"
]
}
],
"prompt_number": 153
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Dictionary comprehensions"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[[back to top](#sections)]"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def dict_loop(n):\n",
" a_dict = dict()\n",
" for i in range(n):\n",
" if i % 3 == 0:\n",
" a_dict[i] = i\n",
" return a_dict"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 146
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def dict_compr(n):\n",
" return {i:i for i in range(n) if i % 3 == 0}"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 147
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%timeit dict_loop(n)\n",
"%timeit dict_compr(n)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"10000 loops, best of 3: 159 \u00b5s per loop\n",
"10000 loops, best of 3: 151 \u00b5s per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n"
]
}
],
"prompt_number": 148
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"
\n",
"
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Copying files by searching directory trees"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[[back to top](#sections)]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Executing `Unix`/`Linux` shell commands:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import subprocess\n",
"\n",
"def subprocess_findcopy(path, search_str, dest): \n",
" query = 'find %s -name \"%s\" -exec cp {} %s \\;' %(path, search_str, dest)\n",
" subprocess.call(query, shell=True)\n",
" return "
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 30
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Using Python's `os.walk()` to search the directory tree recursively and matching patterns via `fnmatch.filter()`"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import shutil\n",
"import os\n",
"import fnmatch\n",
"\n",
"def walk_findcopy(path, search_str, dest):\n",
" for path, subdirs, files in os.walk(path):\n",
" for name in fnmatch.filter(files, search_str):\n",
" try:\n",
" shutil.copy(os.path.join(path,name), dest)\n",
" except NameError:\n",
" pass\n",
" return"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 33
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import timeit\n",
"\n",
"\n",
"def findcopy_timeit(inpath, outpath, search_str):\n",
" \n",
" shutil.rmtree(outpath)\n",
" os.mkdir(outpath)\n",
" print(50*'#')\n",
" print('subprocsess call')\n",
" %timeit subprocess_findcopy(inpath, search_str, outpath)\n",
" print(\"copied %s files\" %len(os.listdir(outpath)))\n",
" shutil.rmtree(outpath)\n",
" os.mkdir(outpath)\n",
" print('\\nos.walk approach')\n",
" %timeit walk_findcopy(inpath, search_str, outpath)\n",
" print(\"copied %s files\" %len(os.listdir(outpath)))\n",
" print(50*'#')\n",
"\n",
"print('small tree')\n",
"inpath = '/Users/sebastian/Desktop/testdir_in'\n",
"outpath = '/Users/sebastian/Desktop/testdir_out'\n",
"search_str = '*.png'\n",
"findcopy_timeit(inpath, outpath, search_str)\n",
"\n",
"print('larger tree')\n",
"inpath = '/Users/sebastian/Dropbox'\n",
"outpath = '/Users/sebastian/Desktop/testdir_out'\n",
"search_str = '*.csv'\n",
"findcopy_timeit(inpath, outpath, search_str)\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"small tree\n",
"##################################################"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"subprocsess call\n",
"1 loops, best of 3: 268 ms per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"copied 13 files\n",
"\n",
"os.walk approach\n",
"100 loops, best of 3: 12.2 ms per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"copied 13 files\n",
"##################################################\n",
"larger tree\n",
"##################################################\n",
"subprocsess call\n",
"1 loops, best of 3: 623 ms per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"copied 105 files\n",
"\n",
"os.walk approach\n",
"1 loops, best of 3: 417 ms per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"copied 105 files\n",
"##################################################\n"
]
}
],
"prompt_number": 35
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"I have to say that I am really positively surprised. The shell's `find` scales even better than expected!"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"
\n",
"
\n",
""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Returning column vectors slicing through a numpy array"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[[back to top](#sections)]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Given a numpy matrix, I want to iterate through it and return each column as a 1-column vector. \n",
"E.g., if I want to return the 1st column from matrix A below\n",
"\n",
"\n",
"A = np.array([ [1,2,3], [4,5,6], [7,8,9] ])\n",
">>> A\n",
"array([[1, 2, 3],\n",
" [4, 5, 6],\n",
" [7, 8, 9]])
\n",
"\n",
"I want my result to be:\n",
"\n",
"array([[1],\n",
" [4],\n",
" [7]])
\n",
"\n",
"with `.shape` = `(3,1)`\n",
"\n",
"\n",
"However, the default behavior of numpy is to return the column as a row vector:\n",
"\n",
"\n",
">>> A[:,0]\n",
"array([1, 4, 7])\n",
">>> A[:,0].shape\n",
"(3,)\n",
"
"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import numpy as np\n",
"\n",
"# 1st column, e.g., A[:,0,np.newaxis]\n",
"\n",
"def colvec_method1(A):\n",
" for col in A.T:\n",
" colvec = row[:,np.newaxis]\n",
" yield colvec"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 83
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# 1st column, e.g., A[:,0:1]\n",
"\n",
"def colvec_method2(A):\n",
" for idx in range(A.shape[1]):\n",
" colvec = A[:,idx:idx+1]\n",
" yield colvec"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 82
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# 1st column, e.g., A[:,0].reshape(-1,1)\n",
"\n",
"def colvec_method3(A):\n",
" for idx in range(A.shape[1]):\n",
" colvec = A[:,idx].reshape(-1,1)\n",
" yield colvec"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 81
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# 1st column, e.g., np.vstack(A[:,0]\n",
"\n",
"def colvec_method4(A):\n",
" for idx in range(A.shape[1]):\n",
" colvec = np.vstack(A[:,idx])\n",
" yield colvec"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 79
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# 1st column, e.g., np.row_stack(A[:,0])\n",
"\n",
"def colvec_method5(A):\n",
" for idx in range(A.shape[1]):\n",
" colvec = np.row_stack(A[:,idx])\n",
" yield colvec"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 77
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# 1st column, e.g., np.column_stack((A[:,0],))\n",
"\n",
"def colvec_method6(A):\n",
" for idx in range(A.shape[1]):\n",
" colvec = np.column_stack((A[:,idx],))\n",
" yield colvec"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 74
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# 1st column, e.g., A[:,[0]]\n",
"\n",
"def colvec_method7(A):\n",
" for idx in range(A.shape[1]):\n",
" colvec = A[:,[idx]]\n",
" yield colvec"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 89
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def test_method(method, A):\n",
" for i in method(A): \n",
" assert i.shape == (A.shape[0],1), \"{}, {}\".format(i.shape, A.shape[0],1)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 69
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import timeit\n",
"\n",
"A = np.random.random((300, 3))\n",
"\n",
"for method in [\n",
" colvec_method1, colvec_method2, \n",
" colvec_method3, colvec_method4, \n",
" colvec_method5, colvec_method6,\n",
" colvec_method7]:\n",
" print('\\nTest:', method.__name__)\n",
" %timeit test_method(colvec_method2, A)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"Test: colvec_method1\n",
"100000 loops, best of 3: 16.6 \u00b5s per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"\n",
"Test: colvec_method2\n",
"10000 loops, best of 3: 16.1 \u00b5s per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"\n",
"Test: colvec_method3\n",
"100000 loops, best of 3: 16.2 \u00b5s per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"\n",
"Test: colvec_method4\n",
"100000 loops, best of 3: 16.4 \u00b5s per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"\n",
"Test: colvec_method5\n",
"100000 loops, best of 3: 16.2 \u00b5s per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"\n",
"Test: colvec_method6\n",
"100000 loops, best of 3: 16.8 \u00b5s per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"\n",
"Test: colvec_method7\n",
"100000 loops, best of 3: 16.3 \u00b5s per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n"
]
}
],
"prompt_number": 91
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"
\n",
"
\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Speed of numpy functions vs Python built-ins and std. lib."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[[back to top](#sections)]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"
\n",
"
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## `sum()` vs. `numpy.sum()`"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[[back to top](#sections)]"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from numpy import sum as np_sum\n",
"import timeit\n",
"\n",
"samples = list(range(1000000))\n",
"\n",
"%timeit(sum(samples))\n",
"%timeit(np_sum(samples))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"10 loops, best of 3: 18.2 ms per loop\n",
"10 loops, best of 3: 138 ms per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n"
]
}
],
"prompt_number": 20
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"funcs = ['sum', 'np_sum']\n",
"orders_n = [10**n for n in range(1, 6)]\n",
"times_n = {f:[] for f in funcs}\n",
"\n",
"for n in orders_n:\n",
" samples = list(range(n))\n",
" times_n['sum'].append(min(timeit.Timer('sum(samples)', \n",
" 'from __main__ import samples')\n",
" .repeat(repeat=3, number=1000)))\n",
" times_n['np_sum'].append(min(timeit.Timer('np_sum(samples)', \n",
" 'from __main__ import np_sum, samples')\n",
" .repeat(repeat=3, number=1000)))"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 26
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%pylab inline"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 24
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import matplotlib.pyplot as plt\n",
"\n",
"labels = [('sum', 'in-built sum() function'), \n",
" ('np_sum', 'numpy.sum() function')]\n",
"\n",
"matplotlib.rcParams.update({'font.size': 12})\n",
"\n",
"fig = plt.figure(figsize=(10,8))\n",
"for lb in labels:\n",
" plt.plot(orders_n, times_n[lb[0]], \n",
" alpha=0.5, label=lb[1], marker='o', lw=3)\n",
"plt.xlabel('sample size n')\n",
"plt.ylabel('time per computation in milliseconds [ms]')\n",
"plt.legend(loc=2)\n",
"plt.grid()\n",
"plt.xscale('log')\n",
"plt.yscale('log')\n",
"plt.title('Performance of explicit for-loops vs. list comprehensions')\n",
"\n",
"max_perf = max( n/i for i,n in zip(times_n['sum'],\n",
" times_n['np_sum']) )\n",
"min_perf = min( n/i for i,n in zip(times_n['sum'],\n",
" times_n['np_sum']) )\n",
"\n",
"ftext = 'the in-built sum() is {:.2f}x to '\\\n",
" '{:.2f}x faster than the numpy.sum()'\\\n",
" .format(min_perf, max_perf)\n",
"plt.figtext(.14,.75, ftext, fontsize=11, ha='left')\n",
"\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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dHTFs2DD4+voCAFq0aCEz78iRI2FjY4OoqChoaGjg1q1blTo48sQSGBiIZcuW\n4dq1a/jll18wY8YMHD16FP369cPVq1dx6NAhfPnll+jduzf3HcQRERHo1atXpfLFYjEsLS0RGhoq\ncz0APH78GEOHDkW7du2wbt06aGpqKhzvwoULER0djWvXrmH06NGwsrLiOojLli3D+vXrsWrVKnh5\neSEvLw8nT54EUPXxrdh5zs/Ph5eXFzp06IDz58+DMQZfX1/069cPN27cgJqaGgCgtLQUixYtQmBg\nIFq0aIE5c+Zg+PDhSEpKahBzB+tbeHg4jcIQuVF7ITUp+4YsZU1XatQjdrVVVCT7sJSU1O5wlZbK\n3q6wsHblMcYqPTmjoaGB4OBgWFhYoGvXrvjPf/6Ds2fPylXef//7XwwYMADm5ub44Ycf0KJFC2zd\nurVWscmiq6sLFRUViEQiSCQSSCQSCIWy637//n306dMHHTt2hFQqRb9+/TBw4ECF9+nu7o7Zs2ej\nXbt2WLRoEUQiEZo0acKlLViwAM2aNUNoaCi3TVJSEtq0aSOzPKlUitu3b1e5P319fairq0NTUxMS\niUTh2+UuLi7w8/ODqakpPvvsM3h6enLnLy8vD6tXr0ZAQACmTZsGMzMz2NraYuHChQDkP7779+/H\nkydPcPDgQdjb28PBwQEHDhzAw4cPceDAAS4fYwwbN25Ejx49YG5uDn9/f6SmpiIlJUWhOhFCCKl7\n1LGTQU2tVGa6iors9JoIhbK3U1evXXmydOzYkRtxAQBDQ0NkZGRwyyKRiLv9VrGj1K1bN+53FRUV\nODs7IyEhQWmxKcLX1xeTJk2Cu7s7AgICEBsbq3AZAoEAtra2vOWWLVvCxsaGlyaRSJCVlcWlvXjx\nosoOmVgsRnZ2tsKxyBuvnZ0dL638+UtISEBBQQG8vLzeaj8JCQmwtLRE8+bNuTSJRAJzc3PcuHGD\nF0/542doaAgAvPb0IaPRF6IIai+krjXqW7G15elpiuDgc3Bz+/f2aUHBOfj4mMHcXPHyEhPflNek\nCb88Dw8zZYQLALxOHVD5fTh///0393t1twmBNyM2ZbcKy0Z+ypdVUlKC0lLldUrLW7x4MUaPHo1T\np04hNDQUK1euhJ+fH5YvXw5A9nt+CgsLK5Uj63jISitfDx0dHbx8+VJmXC9evICurq7C9ZE3XnV1\n9WpjUxZZ70iqmCYUCnm3ist+f1fnnBBCiPLQiJ0M5uYm8PExg0QSCh2dcEgkof/fqavdU6zKLk+W\nmp46bdeg43pVAAAgAElEQVSuHfdTNgJTJioqivu9uLgY0dHRsLCwAPDv064PHz7k8ly/fl3hlyiq\nq6vXOFeuTNu2bTF16lQcPnwYAQEB+P7777l1EomEF0tBQQFvtOlttG/fHqmpqTLX3bt3Dx06dFC4\nTGXEW/bAxOnTp6vMI8/xtbKywo0bN/D06VMuLSMjA7dv34aVlZVCMX3I6L1kRBHUXkhda9Qjdv7+\n/tykREWZm5soteOl7PIqepu3Va9atQoGBgaQSqVYv349nj59imnTpgF409kxMTGBv78/NmzYgKys\nLCxatKjGjmTFeNq2bYvIyEikpaVBU1MTenp6lcrIy8uDn58fhg0bBqlUiuzsbJw6dQqWlpZcHk9P\nT2zbtg0uLi4QiURYsWIFioqKePuTZ1RKVpqrqysuXrxYKd/Lly9x48aNGtuRrLmPtY23PJFIhHnz\n5sHf3x+amprw9PREfn4+Tp48yc2zk3V8Kxo1ahS+/vprjBgxAmvWrEFpaSl8fX1hbGyMESNGVBsD\nIYSQdyM8PFyp/wA06hG7so5dY1PxqUpZT1mWpctT1tq1a7FkyRLY29sjKioKR48e5Z6IVVFRwcGD\nB5GZmQl7e3vMnDkTK1eurPLhh6r2HRAQgOzsbJibm0NfXx9paWmVtlFVVUV2djYmTpwICwsL9OvX\nD4aGhrzXhaxduxZWVlbo27cvBg4cCDc3Nzg5Ocm8dVjTsaiYNmbMGERFRfHm3QHAsWPH0Lp1a7i4\nuNRY54plvk285dOXL1+OFStWYPPmzbC2tkbfvn158w+rOr7ly9DQ0EBISAiaNGkCFxcXuLm5QSwW\n49SpU1BVVeXtu6Zj9SFrjJ8p5N2h9kJq4ubmRt8VKw/6rlhSG15eXvDw8MCCBQu4NA8PD/Tv3597\nlQjho+uJEELeHn1XLCHvwOrVq7Fx40bed8WmpKTgyy+/rOfISENBc6aIIqi9kLrWqOfYEaIoOzs7\n3ve89uzZE3fv3q3HiAghhBD50a1YQshboeuJEELeHt2KJYQQQgghPI26Y+fv70/zGwghSkWfKUQR\n1F5ITcLDw+mpWHnQrVhC6saHdj3Rl7oTRVB7IfJS1mcpdewIIW+FridCCHl7NMeOEEIIIYTwUMeO\nEEIUQHOmiCKovZC6Rh078sGLjY2FgYEB76XEUqkUBQUFNW6blpYGDw8PiEQiqKiovOtQa5Samgqh\nUIhLly7VdyiEEELqAXXsyAfPz88Pc+fOhZaWFoA3LyU2MzPDli1batx25cqVePLkCeLi4ngvNq4L\nZmZmCAgI4KW1adMG6enpcHZ2rtNYPiQ0EZ4ogtoLqWvUsSMftISEBERERGD8+PG89AkTJmDLli01\nTmRNSkqCk5MTTE1NIZFI3mWolQgEgkppQqEQEokEqqr0pTKEEPIhoo5dFRKTExF0MAgbD2xE0MEg\nJCYnNpjy3NzcMHnyZCxfvhyGhobQ09PDuHHjkJeXx+Xx8fFBnz59eNvt27cPQuG/p9zf3x/t27fH\n4cOHYWZmBm1tbXz66afIzc3F4cOHYW5ujqZNm+Kzzz5DTk5OpbI3bNgAIyMjaGtrY/jw4Xj+/DmA\nN3NKVFVV8eDBA97+9+7dCx0dHeTn5/PSExIS0LdvX+jq6kIkEsHCwgL79u3j1guFQuzfv5+3jaen\nJ68zJpVKsXTpUkydOhU6OjowMDDA999/j9evX2P69Olo3rw5jI2NERQUVOmYdO/eHS1btuSlDxo0\nCGlpaYiMjKzyPAiFQoSGhmLXrl0QCoWYMGGCQvEuW7YMs2bNgp6eHgwMDDB37lyUlJTwtgsKCoKF\nhQU0NDSgr6+PYcOGAXjTBu7cuYOAgAAIhUIIhULcv39f5q3YxMREDBw4EGKxGGKxGIMHD8adO3e4\n9cHBwVBTU8OlS5fg4OAAbW1tdO7cGVevXq2y7h8ymjNFFEHthdS1Rt2xq+0LihOTExEcFows/Sxk\nG2QjSz8LwWHBte6MKbs8ADhy5Aiys7MRERGBAwcO4Pjx41i1ahW3XiAQyBzRqejx48fYu3cvfv/9\nd5w8eRIXLlzA0KFDERwcjCNHjnBpK1eu5G0XHR2NiIgIhISE4MSJE7h+/TomTpwI4E2no3379ti1\naxdvm+3bt2P06NHQ1NTkpY8cORItW7ZEVFQU4uPjsX79eujq6lYbt6z6BQYGwtzcHNeuXcPMmTMx\nY8YMfPLJJ2jfvj2uXr2KGTNm4Msvv8TNmze5bSIiItClS5dK5YvFYlhaWiI0NLTaY9etWzeMHj0a\n6enp2LRpk8LxGhkZITo6GoGBgdiyZQv27NnDrV+2bBkWLlyIGTNmID4+HiEhIejcuTMA4LfffoNU\nKoWvry/S09ORnp4OY2PjSvvNz8+Hl5cXCgsLcf78eURERCA3Nxf9+vVDUVERl6+0tBSLFi1CYGAg\nrl27BolEguHDh1fqaBJCCFEuZb+guFHfr6ntgTobcxZN2jdBeGr4v4lqwN8H/oZTTyeFy4uOjMYr\n41dA6r9pbu3dcO7aOZibmdcqRqlUinXr1gEAOnTogBEjRuDs2bP4+uuvAQCMMbneh1NQUIA9e/ag\nefPmAIDhw4dj27ZtyMjIgJ6eHgDA29sb586d423HGMNPP/0EsVgM4M3IUt++fZGSkoJ27drhiy++\nwKZNm7BkyRIIBALcunULFy9elDlv7f79+5g3bx46duzI1a023N3dMXv2bADAokWLsHr1ajRp0oRL\nW7BgAVavXo3Q0FB06tQJwJtbqaNHj5ZZnlQqxe3bt6vcn76+PtTV1aGpqVmr27AuLi7w8/MDAJia\nmmL37t04e/YsJkyYgLy8PKxevRorVqzAtGnTuG1sbW0BALq6ulBRUYFIJKp23/v378eTJ08QGxvL\nneMDBw5AKpXiwIED+PzzzwG8OZ8bN26EnZ0dgDfXTteuXZGSkoL27dsrXLfGjOZMEUVQeyE1cXNz\ng5ubW6U507XVqEfsaquIFclML0HtRi9KUSozvbC0sFblCQQC7g98GUNDQ2RkZChclpGREfcHH3jT\nWTEwMOA6dWVpmZmZvO0sLCy4Th0AdO/eHQBw48YNAMDYsWORmZmJ06dPAwB27NiBzp07V4obAHx9\nfTFp0iS4u7sjICAAsbGxCtej4jERCARo2bIlbGxseGkSiQRZWVlc2osXL3j1KE8sFiM7O1vhWOSN\nt6wTVab8OUxISEBBQQG8vLzeaj8JCQmwtLTknWOJRAJzc3PuXJXFU/74GRoaAkCt2hQhhJD6Qx07\nGdQEajLTVVC711kIqzjM6kL1WpUHAOrq/G0FAgFKS//tQAqFwkojduVvvZVRU+PXVSAQyEwrXzaA\nGkcD9fT0MGzYMGzfvh1FRUXYu3cvvvjiC5l5Fy9ejNu3b2P48OGIj49H165dsWTJEt7+K+6vsLBy\np7g2ddHR0cHLly9lxvXixYsabwnLIm+8NZ1DZZF1riqmCYVC3q3ist/fRTzvO5ozRRRB7YXUtUZ9\nK7a2PB09ERwWDLf2blxaQVIBfLx9anXrNNH4zRy7Ju2b8MrzcPdQRrgy6evr4/Lly7y0a9euKa38\nmzdv4uXLl9xoV9lkfQsLCy7PlClT4O7ujm3btuH169cYOXJkleW1bdsWU6dOxdSpU/Hdd99h7dq1\nWL58OYA3I0wPHz7k8hYUFODGjRswNTV963q0b98eqampMtfdu3ePe1hBEcqIt+yBidOnT8PKykpm\nHnV19RrnwFlZWeGHH37A06dPuVHYjIwM3L59G/Pnz5c7HkIIIe8HGrGTwdzMHD7uPpBkSqCTrgNJ\npgQ+7rXr1L2L8uSZP+fp6Ylbt25h69atuHPnDrZv347Dhw/Xan+yCAQCjB07FgkJCTh//jymT5+O\njz/+GO3atePy9OjRA+bm5pg/fz5GjhwJbW1tAICHhwcWLVoEAMjNzcX06dMRFhaGu3fvIjY2FqdO\nnYKlpSWvLtu2bcPly5cRHx8PHx8fFBUV8Y6BPKNSstJcXV0RHR1dKd/Lly9x48aNGufHyDoXtY23\nPJFIhHnz5sHf3x9bt27F7du3ERcXh++++47L07ZtW0RGRiItLQ1PnjyRWeaoUaPQsmVLjBgxArGx\nsYiJiYG3tzeMjY0xYsSIamMgstGcKaIIai+krtGIXRXMzcxr3fF61+XJesKyYpqHhwe++eYbrFy5\nEgsWLMDgwYOxdOlSzJw5U6FyqkpzdnZGz5490adPH7x48QIDBgzAjz/+WCnWSZMmYc6cObzbsCkp\nKTAxMQHw5vZpdnY2Jk6ciMePH6Np06bo3bs31q5dy+Vfu3YtJk+ejL59+0JHRweLFi3CkydPZN46\nrBh3TWljxozB2rVrkZWVxXvlybFjx9C6dWu4uLhUKqOmY/M28ZZPX758OVq2bInNmzdjzpw50NXV\nhaurK7c+ICAAX3zxBczNzVFQUIC7d+9WKltDQwMhISGYM2cOVxd3d3ecOnWK9647eY8fIYSQhk3A\n5Hl08j0ka56TPOtIzXx8fPDw4UOcOXOmxrx+fn44d+4cYmJi6iCy2vHy8oKHhwcWLFjApXl4eKB/\n//7w9fWtx8jeDx/a9RQeHk6jMERu1F6IvJT1WUq3Ysk78eLFC/z111/Yvn075syZU9/hVGv16tXY\nuHEj77tiU1JS8OWXX9ZzZIQQQohiaMSOKGz8+PF4+PAhQkJCqszj5uaG6OhojBw5Ejt37qzD6Ehd\no+uJEELenrI+S6ljRwh5K3Q9EULI26NbsYQQUg/ovWREEdReSF2jjh0hhBBCSCPRqDt2/v7+9N8S\nIUSp6AlHoghqL6Qm4eHhtf5ue1lojh0h5K3Q9UQIIW9PWZ+lH+QLinV1denlq4QoSW2+T/d9Ru8l\nI4qg9kLq2gfZsXv27Fl9h0AaGPrwJYQQ0hh8kLdiCSGEEEIaEnrdCSGEEEII4aGOHSGgd00R+VFb\nIYqg9kLqGnXsCCGEEEIaCZpjRwghhBBSz2iOHSGEEEII4aGOHSGgeTBEftRWiCKovZCaJCYnIuhg\nkNLK+yDfY0cIIYQQUt8SkxOx9fRWPGz5UGll0hw7QgghhJA6llOQg/k/zkeiOBEAEDE+gr5SjBBC\nCCHkffK6+DUu3r+Iyw8u496Le4BYueXTHDtCQPNgiPyorRBFUHshZYpLixGVFoVNlzfhwv0LKCot\ngvD/u2G6Gsr7zm0asSOEEEIIeUdKWSn+yfgHYalhyH6dzVvXxaoL0tPSoS/Vx+/4XSn7ey/n2OXk\n5MDT0xM3b97ElStXYGFhUSkPzbEjhBBCSH1hjOHO8zs4c+cMMvIyeOt0NXTRu21vWEmscPvObZy7\ndg7TR0xXSr/lvezYFRcXIzs7G/Pnz4evry8sLS0r5aGOHSGEEELqw8OchzibchZ3s+/y0rXUtOBq\n4orOrTpDRajCW/dBv6BYVVUVLVq0qO8wSCNC82CIvKitEEVQe/mwPMt/hsMJh7H92nZep05NqAZX\nE1fM6jILXYy7VOrUKRPNsSOEEEIIeQu5hbmISI1AzOMYlLJSLl0oEMLB0AFuUjeI1EV1Eku9jtht\n2bIFnTt3hoaGBsaPH89b9+zZMwwZMgQikQhSqRS//PKLzDIEAkFdhEoaOTc3t/oOgbwnqK0QRVB7\nadwKigsQnhqOzVc2469Hf/E6dRYtLTDdaTo+6vBRnXXqgHoesTMyMsKSJUtw+vRp5Ofn89ZNnz4d\nGhoayMzMRGxsLAYOHAhbW9tKD0rQPDpCCCGE1KWS0hLEPI5BRGoE8oryeOtMmpmgj2kfGDc1rpfY\nGsTDE0uWLMGDBw+we/duAEBeXh6aN2+OhIQEmJmZAQDGjRuHVq1a4dtvvwUADBgwAHFxcTAxMcGU\nKVMwbtw4Xpn08ARRRHh4OP1nTeRCbYUogtpL48IYQ0JWAkLvhuJZ/jPeOom2BH3a9YFZc7Na3U1U\nVr+lQcyxq1iR27dvQ1VVlevUAYCtrS1vEuqJEydqLNfHxwdSqRQAoKOjAzs7O+4CKyuLlmkZAK5f\nv96g4qFlWqZlWqblhrVsYmuCMylncOnCJQCA1E4KAMhKyIK9oT0muE6AUCCUu7yy31NTU6FMDXLE\n7sKFCxg+fDgeP37M5dm+fTv279+PsLAwucqkETtCCCGEvK303HScTTmL5GfJvHRNVU30MukFZyNn\nqArffpysUY/YiUQi5OTk8NJevHgBsVjJX6hGCCGEECJD9utshN4NxT8Z/4Dh336KqlAVXYy6oGeb\nntBU06zHCGUT1ncAQOUnWzt06IDi4mIkJ//bO46Li4OVlZVC5fr7+/OGPAmpCrUTIi9qK0QR1F7e\nP6+KXuF08mkEXgnE3xl/c506AQSwN7DHTOeZ6GPaR2mduvDwcPj7+yulLKCeR+xKSkpQVFSE4uJi\nlJSUoKCgAKqqqtDW1sbQoUOxdOlS7NixA9euXcMff/yBqKgohcpX5oEihBBCSONVVFKEyw8uI/J+\nJApKCnjrzPXM4dHOAxJtidL36+bmBjc3NwQEBCilvHodsVu+fDm0tLSwatUq7Nu3D5qamlixYgUA\nYOvWrcjPz4dEIsGYMWOwbds2dOrU6Z3F4u/vj6KiIm7Zx8cHQUFBb1VmTEwMxowZo/B2qampaNmy\n5Vvtr2IZFetX14KCgrBq1SoAwPHjxzF9+vQq8y5btgyHDh1SeB+MMXh6elZ77CIiIuDk5AR7e3tY\nWVnhhx9+AAC4urri008/RceOHWFnZwcvLy+kpKQoHMPGjRuRlZWl8HYAsHTpUlhYWMDOzg69evXC\njRs3AACXLl1Cjx49YGlpCUtLS/j5+VVZRkZGBry8vGBubg47OztER0dz69auXYuOHTtCRUUFf/75\nZ61ivHTpEqysrODo6IiIiAiFt4+Li8Phw4drtW9Z3sV1W524uLhK51coFOLVq1fvbJ8fgoyMDHTr\n1g0AUFBQgM6dOyMvL6+Grd4PZRPmScNVykoR8ygGm69sxrm753idOuOmxhhvNx4jrUe+k07dO8Ea\nKUWrJhAIWG5uLrfs4+PDtmzZouyw5HL37l3WokULpZZRsX51qaCggJmamvL2b2Njw9LS0pS6n82b\nN7OJEyeyli1bVpmnY8eO7M8//2SMMZaens5EIhHLzMxkpaWl7NixY1y+LVu2MA8PD4VjkEqlLD4+\nXuHtLl++zExMTNirV68YY2/qMmDAAMYYY/Hx8Sw5OZkx9uZY9uzZk/30008yyxk/fjxbsWIFY4yx\nyMhI1r59e27dX3/9xe7cucPc3Ny4Y6Co//znP2zNmjW12pYxxnbv3s2GDRtWq22Li4srpdX1dSsr\n/vq8thqLOXPmsODgYG551apV7LvvvqvHiMiHoLS0lN3MuskCrwSyZWHLeD+BVwLZjcwbrLS0tM7i\nUVaXrEHMsXtX5J1jVzZ61L17dzg4OODFixcAgPj4eHh4eKBDhw689+Tl5ORg0qRJ6NKlC2xtbTF7\n9myUlpZWKjc8PBxOTk4A3oygtWjRAosXL4aDgwM6duyIixcvVhuXr68vbG1tYWNjg8jIyEplVlyu\nuE5W/ezt7bn6lcnMzISnpydsbGxgY2ODefPmAXhz/ObPn8/lK7/s7+8Pb29vDBw4EO3bt8fw4cNx\n9epVuLu7w8zMjDeq9Mcff8DZ2Rna2tpc2tChQ7F3716Z9S4/6nL06FHY2NjA3t4e1tbWVY4SJSUl\n4eDBg1i4cGG1TxUZGxsjOzsbwJsHcpo1awZtbW1ERERg0KBBXL6uXbvi3r173PFp27YtYmJiAAB7\n9uxBr169Kp3zFStW4NGjRxg2bBjs7e1x69Yt5ObmYvz48bC2toa1tTXWrFkjMy6JRAKBQMCNUmRn\nZ6N169YAAEtLS5iamgIA1NXVYWdnh/v378ss5/Dhw/jPf/4DAOjRoweaNGmCq1evAgA6d+6Mdu3a\nVdpG3vqtWbMGhw4dwqZNm+Dg4IDXr1/D19cXzs7OsLOzg6enJxeXrDb17NkzLF26FGfPnoW9vT1m\nz54NALhy5Qp69+6Nzp07o3PnztyrjMqumfnz58PR0RE7d+7kxaPodbt//3507doVDg4OcHBwQGho\nKLdOKpVi2bJl6N69O9q2bStz1O/p06dYtmwZTp06xYsfADZv3gxnZ2eYmprif//7H5deVd0q8vHx\nwdSpU2XG7ebmxhthdXNz48pxc3ODr68vevXqhTZt2mDt2rXYt28fV48jR45w2wmFQvj7+8Pe3h4d\nO3bk4lyzZg1mzJjB5cvIyICBgQFev37NpQUEBKBTp06wt7eHg4MDcnJyKt0VKL9cdu4WLVoEBwcH\ndOrUCVevXsXEiRNhY2ODrl27IiMjAwBQXFyM/fv3Y9iwYVxZI0aMqHS+31c0x65huv/iPnbF7sKB\n+AN48uoJly5WF2NQh0GY5jQNnVp2qpNvt1L2HDsasft/AoGA5eXlccvjxo1jvXr1YgUFBaywsJBZ\nWlqyM2fOMMYYmzhxIjdiUlJSwry9vdn27dsrlRkWFsY6d+7MGHszgiYQCLiRkp9//pn16NFDZixl\necv2ER4ezoyNjVlBQQGvzIr7qLi/iiN25etX3vr169mUKVO45ezsbMYYY/7+/szX15dL9/f3Z/Pn\nz2eMMbZs2TLWvn17lpOTw0pKSpitrS3z8vJihYWFLC8vj0kkEm6Uadq0aWzz5s28fYaEhLDevXvL\njMfHx4cFBQUxxhiztbVlly9fZoy9+e8qJyenUv6SkhLm6urK4uLiahztvH37NjM2NmZt2rRhIpGI\nHT16lDH25thVjGHevHnccnh4OOvQoQOLiopiJiYm7MGDBzLLl0qlLCEhgVv28/NjPj4+jDHGcnJy\nmKWlJTt58qTMbQMDA5mWlhYzMjJilpaW7OnTp5XyZGRksFatWrHr169XWvfkyROmra3NSxswYAD7\n3//+x0uTNWInb/3Kn5uyfZbZvn078/b2ZoxV3aaCg4N5I17Pnz9n9vb27PHjx4wxxh49esSMjY3Z\nixcvuOvg0KFDMmNhTLHrtvzxvHXrFjM2NuaWpVIp17ZTU1OZSCSSeb0EBwczV1fXSjGUHZOLFy8y\nIyOjautWdizKkxX32bNnGWOVz1f5ZTc3N+6YP3r0iGlqarKvvvqKMcZYdHQ0r44CgYAtX76cMcZY\nYmIi09PTY1lZWezZs2fMwMCAq+/XX3/N5s6dy2339OlTpqOjw16/fs0YYyw3N5cVFxdXutbKL5ed\nuxMnTjDGGFuzZg1r1qwZi4uLY4y9+UxYvHgxF6e9vX2lY9KqVSulj+rXh4qfLaR+ZeZmsv1/7680\nQrfy/Ep2PvU8KyguqLfYlNUla9Qjdm9DIBDgk08+gbq6OtTU1ODg4MDNuTp27BjWrFkDe3t7ODo6\nIjY2FklJSTWWKRKJMGDAAABAly5dcOfOnSrzqqurc/PlXF1doampicTERCXUrLJu3brh5MmT8PPz\nw59//skbWauIlRsN69evH8RiMYRCIWxsbNC3b1+oqalBS0sL5ubmXP1SU1NhZGTEK8fIyEiuOWy9\ne/fG7NmzsXbtWty4cUPmK2/Wrl0LV1dX2NjYVFsWYwxDhw7Fhg0bcO/ePcTExGD69OlIS0vjzYNZ\nvXo1EhMT8c0333Bprq6uGDlyJHr16oWgoKBK9anKuXPnMHnyZACAWCzGyJEjcfbs2Ur5Ll++jC1b\ntiAlJQUPHjyAj49PpW9TefnyJQYPHsyN5MpLnv84Falf+TZw4sQJdOvWDdbW1li3bh33oueq2hSr\nMJp66dIl3L17F/3794e9vT0GDBgAoVDIPRGvoaGBzz77TKG6Vrxuy9phcnIyvLy8YGVlBW9vb6Sn\npyMzM5Pb1tvbGwBgYmICXV1dPHjwQGbdZc3hLNu2S5cuePToEQoLC6usm6zrvrq4a1J2fAwNDdGi\nRQsMHToUAODg4ICHDx+isLCQyztx4kQAb9484ODggKioKOjq6mLw4MHYu3cviouLsWPHDkybNo3b\nRkdHB2ZmZvj888+xY8cOvHz5EioqKjXGJRKJ0L9/fwCAvb09WrduzV2jjo6O3Dm+e/euzPZmbGxc\nq3muDQ3NsWsYcgpycCzxGLb+tRWJT//9W6oiUEFX466Y1XUWepn0grqKej1GqRwN4j12DVWTJk24\n31VUVFBcXMwtHz16lPtWi7ctb8WKFdwtk40bN8LExATAmz8i5f8oCwQCqKqq8m6Rlb9dUltdu3bF\n9evXERISgp9++gnfffcdLly4UGlf+fn5XDwCgaBSfao7XhX/oNf0IsaydevXr0dCQgLOnTuHzz77\nDHPnzsWkSZN4eS9cuIC///6b+8P0/PlztGvXDn///TdEon+/eDkrKwspKSncLZ8OHTrA2toaV65c\n4W57BgYG4sCBAwgNDYWGhgZvP7GxsZBIJEhLS6vmaFZdl7LfZXW0zp8/Dw8PD+jr6wMAPv/8c97Q\n/KtXr/DRRx+hX79+mDNnjsz96OnpAXhzy7Ds9/v373N1q4mi9bt37x7mzp2Lq1evwsTEBJcuXcLo\n0aMBVN2mZLGxsZF5iz01NbXafzKqUrEdlpSUAABGjhyJDRs2YPDgwWCMQUtLi3f9lD/fFdtvTcq2\nLevwFBcXgzFWZd3kibts/6qqqlwdgMrXfMW4ZcWirv7mj5Ws6xAAZs6cidGjR6Nly5awsLDgbv0D\nb27hXr58GRcvXkRoaCgcHR1x6tQp6OrqVvtZVLE+5eMUCoU1Hl96yTxRhtfFrxF5PxKXH1xGcSm/\nzdno28Bd6g5dTd16iu7daNQjdoq8x04sFnNzr2oyePBgfPvtt9yH2pMnT97qK0G++uorxMbGIjY2\nFq6urgCAwsJC7N+/H8Cbjsvr16/RsWNHtGvXDikpKcjOzgZjDL/88otc+6iufqmpqRCJRBgxYgTW\nrVvHzbUyMzNDTEwMGGN4+fIljh8/zm2jyAeuVCrFw4cPeWkPHjxA27Zta9w2MTERlpaW+PLLLzFm\nzLKSvDcAACAASURBVBhuvlh5f/zxB+7du4e7d+8iMjISurq6SElJ4XXqAKBly5YQi8VcByM9PR3X\nr1+HpaUlwsPD8cMPP2D79u0ICQmBjo4Ob9sNGzagpKQEMTExWLVqFeLi4mTG27RpU95x9vT05OYK\nvXz5EgcPHkSfPn0qbWdlZYXIyEju6coTJ07A2toawJs/mIMGDUK3bt1qnIfx2WefYdu2bQCAyMhI\nvH79Go6Ojrw8jLFK50/e+pWXk5MDdXV16Ovro7S0lNsvUHWbatq0KW+OZ/fu3ZGUlMS7Tv/6668a\n911Gkev2xYsX3D9jO3fuREFBQfUbyNCsWTO5r/W3rVsZMzMzbrsbN25wo6JlFLkWy77dJykpCbGx\nsejatSuAN+1PT08Pc+bMqfTEem5uLjIzM+Hi4gJ/f39YWVkhISEBBgYGKCoq4kYWyz6vFCXr8wGQ\n/zOioaM5dvWjuLQYl9IuYdPlTYi8H8nr1Jk1N8MUxykY2mlog+jUKXuOXaPv2Mk7DD5v3jz07t2b\nNwm7qltYGzduhIqKCvdgQ//+/fHo0aNK+QQCQaURt4rrq6Knp4fr16/D1tYWM2bMwC+//AJVVVW0\natUK8+bNg6OjI3r06IFWrVpVuY/yv8uqX5nw8HA4Ojpyt4vKXgEydOhQNG/eHJ06dcKnn37KezCj\nYt2qq4+7uzsuX77MS7t06RI8PT2rrH9ZWf/9739hbW0Ne3t7nD17FgsWLKhyG6DyiNijR49gb2/P\nlXn48GH4+vrC3t4effr0wddff41OnTrh1atXmDZtGvLy8tCnTx/Y29tzr1+Ijo5GYGAg9uzZAwMD\nA2zfvh3e3t4yX8fw5ZdfYvz48dzDE0uWLAFjDNbW1ujevTvGjh0LLy+vStsNGDAAQ4YMgZOTE+zs\n7LB3717uj/DOnTsRERGBkJAQ2Nvbw97eHt9++22l+gHAd999h/DwcHTo0AEzZszATz/9xK1bs2YN\nWrdujStXrsDHxwdt2rRBbm6uQvUrf26sra3x2WefwcLCAl27dkW7du24dWFhYTLblKenJ/Ly8mBn\nZ4fZs2dDR0cHx44dQ0BAAOzs7GBhYYGvv/660r6qouh1+8knn8DR0RF3795FixYtqi1bFg8PD+Tn\n53Pxy9pf2bKurq7MulXVEasqbj8/P5w4cQI2NjZYvXo1HBwc5NpO1rqSkhI4ODhg0KBB+PHHH3nH\nYOLEiVBRUcFHH30E4M3t0/T0dLx48QJDhgyBra0trK2tYWhoiKFDh0JVVRWbNm1Cnz590KVLF6iq\nqlb7WVTVsr29PR4+fMh7Zcy9e/egoaGBNm3aVFk3QmQpZaWIS49D4JVAhNwJQX5xPrfOUGSIsbZj\nMcZmDAzFhvUYJZ+bm5tSO3YN4rti3wUaxm84CgoKYGlpibi4OO7Wmp2dHY4fPw5jY+N6jo6QD4NQ\nKERubi60tLRkrp80aRI6derEPRVfl2bPng17e3tuXunq1atRWlqKhQsX1nks5P3EGEPys2ScTTmL\njLwM3jpdDV14tPOAZUvLOnnKtbaU1W+hjh2pE0FBQcjLy4Ofnx+OHz+OkydPvtMXyRJC+FRUVPDy\n5ctKHbtHjx6hd+/eMDQ0xMmTJyvNLa0LGRkZ+OSTTxAVFYWCggL06NEDERERtZpjST48D3Me4kzK\nGaRmp/LStdW04Sp1haOhI1SENT/wU9+oY1cD6tgRRYSHh9PTa0Qu1FaIIqi9vDtPXz1F6N1QJGQl\n8NLVVdTRzbgburfujiaqTarYuuFRVr+lUT8VWzbHji4qQgghpHHILcxFRGoEYh7HoJT9+2S2UCCE\no6EjXKWuEKmLqimhYQkPD1fqQzY0YkcIIYSQBq+guACX0i4h6kEUCksKeessW1qid9ve0NPSq6fo\n3h6N2BFCCCGk0SspLUHM4xhEpEYgr4j/tL5UR4o+7frAqKl8L43/EDTq150QIi961xSRF7UVoghq\nL7XHGEN8Zjy2RG/BiaQTvE6dvrY+RluPxjjbcdSpq4BG7AghhBDSoKQ8T8HZlLN49JL/jthmTZqh\nd9ve+D/27js6qvPMH/j3zox676jOqJiOEKbZgAoIsI+Nk9jZxcYxLtiOs3GI0zY5i40ROGtvNnFL\nnLa4YMy6pW1sx7/YRjCSaBYGgYwAgZBGDRUk1IXKzNzfH9cacZEEI2bmTvt+zuEs874zcx/2vJEf\nveV558TNgUrg3NR4uMeOiIiIXEJzbzN2V+9G1cUqWXuAJgDZ2mwsSlwEjcoz56S4x84KPBVLRETk\n+joHOrGnZg/KW8pl7RqVBjcl3YRlKcvgr1G+xqISFDsVu379equ+wM/PD6+++qrdArIXztjRZLDW\nFFmLY4Umg+Pl6vqH+1FcW4zDjYdhEk2WdgEC5sXPQ54uD6F+oU6MUDkOn7F7//33sWnTpqveayiK\nIp5//nmXTOyIiIjINQ2ZhvB5w+fYV7cPg6ZBWd+0qGnIT8tHbFCsk6JzbxPO2KWnp+PcuXPX/IJp\n06ahsrLS7oHZijN2RERErsUsmlHWVAa9QY+eoR5ZX3JoMlalr0JKWIqTonMuXil2DUzsiIiIXIMo\nijjddhqFNYVo62+T9UUHRmNl2kpMi5oGQRCcFKHz2Stvua6zwtXV1TAYDDY/nMhVsNYUWYtjhSaD\n4wWo66rD62Wv472K92RJXYhvCO6Yege+u/C7mB493auTOnuyKrG75557cODAAQDAG2+8gVmzZmHm\nzJncW0dERETjau1rxTtfvoPXy15HfXe9pd1P7Yf81Hx8f/H3MT9hPuvR2ZlVS7ExMTFobGyEr68v\nZs+ejT/+8Y8IDw/H17/+dVRVVV3r404hCAK2bNnCcidEREQK6h7sxt6avTjWfAwiRlMMtaDGosRF\nyNZmI9An0IkRupaRcidbt25Vbo9deHg4Ojs70djYiEWLFqGxsREAEBISgp6enmt82jm4x46IiEg5\nl4YvYX/9fhxqOASj2WhpFyBgTtwcrEhdgXD/cCdG6NoULVA8d+5cPPfcczAYDLj99tsBAA0NDQgL\nC7M5ACJXwFpTZC2OFZoMbxgvRrMRpY2lKKktwSXjJVlfRmQGVqatxJTgKU6KzvtYldi99tpr2Lx5\nM3x9ffHf//3fAICDBw/iW9/6lkODIyIiItdkFs0obynH3pq96BrskvUlhCRgVdoqpEakOik678Vy\nJ0RERGQ1URRRdbEKu6t3o6WvRdYXGRCJFakrMCtmFk+5TpLid8WWlJSgrKwMPT09locLgoBNmzbZ\nHAQRERG5vobuBuyu3g1Dp0HWHuQThFxdLubHz4dapXZOcATAysRu48aNeP/995GdnY2AgABHx0Sk\nOG/YB0P2wbFCk+Ep46W9vx2FNYU4eeGkrN1X7YslyUtwc9LN8NP4OSk6upxVid2uXbtQUVGBhIQE\nR8dDRERELqJ3qBd6gx5Hm47CLJot7SpBhfnx85Gry0Wwb7ATI6QrWbXHLjMzE3v27EF0dLQSMdkF\n99gRERFdn0HjIA7UH8CB+gMYNg/L+mbFzMKK1BWICoxyUnSeSdG7Yg8fPoxnn30W9957L+Li4mR9\nOTk5NgfhCEzsiIiIJsdkNuGL81+guLYYfcN9sr7U8FSsTFuJxNBEJ0Xn2RQ9PHHkyBF8/PHHKCkp\nGbPHrr6+foJPOV9BQQFvniCreMo+GHI8jhWaDHcZL6IoouJCBQqrC9Ex0CHriwuKw6r0VUiPSOdJ\nVwcYuXnCXqyasYuKisK7776LVatW2e3BjsYZO5oMd/nhS87HsUKT4Q7jpbqjGp+d+wxNvU2y9jC/\nMKxIXYE5cXN4n6sCFF2KTUlJQVVVFXx9fW1+oFKY2BEREU2sqacJu6t341zHOVl7gCYAOdocLExc\nCI3K6qpoZCNFE7sdO3agtLQUmzdvHrPHTqVyzSyeiR0REdFYHZc6sKdmD75s/VLWrlFpcFPSTViW\nsgz+Gn8nRee9FE3sJkreBEGAyWSyOQhHYGJHk+EOyyXkGjhWaDJcabz0D/ejuLYYhxsPwySO/rdb\ngIB58fOQp8tDqF+oEyP0booenqiurrb5QURERKS8IdMQDjUcwv66/Rg0Dcr6pkdPR35qPmKCYpwU\nHdkb74olIiLyQGbRjKNNR6E36NE71CvrSw5Nxqr0VUgJS3FSdHQle+UtE26Q27x5s1VfsGXLFpuD\nICIiIvsQRRGnLpzCb0t/i4/OfCRL6qIDo3HP7HuwYd4GJnUeasIZu+DgYJSXl1/1w6IoYv78+ejs\n7HRIcLbgjB1NhivtgyHXxrFCk6H0eKntrMVn1Z+hobtB1h7iG4LlqcuRNSWLpUtclMP32PX39yMj\nI+OaX+Dnx0t/iYiInKm1rxW7q3fjTPsZWbu/xh/LUpZhceJi+Kh9nBQdKYl77IiIiNxU10AX9AY9\njjUfg4jR/+apBTUWJS5CtjYbgT6BToyQrKXoqVgiIiJyHZeGL2Ff3T583vg5jGajpV2AgMy4TCxP\nXY5w/3AnRkjOwoV2IsCu9/SRZ+NYocmw93gxmo3YX7cfL3/+MvbX75cldTdE3oDHFjyGO2fcyaTO\ni3n0jF1BQQHy8vK40ZmIiNyaWTSjvKUce2v2omuwS9aXEJKAVWmrkBqR6qToyBZ6vd6uvwBwjx0R\nEZGLEkURZy+exe7q3Wjta5X1RQZEIj81HzNjZkIQBCdFSPai6B671tZWBAQEICQkBEajETt37oRa\nrcb69etd9q5YIiIid9bQ3YDPzn2G2q5aWXuQTxDydHm4Mf5GqFVqJ0VH9lJZWYvdu8/Z7fusysrW\nrFmDqqoqAMCTTz6J559/Hi+++CJ+9KMf2S0QImfivimyFscKTcb1jJe2/ja8X/E+Xj36qiyp81X7\nIk+XhyduegILExcyqfMAlZW1+MMfqrB37wq7fadVM3Znz55FVlYWAGDXrl04cOAAQkJCMHPmTLz0\n0kt2C4aIiMhb9Qz2oKi2CEebjsIsmi3tKkGFBQkLkKPNQbBvsBMjJHu6dAn49a/P4eTJfNhz55hV\niZ1arcbg4CDOnj2L8PBwaLVamEwm9Pb2XvvDRG6AB2zIWhwrNBnWjJdB4yD21+/HwfqDGDYPy/pm\nx87GitQViAyIdFCEpDSTCTh8GCgqAs6dU9k1qQOsTOxuvfVWrF27Fu3t7bj77rsBACdPnkRSUpJ9\noyEiIvISRrMRR84fQVFtEfqH+2V9qeGpWJW+CgkhCU6KjuxNFIHTp4HPPgMuXpTaVCppZjYszH7P\nsepU7MDAAN588034+vpi/fr10Gg00Ov1aG5uxj333GO/aOyIp2JpMnj/J1mLY4UmY7zxIooiTrSe\nwJ6aPegY6JD1TQmegpVpK5Eekc6Trh7k/Hngk0+AWvk5GAwP1+LChSrEx+dj2zYFT8X6+/vjscce\nk7XxBxsREdHknLt4Drurd6Opt0nWHu4fjhWpKzAndg4TOg/S1QUUFgLl5fJ2f38gNxdYtEiLqiqg\nsHCP3Z454Yzd+vXr5W/8aqCJoigbdDt37rRbMPbEGTsiInIVTT1N2F29G+c65GUtAjQByNHmYGHi\nQmhUHn1ngFcZHAT27QMOHgSMo5eDQKUCFi0CcnKAwCuu8HV4Hbv09NFp4La2Nrz55pu44447oNVq\nUVtbi48++ggPPPCAzQEQERF5msqqSuw+shtdg12ovlgN/1h/RCdEW/p9VD64KekmLE1ZCn+NvxMj\nJXsym4GyMmDPHqCvT943fTqwahUQFeXYGCZM7AoKCix/X716Nf7xj38gOzvb0rZv3z5s27bNocER\nKYX7pshaHCt0LZVVldi+ezuaYppQUVaB8OnhMJ40IgtZiEmIwY3xNyJXl4tQv1Bnh0p2VFUFfPop\n0Cq/IAQJCcDq1YBOp0wcVs37Hjp0CDfddJOsbfHixTh48KBDgiIiInJHPYM9+PU/f41TIadg7hmt\nRafJ0KC/tR/f/fp3ERMU48QIyd5aWqSE7twVl0eEhgIrVwJz5gBKbpu06lRsbm4uFi5ciGeeeQYB\nAQHo7+/Hli1b8Pnnn6O4uFiJOCeNe+yIiEgp3YPd2F+3H0eajmBf8T4MJA1Y+sL8wpAWkQZtpxY/\nuOcHToyS7Km3F9i7Fzh6FLJadL6+wLJlwM03Az4+1n+fonfF7tixA/feey9CQ0MRERGBjo4OLFiw\nAG+//bbNARAREbmrroEu7Kvbh6NNR2ESTQAA1Ve3dQb7BkMXrkNUQBQEQYCvyteZoZKdDA9LhyL2\n7QOGhkbbBQG48UZg+XIg2IkXhFg1Yzeirq4O58+fR3x8PLRarSPjshln7GgyuG+KrMWxQgDQOdCJ\nfXX7UNZUZknoRqi71GiobcCUOVNQe7wWuiwdBs8O4sHlD2JaxjQnRUy2EkWpbElhIdDdLe/LyJAO\nRsTFXf/3KzpjN8Lf3x+xsbEwmUyorq4GAKSlpdkcxGT97Gc/w8GDB6HT6fD6669Do+ERcSIicrzO\ngU6U1JbgWPOxMQldUmgScrW5yIjMwJlzZ1B4tBDtF9sR2xqL/OX5TOrcWG2tVGD4/Hl5e2ysdDAi\nI8M5cY3Hqhm7f/7zn3j44YfR1CQvqCgIAkwm0wSfcozjx4/jV7/6Fd566y08++yzSEtLG/f2C87Y\nERGRvXRc6kBxbTGOtxyHWTTL+pJDk5Gny0NaRBqLC3uY9nZg927g1Cl5e1AQsGIFMG+eVJvOHhSd\nsfvud7+LzZs34/7770fglRX1FHbw4EHccsstAKQ7bN944w2XvdaMiIjcW3t/O0rqSlDeUj4modOG\naZGry0VqeCoTOg9z6RJQVASUlkq16UZoNNKhiGXLAD8/58V3NVYldp2dnXjsscdcYuB2dHQgPj4e\nABAaGoqLIzfpEtmA+6bIWhwr3qGtvw0ltVJCJ0I+i6IL1yFXmwtduO6a/13keHEvJpOUzBUXS8nd\n5TIzgfx8ICzMObFZy6oJxIcffhivv/66XR/8yiuvYMGCBfD398dDDz0k67t48SLuvPNOBAcHQ6fT\n4Z133rH0hYeHo/urXYtdXV2IjIy0a1xEROS9LvRdwF9O/gW/Lf0tjrcclyV1qeGpeCjrITyY9SBS\nIzhL50lEETh5Evjtb6W9dJcndVot8OijwF13uX5SB1i5x27ZsmUoLS2FVqvFlClTRj8sCNddx+5v\nf/sbVCoVPvnkE1y6dAlvvPGGpW/dunUAgNdeew1lZWW4/fbbceDAAcycORPHjx/HCy+8gDfffBPP\nPvss0tPTcffdd4/9h3GPHRERWam1rxXFtcWoaK0YM0OXHpGOXF0uUsJSnBQdOVJjo5TM1dXJ2yMj\npZOu06crU2BY0T12jzzyCB555JFxg7hed955JwDgiy++QENDg6W9r68Pf/3rX1FRUYHAwEAsXboU\nX//61/HWW2/hueeew9y5cxEXF4ecnBxotVr89Kc/nfAZDz74IHRf3eERHh6OrKwsy5S4Xq8HAL7m\na77ma7724tctvS34/Z9+D0OXAbosHQDAcMwAAFi5YiVytbk4V3YO1R3VSMlLcXq8fG2/1/Pm5WH3\nbuDDD6XXOp3Uf/68HllZwGOP5UGtdtzzR/5uMBhgT5OqY+cITz31FBobGy0zdmVlZVi2bBn6Lrs9\n94UXXoBer8cHH3xg9fdyxo4mQ6/XW/5HR3Q1HCueobm3GUWGIpxqOzWm74bIG5Cry0VSaJLNz+F4\ncT2Dg1Jx4YMHAaNxtF2tBhYuBHJzgYAA5eNSdMZOFEW88cYbeOutt9DY2IikpCTcd999eOihh2ze\nY3Dl53t7exEaKr8YOSQkBD09PTY9h4iIqKmnCUW1RTjddnpM37SoacjV5SIhJMEJkZGjmc3S9V97\n9wKXzR0BAGbMkJZdPWHbvlWJ3bPPPoudO3fixz/+MVJSUlBXV4df/vKXOH/+PJ566imbArgyOw0O\nDrYcjhjR1dWFkJAQm55DdDX8jZqsxbHins73nEeRoQiV7ZVj+qZHT0euNhfxIfF2fy7Hi2uoqpL2\n0V24IG9PSABuuUU6IOEprErstm/fjqKiItk1Yrfccguys7NtTuyunLGbOnUqjEYjqqqqkPFVKefj\nx49j9uzZk/7ugoIC5OXl8X9YREReqrG7EXqDHmcvnh3TNzNmJnK0OZgSPGWcT5InaGkBPv0UOHdO\n3h4aCqxcCcyZo8zBiKvR6/WyfXe2smqPXWxsLGpqahAUFGRp6+3tRVpaGlpbW6/rwSaTCcPDw9i6\ndSsaGxuxfft2aDQaqNVqrFu3DoIg4NVXX8XRo0exZs0aHDx4EDNmzLD+H8Y9djQJ3AdD1uJYcQ/1\nXfUoqi1C1cUqWbsAwZLQxQXbcLGnlThenKO3F9izBygrk0qZjPD1BbKzgZtuAnx8nBffeBTdY3fr\nrbfivvvuw3PPPQetVguDwYAnn3zScgPE9XjmmWewbds2y+tdu3ahoKAATz/9NH73u99hw4YNiI2N\nRXR0NP7whz9MKqkjIiLvVNdVB71Bj+qOalm7AAGzYmchR5uD2KBYJ0VHjjY8LB2K2LcPGBoabRcE\n4MYbgeXLgeBg58WnBKtm7Lq6urBx40a89957GB4eho+PD9auXYvf/OY3CA8PVyLOSRMEAVu2bOFS\nLBGRFzB0GlBkKEJNZ42sXYCAOXFzkJ2SjZigGCdFR44mikB5OVBYCFyxTR8ZGcDq1UCsi+bzI0ux\nW7dutcuM3aTKnZhMJrS1tSE6OhpqtdrmhzsSl2KJiDybKIpSQldbBEOnQdYnQEBmXCaytdmIDox2\nToCkCINB2kd3/ry8PTZWSui+2q7v8uyVt1iV2L355pvIysrC3LlzLW3Hjx9HeXk51q9fb3MQjsDE\njiaD+2DIWhwrzieKImo6a1BkKEJtV62sTyWokBmXiRxtDiIDnF+7guPFcdrbgc8+A05fUbkmKAhY\nsQKYNw9QqZwT2/VQdI/d5s2bcezYMVlbUlIS7rjjDpdN7IiIyLOIoohzHedQZChCfXe9rE8lqJA1\nJQvZKdmICIhwUoSkhP5+oKgIOHxYqk03QqMBliwBli4F/PycF5+zWTVjFxERgba2Ntnyq9FoRFRU\nFLq6uhwa4PXijB0RkWcQRRFVF6tQVFuEhu4GWZ9aUEsJnTYb4f6uueeb7MNolJK5oiJgYEDel5kJ\n5OcDYWHOic0eFJ2xmzFjBv785z/j7rvvtrT97W9/c/mTqqxjR0TkvkRRxNmLZ1FkKEJjT6OsTy2o\nMS9+HpalLGNC5+FEETh1Slp27eiQ92m1UoHhBDe+LMQpdez27duH2267DatWrUJaWhrOnTuH3bt3\n4+OPP8ayZcvsFow9ccaOJoP7YMhaHCuOJ4oiKtsrUWQoQlNvk6xPLagxP2E+liYvRZi/60/PcLzY\nprFRujGirk7eHhkpXQE2fbrzCwzbi6IzdsuWLcOXX36Jt99+Gw0NDVi0aBFefvllJCcn2xwAERER\nICV0p9tOo6i2CM29zbI+jUqD+fHzsTRlKUL9Qif4BvIUnZ1S6ZIvv5S3BwQAubnAwoWAixfncJpJ\nlztpaWlBghvMeXLGjojIPYiiiFNtp1BkKEJLX4usT6PSYEHCAixNXooQP94Z7ukGB4GSEuDQIWlP\n3Qi1Gli0CMjJkZI7T6TojF1HRwcef/xx/PnPf4ZGo0F/fz8++OADlJaW4uc//7nNQRARkfcxi2ac\nvHASxbXFaO2TX0/po/LBwsSFWJK8BMG+Hn5VAMFsBo4eBfbuBfr65H0zZkjLrpHOr17jFqyq8PKd\n73wHoaGhqK2thd9XZ4hvvvlmvPvuuw4NzlYFBQV23ZBInovjhKzFsWI7s2jGly1f4veHf48/n/yz\nLKnzVftiafJS/OCmH2B1+mq3T+o4Xq5OFIGzZ4Hf/x746CN5UpeYCDz0EHD33Z6d1On1ehQUFNjt\n+6xaio2OjkZTUxN8fHwQERGBjq+OpYSGhqL7yrs7XASXYmkyuMGZrMWxcv3MohknWk+guLYYbf1t\nsj5ftS8WJS7CkuQlCPQJdFKE9sfxMrGWFunGiHPn5O1hYVLpkjlzPOdghDUUvXkiIyMDxcXFSEhI\nsCR2dXV1WL16NU5fWfLZRTCxIyJyDWbRjPKWcpTUlqD9Urusz0/th8VJi3FT0k0eldDRxHp6pCXX\nsjJpxm6Ery+QnQ3cdBPg4+O8+JxF0T12jzzyCP7lX/4FP//5z2E2m3Hw4EFs2rQJjz32mM0BEBGR\nZzKZTShvKUdxbTE6BuQFyPw1/licKCV0AT4euhueZIaHgQMHgP37gaGh0XZBAObPB/LygGD3Xnl3\nCVbN2ImiiF//+tf44x//CIPBgJSUFHznO9/BE088AcFF50k5Y0eTweUSshbHyrWZzCYcbzmOktqS\ncRO6m5NuxuKkxfDX+DspQuVwvEizcuXlUvmSK3dvZWQAq1cDsbHOic2VKDpjJwgCnnjiCTzxxBM2\nP5CIiDyTyWxCWXMZ9tXtQ+dAp6wvQBOAm5NvxqLERV6R0JHEYJAKDDfJ60wjNla6MSI93SlheTSr\nZuz27NkDnU6HtLQ0NDU14Wc/+xnUajWee+45TJkyRYk4J00QBGzZsoVXihEROZjRbERZk5TQdQ3K\n7w8P9AnEzUlSQuen8eKb2b1MW5t0BVhlpbw9OBhYvhyYNw9QWVWXw/ONXCm2detW5Q5PTJ8+HZ9+\n+ilSUlKwbt06CIIAf39/tLW14YMPPrA5CEfgUiwRkWMZzUYcbTqKfXX70D0oX2ML9AnE0uSlWJi4\nEL5qXydFSErr7weKioDDh6XadCM0GmDJEmDpUsCP+f24FD0VO1LWZHh4GHFxcZZ6dvHx8Whvb7/W\nx52CiR1NBvfBkLU4VoBh0zCONB3B/rr96BnqkfUF+QRhacpSLEhYwIQO3jNejEagtBQoLgYGBuR9\nc+cCK1ZIZUxoYorusQsNDUVzczMqKiowa9YshISEYHBwEMPDwzYHQERE7mHYNIwvzn+B/fX7RorE\nBAAAIABJREFU0TvUK+sL9g3G0mQpofNRe2GtCi8lisDJk8Du3UCH/JwMdDrpYIQb3ELqUaxK7DZu\n3IhFixZhcHAQL730EgBg//79mDFjhkODI1KKN/xGTfbhjWNlyDQkJXR1+9E3LL/vKcQ3BMtSluHG\n+BuZ0I3Dk8dLQ4N0MKK+Xt4eFSVdATZtmncVGHYVVi3FAkBlZSXUajUyMjIAAGfOnMHg4CDmzJnj\n0ACvF5diiYhsM2QaQmljKQ7UH0D/cL+sL9Qv1JLQaVRWzRGQh+jslGboTpyQtwcEALm5wMKFgFrt\nnNjcmaJ77NwREzuaDG/ZB0O284axMmgcRGljKQ42HByT0IX5hWFZyjLMi5/HhM4KnjReBgaAffuA\nQ4ekPXUj1Gpg0SIgJ0dK7uj6OHyP3fTp0y3XhSUnJ08YRF1dnc1BOEpBQQHLnRARWWnAOIDPGz7H\noYZDuGS8JOsL9w9Hdko25k6Zy4TOy5jNwJEj0jVg/fI8HzNnAitXApGRzonNE4yUO7GXCWfsSkpK\nkJ2dbXnoRFw1aeKMHRGRdQaMAzjUcAiHGg5hwCg/0hjhH4FsbTbmxs2FWsX1NW8iisDZs1I9ugsX\n5H2JiVKB4ZQU58TmibgUew1M7IiIru7S8CVLQjdoGpT1RQZEIjslG5lxmUzovFBzM/Dpp0B1tbw9\nLEyaoZs9mwcj7M3hS7GbN2+e8CEj7YIgYNu2bTYHQeRsnrQPhhzLE8ZK/3A/DtYfRGlj6ZiELiog\nCjnaHMyJmwOVwKsBbOVu46WnB9izBzh2TJqxG+HnB2RnA4sXAz48/OzSJkzs6uvrIVwlHR9J7IiI\nyD30DfXhYIOU0A2ZhmR90YHRyNHmYHbsbCZ0XmhoCDh4UDoccXmJWkEA5s+XrgELCnJefGQ9LsUS\nEXm4vqE+HKg/gMPnD49J6GICY5CjzcGs2FlM6LyQKALHjwOFhdJs3eVuuEGqRxcb65zYvI3Dl2Kr\nr1xYn0BaWprNQRARkf31DvVif91+fHH+Cwyb5TcFxQbFIlebi5kxM7n64qVqaqR9dE1N8va4OOnG\niPR058RFtplwxk6luvZvboIgwGQy2T0oe+CMHU2Gu+2DIedxh7HSM9iD/fVSQmc0G2V9cUFxyNXl\nYkb0DCZ0CnDF8dLWJp10rayUtwcHS3e6ZmUBVqQAZGcOn7Ezm802fzkRESmne7Ab++v240jTkTEJ\n3ZTgKcjV5mJ69HQmdF6qvx/Q64EvvpBq043w8QGWLAGWLgV8fZ0WHtmJR++x27JlCwsUE5HH6xro\nwr66fTjadBQmUb6KkhCSgFxtLqZGTWVC56WMRqC0FCgulm6PuNzcuUB+PhAa6pzYaLRA8datWx1b\nx+6WW27BJ598AgCWQsVjPiwIKC4utjkIR+BSLBF5us6BTuyr24eyprIxCV1iSCJydbm4IfIGJnRe\nShSBkyele107OuR9Op20jy4hwSmh0TgcvhR7//33W/7+8MMPTxgEkSdwxX0w5JpcYax0XOrAvrp9\nONZ8bExClxSahDxdHtIj0vkz2gU4a7w0NACffALU18vbo6Kkk67TprHAsKeaMLH71re+Zfn7gw8+\nqEQsRER0FRcvXURJbQmOtxyHWZTvg04OTUaeLg9pEWlM6LxYZ6c0Q3fihLw9IADIywMWLADUvEjE\no1m9x664uBhlZWXo6+sDMFqgeNOmTQ4N8HpxKZaIPEV7fztK6kpQ3lI+JqHThmmRq8tFangqEzov\nNjAAlJQAn38u7akboVZLt0VkZ0vJHbkuhy/FXm7jxo14//33kZ2djQCODCIiRbT1t6GkVkroRMh/\n4OvCdcjT5UEXrnNOcOQSTCbgyBHptGt/v7xv5kzpXtfISKeERk5i1YxdREQEKioqkOBGuyw5Y0eT\n4Qr7psg9KDFWLvRdQHFtMU60nhiT0KVFpCFXmwttuNahMZB9OGq8iCJw9qxUYLitTd6XmAjccguQ\nkmL3x5IDKTpjl5ycDF8WtyEicqjWvlYU1xajorViTEKXHpGOXF0uUsL4X2tv19wsJXRXXhAVFibN\n0M2ezYMR3syqGbvDhw/j2Wefxb333ou4uDhZX05OjsOCswVn7IjIXbT0tqC4thgnL5wck9BlRGYg\nV5uL5LBkJ0VHrqKnB9izBzh2TJqxG+HnJ+2hW7xYKjZM7knRGbsjR47g448/RklJyZg9dvVXnqUm\nIiKrNPc2o8hQhFNtp8b0TY2ailxtLhJDE50QGbmSoSHgwAFg/35g+LIrf1UqYP586bRrUJDTwiMX\nY9WMXVRUFN59912sWrVKiZjsgjN2NBncY0fWssdYaeppQlFtEU63nR7TNy1qGnJ1uUgIcZ89zTQx\nW8aL2QwcPy7N0vX0yPtuuEEqMBwTY3uM5BoUnbELCgpCbm6uzQ8jIvJm53vOQ2/Q40z7mTF906On\nI1ebi/iQeCdERq6mpkYqMNzcLG+Pi5MSuvR058RFrs+qGbsdO3agtLQUmzdvHrPHTqVSOSw4W3DG\njohcRUN3A4oMRTh78eyYvpkxM5GjzcGU4ClOiIxcTVubdDDizBW5f3AwsGIFkJUlLcGS57FX3mJV\nYjdR8iYIAkwm07h9ziYIArZs2YK8vDwusRGRU9R31aOotghVF6tk7QIES0IXFxw3wafJm/T1AUVF\nwBdfSEuwI3x8gCVLgKVLARan8Ex6vR56vR5bt25VLrEzGAwT9ul0OpuDcATO2NFkcI8dWcuasVLX\nVQe9QY/qDnk9CgECZsXOQo42B7FBsQ6MklzFtcaL0SjdFlFcDAwOjrYLAjB3rjRLFxrq+DjJ+RTd\nY+eqyRsRkSsxdBpQZChCTWeNrF2AgDlxc5CjzUF0YLSToiNXIopARYV0r2tnp7xPp5MKDMdzuyVd\nB6vvinU3nLEjIiWIoigldLVFMHQaZH0CBGTGZSJHm4OowCjnBEgup75e2kd3ZbWwqCjpYMTUqSww\n7I0UnbEjIiI5URRR01mDIkMRartqZX0qQYW5cXORrc1GZAAv6iRJR4c0Q1dRIW8PDARyc4EFCwC1\n2jmxkedgYkcE7rGja6usqsTuI7tx8sRJRKdGwyfaB8ZQo+w9KkGFrClZyE7JRkRAhJMiJVei1+tx\n0015KCkBDh0CLj9vqFZLt0Xk5AD+/s6LkTwLEzsiomuorKrE/+z+H/Qn9eM4jsNX5QtjqRFZM7MQ\nnRANtaCWEjptNsL9w50dLrmAyspafPrpORQVleOll8xISkpHdLTW0j9rlnSvawTzf7Izq/bYVVdX\n48knn8SxY8fQ29s7+mFBQF1dnUMDvF7cY0dEtugb6oOh0wBDpwFv/t+baI1tHfOe4IZg/Nvaf8Oy\nlGUI8w9zQpTkio4ercXLL1fhwoV89PdLbUZjIbKyMpCVpcXq1UBKinNjJNej6B67e++9FxkZGXjh\nhRfG3BVLROQJBowDlkSupqMGLX0tlr7uoW7ZewUISAhJwGztbNw+9XalQyUXNDQEnD4NlJcD77xz\nDn19+bL+4OB8hIfvwcMPa3kwghzKqsTu5MmT2L9/P9Tc1UkeinvsvM+gcRB1XXWo6ayBodOApp4m\niBj/t2UVVFAJKoT6hWKgagDzbpoHP40fwkycpfNmZjNQXS0lc6dPS8kdAJhMo0X9u7v1yMrKQ1IS\nEBmpYlJHDmdVYpeTk4OysjIsWLDA0fEQETnEsGkY9d31qOmoQU1nDc73nIdZNE/4fpWgQmJIIlIj\nUrEsdBk+O/wZArQBMDQb4Kfxw+DZQeQvz5/w8+SZRBFoapKSuRMngMt2J1moVGaEhUn3uvb3jy67\n+vpOPN6I7MWqPXaPP/443nvvPdx1112yu2IFQcC2bdscGuD14h47Iu9mNBvR0N1gWVpt6G6ASZz4\nCsSR5VVduA6pEalICUuBr3r0DqfKqkoUHi3EkHkIvipf5N+Yj2kZ05T4p5AL6OgAvvxSSuja2sZ/\nT0wMkJkJ+PvX4q9/rYKf32jiPzhYiAcfzMC0adrxP0xeT9E9dn19fVizZg2Gh4fR0NAAQKrhJHBO\nmYhchMlswvme81Ii11mDuq46GM3Gq35mSvAUpIanQheugzZcC3/NxDUnpmVMYyLnZfr7gZMnpWRu\nonOCwcHAnDlSQjdlykhhYS1CQ4HCwj0YGlLB19eM/HwmdaQM3jxBBO6xc0dm0Yzm3mbUdEh75Gq7\najFkGrrqZ2ICY5AakYrU8FRow7UI9Amc9HM5Vjyb0QicOSMlc2fPyuvOjfD1BWbMkJK51FRApRr7\nnhEcL2Qth8/YGQwGyx2x1dXVE70NaWlpNgdBRHQtoiiita8VNZ01qOmoQW1XLQaMA1f9TGRAJFLD\nU5EaIc3KBfsGKxQtuRNRBGprpWTu5ElgYJxhpVIB6elSMjdtmpTcEbmiCWfsQkJC0NPTAwBQTfDr\niCAIMI3364wL4IwdkXsTRRHtl9othx0MnQb0D/df9TNhfmGWGbnUiFSE+oUqFC25o9ZWKZn78kug\nq2v89yQmSsnc7NlAUJCy8ZF3sVfe4nZLsd3d3Vi5ciVOnTqFzz//HDNnzhz3fUzsiNyLKIroGOiw\nHHao6axB79A4Rw4vE+IbYpmNSw1PRbh/OPf+0lV1d0unWcvLgebm8d8TESElc5mZQFSUsvGR91L0\n8IQrCQwMxMcff4x///d/Z+JGdsN9MM7RNdBlmY2r6ahB1+AE0yZfCfIJspxa1YXrEBUQpXgix7Hi\nfgYHgVOnpGSupkZaer1SYKB0zVdmJpCUBLvVm+N4IaW5XWKn0WgQHR3t7DCI6Dr0DvXKllYvXrp4\n1ff7a/wts3GpEamICYzhjBxZxWQCzp0bLR5sHOeAtEYDTJ8uJXPp6QBr8JMncLvEjsgR+Bu1Y/QP\n98uWVtv6JygA9hVftS+0YVrLPrm44DiohKscOXQCjhXXJYpAQ4O0Z+7ECVjuab2cIEgnWTMzpZOt\nfn6OjYnjhZSmaGL3yiuvYMeOHThx4gTWrVuHN954w9J38eJFPPzww/jss88QHR2N5557DuvWrQMA\nvPjii/jggw+wZs0a/PjHP7Z8hr+5E7mWAeMAajtrLSdXL79vdTw+Kh+khKVYllcTQhJcLpEj19fe\nPnoI4uIEk8BTpoweggjlmRryYJNO7Mxm+ZUoE52YHU9iYiI2b96MTz75BJcuXZL1Pf744/D390dr\nayvKyspw++23Y+7cuZg5cyZ++MMf4oc//OGY7+MeO7IX7oO5PiP3rY4UBb7afasAoBbUSA5LthQF\nTgxNhEblXgsHHCuuoa9v9BBEY+P47wkNlZK5OXOk672cgeOFlGbVT9QjR47ge9/7Ho4fP46Bywr8\nTLbcyZ133gkA+OKLLyw3WADSzRZ//etfUVFRgcDAQCxduhRf//rX8dZbb+G5554b8z233XYbjh8/\njsrKSjz22GN44IEHrI6BiK7f5fetGjoNaOxptPq+1dTwVCSFJsFH7aNgxORJhoel/XLl5dL+OfM4\nQ8/Pb/QQhFZrv0MQRO7CqsTugQcewNe+9jW89tprCAycfKX2K10503bmzBloNBpkZGRY2ubOnQu9\nXj/u5z/++GOrnvPggw9aiiyHh4cjKyvL8pvTyHfzNV+PuPw3a2fH4yqvl+UsQ2N3I/72z7+hqacJ\nwVODYRJNMBwzAAB0WToAsLxOzUpFfEg8uk93Iz4kHv96+7/CV+0LvV6P2tpapOalutS/73pe5+Xl\nuVQ8nv7abAbeeUeP6mpArc7D0BBgMEj9Op30/ro6PZKSgHvuycPUqcC+fXoYDKP9HC987YqvR/5u\nMBhgT1bVsQsNDUVXV5fd9rRt3rwZDQ0Nlj12JSUlWLt2LZqamizv2b59O95++23s3bv3up7BOnZE\nk2cWzTjfc95y2KG+qx7D5uGrfmZK8BTLydVr3bdKZA1RlGrMlZdLy61f1cofIyVFmpmbOVMqV0Lk\nzhStY3fnnXfik08+wa233mrzA4GxM3bBwcHo7u6WtXV1dSEkJMQuzyO6Fv1ls3XeZOS+1ZGTq5O5\nb1UXroMuXHdd9626M28dK0ro7JQOQJSXAxcujP+e6OjRfXMREcrGdz04XkhpViV2ly5dwp133ons\n7GzEXbYDVRAE7Ny5c9IPvXLmb+rUqTAajaiqqrIsxx4/fhyzZ8+e9HdfrqCgwDIVTkTy+1YNnQYY\nOg28b5Wc6tIl6X7W8nLpvtbxBAdLp1kzM4H4eO6bI8+i1+tly7O2smoptqCgYPwPCwK2bNli9cNM\nJhOGh4exdetWNDY2Yvv27dBoNFCr1Vi3bh0EQcCrr76Ko0ePYs2aNTh48CBmzJhh9fdfGRuXYsnb\n2Xrfqi5chzD/MIWiJW9hNAJnz0rJ3JkzUjHhK/n4SHXmMjOBtDRApVI+TiIlueVdsQUFBdi2bduY\ntqeffhodHR3YsGGDpY7df/3Xf+Gee+657mcxsSNvJIoiOgc6LXXkDJ0G9AxNsEHpKyG+IZY6crxv\nlRxFFIG6OimZq6gABsaZKBYE6QaIzEzpRghfX+XjJHIWxRO7vXv3YufOnWhsbERSUhLuu+8+rFix\nwuYAHIWJHU2GO++D6RrostSRs+a+1UCfQMtsXGpEqlPuW3Vn7jxWnOHCBSmZKy8HuiYYmgkJo8WD\ngz1spZ/jhayl6OGJV199FZs2bcIjjzyCxYsXo66uDvfeey+2bduGb3/72zYH4SjcY0eeaOS+1ZFk\nztr7VkdOrsYGxTKRI4fq6RktHnxZsQOZ8HApmcvMlA5EEHkrp+yxu+GGG/DnP/8Zc+fOtbSVl5fj\nrrvuQlVVld2CsSfO2JGnGLlvdeTk6oX+CY4LfuXy+1Z14TpMCZ7Ca7rI4QYHR4sHV1dLS69XCggY\nLR6cnMxDEESXU3QpNioqCk1NTfC9bMPD4OAgEhIS0N7ebnMQjsDEjtzV5fetGjoNaO5tvur7fVQ+\nlmu6UiNSER8cD7VKrVC05M1MJimJKy+XkrrhcUoeajTA1KlSMnfDDYCaQ5NoXIomdl/72teQkpKC\nX/ziFwgKCkJvby/+4z/+AwaDAR9++KHNQTgCEzuaDGfugxkyDaGuq85yctXa+1ZHllbd8b5Vd+bt\ne6ZEETh/frR4cF/f+O/T6UaLB/t7cc1qbx8vZD1F99j94Q9/wD333IOwsDBERkbi4sWLWLJkCd55\n5x2bA3Ak7rEjVzRy3+rI0qq1962OHHZIDk3mfaukuIsXR4sHT7RQExs7Wjw4jFVyiKzilD12I+rr\n63H+/HkkJCQgOTnZbkE4AmfsyFWYzCY0dDdYDjvUd9XDJI5TuOsrAgTEh8RbTq6mhKXAT+OnYMRE\nkv5+qTRJeTlQXz/+e0JCRpO5uDjumyO6Xg5fihVF0XJyzmy+ymyCi1aNZGJHznL5fauGTgPquuqu\ned9qXFCcpY4c71slZxoelooGl5dLRYTH+/Hv5yctsWZmAlotiwcT2YPDl2JDQ0PR89XNyxrN+G8T\nBAGm8UqGE7kZW/bBmEUzWnpbLHXk6rrqMGgavOpnYgJjLEur3njfqjvzxD1TZjNgMEjJ3KlT0gnX\nK6lU0uGHzEzpMIQPdwNYxRPHC7m2CRO7iooKy9+rq6sVCYbIHYiiiAv9F2TXdFlz3+rIYQdduA4h\nfiEKRUs0PlEEWlqkZO7LL6Xac+NJTpaSuVmzgED+/kHk8qzaY/erX/0KP/nJT8a0v/DCC/jRj37k\nkMBsNXKPLQ9PkK1G7lsdOexg6DSgb3iCo4BfGblvdSSZ432r5Cq6ukYPQbS2jv+eqKjRfXORkcrG\nR+RtRg5PbN26VblyJyEhIZZl2ctFRESgo6PD5iAcgXvsyBYdlzoss3E1HTXXvG812DfYUkdOF65D\nhH8Eb3cglzEwAJw8KSVztbXjFw8OCpKu9MrMlK744vAlUpYi5U727NkDURRhMpmwZ88eWd+5c+cQ\nGhpqcwBEzlRZVYndR3bj2PFjiE6NRqI2EcZQIzoHOq/6uUCfQMtsHO9b9S7usmfKZJIOP5SXS4ch\njMax7/HxAaZPl5K5tDQWD3YEdxkv5Dmumtht2LABgiBgcHAQDz/8sKVdEATExcXhN7/5jcMDJLIH\nURTRM9SDzoFOy58TZ07g49KPYdQa0WxuRrhPOIzFRmTNzEJ0gvzySn+Nv+WaLt63Sq5KFKWyJOXl\nUpmSS5fGvkcQpCQuM1NK6vxYSYfIo1i1FLt+/Xq89dZbSsRjN1yK9S5m0YzeoV5Z4nb5n66BrjG1\n40r3laI/qX/MdwU1BGFp7lJow7SWk6u8b5VcWVublMyVlwOdE0w2x8dLydzs2VLtOSJyLYrePOFu\nSR15nutJ3K75nRgt0KUSVAjzC0O4fzhSxBT8bOnPeN8qubTeXulKr/Jy6Yqv8YSFSclcZiYQE6Ns\nfETkHFYldl1dXSgoKEBRURHa29stBYsFQUBdXZ1DA7QFrxRzH2bRjJ7B0aXSrsEumxO3KwX6BCLc\nP9zypy+mDwOxA/DX+KOlogVp89IAALFDsUzqaEJOvVd4CDh9Wkrmzp0b/xCEv79UmiQzE0hJ4SEI\nZ+MeO7oWe18pZlVi9/jjj6O+vh5PP/20ZVn2l7/8Jb75zW/aLRBHKCgocHYI9JUrE7cxM26DXVe9\nL9UaQT5BssTt8j9h/mHwVfvK3q8Vtdixdwf8bvCzLLMOnh1E/vJ8m+IgsiezGaiuHi0ePDzOJSZq\ntVQ0ODNTKiI8QU15InJBIxNQW7dutcv3WbXHLiYmBqdOnUJ0dDTCwsLQ1dWFxsZG3HHHHTh69Khd\nArE37rFTlismbtaorKpE4dFCDJmH4KvyRf6N+ZiWMc2mOIlsJYpAU9No8eC+CcomarVSMjdzJhAQ\noGyMRGRfDr8r9nLR0dFoamqCj48PkpKScOLECYSGhiIsLGzc+naugImdfblr4kbkTjo6RosHt7WN\n/56YmNHiweHhysZHRI6j6OGJzMxMFBcXIz8/H8uWLcPjjz+OoKAgTJvGmQ1P4e2JG/fBkLXsPVb6\n+0eLB0+0ZTk4WErkMjOBKVO4b86d8GcLKc2qxG779u2Wv7/88svYtGkTurq6sHPnTocFRvZlFs3o\nHuye8ESpPRK3YN9gy8nS8f74qHlrOBEgFQs+c0ZK5s6elYoJX8nXF5gxQ0rmUlMBFavtEJEVrFqK\n/fzzz7F48eIx7aWlpVi0aJFDArOVty3FXi1x6xzoRPdgt10Stwln3PzCmLgRXYUoStd5jRQPHhwc\n+x6VCkhPl5K5adOk5I6IvIOiS7ErV64cdy/drbfeiosXL9ochKN4UrkTJm5E7qmlZfQQRHf3+O9J\nTBwtHhwUpGx8RORc9i53ctUZO7PZDFEUER4ejq6uLlnfuXPnsHTpUrS2ttotGHtytxk7Jm7OxX0w\nZC1rxkp39+ghiJaW8d8TGTl6CCIqyv5xkmvgzxayliIzdprLiiFpriiMpFKp8OSTT9ocgLcwmU2W\nxO3K4rtM3Ijc3+Dg6CEIg2H84sGBgdKsXGamNEvHQxBEZG9XnbEzGAwAgJycHJSUlFgySUEQEBMT\ng8DAQEWCvB5Kz9hdnrhNNOMmwrZ4QnxDZKdImbgROZfJBFRVSclcZaV0KOJKGg0wfbqUzKWnS8WE\niYiupGgdO3dk78RO6cRtvHIgGhXLyRM5S2VlLXbvPoehIRX6+syIjk5Hd7cW/f1j3ysI0knWzEzp\nZKufn/LxEpF7UfTwxPr168cNAIDHlDxh4ubduA+Grqayshavv16FCxfyceKEHoGBK2A0FiIrC4iO\n1lreN2XK6CGI0FAnBkwugz9bSGlWZRLp6emyTLK5uRl/+ctf8K1vfcuhwdnqt+/9Fivnr8S0jGlM\n3IjouphMwGuvncOxY/kYGgKGhqS9chpNPmpq9iAtTWs5BBEX5+xoicjbXfdS7BdffIGCggJ89NFH\n9o7JLgRBwNr316K3shdzps9BQHQAEzcispooSidb9+4F/t//02NgIM/Sp1YDsbHADTfosXVrHg9B\nEJHNFF2KHU9WVhaKiopsDsCRWvpagCTgy9NfYuGyhVd9rwABIX4TJ26hfqFM3Ii8gChKt0EUFo6W\nKlGppBPrvr6ATictuapUQGysmUkdEbkUqzKVwsJCy546AOjr68O7776LWbNmOSwwezLBxMSNror7\nYAiQboYoLBx7Z+vMmeloaSmETpeP+no9VKo8DA4WIj8/wylxkvvgzxZSmlWZzMMPPyxL7IKCgpCV\nlYV33nnHYYHZQ88nPdBl6bBYtxg/yvkREzciGldzs5TQnT0rb/fxAW6+GViyRPtV0rcHHR3liI01\nIz8/A9Omacf/QiIiKyl684Q7EwQBW/ZuweDZQTy4/EFMy5jm7JCIyMVcvAjs2QOcOCFvV6uBBQuA\n7GwgONg5sRGRd1F8j11nZyf+8Y9/4Pz580hISMBtt92GiIgImwNwpNjWWOQvz2dSR0QyPT1AURFw\n9ChgvuzCF0GQypXk5QEu/uONiGhcVs3Y7dmzB3fddRemTZsGrVaL2tpanD59Gn/5y1+wcuVKJeKc\nNHe7K5aci/tgvMOlS8C+fcDnn4+9JWL6dGDFCum069VwrNBkcLyQtRSdsXv88cfxP//zP1i7dq2l\n7U9/+hO+973v4fTp0zYHQUTkSENDUjK3fz8wMCDv0+mAlSuBpCSnhEZEZFdWzdiFh4ejvb0d6ssu\nORweHkZMTAw6OzsdGuD14owdEZlMwJEjQHEx0Nsr74uPlxK6tDSwZAkROZ3iV4q98soreOKJJyxt\nv//978e9aoyIyNnMZulAxN69QEeHvC8qSlpynTmTCR0ReR6rZuyWLl2K0tJSxMbGIjExEY2NjWht\nbcXixYstZVAEQUBxcbHDA7YWZ+xoMrgPxjOIInDmjFS6pLVV3hcaKh2KyMqSigtfL44VmgyOF7KW\nojN2jz76KB599NFrBkRE5CwGg5TQ1dfL2wMCpLIlCxdKdemIiDyZR9ex89B/GhFdpqmXEOuHAAAg\nAElEQVRJSuiqquTtvr5SceGbbwb8/Z0TGxGRtRSvY1dcXIyysjL09fUBAERRhCAI2LRpk81BEBFN\nVnu7tIduouLCOTlAUJBzYiMicharEruNGzfi/fffR3Z2NgICAhwdE5HiuA/GfXR3S8WFy8rGFhee\nO1faRxce7rjnc6zQZHC8kNKsSux27dqFiooKJCQkODoeIqJx9fdLxYVLS8cWF54xQzrpGhPjnNiI\niFyFVYldcnIyfH19HR2L3RUUFCAvL4+/LdE1cYy4rqEh4NAhqbjw4KC8LzUVyM9XtrgwxwpNBscL\nXYter4der7fb91l1eOLw4cN49tlnce+99yIuLk7Wl5OTY7dg7ImHJ4jcm9E4Wlz4q629FgkJUkLH\n4sJE5CkUPTxx5MgRfPzxxygpKRmzx67+ytoCRG6I+2Bch9kMfPmldDDiyottoqOlJdcZM5yX0HGs\n0GRwvJDSrErsnnzySXz00UdYtWqVo+MhIi8likBlJbBnj+OKCxMReTqrlmJTUlJQVVXlVvvsuBRL\n5D4MBmD3bqChQd4eGDhaXFhjdXEmIiL3Y6+8xarEbseOHSgtLcXmzZvH7LFTueivz0zsiFzf+fNS\nceFz5+Ttvr7AkiVScWE/P+fERkSkJEUTu4mSN0EQYDKZbA7CEZjY0WRwH4yy2tqkPXQVFfJ2tVqa\nncvOdt3iwhwrNBkcL2QtRQ9PVFdX2/wgIqLubkCvB44dG1tcOCsLyM11bHFhIiJPN6m7Ys1mM1pa\nWhAXF+eyS7AjOGNH5DpYXJiI6OrslbdYlZ11d3fj/vvvh7+/PxITE+Hv74/7778fXV1dNgdARJ5r\naEi6/uvll4EDB+RJXVoa8OijwN13M6kjIrIXqxK7jRs3oq+vDydOnEB/f7/l/27cuNHR8REpwp5V\nv0lK4D7/XEro9u6V3xiRkADcf7/0JzHReTFeL44VmgyOF1KaVXvs/vnPf6K6uhpBX+1mnjp1Knbs\n2IG0tDSHBkdE7sVsBsrLpX104xUXzs8Hpk/nbRFERI5i1R47nU4HvV4PnU5naTMYDMjJyUFdXZ0j\n47tu3GNHpBxRBE6flooLX7gg7wsLk4oLz53L4sJERBNR9FTsI488glWrVuHHP/4xtFotDAYDXnzx\nRTz66KM2B0BE7q2mRiou3Ngobw8MBHJygAULWFyYiEgpVs3Ymc1m7NixA//7v/+LpqYmJCQkYN26\nddiwYQMEF11T4YwdTQZrTU3eRMWF/fykwsKeWlyYY4Umg+OFrKXojJ1KpcKGDRuwYcMGmx9oD6Wl\npfjBD34AHx8fJCYmYufOndBwSoBIEW1t0pLryZPydo1GKi68bJnrFhcmIvJ0Vs3Ybdy4EevWrcOS\nJUssbQcOHMD777+Pl156yaEBjqe5uRkRERHw8/PDpk2bMH/+fHzzm9+UvYczdkT21dUllS4pK5P2\n1I0YKS6clyftpyMioslT9Eqx6OhoNDY2wu+ydZWBgQEkJyfjwpU7pRW2ZcsWzJs3D9/4xjdk7Uzs\niOyjvx8oKQEOHx5bXHjmTGD5ctahIyKylaIFilUqFcyX3/8Dad+dsxOn2tpafPbZZ7jjjjucGge5\nP9aaGmtwUCpb8vLLwMGD4xcXXrvW+5I6jhWaDI4XUppVid2yZcvw1FNPWZI7k8mELVu2IDs7e9IP\nfOWVV7BgwQL4+/vjoYcekvVdvHgRd955J4KDg6HT6fDOO+9Y+l588UUsX74czz//PIDR2zDefPNN\nqNXqScdBROMzGoFDh6SETq+XFxdOTAQeeMB9iwsTEXk6q5Zi6+vrsWbNGjQ1NUGr1aKurg7x8fH4\n8MMPkZycPKkH/u1vf4NKpcInn3yCS5cu4Y033rD0rVu3DgDw2muvoaysDLfffjsOHDiAmTNnyr7D\naDTia1/7Gn7yk59gxYoV4//DuBRLNClmM3D8uJTMXXlbYEyMdJ8riwsTETmGonvsAGmWrrS0FPX1\n9UhOTsbixYuhsqHa6ObNm9HQ0GBJ7Pr6+hAZGYmKigpkZGQAAB544AEkJCTgueeek332rbfewg9/\n+EPMmTMHAPBv//ZvWLt2rfwfxsSOyCojxYULC6UTr5cLC5P20GVmsrgwEZEjKVruBADUajVuvvlm\n3HzzzTY/FMCY4M+cOQONRmNJ6gBg7ty54+5PWL9+PdavX3/NZzz44IOW2zLCw8ORlZVlqSc08r18\nzdcA8NJLL3nl+EhJyUNhIbB/v/Rap5P6m5v1yMwEvv3tPGg0rhOvK7we+burxMPXrv2a44WvJ3o9\n8neDwQB7snrGzt6unLErKSnB2rVr0dTUZHnP9u3b8fbbb2Pv3r2T/n7O2NFk6PV6y//ovEFjozRD\nV10tb/fzA5YsAW66yTOLC9uDt40Vsg3HC1lL8Rk7e7sy+ODgYHR3d8vaurq6EBISomRY5KW85Qfv\nhQtSceFTp+TtGg2waJFUXDgw0DmxuQtvGStkHxwvpLRrJnaiKKKmpgYpKSl2vd3hyqvIpk6dCqPR\niKqqKsty7PHjxzF79uzrfkZBQQHy8vL4Pyzyel1dgF4PHDs2trjwvHlAbi6LCxMROYNer5ctz9rq\nmkuxoigiKCgIvb29Nh2WGGEymTA8PIytW7eisbER27dvh0ajgVqtxrp16yAIAl599VUcPXoUa9as\nwcGDBzFjxoxJP4dLsTQZnrpc0tc3WlzYZJL3zZolHYyIjnZObO7KU8cKOQbHC1lLsQLFgiBg3rx5\nqKystPlhAPDMM88gMDAQv/jFL7Br1y4EBATgP//zPwEAv/vd73Dp0iXExsbivvvuwx/+8IfrSuqI\nvN3lxYUPHZIndenpwLe/DfzrvzKpIyLyNFYdnnjqqaewa9cuPPjgg0hOTrZklYIgYMOGDUrEOWmc\nsSNvZDRKs3MlJdJVYJdLSgLy84HUVOfERkREE1P08MS+ffug0+lQVFQ0ps9VEzuAe+zIe5jN0v65\noqLxiwvn5wPTprG4MBGRq1F8j5274owdTYa77oMRRemE6549Y4sLh4dLe+jmzGFxYXty17FCzsHx\nQtZSvNxJe3s7/vGPf6C5uRk//elP0djYCFEUkZSUZHMQRDQ5oijVoCssBM6fl/cFBQE5OcD8+VIZ\nEyIi8h5WzdgVFRXhm9/8JhYsWID9+/ejp6cHer0ezz//PD788EMl4pw0ztiRp2psBHbvBmpq5O1+\nfsDSpVJxYV9f58RGRETXR9G7YrOysvCrX/0KK1euREREBDo6OjAwMICUlBS0trbaHIQjMLEjT8Pi\nwkREnkuxcicAUFtbi5UrV8rafHx8YLqyMJaLKSgosOuGRPJcrjxOOjuB//s/4He/kyd1KpW03Pr9\n7wOrVzOpU4orjxVyPRwvdC16vR4FBQV2+z6rduDMmDED//znP3Hrrbda2goLCzFnzhy7BeII9vx/\nFJHS+vqA4mLgiy/GLy68YgUQFeWc2IiIyD5Gqnds3brVLt9n1VLsoUOHsGbNGtx2223405/+hPXr\n1+PDDz/E3//+dyxatMgugdgbl2LJXQ0MAAcPSn+GhuR9GRlS6ZL4eOfERkREjqHoHjsAaGxsxK5d\nu1BbW4uUlBTcd999Ln0ilokduZvhYam48L59Y4sLJydLCZ1O55TQiIjIwRRP7ADAbDajra0NMTEx\nEFy80ikTO5oMZ9aaGikurNcD3d3yvthYKaGbOpXFhV0F65LRZHC8kLUUPTzR0dGB9evXIyAgAFOm\nTIG/vz/uu+8+XLx40eYAHImHJ8iViSJQUQH89rfABx/Ik7rwcOCuu4DvfIc3RhAReTJ7H56wasbu\nG9/4BjQaDZ555hmkpKSgrq4OTz/9NIaGhvD3v//dbsHYE2fsyFVdrbhwcPBocWG12jnxERGR8hRd\nig0LC0NTUxMCL6un0N/fj/j4eHRdeTGli2BiR66ooUEqLmwwyNtZXJiIyLspuhQ7ffp0GK74L1Ft\nbS2mT59ucwBErsDRS/atrcC77wKvvipP6jQaKaH7wQ+kmTomda6P2ztoMjheSGlW1bFbsWIFVq9e\njfvvvx/Jycmoq6vDrl27sH79erz++usQRRGCIGDDhg2OjpfIrXR2Anv3AuXl0hLsCJUKuPFGKZkL\nDXVefERE5FmsWoodOdFz+UnYkWTucnv37rVvdDYQBAFbtmyxFP4jUlJvL1BSMn5x4dmzgeXLWVyY\niIikWV29Xo+tW7cqX+7EnXCPHTnDwABw4ABw6NDY4sI33CDdFsHiwkREdCVF99gReTpb98EMDwP7\n9wMvvyxdA3Z5UpecDDz0EPCtbzGp8wTcM0WTwfFCSrNqjx0Rjc9sBsrKgKKiscWF4+Kk4sI33MA6\ndEREpAwuxRJdB1EETp4E9uwB2tvlfRER0h662bOlQxJERETXYq+8hTN2RJMgisC5c1Jx4aYmeV9w\nMJCbK512ZXFhIiJyBqvnE06dOoVt27bh8ccfBwCcPn0a5eXlDguMSEnW7IOprwfefBPYtUue1Pn7\nS0uu3/8+sHAhkzpPxz1TNBkcL6Q0qxK7P/3pT8jJyUFjYyN27twJAOjp6cGPfvQjhwZH5ApaW4F3\n3gFee01eXNjHB1i2DHjiCSA7m8WFiYjI+azaYzd9+nS8++67yMrKQkREBDo6OjA8PIz4+Hi0tbUp\nEeeksY4d2aqjQyou/OWX4xcXzs0FQkKcFx8REbk/p9Sxi4qKwoULF6BSqWSJXWJiIlpbW20OwhF4\neIKuV2+vVLLkyJGxxYXnzJEORkRGOic2IiLyTIrWsbvxxhvx1ltvydree+89LFq0yOYAiFyBXq/H\nwIB0KOLll4HSUnlSN3Uq8J3vAN/8JpM6b8c9UzQZHC+kNKtOxf7mN7/BqlWr8Nprr6G/vx+rV6/G\nmTNn8Omnnzo6PiKHqqysxSefnINeX44XXzQjOTkd0dFaS39KinQwQqu9ypcQERG5CKvr2PX19eGj\njz5CbW0tUlJScPvttyPEhTcYcSmWrqWioha//GUVzp/Pt9wUYTQWIisrA7NmaVlcmIiIFGOvvIUF\nisnrmEzAsWPAs8/uQXv7Clmfvz8wf/4e/PznK5jQERGRYhQtUFxbW4utW7eirKwMvb29siDOnDlj\ncxBESjCZgPJy6fqvzk6gr290i2lvrx7z5uUhPh6IjFQxqaMJ6fV6nrQnq3G80P9v7+6Do6rvPY5/\nNk8kkAQChkBCQ9AQBJFQAZUHIYiWyYhSGBWxIKAVxqIXdGyrg0AYZChTpHhFpFKrIhLFOzo+0cFe\nw4ZAIUANuZQHCSiPWiIE8ggh2ez945SVk4DshuWc3c37NZORPb+ze37JfIkffud7zrGaV8HugQce\nUM+ePTV//nxFR0df6zkBftXQYNyyJD9fKiv7cXtYWIMiI40+uvPnpZQUY3tUVIM9EwUA4Cp5dSq2\nbdu2KisrU3gQ3VKfU7FoaJB275aczqbPc23dWvrZzw5r584DiokZ4dleW/ulJk9OV48eXC0BALCO\npadiR40apfz8fN15551X3jmA5OTkcIPiFsjtNgJdfr70ww/msZgYadAg6dZbpVatuuqWW6Qvv8zT\n+fNhiopq0IgRhDoAgHUu3KDYX7xasTt58qQGDhyojIwMdezY8cc3Oxz661//6rfJ+BMrdi2P2y3t\n3Wus0DW+b3Z0tDRwoHTbbcafG6MPBt6iVuAL6gXesnTF7tFHH1VUVJR69uyp6Ohoz8EddJgjALjd\n0tdfG4Hu3/82j7VqJd1+uxHqaA8FAIQ6r1bs4uLidPz4ccXHx1sxJ79gxS70ud1SSYnxPNfvvzeP\nRUUZq3ODBhmnXwEACGSWrtj16dNHp06dCqpgh9DldksHDxqB7vhx81hkpNE/N2iQ1KaNPfMDAMAu\nXgW7O++8UyNHjtSUKVOUlJQkSZ5TsY8++ug1nSBwgdstffutEeiOHjWPRURIAwZIgwdLsbG+fzZ9\nMPAWtQJfUC+wmlfBrqCgQMnJyZd8NizBDlY4dMgIdIcPm7dHREj9+klDhkgB/IQ7AAAswSPFENCO\nHDEC3bffmreHh/8Y6OgQAAAEu2veY3fxVa8NDZe/E39YWNhlx4DmOnrUuMr14EHz9rAw6ZZbpDvu\nkNq2tWVqAAAErMumsosvlIiIiLjkV2RkpCWTRMtx/Lj07rvSG2+YQ92FQPfUU9KoUf4Pdf68OSRC\nG7UCX1AvsNplV+x2797t+fM333xjyWTQcn3/vbFC9/XX5u0Oh5SZKQ0dKrVvb8vUAAAIGl712C1e\nvFjPPvtsk+1LlizRM888c00mdrXosQsOJ04YgW7vXvN2h0O6+WZp2DCpQwdbpgYAgGX8lVu8vkFx\nZWVlk+0JCQk6ffr0VU/iWiDYBbbSUuNZrhctDEsyAt1NNxmBLjHRnrkBAGA1S25QnJeXJ7fbLZfL\npby8PNPYwYMHA/6GxTk5OcrKyuIeQgHk5Ekj0P3rX8Z96S7Wq5cR6P5zq0RLca8peItagS+oF1yJ\n0+n0ay/mT67YpaWlyeFw6MiRI0pNTf3xTQ6HkpKS9Pzzz+u+++7z22T8iRW7wHLqlBHodu1qGuhu\nvFHKypI6dbJlapL45QvvUSvwBfUCb1l6KnbixIl65513rvpgViLYBYbTp6WNG6XiYqnxXXMyMoxA\nl5xsy9QAAAgYlga7YESws9eZM0ag27mzaaBLT5eGD5dSUuyZGwAAgcZfuYW7C8Ovysulzz6TXnlF\n+uorc6i7/nrpscekCRMCL9Rxryl4i1qBL6gXWM2rZ8UCV1JZKRUUSP/8p+RymcfS0owVuq5dbZka\nAAAtBqdicVWqqqRNm6QdO6T6evNYaqoR6Lp1s2duAAAEC0tudwJcTnW1tHmztH27VFdnHuvSxQh0\n119v3JcOAABYgx47+KSmRvrf/5Vefln6xz/MoS45WfrVr4w+uhtuCK5QRx8MvEWtwBfUC6zGih28\ncvastGWLtHWrdP68eaxzZ+O2JRkZwRXmAAAINfTY4SedO2eEuS1bpNpa81hSknHKtUcPAh0AAFeD\nHjtcU7W1UmGhcbr13DnzWGKiEeh69iTQAQAQSOixg8n588ZVrkuXSnl55lB33XXS/fdLTzxhPNc1\nlEIdfTDwFrUCX1AvsBordpBkXASxfbsR6mpqzGPt2xs9dL17S2H8UwAAgIBFj10LV1dn3FR40ybj\nnnQXS0iQhg2T+vQh0AEAcC3RY4erUl9vPPKroMB4asTF2rY1Al1mphQebs/8AACA74JuHebEiRMa\nPHiwhg8frpEjR+rUqVN2TymouFzGUyL++7+ldevMoS4+Xho1Svqv/5JuuaVlhTr6YOAtagW+oF5g\ntaBbsUtMTNTmzZslSW+//bZWrlyp5557zuZZBT6XSyoulvLzpfJy81hcnHTHHUaYiwi6igAAABcE\ndY/dK6+8oqioKE2bNq3JGD12hoYGI9Bt3CidPm0ei42VhgyR+vWTIiPtmR8AAGjhPXbFxcWaOnWq\nzpw5o+3bt9s9nYDU0CDt2mWs0JWVmcfatJEGD5YGDCDQAQAQSiztsVu2bJn69++v6OhoTZkyxTRW\nVlamMWPGKDY2VmlpacrNzfWM/elPf9Lw4cP10ksvSZIyMzNVWFioF198UfPnz7fyWwh4FwLd8uXS\nRx+ZQ11MjHTXXdKMGdKgQYS6i9EHA29RK/AF9QKrWbpil5KSotmzZ2v9+vU6e/asaWz69OmKjo5W\naWmpioqKdM899ygzM1O9evXS008/raefflqSVFdXp8j/JJL4+HjVNn7OVQvldkt79khOp/TDD+ax\n6GgjyN12m9SqlS3TAwAAFrClx2727Nk6duyY3nzzTUlSdXW12rdvr927dys9PV2SNGnSJCUnJ2vh\nwoWm927fvl3PPvuswsPDFRkZqTfeeENdunRpcgyHw6FJkyYpLS1NktSuXTv17dtXWVlZkn78V1Sw\nvx42LEv79kmvv+7U6dNSWpoxfuiQU5GR0q9+laXbb5e2bg2M+fKa17zmNa95zWt5/nzo0CFJxgWh\n/ohktgS7F154QcePH/cEu6KiIg0ZMkTV1dWefZYsWSKn06lPPvmkWccI9Ysn3G5p/37J6ZS+/948\nFhUl3X67NHCgcfoVAAAENn/lljA/zMVnjkYPGa2qqlJ8fLxpW1xcnCob3zkXcrulkhJp5UopN9cc\n6qKijKtcZ86U7ryTUOeLi/8FBfwUagW+oF5gNVuuim2cSGNjY1VRUWHaVl5erri4OCunFdDcbumb\nb6QNG6Rjx8xjkZHGFa6DBxtXvAIAgJbJlmDXeMUuIyND9fX1OnDggKfHrri4WL17976q4+Tk5Cgr\nK8tzXjtYffutEeiOHDFvj4j4MdDFxtozt1AR7DUC61Ar8AX1gitxOp1+Xdm1tMfO5XKprq5O8+bN\n0/Hjx7Vy5UpFREQoPDxc48ePl8Ph0F/+8hd99dVXGjVqlLZs2aKePXs261ih0GN3+LAR6P7TV+kR\nHi7172+cdmVREwCA4BeUPXbz589X69attWjRIq1evVoxMTFasGCBJGn58uU6e/asOnbsqAkTJmjF\nihXNDnXB7uhRadUq6c03zaEuPNxYoZsxQ8rOJtT5E30w8Ba1Al9QL7Capadic3JylJOTc8mxhIQE\nffTRR1ZOJ+AcO2Zc5XrggHl7WJj0858bz3Nt186WqQEAgCAQ1M+K/SkOh0Nz584Nih67774zAt3+\n/ebtYWFSZqY0dKiUkGDL1AAAwDV0ocdu3rx5wXsfOysEQ4/dv/9tBLp9+8zbHQ6pTx8j0HXoYMvU\nAACAhYKyxw6G0lJp7VppxQpzqHM4pJtvlqZPl8aMIdRZiT4YeItagS+oF1jNltudtFQ//CDl50u7\ndxv3pbvYTTdJWVlSYqItUwMAACEgpE/FBkqP3cmTRqD717+aBrqePY1Al5Rky9QAAICN6LHzUiD0\n2JWVGYHu//6vaaDr0cMIdJ072zI1AAAQQOixC2CnT0sffywtWyYVF5tDXffu0tSp0vjxhLpAQh8M\nvEWtwBfUC6xGj50flZdLGzdKRUVSQ4N57IYbpOHDpS5d7JkbAAAIfZyK9YOKCqmgQPrqK8nlMo91\n62YEutRUS6YCAACCkL9yS0iv2OXk5FzTiycqK6VNm6R//lOqrzePde1qBLq0tGtyaAAAEAIuXDzh\nL6zYNUNVlbR5s7R9e9NA97OfGYGuWzfjvnQIDk6n0/arpxEcqBX4gnqBt1ixs0FNjRHotm2T6urM\nY126GIHu+usJdAAAwB6s2HmhpkbaskUqLJTOnzePJScbgS49nUAHAACahxU7C5w7ZwS6rVul2lrz\nWKdORqDLyCDQAQCAwMB97C7h3DnjxsJLlxr/vTjUdewojRsnTZtm3GSYUBcauNcUvEWtwBfUC6wW\n0it2vl4VW1tr9M/94x/S2bPmscRE40kRvXoR5gAAgH9wVayXfDlXff68cYXr5s1GP93FOnQwAt1N\nN0lhrG8CAIBrgB47P6irk3bsMO5FV11tHmvfXho2TLr5ZgIdAAAIDi0ystTXG1e4vvyytH69OdS1\nayeNHi1Nny5lZhLqWgr6YOAtagW+oF5gtRa1Yldfbzz2q6DAeGrExdq2lYYOlfr2lcLD7ZkfAADA\n1WgRPXYul1RUZAS68nLzfvHx0h13SD//uRTRomIuAAAIFPTYeeGVV/KUknKDjhzpqjNnzGOxsUag\n69ePQAcAAEJDSHeQvfzyRs2d+z86cOCwZ1ubNtLIkdKMGdJttxHqYKAPBt6iVuAL6gVX4nQ6lZOT\n47fPC+lY06VLjiTp22/zlJraVYMHSwMGSFFR9s4LAABAkud+u/PmzfPL54V0j92wYW5FREi9ejm1\neHEWgQ4AAAQkeuy80K2blJIiJSc3EOoAAEDIC+keu65dJZfrS40YcYPdU0GAow8G3qJW4AvqBVYL\n6RW7jh3zNGJEunr06Gr3VAAAAK65kO6xC9FvDQAAhBh/5ZaQPhULAADQkhDsANEHA+9RK/AF9QKr\nhXSwy8nJ4S8VAAAIWP6+QTE9dgAAADajxw4AAAAmBDtA9MHAe9QKfEG9wGoEOwAAgBBBjx0AAIDN\n6LEDAACACcEOEH0w8B61Al9QL7AawQ4AACBE0GMHAABgM3rsAAAAYEKwA0QfDLxHrcAX1AusRrAD\nAAAIESHdYzd37lxlZWUpKyvL7ukAAAA04XQ65XQ6NW/ePL/02IV0sAvRbw0AAIQYLp4A/Ig+GHiL\nWoEvqBdYjWAHAAAQIjgVCwAAYDNOxQIAAMCEYAeIPhh4j1qBL6gXWI1gBwAAECLosQMAALAZPXYA\nAAAwIdgBog8G3qNW4AvqBVYj2AEAAIQIeuwAAABsRo8dAAAATAh2gOiDgfeoFfiCeoHVCHYAAAAh\nImh77HJzczVjxgyVlpZecpweOwAAECxadI+dy+XSBx98oNTUVLunAgAAEDCCMtjl5ubqwQcflMPh\nsHsqCBH0wcBb1Ap8Qb3AakEX7C6s1o0bN87uqSCE7Ny50+4pIEhQK/AF9QKrWRrsli1bpv79+ys6\nOlpTpkwxjZWVlWnMmDGKjY1VWlqacnNzPWNLlizR8OHDtXjxYr377rus1sHvzpw5Y/cUECSoFfiC\neoHVLA12KSkpmj17th599NEmY9OnT1d0dLRKS0v17rvv6oknntCePXskSc8884w2bNigZ599Vnv2\n7NGqVauUnZ2tkpISzZw508pvwe+sWKb3xzGa+xm+vM+bfa+0z0+Nh8IpkWv9Pfjr85vzOf6uFW/2\nC+V64XeLb/u25FqR+N3i676BXC+WBrsxY8Zo9OjR6tChg2l7dXW1PvzwQ82fP1+tW7fW4MGDNXr0\naL3zzjtNPuMPf/iD1q9fr7/97W/KyMjQ0qVLrZr+NcEvX9/2vVZ/mQ4dOnTFYwcCfvn6tu+1qBdq\nxb/H4HdLYOB3i2/7BnKws+V2Jy+88IKOHz+uN998U5JUVFSkIUOGqLq62rPPkram5CcAAAs5SURB\nVCVL5HQ69cknnzTrGOnp6Tp48KBf5gsAAHAt3XDDDTpw4MBVf06EH+bis8b9cVVVVYqPjzdti4uL\nU2VlZbOP4Y8fDgAAQDCx5arYxouEsbGxqqioMG0rLy9XXFycldMCAAAIarYEu8YrdhkZGaqvrzet\nshUXF6t3795WTw0AACBoWRrsXC6Xzp07p/r6erlcLtXW1srlcqlNmzYaO3as5syZo5qaGm3atEmf\nfvqpJk6caOX0AAAAgpqlwe7CVa+LFi3S6tWrFRMTowULFkiSli9frrNnz6pjx46aMGGCVqxYoZ49\ne1o5PQAAgKBmy1WxdqmoqNBdd92lvXv3qrCwUL169bJ7Sghg27Zt08yZMxUZGamUlBStWrVKERG2\nXG+EAHfixAmNHTtWUVFRioqK0po1a5rc1gloLDc3VzNmzFBpaandU0GAOnTokAYMGKDevXvL4XBo\n7dq1uu66637yPUH3SLGr0bp1a61bt073339/kws4gMZSU1O1YcMG5efnKy0tTR9//LHdU0KASkxM\n1ObNm7VhwwY9/PDDWrlypd1TQoC78HjM1NRUu6eCAJeVlaUNGzYoLy/viqFOamHBLiIiwqsfCiBJ\nnTp1UqtWrSRJkZGRCg8Pt3lGCFRhYT/+Kq2oqFBCQoKNs0EwyM3N5fGY8MrmzZs1dOhQzZo1y6v9\nW1SwA5rj8OHD+vvf/657773X7qkggBUXF+u2227TsmXLNH78eLungwB2YbVu3Lhxdk8FAS45OVkH\nDx7Uxo0bVVpaqg8//PCK7wnKYLds2TL1799f0dHRmjJlimmsrKxMY8aMUWxsrNLS0pSbm3vJz+Bf\nSS3H1dRLRUWFHnnkEb399tus2LUAV1MrmZmZKiws1Isvvqj58+dbOW3YpLn1snr1albrWpjm1kpU\nVJRiYmIkSWPHjlVxcfEVjxWUneApKSmaPXu21q9fr7Nnz5rGpk+frujoaJWWlqqoqEj33HOPMjMz\nm1woQY9dy9Hceqmvr9dDDz2kuXPnqnv37jbNHlZqbq3U1dUpMjJSkhQfH6/a2lo7pg+LNbde9u7d\nq6KiIq1evVolJSWaOXNm0D/3HD+tubVSVVWl2NhYSdLGjRt10003Xflg7iD2wgsvuCdPnux5XVVV\n5Y6KinKXlJR4tj3yyCPu5557zvM6OzvbnZyc7B44cKD7rbfesnS+sJev9bJq1Sp3hw4d3FlZWe6s\nrCz3+++/b/mcYQ9fa6WwsNA9dOhQ9/Dhw92/+MUv3EePHrV8zrBPc/5fdMGAAQMsmSMCg6+1sm7d\nOne/fv3cd9xxh3vSpElul8t1xWME5YrdBe5Gq2779+9XRESE0tPTPdsyMzPldDo9r9etW2fV9BBg\nfK2XiRMncpPsFsrXWrn11luVn59v5RQRQJrz/6ILtm3bdq2nhwDia61kZ2crOzvbp2MEZY/dBY37\nE6qqqhQfH2/aFhcXp8rKSiunhQBFvcBb1Ap8Qb3AW1bUSlAHu8bJNzY2VhUVFaZt5eXliouLs3Ja\nCFDUC7xFrcAX1Au8ZUWtBHWwa5x8MzIyVF9frwMHDni2FRcXq3fv3lZPDQGIeoG3qBX4gnqBt6yo\nlaAMdi6XS+fOnVN9fb1cLpdqa2vlcrnUpk0bjR07VnPmzFFNTY02bdqkTz/9lD6pFo56gbeoFfiC\neoG3LK0Vf13pYaW5c+e6HQ6H6WvevHlut9vtLisrc//yl790t2nTxt21a1d3bm6uzbOF3agXeIta\ngS+oF3jLylpxuN3c0A0AACAUBOWpWAAAADRFsAMAAAgRBDsAAIAQQbADAAAIEQQ7AACAEEGwAwAA\nCBEEOwAAgBBBsAMAAAgRBDsAaGTy5MmaPXu2Xz/ziSee0IsvvujXzwSAxiLsngAABBqHw9HkYd1X\n67XXXvPr5wHApbBiBwCXwNMWAQQjgh2AgLJo0SJ16dJF8fHxuvHGG5WXlydJ2rZtmwYOHKiEhAQl\nJyfrqaeeUl1dned9YWFheu2119S9e3fFx8drzpw5OnjwoAYOHKh27drpoYce8uzvdDrVpUsXLVy4\nUImJierWrZvWrFlz2Tl99tln6tu3rxISEjR48GDt2rXrsvs+/fTTSkpKUtu2bdWnTx/t2bNHkvn0\n7r333qu4uDjPV3h4uFatWiVJ2rdvn+6++2516NBBN954oz744IPLHisrK0tz5szRkCFDFB8fr5Ej\nR+rUqVNe/qQBhCKCHYCA8fXXX+vVV1/Vjh07VFFRoS+++EJpaWmSpIiICL388ss6deqUtmzZoi+/\n/FLLly83vf+LL75QUVGRtm7dqkWLFunxxx9Xbm6ujhw5ol27dik3N9ez74kTJ3Tq1Cl99913evvt\ntzV16lSVlJQ0mVNRUZEee+wxrVy5UmVlZZo2bZruu+8+nT9/vsm+69evV0FBgUpKSlReXq4PPvhA\n7du3l2Q+vfvpp5+qsrJSlZWVWrt2rTp37qwRI0aourpad999tyZMmKAffvhB7733nn7zm99o7969\nl/2Z5ebm6q233lJpaanOnz+vxYsX+/xzBxA6CHYAAkZ4eLhqa2u1e/du1dXVKTU1Vddff70k6ZZb\nbtGtt96qsLAwde3aVVOnTlV+fr7p/b/73e8UGxurXr166eabb1Z2drbS0tIUHx+v7OxsFRUVmfaf\nP3++IiMjNXToUN1zzz16//33PWMXQtjrr7+uadOmacCAAXI4HHrkkUfUqlUrbd26tcn8o6KiVFlZ\nqb1796qhoUE9evRQp06dPOONT+/u379fkydP1tq1a5WSkqLPPvtM3bp106RJkxQWFqa+fftq7Nix\nl121czgcmjJlitLT0xUdHa0HH3xQO3fu9OEnDiDUEOwABIz09HQtXbpUOTk5SkpK0vjx4/X9999L\nMkLQqFGj1LlzZ7Vt21azZs1qctoxKSnJ8+eYmBjT6+joaFVVVXleJyQkKCYmxvO6a9eunmNd7PDh\nw3rppZeUkJDg+Tp27Ngl9x0+fLiefPJJTZ8+XUlJSZo2bZoqKysv+b2Wl5dr9OjRWrBggQYNGuQ5\nVmFhoelYa9as0YkTJy77M7s4OMbExJi+RwAtD8EOQEAZP368CgoKdPjwYTkcDv3+97+XZNwupFev\nXjpw4IDKy8u1YMECNTQ0eP25ja9yPX36tGpqajyvDx8+rOTk5CbvS01N1axZs3T69GnPV1VVlcaN\nG3fJ4zz11FPasWOH9uzZo/379+uPf/xjk30aGhr08MMPa8SIEfr1r39tOtawYcNMx6qsrNSrr77q\n9fcJoGUj2AEIGPv371deXp5qa2vVqlUrRUdHKzw8XJJUVVWluLg4tW7dWvv27fPq9iEXn/q81FWu\nc+fOVV1dnQoKCvT555/rgQce8Ox7Yf/HH39cK1as0LZt2+R2u1VdXa3PP//8kitjO3bsUGFhoerq\n6tS6dWvT/C8+/qxZs1RTU6OlS5ea3j9q1Cjt379fq1evVl1dnerq6rR9+3bt27fPq+8RAAh2AAJG\nbW2tnn/+eSUmJqpz5846efKkFi5cKElavHix1qxZo/j4eE2dOlUPPfSQaRXuUvedazx+8etOnTp5\nrrCdOHGi/vznPysjI6PJvv369dPKlSv15JNPqn379urevbvnCtbGKioqNHXqVLVv315paWm67rrr\n9Nvf/rbJZ7733nueU64XrozNzc1VbGysvvjiC7333ntKSUlR586d9fzzz1/yQg1vvkcALY/DzT/3\nALQwTqdTEydO1NGjR+2eCgD4FSt2AAAAIYJgB6BF4pQlgFDEqVgAAIAQwYodAABAiCDYAQAAhAiC\nHQAAQIgg2AEAAIQIgh0AAECI+H/3Q2KUDc+3ZgAAAABJRU5ErkJggg==\n",
"text": [
""
]
}
],
"prompt_number": 27
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"
\n",
"
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## `range()` vs. `numpy.arange()`"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[[back to top](#sections)]"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from numpy import arange as np_arange\n",
"\n",
"n = 1000000\n",
"\n",
"def loop_range(n):\n",
" for i in range(n):\n",
" pass\n",
" return\n",
"\n",
"def loop_arange(n):\n",
" for i in np_arange(n):\n",
" pass\n",
" return\n",
"\n",
"%timeit(loop_range(n))\n",
"%timeit(loop_arange(n))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"10 loops, best of 3: 50.9 ms per loop\n",
"10 loops, best of 3: 183 ms per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n"
]
}
],
"prompt_number": 36
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"funcs = ['loop_range', 'loop_arange']\n",
"orders_n = [10**n for n in range(1, 6)]\n",
"times_n = {f:[] for f in funcs}\n",
"\n",
"for n in orders_n:\n",
" for f in funcs:\n",
" times_n[f].append(min(timeit.Timer('%s(n)' %f, \n",
" 'from __main__ import %s, n' %f)\n",
" .repeat(repeat=3, number=1000)))"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 38
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import matplotlib.pyplot as plt\n",
"\n",
"labels = [('loop_range', 'in-built range()'), \n",
" ('loop_arange', 'numpy.arange()')]\n",
"\n",
"matplotlib.rcParams.update({'font.size': 12})\n",
"\n",
"fig = plt.figure(figsize=(10,8))\n",
"for lb in labels:\n",
" plt.plot(orders_n, times_n[lb[0]], \n",
" alpha=0.5, label=lb[1], marker='o', lw=3)\n",
"plt.xlabel('sample size n')\n",
"plt.ylabel('time per computation in milliseconds [ms]')\n",
"plt.legend(loc=2)\n",
"plt.grid()\n",
"plt.xscale('log')\n",
"plt.yscale('log')\n",
"plt.title('Performance of explicit for-loops vs. list comprehensions')\n",
"\n",
"max_perf = max( a/r for r,a in zip(times_n['loop_range'],\n",
" times_n['loop_arange']) )\n",
"min_perf = min( a/r for r,a in zip(times_n['loop_range'],\n",
" times_n['loop_arange']) )\n",
"\n",
"ftext = 'the in-built range() is {:.2f}x to '\\\n",
" '{:.2f}x faster than numpy.arange()'\\\n",
" .format(min_perf, max_perf)\n",
"plt.figtext(.14,.75, ftext, fontsize=11, ha='left')\n",
"\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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zz6usI2nY6L5kRBrUXsjHRiN2Fbx7J36XFBfXfleVlIjftrBQ+jQZY5Uuh1ZW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\nAAAAAElFTkSuQmCC\n",
"text": [
""
]
}
],
"prompt_number": 40
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"
\n",
"
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## `statistics.mean()` vs. `numpy.mean()`"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[[back to top](#sections)]"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# The statistics module has been added to\n",
"# the standard library in Python 3.4\n",
"\n",
"import timeit\n",
"import statistics as stats\n",
"import numpy as np\n",
"\n",
"def calc_mean(samples):\n",
" return sum(samples)/len(samples)\n",
"\n",
"def np_mean(samples):\n",
" return np.mean(samples)\n",
"\n",
"def np_mean_ary(np_array):\n",
" return np.mean(np_array)\n",
"\n",
"def st_mean(samples):\n",
" return stats.mean(samples)\n",
"\n",
"n = 1000000\n",
"samples = list(range(n))\n",
"samples_array = np.arange(n)\n",
"\n",
"assert(st_mean(samples) == np_mean(samples)\n",
" == calc_mean(samples) == np_mean_ary(samples_array))\n",
"\n",
"%timeit(calc_mean(samples))\n",
"%timeit(np_mean(samples))\n",
"%timeit(np_mean_ary(samples_array))\n",
"%timeit(st_mean(samples))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"100 loops, best of 3: 26.2 ms per loop\n",
"1 loops, best of 3: 144 ms per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"100 loops, best of 3: 3.21 ms per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"1 loops, best of 3: 1.12 s per loop"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n"
]
}
],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"funcs = ['st_mean', 'np_mean', 'calc_mean', 'np_mean_ary']\n",
"orders_n = [10**n for n in range(1, 6)]\n",
"times_n = {f:[] for f in funcs}\n",
"\n",
"for n in orders_n:\n",
" samples = list(range(n))\n",
" for f in funcs:\n",
" if f == 'np_mean_ary':\n",
" samples = np.arange(n)\n",
" times_n[f].append(min(timeit.Timer('%s(samples)' %f, \n",
" 'from __main__ import %s, samples' %f)\n",
" .repeat(repeat=3, number=1000)))"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%pylab inline"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 6
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import matplotlib.pyplot as plt\n",
"\n",
"labels = [('st_mean', 'statistics.mean()'), \n",
" ('np_mean', 'numpy.mean() on list'),\n",
" ('np_mean_ary', 'numpy.mean() on array'),\n",
" ('calc_mean', 'sum(samples)/len(samples)')\n",
" ]\n",
"\n",
"matplotlib.rcParams.update({'font.size': 12})\n",
"\n",
"fig = plt.figure(figsize=(10,8))\n",
"for lb in labels:\n",
" plt.plot(orders_n, times_n[lb[0]], \n",
" alpha=0.5, label=lb[1], marker='o', lw=3)\n",
"plt.xlabel('sample size n')\n",
"plt.ylabel('time per computation in milliseconds [ms]')\n",
"plt.legend(loc=2)\n",
"plt.grid()\n",
"plt.xscale('log')\n",
"plt.yscale('log')\n",
"plt.title('Performance of different approaches for calculating sample means')\n",
"\n",
"max_perf = max( s/c for s,c in zip(times_n['st_mean'],\n",
" times_n['np_mean_ary']) )\n",
"min_perf = min( s/c for s,c in zip(times_n['st_mean'],\n",
" times_n['np_mean_ary']) )\n",
"\n",
"ftext = 'using numpy.mean() on np.arrays is {:.2f}x to '\\\n",
" '{:.2f}x faster than statistics.mean() on lists'\\\n",
" .format(min_perf, max_perf)\n",
"plt.figtext(.14,.15, ftext, fontsize=11, ha='left')\n",
"\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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qSftpTFv70AYa29jc9wIA1saLFy/iyJEjnLS0tbXx6tUrtn3I4rsDAFavXo158+Zh5MiR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\nXuIfaui5S+SyaUwAAAAASUVORK5CYII=\n",
"text": [
""
]
}
],
"prompt_number": 7
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"
\n",
"
\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Cython vs regular (C)Python"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[[back to top](#sections)]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here, we implement a linear regression via least squares fitting (with vertical offsets) by solving to fit *n* points $(x_i, y_i)$ with $i=1,2,...n,$ via linear equation of the form \n",
"$f(x) = a\\cdot x + b$. \n",
"\n",
"Therefore we calculate the following parameters as follows:\n",
"\n",
"$a = \\frac{S_{x,y}}{\\sigma_{x}^{2}}\\quad$ (slope)\n",
"\n",
"$b = \\bar{y} - a\\bar{x}\\quad$ (y-axis intercept)\n",
"\n",
"where \n",
"\n",
"\n",
"$S_{xy} = \\sum_{i=1}^{n} (x_i - \\bar{x})(y_i - \\bar{y})\\quad$ (covariance)\n",
"\n",
"\n",
"$\\sigma{_x}^{2} = \\sum_{i=1}^{n} (x_i - \\bar{x})^2\\quad$ (variance)\n",
"\n",
"I have described the approach in more detail in this [IPython notebook](http://sebastianraschka.com/IPython_htmls/cython_least_squares.html)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"
\n",
"
\n",
"**First, the implementation in Python (CPython)**:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def py_lstsqr(x, y):\n",
" \"\"\" Computes the least-squares solution to a linear matrix equation. \"\"\"\n",
"\n",
" x_avg = sum(x)/len(x)\n",
" y_avg = sum(y)/len(y)\n",
" var_x = 0\n",
" cov_xy = 0\n",
" for x_i, y_i in zip(x,y):\n",
" temp = (x_i - x_avg)\n",
" var_x += temp**2\n",
" cov_xy += temp*(y_i - y_avg)\n",
" slope = cov_xy / var_x\n",
" y_interc = y_avg - slope*x_avg\n",
" return (slope, y_interc)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"
\n",
"
\n",
"**And now, adding type definitions and compiling the code via Cython**:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%load_ext cythonmagic"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%cython\n",
"\n",
"def cy_lstsqr(x, y):\n",
" \"\"\" Computes the least-squares solution to a linear matrix equation. \"\"\"\n",
" cdef double x_avg, y_avg, temp, var_x, cov_xy, slope, y_interc, x_i, y_i\n",
" x_avg = sum(x)/len(x)\n",
" y_avg = sum(y)/len(y)\n",
" var_x = 0\n",
" cov_xy = 0\n",
" for x_i, y_i in zip(x,y):\n",
" temp = (x_i - x_avg)\n",
" var_x += temp**2\n",
" cov_xy += temp*(y_i - y_avg)\n",
" slope = cov_xy / var_x\n",
" y_interc = y_avg - slope*x_avg\n",
" return (slope, y_interc)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 3
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"
\n",
"
\n",
"**A small visual proof of concept that our least squares fit works as intended:**"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%pylab inline"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 5
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from matplotlib import pyplot as plt\n",
"\n",
"import timeit\n",
"import random\n",
"random.seed(12345)\n",
"\n",
"n = 500\n",
"x = [x_i*random.randrange(8,12)/10 for x_i in range(n)]\n",
"y = [y_i*random.randrange(10,14)/10 for y_i in range(n)]\n",
"\n",
"slope, intercept = cy_lstsqr(x, y)\n",
"\n",
"line_x = [round(min(x)) - 1, round(max(x)) + 1]\n",
"line_y = [slope*x_i + intercept for x_i in line_x]\n",
"\n",
"plt.figure(figsize=(8,8))\n",
"plt.scatter(x,y)\n",
"plt.plot(line_x, line_y, color='red', lw='2')\n",
"\n",
"plt.ylabel('y')\n",
"plt.xlabel('x')\n",
"plt.title('Linear regression via least squares fit')\n",
"\n",
"ftext = 'y = ax + b = {:.3f} + {:.3f}x'\\\n",
" .format(slope, intercept)\n",
"plt.figtext(.15,.8, ftext, fontsize=11, ha='left')\n",
"\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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oUKGC+RgfH5/nnp1MUSxFp9OphPU1l5HTTCuKJVg8EUhMTGTt2rWpPvf8PIPEHlWwYEHO\nnj2boTEqiqIoSlbl7+/PmTNnXvh4i98aWL9+PUFBQXh4eAApVwHuj4qNiIggV65cAHh7ez/0DPbl\ny5fx9vZ+rLyzZ8+aH13Kjj8jRoyweAyq7ar9qv2q/artL+8nvV9+LZ4I/Pjjj+bbAgANGzZk/vz5\nAMyfP5/GjRubX1+yZAmJiYmcP3+e06dPU758eYvErCiKoiivC4veGoiLi2PTpk18++235tcGDhxI\nixYtmDNnjvnxQUh5BrxFixbmKUZnzpypBukoiqIoSjpZNBFwcHB4aJ5tSJlyc9OmTanuP3jw4FSn\njlX+r2rVqpYOwWKyc9tBtV+1v6qlQ7CY7Nz2jGCxCYUyi0aj4TVrkqIoiqI8UXr7PYuPEVAURVEU\nxXJUIqAoiqIo2ZhKBBRFURQlG1OJgKIoiqJkYyoRUBRFUZRsTCUCiqIoipKNqURAURRFUbIxlQgo\niqIoSjamEgFFURRFycZUIqAoiqIo2ZhKBBRFURQlG1OJgKIoiqJkYyoRUBRFUZRsTCUCiqIoipKN\nqURAURRFUbIxlQgoiqIoSjamEgFFURRFycZUIqAoiqIo2ZhKBBRFURQlG1OJgKIoiqJkYyoRUBRF\nUZRsTCUCiqIor6DIyEgqV66DnZ0juXMXZOPGjS+1/vj4ePbs2cORI0cQkZdad5YSHw/Ll1s6inRR\niYCiKMorqF69luzeXYLExHCuXp1FkyZtOXPmzEup++LFixQqVJqwsO5UqNCAOnXeJjk5+aXUnaXc\nvQtNmkCLFvDll5aO5oWpREBRFOUVk5CQwMGDf5GcPB5wAWqg0dRmx44dmV53YmIilSvXIzy8Hbdu\nHcRgOMWOHbf45ptZmV43gIhw69YtTCbTS6nviRISoGlT+O03cHeHatUsG086qERAURTlFWNra4ut\nrT1w/wqAEY3mJDlz5sz0ut99tyeXLkUCze5Hg8FQjyNHTmZ63SdPniR//hLkzOmFo6Mby5evyPQ6\nU5WQAG+/DevXQ86csGULlChhmVgygEoEFEVRXjEajYapU6eg19fAxqY3Dg7VKV3albp162ZqvSaT\niaVLFwFvAosBAQzY2i4nKChzO0IRISysCf/914Pk5Dji47fSsWMPTp06lan1PiYxEZo3h19/BTc3\n2LwZSpZ8uTFkMI28ZqM8NBpN9h64oihKtvHXX3/x119/4eXlRcuWLbGxscnU+kQEnc6ZhIStwLtA\nPHCD4OCS7N69FSsrq0yrOzY2lly5fElKum1+zcmpBbNmNaF169aZVi9ATEwM169fJ1/u3Ni1bw+r\nV4Ora8qVgDJlMrXu55Hefk8lAoqiKMpzGzp0FF98sRKDoSfW1n/g6rqDkycP4erqmqn1Go1GHB3d\nuHt3B1AKMODgEMivv84mJCQk0+qdOnUGAwcOQWedk4VJEdRPvAs5cqRcCShbNtPqTYv09nvWGRiL\noiiK8poxGo1MmPAF69dvx9fXk7Fjh1GgQD5+/XUrPj65GTJkX6YnAQBWVlbMmTOLLl1qYm1dHZPp\nEI0bV6FKlSqZVufBgwcZMmQcxoT9fJswkPr8RKxGi8vvv6PJIklARlBXBBRFUZQn6tbtYxYtOoDB\n0BcrqwO4us7j338PvpSBian5999/2b9/P97e3oSEhKDRaDKlnkWLfuC993qQGF+ZH9DRguXE4kId\nq3h+j43C0dExU+p9EerWwCNUIqAoyuvkwoULLFiwkORkI61atSAgIOCl1W0ymbCzcyA5ORxwA8DB\n4W2++qohHTp0eGlxvGx79uyhevUmJBhGs4hetCKOmzgTxjhOuowmJiYi0xKQF6FuDSiKorymTp06\nRblylYmLa4WIPVOmhLB16zrKlSv3UuqPjY0l5cmABzu9rNMBZpatW7eSnNCK+WylFXHcQkMtcnHc\ncSSrVy7JUklARlCPDyqKomRRY8ZM4s6dDzEap2EyfU5c3FgGDvws0+u9ceMG5cpVxcsrH0ajFdbW\n9YA1WFmNwt5+D/Xq1cv0GCzJw82NeSyhLT9wG0dqM5hTrgbOnj1K9erVLR1ehlOJgKIoShYVE3Mb\nkynvA6/k5ebN20/cP6N06NCDf/4pRVLSTUROo9FcoGjRsTRrdpH9+//E3d0902OwGKORjn/8QWtj\nBHeworFtTf7Rz2bBglnkypXL0tFlCnVrQFEUJYtq06YRW7cOw2AoBtjj4DCY1q3fyfR6d+/eTVLS\nNlK+K+YhKakn9evfZuLE8Zlet0WZTNClC1aLFyN6PX/17k2jXLmYWm00JV/xSYOeRiUCiqIoWVSb\nNq2Iiopm3Lh2GI3JvP/+u/Tp81Gm1+vt7Ut09J9AAcCETvcX+fLVyfR6Lcpkgq5dYd480OvRrFtH\nWEgIYZaO6yVQTw0oiqIoDzlw4ADVqtUF3sBkCicgwJk//liPnZ2dpUPLHCYTdOsG330HOl3K9MGv\n0CJC6vHBR6hEQFEUJf2uXr3Kzp07cXR0pEaNGlhbv6YXkE0m6NEDZs0Ce3v45ReoUcPSUaWJSgQe\noRIBRVEU5bmIQM+e8PXXYGcHa9dCaKilo0qz9PZ76qkBRVEUJfsRgQ8//H8SsHr1K5kEZASVCCiK\noijZiwj06gVffQW2trBqFdSqZemoLEYlAoqiKEr2IQJ9+sD06SlJwM8/Q+3alo7KolQioCiKomQP\nItC/P0ydCjY28NNPULeupaOyOJUIKIqiKK8/ERgwACZPTkkCVqyA+vUtHVWW8Jo+D6IoiqJkd7Gx\nsfTpM4RDB48xxniLekcOgrU1LFsGDRtaOrwsQ10ReI35+flx/PjxTCl748aNBAcHY29vT//+/Z+4\nX2JiIrVr18bDwwMPD4+Htl24cAFra2sCAwPNP9HR0Q/tIyLUrFnzsWPTq23btnh7e6PVajEYDKnu\n8+677z51+6JFiyhVqhQ2NjZ89dVXD207evQob731FoGBgQQEBDBq1Cjzto4dO+Lr62tu87hx4zKu\nYYqiAJCcnEyVKnVYvCiRtw/lod6RgyQDxsWLoXFjS4eXpVg0EYiNjaVZs2YUK1aMgIAA9uzZQ3R0\nNKGhoRQuXJiwsLB7y2CmGDduHIUKFaJo0aJs3LjRgpFb1rx58x7qWJ4kM+dU8Pf3Z86cOU9NAgCs\nrKz45JNP2LRpU6rbXV1dOXjwoPnHzc3toe0zZszAz8/vuZf97NixI9u3b3/mfl27duXQoUNP3L52\n7Vq0Wu1T6w0MDGTp0qW0adPmsf369+9PmzZtOHjwIPv27WPu3Ln8/fffQMr7MmjQIHObBw0a9Fxt\nUxTl+Z04cYJz564zJMmLIfxIMlZ0svfiaJEilg4ty7FoIvDxxx9Tt25dTpw4weHDhylatCjjx48n\nNDSUU6dOUaNGDcaPT1nk4vjx4yxdupTjx4+zYcMGevTogclkyrBYJk6cyAcffGD+PTIyEi8vL+7e\nvZvusiMjI6levTrBwcGUKFGCAQMGmLd17dqVPn36mPcrUKAAhw8ffmp5aVkLe9GiRQQHB1OoUKHH\nvrWmh7+/P6VLl37mbGNWVlZUr14dFxeXNNdx+vRpli5dysCBA587odFoNM91fqpWrfrEqwxRUVGM\nHj2aKVOmPLXe4sWLU6xYMbRa7WP7+fj4mJPYO3fuoNFoHlq5LLVy4+PjKV26NGvWrAFgy5YtFCtW\njLi4uGe2R1GUh1lZWTEo8QbD+RQjWtqykJ+tdFhZWVk6tCzHYmMEbt68yY4dO5g/f35KINbWuLi4\nsGbNGvM3ug4dOlC1alXGjx/P6tWrad26NTY2Nvj5+VGwYEH27t1LhQoVMiSeLl26EBAQwIQJE9Dr\n9cyePZu2bdtib2//2L7NmzfnzJkzj72u0WjYtWvXY/Nx58iRg7Vr1+Lg4EBSUhK1a9fmt99+o1at\nWnz55Ze88cYbrF69mi+//JJPPvmEUqVKPTXWtHzLv379On///TfXrl0jMDCQKlWqPLaK1okTJ2jT\npk2qx4eFhfH5558/d31pdevWLYKCgtBoNLRq1Yp+/foBYDKZ6Nq1KzNnzkzz1KbpvQrSs2dPRo8e\njbOz8wuXMX78eKpUqcLMmTOJiYlh0qRJ5M37/+VkJ0+ezKxZs/D392fcuHEULVoUnU7HsmXLCAsL\nw8vLiy5duvDzzz/j4OCQrvYoSnZUdMUKhiTdxAi0oydr7FdRpmQBAgICLB1almOxROD8+fN4eHjQ\nqVMn/vnnH4KCgpg6dSqRkZF4enoC4OnpSWRkJABXrlx5qNP38fEhPDw8w+JxdXWlYcOGLFiwgC5d\nuvDdd9+xZcuWVPddvnx5mspOTk6mX79+7Nq1CxHh6tWrHDp0iFq1amFvb8+yZcsICgqibt26dO/e\nPdUy1q1bx5AhQwCIjo4mMTGRVatWAfDhhx/y7rvvpnpc586dAciVKxf16tVj27ZtjyUCxYoV4+DB\ng2lqU0bIkycP4eHhuLu7c/36dRo2bIirqyudO3dm0qRJhISEUKpUKS5cuPDUcsaMGcPKlSsB+O+/\n//jzzz9xdHQEYP78+c9MrB60bNky7OzsqFOnjjmheJHEokOHDrz77rv07duXq1evUrVqVYKCgihf\nvjyfffYZefLkAWDhwoXUrl2bc+fOodVqKVKkCKNHj6ZixYpMmzaN0qVLp7luRcn2PvsM7YgRiFbL\n8roNiUq4wkeBxRgxYhBarRoa9yiLJQLJyckcOHCAGTNmUK5cOXr16mW+DXDfsy7zPmnbyJEjzf+u\nWrUqVatWfa6YPvzwQ9q2bYuHhwcBAQH4+/unul+zZs04e/Zsqtt27dr12FWEKVOmEBsby969e7G1\ntaVbt24P3XI4duwYLi4uXL16FaPRmOqlq7p161L33vOu8+fP5+LFiwwfPvyZbXqwExORVM/Z8ePH\nadu2barHh4aGMmHChGfW8yJsbW1xd3cHwMPDg7Zt27Jz5046d+7Mjh07OHz4MAsWLCA5OZmYmBjz\nbZP7nfx9w4YNY9iwYQB06tSJTp06UaVKlReKafv27WzZsoX8+fObXytRogTr16+naNGiTzzu0fO6\ndetW5s2bB4CXlxfVq1fnjz/+oHz58uYkAKB9+/b07t2b8PBwfH19Adi/fz+enp5cunTphdqgZE1x\ncXEcP34cV1dXChYsaOlw0uXvv/+mR48BREZeIyysGtOnf45Op7N0WCnGj4ehQ0GjQTNvHq3at6eV\npWPKYNu2bWPbtm0ZV6BYSEREhPj5+Zl/37Fjh9StW1eKFi0qERERIiJy5coVKVKkiIiIjBs3TsaN\nG2fev1atWrJ79+7Hyk1vk6pVqya+vr6ydu3adJXzoL59+0rv3r1FROTy5cvi6ekpo0aNEhGRc+fO\nSd68eeXMmTPSoUMHGThw4DPLmzt3rowcOfKZ++XLl0+6du0qIiLXrl0Tb29vOXr0aDpa8rgRI0ZI\nv379nrnf+fPnxd3d/aHXrl27JomJiSIiEhcXJzVr1pTp06c/duyFCxceO/ZJOnbsKNu2bXuufU0m\nk2g0Grlz584T99FoNBIXF/fUcjp06CAzZsx46LVy5crJggULRETk1q1bUqJECdmwYYOIpHwG7tuw\nYYN4enqK0WgUEZGVK1dK2bJlJTo6WooXLy7r169/rrYoWdvRo0clZ05fcXYuIzpdLunS5QMxmUyW\nDuuFXLhwQRwdPQTmCRwUe/sm0rRpO4vFYzKZZNmyZTJq1Cg53K6dCIhoNCLz5lksppctvf2exRIB\nEZHKlSvLyZMnRSSlQ+nfv7/0799fxo8fLyIpnf+AAQNEROTYsWNSunRpSUhIkHPnzkmBAgVS/R8p\nvSdk0aJFDyUoGeHixYtSvnx5KVGihNSuXVvatm0ro0aNksTERClfvrz8+OOPIpLSGQYEBJg7jCeZ\nN2+eOZF4Gj8/Pxk8eLAEBQVJwYIF5auvvsqQ9oikJG4+Pj7i7OwsTk5O4uPjIxs3bhQRkW+++UaG\nDx9u3jc4OFhy584t1tbW4uPjY05OfvrpJylRooSULl1aAgICZMCAAam+p+fPnxcPD4/niqtjx46y\nffv2Z+7XpEkT8fHxEa1WK97e3lK7du1U99NqtQ8lAmXKlDEnqj/88IP4+PiIg4ODuLq6io+Pj5w4\ncUJEUv4BlgPUAAAgAElEQVTwV6lSxdy2MWPGmMuoWbOmlCxZUkqXLi1VqlSRPXv2mNvp6+srp0+f\nNpeRN29eCQ8Pf662K1lXsWLlBL6VlFltboqDQ0lZtWqVpcN6Id98843odB3vtUUEbom1tZ05mX2Z\nTCaTtG//njg4lJW+1BABMYLI99+/9Fgs6ZVOBA4dOiTBwcFSqlQpadKkicTGxkpUVJTUqFFDChUq\nJKGhoRITE2Pe/7PPPhN/f38pUqTIEzvL9J6Qzp07y6RJk9JVhqIoyoPs7BwFYsydp7V1v4eucL5K\n5s+fLw4O9R5IBM6Jvb2zRa5wnDx5UnQ6L+nFuPvBSDdrRzl//vxLj8WS0tvvae4V8tp40Wfnr1y5\nQvXq1cmdOzfr169P9WkBRVGUF1G8+BucOPEuIt2Amzg4VOKHH8bSMI2z20VERJCYmIivr+8TB70d\nPXqUWbPmYjQa6dy5PUFBQRnQgv+7ffs2JUu+QUREBRITS6PXz2To0C4MGvT0OUUyw969e1lRpSkT\nElIGjr/HLJY4TeePPxZRpkyZlx6PpaR3zhiVCCiKomSyEydOEBJSh4QEJxITr9KpU3u++mryc88J\nkpycTKtW7/LLL7+g1dpRrFghNm9eQ44cOR7a759//qFSpZrExfUEbNHrv+C3337mrbfeytD2xMTE\n8MUX07ly5Tp16lTj7bffztDyn1fC5MnY3XvkuDsTmK2xw9NzGufPH8tWX+ZUIvAIlQgoipIVxcfH\n8++//+Lm5ka+fPnSdOyECZMYMeJX7t79FbDH1rY7zZoJixd/+9B+LVt2YtmyEkDfe698T/Xqa9i8\neVWGtCFLmTkTevYEYGye/HwWe5PChQNYtux7ChUqZOHgXq709nvqgUpFUZSXQKfTERgYmOYkYPv2\n7QwZMo67d9sCekBLYuK77Nv3+BTZd+7EA+4PvOJBXFx8esJ+ovDwcDp06E6NGk2YNGlqhs70+kyz\nZpmTAKZPZ3D4OeLiojh4cEe2SwIyglp9UFEUJYsyGAw0bNiC5OQGwG/Au4AWK6t1FCny+DwnnTu3\nZNu23hgM3qTcGuhPly6fZHhc0dHRlC1biaioNhiNNdm9+wvOnbvIzJlfZHhdj/n2W7g/8drUqfDh\nh5lf52tO3RpQFEXJok6ePElwcD3u3DkM1AVuAFrc3W9y8OBOfHx8Hjtm/vyFjB37JUajkV69utCz\nZ/c0rU/yPBYuXMj7768kLu7ne69EYW3tTUKCIXNn7pszB7p0Sfn3lCnQu3eGFv/333+zfft23N3d\nadWq1WPTxWdVaozAI1QioCjK6+LWrVt4eubl7t2dQBHgV2xtO/D33zsemyr8ZVqwYAE9eqwhLm7F\nvVdisbb24u7duMxb1GfuXOjcOeUhwYkT4d4gwYzy449L6Ny5F8nJrbC1PUqRIons2rUJW1vbDK0n\nM6gxAoqiKK8pZ2dnvv12JjpdVVxc6qDTvcfo0cMtmgQA1KlTB3v7PVhZfQqsQ69vSrt2nTIvCZg/\n//9JwOefZ3gSAPD++72Jj/+FpKSpxMX9zsmT1mleV+ZVpcYIKIqiZGHt2rWhcuVKnDhxggIFClC4\ncOFMq+vu3btERUXh5eX11E7dw8ODffv+oF+/EYSH76BOnZoMGZLxYxEAWLQIOnVKSQLGjoVPMq4e\nEWH27DnMnLmAmzdvAPdXJtSQnFyUqKioDKsrK1O3BhRFURQWLfqBrl3fR6PR4ehox2+/rSIwMNCy\nQf3wA7RvDyYTfPop3FuBNaN888239O07GYNhGjAcKAlMBo6g0zVl9+5NaVq91FLUGIFHqERAURQl\nbU6fPk2ZMpUwGLYAJYAl5Mo1kIiIc5ZbtnfJEmjbNiUJGDUKnmO11bQqVaoyR44MB0KBaKAmWu1x\ncub0YvbsqTRu3DjD68wMaoyAoiiKki6HDx/G2roiKUkAQCtu3rzNjRs3XnosIgLLlkG7dilJwPDh\nmZIEANjY2AB37v3mhkbTnI4dO3Pt2oVXJgnICCoRUBRFyeby5ctHcvJBIObeKwfRao24urq+tBj2\n7dtHvnwBtLSyJrllSzAaYehQGDky0+ocObI3Ol0PYCYwHr1+Ch9/3C3T6suq1K0BRVEUhd69BzF7\n9iJsbEqTlLSH+fO/oVmzl7OGQExMDH5+xahxqx1LmYYNyUzTu9A96ip2mbxmwObNm5k9ezH29rb0\n7dvjlRgT8Cg1RuARKhFQFOV1s2HDBgYNGo/BYKBjxxYMGNAnXffuTSYTkyZNZdmyX3Fzc+Hzz4cR\nGBjIwYMH+e+//yhVqhT58+fPwBY83R9//MGsOu8xz3AWG5IZzwDGOv7Enr1rKFas2EuL41WV3n5P\nPT6oKIqShe3atYumTTsQH/814MGnn/bCaDQydOiAFy5zyJBRTJ++HoNhDHCOv/4K4+DBvwgMDLTI\nkwL5jxxhruEkNsBE+jGI3tglfUPOnDlfeizZkRojoCiKkkXdvn2bDz7oR3x8b6ApUBmDYSZz5vyY\nrnJnzZqDwbAIqAW8T0JCG1asWPGswzLHL7/g27s3tsB0azeG2RpwcKhEv359yJUrl2ViymbUFQFF\nUZQsKDExkUqVwjh27A7w4MQ2sdjbp28OfK3WCkgw/67RJGTerIBPs24dvP02JCUhH31EwbAwPj9z\nhpIl36Z69erpKvr27dusXbuWu3fvUqtWLby9vTMo6NePSgQURVGyoNmzZ3Pq1B1MplVAJcAG8ESn\nm8CYMdNeqMxbt26h0+kYMKAXI0e2wGAYjFZ7Dr1+NW3a7MvI8J9twwZo0gQSE+HDD9FMnUrdDFoc\nKWV1xLeIivLDZHLF2nowO3ZsfCUHAr4M6taAoijKc1i+fAWVK9enevXGbN68OVPr+v77efTtO4KE\nBD3gD+wEDGi1I5g/fyrNmjVLU3mRkZGUKVOJnDlz4+Dggkaj4euvh1Cv3jratYvgwIHUVzLMNBs3\nQuPGKUlAz54wbRpk4AqJEyd+QUREJe7cWYfBsJhbt0bRo8eLj6l47clr5jVskqIoFvbjj0tEr88r\nsExgvuj1uWT79u2ZUpfJZBJ7e2eBvQIFBEYK/Ck2Nm2lYsVQMZlMaS6zSpW6Ym39iYBJ4KLo9X6y\nefPmTIj+/1auXClVqjSQ6tUby++///7/Db//LmJvLwIi778v8gLteZa2bbsKzJSUBQpEYK/4+wdm\neD1ZRXr7PXVFQFEU5RmmTPkOg2E60Bx4B4NhODNmzM2UupKSkkhMNACBwFbgOBpNa8qXv8qGDT+h\neYFvzvv2/UVycn9AA+QlIaEFu3fvztjAH/DTTytp1+4j/vijLVu2NKFhw7Zs3boVtmyBBg3g7l14\n7z2YMSNDrwTcV6tWFfT6mUA4EIe9/VhCQ0MyvJ7XhUoEFEVRniGl8zU+8EoyWm3Gd2AAtra2lC37\nFtbWA4EcQHd0uni+/34mTk5OL1Smp6cPKbcXAIzY2+/J1MFzkyd/i8EwFWgJvEN8/Gg2DxsL9eun\nJAFdusDXX0MmrWPQrl1b+vRpjq1tYays3KhTx4EpU8ZmSl2vAzWhkKIoyjOsWrWKNm16Eh8/FjCg\n0w1ny5a1VKhQIVPqi4yMpFmzjuzZ8wdubl7MnTuDOnXqvHB5O3bsoE6dpmi1IYico2xZLzZvXoO1\ndeaMF69UqS5//dURaAFAFXrzm9WX2BuNKUsKf/ddpiUBDxIRjEZjprUzq1AzCz5CJQKKomSGdevW\nMWPGfGxsrBkwoCcVK1a0dEhpcunSJf766y9y5MhBzZo1M/xxQRHh7t276HQ61q5dS8uW3YiPH8tb\nHGU9k3EE6NABvv/+pSQB2YlKBB6hEgFFUTLClStXiIiIoFChQjg7O1s6nCxt165dNGrUmqioK7i7\n52H16iXExMSwadREPv17BzpjMrRvD3PngiXmK3jNqWWIFUVRMti4cZPw9y9B9eqd8fUtzM6dO599\n0EtiMBiIjY1N83GnTp1i0qRJzJgxI0OXF7516xa1azfh+vXpmEwJXLs2jdq1m1DFxobJx/alJAFt\n277SSYDJZGLq1BlUq9aIVq3e5dy5c5YOKUOpKwKKoigPOHDgAJUrN8Rg2AvkAX7F1fU9oqIuv9CI\n/YwiIvTo0YfvvpuFRmNFhQpv8csvS5/rasXu3bupWbMBiYmtsLKKwdn5T/75ZzdeXl7piun48ePU\nqFGfq1c1wFnz69X1hdioicAqLg5at4YFC+AVvk//ySdD+eqr3zAYBqLVHsfZ+WuOH99P7ty5LR0a\noK4IKIqiZKgTJ05gZfUWKUkAQD3u3LnFzZs3LRkWc+Z8z4IFO0lOvkJSUgx793rywQf9n3mcwWCg\nU6ePiIubTFLSl9y9u4jo6MZMnDg1XfEkJydTvXp9rl7tDtwErgFQjvWsNJxNSQJatnzlkwCAr76a\nicGwEngbk2kYd+/WZOXKlZYOK8OoREBRFOUBRYoUwWj8E7h675XfcHBwxMXFxZJhsW3bHgyGTqQ8\nUmhNQsIH/Pnn3qcec+3aNYoXL8fJkxeBIubXk5MLc+1adLriCQ8P5/btROAToBdQjiBqsJF6uCDQ\nvDksWvTKJwHAvW/bD14Ner26zterNYqiKOkUHBzMgAEfYG9fHGfnIJyc3mH16qUWvS0AULCgL3Z2\nO4CUS8Ba7Q78/HzZvn07jRq1pWHDNg9NfWwwGHjzzTAuXKiOSFdgCHAZOIpeP4UmTWqnKx43NzeS\nk28CF4ChBDKQ39lKDiRlIaHFi1+LJACgW7du6PXNgLVotZ9jZ/cbTZo0sXRYGUaNEVAURUnFpUuX\niIiIoHDhwuTIkcMiMURHR/PBB5+wf/9hChfOz5kzZwkPtwZcsbU9yrRp4+natTfx8WMAK3S6oaxa\ntYCwsDAaN27DmjW7EfkSCAP6AguxthYmTfqUjz/+IM3xJCQksHnzZuLj4wkJCeGHH5bxySdjKGUs\nw4bkjbhhSllDYNkysLHJ2JNhQSaTicmTp7Fq1e94eubk88+HU6hQIUuHZaYeH3yESgQURUkLEeG7\n775n5crf8PBwZfToQfj5+Vk6LIxGI2XKVOLUqSASE9thbb0ab+81TJ8+HhGhcuXKvPNOT379tTrQ\n9d5RC6lW7Sc2bVqJra0Oo/EjUgbxLQFM2Ng04ZNPKvDppyPSHE9cXBwVKtTgwgXQaNyxtj5Iq1bN\n+HvOYtYn3iQnyRz1L0SJ40fB1jbDzoPybOnt916P6zaKoigvaPTocUyYsOTeiPCT/PJLJY4d+9vi\nI8LPnj3LuXMRJCZ+CWhJTq5AdPQGcuXKZZ7R0GQykbI88X02GI0mNBoNNjb2GI2dSLkl4AkkEhBQ\nmuHDB71QPF98MY3Tp/ORkLAE0KDRfMnOr4ewGRtyksxawmgXfoCDly9ToECBdLVdebnUGAFFUbK1\nKVOmYzD8BLTBZBqFwRDG8uXLLR0Wtra2iCQASfdeMSFiQKPRMGbMOOrUaYFOBzrdYOBHYBn29n3x\n9XXhiy++oH//vuj1jYBK2NjUJF++vPz550ZsX/Db+pkzl0hIeIv7g+YCJDebuIM70fxKXZqxBo1d\nfiIjI9PfeOWlUlcEFEXJ1kwmI/D/zlHEFqPR+OQDHvHvv/9y7NgxChQoQGBgYIbFlS9fPqpWfYtt\n2xoRH98Ce/tfKFkyH2PGTGLLljvEx7+Dnd1veHo6kTfvIm7evMXJk7dZssSDFSsO4+Kyja++Gsne\nvYfIkyeQDz/8DkdHxxeOp1q1N1m+fCoGQxsCuMwW2uOBsJ7SvM1yElmPvfxHQEBAhp0D5SVJ1yLG\nWdBr2CRFUTJRr14DRK9/U2CDaDTTxMnJQy5cuPBcx86a9Z3odB7i7NxI9HpvGTZsTIbGlpiYKOPH\nT5SmTd+RkSM/lfPnz4udnatAvIAImMTJqYwsWLBAbGw8BJbce13E2vpD6d9/UIbFYjKZ5KOP+ktJ\nK1u5eq+SqHLlpEAef9ForMTTM7/s2rUr3XW8LBcvXpQqVepKzpx5pWLFMDl79uxLqzujpbffe+16\nTZUIKIqSFkajUT77bIIEBVWX2rWbyZEjR57ruJiYGLGzcxY4da/zjRSdzlP+/fffTIv10qVLYm/v\nIZBk7vCdnd+QnDnzCBQQ2Gt+HabKu+/2yNgATpwQk6dnSgWhoSIGg4iIJCQkvFBxRqNR4uPjJSoq\nSqpVqy9WVrbi7OwpCxcuzsioH5OQkCB58xYVK6tPBc6IVjtRcuf2l7i4uEytN7Okt99TYwQURcnW\ntFotgwf35++/N7N+/XJKlCjxXMdFRkZiY+MB3H+MLBe2tkW5dOlSpsXq7e1NUFAgdnYdgS3Y2HxC\nUtI5oqJuAa2AgaQ8178fW9tJNG1aN+MqP3kSqlVDExkJNWrAqlWg0wG80LiDAQMGY2fniIODM35+\npfjzTzeMxhhu3VpPt2592bv36ZMlpcepU6eIiRGMxiGAPyZTP+LinDh69Gim1ZmVqURAURQlDUwm\nEx06vEeJEkHcuXMFWHNvy26Sk49RvHjxTKtbo9GwYcNPdOzoTunSo3BzW0VyciVSJhlqDZQC3gSq\n07t3O+rVq5cxFZ8+DdWqwdWrKf9dswb0+hcurnfvfkyYMIvk5EOYTHe5fbsFSUnhgB4IJDGxNdu3\nb8+Y2FPh6OhIUlI0EHfvlbskJ99I1xiKV1oGXZnIMl7DJimKkkH++ecfadq0vdSs2fSFLz83atRM\noITAZYE1Ao5ibZ1D9HpX+eWXXzI44idLSkoSKysbAYPAXAFPgaZiZ1dAOnXqkXH320+fFvH2Trkd\nEBIicudOuoqLj48XKytbgY8fuI0RK2BvHvfg4BAq33//fcbEnwqTySRt2nQWvf4NgbGi178ljRu3\nealjFDJSevs9NaGQoijZwr///ktwcGXi4gYDudHrhzFxYj969Oj23GVcuXIFH5+SiHwH3J9idiVl\nykxl797N2GTgbHoiwt69e4mKiiIoKAhPT8/Htut0ziQkHAbyA4exs2vNJ5+8zahRo546JfLJkyfZ\nv38/Pj4+VK5c+cn7nj0LVavC5ctQuTKsXw8ODulqV2RkJD4+/iQnlwW2AlbAJqAJ9vbtsLI6SeHC\nSezatQk7O7t01fU0JpOJhQsX8s8/xyhevAgdO3bE6hVdJjnd/V66U5Es5jVskqIoGeCTTwaJRjPo\ngW+hOyVv3hJpKmPPnj1ibZ1HYPQD5YyWGjUapDkeo9Eoly5dkqioqFS3NW3aThwc/MXFJUwcHT1k\n586dj+03YcIU0ev9BcaJvX1zKVKkrBjuDeB7kh9/XCp6vYc4ObUQB4dC0r79e6l/Ez57VsTXN6WR\nlSqJ3L6d5jamxmQySd68xe5dVQkWaCHgIOPGjZMvv/xSFi9e/MKDD7Or9PZ7r12vqRIBRVFS06/f\nQIGhD3Tgu8XXt3iayoiOjhadzlUgl0BbgTYCejlw4ECayomMjJTixcuLTucptrZO8v77vR/qjFes\nWCEODmUfeEzwZ/H1LZpqWWvXrpXevfvLhAkT5fYzOuvk5GTR6VwEDt0r9444OBSS7du3P7zj+fMi\nefOmnKiKFUVu3UpT+57l7NmzEhBQXjQarTg5ucuCBQsytPzsRiUCj1CJgKIoqTl69Kg4OLgLfCWw\nUvT6YjJlyrQ0l7Nx40bR693ExsZZ7OwcZOnSpWkuo1att8Xauq+ASSBaHBwCZdGiRebtkyZNElvb\nB++h3xZra7s01/Og3bt3S8GCZQTsHihXxMamgYSE1JS9e/em7HjhgoifX8rGChVEbt5MV71PYzQa\nM63s7CS9/Z56akBRlGyhePHibNu2njp1tlGp0ndMm9aPXr0+THM5oaGhxMREcO7cMW7diqZFixZp\nLuPAgQMkJ3cjZbpeV+LiWrJnzwFiY2P5/fff0el0WFuvBq4AoNV+Q0BAUJrrue/y5cvUrNmAM2cG\nAHmBr+5t+YekpD/Zvr0MISF1+HvlypSnAi5cgPLlYcMGcHZ+4XqfRavN+C5o+/btNGnSniZN2vPH\nH39kePmvIzXFsKIo2UZwcDDr1i1Ldzm2trb4+Pi88PF+fvm5cWMjIoWAZHS6rTg6lsXfvwTJyQUx\nGq+QJ48zFy8WxtraiVy5XPn5519eqK4bN24wcuRIkpIqkDLXQBlSBjr2IWXBorlAc9zic+Ld7h2I\nj4PgYPjtN3BxeeE2WsKWLVto0KA1BsMoADZubM6vvy6latWqlg0si1NPDSiKorxkJ06c4K23wkhO\nLojJFEmJEnk4fPgEBsMwoDuQiF5fi88/f5tGjRqRJ0+eFxrRHh4eTmBgRW7d8iMhIRY4SMr0MZdI\nedJgLtCePISznSAKEglBQfD77+DqmoEtfjlq1WrGxo31gE73XplDrVob2LDB8otIZab09nsWvTXg\n5+dHqVKlCAwMpHz58gBER0cTGhpK4cKFCQsLIzY21rz/uHHjKFSoEEWLFmXjxo2WCltRFCVdihUr\nxtmzR1i+fBAbNnxLUlISBsNdoM69PWwxGKpz+fIVfH19X/ixtlGjxhMd3ZqEhE2AG1ALGIG9fQhW\nVjmAYeRmMVt5g4JEEu3nBxs3vpJJAEBy8sMLSIEdRqPJUuG8MiyaCGg0GrZt28bBgwfN00mOHz+e\n0NBQTp06RY0aNRg/fjwAx48fZ+nSpRw/fpwNGzbQo0ePe2txK4qivHpy5MhBWFgYZcuW5dCh3aTM\nCPgdKbMExmBnt4SgoPStZnjlyg2MxuKk3ALYABQjV675LF8+nWrVKpHXxoqtdKIw4VzI4Yrb/v3g\n5pbepllMr17votcPAJYDy9HpBvDxx52eddgLS0hI4PTp0w99YX0VWXyw4KOXM9asWUOHDh0A6NCh\nA6tWrQJg9erVtG7dGhsbG/z8/ChYsGCmzkWtKIqS2davX0/Pnn1J+VM8GPgF8AHyULNmMZo1a5au\n8hs1qomDw2RS1h+IRa8/QrduXahfvz4b5s3ksMddipDEHX9//M6cfqWTAIAGDRqwePEMKlb8nooV\n5/LjjzOpX79+ptR14MABvL0LUrZsLby88jFt2lfPPiirSvdzC+mQP39+KVOmjAQFBcns2bNFRCRH\njhzm7SaTyfz7Bx988NDjNZ07d5YVK1Y8VqaFm6QoyissPj5e2rXrKk5OucTT018WL/4h0+r69ts5\notfnFZgqGk01AXfRavuITldBypULkaSkpHTXYTKZZOjQUaLXu4qdnZN07fphSrlXr4oEBKQ8Iliy\npMj16xnQouzDZDJJrlx+AkvvPYZ5XvT63HLo0CGLxJPefs+iTw3s3LmT3Llzc/36dUJDQylatOhD\n2zUazVOnyXzStpEjR5r/XbVqVTViVFGU59KjR19WrIjk7t393L59iS5d3sbHx5sqVapkeF1Dh47F\nYFgBlEPkY6yt6xIaeoIWLbrRtm1brK3T9udZRNi3bx+RkZGULVsWb29vNBoNY8YMZ8yY4f/f8dq1\nlNUDjx+H4sVh82Zwd8/Yxr3mbt++TXT0NeD+o6N+aLUhHDlyhNKlS2d6/du2bWPbtm0ZVp5FE4Hc\nuXMD4OHhQZMmTdi7dy+enp5cvXoVLy8vIiIiyJUrF5Cy/OaDy3tevnwZb2/vVMt9MBFQFEV5XmvW\n/Mrdu5tIuTzvw9273Vi37jeqVKnCyZMnmTjxS27fNtChQzPq1n3yEr8iQnR0NC4uLk/s0BMT7wI5\nzb+bTCWoUMGJjh07pjluEaFjx/f56aeNWFkVxWjcx6pVP1KzZs2Hd7x+HWrWhGPHoFixlCTAwyPN\n9T1a97Fjx4iNjaVUqVI4Z+K8AwsWLGLixG8QEfr160bHju9kWl1P4+TkhF7vyK1b24EQIBqR3fj7\nf/RS6n/0C+6oUaPSV2D6L0q8mLi4OLl1b9rKO3fuSMWKFeW3336T/v37y/jx40VEZNy4cTJgwAAR\nETl27JiULl1aEhIS5Ny5c1KgQIFU58e2YJMURXnFFShQWmCDedY9W9v2MmHCBDl9+rQ4OXmIRjNK\n4GvR631l0aLUVy/ct2+fuLp6i5WVo9jaOsqCBYtS3a9nzz6i11cT2CewVPR6dzl8+PALxb1x40Zx\ncCgmcOde7FvE1TWPefudO3ekS+PWclhrLQJyy8dHJCLihep6kNFolJYtO4pe7yMuLm+Im5uPHDly\nJN3lpmbZsuWi1/vde39+E70+vyxZkvZZHTPK77//Lg4O7uLiEiI6nZf07TvYYrGkt9+zWK957tw5\nKV26tJQuXVqKFy8uY8eOFRGRqKgoqVGjhhQqVEhCQ0MlJibGfMxnn30m/v7+UqRIEdmwYUOq5apE\nQFGUF/Xrr7+KTuchVlb9xd6+lfj4FJYbN25IgwZNRKPp/8DUvJukUKGgx46PiooSKysXgRn39jsq\ndnbucvTo0cf2TUpKkn79hkj+/KWlTJkqsnXr1heOe/bs2aLXd3ogPqNoNFaSmJgoIiKdGraUg5oc\nIiD/4iMFdDll//79L1zffUuWLBEHh2CBuHv1ficBAW+ku9zUVK/eWOCHB9q4VKpWbZgpdT2vq1ev\nyqZNm+T48eMWjeOVTQQyi0oEFEVJj/3798unn34m06ZNk+joaGnSpK1YW3sLjHmgE9oj+fKVfOzY\nIUOGCtjeW0MgZV+ttlGmL6qzb98+0elyC5wTENFoZoq/f6mUjVFRclBrJQJykkKSm3Cxtu4r48aN\nS3e9o0ePfmRFx2ui17umu9zU1KvXUuDrB+qaJXXqNM+Uul416e331BTDiqIoDyhbtixly5YFYM+e\nPWzcuJvk5CVAU8Af8ESv70337v+/Py0ijBz5GWPHTiJlQpv9QDAQh8gBfHw+ztSYg4OD+fzzYfTr\nVworKwfc3Jz55Zc1EBMDYWGUMRk5jQ/V2EoEedDZnMfFxT/d9ZYsWRK9fhhxcf0BV7TahRQtWjL9\nDQKuX7/O+vXrsbKyol69ev9j776joyreBo5/t2Sze3eTkELvhkBo0kFEeu+9iaA08QUVFRuKSlFA\nBcknKDwAACAASURBVBRBQX4goiBdCSJKD72DSFM6hBpKICGbZLO7z/tHYgwKpGxCCfM5x3Nk773P\nzKxlnp07hWHDXmHdutbY7TcAHZr2KcOGhWVJWY+8rMlHHhw5sEmKotwny5cvFz+/xinv3aGJ6HSB\n8t57w2+ZozRnzg9itZYV+E4gSCBAoL1AISlRouJt5zN5Ijw8XJ54oomUK1dLPv30s5T4sbGxEhER\nIU6nUyQqSqRq1aQ5AXnzSglzbtHp3hGzubM89li5lDlannC73TJo0BDx9vYXH58QKVgwRI4dO+Zx\n3OPHj0tAQEGxWjuIzdZa8uV7TM6fPy+7du2Sfv0GSZ8+A2Xnzp0el5NTeNrvqbMGFEVR7iAyMpIS\nJcoTE/MV0Bi9fiqFC8/i+PE/btn2t1evAXz//ePAIOB/wFAgmkaNGrN06SIsFkuW1WnRokV0794P\np/NLID9W6+s88UR+Dhw4gl6v4803X+KV3r2gSRPYsQOKF4f169kSEcHKlavw989Fnz598PHxuWMZ\nLpeLS5cu4e/vn666nz9/nhs3bhAcHIzJZErz/rS0a9eDn38ui9v9DgBG45s8+6yd6dMnexw7J/K4\n38uCZOSBkgObpCjKfbRt2zYpWrSseHlpUqlSbTlx4sR/7hk69D0xmfqmen/9P6lZs8lt4126dElm\nz54t8+fPl5iYmNve43Q6Zdq0afLyy6/JjBkzxOVyiYjInj17xGi0CXyQqqxdotMFCOwT2CV5LSUk\nMrhE0sVixUROncpQew8fPiwFCpQQiyWPmEw2mTJlWoaezwpVqjS4ZfUGzJPGjTve83o8LDzt93Jc\nr6kSAUVR7ubGjRuyc+dOiYiIyLKY165dk6JFS4vV2lw07Rnx8ckje/fu/c99f/75p+TKlV9stg5i\nszWRIkVC5cqVK7fck5iYKMWKlReoLDBWjMZq0rHjM+J2u6V16+4CTQReT9VJhguUFBCxES2bCEm6\nUKSIyMmTGW5L8eLlRKebmhz7qGhaftmzZ09mv5pMeeed4aJpjQVuCFwRTaspEyZMvKd1eJioROBf\nVCKgKMqdbN68WXx984qvb0UxmwNk+PDRWRY7OjpaZs+eLdOnT79jktG4cXvR6candOJeXv8nr776\n5i33DB48RCBQwJ58X6x4eQXJ0aNHpU6d1slLE/MkjwpMTZ6T8KzYiJaN1BIBuaxZRW4zcpGWuLg4\n0euNt6x6sFp7yYwZMzL1nWSWw+GQHj36icFgEqPRWwYOfDVlVET5L5UI/ItKBBRFuR232y2BgYUE\nfk7u5C6IphWW7du337M6lC79hMDGVL/mv5EOHXqmXL906ZIEB1cUKJ3qHhGDoZjs3btXvvnmW9G0\nUgILBDqLwZBXunXrLrmMvrKegiIgZ9DJT+PGZap+brdb/PzyCmxILvumWK2hsnr16qz6Cm4RFRUl\nzz77gjz+eG15+um+cvlfZx4kJiYmTXxU7srTfu++nz6oKIpyL8TGxnLjxlXg79Po8qHX1+bPP/+8\nZ3Vo1Kg2Fss4wA5cQdO+onHjpwCYNm0GRYuGcurUReA6MAY4CozE29tO6dKlee65Xowe/SKFCw+n\ncOFDjB8/jDcHDSTMFUcdznEWX+rzEX0+Gp+pyWM6nY55875F0zrg69sSq7U8nTrVo0GDBln3JSRz\nuVzUr9+KuXNd/PHHCBYutPLkk41xOBwp9xiNxlsmZSrZJGvykQdHDmySoihZILtHBG7cuCF79uyR\nS5cu3fGeuLg4adfu6ZQh75dffkPcbrecOHFCLJYggaMCx5JfDRQVCBSjMUC2bNkiIiJr1qyR0NDq\nki9fiPTr95LEXb0qF5JPETxHfinBkeRXDrZbdmXNqDNnzkhYWJhs3749y5c+iiTNlRg4cJB4eRUQ\ncCX/83CLj09Z2bFjR5aXl9N52u/luF5TJQKKotzJli1bbpkjMGKE57vriSR10DZbbvH1LS9mcy6Z\nPHnqXe9PSEi45ZjhFStWiJ9fg1SvAy6KyRQoH330kURGRoqIyIEDB0TTggR+EjgoAebmciBfARGQ\nC+ilZMpw/q/i758/zQ587dq1kj9/CTEavaVKlbpy5swZz7+IdNizZ49YrUGi0/UVyC3gSK63U2y2\nkCzZ+vhRoxKBf1GJgKLkLE6nU06fPi3Xr1/PkniZWTWQkJAgEyZ8Jv37vyjTp0+/ZeKaw+EQH5/c\nAmuSO7TjYrHkkT///DPd8Y8fP548InA8OcZWsVoDJDY2NuWeTz75RIzGwQIiZuyykjpJWUPevPLV\ny0PEbA4QX99K4uOTRzZs2HDX8k6fPi1Wa5DArwIxYjAMl9DQKtny6z+1b7/9Lnkr5MnJExJbCbQQ\nmC1mc1epVq2emhOQCSoR+BeVCChKznHy5EkpVqysWCz5xWSyybBhI+95HZxOpzz1VFOxWJoLfCaa\n9oT06jUg5XpERIRYLPlumdzn69tCwsLCMlTOl19+LWazv/j6VhFNC5Sff172r+tfisXSRbyJk99o\nIgJySacXST7wJiIiQnbs2JGuhGn+/Pni49M+VZ3dYjL5yLVr1zJU54wICwsTTSsi8ESq1zNxAl0k\nKChEhg59/5bER0k/lQj8i0oEFCXnqFKlruj1Y5J/PV4Uq7XEHU8ezS5bt24Vmy1UIDG584oWk8kv\nZS5AQkKC2GyBqVYDnBGLJW+mTqQ7f/68bNu27T97C4gkzbAPLlhCftMlrQ6IRC+LRozKVJtWr16d\nvCXy38PyJ8TLy5JyWmF26NChl8A0ga8EKkjSBki7RdNKybffZu+hTDmdp/2eWjWgKMoD68CBPbjd\nAwAdkJf4+Hbs2bPnntbBbrej1wcCf5/RZsNotGK32wEwmUwsXDgbq7U9fn7VMZsrMnLkUEqXLp3h\nsvLnz0+NGjUIDAz8z7VcFguHyhSnqZzjptnC0a+n0PH9YZlqU/369alduxRWa21MpsFoWh3GjfsU\nLy+vTMVLD19fDZ3uEvAC0A1ogZdXEz78cCC9ej2TbeUqaVNnDSiK8sAKDq7AiRPvAF2BeKzWusyY\n8Rpdu3a9Z3WIiYmhRInHuXJlEG53M7y8vqFkyc388cdW9Pp/fktdvXqVI0eOUKhQIQoXLpy1lUhI\ngE6dYNkyCAyEtWvh8cc9CulyuVi8eDFnz56levXqPPXUU1lU2dv766+/qFatNrGxz+F2W9G0yfz6\n62Lq1KmTreU+Cjzt91QioCjKA2vnzp00atQana4cTucpGjWqzo8/zr6lA86omzdvomlahmIcP36c\nPn1e5tix41SuXJFvvplE7ty5M12HDHE4oHNnWLoUAgKSkoAKFe5N2ZkUGRnJvn37yJcvH+XL/3Ms\n8bFjx5g+fSaJiU569Oiactyz4hmVCPyLSgQUJWe5fPkyu3fvJiAggGrVqqHT6TIV58iRIzRr1pGI\niGOYTBa++246HTt2yOLaesbtdnP69GmMRiOFChVC53RCly6wZAn4+8OaNVCp0v2u5l2Fh4fTunUX\nDIZyJCYeoVevznz11YRM/3NT0qYSgX9RiYCiKP8mIhQvXpYzZwYhMhDYg6Y15/ffNxMSEnK/qwdA\ndHQ0DRu24dCho7jdiTSq+xRhFkG/ZAnkygWrV0OVKumO53K5SExMxGw2Z2OtbxUWFkaXLs/hcMwH\nmgDRWK1VWbp0arbsTqgk8bTfU5MFFUXJ8W7cuMH58xGIDCJp4mEVDIa67N6926O4YWFhBAdXIl++\nErz00uu3bI97N3/99RcvvTSEAQNeZuvWrQC88spQ9u8Pxm4/gzP+BL1XbU1KAvz8YNWqDCUBY8aM\nw2LxwWbzo3btZkRFRWWqfRkxefIUund/BYcjBmic/KkvIrU4fvx4tpeveMCjNQcPoBzYJEVRPOR0\nOsVs9hXYn3Kin9VaUtavX5/pmFu3bhVNyyuwQuCQaFpjGTjwtTSfO3TokNhsuUWnGybwsWhaHlmx\nYoWUK1dLIFwMJMo8uoiA3DR6iWRwC+RffvlFNC1Y4IxAophMA6R1626ZbWaaEhMTZdmyZWK15kle\nElhaYGbKUkpNK3hPD3Z6FHna76kRAUVRcjyDwcD06VPRtIbYbE9jtVahbds61K5dO9Mxlyz5Gbv9\nBZKGwEtjt09i4cKf0nxu3LjJxMa+hMgo4E3s9km0afMs58+fw9sQxvf0pCsLiMbIt92fgerVM1Sv\n9es3Ybc/CxQGjDgcb7Np06ZMtDBtiYmJ1K3bgm7dhhMbawcCgAXAcKAABkMoI0e+QfUMtkG5t4xp\n36IoipJ9zpw5Q/v2Pdm3bxt58xZlzpxp1KtXL8vL6dGjO5UqVWD37t0UKtSfevXqodPpiI6OZvr0\n6Vy5co0mTRqlu2xfXxteXidITPz7k3NYrbY0n4uNjUck9T4BgSQkFCAxoSff8QbdcRKDnpdLluHL\nKZMy2kwKFcqP2byS+Hgh6TXIDvLmzZ/hOOnx/fff8/vvLuz2bcCrQC/gY2AkFssrhIevU0nAwyCL\nRiYeGDmwSYqSY7ndbilRooLo9R8KxAosF6s1KEPnAHgiJiZGgoPLi9ncRXS64aJpBWXGjJnpejYy\nMlLy5CkmXl79BEaKpuWTxYsXp/ncb7/9JhZLAYHlApsEyomeiTKLniIg8V5esn/q1FsOJcqIuLg4\nqVixlthsT4rN1lVsttyydevWTMVKy6hRo0Svfzv5NYBDYLDodP5SpUp92bx5c7aUqfyXp/2eWjWg\nKMp9c/nyZQoXLklCwjWSfr2Cr29bZs58lg4dsn9p3/Tp0xk8eCl2+9LkT/bi79+K33/fypIlS9Dr\n9XTq1Il8+fLd9vnIyEimTfsfN27cpF27VpQtW5Z58+Zht9tp2bIlpUqVuu1zCxcu4oMPxvPXX0fA\n3Z8ZXOQ5ZnETI6tfe5l248dnuC0nT57kvfdGc+nSNVq3bkCRIgWJiYmhbt26FClSJMPx0mPt2rW0\nbt0Huz0cKILR+Aa1ax9l7dqlaT2qZCGP+70sSEYeKDmwSYqSI9ntdlm8eLEYDBaBU8m/KhPEZist\n4eHh96QO48ePF5PpxVSH71wVk8kqPj55xNu7r5jNvcTfv4CcPHkyzViXL1+WAgVKiMXSWUymgWK1\nBsmmTZvu+sy4TybILINP0sRAjNLWP99tzxlIy4ULF8Tfv4Do9cMF5ovVWknefXd4huNkxvjxE8XL\nyyIGg7dUqVIn5QwG5d7xtN/Lcb2mSgQU5cF37do1KVGigvj41BaTqZxAkJhML4rVWk1ateqS7cfh\n/u3AgQOiaUECywSOi9ncRfLmDRGdbnxKcqDXvy89ez6fZqxhwz4QL6/+qZKKuRIYGCwFC5aW8uVr\n/WeFws3oaNlVqYoISJxeL1927iYXL17MVDsmTZokZvOzqco+IVZrYKZiZYbT6ZSbN2/es/KUW3na\n76lVA4qi3HOjR3/KmTNViYlZj8OxH52uI489tpFvv32TsLC592wXurJly7JkyQ8EBw8jIKAe7dv7\nULBgIUT+OTDI7S7NxYtX04wVGXmNxMTQVJ+Ecu1aDOfOzWP//sE0b96Rw4cPA3D18mUWBOWnyt7d\nxOFFO0NpNhk18ubNm6l2uN1uRFLP/TYC9+4VqcFgwGq13rPylKylEgFFUe65Y8cicDie4u95ASI9\n0Os1OnXq5NE5ApnRuHFjjh3by9WrZ/jhh+l07NgcTRsFRAAn0LSxtG/fJM04rVo1RtMmAweASGAI\nIu2Bx4HOJCR0YeTIkSTExxNe9nF6O2KJw0xrlrMicRuLFi3kypUrmWpD+/bt8fZehk43HliOpnWh\nX79+mYqlPHpUIqAoyj1Xv/4TaNr/gBuAA7N5EnXrPnHH+91uNx999AmPP16bOnVasn379myr29tv\nD6F//9poWkVsthq89loHXnihf5rPtW7dmrFjX8fXtxHe3iF4ef0O/NMZu1wX+HHxbsIKP0bHyxeJ\nR0dbwlhDI8CCiDHdOxP+zel0cv78efLmzcu2beto2XIXNWpM5L33OjFhwpgMtlx5ZGXRK4oHRg5s\nkqLkOC6XS/r2HSQGg7cYjRZp2rS9xMbG3vH+t956TzSthsBagW/Eag2SQ4cOZUldDh8+LJMmTZJZ\ns2aJ3W73KNbYsePF29tXbLYSYrUGitlcWGCcQF+BYJlI/6QlgiBNyS0wSmCbQE957LHHMzQ3YtOm\nTZIrVz6xWPKIpvnL0qU/e1T3++mrr76WQoVKS758IfLBBx/eszkiOYWn/V6O6zVVIqAoDw+73S4x\nMTFp3hcYWETgz5TJcAbDEBk5cpTH5a9evVo0LUjM5gFitTaV0NAqmZ70tn37dtG0QgJnk+v5vQQG\nFhCdziLwtnzG88lJgF4+fLKWmM0FBCqKTldAfH0LyYULF9Jdlt1uF1/fvAK/JJe1TazWoAzFeFAs\nXLhINO0xga0C+0TTKsunn352v6v1UPG031OvBhRFuW8sFgs2W9q78RmNXkBsyp/1+li8vNK3MarL\n5eLSpUsk/rMFYIr+/V/Dbv+W+PipxMb+yunTRfjmm2/uGs/pdHLp0iVcLtctn//xxx9AQ6Bg8ic9\niIqKpE7tunymX84rTMOBkadNPrSYPImff57F0KEt+eyzNzl//s877lVwO6dOnULEF2iR/EkNjMbS\nKZMRM2v+/AU0bNie1q27s2PHDo9ipdecOUuw298FngAex24fy5w5S+5J2UoSlQgoivLAe/fd19C0\nrsAM9Pr3sFrDeOaZZ9J8bsWKFfj55aNQoVB8fXOzZEnYLdevXbsMlE/+k474+HJERt55wt6qVavw\n989PsWJlCQoqxMaNG1OuhYSEoNNtAq7/XTr+ufLya/lgXnH/gQN4zuZLt9nTqVSpEo0aNWL06A8Z\nPHhwhmfc58+fn8TESOBo8icXcTj+onDhwhmKk9rMmbPo0+dt1q7tyrJldahfvyV79+7NdLz0ypXL\nhl4fkeqTCHx9004OlSyURSMTD4wc2CRFUURk/vwF0r59T+nf/8V0bfBz7Ngx0emsAouSh893iNkc\ncMv2xe3bPyPe3j0FYgT2i6YVknXr1t023pUrV8RqDRJYnxzvV7HZcsvy5cvl4MGDIiLSo0cfgVwC\njwuYZUPNmknvMoxGkSVLsuJrSDFt2gyxWHKLr28r0bT8MnLkWI/ihYbWEFiVai+Cj2TAgJezqLZ3\ndvToUfH1zSsGw2DR6YaKpgXJli1bsr3cnMTTfk8dOqQoSrbZv38/3bs/z+nTxylXrgLz58/I9Ha3\nXbp0pkuXzum6NzExkY4duyNiAzomf1qNxMRQ3n9/BH/8cYLAwFy8996rxMdPZNWqICwWX8aPH3PH\nQ4cOHz6M0VgCqJP8STNu3rTQpctQXK7LdO/ejrVr1wOvAzX5iJnU3jobMRrRLVgAbdtmqt130r9/\nH+rWfYpDhw4RHDya8uXLp/3QXST1J6n3b7g327WXKFGCffu2MWvWdyQmOunWbR3lypXL9nKVVLIk\nHXmA5MAmKcpDKSoqSvz9CwjMEDgvBsMoKVasbKYP00kvt9stzZt3FJ2umIBV4HDyL9wrAv5iNpcT\n+FXgS7HZcsvRo0fTNUv91KlTYjYHCpxPjndSwFcgUiBaNK2MGI0WAbeMZJgISCI62fjKK9na3qwy\nffo3yZP25gtMEU0Lkt27d9/vainp4Gm/p+YIKIqSLfbs2YPbHQz0AfLjcr3L5cvRnDlzJlvLPX36\nNOvWbURkBOAH1AbaAKEYDG7i438EmgEDiY/vxqJFi9K1k2HRokV599030bQq+Pq2AyoAI4HcgA9x\ncbVwuZx8wAu8x4c4MdDHOze6Tp2yra2ZdfDgQfr3f5EePfqzdu1aAPr27c3//vch9er9QIsW61iz\n5mcqV658n2uq3Avq1YCiKNnCz88Pp/MckAB4A1EkJt7A19c3W8t1OBzo9d7AM8AV4GNgJQ0b1mfP\nngNERSWk3KvXJ2AwGNIde9iwN2nTphlHjhxhyJC/iIgwkzR6fhmRVbyv82c403AB/bwDMPfqSq1a\ntdKMe+HCBb777jsSEhx06NA+W4fGDx06RI0a9bDbByPix08/9WDevK9p06YNTz/dnaef7p5tZSsP\nqCwamXhg5MAmKcpDye12S+vWXcVqfVJgmFitZWXw4DfveP+OHTukadNOUrNmM5k69X+Z3lTG6XTK\n44/XFJPpBYFNYjS+KcWKlZW4uDgZO3acaFppge9Frx8ufn75bpk8mBGHDh0Sf/+CAgUF/ORd6ouA\nOEHCunWTrVu3pivO2rVrxWDwEXhW4DUxmwNk48aNmapTejz//Eui041MNSnwJ6lYsW62ladkP0/7\nvRzXa6pEQFEeHE6nU7777jt5//0P5Keffrpj575///7kGflTBJaIppWRceM+z3S5165dkx49+kto\naA3p0KFnykY7brdbZs6cJS1adJWePZ+XY8eOZboMEZH169eLppWQt3lHBMSFTnqgSe7cRdJ1nHBc\nXJxYLAECr6XqmGdL0aLlZf/+/R7V7U569Rog8Hmq8tZImTI1s6Us5d5QicC/qERAUR4+b7wxVHS6\nd1N1TtulcOGyWV6O2+2W1atXy/Tp07NkIpzD4ZAJ+QqnJAE9qSTQWkymp+Wzz9LeHW/fvn1iNOYT\n+DJV2zeLTldALJbcMnfuPI/r+G/h4eFiseRNXla5WjStjHzxxZdZXo5y73ja76nJgoqi3Hd6vQ5I\nvVOfM8uPIhYR+vZ9kbZtBzF48EZq127FV1997VFMr4kTefViBG6gD+X4nrbAQlyuAsTGxqb1OAEB\nAeh0N4FPgJ0kbRD0EiKdiYtbSd++L3i0hC8+Pp4NGzawefPmlAON6taty8KFM6hS5UvKlfuAjz9+\nkRdf/L9Ml6E8/HTiyb9lDyCd7t6sfVUUJev89ddfVKnyFHb724gUQNPe59NPX2fgwAFZVsauXbuo\nV68zsbH7ARtwApOpAlFRl9A0LeMBJ0yAIUMAmPlUfQbtNhEXNw44jsXSj61bV1OhQoU0w7z00htM\nmzYHh8MFxAGhwFZAh15vJjY2GrPZnOHqXb58mRo1GnDlijeQSJEiZrZsWZXtkzWVe8/Tfk+NCCiK\nct+VKlWKrVvX0rHjHzRpsphp00ZmaRIASTPzDYbSJCUBAI9hMNi4du1axoN9/nlKEsC0afRY8xu9\ne5elQIFOhIaOZunSuelKAgC++OITFi+exquv9sBk0gFfkZQEjCU0tGKmkoATJ07QsmVnzpxpSEzM\nTmJifufYsbK8996HGY6l5HxqREBRlEfC2bNnCQ2tRGzsYpL2FphO/vwfExHxV4aWEDJpErz8ctLf\nT50KA7IuYVm0aDHPPfc8cXHRhIZWYvnyhRQtWjRDMbZt20ajRq2x230RmQo0Tr6ygEaN5rNq1eIs\nqevx48c5ffo0pUuXJn/+/FkSU8kcNSKgKIqSDoUKFeLHH+fg59cFvd6bYsUmsmbNzxlLAr788p8k\n4KuvsjQJAOjUqSMxMVew229y8OCODCcBAP/3f28SGzsRkbbAt4ATSMBimU3NmhWzpJ5jxoyjfPma\ndOgwghIlyvPTT+q0wIeZGhFQFOWRIiIkJCTcdsh93rz5DBz4GjEx16hbtwndu7flhx9+xsfHysTS\nhSk6dmzSjZMnw6BB97jm6VOoUGnOnVsAFAc6AHswGFw0alSfsLC5eHt7exT/8OHDVKlSn7i4PUAB\nYBea1oSrV89n6jWG4rmHfkTA5XJRqVIlWrduDcC1a9do3LgxJUuWpEmTJly/fj3l3jFjxhASEkJo\naCgrV668X1VWFOUhptPpbtth7dq1iz59BhMVtQSn8zLr1uWmX7/XWbu2M3nCnP8kARMnPrBJAECT\nJg0wm0cAbuBLzGYr06aN59dfF3ucBEDS/AOTqSJJSQBAVUDj0qVLHsdW7o/7nghMnDiRMmXKpCwV\nGjt2LI0bN+bIkSM0bNiQscn/8R06dIj58+dz6NAhfvvtNwYOHIjb7b6fVVcUJQNiY2N57bW3adCg\nHa+//k66ltfdS+Hh4Tid3YFqgA23exzgoC92pjEfgMW16v7zauABYLfbCQsLY/HixURFRQEwefKn\ntGhhwWjMi8VSnVGjXqVPnz5ZthyzdOnSJCbuAf5M/mQlRmOimifwMPNoFwIPRURESMOGDWXt2rXS\nqlUrEREpVaqUXLx4UURELly4IKVKlRIRkdGjR8vYsf+ct920adPbbuF5n5ukKMptJCQkSFBQcYH2\nAovEYOgo1arVE5fLJcePH5cePfpJ48YdPdpa2FMzZ84Uq7WxgDt5Y59N0ptc4kInAvIazWTgwAfn\nJMGrV69K8eLlxGarKz4+zSUoqIicOHEi5Xp2fo/ffDNLzGY/8fEJEV/fPBIeHp5tZSlp87Tfu68j\nAq+++iqffvopev0/1bh06RJ58+YFIG/evCnDTefPn6dQoUIp9xUqVIhz587d2woripIpr732Jleu\nxAMLgY64XPPZt+8Ya9eupWLFmsydW5BVqzoxZMhkhg//6L7UsVu3bpQoEYvV2hij8f/oRSOmcx09\nwht0YAIb6devV5pxlixZQsuW3ejc+Tn27t0LJL0CzWojR47l3Lla3Ly5jpiY5URFDeCll95OuZ7V\nGzKl1rt3Ly5cOMX27WFcuHCSunXrZltZSva7b6cPLlu2jDx58lCpUiXCw8Nve49Op7vrv8x3ujZ8\n+PCUv69Xrx716tXzoKaKonhq48ZdJJ1A+Pd/szqcTqF37/7ExDQChgMQG1uVzz9/ihEjhmVp+SLC\nvHnz2LRpB8HBRRg48P/+M0/AbDazfftaFixYQNCvv9J0bjx6YKgukAm6dUwYN4pKlSrdtZzZs39g\nwICh2O0jgSiWLWuIt7eJ6OjLlChRgWXL5lGyZEmP2rJ3717Cw8NZv34bDkd//v5OXa5anD693KPY\nGZErVy5y5cp1z8pT/hEeHn7HfjMz7lsisGXLFpYuXcry5cuJj48nOjqanj17kjdvXi5evEi+2XUg\nJwAAIABJREFUfPm4cOECefLkAaBgwYJERESkPH/27FkKFix429ipEwFFUbJOYmIiDocDq9WaoedC\nQh7jjz8uAs8DnYB5mEwOLl70A1LH8sqWuT9DhrzD118vx27vidkczty5YWzZsgovL6+Ue9xuN97e\n3vTU62HePAAO9ehBSIMG/Fm7NiEhIWmWM3r0JOz2/wFNAIiPjyY+fh+wgGPHvqJhw9acOnUoY0sW\nU1m0aDG9eg3E5eqCyGV0uomItAHMmM1fUK9ezUzFVR4u//6BO2LECM8CZs0bCs+Eh4enzBF44403\nUuYCjBkzRt566y0RETl48KBUqFBBEhIS5MSJE/LYY4/d9h3YA9IkRclxRowYLUajWYxGs9Ss2Uiu\nXbuW7mdPnjwp/v4FxGgMFb2+qJjNgdK0aTuBMQJ5BCYI/CI6XQUZMmRoltb75s2bYjRaBK4kv/t3\nic1WWVauXCkiImvWrJHcuYuJTqeXQQH5xa3XJ53+M3JkhssqVaq6wNpUBwiNFXgx5c8WSx45e/Zs\nptsSGFhYYEtyPKcYjcVFrzeJ0WiWFi06id1uz3Rs5eHlab/3QPSa4eHh0rp1axFJmgDTsGFDCQkJ\nkcaNG0tUVFTKfR999JEEBwdLqVKl5LfffrttLJUIKErWCwsLE00rKXBWwCkm0wvSpk33DMW4fPmy\nzJo1SyZOnCiDBg2WypVrisnUSGCvQFeBklKuXHVxuVxZWvcrV66IyeQr4EzpkH19m8tPP/0ku3bt\nEp3OKjBHujBbnMkTA+OHpj8ZOXXqlOzYsUOio6NlypRpomkhAksEvhGwCWxILvekmExWiY2NzXRb\nvLw0gesp7TCZXpKxY8fKzZs3Mx1Tefh52u+pDYUURUnTG2+8zbhxPsC7yZ8cJzCwAVeunM5QnMuX\nL1O2bFWiotrhdD6GXj8Kg0GHyeRLkSIBbNjwK0FBQVladxGhRo0G7NtXGofjJXS6Dfj5jeDo0T9o\n0KA1+/dfpxMjmUt3jLgYbQii0ZZfqF69epqx33zzPSZNmoLJVAS9/iJTpkxg48ZNbN68n4AAfwwG\nJ9u2ncblegKd7ldGjx7K4MGZ34OgUaO2bNyYH4fjE+AQFktbNm36lcqVK2c6pvLw87jf8zwXebDk\nwCYpyn03ceJEsVhaC7iSf43OlnLlamY4zmeffSbe3r1SDZ3vlly58svBgwclMTHxrs96shzu6tWr\n0rbt05IvXwmpVq2BHDhwQERE8uYNlg5YJRGDCMgoXhOD3ldOnjyZZsx169aJ1Rqc6pXDAtHpfMTX\nt41YLHnls88midvtluXLl8uUKVNk27ZtGarz+fPnZeTIUfLmm0Nlx44dKe1o2LCteHlZJCCgkCxY\nsDDD30Vqbrf7vi3XVLKOp/1ejus1VSKgKFkvLi5OKlV6Smy2J8THp5PYbLlTOqeMGDNmjBiNr6RK\nBE6Jr2/euz6zcOEi8fcvIAaDSZ56qplERkZmthn/8UnNeuJIfh0wmooCBaRp0zZ3fcbtdssvv/wi\nXbt2FW/v3qna4hTQCyQKnBKzOZdcuHAhU/U6d+6cBAYWEqPxBYH3xWLJLb/++mumYt2O0+mUQYNe\nE29vm3h7+8hrr72d5a9klHtHJQL/ohIBRckeCQkJsnTpUvnhhx8yPeHt0KFDomlBArMFtoumNZAB\nAwbf8f69e/eKxZJHYJtArHh5vSy1azfPbBNutWSJuI1GEZBPdUbR64zSrl2Xu/5Cdrvd8uyzL4jV\nWlZMpjYC+QQuJycC8wRKpZqH8Ljs3r07w9VauXKlBAQUFBiYKskIkzJlnvCktSmioqKkV6++4u39\nhMBFgXOiadXk888nZUl85d5TicC/qERAUR5smzZtkqpVG0hwcGV5/fV3xeFw3PHeiRMnirf3/6Xq\nEGPFYDB5Ppy9dKmIl1dS0CFD5OqVK+maxLd3717RtMICMcn1eVXAKjZbeQFNYGry56vEZsst169f\nz1C1fv/9d7FYggTaCXxyyyuUIkXKZba1KY4cOSJBQYVFry8ssCxV/IXSoEE7j+Mr94en/d5920dA\nUZRHU61atdi5c0267s2dOzdG42ISEtwkHY1yAF/fIM92zfvlF+jUCRIT4ZVX4NNPCUhnvMjISLy8\nSgC25E8mYLHMZ86cD9HpdPTo0YfExGGYTHrCwhbg5+eXoaotX74ch+NZoAXQk6RzD/Kgaa/StWu7\nDMX6N7vdTu/eL3Pt2qu43buBP4CWAOj1+8mfP2snaSoPkSxKSB4YObBJivLISkhIkOrV64vVWke8\nvQeKxZLHswlyy5eLmExJP4NfflkkgyMLkZGR4uOTR2CpgEN0uimSP39wyqhGYmKinD9/Ps2Jj3cy\nceJEMZu7p3rVUFJ0Oj959dW3Mx3T5XJJ376DxGg0C/gJ/C5wRCC/QDcxGDpKQEBBOXXqVKbiK/ef\np/2eWj6oKMoDQ0T45ptvWbFiA0WK5OOdd97Ax8eHhQsXcuXKFerUqUPFihUzF3zFCmjbFhIS4MUX\n4YsvIBMjC5s3b6Zz52e5ePEkJUpUYOnSHwgNDc1cnf4lKiqKcuWqc+VKbRyOEmjaFL788iOeey7t\nMw7u5IsvvmTo0B+w25cDLwEmYBpwFC+vZnTrVptx48al7OKqPHw87fdUIqAoygPjjTfeZcqUX4mN\nHYjJtIv8+Tewf/92fHx8/nOv2+1m9OhPmT59DiaTiQ8/fIsuXTrfNq57xQpcLVvi5XLxrcWXmx+P\n4cWXBnpUV7fbfcuBaVnl6tWrTJ36NVevXqdVq2Y0aNAgU3FOnz7NoUOHGD/+a9asaQv0BqKAxuh0\nf2E0Cs8914evv56YrQcUKdlP7SPwLzmwSYrySHA6ncnD1xdTJrHZbE1l7ty5t71/9OhPRdOqCOwQ\nWCkWS4GUbYNvsXq1JBiS9gmYQhfRsUM0LVjmz1+QzS26f2bP/kEslkDx82ssBoOfGAy95O/jlXW6\n0VK/fqsMT2RUHlye9nv39RhiRVGUv7ndbkTcwD+//kX8cDgct71/1qyF2O2fkTShrjFxcW8ze/bi\nW29auxZHs2aYXC6m0ZKBzEWoht3+DvPm/Zxtbbkbt9vNzZs3sy1+TEwM/fr9H3Fx4dy4sRKXaxtu\n909YrU/h49OcwMApTJ8+McMTGZWcSyUCiqJw4sQJVq1axenTGdsyOCt5eXnRunUnLJYewFZ0ukkY\njRto0qTJbe+3WjUgMuXPev0lfHy0f25Yvx5p2RKT08l0CvIC7ZDk/+XpdCcJCPDNxtbc3jfffIum\n+eHvn5syZapx5syZLC/j4sWLGI0BQLnkT0Lx8anMm282Zdas5zlyZB+PPfZYlperPMSyaGTigZED\nm6Qo2WrSpClisQSJn199sViCZPr0mfetLnFxcTJo0BApWbKa1K/fWg4dOnTHe1esWCGalkfgI9Hr\n3xBf37xy7NixpIvr14tomgjI90Zf0bFFIEjgdYHnxWrNLcePH79HrUqya9cusVjyCRwWcIvBMEoq\nVKiVJbEPHDggM2fOlBUrVojdbhdf3zwCvyW/YtkrFkugnDlzJkvKUh48nvZ7arKgojzCzp49S0hI\nBeLjdwHFgb8wm58gIuJolh/+kx22bdvGnDkLMZtNlC9fmvXrt1MhJooXfwlDb7fj6tGDQis3cenK\n24hUBT7G23sFu3dvpWzZsvekjgkJCQwe/BZz5swmNrYlIrOSrzjQ6zUSEx0eTTqcM2cuzz//Cjpd\nE2AvzZpV5uWX+9GmTRecThMuVzSzZk2nS5dOWdIe5cGjJgv+Sw5skqJkm82bN4ufX/VUO8yJ+PqW\nk717997vqmXInDk/iKYVlJq8LNEk7Rh4s0MHEadTDh8+LKGhVcVo9JbixctnattfT/Tt+6JYLM0F\nJgtUFEhI/q43iL9/AY9iO51OMZt9Bf5IjhknVmtpWb16tcTHx8vx48c9OvZYeTh42u+pnQUV5REW\nEhJCYuJxYCdJk+424XJdoHjx4ve5Zhnz7rtjKW9/h994Gx8SmUMIGwOCmGowEBoayuHDO+95nc6f\nP8/EiV/y/fc/4HBMIGmnwHDgcUym0hiNm5g9e9bdg6TBbrfjdCbyz3wAMzrd41y4cAFvb281F0BJ\nFzVZUFEeYblz5+aHH75B05pisz2G1dqOxYvnPDQzyi9fvsz69espdf0KK3gLX2KYSzeepSszvv2B\nffv23Zd6Xbx4kQoVnmD8+FgcjmHAu8BsYD5GYyE6drSwb99WWrRo4VE5Pj4+FC0agk73GSDAblyu\nNVSrVs3zRiiPDDVHQFEeMW63mwULFnDq1CmqVq1Ko0aNiI2N5fz58xQsWBBN09IO8gBYu3Ytbdp0\npRoFWBL7B37AAhrwNC/gYhDQmeeeczNz5pR7Wq+VK1fStWtPrl9vBvz9i38L0BmTqSmBgRs4cGAH\nAQEBWVLe8ePHad68EydOHMLb28p3302nY8cOWRJbeTh42u+pVwOK8ggREdq06UZ4+BkSEp7CZBrA\n0KHPM2zYW4SEhNzv6qWbiNC+fXdCY0fyE0PxAxbhRQ9O4mISMAf4E4fjj3tar7FjP+addz5EpA1Q\nINWVIMxmB++/X5Lnn/80y5IAgODgYI4c2UtcXBxms1ntEqhkmBoRUJRHyObNm2natC+xsX+QtOf8\neby8QoiKisRqtd5yr4jw/fffs3nzLkJCivLii4Mwm824XC62bdvGzZs3qVGjBrly5brn7bhx4waN\ng/KxwmnGn+v8SHt6mSCRrTgcM4FoLJaXWb58HvXq1bsndVqwYCHPPDOAxMSOwCCgCTAFKIqmvU7/\n/jX4/POPMxz3xIkTvP/+GC5dukbHjs0YMKCf6uyVW6gRAUVR0u3atWsYDMVJSgIA8mMwaERHR/8n\nERg0aAizZq3Hbn8GszmcBQuWER7+C02bduD33yPQ6/Pg5XWMTZtWpRy643A4mDlzJhERZ3nyyZoe\nvwO/E9/jx1nhSsCfeJbQlm58gpexDm8NGcDPP4/F29vEBx/M/E8S4HK5MBgM2VKnqVPnkJjYHTgK\nVADmAW+h0x1n0KBBjB79QYZjnj9/nipVniI6+gXc7kZs3TqGCxcuMWLEsCyuvfJI82jNwQMoBzZJ\nUbLMhQsXko/RXSRwTQyGURIc/Li4XK5b7rtx44Z4eVkFriUvS3OJzVZBXnzxRbFYmgk4k/et/0Jq\n1GgkIklH8D7xREPRtCYC74umlZAPP/w46xvx++8Sb7OJgIThJV4UETDLK6+8fsdHdu7cKQUKhIhO\np5dChUplyxLCFi26CHwhUE2gjcBQ0etzy/Tp32Q65meffSbe3n1SLe88Ir6+ebOw1kpO4Gm/p1YN\nKMojJF++fKxcGUaxYsPx9i5K5cprWbv25/9saBMXF4de7w38vXpAj16fmxMnIoiLawgk/aoWacyp\nUycBWLVqFQcOXMdu/xUYgd0ezvvvv0dgYDFy5y7Oe++NxO12p7uuq1evpnXrbnTs2IvNmzcnfbh/\nP6769fG+eZNllKEzkSTyKzCSv/66/fbIf/75J3XrNuf8+Y8QcXD27HAaNWpNbGxsuuuSHsOGvYKm\njQTaAHqMxolMmjScvn17ZzqmiHDrKm+v5PMYFCULZU0+8uDIgU1SlHvO7XZL5cq1xctroMAB0em+\nkICAgvLVV1+J1VpFIErALV5er0qLFp1FRGTevHni49Mh1a9Xl4BJIFzggHh7V5RPPpmQrvJHjRol\n4CswVeBLMZuDZPesWSJBQSIgy9HExHepyvpRatVq8Z84mzZtEosll0DovzZNejxbRgV27twpffoM\nlN69/0927tzpcbzTp0+Lj08e0ekmCPwimlZDhgwZmgU1VXIST/u9HNdrqkRAUbLG1atXpV27HlKg\nQCmpWLG2LFq0SOLi4mTAgMHi5WUTiyWPlCtXQyIjI0VE5OzZs2Kz5RaYLxAhMFCgbKoOeKWUK/dU\nmuWePn1a9PoAge9Tni3N+xJl8hYBOV+hgviaygiUENgosEWg8H+G4Ldv3y6ali85mQgSuJIcL1K8\nvQMkIiIiW763zLp586ZcuHBB3G73LZ8fPHhQWrXqKtWrN5aPPx7/n9c4iuJpv6dWDSiKckdOp5N2\n7Z5m3bqtGAx++Pu72bx5JZqmYbfb8fb2ZsKELzh//jKtWjWkSJEi9Oo1iHPnzmC3uxDpC3ySHG0G\nVarMYdeutSnxz5w5w4wZM4mPT6Bbt85UqlSJn3/+mfbtX8Ll+gToQiiHWccT5CMaZ/36OBYtouIT\nDThxwozLdQmdLoZmzZ7il19+SplNv2PHDurXb4ndHgecBiYA84FawErq1CnP+vUr7+VXeVfDh3/E\n6NGjMRgsFC1alDVrllKwYMH7XS3lIaFWDSiKckdxcXF4e3tn+lCbqVO/Zt26q9jtxwBv7Pbh9O79\nEqtW/YTBYKBs2WpERjYgMbE8ixa9x6uvdiU4uDhXrlwiNvYq8C0QB1iALxk7Niwl9smTJ6lU6Ulu\n3uyCy+XH5MlN+OWXhRQoUACDIRaXawgluchaPiAf0azW+bO8VHkmBASwa9cGvvhiMhERF2ncuA6d\nOt16oM748VOw24cBy4HPgA+BisD/ATUpX/7B2DMhJiaGhg1bsnPnMeAYiYn5OHZsOF269GHz5hX3\nu3rKoyILRiUeKDmwSYqSYZcuXZKqVeuJwWASk8kqkydPyVSc/v1fFPgs1fD+filYMFRERGbMmCGa\n1i7VtWOi01nEy2uwwDGB5wW8xcsrjxiNmnz++cRbYg8c+Iro9UNTPT9XqlVrKCIiAwYMlhD85BwG\nEZDVFBILC247D+B2qlWrn/xK4FzyLH6bgJfAm6JpxWXZsmWZ+j6yWufOz4rB8LjA26m+h0uiaQH3\nu2rKQ8TTfk+tGlCUHKhBgzbs3l0Bl8uOw/E7b745mg0bNmQ4TsWKZdC0MCAeEAyG+ZQtWwaA+Ph4\n3O7UO+QFIpJIYuJ4IBj4GputFh9//DaRkWcZPPjlW2LfuBGL2516+Lsg0dExAEwdMoitZgcFcLGO\nqrThIGL+mcqVy6RZZxFh374dwPvARuAdkkYkBB+fmYwZM4SWLVtm+LvISmFhYdSs2Ywff1yCy/Us\nsAlITL4aToECRe5j7ZRHTtbkIw+OHNgkRcmQzz+fJGBONTlOxGAYIqNHj85wrMTERGnTpptYLPnF\nxydUihUrK2fPnhURkZMnTyZPDvxGYKeYzS1Fp7MJXE4u1yk2WwVZs2bNLTFjYmIkOjpafvnlF9G0\nwgLrBfaJplWXUaPGihw9KlKwoAjILpuf5NaKitVaXKpWrSsxMTFp1vny5csCRoFlAs0EGglUkbFj\nx2a4/dlh2bJlYrEUEFgoECKwWKCdQGmBuuLtnUu2b99+v6upPEQ87ffUHAFFyWHee28UUAjYATQH\nXBgM2ylQoF+GYxmNRpYs+YGjR48SFxdH6dKlMZmSdiUsVqwY4eG/MmjQ20RGXqF58waYTGX53//q\nExv7NBbLRsqXz02dOnUASExM5Omn+7JkySIAWrVqz6RJIxg5chAOh4M+fZ7mnW4doX59OHcOnnqK\nisuWsTYiAp1OR2hoaLp2Bfz4488Ab+AwSXME9gH1iImJyXD7s8OkSd8SFzcG6AQEAR2AVpjNPgQG\nRrBhw251fLByT6lEQFFyGIcjjqQ97nuRtN/9AQoUcPH0009nKp5Op6NkyZK3vValShW2bVuV8mcR\n4cknq7Jlyw6Cg1vw/PPPYzQm/W/mww8/ZvnySJzOK4COFSs6Ubr0aU6d2p/08KlTULcunD0LtWrB\n8uUYfHwol8EjkffuPUzSCevfAsNIei1QmBIlSmSs4dnEaDSQ9KoFoB7wBqVKzefdd4fQsWPHh+b0\nRyUHyZqBiQdHDmySomRIjx79xGJpKbBU4Hnx9vaRQ4cO3e9qSe3arQR+SjUp7mepWbNZ0sVTp0SK\nFk26ULOmyI0bacb76quvpXjxClKs2OMyceLklPX3Q4YMFaOxukAxgRECncVmy5eu1wr3woYNG0TT\ncgtMEvhKNC2PrF69+n5XS3mIedrvqcmCipLDzJgxmd69S1G06LtUrnyEdetWULp06ftdLUqUKIzR\nuDHlz0bjRoKDC8OZM1CvHpw+DTVqwG+/ga/vXWPNnv0Dr7/+KSdPTubUqSkMHTqJmTNnATBixLtU\nrGjB2zseL69J5MmzlQMHtmGz2e4a0+12Z2gL5LQ4nU5GjBhN9epN6NChJydOnACgdu3arFz5E506\n7aJjx20sX76Ahg0bZlm5ipJRakMhRXnExcfH88Yb77F69UYKFcrP5MljKVWqVMr1vXv3smvXLooU\nKUKTJk0yfQRuZGQkVavW4fr1/IAeX98I9oTNJU+XLnDiBFSrBqtWQTpeBTRq1IE1a7oA3ZI/+ZGA\ngLc4cmQbgYGBuFwuDh48iNvtply5cimvJ24nMTGRvn1fZO7cWeh0el56aTDjxo32+KjfPn0GMn/+\nn9jtb6DX78XP70v+/HMvefLk8Siuovybx/1eFoxKPFByYJMUJVu1bdtdzOa2AptEp5sguXLll0uX\nLomIyNdfTxdNyyea1lus1rLSrVvv/2yBmxExMTGydOlSCQsLk5jDh0WCg5NeB1StKhIVla4YDodD\nQkIq/2t/g69EpysrFSo8meH6DR36gVgsjZPPT7gomlY10/suiIjs379fRowYKXq9Sf45vVHEau0s\nM2fOzHRcRbkTT/u9HNdrqkRAUdIvISFBDAaTgD2lw7LZOsjs2bMlISFBTCarwF/J1+xitYbIxo0b\nPS/47FmRkJCkAitXFrl2Ld2P9u07SMzm6gL+Au8IvCsQKLBNzObcKcsb06tixboCq1MlFd9LixZd\nM9oiEREZNuw9AavAy5J04NLlVIlAe/n2228zFVdR7sbTfk+tGlCUR5her08eAo8laXY9QAwmk4kb\nN26g05mAv1cMWDAYynDx4kXPCr1wARo0gKNHoWLFpNcB/v7pfvz772fhcBwHrgDfAb8BzwOhuN3x\nWCyWuz4PcO7cOXbs2EFgYCD58+fhjz/24nYnvac3Gn+ncOG8GW7Wxo0b+eijL4HpJL2y8AKaAm9j\nMOzBat1D69bTMxxXUbKbmiyoKI8wo9HIwIEvo2nNgW8wmV4gKOgczZs3JygoiLx586LTfQG4gU04\nnZupWrVqpsqKi4vj2KZNuOrWhSNHoEIFWL0aAgLSfjjZ1q1bcTicwE2gDDAWKA4cQ9Oa0LNnLwLS\niLdx40ZCQyvx3HMzadnyBez2GHx9J6Bp3bBa2xEY+CMffPB2htu3YsUqRHyAv/cA+AR4jHz5PqBn\nz+vs2bM5zbopyv2gRgQU5RGTmJjI6NGfsnr1FooVK8DYsR9QpkwIK1eup1ix/Lz77saUGfarVy+l\nZcsuHDv2Gr6+Qcyd+x3FihXLcJlbtmzh2WbtWHbzOgZJ5FrBQgSsXg2BgRmK8+qrHwBtkv96DfgD\nL691dO3aiQYNXuC555676/NLly6lW7f+xMXVB74A/Nm1qzYTJgzHaDRiMBho02Ym/hkYofhbYKA/\nBoMfLtdbwAzgGjrdJqZNm0br1q0zHE9R7hW1akBRHjFPP92XsLDT2O0vYTRuJShoIX/+uQe/u8zW\ndzgceHl5ZWomvd1up3zeYiy9aaYsEeynJA04R+32rZk//zu8vLzSHatkyWocPfo5cAJYDZynffs8\n/PjjnDSfnTx5Cm+99Sl2+yvAX8CvwE5MplF89FEhXn/99Qy3LbXo6GgqVKhJRIQbl+sS4GTQoOeY\nPPkLj+IqSlo87fdUIqAoj5D4+HhsNj9crqtA0q9+m60ZM2f2+89Rvlnh4MGDdKjdmMVRlyiHm4OU\noT7ruEwfTKazDB7cmk8+GXXLMy6Xi1WrVnH16lWefPJJihcvnnLtnXeGM3FiOHb7TOAGmtaR2bPH\n0b59+zTrEhBQiKio5cDjyZ/0AEqhaTNYvvw76tat63F7Y2JimDNnDtHR0TRt2pQKFSp4HFNR0uJp\nv6deDSjKIy47k+eezTuyMEpPOdwcohgNWMtlBNiDwzGaX36Zdksi4HQ6adq0Azt2RAAlcbtfISxs\nLo0aNQJg5MhhREfH8P33T+LlZeKDD95KVxIA4HDEA6lfRfig13/IiBGfZEkSAODj48MLL7yQJbEU\n5V5RIwKK8ojp3r0PYWERxMW9hNG4jaCg+Wm+GrgdEWHq1P+xePFv5Mnjz6hR7xAcHJxyPfHiRQ7m\nz09F4DCFqI+dSwQDx/l/9u47vsbrD+D4567k5mYRkYTYEiFW7BFUkVhFW9Vp/FClKKpV1WHWqFbR\n6jCqRltUbC1qj5qJ1YgRM0RsSWTc3Jt7v78/bprSmE3UOu/Xy4v7POec55zzkjzfe57znAPvoNHk\no2HDlaxbtzQ7z5w5c+jWbRKpqRtxfE9ZjZ/fmyQkHM11u19/vTc//xxLevpI4AgmUx+2bl2rvrUr\njzz1aOAfVCCgPOkSExNJTk7G39//prv1Wa1WRo4cmz1ZcOzYYRQuXPierzN48HDGjVtEWtogtNoj\neHh8Q3T0Lvz9/eHKFWjcGPbu5TD+NGQX57gG1MNgKI5eXwG9/je2bFlNpUqVSE9PZ9Kkr1m4cDG7\ndlXBZvsq6yrXMBh8sVjSctcpOOY5DBw4mCVLVuLllZ+JEz8hNDQ01+UqyoOmAoF/UIGA8iQbNGgI\nX3zxBTqdG4UL+7B+/XKKFi2a59eZOnU6b7zxFo4tfh27+jk7d2XMmIr069QJmjSB3btJ8/cn5Go6\nFwyVsVpjeeGFFtSrV53MzEyeeeYZihYtitVqpXbtxsTEFMBsLgr8DOwASqHTfUz16tvZvn3NXdft\n8OHD7Nmzh6JFi6obvfJEUHMEFEUBYPny5Xz11TwsluOANydPjuCll7qydevveXqdP/74g379BgMm\n4O8RBxEdTmlpEBYGu3dD6dKYNmxgi5MT+/btw9fXl0qVKuUob+PGjRw5korZvAHH0iYv+C9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DHxGnAGx86AbwBOQDeWLp1710EAgJ+fH9Onf8O6dYv54IMBNwQBAE5OTsz9aRrpL7blZbGDuztd\nCgWw2TIScAEKkJb2Jr//viVH2Xa7nQkTJvH00214+eUuHD9+/F/1ReHC3sBiHI8FBFhMsWI+hISE\nqCBAUf4jKhBQlP/YrFnf8swzetzc2lO48Abmz59NaGho9vkWLcLR6QoAvYH6gBsajZ3Zs+fn6WiX\n1WzmTFgY2rlzsbu6wsqVXAosg0azIzuNk9MOSpTIOTHx/fcH8+GHM9mwoSPz55eiWrV6JCQk3HMd\nVqyYj8EQgeMNh9I4O6/g11/n56JViqLcK/VoQFEeMmazmZdf7sKSJb9kHXkF+ApX1zC++64v7du3\nz/01UlNZU7w0z1w+Two6nndx55MNq8iXLx+1az+N1VoTuIa3dwJRUZuz5y/8xfF4Yy9QDACjsROf\nf16TXr163fKaNpsNIMfIRHJyMnPmzEGj0dC+fXtMJtPNsiuKcgv3fdMhRVH+W0ajkcWLf8bHZzsX\nLy4HHJt7paa2Y+fOPbkPBOx2TjRuzDOXz5OKiRasYHP6Wc787y1iYnZw6NAe1qxZg5OTE82aNct+\nZGGz2Vi7di1XrlzJ+qVz/QQ+7S1/EaWnp9Os2XNs2bIOjUZL9+49+eqrz9FqHQOSHh4edO/ePXdt\nUhTlX1OBgKI8pEqVKs2lS2sQCQasmExrKFv22dwVardDt26U27GDVAy04Dc20wA4yblz8QD4+Pjw\n6quv3pAtMzOTsLBniYw8g0YTgNVqx2h8HrP5Y7TaGJydV/LcczlfM7RarZQpU4UzZwoClwAr33/f\nnICASbz9dp/ctUVRlDyh5ggoykNq1qyvKVBgHB4e9XF1rUCtWk5065aL2ft2O3TvDtOnY3Ny4gVn\nHzYRANgwGD6nTp2cCwfFxcUxaNBHtGz5LNu3nyElJZJr1yLIzJyNs3M8det+R5s2B9i1axP+/v45\n8kdERHD2bArwEeABFCAj4x1WrNj079uhKEqeUiMCivKQKlOmDMeO/UlkZCSurq7UqFEjezj9ntnt\n0LMnTJsGRiO65csJ3RbJmmEBAFStWpdZs365IcvJkycJCalDSsor2Gx1gHHAahyv+tUjIyOVP/74\n7baXPX/+PI61EKKApllHt1OsmN+/a4eiKHlOTRZUlMedCPTqBd9+C87OsGwZhIUBjiF/s9mcPQ/g\nem+//R5ffqnBbv8068hiYDSwHb3+Q2rWjOKPP1bd9tKRkZHUr98cs1kPhALXMBh2cupUzC2XSVYU\n5d6odQQU5TGQkpLCwYMHSU5OztuCRaBPn7+DgCVLsoMAcCxJ/FcQYLfbWbhwIePHj2fz5s1cu5aG\n3e57XWF+wBH0ejfKlVtPRMSMO16+evXqTJkyAZPJjEaziFKlzhAdvUMFAYryEFEjAorygK1cuZIX\nXmiPVutFZuYlZs6cSrt2bXNfsAj06wdffglOTo4goFmzmybNyMigbNnqnDyZCTyFs/NyOnVqw48/\nLiYtbQZQAJPpTd555xneeafPTbdAvn1VBJvNhl6vnkYqSl7L7X1PBQKKksdE5K7Xxk9OTqZw4VKk\npi7BMXS+F5OpCceORePn9/dz9L/+T9/1mvsi0L8/TJgABgMsWgQtW94y+bPPvsiSJTtw7H/gDMSh\n15dl+vQpDB8+HrPZTOfOLzN06If/fp6Coij3hXo0oCgPicOHD1O2bHX0egP+/mXYtm3bHfOcOnUK\nrdYHRxAAEILBUIbY2FjA8e7+W2+9i9HojouLB/36DcRut9++UBESu3WDCROw6/WwYMFtgwCAdes2\nAOVxBAHg2LHQmbCwJsTGRnH69AGGD/84z4MAm83GuXPnsFqteVquoih3TwUCipIHrFYrTz/dkiNH\numC3p3L27Gc0bfosFy9evG2+IkWKYLUmAAeyjhzHYjlCiRIlAPjsswlMn74Ni+UYGRmxTJ26kfHj\nv7p1gSIcevZZ8n3/PVY0vKzNR981OfcKAMfjgK+//ppnn32B1FQrsAP4DUgDPsXd3Q0fH59764h7\nsGvXLnx9S1CyZEXy5fNh8eIl9+1aiqLchjxmHsMmKY+A2NhYcXUtLo4xeccfT8+Gsnr1ahERmTZt\nunh4+Iheb5TmzV+Q5OTk7LyzZ/8kLi4FxNOzvri4FJCvv56cfa5u3eYCS64rd4GUKBEiNpstZyXs\ndskcMEAExIJenmWhwFUxmYrJzp07b0iakpIiAQGVRadrJPCJQCEBdwFfAb3o9V4SFRV1y/bu2bNH\nSpasKDqdQUqXriz79++/p/7KyMgQLy9/gYisdu0Sk8lb4uLi7qkcRVFyf99TIwKKkge8vLywWq8A\nf228k4rVepyCBQuyYcMG+vQZTHLyajIzL7BunQudO/+9Jn/79q9y5MheFi0axsGDUfTs+Ub2ucKF\nC6LV7r/uSvs5ffoiI0aMubECIvDRR+g++4xM4GXmspjngHzo9VWIi4vLTmo2m6lcuRZHj5qx2X4H\nPgT2AhlAI7y9C5GQcJiqVavetK3Xrl2jUaOWnDjxHjZbEseO9ePpp1uSlpZ21/0VHx9PRoYW+GtS\nZHUMhqr8+eefd12Goih5QwUCipIHvLy8+PDDDzCZ6uLs3AtX19q88EJzKlWqxNq160hP7wxUAtzJ\nyBjJmjVrbshfpEgRnn76aYoXL37D8TFjBmMwfAG8iGPzoWnYbN8yffqcGyswZAiMGoXodPTw8GYh\nGVkn/iQzcyuVKlXKTvrjjz9y+rQBCAT+2gDIGzACzSlSpCTe3t63bGtMTAw2mx/QHsd2xf/Das3H\n4cOH77q/fHx8sNmSgINZRy5jtUZTrFixuy5DUZS8oQIBRckjgwe/z2+/zWDs2CDmzRvDjBnfotFo\nKFjQG2fnaOCvWb3R5MtX4K7KLF26NG+80RGNJhFoBOwGjDg7O/+daNgwGDECtFo0P/1E742r8fH5\nAKPRB6OxHlOnfklgYGB28k2bNmGx1AZ2ATOA40AvwA+dri8jRgy4bZ28vb2xWE4DiVlHrpCREU+B\nAnfXJgBXV1e+/fYrXFyewsPjWUymEHr37kqFChXuugxFUfJIHj2ieGg8hk1SHnEpKSkSFFRV9Pqn\nBf4n4CZeXoUlNjZWNm3aJAEBVcTTs5C0bPmirF69WlasWCEXLlzIzn/ixAnx8PAVjaanQEvR693l\niy/GO04OH+6YPKDVivz8c3aezMxMiY+PF7PZfENdhg4dKUZjUYGCAvMF6ggUEPAWrdZdpkyZcldt\n6tmzv7i6lhUnp97i6lpG3n77/X/VN4cPH5aIiIjbzkdQFOX2cnvfU+sIKMp/YM6cOfzvf+9hsfQG\nWqPVrqRcuTmcPHmC1NQpQHW02qHAEtzdq2C372f16qXUqlULgLVr19KiRVus1lfQaJxxcfmJI51f\npvCkSaDVYp8xA22HDje9dnx8PG3bdmLPnu1YLBpgFpAEvAskYjDkJyCgFBMnfkLYdasOAiQlJfHx\nx59w8OBx6tQJ4aOPBuLk5ISIsHLlSg4dOkT58uUJDw+/b32nKMrt5fq+l/tY5OHyGDZJeQwMGzZM\nNJoPrpv9f16cnFzF1fW1645ZBAwCGQIRUrx4eRERSU9Pl8aNnxGN5pPstANpLQJiA+mkNQlopGDB\n4rJhw4Ybrmu32yU4uIZotR8KJAosF/AWiBMQcXNrLfPnz79pnTMyMiQ4uIY4OXUWmCcuLi2lefO2\nYrfb73t/KYpy93J731NzBBTlPxAUFITJ9DuOd/RBo1mMr68/Gs0p/p47cAZwAgxAOGfPHufChQsE\nBVVlw4Y9iJQE4F0+YwxLsQOd+YaZ9h+Bgly8OJpnnmnHuXPnsq+bmJjIoUPR2O0jAE+gJVADWAb8\njEazndDQUG5mx44dnD5twWL5HniR9PQFrFu3noSEhJumVxTl0aQCAUX5D7z44ou0bl0Jk6kMHh41\n8PL6hKVL5xEQILi4tAIGA3WAQYAGrXYyQUGVKF++NnFx9bHZRgEj6E9/PuM9AF7nFWbxJvAcUA1w\nRaerzJ49e7Kve/z4cez2TOCv1wetwCFcXT+mXLmJrF27/KYbAEnW3gCOoOQvOjQaXdZxRVEeF2oH\nEEX5D2g0Gn76aRqHDh0iMTGRChUq4O7uzrZta5g+fTpnz54jLq4F8+aNQa//Bm9vTypVqsOBA5eA\nVkBL+rGQcYwH4A2NgR/ks6zSLThm/ruQmRmLr+/fOwYmJyfj7FyCjIwGON7Z34FOl0xU1FaCgoJy\n1HP69Bn07TuA9PQk6tULI3/+VMzmd7Bam2E0zqB69aoUKVLk/naWoij/KTVZUFHug8jISL744jus\n1kzefLMjjRo1uqt8SUlJJCUl4e/vT61a4URF+QBW3iKUL+kPwMKmLTlYvwGjRn2H2dwGu30NWq0V\no1FLu3ZP8cMP32RvTnTlyhVKlgwmObkHjm/3sRQqtIVTpw5iMBhuuPYff/xBePiLpKWtBAJwcupL\nvXoJ+Pn5cejQMWrXrsLYscNxdXW9IV98fDzr16/H1dWV5s2bYzQac9l7iqLcC7X74D+oQEB50Hbt\n2kXDhi1IS/sAMGIyDSciYjrNmze/p3I6derBzz9r6J65mUlZexF8kN+PwWdPYDQaWbt2LVFRUWRk\nZODl5UVAQADh4eE5dijctWsX7dp1Jj7+KGXKVGbRotmUKVMmx/VGjhzJkCHJ2GyfZh05j6treVJS\nLt2yjlFRUTz9dAtEngISKF7cwo4d63IEC4qi3D8qEPgHFQgoD9orr3Rl7tyKQL+sI79Qu/Z0tm1b\neU/lXL58ma/KhTD04hkARvgWpe+RaDw8PPK2wlmmTJnC228vJi3tV0ADrKZIkT6cPn3wlnmqVGnA\n3r2vAx0BwWhsx/DhtRkw4N37UkdFUXJS2xArykPGYsnEsfQuQCawnOjoGDp16s7Zs2dvmU9EyMjI\nyP5cICIiOwg42b8/g84cv29BAEDHjh0JCEjE1bUxLi5vYDK9yrRpE26bx/EGQc2sTxrM5lqcOnXr\nNiqK8vBRgYCi5LE33+yAyTQU+AWoCBwmJWUCs2a5U7VqKImJiTnyLFu2DE9PX0wmN4KCqnJh5Ejo\n0cNxcsIESowbh15/f+f2Go1Gdu5cz9Sp3fj88xAiIzfRtGnTG9IcP36cL774gq+++orz58/ToEEo\nzs6f4ngb4Swm03QaNap3X+upKEoey9UqBA+hx7BJyiNo+fLlEhBQUUAvkJS9EJBO97TMnTv3hrRH\njx4Vk8lbYJuATbry4t97GX/xxQNqQU579uwRN7eC4uTUQ4zGDlKgQBE5cOCANGzYUnQ6J9HrjTJk\nyCcPupqK8sTJ7X1PvT6oKPdBy5Yt+e231Rw9eojrB95sNnI8y9u1axc6XUOgNp2YwRTmA3Bp4EC8\n3377ltc4e/YsY8Z8wfnzV3juuaa8/PJLd6zXiRMniI+Pp1y5cve0SRBA//6DSUkZDjhGKqzW9/ny\ny8msX78cs9mMwWBAp9PdvhBFUR466tGAouSC3W5n6dKlTJ06lejo6BvOBQaWQKsthmPBn+XAR+j1\nUTmG2/38/LDbo+nA90ynC1qEgego/tU0VqxYcdPrXrx4kZCQOnz7rfDLL7Xp2nUIY8d+cdu6Dh78\nCcHBNXnmmQGUKFGO9evX31NbL126Cvy99oDNVpbz568AjscKKghQlEdU3gxMPDwewyYpDymbzSbh\n4c+Jm1s1MZk6i8nkI/Pm/ZJ9PjExUZydCwoUEigm4CYvvdQ+RznTpk2Xbi5eYst6HPA+rgIzBf4Q\nV1cvycjIyJFn0qRJYjRev0/BQfH09LtlPRcuXChGo7/A+az0a8XDw0dsNttdt/fjj0eIyVQ/a5+C\nQ2IylZOZM2ffdX5FUe6P3N731KMBRfmXfv31V7ZuPUVKynYci/XspmvXcNq1ewGNRsPGjRsxGALI\nyBiCY4+BQBYsqI7VOj17MZ+ZM2ezpef7TLMkogU+wsAYPsXxOh7Y7QYuXLiQYzU/i8WC3X79GwTu\nWK2WHHVMTU0lPPw5IiMjsVjqAD5ZZxphNqeTlJRE/vz5c+TbsmULO3fupGjRorRRYooAACAASURB\nVLRt2xatVsvgwe9z5cpVZsyogk6nZ+DA/nTo8FruOlFRlAdOPRpQlH/p/Pnz2O2V+Hs9fgOpqVfZ\ntWsX586dY9++fYAv0BTH44GygAar1ZpdRuyIz5hmuYQOO4MZxki+AdZknV2NwSA3LBn8l9atW+Pk\nFAF8D2zBZOpA+/btc6T76KMR7N5dAItlNbAHOJ11Zilubh7ky5cvR54JEybRtOmrDBp0is6dP6dV\nq5ew2+3o9XomTRpHSsolkpLO8cEH7+VYvEhRlEdQHo1MPDQewyYpD6no6GhxcSkoECnwjYCXaLXh\n4uTkKzqdh7i7VxYwCUwViBYnp87SoEHzvwuYN0+saERAhjI4a8h+nICHQKBotW45thW+XmRkpNSr\n11zKlq0lAwcOFqvVmn3OYrFIfHy81KnTTGBpVtkTBdxFpysunp5+sm3bthxlms1mMRhMAiey8mSI\nm1uwrF+/Pi+7TlGUPJTb+556NKAoOCb9bdq0icTERGrXro2fn98d85QvX56ZM7+hS5dwUlJSgRjs\n9lJYLBeA8ly7FgHsRqPpjo+PNw0b1mfy5DmOzBER8Oqr6BFGaowMlfzAp8AooAWwhHHjRvHUU08R\nHR3NsmXLMJlMtG/fPnu2f7Vq1di8+bcc9Vq9ejXPP/8qNpuWzEwLBkNhrNZngLdwctpJmzYafvjh\nu5suA3zt2jU0GgNQPOuIE1ptIJcvX77XLlUU5RGhlhhWnniZmZk0b96W7duPodWWQGQXa9Yso2bN\nmnfMe+rUKZ57rj179pwAzlx3pj4wAmiIu3sFNm36kZCQEMephQuRl15Ck5nJxrqhtP7zMMnXAFoC\nHoAXev081qz5DpvNRqtWL2GxdESnO0/+/NvYv387BQsWvGl9rly5QrFiQaSmRgBPAUvRaDrg6uqY\nY1C8uBt//PE7np6e2XlWrlzJmjXrKVTIh27dulG9+lMcP94Wm60fsAVX1w4cPLibokWL3mPPKory\nX8j1fS8PRiX+lbi4OGnYsKEEBwdL+fLlZeLEiSIicvnyZWnSpIkEBgZKWFiYXL16NTvPqFGjJCAg\nQIKCgmTVqlU3LfcBNkl5RM2YMUNcXesLWLKGw+dJQECVO+Yzm83i719GtNohAj7XDcFvFvDKmqEf\nKS4u+eXKlSuOTIsWiV2vFwEZQ03R8J5oNK4C/gKjBRIEpohO5y4uLvkFDAKNBdIFRAyG7jJ48NBb\n1mnbtm3i4VHturcJRNzdK8qMGTNkx44dYrFYbkg/ceIkMZlKCHwizs4vSmBgiBw6dEiqVm0ger1R\nChcOVI8FFOUhl9v73gO7ayYkJMiePXtEROTatWtSpkwZiYmJkQEDBsinn34qIiJjxoyRgQMHiojI\ngQMHpHLlymKxWOTEiRNSunTpm776pAIB5V4NHz5ctNpB1908z4nJ5HVDmgsXLsi0adPk+++/lwsX\nLojFYpHmzZ8VKJqVZ6tAYQE3cXJyFycnN/HwqCRGo6cMHPi+rFu3Tlb37SuZOp0IyGc0ELBn5Z0k\nGk0BgYoCHqLRmMTZuZRArMBVgVYCfbPSfiZvvtn3lm05ffq0GI1eWa/4icAJMRrzS0JCQo60drtd\nTKb8Aoez0trF1bWpzJ6tXglUlEdJbu97D+ytAT8/v+yhUjc3N8qVK0d8fDxLly6lU6dOAHTq1InF\nixcDsGTJEl555RUMBgMlSpQgICCAnTt3PqjqK4+RmjVr4uIyH0gABJ3uK6pW/fuxwMmTJylbtgp9\n+vzOW2+toly5qrz99nusW3cJxxr7aUAd4AhGo4k9e7YTH3+CoUP/h0Zj4Jtv9jOu0bM0mDgRnc3G\neI2BAbTAscMfQFHKlClN27ZV6Nz5NZ5//jkyMvoAAUA+YDjwOxCJyfQVbdr8vZ1xYmIiXbr0okqV\nhnTs2B2TycSIEYNxcamBh0crXFxq8+mnn9x0zoOIkJGRCvhnHdFgt/uTkpKStx2sKMrDLW/ikdw5\nceKEFCtWTJKTkyVfvnzZx+12e/bn3r17y48//ph9rmvXrhIREZGjrIekScoj4OLFi7Jx40aJjY2V\noUNHicHgIs7O+aVcueoSHx8vIiJpaWlSpEiwwMfX7RcwVLy8Sgv8JtBRoK7AaNFqq8nzz7cXu90u\nNpst69v2DmnOr2LGSQRkPO0EJohW6yOwQyBKTKYK8vXX32XX66OPhojB0PW6EYpZotV6ScGCJWXq\n1O+z02VmZkrlynXFyambwBpxcuolZctWE4vFIgcOHJBFixZJTEzMbfugRYt24uz8qsARgQhxdfWW\n2NjY+9PhiqLcF7m97z3wtwZSUlJo27YtEydOxN3d/YZzGo3mtu8p3+rc0KFDs//dsGFDGjZsmBdV\nVR4j69ato02bl9HpArFYYunXrxdJSZdJSUnB29s7+/9Wr17vEh9vBqpl57XZKqPRzEKni8Rm+wGY\nhUbzLaGhnsyfPxONRkNSUhJWq4WmXGEhz+OMhS8J4G3aAEVxczPi7t4JEaFPn268+eYb2eW//XYf\nZs0K5fLlNthsBdHplrBu3YockxcPHz7M0aMJWCybAS0WSyPOnCnP/v37qVatGsHBwXfsh3nzptOt\nW1/Wrm2Kt3dBJk9eSEBAQB70sKIo98uGDRvYsGFD3hWYN/HIv2OxWCQ8PFzGjx+ffSwoKCj7eebZ\ns2clKChIRERGjx4to0ePzk7XtGlT2b59e44yH3CTlEeA3W4XT09fgbVZ37gviMlUTHbs2JEjbaFC\nZQQGCIQK/CnwmkAhqVYtVAoUKCKurq1Fr28iOp2HNGjQPPvbtNlsluY6V0nHMTFwEq8IeGfNJWgi\n4CEXL168ZR2TkpJk+vTp8vXXX8uxY8dumubQoUNiMhURsGa1I1NcXUtnz71RFOXJkNv73gObIyAi\ndO3aleDgYPr165d9vHXr1sycOROAmTNn8uyzz2Yfnzt3LhaLhRMnThAbG3tXr3cpyj8lJyeTlpYC\nNMo6UhCdrg6xsbE50jre2a8GVAFq41ii9weio30ICAigWLE4NJo0bLYFbNnyNHXqNOLKlSusef99\nFtjSMJLJt7jQm4VAUtY1vQEN3303mZ07d7Jq1SouXbp0w3U9PDzo3LkzPXv2pFSpUjdtR2BgINWq\nVcDF5SVgDkbja5QvX4yKFSvmST8pivKEyJt45N5t3rxZNBqNVK5cWUJCQiQkJERWrFghly9flsaN\nG9/09cGRI0dK6dKlJSgoSFauXHnTch9gk5RHhN1uF2/vogKLsr5JnxKTqdBNv0lv2rRJTCZv0eka\nCFS57rl9hoCLgGv2q32OV/Way6Zhw8SS9Yrgd3QTDXFZz+ALZP39jEBtCQioLK6upcXTs5F4ePjK\nrl277rkt6enp8uGHQyU8/AV5772PJDU1NS+6SFGUR0hu73tqQSHlibRz506aNn0Wm82DjIwEQkKq\ncvbsBXx9ffj227HUqFEjO22XLm8ya9ZcbLaiwD4cs/3TcewjUBL4H/A2IDR3qcgy+1F0GRn8oHOn\nqy0aoQgaTR9EfgZMQC0MhrXodAGYzVsAIzCXgIBPiY3d8992hKIoj7zc3vfUpkPKE6lmzZrExx9l\n27YFNG4cxv79BThz5meiov5Ho0YtOXnyJAC//PILP/20DJvtAI4fl+7ALzg2EWoFdEanGw9Mo4mh\nORHmg+gyMqBzZ84O+QCdPgi93p2QkP106NAWLy8tRYocpG3b5litjXAEAQDhnDlz/D/vB0VRFDUi\noDzR7HY7Tk4u2GyXATcATKb/MX58XcqUKUPTpq2xWBoCS4GrOJYN/gHoBQxCp6uKRnOOULHxm5gx\n2W3QqRPy/fdodDqsVivp6el4eDi2DBYRDh06xNq1axk48EvS0jYDPmi1n1K16ip27Vr/AHpBUZRH\nmRoRUJRc0Gg0GAzOwMXrjl3AxcWFHj0GYLF8AuwEjgL5gVpotZm4u/+GwVASEQM1M6ey3CaY7DZ2\nl69I4KYo9E7OFC8ezL59+7KDAKvVSrNmz1O9elM++OAbDIZUDIYATKYiFC06m/nzf3gAPaAoypNO\nBQLKE02j0TB48MeYTM2ACTg5/Q8fnziee+45Ll++hGMnwE+AqkAhjMaebNq0klWrvqZ8+WBq2juw\nkq64kcaP1KfOoQSOnngHuz2NuLghhIW1JikpCYAvv5zE5s3ppKUd5dq1A6SmdqJRozBiYrZy7Nh+\nSpQo8cD6QVGUJ5cKBJQn3qBBA5g1axSvv36UQYNKsXv3Ftzc3AgPb4LR+BHQDliL0ahlwYLZhIaG\nUqdOHcI9jKxiCO6kMIeX6aIJw67R45g86AS8hEgRYmJiANi37xDp6a2zzmnIzGzHoUNHKV68ODqd\n7gG1XlGUJ90DX1lQUR4Gbdu2pW3btjccmzJlAikp3fjtNz/0eiMDBvSjRYsWjpM7dzJq9x/oyGC+\nthRddSaMxkmYzWbgEo61AhKxWE7h7e0NQJUqwURELCY9vSvghF4/j0qVyv+XzVQURclBBQLKEys6\nOppx474mPT2Drl1fISws7IbzJpMJo9EZo7EkUJlx476mQoVgXixVEsLD0aWkkNaiBWcaNmSkXk+7\ndsOYNGkqkybVxmYLR6dbR7t2z7FixQp+/fVXWrV6htWrN7NxY2m0Wjd8fZ2ZMmXVg2m8oihKFvXW\ngPJEOnDgALVqNSQtrT8inri4fMLPP3+TvZIlwNq1a2nT5i1SU6MAF2APdY0N2GLUo0lMJLVpU/QR\nETi7ud1Q9rp16zhw4AAeHh706zeI9PRmiBhwdl7Mtm3r0Ov1mM1mypUrh5OT013X2WKxsGfPHnQ6\nHSEhIej1Ko5XFCX39z31m0R5In355WTS0vogMghIIT09hp4936FUqVJUqlQJgLNnz6LRhOAIAiAE\nYZk5BY0ZlmoNdNx8APEvzbJl82nQoEF22Y0aNaJEiRK8+GInkpK6ITIMAKu1LO+9N5xff50HQGZm\nJqdOnaJAgQK4/SOY+KfLly8TGhrO2bMWRDIJCCjA5s0r75hPURTlTtRkQeWxcunSJTp27E6NGk3o\n1esdUlJSbpouI8OKiBuQAJQBDpOQEE6tWo1YuXIlANWrV8dmWwPsoxJ7WUN9vICl6HjBvoWktNMk\nJ8+mVat2pKenZ5e9e/duKleuze7dlxEpl31cpCwXL14BYP/+/fj7BxAcHIq3d2G++WbybdvVv/+H\nHD9eh2vX9pOScoCDB0syZMjIXPSUoihKllwtUPwQegybpNwls9kspUtXEoOhj8BKMRpflbp1w8Ru\nt+dI69hDwFegpECr6/YQWCVFipTLTjdnzjyp4ewmF7MSLEMnBmpfl17Eza2UHDp0SE6ePCm9er0t\nBQsGCPQSmCpQSSBW4ISYTLVk9OjPxW63i79/oMDMrDKOisnkJ3v37r2hjna7XRYvXiyfffaZBAZW\nF1h13XXnSZMmz9/3PlUU5eGX2/ueGhFQHhuzZ8/m9OlMrNYJQFPM5pns2fMncXFxOdLWr1+f+fOn\nAyeB63frK8vlyxeyP71cIZgd7ka8gd80OtrSBSvHgLNZKQ6QmXkZu91OhQo1+PprPRcv9sexEqEG\nx6uHtdDrK9Gjx9OEhTVk9uzZnDt3GuiQVUZptNpG7Nu374Y6du7ck9deG8wHH8Rz4kQcOt0swAZY\nMRrnUrOm2mVQUZTcU4GA8lhYt24dvXsPwGKxXXfUjogNrVZLfHw8zZq9QNGi5WnWrG3W52bo9U44\nlgyOBC4D/alcubIj+4ED0KgRmkuXWKkx8Lw8gwUX4D0cCww1QqOpzdSp3zBhwgRSUtoAY4E3gXnA\nGKAdJpMPM2Z8h6enJw0atKFXr8XYbBpgS1Y9kxDZQcmSJbNrHhMTw/z5y0hN/QOrdTyZmTuw25fi\n4lIcF5fi1KqVwccfv38/u1RRlCeECgSUx8LAgSPJyJgE5AO6AvPR6dpQv35dfHx8qFevKWvWlOPM\nmTmsWVOe0NBwrFYrgwcPxWAAaA4UwdV1K0uWzIGYGGjUCC5eZL3ByLNSjAxex7Hh0FWgBxrNHj74\noB/t2rUlMnIvUOC6GuUDzuHu3oD33+/Irl1RDBs2mrS0SFJSFgLfAc1wdw/DZKpAp05tqF+/fnbu\ny5cvYzAU46/9D6AErq6+LFgwlT//3Mz69csxGo0oiqLklnp9UHksBAfX4eDBT4EQHEsCb6B8eYiM\n3MRnn41j2LDvsdmO4RiuF9zdK7Bx449UqVKFhQsX8vvvGylWzI+33uqNe3w8NGwI58+T8dRT+G3/\nk8SMrkA0MBz4Co1mKUajFjAAZqpWDeGPP/YC3wDFgHfw8jrPpUsnaNmyHWvXxmOxWHGMPDi4ugYy\nduzbhIaG/j0KkSUxMZGSJYNJTPwcaIVGMxsfn885deogzs7O97s7FUV5hOT6vpcH8xQeKo9hk5S7\nMGrUZ2IyVROIElgnJlMR+e2332TMmM/FaCwl4CtgzppoZxaTyV8OHjyYs6BDh0T8/Bwz8ho1Ekti\nori4eApsE3hDwF3ARZycPAUissrbI0ZjAXF2dhcoJ1BG9HovmTNnrpw+fVqMRm+BMwLeAuuz8iwX\nDw9fSUlJuWWboqKipFSpSqLXGyU4uKYcOnToPvagoiiPqtze99SIgPJYsNvtjBgxhmnTfsLJyYnh\nwwfQuHEjSpeuSFraehzbB18C2mAwLCAszIfly39Bo9H8XUhsLDz1FCQkwNNPw/LlYDKxYMFCOnbs\njl5fg8zM/YSF1WHJkrXAleysLi5NGDeuLVFRB0hJSed//2tHs2bNOHXqFOXK1SY9/QywHngVSMPN\nzcTKlYsIDQ39L7tJUZTHUG7veyoQUB5LcXFxVKlSlytXUoAooDjwHRrNdFq1KsaCBRE3rsx39Kjj\ncUB8PNa6dfmsYRgRKzbi5ZWPsWM/xsvLi/3791OkSBFef/0t9uzZB2wHKgCX0WiC2LdvPRUr3jiT\nX0SoU6cJe/cWISOjEzrdcvz9f+Pgwd2YTKb/qjsURXmMqUDgH1QgoAC88cZbTJ/ugc0mOL6JDweO\n4OY2jL17t1G6dOm/Ex875ggCzpxhr3s+GqRkcE1sQBvgaVxdB7Nnz1YCAwP58MNhfPrpVGy2hsDv\nQC0gkoIFXblw4ehN63Lt2jXeffcjduzYS9mypZk4cTS+vr73tf2Kojw5cnvfU28NKI+lCxeuYrMF\n4pg4+DwwCFfXT9m8+fcbg4Djxx2PAc6c4WCBgjQyt+KaXMOx4uAxwITZ/Crz50cAMGXKD9hs44BV\nQF8gEL0+kwkTRtyyLu7u7kyePJG9ezcyd+50FQQoivJQUYGA8lhq27Y5JtOnwCEc7/IbGTDgTUJC\nQv5OdPKkIwg4fZp9rh7UvGzmqvVdQAd4AZ2AHWi1ZgwGx2MErVaHY0nixcB+NJqVtGsXzquvvvKf\ntk9RFCWvqEBAeWxcvXqV2bNnM2PGDMLCGjN48Ovkzx+Ou3stOnaszkcfvQc4NvvZ8csvpNeuDXFx\n7HZ2oX5qDVKoA2zIKs2e9e8juLou49VXXwVg0KB+mEwvA8fQaoPx8LjKp5+O+c/bqiiKklfUHAHl\nsRAbG0tISF0yMqqh0RjRaNaj0Qh2O9hsVnQ6LRUqVGXx4h/p3fplvvwzipJiJVJnoInNnSTmAkWB\nJkBZtNoE3NySaN26GcOGfUCpUqWyr/XTT3OYO3cZBQp48PHHA2581PAPNpuN0aM/Z+nSNfj5efP5\n58MoU6bMfe8PRVGeHGqy4D+oQODJk5mZia9vaa5caQt8AbTAsRfAMhxr87cCeqLXH6Vm4eXMPn2G\nUpLGLqoTTksS+QbogWNC4SXgVZo3d2Hx4vk4OTnlqm69evVnxoxdpKV9gEYTjYfHF8TERFG4cOFc\nlasoivIXFQj8gwoEnjyRkZHUrt0qaxJfraw/s3AEBOBY9/8nCjOEDdQkEDuRVCOM1SRyCmgIuAPl\ngGQMhiMkJMRSoECBm1zt3hiNHmRkxAKOCYIuLh354ou69OjRI9dlK4qigHprQFGw2+1ZawJMxLEM\nsAtw8LoUByiEsJ5WBGJnr8ZEOBEk4glMBmoA6cAaihW7SnT09jwJAoCsBYus1x3JRKtVP3aKojw8\n1IiA8lCz2Wxs3LiR5ORk6tSpc9NX7ywWCxUr1uboUR12+34c+wm4A62BDPxYwAaNliBJIzUggIHV\n6zE5IoLMTC1QCVgCeOHuXp7Nm3/Ose5/bgwY8CHffLOKtLT30On+JF++GcTEROHj45Nn11AU5cmm\nHg38gwoEHh9Wq5UmTdqwe3c8Wm1RRHaxbt2vVK9ePUfaK1eu0L//h/z552H8/DzYuHEzZnMaRQ16\ntrkY8Lt6FWu5chg2bQJvb2JiYqhWLRSzeSOOYGAXJlMz4uOPkS9fvjxrg4jw9dffsWTJGgoXLsiI\nER9QrFixPCtfURRFBQL/oAKBx8e0adPo23cOaWmrAD3wM2XLTuDgwZ13zGu321k8eTJle71FsNg4\noNESN2MGzTt2yE4zZ848unZ9E4PBn8zMs/z003SefbbN/WuQoijKfaACgX9QgcDj4+OPB/PJJxpg\nWNaReDw8qpGUdO6Oea8ePkxCufIEi41oytOIz0k1tScu7vANz/+vXLlCXFwcJUqUyNORAEVRlP+K\nmiyoPLZq1aqJq+tc4Bwg6PUTqVat5p0zXryI8zPPECw2YihHY9ZykWZkZBT8f3t3HhBVuf9x/D0z\ngDJgaqlYoGKIIoi466+ycCFy19zNpUxt1ex2y7LfvWn3XtR2tcwWLa+ZW2maW26hlqWppRYtdsVE\nRJMUlXVg5vn9Mcgvs7qZygjn8/qLOWfmzPMdjp4P8zzneXjhhWln/YO58soradKkyTkh4ODBg8yb\nN4+VK1dSVFR0cQsTEbmMKAjIZatr16489NAQ/P2vpUKFK4mK2sz8+a8B8N1339GxYw8aN27LuHF/\nx+VyeV+UmQkdO+L8/nu+sdlpz2v8SAjwPW73YZ59dh7Tpr30u+/78ccfEx3dnHvuWcaAARNp2/aW\n/z++iEg5o64Buezl5eWRk5PDVVddhc1mY+/evTRpch0ez6NAaxyOJOrXP8noQb0YtXgxjj17KKhT\nh3qHMjnk9gNigN1AP+BuwsJuJy0t5TffLyKiCfv3PwH0Ajw4nYlMndqfESNGlEa5IiLn5UKve37/\n/SkivhUYGIifnx9ZWVlUqVKFfv2G4PHcBDwOgNvdhiNfV6HN3/fjMFl4IiJ4sm0HDr15NXAH8D3w\nI/AsYP/VfzDGGHbs2MGxY8c4ejQdaFO8x05eXisOHUovjVJFREqdugbksvfyy68SHFyVmjXr0KBB\nM3744QDeqYO9qvAja3HT1GTxvc3Jm8OGsevIEbyndx2gAxAKZOPvP5CxY+866/jGGG67bQTt2vVn\n4MCp5OcX4XBMxrvw0EECA+dzww3Xl1K1IiKlS10Dclnbvn077dr1Ijd3ExCB3T4Zh+NZCgsDgAFU\npiFrGUsrcvkPtUnwj+dYhffxeBqSm7sbeAaoDvwFOMXo0bczdepzxTP+eb3//vsMGvS/ZGd/AjiB\n+fj53Q/kYrPZSEpK4q9/HVv6xYuI/AHqGpAyzxjDgQMHKCoqIiIigqKiIjZu3Ehubi7ffvstHk93\noB4AHs9DeDyPA06u4F0+4DCtKGI/dtpxP4c9/8TkDsHjeRGYC9yP9zQvYvjwQUyb9vw57+997+vx\nhgCA3ng8Qzh5MovAwEAcDkdpfAwiIj6hICA+5XK56NatP1u2fILNFkBkZBgejyE11Y3NVgOPZxs2\nW3XABQQAH3PVVWGEVgrmlQNHaE0RqTjpaPfDr85b1LHVYf/+W4uP/i5wMzAWu30Ly5fP4MSJE1St\nWvWsNjRr1gy7/RngEBCGzTaT+vWbEhwcXIqfhIiIb2iMgPjUlCnPsmVLIXl5B8nNPcDevTl8+eVV\nZGd/yunTK8jN/QcVKuQSHNyUSpV643T2Y9Gs6eyoUYk2nCAjoCJvDh3E3lOH2b9/N927dyYwcDpw\nDFgHzAOux+N5lIKCGJKTkwHvzINnXH/99TzxxFgCAhridF5DaOhLLF/+tg8+DRGR0qcgID61ffte\n8vL64/1rfyEezwGMac+ZU9OYtjidFVm+/EVef70/Kds+pP3TT+O/fTvUqsXV36Qwcc5rBAUFATBp\n0gQ6dAjA4aiN91uEvOJ3MsBpkpM3U6lSNQICKtK+fTdOnDgBwCOPPMiXX+7i8cfvZ/z4sVSuXLl0\nPwgRER/RYEHxqfHjn+D5578lP/8NoCYwHngb2ABUxWYbwa23enjnnTmQnQ2dO8OWLZyuXJlpt/al\nSe+edOnS5ZzjZmdnM3r0wyxatJvc3BEEBHxESMhWMjNPkZf3ARBJQMADtG//E6tXv8O+ffto1eom\nCgo6AB4CAzexc+dHhIeHl+KnISJy/rTWwC8oCJQtubm53HRTZ1JSDpGbewzIwhsGXgDAZqvI0qVv\n0qNjR+jSBTZt4oifPx3sHUlxtcXpfJ2JE0czZsy9fP3111SsWJH69etjs9nweDy89NJMkpO3ERER\nRoUKdiZNcuF2Tyl+9x9xOhuSk/MTt946hGXLYoonKQK7/QkGDjzMW2+95ouPRUTkD9NaA1KmOZ1O\nPv10Axs3zqNKlWBgPjAJSAacVKjQkcyDB6FbN9i0ibwqVbgloAUprpXAY+TmruPxxx+nQYNm3HBD\nf5o160Dnzn0oLCzEbrczevS9vPvuHJ566l/Url2bChX24O0mANhN1arVAcjIOIbH06ikXR5PLBkZ\nmaX5UYiI+ISCgPicw+Hg0KF0mjdvhs02CqgMJAKTCLJtpc+cOfDhh1CzJiseeoh9RAJn5gEowuXy\n48CBRLKzvyY39z9s2pTN9OnnricwZMgQIiNPERTUnsDAUTidg5g1ayoA3bp1wOmcjHeBo8M4nU/R\nvXuHUqlfRMSX1DUgPjdz5ms89NAkcnPHAzuAuQQGVsO/6Di761xN+Pf7jO+KBQAAHd5JREFUICQE\nkpNJrVCB2NhW5OS8BDTFZuuI99e9FGhWfMSX6dx5A9988x0//PAt114bw5Il/6ZRo0YUFBSwZMkS\nsrKyiI+Pp2HDhgC43W4eeOARXn/9VcDGfffdx9NP/wu7XVlZRC5vGiPwCwoCZU9YWEPS098EWgIe\n7PYHGHu3jclfp+D/4YdQowYkJ0PxRXvr1q3ceecDZGQc4tSp4xjTDYgEkoBC/P074XDsJD//ReBW\nYAHVqk3k4MFvCAwM/N22nDl3fj7zoIjI5UxjBKRM+PHHH7nttpE0b96B0aP/Sk5OTsm+wkIXMBsI\nAoLw93zEqDWrvSGgenXYuLEkBADUqFGDzMwfMSYK72yAPYAVeFcZDKN27Uz8/SOAwcX7h1NQUIlV\nq1Zx4MCB3/0HY7PZFAJExFJ8GgSGDx9OSEgIsbGxJduOHz9OQkIC9evX5+abbyYrK6tk36RJk4iM\njCQqKoq1a9f6osnyJ+Tl5dG6dTsWLarMrl3jeP31dDp16sOePXtYtWoVUVF1gc3AAQLI4F3SabB/\nP1SrBhs2QEzMWce7884HOH78AU6d+hBjlgD3ERBwNYGB+dx4YzNWrlxEUdEh4GTxK46Tnf0DQ4c+\nRMOGrenbdxhutxsREQGMD23evNns2rXLNGrUqGTbww8/bKZMmWKMMWby5Mlm3LhxxhhjvvrqKxMX\nF2dcLpdJTU01ERERxu12n3NMH5ckv2Ljxo2mUqVWBjwGjIFC43BUMRUrhhins5mBSgZeNwHkm+V0\nNQbMcYefMbt3n3OsEydOmGrVrjWwu/hYxsBE0759oklOTi45J+6+e6wJCmpoAgJGG4ejtrHZbih+\n/xzjdLY1M2fOLO2PQUTkkrjQ655PvxFo27btOfO+L1++nGHDhgEwbNgw3nvvPQCWLVvGwIED8ff3\nJzw8nHr16rF9+/ZSb7OcP++iPYU/21KE211Ifv775Ob+AHTHn+0soh/dWMFPOHm0+Q3QuHHJK4wx\njBp1H1WrhpKZeQyYhneZ4JM4nSsZNKgfN910U8ngvhkznmPRomeYNCmcypU9GDMT750GTnJze7Fz\n55elVb6IyGXtshsjcPToUUJCQgAICQnh6NGjABw+fJiwsLCS54WFhZGenu6TNsr5adOmDWFhDgIC\nRgCLCAjogcNRAwgGrsSPp1nI2/RgOcfxJ9Fu+KzQw5w5c0uOMX36DGbNSga+xNuNsByogsNxDQMH\ntuSOO24/6z1tNhudO3fmL3/5C3FxTXE43ive4yIwcBWxsQ0ufeEiImXAZb364H8buPVb+yZMmFDy\nc3x8PPHx8Re5ZXI+AgIC+OST9fztb//k668X0qBBQ2bN2oXbnYMfx1jAYHqRzQkCSaCQXZ6x8HkL\n7r77EU6ePElCQgcWLlyBx/MPoG7xUV8FxjNyZAdefnn6777/G29M5/rrEzh9+l2Kio7Ttm0z7rnn\n7ktdtojIJZGcnFyygNrFcNkFgZCQEI4cOULNmjXJyMigRo0aAISGhpKWllbyvEOHDhEaGvqrx/h5\nEJDLQ+XKlZk27emSxy1aNGP03e1505VPb7ORLBwk4GEXnfHeBgj5+T8wduw4goNDyck5DFTCezsg\nwDc4HCe58cbr/ut716lTh337drNnzx6cTieNGjXSnQEiUmb98g/ciRMnXtDxLruuge7duzNnzhwA\n5syZQ8+ePUu2L1iwAJfLRWpqavEiMa182VQ5Dzt27CApKYmXXnqJo0ePcvvgQZzokkBvU4inUiUe\njG7MTpoDzYtfsR14AmNWcPr0d3g824CVQE9gCPAk/frdzIABA/7Q+wcGBtK6dWtiY2MVAkREfsan\nEwoNHDiQTZs2kZmZSUhICE8++SQ9evSgX79+HDx4kPDwcBYtWkSVKlUASEpKYvbs2fj5+TF16lQS\nExPPOaYmFLr8vPfeewwadBcFBfF4PGtwkMOiioHcmp+NqVSJlQ88wP1zl/PDD6OACUBfYB7eMQT/\nPw6kUqV4Bg+OpkaNGvTu3fus205FRKxKMwv+goLA5WPjxo3Mm/cOb7+9gPz8ycD/Ymcuc5jLYOaR\njY1B1a5hY14LCgqOUlR0CngQeByYDtwFfAg0AdIIDGzO3r2fEBER4buiREQuMxd63bvsxghI+TB3\n7luMHPkQBQWPAMOAR7ETzRvMKw4BQXRxONmadQNFRQvw3grYGngACAAaA68BHYEIHI5v+cc/nlQI\nEBG5yBQE5KIoKChgzJhHWL58NU5nIAcOpOHxLAQSALBzhFksZSgfk00QnXiTrWYYHneL4iOcBr4D\nPsUbAP4KvALMAQYCLlJTf8AYoz5+EZGL6LIbLChl08iRY5g7dz9HjrzH/v0GjycIqAaADQ+v8R23\nU0AONnr5t2aX8wEGDuyH0zkbOAB8g3f54VjgKSAMaID324TpuN0ZvPnmBt555x1flCciUm4pCMgF\n279/P/Pnzycv7xXgTbwX9t7Avdj4lFe4heHsIhc7Sde15bZXh7B583Lmzp3No48OpWLFOByOm3A4\nTuCdLKgicC9g8N4pMAyoSk5Obz77bJdPahQRKa80WFAuSEZGBtHRzcnKKgKeBJ4D6gHNseHgZaZz\nF8fJAx6LbcU/t24gODj4rGOc+X2tW7eO3r1vw+UKwuXKBGoBY/EOGnThdCYydeptjBgxohQrFBG5\nvGkZYvGpxYsXk5eXCEwBxgPX4e3jf4+XeK4kBPQJqMZXITWpUKHCOcc4M4Nk8+bN2b17G2PG9MXf\nvzewEO8dBC2AurRqFcTtt99eWqWJiFiCgoBcEGNMcRL9GO/I/1WAnRe5gXs4TT7Qg9WscqXz8cf5\nzJjx8jnHcLvdDBp0J9dcU5fo6JYkJ3+G0/kBMALvOIFbsNlak5q6H5fLVYrViYiUfwoCckF69eqF\n270cOAF8DnRmKrW4j5kUAD2pzDq6ADeSl9eGPXu+PecY06a9xLJl/8HlyqCg4Ch794YTHx+PzbYH\nWAv8E2Pe5fjxamzcuLE0yxMRKfcUBOSC1K5dG4ejEO8iQOE8TxXG4KYAG72owAcsA/KBnthsM2jW\nLOas1xtj+OijneTmDgWCAD8KCkby/vtri28TPHOHqw0IwO12l15xIiIWoCAgF+THH3/E43EAB3iG\nvzKWqbiw0ZtrWU0H4CbAHxgH5NCvX18ANm/ezDXXXIvd7mD9+g8ICFiH9y4BgPV4PP8DXIWf363A\nWhyOvxEUlEq7du1Kv0gRkXJMEwrJn2aMISGhJ+6iVjzFjTxEbnEIuJKVHMN7ehUAFYDv8fe3U6VK\nFVauXEnXrn3x3l1QhVOn2mO3r8LPL4aioiuAY8CHeDwHCQ4eQGTkFOrWDeP55zdxxRVX+K5gEZFy\nSEFA/rRjx47xdcpXJGHjYXIpBPrixwoKgLeB+UALbLZmBAau47nnXsBms9G//zBgBdAeSAOaYrP5\n0aZNDbZurYrHsw7vksM7qFMnnB07NviqRBGRck9BQP6UEydOsOOzz5hQlM+juCjCQX9eZTmPAxFA\nXxyOAKpWvYJ77w2na9dlrFy5lmrVapGTU4A3BIB3roAWuN0evvjic664wp/s7Edwu6sRGPgKzz33\nts9qFBGxAgUBOW87duygY4euPF7gz/jiEDCABSylD7ATWILN1onatVNp2DCKDh06sH37Tp555h1y\nctYB8cAGoAPebwR2A+vJzX2LoUN/ol69WuTm5tG79xqaNWvmszpFRKxAMwvKeatdO5rhaTFM4B2K\ngEH8hcU8C+TgXUHwIN6M+TzeGQEfp169KPbsGQvcindp4d7AlUAm3hkJxwAzuO22L3jrrVd9UJWI\nSNmkZYil1BQWFjJ48EhuT/uGCXyNGzuDGcFiZuJdNfAg4MB7Ws0E+gGQm1tIZuZ0bLb9eM/VdsBY\nwsPnc+TIteTntwc+wumcwsCBM3xSm4iIVSkIyB+WlPQ0Dd9dxwQMbmAIQSykKgEBwQQF/UBRURF+\nfnayswMoLPz5nal2GjaM5PTpp8nP3w9AxYrvsmLFRubNW8zs2b0ICAhg4sQn6dKli09qExGxKnUN\nyB/2St2G3HXgGzzYGMq/mUciEM2wYT35+98fo3Hj1uTkTAV+BJKAaUABgYGPsGrVQurWrcvChQsB\n6N+/P3Xq1PFdMSIi5cSFXvcUBOSPmTIFHn0UD3A7c5jLUAD8/Hryxht9OH36NA89tIO8vFnFL1gA\n3E379u0YP/5+OnTo4KuWi4iUaxojIJfeM8/Ao49ibDaGG3/mUql4RxoOxzauuuou3G43dvuRn72o\nBYGBNtavX1I8VbCIiFyOFATk9z3/PDz8MAB3mgrMIRAYClQGjuPxBHPrrUNJTEygevUfKCwcisvV\nGKdzJhMnPqEQICJymVPXgPy2qVNh7FgA7rI14FXzEzAKqAL8E+gLvAbk4XR25sknu5Ofn8/hw8dI\nTGxH9+7dfdZ0ERGrUNeAXBrTp5eEgHvtfrzquQUIBP5V/IRXgPvxrgroJDe3D8nJm3n//UU+aa6I\niPw5Wn1QzvXSSzBmDAAPB1VlpvEHTgJVf/akOsDS4p+LgPdZu3Y1mZmZpdpUERG5MAoCcpYttw2G\n++8HYDQJPJMzAGNqAu/i/TZgKfAR3qmBnwVaAg0BBy5XFJMmTfFNw0VE5E/RGAEpsfWO4Vz35hsA\njOFKptMaCAIGAy8DXwPhQB7QDfgHsAS4Bm8YiCUg4CiHDx/gqquuKv0CREQsSPMI/IKCwJ/0+usw\nciQAD/I3XuBFIADvX/7+wCfAAGA/3mmEc4CaeAcO3gZsAmpTqdKXbNnyNnFxcaVfg4iIBV3odU9d\nAwKzZ8OoUQA8RD9e4EngZsCFdzAgeLsAsrHbuwAzgHY4HA78/bOAU8Bo4H48nqOEh4eXdgUiIvIn\nKQhY3Zw5MGIEGEPqPfcw07kRmIz3L/1CoA/wPnAfEEydOj/QqdN6xoy5joyMfSxY8G+czgUEBz9B\nUFAvFi+eS+XKlX1YkIiInA91DVjZ3LkwbBgYw6nHHmNNkyZMmzaLQ4fSSUs7jMcTDlyLtxsgEmiB\nwzGe6tUr8NFHa4mIiADg9OnTpKenU6tWLYKCgnxXj4iIBWmMwC8oCPxB8+bB0KHg8fBM1RDGnTyN\nxxOA906AAmAcMAb4AFgEGKAHcA92ex5t2qzl448/8FnzRUTES0HgFxQE/oD582HwYPB4mOSswvjc\nLsBPwB1Av+InXQfUB8LwTh6UB3TBu5jQf6hWLYFjx1J90HgREfk5DRaU87NwYUkIWBLbhPG5Drz9\n/wV47w44oy/wHvAMkIV3zMDrADgcb9GoUaPSbbeIiFwSmmLYShYvhttuA4+Hb/v1o987H+C9wK/H\ne1fAKMAN5ANTgO7Ap9jtPzBgwC0sWXItfn5VqFatAnPnrvFZGSIicvGoa8Aq3n0X+vcHt5uPb7qJ\nm7Zsx+1pBaTgzYPVgP8AVwAN8IaAZ4C7qVr1FY4fT+fgwYNkZ2cTGRmJv7//b76ViIiUHo0R+AUF\ngV+xdCn06wdFRcyrVZfBaSeB/wUm4e3/TwK+KX7yFXgHBuYBtXA6jzN9+j8ZPvx2X7RcRET+C60+\nKL9v2bKSELD1hrYM/uiL4h03A1cBtwMV8Y4PWA0cB7YBkwkJOcWCBW8RHx/vg4aLiEhpUBAoz95/\nH/r2haIitrRuQ/tPvgJuwXuHwCPAPCAGbyioVfxzMLAXu93J6tVLadq0qa9aLyIipUBBoLxauRL6\n9IHCQl4LqsK9O2Iocn+Fd9bAOKAj3sWCAGKBCkAofn7VCA4uYPXqVQoBIiIWoDEC5dHq1dCzJ7hc\n7G3XjqabKuL2rMI7J8ALeFcTzMO7jsBxbLa2tG0bRv/+PbjuuuuIioqiYsWKvqxARET+II0RkLN9\n8AH06gUuF9x/P+O+34/bUw3YjffiPwqoDvwd74DBr/D3z2DWrGXUq1fPhw0XERFfUBAoT9at834T\nUFCAuftu9tx5Jx/+TyLeyYKCgRvxdg0sxjtDYBIVKlTh3XfnKgSIiFiUugbKiw0boGtXyM/HjBrF\ngON5LF/xAfn5LryTBX2F9xuBr4CrgQ0EBw/k5Mkj2O2aYFJEpKzSFMMCu3dDt26Qnw8jRvD2DTew\nYtW35Ocvw3tbYA5wZfHPkfj5RRMcPJDlyxcqBIiIWJyuAuVBTAx07w7Dh8Mrr7AxOZnc3AS8F/88\nvHcH9AUaAoH07duEgwe/pV27dr5stYiIXAY0RqA88PODt94Cu51Va9Ywe/Y8oDbexYTyi3/eA9wA\nZJCYmEjVqlV92GAREblcaIxAOZKSkkJMTBugEAjCu4CQH1AVuBtYT0TEIVJSdhAQEODDloqIyMVi\nuTECa9asISoqisjISKZMmeLr5lw2Tp06RfPm7QAH4AGewjtPQBPgBE7nZCZPjmfv3m0KASIiUqJM\nfSPgdrtp0KAB69evJzQ0lJYtWzJ//nwaNmxY8hwrfiNw7NgxwsKicLk8eC/8R4EjQHvgE2y2k3zz\nzS7q16/v03aKiMjFZ6lvBLZv3069evUIDw/H39+fAQMGsGzZMl83y+fatu2Iy2XHO02wE+8KgrnA\nSipVKmTv3m0KASIi8qvKVBBIT0+nVq1aJY/DwsJIT0/3YYt8Lysri+++2w9Uwzs2IBvYBRhsNgcH\nDnxDTEyMT9soIiKXrzJ114DNZvtDz5swYULJz/Hx8eV+GV27vRC3uwDv4MAUvGMEAli2bD5XXnml\nbxsnIiIXVXJyMsnJyRfteGUqCISGhpKWllbyOC0tjbCwsHOe9/MgUN5VqVKFzp17smrVbtzuXMCN\nw1GRPXs+Izo62tfNExGRi+yXf+BOnDjxgo5XpgYLFhUV0aBBAzZs2MA111xDq1atNFgQcLlcTJiQ\nxKZN26lXrxZPP/0PatSo4etmiYhIKbjQ616ZCgIAq1evZuzYsbjdbu68804ee+yxs/ZbMQiIiIh1\nWS4I/DcKAiIiYiWWun1QRERELi4FAREREQtTEBAREbEwBQERERELUxAQERGxMAUBERERC1MQEBER\nsTAFAREREQtTEBAREbEwBQERERELUxAQERGxMAUBERERC1MQEBERsTAFAREREQtTEBAREbEwBQER\nERELUxAQERGxMAUBERERC1MQEBERsTAFAREREQtTEBAREbEwBQERERELUxAQERGxMAUBERERC1MQ\nEBERsTAFAREREQtTEBAREbEwBQERERELUxAQERGxMAUBERERC1MQEBERsTAFAREREQtTEBAREbEw\nBQERERELUxAQERGxMAUBERERC1MQEBERsTAFAREREQtTEBAREbEwBQERERELUxAQERGxMAUBERER\nC1MQEBERsTAFAREREQtTEBAREbEwBQERERELUxAQERGxMJ8EgcWLFxMTE4PD4WDXrl1n7Zs0aRKR\nkZFERUWxdu3aku07d+4kNjaWyMhIHnjggdJucpmRnJzs6yb4jJVrB9Wv+pN93QSfsXLtF4NPgkBs\nbCxLly7lxhtvPGt7SkoKCxcuJCUlhTVr1nDvvfdijAHgnnvuYdasWezbt499+/axZs0aXzT9smfl\nfxBWrh1Uv+pP9nUTfMbKtV8MPgkCUVFR1K9f/5zty5YtY+DAgfj7+xMeHk69evXYtm0bGRkZnD59\nmlatWgEwdOhQ3nvvvdJutoiISLlzWY0ROHz4MGFhYSWPw8LCSE9PP2d7aGgo6enpvmiiiIhIueJ3\nqQ6ckJDAkSNHztmelJREt27dLtXbEhERgc1mu2THLwsmTpzo6yb4jJVrB9Wv+q1bv5Vrj4iIuKDX\nX7IgsG7duvN+TWhoKGlpaSWPDx06RFhYGKGhoRw6dOis7aGhob96jO+///78GysiImJRPu8aODMY\nEKB79+4sWLAAl8tFamoq+/bto1WrVtSsWZMrrriCbdu2YYxh7ty59OzZ04etFhERKR98EgSWLl1K\nrVq1+PTTT+nSpQudOnUCIDo6mn79+hEdHU2nTp2YMWNGydf8M2bMYMSIEURGRlKvXj1uueUWXzRd\nRESkXLGZn/9JLiIiIpbi866BP0uTEp1tzZo1REVFERkZyZQpU3zdnEti+PDhhISEEBsbW7Lt+PHj\nJCQkUL9+fW6++WaysrJK9v3WeVAWpaWl0a5dO2JiYmjUqBHTpk0DrFN/fn4+rVu3pkmTJkRHR/PY\nY48B1qn/DLfbTdOmTUsGXFup/vDwcBo3bkzTpk1LbiW3Sv1ZWVn06dOHhg0bEh0dzbZt2y5u7aaM\n+vrrr823335r4uPjzc6dO0u2f/XVVyYuLs64XC6TmppqIiIijMfjMcYY07JlS7Nt2zZjjDGdOnUy\nq1ev9knbL7aioiITERFhUlNTjcvlMnFxcSYlJcXXzbroNm/ebHbt2mUaNWpUsu3hhx82U6ZMMcYY\nM3nyZDNu3DhjzK+fB2632yftvhgyMjLM559/bowx5vTp06Z+/fomJSXFMvUbY0xOTo4xxpjCwkLT\nunVrs2XLFkvVb4wxzz77rBk0aJDp1q2bMcY6578xxoSHh5uffvrprG1WqX/o0KFm1qxZxhjv+Z+V\nlXVRay+zQeCMXwaBpKQkM3ny5JLHiYmJ5pNPPjGHDx82UVFRJdvnz59v7rrrrlJt66WydetWk5iY\nWPJ40qRJZtKkST5s0aWTmpp6VhBo0KCBOXLkiDHGe7Fs0KCBMea3z4PyokePHmbdunWWrD8nJ8e0\naNHCfPnll5aqPy0tzXTo0MFs3LjRdO3a1RhjrfM/PDzcZGZmnrXNCvVnZWWZunXrnrP9YtZeZrsG\nfosVJyVKT0+nVq1aJY/P1GwFR48eJSQkBICQkBCOHj0K/PZ5UB4cOHCAzz//nNatW1uqfo/HQ5Mm\nTQgJCSnpJrFS/Q8++CBPP/00dvv//7dtpfptNhsdO3akRYsWvPbaa4A16k9NTaV69erccccdNGvW\njJEjR5KTk3NRa79k8whcDL6alKissfoESmfYbLbf/SzKw+eUnZ1N7969mTp1KpUqVTprX3mv3263\n88UXX3Dy5EkSExP58MMPz9pfnutfsWIFNWrUoGnTpr85r355rh/g448/5uqrr+bYsWMkJCQQFRV1\n1v7yWn9RURG7du3ixRdfpGXLlowdO5bJkyef9ZwLrf2yDgK+mpSorPllzWlpaWclwvIsJCSEI0eO\nULNmTTIyMqhRowbw6+dBWf99FxYW0rt3b4YMGVIyj4aV6j+jcuXKdOnShZ07d1qm/q1bt7J8+XJW\nrVpFfn4+p06dYsiQIZapH+Dqq68GoHr16vTq1Yvt27dbov6wsDDCwsJo2bIlAH369GHSpEnUrFnz\notVeLroGjMUnJWrRogX79u3jwIEDuFwuFi5cSPfu3X3drFLRvXt35syZA8CcOXNKfqe/dR6UVcYY\n7rzzTqKjoxk7dmzJdqvUn5mZWTIqOi8vj3Xr1tG0aVPL1J+UlERaWhqpqaksWLCA9u3bM3fuXMvU\nn5uby+nTpwHIyclh7dq1xMbGWqL+mjVrUqtWLb777jsA1q9fT0xMDN26dbt4tV+sAQ2lbcmSJSYs\nLMxUrFjRhISEmFtuuaVk37/+9S8TERFhGjRoYNasWVOyfceOHaZRo0YmIiLCjB492hfNvmRWrVpl\n6tevbyIiIkxSUpKvm3NJDBgwwFx99dXG39/fhIWFmdmzZ5uffvrJdOjQwURGRpqEhARz4sSJkuf/\n1nlQFm3ZssXYbDYTFxdnmjRpYpo0aWJWr15tmfr37NljmjZtauLi4kxsbKx56qmnjDHGMvX/XHJy\ncsldA1apf//+/SYuLs7ExcWZmJiYkv/jrFL/F198YVq0aGEaN25sevXqZbKysi5q7ZpQSERExMLK\nRdeAiIiI/DkKAiIiIhamICAiImJhCgIiIiIWpiAgIiJiYQoCIiIiFqYgICIiYmEKAiIiIhamICAi\nf9pnn31GXFwcBQUF5OTk0KhRI1JSUnzdLBE5D5pZUEQuyN/+9jfy8/PJy8ujVq1ajBs3ztdNEpHz\noCAgIheksLCQFi1aEBgYyCeffFJml3sVsSp1DYjIBcnMzCQnJ4fs7Gzy8vJ83RwROU/6RkBELkj3\n7t0ZNGgQ+/fvJyMjg+nTp/u6SSJyHvx83QARKbv+/e9/U6FCBQYMGIDH4+G6664jOTmZ+Ph4XzdN\nRP4gfSMgIiJiYRojICIiYmEKAiIiIhamICAiImJhCgIiIiIWpiAgIiJiYQoCIiIiFqYgICIiYmH/\nB2H+zOtjC0adAAAAAElFTkSuQmCC\n",
"text": [
""
]
}
],
"prompt_number": 6
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"
\n",
"
\n",
"**Eventually, the benchmark:**:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import timeit\n",
"import random\n",
"random.seed(12345)\n",
"\n",
"funcs = ['py_lstsqr', 'cy_lstsqr']\n",
"\n",
"orders_n = [10**n for n in range(1, 6)]\n",
"times_n = {f:[] for f in funcs}\n",
"\n",
"for n in orders_n:\n",
" x = [x_i*random.randrange(8,12)/10 for x_i in range(n)]\n",
" y = [y_i*random.randrange(10,14)/10 for y_i in range(n)]\n",
" for f in funcs:\n",
" times_n[f].append(min(timeit.Timer('%s(x,y)' %f, \n",
" 'from __main__ import %s, x, y' %f)\n",
" .repeat(repeat=3, number=1000)))"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 13
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import matplotlib.pyplot as plt\n",
"\n",
"labels = [('py_lstsqr', 'regular Python (CPython)'), \n",
" ('cy_lstsqr', 'Cython implementation')]\n",
"\n",
"\n",
"matplotlib.rcParams.update({'font.size': 12})\n",
"\n",
"fig = plt.figure(figsize=(10,8))\n",
"for lb in labels:\n",
" plt.plot(orders_n, times_n[lb[0]], alpha=0.5, label=lb[1], marker='o', lw=3)\n",
"plt.xlabel('sample size n')\n",
"plt.ylabel('time per computation in milliseconds [ms]')\n",
"plt.xlim([1,max(orders_n) + max(orders_n) * 10])\n",
"plt.legend(loc=2)\n",
"plt.grid()\n",
"plt.xscale('log')\n",
"plt.yscale('log')\n",
"max_perf = max( py/nu for py,nu in zip(times_n['py_lstsqr'],\n",
" times_n['cy_lstsqr']) )\n",
"min_perf = min( py/nu for py,nu in zip(times_n['py_lstsqr'],\n",
" times_n['cy_lstsqr']) )\n",
"ftext = 'Using Cython is {:.2f}x to '\\\n",
" '{:.2f}x faster than regular (C)Python'\\\n",
" .format(min_perf, max_perf)\n",
"plt.figtext(.15,.8, ftext, fontsize=11, ha='left')\n",
"plt.title('Performance of least square fit implementations in Cython and (C)Python')\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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Ugo2NDR4+fKjSdWGMMcYYKw1PT09cvny5xPOpfYxc/nbk7du3oampKXdXnKen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qXC/PnzsWrVKvTs2VPK8InoISqNCkcyj+BCwQVxzFHhiInhE/Fs0LNcSiUisjBZllZXrlyJ/Px8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\nAABJRU5ErkJggg==\n",
"text": [
""
]
}
],
"prompt_number": 14
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"
\n",
"
\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Numba vs. Cython vs. regular (C)Python & Numpy"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[[back to top](#sections)]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Numba is using the [LLVM compiler infrastructure](http://llvm.org) for compiling Python code to machine code. Its strength is to work with NumPy arrays to speed-up the code. If you want to read more about Numba, please see refer to the original [website and documentation](http://numba.pydata.org/numba-doc/0.13/index.html)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here, we implement a linear regression via least squares fitting (with vertical offsets) by solving to fit *n* points $(x_i, y_i)$ with $i=1,2,...n,$ via linear equation of the form \n",
"$f(x) = a\\cdot x + b$. \n",
"\n",
"\n",
"\n",
"$\\Rightarrow \\pmb a = (\\pmb X^T \\; \\pmb X)^{-1} \\pmb X^T \\; \\pmb y$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"I have described the approach in more detail in this [IPython notebook](http://sebastianraschka.com/IPython_htmls/cython_least_squares.html)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Matrix equation "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In order to obtain the parameters for the linear regression line for a set of multiple points, we can re-write the problem as matrix equation \n",
"$\\pmb X \\; \\pmb a = \\pmb y$ \n",
"\n",
"$\\Rightarrow\\Bigg[ \\begin{array}{cc}\n",
"x_1 & 1 \\\\\n",
"... & 1 \\\\\n",
"x_n & 1 \\end{array} \\Bigg]$\n",
"$\\bigg[ \\begin{array}{c}\n",
"a \\\\\n",
"b \\end{array} \\bigg]$\n",
"$=\\Bigg[ \\begin{array}{c}\n",
"y_1 \\\\\n",
"... \\\\\n",
"y_n \\end{array} \\Bigg]$ \n",
"\n",
"With a little bit of calculus, we can rearrange the term in order to obtain the parameter vector \n",
"$\\pmb a = [a\\;b]^T$ \n",
"\n",
"We will implement this matrix equation in \n",
"- Python/CPython: `py_mat_lstsqr()` \n",
"- Numba: `numba_mat_lstsqrs()` \n",
"- Cython: `cy_mat_lstsqr()`"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### \"Classic\" approach "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In the more \"classic\" approach that is often found in statistics textbooks, we calculate the following parameters as follows:\n",
"\n",
"$a = \\frac{S_{x,y}}{\\sigma_{x}^{2}}\\quad$ (slope)\n",
"\n",
"$b = \\bar{y} - a\\bar{x}\\quad$ (y-axis intercept)\n",
"\n",
"where \n",
"\n",
"\n",
"$S_{xy} = \\sum_{i=1}^{n} (x_i - \\bar{x})(y_i - \\bar{y})\\quad$ (covariance)\n",
"\n",
"\n",
"$\\sigma{_x}^{2} = \\sum_{i=1}^{n} (x_i - \\bar{x})^2\\quad$ (variance)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We will implement this \"classic\" approach in\n",
"- Python/CPython: `py_lstsqr()` \n",
"- Numba: `numba_lstsqrs()` \n",
"- Cython: `cy_lstsqrs()` "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"
\n",
"
\n",
"
"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import numpy as np\n",
"import scipy.stats\n",
"from numba import jit"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%load_ext cythonmagic"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Matrix equation:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def py_mat_lstsqr(x, y):\n",
" \"\"\" Computes the least-squares solution to a linear matrix equation. \"\"\"\n",
" X = np.vstack([x, np.ones(len(x))]).T\n",
" return (np.linalg.inv(X.T.dot(X)).dot(X.T)).dot(y)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 59
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"@jit\n",
"def numba_mat_lstsqr(x, y):\n",
" \"\"\" Computes the least-squares solution to a linear matrix equation. \"\"\"\n",
" X = np.vstack([x, np.ones(len(x))]).T\n",
" return (np.linalg.inv(X.T.dot(X)).dot(X.T)).dot(y)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 60
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%cython\n",
"def cy_mat_lstsqr(x, y):\n",
" \"\"\" Computes the least-squares solution to a linear matrix equation. \"\"\"\n",
" X = np.vstack([x, np.ones(len(x))]).T\n",
" return (np.linalg.inv(X.T.dot(X)).dot(X.T)).dot(y)"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### \"Classic\" approach:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def py_lstsqr(x, y):\n",
" \"\"\" Computes the least-squares solution to a linear matrix equation. \"\"\"\n",
" x_avg = sum(x)/len(x)\n",
" y_avg = sum(y)/len(y)\n",
" var_x = 0\n",
" cov_xy = 0\n",
" for x_i, y_i in zip(x,y):\n",
" temp = (x_i - x_avg)\n",
" var_x += temp**2\n",
" cov_xy += temp*(y_i - y_avg)\n",
" slope = cov_xy / var_x\n",
" y_interc = y_avg - slope*x_avg\n",
" return (slope, y_interc)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 61
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"@jit\n",
"def numba_lstsqr(x, y):\n",
" \"\"\" Computes the least-squares solution to a linear matrix equation. \"\"\"\n",
" x_avg = sum(x)/len(x)\n",
" y_avg = sum(y)/len(y)\n",
" var_x = 0\n",
" cov_xy = 0\n",
" for x_i, y_i in zip(x,y):\n",
" temp = (x_i - x_avg)\n",
" var_x += temp**2\n",
" cov_xy += temp*(y_i - y_avg)\n",
" slope = cov_xy / var_x\n",
" y_interc = y_avg - slope*x_avg\n",
" return (slope, y_interc)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 62
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%cython\n",
"def cy_lstsqr(x, y):\n",
" \"\"\" Computes the least-squares solution to a linear matrix equation. \"\"\"\n",
" cdef double x_avg, y_avg, temp, var_x, cov_xy, slope, y_interc, x_i, y_i\n",
" x_avg = sum(x)/len(x)\n",
" y_avg = sum(y)/len(y)\n",
" var_x = 0\n",
" cov_xy = 0\n",
" for x_i, y_i in zip(x,y):\n",
" temp = (x_i - x_avg)\n",
" var_x += temp**2\n",
" cov_xy += temp*(y_i - y_avg)\n",
" slope = cov_xy / var_x\n",
" y_interc = y_avg - slope*x_avg\n",
" return (slope, y_interc)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 63
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### NumPy and SciPy libraries:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def numpy_lstsqr(x, y):\n",
" \"\"\" Computes the least-squares solution to a linear matrix equation. \"\"\"\n",
" X = np.vstack([x, np.ones(len(x))]).T\n",
" return np.linalg.lstsq(X,y)[0]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 70
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def scipy_lstsqr(x,y):\n",
" \"\"\" Computes the least-squares solution to a linear matrix equation. \"\"\"\n",
" return scipy.stats.linregress(x, y)[0:2]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 71
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Verifying that the different approaches yield the same results"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import random\n",
"random.seed(12345)\n",
"\n",
"n = 500\n",
"x = [x_i*random.randrange(8,12)/10 for x_i in range(n)]\n",
"y = [y_i*random.randrange(10,14)/10 for y_i in range(n)]\n",
"\n",
"np.testing.assert_array_almost_equal(\n",
" py_lstsqr(x, y), py_mat_lstsqr(x, y), decimal=6)\n",
"np.testing.assert_array_almost_equal(\n",
" numpy_lstsqr(x,y), py_lstsqr(x, y), decimal=6)\n",
"np.testing.assert_array_almost_equal(\n",
" scipy_lstsqr(x,y), py_lstsqr(x, y), decimal=6)\n",
"\n",
"print('ok')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"ok\n"
]
}
],
"prompt_number": 80
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Visual checking the least square fit"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%pylab inline"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from matplotlib import pyplot as plt\n",
"\n",
"slope, intercept = py_mat_lstsqr(x, y)\n",
"\n",
"line_x = [round(min(x)) - 1, round(max(x)) + 1]\n",
"line_y = [slope*x_i + intercept for x_i in line_x]\n",
"\n",
"plt.figure(figsize=(7,6))\n",
"plt.scatter(x,y)\n",
"plt.plot(line_x, line_y, color='red', lw='2')\n",
"\n",
"plt.ylabel('y')\n",
"plt.xlabel('x')\n",
"plt.title('Linear regression via least squares fit')\n",
"\n",
"ftext = 'y = ax + b = {:.3f} + {:.3f}x'\\\n",
" .format(slope, intercept)\n",
"plt.figtext(.15,.8, ftext, fontsize=11, ha='left')\n",
"\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
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c12Aw4OPjw6FDh/D19eXw4cNZ0oOCgjh06JDF2vb+++/TtWtXPDw8CAgIoGLF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\nImIDFaqIiIgNVKgiIiI2UKGKiIjY4C99KgLU7MAmZwAAAABJRU5ErkJggg==\n",
"text": [
""
]
}
],
"prompt_number": 45
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Benchmarking:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import timeit\n",
"import random\n",
"random.seed(12345)\n",
"\n",
"funcs = ['py_mat_lstsqr', 'numba_mat_lstsqr', 'cy_mat_lstsqr', \n",
" 'py_lstsqr', 'numba_lstsqr', 'cy_lstsqr',\n",
" 'numpy_lstsqr', 'scipy_lstsqr']\n",
"\n",
"orders_n = [10**n for n in range(1, 6)]\n",
"times_n = {f:[] for f in funcs}\n",
"\n",
"for n in orders_n:\n",
" x = np.asarray([x_i*np.random.randint(8,12)/10 for x_i in range(n)])\n",
" y = np.asarray([y_i*np.random.randint(10,14)/10 for y_i in range(n)])\n",
" for f in funcs:\n",
" times_n[f].append(min(timeit.Timer('%s(x,y)' %f, \n",
" 'from __main__ import %s, x, y' %f)\n",
" .repeat(repeat=3, number=1000)))"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 66
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import matplotlib.pyplot as plt\n",
"\n",
"labels = [('py_mat_lstsqr', 'matrix equation in reg. (C)Python & NumPy'), \n",
" ('numba_mat_lstsqr', 'matrix equation in Numba'),\n",
" ('cy_mat_lstsqr', 'matrix equation in Cython & NumPy'),\n",
" ('py_lstsqr', '\"classic\" least squares in reg. (C)Python'),\n",
" ('numba_lstsqr', '\"classic\" least squares in Numba'),\n",
" ('cy_lstsqr', '\"classic\" least squares in Cython'),\n",
" ('numpy_lstsqr', 'least squares via np.linalg.lstsq()'),\n",
" ('scipy_lstsqr', 'least_squares via scipy.stats.linregress()'),]\n",
"\n",
"\n",
"matplotlib.rcParams.update({'font.size': 12})\n",
"\n",
"fig = plt.figure(figsize=(10,8))\n",
"for lb in labels:\n",
" plt.plot(orders_n, times_n[lb[0]], alpha=0.5, label=lb[1], marker='o', lw=3)\n",
"plt.xlabel('sample size n')\n",
"plt.ylabel('time per computation in milliseconds [ms]')\n",
"plt.xlim([1,max(orders_n) + max(orders_n) * 10])\n",
"plt.legend(loc=2)\n",
"plt.grid()\n",
"plt.xscale('log')\n",
"plt.yscale('log')\n",
"\n",
"max_perf = max( py/nu for py,nu in zip(times_n['py_lstsqr'],\n",
" times_n['cy_lstsqr']) )\n",
"min_perf = min( py/nu for py,nu in zip(times_n['py_lstsqr'],\n",
" times_n['cy_lstsqr']) )\n",
"\n",
"ftext = 'Using Cython is {:.2f}x to '\\\n",
" '{:.2f}x faster than regular (C)Python'\\\n",
" .format(min_perf, max_perf)\n",
"\n",
"plt.figtext(.14,.15, ftext, fontsize=11, ha='left')\n",
"plt.title('Performance of least square fit implementations')\n",
"plt.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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cx1HPnj3p+++/p7S0NNq4cSNxHEd///23kC8sLIz++OMPyszMpKSkJOrXrx9Z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\n6dIlTp48WaFutYk6Tps2jZiYGD7++GOCg4M5fvw4o0ePJj8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AtX3WG33IzL1O29nZVRi+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\nWVncMnCgNkNco0LhgkLqDtUFxqzDrNjH2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xSBC89WYrXyQVERJ3Jz4eBBcDjwdzi41mRi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\nEu2k9A7zpmB0AZfffjlpaWkMGzaMOXPmUFtb2+prHzhwgLFjx5KYmMi4c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HLt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\nAICkHiAvheE4HrYHAAAAAElFTkSuQmCC\n",
"text": [
""
]
}
],
"prompt_number": 69
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}