mirror of
https://gitlab.science.ru.nl/mthesis-edeboone/m-thesis-introduction.git
synced 2024-12-22 19:43:30 +01:00
531 lines
220 KiB
Text
531 lines
220 KiB
Text
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Perform a grid search to find the timing error"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"import sys\n",
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"# Append parent directory to import path so lib can be found\n",
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"sys.path.append(os.path.dirname(os.path.abspath(os.getcwd())))\n",
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"\n",
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"import numpy as np\n",
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"rng = np.random.default_rng(12345)\n",
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"\n",
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"import matplotlib.pyplot as plt\n",
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"from scipy import signal\n",
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"import copy\n",
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"\n",
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"from lib.signals import DigitisedSignal\n",
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"import lib.util as util\n",
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"\n",
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"\n",
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"km = 1e3\n",
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"ns = 1e9\n",
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"\n",
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"# monkey patch correlation_lags into signal if it does not exist\n",
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"if not hasattr(signal, 'correlation_lags'):\n",
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" def correlation_lags(in1_len, in2_len, mode='full'):\n",
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" r\"\"\"\n",
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" Calculates the lag / displacement indices array for 1D cross-correlation.\n",
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" Parameters\n",
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" ----------\n",
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" in1_size : int\n",
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" First input size.\n",
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" in2_size : int\n",
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" Second input size.\n",
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" mode : str {'full', 'valid', 'same'}, optional\n",
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" A string indicating the size of the output.\n",
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" See the documentation `correlate` for more information.\n",
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" See Also\n",
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" --------\n",
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" correlate : Compute the N-dimensional cross-correlation.\n",
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" Returns\n",
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" -------\n",
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" lags : array\n",
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" Returns an array containing cross-correlation lag/displacement indices.\n",
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" Indices can be indexed with the np.argmax of the correlation to return\n",
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" the lag/displacement.\n",
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" Notes\n",
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" -----\n",
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" Cross-correlation for continuous functions :math:`f` and :math:`g` is\n",
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" defined as:\n",
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" .. math::\n",
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" \\left ( f\\star g \\right )\\left ( \\tau \\right )\n",
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" \\triangleq \\int_{t_0}^{t_0 +T}\n",
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" \\overline{f\\left ( t \\right )}g\\left ( t+\\tau \\right )dt\n",
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" Where :math:`\\tau` is defined as the displacement, also known as the lag.\n",
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" Cross correlation for discrete functions :math:`f` and :math:`g` is\n",
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" defined as:\n",
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" .. math::\n",
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" \\left ( f\\star g \\right )\\left [ n \\right ]\n",
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" \\triangleq \\sum_{-\\infty}^{\\infty}\n",
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" \\overline{f\\left [ m \\right ]}g\\left [ m+n \\right ]\n",
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" Where :math:`n` is the lag.\n",
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" Examples\n",
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" --------\n",
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" Cross-correlation of a signal with its time-delayed self.\n",
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" >>> from scipy import signal\n",
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" >>> from numpy.random import default_rng\n",
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" >>> rng = default_rng()\n",
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" >>> x = rng.standard_normal(1000)\n",
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" >>> y = np.concatenate([rng.standard_normal(100), x])\n",
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" >>> correlation = signal.correlate(x, y, mode=\"full\")\n",
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" >>> lags = signal.correlation_lags(x.size, y.size, mode=\"full\")\n",
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" >>> lag = lags[np.argmax(correlation)]\n",
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" \"\"\"\n",
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"\n",
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" # calculate lag ranges in different modes of operation\n",
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" if mode == \"full\":\n",
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" # the output is the full discrete linear convolution\n",
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" # of the inputs. (Default)\n",
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" lags = np.arange(-in2_len + 1, in1_len)\n",
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" elif mode == \"same\":\n",
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" # the output is the same size as `in1`, centered\n",
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" # with respect to the 'full' output.\n",
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" # calculate the full output\n",
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" lags = np.arange(-in2_len + 1, in1_len)\n",
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" # determine the midpoint in the full output\n",
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" mid = lags.size // 2\n",
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" # determine lag_bound to be used with respect\n",
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" # to the midpoint\n",
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" lag_bound = in1_len // 2\n",
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" # calculate lag ranges for even and odd scenarios\n",
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" if in1_len % 2 == 0:\n",
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" lags = lags[(mid-lag_bound):(mid+lag_bound)]\n",
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" else:\n",
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" lags = lags[(mid-lag_bound):(mid+lag_bound)+1]\n",
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" elif mode == \"valid\":\n",
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" # the output consists only of those elements that do not\n",
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" # rely on the zero-padding. In 'valid' mode, either `in1` or `in2`\n",
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" # must be at least as large as the other in every dimension.\n",
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"\n",
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" # the lag_bound will be either negative or positive\n",
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" # this let's us infer how to present the lag range\n",
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" lag_bound = in1_len - in2_len\n",
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" if lag_bound >= 0:\n",
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" lags = np.arange(lag_bound + 1)\n",
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" else:\n",
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" lags = np.arange(lag_bound, 1)\n",
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" return lags\n",
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"\n",
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" signal.correlation_lags = correlation_lags"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Setup signal\n",
|
|
"########################\n",
|
|
"\n",
|
|
"signal_t_length = 200e-9\n",
|
|
"signal_sample_rate = 5e9 # Hz\n",
|
|
"signal_time = util.sampled_time(\n",
|
|
" sample_rate=signal_sample_rate,\n",
|
|
" start=0,\n",
|
|
" end=signal_t_length\n",
|
|
")\n",
|
|
"double_signal_time = np.concatenate((signal_time, signal_time[-1] + signal_time)) \\\n",
|
|
" - (signal_time[-1] - signal_time[0])/2\n",
|
|
"\n",
|
|
"fc = 50e6# MHz\n",
|
|
"\n",
|
|
"if True:\n",
|
|
"\n",
|
|
" shift = -25.8e-9\n",
|
|
" signal_pulse1_center = 125e-9 # 100 ns\n",
|
|
" \n",
|
|
" if not True:\n",
|
|
" signal_1 = DigitisedSignal(signal.gausspulse(signal_time - signal_pulse1_center, fc=fc),\n",
|
|
" signal_sample_rate)\n",
|
|
" signal_2 = DigitisedSignal(signal.gausspulse(signal_time - signal_pulse1_center, fc=fc), \n",
|
|
" signal_sample_rate)\n",
|
|
" signal_2.t_0 = shift\n",
|
|
" else:\n",
|
|
" signal_1 = DigitisedSignal(np.sin(2*np.pi*(signal_time)*fc/5.4) + np.sin(2*np.pi*(signal_time)*fc),\n",
|
|
" signal_sample_rate)\n",
|
|
"\n",
|
|
" signal_2 = copy.copy(signal_1)\n",
|
|
" signal_2.t_0 = shift\n",
|
|
" \n",
|
|
" signal_1.periodic = False\n",
|
|
" signal_2.periodic = False\n",
|
|
" del signal_pulse1_center\n",
|
|
"\n",
|
|
"\n",
|
|
"del fc, signal_t_length, signal_sample_rate\n",
|
|
"\n",
|
|
"\n",
|
|
"# Pre calculated values\n",
|
|
"sig_1 = signal_1(double_signal_time)\n",
|
|
"sig_2 = signal_2(double_signal_time)\n",
|
|
"\n",
|
|
"\n",
|
|
"if True:\n",
|
|
" fig, ax = plt.subplots()\n",
|
|
" ax.plot(double_signal_time * ns, sig_1, label='Regular')\n",
|
|
" ax.plot((double_signal_time) * ns, sig_2, label=\"Shifted\")\n",
|
|
" ax.plot((double_signal_time) * ns, signal_2(double_signal_time + shift), 'r--', label=\"Cheat\")\n",
|
|
" ax.set_xlabel(\"Time (ns)\")\n",
|
|
" ax.set_ylabel(\"Amplitude\")\n",
|
|
" ax.set_title(\"Lag: {:.4g} ns\".format(shift*ns))\n",
|
|
" plt.legend()\n",
|
|
" plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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9cA9WynglN2zc4mn2KaRUNIlh+ynfu76u/tzsscNnQiIE0U7aP1WSHBfsNo26UCeZtuqf/9rOCBaXk2t+fi9/+/bPq5+HwU6NISgMNo1op/LpqlM/6yGy+cX8ku3KeL5+jdQM7g9AeuMOJijCbcoiP2J/5fumRIllBcWwfZTPwDoiS5crw+w7C4DOJcuqHm7kUw/xsw8fwTuwP+uDm+4IN9g5MQSFwaYR61Y+HUpEB666LdIo6FQEhb2pntoaN10OD+xoRR2DatWZpt0Vv87maBRDZyif3WtJNSvjuWfsCUDH8tVVD7f7h2+w75cfM2PtQi548M/IaLT6uRjstBiCwmDTKBMU9RBp2+zhOhweFg7aFeHzYTWbeHWPmXw9cNRWmGgfIqwKPk8T+AYqCYvVEtwANq9SLgUgsI52i4tFQ3bHMWt/jvjeP1gxdlrlMQqoa28m3H8Qw7s2cOqnLxP8et0m3IjBzoohKAw2jVJB4aiBWGCzk+TennE0l15xO5iUf4o3nXo1b846cWvMtO8QVgWpu1H52RQNLNyqhCHnQpE7mL33Mfzsx3dQ3+jni6YRtGaqi0nJZCS1wU6STf2wDFL8QeGVW5YsuaPzhz/8gbFjxzJhwgQmTZrERx99xPDhw2lrK385eu655/jzn/8MQGtrK3vttReTJ0/m3Xff5bbbbtvka//mN7/hhhtu2OJ72BoYgsJg0ygVFHYfZJKQ3DwTRiCaxOfIL3Reh4VANLWls+xb5ARFg6KBhTdBA4u0KeeZrWCvgUg77aEEdW4btW4bpyx4jZrX/lvVUF2hGDWxEDTUYxuitHWJrDE0Cj0++OADXnjhBT755BM+//xzXnvtNYYMGaJ7/HHHHcdPf/pTAF5//XV22203Pv30U4YMGbJZgqIvYQgKg00jJyj86qdP+YxvXnXPb9/1e37y4O9y33/6n7/ws1+dvQUT7IOEW8FsU4Squ2HTTHXhdnCp2oTqD/rZLVdxzpO3YDWb+OHHTzFq9hNVDdW1oZUOlw9zv364BymBA4n1Gzb1bnYampubaWhowG63A9DQ0MDAgQMB+Mc//sGUKVMYP358rsz4vffeyyWXXML8+fP58Y9/zOzZs5k0aRI/+clPWLFiBZMmTeKaa64B4Prrr2fPPfdkwoQJRSXF//CHP7DrrrtyyCGHsHTp0l6+Y32MPAqDTSMrKOyqgMgKjFgAvP03ebj+61diczlz360WE97ADtYSNdxWkHfSoESOpVNgruK/X6QNBk5UfnfVIyPtjF63jPUjhipDe2twdFX3vFotbg669CEePHcvhjkgZrERDX8DnNkv/RQ2LNi6Y/YfD0f+ueIhhx12GL/97W/ZZZddOOSQQzj99NM54IADAEVofPLJJ9x2223ccMMN3HnnnbnzJk2axG9/+1vmzp3LLbfcwqpVq1i0aFGukOArr7zCsmXL+Pjjj5FSctxxx/HOO+/gdrt59NFH+fTTT0mlUkyZMoWpU6du3fveTAxBYbBpxLrB5skvcvYt0yjckSDh/nkBk/L6cEU3IXP5m0C4VTE5QXHZE2+/yudJmRcyAK56MoFmaqMB1tUr48W8fvzt1TnH29W6UPUeG/5aJ7td9RT/d9RuVJn6t9Ph8XiYN28e7777Lm+++Sann356zgdx0klK6ZOpU6fy1FNaPdf0eeWVV3jllVdyNZ9CoRDLli0jGAxy4okn4nK5AMWU1VcwBIXBphHrzgsHyJueYl2bNZw7EiLgq8l9z/h8eOJhSKfBbN6CifYhoh0agqKtZ0ER61b8PznTUz1y9edYM2lM9UoeS8Jfi2vVkqqmYXr/f9z+9I00fuc+PP1HYzULOsLJzbmj3qWHN/9tidlsZtasWcyaNYvx48dz3333AeTMUWazmVRq03xqUkp+9rOfccEFFxRtv+mmm1D6ufU9DB+FwaYR68o7siEvNGKbrlHEkml8sRDS789tk2rFTRnYuh3Ntiux7uJwYqgu8il7TPYcVx2mLmWbubYWgHRtHd5Id1VRZ5ZlX3LElx/gc1gRQvB/7z3AxAf/uUm3sjOxdOlSli3LJzPOnz+fYcOGbfI4Xq+XYDCY+3744Ydz991354oOrlu3jo0bN7L//vvz9NNPE41GCQaDRUUItzfbVaMQQtwNHANslFKO09g/C3gWyNZXfkpK+dtem6BBOYWLHmyRMzsYjjN/+CScu+6R2xbafTwPTjqSk5JpXFs6175CLJB/TjmfTnfP58XVxSV7rrMWUzrGG6On0TR6NACfnHUB14w8go91hijE1K4IGVv/JgD2XLMQc9sOVqV3KxIKhbj00kvp6urCYrEwevRo7rjjDl544YVNGqe+vp59992XcePGceSRR3L99dezZMkSZsxQkig9Hg8PPvggU6ZM4fTTT2fSpEkMGzaMmTNnbovb2iy2t+npXuAW4P4Kx7wrpTymwn6D3iQeAE+B03pzNIrudRBpJ2gZyQ9O/iV/P2lSbldwxn78YoOfQx2eqgXFktlv03+3EdSOHFr9HHqTQuGa/dwUQWH35s/1mrjm5Cu576CDALA1NrDR1k4slcFhrWyqs3S0E7PYcKg28Ji7hobuHaxcylZk6tSpvP9+ecfFwrLf06ZNy5UKP+ecczjnnHPKfgd4+OGHi8bI9tcu5ec//zk//3nfq8G1XU1PUsp3gB0sxGUHJxbIL1ygOLYR1WsUUsKDJ8Mds4h2KE5Yj70wj8KKKZMmEKwuGmf5vMXsfvQswjMPrPYOepd0UimiaN8KgkIVyl4RwavmngxqW8c1b99HaNmKHoezdXUQdOf9SzFfDc5wsMIZBgYK3wQfxQwhxGdCiJeEELrNc4UQ5wsh5goh5rbuaLWC+hKJMNg9+e8mk2IaqWbhA+harTTvkWk87z7Mx7eczaD338ztHvjVEr66/nhEla0gVz/yDAAf1o0gEu2DHduymlbWfGT3AWITBUXWbOWDRUmevOUqajYopdgbuzdy8YePE1/as6AI2FysGTAi9z3pq8EbrvLvZrBTs71NTz3xCTBMShkSQhwFPAOM0TpQSnkHcAfAtGnTdsBemn2ERFjVIgqw11RvempZlD9t7UKawp2Ebfl/ho46PwDJjs6qhnPMm0O708fVR13ByNYIU4baq5tHb5GNBstqEpsiWLNaWlZQ2L0QkdSHAiRrlW32OsWpHWvvWTH/98mXYTWbyBpBok0D6HDV4MpkciVUDAy06NP/OqSUASllSP19NmAVQjRs52ntvGQykAyDzV283eGr3vTUslj5rB+NvVN5K7b586YsV52yoCa7qxvPue5rWhoH0RDpYsMXfbART+liD2p9rM00PcWUdyCrKiCcDcpnor1nwRqMpYrMfJ+dfh4HXXS3ISQMeqRP/wsRQvQXamCxEGI6yny3oKa1wRaRVBPhSgWFzaP0W6iGrlXg6QcNu2LrVkyE9pp8FJVT1ShkoGfbuZSSx3c7gMXHncUb/76QwbfdVN0cepNS0xNsmqAwWcGiakl2L8QkSYsFHEq0krNByadIdXb1ONzV9/ya41+6L/fdY7eQSGWIp9JV3YrBzst2FRRCiEeAD4BdhRBrhRDfF0JcKIS4UD3kFGChEOIz4GbgDCk3s0ypwZaT7fVcanqyuSFepaAIbgDvAKgZjD2kmEscdflF1FXjJYMgE+x5vEAsxSN7HEznqWexsaYB84bm6ubQm5QWUQQlRLZaQWH3KqU/smPEJAln3rzmaVIERboKQTHxq8/p15Gv7TTqy/k88OgviCz5sue5GOzUbFcfhZTyzB7234ISPmvQF9ATFHYPdFfZ5zrQDLXDoGYwFk+Cl3bfh8P6NeV2u5xW/rXXyQzcdSKTexhqY0snwzvW0d81lpC/AXdbHwz11DM9da6q7tzCCDO7FwaaWeMahdqdAl+Nh92vfIJLj53ApApDSSlxx8NkvPl5+BJR9ls9n+b1G2D87lXe0M6D2Wxm/PjxpFIpRowYwQMPPIC/IDn0m8BvfvMbPB4PV1999RaN06dNTwZ9jKx5SdP0VGV9pmCzUjzQ0w+GW/j7yedibsy7naxmE3875FyWTNq3x6FCcz/lrX9fwC7z3yda14ivc/MbKG0zcqanQo2iBqJdPZ8bDxYLGLOV+FQvX52wZ34oq5m0y0V3rHIZiVgkjisZB19+PKvqD4p1GJFPWjidTubPn8/ChQupq6vj1ltv3d5TAhShn8lkevWahqAwqJ6Eno/CDYkq4vGTMaXukXdgrizFAGuk7LB6kqSqiHoKblAEQ83AJmKNTfgD7ZvdQGmbkau2W6AZbIqPovA8ICyc+EzFOSaXfvwkuz37SMWhQm2KmU/U5AWF3a8IikRHV89z2cmZMWMG69YpvTtWrFjBEUccwdSpU5k5c2auzHhLSwsnnngiEydOZOLEiblkvRtvvJFx48Yxbtw4brrpJgB+8pOfFPWo+M1vfsNf//pXQLsE+apVq9h999256KKLmDJlCmvWrOnVUuV9PTzWoC+h66NQNQop8/Z0LUKqfdzbX+mt8GqMvy/4Ofzq0qLD7rn3GtL9+sG33qk4nWirEtdQO7CJlQccyWvU84dMpm8VE0yEwOoGU8GcHDWKYM2ki7eXUpoFD7j/tZFx/d6GK/PbDl3yHumWekC/uk0kFOPTAbuSGZxvvOOoVyKmkl3fAI1i1qzybaedBhddBJEIHHVU+f5zzlF+2trglFOK96nZ1NWQTqd5/fXX+f73vw/A+eefz+23386YMWP46KOPuOiii3jjjTe47LLLOOCAA3j66adJp9OEQiHmzZvHPffcw0cffYSUkr322osDDjiAM844gyuuuIKLLroIgMcee4yXX35ZtwT50KFDWbp0Kffccw+33XZbr5cqNwTFzkzrUnjtN3DEnxW/QU9kwzW1NIpMikc+WMbStiS/PnYP7SqYUVVLcNUrPzGJWZar0HGHC2e4Z2d2ukN5S7Y31hOdMo2HWr38MgOOPiQnlLyTkmIkWS0hESo2SZUSD0J9SdpQXGIWxVFKcZcHVw8Z1t01dZz4nb9y55H5/tquxjqWNgwlbLb1eBs7I9FolEmTJrFq1SqmTp3KoYceSigU4v333+fUU0/NHRePK4meb7zxBvffr1QjMpvN1NTU8N5773HiiSfidiv/Z0466STeffddLrvsMjZu3Mj69etpbW2ltraWoUOHcvPNN2uWIB86dCjDhg1j7733Bnq/VLkhKHZm3v4LLJ2tvOEf87eej89qFPZSZ7YXpOSOR99kpXMQx+xWz7RdNJoYFYaKuuohKUnby/8JJpwuagJV+Buyb8J+P00iwMT1S+lqnkr/oZveQGmbkYxo+3RAEQQ9CYqCsFopJSKRwWQrNq/F3V7qNqyqOI2Q6sPwFrSddQ1oYv/v38a1+49lr57vZPtSSQNwuSrvb2jYJA0iS9ZH0d3dzTHHHMOtt97KOeecg9/vzzUh6olKQZqnnHIKTzzxBBs2bOCMM87IHa9VgnzVqlU5YVPpuG1VqtzwUezMrFFrjn79YXXHVwqP7ZS8+Y8LWXXdsVh+/n/a5xeGitrcZBICaS9//U+53Nhi5b6LUubvNo1bTrgMXC6GrvqCZx+4itgH1dRR7UUSYcX0VEhW0PYUUlzio4inMpgSGUzW4sUn4fHiiFQOJrC++zaz77mUujX5Uh/Z5LtwYgfrUb6Vqamp4eabb+aGG27A6XQyYsQIHn/8cUBZsD/77DMADj74YP75T6VsezqdJhAIsP/++/PMM88QiUQIh8M8/fTTuaqwZ5xxBo8++ihPPPEEp6imMb0S5KX0dqlyQ6PYWUlEoHuN8nvbl9W15qwU9bRBMYekhAnnF4vQpLCNqhCkEmawl7+rpFwe7NGeBcXifqMJHzqcS4TA1U/pAhdt6WN1vhIamezZSKZKSYqpBKRiRYIiGk/hT6RJW4vNdSmvDzRMeIVk1q9nj40rWW+35qdhMXH3E9di3bAvzKpCo9yJmTx5MhMnTuTRRx/loYce4oc//CG///3vSSaTnHHGGUycOJG///3vnH/++dx1112YzWb++c9/MmPGDM455xymT58OwHnnnZczF40dO5ZgMMigQYMYMGAAoLRf1SpBbi7xu+kdt61KlRuCYmela7XyOeIAWPk2BNb17KdIhMFkgVKbts0D3cpCtWCP6QzY8LX2+fHiUNHAmFqS9hpKjS9L9j6ITzwDKC/CXIxv9QoGOpW5uAcogiLR2scS97V8FDnTU4UyJVkhUhAeG47GaZk2kpFDigXM6+f9hCv3+g6fVphGRjXTORvrctuEEIzpWEvnqmV6p+3UZN/WsxS+nb/88stlx/fr149nn322bPuPfvQjfvSjH2leY8GC8l7geiXIFy5cWNVx26JUuWF62lnJJnyNnFX8vRKJkPJ2XGoDtbmhSxKz2+keszv1nRuVVqallISKrp4xlNjM8naga/aaxb17Ht/jdL7zxM1cfJcSFujurwiKTEcfExTJiEaCoqolVDI95RL1CjSKjOCdw/fCNLr4v63HaSUcr1yGI6PWznKptaFyY9qdWMI7WI9yg62OISh2VrKZ1MNV1TSrYVQiEQabt3y7XdEognW1MGIE1nSK6Oo15cfFAsobshoS2p1w4MqUL5b+TJz6DWu0hU0BznCQhEft0VDrJW62IqqsOttrJEJgLY16KnBm61FaEBAIx5LEU2YsqbBSoFFl9LLPueHpPxNft15/vEA3KWHC7iv++8WcbiyRKsuvGOy0GIJiZyWsRhU1qaUbQi09n5PVKEqxuWGclS8P2Zf4tOncPv0k2qM6GoVqdkqmM+x30/v4ny2v+Dr53dm89s/zSDZvKNuXRUqJOxIk7VPGc9osXHncNcw/oI81Q0xENExPBeGxesTKNQq5eDGX/uVBWJxSNBWVuu5WjlvyDrF1+n/D1tr+vD9mzzJtMOFwYanCH7Q9MMq6bRs257kagmJnJdwKzjrl7dbug1AVTmAtxywoC984K137j8c2ZTJ/PvBcWjx15cfFunM290gijTmewmwtFygmr/LGHWvv0p1KPJXBGw/nBIUQgv9NPICVA0b2fB+9iabpafM0ilR3No+FIkFhqfUDEKugTb15wAn88rw/lW1fM3QMXxc0M+orOBwO2tvbDWGxlZFS0t7ejsOxab3SDWf2zkqkDdxqjSVPE4SrKKinIygSZie2tjT1/YK43Tbc8QidLe0wrNgeTjyQ0ygioQg1GUnGkizL6DarZSaiXd1oGLoACMSS+GJh2gqKtE1p+4q6Bc1w/Lie76U3kFINjy3RKCx2JSCgKkGRd2Yng+o2q1C1EaWYokUtxVFJsIZKelFkeea0S+mKJJjV0730MoMHD2bt2rUY3Sq3Pg6Hg8GDB2/SOYag2FkJt4NLFRTupio1ihD4yv+BdQZT9Ls1zPCTP0SeJFl002nMj10D068rPjDWBb5BAETVQnQma0YJA7U6c4dZVDt6okKxukAkya+PvpLTj52V23bJK3fhT8fhF9/t+V56g2QUkDpaWA89PDSc2elsjw6bKCrCaKtVzXkVSo2f94+fkDGZ4bJXi7a77WbWdfW9fhRWq5URI/qeprOzYpiedlbCrQUaRWN1GkU8VJ6VDXSvUXwJFp+V+voaAjYXskVjvFheo4h1ZiOgRNmbtVXVKBIVahAF4yle2m0/5KR8MfKky40t2ociePSKKIIiADbR9JTO9uiwUSQo7PW1tLr9xCskzjW0rsebiJZtP/yVR7jjL+foz8PAAENQ7LwUmp7cTRDafNNTaK0SbWP1mrFZTHR6/Ji1ekMUOLNDZhuvzpgB/c1l/bbFyJH86pAL6Bg2Wncq4bYu9lv5KbXRvDBJuj3Y+5Kg0OsICKqgqKRRBEGYi8xWLQOH8+TeB4HbVCwohg9jz0se5KuD9R35jmiIpKfckOdNRBm5cVWPEWYGOzfbu8Pd3UKIjUKIhTr7hRDiZiHEciHE50KIKb09xx2STAYiHQWmp0bFLJTuoZRDIlzumAVizYpQsHoUP0PQV4utNJ9BSrURj6ItBNx+Hp11BAwwlyWe2Qf04/6px9LRr4IddcliHnzslzQump+/LY8XZ6wPCYrsYl7qowBFUFQqzV7a3Q5YPXRX7j7oFHAWm548av2mcFz/7+eKhklrCAqy9YMifTPyyaBvsL01inuBIyrsPxIYo/6cD/yzF+a045MIAjJfkM6pOp0r9UjIZJQ3ZI2347TqcLS4lQiVsK8OZ3dHyTVDSpkJ9ZrRYAgZkZCRZYLCbTWx28aVpNfpd81LtCsRPo7G+vwUPR6c8Ujf6UmRUBdfDeGKzdOz6amwaRGQ7urGlVLvrUBQuO0W/v7c9Qz5z31ooXS3iyB95YJCqIIi2V0hS9xgp2e7Cgop5TtAR4VDjgfulwofAn4hxIDemd0OTGEVVwCnX/mMVkhWy4ZjagiKr0fszldHjsCiDvfxzGN4ZuZJJdfMFgRUDqp5503u/vtvoCVTtmC6rYKX77mUgY8/rDudbIlxZ1NeUCw94iTOPfP3+vfQ2+RMT1oahafnzOySpkV7/+cOHv7r5cVjA26bhelrFlKz+HPtoRIpXhmzN127jS/bJzzK3zPWZQgKA322t0bRE4OAwhTfteq2MoQQ5wsh5goh5hohdT1QGlHj8CuflQRFBcfs2obBrJo2DGFR6vJ/NfMwnph0ePFBJS1B8xE8lAsKl4OYxQYh/TfujBrh42zI52ukRo7mncETiKd7t02kLj2ZnnrUKIoFhYiEidkcxWMDZpMg4nBhCmqPF0pmuOy4H9Ny1All+1JDh/PaqD2Jyr6+FBhsT/r6vw6twuqadgUp5R1SymlSymmNjY3beFrfcHJZv1mNImt66tI/J1c5ttx8YVm9CtvGJEI9plEmqP36q6IyE0WVYwFZGOpZ4sx2Ws2EbE4IVXjj7lLmKmrzuRpNgTaOXfw24Q19pHd2RdOTt4fw2HJBYYlEiNmdQLGPAiDqcGPRaV6U7UWhlUcR3msG553yawL9NN+/DAyAvi8o1gJDCr4PBioUtDGoiuybbM5H4Vc+K2oUOiXGgelP3cP0++fkFq8Z7z7Pc7f+gHRbgUM7VzlWuZYMFQiKkjdrk0kQsTsxVRAUH007mB+f88e8MxYYtGIx/3j+euJL+0g11Nwz03Nmh4qFaSEapidzNELC7lQ0lBJBEXO6seh0BUx+9jkL/nYqwz94s2yfy6YIj2jCiHoy0KevC4rngO+o0U97A91SyubtPalvPPESjSJneurSP6eC6ckcCpJ0WHM2d1OdYg4KNReEyBY2LQJEdlGzW4vs7bnD7S5MFaqarvI2sXjKfkVRQZYq8i96lQp+nVw+ip5WoaFRWKNhEg6XMl6JoNjYbwgdPo2yKUC8vRNvIordXV62oWH1cj6+5WysL79Y+V4Mdmq2a2a2EOIRYBbQIIRYC/wasAJIKW8HZgNHAcuBCPC97TPTHYySct/VaRQ63e0AayhI0uFQFvxMBovqNwi3tOV7TZQ4sxfvNo1lR3yfCxyv5k00Bdxz1HkMGNTIWJ3pDFo4l5GZNJBvzJItZZHsK47ZnI9CJzMb1L7ZvvL9GoJi9rQjGOaEEbanywTF/Wf/mEwGHtOahprc6FBrQhVidztoCnfS2teq7hr0KbaroJBSntnDfglc3EvT2XmIl0Q9ma3KwlWVj6J80bOHQyRdTiAJyTB2VVDENhb4Ckp8FAtGTWS1fwwXZN4vW/QAPp+4Hxt9+oXLjpl9P/2j3XDjJbltVrWURaqrwn30JokwmO3anQNzPSk0/ApptTpsSXjsf3efyYxR9dD2Stkz89itrOsqz7yGfGkPe72/fBo1yjxyWd8GBhr0ddOTwbZAI+sXZ21ljSIbyqlRwsMeDZF0qWMlwjjUkNVYYbe5WLeyaFqVxd/asoFBsS5F8GiYnkZ1NTNwsX7PNmc4SNxbvJDaVI0i3VdyApIaJcazVGpelE3EK9E0ajesoSEW0HxmB344m+tvvFAzhyQdUJsWaQgKh1+ZRybYhxIVDfochqDYGYkFlEWosDeBw1+lj6JcUNx48Ll8efQhypd4COeo4fzisItoHl1gOCqoHAvwnfv/wq9uu1rTMQtw6msPcvkdv9CdjisaVHpFF2Ab0I8Tzv4rq2ZVyuHcAuIheO5SWDuvuuMTYW2zE+QExd1vfEY4WGJ606jzBHDHPddw5AN/0/RR1Ee6GPf1Yij167QtZ0DsLZ4fv3+ur3ghLlW4ZnQc4aV8eNM9zD/hbGSqhyx+gx0KQ1DsjGhE1OD0b1bUk5SS1wZPpHPCBPW4IN7GOh6cfBTrGwpCLgvqPAFYYxGSDpdaRbXcR5Fye3DEtctKpDMSTzRExlfcbdvtcTJ/4K50uf3697ElfHK/8jP76uqO1+vfAcp9JyWHX/0zll/9q+J9Wr0o0hlciSi43JqCQvpUoRko0abeuZ4RvvfZePxA7LWl3cnB5bbz9B6z2Dio50qtsXiSva88l0nPPsiqh5/q8XiDHQdDUOyMxAJgL1k0HDWVS3gkwoq5ymwr2hxNpNhv+Vw8ASXZjngIn8PKbhtXwooVxdcsMKXYYxFSuUWv/G1Wuj0441FNU0oolsIXDyMLelEAuGxmTlr4Ot65H+nfx5aw+n/K54bPIZ3s+fhEWNf0FMEBFpAmsL//XvFODUERSaZxJWJIj0fRUkqemfDplBpf9R5kJDNMSxClvc4Bm9nE1cdfw+d7H9rj7Sxc3c5vDj4fgO5XykNtDXZcDEGxMxIPlkfaOPw9Cwq7p6yVZrArxH2P/5qhH32iHhfCYTVz/2O/YtyD/8ofWKJR2GNR0i63spAmyzUH6fFglhmIljtoA7Ekp531F74+szgIzmWz8MvX72TYf5/Vv48tYeMS5TOTgo7yFq5laHW3U1n75Ub4Q5DGjk76r1pavFOjaVE0FMWWSSm1mWzuMi3M7FeOjbUXaIXxIATWwosxdv/bAsiU50oIIXDZzESqyKP4sjPBvdOOY0njcGyLNet4GuygGIJiZyTeXW56qkaj0Fj0Iq1KzSXpV2P4VedsyOXFEugquGagaOFzxCOk3dpmFAC8qpNVwzEdiCVZ2H805pHFbU/NJkHU5kBsi0qomQx0r4ERByjfW7/o+ZxESLt8B9C19GtIQ+fw/vhDXfmSJqDZtCiqhriavF5t4dq/P/MG7ka4cL1v+1K5VroOYUW3L/qjd17OCdf1bE7rmL+Isd3r2DB6LJ3mTWulafDNxhAUOyOxQFnoJY4aJZJGz6SSCGoKiqj6Bitq1eJ8qkkk6vJiDRQIngKNIpXOcMPMs1lx+ImqGaVcULTsdxDfO+XXRJzlNv5Icytnzn+Zxo7y3MuYzYEpsg0ieILNkE7AqIOU752rez4nEdH1UcSWKhpJeuJQZbhFX+Z3apiewsLKzw6/hOC++6v+jUhRVndq0hROPvsGOgsL/3WuUs5NuMAOdK/TnItZKLkwPTH5wdu47+Gf8+xlv+Mnp/ysx+MNdhwMQbEzopHMlUu6i+mEluo4ZrNVR821am8LVVDE3F5shbWHCgRFOJHm6XEH0bH3TF2NQg4fzpuj9iRispbtSy1bzp/+ewsNK78s25ewOzFHt4FG0fW18tlvnCLcght6PqdCeGxqvSLkzFMG8dCkI2hNFZj0YuUaRcRi45FJR5AZNz6vpRRoFdmeFKHCnhTqHBNxk1IqJaBdtj3hcGKJ9fzMXG0tdDX0Y4DfSUsgRibTR8q5G2xzDEGxM6K16Gf9B3pJdzqCIhFQBIMlKyhU01PC68OeFRSpuNIXW/WLRKJxxjcvozbSrSykmSSkEkXj1saCHLrsQ6Jrykt7JdsVc5ejob5snyIotBPPtoiwWpHY0wTe/oqG0ROJkG54rKV1I2mnCfsQJz8//BLW1A3M74wHAVF0bqy9i/HNy3AnCoRPgYCtSUZ56e5L8DzyYH6cYDOY7WRiGaXlrI5GkXI4sVTxzLydrcTqm5i08nMev+cKOj9d0OM5BjsGhqDY2cikIR3fDEER0jQ9tQ0bxdmn/RamTVNzIhRB8cGRZ/L3Y9Wk+lyJcT8A0dYOnr//Ssa89lx+zJIEsvrmNfz7qd8j584tu2ZKLTdR2Isiy83n/JJbf3Ct9j1sCRE1y9zdCN4B1WkUFUxPnw4fR2B6I65MGFMmTVtrV35nVuMz5f972j6fz/P3X0n9ks80n5nL52H31lWwtkBrCG4Ab3+eG3cIqT0cun3Rk043tnhlQZHOSOoCHaSa+lFrNzOpeRmBr6owvxnsEBiCYmdDr0dCTlDoOLR1NIpuu4d3R0zB0b9fUde2jolTeW34VOWgkiKEcbVon9nnzc+jJIrH5tcv8JfpVASFS0NQhPsNYr1buzjeFhFWBYWrvjqNIpVQNCUd09Pze8yi9YhdsKVCfHzrd9jjr7/N79TobpdUNTebz1fwzPKCwudzEbPYip3/wQ3gG8g/9zyR6LR+SvtbDZZO2oc3J8yqeDvtHUHqogEYMADHgH7KNJu1neMGOx6GoNjZyFU0LRUUfuVTT1DEQ5qCwrJqJUcs/R+udFwJn1UXr4GhDiYt/ACZSOS1FFUYxTqUa1h8vvyYJX4KR53q+O7WcLKqtZwsdbVlu6Ytn8eBrz2ufQ9bQrhNmb/FlhcUlVqu5rrbaYfHJto6SFvciESQoLsG88aCt32NhMhMUBEA9trCZ1bsowjaXMUJd8Fm0p5+uIJdxM01uoLis0NO4l8HfUf/XoCWYILzTvol4WNPwDO4v3L5DdoaisGOhyEodjb0SnFUo1GUOsCBxg/e4fZn/oQrrEZFqaancZ+8w92P/Zro+pay1qtJdfG31tbkF70S05OjNtsJr9y5/s4BJ3DG5XeBp3wR3nP+O3zrpbu172FLCLeCS/XDeJoUn0ulxkMVutul0hleuPFsml5cAbEAgZp6HJ0FBRTjgbKaWumQMp7DXygo8td3Ws2E7S5EsOB5hdtImmqYf/NZ2N7tgkhB7a0CXFYTyXBlZ3Z7IsNrY/bCMXEc3kGKoMi09pEGUQbbHENQ7GxkNQo905NWvadMRlnIteztam0hi8+rtvdUFi+z+rYf3thW1osipZqTbH6vrkbhqlfOz2gIio0mJx3DRpUl/wFkXC4ciW3kzHartZKcqmlL5w0dKOhuV/7MOjtD+OJhMn4fxANEautxdxUWUCwPX5ZqdVd7TYGgKIh6EkIwZ9QkmgeqpTgyGYh1E08q+Q5ptw+i2vM95Ok7+fj3x0JSP9s8vnoNs1bMwZ+O4a9x8e6wSbS7yzU6gx0TQ1DsbOQ0ihJBYXMrJTq0NIpKDXiyxeTcblWjULWFemUxjWxsLxMULUNHcfkxV2HZY498ZE+Jj8LtdnDGmX9k0WEnlV1y1/df5dj5r2rennS7saeSkN7KHdsi7eBWNQqXKigq1cbKmZ40/DrNSgSV9PshHiRW20BNoGARjwfKMueXTpzBj0+4BlOtX9NHAfD3U67ixeO+r+4LApJ4XAmbzdTU6GoUQq38mwro51K4Pvwf9z5xLf7OVqxmExed82fePaj8b2OwY2IIip0NvWY6QuhnZ1fobifCEeIWK1gsyn5Vo7CpJa3jbR1lzux2bz3Pjj0Q56D+mmYUAJfVzIdDJ9BS01R2zf3eeZZj3n5S8/aE2hpVVuq3vTnEuvN+nKxGofOGDlQ0PUWzfTr8tZBJsXavfbhvn1PyPo9YcaVdgDWNQ3hj6qFgtRY0PSoWFF6HlYDaHzurGcai6n/xmjpFsGm0XhVej3qKfnn2jBpp5lYr0Na5bXRGErrHG+xYbFdBIYQ4QgixVAixXAjxU439s4QQ3UKI+erPr7TGMdgE9JzZoCTdaQqKbOXYcp+AKRohZnMqX+x5H0U2xyHR3qmMKUy5881rvmb6moW4yOTnUVKSwmQSHLlqLg1z/ld2TXskRKKkxHgOVVDEt3aXu8Kihq5NMT2VP7N4m3KeqFOeUXj6FG7Y6zRy+WvxctOTd+Uypq9Xy4Zo5FEAXPTCbfzs12er81X+jtGoap6rawSZ0Qx/Nqm+nliXvkYh1UgzR6My5588fzPn/OlS3eMNdiy2m6AQQpiBW4EjgT2AM4UQe2gc+q6UcpL681uN/QabQnYB00oE09Uo9AXF84eexbU/vE7d780tXs7RI/nOqdeyevyeqs09nxcw7PUXeOzhn2JJJXXfjgGufPt+pjzzQNl2VyRIUkdQrD3qJKZe8iCRuvLeC5tNJq2YcnKtY1XbfFVl2csFcoevnr/texbsOgaARhGhMdBGoDukhNUWJCdm2e+5+/ndQ2p+iEZmNoA7k6KhTQ3bVQVCR/0gbpj5bUxjxhRtL8TsU+4rXqHXuOjqIma1g90OQG0iQr9mI49iZ6FqQSGEMAshBgohhmZ/tvDa04HlUsqvpJQJ4FHg+C0c06Ankjo+Ctgs09MaXxNrx6i9KLIaRSaDt76Gd0ZOpdVdW1Y5VgRDZIQAl6vA3l5uKoo53Vgixdul1O5FkcXmr6Hd7SecLDexbDal1VyzgqKSRlHBr9NS24+/73cW1l12AWD0Z+/z0W3nEPloboGZrvj+zNEocbuquZnMYHGWPbOMx4srFlZMWOrfsaVpGLfscwbWrKDQaL2aHLMLt+19CmGvX/d2zIFuQs78i0LK7cURNbri7SxUJSiEEJcCLcCrwIvqzwtbeO1BwJqC72vVbaXMEEJ8JoR4SQgxVmN/do7nCyHmCiHmtra2buHUdmASOlFPoAqKLo1z9HMC9pj/Hnt/8WHx/mQYr8PCIcs+wv75/LLudiIcImZ1KBqGxa440TWaFyUcLqwlBf5iyQzeWBhZoy0o6lvXcdU7D5BcvkJz/2aRXVwLe4zbfT1oFDq+IJQciqZgO061wZLTr7ylR1taCxz/xRqFJRoh4Sj4m2mUGpc+H9Z0CuLx3Dih7jQDAq043Op4GrW8xK67cd0B59DdOLBsX5anDzmLG7+fV+jTXi/umNFne2ehWo3icmBXKeVYKeV49WfCFl67PLYRSjOYPgGGSSknAv8AntEbTEp5h5RympRyWmPjVjQ77GhUimDS60mh090O4IRXHuKYl9X6QtnY/3gIq9nEX16+mTHP/0cZs+AN2RwOEcu+HQuh9oAuFxRJpxtbyVtrIJZkxkX3svT8KzRvz9/VyqUf/IfMsuWa+zeLEmc8oPYYr8KZrfHMRj3zMB/f9l1sJqUJlNOnRCbFN7ZpXwulI2DK4cxvsJW3kJWqCUl2d+ec2YNffoUP/vk9LFItrqihUTgtgppokGiFXuNf+gawfvy0gmvVKNFl8bjuOQY7DtUKijVAhWYFm8VaYEjB98FAUQU4KWVAShlSf58NWIUQDVt5HjsXibDSpc5cXpV1c0xP9niUlFN90835GxTBEnF6MAe6y0xPlmiEmLPg7bigRlQhKbcbR0kl2EA0ScDhwalREBDAovaxqBTqucloVHPFWduz6UmoGlMJoqublMmEqFMS15xe5b9hoq2jLDkxiy0eJVn4zGyesiTF6KhdeHb3A4ins6YnQSYQIWUygXqtnCAqwN+6js9uPpPa55/WvZ3x895i4prFue/B0bvx0i77kIrGdM8x2HGwVHncV8BbQogXgdwrhJTyxi249hxgjBBiBLAOOAM4q/AAIUR/oEVKKYUQ01EEm3YwuEF1JMK6zXRw1CiO1GQMrAWNaeL6zmx7PEJYT1C4PFiCgbI2qI8ddBZNyTC5jgY2l6bp6dVTL+Tfe5/C/QXbIl+v41dv3UH/fX8EE8tNJbYaVVAEqzOLxEIRZCKJs07blAXkF9fCkFVXXc8ahdWtmRRoCnYTcnjwq8/E7VGOSbeXhxJn+evhFzBtZAO7ZzdYy59ZYMZMfrmxjo+9fhyxLnD4MAcDhB0earJz19Ao7KoZLx3U9zn88Lnb6Bg/GX51DgCtBx3O7yJD+MzmosKTM9hBqFaj+BrFP2EDvAU/m42UMgVcAvwXWAI8JqVcJIS4UAhxoXrYKcBCIcRnwM3AGVJWKrBj0CNJ/YqmuYWw9K0z+7ZvLxcUjniMjJqwVWh6Aoi7vNhDgTKNYnHTSFZP3Ds/iFXH9DRoMEtqioVB/Vs3ce5HzzFg2Tuat2BXBUW6CkGRzkhWTNib+NBhuWxxTWIai7ejRr93B+gWUQSwBAJEnZ7ceDYR43cHnceyCXvrahQf9d+VjnGT8xs0+nh4HYqWGIqlcnkf1mA3EZc3rw1paBTZuloyqK2F5QIIavwF11LeMQOxKnqHG3zjqUqjkFJeCyCE8Cpf5VbxYqnmpNkl224v+P0W4JatcS0DlUoaRS7ss0upZ1R4jsmimKwKSGckzmQM6VIXxBKNIuH1UbO2rSwvYPdFHzF01EBArS6rYW8HGLFuBSe98zJcPTMXlln/5UsA+IPzNG/B7ldbqFaRcLd03hLGrlR6Knz50FPscvH3tA+MaziY7T7NRTdHIqxbOdYWChB1e5XoJZsHcyLIo/uezBkjh0L87fz4KlJK9ln8PkMGp1AiyVEERYlGM2D1lyy68RQ27nI32LvAUYMtFFSuZXUofz8N4ebyuckgkGFtjSIUS+KLh5VMcpXBXy7gk5vPIjjtITjlGP3nYLBDUG3U0zghxKfAQmCREGJepQgkgz5Mha5ruoUBs2/HJWaUSCLFCWf/lYXfVftO5N5alUX6lbMu449nXg3IIo3i8mdv5tDZBQ12rBo9oIHRX87nZ6/ckcsKJtqFs1uJaLMnvta8BWd9Hbtf+QTzT/qu9j0W0PbfNwB4bdSefO7ur39gaXgs9NxjvILm9vzex/DqUWq1VrsX4gFGxzuxrlyRH7PgWrFkhpufvY6JbzybH0RDo7B73biTMZKdXco4Tj9P7XUsbxx3TsG1yrUGh9VC2OYAHeEabO3ELDNK+RAVp9tJXTRAotWwBO8MVGt6ugP4kZRymJRyGHAV8O9tNy2DbUYiott1rbKg0OiXnUizqm4QcqBqHsppFMpiFB85iq992dwDf+48VyxK2lUwB41QTwCT6piOZAVF+wqIKZZHS3KdZplvl91C1OYgkurZQtm9oZ0up5dfnPlL5vkG6x8YCyghvNaCqCOHT/HnpHSifnQaPQG8Nnovls46SvmiaibXPnkdJ9/6a+VaVjeY88p+OJbAmYrnypMAmj4KZ4OSMa4Iii5w1PDqyD1ZfsCR6rW8mlqQySS49YCz+WLKTM35hlqUkiPm2nwRQLt6rVRnhRBhgx2GagWFW0r5ZvaLlPItQGe1MejTJPVNIrpd7hLavSii3SF+8NFTDFi1VNmQ0ygUQTGyZSXHfvA8ZGSuTlIqncGZiCI9BS4uq6ssggfArDYviqr9K2hfnhMUwhLVzGOwW0xc9e4DDH3lOe17LODJqUdy1p9eZLQLWPC5/oHZIn2FGlWuf8em9RgHaPx6BQMi6twdPogFiHt8OILdipmrxD8R7VCuIXwFz0xDo3A3KAt5uqs756MYvOoL+mefk92nqVEAPLH/KSzcY7rmvk5vHYefewvRo47NbXOo16ro2zHYYahWUHwlhPilEGK4+vMLYOW2nJjBNqJCe059jUJbUMRb2/n5W3fTf/F8ZYPNrfgy1Bj+XRbN4aJXHlcWd1WjCMdTuJMx8BRqFNpRTzbV1BFpUxe6rq9hHzu/+eX/gRXoXlN2jhCCUxe8xuA572nfYwFrO6MMrXNxwWv38pPrL9Y/UKPsd+77JnYElFJyx30/5rDHVVecww/RTuLeGlzhgPLsskIoe/lsR0BviaBIhou0Kl+dl6TJrHS5i3aRsvl45N6r2P/5bJ6LvqAYHA9ga9buqd2VFixtHI5rUN4851EFRabTEBQ7A9UKinOBRuAp4Gn1dx3Pn0GfJhu2qUXuLbmreHs8iFbToriaoGVSq4+WVqA1ZU0VsfzY4a6gYu/2FSy8No+mj8KmFqCLZ+3goRZCJh8bvSOVa3WVCwqAmN2FuYryEj++65cc+84TpAYPwR/uRkZ0mvdolP3OR4jpCQptE18kkcaZjCOygtJVD5EOUjV+XJGQkpvhKs4RyRY4NPlKtDCZUcxfKl6HlUemHMWqYWMgFSWaduBIJTBlOwHavboa0B8eupYzbvul5r7Mki84+5MX8MfzPgyP18lj4w9hw+BR2vdvsENRlaCQUnZKKS+TUk6RUk6WUl4upTSMk99EKpmerA4w28vfkrXeqIGEmtRmrSlYwBz+nKCx1GcFRV6jCGQEJ337etqPK+hlYFWjnkp8Dtbx49nvwrv4evr+yoZQC8k5aQ559y3le1i7VEvc7sAc1Vn0s8ckU8z88mMGdLciByn+icgqbQe5Vg/rnjsCamthoVgSVyKGyGoH7gaItJOpqcGZjEGwDVzFDYG665s46VvXE591UH5jzh9U3LzolhMuY8H4KQBEI8p/b2uhoNCJ1Eo4nFh1npnr07n87tXb8cXywtdpNfOzY67k870P1r5/gx2KioJCCHGT+vm8EOK50p9emaHB1iUR0Q+PBe1onpJaTVmSAeUN01L4puv050xP9roCQaFqFMEUfDJod6zDh+XPsbkAWfR2DODze1hb04+utPrPNLQRy5IokxZ/qnyPaLfiTNidWHoQFO3N7YqDuH8/rP2UUODgmg3aB2uZkbIaxib6KKLdIUxITDmNog6SYdbvM5Orjr0KqaFRBIWNTwbvjm3ggPzGXKnx4kilOpcVqVaQjahWJquqmWn5NbIo5VK0n1mmQwnD9fTLF0UQQuCymgln+18Y7ND0lEeRrfF8w7aeiEEvkElDOq7vowBtQaGjUWT7WdsKBUVBYUFHk7JAZeImTOo142vWccqC16gNjEaxYFLQ5S5cFFnkc1q48MMn8DS2wdTvQqgFGZXE+tWCrQvC2qGZCYcLm4bPo5DulWsYCNgGDcQxUBEU4fUVBIVe61gtjSKdVJ+zRqRY1oyU7fetCgUxehBPrpnFDYm7842RVOTqVZy84HW8kQmA+nfQaIcK8OuHfsfItYvhQoh2Ko2FnIMG5M/RMPEBpFwu7HHtchyiq0uZs7/4ZeGxOy8lPXgIHP+65nkGOw4VNQopZTaraZKU8u3CH2DSNp+dwdalQte1HKXNi7K9GEpt9MDXE/dir4vuxbxnvlhcYWFB+7ixPPvDQ0nsXpeLGDItWsgNs2+idn1BLwOdRjxeh5ULP3qC/u+obU9DGxHRNClfDbjrdTWKv13xN3565W369wiEv1Yct86hg3DsvjtXHv0jmofvqn2wVk5EVnBqmXIq1MaKWO386OgrCc+cpWxQBUW/yAZmrZmHiKTKNArX/E/46+y/4W4vMLUVCtcCUn4/7pAyp/UDR3PZsVfjmDYpP59kRLPLXdrpwh7XFiKm7m5CdjeYzUXbpcXSo4nPYMegWme2VvbSOVtxHga9QaXudlkcNTnTEaCdbKYSlmZavA04vQXjFZiefDUeTPWCmCv/JprsUPZltQ1AtxGP2SQIOr2YurqUJL5kGEs0QdpfC64GCGsLCqfdQjRRuWd2VyTJoqaReEYNxz+wkafHHcR6r069SS2NwuZRiv5V7DFe/pxDZjtPjTsYsftuygZVKAxYvYR7H/4NrE/nO+ipZEtrOPyFAQA6gqKuAVc4DBlJs7c/z+0xi5ohg4rP0dAqlhxwFDcfdl75vaD0ogi7yoMZEg5XjyY+gx2DiqYnIcSZKIX6RpT4JLwYxfm+eVToK5HDUQMdBZHPuYJ45YLCN38el7/3DK7E/qDWGcqZnqTE47Cwx0dfkh6Zf7POqAla7sYCQZFb9MoXnbDLizXQBeGNICUZTFBXB+4EBLTDOfeb8yr+OR/AFfvr3ubi0RM573s3s3TKeJJpyeR1XyAXmWHakPKDtTQKk0k/iqjCc062tTNt7SI8sQlAXU5QOF3qW35UlmkUUq1b5agtMP3oaGGysUF5+4tKkl81s39LGzbL0eo5BcKlpG7XxonTeSTWH61ew3ecdCneo8NltXSSThe29maNMwx2NHrSKN4H/gp8oX5mf64Cjti2UzPY6lRjeir1UWgVxFOp/3wOV/7vYSyFbUQcfsikIBnBbBIMf2cN5sUFsfudXcpwDQVvzTmNotzRGvH4sAW7IdQKQnDRlb9kxcXXqBqF9rvK8DVfcvi8/+rfI9AeiuNzWLBbzLhtZm5/5o/s+vCd5Qemk5BO6PTv6Kl1bPk5ts8/44mHfkLN0kXKBpeixThdqgYUk0okVCFqaY2i8Nhck6gSLaxJrdEVkezy3LP8/fHf53dmzVUaz7kuHmTUmqVk4omyfRuEk+Tg8oaWSYcLW8zQKHYGevJRrJZSviWlnFHio/hErf5q8E2iWtNTrDsfqqpVYltFhNQFp7C0RLZUh2p+kg5BKlaQ0RzoJi1M+fDQwvloaBRxTw2OUCDnIO+SburdNiWEVKfMt3S5caQSkNY3P035z7+574GfKPchBAF3DZYODcFTSbjaazbZR5FWzUjZcug4/SBMOB1qKZCYBG9J+fRwSOkpYS/obaHTQjY1YSLz9h1LxmXH0tFJqKYg1FbHXAUw9v1XeeG+K4hpOPQPe+MxZiwoT2BcOmU/XplyWNl2gx2PaosC7i2EmCOECAkhEkKItBCiQulMgz5JhfacORx+yCQhGVW+65S9BhCRMHGLtdjJWVIGxOSQpCN5jePVQ07nvCv+VVwOo8Kb7iPn/5Lzr7pTETwb01z5zAMMWr9SWaRTMUiVvwHjVhZRvWqoAP61qxjSnu+TFfbUYA90lR9YSbj21OhJ4zlnVDOSPWtGMpnBOxBnqpW02YSMUVy5F3jtsDM577KSZ6ZjrquZPJ6ls0aTrK/F3bGRqL/QxKdtrgIwq0mTsc7y/9ZnvfMYkz95u2z7wlnH8q9Z3y7bbrDjUa0z+xbgTGAZ4ATOQ2lNavBNolqNAvLZ2blGOuUahSkSIW5zFm90qyGv4VZIhDE5gGg+ymaDzUvriJLoogoahaexjg0xdT4dGWZ9MY9ac1q/dwbkNJx4t36XO2tQLfWtEnd7sUU0qqdm56Tl19mMjoAZVQtz1BQIXv9Q7OF1vH/SVCLTmhThUUCrw8eGYbsUD6SjHQyuddEQ6yIetdPY0UJ0UIHPJZekVy4oshperKQdajKdwRsr7kWRxWMVEApqFmc02LGoVlAgpVwOmKWUaSnlPcCB225aBtuE7KJXUaMoyQ/IfmpoFOZoJN/7OotbfRsOtUJoIzgEIppvbjP2/Vc4ZGFJ0yEdezvAuLVLueKZv5Pe2AwhZUHyDhtckPBWvlALv582Vw2xCh3b7OEAiYLChEmPF4eWoEhWMD2pBf3KqCAoULUcc6G/oXYYonsN5t0sdA8ur2K728dvcvjnbxZvNFuV/hIlWliT186Bt/0P8WIr/ULtpIcUJDZa9TUKq0/5GyRKBEUgGMWTiEJtbdk5Bzx/P+//8UTQK31isMNQbSvUiBDCBswXQlwHNLMVqscKIY4A/g6YgTullH8u2S/U/UcBEeAcKeUnW3rdnZbsolKVRqEuwDqtOQFuO+snWJLxolalObNJqEUJXz3eyd9sF/MndfehbzyOw2ICfp4/p8ICNrh7A/t/8iLR1Y1YwxYsgGPQAIjp5zG0HH0S342N5r0Bg/Hr3KYzHCQ5IJ/p/O4xZ/PEhEO5qfTARIVnthkaxYJJ+/Hf03/JDYU+Gv9QRHA945tbae4aV3bO/m8/Q12wA/h18Q6NUuMmkyBRayXdkeTUs/7M1WcWvM9VCI/NZtcnS7SwYEsb9YCpzl92jlCTBpPdAazuLV4ODPow1WoUZ6Ms5pcAYWAIcPKWXFgIYQZuBY5Eadt1phBij5LDjgTGqD/nA//ckmvu9MT1o3FyZJ3R2QUw2gkWZ3EPbZVAGsw+jRpIZrsqKFrBKfjKlLeTO8Ihkt4SM5bFruQkaCxg9sFKDkBqXTOpiIlulw+s1ooahdOmmG40cynm3IV87VoWNo6gdbcJ+XvZdSzvDtToxVVBC0tZPWTiAd76osQBnIt6KjdXra0fyAeTZoGl4B2tbiTIDN43O2h87ouyc6zRCCmnhqCyeTSFq2y04tgYYc7gsQyZNr7g+Ky5SkNz2mUXLj/mKjpGFpsF7e8rbWdy9aIKEDm/RnUVZEOdAT4+8AQW//OBng826FNU2wo1m0YbBa7dSteeDiyXUn4FIIR4FDgeWFxwzPHA/Wqf7A+FEH4hxAAp5TYJ3p7/4PX4PvqsbHtg7GgS/eqxdnRTM7/8P3Jgwi4kGmqxtXbgW7CsbH/35N1J1vqwb2jFu/irsv1de44j5XXjWNeCZ+mqsv0de08g43LiXL0e94ryiqnt+05G2m24vlqDa9X68v37T0NazIz48Anql6aZ+6c7gbxjdPWxpwJQ/9kcGpbNZcIXCVZ0PER77SKGr3sbz+gaXpy7hoZ5H+Jen7/+Lx56iDUHHgnfK+hjIAR4+ilCIrwRVqU4fvHzpH5xPmaLGW+4m1Z/weKVPceq3bzIPVy1sbe0kbDYWDtwMDVQoPmUaxT161fxr6d+j5z5Jzh6Vn5HPAQv/ggB3HfkHznm8CPItuoZEmhh30/fhPj+xdFFFbSwRR2Cie0pvj7/Enjj0fzin4wo5dYttrJz6pZ/wYy1G4CCAn/D9lE+HQLZWi7c7LEISV+/su3YdPp4DDVj+yzBmQtfZUDN0QXH6+er2JoaeXbsgRxVV+BIj3QwYNXN8DMvmYOnll9H1SjinQFy+tGy15SXBA3W3/My0996lvj7L8FeoqxjYinRzhAbnv8fMlWcSd41ZXdSfh/25la8S8r/P3XuOY60141j7QY8X64u298xYyIZp0P//9N+U5A2K64Va3CtLv//1HbAnmA24f5yFc61JfcqoO3AvQDwLFmBo7k4KVRazLTvr1Qy8C74EntrcW3VtMNG5z5Kb3Tf/C+wdRQL4ZTbSddeygtOzbxFWLuLhX73zOlMPu2ysjlvKT0l3C0AdD1VUsoJevuqYBBQ+FdaC+xVxTGDUExfRQghzkfROhg6tDzmuxp2e+uPOO7qKt9xshPGWWFlCu7XsMee6YRdrPBFEv4TLd9/jguGWeDzJDytsf98Nwwww9wEvFheb2ckz0C9Gf4Xh9fKO6qNtD8LHhO8GYN3yqOARnqfA5uAt2PwUYLpz16d25dBcFpceYv800v/4qDPXwFgFA8wigdI2c188eOxXPPE5/zj2X9w4BfvFo3tH6nxrD2NymLRvZZMi+SsOS/Tta4FS/8m6iLdbKzXyIC2uTTfdGtGKOOL9k6WHz6Gu8fcqkRRVCih4U7G2GfZh3yxpqQa7PpPc79ONy2hxplvxLP7gg+56Ok/EVt/AY4RBXb9nDNbo8Df64vghSjfWf8kHZ8soG76ZPUc/aZFM19+hLELPoDbrshv9A+FYfsRdn2AqcCfk8URjxDQMu1kq+4WIiXWMRliTjtnptYiiqLL9E18LpNk+pqFyFX1MFbtO/H1B8piboPG8CJgn6JzzDUlDvBQKzykb2jYZYnyb9eeSMD9PwR/ZYOG8+MEI17SqD/1PRcMtcBnCXhGY/8Fbuhvho8ToHH+SNOzUGuC9+Lwusb/J8ez4DbB6zF4T+P/U81zYBHK2B+X7DfByLrnld+fjcL8kr+nA0bVPKP8/ngEFpdkGfgEuJ9Ufn8oDCtKXhwaTeBQNdX7w7CmeH+nfAN6W1AA27JrutbrRKlQquYYZaOUd6C0bGXatGmbFYbR+eN3MJ2zsWx7pq4O6XJBLIb5B+VlIzL19UinExGNYrqkPBY/3dgIdjsiHMb0o/Lq7OnGJrDbEKeEMP20q3x/v35gtSJOCmIKlKv56QEDwGxGnNiNKVge6ZMeOBBMJsQJXZC0Iq3FDuh3hyoLo+n741kf6GLgA/sSmHwBoYnfp/6Fcxk9oIF3TzwQ07njWF/guBQCdt1jdNn18A5QutG5G0nU1eIgSmTNWjLCwuB0Epoay8/R6ZvdOLCegN2NJRSmNeVkcK069wrVW21qRFEqUCJ4mucDIBMmrrnlLpbZR8FeVwJgrlE0lEhbZ7GgyDmzyxfqxrc/gWblbbf1vY8LBIV+G1RLNEKiNAAA4LvP8b8nv8eBnzyiRBEVLPDOeJQul4agsHnKtYNECOGVWJ65lgmHXFO8z2RWzIgaWohbZHjs4Z/yqf8ncPTeysYNC2B9msyCFN6R5a7B9Kgx/H2fMziiTv17Zqv/HnItjD2x7PgzXR9SN2ABtz7wB1bv+meGnVF5eXngw9X8Z8x8bj9xD6yW/PMo+v90lcb/p6YmsNkQJ4cw/V9X+f4t/f80aBAIgTi+E5NGCHZaDUgwHdeJiJTsFybSg5Q8GdMx7YhY8YujNJnJqFWCTUe3IUoKNUqLlUx/Rbs0HbURkSgWVLm2xFuZioKiwOSEEGIYMEZK+ZoQwtnTuVWwFsXXkWUwUKrnVXPMVmPALuNhl56P22GpGwoMhZe9+Prb8U3aHd6Ogr8fQ+pcUDesxyGUcUbCslfB7iPRNAAH64mt3UBw2C4cf8mD3PitPcvP0emb7bCaOfiXT/Fc5AKm3vkJDs+7cMRuFTUKu/qmmw6WCIrO1eCoIWwZhCf4Ia6CKFSL6qyNtpYI+grObN/GNtjFAktTxJYtLz5HR6OwRCMktQSFyUzKX4c1nYJoFFzK9dIZyTHfuYkfzBpTXoXT5lIiywpREx0tDQOUMiNl52iXGnfWeMggkKGCZ9a5ilibG8eHG7GfubZ8yqNG8reZ32bvftlILfX9zN0ItcX/VjIZybzuxRwy4xDOjZg5bfcDGFZb+d9TwJFkoTNI434HYreYKx67XRi+rffrFKmsdv9WpNqEux8ATwD/UjcNBp7ZwmvPAcYIIUaoEVVnAKU9Lp4DviMU9ga6t5V/wqCAwmgejf4IPVI/WimzvfZjkgOGA5Bav56OSJJ2tx/vAD2NQjucdViTD1d7N/XNXTRmzf4ms/JGralRKIJChkrG6/oaaoYSySjlQ2wN+fuyquGf8faSN9ScM7tYUIRiSWoCAagzEXC5YVWBLVyriGB2brEoSaeGoACWH3QMZ373r2DL+zYiiRStnlqElhamVTY8F85cnveinKNhrgJcNgsRmyMXvgtA52qiCUUzMqXLNW2nRdAY6iSeTdKTqi9Bw/fQ0tLBI/f+iBPaF/PG6Ol8RXlwRClDP3yTv8z+OyJRbo4z6F2qjXq6GNgXCABIKZcBTRXP6AG1BMglwH+BJcBjUspFQogLhRAXqofNBr4ClgP/Bi7akmsaVImrTgltTSeVVp+bKiga8286mV0V7SHe0krqs8+48t0HaQh3lZ+j0zcb4Mi1n+D8l7KAD9ivQBvRCU91+n2sqelH1GIt3tG9BvxDiCSVRdRRn19MHWrtqTJBkQyDxVGWBNf81Tps6RT4BKFaH5b1BQUKdVrHAthiEdIObSEihg3jg/67kij4bxkKRrjivYcYtnxB+QlWDe0gmyhZ0nc7PwHtSCmL2UTE6siXZQHoWk08biNjEohouSLvC3Qy59azqX36P8qGnKAoX1Zav1zF1PVfMMSS5uCNS3C89WbZMaXUL/+C0xe8iklmejzWYNtSraCISylzxjAhhIUKTu5qkVLOllLuIqUcJaX8g7rtdinl7ervUkp5sbp/vJRy7pZe06AKfAOVyqwR1QxTUva6RwZOyf3qmnwku1z1NO8f/S1sn37K5e8/ih+NN0SrflOdsQOVN/CU2Yx/SkH8hN2n2bPa5XYy88K7+PToM4p3BNaBbxCRqCJA3L784m8dM4qTv3Uda6cWO2xJaFSOBTpXriEtBPhMvHnBSfzuwr/kd8a0OwIC/PaoS3jznCs19zXFA5y84HWCK1bltkU2dnDF/x5h4LKF5SdomZF60ii0HODZU+1OzGHV9CQlhFpIREzEnQ5IBPIl51WyZc8zWTt+NkNbQ1CEVyoxKe7hQ7j0vUeY+fCt2vMrRB3PpGVCM+hVqv0LvC2E+D/AKYQ4FHgceH7bTctgu+IbpCyq2TLepUXqesJig28/CUdeh3voBOxuJ83dMVLNitXQO0RjPB2TCMDE4/eGg+1s/MuPiu3udm8+N6QAh9WEECV5FOmksoi6G+nwNsHuFpx1+TBYt9/LvMF70OksyQtJhDUd2WsHjGDXq59C7mrF7xO0RQuuVUGjmNcwksBu5Ul1AP07N/DX2X8jPjfvOI62KYUPzbX+8hOykWKFJTSyvUScGsdDxS5315/0I145Rm09E+uCTIpkUhBV/SWl/T+cftXEFywQLoBWDEpyjeLjcI8cSrS2HndXz10KpDqeMFUOozXY9lQrKH4CtAILgAtQTEK/2FaTMtjO1AxStIk21UFbU15WokdGHwJ7XQDAxZ89z6T7/oF17Rq6Xb5cRm8ROlFPAOZkEPazM/C4Q4t36DhmhRD844UbmPxgQX5mRK00665n6ehJcJoLc0F4pttu4YRFb+L6dF7xYMmwpiO7I5wgZbKCq4bhK1Zw/qM3QEoNdYx3a2ayJ1IZDl/0DkO/Xqp5nw7VZxIvcKjHVEGhlfCG3aeUdC/sNR5VTWdOjeNB1/QEsGzsniwdMEr5opZwf/q007n/l79UtkWKF3e300bEas/7NSr4KOR6xXRVM3IYiboGfIHyaKXyk7KCwtAotjc9/gWEECZggZTy31LKU6WUp6i/G5XAdlR8qmBY85HyuTmCooBJ65cy/Z0XcG1YR0fDAO2DtEI9s+TMKf6Sc7QFBcC4DStoWFGQHJkzo9WzIaOaZcL51qIum5nfvXIbg18piadIRDQd0/WvvMif/nsL2Guo37CB0+a8QHJjq7K4xbVbx0YTaf46+2/s8eaLmnN2qV3/Eu35BTnRoSyojnqNhV8rRDjWpZh+bNoaTSXNbXzrV4ycq+bJqM+mOekm48kWeizWKOwWExGrE5GNlKrgo+gUNuYP2QNLfR3phkY88TDEtHt0Z0lZbATs7h4T8wy2PT0KCillBvhMCLF5WWwG3zyygmH1/5RFUu/ttErCw0bRr72Z2tZmQgN0hE42y1jr/UPP7m7zaJejAOJ2B+ZowYKY7a/tqmf6ww/BTcEiQWG3mIhaHYhwyXha3e2A+s/ncsKitxDuWqxeZSELrF6nmoIymhpFJBbHkUrkSl+U4u6nJCKmO/Jv26ls69gGDT9RVnAWOvSjncp2vbfwCsL1+Hee4rwH1Kpc6rM56NkXGTdHNYWV9CgXQnDbrLNZsNch6hZ9H8Ur+x7LVZffquQfqM2VtHpfFPLxqecy5UePFZc7MdguVKvTDQAWCSFeF0I8l/3ZlhMz2I70U2setX6hRDBt4RudbexumGWGC4/9MfN+e5P2QVaXssCmyjNldSvYVlj0EnZncT/nnEbRgLk7hJSiKAdBCEHU7ixPoNLJiTB3dhJye8FZi82lmJyCa9YX9Bgvf6OPdilv/sKjnWPhr3ETtjrIqMIB4Iu9DmT8Ff/BMWVi+Qlapdajnfr+CdCOlFJJe324ssJVFRT7ffYx/desKdpWyPP7HMfCsWoJlwqmp7ZQgnqP4hPqPOwojvjeP2j3VH4ByUhDmegrVCuqt1Z9J4NvAq66vEO7/5ZUaVGon7k3cbOVKeu/YNdRp2sfVNhfobQAoV4F2wqCIulw4g4XLKAFpidbOEDaYcFSYkpRon40BIWG6cka6CLiqQGHH6tLCQiMrttQsdFTvFMRImYtHw3gc1g4+uwbOPmIqWTd3cFEhrDDjdtlLz8h+zyyIbGgOLMraYA21Rcky1fhjM+HOx5ROgNG2pW+5/EImbpGJUS45HkBDI124FgbAyZUND2dd+e11DjMcMGLuAcP4IumEXQklHo8euzyzkv8/Zmn4PdHGhJjO9OjoFB9FLdKKbVDNQx2TCaeCe/eAONO2uKhxhywJ0uG7s5u0TamDddZxIr6ZpfkbcS6wWSFktIj2DyQikI6Bebif8obBo4g2rGRkdkN4XyorzMUIO20YokWO1TjDhf2aImgSEY0ndnOQBdxbw04/VhsUZImM4mOroqNnuJqTaSiXhQFWMwm1g0eTbMjv3/Au6/xy3feQnBU+QlahRGjnZUFhdUFSKWDYel9qWVMZCCACLeSxodZBjHV1Sm9vSPlkUq/eOw6vDIJlx9TMTx2YPNKbE2Kaa1Rxvn2Jy8S+9QDgw/QnWrD6uXMXFLegtWg9+lRUEgpM0KIz4QQQ6WUX/d0vMEOwkG/gD2/r+RUbCFWi5kRH7zOyHAYq1nPdq7f5U7JS/CVv1Xasw2PwmAuXpif+vZVrO2M8HJ2Q6RdLYFuxRkJkq51FL+JA7ec/XM8Phc3Fm5MRDTDY2NSkGnsBw4/ZkuQEVc/ze+OnsDEuFo9WMP01N3Qj6O/exN/PES/z/TRK+cwsusTOFYx/w369EP2nPuC9hu1Vqn1WJdSQkWPwp4UJYJC+NV6V60duMNtpNI+zKzD0lCnCB+N5Makw4m1NDO7JDw2nZE4o2FSPiWiqpYUv3/1n3w+bTAcqy8o8oLH0Ca2N9WanrI+io9R+lEAIKU8bpvMymD7I8RWERJZvP0aAI2qsVkq9M0m1q2dQFZorirZ77KZiSYLchsi7eCsI5OR/Hf0XnxrwAJc2ZwDlcCgoXSVJgEny30U6YzktDP+yKUHjmai8yWETOEUCQLRZEXTU1hYWdR/NI7+GiXDVU765CX6h9rh7z8DwBwMEHZ60czlLm0yBT37KAqfmbv479E56xBOWmfh1po63LFukhknQVcN1n5NiiDWEBQppwvrBrWwnY7pKRRL4YuHafcp83Wr0V2ZjmKNrhSZMQIr+wrVOrOvRakk+1vgrwU/BgZbh0oaRTygGUVUqQf0QW88wa03F1R8iXWD008okeLv+55F58GTyha+KSvmc8AbT+Q3pBJKnkLJm3conkJK8DmtuUX5V2/fzZjH7q3YEZBVq/jWp7PxBDrK96kkPD4coXwGtDUUJKZVORYUM5Iw56+Zyaj32ZPpCc2cFeuggXwyeHcC0gLxAJHBTUy79CHEccfqlktJOV3Y41lBoW16CsSSeOORnGnLV+slZrEhu3rIpZCSjGYBaYPepipBIaV8G/gC8Ko/S9RtBgZbB2uBSaSUrOmplAod2/zhLsat/UJxzEIuWzoYTWJNJ5GOmjLT017z3+bsF/6d35Adt8T0FO4McOcT17LL3LdzIar7rvyMQfPez2sUGqYn56LP+cMrt+Fq027sA5Dy+nBF8j4HWzhI3KWTEyFE8QIeDyhv9Xp1nqBYoyihNhHh5AWvE/9yGcSDRIUiVHxOq66gyLhc2HOlsLVNRaFogneHTyK+u2JOs1tMBOxuRFflzngxp5sNNRrFEA16nWqrx54GfAycCpwGfCSEOGVbTsxgJyOnUWym6akUtdGPzEYxJUJg8xJu72TZDSdS98aXilBK5ev5Z9xunImC/gBZoVWiUcSaWzhkxRxquttzGkXS5cQa7FYT3sya/SiyNZEcNToLP5CpqcEdCyvaAWCKx0h69I/H4csLp6zgq0aj0BIUoU7+OvtvmD/8AGIBxIIO/vXU76mJhXQFxeL9j+T6o3+ofNEJjw0mMvzg5F8RPPVMdbcg5PJi1ugFUcj/TvweR15ptE3tC1Tro/g5sKeUciOAEKIReA2l9LiBwZZTwSSimJ42T1DEu4M4fD51DC+RFsXsI2v8ynGxLvAoCWDS7VH6QSQSSqnvXHe74kU/tlGJ/jHX1+cW5bTbjr0roPhCXPWaCW/Zsud2v07BPkDW1mKSEgIB8Pv51ndu4PTJA/ml3gmFC3hP5TsgL/Q0nrMzm/DX3gE1QVjv5fBlc8DtUq4TD0AmXVRJt33cFB6PNCjx83o+irhSBNLjyC83//eD6xg2vB9/QZ+MBKPMU9+gWh+FKSskVNo34VwDg56p0M9Z3/SU9VGUm55M2X7OapIb8RDYPcRblVwAUa+aNAod2uo5MlsNNdfdrlijSHQq51jr/LlFWbgsOMPBvKDQQhUUJp3MbIBVx5/BnhffT8ThIp5KE4qnqPVV6N3g8OcFRDZ8taJGoS9cvQP7Kc2LWlogESQTSCo9Klyu/PMvaRRVHw2w26qFyHhc10chPvuMObd8m6aP86Gu0QGD2GDWLreeZdIbz/D3h35V8RiD3qHaxf5lIcR/hRDnCCHOAV5EKQxoYLB1sOlEPWXSkAhusukpPWgQHwwdTzQbxZQIgd1LIluNtUFtp1Lgp8gWK8w14klom55SqqCw1frBrYwj/HbCVkflRk/Ztpha/a9Vavo30Oqpoy2coqsrzN+ev4HdF36oezzuxnxpjZCaOe2p0CrGpu8LqvU66XR6MbeqpTW643T71NIhWjkbwO5z3uKpB64hvma9bnhsqrWdxnAXTke+IdPMZXM4YPaD+vME6tetYsaKeRWPMegdKgoKIcRoIcS+UsprULrbTQAmAh+g9qc2MNgqWByAKNcoKkURZTUKjVLjwX3258wz/6TUlkrFIZ0Am4dkh1qNtb+aE1ygUWw4/Fj2vPh+gg1q+GpWAJU4syNpWO3vj6OxXskit9fQftw4jvvhv1SNQrt/x+uHnsFZV98LZv22ngMSAa547yGCcz8l8PV6Tlz8Fv3aKjR1dDfmM6bDqtJfjaDQ0NzMJkG3x49VdbaLQIxwjSr0tEJxyWtusa6ArukprQpWZ2P+uey5+ANOevl+/XkCZDJII+qpT9CTRnETEASQUj4lpfyRlPJKFG3ips29qBCiTgjxqhBimfqpqSsLIVYJIRYIIeYLIYymRTsyQvTQiKdS1JNGa0+rshiH4+m8ILF7aakfyO3TT8I+Zpfi8VE0hFZPHZG0akLJajclGsWKqftxwAV34thjN2WDpwl/pksJm61geuqwOmkfOEJzX5ZGc4Yr/vcImY8+IrxWERDWAfp5F7gbFGGajCm1q6wuTUd6jpwzW7uY4u+//3ueP+1sALocLjqHqmXH9QSFV/UFVRAUma4uAOwFFXAzvho80aB2EcgsUiINOdEn6ElQDJdSfl66Ue00N3wLrvtT4HUp5RjgdfW7HgdKKSdJKadtwfUMvglo9c3OJbBpmJ7MVjDbNRe9+jVf8eYdP8D62qsFWomXVQNHcuOh52EfkRUUXblz6jpbuPy9h0ku+VLZkDM9FWsUoZhSBNBtV52zniYavlzBPf/5FTS36QqKXT9+k2PnvaR97yr+kUqR5vS69UTXK2/2roH99U9wq76WSBuEWpTvlTKZLXZlIdfp/REdMYZOi3L+jcd9m7d/8mdlh46gsKj+lkQgiF54rAyoxRD9/vw2fw2WTAZC2gJLOUii1QTJoPfpSVBU6oCu3SG+Oo4H7lN/vw84YQvGMthR0OqbXcn0BLqFAe12CyM6m5FtrXlBYvMQb++iv0jk8xwK2nvWBDq58n8PI5csVjZkF9MS09Oo5x7hocd+gc2sLmKeJpzBLmat/AQRSumanmb87yVOfONR7ftQqavz0uXwwIYNpFpUQTG4CkERblU0Ck8F7QOURdzq1u39MX3dYmaoPTm6M04aPKpfIScouoqOt/hUQdEd1NUo1tcN5PUJs8CX/xua1OS7eGfxeIUEfXWsbjS6G/QFehIUc4QQPyjdKIT4PrAlXqZ+UspmAPVTz6gqgVeEEPOEEOdXGlAIcb4QYq4QYm5ra3k5ZINvAFp9s3vqAa3Tsc1eoyxK6WCoqPT3/g/fykvXn6UUGBTmIkFhU1t7pgLqtpyAKTY91axcxsT1X+bfnN1N2MzqOXEJXu3mTJZYhISjcqSP1Wyi3VuPZeMGukMxgnYX/qEVaqxmBUUoKygq+Cey2DQ0N5XJS+dw1OwXIJDhT/fdxB7z1UilrKAu6ZstR+/Cxcf9hI5dxuoKio/2mMEN5/4WrNbcNpMqNCJtXbrTfPPY7/C9y/7V8/0YbHN6yqO4AnhaCPEt8oJhGmADTqx0ohDiNUDrVejnmzC/faWU64UQTcCrQogvpJTvaB0opbwD1cE+bdo0o0jMNxGt7msVaicp57g1TU/2GuVNNxMKF/koLIFuok4PbiHUntv5hS+b35DOCQpVaFmKlWdzMEjU7iTnCagZhMWq9tGISd2OgLZYhJSzsqAACNY24Ojo4LWph/Hna/fkvQadKCrIC4ZgM3SvhRH79zi+8sy0NYrMkKHK2+PqNLs3r2KZS9UodAIHHE31vLj7TE6sbQSZbURUknAXTeB1FC81bYcdzbjugcweMgLdYF6p33/JoHepKCiklC3APkKIAyFXIv9FKeUbPQ0spTxEb58QokUIMUBK2SyEGABs1DpOSrle/dwohHgamA5oCgqDHQCtvtkVynYDuqYnR50fABkI5sewebCFAkRd6qJn9xUJCkdtiaBIqm1QS1YrczhM1FFgjqodAXZ1cawkKOIxUrV+7fso4P6r/8r87gwNXTEG+p2VfQ6+QWCywLp5ShhxXWVnOaCtuak4x6iVZ1cpfpiG8bsq3y02MNuUaxTgMkn2XTUfVtXDaG2N4uJ//YIh3S1wwaL8eT43IbuLULK0CmOefV96hDM+eAN+PKfnezLYplRb6+lNKeU/1J8ehUQVPAd8V/39u8CzpQcIIdxCCG/2d+AwYOFWuLZBX0XLjFQp6gl0NQq3y8HLu8ygrd+g/H67F0coQMxbk/teKCictco1MlkHq17TonCQhLNQUAwHpyBZZyVjNev6CRzxCGlXzxpF4+Am1nbG+M6/r+Vb7z5W+WCzBfxDYcWb+bn0hM2lG/VUu4fi5JerlBpZ/t1GF5znKdMonELy0H9+QePsZ3RLeDjDAURJeXl/dzv/98ZdZObP151m3ca1jF29uOf7MdjmbC/F7s/AoUKIZcCh6neEEAOFENlEvn7Ae0KIz1DqTL0opXxZczSDHQO7tyzzl1i3slibrdrn2DyaZhSH1cTFJ/+CT2ceXWB68uAOB0gUCYr89dwuB+Ov+A8fnXGBskGnaVFzbX/WDdslv6FuJNJpxnqpk8DeuxaVuMgipeTE79zIG5f33CxyYqSVPz13A8d88l+GR/UrzRZen261VUz96MrHgvI8dUxPA8btQtpsQnRk2FjbL5eECCj9P0oEjMvrJi1MSnkSHUHhiIRIeooFvTcZ5fw5T2NarP/uJyVIoxdFn2C7dC2XUrYDB2tsXw9KKy8p5VcoyX0GOwuFBe6yxLr1I55AV6MQQuB1WAjGUmBXtQabh/unHsuECSMYC4qgKOgD7bCaCDnchLNtLBJhzZyE6064grEDfeRa7tg9ZBrHYt64gFbPrvg1pplIZ+iyuZX6UD0wbpcBDF2oKO62vab3eDwDp8Dy15Tf60b1fLzNrYTSalDjd/PG5Qczbe4cVtn2K44ysXnLNQq7hYjVDuEw+fDY/PunlBJXNEzSW2wSc6g5Famukr93EYarsa9guIoM+g5Zn0FhElY8oB/xBBX7Zt/2yK845Y+XKYLE6iYpBQ+MO5Tmg9W2oiWmJyEEl338JKNmP6lsyPooSgjFU2XOWTHpDHg8QvKNWNnxANFEmmvevo9RCz7SvxeVIeNG8/mYKXQ7vYw857Qej2fsiUqr2L1+WJ3316oRNFDAsGEO1h8wCNO/S4ov2D1lPgq7xUTU6kCEw5pRT/FUBm88TMZXLOydWR9St76gEEbjoj6DISgM+g4OH8h08SKmVxAwSwVB4cyk8XS05irHhsJxRravpTajRiiVCAqA4xa+yegPVTdcQtv0dMftl3HQi8V1ikz7XMLKjf0Q67Rt/5FQlIs/fJyBS+br34uKEILd5r6NeekX2Juq6MfQbw/40WI4/A89HwvKM9NxZgOM9GUYOWQg04aX5INo+CiEEMRsDkREW1AEYymeGnsgbXvNLDrP7feRFqZc6XUt2ur7s2zIrtXdk8E2xRAUBn2HXKx+wVtmNaanZCTXv6GQuNuDPRzKVY4Nrd/AG3deyLhXn1Gv5y0zW8UdTszZ4n2JcFmyXTqdYfy6pdREyt+EQ04flpD2whdTm/SYPBXKaxTels+DZ8gmtKL1NGn6RrQH1w+PBRDxADaXhhan4aMA+MNJV/P68d8r0ATzfoVgLMmfDzyXjmOKo+ndDgthqwMZ0Z/Ha0d+i59d9LfK92LQKxiCwqDvkNUcCv0Usa4e+iu4AQmpaNmulMeLPRpWtAabh0iLUjzP2qC+Kdt9ipBJp3LnxB0urFF18UqGyzSKcCCERWaKsoyzRF0erDqCIt6tbDd5KzQh6i2ypVI0hCugPH/NIozlPgqApbtOZmX/kdoaRSSBPRnHay8WYhazib2v+g//Pedq3WlmpKKxGGx/DEFh0HfI5koUahSRjioEBdqlxr0+3NFQrsR4WBUU9ibVoZwt41Fgd086XVhjqqBIlPsoIq1KFJLJV77gJ9xe7GEdQdGlbLdU6EXRa2SFn4ZwBRTBqleEUeM5T173BcM/+Z+moEgtX8HSG09m+Oynys5zOO2EE6my7VmOeP4e/nzL5fr3YdBrGILCoO+Q0yjU3IlMWvldp3YSULF5Ucu4Kcwee4D6huwlvlERFM5GpZObVr2nlMOFKal0ZFPCY4tNT7F2pUmQWaNLXfOQ0azuP1xzmkk1ic9coQ1qr5FrXqRj9lF9OmVkndklFV/PeOtRTnnkpoLGRXktIN6ulnWvLxf25334BNOfuFt3mrXtLQxv/kr/Pgx6je0SHmtgoIm9RFBEuwAJzgqCIlc2u3zRW3Pw0dxi2pWTEz9D2L0kWpUOcO7+qoNYQ1A8eNHvWNYW4VUpNRPuQml4d9gkPEPKi9W9fvL5rGwL81+NaW4cM44xVz/NC4cdoLG3lylqElXiLM/27tDr/yEzkIwWmeRSDie2eBSt8NhERxeQD4ctZMayuXilvkahlBk3TE99AUOjMOg7lLbbrKoHdIXWng4LMiORMcVHsXLEHvzi0B/iHTVMOUBDUDgdNiKJtLJYynSZRtHZbzBnn/F7UvuX11TyOCyE4toLXySRImm24nLZ9e+lt7DpC9ecf0hLUORMdcXaW9rlwhaPaSbcpVRB4WwoF/ZJpxtbVD9MFykrly8x6DUMQWHQd7CXOLOzWcmbaXra7aM3WX798Yg1XUovirpBPLfP8ViyZiONiqiTP3+Pnz76J4hlk/SKBUVYFQRuW7kyvtec13johu9AW1vZPtdn8/jNq7fj7m7Xv5feImt60gqRzQrpSj3KS0KK0y43jnhUsxVqprtLGa5RQ1C43Nij+lFPSGl0uOsjGILCoO9gc6ulv9XFKqIKikqmpwoaha3Gg0VmEJEE2D2YVq5gSvfa/AE5jSLvPB+0fiXHfvYaBNRrl5iefLOf553bv0/NxvVl13OTZnj7OmRHedkN15dfcM4nL+BKJfXvpbfIaRQaOR8FTZ7KsGsLZely40jG8lFUBaantQNGcMc+p2HtX17/KuXx4ojpaxTN/YexZPQE/fsw6DUMH4VB30EItYxH1keRNT359c+pICis/dQCFBEJNi8HPn4HFy2aA3/7vrJdw/SUrW2UbG/BWjh+dn/rRoZ2t9DpLe/bZVI1lXh7R1nHL6kWGrTXVsgJ6S0q+HUqmp50So0vPOIUbvftzmMaUU9fDtmNN476AedrhAUna/wk9Gp4AbMPPYP4rNPYR/9ODHoJQ6Mw6Fu46iGimmeqMj0VOmaLcWdbiEYk2L04O9sJ1RT4OzQFhTJeok2tAVWiUWTUkhOuhnK/iVktIR5t7SyfZyisjt8XwmMrmZ7yTZ7K0PFRpAYPYU7jaDKy3Jmd6uigf0Y7DPd/372cg658SHeamYzhougrGILCoG/hboSwauOPdCiLjl4vCqioUfgGFwoKD57uDqL+gqJ8Gjb3bH5EslMVVqUlPIJB0sKEXSOPwlKnCI9sSGghIhImZTKBvS84s/Wf2eb4KPq1r+f0T18mma3bVLC6H/PATdx7w/c0p+GxWwgnUkipXdPp9Kdu43fXX6h/Hwa9hiEoDPoWrvoCQdGm+CcqFbqzOAGhuejVNdTwwrSZMMAMdi/+YAfx+oJwUJNJzTbOL3xmv59Oh5dkUF30Skp4mIJBIjaH5quudUA/3hoxlZC7XLBlEklCDk/feEXOakkVNQqdEh5QplEM/moxf/7vLaTXq8K1QKOwhbrzjaJKGLX0U2596o9Ev16rub+2u436bqOtcV/AEBQGfQt3gyIgAIItuv2nc5hM+l3urGZeOOooGG0hioPacBeyqcSpWtKTIrL/gUy+/BEiI1RtpESj+HrgSN4Zp91u1DZkCOecdi0tU/Yu2/fYKRdz+u+eq3wvvUVOo9BwZscqOLN1fBTZ+lXJYFbw5IWhPRwi4dZOMqwNdnLkl+8TXb9Bc789HiVm77nRk8G2x3BmG/Qt3I2KySmTUfpAe7W7xRVh1e/YNtASg7CkPWnn2uN/yuknlCzyJRVkXTalJlEypo5X4sx+bb/jWLPHIRytcS2PXfnvFIyV51JEEmlcjj7y381sU6LLtJzZ8QBYHErr01J0QpEtqqM6VwnWkjevOSIhEhrJdgAWv2Leind0a+63xSIk7OVBAwa9z3bRKIQQpwohFgkhMkKIaRWOO0IIsVQIsVwI8dPenKPBdsLVoCS6xboguAG8/Xs+p0I11O8+9CA8EGZj0sarY/bGOXVy8QElgsIX7OTWZ/6E/eNPlQ0lpqdQLJUTCKV4HRZevfOHDPvbH8v2HfbC/Xz75Xt6vpfeQAj9UuN65TtAabtqcZb5KKw+RYBksua6AuHqjIZIebQjvSw1inkr0akjKKIRkk5Do+gLbK9XnIXAScC/9A4QQpiBW1Fapa4F5gghnpNSGk10d2Tcah2m4AYIb+zZ9ATavbZVMj4nNEs6Vrcza8Vc+punFB9QqlFYBEcv/R/Nq/0wiDLT009uvJSkxws/LG8d77FbsMbDBFrKTSkTFn2AU/ShRjx6zYv0Ksdm0Sg1bsk69oMBaLDl2tamM5Lb9zyJffbZQ+koWDpUrSoourQFxfyhY2nsX8duPd6MwbZmu2gUUsolUsqlPRw2HVgupfxKSpkAHgWO3/azM9iu+NQeDM3zlUzfqjUKbdMTDW4ISuzv/I97n/gNTeGu4v0lgsKhmkOEmvegOMvzeLs7sKFdnttttxC0uzEFyntV2GIRUn3p7VhXowjqaxSg2bzIMmoUh3z/NqLj+hdpE+FEiscmHkbbrEO1h6qvZZ23kVhaW4DecPC5vH/WRT3fi8E2py87swcBawq+r1W3GezI+NU6TKveUz59VfzJK3S5szQ5QYLj44/IIPCMLu7djL24T7fLryySpohaYrwk4soRj5DWieKxWZSe2+ZguaCwx2Ok+5SgcOn7KCp1FNTQKBxeF8sbhpIxJ4pMdcFwnDGtq6lLaZsFbSOGs+9F97DygCM090fiaZwapVIMep9tJiiEEK8JIRZq/FSrFWjFEerq7kKI84UQc4UQc1tbjZC6byzeAYqzddkryveGXXo+x+bSbe1pa1RypAd99jHt/kaEoyRnukSjcDptRKz2vKAowRmPkKmQNBd1ejS73DniUdIut8YZ2wmrjhYWD/bQUbC8eZHLIjh3zrPYlqwu0iiiG9p49e6L2fXlpzWHyvp6wvF02b5kOsNb//gOBz56WxU3Y7Ct2WbiWkp5yBYOsRYYUvB9MFBeYCd/vTuAOwCmTZvWh4zBBpuEyQS1w6HtSzDb8xpGJWzaLToBnENddBxQj+PjKK2jdy8tqg2OGqXHQiYNJjM2s4kldYNosMgy/0QmI3HHo8gKXerm77YnQVOs6B+ulJKgzUmitl73vF7H5sqXSimkGh9FqKVok8tu4f/evIuIZQSMyd95tE3Jq7DU+TWHctvN/Oup3+OOHwl7/apoXySWpH+wnQ192eaxE9GX/wxzgDFCiBFCCBtwBtBHAtENtikDVYdz465KpE1PVDA9eWoFzXv1xxOPEJ04pfyAktLmQgjOuPA2Og4bobw9FxCOJXhy3EF0jdcYR+W/h5/Fw8cXZxPHUxkOP/dW5l7ys57vpbewVjA9VfJR2Ms1CqfdQsTqwBSNFWkUsTallImlXrsEi9tmYeq6JfiWlcenxLpDmJBV9xg32LZsr/DYE4UQa4EZwItCiP+q2wcKIWYDSClTwCXAf4ElwGNSykXbY74GvczkbynZvdO0Sz+UUUFQmBJhnA0NnHLhbQz48RXlBzjUDOSCt2u33YI5Fc5nIquEkhn+74hLaT1UK4tCwee0Eogmis9TS5PrhdVuF2zu8vpYmYzaBrVSyRRPWXiszWwiYnNiisWLBEVCraLr0BEUJpMgYnfmAwcKiKohs6IvtI412D7hsVLKp4Eyw6WUcj1wVMH32cDsXpyaQV9gxP7ws7VlyW662DyQiuXMR0XEg4wYNIj/XH4uTpu5/NzSHhjAj17+F03pJXDhvkWHhmNJhMzgqZA4d/wbj3L8f26B80K5uk6R9i7ueuJanAMuhhnDq7unbY1W7kkiiOL5r2R68paZ+YQQxGwOauOhIr9OMte0SL/xVNThxhwuFxSJLuXvYa5g5jPoPfqy6clgZ6ZaIQEFZbM1tIpEEGH3aQsJyL89F5TxGN2yEufXgXwmskpqwUJWXHc8I95+WXcqFocDazoF3XkNJdLawcEr5lDTubG6++kNrBoBAJVKjGexe5Xz0sXZ53G7A1M8WfR3Wzt0F356+CU4dxmtO1zc4caiIShCJguPjzuE9OgxPd+LwTbHEBQG33wqVkMNlpmQisi+PReYnpIOF6ZEqsxWH+/oxoTEWsEcIrLd8wpyKeJqVVVrX3o7zuZRZApyQrLPoCeNAsq0ip+ddx3JE71FwnVdbX+emHIkjiZ9J/76gSNo9TeVbe+ua+Kao68gs9dePd+LwTanDxlNDQw2k1wNIi1BEerBOVtuekq53JjimbLzshnElZoPmfx+AJIdnWRb8sRVE4xe9M92obCCbFaQ5kqM9+CjAEUAFzSUitU1YO+KF0WKmb9exV4dKxEVKube/92fkkhl2Ldke0Stl+XuS36dnRhDozD45qNXDTWVgHS8LHqpCIdf+SwwPaVdLkyJckGRUu3mdrVBkRbZ5kWx1nxPiqyt3l6vf16vo1UyPGd6qiAodDSKQxe/hfnDaJHpacpzD3Pn3VdXnIbHbsk5+wvx//cFvrz+BHzLv6h4vkHvYAgKg28+Nh0fRXYx20TTU7h/P6g3lfko0qoJyVmnv5CK4cN5YPJRBP35SJ9oOsPK2gHY+5WbWLYbWWFQoElVbFqUOy/bFbBYUOyz8D34KFH0zMzBABFnZV/T4W89yfV/+2HZ9kwwiC2TwuEzop76AoagMPjmk12cSp2z2YWvkunJbFXMMAWCYtEJp8K57jIBs2HgMO6eehzOgfr1p8wjhvPLwy6iY3g+o/yrcdM58Px/45g0obr76Q1K8keAAh9FFRpF4XkAbgfEZFHUky3YTdRduUd4XaSb8V8vhnRxdnZGDZl11FaYi0GvYQgKg28+eqan7FuvrYe3UruvSFD4zUqPZ1lisloxajx/POwC7BV8DT6nFXMmTbArP5dQLIUQ4LLqRF5tD7ILfmF2dvb3iiU8tHtSCI8D4oA1X0TREQoS81R24Oey3EtzKdQe43Z/ZUFj0DsYgsLgm49e1FPO9NRDtJGjpugNede578IdIZLdyeLhugM0mFIVnbNeq2DF9cfTcNvfc9tGP/8Yjz76c0z6pcp6n6wwKEyeiweUOltWh/Y5UKBRFCfdmTwOkCCTeeezMxwg4a2sEQif2ryos6t4h1ovS7j6UCHFnRhDUBh889GLesr1f+5JUBRXkPVFu6E5QzxSvLDPuudGXrnx2xWH8rkdhK0OMl1duW01q1cwYd3Syr2/exs901MlsxPo+igsHiXGKxHNP7PrDv4+H532g4rDmWqUeUTbuoq2Lx++B4/ue1LfemY7MUbsmcE3H72Eu3gVCWTZ/dHO/HBOZXFKRIv7TpjDIWJ2J5VG8zmsBO2uooQ7cyhAxOGiTzX11AgL7rEgIBSHxxbQfdCeUPc4of5DsKM0LXpj4DjGT6mcMCcHDeLDIeMYmgZ/wfZ54/ZhWeMEzqjqZgy2NYa4NvjmY7GrPaBLBEWsCmc2lJmerA7FtBSPFDtYzeEw8R56SngcSvMiEcgLCksoSKyH6J9eR8sp3VMvClB6aZvtarmPPF5bCqyCEMrzCcWSHLT8YwZ0lnf7KyS21z6ccdaf6RwyvGh7vDuEz3iN7TMYgsLgm48Q2u1Qs2+9PS1+jmJnts2uaBLxSLFGYY2ESDgrO8bNJkHY4cYczC+ktnCQWA/n9Toms5JfEisxPfWkUYASDVaiUfjbm+GlGIlFqwAIbmzn7id/y27vv1pxKL2eFOf/65fceENls5VB72EICoMdA612qPEgIIq6rmniqClaMG1uYKiZkKu46qk9GiFZRfOhl6Yfyby9D8t9X1PTj+aRfbDzs91b4qMI9OyjyJ1XUmo8GoCPE6SXrQQgulHpRWGu1y8ICFDb2cLr/74A53NPFW23RsMkHYYju69gKHcGOwY2l7aPwu7t2SFq9ykZ3MkYWB1Y+tkIntNA88S9GV9w2JOTD2e34U30tOS/OfN4Vjd4OE39/rujLuXQPfqx3ybe0janRJMi1lWdoLCVV5C1qQ6YlBoWHGlpA8Bap11iPIvL7WRExzo+31BcMNEei5KqqyxkDHoPQ6Mw2DHIFrkrpKe2nllKKsjak9104yaaLDaHPDjuUFYc3nMn3wZTBtOGZkDpbtcdTeB3WXs4aztg9+VNSFJCpB1cVXThK2kfC2B3KM8q06kEBURbFY3C2a+h4lBOVePIFBRRBLDHwmSM0Ng+gyEoDHYMNH0UPXRry5Kt96RGPlkjnTTeuo4Bj9yXHyqVprF9A3WZeI/Dnf3y3dz481OUIZNpnr7rMvad/XBVt9GrOHx501M8CJlUlYJCo3mRJY40QUYtnBhvVTQKd1NlQeGucZMSJmR3XlBIKXHHwqS9RrJdX8EQFAY7Blo+iliVgsKtLmZhZXGzZELY2uNYWppzh4SiSd7+13nMeOzfPQ4nampwJOOQSNDVGWJcywq8yWjVt9JrOPz5sOCoWsTQVdlUBGhqFNZUmLTTQjqi3OeyXSbxrdN/j2f87hWHctuthOyuXIIdQCyZ4Z6px7F25qFV34rBtmV7tUI9VQixSAiREUJMq3DcKiHEAiHEfCHE3N6co8E3DK12qPFgzxFPAO5G5TOiCApzvJu0zYwIFpThaO/GIjMIf89282wFWdnVRXh9i7KtsbHnefQ2rnqIqAIi0p7f1hM2T3kJj0SIz6+awlNnXwVAs9XLp7tM7bFWk8kkeHuXvWgeMDy3LRRPccdeJ9N2yJFV34rBtmV7aRQLgZOAd6o49kAp5SQppa5AMTDAqiMoqtIo1EU83AqAiHWRcNgwBfOO3qzN3VRFTwmrekxoYzsRVVBYmvqgoHA3KKanVBwiqmaxmT4K4kGSVg8dYaVfeM0nH3Psqure7f54+k95++BTc99DkTj9A234SFY4y6A32S6CQkq5REq5dHtc22AHxeHTWLyqyDSGvLlFNT0R6yLusGMpcLDG2pSF1FKhF0VuKmqP6EBLO3E1msfevw8KiqxQiHTkNQpnlaanZETpUZ4lEaL+kzaOued6AKa9/B+unH1bVdNw2y2EEvmeFInVX/PhP89h9KvPV3W+wbanr/soJPCKEGKeEOL8SgcKIc4XQswVQsxtbW3tpekZ9Bmy2dWFi1e1GoXZCs5aRaNIhCEVY82Y4awcnO/1nGhTFlJ7Q89v3Kbx4/nDrHNp89bRJay8M3wyzpHDN/WOtj1Z30ykbdN9FFBSUDCIuznMPh+/AoCzs4Owr7rw1l89+kd++Id8T4q8UDZKjPcVtpmgEEK8JoRYqPHTc3xhnn2llFOAI4GLhRD76x0opbxDSjlNSjmtsS/agw22LdkQ12xeQDqltvmsMnLG3agIipBiKnrjxBN57Khzc7vbGwZw7cE/wDxubM9D7bEr/97rJJpddXwxbA++c/rvqJ1Q2am7XchpFO0Q2ggmSz4CrBJapcbjIZI1PnzhbshkcHd3EK2twowFOGSa2vZ8qY9EuyIobD3kYBj0Htss4U5KechWGGO9+rlRCPE0MJ3q/BoGOxuFgsJVV123tkLcjRBWF0wg7qgnEM3byDfWNHLPtOO5ZOSwHoeqd9sZ0rWB6Fcrac148bus2C19qBdFFldBtFdwA3j6V1ettbArYM1gRYtLhknV+jHLDOm2dnzBTlrGV9eoKe7z4wrntZOUWnLc1pdax+7k9NnMbCGEGzBJKYPq74cBv93O0zLoq5RqFNWWGM/iqofWpcqCCez78huc/cEf4eJ1AGSamxnTuhqPVb8XRZY6t43n7ruSNc3H4otJvrXkU/jVkk26nV6hMCw42Ay+AdWd51RNStEu5VPVLNKqWW7dkq/oH+lmY1N1rV8zNX68kYCS9CcEaVVQZH09Btuf7RUee6IQYi0wA3hRCPFfdftAIcRs9bB+wHtCiM+Aj4EXpZQvb4/5GnwDKBMUVZYYz+LtD4H1OdOTsDhp6tygLF7AiOcf49W7L8YuM5VGAcBmMdHmq8fc3Ix/3SocpHs8Z7vgqgeLAwJrFUHh1W/xWkROUKiRUuozNw8YwEZ3LUtXtXLEubfQ9p3vVzWcrKvFkklDWIlaWzNsDH+YdS6uYUM36XYMth3bRaOQUj4NPK2xfT1wlPr7V8DEXp6awTeVUkGRXcScVb6V1g5XSmc3fw5mO4naJiyZDEQi4HZDVxdxixW7o0L3twJCdY34WluwR6OEhvRsrtouCKGYjrq+hu51MOKA6s4rFRSqZmHef1+mBw7nNPdgvqoX1OwyqqrhQruP4/Fxh3BsLIHDA6v6Dee+fU/h54ZG0Wfo61FPBgbVscWCYoTyufw1qBsJtYojNZbNnwgECG9CqfDwwCE0tKyhqWsjmUGDqj6v1/EPhTVzFCHZULnJUI4yQaF81jUopqaWN//HOXOfY1SVpZpCMw/imqOvoEttQCXXrGVcZGMPZxn0JoagMNgxyEbrZAVFNuO4WkFRpwqK0AaoH5XLlwirVVAtwW5izir9HUB8tz2oiQbxxcOYd9216vN6ndoREFyv/F6toLB5lAipEkHh8Tfyxzf/zX23Xcwv3rwTv7e6nn5+lxWkpCscA2Cfx/7Nvf+6bJNuw2DbYggKgx0DmweEqUCj2IS8AID6gkWy31gyo8fwxLiDCZqUqq/2QDdRb/Vx/ZZjjuHXh1zAi7vui++Afas+r9cZunf+96Y9qjtHCEUAlwgK4apjdEZxbDcPGA5VmukGrlnOlzeciHj2OQBs3R2EPEYORV/CEBQGOwYmk+K4LjQ9WRxgrbJTtdkCE89Uft/taOTkyVx99JW0Nw0G4J79TuPt0yrmfBYx+cApPDfzJP76g98z+MgDN+VOepcR+yvPaeg+4KkuSgnQFBQ4/MSOPxGA9iOrT5dyNfixZVK5pEZndxcRn7/6uRhsc/pseKyBwSbjqFGa74BSu6iachSFHH0jHPBjqBuJL9kJUhIIKeaQVweMY9A+w6seyuewMvvymbhsFoToOaR2u+HtD5fOq67GUyGFgiLWpfTRtjqZ+fOLWLfvFCbuV31pNk9/RUCl29TS5KEuYoOGbNp8DLYphkZhsOPgqsvXLIp2Vu+fyGJzKY5soC6T4IsbT6b+37cSS6SYtvwTBobbN2m4ATVOapx9sGFRKTWDq9e8shSVKFeftRAIIRh04AyEtfr79jXVkRImMh3KeL5QF6laIyu7L2EICoMdB3dTLg+CaEf1/gkN6vvVIqQk07KRrpZ2HvrPL5jwzuyeT9xZKDU9Of2bPZTbbqHT5cPU2ko8leZ3B57H8qNO2TrzNNgqGILCYMfB0wQhtSBkuHXTzSmFQzmstLv9iNaNdK9RsrUt/fttjVnuGLgblGcspfLM3ZtfX00IwdN7H8eiXafQHkrw4u4zSczowwEAOyGGoDDYcfA0KYtXJgPBluozjTUQQhDw1mJtbyPwtRI+6hq4+ePtcPgGQiqmaBOhFvBsmRB98YQf8PKEg2jf0M5eXy9gYDrS80kGvYYhKAx2HNxNINPQvUZJINsCQQEQrqnD0dlOZJ3SEtU3tMpaSDsDXvVZBJu3iqDo57ERW7+ByPwF/OeRnzHsi0+3wiQNthaGoDDYcciGd25YoH7fMkHx+YxDeWPCLDKrVgNUXZJip8A3UPlsW6aUc/dumaA4a/ZdPPrrk0iuWAmAZ8yILZ2hwVbECI812HHIvtU2z1c+t3DxWnb0qby0oJnTBgieP/PX3DjI0ChyZLW19Z8on1solMXAgZhlBsun8wDw7za6hzMMehNDUBjsONQOVz6XKV3WsqGum8vQWie0tfGxqwn2O7S6Xg07C1nT08p3lc+6LdMAzEOVvAn/vI+I2By4qugkaNB7GP/yDXYcfAPB6oLmz5QEsJotS9qasmYRn/7jW5x5/1/YN7x+K01yB8FiB/+wvEZRv2UaQO00pVD0bqsW0dEwUCkTYtBnMASFwY6DEPkFq340mLasq1zTVKVD22kLXuOQOUYrlDL6j1c+nXVblLMCMGLPcUQtdt4ZPpnXLvrFVpicwdbEEBQGOxbDZyqfI2Zu8VBDdxtOq9sPgPfwg7d4vB2ObEHBIdO3eCiX0869h3+PG2d+m/7HH7HF4xlsXbaLj0IIcT1wLJAAVgDfk1J2aRx3BPB3wAzcKaX8c2/O0+AbyL6XKWaR6dUX8NPDZBKsv+sh1j77LJO+c+pWmNwOxtRzlNDYKedsleGm3/pHYl+2cvDuRmJjX0NItdVjr15UiMOAN6SUKSHEXwCklD8pOcYMfAkcCqwF5gBnSikX9zT+tGnT5Ny5c7f+xA0MDAx2UIQQ86SUmtUct4vpSUr5ipQypX79EBiscdh0YLmU8ispZQJ4FKi+drGBgYGBwVahL/gozgVe0tg+CFhT8H2tuk0T8f/t3W+MXFUdxvHvk9IWIzVKQbOCkRYatCDBUhsqSvxDFIoRNBhJTOgLDTGRxL4wWrKJ1Be+KFET0aipkaRq1ZhYoSEtpSiVN4Ta1m27Ta0tikm1tmuMkSZYC/354pwJ43jvnc527r3D7vNJJnt77szcZ8+5s6f3z5wj3Stpt6TdU1NTQ45oZjZ71XaNQtKTQNG3cMYj4tH8nHHgJWBT0VsUlJWeJ4uIDcAGSKeeBg5sZmaFausoIuKWqvWSVgMfAT4YxRdKjgHdN8JfDvhmdjOzhrVy6infzfQl4KMRUTZM5G+BJZIWSZoH3A1saSqjmZklbV2j+DawANghaULS9wAkvVnSVoB8sfs+YDtwCPh5RBxsKa+Z2azVyvcoIqLw+/4R8VdgVde/twKeVszMrEWjcNeTmZmNsFa+cFc3SVPAn6f58kuAvw8xzrA412CcazDONZiZmOutEVE4p+2M7CjOh6TdZd9ObJNzDca5BuNcg5ltuXzqyczMKrmjMDOzSu4o/t+GtgOUcK7BONdgnGswsyqXr1GYmVklH1GYmVkldxRmZlZp1nYUkj4h6aCks5KW96y7X9JRSYclfbir/AZJB/K6h6R6Z4CXtE7SX/IwJxOSVnWtK8zYFEm35m0flbS26e33ZHk+t8uEpN257GJJOyQdyT/f0FCWhyWdlDTZVVaapal2LMnV6v4l6S2SnpJ0KH8WP5/LW62vilytfx4lXShpl6R9OdtXcnm9dRYRs/IBvB24GtgJLO8qXwrsA+YDi0hTtc7J63YBK0lDoG8Dbqs54zrgCwXlpRkbqrs5eZuLgXk5y9IW2/J54JKesgeBtXl5LbC+oSw3A8uAyX5ZmmzHklyt7l/AGLAsLy8gzWi5tO36qsjV+ucx/+25KC/PBZ4Fbqy7zmbtEUVEHIqIwwWr7gB+FhGnI+JPwFFghaQx4HUR8UykFvghcGdziftnbHD7r4bZB+8ANubljTTUVhHxNPCPc8zSWDuW5CrTSK6IOB4Re/PyC6TBPy+j5fqqyFWmyXaMiDiV/zk3P4Ka62zWdhQVymbWuywv95bX7T5J+/Opg87h5ECz/9Wg7e33CuAJSXsk3ZvL3hQRxyF98IE3tpauPMso1ONI7F+SrgDeSfof8sjUV08uGIH6kjRH0gRwEtgREbXX2YzuKCQ9KWmy4FH1v9+ymfUGmnFvSBm/C1wJXA8cB77eJ2NT2t5+r5siYhlwG/A5STe3mGUQbdfjSOxfki4CfgGsiYh/VT21oKzJXCNRXxHxckRcT5rMbYWkayuePpRsrQwz3pToM8teibKZ9Y7l5d7y83KuGSV9H3isT8amtL39/xFpeHoi4qSkX5IOrU9IGouI4/m04cm28lVkabUeI+JEZ7mt/UvSXNIf400RsTkXt15fRblGob66RcQ/Je0EbqXmOpvRRxTTtAW4W9J8SYuAJcCufDj3gqQbJQm4B3i0ziC5wTs+BnTuWCnMWGeWHiMz+6Ck10pa0FkGPkSqpy3A6vy01dTcVn2UZWm1Hdvev/Ln6AfAoYj4RteqVuurLFfb9ZUzXCrp9Xn5NcAtwO+pu87quDL/aniQGvoYcBo4AWzvWjdOujvgMF13NgHLSTvHc6RZ+lRzxh8BB4D9ucHH+mVssP5Wke4GeQ4Yb7EdF5Pu6tgHHOxkARYCvwKO5J8XN5Tnp6TTEmfy/vXpqixNtWNJrlb3L+A9pNMg+4GJ/FjVdn1V5Gr98whcB/wuZ5gEvtxvfx9GNg/hYWZmlXzqyczMKrmjMDOzSu4ozMyskjsKMzOr5I7CzMwquaMw6yJpYdfooH/rGi30lKTv1LTNNZLumcbr5kl6WtKM/uKstc+3x5qVkLQOOBURX6txGxcAe0mjlb40jdc/QBqgcdPQw5llPqIwOweS3ifpsby8TtJGSU8ozYXxcUkPKs2J8Xge/qEzf8lv8mCF23u+2dvxAWBvp5OQtFPSeqU5B/4g6b25/JpcNpEHpVuSX/8I8KnaK8BmNXcUZtNzJXA7aRjnHwNPRcQ7gBeB23Nn8S3groi4AXgY+GrB+9wE7OkpuyAiVgBrgAdy2WeBb0YaDG45r4xkPAm8a0i/k1khn9s0m55tEXFG0gHSRE6P5/IDwBWkSbGuBXakoYOYQxpCo9cYab6Dbp3B8fbk9wJ4BhiXdDmwOSKOQBpJVNJ/JC2INHeC2dC5ozCbntMAEXFW0pl45WLfWdLnSsDBiFjZ531eBC4sem/g5fxeRMRPJD1LOorZLukzEfHr/Lz5wL/P67cxq+BTT2b1OAxcKmklpGGrJV1T8LxDwFX93kzSYuCPEfEQaUC663L5QmAqIs4MLblZD3cUZjWINEXsXcB6SftII5C+u+Cp20jzWffzSWAyz2z2NtJUvADvB7aeb16zKr491qxlebKlL3auOwz42s3A/VE8/7vZUPiIwqx9a0kXtQeSJ416xJ2E1c1HFGZmVslHFGZmVskdhZmZVXJHYWZmldxRmJlZJXcUZmZW6b8Aki0FKnr3KgAAAABJRU5ErkJggg==\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"## Using scipy\n",
|
|
"\n",
|
|
"if True:\n",
|
|
" scipy_corr = signal.correlate(sig_1, sig_2, mode='same')\n",
|
|
" scipy_id = scipy_corr.argmax()\n",
|
|
" calc_shift = ((len(scipy_corr)-1)/2 -scipy_id)/signal_1.sample_rate\n",
|
|
"\n",
|
|
" if not True:\n",
|
|
" signal_2.periodic = True\n",
|
|
"\n",
|
|
" fig, ax = plt.subplots()\n",
|
|
" ax.plot(double_signal_time * ns, sig_1, label='Regular')\n",
|
|
" ax.plot((double_signal_time) * ns, sig_2, label=\"Shifted\")\n",
|
|
" ax.plot((double_signal_time) * ns, signal_2(double_signal_time + calc_shift), 'r--', label='Recovered')\n",
|
|
" ax.set_xlabel(\"Time (ns)\")\n",
|
|
" ax.set_ylabel(\"Correlation\")\n",
|
|
" ax.set_title(\"Calculated Lag: {:.4g} ns\".format(calc_shift*ns))\n",
|
|
" ax.legend()\n",
|
|
" plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## new code"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def lag_gridsearch(grid, sample_rate, signal_data, reference):\n",
|
|
" \"\"\"\n",
|
|
" Return the best time shift found when doing a grid search.\n",
|
|
" \n",
|
|
" Parameters\n",
|
|
" ----------\n",
|
|
" lag_grid - ndarray\n",
|
|
" The array specifying the grid that is to be searched.\n",
|
|
" sample_rate - float\n",
|
|
" Sample rate of signal_data to transform index to time.\n",
|
|
" signal_data - ndarray\n",
|
|
" The real signal to find the time shift for.\n",
|
|
" reference - ndarray\n",
|
|
" Real signal to use as reference to obtain lag.\n",
|
|
" \n",
|
|
" Returns\n",
|
|
" -------\n",
|
|
" lag : ndarray\n",
|
|
" The best time shift obtained\n",
|
|
" err : tuple\n",
|
|
" Difference to the previous and next time shift from lag, resp.\n",
|
|
" \"\"\"\n",
|
|
"\n",
|
|
" assert signal_data.shape == reference.shape\n",
|
|
" \n",
|
|
" corrs = grid_correlate(grid, signal_data, reference)\n",
|
|
" \n",
|
|
" idx = np.argmax(corrs)\n",
|
|
" \n",
|
|
" lag = grid[idx]/sample_rate\n",
|
|
" \n",
|
|
" err_min = (grid[idx-1]-grid[idx])/(2*sample_rate)\n",
|
|
" err_plus = (grid[idx+1]-grid[idx])/(2*sample_rate)\n",
|
|
"\n",
|
|
" return lag, (err_min, err_plus)\n",
|
|
" \n",
|
|
"\n",
|
|
"def grid_correlate(grid, x, reference):\n",
|
|
" \"\"\"\n",
|
|
" Determine correlation between x and reference using grid as \n",
|
|
" the lags to be used for the correlation.\n",
|
|
" \n",
|
|
" Parameters\n",
|
|
" ----------\n",
|
|
" grid - ndarray\n",
|
|
" The array specifying the grid that is to be searched.\n",
|
|
" x - ndarray\n",
|
|
" The real signal to find the time shift for.\n",
|
|
" reference - ndarray\n",
|
|
" Real signal to use as reference to obtain lag.\n",
|
|
" \n",
|
|
" Returns\n",
|
|
" -------\n",
|
|
" corrs - ndarray\n",
|
|
" The correlations along grid.\n",
|
|
" \"\"\"\n",
|
|
" grid = np.asarray(grid)\n",
|
|
" x = np.asarray(x)\n",
|
|
" reference = np.asarray(reference)\n",
|
|
"\n",
|
|
" assert x.shape == reference.shape\n",
|
|
" \n",
|
|
" ref_conj = np.conjugate(reference)\n",
|
|
" \n",
|
|
" corrs = np.array([np.dot(np.roll(ref_conj, lag), x) for lag in grid], dtype=np.float64)\n",
|
|
" \n",
|
|
" return corrs\n",
|
|
"\n",
|
|
"def correlation_grid(grid_size=None, in1_len=None, in2_len = None, end = None, start=None, mode='full'):\n",
|
|
" \"\"\"\n",
|
|
" Abuse correlation_lags to determine the endpoints of the grid.\n",
|
|
" \"\"\"\n",
|
|
" \n",
|
|
" if in1_len is not None or in2_len is not None:\n",
|
|
" if in2_len is None:\n",
|
|
" in2_len = in1_len\n",
|
|
" elif in1_len is None:\n",
|
|
" in1_len = in2_len\n",
|
|
"\n",
|
|
" lags = signal.correlation_lags(in1_len, in2_len, mode=mode)\n",
|
|
"\n",
|
|
" max_lag = max(lags)\n",
|
|
" min_lag = min(lags)\n",
|
|
" else:\n",
|
|
" max_lag = np.inf\n",
|
|
" min_lag = -np.inf\n",
|
|
"\n",
|
|
" if end is None:\n",
|
|
" end = max_lag\n",
|
|
" elif end > max_lag:\n",
|
|
" raise ValueError(\"Grid end is too high\")\n",
|
|
"\n",
|
|
" if start is None:\n",
|
|
" start = min_lag\n",
|
|
" elif start < min_lag:\n",
|
|
" raise ValueError(\"Grid start is too low\")\n",
|
|
"\n",
|
|
" return np.linspace(start, end, grid_size, dtype=int, endpoint=False)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Debug and test functions"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"ids 87 871\n",
|
|
"ts -2.62e-08 -2.58e-08 =: -2.58e-08\n",
|
|
"avail ts -2e-07 - 1.978e-07 : 1.989e-09\n",
|
|
"grid size 200 2000 2000\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"#################\n",
|
|
"grid_size = 200\n",
|
|
"my_mode = 'same'\n",
|
|
"grid = correlation_grid(grid_size, in1_len=len(sig_1), in2_len=len(sig_2), mode=my_mode)\n",
|
|
"t_grid = grid/signal_1.sample_rate\n",
|
|
"\n",
|
|
"scipy_mode = my_mode\n",
|
|
"scipy_corr = signal.correlate(sig_2, sig_1, mode=scipy_mode)\n",
|
|
"scipy_lags = signal.correlation_lags(len(sig_2), len(sig_1), mode=scipy_mode)\n",
|
|
"corrs = grid_correlate(grid, sig_2, sig_1)\n",
|
|
" \n",
|
|
"\n",
|
|
"scipy_id = np.argmax(scipy_corr)\n",
|
|
"my_id = np.argmax(corrs)\n",
|
|
"\n",
|
|
"\n",
|
|
"fig, ax = plt.subplots()\n",
|
|
"ax.set_title(\"Correlations\")\n",
|
|
"\n",
|
|
"if not True:\n",
|
|
" x_grid = grid\n",
|
|
" scipy_grid = scipy_lags\n",
|
|
" ax.set_xlabel(\"Index Lag\")\n",
|
|
"else:\n",
|
|
" x_grid = t_grid * 1e9\n",
|
|
" scipy_grid = scipy_lags / signal_1.sample_rate * 1e9\n",
|
|
" ax.set_xlabel(\"Time [ns]\")\n",
|
|
" \n",
|
|
"ax.plot(x_grid, corrs, label='grid correlation')\n",
|
|
"ax.plot(scipy_grid, scipy_corr, label='scipy')\n",
|
|
"\n",
|
|
"ax.legend()\n",
|
|
"\n",
|
|
"plt.show();\n",
|
|
"\n",
|
|
"\n",
|
|
"if scipy_mode == 'same':\n",
|
|
" scipy_corr_grid = scipy_corr[grid]\n",
|
|
"else:\n",
|
|
" scipy_corr_grid = scipy_corr[grid]\n",
|
|
" \n",
|
|
"\n",
|
|
"if len(grid) <= 10:\n",
|
|
" print(\"G\", grid)\n",
|
|
" print(\"TG\", grid/signal_1.sample_rate)\n",
|
|
" print(\"C\", corrs)\n",
|
|
" print(\"SC\", scipy_corr_grid)\n",
|
|
" \n",
|
|
" \n",
|
|
"print(\"ids\", my_id, scipy_id)\n",
|
|
"print(\"ts\", t_grid[my_id], scipy_lags[np.argmax(scipy_corr)]/signal_1.sample_rate, '=:', signal_2.t_0)\n",
|
|
"print(\"avail ts\", t_grid[0], '-', t_grid[-1] ,':', (t_grid[-1] - t_grid[0])/len(t_grid))\n",
|
|
"print(\"grid size\", len(t_grid), len(sig_2), len(sig_1))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Showcase functions"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 6,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Known time offset: -2.58e-08\n",
|
|
"Calculated offset: -2.62e-08\n",
|
|
"Uncertainty on offset: (-1e-09, 1e-09)\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 1152x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"grid_size = 200\n",
|
|
"\n",
|
|
"grid = correlation_grid(grid_size, in1_len=len(sig_1), in2_len=len(sig_2), mode='same')\n",
|
|
"calc_shift, err = lag_gridsearch(grid, signal_1.sample_rate, sig_2, sig_1)\n",
|
|
"\n",
|
|
"print(\"Known time offset:\", signal_2.t_0)\n",
|
|
"print(\"Calculated offset:\", calc_shift)\n",
|
|
"print(\"Uncertainty on offset:\", err)\n",
|
|
"\n",
|
|
"if True:\n",
|
|
" signal_2.periodic = False\n",
|
|
"\n",
|
|
"fig, ax = plt.subplots(figsize=(16,4))\n",
|
|
"ax.plot(double_signal_time * ns, sig_1, alpha=0.5, label='Regular')\n",
|
|
"ax.plot(double_signal_time * ns, sig_2, alpha=0.5, label='Shifted')\n",
|
|
"ax.plot((double_signal_time) * ns, signal_2(double_signal_time + calc_shift), ls=(0, (10,)), label='Recovered')\n",
|
|
"\n",
|
|
"\n",
|
|
"ax.axvline(calc_shift * ns)\n",
|
|
"for i, _ in enumerate(err):\n",
|
|
" ax.axvline((calc_shift + err[i]) * ns, ls=(5*i, (4, 4)))\n",
|
|
"\n",
|
|
"ax.set_xlabel(\"Time (ns)\")\n",
|
|
"ax.set_ylabel(\"Amplitude\")\n",
|
|
"ax.legend()\n",
|
|
"\n",
|
|
"plt.show()"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.10.2"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 4
|
|
}
|