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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "EAt-K2qgcIou"
+   },
+   "source": [
+    "#  Eigenvalues and Eigenvectors"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "FZYK-0rin5x7"
+   },
+   "source": [
+    "Welcome to the last assignment of this course and congratulations for making it this far. In this final assignment you will use your knowledge of linear algebra and your skills using Python and NumPy to address some real-world scenarios where linear algebra is actually used to solve and simplify problems.\n",
+    "\n",
+    "**After this assignment you will be able to:**\n",
+    "- apply linear transformations, eigenvalues and eigenvectors in a webpage navigation model\n",
+    "- apply PCA on a dataset to reduce its dimensions"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Table of Contents\n",
+    "- [ 1 - Application of Eigenvalues and Eigenvectors: Navigating Webpages](#1)\n",
+    "  - [ Exercise 1](#ex01)\n",
+    "  - [ Exercise 2](#ex02)\n",
+    "- [ 2 - Application of Eigenvalues and Eigenvectors: Principal Component Analysis](#2)\n",
+    "  - [2.1 Load the data](#2.1)\n",
+    "  - [2.2 Get the covariance matrix](#2.2)\n",
+    "    - [ Exercise 3](#ex03)\n",
+    "    - [ Exercise 4](#ex04)\n",
+    "  - [ 2.3 - Compute the eigenvalues and eigenvectors](#2.3)\n",
+    "  - [ 2.4 Transform the centered data with PCA](#2.4)\n",
+    "    - [ Exercise 5](#ex05)\n",
+    "  - [ 2.5 Analyzing the dimensionality reduction in 2 dimensions](#2.5)\n",
+    "  - [ 2.6 Reconstructing the images from the eigenvectors](#2.6)\n",
+    "  - [ 2.7 Explained variance](#2.7)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "XI8PBrk_2Z4V"
+   },
+   "source": [
+    "## Packages\n",
+    "\n",
+    "Run the following cell to load the packages you'll need."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "graded"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import scipy.sparse.linalg"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Load the utils module and the unit tests defined for this notebook."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import utils\n",
+    "import w4_unittest"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a name='1'></a>\n",
+    "## 1 - Application of Eigenvalues and Eigenvectors: Navigating Webpages\n",
+    "\n",
+    "As you learned in the lectures, eigenvalues and eigenvectors play a very important role in what's called (discrete) dynamical systems. As you might recall, a **discrete dynamical system** describes a system where, as time goes by, the state changes according to some process. When defining this dynamical systems you could represent all the possible states, such as sunny, rainy or cloudy, in a vector called the **state vector**. \n",
+    "\n",
+    "Each discrete dynamical system can be represented by a transition matrix $P$, which indicates, given a particular state, what are the chances or probabilities of moving to each of the other states. This means the element $(2,1)$ of the matrix represents the probability of transitioning from state $1$ to state $2$.\n",
+    " \n",
+    "Starting with an initial state $X_0$, the transition to the next state $X_1$ is a linear transformation defined by the transition matrix $P$: $X_1=PX_0$. That leads to $X_2=PX_1=P^2X_0$, $X_3=P^3X_0$, and so on. This implies that $X_t=PX_{t-1}$ for $t=0,1,2,3,\\ldots$. In other words, we can keep multiplying by `P` to move from one state to the next.\n",
+    "\n",
+    "One application of discrete dynamical systems is to model browsing web pages. Web pages often contain links to other pages, so the dynamical system would model how a user goes from one page to another by hopping from link to link. For simplicity, assume that the browser is only following links to a new page rather than navigating to an unlinked one. \n",
+    "\n",
+    "In this case, the state vector $X_t$ will be the probabilities that the browser is on a particular page at time $t$. Navigation from one page to another advances the model from one state vector $X_{t-1}$ to another state vector $X_t$. A linear transformation, defined by a matrix $P$, will have entries $p_{ij}$ with the probabilities that the browser navigates to page $j$ from page $i$. For fixed column $j$, the entries represent a probability distribution describing location of the browser at the next step, given that you are at state $j$. Thus, the entries in each column must add to 1."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a name='ex01'></a>\n",
+    "### Exercise 1\n",
+    "\n",
+    "For the sake of the example, consider there are only a small number of pages $n=5$. This means that the transition matrix $P$ will be a $5 \\times 5$ matrix. In this particular case, all elements on the main diagonal should be equal to $0$, since we are making the reasonable assumption that there is no existing link to the current page. Also, as metioned before, all the entries in each column must add to one. Here is an example of such a matrix for $n=5$:\n",
+    "\n",
+    "$$P=\n",
+    "\\begin{bmatrix}\n",
+    "0    & 0.75 & 0.35 & 0.25 & 0.85 \\\\\n",
+    "0.15 & 0    & 0.35 & 0.25 & 0.05 \\\\\n",
+    "0.15 & 0.15 & 0    & 0.25 & 0.05 \\\\\n",
+    "0.15 & 0.05 & 0.05 & 0    & 0.05 \\\\\n",
+    "0.55 & 0.05 & 0.25 & 0.25 & 0\n",
+    "\\end{bmatrix}\\tag{5}\n",
+    "$$\n",
+    "\n",
+    "Define vector $X_0$, so the browser starts navigation at page $4$ ($X_0$ is a vector with a single entry equal to one, and all other entries equal to zero). Apply the transformation once: $X_1=PX_0$ to find a vector of the probabilities that the browser is at each of four pages."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "deletable": false,
+    "tags": [
+     "graded"
+    ]
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Sum of columns of P: [1. 1. 1. 1. 1.]\n",
+      "X1:\n",
+      "[[0.25]\n",
+      " [0.25]\n",
+      " [0.25]\n",
+      " [0.  ]\n",
+      " [0.25]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "P = np.array([ \n",
+    "    \n",
+    "    [0, 0.75, 0.35, 0.25, 0.85], \n",
+    "    [0.15, 0, 0.35, 0.25, 0.05], \n",
+    "    [0.15, 0.15, 0, 0.25, 0.05], \n",
+    "    [0.15, 0.05, 0.05, 0, 0.05], \n",
+    "    [0.55, 0.05, 0.25, 0.25, 0]  \n",
+    "]) \n",
+    "\n",
+    "X0 = np.array([[0],[0],[0],[1],[0]])\n",
+    "\n",
+    "### START CODE HERE ###\n",
+    "\n",
+    "# Multiply matrix P and X_0 (matrix multiplication).\n",
+    "X1 = P @ X0\n",
+    "\n",
+    "### END CODE HERE ###\n",
+    "\n",
+    "print(f'Sum of columns of P: {sum(P)}')\n",
+    "print(f'X1:\\n{X1}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### __Expected Output__\n",
+    "\n",
+    "```Python\n",
+    "Sum of columns of P: [1. 1. 1. 1. 1.]\n",
+    "X1:\n",
+    "[[0.25]\n",
+    " [0.25]\n",
+    " [0.25]\n",
+    " [0.  ]\n",
+    " [0.25]]\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "deletable": false,
+    "editable": false,
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[92m All tests passed\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Test your solution.\n",
+    "w4_unittest.test_matrix(P, X0, X1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Applying the transformation $m$ times you can find a vector $X_m$ with the probabilities of the browser being at each of the pages after $m$ steps of navigation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "tags": [
+     "graded"
+    ]
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[0.39392366]\n",
+      " [0.13392366]\n",
+      " [0.11407667]\n",
+      " [0.0850993 ]\n",
+      " [0.27297672]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "X = np.array([[0],[0],[0],[1],[0]])\n",
+    "m = 20\n",
+    "\n",
+    "for t in range(m):\n",
+    "    X = P @ X\n",
+    "    \n",
+    "print(X)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It is useful to predict the probabilities in $X_m$ when $m$ is large, and thus determine what pages a browser is more likely to visit after a long period of browsing the web. In other words, we want to know which pages ultimately get the most traffic. One way to do that is just apply the transformation many times, and with this small $5 \\times 5$ example you can do that just fine. In real life problems, however, you'll have enormous matrices and doing so will be computationally expensive. Here is where eigenvalues and eigenvectors can help here significantly reducing the amount of calculations. Let's see how!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Begin by finding eigenvalues and eigenvectors for the previously defined matrix $P$:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "tags": [
+     "graded"
+    ]
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Eigenvalues of P:\n",
+      "[ 1.         -0.70367062  0.00539505 -0.08267227 -0.21905217]\n",
+      "\n",
+      "Eigenvectors of P\n",
+      "[[-0.76088562 -0.81362074  0.10935376  0.14270615 -0.39408574]\n",
+      " [-0.25879453  0.050269   -0.6653158   0.67528802 -0.66465044]\n",
+      " [-0.2204546   0.07869601 -0.29090665  0.17007443  0.35048734]\n",
+      " [-0.1644783   0.12446953  0.19740707 -0.43678067  0.23311487]\n",
+      " [-0.52766004  0.56018621  0.64946163 -0.55128793  0.47513398]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "eigenvals, eigenvecs = np.linalg.eig(P)\n",
+    "print(f'Eigenvalues of P:\\n{eigenvals}\\n\\nEigenvectors of P\\n{eigenvecs}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As you can see, there is one eigenvalue with value $1$, and the other four have an aboslute values smaller than 1. It turns out this is a property of transition matrices. In fact, they have so many properties that these types of matrices fall into a category of matrices called **Markov matrix**. \n",
+    "\n",
+    "In general, a square matrix whose entries are all nonnegative, and the sum of the elements for each column is equal to $1$ is called a **Markov matrix**. Markov matrices have a handy property - they always have an eigenvalue equal to 1. As you learned in the lectures, in the case of transition matrices, the eigenvector associated with the eigenvalue $1$ will determine the state of the model in the long run , after evolving for a long period of time. \n",
+    "\n",
+    "You can easily verify that the matrix $P$ you defined earlier is in fact a Markov matrix. \n",
+    "So, if $m$ is large enough, the equation $X_m=PX_{m-1}$ can be rewritten as $X_m=PX_{m-1}=1\\times X_m$. This means that predicting probabilities at time $m$, when $m$ is large you can simply just look for an eigenvector corresponding to the eigenvalue $1$. \n",
+    "\n",
+    "So, let's extract the eigenvector associated to the eigenvalue $1$. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "tags": [
+     "graded"
+    ]
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Eigenvector corresponding to the eigenvalue 1:\n",
+      "[[-0.76088562]\n",
+      " [-0.25879453]\n",
+      " [-0.2204546 ]\n",
+      " [-0.1644783 ]\n",
+      " [-0.52766004]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "X_inf = eigenvecs[:,0]\n",
+    "\n",
+    "print(f\"Eigenvector corresponding to the eigenvalue 1:\\n{X_inf[:,np.newaxis]}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a name='ex02'></a>\n",
+    "### Exercise 2\n",
+    "\n",
+    "Just to verify the results, perform matrix multiplication $PX$ (multiply matrix `P` and vector `X_inf`) to check that the result will be equal to the vector $X$ (`X_inf`)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "deletable": false,
+    "tags": [
+     "graded"
+    ]
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Original eigenvector corresponding to the eigenvalue 1:\n",
+      "[-0.76088562 -0.25879453 -0.2204546  -0.1644783  -0.52766004]\n",
+      "Result of multiplication:[-0.76088562 -0.25879453 -0.2204546  -0.1644783  -0.52766004]\n",
+      "Check that PX=X element by element:[ True  True  True  True  True]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# This is organised as a function only for grading purposes.\n",
+    "def check_eigenvector(P, X_inf):\n",
+    "    ### START CODE HERE ###\n",
+    "    X_check = P @ X_inf\n",
+    "    ### END CODE HERE ###\n",
+    "    return X_check\n",
+    "\n",
+    "X_check = check_eigenvector(P, X_inf)\n",
+    "print(\"Original eigenvector corresponding to the eigenvalue 1:\\n\" + str(X_inf))\n",
+    "print(\"Result of multiplication:\" + str(X_check))\n",
+    "\n",
+    "# Function np.isclose compares two NumPy arrays element by element, allowing for error tolerance (rtol parameter).\n",
+    "print(\"Check that PX=X element by element:\" + str(np.isclose(X_inf, X_check, rtol=1e-10)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "deletable": false,
+    "editable": false,
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[92m All tests passed\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Test your solution.\n",
+    "w4_unittest.test_check_eigenvector(check_eigenvector)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This result gives the direction of the eigenvector, but as you can see the entries can't be interpreted as probabilities since you have negative values, and they don't add to 1. That's no problem. Remember that by convention `np.eig` returns eigenvectors with norm 1, but actually any vector on the same line is also an eigenvector to the eigenvalue 1, so you can simply scale the vector so that all entries are positive and add to one.This will give you the long-run probabilities of landing on a given web page."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "tags": [
+     "graded"
+    ]
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Long-run probabilities of being at each webpage:\n",
+      "[[0.39377747]\n",
+      " [0.13393269]\n",
+      " [0.11409081]\n",
+      " [0.08512166]\n",
+      " [0.27307736]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "X_inf = X_inf/sum(X_inf)\n",
+    "print(f\"Long-run probabilities of being at each webpage:\\n{X_inf[:,np.newaxis]}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This means that after navigating the web for a long time, the probability that the browser is at page 1 is 0.394, of being on page 2 is 0.134, on page 3 0.114, on page 4 0.085, and finally page 5 has a probability of 0.273.\n",
+    "\n",
+    "Looking at this result you can conclude that page 1 is the most likely for the browser to be at, while page 4 is the least probable one.\n",
+    "\n",
+    "If you compare the result of `X_inf` with the one you got after evolving the systems 20 times, they are the same up to the third decimal!\n",
+    "\n",
+    "Here is a fun fact: this type of a model was the foundation of the PageRank algorithm, which is the basis of Google's very successful search engine."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a name='2'></a>\n",
+    "## 2 - Application of Eigenvalues and Eigenvectors: Principal Component Analysis\n",
+    "\n",
+    "As you learned in the lectures, one of the useful applications of eigenvalues and eigenvectors is the dimensionality reduction algorithm called Principal Component Analyisis, or PCA for short.\n",
+    "\n",
+    "In this second section of the assignment you will be applying PCA on an image dataset to perform image compression. \n",
+    "\n",
+    "You will be using a portion of the [Cat and dog face](https://www.kaggle.com/datasets/alessiosanna/cat-dog-64x64-pixel/data) dataset from Kaggle. In particular, you will be using the cat images.\n",
+    "\n",
+    "Remember that to apply PCA on any dataset you will begin by defining the covariance matrix. After that you will compute the eigenvalues and eigenvectors of this covariance matrix. Each of these eigenvectors will be a **principal component**. To perform the dimensionality reduction, you will take the $k$ principal components associated to the $k$ biggest eigenvalues, and transform the original data by projecting it onto the direction of these principal components (eigenvectors).\n",
+    "\n",
+    "<a name='2.1'></a>\n",
+    "### 2.1 - Load the data\n",
+    "Begin by loading the images and transforming them to black and white using `load_images` function from utils. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "imgs = utils.load_images('./data/')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "`imgs` should be a list, where each element of the list is an array (matrix). Let's check it out"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Your dataset has 55 images of size 64x64 pixels\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "height, width = imgs[0].shape\n",
+    "\n",
+    "print(f'\\nYour dataset has {len(imgs)} images of size {height}x{width} pixels\\n')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Go ahead and plot one image to see what they look like. You can use the colormap 'gray' to plot in black and white. Feel free to look into as many pictures as you want."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.image.AxesImage at 0x7647ae6525b0>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.imshow(imgs[0], cmap='gray')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "When working with images, you can consider each pixel as a variable. Having each image in matrix form is good for visualizing the image, but not so much for operating on each variable. \n",
+    "\n",
+    "In order to apply PCA for dimensionality reduction you will need to flatten each image into a single row vector. You can do this using the `reshape` function from NumPy. \n",
+    "\n",
+    "The resulting array will have 55 rows, one for each image, and 64x64=4096 columns."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "imgs_flatten shape: (55, 4096)\n"
+     ]
+    }
+   ],
+   "source": [
+    "imgs_flatten = np.array([im.reshape(-1) for im in imgs])\n",
+    "\n",
+    "print(f'imgs_flatten shape: {imgs_flatten.shape}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a name='2.2'></a>\n",
+    "## 2.2 - Get the covariance matrix\n",
+    "\n",
+    "Now that you have the images in the correct shape you are ready to apply PCA on the flattened dataset. \n",
+    "\n",
+    "If you consider each pixel (column) as a variable, and each image (rows) as an obervation you will have 55 observations of 4096 variables, $X_1, X_2, \\ldots, X_{4096}$ so that\n",
+    "$$\\mathrm{imgs\\_flatten} = \\begin{bmatrix} x_{1,1} & x_{1,2} & \\ldots & x_{1,4096}\\\\\n",
+    "                                           x_{2,1} & x_{2,2} & \\ldots & x_{2,4096} \\\\\n",
+    "                                           \\vdots & \\vdots & \\ddots & \\vdots \\\\\n",
+    "                                           x_{55,1} & x_{55,2} & \\ldots & x_{55,4096}\\end{bmatrix}$$\n",
+    "\n",
+    "\n",
+    "As you might remember from the lectures, to compute PCA you first need to find the covariance matrix\n",
+    "\n",
+    "\n",
+    "$$\\Sigma = \\begin{bmatrix}Var(X_1) & Cov(X_1, X_2) & \\ldots & Cov(X_1, X_{4096}) \\\\\n",
+    "                          Cov(X_1, X_2) & Var(X_2) & \\ldots & Cov(X_2, X_{4096})\\\\\n",
+    "                          \\vdots & \\vdots & \\ddots & \\vdots \\\\\n",
+    "                          Cov(X_1,X_{4096}) & Cov(X_2, X_{4096}) &\\ldots & Var(X_{4096})\\end{bmatrix}$$\n",
+    "\n",
+    "<a name='ex03'></a>\n",
+    "### Exercise 3\n",
+    "\n",
+    "In order to get the covariance matrix you first need to center the data by subtracting the mean for each variable (column). \n",
+    "\n",
+    "As you've seen in the lectures, the centered data matrix looks something like this:\n",
+    "\n",
+    "$$X = \\begin{bmatrix} (x_{1,1}- \\mu_1) & (x_{1,2}- \\mu_2) & \\ldots & (x_{1,4096}- \\mu_{4096})\\\\\n",
+    "                                           (x_{2,1}- \\mu_1) & (x_{2,2}- \\mu_2) & \\ldots & (x_{2,4096}- \\mu_{4096}) \\\\\n",
+    "                                           \\vdots & \\vdots & \\ddots & \\vdots \\\\\n",
+    "                                           (x_{55,1}- \\mu_1) & (x_{55,2}- \\mu_2) & \\ldots & (x_{55,4096}- \\mu_{4096})\\end{bmatrix}$$\n",
+    "\n",
+    "From the lectures you know that, for example, the mean of the first variable (pixel) can be found as the mean of all the observations: $\\mu_1 = \\frac{1}{55} \\sum_{i=1}^{55} x_{i,1}$.\n",
+    "\n",
+    "\n",
+    "For the following exercise you will implement a function that takes an array of shape $\\mathrm{Num. observations}\\times\\mathrm{Num. variables}$, and returns the centered data. \n",
+    "\n",
+    "To perform the centering you will need three numpy functions. Click on their names if you want to read the official documentation for each in more detail:\n",
+    "- [`np.mean`](https://numpy.org/doc/stable/reference/generated/numpy.mean.html): use this function to compute the mean of each variable, just remember to pass the correct `axis` argument.\n",
+    "- [`np.repeat`](https://numpy.org/doc/stable/reference/generated/numpy.repeat.html#numpy-repeat): This will allow for you to repeat the values of each $\\mu_i$ . \n",
+    "- [`np.reshape`](https://numpy.org/doc/stable/reference/generated/numpy.reshape.html#numpy-reshape): Use this function to reshape the repeated values into a matrix of shape the same size as your input data. To get the correct matrix after the reshape, remember to use the parameter `order='F'`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "deletable": false,
+    "tags": [
+     "graded"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "# Graded cell\n",
+    "def center_data(Y):\n",
+    "    \"\"\"\n",
+    "    Center your original data\n",
+    "    Args:\n",
+    "         Y (ndarray): input data. Shape (n_observations x n_pixels)\n",
+    "    Outputs:\n",
+    "        X (ndarray): centered data\n",
+    "    \"\"\"\n",
+    "    ### START CODE HERE ###\n",
+    "    mean_vector = np.mean(Y, axis=0)\n",
+    "    mean_matrix = np.repeat(mean_vector, 55)\n",
+    "    # use np.reshape to reshape into a matrix with the same size as Y. Remember to use order='F'\n",
+    "    mean_matrix = np.reshape(mean_matrix, (55, 4096), order=\"F\")\n",
+    "    \n",
+    "    X = Y - mean_matrix\n",
+    "    ### END CODE HERE ###\n",
+    "    return X"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Go ahead and apply the `center_data` function to your data in `imgs_flatten`. \n",
+    "\n",
+    "You can also print the image again and check that the face of the cat still looks the same. This is because the color scale is not fixed, but rather relative to the values of the pixels. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.image.AxesImage at 0x764796971610>"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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2RGIgmPqWzWMt4wkfCNdT1EnUgr5NMCOdfCUadfRxxx3Xld3u4edaiQCoNU899dTqGFeDtRIAehsJ2kueG56f85Vz7CtuS+WJIVzzEbShGOHWiixzO4z9w/a77m/ltncLdgy3S6nZ3Ubsy/XvupnWXitJqINzQ7wXr4NJQDyxBcE+9jFiko7Wltt9yG/2RGIgyJc9kRgIpkrjd+7c2dEU5mmT6ogjtxEYVUQK5wtVSAN9MQ3tn3Xr1nVlt+hI2Zxm99mDvpCEEW6+NRTtFLfU+izBvp1CJeltb3tb9Tv7hHab9zfpued0YxsZKehRW6TCLhNIi88+++xZ/y7V/e9jRknSouAcJ180xDEjxffIxlbkGdvli1i45RifCY96bG3ZRfpPaerWI+m/98HYVmwlTslv9kRiIMiXPZEYCPJlTyQGgqmvehtrCtey1OKe05uJFmjxeCgqbQtqdP+dSQE8NJShi65RqbtogyxdurS3HW4nUVN5wgeG51Lz+X1ybznXwNSv7Ee3zRia6jqXCR1pa7kFxXvhPIhU93frnlm/9xW1LTW7a1mGrLaSVtLKc43O+QHX5S2LlPfGe/Zx4dh68k/OrbT6inre73OvrHqLiKMj4uaI2BwRmyLi46O/z4uIGyNi6+jnYburK5FIzB0mofHPSvpkKeUkSSskfTQiTpZ0uaSbSilLJN00+j2RSLxIMcleb9slbR+Vn4yIzZKOknSRpPNGp62R9C1Jn27V9fTTT3dWhdN4UlWnzx6dNYbTSuaFc2pK64kU2ektr+WrjtjGPorp7XC6xXb4MVJrWlIeUcjruf3YZ715Ln6udPP+5eowXsvbQdpK+eP1+9ZTBMfaI+PY37QfPXKSz4Fvn80oNCbUcIuK1q+PO6mx9xXP5T179FsrrzttNN6LPx+tBBv+Ps2GFzRBFxGLJZ0h6XZJC0b/EYz/Q5jf+GgikZhjTPyyR8TLJH1V0idKKb/e3fn43GURsTYi1rZ2YkkkEvsWE73sEfESzbzoXyml/Mvoz49HxMLR8YWSdsz22VLK6lLKslLKMp+FTCQS08NuNXvMiI2/k7S5lPLXOHStpEskXTH6ec0sH/e6Oq3rmVMYCuh6x0MPx/C9x6hX/T8W6kvqRN/Xi+zDs5LQgmEbuaLJ4bYZ7SXPZsJ5gL4tpqVay7k9w3NZn/ch6/fVZewf3rNrZV7L20g7jKG0bq+xHd5XHF/OdXi4KcfQ75PzINS1DGmW6rkbD6Fu7dPG54B63ueTeG0/1rKMCT5nbrGNw4I9jJaYxGc/V9K/lXRvRNwz+tt/0sxLfnVEXCrpEUkfmKCuRCIxR5hkNv4WSX1TiRfs3eYkEol9hTmLoHMaRdvCbQqeyxVmHv1GyukWCa0hUj2nQ7SdWjSe1NepF2mgW2NMgOi0mFForNMTQrbsQV6b0sijzrgNtCfwII0nZXZrjNd2at23UtFXtrUSa7J/SIN9ayUmI3Hbtm87pFbylAcffLD6nc+BSw22i8/tpCsapdoGbCUE4XPg49mK8uuus9szEonEnwTyZU8kBoKp0viDDjqo2ybI88Yz6szp8+23396VOVvuVImJClwKcJaSFLmV98ylBrcuYqSWU0VG73liC87e+tZN3GmVs74eDcjZXL923264nq+dkXE+g828bZz5Z249STrqqKO6skuS+++/vyufe+65s7ZPqmWHR7WxTm4T5eNCueIygU4AFwa5C8M6XCbwmEcRMjc/n02PKaEr0Mqhx2ffaXxrIcz4mcjkFYlEIl/2RGIoyJc9kRgIorXYfW/j8MMPL+985zslScccc0x1jDr6e9/7XnWM+pLWhK9wol7xCDrqY/8cwWtTJ0r11tHnn39+V3a7h3W4NbZp06au7PMF/J26kYkypNpy9CQJtJQYmeX3Qk3tVlOf7vNtiDnv4jq6b4WW18E5Ere1+IywPu9T6uELL7ywOsY5E7bX89fTynKrk9s7r1ixojpGbc7PeR0cC39eGB3IuSWfB+HvHoU3nr+666679OSTT84aF5Pf7InEQJAveyIxEEzVejvggAM6y8O3wGlRPVJw0heP2qIk8fpJj2jZuUXHOjwpBa29q666qit7Tvb3v//9XflLX/pSdayVc41t5nmek480u7X1NfvNqS/Pc0lFCkoryBNgMHLNpQbHkxZSK2mJ9wePUbq4JXXOOed05b/927+tjtFyZC5DX0RFiuzRaHzOfAEXIyS5sMmTotAq8+f2DW94Q1emvPIIUUoNt94yb3wikeiQL3siMRDky55IDART1eyllE5ze9ghc5V7+Gbflr+0XKRaz3soLbU5NZ+HLlILuc6lDmW4pYdefupTn+rKrlEZHupanPfNsE9PjkHrsLUK69Zbb+09j+HJPjfB+Q3acm95y1uq8xjG633A7aJ5LdflHE+/T9ZP/eo2n1uHBPdiayVlpB72eZwlS5b01sFzacP5vEIrqQTnZ0477bSu7M8f5xxaW5L3Ib/ZE4mBIF/2RGIgmCqNl9S7/RMtA4/qI33meW4zkDq59cZIM9J93674+OOP78rf/e53q2Okqq2caJQQ3kZSd5ca7BNaQb5SzCkzQXnEfO2+kosr2Dz5Bm0jJv3wFWWkvk5TKYd4X34trgL0hAy0sii3/PngePpWXHfffXdXHq+4lJ5Pg/m75wYktfb2U0LQzuxLmiE93/bjtSlNvT/Yj97f42d/j7Z/SiQSfxrIlz2RGAimnoNuPPPoi/tJxZinTapnYnmeRymR+jpt5WKGvi2BpJoie5QSo9ValPADH9iVaNcjy3htp/9sP2eiOaMsSR/60Ie6stNFzuiz/aSYUn/uNK+T/eF52yib/F54bd6Xz6SzHZ6kg5F8bEdrZtsTnyxfvnzWYz62kybzuP7666tjHBt+zp8J3re7SJRpfL69DuZHdIz7PyPoEolEvuyJxFCQL3siMRBMVbMfeOCB3aqhBx54oDpGDe/6j9qltR0RNbzPCVDD0y5xDcnzqMuletVXK/lf35ZD3i5PsEF9z1zurlGpv32rIlpDtGF8S2XOVXh/91k8riGpc31bJPYJtXJrK2PXstSftCm9P2irep/2bbvkdXB+gIk0pdqC9aQUfe33aEDqcrdcuXKO8yU+tuxvf+b2SgRdRBwcEXdExPqI2BQRfzX6+7yIuDEito5+Hra7uhKJxNxhEhr/tKTzSymnS1oqaVVErJB0uaSbSilLJN00+j2RSLxIMcleb0XSmLu8ZPSvSLpI0nmjv6+R9C1Jn27V9eyzzz4vuH8MUkSPAiLVpt3jkU6kQE5baZEw6QItOammyMuWLauOvfGNb+zKzJ123XXXVecxCs+lBukXFzZINdUjHXV7jVKgFWXFvvLzaGX5oo2+3Ug9eoxRin6M4+mLcPrgkYKkrTzmVJp96vKNv1PmMSpOqhe7bNiwoTpGy9XpP+02jplHG3reOYLjS8nTWqTlUmCS7dAn3Z99/9EOrjsk3VhKuV3SglLKdkka/ezftziRSMw5JnrZSyk7SylLJS2StDwiTp30AhFxWUSsjYi1PgGTSCSmhxdkvZVSntAMXV8l6fGIWChJo587ej6zupSyrJSyzGcQE4nE9LBbzR4RR0j6QynliYh4qaS3S/rvkq6VdImkK0Y/r5mgrk7LuT7jfwSu/6h/eMzPo/52XUdLjTrOLRLOKbieZ7JBln0VGuvwLZuprVwrM7EDtZvnhqdtdsopp1THeG9cAefzG9TRLZuSWtPby3kAD1PlXAXnYLwO9pUzP84/cN7G7VL2j++fxzZyhaPPC911111d2Z9NntsKR6XG9tBW/u7zVhwLPh8eDs529bXD+7dqX++RXVgoaU1E7K8ZJnB1KeW6iPi+pKsj4lJJj0j6QKuSRCIxt5hkNn6DpDNm+fvPJV2wLxqVSCT2PqYaQffcc891lNypKVcWeUQXaTKtMVpoUk0lmdNO6t+OyEFK5XSujyL5CjvScaeVrS2nKUt4jDafVPePt4lUmJTQ28j+b9k4lFetXOitlXM85hYUZY7bVZQCTPjg8s2lGEGrjAk7vE8Jn1viM+d545lznxadP9+UHq289K19C1iny5DxfbZWBGZsfCIxEOTLnkgMBFOl8Tt37uxmIj06iLOm27Zt662DNNij00jj/RjpLam60yFScN/WqU8KuCzg5zxSi5TNqS9nablQyJNGkC56P5Ku8958tpxw6sfION6b033W73X07UzqLgnP8/r70js7DSb9d/nGWevWNlSUKB5tSLnoWzJt2bKlK/M+fcEPx9ClDLc74zPgbWQKcZcJ489lDrpEIpEveyIxFOTLnkgMBFO33sba2XUX9ZRbK9Q7fdvtSLV95xFjTGZIa8mTC/I8X61FK47td+3N+m+77bbqGLWcJ0mgTcdre8JJampGfkn1irvWlkbUlx6Nxfo5Lq0ECa63CWpqX+nHMezbhliq78XnMDgu3kbaV27pEnwO3KbkvIXbsRxrjq3PO/GZ9qQU7B/W53sfsI892nDcfn+viPxmTyQGgnzZE4mBYKo0/qCDDtIJJ5wg6fnRUqQfTl9oo5FSeR472ma+xQ5pDxMyeD71VqIFUlpSKrc7SDNbi3U8Qsotn76/0yZyi4f3RjrKv3udTn3Zj7xWKzrLj9E24li7BUgbqpV70MeJYP0tqs5nxyMbSc/92SS1pkyS6v5pJa+gRPHnhZF9rSQu7GNv//g5a+1Um9/sicRAkC97IjEQ5MueSAwEU9Xs+++/f6cxqQul2oJx3UFN0xfK6XW6Rl28eHFXpkZtbVfM/PIOaiu3nWit+PwD5wRaYZ+cj2glTHCNyvBZzlP4ffp8QR+oNT1Ek/fi/c0+YfJPX23G8FBfwcfr8fnw8/i8eH/zXNbndTDRh/cN+87HgtticwUfQ1ulun88KQq1Pq/lz0dLs4/bnHu9JRKJfNkTiaFg6hF041VPvlqLNoNHSJGakNK7vUEbivTKj/HaTudo8XiEG+kiI6ScbpGyeX460lun4KyT1/JIwdbWvVxVNmmCT5ch7B+W3V7j7x6JyHHy9hN921U5SM89wo195X3KZ4Qyz/PAcQy9Dso+v0/2NyM4PdKOq/s8+o3WMtvYysnnfToep1aUY36zJxIDQb7sicRAMFUaX0rpZg1bEV2efpmLU1oLJ/i70zTOsnOm1KPTSCW9jaRVnLF1uuUzpX1tdPrM67H9fp+c7d+4cWN1jP1DKePbA7H9Tk37dsN16tiKcGMdTPjgiRt8my6CFJnt9Sg8Ulen+NwZl7PxntyE9+apquk6+FhTyvCeffESn2l3m/gMtu6T8Od7LFdaLkt+sycSA0G+7InEQJAveyIxEMxZBB2tGakdGUfrjZFObjNQ4/iqt75tnVyH9q08c7zuda/ryq6TaJ94gkLOCbjuojbnvbimpq3TWkVGvdqy4TwffJ/F47qfOt1tOeptn/sgaO25ju6zSD1pJc9z+4553Tn343Yp50888Qnv2z/HPmAdHm3YGneCtqrP6dAS9LmDSZ7bib/ZR9s23x0R141+nxcRN0bE1tHPw3ZXRyKRmDu8EBr/cUmb8fvlkm4qpSyRdNPo90Qi8SLFRDQ+IhZJ+jeS/puk/zj680WSzhuV12hmK+dPt+oppXR0xi0S2klLliypjvUlQnDq2Bf5JdXRcH0LLKSaIvox0nVe22kZ6ZdvF0RK69SLx0hpW/ag25R9lqDXwYhCp9mUBrwX72+e58coG9gmH3dSU6fxRGsn1b5+k2pJSGnnUoD02RfTMMrPZRlBWenyiv3f2g2XEsIXL7UWuYzHaW/kjf8bSX8pia1cUErZPrrAdkn9G24lEok5x25f9oj4c0k7Sinr/pgLRMRlEbE2ItZ6LHsikZgeJqHx50p6T0RcKOlgSa+IiH+Q9HhELCylbI+IhZJ2zPbhUspqSasladGiRf0cI5FI7FNMsj/7ZyR9RpIi4jxJnyql/EVE/A9Jl0i6YvTzmt3VFRGd/vaQQVpqzgCokxjK6OdRi3MPLqlekeRJGglqLdfD1JfUsscee2x1XitXOZM3eDt4b6191DiX4Nf2xAhjuN5r7XvGc2k7+TwI79P1JS0qzsf43AHvxW0tbsXMsfA5BlqTvtcb62A/+rWo4d3W4rXdfuT4tvYQbG3FzD5pzR3Q0vX6x3MV+yp5xRWSVkbEVkkrR78nEokXKV5QUE0p5VuamXVXKeXnki7Y+01KJBL7AlONoHvmmWc6mtXKN+YgtfFtlAnaOoyckmraTdpEmjdu4xi+Ios0llFnvpKL8O2OaAE6fWYf0MbxSEHSYqeElCGknE77SGOd+pHuso2tJBc+nn2U2WUN5ZWDMo2WmttaHAtPONJnP3qf0ir0iEL2j48Z62H93kYmMfFVdayfEsVtPva/S8BxuzIHXSKRyJc9kRgKpp68YkzvfJsl0mfPscYINVLd1gIRX/hBukuqw8URUh1l5RF0pGykqT5L3ZfkwtvoVIzUr2+GVqrvzWfqmceO7XepQbro7SdIW52qM1eg5w0k5WSZKb2lWkY5fSb9Z3v9njkuLgfZd3yOXD5wxt37m3X6ePbtmup92lrEwn6lW+PvSGuH1nGdPkZEfrMnEgNBvuyJxECQL3siMRBMXbOPdaRHQTECyyPj+lZNtbYc8mPUTNTDrouoz1wbUmtRez/88MPVeVxp5VqWWs6jzpggkvaMt5E62rfRYhs5B+BWUCtfe59N6XqY1/YxYyQfNbDfC/W2H+tLOOn2F8/zY5wH4DPgtlYruSPvza3aPqvLtT3nT1yzs/1sh2t0RtT5HMz4uWolschv9kRiIMiXPZEYCKZK43fu3NnRqtaiCqdKpNOkkk5zGGXl9KrPXnLrjYkz3Brj9TyHHsEorrVr11bHaI14rr177723K9NCe9e73lWdR8vRI9IuvvjirszoPb9/UmuXE6SVrN+TdLQkDxc2nXLKKbO2XapzuLlMIFW9//77e69FiuzbbZH6ko772B599NG97eC4+7ZOfdt5+fPH8zyBB2UUr+3toERxuj62YzOCLpFI5MueSAwF+bInEgPB1PPGj/WK2z3UUJ40gjqPusVXLjWT7UHLUDd7WC01mWsrTyYwhttf1FpnnHFGdYz62OcLaBfSMnIbp7XtM9vMPn3ggQeq8xiW6TqXmrhP80p1oghqXqnOq9/aP6+lQ/uSaPjKNrbXx4y/c1zcuuJ9eshpXxiz1B9C7WPWt7LNz+W13B5kX/Xtz+fzGVUbeo8kEok/KeTLnkgMBFOn8WN7zK0gRox57m9aH608YoTbFvwcaWVrC17P50ZKyLJvz8uouU2bNlXHTjzxxK7sNgmpMM9zyknq7pFflCWkfcuWLavO+/a3v92VfSxovVEyeDtor7lc4dj0RcI53A4jRSZt9X5jnU6zKQl5nifi4Li79cv+9ufKV0aO4ePCNrfyEraiASmjvB/HMiQj6BKJRL7sicRQMFUaTzgl5OzzEUccUR1j3jnOfDsFJ/1v7VpK6tWKOHJXgJ/r2+lUqimc57HjfftsPGfMSdPOPPPM3jb67DPr5zGnlZwtv+2226pjpNOktx499t73vrcru6Ti5zj77PSZY+j5+hhhyHH3PIR8djwakItrSHF9NpvHuPutVMscT2xBl6CV6KMvf6HXyXH3OkjjvR89xfVsyG/2RGIgyJc9kRgI8mVPJAaCqSevGOsQ1yPUIC0t3srhTd3leriViK+vDgcjzR599NGu7Fswcdtd2lNSO0kHV5X12V9SeyshzhHwPLfXTjjhhK7scw7XXLNrJy9q5Y997GPVea2tjKmrWb9rZa4edN3JpJC0vNwa40pFt205V8G+8ueD8xQeKcm+8zZyDPlseh28tvc328xnmisfpVrbex+M52d8PoCYdH/2hyQ9KWmnpGdLKcsiYp6k/yNpsaSHJH2wlPLLvjoSicTc4oXQ+LeVUpaWUsbRGZdLuqmUskTSTaPfE4nEixR7QuMvknTeqLxGM3vAfbr1gf3226+LHvLEDbRunIr05Y9zaspIJLeaSONJi51WnnbaaV2ZCROkmmYfd9xxXfmuu+6qzqPdc+utt1bH+hZOSNKKFSu6Mum4t5H37Yt/aHOR9rnVSVrsVuepp57alWnReX977j2ibxsqr4N59xxsIymtL4DiPfsurkyOQUn1lre8pTrva1/7Wld2e43PZmsvgbPPPrsrf/Ob36zOayX64LO5devWWa/r7WrtRNyHSb/Zi6RvRsS6iLhs9LcFpZTtkjT6Ob/304lEYs4x6Tf7uaWUxyJivqQbI+L+3X5ihNF/DpdJz/+GSiQS08NE3+yllMdGP3dI+pqk5ZIej4iFkjT6uaPns6tLKctKKctaUW2JRGLfYrff7BFxqKT9SilPjsrvkPRfJV0r6RJJV4x+XtNfS1dXp99cc1B7tpJQMITVtRs1jmtD6jUmP/je975XnXf33Xd3Zep3qdao1G7nn39+dR5Xy73jHe+ojrHNHqrLFXKcH3Cd+IY3vKErP/jgg9WxpUuXdmUmsDzyyCOr83htt8243x318IYNG6rzOH/iYaq01Hgtt1VZh68epF1FverJPnnPnLeR6jmB448/vitfddVV1Xl8Ps4555zq2LXXXtuVXW/zmeMcjz+bfEY87Pi73/1uV+Z23D6XwmM+J9Xa8nyMSWj8AklfGzX+AElXlVK+ERF3Sro6Ii6V9IikD0xQVyKRmCPs9mUvpfxQ0umz/P3nki7YF41KJBJ7H9GizHsbRx55ZLn00kslPd9eozXkE3mkc2yvr/iiXeUygfnbSfHPOuus6jxaJh6lRBuKNGrz5s3VeYz8cvuElNbpOaPm2Ac+Rq1jrJPHWtdqra4izfZce628an0Wo0sXyjK2SaqfCd4LbU+pXi3IyEZJ+uAHP9iVP//5z3flVatWVeex/bfffnt1jBGS/kxQRvX1vVRLDW8jn9vXvva1XdklJq/tUZVji3H9+vX6zW9+U2uIETI2PpEYCPJlTyQGgnzZE4mBYKqafcGCBWW8F1lfDnbp+eGKDD+l7eSrghga6TqUuogrsjypJPX28uXLq2PUSXfcccesf5ekxYsXd2WfV6AmczBUkvfsOd9b2xdzBVVfthivw/V8X0iyrwikhvc6eD0e8/3i2D+eIaZvbz1/PrjqzS2or3/9612ZCT3f/va3V+d94Qtf6Mqf+9znqmNf+tKXurKHeV944YVdmWHTrSxHHm9Ce5bPwEknnVSdx2faQ5XH8x333ntvavZEYujIlz2RGAimSuPnz59f3ve+90l6vjXBZApOTZmHvUVNSSs90SNXQ/FzpO1STQPdAvzqV786a/2+fRKpGLdQlmoq5skrSGlbOfEpgVxCkGqz3zziqu8zUk3dWwknaaM5vWUd7G8fM/8cQYlFaeSyhqsiV65cWR1jdBrp8/r166vzLr981wrtW265pTrGsfD8+F/84hdnrd/H/eqrr+7K3CNBqseG0YueX55JUc4777zq2He+8x1JM1F8Tz31VNL4RGLIyJc9kRgIpkrjFy1aVMZ5zHy2kvTWZ2wZMdWXnEGqKacvuCCtZH0+q0ka5RFMpPyM7vKFJIzK8zZyoQZnkb3NfbuxSu0c4d6WMVoLJ3wGe9KtmzhmpJhSvTCGY+bShbng6Kb4MboYvsiEdN/byIQS99xzT1d+z3veU523Zs2aruxbZTFy0pOR8Jkg7fbEJ9zOi8+YVLsQ7FN3OFiH59gfy5wbbrhBv/jFL5LGJxJDRr7sicRAkC97IjEQTN16e//73y/p+fZay2qilrvggl2raj2ZAnW5W1JMokjbxRNUUAu5zqX1RO3pFgktO0+0QNvFLTv2CceF0XR+nreR/dhXltp2GLUy5wc86pGWne+/RtuPGtWTbXBsvX7OJbA/PKkDNa/fJyMKWfbkJpw/YdSdVPe/27HU9xxrRnpK0ve///2u7M/L6afvWkF+8803916L4+59NZ4bWrdunZ588snU7InEkJEveyIxEEydxo+TCTjN5u+eIIC0h5TNkynwXpivS6qtvlNOOaUrO62kZdTadonJNzyZAimsg232vqftwnv2RT2tKD9STlJaz51GS82pL61PXtstOtptbnV6/vYxWvnr/T77tq/yLbUIT4rSt1+A21pvfvObuzKj7vzaHm3I7bQZUegLoEi73Tpku1iHjxktRl9MM5ZiW7Zs0W9/+9uk8YnEkJEveyIxEOTLnkgMBFPV7PPmzSvjVUmuNRkS6uGg1H/UYNRZUp3Iz3XRySef3JVpkbguohXk7aD1wVV6nkCQ+rUV2ur2D89lHR5yS63s2o02F495Msc+LSvVFiM1qq96o7b3fuQxlj1cluGt3lect+B9+bUIvxdej33aSubhobQMkfWEJrw3jpPPHfBznnSF981nye1pPnPcm07aZeNu3Lgxk1ckEkNHvuyJxECwJ1s2v2Dst99+HdXhCh6p36qRanrEaCNubyTVNM23ZGLCA9obTvta2+jQEiQV82gmUma35fpy4Leu7edx5Zxv68Q+oAXosoZ96hTfbbQx/D4pBXwVo1tUY3j0G61CzylPmUPLzutmO/wYaTbv0yUDrVrfhooJK3xFJpOY8Bnz++QxT6xy2223dWXSfbcAadv6VtfjPvA+JCb6Zo+IV0XEP0fE/RGxOSLOjoh5EXFjRGwd/Txs9zUlEom5wqQ0/guSvlFKOVEzW0FtlnS5pJtKKUsk3TT6PZFIvEgxyS6ur5D0Z5L+nSSVUp6R9ExEXCTpvNFpayR9S9KnW3UdcsghHQ2/8847q2OkPU6x3vSmN3VlJpTwyK8VK1Z0ZZ/x5Gw/Z0qdsnIG2Gk1aSUXi7R2JvUZbNJpn43n/ZDue2QZP8fFHV4/r+1Ria1ttHg90mdvB2e0vR3sb84qO81k37mk8mi7MVrpqH2WnffdtzutVFNrd4r4LLlMYPIKUms/j5LKU2bz2ny+PZU0E2L4rrnjfm25a5N8sx8n6aeS/ndE3B0R/2u0dfOCUsr20QW2S5rfqiSRSMwtJnnZD5B0pqT/WUo5Q9JTegGUPSIui4i1EbHWJ4ISicT0MMnLvk3StlLKeGvLf9bMy/94RCyUpNHPHbN9uJSyupSyrJSyzKleIpGYHibZn/0nEfFoRJxQStmimT3Z7xv9u0TSFaOf1+yurqeffrqz2Fyf8VufCf6kOtkE7Qe3k6hpXM9Tp/PaHo1FS4oJL6Q6HzxXTXkCCeop17lsv+tGfo5623U/I+M4dyDViRmZa93rYL52T6LBsWBElyddYP0O9gm1t/c35ybc2mMyUM5TtOxR3weAv/N58Wtxzsij3zjn4M/Vfffd15Vpsx511FHVeby2t59JQjlf4HMTHFu3qj0p6WyY1Gf/D5K+EhEHSvqhpH+vGVZwdURcKukRSR+YsK5EIjEHmOhlL6XcI2nZLIcumOVviUTiRYipRtARnoCAO2xu2rSpOkZrhTTbpQA/53YS6RGpo9PKt771rV359ttvr46RzvHa3g6e54tYWpSQ9dAmcjuFdpVTa4J03M+jnPBc86T4ntueYJ1uk7GP2Q6fpOXCI89jR5uOVpbLN84FeXQaJQotNLeuCM/rzsU0fm1KKkYRuh37xje+sSs7BZ80YpHWntvT40jEVi7HjI1PJAaCfNkTiYEgX/ZEYiCYqmbfuXNnZ2v4qrQbbrihK/ui/b5klJ4skjrGrSZaZdTRtDMk6frrr5/1ulKth7hay3U/9aCHh1KztlZ5sQ889JLt8OQVrIOr4xzUl558gyuv2G+uB1u581k/taeHirKNHqbaF/rpK/1oebkWZzs4Zp6slG30XP/sf++DPu3v/cEEGD4nwOeA7XItz6Ql3lc+lzAb8ps9kRgI8mVPJAaCqeagi4ifSnpY0qsl/Ww3p08D2Y4a2Y4aL4Z2vNA2HFNKOWK2A1N92buLRqwtpcwWpJPtyHZkO/ZRG5LGJxIDQb7sicRAMFcv++o5uq4j21Ej21HjxdCOvdaGOdHsiURi+kgan0gMBFN92SNiVURsiYgHImJq2Wgj4ssRsSMiNuJvU0+FHRFHR8TNo3TcmyLi43PRlog4OCLuiIj1o3b81Vy0A+3Zf5Tf8Lq5akdEPBQR90bEPRGxdg7bsc/Stk/tZY+I/SVdKeldkk6W9OGIOLn9qb2Gv5e0yv42F6mwn5X0yVLKSZJWSProqA+m3ZanJZ1fSjld0lJJqyJixRy0Y4yPayY9+Rhz1Y63lVKWwuqai3bsu7TtpZSp/JN0tqQb8PtnJH1mitdfLGkjft8iaeGovFDSlmm1BW24RtLKuWyLpEMk3SXprLloh6RFowf4fEnXzdXYSHpI0qvtb1Nth6RXSPqRRnNpe7sd06TxR0niiotto7/NFeY0FXZELJZ0hqTb56ItI+p8j2YShd5YZhKKzkWf/I2kv5TEZH1z0Y4i6ZsRsS4iLpujduzTtO3TfNlnW5YzSCsgIl4m6auSPlFK+fXuzt8XKKXsLKUs1cw36/KIOHU3H9nriIg/l7SjlLJu2teeBeeWUs7UjMz8aET82Ry0YY/Stu8O03zZt0k6Gr8vkvRYz7nTwESpsPc2IuIlmnnRv1JK+Ze5bIsklVKe0MxuPqvmoB3nSnpPRDwk6Z8knR8R/zAH7VAp5bHRzx2SviZp+Ry0Y4/Stu8O03zZ75S0JCKOHWWpvVjStVO8vuNazaTAliZMhb2niJlFx38naXMp5a/nqi0RcUREvGpUfqmkt0u6f9rtKKV8ppSyqJSyWDPPw/8rpfzFtNsREYdGxMvHZUnvkLRx2u0opfxE0qMRccLoT+O07XunHft64sMmGi6U9ANJD0r6z1O87j9K2i7pD5r53/NSSYdrZmJo6+jnvCm0482akS4bJN0z+nfhtNsi6TRJd4/asVHSfxn9fep9gjadp10TdNPuj+MkrR/92zR+NufoGVkqae1obP6vpMP2Vjsygi6RGAgygi6RGAjyZU8kBoJ82ROJgSBf9kRiIMiXPZEYCPJlTyQGgnzZE4mBIF/2RGIg+P8qeyhr2Rjy8gAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "X = center_data(imgs_flatten)\n",
+    "plt.imshow(X[0].reshape(64,64), cmap='gray')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "deletable": false,
+    "editable": false,
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[92m All tests passed\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Test your solution.\n",
+    "w4_unittest.test_center_data(center_data)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Exercise 4\n",
+    "\n",
+    "Now that you have your centered data, $X$, you can go ahead and find the covariance matrix \n",
+    "\n",
+    "You might remember from the lectures that once you have your centered data, the covariance matrix can be found by appliying the dot product between $X^T$ and $X$, and divide by the number of observations minus 1.\n",
+    "\n",
+    "To perform the dot product you can simply use the function [`np.dot`](https://numpy.org/doc/stable/reference/generated/numpy.dot.html#numpy-dot).\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "deletable": false,
+    "tags": [
+     "graded"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "def get_cov_matrix(X):\n",
+    "    \"\"\" Calculate covariance matrix from centered data X\n",
+    "    Args:\n",
+    "        X (np.ndarray): centered data matrix\n",
+    "    Outputs:\n",
+    "        cov_matrix (np.ndarray): covariance matrix\n",
+    "    \"\"\"\n",
+    "\n",
+    "    ### START CODE HERE ###\n",
+    "    cov_matrix = np.dot(X.T, X)\n",
+    "    cov_matrix = cov_matrix / 54\n",
+    "    ### END CODE HERE ###\n",
+    "    \n",
+    "    return cov_matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "cov_matrix = get_cov_matrix(X)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Check the dimensions of the covariance matrix, it should be a square matrix with 4096 rows and columns. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Covariance matrix shape: (4096, 4096)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f'Covariance matrix shape: {cov_matrix.shape}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "deletable": false,
+    "editable": false,
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[92m All tests passed\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Test your solution.\n",
+    "w4_unittest.test_cov_matrix(get_cov_matrix)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a name='2.3'></a>\n",
+    "### 2.3 - Compute the eigenvalues and eigenvectors\n",
+    "Now you are all set to compute the eigenvalues and eigenvectors of the covariance matrix.\n",
+    "Due to performance constaints, you will not be using `np.linalg.eig`, but rather the very similar function [`scipy.sparse.linalg.eigsh`](https://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.linalg.eigsh.html), which exploits the fact that $\\mathrm{cov\\_matrix}^T=\\mathrm{cov\\_matrix}$. Also, this function allows you to compute fewer number of eigenvalue-eigenvector pairs. \n",
+    "\n",
+    "It is outside of the scope of this course, but it can be shown that at most 55 eigenvalues of `cov_matrix` will be different from zero, which is the smallest dimension of the data matrix `X`. Thus, for computational efficiency, you will only be computing the first biggest 55 eigenvalues $\\lambda_1, \\ldots, \\lambda_{55}$ and their corresponding eigenvectors $v_1, \\ldots, v_{55}$. Feel free to try changing the `k` parameter in `scipy.sparse.linalg.eigsh` to something slightly bigger, to verify that all the new eigenvalues are zero. Try to keep it below 80, otherwise it will take too long to compute. \n",
+    "\n",
+    "The outputs of this scipy function are exactly the same as the ones from `np.linalg.eig`, except eigenvalues are ordered in decreasing order, so if you want to check out the largest eigenvalue you need to look into the last position of the vector. \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Ten largest eigenvalues: \n",
+      "[ 293297.76716381  383558.95285037  399091.64921256  479564.23517501\n",
+      "  839756.42124326  879138.93723794 1011092.7845815  1536790.5408648\n",
+      " 2484055.10309963 4198829.23262023]\n"
+     ]
+    }
+   ],
+   "source": [
+    "scipy.random.seed(7)\n",
+    "eigenvals, eigenvecs = scipy.sparse.linalg.eigsh(cov_matrix, k=55)\n",
+    "print(f'Ten largest eigenvalues: \\n{eigenvals[-10:]}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The random seed is fixed in the code above to help ensure the same eigenvectors are calculated each time. This is because for each eigenvector, there are actually two possible outcomes with norm 1. They fall on the same line but point in opposite directions. An example of this would be the vectors \n",
+    "\n",
+    "$$\\begin{bmatrix}0.25 \\\\0.25 \\\\ -0.25 \\\\ 0.25 \\end{bmatrix} \\text{and } \\begin{bmatrix}-0.25 \\\\ -0.25 \\\\ 0.25 \\\\ -0.25 \\end{bmatrix}.$$\n",
+    "\n",
+    "Both possibilities are correct, but by fixing the seed you guarantee you will always get the same result. \n",
+    "\n",
+    "In order to get a consistent result with `np.linalg.eig`, you will invert the order of `eigenvals` and `eigenvecs`, so they are both ordered from largest to smallest eigenvalue."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Ten largest eigenvalues: \n",
+      "[4198829.23262023 2484055.10309963 1536790.5408648  1011092.7845815\n",
+      "  879138.93723794  839756.42124326  479564.23517501  399091.64921256\n",
+      "  383558.95285037  293297.76716381]\n"
+     ]
+    }
+   ],
+   "source": [
+    "eigenvals = eigenvals[::-1]\n",
+    "eigenvecs = eigenvecs[:,::-1]\n",
+    "\n",
+    "print(f'Ten largest eigenvalues: \\n{eigenvals[:10]}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Each of the eigenvectors you found will represent one principal component. The eigenvector associated with the largest eigenvalue will be the first principal component, the eigenvector associated with the second largest eigenvalue will be the second principal component, and so on. \n",
+    "\n",
+    "It is pretty interesting to see that each principal component usually extracts some relevant features, or patterns from each image. In the next cell you will be visualizing the first sixteen components"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x1440 with 16 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(4,4, figsize=(20,20))\n",
+    "for n in range(4):\n",
+    "    for k in range(4):\n",
+    "        ax[n,k].imshow(eigenvecs[:,n*4+k].reshape(height,width), cmap='gray')\n",
+    "        ax[n,k].set_title(f'component number {n*4+k+1}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "What can you say about each of the principal components? "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a name='2.4'></a>\n",
+    "### 2.4 Transform the centered data with PCA\n",
+    "\n",
+    "Now that you have the first 55 eigenvalue-eivenvector pairs, you can transform your data to reduce the dimensions. Remember that your data originally consisted of 4096 variables. Suppose you want to reduce that to just 2 dimensions, then all you need to do to perform the reduction with PCA is take the dot product between your centered data and the matrix $\\boldsymbol{V}=\\begin{bmatrix} v_1 & v_2 \\end{bmatrix}$, whose columns are the first 2 eigenvectors, or principal components, associated to the 2 largest eigenvalues.\n",
+    "\n",
+    "<a name='ex03'></a>\n",
+    "### Exercise 5\n",
+    "In the next cell you will define a function that, given the data matrix, the eigenvector matrix (always sorted according to decreasing eignevalues), and the number of principal components to use, performs PCA."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 92,
+   "metadata": {
+    "deletable": false,
+    "tags": [
+     "graded"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "# GRADED cell\n",
+    "def perform_PCA(X, eigenvecs, k):\n",
+    "    \"\"\"\n",
+    "    Perform dimensionality reduction with PCA\n",
+    "    Inputs:\n",
+    "        X (ndarray): original data matrix. Has dimensions (n_observations)x(n_variables)\n",
+    "        eigenvecs (ndarray): matrix of eigenvectors. Each column is one eigenvector. The k-th eigenvector \n",
+    "                            is associated to the k-th eigenvalue\n",
+    "        k (int): number of principal components to use\n",
+    "    Returns:\n",
+    "        Xred\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    ### START CODE HERE ###\n",
+    "    V = eigenvecs[:, :k]\n",
+    "    Xred = X @ V\n",
+    "    ### END CODE HERE ###\n",
+    "    return Xred"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 93,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(4096, 2)"
+      ]
+     },
+     "execution_count": 93,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "eigenvecs[:, :2].shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Try out this function, reducing your data to just two components"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 94,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Xred2 shape: (55, 2)\n"
+     ]
+    }
+   ],
+   "source": [
+    "Xred2 = perform_PCA(X, eigenvecs, 2)\n",
+    "print(f'Xred2 shape: {Xred2.shape}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {
+    "deletable": false,
+    "editable": false,
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[92m All tests passed\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Test your solution.\n",
+    "w4_unittest.test_check_PCA(perform_PCA)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a name='2.5'></a>\n",
+    "### 2.5 Analyzing the dimensionality reduction in 2 dimensions\n",
+    "\n",
+    "One cool thing about reducing your data to just two components is that you can clearly visualize each cat image on the plane. Remember that each axis on this new plane represents a linear combination of the original variables, given by the direction of the two eigenvectors.\n",
+    "\n",
+    "Use the function `plot_reduced_data` in `utils`to visualize the transformed data. Each blue dot represents an image, and the number represents the index of the image. This is so you can later recover which image is which, and gain some intuition."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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GUeVr+fLllee8/PLL/PznPyc0NBTDMPj44489FzDQyKOfLiIiIiLixPbt2wkICKh83blz58rv33zzTQzDYPDgwaxZs8YT4TlQQi0iIiIiXqd3795YLBanx9LS0vDx8eHAgQNekVCr5ENERERE6hQfH+9KYb0rGhERERERoEuXLjRq1Ijo6Gj+8pe/eDqcK1LJh4iIiIh4jdatWzN37lxuvfVWbDYba9asYcKECRQWFvKb3/zG0+E5pYRaRERERLzG4MGDGTx4cOXrxMRESkpKmDdvHk888YTXlXuAEmoRERER8SDTNMk8eY60bCunCooJt/gT3zWUmIimGIYBwIgRI3j77bc5fPiwQ7cPb6GEWkREREQ8wjRN3t13jF1ZuQQ29iWwSSNycgs4cPwsCVFhDI9tW5lUAw7fexMl1CIiIiLiEZknz7ErK5e2zQPw8SlLlgP8fAmxm6Rm5dKjTTAxEcFs2LCBsLAwOnbs6OGInVNCLSIiIiIekZZtJbCxb2UyDfD67yfRIfomLK078/LhdM4c2MG6detYunRpZf10eno6hw8f5siRIwDs2LGD3NxcOnXqRFxcnNvvQwm1iIiIiHjEqYJiAps4pqMt20Xy2T82kHfqJKZp8rMbb+DNN9/koYceqjxn2bJlvPHGG5Wv58yZA8CYMWNYtWqVO0J3YJim6fYPrUlxcXFmenq6p8MQERERkeu0IjWHnNwCQi1NqhyzFpQQGWZhXEKkByJzzjCMvaZpVpkC976+IyIiIiLSIMR3DeV8qQ273XGC1243OV9qo19UqIciuz5KqEVERETEI2IimpIQFcbRvCKsBSUUXbBhLSjhaF4RCVFhRLdq6ukQr4lqqEVERETEIwzDYHhsW3q0CWZ3Vlkf6sgwC/2iQolu1dRr2+RdTgm1iIiIiHiMYRjERJS1x6urVPIhIiIiIuICJdQiIiIiIi5QQi0iIiIi4gIl1CIiIiIiLlBCLSIiIiLiAiXUIlIjkpOTiY+PJzQ0FH9/f6Kjo5k3bx6lpaWeDk1ERKRWqW2eiNQIq9XKwIEDmTZtGs2bN+ezzz5jzpw5nDx5kmXLlnk6PBERkVpjmKZ59bO8WFxcnJmenu7pMETEiVmzZvHSSy9x5syZOtOcX0REpDqGYew1TTPu8nGXSz4Mw2hvGMZHhmFkGIbxtWEYT5SPtzAM4wPDMLLK/xtyyTUzDcPINgzjkGEYgy8Zv8UwjP3lx5Ya+hdYpE4LDQ1VyYeIiNR7NVFDfRGYYppmd6Av8LhhGD2AGUCKaZpRQEr5a8qPjQJuAIYALxuG4Vv+Xn8GHgWiyr+G1EB8IuJGNpuNwsJCdu3axdKlS3nsscc0Oy0iIvWaywm1aZonTNP8ovz7c0AG0BZIAt4oP+0N4N7y75OAtaZplpimmQNkA7cahtEaCDZN8xOzrA7lzUuuEZE6IigoiKCgIBISEujfvz+LFi3ydEgiIiK1qka7fBiG0QmIBfYArUzTPAFlSTfQsvy0tsCRSy47Wj7Wtvz7y8dFpA5JS0sjNTWVxYsXs3HjRiZOnOjpkERERGpVjXX5MAzDAmwAJpummX+FR7zODphXGHf2WY9SVhpChw4drj9YEak1vXr1AuC2224jLCyMMWPGMGXKFLp06eLhyERERGpHjSTUhmH4UZZM/9U0zXfKh38wDKO1aZonyss5fiwfPwq0v+TydsDx8vF2TsarME3zFeAVKOvyURP3ICLXxzRNMk+eIy3byqmCYsIt/sR3DSUmomllzXRFcp2Tk6OEWkRE6q2a6PJhACuADNM0l1xyaBMwpvz7McDGS8ZHGYbRxDCMSMoWH35WXhZyzjCMvuXv+fAl14iIFzFNk3f3HePVnd+Rk1uA3YSc3AJe2fkd7+47RkU7zt27dwMQGRnpyXBFRERqVU3MUPcDHgL2G4bxZfnY08AC4G3DMMYB3wP3AZim+bVhGG8DBynrEPK4aZq28useA1YBAcC28i8R8TKZJ8+xKyuXts0D8PEpm41+838fJerm/yBnXwfOfNOW7zO+ZPHixYwcOVKz0yIiUq+5nFCbprkL5/XPALdXc80fgD84GU8HbnQ1JhGpXWnZVgIb+1Ym0wAdut1E+gd/x/rDUd5v1IiYqK7Mnz+fCRMmeDBSqQ/Wr1/PW2+9xd69ezl79izR0dFMnTqVBx54oPIc0zSZP38+f/7zn8nNzaV3794sXbqUm2++2XOBi0iDoa3HReS6nSooJrCJ418fiWMnkzh2MkUXbPgYMCOxu4eik/pmyZIlREZG8vzzzxMWFsbWrVsZPXo0ubm5TJo0CYAFCxYwd+5cFi1aRExMDEuWLOGOO+7gwIEDREREePgORKS+09bjInLdVqTmkJNbQKilSZVj1oISIsMsjEtQ3bTUjNzcXMLCwhzGRo8ezSeffEJOTg7FxcW0atWKKVOmMHv2bADOnz9Pp06dGD9+PPPmzfNE2CJSD9Xa1uMi0vDEdw3lfKkNu93xB3K73eR8qY1+UaEeikzqo8uTaYDY2Fh+/LGseVRaWhr5+fncf//9lceDgoIYNmwY27ZpKY6I1D4l1CJy3WIimpIQFcbRvCKsBSUUXbBhLSjhaF4RCVFhRLdq6ukQpZ5LS0ujR48eAGRmZuLr60tUVJTDOd27dyczM9MT4YlIA6MaahG5boZhMDy2LT3aBLM7q6wPdWSYhX5RoUS3+ncfapHakJKSwsaNG1m5ciUAZ86cwWKx4Ovr63BeSEgIhYWFlJaW0rhxY0+EKiINhBJqEflJDMMgJiKYmIhgT4ciDcjhw4cZPXo0SUlJjB07tnLc2Q9xFWuE9AOeiNQ2lXyIiEidcPr0aRITE+nQoQOrV6+uHA8JCeHcuXPYbDaH8/Py8ggMDMTPz+8nf+b69eu55557aNu2LRaLhVtuuYU1a9b85PcTkfpJM9QiIuJVnG1rH9smgIkP/T9KS0vZsmULQUFBlefHxMRgs9nIzs4mOjq6cjwzM5OYmBiXYrmWln0iIkqoRUTEa1Rsa78rK5fAxr4ENmnEtz/kMe+Jhzmdc4jPPk2jZcuWDtfEx8cTHBzM+vXr+e1vfwtAYWEhmzdv5tFHH3Upns2bNzt0GRk0aBDHjx9nyZIlSqhFpJISahER8RrOtrXfvHIBh/ftov+YaezLPsqZM2cqz4+NjcXf358ZM2Ywd+5cQkJCKjd2sdvtLie91bXs27hxo0vvKyL1ixJqERHxGs62tT/0xW4AdryxiB1vLHI4Pycnh06dOjFjxgzsdjvz58/HarUSFxfHBx98QKtWrWo+xkta9omIgHZKFBERL7JgWwZ2EwL8fKsc84Zt7VNSUrjzzjtZuXKlQ5cREWkYtFOiiIh4vXCLP4UlF50eKyy5SLjF380R/Vt1LftERFTyISIiXiO+aygHjp8lxG46lH24a1t7Zx1G4ruG0rLxBact+0REQAm1iIh4kYpt7VOzcgkq7/JRWHKR86W2Wt/W3lmHkZzcAvblnOTDxZO44KRln4gIKKEWEREv4slt7Z11GGnsY7Jh/ky+z/mWDdtSqrTsExEBJdQiIuJlPLWtvbMOIxuW/o7Mz3dw17inSN1/mBDf0spjsbGxNGnSxK0xioh3UkItIiICnCooJrCJ4z+LFS373l+xkPdXwPxLjlW07BMRUUItIiJCWYeRnNwCh5Z9z7y1HQBrQQmRYRbGJUR6KjwR8WJqmyciIkJZh5HzpTbsdsf9GdzVYURE6i4l1CIiIvy7w8jRvCKsBSUUXbBhLSjhaF5RrXcYEZG6TSUfIiIieLbDiIjUbUqoRUREynmqw4iI1G0q+RARERERcYESahGROujYsWNYLBYMw6CgoKBy3DRN/vjHP9K+fXsCAgL4z//8T7788kvPBSoi0gAooRYRqYOmTZuGxWKpMr5gwQLmzp3LU089xebNm7FYLNxxxx2cPHnSA1GKiDQMSqhFROqY1NRU3nvvPaZOneowXlxczIIFC5g5cyYTJ07kjjvuYP369RiGwbJlyzwUrYhI/aeEWkSkDrHZbEyaNInZs2cTFhbmcCwtLY38/Hzuv//+yrGgoCCGDRvGtm3b3B2qiEiDoYRaRKQOWb58OcXFxTz++ONVjmVmZuLr60tUVJTDePfu3cnMzHRXiCIiDY7a5omI1BFWq5VnnnmG1atX4+fnV+X4mTNnsFgs+Pr6OoyHhIRQWFhIaWkpjRs3dle4IiINhmaoRUTqiFmzZtGnTx+GDh1a7TnONh8xTbPaYyIi4jrNUIuIeCHTNMk8eY607LId+0pPfc+KlSvZuWMHeXl5ABQWFgJw9uxZfH19CQkJ4dy5c9hsNodZ6ry8PAIDA53OaouIiOuUUIuIeBnTNHl33zF2ZeUS2NiXwCaN2H8wk4sXLhAfH1/l/Hbt2jFu3DhGjx6NzWYjOzub6OjoyuOZmZnExMS48xZERBoUJdQiIl4m8+Q5dmXl0rZ5AD4+ZWUaP4vrQ9jCNzhVUMo9N7emQ4sg3nvvPRYuXMjWrVvp3LkzHTt2JDg4mPXr1/Pb3/4WKJvF3rx5M48++qgnb0lEpF5TQi0i4mXSsq0ENvatTKYBLM1a0C22L6EFJVwIszAgIZLDhw8DkJCQULnJy4wZM5g7dy4hISHExMSwZMkS7HY7kyZN8sStiIg0CEqoRUS8zKmCYgKbOP/rObBJI04VFFd77YwZM7Db7cyfPx+r1UpcXBwffPABrVq1qq1wRUQaPKNi9XddFRcXZ6anp3s6DBGRGrMiNYec3AJCLU2qHLMWlBAZZmFcQqQHIhMRadgMw9hrmmbc5eNqmyci4mXiu4ZyvtSG3e444WG3m5wvtdEvKtRDkYmIiDNKqEVEvExMRFMSosI4mleEtaCEogs2rAUlHM0rIiEqjOhWTT0dooiIXEI11CIiXsYwDIbHtqVHm2B2Z5X1oY4Ms9AvKpToVk21QYuIiJdRQi0i4oUMwyAmIpiYiGBPhyIiIlehkg8RERERERcooRYRERERcYESahERERERFyihFhERERFxgRJqEREREREXKKEWEREREXGBEmoRqVOSk5OJj48nNDQUf39/oqOjmTdvHqWlpZXnmKbJH//4R9q3b09AQAD/+Z//yZdffunxuPLy8vjVr35FixYtsFgsJCYmkp2dXatxiYhI7VNCLSJ1itVqZeDAgbz22mts27aNX/3qV/zhD3/gySefrDxnwYIFzJ07l6eeeorNmzdjsVi44447OHnypEfjGjlyJP/4xz944YUX+Nvf/obVauX2228nPz+/1uISEZHaZ5im6ekYXBIXF2emp6d7OgwR8aBZs2bx0ksvcebMGUpKSmjVqhVTpkxh9uzZAJw/f55OnToxfvx45s2b55G4Pv30U+Lj40lJSWHQoEEA/PDDD0RGRvL73/+eqVOnui0uERH5aQzD2GuaZtzl45qhFpE6LzQ0tLK0Ii0tjfz8fO6///7K40FBQQwbNoxt27Z5LK4vv/ySRo0a0b9//8rjrVq14mc/+xlbtmxxa1wiIlKzlFCLSJ1ks9koLCxk165dLF26lMceewzDMMjMzMTX15eoqCiH87t3705mZqbH4iouLqZRo0b4+vo6nN+kSRMyMjJqPS4RkZpwtfUipaWl3H///XTu3JmAgADCw8NJTExk7969Ho68djXydAAiIj9FUFAQJSUlADz88MMsWrQIgDNnzmCxWKokriEhIRQWFlJaWkrjxo3dHlfXrl0pLi5m//793HTTTQAUFRVx4MABzp07V2vxiIjUpIr1ItOmTaN58+Z89tlnzJkzh5MnT7Js2TJsNhuGYTBz5ky6dOlCfn4+zz//PIMGDWLfvn107tzZ07dQK5RQi0idlJaWRmFhIZ999hm///3vmThxIi+//DIAhmFUOb9ivYizY+6Ia/DgwURGRjJ+/Hhef/11goODmTFjBmfPnsXPz69WYxIRqSnjx493eD1w4EDy8/N56aWXePHFFwkICGDdunUO59xxxx2Ehoby97//3WGhdn2ikg8RqZN69erFbbfdxpNPPsnSpUv585//zLfffktISAjnzp3DZrM5nJ+Xl0dgYGCNJa+maZJxIp8VqTks2JbBitQcMk7kExsb6zSuxo0bs3btWn744QdiYmJo06YN3333HQ8//DCtWrWqkZh+qmtp+Qewf/9+7r77bpo1a0bTpk259dZb6/1jXBG5ukvXizgTFBSEv7//Fc+p6zRDLSJezTRNMk+eIy3byqmCYsIt/sR3DSUmomnlbHOvXr0AyMnJISYmBpvNRnZ2NtHR0ZXvk5mZSUxMTI3F9O6+Y+zKyiWwsS+BTRqRk1vAgeNnSYgKY3hsWwzDcIirS5cu3HrrrWRnZ/PNN9/QqFEjunTpwt13303fvn1rJK6f6mqPcKFsUWVCQgJJSUmVs0+ff/45RUVFngxdRDzEZrNRUlLCF1984bBepIJpmthsNnJzc1m8eDG+vr488MADHoy4dimhFhGvda2J6+7duwGIjIykbdu2BAcHs379en77298CUFhYyObNm3n00UdrJK7Mk+fYlZVL2+YB+PiU/QMS4OdLiN0kNSuXHm2CiYkIdoirgmEYlYl+VlYWH374IZs3b66RuH6qqz3CNQyDCRMmMGzYMFavXl153pAhQ9wdqoh4ierWi1RYuHAhM2fOBCA8PJytW7fSsWNHt8fpLkqoRcRrOUtc3/zfR4m6+T/I2deBM9+05fuML1m8eDEjR46kS5cuAMyYMYO5c+cSEhJCTEwMS5YswW63M2nSpBqJKy3bSmBj38qYAP7y9Di6xcYT2Kojrxz9J03zv60S19y5c4mJiSEsLIz9+/czd+5cRo0axZ133lkjcdWkSx/hHjx4kD179vD88897OKrrd+zYMaKjozl//jznzp3DYrEAcOLECZ5++mnef/99zp49S1RUFFOnTuUXv/iFhyMWqRuutI4FYOzYsdxxxx2cOHGCl19+mbvvvpudO3fSo0cPD0Zde5RQi4jXcpa4duh2E+kf/B3rD0d5v1EjYqK6Mn/+fCZMmFB5zowZM7Db7cyfPx+r1UpcXBwffPBBjdUqnyooJrCJ41+fHbrdxOfvv8vpH47i49uI7t2qxmW1Wpk8eTK5ubm0b9+eqVOnMmXKlBqJqSZU9wh3z549QFkHlZ49e/L111/TsWNHnn76acaNG+fhqK9s2rRpWCwWzp8/Xzlmt9u55557sFqtPPvss0RERJCcnMyDDz5IYGAgw4cP92DEIt6lurK72NhYDMPgtttuIywsjDFjxjBlypTKCYSIiAgiIiIASExM5IYbbmDBggW8+eabnrydWqOdEkXEay3YloHdLCunuFzRBRs+BsxI7O72uFak5pCTW0CopUmVY9aCEiLDLIxLiHRypXfz9/d3eIT7+uuv4+Pjw/z583n66acJDQ1l+vTp9O7dm+TkZF5++WW2bNnC0KFDPRy5c6mpqSQlJfH0008zbdq0yhnqzMxMunfvzqZNmxg2bFjl+b169SIqKqpKhwKRhspZ2V1hyUXOl9ocyu4OHDjATTfdxAcffMAdd9zh9L1GjBjByZMn2bVrl5vvomZpp0QRqXPCLf4Ullx0eqyw5CLhFn83R1Qmvmso50tt2O2OExJ2u8n5Uhv9okI9Eper0tLSSE1NZfHixWzcuJGJEycCZTO6AI888gjTp09n4MCBvPTSSwwcOJD58+d7MuRq2Ww2Jk2axOzZswkLC3M4duHCBQCaNWvmMN68eXPq+iSTSE26tOwu1NKEAD9fQi1NaNc8gNSsXA79UNZD39l6kUsVFxfzxRdfVHu8PlDJh4h4rfiuoRw4fpYQu+lQ9uHpxDUmoikJUWGkZuUS5GTWJrpVU4/E5aqKriSXP8Jt0aIFULZY8VKDBg3y2rrq5cuXU1xczOOPP85f//pXh2M33ngjffr0Yfbs2bz66qu0atWKd955h927d7t9e3oRb/ZT1ousWbOGbdu2MWTIENq0aVNZQ33ixIl624MalFCLiBfz1sTVMAyGx7alR5tgdmeV1RVGhlnoFxVKdKumtb55jCuupQ0hOLYi7N7deVmNaZr4+Hjfg06r1cozzzzD6tWrnfYdNwyDbdu2kZSURLdu3QDw8/Pj9ddfZ9CgQe4OV8Rr/ZT1ItHR0axevZonn3ySM2fO0Lp1a/r06UN6ejo33HCDJ27DLZRQi4jX8ubE1TAMYiLK2uPVFdfahhAcH+G2b9+ekJAQUlJSGDx4cOX7paSk0LNnT4/cy5XMmjWLPn36VFvbbbfbeeihh7Baraxbt46WLVuydetWxo0bR2hoqNoBipQLt/iTk1vgsI4lcexkEsdOrna9SK9evdiyZYu7Q/U4JdQi4tXqYuLqrarrn508cxx7Y3qTm9iPTuFN2b17d5WWf7Nnz2b69Ok0b96c3r17s2HDBnbu3MmOHTs8eUtVZtxLT33PipUr2bljB3l5eUBZH3KAs2fP4uvrywcffMCWLVv45ptviIqKAmDAgAEcOXKE6dOnK6EWKeetZXfeSAm1iEgD4aweEqBD9E18uXMTv37nL/g39qNz585VWv5NnjwZu93Oiy++yJw5c4iOjiY5OZmEhAR330YlZzPu+w9mcvHCBeLj46uc365dO8aNG0e3bt0IDAysTKYrxMbGsmnTJneFL+L1vLXszhupbZ6ISAPhrW0If6qME/m8uvM7hxn3grOnOf7dN5wqKOWem1vToUUQ7733HgsXLmTr1q107tyZL7/8klGjRpGZmemwPf3IkSM5cOAAX3/9taduScTrmKbJoR/OVZbdhVv8vaLszlOqa5unGWoRkQbCWT1khcKSi0SGWTwQ1U/nbMbd0qwF3WL7ElpQwoUwCwMSIjl8+DAACQkJWCwW2rRpQ4cOHbj33nuZPXs24eHhbNmyhbfffpuXXnrJQ3cj4p1UdndtvG95toiI1Ir61j/bWQeCCoFNGnGqoNjpsaZNm5KSksKNN97IlClTuPfee9m+fTvLly/nscceq82QRaSeUsmHiEgDUVFzXF095KVdPuqC+rpjpYh4L5V8iIg0cN7chvCnUAcCEfEWSqhFRBqQ+lQPqQ4EIuItlFCLiEidVN9m3EWk7lJCLSLiBY4dO0Z0dDTnz5/n3LlzWCwWTpw4wZIlS3j//ff59ttvCQkJYdCgQcyfP582bdp4OmSvUJ9m3EWk7lKXDxERLzBt2jQsFse2dXv37uXdd9/lgQceYPPmzSxatIg9e/YQHx9PQUGBhyIVEZHL1UhCbRjGSsMwfjQM48AlYy0Mw/jAMIys8v+GXHJspmEY2YZhHDIMY/Al47cYhrG//NhSQ8/rRKQBSE1N5b333mPq1KkO47fddhuZmZnMmDGDgQMHMmrUKDZt2sS//vUvNmzY4PLnJicnEx8fT2hoKP7+/kRHRzNv3jxKS0sB+PjjjzEMw+nX4MGDr/LuIiINR02VfKwClgFvXjI2A0gxTXOBYRgzyl8/ZRhGD2AUcAPQBvjQMIxupmnagD8DjwKfAluBIcC2GopRRMTr2Gw2Jk2axOzZs2nevLnDsctfA5XbZv/4448uf7bVamXgwIFMmzaN5s2b89lnnzFnzhxOnjzJsmXL6NWrF5988onDNd9//z0jR44kMTHR5c8XEakvaiShNk1zp2EYnS4bTgIGlH//BvAx8FT5+FrTNEuAHMMwsoFbDcM4DASbpvkJgGEYbwL3ooRaROqx5cuXU1xczOOPP85f//rXq57/z3/+k8LCQnr06OHyZ48fP97h9cCBA8nPz+ell17ixRdfJDg4mL59+zqck5qaio+PD/fff7/Lny8iUl/U5qLEVqZpngAwTfOEYRgty8fbUjYDXeFo+diF8u8vH6/CMIxHKZvJpkOHDjUctoiIe1itVp555hlWr16Nn5/fVc+32+088cQTREVFcdddd9VKTKGhoZUlH86sWbOG/v37a1GkiMglPNHlw1ldtHmF8aqDpvkK8AqU7ZRYc6GJiLjPrFmz6NOnD0OHDr2m82fOnMknn3zCjh07rikBv1Y2m42SkhK++OILli5dymOPPea05VxWVhb79u3jlVdeqbHPFhGpD2ozof7BMIzW5bPTrYGKgr+jQPtLzmsHHC8fb+dkXESkXjBNk8yT50jLtnLg6/28tmIlq9/dxpkzZzAMg8LCQgDOnj2Lr68vAQEBlde+/PLLLFq0iDVr1tCnT58ajSsoKIiSkhIAHn74YRYtWuT0vDVr1uDn58d//dd/1ejni4jUdbXZNm8TMKb8+zHAxkvGRxmG0cQwjEggCvisvDzknGEYfcu7ezx8yTUiInWaaZq8u+8Yr+78jpzcAk4d+xe2ixd4YNgdtGjRgpCQEB5//HEA2rVrx6RJkyqv3bBhA5MmTeLZZ59l5MiRNR5bWloaqampLF68mI0bNzJx4kSn561du5a77rqLFi1a1HgMIiJ1WY3MUBuGsYayBYhhhmEcBf4XWAC8bRjGOOB74D4A0zS/NgzjbeAgcBF4vLzDB8BjlHUMCaBsMaIWJIpIvZB58hy7snJp2zwAHx+DJj178z+L3sRuNzlVUMo9N7fm4GepLFy4kK1bt9K5c2egrHXdL37xCyZOnFilrd71unSG/FRBMeEWf+K7hhIbG4thGNx2222EhYUxZswYpkyZQpcuXSqv/eqrr8jIyGDWrFkuxSAiUh/VVJePB6o5dHs15/8B+IOT8XTgxpqISUTEm6RlWwls7IuPT1ltsqVZC7r2LCvdCC0o4UKYhZiYUwAkJCRgsVjIyMjg3nvvJSYmhpEjR/Lpp/9ezx0eHu6Q8F5NxQz5rqxcAhv7EtikETm5BRw4fpaEqDCGx7bFMAx69eoFQE5OjsP7r127loCAAJKSklz+tRARqW+09biIiBucKigmsInzv3IDmzTiVEExEZeN79mzh7Nnz/LVV1/Rr18/h2Njxoxh1apV1/z5l8+QAwT4+RJiN0nNyqVHm7Ltu3fv3g1AZGSkw/Xr1q1j2LBhVXZzFBERJdQiIm4RbvEnJ7eAAD/fKscKSy4SGWZhbOJYxo4dWzk+dqzja1dcPkMO8Jenx9EtNp7AVh155eg/aZr/LYsXL2bkyJEOs9OffvopOTk5LFmypEZiERGpb5RQi4i4QXzXUA4cP0uI3XRIau12k/OlNvpFhdbq5zubIe/Q7SY+f/9dTv9wFB/fRnTv1pX58+czYcIEh/PWrl1Ls2bNtDuiiEg1DNOs222c4+LizPT0dE+HISJyRRU1zKlZuQSV1zAXllzkfKnNoYa5tqxIzSEnt4BQS5Mqx6wFJUSGWRiXEOnkShERqWAYxl7TNOMuH9cMtYiIGxiGwfDYtvRoE8zurLIuG5FhFvpFhRLdqmmtJtPg+RlyEZH6TAm1iIibGIZBTETZ4j93i4loSkJUWLUz5NGtmro9JhGR+kIJtYhIA+DpGXIRkfpMCbWISAPhyRlyEZH6rDa3HhcRERERqfeUUIuIiIiIuEAJtYiIiIiIC5RQi4iIiIi4QAm1iEgdMGDAAAzDcPr1ySefeDo8EZEGTQm1iEgd8PLLL/PJJ584fN15552EhYXRu3dvt8Vx7NgxLBYLhmFQUFAAQGlpKffffz+dO3cmICCA8PBwEhMT2bt3r9viEhHxJLXNExGpA3r06OHwurS0lPT0dEaOHEmjRu77q3zatGlYLBbOnz9fOWaz2TAMg5kzZ9KlSxfy8/N5/vnnGTRoEPv27aNz585ui09ExBM0Qy0iUge99957nDlzhgceeMBtn5mamsp7773H1KlTHcYDAgJYt24d//3f/82gQYO499572bJlC8XFxfz97393W3xSd6xfv5577rmHtm3bYrFYuOWWW1izZo3DOXl5efzqV7+iRYsWWCwWEhMTyc7O9lDEIlemhFpEpA5au3Ytbdu2JSEhwS2fZ7PZmDRpErNnzyYsLOyq5wcFBeHv709paakbopO6ZsmSJVgsFp5//nk2bdrEwIEDGT16NC+++GLlOSNHjuQf//gHL7zwAn/729+wWq3cfvvt5OfnezByEedU8iEiUscUFhayefNmHn30UbdtGb58+XKKi4t5/PHH+etf/+r0HNM0sdls5ObmsnjxYnx9fd06gy51x+bNmx1+MBs0aBDHjx9nyZIlTJo0iU8++YT333+flJQUBg0aBECfPn2IjIzklVdeqfKURMTTNEMtIlLHbN68mYKCArclq1arlWeeeYYlS5bg5+dX7XkLFy7Ez8+P1q1b88Ybb7B161Y6duzolhilbnH2lCM2NpYff/wRgC+//JJGjRrRv3//yuOtWrXiZz/7GVu2bHFbnCLXSgm1iEgds3btWrp27UpcXJxbPm/WrFn06dOHoUOHXvG8sWPH8vnnn7Np0yZuueUW7r77bg4ePOiWGKXuS0tLq1x8W1xcTKNGjfD19XU4p0mTJmRkZHgiPJErUsmHiIgXMk2TzJPnSMu2cqqgmHCLP/FdQ2kdYGfbtm1Mnz7dLZ9beup7Vqxcyc4dO8jLywPKSk4Azp49i6+vLwEBAQBEREQQEREBQGJiIjfccAMLFizgzTffrJVYa1p2djaLFi3i008/5cCBAyQkJPDxxx9XHv/4448ZOHCg02vvuusu/vGPf7gp0vonJSWFjRs3snLlSgC6du1KcXEx+/fv56abbgKgqKiIAwcOcO7cOU+GKuKUEmoRES9jmibv7jvGrqxcAhv7EtikETm5BRw4fpYLGdspKSmplXIPZ5+7/2AmFy9cID4+vsr57dq1Y9y4cbz22mtVjjVq1IibbrqJ7777rsbjrC1ff/01W7dupW/fvk4XU/bq1avKJjrff/89I0eOJDEx0V1h1juHDx9m9OjRJCUlMXbsWAAGDx5MZGQk48eP5/XXXyc4OJgZM2Zw9uzZK5YdiXiKEmoRES+TefIcu7Jyads8AB+fskWHAX6+hNhNXvz7BmJuuInu3bu75XN/FteHsIVvcKqglHtubk2HFkG89957LFy4kK1bt1bbY7q4uJgvvviCfv361XictWXYsGEkJSUBMGLECHJzcx2OBwcH07dvX4ex1NRUfHx8uP/++90WZ31y+vRpEhMT6dChA6tXr64cb9y4MWvXruWBBx4gJiYGgNtuu42HH36Y7du3eypckWqphlpE6pRVq1Y53X57+fLlQO3u2ne13rkff/xxtduDDx48+Jo/Jy3bSmBj38qktkLhuTMcOfAZPfoNcflervVzLc1a0C22LzGxfbgQ3oMBAwZUJjgJCQlER0ezZs0aHn74Yf72t7/x8ccfs2bNGu68805OnDjBk08+WSux1gYfn+v/J3HNmjX079+fNm3a1EJE9YdpmmScyGdFag4LtmWwIjWHL749yd13301paSlbtmwhKCjI4Zpbb72V7OxsMjMzyc7OJjU1lR9//LHKDzUi3kAz1C66Ws0dwIkTJ3j66ad5//33OXv2LFFRUUydOpVf/OIXnglapB7Yvn17Ze0uUDlTWpu79i1ZsoTIyEief/55wsLC2Lp1K6NHjyY3N5dJkybVWEnAqYJiAptU/evZ0qwFczf9E59a6pRX3ecCBDZpxKmCYqfHoqOjWb16NU8++SRnzpyhdevW9OnTh/T0dG644YbaCdYLZGVlsW/fPl555RVPh+LVnJUSfftDHvOeeJjTOYf47NM0WrZs6fRawzCIjo4Gyn69P/zwQzZv3uzO8EWuiRJqF12t5s5ut3PPPfdgtVp59tlniYiIIDk5mQcffJDAwECGDx/ugahF6r7evXtjsViqjFfs2nepO+64g9DQUP7+97+7NGN6td65NVUSEG7xJye3gAA/3yrHCksuEhlW9b5rwrV+7tixYytrXaGstrghtjJbs2YNfn5+/Nd//ZenQ/FqzkqJNq9cwOF9u+g/Zhr7so9y5syZyvNjY2Np0qQJc+fOJSYmhrCwMPbv38/cuXMZNWoUd955p6duRaRaSqhddLWau2+++Yb09HQ2bdrEsGHDALj99tvZs2cPa9euVUIt4gY1tWtfdb1zN27cWO01P6UkIL5rKAeOnyXEbjqUX9jtJudLbfSLCr2+wL38c+uqtWvXctddd9GiRQtPh+LVnJUSHfpiNwA73ljEjjcWOZyfk5NDp06dsFqtTJ48mdzcXNq3b8/UqVOZMmWKW2MXuVZKqF10tZq7CxcuANCsWTOH8ebNm2OaZq3FJVLfdenSBavVSpcuXXjyyScZP368w3F37dp3ae/cy/3UkoCYiKYkRIWRmpVLUPkj8sKSi5wvtZEQFUZ0q6Y1EbrXfK6nVNeaMCbi6vf51VdfkZGRwaxZs9wQad3mrJTombfKFhYWXbDhY8CMxKqLbP/0pz/xpz/9yR0hirhMCXUtu/HGG+nTpw+zZ8/m1VdfpVWrVrzzzjvs3r2bbdu2eTo8kTqndevWzJ07l1tvvRWbzcaaNWuYMGEChYWF/OY3v6k8b+HChcycOROA8PDwWtm17/LeuZf7qSUBhmEwPLYtPdoEszurLNmLDLPQLyqU6FZNa227cU99ridcqTVhQpTjk4i///3vzJ49m0OHDtGmTRsmTZrEqVOnCAgIqHxCKdXzVAmTiDsZdX2WNC4uzkxPT/d0GMC/Sz4uX5R45swZkpKSSE1NBcDPz4/XX39dixJFasjIkSP58MMPOXXqVOVTo5MnT3L06FFOnDjByy+/zOeff87OnTurnU2+XocPH6ZPnz7Ex8fz7rvvOj2nR48edO7cmf/7v/+rkc+UmpNxIp9Xd37nUNcLZeUtR/OKOPjW/1JScJY//OEPJCQk8Ktf/Yr777+fPXv28Pvf/57g4GDuuOOOKvX6UlXGiXxe2fkd7ar5tR7fvzMxEcEejFDk2hmGsdc0zSrb1GqGupbZ7XYeeughrFYr69ato2XLlmzdupVx48YRGhrKkCG10/5KpCEZMWIEb7/9NocPH67s4lETu/ZVVxLQsvEFp71zL6WSAO/mrK63tLiIjM92cK74AtmHj+BvlvA///M/REdHs3TpUgIDA7nrrrs4ePAga9euZcSIER68g7qjoZUSScOkhPo6XW/N3f/93/+xZcsWvvnmG6KiogAYMGAAR44cYfr06UqoRa7iSn/mLi9BqK4k4afs2lddScC+nJN8uHgSF6rpnVth7dq1KgnwYs7qegvyrLwx7wmn5//444906tQJKNsCG8rWwsjVNaRSImm4lFBfh+upuauQmZlJYGBgZTJdITY2lk2bNrkjbJE662p/5obHtsUwDDZs2EBYWFi1NdI/Zdc+Z62+GvuYbJg/k+9zvmXDtpRqe+cCrFu3jmHDhjlt7See56yut0VEO5a8fwhrQQmRYRbGJUTSrFkzZs6cWZlMAzzxxBNs3LiRb7/9Vi3crpFhGMREBKu0Q+otJdTX4UrbAadm5XKu+EKVazp27EhhYSGHDh2qbE4PsHfvXoe/oEWkKmd/5tbOn0z7bjeRs68TP3zdkrT3N7Nu3TqWLl2Kj48Pa9asYdu2bQwZMoQ2bdpU1lBf7659zkoCNiz9HZmf7+CucU+Ruv8wIb7/bsNX0TsX4NNPPyUnJ4clS5bU0K+E1LRrbRHYtWtXPv/8c4drP/vsM6Bs22wREVBCfV2uteYuOTkZgKFDhzJ06FA6dOjAvffey+zZswkPD2fLli28/fbbvPTSS566FZE6wdmfuZbtIvn8/Q2c+fEkWzG56cYbePPNN3nooYeAmtu1z1lJQEXv3PdXLOT9FTD/kmMVvXOhrNyjWbNm17U7orjXtdb1Tpgwgccee4xXX32VESNG8Nlnn7F48WIAfH2rdq0QkYZJXT6uw4JtGdhNHB4Rnj55lHkP3+70/Ip/YLOzs5k5cya7d+8mPz+fLl268D//8z88+uijqh0TuQJnf+YqXKl/bU1YkZpDTm4BoZYmVY5dWhIgdZdpmhz64VxlXW9ZfX4LTBM++fY0pwqKCQ3w4+M3nmXdWyux2WwEBgaycOFCJk2axOuvv+6wY6SI1H/q8lEDrrXm7nJdu3Zl/fr17gxVpF7wZP9a7RpY/11e1+usZv9fZ4poOeR/WDnm19zcwk7nzp3JzMwEqLLNvIg0XFfe5k8cxHcN5XypDbvdcVZf/8CK1A5P/pmrKAk4mleEtaCEogs2rAUlHM0rUquveurSmv1QSxMC/HwJtTShXfMA9v1wkcYtO2GxWHj55ZeJj48nJibG0yGLiJfQDPV1UC9NEffy5J85tfqqGRcvXuS5555jxYoVfP/994SHh3Pffffx/PPPezq0KpzV7B/O+JKcA3tp2qYrS7M+4dRX2/nHP/7Brl27PBipiHgbJdTXQf/AiriXp//MqdWX6375y1+SkpLC//7v/xITE8ORI0c4ePCgp8NyytlCVF/fRny5Yys/fP8thuHD7QP7s3v3bm666SYPRSki3kiLEkXcIDs7m0WLFvHpp59y4MABEhISqmxRb5om8+fP589//jO5ubn07t2bpUuXcvPNN3skZhFXvffeewwbNoyvvvqqxrZ8r01aiCoiV1PdokTVUIu4wddff83WrVvp1q0b3bp1c3rOggULmDt3Lk899RSbN2/GYrFwxx13cPLkSTdHK1IzVq5cyaBBg+pEMg1aJyMiP50SahE3GDZsGEeOHGH9+vVOeyEXFxezYMECZs6cycSJE7njjjtYv349hmGwbNkyD0Qs12v9+vXcc889tG3bFovFwi233MKaNWuqnLd//37uvvtumjVrRtOmTbn11lvZu3evByKufXv27KFbt25MnDiR4OBgAgMD+X//7/9x/PhxT4fmlBaiishPpYRaxA18fK78Ry0tLY38/Hzuv//+yrGgoCCGDRvGtm3bajs8qQFLlizBYrHw/PPPs2nTJgYOHMjo0aN58cUXK8/58ssviY+Pp3nz5qxbt47169czbNgwioqKPBh57Tl58iSrVq3iyy+/ZO3atbz++uvs3buX4cOH443lhhU1++P7dyYyzIKPAZFhFsb371y5zb2IiDNalCjiBTIzM/H19SUqKsphvHv37qxbt85DUcn12Lx5M2FhYZWvBw0axPHjx1myZAmTJk0CynbdGzZsGKtXr648b8iQIW6P1V1M08Q0TTZu3EhoaFm5ROvWrenfvz/bt2/n9tudb4rlSVqIKiI/hWaoRbzAmTNnsFgsVbYyDgkJobCwkNLSUg9FJtfq0mQaIDk5mbS0NA4fPoy/vz+RkZHs2bOHCRMmVJ7z8ssv8/Of/5zQ0FAMw6iyULWuMU2TjBP5rEjNYcG2DPwtwXSN6UGLFi0qz7ntttto3Lix13b6EBH5KZRQi3gJZ4+TKx6L61Fz3WO1WmnSpAldunRh27ZtxMWVLQpftGgRPXv2pFGjRjz55JNkZmYyePBgD0fruopdBl/d+R05uQXYTQhpE8kP+cW8u++YQ4mHaZpXLYMSEalL9DeaiBcICQnh3Llz2Gw2h/G8vDwCAwPx8/PzUGTyU3Xt2pWsrCx++9vfMnDgQHr16gXAli1bGD16NB988AG/+tWv+O6777jttts8HK3rnO0y2DN+ENbvs3l/bxaHfjgHwM6dO7lw4QI9e/b0cMQiIjVHNdQiNcw0TTJPniMtu2wjknCLP/FdQ4mJqH4jkpiYGGw2G9nZ2URHR1eOZ2ZmanvjOujw4cOMHj2apKQkxo4dC4DdbgfA19eX6dOnYxgGAwcOJDMzk9dee82D0dYMZ7sM/sfQkaT+/S3+77nJ+Fkn8R8dAnnqqae444476sUPESIiFTRDLVKDnD32zskt4JWd31V57H2p+Ph4goODWb9+feVYYWEhmzdvJjEx0V3hy3W4vF54RWoOGSfysVqtJCYm0qFDB1avXo3NZqOwsJDTp08DcM899zj8YDVo0CC+/fZbT91GjXG2y6B/kIXHnn2DoOBm/GXOr3n88ce5/fbbefvttz0UpYhI7dAMtUgNuvSxd8VMXYCfL0GFhax8aw1HvmjFsWPHyM/PJzk5GYChQ4cSGBjIjBkzmDt3LiEhIcTExLBkyRLsdntlhwjxHhU/OO3KyiWwsS+BTRqRk1vAvpyTfLh4EhdKS9myZQtBQUH4+/tTUlJSee0jjzxS5b3qQz1xuMWfnNwCAvwcF9aGt+3IfU+/pF0GRaTGXcsuxO6ihFqkBjl77A1QmH+aLX+azpZLxu677z4AcnJy6NSpEzNmzMButzN//nysVitxcXF88MEHtGrVyo13INfC2Q9OjX1MNsyfyfc537JhWwotW7YEynqMFxYWkpaWxowZM3j66acdnjqkpKQQHR3Nnj17PHIvNSW+aygHjp8lxG46/P7XLoMiUlsqdiHu27evx7thKaEWqUHOHnsDtIhoxx+2HMTHgBmJ3Z1eaxgGs2bNYtasWbUdprjI2Q9OG5bOIfPzHfxsxBM8v/kLUvcf5mftmtExNJDevXtz22238dVXX/G3v/2NKVOmMGTIEDZs2MDOnTt5/fXX63xCXbHLYGpWLkHls/aFJRc5X2rTLoMiUiuGDRtGUlISACNGjCA3N9djsSihFqlB1T32BigsuUhkmMUDUUlNu/wHJ9M0OfD5LgD+mfwCAB9ccv53331HZGQkM2fO5G9/+xt//etfefHFF4mOjiY5OZlu3bq5M/xaUbHLYI82wezOKluQGxlmoV9UKNGtql+QKyLyU3lTuZwSapEapMfeDcPlPzjlFpTSb9Zagv0bUXTBRkhgY2I7hGC3mxzNK6IkoOz/++7duyv/26VLl8r3O3DggPtvohZol0ERaaiUUIvUID32bhgu/8Hp6JlC/HzLZkou2EzatwjkL0+Po1tsPIGtOvLK0X/SNP9bFi9ezMiRIyuT6fT0dA4fPsyRI0cA2LFjB7m5uXTq1KlyIxgREfF+SqhFapAeezcMl//gdLboAhdtNvJtdjq0CCTM0pgO3W7i8/ff5fQPR/HxbUT3bl2ZP3++w9bjy5Yt44033qh8PWfOHADGjBnDqlWr3HxXIiLyUxnV9cWtK+Li4sz09HRPhyEiXio5OZklS5Zw6NAhzp8/T8eOHXnooYeYPn06jRs3BqBTp07861//criuVatWnDx5str3NU2TQz+cY3eWlQ8zT1J6wU5M62DCLI2Bf//gZC0oUcs4EREXXW3TtIpFibXdNs8wjL2maVZ5hKgZahGp16xWKwMHDmTatGk0b96czz77jDlz5nDy5EmWLVtWed7o0aMden5XJNvVubReOL5rKK/s/I4WgY7JtGrnRURcV13v/wPHz5IQFcbw2LaeDlEJtYjUb+PHj3d4PXDgQPLz83nppZd48cUXK8twWrduTd++fX/SZ6h2XkSk9lS3aVqI3SQ1K5cebTy/ENp7+o2IiLhJaGhojW4CUFE7P75/ZyLDLPgYEBlmYXz/zgyPbava+Xpm/fr13HPPPbRt2xaLxcItt9zCmjVrHM7p1KkThmE4fEVERHgoYpG6rbpN0y6WFvN9egovvPoWx44d49SpUyQnJ5OcnExhYaFbY9QMtYg0CDabjZKSEr744guWLl3KY4895pDorly5kqVLlxIQEMCdd97J4sWL6dix4zW/v1rGNRxLliwhMjKS559/nrCwMLZu3cro0aPJzc11KBu63jIiEXGuuk3TCvKsvPPcVIexy3chdhcl1CLSIAQFBVFSUgLAww8/zKJFiyqPJSUl0bdvX9q1a0dGRga/+93vSEhIYP/+/TRr1sxTIYuX2rx5M2FhYZWvBw0axPHjx1myZIlDAu1KGZGI/Ft1m6a1iGjHrHf+6RULv1XyISINQlpaGqmpqSxevJiNGzcyceLEymMvvPACDzzwAAkJCTz66KP84x//4Pjx47z++usejFi81aXJdIXY2Fh+/PFHD0QjUv/Fdw3lfKkNu92xM503LfxWQi0iDUKvXr247bbbePLJJ1m6dCl//vOf+fbbb52ee+ONNxIdHc0XX3zh5iilrkpLS6NHjx4OYytXrqRx48Y0a9aMESNGVGnNKCLXpmLh99G8IqwFJRRdsGEtKOFoXpHXLPxWQi0i9YppmmScyGdFag4LtmWwIjWHjBP5XNpzv1evXkBZjd2VaDGh52RnZzN+/Hh69uyJr68vAwYMcDh+4sQJpk2bRs+ePbFYLLRv354xY8Zw/Phxt8eakpLCxo0befzxxyvHkpKSeOmll0hJSWHRokV88sknJCQkcPbsWbfHJ1LX1YWF36qhFpF641p6lRqGwe7duwGIjHRec3fgwAEOHTpUpeWeuM/XX3/N1q1b6du3r9OOLHv37uXdd9/lkUceoU+fPvzwww/MmTOH+Ph4Dhw4gMVicUuchw8fZvTo0SQlJTF27NjK8RdeeKHy+4SEBOLj47n55pt5/fXXmTx5sltiE6lPvH3htxJqEak3nPUqffN/HyXq5v8gZ18HznzTlu8zvmTx4sWMHDmSLl26sGXLFlavXs3dd99NmzZtyMzMZN68eXTo0MEhQRL3GjZsGElJSQCVO6Bd6rbbbiMzM5NGjf79z1ivXr2Ijo5mw4YNjBkzpsZiqW6HtpaNL5CYmEiHDh1YvXr1Fd9DZUQi9ZsSahGpN5z1Ku3Q7SbSP/g71h+O8n6jRsREdWX+/PlMmDABgPbt2/Pjjz8yefJk8vLyCA0NZciQIfzxj38kONg7Z0IaAh+fK1ckNm/evMpYt27dCAwMrNHFgdU99diXc5IPF0/iQmkpW7ZsISgo6Jrez92Ppo8dO0Z0dDTnz5/n3LlzlTP3eXl5PPnkk/z973+ntLSUhIQEXnzxRbp27erW+ETqCyXUIlJvOOtVmjh2MoljJ1N0wYaPATMSuzsc/9nPfkZKSoo7w5Ra8s9//pPCwsIqiwNd4eypR2Mfkw3zZ/J9zrds2JZCy5Ytr/o+niojmjZtGhaLhfPnzzuMjxw5kgMHDvDCCy/QrFkz5s2bx+23387+/fv1g6TIT6CEWkTqjep6lQIUllwkMsw9dbXifna7nSeeeIKoqCjuuuuuGntfZ089Niz9HZmf7+CucU+Ruv8wIb7/rvGOjY3lww8/9IoyotTUVN577z2efvpppk2bVjn+ySef8P7775OSksKgQYMA6NOnD5GRkbzyyitMnTq1urcUkWoooRaReiO+aygHjp8lxG46JEDe1KtUasfMmTP55JNP2LFjB35+fjX2vs6eehz6omxR6/srFvL+Cph/ybGcnByvKCOy2WxMmjSJ2bNnVymP+fLLL2nUqBH9+/evHGvVqhU/+9nP2LJlixJqkZ9ACbWI1BsVvUpTs3IJKq93LSy5yPlSm9f0KnVm/fr1vPXWW+zdu5ezZ88SHR3N1KlTeeCBB4CyFnFLlizh/fff59tvvyUkJIRBgwYxf/582rRp4+HoXVfdor+YiKbXVHP88ssvs2jRItasWUOfPn1qNDZnTz2eeWs7ANaCkmp3aPN0GdHy5cspLi7m8ccf569//avDseLiYho1aoSvr+OTnCZNmpCRkeHOMEXqDSXUIlJvVPQq7dEmmN1ZZclZZJiFflGhRLe6tuTME5YsWUJkZCTPP/88YWFhbN26ldGjR5Obm8ukSZO8pkVcbbiWVodXsmHDBiZNmsSzzz7LyJEjazy+uvjUw2q18swzz7B69Wqns/Vdu3aluLiY/fv3c9NNNwFQVFTEgQMHOHfunLvDFakXlFCLSL3i7b1Kndm8ebPDdtaDBg3i+PHjLFmyhEmTJrm1RVxNqK6zRKdOnarsFhga3pKHX/yHw6K/AD9fQuwmqVm59GhT/f/Hjz/+mF/84hdMnDix1soU6uJTj1mzZtGnTx+GDh3q9PjgwYOJjIxk/PjxvP766wQHBzNjxgzOnj1bo+UyNaG630sA+/fvZ+bMmaSmpmK32+nevTt//vOfueWWWzwYsTRUXpdQG4YxBHgB8AVeM01zgYdDEhGpVZcm0xViY2PZuHEj4L4WcTWlus4SAKNHj2bSpEmVr7ceOIX9skV/ABdLi/k+PYUXvtnNsWPHyM/PJzk5GYChQ4fyr3/9i3vvvZeYmBhGjhzJp59+WnlteHg4Xbp0qZF78fanHpeXy5Se+p4VK1eyc8cO8vLyACgsLATg7Nmz+Pr6EhAQwNq1a3nggQeIiYkByvp6P/zww2zfvt1Tt+JUdb+XvvzySxISEkhKSmLdunUAfP755xQVFXkiTBHvSqgNw/AFXgLuBI4CnxuGsck0zYOejUxExL3S0tKu2P6tNlrE1YTqOktUaN26NX379q18/fGZDOxmldMoyLPyznOOs8733XcfULbwb8+ePZw9e5avvvqKfv36OZw3ZswYVq1a5frNlPPWpx7OymX2H8zk4oULxMfHVzm/Xbt2jBs3jtdee41bb72V7OxsvvnmGxo1akSXLl24++67Hf7feFrF76XHH3+cefPm0bRp08pZ6gkTJjBs2DCHDXWGDBniwWilofOqhBq4Fcg2TfM7AMMw1gJJgBJqEWkwUlJS2LhxIytXrnR6vLZaxLnqSp0lqlNdq8MWEe2Y9c4/q130N3bs2Aa/k6WzHtk/i+tD2MI3OFVQyj03t6ZDiyDee+89Fi5cyNatW+ncuXPl9YZhEB0dDUBWVhYffvghmzdv9si9XO7S30tr1651OHbw4EH27NnD888/76HoRKq68lZU7tcWOHLJ66PlYw4Mw3jUMIx0wzDST5065bbgRERq2+HDhxk9ejRJSUnVJowVLeLeeustr6p5vbSzRHVWrlxJ48aNadasGSNGjKCj/3nOl9qwXzZN7c2L/ryFsx7ZlmYt6Bbbl5jYPlwI78GAAQMqyzoSEhIqE+i5c+eyfv16PvroI5YuXUp8fDyjRo3izjvv9Mi9XK7i91LPnj3Zv3+/w7E9e/YAcObMGXr27Fk5w75ixQpPhCoCeN8MtbNitCoPA03TfAV4BSAuLs7Jw0IREe9VXZu4lo0vkJiYSIcOHRweZV+qNlvEueJqnSUAkpKS6Nu3L+3atSMjI4Pf/e53fPZfQ/nDW+/xxcmiOrPoz1s465FdIbBJI04VFFd7rdVqZfLkyeTm5tK+fXumTp3KlClTaivU61Lxe+mNN97gN7/5DUlJSaxZs6by+MmTJwF4+OGHmT59Or179yY5OZlHHnmE1q1bV7sYU6Q2eVtCfRRof8nrdsBxD8UiIlLjqmsTty/nJB8unsSF0lK2bNlCUFBQlWtru0WcK67WWQLghRdeqPw+ISGB+Ph4br75ZnK/+AfjHxjnlYv+vNm17gzqrDzmT3/6E3/605/cEOX1q/i99P3331NcXMztt9/ukFDb7XYAHnnkEaZPnw7AwIEDycjIYP78+UqoxSO8LaH+HIgyDCMSOAaMAkZ7NiQRkZrjrO61sY/Jhvkz+T7nWzZsS6Fly5ZVrnNHi7if6uuvv2blypXs3Lnzip0lLnfjjTcSHR3Nvn37+M1vvG/Rn7eriz2yL1ddl5LNmzYxatQoXnnlFXJzcyvPLyoqokWLFkBZEn2pQYMGqa5aPMarEmrTNC8ahjER+AdlbfNWmqb5tYfDEhGpMc7qXjcs/R2Zn+/grnFPkbr/MCG+pZXHYmNj+e6779zSIu5aXZ4EHd23iwsXLvAf//EfVc69tLNEdTQL/dPUxR7Zl7pSl5LExESAKk9ipk6dyi9/+ctq38/Hx9uWhklD4VUJNYBpmluBrZ6OQ0SkNjirez30xW4A3l+xkPdXwPxLjrm7RdzVOEuCGrftzn898yo/a9eMhKgwDMOotrPEpQ4cOMChQ4cYP3682+KvT7y9R/bVOD6tgdyCUoyIGHo9OJMv/raQx2bMI7HvjaSkpFSWC40bN46ePXsSEhJCSkoKgwcPrny/lJQUevbs6anbkQbO6xJqEZH6zFnd6zNvlW2mYS0ocdomzptaxDkrWWnfJoK2Ea04mldE6+6diYkI5vDhw0BZrbTFYmHLli2sXr2au+++mzZt2pCZmcm8efPo0KGD19xbXeStPbKvxb+f1kDGiXN8f7oQP99A/AKbgt3On//4NH++7Jr+/fszbtw4Zs+ezfTp02nevDm9e/dmw4YN7Ny5kx07dnjkXkSUUIuIuFFdr3t1VrIC4ONjENTYl91ZVqfJXfv27fnxxx+ZPHkyeXl5hIaGMmTIEP74xz8SHFz3ksErSU5OZsmSJRw6dIjz58/TsWNHHnroIaZPn07jxo2rnD958mReeOEFpkyZwnPPPeeBiD2j4mlNbkEp358uJNi/EYZhENHtZm57YikArYIDCDn9Na+99CeAyice0dHR2O12XnzxRebMmUN0dDTJyckkJCR48I6kITNMs253nYuLizPT09M9HYaIyDWpKJmoru51eGxbr35Uv2Bb2c6GzjpLFF2w4WPAjMTuHojMe/zlL3/h+++/Jy4ujubNm/PZZ58xZ84cxo0bx7JlyxzOPXjwIH379sUwDP77v/+7QSXUK1JzyMkt4PvThZwpLCWw8b/n+ApLbYQE+tGhRSCRYRZ8v93BL3/5y8qdEkU8xTCMvaZpxl0+rhlqERE3qut1r9faqq0hu7wmfODAgeTn5/PSSy/x4osvOvw//vWvf80TTzzBW2+95e4wPa7iaU1ByQX8fP+9mNA0TS7Y7LRvEVjZTzvCg3GKXAsl1CIiblaX617resmKp4SGhlJaWuowlpycTEZGBhs3bmyQCXVFl5LsHwsovnCBpv5+XLCVJdMdWgQQGtSY0+dLiQyzMDbRe9YRiDijhFpERK5ZXW/V5k42m42SkhK++OILli5dymOPPVY5O11UVMSUKVNYsGCB0018GoKKpzX+fr78+eNvAQgJ9KN9i0BCgxpjmuiHNKkzlFCLiMg1q+slK+4UFBRESUkJULZN9qJFiyqPzZ8/n9atW/Pggw96KjyvYBgGiTdGUHzB5vBD2unzpfohTeoUdUAX8WKrVq3CMIwqX8uXL3d6/uTJkzEMw+t20muoDh48yO23305gYCBt2rRh9uzZ2Gw2T4flsoqSlXEJkcxI7M64hEhiIoKVTF8mLS2N1NRUFi9ezMaNG5k4cSJQ1lv8ueee409/+pN+zfj3D2nj+3cmMsyCjwGRYRbG9+/s9Yt0RSpohlqkDti+fbvD1s3ONso4ePAgK1eurHctyOqqM2fOcMcdd9CjRw82btzIt99+y5QpU7Db7cybN8/T4Ykb9OrVC4DbbruNsLAwxowZw5QpU3j66adJTEwkJiamcqt2u91OSUkJeXl5NGvWrMElkXV5XYEIKKEWqRN69+591VZRDblbgDdavnw5RUVFvPPOOwQHB3PnnXeSn5/PnDlzmD59un7wqScu34Y93OJPfNdQYiIcy18qkuucnBwOHTrEV199xTvvvOPwXsuWLWPZsmUcOXKEdu3aufU+RMQ1KvkQqQcqugXMmDHD06FIuW3btjF48GCHxHnUqFEUFRVpN7d6oqKn+Ks7vyMntwC7CTm5Bbyy8zve3XeMS/d52L27bHv5yMhIXnvtNT766COHr1atWnH//ffz0UcfER4e7qlbEpGfSDPUInVAly5dsFqtdOnShSeffNKhz626BXinzMxMBg0a5DDWoUMHAgMDyczMZNiwYR6KTGqKs23YA/x8SZ45jr0xvclN7Een8Kbs3r2bxYsXM3LkSLp06eL0vfz9/Wnfvj0DBgxw4x2ISE1RQi3ixVq3bs3cuXO59dZbsdlsrFmzhgkTJlBYWMhvfvMbQN0CvNWZM2do3rx5lfGQkBDOnDnj/oCkxlW3DXuH6Jv4cucmfv3OX/Bv7Efnzp2ZP38+EyZM8FCkIlLblFCLeLHBgwczePDgyteJiYmUlJQwb948nnjiCf71r3/x3HPPsX379ga3iKkucPb/xDRN/b+qJ04VFBPYpOo/o4ljJzPgF5Ouaxv2w4cP13B0IuJOqqEWqWNGjBjB6dOnOXz4MDNmzHDoFpCXl+fQLeDSGk6pXaZpknEinxWpOSzYlkGApRlZR36o8v/g7NmzTmeupe4Jt/hTWHLR6bHCkouEW/zdHJGIeIoSahEvcXlCtiI1h4wT+dUmxYZhcOjQId555x1CQkIqv44cOcKyZcsICQnh2LFjbr6LhsnZ4rTmbTrywSdfOCxOO3LkCOfPnycmJsbDEUtNiO8ayvlSG3a7459RbcMu0vCo5EPEC1QkZLuycgks3yksJ7eAA8fPkhAV5rC5wYYNGwgLC6Njx4689tprFBQUOLzXqFGj6N+/P4899pi6BbiJs8VpN/UZwEfrV5Dyz3/Ro01Zf91169YREBBA//79PRyx1ARtwy4iFZRQi3iB6roFbPrdRD7v0J3cn/8nbZo1Yd26daxbt46lS5fi4+NDXFxclfdStwD3c7Y4Lf7uUaRufIttz0/F/8z/EB1UxJw5c3jyySfVg7qe0DbsIlJBCbWIF6iuW0DL9p3Zt2Mjk955BR8DevTowZtvvslDDz3koUjFGWeL0wKbNuOxhatIfvH3LJ3x34S1COE3v/kNc+bM8UyQUiu0w5+IABh1fdFSXFycmZ6e7ukwRFyyYFsGdrNsVvpyRRds19UtQNxvRWoOObkFhFqaVDlmLSghMszCuIRID0QmIiI1yTCMvaZpVnk8rEWJIl5A3QLqNi1OExFp2JRQi3gBJWR1W8XitKN5RVgLSii6YMNaUMLRvCItThMRaQBUQy3iBdQtoG7T4jQRkYZNCbWIF1BCVvdpcZqISMOlhFrESyghExERqZtUQy0iIiIi4gIl1CIiIiIiLlBCLSIiIiLiAiXUIiIiIiIuUEItIiIiIuICJdQiIiIiIi5QQi0iIiIi4gIl1CIiIiIiLlBCLSIiIiLiAiXUIiIiIiIuUEItIiIiIuICJdQiIiIiIi5QQi0iIiIi4gIl1CIiIiIiLlBCLSIiIiLiAiXUIiIiIiIuUEItIiIiIuICJdQiIiIiIi5QQi0iIiIi4gIl1CIiIiIiLlBCLSIiIiLiAiXUIiIiIiIuUEItIiIiIuICJdQiIiIiIi5QQi0iIiIi4gIl1CIiIiIiLlBCLSIiIiLiAiXUIiIiIiIuUEItIiIiIuICJdQiUq8lJycTHx9PaGgo/v7+REdHM2/ePEpLSyvPOXHiBL/85S9p27YtFouF2NhY/vrXv3owahERqUsaeToAEZHaZLVaGThwINOmTaN58+Z89tlnzJkzh5MnT7Js2TLsdjv33HMPVquVZ599loiICJKTk3nwwQcJDAxk+PDhnr4FERHxcoZpmp6OwSVxcXFmenq6p8MQkTpk1qxZvPTSS5w5c4ZDhw7RvXt3Nm3axLBhwyrP6dWrF1FRUaxbt86DkYqIiDcxDGOvaZpxl4+r5ENEGpzQ0NDKko8LFy4A0KxZM4dzmjdvTl2fcBAREfdQQi0iDYLNZqOwsJBdu3axdOlSHnvsMQzD4MYbb6RPnz7Mnj2brKws8vPzWbVqFbt372bChAmeDltEROoA1VCLSIMQFBRESUkJAA8//DCLFi0CwDAMtm3bRlJSEt26dQPAz8+P119/nUGDBnksXhERqTs0Qy0iDUJaWhqpqaksXryYjRs3MnHiRADsdjsPPfQQVquVdevW8dFHHzF58mTGjRvHe++9d8X3XLVqFYZhVPlavnx55TmmafLHP/6R9u3bExAQwH/+53/y5Zdf1uatioiIm2mGWkTqFdM0yTx5jrRsK6cKigm3+BPfNZTY2FgMw+C2224jLCyMMWPGMGXKFL7++mu2bNnCN998Q1RUFAADBgzgyJEjTJ8+nSFDhlz1M7dv305AQEDl686dO1d+v2DBAubOncuiRYuIiYlhyZIl3HHHHRw4cICIiIia/wUQERG3U0ItIvWGaZq8u+8Yu7JyCWzsS2CTRuTkFnDg+FkSosIYHtsWwzDo1asXADk5OWRmZhIYGFiZTFeIjY1l06ZN1/S5vXv3xmKxVBkvLi5mwYIFzJw5s3JG/D/+4z/o1KkTy5YtY968eS7esYiIeAOVfIhIvZF58hy7snJp2zyAUEsTAvx8CbU0oV3zAFKzcjn0wzkAdu/eDUBkZCQdO3aksLCQQ4cOObzX3r176dSpk0vxpKWlkZ+fz/333185FhQUxLBhw9i2bZtL7y0i4k2OHTuGxWLBMAwKCgoA+Pjjj52WxRmGweDBgz0ccc3SDLWI1Btp2VYCG/vi42NUjv3l6XF0i40nsFVHXjn6T5rmf8vixYsZOXIkXbp0oWXLlnTo0IF7772X2bNnEx4ezpYtW3j77bd56aWXrulzu3TpgtVqpUuXLjz55JOMHz8egMzMTHx9favMfnfv3l39rUWkXpk2bRoWi4Xz589XjvXq1YtPPvnE4bzvv/+ekSNHkpiY6O4Qa5USahGpN04VFBPYxPGvtQ7dbuLz99/l9A9H8fFtRPduXZk/f35lS7ymTZuSkpLCzJkzmTJlCvn5+XTp0oXly5fz6KOPXvHzWrduzdy5c7n11lux2WysWbOGCRMmUFhYyG9+8xvOnDmDxWLB19fX4bqQkBAKCwspLS2lcePGNfuLICLiZqmpqbz33ns8/fTTTJs2rXI8ODiYvn37VjnXx8fH4cldfaCEWkTqjXCLPzm5BQT4/TuBTRw7mcSxk7EWlBAZZmFcQmSV67p27cr69euv+/MGDx7s8NgyMTGRkpIS5s2bxxNPPAGUteW7XMWGMc6OiYjUJTabjUmTJjF79myaN29+1fPXrFlD//79adOmTe0H50aqoRaReiO+ayjnS23Y7Y47HNrtJudLbfSLCnXp/U3TJONEPitSc1iwLYMVqTlknMh32FFxxIgRnD59msOHDxMSEsK5c+ew2WwO75OXl0dgYCB+fn5X/Lz169dzzz330LZtWywWC7fccgtr1qxxOOfEiRP88pe/rDwnNjaWv/71ry7dp4jItVq+fDnFxcU8/vjjVz03KyuLffv28cADD7ghMvfSDLWI1BsxEU1JiAojNSuXoPIuH4UlFzlfaiMhKozoVk1/8ntfaweRCoZhEBMTg81mIzs7m+jo6MpjmZmZxMTEXPUzlyxZQmRkJM8//zxhYWFs3bqV0aNHk5uby6RJk7Db7dxzzz1YrVaeffZZIiIiSE5O5sEHHyQwMJDhw4f/5PsVEbkaq9XKM888w+rVq686QQBls9N+fn7813/9lxuicy8l1CJSbxiGwfDYtvRoE8zurLI+1JFhFvpFhRLdqqlLJRaXdhCpWPQY4OdLiN0kNSuXHm2CiYkIZsOGDYSFhdGxY0dat25NcHAw69ev57e//S0AhYWFbN68+ar12QCbN28mLCys8vWgQYM4fvw4S5YsYdKkSXzzzTekp6ezadMmhg0bBsDtt9/Onj17WLt2rRJqEalVs2bNok+fPgwdOvSazl+7di133XUXLVq0qOXI3E8JtYjUK4ZhEBNRltzWJGcdRF7//SQ6RN+EpXVnXj6czpkDO1i3bh1Lly7Fx8cHf39/ZsyYwdy5cwkJCanc2MVutzNp0qSrfualyXSF2NhYNm7cCMCFCxcAaNasmcM5zZs3dyhDERFx1eWbZpWe+p4VK1eyc8cO8vLygLIJA4CzZ8/i6+vrsOHVV199RUZGBrNmzfJE+LVOCbWIyDVw1kGkZbtIPvvHBvJOncQ0TX524w28+eabPPTQQ5XnzJgxA7vdzvz587FarcTFxfHBBx/QqlWrnxRHWloaPXr0AODGG2+kT58+zJ49m1dffZVWrVrxzjvvsHv3bvW5FpEa46zkbf/BTC5euEB8fHyV89u1a8e4ceN47bXXKsfWrl1LQEAASUlJ7gzdbYy6PosRFxdnpqenezoMEannVqTmkJNbQKilSZVjV+ogUpNSUlK48847WblyJWPHjgXgzJkzJCUlkZqaCoCfnx+vv/46v/jFL2o1FmmY1q9fz1tvvcXevXs5e/Ys0dHRTJ06tdpFZpMnT+aFF15gypQpPPfcc26OVmpKxol8Xt35nUPJW8HZ0xz/7htOFZRyz82t6dAiiPfee4+FCxeydetWOnfu7LB2pHPnzvTu3bvO9+A3DGOvaZpxl49rhlpE5BrEdw3lwPGzhNhNh7KPmuogcjWHDx9m9OjRJCUlVSbTdrudhx56CKvVyrp162jZsiVbt25l3LhxhIaGMmTIkFqNSRqeqy2UvdTBgwdZuXIlwcE1W34l7ues5M3SrAXdYvsSWlDChTALAxIiOXz4MAAJCQlYLJbKcz/99FNycnJYsmSJu0N3GyXUIiLXoDY7iFS4vEYx3OJPfNdQWja+QGJiIh06dGD16tWV5//f//0fW7Zs4ZtvvqncjXHAgAEcOXKE6dOnK6GWGne1hbKX+vWvf80TTzzBW2+95e4wpYY5K3mrENikEacKiq94/dq1a2nWrFm92x3xUi71oTYM4z7DML42DMNuGEbcZcdmGoaRbRjGIcMwBl8yfothGPvLjy01ypfdG4bRxDCMdeXjewzD6ORKbCIiNamig8j4/p2JDLPgY0BkmIXx/TtXaZn3U1TUKL668ztycguwm5CTW8BLH3xNv0GDKS0tZcuWLQQFBVVek5mZSWBgYJWtzWNjY/n2229dikfEmeoWyv74448OY8nJyWRkZDBjxgx3hSa1KNziT2HJRafHCksuEm7xB2Ds2LGYpukwOw3wpz/9iby8PJo0qVoyV1+4OkN9APh/wF8uHTQMowcwCrgBaAN8aBhGN9M0bcCfgUeBT4GtwBBgGzAOOGOaZlfDMEYBC4GRLsYnIlJjaquDCDhvy9fYx2TD/Jl8n/MtG7al0LJlS4drOnbsSGFhIYcOHXKoVdy7dy+dOnWq8RhFnLl0oSxAUVERU6ZMYcGCBQ4/AErd5emSt7rApYTaNM0McLp9bhKw1jTNEiDHMIxs4FbDMA4DwaZpflJ+3ZvAvZQl1EnAnPLrk4FlhmEYZl1fNSkicg2c1ShuWPo7Mj/fwV3jniJ1/2FCfEsrj8XGxjJ06FA6dOjAvffey+zZswkPD2fLli28/fbbvPTSS564DWlgUlJS2LhxIytXrqwcmz9/Pq1bt+bBBx/0YGRSk9xR8lbX1VYNdVvKZqArHC0fu1D+/eXjFdccATBN86JhGGeBUCD38jc3DONRyma56dChQ03HLiLids5qFA99sRuA91cs5P0VMP+SYzk5OXTq1ImUlBRmzpzJlClTyM/Pp0uXLixfvvyaNo4RcYWzhbI5OTk899xzbN++3eUyKPEetblpVn1x1YTaMIwPgQgnh2aZprmxusucjJlXGL/SNVUHTfMV4BUoa5tXTQwiInVGuMWfnNwCAvx8K8eeeWs7cOW2fF27dmX9+vVui1MajuoWycZENOXMmTNOF8rOmDGDxMREYmJiKjf7sNvtlJSUkJeXR7NmzZR81VG1WfJWH1w1oTZN846f8L5HgfaXvG4HHC8fb+dk/NJrjhqG0QhoBpz+CZ8tIlLnqEZRvImzjTxycgs4cPwst7YL4sVpY5wulD106BBfffUV77zzjsP7LVu2jGXLlnHkyBHatWt3+ceJ1Hm1VfKxCfibYRhLKFuUGAV8ZpqmzTCMc4Zh9AX2AA8DL15yzRjgE2AEsF310yLSUKhGUbyJs0WyAX6+BF+4wNOTfsXZf33Dp5+kVVko+9prr1FQUOAwNmrUKPr3789jjz1GeHi42+5BxJ1cSqgNwxhOWUIcDmwxDONL0zQHm6b5tWEYbwMHgYvA4+UdPgAeA1YBAZQtRqzYH3cF8Fb5AsbTlHUJERFpEFSjKN7E2SJZgHeX/Z7D+3Yx6tezOX36NJ9++u/lUrGxscTFVdlADn9/f9q3b8+AAQNqO2wRj3G1y8e7wLvVHPsD8Acn4+nAjU7Gi4H7XIlHRKQuU42ieIvqNvKoWCi7dunvWbv09w7HKhbKijRE2ilRREREHDhbJAtlC2WvtEjWmYrtqEXqM5d2ShQREZH6J75rKOdLbdjtjkuZtEhWxDkl1CIiIuKgYpHs0bwirAUlFF2wYS0o4WhekRbJijihkg8RERFxoEWyItdHCbWIiIhUoUWyItdOJR8iIiIiIi5QQi0iIiJeb/369dxzzz20bdsWi8XCLbfcwpo1ayqPl5aWcv/999O5c2cCAgIIDw8nMTGRvXv3ejBqaSiUUIuIiIjXW7JkCRaLheeff55NmzYxcOBARo8ezYsvlm24bLPZMAyDmTNnsmXLFl599VUKCwsZNGgQ3333nYejl/rOqOu7e8fFxZnp6emeDkNERERqUW5uLmFhYQ5jo0eP5pNPPiEnJ8fpNQUFBYSGhjJ//nyefPJJd4Qp9ZxhGHtN06yyJahmqEVERMTrXZ5MQ9l25z/++GO11wQFBeHv709paWlthiaiLh8iIiJSN6WlpdGjRw+HMdM0sdls5ObmsnjxYnx9fXnggQc8FKE0FJqhFhERkTonJSWFjRs38vjjjzuML1y4ED8/P1q3bs0bb7zB1q1b6dixo4eilIZCCbWIiIjUKYcPH2b06NEkJSUxduxYh2Njx47l888/Z9OmTdxyyy3cfffdHDx40DOBSoOhRYkiIiJSZ5w+fZp+/fphsVj4+OOPCQoKqvbcixcvcsMNN9CnTx/efPNNN0Yp9VV1ixJVQy0iIiJexTRNMk+eIy27bNvzcIs/8V1D6RDsy913301paSlbtmy5YjIN0KhRI2666Sa1zZNap5IPERGRa5Sdnc348ePp2bMnvr6+DBgwoMo5nTp1wjAMh6+IiAj3B1tHmabJu/uO8erO78jJLcBuQk5uAcs/+ob/HHwPWVlZbNu2jZYtW171vYqLi/niiy+IjIx0Q+TSkGmGWkRE5Bp9/fXXbN26lb59+16xFdvo0aOZNGlS5evGjRu7I7x6IfPkOXZl5dK2eQA+PgYAAX6+fPjqXL7YvZ2n5y7k9OnTfPrpp5XXxMbG8s4777Bt2zaGDBlCmzZtOHHiBC+//DInTpxQD2qpdUqoRURErtGwYcNISkoCYMSIEeTm5jo9r3Xr1vTt29edodUbadlWAhv7VibTFb75Ig2APz7zFH98xvGanJwcoqOjWb16NU8++SRnzpyhdevW9OnTh/T0dG644QZ3hS8NlBJqERGRa+Tjo0rJ2naqoJjAJlXTk2fe2k7RBRs+BsxI7F7leKdOndiyZYs7QhSpQn8ziIiI1LCVK1fSuHFjmjVrxogRI/jXv/7l6ZDqjHCLP4UlF50eKyy5SLjF380RiVydZqhFRERqUFJSEn379qVdu3ZkZGTwu9/9joSEBPbv30+zZs08HZ7Xi+8ayoHjZwmxmw5lH3a7yflSG/2iQj0YnYhzSqhFRERq0AsvvFD5fUJCAvHx8dx88828/vrrTJ482XOB1RExEU1JiAojNSuXoMa+BDZpRGHJRc6X2kiICiO6VVNPhyhShRJqERERJ6rrhRwT0RTDMK7+BuVuvPFGoqOj+eKLL2ox2vrDMAyGx7alR5tgdmeV/dpHhlnoFxVKdKvr+7UXcRcl1CIiIpep6IW8KyuXwPJZ0pzcAg4cP0tCVBjDY9te93sqEbx2hmEQExFMTESwp0MRuSZalCgiInKZS3shh1qaEODnS6ilCe2aB5CalcuhH85d83sdOHCAQ4cOccstt9RixCLiSZqhFhERuUx1vZAvlhbzfXoKL3yzm2PHjpGfn09ycjIAQ4cO5aOPPmL16tXcfffdtGnThszMTObNm0eHDh0YO3asB+5ERNxBCbWIiMhlquuFXJBn5Z3npjqM3XfffUDZ5iLt27fnxx9/ZPLkyeTl5REaGsqQIUP44x//SHCwyhdE6isl1CIiIpcJt/iTk1tAgJ+vw3iLiHbMeuefRIZZGJcQ6fTalJQUd4QoIl5ENdQiIiKXie8ayvlSG3a76TCuXsgi4owSahERkctU9EI+mleEtaCEogs2rAUlHM0rUi9kEalCJR8iIiKXUS9kEbkeSqhFREScUC9kEblWKvkQEREREXGBEmoRERERERcooRYRERERcYESahERERERFyihFhERERFxgRJqEREREREXKKEWEREREXGBEmoRERERERcooRYRERERcYESahERERERFyihFhERERFxgRJqEREREREXKKEWEREREXGBEmoRERERERcooRYRERERcYESahERERERFyihFhERERFxgRJqEREREREXKKEWEREREXGBEmoRERERERcooRYRERERcYESahERERERFyihFhERERFxgRJqEREREREXKKEWEREREXGBEmoRERERERcooRYRERERcYESahERL3bs2DEsFguGYVBQUOD0nMmTJ2MYBlOnTnVzdCIiAkqoRUS82rRp07BYLNUeP3jwICtXriQ4ONiNUYmIyKWUUIuIeKnU1FTee++9K848//rXv+aJJ54gJCTEjZGJiMillFCLiHghm83GpEmTmD17NmFhYU7PSU5OJiMjgxkzZrg5OhERuZQSahERL7R8+XKKi4t5/PHHnR4vKipiypQpLFiwgKCgIDdHJyIil2rk6QBERMSR1WrlmWeeYfXq1fj5+Tk9Z/78+bRu3ZoHH3zQzdGJiMjllFCLiHiZWbNm0adPH4YOHer0eE5ODs899xzbt2/HMAw3RyciIpdTQi0i4kGmaZJ58hxp2VZOFRRTeup7Vqxcyc4dO8jLywOgsLAQgLNnz+Lr68uMGTNITEwkJiam8hy73U5JSQl5eXk0a9ZMibaIiBsZpml6OgaXxMXFmenp6Z4OQ0Tkupmmybv7jrErK5fAxr4ENmnEvp3vk7xwcrXXjBs3jvT0dL766qtqzzly5Ajt2rWrhYhFRBo2wzD2mqYZd/m4ZqhFRDwk8+Q5dmXl0rZ5AD4+ZTPKP4vrQ9jCNzhVUMo9N7emQ4sg3nvvPRYuXMjWrVvp3Lkz586dq7LJy6hRo+jfvz+PPfYY4eHhnrgdEZEGSwm1iIiHpGVbCWzsW5lMA1iataBbbF9CC0q4EGZhQEIkhw8fBiAhIaHaTV78/f1p3749AwYMcEPkIiJyKbXNExHxkFMFxQQ2cT6vEdikEacKit0ckYiI/BSaoRYR8ZBwiz85uQUE+PlWOVZYcpHIsLLZ6LFjxzJ27NgrvlfFLLaIiLifZqhFRDwkvmso50tt2O2Oi8PtdpPzpTb6RYV6KDIREbkeSqhFRDwkJqIpCVFhHM0rwlpQQtEFG9aCEo7mFZEQFUZ0q6aeDlFERK6BEmoREQ8xDIPhsW0Z378zkWEWfAyIDLMwvn9nhse2VS/pBmLt2rX06tULi8VC27Ztefjhhzl+/LinwxKR6+BSH2rDMBYBw4BS4Fvgl6Zp5pUfmwmMA2zAr03T/Ef5+C3AKiAA2Ao8YZqmaRhGE+BN4BbACow0TfPw1WJQH2oREamrNm3aRFJSEo8//jjDhw/nxIkT/Pa3v6VFixakp6fj46N5LxFvUlt9qD8AZpqmedEwjIXATOApwzB6AKOAG4A2wIeGYXQzTdMG/Bl4FPiUsoR6CLCNsuT7jGmaXQ3DGAUsBEa6GJ+IiIjX+tvf/kavXr1YtmxZ5VhwcDBJSUkcOnSI7t27ezA6EblWLv3oa5rm+6ZpXix/+SlQsTVXErDWNM0S0zRzgGzgVsMwWgPBpml+YpZNjb8J3HvJNW+Uf58M3G7oeaeIiNRjFy5coFmzZg5jzZs3B8p20hSRuqEmnyX9irKZZoC2wJFLjh0tH2tb/v3l4w7XlCfpZwGnS9wNw3jUMIx0wzDST506VWM3ICIi4k6/+tWvSE1N5c033yQ/P59vvvmG3/72twwcOJAePXp4OjwRuUZXTagNw/jQMIwDTr6SLjlnFnAR+GvFkJO3Mq8wfqVrqg6a5iumacaZphmnLXZFRKSu+vnPf86qVat49NFHadasGdHR0dhsNt555x1PhyYi1+GqCbVpmneYpnmjk6+NAIZhjAHuBn5h/vv51FGg/SVv0w44Xj7ezsm4wzWGYTQCmgGnf/qtiYiIeLePPvqICRMm8MQTT/DRRx+xdu1aTp8+zfDhw7HZbJ4OT0SukUslH4ZhDAGeAu4xTbPwkkObgFGGYTQxDCMSiAI+M03zBHDOMIy+5fXRDwMbL7lmTPn3I4DtpgrIRFyWnZ3N+PHj6dmzJ76+vgwYMMDpefv37+fuu++mWbNmNG3alFtvvZW9e/e6N1iRes40TTJO5LMiNYcF2zIYO34S/e9MZMGCBQwYMICRI0fy97//nY8//piNGzde/Q1FxCu42uVjGdAE+KB8/eCnpmlOME3za8Mw3gYOUlYK8nh5hw+Ax/h327xt/LvuegXwlmEY2ZTNTI9yMTYRAb7++mu2bt1K3759KS0tdXrOl19+SUJCAklJSaxbtw6Azz//nKKiIneGKlKvmabJu/uOsSsrl8DGvgQ2acTxf31Lh1vv5N19xyp7j0dHRxMQEMC3337r6ZBF5Bq5lFCbptn1Csf+APzByXg6cKOT8WLgPlfiEZGqhg0bRlJS2ZKHESNGkJubW+WcCRMmMGzYMFavXl05NmTIELfFKNIQZJ48x66sXNo2D8DHp2zZUItWbSg4+g2pWbn0aBNMTEQwGRkZFBUV0alTJ88GLCLXzNUZahHxclfbGOLgwYPs2bOH559/3k0RiTRMadlWAhv7VibTAPF3j2Lj8vk0CQ7D5/gd9Grpw+9//3s6derE0KFDPRitiFwPbcEk0sDt2bMHgDNnztCzZ08aNWpEly5dWLFihYcjE6lfThUUE9jEcR4r4d6H+X8TZ3N4/6e8OHM806dP5+abbyYlJYWgoCAPRSoi10sz1CIN3MmTJwF4+OGHmT59Or179yY5OZlHHnmE1q1ba5ZMpIaEW/zJyS0gwM+3cswwDPoNG03MwP8iMszCuIRID0YoIj+VEmqRBs5utwPwyCOPMH36dAAGDhxIRkYG8+fPV0ItUkPiu4Zy4PhZQuymQ9mH3W5yvtRGvyine5mJSB2ghFqknjFNk8yT50jLtnKqoJhwiz/xXUOJiWjq9PwWLVoAZUn0pQYNGqS6apEaFBPRlISoMFKzcgkq7/JRWHKR86U2EqLCiG7l/M+oiHg/JdQi9Yiztlw5uQUcOH6WhKgwp9d079692ve62oJGEbl2hmEwPLYtPdoEszur7AfeyDAL/aJCiW7VlPL2syJSBymhFqlHnLXlCvDzJcRukpqVy7niC1WuiY+PJyQkhJSUFAYPHlw5npKSQs+ePd0Wu0hDYBgGMRFl7fFEpP5QQi1Sjzhry1VaXETGZzs4V3yB7MNH8DdLSE5OBmDo0KEEBgYye/Zspk+fTvPmzenduzcbNmxg586d7Nixw1O3IiIiUmcooRapR5y15SrIs/LGvCccxu67r2wPpZycHDp16sTkyZOx2+28+OKLzJkzh+joaJKTk0lISHBb7CIiInWVYZqmp2NwSVxcnJmenu7pMES8worUHHJyCwi1NKlyzFpQorZcIiIiLjAMY69pmnGXj2vFkUg9Et81lPOlNux2xx+U1ZZLRESk9iihFqlHKtpyHc0rwlpQQtEFG9aCEo7mFaktl4iISC1RDbVIPaK2XCIiIu6nhFqknlFbLhEREfdSyYeIiIiIiAuUUIuIiIiIuEAJtYiIiIiIC5RQi4iIiIi4QAm1iIhIA7Jq1SoMw6jytXz5cgBOnDjBtGnT6NmzJxaLhfbt2zNmzBiOHz/u4chFvJe6fIiIiDRA27dvJyAgoPJ1586dAdi7dy/vvvsujzzyCH369OGHH35gzpw5xMfHc+DAASwWi6dCFvFaSqhFREQaoN69eztNjm+77TYyMzNp1OjfKUKvXr2Ijo5mw4YNjBkzxp1hitQJSqhFRESkUvPmzauMdevWjcDAQH788Uf3ByRSB6iGWkREpAHq0qULjRo1Ijo6mr/85S9XPPef//wnhYWF9OjRw03RidQtmqEWERFpQFq3bs3cuXO59dZbsdlsrFmzhgkTJlBYWMhvfvObKufb7XaeeOIJoqKiuOuuuzwQsYj3M0zT9HQMLomLizPT09M9HYaIiEidNXLkSD788ENOnTqFj4/jw+unnnqKF154gR07dtCnTx8PRSjiHQzD2GuaZtzl45qhFhERqcdM0yTz5DnSsq2cKigm3OJPfNdQYiKaYhgGACNGjODtt9/m8OHDld0+AF5++WUWLVrEmjVrlEyLXIESahERkXrKNE3e3XeMXVm5BDb2JbBJI3JyCzhw/CwJUWEMj21bmVQDDt9v2LCBSZMm8eyzzzJy5EhPhC9SZyihFhERqacyT55jV1YubZsH4ONTliwH+PkSYjdJzcqlR5tgYiKC2bBhA2FhYXTs2BGAjz/+mF/84hdMnDiRqVOnevIWROoEJdQiIiL1VFq2lcDGvpXJNMDrv59Eh+ibsLTuzMuH0zlzYAfr1q1j6dKl+Pj4kJGRwb333ktMTAwjR47k008/rbw2PDycLl26eOJWRLyaEmoREZF66lRBMYFNHP+pb9kuks/+sYG8UycxTZOf3XgDb775Jg899BAAe/bs4ezZs3z11Vf069fP4doxY8awatUqd4UvUmeoy4eIiEg9tSI1h5zcAkItTaocsxaUEBlmYVxCpAciE6mbquvyoY1dRERE6qn4rqGcL7VhtztOntntJudLbfSLCvVQZCL1ixJqERGReiomoikJUWEczSvCWlBC0QUb1oISjuYVkRAVRnSrpp4OUaReUA21iIhIPWUYBsNj29KjTTC7s8r6UEeGWegXFfr/27v/4KrrO9/jzzcJPxIDWhMk/FAJEpPiquUafww0U1e3i6DVdS9WdK7iyEyxY51trXevP6bdTulOdXdbt04va7eVC5SuP6r1qgt2t2pli9Af8UcXUJRcQysIygmCRAiR5HP/yIFNIIByQk5+PB8zGc75fL/fk/d3PvM9efE5n/P5UjVqeKdl8iQdPQO1JEn9WERQXd6+PJ6kY8MpH5IkSVIODNSSJElSDgzUkiRJUg4M1JIkSVIODNSSeo2FCxcSEQf93H///fkuTZKkQ3KVD0m9znPPPUdRUdH+5xMmTMhjNZIkHZ6BWlKvc+6551JSUpLvMiRJ+kic8iFJkiTlwEAtqdc57bTTKCwspKqqih/84Af5LkeSpMNyyoekXmP06NHMmzeP8847j9bWVh588EFuuukmdu3axVe+8pV8lydJUpcipZTvGnJSU1OT6urq8l2GpGPk6quv5plnnmHr1q0MGuSHapKk/ImIF1NKNQe2O0ItKW9SSqzbspOV9Y1sbWpmZMkwpkwspbp8OBEBwMyZM3nkkUfYsGGDq31IknolA7WkvEgp8fjLm1ixPkPxkAKKhxbSkGlizds7qK0s48rJY/eHaqDTY0mSehMDtaS8WLdlJyvWZxh7QhGDBrWH5aLBBXyiLfGr9RkmjRlBdfkIHnvsMcrKyjj11FPzXLEkSV0zUEvKi5X1jRQPKdgfpgH+zzdv4ZSqMykZPYH5G+p4b81yHn74Ye677z7nT0uSei0DtaS82NrUTPHQzm9BJ42r4Lf/9hjbt24hpcRZf3IGixcv5rrrrstTlZIkHZmBWlJejCwZRkOmiaLBBfvbLr3xVi698VYam/ZQUVbCnNqKPFYoSdJH42eokvJiysRSPmhppa2t89KdbW2JD1pamVpZmqfKJEn6eAzUkvKiunw4tZVlbNy+m8amPez+sJXGpj1s3L6b2soyqkYNz3eJkiR9JE75kJQXEcGVk8cyacwIXljfvg51RVkJUytLqRo13GXyJEl9hiPUkvImIqguH8Gc2gpun/5J5tRWUF0+wjAt5ai+vp65c+dy9tlnU1BQwIUXXthpe0tLC5///OeZMGECRUVFjBw5kunTp/Piiy/mp2CpjzNQS5LUz6xdu5Zly5Zx+umnc/rppx+0vbW1lYjgjjvuYOnSpfzwhz9k165dXHTRRbz55pt5qFjq2yKldOS9erGamppUV1eX7zIkSeo12tra9q/dPnPmTDKZDM8///xhj2lqaqK0tJRvf/vb3HrrrT1QpdT3RMSLKaWaA9sdoZYkqZ85mhshHXfccQwbNoyWlpZjUJHUv/mlREmSBqiUEq2trWQyGb7zne9QUFDANddck++ypD7HEWpJkgaoe+65h8GDBzN69GgWLVrEsmXLOPXUU/NdltTnGKglSRqgbrjhBn73u9/x5JNPcs4553DZZZfx6quv5rssqc8xUEuSNECVl5dTU1PD5z73OZ566ilKS0u5++67812W1Oc4h1qSpD4spcS6LTtZWd9+g6SRJcOYMrGU6vKPd4OkwsJCzjzzTJfNk46CgVqSpD4qpcTjL29ixfoMxUMKKB5aSEOmiTVv76C2sowrJ4/9yK/V3NzMSy+9xNSpU49hxVL/ZKCWJKmPWrdlJyvWZxh7QhGDBrWPRhcNLuC4XbtY8OMHeeulUWzatIn333+fRx99FIAZM2bwxBNP8PTTT3PJJZcwZswYNm/ezPz589m8ebNrUEtHwUAtSVIftbK+keIhBfvD9D673t/G0n/8a5Z2aLvqqqsAaGhooKqqiiVLlnDrrbfy3nvvMXr0aM4//3zq6uo444wzevAMpP7BQC1JUh+1tamZ4qEH/yk/sXwcf7v0VQYF3D79kwdtHz9+PEuXLj2oXdLRcZUPSZL6qJElw9i1Z2+X23bt2cvIkmE9XJE0MBmoJUnqo6ZMLOWDllba2lKn9ra2xActrUytLM1TZdLAYqCWJKmPqi4fTm1lGRu376axaQ+7P2ylsWkPG7fvprayjKpRw/NdojQgOIdakqQ+KiK4cvJYJo0ZwQvr29ehrigrYWplKVWjPt461JKOnoFakqQ+LCKoLh9BdfmIfJciDVhO+ZAkSZJyYKCWJEmScpBToI6IeRHxnxHxSkT8e0SM6bDtjoioj4jXI2Jah/ZzImJ1dtt9kZ3gFRFDI+LhbPtvImJ8LrVJkiRJPSHXEeq/TymdlVL6FPCvwNcBImISMAs4A7gEmB8RBdlj/gn4AlCZ/bkk2z4HeC+lNBG4F7gnx9okSZKkYy6nQJ1Ser/D0+OAfQthXgE8lFLak1JqAOqB8yJiNDAipbQqpZSAxcBfdDhmUfbxo8DF4deTJUmS1MvlvMpHRPwtcD2wA/jTbPNY4NcddtuYbfsw+/jA9n3HvAWQUtobETuAUiDTxe/8Au2j3Jxyyim5noIkSZJ01I44Qh0Rz0TEmi5+rgBIKd2VUjoZ+AnwpX2HdfFS6TDthzvm4MaU/jmlVJNSqhk5cuSRTkGSJEk6Zo44Qp1S+rOP+Fr/AiwF/ob2keeTO2wbB7ydbR/XRTsdjtkYEYXA8cC2j/i7JUmSpLzIdZWPyg5PLwfWZR8/CczKrtxRQfuXD3+bUtoM7IyIC7Lzo68HnuhwzOzs45nAc9l51pLUZ/30pz/l8ssvZ+zYsZSUlHDOOefw4IMPdtpn/vz5XHrppZSWlhIRPP/88/kpVpJ0VHKdQ313RFQBbcAfgJsAUkprI+IR4FVgL3BzSqk1e8wXgYVAEfB09gfgAeDHEVFP+8j0rBxrk6S8++53v0tFRQX33nsvZWVlLFu2jGuvvZZMJsMtt9wCwOLFi4kIpk2bdlDYliT1ftHXB4FrampSXV1dvsuQpC5lMhnKyso6tV177bWsWrWKhoYGANra2hg0aBBr1qzhzDPP5Je//CUXXnhhHqqVJB1ORLyYUqo5sN07JUrSMXRgmAaYPHky77777v7ngwb5VixJfZnv4pLUw1auXMmkSZPyXYYkqZvkvA61JOmje/bZZ3niiSdYsGBBvkuRJHUTR6glqYds2LCBa6+9liuuuIIbbrgh3+VIkrqJgVqSesC2bduYPn06p5xyCkuWLMl3OZKkbuSUD0nqRikl1m3Zycr6RrY2NTOyZBiTxxTxpev+kpaWFpYuXcpxxx2X7zIlSd3IEWpJ6iYpJR5/eRM//I83acg00Zbg/72znf9+1VWsfe11li1bxkknndRtv6++vp65c+dy9tlnU1BQ0OVSe9u3b+fGG2/kxBNPpKSkhOnTp1NfX99tNUiSHKGWpG6zbstOVqzPMPaEIgYNCgCeWnA3G15ewWdm/09ert/Ie++9t3//yZMnM3ToUOrq6tiwYQNvvfUWAMuXLyeTyTB+/Hhqag5a7nS/tWvXsmzZMi644AJaWlq63Ofqq69mzZo1fO973+P444/nW9/6FhdffDGrV69mxIgR3Xj2kjRweWMXSeomD/yqgYZME6UlQ/e3zbvuIt57Z1OX+zc0NDB+/HhuuOEGFi1adND22bNns3DhwkP+vn03hAGYOXMmmUym023LV61axZQpU3j22We56KKLAHjnnXeoqKjgm9/8JrfddttRnKUkDVyHurGLI9SS1E22NjVTPLTz2+rXfvwcALs/bGVQwO3TP3nQcQsXLjxscD6UI90Q5pVXXqGwsJDPfOYz+9tGjRrFWWedxdKlSw3UktRNnEMtSd1kZMkwdu3Z2+W2XXv2MrJkWI/W09zcTGFhIQUFBZ3ahw4dymuvvdajtUhSf2aglqRuMmViKR+0tNLW1nkqXVtb4oOWVqZWlvZoPRMnTqS5uZnVq1fvb9u9ezdr1qxh27ZtPVqLJPVnBmpJ6ibV5cOprSxj4/bdNDbtYfeHrTQ27WHj9t3UVpZRNWp4j9Yzbdo0KioqmDt3Lq+//jqbN2/mpptuYseOHQeNWkuSjp5zqCWpm0QEV04ey6QxI3hhffs61BVlJUytLKVq1HAi4qhfu6v1radMLKW6/NCvO2TIEB566CGuueYaqqurAfj0pz/N9ddfz3PPPXfUtUiSOjNQS1I3igiqy0dQXd59S9LtW996xfoMxUMKKB5aSEOmiTVv76C2sowrJ4895LHnnXce9fX1vPHGGxQWFnLaaadx2WWXccEFF3RbfZI00BmoJamX62p966LBBXyiLfGr9RkmjTl8eI8IqqqqAFi/fj3PPPMMTz311DGvW5IGCgO1JPVyK+sbKR5SsD9M77O3pZk/1j3L9954gU2bNvH+++/z6KOPAjBjxgyKi4uZN28e1dXVlJWVsXr1aubNm8esWbP47Gc/m49TkaR+yUAtSb1cV+tbAzRtb+Rn/9B5LemrrroK+K+bxjQ2NvLlL3+ZTCbDySefzG233cZXv/rVHqlbkgYK75QoSb1cV3dg3KexaQ8VZSXMqa3IQ2WSNLAc6k6JLpsnSb1cb1vfWpLUmYFaknq5jutbN/zhj9x++ae49c+reHNL4/71refPn8+ll15KaWkpEcHzzz+f77IlacAwUEtSL7dvfeu5n5nAbx6+jyFFxQDc+OnxXDl5LBHB4sWL2bZtG9OmTctztZI08BioJakPiAi2rv89619cwd/ceTsAVaNG7L+py8qVK1m1ahV33nlnPsuUpAHJVT4kqQ9obW3llltu4etf/zonnHDCQdsHDXJ8RJLyxXdgSeoD7r//fpqbm7n55pvzXYok6QCOUEtSL9fY2MjXvvY1lixZwuDBg/NdjiTpAI5QS1Ivd9ddd3H++eczY8aMfJciSeqCI9SS1IuklFi3ZScr6xvZ2tRMy9Y/8sCCBfzH8uVs374dgF27dgGwY8cOCgoKKCoqymPFkiQDtST1EiklHn95EyvWZygeUkDx0EJWv7qOvR9+yJQpUw7af9y4ccyZM4cf/ehHeahWkrSPgVqSeol1W3ayYn2GsScUMWhQ+3J4Z9WcT9k9i9ja1MLlnxrNKScex89//nPuueceli1bxoQJE/JctSTJQC1JvcTK+kaKhxTsD9MAJcefyOmTL6C0aQ8flpVwYW0FGzZsAKC2tpaSkhIA6urq2LBhA2+99RYAy5cvJ5PJMH78eGpqanr8XCRpIDFQS1IvsbWpmeKhXb8tFw8tZGtT8yGP/f73v8+iRYv2P//GN74BwOzZs1m4cGF3lilJOkCklPJdQ05qampSXV1dvsuQpJw98KsGGjJNlJYMPWhbY9MeKspKmFNbkYfKJEkAEfFiSumgj/1cNk+SeokpE0v5oKWVtrbOAx1tbYkPWlqZWlmap8okSYdjoJakXqK6fDi1lWVs3L6bxqY97P6wlcamPWzcvpvayjKqRg3Pd4mSpC44h1qSeomI4MrJY5k0ZgQvrG9fh7qirISplaVUjRpORBz5RSRJPc5ALUm9SERQXT6C6vIR+S5FkvQROeVDkiRJyoGBWpIkScqBgVqSJEnKgYFakiRJyoGBWpIkScqBgVqSJEnKgYFakiRJyoGBWpIkScqBgVqSJEnKgYFakiRJyoGBWpIkScqBgVqSJEnKgYFakiRJyoGBWpIkScqBgVqSJEnKgYFakiRJyoGBWpIkScqBgVqSJEnKgYFakiRJyoGBWpIkScqBgVqSJEnKgYFakiRJyoGBWpIkScqBgVqSJEnKQaSU8l1DTiJiK/CHj3FIGZA5RuWoZ9mX/Yd92X/Yl/2Hfdl/2Jfd59SU0sgDG/t8oP64IqIupVST7zqUO/uy/7Av+w/7sv+wL/sP+/LYc8qHJEmSlAMDtSRJkpSDgRio/znfBajb2Jf9h33Zf9iX/Yd92X/Yl8fYgJtDLUmSJHWngThCLUmSJHUbA7UkSZKUg34XqCPiloh4PSLWRsTfdWi/IyLqs9umdWg/JyJWZ7fdFxGRbR8aEQ9n238TEePzcDoDXkTcFhEpIso6tNmXfUhE/H1ErIuI/4yIxyPihA7b7Mt+JCIuyfZlfUTcnu961FlEnBwRv4yI17J/I/8q235iRPwiItZn//1Eh2M+1jWqnhURBRHxckT8a/a5fZkn/SpQR8SfAlcAZ6WUzgD+Ids+CZgFnAFcAsyPiILsYf8EfAGozP5ckm2fA7yXUpoI3Avc01PnoXYRcTLwWeCPHdrsy77nF8CfpJTOAt4A7gD7sr/J9t3/BqYDk4Brsn2s3mMv8NWU0ieBC4Cbs310O/BsSqkSeDb7/GivUfWsvwJe6/DcvsyTfhWogS8Cd6eU9gCklN7Ntl8BPJRS2pNSagDqgfMiYjQwIqW0KrV/O3Mx8BcdjlmUffwocLH/a+tx9wJ/DXT85qx92ceklP49pbQ3+/TXwLjsY/uyfzkPqE8pvZlSagEeor2/1EuklDanlF7KPt5JexAbS+frahGdr7ePe42qh0TEOOBS4Ecdmu3LPOlvgfp0oDb7UfDyiDg32z4WeKvDfhuzbWOzjw9s73RMNgzsAEqPYe3qICIuBzallH5/wCb7sm+7EXg6+9i+7F8O1Z/qhbLTpSYDvwFGpZQ2Q3voBk7K7nY016h6zj/SPujU1qHNvsyTwnwX8HFFxDNAeReb7qL9fD5B+0dZ5wKPRMQEoKsRrHSYdo6wTd3gCH15J/DnXR3WRZt9mWeH68uU0hPZfe6i/SPnn+w7rIv97cu+y77pIyKiBHgM+HJK6f3DfMhzNNeoekBEXAa8m1J6MSIu/CiHdNFmX3ajPheoU0p/dqhtEfFF4GfZjy1+GxFtQBnt/+M6ucOu44C3s+3juminwzEbI6IQOB7Y1l3noUP3ZUScCVQAv8++0Y8DXoqI87Ave6XDXZcAETEbuAy4OP3X4vf2Zf9yqP5ULxIRg2kP0z9JKf0s2/xORIxOKW3OTgHYN13yaK5R9YypwOURMQMYBoyIiCXYl3nT36Z8/F/gIoCIOB0YAmSAJ4FZ2RUCKmifdP/b7MchOyPiguw8zOuBJ7Kv9SQwO/t4JvBchyCgYyiltDqldFJKaXxKaTztF/x/Syltwb7scyLiEuB/AZenlHZ12GRf9i+/AyojoiIihtD+Bagn81yTOsheTw8Ar6WUvtthU8frajadr7ePe42qB6SU7kgpjcv+jZxF+3vh/8C+zJs+N0J9BAuABRGxBmgBZmf/2K6NiEeAV2n/yPnmlFJr9pgvAguBItrndu6b3/kA8OOIqKd9BGxWj52FDimlZF/2Pd8HhgK/yH7i8OuU0k32Zf+SUtobEV8C/g0oABaklNbmuSx1NhW4DlgdEa9k2+4E7qZ9iuQc2ldVugqO+v1W+WVf5om3HpckSZJy0N+mfEiSJEk9ykAtSZIk5cBALUmSJOXAQC1JkiTlwEAtSZIk5cBALUmSJOXAQC1JkiTl4P8DQCNg/5TPkxAAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 864x864 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "utils.plot_reduced_data(Xred2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If two points end up being close to each other in this representation, it is expected that the original pictures should be similar as well. \n",
+    "Let's see if this is true. Consider for example the images 19, 21 and 41, which appear close to each other on the top center of the plot. Plot the corresponding cat images vertfy that they correspond to similar cats. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 0.98, 'Similar cats')"
+      ]
+     },
+     "execution_count": 98,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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Na17T2HyZzv44GH0M67lp06bGZhuvXbu2sbPnnVjWQw45pNnGF3WWm9fmdl47zpFsPsU2uP3222fcb09ezqYbySOvzaWUD0r6oDRaYWOMeYlI/VP0TeN+iTHGmDky9rNT9iXSGLO02JOXsx2Sjg72ak0sB9pQa/2YpI9J0kEHHVSPPPLIqW3XX399s++BBx7Y2PFtl85p+/btjX3ooYc2Nv/iwr/Y8K8N8VMj/+KSff3IPjv3Ptdmn1f5Vy7+5YJ/LeBfg+IbP/+aef/9bZ7DccPm+JerWFa2If/ykLVpFkrKv9jEevNaHDu0xw3/i9fmV1aG+vCvjuzfE044obFZ9i1btkz9jn85ldovldLoX0/Zf/zLIssSy8qvcvwiE788Z1+p9xKpf4q+afny5c0Kxpx3vS85HJtsD45ljj9+DeO14vkeeuihZhvHLs/NMcGvCr2v5zz2y1/+cmNffvnljX322Wc39jghSqwHj6Wf5LnoY3t/FR/3RTz78p6F8sSyjBs6znOzXr1Qdfrgj370o43NL2W8/x511FGNfdVVVzV2nCPsn+9///uNze3ZH2rp22IfZJEPA/VHkbGfnfbff/8a/1rP9qO/iuOKbcmoFvqM7JmE4yR+KeD9j88ILDd9DMfs3XffPWNZOef5NYRj8Nprr23s008/vbH5daX3xZttQj9Kn8F6977sZ76Qz3yEx2dfs2LZ+NWH5ab/4ZdPPmfzOT2Wbdu2bc02ztvsS1kvoklqxwP766mnnmpsPlezDfkcx+NjO7F/OA5jPXr3oj1ZrfG7kk4qpRxfStlP0i9K+sIenM8YY+YL+ydjzBCxbzLGdJnzl7Na6wullP+PpK9IWi7pP9Va75y3khljzByxfzLGDBH7JmNMxp6ENarW+l8l/dd5Kosxxswb9k/GmCFi32SM6bFHL2dzIcZYMs6TcZ0xpphxm70VzaRRbUUW2x/jerN9SbZUPmN+Y8x3Fu/NmF9uz+LvY12efPLJZhtjdBkvTj0V24Vlj/3FfRlPnC0vvifLxWYx84S6DZb11FNPbeyov8pW+WG8+NFHH93Y1BtdccUVjR3j+3srBEmj8d+MwWeM/jHHHNPYsS7sH+qJYn9lMfCLEbYVx0RP15ItF822pW+jP4n9TL0H/SBXUuMqmxx/9AnRB1CrQn/x4Q+3uXP/8i//srE5Nzgv41Lu1EOuWbOmsemLqLHJdKLRn9BvZasasv9YD+7P/u/5smxlyEx7y+2xzf/0T/+02fapT32qsan3ybS4LGtsl8xfs5zZapssS6w3xxX9IPXnUbe7WFm+fPnIvSJCHxz15dSYsS84r7Mx1xsHmRaOz2XUOHEFYerkeY+LUN907rnnNvZNN93U2KzXeeed19jRl27evLnZdvLJJzc26039Wraib5wPbF+eO/NX4+hvpbZu1JbzGYF8/etfH+ta8f7Fexfb/7777mtspm7h8w39QHz2ylKzcBzyuY0+ndeKz2a8B2fnmok90ZwZY4wxxhhjjJkn/HJmjDHGGGOMMQPAL2fGGGOMMcYYMwAWVHO2fPnyJr6ZceaMT42xm9QkMOaTmgTG5TIOt5dXK8vBxZjgTAfGGPloU3fHWHsey3hVxpr3tF3MzUD9CuuR5Rbq6XCyuOgsB1KmQePYibqyTGPG7Vk9OfbitXkujhXmC1u5cmVjM9cf6x3HNa/FczMHFuPejz/++MY+//zzGzvqkdi+JGoDsnjuxUAppRkH9BfUY1L/1yPLicPxx7Eec8ewX6gX4XbGv1NTQE1H9D/Uo1HLs2nTpsb+4Ac/2Ni/8Ru/0djU/nzrW9+a+v2zP/uz3XJzbDMH16OPPtrYzAkY5yXrQZ9LDSC1WZm+iv4izmnOFeouxrknSqPjMvbJH/7hHzbb2Nf0VRwbvF/wnhvHMcvdy1kqjY553r95f4iakEyDw7GwFNi1a1eTM4z6M/oj9nUkuxezfTPNbBwH2b2Ac62Xr1QafcaI4yybK3fddVdjr1ixorFvvvnmxr7zznbBzDjPWQ5q0M4666zGpraO+inee+M9gnOaz3jsa+r6qJ9i2Xn/ufrqq2fc99Zbb21stiH9EfuPucqif2KOV7Y//S7HYbZmQvQx1DJSh5m1KfO39TRq1HVTJxnnwEuV58wYY4wxxhhjzDzhlzNjjDHGGGOMGQALGtZYSmk+RTP8g6FEMRSCn8MZDpKF6JHe0qZZCB3JlsbshUnyUyxD1Rg6xM+xDAfphVyynA8//HBjs560s1DDcZYXz5bWHzc0sbdUdhZWxv35af7uu+9u7Nh/vaViJenII49s7G3btjU2+59lifViaBdDCvjZn2ODSw0z/OfCCy+c+n3SSSc12/iZP4Y4ZakmFgPLli1r6tgLm5Xa8cvxlC1FnYUP0zfFMCPOG4ZbcPxlYdL0ATE8h+W49957G5sh2ffff39j/6t/9a+614rhOrfffnuz7corr2xsjm2GoTAUkX4yXvuUU05ptjH05sYbb2xshgNzLJx++umNvX79+saO4WgxfYAkHXfccY3NEBjW+6//+q8bm2363e9+d8Zjs3A1jkP6JvqAWPYsHQnLSbh/z79n/iZbtnwxUkpp7ksME2XYVuw7hkAylJBzqSfDkEZDuuKzGENjeSz7jv6J/oxlj+GCHHMZDGdmqpBeiDF9AOfpLbfc0ti8B2TPP3G8Z/2TSSfohzlWOK8jWch2Tw4kjbZxLwUKr8U5z3IyXJDPM7xnx7HDdw3Wg+OQz0a8n9CXxnGdpceK/emwRmOMMcYYY4wZOH45M8YYY4wxxpgB4JczY4wxxhhjjBkAC6o5k9oYSy6lyeVJ41K+jAfmMs+EegguYc5Y5u9973tTvxkPTA0S41Wz5WMZCxvjsBmfylhmHvvYY481drYMfLQzjUHv2OnK0lv+PlsaP9P0ZNdmLHvcni3PSzvT1jFuuhdfzDHNGHrGMjN2uaetZP8xZj7TlLDNtm7d2thx6Vou8X/JJZfMWM5Mc7kYKKU07cfxF3VDUhsPn2k1Mz0OlyhnP0ZfRW0V9+VYpd9jPXp9R+0U/TPLzbJxqWPG7e/cuXPqN5eLpj+gVovziDqjY445ZsaycU6yvzZu3NjYnCds8+uuu66xv/SlL81YlhtuuKHZRq0Q25Q6v9tuu62xOU6jb7v88subbVyqOra/NHo/OPvss7vHxz5hG7I/6XOpAWE9eL+P7ZKlyeH2pcCuXbsan8P7BNMeRF0L257tRZ/A7dSRUesT5yr7lf6FPoK6I45/Xisu5U7tW7bkP+cxxyjHXCxbprXKdMWcH9SeR9i3vDa15ux73ue5nW0ebdaLejfWg9upC2P6lDVr1kz95jL9vDa1dJm/Yh/E50BqXvl+QK02r03ot3t6dZ4r3n96a2P4y5kxxhhjjDHGDAC/nBljjDHGGGPMAPDLmTHGGGOMMcYMgAXXnEWy+NYYl8t4YOoXGEdLTQL1Occee2xjxxxPjK3Pch4wppcx3qxnjDNl3DRtxkXzXLSph4jxyYznzrRzPDfjyXu6AMZFE8YHZzkvsu3jwDhftjljttmm8XjmMWObMbac8eSMfe7l08rqnOVW4bWjzpIcddRRjf25z32usWP/UeO3GHnhhRcaH8F5RzvqMjgP2O6Z3pLbe3loMj0Nz03fxHrQB8TxyjkXfaQ06hepD2HuMup84/nvuOOOZht9DecotQ3MRUhdWaw32yTmBpNGtQ29+S+N+jLmI4y5KjnnmOeM16L+J9M3XnDBBVO/mXuJ144aU2k0jxk1ISxbvDa3EfpUjrvMt8Vng2y+LUVqrc1YoI/gfSS2L8cr+4KaMo65Xv4vqW3/++67r7svy53pv9m3UTdGH0BNGccY/RnzHfK5L85rlitrU9aL84N2vIfyXNRDsR68/2Z5tti/0eY85LWzvKz0u8x7FjVo7NuoR5NG+zMbGyxL9Bl89mUb892D9wDCORE1aLzWYYcd1tjxXtZbr8JfzowxxhhjjDFmAPjlzBhjjDHGGGMGgF/OjDHGGGOMMWYALKjmbPny5SP5ASJf//rXGzvG1jIenpomxp9SW8HtzJsT828cf/zxzTbqipi7gbGutHv6KW5jLDJjW0kvt4PUxrSyDbJcZCwLdR+MR459wnMxDjfLJdfLxTFd2eL1slhkjo0sZpvni5pDjmfGSfNcjHVmvbh9nJw93DdrQ9qx7E888USzjTHZMc/gUtB8lFKavmLun14/sf57qg3s6TCyuHvqujjvWDZqVaLWi2OXY5v6Al6bOdeY4yhCPRTbIMvtw3ZgveLxvRyJ0qjPze491HDQr0bdBY+l/2A+Ht6nOA6ZSy5uZ5vyvsZ6UjPIPmC7RS1LlmOK/oPl5rjk+WIbZ2Oaxy4Fli1b1oxD6q14D4v3R86NQw45pLHZzzwX75ecx9FXsp85nun7OAbZd718qDw3tT30T5w7LCvnOZ93ett4Lj6f8No9nzFunjJqytiGnC/UjXGu9rZxrJx66qmNzXvEEUcc0dhRk8jnavYX24FtxjZnu8T7EfelzTlCP81xyjkR+yB794hzgGWO+MuZMcYYY4wxxgwAv5wZY4wxxhhjzADwy5kxxhhjjDHGDIAF1Zzt3r27iXdlbpqeNivTS5FMB8I43Rg3feONNzbbzjnnnMZet25dYzO3R9TjSH2dSKatYLwwY1SzGO3YTr2cClKeW4waFF47xtpm2qlerO10ZWXZelqs7NyZ9optSFatWjX1m9os6myyXH60Gdsc680xm+nRsrx1vfHAuPQVK1Y0dswJsxTynO3atavRUmQ6pF7bZfpIziPG0pM4h5k3huOP8476Emrp6EejvoF5sO69997Gjjm1JOmxxx5r7EwXzPEc4fjLNIBZfrA49plD7cEHH5xxX2n8PHasF/sownsF25z3SN4PLr300sb+whe+MPWbGjPO0ywHHvfv5abkfMm0tNn9uZcnk+ceR5e7WHnta1+rd7zjHVN2dn+M92b2I222H3PCcpxwPsS5yWMz/Xd272DZYj05RqhvojaO5abGiT4k3pupMcvykxJu7z0TZrkMOf4zzXdPj8jj6bvYXxwLLBufE/hsHO9fLAfzQ477XMayxvNT45ppzuiHs3zDcWyxDVnu6MN7dfKXM2OMMcYYY4wZAH45M8YYY4wxxpgB4JczY4wxxhhjjBkAC6o527VrV6PJyXLV9PKB9XIBSaPx8Vm+qRgnyn1vvfXWxo6aI0las2ZNY+/cubNr92L1GQvbi/OXRjUIjIWNdWGdWU/GyjImmBoz5gWJOhHWgxqQLLdTpo8bJ7cU65VpX3guxrLHPmNuIJL1F7U0Pf1KppUjmRajpzFk31NLEHPMUB+0FGDb9eL2OVYzPSxhW/dyFfZ0EdNdm+fiHGZusuiTObY5Xqgxy/Lt9HJfsQ05L3juLFcZ7y2xP9lm7GuWM9POZfei6PtijkRpVI/W05xOB+9NsT95LNuE5V69enVjs57Ux8X+z8rJew31QBwrPT/Ia9HO7pmLkeeff77R5GT5NeP84fMJxyfnGn3Go48+2tg9PWiWc47XGnctgVj2Xp5OSVq7dm1jb9y4sbE5r5l3K45R7ksfkq1pkN33I2wDnnvcfF+ZPjHeUzjvqL1if1G3t3LlysZmTuCYn4/3l6zchPvzeTQezzHL+0dPey2NjmP6s3gt9jU1zjEfX0937S9nxhhjjDHGGDMA0pezUsp/KqU8Ukq5I/zbIaWUK0opmyf/f3DvHMYY81Jg/2SMGSL2TcaYuTKbL2d/Iukn8G8flnRlrfUkSVdO2sYYs9D8ieyfjDHD409k32SMmQOp5qzW+o1SynH453dLumTy9yclXSXpt7JzlVKaWM0YeylJDzzwwMj+L5LFlTNWlnG5jBEl8fyMdWW8KeNsGYvP/DInnHBCY8c43CxnRaYxYewy2zTGj/NajHdlvbk/49yZ+yHCGF+2YZa/LdOU9Mqa5RShzRwmbONTTjmlsZkHL5Lp+LJx2dOJZdqWLC6a9DRnPBfHeGRv5hmaT//Ug20VxyfnaDaWuZ0aD46/OO/oH3o6iemuxX5lXr44prK8h/fcc09jv/Od72zszZs3NzbHSWw3ahu2bdvW2PQXbAe24VFHHdXYUUPAeUHdHbUQ7I8s3w73j/3POcyxwf7h/meffXZjU3N26qmnTv1mjqFjjjmmsakjpR/kfe7AAw9s7KjFZbnp57idNmEfxbGY5czMNDYLxXz6pmeffbbJM8j8hcwRFfNJcW5Qm8P7OvuGmmsSxxH1NVlOtXFz1sW5x37mvOP4Zg4uPqOwTaOPYbn43MU2Zb2pWWObR61pll+Wbcx5mz0r8/heLlWOBd5veK4dO3Y09nHHHdfY8RmfbUQfn+n2WDb2d9TzMi8dn5M5NjItd+/5dZxn1R5z1ZwdUWvdOXmhnZJWJPsbY8xCYf9kjBki9k3GmJSXfLXGUsoHJX1QGn3LNsaYvUX0TcYYMySif+Jf6o0xS5u5vpw9XEpZWWvdWUpZKemRmXastX5M0sck6eCDD67x821cVlOSbrvttsaOn4KzpfKzkL1xQhv4uZXhe9lysQwn4ZKuMbyE4Tu8Fj9ps57cn+E88TNztrQ1P82zDS+66KLG5jKpMfyB/XXNNdc0NtswW86aYUwkljVLo5AthX3eeec19p133tnYMXQsC4FlyFtvGdvpjo/tkoWZ8Vxs02wOxAeALGQytvfeDGucgVn5p+ibSik1jhv2a68tsxBctjuXS8/CbuMcZ58zNIcPcTHlgTTq20hvjDCsjW2SLY9O4nhlvRhWwv6g32Obst5xCXsuZ88QPC4p/+CDD46UPZLN8WjT9xx00EHda/HcDDE7/fTTGzumbeE44n2JoVXsz2xexyXW6XNZTqaTIRy37O8YusWxkkkcBsacnp1e8YpX1N69nH3de5nLjuX9kvszdC32Fecd+yYLOeX+LFvsW56Lc4sh20wpQJ9BPxDvcfSzWXoenoswhUb0ZzzXaaed1ticx+Pcq6bb3ltKn3ON/or9w/DNXgoUPm/y/sLl7Nmf2TNhL1UL7y+8nzDUPXvOi/3N1BMcZzHdQC9Efq5hjV+Q9N7J3++V9FdzPI8xxsw39k/GmCFi32SMSZnNUvp/Lunbkk4ppewopXxA0kckvbWUslnSWydtY4xZUOyfjDFDxL7JGDNXZrNa4y/NsOmyeS6LMcaMhf2TMWaI2DcZY+bKS74gSKTW2sRqcplN2nGpZsbNMgaUscrUVmT6nHh+xqOSLNaVMdvULL3hDW+Y+s16xOVyWS5pNJac9aCOL7bL1q1bm21cXpQxv9Qz8NzUnMX4WcZJX3/99Y3NNsq0MIT9GduJcbzcl9vjssNSvqR0LDv7J1uClW3OenM8xJhtxrFnseTczhjv3vGZDirGjs92adjFRKaF6O27p0t7c5nfuGwzl5yn3o1LPHMsZ3rMOAYYd8+Yf47lO+64o7GpO6ImLbYL4/Qz3VDmL3jt2ObU+b7uda9rbGpqstQc1CuwnWI9Mz0i602f+9WvfrWxmbYl+qpMx8s2Z5v1dF9SO05ZD/qqzCeTbE71zr23ls5/KXnhhRcanRLv+yeddFJjx+esLPUDl+Fn3/H+13v+4fNJby5I+XMdzxf1O9xGn0BNJX0l74d8Por6Ks5xXov9kaUUYJ/ENue5Nm3a1NgsC+c1tVqZvirO6959ThptM7Ypn+F5T4jXpvaXutRx53Ev5Qm1cNQQcil9LstPP8vj47V5D2Z/zvbZaa6aM2OMMcYYY4wx84hfzowxxhhjjDFmAPjlzBhjjDHGGGMGwIJqzpYvX97E4jLXAzUOMVaTcc6ZJiGLs+7lc8jibqkJ4bWoreD5ov7qkksu6ZaL+ogsHwzjrGNZTznllGbbd77zncamvoE5LVjvDRs2NHbUw1CPxnqxrxlfzBhhamPY5nF8ZDnueG62y913393YvfxhjN/OyLQYvXj+bExn+X7GyRWX5dfL5shio5TStG+WoyvOO7ZNpqfJcjTSf8Tt9JmEOiLOhSyXVfQvLCdzKFKrwvF54YUXNjZ1pzFOn/6ip4WbjkwH9thjj039pm6C8FrU4lI/wv6iv+jlEWI9CbUQ1HTceOONjR3rTY0YxxnLwrHDNuxpXXq6Cu47HZnGM9pZLqxx5+NiIfbXk08+2WyjVv2EE06Y+s1nBtrs97vuuquxec+ipiY+02V5srJ5nOX9jH3N+9m4OSBjvllp1AdFfRufs3gttknm43v537JcqNQdR98m5Xkc2W7Rv2XP2ZzXDzzwQGOznficF59PqfEbJ1+kNDo2ej6E+1JHyTY88cQTG5vzi9vjHGAb9bS7PV2dv5wZY4wxxhhjzADwy5kxxhhjjDHGDAC/nBljjDHGGGPMAFhQzdkLL7zQ5GBYu3Zts/3SSy9t7BgzessttzTbGAub5TrJ4tTj9kwfRRgDzP2ZMyHGnH7jG99otr35zW9ubOobqDlhbgfWe9WqVTOWi/kwqCmj5oyag/Xr1zd2bNONGzeqB/UQ1F4wPjyLP47XzvJjsL/YP4wP7+ndGMvMsZNpftjG4+rEIqx3phvr2awXz3XIIYdM/Wb89mKk1jqWNmWcHCzcl2OCMH9YjIenXpLx7Bw/1FdlfjLOu2zs8drUNlAv1fNlmV6S/iDTG1Bvcuyxx079/t73vtfdl3oCasqoTaFfpQ4jlpV6ENqZ3uTBBx9sbPZnnKccKxwLWe4l+miWLepHeCzzW2W54jj3enqibJ4uFY1ZZPfu3c38inooaXS+9LTQ1I5yPnDcZH0Z9W+8bpZjNNNc9nJ1Zjou+ows1xXnedQR8dz04fR9PU3ZdGWP21luzoUzzzyzsZkHjc91measpwelD+Cx9F/UZnGsxRyS7PtM78Y2pG/k8b3ct9maBlzrgW3O42OfccyyP2b7rOovZ8YYY4wxxhgzAPxyZowxxhhjjDEDwC9nxhhjjDHGGDMAFlRzxlxChLGxjL3luSKZxiyLQ48xxCwj47upzXr44Ycbm/Gphx56aGPHGFTqnb773e829sknn9zYd9xxR/fczLEQ43AZ+3rWWWc1NsuyZs2axmZ8MfVu8XjqGWL8tjTaX9RtZBoUnj+ej7HIjFUmjB9mvRjLHM9HHQePzWLRqZ0ZR2OW6SgzXWZP98EY7Ey7tBSIbZ/l2YrjbRw9qzSqV+B2xvnH8cb5zXmUaZhYNu4f5xV9SzY2ea2rr766sVlPajwibG/64J5mY7rtUSfGfamN43b6LrbL/fff39hRjym1vm2cfI3SqJ9jbiBqfOLx9IP0RZzTWU4j9kFsJ44jlov1GGd+SW1/sn+ye8VShOObec9i3/I5iv6np3GV8vaNfc0xw2v38tdNZ/f0V5w7HBccc7zXcl5zvkQ/zPZmPTN/lN2L43Y+j9A/sdynn356Y99+++2NzWcSzuNYFuoL6cu2b9/e2JynzJVLPWP0QWxv+gyem204jg4wyy+Z5Rpl7lu2S7wW25t5BKOv7L2XLL0nLGOMMcYYY4xZhPjlzBhjjDHGGGMGgF/OjDHGGGOMMWYALKjmrNbaxAxv3ry52c68EzGnSxabPN21IuPobXjuLHafeinmwaFGLcbWMl6YMbrMIXXkkUc2Ntusl8uMcbKMD+a5jznmmMbOcl/FOGvmElu5cmW33Cwb838xdxDji2N8MsvJ/svivxkvTm1G7D/qg3juLA8d25D1ijHgPPc4eT6kPC9ML9cfzx21ANlcXCzEemS5YGI/ZXoZ6iYYW88+f+aZZxqb/dy7FqE+gfOOetlYNmpUs5h/2tQn9HTCmWaD9cx0pNTPxnlG30SNRqa1pY+l/qSnUeO5rrrqqsaOucOk0XsJ9SIcW7GPOG6oweF9jHbmX6I2Jsvll+XEy7RJvXMtxbxmpJSS5gSLxPvGEUcc0d2XejXes3g/5f0yjiuWkb4uWwtgHD0u983yZHGMPvTQQ92yzHbbdOXM9u/5N54r5qqVpLe85S2NTY3gtdde29jMjUg/EO8JbEPei6hJY9n4nMZ5HscDxwr7h+OQbdpbd0Bq/Ve2RgV9OKFf7vlO6oJ5H41tyDpE/OXMGGOMMcYYYwaAX86MMcYYY4wxZgD45cwYY4wxxhhjBsCCa85ibCfjU7P41h5Z3iXGnPbi1nmuLCcC96dGiTqPGMNNDQFzj911112NzRw7jIWlniK2N7Vv1LsxtvzAAw9s7Cy/TIyf5bmY+419n+l0TjnllMa++eabGzv2UaaByq6VxbJHnQ63UafBduC1Ml1H1LdwPmT5fLJ8W739M41IrNdSySsU2yeLUe/l1WN7ULvJPqb2gf0Wr0XfQnr9JOX5eqLNMcB5wWMzDVpPh5G1d69NpFHNKnMFRT9JPRq1t5yj1JAxLxRz4vTyc1Lfk+mbqTlmG/L+Ecl01tR0UP+Q9WfsA45plotjh/cp+rZeHiiOacI5wrGwGHnFK16hE044Ycq+8847m+18RonPUty3pzmS8vsfx2C8R2X+h2Mu0/NnevAe9MMs97ga2h7j6h557VgvPuOdd955jX3ZZZc1Nu8fH//4xxt79erVjU2Nbexv1pljo6chk/o51KR2ntOP0s+yrzmWeO1eTlmuDZC9D9CHZznzNm7cOPWbWmtqlKMmjeWK+MuZMcYYY4wxxgwAv5wZY4wxxhhjzABY0LDGXbt2NZ81GRbDT/PRzj5RZyEc/DRP4idVfuLk59beksLT7c8Qjvhpn59Lb7vttsY+44wzGpvtcM455zT2hRde2Njx0y9DgWKYhDT6iZWfjbMwgNgO69ata7ZdccUVjc1P7Vw6n8uREoauxE/aWdhitmw3l6ZlveO4zELask/1WbhWDDng53GGARP2Ty99BO1sifa471JcynqckJZsKXWGejzxxBONnYWFRh/BOdlbZn+6a3MM9MJws3QKhGM78xe9cmVpII477rjG5nLF9A8xrJF+jm3AUHH6Im7n0vv33ntvY8fQRNbjtNNOa2ymlyFs494S0L30D9JoGzOMnWFCJJ6P9zG2Kcct+ztbyjrun/km1nMpsGvXrpGQWG6PxHHCtubzCkO06DMyXxj3z/wTy8kxli2HH+3Mv2T3O8JxNc49IAvhzrbHdmKI9ute97rGZjgg03Pw2WvTpk0zXot2lm6Dx959992N3Qv/l9p7Yy8lgzT63JbdI0icAzxXdn/hnGA73H///Y0dpS7cl2Hv8dq9e7+/nBljjDHGGGPMAPDLmTHGGGOMMcYMAL+cGWOMMcYYY8wAWNDg7N27dzfxzowv7sWrMo4zW9adMBaax8dYWmrfGKPN5WCpBWKM6bZt2xo7xr9Sa8VjuUzq8ccf39innnpqd3vUXlALw/ZmG7F/qOPg9qgjY72opbjhhhsamzG+vBbbhUvrx/NRc8DlYDM4lnqpERiD3UvRII1qK7LlymMcdqaVy+K9M51mD+4bx3BvOdjFQimlaXuO7Z5/4RjgvmwfjgFei/6np6HJtA2ZDqOnK8rGV6YxyzQf4+iIyI4dO7plo5426kjZJvTn1Jhx6f21a9c29s6dO7vbY/9yrFDnxdQpGT0dRuZ72PdZShG2W0+DSH/OOcB7am/pfGm88cGUMbx3LEaef/75RteSzb3Y99z2ve99r7E5/jkO2Jccw7HvMs0Y76UckxwH1L/1tHRZigUyroYpkqX+GJdYFmpaubQ+25jbqee/6qqrGpv9HTVs1LGPqw3NnlHi8XzeJFlaBd4nSRyn42hapdF6UCdO/Wc8f3aPjfXu+VB/OTPGGGOMMcaYAeCXM2OMMcYYY4wZAOnLWSnl6FLKfyulbCyl3FlK+dDkvx9SSrmilLJ58v8HZ+cyxpj5wr7JGDNU7J+MMXNlNpqzFyT941rrTaWUAyTdWEq5QtL7JF1Za/1IKeXDkj4s6bd6J1q2bFkT35rlVIixm4wvZYxvliso2z/GQlMHQHq6IEk68sgjG3vVqlWNHeNwGYPNHBfMg3PSSSc19ooVKxqb8eKM+Y0wrpbaLMYEM/6bseeMZY6cfvrpjb19+/bGZj0JY36pWVi5cuXU75hXSBotN9uc/c2cSb38b4wZzrQTWc41jqU4brkt012Om7clzrEsHj/Way/mOZs331RrbeLGM01HzF2Y5Ujh+KP/4PGcd3E7z805m+U9y3RhPf0IYVmyuP1x8gaRTDvHelE7Ecc2NcJHHHFEY3/nO9/pXpvnZi5KapzivH300UebbVFHNB1Zvs6ebnTc9uf9N+vfaNOvZTpLlqWXb29c9mSczTPz5p+ktl5Z3/bGRZZ7jL6e9/Xetbkv+533bfrZzFfGcdHL0zndubN69sZNdq1xx1xPz8k2oH420wJv2LChsT/+8Y83Nvsoamp57uwekNW7p6emj+Az/jg5OaXRssftvKfy2tm9K3v2ivuzzuzrXk7epkwzbvnbi+6std40+fsZSRslHSXp3ZI+ObnbJyX9VHYuY4yZL+ybjDFDxf7JGDNXxlqtsZRynKRzJF0n6Yha605pwgmVUlbMcMwHJX1Qyv+qa4wxc2FPfZMxxrxU2D8ZY8Zh1guClFJeI+n/kfSPaq1Pz/a4WuvHaq3ra63re0tCG2PMXJgP3/TSlc4Y83LG/skYMy6zelsqpeyrCefyZ7XWz03+88OllJWTf/lZKemRmc8wwe7duxuNRKYTi3Gg/OrGuNxePHx2bqnNW8A4WubsomaJ8fbULL32ta+d8XjGnFKbxXJSm0W9RE//Qq1ET48m9fVPkvT00+19Jl6Lfbt+fXt/ofbitttua2zmCmLcNXN3xFwfPDdjgBkHH3MgSaP1ZB/EuPksfj/LxcLje/HKme4yy82VxVXHsvEPKePkRFtI5ss3TZ5rxm30AbGfqVlkXiyOCfYT52FP+8My0rdQ78QxQ/0rj49+kNoEajnpTzJdBsd6nIesF4/leDzqqKMam7kk2ebx2vTPzPvENqQvYv9ybLCecf8tW7Y029iGGdkfOKNmOdPK8R6a9UHPv3CcUeORac547p6+hNs4X5gDb28yn/4pthGfOdj+sU0y7SDp5aaSRv1CLBf7lc8QWQ5I0ntGZJ2zvLlZvcfVaPfInkf5DBnrwmc6amQzbV2WS5G+MvYnfWOmbxtXexfbgX3by7kpjY4lHh/Xs5DaNs10YIT14phnWWO9s7UAZqvRn81qjUXSf5S0sdb6v4dNX5D03snf75X0V7O6ojHGzAP2TcaYoWL/ZIyZK7P5cnaxpP9e0u2llFsm/+23JX1E0mdKKR+QtE3Sz78kJTTGmOmxbzLGDBX7J2PMnEhfzmqt10ia6VvlZfNbHGOMmR32TcaYoWL/ZIyZKwu6QseyZcu0//77/+3FEfdJTQNjnXmuHowxpc2Y+GgznpSx+rRZTsZCMxdRpKd9k6Szzz67sZknhNdmm8Z6sxy9HCLTbWfsbOxLXouxyYyDvvDCCxubuo+vfe1rjX3OOec0NnUeUXOWxZpzLDAGmMezHWJdsrhnHss+4Fjj2Bkn38+4+cZ68fw8F8sV6zWgvEJzZtmyZd08fb28JtTu9DQZL14rwvGW5RmK0BetWbOmsY877riufdFFFzX2d7/73anf69ata7b90R/9UWNTq7lz584Zyyn14/QJt7Fe1GE8+OCDjc15FvUK1N1R90IdHvuDGo6LL764senLok3/kOmAOUeZBzPmd5Ra35TlnOI4pBaF2joSfUKWn4r1yPSwLHtP05HpQZYCpZSmnmw/3ifivplGL8tlRX1bT++fPUP08stKo/d53nfuuuuuqd/Ulmd5snracSnXf0cyHRGvxf3pB6KPoX/h+M6efflsy/5jm2e5FiPZvZ7npk4sjg/21/HHH9/Yhx12WGPfdNNNM55LGh2X0a+zXJmfzTSzPe0dz8U5EK/dewYbpsrfGGOMMcYYY15m+OXMGGOMMcYYYwaAX86MMcYYY4wxZgAseFboGG/JWEzGp8Y4znHyoEwH424Zdx2vxXIxlpXxxdQBcDtzR/TySfFahx9+eGNTz8DYZerAYuwstRXM58NrsU1ZL8ZsxzhcxvSy/xhv/KY3vamx2S4PPfRQYzPPUdS/MB44iy/OcpPxfDH+mNoXlotx1Gwz5msj8dqZVq6nN5Ry3UcvnryXJ2RcrdsQqbU27cMxQ98U+51twz7e0xxxxx577NRv6oKoGWOOHGqSmEeRc/4v//IvZzzX7/7u7zb27//+7zc2tRHM6dXTYWRj84knnmhs+kH2D+8PcYzSX9PmsWyHY445prGZ7/HrX/96Y8fxwH1ZT/oa9h/bmP1/++23z3iuj3/84439b/7Nv2lsal2oKbzzzjsbO7YT76fjasw433jviZqRTCPFNspyaS0GqIkdR4uc5VXkvZh2T28rtbpJ9ivzk1IndumllzY2/dFnPvOZxo7PR9QF8dr0CQcffHBjU0eUaTJ72zjes5yPvWcSPtPx2TXTyGfX5vyI9/JM/8x5nOn0enlguW3r1q2NHe97kvTzP98uavqlL32pW7ZYdvpdtinLzbGTzZFerr/ec1pvHvvLmTHGGGOMMcYMAL+cGWOMMcYYY8wA8MuZMcYYY4wxxgyABdecxThQxrQzNjPGpzKml/HBjHnPdEa9+FTGm/JcjF0++uiju/sz/0+Mu2ZeM+bYYa4Z5vPh/oxXjrH6Wf4F5txhbgjG5bIP4vYst0rWH+vXr2/se++9t7H/+I//uLHj9TLtFenlkZru+FhWjhXGMp977rmNTe3Mdddd19jUR8S6ZP2XaedIL8dGluMu9udS0JwtX7680dywHzino46Ufc45SZ1Fpgmg9idqnjjnTjrppMbmnKWv2rRpU2N//vOfb+yYH+xf/+t/3Wx7//vf3702fRPrzdxjcfxlGg7eK3pjVxrVBMR22b59e7ON/UftA+vxsz/7s439p3/6p43Ndvnyl7889bundZZG/SbzOVLTumHDhsb+5je/OfWbY/bP//zPG5v9wbFDv8h6RZ984oknzrhNGtWuUC9E7QXLHo9n32Z6nqWgOcs0sb2cXpm/4bHcTh18L5cZj+X9juObeRevv/767v7x2tl9h/Oa97BTTz21sWMONanvn7JnCo5R6lq5Pfpplivrn54GUBqd1/fcc8+MZeHzDK/Nch955JGNzf4mcdxmejb2x8knn9zYfO7esWNHY0edWaYx43zKtMDcv1evbK2AmfCXM2OMMcYYY4wZAH45M8YYY4wxxpgBsKBhjc8991zz6TFb0rwH9+2FQUy3nZ8a4+dyhlwwLGLdunWNzf1XrVrV2PwUHJeB5mdjLm/PsEbyyCOPNDY/x8Z6MUQgazOGUDGcobdUe7YvlxtnGB2XPmUfsI3jMs+sZxbekH2G5v6xrNzGUCGWm2EADENlu8UwKI6VLBQoo7d0fhZyED/NL4Wwxlpr056sP0O8YrgZw0gYusZjszAH9mv0H2vXrm22MZUDbY6Zr3zlK43NMJRYdpYzC4PjMtgMO2GYSpynWVoH9gfrxfAo+s3zzjtv6jdDyTlv6IuYfoBhXj/zMz/T2Ew5EJfDZ4g7z3XKKac0NsOhzjjjjMb+7Gc/29hxLPJewqXzea7TTjutsRlCefbZZzd2bEcey7BG3gNZb/Y37+9xrPSWApfy0KrFSCmlGfOcD6QXApmFePG+Tzj3eL+NsF8Zss2ybN68ubE5huM4oq+jv7ntttsam2Puda97XWPTZ8T0PRxj2fMlwwN5bT4HHHrooVO/3/72t3fP3ZP/SKP3D/ptEn1+b4l4Sfrpn/7pxr766qu7ZWEodGwXhsGzjdkffJZiyDfHTjxfL+xXGj/0l8x2eXxp9u85/nJmjDHGGGOMMQPAL2fGGGOMMcYYMwD8cmaMMcYYY4wxA2BBNWfUdTCOk3G80c7ibMfVLDBOOsZZM+aasc08NzUMXHqZS5dGvRXjUxlPz2Wdv/WtbzU29Q6My43t1tNOTcc4GkBei7HKvBb1KtTpcAnwLK76hBNOmPrN9mfMNpc6Z39nOr64P+vFWPPbb7+9sdm/1Cs+/PDDjR3HKcvJMTxuf40D519Pr7YY2b17dzMGOWYYix91LRzLmR62N54kaf/992/seH7Ob+q8eC0uGx/1rtLovIvzlnoQlivzXfQBhx12WGNHLQTPlWlqeO9gPahtifuzHlHvIUlveMMbGvuss85qbC7pfOuttzY2NclxeXDOI46rXhoFadS/0F9EHQfPzXpzO/0i+59tHs9HDU221Dv7l9finIp+kmOFbdJbfn0xE8cO7zu8j8T5wPahf8r6IkstFNub+9K3UWtOm9dmX8ay8tieplUa1amzzaiPino31oPzmG3IubVixYrGZv/FZ0ympch8Ic9F3Sr9Lp9J4v2I9VyzZk1js1681s0339zYW7ZsmfFavA+yP7O1H6hJo8+IY5H3B9aD45ZkcySen/2RjZ2Z8JczY4wxxhhjjBkAfjkzxhhjjDHGmAHglzNjjDHGGGOMGQALqjnbd999RzQSEcYI92J+Ga/KmHbGlDLmlHHX8fgspwHzRjBX1VNPPdXYjDHt5aNiPRl3S30bNWkxn4/U1oWxsJmOL8vH1Itdp/6E8cJsA9aT13rssccae/Xq1Y3NOOoI46KpSSO9HHhSG9vMbdR1xFwp0mgOHtab9HQG4+biGIdMwxmvtRT0Z7XWxkewXzjWo06J42XcHItZjqeov2RsPGPfmR+Q85D5wHr6g2OPPbZ7LtYjuzbnbNRLcZ7Qf2d5zqgTPeaYYxr7y1/+8tRv5kN64IEHGpvb2cbUqLFszE0W+5/j6oILLmhs+ge2A9uUvm3jxo1Tv+mbmGuJbch6cn/q36L/Yc4ijo1MS0Rfxvt1vC+yDXoaKGlUy7IYKaU0YyF7nonzmGNo3Pt8puGLz0M9jZg0mrfsvvvua2zqozivY99nWiyWk3n6+KwV8xFK7f2WcyG7F9PmmGX/vetd75r6zf7JdKq9tRqmO57autgHfJaNWn5ptM34PJ8998Vxma0Dwf7gPGcuxZ5Wkr4u60+Wjdt5fLw22yjLJzwT/nJmjDHGGGOMMQPAL2fGGGOMMcYYMwD8cmaMMcYYY4wxA2BBNWf77LNPE1PMWGfqKWL8apZPimTxrL04a8anMk6a8abMD0PdEfOkRW0G9SaMT2V+DMb4Mm/Raaed1tgHHXTQ1G/GKmc6vQz2SU+3l2mreC7GZDP2+ZZbbmnsqPPL+jrLYcWcPdTDxJhixmgz3pgx17E/JGnbtm3dskU7qwfJYs/HIdOgLXaWL1/e9CX7keMx2hzrnO/UoGZ5zzhmYp4s+gNqNhinz7lAPRXj9mMb/ORP/mSzLct/xHnC7ZzjUUtHHSh1F/SxnHfsnx07djR2vJfwXGwz5jWjz6X/P//88xv7mmuuaWz2WYR6N85x5mbKcsdFnSBz3HGc9soljWrnmFMt9h/rkfmHTHNMnxx1Yzw3910qec0iu3fvHhl3EfZtbCPOJfo2zkv6DM7jnlYxy8XJa33ta19r7NNPP72xqZGN8zrLPXXuuec2Nv0ydZK9dQiyeyfHJDWvXKfgne98Z2NfeumlM14ru1+wP3ht+jPeM3pjhXOJucXOOOOMxmaOxxtuuKGx4/igL+NzF/3TN77xjcbOdGTx/ByHWZtyO9uh9z7Ccdh7buv5SX85M8YYY4wxxpgB4JczY4wxxhhjjBkAfjkzxhhjjDHGmAGwoJqzWmsTf3nggQc22xmvHOM4GbfJGNIs3w+1Poz1jDHBjC9lPDxzb/Da1Jwxdjaen+XkvtRWsNzM4cKyRc1Clkss05xxf8Z8R90Ht/HaWe6HmEuM555uO/sgsnPnzsZmviVqZRhPTF1H7LNMc8ZyMo8R9UisR4wBz3JvZXHxWf/F7ePkOVsK0DdlOow4h3vzQBodI88880xjZ20Z9Tyco8xzSI0G9SLMcUMNWiwr/RjLzdyDHMucN5yHcfyyDamboJ6A/uPMM89s7HvuuWfGsm3atKnZ9ou/+IuNzfxuzI/EPqD/YB985StfmfpNXQXnO+cZ/QX7hOeLWpYbb7yx2cYxzGPZB7znsk3Xr18/9ftP/uRPutfiGGf/0Zf1NCG852X6kaVCrBf9E9uvN7cyMk0ax0W8Fvs5y0/IvFh33313Y1P3GJ9n6Fc5b3m/pGaS2l7mkO35Zc5b1pO+kbrUmNdMap9J2L7Z/YH70z+dc845jX3//fc3dvStHEdbtmxpbGrMvvvd7zY2fd/rX//6xo46Pz778vnkrrvumrGc0mj/9rRd4z6vZH3QyzfK+39vrvae2ZbWE5YxxhhjjDHGLFLSl7NSyitLKdeXUm4tpdxZSvndyX8/pJRyRSll8+T/D87OZYwx84V9kzFmqNg/GWPmymy+nD0r6dJa69mS1kn6iVLKhZI+LOnKWutJkq6ctI0xZqGwbzLGDBX7J2PMnEg1Z3UiKPJFQda+k/9VSe+WdMnkv39S0lWSfqt3rlJKE4vOOF3GF8fYTGqpqH+gToy5bBiHzu3RpnaCcdHUGDDGl7nGqCOLMaiMT425Y6RRjQHjwZnLhrGyPQ0J981gG7Lssb/YvtQXZno3jg3qDNimhx566NRv5n5jm/Famc16cpxGqDFjfhOO40wvEecL48EzeC62OeOox9GcRXtvaTzm0zdNnm/a39JoP8a2Y+w79TbMk5jlZeppOqj74dj+sz/7s8am1vbtb397YzN2Ppad/Upf8+1vf1s9OLapb4saD84L6tPoF+n/mSeN5+vlObvjjjsa+5JLLmls+i72N89HnUXMz8OxwBxr1FlQJ0O9LMdlvLesWbOm2cZxxnFIjeAnPvGJxma+pE996lMznpu+hTb9JMdxL09pT/8pje8nXyrm+9kpzqdMXxx9CP0J5zXbK9OL9/KbZjnmWBbOHc4Pardi2fhcRn0mz5Xl/eTzURxnnCtsM47J+DwijeaMfOMb39jYsU8yPWamhyY//dM/3dif/vSnG7vXZ3wWZt4y9ifzZvaeDXhu9g/7lz6jd5+U2nZkHbNccvRXvFZPR8ZtvNZsn5dmpTkrpSwvpdwi6RFJV9Rar5N0RK115+TFd0rqZ7Q0xph5xr7JGDNU7J+MMXNhVi9ntdZdtdZ1klZL2lBKOSM5ZIpSygdLKTeUUm7I/qpijDHjMF++KftLtDHGjMt8+adxV1w0xixuxlqtsdb6lCY+wf+EpIdLKSslafL/j8xwzMdqretrreuzpdqNMWYu7KlvWqrLbxtj9j576p+WWuoSY0yfVHNWSjlc0vO11qdKKa+S9BZJfyDpC5LeK+kjk///q+xc++23n4466qgpmw6HMb9RD8GHpxNOOKGxqVFgPCthPHI8P/NnrF27trEvv/zyxr7mmmsam7qBmJtDkg4//PCp31nOFmonGNNLTUkvfpwxvPxakNl8uWYMcIy1Zcw1y8W+zq7NuOoLLrigsT/3uc9N/aZ+gTlJmOeD29mm3B7bkbHI1Ig8/vjjjc0xn+Wrie3A9qdeiOci2QtIbzu3cZzuDebTN0nqajpY39jvjAjgvpwL9E08nvM0jmeOD+YF4higPnLjxo2NzfEY5xnHVzYGWA9qnqhdiZqz6BOlXJdHzSk1Zz39CLVv73//+xub/cX7QaY/uPjii2e8NvdlGzK/G/XNX/ziF2c8t9Rq2LLcn9SrsV48nve5OC5ZL+r0Ml9FXS/HSvSjHIc8F3VMrPdCMd/+KdY7y23V+9KWac6yfJps75gvLMvbx3JRJ8bjWc845jimYg4t7iuNzjXarBefzSKcd8yFSN3q+973vsbuadgyvWYG25i+8Gd+5mcaO2qHmfuN8zjLBUc/zXaK91UeyzbhduqMeZ9kf/Y+BnFcZV+m+TzQmxNZzsbZRunMJgn1SkmfLKUs18SXts/UWr9YSvm2pM+UUj4gaZukn5/VFY0xZn6wbzLGDBX7J2PMnJjNao23STpnmn9/XNJlL0WhjDEmw77JGDNU7J+MMXOlLKQQfvXq1fVDH/rQ314cn7x/9KMfNXYM6bv99tubbfxkmS1Jzs+YDOmIn2/5uZRhMAw9WbduXWPz8/pNN93U2PFTPj+n8lM8Q2pOPvnkxmY9GO5z3nnnTf1m6BDbiGECbFN+ouYn71iX7NzZ8vVZyNR1113X2B/96EenfjMcgWEt/HTPNuQ47C3NnC05zzbjOMzCN2ObshwMAeHYycIce6Gk2af5GCrxxBNP6Pnnn1/Uoq3ly5fXWCfOy164MMOAGEbC8ZgtOz5N2aZ+c3xw3nCss984Dw844IAZr0vfw2tzmWuGObPNjj/++MZmeHHkiCOOaGz6YC7rf8457TMwyx7nPEOOaHNejRuWwu2f+cxnpn7/wR/8QbONIa6nnnpqYzMtCMcK70WbN2+esRwMC+qFUE+3nffF6CfZZtmy/dyf9xKGOUab5eqF5krSY489dmOtdb0WMcuXL6+x/elzeM+KY5b3hSxkm76PNtM/xPsny8H7IX0jxwnHAe+XsQ127NjRvVYWppvdT6PNel100UWNzbDG3/u935ux3NNduycTmOtS7C+SzcW4rD+fs3ktnitL18Nrxe18PmH7Uw7E/uT9h8fH7eMuRsj+oD8ivTQ8vXDNH/3oR9q1a9e0HWqVqTHGGGOMMcYMAL+cGWOMMcYYY8wA8MuZMcYYY4wxxgyA2azWOG8sW7asiZVmLCbjcg8++OCp34xV5hLDjD/lcujUVlCTEHUhjF1lvCmPZYzpiSee2NjUpMU43SxGmzHYrPcdd9zR2NScxTakJoSx6L2l8aXRduH22J9sE+oCMi0MdWEcK2y3uMQr+4v1ZPwxxxbjwXsx3pnOa67LqL5IjPfPzpXp27LlYmO9s7j2WJalkCOslNK0H/uV4zHWn+OFGkaOL45PaoF6y8hTU9ZbqlgaXUqfY5/alajtuueee5pt9GtnnXVWY59++umNfeWVVzb2Kaec0thRe0vN2EknndTYnFe/+Zu/2dhctp/Eewt9B2Gb0Hex/9j/nHc/93M/N/X7yCOPbLYxNQqXq+e5eG3eD2KfbNu2rdnG+yvTyWS6MN5j49jKNGTUznF+UXtHXxfvz5kfXAr+aDriOOT9kvM6jhuOIY5n3heyJeeZLiY+N/DZKLvv9/Rr0qjWdOvWrVO/s9RA9I2cO5nOPfoB6vVZz9/+7d/unpvQn/X0+pmdpSHqzSVJeuc73zn1m/cipijhsWzTww47rLGZ8ir2CTXIrNeWLVsamxpDXovptMZJPcH5Q5+ePRP2fE7WPzPhL2fGGGOMMcYYMwD8cmaMMcYYY4wxA8AvZ8YYY4wxxhgzABZUc7Z8+fImVpex/YxnjXG4jE9lvOkDDzwwcq0IY4QZrxzzxTDHTtRtTWfzXIxvZTxqrBfPxRht6iMY20/dB2P347V4bsY906bOJosfj3G7LCf7mpoD2owXZ1mixkxqNSscC4Tnivn0pFHdHrUZMWY4y2uWkeUW6mnOSKYtyI6P+7NePNdrX/vaqd/si8VIrbUZv5k2K2o+2DaZX8tylbHto3/JdIRZ3rPVq1c39oYNG2Y8PmqlJOmMM85obLYRdb7vec97Gpt6qtgu7373u5tt1K9Rw8R6ss17eS+pAcw0OLQzPS37L/rVt7zlLc22173udY39q7/6q41NTdm3vvWtxmY7xNxx7J9Pf/rTjZ1pPpifk5rkeK9hm3DMZ+OW/p9lyXxXpJeXcrFSSmnaILs3x77vacOl0bZnX/H4Xl7GQw89tLGpjeMY4nNZzMs6XVmitpTaN16LGiS2WTav4/7Uy1LzSv/E8Zrl5ot2pklimxAe38sZKEkf+MAHpn7zWYi6YY4d+nz6YeZtjPo26g05dqg5+/znP9/YvJ8cd9xxjR3zDbPNMn9DehpBqZ/nrJdnrtfX/nJmjDHGGGOMMQPAL2fGGGOMMcYYMwD8cmaMMcYYY4wxA2BBNWe11ibGkrGYvdh9xoQyPpU6Auo6GDPKWOeokWJONOYKyvJMUEfGeNdoZ9oeloUxvVmsbCwb24Rxt8xj0zvXdMfHuOss7p+aNLYx46LZDtTaxXhjxpqzXps3b27sGJssjWoIuT3qQNj+zNMyjlZiuvNF2KacP5lOg9t7GrVMpxB1mcw/sliJ7cuY8l6OHG5ju9If9HKmTXe+OG+j1k8azUsTtbOStHbt2sZ+/etf39jU10Yd0cknn9xsY84aHkv/wDF08cUXN3ach8yhRn/Oc/V8qjTapnF7pgehzWsTal16x/e0m9OVjbow5n3ivIx9wDx1HAtXXHFFY3/ta19rbNajN26p06XWkWOF+pCbb765e+14v2A5OF96mqjFSq21+9xAOz4nUP/He2+Wbza7j0RN9vbt25ttzA9Gzeuxxx7b2MwJS38Wyxb1lZJ09dVXN3aW14zzmvW64IILpn7/8i//crONmtieXk0afW7rPR9x/GY5ugjvCex/Hh/vdczXxv75i7/4i8ZmPahhjm0oSZdddtm015VGn2dWrVrV2LwfMY8jNbLx+ZRjnj470xln94Dec964+WZfZOl5MWOMMcYYY4xZhPjlzBhjjDHGGGMGgF/OjDHGGGOMMWYALKjmjDBelZqoGJvJ+OHsWNrUMDDuNubfYC6OTEOSxbj3zpdpxlhvxrby3EcddVRjxzbM8lExbpqx52yznmaQ2wi3Z/3FOGoS45GZK+XOO+9sbOrCqJd44oknGruXY4l56Jj3g/3F3Cy8Fon929PRTGeTTN8Yz89xxf6I25eCxqOU0ox36ikZcx5j2LMYcupvOJ44L6m/jHOFfo/ah61btzY2Y/7pH1i2OHdi7sDpyPImMq6fvuwf/IN/MPWbGmBqNrKxTk0Bj4/txnnEYzNtJ23Wkzqyno/P5s64+ZLiuKUum7o+bqdvoiatdy0eyzpTH8J8SuzPXj0539h/9MHUIC9GqDnLcmHF9uPcynwb+47jm88FRx555NRvagt53+CYi3mvJOnss89ubNYz3nf4HEYtefbMwHv3+eef39j/5J/8k6nf1NuyTXgujtEsb2vvHsI2yPKZZr6T/R37iGPl13/91xv7zW9+c2Mz99jll1+uHtGfZT6dbUyb9ezplDkWqAHM7j+cM7wHxP7r5TWW+jnRIov/qcoYY4wxxhhjlgB+OTPGGGOMMcaYAeCXM2OMMcYYY4wZAAuuOYvxl4wr78WdM/aeMbyM3WRMKGNIGWMa40RZDubYYgwpy5bFcPf0KrSpX+C5GQvLdoj6KLZ3zGnEcknSYYcd1tjUR7HeMRadMb2Mi465UaTRXBzsH9rMvxHjz1ku6nIyzQjzmjGWPY4PlvuOO+5obPZXL5efNNpHmSYxkmnSqCPrxbmz75lfKWoLOBcXI69+9asbjdV1113XbO/F8bPPermnpNF5xPHI7bGf2Mccm/QXHJ/MSUd9ZtQlcaxmud+y/U855ZTGjjoN6ljY3o8++mhjU0fEvFn0F3Eesg2p+WM92H/s70xvEn1TNv+zNuzpsnm+nk5UGvVNb3/72xubeaSoZ4z3ReajYm7JrI3YJ7Rju7DNeA9829ve1tif/OQntRSIbZZpztgmPXiv5n2Dc5NjMM6fTIN90kkndbfTp3B7HNO8r7///e9vbPpwPnO84x3vaGzqceN8Yb3oV2lz7nE+UOsb7xn0fbw2c8dleqpx8r1lesQzzjijsc8888zG5rMU53FPb8XnUc5zarHZX1xL4PHHH5/6zTajz2eb857MOdGbf9zW02b35qm/nBljjDHGGGPMAPDLmTHGGGOMMcYMAL+cGWOMMcYYY8wAWFDN2T777NPEjTLGlLH8EcaoM8Y306QxdpZxvBHGulIDwpjeLJa/F+PLa7EePDbTqLFssU3ZvtSYMUcJy8K4XGrxYlx1LzeYlOelY7tkcfA9mA/lkksuaewHHnigW1bWM7bLpk2bmm3UZnGMMy6aY4v5guI4Z+w424zxy9w/0zOeeuqpU7+Zb4aakshXvvKVGbctVhg3zjkdtzOmPIvx59geJ38gxxdj5zN/wvxS1AhEn8DxxPFDXQX3z7QPsWycB6zXtdde29g33nhjY3O8XnzxxY0dNWj0JWx/lpN9z3agloXzKl6Pfcv+4pzu3aemOz6OS9Zr1apVjX3XXXc1Nvtvw4YNjU3/H6H2MRvjmW9iO8Q2zHIU3XrrrTOWc7GybNmyZr5RE0xNUxwHHL9sP26nr+c9i+Mk6nl4r6Q2nM8cnDv0bxwX8b7PeUw9G/P6cQxmeUHjtdlGbO+ob5JGfSP9G8d/bEO2CfuLels+C/PeRb0Vcw7G/mb/ZJp5+rOsf+P+9G3sH8LnV9r0u1GLx3HEa9G3Zf6rp0vO9GmzXUfAX86MMcYYY4wxZgD45cwYY4wxxhhjBoBfzowxxhhjjDFmACyo5qyU0sQMM2aUcaG9OE7ajAFlPGumWYrbGSfLmPYsppTxqYzDjdfmNtajlydCGo0JJvF4lpv1YuwyY8sZX9yLc+e5GEue6Ww4FlhP9l+8NtuM52I7UIvB4xnj/e1vf3vqN+OHGWvO+O5M99XLnzKuXmXt2rWNzTwhHHtr1qyZcV9qCWL7Z7Hii4FXvOIVTa6s66+/vtneyz+V6SPHjTnv7c8cfNSeUF/JvDTvfve7G5tjJuYT4xhgP3Osco5m/j3y0EMPNTZ9y9VXX93Y1Dmyf3o51TJNYJZrLPMvrEs8fzZXsrHS02WzLDwX671y5crGpsaMueWOP/74xo5tvH379mYbNWiEeZ4y7WSEOkm26Zvf/ObGvuWWW7plWQzst99+jX9ivkLO4zhGed/gvOU85/2O9zTeL+NzBK+VPa8wjxm1PyxbTwdGv8v7W5bDqwfnDtcZuPLKK7vXzo6P27O8i/QBPDfnB+cm7xknn3zy1G/6MuoNOc6ysdXTQPMZjro96qOztR3Yv3F/5oLjcxefb1hv+sKefjq7X8wWfzkzxhhjjDHGmAEw65ezUsryUsrNpZQvTtqHlFKuKKVsnvz/wdk5jDFmvrFvMsYMEfsmY8xcGCes8UOSNkp6cY30D0u6stb6kVLKhyft3+qdoNbafHrkZ01+KuQn0x78HM5PwYSfhuP+/CzMT6L8BMoQSm7vfX7nZ+JsyWHCT6i9EKvs3PyszHNxf9rxUzHbl/3DkEpeK1sqvxcWyVCKXrisNPo5nGOHYQCXXnrp1O+NGzc222644YbuuXitLVu2NHavvw899NBuubh0MOvJcc3jjzzyyKnfDI/jGI7jdrZLw76E7LFvetWrXtUsx/7Xf/3XzXaGOcTxxj7uLQM+3f602Z4xxQV9C8d2TIcgjc67bOnqOO947t5S6lIe8tILk/7e977XbGN7v/3tb2/sGIojjS6jTf8TfTT7oxduKY3Oo+zewnrfd999U7/Zf1nYYha61UuFwHKzfxg+xf5dvXp1Y3/jG99o7M997nNTvxl+xv7jPTIL56d/j76P/cV0JQyH2svssW+SJu4L995775TNvmQ4WWxP7nvCCSc0NsNweV9gOCu3xzHIMEUupc9l4bnEfLwHSaPzoxdOns0Vhpf1ngF5LYZ28lrnnXdeYzMM+1vf+lZj33HHHY39K7/yK1O/e3WWRufSZz/72ca+8MILG/vcc89t7Le+9a2NHe/19CdsI26nj+FzG31hLHu2TD99AOvNZ0huj+enL7vnnnsam8/4vRQOUv9exjGeyVFmYlZfzkopqyW9U9Inwj+/W9InJ39/UtJPzeqKxhgzT9g3GWOGiH2TMWauzDas8aOS/qmk+Dp5RK11pyRN/n/FdAeWUj5YSrmhlHIDRcDGGLOHfFTz4Jv4l35jjNlDPqo5+iap9U/8QmGMWdqkL2ellMslPVJrvXEuF6i1fqzWur7Wuv7AAw/MDzDGmFkwn76JIRLGGDNX9tQ3Sa1/GkDouDFmAZmN5uxiST9ZSnmHpFdKOrCU8n9LeriUsrLWurOUslJSGui9e/fuJjY601pE/U22NGmmvcqWKI5xoVksMrdTC5TFCMdY6OwvYlkb8XiWLV6LsfksJ2Njs+Xtee0Y65+9iLOc1GIwhp5Ln7JsMZ48W26610bTbWd8cWyHFSvaP3yuW7eusRl/zHoxlpl6iagXoKaMOg/OCV6L2oPDDz98Rpvl4rFxmdpMg/MSMm++aZ999mm0FFHnJY2nae2lzpBG+43nZoRBXAqZ16UWguVmrD3p+QDOA44B1pPn4rzpzTNqU6699trGjrotadT3/Jf/8l8a+/LLL5+x7Jl/pxYian2k0XplKQfe9KY3Tf3mWMiWWe4t2Twd8V7D/qDN/uT94e67725s+vQzzzxz6je1jGwjbqd2hbB/4/LuvAdSA7UX/VFk3nyTNDGmoh6Lf0ziXIypKKgfZttz7nH8UpvIe94FF1ww9ZsaVo5XloWaM/o+1iv6O47fTMvLemX3/djG3MYxSM0Zn2fohy+55JLGjpqnTAPPufRrv/Zrjc3+ef3rX9/YfJaK16Pvy/SdHEs8N+9tsZ70bZzzfMZjf/Fex7EVxxJTT7DcbGOei/WgH4/jg/3H/ohjg/e1pkwzbpmk1vrPaq2ra63HSfpFSV+vtf49SV+Q9N7J3d4r6a+ycxljzHxh32SMGSL2TcaYPWFP/sT0EUlvLaVslvTWSdsYY/Y29k3GmCFi32SMSRlnKX3VWq+SdNXk78clXTb/RTLGmPGwbzLGDBH7JmPMuIz1cranPP/883r44YenbOamYUxpjBHO8i8wVpbxqjyesdAxhjjTeWWaJeZMoPYn6nV4bpaL9cq0c724a8Z3M4420/Xx3FzhLm7P8rOxniwbY5d7ebakto1ZD/YPx0aWy4PbY93YH7FvJWnVqlWNzZhtagdOP/30xo6aNdaLWgD2B7Uw1IwwLj5eizHVrNdSWz1s//331/r166ds5gvbunVrY8fxR81ppvHgeGS/sN9ibH3Wp8xhxLh8jrdeP2Y5a6Ivl0bnKMcrj4/+gvOd9wb61FtvvbWxt23b1tj/7t/9u8aOugzOQY5tbv/EJz7R2FFrJUnnnHNOY2/YsKGxYx+xjahPyHxyljsujktqbHgf4rW4fdOmTY1NDVrU0XAcHnPMMY1N7S3HIX0ZtZTR5/JaHIdnnHGGljpRgyeN+pTYfswhSH9FTTx9zNq1axu7p2Fiv/H5hNeir2Su1Z6eM8uVyvs2nzmy57w4P7gv25vzkGXjfOB4j8dTd06fwXOzP+mfOF/4nBB1ZfQZhPpO1jt7Po3t1stFyXJJ0po1axqbbXrUUUc1dsw5S5/e04xJo/cbHt97f6Cf5LXis25vfYRBKGeNMcYYY4wx5uWOX86MMcYYY4wxZgD45cwYY4wxxhhjBsCCas6WLVvWxJ4zFprx9DHenroNao4yHRHjdkmMlc3ywzDeOMu5xpjTWBfG/TNmlzHcPDdhO8Wy9eKcpzuWbcwcJNwej6eO48EHH2xs9g+1FYw9pwaF8cmx3RhTzbJkmkH2AePN4/YsbxGvzT7gtUmsS5Zf6aCDDmpslpv9RTvGm7M/qBmJ514qCVJjnX7pl36p2ca4/TgX6Fuidk0anVcPPfRQdzvH/k033TT1+zvf+U6zjf3EPqceinoEaiJjWahBynIqcjvnArdH30S/tnLlysZm/kD6TY5B9knUENB3ZPnY2IYnn3xyY5977rnd7bFumf6Qbcb92Sec87FNeS7OYV475tGSpF/4hV9o7I0bNzZ27H/2FzUb1LKwD2JerunKFuvNvqWukj53KZLlwopaLvoIjpnzzz+/sekTmKOL+TFj37LtMx0qteZ83qEdxzR9QE8bLo2vk47Xyu7T2fMn24xtfP/990/9Zr1ILz+pNDrveT/hfT/WjX6Y52I9qVunv+LzUdyfY5bPRvQJPBdt6pbjfZhtQI0ydav0V3z2Zd603toA9Luxv3jeiL+cGWOMMcYYY8wA8MuZMcYYY4wxxgwAv5wZY4wxxhhjzABYUM3Zs88+q3vvvXfKPvroo5vtPf0E82EwVpnwXJlWK8bhcl/GKnM742wzzRrjqHv7UmOQaRQY6xx1fdQMMD6cbcy42yw3Wdyf8cOML37ggQcam/HDWV4Jxs1HTRDPxTZlvdi/1Evw+BhHz/bmvozvZrkZX069XKx3T/sm5WN+HM0ZoaYntjHLtRRgfZnnLPoxahu++MUvNjbjytlenIc9nQV1hsz1Qu3P2972tsamfoTjL/YrdS20M70l4fY4PrmNfo9jlbms2Kacw7EPWGcem+VcYz4d5v4hMS8R65VpoTN9FesS5zCPza5FqCdZsWJFY0cfT3/96KOPNjZ9E+cTNWhspzgf6UNPOeWUxmZ/LQX23XffZtxxzPIZJPY1fQI1kbTpY5hHi+Mizl3eQ+gzCH0fn294P4zjhPonjm+WhTbvjzxfHHM8lvvS5rkzvfjxxx8/9Ztzh3nNTjvttMam5ix7JmFZelpzzstMA9vLu8jtvBbvJ/SrHPPsE14rPhOyjZgPlHkD+Wx73HHHdbfHOXDHHXc02/gsHMvSe+Zaek9VxhhjjDHGGLMI8cuZMcYYY4wxxgwAv5wZY4wxxhhjzABYUM2Z1MZmMk6dcZ0xPwBjWbPYe+pAstjnWC7qHxjrytjmLHZ5HG1Gpm/j9kyzFLdv2bKl2Ub9CevZ01pNt39s4ywHEnU4d911V2NTU5LFF7O/I1l/UuPDcci462hnMfJZjrVMvxjjsnks9+W4y/JM9cYpy53F6y92li9f3miNTj311Gb7m9/85sb+/ve/P/U75qiRRsfmiSee2NgcI+xXxvFHDQ3bnf109913Nzb1IW94wxvUI+aW4fjgGKBmgHOB84xlie3EazE3DP03dTSxPyRp+/btjR3nCn0P5z99KscCNTrsL/qLmEOHYyPL18Y5TK0udWBxjrMcvDbPzf7juGSbR+0E68E2YU5TtnlP0yq1+hPOH+ZDomZwKXDAAQfokksumbLZnszjtHnz5qnfzKvIYzkfqGnifYb58OI4Yr/RP3FeE/Zt776faSqz5zLSy3+aaSLpnx555JHG5vimZimWlZpKPqfxuZlrCRx77LGNzTakhi3WjT6bNvs3a3O2Wy93HNuIzys9fZY0Wq/Y39mzENuMbZ7lwow+iDlROf/i2g70yRF/OTPGGGOMMcaYAeCXM2OMMcYYY4wZAH45M8YYY4wxxpgBsKCas1prE7vJGODvfOc7jR3jVRmbSV0Q4zwZP9zLscNrZXG3WXw8y8r41l7cdJa3LNMksCwxtv/8889vtl177bWNzdhl5j1jbg7WM8aTM+b6hhtuaGzqBKhnYGx6T1MmtTHBbBPGzNPm2GFsM/soxjYzpprtz1hlamM4thg3HWPwqQ3g2KAGiLoOnruX5yzLBRe3c0wuVqJPoFaCuZTe8Y53TP2m5ozazqg5kkbj2dl+HJ+XX3751G/qtjLNIvULHCMcA6x3hHOQ45Fl4RymLinmIuOc5b0hyyXJ+wHHb/Q/mVaT/oB5szhnY44iqa/tzHQWLAs1OMw5Re1LLHtP4zfdtTnGqW1h2aK2i7l8qPvivYe5nDI9bBzH1N2xnpk2ZTHywgsvNPdM+pzbb7+9sWP7sd85nq+77rrGZs6n9evXNzb7No7png5dGp1b7Gfe06jNivcwziXanOfczvs650NsN/o+zkvWi76PbcrnnzhmMw1ylvuQzxjsrx07djR2nD+cO/TxvD+wXVg27h/9PNub9eTY4LMWn29Y9tgOfB5lG7Pc4+r747jnc9a5557b2DG/M3OiNueccYsxxhhjjDHGmAXDL2fGGGOMMcYYMwAWNKzx2Wef1X333dfYEX4Sj59AjznmmGYbQy74yTpbwry3jHAWpsUQjLiksDT6GZl2LBs/xTIMIPts3Fv+VWrrEj+nStIFF1zQ2LFvpNFP7/zETWLYIz+tE/YnQy3i0snSaBgTyxbHDtuEoV1ZKClDv3qhpTw2W7I1C3PkteKn/CycNgvHJJxv8XiGZfRCKJdCWOOyZcua9mQYw+mnn97YmzZtmvrNfli1alVjM6yBYQ8MueCy2DHNBMcXl3W/6KKL1INzuLeUb9avWTgwYZvG/bMl5TOb84j+P/obhsUxpJphQpyzrCf7i9eOPiBLR8KxxDZmG3KexrJl4dy8t9DO+jP6BPYHfSjDgLgcO+cEzxdDg3ksQ1qXWpoPaWLex7Gwbt26ZjvHUfQp9N1sP9576RMYThaX6ZfaMcqwW9qE12I9uAx5vJdzX54rC9nmOOE8j6GL2X3+tttua2yOf7YhrxVD4VkutgHnJVMjMMyXz4T0KXGu9UKXpVF/w3rxePqU+NzOcRnD3KXR5zaWm9fm8dGXcoyzfxhmzf7hcxz9UxyL7B+GwN5zzz1Tv+mTm3POuMUYY4wxxhhjzILhlzNjjDHGGGOMGQB+OTPGGGOMMcaYAbCgmrP9999fGzZsmLIZ98lY2xifz5hPahSyZd7HWao5W66esc7UEbBePS1dtpQsr81YWMYT8/gIY2EZe854YmozGPvMa3PZ28h5553X2CtWrGjsrL8yLV48nuOIY4Wx55nGrNefHJe8NscS96fWgm0a48dZD4673tL405WF4zLCWGgeG8uyVDQeccyxz9lPF1544dRval6of6I+lrHxHI+Mj49LWVMzxmvRn1DDxHnD8dZLWcF9e0sXS6N6E479uH+27D7HGM/Fduktu5xphtn3Dz74YGNzyWf6MpY1piTJ5iTbn/OQ45A+IF6b9aRmgz6W2gjCcRuPp39mGha2EccpdZdMPxG1L6eeemqzjeWmdnqpEP31UUcd1Ww788wzGzuOIy6zz3GRaWZPPPHExu7pCdmvmW41W/6+l56Dc4n7Zkux83mG9MZ3psek/+JS+nxWiv6JqVboV6kxY73oQ9gO7P+omeUzBP1Ldn/h2OC14vMMxwZ9OP0Nz8X7JpfW75WLY4VtzmvzWamX1qj3bCq1Y5x1aq454xZjjDHGGGOMMQuGX86MMcYYY4wxZgD45cwYY4wxxhhjBsCCas723XffJqcMY2UZv8q43QjjVRkTnMXCMmY4xoXyujwXY10Zj8oYeNrxfIw5zTRMrCe3M4Y7xgxTK8FzMb6YMbzczlxjsd2OPfbYZhvbjJqErH+yHD09vRDbiPViXpBe/i+pH/fOcnEssc1ZL86J2GdZTpisv7idOp+4f5avJNq9uOnFRIwbz9ou6sKo5dmxY0djUx+S5Z+j/mb79u1TvzneqL+hXjKb4z3fluXo49hlOxCWLeqnGOPPvDPUWlGzMY7+hGM5tq+Uaxmob2Ybsp2in6T2ir6KbUh/nuV2GicHI8vJNqYP4PFRd8FtvD+zP1kv2tRx8vy9Y5mbaSmwfPnypn843qkTi+192mmnNduYxy/zCZy3HHOxvfmMwWM5Lzn+OffoF6JOjP4nuw9lunbaUevFc1P3lWkmOa/ZX/FezDahv2Hf81rUyLJszHfLZ7EI603/w3nNstGHxLnK9ubzCNdEoN+m7ot+Or5rZGsB0BdyrFA3zmvFunAOxLxmUvs+0Fsjwl/OjDHGGGOMMWYAzOrLWSllq6RnJO2S9EKtdX0p5RBJn5Z0nKStkn6h1vrkS1NMY4wZxb7JGDNU7J+MMXNhnC9nb661rqu1vriu84clXVlrPUnSlZO2McYsNPZNxpihYv9kjBmLPdGcvVvSJZO/PynpKkm/1TuAcdPMg8O4UMacRjKtFsliYWOcKGNfGdPLeFXG7PJajOmOZWUcLWNfs3pmua5ijC/LzVh96p2yfG69fCmMyWVsbabrYzxyL5+P1PYZ24Ax3JnN/u9p2Nim3DcbKzHHyHTEsZTph9h/WQ6Z3jgdJ4dalstmLzC2byIcr/QXsZ/Zp1mePZ6Ldi/vFstF7QPH7kEHHdTYme4o2rwWxwvneJYbhteK8Fq8NzDmn/6CY59jfdu2bVO/WY9eG0ij9cxyqvX0tZwrmW6G/ck27Wm3WA7ea3guXpv7c3vUz7HNOOazfJzUu/XuVVluONZ7gIztn5577rlmDFOHxGelqCtinjLmzco0k9RLUVMTxz99H/uV0D9RL8X7adRPsd9ZD2rrnnyy/TiZ+eE45pjzlbpi9gd1ftmzVLTZ/jyWmkrarCfb6a677mrsqIk+7LDDmm3sP/p41jt7rovjg2sxcJyxHrx3cf/eOOU4os9mf/B+k+XZjM9H9Onsn9gmvVyzs/1yViV9tZRyYynlg5P/dkStdedkQXdKWjHj0cYY89Jg32SMGSr2T8aYsZntl7OLa60PllJWSLqilHL3bC8w6ZA+KI2+lRtjzB4yL76JK1gZY8w8MC/+KfsCZYxZWszqy1mt9cHJ/z8i6fOSNkh6uJSyUpIm///IDMd+rNa6vta6Pltq2RhjxmG+fJP/cGSMmW/myz8xvNUYs7RJv5yVUvaXtKzW+szk77dJ+j1JX5D0Xkkfmfz/X2Xn+sEPfqBrr712ys7yLsUYU8aoM+6cx2Z5DKgTiXG3vFYWV0vdEP/KxbjSXpxpL5+LNBr7muU5i7GxjBdmbCzbiOdiLD/bPMbpsg2ZS4xQx8G4dl67p7/itkwrQ7idf1To5YJifzCGnvVi/D9jn2PZOQ5ZLpaFY4llYyx6HB/cl20YY7g5ThaK+fRNtdam/TJtZ2wf6vGoGaNmNcvJ2NNAsV9iLhep36fS6Jxl3H/sZ8bp9/J3SaNzvpfDRWrbONMA0Ofy3JxHnGdRT8IcWmwz5gXitakhoLaF2pWYC4i+hX6N/ct6cKz19A3s2+w+RB+d6fpizin6AN4DabPNWS+2Q9x+//33N9vuvffexuac2FvMp3/avXt3Mw4zDXa8N3A8Mtcet9PXk949jxoyPofR5rMT72ncHu+BvLey3DfddFNjs8049+hTYi5FPp8wv2SmW2f/kLidc6U3F6TR/qM/4lyjnjfm4eK5e/cHHiuNtin9UxwfLAf3ZTtwbLDNSawL+6+Xt3W6a/OPt7zfbNmyZer3zp07m20c83Ee98bFbMIaj5D0+ckL7CPpP9dav1xK+a6kz5RSPiBpm6Sfn8W5jDFmvrBvMsYMFfsnY8ycSF/Oaq1bJJ09zb8/Lumyl6JQxhiTYd9kjBkq9k/GmLkyTp4zY4wxxhhjjDEvEXuS52xsfvzjH+vuu/92saIY0yuNahhiDCpj9al/oM6DcefUGTB2NuZ+YI6KtWvXNvamTZu65abOI9Ne9PbNdESE+8d2Yp15LcbdMpaZMcGM443bGUvLc1G/wBht6h14PK/NWOlIL0/ZdOdmbHOvXbKcOzx3lmuFfRS1HKwz456phenp16YrexxbHGccV73cNouVXj2oz4nt08vlIo2OJ7Yt+5X9FPen3+M8Iiwb5zznRhy/9GM97aWU59Hr5RXivGGeGZ6bY7+ntZXaerLcLBf7j9diu7Cs1FJEncU4813KtdTUTsftbFNeizbHYaZrivfcqKuTRtuf9aK/znKTxT7I8nAxB9VSYNmyZY0OhnnN7rzzzsaOY5B6GbY9NZWZ5ozjO46zng59unNzjFHjROL84TMecz5yXNCH06fQV8Z1CDjP6MPZxr38g9Mdz7nX2ze737KemTbr+OOPn/Fa7A/OvUz/xnkdy5blA+NYytad4DiO52cbsK+zHL70bz0tHp/xenkw5yPPmTHGGGOMMcaYlxC/nBljjDHGGGPMAPDLmTHGGGOMMcYMgAXVnD3zzDP65je/OeN2xn3GfByM+WV8KmNlGfu6bdu2xr799tsbO8bdHn300c22NWvWNDb1bYRx1izbOBo0xhdnuYRoxzZlTC7jannsuPHGURfAXA+92NrpysZrMWaYMdyx7NyX8dxZ/DjbhXZPH8F6ZnmpMi1dPL4Xvy2NxnBn+kUS46aznHa9cixWYvuwTtTvxDHD2Hf2eZZPJ+unOK8YK5/lmMv0Cb1rs9z0a2wjtgPLRn8Sz8exS5s6L/oeXrunm2GbZMcyLxR9E9uwp53mfYvHZvcWtjnbJfp76rTH0QBOd+6eRo0+l3aWN5D53FjP2N+rV69utjE/G3NtLQVqrc18ogaGYzjqXni/62lgpiPL2RX7KtOS8/6W6Qfpd+O1eN+mFi7T53Ku9eYH24j+J7sW82ZxbkW/zrnRy3spjc4tlo3now+Kfpk+gGOH5Sa9sSG1foHtzXJnOlWOJV4rnp9tQNgmfH7lWON6GTfeeOOM5eJ6FzF3X+9dYGk8VRljjDHGGGPMIscvZ8YYY4wxxhgzABY0rHHZsmXN5+Fjjz222d5bFpghNVw29aGHHmrsM844o7HjsqjS6KfG+Dk9W8KTn88ZgsPPsdzeW4qdn6izZd+zEJsYFsBrZccy1IQ294/hJSx3/JQrjYYx9sLmptuf146fnfl5m+fO2jgLsXzkkUdmvBZDbPg5PCsLwx/ip3y2f7b0dS/0c7prxzCA3jL70tIJZXyRWmszDlhfhmDEtmNbjTv+aHOOx/A09iHDbRhOk4V7c8zEsvfKIY2GuGS+isSxnZWT9wa2Mecox35sJ25jqCjPzTmZhYX1Qk0z/8BzZ6HIDAPrhbFmYYwcWwwj6qVK4L6Zf+C5svtgPB/HAkMoszC9xUpsE85bPpNs2bJl6jf7gmG6HJPZmOvNVc4lzsss1Jb3OBKP5/jN5AnZcum99BusB9s0s3lutkN8TuN9nW3KY7PnT84thpfHdmOb8lmIvpDtQv/DEOPYB9kS/7wWxwaPZ7vEemUpZ5guJZMisI8efvjhGY+96aabGvvcc8+d+t0Lt1xaT1jGGGOMMcYYs0jxy5kxxhhjjDHGDAC/nBljjDHGGGPMAFhQzdkBBxygN77xjVM2l6PkEsTRZixrXPpekjZs2NDY1ENwKX3G6h955JFTv3fs2NFso16NS7Ay/pSxsT3NWS+2XhqNdc2WnGY7xVhmxhr3NAQspzSqK2AbxrLy2Gy5asZJU2PI2FxeO8Ybc1lUxiYzhptlZfwxiWVle2dLfrPemWakt1w160HdJduM+zNGP/ZRph+K4zTTKCwGSindtBNsq0gWO5/Fu3PO99qafdpbano22zkv4xzm2OW5qKUbV5fRW+6ebcpjOUczzWose7ZkM+cJy0k70zzF82fLRxP2D/uf2+P5WC/O6ay/shQwsSxZWo9MDzSOLpPlpr/n9qXAvvvu2zyjcPzz+SaOYT6vUG/PccHxz+cZjuE4BvmMkem6Mv13ryw8NtNJZ+O9p2OnLi/z6RzPLAvrGbdn92lemz6BY4Pnox37jL6M5eS8ztIM9bTbPDc1ZtnzKa/d25/H8jmN5+K9jmsmUEu3atWqGc/FfXva/oi/nBljjDHGGGPMAPDLmTHGGGOMMcYMAL+cGWOMMcYYY8wAWFDN2QsvvNDozBhvyfwlMY7zhBNOaLYxtvnOO+9s7JiLSpIOOeSQxu7lMWAONcYPZ3mMaDNGOMYvM7Y1yxuR6QJ6+TUY+8oYXcI43Z7uhmSx4738StNtz8ZKjJXO9CeMH169enVjc+wwZj/WjfqgrD9Zzyx+PNYl5q6RRvuHeQNZD8bUMy9IL/8e9SuxnEtBc1ZrberY02JJ/dj5np5gunONozulFo70yjmb/WNZszxBbCPaPe3cdOePUIvFc1EbQV+W6fgivJfQt2T9l2nSYrtkbUbYDtyfYy1up1aI+/Y0ZFI/VxzJxnCmZSG8X0ToU1nPpZjn7Lnnnmt0ZZkuMmry16xZ02zL9E+ZZon3uF45ejn/poPjpHc/5fgd99zZ3IvXpgaeUPfIemd5/2Jdsmch+jJei9ottlPvmSPLM5flhKS/6vVRpoHlWMo0yzy+9zzDOcD1L+jP+P7APrn88sunfl9zzTXNtiOOOKKx4/yy5swYY4wxxhhjBo5fzowxxhhjjDFmAPjlzBhjjDHGGGMGwIJqzvbbbz8dffTRUzZjSKPGTGpjfjdv3txsY2ws42yZy4PXYrxrjDGlZunRRx9tbOY9y/LeMEdGLDvjhRnrypjdLHa2l0+M5+7F9Ut5nHQvj06W+yfLgTRufrBeuRijzZjr22+/vbHXrVvX2FdffXVjn3nmmVO/qVfJNCG89pNPPtktaxw75513XrPttttua2zqLtevX9/YzO3R05RwXFGHExlHizhkehqoTNvZg2OA7Z5pH+Lx9AeZfi2jt3+Wgyi7Fucs4/Tj8Vm9eCz9A232V9SkUcdy6KGHNnbWH9RqZj66l9dmXA1aptOIx4+rf+X+bFP6rugv2AY8ltfm9iznVC/XH8dhT1+4WGEexkzTHduEmmk+31Bvw3t3lrM0loVjJNOQ0UewbL3nHfrRXj5ZaXRMcXuvntnzI8d3lqexp/XN8vRluS57uW6l/nMbn9MyHTGfbTNde6wn+zpbhyDTwZNYL2oGeSzHId8nsvkW2+Xtb397s43+afv27VO/ezlS/eXMGGOMMcYYYwaAX86MMcYYY4wxZgD45cwYY4wxxhhjBsCCas723XdfHXnkkVP2YYcd1mxn7HPUyGQ6r3Hz+zA+OcbAM96U+cGov6H+idoeXivG3e6pBiHTbsVY2Cx/BqFug/HGjKWNcbyMNWZsbaYbyGK0qfWKse5ZbDnblHHyHIfUL27dunXqN/ObPPbYY91rZfmbaMfzXXvttc22s846q7GpjbzvvvsaO+o9pdHcHbHeWfvH2PRsjC4W4hjM5lW0OXYzrVamE+tp1DJt1rjXYt/F7eNqzDI9LIk+IMsllun0Mu1t1AiMm/utl7dsuu3Z/pFs7FB/kuUsitfO8syxnOzvTDcW7d69QBrVl2Q67V4+zyyHXZa/czFSa23qyXvSzp07Gzs+ozA3IucK+4b7Zz4m9gfPxXGR5Rrr6aF4LZ6L9aJN7RWf01jv2N58JszyfWU5A0ncP5vzmdYuux+zXWIfsQ1YT2rM+JzX0z5KrU/JfDbtnr52urLHdutpkKVc68hnfNYz6jqpYSYnnXTS1G+2Z8RfzowxxhhjjDFmAPjlzBhjjDHGGGMGgF/OjDHGGGOMMWYALLjm7Igjjpiyqe1h3G7U82TxqFnsPvOiMYb0mGOOmfrNmF7GJvdyVEh5THw8vhdbL+Wxy1n+jV6sfi+eezo7yyUUt7N/eK4sl0qWG4rxx1F7wW2Zzobxw3fddVdjn3322Y39ve99b+o3x1GW8yjTpPX6m+3Ncp5xxhmNzXo98sgjjc145xgrncX+x/j9cXNrDZXYF9n4je0xrjaLZLqwPclFll2L9Yrny3IuZvMq0z5E3dG4mtSM3rUz3Wemf8q0Wb0+GbdNqZOhVoK+LtYl6w9eO9ML9XQZme6Ovoj9S5vHR9+XjbtxchAuFvbZZx+tWLFiyt62bVuznZr82LcPPvhgs+34449v7Kyfs3txL68cx2em98y0pD2dY3YvzbTnPS0W5yE171yX4Omnn25sataoFY39leUjHCc/23Tbe89SnKeZfjbTpvfyeI2rj87y1bJevdxxfPZh3/f8jzTq86P2LsvtF+dXz1ctPS9mjDHGGGOMMYuQWb2clVIOKqV8tpRydyllYynlolLKIaWUK0opmyf/f3B+JmOMmT/sm4wxQ8X+yRgzF2b75ezfSvpyrXWtpLMlbZT0YUlX1lpPknTlpG2MMQuJfZMxZqjYPxljxibVnJVSDpT0Rknvk6Ra63OSniulvFvSJZO7fVLSVZJ+q3euXbt2NbG4jCllvGtPN8CY0Cw/DHMPMMfT97///anfjC9luTKNGWHsc9w/y82R5aohPS0etzHmN9OgkZ4+LsvFwfhi9lemMevFYWexyzw3+5dl3bJlS2PHsfP444832xiv/+STTzY225i5ydhHUaOZ5SV64IEHGvuUU05pbMZZU/8W25D7sv2HwHz6pnGJbZ/lAdpTTVokm5OZBoD0ypLVI6tXVs843jLfk+lLqAHo5SKjT800NiwL5wI1Bcy3E8sy7jzK+pPbo2/LdFwk03H38mJSZ8H+GDcnFa8Vy5bpKoeiOZtP//TCCy8094qVK1c225966qnGjn1NX059FNszPgtJeT7UOJ+o7eeY49zI8t31/Femac3yg5Gevo1twn3Z/sx/yucAPnPEsrGcnIfZs1TmI3p6UPY1+4N2b42D6coS60a/mT37cv8sp1q8NjV/3JdzhGsJ0J9F/afUtinrEXPCSn1dcGQ2XuwESY9K+uNSys2llE+UUvaXdEStdackTf5/xXQHl1I+WEq5oZRyAyemMcbsAfPmm/iSbYwxe8i8+aelmFjbGDMzs3k520fSuZL+Q631HEk/1Bif4WutH6u1rq+1rucbpDHG7AHz5pv4Zd0YY/aQefNP/EpgjFnazGYp/R2SdtRar5u0P6sJB/NwKWVlrXVnKWWlpEdmPMMkpZTmUyRf1vhlLX6K7C1HL41+dqTNz5pc6jR+ruWDWhb2lpWFn5Xjp8wsnCMLZcuWI+2FgPDcvSVxp6OXUoB15idpLoOaLaU/TjjQuGEv7E/2CVM+xJASjqPDDz+8sRkyxbQM7O+HHnqosePndo5Dfnpnvbnc8mGHHdbYDI2JfcRzcf4MJMxx3nyT1NY5C5npLaXPsJQsLQHppbTIQs/2NNQwbt8T35Kdm8fTH2Tlzpav74X2cF/Od4ZmZaHK9G2Zf+ldm2T17IWcZctgZ+H59De9UMXs/jtuGGMvNJHHZikC9iLz5p+WL1+ugw8+uLEjMRWQJJ155plTv1evXt1sy5aY53NZNjdjezPsLZtr7CvOld4y8dk44BiKy51Pt70XVsdj6SPoA3jvZb14T4g+hnXOlnXvhUhOt38vJJx9n6XIYEoB+kpuj+Nj3GfZLLyW1477s035PJP5OrZLb+l9hsD2wuZ79+P0y1mt9SFJ20spLwpYLpN0l6QvSHrv5L+9V9JfZecyxpj5wr7JGDNU7J+MMXNltkmof0PSn5VS9pO0RdL7NfFi95lSygckbZP08y9NEY0xZkbsm4wxQ8X+yRgzNrN6Oau13iJp/TSbLpvX0hhjzBjYNxljhor9kzFmLsz2y9m8UEppYjOzJc1jbCxjXXvLU0qjS2PyWjF+m+djjCi1PYzZzZba5/7RznQAmS5gXN1HhPGuPa2LlMf2RzvTnGX1yNqlpyvI4tyzsjFuvqeHY2wy4/PjUvjSaLk5jhlX/fDDD8+4jdfmEsksN+O/GXcd25wx8uyfqK3LYsEXCz2dS0/LNY6Oazb79/RumW8Z99q9tBNZSoqeX5vNteP+vNa4GlT2XW85e85vHstlsTlHubIny8L7R7z3ZPetcdoss7MlnTlvafO+xntw9D+Zdi7TA2Vjp7fvuNsXK3Ec3X///c029tWpp5469XvVqlXNtmwJ86wve9pTHst5yDE2rrY8zpfs+SXTNVJH1hvf1BFlqZuyNu2lChrXj2YaM44NLvMf/QL7lmXh2KFPYVl4fHw+yvRs2Vjh8w/7INYl62u2WZb6o6f9pf/v3Uf3dCl9Y4wxxhhjjDEvMX45M8YYY4wxxpgB4JczY4wxxhhjjBkAC645i3HBjOvMjo0wjpO6MMYfMxa2F8fLOGnqiFhuxr4yxpd2PN+4ucV6upjptvdi9xnDyzjc7Fo9rVF27mx/wv7vXTvT5WQaKR7fi4vP8p8Q5tDj/owHj2OHfcn4b9osW5b/J9abbcZx2ov9X4yUUpr6j5Mradz8X5mmINNbRrL5Tr9HMl3ZXMs13bnJOOMmy4HDc1FfGduJuQapm+CxnFfZtZn7MM7DXs4zKddZ8F7C/WOf8D5Ff9A7Vso1PHE8cN9MH0vG0aSNq4VcCtRam7m8YsWKZvvJJ5/c2OvWrZv6nelnMn0xj+/5AZ6LOmg+S/FcfE7g3Itk45O+j2UbR9/JbVmO0Uwb2sudm/lZziXONfozznv2STw+y6uYaYF7elvun+VhJNn9gueLbcwxzDUpWG+OOz639Z4Re2N2umNnwl/OjDHGGGOMMWYA+OXMGGOMMcYYYwaAX86MMcYYY4wxZgCUhdSLlFIelfSApMMkPbZgF549Qy2XNNyyDbVc0nDLNtRySXMr27G11sPz3YbLIvBN0nDLNtRyScMt21DLJQ23bHMtl/3TS89QyyUNt2xDLZc03LIttXLN6JsW9OVs6qKl3FBrXb/gF04Yarmk4ZZtqOWShlu2oZZLGnbZFoIh13+oZRtquaThlm2o5ZKGW7ahlmshGWobDLVc0nDLNtRyScMt28upXA5rNMYYY4wxxpgB4JczY4wxxhhjjBkAe+vl7GN76boZQy2XNNyyDbVc0nDLNtRyScMu20Iw5PoPtWxDLZc03LINtVzScMs21HItJENtg6GWSxpu2YZaLmm4ZXvZlGuvaM6MMcYYY4wxxrQ4rNEYY4wxxhhjBsCCvpyVUn6ilHJPKeXeUsqHF/La05TlP5VSHiml3BH+7ZBSyhWllM2T/z94L5Tr6FLKfyulbCyl3FlK+dCAyvbKUsr1pZRbJ8v2u0Mp22Q5lpdSbi6lfHFg5dpaSrm9lHJLKeWGoZStlHJQKeWzpZS7J8fbRUMo197C/mlW5Rqkf7JvmnO57JsWAfZNsyqXfdPcyzg4/zRU3zRZjpfcPy3Yy1kpZbmkfy/p70g6TdIvlVJOW6jrT8OfSPoJ/NuHJV1Zaz1J0pWT9kLzgqR/XGs9VdKFkv7hZDsNoWzPSrq01nq2pHWSfqKUcuFAyiZJH5K0MdhDKZckvbnWui4stzqEsv1bSV+uta6VdLYm2m4I5Vpw7J9mzVD9k33T3LFvGjD2TbPGvmnuDNU/DdE3SQvhn2qtC/KfpIskfSXY/0zSP1uo689QpuMk3RHseyStnPy9UtI9e7N8k+X4K0lvHVrZJL1a0k2SLhhC2SStnpwQl0r64pD6U9JWSYfh3/Zq2SQdKOl+TepOh1KuvfWf/dOcyzg4/2TfNFbZ7JsG/p9905zLaN80uzIN0j8N0TdNXndB/NNChjUeJWl7sHdM/tuQOKLWulOSJv+/Ym8WppRynKRzJF2ngZRt8vP3LZIekXRFrXUoZfuopH8qaXf4tyGUS5KqpK+WUm4spXxwIGU7QdKjkv54MpzhE6WU/QdQrr2F/dOYDM0/2TfNCfum4WPfNCb2TWPxUQ3TPw3RN0kL5J8W8uWsTPNvXipyBkopr5H0/0j6R7XWp/d2eV6k1rqr1rpOE39t2VBKOWMvF0mllMslPVJrvXFvl2UGLq61nquJsJR/WEp5494ukKR9JJ0r6T/UWs+R9EO9TMKEZsD+aQyG6J/sm+aEfdPwsW8aA/um2TNw/zRE3yQtkH9ayJezHZKODvZqSQ8u4PVnw8OllJWSNPn/R/ZGIUop+2rCufxZrfVzQyrbi9Ran5J0lSZiz/d22S6W9JOllK2SPiXp0lLK/z2AckmSaq0PTv7/EUmfl7RhAGXbIWnH5F/wJOmzmnA4e7tcewv7p1kydP9k3zR77JsWBfZNs8S+aWwG658G6pukBfJPC/ly9l1JJ5VSji+l7CfpFyV9YQGvPxu+IOm9k7/fq4mY5QWllFIk/UdJG2ut//vAynZ4KeWgyd+vkvQWSXfv7bLVWv9ZrXV1rfU4TYyrr9da/97eLpcklVL2L6Uc8OJvSW+TdMfeLlut9SFJ20spp0z+02WS7trb5dqL2D/NgqH6J/um8bFvWjTYN80C+6bxGap/GqpvkhbQP82nUC77T9I7JG2SdJ+k/3khrz1NWf5c0k5Jz2viTfgDkg7VhDBy8+T/D9kL5Xq9JkIWbpN0y+R/7xhI2c6SdPNk2e6Q9M8n/32vly2U8RL9rah1r5dLE/HJt07+d+eL434gZVsn6YbJ/vxLSQcPoVx7cezYP+XlGqR/sm+aU3nsmxbJf/ZNsyqXfdOelXMw/mnIvmmyHC+5fyqTFzLGGGOMMcYYsxdZ0CTUxhhjjDHGGGOmxy9nxhhjjDHGGDMA/HJmjDHGGGOMMQPAL2fGGGOMMcYYMwD8cmaMMcYYY4wxA8AvZ8YYY4wxxhgzAPxyZowxxhhjjDEDwC9nxhhjjDHGGDMA/l8R0+Tzp2F5bAAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 1080x360 with 3 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1,3, figsize=(15,5))\n",
+    "ax[0].imshow(imgs[19], cmap='gray')\n",
+    "ax[0].set_title('Image 19')\n",
+    "ax[1].imshow(imgs[21], cmap='gray')\n",
+    "ax[1].set_title('Image 21')\n",
+    "ax[2].imshow(imgs[41], cmap='gray')\n",
+    "ax[2].set_title('Image 41')\n",
+    "plt.suptitle('Similar cats')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As you can see, all three cats have white snouts and black fur around the eyes, making them pretty similar.\n",
+    "\n",
+    "Now, let's choose three images that seem far appart from each other, for example image 18, on the middle right, 41 on the top center and 51 on the lower left, and also plot the images"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 0.98, 'Different cats')"
+      ]
+     },
+     "execution_count": 99,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x360 with 3 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1,3, figsize=(15,5))\n",
+    "ax[0].imshow(imgs[18], cmap='gray')\n",
+    "ax[0].set_title('Image 18')\n",
+    "ax[1].imshow(imgs[41], cmap='gray')\n",
+    "ax[1].set_title('Image 41')\n",
+    "ax[2].imshow(imgs[51], cmap='gray')\n",
+    "ax[2].set_title('Image 51')\n",
+    "plt.suptitle('Different cats')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this case, all three cats look really different, one being completely black, another completely white, and the the third one a mix of both colors.\n",
+    "\n",
+    "\n",
+    "Feel free to choose different pairs of points and check how similar (or different) the pictures are. \n",
+    "\n",
+    "<a name='2.6'></a>\n",
+    "### 2.6 Reconstructing the images from the eigenvectors\n",
+    "\n",
+    "When you compress the images using PCA, you are losing some information because you are using fewer variables to represent each observation. \n",
+    "\n",
+    "A natural question arises: how many components do you need to get a good reconstruction of the image? Of course, what determines a \"good\" reconstruction might depend on the application.\n",
+    "\n",
+    "A cool thing is that with a simple dot product you can transform the data after applying PCA back to the original space. This means that you can reconstruct the original image from the transformed space and check how distorted it looks based on the number of components you kept.\n",
+    "\n",
+    "Suppose you obtained the matrix $X_{red}$ by keeping just two eigenvectors, then $X_{red} = \\mathrm{X}\\underbrace{\\left[v_1\\  v_2\\right]}_{\\boldsymbol{V_2}}$.\n",
+    "\n",
+    "To transform the images back to the original variables space all you need to do is take the dot product between $X_{red}$ and $\\boldsymbol{V_2}^T$. If you were to keep more components, say $k$, then simply replace $\\boldsymbol{V_2}$ by $\\boldsymbol{V_k} = \\left[v_1\\ v_2\\ \\ldots\\ v_k\\right]$. Notice that you can't make any combination you like, if you reduced the original data to just $k$ components, then the recovery must consider only the first $k$ eigenvectors, otherwise you will not be able to perform the matrix multiplication.\n",
+    "\n",
+    "In the next cell you will define a function that given the transformed data $X_{red}$ and the matrix of eigenvectors returns the recovered image. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "def reconstruct_image(Xred, eigenvecs):\n",
+    "    X_reconstructed = Xred.dot(eigenvecs[:,:Xred.shape[1]].T)\n",
+    "\n",
+    "    return X_reconstructed"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's see what the reconstructed image looks like for different number of principal components"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'reconstructed from 30 components')"
+      ]
+     },
+     "execution_count": 101,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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nxbPKbtLgSC8y9f/dqP7rzTM2u/XT8NvhXXPKPqEhUK0w9U/QEPiuNWt8r2YFtlnfe9/o+6fOKrtKOVicNvreByW1w7E5/h3S9mfsghhGDHNjueZQ/Zr1M9doicewURvfrMH3bpG0cs73iGHEsNn1iWFH+Z+IYbN//hUihs0dyzWH6tesn7lGSzSGafg0Wp/170ZJl5t6xDBi2Oz68xrDpuXPYz/Ve7/PlD9Vw2R/W2vt28z3HyZpbWttdR+UWJ4yKp+bFNLxhNHX9879Ru/9/tba+zUYyOM13P7P5jrT3pbR19lyzm/RoBbz1tban2r4COQHe+9fmKB/iWuP4Gdnc5GGG+CP9CNPGvokDcafJI8fOvr66FllT9CwWT9g6l9zhP1xbO697zDlB7ODG1trWyWd01pb0b/2Y8X7wjreqeHjwR8z37tDwzydPvrvhaaNvvYJ6s7XXtrbWvuEpK/TYHOfmlPF7aUZe0xzKA35Um6b872P997vMT9zjYaPLj9e0htba6dq+NOIO3rvN5j6M+N4vPneJ3vv7k8htmjwV5Kk1tpJGg5JuyT92PBXCGPcp6/dEzPc1Gf9qcmcZ0jDb7rcOL+G3vvdrbW/lPQvJX2ytfZnGnJFfKT3/qVD/TyUIIZNDjHs8Fj0May19jQNf/p0r6Rv6b3vrTYx+koMI4YRw+YXYtjkEMMOj0Ubw3rv3yHpO1prp0m6RIOI0gdba9/fe3/DpO2IGEYMO4IYNi2XdneF8tUa+vjzh/j5UzR8THXF6P8n2YjLR1+3he/PlK8w39tnymb+HvqEmYLe+7WttWdouAH/Vkn/VpJaa5+X9Mre+x9N0M+5pLmqsmL0dT4uj1aPvj5p9C9xyqz/Xi5pTx/PUSDN3xgnaXMSO9g4qrdvVvn+UP9+Seq9u+/P2MhDzffmg5lnLg/fP21OvYOxYvT1qO6lQ8xTdQ63h+fPrP3yOV/na+/P9GvZrP9fqSE4r9Wh/VflGdIsHzMB/0bDn5l8px7MM/Ll0eH1P/be05xBDWLY5BDDDo9FHcNaa0/V8PJxQNK/6L27F19imIcYRgw72hDDJocYdngs6hg2avNuSR9qrf1LDZddv9Na+7ve+9Y5fSKGfS3EsHmIYcsOXWVBSDfO+yXt7b23Q/ybuendN/p65gTPnDHE08P3N8ypd1j03j/ce79ag/FcqSHx4XoNSUG//nCaDOUzCS/HLmJHyUnnsm/0dZK5OhQzc/Trh1inZ835mVWtNbfp05ocCQezsYM9c17sYIH4/OjrBeH754++3jhBW/tGX6dmL03A+lA+06/9c74ezf7O/OwnDuW/juAZh6T3/s+991f03i/QcOj5bg2/Vf1uDclVYX4ghhWaDOXEsIOzaGPY6KX5XXrwz9Q+GKoSwzzEMGLY0YYYVmgylBPDDs6ijWFz6b1/RYMww8P14CfiJGIYMWwO8xnDpuXSLvGPkla21i4u1JcGxZlD8YnR16vmfqO19hANqh7SuDLMYdF7v6/3/qHe+89pkP6VBsWeGWY+6lm5vZ3NzJ+ZnG2+d7kpu0GDQ7i0tXbGBO0frH/XaghWz5ignRk+rsH+nm6+d1WhnSPlYHZwnoaP/97aveLOtPH3o6/Pa619zd4efRT5Sg05Df5x7g8a5msvrZD0OD0osX00ecJonHO5avT1E5LUh49uf0HSma218039mUPNYe/93vsXNciDX9xaW3W47UzAxH6j976l9/5mDQlbb5L09Nba6kP8GBwZxLDJIYYdHlMdw1prz9bwCbv7JT23936w+EMMI4YdrE/EsIWHGDY5xLDDY6pj2EGYuUybrTxKDCOGHaxPRxTDpv3S7tdHX3/XObTW2smttdk33H+pIUHhN7fWXmTqz76tfqsGdZkXzWlDkn5Mg3rK3/Xe5+ZRmJjW2jNaa+4jsjM30bP/nnn36OvGw3zcdRoc9neO/o57pg+rNEijfw19+Hvw39Yg6/4/W2snzun7w1prayfpXx9yFLxZ0uWttZ8dBduvobV2bmvtnFlFvz/6+qrW2sPn9PdntHC8fvT1Z2aPt7V2gqT/pmGP/N4C9uew6UNuh3dryAHyQ3O+/UpJJ0t6U+/93gmae6OGxKU/2Fr7urnfbK2dNet//0BDzpMfHgXY2fwXDR8H/4Pu86XMJ8s1SJH/X1prl2tIdrxfQ0LlGV6v4WPTvzJa65n6ayT97Kw6R8Kvacj38nr3W9bW2srW2hPGfqpG3JettbWttSebnzlZ0qkaDhpfOcLnw8Ehhk0OMezwmNoY1lp7nqR3aHhZeE7v/aMHq08MI4bNaZ8Yduwhhk0OMezwmMoY1lpb3Vp7bPje1ZL+laQvahAnkEQMEzFsbvvzGsOmJaedpff+ntbayyX9oqSbWmt/rUFN6BQN8sbP1PARw28Y1f9KGxKlvlvDx56/X8NN9cM1JBp8jkZj7r1/sbX2PZL+j6T3tdb+j4ZEp0+U9DwNf3/9/Uc4hB/XcNt+jQY1my9KuljDrfn/396/x2p6XfeZ4NqHou6kyGLdi3XjRbyIutOiFDUsWep47MSIjKTdYwfuaAwPNINJBgnQPbGcAXomQQejaQwaidGNDITEtjQdp634Eil2fFHkaLptWaYYUSRFUmSRRVax7hcWSdlKdGG988c5HrH5/Z6qb5GnDr9z6nkAoVSLm/vdl7XX2u/Lc9bvXC2rzPw5/66Wg/3/Y4xxx8o/r2ma/pt5HjRN0/Exxj+v5XoNXxtj/HYtH9K/VMsy6KmY49+vqrtquUDio2OM36rlwoq7a3kN/i+1rPgyz/j+Vi3/2O8/qKr/Yozxh7X8u+07a3ntf6CqfqqW96+q6l/U8u95/5Wq+voY47O1/Pvx/1kty0/fOM+8Xy7TNH1pjPHfVtXfXRnHr9VykewfreVio39YyxLea84Y49aq+viLzNeOMX75BX//r6ZpOvOCv/+fqupLVfULY4wP1/J/Vbmrlv+rxaO1XNfjokzTdGaM8ddr+Ud3/90Y43eq6v5a9qm31bKP7F9p++QY4+9U1f9QVV8dY3ymluXAP1DLRUG/Ucu/z3+p+Z+r6n+/EiD/qJZ/vPp/W8sJ//8w/a+Liv6/anmPP1JV963EltdX1U/Ustz4fztNUyrOOzfTNP3iGOPdtbwnj48xfq+WY8ymWl67H6zlS9P/8WU85pFarnfxk2OM76z0P1XV/6eWfxXky2OMh2v5v1Y9Vcv792O1/CPpvzDlgrGySpjDzGGXmkXNYWOMW6rqs7Xsu/+mqj4yxvjIi9tN0/R/f5HJHGYOM4ctCOYwc9ilZlFzWC3vwb1jjK/W8k9sHa3lGmvvqOVfif1uLavEvlhQyRxmDrs0OWx6mfKzL+d/9X353l++SLv/pKo+U8tqJt+pZUf8Wi1/QU2Sy3tq+b9ePLHS/mxV/UlV/V9D2x+o5S+/p1faHq6qf1JBfru+L1m8L/yzD9aLJH9rOeD+UlU9VMtfmP9sZXN/oV4glfyC9j+9Mq//sNLXNM+zX9DmNbUc2I6szOWxqvr5Wk6QUwXp7pV/9rdq+Uer/3RljAdqOZHdNO/4Vv75q1f6+tLKfL+9sp5fqOX/anZdaP9f13Ii/XYt/9e5f7gyjzjeC8z9iy8ezwv+2UX7qqqfrOXE8M1a/qmAB2s5sL42tH2yllWQuuO46B6CT13of8kXd6/43fEVPzhUVf+4qja9hDP6lqr6dC0HpO/U8gXg/1tZmv2Ha/midm5lPx+r5f+6eM1qrVMFyft6QRyp5YvJZ1fG8K1aThr/G3jOa6vq71XV11d8+psrPvBToe3//xkvYd9/rJZ/2uTUyhqeqOXz9t/Ui6TOL+SrtC61HMO+UMtn7vyfr08tXy7+61pWYTq6sifHV8b6U7UK8uOX+/8u5hcvaGcOM4ddzJe++OLxvOCfrbscVvPlL3qOOcwc9sEyh13y/13ML17QzhxmDruYL33xxeN5wT9bjzns2pW1+F/q+7noz2r5I9z/u6puu8C/aw4zh32wVjmHjZWHiYisS8YY+2r5YvipaZr+d6/saERERObHHCYiIusVc9jasOg17URERERERERERC47/GgnIiIiIiIiIiKyYPjRTkREREREREREZMGwpp2IiIiIiIiIiMiC8bJ+0m6M8SNjjEfGGI+tSIKLiIisC8xhIiKynjGPiYhsfF7yT9qNMa6oqker6i/WsrT1V2pZovch+nde9apXTa9+9atn7EtLs98Oxxj03GhfjT46bTv2bh/nz5+fsdE+pT7SWlyoj0Tap6qq17zmNdH+qle9aq6xVVVdccUVc48jrcWFSH1TH52+aU1XY607bWlNqY80x+eff77VR5ojte30TW0TNO9vfetb0f6d73xnrjFUsU9/73vfm3scnZjS2Svqm/ro+FKa33e+85367ne/O/9k1jGXOodRbOjksC5p/7u+kmJoiu9VPJfO+Ut+38mNxOte97pof9Ob3hTtV1555Yytu4dpjt39prVO0HqkcXRzWKKbf1L71cg/3byb7LR2KS4Snba0dufOnYv2dIZozHSn+o//8T/O2FYjznTvVOmZnbZEWqPnn3++zp8/f1nksKp+HnvVq141zRvrurGr8+5CdO/8iTS+NOeq1clhnX47MfSqq66KbTdt2hTtKQ6sxjssQXFnNe7Dl3KtO89LfXTyLtHNpZ22lJc6c+l8Wzh58mS0f/vb356xUf6ne89/+A//YcZGftfJHd0clp5Jc+l840hxpqrqu9/97plpmra82D7/7XCW91TVY9M0HayqGmP8T1X1karCF55Xv/rVdcstt8zYX/va187YaANT26qq17/+9TM2WjjqO7WnQE/OkdrTRwEaX/oQ8d3vfje2TXN5wxveENtSH4m9e/dG+/79+6N969atc42tihNRWg/6KEMBL809XVyrqv7sz/5s7r7pBfCNb3xjtHcSPh38NA5aUwrSzz333IztT//0T2NbCh5p7uRL3/zmN+fum9om6Kzce++90X7kyJEZG41537590X7mzJkZG33MJnvaQ/LHlJyqckyhuXReiJ9++ukZ29e//vX4729QXlIOu/nmm2fs6YyknFTF+SD10X3hoQ+xCfKVa665ZsbWeUmoqjp69OhcY6vKMZ7ya2cub33rW2PbH/3RH432Xbt2zdjovkFxOF34aC5XX311tKf1JyiWpLUmvyM/TXtLc6G9TbGL4j7FtDRuyru0Hqnv9EJRVXXq1KloT7H87NmzsW2CcsS//Jf/MtoPHTo0Y6P5kc88+OCDMzZau86HUMpVdF9Lc6e5kD8m0hrRR9ANTCuPXXnllfHOk9ad4h/FkuQXnQ/bVdkvui/YKbbu2LEjtiW/T77VGQedd8qZKYd98IMfjG3/+l//69Ge3q3oHZb2tvMfSSiWpGd2PzCl9aA7SydP07sj5Z/OeymNL/kH7UvnfZDWLr270DPpPTitHa3zL/zCL0T7gQMHZmzpnbSK75gPPPDAjI3yHb2nJyiH0b0gfVugd2n6xpHOwLFjx2Lbp556ajYA1cv79dhdVfXUC/5+ZMUmIiKy6JjDRERkPWMeExG5DHg5P2mXPlfPfEYcY3ysqj5WxV+WRURE1hhzmIiIrGcumsdemMM6v34vIiKLw8v5SbsjVbX7BX+/vqpmfs5vmqZPTtN05zRNd5osRERkQTCHiYjIeuaiecwcJiKy/nk50fsrVXXzGGN/VR2tqp+sqvyL9issLS3F34lONQw2b94c++gUlqSfiqBaA53ffyfS7/jT70jT766n+gGd2gH0PKrHkPo4ceJEbEtFvBPXXXddtNPvxadx0+/s01xSXQKqv9GpYUB1KKiP9PvyVKuF6jSlOVJbqrGQfoeeahjQmqa+aU2pbkWqY9Qp/Pq1r30ttqV6AGkuVGcg1d+qyn5KZ6tTCJwuzRSvUt0Eet7LLUzfjXfrnHYOG2PE/JHWl2I2xbRO8exOHRg6qx2xh8ceeyy2pfqp6ex06pBRPCO/T7VMHnoolybcvXt3tKe1plxFsSStfzd3dIRAnn322WhPe0h3KiLliW6d4FS/plsPKPkpzbtzLiiW07lIfVNOT3P8/d///dj20UcfjfYUZ+jummoHVeX7GtUU6vwUMZ17qimU9ovqZHXqtaZxkG9sYFp5bIwRc0LaO9pnOjspDnTrMKexdQUxki8/8sgjsS3lpWSn56U6iuTHdO9Nz/vDP/zD2Pamm26K9ne+850zNjrXtLedewj5QacuJb3TJCgfEykW0LxpX1Isp3nTXFLepJpqRIp/dC66tXgTaS6f/vSnY1t6P0vzpvso5cFOjO+IXNAaUQ5LeZPOBdVrTfeyzlmpehkf7aZp+t4Y429V1e9V1RVV9YvTNM1WvRUREVkwzGEiIrKeMY+JiFwevKyfk56m6d9U1b9ZpbGIiIisGeYwERFZz5jHREQ2Pi+npp2IiIiIiIiIiIhcAvxoJyIiIiIiIiIismCsqYwQFfFOUJFSKhqaCh5SUcJOwV0qKEhFDNM4du7cGdtSAfxUEJPGkQpR0tioSGanEOiRI0einYpLJqiYayrumQQMqrgQeFo78jkqBJrWmsZM805rSj5N9rQeVESV6BR5p6KmyX7q1KnYlgqd0llMpHNx+vTp2JbWLp0B2kPqI+0hFSlNYhH0TGpLa5R8mgrhEldfffWMLfmuynIvjbS+tEcUn1NeIt8k0v5R4XmKi8lnN23aFNtS30nEIK1RVdWWLVtmbM8888zc/VblPEHr/Cd/8ifRvm3bthnbNddcE9vSvqScQmeKBDFOnjw5YyNRJ4rlKXZ1xKyq8hxJ6KYjAEEFv6kP8rEEjS/x9NNPRzuNj+5giXvvvXfGRoXw6Vyk9aAxUG5L60HPo7VL+b8rrkZrmqD8mM5zimGXmZjSSyLtR4pTJKZA9uSHHaE1GhsVnqfYmmIdCfFQfElnjWJoyh2Uq2jt0hzpeb/6q78a7WmO9K7UEbWj9w7KS2kulEs776UURzqiNh2RALLTHq7GOzbFr+TrHeGLqiyYQjH7j/7oj2Zsf/zHfxzbkn+kdaIx0zlMfdO5oH1JdONSysfdd8qUrzrinlX+pJ2IiIiIiIiIiMjC4Uc7ERERERERERGRBcOPdiIiIiIiIiIiIguGH+1EREREREREREQWDD/aiYiIiIiIiIiILBhrLhWYlFGS0kZHna0qq4aQehypUyVlSOqDlPeSItnZs2dj2x07dkR7UnNJinJVed6kqERKJ2ku1JZU/e6///4Z2x133BHbkgJt6jspC1axal6C5kJ+kNaD/I5UbJJyFCkwklpNUvWjeZOqUhoHtSWl3s7ZIsWs5JPHjh2LbR977LEZGyn9kHpvR3GQ9jap7NE4SFU2nWXyR+o7xULaQ1IiSj72+te/fu6xyfdJa5TOCO0F+UpSNesoe1blfabnUZ5IypDUlhT5kkoZ5cE0PuqX4k7KHaRsRznsd3/3d2ds733ve2NbUrN+6qmnZmx33XVXbEvqpSkOXHvttbEtzSXNnVTiyD86bUkZMMVWGgcp3qU5kv9TfkyxjuJtZ19OnDgR237xi1+csVHMJsW71DfdNzr5kWI85dK0L7RXdMaTmiSNg+wpLnVyoywzxphbqZzOO73/dBSn6aym+EDPo75T/qGzQ+9h6f2A7rfJ57Zu3RrbkvJyWo+kSlvF74O/9Eu/NGP7y3/5L8e2R48ejfZ0L//Qhz4U23ZU5Um1mt7DUg6jPaTYlfaFfJr6TjmM/I7i4ryx60J9pzNLSrPJ/6tyHKaYnRSKaX6U01MOozFTHyk/0trR3qZ7I6kIdxSAaRx0T033aOqD8A1NRERERERERERkwfCjnYiIiIiIiIiIyILhRzsREREREREREZEFw492IiIiIiIiIiIiC4Yf7URERERERERERBaMNVWPnaYJlXNeTFeVIymukEoJqbMkSFmS7AlSRTl16lS0b9++fcZGKqpJWYUUVEilLCkikWohrV1SALrvvvtiW1JnSaphpFaTVPqq8p6TSgytR1IRonm/4Q1viPY0l4ceeii2Tcp29MydO3fGtldddVW0p/NGioO0HqkP8n9SoE3n+fjx47Ft2i9SnqJ4ktQMSVGJzkvyJToXNI6Oei/FvNQ3qanR+NJckpKRynsXZmlpKa59WneK+xSPUh8Ud8hXOkrgROqblP4olqfzSgpvKZbQ80gRNq01KbxSzE5xMSnKVvXUqUn5taMaRncZiuXpDkEKwKQAmNSPk/pcFav9pjlSDtu9e3e0J/8gxTuaY1onOoePPvro3H0cOnQotk3ngmI2rWm661JbOhfp3kgKmKTimNa/q3zYaUv3oTQO81WfMUb0rZR/6E5I6073j0RHvZHONb0fpD7o7FBs3bVr14yNfDOdBzpPKTZX5fNA6tQ0jtT+V37lV2JbGl+6L9Dz6I6T1oP2ivwg5U2KXZR/0londdyq3t1i7969se2NN94Y7ekOf+bMmdiW3uWST9N7x7333hvtKYc99thjsW3n2wL5aYoTdGehPUx+QPdDuusmRXjqg74xpfXvKP1WrY7auT9pJyIiIiIiIiIismD40U5ERERERERERGTB8KOdiIiIiIiIiIjIguFHOxERERERERERkQVjTYUoiFTkslMUtyoXl6biiFTokYrod/pIBfCpOCIVV01zT+IIVXntqEg2FVhM46MCtJ3i6lRgkQoypyKjJB5Ac0zFzql4KfWdfInGTEVsk3+Q8AgV90z7RQW4qbh6Kv5K46A9T3Ohc0iF6ZMv0PNSkVcqGkoFP1PRYSoeSwWKk69TXCJ/pPOSoOLeaW+pqC8Vpk3r1BUokGU/TsVnky+Tf3eET6hoL4kbpHNCZ5KK6KYYSn5M5yHlg5Qbq3Kc6xZp3rp164yN1p/8Pq0TnTPKpekOQWtH942Ur8gPKA5Tce8ECYQkYQgSgKI5pn05ePBgbEt7mwpUU/Fs2pd0f6L8Tz6d9ovy7o4dO2Zshw8fjm0799G3v/3tsS3l9HRfoFxF+YfuOJ22SdSE/I76SOezk1/lwqQ7GsURWvcUW6kPev/pCPSQQELKNV0BlqNHj87YkjhFVfZlymE0v23bts3YTp48GdtSXkr7QutPsTKtB90h6O6c8hW9u3SEQGgulA9uvfXWGdsTTzwR29L7ahJqeuSRR2JbElNIfXTzQbInH72QPc2RzvJb3vKWGduBAwdi244w0bve9a7YlgRCkogE3V07og4dUdOq/A2AvsvQe2nyXzrLhG9tIiIiIiIiIiIiC4Yf7URERERERERERBYMP9qJiIiIiIiIiIgsGH60ExERERERERERWTD8aCciIiIiIiIiIrJgrKl67DRNUWUkKQ6R+gYpzSTVPFL8TGokVVnVL6leXWgcSeGFlFVI3S4p9ZDiVxofqZ+cPn062jsqkqT4lJSZOkouVVkJjxReaG+TYjCps5AiUoLmQn0n1SdSTyKSehI9j/pOvkBtr7766mhPSlAdhbeqPG5Sk0znhRQ3aV+SihMpq5ICWVLvI6UxUiZLc6HzSSpOKU5QXKJzkUh71T2zlxvf+973olJjUskkdcSOL1MeJBXPdKZIjYyUR5MfUtynPpKd8kw6f6TKSSpxaU137twZ21L8S2OmM9nJKcePH49taV9Se4q3pKaXlFFJ6YzuJ0mBjtaO4kbnbkdqi4cOHZqxkVoqqTumuw/5GN210h5QHD5y5MiMjXyG/CCd5dRvFa9pembnDlfVU/OkvtM4KFeRT6f1SHulKvqF+d73vhfvp+nORH5F9vQeRpB6dvKhpL5ZxXep5G903snfkt/TmFMcIIV3yt3pnnfzzTfHtqQqm84DnV+KOykOPPnkk7EtzTG9h9FeddSsKb7Qe8c3vvGNGRu9B1PfSSGX7naU61Oso3nv3bs32lN+pHnTt4W0B0npvCorxdL5JtXc9P5Oa0T3k3Q+O/fOqpy7Kf+Qnyb/oFxD75rpnkp7RZjdREREREREREREFgw/2omIiIiIiIiIiCwYfrQTERERERERERFZMPxoJyIiIiIiIiIismD40U5ERERERERERGTBWFP12DFGVF1JKh6kZNVRXiS1LlK8SYpIpGiS1AKr8lxI+SgpvFX15pIU3rZs2RLbEul5tM6kvJvWiZRVqO+kFkTqfaRik9p32pI9KahWsRJkWg9S+iHlvaRaRJACVoIUdkhNKinv0B4SaZ1o3ukckkofKe8klS/yR/KPNA5Smr3uuuuiPSklkd+RQiT5WKKjckzPE2aMERWx0nnoKvF24j4pfqX2dFbJl9M5IdVk6jv5Fp2/lOtJnZAUANM4aMykppdiNsXgTg4jJTHKpak9jZkU79LeUg6jPtJa072MVN7THOlcUCxPquakAEgqdmn9KA/SvqQ7X0eRnHyX7oFJLZDOEOX/dB8lX6I9TOtEOYl8KUHxpzMOlWJfGilPpPsp7TOte+qDYiXtc/JPiuUpNlTlcdM4SEUyrRGphqbzR2eB3j/T+Cj/UOxK75qktE0xI8Vneh7FrqSMSs+jXJ/8gxTGKaYlxWlaU3r/Sb5Hz6NzkfISvXds37492lN7yoM0vuR7HfXS66+/Pto7uZTiPo0j+QE9j+7LqQ8aB61dutPSXYbO/mq8J5jxREREREREREREFgw/2omIiIiIiIiIiCwYfrQTERERERERERFZMPxoJyIiIiIiIiIismCsuRDFvMX8qGgvFStM/VKh9U6xQio0TONIBQi7xaxTEVUaRyq0ScWiu8WsE1ToOa01FQ2lvU1FZWneVLwxzbEjeECQ0ACtdRJCoIK3VJA3FUantjSOVPyV/I76SEXv0/yquBBr8g8qJrpnz54ZGxUHpz7SOlEhXIoHaS4kKkNFZdOekz+SQEXyaRI1oWK6KV4lW7co6uXGGCPGy3RWKa52fJb2g2JJ2lM61x2/p4Lf1HeaO+Xj1JbiCxUCT30nkaaqqhtvvDHaU3xIBbWrOM6luVAOo/VI5532ioopp3hEPkNzSXOn3EHjS75OOYyK3idf6DyvKhfgpiLe5GO33nrrjO2+++6Lbbdt2zZjoxxGvt4pwN3ZFyqET8X+OyJXdMfsPI/8Mc095UFz2IU5f/58jA/J7yl2kb+lvaM8SOcsPZPetzqCaJTDSEyhI3KSzhndCTs5/eTJk7HtTTfdFO0pZlMfFEM7902KR+ku273LpHHQuyPdnVPM7bz/V/HcEx0BR2pL780pblO8Jfttt902Y/vSl74U2+7evXvGRrmA/CDdi0kQi/wj3XHoPYzG13kPpj5Se4oR5NOd5xH+pJ2IiIiIiIiIiMiC4Uc7ERERERERERGRBcOPdiIiIiIiIiIiIguGH+1EREREREREREQWDD/aiYiIiIiIiIiILBhrqh47TVNUAUoqO6TYQqooSUWV1IlIzSgpnZCiCSnCpvmRoiPNMSkAkXppWg9SpaP1SOospGCTFGWoPa0zKVIlNTFSYCKln47iE40jQQovpFqU5kJ90DolX+qq93SU1GgcSSGSxpHOYVVPCffYsWMzNlKaI59OyoCkTkhrlOZNZ4vmkiAlNPL1pHZF4yCSUrLKe32maYq+T4pYHUiZO0E+1FGt7ii/kvIe5bbkyzTmTs48e/ZstKccRjGKYkmad0edkPqgcVD+74yD7kMdFUfKmXTHSXTVBROkDJjiNsV9Wo90Lmh+W7dujfaDBw/O2GjMKR6QeiytXTq3dC5o3ukc0rw7SoSUqygvdfJV556U4hKpQ8r3SffWlA/IN2mN01klv+rENPIfiuXpPkb3P4pRyQ878SXdeas4DqQxd5SUqzguJjrrTyrqHf/oxoZ0L6D3LfJHuuMkaI6d94COaijdqcin03rQvZPy0iOPPDJjo3eX5P/ku/Qund4HKb9STkm+TndJIp2j7jem1AedT8phyT86745V/qSdiIiIiIiIiIjIwuFHOxERERERERERkQXDj3YiIiIiIiIiIiILhh/tREREREREREREFoyLfrQbY/ziGOPUGOPrL7BtGmN8foxxYOXPay/tMEVERF4a5jEREVmvmMNERC5v5lGP/eWq+u+r6tMvsH28qr4wTdMnxhgfX/n7z12so+9973tR7SSpQpEaCamzJCUQUksj5ZekgJpU6apYnSWNmxRvaBxJRYVUHZPyyLXX5rxNiiZpT7Zs2RLbnjhxItq3b98+YyM1GFJtSWtH60/qtmncXbU0UvVJkB8kyKdpHGlvqS0pYyXfIwVGUihO6knUltSrki+QulbaL/IDWtPkY6QkRWcrKQPRWaY+0nqcO3cutqW9TepJ5KM0jmRPsbSrSruO+OVahTz2/PPPR3Wv5Cvd+JLiMKlT0T4lRTiKt3T+kjJXR2mWxtcZc1Ljq+Lzl3Ibze/QoUPR/o53vGPGRveNjuL3m970ptj2iSeemLtvWn+y33zzzTM2WlOK5Ump9OjRo7EtqbmlvET+T/eWdI7oLkMqgilPkNI5jS8pkm/bti22TT5G/dJdJp1bUgukc5EglUTKsSmHkcIhjaNzl6Fzm85iih0UMzcAv1yrkMOmaYr7lO4IdM42bdoU7WlPKf8QaWxXXnllbEtnKvkKxT/qO927OsrE9P5DZ6RzR37yySej/T3vec+Mjd5RSD02xWyKc5TDEnTe6f0sPbOjHl+V50L5n+7OyZfIZ0gJNPVN70p0T0rniPx/79690X748OEZ2w033BDbPvXUUzM2ytEdZXT6hkBxO601te3cRymH0blIfdM4yA+Svat2ftHsNk3T/1xVL96Rj1TVp1b+/6eq6sdbTxUREVkjzGMiIrJeMYeJiFzevNT/JLVtmqbjVVUrf25dvSGJiIhccsxjIiKyXjGHiYhcJszz67EvizHGx6rqY1X8o4siIiKLyAtzWPdH2UVERF5JXpjDNvCvD4uIbGheavQ+OcbYUVW18ucpajhN0yenabpzmqY7feEREZEFYa489sIc5guPiIgsCOYwEZHLhJf6o2+fq6qPVtUnVv787Dz/0jRNsSBwKshIP5VHCScVPKRigFTMNxU8pA+NVHi5I2JAfaS5UxHVVOCS5pcKSxO0/lSANhVMpYKrVAAyFYameZMfpGKuVFiSCqOmQs1UHHTHjh3RnqAiqqngbVUWLKC5EGmOJFpBxVyTL1DxcirQmgoaU1HztB50VuiMp/2iAtxUbDn5GJ0LKmqezgAVt6fCtGkctB505pLfdIqXb1Bech57MSmvka9QYe5OUfXOfwCjPsiHkh/SGaEYmp5JxYo74idUVDutaUckqCqfB8pVtP4pH1AxcbKn+EdnlXJHEjfo/qZD8nPKHZTbUlwkfyQfS3tL60++lOZC609z3Lp19jcPjx8/Pvc4SHCCSOtE9yEirR2d+zS/qjxuyvO0/mm/KA6SH6T9ovx/GdHOYUtLS3HdOsJbHXEJurOSHya6Alkp1tE4OqKHSYyGIGEDumendxeKlZTb0tmhHE3nbPPmzTM2urOSvXOHp/XviPlQPErPpPWn+0l6b6a9pXPRESqj/JOgnE7rtGvXrhnbyZMnY9s0PsphFIfTepDfUR9JbIvmnXy3ir+JJDrvUCQ2Q/6RoPc+4qL/yWWM8S+q6o+r6pYxxpExxs/WcoL4i2OMA1X1F1f+LiIisnCYx0REZL1iDhMRuby56H96nabpp+AffXiVxyIiIrLqmMdERGS9Yg4TEbm8sbiBiIiIiIiIiIjIguFHOxERERERERERkQXDj3YiIiIiIiIiIiILxktVj31JjDGiUkZHgpzU3JJaSlIdqWKlx6QuSWMjlZKkuEKqKKRmlOykvJPUWUjRh5TH3vSmN83YSGmT+k4KQKSsSqo5SbWFlFxIPY5U7BK0pkndhtR4SCUm9UHrTyp2SV2VlGZonZKfkjoRKVIltSV6HqkLpXWi9Uh7SwpTZE/Po3hA/njttdfO2Ei1qKOiSWeo44/kd+QfSV0rxaWuStvlyLxKvB217qrsF+QTnbhDZ4TiczqXFBsohyX1OFI6TZCSJamzpbWm+ELxLymMUZ6nOJfmSGeK4kDi2WefjXbalxS7OorrVXnuSdG8ihX50lpTLiWFtzQ+eh7d7VLcpvP51FNPRXsaNykOpnxAZ5byUppjJ89UZf+geEDnM60d7VVHzZXOBeXYjrq2MGOMuMZpLSlWdu5BpBbZeU+hOEd35/SeuGnTptiWzmWKO3R2EnQWaD2uu+66GRvlMFr/J554YsbWzWHpnHXu6lXZl+isUsxO4+4ojFZV7d+/f8ZG60/2tNZ0Luj7xLz9XqjvZKdzcd9990V7uvPROzPtbYLWLr2PdO49VTnvki9RfkzPpDsVvdumOEFrRGrGqX33ncuMJyIiIiIiIiIismD40U5ERERERERERGTB8KOdiIiIiIiIiIjIguFHOxERERERERERkQXDj3YiIiIiIiIiIiILxpqqxxJJeYRUQEg9Jil+kCoNKfIlBZqOklVVVmIlNRjqI42jqxqaIEWTpKxCbUktLa1pUrCr4jVN8ya1OlI6S+1JPYmUp9JcaJ1JzTApzZDST/KZqrzWpHhDdFQESQknKUeReh/N5eDBgzM2UnxK4yB1Ilr/tF/k06QIlmJQR52oKo+7M++qPG7yJdrbeVVFO/HkciXtU1o3ilGUDxLks3Qekqoj+eapU6eiPalZkd+T8l6KUxT3k892FQdTzCZ1UFJ4Szn2rW99a2x79913R3vyg6ToV8UqqmmOdK7pDpHmQrmU1inlR8qZNJcUp0iZnvYlnQHyO8r1yZ9o7Xbt2hXt999//4yNYnZ6Ht07ibRONObVUP2m8SW/6ahGV/VUZSlOJN+jcUifdJci/6Y9StBdke5daRz0/nP69OloT+eB+iAfSvfeznmnNaKzkOadFGVpbFU5d9x0002x7QMPPBDtKd4eO3YstqW4k3IKxWxa0y1btszY6P2T1jTtObXdvXt3tCf/oBxG7yPpDJB/UA5L7w10P7ztttui/cCBAzM2uo8mn6Z7Gd1PUk6hMRPpTtV5z6nKStD0rkP25Evku6sRNwl/0k5ERERERERERGTB8KOdiIiIiIiIiIjIguFHOxERERERERERkQXDj3YiIiIiIiIiIiILxpoKUYwxYiG+VJC0W7AvFQ+kov1UzDoV26ZiqVRcNRXtpSLeNMdUTDwV5azKhZ474ghVeZ127NgR21Ih6s68qZgoFejvkPalu4epyCUVhKU5Jvbs2RPttKZp3FTgktauU/ya2qYC4XSGqEBuKnaaioNW5bnQ2KgQbtoX6oMKFKd50xmiAqjJTkVUqUBrim20dlRUNsWEJBpCY5NlKIelPaIz2cltVDSZCr4n/yS/J3vKBzQOmksaHwlDpb7pXNNZTeeBYjMVGk7xltaIznvac4qJRFonyukUh1OOpXxHa5rmTgWuSUQi+RKNmWJa8ulNmzbFtjSXtB4k5vPoo49GO+XeRCpeTvGd/DTZaZ3pfKYxU4yn4uppTTsF16vyXGjMNL70zI7AhSwzxojr1nn/6QoTJTo5rCs40rm70blO4yP/Tvcumh+RcgflwY4gDeXo7t4mKA6k2Ep5l+aS3inpXYn6Tjll//79sS3N5eTJk3OPI7WtymtK4k1kT6IrJPaYhP+q8hkgH0tniObdEahI3zeq+N2lI1xB+TGNg+ZNz+uIanTe5eg+RPiGJiIiIiIiIiIismD40U5ERERERERERGTB8KOdiIiIiIiIiIjIguFHOxERERERERERkQXDj3YiIiIiIiIiIiILxpqqx07TFFVUOoqFpDCW+iBlqY4SHikLddR7SJWGFG+2bds2dx9pPWh+HcVJUsEhtZo0vqNHj8a2pFKW1FlI+aijNEMKgKSEk3y0q3y0ffv2GRvNhZSBk3oSKSKTal5ScaLzRqo+SQWLFI5ob5OCYufck8JORxGM9ormkhSRSBGMlDHPnj07Y6M1Iv9I60RrR32kdUpntqP+djkyTVOMJxSPEqQqS/EoQec9+SepZBFXXXXVjI1yB/Wd8gTlpaT4RSp9FMtTe4qVRFLT+8Y3vjF32wvZE2fOnIn2FLtov8mXUuwihTe646RYQirqSYm6qqfiTXE4QcqvtOcpl5LCG61T6pvibUftkva2ox5PpHsLrR3FsHQvWA1VS2rbWdOO0qV8n3n9gu4DdEZSDqO4T3EgQf5G9/LkQzRmigNJoZp8No0j5dEqvkOmdaIxE2lNH3roodiW5tJ5DyNl9HRfoD3sqAjTO+XmzZujPcU0eoftqJQeO3Ys2tO7e1WO8XTfo7tWWic6Q/T+3nnnSntOe9XxdRoD2dMZoLvC1q1boz2px3fVnVfj3SjNkWIY9vGyRyEiIiIiIiIiIiKrih/tREREREREREREFgw/2omIiIiIiIiIiCwYfrQTERERERERERFZMNZUiGKMEYs9puJ83aKViU5R9qpcTJ4EIDrFFKl4MBXbpmfOSyrsXcVFTVMxXyqOTMWzUzFFKlJK40h2KmJLpOKqqaBsFRezTEU8qTgoFXVO46DCoyREsXPnzhkbFR6nIqok4JA4depUtCefPnLkSGxLvpvOYkcYotNvVS5ASwIQJMCRzgAVfu0UKe0WE09ngAreJ+GLqrxO6cx2i6Jebowx5hYsoiLp5PcpxpCv0Lmm85CgvU65l4rUU55I55Vyd+qjI7xUldeJ5kdjTvtFsaEjAEFnlfY2xSm6KxApT1Mf5KePP/74jO3WW2+Nbek+lAQqKHdQrk/rRHMh4ZDkv4cPH45tqdh5Olt0Djv7Reu/GvmnI2ZBe5juFnS2OmI69Dxaj3S20rw7AgeXK8kHUsylfEJ7RPE5QYIA6Q7TLQKfzk5HtKIqz5F8Nq1nV0Qi5RRaZxI+S5BoAt1Dkp3yMcW/1J7iO60p5YkECUA88cQTMzZ636L3wdQ3rSn1kYQa6E514MCBaE/tH3300diW3tPTuaB32CTqQOeQ/DTdJbuiWin/0JmlvtO4u32shohEyscKUYiIiIiIiIiIiKxz/GgnIiIiIiIiIiKyYPjRTkREREREREREZMHwo52IiIiIiIiIiMiC4Uc7ERERERERERGRBWNN1WOvuOKKqC6VVHZOnz4d+yAFyKRMQ2o1pJaSxkYKqB01S1JW6SjQdhSOSBWISGpbpEDbUTMkFS9SzenMJanS0TNJ4Yj8IPkNqcGR8ktSvCHFJxpfUrEhlVhSqppX6bKK1XvSenRUI6vyvpDSXJoL9Usq02lfSNmJ+khKaNT23Llz0Z72lvaQ5kjnJUGxJil3Jj/oxo7LjaWlpbgfaS1JaYsU9tJZJeVRUsROfVAs76o3dtp2Ynk6q9SWYmV6Hs2703dnLQjK3WRPdw6KGZQHk3oczZvi/t69e2dsFKM2b94c7SlvUv6h/Urnjc4Q5cGUr+hu11F37qrbJzpnqJv/0xnvxvjkp3SX6dx1SU2aYl4aR7JRjpbvk9aoo4BKPtRRTSb12ASpeFM8otzWaZvm3nkP68b95Pe0/nR20jsNza8zF4rZ9P6T9ovu+/Qukd716Z0tKQ5XVe3YsWPGRu+lNMcU6yjGkD2dF4qVnfhH7x10PtOdtKNETD5Dd92O6nNH1bx7l0l587rrrottKdakudAeko+lO2b3DuFP2omIiIiIiIiIiCwYfrQTERERERERERFZMPxoJyIiIiIiIiIismD40U5ERERERERERGTB8KOdiIiIiIiIiIjIgrGm6rHnz5+PajikGpYgdaKkIkQKI6T4cfjw4RkbKTeSSkxSAiFVlE4fpCKU5k2KPvS8tKakTkQKQB3VVlJtS/MmtTRSHEoKL+QzpISzbdu2GRutR0c9lsZMajUJWn9aU1KxSWzdujXakzLTiRMnYlvar3QGSPko+SntIa1p2i9SMuqos9J+k6pVikF0Dml8Hf+g2JbWKalUddSe5PuktaT8c9VVV0V72jtSliL1zKQaSnGuo2JMOYzmmMZNeT7lNjpnHYU36oPWLp1LOk/URxof5cGOqh8pX9PedhTQKb7cfvvtMzaKt8eOHYv2lH8oz5B/JH+k+9CePXui/eDBg3M/r3NPonGQn3ZIa0fKgqSiSerCia7KZKJzT+2o5lblu09qaw57aXTuihQH0n5QvqO4c/r06Rkb+Sads47ya+deSP6d1q6bM9Oa0thoryjnJeidJs2b1p+el84qqZTSmqY+KA/S+8/u3btnbHTff/LJJ6M93e1vvPHG2PbQoUPRntaa1n///v3R/uijj87YyJfofSTlMFJcTXmQ9qoD+S7F/XRPpXF03vXpbFGOpfElaF/mVe2+EP6knYiIiIiIiIiIyILhRzsREREREREREZEFw492IiIiIiIiIiIiC4Yf7URERERERERERBaMNRWiqMrF/1Ihvueeey7++1QkOJGKcldx0d40DirSSAV+U8FOKppIRTzT+Gg9Uh9UJJZIQgNUpLEjGkIFP6mYaCpQScXSO+IBtP5UTDz1TX5HxSlTQUwqvEt9p2KiNObNmzdHe6dAPnHq1KkZG82bCqAmn6QC7akALRUHpbl0BFo6heKpaCitR+qb+qDxpTnSepBQSXrmahRLvxxJRW2Tjc7qs88+G+0p7lDMIIGK5BdUpJliaPILyplU+LdTtDedka6YUsqPFItobKkwNK0dxYwEFfG+9tpro/3pp5+esZHPUJ5ORb/pDkF9pHHTnaqTlx5//PHYdvv27dGe/JFyOp2L1J5yB8XFtE7kp+kuQ23Jnsbcuf9W5X0hYQBa03lFjKq42H86cxRTiOSPab+7a3S5sbS0FON22g86151C8PQO1RH56YiTVGUfoAL4lCc6whyr4XNpnSieUU5J55LiC/Wd9rAjOEXjoNxBggw7duyYsdH7ZyceHT16NLalHPvWt751xpZydFXVvn37Wn0nOiIv9H5M95O0j+Tnyd6N2Z32dIaS/9L8yJfSOlFM6XyfoPs53anSHDtCT1X+pJ2IiIiIiIiIiMjC4Uc7ERERERERERGRBcOPdiIiIiIiIiIiIguGH+1EREREREREREQWDD/aiYiIiIiIiIiILBgXla0YY+yuqk9X1faqOl9Vn5ym6R+PMTZV1a9W1b6qerKq/vNpms5drL+kqpFspA5CailJCYTUQUgtJT2TlD2ojzQ+Uumj8aU+aD2Suh0p7JDSUlIiorGRPe0htaX1SOMgRZmOshOtHe1teiapwVAfSb2PlGZoXxKkdEUk1SJSBKM1JaWwREchjxSwkv+SL5ESXkcBixSO0jhozOQHqW/yaVLiWg0Vs3QGUpzZiMp7q5nDpmmKClVpLWnfSDU0+TipotGZTPtMsYsU0JPProZaF5HyAc2blNVojonOmnbVY1Msp7YdBdSOGllV3hdqS2ppaV+S0vyFxpdi6LZt21p9JPVyyqVkT1Cu6ijCkz8maP0pd6TndVWE01xoHB3FZxoz2dNa0zgox6bz0lFxXs+sZg47f/58VJJOe0d3pnS/pfYU5zrvB6RAS/7Weaeh8XV8Np1VumfTPS/RfQ9Ldw7KdxT/0ppSPqe7czqXtB6k1p3a0/onlfKq7KdPPfVUaxxpjnv27Ilt6T6UzlvKa1V8b0z7QutB+5LyFflj6oPyHY0jrSnlaOoj5baOSjnRzccpBnXGXJX9o/tOP89P2n2vqv7LaZpuq6r3VtXfHGPcXlUfr6ovTNN0c1V9YeXvIiIii4Q5TERE1ivmMBGRy5yLfrSbpun4NE1fXfn/36yqh6tqV1V9pKo+tdLsU1X145dojCIiIi8Jc5iIiKxXzGEiInLRX499IWOMfVX1zqr6k6raNk3T8arlhDLG2Ar/zseq6mNVvV+ZERERWU1ebg6jH50XERG51JjDREQuT+YWohhjvLGqfr2q/s40TbO/oA1M0/TJaZrunKbpTpOFiIi8EqxGDqO6JyIiIpcS38NERC5f5vpoN8a4spYTxT+fpuk3Vswnxxg7Vv75jqrKVRVFREReQcxhIiKyXjGHiYhc3syjHjuq6p9V1cPTNP13L/hHn6uqj1bVJ1b+/OzF+nr++efnVi2iX6Ule/oJiK7CVVI6I2W1riJpoqMKSf0m1RxSBSIFpqQS01Fhqcrjo59KIUWqpExDa0TjS2oupDDaUcKlMZPSWeqb2naUmUi9h5SIkvohqfd0FOi6qm1pDzpK0ORLpIyV/ICUfkghMu0XnUNS4uwo4VLfyfdo7ToKuR0Vs/XMauawaZrmVpWj3EHnrKN43IH2meJROtt0zkgJPMVtart9+/YZGylqkTpb6vvkyZOxLZ2/NEdafzp/6Qx3FLXpmVu3xt96w5ze8Rta06effnrGRj6zb9++aE+xlcZGuf7cuVkxzMOHD8e2FIcTtId0X0g+SXmwo6JJe9hRzeuo95H/k4p9Ggc9L+U7ak/rTP6RfCn5TPfuuh5YzRxWlc9xspFKLO1/8qHu3TnFYTpnnfs3xVuKGak93b+3bNkyY+vEhqq81pTDzpw5E+3pnkfz7ihf07km0vpTDqO5JD+g+Eeq5idOnJixUb676aaboj21p3FQDkvvXE8++WRsS3eflK/oLklrnXyd/DT5Dc2P3qFS310V57TWNG9au/RMOofk62kudIZojukuQ+/uxDxfmN5fVf9FVT0wxvjaiu3v1XKS+MwY42er6nBV/UTrySIiIpcec5iIiKxXzGEiIpc5F/1oN03TH1ZV/s8qVR9e3eGIiIisHuYwERFZr5jDRERkbiEKERERERERERERWRv8aCciIiIiIiIiIrJgrKn299LSUixUmgr/UaFBKoSYijSmopxVVd/61rfm7oPaUiHKVFyXCoFScf1URJKKJqdCiKmgeRUX/Lz22mtnbA8++GBs++yzz0Z7mgsVq6UijangJ82bilbu3bt37nFQAehUcJKKVlIR2zRuKg5KhS9TcdW0VxfqI+05Fe+lAq3J1zdt2hTb0vg6hdHT88inqYhq8o9uAVRajwTNL/kYte0IVHSKtlblQv2pD4q7sswVV1wRBSY6xc87gjTk9+RDyU5nhPpOvkJ5l8axc+fOGRvFvxSzb7jhhtiWijfv379/xvZ7v/d7rT4OHTo0Y6M7BAlzpLWmPE/2TlFzivtpX+geQjG7Ix5A/pGKq1Px5qNHj0Z7ilNUcJrGkXydhBd27NgR7WkunQL5FFvpDD300EMzNir4TXub1qMb41Pf1AetR4pttFcdwQBaD2GWlpZQFOjF0D2D7uUJEkKivtN5oJhBfXfu8NR3ymHXXXddbJsEAd/2trfFthTn7rjjjhnb5z73udj2iSeeiPbjx4/P2GjeHRE3ut/QWd21a9eMje49JIyXxkfnPYlZ0TO77ygp7u/evTu2PXDgQLSn7wjkux2Rl3RXqOL1SHmwI4BHZ5buSUlkgQTaqO+UJyh30FySAGpX5C2tXfc9LPleV+TFn7QTERERERERERFZMPxoJyIiIiIiIiIismD40U5ERERERERERGTB8KOdiIiIiIiIiIjIguFHOxERERERERERkQVjTdVjq7LqVFJR6arHJpVGUvAg1bakgELqOKRikxReaBxJYYfGlxRsqvLakeolqZQk5aP3vOc9sS0pHz399NMzNlKrJZIiFSkOkR8kO+13Rz2G+qB9SSoxNBfyj+SPtKYdFbWkpFPFakb79u2bsZHCEY3jtttum7HRGU+qUXRWOorIXdW8jqo1KREndSFSHCZFxNQ3rT/5aYpjKVaRj8oy0zTFc5nWjVTpSHEq7TOptpF6c+qb4hwpfiVlNGqbFO+qso+TWmdS6aOY+I1vfGPuPn76p386tv393//9aN+2bduM7Ytf/GJsSzE0xQdS6aW9TUpzSUm8iuNAUoek55GaXloPUgeluJPGl+ZXVfXwww9He2pPioNpzFVZTY+U9yin33rrrTO2pI5XlXPHD/3QD8W2X/rSl6L9B37gB2Zsp0+fjm1pHOk+dPLkydi2EycoD9IdIvVBvkR+msaX1DxVlL0w58+fj3ki3b8ph9E9Ib170DsU5YN03jt35KqcD8i/3/3ud0d7Ujsn1d0Ud2h+pAibYtTP/MzPxLa/8zu/E+1HjhyZsd19992xLe1hun/TvOldM70PUtx/9tlnoz2tHz2PclhSAiefoft3OhdpflVVX/nKV6I9zZ3OBSm/7t+/f8aWfLSK55hyGOWDFEf/xt/4G7Et+XTKB+QH9C6Xchh9y6DckaD1J2Xs1DfFJcqP6Z5Ez6M7n29oIiIiIiIiIiIiC4Yf7URERERERERERBYMP9qJiIiIiIiIiIgsGH60ExERERERERERWTD8aCciIiIiIiIiIrJgrKl67BgjKmUk1TxS9iDV0KRydNVVV8W2pF6SFFdIJY5UbNL8SEUoqfRUZWVAUpRJiiukZElKUElxiNQ6ae2Seg/N+9FHH22NL0H+ceLEiRkbqcGRWlDqmxQAaT0SpJJEfSRltKeeeiq2JV8/ePDgjI3UK0mRMvk6qcQldaKqvNa0h0lhh9rSGUrPI2UhUgA6d+7cjI18mvY2jZv2mxQY07jJd0kRjPZcekzTFPcjqUV11EGrcowhdTDqIynk0d6TLyelOIrNFDNS+6RKW5UVyR9//PHYllTDfvu3f3vG9v73vz+2pdi1d+/eGRspC375y1+O9nTeu8qHSTWM7j2kmpegPEjjSHt47Nix2Jbi8Pve974Z2+c///nYltRcky9QrCRF0tQ3nS1S5E1ni+J+Uk9+8sknY1tSIkxni84h5f90tuhu98QTT0R7R/mV/CDFIFKkpL5TbqNzIX3mzWtV/I6RYms3h6X9p33evHlztCcfp3c2ukulcaRzXZXfw+65557YlvLxr/zKr8zYPvCBD8S2FLPTetx+++2x7b333hvtFP8S5B9pPehuSqRcT3tFCqhJcZXiMPX91re+dcb2r//1v45tSb380KFDMzbyJcrpKfaTT9P7UlKEJdXWtB4PPPBAbEv+mHyJ8h2tx+HDh2ds6a5WxTmM7mCJjno55bDOHYJUrQl/0k5ERERERERERGTB8KOdiIiIiIiIiIjIguFHOxERERERERERkQXDj3YiIiIiIiIiIiILxpoLUaRilKkQHxW4pCLSqfAfFfwkcYlUpLFTHL4qj5sKXFIfVJAxcerUqRkbFYWkcaTCkEkEoSqLVlTlNb3lllti2yQWUZXXg4qXUiHctF9UvJn2NvkNFfHesWNHtKdCoEmkpIoLUaZxUBFpEvdIfZN/UWH6m266acZGBafJb5KPdQpwJkGNC/WR9ovWnwq/dgrn0plL46P4k4QvqnKRcfJpEky5+uqrZ2zpvHWKEF+OjDFiUdt0VmmPqHh2J/5RYd3UR9r7Ko5/yWdJcIL8JY2Pzt/DDz88Y0tiDFVV+/bti/ZOEXUSs0gx++abb45t77vvvmjv3CGItOe03yTekAq3U/Fmym2pD9rvzh2HxD1+4zd+I9rTeaG7E+WwNHe6H5KPPfPMMzM2OuPpDP3RH/1RbJt8piqfOcqvdLaScAjtIeWw5I+0/iQYQO0TJESR7OkeaA67OPO+L9H7FvlhiqFUFL9THL77HpaeSSIB1EdaDxLP+MpXvjLXv1/Fgkzpjkt3QrpDpjhAsZnuikncgO4hnfxPfZAvJZEfeqckH0tzoVhJ97J0X7jzzjtj21/91V+N9pRTaD1oLslP6Xy+5S1vifYDBw7M2OhspXn/q3/1r2JbumOm92Pa7z179kR7ugtS7KBzMe93pyr+tpD6oFxF+5L6oDET/qSdiIiIiIiIiIjIguFHOxERERERERERkQXDj3YiIiIiIiIiIiILhh/tREREREREREREFgw/2omIiIiIiIiIiCwYa6oee/78+ai+kxQ1SJ2S1GqSUlxS+6pihavUBynskHpJUqYhNZjt27dHe1I1IYWxNEdSLSJ7miOtP5HUUkgV5Y477oj2+++/f8ZGe0V+kJRwSB2H7Emtk55HKjHJD0hphlSEXve6183YSPmQ+k5KOKT0k55X1VsPUgZO4yDVrvQ8UrYjUt+kFkTrn1R2aZ0pHsyreFfF5zP1TYpg5I/zrgcpbsoy0zTFNUr7TOeMznDau6R+VsU5JUH+TUqbKS5SPiD10hQHjh8/Htum80DzpjyYzgipZFMsSbkmqW9WVd12223Rfs8998zY6LzTmqazSvGF5pJ8j/Id3UOSMir5HSnQJqW4M2fOxLbkS0kZnVTbSZku3XE6qrlVVQ8++OCMjdY0KZLTHlLeTeeWziz5Unom5TA6c2l8lLspf6Q+uveh9O5gvuozTVPc6+QrpI5MOSzF3I4a5oXsCTo7yS/IvymWnzx5csZG8z516tRcY7gQ6TyQajvlthS7SPF2586d0Z7mTX1Q3El2il20TimHUWyge2+K+5Tv9u/fH+0pp5Cq74033hjthw4dmrFRDqP8mMZxww03xLZ0Lzh69OiMjdY/5TA6b/Tukvxx165dsS31nXIs5Q46n8n3KM9TzEt2+j5E75rpXHTiXZU/aSciIiIiIiIiIrJw+NFORERERERERERkwfCjnYiIiIiIiIiIyILhRzsREREREREREZEFw492IiIiIiIiIiIiC8aaqsdWZfWXpF5CKjGkdJLad9XjkiIJqYAkddCqrEhG6iCkXnL27NkZ2549e2LbpIpCCiqkipL6OH36dGzbUUsltbRt27ZFe1KJIeU96pvsCfKDNEfaK1LITeqepDRHKnZpv0itic5F8j3yg9tvvz3akzIQKYLReeko0CalKlIn6ijQ0V51VL5ofjQ+2vMErWnqo6NAWpXPRWpLeyLfJ+1TOlPkE5SXki+T4h2pByf/pFxKeSn5Bfk9nakUW8m/01yefvrp2JbicFLZo/hO5z2dEcrzpDh49913z9hIgZbU9NK4KY5QfkzKe+leUcW+lOZOfkCKfMn3nn322di2o4CalO2qqm699dZoTzmF/JFySlJbTEqLVXlfSBWQ/CCdQzpvFPfTvMmX6Lyk2EZ+QCqTqT2No6PQnvqgeCfLnD9/PuaVFDMoh5HPkppigu7q6W7TVWLtjIP8Jc29Mw66o5FKZnovojNJpJhGdzp6D0txn3JHRz2TxkH5II3vG9/4RmxLquGpb7p/UUxL46Z9IV9KdloPUqBN+0L5f/PmzdH+5je/ecZGa5r8n74LUMym+1qC7iHpHNH9kO60aS6033Qv6Nxl0vtuVd5DmjdhdhMREREREREREVkw/GgnIiIiIiIiIiKyYPjRTkREREREREREZMHwo52IiIiIiIiIiMiCsaZCFEtLS7GAaSoSSMXyO8UiqQ8qrpqgwpJUiDIVTaQiwSdOnIj2VPCYihinApxUpJGKJu7atWvG1hXgSAWBqdBmel5V1Q033DBju++++2JbWtNU5DUV2K2q+uY3vxntac+pj1QAvSoXl6QitlTUNxXqpeKxVLA+7Vfyryounpl8gdpSMfHUxzPPPBPbdoqXkohH8nVafzpbqagpFTql9UhngNqST3cESaj4cSq++3ILLV+OUA5LfkGFtmnvUh/k35R/OgI41Ec6DxR36Awnvz916lRsm4omHz9+PLalvLRv374ZG8XETj6muwIVD06CUV/72tdiWyran3I6FS/vCC+RWERHGIXWjgpRp3Fv2bIltiV/TMXOu8WbU66n3E3jSOtEd630PPLHVByc2tNZpnOY9oXiD4l7dKB7UkfkrSOQ0ykwLsssLS3Fc5n8jd6h6J6Q7JQ7qIh+Ghv5PcXQw4cPz9go/pHIQsrzJDyTzg7lO8opt9xyy4yN7sJ0RlI8orhDfaR1ovhCsSTlMMoRHVEbii9kT/tC758dEbfrr78+tj1w4EC0J2jetE4pp3SEF6qyT9PdIt3B6BsCCXOl3E35n76HpHfYc+fOxbZ0l0niEp27E7Wn9e/kMGpL+JN2IiIiIiIiIiIiC4Yf7URERERERERERBYMP9qJiIiIiIiIiIgsGH60ExERERERERERWTD8aCciIiIiIiIiIrJgrKl6bFVW8UgqXqSCSIqfSQGF1EFIATUp9ST1kypWlU1KPTQOUmJJioGkipLUmpIKEbWtymo1tEak2pJUhEhRhhSRkqoMKW2SqmJSx6G57N69O9oTNA4iKWaRz5BqUdovUkkiZaykdkVqQaTIl84sKQOT2lhSyKG5JPVKGnMaW1U+c0lRrIoVwdIeHj16NLaleaf4QYpnFCeSmiH5DCkfJqW2pMim8t6FWVpawrVPbTskX+6oUFF7Otc0vqRARwrXlA927Ngxd9t0Rt797nfHtjTv5Lc0PxpHigNJ2baKFflSHKBzTaqKKV+Rotz+/fujPa0pxVC6h9x1110zNlrTrVu3RntaD8qlpOr30EMPzd0H7UuaOym/0p0v2W+66abY9rHHHpuxUb6jXJryP8X3gwcPRntSVb7//vtj207+J3XCTv4gX6I5dtX+JDPGiDGmoxxPe5f6pTsaxaOOEjvd7dM9jdoeOnQo2t/ylrfM2ChmpPH9wA/8QGxLcSDdC+ks0DieeuqpGRu9Kz333HPRnuZCMZHyY4oPtN/0HpYUa+m7ACkAf/jDH56x0R2CxpFyL93LKIfde++9MzZSoKU9T7GV4j7tebqX0R0irTXdQygfp/dS+oaT8nxV1c033zxj+9KXvhTbdmIKrXPn3k5tKT+ms9V9T/An7URERERERERERBYMP9qJiIiIiIiIiIgsGH60ExERERERERERWTD8aCciIiIiIiIiIrJgXPSj3RjjtWOMu8cY940xHhxj/P0V+6YxxufHGAdW/rz20g9XRERkfsxhIiKyXjGHiYjIPHJM366qD03T9KdjjCur6g/HGL9TVX+1qr4wTdMnxhgfr6qPV9XPvZRBkIpHHDCoCHUUh0itKymukPIRqaikZ5LSDCmdPfroozO2pPpSldXBSMGro+xF6kSkOJRUc6gPUk9Kqj6kSkNKUGkPaa9IYSftF+1VUj6uyso7pDRH/pFUZUiRN/lMVVbqoeeRElFScSI1qaQAXJUVg2kcSYk42ao4dqR50xqRH5w4cWLGRrGD/DGNj+ISrWlSd6SzTCqf8ypg0fzWOauaw5LKXkf5lUhKm+T3tP8pttIZob1OMTfFgAv1ndTcrr02v08mO6lvJRXkqrz+pAp45MiRaE9nh55HCnTXXXfdjI1yGK1dUvEkhTGKJclHuzEjqem+4x3viG1JebSjqthRBkwK41U9RXJaO8qxySdJNTypKpJqHql2Jvu//bf/NralvPvII4/M2Ojcpxxdlc8W+T+d2+S/5I+UB+ke92LMYRfOYdM0xdyUbOQTFLuSIj3djSg/pvsY+Qr1keJAimdVHONTe1IYvf3222dslH8oDqS5JBXqqqrHH3882tPaUYwi9fJ0fijekh+ks0rv0rQe6c5BMftNb3pTtB8/fnzG9v73vz+2JeXRFOv27NkT25I/PvDAAzM2ej+me1KaC8Xbt7/97dGe7j4UV9O7LbXtvPf95m/+ZmxLa/rVr351xkZ+QHEirRPNhfx03nt/FfvSanDRn7Sblvnz29SVK/+bquojVfWpFfunqurHL8UARUREXirmMBERWa+Yw0REZK6admOMK8YYX6uqU1X1+Wma/qSqtk3TdLyqauXPrZdsEWEUwAAATW9JREFUlCIiIi8Rc5iIiKxXzGEiIpc3c320m6bp+Wma3lFV11fVe8YYd8z7gDHGx8YY94wx7un+upCIiMjLZbVyGP26kIiIyKVitXIY/UqXiIgsNi312GmanqmqL1bVj1TVyTHGjqqqlT9Pwb/zyWma7pym6U76PWQREZFLzcvNYVSfR0RE5FLzcnNYqjsnIiKLz0W/oo0xtlTVd6dpemaM8bqq+k+r6v9ZVZ+rqo9W1SdW/vzsPA9MRS5TkUD6wNcRl6C2lLRSsVwqitsRD6BinVRkPBUxTEUoq3KxUypkSeuRRBbov8ZRwek071SMuYqLNKb1oLlQcdVUEHP79u2xLflBKnxNxbrpJX7v3r0zNip8Sfbke7SH733ve6P94YcfnrFRoeZz585Fe9oXKoB66lS8M0YxBfKl5HunT5+ObamIcDqftM5pbFXZT2m/qQBqmgv1QcXmU3v6iS/a2+TryZc2YhHv1cxhzz//fCycnGI8+RvFv7T2VKS+U4iXzirF0ORvlA/oXKb2dM4OHDgwYyM/JEGMNG86kyQMkWI85f9OYfQkFlXF5z3NnYo0Uw5LfkPxloR47rrrrhkbCT10is2T3/3gD/5gtH/5y1+eq98q9vVOYfSvfOUr0Z7yYCcfdHJEVRb9opiSRJOqegJtdMdJ53Y1/gM8CY907kPpDNG5Ws+sZg4jIYrOT+DRGU590F2FYmtqT+9KHSEeipV0dpKd8s9DDz00Y6Mc1rkjd8Q66JkkOEHnJN1lSAiR+kj7Re+DtB7JxyhG0Rw//OEPz9iSWFQV+0eC4v5b3/rWaE/++K1vfSu2JbHHdG+hWJn8sSqfT3rHTueTvmXcf//90Z7ez0g05NixY9Ge4kE3h6XcS3drioPJ10lMhO5ayU6xlJgn8+6oqk+NMa6o5Z/M+8w0Tb81xvjjqvrMGONnq+pwVf1E68kiIiKXHnOYiIisV8xhIiKXORf9aDdN0/1V9c5gP1tVs5+xRUREFgRzmIiIrFfMYSIisvF+jlxERERERERERGSd40c7ERERERERERGRBcOPdiIiIiIiIiIiIgvGy5eAukSQClhHNY+UVUjVJ6mGkKIMqYOk8ZHCJanYJYUWUh5L46CxdZQhacykbJPWmtTBklot9bF169bYltSCkp3Ugl772tdGe1KgIaUZUlVKfZBqJClEzav4WVW1c+fOaH//+98/Y7v77rtjW1IzSv5IKj2kCJaUsR577LHYNs2RfIlUnJKdYgrtS5o3PY/UzRKk1kTKTEm1iBSHOmc89bERlfdWk/Pnz8dzkhSuKIbSOUtnmHIY5YPUN/km9Z3iM8UdUrFL551yR7JT3KezmpSvaY2SOnhVjvFPPPFEbEuK5Gn9Kc+Tml6KD3TeaRxp7rSHt9xyS7RTTkmQT6dx0zhuvPHGaP+rf/Wvzth+/dd/PbZ95JFHoj0p1nXV3JPvPfnkk7FtisNJdbqKz1BHrY7idrpbUI4m9fjkS6QISnub8je1JV9KuTfd4eiuJstM0xRzQlr3jkp2Vd4PujORSmPyLbq70R0+0b07p/NAvpn8m947KJan9pS7af3Tmj7wwAOxLc073UM3bdoU21KsTO9hpNL79re/PdoTFOfuvPPOaE/K7eQH5GOdezLl9L/21/7ajO3Tn/50bHv06NFoT/5Bc6FvAKkPel66J5F6MuWUNL4zZ87EtnS3S2eA4hLdMem8JGguyT+oLZ3b5Dedd7Yqf9JORERERERERERk4fCjnYiIiIiIiIiIyILhRzsREREREREREZEFw492IiIiIiIiIiIiC4Yf7URERERERERERBaMNVePTaofST2DFDVILSWpg5DSD6n6pD5IdYSUTpLSDKlZkZpYUiQhNb0EqTWRit2xY8dmbKTKRPNO+5IUBC9kTwpvd9xxR2xL6ji7d++esZEqHfnS8ePHZ2ykBkN9JAUsUryh/UprTaptpGa0d+/eGRupJ9J5efzxx+d+Hqktp3WifUl90Fkhxbs0F1pnWtOrr7462hPJd6ty/CA/IPXYBCmQ0fqn9l3VIlkmxfOkuEoq2RRb0xkhv+r4JuWfbjxKnD59OtrT3ElpO/k9+SbF/aTySsp2FHd27do1Yztw4EBsS3uYztnNN98c25IiXxrHDTfcENt21pTuMpTbkvpxN2YkP6V9Ib/7C3/hL8zYaO1IPfbRRx+dsZF6JY0v3VtuvfXW2DatKd17KIel8dEdjmINqdslaE2T2h/5TEe9r3NXqMpxjPZQLkxa45QP6E5IcaCjErwa72FEiiV0z6NzmWJoUkWlvuk+R/NOOYyeR8qv119//Yzt4Ycfjm3f+MY3Rnvyg7e97W2xLSlfpz3/oR/6odiW3m2TWifdZWhvUw6jeXdyOvk/5bAPfvCDM7bO+3hV1cGDB+ceB80l3ddIPT6p/dK9k1RlU4ynedM7XpoLxRRS7z18+PCMjWIKzSXlGrpDd+743djmT9qJiIiIiIiIiIgsGH60ExERERERERERWTD8aCciIiIiIiIiIrJg+NFORERERERERERkwVhTIYqlpaVYhDAV+OsWmE3Fg6ngZCpOWZWLB1JRYioAmezXXnttbEtFtTts2bJlxkbFIklEIhXKpnlTkcZkp2KpqcBlVV47KrRNfaf16IgEVOVCmZ22VbngJBVLpeKlyX+pWCcJQ+zfv3/GRsWiT506Fe1prakQaCpaXZUL5NL5TAV8qcA4FepNZ/zIkSNzP68qF9umQridwqgU20hcItmpACr5aZpjmgv1K8tM0xT3LxVNphxBReOTQAz5G/WRYjzlmTTmqly8ngrPEykuUt5Nwgvbt2+PbanA71133TV3WzrvqWjyO9/5ztg2FYWuyuuUxlbFIgYpllB8ob1NfkDrT3EnrRPlH7rjpKLrFGPI15MvUB90L/jwhz88Y6Mi+7S3KV9RvE3ju/vuu2NbEttKRf2/+tWvxrbk62mOtM6dOzfNu9MH3Yc6wijJRxWnuDjJP5ON3gMohnaEKGj/U+wi/+4IotHzKE+nPEiiMUlMId29q3guSayACusTqe8PfehDse3Xv/71aE9r+r73vS+23bNnT7Sn+wnFbPKxZCfREHoP6wiSkJ+muN+Noem99P3vf39sS+9n9L6UoPelNHfy6dT2S1/6UmxLvp72/MEHH4xtO/c1yhEUl5JPd0VNKNZ0+kh5s9NvlT9pJyIiIiIiIiIisnD40U5ERERERERERGTB8KOdiIiIiIiIiIjIguFHOxERERERERERkQXDj3YiIiIiIiIiIiILxpqqx44xolJGUvohZQ9SGOkoRpHSWVKaSWOrYqWZjtIJqYYk9dekvlmV1XtobKSimpSPukqnSVUuKUlVVd1www3Rfs0118zYbrnlltiW1i4p4ZFKIq1TUpMihSkaR1LNoecllaqqrDRD/k97m+yktPTkk09G++nTp2ds5B9pD6vyvpBCZFIXJuWkAwcORHvyx64SZ9oXUrrqqJslRcUqVnFK4yafJlIfaU/Iz2WZaZri2qfzTkpWpO6dchgpfpJqaNo/UnokkhI4xSiaY4oD+/bti23f8pa3zNhI0ZRICrSUqyhmpzhAsYFU/dLdgtRBN23aFO3zqmRW9ZTHumc73X06CntVOV521Lqrsi/QfYjUbZMyOp2hd7/73dGe9pxieXoeKZ0/9thj0X7PPffM2OjuevLkyWhP55b2kFQL01lOCp9VVU888US0p/hIcYnu3Mk/zFd9pmmaW8WQziTtUbrz0x6l944/H9+LIeVRUoBOMYb8nvwwxWfKYW9+85vn+vdpbFU5ptE5o/t+WifKgxSz0z0kqZ9W8X0/zZH2kHwp+SP5Er3/p/xD7wG0TgnaQ7qXpzjcXdM0R5rL2972tmhPa03Pe+qpp2ZsO3bsiG1JEfa+++6bsdG7En0vSPmffJfUhdMcqY9HH3002hPd/JPOAO0h4U/aiYiIiIiIiIiILBh+tBMREREREREREVkw/GgnIiIiIiIiIiKyYPjRTkREREREREREZMHwo52IiIiIiIiIiMiCsabqsURSeCFVNFKxSyo7pFZDfSd1IVKLJOWjpB5DyjakmpPaJ3W8qqweS2pINOadO3fO2JKCYBWr5nQU3kithuaYIJWYBCkAkjJTmjupOBJJoZVUc8hP0zOpLanKJYUc8gNa/6Qqe+jQodi2o+rbaUtKP6RAm9T7SOmHlLgo1iTIlxKkeEbnglSVEqTqm/ymE3fl+6Q8kWIunVXKB8nfqO3TTz8d7ek80J6S8mVSsyIVQTp/Z86cmbG9613vim1vuummGRudEVJtTXMhRU1SiUv5mPI/KREmtXNa544CNOV0ysdJCZRyGCn1JpVjmjcpoCU1V+qDVM3THtDdifJEemZSRa9i1cfkN7QvqS3lmRtvvDHak6rs17/+9diWSP5BPkO+nu5DlJNo/VN7eh7FzeRj5AfCjDHiuqUYT/7dUeskVWLKKel9hO7OpMCZxk0xivpI996Uq6pyHqR5p3e2qqxMS33Q+qd7KMVbyj8f+MAHZmwUu+j8dVTsyZ5iBsWdzncBug9R32ku9C5B9uR7tC90P0n5++zZs7EtxdakmN55pycFdBpzek8khXEi+Qf5P+WOEydOzNho/Wnt0ncEujtRbEvjppxJ+IYmIiIiIiIiIiKyYPjRTkREREREREREZMHwo52IiIiIiIiIiMiC4Uc7ERERERERERGRBWNNhSiuuOKKWGw9FWmkIplUTDRBhQapiGEq4p4KKVdxwclUEJPGTIWhUyFWKlaY5rJ79+7YlsQKUrFOKsZIxTrTWlNh/U4BTipSSsVEz507N2MjIQoaRxK5IJ+hIp7pmVSQvFPMulOAltp3fLcqF+amApzkH6mgLp3xtLe0VySqkQrCk3gJnfH0zL1798a2VDA4PbMjWlGVizBT4Vfyj7SmO3bsmLE99NBDrbFdbrzmNa+JBaPTmaIizRRbKZYkKB+kWEJnkvJSmgsVAiexh+Rb9LwkGpPWmPql8dGY6aym9U+5uIrPcOqD9oricBIZSWtUxYWX0zg6batyEWkqRE17m/qmuaQi2VV5rSn/UPxL8ZJyB/WRoLXrnKEk+FFV9Y53vGPGRmtHxb3TM2kPSZgjFdWm/aY8TQIyCcrH6b5w8803z9iOHj0697MuR17zmtfUDTfcMGNP8aEjClLFAkIJyoNpnzu5sSr7PcVsOlPp/YXm99RTT83YSGCGhC/SelCMojOS7nkUKzsiHiQS1BGCIdEEErlI4yCfoXEcO3ZsxkZ+QPkn5QPyRxpHiqF0L+t8+6C9pbtFei/tCnYmKLelHEYiasePH597HHQPTO//VXlNad6Uw+i8JGhv0/q//e1vj22TEE6VP2knIiIiIiIiIiKycPjRTkREREREREREZMHwo52IiIiIiIiIiMiC4Uc7ERERERERERGRBcOPdiIiIiIiIiIiIgvGmqrHjjGiildSVyOVmKTwWpVVWzrqeFVZpYQUV0lhLKkLkXocqYaluZBqURofrRGpoiQ1HVojGnNaa1p/UktNqn6kSkPr/8wzz8zYkoJQFc+xo1BMKkJp3LQv5GPJH0mdiNY0tSd1IiIpFJHyMSkOJb+hvU1+Sn6XVLuqshLUbbfdFtuSal7yMTqHSR2qqheXiLQepBpFZzw9s6MwKcssLS3FeJ4UllMsqmLlt6TeTPtMSs/JDyk2kD31TWeVlN+SH5LicTpTtEYd9ViKRXRG0trReaD4lxQHaZ2pj6TaSuqgpHyYlMpp/Wl86V7QUbajvkk9jvYlzYXuVKQMmMZBdwja85S/ae3SuaWzQrkj2cn/O3mJfKajZki+RPa0tx2/o76PHDkyY+sqjV5ujDHmVtumGEX+ls4UnTPKbSlv0l2d4lG6L1J8oViS7m6UB1O+evbZZ2Nb8s90HrpjTlBsprkkO61zUsOsqjp48OCM7cCBA7Et+UFSbqf3HxpHak/vYTTHtC90P6G5pNhPeYa+fSRfoDFTTkmQP6Y4TH5H8SD5Hr2HEWkupDRLc0nrRL5E5yLdJ2kPaZ3S3ZrudoQ/aSciIiIiIiIiIrJg+NFORERERERERERkwfCjnYiIiIiIiIiIyILhRzsREREREREREZEFw492IiIiIiIiIiIiC8aaqsdeeeWVUf0qKUBdddVVsY+O8mJHBawqK4yQGgmp9yWVGGpLiiukTJNIKiWk4EUqTh1VGlLk6+wLjSONm9aCFD8ff/zxGdtDDz0U2yaF0aqqLVu2zNhIxamjpkdzOXv2bLQnXyKlWfLp1AeptpGvJ+Uu8mlS+Up7e+7cudi2o/RHinzbtm2bsdH8aO1SDKJx0B6mvmntKF4lO60z2ZMi1fbt22dspH4ly1x55ZXRt1IOS3Gkiv0w2Sne0j4nnyUVW9rrpJ5F8Z3iXzrvSQW0qurd7373jI3OCKnE0blM0PqnOdI6Uz5I7SnOJZ+pqnrggQdmbKS8t2fPnmhPymi03x0lPIq3pLjWUTPuqLmROhv1neiqx6cYSneITg6jee/atWvGduLEidiW1NX37t07Y6P9TnenqjxHmgvdaVMepD5oD1MsvP3222dsXTW+y41Xv/rVdf3118/Y07pRzCa/T2qzHSVL6pviPuXHdKYoV1GuSX2nO1NV1Qc+8IG5xlDFfp/OJfVBpDFTbKb3xNQHKU6TQu79998/Y7vnnnti2xSjaHw0ZvKxtLfku+RjKU909rAq5yval46qefc9IN1bOqryFJtpLmlvSaV88+bN0Z7uOPS+Rfek5Af0vkX3Q2qfoHfKtC/p/luVz1CVP2knIiIiIiIiIiKycPjRTkREREREREREZMHwo52IiIiIiIiIiMiCMfdHuzHGFWOMe8cYv7Xy901jjM+PMQ6s/JmLbYmIiLzCmMNERGS9Yg4TEbl86QhR/O2qeriq/rzi7cer6gvTNH1ijPHxlb//3IU6eM1rXlM33XTTjL1TtJcKTqYikq973etafaRiilTgd9OmTdGeCj2mAsZVXNQ5jZuKRaZi0VQAvVOImooxdwqjdwp+V+VCsVRwkgq0pvWndaZikcePH5+xbd26NbalwqNpncinDx06FO2pWDAJtFBh7lRAlgrvUpHRtLedAvTUvlPEmwre0tm65ppr5u6DinuT7yWo2H+KKTTmTuFiOofkH2kP0/OogO0GYVVy2M033zxjf+SRR+YeRKdYPp3VVPC7KuerJP50ob7T2SGfpfyYYi6dv1QAff/+/bFtiolVXNw4QeeM8kGHNEeKI3TW7rjjjhnbzp07Y1sSxEjxiEQrKE+n+wIVYz58+HC0d+4yVMw6xeeuqEO6c1DbjghKR9SJnkf3suSPVKybilZ/9atfnbHROtP5TOMgv6M7d9ovGgedi3TGk/BFp2D4OuRl57DXv/71sfj5ww8/PGOjdyW6w6e1p3se+Vu6K3YFmVLOo/ciym1J9I3WI93h9+3bF9smIauqfM5o3pSr6FwmSDQmxS66b1BMS3ekdK+o6r2nkxBfJ5ZTW/LHtAddscckOkV3GfLp1Hc3h6U9Jx9L77YdocGqnB9J3ObBBx+M9rvvvnvGRmeW3sdTTKG8S/YU8yiHUQ5K46B3R2Kun7QbY1xfVX+5qv7pC8wfqapPrfz/T1XVj7eeLCIisgaYw0REZL1iDhMRubyZ99dj/1FV/d2qeuHnw23TNB2vqlr5M/8okoiIyCvLPypzmIiIrE/+UZnDREQuWy760W6M8WNVdWqapn//Uh4wxvjYGOOeMcY9nV9hERERebmsZg6jXykRERG5FPgeJiIi8/wC/Pur6q+MMf5SVb22qq4eY/yPVXVyjLFjmqbjY4wdVTVbPKuqpmn6ZFV9sqpqz549uRCCiIjIpWHVctjOnTvNYSIispb4HiYicplz0Z+0m6bp56dpun6apn1V9ZNV9QfTNP10VX2uqj660uyjVfXZSzZKERGRl4A5TERE1ivmMBER6ajHvphPVNVnxhg/W1WHq+onLvYvLC0tRaWYpHxJajWkWpnURKgtKaukcZBKEimupT7oedRHUiQhddCkFkm/wkXKQsneVS1K6jGkpEN9JMUVWn9S/EwKb8S5c+eiPSm00fNIJSbtIe039XHmzJm5bBfqIyk2kQIWkcZNe0j2pCLUaUsKwKRa9Nxzz83YyKeJtId0tmgciY6yUFU+A6RaSGpSSX0yqTh15rEBeEk5LMXz7du3z9i6imuJ5MdVrMSWxkHqVOTLKadQHzTHlOdJlSspc5MKGMW/FEso/1AcSPtC54zyUrKT4ufBgwejPeWwjrJqVfYD+rU4Uu9L60Exm/w07VdXzT2p7FEOo7lQ7k1QDEzPpJid7HSHo+el9SCVXoopSd2Z9opI86bnUW5LZ47OON1TU8xLOawTXzcA7Rx2xRVXRF9Mcfj06dOtwSSfpTv5pk2boj2dYYpzdK6ffvrpuWxVrICe8jypl6YYT2OjnJnOCOUZymGpPcVVOifJTvNOyu9V2W9oPR555JFov+WWW2ZsdA+h2JrWg9b/sccei/YUy+n+RfakGEx7SDks3dc63yGqcq4h/0h9k2or2dPa0b2H/DHFJfIDumOmu09Hab4q5zYaR7pDV+W7D8VBovXRbpqmL1bVF1f+/9mq+nDraSIiIq8Q5jAREVmvmMNERC5Pej96IiIiIiIiIiIiIpccP9qJiIiIiIiIiIgsGH60ExERERERERERWTD8aCciIiIiIiIiIrJgvBz12P7DXvWqqEKTlE5I4YpUOZLixxgjtiXFr6Q8QgojpKaT+iAlF1LJSmpGpM7y7LPPzthIjayjoEbKNqTaltaU5keKfGl8pDxFe5uUcEg1j1SEkiLMjh07Wn0kfyRVmpMnT0Z7UvykuZBCcdoX2luyp32hc0G+l9qTImJST+oqrqY+aP1JPSypT9K8ydfT2acYRipOqW9SmKK+51Wk7irsXm685jWvqT179szYkzrYfffdF/sgH0rKUnv37o1tKe4k9TKKDR2VRlJFo76Tv5GyV8phpKhF8059UyyinJJiK50zymFJzZJUbGmOSXGVVBxJvezJJ5+csd1+++2xLeWUtKZ0L/viF78Y7UnF9rbbbottU76r6ilakyJyspOqL91xUg6iHJbuJ+QHpGqZfP348eOx7blz56I95bY3vOENse2WLVuiPeUUuo+SP6a80lVmTvuSzhDFNVnmyiuvjIrMSaXx8ccfj33QGqd7Mvkb+X3Kg9QHxfKUjym+UN8pPtB7XzoPFBtozOk+RvdeyoPpTJFaN8Wjjoo63TeTfxw7diy2PXv2bLT/wR/8wYztAx/4QGxLcT/twalTp2Lb3/7t3472Xbt2zdje9ra3xbb79u2L9uRjdA+kvU33JPq2QDk9vcvRHSfd7egbAr3DpjNOKr3kB+kOQXeCtFdVVW9+85tnbOS7NI6U0+lc0L6k+1O6M14I39BEREREREREREQWDD/aiYiIiIiIiIiILBh+tBMREREREREREVkw/GgnIiIiIiIiIiKyYKxpxdYxRiwMmQp7UzFaKvyXChNSAU4SMUjFG6l4NhVCTMVyqVg+FXNN7amwYSq4SvNLhSyr8lxonWnMnaKVVDQ0FVmmYp2d4t7kS7SHqeg3PY+KzXaKmtPepkKZq1FcnQpw0lqnYrg0l47YAxX8Tn1/85vfbD0vFQym4rGp0GkVr2mnbRofnYujR4/O/Tzqg9YjxbG0J+QDsswYI57B97znPTM2EjihYv6p3654QIpTFLOpeH0qGJ2EDaq4MHc621QkOJ0/iolUvDytKRV07gi+UK7qFAinNaIYmgQBKP6RmEXyAxIJINIcOwIcVbm4PY2ZcmkS5iABFNqXNG7yA7rzpfFRvE3CC+RLHTElKsR+4sSJaE/+SPdDult0RDWOHDkS7Ynu+qc9T3d8c9iFGWPENfrhH/7hGVsSrKjiYu3JL1IR+Kqqw4cPz91HtwD+E088MWN78MEHY1sSpEniEm95y1ti2xtuuGHGRnGO8m6Kzx1Rlqp8duiuQH2n90S6Q5A9+U1XEDDNkfI/xaOUDyjepu8QVVkMjNpSHkzvlPR9gnJYisPkB53vJNRHihFdQZh0t/vIRz4S25JASNpz2u+OQB/5Ab2HkfhSguJVWr+O0FaVP2knIiIiIiIiIiKycPjRTkREREREREREZMHwo52IiIiIiIiIiMiC4Uc7ERERERERERGRBcOPdiIiIiIiIiIiIgvGmqvHJgWOpLRF6iCk+JHU40hphtRZ0jNJAYgUqpIiDKmOkFpa6pvGkRRlVkMtiFRiSPEr7QvtFSnNJPUkUmEhZca0pqQOSgo7HZW9jsoxqbaRumBHVfnQoUPRntSdOmp1VVXXXHPNjI0Uh0gJJ/kN+WlSiUtjqOIxJ5+mtnSWk6oV+SMp3qVYQ+phSaWK+qDn0RyTQlpSuiI1MFnmVa96VVTETLmGFB1JRTL5Fp1rOsMpbic10ir2++RDFHd27Ngx9ziobYp/NO90V6jKKoIUiyjvdhRGKZanPuhM0f0kjZviH/lSWn8aB6kZpzhFeZfuJ+msUAyl9UixjtR0yafTvnTU0qtyviI/6CiY0l0rPY/6JXtHAZ3ycSKpc1ZxXkpzpBhGfSRfMof1ueKKK+J7SrozkcIrqQSns/2Vr3wltqV7UPJlijsdVVOK+5SXktr5bbfdFtsmtfOkwl7F74PHjx+fsVG+ozOS7uWktE0xI+U8Gkcac1We47Zt22Jbired9zBSoE05hXLVzp07oz3dnTvrX5X9keZHPp3uBbSHNL4Uc2n90/Mod5OPpTlSzqQ8SO0TdIdIue3gwYOxLd2Hkt/QvZjOePoWQeeC8CftREREREREREREFgw/2omIiIiIiIiIiCwYfrQTERERERERERFZMPxoJyIiIiIiIiIismD40U5ERERERERERGTBWFOZpaWlpajgk5TRdu/eHft4/PHHoz2peJCSC6mUJAUUUgche1JzI6UzUoRLil+kaHLjjTfO2K666qrYtjNmUqWhPpJ6EikOJZWqqqzwRgpTpBaU1Flo7TrqZR3V4qrsS6RESCqHSann6NGjsS31nfaLFIDIH5PyDqk7kyJvUnkjhZ3UB60zKTAlnyZ1PBpHUlUiJaOOmiStM6lGpZhJY+74QVojUpKSZZaWlmKsS/nq1ltvjX18+ctfjvYUY2g/SRE2xdyO0mxVjv1dNfGkzEVKp0m9j9QCz5w5E+3pnFH+odiV5kL5jvpIZ5UUzei8p/xDOYLibYrxFPdPnToV7WkulHeTwl5VjnWkOEjxOa0HqWSTvaPe11Gs7+QOupfRPTXdk+i8ESkvpfhVxfNO99d0z6ri/EHxI0FnPPlB6pfOvSyztLQUz0na09tvvz32QffQ5Muk2nrHHXdEe7rr0TsU7XVSJKfzR2fqkUcembFRPrjllltmbKSoefbs2WhPeZqeR3E/nT9636KcklQyKXeTSmkaN8Ud6iNBe3X69Olop3yQSGrBVfl+Qu8jdC9I+Yd8l3JKguZN54XOQCKd5XSuqtiX0vg69y+C5kF+ms4czYXObfIl2ival3TnoLsuYXYTERERERERERFZMPxoJyIiIiIiIiIismD40U5ERERERERERGTB8KOdiIiIiIiIiIjIgrGmQhTTNGERwhdDRQmpSCA9L0GFQFNBTCo0SEUMU7FNEnWgAq2pyDi1JcGOBBVpTMIXVByZCiymQpRUlJgKc3cKsVLR6jQ+8plUYLQqF8qkwrvkS2ncVIx527Zt0Z7mQsVLO8WXqYgtFVdNvkfCCzTHtB5UgDMVwiWfoQKoac+p4G2nACq1paLyqXgprT+taYpBb3rTm2JbOhepyHjql8Ygy4wx4llL+09iEe9617uiPfl4is1VvM/pPNA5o73eu3fvjI3yHZ2HnTt3ztjo/KXxUQHpJGhTlXMHzY/EjVK+6opZpKLfdIegvJTWidaO9iXF22PHjsW2lNNTsWcS0aFcmvZl69atsS3FxQ50XtL5pOdRLE9njgQZOgIJNOZ0Bugs0x0zxQN6HuXudKelexnd+dJZ7NyhqQ9ZPZJ/Ury96667oj0VWqe7G+Ww9EzKpVRw/6abbpqxUewi0p2JfDPFcsphJNqTzjDFKBLR6dxlqe8kBEP5pyOIRueXfCytx0MPPRTb0rttGh+JGLz5zW+O9pTDaMwU/9J6UMwm4bC0fnQPofOSxkE+naAcQQJVKcZTfiXS2eoIsVTlOwcJL3X6Jj+gderOPeFP2omIiIiIiIiIiCwYfrQTERERERERERFZMPxoJyIiIiIiIiIismD40U5ERERERERERGTB8KOdiIiIiIiIiIjIgrGm6rFjjKiYkhReSJWDVE07ykCklpLUfkhRk1R6kvIIqZGQeklHLeX48eMzNlLpIeWSpLzTUSOryioxtHbUR1KTojUi1ZzkH6TSR+pVSd2pq7ia1GNILY3U3NK+kGob7W1aJ1JPpDOUziep2JGqadpz8oOkyEvqROQfqe9uH2m/SEWL9iWdRfJHWtO0h+SPtKbpPCely3nVvS9XlpaWovpYOu+0F5TD0hmmWE4+lBQASWGPFOiSehypZJNqaFLvI/XMpJZGz6NYmeZIa0fjSPmfVNspZqR7AanBUcxIfrNr167Ylu5JaRwUm+nMp/GRWiqptiVfJ/+n2JrOBY2Z+kh2OkM0vuRPlEuT2jz5EuXuND7qg9QT0zqR4iPdi5OvdxVok39QXOrsYVp/c9iFWVpainud4k6K41U5R1TlM0IqqqTimeIOnTPKE+luT/kuKZ1XVd14440zNjqraXw0Zoov6TzQ8+gMpzPSVazsqNhS3E9xiuILxZI0R1IeJ4Xi9MxNmzbFtrRfKZdS7qb4nM5Wt49kp7b0rpN8gcaRznj3HSqdfboXp/eRqnwuqA/KP2l8lCc6d2s6F/Qul9aD8iDhT9qJiIiIiIiIiIgsGH60ExERERERERERWTD8aCciIiIiIiIiIrJg+NFORERERERERERkwVhTIYorrrgiFrtPxSKpwPW2bduiPRUxpIKfVIAwFZykIqpUVJMKIXZIBQ+p0GMq4knFQakAdypiTMVLqRBlKshI60/jS3aad2d89LxO0WQqLLl79+5oT35DYz516lS0J0gghNYpFfulQs9UuD31TQIcdLbS+lHb5KdUrLZTZJcKjFIh1jQOEi8hH0txjIrHUiHWtNZUgJ7ETlJsS+tPMUKWGWPMLRhB4gEUF9M+U5FaKjyfim1Trtq3b1+0JyEe8m8SZEpFpCl3JKEGOu8U/9IZpsLjFP9SezqrHSEqiqtUTDy1p6LtdD9JhZqpADeJSyThCoqVVBA+QXtIhcDTOLr3rI4gBuX6tKbUR/Ib8hnKpSkWUwFuyqUpT9A5JPbs2TN3H1QQPhU1pz3csmVLtM8ryEQ+Khcm5Qkq/H/HHXdEe7rD0J2JYnxqT+99b37zm6M9vWdSzqR7Vzqv1EdqS3GOYnY67xQTycfTeaCY0bn30lml+2I6q5RL6V6eYgblsI64FM375MmT0Z7mQmOmO0fyR+qD3uXSXZDyD90tEnS3S2tHwgsktpXOC42N8mC6n9C5oPGlHEbrTH5w4sSJGRvdrdMdmp5J60/4hiYiIiIiIiIiIrJg+NFORERERERERERkwfCjnYiIiIiIiIiIyILhRzsREREREREREZEFw492IiIiIiIiIiIiC8aaqscSSc2tq5KVIGUV6jspoHQUNak9qdV0FF5IeSf1TYomNOakXkKqhbQeSYGJ1NJIVSmp6ZAqEClPJf8gpTNa//RMUgUi5de0B0kFr4rVY9J+0drRuUjrREpQtF9JLZNUW5NKUlVWsesolZKiHI057TnFA9qX1DcpPpGaUToX5Eu0Hmntuopgae7Jl+h8yzJjDDyDL4b8ilRbkzoVqYZS/Lv++utnbLSnpLSVYj/5PSnkJtWwTi4lhT1a+xTTuups6bx31y6dYWpLcSCd4YMHD8a2SRWtqqcATGua2lMMpbiT4hTFOVrr9MyuimCaC+0L2ROUB9O86Q5HY077QncZ6oOUOxO0h4cOHZqx0bzpHpL8tLPOVdkP5lXylouT9oPuyCnPVGX1erob0d0t+TLFLlJzpfeXxG233RbtSc2S4l+CVMopt6V3hu5dvfN+TGuU4g6pg9JZS3uY7jdV2Weqcg4jdWry05TrT58+HdtSDE1xm+7ftC/pPYDGTH2nM0DngnwvzaXzHYLuCmRPa3r8+PHYls5F8lPKHZSXnnrqqRkbrRH1ccMNN8zYKL9SLk3nk+ZN+JN2IiIiIiIiIiIiC4Yf7URERERERERERBYMP9qJiIiIiIiIiIgsGH60ExERERERERERWTDmEqIYYzxZVd+squer6nvTNN05xthUVb9aVfuq6smq+s+nacoVR0VERF4hzGEiIrKeMY+JiFy+dNRjf2iapjMv+PvHq+oL0zR9Yozx8ZW//9zFOplX3YbUN0iBK6nYdFTiqrJKCSmrkGpOak8KR2RPSpmkRJjGTPOmte8oyiQVnKq8Ht21S/tCcyHll9SexkHrkRRhad40vtSe1AxJCS/1TWo1HX8kRSpSLUrqTtQH7UuCznhSxqR5k5peUvmic0/KWMk/SJl5//79c4+jozhclZWSSOmK/DGpO12G6rEvO4edP38++mdaN1L2on1OZ4r2k85f8uWu4lc6w+RvdHZSbqM+0vMoNtAZTkqsXbVOemaCzkmKoZ28S+MgVe6O0hyNmfJPWmsaM/WR4jadC8qPdPdJ0ByTr1999dWxLfl08hvymWSn80Y5LJ0LusuQqmWKNbTOpEid+qZ8TEp4tOcJ8uk0l3S2Oqr065SXlcemaYp3inTead/ID9PZ6ahyVuWcRz5BeTCdbVKcTCqxVdm36Hmpb4pFdM7S2tF9ejVyGJ3VNG5S1KSYlnyJ7j3kY8k/KJdSLE/rQX63Y8eOaE/xme5l1HeKuXSGaD3SnlPepT7SOaJ8l9aOcke6f1XlPad8Tn2kvd29e3dsS2crKRfTHtIck+9141JqT2eLeDnZ7SNV9amV//+pqvrxl9GXiIjIWmIOExGR9Yx5TETkMmDej3ZTVf3+GOPfjzE+tmLbNk3T8aqqlT+3XooBioiIvEzMYSIisp4xj4mIXKbM+3N575+m6dgYY2tVfX6M8Y15H7CSWD5WxT9+KiIicglZlRy2c+fOSzU+ERGRC/GS8pg5TERk/TPXT9pN03Rs5c9TVfWbVfWeqjo5xthRVbXyZyzUNE3TJ6dpunOapjtTbSwREZFLyWrlMKohIiIicil5qXnMHCYisv656E/ajTHeUFVL0zR9c+X//3BV/YOq+lxVfbSqPrHy52cv1tfzzz8fC/Sngozbtm2j8UR7KibaLV6fij1T4WvqOxWLpCKZV111VbSnAqHnzmUxqFTokYpWnz17NtrTmKloK9kTVBSViianvqlYJNEpBE57mIp4UsHJrVvzbyJ0hFFofKnIKxWP7RQkp32h4qXpDFDxUtrbM2fORHsirQetERUeTQV86SxTQdh0jmj9ad6pPcU2KmKbxkfrQeuchAHSfs8rFLSeWM0cRkW80/kjvyJ7iiXUlkSMUlFbKlpN4jop7lDcp1iScl5nzHRWaS4pD9KZpFzaKcRO95DUvitIks4gFUunOSYo/9BP3qR1oj5IXCfdcagQNflS8hsqgN4Rhuj4Y1W+N9L5TOtEe7hr165opzkmaByJkydPRjvltpQHkwBaFft0Ore0zsePH4/2p59+esaWCn5vxBxWtXp5bJqmeG9Ke9Txq6p877ruuutiW7p/p7NKvkJ5ovMuQR8xO3E4nR3yQ8qlae0od9A4Ou9ynRhK60wxI8XK7rtBR5iQclhaJ+rj2LFj0Z7WieIckcbREZyoygIJ9C2DhBBS3KZ8nNbp4MGDsW0Sz6zKvkfvbCQAkfzgyJEjsS3N5dZbb52xnT59Orbt5A+aN+XYlNs2b9489/Oq5vv12G1V9Zsrl9RXVdWvTNP0u2OMr1TVZ8YYP1tVh6vqJ1pPFhERufSYw0REZD1jHhMRuYy56Ee7aZoOVtXbg/1sVX34UgxKRERkNTCHiYjIesY8JiJyeTOveqyIiIiIiIiIiIisEX60ExERERERERERWTD8aCciIiIiIiIiIrJgzCNEsWqMMaLaTFJiI/UNUgdLKiqkzkKKN0nphFQyr7/++mhPkPIOqZcldZWOTDv1S8oqScWJFHZILSWtU0dhtyqrGdIekj3tIfkMjSNB6lXkS+mZpEpDa53sNA6aY1I5IqVZUhzqqFoRaV9oLsn/6RyS4lBSmiMVM1K1Sn13/I7oqIdS+47icFXViRMnZmxJ0Yr8SJZZWlqK5ySdEdoLUhNP54H8+5lnnon25PeUD0hlPPl4J0aRvRMrSZ21oxZIz6O4k2IMKZ1RzEg5hc4UrV1qn/a1imNJJ2bTmqY+KGd2lAHpXtBRW6Z9odyW9paeR7km9U0qqsnH6LzR+Ux3Ptormnfqm84WkZ7ZyVVVPYVouoeknJfOxUZVj10txhjRXzqxi/Y5xVzyTSLlTVLJpBjfUUCn857ic0fxm/yQ/D7NkdaO7gVpv+geQvknQXOhWN7JpRSPkr3TtirvF+VBisNpnVYjh9H6k48lv6H3ceo75XTK3cm+Y8eO2Jbuo6997WtnbHT/SmOr6n3boTOevi3QNxUaX4qP5Ad0XtIzae0If9JORERERERERERkwfCjnYiIiIiIiIiIyILhRzsREREREREREZEFw492IiIiIiIiIiIiC4Yf7URERERERERERBaMNVWPnaYpqsoklRJSYSGlk9Q+KZdcqI+kGkJKLh2lGVILJLWUpIhEiiZJZberUpbUuuh5tHYdpR9Sa0r2jsJRVVZt6SoOJZUe8seOMhMpQZE9KeFQ26uuuirak+IN+TQp8iSVUVo78pu0fh2Vvq4vpTOQFISqqq699tpoT6pF5I/UR1oP2kM6W6dPn56xkRI0qRbt3r17xnbs2LEZG/mzLDPGiHvaUYsmxank4x2F0aocy0mtjpT35s3R1JbGQcqjKb5QLKLnpZhGSmIU/1KM6qqGpxjTVd5N+0XPIx9L+0Vxh9aD9jzRUTXvqpd2lMdpPZLvUazr3H06dwhaf7pbkGJmgnw93QtozKSEm/qg59EZT3TuklVZuTDdobtqpZcjyfdTzKV9JiXQzn2H7OkM0zioj+TL3btNukNSH2fPnp2x0Zgp7nfUe+mcpbNDY6Y+Ug6j2NBRyO2+dyRformQvZNr6H2c7hwJ2q8EjY36SN8zaA9pPdJaU55J46N7CKkZpz7Il+hcJKVyakt9d75PkHp5WlPK3aRMm3wsfcO5EP6knYiIiIiIiIiIyILhRzsREREREREREZEFw492IiIiIiIiIiIiC4Yf7URERERERERERBaMNRWiOH/+fBRDSIX/SDSBCh6mIpdUQLIjTNApfF2Vi+tSYUPqIxXmpqK911133YyNilOSMEcqREkFJ4lUdJWKNFIRyVRcn8ZBBSdTYVoqCEsFUDvFS6nvTtFbEiqZ96xUcUHeVNT0zJkzsS2tdSoIS2tEBYrTOGjeaXx0VmjeyacpdlCh/gQVGCVSoV4aMwllJCGKI0eOxLb79++P9uRL6bwpRHFhzp8/H4UkUmyl+EL+lnycfJbyQYqtJFJD4+vEcjqXyZc7hfXpeTSXNGbKd1Q8O/VBz6Ni0ak9xcSU56tyfOgUuKb2dC8gf0y5hnyG+k73Jyr4TbEn5XraQ7KncdMdk9YjnUUSBEr58dy5c7Et5cF0xsmXqI+0HjRmsncECui+/PTTT8/YyA9I1Cn5QdoTc9iFofewtG60zxRb0552hBeqekJkRLrLUuyiHJbyFd3RUt9doYFO3Ke5dMZBd4t036c8SDks+RL5DMXbNBcSCSIfS3tLOYLuHGkP6A5Pa51iOcUp2vO0TpRTSOwsxVby/zSOEydOxLbbt2+fexx07smeYhWJbZK9k/9pTdP6p+8vF7KnHEa5m/An7URERERERERERBYMP9qJiIiIiIiIiIgsGH60ExERERERERERWTD8aCciIiIiIiIiIrJg+NFORERERERERERkwVhT9dilpaWoSJbUOkjRhBRXkhIIqcGQwlUaG7Ul9dKknkTjIBXPpExDajXpedSWVFGSIg8p2NBckiIPqQV2FAdpLqR0lvqgPeyoJ5E6EfXdURwiRbik3EX7QuNL6j2knkQkxSEaB6nbpjUlBcytW7fO2Ei1iJR3kp/SfndUNKktrWlaJ9or8o/rr79+xkZni+Jjmnuan8p7F2ZpaSmu5dGjR2dsyY+respvFF9o/5PCFalCk8JYgtTjTp48Ge1nz56dsZHyWydnUsxIZ4fUyIi0Tl0FwDSXjuJ9VZ47KezR+JJ/UIyiXJrmSPvSuZfRHhKd3EHr1FHTpRzWUaRMfkDrnNTBq7LfdNWMk3/QvEkZM+VY8l26F6e5U1sixdN0dzKHXZgxRoyXx44dm7Ft3rw59kHKi8kP6X5Lua2zpzSO5OOkVkx5MMVQGkey0z2PYnayU8ymnJ7iIvVB4+jkMBpHWg+KzbSmaS6kZkx35zR3il0dld3O+3hV767V8Q+6U1GeSFAOS32TKuqTTz4Z7SmXks/QXJLf0BrROifl4o5qblWOB8ePH49t0ztbVc6l3XuqP2knIiIiIiIiIiKyYPjRTkREREREREREZMHwo52IiIiIiIiIiMiC4Uc7ERERERERERGRBcOPdiIiIiIiIiIiIgvGmqrHnj9/PioGJfUYUqsh1ZakwEEKI0kNsyorgZDSCSmPJAWUpKR3oT7SepCiWVLTIdUi6mPePaHnVWV1FlIHo73tqOZ1xkGqbUQad+q3itc07QG1JfWe1L6rHpuUuEjhiOxpfHQOaXxJ5YvWNI35mmuuiW3JP9LakeLmjh075u67q+aV5kh7RXEpqWht2bIltqUzl+bSVS2S5f1PKovJPymGUtxP54z8m1STk3+Seh+d4TQ+UuUiFc+UB2neKZbTWaW4n6D40lF+7SrvpfbkBxRvU9+UOzqqoTQOyj/J92gc5Aedexn5WFpT8oOO2i8p4VIfaZ3IP9KdqnuXTGtKe7h9+/ZoT7mG9ooUB1Mf5DOkmN1R7yVFvs69TJjnn3++nnnmmRl7yinkb+TL6TxQ244CZ1dxOo2Dcikp0CYfp/iX8hWdEYo7aRzUluJ+R2mbSGeKchXtLc09QffhtIekMEqxpPP+Qzklva/SvlA+SL5Oa0RzSe0pVxHJb+hcpLWjMVPuOHPmzIyNfIYUV1N+JOVpygfpDNDa0btmslO+O3XqVLSn9e/mMN/aREREREREREREFgw/2omIiIiIiIiIiCwYfrQTERERERERERFZMPxoJyIiIiIiIiIismCsqRDFGCMWZExFHangJxUr3rVr14wtFQy/UB+pEDwVvqRClKtR+DL1TQUgk53aUvHSVGiTioNSH6l4JhVYpMKXia4gRipySXvVKWreKbRdldeU1o6Kl6Z1on0he/IF8kcqDJzGR/Om4p6pcCj1kcZHbTuF2KkAKok3pPZUtJjiROqbiraSYEDypVRIuqonWJPoFra93BhjxLiWcg3tM+WfVOiWfPbcuXPR3jmrFFvTXMg3KdekcXTzUud5KcaTmAXFubQedB46xaLp7NFckn9141+KGZTDaHxpD8nvyD/SM6ltR9yjK4SU9pbyIK1TJzamfNDx86qegBb5esoHlO9oTTsCHHQPSXGM1oOEoZLfpLl01/ly48orr4zCJelsU/6hM5L8je775LPpnFH8o76TnYrX01xSzOjESoovnfsmPY98vCMa11nTjsBPVZ4L3ZGpj3R/oj0kP0h7SOtP+TjNnd4DOtD6d3I9rV3nXbNzL6MzS6R7CPkB3S02b948Y6Mx05022ekeQuc23cvobKUxV+W7P70PEP6knYiIiIiIiIiIyILhRzsREREREREREZEFw492IiIiIiIiIiIiC4Yf7URERERERERERBYMP9qJiIiIiIiIiIgsGGuuHpuUUa6++uoZG6mUvPGNb4z2pFrVVW1Naimk4HX69OloTwojpFKydevWaE8KLx3FVaKjuEoKLx3Vlq5aU1LpoecRaRykKEMKO0kRpqv8mtpTW1qPtH60hzTHNBdSvCHSmaV9Ib8hJeF5n0f9JnWiqqxERGqetLdJZYrU8Whv9+/fP/fzOsq7pBJLqlYpbqY9IT+SZc6fPx/VnpIfUo5IKrFEVy26o3BF6urp/FEsp77T+CgPJuXXbr5LcbGjJFaVY0z3vHfyD61dsndUeqtyjKG5UE7pKDDS3iboXkbx71LtLT2P8nGaI91H075QDqTc1lGgJQU6UiJMnDp1Ktr37NkzY6N1TmeZoLZ0LtI9Nd2hyb9kmeeffz7G/uQrpLRJOawTdyh2Jb+gM0J+mN4fn3vuubmfV5XHTXkp+SbFSpp3Wv9O26q8Tp0cQXRVSlO+Wg31+NVQc+/O5eW2rcp70FXT7eSDjlI85aXkv915p3cu6oO++aQYRD5N95Drr79+7j5oXxIUf+hdM/nvpk2b5n5elT9pJyIiIiIiIiIisnD40U5ERERERERERGTB8KOdiIiIiIiIiIjIguFHOxERERERERERkQXDj3YiIiIiIiIiIiILxpqqx1Zl9YyOKhcpESUVj67SZlINIYW9pHhbledC6iA0vo56SVqPrlpgUj7sqAJVZfUeUmUi1ZbkG13lqTQO6qOj4knzJnvyA2pLKlNp3OQzpADUUTPsKHTR+pO6VuqjozRH6lCkFpR8mvyA+k4qdKReRUrQad6kbtc5czTmbdu2RXvysTQ2mp8sc8UVV9S11147Y0/qjZQjyA/THlFs6CgkdlQ5q7Ja1+bNm2Pbs2fPRntnfGmOFItIHTmpKXdV89I4qA/awxR3ukrsaXzdc5n67uTdKvaPBMWjNBeK+537EPkX5bY0R1oPUiRP6nZ010rrQW3JH1MupTXq5EeaH53xtHakHroa90O6y6T1SGvaUcy9HFlaWopqpx2lTfLDjkpmyqNVeZ/pXklnOJ1V8vvVUL5OuaOr+J367qpkd5S26W6RziXlCPKPlB/JD2hN057TXGgcFHMTpF66GuNIcyd/7ND9xpF8vZOPaQ9pnZOv05g7Z4tyROfOfd111839vKqeAn1HXb2rdm52ExERERERERERWTD8aCciIiIiIiIiIrJg+NFORERERERERERkwZjro90Y45oxxq+NMb4xxnh4jPG+McamMcbnxxgHVv7MBQpEREReQcxhIiKyXjGHiYhc3syrePCPq+p3p2n6z8YYr66q11fV36uqL0zT9Ikxxser6uNV9XMX6mSMEYvuJVunSGZVLnhIxRE7hTk7hSyrcoFEKnRKhVhTAVMqVtgp/Ep9pMKQVFCTiqh2oCLGqRDot7/97diWCtOmuXQFIFKR3k6xaBpHV9wj2akAOgm3JH9cjWKu1EenEHVa56q8L88991xs2ykESoVfaS7J12nMVPy6M2/ypbSHdJZp/VPcTOdtNc73grIqOWyaphjP057SftI5SwIQVHC3Ix6Q+q3i2JpEHagt5Zp5i8ZX5ZjWiSNVOcfSOeuc927MToIkdFY74g3UlvygI95AeTDtFwmBEOmZ3aLhHUGmjhBFN5anc0FzSeeFzmEnd9AaUW5Lfkp9rMYdIq0RPZP6IB9La90RANgArNp7WPL95LNdwbEUdyh3dOIi9UF7nXyZ3sM67zr0/pnifld4Js2x+w7byWGUO9I6UdtOnu6ufyfuUA5LdMeRfJrm3RFkSD5Txfkg+R7dvyi3pfYdgSo6hx2Rv+73idSeziH1keIB+TSJWST/ID8gUZPOOz1x0Z+0G2NcXVU/WFX/rKpqmqbvTNP0TFV9pKo+tdLsU1X1460ni4iIXGLMYSIisl4xh4mIyDy/HntDVZ2uql8aY9w7xvinY4w3VNW2aZqOV1Wt/Ln1Eo5TRETkpWAOExGR9Yo5TETkMmeej3avqqp3VdU/mabpnVX1Z7X8I9hzMcb42BjjnjHGPc8888xLG6WIiMhLY9Vy2NNPP32pxigiIpIwh4mIXObM89HuSFUdmabpT1b+/mu1nDxOjjF2VFWt/Hkq/cvTNH1ymqY7p2m6k2qZiYiIXCJWLYdt2rRpTQYsIiKygjlMROQy56If7aZpOlFVT40xblkxfbiqHqqqz1XVR1dsH62qz16SEYqIiLxEzGEiIrJeMYeJiMi86rH/56r65yuKRQer6mdq+YPfZ8YYP1tVh6vqJy7WyRVXXBFVPJLyC6mAkMJLUhMhdRBSZ+koqxAdpRlSvEnjI4WRzvNIiTCtKa0zqfckaP1J2aajzkLqcR11O2qbfo27o/RHdhozKQ6lvaU9JDWdNO6OWt2lhNYj7Xl3zMn3aI06CmREZ3ykwEQ/iZza0zkkVbcUa8h3NyirksNIea8TF+m8p/NA+aez/+QTNI7kK9QHKaClM9WJfzRvUh5Lz6MxdxRG6XlkT6phHaVFGkdXxbETd2g9kr0bh9O4u+uR+u6oJ1fl2N+Zd1W+g9G9LPlj93lp3qQSS6qtqW+6W3fUljtKswTlXVqP5L/kBxuUVcth8971OqqQVT3V8I5q63PPPdcaR/IhGgepiSbfonF06Ci/dpWQU3s6IzSOtC+UOzp9Uw4jpc30THpn7saSBL0fpGfSuSCfTudiNd7DKGd2vlvQmqa1o9xNfpDslCMoL6VzS/muo6Le/caU1qOrYp/8pvseNtdHu2mavlZVd4Z/9OHW00RERNYYc5iIiKxXzGEiIpc3a/ujNSIiIiIiIiIiInJR/GgnIiIiIiIiIiKyYPjRTkREREREREREZMHwo52IiIiIiIiIiMiCMa967KoxrzJaV1llXlXaqp6KHamAkPJIUlfpKqB21GOT4hcpudA4knoSKemQ0kkaX1etM61/Rx2UxkdKOjSX5Dfd9UjP7CgfU/urr746tu2o1dCakrpWat9Rza3Kvk57mBSRaI1IPSlB86O+05p21KiqsgLW5s2bY9uOEiHFDlLimncul5kaX5ulpaWofkV7lyAfSrGc9rNzzsi/aa9TPugo7FXl9aA+0np2lCyresp7tFcpp9M6U9yhe0Gio4BKbSm3JZXDbtxP0Hp07jjdnJ76Xo3176iUVuW7HflSUrGjMdP6JzudZVJzTfeFzr2zKiv10TrT2iVIRbCTg9IamcMuzBhjbpVf8gnyoQTFBtqnb33rWzM2Uovs9PHss8/GtjTH5Ms0l45adyeWd5TmaXxdBfQ0Por7nfcwyv+0Th2lXlqnND6K2R31WFJRJdK+kN/RvqR81b3jJDr3go7PVOU1pdxx1VVXRXtHkZzuQ+k+2V275NOd98+q7OsU2wh/0k5ERERERERERGTB8KOdiIiIiIiIiIjIguFHOxERERERERERkQXDj3YiIiIiIiIiIiILxpoKUYwxYmHCVGiQiiNSIf7UvlPonugWb55XaONCfacCiVS8MRUkpSKlHdGEbgHaND4qPNrpmwqS03r86Z/+6Vz9VvWKWdOYqXhpgoqX0hxTMWt6Ho0v7XlH8KAq+wf5NJHGR+uf4kFHJIPs5Aff/OY3oz0V96b137p1a7Sn4rFnz56Nba+77rpoT8VL6WzROqX9SutvEe8Ls7S0FM9lOmd0rqlofBKdoP0kgYqOmBLtdYp/lHefeeaZaE+xhNYjtSURqY6IAa0d5Y6OeFCnmDXFyo4ABMVmIsW6btHk1L4rRJHWuiP8U8V7/nKhAugdwQgqkp2KS5P/072gI8xFPpbWlNY/xTWCisRTMfE0x85dkugWhJflWJn8IvlWRzSuqidE0okZXdGYFKfINymWpzsWxYbUtrt2CYq3nXtvRzyjqhd3aF+SEEh3HGlNae0oDqS+qS3dh9IcaV8673i0dmTviO6QvdNHakuiCXQfXQ1hrmSnc9h5PyZhGsqDaRzk0zSOdI9OZ+VC+JN2IiIiIiIiIiIiC4Yf7URERERERERERBYMP9qJiIiIiIiIiIgsGH60ExERERERERERWTD8aCciIiIiIiIiIrJgDFJBuSQPG+N0VR1a+evmqjqzZg9fezb6/Ko2/hyd3/pno89xtee3d5qmLavY34bCHLbh2Ohz3Ojzq9r4c9zo86ta3Tmawy7AZZbDqjb+HDf6/Ko2/hyd3/pnTd7F1vSj3f/qwWPcM03Tna/Iw9eAjT6/qo0/R+e3/tnoc9zo81tkNvrab/T5VW38OW70+VVt/Dlu9PlVXR5zXEQuh3Xf6HPc6POr2vhzdH7rn7Wao78eKyIiIiIiIiIismD40U5ERERERERERGTBeCU/2n3yFXz2WrDR51e18efo/NY/G32OG31+i8xGX/uNPr+qjT/HjT6/qo0/x40+v6rLY46LyOWw7ht9jht9flUbf47Ob/2zJnN8xWraiYiIiIiIiIiISMZfjxUREREREREREVkw1vyj3RjjR8YYj4wxHhtjfHytn38pGGP84hjj1Bjj6y+wbRpjfH6McWDlz2tfyTG+HMYYu8cY/26M8fAY48Exxt9esW+IOY4xXjvGuHuMcd/K/P7+in1DzO/PGWNcMca4d4zxWyt/32jze3KM8cAY42tjjHtWbBttjteMMX5tjPGNlfP4vo02x0XHHLb+2Og5rMo8toHmt6HzmDlsMdhoeWyj57CqjZ/HzGEbZn7msEs0vzX9aDfGuKKq/oeq+tGqur2qfmqMcftajuES8ctV9SMvsn28qr4wTdPNVfWFlb+vV75XVf/lNE23VdV7q+pvruzbRpnjt6vqQ9M0vb2q3lFVPzLGeG9tnPn9OX+7qh5+wd832vyqqn5omqZ3vEB6e6PN8R9X1e9O03RrVb29lvdzo81xYTGHrVs2eg6rMo9tlPlVbew8Zg57hdmgeeyXa2PnsKqNn8fMYRtjflXmsEszv2ma1ux/VfW+qvq9F/z956vq59dyDJdwbvuq6usv+PsjVbVj5f/vqKpHXukxruJcP1tVf3EjzrGqXl9VX62quzbS/Krq+pVA8qGq+q0V24aZ38ocnqyqzS+ybZg5VtXVVfVErdQi3YhzXPT/mcNe+XGu0lw3bA5bmYt5bJ3+byPnMXPYYvxvo+axyymHrcxpw+Yxc9grP9aXMUdz2CWa31r/euyuqnrqBX8/smLbiGybpul4VdXKn1tf4fGsCmOMfVX1zqr6k9pAc1z5ceWvVdWpqvr8NE0ban5V9Y+q6u9W1fkX2DbS/Kqqpqr6/THGvx9jfGzFtpHmeENVna6qX1r50fp/OsZ4Q22sOS465rB1zkbNYVXmsQ0wv6qNncfMYYvB5ZLHNqxfbdQ8Zg5b9/OrModdsvmt9Ue7EWzK164TxhhvrKpfr6q/M03Tc6/0eFaTaZqen6bpHbX8X0HeM8a44xUe0qoxxvixqjo1TdO/f6XHcol5/zRN76rlX/n4m2OMH3ylB7TKvKqq3lVV/2SapndW1Z/V+v4R8/WIOWwds5FzWJV5bIOwkfOYOWwxMI+tYzZyHjOHbQjMYZeItf5od6Sqdr/g79dX1bE1HsNacXKMsaOqauXPU6/weF4WY4wrazlJ/PNpmn5jxbyh5lhVNU3TM1X1xVqujbFR5vf+qvorY4wnq+p/qqoPjTH+x9o486uqqmmajq38eaqqfrOq3lMba45HqurIyn95rKr6tVpOHhtpjouOOWydcrnksCrz2Cs3xJfPBs9j5rDF4HLJYxvOry6XPGYOW7+Ywy7d/Nb6o91XqurmMcb+Mcarq+onq+pzazyGteJzVfXRlf//0VquPbAuGWOMqvpnVfXwNE3/3Qv+0YaY4xhjyxjjmpX//7qq+k+r6hu1QeY3TdPPT9N0/TRN+2r5zP3BNE0/XRtkflVVY4w3jDGu+vP/X1U/XFVfrw00x2maTlTVU2OMW1ZMH66qh2oDzXEdYA5bh2z0HFZlHltptm7nV7Xx85g5bGG4XPLYhvKrjZ7HzGFVtY7nV2UOW7FdsvmNlaJ5a8YY4y/V8u90X1FVvzhN0z9c0wFcAsYY/6KqPlhVm6vqZFX936rqX1XVZ6pqT1UdrqqfmKbp6VdoiC+LMcZ/UlX/S1U9UN//Pfy/V8u1FNb9HMcYb6uqT9WyTy5V1WemafoHY4zragPM74WMMT5YVf/VNE0/tpHmN8a4oZb/i07V8o8v/8o0Tf9wI82xqmqM8Y6q+qdV9eqqOlhVP1MrPlsbZI6Ljjls/bHRc1iVeaw2wPwuhzxmDlsMNloe2+g5rGrj5zFz2Pqfnzns0s5vzT/aiYiIiIiIiIiIyIVZ61+PFRERERERERERkYvgRzsREREREREREZEFw492IiIiIiIiIiIiC4Yf7URERERERERERBYMP9qJiIiIiIiIiIgsGH60ExERERERERERWTD8aCciIiIiIiIiIrJg+NFORERERERERERkwfj/AeTy9poQsxlnAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1584x1080 with 6 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "Xred1 = perform_PCA(X, eigenvecs,1) # reduce dimensions to 1 component\n",
+    "Xred5 = perform_PCA(X, eigenvecs, 5) # reduce dimensions to 5 components\n",
+    "Xred10 = perform_PCA(X, eigenvecs, 10) # reduce dimensions to 10 components\n",
+    "Xred20 = perform_PCA(X, eigenvecs, 20) # reduce dimensions to 20 components\n",
+    "Xred30 = perform_PCA(X, eigenvecs, 30) # reduce dimensions to 30 components\n",
+    "Xrec1 = reconstruct_image(Xred1, eigenvecs) # reconstruct image from 1 component\n",
+    "Xrec5 = reconstruct_image(Xred5, eigenvecs) # reconstruct image from 5 components\n",
+    "Xrec10 = reconstruct_image(Xred10, eigenvecs) # reconstruct image from 10 components\n",
+    "Xrec20 = reconstruct_image(Xred20, eigenvecs) # reconstruct image from 20 components\n",
+    "Xrec30 = reconstruct_image(Xred30, eigenvecs) # reconstruct image from 30 components\n",
+    "\n",
+    "fig, ax = plt.subplots(2,3, figsize=(22,15))\n",
+    "ax[0,0].imshow(imgs[21], cmap='gray')\n",
+    "ax[0,0].set_title('original', size=20)\n",
+    "ax[0,1].imshow(Xrec1[21].reshape(height,width), cmap='gray')\n",
+    "ax[0,1].set_title('reconstructed from 1 components', size=20)\n",
+    "ax[0,2].imshow(Xrec5[21].reshape(height,width), cmap='gray')\n",
+    "ax[0,2].set_title('reconstructed from 5 components', size=20)\n",
+    "ax[1,0].imshow(Xrec10[21].reshape(height,width), cmap='gray')\n",
+    "ax[1,0].set_title('reconstructed from 10 components', size=20)\n",
+    "ax[1,1].imshow(Xrec20[21].reshape(height,width), cmap='gray')\n",
+    "ax[1,1].set_title('reconstructed from 20 components', size=20)\n",
+    "ax[1,2].imshow(Xrec30[21].reshape(height,width), cmap='gray')\n",
+    "ax[1,2].set_title('reconstructed from 30 components', size=20)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As you can see, as the number of components increases, the reconstructed image looks more and more as the original one. Even with as little as 1 component you can are least identify where the relevant features such as eyes and nose are located. \n",
+    "\n",
+    "What happens when you consider all of the 55 eigenvectors associated to non-zero eigenvalues? Go ahead and experiment with different number of principal components and see what happens."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a name='2.7'></a>\n",
+    "### 2.7 Explained variance\n",
+    "\n",
+    "When deciding how many components to use for the dimensionality reduction, one good criteria to consider is the explained variance. \n",
+    "\n",
+    "The explained variance is measure of how much variation in a dataset can be attributed to each of the principal components (eigenvectors). In other words, it tells us how much of the total variance is “explained” by each component. \n",
+    "\n",
+    "In PCA, the first principal component, i.e. the eigenvector associated to the largest eigenvalue, is the one with greatest explained variance. As you might remember from the lectures, the goal of PCA is to reduce the dimensionality by projecting data in the directions with biggest variability. \n",
+    "\n",
+    "In practical terms, the explained variance of a principal component is the ratio between its associated eigenvalue and the sum of all the eigenvalues. So, for our example, if you want the explained variance of the first principal component you will need to do $\\frac{\\lambda_1}{\\sum_{i=1}^{55} \\lambda_i}$\n",
+    "\n",
+    "Next, let's plot the explained variance of each of the 55 principal components, or eigenvectors. Don't worry about the fact that you only computed 55 eigenvalue-eigenvector pairs, recall that all the remaining eigenvalues of the covariance matrix are zero, and thus won't add enything to the explained variance.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 102,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7647adde71c0>]"
+      ]
+     },
+     "execution_count": 102,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "explained_variance = eigenvals/sum(eigenvals)\n",
+    "plt.plot(np.arange(1,56), explained_variance)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As you can see, the explained variance falls pretty fast, and is very small after the 20th component.\n",
+    "\n",
+    "A good way to decide on the number of components is to keep the ones that explain a very high percentage of the variance, for example 95%. \n",
+    "\n",
+    "For an easier visualization you can plot the cumulative explained variance. You can do this with the `np.cumsum` function. Let's see what this looks like"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.lines.Line2D at 0x7647ae117700>"
+      ]
+     },
+     "execution_count": 103,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "explained_cum_variance = np.cumsum(explained_variance)\n",
+    "plt.plot(np.arange(1,56), explained_cum_variance)\n",
+    "plt.axhline(y=0.95, color='r')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In red you can see the 95% line. This means that if you want to be able to explain 95% of the variance of your data you need to keep 35 principal components. \n",
+    "\n",
+    "Let's see how some of the original images look after the reconstruction when using 35 principal components \n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Reconstructed')"
+      ]
+     },
+     "execution_count": 104,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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qm8qh9upMbq46j9BxncmPVett7dq1xfx4JJqaiyStTCmtbhb8LTU2Jiq+1PTp00d/8Ad/cECMOvMpp5yC55977rlZbMuWLVmMXiJocFaddCXp2WefzWJnnHFGpfMXLFiA12zlpZdewvjVV1+dxb73ve9lMbpHesZrr702i73zne/Ess8+++wsRgP7tNNOy2JVoZcNiTs41TkNrlWrVmWx+++/P4tt374dy+7du3elsqm9n3nmmUoxieuXJi+qo9WrV2exJ598stL1JH6RnTlzZhZra2vLYrRooDrr169fFpOkXr16ZTG6TxrLrQs/iduB6lbiBUrVSZv6JP3RoTMvNdSvPv7xj6/FC5g60akcOWDAAP3FXxy47zAt2Gn+lRr5tRXKKTSm6Diac3bu3JnFSucPGjQoi9GictOmfN/Fqi9ZkjRjRr6P8h133JHFaM6hsTd27NgsdtVVV2HZNL/R+oXajNYklEepzkpQHW3dujWLUe5YvDjvltQ2kjRkyJAsRvMqrUlozbdjxw4sh+ZwekYaJxs3bsxi9Nyl9SblxzFjxmSxtWvzqZr6GvWBUttSLqU1BD0P9SEai5RHJa6Pqi/GFDvnnHMqXU/ieqOc+f73v7+YH4/kT5ZD1XCVamdDM9Z6Q++PiMcj4vHnn3/+CIozxhhjasMhc2TH/Fj6w4cxxphqHMlLDX0Gnv15MqX05ZTS7JTSbHoLM8YYY45DDpkjO+bH0ieLxhhjqnEkLzUbJA3v8P/DJPFnlcYYY8yJhXOkMcZ0IUeiqXlM0viIGC1po6R3SnrXQQs76aTse7/0fXSKSfxd4EmTJlU67oEHHshiJGAiDYrE352l7xzT92Tp+4xr1qzJYqXvGdL3Jkn78Itf/CKL0TM+8sgjWWz9+vVZTJI++MEPZrH+/XN9Fn2XktqRxIglMSC1RVVBalWBYUlvQu1I3xuv+t3vkuaI+uqGDRuyGLVtVZFgqWwSCtL3otetW5fF6Pu4VD+l7wxTvOr3fqkPkYZqypQpWDbpYmh8UzmbN2/OYlW/Gy9xf/Mn2MctncqREZH1m2HDhmXH0fftJdYlDB48OIvR2JszZ06l40p9lb43T3oKgrQGpNkrGQpQfiQ9BGkfSD9A89iSJUuw7Pe+971ZbODAgVmM5giaX4iSPq+qeRHlBJIC0HOXyqa8Re1Daxo6t7T2oT5EX9MsrV9aofopmSFQnLQ7VDZpjnbv3p3FSgYUtLaksTdhwoQsRu1A+qKS3pXWUzSeqJxt27bhNVsprc+oH5TeB0oc9ktNSmlvRHxA0p2Sekr6akpp0eFezxhjjDlecI40xpiu5Ug+qVFK6UeSfnSU7sUYY4w5bnCONMaYruPobthgjDHGGGOMMV2MX2qMMcYYY4wxteaIvn7WWfbu3VvcvKsjJDqUWNhMImYSZJFAjK5XEviSQIwEePR8tMFX1Z3bJRZfXXLJJVmMhH7z58/PYiRQLAkhf/3Xfz2L/emf/mkWu/jii7MYPQ+JKEvPTSJFEpVSXVbdOLG08RYJKel+SExLz1Pq97QhKAkpSRRKgj56ntIzksnG8uXLs1hVkwzaHLckLKaxV9rhuBUSV06ePDmLlXZep3unvkH9ip6RrlcyHCGRN5VjTjz279+fjX2aN0oiWxrntDk1Ca0p51K/plwm8fxU2Ak8i5EZSGeMAmhzyaFDsy3zcF1A9UuGC6X5+6abbspiH//4x7MYGftQ7qD5hfKBxDmO5lCa26hsOrc0j9Gm1WQgRHmUBPglgTnlI7p3ErIf6ZqPjGtoI3Vak9BxlLdKZdMzVjWBILE9PUtpXyzqbzTGqm4wSvNI6bmpjkqbDZfwJzXGGGOMMcaYWuOXGmOMMcYYY0yt8UuNMcYYY4wxptb4pcYYY4wxxhhTa/xSY4wxxhhjjKk1Xep+1qNHj8zphxxbdu3aheeTwwo5bpBLCjk4kVsYOYpI7Bh25plnViqHHGieffbZLLZq1Sosm5xG5s6dm8UuvPDCLEbP2NbWlsVKrjZ0/ic/+cksdvbZZ2ex7373u1lsxYoVWaxPnz5YNt0TtQO5gpCDBzm5lBy3yLGDXFvIpefuu++udK7ELifkAFLVrYZcRcgZRmLHGXL5qVqXdG7JPWfs2LEYb4WcT6jOyVWs5Ly2YcOGLEb3SS4ydD8UK/WrIUOGZLGSS5s5sejRo0fWl2guqOIg2g7NoVVdIOk4crOSeH4iyJWM8jq5NS1cuBCvSeOZ1hBjxozJYvTcVL80v0g8R3z605/OYjQH33LLLVmM1gAlN1ia32jtQ32A8vXgwYOzGOVbifMjlU0OW+TIWnK2o/UHzdVVcxS1V2muJqc+ypm0lqP7prqgNWQpTg5k5JxJ44n6UMl1c/PmzVmM+j/ND+TMSHNGyZGV5rvS2qmEP6kxxhhjjDHG1Bq/1BhjjDHGGGNqjV9qjDHGGGOMMbXGLzXGGGOMMcaYWtOlRgH79+/PhGckop88eXLx/FZIDEZirpRSFiMB07nnnotlkziZxIgkrKMYiZ9I4CWxqGrdunVZjASTVcVcJKCTuH6pLidMmJDFXv/612cxEoh/6lOfwrKpPqhsEraRcHD9+vVZjAR9Erft/fffX+l8Eo7TfZeOHTBgQBZ76qmnshiNB+prJOqUeJwQpb7RCgned+zYgceSMLSqQQKZIZCZRkmEOWrUqCxGQt7x48dnsUcffTSLUf2QIYDEY6807s2JBeVHEiuPHDkSz6ecQvMgCY4px9B8WRKtU56ge6f5oOocWDL+2L17dxZbvnx5Ftu4cWMWo7mEhOOURyWen6guqM0++MEPZjES63/oQx/CsqneaF6ldQ4dR/2iJNKm+D333JPFqN6oHUtifeqXw4YNy2LUrygXkqi/ZGZD/ZdyHOV2ys2Uj6hPSmzkQNckYyrqF7R+KJlDUS4kMyfKj0uWLMli1AdKZZNJR2nslfAnNcYYY4wxxpha45caY4wxxhhjTK3xS40xxhhjjDGm1vilxhhjjDHGGFNrutQoIKWUiWpLwvwjgXYtXrx4cRYjkV9JVE3COhK8keiXBGskbCahtMSCbiqHdqwlwRkJK0vC5tmzZ2cx2tmZhGhUl9QOn/nMZ7DsiRMnZjESmF1++eVZ7L777stiZPbwyCOPYNkkkiWRIAlnSRTa1taG5dA9kQnEVVddlcVIoEjGGyWxPomI6ZrUh0i8R4LLkriXxhMJ7knkeqTGGyQO/vnPf57FqG0nTZqUxUo7MxMLFiyodD/GSNw3KG9JbFpCOYXG5OrVq7MY5SgSK0s8N9K4oPMpH9HcRAJoiYXNa9asyWIkyh40aFAWI3E6rSkkacqUKVmM5m8S4dNzU878yle+gmWTOQ8Juum4qqY3Tz75JJZNfYPqjfof9YvSXE31QWJyMpeinEBrpJJhTtWcQgYAlMvouck4RuK+XtVQhuYHGndUjxI/N63bKJeRCU9n8tuyZcuyWO/evSufL/mTGmOMMcYYY0zN8UuNMcYYY4wxptb4pcYYY4wxxhhTa/xSY4wxxhhjjKk1XWoUcOqpp2ZCoqVLl2bHlXaxJdEYibRI4Es72W/atCmLlYTN/fv3z2Lz58/PYiQoJOEWCcFKwi0SQlK9kVCbRFokqiNhvCStXLmy0jWpLkg4SAJzEstLLCb/2c9+lsXuuOOOLEbPQ+K9Ul8jAR+12bhx47IYid1KO3HTDsdUzubNm7MY7bo9fPjwLEYiXokFeCXRZCt039RPSdQvcT+gcUI7JpMZAvW1krCY4mPGjMlitMv1rl27shjNDaU+TXVUMggxJxY9e/bMhN6U82helFh4TgJhEpPTTvZUdmm+pDEwb968LEZzDonOybCkZJBARiZk1kLjmcYexUr5kUxY6HwyLqB8RGJ9EreXyqb8SOsCMq6hOb00f9O6i6D5jnJMyYCCDCOo/1Jd0HG0Pis9I60BqBxqH7pvagcadxKPM4rReCLTJjJYKrUh9cuqRiCUmwcOHJjFSgYJ1GY0vg+GP6kxxhhjjDHG1Bq/1BhjjDHGGGNqjV9qjDHGGGOMMbXGLzXGGGOMMcaYWtOlRgF79uzJdtYlARIJlSQWLpIoe+bMmVmMTAFIrEyCKonFjK973euyGAnrhwwZksVI9FUSblXdvZ0gkRWJuUhgLrHojMSMJPQjYSYJQEs73tNuxrNnz85itDsyCVdpd3oSR0psAEDH0vOQSJV2mZZ4R+q1a9dmMapLOo6EdiVx77nnnpvFpk+fnsVIJEuiZCq71KdpnJHYn/rV+eefn8XIZIN2Cy+VQwYANOZp3JGJQ0nMTUYkJCo1Jx779u3L+jHN/TT/SpwfSaA+fvz4LEbjmQw1SqYWNP4uu+yyLEYGN5R7aNyX1gU0l5DxB+12TuOURPR0rsT5sWQS0gqJvOkZaW4qxSn30JqE6oz6Vcm8iExqKBdu3Lgxi1HblswQyGiA1nJkxEPzMtUvXU/iZ6T8SOspKocE8yVo7FHeonxE+ZHmBlojSdzmVA4dR21LfaAk/qf2prnpYPiTGmOMMcYYY0yt8UuNMcYYY4wxptb4pcYYY4wxxhhTa/xSY4wxxhhjjKk1XWoU8Morr2SiY9oluCQuJjHYxIkTsxjteE9ifRJzlXY6JdEwCQpJXLZ8+fIsRuJgEn5LvHMric7ofkigTqJzEpJJLI6nXd7puWnn4M6IES+66KIstnDhwixG4ut9+/bhNVuhfiGxuJ76BglnqU+XRHnUZiQILO2m3Qrdd0lgS8YJ1GZ0HJkCUL8qiZqpfciQ4MILL8xiq1evzmL0jHSPEot7aadpEkeSqQUdVzJnoOcmMbg58dizZ0+WZ0hMXpqrad6YMWNGFqP8SPMY5ajSXE2CexIIk3kHXZOE4zQPSSw6progQXdVSuL/I8kTJGQvrT8IatsVK1ZkMZrvqF9RXqfcKvE8Rs9I51MuI2G8xPdOcz3VJd0j5ajSWoHuk+6HhOxkNETXI2G9xDmBxgkZWLz44otZjPpVyWyK6oPasaoxBNU5jU+J1/idzY/OpsYYY4wxxpha45caY4wxxhhjTK3xS40xxhhjjDGm1vilxhhjjDHGGFNr/FJjjDHGGGOMqTVd6n4m5W4P5557bnZMyZVh9OjRWayq2xO5qZCrwpo1a7BscqkaNmxYFlu1alUWI+cJcqgoOUKcccYZWezRRx+tdBxdc/jw4VmMXD0kacKECVmM3NwIaoeIyGLkXiOxawY5bpBD1rJly7IYOaRQ/5O4fchNi+qXXOzouSV2GiGXH6rLkSNHZjFyLCJnIonHzqZNm/DYVui56VxqL0maNGlSFiMHHHKWIYc2mjNKTkLk/kR1RH1j+vTpWWzBggWVridxe5PrkDESu1SVxhTNB9QPyXGJxhQ5fnXG/YzunRwOaW6kWMlJkeYiKofmF3KSI2dRygcSu1pS2XTvlK9p/i7NY1Tn1GaTJ0/OYuRqumHDhixWcp6i5ym5TbZCa6S+ffvisTRfUpvRc0+dOjWLUY6ifFBi165dWYz6OR1HY6zkfjZ48OBKx1I70hglV7GS4xzNL7Q+JJfiadOmZTFaU5fcXGmcUV0cDH9SY4wxxhhjjKk1fqkxxhhjjDHG1JpDvtRExFcjYltELOwQ6xsRd0XEiubPap87GmOMMccRzpHGGNM9qPJJzdcl3dASu1nS3Sml8ZLubv6/McYYc6LxdTlHGmPMMeeQRgEppZ9HxKiW8I2Srmn+962S7pX00QrXysROJDgjcZjEYjAS0ZGomo4jMXnJpIBEUSS0JtEZPePWrVuz2JAhQ7BsEo6TOJLKIaEfnUt1Jknbt2/PYiSOpLqgOqf6GTt2LJZNor5BgwZlMXru008/PYuR8QCJOiVp5syZWYzqgsSal112WRYjcaMkzZ8/P4tRHyTxKtUlmSGUjBhInLl48eIsRoJ5EkJSO5aExSQU7NWrVxYj4SCJiEncuGPHDiyb2oLEiNQOVA7VLwl+JX6ekljU1IOjnSM7QuOkJBynPkdjhfIribxp/i3lCYLmCMo9JKCmuXbcuHFYTlUzBMoTNOdQ7iBBtsQi6AEDBmQxWrvQfZN5QEmAT/MblU11UdVYpZQfqS3IIIdyzBVXXJHFqK9IbNBEfZrmb+prNH+PGjUKy6ZyyEyB+gs9z4gRIyodV4JyBwn46RmpbUtlU18tGUa0UtVwp2R2QvNLKZeWOFxNzcCU0mZJav7MR5IxxhhzYuIcaYwxXcyrbhQQEe+PiMcj4vGSLaIxxhhzotExP5Y+zTXGGFONw32p2RoRgyWp+TP//LhJSunLKaXZKaXZ9DGdMcYYc5xRKUd2zI/0FWdjjDHVOdyXmtsl3dT875sk3XZ0bscYY4ypPc6RxhjTxRzSKCAi/lkNweO5EbFB0v+UdIuk70TE+yStk/QbVQrbt2+fnnnmmQNi9OkNiaIlFvW1Xk9iwRoJzjqzWzOJgenrdHTvK1euzGIk1Nu4cSOWTcLO0aNHZzESZJHwiowHqG4lFp6PHz++0jXpGclQoPQXSnoeEmwuXLgwi9H9kCCQzCIkFq/Szu+04/2ECROy2JYtW7Acgupj+PDhWYxEqiSYXLJkCZZDwkUSdk6cODGLrVixAq/ZSsl4g0TItOsxje+quy1TXyvFaZyQmQf1AYL6hcTi0wULFlS6pumeHM0cSf2jlVIfPOuss7IYjR+aiyj30LklEx/KHzRXk1kLmSFQPaxbtw7LJkE45UfK4TQ/0XOXTEdIGF1VqE3rDzIzKJkz0DxIwnFqW7of6lelvEV1RO1Ax1E7UL6VWCROfY1MlkjwTnmU2rB0TcozZM5QWke2QmY/Eq9f6Fgy1Bg6dGgWo7Yp5UdqM4L66rBhw7IY1W/JpIDau7NGAVXcz36z8KvXdKokY4wx5jjDOdIYY7oHr7pRgDHGGGOMMca8mvilxhhjjDHGGFNr/FJjjDHGGGOMqTWH1NQcbVpFb7RTKe1YL7FonQTLJByfOnVqFiOhU2mvABI4kjCTRFEkCCThFt1P6XwSTc6dOzeLXX755VmMDA5KOyafeuqpWYzqgsTtJP4jsVtJyE67K19yySVZ7Ld/+7ez2P/4H/8ji40cOTKLkdhSYqHeoEGDstjMmTOzGPWhksCWjDJIZE6mACT2JKHoBRdcgGVTH6Kxt3z58ixGwlk6t/TcVYWUNJ7ouWk8lfo0nU/tTfe4dOnSLEZ9v2R+QfNVySDEGJqrSawssfkGzcE0nsnghsbPzp07seyq4mSKTZo0KYvRHFgSk9N4JgE1PQ+ZupBJQWfstmnOo+cmkwJq25JJAdXRrFmzstgNN9yQxf7u7/4ui9H83adPHyyb5mV6xgsvvLDSNelciUX4NFeToQEZH1DbUh+QWMxOa75Vq1ZlMRK3k8ESrXEkNqmh/kJrMRoPtM6mtYLE6xcyFaA5g8Yd1XnpuakdaV47GP6kxhhjjDHGGFNr/FJjjDHGGGOMqTV+qTHGGGOMMcbUGr/UGGOMMcYYY2pNlxoF7N+/PxM+Tp48OTuutIvt/fffn8VoN2ISnZG4jER5JcEa7W5PZZMgiwTmJPoiwZnEgu6qArGqYmd6PokFYiQWffe7353FVq5cmcXuuuuuLEYGEJL01re+NYuRcQGVc+mll2Yx2mG4BAkUSaxPO+hS26xfvx7LIVHplVdemcWoXxG0+3SpX02bNi2L0W7CI0aMqFQO9b/Sbs10TRLyknlGSTDcSmkeoR2tSXQ7ZsyYLEZ9dezYsVmMBJNS9Xs3Jx579+7N5tZx48Zlx5WEs2vXrsVrtkLzEwmTaTyWhONkZkNzFs0RZJZCwnwyTZB4bqWySfg9atSoLNbW1pbFyAhB4nmDeN3rXpfFaG77yU9+ksVKuYPyBOWtDRs2ZDEyTqK8Xqpzah+a82idQ8Lx0jNSH7z44ouz2DnnnJPFKDeT6QK1tySNHj06i1FOGT58eBZbvXp1FqNcX6pfyj1V1y+Uw6lsGg8Sr5XJ+IDWjFUNhErjhtabpTmnhD+pMcYYY4wxxtQav9QYY4wxxhhjao1faowxxhhjjDG1xi81xhhjjDHGmFrTpUYBEZEJ8RctWpQdVxKOk1CKBEe0WyntZE9C/5J4ioRWVXcZJkMCEgyXxMUTJ07MYgsXLsxiJI4koSiZIZDIVGLRGO2qS2YGJMK8/vrrs9hXv/pVLJt2vn7f+96Xxcj4YPHixVmM2osErhLXUd++fbMY7cpbEpUSVJck5CXBPYl76X5IRCmxwQKJV2lXaKoLuseSIJCEh9Q+FKNziZL5BZlN0NihcUtzEwmdaZf00jVpB+eNGzfi+eb4JSIyIT2JvEt9g3IXjUmacyhP0Lkl4w/Kj2QGQsY1JA6muamUm6sKuqkcmp9InP7EE09g2TSeKadQO9KO7LNmzcpilFtL8fPOO69S2bR+oHmV7lHi/kIGLLR+IGE95R2J51Yym6D5m/oAxWhtKEkrVqyodP6MGTOyGJlDUb8qif+p3sh0gXI7rR9o3JWeu6oJFa01yCiA5gYy15F4PJbus4Q/qTHGGGOMMcbUGr/UGGOMMcYYY2qNX2qMMcYYY4wxtcYvNcYYY4wxxpha45caY4wxxhhjTK3pcvezVgcHcgErOWGQi8fFF1+cxci5itwb+vTpk8XI1UmSdu7cmcXItSgishg5XNAz0vUkdtwYMmRIFiN3l8ceeyyLkXMJuWNI/DzUZps2bcpiEyZMyGLkiEPPInGdf+Mb36hUztVXX13pHsllRJLWrFmTxXr16pXFpk6dmsUeffTRLFZq29mzZ2ex888/P4vdfffdWYycRp555pksVmpbgsqm/kvuLkuWLMliAwYMwHKoD5F7DjmsUD8nl5xx48Zh2dSvKEZOZ+QGRO4udD2Jn4fONyceKaXMXYzcgEr9hRwsJ0+enMVoHqO5kRylKI9KPMdQX6fzaayQ0xm5lUo8h5MrFOX2BQsWZDGaQ0vPTU5y5GJK+b5fv35ZjOZLym8S1/lPfvKTLEZzNTmqUp3T2kPi3EN1Pn369Cy2bNmyLEZ1LklXXXVVFps2bVqla9L8TbmDXMVKx5KjK9UROfDScZ3Jj7R2Ikc1crEjJ9AxY8Zg2eQc++KLL2YxWhdQDqf1Js0NUvW6PBj+pMYYY4wxxhhTa/xSY4wxxhhjjKk1fqkxxhhjjDHG1Bq/1BhjjDHGGGNqTZcaBZxxxhm64IILDoiRuHjr1q14Pgn9SEhJoigSg5E4ks6VWFxJIi0SV9J9k3CQhFelY0nAX7VsgoRgpbKpfUaPHp3FSHhIAjg6V2LBPYm/e/funcVITEtll8SnJAgnkSCJ8qh+zjzzTCyndTxILJYjMSzF9u/fn8VaxcftkFEGiQSnTJmSxeh5SMhIY0ySTjvttCxGbUEGANSn6RlXrFiBZZMAlGLULwcPHpzFqgqDJRYHl0wFzInFaaedlonCaS4p9S0ak2QeQH2QBL6rV6/OYv37969cNs3BJ52ULznIKIZE5/QsEs/BJOCvas5DcyjFJJ6zaF1A6w+aN2heHDp0KJb9+OOPZzEyhiChNYnoaS1WgtqHBPy0rmhra8ti1P8k6bzzzstiNNdTzqR+Qe1dMtKhNqM6J9MFWpOQaQKNsdI90fNQfyFjCDJiWL9+PZZN44TakXIhrSkov5WMIciQo2QqUMKf1BhjjDHGGGNqjV9qjDHGGGOMMbXGLzXGGGOMMcaYWuOXGmOMMcYYY0yt6VKjgJdfflmrVq06IEaCNRK8SyzUJqEUiZNJwESixVNOOQXLJqEgCb8eeuihLFZV9EXif4lFcBdddFEWI+EXib6ofku76tKxVBdVd30loSm1ocRGAa39R+J+QfdNAtmSiJ4MKEgMS21G7VCqHxL1kaEBieNJ2FnVQELier/wwguzGIkeSXBJYns6TuKxR2JEuncy8yiZixAkvCVxL0H9gvp0SdRM/aC0Q7w5sdizZ08211Muo7Ej8fxGQnYS6ZJJDY09EohLPO/QnEXCaDLhoV3IS2JyEhKTacmGDRuy2KmnnprFKL+VchTVL+V7Op/KpnUK1Y8kPfzww1mM1gpUNq1zaG4qPTeZHFSF8mPJSIeMgebPn5/FSLQ+b968LEb5qGR+Qc8+Y8aMLNZq7iFVN1gisx+JxxONUeprVJeUt0pQfdCcQ6J+MoeiPk1jUeJ7p3XFwfAnNcYYY4wxxpha45caY4wxxhhjTK3xS40xxhhjjDGm1vilxhhjjDHGGFNrutQoYN++fZlgad26ddlxpR3mSUBNQmsSeJGwjXaNLwmbScB03333VbomCTNJJFjaWZyE2suXL89iVBdUDonGSmJEEqKRkJJEcNQO73znO7MYiRslNgAgAfacOXOy2NVXX53FSLi6Zs0aLJtEeQQJX8kE4vWvfz2eT0JBEtaRoQbVLwlXSXRbgowYSFR6+eWXZ7HHHnuscjkEGQWQYJL6Pu0gXhIWEySSpfFIhhpkNlHaMZnGTkkka04s9u7dm/U5mhuHDRuG55NIl3IHiZjJkIDGVMlYhfowGZlQfqRrkjiY7rt0nyRGP/3007MY5UeaL0u7ztP8RHPEjh07shjl3GuvvTaLlfLj5MmTs9jKlSuzGAm6x44dm8VIbE/rM6m6UQz1AZob6bklbnPq/7S+I3E7mV+URPRkNkHPuHTp0ix2/vnnZ7HHH388i5WMGIiqpk+0RiITkRJ0TeqrtEai4yivl8T/VddDB8Of1BhjjDHGGGNqjV9qjDHGGGOMMbXGLzXGGGOMMcaYWuOXGmOMMcYYY0yt6VKjgIjIxFskQibxniRNnTo1iy1atCiLkRiXxEYkdCqJqkmMSLsrb9y4MYsNHz48i9EuyKWdokmsd+mll2YxEuANGDAAr9lKaYdXqg8Sg5FQlMSIJDAksaUkTZo0KYtRvZHQlISvCxcuzGIloR6J24j7778/i1FfKT0jCRxJ2Em7/FKdU12UnoXuk65JMeovVXc3lriv07ElgW4r1I7PPvssHktGDjSWSShKUBuSKYXEhgSdMXIwxzdV+nupv9AcQUYoNPao/1MeLZVNY/fcc8/NYiTKJhEzzVklowDK49OnT89iNE5prUFzNdVF6T6pjmj9MWvWrCxGz1jKUWSkQ6YClDPpOFpn7Nu3D8umPENz2wMPPJDF6HlK/Z4MiMgAhvo+Cd7pvktC9HHjxmG8yjXb2tqyWGdMASg3Uz6j/kLmIFQ2GYtI3KfJ/GLo0KFZjAwAyCSDTDskzpu0HjoY/qTGGGOMMcYYU2v8UmOMMcYYY4ypNX6pMcYYY4wxxtSaQ77URMTwiPhZRCyJiEUR8cFmvG9E3BURK5o/O7dDjjHGGFNjnB+NMab7UMUoYK+kD6eU5kbEWZLmRMRdkt4r6e6U0i0RcbOkmyV99GAXeumll7LdV0m0SEIniYVNJOAjgRiJgydOnJjFaOd2iXcoJnEaifVJZEXHkVizdD7tvDp69OgsRoIzEpeR+F9iQRc9N4kWSUBHRgokBpT4eebOnZvFSChKUL8i4wKJTQ6oLuk4EsaRcFViISb1c2oHEuJSXZYEiiTapXakcqgdCLqexP2XBIE0lql+qQ+UBKDUL2keoXFCglbqFyXTj6o7X5vacFTz4/Llyw+IUd+i+VeSVqxYkcVofqEYCXynTZuWxUq7r1fNjzS3Uf+vupO8xHVE88ZFF12UxUjUv3LlyixGwnqJ52USWlfdnZ7qh+YMiU0OaG7buXNnFiNBNtVjqb3HjBmTxcj0iXIH9b8ZM2ZgOWRAQWs0qgvqV3SPpX5FOWHQoEFZjMyYVq9encWoD5QMZajN6d6pr1GOoj5Qgvo05eaqcwv1K1rTStz/yRjiYBzyk5qU0uaU0tzmfz8raYmkoZJulHRr87BbJb2lUyUbY4wxNcb50Rhjug+d0tRExChJ50l6RNLAlNJmqTGxS6rmHWyMMcYcZzg/GmPMsaXy9x4i4kxJ35f0oZTSM6V9N+C890t6v8QfnxljjDF15mjkx9LeDcYYY6pR6ZOaiDhZjQn7GymlHzTDWyNicPP3gyVto3NTSl9OKc1OKc0ufY/OGGOMqSNHKz+WNp02xhhTjSruZyHpK5KWpJT+qsOvbpd0U/O/b5J029G/PWOMMaZ74vxojDHdhypfP7tc0nskPRkR85uxj0u6RdJ3IuJ9ktZJ+o1DXahHjx4644wzDoiR8wQ5IEjsZkQxcj4h1wpyNCl9Ra71viV2qCC3j6eeeqrSPZLDhMQuMvQ85HxCn46RmwS5Vkj83HSf1A7k7EEuHCXXN3LtomuSAwi58VA7lKC/mpJDHLmzkNsHORNJ3I5Uv9SvyHVlyZIlWaz0F+DBgwdnMWrv0nhshe6x5Bo0cODALEb9ksYY1S/132effRbLpjH+8ssvZzFyKKSyyUGp5KhD7nTbtuEf8U09OGr5kRg5cmQWKzl0Ut+knEB9fejQoVmMxk/JqY/uk/o6zXc0fqickhMXzVn0VT5ySBw/fnwWo68OkhubVM6brZDTGeUOmnNKX0uksilnUt6i/EiukqX2prl+yJAhWWzdunVZjHL4hg0bsBzKEwTlOOprdFzJXYvyI7mdkoMqre8o75ScX/v165fFqC2ov9B4oj5UyjvknkbQeormIKLkyEqOcyX3vxKHfKlJKT0gqfQF4dd0qjRjjDHmOMH50Rhjug+dcj8zxhhjjDHGmO6GX2qMMcYYY4wxtcYvNcYYY4wxxphaU3mfmlcLEmOVBIEkeh8+fHgWW7RoURYriStbKYmkRo8encVIoEjCTBKN0bklUR7dO9UbifVJoH7BBRdUuh9Juv/++7NY7969s9jzzz+fxai9SJxGAkNJeuGFFzDeym/91m9lsQULFmQxEkKWRPQUJ8EaiTBJCEmiUIlNDkiUSuI/uiaJEUvivTFjxmQxqiMyLqC2obYt9Wkao3TvZJJBfZXGGI1FiYWdNO5JMExjjI4jUXLpnqruaWKObyIiGwNkBlLKUSQcpzmYcsKmTZuyGImLae4vlUP3TuYDVM64ceOyGM2BkrR69epKZVOeWbVqVRabMmVKFiNhvMS5meZ0mlepzml+oGeRuD5IgP2Wt7wliz300ENZjITflN8knrPIUIbunfoQmVdI0saNG7MY5QkSmFPZVA6tISXp/PPPz2JtbW1ZjOZ6am9a15bWBWvXrs1iNE4ot1fdOoXqTOI6ojmH+jndI91PyXjjaNja+5MaY4wxxhhjTK3xS40xxhhjjDGm1vilxhhjjDHGGFNr/FJjjDHGGGOMqTVdahRw+umna9q0aQfESLRIIkGJRVH33XdfFqsqvibhFomiJRZPkQiaRHD0jCT0f81reK822vWYhFtUDgmy6R5LQsi3ve1tWYzqjUSCO3fuzGIkBCNRncTmA7Nnz85iJJgkgSPVeUkISTsh0y7xtBsx1fm1116L5ZDQlIwGSARMZU+ePDmLlYSQVO+0wzH1qxkzZmQxMh6gNpTYAICEqnTvixcvzmI05ku7fdNYJvEpCRxJiEsmBSVzBjI5qLqDszm+OeWUUzRixIgDYsuWLcuOK41n6q/z5s3LYjRvUN4jIXGpr9KcR+fTHEoGI7STfGl3eRInk+B+6dKlWYyE3yTeLtX5xRdfnMXIDGH58uVZjOZamhdLO7+TQH3SpElZjHLzOeeck8Wqmg9JbJpD5jE039H8PX36dCyH1hBV10PUjmPHjq10j5K0cuXKLEbPTWYT1F8od1BM4non0wRag1KdUY4iwxxJ2rNnTxaj8UQxmoPIVGLo0KFYNtUHje+D4U9qjDHGGGOMMbXGLzXGGGOMMcaYWuOXGmOMMcYYY0yt8UuNMcYYY4wxptZ0qVHAyy+/rDVr1hwQI+FWaRfy2267Da9Z5XwyHyDxVEm4NWjQoCxGYrCqu7GS4P2SSy7Bst/4xjdmMRIP/tu//VsWu/DCC7PYggULsljpuUlIP3r06CxGAsdnnnkmi5GIsmQUQMfSbs9PPvlkFluyZEkWI5MCEphL0syZM7MYiWGpD9C5c+bMwXJIXE/3Tn2adkyeNWtWFivVLwkKf/d3fzeLPfjgg1msdRyX7qdkvEGmADR2qC6nTp2axaivkHBVYvOCqgJQGndkvEHiXIkNS0q7aZsTi1deeSUzKCFRNBmjSNIDDzyQxahvkSCc5lUS+JKhhsT5sWTC0srdd9+dxcgshe5bkt7+9rdnMXruhx9+OIu94Q1vyGKPP/44lkPQXDJq1KgsRvVGMZrnyRCgFCcjBjJIIPMXguZViddta9euzWL9+vXLYmRKNHfuXCyHjG9oDiZTAMoTVL9k4iDxXE3GSZSv58+fn8XInKG01qU4tRnlHuoDtPYpGQXQmoiOpfuhnEvrbKrbEqX5roQ/qTHGGGOMMcbUGr/UGGOMMcYYY2qNX2qMMcYYY4wxtcYvNcYYY4wxxpha06VGAaecckomrKbd6bds2YLnkziNdiaturMtCfhJwCzx7uQlEXQrJJSiskuC7s9//vNZjHa7fe9735vFPvnJT1a4QxZ5S9WFXyNHjsxiVJerV6/OYqXnJhE+idtJlE0CQxK7lXarfeSRR7IY9T/a5ZeehwSlkrR+/fosRrvRk+iWjqMdskuivOuuuy6LfeQjH8litNsziQTJ9IDEkRKLkGmMUp2TUJTaoSSEpHJIaHrVVVdlMdqhneYr2m1Z4nakHd7NiQflRxJqk6mFxEJ6mtdpTJKgm8bo1q1bsWyag2lnchIhkxCYxnjJzObOO+/MYjQmr7zyyiz2xBNPZDESX5fyI823VG9krrN///4sRvmglDtozqLnpnxEczXNlyTql9j4huZq6qu0pijN1WSGQP2cciH1FzJNoPWMxPP/P/7jP2YxEubT85CZBrWDxGOCjBioLmjcbdiwIYuRkZPE9UZ1NG3atCxGpk20Zjv55JOxbGpHMjk4GP6kxhhjjDHGGFNr/FJjjDHGGGOMqTV+qTHGGGOMMcbUGr/UGGOMMcYYY2pNlxoF7Nu3LxM+kshq2bJleD4J+EhEROIpElx2Zndv2uGVxE4kQiZhJgngOiMAJRH9W9/61ixGZgZ0vZIIs+q9k7CNTBxIeEjiMEm65557shj1gUmTJmWxklC7FdoNWOKdpkmEScJv2pGadpmWWKDbv3//SuWQSJVEmFSGxMJDEgQuWrQoi9G4I+FryaSAdtMmQwIqh8YilV3VyENicS+Vfckll2QxGre0o3SJqjuvm+Obffv2ZeYqNG/QuJdYOE7zLYnWqf+T+J9inYHGLs3/lE/IVEjiNQTl4S996UtZjMTbNAeWBN107yQSJ4OEiRMnZjGa+0tC6X/5l3/JYjTfUv2QmJygHCFJl19+eRYjQ4I+ffpksXXr1mUxMhqSeA1B/ZfWKZTbly9fnsVmz56NZZNpA60raL1K65S+fftmsdK6i8bZhAkTshjldmrbkvkWQWOP1hVksjRjxowsRv2CDKMkvncy6ToY/qTGGGOMMcYYU2v8UmOMMcYYY4ypNX6pMcYYY4wxxtQav9QYY4wxxhhjao1faowxxhhjjDG1pkvdzyIicxYh9wdyHymxefPmLEauRxQjlwdy9pLY4SKllMWmTZuWxc4///wsdvfdd2cxcvqQpE2bNmUxcpGh+yFXmwsuuKDSuRK3BTm07Ny5s9Jx5BZTcgYjNyxy8yGXEnJDIfeccePGYdnklkfOeFRvZ599dhYrOdiQSwrVG/XLNWvWZDGq35K7HLmKXHPNNVnszjvvzGJTpkzJYuQGSC5nEjvgnHfeeVmM7v3+++/PYuQWU6pzcm0hFyR6HmoH6helOYzmnM66u5jjl9Z5nZzxqF/SuZL0/PPPZzFycKJzn3nmmSxWcs3aunVrFqNxQXM6zdU/+MEPstjUqVOxbFoD0Bw6YMCALEYuaUOGDMli5OAk8VxPsVWrVmWxWbNmZTFyyCq5V9IcTC5r5JZHcyDNQ+SUKrHbJEHzHa35qA9I5WdvhfofOWxR2VTnJaj/PvLII1mMnAipX5XqkdwzL7zwwiw2cODALPbEE09kMeq/pXmE+gblUspxtG6i+Yb6Rel8qsuD4U9qjDHGGGOMMbXGLzXGGGOMMcaYWuOXGmOMMcYYY0yt8UuNMcYYY4wxptZ0qVGAlAv2X3jhhewYEjdKLHAnEf1zzz2XxUjg26dPnyxGQnSJjQJIeDhv3rxKx5FgjYTfkjRp0qQsRgLH//bf/lsWI0E2ictI3CixUJUEeI8++mgWI+E3CQKpD5TKJsFbSRDeConWqW0kacuWLVmMzCaoHaltSLgqSSNHjsxiJB7csGFDpRjVeUm0TkJBEk2++c1vzmJUl9S2ZFQhsQCURKnf+973shiJbkv1S1A5JIrevn17FiMhI9VvSfhKxhLUh8yJR8+ePTNRLOXCl156Cc+n/EhzCYn9yWyF5jHKHZK0cuXKLEbz96JFi7LY+PHjsxiJqskQQOLcRff5rne9K4tRfuzMeKb5kq5J9VMyPmiF1ikS5z2as2iuplhV0xtJ2rZtWxYjswkShJM5DsUkXo9Rn6a1Ez0jic5LJhDUf+maNO6ozai9FixYgGXT+bRWWbhwYRabM2dOFiOxPhkCSNKIESOyGOU9ypm0zqZ+VSqb5jZadx0Mf1JjjDHGGGOMqTV+qTHGGGOMMcbUGr/UGGOMMcYYY2qNX2qMMcYYY4wxtaZLjQJOPfVUjR49+oAY7X5KOxFLndtduRUSvO3cuTOLkcmAxMIt2vV11KhRWYzEhLSb8IMPPohl03O31qPEAlAS4JHwisRcEgsc/+3f/i2LUZuR+JTEbqUd7wkSsT355JOVrklCvdJu7tSv6Blpt2aq85IwjgTuJFykvkq7R5OAsyRyrWp8QGOHzB0oVhI1Dx8+PIv99Kc/zWIl05BWqH5Ku2FTv6xqzkBiWDI9KM1hVU0tzInHySefrKFDhx4QW758eXZcKUfR2CWB71NPPVXpXBq7pTxBcx7lDhJqk1nK+eefn8VK+ZGekebQ3bt3V7ofmu9KYmWadygfkWCe7mfQoEGVy6Zr0vm7du3KYpTfKJ+U5m8qm8ToW7duzWK0niFTConzI90T9WlaD5HxQMmoiObqqusKqnMyuKE+IEnTpk3LYmSGQMYQ1PfJsIfyliStXbs2i5FBArUt5UcaY5SDS5Tap4Q/qTHGGGOMMcbUGr/UGGOMMcYYY2qNX2qMMcYYY4wxteaQLzURcVpEPBoRCyJiUUR8shnvGxF3RcSK5k/eIcoYY4w5DnF+NMaY7kMVo4CXJV2bUnouIk6W9EBE3CHp1yTdnVK6JSJulnSzpI8e7EJ79+7NBFQkLCqJ/0mkSGJgEv2uWLEii9HOwWPGjMGyFy9eXOlYEkeSmOvqq6/OYr/yK7+CZa9evTqLffe7381iZD5AwjYS9JV2tqWyqX1IDEblkPC7szvGtkKmCdS21H9KQkgS9lcVmlL9lER5BJkX0G7adByJ22mXX4lFkyTaJaEe1cVFF12UxWi3cEmaO3duFqOduEnsSW1D80hpp2iqDzqfYiRyrRqTygYCprYctfwo5bmLhN8l4SyJ1mms0LxB/ZLmtpL5Bs3106dPz2Ikor/rrruy2K/+6q9msbe+9a1YNpkN3X777VmM5jt6HsonJcOSjRs3ZjGqN5rHKPfQ2oVE2qVrkmid5nQ6l+b0Ul8jYwk6v6qRE7VNqXzayZ7WWFSX9Nw0z0tc72QiQcYdlHvIRIrWbKXzFy1alMW2bNmSxaoaFZHBRilORgNk7kDH0fquZJxEfahkTlLikJ/UpAbtrXZy81+SdKOkW5vxWyW9pVMlG2OMMTXG+dEYY7oPlTQ1EdEzIuZL2ibprpTSI5IGppQ2S1LzZ+7V2zj3/RHxeEQ8TpaBxhhjTF05Wvmxqn25McYYptJLTUppX0pplqRhki6KiNxEu3zul1NKs1NKs0sfORljjDF15Gjlx9JXFo0xxlSjU+5nKaXdku6VdIOkrRExWJKaP/Nd/4wxxpgTAOdHY4w5thzSKCAi+kvak1LaHRGnS3qtpE9Lul3STZJuaf68rcK1MlEW7QRLYiyJxbckeiShHomnFi5cmMXofiSpb9++WYwEYgMHDsxiJH6aN29eFiuJqidNmpTFJkyYkMVIXEYxEsaVxPp0TyT+o2ckUSgJ5kuf4A0ZMiSLkZicdh2mHY+p7FJ7k+CNRIYklqO+RteTuP/SM9JXN0lcSWJE6pMS91+qSxLqzZ49O4uRMPMXv/gFlk3CThLOUjuSCQQJZAcMwG/8YJx2gD7nnHOyGM1B1IdK/YrqiJ7H1IOjnR9b+zHN3yXTEYrTXF9VNEzGAyRMlniskKB73LhxWYxMUB5//PEsRjlPYrH1lClTshjlI3puEv+XvhpIOYHmLBK80/10xjiJ5mraqZ3mfzJLoXyyadMmLJuekWJ077S+K4n1qa+SYJ7akeZqMt4omV/QNek+KfdMm5Z/WEtjhPqaxMZNlDMpd9BajuYGum+Jn5v6C5lFUIzuu2TiU7UdD0YV97PBkm6NiJ5qfLLznZTSv0XEw5K+ExHvk7RO0m90qmRjjDGm3jg/GmNMN+GQLzUppScknQfxnZJe82rclDHGGNPdcX40xpjug7/3YIwxxhhjjKk1fqkxxhhjjDHG1Joqmpqjxv79+zPBM+1kPHz4cDyfRNkjRozIYiRCmjx5chajHWNJvCdJffr0yWIk/iMhMN03CS5LO6eS+IoEb1RvZDJAdU73XYqTwJxEpbTLNEGCUomfm0SPVA6JFklwVnpuEnpTO9I9lgR4BAkxSThLInoSOE6dOjWLlYw3KE7CQ6ojMjNoa2vLYqU+QAJSEiOOHTs2i5HYePny5VmstC8WmSmQAJQMH6hfUduUduKm80t90JxY7Nu3LzOsoDFx1lln4fmUz2bMmJHFSIxLQniaL0mkLXF+pHFBY5LOpRyzePFiLJviNG+QEJ7myzVr1mQxMgSQOA/TsWSkQ+uUqjlTYhE9mSRR21I5ZFpTEmnT81B+pGtWNXqReB6l/kvl0DqHch7VWelYyvdUl2QAMH/+/CxWMqAorQVbofXv9OnTs9i2bbn5Io0xifsVtUPV9RStpcg8QOI5o2SyVMKf1BhjjDHGGGNqjV9qjDHGGGOMMbXGLzXGGGOMMcaYWuOXGmOMMcYYY0yt8UuNMcYYY4wxptZ0qfsZubuQCxI5BEnShg0bshg5vpATxjnnnJPFyOWhb9++WDa5VPTr1y+LkQvYgAEDshi5R5XKpmtu3bo1i5Gj2hVXXJHF6L5L7i50zXnz5mUxcoyh9iIHmmHDhmHZ5EhFTiXkPkLOHuSyVnLhoD5Ezid03Nq1a7NYyeWEHFqWLVuWxcgBhOqHHGjIxavEwoULKx1HdU4ONiWHFXJJIdcWcoIjFxmqn/79+2PZ69evz2LkMkX1Rq4/9NzkOlg6n1yQzInH/v37M/cfyo8lpygaK5RTaI4gRzVyKis5r9H8Ru5RNN9RTiBXSHK+LB1LjmjkmjV79uwsRu5cJRcwcmuidqB8Tzm8Z8+eWWzatGlYNt0Txch9ivI9PQudK/F8S32V8gTVRWmupj5ILptVnWhp7NA6UOL1Qsn9rxVaw9K4Kzl00vlTpkzJYpS3lixZksVorUDrGYmd26guaHy3ru8l7pPkRlw6n57xYPiTGmOMMcYYY0yt8UuNMcYYY4wxptb4pcYYY4wxxhhTa/xSY4wxxhhjjKk1XW4U0CooJGFcySiAhFYkEiQRG4ngBg8enMVWrFiBZZP4j8RXJMwksT0J40gkJbG4jUR5xJ133pnFhg4dmsXGjx+P55PJwaBBg7JYVWHmww8/nMUuvPBCLJtMIChGkAiO2iGlhOeTWJSgfkUizJLgkoT5JIwjg4SS0K8VEqRKLAgkcSWJMGksUp1RX5PYuGP16tVZjNqMnptExGReIXFdUp+m56axSOL/0hxGwlCaM8hkwxzf7N+/P+sf1Ncp70gs4qfxQ3mP+jUJ+EnkLbHhCl2zal8nEXJpDqU5nOqC5rb77ruvUtkjR47EsilvkjkK3TvNv5Qf6X4knktoziJzBqoLMnso9TXKw5T36B5pfVbKUdR/6Zo0p1OOofUmGftInI9o3VXVxIfqjNZXEovraQ1KAn5qR7peaSyTcQLlR8px1FfpHslAQuL1VMnIoYQ/qTHGGGOMMcbUGr/UGGOMMcYYY2qNX2qMMcYYY4wxtcYvNcYYY4wxxpha06VGAWeccYZmzpx5QIxEdSURfFUBFIkWSXDWp0+fLEYiSonFwCRYW758eRYjwSUJpUridNq1nmK0UzoJ6J544oksRmJCSZowYUIWI/FqVWE+tXdJNEaiUnpuEigSJHYrGQ9Q25LIkO6dhG1kmiCxmJH6L90njZNt27ZlMbpviccT3TuVs3PnzixGYn26H0nasWNHFiPBJe34TcJDmgfo+SQWEVPZZBpSqstWSkYBQ4YMyWJkukBj1Bzf9OrVSxdccMEBMerr1Fclnlupr1MuI8MdmnNKonUSqNP4I8E8Cf07M8/T+ZTPyJCAjqO6oLotnU8xEnlTO1B7l8qmuYjqguZGai/KRaU5lPI9ibzpfDKQKBmjUH+jeiNhPuUyMo8prX2oLWjNSFBd0HOX6pfWH1XXq1VNO0rrLpozaC4gcwcaoxSj8S2xcQKtP5YuXYrnS/6kxhhjjDHGGFNz/FJjjDHGGGOMqTV+qTHGGGOMMcbUGr/UGGOMMcYYY2pNlxoFnHTSSZkQaNiwYdlxJLKSWKy0cuXKLEaibBKt9+vXL4uVhFuTJ0/OYiTYJGE+3Q8ZCpQgkRftCEy7t9Pu9CToLkGivMWLF2cxEnORQJHE/6UdY+neSSxHgreSmLYVai+JhWz0jNS2JIwbPXo0llNVhE91SaJQeu6SwLZ3795ZjOqcxiMJTel+SjtxU71RXZAYttVsRGLR4sSJE7Fsqg8ajyQ+rbpLNbWXxGYVJAo1Jx6UH0kITHOyxGOSzGOqCuZpzioJfEnQTXM15TKac9ra2rJYyUCIDHZozqK6XLVqVRajebFkEEJicrp3Mg6pajJTErLTGoDmJzqf2pHE/6XnprKpD9A8TzmKBOISmzasW7cui9F8S/2iqsFB6VhaR1I5VG8kwB8+fDiWTeYQ1GZ072RMRceNHTsWy6Z5hJ6bnpFitG6n3CpxHXU2P/qTGmOMMcYYY0yt8UuNMcYYY4wxptb4pcYYY4wxxhhTa/xSY4wxxhhjjKk1XWoUsG/fvkxYR8IiEl5JLBAjwRrtBE5iIxKtkyGAxAKmqjv67tq1K4uNGDEii9HO4hILO0lsR4LAUaNGZTESnJHAsFR2SdjfCtUvicZIKCqxiJ/unWIkdqP2Kj0LnU8CcxJHkqiutMM89fWSaLIVEjJSP696PYlFsmRcQIL3bdu2ZbHSWC4ZNLRC/ZLEuf37989itLOyxPMD7XQ+ZMiQLEbiZ+orJSEkiYNpTJgTj/3792eCXsonpfly9erVWYzyBInjqf9TX50xYwaWTYY/lI9IOE5zI+Wt0hxKz005gcTXNI/RmqI0RsmIoWSm0AqtKajOaf0gsekCzYN0PzQ/0dxP/U9iQyVqn6o72VNdSJwnyBSAhPDUjtTPyTBK4vUCPQ89N619KDeXxjKVQzGqNxp3lEdpPEjSjh07shjlXFr7UDlVTSkkrvNSLi3hT2qMMcYYY4wxtcYvNcYYY4wxxpha45caY4wxxhhjTK3xS40xxhhjjDGm1vilxhhjjDHGGFNrutT9LKWUuVSQcwS5Y0jSpk2bshi5j9A1yeWKXDTI+UFiB6gJEyZkMXK4IBcOcqggdy2JnUbIUYIcY8i9hBycStC90zOee+65lcq5//77s9ju3bux7GnTpmUxcqEhFw9yriKXKnJNkcpt0Qo5fpFTyMMPP4znkxvQxIkTsxi5gtC9U78gV5vSsdRmdI/kqkRuKCUnIHJkI/c/6hs0vskhaPHixVg2tdnJJ5+cxagPUJ2XnFyqll1yoTEnFnv37s3yDI2zkgsYzdXLly/PYjSmaOzSXLtx40Ysm5wGaQ6m56FxTzmv5BRFz13V6YxyGeXMUj6gPL5169YsRmua0aNHZ7Ennngii5Xcn2bOnFmpHHoecueiZynVOc2D1C83b95cKUbrK4lzNjm8HYnTXsmJk9zGaJzQmKD+QnVeWn/Qeoruk56b+gCNJ3INlHgNTDmOxnLV8V1yE6SyybHuYPiTGmOMMcYYY0yt8UuNMcYYY4wxptb4pcYYY4wxxhhTa/xSY4wxxhhjjKk1XWoU0LNnz0yITELGkjitJFJsZdiwYVmMxHYkfiIBs8RCZLp3EmSROK1Hj/x9ksTKknTeeedVuuaIESOyGInyqOwtW7Zg2WeddVYWI+EXCeiobKrzklHAmjVrKt0PPQ+Jy8gsgkSmErcFibxJEEjPQ4LHEmQKQOJIOo6E+SSYlKqLkMePH5/F1q5dm8VIWElCRklat25dpfshaB6gcVcSYVKbl4SqrZDpArU3jRGJTSRKwm9zYnHSSSdl/YvmZRLlS9X7Ic3VJbF0KwMHDsQ45Wy6HxLw0xxB+ZqMfSR+RsoTdO+UJ8g8oK2tDcsmwTOtIcaOHZvFqH5oDiwJpWkOpvxK9UbzZcmQgKD8SH2A5mB6npI5FOV2qt9+/fplMepXlDNL6w9aL9D5ZBhF+YTapvTctHYiw4eq/YXqopR3qE/TGoLWPnSP9Iw0PkvllMyGSviTGmOMMcYYY0yt8UuNMcYYY4wxptb4pcYYY4wxxhhTayq/1EREz4iYFxH/1vz/vhFxV0SsaP6svqOjMcYYc5zg/GiMMceezhgFfFDSEkntKsObJd2dUrolIm5u/v9HD3WRVmETCbwoJklTpkzJYiRwJDEiiZWqmgdI0rhx47IYie0oRuJgEj+Vdi2uuoM6CaBJoEjllERjJPSjXedJiEaiMRJrlnZUJ3E93TsJX+k4am8SIpYgcWTVHeZLYv3hw4dnMRLRUZ0T1K9I3CixoJDqkvoamVLQbsB0vVLZJMInswh6RmrbkviZ2rzqLuIrV67MYiTELYlPiZJZhakVR5wf9+3bl4mtqQ+XBPNjxozJYjSvk6CbxPFEqa+OGjWqUtlVjTZIrFwSDNPcSvmIDEaozqh+aA4s3ScZptBx1I70LCWTmdJ6oRWa/6kdO2NeRG1BeZzWQ/TcpTXAoEGDshiNCcqZ1P+on5eekaC23bRpUxajfk5rhVJ+pDFBx9LaknIhtXdpPFVdH1JdknkFtU3JxIfipWNLVFrRRcQwSb8q6e87hG+UdGvzv2+V9JZOlWyMMcbUHOdHY4zpHlT9M/VnJf2xpI6vewNTSpslqfkTvZAj4v0R8XhEPE5v7cYYY0yN+ayOQn4sfZprjDGmGod8qYmIN0rallKaczgFpJS+nFKanVKaXfrY3BhjjKkbRzM/lvZuMMYYU40qmprLJb05It4g6TRJZ0fEP0naGhGDU0qbI2KwpHxnQmOMMeb4xfnRGGO6CYd8qUkpfUzSxyQpIq6R9JGU0n+KiL+QdJOkW5o/bzvUtXr27JmJvEjQN3ToUDyfPp6nXd5JxEzCZBLgLVy4EMseMmRIFuvbt28WI5E4CfBWrVqVxUoGCXT+1KlTsxiZIdCuuBs2bMhiJGyTWJxGQrSqxgdk9vDkk09i2VQOxagcqrPOCLKrtiN9+kj3OGzYsMplE7Rr9uDBg7MYiRZJ+CpJ/fv3z2LLli3LYtT3SVhPIsqSAJnG/eLFi/HYVqhtzj333CxWEkLSbs9Vdzonwwb6Wi3tei1xH6S2NfXgaObHHj16ZPM1ibxp3EosZt+yZUsWo/xK+ZHmkiVLlmDZlHNprJBgnsYuPQuNR4nzHhkXkKia5iwazzQHSiygrjrGSaBOO8TTWqF0LK1JqA9RLqN5tSQZoHqj82ldQeuPkqkLQfmenpFMBrZu3ZrFqP9IXJdkXEPHUdvQfdP6VeLcRfdO5VBfo/qlNpS4zSnfk4CfyqaxXDJIoLVTZ7/hdST71Nwi6bqIWCHpuub/G2OMMSc6zo/GGNPFdMbSWSmleyXd2/zvnZJec/RvyRhjjKkXzo/GGHNsOZJPaowxxhhjjDHmmOOXGmOMMcYYY0yt6dTXz46Ul156ScuXL89irZTEaSRWOuecc7LY6tWrK51LgsvJkydj2ST+I1ET7RBPAkcSzNP1JBYx046zJBoj4wPaRbkkVqZ7J5EhQUL2qjsMl+6JnpEElyQcJKFeaTdhem5qHxKKdmZnZuq/JOSlskmET2YTpX61ffv2LEYC29KO1q2QKUWpX5Fol84nMSM9D9VvSXxKdT5y5MgsRn2I2pt2Ki/t9k2iUhJPmxOPV155RZs3bz4gRn29lB+pz9EYIPMAGuMk8i6NKZovKWfSNalsyh0lMxvKhRSjsTt//vwsRnNgaf6meYzWGgTNQ7QeKuVHmhvpfDJiqLrrfCnXU10SVUX9JdE61RHlOJpDqU/S9UoGQpRfqV9SH6CyKb+V8gTl5qrGSfQ8tG4q5R1aH9IatKp5ABkFlNYURyM/+pMaY4wxxhhjTK3xS40xxhhjjDGm1vilxhhjjDHGGFNr/FJjjDHGGGOMqTVdahQg5SImEh6S2EjiXUhJUEXiKxLLPfvss1nsrLPOwrJph1cSvNH9UNkklCqJMEn4Rbv30vOQYI1ElPQsEtcH1S8dR+1Fz7106VIsm3b6pZ2vn3766SxGz9MZgSIJIcmAgnYYLu1kT4wbNy6LkdkEiRFJxEljpyRGJEiETG1LOyEPGDAgi5GIXuK+QfVGz0Oi3ao7dks8dkgISfW7du3aLEbjtmTOQJSE3+bEIqWU9XcSRdP8LbEImvo15SgS6NJ47NOnD5a9c+fOSuVQPqKd36vmrVKc7p3E0pRbSdhcMimgOq8qoqd5g+67ra0Nz6d5g+6dnpvum/ItzZWlY9evX5/FWo0vJG7b0vqDciGtp6ifE1R2CRLCU9uSeQCtc2itQWNE4vog4wLKj1X7VckEojOGBq1QH6A+VJpH6J6orx0Mf1JjjDHGGGOMqTV+qTHGGGOMMcbUGr/UGGOMMcYYY2qNX2qMMcYYY4wxtcYvNcYYY4wxxpha06XuZ/v3789cIcjt4JRTTsHzybmCXB369++fxchBga5XclogRwlywqCyyaGCXFfIMUNiR5OVK1dmMXLSIPeRBQsWZLFevXph2bNmzcpiQ4cOzWLkPkUuGuR0Q65tEjtkkaMVxagdq7qHlOLkGENOLORWQy5GErsO0ZigsslxiBxxSi5g5BpEDi1Ub9S25IhWGssE1Tk5qpGbD51bcqGjY6kPUoycXOgZya1OYve+kguNObHYv39/1jcpJ5TmapoPqG+OHj06i1E5NH7IaVJityYaZ9TXaX6h3ErHSTznkSvljh07sti6desqlVOav2fMmJHFaA1AuYzqgmK0VpA4J1CM+kvVOi+5hVHbkktmVfe+Uo6iuiRnScqj5IhWyvcErbto/qe5ntZDtCYp5Ucae1TOsGHDKpVNTm6l8UR5j8qm+qW+Rs9IY7FUdmdxNjXGGGOMMcbUGr/UGGOMMcYYY2qNX2qMMcYYY4wxtcYvNcYYY4wxxphac8yNAkhYRAIkSRoyZEgWI3EbiY1IiEbCNhJKS9UFzyTMP++887IYCfpIACdJ69evz2IkzJwwYUIWu/fee7MYCQ9J5C1JDz/8cBYbOHBgFnvXu96Vxfr06ZPFSGD+4Q9/GMu+//77sxiJxHv37p3FqC5JpE2iOolFgiSso341efLkLHb11VdjOYMHD85i1BbUp0kYPG/evCxGY0Ri0eTw4cOzGIkESTBMfXrUqFFYNo1x6tNUNt03tXdJgE+iaBKa7tmzp9K51K9KYm66dyrbnHhQfqT5sgT1IxJlk6EMlUPjuZSbqwrcKT/S/E0Cc8onEudHyhMjRozIYlQ/dN8bN27Esmns05x+7bXXZjEymaE6v+mmm7DsFStWZDFap1COo/mJ5trOmPiUDA2qlD116lQ8lupy7dq1WYzyNbXtkiVLshjlHYnnamozyglkCkD9nNa0Eptf0Bij5966dWsWo2ek/CZxO5JhD/Urukcym6C6KN0TjYmD4U9qjDHGGGOMMbXGLzXGGGOMMcaYWuOXGmOMMcYYY0yt8UuNMcYYY4wxptZ0qVHASSedlInMSRhUEgSSWI8ERyXxdyskaiKBocQGAiS+IsElCbdop1wStkks3KLzSbB21VVXZbEzzzwzi23atAnLJsEb7QZLx9F9k0iwJBqjYx966KEsRoJJErzTPZZ21aW2WLZsWRabPn16FrvsssuyGO1ELLGIjo4lsT/1SWpb2kFc4rFHbUF9jUSlVQ0OJB57ZLpA90imANTXqL1L0LG0qzPdI42dkrEICV+pLs2JR8+ePbPxS/2yZGazbt26LEbjmeYXKod2IS+Jqgka4zSnk9h56NChWay0GzwZ/tD4I5ODK6+8MovRnEwGBxILumnOouMGDRqUxWj+JnF66XzKUatWrcpiVQ1hSsYQ1BZUR9SOV1xxRRYr9SsypKE5mKBrUv1SXUjch8iMg+6HzDgoh5PRhFTdlIjage6bxmIpP1IupXagcUIGErQuLRnpUH8pjb0S/qTGGGOMMcYYU2v8UmOMMcYYY4ypNX6pMcYYY4wxxtQav9QYY4wxxhhjak2XGgWQEJJEj7RjvdT5nUU7QuJiEpKRoE9iURQJskjgReYDJN4jQbbE4qn77rsvi5Fgee7cuVls9uzZle5RkkaOHJnFpk2blsVod3sSjZGJQ8kogPoGiUL/+Z//OYuR2I0EqSTeKx07fvz4LPba1742i9Fzl0R5VQXqZJ5Bz0hCSBIJStynqWzqV6V6a6XUr0j8Sn2DxiPFqC6q7nAtcb3RTuUEiUdLBgkkICURpjnxiIhszqO8VRKOU34kITHlPRp7NDeV+irNMTSmaN6g+yHTEZr7Jc7DCxYsyGJkNPTkk09msbFjx2ax0u7rZPxBAn6aD6ht6BlLz02mRGRSs2XLlixG7VC1r0hsKkCGNFOmTMli1FdKJhAkjiejiyFDhmQx6qu0ninlRxK4Uz8gsT+ZKdF6hsw4JF7zUVtQO1Q1ryjlZqoPuk96RjKWoPYqGVDQfFcy0CrhT2qMMcYYY4wxtcYvNcYYY4wxxpha45caY4wxxhhjTK3xS40xxhhjjDGm1nSpUYCUi5NIkF0SBg0YMCCLkQiuX79+WYyE7CTwLYkwSVRFQmQ6jmIkQibhtsRiORJ0k9hz1KhRWYzqjMTgkjRnzpwsRqI+2iWYhKYXXHBBFiPBmcTCV2qfGTNmZLEf/OAHWYwElyUBKIkM3/Oe92QxEvBTe5WMAkiMSH119erVWYyErzRG6DiJxx71IRpPVG9UFyUBaNVdgul+iNIOxQQJIam9ybiD2otEt3ScxP2AhM7mxGP//v3ZeKGcQGY0Eo9TGvtkxEP5hMbUiBEjsGyaD2geI4EwjR8yCqD5ReI8Qc9D9UO7yVN+pLlSkpYuXZrFaM67/PLLsxitH0j8TwJzidcv1GaUc2+99dYsRvVDZUg8Z1133XVZjOZaErxTPUpsrELtQ2tGMmcgY4dSfqT+S32VDDFI8E5jpGQos3Xr1ixGgntqHzJeojUomQxI3N8ob1Ffo3LoXDJXkHjslMwUSviTGmOMMcYYY0yt8UuNMcYYY4wxptb4pcYYY4wxxhhTa/xSY4wxxhhjjKk1XW4U0AoJr0q7lZNAksSDJNKqKiQuCZhJrESiKDqOyiYBHe12K0krVqzIYrTr8apVq7LYJZdcksVIMF8SblXdAZ0EXiSEpHNpJ+IS1LazZ8/OYiTA+7//9/9msZIxxC233JLFaNdiEhOSyK8kHCdR38qVK7MYmQ/QztVUDgneJWnSpElZjMZTVeHg2rVrs1hJaEr9jUwBSBxJ53ZGhEn3TqJJEoCSQHbdunVZrGRwQH2I6pyMRMyJB+XCksCX+iv1LcpHNG+QSQGJtCWe12n+p7xHx9E8X8oTZCpAcxsJwmn+pRxeMjwhAwHa0Z2g9QPNLyWDBOobNA9OnTo1i914441Z7Gtf+1oWo3qUpD/6oz/KYpSjaG5cvHhxFiuZBVH+oPmfDHLIQILqh4wzJGn8+PFZjHIh9V9qG5rTqc4kzl1V5wIaD7TOKRlTUf3SuC2tnVqh9SuZRUjcFlTOvffeWyzPn9QYY4wxxhhjao1faowxxhhjjDG1xi81xhhjjDHGmFpTSVMTEW2SnpW0T9LelNLsiOgr6duSRklqk/T2lBILM4wxxpjjFOdIY4w59nTmk5pfSSnNSim1q7JvlnR3Smm8pLub/2+MMcaciDhHGmPMMeRI3M9ulHRN879vlXSvpI8e7IQePXpkbkbPPfdcdtzpp5+O55PTAzm5VHVdITcUclsqXZOcNMhp6oorrshic+fOzWLkmiWxA8lDDz2UxcjJ5cc//nEWo/vet28fln3ttddmseHDh1cqm5w9qOzdu3dj2eReQs4e5NBGLlOXXnppFiNnGIldaJ588sksVuovrZTcPqicyZMnZzFy5KGxs3r16splk5vgkiVLshg5vI0aNSqLvf71r89iX/nKV7BsGuPkBlTVIeh1r3tdFrv11luxbHIsovFN/Y/qh+YW6n8SOxmV2sfUnk7lyJ49e2YOZjTGS3MOuRbR+KFxT5CjGY0Jid3+aF6n88m9knJzKU+QCyQ5LtGc88ADD2QxckcsuVdefPHFWWzMmDFZjJ6bxn3VeV5iVyhqM8q55CQ3a9asLDZlyhQsm/oVua9Sn6T+O2zYMCyH6oPOJ1cyylvkslZqW+pv5I5L/YVcvK666qos9s1vfhPLrurgS2XTcRdccEEWu/vuu7Fsmh9o7FC/pPohV8bBgwdj2VROyaWtRNVPapKkn0TEnIh4fzM2MKW0WZKaP3NPPWOMMeb4xznSGGOOMVU/qbk8pbQpIgZIuisillYtoDnBv1/iv+YbY4wxNeewcmTH/Fjaj8QYY0w1Kn1Sk1La1Py5TdIPJV0kaWtEDJak5s/8e0GNc76cUpqdUppNH0MZY4wxdeZwc2TH/Fh1g2hjjDHMIV9qIqJXRJzV/t+SXidpoaTbJd3UPOwmSbe9WjdpjDHGdEecI40xpntQ5etnAyX9sCkMO0nSN1NKP46IxyR9JyLeJ2mdpN841IUiIhOP9+3bt/rNgniK2LJlS6XjSKhHImSJhXVjx47NYnfddVcW+/nPf57FLrnkkiy2cuVKLPull17KYjfccEOl89/61rdmMRJFk/BPkh577LEsVlVsd+GFF2axhQsXZjEyUpBYxDly5MgsRvdOfWDo0KFZrGSQ8Mgjj1Qq5+yzz85iJJYr9SsS25EwbtmyZZWOo694rl27Fsu+8sorsxgJdKdNm5bFyGDhb/7mb7IYmUpI0hve8IYsRqYCJHKldqB+WqpzGhNkNvGjH/0oi/Xr1y+LkVCZDENK90QGKKZWHLUc2Wo6QaJoGhMS50ea68lsheaxkikAQWPgvPPOy2I0r86fPz+LzZw5M4uRwYfE44cMbkg4TmJ7mleff/55LJvunfI15WZ6xk2bNmUxahuJcwJ9G4aeZ8OGDVmM+ho9iyTNmzcvi1Euoz5Jubk0V9O9k5Cd6pfWKWRoQcdJbNBE44nWsNSvvv71r2cxWs9IvD6ktSW1D8WWLs2/DVsyqHnLW96SxWiM3XnnnVmMhP6UM0tmYNR/S2u0Eod8S0gprZaUjb6U0k5Jr+lUacYYY8xxhHOkMcZ0DzqzT40xxhhjjDHGdDv8UmOMMcYYY4ypNX6pMcYYY4wxxtSaqvvUHBVSStq7d+8hjyvtHEyCI9pBl0RnJNwioX9J4HvfffdlMRJVv/nNb85i3//+97PYo48+msVImCaxuO3222/PYrSLLQn1KFbaVZfq6KyzzspiJOai+6Zdi2nXYYnbgsSidD6JaekeSTwq8Q7FVXctpucuid1ob4qtW7dmMdpxmcYJiehJ+CdJTz75ZBYjYeab3vSmLPaRj3wki73jHe/IYiWB7ec+97ksRv1/1KhRWYzum4SQpbmG+gYZBdDz0Hi44447sljJvp7uqbNCSHN8sn///my8kCi6ZCxBOY5EwyQ8p3mIRMwlQfeiRYuy2LPPPpvF3vjGN2axn/zkJ1mMxvOYMWOwbDJHmTt3bhajebnVmEHiZ6Sd2yWes6h+ac6hXdXJWKW0ozrdJ+UOilHuoL5WMplJKWUxWlfQvVc1Z5DYrIKep6qBEM2/l112GZZNz05GAZdeemkW+6u/+qssdt1112UxWkNK0re+9a0sNmPGjCxGBlY0dsi8qNSnqW/QPEKGO5T3yMSnZEJCcwYZUBwMf1JjjDHGGGOMqTV+qTHGGGOMMcbUGr/UGGOMMcYYY2qNX2qMMcYYY4wxtaZLjQL27t2bCXJJoF4S+FKcdjK++OKLsxjtONvW1pbFSsI42h2Zjv3qV7+axUjAf8EFF2Sxklifdm6lY0mkRQJQEjuXxMokACUh5BNPPJHFaMdjEtv36tULyyZRHokZq8ZI7FYSvlJ/oXYkgSMJ8Ep9mowPBgwYkMWq7sK8fv36LFYyYiDhIZlx/OEf/mEWoz40dOjQLHbzzTdj2d/+9rez2Cc/+cksNmfOnCz2rne9K4s9/PDDWaxkAvGd73wni9HYofq5++67s9js2bOxHGLx4sVZjPq5OfHYv39/JoqlvkGCbInnGBLRT5s2LYtRLqS55OSTT8ay6Zokgv7ud7+bxSiH05gqickffPDBLEZzMM1PJFqn4ygmcR1RPqPjVq1ahddshXKmVD3vkbEE5ULaYZ7E9pK0adOmLDZkyJBK91MSqFcth1i3bl0Wo3un65FJjMQifDKb+OxnP5vFKJ+QmcG9996LZf/Zn/1ZpXJo3UXGPmRUQWscSfr3f//3LEbmUGQUQH16+vTpWYz6hcRrldIarYQ/qTHGGGOMMcbUGr/UGGOMMcYYY2qNX2qMMcYYY4wxtcYvNcYYY4wxxphaE7Qz7KvFwIED07vf/e4DYiSEPP/88/F8EimSAI92CSZhHIkEJ0yYgGWTwJfE+rRLMJVNAv4vfvGLWPaIESOyGO08TDut//7v/34WI1MAEqxLUv/+/bNYSajaCu1MSyLBkmiMhKannXZaFqu6czAJIUviUxKsUf/btm1bFiORYMkEgvoGXZPuffny5VmMdrimviux+O/tb397FrvtttuyWN++fbPY/fffn8VI3CjxLuL0jFdccUUW++hHP5rFSJz7gQ98AMv+whe+kMVICEzXJBMHEvLSrs6S9Ja3vCWL3X777VnsoYcempNSqu5AYGrPwIEDU6sJBuXncePG4fk0fkgETXMozW0095OoX+L+TnMbnU9rALrHH/7wh1g25VIySCCROM13lE9KOYrE8XTv1DZPP/10FqPcTLusS7xLPOUe6kOUh6m9SgY3JDynetuxY0cWo/YurT/o2K1bt1a6n9WrV2cxaq/SXE3z/6WXXprFyMyGxg6J+smER5Lmzp2L8VYo33/mM5/JYmRy9Du/8zt4ze9///tZjNqW8h6tqWmdQcYkEuf7Bx54IIs9/vjjxfzoT2qMMcYYY4wxtcYvNcYYY4wxxpha45caY4wxxhhjTK3xS40xxhhjjDGm1nSpUcDIkSPTxz72sQNiJPoqibdph/CpU6dmMRLbkViJRGglQTdBZS9btiyLkdD/xz/+cRYjMZfEgnnaYf61r31tFjvnnHOy2Nq1a7MYPYukbIdriXedpxgJ7ai/kdmDxIYPJMJ8/vnns1hJ2NkKPZ/EAknqLyRGPPvssyuXQ+JMam/q+yQUHT9+fBYrGTssWbKk0v1QvyLx3vve974s9hd/8RdY9pVXXpnFaOdhGidkxkFC5/nz52PZM2bMyGIkICUxI80tJFItjSe6p4kTJ2axL37xizYKOMEYPnx4+tCHPnRArOqu8xLvHE/GNyT6pTxB8yqNM4lFw8OGDctiJHon8wCaXyifSJzPKD+SCJnyFpnEkCBb4vUC3SfV7+mnn57FyFCA5vnSsXRN6hdkFEDrrlIepTmPcjvdO903meNIbKZA1yRTIjLJIIOlzhgV0bFk3EH979d+7deyGJnWSNLs2fnUT/lxwYIFWYzGKK0B6B4lXq/SPEJGRVTntPa58MILsWwyu6Ln/sd//EcbBRhjjDHGGGOOT/xSY4wxxhhjjKk1fqkxxhhjjDHG1Bq/1BhjjDHGGGNqjV9qjDHGGGOMMbWmS93PBg4cmN797ncfEDvjjDOy48hlSmLXDHJTIZeJBx98MItR2eT+JLEbBV3z0ksvzWKLFi2qVPa6deuwbHpGcgHr06dPFiMHJ3J6IlcQiV1tqrrnkOMGubPQ9Upln3LKKVmMHGiquopRO0jsGEOOaNRmmzZtymL9+/fHcsgtj5xcyJGn5KjWSqlt6d6rti25CVLblFzAvvWtb2Wxqg565MZGLnQlh5W77rori9F4uuSSS7LYD37wgyzWt2/fLEZ9V2I3Hzr2xz/+sd3PTjD69euX3vCGNxwQ6927d3Zcyc2QXI9ozrr22muzGOUJKpvc/yRp7NixWYyc/mbNmpXFyIWRxn3JJZPcsGg8k7soXXPMmDFZrDR/U53T+qXqOufMM8/MYjSvSty29NzkakY5k+qiNI+RMx45qm3YsCGLkeMtOYZK7LBF55MbW2ktV7VsWi9QfqR2GDBgQBajcUvOXpJ05513ZjHqG7SWu/rqq7MYuSiS66DEdU7rNhrLDz/8cBaj/ldau9CxNA898MADdj8zxhhjjDHGHJ/4pcYYY4wxxhhTa/xSY4wxxhhjjKk1fqkxxhhjjDHG1BpWHL5KREQm9ifBGgnOJGnEiBFZjAR8//Iv/5LFBg8eXKmcc889F8smARQJiRcuXJjFSMD/4osvZjESl0ks1hs/fnwWI1EeHUd1VhKA0n2SiJPE7SQmJNE51Y/E7UPiShKdkbiy6rmlsleuXJnFyMSBRHkkZJdYOE71VmqfVqivlMwQJk+enMV27NiRxajeyLiAhJkzZ87EsqkPEVQOCUXJZGDnzp14zZEjR2YxMkxZvHhxFpsyZUqlc0n8LLEolUwpzInHKaeckpl6kDlOCRoDJBx/9NFHsxiJcXft2pXFSoJ5ynvTpk3LYitWrMhiJEKmOaeUm0kkTsYF27dvz2JkokLGHyUzG1q/0PPQ3Fh1DiWBuMTzDs0llE/oeSjHUF6X+D7XrFlTqWzKoyXoeShnk1if+hCNp9IYGzp0aBajMUHl0PqB1gol0w8ajz165J9B0P2QcQZdj+YGifs/1RG1I62zqV8tXboUy6b8uG3bNjy2hD+pMcYYY4wxxtQav9QYY4wxxhhjao1faowxxhhjjDG1xi81xhhjjDHGmFrTpUYBe/bs0ZYtWw6IkbixJJgnwdHcuXOzGAnoSNRPQqeSKOnSSy/NYiQIJwE07TBPOxFTrFR2VbEdCbxIoFgSy5GYjITaJEQj4SAJwUo725JAsqqomoSD1LYlUwoSSJKInvoaiTDJEKAUp111yQCA6od2zS7trExtTu1d1QSCRLN/93d/h2X/7u/+bha77bbbstgNN9yQxagd6VnWrl2LZV988cVZjMYy9VUad1Rn73jHO7DsL37xi1mMBKnmxGPfvn3ZWKMxftZZZ+H5NBfR7uA0didNmpTFaL6juUmSLrzwwixGpgAkdqZyyNyklKNoPLe1tVUqm8ohIXqpbJqXaU4ngxzKw2TMUzJ6ITMcMk2gfkFzNc2rdJzEz0hCeOov1A50bmeuSWJ9EuFTO9B4KF2T1mi01qB1BbXN7bffjmW/+c1vzmKPPPJIFjvvvPOyGNUZ9d/169dj2ddff30Wo3mErtm6vpe4vV/72tdi2f/6r/+axSg/0v38srzib4wxxhhjjDGmBvilxhhjjDHGGFNr/FJjjDHGGGOMqTV+qTHGGGOMMcbUmi41CujZs2cmfKQdx0u7jZIgl4Rfl112WRZ76KGHshgJAt/2trdh2QsWLMhiJNQjYR0JrUkAWjJIoN3oSWRIgrdx48ZlMXruEiQIJOEhieVIiDZ69OgsVhL/r1u3LouRCL+q+I/KKe0UTTv10nOTaQKJPUksJ/EOvH369MFjq1yTnpEMNqSyQLIV2omb+h/tpF3q0zSerrrqqkpl027hixYtymKlHchp93Pql3fddVcWu/baa7PYv//7v2ex0nNPnTo1i5Xax5xY9OjRIxOFU1/fsGEDnl8S8bdy5ZVXZrFly5ZlMRLBz549G69J448MSihWNR+VDDXIEITmYJobqX6ritulstFMlWtSjhkyZEgWI4G5xP2AchStNajOaU4vzU0kRqe6oLUP9YFSHqY5nPIMifrpfui+OzP/kvkAXZP6Hxl8lMyhyGSD1spUv7SmINOm/v37Y9lkSHD++ednsfvvvz+LjR8/Pos9+uijWaxkfjFs2LAsRuu7g+FPaowxxhhjjDG1xi81xhhjjDHGmFrjlxpjjDHGGGNMran0UhMRvSPiexGxNCKWRMSlEdE3Iu6KiBXNn9WEAMYYY8xxgvOjMcZ0D6oaBfy1pB+nlH49Ik6RdIakj0u6O6V0S0TcLOlmSR892EV69eqVifjvueee7DgSC7Wf38qsWbOy2I9//OMsRoIs2tWUBJMSi5VIRE/CLRJcVt31VZJ27txZ6XwS69MuwURJsEbCOBL6kZiRziWxXEmESfc+fPjwSuf37ds3i5EgkMSaEgsPyQSCBG8jRozIYtQHSuWQgJ/qnPoaQWYGktSvX78sRmLaQYMGZTEScJIYlowqJG4f2gWc6pzuZ/LkyVmM6kxiAwsSqpKI+I477shiF1xwQRabM2cOlk3zSKn/m9pw1PLjRRdddECM+hHlQYn7UVXTHJqrL7zwwiy2atUqLJvmN5rHKEbCb5qHSsYflIdJJE75seocWoJE+FQ2zfME1UVJyE7rAsqvZABAJkdUP7TOkLh9qBzqV5TDS/mR2LFjRxajOiIzBBo7dD2J+xtdk8wdqL0pH1FdSNyvNm3alMVoPNGahO6xBPWrxYsXZ7FRo0ZlsSeffDKL0XqIjpO4/1c142jnkNk0Is6WdJWkr0hSSumVlNJuSTdKurV52K2S3tKpko0xxpga4/xojDHdhyp/Ihwjabukr0XEvIj4+4joJWlgSmmzJDV/soepMcYYc3zi/GiMMd2EKi81J0k6X9IXUkrnSXpejY/SKxER74+IxyPi8dJHmcYYY0wNOWr5sbRflzHGmGpUeanZIGlDSql9R57vqTGJb42IwZLU/InijZTSl1NKs1NKs+n7nsYYY0xNOWr58eyzz+6SGzbGmOOVQxoFpJS2RMT6iJiYUlom6TWSFjf/3STplubP2w51rRdffDETCJG4uCTemz59ehZ78MEHsxgJoEmEP2/evErHSSxGpHsnsR0Jt1oFoRLvsl4qh4T9VUWGAwcOzGKl3eWrCutIXEZJmsRuEyZMwLInTpyYxWiHeYqROI3+EloSvtK90265JAg87bTTsljJkIB2gCZxPPW/lStXZjESgFbdsVtiQSEJ80mUTPdYMv2gY2nsUf977LHHstikSZOy2MiRI7FsKofuh/oqjR2ar6ZOnYpl087rNF+ZenA08+OePXsyUw+av0sGGGTKQYJc2kmcypk7d27lsmm+JPMNEo5TLiMDIBo7Et87zcs07mmurWoyI3HOpVxaVUS/bt26LFaaH2gu2rJlSxaj3e2pD1BdkHmLxM9NwnHKhRSj+Vcq97dW6BnJaIjyCeVgieuDzAMoRn2a1gADBvC3UulbTXRNqssVK1ZkMcqFtEaSWJhP7bB58+YsVnXsUP+TpLVr12axzubHqu5nvy/pG01nl9WSfluNT3m+ExHvk7RO0m90qmRjjDGm/jg/GmNMN6DSS01Kab6k2fCr1xzVuzHGGGNqhPOjMcZ0D7xBgjHGGGOMMabW+KXGGGOMMcYYU2v8UmOMMcYYY4ypNVWNAl41hg8fnsXIZUqSfvGLX2Qxcp4gJxZydCAXpT59+mDZvXv3zmLkjkGOL9dcc00Wu+uuu7IYuVtI1V3WTj311CxGzhHkXHXmmWdi2Xv27Mli5FxBz031Q05wJcgRhdxLBg8enMU2btyYxcitg1x2JK4jql9yfSMnFnK/kdjlhK5JriB0j9RXSpDF+pgxY7IYuaSQwwo5sZALkcTjltzpyDmFyqH2Lu37cfnll2cxciyi/ksuMOR+NmPGDCyb+i/NLebEIyKyHEBjr2T9vGzZsix2zjnnZDFySKR8snDhwspl01xC44fmA8qPlJtLUG6nOZhcrigf0bxKTmUSzwd0TcqvNI/RGqDkTEpuWtS2tAagHEPtVZrHqB2pD9C905qitIchtSNdk3J7aU3TSmndRX2d3DzJMZQcWal+Ss5rlB+pr1F7U45pdVWUuB0kXhORSyy5qpb6aislV1Ry7+us1b0/qTHGGGOMMcbUGr/UGGOMMcYYY2qNX2qMMcYYY4wxtcYvNcYYY4wxxpha06VGAXv37tWOHTsOiP3ar/1adtx3v/tdPJ8EeCRwJPOBBQsWZDES/5FQSWLBGgl8SWj9jW98I4vRfZcg8wIS6pFojJ6RRHkk9C+dT+WQWJMEl9SGJaEeieMJEomvXr06i732ta/NYiREl6rXG4k9SZRXMgpYv359pVjfvn2zGPUBqvNx48Zh2dOnT89iJGak+qW+3xmR68qVK7MYCSGpHUgASu1I/VSS7rjjjixWEi62MmDAgCxGz7h06VI8n4TbpbFnTiz27NmTjbWLL744O+62227D82nskmh45MiRWWzOnDlZjITjpfFMgmcafySq/pd/+ZcsVjW/STzv0FxCczXdN+X6Uo6iOqe5iPJ9VaOA0vxAcSqbcg+tcy688MIsVjJbofskkxoSeW/bti2LldZDdO9kkHD66adnMcodFCNRvsTjhPogCeYpP1IOp7qQOOeSsJ/GCdUF1S8dJ7FJB80jNMZorUpzBj2fxKZPPXv2xGNL+JMaY4wxxhhjTK3xS40xxhhjjDGm1vilxhhjjDHGGFNr/FJjjDHGGGOMqTVR2tH0VSksYrukdvX3uZJ2HOTwOnE8PYvk5+nOHE/PIvl5SoxMKfU/CtcxNeE4zo/S8fU8x9OzSH6e7s7x9Dyven7s0peaAwqOeDylNPuYFH6UOZ6eRfLzdGeOp2eR/DzGEMdbPzqenud4ehbJz9PdOZ6epyuexV8/M8YYY4wxxtQav9QYY4wxxhhjas2xfKn58jEs+2hzPD2L5OfpzhxPzyL5eYwhjrd+dDw9z/H0LJKfp7tzPD3Pq/4sx0xTY4wxxhhjjDFHA3/9zBhjjDHGGFNruvylJiJuiIhlEbEyIm7u6vKPlIj4akRsi4iFHWJ9I+KuiFjR/NnnWN5jVSJieET8LCKWRMSiiPhgM17X5zktIh6NiAXN5/lkM17L55GkiOgZEfMi4t+a/1/nZ2mLiCcjYn5EPN6M1fl5ekfE9yJiaXMMXVrn5zHdA+fI7oNzZPfHObL7cixyZJe+1ERET0l/K+n1kqZI+s2ImNKV93AU+LqkG1piN0u6O6U0XtLdzf+vA3slfTilNFnSJZL+a7M96vo8L0u6NqU0U9IsSTdExCWq7/NI0gclLenw/3V+Fkn6lZTSrA62jnV+nr+W9OOU0iRJM9Vopzo/jznGOEd2O5wjuz/Okd2Xrs+RKaUu+yfpUkl3dvj/j0n6WFfew1F6jlGSFnb4/2WSBjf/e7CkZcf6Hg/zuW6TdN3x8DySzpA0V9LFdX0eScOag/5aSf/WjNXyWZr32ybp3JZYLZ9H0tmS1qipS6z78/hf9/jnHNm9/zlHdq9/zpHd99+xypFd/fWzoZLWd/j/Dc1Y3RmYUtosSc2fA47x/XSaiBgl6TxJj6jGz9P8KHq+pG2S7kop1fl5PivpjyXt7xCr67NIUpL0k4iYExHvb8bq+jxjJG2X9LXmVx/+PiJ6qb7PY7oHzpHdFOfIbsln5RzZXTkmObKrX2oCYrZfO8ZExJmSvi/pQymlZ471/RwJKaV9KaVZavwF56KImHaMb+mwiIg3StqWUppzrO/lKHJ5Sul8Nb5a818j4qpjfUNHwEmSzpf0hZTSeZKeV72+FmC6J86R3RDnyO6Hc2S355jkyK5+qdkgaXiH/x8maVMX38OrwdaIGCxJzZ/bjvH9VCYiTlZjsv5GSukHzXBtn6edlNJuSfeq8d3uOj7P5ZLeHBFtkr4l6dqI+CfV81kkSSmlTc2f2yT9UNJFqu/zbJC0oflXTkn6nhoTeF2fx3QPnCO7Gc6R3RbnyO7NMcmRXf1S85ik8RExOiJOkfROSbd38T28Gtwu6abmf9+kxvduuz0REZK+ImlJSumvOvyqrs/TPyJ6N//7dEmvlbRUNXyelNLHUkrDUkqj1Bgn96SU/pNq+CySFBG9IuKs9v+W9DpJC1XT50kpbZG0PiImNkOvkbRYNX0e021wjuxGOEd2X5wjuzfHKkd2+eabEfEGNb4H2VPSV1NKn+rSGzhCIuKfJV0j6VxJWyX9T0n/Iuk7kkZIWifpN1JKu47RLVYmIq6QdL+kJ/Uf30n9uBrfGa7j88yQdKsafauHpO+klP40Ivqphs/TTkRcI+kjKaU31vVZImKMGn95khofS38zpfSpuj6PJEXELEl/L+kUSasl/baa/U41fB7TPXCO7D44R9YD58juybHIkV3+UmOMMcYYY4wxR5Mu33zTGGOMMcYYY44mfqkxxhhjjDHG1Bq/1BhjjDHGGGNqjV9qjDHGGGOMMbXGLzXGGGOMMcaYWuOXGmOMMcYYY0yt8UuNMcYYY4wxptb4pcYYY4wxxhhTa/xSY4wxxhhjjKk1fqkxxhhjjDHG1Bq/1BhjjDHGGGNqjV9qjDHGGGOMMbXGLzXGGGOMMcaYWuOXGmOMMcYYY0yt8UuNMcYYY4wxptb4pcYYY4wxxhhTa/xSY4wxxhhjjKk1fqkxxhhjjDHG1Bq/1BhjjDHGGGNqjV9qjDHGGGOMMbXGLzXGGGOMMcaYWuOXGmOMMcYYY0yt8UuNMcYYY4wxptb4pcYYY4wxxhhTa/xSY4wxxhhjjKk1fqkxxhhjjDHG1Bq/1BhjjDHGGGNqjV9qjDHGGGOMMbXGLzXGGGOMMcaYWuOXGlNrIuITEZEi4pojvM41zet84qjcWOfK/nqz7FFdXbYxxhhjqhMRbRHRdqzvw+T4pcYYY4wxJzTNPyx1/LcvInZFxL0R8d6IiGN9j8eK5vOniHjvsb4Xorvfn+k6TjrWN2DMEfJ5Sd+StO4Ir/OopMmSdhzxHRljjKkrn2z+PFnSOElvlXS1pNmSPnCsbsoYc2j8UmNqTUpph47Ci0hK6QVJS4/8jowxxtSVlNInOv5/RFwu6eeSfi8iPpNSWnNMbswYc0j89TNzTIiIt0fEzyPi6Yh4MSKejIiPRcSpLce1Nf+dHRF/1fzvPe3al4NpaiLi3RExt3n9bRHxjxExpPl1gtRyLGpq2o+NiJMi4uMRsSIiXo6I9RHx6Yg4Bcp9S0T8U0Qsj4jnI+K5iJgTEX8QER5zxhhTE1JKD6rxB6+QdEHr7yPi4oj4XkRsiYhXmrnhSxExhK4XEX0j4lMRsTAiXmjmwAURcUtE9Go5dnxE/ENEbGxee1Pz/8fDdX+ZCyPi1yPi0eb1d0XEtyJiKJwzJiK+HBErm3lyVzMXfzEi+jWPuVfS15qnfK3lK3qjoOx3RcQjzbzX1vz9QTWrB9OoRMQ7IuLu5r291Dz2nyNidtX7ax53UkT8XkT8IiKeadbNvIj4AOXlaPCBiFjULHdjRHw+Is6h+zTdA39SY7qciPhzSR9T4xOWb0p6TtLrJf25pOsj4rqU0p4Op5wi6R5JfSX9RNIzkg7617KI+CNJ/0fSU5JulfS0pOskPdj8787yTUlXSrqjWf4bJP2xpAGSfrvl2Fsk7Zf0iKSNks6RdK2kv5Z0oaT3HEb5xhhjjg3tepo9BwQjflvS30l6WdLtktZLGi/pP0t6U0RcklJa1+H40ZJ+JmmkpDmSvqDGH5cnSPpDSV+U9Hzz2Asl/VTSWc1rL5Y0SdK7Jd0YEa9JKT0O9/p7kt7cPOc+SRdLeoekmRExK6X0cvP6gyU9JulsST+S9H1Jp0karUaO+ryknZK+Lmm3pBsl3SZpfoeydreU/WE18uy/Np/zsF8AIiLUeFm5SY21wg8kbZc0TNKvSFom6fEq9xcRJzfv6frmed+U9FLzOp9To45a8/JnJf2BpM2SvqxG29/YPPYUSa8c7rOZV5GUkv/5X5f9k3SppKSGBmZQh/hJakw6SdLHO8TbmrGfSuoF1/tE8/fXdIiNUWMC2i5peId4SPrn5vGp5TrXNOOfaInf24zPkdS3Q7yXpJWS9nV8jubvxsJ99lDj5SpJurjld19vxkcd6/bxP//zP/87Ef9RXmjGr2rO8y9LGtwhPkGNhe1KSUNbzrm2ec4PW+IPNsv5GJRzrqTTmv8dkpY0j313y3HvaMaXSurRId6eC5+RNL3lnG82f/f2DrHfb8Y+CPfSS9LpHf7/vc1j31uou/ayn5d0Hvwe82uH37dJamuJvb95zqOSzmn5Xc+Wtqh6f5+T1LPlOl9p/u7GDvHLmrGVLXn/NEkPN3/XRmX537H956/CmK7md5o//1dKaUt7MKW0V42/8uxX469crXw4pfR8xTLepcZL0udSSus7lJEk3axGsuksH00p7epwreclfUONl5XZHQ9MKa1qPTmltF+NT2qkxl+LjDHGdDOaX6X6RPMrYt9W4w9qIekjKaXNHQ79f9QwE/hgSmljx2uklO5R45OSN0XEWc3rXqDGYnm+pE+3lptS2pFSeqn5v5ep8anMwymlb7Qc921JD0iaKOkKeIS/SSk92RL7u+bPi+D4F+Fenk8pZfEKfDmlNO8wziN+v/nzd1NKB3y7IqW0r6UtijS/WvYBSVsk/WFK6Zf5v/nfH1bz5bHDae3fvvhUS95/SY1vmZhuir9+Zrqa85s/72n9RUppeURskDQ6InqnlHY3f/WSpCc6UcZ5zZ8PQBlrI2K9pFGduJ7U+Ji7lfYXpj4dg83vIv+RGl9RG6PGX706kn232RhjTLfgf7b8f5L0vpTS11rilzZ/Xt38qlgrA9T4JGCCGp/0X9KM39n8I9fBKObJDvEr1Mh1P2/5XdVcdbsaX/n+24i4XtKdanyStLj5B8DD4dHDPO8AmtqiaZK2HoWXpAmS+klaIelPgp25X1TD/bSd9vq/D469X9LeI7wn8yrhlxrT1bR/x7b0V5bNkkY0j9vdjG3r5CTbXsbWwu+3qpMvNR1esDrSPrH1bA9ERG81vqc8Wo0J/h8k7Woe21vSByUdYIZgjDGme5BSCumXC+tL1fh60hcjYm3zE5h2+jV//tEhLnlm82fv5s+NheM6UiVPdrxmR3ZDLMtVzT/wXaTGV7NukPRrzV+tj4i/TCn9TYX7bGXLoQ+pRO/mzyp1dSja22m88hfWjpzZ4b+La4iU0r6I2HkU7su8CvjrZ6araf8YeVDh94NbjpMafynrDM80fw4s/L4UPxr8ZzVeaD6ZUro4pfR7KaU/SQ2b0G+/iuUaY4w5SjS/gvVTSW9S42Xg1og4o8Mh7TnqnJRSHORf+1/7dzd/Vvmk/nDyZKdJKS1JKb1DjYX/bDW+nt1D0l9HxPsO55KFePsnU6U/pLcaCuxu/jwa32por6MfHqKdRsM52VohInrqP16UTDfDLzWmq2n/KPma1l9ExDg1nE3WFD4Z6WwZ2feNI2KkpOFHcO1DMa758/vwu6tfxXKNMcYcZVJKT6ihSRmmhkNZO79o/ryy4qXaj7+eLIRbKObJlvjcimUflJTS3pTSnJTSpyX9ZjP8lg6HtOtQeurweKr5M8u9zbzfu+V+npe0UNLAiDiv9RzgYPe3VI2XpEuaLmhVaK9XytlXyt9y6rb4pcZ0NV9t/vyTiOjfHmz+9eMv1eiTXznCMr6pxsftvx8Rv5xEmxaR/1uHPzFXoa3585qOwebEbIGhMcbUj/+lhrbzIxHRrkv5vBoum/9fRExoPSEiTomIX77wpJTmSHpI0ixJH4Xj+0XEac3/fVAN6+ErIuLXW477dTUc2ZYLdKNViYiLIoK+tdAee6FDrP3rViMOs7ilanyD4saIGNDhHk6XVPqaW3v8S617w0REj6Yl9SHvr2lC9Dk1Pt36m2aZBxARgyNiSofQ15s//3tE9O1w3GlqrCFMN8Vvm6ZLSSk9FBH/R409XhZGxPfUsIF8vRrCwAck/cURlrEqIv5fNUSQC5oONu371PSVtEDSjCMp4yD8gxrfsf5sRPyKGuLE8ZLeqIbP/jtepXKNMca8CqSUNkbEl9TQRP6xGpbMSyPid9T4Q92iiPixGi8aJ6uxuL5SjW0FJnW41H9SY5uAP4+ItzX/O9TIEa9rHtuWUkoRcZOkuyR9OyJuU+PFYKIan6A8K+m3KhgOHIx3SfqvEXGfGtbFT0kaq8bX7V5WY5+Wdh5W4yXnQ81FfrvW5HOtzmRESmlPRPy1pP8haV5E/FCN9ed1kjY1/7Xy92p82+K3JK1o1sF2SUPUsMz+qhp6oCr392eSZkr6L2o40t2jhl5ngBp1f7mk/67GXkBKKT0YEZ9Tw4GtfZ3Svk/NUyprncyx5lh7SvvfiflP0jvVeIF5Vo2/gC1SY1I5reW4Nh3ED16wT02H371HjY/xX1JjMvwnNSbEhZJ2txx7jQ6yT02h7PcKvPElTVHDWWabGi9sc9TQ2oxqHv/1luO/Lu9T43/+53/+d8z+qbBPTYffD2zO589LGtghPr05h69V42VgVzPHfEnStXCdfmpYOi9r5qbdatg8f0rSGS3HTpT0j2osovc0f/6TpIlw3YPlwiz3qLGJ5BfU+CPfLjUcwFaqseHlNLjGDWq8PDzXXlftOetgZXc4P9TQ7KxSY3+fdWpskH3GwfK8GlbL96nxh8mX1Nh4+xuSzq96fx3Kf4+ku5vP+4oaLzYPSPq4Ouxp1+H4D6ixX9DLarx4/a0a+p/i/frfsf0XzcYz5oQgIs5W468481NKlx7qeGOMMcYY0/2xpsYcl0RE/1ZRYEScJOkzauwK/MNjcmPGGGOMMeao409qzHFJRPwXSX+qxm7Q69XQ0lylxkZc8yVdlg5vx2RjjDHGGNPNsFGAOV55RI3vyl6l//CUX6PG95Y/7RcaY4wxxpjjB39SY4wxxhhjjKk1R6SpiYgbImJZRKyMiJuP1k0ZY4wxdcc50hhjuo7D/qSmuVnicjV8xjdIekzSb6aUFpfO6dmzZzr55AM3dG3sh3ggJ53E34rr0SN/B+vZs9o+inRNut6ePXvw/FdeeaXS+fv357bxrc9cOpfKkCRqI7pPKufss8/OYrt27apUhsTtQ/dO0HGduR4dS+zbty+LUTtQOaXnPpJPMOnczlyPjqW6qHpcqX7pfKo3Ou60007LYnv37q0UK3Hqqadmsapjh8Z3qf9U7ZdHUr8vvPBCFisdS3W+ffv2HSml/tkvTG3obI7s2bNnau3HlN9K45nmwapzHvVrKrs0jx3JfEsxKrs0l1Qth+6R5hzKrXRu6T6r5keqcyqnNI9R2RSrmh+Jqjm4dCyVTZSOo3asOn/TM1I5R/qMRNX+S/2vVA5ds2o+qhorlUNQ/VadB0rrbCqbrrl169ZifjwSTc1FklamlFZLUkR8S42NiYovNSeffLKGDx9+QOyUU07Jjuvfn3P5GWeckcXOPPPMLEaV2Ldv3yzWq1evLLZlyxYsu62trdL9vPTSS1ls0KBBWYwWhevXr8eyaSBu3bo1iw0cmG8OfN1112Wxb33rW1mslDBoUUn3TlD9UntT7GDxVp555pks9vzzz2ex00/PNhIuDi6KV134Ul12ZtJ++eWXs1jVlwiaFErtRedT2dSnp0yZksWoT+7evRvLpvoYP358FqOxQ4mA5oxS/6FxeyRJiPrVvHnzsGw6lur385///Fq8gKkTncqRJ510kgYPHnxArE+fPtlxpfH83HPPZTHqrzT2aKzQ/F2ax2i+pfPpD3c0zui5t23bhmVXnddpnI0bNy6LUR4u/cGR1h9nnXVWFqN5nnIr1WNp4Ut/sKT7oX5B5dDisdTXqr6IPv30IffllMQ5XOL+RvVB9/nii7lsdufOnVmM2kHi5ykd2wq1w1NPPZXFRo8ejefTH+movel+aNxRzqNxI0m9e/fOYrSmpn5FY4zKLq2z6d7pmn/5l39ZzI9H8vWzoWq4SrWzoRk7gIh4f0Q8HhGPV31rN8YYY2rOIXOk86Mxxhw9juSlhj6Hy17fU0pfTinNTinNrvqxljHGGFNzDpkjnR+NMebocSQvNRskdfwu2TBJm47sdowxxpjjAudIY4zpQo5EU/OYpPERMVrSRknvlPSug50QEdl3H+m7g6XvYdJ366oKsOk7myVDAoL0KqSxGDt2bBZbtWpVFqP7Jk1CqWz67iHpF376059msbe97W1Z7J577sGyqY769euXxdauzb/iSO1If40sfbeTvhPbGVFfK88++2wWKwm6q353tqqgr/RXWPrKyTnnnJPF6Pu09F106lf0HW9JWr16dRaj78mSroXae9OmfL1W+j44adzoe9FUb/R9e5obSt8Hp+82Dxs2LItR36fvB9P3jS+44AIse+7cuVlsx44deKypPZ3KkT169MjmQhrjJZ0ajRUaf6QPKZhV4D0SpMmh+6F5jJ6H5uqS7pPGPh1LczXNYxMnTsxilMMl1h9UFcyXck/V42h+onak+qF5nnQgpb5WVS9V1biglNerzsEUI1o1a1K5X9H6g6A8Q/qvc889t3LZFKexQ/2P+kBntFoEtTet20iTS/dDa1qJ+1tpfVjisF9qUkp7I+IDku6U1FPSV1NKiw73esYYY8zxgnOkMcZ0LUfySY1SSj+S9KOjdC/GGGPMcYNzpDHGdB1HtPmmMcYYY4wxxhxr/FJjjDHGGGOMqTVH9PWzzhIRmdCQRGwlSNxGgm6KVd0AsyTcIuEiiZ1ok84rr7wyi91///1ZrCTo3rx5cxYjAR0JjklcRvc4ffp0LJuEzSSuJCHZhg0bshgJAkuGDXTvK1asyGJkXFBVXFYSGFbd/IrqnPpVyfyiqo0r1Tn1F9pcjNqmdOxFF12Uxeh5Fi3KpQFUP6Xnq7ppbtUNcqkdS/2qqtFAaWPWVqpuQibxBqOdMSwxxy8RkQnuSYBfMsehOYbGOAm1aQ7tzOabNBeRiJnE12Sus3hxvj9paS6hnE1zFomQad6gOX3kyJFYNuUjMkGp2o5kCkDzlcT3TkJtmldp/qV5qJQ76Hlo3UXrJjpu165dWA6tF6iOqJyqgvmSSQE9I22WSfdD8z8ZAJXWm1Q2tSOVQ4YNdD2qH4nz3rp167IYtSOtAWjMl8byqFGjslhpY9YS/qTGGGOMMcYYU2v8UmOMMcYYY4ypNX6pMcYYY4wxxtQav9QYY4wxxhhjao1faowxxhhjjDG1psvdz1odNsj9oeQIQQ5m5CZEThjketEZJwxykaFjyfHl3nvvzWIjRozIYiUHELrPGTNmZDFybVm5cmUWIxcYqkdJmjlzZhZ76KGHstjGjRuzGDnqnHvuuVls+/btWPawYcOy2PXXX5/FyGXt1FNPrXRcCXKCIVcR6qvkLFPq0+QgQm4qY8aMyWLkukWxUtnkdEaOKE888UQWI3chcikpueeQaws5p1R1PiHHltJ4onFS1YWR+hW5INKYlbhtybHInHicfPLJGjp06AExGo+l/lJ13qHzKUZjquTQSdB8WdV5cPjw4VmMXA8ladu2bVmM5h1yC6Oyqzp2SZwfn3zySTy2lcGDB2cxaq+tW7fi+eQgRX2A5iJaA1R1DJW43ihnkvMVnVty1aN2pGtWbdvOOJBVdbGj9Qu5pJGLLeU8qbrzIOUT6hcUo3qUpDVr1mQxGst0jzQ/0JqvtM6mcijnHgx/UmOMMcYYY4ypNX6pMcYYY4wxxtQav9QYY4wxxhhjao1faowxxhhjjDG1pkuNAlJKmSiLRLYlSOy0evXqLEaiahIrkQiTYhILHMk8gGIkwiRxGd23JD311FNZjER948aNy2Ik9qT7IbFlCTJDoPNJTJ5SqnScxAK+9evXZzESyy1ZsiSLkSivRw9+rydhKLUD9RcSto0aNQrLWbVqVRYbOXJkFiPxHkGi0FbxcTvr1q3LYnSfJJik9qa6pDFbuicSmlJfJbEmiSjpOInnAjK1IKhPkiFByXiA4iTaNUbivNMZnn766SxGfZjGHs1tJTE5jT8a+1X7Ogm6yTxA4ueh+yRxMs1tlKMox0gstqY8Q+Oe1gB0XCk/EiS0pj5ABiw0f5dE2mSmUFo7tdKZ56H5n+ZqOo76NPUBMleQuD7ofLof6kPUJ0v1S2VT29Iz0vqMxmdnzBnIiIHGN903mReVDIRoLJfWECX8SY0xxhhjjDGm1vilxhhjjDHGGFNr/FJjjDHGGGOMqTV+qTHGGGOMMcbUmi41Cti/f38muCNxGYmfpOo7k5KomoTjJNwigaLEQsGqYi4SSpFArCQamzRpUhZbunRpFps8eXIWI3E7CeNKojGCBJskAKV2pN3cSyJ4EqOPHTs2i1H9VhWclXa23bhxYxYbNGhQFiNhPsXa2tqwHLpPEvpRX6MdqakPUR+QWNBK42TIkCFZjOqCxJFUFxI/I/WN0o7LrZDgl8SwEpt5UD8gkTbVJT13qV/RsSWzCnNisX///kyAXdU8Q+I+V3UXcuqDZJZC47Z0TbpPMq4hcTzFaM6RePd2GuN0PtUPCetL0PxGczDNbbT+oHxQmseojsiAhfJ9yfigFWqv0j0NGDAgi9G6oDOCeSqfnofMB2h3ezI4KD0jGQBs3rw5i5GxT9VcRmNMYpMbOpbWYmReQeObjivFae1EuYzW89Q2mzZtwrKpH9Ca+mA4mxpjjDHGGGNqjV9qjDHGGGOMMbXGLzXGGGOMMcaYWuOXGmOMMcYYY0yt6VKjgIjIREOd2UGUduAl8R8JfElUR2IuEoKVINEZCbyqij1LomjafZXOp+emZyTBWWlHdTIkIFE2icGoHbds2ZLFSjsRk6CQRGMkghsxYkQWqypIlVj0SOI2esYZM2ZksZL4dPny5VmM7p36BolcSWg3ffp0LJv6wcqVKytds6oY9uKLL8ayadxTPyBBKo2H9evXZzESMkrVdz2m+YaMAmg8lMwZqP+W7tOcWKSUsnFB+ai0Izv1YTK+GTZsWBajuYBE8KX5kuZqEmBTfqTx2Jld52n8Uc6lsslQgOqiNH/T/ET3Ts9Y1cShM0L2rVu3ZjFaF5DpEgnES+1N666qInHqK50RrVOdU3vTHEx5i4wHJO4vZD5AZgh0LtVFyXiDju2MaUgrVI+lHEXtQ3VO7V21vUrQmCAjkIPhT2qMMcYYY4wxtcYvNcYYY4wxxpha45caY4wxxhhjTK3xS40xxhhjjDGm1nS5UUDJBKD1OIIEcyRMIvEUCd5IeFXa4ZVMASZOnJjFSExO1yShXWmXVdqxdtSoUVmMRIb0jFROqc6r7t5Lwri1a9dmMRKulvrEtm3bshiJHklY/7Of/SyLXXHFFZXuUWLROwnuSWxHfY3E7RI/+y9+8YssRv1l6tSpWYzGAwl+peoCdTIpoGuSoI/6XylOgl/q0yQmpD65Zs0aLJv6ILXPqlWrKp27ceNGLIeg+yyJcY0hSsJx6sPU3yg/0ngmIXpJwE9GHTRn0fx0xhlnZDF6xtI8Rrmn6m7wJHam8Vja8b6qSJzmOzINoePIVEVik4Px48dnMRKj79q1K4uRCJ7MJySelwcOHJjFqE+SaQKtrySuSzJDoHUKPTf1IbofiXM75R7q51SXRGk80ZqR1grUX6jO6XrUByReF1A51A4E1W9pnU3tXRr3xfI6dbQxxhhjjDHGdDP8UmOMMcYYY4ypNX6pMcYYY4wxxtQav9QYY4wxxhhjak2XGwW0CoRo99KSMI4EfLRDPYmNqgreS6Kx4cOHZzESWl122WVZjMSEJH4i0aIkLVq0KIuRsJ92QH/Tm96UxUjUWdoxmQRigwcPzmJtbW1ZjNqWyiGhqCQNGTKk0rEk6idDAbrvFStWYNkkwifRJJU9a9asLFYSk1M7koC0qpi8JMAjqL9Q/6d7J/MA6isrV67Esvv375/FSFxJfYCEzjTGaMxKXEckVKV7JHEuiUfpXIl38i6JkM2JRY8ePbIxQIL5Un4kSjmlFRrPdG4pT5Aom8YkGdxUNQUo7UxO90QmM1RvAwYMqHS90s7ttNYgoTbN35RPaP6ltpF43qhqfFDVsIFyuMTzG7Ujrc+q5nWJxfHUN8i4gPIJXa9kVETtQ/VB60i6JvWVUl6n82mMUe6h+qFnoTWxxH2Qzqc1FvUrWuPQfZfuqWSMUsKf1BhjjDHGGGNqjV9qjDHGGGOMMbXGLzXGGGOMMcaYWuOXGmOMMcYYY0yt8UuNMcYYY4wxptZ0qftZSilzMiCHCnJ/ktgpgmLkHEHOJ1UdKiR2SSHWrVuXxciRhBzISu4u5B5BjhvTp0/PYnfccUelc0suHOS8Qk4j5Ao1cODALEaOLcuXL8eyyYWDHDcmTZpU6R7Xrl2bxUouHNQ+gwYNymLk1kEOIBdddBGWM2fOnCxG/X/atGmVrvn4449nMWpvid3g6LnJdaVfv35ZbP78+VmsVL9r1qzJYiNHjsxikydPzmLkTkR9reRqQ65M5NxG/YVckKifnnPOOVg29ZeSu5E5sUgp4dxRFcqlNK9TPqo6JkpOfTQGKLZ69epKxxGluqExmVLKYjQP0nzXt2/fLEaOUhLnGapfmgdpTUHrlNJ6iNYF9NxDhw7NYp1ZAxBPPfVUFqM8QW6P1K9K6ytymK3qNkn3Q7mj9NyUH6ltqRx6RnJKLfVpanPqg/TcdI+0ri3lZoL6Cz0PXZPGJ9WZ1Dl3uhL+pMYYY4wxxhhTa/xSY4wxxhhjjKk1fqkxxhhjjDHG1JpDvtRExFcjYltELOwQ6xsRd0XEiubPXOhgjDHGHOc4RxpjTPegilHA1yV9XtI/dIjdLOnulNItEXFz8/8/eqgL9ejRIxPKkjiexFzt57dCgiwSK5188slZjERWJVHeypUrs9jWrVuzGAm/SERPQmK6H4nNB0hoRfc4duzYSuXMmzcPy6b2IeHhGWeckcU2btxY6VwStkksfCVxPPUXEl/36tUri5XEciRwbGtry2Ljx4/PYjNmzMhimzdvxnLoGalvUN8n4eCQIUOyGAn1JK53Gk/bt2/PYnTfJLClcSfxM5L4lAwFSPRIAnzqkxILQKlsMoagOqP+t2XLFiy7qsmBqRVf11HIkSmlTOhNImbqq5I0YsSILEbCcxK3EzQXlETVNI9SOTSPbdu2LYudfvrpWawkLq5qAlRVrE8C/FKd0XxAcx7lE5q/yQintCaheX306NFZjOZqMnygeb5kXkRzKz0P5VyaV6nOS+VT2dRX6TjKEyUTCMpnlLdoHUjlUF2UjKmor5KZR9UcXiqnKtQ+tNatKvQv9Wnqg6X1YYlDflKTUvq5pFYLihsl3dr871slvaVTpRpjjDHHAc6RxhjTPThcTc3AlNJmSWr+LPodR8T7I+LxiHic/qJijDHGHGdUypHOj8YYc/R41Y0CUkpfTinNTinNpo/FjDHGmBMR50djjDl6HO5LzdaIGCxJzZ/5l2KNMcaYExPnSGOM6WIO909Dt0u6SdItzZ+3VT2x9SN2EmmVdhgmYRyJkEiURzESXpFQSWKROAkCSVBFgrOqgmNJmjVrVhYjET6JDOkeqR5LQjKqNxIekkCRxNLPPvtsFivtqE5iURLgDRs2LIuNGjUqiz3yyCNZjO5bYvH2ihUrshiZLlC/KtXvxRdfnMVIeEjCwT179mQx6n+lsun8a6+9NouRWHPt2rVZjHYdLplfUD8gIfCyZcsqXZN2nqZ+KrF5BolXadyS6Qe1Nx0nsaiZxq2pPYeVI1uNAii/lfo1QXMozRFV5xeKSWXzglbIaIDu57nnnstipU+y+vXrl8Uox9EzkmCZ6rwkZKc8QfmMYuvXr89ire0vlc1WSAhPczDlOFprUP10Ztd5moPp3ql+S89IOYH6BrUPnduZtqV7ovoYOXJkFqN1bVWhv8T3WdVch+YHahsyi5C4D1Leqlo/9NyU/yVe35UMQkpUsXT+Z0kPS5oYERsi4n1qTNTXRcQKSdc1/98YY4w5oXCONMaY7sEhP6lJKf1m4VevOcr3YowxxtQK50hjjOkevOpGAcYYY4wxxhjzauKXGmOMMcYYY0yt6VIPyZRSJjgiQVRp917awZR2aSUxI4mVSCC2YcMGLHvo0KFZbPny5ZWOI+ODiRMnZrFVq1Zh2STcInEkmRyQuJLEo294wxuwbDIkIIEZ1QUJ+EnASW0j8b2TEI0E3SSOJ0Ef9T+JBXgk6B4zZkwWI6Hev/7rv2I5JBb91V/91UrHESRIJVG/JA0ePDiLUTvS85Cwnuqy1LYkGKbdvWksk1EAmStQP5ekJ554otI1qX7I/IJEmJ3ZpZrmNXPisX///qzf0NgjMbjE8yUJkWkOrSrMp3FbOpbyOPV/ym8kiqbcIbHomHIUzY1UNs05ZDwj8dglAT8JrSkfUT2WDISoHWnOIjMDMkig+bJk4rNp06YsRs9N6yGaa2leLUHmRdRmtDYkSs9IAvV169ZlMRpj1N60ZisJ5mk80v1Q/6XnofvpzHiie6cYmQpRrGRSQFBfPRj+pMYYY4wxxhhTa/xSY4wxxhhjjKk1fqkxxhhjjDHG1Bq/1BhjjDHGGGNqTZcaBRAkdivtLkuCexI7Vd01lnb9LgmY6FgSwlOMxIQkRKfnKx1LwmgSg5Ho66qrrspiJPqSpIcffjiLkYiTxFwkriQh+o033ohlL1q0COOtkHiV2pGOI6G/xGJyorTDditLly7FOIkeSRDYmd29W5kwYQLGqc3JGIJEizt27Mhi1C9KIsxx48ZVuiaJXGmckMCWzpX4eciIgYwLSLRLc0vJpICE3ySmNScePXv2zMYQ9a3SLu80H9D5lCcIEm/Tjt8Sz61kCkBmK3TfNJ5L6wKqD8qPZB5Dhic0/5Z2NSeTEJqfqJzRo0dnMcqjpXm+ajuSWQvlHVrjlMT21D50LLUZ9aGSoUxVkyQ6rqphA/ULifs0zd9kFEC5jPpQSQRPx1Y186BnpDVoab1JRiTUz0tzQSvUB0pmJ7RuoznjYPiTGmOMMcYYY0yt8UuNMcYYY4wxptb4pcYYY4wxxhhTa/xSY4wxxhhjjKk1XWoUkFLKRH0ksirtsE0CKDqfBF4kJuxM2SR4JiExCapIsEa7rJbEU2SGQEIyErGVxNKtlAwSqu4uS89DdU67KJfE+gQJX0lIWXUXWhIYSiyCo12UhwwZksWqtpckXXLJJVmM+tXatWuzGIkE58yZk8UmTZqEZY8fPz6LkYCUBL+tO59L0oIFC7IYmXZIPCZojJE4kuYBEuY/9NBDWDbtuk0i2WXLlmUx2g2bxkhph2zqv9u3b8djzYlHa06icVKC+haNHxorL7zwwiHvReJxInFOIOE45WaaI+i4klEAnU+mJVXF7fQsJXMGilM+IlE25RhaA1BuLUHtWNVgic7tTJ3T2omeh9qW+prEBgvUtlRH9NxkIFEyYiCBOo1HWjtRvVFOKIn1q45HWr/Q2odilLckXkfSsfTc1KfJiKHq+kwq11Hx+E4dbYwxxhhjjDHdDL/UGGOMMcYYY2qNX2qMMcYYY4wxtcYvNcYYY4wxxpha45caY4wxxhhjTK3pcvezVteDzrggEOReQs4RVSEHGYndQujeyQ1lx44dWYxcIug4SRo6dGgWIwen3bt3Z7Hrr78+i5ELR6nONmzYUOl+yNHkqaeeymIzZ87MYuQoJbFbDZVDDm/kxEIuYF/4whew7Le+9a1ZjNqHnFjIraPkQjd9+vQsRm5w8+fPz2LkREQOKStXrsSyr7322iw2ZcqULPajH/0oi5Uc1VopOayQkxz1A3JEI4dBcm0jpz2JXc3IZYfmFhrfdN/k+CJ1zvnHnFhEROaaRPNyaUxRTqH+So5odBzlwlK+JkdCypnU10uun62UXKqqOp1RbMSIEVns6aefzmLkGCfxM5JrFtU51SW5a9E8JHF9kMsm9Reqc1pT/OxnP8Oyq/Y1ahuqy5LLH83LNNdXdfwi105qG4ndQam9aZ1DeYvqrASt5SinUIzuh/o+uZpK1deHdE1yTqP+W3JFpb7a2fW8P6kxxhhjjDHG1Bq/1BhjjDHGGGNqjV9qjDHGGGOMMbXGLzXGGGOMMcaYWtOlRgH79+8/IhF/SimLlQRHrZx66qlZjERJrULNdkiAR+LIqseRCJME4hIL3khwTKK6OXPmZLGpU6dmMRLWSyxwnzdvXhaj+iWxHF2vJKCj5yFRH9UFidgWL16cxUp1Tm126aWXZjHqLyTgvOqqq7CcCRMmZDES1pFwkPo+CRlLAlsSTVI5559/fhajcUz3XepXdE8UI1MA6i/PPPNMFiuNZTJnoLogYwjqv2vWrMliJDaWWEjZGQGpOX5JKWVjgES/ZBAicR+uKqInkTfFSqJ1gs4nQTjdD+X6kokP5Uca+ySOp3xCz1gySKB8T+1D4naa70hET2VI/DyUEzZv3pzFKGfSnDVs2DAsm9qW1hVDhgzJYlSXJMqX+Nnpucmch/oatTfljtKxNFfTvdM16b5LeYLWUxQj4w3qQ/QspfxIxjfbt2/PYjQeq44xWqdI3I6dNRPzJzXGGGOMMcaYWuOXGmOMMcYYY0yt8UuNMcYYY4wxptb4pcYYY4wxxhhTa7rUKCClhALsVko7JlfdYZ7EZSQ4JjEi7QZcipN4iiDhIQmq6PlK59OO7CTMp12CV61aVek4Sdq6dWsWI9EjPQ8JzqgeS89Nojxqs379+mUxEpyReI/EjaVjafdeesaFCxdmMRJMSryrL4nwSdRHAlDq53SPEo8zekYSG991111ZbPXq1VmstFszGSSQiJ76BpVDO4PT3CBx36g6j9DYmTRpUhZ79NFHsWzqVyUzBXNisXfv3syog3JMSThLeYL6NYnJqQ/SXFva+Z3majIuoHJI2EyxkuEJlU0CbHpuypkkgi/NJTSHUo4jkTc9I+XR0s7vVdts+PDhWYzyOrUtzasSz8vU/+jeqWy6R4nzUWl92MqWLVuyGBlvUBkS9yvqLyR6J/OYzozlUn20Qu1NUM4rmWxRH6S8RX1g/fr1WYyehUx4Ste0UYAxxhhjjDHmhMIvNcYYY4wxxpha45caY4wxxhhjTK3xS40xxhhjjDGm1nSpUcD+/fsz8SCJkkhAJ7HgmURaJKAmQRUJgWlHdYnF0gQZIZDImwR4a9euxWuSgO/666/PYtu2bctiJNwaN25cFlu8eDGWTTvWkhCyqsCRxGkkYpN4x9qqO1IT1K9Ku7lTfyn1y1ZGjx6dxah+JBal0j3Rzs5tbW1ZjIwCSkLTgQMHZjES2K5YsSKLjRw5MouRgPOCCy7AskmwSc9I44lEhnTuhg0bsGwyYqB5hASKJHqksUPtKvFu42R0YU489u/fnwlySaBemi9JjE5zCQm1qa/TXFsy+qE5mIT9dBzN82QaUhLr0/k0t9FxNGfRXF0qm+qDjHRo7UJrCsox1K4S5yiK0fqDjqu6xpF4XUDPTfMy9YvSfFm1v1C9kZkStWNpDUD1TuOEyqE5nXJMyZiK1qFkxEAmB1QOGRXRelHiOqIxQe1Aa+p169ZVKkPiflDVDKEdf1JjjDHGGGOMqTV+qTHGGGOMMcbUGr/UGGOMMcYYY2qNX2qMMcYYY4wxtaZLjQIiIhOtkdCutIMo7VBMQjIS5ZEAiYROJUE3CaBIsEn3Q8YFtNstCcEkFpORyGvMmDFZjHaxJZH2rFmzsGy6z6o7IVM7kMCwJAQjsRzt6EvtUFVsXzKGIEMDEtsRJMwvmRmQiJPEf9Q3SPBL1yuJe0lwTwJHEt2SCH/69OlZjNpb4j5Nphb03LNnz85i9CzU/yQ2Q6D2ob5BdUEC21JfIdOFklDVnFjs27cvy3E0fmiMl46lXedpTJEomublkkkBxSkn0L0/99xzWYzm39I4qSqEr/qMNF+WcvOAAQOyGM3/NG8MGjSo0nGlOidBOM1FJMomIwYyhiiZFJDBAj031S/N/dQHJF6jUXvTcWQIU/W5JTY0oH5A/byqyUxpXUBrrFYTEYnXtbRGovotzSNV19nUN+i+6R5pjSNxv6I57GD4kxpjjDHGGGNMrfFLjTHGGGOMMabW+KXGGGOMMcYYU2sO+VITEcMj4mcRsSQiFkXEB5vxvhFxV0SsaP7kXYSMMcaY4xDnR2OM6T5UMQrYK+nDKaW5EXGWpDkRcZek90q6O6V0S0TcLOlmSR891MVaBV0kDCLxncSCoaFDh2YxEivRTt4kYisZBZAom8qhGImGSYRWEk9t3Lgxi5F4kEwBSMxFYjk6V5KuuOKKLEZ1MXXq1CxG4j167pJgjQRmJI6ka1I7kNlDaVddEmxSjCDhIQlfJX4eEuWROP4Xv/hFFqPnmTBhApZNdbRw4cIsRv2Sdo8mMWJJhElj74YbbshiZGpBdUn3uGvXLiybxg71DWobipF4lESdEgt5yUjE1Iajmh9bxf4kWqe+WjqW8hnNL3RuZ4x0CMozpXmwFRIrl6gqRCYhO5kP0LklIfuUKVOyGBkA0DqF6pKehWIStyMJ1GmupXYgk5iSSJvalvolmQLQ/VAOL0H3TiZJZDxDbVtab9K8TqYL1A6UJ6guS6ZYVPbo0aOzGOXHUl9tpWQgRHVEMWqzqmvq0nPTPZXMnEoc8pOalNLmlNLc5n8/K2mJpKGSbpR0a/OwWyW9pVMlG2OMMTXG+dEYY7oPndLURMQoSedJekTSwJTSZqkxsUvi111jjDHmOMf50Rhjji2V96mJiDMlfV/Sh1JKz9BH04Xz3i/p/VLZb90YY4ypK86Pxhhz7Kk0i0bEyWpM2N9IKf2gGd4aEYObvx8sCcUJKaUvp5Rmp5Rme9I2xhhzPHG08mPVFyFjjDFMFfezkPQVSUtSSn/V4Ve3S7qp+d83Sbrt6N+eMcYY0z1xfjTGmO5Dla+fXS7pPZKejIj5zdjHJd0i6TsR8T5J6yT9xqEulFLK3A3Gjh2bHVdyLSLnIHJRoBh9SkTlkEuaxM4p/fv3z2IbNmzIYi+88EIWI0eH0nOTexW5lS1atCiLkSvI9OnTs1jJMaOq41yra4/EznbUNuQeIrFzGznBnH322Xh+K9R/xo0bh8fSc1M55IZCfY2Ok8rONq3QX3EpNnz48CxGY0xi5xRyNSMnr8ceeyyLUT8vQc4pI0aMyGLUf6lfkMvajh07sGwae+S6QuObnFyoHUplk6tTyc3K1IKjlh8jIuvb5M5VchCj+Y2OpbmayqExSnN66Zo0H9BxlHPpOIpJPB/QnLV06dIsNmrUqCx2/vnnZ7HSp2jkUkXtQFBdlvIEQWsSyuN07+RSRc9CDpmlY6s6YlJ+LLlkVs1RdE1yC6M1VsnRj+6d1i9r1qzJYlu2bMli1H9Lrm/0PDRGqQ+Qmyw9Y8lhkMZOZ+ahVmh8luqcrklOewfjkC81KaUHJJU+F39Np0ozxhhjjhOcH40xpvtgkYsxxhhjjDGm1vilxhhjjDHGGFNr/FJjjDHGGGOMqTWV96k5GvTs2TMTmJEw7pRTTsHzSUy2bVvulEnCQxICd8ZCk4R1W7duzWIkvqJzBw0alMUGDx6MZZNwi56bROdPPvlkFlu5cmUWu+KKK7DsPn36ZDGqSxLQUTtQG3ZGCEZCMoqR0J/Ed6U+QM9Ioj7qqySMK4no6T4JEtZNmTIli5G4kUSdUnUx7e23357F6LmpbTtj407mAyRUpbro169f5XJIsEn9gMYOte21116bxUjMKnG9kfHGQw89hOeb45eePXtmZiQ0fmhuknisUF8nsTTNoZRPSsJmmv8Jygl0TRrjJdE6zaGbN2/OYvQ8CxYsyGI0B1555ZVYNpkC0BxM457uh+YhEn5LvK6g9qbjqubCl19+Gcum+Y3mRuoX1F4lwxzq6xQjIfuQIUOyWGfMbKgu586dm8XIKID6LxkilUySqH2efvrpLEbjieqX1paleYSMdAjqG7QGIPOikskA9QNqRxqj7fiTGmOMMcYYY0yt8UuNMcYYY4wxptb4pcYYY4wxxhhTa/xSY4wxxhhjjKk1XWoU0KNHj0wUTsL6I905mERaJJYmsVJJVD1w4MAsRjsCk5CsqilA6blJDEYCMxJSkphryZIlWawkGvuN38g3wq662zOJI+m4khiRRH0kJCORINUFie9KgrXSjrdVjqu6W7PERhnUr6icmTNnZrENGzZkMRLNStK///u/ZzES4FG9kYEECQIvuugiLJvaZ/78+Vns7rvvzmLjxo3LYmQUQP1cYsFlVeEstS0ZHLz2ta/FsufNm5fFSuJrc2LRo0ePbJxTfiyJqmlupfmF5hKKUU6g/i/xHEzQ3EbXPO+887JY79698ZqUH8nEh/IM1RntYv/4449j2TTvVK1Lml/INIfaUOJ+QPMqHUe5uTOmFNSOZApAeY+E6CWjib59+2YxWvNRHicTB3pGMnaQeK4mgyZai1E7kuB9xIgRWDZBeXzt2rVZjIwlqO+XTBOoPqjNaD1O/YL638iRI7HszrwPlPAnNcYYY4wxxpha45caY4wxxhhjTK3xS40xxhhjjDGm1vilxhhjjDHGGFNrutQoIKWUiWJJRFQSVS9btiyLkZBt2LBhWYxEYyTAKwm3SAhJIi0SrNEuqySy6t+/P5ZN4jQ6n0RwJWFnK9u3b8f4bbfdlsVuvPHGLEbPeCQ7HkssuCRRNYnLWnfmLpVTEkJSXVIfoueh+y6Je0kISUI9ElLSubRD9je/+U0sm0SldE0SQlI70Nh505vehGVTW9AYu//++7MYtcOv/uqvZrHx48dj2W1tbVmM6oLaYfny5Vls3bp1WYyEylL1Pm1OPPbt25cJcqvuBi9xPqJ+TeOHjqM5h8TOEuc92tmcxhSJqikXTpw4Ecum8Uxjqur8T7FSnf/0pz/NYpQfSZhPkNC6JJSuahRA7UhmKTQ3kehcqr6modxBdUGmCRKL4+l5qGzqf3TcI488gmWTYQTVGxlBkXnFpZdemsVKOYpy4apVq7IYmSZQH6K8Xlr7kCEH3Q+NZaqzLVu2VCpD4vaxUYAxxpj/n70/j9b0uus70e8uybJsSVWlmqtUqirNtjzb5QkbMBgbQxxMdyCEkLSh6eXbl5AmvULApnNvQ98m1/SQC4EsgsOkBBziZaDt0AHiCIzBowbLtmTNqpJqngcNtiSrnvvHeYuU3v3Z0n51SqfOU/X5rFXrVP3qeZ497/3s877f7xYRETmncFMjIiIiIiKjxk2NiIiIiIiMGjc1IiIiIiIyahbUKKCUUonESOxGp5cm/eJkEqeRmJzEU3RCcMICPDIaIEEhCfBIGHfZZZdh2l/+8pe77qcTYqkuSNTZEm7RMz/xiU9UsR/6oR+qYiQypHy3RPTU3i3h4jQkJqR0WiK03hOgqS57T4pO+sW09Mzdu3dXsRtvvLGKkXFGwn2j98RkKjfFWqYfvaLH3nQuvfTSKvayl70M016zZk0V27ZtWxUj0eLll19excic4aabbsK0X/e611WxVv+Xc4sTJ05UJ3+TqLp1+jqNCzJMoVivcQ3dm3AfpjmU5nRaW3vX0SQ5fPhwFaO5hNKm8tDzWmOUROL33XdfFaP1tVcwT2tE0m8MRNf1GgrQ3J+wIJzenSg/lE5rHaY6onak/ktifVrfWuYXVG/UXyjv9L5JsZZJEhkS9PZpMnGgdqTrWnF616V1lNqLDExaRjo0nmbFT2pERERERGTUuKkREREREZFR46ZGRERERERGjZsaEREREREZNQtqFJDUoioSOs0ijCPRGYm5ek+2JcFZwoLntWvXdj2TBF50OjKdjJywWJ+gepuPcDBhsSidWPvVr361im3durWKkdCfBK5J+5ThaajcVGeznGRMUN+gumyd1EtQ2clUgMrzqU99qopR328JAkmMSKJHElzSqeSUzhe+8AVMm8bE7bffXsVofiBDDRIYtsSIO3bsqGKUdzIs2bJlSxU7ePBgFWvNYdTfpsXhcm5CRjpES7ROcwnNt7SW0fxPeWnNbXQ/zUUkmKf5hUTVrfFMcyPdTyebUxlpLmjVOc2XZFpCYulXvepVVYzW61afoDLS2ty75tL6RgLxpH/do2f2GgglPI+SIQFdR/VDtEwK6J2R0qFyU71R29xxxx2YNqVD5gwHDhyoYtdff30Vo3agNTxJdu7cWcWojqgP0TpM97beaSmf9A7wTPhJjYiIiIiIjBo3NSIiIiIiMmrc1IiIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIyaBXU/K6VUjhLkMEGuKQm7LZCbCrk6kJsEOVSQI1TCbh/kUvXyl7+8it15551VjByYLr74Ykyb4uSkQQ4t5DzRqt9eyH2E3M9e97rXVTHK4yxuPuSyQ2UkVzx63oUXXohp97q70P0Ua7m7UJwccG699dYqtn79+ipGji+z1C85+u3evbuKUf+jfkX3Jsk999xTxQ4fPlzFqM7f+c53VrFHHnmkirVc9chN5YEHHqhiq1atqmI0t3zbt31bFfvTP/1TTPsv//IvqxjNGXLusWTJksr9h/o/rZmtOI0Bmtt6XSBbcwm5GdK8TG6ae/bsqWK0Prbcmmgdp/mf5kaqX3qnaEFuTfRMev8gVzOa+1sOZASl3esaS+8ZLWcwgspI9UPrY8sNi5z6yD2NnO0o79TPW+5aVJf0zF5nXRo7+/fvx7SpPFSXVOfkvkd9v+X0S+Wh8U3tQM+84oorqth9992HaVO56T37mfCTGhERERERGTVuakREREREZNS4qRERERERkVHjpkZEREREREbNghoFPPXUU5XgiIRBK1aswPs3bdrUFSPRGYmfSCxHAugkWbduXdczr7/++ipGZdy1a1cVIwF+wkI2EkaTsI3EXCQwJ1F0kjz++ONVjATdVB7Kd0ucRpDAkWL0TGqbWQT8JEqlZ1J+esW5rTi144033th1L/XTgwcPYtqUzy1btlQxam/qQyRoJRFwwkLg7du3VzEym6AyUj/9zGc+g2lTPumZGzdurGLUp6ks9Lwkeeihh6rY0aNH8Vo5txiGoRIik7i4NZfQnEUiWzJboXWCYi2jgBe/+MVVjOYXEn7T+KFYa+2gfNI47a1LMjwh8XXrmTRf0rsGrT1UPy0RPdUvrR1UF9ReJG5vpU157zXnoTK2+jTVL/WNffv2VTES0ROtuZrqg8pN7U3vsLRGtcYTvav0rjN0L40dqrOEy0jloWdSfyHzC5qDEn6vbfWNFn5SIyIiIiIio8ZNjYiIiIiIjBo3NSIiIiIiMmrc1IiIiIiIyKhZUKOAEydOVCJdEo21TrHtPRGehLckYqN0SByWsBD+la98ZRV74xvfWMVIZPX7v//7VYwEZwmf9EsCMRJpUdr0PBIYJizSIrEzCQ9JqEcizNbJ7ySsoxgJRUmIRmVsGQVQnuhaipGhQKtPk9iOxIN33nlnFaP2/qEf+qEq1qrfa6+9top97nOfq2JvetObqtjmzZur2O7du6vYtm3bMO0DBw5Uscsuu6yKve997+u6l0wGWgJ8mgto3JPBAl338pe/vIqRODLpN9mQc5PpeYLmX5rvEjYKoLmE5kGav+kU8jVr1mDaJEantZ3Gz5vf/OYq9olPfKKKPfjgg5g2rYU0P9HaQfmh+eHYsWOYNs1ZNO/QukdQfqgeE24fWnOpD1B+6LrW+kjX0hpH/YL6dOvUeKoP6r8keqc1gdY8au8kWb16dRXrNS+i9y5Kh0xrEl7jyEjqDW94QxUjcx7qQ633AnqvoHakdqB3H6oLui7h/tZ6d2rhJzUiIiIiIjJq3NSIiIiIiMiocVMjIiIiIiKj5lk3NaWUC0spXyilfKmUckcp5ecm8RWllE+UUu6d/OTTqURERM5CXB9FRBYPPUYBjyf59mEYHimlvCDJX5VS/jjJf53kxmEYPlhKeX+S9yf56Wd60DAMlZCNRI8tUR1dS8JbEsKTyIrEbsuXL8e06QT1lhh4mm/6pm+qYps2bapiN998M97/5S9/uYqRcJGEopRHEqwdOXIE096/f38VI9EYCf3IxIGEYK16JDEZCevJFIDEe5TvWU4Tpv5H5aG0W2UksR2JB0kASqfvfvzjH69i3/d934dp0wnFr3nNa6oYCXTvu+++KrZz584q1ir3O9/5zipGJhsk1r/rrru60qH2Tnh+oHmE+nTrBOhpWnMYzSMtAbSMgtO6Pk73WRL4tkTVNA/SnEXCW5prKW2afxM2EKC5kcbPhg0bqtg73vGOKrZ3715Mm0TVNB+87GUvq2JUP72npyf962PrBPVpyLChJWSna3tPbyeROAnEKY2E59DevkZra2/9JPwuR+sjtQO9Y1199dXzSpvq4vjx41WM8thaH1/1qldVMXpXof5HdU6xlkkBtQW9a/SaJsxidtJr/PVMPOsnNcMcJ0v0gsmfIcl7ktwwid+Q5HtnSllERGTEuD6KiCweujQ1pZTzSim3Jdmf5BPDMHw+ydphGPYkyeQnej2WUt5XSrm5lHLzrNZsIiIiixnXRxGRxUHXpmYYhqeGYXh1ko1J3lBKqQ9maN/7oWEYtg7DsJU+hhIRERkrro8iIouDmWbRYRiOJvlkkncl2VdKWZ8kk5/1l/tERETOAVwfRUTOLM9qFFBKWZ3kyWEYjpZSXpTkO5L8QpKPJ3lvkg9Ofn7s2Z513nnn5dJLn90Ehk7pTVi0RjESwZHYjkRfLaMAElKSYJPElSRYo9Nq/8bf+BuY9tvf/vYqRuLihx56qIqRoQAJLlvCZmovEm+TiK1XMN862ZbqnARmlA4JOylGAriExX8kICWhf68QN2kL5qahU+upvel5H/sYD03qg72nBF9++eVV7PWvf30V27hxI6ZNYkQSBN5///1VjASONJZbcw31wVWrVlUxmltozFOdk+AxYZHsFVdcUcUeeOABvF8WF6dzfUzqvkli+5a5Cc1PdD/1TRKJ01rWmi9pPNMcSmnT/E9zNc1XCa+vtN6ToQBdR/NdazyvXbu2ilFdbtmypYrRXECxFlTnjz/+eBWjvLfWo2loPUi4jDSH0v2963WLQ4cOVTFqR6oLmlepXyS8ptBcTzEybaJxS2MsYUONffv2VTEyuKH2pjySuUfC74zUtjRu6f15FnOoWd4PW/T07PVJbiilnJe5T3Y+MgzDH5VSPpvkI6WUH03yUJLvnyllERGRceP6KCKySHjWTc0wDF9OUvm8DsNwKEn9EYKIiMg5gOujiMjiQWWiiIiIiIiMGjc1IiIiIiIyavrUYqcrsfPPrwRHJKqmk1cTFlX1CptJgETCZBJ4JSxk6xX10b0kQm6Vm4RWJDwkUTaJqkkI1oJEdH/5l39Zxeik9IcffriKkSEBlS/hdqR6o2dS21AfaAn1evsQidhICDlLGb/yla9UMSr3D/zAD1QxOjW7JXKlvkHlOXLkSNe9dIpyS/BOws5ewWVL4DjNnj17ME59o3d8Uxl7RbdJcs0111QxKveNN97Y/Uw5OzjvvPMqsf8sAmqan+h+mp96Bb6tvk7PJAE/zbeUbzLk2LRpE6ZN5gXbt2+vYmSk8Oijj1axWcYzmXzQfEnzN81jdF3LTIbyTmshtQ3VWa8JTyufJMyndqQ8kulBwu931LbUh8i4ZuvWrV1pJPw+1tvPac2lNY/W0YQNAMg8gPoQ1TnROher14CC2pHySOtoq1+Ruc8s4zHxkxoRERERERk5bmpERERERGTUuKkREREREZFR46ZGRERERERGjZsaEREREREZNQvqfkaQiwbFEnZ1IGcEclagZ5IzTMspiuLkFkJOGOQ0QnlsOd1Q3sm5jdwsKEZON+RakbATxvd8z/dUMXKtoDJSnbVcOHrzQ21DaV988cXd6fS6BrVczaaZpYyXX355Fbv66qur2Dd90zdVMXILa6VNjjHkqEP1Ro4xdO/KlSsx7fvvv7+KUTuSAw05sdC4a7klUTs++OCDVYzcBFevXl3FqH7JRS5h10JyxRFpQX094Tmc5ifqrzR2p51Kk/b6SM5ilDbNJZRvirUck+iZ5DJIc1bv/P3YY49hnNZ2WjsodujQoSpGbUvXJfzuQ/mkeqP6bTmBEuvWratiVJeUNuW71afJBYzWBEqb3Fepn9J6m3CbkfslzfWUH5rn6T0u4fek3ndd6pO9zogJ551c2uhdg97P6P21NZZpfmk547XwkxoRERERERk1bmpERERERGTUuKkREREREZFR46ZGRERERERGzYIaBZx//vmV0JYEUS3xHhkF9BoA0DNJPNUSQvYKvel+yg89j4SMCQvRSMRJQjQqY69QtMVll11WxXpFgiRQbIkE6X66loSDdO/SpUurWKvOqTyUdq94rwWlQwL1t7/97VWMROuUn5YJRK9ZRW9fpbHcYv369VXs3nvvrWLHjh2rYmvXrq1iJI5slZsEsVu3bq1iV155ZRWj9qKxQ30ySQ4ePFjFqF/Kucd5551Xid5JJNuaX3oF2LSekKEHrWVkMpPwOkMCfppfKN80v9D637qWnknjnuqHYq11gkxLaB0mgTmJ4Eno3zIpaM0x01xwwQVVjObG3jpLeB6kOqJ+0WtQk3AZae2geZXu7e1rCZeRxgSNHeoXsxhTUZvt2rWrilFfpTFKa3jLoIbqkkx3yByK+hW9F7TqnPp6yzishZ/UiIiIiIjIqHFTIyIiIiIio8ZNjYiIiIiIjBo3NSIiIiIiMmoW1ChgyZIllTCKhFItgW/vya0kTCLBJd07y+mlJHijZ/aKt1vlJtFZr3EB1dksp8vS/VS/dB0J0WY5Kbr3ZFwSjpPQjoSZJHZr5ZNivXU5i3kACWxf9rKXVTEqT68oNOF+1dt/KR2KtQSBVO+veMUrqhgJSO+///4qRnXeEhjSGCfTBWpbOlmZ8tgS927YsKErbTn3OO+88yqRL82rrbmfximtrzR/0/xE44fSSPh08d5nUnl6BfitPJHAne7vXZtbgnkSifeuuTRv9AqtEz6NnuZbqt9e46RWuWmubxk8TUN5bJkeUH+hOqe1Y/v27VWsVR6C8kn9nPoqtRmtHS3zi973JMojvTfRdWTCk3Cd0/3Uf2lt7X0PTPhdjsbTM+EnNSIiIiIiMmrc1IiIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIyaM24UQKeftgSBvSeWkwiJxHKziLdJGEciQ8o7CehI/NTKT0tUNQ2JtHpPc22J/Ei0ToLCXnFl7ynICYtcqd5IqEesWLGiilG7Jv1t1mso0GrbXvEfQSfRU/3SqcMtqC5bdTQN9f2WWJ/iJHC87777qtgdd9xRxV7ykpdUsdYp1dQPaCx/9atfrWI0X9G9rZPXqdyznpgsZyfDMFRjn+b01inkNJfQXD3LqfXTtOYmGvs0P1F+esX6s+SJ5moyEzl+/HgVo7ogkXfCeV+1alUV6zUdmcUooNekptVfpqG+1prHKB3KJ8Wor7SMih5++GGMT7Nu3boqRu8u1N6ttZnyTu1D5aF1mN5BW2srrQkk7D9w4EDXddQHWv2C0qa+1mvkNItxEtWHRgEiIiIiInJO4aZGRERERERGjZsaEREREREZNW5qRERERERk1CyoUcCTTz5ZCZt6RWwt6H46pZVEXyTcagkh5yMIJyHZLCdFE1QeEmlR2r33tuK9Yv1esWer3JR3ql8SrJE4ntJpidCo3JQ2PbNldEHMp//TvVTulgnELEYZ09A4IdFsy6SAxIg0bt/61rdWsTe+8Y1VjPpAS2RKIs59+/ZVMarfe+65p4pt2LChiq1fvx7T7jVdkHOPYRiquYPmahpnCc9lJP6m+2keo1hrviJTAILmIiojzRut9YTmMRL7Uzp0L5WlNadTnnqNa3qf15rHqC7JBGU+JgWtvjafdqS1o7UWUfoUozono6JZROdUH1RvlHcad9SHWu+btE5Q29KaSdB4aK3NZKZAdUHrXq8RQ2t9pPmlZfjTwk9qRERERERk1LipERERERGRUeOmRkRERERERo2bGhERERERGTVuakREREREZNQsqPvZiRMnKicPcqNoOTqQMwI5YZDbBzk9UNotp6hed69ehxVKu+XM0evYQe4a5GBDdUb5TvqdXCgdcvCgPLZcOKi9qX16nXuIlvsI0duHqM5a/Yrqna6lvkZlpOe1+k9vPlvtMw21bav/0BglxxhyKqP8vPCFL6xivY5MCbun7dixo4qtWbOmilEf2rlzJ6azbNmyKjZfB0g5OyilVHMmjYnWXELjgvo1jRVaE+i6affSk9BcRG5N5GS0f//+KkZlbDl0kpMiOYbROkzp9DrGJeyGRfnsdQtrOZ0RGzdurGL07nT06NEqRmsClbHlOEd9g/oAlZvWBOqnrWtXr15dxcjpjNqb3kla6xvN672OrBSjtmmtj1SXvQ689Ewq98UXX4xpU96pjigdWnNneSeha1v5bOEnNSIiIiIiMmrc1IiIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIyaBTUKeOqpp3Ls2LEqNg0JlVrXEiRgIuEVid1aaZDQikRwvSIrSrslhKT7e+uNhFePPfZYV35a91NdUtrUDrMYBVAZqc7Xrl1bxUjsSSLVWURoVB4SqRKtftUrPCQRJ8Uoj63xRGK9XmEy5bt3jCTc3yhG9dtbxpa4lwwAjh8//pxjNG7XrVuHaZMgloS8cm4yPV5o/CxfvhzvJWFzr9EL9WF6XsuAhfowmXzQnEPp0HxJ61bC5hskyu4Vrc9iHtNreELXUf2Q8UBrHqO5hOZBSpueOUv/6V0LKW1aO3rNkFrPpDonqH5baVMfpPcFakeK0fNoPUl4LaX67e1DNHZa7129fZDqgvoklbtljkN56jUqOomf1IiIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIya7k1NKeW8UsoXSyl/NPn3ilLKJ0op905+Xvr8ZVNERGRx4vooInLmmcUo4CeS3Jnk5JGh709y4zAMHyylvH/y759+pgcMw1AJDUn01RI2957c2issoutaQkjKJ8Xomb3XkSi/Fe89Tb63flt11lvnJGwjYT6l02rvXqFqr8iQntc6ybj3lHcSKFIeW/2K0uk1oKDyUF20TApI/EciTrqf2psEhrOMZYLSoX5OeSQRZSttipEgmwwAqJ+3BLbU/2cRycqiZd7r41NPPZUjR448LbZ58+bqOhoTCZ/m3Su8ba090xw8eBDjhw4dqmJk4EJzG4n6aV5sjeedO3dWMTp1fuXKlVWMxh7NgS1BN91Peae5mspDbdiav/fv31/FaD2j/FAZSfjd6he9xizTxlBJv5A94froNYGgcULvQy0zG1qzqYw0nqguyUyjZdDUa3ZF1/W+U1A7JP31S3VJY2yW9yEqT69B2Em63ixKKRuT/I0kv35K+D1Jbpj8/YYk3ztTyiIiIiPH9VFEZHHQ+/WzX0zyU0lO3V6tHYZhT5JMfq6hG0sp7yul3FxKuXnWHZeIiMgi5xdzGtbHWayERUSk5lk3NaWUdyfZPwzDLc8lgWEYPjQMw9ZhGLb6NQsRETlbOJ3rY+s8EhER6aNnFn1Lku8ppXx3kguTLC2l/E6SfaWU9cMw7CmlrE9Sf8FTRETk7MX1UURkkfCsm5phGD6Q5ANJUkp5W5KfHIbh75VS/vck703ywcnPjz3bsy644IJs2rTpabFLL61NYVriKfr6Gom0eoXWFGt9RY6+GtBrNNArwpwF+q0e5Z0+HWsJTQl6ZkvkNQ3lkfJDQuuE643yTvmh9iIBXUss1yuEpPrpFcEnnM9egSPFKD+tr7VQOjR2ek8tputaBhRUl9SOvSed9wpSExYjkrCTTnCmtqX5qvWpNF27YsUKvFYWP6dzfVyyZEnV52gOXLZsGd5PY5fuJzF573hsfZpE45zGKY1nEomTAcsspiM09knsT3U2ywnovfMy1QWlTW1Dov7WM+l9iuYXaluq85bhSW8ZKW26t9WvqP9SX6P7e/tF652P5urDhw935ZHSJtODhx9+GNOm8pDRAPUNyg+tb9QOCffLiy66qIrRmOidR1rGEL3j6ZmYzzk1H0zyjlLKvUneMfm3iIjIuY7ro4jIAjPTl3iHYfhkkk9O/n4oydtPf5ZERETGheujiMiZZT6f1IiIiIiIiJxx3NSIiIiIiMioWVAPyRe+8IW54oornhaj00tbgsBewRDdT2IlEo21BGuU9iwnpU5DYq5W+XrF+r0CvFlO1e2l15xhvkIwarNesT2JMFumFCSMIyE83U/t1epX1I5UbyTYpDL2tneL3r5BsZaYlugdO1RuEvxS27ZMCqjeaB6itu0VrtLzWvfPYiwhZzfTY4DGBPX1pG1OMU2vWH8WegX3lEcaPySAbpWP5ggqD8VIWE+i6paYvHc96j2Jnua2VtvQPEb3U3nIFICE6C2TGTKroDqi2CxmCASVkWK0hlN+WoYyvRw6dKiKUXtTP6V7Ex731P+XL19exag8ZMbUei+geuudW6h+qW1bZlUUn/V8S1dTEREREREZNW5qRERERERk1LipERERERGRUeOmRkRERERERs2CGgUsWbKkEq2RGLclnCWxEonOWuK2nnRa4mK6lvLTK44nIVhLENUrwqf8UGwW4VVveUgE1ysaa0HtSO1DAn4SZPe2V8KiyZUrV3blh0SYLSjvJLjvNb8gWiI/eiYJHKk8vUL/lkECjdve/tJ7Inqr3L2GBr0ni5O4cfpk+JPMclK6nFs89dRTVd+mvk7i9oT7IZ1YTkLiI0eOVLHeNSbhNYHEyfRMmldpnLTmVUqn96R1mr9p3WkZ6VB5KG2a50ncTuto69R5Kg/NO1Q/1FdmMT46ePBgFVu6dGkVo/574MCBKtZaJ6h9KJ1e4ySq31baJJinvkGmMFRuGjurVq3CtKlf9b4HUp3RmKf+k3B9UNq979lkKtFrPJDMbuTgaioiIiIiIqPGTY2IiIiIiIwaNzUiIiIiIjJq3NSIiIiIiMiocVMjIiIiIiKjZkHdz84777zK/azX5SFhxw5ywpjFWaH3XnLSoBg5QpCLEt07i/sZOVdQjJwsKO1Z3F0Ieia5tuzfv7+KtZyiyNGE3EvI7YPSpuvIeSfhfkXtQ84e1E8feughTGfNmjVd+aS2pbro7SsJu/TQ/TQmqF+Rw0+rT8/SB3uge1vPozHa69zW67LWKjelQw6Qcu5RSqn6Uu8c2LqWnJkoRvfSPEbjNmFXwF6HT5qfHnvssSp26NAhTJvWKHJMovL0Oqq2nNdabqnTUB7JlYxcN1vlpnWT6nLFihVVjPJN82XLeY3a9vDhw135Iee01nvX5ZdfXsWoD/Y6lfX284TbguqN1gTqv9T3p9+HT9K7FtIzex2Fqc4Sbgty6qP6pfcpGoutcUNt2+tWehI/qRERERERkVHjpkZEREREREaNmxoRERERERk1bmpERERERGTULKhRwDAMlbiIhFstYTNdS6I+uo4ggVcLEjb1mgeQ8IrEaS1BFIm8SLhI4rJesVwLSpvKQ7FLL720iu3atauKkcCwBdURCWfpmSSgI7FmwmLa5cuXVzGqc+pXLVFeKz5NrylFb3slbTH7NDQeqS4pHTIjSFjkSm1B5aF8zzIP9IpFew0Sek07WvfPMg/J2c10nyOReKu/0JgkgW+vCJnubaVNz6SxT+OMBNm0drQE3UeOHKlitD72rnu01rfmUFp7aK6m9YTmCBJVk2lNwvMlCdRJ7E/tNYtpU68pDOWRnnn11VdjOtSnqR2pjJQfaluqs4TfNei9gt4Lep/XMkmiOuptWxp31LYtsT7VG91P7bBv374qRu84rXddGuOzGun4SY2IiIiIiIwaNzUiIiIiIjJq3NSIiIiIiMiocVMjIiIiIiKj5owrVEns3KL3tHQSOpGgj9JuCQJJVEXiKYr10hLlkXiKhJBUbhJz9cZa9AoKqX43b95cxR544AFM5/77769iJDrbuHFjFes1dmi1N4lkd+7cWcWoX1Ee169fj+lQXZKIjvJOfZ/y0ypjS3g7DeWxJYSf5tixYxgncTCZSFAfIuEgCXFbpzXTM6k88zEPaM0DNM56TyWXs5sTJ05U8w4Jx1sGHzTv0DpBJ8xTH6Z+2RJF0/xPc2jvfDfLmKA6onFK6fSu4S2xMpWb8kMxgvJIJigt6Nr77ruviq1du7Yr7VZfo3mM1nESwr/uda/rSruVTq85z3zMdRIW3JNpA40x6i+Ub1oHEzZYoLWd2ofKSHXR6pM0dmjOoDW3932e6izh9iZTimfCT2pERERERGTUuKkREREREZFR46ZGRERERERGjZsaEREREREZNQtqFHDixIlK9EPCoJYImYRWvYLw3lNSWwJFemavyJDK2CscTFiwTOKpXpOCXqHdLM/sFeFTbPXq1fhMaott27ZVsf3791cxEkKS+I6uS5LPfe5zVewVr3hFFduwYUMVm+WEeKo3yidB44TqtyX27M1Przie2qvXjKB1P53gTGLEWdIhkSKJHkkUvWzZsipGYthZTkzuNV2Qs5sTJ05U6wKNs0OHDuH9NK9T36Tx03syeUu0S+mQcQHNLySAnmV96xUs7927tys/NEYpjYTnAxKT95rzrFy5soq1TAoo71RvVBckUKe0W3VOpgCU9hVXXFHF1qxZU8WoryS8JlB/6TVgobW1ZaTTu8YRvf2qtW71jr2DBw92XUf9l+qxlSfKD8031PepvVt9epY5p4Wf1IiIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIwaNzUiIiIiIjJqFtQo4Bvf+EYlbCIBU0tk23tKK4nGSPTbK4JPWPhFojES5ZHgjPLYOo211yCBBG8kBqP89J4Em/QL3qjOSAjWOqWaBO4kcCSRKtUv1c+qVasw7SuvvLKKrVu3ror1nibcEhj2Ckip3uiZ1Fdabdsreu8VCdJ1JEBOksceewzj05CJRG/bUn4Snl96TRd6TUhaIsxecxE591iyZEkuvvjip8VIQN1aH2lepxPmqW/SXEDzWMvUhZ5JouxeMxESB8/yXkDp0LsGjT0a4y0zj2PHjnWlTW1DwnyiVe5ewxTqA73rTittqrfNmzd3xagPtQTzVO+95gHE9PhK2qZNNK/TOwCtM73pHDlyBNOm/t/7LkdzBq3XrT5NYn9ar3vfAagsLTMk6lezGum4moqIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIwaNzUiIiIiIjJqFtQoYMmSJZXwjASKrRNeSWhFJ6qSeO/SSy+tYnTS6SyiXRKSUYzEdiQwb0HCuF5BFYn/SAg5S7lJoEhtQ88kUWdL0E11dNlll1Wx/fv3d+WR6mL37t2YNgkXKe9URhL0teqX+n/vickk6ifx3iwnUlPa1Kd7hYyURpLs2bOniu3bt6+KkTEEiTBJwNkS4pK4kuqSYlQeilEaCY/RWUw65OyF1sdZROsk5qW1lPo1rZkrVqyoYtu3b8e0aa4mMXCvSQflkeahFvReQGnTOKU5tCUmp3xSeWj+p/bqXcNb+aR26F3vH3rooSrWmkM3bdpUxcgUgOZlgswMEm4zqo/eeZXqvLU+0jtArwnV8ePHq9ihQ4eqWGudoPG4d+/eKkbloXfdXnOnVjpkHkDpUJ+k94LWO36v2dUz4Sc1IiIiIiIyatzUiIiIiIjIqHFTIyIiIiIio6ZLU1NK2Z7k4SRPJfnGMAxbSykrkvz7JFuSbE/yt4dh4JOEREREzlJcI0VEzjyzfFLzbcMwvHoYhq2Tf78/yY3DMFyT5MbJv0VERM5FXCNFRM4g83E/e0+St03+fkOSTyb56We64YknnsiOHTueFiOXB3I3StjNglyY6H5yqKDrWi5VlDa5sZBTGTlUkBMGOUcknHe6lvJ+ySWXVDFy8JjFrYmcYMh1Zb7OYOQsQw4r5O4y3c8Sdklr1fmrXvWqKtbrpkJ13nIBI5cUqo9eFxhyC6N6bEFpU4xcSqhPf+pTn8J0aNxu3LixilH/Iwc8ctA7coR/KU51SVDa5BhDddFyaqKx0xp7MnpmWiNPnDhRjYtZXDJpnaCx27t20FxNabSeSWshjYsDBw50pU1OkQk7M61fvx6vnYYcF6ksreeRAxStE1S/NBfQPNZyP+tdJ2geI7cxcgFrub5dddVVXff3upC23gF6nbN63WCpT7bmX+oH1D6HDx+uYlRGapvPf/7zmDa9V1x00UVVrNe1ltatVtvSGKW6pOuovek9u+V+RvU7qzto7yc1Q5L/VEq5pZTyvkls7TAMe5Jk8rP2RxYRETn7cY0UETnD9P6K8C3DMOwupaxJ8olSyl29CUwm+Pcl/b8hFRERGRHPaY08dX1snT8jIiJ9dH1SMwzD7snP/Un+MMkbkuwrpaxPksnP+rs9c/d8aBiGrcMwbG0d9iMiIjJWnusaeer62PpKhoiI9PGsm5pSykWllEtO/j3JO5PcnuTjSd47uey9ST72fGVSRERkMeIaKSKyOOj5+tnaJH84EU2dn+TDwzD8SSnlpiQfKaX8aJKHknz/sz3oySefzJ49e54WI7FS6zdWJFKkr7SR+O/RRx/tupfEbgmLoiifJMruFY6TKC5h8RTFSJBFgjNKuyVkpzyReJUEeFS/s6RNUJ1fe+21Xfkh84BVq1Z1p0PidjK6oD7QEnv2GjFQHVH9Uj9t1S+NJ8oP9TUyBSAhY0tYvGHDhq60SYRJ45v6aattV6xYUcVojFIfoLqktp3lU+mWqYCMhtOyRp44caJap2jOaUHCZhJBkzCf+v+aNbUEiNaTpL1mT0NjnOaxWdZmmutpjaL56eGHH+56XqsdegX3JHamMtLcP0u56Zlr166tYjSn09xGRghJv3ESxWhOp/wk3I5URjLIobWH+mmrT69cubKKUX+hGEHlbhmBUD+g+6l+6f2DTJKofAkbb1B+aI2jd1CKtdp7vmtp0rGpGYbhgSSVFdQwDIeSvH2m1ERERM4iXCNFRBYHs5xTIyIiIiIisuhwUyMiIiIiIqPGTY2IiIiIiIyaBT3K+gUveEElECaBLwmBk2T37t1VjEReJI6kE4FnOamUBI69sV5xcUsQSNBJ9FTu3hNnW9dRPkmc1hJ+TTPLifckhCSRN/WLXvF1S0Q/i6lAz3Wt03tJvEp1SSJgEj2S8LDVz0n8SgYAlJ+DBw9Wsf/wH/5DFWudvXH55ZdXseuvv76KvfnNb65iVG4ybGgJOHvF1zSees/aao2n+RplyNnN9HxLff2BBx7Ae6lvUj+kOb3XuKMlbF62bFkVI/MBmuvJxIfGbmuc0BxKa8eDDz6I9/dAQuuE67L3vYCE37PMBbTG9ZrZUDr0TtFam3uNAqgdyICitUbRM6k89O5E75YkOm/N1bt27apiVB7KT+97betdl9bH3utoPK1evbqKtd7Z6F2F3p8pHWoHGjv0HpewuUOvEcNJ/KRGRERERERGjZsaEREREREZNW5qRERERERk1LipERERERGRUbOgRgFPPPFEtm/f/rRYSzBE9J5ES4JJOtWUxGmtE9Dp2pb4exoSotHzWqcy9546T4IsEmuSAJpiLSgdEuBR21AZSVSXcBlJmEmQeI8g44KEBZJURySMIxF961RcKjsJNkkASqJdOg2YYgmLHkn8R3z1q1+tYq985Sur2JYtW/D+6XkgSW666aYqRiJgKg8JlUkcmfBJytS2JKal9qbx3Tqlmgwfes0H5OzmiSeeyEMPPfS0GM1DNG4Tni9pPaM1t/ck+9YJ8yToPnDgAF47DY3Hyy67rIq1xOS0ztAa1Wt8QNfRPJSwiJnmUMojtSOl3Vrz6P5eAyKa22iNaa0HNF/S/TTfUZ9uGcrQPEp9leqC1lzKT2t9pDan/ND8T+ZF1NfIoKOVT3p3uv/++6sYjXl6z6A0El5LH3nkka50et/PWsYbZLLUmu9a+EmNiIiIiIiMGjc1IiIiIiIyatzUiIiIiIjIqHFTIyIiIiIio2ZBjQJKKZUoloRFrZNOSShI4isSG5Hoa+/evVWsJdrtFduRiI1EcCS0awm3SCjVK+YiITzVRUuoR0LBXjEYXUdt2Co3idvofsojtS2117Qw9yTXXHNNFTt06FDXM0lMSO2VsCkAtQ+JMKl+SARMIt7W/UeOHKlit956axUjwTC14+23345pk7hy06ZNVYyMLqg81A4tYTGJeykdagcSa1J+WuOJaLWPnFuUUipxM60TrbmE1omW+cw0vcLvlqlL7zMp79T/Ke1e85eExy6tEyQmp3zPIlbuXe/pOlo7WiY+vW3WazxD82VrDu01JKDy0DpB73EJz9W9xkmUDr0b7tq1C9Net25dFaN3rB07dlQxMqaidGYxpqI1kww1qK/Se+DatWsxbUqndz2jftUy2SDIZGkWE6vET2pERERERGTkuKkREREREZFR46ZGRERERERGjZsaEREREREZNQtqFJDUAjMS+LZOXydRFQnJ6LTzNWvWVDE6Ab0lSiLRGeWdrusV4LXSJpEWiSvpfhJ9kZCsJYQkQSCJ8qg8JPqa5fR0ErlSe5OAn+qM+k/LpGDPnj1VrPd0Y0pn3759mA49k4R1dAoz9Wnqky1x77Zt26oYtQ+lQycmU7lJOJgk69evx/g01P+oX5DQtCVQpDJSOiQs7jUMaQm0aTy25js5t7jggguyZcuWp8Vo/LSMdHrXHnommXRQvybReQuaD2i+pDFFpgCtk99b9TENzQe0nlA99qaR8HgmgTnN/bSut9bmlStXVjEq4+HDh6sYzYHU3i0BP+Wzd76ktZDuTbgtaD2i8tD7EI2H1jvJvffeW8Wobel+MirauHFjFbvnnnsw7d4ykrEPtePmzZurGJkZtO4nIx1qM2ovMmO67rrrMG0aj7PiJzUiIiIiIjJq3NSIiIiIiMiocVMjIiIiIiKjxk2NiIiIiIiMGjc1IiIiIiIyahbU/eyCCy6oXFaOHj1aXbd9+3a8nxxIyMHh0ksvrWLkFEJOC+TOkrCLB9Hr1kS0HFbIxYPSIecJckOhdMgVpAXVBbk60XXkmtJyfyIHMyr3fFzAWg4gVJdURsoPOZKQe0jCZeztv+SGQs5GLQeyXbt2VTEqz6pVq6rYihUrqhiNp5ZjEeWJ6pzupzz2ts0s9/eOE+rnLcc5mgtarodyblFKqeaDXqfJFjROqW+SYyj1S5qbkv5xSnMJzQW0brXGFOWTxi7VJblKUjqtuYTcwWg9o3meoLRbDp1Ub73OkFQ/s7g4EuTwRn21tx1a6VNf633PIce5Fvv3769ilE9ahyk/5NJKroMJO4ZRuWk80npEaa9evRrTprxTvdG4o/c7GvPkLpvw+1jLga+Fn9SIiIiIiMiocVMjIiIiIiKjxk2NiIiIiIiMGjc1IiIiIiIyahZUofrEE09k586dT4uRqInEjQmLtEg89eSTT1YxEjGT+JrEbgmLwQgS25F4isR/LUFgr7C5V9xOtK6jtKmMlDbVL7VNK+35CKgpjyTgbAkUW31wGhKxUZ+eRexGwjrKO9XlgQMHqhiJBJNk2bJlXdcePny4ilHbUju2xg21LYkESQxLdUHzQEuc22sK0Cvqp+taAlvK+yzCbzl7efLJJyvzDppXW3MWzRskyqY5ncTBNGfRdQmPC5oHe01UaJy00u4176AxOV/BfO9aSHmndqT57tFHH8W0KU51QWWkd5L5GgX09jWaf1vvAOvXr+/KE5Wb3vlmqd9169ZVsYMHD1Yxau/e98UWvcYHFKOxeNlll1WxlvEGjXuqcxqjrXfYaVqGXJT3WddHP6kREREREZFR46ZGRERERERGjZsaEREREREZNW5qRERERERk1CyoUcCSJUsqARSJ01qnvJMwqSXsn4YEZyRaXL58Od5PgjcSRbVOHp6Gyt0SxtO1BIntSODVe13CgkIqI4myqTwtcRrRa3JA7UBpkwCulUav0LRX2EaCvoTFoiSiO378eBUjAf+xY8eqGAlxEx47JFCk60hcSem06re3v5ABANUv9dMWZJBAz6RxR+YMdF1rHqA5TCSZGyvTa98sY4rmjV6Bb68pS0sITCeb0/xE5aH5hd4BWmNqvnPwNLOYuvTWGwnHe8X6rTmDnkl1OZ91dBaDBFoze981WuYXVHZqRzK4IVOAWaC5nvolGRJQX6Xn0XqdJBs3bqxiZFJAfYDeYakdWu+61BZURnom9QEqY6u9qc1a7y8t/KRGRERERERGjZsaEREREREZNW5qRERERERk1LipERERERGRUbOgRgGllEqMRqKxllCPxGAk3CKxEp20TiK01kmnFCexU68obxZhc68QstdQgOp8ltPX53NKcO/zWnEyGqC67BX1U19JWNRHdUR9gNJutQ2lQ/2c+upjjz3WlQ6l0XomGQXQM0mQunLlyq48JmwAQO1D99O9sxhQUHlINEnP7D2VvCXuPXr0aBVriSbl3OKCCy7Ihg0bnhYj4WxLnE7zJY1nuq5XYE5jL2EjExpTtI72Csxb0PxPY7d33ZpFME9tQfmhdGgemuUkerqf8k7vU/T+QLFWX6Py0LsYzYMUa73zUf+nGK1x1KepzlrvPtSnaY0j0xya52cxaCJhPqVN91Osdx5IuM1XrFhRxfbu3VvFVq1aVcWoT8+yXs9q+OAnNSIiIiIiMmrc1IiIiIiIyKhxUyMiIiIiIqOma1NTSlleSvloKeWuUsqdpZQ3l1JWlFI+UUq5d/KzPn1LRETkLMb1UURkcdBrFPBLSf5kGIbvK6VckOTFSX4myY3DMHywlPL+JO9P8tPP9JATJ05Uoh8Sl5GoP+FTi0l8tW/fvirWezrs/v37MW0SM/YK8Ei8R4K1lpicBF29RgO95gEtYSblvVdcSQIxKksrj1SXlHaveQA9ryWW6zUFIEgISaLFhE/bpbzT/dQnaYy00iZBIeWHxgndSyJgEg4mPB6pPNS2JByksdgaI3Q/lYfKTWUkQXRL3Ej5bJ3SLqPhtKyPTz31VDVWqW+0zDeIXlMAEgevXbsW80jQqd+9JkA01/YK61txmjd6hfVk/NESzBO9cyNBddGaH3rrjeZaWgt7zWgSXtspn1RvtI5SfhJuR1qjqM2oHah+ZikjpU39isYJlbtlkEB1SesjpU3tSNe13vlofiCDkE2bNlUxevdetmwZpkOcjrXwWT+pKaUsTfItSX4jSYZheGIYhqNJ3pPkhsllNyT53nnnRkREZCS4PoqILB56vn52ZZIDSX6rlPLFUsqvl1IuSrJ2GIY9STL5ueZ5zKeIiMhiw/VRRGSR0LOpOT/Ja5P86jAMr0nyaOY+Su+ilPK+UsrNpZSbWx8xioiIjJDTtj7OcnaZiIjU9GxqdibZOQzD5yf//mjmJvF9pZT1STL5iWKUYRg+NAzD1mEYts7yvVQREZFFzmlbH1sH8YmISB/PussYhmFvKWVHKeW6YRjuTvL2JF+d/Hlvkg9Ofn7s2Z61ZMmSShhFwqvWqbpHjhypYocPH65iJIzrFebTSa4Ji7zWr19fxUjo1HvCcEu03or3QGnPIsbqFfbTM3vrYpbykbCOTsvtTaf121ESYdK1JAgnUWhLOE7PJEFgb96p/7ZOTKZPTlvXTtMrPGx9OtvbZiQypLRJKNoSKPbOBdRmNA+QmLUlAKVf7PgyO15O5/pYSqn6wiynkFOf27NnTxWjMU79kvp1a36gOY/GX6/hDpWxNVfTek/vEDRHEFTGVp33muZQ3umZVOet9yEShFM7UDrU3r3GPC0oHapzEua31kdqW4Ly3iuib0Ft9uijj1Yxah+qX6rL1niicUL1RgL+3nZsGR/R/dSvqH7JXISMB1r9ivrQrOYBvR+d/MMkvztxdnkgyY9k7lOej5RSfjTJQ0m+f6aURURExo/ro4jIIqBrUzMMw21JtsJ/vf205kZERGREuD6KiCwO+j9bFBERERERWYS4qRERERERkVHjpkZEREREREbNgnosf+Mb38jRo0efFlu+fHl1HTmaJanuTdhlgq7rdXVq2U6T8xqls3LlyirW6xTVotdtbJZnTtNylqG0e6+jGKXTcjjpdezodQsjV49W2r3OeJQf6kMtB49el7VehyBym2mlTU4wVEf0THJ8oTySY0vrWnomxcgp55JLLqliLec16i+9Z4T0juWWo9983f/k7GUYhi6HrtY8T+tRr8tg71zQ6qs0D/bOEStWrKhivQ6HCdcHlZHm2l7XTnJ/Srg8vU5nVL/UDq32pvqg/FC5aV6mdYvctRJ2aaMyUt573ylaUPtQ2jTP9977TPGe62jczfJeQHknevsfxY4fP47PpHdy6qvkakbr8MUXX9yVn4TnF3rmM+EnNSIiIiIiMmrc1IiIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIyaBTUKKKVUYqkdO3ZU1x07dqx5/zQk3iaxEYnTSCROwqskOXjwYBXbu3dvFSORFaU9iziY7idxWq/okWLPh3ivJdTuubcV7xUj9hoStIwCSLxKfY3KSPluiVxJxEliUeovlA6Jc+l5rfuJ+fSNltCUhKq9InwqY6/hQitOdUT5IYFsr1lEcvoNPuTsYnp+m6/5BvVXuo76cO9c27qW8kn9/9FHH61il156aXfaNB/QfEtzda8xSmuuJAMBmovI3ISuo/ZqmRTQnNUrHKf5qdcsonUtrVFUl7MYJ5HInATqrXVmGuqnrXWCykjvC1SX1LZ0XUsET/VOeae+MauwfhqqXxpjVB4a87OMZSrPrEY6rqYiIiIiIjJq3NSIiIiIiMiocVMjIiIiIiKjxk2NiIiIiIiMmjJfgfhMiZVyIMmDk3+uSlKr78fJ2VSWxPIsZs6msiSWp8XmYRhWn4bnyEg4i9fH5Owqz9lUlsTyLHbOpvI87+vjgm5qnpZwKTcPw7D1jCR+mjmbypJYnsXM2VSWxPKIEGdbPzqbynM2lSWxPIuds6k8C1EWv34mIiIiIiKjxk2NiIiIiIiMmjO5qfnQGUz7dHM2lSWxPIuZs6ksieURIc62fnQ2ledsKktieRY7Z1N5nveynDFNjYiIiIiIyOnAr5+JiIiIiMioWfBNTSnlXaWUu0sp95VS3r/Q6c+XUspvllL2l1JuPyW2opTyiVLKvZOfl57JPPZSSrm8lPLnpZQ7Syl3lFJ+YhIfa3kuLKV8oZTypUl5fm4SH2V5kqSUcl4p5YullD+a/HvMZdleSvlKKeW2UsrNk9iYy7O8lPLRUspdkzH05jGXRxYHrpGLB9fIxY9r5OLlTKyRC7qpKaWcl+RfJvmuJNcn+cFSyvULmYfTwG8neddU7P1JbhyG4ZokN07+PQa+keQfD8Pw0iRvSvIPJu0x1vI8nuTbh2F4VZJXJ3lXKeVNGW95kuQnktx5yr/HXJYk+bZhGF59iq3jmMvzS0n+ZBiGlyR5VebaaczlkTOMa+SiwzVy8eMauXhZ+DVyGIYF+5PkzUn+9JR/fyDJBxYyD6epHFuS3H7Kv+9Osn7y9/VJ7j7TeXyO5fpYknecDeVJ8uIktyZ541jLk2TjZNB/e5I/msRGWZZJfrcnWTUVG2V5kixNsi0TXeLYy+OfxfHHNXJx/3GNXFx/XCMX758ztUYu9NfPLkuy45R/75zExs7aYRj2JMnk55oznJ+ZKaVsSfKaJJ/PiMsz+Sj6tiT7k3xiGIYxl+cXk/xUkhOnxMZaliQZkvynUsotpZT3TWJjLc+VSQ4k+a3JVx9+vZRyUcZbHlkcuEYuUlwjFyW/GNfIxcoZWSMXelNTIKb92hmmlHJxkt9P8o+GYTh+pvMzH4ZheGoYhldn7jc4byilvPwMZ+k5UUp5d5L9wzDccqbzchp5yzAMr83cV2v+QSnlW850hubB+Ulem+RXh2F4TZJHM66vBcjixDVyEeIaufhwjVz0nJE1cqE3NTuTXH7Kvzcm2b3AeXg+2FdKWZ8kk5/7z3B+uimlvCBzk/XvDsPwB5PwaMtzkmEYjib5ZOa+2z3G8rwlyfeUUrYn+b0k315K+Z2MsyxJkmEYdk9+7k/yh0nekPGWZ2eSnZPfcibJRzM3gY+1PLI4cI1cZLhGLlpcIxc3Z2SNXOhNzU1JrimlXFFKuSDJ30ny8QXOw/PBx5O8d/L392bue7eLnlJKSfIbSe4chuGfn/JfYy3P6lLK8snfX5TkO5LclRGWZxiGDwzDsHEYhi2ZGyd/NgzD38sIy5IkpZSLSimXnPx7kncmuT0jLc8wDHuT7CilXDcJvT3JVzPS8siiwTVyEeEauXhxjVzcnKk1csEP3yylfHfmvgd5XpLfHIbh5xc0A/OklPLvkrwtyaok+5L8z0n+ryQfSbIpyUNJvn8YhsNnKIvdlFLemuQvk3wl/+U7qT+Tue8Mj7E8r0xyQ+b61pIkHxmG4X8ppazMCMtzklLK25L85DAM7x5rWUopV2buN0/J3MfSHx6G4efHWp4kKaW8OsmvJ7kgyQNJfiSTfpcRlkcWB66RiwfXyHHgGrk4ORNr5IJvakRERERERE4nC374poiIiIiIyOnETY2IiIiIiIwaNzUiIiIiIjJq3NSIiIiIiMiocVMjIiIiIiKjxk2NiIiIiIiMGjc1IiIiIiIyatzUiIiIiIjIqHFTIyIiIiIio8ZNjYiIiIiIjBo3NSIiIiIiMmrc1IiIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIwaNzUiIiIiIjJq3NSIiIiIiMiocVMjIiIiIiKjxk2NiIiIiIiMGjc1IiIiIiIyatzUiIiIiIjIqHFTIyIiIiIio8ZNjYiIiIiIjBo3NSIiIiIiMmrc1IiIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIwaNzUiIiIiIjJq3NSIiIiIiMiocVMjIiIiIiKjxk2NjJpSys+WUoZSytvm+Zy3TZ7zs6clY7Ol/duTtLcsdNoiIiLSTylleyll+5nOh9S4qREREZFzmskvlk7981Qp5XAp5ZOllB8upZQzncczxaT8Qynlh890XojFnj9ZOM4/0xkQmSe/kuT3kjw0z+d8IclLkxycd45ERGSs/Nzk5wuSXJ3kv0ryrUm2JvnxM5UpEXl23NTIqBmG4WBOw0ZkGIbHktw1/xyJiMhYGYbhZ0/9dynlLUk+leTHSin/5zAM285IxkTkWfHrZ3JGKKX87VLKp0opx0opXyulfKWU8oFSygunrts++bO0lPLPJ39/8qT25Zk0NaWUHyql3Dp5/v5Syr8tpWyYfJ1gmLoWNTUnry2lnF9K+ZlSyr2llMdLKTtKKb9QSrkA0v3eUsrvlFLuKaU8Wkp5pJRySynlfyilOOZEREbCMAyfztwvvEqS103/fynljaWUj5ZS9pZSnpisDb9WStlAzyulrCil/Hwp5fZSymOTNfBLpZQPllIumrr2mlLKvyml7Jo8e/fk39fAc/96LSylfF8p5QuT5x8upfxeKeUyuOfKUsqHSin3TdbJw5O1+F+VUlZOrvlkkt+a3PJbU1/R2wJp/91Syucn6972yf8/o2b1mTQqpZQfKKXcOMnb1yfX/rtSytbe/E2uO7+U8mOllM+VUo5P6uaLpZQfp3W5zPHjpZQ7JunuKqX8SillGeVTFgd+UiMLTinlnyX5QOY+YflwkkeSfFeSf5bkO0sp7xiG4clTbrkgyZ8lWZHkPyU5nuQZf1tWSvknSf63JEeS3JDkWJJ3JPn05O+z8uEk35zkjyfpf3eSn0qyJsmPTF37wSQnknw+ya4ky5J8e5JfSvL6JH//OaQvIiJnhpN6miefFizlR5L86ySPJ/l4kh1Jrkny3yX5m6WUNw3D8NAp11+R5M+TbE5yS5Jfzdwvl69N8j8m+VdJHp1c+/ok/znJJZNnfzXJS5L8UJL3lFLePgzDzZDXH0vyPZN7/iLJG5P8QJJXlVJePQzD45Pnr09yU5KlSf5jkt9PcmGSKzK3Rv1KkkNJfjvJ0STvSfKxJLedktbRqbT/cebW2f8wKedz3gCUUkrmNivvzdy7wh8kOZBkY5JvS3J3kpt78ldKecEkT985ue/DSb4+ec4vZ66OptflX0zyPyTZk+RDmWv790yuvSDJE8+1bPI8MgyDf/yzYH+SvDnJkDkNzLpT4udnbtIZkvzMKfHtk9h/TnIRPO9nJ///tlNiV2ZuAjqQ5PJT4iXJv5tcP0w9522T+M9OxT85id+SZMUp8YuS3JfkqVPLMfm/qyCfSzK3uRqSvHHq/357Et9yptvHP/7xj3/OxT+0Lkzi3zKZ5x9Psv6U+LWZe7G9L8llU/d8++SeP5yKf3qSzgcgnVVJLpz8vSS5c3LtD01d9wOT+F1JlpwSP7kWHk/yiql7Pjz5v799SuwfTmI/AXm5KMmLTvn3D0+u/eFG3Z1M+9Ekr4H/x/X1lP/fnmT7VOx9k3u+kGTZ1P+dN9UWvfn75STnTT3nNyb/955T4t80id03te5fmOSzk//bTmn558z+8aswstD8t5Of/+swDHtPBodh+EbmfstzInO/5ZrmHw/D8GhnGn83c5ukXx6GYccpaQxJ3p+5xWZWfnoYhsOnPOvRJL+buc3K1lMvHIbh/umbh2E4kblPapK53xaJiMgiY/JVqp+dfEXs32fuF2olyU8Ow7DnlEv/n5kzE/iJYRh2nfqMYRj+LHOflPzNUsolk+e+LnMvy7cl+YXpdIdhODgMw9cn//ymzH0q89lhGH536rp/n+SvklyX5K1QhH8xDMNXpmL/evLzDXD91yAvjw7DUMU7+NAwDF98DvcR/3Dy8/8xDMPTvl0xDMNTU23RZPLVsh9PsjfJ/zgMw1+v/5O//+NMNo+n3Hby2xc/P7Xufz1z3zKRRYpfP5OF5rWTn382/R/DMNxTStmZ5IpSyvJhGI5O/uvrSb48Qxqvmfz8K0jjwVLKjiRbZnheMvcx9zQnN0yXnhqcfBf5n2TuK2pXZu63XqdSfbdZREQWBf/z1L+HJD86DMNvTcXfPPn5rZOvik2zJnOfBFybuU/63zSJ/+nkl1zPRHOdPCX+1sytdZ+a+r/eterjmfvK978spXxnkj/N3CdJX538AvC58IXneN/TmGiLXp5k32nYJF2bZGWSe5P808LO3F/LnPvpSU7W/1/AtX+Z5BvzzJM8T7ipkYXm5HdsW79l2ZNk0+S6o5PY/hkn2ZNp7Gv8/77MuKk5ZYN1KicntvNOBkopyzP3PeUrMjfB/5skhyfXLk/yE0meZoYgIiKLg2EYSvLXL9ZvztzXk/5VKeXByScwJ1k5+flPnuWRF09+Lp/83NW47lR61slTn3kqRyFWrVWTX/C9IXNfzXpXkv968l87Sin/xzAM/6Ijn9PsffZLulg++dlTV8/GyXa6JvWG9VQuPuXvzXeIYRieKqUcOg35kucBv34mC83Jj5HXNf5//dR1ydxvymbh+OTn2sb/t+Kng/8ucxuanxuG4Y3DMPzYMAz/dJizCf33z2O6IiJymph8Bes/J/mbmdsM3FBKefEpl5xco5YNw1Ce4c/J3/Yfnfzs+aT+uayTMzMMw53DMPxA5l78t2bu69lLkvxSKeVHn8sjG/GTn0y1fpE+bShwdPLzdHyr4WQd/eGztNMVcE/1rlBKOS//ZaMkiww3NbLQnPwo+W3T/1FKuTpzzibbGp+MzJpG9X3jUsrmJJfP49nPxtWTn78P//etz2O6IiJymhmG4cuZ06RszJxD2Uk+N/n5zZ2POnn9d5KF8BTNdXIqfmtn2s/IMAzfGIbhlmEYfiHJD07C33vKJSd1KOfluXFk8rNaeyfr/vKp/Dya5PYka0spr5m+B3im/N2VuU3SmyYuaD2crFdas785fstp0eKmRhaa35z8/KellNUng5PffvwfmeuTvzHPND6cuY/b/2Ep5a8n0YlF5P83z31i7mH75OfbTg1OJmYFhiIi4+N/zZy28ydLKSd1Kb+SOZfN/18p5drpG0opF5RS/nrDMwzDLUk+k+TVSX4arl9ZSrlw8s9PZ856+K2llO+buu77MufIdk9AN9pLKeUNpRT61sLJ2GOnxE5+3WrTc0zursx9g+I9pZQ1p+ThRUlaX3M7Gf+16bNhSilLJpbUz5q/iQnRL2fu061/MUnzaZRS1pdSrj8l9NuTn/9TKWXFKdddmLl3CFmkuNuUBWUYhs+UUv63zJ3xcnsp5aOZs4H8rswJA/8qyf8+zzTuL6X8vzMngvzSxMHm5Dk1K5J8Kckr55PGM/BvMvcd618spXxb5sSJ1yR5d+Z89n/geUpXRESeB4Zh2FVK+bXMaSJ/KnOWzHeVUv7bzP2i7o5Syp9kbqPxgsy9XH9z5o4VeMkpj/p7mTsm4J+VUv7W5O8lc2vEOyfXbh+GYSilvDfJJ5L8+1LKxzK3Mbguc5+gPJzkv+kwHHgm/m6Sf1BK+YvMWRcfSXJV5r5u93jmzmk5yWczt8n5R5OX/JNak1+ediYjhmF4spTyS0n+R8asowAA2dNJREFUX0m+WEr5w8y9f74jye7Jn2l+PXPftvhvktw7qYMDSTZkzjL7NzOnB+rJ3/8nyauS/PeZc6T7s8zpddZkru7fkuR/ytxZQBmG4dOllF/OnAPbyfeUk+fUHElb6yRnmjPtKe2fc/NPkr+TuQ3Mw5n7DdgdmZtULpy6bnuewQ8+cE7NKf/39zP3Mf7XMzcZ/k7mJsTbkxyduvZteYZzahpp/3DAGz/J9ZlzltmfuQ3bLZnT2myZXP/bU9f/djynxj/+8Y9/ztifNM6pOeX/107m80eTrD0l/orJHP5g5jYDhydrzK8l+XZ4zsrMWTrfPVmbjmbO5vnnk7x46trrkvzbzL1EPzn5+TtJroPnPtNaWK09mTtE8lcz90u+w5lzALsvcwdevhye8a7MbR4eOVlXJ9esZ0r7lPtL5jQ792fufJ+HMndA9oufaZ3PnNXyX2TuF5Nfz9zB27+b5LW9+Tsl/b+f5MZJeZ/I3Mbmr5L8TE450+6U6388c+cFPZ65jde/zJz+p5lf/5zZP2XSeCLnBKWUpZn7Lc5twzC8+dmuFxEREZHFj5oaOSsppayeFgWWUs5P8n9m7lTgPzwjGRMRERGR046f1MhZSSnlv0/yv2TuNOgdmdPSfEvmDuK6Lck3Dc/txGQRERERWWRoFCBnK5/P3HdlvyX/xVN+W+a+t/wLbmhEREREzh78pEZEREREREbNvDQ1pZR3lVLuLqXcV0p5/+nKlIiIyNhxjRQRWTie8yc1k8MS78mcz/jOJDcl+cFhGL7auuf8888fXvCCF0zHutP8xje+UcVOnKht2qlMvbEW87mfrluypN5Ptp53wQUXdMUuuuiiKrZ06dIqRnVO+UmS6fZKkrkzLJ8OtcN559VnXM5S55QOMZ92aNHbr+i6J554ooo9+uijmM5jjz3WFXvqqaeq2Hz7OdUv9Y3e6yj2whe+cF5pU/0++eSTVYzGA12X9NclpT2f+WaWa7/2ta8dHIZhdfUfMhpmXSMvuOCC4cILL3xajObfFrQ+nm5a68R8xkrvWthKez5zEc0btG610qZraW6bpTynG0qb8jjLO8l81keafx9//HFMh+ZwurZ3Xu1tmxa97yRUl3Qv9Z/Wtb1rM9U55ae1Pva243zWzBa97XPkyJHm+jgfTc0bktw3DMMDk8z8XuYOJmpual7wghdky5YtT4utWbOmuq7VcQ4dOlTFHnnkkSrWO2hmWQTmcz/lhybT1uDasGFDFdu0qT7Y901velMVe+c731nFLr300ip2ySWXYNqrV9f9hhZaepGnTdYsE0jvxED127sBbg04Kg9NArRZ2b59exX7whe+gOl86UtfqmI33XRTFXv44YerGPVJymOrzmlCXbFiRRV70YuqA5ixD1FfueqqqzBt6kOUNpVx9+76nLbLLrusiu3duxfTpjnj61//+nOOUR6p/yTcPhT78pe//CA+QMbETGvkhRdemDe84Q1Pi9Hc31p3jh49WsVobuz9ZRPNta1fUnzta7VEkcYFjR+aX2hepusSnndofrryyiur2ObNm6sYrYUvfvGLMW1Kh14+aYy31txpqA2T/nakuYjakWKtvkbtTdfSXHvkyJEqtm3bNkyH5npaX6mMFOv9xVnC9d77SwbqL/TOR2teK52VK1d2XUfvChdffHEV27OHzw+leut916C0aczP8k5C1/7e7/1ec32cz68KLsucq9RJdk5iT6OU8r5Sys2llJsX4jdJIiIii4BnXSNPXR9bvzkVEZE+5rOpoY9Tqi3VMAwfGoZh6zAMW2f5qpmIiMiIedY18tT1cZavmomISM18NjU7k1x+yr83Jqk/KxQRETn3cI0UEVlA5vPRyU1JrimlXJFkV5K/k+TvPtMN3/jGN6rvU9L390hnk/D3Iek7eKTlOHbsWBWj7+rR9/9a0HeOqTy91y1btgzToe8zUh3Rd1VvvPHGKvbGN76xir3uda/DtCmf9H3aaYFrMr/vc7fi9Mz5iPdaQj2K9+ps1q9fX8Xo+7Cta0mH8sADD1QxMhQgjQ99lzfh+qD6pXFHXyWl72S3vlJDY5TqiL4LTGOU6qKVNpWbvvvd+91iuq4lAiZdQKsPyuiZeY2c/n7//v37q2vI/KUFffozH7OLlqCb6P1mBq3NNE5aX1+nONURrVuk2bj66qurGM1XSf8a1bvuUXvNMj/0pt17b4teAyFae6htWtqSljZxGtJb05pAa0dLL9VrUkB1QWnTmtDq06S3oj5Iz6T3QNK6tNZHytPx48erGNVlr8SkNZ6oPJT2M/GcNzXDMHyjlPLjSf40yXlJfnMYhjue6/NERETOFlwjRUQWlnmJXIZh+I9J/uNpyouIiMhZg2ukiMjCsTBG6SIiIiIiIs8TbmpERERERGTULKjH8okTJyqxHokJSbTbupbEaSSWno+gr3U/xeh+Ek/RgWEtEebGjRurGAnrXvnKV3ZdR4YELdEYib97zRBI9NXbhkn/gXC9BhLUDi2TAkqHzBCojFRnW7duxXRIlHrNNddUsc9+9rNV7JZbbqliVMbWIW/U35YvX17FqDxUFzt37qxiLaEnHRRIgmEyCiBzhTvuqKUKrT5NolKaM6jcJAqlPtQSn1K/PHz4MF4r5xbDMFR9lvoRiZBb0NzYK3am8dMaz70HG/ceOk3jvnVIIs3BJES+4oorqhgZEpCQvTWeaR6kuY3qt3c9apmOkFCb0qE6p35Bac9ytiA9s1fcPn0o+0noPYnmbzLSeeihh6rYLGYIdC31A6rz3gPBW+98tBbSeOw92P3gwYNVrDWWyVCD+nRrPE7TOrCXoPWxdehuCz+pERERERGRUeOmRkRERERERo2bGhERERERGTVuakREREREZNS4qRERERERkVGzoO5npZTK3YBchyiWsKsDOSOQKwM5T5DTQsvRoddhiyCHFHJ3ufTSS/H+yy67rIqRk8vatWu77iX3s5YDGblrtNxYpqE6pxjVbcJtQXXZ6xjT69DWupb6GrmhUP9dt24dpkNtRn3jqquuqmLXXnttFbv33nurGDnDJNwWVB8Uozqn+iEnlYTb8ciRI1Vs7969Vezuu++uYuQE1HKJIrcayju5ttAz6XnUhgk7Ox4/fhyvlXOLYRiqOa/XSWsWeh1DiZZjUq97IKVN616vy2DCDlk0/siJi5xFaW7qXesTLnfvuwZdR+89Ca+bva5xlMdeN7XWM6lte12zWg6dFKf6oOtWrVpVxcgRbf/+/Zg29QOa/2mNozxSuWdx+j1w4EAVozVzvs525LLW+17QS2ss0/tmy8W0hZ/UiIiIiIjIqHFTIyIiIiIio8ZNjYiIiIiIjBo3NSIiIiIiMmoW1CjgxIkTlRhtFrE+CdxJZEjiNBLQkcCrlTYJv0hsR+IygvKzYcMGvHbTpk1VjMSRK1asqGIkgCYhWUuMNR+RIUECsVbalA4JVak8vaYALSE7QXlviTinafULEsaRCQT1/ccff7yKkTFEy4Bi27ZtVYyEob11Tu21dOlSTJvyTm1x6NChrntJ9NgSn1IZSUTcay5CddESUZLQtCW+lnOP6fmW5pfWXEtzfa+hB/VXEjHT2Gvls2WW0cPy5curGK1vSbJ+/foqtnLlyq4YzVm9YvtWnOYdmkvIZIbaq5U2zWOUDt1P7UVrZittmgdpHafraC1srRM0N9J7Eq0TDz/8cBWjvtKaqw8ePFjFqI5oDac1geq89f5A7di7DtN1ve9xCZen972t11CjVe5Z3slb+EmNiIiIiIiMGjc1IiIiIiIyatzUiIiIiIjIqHFTIyIiIiIio2ZBjQKSWoREYreWIJCEW2QKQIJAEj/1nlifsHhwy5YtXffTacskGCZxZMKnHpOwjspDwk6q816Dg4TFXCRYo7RnOYW294R6ynuvQLYlWOsVy5EojwR4rXL3iv9IOPjyl7+8itGpw620qV898MADXfkhKO3du3fjtfRMilE7UJ2RkUIr370nhveaX/SaHiQsXp3Pycxy9jAMQzXOac5qrRMk7Kfx02uOQnNOa74kMxISzNM4681ja41au3ZtV35I5E1jnAT8FEv6jVXonYSuo7lkFmMI6gNkgkLp9J4kn/Svhb0GCa22pTi1I+Wd+gX1yVYZKZ/79+/vur/3PbBlkkRjgsY9tTelTeO2NQ9QmxHHjx+vYvTuQ2Oe6iLpN7V4JlxNRURERERk1LipERERERGRUeOmRkRERERERo2bGhERERERGTULahRQSqlETCQMIgFSwoIjEo2ReQCJuUj83zoRdfPmzVWMRFEk8KJnvvGNb6xiLYOE3mcSJEQj4WFLHEYiQ2ozyg8J0ai9WmWhdChG9UOQOLJXBJ/0i+166yfpN0Mg0SKJVKk8VOcJi/jJ/IJMLWiMUhm3bduGaVO/Onz4MF47Ta8AuSXupWupjCRmJDEsXdcaT7P0Nzm3KKVU/YP6WwsSb9NcT/MYzVm0HrXmMRJl05pL+aG0r7766q78JFzu3nFGomqq85aQvdeAqPdEdrq3NX/3rj0UI8MSKmNLyN5rxEPX0XtTa67uNSAiYwjq50eOHOnKY8L1QX2Q8kMxel5rzaO6pGfSeKS1h8YircFJ/7rXa9DUWz/JbIYGLfykRkRERERERo2bGhERERERGTVuakREREREZNS4qRERERERkVGz4EYB04IlEkS1RLYkIqJrSazUe0IrnbLeuvZbvuVbqhiJrB588MEqtnr16irWKjcZGhw6dKiK9QoPSQxO17UgUR8Jv0hcRu3QEqzR/b2ny5K4kvLYKndLnNmTH7q3lQ6J/WlMECT+I+FgS+xJUB3RqcWURxJhUj9NkgMHDlQxEhFT/VCdk2ixJRYmkSyVkaD+S+m0hMU0lnvTlrObUkrVt3vnl9a1vWshjT0a49R/E14fyVyH5sEdO3ZUMVoTWuJiGs8kwKZxSmsMicGPHTuGadMzaV6mGK33VMZWe1Nd0jN7DXvI/KU1h1Kc5mqK9Z5Yn/QbJ1B+et8tW/VL44Tah8YO3Uv12zICof5G63hveSiP1CcTNs2htHuNimZpb8pTy8ih+YyZrhYREREREVlkuKkREREREZFR46ZGRERERERGjZsaEREREREZNQtuFDAtZiRBVUtkS6IqEpJdf/31VYyEVyRgahkFbNq0qYqRwJdEWkuXLq1idALunXfeiWnT/b0nry5btqyKUT22xFhUHqo3akeKkZC9JdQj0wWqNxKx0TN7BXQJi+Ao7ySMo3Ra9dsr9OtNm2iZK6xfv76KkZiR+h8ZALzuda+rYtReSXLXXXdVsXvuuaeKkWiR6mKW07Cpzqm9V61aVcWozvfv31/FWiJMEq/OYtIhZy8nTpzA/j5Ny0ik1xSAxmRLhD8NGdwkydq1a6tYr0EJmQysXLmyiu3atQvvp7FPaweZB1Bd0PzQKgvNG5QfMjOgcU9t2Jrnqa9Q36Bn9oqvW6e5U7kJqote04TWtfT+QvmkMl5yySVVrPX+QfN/7+n2NO7WrFlTxVomSbSm7N27t4pRH6A67zVOat3f28/pOhp3ZDbVitNYfib8pEZEREREREaNmxoRERERERk1bmpERERERGTUuKkREREREZFR46ZGRERERERGzYK6nxErVqzovpYcMsjZidwxXvOa11SxDRs2VLGW+8z9999fxdatW1fFyG2MHGMefPDBKtZyXqPy9LqIkbsX1WPLfYTcPsjhghxael1XWg5k5LpFdUEOKS1Hk17o/l6XKnI+ablhzQeqc6qf1hgj9z6qcxoT1KepD7XG0759+6oYOfe0+uU05NrWupfah1xXyLGIxjw5I7YcW6gPzbevytkBuYPSPE9jPOG+RXME9X9ae8j9qTWmyK3p4osvrmIvfOELqxg5p9H4ueKKKzBtcnGidZjqktY3uq7lUkVtQXVE7UBrQq9jXNLvaEX5ofJQ2rM4M9K7GOWH3h9a/YrSpxilTf2cythyB6V1k55J7zS97dByUzt48GAVo35Jead0qK/1Oti10qa8Uzq9YzGZfx9M/KRGRERERERGjpsaEREREREZNW5qRERERERk1DzrpqaU8pullP2llNtPia0opXyilHLv5CcfGy4iInIW4xopIrI46DEK+O0kv5Lk35wSe3+SG4dh+GAp5f2Tf/90T4I9gukLL7wQ4+vXr69iJHYiwTEJk0n02xJhXnbZZVWMhMQkcFy+fHkVW7NmTRVrCbcOHTpUxUic1isQI1E11UXC9UFptwRv05BArCWOpLRJfNprHkAxEq62riVIOEgxEoomLPakOqJn0r2U75YQkspO6dB4ovKQWJhEgknyspe9rIpRv/zSl75UxY4ePdqVn9Z4ojqiZ5JQmuqHRLctcSOZYmgUMHp+O6dpjZzuX73jPmHjm9558MiRI1Xskksu6bo3YVE1rUckoO6d51vvBb2i7N780HxJBioJzzu0ntHc1mty1DLSoTW714iE2pHWHVrrE14TCOq/1LZ0XcLt01pLe6A+0HoHoPqgctO7D+WR3kFbBhSbN2+uYmS6Q2Y/FJvl3YdMcw4fPlzFaDxSX6N+3lof6dpZTZae9ephGD6VZLpE70lyw+TvNyT53plSFREROQtwjRQRWRw81y3v2mEY9iTJMAx7Sin1xw4TSinvS/K+5PmxtRUREVlkdK2Rp66PrU9URUSkj+d9lzEMw4eGYdg6DMNWNzUiIiJznLo+znJuhIiI1DzXXca+Usr6JJn8rL9MLyIicm7iGikissA816+ffTzJe5N8cPLzYz03XXDBBZXgvvd044RFx5dffnkVIwE/iaxuvvnmKkangyfJ7t27qxj9Zo3EeyROIzFhSxBIAlAS8JH4ioSHx44dq2KXXsrmPJR3ElWTQGzlypVVjIR/LeFrb3kIEvn1Gim00u5NZ5bnUZye2WsoQELGlgiThILUL+k6EiNS3yfRYSuf1F+ofUiE2RI9EiTspD7da5BApz+3hMVkptA6TVtGzcxr5JIlS6rxQmO8NaZIuEsGN9T/aX3csWNHFWsZytD4IUE4meb0mv3QnJOw6Q6Vsfcke0qnZVJAQm8yC6L1muZ0Wt9an+DRXETtSNfRvErrRCvt1rvKNFRG6gOtdZTyRG1L7UN5n8UMgeZwerekPkDzPBnPtPo0lZvqjcYo9eleg4OE27b33Ynql/p0azzR2JmVHkvnf5fks0muK6XsLKX8aOYm6neUUu5N8o7Jv0VERM4pXCNFRBYHz/pJzTAMP9j4r7ef5ryIiIiMCtdIEZHFgcp9EREREREZNW5qRERERERk1Dz3o1mfAydOnKiE4tddd111XeuUVRJVk3CLxM4kBqO0H3zwQUx7/fr1VYyEaHv37q1iJDgj8VRLMEyCLBInUx7pmSTeO3DgAKZNAjPKD11HdU73krgx6T8dmU6+pn5BAlsyLmil3StQ7zUpaKVDQr1e0WNvvpP+k7wp7yT0I+FhS8BPJ5CTIQYJk6mvkrCS5oGkX+RKpyhTnVGfbrU39UuRk0yPaTLNaRmr0Dk3vSYUNE5p7LXGDomYKZ9kKEB5pLK0DE9oTPWKk3uF4y1Bd+8aRTESRdNa2DIdoWtpPaN5kGK0hrfau/fUelpz6d6WIUGv8QG1GfUhuq71DkDloXdT6mv0TkJlaa2PZNxEz+xtM+p/8zWooXrrfWbLnIHqqDXftfCTGhERERERGTVuakREREREZNS4qRERERERkVHjpkZEREREREbNghoFnH/++ZWgkIRBrVPjSfh15MiRKkbiKTrNlQRVW7ZswbR37txZxV7/+td3PZPyTWK31knRJIRcu3ZtFTt27FgV27dvXxWb5WTbZcuWVTESkJJAjIRkJCZvCcFISEnXtoTw0/SKGxMuD4lCqa/2nqqbtAVz01AZSew5i1FA74nAlMfWicDTtMS9NE5IhHnllVdWMepDZJzRqvNDhw5VMaoLKjeZB8wiqKY2a+VTzi1KKVU/pDmQ1rcW1NfJDISE2tT/V69ejenQGrV58+audGjOorm6JUKmOYvmJ3rXoHRofWytUTR2aW3uNa6ZxWyF6oPmeorRfEfrda+pSsLt2LuetMT61Gb0PtVrmjOLOJ7y2fue02vs05r7qV9SudesWdP1TFq3WlDaVJfUh44fP17FyESk1d5E6x2ihZ/UiIiIiIjIqHFTIyIiIiIio8ZNjYiIiIiIjBo3NSIiIiIiMmoW1CjgggsuqIT4JJxtCeNItEYCpv3791cxEkySwJfEXAmfdk7iZBJukdCJBGckyk9Y9EjCQ7qfxG5UF1S+FiQko3ojEwe6rlXndPo0iR7JIKH3NOGWUJ/ap1egS/23JYzrPTm7V/RIadMYS/rFlXQdCWcp362Toul+OjGZ+uXdd99dxUgcSSLrhOuDytgrKqXr6ETohIWvrf4v5xYveMELsn79+qfFaJy0+hbNjbRm9oqQ6ST7lmiX5kYaf2QGQnMwjdGVK1di2jRn0TgjgwQSNtP7Q2se6xX70/xE7UDXUVlaUBkpP9QOVOetdat3/qd3F2rvVhmp/9L99O5D5e41FUq4jFQfvesorc10XeuZ1GZkarF79+4qRmtU672A2pHmB8p7b3vP9x3/mfCTGhERERERGTVuakREREREZNS4qRERERERkVHjpkZEREREREaNmxoRERERERk1C+p+duLEicoRhVxFyPUqYTeVFStWVDFyJCF3FnLHaLkykBNGyzlrGnKEoOeR80PC5VmypN6P7ty5s4qRY8y0w07SdnfpdSohtw4qD5Wl5W5BDm/k2EEOIOSkRemQA03C9UuQUwjd23INasWn6XUFIXeXlotXrxMd9QHqvzR2Zik3uRHSGCWHn+XLl1cxchJKeDxSv6L7qYzU16h+Ei5361o5tzhx4kTV32l9a7n60bxDTmm96wmNiZZ7FN1PY5fSpvmF3JZa5e51aSNXKJpLWq5QBJWb1i2ag6l+aE5vvRfMx6mS8kMxcodLeA6ldyyqH3Irbb1LUX+j8tBcTXmk66ivJfyeQ/2K8kjl7nUwTbhfUjrkxkblpjK2+lWvm1vrnbEn7d5356T/Xeyvr5/pahERERERkUWGmxoRERERERk1bmpERERERGTUuKkREREREZFRs6BGAU888UR27NjxtBiJbEmolLBgiMR/JEyidFavXl3FWiJBEjiSaJiuI3HZoUOHqhgJHhMWHm7ZsqWK7d27t4qRKI8EXmQekLCg68iRI1Xs8OHDVYzql+6l65LkoosuqmLbtm2rYiS43LRpUxWjOm9B9UaiXao3EjKSoC/hPkSCS+pD1NdaYlqC8kljh8SVy5Ytq2KUx1afpmeSEJKMHKhPkqC1NZZJ9Eh5p7a57LLLqtjatWurGJl2JNwPZhFNytnLU089VZnk0FpI4751LZnukDiZ5pzeeShpi62n6Z1zaB6j/CRcHhqTVD+0JlAZW6LoXsMfmouojLSW0ZyTcL3ROtwrtKY1j8TyCc9Za9asqWI0h9K63upXtCZQjOqXzGOofluGMhTvNQAgoT/1C8pjwu9JlA6tJ73jtmVQQ8/sHRP0XkB1cfDgQUy7ZRI2C35SIyIiIiIio8ZNjYiIiIiIjBo3NSIiIiIiMmrc1IiIiIiIyKhZUKMAgoRoLQETnY68cePGKkZiMBI6kfCqJdwiIRqZD5BYf8OGDVWMhP4twRoJIQ8cONCVHzpdluqHnpf0n3hPgm4Sb5PYnvKdsGiMTBNIvEd9iGItQTcJSOnEexKfkoiyJbik+qDykCiU6oL6dEsoSn2a2nHVqlVVjPoQCQdbfZrEoiTuve6666rYPffcU8VuvvnmKtY6DZuEkFQX1DYUIwEotU3CY7lljCLnFqWUagxRv2yZjtD4o3FG91OM5uVZ5hJae2hM0vxCa31rLaK8k+idTEt65+rWXELjudf4YBazIILyRHmnNYHai+ah/fv3Y9pUHmof6gPUT1umLr2n0dN11DbUf1tpE9RmtCbQOkoGB60+Te+hvQYAZBZBa+Ys75tUR9SO1A40FluGRjSWqd6eCT+pERERERGRUeOmRkRERERERo2bGhERERERGTVuakREREREZNQsqFHAMAyVCGnlypXVdS0xIongSEREIqtZxUbTkICvV5jZKy5rCUDpBOlZBKTTUP2S4ULCgrcdO3ZUsZYQvidtqp9W2iQSJDFjr2ixJdIm8fe+ffuqGLUj0RIjkviPBHzUf8n4gE5wpnpMWEBKAvdeUSmdJkxpJNwPaDyRYHjz5s1VjOYREkwmXJc0vilGBglkDkLiyITrcr5zk5wd0PrYeyJ7wn2L5mV6JsVoHqLrEhYI03imtazXdKQ1h9KJ5USvqJ/WDppfEq4PqnNaT3rz05q/e9dcMtzpNQCiPCZcHprzyIBoFkMZMqsgkTnlk9qGrmuZulAd9b6Drl+/vopR27bmfurr9O5D77r0TrJmzZoq1uo/VG5616Dy0Dso1W/LKIDSbvWNFn5SIyIiIiIio8ZNjYiIiIiIjBo3NSIiIiIiMmrc1IiIiIiIyKhZUIXqi170orz0pS99WozESi1hEImGSTRJAjESp5FIi8RPCQu66ZkkqCLBMYmLW4JHqg8SZR85cqSKkWCN8kiCvoTrg8Rp999/fxUjYT0JyV7ykpdg2lQeEpiREJLEp1u2bOnKYytO/Yrq4uDBg133JixcpGeS4J6Eg9QvWqI8ql8SGZKon8R/VJbWCdnUr8h8gPrvd3/3d3el/a//9b/GtKkuySiDriNTCjIkoDHWiveKduXs5oILLsimTZueFqOx1+ovNKZImE/9msYezVkt4w8yYek9Db7XXKc1h1J9kMCcxinNl7Tetkx46B2A3hXoflq3qM5I5J2wMJ8E5rQeUf2uXbu2irVMCuh9obcdetey1jNpDqX5n55JabfaluLUB2mM0nst5ZvGTdKuj2mofl/xildUMXoHoLWs9UyaH8gs4vjx41Ws1/Ap4XfyWddHP6kREREREZFR46ZGRERERERGjZsaEREREREZNc+6qSmlXF5K+fNSyp2llDtKKT8xia8opXyilHLv5GcteBERETlLcX0UEVk89BgFfCPJPx6G4dZSyiVJbimlfCLJDye5cRiGD5ZS3p/k/Ul+etYMtITEvZAIicRyJMAjkdbq1asxHbq2N20SP5FgbefOnZg2iRF37dpVxagu6ToSg7fE+iT82rFjRxUj4SGJ5Uj0dcstt2DaVL+UDuWRoPxQ3bbSJmE9if9IaEcmFwn3DRKq9l5H4tOW2JPySddS3yfhIMVaaVN5emPUf9/97ndXMRJwJslXvvKVKkbzw+7du7ti86WVTxkFp3V9nO4LJPRv9ReKk5i3V0BNz6M5I+GxT8+kuYRE3rROtExdaF4ncTylTeOZ5hwyb0nYkIYE/LRGkXib5vS7774b0yYhO61RZJBA7wqzrI+t0+inefDBB6sYmTOQWUTC/YrmalpnKNbbT5N+wwfqq/QeSG3bEszTtZQO9VVqs5e97GVVjPpuwiZWVB7q09TXqIyU72Q2Y5QWz7qaDsOwZxiGWyd/fzjJnUkuS/KeJDdMLrshyffOlLKIiMiIcX0UEVk8zPQrwlLKliSvSfL5JGuHYdiTzE3sSdh3UERE5CzH9VFE5MzSvakppVyc5PeT/KNhGPq+7zN33/tKKTeXUm6mj8JFRETGjOujiMiZp2tTU0p5QeYm7N8dhuEPJuF9pZT1k/9fnwRP8hmG4UPDMGwdhmFr66AhERGRMeL6KCKyOOhxPytJfiPJncMw/PNT/uvjSd47+ft7k3zs9GdPRERkceL6KCKyeOhxP3tLkr+f5CullNsmsZ9J8sEkHyml/GiSh5J8/3PJAP12ihwmEnaEIKcHctcgtwVKm9JI2P2BXB3IEYLcUOirBuSk1Uqb3F3IRYZcW6666qoqRo4XSbJmTf1VcKqjhx9+uIrde++9VYzcR6h8rTg5r1GdU/1SWVp1TuUhZw+6nxzINmzYgOls3769ilGfJnc6csujtlm/fj2mTfVG7nLkPkIONBdffHEVa7m+vfCFL6xiVO5Vq1Z1pb1u3boq9rrXvQ7Tpr7x0EMPVbFed6JZ3Fmo/+t+NmpO6/o4vabQmJilv9BYoTmL1ke6l/pvwms2XdvrjkRjrzXOaEz2OkhSjOacbdu2YdrkBkf5PHDgQBWjNZfapvW1xN73Akp7//76g0Oaq1suVeR+RuseQfkmp7GE52XqV9RmtJZRX2utzfQ+RfmkMUr3kttYy3mN+hD1DZoLaB2md93rrruuO21676IxSuWmMrbKTeVp9cEWz3r1MAx/lYTf/JK3z5SaiIjIWYLro4jI4sFfEYqIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIya2RQ486SUUokPSTz1yCOP4P0kYCIREd1P15ForAWJ20ggRuIpEtCREJ1E/QkLBVevXl3FLrrooipGYnCCzAwSFh6SgJTahkRf9913XxVrWZmSqJQgcRrVOYlHW2lTnNrhyJEjVYxE63fffTem8+IXv7iKkeiW+hpBfbo1nkhISQK+W2+9tYpRH6C03/jGN2Lal19+eVeM5gfqa2Q8cPXVV2Pa+/btq2IknO3t07OI/6mOWsYocm6xZMmSaj6YxVil10inV4TcK+BP+s0L6JlUHlqvSQCdsGidBN1Lly6tYlRnlE7LQIjmVlqPqNxU52Qe0KpbWttpvqQYzTm0vrWMXihPVG6qN5p/W4Y9FO+t314zm5ZonUwKKB0qI+WR+vSWLVswbXqHIDMEGjtUZzSPXHHFFZg2vQtSv6S0KR2qs5b4n9qC6vKZ8JMaEREREREZNW5qRERERERk1LipERERERGRUeOmRkRERERERs2CGgWcOHGiEhqSaLEliibxH91PwiIStpHAsCWqJlEUpbNr164q1iswn+Vkcso75WfZsmVV7J577qliZDKQsJCNxFxUP3SSMQm6Zyk3tU+vGJYEcC0RJuW9tw9QOlTuJPnKV75SxUjg/uCDD1axXkHg/fffj2l//vOfr2Ik4PvJn/zJKvbLv/zLVYzG5yte8QpMm+pozZo1VYxOMqYToKl+W3W+adOmKvalL32pivWKaWcxHKFrW6e0y7nH9LxFwvyWuQn1994TvnvNKuZ7EjgZ5NA8RmLy1on1lCdaEyhGQngSmK9cuRLTpragdqAxTu8ABM05CZebzAPofmoveh7VRcL9hUT4tGZSflrvXWRURG1Gov61a9dWMSrPbbfdhmk/8MADVYyMfd71rndVsY9//ONVjMZia43qXRPoOnrno/e71ns2vX/QeKR3XaLX5Cjh97bWnNPCT2pERERERGTUuKkREREREZFR46ZGRERERERGjZsaEREREREZNQtqFFBKqURDJFhrCeN6Rbq9wiQSMrZEv72nK5OYkUT9dEJr6+RUEreRuJLKQ4J3SrslxvrqV79axUh0RoLwXsF7q71JNEbCuF7TBBKyz2IMQaJQyvvy5curGJ1Yn7DwkESY1LaXXHJJFbvjjjuq2Gc+8xlM+8orr6xiq1evrmKf/vSnq9irX/3qKkZizVlOw+4Ve7b6yzTU3gkbEpD4tNcAYBahf69AV849hmGo5i1ay0hsn/B8SesE9UHqw7Oc5N0rCKc1k068n2WdoHFOYmkqN62FNNeSoUvCp7zTafA0v9B1tF7PskYR1I5PPPFEFaN5qDV/07XUDvQ+RO8PZByT8BxMBgtUl9Sn77vvvirWMgq45pprqtj69eurGBnx0Pp48803V7FZjIpo3G/evLmKUb/ofX9NuN7oXYPeS+leau/WmjcfE5OT+EmNiIiIiIiMGjc1IiIiIiIyatzUiIiIiIjIqHFTIyIiIiIio2ZBjQKeeuqpSuxE4kYSsSUsIiIBFIkje2mJ73pFeSS+olNjN27cWMW2bduGzyQBHpWRBIEkeiThVctcoffU4ptuuqmKkUCMRP2tuiXRGfUNqgtKh6D+13omnZhMokUSvr7kJS/BdEgQe9VVV3U9k/K+ffv2KtY6gXzTpk1VbOvWrVVsy5YtVeyuu+6qYiSibNUvjVvqv2SwQKJbEhG35gHq60uXLu26n8ZT76ntSVsYKnLixImqH9Pc2Jove4X9vYJw6v+t8Uz0ipNJcExmKy3BPK0zNEf0rnu0xrTqltZCWu8p7YMHD1YxapvWXEJ5ojWTYr3rCbVNK07pkFEA5ZvaK+H1lcwZqB1IRE/rI9VFwn2Q1kIyntm3b1/X81pt2/sOS32Vxh2tjy1zhpaBwDRkXEDpUL9ovW9Sv2rtB1q4woqIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIwaNzUiIiIiIjJqzrhRAIma5iuM631m70m7CQu3SOxEJ8RTfkh0/tKXvhTTplOPSdTXKxAjsXMLKiPVBaXTK8ycpb1nOfW4Jz+t9qZ8Hj58uIqRKJSEdocOHcJ0Vq9eXcWoLqncJKK//vrrqxidopwk73jHO6oYCTbvvffeKrZjx44qRuYX1M8TPqGYhMB0P7UZtUNLjEjXUh+iduwVY89iCEDjVs49hmHAsd8LzRE018/nJPqWAUvvOty7FtI62hKTkyib5hIyFKBxSsJxKl8yv3WP7qW5rWXO0Guy1GumRPe2RPRUb7TG9RoftETry5Ytq2JUv1dffXUVo766YsWKKtYyQyDDHlq3du3aVcUOHDhQxWitJ5OBhOudxiONZWpH6vtUloT7OvU1ivXe26LXgOKZ8JMaEREREREZNW5qRERERERk1LipERERERGRUeOmRkRERERERo2bGhERERERGTUL6n6W9DkhtNyAet2wyP2h97peZ5hWftatW1fFyIGGnE/Wr1+P6ZCr1M0331zFyNWJXE7IFaTlLENOI9SGVBdUbmrbllMUtQWVh9q21wFvFucpKjc9k5xuyMEuSV7ykpdUMWrHF73oRVXsuuuuq2LkmvKa17wG06b2ufPOO6vYXXfdVcXWrl1bxS6//PIq1nKXo/jx48er2MqVK6sY9RfqF9R3E3axe+ihh6pYrxMVlaXVp8nJpeXSJucWwzBU8xG5AbXWKOqvLYejaagPU6w1pgi6lhygyP2M5lWaA5PkZS97WRXbtm1bFeudv8n1sDVGaS3tbQeaC44ePdqVx1baNKdTO9J8SWthq72pLchxjtYyynfLHZTeiSjvGzZsqGLkLLZ06dIq1iojjT1ax3fv3l3FqNybN2+uYq318ciRI1WM1lyi1z215SpG9UFrZq+rGZWx5cBLc9uFF17Ylc5J/KRGRERERERGjZsaEREREREZNW5qRERERERk1LipERERERGRUbOgRgHDMKCgnK4jekX8lAaJmnoNBVqQYG3fvn1VjIROK1asqGLHjh3DdK644ooq9j3f8z1V7HOf+1zXM0mkRQLzhMVkVJdUF73t0BKNkVCvV+zZayjQEsuR0JuupRiV58UvfjGmQ+Uh4eyuXbuq2Bve8IYqdu2111axO+64A9P+0pe+VMUOHDhQxUhwuWXLlip20UUXVTESZiYsiCUxLglsKR1qr9Y8QmOU6oKErwT1Aeq7CY+JWcxJ5OyllFLNW71GLQmvZwcPHqxi1F9pbqS0aV5txWkeJMExjQmaX/bv349pk5kImaPce++9Vezhhx+uYlQXZGKSsGCe2ofE8TRHUD225gcSo1Mf6F3D6T2lZZBAfYPmYOoD9MxZDGWob5BY/1WvelUVozonI5yE100S4S9fvryKUZ+k9mq9dxH0XkDloXRmMUmitXnPnj1dz6S0qf+20u41H3gm/KRGRERERERGjZsaEREREREZNW5qRERERERk1LipERERERGRUXPGjQJIMNQSC/WKiHpFi0TLKIBEwySC7j2FnMRYrZNt6Zl0ivJ3fud3VjESONKJyV/4whcwbTrZltqsV5xGotCWeQSJxHvF272GD63rek+t7z1NvtV3SYBH4tPrr7++it1yyy1VjAwoqK8lyZVXXlnFyJSChPkE9YvWSdHUjnTiMokwe09Jb4kwH3rooSq2c+fOKkZzBvWX3tPYW7TEuHJuMQxD1b9o3qD5O+F1gkTivXM1Xdeax2jtIuE5jQsyDyABdGuc3HnnnVXsJS95SRV77WtfW8VofaS54O6778a0Ccp776nqJAZvvRfQvEztSLFeI5xWe1MZe+dLWu9b701kDrFs2bIqRqYAZB5Aa0LrnYLe71avXl3FyASI6of6ObVDKx3q/9RfLr300q50WnVO9dFr7NNrQtIyxSJ636lP4ic1IiIiIiIyatzUiIiIiIjIqHFTIyIiIiIio+ZZNzWllAtLKV8opXyplHJHKeXnJvEVpZRPlFLunfysv8gnIiJyluL6KCKyeOhRzz+e5NuHYXiklPKCJH9VSvnjJP91khuHYfhgKeX9Sd6f5KdnzQAJ0VrCcYLEyb2nyROt60gURYIqyjsJ+kgo1Tp9nZ754IMPVjESc9HpuyS0/q7v+i5Mm0SpdCI7XUdCPRJmkoAu6Rc49hpIkJCxdS9dSwJ+EnGSUI8EfQmfaE0CW+oDJKKnPnT55Zdj2rt27apilE9qHxL107gj0W3CQt5169ZVMRIe0pinvtI6iZv6JYkR6X5Kp9eEJOE6ap2uLKPgtK6P0/1jlr5Bwn7qb73rK4mdW2Oqd82lGK1He/furWI0PyS8vpIZyIEDB6oYCbI3bdpUxVpzKM1PtMbR/ELXUdvQGpH0n9RO1/XOWS2RNqVDazOVh4T1Lei9gvL+2GOPVTEyZ1i1alV3fu65556u/NB7F/UXMjhovX/QOk59jeqi17Ch9a5L5gxksNC7DhM0VyXcX1pzTotn/aRmmOPk2/sLJn+GJO9JcsMkfkOS750pZRERkRHj+igisnjo0tSUUs4rpdyWZH+STwzD8Pkka4dh2JMkk59rnrdcioiILEJcH0VEFgddm5phGJ4ahuHVSTYmeUMp5eW9CZRS3ldKubmUcvMsXysTERFZ7Jyu9bF1HomIiPQxk/vZMAxHk3wyybuS7CulrE+Syc/6i3hz93xoGIatwzBsneW75yIiImNhvutj63vmIiLSx7PuMkopq5M8OQzD0VLKi5J8R5JfSPLxJO9N8sHJz489lwy0TlQ93fQKmOYLCa17RVYtwXzvycx0Oj2d6E4itrVr12LaJAAl84EjR47g/T20TpelT/aoLkjM2CtkbPWLXhOINWvqb5WQqURLEEjpk7ieBIrUjlRGElEmLFyktqD2pvqlPnnNNddg2iTupfqluqQ+SdeRMDhhkw3KO5WRYiTgbH0qTddSeWQcnO71cbrfzPLtht5NEf1ykUTrJKCm/pvwPEbXtgxTpqH1iPKYcHkoHZpDe41eyCQmYREzzW1UFzRX967rCfcNSufgwYNdaVMZW3MTrbnUB2iNmUX4Te1Iae/YsaMrP1Q/rXHz8pfXH7hSXa5cubKKUZ+kNar1/ksmHXQ/vQ9RGek6KksrTn2N1sJeoT/18xaz7hF6PjpZn+SGUsp5mftk5yPDMPxRKeWzST5SSvnRJA8l+f6ZUhYRERk3ro8iIouEZ93UDMPw5SSvgfihJG9/PjIlIiKy2HF9FBFZPCzMd79ERERERESeJ9zUiIiIiIjIqFlQO7JhGLqEjy0xIomt5yOyJSFZ6wTn3hNZSYy4YsWKKtYrdm7liZ5JAkcSftMJxa1y9wrCSbxH11GdkbAy4fYm0Rld13u68SxCPbqWThOm61r9lAR8JF6leiOBI/WL1ngiNmzY0JVOb/2SUDThci9fvvw5p019jU5GTpK77rqripGZR+980ytIbd0vksz1t2mDklnWqN6TxGmskEi8ZW5C9JqwUP9ft25dFaN5nk5ZT3jtoXmH8kP3kmEPzQ8JmynQmkvrCbUDpdNaH2kdp/K03it68tOar6jcBNUF9bWWWJ/iZOJzySWXVDHqQ9S2tBYl/cJ86vt0L9UvvbO10qH+T/2Kyk2xlgHF7t27qxjNBWRARP1lFmOI03Hsi5/UiIiIiIjIqHFTIyIiIiIio8ZNjYiIiIiIjBo3NSIiIiIiMmrc1IiIiIiIyKhZUPezUkrTbepUyKUk6XeV6nXDmiVtcuwgNwtyriIXJnI0IfeahMtIrlvkfLJ169YqduTIkSrWctQhdw5KZ+fOnVVs3759+MxpyPUq4TKSOwY5gNB11LatftHrlEYuJZQOOYW07ifHGHLT2rt3bxXbvHlzFet1qknYfYfSpjJedtllVYzGSMJuNZQO9TXqkzTuDh48iGlTGXtdg2ZxciF6HaHk3KOUUvU5Gj/zdeik9ZHGHsVa8yWtj71ORrQ+0rzYWh+pPOSQRXMEOa+Rg2nLIYvcuShG7UhrQq8LY+t+KiO1I/Wh3r6ScP3S/bT20BxK+W6lT/M6ud0dOHCgilFdUN9t5bPXvY/6wPr166tYq9y09lDf6HVUI6e848ePY9rUr+h+qgsqT289JjzGZ3FvTfykRkRERERERo6bGhERERERGTVuakREREREZNS4qRERERERkVGzoEYBSS00JMFar6i/xazColMh0XnCgiwSNdH9JJ6i61oiZKoPEmGSsP7mm2+uYiQEI3FZkhw6dKiKkQDv8OHDVWzlypVVjMSELUFpSxA7Ta8xBInvWmnTM1t9oyftWdIhyHSB+h/FWiLXNWvWVDHqGytWrKhil19+eRWjMrZMIHrFytSHSGS4a9euKvbpT38a06ZxQn2jt1/RuJ1F1DyLkYOcvZw4caISA1Nfb81DLZObaWicUTrU11v9mubq+cxPdF3LbIXGFIn9SRhNpiy0XrfGKAnCe81fSNxOtNZBKjfNwb3t3ZtGC+ov1Fd7TWISFqjT/WRURGsPGcK01uaLL764ilHbUt43bNhQxagsrbWZ+ir1g1WrVlUxelclU6HbbrutO21qW0qnt0+2+hWNp1mNdPykRkRERERERo2bGhERERERGTVuakREREREZNS4qRERERERkVGz4EYB05AIqFcgPssze80DWmmTcJEEUCSeuuiii7rubYnGSMRPYn3KI52+S+m0Tl8ngWMrn9M8+OCDVWyWE7JJnEZCMhJq956Y3BLXUh+iGJWnNz8J1+/SpUurGNU55YfasSVy7RUWkzCT+jQZD7QEgXSKM+WT6o0Ew1/+8per2O23345pk1EAzQ80RmmMUTuQ8UALOilazj2GYaiEzDQHtoSzvQY7NO6pX89i2EP3Uzq9azvNi601nOL79+/vSofmbyo35Sfh8tD8TdfRXE11RqYHCYveid53LKqL1txEddQrEqe+0uoXVHZaj2jNpXWC6rfVz6kde8tN0LtLC1rv6X5qH6rz+++/v4rt3r0b037kkUeqWO8a12vE0DIcIVoGWi38pEZEREREREaNmxoRERERERk1bmpERERERGTUuKkREREREZFRs+BGAdNCKxJuzSKE7BU79woUWwJfOmWYTsvtFUD1nr6bsOCeriVRHeWn90T1hEVevWLG3hOpSaDYSptEeb1CyN4T4lvP7BW+krCtZa5A1/YKeanOqR3p1OEWL3/5y6vYVVddVcWo3qhftUwKqDzUp0kETCce33fffVWMTnBuPbP3RHUqz+bNm6sYjdmkX/gq5x6llGr89hrcJPMT5tP6RvPvihUruvND45ny2Dsvt9b6ffv2VTESLNN8QGnTnNxa13vNY1qn1k/Ta3CTsHCcRN69awzVxSz9j+gt9yzvH9S2VOc011L/bfVpqo/LLrusitH6Sv2F8t1rupT0C+6PHDlSxXbs2FHFDh06hOlQXdJYpvxQbMOGDVWM1vDW/bOY7iR+UiMiIiIiIiPHTY2IiIiIiIwaNzUiIiIiIjJq3NSIiIiIiMioWXCjgGlmEQS2DASmIYFXr6FAS1xMojx6Zq8wjmidEExiPao3EnuSSJBOoW0J5knETO1AAmpKe5b6ofKQkLL3pN3e/tNKh/JOQr/eE4aT5KKLLupKu/fEbmqvVp2vW7euilHe16xZU8VIOEgCxVbaJP570YteVMWoX9IYJSFk6yTuTZs2VbE9e/ZUMepX1F503XXXXYdp0xg/fPgwXivnHq15+FRaJ5PTOkH9rddshZ63f/9+TJvGBc2NNB/QPE9zW8tQhqD5qXf+p7WjJVbunbMo1nsafEtM3mtmQ3mn9YTW61ad9ZrhUIzWt1YZqd6oTy9durSKUX/pfZdq5Yn6KvUBqjdat6gPtPJE457qktKmtbD1Trx8+fIq9thjj1UxmkdoHqC+1jIvojy1TAVa+EmNiIiIiIiMGjc1IiIiIiIyatzUiIiIiIjIqHFTIyIiIiIio8ZNjYiIiIiIjJoFdT8rpVSuDuR20HKjoGvJ6WEWl6tpyL0hYVcScp4gdw1yiaB7W+5nVG5yo7j44ourGLlekFtHy1Gnt9x0P9UF5bvVXpQO9Y1etzHKD6XRylOvU98s7mf0TMonuc1cffXVVYzcWVocOnSoir3sZS/rSpvam65bu3Ytpj1LH5zmgQceqGLkdvSmN70J7//iF79Yxcgph9qWxuju3burGDm+JNzfWn1Qzi2WLFlSjYve+SFhlytycKI1geY7Gs80zhIeK71uWr1Onq25jdKmMlK90fpGTp6tclN5el3aaI7onQMTrg96B6B26HUmbfU1mr8pRvf3urG17n/kkUeqGK1ll19+eRXr7edJcvTo0Sq2ZcsWvLYnHXr3IQfShPtbyyFuml27dnXl56qrrsL777rrripGzm297xo0FltloX7QcjFt4Sc1IiIiIiIyatzUiIiIiIjIqHFTIyIiIiIio8ZNjYiIiIiIjJoFNQoYhgFFfb30CrXpupYQrRcS/5HYicR2BAm3WmJESpvEdr3XUdotQSAJFzdv3lzFtm3bVsW+9rWvVbH5Cl8p7yTeno+hQNIv1KP2pny32pbyuWrVqq506JlUFy1RXq+Ql6DxdMkll3Q/j9p8z549VYxEgnv37q1iO3furGLUJxMWOPb2l17ThN55INEoQOYYhqHqc9QvZxHZEtRfaa4m05xeEXwrP5Q2jTMqd8vE58CBA1WM8klzCeWxV9zeup/yefDgQby/594WNG+QWJ9E3gTNba25ifog1VHvu9gs72fr16+vYseOHatiNAdTv1ixYgWm02u8Qe+gS5cu7bquBY1HKg/FqJ9T/dB620qb1ky6juqMzCta/arXhOqZ8JMaEREREREZNW5qRERERERk1LipERERERGRUdO9qSmlnFdK+WIp5Y8m/15RSvlEKeXeyc9Ln79sioiILE5cH0VEzjyzqOd/IsmdSU4qoN6f5MZhGD5YSnn/5N8//UwPKKWgcGya1jWznHj7XGkJIXsFYr1CJxLltdKmdChGdUF12TpBlyABH51Y22sAQG3Yam8Swh8/fryK9RofUJ21BIqUJ2pHEgRSfloiweXLl1cxMgo4cuRIFaMTjymPLfEpnShMpzU/9NBDVYwEgSTgp7IkbCqwbNmyKnb33XdXsTvuuKOKkRC3JdYn4SL1A2qb3hPEW+1NY4+u3bFjB94vi5Z5r49Lliyp1hmaA1vzZa8QmcYuifUp1hL49p4E3mtkQtfR3J/0C6hpHqQy9s4PCZ8ST8L83jqncrfmb5pbSbxNcy2lQ32t1aeozSifFOuti6T//Y76Ja0JK1eurGKtMm7cuLGKUf32rglkaLFlyxZM+8UvfnEVozqiZ95///1VjPLd4tJL69+/UN+g/kdGFVS/LeMNYpZrk85PakopG5P8jSS/fkr4PUlumPz9hiTfO1PKIiIiI8f1UURkcdD79bNfTPJTSU7dcq0dhmFPkkx+rqEbSynvK6XcXEq5eZZPCEREREbAL+Y0rI9kmyoiIv0866amlPLuJPuHYbjluSQwDMOHhmHYOgzD1lk/RhIREVmsnM71cdbzGERE5On0aGrekuR7SinfneTCJEtLKb+TZF8pZf0wDHtKKeuT7H8+MyoiIrLIcH0UEVkkPOumZhiGDyT5QJKUUt6W5CeHYfh7pZT/Pcl7k3xw8vNjz/asCy+8MNddd93TYiToa52Y3Cs4ot94kdCPxGWtT5NIDEZfp6N0SNBNZSShdMLCw89+9rNVjIRxJPAicWPrqw+UTxJSkiBw3759VYxOtm2dOk9CU2ofasdekWtLdEvpUP8jQV9vv0jYaIBEfatXr65i1N7UjiQmTHicUHmojshQ4Nprr+16XsJ1SeJV6gM0TkgM2zIKOHz4cFd+yPiA+lDv3NJKZ5bTtGVxcTrXx/POO68yp6CxN8v6SELr3pPfe9NoxWn80Rin+b91yjtB8y2JpWndo3WCnkfzXcLrHo3nXvMYqrNZTEcI6gOtPtR7Hb1X0HsBtSPlm/pF61pazyifVJe0nuzZswfTpnFy9dVXV7He+Xv9+vVdaST944T6Bq2F9C5Gov6E10eqt16DHIpRX2ldO+v6OJ9zaj6Y5B2llHuTvGPybxERkXMd10cRkQVmpi3QMAyfTPLJyd8PJXn76c+SiIjIuHB9FBE5s8znkxoREREREZEzjpsaEREREREZNQuqUP3617+eu+6662mxXuFt0j51dhoSVPWKyVvi4l4BVO/pxiTM7D0ROmFBOAm3SGhHAvFv+7Zvw3QefPDBKrZ9+/YqRiJMKg8JB3fu3Ilpk4iOykP1S+3da/bQggT8lM7mzZurGIn6W/FpM42E25ba4Yorrui6N2ERPwkuqR0oRuLR1lgmMeJXvvKVKvaxj9X66jvvvLOKkQFFaywTvWOUYtSHWuYXlE7vvCZnN9/4xjeqcUFiXurrCfcjitH8T3ME3UuC4YTnRhI79wqBaW5qjWfKO43T1jzYcy8JxBMWrR86dKiKURkpHRJQ09raembviffzNSehvNM7yZEjR6oYvQPQetCKUx1R36C22bBhQxVrWanT2CPThd62pXtbhjI09sjQ4HOf+1wVI4Ob3vfFhNezXsMSeiaN5VbavQZCz4Sf1IiIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIwaNzUiIiIiIjJqFvwo62lRFQmlZhHMk0Cs94RvEj+R2LmVJxIwUdp06vCll15axVpCSBJl79+/v4odPXoU75+G8vjZz34Wr12zZk0VW7duXRWjvFN+qB1ap+qSuI1EffMRTLaEepQ29Q0Sce7YsaOKtU5mppN+qd6ozqncJOS99tprMW0SYVJ5qC6o3ijWEhbT2CEh5bvf/e4q9q3f+q1VjE78bgnw77777ipGhg3btm2rYlQ/vSYkCZdRowBJ5uan6TFNY6+1PlI/pP5G694spjkEiaopn72i9d7nte6n+YXmot76IXOSVj5pjeqt35ZonXj44YerGNVR75pLdTELtMZRO5AxUMsMgeZ1upbE6NSOBN2b9LcZlZHMEOh5rT5N457K89rXvraKUb8g84pW/dx7771dz6QY9ave99KEx/KsphZ+UiMiIiIiIqPGTY2IiIiIiIwaNzUiIiIiIjJq3NSIiIiIiMiocVMjIiIiIiKjZkHdz4ZhqFwdWm5jrfunIRex66+/voqRU8MXv/jFKtZyACFXB3IqoTySkwU5gLRcHshdg5755JNPVjEqD13XcrohJ4zNmzdXsUsuuaSKUXmoHVoOZHT/8ePH8dppeh1+yI2nlSeqc+oXlEdyH0nYJYWeuWvXrq7raDyRg0zCbjXUN5YvX17FqF9RXZKrWJLccccdVewrX/lKFbv55purGLmpzOLURH1j/fr1VWzr1q1VjJx3qG1azjJXXnllFSPnQZof5OxmGIaqH9PcP4sLGI1TclKksUsuga01qtf1k+YiWhNoHmqNKaqjJ554Aq+dpteNrQWlvXTp0ipGeacyzuJ2Rxw5cqQrbWobis3iiEaOo+Q4R3VGbq4Jr8PkVkZrO62PdC/lJ+G80zpDay7VRa8Db5I88MADVYzWGVonevPdGiOUd3pPoffsY8eOdcVa7/2rV6+uYvQO+kz4SY2IiIiIiIwaNzUiIiIiIjJq3NSIiIiIiMiocVMjIiIiIiKjZkGNApYsWVKJk1etWlVd1xJukUCYYrfccksVI/ETCaVbguNeET6JrygdEoiRIDthcTHFqN7+/M//vIrt2LGjipGorhUn4RaVh0SYJFKdRQhJYrveGLVXy6SA8k75pP7SK1pMkm/91m+tYn/xF39Rxah+SWxH6ZAQN2GTDYJMDpYtW1bFyCBhz549+EwyBbj88sur2MqVK6sYmQyQYJKEjEly1113VTEaE7t3765i1F+oX7z+9a/HtHuFr3LuQUY6NM5a0JxFMRKT0xxx8cUXV7FZ1sdeQxoSqNMc+qIXvQjTvuqqq6rYmjVrqhi9A5AZwoEDB6rYLOYB+/btq2I0R9B6RLHW/E3zBq0T9E5Cawe1TctIh/JJ/Ypi9J5CbZMk1113XRW7//77qxjVRW/9tPp0r0kCmTuQ4J1oGQg9+OCDVWzt2rVVjOYHMhkgIwZ6F0vY3IfWdlozyTyL+j6997eunXV99JMaEREREREZNW5qRERERERk1LipERERERGRUeOmRkRERERERs2CGgUMw1AJgWYRrZPIi8RcJDIkYRyJkki0mCRbtmypYnRyK4m0vumbvqmKkSj6ox/9KKb9V3/1V1Xsk5/8ZBUjwRuJDEn02BKkvvSlL61iX/jCF6oY1SWVcdu2bV15TLgfUN6pvUmQ3Sv+b0F9je7v7adJ8ulPf7rrfuqXJPSfRWhHBhZUl3QdCfipHam9Exb3PvTQQ1XsS1/6UhXbu3dvFSMxLF2XJN/xHd9RxbZv317FqNy33XZbFTt8+HAVu+mmmzBtattZ+qCcvSxZsqQa54899lh1XUtUTX2LhLstwf00vSYoCZsKUN5JOL5p06YqRqY5t956K6ZNZkE0TinvdC+Ne4olLLYmITzVJdUZmRTQiewJGzH05p3ehyg/Lejdh8pNdU7rcMuIgeqD1jPKO8Uoj7OYcVCd07ijMUZ9oGWks2HDhipG6wzdT0YV1M9b7ySvfOUrqxi1A0HXUXu3yk11SUYMz4Sf1IiIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIwaNzUiIiIiIjJqFtQoIKlFsSQGbwlnKU4nt5Kw6JFHHqliJEoiIVnCouPXvva1VYwEx5/5zGeqGIm0Wqf3kpCNytgSkE5DIkyqnyT54he/WMVI8EaidXommQe0IDEiCcIJ6iu9pzq36DUKIHFkK9/UZiTCp3FC91KfvuSSSzBtql8SvlKbkQCZnnfllVdi2r/2a79WxWjs0Jgg047XvOY1Veyzn/0spv17v/d7VYyMJYirr766in3nd35nFdu5cyfe/+d//udVTKMASeb64PS8TutRq7/Q/EQGI9TX6V66rmUUQPlcv359FSPzABIN33vvvVWsJdYnkTkJ4ek6embv3Ja0zUimoTWc1lFam1vvBdQWlHdaEyhGwvrWukWCeeovVMZec51WOlRH1H+pD9C9rfWRxg6tzfQO2mtKRIYACRtB7dq1q4pR/VK5r7nmmir24IMPYtp/8Rd/UcXInIHKs3Tp0ipGpkCt983777+/ivWuzSfxkxoRERERERk1bmpERERERGTUuKkREREREZFR46ZGRERERERGTZlVhDMfLr744uHVr37102IksmqJ70gUReK/3uvo1NeXvexlmDaJ/XsFb3Rdr2gxYaEUCbJIIHb99ddXsT/4gz+oYi0xIuWTRKF0UjS1Awnejx8/jmmTEJLyQ/VDAkMSE7aEr5QOCQdJrE/PbAkhSZxJ5SEjBnrm2rVrqxiJBBMW3L/1rW+tYtddd10Vo3J/7nOfq2ItwTzVJYk4f+mXfqmKkdiYYvS8JJmeg5LkoYceqmJkXED9gsY39f0k+eZv/uYqRmP5V3/1V28ZhmErPkTOSpYtWza86U1vmo5V17VEttQPaU2g62hepjXhsssuw7S3bdtWxY4dO1bFaO2geYzyTXmcBapLmi9vueWWKtYSzJOAmspIbUYxWrdobkt4PaM5j9YYmseofh5++GFMm9ZsWrcOHTpUxcjkiMqd8DpB70n0Hkn3knkFxZJk48aNVYyMbyhtWh8feOCBKtYayzQmqM1uvPHGKnb06NGuWOt9c/PmzVWMjDIo72S6QP23te8gUwGqi9/93d9tro9+UiMiIiIiIqPGTY2IiIiIiIwaNzUiIiIiIjJq3NSIiIiIiMioqZVHzzPTImoSEs9yyjuJHkkg9trXvraK3XTTTVXsC1/4AqZDYiUShPeeWk9CSBKcJXziMgn4SOT9qU99qorRqfEk9E+43CQ8v+2226rYK1/5yir2pS99qYq1TvQlMSLVOYmySeRKQtPW6dwkypvPdSQoTViASiI6MrUgoR/VJQlXk+RVr3pVFSNjCeq/vUJROiE44fahtn3nO99ZxWjsfPjDH65irVPA77nnnip28ODBKvYt3/ItVezWW2+tYiTCpDkoSf7yL/+yirVMJOTcopRSzVEkxm2tj71zI506v2nTpipG4v/WeKZ5rGWWMQ3Ny5TH1hxK6yONPzJbofKQYL4lZKf1g4TnVJckOqf3odZcQmJ0qnNqG6pfmpPJZKD1TKojyjulQ2YpCa8p1P+pb6xYsaKKUdu2oPvpHY3m716hP607Lch4g9ZraofPf/7z3enQuyClfe2111axHTt2VDHqky2TAhqPve9YJ3E1FRERERGRUeOmRkRERERERo2bGhERERERGTVdX1YrpWxP8nCSp5J8YxiGraWUFUn+fZItSbYn+dvDMLAwQ0RE5CzFNVJE5Mwzyyc13zYMw6tPOcXz/UluHIbhmiQ3Tv4tIiJyLuIaKSJyBpmP+9l7krxt8vcbknwyyU8/203TrhDkbECOF3Rvwk5cDz74YBUj1yFKhxxkEnbcIEcqipGbBKVDLi4tyLnqs5/9bBV705veVMXuuOOOrvy0eOCBB6oYuamQkwU5Ztx3332YDtUl9QFyuSKHLHLhoDQSduQhtxlyGqE8kkNWwm5l5Djz+OOPVzFykSEXox/8wR/EtK+77roqRv2cHH4oRn3gsccew7S/+MUvYrwHctX7p//0n1axG264Ae8nhxYqz6c//ekqtmrVqipGzj379+/HtIlZ3B5lVMy0Rg7DUM3DNI+1nLhoPSMHJ5ov77333ipGY4Jcr1pp0zxGcxY5KVIeWw6d5KS0YcOGKrZ9+/YqtmXLlipGzqI09ydcR5RPcgGjOZ0c0VrvBdQ3KEZrGa17NA+13sWoX9FcT32A6rLlVEn5pGdSjNZ7mr9f85rXYNrkYkd1RO1IfZr6PvW1hN+xqB3JyfOKK66oYt/1Xd9VxW688UZMm94F6T2d5gx6B5jlfYjGcsuhtkXvJzVDkv9USrmllPK+SWztMAx7kmTyc81MKYuIiJwduEaKiJxhej+pecswDLtLKWuSfKKUcldvApMJ/n0J/xZBRERk5DynNfLU9bF1doOIiPTR9UnNMAy7Jz/3J/nDJG9Isq+Usj5JJj/x+xbDMHxoGIatwzBspY/PRERExsxzXSNPXR/9pZ+IyPx41k1NKeWiUsolJ/+e5J1Jbk/y8STvnVz23iQfe74yKSIishhxjRQRWRz0fP1sbZI/nIiczk/y4WEY/qSUclOSj5RSfjTJQ0m+vyfBadEPCdFIlJQkL3vZy6rYrbfeWsVIINZrSND6bdmaNfXXoXfv3t2Vdq9onYRkSfKt3/qtVexzn/tcFXv5y19exW6//fYqRuUmAV3Cdf5Xf/VXVezFL35xFbv77rur2M6dO7vy03omCetIiNYrLmuJtEnMSO1DwjgqTyudZcuWVTEqIwkhX/3qV1exn/iJn6hiq1evxrRbJgnTkKiPYiQi3rhxIz7zy1/+chUjsSjV5S233FLFqJ+/5z3vwbSvv/76KvaJT3yiilF5SBT6yCOPVDESKic8Z7SE3zIaTssaeeLEiXz9619/Wmz63wkbUyTJ5s2bqxjNwQTNT70mKK08HTt2rIr1rntU7tZ7wVVXXVXFaJ1Zt25dFdu7d28Vo68BtuZKqnMSUNMzaS6guaRVbnom1Ru1GbUDzbU037WgdChG5Vm+fDk+k77dQ3mi/ktt85a3vKWKtb72Sf2y10CI8kPPa713kdkVrY/UjtT/7rzzzipG74sJ90Ey2aC2pbahdZTe7RIuD8WeiWfd1AzD8ECSymprGIZDSd4+U2oiIiJnEa6RIiKLg1nOqREREREREVl0uKkREREREZFR46ZGRERERERGTe85NaeFYRgq0Q+dtNsS2d52221VrFec1is2otNUExYUtq7tgURjJGBOWJhPp8GTmIvEmpdeemkVI8F7wqJ1EreRGIxOHaZ6bEFif6rzWU5CnqZVbioPpdN7GnwrHeIlL3lJFSOR69vfXn9d/5JLLqliZDKQsGCThH4UI+EstdfBgwcx7de+9rVV7KabbqpivYJWEsh+5CMfwbSpfv/W3/pbVez//r//7ypGJ0WTeJSEnkly+eWXVzESNcu5RymlWhdo3miJbEkM3CvCp3FG6ZAoOmFTAUqHykPzBs1ZLdMRGj+0Rh0+fLiK0dxG82JLTE7zAV1LcxbVBdVZ6z2D8t5b571GOC3jJFofCaoLqt+WEQP1K1oLad2j9ynqV6227T2ChPovjScy1zly5Ag+k8wvduzYUcXo/Y76AMU++9nPYtpUl1dccUVXfqiMVOdkRpDwuJ3VKMBPakREREREZNS4qRERERERkVHjpkZEREREREaNmxoRERERERk1C2oUcP7551dCIBKN0YmoSf8p8WQUQOL4Q4cOVbGWKI/SJhFd74moJIy75557MG0SbtFJ0SRaJ5EgCe0OHDiAaVMdkfCL6ofa9rHHHuu6twWJ90jgSFC/aJ3mTtf2pk31s3btWkznsssuq2Jr1qypYm9+85ur2Fvf+tYqRv28JXjsPTGZ+iqJc0k02zoNm0wBXv/611cxEjOS6JYE+C2x/l133VXFqIwkNKV7SRzZKveePXuqGIkjyfRDzm5KKU1h9qm05mq6t/f0dZo3aDy3RLs0r1N+aM6hsUfzEI2zhIXerTrquXflypVVjMqXsAC710SF0plFFN1rokJ13mvC04L6UGvOm4beScgwKmGzoeXLl1exa665poq99KUvrWJkftEyKaC6pDqnclNd0r2t8U7vgldffXUVu//++6sYvdMsW7asirUMasgcitpn9erVVYz6FZkCUBsmPM5onDwTflIjIiIiIiKjxk2NiIiIiIiMGjc1IiIiIiIyatzUiIiIiIjIqFlQo4ATJ05UJ9n2ChlbkEiLhFIkHCRREwnEk/6TmUn4Relce+21VYxOhE5YaEVCSjolmNImEXLrlGo6hZnqnISmGzZsqGJUZ60T7/fu3VvFSDhI7U3tQPXTEmZSOlRuSmfTpk1VbP369ZgOiePp9N7rrruuitEJ2z1C42eCxJEkeqTxQALDlhiRjBPIFOAVr3hFFfvyl7/cnQ5B/YWMC1772tdWMeovmzdvrmJkCJDwSdwHDx7Ea+XcYhiGqn/QetQSNtM4pfmf1o5du3Z1XdcyZSEzm16BOkFrR8sogNYUyjulTTEaj61T52ltprWU8kNCa5p/aV5NWFRNaT/66KNVrFfI3nofoj5I7T2fd4Uk2bJlSxUjYxW6n8TxZFLQWjOp3lrGQtNQn6T6of6TcB2RSQ29A9A4IcOnlrEDvZPTekZjgp5J70MtIw8aJ63+38JPakREREREZNS4qRERERERkVHjpkZEREREREaNmxoRERERERk1C2oUMAxDJUIicVrLKIBONe0VwZFIi9JpCSFJ4EuiJkqbhGh0Euy73/1uTPtP/uRPqlivOJLEclSWWU4TprTp9GnKDwn61q1bh+mQuJ4EZpT3XnFZSwDaK9AlQR8Jx9/4xjdiOmQUQEJIOlW31xSgJfYk6Jk0TqhtqX5IyJgkn/nMZ6oYGUbccsstVYz6C5lKtNKma6kP3XrrrVWMDA727dtXxahfJP39V849hmHoEtLT/Jv0C/upD/bOJa21mcTFBAmJad4gsTOJxhNeS3tNE0hY3zKPIeiZvQJ+qrOlS5dWsdbp67TmUozeAWh9pHy3xORU7l5TAJpDyTgpYdMcWida5hk9tNqb1s1eAwoygdi9e3cVa60Tx44dq2L0rkLmAb110Xr3IWjO2bZtWxWj9zsyaGrlsXfsPBN+UiMiIiIiIqPGTY2IiIiIiIwaNzUiIiIiIjJq3NSIiIiIiMiocVMjIiIiIiKjZsHdz6adIlpuKgQ5nfW4xSRtV7Pe5/W6w9D9K1asqGJUlj/+4z/GZ/Y6t5H7CDmd9Tp7Jex60etyQs88cuRIFSPHlyS57rrrqtiVV15ZxR555JEqRo5U5Dbzwhe+ENOmOLnIXHbZZVXspS99aVcsYScvciV5PpzOeqH2pvyQM8wwDPhMcpyhMUHOJ+TwQ32I3GaS/jqicUfjicpy8OBBfCa54uzcubMrP3J2U0qpxhr1VeqDCTt+Pfnkk1Xskksu6coPzf2tdbR3jqA80nxHcwG5nCVcRzTvUH6ofqiMrXLPJ22aL8mVjFxfE147yDmT1r1Dhw5VsV5Hs4TzTmsmvReQo9mmTZswHXI6o7agdYLySHN1q22pHem9i9Imxy9ao8iJMGH3s96xQ2sP5ZucxhLu073vHzRnUNo07hJ+Z6S6fCb8pEZEREREREaNmxoRERERERk1bmpERERERGTUuKkREREREZFRs6BGAURLSNxLr4i+N52WMI4EUCTSmo9RAD0vYSF8S+Dek5+WSIvoFY2tXbu2ipHAi4RgLREapU1iO0r76quv7kqn1d4k/iOjAIpRey9fvhzToXYkgWOvuJ36+SxCSLqW+iWJV0mATILUhMtNglYad1QX9LzWGKG8Hz58uIpR/Rw9erSKXXXVVVVs27ZtmDYJQ0lMu2vXLrxfzl5KKdUcRcLm1pxF44fmkt57afy00qZ80trTK8KndFrjudc4pNf0htbHlqFR77xMgneq8/m8uyQ8B9PaQ4YlVBet/kNrKc2r1A5kZtB69+lds+l+6pPUXiTAb9HbNyjfdB0ZArTup3dGilEZaSy2xhPVJeWd3ktpfdyyZUsVI8OohMdoyyijhZ/UiIiIiIjIqHFTIyIiIiIio8ZNjYiIiIiIjBo3NSIiIiIiMmoW3CiABEu9zCKCfq7PI3FZwkKpXnEkiQRJcEair9b9BD2z95T3Vrl7T5Ldt29f170kwKdYK051QWJEErvNIj7tFcdT2iTWbIndKJ1ecW8vswhNe0W7lEcaI72nlyecT2ofEijSuHvzm9+M6Xz2s5/tzlNPOvfee28VaxlD0BhvXSvnFkuWLKnmPDphfpZT3nvHPvXrXhF8wmLr3nWGTF127txZxVqiaho/vWY4tEZRvlvvLXQ/1QXNWcQs6wHNjXQ/mfPQXE3Xtd49aJ2gNY7WcEpnvkYBRK9gvvUO2WsK8MQTT3TdS/2itT6SoUxv3ik/VGeXX345pr179+6uZ/aaVe3du7eKtd4re/vlM+EnNSIiIiIiMmrc1IiIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIyaBTcKmBbhkdBpFmFz77WzPJMgARMJ0SgdOj21JYwjSKS1efPmKnbw4MGu55F4r2UU0CuuJzEjpUPC+pYYkYSHy5Yt63omicuoveje1rVURsojxVqiOkpnPmNiPsYZrXRIoEh9kpjFiOGxxx6rYl/72teqGIkMKY8tQwBqn17zgV7DkNb4JqMAEkXLuccwDJXAuHd+OHn/NL0iZhIs0+nerdPXaZ2g8UynydN1tCa0xPpUHlonyHSByjPL2kzlbhnf9FxHc1trDqU1jmK961GvMU/C/bLXUIbqtyUcp3jv+kjXUR9q9avTvRZSXbTMOHrNEHpNAWgd3bZtW3favflpzQ/TtPoVrcO9Jhsn8ZMaEREREREZNW5qRERERERk1LipERERERGRUdO1qSmlLC+lfLSUclcp5c5SyptLKStKKZ8opdw7+Xnp851ZERGRxYTro4jI4qDXKOCXkvzJMAzfV0q5IMmLk/xMkhuHYfhgKeX9Sd6f5Kef7UE9gudZxM4tkddzpSXc6hXGUez48eNVjATDs5wkv2vXrq60Kd8kEmyVm0R9JCikU51JoHjppfXaTte1rl2xYkVXfnqNHVqn1dL9JFrsFXu2hHaUDjEfA4D5jicSwlP/3b59exVrieBJhExQXZI4sve6hEXRJEakZ5Iomdp2//79mDb1dapLGRWnbX2cHn80V7fEuDROe8Xb9MxZRNW9Jiy0/veevt6aQ+n+o0ePVjGaB2n+pTpvifXpfqpfmnN6jWdaadMze/NO6x5d1xLw94re6Tp6ZisdKmPvfNkr9G+tj9S21NcIWntmWR/J1ILWzN61nYT5jz/+ePe1NJ6ov1B+aNweO3YM06Zn9tb5SZ71k5pSytIk35LkN5JkGIYnhmE4muQ9SW6YXHZDku+dKWUREZER4/ooIrJ46Pn62ZVJDiT5rVLKF0spv15KuSjJ2mEY9iTJ5Oea5zGfIiIiiw3XRxGRRULPpub8JK9N8qvDMLwmyaOZ+yi9i1LK+0opN5dSbm6dhSIiIjJCTtv62HvehYiIMD2bmp1Jdg7D8PnJvz+auUl8XyllfZJMfuKXyIdh+NAwDFuHYdjae4CPiIjICDht62NLVyAiIn086y5jGIa9pZQdpZTrhmG4O8nbk3x18ue9ST44+fmxjmdVQq35npjcy3xPWu8VjV133XVVbM+ePV3Pa9FbRyRapzrrNRRIWKhHMbp/3bp1XXlsifVJsEaxXtEjlbv1IjGfE5NnOTm49yRkovfE5Fn6fu8zSbRIwkM6yThhISV9kktp09ihemyNscOHD1cx6i9UHmrbXuOCVj5lvJzO9bGUUvWvWYxwSFzfa6BBY4/mrJZJAc3BlHdaE8ikg+ba1tghMxtKm9aO3nK35m+qX8oPpbNq1aoqRvNQy0iHrqW1uTePdF1rDu01IKJ2pL7Salvqb5Sn3rVjFvOL3rFHeac+Te+LrfWR1h5Kh+qn1VenaZWP8k79hd4B6Dqab+i61rWzmoH1fnTyD5P87sTZ5YEkP5K5T3k+Ukr50SQPJfn+mVIWEREZP66PIiKLgK5NzTAMtyXZCv/19tOaGxERkRHh+igisjjo+5xKRERERERkkeKmRkRERERERo2bGhERERERGTUL7rE87eAwq7NBD/Nxj+p1jmjdf/vtt1exNWvqc9eo3OSs1EqH3CPIMYOuIxcYciVr3U/XknMKOXOQgwe5piTs5ELOKRSjuqR0Wi4cBLUDubuQO8ssLjK9Dlm9zmmt583HiYtcSg4dOlTFyCElYbeaXkdAuo7SaVnIU95XrlzZdR2NMUqndSYXPZP6uZx79LqDPvroo3g/zW80B1PfpLmAYq11gtImt6dt27ZVsY0bN1YxGs+tdZ3mA8onrbm0btH62HIzpDilTe3YO9+13gvIFY3S7nX9pDZsvZ/1roVU7lne+agPzcfprLefJ/3vL70xKkurT1NdUozeXyidxx57rIq1+lXvOw3VL6VN91J+Wsy6PvpJjYiIiIiIjBo3NSIiIiIiMmrc1IiIiIiIyKhxUyMiIiIiIqNmwY0CekX8vffO53kECXkTFrytWrWqih07dqwrHRLqtYSDJAYjkRZdt2zZsq7rli9fjmmT4I2EekuXLq1iJPAiISMJHpN+cRr1AapfSmcWAT/FFqJPJvMT9begfPYKLmmcUP222vb48eNV7JFHHunKI6XdMpsgSAB65MiRrnvnK4YlcebzYZYiZwfUN1p9ncbKfMTOs5io9K5HLeOQaXrNcVppU7l7DQVojLcMEmg803xA6zCtj7RutdZmqg8qI13Xm+/W3ER9kOqtdy2k9mrRux7RewqlQ+YvCfdVGie983dv/0s4n1/72teqWG/9zmJm02sk0ttfet8XW/mcZR5K/KRGRERERERGjpsaEREREREZNW5qRERERERk1LipERERERGRUVOeDwFyM7FSDiR5cPLPVUkOLljizy9nU1kSy7OYOZvKklieFpuHYVh9Gp4jI+EsXh+Ts6s8Z1NZEsuz2DmbyvO8r48Luql5WsKl3DwMw9Yzkvhp5mwqS2J5FjNnU1kSyyNCnG396Gwqz9lUlsTyLHbOpvIsRFn8+pmIiIiIiIwaNzUiIiIiIjJqzuSm5kNnMO3TzdlUlsTyLGbOprIklkeEONv60dlUnrOpLInlWeycTeV53styxjQ1IiIiIiIipwO/fiYiIiIiIqNmwTc1pZR3lVLuLqXcV0p5/0KnP19KKb9ZStlfSrn9lNiKUsonSin3Tn5eeibz2Esp5fJSyp+XUu4spdxRSvmJSXys5bmwlPKFUsqXJuX5uUl8lOVJklLKeaWUL5ZS/mjy7zGXZXsp5SullNtKKTdPYmMuz/JSykdLKXdNxtCbx1weWRy4Ri4eXCMXP66Ri5czsUYu6KamlHJekn+Z5LuSXJ/kB0sp1y9kHk4Dv53kXVOx9ye5cRiGa5LcOPn3GPhGkn88DMNLk7wpyT+YtMdYy/N4km8fhuFVSV6d5F2llDdlvOVJkp9Icucp/x5zWZLk24ZhePUpto5jLs8vJfmTYRhekuRVmWunMZdHzjCukYsO18jFj2vk4mXh18hhGBbsT5I3J/nTU/79gSQfWMg8nKZybEly+yn/vjvJ+snf1ye5+0zn8TmW62NJ3nE2lCfJi5PcmuSNYy1Pko2TQf/tSf5oEhtlWSb53Z5k1VRslOVJsjTJtkx0iWMvj38Wxx/XyMX9xzVycf1xjVy8f87UGrnQXz+7LMmOU/69cxIbO2uHYdiTJJOfa85wfmamlLIlyWuSfD4jLs/ko+jbkuxP8olhGMZcnl9M8lNJTpwSG2tZkmRI8p9KKbeUUt43iY21PFcmOZDktyZfffj1UspFGW95ZHHgGrlIcY1clPxiXCMXK2dkjVzoTU2BmPZrZ5hSysVJfj/JPxqG4fiZzs98GIbhqWEYXp253+C8oZTy8jOcpedEKeXdSfYPw3DLmc7LaeQtwzC8NnNfrfkHpZRvOdMZmgfnJ3ltkl8dhuE1SR7NuL4WIIsT18hFiGvk4sM1ctFzRtbIhd7U7Exy+Sn/3phk9wLn4flgXyllfZJMfu4/w/npppTygsxN1r87DMMfTMKjLc9JhmE4muSTmftu9xjL85Yk31NK2Z7k95J8eynldzLOsiRJhmHYPfm5P8kfJnlDxluenUl2Tn7LmSQfzdwEPtbyyOLANXKR4Rq5aHGNXNyckTVyoTc1NyW5ppRyRSnlgiR/J8nHFzgPzwcfT/Leyd/fm7nv3S56SiklyW8kuXMYhn9+yn+NtTyrSynLJ39/UZLvSHJXRlieYRg+MAzDxmEYtmRunPzZMAx/LyMsS5KUUi4qpVxy8u9J3pnk9oy0PMMw7E2yo5Ry3ST09iRfzUjLI4sG18hFhGvk4sU1cnFzptbIBT98s5Ty3Zn7HuR5SX5zGIafX9AMzJNSyr9L8rYkq5LsS/I/J/m/knwkyaYkDyX5/mEYDp+hLHZTSnlrkr9M8pX8l++k/kzmvjM8xvK8MskNmetbS5J8ZBiG/6WUsjIjLM9JSilvS/KTwzC8e6xlKaVcmbnfPCVzH0t/eBiGnx9reZKklPLqJL+e5IIkDyT5kUz6XUZYHlkcuEYuHlwjx4Fr5OLkTKyRC76pEREREREROZ0s+OGbIiIiIiIipxM3NSIiIiIiMmrc1IiIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIwaNzUiIiIiIjJq3NSIiIiIiMiocVMjIiIiIiKjxk2NiIiIiIiMGjc1IiIiIiIyatzUiIiIiIjIqHFTIyIiIiIio8ZNjYiIiIiIjBo3NSIiIiIiMmrc1IiIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIwaNzUiIiIiIjJq3NSIiIiIiMiocVMjIiIiIiKjxk2NiIiIiIiMGjc1IiIiIiIyatzUiIiIiIjIqHFTIyIiIiIio8ZNjYiIiIiIjBo3NSIiIiIiMmrc1IiIiIiIyKhxUyMiIiIiIqPGTY2IiIiIiIwaNzUyakopP1tKGUopb5vnc942ec7PnpaMzZb2b0/S3rLQaYuIiEg/pZTtpZTtZzofUuOmRkRERM5pJr9YOvXPU6WUw6WUT5ZSfriUUs50Hs8Uk/IPpZQfPtN5IRZ7/mThOP9MZ0BknvxKkt9L8tA8n/OFJC9NcnDeORIRkbHyc5OfL0hydZL/Ksm3Jtma5MfPVKZE5NlxUyOjZhiGgzkNG5FhGB5Lctf8cyQiImNlGIafPfXfpZS3JPlUkh8rpfyfwzBsOyMZE5Fnxa+fyRmhlPK3SymfKqUcK6V8rZTylVLKB0opL5y6bvvkz9JSyj+f/P3Jk9qXZ9LUlFJ+qJRy6+T5+0sp/7aUsmHydYJh6lrU1Jy8tpRyfinlZ0op95ZSHi+l7Cil/EIp5QJI93tLKb9TSrmnlPJoKeWRUsotpZT/oZTimBMRGQnDMHw6c7/wKkleN/3/pZQ3llI+WkrZW0p5YrI2/FopZQM9r5SyopTy86WU20spj03WwC+VUj5YSrlo6tprSin/ppSya/Ls3ZN/XwPP/eu1sJTyfaWUL0yef7iU8nullMvgnitLKR8qpdw3WScPT9bif1VKWTm55pNJfmtyy29NfUVvC6T9d0spn5+se9sn//+MmtVn0qiUUn6glHLjJG9fn1z770opW3vzN7nu/FLKj5VSPldKOT6pmy+WUn6c1uUyx4+XUu6YpLurlPIrpZRllE9ZHPhJjSw4pZR/luQDmfuE5cNJHknyXUn+WZLvLKW8YxiGJ0+55YIkf5ZkRZL/lOR4kmf8bVkp5Z8k+d+SHElyQ5JjSd6R5NOTv8/Kh5N8c5I/nqT/3Ul+KsmaJD8yde0Hk5xI8vkku5IsS/LtSX4pyeuT/P3nkL6IiJwZTuppnnxasJQfSfKvkzye5ONJdiS5Jsl/l+RvllLeNAzDQ6dcf0WSP0+yOcktSX41c79cvjbJ/5jkXyV5dHLt65P85ySXTJ791SQvSfJDSd5TSnn7MAw3Q15/LMn3TO75iyRvTPIDSV5VSnn1MAyPT56/PslNSZYm+Y9Jfj/JhUmuyNwa9StJDiX57fz/23vzaL2ys7zz2VJVuUoqjVdXY0mlGm0Xdg1GFDZliMEMZgh2ICQhQAwxy51uoE0vSFyQdAeS0G066TSEZEHc4LjCEPCCGLtrpe045RiD8VSDylYNKqk0z+OVyqoB29r9x/dduPXt3yu9R1e6uufq+a2ldaVX55y9z57ec+73Pc+WJiS9VdKHJG2eUtbESNk/o0Ge/X+H93nBLwCllKLBy8rbNXhW+M+Sjkq6QdI3S9oq6eFM/UopVw/r9B3D835P0ovD6/yaBm00mpd/RdL/LOmgpPdq0PdvHR57jaS/uNB7M5eQWqv/+M+M/ZH0BklVAw3M6inxqzRYdKqkn58S3zWM/TdJC+F6vzD8/zdNid2swQJ0VNL6KfEi6T8Nj68j13nTMP4LI/FPDOOPSFo+Jb5Q0nZJX516H8P/uwXqOU+Dl6sq6etH/u/9w/jGy90//uM//uM/V+IfygvD+DcN1/mXJK2ZEr9dgwfb7ZLWjZzzLcNzPjgS/9SwnJ+DclZIunb49yLpqeGxPzRy3N8exp+WNG9KfDIXnpb02pFzfm/4f39rSuynhrF3QV0WSrpuyr9/dHjsjwZtN1n2GUn3wP9jfp3y/7sk7RqJvXN4zuckLRn5v/kjfZGt369Jmj9ynd8a/t9bp8S/YRjbPpL3r5X06eH/7aKy/Ofy/vFXYcxM8/eHP/9FrfXQZLDW+hUNfstzVoPfco3yM7XWM8ky/q4GL0m/VmvdO6WMKul+DZJNV95daz0x5VpnJP2uBi8rm6YeWGt9dvTkWutZDT6pkQa/LTLGGDPLGH6V6heGXxH7Aw1+oVYk/Wyt9eCUQ/9HDcwE3lVr3T/1GrXWj2vwSclfL6UsGl73azV4WN4s6ZdHy621Hqu1vjj85zdo8KnMp2utvzty3B9I+jNJr5T0RriFf1Nr/eJI7P8Z/rwXjn8B6nKm1trEE7y31vrYBZxH/NTw5/9Qa33ZtytqrV8d6YuQ4VfLflLSIUn/S631L/P/8O8/o+HL45TTJr998Usjef9FDb5lYmYp/vqZmWleN/z58dH/qLU+U0rZJ+mmUsrSWuvE8L9elPSFDmXcM/z5Z1DG7lLKXkkbO1xPGnzMPcrkC9OyqcHhd5H/oQZfUbtZg996TaX5brMxxphZwT8d+XeV9I5a638Yib9h+POvDb8qNspKDT4JuF2DT/pfP4x/dPhLrnMR5skp8TdqkOs+OfJ/2Vz1YQ2+8v3vSinfIemjGnyS9OTwF4AXwucu8LyXMdQWvUbS4YvwknS7pDFJ2yT9k8LO3C9o4H46yWT7/wkc+6eSvjLNOplLhF9qzEwz+R3b6LcsByVtGB43MYwd6bjITpZxOPj/w+r4UjPlBWsqkwvb/MlAKWWpBt9TvkmDBf4/SjoxPHappHdJepkZgjHGmNlBrbVIf/lg/QYNvp70G6WU3cNPYCYZG/78h+e55PXDn0uHP/cHx00lkyenXnMqExBrctXwF3z3avDVrLdI+r7hf+0tpfyrWuu/SdRzlEPnPyTF0uHPTFudj8l+uk3tC+tUrp/y9/AZotb61VLK8YtQL3MJ8NfPzEwz+THy6uD/14wcJw1+U9aF08Ofq4L/j+IXgx/X4IXmF2utX19r/Z9qrf+kDmxC/+ASlmuMMeYiMfwK1n+T9Nc1eBl4oJSyYMohkzlqSa21nOPP5G/7J4Y/M5/UX0ie7Eyt9ala69/W4MF/kwZfz54n6VdLKe+4kEsG8clPpqJfpI8aCkwMf16MbzVMttEHz9NPN8E5zbNCKWW+/upFycwy/FJjZprJj5LfNPofpZRbNXA22Rl8MtK1jOb7xqWUGyWtn8a1z8etw59/BP/31y5hucYYYy4ytdYvaKBJuUEDh7JJPjP8+Y3JS00e/x1kITxCmCdH4o8myz4ntdav1FofqbX+sqQfHIbfNuWQSR3KfF0YJ4c/m9w7zPtLR+pzRtIWSatKKfeMngOcq35Pa/CS9PqhC1qGyXalnP2N8recZi1+qTEzzfuGP/9JKWV8Mjj87ce/0mBM/tY0y/g9DT5u/6lSyl8uokOLyP9DF74wZ9g1/PmmqcHhwmyBoTHG9I9/oYG282dLKZO6lH+rgcvm/11KuX30hFLKNaWUv3zhqbU+IunPJd0t6d1w/Fgp5drhPz+lgfXwG0spf3PkuL+pgSPbMwLdaJZSyr2lFPrWwmTs+Smxya9bbbjA4p7W4BsUby2lrJxSh+skRV9zm4z/+9G9YUop84aW1Oet39CE6Nc0+HTr3wzLfBmllDWllDumhN4//PmPSynLpxx3rQbPEGaW4rdNM6PUWv+8lPJ/arDHy5ZSyh9qYAP5nRoIA/9M0r+cZhnPllL+Nw1EkI8PHWwm96lZLulxSXdOp4xz8B81+I71r5RSvlkDceJtkr5HA5/9v32JyjXGGHMJqLXuL6X8ew00kf9IA0vmp0spf1+DX9Q9UUr5iAYvGldr8HD9jRpsK/CqKZf6YQ22CfjfSynfP/x70SBHfPvw2F211lpKebukj0n6g1LKhzR4MXilBp+gPCfp7yUMB87F35X0E6WUP9HAuvikpFs0+LrdSxrs0zLJpzV4yfnp4UP+pNbk10adyYha65dLKb8q6X+V9Fgp5YMaPH9+m6QDwz+j/KYG37b4e5K2DdvgqKS1Glhmv08DPVCmfv9c0l2S/oEGjnQf10Cvs1KDtr9P0j/WYC8g1Vo/VUr5NQ0c2CafUyb3qTmpWOtkLjeX21Paf67MP5L+jgYvMM9p8BuwJzRYVK4dOW6XzuEHL9inZsr//YgGH+O/qMFi+DsaLIhbJE2MHPsmnWOfmqDsHxV440u6QwNnmSMavLA9ooHWZuPw+PePHP9+eZ8a//Ef//Gfy/ZHwT41U/5/1XA9PyNp1ZT4a4dr+G4NXgZODHPMv5f0LXCdMQ0snbcOc9OEBjbPvyRpwcixr5T02xo8RH95+PN3JL0SrnuuXNjkHg02kfx1DX7Jd0IDB7DtGmx4+Rq4xls0eHn40mRbTeasc5U95fyigWbnWQ3299mjwQbZC86V5zWwWv4TDX4x+aIGG2//rqTXZes3pfwfkfTQ8H7/QoMXmz+T9POasqfdlON/UoP9gl7S4MXr32mg/wnr6z+X908Zdp4xVwSllMUa/BZnc631Dec73hhjjDHGzH6sqTFzklLK+KgosJRylaT/S4NdgT94WSpmjDHGGGMuOv6kxsxJSin/QNI/02A36L0aaGm+SYONuDZL+oZ6YTsmG2OMMcaYWYaNAsxc5bMafFf2m/RXnvI7Nfje8i/7hcYYY4wxZu7gT2qMMcYYY4wxvWZamppSyltKKVtLKdtLKfdfrEoZY4wxfcc50hhjZo4L/qRmuFniMxr4jO+T9HlJP1hrffIc5zSFDfZDfDlRnejY7PkUmzcv/0539mxrB79o0aImdu211zaxL33pS01swYIFTewVr3hFuj5U96uvbjfL/Yu/+IsmduzYsdRxknTVVe03FKmeX/nKV5rYiy++2MSov+bP570w6X4oRm1B/U19SPXpciy1D50bQfV84YX2m3Ff/vKXmxjdN9UnGufZekZtlDkumsvZdWc6czm674td9qXgy1/+8rFa6/j5jzSzla458qqrrqrXXHPNy2I0R6N5m12fsuOa1uUua8n111/fxCh30Ho32g5RLCK7flOOev7555vYV7/61SYmcRtlcwKt6V2gcqg+l+IZaTrnU1tE5VDdqd2o7OyzRpTfqM+nkwvpHqPrZZ9fsuM82z4SP8tlz5/OM3oEtdvExESYH6ejqblX0vZa6w5JKqX8vgYbE4UvNcPjXl6BDg+FdHO00NEDOl3zuuuajWXDyfXcc881sU2bNjWxO+64o4l96lOfamJ33tnu/XjLLbdg2cTChQub2KpV7ebABw60e1q9733va2K7du3CcsbH23GzcePGJnby5MkmtnXr1iZG7bt48WIse+3atakY9SONAUpW9BIqcaKlsbp06dLUuRE0Ljdv3tzEDh061MTovmkMRA8D1B4EtRHVm46LEjfFs4mfkg09LFH7SLyg0kKeLZvIJr+Iffv27Z7WBcxsoFOOvOaaa3Tbbbe9LEZzlB7EJ88fhdYnmme0XtK6THknqtM3fMM3NDHKHVu2bGliGza0G9dTTMq/rNBxzzzzTBN77LHHmtjp06exbHpxW7lyZROjX2weOXKkidH6Ev3Sj3Iz1YfGBa13NAaiX7Rm12r65S2NaTpO4ucF+qXsSy+91MToF6DZ9pG4z+maNK7oOGrLqGxqyzNnzjQxGufZX27T84wkTUxMXHA59AyQfbGNoHb74z/+4zA/TufrZ+s0cJWaZN8w9jJKKe8spTxcSnl4GmUZY4wxfeK8OXJqfqQHTWOMMXmm81JDv4psfgVaa31vrXVTrbX9WMMYY4yZm5w3R07Nj9FvTo0xxuSYzkvNPknrp/z7Bkntd52MMcaYKw/nSGOMmUGm86uhz0u6rZRyk6T9kv6OpL97rhPmzZvXfOeOPnKPdC30fV767VZWU0PfCezyXT/STpw6dSp17tGjR9PnHj9+vImRLmBsbKyJ0Xcz9+/f38Sirz7Q+dTmq1evbmI7duxoYtQ3kQYlK4Kj7yFTOXRc9NtR+m4otRF9zzX73eIIao/sd3npu8VdxnRWoEv3mNXoSNzuFKM+o+/30j1G2oNsOdkYEWlqpiuaNL2iU46cP39+o2OheR9pLOi75zTWT5w4kTo3KoegNSKrB6Jy6Hv9tLZJef0BzT1aa0n/Eq0l1G7UZytWrGhi1A/07BPl5qzGmOpD6xidG2lOqc2zGhYqm7Rf0TWzfZt9VojWdKp7Vuyf1a1FZdM1aRzQ3KExTcdF5lDU5tPJzVQ2lRFdM/tMPckFv9TUWr9SSvlJSR+VNF/S+2qtT1zo9Ywxxpi5gnOkMcbMLNP6Em+t9b9I+i8XqS7GGGPMnME50hhjZo5pbb5pjDHGGGOMMZcbv9QYY4wxxhhjes2MekjWWhtRLAmDIqMAEltTLLvx3Zo1a5rY6OZnk+zbt6+JkXhq586dTYw22eqywysJLqlsEtARVHYX4VbWKIA2giSTgkiESXESy1Ed6TgSQkZlk7iN2i3bPpHgkvqMBLEk6qM+ow0nIzME2lCW6kNlU/tS2ZEQMiuazG5s1mUHcrrvmRLr2xTARNRaG4ExrUPRprIkWl+2bFkTi/LrKJQfX/nKV+KxtDkwzWcyjyEjHIIE/FJetE7ibRIh0xyN1hJaL2m9Xb58eRMjYx+6R1qvpLzJUlYcT0ZM0X1n8yPRZRNKukfK2ZQz6ZrR5rHZsqm/u5gAjRKZ60Qi/lGyG4J32Ug6a7pDdaTxR7Ho/qhOXXOmP6kxxhhjjDHG9Bq/1BhjjDHGGGN6jV9qjDHGGGOMMb3GLzXGGGOMMcaYXuOXGmOMMcYYY0yvmXH3s1GXii4uYORGQWRdPMglYteuXemys05RVDa5s0TOHIsXL25i4+PjTYwcQMhNhcp54YUXsOys8wTdzy233NLEyG1mYmICr0nxw4cPNzFy66B6X3/99U0scoyjY8nxhY4jR5LI7YPcT2j8Z8cQEbmfkSNb1s2N6khtHo2f7LHU5lmnM3LZkXhO0P1kY0TWYcqYSb761a/qxIkTL4vR3Ivmc9bxa9GiRU2M5hm5c+3ZswfLpvxI84/WHKo3rZdRfqS60z3SnKSyjx071sTIPSo6Pzv3N27c2MTIPTUqm9qcngGyx9FYiRyyaB2kcUntQ/WJnO2onvRcQNekMUBEzqSUm6lvaZxnn8Wi54Jojo9C/UPXpNxK/R0dm3Uwo2dqck6LnguoLyJnvAhnXmOMMcYYY0yv8UuNMcYYY4wxptf4pcYYY4wxxhjTa/xSY4wxxhhjjOk1M2oUQGTFyhILxEhER8ItEkWRIJAEXpK0Zs0ajGeuma1PJFij80kYR+1Gx5EpQHTfJBAjAd3x48eb2IIFC5rYdddd18ROnjyJZZOI/9ChQ02MhGjUFiQcjITfdE0S72WF9dRmUZyEryS4pH4cFRpL0vLly7HsrAiZ2ojGBfVXJHgk8R/dN5VNc4fWhmgdobKzxgVZY5NICJk1GjBXHqWUZq2nMRwJx2ltXLduXROjuUt5Yv/+/U0smlMrVqxoYrTW09yLBMujRMYfFI8MYEahdZXWochIJyuEJ1E1HddlfSDTnWwupDGQXeeja2bNeeg5J3r+IKjNaQw899xzTYzafNWqVVgOtQeNaRq/1A80b6Oxn+0zmk/03EXPBZE5A+VsGmtkYEVk55jE99M1Z/qTGmOMMcYYY0yv8UuNMcYYY4wxptf4pcYYY4wxxhjTa/xSY4wxxhhjjOk1M24UMCp2IhFRJLIl8RWR3T2VYnfffTde87bbbkudv2XLliZ29OjRVCwSy2VFY1kBKIkeu+yATiLMaGfcUajNIgFodofsbH+TKD/arZbaiIR+dByVffr0aSwnK8ynNqd227BhQyomsXhw9+7dTSwrACURZSQIpGtmhZQUo/EXzScSOGZNNqhs6q9I3GijAHMuRscHzfFIrE/rJeVMmpMkLqZyNm7ciGWTkQ6tbbTmUB1pvSTht8TzOSvezpp8RPmRyjlw4EATo/U7a5IUiclpzcvmCeobKicyeskaxdCaTudG5hfUt7Qu0zXpvmmcjo2NYdlUDo1BGqvUbmRUFI1pGpc0NijH0bl0L5GZBo1LaksyD6DnKWrfaD5lDSzOhT+pMcYYY4wxxvQav9QYY4wxxhhjeo1faowxxhhjjDG9xi81xhhjjDHGmF4zo0YBpZRG9NNFGEfiq6yYnER1dC6J/CTplltuaWK0Ey0Jskgo9cQTTzSxSNi8Y8eOJjY+Po7HjpLdpZ3EYREkMCOBF90PtXkk1MuOjWzds7vTSyyMo/uhneyz409icT1B90jCQzIFeO1rX4vXpB3DSchL/U1GAbRDcWT6QfMkKyolMWJWdBuVQ/XMxggbApiulFKaHJddVyUW+9M4pHWD5k+XnLBs2bImtnTp0iZGeYvWnKeffrqJkSmLJO3atauJkcCc2i275lDbRtektY1E1WRcQPkx2rmdyqZrUu6Z7s7t9FxBMRLR03GRWRC1JUFrfVa0vm7dulQZkvTss882MRq/NHcoP0bjivpsOs9ylLfIOCkqe+HChU2M6p6dT5EBBY3pyMwpwp/UGGOMMcYYY3qNX2qMMcYYY4wxvcYvNcYYY4wxxphe45caY4wxxhhjTK+ZUaMAqRUIkbAoEviSYIjEUySAIqEUnbt8+XIsm4TRJLjM7la+du3aJhbtskriPxJNUozuscuOydQ/JOYioR+JHklwFvU3CfDoHqnudN9UDtVRYhFcdodhqk9UDo1pEubTWDt06FAT+/znP9/EIhEmlU33TeOP5tjRo0ebWGSEkDU+oPOzpgCRsJhEu13mxCgk1ozOtYGAiZg/f34zB0i0Gwn4SZif3V2cBN00x6P8mBVqE7Q+0b3Q+iDx3I2MWTLQ+kCmQBKvMZQfs4YnlLciUfWxY8eaWGR8Mwq1+cmTJ5sYPfdInMez0H1HBix0bLZvyfSJnmcisX72Huk46gcqO5rLFKdxQPmRjqO5HI0rmstUdzqfxi89P0T9HT2rdMGf1BhjjDHGGGN6jV9qjDHGGGOMMb3GLzXGGGOMMcaYXuOXGmOMMcYYY0yvmXGjgFGyu6RKLL7K7lpPQj0SMJFYTmIh5YoVK5oY7axM5gF07vbt27FsEimSmDES3GfqQ4J3iduNyiYhGondbr755kwVJbGYjER9VHcaF7RzMPWrxMI4GlckZMyaSkTlk1EAjf0lS5Y0MTIP+MQnPoFl33bbbU2MRJgTExNNjPohK26M4nSPNKapHFozaAfn6PzpmItQLBLs0v1EoklzZXH27Nlm3aI1h9Y2iddlmmc0V0hwnDVGicomUwFaLym/0Rq6f/9+LJvWLFpDSdRPIm+6bzKtkfLCZlpDqc02bNjQxKK1JDJhGYVyOK1DlE8oD0o8Bqme1L60/pIxhMRrOPU39RmVTfezdetWLDs7d6hvqc3puSsyECLovqnNKTdTfjt+/DiWQ/mMyqbxGxlLjELPyRFdTT/8SY0xxhhjjDGm1/ilxhhjjDHGGNNr/FJjjDHGGGOM6TV+qTHGGGOMMcb0Gr/UGGOMMcYYY3rNjLqfzZs3L+UWErl9TMclKHtu5PZBThjk4kFODeQUQs4lN910E5ZNLh579+5tYuQAcuzYsSZGbRH1C5VNjh10TWqzXbt2NTFy5pDYIe7uu+9O1fHZZ59tYgcOHGhi0bigcUCOHeTcQ2MgcuIiNyFqD3LuoT6jviEnIEnas2dPEyPXFhqr5HJCdSQnFSk/n8iRZ+XKlU0s69omsZNR1jmQ6LIuUftGbo/myqKU0owPGpc0hqTpOYHSGKZY5A6aHcN0HK215OBEzmDRsbTWHz16tImRAxStbdEaOjY21sSo3egeab2j9qV1VeLnpK/5mq9pYrR+U97Zt29fE4ueC2hdJ3cvaktqn2j9pXbLOpNGuWeUqG+zzmTUD+TmRs9n0X3THKW+oDFEroOUHyP3PHJQJaju2TUoGtNE1uVvEn9SY4wxxhhjjOk1fqkxxhhjjDHG9Bq/1BhjjDHGGGN6zXlfakop7yulHCmlbJkSW15K+VgpZdvwZ357UGOMMWaO4BxpjDGzg4xRwPsl/VtJ/3FK7H5JD9Va31NKuX/473ef70LXXHNNKPbLQIKsix2LRJgkMiSBIl2TRNEkJCMBtMQGAnQsCeOeeeaZJkYC6kjsTCItEgSSoPv06dNNrIvwlcSMjz76aBMjQwES9d91111N7IknnkiXfc011zQx6ltq30hgS5C4ktqNxgCdGxkx0D1mTSRIeEhtHok16ZrUviSEpDqSEQOZZEgs2KR5S6LmrCA6mk90flbQamYt79dFyJHz5s3TokWLXhajcRQZ6dDYohyVNXUhMS+tLxKvMRTLrqE0J6KySRhN6waVTW1BZdOaEZVDMeob6kdaV6l9ovO3bdvWxOhZY82aNU3s1ltvbWI7d+7EskkQTms6tS+1BeUiids92770nEKxiCNHjjQxanOqz4svvtjEqB8jYyoa0zR+R9eL6Jpd8mP2fqi/qR+oD6NnErqfrgZh5/2kptb6SUmjdkFvlfTA8O8PSHpbp1KNMcaYOYBzpDHGzA4u1NJ5Va31oCTVWg+WUvgjBkmllHdKeqeUt8gzxhhjekwqR07Nj/QbUmOMMXkuuVFArfW9tdZNtdZN0ceoxhhjzJXG1PxIXy8xxhiT50Jfag6XUtZI0vBn++VDY4wx5srEOdIYY2aYC/3o5MOS3i7pPcOfH8qcVEpJfQWtyw7b0zEFIPF19BUAEnqTqIkEXgQJr0jQJ/GuxSS+omvSPW7fvr2JRaIxEvBRG1EdSdhJ9Y6EYCSapBiNKbom3UvUX9TfZGhA7UtCvUjkSiYHWSHvwoULUzEyLpDy7UuCQIqRKJliErcHzXtqczqO2ieay2RgkRW0Un2y602Xa5re0zlH1lqbNZxE611MKAgam3RNMv6Idvem8yMRdAbKE9H90dxfvXp1EyOxNJkhnDp1qonReidxnqB2o9xOay0JqGlNl3htpd3g6R4pRuMi6u+sIJz65syZM00sWqvJgIjKoXxCbU6xgwcPYtlUdxpD9BxI/Uh1jMYVzSdqIyqb8gmV08WghsYgjYGsyUBUdhdjlIiMpfN/kvRpSa8spewrpbxDg4X620op2yR92/DfxhhjzBWFc6QxxswOzvtJTa31B4P/evNFrosxxhjTK5wjjTFmduDvPRhjjDHGGGN6jV9qjDHGGGOMMb1mRj2Wa62NyKuLKcB0BLXZ3cEjURLZbZLInESCJMqjsiNhJYn4SaCeNS4gsRyJ9yQWvJ04MbrPHEO7FhOREJJEiiQwo7akelM7rl27FsvOthvVh8SNkVFAVuxJfUvGB0ePHk0dJ7FQle6H2oKMISgWmV/Q/dAYPH78eBOjemdFqlJ+LciaFBDROkJCyK47Jpu5Sa01NRYi62carzQHsjEiGtdk1kLrINWd8gnlt0hUTWVTPSnP0A7zZBQQ8dJLLzUxMmaJ1sFRaP2ltTK6JrUvidup3kRkpEP5lXIZCcdpnEbPdvQMQOs/9SNBfdvl2Se71yI9+1B/dTFioLWBni2JbH9Fx1IepvlN7UPPtV3MTrrmR39SY4wxxhhjjOk1fqkxxhhjjDHG9Bq/1BhjjDHGGGN6jV9qjDHGGGOMMb1mRo0CSilpoRWR3QE1K+YlAVIkoCPxFAnMSIxIArF169aly968eXMT27hxYxMjISUJ9cjMIBKKkkCMhJAk9iTxHwkPSeQt8c7vJCCl/ibB5MqVK5tYNKZInEltRH1GZUdGAXQ/JOwnQSAJQKnNIgMK6p+s6Jbags6NhJAUp52HaWxkd8im60l5o4CsQLGL2Qn1N8XMlUcppRlLkTieoDlFczw7rklIHI11mmtkzEJrI5VDOSrKjzt27GhiGzZsaGKUC2ldplgkZM+uG7RWT9cghNblLs80o2SNByKyZi3UZlEeprWRnruyz4bUFpQzJa47tS+VTXORrhc9F1Df0jMotQ8dR88U0XMBXZPmTvbZh56JI8MReo7MmkBM4k9qjDHGGGOMMb3GLzXGGGOMMcaYXuOXGmOMMcYYY0yv8UuNMcYYY4wxptfMqFGA1AqEIsEQEQnKR5mOoUB0LokeDx482MRol9XsTvSRiQIJKUmQRUI0En1Rm0dlU5zaja5JJgMkuIx2xc3uUk07DB89ejRVRzJckPgeSVBIsezu3BKL+kgsd/LkySZGAjpqi0gomjVDoDpSfUgMS6YSkjQ2NtbEsiYQJK7Mihslbo/sOpTdDTsSFpPQtMsaaOY2o/OPxmq0wzyZCtDYojxKc4VyTJSDaZ6TQJjWb5rPlPOidZXKoXWQ1ggyOOgyHymP0xyn+lDeo5wX5Ucqh3IC3Q+t37TOr127FsumsUZ5i+67yxqYzcNU9+mMC4nHBs0TqjsJ87Mxicc/rQV0P1RHmjvROkJ5nPJZ1qiCYtHzJpUTGf5E+JMaY4wxxhhjTK/xS40xxhhjjDGm1/ilxhhjjDHGGNNr/FJjjDHGGGOM6TV+qTHGGGOMMcb0mhl1PyulNI4qWbcEaXoOReSiQTFyfJGkM2fONLHrrruuiS1btqyJkTMMualt2LABy37d617XxA4cONDEyAmDnCyOHDnSxOj+JOnUqVNNjJxGyEmDXDhWr17dxCInDHLaoWPJFYRcachxK3IfIXeXL3/5y6lyyHUlgtqd3FioH2j8UVuQ043E82z58uV47Ch033RuNJ+yUH/TuCCHIBrnUZ2yjjx0313cz2jNidY7c2Uxb968Zs2ksRG5+tGYo7FOx5E7EsWitZpyAs0VWrPo3D179jSx6L7JwZLyK90Prf+0bkTzmfIruTWtWLGiiVGeoFjkzkXtQTFyl6O1jRy3IvdKWuvJ5ZXqnnXfk3hdp+ccanMa++ScRrlVyq//dI9UNj0jdXnWpWtGz22jdMmP1BfU5lnnPyJyNKOxavczY4wxxhhjzBWFX2qMMcYYY4wxvcYvNcYYY4wxxphe45caY4wxxhhjTK+ZUaOAs2fPNqIfEhuRmFZioV+WrBCYhNYS15POJzHY8ePHm9ihQ4ea2L59+7Ds9evXY3yUj370o02MhH4k1oxEYySEXLJkSROjPiNRKQnwo37NCg9JLEeCMxLMkwBOYkMDqjsJ8Ej4SiYFEovy6Hw6jkSPBPW3xILNrHFBVgx78803Y9kkzjx69GgTW7VqVROjMU1zh4wdJB6XkRB4FGozikXQWKe1JTKwMHOb0ZxCY4ME3RFZUwwal1mjlihO6wYdR+sy5R1qC4nXEpr7W7ZsaWK03lEui/IjtSU9A1DdqY7Z60nS4sWLU8fScwr1d3SPBJ1P9aF1rMuYpvxMOZegHEVjOjL2of6hMU0xeuajvlmzZg2WTfd9+PDhJkb5kcqmcR4Zb9EYpL6NDCxGoeeP6Bmf7jsykYjwJzXGGGOMMcaYXuOXGmOMMcYYY0yv8UuNMcYYY4wxptf4pcYYY4wxxhjTa2bUKKCUMi2xPwmbSHA0nRgJFCVpfHy8iZG4eMeOHalybr/99iZGuyhL0oMPPtjEXv3qVzcxEuWRiJLuMRJVk0grKwqlcmin50h8Su1LgkIS+tH9UKzLjvfUj1QfEtpFon4SPVKbk4EFtQ/NkUgQSJCQksqmtnjiiSeaWDSfyASCRIJ79+5tYrSGkLFDJLanupN4ldo3u4502Sk6K7g0c5tSSrMe0foUmVrQvKDxRusLXZOuF81nWgdpXuzevbuJ0VwhY5WDBw9i2WQAcOONNzYxMiKh/Ej1yRqJSHnTBWofWgMjIxLqx6w5QzafRPmR2o3WdBKJU/tE+TEybhqF6kltQWJ9Mp6JoLGRXb/p+S567qL7ofFC7Ua5jPomyo90j1kjKDqXnnHIyCm6Zlf8SY0xxhhjjDGm1/ilxhhjjDHGGNNr/FJjjDHGGGOM6TV+qTHGGGOMMcb0mstuFNBFeEWix6yYl46jGAmOJRY7kfCQdm6l3Vhpt9vly5dj2XfddVcTe/bZZ/HYUagt6F4igRaJEbPtS2Iw6ttod1nqbxLBUYz6gUSYkRCS+ie7Ez2VTbtmS9Lzzz/fxLoI+0fJ9s254qNQn9G8JeEhCf0lHlckIN23b18TI1HyK17xiiYWtSOJM7MGANGu5qPYKMB0JWsUQOJricc1jTdaB2lto+O67PxO+ZGMYsgUgNaCFStWYNm0jmXXDWozyo/RvKd1h4T9tN7RGkGxqGw6lvIWrS+Uo+jcyNiJyqad7Am65okTJ/BY6guqJ42BrOA9u6ZL3Lc0hrLPTVGbkbCfzs+aHFB9omcfitN4obFP60gXQy5aryKjjAh/UmOMMcYYY4zpNX6pMcYYY4wxxvQav9QYY4wxxhhjeo1faowxxhhjjDG9ZkaNAqScODkSjmeFzV12/x0lEu2SCJoMAKjuJAan3WWXLVuGZZMQ7fDhw02MBHiRGGwUEpJJeWEc7dQ7Pj7exLJi+yieFZKRwJCOi0SC2V3iacdjEsFFRgF0PvVjVkye3Rk8imd3Mqb6LFy4sIlFYn0SFlN9aKyRAJnO7SLWz64Z0TWzx1G72SjASIMxOCpm72KAkd1VnciaDETCZMpxlBMox9HcO3ToUBOLdiHPGqvQWk9tRmtTZM5AZdN9U90pF9IO8ZFQmsqmGOVCep6hWGQgRH1GRgw0/ig/Uh6Mjs0+02TzaHQ9Op9yIR1HY4ieF2neRedTX1D7ZM1BopxH5WSNRLLmTnSulH+WOxf+pMYYY4wxxhjTa/xSY4wxxhhjjOk1fqkxxhhjjDHG9JrzvtSUUtaXUv57KeWpUsoTpZR3DePLSykfK6VsG/5kQYgxxhgzB3F+NMaY2UPGKOArkn6m1vpoKWWRpEdKKR+T9KOSHqq1vqeUcr+k+yW9+1wXKqWkBLmROC0yEMgwHVGdxEJBEpiR2G7JkiVNbOXKlU0sEss99thjTYx21aVdaKmOJOiLdoomIRqJ21avXt3EyHygi5CdxNaRwCxDZIaQPTYrZKdx1aVsuiaJ7ShG7RvNORob0dzLXnOUSMRLYn8S2FJ9aPdpmg+RsLjrDsVTofumdanLWjWddc1cdi5afpRaIXPWsETKr400V7K7r9O5EguwaX3qMk9HOXXqFMZ37drVxCgP0/pC9R4bG2tikZic1hJas6hsOpfKifJj1gwnO4ao3tFaSflsOmLyKO9Qe9BzEpWTNQWI5tN0ci6VTWYakVERjV8qh/ph7969TYzaJxrTVCfqHyqbxgu1RfT8QH2RNQL5y2uf74Ba68Fa66PDvz8n6SlJ6yS9VdIDw8MekPS2TiUbY4wxPcb50RhjZg+dNDWllI2S7pH0WUmraq0HpcHCLqn96MEYY4y5AnB+NMaYy0v6paaUcr2kP5L007XW1kw9Pu+dpZSHSykPR57cxhhjTF+5GPkx+mqXMcaYHKmXmlLK1Ros2L9ba/3Pw/DhUsqa4f+vkXSEzq21vrfWuqnWuin7fX1jjDGmD1ys/NhFd2eMMaYl435WJP2WpKdqrf96yn99WNLbh39/u6QPXfzqGWOMMbMT50djjJk9ZNzP7pP0I5K+WErZPIz9vKT3SPpAKeUdkvZI+oFMgaOuB+TMETkjTMdxKeswRC5nErsykJvFyZMnm9iZM2ea2Lp165rYwoULsezly5c3sdOn2284ZN3PqB2jT9HovsnhInJPG+UVr3hFE4t+Q0ntSy4edD/ZMRA5y0SuJKNkHVYWL16M51P5NIZoXE7XiYv6nOqedQ4kojlL7i40rqgfaFxQjFyMJJ47dD809imWdcSRuo1B0wsuWn4spTTznMZG5NZEc5fWS/oaOK1jdG6X9ZLqSc5V5GZI+SRac7LOTORCSm3W5WuA2flMeS/7PBM5kFGfEdn1JVufqE5ZpzPqm6hvqX/IkTXr5EnjKpJFUHvQmKbzs8520XMTnR/N+wx0vei5K3s/NOez7nvRWJuuc6yUeKmptf6ZpOiN4M2dSjPGGGPmCM6Pxhgze+jkfmaMMcYYY4wxsw2/1BhjjDHGGGN6jV9qjDHGGGOMMb1mxhWqGcF+VoQcQYIqKpeETlHZJMojIRqJ+vfv39/ETp06laqPxCLolSvbvdxIGE2CrBdeeKGJRfe9aNGiJkZtQQIxEihSP5CATmKDBYJEmFQOiVTpXIlFj5Fgc5QuIle6JvVZ1EbTgcrJmi4QWXGkxHOUBPx0TepHGmuRkDZrAEDnZ0WPkfFGdk6YK4958+aljAKidYjmRdbkI2usEpVNeYIEvmSGQ9fMipUl6frrr29i4+PjTYyMArLrBpm3SLxm0XpAfZM1YoiE7JRnKLdnTRyISNCd3XOQ6kP1jox0yLSB2o3O7zJ+iewzAJVD7UttEeWobJ6gfqC5mDW4kfLPcrRmZJ+po7Jpfej6PuBPaowxxhhjjDG9xi81xhhjjDHGmF7jlxpjjDHGGGNMr/FLjTHGGGOMMabXzKhRQCmlEZ6RCCgST2V30M0KoLvsoEvC36z4isRcS5cubWLR7rJkPkCis+z9ZAX4UdlUDhkfkNCui2iR4tQPJBI8fvx46nqRUQC1L/XjdHctJhOIrPEBkTXJkPJzIitWfu6555pYtBswGQhQW9Bu49Tmy5YtS9VRyouDqd0olt3RXFIjBI/qY648SinNWMqKziVeb2mtzwp3aQxHAl8SJ5Pol0T9ExMTTYzmSXTfVE8SmNOaQ+2bFaJLfD9UdnYdo76JTEdozaL1n9YXaosugmy6R6onrcHZOkqcC7OmANk6RrmZjCWyBgk0Jvfs2dPEomc26lvKjzRWqS1oLtIck7jdqB9oLaD2peeCaB2hukf1jPAnNcYYY4wxxphe45caY4wxxhhjTK/xS40xxhhjjDGm1/ilxhhjjDHGGNNrZtwoYFSgRkKnSDyVFVDTNQkSy0WidSqHxE4Ue9WrXtXEsqYHErfH+vXrmxgJLmnH4y7CZoIEm9Ruhw4dSp1LIjaJxYM7duxoYq9+9aubGN1PdtdsSVq7dm0TO3z4cCpGQsZItE4CUqoTtQWNC7rHqOysOJgEihQjsXAE1YnqnhW0krFDFwE+tUXWnIH6IRJC0hrWZe6Zuc3omOuyEzit6yRkp7lCc5fGZSRazwq6SfRL5WR3c4/iN954YxOjdYPWXxJKR0YBtMbQPdI1jx071sSobyOhNB1LBjmUX6m/qB1p/Y2uSW158uTJ9DUJMiCi3EPPFWNjY02Mxi+ZNkn5dZ3mE7UllRM9q9K8pbYkIycaa1THqGxqo6wpAK1XNHe6PGd3NdLxJzXGGGOMMcaYXuOXGmOMMcYYY0yv8UuNMcYYY4wxptf4pcYYY4wxxhjTa2Z8K+tRIdCl2E17OteMdowlYVxW4JvdiT4ySCDxFF2Tzqfd7al9IgEo7QZ79OjRJvalL32pidEu71T2vn37sGwyUyARXHbHWuqvqA+pzUmMSEJGqmPUtySYI2EoHUdiT2qzSGBL7Ub3SMJOEv/R9SKxPcWpnKxRALVPtAM5tRv1D5WdNdmIxlU0z4yptTbrOo316Qp8swYAtFZHAl9as2iOZ3dFp/xGYmeJcxzdN61ZJG7Prr8Si7fPnDmDx45C+ZHukfKtxMJzWseozWlto7wVmVJQn9FYpecCGldROdHz2CiU9+iZje4xMi6gOBkvEdn5EJlAUPvS2KBcRvWmc6lvJGnJkiVNjMYQrRnZ/BgZb1A/djHVkvxJjTHGGGOMMabn+KXGGGOMMcYY02v8UmOMMcYYY4zpNX6pMcYYY4wxxvSaGTUKICFkJKAmSPjbZTfvUbJiN4kFXbTrayROHoXqGBkckNA7uxtxVlQdiTCpHBJHkgiOjiMhGYk1JRaYkQiOBG8kHo36lqB+JLEclU1C0ahvKU4CRxLLUZvTmKTrSTwOaD7R+KO5Q+MvMimgvqCyad5lxbDRmKb7pn6gckiYSe0biU+p7C7j0sxdSinNHKJxGY0XGlu0RtC4pnNJVN3FWIWuSesBxaZrIHTkyJEmRnWncmhNjwxPaK2nnEm721OOISE65VEpL6qm9s0+K9AYkLjdsgZCkdFFthwavxSjtiCB+qJFi7BsGr/r1q1rYnv27GliJLY/fvw4lkOQ6U7WrIryXvbZReI2pzai3Jw1zYme+ylvUlucC39SY4wxxhhjjOk1fqkxxhhjjDHG9Bq/1BhjjDHGGGN6jV9qjDHGGGOMMb3GLzXGGGOMMcaYXjOj7mdS67BBblgR5OJBjh1Z5xRyx4jcXchNi44lZw9y0SD3ETpOYjcLcoRYvXp1E8u6gEUuJ+S8Qv1A7jATExNNbNmyZU2MHF8kduwgFw4qh5w5qG8id65Rlz6J65l18YrKoTFIfUtuKtlxHpVN7js0LmmcUz9mnemiONWHxhU5kNFxXRyLss5tXVwLs0T9Y64saq3NHKAx3MUtj9Yxmj9ZV77I1S/rPkVrKK0vdG7kakprCd0PPWtQ+1KOifIjzV1qczqf1jtq88hRldzGKN9TPsn2V3TfdGwWarPIqZLunXL7q171qiZG44XW/ui5Kzs2VqxY0cTI7Y76gcaKJJ06dSp1LLUlndvlOZnqSW1EMVpbyHGOXFolvseuY82f1BhjjDHGGGN6jV9qjDHGGGOMMb3GLzXGGGOMMcaYXuOXGmOMMcYYY0yvmVGjgFJKIwrMihajOMVIzJgVQpIILbomkRXRk0iri6B7zZo1TYyEcbt3725ix48fb2LRfZOAj8SDdI9ZgVdkFkGCtay4ncR7JBKMIEErxWhckQgzgtqIhK903MqVK5vY+Ph4uj40Dsh0ge6Rxi8JAiMxIo11al/qs6yIOCqbxi+ZSFA5tGaQuJEEuxL3RRfht5nbjK6jtDZGgvmsIQ3lMppn0RgmqByaFzTP6B4pH0WCeZrPCxcubGK05hw+fDhVTmQ6QnOX7ofWEuqH6B4JWi/JXIf6htqX+iuqD+WJAwcONDF6viPTmyg3U/uSEJ4MjZYuXZqKRdB4odxMRhcnTpxoYpSbafxFkPnAnj17mhjNMTI4iPIjPfPR2KAxQPmN6kPjVOK27PI8JfmTGmOMMcYYY0zP8UuNMcYYY4wxptf4pcYYY4wxxhjTa/xSY4wxxhhjjOk1M24UEInCM5CwiYRkWUMBEiBlDQGkvBCeyonEngSJp3bu3NnESBy/fv36Jva2t72tid11111Y9uOPP97EHnjggSb25JNPNjG6RxIT0v1J+R2gqW9JPEpiwmhnWxJhZneupjpGYrfs/VB9suOXBIYSiwezuz2TWHP58uWpOkrc51QOiQwjQ41RIsMREq/SNbNt0WWHbJoTkQjZXFnMmzevEednx3oEzQHKW9m1Nlqr6djs+UeOHGliq1atamIkMJdYzE5rPYnRV69e3cRuvfXWJrZhwwYs++DBg03sqaeeamJk2ENk13mJ10Z6HiLDHcp7VHa0NlFbUowE5lTH6FmK8hmZQFDdI/OjUbrsbk9QG9E9krA+KmPt2rVN7NixY02MDAmofYhoLmfXDKo7tQXNRRqTEpsNZZ+zJ/EnNcYYY4wxxphe45caY4wxxhhjTK/xS40xxhhjjDGm15z3paaUcm0p5XOllMdLKU+UUn5xGF9eSvlYKWXb8OeyS19dY4wxZnbg/GiMMbOHjFHAS5K+pdb6pVLK1ZL+rJTy/0n6PkkP1VrfU0q5X9L9kt59rguVUhrRW3bX7snzRyERHQmYskYBkSiP6pQV+NI9ksgv2uGVdnYmcSTtTksCUBKhfd3XfR2WTdx7771N7Oabb25i27Zta2JkKBAJ1kjQTf1DxxHUX5FQj4wGqB+pz+i4SOxG51M9SexP7UbnRrtC066+0U6/o5C4sstO3FnBPM1bmoskqI7aPDvvqY5Uny5mBl3WHNMLLlp+lKZnGkHrAc1JWtuy+THKUVRvyltkoEFi8KNHjzaxNWvWYNnLlrXvi3Q+zUkSmJPhSWSkQ0Y81G4bN25sYvv27WtiJAYngxppemtR1mApyo80rui+yTygi0ETjemVK1c2MTKWoHJIiB6VTXUngTuVkzXOiIyzqM+pbKo7tRnN28jMhqCxQXWntqA5FpkZkJlC9D4Qcd5sWgdMtvDVwz9V0lslTdpgPSDpbZ1KNsYYY3qM86MxxsweUr8iLKXML6VslnRE0sdqrZ+VtKrWelCShj/b12djjDFmDuP8aIwxs4PUS02t9au11rsl3SDp3lLKa7IFlFLeWUp5uJTycPQ1GGOMMaaPXKz8mP3qpzHGGKbTl7lrrROSPiHpLZIOl1LWSNLwZ7uD1uCc99ZaN9VaN2W1D8YYY0yfmG5+JA2KMcaYPOc1CiiljEv6cq11opRynaRvlfTLkj4s6e2S3jP8+aHEtRphE4kWI+EsiZ2yu58SkUjrYkPiPap3JJinepIwf//+/U2MhIckojx+/DiWTULBO++8s4ndfffdTezjH/94E/v1X//1JhYJwUiol4V2EyaDBGozicWVNP7oRZ3aLBKOZ80vqI3uueeeJvbmN7+5iUUPS5/5zGea2J/8yZ80MfoNctYgIYKOpTaiuRMJO7P1oXKyws7s7tHRmJ6O4YiZfVzM/EjQWhKNf8opBJ1Pay2NS8rXEq8xVB9aL+lcmidRjqK8OT4+njqf8uPBgweb2KlTp7BsWmNItH7TTTc1sa1btzYxMvuJdl+n9qW1mowPyASFzF8OHDiAZdN903MKHUd1jJ75VqxY0cQoj9P90LlkchTNp127djWxzZs3NzESt5MQnnLZiRMnsGw6lp5pKA9TP1DOi55Jss/UNJfp21g0P6PcnDXnORcZ97M1kh4opczX4JOdD9RaHyylfFrSB0op75C0R9IPdCrZGGOM6TfOj8YYM0s470tNrfULkppfCddaj0tqfy1sjDHGXAE4PxpjzOzBGyQYY4wxxhhjeo1faowxxhhjjDG9JqOpuWicPXu2EYlld/KW8mInEhaR6DErTI7I7spLQik6LtrhldqIBJskEKOyP/GJTzQxEv9L0oYNG5rYo48+2sRIGPcTP/ETTezIkdYE6Ld/+7ex7OxuudQWJEakMRDtkE2iPNrll8YqiXujMX3LLbc0sR//8R9vYjt27Ghie/fubWJLlixpYkuXLsWySeBIgmFqSxIJ0nyKbGrpWGqjrPiU5lPU5tl5S+OPzo2EvASNXxsFGGkwrkfHUtbUQuK5QmsRxbLrXWRmkzX+yOYtmmeRuJjWMRIs09pG1/z0pz/dxG644QYse+PGjU1sz549TezGG29sYt/6rd+aquPOnTuxbKo7rfXUD7RmLV68uIlFayiNF6o7HUfjL8pRr3rVq5rY3/gbf6OJkeCeciaNFaqjJG3fvr2JkbEEXTNrILRo0SIsm/Lm6dOnmxj1Lc1bIupbIpuvsyYkEVnjg3PhT2qMMcYYY4wxvcYvNcYYY4wxxphe45caY4wxxhhjTK/xS40xxhhjjDGm1/ilxhhjjDHGGNNrZtT9TGqdvLo4/2Tdq8jJiGLksEIOFRK7P1DZ2fvJOrRJ7DKRdRqhch555JEm9vu///tY9g//8A83sfvuu6+JjY2NNTFyWFm1alUTu/3227FscoOjfiCnEWqzo0ePNrHImYPGBjm8ZesTOay88Y1vbGLf+Z3f2cR+4zd+o4m95jWvaWLLli1rYk888QSWTU50N998cxMjJyGKETT+Imj8Z2PZ+d2lTuQ6mHVrjMqmeHSsubKYN29es05k18DoWMpR2ZxJ45LcyyTOm+SURo5dtJaQg1OUm2n+URuRwxa5TD399NNN7MEHH8Syv+M7vqOJrVu3ronR+k/5keq9YsUKLPumm25qYuQCRv1AbXby5Eksh6A+o3FFY+j6669PxSRp/fr1Tey1r31tE/vMZz7TxMjRldxtt27dimUfOnSoiZG7KD0XZF1wo7lM45LaMjo/c9yCBQvwWKo75T06juY35evIeY3K6Zof/UmNMcYYY4wxptf4pcYYY4wxxhjTa/xSY4wxxhhjjOk1fqkxxhhjjDHG9JoZNQqYN2+errnmmpfFugh8R8+dvOYoJEwigRiJmroIm6nsq6++uollBV5Un+j81atXN7HTp0+nyiGB2J/+6Z9i2ceOHWtiJFwkod/GjRub2L59+7AcgsSIJDBbvHhxE1u0aFETI2F8JHinviBBIIkrSRAYifJI2E91+rEf+7EmtmXLllTsU5/6FJZNfbt8+fImRgJQMkMg4Ws0prvMsws9N1pHIpHixTwuKpvaIxJAmyuLWmuzXtPYisY/5Ueau5QTKD9SLiMBs5Rfq+maVB86juoYlUNrddbMgHLZ5s2bsexTp041Mcp7O3fubGJkKLBnz54mFq0l2WcIWqvp2YVMc6L8mM0J9ExCYnvqB4nH2+HDh5vY3Xff3cSozQ8cONDEdu/ejWVnx3RWHE/5MTIqyuYEmvNZUyuKSXw/WYMbumbWZEDiOd71WcGf1BhjjDHGGGN6jV9qjDHGGGOMMb3GLzXGGGOMMcaYXuOXGmOMMcYYY0yvmVGjAKkVUE1XrE+CQhJpkaiJyo52fidBVnan1KzgOBLlkfCLBN0kRCNuv/32Jnbw4EE89pOf/GQTo52Z16xZ08RIrEltQaJ+ie87a85AgjPapTrqGzqfdtOmMUB1jHj00Ueb2PHjx5vYHXfc0cQefvjhJkb9GIn1V61a1cSojchgYWxsDK+ZheqUjdFcpn6gmMRzOXvNrrsbj0Jr23RME8zcodbarDs0/qNdxGndIeFu1tgiu/5KLGzOiospRnWMyn7hhReaGOUoWlfpmrfddlsT2759O5a9bdu2JkZrKJmyUI6hHB4JurNmCAQ9a1B+i65HAn46lsZQZApAkHHCgw8+2MSoz3bt2tXEDh061MSi5y4aQydOnGhiNK7IbILGWtS+1BddTENGoZwXPfvQeKM5Sv0YjdVRIsORLnk8wp/UGGOMMcYYY3qNX2qMMcYYY4wxvcYvNcYYY4wxxphe45caY4wxxhhjTK+ZUaMA2jGZhGRdxLgkTJqOUQDtihtdM2tykBVpdRGNUYzE2ySMO3nyZBOLxFgkeKMYif1p598uu84vXry4iZEpAAnwqBwSp0ViObomCUAXLFjQxEh4GJkhbN26tYk9/fTTTeyhhx5KXZPEjV3ukWLZXYu7CPpontAcpeOonC47JpPAMbuTcVa4HQk4qX27CiHN3KSU0sy1rDmJlDekITMcOpd2O4+MdGjuUt2zJh1Zg5DomjSfszmK8mOX+6a6U31IBE85iowQJGnZsmUYH4XyEV3z1KlTTSxqc1rfsuMlMrogSIT/hS98oYlRzqTcTOYK0XyifE/tQeOPnuWoPpFpQjb30HFZsX4EPXdRjMgajkTzie6R+uFc+JMaY4wxxhhjTK/xS40xxhhjjDGm1/ilxhhjjDHGGNNr/FJjjDHGGGOM6TUzahQgtULZLruvk5gxKxrOCrwigW9WIByJ3kehOlJ9IkhQuHz58iZG4rQuAlAS5pP5AIlCSQhJ7RMJIcfHx5sYCeGpLbIC2+wOzBKPVWofErZFfUtxKofMGUj0SOM3EtpRu1MbUZvTfZPQtIsolOZ31mSD6kOxKJ4VJmePi9YRat8ua6AxkRA4O38oRnOCckc0n2kO0PpC55M5D82zaA2lNZzqQ/dIQm3KHdF9U+4hcfvExEQTyxoFRM8UK1eubGJd+mwUGj9kcBDFs+YM1F+RQRP1Ga2tdD7FqGzqGylvHkNQP1DfRmt/9jmS5gQ9y5HQP3rmozxOeStrdkXrFc2xiC7PEJI/qTHGGGOMMcb0HL/UGGOMMcYYY3qNX2qMMcYYY4wxvcYvNcYYY4wxxphe45caY4wxxhhjTK+ZUfezUkrjokDuD+S0EB2bPZ8cGOi4Lk4LVDa5rrz00kupc6P7JhcPuia5XJFrFsWo3hI7pZG7y8mTJ5sYOXNQP0ROH1QnctcgVxFy8CDHjchJiMYBuYVkHfCoHSVpyZIlqTqRCwy5ttAYiFxOsu5p5AJDZdOYjOYTjXVyIsrOZWqfqG/pfqK5l6HLudMpx8xt5s2b16z1NK4jt0hab2n+0fgntyZaCyLXouy4prKzrlCRmyGtt5Gj1SjUPrQuRjmK+uLIkSNNjPIW3WPWsUuSnnvuuSa2YsWKJka5+fTp002MckfkzkX9TQ5bBLVZlB/J0ZXag55Jjh492sRorFHekThvUhuRCxjdTxd3Ocpd2edfuh8a09QWEt8jPYvRWM26Di5btgzLpr61+5kxxhhjjDHmisIvNcYYY4wxxphe45caY4wxxhhjTK/xS40xxhhjjDGm18yoUcDZs2cbYRSJESl2rvgoJMiK6jNKJIyja07HKICEdlHZJAAdGxtrYpHobJS9e/c2sUhYSaIzKptEiydOnGhiJFiLxKfUHiQaI8EbtTmJPSPxKZ1Pon4SXFK9SbQosRiRhJS33357E1u6dGkTo/uJBIHU59Q/JFokI4Yu0HyiciiWNaCI5lN2nhBdDD6yZNc1M7c5e/ZsM/dprHYZL7S+ZMX6JASO1moyn6FjKUbzmeZZJCan80m0Tms6XZPWalrnpfyaRW1OuYzOjdZvOpbyNYmvs8YFZCAhcbtR7okMFkahZ5KoTtQelAsXLVqUKpueXSRuI5pP9MxHY4jmE+VbiccLlU15NGuw1MV4g+YtzSeCxmm0jmTPPxf+pMYYY4wxxhjTa/xSY4wxxhhjjOk1fqkxxhhjjDHG9Jr0S00pZX4p5bFSyoPDfy8vpXyslLJt+JN30zHGGGPmMM6Pxhhz+emiwHmXpKckTSrw7pf0UK31PaWU+4f/fvf5LjIqqiWh03SNAiIB1ChZ4aCUF+Znd63P7vQssZgsKxojQTcdF+3wSqJ1Ep2RuIzEoyTgJGGblBdg07gg8SjdN4n3JO4f2ml3urvbU/uSODPb5lQ29YPE4z+70zSNcxJ10jiN4tRGNDZonnQR/9MO2ySwpfGXFUdm1yApNjQwvWLa+bHW2oxjGhu0tkXQsTSuab3LCv27kM2PNM+isilO90hrRFZAHa1j2XWH6khrTpccRc8FlBOmY1QU3TfVkwT3tH6T4U70DED5iMrO1ofajOojcRtRfahvswZY0X1Tzs4+V9CYzD7HSWzwRGM1C+XbCBpv0fiPSGXTUsoNkr5b0m9OCb9V0gPDvz8g6W2dSjbGGGN6jvOjMcbMDrK/IvwVSf9I0tTXylW11oOSNPy5kk4spbyzlPJwKeXh6VipGmOMMbOQX9FFyI/021RjjDF5zvtSU0r5HklHaq2PXEgBtdb31lo31Vo3dfnY3BhjjJnNXMz8GH3VxxhjTI6MpuY+Sd9bSvkuSddKWlxK+R1Jh0spa2qtB0spayQduZQVNcYYY2YZzo/GGDNLOO9LTa315yT9nCSVUt4k6WdrrT9cSvmXkt4u6T3Dnx86b2FXXdWIskiMFe1CS19fywqJqZysmEuSjh071sRox1oSwpPwisR70SdZJEQj8dWaNWua2OrVq5sYCdHp/iQWmJGpAJVN4lMSfdFxEov/ssdRf9N9U9+cq06Za2brI7E4MysgJaEfjd+oHbNmE1lTCxI3dtkNmMrJxmgdiNqc6kT9QG05HfOKi3GsmV1czPxYSmnmPs3HaE7RekDzlPJMJFgeJRLrU56gdYxilAspv0X3TXWnXedXrFjRxMgAiHJUtIaSGJ1yApVNaw6VHQmtad2ga5IQntbqpUuXNrGJiQksm6B1mcqh9onyLfVt1liCDG6ov+g5LiqHxi/NsayBUHTfNJdpjtE1qY40H6JnHzqf+oz6JvsV2i5rGPXjuZiO7c57JH1bKWWbpG8b/tsYY4y50nF+NMaYGaaLpbNqrZ+Q9Inh349LevPFr5IxxhjTL5wfjTHm8uINEowxxhhjjDG9xi81xhhjjDHGmF7T6etn06XW2oiLSNgWiXGzO8mSEJIEVVQOCf0lFphldx7es2dPEzt8+HATi4wCSDy1fv36JkbCQaoj3WMkFM2K27LCfConEp9mzRSyQlFqHzI9kKRTp05hfBRqSxJHdiErDs6aB0T3QiJQOp+EgyR87SJAzpoPZI0CiEiAT2sOQXXPivptFGC6Umtt5gDNqchIJytOpvFP59I8W758OZZNazgJsGms79u3r4nROhTlCVrraV2m82mHeWrzKDdTjqM2JwOArIX3mTNnME7rP63VVHdqX+pvMlKQWLxN6zeNAWqzaE0mkwRal+l+KA/TGDh9+jSWTe1BbUnXpHaj60VjOls2jTV6bqLn18j8Irtm0DpEZVM5dFxUTtf9u/xJjTHGGGOMMabX+KXGGGOMMcYY02v8UmOMMcYYY4zpNX6pMcYYY4wxxvSaGTcKiARCU+my+3pW1JcVWkdCSBJa0bEkUCTx3t69e5tY1DZZcSWJzkhESUK9CBL6Ubtld1+n2MqVK7FsEv9R39I9HjlypIlR+0QCRRIjkhCSzicRPY0BicV2dE0qm8Sn2VgECRQjYfIoWaF/dCz1N/VDNhYJ8GkMZg0JsjuvdxH/R+udufIYHV9ZEXwEzV0abzT36NxoHSNoJ3vKJySYP378eKo+Etf94MGDTYzE7dn2icia4WRF/URkKJB9pqFyMs9hUtwWFKf6UPtE5gNEZNAwCvUttQWZB0Q5iq5JuZTuMfvsQ20WQTmT1ge6Hzouevah82kMUY7LPitE0DW7Gun4kxpjjDHGGGNMr/FLjTHGGGOMMabX+KXGGGOMMcYY02v8UmOMMcYYY4zpNX6pMcYYY4wxxvSaGXU/K6U07hFZFySJ3SzIUYLcR8iVgY7bv38/lk2uLXT+woULm9idd97ZxNauXdvEyLFFYgeQr/3ar21i1D7kzEFObs8++yyWPTEx0cTIAYScNOg46q/IcY76jJxgyK3j6quvbmJLly5tYuQKIrHjBrmh0P1Q+0blZN20li1b1sTIIejkyZPpsqnu1L7kfEJ9Q2VH90d9Nh3nky7uZzQuqT5ZR6is818Up3lrrjxKKc1aT/nx1KlTeD6teXQ+rYMvvPBCqo7Hjh3DeHZtpbm3cePGJjY+Pt7ETpw4gWVT7rnxxhubWHaNoHWe1lqJ1/oubpOj0FobuYWRmye5e9E1qc3oGSfKHadPn25iNNayROVQnNZlWlcpH1HfdnETJNc4cjCjtujSPpSPsk5pNJezuV7i502aO1Qf6hsaa5HjXNbh+Fz4kxpjjDHGGGNMr/FLjTHGGGOMMabX+KXGGGOMMcYY02v8UmOMMcYYY4zpNTNqFCC1gqUu4uCsSDcrviZIfCdJS5YsaWIkGjtz5kwTu/nmm5sYCaJIlC/lRWdUHxJu0T3SuRILzEh4SMdlRd4kcI3OJ1E1CTOpv0jMGrU5nU99S4JJEpVGwjgSwWXNEEgQSLGo7EjMnjmfxm8XwTyJDGneZsW92fpE0NqSNTOge+xiFJDtBzP3yYyFyEiH1lFaqyl30LimcsgIR2JDGoLmMwnUaQ2MhNaUz6icrOic1nkyBIjOpzU9ynGjZM1xojiVQzmBjlu9enUTiwT8ZO5DbbR3795ULCJrVETzhp5p6H7IPECKDYxGoWeSrDkD9beUn080J6hvaX5HZdP4pbrTHKN6U5tHpgd0P13zoz+pMcYYY4wxxvQav9QYY4wxxhhjeo1faowxxhhjjDG9xi81xhhjjDHGmF4zo0YBtdZGCERio0gYRGIlgkRIJGCi2A033IDXzAr9SEhJ595yyy1NjHZRlqTDhw83MRKxkWidyibxXSSYP3LkSBPL7r5OAjrqw0g0RkI/ErfRPZL4j46LBKAkRqR6UltkBXQS7wBNQj2qz2233dbE1q1b18QicS8J+GjHcNrJm8Sn0RgiqB+pv0k4GBkfjBKtF1lzEVqHsmtQF6MAYyYZnRc0T6IdtrM7rdM6RmJ9OpfWK4nXeionawBAa3WUmyk/Uj3JwIXqSHk0ElVn8yOtL2RwQO1DonOJ25xiNC7oHilHRcZJVM501uXIBIKec6g9qH1pnqxataqJRfkxMk8a5eTJk02McgzlR8qjUv4ZgtqSnn1oXHW57+yYjowlsnR5H4jwJzXGGGOMMcaYXuOXGmOMMcYYY0yv8UuNMcYYY4wxptf4pcYYY4wxxhjTa2bUKKCU0gibsruXSvkdx+l82iGehPmROIwE1ERWxEaiRxJ+S7wDL4m8SPQ4NjbWxHbs2NHEtm7dimXv3LkzVQ7Vh8R/JDDMmjBI3D8kZqT+IrE9CWQlFvqdOnWqiZHgkuoYjWkS4ZN5AY0Xqs/u3bubWCQsjuKjUD9SbNmyZU2M2jE6n8ZGds6TmJCuF9WJhJDUZ9H9GDNdSinh7vFTiXIUCcKz+ZHWb8qPkRic1iIqmwT8VJ/bb789da6UX3c2bNjQxKi9yXiA1nmJhdF0P5TjqC2p3lF+pDWU1nSKZQ1YqG2jY8k0gdqnyw7zJHqn3E5jldqSzCIicTvdI809Op+Oo/G7ePFiLJvmI903GQ1Qf3dpcyqb1haa8wSZbJw5cwaPpbkT5fEIf1JjjDHGGGOM6TV+qTHGGGOMMcb0Gr/UGGOMMcYYY3qNX2qMMcYYY4wxvWZGjQJqrY1oiIT1XXbQJWERCRRJuLVnz54mlhFqTkIiLxJAPfnkk02Mdn4nIaMkrVmzpolld/QlMdidd97ZxCLR+Ic//OEm9thjjzUx2i2XhPnUvpFoLCvAi3YjHoUMBSLRLYn6aOdgqiOJ+iOjALomiR5JCP91X/d1qXOj9iVTgV27djUxal8yMyAxLY3zCKonjUuad9S30W7NJLylNYMg0SP1bbQLMp0f7VZurizOnj2L82qUKEfRjuM0tmg+0zpIhjKRsQqt9VTOoUOHmhjdM4mV77jjDix76dKlTYzmH9WH2vKWW25pYpFByObNm5vY008/3cSyRiSUryMhO61jtAZTOfSMRWVH6xhdk8qmNX358uVNLMrDtK7T+k/j78Ybb2xiq1evbmKR4J1MfKielDtovJDYngysJG43ymfUjzSmV61a1cSivENtTvdIawGdmzUmkfJr07nwJzXGGGOMMcaYXuOXGmOMMcYYY0yv8UuNMcYYY4wxptf4pcYYY4wxxhjTa2bcKIDEUnQckTUVIHFxdhfxaPdSqjeJuUjoRCIr2h2WdjKWeFdfEvBRW2SFoiSOlKTv//7vb2IkRPvIRz7SxKjNqX0jIRgJ40iIRv1IwkES5UXjMStuy4rqIsEltSWVQ/34hS98oYnRWCGRoMQC2/vuu6+JUVuQWQQJTcmMIDqW+vHZZ59tYjTOyWQjEv+TMJnGQdaAgtonMoagOWGjABNB60u0ZtE4ojWP5j3ttE7Xi3ZAzwq6ae7SrvG09tNxUl4IT8fRswKt1bfeeiuWTe1LZT/++OOpcrJmSFJ+zSJDAaojCfjJMEfi5xe6ZiSEHyVaAykXkkCd1lWqI42hyPyC2m39+vVNjO5727ZtTYxyPRkFSdy3NA4OHjyYOo7qHa0jNPfomtnxR893kVEAPQNQP5wLf1JjjDHGGGOM6TV+qTHGGGOMMcb0Gr/UGGOMMcYYY3pNSlNTStkl6TlJX5X0lVrrplLKckl/IGmjpF2S/latlb8gaIwxxsxRnCONMeby0+WTmm+utd5da900/Pf9kh6qtd4m6aHhv40xxpgrEedIY4y5jEzH/eytkt40/PsDkj4h6d3nOmH+/PmN80oX5x9yuCCHI7pm1qkhcoQgd5esuxc5rBw6dKiJ7d27F8tesWJFEyOXCHLXoLYg17bIpYRcX77ru76riZGbBTlknT59OlUfidty7dq1qeOyznbkkBLVk5xTaAzQuCJnGUm66aabmtj4+HgTe/7555vYggULmhiNoS9+8YtYNjmaUNl33HFHE/vu7/7uJnbgwIFUHSXps5/9bKo+r3/965sY9Rnd95o1a7DsEydONDGaJzSGyLGInNwixyIicmkzveeCcuRUaP5E44VchiYmJpoYuTWRAxSNYXJGknhe0LpO84zmD60l5NomcY6icugeKd/Tmk45XGLXRbofWv937NjRxKjNaO2X2OGT7pHajdY2gpwiJenUqVNNjJ4/xsbGmhiNocgNi+pOzyrUZzQmKXdEDp3URtS+GzdubGL33HNPE4vakiD3NBpXd911VxPbtWtXEzty5EgTW7lyJZZNz7r0TEPObTR+qW+jZz4aQ1kX0kmymbdK+q+llEdKKe8cxlbVWg9K0vAnt5Axxhgzt3GONMaYy0z2k5r7aq0HSikrJX2slPJ0toDhAv9OKX4bN8YYY3rMBeXIqfkx2hPEGGNMjtQnNbXWA8OfRyR9UNK9kg6XUtZI0vBn+/nW4Jz31lo31Vo30cfexhhjTJ+50Bw5NT/SVy+MMcbkOe9LTSllYSll0eTfJX27pC2SPizp7cPD3i7pQ5eqksYYY8xsxDnSGGNmB5mvn62S9MGh6OoqSb9Xa/1IKeXzkj5QSnmHpD2SfuB8F5o/f34jtCJxY1bEJrGIiM6n40hMSOI7KV/PrODy4MGDTezJJ5/Eskkcv3r16iZGYjkqu4sAlISqJIxbtWpVE7v33nubWBeDBBLEUn1ItEhCUxKnRQJQMhXIGjGQ0C4SzNN4oU80s+J4Git33303lk3XpPFP4+WP/uiPmhgJ8L/ma74Gy/6+7/u+JvbUU081sS984QtNjNpy/fr1TYzGhcTzJDt3SHyajUV0MRUws5KLkiNLKc26kxXeSvz1NVrfaH2h8UrCZlqvJM6P0fwbheYzmbLQmi6xGJ1E0FdffXUTo/WO8nqUJyh+8803NzHK13feeWcTO3r0aBMjswcpbxZEeZSMcEiIHpVN5ZAZAo21Lu1LY53GOQnhjx8/nqoj5UyJxz+NVar7li1bmhg980UGQmQ0sHPnzib2zDPPNLHFixc3MZoj0fzMPj9HfTYK9VdUNo1VGgM0TyY570tNrXWHpMZiodZ6XNKbz3e+McYYM1dxjjTGmNmBf0VojDHGGGOM6TV+qTHGGGOMMcb0Gr/UGGOMMcYYY3pNIYHspWJ8fLyOCoSzO/pKLGYkoXZ2B1ISxkVGASRgonJIFEUCRRJpRzsm33fffU3se7/3e/HYUUiETPUhYXwECcmoH0kkSMdFu8vSsSTCJ9EYCdFI2EZiQomFhwS1BQn6IsElQaYNZMRA90NGDNGYHh8fb2Ik9t+zZ08TI9EjiSi/+MUvYtk0Bl/72tc2MbrH/fv3NzHqRxIvS9xnWfOAS2EUQDz33HOP1Fo3TesiplesWrWq/tAP/dDLYpTfaF2UeJ7T/KG1nuYE5ccoN2dNAbJ71dE9RgZCtKs6mdRQW5Komo6L6k11yhp/UFtmjWeiY+mZhPJJ9tmFxPISr7fPP/98qhzKHdFaTc8GdOySJUuaGD2zUb2j/qKxQfmV7pueAeh56PDhw1g29RkZUFDdaUxmn5skbnO6RzI5oDWIxnk0pmltolx66NChMD/6kxpjjDHGGGNMr/FLjTHGGGOMMabX+KXGGGOMMcYY02v8UmOMMcYYY4zpNefdfPNyEIlsSRRFYjkSiNE1syIriUWTJMKka1KMzo3Ecrt27WpiJESjXYtJQEdtRjGJxW0k8iZhJ4ndqG+iNs8KNqlvVqxY0cRIxLZmzRos++TJk02M+pHu56abbmpikXkFjUvaTZtMJEice8MNNzQxEtZL0ic/+ckmtnfv3iZGgkAS+tEu1Zs2sdadBJJPPPFEE7v11lubGO0ATe1LfSPxeLvYYv+ZNGAxc4fRNY/GIK3JEo85WqtJCEzl0HpJQmmJ8wzlBLomiYNpHYqMdGitJnMTWhspd1D7RmYrZI5CbUmC+6xRQGQMQfmIxO3Lli1rYrQG0lihc6M43Q89A9C5lPOiOlHuoT6j48iwJxrTzzzzTBPbvXt3E8vmEzIfWrRoEZZNbUTPgRs3bmxi1BZkkBCVTW103XXX4bGjkAEWzRGKSWxIQGPgXPiTGmOMMcYYY0yv8UuNMcYYY4wxptf4pcYYY4wxxhjTa/xSY4wxxhhjjOk1M2oUMH/+/EacRMKgSGSbFeuT8JBEw1kRZVQ2xbI7M4+NjWE5BLXRk08+2cRInBYJskaJxPrUltTmtBsxQXWcrqCbhHFkunDixIkmRn0jxcLQUah9aOffaEdqOp/6m8SM1D4PPvhgE3v88cexbGo36osDBw40MTKloOuRoYXEot8bb7yxiZFYk8Yfzaeob0mMmzUKmI55QMSluKbpH1dddVVjcBKtywSN66wgnATdJFAn0xApb4ZDImQ6jtaXSDBPO6OT0JqE0WQoQ88AJPSXpPHx8SZG6yC1G/UDGZ5EzyTUHtSWNC7ofkhYT/kpKofOp3FB5jx0PYnrTvmRcjuNtUcffbSJkSmFxPdDZdPcoTFAbUllRGzYsKGJ0XMBjSEqOzKmomPpeYiMgWje0TglkyMpztld8Cc1xhhjjDHGmF7jlxpjjDHGGGNMr/FLjTHGGGOMMabX+KXGGGOMMcYY02tm1CiglNIIqEhEdCl2tyfBJAmiIjFitIvzKCQko7Jp518S1Um82y7tEEuiMRIokggzEgSScJzaiI6jGO1MG4nop1MOCc6onEiIS/2TFXRTP5J4T5IOHz7cxEiYT6K+rVu3NrHNmzc3MRorEgvzyfCB6rh9+/YmtnbtWiyHIGEnlU3iSKoPjf1169aly6Y+mylTgGjemyuP0fFB+S0S2dKxZBRz8ODBJpY1ronWsekIielcynnRcwHdI63r1G601lLOjHZfJxE/GR1RPqL7oXuJdlSn9qU8QWsO5XsqJ8qPWUOC7HNTZIZAuWvPnj1NjJ67KEc99dRTqTKk2BRjFGpzMmJYuXJlE4ueN2lOUN6KDBZGoTrSM47Exgc0DmhOZM1KoufNrBnYuXA2NcYYY4wxxvQav9QYY4wxxhhjeo1faowxxhhjjDG9xi81xhhjjDHGmF7jlxpjjDHGGGNMr5lR97OzZ882rhDk8hCRdQki9xGKkasCOYNJ7B5BTg9Lly5tYuTo8OKLL6auF0HOJ+RMQ9ckZ5nI6Yn6h2LUvnRNcvuIyqa2JGeOrPsZOZJEZWdd36gtqR/InUuSPve5zzWxz372s02M+pvKJheZyGmEXJBojpHLyZIlS1J1JEcziV1xsmOarknOPVu2bMGy169f38TIPSc7Xmg+0PyWeFxFLjTmyqLWmsoBkRMXjbmTJ082MXJhorFOc5zGr8RrDM1Tcj87cuRIE6P5SOdKPCdpHaS1LbqfTH0kzjPZZwVaNyi/Re5n0Ti4mGVH7UP5no6lcUVuWJSLJHbzfOSRR5pYNheSA150j+SKRvdN0Jik9qVnHCnvIkb3TcdRfx89ehTLXrVqVROjtqR7pLLJ8TZyu6P77pof/UmNMcYYY4wxptf4pcYYY4wxxhjTa/xSY4wxxhhjjOk1fqkxxhhjjDHG9JoZNQqotTZi60jETJDQj4R6JPzKCrxI5BfFSdTURQifhe6RhHVjY2NNjERfZJAQCbqp7tm2JOEq9SHVR8qL5abT37t378Y49Te1OYkJ6biJiQksZ+vWrak6LVy4sImR8JCE9RFZcweaozQmKUZ1lLjPsmtB1gwhEhbTGKJxSdekMUn3kjU1ic43Vx611ma+0NoYrW00jkhMTmsbjXVa2yjHSJz3yGiAxMmUJ0hAHZkokFiaxMkHDhxoYiSgpnpHhkbZZxJac+i+6Vy6F4kNBGj9pjpm83okJqc1+PDhw02MjALIvILOlaQnn3wydSy1RdaMKVp/6VgyuKGyKV9nzYsk7h+at9S3NF7I6CIymqCxSrmUrkltTmsLtU+Xa54Lf1JjjDHGGGOM6TV+qTHGGGOMMcb0Gr/UGGOMMcYYY3qNX2qMMcYYY4wxvWZGjQKkVoyW2UE5OldiQRVdk87NisklFmRlz8/Wh4RkUdkUIyEZifJICBntWpwVjlN96JokZO+yuyyJ+kiMvnfv3iZGosN9+/Zh2XTNZ599tomRiG3nzp14TYJ20yamY5oQCfCzcy8770jUHAkh6ZoLFixIHUfXJHFkl53Xs2YINH6pHaM2z+7CbK48zp4924wvGlvRWk1mL1mzFjIyueGGG5pYZERCc5+MBmjukviayiFDAEm66aabmhit3zQnqd50bmQUkDUdyT4DUH9FbU73Q9ckEwcyANizZ08Ti9ZvGi+US+n8Q4cOpcuhY4nI4GmUyJSIoHFA+ZXGBp1LYyAaVwTN79OnTzcxGn/0zBc9d1E5lAup7rQ2ZeeIlF8LzoU/qTHGGGOMMcb0Gr/UGGOMMcYYY3qNX2qMMcYYY4wxvcYvNcYYY4wxxpheM6NGAbXWRizVZYdXgs4n0dh0djCX8juoUzkk1KNYl/smoRWJDEkM1kW4RfHp7MhO9xjtGJvdeZhijzzySBP7zGc+08Qicwa6R9qRmna+pnqT+C4ie00ShWYF7xFdjDsy5URjmtqXys4aJJCYMBIY0twjAWkkyB6F7jF7rjS9Njdzi4xpRDS2smLpEydONLHsjuFk5iGxiJ/E0mNjY02Mxj/lrdWrV2PZWdMdWg/oHpcvX566nsQ7o2fF+gS1GdUxOpb6gcTk27dvb2JkhBNBOZtE/ZSPKF93efYh0TvVh0xZqJyobOpzKofmHRnXZJ8No/PpGYLWCxov1BaRkQ6dT21B85b6hq4XGSTQHO1i6CX5kxpjjDHGGGNMz/FLjTHGGGOMMabX+KXGGGOMMcYY02tSLzWllKWllD8spTxdSnmqlPKGUsryUsrHSinbhj/bL+UaY4wxcxjnR2OMmR1kFcS/Kukjtda/WUq5RtICST8v6aFa63tKKfdLul/Su7tWgMRTkTCI4lnRcHbX70gQSEIrOj8rTssKpaX8zsNUDglA161bly67i7AuA/XNqVOn8NgnnniiiX3uc59rYnv37m1iJEakXZSjHYbpHkmEmTUAiMZ0VgifFeGTYUNkApEV4FE5VG8ak13mMokmaT6RiJKOi3Ygp7bMGl3QcVR2lzafznwys4KLlh9Hx2ZW8B5BawmJ/UnsTMdFu5BTncbHxzNVxHNp7kX3fezYsVQ5dI9kCtDFVIjmPq2DtB5QfbLHSZz3nn766SZGeY9yLpnRRPdNazVdk8YQ5Q5a0yUev1QnOj8yIMqSnXtZQyRqs0gwT+OKDB8IMgCg60XQM1F2TNNx1157bROLxlXWNORcnPeTmlLKYknfJOm3JKnW+he11glJb5X0wPCwByS9rVPJxhhjTI9xfjTGmNlD5utnN0s6Kuk/lFIeK6X8ZilloaRVtdaDkjT8ufIS1tMYY4yZbTg/GmPMLCHzUnOVpNdJ+vVa6z2SzmjwUXqKUso7SykPl1Ienu7HgcYYY8ws4qLlR9p3xBhjTJ7MS80+SftqrZ8d/vsPNVjED5dS1kjS8OcROrnW+t5a66Za6yb6bp0xxhjTUy5afox0BcYYY3Kc1yig1nqolLK3lPLKWutWSW+W9OTwz9slvWf480Pnu1YppRFGkVAqEs6SyDYrzCeBFwmdorKzpgBZQ4FISJyFdp0nYdvx48eb2DPPPNPEIhHmhg0bmhiJK+mFla554MCBJrZ582Ysm0wBtmzZ0sToN5wkdlu8eHETi3ZrzuzsLbGILTv+IkhQSH1LdewiOr/YonUStEYGFHQ/VB+aO9GO6qNEAsOsaJLmKJU93bkciSbN7Odi5sf58+c3axTNn8h8g74Jkd2FPGuuE62Xq1evbmLZeUb1oXpHgvmxsbEmRnWnHEXi6507dzax6L5XrFjRxEgcn11XDx482MR27NiBx1I9yTxgYmKiiVFb0NoW3TfdDz3L0Vjt8sttOpbqlB3n2bwu8ZzI3iNBOY9yvZQ3U6DjqI40d7q0BV2TjHjofrJzUeK2XLhwYRMj84tJsu5nPyXpd4fOLjsk/ZgGn/J8oJTyDkl7JP1A8lrGGGPMXMH50RhjZgGpl5pa62ZJm+C/3nxRa2OMMcb0COdHY4yZHUzvexPGGGOMMcYYc5nxS40xxhhjjDGm1/ilxhhjjDHGGNNrskYBF4VSSuOIQs5BXdyEyGGFXCbIgeFSuJJRfciJi4jKJleStWvXNjFysyCnkG3btjWxaA8hqju5UZAzB7mSbd26tYn9+Z//OZZNLm3PPfdcE6P+JncWap/ovsmFg8qhe6RzI5cTchXJjksa09lYdM2skwu1b/ZciduS2iLr8EbzLrLIzToR0TVpLmZdnqS8w5u5MhkdHzRPIhcwcsQk6Hxyejp16lQTu+WWW/CalCeonBMnTjSxbC6L8iOVvWrVqiZG90jlHD58OHVuVPaiRYuaGK0btC6TOyi5nEnslEZubtn1hXJh5H6Wda8khywaF1HuyK6t2TxM/U33EpWdfT6kcUHXi/amyjp8Zt04qezo2YfyJuVMKpvanOrTxXkt6p8If1JjjDHGGGOM6TV+qTHGGGOMMcb0Gr/UGGOMMcYYY3qNX2qMMcYYY4wxvWZGjQLOnj3bCM9IgBSJsbLCLRL1ReLKURYsWIDxrDA6K8ojkVV0Lh1LAjNqn6zQOhKsUfzMmTOpa+7du7eJkRCSxIQR1N8keKO+oTHQRQhJ/RCdP0oXoSm1ZVYslxXBS/n5lDUAoHuJ7pvu59prr21iNP6ov7PGA1I3oeooNEez8y4qx0YBRhoIx0+ePPmyGM3HKEdNZwzTnFq9enUTi3Izid6pPsuXL29itGZRTqBzJa47rTsUo7Ygg4Ro/aWyac2i9YBME7KCd4nbnMqhGN0j5TLK9RKv1dQWkRh9lOj5I2sElV2X6dwuazWNVRpX2XwU5evs80fWvIjm7fXXX49lU36k/s4+k1D7djEVigx/IvxJjTHGGGOMMabX+KXGGGOMMcYY02v8UmOMMcYYY4zpNX6pMcYYY4wxxvSa0kWwM+3CSjkqaffwnyskHZuxwi8tc+leJN/PbGYu3Yvk+4m4sdY6fhGuY3rCHM6P0ty6n7l0L5LvZ7Yzl+7nkufHGX2peVnBpTxca910WQq/yMyle5F8P7OZuXQvku/HGGKujaO5dD9z6V4k389sZy7dz0zci79+ZowxxhhjjOk1fqkxxhhjjDHG9JrL+VLz3stY9sVmLt2L5PuZzcyle5F8P8YQc20czaX7mUv3Ivl+Zjtz6X4u+b1cNk2NMcYYY4wxxlwM/PUzY4wxxhhjTK+Z8ZeaUspbSilbSynbSyn3z3T506WU8r5SypFSypYpseWllI+VUrYNfy67nHXMUkpZX0r576WUp0opT5RS3jWM9/V+ri2lfK6U8vjwfn5xGO/l/UhSKWV+KeWxUsqDw3/3+V52lVK+WErZXEp5eBjr8/0sLaX8YSnl6eEcekOf78fMDpwjZw/OkbMf58jZy+XIkTP6UlNKmS/p30n6Tkl3SPrBUsodM1mHi8D7Jb1lJHa/pIdqrbdJemj47z7wFUk/U2t9taTXS/qJYX/09X5ekvQttda7JN0t6S2llNerv/cjSe+S9NSUf/f5XiTpm2utd0+xdezz/fyqpI/UWl8l6S4N+qnP92MuM86Rsw7nyNmPc+TsZeZzZK11xv5IeoOkj075989J+rmZrMNFuo+NkrZM+fdWSWuGf18jaevlruMF3teHJH3bXLgfSQskPSrp6/t6P5JuGE76b5H04DDWy3sZ1neXpBUjsV7ej6TFknZqqEvs+/34z+z44xw5u/84R86uP86Rs/fP5cqRM/31s3WS9k75975hrO+sqrUelKThz5WXuT6dKaVslHSPpM+qx/cz/Ch6s6Qjkj5Wa+3z/fyKpH8k6eyUWF/vRZKqpP9aSnmklPLOYayv93OzpKOS/sPwqw+/WUpZqP7ej5kdOEfOUpwjZyW/IufI2cplyZEz/VJTIGb7tctMKeV6SX8k6adrracvd32mQ631q7XWuzX4Dc69pZTXXOYqXRCllO+RdKTW+sjlrstF5L5a6+s0+GrNT5RSvulyV2gaXCXpdZJ+vdZ6j6Qz6tfXAszsxDlyFuIcOftwjpz1XJYcOdMvNfskrZ/y7xskHZjhOlwKDpdS1kjS8OeRy1yfNKWUqzVYrH+31vqfh+He3s8ktdYJSZ/Q4Lvdfbyf+yR9bylll6Tfl/QtpZTfUT/vRZJUaz0w/HlE0gcl3av+3s8+SfuGv+WUpD/UYAHv6/2Y2YFz5CzDOXLW4hw5u7ksOXKmX2o+L+m2UspNpZRrJP0dSR+e4TpcCj4s6e3Dv79dg+/dznpKKUXSb0l6qtb6r6f8V1/vZ7yUsnT49+skfaukp9XD+6m1/lyt9YZa60YN5snHa60/rB7eiySVUhaWUhZN/l3St0vaop7eT631kKS9pZRXDkNvlvSkeno/ZtbgHDmLcI6cvThHzm4uV46c8c03SynfpcH3IOdLel+t9ZdmtALTpJTynyS9SdIKSYcl/VNJfyzpA5I2SNoj6QdqrScuUxXTlFLeKOlPJX1Rf/Wd1J/X4DvDfbyfOyU9oMHYmifpA7XWf1ZKGVMP72eSUsqbJP1srfV7+novpZSbNfjNkzT4WPr3aq2/1Nf7kaRSyt2SflPSNZJ2SPoxDcedeng/ZnbgHDl7cI7sB86Rs5PLkSNn/KXGGGOMMcYYYy4mM775pjHGGGOMMcZcTPxSY4wxxhhjjOk1fqkxxhhjjDHG9Bq/1BhjjDHGGGN6jV9qjDHGGGOMMb3GLzXGGGOMMcaYXuOXGmOMMcYYY0yv8UuNMcYYY4wxptf8/9LC3OwQlR4AAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1080x2016 with 8 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "Xred35 = perform_PCA(X, eigenvecs, 35) # reduce dimensions to 35 components\n",
+    "Xrec35 = reconstruct_image(Xred35, eigenvecs) # reconstruct image from 35 components\n",
+    "\n",
+    "fig, ax = plt.subplots(4,2, figsize=(15,28))\n",
+    "ax[0,0].imshow(imgs[0], cmap='gray')\n",
+    "ax[0,0].set_title('original', size=20)\n",
+    "ax[0,1].imshow(Xrec35[0].reshape(height, width), cmap='gray')\n",
+    "ax[0,1].set_title('Reconstructed', size=20)\n",
+    "\n",
+    "ax[1,0].imshow(imgs[15], cmap='gray')\n",
+    "ax[1,0].set_title('original', size=20)\n",
+    "ax[1,1].imshow(Xrec35[15].reshape(height, width), cmap='gray')\n",
+    "ax[1,1].set_title('Reconstructed', size=20)\n",
+    "\n",
+    "ax[2,0].imshow(imgs[32], cmap='gray')\n",
+    "ax[2,0].set_title('original', size=20)\n",
+    "ax[2,1].imshow(Xrec35[32].reshape(height, width), cmap='gray')\n",
+    "ax[2,1].set_title('Reconstructed', size=20)\n",
+    "\n",
+    "ax[3,0].imshow(imgs[54], cmap='gray')\n",
+    "ax[3,0].set_title('original', size=20)\n",
+    "ax[3,1].imshow(Xrec35[54].reshape(height, width), cmap='gray')\n",
+    "ax[3,1].set_title('Reconstructed', size=20)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Most of these reconstructions look pretty good, and you were able to save a lot of memory by reducing the data from 4096 variables to just 35!\n",
+    "\n",
+    "Now that you understand how the explained variance works you can play around with different amount of explained variance and see how this affects the reconstructed images. You can also explore how the reconstruction for different images looks. \n",
+    "\n",
+    "As you can see, PCA is a really useful tool for dimensionality reduction. In this assignment you saw how it works on images, but you can apply the same principle to any tabular dataset. \n",
+    "\n",
+    "Congratulations! You have finished the assignment in this week."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "collapsed_sections": [],
+   "name": "C1_W1_Assignment_Solution.ipynb",
+   "provenance": []
+  },
+  "coursera": {
+   "schema_names": [
+    "AI4MC1-1"
+   ]
+  },
+  "grader_version": "3",
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.8"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "478841ab876a4250505273c8a697bbc1b6b194054b009c227dc606f17fb56272"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}