiILWFtC49YzLAtolKeM9LLamGrC1p6NksP16ZVBAv1Qt2+zr3KstHkzVJbyjpzwm1W9kMjblGYxlvuQs34Wpy1WURv6GXa23wym2leohUO7V53V//KfWbUF53NKNtMsN1nspz7LYoLvrLsWm+RktKscm8G2VK+2QqKlp7OFh6xmVpLK2cz0V0Kv1jevNTNloN+f/VvNEs+z3Pgzyw4VxkutrjRio8epdncpY2LnMUYv62VDpt7mrV4y7laITBPWS+KtJz2694S5JYiz+5tGUgmKV1fiWaXfavrrPEWfalq26jrWxRPfZW7t/rX7nNjv6zVBV/zrrMX/Cz3s5n11WKwN7au19LhGVpQpdZLbXeR4rbv2nOH+/zJX3OP6kvEB7SAzPqWta5A8dOnF5ypMJlX3AVavMa42fMtvMRyYts99nVWu69+6utu1apV/HvlDwxbCEAg4QSYgU74ENAACEDgRBEYMXLE7cVX5CpTxD73bO1874U3W/TkbS2SMqNgljJKvOq9pGeOrYUlrNFCIW+3vuXGZI3VAiVLtHLeqVo++x03oWCie1kLgFQrtKJdDvXdu3/pOpTyra2rze3s2u6KI0XKJjFZeZELXWtbq8vNyXW1bbWuIKfALW94W7OrdW5sznj3kFLc2TmWIm+PZm93tm7Vdpf3wt6u1p1a4bDGPbb3fmW32OdeqlmgpcafclmRLG8J7VKtnLi5aa0r1iqEFr/9buti19ppM86PaTnwEm+Zb3M+H9QCLk1aybBKs9N723YrTV6me2HfApelPNSr5SS/pxcF1zev8ZzUXV073Nbmzd5LjisalniLruT3FLjuzC4vi8iCvfMVqNLhXq55Ti88NrqGDs0Ed1W70twRbk3DCnd6yZnuvea1Xhq8prYml5Wd5X1xeHX/S2pDvWabn/fS5lkstsVl2wuPS+oWiXWxW6+Z51w587Zojb3Aabmlbalwq/t/O/7bTS48xTV2NLjNWlL8jcffcnv37mUG+kT9onBfCEBg0AR4iXDQyLgAAhBIFQIRxR5b/O+coosUxqH0aHq5r76nRi/pzXAWUpEl53JMzsnubC3L/cHym5WKbb+Xzq5Y8bn5mnW2FfNsVrRNccs5eqFvmDJY2EIfo/PHuutKP6z80p3u0mGKSdbMdaEc45q2Gre1Z6OHZ5WycVju5ZWtbzsLn7CwiymKN7alvy0U5JJhFV56u8+M+ZLStp2qTCGFbo4WYplTeIEXU9ysXNSzC+fI4S7ysmis08uAe9U+i7le377KS0HX0FvvzXrPUKq7HgVkWJ7r6Qq9OKPgLC+jSKtS23mx13KCCzXzXpI1zHv+LM1ED1OWC4uzbtEXgrUtK11mJMcL4djVvV0rES7x+mDXXzT8cmXjmCwneYzeoYx46fgaFXJhy3fvUiiIxTZbbPcmhbG8U3fgOlvx0ZYcn6ylu2322TJu5On5pdkjPJ627HeuVkgs1Yy9TSufnDNB8eDnKFxlvpfmb3z+BI/dHi3I0tzelCofN9oJAQiEiAAz0CEabLoKgbARGDFqxO35V2e4GVrNz4KBa+SAnq6yhW/MLD5LoRWvu/LckUpi1+0WaMEUe9HOFjqZLYfaXjg8S2ne2rTwSK1yEtvM8SLFK0/Mm+jNkloKvE+O/rzCQiZ459iLg6W5ZXKWi72whbF5J7tXtVCLhYi80VTpZhTPkvPY6yy+OUMhD+297e7MkrPdOi0rfooc6ucbnpazm6kZ5hL3mpbwtjCM6XJCr9BLgXnZed5KgpvbNyiE4wo9z5zeVd6qhpaHepjyU2/sWKdVCudqplgp94ZfrBccx2p2e6f3/Hc1wztSTv6G9rVelgxbFXFm0WzP+c7WQi6XlFa4Fv1pVro+Cxd5t0Uz9HqRz/I852lG2GKqh2nm+4Lhlyg/dY47R0t3nzXsXKX1K/NS3ZmTPkbPszZY7LOttDhdKxpaOj6z04pPd3s793h9Mfb2YqPNRk/UrP2Zw87xQlfshcP1ivO+UqskGm+LvR6WO8z734K1T29gBjpsv7z0FwJJToAZ6CQfIJoHAQgcOwGLU27WTPNCpaJ7uPZeC9J1T9Q8Ige33UsN19bT7lp0/KF9d3srDC5TLLPFHL+ilQlt2etmOaP2guFJmqVeUPsHLV/drhCI9e6l+mfcFcOuUVq4R714ZIsHrlZKNlvx72WtGmjx1r/a8TPFMJd4GSbseaUZpcqaUe9GZo9RKrfVbmbBbPdg9V1azrpNz3hRIRebNBub6b3YOEzZPyy0oVWz0K/pnsuVNq9Jcdqb2tZ5MCxdnM0ev9u8xAt76NRS2V09nYoX3uO125bJ/oVSz71e+4pivgu8NHO2sp8ilL28zg/v/b27a9cd7vG9D7oH9+hFRjm8S+sXKavGJBdRar/R2Sd5uaxthnl183Lv5cfFDQvd73f/xuX1HkjeZCnqzPztkvo3XEdXp/qx2dV07ldGkf1usV5M3KUXM3+17ScK9VilNHUv6/gGcah1b9W97mo7a70wj0a90Llf11S371acebOXMm9X+w73ePVDSnFX7z2HHxCAAASSiQAz0Mk0GrQFAhCIK4FxY8bf/ulPfEYvz53tJsg5PLtkjrc9q2iOZn/P8l4ctHR0Zxef771sd0r+dGW0cMqLnKX9S7yXCm0WtVExxTajPFNp6Wy1wnknfU1p46YrMKLDczrtBUSnhUays7KVum62t2rgBC1CYrO54zVjfd2IjyhGepK3xLe9kDg8p1QrD47xVi88VYu3nKHZ8JzMHIWKNLt5Y76uUIydmuXOVRq7G7377+/Zq9zSMxSOkqcwjt2a7bW2zPJmnou1MIzNek8rmK4QkWle9ow5JRd6cc228qClg7M+2EuRlqLvhhE3e8//QPl17rzhF3rhKdYmW+J7pkJBaiP7Fb5S4IVuWFo/W/zEZs0/MuoTbo7OH5U31hujiQrrsJhqm5m3vNDNantN916FXvR4MeNztDqhvUh5g9LTXVR2uSvSzPrFpVd497Y2jVUKwJklsxT/PUmhM3u9mfKszCx9aWn0nmf/azBTY2Qx2G8+voQZ6Lj+ZnAzCEDgeAngQB8vQa6HAASSlkB+ed7tLZft97I9zN//oNupmNq3tKDIPjlsWzXDO7/2Qc+JXdO8Uo5kq3uraaEcvHx3es4sZYao1PLYTXpJ7xEvC0el0szZC20TMqYoxdwKL4zipboFynpR5a3EZ85tdmeWe6PlFW/Vvrv3/MoL2VindHTtmkneqJftarvq3HQtlf1izdPevZ9Xirs9XTu9GWBLV2dxw69oxvnq8g+5LS0bld0iyy1VBo0lmv3d3rVVLxg+oHtq1UTNMFsIyI42pd3TjK6tEvh8zRNqZ7Gbv+9BOaAjXL1mblcpv3S54o+f0zELs6ise877MvBi3TNuXdMql6vQkE3N690ZclQXKQ2dcdncsl6zwfsUWrLKmwHeqaXHn9/3lMJTyt3Olm3KspGlcI5h7vn9TypU5BJvBrkp0qgXMFfq5cg3ncvqdZVKg2dp9BbXL9QXjhr3By2a0tnd6T3bZqzPV6z3orpKb+XCZ7SozBb1wcJa1qtNlylk5el9j3nhJC/tf84t0cx4zYtNONBJ+1tGwyAQTgKkBQrnuNNrCISCgKWxe+CBBw7pq59q7ZDKo+z4adrsNHup0MxPU2dp2zoUCpKVke05qd7B6A875ptdZ2nZDqlTCjjbD97fX3TFv87f2nmWf9lS75nZvvXFltW22WvfLCTEXpw0h9nMzrOX/HJU5/fd3/rX+Fs718za6vfPP2bbtp5Wl6/Uc/55wWNW9tvUpXZaG2y1RptV9u/nP/dAu7u8FRD99mVottrOt5jrvnbLLbeQxq4vFPYhAIGEEmAlwoTi5+EQgMBQE+jP+RtoO2I5ljb7fDSLdZ21pW97go6vf09zOM1syW2/7B8LOs9WV6DwC9/8e5vzbObv+1v/vOAxK8dqq9VbuMbRzO5tLx2amfNs5t/Pf65tLW2db377LAQGgwAEIJAKBN6fHkmF1tJGCEAAAoMjsE+nbx3cJZydhAQmqU2jkrBdNAkCEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAwBARuE/PuXmAz3pU510/wHPDfNpl6vz6BAMYFW1DfoLbEe/H/0I3/L/HeNN5um7hMV7b32WLdeCM/g5SDwEIQAACEIBA+hGYrS6tkTKiXbtS25VSvVQjPSaNk3ybq8IyfyfGtkJ1O2LUV6rutkB9qcr/K+2RWiV75hekvvYpVbwltUh7o+U/0dZvr4qHWKX22qUmqVGytn5HypOS1SrUsFjMjre9/59uYH03M4e+OYYiqrtTSpSN1YN7pTGBBny3n7pnAucca3GeLoy3A/0J3fORY20Q10EAAhCAAAQgkDgCQQdkMK34uU42h8U3u8/J0R1zOv9Nmh/d9zcbVJjj7/TZVmg/ljNYqXrfgc5Vean0tDRFypFsVrta+pbk21+pYHW3SiWSOc3nSL+X+nOIK3XMf06RyhXSu9KLUn9Otw7F1bIHebcKnR+L2UBvE+t5xme/NP4IN7lWx+xLxplHOGcoDtnn6eOBBz2r8toYdX8XOOdYi/N04cJjvbif62yGv1ayLwODtQJdYJ9tDAIQgAAEIACBBBBYoGfafyV/XbLZ3YHaZp14aT8nmxP2z9KaPsd/pf3v9anzdytUiOUMVqr+NsnsS5LNJpuDG7RPasdmSYdJwyWbdf6YNBir1Mn+c/zrJqpgs9w3RisytbWZ2U1SjfSgVC6ZmTN0j2T1Ngu/RLIvFWZ2zm+kXVKd9AfJrEKyPn9bshn1u6UKyep8q1LhbyVjadfafexZxqBNsplgf4bYvsAY+/+S7FkmK1udWYXU93lWH7TLtbMxWNGnPEH7+6TPBeqN+V3R+q3a/r2UKZnZ1vat3sbOzrPzzSZLNov8BWm7ZP37mnS+tEIyjv8t9We/1oGfRQ9maWv3t+uDdeboXyqZ/Vb6oRVkFZKxsC9bdt1uydrh2wgV5kt2/WLpB9JCybeLVbAxbohubd/sSmmlVzrw4wVt7Hrf7B43+zvaPi99PrB/tOKFOuEOyVhddLSTOQ4BCCSOgP0FFktPBppk5VjnWB3nxWYDF7gky++HzeLeLD0mmTNwr3SN5DtAKh5m5ryZ4zOqzxFzOK1f5tR1SfOkoH1LOxYLHcsqVGkOTV+rVMVt0cr7tf1dtBzcZGunW7pOuj5atrrBWKVO9p8TvO5V7fxrtOIvtH1TGi+ZU2qOzH2S2VelJ6RCyZy58yRz6M2ekh6QyiTjfYVkViFZu+3+dr8CqULaIflWpcIqyRzXcul16YeSWYUUPNfqvi9ZG0dLNj5vSOb8mVVIfZ9n9UH7U+1Ye2OZtX2R9L99Dt6l/cclmxGdLL0nfUky+6K0UZoqFUs2/ndLZpMl+xz9QsqXrpXapT9I1v5xkjm3Pi8VD7HPa295tGaOtq9Kp/apsy8ZuZLZb6UgO2Pxfcn69UHJvizZGJndLz0o2WfdZtp3SgslMxsHc2D/SMqWPh3dN6fb+mHPHCnZsT3SLsnY2PjaMTvPt5+q8B/+Tj/bsar/G2mttEn6njRF8u1SFez3rj/ZcTPOO5QRXA7l4X9+4BIfLgd+6/gJAQiEgoD9o/9n0tvSNukbUiwzx8YcH3MWYpk5GN+WbLYsaF/WzkvBikC5QmVzvP2/xP1tt+puk8xekP7FKx3+wxyVz0qfk6wcNHMi7X7mvFwePBAoV6rsPydQ7TlSv4pWmANzVeCgOTZdkjlKX5TsObOloNk51i/fMQseq9BOpxTkaHU7JN+qVPiav6OtOXrmRJlVSMFzrc6O2Tm+XadCVXSnQtu+z4seOrj5rkr3H9w7tPAz7dqsqzn7vmWp0CHN9Cu0/apUGd1/Uds/iZZtM13ymU1W2T5H4yTfbAb/k/6Oto9IfxHYDxYna6dHMrZ/Kf2TZGbOrl/3sldz4MdvtflhdL9CW/s82Nj5tlcF+8xan6yNp0u+/UiFhdGdP9J2sX8gul2k7bxo+TVtPyrZvZ6THpSul66UVkhBszbfGawIlCeq/KRkzrqdc7mUIWEQgECSEwj+xZLkTaV5EIBAHAiY82L/wL8rfVwKznJp96CZM2pms2o2Y9jXalXxO2m5ZM6ROcFmdr5/rVfR58cu7Y/vU1cZ2N+vsjmkfc3+rjLn345nRstW5z/3YpXNdkh2fDBm7TfH2GySZDP1EduJmjlwY6S7pQmSOZ+l0j3SdyWrMx7mBMWyfaqMxTB47vbAzlaVTw7s9y3aMTvHt77nH+151k4bp772KVV8RjpXMofZN+OeK/V9pnEzi9UeGxtj5lu1X9DWnNq++8WB48FilXZsTC+VzLm8QzIzZ9ave9Wrif3DPu/+Z8TOsBloe5bN3Fsb+3JXlWd9+2SV1n+/z6+oXCFZ26xsTK+QjJvtB+1IvxM2+32GZPex36W1kn3hwCAAgSQnYP/QNPejBYG2W5nzDjCAS+zPAlySl4v9Kp8q/UDaIv1EWilNlf5KimUtqtwknRbrYLTOHBD7b/hhgXNmqGyOwLHaC7rwBskci6B9TDvmnLwpmfNk5Zuk4zVzfs+TXoveyBwqe745yL7yVbYZzy7pH6WZ0sXSjdIfS3ZNuWTnx7KBOETWDt8mqmBfNMxiXWvHJnlHD/wInm81sa4JnO59geo7rjZuv5T+SNoaPFll+9Jife/7TGNiFqs95rRWe0eP/4eNjTnPF0lvRG/n15kTfSQHOnr6YRv7kmFt7MvdP7Fvn6zeOPt9Nie5QrJ2Wdl0RVRWDpqx7e93Yq2O2e/hn0n2OdwgzZdulfIk3y5Tob9/g63ejptx3qGc4HIoD/8zBJf4cDnwW8dPCEAgbQncqZ6ZE/Qzyf6RHqj9VCf+XeDkj6o8XcqUbAbP/tv6bSlo72lnbrAiUK5Q2Wba+lqlKm6LVprTYPd8Wpos5UjXSeaM/bXk29+oYHXmaNiMorXpbMlmAiukWFapSv85hSqbw2PPqpTserO/lCol31m0fvqO+pUqz5KyJHOYzSmaJ5k9Jd0rlUnWZnOszCqkvn3uW1elc1ZK4yW7rzmHP5LMTpfapOG2E7UfavuGZG0bKS2UrM6sQur7PKsPWq52zIH0Z1Pty8oa6QdSf3aPDjwm2WyqsVkn3SaZ2dYcvymSjcXDkp1vNlnqlbIl33aoUOHvaGvn/n1gv2/xK6qwsQ5+1uxzbHWdko2lb79V4YfRnQpt7VlBq9LO1dGKB7S1/02w62dKdu5CyWyEVC99RsqWPhndN95mxsy+xO2VjKeZOdet0mjbiZp9nmulk/2Ko2yN75ck+wzYdbMlDAIQgAAEIACBBBCYq2f6/8gP5vFn6uTVUkb0om9qu0VqkfZI5nz4jqaKXmaFd6zQj1Wo3pyUvlapitsCleZE3iGZg2TOo7UheFy7nn1WPxdL5rSYQ/iWZM5Wf32t1DELpWiKytr6XSlf8s0c6W9J6yU7b5P0I8ns05LVW/+tbT+VzLkyszb/TrL6OulRyaxC6tvnvnVVOudvpTWSOW12H3PqfLMvQDWSHTNHzNprz94dlZX9PlSo3Pd5qjrMfqyab0dr/1hbc3KtX/4Mlb9dED3HvhjcIxnn7dI/SMbKzLa2b/V23M6z880mS8frQE+P3sP66VuWCo3SIr8iuv2ttj+Mliu07cuiSnVXS2ajpCclu499jn4gLZR8s9ntZVJDdGv7QbNnvxyosC8OawP7Vvy45H8W+hw66u40nXHSUc/iBAhAAAIQgAAEko7AvWrRzQNs1SM674MDPJfT3idQpaLv1L1fe2JL5jzaLHLBiX1M6O9uX+rsiygGAQhAAAIQgAAEIBBHAlW611A70HFsPreCAAQgED4C/n/Bha/n9BgCEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhBIRQJ+eqpUbDtthgAE0ohAaWlp78knDzRdbhp1nK4khMCaNWv268GWjQSDAAQgMGgC2YO+ggsgAAEInAAC5jzfd999J+DOR75lRgbzCLEI9fZa+ubjs2RmO3v27K3H1zuuhgAEwkyALBxhHn36DgEIQAACEIAABCAwaAI40INGxgUQgEA6Eejp7Umn7tAXCEAAAhAYAgI40EMAmUdAAALJSaC5p8nt77LVt7ETQcDCQI6mE/Fc7gkBCEDgRBPAgT7RhLk/BCCQtARWtC5zRVklSds+GgYBCEAAAslJAAc6OceFVkEAAkNAoLGn0RXjQA8BaR4BAQhAIL0I4ECn13jSGwhAIAEEOiMdrqZrXwKefOgjiec+lAd7EIAABE4UARzoE0WW+0IAAqEgsKtzu3u+/ilXnj0yof3tjHS6HZ1kZkvoIPBwCEAgNATIAx2aoaajEIBAkEBHpN3lZuQGqwZdXtX6rtvbtcd9sOwWl+icx+vaVrrROWMH3QcugAAEIACBwRNgBnrwzLgCAhBIAwJbO7a4SXlTj7knrza+6Lo06/uB4dcn3Hm2Tuzu3CkH+qRj7g8XQgACEIDAwAngQA+cFWdCAAJpRGB75xY3IXfyoHtkccbzax9yk3KnuHOK5w76+hN1gRLGucwM/ko/UXy5LwQgAIEgAUI4gjQoQwACoSHQ1dvtcjMHF8LR2tPinqx7xF1b+mFXml0WGlaJ6GikN8IXgkSA55kQgMCACOBADwgTJ0EAAmEnUN25y73W+JK7ufxTg3a8TzQ7czYz9CeedqJiui1jSW5m3hGbWtdd4x0vyx5xxPM4CAEIQCBRBPj/vkSR57kQgEDKEFjXusotb33bfWzEZ5POeTaI1V273Zjck1OCp+Xe3tT+3hHburxFC9xkssDNESFxEAIQSCgBHOiE4ufhEIBAIgg0dNe5YVnDB/ToNxpfcU2RRoVt3JjQlwVtSez+bHP7Bjclb1p/h5OqfmTOKLei5W13pJzV7ZG2pPyiklQgaQwEIJBQAjjQCcXPwyEAgUQQ2NKx8agOp4VFPFX7qGZ2x7rziy9ORDMPeebmjg2H7Ad3mnoa3PDs0mBVUpcvH3aVe7XxhaRuI42DAAQgcCQCONBHosMxCEAgLQl4IQ9HyJlsM6CP1PzeXVRyuTsl/7SkYGCxw++1rUmKthxvI0ZoFtrycDf3NB3vrbgeAhCAQEII4EAnBDsPhQAEEknAgiH6S/m2X0tyP1n7iPtI+cddeU5iVxcMMppROMutbl3hjhTKETw/2cuWP/vlhmcPa2aTYqSLs4h/PgwMFRCAQFIRwIFOquGgMRCAQCIJbGhb55Y0v+69LJiXmZ/IpsR89sUlV7g3mioPOWZLeOdk5BxSlwo7lonDFn7Z0XHo8uNbUiieOxU400YIQODEEMCBPjFcuSsEIJCkBA6kfDu8cYubXnc13XvdDWU3J/RlwcNb9n6NxWM39NS7NoWY+LZNKypO7LOios1S7+jYlvSz1XOLL3GL9YUlaLai4tjc8cEqyhCAAASSjgAOdNINCQ2CAAQGSqCuu9atbV15xIwOfe+1p2unOyln3MFqczafqXtcL+GVuQsV85xoMwf/SHalQh8qA6EP27Si4qS8KQcv8eO3LcvIicrlfPBhx1mw9p1TNNe93fzWwTuxouJBFBQgAIEkJoADncSDQ9MgAIEjEyjLLncjFKf8XP0T7qm6R4+aX9jutqVdGTjyD6R8sxfz7GXBc4svcNMLZnoPa+lpdm82veqqO3cf+eEn6GhrpMUtanrFLaj7g9vXVX3YUwoyC7wUfH77gguTWPz2E7UPuw+X3+qGZQ8sTd9hD4hzhX0hsLzPrza84Ixt0PZ37dXs+RS3vaPKdfd2BQ9RhgAEIJDUBFiJMKmHh8ZBAAJHIzBa2TQs7MJmkte1rfIc6ayMbDen6CJnOYf7WlOkyXNAbfb6hfon3YdHfMLlKobYQjj2du1xRVnFzkILbJsIsxfoLlKsszmUS5vfdG81LfTackHxpa4wq8jr57lFF7hn6ue7W0Z86mATLX57Q/tad+uIzyXVzLO9rGmZTMZonCxcw5ZDH5Uzxp2nLy22HPr82ofceepPZcNz7qrhHzzYHwoQgAAEkpkADnQyjw5tgwAEBkzAwgEsU4WpS87nsuZFcthek/NZ4jnEBZmFB+9ls9CrWt91swrPcy/WP+XM4T5XoQRzSy45eE6iC9ly6i8sucxrhqV7W6RZ8bZIq5eXujSr3Fu62/pgZs5/j+t2Hyy7xdtPxh/2xeDK4dd5TbNl0Z/Tl5ee3m43s2C2W96y1DXri83G9nWeo52M7adNEIAABIIEcKCDNChDAAJpQcCyUvjxzJYWzTJXtCvv8Mjs0W5V89tePmWbFTWn+0NlH0uqGdtYA2DO51WlN3iH7CW7d1uWuP164fH16kpXlFHsTi2a7q4rvSnWpUlZZ8uO35B74H8N3tOseWZGljf7/8s9P3HfnfDPSdlmGgUBCEAgSAAHOkiDMgQgkHYESrKGHQwN2N25wzV0N7iLi87WrHOW29qxyW3r3HzEPudk5LrT8me4k3MnJIWjPTZ3nLJUjPNCOR7bf79b17ra+2LwdsubR+yH05z1xNzJCqeY7nIykyPtnX2Bsdhzk4Ws/Pv27+t/DRYepR92OMONz53opuWfzpLfA6DFKRCAQPwJZMT/ltwRAhCAwOAJzJw5s/e+++4b/IXHeYU5cVj4CMyePXuZej0nfD2nxxCAQDwIkIUjHhS5BwQgAAEIQAACEIBAaAjgQIdmqOkoBCAAAQhAAAIQgEA8CBADHQ+K3AMCEEgIAcIvEoKdh0IAAhAIPQFmoEP/EQAABCAAAQhAAAIQgMBgCOBAD4YW50IAAhCAAAQgAAEIhJ4ADnToPwIAgAAEIAABCEAAAhAYDAEc6MHQ4lwIQAACEIAABCAAgdATwIEO/UcAABCAAAQgAAEIQAACgyGAAz0YWpwLAQhAAAIQgAAEIBB6AjjQof8IAAACEIAABCAAAQhAYDAEcKAHQ4tzIQABCEAAAhCAAARCT4CFVEL/EQAABJKHAAujJM9Y0BIIQAACEOifADPQ/bPhCAQgAAEIQAACEIAABA4jgAN9GBIqIAABCEAAAhCAAAQg0D8BHOj+2XAEAhCAAAQgAAEIQAAChxHAgT4MCRUQgAAEIAABCEAAAhDonwAOdP9sOAIBCEAAAhCAAAQgAIHDCOBAH4aECghAAAIQgAAEIAABCPRPAAe6fzYcgQAEIAABCEAAAhCAwGEEcKAPQ0IFBCAAAQhAAAIQgAAE+ieAA90/G45AAAIQgAAEIAABCEDgMAI40IchoQICEIAABCAAAQhAAAL9E8CB7p8NRyAAAQhAAAIQgAAEIHAYgezDaqiAAAQgAIHjIlD6r50ud33kuO6RbBd3Ts909d/OTbZm0R4IQAACCSHADHRCsPNQCEAgnQmY85xODnS69SedP3v0DQIQGBoCzEAPDWeeAgEIhIyAzdjuvTM/LXo9+ovtadEPOgEBCEAgXgSYgY4XSe4DAQhAIMEEent7XWekI8Gt4PEQgAAE0p8ADnT6jzE9hAAEQkJgW+cW1x5htjgkw003IQCBBBLAgU4gfB4NAQhAIJ4E1retcUVZxfG8JfeCAAQgAIEYBHCgY0ChCgIQgEAqEoj09risjKxUbHrMNkd60yuTScxOUgkBCKQkARzolBw2Gg0BCEAgvQlYPPf2zqr07iS9gwAEUpYADnTKDh0NhwAEIPA+AXM408nMeSaeO51GlL5AIL0I4ECn13jSGwhAIKQE9nVXu1E5Y9Km95vbN7iJuZPTpj90BAIQSC8CONDpNZ70BgIQCCmBLe0b3dT8U9Om9+2RNleQVZg2/aEjEIBAehHAgU6v8aQ3EIBASAnUdde4suwRIe093YYABCAwtARwoIeWN0+DAAQgAAEIQAACEEhxAjjQKT6ANB8CEIBAuhFo6Wl2hZlF6dYt+gMBCKQRgew06gtdgQAEQkYgIyMjZo8tI0V/x/wLOiOdLjcz16VD9oru3q60yv9c1bHJTc4/xR8qthCAAASSjgAz0Ek3JDQIAhA4XgI7Orce0TE2p3lD+5rjfUzSXL+9Y6ubkEYZK3Z2bnfjcickDV8aAgEIQKAvARzovkTYhwAEUp7A8Kwy90rj8/32Y2/XHtcR6ej3eKodsBnbSWk0Y3tgRUX+gzTVPoe0FwJhIoADHabRpq8QCAmBYdnD5SC3u+aeppg9thzDU9Io5Zv1tSCzIGZfqYQABCAAgfgTwIGOP1PuCAEIJAGBDwy/wb3c8EzMljT01CnlW3nMY1QmlkA6xKQnliBPhwAEhoIADvRQUOYZEIDAkBPIycxxY3JOdts6tgz5s3ngsROo6d7nRuaMPvYbcCUEIACBISCAAz0EkHkEBCCQGALnF1/sljQtGvDDG7rrB3xuok5s0wp9QbMwlcKs4mBVSpe98Jq8aSndBxoPAQikPwEc6PQfY3oIgdASsFR25xVf4JY2v3mQQVfEUr4d+oJaT2+PW1D3B9eldHDJblVasru2a//BZtoLhFPykivlW6Q34ozpsVht935Xnj3yWC7lGghAAAJDRgAHeshQ8yAIQCCeBMxBe69trXum7nG3Q2nc+jPLJ7yrY5szx9lse2fVISnfWnta3MM197iLSq5Q6MCo/m6TNPXTC85QhpEXDrZnl1K+nZxkKd8yMzLd9o4q70vJwsaXvBc6DzZ4AIWj5fAewC04BQIQgMAJJXDoNMwJfRQ3hwAEIDBwAkdzorI1i3xawQx3Sv5pbkXLMvduy1KXl5Hn5pZc6oZnl3oPshfS9nfvdVeWXu8qG55115Td6LZ2bJazfLl3vLpzl3u14UV3S/mnvUVVBt66E3+mtb26a7cbpXjg4Iy5OafTC2a6ta0r3YzCWc5me7Mysk58gwb5BPviYqrvrnOvyuG3tIET8ia7WYXnOOsDBgEIQCCVCeBAp/Lo0XYIQMBzHs8pnuvOcXOdxQcvblromnoavSwb5xdfIkIZnvOcn1Hg6rprvdnQfKV8W9e6ynvB8GMjPnvUVQsTgdm+QAzPLlMmkWddu9LUTcqb4s4oPNtzPmcWznaP1dwvR/qMRDRtUM8sVR+uKb3Ru8Ze6LRQGbNZRee4ieqTb/u79rlSffHJTMIvA34b2UIAAhDwCeBA+yTYQgACKU/AciFfMfwarx81csheUho7W+Z6dPZYt6n9Pfdc3RPe7PQbjZWq73FnFZ2XlM6zPxDWn6tLP+Ttbm3ffND5tHbPKDjTvabZ81Qyc5hNNmu+svUdt7LlHZej5dTn6ovOXs22b2xb58blTPCOM0udSiNLWyEQPgI40OEbc3oMgVAQGKF45uvLPuL1dYtevLNwiMqG59y+jj1uVsl53oxuefYIZzOfR7IMzWDbTPDonDEuOyPnSKee0GOT8qdqtcGpnnO5onWZ26w+Lah9zJ1VMMetyVvR77MLMguVzm+sMnUU9XvOUB8w59i+BJhsEZjFza+7+q46N7/2IX1h+OCgv9Tp0SNkAABAAElEQVQUZRa70bljWUxmqAeS50EgxARwoEM8+HQdAmEhMCV/mlYenOY+WHaLW9G4zI0qGHOw60dbuMMc6GFZw12WS46/Ls35PLvofE8XFV7mGiONco4LD/anb6Egs8jlZeb3rU6afWvbZcOucjYOU3NPdUXZxS4rc3Ax3eZAW/w7BgEIQGCoCCTHvwhD1VueAwEIhJpAdma2O7f0gkMYHM2BPuTkJNsZWzDejU2yNh1rcyzm+4ySs471cq6DAAQgMKQEeBV6SHHzMAhAAAIQgAAEIACBVCeAA53qI0j7IQABCEAAAhCAAASGlAAO9JDi5mEQgAAEIAABCEAAAqlOAAc61UeQ9kMAAhCAAAQgAAEIDCkBHOghxc3DIAABCEAAAhCAAARSnQAOdKqPIO2HAAQgAAEIQAACEBhSAjjQQ4qbh0EAAhCAAAQgAAEIpDoBHOhUH0HaDwEIQAACEIAABCAwpARwoIcUNw+DAAQgAAEIQAACEEh1AjjQqT6CtB8CEIAABCAAAQhAYEgJ4EAPKW4eBgEIQAACEIAABCCQ6gSyU70DtB8CEEhPAr29vUftWEZGxlHP4QQIQAACEIBAvAkwAx1votwPAhCAAAQgAAEIQCCtCeBAp/Xw0jkIQAACEIAABCAAgXgTwIGON1HuBwEIQAACEIAABCCQ1gRwoNN6eOkcBCAAAQhAAAIQgEC8CeBAx5so94MABCAAAQhAAAIQSGsCONBpPbx0DgIQgAAEIAABCEAg3gRwoONNlPtBAAIQgAAEIAABCKQ1ARzotB5eOgcBCEAAAhCAAAQgEG8CLKQSb6LcDwIQGDICLLZy4lDHWqQmVt2JawF3hgAEIJC8BJiBTt6xoWUQgAAEIAABCEAAAklIAAc6CQeFJkEAAhCAAAQgAAEIJC8BQjiSd2xoGQQgkMIEctdH3OgvtqdwD95vuvWlczrzLe8ToQQBCISdAA502D8B9B8CEIg7gUQ6m72u12XoTzzN+tN1emIc6K5Il8vJzIlnd7gXBCAAgeMmgAN93Ai5AQQgAIFDCdR/O/fQiiHc29i23k0rmH7cT0yGFwYbuutcc0+TG5c38bj7ww0gAAEIxJNAYqYU4tkD7gUBCEAAAh6Buu4aV9u9P21orGx9xw3PLkub/tARCEAgfQjgQKfPWNITCEAg5AQ2t29wU/KnpQ0Fm30uzipJm/7QEQhAIH0I4ECnz1jSEwhAIAYByxV9JMW4JGWr9nVVu5HZo1O2/TQcAhCAQKoQwIFOlZGinRCAAAQGQCAZYpcH0ExOgQAEIJDSBHCgU3r4aDwEIACB9CTQHmlzuRl56dk5egUBCKQ8ARzolB9COgABCEDAuZ7eHpeZkT5/pVe1b3aT809haCEAAQgkJYH0+ds2KfHSKAhAAAJDQ2BX53Z3cu6EoXnYEDxle2eVm5A7eQiexCMgAAEIDJ4ADvTgmXEFBCAAgaQjsKVjk5uclz4ztj293SygknSfMhoEAQj4BHCgfRJsIQABCKQwgdaeZlK+pfD40XQIQCC1COBAp9Z40VoIQAACEIAABCAAgQQTwIFO8ADweAhAIDEEuiJdiXkwTz0qgVqtqFiaXX7U8zgBAhCAQKII4EAnijzPhQAEEkpgY/u6hD4/ng9vU8q3vMz8eN4yoffaYisq5qXPiooJhcnDIQCBE0IAB/qEYOWmEIBAMhOwF9R2dm5L5iYOqm1b29PrBUJbUXF0zkmDYsDJEIAABIaSAA70UNLmWRCAQFIQ2CHn+eTc8UnRlng0wkv5ljcpHrdKmnuwomLSDAUNgQAEYhDAgY4BhSoIQCA9CNhMcyyr8mZs0ydEwBZRyc7IidVV6iAAAQhA4AQQwIE+AVC5JQQgkBwE1rSujNmQtkirK8wqinmMysQSsC8DGfqDQQACEEhmAjjQyTw6tA0CEDguAkVZxe6d5sXHdY9kv7i3t9fZn3Sx3Z070mpFxXQZF/oBAQgcSgAH+lAe7EEAAmlEYGr+qW5rx2bXXyhHOnS1TinfyrNHpkNXvD5sad/opuSnT3hN2gwMHYEABA4hgAN9CA52IACBdCNQMfw6V9nw3MFutfW0uvzMgoP7Vuju7ZKT3XNIXarsbOlIToezM9IxIITGPtIbOXhuS+TwFRWDxw+eSAECEIBAAgngQCcQPo+GAATiQ6Aj0n6IExa8a2l2mYvoT0N3vVdd1XFoyrdtHVvc8pZlLisjK3hZQsq1XfvdKw3PuyXNbwx41txSvo3KHnOwvXs6d3lfCA5WJKhgYSVvNL7inqx9xK1vW+0s1CSWZbls905L7DAbu+bNptecOdUYBCAAgWQigAOdTKNBWyAAgWMikJOR695tWeKeqn3ULW1edNhs8pU2C914YBZ6R+dWNz5vovecd1uWOgsZOK/4wmN6brwvKs8Z6a4Yfo2bkDvZPVf/pJzPh92GtrX9Op/+8y3lmzmbL9Q/5TmbyZCRwxZ2uXjYFe5DZR/1Xgp8qu5Rt6DuD666c7ffbG9rbbdZ6B0dWw+ptxnsh2vucVPzTnUlWcMOOcYOBCAAgUQTyE50A3g+BCAAgeMlkJmR6c4tvsC7ze7OnXI+n/Cc6BmFs9wp+ac5W7Z7dPZYz1n2U7693PCsG5k9ynNYj/f58b7+pNyT3Q25N3tO8fr2Nc6cz+yMbM/RH5VzYLbZHGY/V7L174m6h9zFJRXOrk0mszaeVjDTkznKb+ulTpthL8wsdBeUXObsRc+5xZe6x2rvcyNzRrvcjDxX113rntcXiA+Xf9wV9Am3Saa+0RYIQCC8BMgVFN6xp+cQSCoCM2fO7L3//vvj1iZzMNe1rXKb2t/znM/O3k7Nfu7yMjx09La7EXKezy6a44YrxCMVzJzPZc1vOQvZ8JzOokvc3u5qhZ8sdRbCYjO9xdklceuK75zH7YZ9btTc0+QWN73uWiMtzr4U2P8ibGvf4kZoFr62e7+7sexWl5V54sJqZs2atUxNmtOnWexCAAIQGBABHOgBYeIkCEDgRBOItwMdbK/N0C5rWeRerF/gVja/484qPs+dVjjziKEBRZklbkbBmc7CKpLNPOez+XW3qKHSvdey1l094kPe0tcDcXpHZo920wvO8JzwI/VrIPc60vWDOWZhHeZMP7D/d/qfgpPcnJIL5UiPGtAtLFTEZrjH5ow7OCM/kAtxoAdCiXMgAIH+COBA90eGeghAYEgJnEgHekg7MsQPa4+0HZZVJB5NGEoHOh7tHew9cKAHS4zzIQCBIAFeIgzSoAwBCEAgxQj0TcmXYs2nuRCAAARSkgAOdEoOG42GAAQgAAEIQAACEEgUARzoRJHnuRCAAAQgAAEIQAACKUkABzolh41GQwACEIAABCAAAQgkigAOdKLI81wIQAACEIAABCAAgZQkgAOdksNGoyEAAQhAAAIQgAAEEkUABzpR5HkuBCAAAQhAAAIQgEBKEsCBTslho9EQgAAEIAABCEAAAokigAOdKPI8FwIQgAAEIAABCEAgJQngQKfksNFoCEAAAhCAAAQgAIFEEcCBThR5ngsBCEAAAhCAAAQgkJIEcKBTcthoNAQgAAEIQAACEIBAogjgQCeKPM+FAAQgAAEIQAACEEhJAjjQKTlsNBoCEIAABCAAAQhAIFEEcKATRZ7nQgACEIAABCAAAQikJAEc6JQcNhoNAQhAAAIQgAAEIJAoAjjQiSLPcyEAAQhAAAIQgAAEUpIADnRKDhuNhgAEIAABCEAAAhBIFAEc6ESR57kQgAAEIAABCEAAAilJAAc6JYeNRkMAAhCAAAQgAAEIJIoADnSiyPNcCEAAAhCAAAQgAIGUJJCdkq2m0RCAAATiRCAjIyNOd0qv2/T29h53h2B73Ai5AQQgkKQEmIFO0oGhWRCAAAQgAAEIQAACyUkABzo5x4VWQQACEIAABCAAAQgkKQEc6CQdGJoFAQhAAAIQgAAEIJCcBAj+S85xoVUQCCOBfer01jB2nD4nhMAkPXVUQp7MQyEAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIJC2B+9SymwfYusU674wBntvfaZ/Vgef6OxiS+gL18wmpQXoogX2+Xc++J/r8ido2S1nRfTYQgAAEIAABCEAAAjEIzFbdGikjxrHfqK5XmhY49gmVHwns9y3OU8XCvpXar5KujlF/pKrf6uAPj3RCCh/7I7XdvoxkH6EPp+rY/dI+qVHaIP1MGi/Fy27Xje6J180C96lU+bbAPkUIQAACcSOQGbc7cSMIQCDsBMYcI4Cv6rrfS+YoB+1S7ZwSrIiW52t7pTQ2xrFUqjqS4zoU/Zikh7wndffzsGmqf0vaJZ0jDZMukTZJNjaxLNF9itWmeNcd6+c83u3gfhCAAAQgAAEIpAGBBeqDzWh+XSodRH8269y+Dpk5Yu9INjvddwZaVe556fNWiGHzVLcwRn2V6q6O1s/T1j/HZr7/U9orWTjDCulM6StSl9QpWViBhTuYzZAqpXpptfQRybcRKth5Nlu7RPqh5D9HRa8vf6qtzeRusQrZT6Ttkl2zTLpM8u12FSy84h6pSVopnSb9rWTtteuulfqz/tr6j7rA+mX9s759Sepr9kzry5GsQgd3SN+W9kh3S2XSk5LNWtdFy+O19W2KCq9I1h8bx/+W7FlmkyUb72zJbLj0a2m3tFP6oZQlmc2TFkr/LtlzjOcNktk/ST1Su2T9s2dkSLHGWdVHtUKd8TnpJcn+twSDAAQgEJOA/eVn/zjEkh3zjfPeZwSX91kEPzdwCQ+XHP3FcLP0mGSO6L3SNdKR/qerSMfNYRolBe2vtWOOpZkdn+aV3v/xUxX/4/3dQ0rztGeOVV+rUsXV0cp52vrnXKeyOa6lkjlZ5nT6s9u/VfmHkm/Wx43S30m50gckcwSnS2YW7mAyh2umtF3yn6Oi1xdzGsulAquQmWM2QsqW/koyRzRfMrtdMifQ2mjH75LMUfyuZG35cnRfm8PsaG29XVfcc9hV71dYO+a9vxuzVKHabulfpTzJ+mR9+ZhkDEok+wLwB8m3RSrY2Nn5l0tNkt+OySrbeFtfzey6OyT7nIyWFktflczmSfYFwBhkSV+Xdkk2hmaV0m1WiNp12vY3zv45fbcXqeKXkjnoNm42Vv64qej+R6rvRyvshKhx3vuc4PI+i+BnBy6px8X//WYLAQhAIG4ERupOfya9LW2TviHFsnGqNIfJdxjtnAmSOanDbUcWy4H+J9Xf6R09/Mc8VZlTF/zHycoR6WrJbJ600Aoyc4Lfky6UMqWg/VY7PwxU2OywOZbB8+7T/u2SOXHm0E2XfLNr/edYnfXFnnckM2ftrOgJt2trjptvH1ahWbJnmZmDavcstZ0+dqS22qm3S/dYoR8zhtcHjtkYGkd7/q+i9RXa2kx2cPyihw5uzlbJ+mQ2UbL7mkPsm33R8tsxWWXrT7ZkoRIdUtBh/bT2X5bM5kn2OfHNHHa79qRoRaW2t0XLtjnSOAdO84qf0M910nrJvizZZxKDAAQgcJBA8B+Bg5UUIAABCBwngRpdbzMq70r2X/pTpFhmDpmZOYK+/ZcK35dsFrs/s/P9a2Od86YqS/toW6wTVfeS9N/Sz6VqyWYch0mx7GRVbpfMGfdtqwr2RcBm0c3xs+O+Bcv91dms81rJ+mt9si8O9gXEN2uTb20q7Jd6ohW2b1Z8YHPIzyO19ZAT+9mxMRwbOGaMjOl/STa77ds+FWyW3DdzZO+QjEuj9Kpk12VJ1iZzplsk3+y8WDZJlfac3ZJxMdl9bSbaN/sy41trtBCLhR0azDiP1/mm5VFZGzAIQAACBwn050Av0Bk2yxBLdsw3znufEVzeZxH83MAlPFzs74VTpR9IW6SfSCulqZI5ibHMHKlN0mmBg1ep/GPJnCPfQVqk8mck32aoYM5NvOynutF50hmSteWvJTOb0QzaLu3YbGTw706bVd0pmSNps6vmePkWa+YyeM/LdOK3JZvxLJPM0WyQMqTjtSO1dSD3flEnfXQAJwb7Y6fbWNss/AWSfRG5XDKzPpkjav0sknwzfrHMvnx0SCMl42Ky+9kYDcT6tsuu6W+c+97vP1Rhzr7N/n9X2iH9p3SOFLRfaCf4912wvDpwIue9zwku77Pg83LglyRVfz8Cv+IUIQABCBw7gTt1qc2O/kwyZ3SgZk7N3wVOthnGkwIyR+hCyf+v/DyVayVzcGLZPFUujHGgSnVXR+vnaeufc77K5uzZbKc5ds9It0tm/yLd65UO/MjVZpP0HcnOr5CapNMlswckO99mYa1um+Q/R0XPIZ9mhah9UFtzdK2/du9/kHqkqyWz26V7rBA1q6/yd7TNloxP0Gn3Dx+trbfrxOC9/ev87Wkq2KyvOZM2w25mzuwj0m8lswpphxUC9m8q2xfnfKlcekyyNlpbzd6U/l2y9l0qNUp+OyarHDz3ce3/RDLH2b60nCJdIZnNkxZaIWB27bTo/v3a/ihw7EjjHDgtZtG+EPyztEOyLxYYBCAQcgL2FxIGAQhAIB4EfqGbmFP7TWnZIG74S537Wcmfdd2r8p6AVPQc8zYryD4iVUq7pHiYOWe/kiy0wMIJLHTBHDyzX0szJXMk/yB1Svb8GyT7svA/0h9L6ySzb0jDJWv/3dJ9ks2i9mfP6oA5m+9J9ux2yWZe42FHa+vRnmFtulAy53y5ZF8UXpeM+/+V+rP/0gH7smN8zFl+RgraZ7RjX1hqpe9Jd0n9mbHNldZINj4PS2OlgZg53rdKdp19STvSOOvwEW29jv6tNFH6+yOeyUEIQAACEIAABCAwRATu1XNuHuCz3tJ5Zw7w3ESf9q9qwO8S3QieDwEIQAACEIAABCAAgWQlcLoaNluy2fS5ks3CDvSLgU7FIAABCEAAAhCAAAQgEC4CFme7UWqVqiT7b39zpjEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAE4keA2Lz4sTzinYYPH947bZqfnvSIp6bVwZaWFldUFFwzIa26129n6He/aNLyAOOdlsPab6cY737RpOWBsI73smXL7CXoUWk5qHHoVHYc7sEtBkBgzJgxbunSpQM4M71OqaysdBUVFenVqQH0hn4PAFIancJ4p9FgDqArjPcAIKXRKWEd74yMjK1pNIxx7woLqcQdKTeEAAQgAAEIQAACEEhnAjjQ6Ty69A0CEIAABCAAAQhAIO4EcKDjjpQbQgACEIAABCAAAQikMwEc6HQeXfoGAQhAAAIQgAAEIBB3ArxEGHek3BACEAgbgd7eXtfU1BS2bjvrNwYBCEAgjARwoMM46vQZAhCIG4H29nZXvava/fibP4rbPVPlRjOvOctZ//Pz81OlybQTAhCAQFwI4EDHBSM3gQAEwkqgq6vLRbp63BdG3OqKc8OT87y5s8Ut6lrnrP840GH99NNvCISXAA50eMeenkMAAnEkYM5zSV5xHO/IrSAAAQhAIFkJ8BJhso4M7YIABCAAAQhAAAIQSEoCONBJOSw0CgIQgAAEIAABCEAgWQngQCfryNAuCEAAAhCAAAQgAIGkJIADnZTDQqMgAAEIQAACEIAABJKVAA50so4M7YIABCAAAQhAAAIQSEoCONBJOSw0CgIQgAAEIAABCEAgWQngQCfryNAuCEAAAhCAAAQgAIGkJBB2B/p6jcp6aaP0nRgj9DXVrZTelRZKMyXf/lYFu86uv86vZAsBCEAAAhCAAAQgkN4EwuxAZ2lofy7dIJlj/OnoVpuDdq9Ks6SzpX+T/kMys/M/JZ0hmRP+P5LdD4MABCAAAQhAAAIQSHMCYXag52psbQZ5s9Qp3S/dJAWtMbBja/T2RvftPDu/Q9oi2X3sfhgEIAABCEAAAhCAQJoTCPNS3uM0ttsD47tD5QsC+37xT1X4lpQrfSBaade+GS3bxq61OgwCEIAABCAAAQhAIM0JhNmBzogxtv4Mc/CQhXmYPiP9vfR5aaDXfkXnmlxdXZ2rrKy0YqisubmZfodoxMM43pFIxOWXFLjlZ1a5rMzwRHL1RHpcfn6BW7JkicvMDNd/Zobxc25/jdHvEP1lTlePSiDMDrTNGk8IEBqv8q7Aft+ihWz8b7RyoNf+UuebXFlZWW9FRYUVQ2X2pYF+h2fIwzjeTU1N7olH5rvL1s90JXnFoRnspo5m9/z0Ze78a69xJSUloem3dTSMn3P6XWEIMAgcJBCuaYOD3fYKS/TzVGmKlCvZS4HzpaDZcd8+pMKG6I6dZ+fnSXa9nbdYwiAAAQhAAAIQgAAE0pxAmGeguzW235Celez/Xe+UVkvfl5ZK5iTb8aulLqlOsvANMzvvQWmNZPexOOkeCYMABCAAAQhAAAIQSHMCYXagbWifjio4zP8Q2PnzQLlv8Z9UYcIgAAEIQAACEIAABEJEIMwhHCEaZroKAQhAAAIQgAAEIBAvAjjQ8SLJfSAAAQhAAAIQgAAEQkEABzoUw0wnIQABCEAAAhCAAATiRQAHOl4kuQ8EIAABCEAAAhCAQCgI4ECHYpjpJAQgAAEIQAACEIBAvAjgQMeLJPeBAAQgAAEIQAACEAgFARzoUAwznYQABCAAAQhAAAIQiBcBHOh4keQ+EIAABCAAAQhAAAKhIIADHYphppMQgAAEIAABCEAAAvEigAMdL5LcBwIQgAAEIAABCEAgFARwoEMxzHQSAhCAAAQgAAEIQCBeBHCg40WS+0AAAhCAAAQgAAEIhIIADnQohplOQgACEIAABCAAAQjEi0CYHejrBXG9tFH6Tgyg31LdGmmF9KI0SfKtR4V3o5rvV7KFAAQgAAEIQAACEEh/Atnp38WYPcxS7c+la6Qd0hLJHGFzmH17R4U5Uqv0denfpE9KZm3S2V6JHxCAAAQgAAEIQAACoSIQ1hnouRplm3neLHVK90s3SUF7WTvmPJu9KY33SvyAAAQgAAEIQAACEAg1gbA60OM06tsDI2+z0FbXn31JBxYEDuarvFQyx/rmQD1FCEAAAhCAAAQgAIE0J5CR5v3rr3sf14HrpNuiJ/yRtjYr/c3ofnDzOe18Q7pC6ogeOFnbXdJU6SXpKmmT1Ne+ogqTGzVq1HkPPvhg3+Npv9/c3OyKi4vTvp99O0i/+xJJ3/1IJOLq6+rdsPZCl5Vp0WHhsJ5Ij2vMb3WlZaUuMzNcczH8fofjM+73MqzjfeWVVy4TAwtlxWIQCGsMtM04TwjwsPAMc4j72tWq+K4UdJ7tHP9cCwGplM6RYjnQv1S9yZWVlfVWVFRYMVRWWVnp6Hd4hjyM493U1OSeeGS+u2z9TFeSF54vi00dze756cvc+dde40pKSsLzIVdPw/g5twGm36H6mNPZoxAI17TB+zDspcFTpSlSrvQpqW82DXOK75A+Iu2VfCtTIS+6M1LbS6Q10X02EIAABCAAAQhAAAJpTiCsM9DdGlcLy3hWsv9zvVNaLX1fWiqZM/1jyaaTHpLMtknmTM+QzLGOSPYF5F8kHGhBwCAAAQhAAAIQgEAYCITVgbaxfTqq4Dj/Q2DHwjdi2RuqnBXrAHUQgAAEIAABCEAAAulPIKwhHOk/svQQAhCAAAQgAAEIQOCEEMCBPiFYuSkEIAABCEAAAhCAQLoSwIFO15GlXxCAAAQgAAEIQAACJ4QADvQJwcpNIQABCEAAAhCAAATSlUA6vERoKeU+Jk2Wgv35vvYxCEAAAhCAAAQgAAEIxJVA0OGM642H8GaP61kNkq2Y468UOISP51EQgAAEIAABCEAAAmEikA4OtK0ieH2YBo2+QgACEIAABCAAAQgkjkA6xECTlzlxnx+eDAEIQAACEIAABEJHIB1moC/VqM2TtkgWwpEh9UqzJQwCEIAABCAAAQhAAAJxJZAODvQNcSXCzSAAAQhAAAIQgAAEIHAEAungQG9V/86SLov28zVtl0fLbCAAAQhAAAIQgAAEIBBXAukQA/3nIvJ7aXRU92j7TQmDAAQgAAEIQAACEIBA3Amkwwz0l0TlAqklSudftV0k/Sy6zwYCEIAABCAAAQhAAAJxI5AOM9D20mBPgIiVrQ6DAAQgAAEIQAACEIBA3AmkgwP9G1F5S7o9qje1/bU0ELP80euljdJ3YlzwLdWtkVZIL0qTJN8+r8KGqKyMQQACEIAABCAAAQiEgEA6hHD8h8apUrJ0djbz/AXpHelolqUTfi5dI+2QlkjzJXOYfbP7zJFapa9L/yZ9UiqXvifZsV7JVkG0a+skDAIQgAAEIAABCEAgjQmk8gz0sOi4mDNbJd0j3S1tlazuaDZXJ9jM82apU7pfukkK2svaMefZzGa2x3sl567T9nmpVjKn2co2m41BAAIQgAAEIAABCKQ5gVSegb5XY3OjZLO/Ngvsm81C2/5Uv6Kf7TjVbw8cs1loexmxP7OXFRdED8a61uowCEAAAhCAAAQgAIE0J5DKDrQ5z2ZTDmwG/dMc7b4WdMSDxz6nHQvXuCJaOdBrv6LzTa6urs5VVlZaMVTW3NxMv0M04mEc70gk4vJLCtzyM6tcVqZFhoXDeiI9Lj+/wC1ZssRlZqbyf2YOfrzC+Dk3SvR78J8VrkhfAqnsQPujYi/3XeXvRLex6vqc4sU9TwhUWnjGrsC+X7xahe9K5jzbUuFmNltdYYWo2bWV/k5g+0uVTa6srKy3oqLCiqEy+9JAv8Mz5GEc76amJvfEI/PdZetnupK84tAMdlNHs3t++jJ3/rXXuJKSktD02zoaxs85/a4wBBgEDhJI5WmDfPXCYp1HSmXRsu1Plk6Wjmb20uCpks1g50qfkuZLQTtHO3dIH5H2Bg48q/K1kj3XZGWrwyAAAQhAAAIQgAAE0pxAKs9Af1Vj8xeSOcsWB+2HVTSqbNk1jmbdOuEbkjm+9v+ud0qrpe9LSyVzpn8s2ZTSQ5LZNsmcaXt58AeSOeFmdo3VYRCAAAQgAAEIQAACaU4glR3on2hsTN+UjnXVwad1rSlo/xDYsfCN/swcbhMGAQhAAAIQgAAEIBAiAqnsQPvDZM7zmdJMycI6fLvLL7CFAAQgAAEIQAACEIBAvAikgwP9PcGokMyBttnkG6SFEg60IGAQgAAEIAABCEAAAvElkBnf2yXkbrfqqZaFY4/0BeksKU/CIAABCEAAAhCAAAQgEHcC6eBAt4lKRLKXAodJli1jqoRBAAIQgAAEIAABCEAg7gTSIYTDMmaUSr+SLBtHs7RYwiAAAQhAAAIQgAAEIBB3AungQP9JlMovtH1GslnoFdE6NhCAAAQgAAEIQAACEIgrgXQI4bBVB32rUsGc52Cdf4wtBCAAAQhAAAIQgAAEjptAKs9AW8q6QslfidBfSMVmoAeyEuFxw+MGEIAABCAAAQhAAALhI5DKDvTxrkQYvtGmxxCAAAQgAAEIQAACx00glR3oeKxEeNwAuQEEIAABCEAAAhCAQLgIpLID7Y+UrUR4sTRZCvbnLu1jEIAABCAAAQhAAAIQiCuBoMMZ1xsP4c3u1rNOkd6VeqLP7dUWBzoKgw0EIAABCEAAAhCAQPwIpIMDPUc4ZkrmNGMQgAAEIAABCEAAAhA4oQTSIY3dKhE66RgoXa9r1ksbpe/EuP5y1b0t2QqHt/Y5bjPdNuNtmt/nGLsQgAAEIAABCEAAAmlMIB1moC2N3RrJVh/sCIzVRwLlvsUsVfxcukbaIS2RzBG2+/i2TYV50v/xKwJbWz787MA+RQhAAAIQgAAEIACBkBBIBwf69mMYq7m6xmaeN0evvV/bm6SgA10VPRaJbtlAAAIQgAAEIAABCEDApUMIxysaxyopR7KyzSZb6MWRbJwObg+cYLPQVjdQs0VclkpvSjcP9CLOgwAEIAABCEAAAhBIfQLpMAP9ZQ3DV6RyybJxmCP8C+kqqT/zVy0MHh/MS4gTdeEuaar0krRS2iT1NWuXydXV1bnKykorhsqam5vpd4hGPIzjHYlEXH5JgVt+ZpXLyswKzWj3RHpcfn6BW7JkicvMTIe5mIEPXRg/50aHfg/8M8KZ6U8gHRzoP9UwWUjGW9Hh2qDt6Gi5v43NOE8IHByvsjnEAzX/XAsBqZTOkWI50L9UvcmVlZX1VlRUWDFUZl8a6Hd4hjyM493U1OSeeGS+u2z9TFeSVxyawW7qaHbPT1/mzr/2GldSUhKafltHw/g5p98VhgCDwEEC6TBtYC8Odh7s0YHFVI42m2xhHqdKU6Rc6VPSQLNplOncPMnMXmC8RArGTls9BgEIQAACEIAABCCQpgTSwYG2uOe/kwoky6rxkPSEdCSz1HTfkJ6V1koPSqul70t+9o7zVbaZ6o9Ld0h23GyGZPHPy6WXpX+RcKAFAYMABCAAAQhAAAJhIJAOIRyWw/lLksUhf1V6Wvp/0tHMzjMF7R8COzZLbaEdfe0NVczqW8k+BCAAAQhAAAIQgEA4CKSDAx3RUP0qqnCMGr2EAAQgAAEIQAACEEgYgVR2oC3s4hOSzTzHinmenTCq/TzYXjYKm/X2xhqasFGgvxCAAAQgkKoE7N+xMP77narjNVTtTmUH+s+jkG4cKljH85yuri7342/+6HhukZLXzrzmLNfe3q50V5Y6G4MABCAAAQikDgH796t6V3Uo//1OnVFKTEtT2YHeLWSWdPXX0tWJwTeIp2oi9gsjbnXFuUWDuCi1T23ubHGLutY5+/KAA53aY0nrIQABCISRgP37FenqCeW/3z/wciSEcdQH1udUdqCthz1SqzRcapCS2sx5DlOe2KQeDBoHAQhAAAIQGCAB/v0eIKgQnZbqDrQNVbtkcdDPSy2Sb3/mF9hCAAIQgAAEIAABCEAgXgTSwYG2XMyvSZaNw2ak2yQMAhCAAAQgAAEIQAACJ4RAKjvQ1nZ7K++L0lbJFoWZIP1GsoVVMAhAAAIQgAAEIAABCMSdQCqvRPhj0SiXbDnu86RzpKmSxUPbMQwCEIAABCAAAQhAAAJxJ5DKDrSlr/uyFEyu3Kj9r0sfkjAIQAACEIAABCAAAQjEnUAqO9C2Qoepr1kcdKz6vuexDwEIQAACEIAABCAAgUETSGUHeo16+8cxevw51a2LUU8VBCAAAQhAAAIQgAAEjptAKr9E+Kfq/aPSF6Vlks06ny8VSLdIGAQgAAEIQAACEIAABOJOIJVnoHeKxgXS96UqaVu0PFdbOzYQu14nrZc2St+JccHlqntb6pZu7XP889rfEJWVMQhAAAIQgAAEIACBEBBI5Rlof3heUsE0WLNlwH8uXSPtkJZI8yULDfHNnPJ50v/xK6Jby/7xPWmOZDPfNgNu19ZJGAQgAAEIQAACEIBAGhNIBwf6WIfHZqpt5nlz9Ab3a3uTFHSgq6LHItGtv7lOBVv5sDZaYWWbzb4vus8GAhCAAATSlEBvb69ragomgErTjvbplvUbgwAEDhAIswM9Tgi2Bz4INgttISEDsVjXWh0GAQhAAAJpTKC9vd1V76p2P/6mreMVLpt5zVnO+p+fnx+ujtNbCMQgEGYHOiMGj4F+vR7otV/RM0yuqbnJLT+zymVlWuRIOKwn0qO/aAvckiVL3P/f3t3HWHbWdQA/fdl2W3YEWtDUFthWKLoQIVCQTSnZCK3QPyBCG7pqBCQhqBU1AUNDbGqJRjQS5UUo0kYhIFQatGhlKeIasUhLBUopbIB2Y2uhSIGyg7vD7s76/e3eA4fbme3sMNude5/Pk3znvNxz75zf55l75pkz59579NGTfLn9offX7Oxst3Xr1kO/44Tfo8W65+fnu7UzJ3h+T/jP7lJ3v/r7uLXHdc98zjnd0Ue1c1yb3zffza7d1d1www1NHc9bfn4v9TnR6nYtD6DrjHN99HffTsvM3f3CA0zrvpsG29R9tw6W+9l3ZKbSzayb2fekW9d3M8ev62+b+umOudnu+sff3D3tvHO7mZmZqa93WGANnjdt2jRc1cR8i3XXv/I/dM213TnbNnh+N/BTrr/bOp633N8NPJ1/pBLb+fP5/kz1osHHJfVR4MclFyX1QsCltC3Z6Lzk4aPUfK3TCBAgQIAAAQIEplyg5QF0vTXdxUkNfL+QXJ18Prk8eX5Srd5Xus42X5hckdTt1erFg69PahBeqfv0LyjMrEaAAAECBAgQIDCtAi1fwlF9et0ow/69dLBQg+O6PGOhdlVWVjQCBAgQIECAAIGGBFo+A91QNyuVAAECBAgQIEBgpQQMoFdK0uMQIECAAAECBAg0IWAA3UQ3K5IAAQIECBAgQGClBAygV0rS4xAgQIAAAQIECDQhYADdRDcrkgABAgQIECBAYKUEDKBXStLjECBAgAABAgQINCFgAN1ENyuSAAECBAgQIEBgpQQMoFdK0uMQIECAAAECBAg0IWAA3UQ3K5IAAQIECBAgQGClBAygV0rS4xAgQIAAAQIECDQhYADdRDcrkgABAgQIECBAYKUEDKBXStLjECBAgAABAgQINCFgAN1ENyuSAAECBAgQIEBgpQQMoFdK0uMQIECAAAECBAg0IdD6APq56eVtyZeT1y7Q48dn3ftHt38y0/VJtfXJzuQzo7w9U40AAQIECBAgQKABgWMbqHGxEo/JDW9Nzk3uSm5Krk1uS/r28sx8K3lsclHyhuTFSbWvJE/eP+cLAQIECBAgQIBAMwItn4F+enq5zjzfnnwveV/ygmTYavlvRis+kOmzk6NGyyYECBAgQIAAAQINCrQ8gD41/X3noM/rLHStG7bhNntyw33JyaMNTs/008m/JeeM1pkQIECAAAECBAhMuUDLl3AsdCZ531h/L7bNV7Pdo5N7k6cmf588IflOMmyvyEKl2zG7o/vsE7d3xxxdV4600fbO7+3Wrj2hu+mmm7qjj27rb7XZ2dlu69atbXT0oMoW656fn+/Wzpzg+T34OZjmWf3d1vG85f6e5ufxStTW8gC6zjg/aoB4WubvHizXbL9NTcvqock3kxpozyXVbk7qeugzk08lw/aOLFS6mXUz+5506/pu5vh1w9unen7H3Gx3/eNv7p523rndzMzMVNc6XlwNnjdt2jS+euqXW6x7x44d3YeuubY7Z9sGz++p/wnPyRD93dTxvOX+buDp/COV2NZpwR+mqhcNPi6pSzGOS+pFgvUiwmGr5ZeMVlyQ6ceSGjw/MulPJZ+R+XqcupZaI0CAAAECBAgQmHKBOqvaaqtrmi9OtiQ1GL4q+XxyeVJnkmvwfGXy7qRebFhnnmuQXe1ZSW1Xj7E3eWVSt2sECBAgQIAAAQJTLtDyALq69rpRht186WBhV+YvHCz3s9dkpqIRIECAAAECBAg0JtD6ALqx7lYuAQIECBBYnsC+ffv2XwO+vHtP5r3qGuj9F25O5u7b68MoYAB9GHE9NAECBAgQmAaBXXvmup07d3Zvfs0buzVr1kxDSUuqYW73XHfm2Ru6PXtyxWZ9NrFGYCRgAO1HgQABAgQIEDiowJ69GUDOd91LT3pRd9K6hx9022m68WuzX+8+Ob+t27u3Xu6kEfiBgAH0DyzMESBAgAABAgcReMiaE5t6u8bZue8eRMNNLQu0/DZ2Lfe72gkQIECAAAECBJYpYAC9TDh3I0CAAAECBAgQaFPAALrNflc1AQIECBAgQIDAMgUMoJcJ524ECBAgQIAAAQJtChhAt9nvqiZAgAABAgQIEFimgAH0MuHcjQABAgQIECBAoE0Bb2PXZr+r+jALtPiJXUVadWsECBAgQGDaBQygp72H1fegC+zatau75+57uj/9rT960L/3kf6GG859Ulf1r1279kjviu9PgAABAgQOm4AB9GGj9cCtCuzevbub3723e9nJF3TrjntIMwyz3/tu94ndX+yqfgPoZrpdoQQIEGhSoPUB9HPT63+RHJO8M/njZNjqk+/flTw1uTd5cbI9qXZJ8vKkPt/zVcmWRCPwfYEaPM8cv+77y2YIECBAgACB6RBoeQBdg+a3JucmdyU3JdcmtyV9qwHyt5LHJhclb0hqEL1htPyETH8y+WhyZlKDaW0g0OK1wDt27MjFwAMEswQIECBAgMBUCbQ8gH56evLLye2jHn1fpi9IhgPoWr4sqfaB5C3JUUmtr+3nkjuSepx6vE8k2khg1565bufOnd2bX/PGbs2aNc24zO2e6848e0O3Z8+erqv/YWgECBAgQIDAVAm0PIA+NT1556A378r8zw2Wa3a4TUZD3X3JyaP1/5lp3+q+te1BW10j2lL79q5wzXfdheue1z1s3UObKf1/Z+/tPjf/3913du3ojj22nadY/Xy3/B+H1p7f+rut4/ns7gP1fnf3/3XHz7VzZqDZuhsbryxngNLOb/f769SZ5PE2/o/3xbZZbP34470iKyrdHdvvmDvjjWfdOr5BA8uPSI3faKDO8RLVPS4y3cv6e7r7d7w6/T0uMt3Lrfb346e7W1W3XIGNuePwhX+XZLkybHX7xtGK+mOjBoI1eB7fdrjdaPP7TT51vzVtrFB3G/3cV6m/e4k2pvq7jX7uq9TfvUQb01b7e0m92/InEdaLBh+XnJ4cl9SLBOtFhMNWyy8Zrbgg048ldZa61tf29X+sun89zo2JRoAAAQIECBAgMOUCLV/CUdc0X5zU2eN6R46rks8nlyf1V1cNkq9M3p3UiwS/mdSguVptd3VSLzisx/nNxDtwBEEjQIAAAQIECBAgsFIC+6+FXqkHm6DHUfcEddYK7Kr+XgHECXoI/T1BnbUCu6q/VwBxgh6i1f6eoC6yqwQIECBAgAABAgQIECBAgAABAgQIECBAgMD9Bera6a8ntw5uOinz1ydfGk0fPrhtOFsvUKxtKv2LFYe3r+b5tdm5euHkZ5O6JvwPkmr1ospPJlXT+5PjkoVavZNJXVu+LfmFhTZYxeu2Z98+l3wm6V+lPO19Xm9nVPX2+U7mfyeZ9rpTYvfbST2/6+e8aq42jXUvdCy7MLVW3fPJWcmwLeU5vNTjwfBxH+z5hep+fXbilqR+3j+S1CfOVjsqeVNSx666/SnJQu2pWVnHiNqutq/7rba2UN2XZSf/J+mf5+cPdnqa+7t+V/U1bx/N96VPS919PaYEVo3As7IndRAdDqD/JMuvHe1hTesjwMfbSVlxe1LTGmDX/GID7dy06lr9Qlg32qv6mMEaND8juTrpX2z59sz/ejLeNmRFDbz7dzH5SubrhZyT0rZnRx8xtrMt9HlfcvXV15LHJNNe9xNTYz23T0zqRdcfTepdd6ax7oWOZT+TWuuPp63JcAC9IctLeQ5fne0e6HiQTY5oW6juHxvs0asyX8eyaucn/5zU8e8ZSR33Fmo3ZuXGpLar7Z+XrLa2UN2XZSdfvcCOTnt/D0v+syxcOloxTXUPazRPYNUIrM+e1C/Zvm3LzCmjhZrW8njbnBVXDFbWfK2bxHZidvq/kvokx28k/bu7bMz8lmS8XZIVlb7VNhv7hQmYbs8+PmJsP7dl+ZTRuprW8njbnBVXDFbWfK2btHZedvg/Rju9LdNTRvM1reXxtjkrrhisrPlaNwmtzsC+c7Cjv5/530u2JaeM1te0lsfb5qy4YrCy5mvdam7rs3PDY1m/r1szc1a/kOklo/SrtmRmY78wmtbgcSnHg7G7HZHF9fmuC9VdO1O1vq1m0q5INu+fO/BlWyanDJZrtpa/OFhX218xWF5Ns+uzM8O6L8vyq5PxdklWVPq2JTMb+4XRdBr6u2q4M6k/kqtNW90HqvJ1RQRafh/oFQFc5EF+Iuu/Orqtpj++wHanZl09Uft2V2Zq3SS1OhNZ//b6enJ9UmeSv53sSaotVtOk117vBV7/1r056V+l3Eqfp+T9ZxT/tmbSpr3uGlzUmbqTk/pD8fzkUcm0150SD9qW8hwus6UcDw76jY7gjX+Y713H6F9O+jOSS6m7tqljX98WOw72t6+26cXZoVuSq5L+v6JLqXvS+7v64ZzknuRLtZDWSt0HqvX1kAQMoA+Ja0U3rr90x1sNzCap7c3OPjk5LXl6Uv/uHW8L1TTptZ+dIuuynfq3bL0HeA2wltImve6qsa5pf37yd7WwxDbJdX8hNb4huT75cFKXLfR/IGb2oG2S6z5oYblxKbUtZZsH+j5H8vbX5ZvXH0vvSWpQWW0pNS1lmwOPtvq+vi279FNJHdfr5E9dzlBtKTUtZZsDj7Z6v27OrvUnB2ovl1LTUrZZvRXbs2ULGEAvm+6gd6y/YE8ZbVHTOkM73uqsRB2c+1aD0Lv7hQmb1lmmrUldE/iw5Nik2mI1TXrtfT9Vv34wqT8eWunz+qOhLtepequ1UPeVqbP+YKo/lL6ZfClpoe6UuWhbynO4Lt9YyvFg0W+ySm54b/bjRaN9WUrdtU0d+/q22HGwv301Tevnuk6MzCd/ldSxrdpS6p70/j42db4weX8VPGot1N3XanqIAgbQhwi2xM2vzXYvGW1b039Y4H5bsu68pP5FVqn5Wjcp7ZHZ0frlWO2E5DlJna371+SCpNpitZfPRcnxyelJXW92YzIJ7SHZyZnRjtZ89Vv9m7+FPq+yNyfDMzQt1N1fgvXo1P7CUf0t1J1SF21V/wM9h/dlm6UcDxb9Jkfwhv4a2NqF+o/LF0f7UnX/alJnHeuEwX1JnakdtlrekdTttV1tv9DvgKxeda1O+PTtFzNTx7Zq097fVWP9Dqt+rkFz31qou6/VlMCDLlCDiTpg7k7qiffypK4F+5ekzlTV9KSk2lnJO/fPHfjya5l8eZSXDdZPwuzPZic/ndyS1EH20qTaGUkNhquu+jf/8Um1+iV0+f65A19el8lXkm3J8w6smoivVd9nR6m396o6qrXQ5yemznuTh1bBo9ZC3f+eWm9Lqt+fPcV1L3Qsq0FUHdfmkjo7uSXp22LP4euyQf+2b4sdD/rHWA3Theq+JjtWx7U6vn0oOTWpVgPityZ17PpcUsf0vn2mn8m01tf9a7u3JHW/1dYWqvvd2cmqq+q+NhkOqKe5v1Nq99fJK2tmrE1L3WNlWSRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJgugXrruHoP5Z/+Ecp6ae5bb5+mESBAgMBhEDj6MDymhyRAgACB5Qtszl0/nly0/IdwTwIECBA4nAIG0IdT12MTIEDg0ATWZfOzk/pApn4AvSnzW5MPJPVJae9J+g/mOH+0rgbcb0r+MRlv9amh9cEgN41Sj68RIECAAAECBAgQmAqBX0kVV44quSHTpySbkvuS05I66fGJ5JnJ2uTO5PSkWn2yXD+Afmnm+0s43pv52r5afRz5F/bP+UKAAAECyxY4dtn3dEcCBAgQWGmBunzjz0cP+r5Ma/mfkhuT+kjtavWR0euT2eT25I6kWg2gX7F/7oe/PCeLGwarfizzM8mOwTqzBAgQIHAIAgbQh4BlUwIECBxGgZPz2D+fPDGpFxEeM5pel+lc0re9maljd38ZR79+sWmdtd6Y7FxsA+sJECBA4NAE6sCqESBAgMCRF7ggu/Cu5DHJ+uRRSZ1d7i+/yOwPtboe+oxk/Wjti0fT8clHsuLiwconD+bNEiBAgMAyBAygl4HmLgQIEDgMAnW5xgfHHrde/PdLY+v6xTqj/BvJh5OPJ/ckda30eHtVVpyV3JLclrwy0QgQIECAAAECBAg0KVDv2lGtLuf4y+R3a0EjQIAAAQIECBAgQGBhgRow14sK68xyvb3diYlGgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIYGRhfQAAAdpJREFUECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAssR+H9Igsb4VEM+OwAAAABJRU5ErkJggg==\" width=\"720\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "# Setting the default figure size\n",
    "plt.rcParams['figure.figsize'] = [10, 20]\n",
    "\n",
    "# Creating figures with 5 subplots\n",
    "fig, (a, b, c1, c2, d, e) = plt.subplots(6, 1)\n",
    "\n",
    "# Defining colors\n",
    "\n",
    "greenish = '#16a704'\n",
    "\n",
    "\"\"\" Visualizing BEFORE interactive mode \"\"\"\n",
    "\n",
    "# Visializing (a - Original image)\n",
    "a.imshow(image)\n",
    "a.set_title(\"===========================> (1) Original Image - INTERACTIVE <===========================\")\n",
    "a.set_aspect(aspect = 1)\n",
    "a.xaxis.set_visible(False)\n",
    "a.yaxis.set_visible(False)\n",
    "\n",
    "# Visualizing (b - Gray scale image)\n",
    "b.imshow(gray_image, cmap = 'gray')\n",
    "b.set_title(\"===========================> (2) Gray Scale Image - INTERACTIVE <===========================\")\n",
    "b.set_aspect(aspect = 1)\n",
    "b.xaxis.set_visible(False)\n",
    "b.yaxis.set_visible(False)\n",
    "\n",
    "# Visualizing (c1 - HOG descriptor or feature vector WITHOUT background))\n",
    "c1.quiver(Y, X, U, V, color = greenish, headwidth = 0, headlength = 0, scale_units = 'inches', scale = 5)\n",
    "c1.invert_yaxis() # Because it's upside down\n",
    "c1.set_aspect(aspect = 1)\n",
    "c1.set_facecolor('white')\n",
    "c1.set_title(\"===========================> (3) HOG Descriptor WITHOUT background - INTERACTIVE <===========================\")\n",
    "c1.xaxis.set_visible(False)\n",
    "c1.yaxis.set_visible(False)\n",
    "\n",
    "# Visualizing (c2 - HOG descriptor or feature vector WITH background))\n",
    "c2.quiver(Y, X, U, V, color = greenish, headwidth = 0, headlength = 0, scale_units = 'inches', scale = 5)\n",
    "c2.invert_yaxis() # Because it's upside down\n",
    "c2.set_aspect(aspect = 1)\n",
    "c2.imshow(gray_image, cmap = 'gray')\n",
    "c2.set_facecolor('white')\n",
    "c2.set_title(\"===========================> (3) HOG Descriptor WITH background - INTERACTIVE <===========================\")\n",
    "c2.xaxis.set_visible(False)\n",
    "c2.yaxis.set_visible(False)\n",
    "\n",
    "# Set the title in d and e\n",
    "d.set(title = '===========================> (3) HOG Descriptor (Zoom Window) <===========================', xlim = (0, 18), ylim = (0, 18), autoscale_on = False)\n",
    "e.set(title = '===========================> (4) Histogram of Gradients <===========================')\n",
    "e.set_xticklabels(angle_axis)\n",
    "e.set_xlabel('Angle')\n",
    "e.set_ylabel(\"Orientation\")\n",
    "\"\"\"\n",
    "# Eliminiating the axis number in d and e\n",
    "d.xaxis.set_visible(False)\n",
    "d.yaxis.set_visible(False)\n",
    "e.xaxis.set_visible(False)\n",
    "e.yaxis.set_visible(False)\n",
    "\"\"\"\n",
    "\n",
    "\n",
    "\"\"\" Visualizing after interactive mode \"\"\"\n",
    "# Define function for interactive zoom\n",
    "def onpress(event):\n",
    "    \n",
    "    #Unless the left mouse button is pressed do nothing\n",
    "    if event.button != 1:\n",
    "        return\n",
    "    \n",
    "    # Only accept clicks for subplots a and b\n",
    "    if event.inaxes in [a, b, c1, c2]:\n",
    "        \n",
    "        # Get mouse click coordinates\n",
    "        x, y = event.xdata, event.ydata\n",
    "        \n",
    "        # Select the cell closest to the mouse click coordinates\n",
    "        cell_num_x = np.uint32(x / cell_size[0])\n",
    "        cell_num_y = np.uint32(y / cell_size[1])\n",
    "        \n",
    "        # Set the edge coordinates of the rectangle patch\n",
    "        edgex = x - (x % cell_size[0])\n",
    "        edgey = y - (y % cell_size[1])\n",
    "        \n",
    "        # Create a rectangle patch that matches the the cell selected above        \n",
    "        rect = patches.Rectangle((edgex, edgey),\n",
    "                                  cell_size[0], cell_size[1],\n",
    "                                  linewidth = 1.5,\n",
    "                                  edgecolor = '#f000c8',\n",
    "                                  facecolor='none')\n",
    "        \n",
    "        # A single patch can only be used in a single plot. Create copies of the patch to use in the other subplots\n",
    "        rect2 = copy.copy(rect)\n",
    "        rect3 = copy.copy(rect)\n",
    "        rect4 = copy.copy(rect)\n",
    "        rect5 = copy.copy(rect)\n",
    "        \n",
    "        \n",
    "        # Updating (a - Original image)\n",
    "        a.clear()\n",
    "        a.set(title = '===========================> (1) Original Image - INTERACTIVE <===========================')\n",
    "        a.imshow(image)\n",
    "        a.set_aspect(aspect = 1)\n",
    "        a.add_patch(rect)\n",
    "        a.xaxis.set_visible(False)\n",
    "        a.yaxis.set_visible(False)\n",
    "        \n",
    "        # Updating (b - Gray scale image)\n",
    "        b.clear()\n",
    "        b.set(title = '===========================> (2) Gray Scale Image - INTERACTIVE <===========================')\n",
    "        b.imshow(gray_image, cmap = 'gray')\n",
    "        b.set_aspect(aspect = 1)\n",
    "        b.add_patch(rect2)\n",
    "        b.xaxis.set_visible(False)\n",
    "        b.yaxis.set_visible(False)\n",
    "        \n",
    "        # Updating (c1 - HOG descriptor or feature vector WITHOUT background))\n",
    "        c1.clear()\n",
    "        c1.set(title = '===========================> (3) HOG Descriptor WITHOUT background - INTERACTIVE<===========================')\n",
    "        c1.quiver(Y, X, U, V, color = greenish, headwidth = 0, headlength = 0, scale_units = 'inches', scale = 5)\n",
    "        c1.invert_yaxis()\n",
    "        c1.set_aspect(aspect = 1)\n",
    "        c1.set_facecolor('white')\n",
    "        c1.add_patch(rect3)\n",
    "        c1.xaxis.set_visible(False)\n",
    "        c1.yaxis.set_visible(False)\n",
    "        \n",
    "        # Updating (c2 - HOG descriptor or feature vector WITHOUT background))\n",
    "        c2.clear()\n",
    "        c2.set(title = '===========================> (3) HOG Descriptor WITH background - INTERACTIVE <===========================')\n",
    "        c2.quiver(Y, X, U, V, color = greenish, headwidth = 0, headlength = 0, scale_units = 'inches', scale = 5)\n",
    "        c2.invert_yaxis()\n",
    "        c2.set_aspect(aspect = 1)\n",
    "        c2.set_facecolor('white')\n",
    "        c2.imshow(gray_image, cmap = 'gray')\n",
    "        c2.add_patch(rect4)\n",
    "        c2.xaxis.set_visible(False)\n",
    "        c2.yaxis.set_visible(False)\n",
    "        c2.imshow(gray_image, cmap = 'gray')\n",
    "        \n",
    "        # Updating (d - Zoom window)\n",
    "        d.clear()\n",
    "        d.set(title = '===========================> (3) HOG Descriptor (Zoom Window) <===========================')\n",
    "        d.quiver(Y, X, U, V, color = greenish, headwidth = 0, headlength = 0, scale_units = 'inches', scale = 1)\n",
    "        d.set_xlim(edgex - cell_size[0], edgex + (2 * cell_size[0]))\n",
    "        d.set_ylim(edgey - cell_size[1], edgey + (2 * cell_size[1]))\n",
    "        d.invert_yaxis()\n",
    "        d.set_aspect(aspect = 1)\n",
    "        d.set_facecolor('white')\n",
    "        d.add_patch(rect5)\n",
    "        d.xaxis.set_visible(False)\n",
    "        d.yaxis.set_visible(False)\n",
    "        d.imshow(gray_image, cmap = 'gray')\n",
    "\n",
    "        # Updating (e - Histogram of gradients)\n",
    "        e.clear()\n",
    "        e.set(title = '===========================> (4) Histogram of Gradients <===========================')\n",
    "        e.grid()\n",
    "        e.set_xlim(0, 180)\n",
    "        e.set_xticklabels(angle_axis)\n",
    "        e.set_xlabel('Angle')\n",
    "        e.set_ylabel(\"Orientation\")\n",
    "        e.bar(angle_axis,\n",
    "              ave_grad[cell_num_y, cell_num_x, :],\n",
    "              180 // num_bins,\n",
    "              align = 'center',\n",
    "              alpha = 0.5,\n",
    "              linewidth = 1.2,\n",
    "              edgecolor = 'k',\n",
    "              color = '#f000c8')\n",
    "\n",
    "        fig.canvas.draw()\n",
    "\n",
    "# Create a connection between the figure and the mouse click\n",
    "fig.canvas.mpl_connect('button_press_event', onpress)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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