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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 95-865 Recitation 1 - Basic Python Review\n",
"\n",
"*Contact TA: Ziyuan Liu (ziyuanl3@andrew.cmu.edu)*"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 0. Setup the environment\n",
"\n",
"Download and install [Anaconda](https://www.anaconda.com/download/), [spaCy](https://spacy.io/) and run a Jupyter notebook.\n",
" * The tutorial slides included in HW1.zip (95-865 Anaconda, Jupyter, and spaCy setup tutorial.pdf) will guide you through this process (tested on Linux and Mac OSX).\n",
" * The following [video](https://www.youtube.com/watch?v=xKg2anRkg-M&index=1&list=PLcHK-U_3XaQvdjiU1d9r3dn_1xLyablE4) guides you through installing Anaconda and running Jupyer on Windows 10.\n",
" * Note: **DO** check the \"Add Anaconda to PATH\" option during the installation!\n",
" * Installation on Windows 10 requires Visual Studio 2017.\n",
" * The following [video](https://www.youtube.com/watch?v=hY_0YUKVNMU&index=3&list=PLcHK-U_3XaQvdjiU1d9r3dn_1xLyablE4) guides you through installing spaCy on Windows 10.\n",
" * Note: Run `conda config --add channels conda-forge` prior to installing the package.\n",
" \n",
"If you already have a reliable way to install Python packages and run Jupyter notebooks, feel free to continue using that instead."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 1. Python basics\n",
"\n",
"The subproblems below use the following two lists:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"a = [13, 1, 55, 34, 2, 3, 89, 5, 8, 21]\n",
"b = [17,55, 34, 2, 3, 8, 9, 1, 4, 5, 6, 7, 20, 21, 36]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### List intersection\n",
"\n",
"Find the elements that are common between the lists and store it in a new list `c`. Print list `c`."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1, 34, 3, 2, 5, 8, 21, 55]\n"
]
}
],
"source": [
"c = list(set(a).intersection(set(b)))\n",
"\n",
"print(c)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### List filtering\n",
"\n",
"Using a [list comprehension](https://www.pythonforbeginners.com/basics/list-comprehensions-in-python), construct a new list `d` containing only the **even** elements of `c`. Print list `d`."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[34, 2, 8]\n"
]
}
],
"source": [
"d = [item for item in c if item%2 == 0]\n",
"\n",
"print(d)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[34, 2, 8]\n"
]
}
],
"source": [
"d = []\n",
"for item in c:\n",
" if item % 2 == 0:\n",
" d.append(item)\n",
"print(d)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Fancy list operations"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Reverse the list `d` and print it."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[34, 2, 8]\n",
"[8, 2, 34]\n"
]
}
],
"source": [
"f = list(d)\n",
"f.reverse()\n",
"\n",
"print(d)\n",
"print(f)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Sort the list `d` in increasing order and print it."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2, 8, 34]\n"
]
}
],
"source": [
"d.sort()\n",
"\n",
"print(d)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Sort the list `d` in decreasing order and print it."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[34, 8, 2]\n"
]
}
],
"source": [
"d.sort(reverse = True)\n",
"\n",
"print(d)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### User-defined Functions\n",
"\n",
"Write a function that takes as input a list and returns the maximum element of the list, **without** using a call to the `max()` function built into Python."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"19\n"
]
}
],
"source": [
"def my_max(ls):\n",
" ls.sort(reverse = True)\n",
" return ls[0]\n",
"\n",
"print(my_max([1,2,19]))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Using Loops to Evaluate Expressions"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Use a for loop to compute $\\sum_{n=1}^{100} 2^{-n}$. Print your result."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1.0\n"
]
}
],
"source": [
"s = 0\n",
"\n",
"for n in range(1,101):\n",
" s = s + 2**(-n)\n",
"\n",
"print(s)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 2. Scientific computing with numpy\n",
"\n",
"Install the `numpy` Python package before starting this section."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"### Numpy arrays"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Construct a 4x4 \"identity matrix\" `I`"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[1. 0. 0. 0.]\n",
" [0. 1. 0. 0.]\n",
" [0. 0. 1. 0.]\n",
" [0. 0. 0. 1.]]\n"
]
}
],
"source": [
"I = np.identity(4)\n",
"\n",
"print(I)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Construct a 4x4 \"zero matrix\" `O` "
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[0. 0. 0. 0.]\n",
" [0. 0. 0. 0.]\n",
" [0. 0. 0. 0.]\n",
" [0. 0. 0. 0.]]\n"
]
}
],
"source": [
"O = np.zeros((4,4))\n",
"\n",
"print(O)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Construct a 4x4 \"all-ones\" matrix `X` "
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[1. 1. 1. 1.]\n",
" [1. 1. 1. 1.]\n",
" [1. 1. 1. 1.]\n",
" [1. 1. 1. 1.]]\n"
]
}
],
"source": [
"X = np.ones((4,4))\n",
"\n",
"print(X)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Construct a 4x4 \"all-3s\" matrix `Y` "
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[3. 3. 3. 3.]\n",
" [3. 3. 3. 3.]\n",
" [3. 3. 3. 3.]\n",
" [3. 3. 3. 3.]]\n"
]
}
],
"source": [
"Y = np.ones((4,4))*3\n",
"\n",
"print(Y)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Numpy functions"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Consider the matrix `Z` defined below and use numpy functions to answer the following questions:"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[ 1 2 4]\n",
" [ 2 3 5]\n",
" [ 2 7 10]]\n"
]
}
],
"source": [
"Z = np.array([[1,2,4],[2,3,5],[2,7,10]])\n",
"\n",
"print(Z)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Print the maximum element of `Z`."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"10"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Z.max()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Print the maximum of each row of `Z`. Note that for this question and other questions below, your code should work even if Z is a different 2D array of numbers."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 4, 5, 10])"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Z.max(axis = 1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Print the maximum of each column of `Z`."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 2, 7, 10])"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Z.max(axis = 0)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[ 1 2 4]\n",
" [ 2 3 5]\n",
" [ 2 7 10]]\n",
"[ 2 7 10]\n"
]
}
],
"source": [
"Z = np.array([[1,2,4],[2,3,5],[2,7,10]])\n",
"print(Z)\n",
"print(max(Z, key=lambda x:x[1]))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Print a \"row-normalized\" version of `Z` so that each row sums to 1 (the row-normalized version of `Z` has the same number of rows and columns as `Z`). \n",
"\n",
"For example, if a row is `[1,2,4]`, then the version of this row that sums to 1 is `[1/7,2/7,4/7]` (although when printing this out, you would get a decimal representation like `[0.14285714,0.28571429,0.57142857]`)."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[ 1 2 4]\n",
" [ 2 3 5]\n",
" [ 2 7 10]]\n",
"Before reshaping: [ 7 10 19]\n",
"After reshaping:\n",
" [[ 7]\n",
" [10]\n",
" [19]]\n",
"(3, 1)\n"
]
},
{
"data": {
"text/plain": [
"array([[0.14285714, 0.28571429, 0.57142857],\n",
" [0.2 , 0.3 , 0.5 ],\n",
" [0.10526316, 0.36842105, 0.52631579]])"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"print(Z)\n",
"\n",
"row_sum = Z.sum(axis=1)\n",
"print(\"Before reshaping:\", row_sum)\n",
"row_sum = row_sum.reshape(3,1)\n",
"print(\"After reshaping:\\n\", row_sum)\n",
"print(row_sum.shape)\n",
"Z / row_sum"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Convert `Z` into a matrix with a single row (a row vector) and print it. There are multiple two ways to do this, any of them are fine."
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 1, 2, 4, 2, 3, 5, 2, 7, 10])"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Z.flatten()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 1, 2, 4, 2, 3, 5, 2, 7, 10])"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Z.reshape(-1)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 1, 2, 4, 2, 3, 5, 2, 7, 10])"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Z.reshape(9)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Return the first 3 elements from `arr`."
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0, 1, 2])"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"arr = np.arange(0,11)\n",
"arr[:3]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Return the last 3 elements from `arr`."
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 8, 9, 10])"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"arr[-3:]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Return the elements that are larger than 5 but smaller than 10 in `arr`."
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[False False False False False False True True True True True]\n",
"[ True True True True True True True True True True False]\n",
"[False False False False False False True True True True False]\n"
]
}
],
"source": [
"print(arr > 5)\n",
"print(arr < 10)\n",
"print((arr > 5) & (arr < 10))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Get the first 2 rows and first 2 columns of `mat` and name it `mat_slice`. Change `mat_slice[0][0]` to 1000. See what happened to the original matrix `mat`."
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Original matrix\n",
"[[11 12 13]\n",
" [21 22 23]\n",
" [31 32 33]]\n",
"\n",
"Sliced matrix\n",
"[[11 12]\n",
" [21 22]]\n",
"\n",
"Change the sliced matrix\n",
"[[1000 12]\n",
" [ 21 22]]\n",
"\n",
"The original matrix now\n",
"[[1000 12 13]\n",
" [ 21 22 23]\n",
" [ 31 32 33]]\n"
]
}
],
"source": [
"mat = np.array([[11,12,13],[21,22,23],[31,32,33]])\n",
"print(\"Original matrix\")\n",
"print(mat)\n",
"mat_slice = mat[:2,:2]\n",
"print (\"\\nSliced matrix\")\n",
"print(mat_slice)\n",
"print (\"\\nChange the sliced matrix\")\n",
"mat_slice[0][0] = 1000\n",
"print (mat_slice)\n",
"print(\"\\nThe original matrix now\")\n",
"print(mat)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"12"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"arr_2 = mat[0,1]\n",
"arr_2"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"12"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"arr_2 = mat[0][1]\n",
"arr_2"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Original matrix\n",
"[[11 12 13]\n",
" [21 22 23]\n",
" [31 32 33]]\n",
"\n",
"Sliced matrix\n",
"[[11 12]\n",
" [21 22]]\n",
"\n",
"Change the sliced matrix\n",
"[[1000 12]\n",
" [ 21 22]]\n",
"\n",
"The original matrix now\n",
"[[11 12 13]\n",
" [21 22 23]\n",
" [31 32 33]]\n"
]
}
],
"source": [
"mat = np.array([[11,12,13],[21,22,23],[31,32,33]])\n",
"print(\"Original matrix\")\n",
"print(mat)\n",
"mat_slice = np.array(mat[:2,:2])\n",
"print (\"\\nSliced matrix\")\n",
"print(mat_slice)\n",
"print (\"\\nChange the sliced matrix\")\n",
"mat_slice[0,0] = 1000\n",
"print (mat_slice)\n",
"print(\"\\nThe original matrix now\")\n",
"print(mat)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 3. Plotting with matplotlib\n",
"\n",
"Install the `matplotlib` Python package before starting this section."
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"\n",
"%config InlineBackend.figure_format = 'retina' # if you use a Mac with Retina display"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Line lot"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"x = np.arange(10)\n",
"y = x\n",
"z = 2*x\n",
"m = x**2"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"image/png": {
"height": 248,
"width": 368
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x,y, '-', label = 'y = x')\n",
"plt.plot(x,z, '--', label = 'y = 2*x')\n",
"plt.plot(x,m, ':', label = 'y = x^2')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Scatter plot"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
"x = np.random.normal(size=1000)\n",
"y = np.random.normal(size=1000)\n",
"# y = np.sin(x)"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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0qn5Gjn/puNLjvMDuzxgRkVnsAFBV4EI7+1XrTqaxnhg6H+qsfDU0Ud0m3+E/P6zeOAPKBdRWOsamglYAU/umDHUCVb9zz9//vG87mXZ/xoiIzGIHgKoCF9rZy66dTFODKYzsGkHi3gRGdo0gNZiy3lgFbTva0LWnC9Hu4qPe0e4ouvZ0mapGkxpM4chfHMHU/ildzSyqXEBtpWNsOGjNY6QTaOU759dOJmDPZ8zvvPL9JwoiRj9UFbjQzl66F216sf57rCeGWE/M8voG5RKeisoF1FY7xm072hCOh5H4aGIxNaiiCpV7LJ9XH1cG0vUZ8zsvfv+JgoYdAKoKXGhnH92LNr1e/z2yKaL8uaj02uxQLlDS0THOBa37t+0vWr60qDKdQJXvqpnn9wMrnzG/8/r3nygomAJEVYML7eyhc4G1XalEXpCeTDse/FfqxOaCbavPmRpMGQ/+s3KdwGLMri8w+/zkTdX8/SfyG3YAqGr4aaGdn3JfdS6wVkkl8ovZ0VlHg3+jnVgdHWPdVbZU1heYeX7ypmr+/hP5DVOAqKpUylkut2GSE/yY+6prgXU1139fmFlAeiqt7wkFyu8JYKITmwu2K468CqDljS1IDaZQ11q35D23o8qW0vqCAtPD00qP84tqWitQzd9/Ij8KXAdACNEC4H8AeAOAKwFcAmAOwLMA/gHAP0gpnRzHI828utDOr7mvuhZYWxlF9noAkJ7QF/y3396Olte1aO3EGgq2JXDqiVM49cSpzHHyOqR2VdnKfVcP/8VhvHD/C6af/8VPv4hT3zuFC159AZq2NGFh4wJqwv6f2PbjQEEl1fz9J/KjwHUAAPw+gM8DGAXwJIDnAVwM4C0AHgHwOiHE70spTe7JSV7jpYV2ZnNfvVThRNcC62req0Eu6LlctN/ejo5PdACA9k5sYcf4zJNncPLbJ0vONOR3SO2ustX6zlalDgAAzByewdjhMeAxIPVACqGmEJLppGe+P2b5daCgEru+/14b6CHyiyB2AA4CeCOA7+aP9Ash/hLAfwF4KzKdgW+40zyqRrrLaDotvjOOgesHjL2GEnnk1bxXg6gRlh7ftLUJ6+9fv+yc29GJjWyKYG5sDsO3DZdPMwIWO6Rde7psrbKlpTJQVnoqbXuAbFfQ6eeBgkp0f/+rcZaEyEnev7NqJqX8jxI/HxNC/B2AjwHYDnYASJNqyH01nEdeJje9mvdqCK0MqT1QAPG7445XpFLpkOroBJZj6vkr0RAgFwvy58bmbA06/T5QUI7O73+1zpIQOcn/yZJ6ncv+1/s5B+QbuiuouMXqTqa6SlJ6UU24BqEmhU6ABBJ3JRw916od0rrWOlurbOmqDLRIsYpMsjeJ/u5+9G3uw/Ctw0jcmcDwrcPo29yHgdcOlHzvrO5SbGWgwA90ff9ZSpRID8FU9wwhRC2AfgCbAfy2lPL7Ff5+f4lfXbFhw4bGhx56SHcTPWdyMlMXvLm52eWWeNvc2Bxmj82aflz9mnrUtdZV/Ds3zsPCzALSE2nIBQlRIxBaGTK0+DI9mcbZQ2cNH6dxQyNCzYqj6w6anJzMBCSH1R4fagqhcWOj1jaVcu7EOcyMzJh+XLg9jBWrVyA9mcbs6GzRqkehphDq2+otnbNyz1/JQnsmKqwZOf9ZjLw8Ynhh8LlT5zBz1Px7U0jlc2v1vHhFueuRju//2YNnTX02nPxueQnvz+5z6hzcdNNNOHTo0M+klFebeVzgUoDKuB+Z4P97lYJ/IjNU88Ot5pXbqSZco1RtJdQcQnht2FCQFV4b9kXwv6gGhl9bofRUGgszzlSwUV2wnHtcqDmExuZG5U5gJbnnn31hFnMvzVl+vvRE2nDnVEfwDwAzz89gRcsKU++L1fPiB1a//yrldp38bhH5CTsAAIQQtwC4HcAvAbzLyGNK9bSEEPubm5tfsX37dn0N9Ki9e/cCAILwWq1IDabQ9/Y+04/bdmCbofQXP56HZG/S1r0anK4Mkn8ODr7vII599pjp5+h4sAPtt7RX/Durr21k1wiGbx9Wa987KrdPF5V2Tj6QHXG7/fyIW/yjccTfFq/42P7ufoSetqfDaWR9gF/OSyVGrkeq339L75GB71Y18eN9odo4dQ5UZxgC3wEQQvwpgAcB/BxAj5TytMtNoiqjq4xmNbFrrwYvVAYxkrZVTKVyh0ZeW11rXcX3U/X1h9eGATjXudJ1noxUn1HJvzfDyKLUal4kX0j1+1/NpYSJnBboDoAQ4v8A+BSAA8gE/yfcbRFVK7srqPiVzjKXuiuDqAa6dpQ7TdyTQOKuRPma/a8dKPq7wo6PasnNA28+gFA0hPT48hQMOzpXkU0RNGxswPRBa7v9GmmTIwtFK1QmCuJAgdnvfzWXEiZyWmCT4oQQf45M8P/fAF7D4J/sZLjCiWIFlaDTWRmkXBWY/u7+isGizpHcZG8SfV19SHwkUblmfwnFqtPEd8aVrv7Fgv9Sx7Aq2ZvE9CFrwb/RANmxEeIKlYlMnZcADRTkBGmWhMhugewACCHuRGbR735kRv5PutwkCgCrZTSpNJX66cWM7h7FwPXWSj2qlDsMrw+XbEvqGQ1lHgs6PtpLbhY5hlWJexLKnR4ApgJkJ0eIy5Xu5EBBedVcSpjIaYGbFxNC/AGAewCkAfwAwC1CLKu2kpBSPuZw0ygA7Mp9DzJdG63p3IXV7KZWM4dn0Le5bzGVBoCxtphRsHFU2442hOPhkosxdRxDleWcfJMBstOB9NGPHcXLv/zyor+rdF78uEheJ6ZTEukRuA4AgMuz/w0B+D8l/uYpAI850RgKJp2570GVC2JOf19t3X6yN7nkHOjchdXwzskFcjMMDR0NeoP/3PMXdHxyHdKT3z6JA28+YMsxVFiZRQg1hdC1p8tUgKy6LkLVia+eQNuOtrKfn2pdJG+Vjl3JiSiAHQAp5V0A7nK5GUSkqFwQY0Z+3reuWYR8yiPsC7C88LWcwo4PAG3178sdwwzVnPy6i+pQf2k9YtvNB31mZ20skcZmSry8SN5Nlb5b9fF6tLy+BSuvWelC64j8IXAdACLyr0pBjBn5ed+qI86VAt3cSO7o7lEM3TikdAzdzh46i5FdI0tGlXUvgrX6fG5UbVGdtVGV34G0OyVHZ3qbV+TPkrz4+Rdx6junMHs0s+P6bGIWxz53DMc+d8w3MxtETmMHgIh8wXAQY1B+QGB3ffEXP/+i0vPb4dhnlm9SVmwRshVWA3jVYC2dMrdLbCGj+ff5+y2MPTaGmcNqMygvfu5FpA4Un33SGbjqTG/zmomfTODY549VxcwGkZPYASAiXzAVxFRQWBnEzvriqcEUpvZPKT2/U1QD2FKsBo+RTRE0Xd1k+n1Ln01jYcbah8Ro/n3u/0d/NVpyD4ZKjn3+WPm9HTQErnakt3lFNc5sEDmFHQAi8jytO7UWqQyiGhSEIqGKf+PIJlMeoqvs4spXrVTqOKUnjM8ClAvyjebfx3piWHHRCpx76ZzptlYsc2ohcNW9SN6Lqnlmg8hu7AAQkedpC6JLVAZRrQIz9sUxtO0oPzrr2CZTXqCx7GJda53S4+RC5c0DdFbDSQ2m1IJ/o0wGrnYskveiap7ZIHICOwBE5Hk6gpFK9dNbb2hVDijKcWNBqys0l11Ufd9EzbJ9XZYwVA3nugGsfsdqNL68seKiXCdmeIwGrnYtktdF52JnuxbuEwVFQO5MRORnqsHIha+/EBf+1oWGAg3VBaTJ3iRwVenfO5JyIICGDQ22lg8FkNk9pcjbpGNzqkLKaVkrS6dlGc4Zl8CJr5xY8qNSMwNOjZRXClztXCRvlR37D9i9cF+VnzdZo2BhB4CIPKHcjVM1GFn/N+sN33ztCijs3mQqP/hODaZw9N6jOPG1E5Xzy1Wkgc1PbMbM0RnbAxyV9y3UFEJNuKbk760sJC+1KNepGZ5Kn7PDf37YtkXyVti1/4CdC/dVVMMmaxQs7AAQkRaqI19Gb5xmg0GzQYydAYWVTaai3VFs/OxGJHuTmB6exuyLs6hbU4fGDY3L3uO5sTmc+LpNwX/WzNEZtN/Sbt8B8ph632qA+rb6kr/WspC8yKJcIwvBdSj1OUv2JnHkjiP6Kk1pXMdhZ5Ue1WDajiC8mjZZo+BgB4CILLEy8mXmxmk2GDQbxFgKKF6q/DdKm0xlX4fRijQ6S6WW4uTiUMPvW3b9wVBz6c3WtOXqFyzKHXt8TM/zVlDs86kz5x9A0XUcqcEUjn/pOKaeyXQwIldF0PrOVv2fR5OLnVVmiHTObOSwFCn5Vem5UiKiCkZ3j2Lg+oGSN+FcAD/66Oiy35m9cQJA50Odla9aiotRcwGFGWYCirYdbeja04Vot8FjmHwdWkulluH0ouZK71u0O4quPV0VR1Z1dlxyi3JV3/OGjQ2m/r7Y50x3zn/h+5jsTaKvqw99m/vw/P3P4/T3TuP0907jhftfQN/mPvRd1bfYqUoNpjCyawSJexM4d+IcFmYWLFXpMSq+M248itE4s5FPpZND5AWcASAiJVZHvlRunFv2bjG0U6vqCJvdswx1rXW46C0XoemqJkz2T2L6yDTOHVteQlLldTi134Abo5dGN+cqR3fHxcr7HbsuhunhaUufMx2zPaUWyY/uHs10usukkqWeTWHgtQNo2Lh08fnMA5lN5Z5937NKbTJTpcfsDJHuzy5LkZKfsQNAREqsTO9buXHqCAaLyaUyGQ3KzAQU5dKkmrc2o/mVzahrq7P0OpxIzbEjhcIMo6lQxegO/uYn5jF9WK3qUl1rnaXAVddsT+Ei+dRgCi9+/kUc++wxw89RqvKU6u7SZj/HbTvabB0UKIelSMnP2AEgLVj6LFisjnzpuHFaCQYLmcmlNhtQVHruyX2TmPzZpOUFgran5tiUQuEU3dWYalfWYvwHas9Vu7LWUuCqY7YnvzOna/MwHVQ+x6qDAlbvW14tRUpkBDsAZEl6Mo3+7n6WPgsYqwG8l26cpnKpBUwF/04uELT1eyYqz3j4YRDASjWmQuG1YeVR7tz7qBq4Wv4e5HXmtC8ktsjK59jooICukp1eK0VKZAY/haTs3KlzmDk6g9DTxcvgsfRZ9bIawHvpxmkqlUmaq1RiZxWUQnbuN1DuO+yn+ufK1ZgK1MfrMXNULfgPrw8vC1LNzmZZ+h7kpRXpXkhsVeQqfbN6pegs2enJzjqRQawCREqSvUljN8DsyKZTCxTJGVYDeK/cOO2sVOJEFZRCpqqiGBTtjqJtR/FAyEoVKLfkqgqF14eVn6Pl9S3KneALXn2B8nFzVL8HTVubllT6caJsrJeYnZGrdN+yu3KYF+VXfBrZNWLpekXuYgeAlCTuSRj/Y5Y+qzrhtWrBUy5w8cqN00oqk5vPXUpuhFvblb1M3r/uYMouxQKWWE8Mre9uVX7OS26+RLkT3LSlSfm4OSrfn8ZNjdjat9XSQny7pZ5J2RpQ2lGy0wulSJ2Q7E2iv7sffZv7MHzrMBJ3JjB86zD6Nvehv7ufg3w+xA4AmebGyCZ5Q+4mcODNB0w/tjCA98KN0861CG6tczBSN7/99nbL+yl4vf55pYBlbmxO6XlzKTxuz2KZne05O3h2SaDm1YCt2N4COkaa7bpvGe5021SK1Al+nOmjyrgGgExj6bNgsrRYsEgA73YNb0A9lWkhVflNsHOdQ7FFowCW/GzjZzcu+1n+4tKW17Uol070ev1zI3neyhV8LqzFkb84gppIDcLrzS0EtjqLVXje4x+JI3F3wvB3Mj+/3auVaCb7J20pLGHnfcvNUqR2407H1YsdADLNSxVcyBmWFguWCeDdvHGmBlOYG1UbBX7+/ucx/qPxssGIHSPEZss1lguYrOyn4OVBgPRk2thntcwmV+VM9U1hqm/K/AMtzGKVO++RqzLvZ+oZgyPk2UBtzZ+sUWqL3Y5/4XjJc2OlsITd9y279idxU2owhaE/NnHdt1jIgJzFDgCZ5qUKLuQM1cWCRgJ4p2+cumqejz89joHrBhC/Ow68evnvVarylBshVpmBMRIwqeyn4OVBgNnRWTQuNNp+HFMszGJVOu+pZ1JADVC/th6zR2eNPekCMPlfk6bb4ohKHTPFkWan7ls69ydxi5VrJHc69g9GZGSa27mv5CzVxYKbn9iMVW9aZfjvnbhxaq95LoHEzgTOfu4s6tvrl/3aVN15HQtui7Fhat6rgwALMwtIT6VtPYaKyKaI0sJ5M+kXhoP/rMl9k2i6uglT+xVmMwCIOgE5pziNYpXCSDPvW8bouEYy3dcfuAiYTPNKBRdyhmq6h2qddLvYWfM8PZ3G2UNnly2C07VA0HK5Rs2LcL0aTKUnvBf8A0Dq2ZTSIkm7y3SufNVKU1FA8yubcekdl2LbgW246ntXAcK+tlVitrAE71uV6bpGMt3XHzgDQEriO+MYGRgx9sc+Ln1G+tM9VFJ9dKQHOVHzvNhIu9V1DrrKNeqcmteV3qQ77UsuuDQibYTJmRgnynTWtdaZWoifn0YW2RRB58PWN1UDkOlIKJw6syPNumbkqpWuayTTff2BZ4mUxHpiCJ8JVx7l9XHpM8rQle6hsmOsrl1mHat5XiI1QXWdQ7I3mVmEp4nOqXkrwVS589q8tRnr7l+ndM0QNS4OSRuxABy54wiueOyKip8DJ8p01q6stdRBrfRYI6LdUTRc3oCxx8ZMP9bs4IQXKo95lc5rZJDeNz9jB4CUrWhZgZq6GkS7o1VX+ozO05HuYaQsY+FiVZXHlOJkzfNyI+1m1jloX68AvVPzqsFUpdc1uW8SA68dQPvt7ej4RIepTlNoZcjiq7Lf5L5J9G3uW/bzwg6tE2kUuWNZWYhf+Nifr/45RI3AtgPbAADHv3QcU89k1hnUtdWh7qI61ERqljz/yK4R4DHz7VcZnKjmkp1W6LpGBi1tys/YASBLQs0hbNm7papKn9FSVtM9VOpIA9Bae9rpnFSrI+12rVfQPTVvNpgy87pGHhjB6COjSI8vz+svNftTE65BqMn7nYBiCju0dqdRFAvUrCzEzz12eO8wAGBubK7i7F3uWE6vKanGkp1WablGBjBtys/YASAtqqH0GZVmJd1DacdYCa21p53OSbV6M7VrvYIdo5pmgimzr6tY8A+Un/2pb6vPLGy1eb2HLZzaTMnmQO3cqXMYeFvp60Xh+dNdMtco3rfOs3yNDGDalN+xChARVWS4mo1YehNQ3TFWdZfZUpy+KVm5mdq1XsHuqfnIpgjab2lH/MNxtN/SXnTBr9bXlQ2WC1MXQs0hY59Vr8p2aFWq1jRsbLBcccqq9GQ6szbM4Oxd7vzFd8aNnzMPjTSnBlMY2TWCxL0JjOwaMVWZyEusfB6i3VF07ekyvTkbucuvl0gicljbjjZ07elCtLtMUCKBsS+MLd7Uncy9L3cslWDKCis3U1veMw8ETLa8rhLlTQ19Vj0s16E1GxRv/NzGsq/biUBtdtTEfgR5509XyVynJHuT6O/uR9/mPgzfOozEnQkM3zqMvs196O/ud/Tap4PKNTK8PoxtB7Zhy94trp8PMo8pQERkWKwnhpnEDMZ/MG5oet/J3Pv5ifmyaSim0pgssDrSrv09MxAwOZELbddnodSi68LUpBc++YLpzbLc9OLnX0Tq2ZThtLv8c2w2v13X+U8NpkxvxJZ//vyyQFdngQIvMZvq2fn3nUyh8jF2AIjIMLMLete8d40j7QKAscfGkLgzsezn+QtGDVWtUaxJnnus1ZF2nesVcgFTXWsdRnaNLAvwVMusqgSMdq7DKLfoOpfnHdkUcaQDqMuxzx0z9DksFRQbyW/XVWY3//lU5J8/ry/QVSlq4HaHxSiWSQ0WdgCIyDCzC3onfjphZ3OWmDlcfE+KJaNxBkcYSwVFhtphYQfk1GAKc6NzSo/d/MRmzBydWRIwlavE0rChAdPD0yWDzGKjmFYCRjuDBSOzC4aDG68w0gnNdjhV3ls7RrHnJ+aBRtNNKXr+vLpAV6WogZ8CZb/MwpB17AAQkSEqizin9k2heWszJvdNGn5MtDsKSNiyYDQ3GmdkhFFptFiqjfqVC6yNiHZHsepNq5b8rFKAN31ouvIT571vM4kZSwFjZFPE9GfBKKOzCzo2rvIUqRZgWhnFLve9qV1ZCyhkevll51jVoga6duC2U+F53fjZjQDgyVkY0sMf3zoict2Ln39R6XHNr2zG5M8mTZcQ1Z6uUTAaV26E0dJosclRP8sbfhVZ4Kt1H4EFYPj9w0gdMJCPXiHtYd396zDw2gENjVrKTABcrAN49GNHIWdU877cpRJgKpXmzT6u4uzP9w03Y5FfRpN1pDh5je40MPIPVgEiIkNOfeeU0uPq2upMV/cwXBHEpErlQvPlKsk0b2227TiWA/W89yy/HOHQH+tNc0k9Y3AxKlCyMg+QCfTab2/X1i5AfdF1rmzpRf/jIuvBv7D2cKvMBKaqo9gD1w+UfFxu9mfipxOmN2Lz086xqgvZnd6I0KjR3aOGzuvoo6MOt4ycwBkAIgVeXaBml9RgSrmCSu3K2oqpF01bm7DympWYPTaLkV0jiPXEKj4mvD5cMu+/HDOjcbGeGC5+18VKaStGjmNlw69cLi4A9Hf327J3gKpyo9Idn+gAkNnp1zIN5U2tlmuMdkfR+q5WDN04ZOl5ACgvQDcTYCq/XoOzP7VfrjVeCcgD5WnNUE1V8mKKUzUvZiZjvPepJPKwoE6XWgmS8ksTFqZezI3OYfK/JjG5bxJT+6aWPC73fm7Zu6Voh+ulb71UtOpPJWZH4+wa9VPdGOvSOy5F6ztbEdkUsZ4+ZKNyHaCOT3Sg5XUtOHzH4WXn3TBNlUhUz++Fr78Q6/9m/eJrfP6vnze2rqKE3Ej4sc8dM/3YYgFmqUEKW0ejF4D58XmE14Yr78bsw0oyqm314mtUXcwctMGvasYOAJFB1Vr72QjVoKE+Xr/s5pDLvR/dPYrERxKG38/C51HtlJz81klc9D8uMnzTsmvUT7X99W31iyU8vRr8A5U/M7GeGLb2bUVqMIWj9x7Fia+dMDz6rbMSier5vfC3Llz8DCV7k5mKSias+dM1qGutWxJEpQZTSh2A/Peh0iBF5Ep7g7X0VBrhy8Lo2tNVdZVkcptlmem4ezHFSTUNbP+2/UVnQ6t58KuasQNAZEDQp0tVg6SW17cU/bmO91P1/Z362RT6NvcZvmnZNepndWbBSvqQExZSC0X3HigU2RTBy7/ycrTd2FY63asjjOhvRNG8pbnk86QGUzh34hzkglxMIzMSeFk9v6nBVGbNhYnUnYbOBmz8zMZlP7caYBoZpBj/gf2pYumJNGJv83Y9f1VmN8vyYoqT6uBDqVTIah78qmbsABAZUO21nytRfS2X3HxJ0Z/reD9VgqV8Rm9aukb9CgOhhZRa9F67slY5fchJz9///LKflet0qW4AlT/iPfNAZk3I8O3DFY+Xo3p+58bmcPDmg0rnYXpouuQaCdUA03Cn2oFiR3Lh/EG8Ws9fVTVslmVLGliVDn5VM3YAiCqo5trPRumc+tb5fsZ3xjFw3YB6UGPwpmVl1M9qjf9CsZ6Y5YWrptRkzn/qWWPVk8ox0ukyEzCaSctb0bICY4+PYX58HrXRWrTe0Lq4d4LZ89u8tdlymdpSayRUA0wvzQiJGpfLItnM75tl2bYouQoHv6oZOwBEFRz/0nGlx3m59rMKXVPfOmtpx3piWP321Tjx1RNKzwnA0E1LNSjTvUg316l68e/U9mQwTWReT3htWN++DJpGCk2lke1YXqHn5DdPIhQNYe1frcVlH7zM2PkVwAXdF2DkUyOW34tyo7BmA0yvzQiFVporBaqbE2lHqjNWdsu1Z271HESNKDpwYmeAXm2DX9WMHQCiEqyO3Hq19rMqXVPfuqvqNG5qVHq+fEZuWpWCslBTCF17uhZft/ZFujVAyxtaHC35mT9Sr7wxWjEaRgp1jHinx9M48qEjOPvzs7jiH66ovEuwBM48ecbaQbMqjcKaCTAdnRGqINQUQk3Y/AYeOgJpN6q0eSXFqfC1zz6QKdvc9/bl652spk8aaYsX3hMqjx0AoiJ0jNx6sfazVTqmvnVX1dH1Phu5aZUKyg5uPIiacA1i28+/bq0pGTXAxTdcjCN3HHEszSPaHUXbjvNpOm072nDu9Dkc/dhRpMcN1nkvw8pIoe4R77HHxtD48kZc9sHLFs+v2cpEZhkNRI0EmJ4ZbKjJVKkyQ1fQHuQqbSqv3dSMrkl2fB69NtNSDaovQiGySNfIbbXmQVqd+tZdVUfX+2zmplUYlA3vHV7ye50BarQ7ipY3tDga/APAfHIeo7tHkU6lMT8xj7ODZ3Hi6ye0tuHox47i5V9+uenH2THiffRjR3HZBy8DAMyNzWVeq03Bv+7SkJ4YbMjO/A01G98QTVfQHuQqbaqv3fCMrgKdn8eg7r3jBA9cNYi8RcfIrZEqMH4fwbAy9W12F9/6eP1i0FdsXwEd09m6b1oqLr3jUtS31S/7jPR39zu+wDP1TErP7rZlnPjKicVdn82wY4QxPZ7GyW+fxKo3rbJ3Qa0NpSGdCoDq4/WYTSzfETx/5m9or7HPjM6gPchV2qy8diM7tKts1KfrvQ3yrI4T2AEgyqNl5NZEFZggjWBYWVMxm5jF8K2lSzvqmM7WuaBPNUANRUJov6V9yc+8tsBTt6EbhzD2+Jip74FdI95jj4+hoaPBvvfbptKQdud051x626WLVaisfkd0Be1BrtKm47VXmtE1u+ZI1+xWkGd1nBK4DoAQ4vcAdAP4FQBdAJoB/KOU8p1utou8wXJqgckqMKojGPkX63Mbz7ledaMc3fnUxd4zq9PZkasiJWu6q3TSdK5z8NICT7uY/R7YdaOfH5+37f22uzSknTndObmg0GqApzNo11lVzG90vvZS59Wtjc+CPKvjlMB1AAB8GJnAfwrACIAr3G0OeYmV1ILCG7wdIxjFRtFzmx/139fvqdkE3fXvlyjynlWazi4n9UzpGvdmg9PUYAqzo8vTJIwodu48s8DTbtlzOrl/EnVtdahdWYvw2jBmjs4sG5W0a8S7Nlqr/f0Od4Rx5RNX2h5s2pnTDWT2Pkj2JvHSt16ynMKoM3DVXVXMT5x47W5sfBbkWR0nBbEDcBsygf8wMjMBT7rbHPIS1ZHbS++4FOvvW7/kZ7pHMPyUD6m7/n1RRd6z3HT2vq37MLXffO5quWOV6qSlBlM4d+Ic0tNp/KTjJ6bWNuQLRUOYG5tbdgPzxAJPpywAxz53rOyfNF3dhPV/vd6WEe/WG1oxc1Tt/BVVA3T+XadjQYmVTnAlk/smMblvcsnPVFMYdQauuquKGeHmeq78Y0/1q13jzL52pzc+C/KsjpMCdGfJkFIuBvxCVPduhWSe6gWs9Z2tS/6tewTDT/mQ2uvfl1HsPUsNpvQG/zkFHY78GY7cLIxq8A9kFqHmd+ByN/qzh85qaX61mNo/hYHXDmDlr6/E6ret1pZaJsICU89OYSGl6YNbYUTUriAyP6f7uZ3P4eQ3T1p+zlJUBx10Bu26q4qV4+Z6Lp0zqiptdHLjsyDP6jhJSGlTnTMfEEJsR2YGwPQaACHE/hK/umLDhg2NDz30kMXWed/kZGY0qLm52eWW6HX24Fmkp4zXOQ81hdC4celmVOdOnMPMiPlgMNwexorVK0y1aaE9E7DUjJzffKdYm5xi9v2zqvA9U33vjYq8PIJ0Kr1kpLjYObAiFA4hPePce+h3IiQg01L7eVAVagqhvq0eoebla3PSk2nMjs4W/Y6Ue5yKhZkFpH5eOr1Np8YNjRArBKamM53vhnMNCK0svimYarsiL48UfT4d1+xKzp06Z2h2KLw2jBUty6/hVhg9dr5S3wU37w1G6b5/usWpGOmmm27CoUOHfialvNrM4wI3A0BUSX1bvalR12Ib38gFtY51scctzCyYDqjTU2kszCwo7chphUpbrSp8z1Tfe6PmRudwLnnO1mMw+DdHpt0dyKq7qA5ihYCoESWDXqByIJeeSuPsobPagsiacA1CTSFHvpPTR6Yh0xKyPXMucgFcsU6NSrtCjSGkJ9KYPzO/7H3Wcc0uJz2ZNhyAzxydQU1djbZOnJljG2H2tbtBtaiFl4theBE7AIpK9bSEEPubm5tfsX37dodb5Ly9e/cCAKrxtRrKYc9O8bf97vKp75FdIxi+fbjIg8rreLAD7e9YWgay0nNNPpAdZbh96ShDx4Mdy0pK2k31dVtR+J450YYwwkv+XeockLPcOA8NnQ245pfXVPy7ZG8SA28bwIoFA4F9DdC1p0tLOkkynbS9OlC+oucgd63MSxPS0a7FtJvfjRm7Zgug85Hi1+xy+rv7EXraeHAZ7Y5iy94tpo6h69g5Rc+D4ut3Q/995suPbnm/nvdcF6diJNUZBnfnSYk8qm1HG7r2dCHaHS36+2h3FF17ukrmverMS/VTPqQbxyx8z7xSBYmCYXpoGqnByuksKkUBdMhVcXH1bp9dm5S/uDPWE8PF77rY0tPm1iCMPjqKth1t6HyoE+H14dIPkMDYF8aQ7E0iNZjCyK4RJO5NYGTXSMlzaGU9l1Xa9wCRy8+DV8V3xo1/Zm3YXC8IOANAVIKVRU8qZQpLbaDiRpULVU4fs2lrk207AxMZVan6iNtlDXNVXIbfP1y25K2tiiyiP/7F41qed+jGIYw8OGLotY0/PY6B1w4U/V2xhbxuVqSxJVD3Sc18N8qPBg1nAIgqiGyKoP2WdsQ/HEf7Le2GL+q6RjDCa8uMaJWh+jgrnL4Ir79/fdGfm3rviSw6+c8ny44iWwkidYn1xLBtYBvid8eBSgXwbCqQlz8ybmpGpBJZfi8Po/JnFHLcnIG1a0ZV1wyF3azOxFN5nAEgskmsJ4b229ox8sBI+T+sMIKhugBMaz1zD2q/vb3ke2Z49CgX6AS3GBppcKb3DM70ngFQfBTZS2l88Z1xRH89Wrame+u7WjF045D2YwPnOzWenaErKKWsOqs59tgYor8arTgoUm6G2c4ZVb/UzHey/GjQsANAZJPR3aMY+VSF4B9A+23tZUcwvBQ8VOJUbmn77e3o+ERH2b8xunnNqX85VbmTRmRQsdr4XkvjMxJUjT0+ZkuQfvbQWZx56oz259UqL01GdVZz5vBM2T0S3NxTAPBfzfzcDuBmsNNQXuA6AEKINwN4c/afud2bflUI8Vj2/5+UUn7A4WZRlTGzGdbIp0bQ8rqWkhd7rwUP5dh9U2ne2ox1968zfGM0Eugk7knY2GIKpIJR5Pkzat+L3OfcrkCmXFAV3xnHwHUD2mfHjn2m/E7PXpG/BkN5TVGJjRnN7Opu13qmat5h3O3OlV9U7yegtF8B8AcFP1uX/R8AHAXADgBZolLxo1w6iwo3LnA6byrxu+OovaBWS9BTKtDRXmXDx1b/z9VY+1drkexN4syTZ3Dy2yeZGmVFXiWfxN0J0w+PdkcxNzaHgzcfdCWQifXE0LChAdMHp215fj/IpcnEd8bVS5YWWfxsZlf3dfevw/gPx7WXca3WANhM5yo3MxPUmYLAdQCklHcBuMvlZlAV013xQ2dFIbvpvKnUt9fburgr2ZvE0B/bk+fsR40vb1zsKLXf0o7nP/48jn7sKNLj3JRM1fhT4zg8ddh88FaTme0qF3QWC2R0Sg2mAh38A+dnNA2vKSoh//pudnDo1HdPWTp2MSr3Bz8EyWY7V+dOncOp75wK7EwB62QQaWZHxQ+/1ETOdVZ0sLNe9ejuUQxcP4CZw9W9UNqM/Nmb0d2jOHLHEQb/GkztnzL9mNYbWjPrhwwGMnZ8T/xQK95u+d+JXEWacIdadbXc3gMqg0MrX7WybDWcyFUR45WbTN4fkr1J9Hf3o29zH4ZvHUbizgSGbx1G3+Y+9Hf3e+pzYrZzdeRDR0qej2IVoaoNOwBEmtmxaNfwZj4eqIncvE3TLqwaN0PKZ2Z9RkU1mZ01w+1hrelPTVubtD2XUaZTFMg2Z35wxtFNw4ptiuW3RaJ2KLbJYOsftJb46/LmJ+YtDQ7FemLYsncLth3Yho4HOxD/aBwdD3Zg24Ft2DawDZ0PG9vsraGjwfBxcwMlfgiSbUnntLGD7QWBSwEisptdi3aNVrVxM/hP9iYNVT4ySmUzpEpT1drqj2c7W21/1IahvUOQC/oS5hs3NOJlj71s2esolQ9uVX5KgNb67KTE7MzU+FPjOPntk5g5OmMqRaPcYsmyO+oGgB0bM+oYHCq1nil3f/jFu3+BuZG5ks81fXDaUOqY2XSawoXOTrMtSPfJxmkq2AEg0szORbvFqtocaj+E0MoQtrx/i6nj2ZHTaUfwaLRetZHKD3WtdVoC6GKdLVGjb/ekE189gbYdbWi/pX3Jz22pzJKXEsBF0f514M0Hlv2sXB5zpcWSgU6PK5MmY+X6rhqkGu10nPqXU2WD/0UGgnadhSycYOeMlc5dub2EHQAizZxYtJs/CpTYmzDVPrtKpNkVPBq5sBut/LD67autNUZkR/13LB85C60MWXvufLL4DTXWE0Pnw50Yes+Qnk5AQcpYtU51B1WphcJM8yqjQhqlG0UZjFyPk71Jc/uZlAnadReycILdZU39snGaGVwDQGQDry7aNZTTeZ1aTqddwWOlC7uZqeoTXz2h3hCRyfcvFvwDQE24RtsCaCBzQz10y6HFnOycth1t6Pq3rszCPwui3VF07elaEhgGOu+7Wu+GRfKYg57m1by1+DqlYt+JYlSv7ypFEox2Hg7/+WFTzwucD9oL2VHIwm52zz5U47WRMwDkSX4oOVaO4bJxDi7aNRwoS2BoR6ZE2mUfvMzw89t1gaz03pgKZiyMmkeujCwLDHKf07nVcxA1Aq03tGqt2f3ip19c/P/5szOxnhi2DWxDajCFgdcNYO4FA9P+WeGOMK584sqi36e5UePPU1Wy38OxL9iz+63r8kZ7g57mFe2OYsveLZbuMVau76b2FCgyOFSs3YBatSmg+Mi2n3afz7G0YZsB1bhxWvW9IvK1atrBz2uLds2O+h350BGsaFlhuMa4HRfISqNfTgYzqWdSi1PchZ/T2QdmAQBDtw9lNk8anta+iVapdA4zwT8AzAyXzu2e/K9J5fb5Vf73MLw2rL7hk8flRnsDneZVMBpvZVBJ9fqu2nmwa8F2saDdT7vP57O0YVsFfok7zGAHgDxDZQc/ryu2aNeNGQ3VQNlMdQftF8gSqVH57+VUv9qol6pkbxITP5ko+zmdPjQNCKChswHTQ5o3UipYvGdlqr7w85caTGFyX3A6ALHXxdDx8Y4l70OsJ4b4R+JI3JWoyl2Qc9+boGq/rV3rdUr1+m6282Dngu1iQbufdp8vPL7uTdMA9zbWtBs7AOQJfis5ZpbV0SarlEf9TFR30DoFW2TqvNwImFOm+qcw9viYoTSq6UPT6HykE+lUGtPD00vSeSzJOyc6p+qDNjKc/Jck5m6fW/xeeuHzZbdcgOqGzkc6MfbFsaIBbygacmTTObs6uCrXd6OdB7sXbBe7tvtp9/lCRjpXLW9owZE7jiinYVULdgDIE/xWcsxvrIz6manuoGMKttjUeaURMLOaXtGEqZ+Znz0wu0HT2BfHsGVvpjzr1MCUtuAyd050TtUHcWT44M0Hcc3QNdo/X1411T+F1hvUNrKyIhQNIRwPl8y9nxubcyT1yu1KNcVU6jzYuWC7eWtzyWNbXavgJiOdqxUXrvDUGj03sANArvNjyTG/sTrqd/xLx7HuvnUV/85sfuvKa1ZWnDq3YwQsvjNetG56JSobNOU+p7rzU3O7g6oo9ji383fdMH1wGr949y9w/IvHqz74B4CT3zyJk9886diIe056PL0kfbPwOx7ZFLEldaMYP5VztHuN07r7z1/TiwXLXitkYVa5zpXX1ui5IXhXfPIcnXnMVJzVi9jz9z+P8R+NG1qEXenCGu4IY+0daxfXcVQ6h7pHwKLdUax60ypbK0bkO/6l46hrq8P8xDxWv201Tnz9hJbXMz8xr22qPtmbzKQ2BdDxLxx3uwmOczL4X1QhfbPSdUMXp2a6dKz7sjMtr/329sV1ROUKb6y7fx1OffdUVQbJXlmj5xZ2AMh1fiw55jc68vPNLMLOXVhHd4/i6H1Hl4yczwzPYOjGIYw9PlaxQ2HHCFjruzIpEHZWjMj3/P3PL/uZjhHY3Ii91an6oKS/kAdUSN8sDMiSTyZx6tuntC7I1j3TVRg8hiIhjD1evJys2Up2dt3j2m9vR8cnOgwV3hj/4Tg6H+7Exs9urNog2e01em5hB4Bc59eSY34T3xnHwHUD1m6mBhZh526IZ548g5PfPlnyeEY6FHaMgKVTmcDbrooRhtowngYEsPodq1HbUotjnzlm+jly77+VqXruCFsFamDp/ImwgJxxruRR/uZTpQLKyKYI5sbmMHzbsPZqTEaCbyMjwiqLxs1WslO9x4XXhzGJ5Quem7Y2Yf396xdH/s0U3uja04X2W9qV2kPexAiKXOfXkmN+E+uJofPhTgzdOGTtiUqM4ilVUanQobBjBCz/OZ1KOyhKAie+dgJde7qQesbcTEdhGs/KV63Emj9Zg1PfO4XZxGzRvy82VR/0HWGrwZo/WZOZKVP8/BYG/+H1YYQvDePM3jMaWlfcs296tuh6mvwRcjs+m5Uq1Rjdh8bSrJmJSnaq97grv30lfvrCT5GeSCP+0XjRToyThTeCmmLjdewAkOv8XHLMb9p2tOHox45i5jn1utHA8kXYVm+IpW4udszyFD5nsTzQdCqNF+5/Qfuxl8m+drPpSOF4ZuOfcgFL/dp6tPxOCy557yVFvytB3xG2amTTugaetji7lzVzeAYzR6xdH4wco5jcCHn8rrj+z2aFSjVG96Fpv60dI58asdY5MRhQW7k31rxUg5pwDeJviy/7G6cKb1TTxp7VqMbtBhABmfQUw59Gj5Uc85PUYMpy8J+TS8/RkUaSnxaQz46bQ6nnjGyKoP2WdsQ/HEd9W73245Yy/tQ46lrr0H6b8en14184jh9d+iMMXDdQ8kY+e3QWxz5/DBM/nSj6+6DV/a9Wxz5zDAfeekBvqoybm6AtAImPJLQ/bblKNc9//PnMzKiBdJiRBywG/1mlrnmF7Lg3Wim8YdTo7lEMXF/6+pTrUI0+OqrUFrKOHQDyhFwec8VPpIdLjvmBzqAvl0qja6q+WNtyI2C6GJ05cnqBebI3ick+c5sUzY3MVQ7UsukGxd5bLqKvHq5U9bGT5g7Iur9ZVzLnfnT3KI586IjeAxpk5Hpsx73R7sIbZtcXcDDCHewAkGe07WhD154uRLuLB3zR7ii69nQZWjxFxekM+mpX1mpNIynVNlMjYOWYmDlyeoH59PC0fek42XSDQlxET1VPAJ27O3HZBy8r+utkbxJD77G4JsoCo9dj3fdGuwtvqKwvIOfxDkCeEvS6vHbTGfTlKknoUqptWqr1CGDVG1chNZhCXWtdxc+S6gxT645WjO02X09//D/tzcUvlr/LWTSTBNxNjSFTjNSoT9yTcPWcmrke67w32ll4gxt7+gc7AORJQa3LazddQV8ulealb72k5fmA8m2zXK1HAiefOImTT5wEUHkBmsriu1BTCJfedqlSB2DqZ1OmH2NW4cZ5OvaGCIqahhosTAe0XJJPOj7h9WG0vrvVcFDshUXwKtdjHfdG1cXFADCya6RieVQV3NjTeUwBIgoQLTn1eak0umYUjOTmx3pi2LJ3C7Yd2IY1f7omE5goMrIAzWzqUX1bvfY1CzoVSzfQll5V5QIb/ANYc/Oakqkn+USDhS+kVTVA5993Iv7hONpvaTcUSLqdd968tdnVgNfUd18A86fn0be5D8O3DiNxZwLDtw6jb3Mf+rv7l7yX3NjTP3jpJwoYS0FfwUIzLTMKJqs6RTZFkHo2ZX1UssICtMXFd5XiGgGE14YRag4B8G5QXayzZniBoYc0bmp0uwmBcsl7L1nseF92x2W48PUXInptFBe89gKsed8arLl5DcLrw5DTLk0TKBaGcDvgbH5ls6vHN/zdz17/Us8Wr1hUOJjCjT39g+84kWY61y/YsRYi1hPL1LJ+YMTU44rl1FpOI1G4eWudui+ox134fs+fMRYkyDmJcyfOIXFvArUraxH/SByJuxOe2mSr1Hu88lUrsea9a3Dqu8U3EfOSaHcUW/Zuwf5t+zG5z1zVJDIvNzNXqp77mX8/407DskLREDZ/Y7PSQITbAWddW52rxwcqp1ZGrjI42GJic7NSuCbJeewAEGmic9MTOzdQGd09mtnIpoLoa6KI/WasYsfD7CZWi89vYJFeMbqn7sefGsfo7lGMPT6m1rGQwOxoJnBO3JlY/HHkqsz7lXqmcq1vuxVLsSq7iVi8Hi2vb8GF11+IA28+4FQzy8vOFKUGUwz+nZB9vy1t8mez9Hgada1qgbRywFkDLZuBud0BySm3uPjgzQeNz7RmB1O27N3CjT19wkcTv0TepXPTEzs3UDGzadf4U+OI/mq0Yk6tmanklje3oOPBDmw7sA1b9m5RugnbMXU/9J4h7QsCU8+kkDqQQvyeOC67o3gZQkcUSbGq9BmbTczi2N8dw7lT5xC50gM35ryZIrdztwMh+34D8Gzwn6P6eVBdr9P5cCc6PtFRtiynEV4b8c7fCLH9lsymhKrVfLixpz+wA0Bkkc5NT+zeQMWu+syG6lT/Wxeu/NaVhhfplWLLyJld6csLQOKuhHv5xkVSrMx+xho6G+xtYwWFNc7dzt2udqFoaPH91rXJn51yn4fUYAoju0aQuDeBkV0j+nfZxdINxfKLEoTXh0212Q8j3laq+XBjT3/wxhwUkY+pBNWlLnhKAfpdxv7c7vrMTu3h4LubxQJw6nunHD9sqRQrs5+xk/90UnvbTCnonHkldaIqCSzm1NtdJrN5azMuftfFi9eJudE5PH//86afZ25sDv3d/Urpkob3GBFA5yOdRTfaimyKoPPvO42nQQp/jHhbreZTaX2Bagoo6cMrKZEFOoNq1edamFlATbjyMJZT9Znt3sPBj/XrnVxce+kdl6L1na1Fz4EXap+bNf70OAauG1gMwBgw2KfzkfOjsbamWtUA6+5ft+RcpgZTSh2AY587VnIGL5cu2flw8eAd0BOomtqsUGY74fD2YIaOaj7c2NPb2AEgskBnUK36XOmJtKEOgN31mZ28yKsuPK520e4o1t+3vuTvfZs/L4GhG89XGfFbB1Cn6PYoLvofF2F+Yh5T/VM4+U2NMzTZQDo1mMLp75/W97z5SqR9KHfsNVSo0RGomtms0EjHxG06q/lwY09vYgeAyAKdQbXqc8kFYwnsdtVntrNiUb7Cm3P8I3Ek7kr4YpdSRxhYTOfr/HkJDL9/GNsGtqH1htbAdgBiPbHFRZqpwZTWDsBzO59Tr4ZlQNPWJqy/f33J60F8ZxwD1w3o/05XSL3MsRqo5p5/4AcGBic0lM60k+puwQz0/YMdAAoEu0andQbVqs8lagQWZhYqbtFuR33mSiUCdYx0letgrLh4Bc4dP6f0vFXF4GI6v+fPp55JITWYQjqVdrsprsk/h7rT4eaOzWHu2JyW5yrUuKkRW/u2lv2bmcSMsScTMN1JMLOeyQrVNWFeTJMxNdPKaj6+4++7AVEFdo9O6wyqVZ/r3OlzmBmZwfDtw0t+Xvj6dI/omK0mozLSVamDweA/s99Axyc7DL23XhxpNOv4l46jJhLcAnaF57Dld1p8MRuy4cENJX+XGkzhxc+/WDaffwnFGQKz65nMUl3HtW/rPkztn1r2O50zqCoMr23wQTUfL3aw3MYOAFUtJ0andQbVqqN56bPFR0OLvT6dIzo6qx8VY2bPgiCrjdUWfV9L3fDq4/We3/G3nKlnpnDhb13odjNcUXjtGN09iiN3HHGxRca0395edJQ7FAnZmnJUyO4UONU1NsWCf8AbawX8Xs3HqRRVP2IHgKqSE6PTOTqDau2LWwten64RHbtLigImOxgBVvi+Vrrh1UZrMQv/dgCA6pjJMK2gfKRfOsjtt7ej5XUtJUt1OsnuFDhbOhgeWCvg12o+TgwC+hk7AFSV7B6dzmemlnT8Lo3l5IwqyDNNp9K4+IaLMf7DccwML8+5NTKiY3dJUc+Vq6zJnLvaaO3izW/+zDwSdyc8EYDl3lcjNzy/i1wV8WUpWKtWv2M1xn+c6ezFemKe6SCHoiGkx5fPQuYW/M4kZjxTscvuANq2DobFe5Qufqrm4+QgoF+xA0BVx4nR6UKGSsBJILEzgeS/J8tOO5opJ2dUuTzT8PowLnj1BWja0mR4RMfukqKeK1e5gKLnLfrrUSQ+msAkJpc9ZMWaFTh3zJk1CvMT874ZEbaqsaMRQPBKwZ74ygm3m7DEha+/EOv/Zj0imyJLRoYPtR9CaGUIW/u2euoz6USFGjsDSKcWMVcLJwcB/YodAKo6Tm14VSg3TZq4J1G2PKWRacdSU65jj4+VzBetpNTjZg7PYOy5MXS+urPs689vy1S/WhuMjpB5sVxlsfOWO0/Jf03i3EvnluTXOxX8A5n31SsjwnYbunEIp75zChe85oJMKVgrszAK1WQo48LfunDxepE/MpzYm1j8G9s/k0bPn8UKNUZTX+yembJ7EXO1cGMQ0I/YAaCqY/fodDnJ3mQmINGwOQ2w9MaaGkxh+Nbhkn9rSZn2lMspNyu8NlyxXCng4XKVJd6ndCqNuZfmXFtcO39mPlDpMCefOImTT2Tq30euiiA9mcbMcwZLSOZk17kc+/wxTO5bPoND5VUaLXUijS9+l4EOoIUKNSoLSO2cmfLiwIgXuTUI6DcevcsSqbNrwysj7Jx2tD0tpkh7KuWUmxGKhnDgzQeW/bzYjdTTU7EF71OyN4mZoyaDT40aNjZkZpwCKvVMSu2BC5mNxYrlr1N5RtJp7L5eRbsz141cGp7uCjWqC0htWceV5dmBEY9xcxDQT/hpoqpjx4ZXRtg97ejExSm/Pbrzd0sFWsVupF5f5Jn/PiXuSQBvcqkhApg+NM00FkUM/hUYTKex9XqV14Zi6ZLpVBoCAjWRGqQGU6hrrTM1smt1AWmldVzNW5uVZp08PTDiIW4OAvpJsF4tVZ1SuZlubGFu97SjUxenXHsczSkvciM1NZXuQi537nyPPz1uTweg0muqARo6GjB9cNqGg1O+8PowZg67N8vjGSbSaWy7XuW1odi+Ai994yXLNd91zORWKp1ptiyqE4uYq4Vbg4B+ww4A+VKl3MyW32nB+A/HHd3C3O5pR6cuTvMT8+6U4Sy4kZrds2DsC85tKAScr7xjl9Y/aMX0c9MlUxta39WKoRuHbDs+ZTRtbcKqN61C4s6E201xldl0GruuV+23tSO8Nmw6gDZa8133TG6p0pk694+hpdwaBPQbdgDId4zkZo7/cBytN7Ri7PExx7Ywt3va0am0mNqVta6V4Sy8kZrZhTK8NuxoWcjalbW2pjk0bWnCFf9wRckRxJFdI7Ydm86b2jeFpq4mt5vhivp4PVpe34JLbr7EdHBk1/Vq5IERjDyg+Nk3UHzBjpncYt9hXZsyUnEtv9Ni6rPX8oYWG1vjTewAkK+Yyc0ce3wM6+5fh1PfPeXIFuZOTDs6Ufs81hPDS996yb4DVFB4IzW6C6Wdi++KifXEbO0ozY7OInFvomS1pKAtWHPT2O4xt5vgitnELI793TE0X92sNDoa3xnHwHUD3lqjUqH4gs6ZXCNVhLr2dNmyiDnoTn3nlLm//+4pXPbBy2xqjTexA0C+YjY389R3T2HL3i2ObGHuxLSjmV2HOx8xnxaTa4+bG3GVugEb2YXSjk3UinFiuviF+19YesyCHOagLVij0qLdUWz87MYl17jZ0dllnyElFnZKjfXEsPrtq3Hiq97axKxcyo6umVwzVYScukcFBfcBMIZ3EPINq19qJ77YZvM6W9/Vaqgufj7b0mIKKmu4xWpgW2rGILw2XLQMqWl571Ou01dsJ2DdCnOYOSpIABY/j4XXuMS9CX3HsLBTauOmRn3t0Oi5nc+haUvTsuuujplc1SpCQQo+7cR9AIwJbAdACNEO4B4Avw2gBcAogCcA3C2ldG/4k0ryw5fazAh9Q0dD0UWcRqpV5Ae5Pxr8EeSCRMeDHeppMQV5pm6W4dQV2Bbr9Fmu5lIkHze+M46RAYfy8QsCBjvOUePLG3H252e1PifZpEx+eDqlt8Rp4Qip0RFrr85UnfzmSZz85snFf+dfd63O5Nq5HwxVxn0AjKlxuwFuEEKsB7AfwB8C+C8AnwJwBMCtAH4shAjeahAf8MuXum1HG7r2dCHaHS36+4aNDQBQsnxjbqR39NHRiseKbIpgxeoVqGutQ/st7UVvwJXaE+2OomtP17LKGPGdccevEHan1qz9i7XKj23a2lT0fcrNtDgmGzAA7pwjclaoKVT056W+t8neJPq7+/Wk/xRI9iYXn79vcx+Gbx1G4s4Ehm8dRt/mPvR39yM9ubTj4ZfANv+6a+p7VVChx8pMtVmpwRRGdo0gcW8CI7tGlJ6jGnEfAGOC9WrP+xyA1QBukVJ+OvdDIcQnAdwG4GMA/sSltlEJfvpSl0pDCUVCmdH4SoviLOTdmmlPuWlnpxfVOlHqrm1HG57/6+czm2eZNLVvKjOyh+VBzYqWFTqaZ1guYLDjHFka/RfZ/3pp0afPpafSaLq6CStftRJ1rXVlv7c6d+4u5syTZzB823DZvPazbzq7pEMc2RRB5MoIUs/6IDjNXne79nSZmjmta61bTOWc6p9SOrSZmWoji4tRvN8YCNwHwJjAdQCEEOsAXA8gAeCzBb/+CICbALxLCHG7lNIHV6zg8OOXujANpb+739WpYbNrIZxaVAtkUqLMUF001/aeNhz50BGlNparJb6iZYWjaVMvfu5FbPzsRkfPUTm5tScAXG9LtZnaP4Wp/VPo3F26hr3unbuLOfntk4Y6dzNHZ5DsTSLWE8Po7lGkDvjoVpq97m7Zu6XiWquWN7Rg7AtjGNphfT8OozPVRhcXn/v6OccHJryC+wAYE7gOAIDfzP53j5RyyVdISjkphPhPZDoIrwLQ63TjqDS/f6n9Wpkgf/bg8IcO4/T3TttynOmD04Y26jEy+lWq0zT8gWH1GuI5ZWZnnCjTmnPqe+fL3JWa4Xnxsy/av1OwyIyCtu04f87y2zLx0wlM7pvEwuwC0lNpzJ8KVp6tzl2qh3aUnhV0ZOduE68jl6ZmaMbTY/Jn2ErNnE78ZEJrh8vITLWZxcUzR2dQUxfc/EButFaZkNJn30yLhBAfB/ABAB+QUj5Q5PefAfCnAG6WUn6+zPPsL/GrKzZs2ND40EMPaWmvl01OZiqfNDc3O3bM9GQaZw8ZT1Fo3NCIULM35kLPnTiHmRHzC1DD7WGsWF16JMfu87Aws4D0RBpyQSJ9No35M/YHcKXO27lT5zBztPJ7GF4bXjb6NTsyi7kTc9raGGoKoXFjpsJJ/jkw2kYd6i6ugwgJiBqB0MoQasLnb/hOtaO+rR5yQWJhOnOnrWmowYqWFZDnJGZHZ5Ge0rsYtZyF9mwbRrwR+ISaQljRskLreaipq0Fk89IBgYWZBaR+7o1R9vxzEGoMIX3WufOvU7nrrtn7kBGRl0eWfH+LOXvwrOHv00L7AlADRFcVX/sVBFbuFzo4FSPddNNNOHTo0M+klFebeVwQZwBy34ZSQ7G5n19gf1PIrFBzCOG1YcNfaq8E/wAgF9Q626qPsyo9mXY8gMuZHZ1FY/PS8oHpybThQCo3+pU7/+nJtNbgH8jkZi/MLCy7aa9oWYGauhrMvjhre/Azd3zpawo1hVDfVg8Atgf/oYYQZDoT5C8xsbxdQdSwvgG10cwt9typc9q+RwtzC8s+d+kJbwbZfg3+AWBhdgHnTpyDXJDLOtjLPvMWhZpCFYP/hZkF85+hBRS9RgXF4rW4xH0sd730UpzgpCB2ACoxtIytVE9LCLG/ubn5Fdu3b9fdLs/Zu3cvAMCN15rsTfpu98SRXSMYvn3Y9OM6HuxA+zvaS/7eynkolUefyzNtXHCvhve2A9uWrZ8IPW38Qh3tjmLL3i0AgH1b9yG0X/9FvuPBDrTf0l70HKieb8tqMuspQgftuamtessqNHU1IfGBhOdSOyYfyI643e7crGQxTVubsLVv6+K/k+mk1tSw1h2tuOKRKxb/nbg3gcSdCT1PbpFXzoEdotdG0XpDK4b+2HrO/6IaoGtPF2Lby9+vzF5PcudhY+1GtN9S+v4RFG5stOZUjKQ6wxDEDkAuYiw1L7ay4O/Ig1Sq2rjNiUXMRt+Pcnn0kSsjmUV7Lgd3+VUxrJbWm9qvVpmjknIL91yrKb1QusSsDqGVISTuSjj6+QivDyMcD+NM7xnnDmrBymtWLvn3YrWm9+jJh5/48cTi/0/2JjH22Jj1J6WKxp8ex/gPNIYGZfZxKOSXMthe5dRmoH6irQMghIgDeDmAp3LVc4QQtQDuBPBmACkAH5dSfkvXMRXluu4bS/x+Q/a/Bx1oC1nkpy+1nYuY05Np9Hf3G1oYW6mKhFfK9eXfuKxsAnd2yL5Nrcot3KvWmtLjPxh3tnNYA3T+fSdSgynfdADqWuuW/SxXrengzQctd9DkfOYE2F32k4rQ9Nk3O1Otej2ZG2U6HhWn8w71EQBvBHBx3s8+jEwHIOfrQohXSyl/ovG4Zj2Z/e/1Qoia/EpAQohmAL8OYBqAm22kKmVHZYLcQqdS6TH5pSvDa8OOBAy5m1tdax2e2/nckh03jcq/4VkZ/cqvlqNb7uadWyiduDexOPPitRQ0XSztpGxW3ghpsaDaq0oFa7GeGK4Zugaju0dx9L6j6u9lyJmyn6TPqresQtOWJuWZatXrybG/O4bmq5vLVlajYNLZAfhVAL1SynkAEELUALgZwC+RKavZCuDfkdlo6+0aj2uKlPKwEGJPtk1/CuDTeb++G0AEwN9zDwB/cjMlyMixDW/cZHBqONmbNLbYM1u6MrIpYkvAUO7mdvk9lyt1APJfu+roVzqVxmxC74K9nPD6MJ7/xPMY/8E4UjdnLhf5edjRa6OIXBVB6pnquZSE14cd6wAUjpCqzKC5pdL3tm1HG9p2tGHk0yMYvsX8OpHpX0zjmd99hsG/j1x+z+WW7kXKn3/Nm0pS9dDZAbgYwNG8f/8KgFUA7pZSjgAYEUJ8G8CrNR5T1c0AfgRglxCiB8AvAFwD4DXIpP78lYttIwVWasM7fexKGzdFu6NofVcr0lNLR5SL3TwS9ySANxls6IJ96T1NW5oQ/3C86O9UU58ALO6uuZBSi3TE4pp+/WYOz5QNhsefHs+UFNBYB95VNcAFr74AY4ftzze/9I5Lsf6+9ct+7uQ+C6oiVxlPS2z/s3Yc/tBhyBnzHxA57d0PVbWmv6nStR+N8uffhk0lyf90fktXYOlt7tez//6PvJ+NAHB9Hio7C7AVwD0AfhvA6wGMAtiFTIfFnp2OyBZGd0astMGUk8fOX8Q89qWxxVHi2pW1OHvoLIZuXF5lorAzsbgw1mgHwEaVbvimblwCmD89j77NfZbaFO2Ooibicvk778Zo5mRnpNJTaeAx+w/X+s7Woj/XvZjWC+rb6jHznINpVTaKdkeR3pD2/MLTNe9bg8YNjYuztdPD03jx0y/aczCNm0xZ+fx7YVNJ8hadHYARAFfl/fv1AE5KKX+R97PVACbgAVLKFwD8odvtIGvM7IyoexrU6rHLzRwUU9iZUF0Ya4dK76nh1KfsgL3lmYrsTTdXBYjU5afiOPF+1l5Yi8MfOozIVRG0vrN1WcCS23G4WCfZC1LPpAwHWqnBVNUE/wCw8bMb0fdSn/Y9N3Rr3NC4pDTmyC6Lu4OXYqLKj1FtO9ow2T+JY589Zvqx+ZXViHR2AL4D4DYhxCcAzAC4DsA/FPzNFViaJkRkSeKehPHpUM3ToFaOrVy9I68z4ZVRNqPT25VSnyJXRTKBv9WRXR0LRwUQvzuO2mgt5ifmMfbYmLOLXz1gzZ+uwSXvvWTJuXUiD3/+9DxOf+80Tn/vNF64/wVEroyg41Mdy9Loxh4f8+x6gMF3DGL121dXXIf04udtGnW2QgCRzRGlTniyN4n05WnMj3vj2lRK4T3AjtSYpq1NWH//elueW/W65pV7BnmDzg7A3yBT7vP92X+/iExlIACAEGItgF8D8CmNx6QAs1Ib3uooiJVjz43NWaveke1MXPSWixSfQCOT09vl9m84ePNBy8G/joWjoWgIm7+xeUmqlVc2WXJS6kDx70l8ZxwD1w04loKTejaFgesG0PlIJ1ZeszJT2vXQWdd2yDbi7IGzSBxILP47P30v/7N/4isn3GtkEfXxelzxyBUY//G4UgdgfmJe+y65ZWU3vTNTVrXYgIUdHdvWd7XalnOvusaCazMon7ZPg5TyhBDiSgA92R89JaWczPuTJmQ6B9/XdUwKNiu14a12AKwc+6VvvGR5EeP4U+O49LZLrT2JVRqnt6eHp5VuvpfecSlCkVDZkVazpVdzwX8uUDv9/WAuCSrVWY71xND+/naMPGBT2kQxEhjaoZjyUwPUranD3Ih7aSnjT49j4LoBNGwwF6w67dLbLrWU6pVOpTPrRByQG2EHoKW0su4F5sVG23VVqXNiU0mqflq7g1LKaWRSgYr9bhDAoM7jUbC5uTOi6nOcPXRW2yjTzNEZRK+NYhKTlf9YM7Ob2OSYXfdQSX1bPWI9sUzH6lsvIdmbXHZTNVt6FUDJTdWCplhneXT3KEY+6WDwb1FkUwTnkufcbgYg7d2hWYdQJLOXiGqgaGfVrXzNW5txdd/Vi/82ur5o9dtXl0yfMXydMCh/tL3cda95azPW3b/O1Htu56aSFBwul8ggUufmNKjyrozH9I1Czk/MI74zru35jNr8xGZs2bvFdJAwunsUA9cPaA2sX/jkC+jb3IfhW4eRuDOB4VuH0be5D/u27lsyS9O2ow1de7oWy4sWinZH0bWnC5DQ3kY/K+zoLi589272zTKpZ1Oujv77ydgXMyVecwGmGY5V3aoB1t2/bsmPKn2/AQASOPGVE+jb3If+7v6is7i556mP11tuZv56r3LXlMl9kxh47QCGP2BuP4j4zrjxCE5jJSKqHsqRkBDiUWRuA38ppTye/bcRUkq5Q/W4RDluToOqPkf9JdZvLDm5KeTwmbCxzcA0iHZHsepNq0w/zq5dS2ePFs83nto/hYHXDqD99nZ0fKIDQPn1B5FNEU/urNqwsQFtN7bhyB1HXGlXYUfX1MJ38p38tC+VXctTgynAznWmeWmHxb7HW/ZuQWowhaP3HsWJr50o2VEtVxo61hPDpbddiuFbzW/QlpMbbTdzTcml1OWuV5WYmdmM35U5N+M/Hnd8g0zyLitDoe9G5uv11wCOZ/9thATADgBZ5uY0qOqxGzoaLB87J9cJWdGyAjV1NYh2R4tW19HGwiiSW4FjsZtqZFPxjZq8GNxOD0+j+RXNWlMTzAivDS/+f5WF7+Q/ubSvWE8M8Y/EkbgrUX7Gp7Dqlk2r/HJph0DpFL3otVG0/E4LTny9dPC/qExpaEuDRHnXSbPXlJEHRtDyuhbDx69UWS3UEEJkUwSJnYllv7N7g0zyPisdgMuz/32x4N9EjlEZpXLz2MplKQsU7jYaag4tjn7lRsW0lq5UXPCbGkzh+JeOuxo4Grmpeja4XQAO33EYW/u2IhwP48BbDyA97swiSwBLZpa8tO8E2Wd+Yt7wWp1iVbdC/xnSvxBYAK03tGImMVNx40VT3+MSpaGVqwKJpTMUKteU3PfdqFIzmz+/6OeYHZ0tWc3Jzg0yyR+UOwBSyqPl/k3kBLMLPHWOdqgeW0e5udSzKYw+Orrswp0/uh391aip3XcjV0YWdyTOl7vJ17XWYWTXiKEKFroX+1p15I4jSxYNFvJycDu1bwr7t+3HuvvXYfM3NjtagvP0908j1hPD3NgcXvjUC84clFw18skRJM4kyn/GsvtkFBtQqW+rx9lDZ/U2SuZt/Kb5s1+q2lV8ZxwDrx0w9VyRKyOL12TVa8rUvimlUtX51/5kbxKzAwbKsdqwQaaf6arS5BeOF4UVQqyUUnpiN2CqDpWmQVUr1th1bC3l5uT5CzdCxf/EbAel7Y/ail4A58bmSgbzxaaRlTc5s9HkvsmyN1Wvb5AzuW9ycbSu8+FODL3HmYW4uQ25KDjmkwa+CxJI3JVA9NeizgWONn7ei1W7Upmtzd8F2so1xWqp6sQ9CeBNBv9Y8waZflRuwKqaU6W0dQCEEN8H8L+llCfL/M01AL4CYF2pvyFSUWmBp5eOra3cXPbCjbtK/4nZDkphfnylYL5wGtnuhbT18XrMJtQ2Gip3U1Wt6nTh6y9E01VNGHSiwnF2tK5rTxfW3LwGxz57zP5jEpVSInB0dCMwTQqD9dRgCs/tfE7puXLXGSvV5k5//7TyPWwx9choBwD6Nsj0I7P3uGqicwbgOgADQoh3SimfLPylEOIDAD4GT40LUrUptcDTa8euFJgbNf7UOBZmFlATLl0PTrVzZDiYz5tG1rmQdvMTmzFzdGZJe5O9SeXqHFP9UyV/pzq6s/5v1mem+p2aQFjIpDOtWL3CoQOS00IXhFC3ug6iVqDhigac+uYpt5tUUmHgmBpMObYRmE65YF1H6mKuM2FlxLhw5s3MKLSbG2R6WanZbbP3uGqaCdDZAXgPgAcB7BFC/H8A7pJSSiFEC4DHAfw2gCMA3qHxmES+VRiYn/6+WrpFeiJdtgOQY7ZzZCqYzy5WndpXOsg2Q7XcaDljXxhD9NXRoqM4VipKvfStl4BGnS0tb3Kf8xu/kXPSZ9KYPpPZMOzsz88iFA05uvDbrPzA0ctracoJrw3j5//z52VLhxqV60xENkXQvLVZy/fVzCi0mxtkelG5Tl0oGjJ1j6u2VCltu3ZIKXcDeCWAIQAfBvCkEOL3AAwAeB2ArwF4hZRyv65jElWDyKYI2m9px8pfXan0eLmgPzlWpYKFruC/XLWmyKYImq5uUnve7LqJUkGK6sY6OjaWIyrFy8E/sDRw9GMQGYqGcODNB3Diq9aDf2DpyH/hhmWWLJS/fuW4uUGm11TahM3sdys341UttG7bJ6X8OYCtAB4DcC0yQX8UwI1Syv8lpeTQFWmXGkxhZNcIEvcmMLJrxLdfUNULsKgRFf/G7Hvk2kiegWpN6/96vfrz59ZNFJFbm1HxqljQxmoaEQqShk369uTwhBogfk8cHQ92YNWb9c6elZN/3fJjEKmzg1W4z0ysJ4b229u1PX+561f+MVVU23XMrvVofp3lKsaOb2sMQO4OnYtMfLRxPPlFta3cV21raGWJMkBQf4/cGMkzWq0pd1PNbfJlVrkFbypVnWyrfU72qQFi22OYHpx2uyWm1ERqsJBaHtGE14dxwasvQG20FqFICCf/uWQtDu3yvwuxnphtG4F5XomZy9wmhKrXq0KVFuzm0hknYXy8VdcGmV5i18aOfpzlKkVrB0AI8TpkRv8vAvAIgH8C8CiAR4QQ1wH4Y84CkA7VuHJfJQ89vD6Msyhec9voe7T67avR+PLGJQuDnRzJu/SOS9H6zlZTNyCrN9VyC95UFk3bUvu8SkS7o2je2oyRT414pgREQ0cD0in/ddgWUguLi+Mn+ycx/oNxzByewczhGYwdHsvcfR3k2cCxJpN+c+q7p4rvkKt7XUWFmcuOT3Sg5XUt2tZJVVqwG98Zx8iAwWuj5g0yvcDOjR39OMtVis4yoB8HcBuAFID/KaX8WvbnXQC+gMzi321CiHdwHQBZoVKdxi8zAWb3CJg5PIPUz1MINYaQTCcXX6eZ9+jEV04s+VH02ihab2hVaL150e4o1t+nltLT8YkOnDt1DscfO276sUZGccwsmg41hzJ7MtSg/HsuUNXzoc1bm3Hxuy4u2mlqeV2L5apXukwfnMb0QX+N/udM/GQCDR0NOP74cXc7VAWBY7I3iaE/HgJutu+QDRsbMD08bXhfk8s+eNmyjnx4bRgH3nxAW5vMzFxu7du6pD0TP55QKvxQ6foV64khfCa8ZCfvomzYINML7EzTqab3SucagNsB9COz0PdruR9KKU9JKX8HwAcBXAbghxqPSQFktjpNpZxJLzGch14gfTaNgdcOYPgDmRKZVqY/x58ex9BNQ2jYaHOOtIaRp+YtzUqPs2MUZ0XLCnTt6UK0O1r099HuKDof7tR+XM8QQPM1zUuCfwCLa09Sgyls/OxGdD7SifD6sMuN9a/kf9i714YhYmngmFtsOXO4QsBpUduNbRW/Y117upbM+uaKLMQ/HEf7Le2Vg2KDVr1lFbYd2IYte7eYCgrz23Phb12odGwj168VLSvQuKHR1HtVLexK0/HsjJcinXfBTwP4gJTyXLFfSikfEEI8DeCrGo9JAaMytee3TU6s7BEw8sAIzvzgDKb+y+I08wIwfWjavhFrTSNPXlvwZiR9aOzxMdump10lwc3JHHB2+KwnUqlmX8xs+GX35n/5Tn33FC774GWWNn3UFRxefs/llu8pOq5f5d6HUHMIW/ZucWWDTDfZkqZThalS2t4lKeWtBv6mTwixRdcxKXiCsslJfiD57JueNTWyZjn4z5FA/dp6zB7Vu7On0SlzI6zU78+x4+ZYLn0ovjOOgdcOWHp+coFHSlqkT3tg7YIEEjsTeOn/vpR5XxzqkOQP5qhu+qgjONQ1Emzl+lWpwEP6A2mEmkOLx/HT/c8q7QM8VZoq5fhqBinlhNPHpOoRxE1O7J5WL0d38L/5ic3aN/gytW4ibxTHrSpSda112p+T7NewoQEtv9viqcXMbks963zJZauDOZa/05pHglWuX0YKPJx909nMuqQAUulYlVoYbmTAyq8zLLZ0AIQQ7QAuAVBf7PdSyqftOC5Vv6BtclJNNYcBaMu/zZdbN1ExDSFvFMfNKlLVdk6DYvrgNEY+OYKVv7YSc2NzrnTMV1y8AueOF82yDQyrgzkqweGiCiPBKoGg2esXAMMpVzNHZ5DsTVbdyLURZjtWm7+xGXWtdabOn5lZGC/SXQb0egCfAnBFhT/17jtCnua1nG+7+Xnmohi7Xo+Z+v1OV5EqDApYLtTHJDDxn3mT2LUAnPqKCuCi37so8OssRv52BPVt9Wjbod4xN1ttDSg/Emx1NtHM9au/u99UuxMfTfj2/meFysAQAMMj99UwC6OzDOg1AL4D4CUAnwHwZwCeAjAE4NUAXgbgn5GpFESkREfOt5/4deaiFDtfj9H6/SpVpFRuoOWCAqoSOoJ/IwvtBdD5SCdWXrOyKjoAKy5agXMnzymtp5g/NY+hG4fw/N88j42f21jxu1nsemA4OBTA6nesxtq/Wrt4DSl8vvkz80jcnbA8m2jk+hWEIhg6qWzsaISZhe9enoXReTf+SwAzALZJKY8JIf4MwJNSynuEEALAXciUCv0rjcekAFLN+fYjL140rHAij7LcgjfVG+jhvzhccbOyhZkFjOwawfzEPM4OnsWJr59grrjDQk0hwANrZM2Ibo+i9X+3YuyLY4aCFOX0FQ+pCddYXkw9fXAaA9cNoPOR4oG1kVH5rj1dhoNDSx16E7OJ5a5fQSmCoZPKxo6VmC2z7dVZGJ0dgF8F8M9SyvzhiRoAkFJKAB8RQrwewN0Afk/jcSlgVKf2/CiyKYLmrc2Y3Of/DbRLzcQ4uRhX9Qb6wv0v4IX7XyjanmRvEmcPn0V6Ko3h24e1tJMMEMCam9egrrVu8Yb+0xd+inMv+StHfvzJcYw/OY7otVF0PtKJdCpdNkiJ74xj4LoB16sRWTH7gqbiArJ4YG1mjY+RMpmVns8QC7OJOUEsgqGLrkpI1TQLo3MjsCiA5/P+PQeg8NX+J4BrNR6TAqpth/kNYXQ7+e2TOPDWA/jv1/43Drz1AE5++6Qtx1l3/zpbntdRovhMTG4DoVIX1NyNevTRUS3NsHojHH96HAPXnW9Prv3pKZ8NO/tdTSYlZuNnNiL+4TgimyI4ePNBpH6ewtxLc263TkluA76Jn5QvlBfriWmvpOVrBZs9ml3jkxsdz98sLD9Q07nPQS4QVBW0IhheZGUWxmt0fipOAIgV/Ht9wd+sAGDz9qIUFHZM7Rnx/Mefx9GPHV1WMuzkN08iFA1h7V+txWUfvEzb8WI9MbTf3o6RB0a0PacXjO4exdB7hiqPZGpajAtouhFKYGhHJlAb3T3KNB8XdD50Pu1jyejsm9xtl2ULwImvnFjyo2KzThe85gKcfMKeAQc/yh9h1b3Gx8qu6sVYSccJWhEML6qmWRidMwAHsTTg/wmA64QQGwFACNEK4K0ADmk8JlHZ0RvdfvHuX+DIh44UrRcMAOnxNI586Ah++Ye/1Hrcjk90oP32dq3P6Sh5fpQu2ZtEf3c/hm40EPznFIzyqdJ5Ixx92L/B/4qLVrjdBEvSqcz3z8ldaN1SbBbMzwFdeL09VVGSvUlL6RnFqDxfJVYCwVwRDDP8XATDi6ppFkZnB+BfAXQLIS7M/vtBZEb7+4UQfQB+CeAiAH+r8ZhEjnn+48/j+BeOG/rbscfG8PzHn6/8hyZ0fKIDXf/ehaatTVqf1ynjT40jcU+ibMpPpcdbmT4H1G6g1chvefKFckGU7tFZz1oAhm4cwsH3HUTi3gSSvUk0b212u1Xm1QBr/2KtLU89PzGvPT3DjrQNq4FgfGfcVOTm5yIYXlRNszA6OwB/j0x+/zkAkFL+J4DfB/AcgM0ARgG8V0r5uMZjEjnm6MeO2vr3RsR6YtjatxXbDmxDx4MdiH80jhUx/4zmJu5KWArYntv5HBL3JjCya0S5M2D2Bup1okG43QTH1a6stWV01tMkcOyzx5C4M4HhW4c9VRigobMhU860nGxRhrYdbbZ0wmtX1mpPz7AjbcNqIJgrgmHkGqYjbZKWqqZZGG23QSnlhJTyp1LKybyffUtKuVlK2SClfJmU8iFdxyNy0slvnyyZ9lNKejxt28Lg/LSn8OVhNG5oLLsget3frPNG0GuxcsnJb55cDID6Nvehv7vf9CidmRuoH8hpH5eDUZTb0I28YXpouux3u7Aogx2d8FhPTHt6hu60DV2BoJEiGI0bGrGixT+DQ35SLbMw3ktKIvKgscfHlB/nRMWOUHOoYjm7FReuqLp8aaOb7BSqtEGMJ9Sgqs6VLrkg6qVvvaT9uVdctML36VGeIoD43fFlAZDhUs4GNW9tthRYlxol1zp6rnlPmkpFMPbu3WvoeZwuolENzHx+vTwLY1sHQAjxBwD+QEr5m3Ydg8gp8+NqU8Ezz81obkl55Wodawl6azIVWKaHp/H8/XrXOCjL5kdP/mxySU34Sjex/Bvo8S8d987rwflNiDzdQXFDXhC1kNLfO7qg5wK89FX9HYvAkpm0v+ivRZcFQbnr0ZE7jlhOZ2p+ZWY9hO6d4lWerygb96RRrW/v5P4r1cjILsPpDWmEmkMutM4YO2cA4gC6bXx+IsfURtW+KlP9Uxh9dNTW/QjMKDVqVGk7ewDnc3izr+XE/z2BmcPOdnBKyuZH5zN6E4tsimDdfetw6runkHrW2iJjLbJBbu5c7d+231SA1Ly1GRe89gK8cP8LNjbSHa03tC5+fif2la+XryKyKYK5a+eCtbbAbmVKbcZ6Yri672rs27oPU/unlA9R11a3+P917xRv6vmKyN9R2Cuj7WY2SvPKvcuLdM3CuIUpQEQGtN7QipPfVMvn11XDXqdio0bRX4+WHc3I3cQWf/bqqHc6AEWYuYmN7h5F6oAHgn8Aq9++GnWtmYAmNZgyPTo6uW8SF7z2Ahta5r6xx8Zw8p9PYv60PTW106k0IpsjGP/BuKX1KvWX1uvb7bYKVNoJdf1fr7cUZOfn6uveKd7M88XviqM2WrssEMyVPvbCaLvZjdK8du/yIl27DDuNHQAiA1a9aRVC0ZDphcAAtGwB7wSzG6s1b2nG8ceMlUV1jYGb2OIN0SNraU985QROfOUEotdGEblS7aaSesbezkzT1iZM7VMfsbXCruAfgLZZk/o4OwCFjn/pOOra6opeV6yuCSiVXmRmQKOcth2ZAYSj9x0tOuhR7vm8Ntque6M08i92AIgMWvtXa3HkQ0eUHltpBMxLjI5m+OamUOEm5tVa8uNPj2dGoj2ktqUWW57agsimSMkRTQImfqA/PUmVCAts/MxGjH1xzNX1JMXW2OSPfueC9gNvPWBqoKVUDr+uneLL5cqH14ex9i/WLnYQij3WS6PtVjZK88O9i8zRVohLCLG64Ed7Adyj6/mJ3Nb8imasWK1eVq3ayhb6aVOtUpuI2VFLvvXdrVj1Fk2VnxRnJZqusmezuPlTmdH3ZG8S80nvbW1Py8kZiRWrVmDL3i245M8ucbs5SxTuchzriWHzNzZX3lMgx0AOv5Wd4kd3j5bduHDm8AyGbhpasktzPpXRdjvp3iiN/E1nJd4XhBBfE0L8JgBIKZ+SUt6t8fmJXJO7EZw7oV4i0I5NZdxmqh5yDdB+e7tr9feL3cSO3qt/s7apA1O4/J7LtT+vGRe/82LbOmdH7z2KgesHvLFgmgzJlTFu6GhwuSVFZEe/c9/PWE8MnQ8b2KfDxso6gPnR+8Lri5XRdrvo3iiN/E3nrfggMjv//psQ4qAQ4nYhRIvG5ydyheEbQQW6N5XxAsObamVv1h2f6EDXni6Eos6XRjvz5BmM7BpZ3El4dPcoTnzthPbjTO2bwoG3HFDO37cqlxJh147HJ752wpMpU1RaroyxZ9P2Cka/jWx0lb+xmB2sjt57cbRd90Zp5G/azqqU8kohxK8BuAmZjsDHAdwrhPgmgL+XUj6t61hETtKVI+7Zm69FZhfc1bXWqS2mtujkEydx8gl7dmYuNH1wOpPGIODs4mJxPiVC92ZLizyyWNqKVW9ZhcaNjZ7a+8FOuTLGkU0RNF3dZKnkpl0Kc8115fCr0JEr78XRdtV7ULXeu4JOa7dOSvkjAD8SQtwK4AZkOgP/E8A7hBAHAfwdgMellEwoI1/QlSOuawt4rzJzsw5MPqmE452Ahg0NS27Wuc7Z0J8MYWbYuyVbnda0pclSOp/ftN7Quvj/V75qpeUOQLQ7iuatzRj51IjWzmWyN7nsemGkKIGVTkKxx1oZvc8d14uj7bo3SiN/s+WTJqUcB/BpAJ/Ozgq8B8DbAHwSwH1CiK8D+IyUcp8dxyfSRUuwqnkLeC8zcrMOVD6pBCJXRVAbq3WkAsv0wellFTtiPTFc+cSV6NvcZ/vx/aJ2ZS2m+r03Cm6HUDSEVW86vyg9t8eE6ee5IITL7758SXDd8roW/PLGX2I2oafkqdlrw+ju0dKlOSvU1y9X3ad+bb2pduTkt9+ro+26N0oj/3JiOd4pAEkAM8iMhdUhMzvwUyHEE0KICx1oA5ESy8GqzQvV/MjqCFd9vB4tb2xxbTGxWalnUtj42Y3YdmAbOh7ssL0SS7FOq58qNjkh1hND3Rq1QNhv1v7V2iX/Vv3+pc+kl42sx3piuPS2Sy21L5/RtiV7k/hp508xdONQyc0ICysM5atU3Wf2qFqHZuLHExjZNbLYCTf7nXNitN3suq261rola6fsXKRMzrJlBkAIsQLAWwH8MYBrkQn8DwL4KIDHAPwKgA8BeCOAzyKTJkTkOVaCVbObzQSF6vtx2R2X4eJ3Xrx4gxzdPYqh93hnA69ykr3JJSUIpwambKuhX6rTamrkr4rlFpbOHZtzuSX2a313Ky774GVLfmblelQsRUfn9c3Ic5n63hepr2/ndeP0907j9PdOA8jMQLT8TgvGfzjuudF2I+u2Wt7QgrEvjGFox9Dy3zu8ezHZQ2sHQAjRgUze/7sBtABIA3gCwOeklL15f7oXwF4hxD8B+G2dbSDSSfUCt/mJzUum3ek81TzUdfetW/Kzth1tOPPDM97fjRjLg3I7g/Gp/ikk7k1o3221Wswn56s+HSoUDWHtX61dFvwDme9ffbxeKW3nzJNn0H5L+7LnM/t9LsbI6LfSrt15FXpKpfzYYfzpcYz/cBytN7RmyrCW+865MFNcbt3WxE8mPLV7MdlD50Zg/w5gCMAHAMwhM9ofl1K+tSD4z7cfwEpdbahECLFCCHGrEOIfhBD/LYSYE0JIIcSNTrWB/EV1GpfBf3lm9w8oNTLWvKVZV5NsVTiTZHgaXsHJb55E4s4Ehm8dRt/mPvR39y+mBVUqrxgEqWeqL4Wh6RVNuKDnAqx6yypsfmIzXn3m1UWD/5yW16tV6D757ZNFU8wsl5w1OPqtWpFt/Knxsik/tlnI7MGw7v51rpY0Ladwo7S5sTlL+x+Qf+icAfhNAE8C+ByAJ6SURur8/T8AxzS2oZIIgL/N/v/jAMYA6EtgpKrERVP6GR6NrjAy5tiImQDab2vHyCdHlB5erJ1GpuGnh6cx96K1VJXxp8cxcN0AVr9jNRpf3ojalbVofVcrxn9gMDWBPG/qv6fQtafL8PfhkpsvwbHPKdx6ZWY0vfA4S77PZhkc/bZckc2tz/oCcOq7p7Bl75Ylo+3pVBoCAjWRGqQGU6hrrfNEtR2V/Q/qWuscL9VK1unsALxMSmnq2y+lPADggMY2VHIWwOsB/LeUclQIcReAjzh4fPIhXcEqLWV2/4BidKUfVNLyphZ0PNCByX2Tpo9VLrWh3DT83NgcBq4b0NF8QAInvqJ/0zOntby5BbHXxDA7OosX7n/B7eZ4x8LSwLxSWUwr35vCevc5ue/zjw//GOkpY/t8mFkn5eZIs2rKVE7+ezY3NlcyFcnt3HrV/Q+KpdS5/VqoMp0bgSl0/Z0lpZwD8C9ut4P8R0ewSsvp2OzHicWtsdfEzh/rugHjOcjC2IxQsfKpB28+6IsFzk5ad+86RDZFkBpMebIDUNNUg4Upd4aax58ax+juUYw9PmYouDT9Wc5TbDEwkPk+N4YasTCzgI4HO5Z8n3OPU63Vf/r7p803VJNLb7t0cX+A098/v9DXjGRv0vO59To7WW6/FqqM+zsTGeTmzpTVzsj+AaU4sbg1F8DEemLofLjTWBURAXQ+ojYjpGsDumqTCzydmPmJvTaG5L+bC4gWphYQvzuOxF0JVzpv5T6XhQFZrCeGlje14NQTp0wfp1J55JpwzbLFwgBMf8fL1ep3Uu4aH9kUwfzEvFIHYLJ/EscfP244tz6/cpFTtO/R4uJrocqElMEdYspLAXqPlPIRk4/dX+JXV2zYsKHxoYcesto8z5ucnAQANDf7YyFmtXL7PCzMLCA9kYZckBA1AqGVIdSEnS/Sn55MY3Z01nD6gVGhphAaNzYuP9bILNLTmWMttGfu6jUjmdcdagihvr0eoeaQ0jHPnTiHmRHu3FuodmUtGjoaAGTOwdlDZ5f8vvA8WD2WSkAUbg8DIWDmqHfPX+OGRoSaQ8qfs3B7GCtWryj6O13Xo3OnznniPSz8/qu+ZzV1NViYMz5CUey6Y4bKebDrumP1tfiVU/fmm266CYcOHfqZlPJqM4/jDAARKSkXcIeaQqhvUw+AVYSaQ2hsblzWIUEoE0yodgzq25bvChpqDqHxZZljnTt1DrM1mfzguovrsKJlheUOkFwI7sBMOfMT85g5OoPw2jBCzSGE14Y9ESTmmzsxh1CTc597FbOjs2hsbkRopVo7VR9nVHoy7ZnzWvj9V33tZoJ/AEhPpbEws+DoYIpd59WN10KV+a4DIIRIAFhb6e/y/KOU8p2621GqpyWE2N/c3PyK7du36z6k5+zduxcAEITX6mVunIfR3aMYumkIjQtlRnWyi6J15n9aSb/Kf+zZwbM48bUT5dM0cu3/3crt130ORnaNYPj2YS3P5QRRLyBnneu0rPubdYtlLvuu6kPq2Uxpz8kHsiNut1sfcbvoHRfhpa++pPz4MMKW22CnbQe2ZRaa325uoXm0O4ot799S8vc6vgv93f0IPe1yJ6rM97//vn5TaUnh9eGSOxaX0/FgR9FUKiNUz4PZ12aUldfiV07dm1VnGHzXAQBwGICZb5KTZUaJqt7iZjwO5rKWywU2Wm2icJ1B0yuacPRjR5EeLzKDkd1Iya3Fa37Ll3Uy+AeAox87iss+eBlSg6nF4F+3l76uHvz7QbI3iZe+Yf412l3m2AvrXyoVdTBbGvqCV1+AscNjptuhPSffALuKKrjxWqg833UApJQ9breBKMhU6kRbCWhzsw1WK2csmwH4+omSz5keT+PIHUewomWFK50Ap8qb+lV6PI2T3z6J03tsrAxT5XsknD10VunzVddaV/J3qcEUzp04B7kgMbJrRKlAgqsbS4nsqP+O8t95s6Wh01Np4DHzzSncQNAJdhVVcOO1UHk8I0RkmGqd6GJ1w41I9iaNVdwpM9ugXEnE5QoWTpQ39bPEPQlM9U+53Qz3CShVHJo7prbBXLESoPnfsZkHMhP0uRQ2s/XgXRspzlbtMtrhN1MaOjWoNkvl1kxgpdemotxrYWU9d7ADQESGqY7OlaobXompWvhFZhsqzR6oPKdTnChv6mdTP3Mw+FcMsi2ryexAPblvsmggFu4Io/VdrUh8JGH6qesvWb643YjCAF3XDF2OWyPFa967Zkn7jASlRktDq8zoldtA0AnlXtvBmw9qeS06UjtJXeA6AEKIOwBckf3nr2T/+4dCiN/I/v8fmi0JSlStCi/+hWUXjVIZ1RvdPYrpg9OmHpM/22B4rYKJ53SaHSNxy9QAnQ91Ip1KY35iHgupBTx///P2HMun1ty8Bqe+e8rSbrBmFeahj+4exdH7ji5ZTDozPKMU/DdsbFgsp2pWfoBux3ogtwK+S26+BIBaUGpkHxOz6wbsXmthVLHXpuO16O44knmB6wAA+G0A3QU/+7Xs/3LYAaBA070Bj8qo3tH7jiodKzfbYGqtQgXP7XwOl99zuSudgPyRuKP3HsWJr57Q9+RFKjUle5PsABSoa63DpbddiuFb7anMVNNcgwuvuxD1l9SjoaNh2Qiy5ZmsAtOHphGKqFXZyQ9+7VgP5Mb6l9wItZ1Bqdl1A14e+bb6WtwoJEHLBa4oq5Ryu5RSlPnfu91uI5GbRnePYuD6Aa03YLMX79RgSqlsHpCZbdBdSeTkN0+ib3Mf+rv7XVukODc2l1m4rEm0O4quPV3LApnEPQltxzAiFHWw3KNQe1gu9cEuC5MLuPyey7Fh1wa039K+JPjXNZO1hATGvjiG6LVRUw/LT+Wwsh6okvjOuPHopAZov71dPZrJjlCbDUpVrgNtO9rQtacL0e7i73up76QXWXktKh1H0i+IMwBEgWN0kZUdwYZKLquVILt2Za1tQbpb09KpwRSG/tjaebnsjstQE6kpe/7dKMFYrAyrXeJ3x5HYmTD9uNz7ZefIdKl1MjpnsvKNPzWOzkc6Mf7DccPP3/KGlsX/b+d6ILMjzG1/1IaW17WYT5XLG6Hu7+53pLqZ0XUDTrDahnKvBcic6/Efjy95bqcLSVBp7AAQVTGz+azagw3FXFYrlUBiPTG89C0ba7g7OC2tKxUr2h3FuvvWGTqe1zW/shmT/zWp9NiL3nIRkv+eVF7AaGdlpmKfebs7ZOlU2tRC8/zSuKrfUaOPM1NlBygejE72TeLMf5wpvlt53l4fbgSlRtYN2EX34tv815LsTZZcJBy9NorIZrXXrFpIgkpjB4CoSpnNZ9UebFjIZVWtBBLuCC8uALZV3gigjtrnxWjL+zbRCfPyZj25gK3l9S3o29yn9BzJ3qSlBYx2VmYq9pm3+3M8PzGP9lvace70ORz50JHKD8jr/Kp+R/MfV2kEWmW0PBeMju4eReI7CUN7fRTrIBjhx6DUznUORp57/Adq9xgvX5v8ih0AoiqksshKtVZ1MZV20qxE9XFr71hr6fFmjD81jv3b9mNy36Tl2ueFtKViCXOdMC9v1vOK/3zFYrBVH69XqsgzPzFveQGjXZWZip0ju4Oe3Pk+9Z1Txh+U7fxu/OxGpWOG14Zx8H0Hceo7pzB7dPk5LPbdMTtabvb613pDq+Hnzue3oNTOxbeGn1uxnK6Xr01+xXe0Cnghl5C8Rak6x2vVgtVL/uwSNHQ0GPr8Gf2squRbN2xsWNzBM7IpgvD6sPJCYqMm9xVPRbG6VkBXKtaam9eYOr6XK23kj7a2vL4Fxz53zPRzTPVPITWYMp1eAiz/7OYC4GRvElP9Uxh7bEzxlZVeJ2N30JMbXVdJfwFg+jsaioZw4M0Hyj+3hnU2Zq9/Z35wRuk4fgtK7dzF3a61Kjlevjb5lb8+vbQEN9GgYlRv6NFfNVcRJKehowHtt7SX/RuVz6qpVA0BbPzc0hHJC159AcYOqwdllimuFdCZinXJey8x9fcTP5nQclw75I+2XnLzJUodgJPfPImT3zy5+JnbsndLxU6pkc9u+y3tiP5G1Niu1YUE0Pqu4iPQdl6/c52OkV0jSo9/8fMvYv6MuRFwwwu+LayzUfn+qA4U+On+auc6B7vXqri9KVq1ClwZ0GpRqVRjbhRl9NFRh1tGblPNG5aKc7OVboKqn9VcqkbFq1QN0PnI8lSNpi1NFdtuO4USdrryvs3eNBen8D0qf7R1bmzOUvnQ/M9cZFME7be0I/7h+LISnGY+u2072tD1b12IXGUyUJHA0I1DRUvM5mbCtMtb26CaxnLsc8eQekZf2uAyiuUfVb8/4fVhU3/vt6DUStUmu57bEA9tilZt2AHwISfqFZN/qd7QQ5GQpbrgxVj9rFqpNe2V0Tmjtc9ztOQVK9w07Z7Ctyp/R9yB6weslw+tcH1U+ezGemLYNrAN2w5sw2V3XIbmVzYjdKGxjkqpjrCpmvhGFKxtUE5jMTheUBNRb7zZ7w6g/v2Jvjpqau8BvwWldlZtUr5mVdqXwwebovkZOwA+xE00qBwr1TnMbsBT6Sao47Ma64lhy94t2HZgGzoe7ED8o3F0PNiBbQe2YcveLSVvDraNniow0wm3nFescNNUnsJX3FjLrFxHU/s+FWWuj2Y/u0fuOF9FJ7IpgnX3rcPVP70arz71anQ+0mnsvSrSKTE8E2ZAsQ6z3cHVQsrayTI7gKX6/Wne0mx8xtGHQamOqk26n3vNzWuqYlM0v+IaAJ/hJhpUiZXKO5FNEW3b1ev+rKrUzbazbrsZZkbIwmvNpSIseWxHGGvvWGv6pqk6S7jm5jVIHUgVXUgbiob0bPKV19G0Y5ai2GdO5bM7uW8S+7buw/q/Xr/4vcitL3jhUy8YXxtQZPGl0cpD4Q1hLKQWMHdsbtnvmrc2F63MZfcGZ1YZ+e7kr+OYSajl84fXhrHqTatMLw73Czsrsqk+9yXvvWRxczAWMnEeOwA+Y+fui+R9pXZczKdyQ89P5VGpkFKMFz6rdtZtN8PMCNnMUfXKRTPDMxi6cQhjj4+ZKgJw5skzSsera63Dxs9sLHkDTw2mcPxLx/H8/c8rPX9+R9POhYaFnznVz+7U/ikMXD+A9tvaMdk3qdzeYp2SWE8MM4mZzHOW6EzMHCr92ZncN1myuo5XOsrFlPvu6NooDzj/vfPSTr06Wb0v2Pncbm6KFmTsAPiM3bsvkjeVu9Gd/fuzqG+rX/IzK5sdAXpugm5/VvPbvuZP1mDyvyZLlu00qmlrE6b2TZl+nJkRMh2v30wpxWRvEie/fVLpOLngrNQNPJcKM/6jcdNBWmFH0861TIXvuaVzsACMPKBWWSffi59/ERs/c76y1WL6k2Id9Vzbhm7MPEc6lV7yvTbUURawdnwFpb472jbKyyo859UYlFq9L7j13GQPdgB8xs48PrKH1ZGkSje69FQaZw+dzVQiyQZ7Vjc7yrFyE3Trs1qus9R0dRNWvmolTn33lKmNpMIdYVz5xJWIbIqgv7vfllG0HG3fVYOlFBP3JJSDutnRWUPphWZLunY+3Lm4p0OOnYMYC6kFjOwaWfyOWs1b1+HY546h+RXNi99pbelP2apDhaLXRrHu/nU49d1TJWf+IpsiSuVXVYXXh4t+trSvBYGe753XZw103RdKPXf8I3Ek7kqUv574dA1FNWJU6DNO76xK6nTs02DmRlcY7OlK5VFl9bOqcjOt1Fma2j+FqZ9NmQ54Z4bPp1aojnQZfT1az0eFzXysptW8cP8LeOH+Fyp+ns0GHsVmLewcxFBOUbJTNlAPrw2jrrXO9hz98afHMf7DcXQ+3ImNn91YMqXLyQ7ABa++oOjP7VgLYuV756c9eey4LxhNxfLzGopqxA6Az9iZx0f6VApEjaZoWN250c18VtXP6tzYHA7efND0zdTurehzeeJmg1kAJWcNir0e3Ysyyy2s1pVWY+TzbDXwCGTQIIGDf3oQl9xsbkM3ZdlZo649XUU393N6wXCxvTzsWAti5R6p61rvJJ33BUOpWAKI3x1n2o/HsAPgQ8y18zaz9cNLpWjorKLjVj6r2c9q89bmsn9f7mZqdx37/BQUo8HsTGJG6fXoXpRZamG11rQaAylHVgIPr1erscv00DSS/+HgXi4VZo2cXDBcqqOvlYV7pK5rvVus3hfMDLok7kog+mtRT73+oOM+AD5kaodU5to5Ttc+DXbu3OgUM5/V9tvaMfKpEaVNw+zeih5YnoKSvz9BuD2M+jX1S/YnAGA8OLjRvtrvQOlAX3tajcF9R8rtvltOfGfcsb0HvGT8P53t9JTbgEv3Z7OUwlH51GAKI7tGcPKf1RasF2XxHhn0PXmC/vr9jh0An7KyQyrZx8qofSG3q+joYvSzOtk3qXwzcaLTU26h9IrVK1DXWrckmDV1c5TAgbceWPI62na0Yd396xCKGttJtpxSgb4dgwMqu7caFeuJof39y1NTqt38See/0+W+U7nvdHi9+p4VZeWNyid7k+jv7kff5j4M3zqMM71ntBzC6j1S57Xej4L++qsBU4B8rFrrFfuZztr31VTxqdJn1Wq6k92dHjM5wqnBFMa+NGb69aTH00vSgUZ3j2Z2l9WQalFpt2Tdsyd27jsy2WehlKsALnzdhTj9vdP6GuSQ8PowZg6r7xFhVqXvVKwnhiu/fSX6NvfpPXDeqLzOUp+r37EajZsatd0jvbDPiZuC/vqrgfciBTKtGusV+5XOUftqrPhU6rNq9WZia6fHYI5wejJtukToMtn0pnOnzmkL/it1XuzI6barQ2Yl1Su3LmP8x+O+7ACsWLUCM0dmHKvDb+Q7pdKBjFwVQW2stuJCcN2lPk98/YTWhbjVMkOrKuivvxqwA0Ckkc5R+yBVfLJ6M1Hu9NRASz3sc6fOYeboDEJPW0/XwQJw9GNH9QQ+BjovduyWbFeHTLWjeOkdl2L9fesBwLcpCJM/tbaJnVnhteEleyOUGjU3u9C/45MdhmautS/q17wQt5pmaFUE/fVXA54JIo10j9oHpeKT1ZuJamcpfmfccj3sZG8SM0f1pmakx9PWn8TEAsdKVY3MsmMWKjWYwunvq43chyLnO2Z2zpBFu6MIx8M4/oXjth3DCaFoCAfefGDZz4uVrVXdXKrczLVti/orVDgyoxpnaM0I+uuvBuwAEGmke9TezOisGxWfdK0/0XEzUeks6VhHk7gnAbxJqfm2Udlwp9R7Mfb4GKb2T5k6ts5ZqNHdozh631FL+e/5HUw71j2sessqXH7P5YhsimBk14izHQABrHnvGlxy8yWY+MmElpmcUh3QUmVr8zuQk1g+U2H282jnov5y+2KYEaQZ2mKC/vqrATsARJrpHrWvNDobagqhvq0ebb/rXMUn3Ttf6riZWNnmXnUdzeJIpQc6ABf0XIBVb1xleYFj4XsR2RRxZRYq2ZvEwfcexPShacvPVfhZ1L3uIRf8Ay7kOMvzaU3pVBoX33Axxn84vmT3aq1KpNLkOpDJf00iPZFG/KNx5UEBu99DXQtRgzJDW0rQX7/fsQNApJmVQLTcc5Yaqe57SXMVjgrs2vlSx83Ejm3uy/HSngur3riq6O6tVtnxea5kdPcoht4zpGXBa7FRR53rHgqf340c5/GnxotW4wmvD+OCV1+Api1NiPXEMDc2V3ogIRoynnpWJpWmJlyDmnAN4m+Lm30Zi+x+D3V1MHR9N/xayc+NawPpww4AkQ3sCkRzN4XczSLZm8TCxgXUhJ3Z0sPOnS9VbybFbp5b9m6x9aaae26tmxJZZOfN1cmO1eJnTEe1mzKjjrnXdOCtB9TXXBR5fi8FOTOHZzD23Bg6X925OLNTbCAhvDZcNOe/HF2pNMXY/R7q7GBY+W7onkl1g9ODLqQPOwAUKE6OtOjep6HUzSL1QAqhphCS6aTtF1mVnR/NtMnMzcTIzVP3iHi5Y7rJidxap/Yd0Vb9xcCoY11rnaUF18WeXyWdrWlrE1rf1Yr5iXlM/HhCb5nSIp3xwjSvkV0jSk9tV013u/anyNF9nVT5btg1k+oG7knkT+wAUCC4OdKiY5+GSjeL9FTa9puF1c26jDJyM7Fy81S9SenclEgrh3Nr7dx3RFf1l6atTVh5zUrMHpvFyK6RkufYagrXymtWFv252XS29fevX7z+jOwa0b9PQYXOuBdrutuxPwVgb2fZ6HfDzplUN3FPIn9hB4Cqnt9HWrxys3B658dym4apvB9WOoG6NyXSRlRXbq3VgDzUmCn3ObVvClP7llYuKnaOrQawpT7bVnKj7TqX5TrjXqzpvvgealoLAsAzC1HtnkklMsKZxGEil5gNFr20qDNH5WZhB6+MEqq8H6O7RzFw/UDJ0eVcJ3D00VHrxyxHAHVr6jQ8UYZXO62qrH5W0mfTSJ8tX8Iy/xxbDWDLtbdtRxu69nQh2h0t+vtodxRde7qWnb9c+osdSl3fvFrTvW1HG9bcvEbPk3lkIaqVmVQinTgDQFXN7yMtTqXdGOGFUULV92P8B+PKMyjaNiXKBiCzx2aRuDNh+emi3VG07aie4B9woIJOwTm2+l2v1F7V3Gi70l9KdVi8XNO9rtV6h9lLC1GdnkklKoUzAFS1qmGkxcrNQjcvjBIqvy4LMyg63sv80V4tQa5HUhl0cyRAyzvHVkfbjbY3simC9lvaEf9wZmF6pUAul/6i+w5d7rMX3xk3fjwHP3+q35cLX38hOh7swLYD27Bl7xZPBP+Ad2ZSidgBoKrlpeBZlZduFirBku5RQidugoWdQNVjXtBzQdEAxHIg4pFUBjvYmf6SL/8cmwp889g9Al4phUhFuc+M4U6Hw58/1eOs/5v1hjpbTvPCTCoRwA4AVTEvBc+qvHazcHuU0KmbYH4nUPWYuY25CgMQK0FutDuKzoc6kZ5KI3FvAiO7Rjw1Y6WDakBuVu4cLwa+wsSDi3y2U4MpjOwa0XpecntabDuwDR0PdiD+0fhip9KOzrjqugU7eWHgQScvzKQSAVwDQFXMa8GzCq/dLNze+dGpm2B+J9COc2Aqx1sAa967Bs2vaMbY42MYunFo2Z9UqmLkp/rcOnfpLSf/HOf2nzh480FMH5wu/8CCz7YTJYaLVcRq+Z0WUymOLW9oMfR3XqzprmOXcK/w8noLChbvRDpEmnkteFbhxZuF0zs/FgYiTVc3YWr/VOUHWpDfCbTjHJjtSEFCqZStX3cazS1uLtbZ0aWwox/rieGaoWswunsUR+87ipnDM8seU/jZdrPE8KnvnDL39989hcs+eJnhv/dSTXe3Bx50q6YODfkXOwBUtbwYPKvw4s3CiVHCcoGYYQJKNcQLAwg7zoHRjhQAY8cuqHDj9/0v0in1HXqNKBUktu1oQ9uOtoqfbTf351AtcDC6e9S3laOMfl/qWuswsmvEEzMXpbjRofHSjA55AzsAVNW8GDyb5eXRLztGCZO9SRx870FMH6qQilFJDdB+WztGHxlFetx4MFmsE2jXOTDSkerv7leqYuSFzeOssHMtjpGOfqXPtpslhlULFQy9ZwgQ8GSHz4hy35e5sTlfzXY5NZPq11lAsh87AFTVvBw8m1HpZhFqCqFrT5dn22/U6O5RLTt/RrujaN7ajJFPjZjLIy/TCbTzHJQKNlVHeo+kjjganNoxumjbWhwNHX039ufIf48nfjyh9ByQ3u3wmVH4ffHrbJfdM6nnTp3DwNtKD4B59X0hZ7ADQFXP6Zx1u5S6WRzceBA14RrEtnu7/ZUsplSYDP6btzbj4nddvGw00PRGSgY6gU6fA9WR3sl9k6b+XjU4tXN00Zbvo6aOvpObOZV7j5V4cMNDK9xMxdLFjpnU9GQaM0dnsGJhRfk/9PD7QvZiB4ACwYuVLVQV3iyG9w672Bp9TKVU5JncN4krHrtiyXty8OaDpp4rFA1h8zc2m9rYyYlz4GRJWrPBqdlRV7PfPZU1PKGGEBAq/judHX2nSgxXeo9V2bVbuBv8vtu7XWZHZ43/cYDeFzqPHQAKFC9VtqDzVFIq8uUHryrPlR5Po661Tvn4dnGyJK2Z4NTUqOuNQxh5cASpZ5bXxa80S2B2DU99ez1CzSFsO7DN1o6+EyWGDb/HilRmI7zGjVSsSu3xwgBTajCF9JS5RfTV1CkkY9gBICLXWd19OT94dTI9w25OjsiZCU5NjbpKFA3+gco5yGbX8Aw1Z8qG2t3RdyKtSXVGzCgvbXioyivfda8ttPXK+0Lexp2Aich1VoOR/OBVR3qGHbu6qlDZBbVpa5PSsYwGKFZna5bJ5iCXClqCuDut9ve4CC9teKjKC7u9j+4excD1AyXPV66TO/roqLZjVuKF94W8z/9XACLyPavBSH7waiU9w2sjeYD5NJj19683vWjUTHBqdbamqAo5yF5cw2NniWFb3uMC1ZDv7fZu715dgFy7shZQiOWroVNIxvFsE5HrrNwUC4NX1eeaPzNfNqDTUTJPJYBVLWVrODgVQOu7Wg2/BrtGCY3kIHtpDY+dJYbtHolt3trsmffRCrcrTHl1AXKsJwZ8X/FxFBhMASIi16mkVAAoOrKq8lyRqyJI3J0wPJJndoQ22ZtEf3c/+jb3YfjWYSTuTGD41mH0be5Df3d/xeczmwaTC04NXeFlZqGukXYA9o4SOjHyrZNd6Ul2j8Q2v7LZ1ud3it2pWOVYWYBst8imCEJNJcphlaDrfSH/4AwAEXmCqZQKABClR1bNpmcAsG0kT9cmRWbTYCrtf2GlHXbxYw6yHelJdo/E1rV5r+KVKrd2e/f6Qtv6tnqcPXTW2B9rfF/IPzgDQESeYGbUuqGzAV3/Vnpk1fBz1QDxu+Ilq9SUYnQkz2yOsJGgIrIpgvZb2hH/cBztt7SXDSZiPTFs2bsFnY90AqLiUxtqh/JsjQF+zkE2c16MPJdd7zHg7/e5kJnvus7d3r2+0DbUHEJ4bdjx94X8I1AdACHEBiHEnwsh/kMI8YIQYk4IcVwI8W0hxGvcbh9R0FVKqQivD6PzkU5c88trKt6wjKZn1EbVgiEjwbpKjrAdxh4fM77DsoF2xHfGbbl7hNeGPVF9yQvseo+B6sv1dqNSlNsLkI1Y0bLCcxW0yDuqZxjAmI8CeDuAnwP4HoDTADoBvBHAG4UQt0opd7nYPqLA05lSYeS5xn+sVm7xhU+9gMimSMlgyiubFNnRDsMLYE0IRUM48OYDy37uVvUlt9nxHgPVm+vtdKUotxcgmzme1ypokTcErQPwrwD+WkrZn/9DIUQ3gH8D8HEhxP+VUjpXsJeIitJZ8aXcc6mOyM0mZhdz5rFu+e+9kiNsVzsqrTGIXBVB6tmU4ZmH9HjxnUt1VF/yCrNBWKX3ONodRcsbWnDkjiOO58B7lVOVonJpWnaV29XNSxW0yBsC1QGQUj5W4udPCSH2ArgOwK8B+IaDzSIiF1kakcvmzKefSCPUvLTqhldyhO1sR6XRxUoLoA1zuI66blb2lzAygrviwhW2lCOl8txagEykQ6A6ABWcy/7Xf2UoiEiZykjeEgvA7OgsGpsbl/zYKznCTrSj2OhiajCFdCqNi2+4GOM/HMfM8Myyx4WioZIj/8s4WEddJ11VoMqN4BqZKYjfubSTwZQQ6+zcC4LIbkJKoyvDqpcQYi2AIQBpAO1Syopz5kKI/SV+dcWGDRsaH3roIZ1N9KTJyUkAQHNzddSU9iueB+vSk2njJfOKWGhfQE24Bs0rz5+DhZkFpH5ufhFr5OUR1IT1rf50uh3pyTRmR2eRnloe2NfU1SDUHEKoIQRRLzB9eFpru7z2XTD7uWrc0LhsJsmshZkFpCfSkAsSokYgtDK05P0qd35CTSHUt9VbaoPXzoET7H5PVQTxPHiNU+fgpptuwqFDh34mpbzazOMCPwMghKgH8I8A6gF8yEjwT0TVJVcyb+bo8lFqo2R66WBKTbgGoaZQ0aCgZDuaQlqDf6fbce7UubLv4cLcAhZOLSC0NgQ5qzb4lJ5Ia3+P7DI7Omv67wtnksyqCdeUfH8qnZ/0VKbDEl4bxoqWFZbaESSh5hAamxsrdr6IvMR3HQAhRALAWhMP+Ucp5TtLPFcIwBcB/DqArwH4hNEnLdXTEkLsb25ufsX27dtNNNGf9u7dCwAIwmv1Mp4HfZK9Sfzyxl9iNmEucJt8YBL1a+qXnYNkOmkqR7hrTxdi2/WnCTjRjmRvEgNvG8CKBQOBYw3QekMrxh4bM3UMAIh/NI742+JFf7d3714szCyg45kO11NbUoMp9L2mz/Tjth3Ypq29+Wk+c6NzOPZ3xwyfn649XUopK7weeQPPg/ucOgeqMwy+6wAAOAzAzDDdsWI/zAb/XwLw+wC+DuCdkvlQRIEW64nh0tsuxfCtw6YfK2rO77SVH3itfttqnPj6CVdzhJ3IVTa758GZH5wxfQyg9NqEZG8SZw+fRXoqjeHbl54/N0qJulkFqtyiY0N8ut6CiIzzXQdAStlj9TmEELUAvoxM8P9lADdIKY3PjxNR1VINekIrQ2UDr1ILXost0LSDykJRo1T2Gpg5rJZuVax9uYW26Y97p5SoavUlK2tRgMqLjo2yY08KIvIO33UArBJC1CEz4v8mAI8D+EMppcZtVojIz1SqAoWaQkin0hh4W+k0m/R4GhDA6nesRuPLG11JT7FrU6AXP/+i0uPC68OmOgLF6qgne5PGAl6HS4mqVl869pljSD2TUpqxMPxemHg+dgCIqlOgOgDZBb/fBPB6ALsB3MTgn4gKma3vXRutxczRmcr51RI48bUTyvnVuujeFOjUd04pPS766ihmnpuxVEfdbOqRU6ktVo6hOmNh6r0wQPeeFETkHUFbnv53yAT/JwG8CGCnEOKugv9td7OBROS+XM58xStkNmd+ftxEoJQNQqtFajCF2aPmFk3nNG9pNvU+FwbVKqlHudQWu+VmkpRlZyyMriVQeS8q0b0nBRF5R9C+3Zdn/7sKwM4yf7fX/qYQkZcZzZmva61D+vvmlhBVU3616mJXAIupR6prE9xcaGuEqZmkYkzMWFg5D6VwETBR9QpUB0BKud3tNhCRfxjJmR/ZNaL03NWSX62aJlIfr198/aprE1SP7VRqi+HqS2UY7Szqfk3F1lsQUfUIVAeAiEhFuZz5+Yl5QGHvpmrJr1ZNE2l5fcuyn5ldm6B6bCdTWyrNJBlhpLOo9TWVWG9BRNUjaGsAiIi08kMQaifVNJFLbr7EtWM7ndoS64lhy94tuOTP1F6zkc6ittdk854UROQN7AAQEVnglyDULiqLXXWll7h5bBUNHQ1KjzPSWbS86BiZ96ZrT5djeyV4TWowhZFdI0jcm8DIrhFHFosTuaU6hqCIiFwS2RRB6D9DSE8ZXwhcbfnVZsum6kwvcfPYZtndWTT1Xghgzc1rUNda58qeFF5SbgM/N3aRJnICZwCIiCyqb6s3/sdVmF9ttmyqzmDKzWObZfeMhan34pFObPzMRsQ/HEf7Le2BDf5Hd49i4PqBkiVUc3syjD466nDLiOzFDgARkUWh5hDCa8O+CELt0rajDV17uhDtLh7g2plekjt2qCnk+LHNiu+MG7/zKnQW3TwPZngh3cbsLtJ2lFolcgtTgIiINFjRsgJde7qU6tlXC9VynrqO3RhqxMLMAjoe7HD02GYYLg1qobPo5nmoxEvpNl7dRZrICewAEBFlWQ2YvBx4OclsOU+dasI1aL+l3ZVjG2V0kzmrwaab56GY0d2jZTs+uXSbzoc7bZ+hsLKLtJfeUyJV7AAQUeDpHpX0WuBF3uOVzqJTxzebbhNeG7Z1tN3ru0gT2Y0dACIKNC+NSlLwuNVZdDoVx2vpNl7fRZrIbuwAEFFVUBnJ9NqoJJEdCr8b82fmkbg74Vin14vpNkHfwI+In2Qi8jUrI5leG5Uk0qncd6MijZ1eL6bbBH0DPyKWASUi37JSw9vKqKSdvFAekfyv0nfDkGyn1yovptv4bRdpIt04A0BEvpJLZ5jqn8LYF8YAWeEBJUYyvTYq6aXyiJW4tXDV7QWzfmE4tc0AHak4Xk238dMu0kS6sQNARL5gNZ2hMH3HS6OSflmI7FYnxU+dIy8wldpmgNVOr1fTbZzYk4HIq5gCRESepyOdoTB9xyujkn7ZjdRKupUfj6uDG+lcKqltlVjt9Ho53cYvOycT6cYZACLyNJ3pDPkjmV4ZlfTDQmS3qiWZPW76iTRCzSHLx7XKzRkLOzqIOjq9Xk638cqeDERO4gwAEXmaznSG/JFML4xKenUhciGVToobx50dndVyXCvcnrGwI0VNR2cll25TMepwMd0msimC9lvaEf9wHO23tDP4p6rGDgAReZbudIbCkcz4zrjxq6ANo5JWFiI7xa1Oispx01NpLMxoTH43yQvpXLpT1HR2epluQ+QdTAEiIs/SHSAVjiq6vQjQSwuRS3GrWpLqcdMTaeVjWuV0OlexlBWtn1EbOr1MtyHyBnYAiMizdAa6pUYy23a0IRwPI/HRBMafKpKz3R1F/E57cra9shC5HLc6KaqPlwuV6sLaw8ndbiutMYhcGUHqWYtpYjan4kQ2RRjwE7mIHQAi8ixtgW6FkUy3RiW9shC5HLc6KaqPFzXC0nFVOTVTYqRkLAQy/1PsC9nZ6SUib2AHgIg8S0sAYmIk0+lRydxCZDMjx07vRupWJ0X18aGV7lQBcmKmxPAaAwljnYAaIH5XHLXRWqbiEAUMOwBE5FkqAXI+P4xkerk8IuBeJ0XluKGmEGrC7tS2cGKmxNQaAwlEroqgNlbreGobEXkfOwBE5GmmAmQBXPwHF6N5S7NvRjLdXohshFudFLPHrW+r13JcFXbPlKisMUg9k8K2A9sAgAtuiWgJlgElIk8zVT/8kU687B9e5rsa3l4vj+hWDXezx3VzEzC795WwusaA9e2JKB9nAIjI89ys1OMUr5dHdOscmDnu0N4hrcc2y86ZEj+UjCUi/2AHgIh8wesBsi5eLo/oZrUkP5x7O9O5/FAyloj8g1cGIvIVLwfIQeHWOfDDubdrpsQPJWOJyD/YASAiItLIjhkLP5SMJSL/YAeAiIjIBrpnLLxeMpaI/INVgIiIiHzArWpMRFR92AEgIiLyCa+XjCUif2AKEBERkY/4pSoSEXkXOwBEREQ+5IeqSETkTUwBIiIiIiIKEHYAiIiIiIgChB0AIiIiIqIAYQeAiIiIiChA2AEgIiIiIgoQdgCIiIiIiAKEHQAiIiIiogBhB4CIiIiIKEDYASAiIiIiChB2AIiIiIiIAoQdACIiIiKiAGEHgIiIiIgoQNgBICIiIiIKkEB1AIQQlwohPieE+KkQYkwIMSuEOCaE+IEQ4g+FECvcbiMRERERkZ1q3W6Aw9YD+N8AfgrgCQCnAbQAeB2ARwHcIIS4Tko571oLiYiIyHNSgykke5OYn5hH7cpaxHpiiGyKuN0sIiVB6wD8CEBMSrmQ/8PsyP8eANsBvAXA151vGhEREXlNsjeJxD0JjD89vux30WujiO+MI9YTc6FlROoClQIkpZwrDP6zPz+HzIwAAGxwtFFERETkSaO7RzFw/UDR4B8Axp8ex8D1Axh9dNThlhFZE6gOQClCiBCA12f/+YybbSEiIiL3JXuTGLppCFg2bFhgARh6zxCSvUlH2kWkg5BSut0GxwkhVgF4HwAB4CIA1wHoAPBlAO+UBt4UIcT+Er+6YsOGDY0PPfSQruZ61uTkJACgubnZ5ZYEG8+D+3gOvIHnwX3VdA7OHjyL9FTa8N+HmkJo3NhoY4uMq6bz4FdOnYObbroJhw4d+pmU8mozjwvaGoCcVQA+kvdvCeATAP7SSPBPRERE1WthZsFU8A8A6ak0FmYWUBNmcgV5n+86AEKIBIC1Jh7yj1LKd+b/QEr5y8xTiRCASwD8DwD3APgNIcQbpJSnKz1pqZ6WEGJ/c3PzK7Zv326iif60d+9eAEAQXquX8Ty4j+fAG3ge3Fct52Bk1wiGbx82/biOBzvQfku7DS0yp1rOg585dQ5UZxh81wEAcBjAjIm/P1bqF1LKNIDnATwohDgO4CvIdATeZ6mFRERE5FvzE2rVwFUfR+Q033UApJQ9Nj31v2T/u92m5yciIiIfqF2pFh6pPo7IaUxUO++S7H/ZfSciIgow1br+3A+A/CJQHQAhxDVCiGVL9IUQTQAezP7zu862ioiIiLwksimC6LVRU4+Jdke5MzD5RtDmqv4CwHYhxFPI5P6fBXApgNcBuACZnYLvc611RERE5AnxnXEMXD9QeR8AAKgB4nfG7W4SkTZB6wA8DCAFYBsyuf6NAJIA9gP4OoBHpZRMASIiIgq4WE8MnQ91Vt4MrAbofLiT6T/kK4HqAEgpvwum+BAREZEBbTvaEI6HkfhoAuNPjS/7fbQ7ividcQb/5DuB6gAQERERmRHriSHWE0NqMIVkbxLzE/OoXVmLWE+MOf/kW+wAEBEREVUQ2RRhwE9VI1BVgIiIiIiIgo4dACIiIiKiAGEKEBEFFnN6iYgoiNgBIKLASfYmkbgngfGni1T1uDaK+E5W9SAiourFFCAiCpTR3aMYuH6gaPAPAONPj2Pg+gGMPjrqcMuIiIicwQ4AEQVGsjdZeVMfAFgAht4zhGRv0pF2EREROYkdACIKjMQ9icrBf84CkPhowsbWEBERuYMdACIKhNRgqmTaTynjT40jNZiyqUVERETuYAeAiAJBNZ2HaUBERFRt2AEgokCYn5h39HFERERexQ4AEQVC7Uq1qseqjyMiIvIqdgCIKBBU6/pzPwAiIqo27AAQUSBENkUQvTZq6jHR7ih3BiYioqrDDgARBUZ8Z9z4Va8GiN8Zt7E1RERE7mAHgIgCI9YTQ+dDnZWvfDVA58OdTP8hIqKqxA4AEQVK2442dO3pQrS7eDpQtDuKrj1daPujNodbRkRE5AyWtyCiwIn1xBDriSE1mEKyN4n5iXnUrqxFrCfGnH8iIqp67AAQUWBFNkUY8BMRUeAwBYiIiIiIKEA4A0BEROQzTF8jIivYASAiIvKJZG8SiXsSGH96fNnvotdGEd8ZZ/UqIqqIKUBEREQ+MLp7FAPXDxQN/gFg/OlxDFw/gNFHRx1uGRH5DTsAREREHpfsTWLopiFgocIfLgBD7xlCsjfpSLuIyJ/YASAiIvK4xD2JysF/zgKQ+GjCxtYQkd+xA0BERORhqcFUybSfUsafGkdqMGVTi4jI79gBICIi8jDVdB6mARFRKewAEBERedj8xLyjjyOi6scOABERkYfVrlSr2K36OCKqfuwAEBEReZhqXX/uB0BEpbADQERE5GGRTRFEr42aeky0O8qdgYmoJHYAiIiIPC6+M278jl0DxO+M29gaIvI7dgCIiIg8LtYTQ+dDnZXv2jVA58OdTP8horLYASAiIvKBth1t6NrThWh38XSgaHcUXXu60PZHbQ63jIj8hiUCiIiIfCLWE0OsJ4bUYArJ3iTmJ+ZRu7IWsZ4Yc/6JyDB2AIiIiHwmsinCgJ+IlDEFiIiIiIgoQNgBICIiIiIKEHYAiIiIiIgChB0AIiIiIqIAYQeAiIiIiChA2AEgIiIiIgoQdgCIiIiIiAKEHQAiIiIiogBhB4CIiIiIKEDYASAiIiIiChAhpXS7DVVFCHGqoaHhwpe97GVuN8V2k5OTAIDm5maXWxJsPA/u4znwBp4H9/EceAPPg/ucOge/+MUvMD09fVpK2WLmcewAaCaEeA7ASgAJl5vihCuy//2lq60gngf38Rx4A8+D+3gOvIHnwX1OnYM4gAkp5eVmHsQOACkTQuwHACnl1W63Jch4HtzHc+ANPA/u4znwBp4H93n9HHANABERERFRgLADQEREREQUIOwAEBEREREFCDsAREREREQBwg4AEREREVGAsAoQEREREVGAcAaAiIiIiChA2AEgIiIiIgoQdgCIiIiIiAKEHQAiIiIiogBhB4CIiIiIKEDYASAiIiIiChB2AIiIiIiIAoQdANJGCHGpEOJzQoifCiHGhBCzQohjQogfCCH+UAixwu02VjshxAYhxJ8LIf5DCPGCEGJOCHFcCPFtIcRr3G5fUAghVgghbhVC/IMQ4r+z50EKIW50u23VSAjRLoR4NHu9mRVCJIQQfyuEiLndtiAQQvyeEOLT2Wv9RPaz/iW32xUkQogWIcSNQohvCSGGhRDTQohxIcQPhRA7hBCM9xwihPhrIURv9h48LYQ4LYToF0J8RAjR4nb7crgRGGkjhNgO4NsAfgrgCIDTAFoAvA7ApQD2ArhOSjnvTgurnxDiqwDeDuDnAH6IzDnoBPBGACEAt0opd7nXwmAQQlwAIJn953EAc8h8B94jpXzErXZVIyHEegA/ArAamevPLwG8EsBrAAwB+HUp5Sn3Wlj9hBD/DaALwBSAEQBXAPhHKeU73WxXkAgh/gTA5wGMAngSwPMALgbwFgBRAN8A8PuSQZ/thBBzAH6GzH34BIAIgFcB2ArgGIBXSSlfcK+FGewAkDZCiDoA81LKhYKfrwCwB8B2AG+XUn7dheYFghDi3QAGpJT9BT/vBvBvACSAuJRy1IXmBUb2u9AD4L+llKNCiLsAfATsAGgnhPg+gOsB3CKl/HTezz8J4DYAfy+l/BO32hcE2dnFEQDDALqRCUDZAXCQEOI3kQk0v5t/DxZCtAL4L2QGIH5PSvkNl5oYGEKIsJRypsjPPwbgLwF8Xkp5s/MtW4pTQqSNlHKuMPjP/vwcgCey/9zgaKMCRkr5WGHwn/35U8jMwNQB+DWn2xU02e/Cv7CjZS8hxDpkgv8EgM8W/PojAFIA3iWEiDjctECRUj4ppTzE0WX3SCn/Q0r5/wrvwVLKMQB/l/3ndscbFkDFgv+s3OCnJ+IgdgDIdkKIEIDXZ//5jJttCbhz2f8yBYuqxW9m/7unSOAzCeA/ATQiM/1OFFS89nvD72b/64k4qNbtBlD1EUKsAvA+AALARQCuA9AB4MsAvuNi0wJLCLEWmZSUswCedrk5RLp0Zv97sMTvDyEzQ7ARQK8jLSLyECFELYAbsv/8VzfbEjRCiA8AaEJmDcZWAL+BTPB/v5vtymEHgOywCpnp9xwJ4BMA/pJTxM4TQtQD+EcA9QA+JKVMVngIkV9Es/8dL/H73M8vsL8pRJ50P4DNAL4npfy+240JmA8gsxA7518BvFtK+ZJL7VmCKUC0RLZ8njTxv2Wl3qSUv5RSCmQ6mGuRWYh3E4CnhRAXOvySfEfHOch7rhCALwL4dQBfQ6YjRgboPA/kGpH9LwceKHCEELcAuB2Zyljvcrk5gSOlbM3GQq3IVGNaB6BfCPEKd1uWwRkAKnQYQKkFLMUcK/ULKWUamVJkDwohjgP4CoB7kEkPotK0nINs8P8lAL+PzOKjd3IGxhRt3wWyTW6EP1ri9ysL/o4oEIQQfwrgQWRKUfZIKU+73KTAklIeB/AtIcTPkElXfByZWRlXsQNAS0gpe2x66n/J/ne7Tc9fNXScg2ze55eRCf6/DOCGbIeMDLLxu0D6DGX/u7HE73PVNkqtESCqOkKI/wPgUwAOIBP8n3C3RQQAUsqjQoifA/gVIcQqKeVJN9vDFCByyiXZ/7IKgc2yNej/CZng/3EA72LwT1Xqyex/ry/c6VQI0YxM6ts0gJ843TAiNwgh/hyZ4P+/AbyGwb/nrMn+1/V7MjsApI0Q4hohRGORnzchMxUJAN91tlXBkl3w+y0AbwKwG8AfFtubgagaSCkPI7PJYBzAnxb8+m5kNkZ6XEqZcrhpRI4TQtyJzKLf/ciM/Ls6whxEQogrspuvFf68JrsR2GoAP/JCMQ7uBEzaCCGeQCbF5ylkcv/PIrP74OuQqcLxIwC/JaWccqeF1U8I8Q8A3g3gJIDPofjix71Syr0ONiuQhBB3ALgi+89fAdCFzHfgUPZnP+SuwNYJIdYj876uBvBtAL8AcA2A1yCT+vNrUspT7rWw+gkh3gzgzdl/tgL4LQBHAPwg+7OTUsoPON+y4BBC/AGAx5AZWf40iq97SUgpH3OwWYGTTb/6ODLltg8DOIVMJaBuZBYBjyHTOfu5W23MYQeAtBFCvAHA/wKwDZkPfCOAJDJ1b78O4FEpJVOAbCSE2IvMhaacu6WUd9nfmmAzcC6+IKV8tzOtqW5CiEuRKTDw2wBaAIwis/v43Vz8aD8hxF1YWvq50FEpZdyZ1gSTgXMAAE9JKbfb35rgEkJsBvBeZNIP25EZ/EwhMxjxXQC7vHJNYgeAiIiIiChAuAaAiIiIiChA2AEgIiIiIgoQdgCIiIiIiAKEHQAiIiIiogBhB4CIiIiIKEDYASAiIiIiChB2AIiIiIiIAuT/b+/eQuWq7jiOf3+pVklARUVrpV5rqHiBFFKrWBRFBBVUaC6mVoMPaiWxghGrILEUtF4eoigYFEWMqEi9okEFOQqmRNAoEonaWItUsCbalEZTjfn7sHfKMGfOyZynmNnfz8swa+219pp5Wr/Za60xAEiSJEkdYgCQJEmSOsQAIEmSJHWIAUCSJEnqEAOAJGmXl2QsSe3scUjSrsAAIEmSJHVIqvzBRJK0a0tyCDC9qtbt7LFI0vedAUCSJEnqEJcASZIGSvJUkkqyeEDdn9q6+4bs67wkK5K8n2Rzkv8meSPJlUmm9V17QpKvk3yYZO++uoOSfNq2/1lP+bg9AGlcnGRVks+SbEnycZIXksyb2rchSaPDJwCSpIGS7AusAQ4ETqyqNW356cCLwDpgdlV9OURf64BtwBvAP4G9gdOAmcCKqvpt3/VLgNuAx6tqbls2DXipbbewqh7suX4MOKWq0lN2E3Ad8HdgJbAJOAiYDayrql9P8SuRpJFgAJAkTSjJScArNJPonwPTgbdpJvCzq2rtkP0cWVXr+8qmAQ8AFwG/rKrVPXUBngXOBi6vquVJlgI3Ag9V1UV9fY0xPgBsBL4CZvaHlCT7V9WGYcYuSaPGJUCSpAlV1SrgBuAoYDmwAvgRcOWwk/+2n/UDyrYBd7Rvz+yrK2AhzdOCZUmuaMfxHvC7KXyEb4BvB9zbyb+kztptZw9AkvS9dwtwKrCgff9IVf1/7X+SfYCrBrRbVlX/bq/ZD7gGOAs4ApjRd+3B/Y2rakOSBcDLwN3AFmBeVW0ectwPA4uBtUkep3mS8deq2jRke0kaSS4BkiTtUJLLgHvatydU1es9dYfRLBHqd3hVfdQGhDeBw4HXafYBfA5sBfYBfg88WFULB9x3T+Ddtu3KqjprgvGNMX4J0A+ARcAlwPFt8VbgeeDqqvrbjj+5JI0eA4AkaVJJjqKZwH9Ds/Z/LfCLqtoyZPvtG3r/WFU39tWdCKxi4gCwHLgU2ADsD1xYVQ8PuG6MvgDQV38AcDIwH5gDrAeOqar/DfMZJGmUuAdAkjShJHsAj9Es2ZkP3AwcByybQjc/bV//MqDulEnuPYdm8v8qzQbkz4B72kAyJVX1r6p6oj1R6GXgSODYqfYjSaPAACBJmsztwCzg1qp6EVgKvAZclmTukH181L6e2luYZBbNMZ3jJDkCuBfYCPymqj6mOS1oBvBYG0wmlGSPJKe3pwn1lu8O7Nu+3eHxpZI0ilwCJEkaKMl5wJPAauDkqtralv8EeIvmIIlZVfXhDvr5MfAOzXr/p4EPaE4VOgd4AphHzxKgdpL+Gs15/edW1TM9fd0GLAHuqqrFPeVj9CwBavcdfEETPlYD/wD2BM4Ajgaeqapzp/6tSNKuzycAkqRxkhwC3E/z51kXbJ/8A7S/xl8C7AU8muSHk/VVVZ8AvwKeo1mHvwg4FLgC+MOAJn+mmfzf2Tv5b11Ps5F4UZLzJ7ntZuBamj8rO4lmo/EC4D80x4jOmWzMkjTKfAIgSZIkdYhPACRJkqQOMQBIkiRJHWIAkCRJkjrEACBJkiR1iAFAkiRJ6hADgCRJktQhBgBJkiSpQwwAkiRJUocYACRJkqQOMQBIkiRJHWIAkCRJkjrEACBJkiR1iAFAkiRJ6hADgCRJktQhBgBJkiSpQwwAkiRJUocYACRJkqQO+Q6EWD5ohUtkHwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"image/png": {
"height": 277,
"width": 384
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(x,y, color = 'm')\n",
"plt.xlabel('x-axis')\n",
"plt.ylabel('y-axis')\n",
"plt.title('My plot')\n",
"plt.grid()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Histograms"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"image/png": {
"height": 248,
"width": 375
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.hist(y, bins = 20, color = 'pink',edgecolor = 'black')\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Bar charts"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"image/png": {
"height": 248,
"width": 368
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"y = [3, 10, 7, 5, 3, 4.5, 6, 8.1]\n",
"N = len(y)\n",
"x = range(1, N+1)\n",
"plt.bar(x, y, width=0.5, color=\"orange\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"image/png": {
"height": 248,
"width": 372
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"z = {\"a\":1,\"b\":2,\"c\":3,\"d\":4}\n",
"plt.bar(range(len(z)), z.values())\n",
"plt.xticks(range(len(z)), list(z.keys()))\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Just for fun: [XKCD](https://xkcd.com/)-style sketch plots"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"image/png": {
"height": 263,
"width": 379
}
},
"output_type": "display_data"
}
],
"source": [
"with plt.xkcd():\n",
" # Based on \"Stove Ownership\" from XKCD by Randall Monroe\n",
" # http://xkcd.com/418/\n",
"\n",
" fig = plt.figure()\n",
" ax = fig.add_axes((0.1, 0.2, 0.8, 0.7))\n",
" ax.spines['right'].set_color('none')\n",
" ax.spines['top'].set_color('none')\n",
" plt.xticks([])\n",
" plt.yticks([])\n",
" ax.set_ylim([-30, 10])\n",
"\n",
" data = np.ones(100)\n",
" data[70:] -= np.arange(30)\n",
"\n",
" plt.annotate(\n",
" 'THE DAY I REALIZED\\nI COULD COOK BACON\\nWHENEVER I WANTED',\n",
" xy=(70, 1), arrowprops=dict(arrowstyle='->'), xytext=(15, -10))\n",
"\n",
" plt.plot(data)\n",
"\n",
" plt.xlabel('time')\n",
" plt.ylabel('my overall health')\n",
" fig.text(\n",
" 0.5, 0.05,\n",
" '\"Stove Ownership\" from xkcd by Randall Monroe',\n",
" ha='center')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "UDA Python",
"language": "python",
"name": "uda"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.12"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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