Skip to content

Instantly share code, notes, and snippets.

@HarryRybacki-zz
Last active August 29, 2015 14:08
Show Gist options
  • Save HarryRybacki-zz/5d91ad0207d6e52f9b05 to your computer and use it in GitHub Desktop.
Save HarryRybacki-zz/5d91ad0207d6e52f9b05 to your computer and use it in GitHub Desktop.
{
"metadata": {
"name": "",
"signature": "sha256:72611f3780e84d83218518aef29204e42b767d6f70f7cc484a2254fe80f0bb79"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "code",
"collapsed": false,
"input": [
"%matplotlib inline\n",
"\n",
"\"\"\"CSC490 Work Notebook -- Harry Rybacki\n",
"I have abided by the UNCG Academic Honor Code. 3Sep14\n",
"\"\"\"\n",
"\n",
"# Import necessary libraries\n",
"import copy\n",
"import math\n",
"import matplotlib.pyplot as pyplot\n",
"\n",
"import helpers # helper functions are the baseline functions from Dr. Shan et al's research"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 24
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Phase One - Read Input"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\"\"\"\n",
"Begin phase one - Read Input\n",
"\n",
"Note: This phase will need slight tweaking for each data source as they do not follow a truly standard data format.\n",
"As a result, interfaces will likely need to be written for each source akin to read_ibrl_data()\n",
"\n",
"Note: While I had originally intended to use Pandas DataFrame objects to store / manipulate the data I opted out as\n",
"it expects each column (sensor) to be of the same length (number of measurements) but that isn't the case with the IBRL\n",
"dataset. I could cast each column to a Pandas Series (1 dimensional vector object) and add each Series to the DataFrame\n",
"but that might be overkill. For know I am using a simple dictionary mapping each sensor to a list of tuples containing\n",
"temperature and humidity data.\n",
"\"\"\"\n",
"# location of IBRL sensor measurements dataset\n",
"ibrl_sensor_measurements_file = \"./datasets/Reduced2530K.csv\"\n",
"\n",
"# Create dictionary of original sensors mapping to their measurements\n",
"# x1, x2, ..., xn where xi = (ti', hi') and X = (T, H)\n",
"measurements = helpers.read_ibrl_data(ibrl_sensor_measurements_file)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Total rows: 171848\n",
"Total incomplete rows: 0\n"
]
}
],
"prompt_number": 25
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Phase Two - Process Data"
]
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Perform Transformation"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\"\"\"\n",
"Begin phase two - Process Data\n",
"\"\"\"\n",
"# 1A - Transformation\n",
" \n",
"# Shuffle measurements \n",
"# y1, y2, ..., yn\n",
"shuffled_measurements = helpers.randomize_readings(measurements)\n",
"\n",
"# Calculate successive differences and construct the lookup table\n",
"# p1 = y2-y1, p2 = y3-y2, ... pn-1 = yn - yn-1 where pi = (ti, hi) and P = (T', H')\n",
"differences, lookup_table = helpers.generate_differences(shuffled_measurements)\n",
"\n",
"# Standardize the differences\n",
"standardized_differences = helpers.standardize_readings(copy.deepcopy(differences))"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 26
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"standardized_differences == differences"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 29,
"text": [
"False"
]
}
],
"prompt_number": 29
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Perform Ellipsoid Boundary Modeling (BASELINE)\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"################ INCOMPLETE ################\n",
"\n",
"# 1B - Ellipsoid Boundary Modeling\n",
"\n",
"# Model ellipsoid for each sensor with data\n",
"ellipsoid_parameters = {}\n",
"for sensor in standardized_differences:\n",
" ellipsoid_parameters[sensor] = helpers.generate_ellipsoid(standardized_differences[sensor], \n",
" 1.7601, # manually set 'a'\n",
" 4.1168) # manually set 'b'\n",
"# Calculate the aggregate ellipsoid\n"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 20
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Perform Ellipsoid Boundary Modeling (ALTERNATIVE APPROACH)"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\"\"\"YOUR CODE HERE\"\"\""
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Perform Inverse Transformation"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"################ INCOMPLETE ################\n",
"\n",
"# 1C - Inverse Transformation\n",
"\n",
"# Segregate anomalies from true measurements\n"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Phase Four - Visually Model Data"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"################ INCOMPLETE ################\n",
"\n",
"\"\"\"\n",
"Begin phase four - Visually model data\n",
"\"\"\"\n",
"\n",
"# Relevant imports for plotting\n",
"from pylab import figure, show, rand\n",
"from matplotlib.patches import Ellipse\n",
"\n",
"# FIXME(hrybacki): This is just an example. Working examples from actual functions are below\n",
"\n",
"# Generate example ellipsoid\n",
"NUM = 1\n",
"ells = [Ellipse(xy=rand(2)*10, width=rand()+5, height=rand()+4, angle=rand()*360)\n",
" for i in range(NUM)]\n",
"fig = figure()\n",
"ax = fig.add_subplot(111, aspect='equal')\n",
"for e in ells:\n",
" ax.add_artist(e)\n",
" e.set_clip_box(ax.bbox)\n",
" e.set_alpha(rand())\n",
" e.set_facecolor(rand(3))\n",
"\n",
"ax.set_xlim(0, 10)\n",
"ax.set_ylim(0, 10)\n",
"\n",
"# Add true measurements in blue\n",
"for reading in true_measurements:\n",
" fig.plot(reading, 'bo')\n",
"\n",
"# Add anomalies in red\n",
"for reading in anamolies:\n",
" fig.plot(reading, 'ro')\n",
"\n",
"show()"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Save Plot?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# save plot to disk\n",
"#filename = \"\" + \".png\"\n",
"#fig.save(filename)"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print \"Completed...\""
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Begin Testing:"
]
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Functions to be ported to helpers.py"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def generate_regional_ellipsoid_parameters(sensors_ellipsoid_parameters):\n",
" \"\"\" Generates the aggregate ellipsoid parameters from a list of ellipsoids within a region\n",
" \n",
" :param ellipsoid_parameters: list of dictionaries representing ellispoid parameters from individual sensors\n",
" :return: dictionary representing the aggregate ellipsoid paremeters for a given region\n",
" #@TODO(hrybacki): impliment after figuring out the ellipsoid stuff\n",
" \"\"\"\n",
" num_of_ellipsoids = len(sensors_ellipsoid_parameters)\n",
" ave_a = sum([sensors_ellipsoid_parameters[ellipsoid]['a'] for ellipsoid in sensors_ellipsoid_parameters]) / num_of_ellipsoids\n",
" ave_b = sum([sensors_ellipsoid_parameters[ellipsoid]['b'] for ellipsoid in sensors_ellipsoid_parameters]) / num_of_ellipsoids\n",
" ave_theta = sum([sensors_ellipsoid_parameters[ellipsoid]['theta'] for ellipsoid in sensors_ellipsoid_parameters]) / num_of_ellipsoids\n",
" \n",
" return (ave_a, ave_b, ave_theta)\n",
" \n"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 7
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Using sensor 31 (it's easy to compare as it's in the paper) to test the ellipsoid boundary modeling"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Calculate sensor 31 ellipsoid parameters\n",
"sensor_31_ellipsoid_params = helpers.generate_ellipsoid(standardized_differences['31'], 1.7601, 4.1168)\n",
"\n",
"# Insantiate a new figure\n",
"pyplot.figure(2)\n",
"\n",
"# Plot the successive differences from sensor 31\n",
"pyplot.subplot(111)\n",
"pyplot.plot([reading[0] for reading in standardized_differences['31']],\n",
" [reading[1] for reading in standardized_differences['31']])\n",
"pyplot.xlabel('Temperature')\n",
"pyplot.ylabel('Humidity')\n",
"pyplot.title('Successive Differences from Sensor 31') \n",
"\n",
"# Plot the points calculated that represent the ellipseoid's boundary sensor 31\n",
"pyplot.subplot(111)\n",
"pyplot.plot([reading[0] for reading in sensor_31_ellipsoid_params['ellipsoid_points']],\n",
" [reading[1] for reading in sensor_31_ellipsoid_params['ellipsoid_points']],\n",
" 'ro')\n",
"pyplot.xlabel('Temperature')\n",
"pyplot.ylabel('Humidity')\n",
"pyplot.title('ellipsoid generated from sensor31')\n",
"\n",
"# Group the subplots and display below\n",
"pyplot.tight_layout()\n",
"pyplot.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAakAAAEbCAYAAABgLnslAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n22oZl2EAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x108ea3ed0>"
]
}
],
"prompt_number": 8
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here we can see that the ellipsoid modeling isn't quite working as we would hope. I need Dr. Shan to review the process i've used (the new helper functions).\n",
"\n",
"1. Q: Each sensor calculates its ellipsoid parameters and sends them to the base station. Above I have used sensor 31 in the this fashion. Once each sensor has calculated it's 'ellipsoid parameters' and send them to the base station, how does the base station determine the overall ellipsoid? What is that algorithm?\n",
" * **A: Each sensor detemines it's a, b, and theta. These are all sent to the base station which averages them. These averages create the 'regional' a, b, and theta used to create the aggregated boundary ellipsoid.**\n",
"2. Q: In the paper, sensor 31 has temp bounds of -3 to 3 not -12, 12. Why and how? Did Dr. Shan's team manipulate the readings before calculating the successive differences? If so, what and how. What is the alorithm?\n",
" * **A: We want to calculate an hi1/hi2 for each temperature reading a given sensor has. Done: this wasn't readily apparent in the paper was it? If so, where?**\n",
"1. pyplot was based off of matlab plotting. How does matlab plot ellipses? Pyplot takes a center point, orrientation, height, and width. That's quite different than determining the points that outline the ellipse and then 'connecting the dots.' I'm a bit confused as to how I should work this.\n"
]
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Generate a plot of data from all measurements"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Insantiate a new figure\n",
"pyplot.figure(num=3, figsize=(12,12))\n",
"\n",
"# Plot of Original Data\n",
"pyplot.subplot(321) # Num rows, num cols, figure num\n",
"for sensor in measurements:\n",
" #pyplot.plot([reading[0] for reading in measurements[sensor]],\n",
" # [reading[1] for reading in measurements[sensor]])\n",
" pyplot.scatter([reading[0] for reading in measurements[sensor]],\n",
" [reading[1] for reading in measurements[sensor]],\n",
" s=10)\n",
"pyplot.axis([10, 75, 10, 70]) # [xmin, xmax, ymin, ymax]\n",
"pyplot.xlabel('Temperature')\n",
"pyplot.ylabel('Humidity')\n",
"pyplot.title('Original Data (of all sensors)')\n",
"\n",
"# Plot differences\n",
"pyplot.subplot(322)\n",
"for sensor in differences:\n",
" #pyplot.plot([reading[0] for reading in differences[sensor]],\n",
" # [reading[1] for reading in differences[sensor]])\n",
" pyplot.scatter([reading[0] for reading in differences[sensor]],\n",
" [reading[1] for reading in differences[sensor]],\n",
" s=10)\n",
"pyplot.axis([-60, 60, -60, 60]) # [xmin, xmax, ymin, ymax]\n",
"pyplot.xlabel('Temperature')\n",
"pyplot.ylabel('Humidity')\n",
"pyplot.title('Successive Differences (of all sensors)')\n",
"\n",
"# Plot standardized differences\n",
"pyplot.subplot(323)\n",
"for sensor in standardized_differences:\n",
" #pyplot.plot([reading[0] for reading in standardized_differences[sensor]],\n",
" # [reading[1] for reading in standardized_differences[sensor]])\n",
" pyplot.scatter([reading[0] for reading in standardized_differences[sensor]],\n",
" [reading[1] for reading in standardized_differences[sensor]],\n",
" s=10)\n",
"pyplot.axis([-10, 10, -10, 10]) # [xmin, xmax, ymin, ymax]\n",
"pyplot.xlabel('Temperature')\n",
"pyplot.ylabel('Humidity')\n",
"pyplot.title('Standardized Successive Differences (of all sensors)')\n",
"\n",
"# Plot differences ellipses\n",
"pyplot.subplot(324)\n",
"for sensor in differences:\n",
" ellipsoid_params = helpers.generate_ellipsoid(differences[sensor], 1.7601, 4.1168)\n",
" pyplot.scatter([reading[0] for reading in ellipsoid_params['ellipsoid_points']],\n",
" [reading[1] for reading in ellipsoid_params['ellipsoid_points']],\n",
" s=10,\n",
" c='r')\n",
"pyplot.axis([-5, 5, -5, 5]) # [xmin, xmax, ymin, ymax]\n",
"pyplot.xlabel('Temperature')\n",
"pyplot.ylabel('Humidity')\n",
"pyplot.title('Difference ellipsoids')\n",
"\n",
"# Plot standardized difference ellipses\n",
"pyplot.subplot(325)\n",
"for sensor in standardized_differences:\n",
" ellipsoid_params = helpers.generate_ellipsoid(standardized_differences[sensor], 1.7601, 4.1168)\n",
" pyplot.scatter([reading[0] for reading in ellipsoid_params['ellipsoid_points']],\n",
" [reading[1] for reading in ellipsoid_params['ellipsoid_points']],\n",
" s=10,\n",
" c='r')\n",
"pyplot.axis([-5, 5, -5, 5]) # [xmin, xmax, ymin, ymax]\n",
"pyplot.xlabel('Temperature')\n",
"pyplot.ylabel('Humidity')\n",
"pyplot.title('Standardized difference ellipsoids')\n",
"\n",
"pyplot.tight_layout()\n",
"pyplot.show()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAA1kAAANbCAYAAACwyVU4AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzsnXmcXUWV+L/nLekkkG4SSAwCgoAQCCFsMu7EZdgElM3E\nDdFRULaAgAkQSZAAAZLQHZIoKKPIIOA4wIDbAA7hpzIKAcIWgxAFwQAJW3dYutPd7/z+OFV973v9\nutOdvN7P9/O5n3733rp1q+q9rlOnzqlToqo4juM4juM4juM4lSHT1wVwHMdxHMdxHMcZTLiS5TiO\n4ziO4ziOU0FcyXIcx3Ecx3Ecx6kgrmQ5juM4juM4juNUEFeyHMdxHMdxHMdxKogrWY7jOI7jOI7j\nOBXElSynXyAi54nIDyudtgt5FURk50rk1VOIyGUiMr2LaT8sIk+LyHoROaqb7zlRRH6fOu/3bdNd\nRORIEbm5r8vhOM7ARkS+LyKz+sO7ReRbIvKyiDSIyOjNkQMDARHZU0Qe7GLaESJyp4i8ISK3bMK7\n2uSgiPxERC7ubh79GRGpEpG/iMg2fV2WwYgrWU7FCYP1x0XkLRF5UUSWikhNZ8+o6mWq+o2u5N+d\ntJuDiCwTkXeC4KoXkeUiMkNEhnUjj81SVERkLPBl4AddfOR7wCJVHaWqd2zqewcrqnonMFFEJvV1\nWRxnKCMiHxGR+8Pg91UR+YOIHNDX5eoqqvotVZ1b6XxF5FkReTvInddF5I8icrKISLl3i0geWAB8\nUlWrVfV1Br8cuBi4sotpjwPGAWNUdepmvlfDMWhQ1Sbg34GZfV2WwYgrWU5FEZGzgXnA2UA18AFg\nR+DuIAzKPZPtvRJ2CwVOVdVqYDxWp2nAr7uZj2w8SYecCPwqdIRd4T3Ays1434BGAhtJdhNwUm+U\nx3Gc9ohINfBLoA4YDWwHXAR0tZ8bzChwRJA778Hk6Qzgug7SjweGA39JXdtkOdCP5TEAIrItMAW4\nvYuP7Aj8VVULlSpChfLpNbrwnd4EfKWjMZqz6biS5VSMIDjnAKep6l2q2qqqzwGfA3YCvhTSzRGR\nX4jIDSJSD5wYrt2QyusEEXlORF4RkVlhdu8TqedvCJ93CtaimH6diJyfyudAEfm/MCO4RkSu7mZH\nIgCq+o6q3gccBXxQRD69sfxF5P+FPB4NbhvHi8hWIvJLEVkrIq8FN4btOnn/ocB9Je38jeAK8qqI\n/HcQOojIamBn4M4wC9quniIyU0SeCfefFJHPdqMt0vmcKCKrQz5/E5EvpO59TURWhvr9VkTek7pX\nCLOyfw1ttjh1b1cRuS/MbK+TlFufiHxIRB4M9x4QkQ+m7i0Tkbki8kfgLWDnzsoHLAM+vSn1dhyn\nIuwGqKreokajqt6tqo9DcR8fzmM/nwnnY0TkxyLyz9DP3JZK+xkRWSHmffCMiBwSrteIyHWhn35B\nRC5O5Ve277EpG7lKzBWvXkQeE5E9w7021zExd6tPp8qQC/nsE84/IGa1ez2U7aCuNJKqrg/W96nY\nILjo3SLyPmBVSP6GiPxORJ6hRA5spO4nilnLForIK8BsERkmIvPFZOpLYu6Jw0P6KSGPb4d2WSMi\nJ6bqPkJEFojJ7DdE5PepZztsh4302Wn+FXhIVTeknt0jyIHXReQJETkyXL8I+C4wVUwGf7U0M9n8\nMULMpzP5NUFE7haT2atE5PjUvZ+IyBKxcUGDiPxJUt4vZX5/E8P1GhH5qdhY4lkRuUDEJhg7+E47\nLJ+qvgC8DrTJVadCqKofflTkwBSCZiBT5t5PgJ+Fz3OADcBR4Xw4MBu4IZzvCawHPgTkMbeADcAn\nwv102p2AAnANUAXsDTQCu4f7+wEHYhMKO2Kze9NT5SoAO3dQn3uBr5W5fh8wb1PyB8YAR4c6bwn8\nHLitkzZdC+yfOv8EsA7YBxgGLALuS93/e2ynDvI7DhgfPn8OeBN4Vzg/Efj9xtoG2AKoB94Xzt8F\n7Bk+fwZ4Gtg9tMkFwB9L8rwDs3LuEOp3cLh3E3Be+DwM+FCqzV4HvhjynAa8BowO95cBzwJ7hPs1\nHZUvlV8B2LKv/2f88GMoHsAo4BVMLhwa/5dT99v6+HC+U/ifzYTzX4X+ogbIAR8N1w8E3sBc5wDe\nTSILbgO+D4wAxgJ/Bk4K9zrqew4BlgPV4Xz3VP/5Y+B74fN3gf9IlffTwJPh83ahroeG80+F8206\naJuyfTjwHHBymXfvmG6bcnlspO4nYnL71NB/DgeuwixFW2Fy6g7g0pB+Skg/B8gCh2GTWzXh/hLg\nf4FtQ34fCG3aUTtsTScypUw7XAlcnTrPA89g7m454ONAA7Bb6rf0005+i12W4aHdL+4gn45+Q1sA\nzwNfCe/YB5Phe4T7PwntcEBoz/8AburC7++n4XvdIpT7KcJ4pYPvtGz5UuX/b+D0vu4bBtvhliyn\nkmwDvKLlzfIvhfuR+zX4iqtqI8Um+OOAO1T1flVtBi6k2A+6nLn+IlVtUtXHgEexjgxVfVhVH1DV\ngppV7VqgS7OInbAGc3Hpdv6q+pqq3qY2c/smcOlGyrMVpnBGvghcp6or1GbyzsMsa+8p+3T79/9C\nVV8Kn3+OKUT/0pVnSygAk0RkhKq+rKrRNeWbwGWq+lT4HVwG7CMiO6SenaeqDar6PKbI7hOubwB2\nEpHtVHWDqt4frn8aeEpVbwztfDM2exsXdCvwE1X9S3hnSyflg6Q9t9qEejuOs5mo6nrgI9j/7g+B\ntWJW+XEhSYcuWWKW+0OBb6pqvaq2qGoM2PNvWP/4u/CeNar6lIi8C1MGzlLzSlgH1GITNtBx37MB\nUwj3EJFM6NdeShcn/L0JOCpabIAvhGtgHhy/VtXfhjLdgw2cD+9ygxlrsAmi0nd36r7WhboDrFHV\nJaH/bAK+AXxbVd8IcuqykvTNmJLXqqq/wSbrdg/Wsa9iSsqLob/+U5BVHbXDp7HfQWd9dpqa8L7I\nB4AtVHVe+C3ci7mifj7VPh22UQXHCB39ho4A/q6q14d3rABuBY5PPXurqi5X1VbgRhKZ2EyZ35+Y\n+99UTGl6K5R7AbZ+O9L2nYYxVkfli6zHZWLFcSXLqSSvANtEN4QStsVmbyIvdJLPu9P3VfUd4NWN\nvDst+N7GZncQkd2CGf5FMdfES7CZs81he8yS0u38RWSkiFwTzPv1mFWsJpr5y/A61slGtsVmNAFQ\n1bewtunM5TD9/hNE5JHgGvE6sFdn5S1HeOdUTKFaE+q/e7i9I1CXyj9+b+nylX5XsX7fwYThA8Hl\nI7p2vBv4R0kxngvXI893sXyk3vdGlyrsOE7FUdVVqvpVVd0B64fejQ3+N8YOwGuqWl/m3vbA6jLX\nd8QsHi+m+qYfYFYd6KDvCQP2xZh15uXQd48qzVxVn8HWRB0lIiOBI4Gfpd59fHxvePeHsbVU3aFN\n7nSTjdUdUv1nuD4SeCiV/jcUT5K+WjKZ+jZm8doGs5p09B2UbQdVfZvO++w0pTLx3SXlB5MPXZWJ\nlRojdCS/dgT+paTeX8CsdWAK5supfN7B2hJV/V/K//62wb7T51LP/YPiOpe2SUfli4zC2tapIK5k\nOZXk/7BZsGPTF0VkS2zm8Xepy51F6FmDCZT4/Ag2XTH6Pmb+31VVazD3tU3+3QeLzH5AnDntbv5n\nY+sRDgzpD6LzmbbHMBeByBrMdSaWZwusbf7ZhbLviM3SnYpFWhoNPNHJuztEbc3dwdhAYRU2Gw3W\n0Z+kqqNTxxaq+qcu5Pmyqp6kqtsBJwNLRWSXULcdS5LvSHGdi35PnZQPzK3w2TBD6zhOH6OqTwHX\nY8oWmPvZyFSStELyPDBGykesfR7YtYPrTcDWqX6pRlUnhfeX63t2DveuVtUDMDf23YBzO6jGTZj1\n5DPASlX9W7j+D8z1Md0njlLVKzppkiJE5P2YMvGHrj6TotO6B9L95yvYQH/PVPqt1AJxbIxXMHf9\nct9Bp+2wkT47zWPY9xBZA+xQMlG5I51P5KapyBihE/n1D8ylv7Tep3Yx33K/v3WYlWunVNL3UFzn\nUpnY4W88sAfmBeRUEFeynIoRZhYvAq4WkUPEFtzuhK07eh64oZPH0/wXcKSIfFAsXPocNj2iz5aY\nGfxtEZkAfKubz8eFpCPFFun+N/BnVY0RBjeW/8vALiXleQeoF5ExmL94Z/yaYteFm4CvishkEanC\n3A3/pKqllp5ybIF1vK8AmTCTtVfnj7RHRMaJLS7fAuvo3wJaw+0fAOdLskC7RlKLfMtll8r3eBGJ\nyvUboayt2CzqbiLyebEF5VOBCZhLSLl8OisfWHt2N0Kk4zgVQkR2FwucsF043wFTUP4vJFkBfExE\ndgjK1HnxWVV9EesTlooFEsqLyMfC7euw/vETIpIRke1EZPfwzF3AQhEZFe7tEp/roO8piMgBIvIv\nYoEQ3sYUiNiXlMqkm7E1NN/EXL4i/4HJs4NFJCsiw8WCR3RmaYlyp1pEjsD6/RtU9ckO3t0hG6t7\nmfQFTMGpFdtChNCOB3fhXQUsHPhCEdk21DfK8Q7boQt9dpp7gP0k2UrlT9h3853wW5iCueh1dT/E\n7owROnNj7Uh+/RKTX18K5cuLyPvDuzaWZ9nfX2jnnwOXiMiWYQL1LKyNu1O+Qri3HeaKutHJUKd7\nuJLlVBRVvRI4H5iPLWT9E2bS/qTa+ioov9dE27UgSE7HOsk1WAe4liS8b+nznVnFzsFM8w2YFefm\nbjwLsFhEGjAXt6uA/8Sscl3Nfw5wfXATOA5zhxmBKTr3Y4OFzsrwU+BwCb7+amsNvospomuA91Ls\nK98hwcd9ATaQeQlTsNIzo11t1wzWof8Tcwf8KEEwqertwOXAzcH14nFs4NFRnul3HgD8SUTWY8rs\nGar6rKq+ignNs7F2OwcLcfxaST4bLV9gGhYoxXGcvmE9thb0zyLyJtYnPYb9j6OqdwO3hGsPAndS\n/D/+ZWwwvgqbyDojPPcgtiboKmwguQyb4Qc4AVvwvxJzu/tPEgtZ2b4HC9BzbUj/LNb/xP2ZivpL\ntbVa92MR2m5JXX8Bs26dj8mxf4R6djb+ujPInX9gCuaCUK+2bOmeHOus7uXk8QwsmMSfQj9+N8XW\no43J3Mex7+1VbD1XppN2EDbeZycvVn0ZC6zx2XDejLlnHoZZeBYDX1bVv3ZSv9LydnWM0FleHcmv\nN4GDMbnzT+DF0CZRSexoPASd//5Ox5TRv2GeNTdigTk6yrOj3zih/j9JjdGcCiGqG/vf7KEXm79t\neqZhZ0KEHqyD2hH7UX1OVX3txBAmuBu+jpnzn9tY+sGGiFwCrFXVur4uy0BHLLTvF1W1S4qpM3QR\nka2AHwETsQHLV7FAMS6fHKcPEZE9gOtV9cC+LstAJ3jErMAidL7S1+UZbPSZklVUCAuU8E8sjObp\nWIS6K0RkBhba1XeiHmKEwfDvsFmuBcD7VXX/vi2V4zhDBRG5HltL8e8iksPcbS/A5ZPjOI7TBfqL\nknUw8F1V/aiIrAIOUtWXRWQ8sExVJ2wkC2eQISI/xEK5C+Z2cIqqPt23pXIcZygQ1gE9oqo7l1x3\n+eQ4juN0if6iZP07sFxVl4rI6yHqGSIiWKjW0X1bQsdxHGeoICL7YOv2VgKTgYeAM4EXXD45juM4\nXSHX1wUIEWKOxBZaFqGqKiLttMBy1xzHcZzBgapuajTRSpHDtmo4TVUfFJFaoMgt0OWT4zjO0KM7\n8qk/RBc8DHhIbRdysA3XxkPbzu5ryz2kqoP+mD17dp+Xwevp9fR6Ds069lU9+wkvYFarB8P5LzCl\n6yWXT/3r99IfjqFab6/70Kz7UK23avflU39Qsj6P7QERuQP4Svj8FeD2Xi+R4ziOM2RRC8f9vIjE\nsNWfAp7EQom7fHIcx3E2Sp+6C4aN5z4FfCN1eR7wcxH5N0KI3D4omuM4jjO0OR24Mbi0r8ZCuGdx\n+eQ4juN0gT5VslT1LWCbkmuvYYrXkGfKlCl9XYRewes5uBgK9RwKdYShU89yqOqjwPvL3HL51AFD\n9fcyVOsNXvehyFCt96bQL6ILdhcR0YFYbsdxHKdzRATt+8AXm4zLJ8dxnMFJd+VTf1iT5TiO4ziO\n4ziOM2hwJctxHMdxHMdxHKeCuJLlOI7jOI7jOI5TQVzJchzHcRzHcRzHqSCuZDmO4ziO4ziO41QQ\nV7Icx3Ecx3Ecx3EqiCtZjuM4juM4juM4FcSVLMdxHMdxHMdxnAriSpbjOI7jOI7jOE4FcSXLcRzH\ncRzHcRyngriS5TiO4ziO4ziOU0FcyXIcx3Ecx3Ecx6kgrmQ5juM4juM4juNUEFeyHMdxHMdxHMdx\nKogrWY7jOI7jOI7jOBXElSzHcRzHcRzHcZwK4kqW4ziO4ziO4zhOBXEly3Ecx3Ecx3Ecp4K4kuU4\njuM4juM4jlNBXMlyHMdxHMdxHMepIK5kOY7jOI7jOI7jVBBXshzHcRzHcRzHcSqIK1mO4ziO4ziO\n4zgVxJUsx3Ecx3Ecx3GcCuJKluM4juM4juM4TgVxJctxHMdxHMdxHKeCuJLlOI7jOI7jOI5TQVzJ\nchzHcRzHcRzHqSCuZDmO4ziO4ziO41SQPlWyRGQrEfmFiPxFRFaKyL+IyBgRuVtE/ioid4nIVn1Z\nRsdxHGdoIiJZEXlERO4M5y6fHMdxnC7R15asOuDXqroHsDewCpgJ3K2quwG/C+eO4ziO09tMB1YC\nGs5dPjmO4zhdos+ULBGpAT6qqv8OoKotqloPHAVcH5JdD3y2j4roOI7jDFFEZHvgcOBHgITLLp8c\nx3GcLtGXlqz3AutE5Mci8rCI/FBEtgDepaovhzQvA+/quyI6juM4Q5SrgHOBQuqayyfHcRynS+T6\n+N37Aaep6oMiUkuJ64WqqohouYfnzJnT9nnKlClMmTKl50rqOI7j9AjLli1j2bJlfV2MIkTkCGCt\nqj4iIlPKpXH55DiOM7jZXPkkqmVlRI8jIuOB/1PV94bzjwDnATsDH1fVl0RkW+BeVZ1Q8qz2Vbkd\nx3GcnkNEUFXZeMoeLcOlwJeBFmA4UA3cCrwfmOLyyXEcZ+jRXfnUZ+6CqvoS8LyI7BYufQp4ErgT\n+Eq49hXg9j4onuM4jjNEUdXzVXWHMAk4DfhfVf0ycAcunxzHcZwu0JfuggCnAzeKyDBgNfBVIAv8\nXET+DXgW+FzfFc9xHMdx2qILzsPlk+M4jtMF+sxdcHNwdwzHcZzBSX9wF9wcXD45juMMTgaMu6Dj\nOI7jOI7jOM5gxJUsx3Ecx3Ecx3GcCuJKVi/T1NREU1NTXxfDcRzHcRzHcZwewpWsXmTp0mvZcsvR\nbLnlaJYuvbavi+M4juM4juM4Tg/ggS96iaamJkaOHE2hUAAKQIbGxnqqqqr6umiO4zj9Bg984TiO\n4/RHPPBFP6WpqYlCoRVTsACUrbYa35dFchzHcRzHcRynB3Alq5fYe+99MQXrUWAVZsl6k5UrVwLQ\n0NBAQ0NDH5bQcRzHcRzHcZxK4EpWL7Bu3Tqee+45QIADgJuAVkC56qpFTJt2AjU1W1NTszXTpp3Q\np2V1HMdxHMdxHGfz8DVZvcCKFSvYd98DMQsWwITwtwXIYrpuFlCglfr6V6iuru79gjqO4/QxvibL\ncRzH6Y/4mqx+yIYNG0qu5DCFCsyiVQAuIH4d3//+D3utbI7jOI7jOI7jVBa3ZPUCq1evZtdd9wxn\nirkNxs/xbxaw9Vn5/CTWr3/NIw86jjPkcEuW4ziO0x9xS1Y/ZPvttw+fLHQ7nEISZXAGZtkqAD+x\nVIUCjuM4juM4juMMTFzJ6gWqqqqYM+fCcHYe8IPwWYG5QCNwEDAPmEBra4FrrvlR7xfUcRzHcRzH\ncZzNxt0Fe5GamnE0NLyBhXHfh8R1sDWkyGIWrbvIZg/nrbfecJdBx3GGFO4u6DiO4/RH3F2wH/PM\nM0+GT29iCtaD4TxD8lUUgENobW3lC1/4Si+X0HEcx3Ecx3GczcWVrF7EwrJngQ+EK9djytaqcCim\nZJ0KrOLWW29lwYLaviiq4ziO4ziO4zibiLsL9jJXXLGAGTPOJdFvMxTvn9WMuRA+AhxAJpPl7bfr\n3W3QcZwhgbsLOo7jOP0Rdxfs53zzm9/Amr01/P00plxNwJSrfDj2BwoUCs0eBMNxHMdxHMdxBhBu\nyeoDjjrqWO6881ZgGOY+2IIpXU+HFNGilcUUL6Gxcb1bsxzHGfS4JctxytPQ0ADEpQeO4/Q2bsnq\nRzQ0NLBu3TqampqKrv/nf/4sfFLgIeCPmEJVSg6zasERR3y25wrqOI7jOE6/Zdq0E6ip2Yaamm2Y\nNu2Evi6O4zhdwJWsHuLYY6dRU7MN48Ztx4gRNSxdem3bvaqqKmprF2NWqsnAh7GvIu02GC1cMwC4\n55572maxHMdxHMcZGjQ0NHDLLTcTg2TdcsvNPh5wnAGAuwv2AMccM43bbvsvYDnmErgfmYwWBbBo\nampi1KgxNDffAEwFngKeBD6LWbBi/QSLOFhg223fw5o1f+/l2jiO4/Qe7i7oOMU0NDRQU7MN6SBZ\na9f+k+rq6i4vI3BXQ8fZfNxdsI9paGjgtttuw5Sj95MEsGgpchs0a9ZVZDJfCGkBxmMKVWlY9xYg\ny4svPs+6det6rzKO4ziO4/Qp1dXVTJ06jejtst9+B7DddjsxatQYFi6sa7ckoRRzNdyampqt3dXQ\ncXoRt2RVmBUrVrDvvgeSzDhNAjYArdTVXc0ZZ5xalL6pqYntt9+FV15ZhylUiild6bDuAI8Ckznh\nhC9x/fX/3tPVcBzH6RPckuU45WloaKCpqYntttuJ5ubl4epkMpkMV1+9iFNOOansMzU1YzEPGYAW\n6uvXuUXLcTaB7sonV7IqzG9/+1sOO+woEiVpImaJAsjR2PhGkXm/qamJ4cNHhbP4zB4k7oKTgMeB\nBzHLWDONjY0eadBxnEGJK1mOU0xTU1ORtWqrrcahmnZEeoh8/gD++c9nGTt2bNGz69atY9y47Sh1\nNSxN5zjOxnF3wT7mrbfewixRk4C9sNDsM7E1V61l3f0ymdKvIYcpZv8D/Ee4tn/b3fnzr6p0sR3H\ncRzH6WcsXXotI0eObossOHr0eFQLwBPhaAWgubmZcePe3c4dsLq6GpE4xmgClJNPPt3OSpQ3x3Eq\niytZFSafz2NWqO+krq5o+7TDDu9tF2nw6qsXhWcmYMrZ+Vjo9kOw6INg0QYVyDFr1oXeMTqO4zjO\nIKapqYnp08+kUIC4Tts+K/DjkEqBPYFDgafaRR6sqqpi/vzLMQ+ZyUCW2267lc985ni23HI0o0aN\nYdGiJb1XKccZQriSVWEmTpwYPl2CzTKtwixSuxE3Fj711DOKlKRTTjmJtWvXYJ3lBmAOSfCLR8Pn\nVszCNQwQLr98fm9Ux3Ecx3GcfkMLNpa4DFOcBJuU/S1wA0C7Sdj169djQbVmE/fkvOOO22hpgebm\n85k+/Szq6lzRcpxK40pWhdlll13YcsuaDu7+BVOcCsycOavoji1CFUyhuitcvYnETTCDda4fB5TZ\ns7/r1izHcRzHGaRUVVVRV1eLSIHE02V2uJvHFKcMNhm7CpvchW23fQ8LFtTS1NTEokVLmDPne9j4\n4hJsjfeq8NxpwFwgw9lnn9PmPuhjC8epDB74ogewYBZbkihNh2GzTA8Co7DOssD48Tvw4ot/b3vG\n9s06G5hHYrlKIgJZh9pK1I0bG9/yABiO4wwqPPCFM5SIEQM72/OqoaGB0aPHUSg8AlRhY4gLgEux\nMUYeW6JwCcm4QxDJkMlAa+uTIacJmEJWhQXlak29RTn66GO58847AKirqy0brdBxhjIDKvCFiDwr\nIo+JyCMi8kC4NkZE7haRv4rIXSKyVV+WcVP40pe+RqIU5YF7sI7vAKyTOwwYxksv/ZM99tgXiH7T\nV2AuAAocH/4+Ho4Y3h3sa3MjpOM4Tk8gIjuIyL0i8qSIPCEiZ4TrA14+OX1LU1NTm2J1/PFfpKZm\na8aN247hw7dqW69dak2qqqpi4cIF5PMHkM1ORCRLLnc5ybKCxzEFS4ELw7UcqgVaW1uwgBeRvTE3\nww3YJO4qTGGD2267lZYWaGkRTj/9TLdoOc5m0tcjdQWmqOq+qnpguDYTuFtVdwN+F84HDAsW1PKL\nX/wC67wyJBGA4qbCCvyGuF5r1aon+exnjwfg5JO/Ti6XB04G/qsk5yymqP2OGIr10Ucf7enqOI7j\nDEWagbNUdSLwAeBUEdmDAS6f0qQH8g0NDUXBEpyeYenSa9lii62oqdmG4cNH8Ytf/AyT7RcArZx+\n+hnU1S1h1KgxbLnlaBYurGXRIjs/99zvcPHF3+O1117mnXfe4NVXXyKbzaZyzwPLgYuJUQSTfTcn\nA3tw6KGHYeMSDe9tBU4Kz+RJXBGXUyi0UFd3dY+3ieMMalS1zw7g78DWJddWAe8Kn8cDq8o8p/2R\nxsZGhZxCXmGlwkiF1eHIp+7lS65ntb6+XlVV586dpyAKGYVhqfRV4fk/tD03ZcrBfVxjx3GcyhL6\n9z6VTaUHcDvwqYEsn9IsWXKN5vMjNZ8fqfvsc2CbnDnmmKltskjVZFpjY2MflnTw0NjYqPl8HBPM\nTcn2YUG2E2R/TmFWuJ4pM17I6SWXXKaNjY1aV7dYs9nh4fpnwzgho5AN+VSFsUh8lrL52buOUhge\njhXhWlZraxf3ddM5Tr+hu/KpT9dkicjfgHpsOuUaVf2hiLyuqqPDfQFei+ep57Qvy90RtunfeGyG\naBUWuOKicHc28HnMXTBDEpLd3Aqff/5Ztt9++9TmxHnMnC8hfSH1JgEOBv6H+vpXfOd2x3EGDf1t\nTZaI7ATch218+I+BKp8iyfrfx4H12Cb3yUa10MpnPnMMH//4FM4917YiufLKK/jmN79etGYoWsGq\nqqqKPpfec4yk3ZdjAa2eCHcmYbI+RhEGk/lR9meAP5Os546/Lfs7d+5cZs26kGQtFiWf89i2MBdj\n440Myfc9CbN+HRDKUIoCGRob1/t36Th0Xz71tZK1raq+KCJjgbuB04E70kJLRF5T1TElz+ns2bPb\nzqdMmcLRbxjwAAAgAElEQVSUKVN6qdQdM2nSATzxxApMgSqQmOrBNiOGGPSi2FNTOPzww/nVr24D\nYNGiJUyffhrFHW1aCMbOOMvYseNZu/b5nquU4zhOD7Js2TKWLVvWdn7RRRf1GyVLRLbEFKyLVfX2\n9CRguD9g5FNk40pWdCMDmxxsAeaSzw9j3rxL+frXv8pPfnID55xjCtgxxxzLrbeae3tt7VUAnHnm\nWW3nHjwhwWT7mZhcTys6aQUr7eY3AYtKDMlYIh3wogAU2Hnn3fjb3/6WynP3kD4uKZgc0j8FnA38\nKlyPk7+xDM0kQbeioqZ85jNHc/vtP69ACzjOwGJz5VO/iS4oIrOBN4FvYOu0XhKRbYF7VXVCSdp+\nN1NoVqztSHydo+Upfhfp680kC04hzmTV17/aZpX61389hHvu+V1I3z5tMiOl7LXXvjz++EM9WDvH\ncZzeob9YskQkD/wS+I2q1oZrqxiA8qkUG+yfhVk5JmCBE8BkVIxEtxdxEJ9YQy4imSRchSlpBxAn\nEfP5SagqLS0mj3K5/Xn11Zfa5JpbuKCubglnnvltEktTDlN8LiOZfI3RAi8O51mS/bHKTbrGf5e0\nkhXXhROebcW+59eAKRSPU3LADCycOyG/iZi1LQcUWLv2BcaOHbvpFXecQcCAiS4oIiNFZFT4vAXm\n//Y4cAfwlZDsK5gvfL8nicJzMNZxrSLZiyKDhW+X1NGexYuXtuVzySUXh+d2DnfjHhnnp/LIAjme\neOIJ1q1bV/E6OY7jDEWCK+B1wMqoYAUGpHwq5YwzTqW29ioymTjwzjBx4l4Uh/SGRJY9jllPckCc\n0LsJ+CAmi24A1tPS0kprawFTvPanpaWFMWPexdKl17J06bWMGjWGUaPGtEXRG4pMn34qjY0NHHro\noSTWo2iZguL2juOHVoqVMlKfH8OUsguwccIETEGG4ujEgkUW/Hj4fB42hjgolCGGf98O+96LoxqP\nGzd+SH9vjrMp9JklS0TeC9wWTnPAjap6mYiMAX4OvAd4Fvicqr5R8my/mylM1lJF0jNNGeARzGR/\nAXHDwISo67aSzeZYtKiOU045CZHhWJSg9H5ZgnW4G4DhwMPAZD784Q/zhz/cW+lqOY7j9Cr9wZIl\nIh8B/h82go3C5jzgAQagfOqIGGGwqqqKqqoqjjlmGrfddmtJqrQsuwD4HCbLSu/Z+h1jBbbu6CGg\ninx+Eq2trRQKK4Emcrn9WbPmOaqqqtpZuSJDwdrV0NDAhz40hSeffBRTeMDatAlr49K13WBjgehe\neAHwZWwC9n5gPxLvl7RL4gQsbPtK7CddFc4J6UvTxu8y/TtuIZut4q233hgS343jlGNArcnaVPqr\nEDM3gDNIzPStFC9ATRPvF4BhwCysIzXTfGNjPatXr2bixIlY5xsPwnMx7+WYT30z9fX1HgTDcZwB\nTX9QsjaH/iqfukoM5/6e9+yC6oWYRaWZJABTdH0XEtfCGEBhf2wC8HxgHsVuhopZUlaRbGcCxx13\nPB/5yIc4++xzaG0tIAK5XG7IrOdqamrihRdeYNdd9yQZK0SXzEcxq2B055yABbm8m2KlNrr+Rfe/\ntIIUv4PvkWxcHL+TaJksfceDwIdKrrUCGerqajnjjFMrUXXHGXC4ktXHfOlLX+HGG38WzuKM0QRg\nB+C5cP3xcH03ks4wugCeAizm+ef/TnV1NTU1Y7DOLU8yw7U37SMOtpLJjKS19c2erJ7jOE6P4kpW\n39PQ0EBNzTakZc7atWuoqqrixBNPCtau6LLeQrK/UrS4CEnAhgnYep+vYmuF7gIOofy6ovi1H0Iu\nd0+btSta3MaOHVsUwbChoaHIGjZQiPX58Y9vaIvgeMwxx3LLLTeSKLGR0iAZG7A2W01aWU2sV4Tr\nj2KWrYfDtcmURpG0Cd4nKQ6GIdh6sAVES2SS3qIiNza+6dYsZ0gyYNZkDVa+9KXPkwiMdCf0NxLl\nKl5vxWYIkyg+sBTIcOWVC5k79zKKfeRvwmacBFOwvoB1pgA5CoUNfOITh/REtRzHcZwhQlVVFZlM\nDhvUH0Amk6e6uprq6mpuvfVm1q79J/l8tIJcAMzBFKy4Flkx5SwyHxvIC/BpEmXghvB3GKaoRUXh\n17S0NDNu3PbU1GzDuHHbscMO72X48GoWLKilrm4Jw4dXM27cu6mp2Ybjj/9iTzZHRVm69FpGjhxN\nTc02nHnmWTQ3f4fm5uXceut/sXbtSxxxxNEkMh7gHIrXZIMFGnkCa+vYltG7ZUbquRZMuYrRA9NE\nb5oJWHyXGSSuiPOwsYltYmzKVVVbHvPn1+I4zsZxS1YPYGupkgWjyTqqx4Fa4FpMqMR9KaKVCoqj\nB6ZnCvPhfunsH1jH+HB4Fo4++jhuvfXmCtfKcRyn53FLVv9g6dJrQ7hxqKurbee6t3TptW2h2mfN\nOp/Zs6OSBUko+Oip8X+U248r2VMSEkWghUTZKgAzsah38TzODSsmR8317fLLL2P69NOK9u0Citac\n9TVNTU1sueVoWlqiq//PsTXatkwgl8sgIsydexHr17/F3LlzSdZMCVbfTwK/pX249nQ7Nqfe+m5g\nTfgc3TxbMUtjE7AviYKWDvn+IMneXBnguyTRJZXGxrf7RZs6Tm/i7oL9hDFjxvP66y9jndNR2ExR\n9KFOd5rlBE1UsqDYLTCtjE3AQqz+FetQ0+4WrdTXvzbgXCgcx3Fcyeo/bCzkelqZGTlyNIVC2l0N\nTL5dBBxDsbvaHnQccKH0WnobFIDxwEska4suCXm1kM3mOfroY7j99ttQVQoFRbVAJpPj6qtr+bd/\n+0qn9elpEiUrXomulp8nUUxtffb8+VcAcM45Z5MolsuxtVIHk7j3RcopXekAGpC0p4b3XhLKcAFw\neepedDeMroIFoqugUWDevHnMmHHOJreF4wxEXMnqJ1gQjOmYO8UvSXzV9yDxVVcS//Q0saMr3cGd\n1PUZmEk/3Xn+EQvHuoFMZrivz3IcZ8DhStbAJG35amlJ1u9AgWw2Q2tr3Dw3uqQ9SXHkvPSEYpRr\nE7FJxCqKgzBEBSBOSpaSBc7F3BT/H/AxQNssRemgGr29d9fChbWcffZ3KJ5YXY4pQ/Fnb8sIDj/8\nKH7zm1+jGi146QnXGEr/AIotV5FySlZ64+MCybrxvcL1mZiyFdd6xYnb+Hsu3tzY12Y5Qw1fk9UP\naGpq4qyzzsZm2Q6g2Ff9L1hHFX2pryeJ2HQDiVXqUZJNiKOP+wpsxqmACY/S7/lNopthodDEihUr\neq6SjuM4jhM45ZSTePPN11mz5jlMXj2BKVLKiy/+g/r6teRyOcx1MA49Ph+uFbDw4lEuxr2eZtJx\nhF5Ioh4eTvH+kQXgCkyZ+HA4b6alBZqbz+CMM6azbt06Fi6s7fW9u77+9a+VqcP+mGUpKkDmLvnr\nX/8S1UNS11uIVrvi9d05zI1QsTacjbXh/lj7xPb8DlHxtbY6AFN0m0P+l1C81kuAC0kUrv3DYWOP\n0rD7juMU40pWD9DQ0BBmnk7EOr5S0jNvN5IoS58vSVcqWDZggiMuelXMNWBCuP8pzMK1HBD23fdf\nNrEGjuM4jtM9YqS/bDaJjpfNZtuCZhx77HHY2qwWYAIie7JgwZWIJBvsigizZl2ASAEb9Gfa0pui\ncChmSYkb7grwG5IJyQK2nqh0kjIqcwtobW1l3LjtOfvs79DcfD7NzY8zffqZvPDCCzQ0NBTVKUYC\nrBTV1dVMnTqNZONgMKvU50MZ4/rrqAz9NrRBnmTIlkk934IFFbmHZD/NGIBrA3AYSRteQgzFnmx6\nnKyzSt6d5mKSNeZPkIw9WjjqqOM2uR0cZyjgSlYPYOZzxTrA+zAhMCkcgoVVnYB1iHMoXps1OpzH\nxaixI42zTqVuAbEjjtfnhfxtkfADDzzQAzV0HMdxnPZUVVWxaFEd+fwk8vlJLFpU1xaM4r/+6xeY\n3FsBPEo2m+Hkk7/O4sWL2tIvXryIWbNm8sYba6mvf4Ujjvg0iftaC6Z0HIJZxAD+THnlIE0e20e6\nQKJ4ZTEX+7nAT2hpaWWHHXampmYbjj12GuvWreN737uELbbYilGjxrBwYW2bwrW5StfNN/+U+vpX\nWLDginBlMjZhml6vHffGvCAccYwQowJGy9ZpmPIUrU0TKV7L9ivgEZI13aXRH3MkgUbOx8YpEzAr\nYrSalSPLfffd104pdRwnwddk9RBHHHEMv/rVnZhV6YOpO7FzPA/bNyT6lMfZpSoSgZLeF0vC9SzW\nWZYumG0Jz2dJFC7bFFm1saeq6TiOU1F8TdbgoHStU3FkPVtflc9PYv3614oiAl533fVtUQtra68C\n4NRTTwu5lgbJyGAu+Om1XeXWNM+mffCNCSXpSgNupCMZTsJc+AWRHLlchiuvvIIvfOFzbXXc1AiG\nTU1NzJo1OwS6yAH3Ah+nfSCL9HqoaHnK0H699qNYYJCDU+1RuqnxRJKoxRdgbSck6+VawvN3pfKI\n74jumDHoiKJabk2Y4ww+PPBFP6GpqYnhw6tJOqU4G3QE1nE1Y53bJeF6XIgaO81ozofiiIOxExTM\nbRCSDjPOgG3AOk8BmjnnnBlceeVlPVJPx3GcSuJK1uBl6dJrOf30MykUWshmsyxaVFcUGr6pqYlR\no8bQ3GzKQC63F6pKa+tMTFa2DxaRyZjMLBTiuiKbXIQ/AB/FAmAsJFm/FYNHZLE1Y9A+DHpUwM4B\nTgD2oVix+TjwvyGt/VRFstTWzueMM05ts3Z1R/Fat24d48Zth1nXPpwqyx7hb5T9raFuBwGNJG6R\ncUI2XcfHgFsxJSpLsu9mem/OmD7ez5GEzV+OhY2fXPKOWViAjA2AMmHC3vzlL490qZ6OM5DxwBf9\nhKqqKurqFpJ0isuxTuwubDZpFYmJfxKJhSpHsvFfegPCOMsESWcffdSjwhXdAL6KzVxZuvnz57Fu\n3bqerbDjOI7jdMIpp5zE22+/Tn39K7z11hvt9t4qR2trCzagz2HybgImE6vIZrMcccSRFAoxEMR+\n4SkFfo3JwIVYwIcciZIR5fJNmOKQoXidU1zHtABTsKB4TdQyTO7msc2VQbWV6dPP4vjjv8gWW2xF\nTc02jBw5ussBNcaOHRvWan2YJPjHbqGcSjIOKGDeMWnr0U2YpSrWbRbJEgNCuZvCvT9irpMxbbyf\nVsAuC9c+iO3lFanCxiefDe83V8NVq57khRde6FI9HWdIoaoD7rBiDwwuueQyhbzCaoVzU59Xh8+Z\nDq5lw5FTGKkwN9wbFqafJJWu9PmcwojU55xCVnfddUJfN4fjOE6nhP69z+XMph4DST71R5YsuUbz\n+ZGaz4/UurrFKjI8JQdXKsxRyGs+P1IXLKgtI/+SNMXX87rlltuk0qwsI4NXhnc9EP6uTH0emcpv\nRLg3Itwrlb9Jumx2uNbX12tjY6OqqjY2NrZ9Lkd9fb1+97uzg2yPMj49DhiZKjdtdSsu/8iSMs0J\n6YeFeyPD5yqF4aEes0raLLZ3zH946rl4Pie8z8q5ZMk1vfUzcZw+obvyyd0Fe5iGhgZqasZS7Osc\nF5nGcKzl3BQUuBvzi457WaTvRRP/KcA1JDNSkzBLWek+InFH9xzPP7+a7bffvsfq7DiOs6m4u6CT\nXs+1dOm1nHba9BCxV8lmsyxYMJ9vfvPrNDU1UVOzDcXyM712KX0dEtkZvUJaMQtPjsT9fvdUujxm\nBZuLuc3FNU17YREB98csOvHZKKNLzzNksxmOPvoY/vu/bwdg/vwrOPHEL7e5FMYAEtXV1W1tcNhh\nR3HvvctI3P9iGY5PlSVSbjPiWIaO9rqagW0H00LiKlhu/y7FxiE/w6yK5cYrSi5XxZtvvu57ZzmD\nll5fkyUiWVVt3XjKyjHQhNhnP3t86Fjz2KaIvyNZcDoX69zSYVubSXyk0xyKharNkHSYcfGqkkQf\nSvuaT6JcRMJx47blH/942jtDx3H6Fd0RYn0hfzbGQJNPA4F0RL/SdU7Tpp3ALbfcDMC+++7HE0+Y\n8jFp0mQefnh5SHUBtv3Jcsz9r1ywjEj87maTBJY6DItqqKn0URFTiic5nyjJ40/A/9BxcI0ckydP\n5tFHbU3T1KnTuPnmn7bVd8mS73P22d/G5LrQfs1WOkhHjFScViTjWrXYZtHlMSpWWYrXe+VI1pDH\nMl+IjVVKN4aOymZUxAo0Nr7t4wpn0NIXa7KeFpErRWTPCuQ1KLnllv8gaer7wt+4L0aMCrg8HNGy\nFRWsG8K1mZhyJtjsU+xgo492/CyY9Sv6lsc9uValntmVtWtfZPjwkb22AaPjOE4P4PJnCBD336qu\nrm43gI/h0OvrX+Hhh//E+vWvsX79azz00P2sXfvPsNnx50JqC9Rg1qtLSeRiDJaRSV27lCTM+fcw\nmfwgyXpnQl5/CdcymLUnE9Ip8P8wBWtVuJcmi1mmCkHBehR4lFtuuZmFC+vaNkkePnwkjY3vcMQR\nR4Y8P1CSj4R8SgNbtJIE+0grUY+HQzBvGQ3nT6TSFIhh9hMPnBiQ6+MkYeJnkChv9u5jj52G4zhG\nJSxZ1cA0bOfdLPDvwE2q2mObJwzEmcJFi5YwffqZ4SzOfsXZsNg5xtmo9AxVnJVKz4Dthe0R8n6S\nTjVLsRtANfBG6n0d5ak0Nr7pM0+O4/QLumnJ6nX504UyDTj5NJhZuvRazjzzLFpaWjGjZ9zqpIVi\n17g4wflEuDaBXC7H3nvvw8MPP0ixDN6DZIJzNhYefm9Mnp+LRSSModYzJLJ5//A3Tq6ubHtXsoxg\nA7lcnpaWJ4Amcrn9ufzyS5k58wIAmps3UGxBk1CGSzGlKr3dSzp0exOJC2W04sWxR3p8cC/wKcwb\nJkYTBHOBLLX+xTZI/7sWmDfvMmbMOAfHGWz0aQh3EZkC3IjtqPufwMWq+kzFXpC8Z0AKsQULajnn\nnLMw9757Kd4Lo3Tfj3gt7ntVqigpyQ72G7CZrPS6r5ZwbSVwFuZmCEmnGn2sJzNmzFheffWfla+w\n4zhON9nUNVm9JX+6UI4BKZ8GM9H1rqmpiR/96MfMmHEera1K4mmadsE3i5ZIgZdf/gfvfveOtLSk\n3QSjPE7L6ajspNc+SUhzNrYhMKn7aeUouiQ+CNxOsq3LocA9JPtm2tpskT1DuaNLX5T90YUv7T5Y\nuj/WHrRfB74HiedMHBvEdkh7yawoyWuv0BbLgVEkiqqVq66uljPOOBXHGUz0urugiORE5DMicjtQ\ni8U83Rm4E4uh6gROO+1bqbMxFDd/DuuswBauTgj3Z2Hm+AKJC+BsbFapQLJ2S0lCvEKyYWBTyEMx\nv/T4TgVs/PHaa+u49NJ5lamk4zhOL+Hyx+kKcR1XdXU13/72dN5883XeeecNamuvIpvNkstlqK1d\nSG3tQnI5IZdTFi+uawtCUaxApRXoG8LfYZhcVkyxiduprMe2bYkuiFFpiVuuXEQSqOIDJC6MF2Br\nwAQLES+YFexHZDJCLpfHJmvzJG6BaaL74GRM6YljhwtJxhmRuA48hnhPlzXWJYOFxy+36fCwMteE\n6dPPalNuHWeoUgl3wb9hm0b8SFXvL7l3taqevlkvKP/OATlT2NTUxIgRW7VFSSqe9UpHHIy7rd+D\ndWAZbNPB+FycnE1HUtqb4uhHcTYLEsWr9H4zcBRm5WqmsbHR3QYdx+lTuuku2OvypwtlGpDyaaiS\nDqhR7jyJbph2q9uDZG+ptMvhBoqjAcfAEjHNRNq75xWAv6bOH8T2p3oidS1GC46RAtNWtGZMtqct\naCtSZUpbpp7ClKl9aL/vZnRhLI3UGKMU348pgnGcAhYQ5C6S6MWRDNDC88//3SMZO4OKvgh8cYKq\nfi0t4ETkIwB9IeD6O7lcBvg2iRWqGevgnsAUoKh8LcGCXbyNddxxI8Qs1sFPSOVaFe6lZ5nyJJ1e\na5n7kSRikm9Y7DjOAMPlj7NZlEYrLD0/5ZSTeOONl8nn86mnYlCLXOpaXA+1H6aU5LDIgorJ64nY\neq240XD0VkkPw7LAgSRKTDkUeBGAfD7P888/jwjEwBl2fz9g35B3FTCcZLPlvcPn+8MR11VFi1Qs\n26cx98CoyB0AfBJzfWwGdsECZ8StaDKYN020jMH++3+4k3o4zuCnEkrWojLXrq5AvoOOqqqq4J5Q\nSzKrtILiGSBIOsPowhcVsmEkHWFUmCZjSheYUjYB2BM4NaSNEYGiu+BeJApajiTgRpZXXnmlIvV0\nHMfpJVz+OD1OdXU1tbVXkc9PIp+fxNSp08hmP4bJzwlksxNDyrhWagNwCHAQiXxvIZHpYHL3EUwu\nR8VmFsmYIMrqj2Nyfq+QVoGPkcvtxdy53+NnP7s5eMdUkUT6exjb34uQV1R+osWpgAXOej/Jmq8n\nMCUtetgswFwLFRtb5DGr1aHh898wq1grcHp47hJiKHeAtWvX8MILL3SjpR1ncLHJ7oIi8kHgQ1hU\nhYUkPcko4GhVnVyREpZ/94B2x1i3bh3jxm1HseuBUrzxYXT1izNEaZeDOLO0msT03wI8jZnzY1TB\nauAdrMNvwRSvU7GZrHQEIvvqTj75a/zgBz+odHUdx3G6TFfcMfpS/myMgS6fnI5JuxKW7t113XXX\nc9ppZ6Aaw52DTXQuxyxLf8J+njGC3ydJ1lNHK1gMNhFDsEMS/CpHcZh2SFwBoxyPLn9/wBS86HIY\nXRnj8+X26zoSU6JKPV6E4sAacZPivVP34/Ft4ErSyyF23HFHnn12ddn2dJyBRm+6Cw7Deoxs+Ltl\nOBqA4zYj30HP2LFjOfLII7HObRIwHuuUvoNtmCjYjNUTFPtal7Ir1nnHMPC7YQpWXLjagAXYiB3e\ntZhCFjvkOOP0IADXXffTitbTcRynh3D54/Q6aVfC0r27TjnlJN55p561a1+k2DtlJqbYvB+LNCiY\ndaqAhUoHW8cVg01EeZ+2TEW3xFkkLoG7hbzymBtiVNQK2PxD2uUwKk4FypPH3AAfJ1G+YlnisoY0\nPydRrGaGa63AZSQukKYUPvfcs2y77U4dvNdxBjeVCHyxo6o+V6HydPWdA36msKmpieHDR2EdYQ5T\nqi6hvbVqGEmI9tLd5iNxcequIa/SPKIljNRz6RmzCeGZZtauXcvYsWMrVk/HcZzu0M3AF70ufzbG\nYJBPzqZTHOCqNFz67rS3Iikm38/HvFjKbdkSZfyeJBarmE9676pJWFCM6AIYrVAxNHs+vOdiEoUr\nvc9XOmjHoyHtL2kfnp6S8kFiRYubMQ/D3Bwt+MeECXvyl7+swHEGMr1myRKRuvBxsYjcWXLcsan5\nDhWqqqqYN+9Skk7rcxTPfuWwSMSKuQWCdYqxs4zWKrDO8QaSDYYnhUMw5WqvVNo401XATP7pcK05\nxo17F0uXXtuuvGnXCMdxnL7E5Y/Tn7EAV+d3MfVjmAXpIuAcErldyk0kStuscK2JJOz7qpDPQ+Fz\nOuS8pu5fgily/xOuf57EMjUZC9AB8CZm3Yqh4mM+pdawPMmyhu+GfN6PedkkY5pVqx7j8ssXdLFN\nHGdwsDlrsg5Q1eVhA8h2qOqyzSjXxt49KGYKzZpVTeIjHTcjjh1TnImK4Vp3JZmNKg0bm56pim1z\nBLZ4dQLwR2BKSBs7ykdIZptiOFqbjZoy5WNkMhm23357WluVG2+8AcixZMkSTjnlpAq3hOM4jtHF\nNVl9Jn82xmCRT86ms3TptZx55lmoKuPHv5sXXvhHuJOW7fE8HY69ozSlFrG9SMLDt1De6hXz+1cs\nCmCp9SxHMuFazroW3x2tXxdRbFErhHsHY8pYDLDVgi11qErllcHGHvhWMc6ApruWrM12F+wLBpMQ\nW7CglnPOOYtkQWoW6/xWhhSl7gSzSQyQsfP7HkmnWEjlk957g/Ds9yjuWKNSV7rJopbcg+gy0NhY\n752k4zg9QneFWH9jMMknZ9NJB8VYt24d1157HbNnX0Rrq8nfTCbLxImTePzxRzGZfzoWw2UYtvXb\nBzHLUxXwPoqDX+0ezv+MBbuKY4Io1+N6rBjcKr0P52xsAvYALMLxj4HLKZ64vR+zRpVO5i7H3Aej\ne2IcH5S6LcYlEBcB04E64rquj33sE9x33++60ZKO03/oNSVLRB7v5Laq6t6d3N8sBpMQS9ZmxVDq\nOUx5Sm9ECIlVKx7pCEPlIgXFfbFi50rItxlbdHsvSYTCuGniCMx1YQLmSjAes3IV5/373y/jIx/5\nyOZX3nEcp4QuWrL6TP5sjMEkn5zK0NTUxKhRY2huPh9z72tmwYIryeVyTJ9+ZkiVw5SgYbRXciZg\nnizPhPP0OEAwCxOY4nQ/pqA1h/sxKmEMjDEHcxlswRShK0isUYq5In6O9rI/esAIifK3GzbWeDS8\nOx2BcEOqBaIly5TBww8/kl/96vYut5/j9Bd6U8naKXw8Jfy9Afvv+yKAqs7YpIy79u5BJcTq6pZw\n5plnkQS6iO4BaUtV7LCiq+CTwFEl18A6w3SY12i+B3gX8Fr4LOF9WwFvkbgdxIAY92KRCdsrWSDu\nNug4To/QRSVrp/Cx1+XPxhhs8snZfJqamthyy9G0tEQFBfL5SagqLS3pCdXocpeEQDcOA35D4tYf\n5XQmlSaGgy+UPAtmvfo8iZtflOkxQuEwLNLhb1LPlHqxxDECFFuq0mlKLV/ZUMYWkklfSzt58r6s\nWPHnjhvNcfohve4uKCIrVHWfkmuPqOq+m5Vx5+8cdELsoosuYc6cC0k6pBxJpJ9JtO+kYifcTNKR\nQTIzFWeUoiUsEn3Ao/UqKnTPpNJHV8HSjl6AkcD95HL78+abr7vboOM4FaWb0QV7Xf50oUyDTj45\nm08ymWqKSHslay8saMUkbA3V4Zjs/TPJ/lpxTdTuvO99u/H000+TbOESlwGATc7OI5movRRz9ds/\n3H+CxL0vWsRKIxpGq1YjMB8bezxMMiaJGy7/D8n4Ix29OIONR8xyl9yL0Q4LPPPMU+yyyy7tgmql\nx5RYnLYAACAASURBVBUx6FY6fL7j9BW9uU9W6p3ykdTJhykOk7exh7Mi8oiI3BnOx4jI3SLyVxG5\nS0S2qkAZ+z0zZ56DdZBxpiiD7WkVO7sLsc6pORwtJNau9Jqqz5XknCMJ674qpHlfuKclf0mdtxDD\nxF533Q+4+uqF4X3nAAfQ0tLCNdf8aJPq2tTURENDAw0NDR6x0HGczWGz5M8mvvBQEVklIk+LSJ9Z\nzJyBxfTpp1JXdxX5/CTy+UnU1l5FXV0t+fwkTM5fgCkwGcxVfxYmi99PNjuRTCYX7t8ECE8//VS4\n/xi2hjsqL4IpRTGa4KWYQrQ3iVzfHVOwZpNM3KbJh3wvB2pJvGMOCO8nvPu34fMDIc2j4YgK36Uk\ne2/FccpO4TzDrrvuzn77fYCRI2sYPryGLbbYilGjxrBo0RLAAoiMHDmamppt2GKLrYoiH6cjHnv0\nY6ffoqqbdWBTI48Bz4XjUWC/bjz/beBG4I5wfgXwnfB5BjCvzDM6GPnWt05LxVvNKQxTyITPIxXm\nKuRTRzo+a17huwojwnMxzZxwbXU48iG/bMib8Ln0HVkFtLGxsa18tbWLw73VCis1lxtRdL8rLFly\njWazw8P7rOynnz692/k4jjM4Cf17r8if7h7YSPIZbKSYB1YAe5Sk6dkGcgY0jY2NRfKusbFRa2sX\naz4/UvP5kTp16peDjMyryHCdP/8qbWxs1CVLrtFcbkRKBn83fE7L7cNSsj8t82cFmV6lcF74HJ81\neV48bpibejarMDykWRmuVaX+5hQ+VTLOGJl6x+qSvDIKB4fzOF6JY5Ak7dy580I7jGy7ns+PbGuL\ndHvFz7W1i30s4fQo3ZFPqrr5SpYmgqUGqOnmM9sD92CRGO4M11YB7wqfxwOryjzXA03X9zQ2NhYp\nH0nng8JloaMZ0a4zso4udq45hXMVrgnnw0sUs9h55kJn995U57cy1UFaOebPv6qofPl87NBHKuR1\nwYJara+v1/r6+rJ1qq+v17Vr12pjY6M++eST4V0nlpTJOvfa2sUdPus4ztCgu0JMN1H+bMqBRRT4\nbep8JjCzJE1PNY0ziEkrX42NjVpfX99O9q1duzbIzJVFykeUpdnscBUZpsnkahwfVKXkbVRczitR\ngqpSyk5Mu7UmE74jw1Gl7Sdus5ooacPDGKF0wneYwk5tYwcbs6wI12NZ4/hkRMgzKob2rlxuhK5d\nuzaMQ6JyGOtgimY+P1KXLLmmL75CZwjQa0oW8OXw9+xgjYrH2cC3u5jHfwL7AgellKzXU/clfZ66\n3kPN1/fMnXtZiZKV7hyHKYwPHU+6g0PhBk2sXunOJ221ivfSFrHYqcZjROq+KAzrxJq1OpUuq1On\nfrlIUEyd+uXUO9IWulxJHiPartfVLS551pTBb33rtA4VOcdxBg9dEWKVkD+bcgDHAT9MnX8JuLok\nTY+2jzO0Oe64L5SRoXk9+uipJZaulZpMppbK7DlBGUorVFHerkwpP8M6eL7cRO8wTSZ103I+WsDa\nl9ksYPGd6bzT+YiaVa9Ks9nhms+P1EwmKnkrUu9ob/FynErTXSVrc6ILnqyq14jIHIoX9UgoxEXl\nn2x7/gjgMFU9NWwoebaqHikir6vq6FS611R1TMmzOnv27LbzKVOmMGXKlE2qR3+kqqqGDRsawlk6\ncuAeFEcSgmSha9Rj4t5W6V3ZFfPvnhvOOwr5nt7QeFtgTUjTHAcPqVC06cAa8b0gAtlslrlzL2bm\nzPOATwO/Du+I6UrDve6FrTO7n1zuINaseY5x47bD/MXnkviZw9SpU7n55p923oCO4wwYli1bxrJl\ny9rOL7roInTj0QU3S/5sKiJyLHCoqn4jnH8J+BdVPT2VZlDLJ6dvSSIVzsBWVzQjkiGTEVpbnyQJ\naJHD/jXuAT5J+703IQlwFYNqxf044zouJYlamB4zxL04oTjS4IOYbE+PJdJ7e5WOPSiTRzakewiL\nbqwk67meSj1r10QyiEChUCjKe/78K/jGN77WLmBGev+yzq45DmyafCqiOxpZJQ/sv/h54O/Ai1gc\n8Ruw/5LxIc22DCF3wciee+6ZsvykZ6VQ+GZqxmdYyQzOCi3vB52eifrXkvvRNTCuz4ozV1tpsbvi\nsLby1dVFa1bavB99sCU1qyUhr+hqEN0HSq1pMf2KNneAxKpWWk7couU4gxg2wV2wtw5s59e0u+B5\nwIySND3TMI4TiGuSTCbO0WK3ubgcoCp1rXQ9t2hiQfpDaqwxJyXXR6TS75j6fERIn7ZAjQwyfE4q\nXdpDJuYZyzEi9Y4qLV7rFa1TK8L9Wak852ixO2Hi6igSLXNVCke1PZPJjGhbq5Vey7VkyTXa2Nio\ndXWLi645Tmd0Vz5VIoT7zthW5TuRii+uqkd1+FD7PA4CzlGzZF0BvKqql4vITGArVZ1Zkl43t9z9\nmY9+9KP84Q9/IAnNriT7YkBxuNbHSaxCTdg+GKX7ZkVL1aexDQfjPhpx1uoikpmndKShqKybJWny\n5MmsWLEcgAsvvIiLL55LMrO0F8V7aLQSoxOWDw0br8f32mzZkiWLOeWUkzjyyGP55S/vTD23V6hf\ngUceeYR99imK2uw4ziChmyHcN1v+dLNsOazT+yRm6n8A+Lyq/iWVZlDLJ6d/0NDQwNZbj28LAZ/J\n7EU2a/82ra1KofAQ8HPgErLZLK2tioiNJez3mfZ2iYGm4/6aMWpx2mMlepRUAd/BNjROy/VobSqV\n9XE8kISfh2Uk+3AqFq7+N6FMw4gh3pNnLwA+i411kvGCXY8h5mcBl5GMb1aEcuwHNJPN5kPbPAlA\nNjsxnLeSDqu/fv1rbtFyOqS7IdwrMbP3GHAG8AlgSjgO6mYeB5FEFxyD2bf/CtyFKVlDypL1zDPP\npGaK4pqr9MLTYQrvUthb04EjzI/58JK0I8J1Sc0mxYWnMf/9SmafooUsvjtaudBzzpnRVs4ttti6\nJJ9Sq9MfNPGvLhfdMKdbbz1eFy5cqL///e/b+VCPHbt9qlzFC2hHjRrX21+L4zi9AN2LLrjZ8qe7\nB7Yz7FNYlMHzytzvwdZxnIRylplSi0204pQe8+dfFeRwDJJRun67NLDGzHB/RcralB43PKDtA2JE\nS1d6bVh6nfkRWrx2bEVIP1yTYFxztXicEccUczSxlJXz4BmRGi+N0MQyl06zIqSxdWO+lsvZGN2R\nT1ohS9YDqnrgZmXS/Xfq5pa7v5PJjES1BbgX+AjtrVPN4doU4H+xNd9Xk1iTCPcPwaxXcbPBYRTP\nTsWNj0v9rQ/HNhmMvtdx1ksYMWIUb7/9GitWrGDffQ/AJpKXULzbezPFu9HHv7YBYXV1NQBjx44t\nW/9p007glltuCs99G9uro3g3+Zqa0dx11y858MBe/fk5jtODdNOS1evyZ2MMBfnk9B86Wk/UlXVG\nCxfWcfbZ55JYnGZhni1KsfyOVqr4bxnnXaPVKFOSjpBf3PR4Trj2XuBZiscbcQ8uDZ/Pw9aaNQH/\nh83Bl25qfC62h1eWxIDdUpJvtJylP6fXtQu2/+hybIwEU6dO8zXfTqd015JVCSXry8Au2Ii8bTc4\nVX14szLu/J2DXoitXr2aXXfdg46VLMU2F3zy/7N35mFSFtf+/5xepgeQYQnghlkkUQTRuMQsNwtZ\njLgrajCJxJjELGoCsgsYQEHZGcAh0au52Y2KJi4JLonyS3KzuIIGxEQSDFwXMOoMqNPMUr8/qmre\n6nd6WHtmerrP53n66X73qre736pT59T3ED3ovLhEGIqXwApI+Ims8YmnDXnO7V31hwKvu+O8sWUN\nrr/+9Y+cdNJJpNNVNDbWx0rvy+KvlcUaRnbb5s3/YuDAgW3Wva6ujl69+pE7nz2NfWBDlG0et08F\nxrzV5vkURek67KWR1eHtzx6UqeTbJ6U0iEQ0xgOLsIZKXDRLsO3+s9i/2LFEfYoGt5/vPwwFfg/4\nnOB+qkJoCDVhA5XATgMAmxJ1HrmDxKGAV3xwODSUwr5LimiawrPB+mnAaKL+TQUwARteGE1nSKWO\n5sUXX6CqqkpDBpW87K2Rldj9LrtlKHApMBf7L/UvZT8YNGgQvXu/A5tCLIV9aAx2rxnYaJVnsMbG\ne7EPo+ewD68wvtpgH4ZTsQ8WgvOQ59zD3H5pYCtRjLaPgbbn/OAHP8KFF36JhoY6nnrqUVatuodb\nb/0x9qHrVYk8GXcNO09r0aKlu6y7HYHzo1pPu/JMw/7UvPdtuqtvAmhg0qSpuzynoiglibY/irKP\nZDIZli6tJp1eTNRfMMFnj/+8g6hP8QyRgZPFeqyagI9j2/tGIm/YM+7lz+P7G5PdujnYQVR/vmbs\nnKrnsP0Ab8yB7Zv4MvnPt7p3H0EzHjv3a6i7xhzsfHV/TDPWwLKdZlv+/6GxsZEBAw6lW7feLFpU\nTV1dXYtHUFH2hUJ4sjZiM97v3O3OBaKcRgqtR+sIIjd8glwZU/9QSWANj9HY0SHvfUrjvT3RSNAR\nbn+/rZFo9MdPOg1Hh94B/C/RKNDvscafaeWVWrq0hrFjr3DnCT1a/uFtBwDq67e3OVKUzWaprOzp\nljYQSdKGoYfe8LoOeJxk8njefPMNHX1SlC7OXnqyOrz92R3l1D4ppYE3JM466zwefPABohA+wQ7i\nbsQOyDYTDbzmE9fy64ZgQ/rmuuPWufVHuX0biQZu49MYhrrtjwM9iSJXBNtnmQpc484zE5vmpZGo\nX3QUrfse/t0LafhInzD8EewA9ucJvWUiKW64YSmXXfb13d5HpfTpDE/WM0Cf3e6l7BODBg3ikksu\nJvLshF4n/9Dxc6auJfJQeWVC/1vwI0G3En3tnw22+5wX+foqW7E5o3HX+UTLOQ477N2cd96FLXuO\nGXM506fPdOV9CjtnzGAfXt6ow+2Tn0wmQ3X1Ele2YVhDyl87QeQZuwY7XyvjRqMURSkztP1RlP3E\n55J64IH76NGjF1HY3juw+i6C7Rv49dOwg7mDsTowkKtMnAC+QGTshNEzCaDSvft+ylRsW+8HchPA\nB7AGU2NwDe9F832ha4iMpVuxHimDzQm2wZVpLdEg75/d+7pge7PbZ4M7t/dcTcdORWjiiivGqFdL\n2ScK4cn6f9jJQY8R/TqNaScJXXfNshopvPTSS7n55ptpPak09Gh5A6QB62Y/0e2TwPZBXnbHx2OY\nH8OOIh0LHIRVJQ4nkzZhjaVjyRWzMFhjx45qfeYzJ/PQQ79pKXPPnv3YsaMuKK+XhAX70NxJdfUN\njBlzeZv1XrashvHjJ2KMoanJT3hNxsrvpe2FmprlXHTRhWzZsoV///vfABx00EH069eP/v37q5dL\nUboAe+nJ6vD2Zw/KVFbtk1Ja2EiSA9xS2F/wXijvdcpi5dGFaBA3/rc12JB/3L5/wRpP5DlvCrgS\nWEDr1DC+f7PWrffS7+Fc7bA/EKZ++bO7pi/L8USeNe8l81FAoex8AutN89cT0ukU1dVL1KtVxnSG\n8MXwfOuNMav368S7vmZZNWLXX389U6dOJcrg7sMA48bSB8ifiX02NpdEEvuA9A+lo4hGhBqxIXm1\n2JwTnplE7nM/qTQkcrv37NmHurpXANi2bRsDBhyCfUidRJQ/I4vtE1lVw/r6Hbs0fvzI0YQJU7jh\nhhvc9fyE1qOwaWpOJHrQ+9++n6wbhQssWjSfyy//phpbilLE7KWRNTzf+vZsf3ZHubVPSumxeHE1\n48ePJ3dQ80hsexqKXkzDzncaijVcwtA8/xdOY6Nmfk0UrufnkENuDq4KIk+T3xbmB/X/q2nuPZ6r\nq8ldI+yr+JDEUBjM4/tIs4gMOX9+7zHDnbcBmEA6XaO5tMqYDjeyOoNya8TsyFIl9oGQprWhczp2\nrrd/yEAkNOFJYOOb3yZ3flRbSoPDsAaRd+n7uVvjgG8SjfgYrNiGVRAcPvyTPPLIQ4FC4Frg/UQh\ng/7h/CHgTwwZcgzr1u1eCMzegyq3FCoLec9ac7DObx+GHXFrxqod/R6AKVOmcdVVk1pk5PeVeOiA\nPnQVZf/Z62SPRUa5tU9K6WHb217kzluCfPOrW3uUhrnjmoi8WMfSOgLFGzCNRIPH4VzxJmzf5kEi\n6XafciY00MKy+SiePwEfJtfLFZbfe86eIpJ2Dw0qP1gdqiL6OV7CokXzGD36i2QymZx+RCibn81m\nyWazLaGYSmnQ4XOyRGSHiGx3r6yINItI3f6eV4nIZDLU1NyI/br8A6mBSAHo10TKgJVEcc5J7AMr\njX1Y1GJd4/6BlaZtvBKQN15OdeesBn7ijn3arfswcAKQYPXq/8chhxxOJpMhkUi59d7Ym+XOuxbr\nwhfWr3+ak0/28da7uwc+D5gfCfP3wYcHPEbkMdvgruUfln92Za5g7tz59OrVj1NOOZNt27YB9uG4\nZcsW1qxZw5YtW1rWbdu2jS1btvDHP/6RO++8kzVr1lBXV8e8eYs44IA+dOvWi8rKnlRWHsCkSVfx\n8MMPs2bNGjZu3Njy2rZtW8sDV2O6FaVwaPujKIUnk8mwcOFcrFExlqjP8F0iw8MbQj4SJo5gDZ7b\n82ybiO2L7MSq/4HtS3wK25778MMHiVQMfXRKAiuscTS5fYAk1mCa6q7ry+TnaYGNgtlA5Nk6Fuuh\nM1iD7G/Bvl4V8XG37+PYvksz48dPYMCAQ+nVqx9nnDGSuro6Vqy4iZ49+9KzZ18uvPBL9OjRm169\n+tG9ex9WrLgpp/baFygj9iZz8e5e2F/uOcDcQp43z3XyZmIudS655BI3hOQzp280cJJbTpjcDO1h\nBveZxmY991nWce+z3TFpt51gn+4Gprvz5sumPjP47MsUbf/Upz5jampuNKlUt+Cc/pp+nS9fyhx6\n6OF7dA/q6+vNunXrzMSJU0wikTEgQdnW5ClnIrbOZ3f310+YAw7o586TdOvEZDK9jEiFiTLKh/cv\nX13SwT6p2H72PIlEpUmnu5u5cxea559/3mzevFmzyytKDPd8L9r2Zw/K0S73RVE6kvr6epNIVLp2\nNWmgMuhjzHZtW8a9J/O0j2E7nMnTToavmQbOadVmtj7Po679tn2HkSNHmdraWnPwwe8JzlsRXC/s\na8TPtd694n0Ef45Kk9tHOsudz/cV1rt1vsyV7nhfvvUtfY5UqltLW19Tc6NJp7ubdLq7qam5sZO/\nZWVv2dv2qV3CBUVkjTHm/QU/cXR+0x7l7gqIZLCjPz6/lSE3Zjmc8OnlVv1+3sV+JLkCFv5eeq+P\nYCeCziUaDYqHFvqEft6j1Az0J5J6b+aAA/rw6qtbyGaz9O7dH2MmYRMOxpMqWw/dunXP8PLLLwPw\nqU99arf3wp73IOrr3wrqILHPPgTBX3MYdkTq2GAfgmP8CBfYUIX7ie6hnwt2pHv3Yh5hksRp2Gz1\nPl59NFEse7zeVnlp4sSJfOELo6ioqGDQoEEaWqCUNfsbLtje7c8eXL9s2yeltFix4iYuv/wKtxSK\nT5xIbrvXQBQ581vg01iFP7/dC1YcT648+5FEoXuG3DaykVCR2LaX3ovWjBfRmDv3Oq6+egYNDY9j\n+0YnEoX+Cbny8SY4x9+IxDv8vhD1Z6bSes5XvH8RL/NjwK/ccemWcyQSzbz88mYymQz9+h1MQ4O9\nd+n0MLZvfw2Ptv3FT2cIX5wXLCaw8WGfMMZ8eL9OvOtrlm0jdsIJJ/Dkk/E5TEkiGfdQ+MGQm8Tv\nYeyD7wrgaiIjKolNIPhn4H3Yh1I850UYmx0adwmsMXJfcJ0zsG7+nfTp8w5ee+3l2MO6LcEO/6C1\ndTLm7T26J+vXr2fmzNncccetsS3eYPQGJUQ5xXxst69P2GCECkYbYuszREkU59I6E32KKA78aOAJ\nrNBHXAVpLXAXNoTSl8EaXkuXLuYb3/iaPnCVsmQvhS86vP3ZHeXcPimlRzab5YAD+tPYuIOojY4P\nGiYIBw5bGyN+gNKr+f0J20eYRSSGYYjaXi+O5eeD/wbrpPYG01DgSbzqcTJZSVNTXCwjn5pyAjsP\n6y6s/LsJ9vPTGvwsmqQrQ3h82L4PIVfJ0BuGqdg6fw8MccMsnR7G9dfPYcqUqYiIKhd2ATrDyPoh\n0b+pEdgE/LcxZut+nXjX1yzrRiw3J5SfVxVKqCaxDykfX+z/3H4//3md288fJ8Bp2JGYUL1wGPAW\n9uExnchTEz5Iw3I0Yx+e17XsZ0zWJVYeQm5M9xPYB2Xrh9MVV1zG8uXVe3pbArGNXwB9SKVO58UX\nX2Dbtm0sXryUW265hdyHnS/znhhZXmbW36dnsXPTrmPXI1veU/fdnPthJ+ieQO5k4cexo3A7SaXS\nLF1arQ9cpezYSyPrh3Rw+7MHZSrr9kkpPawQRndyFQO9YdVAJHXuvUI+/5RvMxPBei8sEQ7k5qZj\nif7SEBlb+aJBQuMO0ukUI0eex8qVd7hwLTAmLrABuW11lty2/uigTreRq7acJjdpMkHd7HzxdDrj\nPFVeSdnLwYfH2XlsI0eO5K677sJ7vVKpOfzrX3+nqqqqRVAjFNNQOp+9jrTYm9jCYnlR5jHv9fX1\nYZxfECM80UTzs8J5RN1NFEPtX8ngeB9f7OORuxk4Otg3nGsUzvsK5zdNj10jmRPjvGrVKmOMMYce\nerhpPc/pHJM/Zlr2es7SruKd6+vrzVNPPWWuvHJCcP0KkxsjvqvPfg5ZPKZcgvtuY9MTiUpz+uln\nu3ljPj48nKsVr6+/l93d/utNOt1d52wpZQf7OCerWF7l3j4ppcn06TNNNH9ptrFzkHw7Fs65Oi1P\nO+fbwaTrK6w3rdv7TNAGhuvDttqf96xgX38u25dZuHCJqa+vN/X19cG88JQr83pXhvuD68fLEp9H\n3lYZ/HKqje3hXK34fPk1Jpm0c7Sj9ZU5x5177iizaFF1S39m6dIbtD9QBOxt+7TPniwRWR7aauTq\nfBpjzHf26cR7dm2zr+UuFWz43TfcklcS3ABsB45z60PPkHfTJ7FKgb8hV0WnETgXG/bnv04/p8tn\naL8cqy6Yb35TIzaULnTZj8bOSxrMqlX3MGLECABOOeUMHnxwlbvGE0Sx2SEJRODtt+v2egRnT0Z+\nvHLgpk2b+MMf/kB9fT3HHHMMffr0YefOnbz44ot0796dgQMHsnPnTnbu3Enfvn055JBDePXVV/n3\nv/9N3759OfLII/Nex8u2+rJs2WLnpg0cOJBsNsuKFTcxc+ZMIs+jIVJIAvgL6fRHNB+HUnbsyUhh\nZ7Y/u0PbJ6UUsd6sHm4pDMWLe4L8nO1J2NQyfv1QonlWk4HrieZjnQysIv98L5/rM/SMPe+2+z7I\nMUTtp3DmmWdwzz13AmHOznheLh/6GEq3Q+twyLCf4//XEhzfiFVazhB5t5poHTJIS/kTiTQjR57L\nypV3xPZrdnWfiu2L5XrvUqmURrh0Mh3myQK+DFzs3l8IPn8ZuHhfz7uH1y6IRdrVWblypcnvjekf\njDiFI0JXmUhBL99oUagyON3tEyoR+mt0C/b1797DMzvPCFSmVdnPPvv82DX9iE84mlNhqqtvaBmV\nKjXq6+vNlCnTTDLpRwTDEb6UGTVqdGcXUVE6HPZgpLAz2589KFu73RtF6UyuvnqGiaI22vIExb09\ncUW/ja69G+H6DeL6FKcHfYZKt67SRB6wuMqv7y+E/R+vLJgyRx55jKmtrTXGGDNq1OiW484//wum\nuvoGk0h4D1fKJBIZM2fOXHedKbH6xBWJQxXjfB656XnWXRGU25bdethmBn0eXw+/HPfq2XKk093N\n1q1bS7JP1BXYk/YpfBVEXVBEnjLGHLf7PQuDjhRGiFRiR5IgGsz18cvhaEszdsKnn4MVF2wIRR38\n/K5zsCNRoZfpNKwXzHu6AM7Ezjc6hmgUaCbweWAwzz//LIMGDWpV9sWLlzJ+/DhyVRHjo0YJkskE\niUSiZCeF2rlkA4ju5wzg8y3KQ+rJUsqJvZ5Y3MHtz+7Q9kkpVaw3qyet503FkxTH506BbefXA7cS\nCT5BpPjn+ylgPV0LiQS3fJ+mKbaf917FI3Zo2X/UqC/yi1/8mLo6mz4vnOsUj3rp3r0Pzc1hFE9Y\nN1w5n8DOPYurFvp9E0T9L7CergZaC2IYrFevATvXfbQr/5+wYmAbgPHYPKjg+wX+2GQyxbJlS9vs\nE8XzcGk/ojB0eDJipXMxpp67777bLfmwM4jEJR7HPhSayTWCGrF/Vi9LGv8DJrHG1H+C8wqwhCg5\nn38Inehe/sGSxD4MLMcf/5G8ZR83bgy1ta+3UbMU1gVvaGp6koaGZxg79sqSTOCXyWRIJgUrfx/d\nu+bm5l0dpiiKoigdRiaTYe7c67Btvxe58q/JwJV5jvL9gmZsf2MW1oDwBocXyVgfrLveHTODSCDr\nGSLjyotktNVGRkbfbbf9nDvvvJO6uroWA8vXxQtM+PD+5curSaUMqZSwaNF85s69jkRCSCQSiCSw\noYvHBXU5isi4XIsVxPL9osfdy2+P0+zq9ThWqXi7W1fh6nck1sBa6647y10zCTxHU9OTjBkztlWf\nKJvNsnRpDT179qV79z706NGbnj37tkqIrHQM6skqIXJzaHn72d+nZuAdQFx0y8u/h/fTf0648/mR\nmXC/+EhWGHftFfT8w3MnmzdvZuDAgXnLbT1aE2PnDUdtrJetVD072Ww2GEEzhLnJzj//fO6442ed\nWDpF6VjUk6UoxYv1Zh3glhJYwyKL9cIksG23V9L9JPAIrT04fn7UMGA18F+xfZLkqhf6OU+hPLt/\nzze47A1AiOZcwUEHHcJLL23abf0g8vz45Vtu+RFjxoylsdHLumexCsG+vxOmvAmvHRqCvpynYw0o\nbyz6QWzvCZsCXEuuAuPR7pppbAoee4/PP/8C7rjjZ2SzWW688WYmTJhEQ0ODO8dCrCEH6fSJJdl/\n6mg6zJMlIjtEZLuIbAeG+c/uVbev51X2HWOyLizPj/A0Bq8/Yx9maWCjeyWxoy47sX/yaUQPxFJM\nRwAAIABJREFUr1RwZm+0haNXz2L//PHOhJdn9dfvDaQZPfqSNss9btwYzj//AnecNzD8qE0C65of\nzMKF80v2ASFisCN1Xnb/MWANK1f+gvXr17eEOiiKou2PonQWmUyGhQsXEA2I3koUyQJ2cNR7cIbm\nOYMQRdFMBQ5w64a5l2BzYD2D7Q981p3fR92kyQ3L8yGDj2ENColtX4tPy/Lyy/9Ht259dhkR471a\n8eXLLvs6//nPy6TTPvVLBmjkrLPOYejQY1z5hmEFP3wb/qT7PCko62PYaRgAfnC5gshrt5PIwJqB\nNa6OwPaPvNF2jbs/G1i58g7mzJlLjx69GTPmSicfv4EoD+rxwAk0Nub3+mWzWerq6koySqgo2JsJ\nXMXyQicW75bDDz/c+6hNJDDhJ1TGpUp/4vYJZViPd++Xu/f4BM1Q4CIZHBtOTM0V05g7d+Euy1xb\nW2uef/55M2fOXCd9XmESiYxJpbqZ6uobOujOdTz19fUxKdf4/bavM844t2Uir6KUKqiEu6IUPWef\nfYHxKUtai154wYqU62d0d+8VTtBhjYmkz8MUKT79TNgWDnPHdDOtZdt96pi42IYXzfApbPz1ozQs\nixZV71O9wzQx4TnmzVtoUqluJp3ubgYOHBQrj+8PnRLrZ3UzucIWmWC972eF/QAvQ+8FONabSHjM\nC4NsDPbJ5NzLuJBYTc2NTngrbUQq8/azSlV4bF/Z2/ap0xukfXlpI7bnWOUegj9lmDtrpolUbLyK\nYPhwSxhrZPkHZWic+QdkfxPlqIgrGqYMfNit+2TLn3xP8H/scvmD+we3feD5h2b8+7APUVUdVEoZ\nNbIUpfix+TrjbX6YN8q3YbNdnyHhtnujxysBrg+MhdAw8QqDvu3zA7uhkSUGHnbbfR/EGxzxXJRe\nxderA2LOPXfUPtc9X78kXL9161bz/PPPm9NPPzcolzegpuRp41OujGGbnzSRwuB6d7/iebziubr8\ncaHRZe+bH7ROp7ub6uob8gzupszSpVEfbVd5R8uVvW2fCjInq6PRmPc9J4qfDjOje8Ue/zLYMMA0\nuXHRXmXQu8fjeR8a3XkTWNGGDxPFEIcKQj7U0Obcqq9/s2TD/vYH766vqfmeU12MqxH58E7D1q0v\n0r9//04pp6K0J3udh6TI0PZJKRcWL65m/PjJROIOhtzcl/5vnAi2x9u06dg8WPHcUgmsGEaWSLQr\nDBH05zZEqoMVwTLkKg8Oxs4R+x7R3DBh0aIFjBs3Zr/vxa5YvLiaCROuwhhfTsHOy4rnK40rMzZj\nwxInAfOwfa5pREqEq4GPEs47i/ptKbd/kzuHn+dlv59kciiJRMKFF4JXdvZzt7LZLO94x0E0Nto5\nXanUCezY8XrZ991UXVDJIZPJsGjRAiIZ0Z1ED6DJbr0B7iE3VtrHPkM0D8vHHM9w6/0fuxk7cXWo\nO+5IchWE/MTOFCBOAlaJ4x9eU6ZMw3434ffhJ8jaeWsDBhzIsmU1nVRSRVEUpdy5/PJvEakV+3lQ\nH8BKj/t53T59zKN5ztCI7Sv8pY1tt2LFJSAyrqYS9U38PPKku14T8ClXjr+497BP83Dw+TlgA5Mm\nTWn3Oc/jxo3l7bffoLb2VWpr/+PmoP8aaGbEiFN5/vlnWbRoASJJV74hrm4JbP9rDna+9gZgPlHa\nHj+f/m/u5ftzT2Ml5v29acQasgJ8CPgOTU07aWxsctc7EntfbR/k+9+/mV69BjiRDz+nq4Gamu+1\n300qUdSTVSaceeZI7rvvHrfkbesNWIl2r+xzAuAfNj2AeiIRC4hk1TPky2cV/cH9vuGITCPwV3ct\nO7JizFsFrWMpkM1m6dmzLw0NPos92Ht+F5Fn0A+iNPHtb1/BggXzyn50SSkd1JOlKF2HRYuqmTDh\nSqJIGK80GOaKCv/OfnDWC12lsEJaYU4o359I5tk/gzUowIpC+DxT891nQySG4Q0z7+UajzVYcvsn\nyWRylzmn2oN43i6/rm/fA2lqehJbz6HYOsfzmvo+VxO5CoRx9cbBWGNtLpFwxgii++wjmwCSiAgL\nF85j8uSraGyU4Jp+AL2RpUuX8J3vXF6IW9Al2Wv1267YGGgjtm8cddRxbNiwFvuAmYCV90xj1X18\nvqowRDB08UOubPsMrIqQT/4Xury9Sx+iB503wPzIShM9elSxY8erha1kCbBixU2MHXslDQ312Hu1\nFquuFLr1m4m+qyQ1NctLMlGzUn6okaUoXYe6ujp69eqF7TPMwBoxXiXY9xO8/Lhvz8AO6vrQPm8M\nfRtYCvwe+DRRBAxESsnxEMCEWxcaId74sDmumpubiDxdPtFxmObmiaKROI/a/wYiA2k6kSy+91SB\nNX7S5N4jH1roEzwLrY3S0AjzWIMrlapwHq5kcFzpp9LZUzRcUGmTNWv+QjQqNB/7B1yNNbAec680\nMJAotNDHUHu59ma3zyxsZ38qrUepJNjX/8E3BOs/A2zgzTfrGDKkaNLbFA2XXfZ1tm9/jerqZdh7\ndgyRQQWRPH4C/3D99re/oxKsiqIoSodSVVXF2Wef75ZmEs0r2oA1uLJuXYXb5wSiOVbr3H6+K/o9\nbB9iONHA7DPuFQ7wDiPy2oQDjp5ooPeUU05h3rzrSaW8Z20ePn+nfU3Dh8kVA1H7v4R0ej6JhCBy\nLVF/TLDlzRDdN18XgEuwdWogNy0Osc8QGWhr3bk/4Qws3LFhqKW9Rw0NDSxdegPZbFb7HHuAGlll\nRCaToaamhsjYEaxYBdiJqn6u1AoiL1ZIGvuw83/2nVhj63Sih9Ro4M7gmPifGuB+bJgiPPvsGrZt\n27bPdSpVMpkMY8ZcTn19HRMmTHBr/QOvGR9P7kefmpubGDQoX04SRVEURWk/fvWrOxg06Ig8Wxqx\nBlUTVngBrPDCBKIwNdzn6URd0ultXEnIzcMVvnz7eCqhobdq1SomT57IiBEjqK3dRm3tq2zduoXa\n2v9QXV1NOn0d6fQwqquXFI13xrf/27e/xltvvc7bb9e2lNcaob6uSUTA3o8/AZBOD8MatwnswPmV\nwf4zsIbwYKxXKxwkTwJ/IOobriEyvpqw87aOBqYxefIUKit70bNnX5Ytq2Hbtm0589rUAIvQcMEy\nJJvNUlPzfcaPH4/9M/UA/Pyo3BjdXEPLu/4HA6dgjSWDNbA+i43z9a5/f2wz0YMzPD4KL9y69SVV\nytsNUaz2wcAWonCJowhDMtete4ohQ4Z0VjEVZb/RcEFF6XrYsMF+5E4rmAacgw13h0jAyfcPwv+J\nH8QF25nfSW4fJFQq9P2M0OsCUVuYwnrJIAofbEakguuvv47Jk8e3XNUbA8ViYO0OnzwYrBfxllt+\nxNixVwJQXb2Eiy660KkCTsMaWz7EME10T44kd2qHv6f5lB+vIQrn9H05f/8fwwqd2O9o1KjP8/GP\nfzSnPKU2jUHnZCl7zPr16xk69DjsAyl0RUM02fJcYKVb5/9g4UPU/9kSWBf+M8E+zbF9fRywlx79\nMFChAhh7QCSI8QxwFvB32pJ8HTXqC/ziFz/upJIqyv6hRpaidD2y2Szdu/dx8592YvsV4dyf/wUe\nJBJwSmHnR3lRBmg916oZK1Yx3y2fCqwiEuDykR0QCW2Ec8m9oTDLLfcCajn22ONYsyaf2mHXJG4o\n+nldxhgWLlyACIwdOx5jwnvlpxxMIZo+Et7/x7DGscH2N7LA+8md/3U5UJOzLpVKOtn3nSSTH+K1\n115pEffoagZtPrqMkSUilcD/w/5TKoC7jTFXiUhf4DbgXcAm4HPGmDdix2ojViB69z6Q2trX3JIf\nzQil2SuwLuWriR5avnM/C+uZep/bPz4htQGb58I/DD2hMWZYt26tel/2AP/gbG5upqnJ5x0L7/lQ\n4EngWNatW8OgQYO69MNMKU8628gSkQXAGdie4kbgEmNMrdt2FfAV7J/vO8aYB/Mcr+2TUpYsW1bD\nmDFjsX2HFLkd8keBj5ArUOFzYfllT5LI6+JFM8JBXt/mxVWO/aCu76usobUash38/epXv8LMmVcz\ncODA/a53MRI3aLwHLJPJ8NOf/oIrrhjjjC5/v8IpIqdjDSxvEM/APhI/QOs+Xjy/qvea2akiiUSK\nJUsWkEqlWzxcCxfO5xvf+FpO+boKe90+7U3m4kK/gO7uPYVNavBRrEk9ya2fDMzNc9zu0zIre8xR\nR70/Htxsomzi3UyUnR1js4g/6taHmcLF5GYvTwf7zwz2iWc5TxtImOrqG3ZfUKUlo3xtba3JzfCe\nNjDbhJnboULvq9LlcM/3zmyXTgYS7vNc3wZhk9eswfYg3g087/eLHd+et0dRipp58xYYSLg2yL/O\ncn2GeNufNLA+T58hvl/KQMbAqcH2eJtX6faJ9zvC/bq5bcmWbQcd9C5TW1vb2betw6mvrzcLFy4x\niUTGJJOVpqbmRrN582bXp8jk+Q4q2/heKvKsqwzWVebdT6TSpNPdTU3NjZ19K/aKvW2fOtXIaikE\ndMf6JodiTeID3fqDgA159i/0fSt7tm7dambPvt4kk5XuAeT/aOGDUgxc5f5IYee+Inj5dZnY9ne4\nzxPbeNCmzaJF1Z19G7oM1sjy93G9+366BQ2Zb7AwV1013axbt85s3ry5s4utKLuls42s8IWNl/6p\n+3wVMDnYdj/woTzHtNetUZQuwRlnjIz1IXwn/bOxfkE62OY740kDVwd9iLghlTTWiEvHjp9t7IBw\npTt3tzb28X2OmTl9kFGjRnf2besU/MCtp6bmRtcPzO2nJZOV5uyzLzCpVLc834s3rEIDNm6gpUxk\nUHd3388ak0p1y7l+sbO37VOnqguKSEJE1gCvAI8YY9ZhDaxX3C6vAAd2WgHLiP79+zNt2hRee+0V\nRNLYaJgmIre7n0zqY3d3Yl3FDUQTWcfH1oXS769jwwp7uSt6tZvT8WEA48dfydKlNe1d1ZIgk8mQ\nTPqwzgz2+5kQ7OElc9Ncf/08hg49hsMOeyf9+g3k4YcfZsuWLS0KQKoCpCht8hXgN+7zIVjVGc8W\n4NAOL5GiFDn33nsn733ve4lC2g02fOwRbN/Aiyj4PoLva3ghhi8Dv3PrPh+c2WCnLvgcUE1EKU1m\nuc9exdDLuvv8WmBzTaWwbeM8bBgigHDbbT9ny5bw710eZDKZnJC9yy77Om+++QZLly4hnR5GOj2M\npUuX8Oabb/CrX93Oiy++QOvvxUrFv//9JxB9h8OIklJPIUpH41P/AHyYxsZGbrzx5vauZqdRFMIX\nItILeAA7UniXMaZPsO01Y0zf2P5mxowZLcvDhw9n+PDhHVTa0iYSWPgTUbLAfHOt1mAl348gmsPl\nf0s+i3s8TtdgH4LXYmVEDdZAmIp9QNqH4ubNm0s2TrqQ5CYt9Ph7fgRRI3YrUWx1KETiw4oNEyaM\n49OfHk5FRQV9+/alX79++h0oHcLq1atZvXp1y/KsWbMw7TwnS0QewkZKxJlqjLnX7TMNON4Yc55b\nXg78xRjzM7d8M/AbY8xdsXNr+6SUPVZY6/3Y/oEXtvDGToKofYJIaOEDwHuAf5GrUAx2btZ6IkGt\nZmAssNyd9xDgJXIlyZ8EdmDngnnSWNXDWUQJiiFSyLtQhaMcbQlVXHjhl7jttl8A9n7ddNMNgFU7\nXLashrFjJ2CMFdYQSZBKJRg58jxuv/2OlvWh0EYxJzje3/apKIwsABG5Gngb+Bow3BjzsogcjPVw\nDY7ta4ql3KVI1Hn33qy4gl2UTd1OiJwN1LvtXr49nETpOxy+o2+AT2JHtUKVIFrOccwxx/Doo38s\nyj9dMZHNZrnooq+wcuUdbk3cyFqLncAaTjZ+DGsgDyNKYOi/L//saKZ//wNZt+4pqqqq9HtQOozO\nFr5wZfgycCnwaWNMvVs3BcAYM9ct3w/MMMb8NXastk9K2ZPNZqms9Lk3N2C9RsOwY+nziKJjwLY9\nTxAJUySJjCw/iOgfCVGfQURIJpOMGDGC++67j7jSbhTRMRXbD/HnjgYY4x1+GExt7astinhKfkIZ\n+Tg+QibsN2QymZzImX79DnZqycVtZMXZ2/ap08IFRaSfiPR2n7thJxs/BdwDXOx2uxj4VeeUsHzx\nGcfr62sZOfI8chP9DQMqiUaSZhKpyaSxPynvnvf5GUZi3fQ+NECwBtYhWG/ZYOAzbv1aIMHTT6+h\nW7cqVqy4qSOq3GXJZDLcccfPqK19ldmzr8XmzfI5Lrx7vmEXZ0hjGy2f9T2FHznctm0rAwYcTGXl\nAcyaNYe6urqchIOKUoqIyAhgInC2N7Ac9wAXikiFiLwHG/9cOjrQilJAMpkM1dVLYmsTwCXYtgbs\nIJ8f6DuRyPjxMvB+4K8Cm4tTsAaWxZhm5sy5hp/97IdB+DyAkEymEUli279Z2DYxzVFHDcO2cQ3Y\nfspOlL2nqqqqTUM0k8m0DM6G4Yh+fVVVFdXVUThiMSWCLjSdKeE+DPgRkd/4J8aYBU7C/XbgnaiE\ne6eTzWbp0aM3TU3fBJZhDSzvFfEJ7VJEMqxHEsVb+5Ek/wplV3cShRWGSQW93e9Hq45i69Ytmqx4\nD8lmsy3Z12+99Q5mz54T2yMeLvhdbGy1l7j1eTEmYEcbTew4w6mnns5NN91A//79S/bBqHQene3J\nEpF/YHt1PrfFn40xl7ltU7HztBqBMcaYB/Icr+2TojiWLathwoRJLqw9QTS9oAHb7n8C+INbdwbw\na6CZs846l3vuuZvW/QbvAZuGjaJpJJ2uYOTI87jrrjtbBAeamqwEfDo9jGeffTrHKKisrHLXfsKd\n+yQ0XLDj6Yp5s7pMnqz9QRuxjiU3fNALWvh5Pklsf+Np4C6ikMABRPHR4YTWNNEcLG+E+fxcPv46\nhfWQjcR6YhoZNWq0Pvj2AZ8b45lnnmHHjh1UVFQwcuQXePvtWqLGDqLvSbDfz1zs9/IMNszjWGy4\nxXVEwibC7NnXcuGFF+QdrVKUfaGzjaz9RdsnRcklCmtfSRSydzJWoDNNFPXi+wn2czqdbAkpsxEa\nPnlxOM1gLZAhnR7Gq6++BOw+FG3Fiptcnqgmkskky5Yt5aKLLgTyh78pikeNLKVd8LG0vXr1I+qM\nh8ZWuA7sw+99wD+IEtaFXpFwRMu77NPBdp8kzz90obZ2mz4AC8TGjRt54YUX2LlzJxUVFXz9699m\n48b1RI5lsIP53sg6JliGSMwknHsH9rs0DB/+GX7yk/9Rb5ey16iRpSilSV1dHQsWLHGh7T4M8E/A\nB/Fth42uGA0MZvbsa5k+/Wp39DRgNCJDsEl0ced41n0eTHX1EsaMubxlYBigunoJl1329VZlCecN\naRul7ClqZCntRjabpVu33k4dxs+f8qIK3tsRd+0DXAlUE8m55lMfbAI+BTxMFD4o2AfrIqCBlSt/\nwXnnndeeVSxrfJjh9u3bOe+8C/nnP/9FZECNwI46ht/v49jvfC3Wi3kNuYY0QANXXz2DCROuVANZ\n2SPUyFKU0qWuro5evfpg+wJeOKsJ+F+sCuBzbs/BnHvuSD7xiY8xdux4oLnF69TQ0MD48RNobjbO\n4EoBk0mn57N9u43yVQNKaQ/UyFLajUjefRzWZQ+53qujiDxa38WGlvmOOERztbxnKzxuKj6+2uI9\nXZHi3apV9zBixIj2qJqSh/nzFzJ5ss85EtfImYGdy+XVCj9IFEoKkbqTP04YNWqUhnwqu0WNLEUp\nbawE+G1EUwS8nPt47JwsgFOBVdTWvtqiTBcaTd4T1bv3gdjHhZBIGJYsWcCECZOAtr1YirKvqJGl\ntCsrVtzEmDFjaWxsJFfYAmxi4ZlYxcAmrNH0eSKBjCfcNr+/f5+GFVnwSQr9tkexeTPGA/MYPfpL\nXHfdbM3f1IH4iamh9OrFF1/KqlU+P2s8tDPunfxHsNxMbe1rOR6tXcnA7qo8OjpZuqiRpSilj1er\nraqq4oc//Anjxk2gqcnPzZ6CVSHctZx6JMxlRS4SiSEkk8kuKQ2udA3UyFLanbq6Ojex9HHgfKyy\nYBI7NysURvAGUyp2Bh8KmCLyXDWR693ySY8riCvcDRhwMK+88kKhq6XsBXV1dS2GVzab5aMf/TQv\nv/wSrdUIcz1boZEVJjQ89dTTWhIavvjiixxwwAEMGjSo1WTl3cXZK10fNbIUpfzwbclXv/qtlryP\nu1P6i6JrrFGVSh2NiKiRpbQbamQpHcLixUsZP34i1riqJxKtCMUwwHa23wPcgk1A7OdlTQOuJfKC\nQH4jK4n1gFUAxwF/BT5AOl3Jzp2as6mYmDNnHldf/V0AunfvyZtvbic0usJwQRuX34/8vxfT8po4\ncSITJ46jqqoqpzH1jadHG9HSQY0sRSlv9ibCIT74BuhgnNJuqJGldBhnnjmS++67m9xcWGuxIYF/\nc3sdjRXF8N+XT1wMkRcrBfQC6oL9egBvYo2yBFGSXIMXz+jRoxc7drzaLnVT9o0wnG/Lli0tXqmB\nAwfmNJjbtm1jwIBDyRVPAWtc+/BR//toZtCgI3jhhU00NtrfVTo9jNmzZzFtmjXq5s27jq997SuA\nSvB2ddTIUhRlb4iHkWtYudJeqJGldBjZbJbKygOIBCrC+VTeQ3GNWxeGkTUEyxXuvZkoVxZYQ2wY\nUec7PIf3dDTzhS9cxA9+cLM+TLsY9rfTiyh0NPRgJolydPl1cbn4eP61ppZ1n/zkJ7nmmqs55phj\n1ODqgqiRpSiKohQje9s+xSXDFGWPyWQy1NTUYDu7Te4F1mA6EiuCkSSSa99A5IlKY39+O93LhxF2\nI+o0P+OOmRFc1asNpoA0P//5z6msrGLFipvarZ5K4bG/nWVEj6DB7iVEHixPCpt80gCPYNUMDdbj\n1Qysw/5OUsA0HnnkET72sU/Rq1d/hg8/mfXr17Nly5aW0U1FURRFUZT2Rj1Zyn6TzWbZsmULt9zy\nQ66/fh5wL3CG25rGdpy9V+JobNb2OXnOdAjwEpFoRpIonGwqkaiG92g0B8c2sm7dOoYMGVLIqint\nTDabbVGZuu22O1z4X9xrFcrF/y/W+3ki+X9bkBuq2kDo8Zo9+xomTBgLaChJsaKeLEVRFKUY0XBB\npVOxghgTiDrISfful6cB82kdCpYkMpq8V+vbwDK3riJ2jA8t/AORoEaK3r378vrrLxW4VkpH4RWm\ntm3bRk3N91iyZFmwNRTF8M+4GUTGt8eHHnojKwVMx4prWG+rSIqFC+cxevQXyWQyrcIKNaa/81Aj\nS1EURSlGNFxQ6VTGjRvDzJkzsZ3gBLAGqyzYQJQ7K+wQp7GhYM1uvc+/1QwsJ5J/D4/xiYpTwHC3\nnACaeeONV9i4cWM71EzpCLzBM2jQIBYvXkh9/XamT5+GiJBMJpgz51rOPfe84IhZ2HDTEB96CDZk\nNYH1nHrRlSTGNDN+/CQGDDiUXr36ccEFX2wxrFasuImePfvSs2dfDUNVFEVRFGWfUE+W0i4MHPhe\n/u//XiDyOHiBgo9i59V4+z4MBWsCPgOsdtsiMYPoHN6LkZt/KZoPBn/961856aSTCl0lpROJe5bq\n6ur43vduYsqU6UQGuP+NNRIJZ2SwAireEKsgN/R0GjAaGEwymWT+/OuZMmWa5lnpRNSTpSiKohQj\nGi6oFA3r169n6NBhwKXAzdiO7waspPsQIhU53HsT1mBKu33Adpo/B9yFDQt8kNx8WkPIVTXcycEH\nv4t//es57RiXAT68EKzh5b/ziy76Cg8++IDbS4h+I/nmcT0BHIsNT12K/S2udduPYc6ca7n00q/m\nDStUCo8aWYqiKEoxokaWUlRccMEXWbnyNreUxOe4sh6sM4D3Y8P+ZmJDv3y+Le+dSmA7xn4OVijh\nnXTr4wmMrUdj0aJFjBs3ph1rpxQzdXV1bNmyhe9//79ZvnyFW+t/P+FvJgFcjU2O7ecDNpPrRbWf\nzz13JLNnf5dMJsPAgQPJZDI6f6vAqJGlKIqiFCNqZClFx+LF1YwfP4ncfEbPua2hYfRdfOiWDePy\nCoQGG+bV6F4Ga5j5DnHYYW7EGmX293HGGWdw7713tV/llC6B93gtX76C6dOvJgpjNdg5gRns7+cx\n4MNY71Y8SfJ4YFFwHIwYcRr3338vkKSmpobLLvt6R1SnpFEjS1EURSlG1MhSihKbfLYn1qAKwwTD\nzi7AFGAB1oBqwM7ReoQo4bE/PomdZ5MKznEo8DuiOTjW83XUUceyfv2T7VY3pWvhZeMzmQzLl3+P\nWbOuobm5maamZqxQywnkN7Kagb8HyxD3dm3duqXFu+U9XFVVVRpmuBeokaUoiqIUI2pkKUXNmDHj\nWbZsOdbj5BUI4/LszURGmA8b9FLwAnwKa3iFIYQCPO/2GUZkkNl8WkcccTTPPfd0+1VM6bJ4Y+jG\nG29m3LgJztjyv6l4eKrPwTUMO2/QzzOE6LebjB0HZ5xxOtXVCwDYvn07PXv2ZNCgQbssT7mGH6qR\npSiKohQjamQpRU82m2XgwMN59dVXsJ3Q0Mg6kvzqgblzY2xH9pvACiJjze+TwoYbXof1aDUC0KfP\nQWza9Jx6FZQ28R4o//rxj3/qEiRDFMKaxioUzqT1bzWfMbaTyNsaGW49elRxzz2307dvXyoqKqiq\nquLOO+9m4sRJAFRXLynL8EM1shRFUZRiRI0spcuQSh1AU5OX344bUWHHNcRgjaYKIi9WJaExFXnH\npmLFNBqJ8m0ZTj/9TO67T+dpKXtGNpulpub7TJkylcbGZozx6QLioa4+XxvkGln1bv3TtA5BNOQO\nEABMBi4pW/l4NbIURVGUYkSNLKVLcfjh7+Nf//JhfkmsceS9UA3AKcADtPZsQaQ+mHT7eo9WmE/L\nr/PhifbYAw88lBde+HvZdWCVfceH8YFVLvTerpdeeokHHvgd1103j+Zmb4DFBw3A/q7nkWuA/Qn4\nALm/bwOMIJn8LZs2/YOqqirq6uoA6N+/P1DaoYRqZCmKoijFiBpZSpejV68Dqat7lUhOK+g9AAAg\nAElEQVSu/W/Y+S4nYDucoUz7UeSO+iewhpOfx+U7td6oOgubW8vP0boPOBOvaDh79hymTZvSntVT\nyoRQ7MImSp5C6zlb3vgHm8ZgJDZHl99nGPA4NrVB3FCLlufOvY6xY79dksaWGlmKoihKMaJGltIl\n2bhxI+9979FYgwqieS8+d1YocJHbaX33u9/Fpk0b3bokMN0d51UM/Ryt8Fw+D5LQr9+BrF//pCab\nVQpGNpulR4/eNDUJkedqMBMmjGPhwoVEYYUQzePy+ePihtdQt83n7/LHGObOvY6vfOViwKoYeqOr\nK4tnqJGlKIqiFCN72z4ldr+LorQ/gwYNwpi3GTTofdiO5E6sUeTDAR/DhlbFaeaXv1zJnDnXE4UK\nXocNO/Rhgw3uXMOAZ7Ed1DTeo/Dqqy8xYMCB9Or1Di644IvtV0mlrEgkEljjfhgwmEWLFrBgwVxG\njfoC9jfewMc//jEGDz4K+xsF+zs9hkhNE+zAw+NEOeE24L1aU6ZMZcCAgQwYcCjdulUxf/4irrlm\nNt279+KAA/qwYsVNHVFVRVEURVFiqCdLKTquu26eC+HzI/xxYQCfG6sJL+MukmThwvns2LGDGTOm\n5zlrAvgHNgwx9BKEyZDtdebNm8ekSePboWZKObFixU2MHXslxhgWLlzAmDGXt2zzc6y853Tbtm1s\n27YNgPvuW8VVV11Nc7MXchFs/q64aEaK3Hxet2KNNH+MIAJvv12b49Eqdi+XerIURVGUYkTDBZWS\nYOnSGsaOvSK2Nu3e42pu3iHbyBlnnMall17CqFEXU1+/g2jOlv9PpNzx69yyN7IeBf4La7QJc+fO\nZfLkCYWullJm7KtB4+d31dXV8a53HUFzczjX0JPGerhODN69Eeal42Hr1hdbjLl58xYyc+Y1JBIJ\n5s+/nssv/9Y+la89USNLURRFKUbUyFJKhmw2y7hxE1mxYoVbkyTyXh0KvIo1oEKvVJS4+JJLLuac\nc85k+fIb+O1vHyGajxV6xrwCoVcobMQbbqeddhq//vWv2reSirIbVqy4iTFjxgJw2mmnc889d5Mr\nH5/ADw7kCmjsBJqZO3c+V1/9XRoaGmmdZDlBKpVg4cIFXHLJaMAaXJ1pdKmRpSiKohQjamQpJYf1\nao3DGkH+e08He4TKg15AALzEe01NDa+//jrTp+dTEazAztOC3LxFADs58MB3qtS70umEHjH/eenS\nG5g8eTJR+KxX1MStawYaSaczNDR4qfi1tA479N5e8CGGCxbMY/z4se1er3yokaUoiqIUI2pkKSWJ\nD50aMOAQcpMOJ7EdSp9wOFJyi2TdYfPmf3LmmeezZs0TREpt3piKy2efSG5y4wpqapZz2WVfb6fa\nKcq+sXRpDRMmTARgzpxraWhoZPr0aVhjK4UIpFKJXRhZQ92+/n9zFD68duTIkdx55y86sDYWNbIU\nRVGUYkSNLKXkufLKiVRXL8F6nZLkhv6FoYNrgQzeQ3XccSfwwAP38rGPfYbnnlsXHBPmLfo81thq\njJ13J7W1tSrxrhQd8XlfS5fWMH78BESEpUurARg79spYuCDu82RgMbmereh/s3Dh/A73aKmRpSiK\nohQjXcbIEpHDgB8DA7Ct/U3GmGUi0he4DXgXsAn4nDHmjdix2oiVOd6zdeGFF/Hwww+6tScAT7vP\nQhQG6D1UxzJ37nVMnjyB+fMXMnnyFKK8XKFnK18+LqtieO6557FgwVwGDRrUfpVTlP0kbnj55XPP\n/RyrVv0a+/tOkEwmMEYwphljvEBMFD6bTCZ58803OjRctliMLBEZDywA+hljXnPrrgK+gn0gfMcY\n82Ce47R9UhRFKUG6kpF1EHCQMWaNiByA1SI+B7gEeNUYM19EJgN9jDFTYsdqI6a0UFdXx5Ily5kz\n5zqMMQwf/gl++9vfBXt4D9VgEokEb71V2zK35ZxzPsf9968ikoT3iYrT5BpZJwMPtZyxV6++vPHG\nyx1QO0UpLHV1dWSz2VZe2Ww2y5e+9DXuvtuLvZxOOv0g27e/VnZGlhsE/G/gSOAEY8xrIjIE+Dk2\n7vJQ4LfAEcZap+Gx2j4piqKUIF0mGbEx5mVjzBr3eQd2+PRQ4CzgR263H2ENL0Vpk6qqKmbMmMb2\n7a+xY8frPPTQKurrt3P33SsZNOhwbO6gwcAwkskoyWsmk2HVqrtZtGgBkTpbJABgjxmMnafyEFEi\nWKitfZVZs+Z0UA0VpXBUVVXRv3//FhVB/6qqquJXv7qdhQvnk0wmSacfpLp6SbmKviwGJsXWnQ3c\naoxpMMZsAp4HTurogimKoihdg6KYkyUi7wb+H3A08G9jTB+3XoDX/HKwv44UKnvMvHkLmTp1Oslk\nkurqJXkFLLLZLNu2bePYY0/itddecWu9cIa499CzZUOr6ut3lGsnVClhOjNhcWd7skTkbGC4MeZK\nEfkXkSdrOfAXY8zP3H43A6uMMXfGjtf2SVEUpQTZ2/Yp1Z6F2RNcqOCdwBhjzHZrV1mMMUZE8rZW\nM2fObPk8fPhwhg8f3r4FVboskydPYOzYbwNtdxozmQwDBw7kP/95kS1btpDNZunfvz8nn3wqjz76\nJ6yRNdjtfTrwayJhDEUpLTrSuFq9ejWrV6/usOsBiMhDwEF5Nk0DrgI+G+6+i1Np+6QoilKi7G/7\n1KmeLBFJA/dhRwOr3boN2FHEl0XkYOARY8zg2HE6Uqh0GH4Oi5WP93m0RGXdFaUd6ExPlogcDfwO\neMutGgj8H/BB7HxhjDFz3b73AzOMMX+NnUPbJ0VRlBKkKwlfCHbO1X+MMVcG6+e7dfNEZArQW4Uv\nlGLh/vvvZ+fOnZxyyikaJqgo7UBnhwuGxMIFvfDFSUTCF++NN0baPimKopQmXcnI+ijwe6zmti/E\nVcCjwO3AO1EJd0VRlLKiyIysfwInBhLuU7ES7o3YEPcH8hyj7ZOiKEoJ0mWMrP1BGzFFUZTSpJiM\nrH1B2ydFUZTSpMtIuCuKoiiKoiiKopQiamQpiqIoiqIoiqIUEDWyFEVRFEVRFEVRCogaWYqiKIqi\nKIqiKAVEjSxFURRFURRFUZQCokaWoiiKoiiKoihKAVEjS1EURVEURVEUpYCokaUoiqIoiqIoilJA\n1MhSFEVRFEVRFEUpIGpkKYqiKIqiKIqiFBA1shRFURRFURRFUQqIGlmKoiiKoiiKoigFRI0sRVEU\nRVEURVGUAqJGlqIoiqIoiqIoSgFRI0tRFEVRFEVRFKWAqJGlKIqiKIqiKIpSQNTIUhRFURRFURRF\nKSBqZCmKoiiKoiiKohQQNbIURVEURVEURVEKiBpZiqIoiqIoiqIoBUSNLEVRFEVRFEVRlAKiRpai\nKIqiKIqiKEoBUSNLURRFURRFURSlgKiRpSiKoiiKoiiKUkDUyFIURVEURVEURSkgamQpiqIoiqIo\niqIUEDWyFEVRFEVRFEVRCogaWYqiKIqiKIqiKAVEjSxFURRFURRFUZQCokaWoiiKoiiKoihKAelU\nI0tEfiAir4jIM8G6viLykIj8XUQeFJHenVnGzmT16tWdXYQOQetZWpRDPcuhjlA+9YwjIt8WkWdF\n5G8iMi9Yf5WI/ENENojIZzuzjMVIuf5eyrXeoHUvR8q13vtCZ3uy/gcYEVs3BXjIGHME8Du3XJaU\nyw9Z61lalEM9y6GOUD71DBGRTwJnAccYY44GFrr1Q4BRwBBsu7VCRDq7DS0qyvH3AuVbb9C6lyPl\nWu99oVMbCGPMH4DXY6vPAn7kPv8IOKdDC6UoiqKUM98CrjfGNAAYY7a59WcDtxpjGowxm4DngZM6\np4iKoihKsVOMo3AHGmNecZ9fAQ7szMIoiqIoZcX7gI+LyF9EZLWInOjWHwJsCfbbAhza4aVTFEVR\nugRijOncAoi8G7jXGDPMLb9ujOkTbH/NGNM3dkznFlpRFEVpN4wx0p7nF5GHgIPybJoGzAEeNsaM\nEZEPALcZYw4XkeXAX4wxP3PnuBn4jTHmrti5tX1SFEUpUfamfUq1Z0H2kVdE5CBjzMsicjCwNb5D\nezfAiqIoSulijDm5rW0i8i3gLrffYyLSLCL9gP8DDgt2HejWxc+t7ZOiKIpSlOGC9wAXu88XA7/q\nxLIoiqIo5cWvgE8BiMgRQIUx5lVs23ShiFSIyHuwYYWPdl4xFUVRlGKmUz1ZInIr8Amgn4hsBr4L\nzAVuF5GvApuAz3VeCRVFUZQy4wfAD1xqkZ3AlwCMMetF5HZgPdAIXGY6O95eURRFKVo6fU6WoiiK\noiiKoihKKVGM4YI5lEvCYhE5TEQeEZF1LgHmd9z6kqmriFSKyF9FZI2IrBeR6936kqljiIgkReQp\nEbnXLZdcPUVkk4g87er5qFtXivXsLSIrXYLa9SLywVKqp4gc6b5D/6oVke+UUh07gnJOYiwi4938\ntb7BupKut4gscN/3WhG5S0R6BdtKve4jXN3+ISKTO7s87Uk59M92RTn0ZfJRiHa/6I0syidhcQNw\npTFmKPAh4HIROYoSqqsxph74pDHm/cAxwCdF5KOUUB1jjMGGFnl3cSnW0wDDjTHHGWN8zqBSrOdS\nrJLcUdjf7gZKqJ7GmOfcd3gccALwFvBLSqiO7Y2UcRJjETkMOBl4IVhX8vUGHgSGGmOOBf4OXAWl\nX3cRSQI3YOs2BPi866+UKiXfP9sN5dCXycd+t/tF/6cvl4TFxpiXjTFr3OcdwLPYHCwlVVdjzFvu\nYwWQxH63JVVHABEZCJwG3Ax4tbGSq6cjrqZWUvV0o9MfM8b8AMAY02iMqaXE6hnwGeB5Y8xmSreO\n7UE5JzFeDEyKrSv5ehtjHjLGNLvFv2IVJ6H0634S9hmxyf3ef4Gtc0lSLv2zfJRZX6aFQrX7RW9k\ntUFJJywWmzvsOOxDu6TqKiIJEVmDrcsjxph1lFgdHUuAiUBzsK4U62mA34rI4yJyqVtXavV8D7BN\nRP5HRJ4Ukf8WkR6UXj09FwK3us+lWsf2oCyTGIvI2cAWY8zTsU0lXe88fAX4jftc6nU/FNgcLJda\n/dqklPtnbVAufZk4BWn3izFP1l5hjDFSQskfReQA4E5gjDFmu0jkJCiFurpRv/e7UYIHXIhNuL3L\n11FEzgC2GmOeEpHh+fYphXo6/ssY85KI9AceEpEN4cYSqWcKOB64wuVNqiYWIlAi9UREKoAzgVZz\nLEqljvuD7DqJcQroY4z5kNgkxrcDh7dxqi51H3dT76uAcM7RrvKEdal6wy7rPtUY4+eoTAN2GmN+\nvotTdbm674JSqsseU+r9szhl1peJU5B2v6saWbtNWNwVEZE09g/8E2OMzw9WknU1xtSKyK+x8z9K\nrY4fAc4SkdOASqBKRH5C6dUTY8xL7n2biPwSG0ZSavXcgh2pf8wtr8R2LF8usXoCnAo8EYS6ldp3\nuV+0ZxLjYqateovI0dgR37WuwzkQeEJEPkgJ1Bt2/Z0DiMiXseFUnw5Wl0Tdd0G8foeR67krOcqp\nfxZQNn2ZPBSk3e+q4YIll7BYbAt1C7DeGFMdbCqZuopIP6/EIiLdsBOln6KE6ghgjJlqjDnMGPMe\nbOjVw8aY0ZRYPUWku4j0dJ97YEezn6HE6mmMeRnYLDYxLdg5S+uAeymhejo+TxQqCCX2XbYzZZfE\n2BjzN2PMgcaY97jn3RbgeBdOU7L19ojICGwo1dlO2MlT6nV/HHifiLzbeb9HYetckpRD/ywf5dKX\nyUeh2v2iz5MlQcJibPzjd4G7saEY78QlLDbGvNFZZSwETmXv98DTRK74q7AP5pKoq4gMw04UTLjX\nT4wxC8RK/pZEHeOIyCeA8caYs0qtnq7z8Eu3mAJ+Zoy5vtTqCSAix2In/lYAG4FLsMItJVNPZyi/\nALzHGLPdrSu577K9cCPdPwDej01iPN4Ys9ptm4qds9OIDTV6oLPK2Z6IyD+BE40xr7nlkq63iPwD\n+0x4za36szHmMret1Ot+KlCNfQ7eYoy5vpOL1G6UQ/9sd5RyX6YtCtHuF72RpSiKoiiKoiiK0pXo\nquGCiqIoiqIoiqIoRYkaWYqiKIqiKIqiKAVEjSxFURRFURRFUZQCokaWoiiKoiiKoihKAVEjS1EU\nRVEURVEUpYCokaUoiqIoiqIoilJAUp1dAEXpCojIO4DfusWDgCZgGzZnxknGmMbOKlscl89ipzHm\nz51dFkVRFKV90fZJUYoTNbIUZQ8wxvwHOA5ARGYA240xizurPCKSNMY0tbH5k8B2YI8bMRFJFVND\nrCiKouwZ2j4pSnGi4YKKsm+IiJwgIqtF5HERuV9EDnIbVovIYhF5TESeFZEPiMgvReTvInKt2+fd\nIrJBRH4qIutF5A4R6ea27eq8S0TkMWCMiJwhIn8RkSdF5CERGSAi7wa+AVzp1n9URH4oIucFBd/h\n3oeLyB9E5G7gbyKSEJEFIvKoiKwVka935A1VFEVRCoK2T4pSBKiRpSj7hgDLgPONMScC/wPMcdsM\nkDXGfAD4HnA38E3gaODLItLH7XcEUGOMGQLUAZeJSApYDpzXxnnTxpgPuFHKPxpjPmSMOR64DZhk\njNkEfB9YbIw53hjzR3dcSLh8HPAdY8xg4GvAG8aYk4CTgEtdo6goiqJ0HbR9UpQiQMMFFWXfyGAb\npYdEBCAJvBhsv8e9/w34mzHmFQAR+SdwGLbR2hzEpf8U+A5wPzAU+G0b570t+HyYiNyOjcGvAP4Z\nbJM9rMejxpgX3OfPAsNE5Hy3XAW8F9i0h+dSFEVROh9tnxSlCFAjS1H2DQHWGWM+0sb2rHtvDj77\nZf+/C0fsxC3v7rxvBp+XAwuNMfe5ycQz2zimEee1FpEEtsHLdz6AK4wxD7VxHkVRFKX40fZJUYoA\nDRdUlH0jC/QXkQ8BiEhaRIbs5Tne6Y8HvgD8AXhuN+cNRwCriEYRvxys3w70DJY3ASe4z2cB6TbK\n8wBRSAgicoSIdN+bCimKoiidjrZPilIEqJGlKPtGE3A+ME9E1gBPAR/Os5+hdcy55zngchFZD/QC\nvmeMadjNecNzzQTuEJHHieR6Ae4FzhWRp0Tkv4D/Bj7hzvchYEcb57sZWA88KSLPYOP11dutKIrS\ntdD2SVGKADGmrf+XoijthZuwe68xZlgnF0VRFEVRWtD2SVEKg3qyFKXz0BEORVEUpRjR9klR9hP1\nZCmKoiiKoiiKohQQ9WQpiqIoiqIoiqIUEDWyFEVRFEVRFEVRCogaWYqiKIqiKIqiKAVEjSxFURRF\nURRFUZQCokaWoiiKoiiKoihKAVEjS1EURVEURVEUpYCokaUoiqIoiqIoilJA1MjqYojIcBHZXMDz\nfVlE/hAsb3fZ3guGiKwWka8W8pzFgoh8TEQ2FMO1ReRIEVkjInUicoWIVIrIvSLyhojc1hllbG9E\n5H9F5Ng93PdbIvKKuz999vI6PxSRa93ngv4HiwURWSgi3+zscihKqSMi3xOR6cFyzrNJRP5LRP7h\n2uOzOrOs7YGIzBSRn7jP7xaRZhFJuOXfiMjodrz2O919ld2VTVH2FzWy9gER+aiI/Ml1Xv8jIn8U\nkRPdthyjpathjOlpjNlU6NPSRvZ4EektIj8QkZdcA/OciEwu8PXbDWPMH4wxgwt9Xvegb3D3xN+X\n5SJy0C6uPQn4nTGmyhhzA3ABMADoa4wZVegydjYiciZQa4xZuwf7poFFwKfd/Xl9Ly/X5m+4hFgI\nTHX3SlGUfUBENonIW+65/bobCPpG2Kk3xnzLGDPb7Z/v2XQNsMy1x/d0Tk3alTafpcaY04wx7Wbk\nGGP+7e5rW2Uo9ee80oGokbWXiEgVcB+wFOgDHArMArKdWa49QUSSnV2GPCwBugODjTFVwFnA851b\npKLAALe6e9IHOBc4CHgiNLRivAtYH1v+uzGmeW8vLiKpvT2mE/gmsKeN8UFAJfDsflwv78jn/2fv\nzMOsqK69/e7TfbqhBVoQWhEcQUEGBUUxRgzRmxhFozGamHy5xpg4xAmnKIJexAFnxQEi3pib5CbR\n3KgxahzihNE4oRFQEAeccEAaUVokHHrY3x9rr659qqubBpHuhvU+z3m6Tg27dtWp3lW/WlNHYXW/\nqfd+ETAf+R80DGPt8MBBYezeGrgMOAe4pZn1s8amrSkey1tNO73Pp+nQY6lhtBYTWWvOjoD33v/J\nCyu99w95719yzu0E/BL4SjBHLwVwzo1xzr3onFvmnHvXOTdRG4tM5Uc5595xzlU758ZHyzsHV6Wl\nzrm5wO5xZ5xz45xzb4S3ZnOdc4dGy44Ob9Gucc4tASY653o45+4OfXkW6Jdqr8E5t71zbstwDPpZ\n4ZxriNY7xjk3L/TrAefc1tGybzjn5gdL3w3IgNrcoDoCERPLkBP7qvf+jtS5abxOXcr10Dl3bOiH\nHv/wMH8r59ydzrnFzrkloR+t6fu1Ttw2ljnn5jjnBof5B4b2a5xz7znnzgzzG13HnHPnOOf+nDqf\n1znnrgvTlc65W5xzH4Q2LoqPLUXjOfPe13vv5wHfB6qBrH0/CowGbgy/1x+B84Hvh+8/acWxNzjn\nTnTOvQ68GuYd5MQFUd/IDo3Wf9s5d6Zzbnb4rW9zzpVHyw8J2y4L1+j+qzsPzrn+zrnHQ3vVzrnb\nMk+Oc2XA14HHo3nlzrkpzrn3w+da51yZc25HkgeYT51zDzfT5p+dWFQ/DX0Y1Mxv0yItXEPlTlzy\n3nHOLXLiMtQpLBsdzsUZYdsPnHNHR21mXn9h2bFOXIs+ds791TnXO1qW9Ztm9i8wAxizNsdtGEYx\n3vvPvPf3IGP3j3VMccH92Dm3A/JiA2RsesQ59wawPXBP+H/Pr2bMzLrPl32Bsaazc+7qML5/6px7\nItp2TydePJ+Esf1rzR27k2eIO5zcg990zp3SmnPmont8dGw3hL684pzbN1r3aOfcgnCe3nTO/TDM\nd86588IxfOSc+62TF+RZ7onbhfG+xjn3d6Bn1H4n59zvnTxDfOKce845V9Wa4zAMALz39lmDD9AV\nWAL8BvgW0D21/MfAE6l5XwMGh+mhwCLgkPB9W6ABmA6UAzsDK4EBYfllyIPkpkBf4GXg3ajtw4Et\nwvT3gOXA5uH70UAtcBIiqDsBt4VPZ2Aw8B7wj6i9BmD7jOP+PfCHMH0I8DowILQ7AfhnWNYTqAEO\nA0qA00IfjmnmfP53OKajgR1Sy/Tc5KJ5j2lbiDvce8Bu4Xs/5A1gCTAbccHoHM7rV1vR9/2B54Fu\n4fuA6Nx+GLVRCQwP06OBhWF6G+BzoEv4XgJ8AOwRvv8FEeGdgV7As8BxzZyXC4D/zZg/CXgmve/0\nuQnfJwK/i743e+zRb/8gcq2VA8OBjxBh74CjgLeAfFj/LeAZ5E1sd+TN6/Fh2R7Ap4gLDMCWJNd0\ns+cBuBU4N0yXAXs1c34GA8tT8y4EnkKuwZ7AP4ELo9+m6FrKaPNoYBMgj1hYX4yW/Q9wUdZ5T7XR\n0jV0LXBXOL9dgLuByVGbteF3LwEOCNdS5Wquv30R4T0snK/rgcdb+E2b7V/4fhjwwvoeV+1jnw3l\nE8bFfTPmvxONj//T0tiUbmM1Y+bRNL3Pf5GxZirwKNA7tLdnGFv6IM8+3wrr/Uf43jPjWHPAC8B5\nQCmwHbAA+GZYfgHh/kbqPk/xPV6PbWzo6/eQ+8qmyFi9jPDcAGwODArTxyD3um3DencQ7oUZ+3sa\ncZXOA6OQ5xdd9/hw7joh98DhQNe2vsbs03E+bd6BjvgBBoZBcmEYAP4KVIVlR5MSWRnbTwGuCdP6\nD79ltPxZ4HthunFgCt+PpZkHvLD8ReDbUV/eiZaVAKuAHaN5l8T9JUNkIa4OM4Hy8P1+ih/mc8gg\nvTXyIP5UavuFNC+yOgHnIg9+q8LAqIN40WAY5sUD8IPAKRltfgVYTMYD9Wr6/nXkbf/I9LbIDfI4\nwsNpNH80xULnCeA/w/Q3gDfC9OaIeO4UrfsD4NFmzssFZIusExAXwKx9Pwb8tLk2Wjj2raLffnS0\n/JeEB4Fo3nxgVJh+C/hhtOxy4JdhejpwdUb/WzwPwG/Dtn1W8z/0VeDD1Lw39NoJ378JvNXctbSa\n9jcN63cN31srsjKvIeQGvZzofytcp29Gba5IbfMRiUBv7vq7Bbgs+r4J8n+0dTO/abPXeHTNLmjN\nObKPfezT9EPzIutpkhdI8XjSZGyK22jFmHk0xff5tR5rkHvCCmBoRv/PIXppF+Y9AByVse7IuE9h\n3rnAr8P0BbReZL2faudZ4EdImMEnyIuhzql1HgFOiL7vGMbFXLw/5L5fG28P/IFEZP0EeVnX5HzY\nxz6t+Zi74FrgvZ/vvf+J934rYAjyln5Kc+s750Y65x4LZvNPkbcjm6VWWxRNr0DePhHajjOZvZtq\n+ygnroifOOc+Cf2J24637YW8VWq2vYy+HwCcChzqvde4s22A66J9fhzm90Hefr2XaqbZTGxe3C0v\n9d6PCP3+P+DPzrlNW+pXoC8iQtNshQzwWbFIzfV9S+/9Y8CNyJu8j5xz051zXcPy7wIHAm8Hd4Y9\nm+nTH5EbIMAPkQFb95sHPoz2fRPym6wJfaI+Z+FbWNbS76YsTK1/pq4ftumLXJNKfN3+G3nIh+Z/\nm9Wdh7ORh4TnnHMvu+DmmMEniFU5ZktEjCjvpvraLM65nHPuMidujcuQhxyIXEdaQwvXUC/koeCF\n6LjvT7X/ceqajceB5q6/3kTH7L3/HPldM3/T1VzjIOf00zU5ZsMwWkVfYOlabNeae0f6Pr+2Y01P\n5MVnc2P3Ean7wVcRT4asdbdMrXsukohpTXk/9f0doLf3fgXihnkC8IFz7l7n3ICwTtG4iNwLShHB\nGrMl8In3/t+p9jW84X+Rl7m3OXFBv9x1jHhlo51gIusL4r1/FXn7PkRnZaz2R8R039d7vykyQLb2\n3H+IvG1R4hiabYCbETeBHt777ojrXRz/FPenGqhrrr00YcD6DXCE9z4e6N5FXGv/weAAACAASURB\nVBW6R59NvPdPh/5uFbXh4u8t4b3/DLgUeVDfDrGygNwwlHhAXwj0z2hqIbC1yw4Abq7vz4Q+3BAE\n3yDk7dcvwvznvfeHIjewuxAxmMXtwGjnXB/gUOS31z4VgM2i/VZ674c2006T6yj4kB+MWMtaQ7qN\nFo89Y5t3gUtS63fx3rcmHXxLv02z58F7/5H3/jjvfR/kZcQ059z2Ge28gVxevaN5HyBvKZWtw7zW\n8P+QhA/7ee8rkesPmv9fapZmrqFqRIQOio57Uy/B8a1ps7nrr+iYnXObIC8r4v/Xon43d40HdgJm\ntaZPhmG0Dufc7sgD/ZNrsXlr7h3x//gS1n6sWYJYzbLG7ncR61N8P+jqvb+imXXfSq3bzXt/UEZ/\nV0ef1PdtCOO69/7v3vtvIs8F85HwA8i+F9QhFruYD4Huzrn4GWMb7Z/3vs57f6H3fjCwF3AQ4q1j\nGK3CRNYa4qQW0RnhIRrn3FaI5eLpsMpHQF9XnAa5C/K2ZJVzbg/EwtHaQeb/gHOdpDrvC8TBo5uE\ndpYAufDWf0hGG4AkUADuBC5wEtw6CIkhyzrObogb5ATv/VOpxTchqZ41iLfSOXdEWHYfMNg5953w\nxudUst906X7Od86NcBKo2wnxvf4EeNV7X408LP6nc67EOXcMxYk6fgWc5ZzbNQS69neSyOFZZPC8\nzDlXEYJX91pd30M/RobfbgVys6l3Enj8/5xzleEcfgbUN3OOq5HkAb9B3DNeDfM/BP4OXOOc6xos\nJ/2cc/s0d2qic1TqJKnKrcibwGuaO58Ui4J0spGWfrcs/hs4wTm3Rzi/mzhJ4tKlhW10n7cAP3HO\n7RuOtY9zbsDqzoNz7ohwnYNYVDzi2lGE934V8DDi+qLcCpznnOvpnOsJ/Betzz7YBXmQWRqEyuSM\n41ptRqzmriHvvUfO5xTnXK+wbh/n3Ddb0WZL19+tyHnexUnSkclIzF6mhbq5/kWrfA15620Yxtrj\nQO6jzrmDkP/T//Xez42Xt4Y1vXcEC9VajTVh21+HffUO992vOEk09HvgYOfcN8P8Tk6SaKRFEMBz\nwGfOubPDs0aJc26IC6Vu1uT4gSrn3KlhHDwCiSO9zzlX5SS50iaIy9/nFI+LpztJctEFGRdvS3u3\neO/fQUIVJoX290aElHRSjm+okxe2n4X9ZN77DSMLE1lrzmeIv/GzzrnliLiaQ8j4hvgCzwUWOecW\nh3knAhc652qQjG9pS0BLgmsSYr5+C/F//h3JW5Z5SHKHpxG3rSEUvynzGW2fjDxQLkIG01+n1tHp\nXZG33Ne6JMNgTdjvXUj8zW1OXKteQgLq8d4vQRJSXIaIv/60/PauAfFPV0G1HzAmuAKAxKD9IrQ1\nCPGPJuzrdiSm7I9IsOqdSCKSBsTi0x95o7YQCZhtse9AN8QyuBR4O+zzyrDsR8BbYZvjEMtH+pwp\nfwzH8cfU/KOQAOJ5YR9/pnkB6gmZARGx8ddwjnbzkmq7uX2nf8vG76s59iZtee9fQM7/jaG/r4dj\naO56bdyf934m4s9+bej/DBKraUvnYQTwTDjuvwKn+ubrtk0H4qKVFyM3zDnh83yYl3l8KX6H/J+9\nj1iDn6aFc9lCWy1dQ+cgFrhnwvl/CPkfa03/Mq8/7/0jyJhyB/L2djvgyBbabLZ/TqyCOyGWMsMw\n1p57wv3yXcRN7mpkPFRaO54oLY2ZWff5LzLWnIXcG2YirseXIvFS7yHJk8YjMc/vIs89TZ4jwz34\nICQhz5vIvetmZPzJ6nNL/XkW2CG0cRFwuJdaYjngdGTM/hhJWvHzsM2vkRds/wj7X0HxC+p4fz9E\nnumWIi/mfhst2wI518uQcz+D1r+4MwycvGBto50792skXfBiNX0753ogImQb5CHge957ixEwDKMJ\nzrkngZN8KwoSGy3jnLsKSdRyU1v3xTAMw0lq+Z9670e1dV8MY21oa0vW/yBp0GPGAQ9573dErELj\n1nuvDMPoEHjv9zaBtW7w3p9lAsswDMMw1g1tKrK8908g8Tcx3yYx1/4WSR5gGIZhGIZhbDxkuUIa\nRoehTd0FQapvA/dE7oKfhCx5mpluqX43DMMwDMMwDMNo77TrfP/ee++cy0plbW82DMMwNlC892uS\nfaxdYfcnwzCMDZc1uT+1dUxWFh8557aAxmxXi7NW8u2gkvPG9pk4cWKb92Fj/Nh5t/O+MX02BNr6\nHGZ97Hq2c2Xnys5VR/m013O1prRHkXU3Se2mH2PphA3DMAzDMAzD6EC0qchyzt0KPAUMcM4tdFJM\n9zLgG86514B9w3fDMAzDMAzDMIwOQZvGZHnvf9DMov9Yrx0xWsXo0aPbugsbJXbe2wY778aGhF3P\nrcfOVeuxc9V67Fy1ng3lXLV5dsG1wTnnO2K/DcMwjJZxzuE7eOILuz8ZhmFseKzp/ak9xmQZhmEY\nhmEYhmF0WExkGYZhGIZhGIZhrENMZBmGYRiGYRiGYaxDTGQZhmEYhmEYhmGsQ0xkGYZhGIZhGIZh\nrENMZBmGYRiGYRiGYaxDTGQZhmEYhmEYhmGsQ0xkGYZhGIZhGIZhrENMZBmGYRiGYRiGYaxDTGQZ\nhmEYhmEYhmGsQ0xkGYZhGIZhGIZhrENMZBmGYRiGYRiGYaxDTGQZhmEYhmEYhmGsQ0xkGYZhGMYa\n4Jwrcc696Jy7p637YhiGYbRPTGQZhmEYxpoxFpgH+LbuiGEYhtE+MZFlGIZhGK3EOdcXOBD4FeDa\nuDuGYRhGO8VElmEYhmG0nmuBXwANbd0RwzAMo/1S2tYdMAzDMIyOgHPuIGCx9/5F59zo5ta74IIL\nGqdHjx7N6NHNrmoYhmG0U2bMmMGMGTPWenvnfcdzKXfO+Y7Yb8MwDKNlnHN479ulG55zbjLwn0Ad\n0AnoBtzhvT8qWsfuTwY1NTWNn+XLl7Nq1SrKysrYcsstKS8vp1AoUFNTA0Dfvn0pFAq89dZbAGy3\n3Xb06tWrLbtvGEYGa3p/MpFlGIZhtBvas8iKcc59DTjLe39war7dnzYyCoVC49+amhrG/vzn3Hvv\nvYBkRnEkGVJcM/NIfR8+fDh/nzGDN998k0WLFtGjRw8GDhxIt27dvvwDMgwjkzW9P5m7oGEYhmGs\nHaamNkIKhULjZ+oNN3DZJZfgGhqoD8sdErBXBjwPjABeCssGAjOBrwAvh3lDgFrg1Wid5198kV6V\nlUDxRbbPqFFcdf319OzZE4BevXpRXl7+ZRymYRhfEBNZhmEYhrGGeO8fBx5v634Y65errriC88aN\no8H7Jtao+WF6IOsmq1gOqA/t3gpMAv7xxBOMHD68aL9njxvHd7//fXr27Enfvn3XwZ4Nw1gXmLug\nYRiG0W7oKO6CzWH3pw2LmpoaHnroIebNm8evf/lLFn74ITlgNk0tVLOB8jB9DnAFa+cumAvTKrJW\nty8fbbNZ9+5cctVV7LnnngwaNGidnQfDMCwmyzAMw+jAmMgy2pJZs2axdOlSXn/9dW668UZeevll\nSsIyFTMO+BdNhY+KJxVQ9TTN86/LOjnHqb/4BdXV1fTu3ZuBAwfSp08fHrr/fq6bMoWG+nr0Omqg\nqaVMRdbQsLyORGjpfsrzee579FG23XZbs3AZxjrARJZhGIbRYTGRZaxvFixYwM0338wVV1xRND9H\n4vZXRiKoBiMCKm2NWhVt54ASiq1WDcA3gAdS+8+Hvx4YOGAAh33/+2yzzTbsuuuuACxatIgfHXEE\nNcuXN+7Lh+3GA5OBlWF/sRBriPqyxeabc/+jj9KrVy/LXGgYa4mJLMMwDKPDYiLLWB9UV1dz4403\ncuGFFzZZVkYiniYAlyNCJW21UmuVQwSPblMPHA78H/Aj4PfA98J3SERVfJGPAf4SpnOIYGoAOpeW\ncum11zJs2DC6dOnCokWL2GKLLbjw/PO55957Gy1nWdaumUBXiq1sAIMGDuShf/zDxJZhrCEmsgzD\nMIwOi4ks48vk0Ucf5bAxY6hZuZISEuGh1qFaROC8FuYPBc5GrEX6q54F/IzEWvQ08FVE4BxBIsay\nYrEI+9gPeCR8V1EVr9MAjdkKIRFmO++yC9/9/vcZOXIkI0aM4L333mPVqlWcf845/P3vfy/a3yvR\nMTwP7EJx/NbW227LNdddx+jRoy01vGG0AhNZhmEYRofFRJaxrikUCjz44IMcfsghTZJMTAR+gAim\nWOSMAa4msQL1RxJZHEZxqvVYZP2TRGx9BuxOYlmKhQ7RvtQKVQl8DPwvsB3w9agvdYjIqg3fS8N2\ntcDxxx/P6NGjOfLII6mpqWHGjBn86PDDWVmrayfHqH0YAQwgSSHvgH1Gj+amX/2Kfv36teKMGsbG\niYkswzAMo8NiIstYV1RXV3PEYYfx5JNPNsZWaZyVCoyhwAxgJCJe0jFNKoZ0++ayAjpEDGlcVHMi\na0S0/Qvhe100DxIxtTXwbphWF8bYTZGwv5Kwza9uuYUhQ4awxx57sGDBAt555x1OOf54Xn/jDSAR\nW4PCsaWPtQSo6NyZe/7+d/bee++mJ9QwNnLW9P60Lko5GIZhGIZhtAuefPJJqior6VNVxVNPPtko\nfOZT7IIHIk6+SvbDUD1wEXBZWO9U4PQwXQucAvw8TJ9PIrYGIgJLpwciQmoEkqgifkJrCNvNR0QQ\niNWqDFgUpjWpxjYkWQTz4aNp3j3w05/+lFEjR1LmHA8//DA9evRg7uuv8/7ixfTefHMmkQiqNC8g\nInP5v//N6FGjyDvHc889l3l+DcNoHSayDMMwDMPo0BQKBSZMmIBzjlGjRvFpTU2jsPJAIaynFqeB\niMscYZ3XKBZFKoSWIG6AADXA0mifbwPvhHW/C3RCxNAZiPBaFf5+O+xzFVJQuA4RRhojRejfZBIx\nWIpYlg4gEVTvIOKrIbR7Rlg3F9aPl51ywgnsPnw4zjleeOEF3lm0iDcXLmTgjjsWicGBiGtk19CP\nUhJ3xL1HjqSTczz55JOrO/2GYWRg7oKGYRhGu8HcBY014YEHHuCE447jnYULi1KhpzPtxdn1ail2\n/3stWq8W2Bd4ItomXUA4HdelbSr7Aw+G6QqSRBj9gGOAXyMxVy8AK0Jf0tkBhyJCrJ7i9PEDU8fv\nEdF2JWIJ0zTyDSQWq9Iwfd0NN3DooYdSXl7O+++/z9677UahoaHIsqZJONKZFEuAlXZdGxs55i5o\nGIZhGMYGzYIFC3DOccABB7Bw4UJKw/z5SGKKUoqtUg4RLDnE4qSWohxS90rFxDeB/w5tzSGxKs0O\n688miV9Sq5OmcFc3v0fD3zxSv6pf+GyJiKA8MBV4JvTp58BBYf+xe2HatRESS1O871LEDbEQtts3\n9E/7ozW6zjzlFLbfait22Hprli5dyvL6embPncuoffZpdFvM2ufzYb5zjjvuuCNjDcMwsjCRZRiG\nYRhGh2DWrFk459ipf//GmKTYYqNo1r5a4PuIOOpEcQxTHKel4uIxROTkgPJW9KeQaisWZN+iWOxU\nA7eF9QeFjwf2QVwFHWLl+jYixrSYsLo3DgTOoTimC5L07xqr9RiJO2FptEzdF1esXMm39tuPMudY\nunQpjzz+OEuXLWPcuHGNlrGBiPgsBe4iEZI/OPxwSp3j7rvvbsXZMYyNG3MXNAzDMNoN5i5oZFFd\nXU3vqqrGGk8O2BSJmfKIAJgIXExSIDj9K+g8FS+xO2E9iVjTjH3pGldZ7oIeESJzwzzNIrgbImji\ndO/jELe++ow2VPidAAxBEmzMRwoYnxv1K5c6tgOA+yh2KdwpWh4fl7pTAvwnIui0rVtuuYVjjjmG\nQqFAn80249PPP2+0ABL6cisSU6b9BnjwkUfYd999MYyNAUvhbhiGYXRYTGQZaXpvthmLly5tFDSz\nSepNqejpDnxCIqIawroeiYNSF8B+SFr0McDfwryBwBuIBWc+Ipi+DVwKfApcThJndSxSF+tlEle9\nrKLD6biwAYjIiVPHe8QydUnGtmrh2gu4BhFs/wNMC/svibaBRGQVwrlJiyI9V2eG9lRoaixZPiy/\n8aabGDx4ML1792ZQ//6N7o2zkeyI6dgwbWeVXfPGRoCJLMMwDKPDYiLLUE444QRunj690R0uFi4D\nSFzYxiNiojajjTuAZYjQgsTiNZnE1S9Oab4g/B2ICIvyMP0YkqwiLTYGAD8DbgrfhwO9EUEWW8OU\nOLGF7je2gqmoUQuUCiEPTAB2BX4U5p2ECMW3on1pTa9ZUT9jsaXnMS2uVJjG1q43Fy5kyZIl7Dl8\neKP1Le7/quj4GoA/33473/3udzGMDRUTWYZhGEaHxUSWMWHCBK6aPBlIHuLHIMJoEEkGvPQDfz2J\nZUmJ3fxikVYAdg7rxC6IDYhFa3WoGBsK3IkkrkhnATwbeBJ4PMxTdz8otn7Fx+GRrIO7ADOBPSi2\nksX9uxuJNwP4N0lMWpwVMS0K9VzpehqLpvW4Gii2dvWorOTOe+8FYPSoUY1xXyps1X1RRaFHYr7K\ny1sT0WYYHQvLLmgYhmEYRofjxhtvpNQ5Lps8mVWImJgJTEeSLwwjKcAbW1xqkQf9i0jqYmkyi5mI\n+DiLxL1vMCJi9iPJRDibRMxoogrNEJj+XopYsPohKdi/Ffq6IszTjIbHAL8M2yxAUsXXIcJoFYnL\nXZxRcAJiPSshsRTF9b7iTIaHI+Lq36GdV4E/URzztTNNLXx54DySpBylYRsVX1eSZDf8dNky9h01\niv1GjaLOe/K5XGO9LxVycxHroIrfbp06Men88zGMjR2zZBmGYRjtBrNkbZyUO9doCVExkbb6qHtd\nGSJGJpPUvJpHknRil2jdF4CvRNMgSSlWIbFNm6W2mx2WjaDYMjUk7OuCaL/pellxP9Op0Och4ine\n18ywn/8H/BmxrsXHrCnn0/W+NJlGnODCkYgk3d+1SCxa2oI2Hokz02k9Hj2WOhIRW4/EjP1XOK4/\n3X47/fr1Y9Qee7CitrYxrX06XqsW6JbPs2xV3CvD6NiYu6BhGIbRYTGRtXFRU1NDZWUlIEJAk1WA\nWEd+QCJMdkaEgcZo1SIP/i+TxE5pTJLio7+lJCnR418ojvd6BfiMbJG1KuwnjseK45QGh7bV/TBu\nW8VLmjLgOWD30M5TSOa/HYHXSWKm9Bh0f59F20BTwVUP/BhJlvEIEsf1QXTuIHERTAtJbWcU8M9o\n33UkhY0feuQRttlmG3bq37/F4s/bbLUVjz31FH379s04esPoWJi7oGEYhmEY7Z6hO+3EZpWVje5v\nmrxB3eM0OQVI9j99kJ9LIlgcYhXSB/s6RCisIqkLFccojSdJ/FAbrauCbSAiXtL1qdSqlJVcQ6lH\nxGBcLLgUsbqpm5+6HargW4W4QdYCHyJWtlLgvXDMp4dlvaJjGBjWU7JqdTngd+GcjkEE1gLguui8\n6bkimldK4pL5VDgn40ksi3Vh3rf224+d+vfnyWef5bbbbweKiz+/GvryzsKFbLXVVmzRvTs1NTUt\nnD3D2PAwS5ZhGIbRbjBL1obPc889x6iRI2mg2AKiSS00zXlsmaolES+6rB74bVh2DJJRr4wkhXkB\nsc7ESTIGh791FNewas7SlCZOrJHlLhhn9SPsH4pTt6srYUO0XZab4aPANiTZDfchu5ZX2pI0lKbi\nSY9vT8RNcjpwPMWxbdquZjscQnJO4r5pHJcm2/DA2wsX8vV99uGNt94iT7aFDeCAAw7gr/fdh2F0\nRMySZRiGYRhGu6NQKOCcY8+RI/GI1SemAUlQoRYRwjrXkLi5DQ0ftershQiHPNA1Y59puVsPHEdx\nBkKAOYilRy05C8Knc/jo9zzFFrBV0fd6RODFFrA6moo3tZrFCS3OIUnooQk29kfcBmuBvUlSrC9A\nUrfrvutILFwDSYRYbNkibPt8+HtKmKfWLO2TCqkCSd2w+SRJMtTFsC7avgHYbqut+HzZMhYvXsy2\nW2/NQMSdMrawAdxz//10r6iguroaw9jQMZFlGIZhGMaXyk9//GMqOnUCigvollIsnC5FHvR1WVfE\nwgWJq59m3fsFYinZhURkpKe1aO+QaB9TKRYlDom1ai3q6heLr04kcWKx8FKLUiy6sl6DX0mx6JpN\nkrEvFl4NSAbDb4XvncLfY0nSqKddGtXaFbsxxi6UIC6N9WH+QJL09tDUHTGd+j0X9rto6VKqqqr4\n/Z//TKlzmZbBEuDzf/+b3lVVDB80KGMNw9hwMHdBwzAMo91g7oIbHqXOFRXmdYjoeYmkNhOp5a+S\nFNGNU5efDVxM8YN+S2hmvVLEWnQJLcdVlWX0Jeu7WpVi10YtXrwjxVkBB1BszYpd/bRNT7Er5EzE\nShfXt9KshPE2KqxuQ2LJdgjf44yCun4pxRkAVRzp8TUA5yOp5m8jsR7qell1yeK091rQuCTs66uj\nRvHEE080rqNZIOPiyN022YQly5djGB0Byy5oGIZhdFhMZG04VFdX07uqCkfTQr1xuvZy5GF+JU3d\n+4CiGJ84c11c0Dc9TdhHOusdzazvo23qga+F6SeAryMxUWnS8VmvhOlYZKWzAKpYGkJ2fJW2le67\nbjciWk/T18fZB1XMzUMsgF8H/kFSNDjexyuI4Lkw1YYuPwNx1awnsQhqIeKLKI4p0yLJek5qwzbd\nNtmEZZ9/3nicWeneS4DXFy60DIRGu8disgzDMAzDaFN23H57tqiqanwQT9OdRGj9gcQ9MHaNKyPb\ntU6L3qZd2GZH0w00jfkizJ9NU9c53TYX9vs08Ezoxz/JLk4M0BsYjVh2+oVPPSIy+lOcBTBGrT1a\nP+tR4Nck7oYqlmI3wxEkmf60jfgcqGthHhFlAN9F4rc0dkuLNHvEDfCS1LmIz/dVYZsB0fxVSK2w\ndEyZCjGN11Lr1yeff04OGLTjjniyiyPXIanet+/Tp5mzZRgdk3Yrspxzbzvn5jjnXnTOPdfW/TEM\nwzAMY/WUOcfbb71FDho/cTIIgE9IxMqRwIowfwLy0D8TeXh/lqYJL84gW3w16Qfy4K/bxjWimkPr\nQMXCI3Y5jAWNQ9KuP06xONTp2KqjAmwFYmGKixmDiLW9wrbzgCcpjuuqRwTOJBKx9Ito+3TclAqu\n04GDo+O6Czg6rJslePJIEhCiY36DJO29uic2h1oZVUDrOXj1tddoAHbs168x7msoEnemFrZ3PviA\nnQcMaKF1w+hYtFt3QefcW8Bu3vulGcvMHcMwDGMDxNwFOza5EH8Vu7GNAe5FHtDjYsL7A/dTHNuk\nKc+fRtzsZgPDSeKv1EKib4hbcheMH/hJbZPlLhjHfKULEWsq+ZcQQaNp4kHEwlM0dQs8G7EUZfWv\nuQLFZSRuh+pWqZa1BYhlSs+fS7WVi7ZNp47fiWL3vlrgJOAmil0VtQB0enu1pul6ZdG0/tbjgStI\nRKCilkXd98OPPML+++3HHMSKl07zvtPAgcx+5RUMo72xwcRkBZE1wnv/ccayjfomZhiGsaFiIqvj\nUuLkZ9OkEHEslMYYaW2qoYhYyYrXUuLYpJnAciSVOcCPEXHw63XQ7ypgcTPLNJOg0lxdqrTIikVK\nWpRpYovdScRRfMWkrUtp4TUbWATsG+apVS2dLfAKElE4jCSVu6ZdV/FzIvAu4lZYkrG97lePG4rT\nvau1SlPE7xotU0GnIhYSC1csxPKpfW1RVcXLr79Ot27dMIz2woYUk+WBh51zzzvnjm3rzhiGYRiG\n0ZRjjz2WEucas8tlMZqmrnoqCupI3OliFzmNTapFRMK+JO54twK/J3HNS7vqNTedte4nLWyjKePj\nmljap9gFcFg0T7MJrq64saY/T9eSylPclzjeqxaJFdsiLJ+FpHG/CjiTRKxdQuKiOTTMfyl8PPBN\nEnfAm4H7SNK/16a2H4gUcVZhGaeWh0Rw1SJCuJ7ieC3dj4rHeiTJiV4v6VcSpcAHixfTvbKSIw45\nZDVn0TDaL+3ZktXbe/+hc64X8BBwivf+ibDMT5w4sXHd0aNHM3r06LbpqGEYhrHWzJgxgxkzZjR+\nnzRpklmyOhDlzjW6AepH3fn0LGwBzEDcwlZltKEWlqyMgZBtPdKsdP9Ckks4ii0hs8N02q1Ps+C9\nSmJh+ifw1VTb/wQ2I7HgxMfTXFr3+FdfXexSZ8RapFn64nTv6dTwuv94H+pqeDBwD1Jf7HvhGK8F\njqc4o2BJ6vg8xWnyidaN3QJz0V9HdnZA3UbTuMfp62OrnSbHqEV+8zhLpIu+H4hY1fQ4Bw0YwOz5\n2qJhtB0bjLtgjHNuIrDce391+L5R3cQMwzA2FsxdsOPgnGtMbOGQh+hSEtGklih9gNasgPEDtZ6p\nUkR0TCKpN7U6l7v1IbLSroCfISIjHUdWS+IKqQWO0zFY8byseCylc6rtF0I/0uIlFimEYxsSjum3\nwHPAQiSOS61ORNvNRs6d7kvrX6VFYxXwAWJVay61/C4Uiy1lDHA1ye+l2Q3jGC3tz5Y9e7JoyZIm\nxwlQXlrKZ7UtVTgzjC+fDcJd0DlX4ZzrGqY3QSzbL7W8lWEYhmEY64My5ygjEVjzgYeRB+YZSDxP\nLLp0XY3HmU1iXdHU4ZeQXScLRHSVkrivqcVsl7CfutSyXcLHRfM1FikXvuvyr6bW03kDkWQOmq69\ntWSll/9nNE8z6jXn6lhP4h54OPBgdIwxc6L2CW3OBf4Y2toTSbcOIgKnk9TEckh2wXSb+ntNJEmh\nvzi0F7tv6rkaj/w2mpVQBZZaw/5GUvh4bmi3JDrekujvoiVL2HabbYr6oy6bn9fVscvAgRhGR6Jd\nWrKcc9sBfwlfS4E/eO8vjZZvNG8KDcMwNibMktX+KQkWrDKSRAcPA0uBQ0ksWeqmNg4RUGo5cWG7\nlqwo0NSiotayOGHCfsgD/ePAsaGN3yLWmzvC3xok5mA40Bdxr4sLDA9FUrEvSR1nbJFpzo0x6/s5\nwOU0tYx9labuduksfkNJ0rtnZU6MrUBjkXisy6O+pi1d+iZd4580nT5ItIr9CgAAIABJREFUweUn\no3UcIpoup9gyOIhi10dH4vap+42zEmqiC/2dNNtkc66GcZ0tbV9F6HjEulkS+r3PPvvwl3vusYQY\nRpuwQboLptkYbmKGYRgbIyay2jcuElgg2f4eI7HeqJUkzhY3mCQZwq0UW1OyBFQlcB5SB+oioA9w\nTFgvK9ufbt+Se15zy9NtpL9nxZAp2yLirIC4+P2bJNNec/tLu9ulRdaQsM9ymro/3okIjpbE55nA\npsD5wANIzFb6nykrk+FgxN0xXjcrhiv+rsdTT1LE+bzQR021r/uI085nuRqm+xa7Qo5BxNmkaNmh\nhxzCn++6C8NYn5jIMgzDMDosJrLaL+XONVodVCzE1of5iODYmebTskPTpA3fBu5G6kAB9A/rxLWY\nVKjUIwk05ob524a/bwM7hOnXU/sbicQV3RO+Dw37fyVMaz/VurV92J/2ZzvgrTAdi7wsAZcVa9UL\nqI6+qxCDpoJJ/6bP30ykWLFaANMxaK2xfAFUhO3SCS8gcaeExPqkfUonHdG4ubQ1ijBfXRchqYOl\nCS90f2r9Ghotj9vRfrxEsQVsx7De0IEDmWX1tIz1iIksY4OiUCgAUF5e3sY9MQxjfWAiq32iFqzt\ngHcoFgl6tPoQvlP4GwuHI5AH+9sQETaMYouKbr8f8H7U9rGIwHguzFPhlWXNSVukyFgna5t4fnNu\ngTq/NakXVFQ1J6ZaaqOERLjG/VBRG7tcZlkKIXG9jPcbH9cZiEvgpYgAPSisn85iqGJRhWWccXBe\ntK848YWuV4v8Zl1Iko+osNNslJoGfjwwmSRdfrr+VizyziTJPAhST+vdjz7CMNYHJrKMDYZp027m\ntNNOB2DKlGs58cTj2rhHhmF82bR3keWc2wr4HWIc8cDN3vvro+Ub3P2pLNTASrsExpaNgdH32M1O\nXQf1jFQg8VO7p7bXmKHS1Py6aPuSkhK+c9hh7DR0KPfdfTfPPP88ADsPGsTRP/sZFRUV9O7dm2XL\nlrFo0SIGDBjA1ltvzbvvvsuyZctYsWIFPXv25MMPP+STTz4BoKqqih122IHly5ezYsWKxk9lZSV9\n+vTh/fff5+2336ZLly5UVFQ0LuvZsydLlizho48+YvPNN+fU445jVX19k4x/LbkbQpJxMSZLhDUn\n2EqAU4ApFIssj2Ql3C383YUkJisWXFCcsv1M4B9I/S3dV/xban91/dgapWIrzhyo4jBtjdohaseF\n49ufREDptrHQUxGXvm56dO3K4pqaJufMMNY1JrKMDYJCoUDXrj2orZUhOZ8fymefLTWLlmFs4HQA\nkbUFsIX3fpZzrgvyDHuo9/6VsHyDuj/lnfwU6r7XXDp1D+yBpDuHJCFCbZiO19V5mnji6+Hv0cBv\nUuvecNNNnHHKKTwV0nfvlc/z9vvv06eqqmi9JcuWtXkyhHnz5vHggw9SV1fHFltswYoVK6ipqaG0\nVFKBqDg7PBTYVYHRkmUrtubUUyyO1F0zKwbsv2gqfmaG5WmB25yr4dlIwhIo/j3j74qKrbguVtqN\nEBIXzLhmmgq/WECpNS4WrZocI12Dazdg3LhxXHxpY340w/hSMJFlbBCYyDKMjZP2LrLSOOfuAm7w\n3j8Svm8w96fOzhXVuSolibMZQmJlUNeyrGK0/cgWWeU0rZWUnu7SuTMffvIJlZ06Na6bAxYuXtxq\nkdVeXc7nzZvHnDlzWLZsGRUVFbz99tusXLmSrbfempqaGq6+7DIWL13amFUvjVp/sooex9ax2N3u\nFaTOVyyyNHNgVvHg2H2wFnEzXIJkbywlqYGm2SQhqYs1lESkaR80SQahf+WIq+B5YV58ncQiK7ae\nxla/MeHvveHv9w4/nD/8+c8YxpeFiSxjg8HcBQ1j46MjiSzn3LaI99tg7/3yMG+DuD+NPekkbpg2\nrch9TxMYgDzwdkLSo+sDtz70O5LkE+n4rFIkC19aeJ2EWLL2oNgdbt4bb7BT//5FxYVnzZ3LsMGD\nG60p9c6x7N//biKkbp42jdNPOw2Aa6dM4bgTT1yLM9F21NTUMH/+fN58803y+Tz5fJ4lS5bwt7/9\njbvvvLPZYsZ5mlrH4kQWKnrywKmIKEqLLE2yMYLiRCf6O6pgOhjJ/ngTxYJrAhL39UJo45s0dQVM\nu/8NoNgl8kCaZhVUYaefkmifdcj10q9fv2bOjGF8MUxkGRsU7fUtpGEYXw4dRWQFV8EZwMXe+7ui\n+R3+/rTbkCHMmTs3MwZGxZS6/MWiK22RKiktZeKkSZw/YQJnAtciD9dZLoQe+DsSlxPPf+7FFxk5\nfHjRg7SmDD8AuAwYkc+z9LPPiu4ThUKBTTfZhLn1YjsZXFLCp59/vkHdSx544AFmzpxJ9+7d+eyz\nz5g7dy6vvvoqz4dYtZgSit32ciRuevHvpqnX1f1Pk2o0V+NKt1+FCOWpYbm6Oc5G6qhlJeZQC9Um\nwH8D/0lSIyxHcRxXnA1RLXf1NL2O6oHdhw/nmX/9q8VzZxhrg4kswzAMo8PSEUSWcy6PeCnd772f\nklrmJ06c2Ph99OjRjB49ev128Auw+y678OKcOZQitZYuInmo9cAJwOkkadb1YfpBmgqkeqCspIS6\n+vomKcmzXASzxNegnXbilfnzeSXc83dCBEOczCHvHNfdeGORpaqmpoaelZXtLm5rfXHbbbcxY8YM\nAOrr6/nbXXfx4ZJ0ueWmxAk2IHH/zBJZ6TTuceHjtJUt7QoYuw46kvTxJSTXnQq45gReXardnZCE\nHbsAF15yCePGj1/t8RpGS8yYMaPx/whg0qRJJrKMjkdNyAzUrVu3omnDMDYu2rvIcs45JCzlY+/9\n6RnLO+z9qbq6mr5VVUVWDS1yq65g6TTn3ZA4nzqSpASfIckIHgd6kBSbTVvESpB4nCsQgdUT+Jhi\n9686oFM+z0sh8YUKNH2YbuxXLscnK1Y0WqoKhQLdKypwDSIR08s3RtT98JFHHuGpp57itdde443X\nXmsS0xWTI/t3LyUpoKzJNWLXQlLrxynhy0K7Gt+XZRW7FslEeVLUVtoSpqJMiZNv1AKXmtAy1jFm\nyTI6HEceeRR/+tNtAPTpszXvvy9VWA4//AhuueWXlJeXr/Mbo7khGkb7pAOIrL2RLNdzSJ4hz/Xe\nPxCWd9j7k3MuM0mFQ2JsfogkSkiv0wC8htTCepnkpGgcUJwgQy0eq5AH9bSFqx/wRvh+EBLHM/68\n85h88cWNNZUmhT6NR+J+HkIyFKYtVTdPm8ZpY8cCMOW66zpcTNb6oqamhttvv52PP/6YBQsWMH36\n9GbX1aQasYBKuxZmFS2O4/k04+B/AV9DLKBZ66ngUiEV19W6kOR6UouWxujVkRQ23nXIEF54Sa8w\nw/himMgyOhTV1dVUVW0JvBrmDERuvROQW2kDuVwZ11xzJSec8LOit5RAEx/8QqFQNC9LRFlCDcNo\nv7R3kbU6Our9qTTUwkrXqdoMySinNZk0HiodT/UqYoX6Kk2TKOwatp2AxFDVIUkO5me05YAtkILE\nHti6d28efuIJBvbvzxwS9zRCmyrgckDNypVNxvz4vmAv1VrPrFmzeOyxx1i5ciX33Xcfr7/+Oh9l\nFP2NMxlm1U+LE5bE82M8YrHqiYintMhX4iyGOUSkTUaEWCz6+lJc0HrokCE8b0LLWAes8f3Je9/h\nPtJto6Mzdep0n89XeMh7uNjDAg8VHuaFv6UeZnno5CHv8/kKP3Xq9Mbt8vkKP2XKjX7lypV+6tTp\nPpcrD9uU+1yuc+P6MStXrgz7XOBhgc/nK/zKlSvb6AwYhpEmjO9tfp9Z209HvD+Vgi8BnwdfHv7m\nwZeBnxemc+HvAvDfCtOl4A+IlhOtsyBMPxraKQXfGXxF+JSF9csy5lWAHx71Y7ehQxunO4O/IExr\nn3Xd74wZ0+TYpk+d6ivyeV+Rz/vpU6e2wdndsJg7d64/8sgj/TbbbBNnV2/8lKauH/3NOkXXRUVY\nb174Xpba5lrwF4X2ctF8/Z4L21eAvzi0Xxrmu9Q1WBGukwnnntvWp87YAFjT+5NZsow2IV0HK3kf\negFwGLAzkjtqCHAV8m6rQEnJrngPDQ1z0XxD+Xye2lp1KlDnlBLgX+TzI/jss6VAEvfVp8+2mfW3\nampqqKmpoVu3bo1vPO3Np2GsX8yStX557rnnGDlyZJEL4CASN608MqJq1rn5wIfAvhS7danLlibD\ngCQTYBmJ22FWUeLY2qEpujW+q4DcDcYccAD33X9/o6taPfAc0JUkyQbAJ5HLYKFQoEfXrjwf4rmy\nshAaX4xZs2bx7LPP8sQTT/CHP/yhyfI4iyFQ5PKZZeVKuwt64Ebg5yR3d21T24tjs1ZQ7M46mOSa\n2qpPHxa8994XOFpjY2dN70+51a9iGF8++Xyeyy+/lFzuEmTIzSH5qq5Ehtlbgd2or6+loaEeufVO\nBuZTW6vVNRqAb4S/q4DlAEyf/is6d66kqqoPVVV9GTJkKKWlQ8jnhzJlyrWUl5dz5JFHUVnZi622\n2p7Kyp507lxJ1649uOaa69bzmTAMw1h/nHz88U0eBBoQYQTwe5I4ql6IoBkV5s0PHzVjzCMRaOrC\nVYokwGiuppNDRvxdgH3CvK7h761IMgUH/GPGjMbU3vqEsyrV59idTPH19YwI7fj6+ow1jC/CsGHD\nOP744/n973/f+Pb+xRdf5IgjjgCSTIO1iBBeRRJTtwuSIEUF0mc0va7qgZMpTkHfEP0thL8vIbW4\n8qHtgSTxgq8igu7d99/n8smTv4SzYBjZmCXLaBOmTbuZk04aiw6bzuW46qrLGTdufMq6Fb+jKiEZ\ndtUbfwYS8pyOEJDb8He+cxj33HM3dXUvI8PxbkAtpaV5rr76Sk499SRqamqorNyM4hBszZe0C9/5\nzmH85jc3N4n1as7X35JqGMbaY5as9UdNTQ3dKysbLQNpC1TnkhI+r68vqocF8L9ITaN0tsCLgIuR\nB+pzkVdkakVQEaQZC12qzZh4me6jH9k1kdSytQoZwatTlqwNvVZWR2DBggVcf/313HDDDcT/G/rb\n5ZDfW9PFx7/xP5H6aSrMsrIV5pHYv92jbXcI7eWRxByTkesyByxcvJhevXqt8+M0NnzMkmW0ewqF\nAmPHnkbynnM23s/jzDN/QW1t/L7TkeQLSt+ONfz6a6n5eSQpsPCXv9xBXV0tcCbyLlNcCevqnuas\ns85uFEQt8Ze/3EFlZQ86depK587d6Nq1B0ceeRSbbLJpsHptynXXSQnGadNupmvXHnTt2oNp025u\n3QkxDMNoA/r26lWUKe758NHRtlBfT6cwrdYFgKqwzdDw0eQHE4F/IaP6lSQPzTkkYUU9MgLPBl4J\nbamFI96HB7qspu/qHK6JEQ4M+7thSlHZMnK55DGnvr6eX91002paNtY1/fr147rrrqOhoaHR2nXi\niSc2Xg+rSLIBxlaoHHIdXIJcM5qUZT7J00Mp8rsPC218HPZZgriTggi0l8J2DUDvqioOO/jgL/eg\nDQOzZBltQKFQoEuX7tTVqRNKOi6rDBkK1Yql70JfIfHQ13erzwB7kDwWTECqrsRt/pOmOa9y5HI5\nVqz4pNFd8E9/+hPF3uB6c9b9K/8BPBzaS+rQX3DBRC666GLq6+cCBUpLd2P58k+aHL+9RTWM5jFL\n1vrhO2PGcNd99zUKpAlIOnQtChtbFHYEnkYyDca+AnGq9rrw/XXgl8B1FI+4j4XptN+BWhfSMVgH\nI+nb1RVRayjF+6xHnMq3odjvIc4yOPX66zl97NjGWKDJFpfVLjnhhBOKUserZbWB7ILEQ4GzEQEG\nybWh8Xp7I0J/H4rTyg8Jf+uwGC1jzbEU7kaHYNq0mzn55LF43wCNyYFBhr45SDxVWhiNQ5Jg1CFJ\nMe5HhuG4/KF+j7fbG3gyNU9YuPDNxgLIW221HfIedzkSdaA3YX3POgH4HvIIkB72E7Elw/98oJYx\nYw7igQfup6EBnPOUlJQwZcq1/PSnPwZMcBlGGhNZXz41NTX0rKzkQWA/5JWVFpxVsaTO06cjIy0k\nD7IPAouBHyEj8QOp9rNSeX8dcSXciySxhSbM0LZ1W0XFXvzdUVzA+CzEdXFnxK3sm8DBBx3Enffc\nA8hLvcqKCp5taKAM2NVcBts9hUKB7bffng8++KCoRlYsstOvUxMH/zhgADYFqklcYUuRIshaMPvt\nhQvp27fvl3g0xoaEiSyjw1BTU8NNN93MuHETgtjS26l676fFEqnvM4G7kHdZE0miAbSd9JB8CUlu\no4tIxJN6hDvE6eRv0falFIsoHaq/EdZziCiM37FpdZDxqbZKgNOAK8nlShoFl9bpslguwzCRtT5Y\nsGABO/Xvzz+BkTStjVWHiKvraSqWdKTW11pq8VILVB3QiSTGBmAMMhLqKzWHiLinw/LhYX5WkePY\norZD+J4uYKwxXhq1C0lh4kKhQGWnTkX9XZZRT8tovxx44IHcf79Iff2ddVqvjVhklSBCChLLKySC\n/lCSO3M+l+NzS4hitBKLyTI6BNOm3UzPnr0577yJTJlyDQsXvkVikVKD/wRkiBwUtsqnWhmJhLOW\nIAJqHIn1SZ1MZoflh4a/zyMp4vVdreYimhn2/Tea5jYqhPZnIo8F6qRSFtrcheKSiSDWsLitUuAF\nxBIHDQ0N1NYO5LTTTqdQKHDddVPp0qU7Xbv24Prrp7YqVswwDGNt6NatGw7xFYifFgokD6TXUGxV\nUl4gKSJcFeZJ7tfkAbgeOAMZUWcCV4f1BiLuhJr8Yvfw0VE4RkfweGTtFNbTedpfjc8CcQ6H5KVV\ndXV1Y+p5jcmprq7OODKjvXLfffc1xnI1eE8dicVV47fqkDvxARQ/2OpTg0Z454F7kKLHtwG1DQ1s\nudlmvGdug8aXgIksY71TKBQ47bTTqa19idralzjrrLP5wx/+RPKO8hxk+Pwecvt8Imw5HnlfNRDY\nn+KcRHWIEBqP3Eo1ZmtV+Ls7clsfjnhlN4R1Ne/VHjS9zYPczrV6y+4k8V8NwMtI0mJoGq77lRbO\nwJzQx5eor69n6tSbOO2006mrc9TWjmfs2NPp0qW7Jc4wDONLoVu3buAcMxHbvUPqE+0clueRkTiH\nWKF0ZHPAvVE7WhVpEjIaqvhqQISVQ0bNwchI/irwK5IH5HQKeH1oHoK8lioJn4HIyD8+7O/on/yE\nnZCRWUfwmWH7/w3r/N8f/whkewb8KSwzOiYquGq9pxa5S69Crqv7w9/4mlF32PmIz0sO+C/gB8j1\n8+HSpWy91VY457j77rtNcBnrDHMXNNY7hUKBTTbZNCSIgFxuECUlJSF1exzbFCee0OkSkqQYeSRr\n4OVkOw24aNs5iJUrdh5Q72yQ27pHrGHq7a+377RTglZn+QXwfeQxYmaY/xUSN8VvIVEC2u/6sE9N\nJ78z48adw9VXXxulrR8atn2B0tLd+PjjRY3piA1jY8DcBb98tEjvjNpa9iYRRuoM3YCMgOOBy5AR\nSUfQASQJCXQkzHLzK0Vyvz4Slus+6sL8f6S20VdX6kr4crRMXRB1RF+Vsc986HNd2LcjSYCx5667\n8q8XX6QU8Y+w5BcbHrNmzWL48OFAYtlU11SN33qepo796kYaC33l/vvvZ6+99rJ7sNGIuQsaHQK5\nRiUBcHK9JgWGE8cOdQzJIUOlUoYMh5elWq4FdkXeV3mS2+0IRMCBPC7MQW7H6panroGXA2PD91eI\n08EnaJr4qxCBtTniLKMh3Tq0P0zi+viP0JcJiKATEXjZZZdTWxuX1FyFCMc7qaurpXv3qkyLltbo\nMgzDWFPKy8s5+OCD2RMZrf4R/r4UPhqhcguJY3U5MoKmxZUKM7UcqKWgFkk3NCi0N54kecEcim3/\nExErF2GddOFidRv0SEa5NPnQp71Cf7qGddUi8fjTT5PL5XgBsV40NDRktGJ0ZIYNG9Zo4aonEdwe\n8XGpQyy1acd+SKympRQHJRxwwAFUVlay1ZZb8txzz2VsaRgtYyLLaBOkdMlTwPOUlua46qorKC2V\nQsEJWrpSrVeXkNR3PwO5db+K3KL1dh2/i9J3WeKaJxYyjzwu3ElSc74/MgTPR96fXhWWFRDRNRFx\neNGEw2ci78VUDH4U7U//arwWYZ8jwz4mRvuaHZars85OYfry0Nc8DQ05Tj75VBYsWEB1dTWFQoHr\nr59qtbgMw1hrCoUC99xzDw+H72UZ6xwILEJGpPHIq6ELSYQSyAgWF5N9HhExmjmwAHw3LJtMUqvo\nU+BR4Jiw7AehvU4k1iwdcfU7SLqhy5EH4QaKXcIc8LOwrAYZqU876aTG48khr9qGAq6dWxqNL4aK\nLUVdCtN1uLQsQByzB3L9asR2Dnjvww8ZOXIkzjl+8IMfcMcdd6yvQzE6OOYuaKx3pk27mVNPHUt9\nfT25XCk33DCFE088jkKhwA9/+GPuvPPOsGYJxZas2YjH/VVhnrregbwvjd9OZrn6xa6COv8IEueB\nicjtXl0CtY7XRETgaebCrHbrSUSVtnUQxTW81MrVAJyLhJavIsnjBRLjVUDEn7a/U6qNBvS9bz4/\nlPfff5vy8vJG1xdzgTE6MuYu+OVTKBTo1rkzd3vPt5GRVN/6lyK2/CtIMv6VIiOVFhbWbH79kUQW\ntSQuWnFqds0OeApwA8Uj5teQkXy3sE4eOBXxTVCLwkCSEV5HT22jH0nkbVxDayLyiqoWeVCuXraM\n8vJyenTtyvO1cj8ZYe6CGxXOZQ8n+oIgzmCpeYt3pzgVvJY30O08cMYZZ7Dddttx8sknfzkdN9od\nlsLdaNcUCgW6du3RGIOUzw9lyZIPKS8vp6amhj59tqW29vmw9q4kjisOqd/+FZLb7mASN7+zkFBr\nTSasIiWO8VIRpWLrKZrW4ipBXAEnIY8Iv0BKGr6AOKNo3NiFJHmt4vSvsTBahTwuqCOMijF9FzwU\nEVX6yKKPCE8BD2Uci7bRAJyPJAYZjopL53KUlOS47LLJHHvsMUXCyzA6Ciayvnyqq6vpW1VV9GpI\nR6uhFAsbfXWlhX7T0an7IVap+IhfReoQ7RraeAkYFq0zFHEZjKNr47TwcfXEdOHiBeF7P5KU7c+Q\nFEpWcdULqeV1zrnnctHkydw8bRqnnHwy3nscsNuuu/LUCy+0/qQZHR7nXKM7oL6+LafY/2UM8iQx\nALku49hASJ449IWECq9nn32WLbfc0mpubeCYyDLaNWmRBQPJ5XJ4D96r2JiP3KJ3J9talGXh0XdO\ns5Fb/+7RtCYXVrEziOS9bfo2rmHT+g7WResB/Cu0pzfnROQIcd9KSFwEVdzVI8O2JuGYHabjhB2a\nICMuD5pVPSZd8nMQye3CkcuVNFoJDaOjYCLry0frZM1ERrM4nVCWsCml6SspFVkzkELDmmJIMxLG\nFQJj8fQMkg5Iqw6eg7yyam4kbs5fILaopUfHc4FLSUbKz1eupKamhi2rqpgT1t0Z+GDxYnr16tXq\n82ZsGKhlSy2hKpQ0gpvou4qsoSTXsb5WjbdVKsvLuffhh9l7773Xca+N9oAlvjDaNeXl5UyZci35\nvKZin0hDwzy8L0HebZaG+btlbP0vkvirARQnAda4pl0QgdU9mi5BIgyGhnX01qsiKk69PjHsS/+H\nXiGJPKgnSec+Avg/Em/u2WH7IVHfNKnxpDBPixunrUtxdRrddw55fHk8zNsxtD0x6svPSZJ3fEby\nbu5MoISGBs+pp461BBmGYRShwqIrIpw8cAHFr4ti4ppacV0iB+wT1tHXQvU0rRCo7IL4A0wKy15A\nHLFbSkOh+9P6R5r3dR5yx9C073HSjUtJXBdzJHWxHBKNOyJM/+7Xv25hz8aGiveeo446inrkes0D\nfUlqsGn8VpwK/mySFwnxU0cpxRHYywsFRo0ahXOO6dOnW022jRwTWcZ658QTj2PJkg8pLS0lCXkG\neS+qjiJQfEsvQR4JdP2sN8VzEbEzE/iEZCjMAfchHv9pYdaAvEvVYsSXhTaeIqm6MoLE8gVJIo2L\nU+uo8Mnq2ynArDCtxzQUEZOa82h46FPv0NZeJI82+t72WZKSn9ORIX4YEvulzjPXhP7WU19fx3XX\n3ZjRH8MwNla6devGmAMPZCBSXt0j1qRymiYGUCuXukidSVJlUN38QAROA9BcBSqNJNWiFrci7oQN\niKtfjuKRsTMyKuoIrblaNa+soiPz88A3o++Pkbh2nXz88fTq1Ytdhw1jEkkCjvMmTLCXUBspv/3t\nb6n3vvFa+ogk6roz8tJBRdgq5G6fJk/yalj/V5Qy4IQTTqCqqorePXpw4403muDaGNEsLB3pI902\nOjpTp073+XyFd67cQ5mHUg95DwvCJ++h3MMsDxeH7/E6Oi/v4aDwt1PYJt1OJw8lqfmdPczzUBH2\nURLa7xz6o21fHNbXPi6Ivus6h4Z2tI+5MF0Rtq+I9lUW+jgv9Ktz+GgfSzO2vSDa1wWp/peE9rRf\nnaI2OnnI+4MPPqzxvK9cudKvXLmyDX95w2ieML63+X1mbT8d5f60ePFiXwK+M/he4PPgF4AfDL4E\nfDn4i8P8XJiXBz8PfCfwFWF5RZifD+s48F2jeWVhH2Xh+3nR/Hz0OT34OudCmwvCvnJR3xZE+ymJ\nptPtpdvOgV+2bJlftmxZY1vzwJeCv/bqq9v6pzDamIMOOkj97H1p+FRE11wuWhZfWxeH5RXh/6Vz\n6n9B28yHvyXgd9x2W//GG2+09SEba8ma3p8sJstoE2pqahqne/TYnPp6EHfAdKlARX/vvwP7k3jh\nD6BpJIEWFo6LGf8HkkxiIvJOSuOezkEcVhTNU1US9SOOlxqMWMw8STRAVnIKSKIDfhj6VILUybqY\nxDEhXVJTE2No/NhQEieFf4V5u4bpnZE4rHkk8WiEvjSN9Ro0aAjHH/9TzjpLKs1cddUVnHpqkuLY\nMNoDFpO1/hg+aBBzX3mF24AjSUaznSku3x6Xg4/zq5ZRPFrrqEhUCtXaAAAgAElEQVS0zUskRYzV\nT2E0UkNLUxNdELaJR+10FsF03JVa3yYDK6J1tP8NiP/CQaEv22yxBa++/Tabdu5MQ7BglAAul+OT\nFSssSZBBSYjVUt+RdF7iOcgdF4rjt/SJQeO3hlCcFznOtKnKKw/c/te/sv/++9u114GwmCyj3XPk\nkUdRWdmTysqe/OQnmpShHrkVj6fYWUWX6W19C4odWi4gGdoUh2QbLJAMbw8iw+BBJILkZRIngDiC\noI7ijIG1JMkzNP7qqRaOUIdfh7gf7kzyr3ZJdFxZ/34aJ6aFk9VhpgERVyPC9PCwn3nAOOBbiLja\nJWxfTnGsV5558+Ywduzp1Na+RG3tS4wdezrXXTfVChsbxkbK4888gwd+FL4PRJyPtYLgQKAPScXC\n+CFRXxMpOv9kZJRUwaRFjPXBtQR4LWxTQEbEMpK4ls1JamANQh5G047jk8LfCxER90Bo71aSeKsc\nyWhfAby/aBHV1dVceuWVjU7jc4G6hgYb/wwA6r1vfNLwFMf6ae22cpLYQ3VNbaA4AYYjcSUsISl0\nHAuseuCQQw6ha6dOnH7qqeZKuKGyOlMXULImprH18aGDuGMYTVm2bFkTV75vf/vw4ELXObi5qSvd\nvDBPXeVil8LzIte9eWGeuvnFbnyx+138iV0GO0ffKzLWP9+LO2E+2ues1H6+HbnplYe/Yxrd9eSv\nujfqdp3DuhXho33R43HRenEf1Y3y4uiclYZ+6vL4GDqHdTtltFPm8/kKn89X+KlTp7f15WEYnnXg\nLtiW962Odn869MADG92gCC5RC8DvF1z/0q566jqVB79v+Ns5uBDmw/bDI7e90si1Sl0L065+aVdA\nMtwEdd488LNIXBN1eWlGW+qGqO5am3Xp4leuXOk7lZT4BVE7N06Z0tY/g9GOKAvXVmm43hZE11Au\ndY0Bfrvo+tPr/uKwrV77naJl+r+W/vTfbjv/4osvtvXhGy2wpven1boLOufeBO4A/sd7P28da7y1\noiO5YxjF1NTUUFnZkzgRcGmp54ILJnLeeeeRvCudiDiCaJnLuch7zyHIe6B5SMKJySTWmgnAoSSp\n3wvIe6hc0f6KiwpPDOtdFpZr3auZwJ4kObQI25yBVNHwFJfA1PdfGvqq5Ti174S+a0nPtPNLWej/\nZMRKptkVJ5Gkf1cXQHUrLIv6AIlb5IMZ+/AkljN9lzY+tC/tlpQMZunSj6y+ltGmrAt3wba8b3W0\n+1N1dTW9q6rIAT8DfkUycvQnO426jlglyIhWRnE9IR0RtZy8ZmB7KdXOfcDBNB2p9kNGsdhNUPsS\n19MitF8BHAdMpXik15LyDtgEcSvss8UWnHXuuZwxdmzjnaME+HTlShv3jEZyzhVlxoyvO4849A+K\n5pUC/w7T+Wg9/R6ngtcUXyXR9vrEoNO/vOkmRo4cybBhw9bJ8Rjrhi/DXXAYUtT9V865Z51zxzvn\nuq11D42Nmm7dunH44UeQGOLH45zjlFN+Ti5XgsRIAUU5oOoRQbUbSZa9wUiiXk/i6ncJiThRxxF1\nv4vxiLACETVXhnnnROveQXFdrvnIcHh1+DsTGVbPJxE66oBSjyQn1r7rvuqAfTPOSgMy7E5EHhl2\nD/0uQ9wZPwzr7BydN01mXBfO00vhGNQtMgd8HLbVajKzkJT0DUh6+DizI9TX17PZZlvQtWsPpk27\nOaOfhtFhsPtWK+nVqxfDhgwBxDUwds0bSuI2NZhit0FI0qmnawUR1jmAxN2vNmP5mNT+JiIPr4+E\ndbRk+1CgE4nz9HySYhv50K9TorbkzpLQACwP0+8tWsRX99mn6M7x/9k78zC7qirt/84dqioFCRiT\nMCWoTEnIQGQUQQ2IEAYBGRpQsP0++0MbQcIgRBJMokkkDFKhCRrbtruxuwFBmkFFVCAtoEIYMpAi\nAtG2E4FOMVUFsG5q2N8fa6+71zn3VkglldSQ/T7Pee695+yzz77nnrv3Xnu9610dpOOEIyI6naMd\nyps+d6pLvHdmn/4H8v74h8151f4fvydoH6sBlycodn75y1/m4A9/mJok4eGHH94aXzFiW6A7bi8k\nXvUvyILQvwL7dOf8ntroZ3SMiErccMONrlAYlKKpNTTc7GluSrGztDZV26s1n4/3r42evqcUuayK\noKXP1fjz6lygHw5yMMm/bzTnZFX77PVVxVCpfPWZ6zVWufaeDr7ur6sUQW1DrSmn9dh9Wu4xc61Z\nrvJ7zjL1Wjqjvj/G1FmbKRPanc/XRQXCiF4BPUAXdOnxYpuOW/1xfFLVPVUPzPlNaVOqQpil/EFQ\nIswqrg3yx5QymK9SRvfvT6ApzjHl6ghqb3UEmmIjafU3pSnO8fVpeUthTMDt6N+P32+/CmrhZ046\nqbd/hog+CKtkmX3eutpX4/ctNf8jSyWsNefV+3363B7mn1X9D2IohuvWrevt27Hdo7vj06YMGAXg\nFOAeZCn8UkR94Azghe5crKe2/jiIRVQiKyXe3Nzs8nk1sFS63BpN1YyKbPxU3hgOtpzut/FQGqPU\naOpW2fQ6F4w93a9lbNvUSLP7ssbNNH+Ngjl/kG9T3omBaCXeqxlrdU5k4XO+nqX+mJW/z5t6soZf\ntk36XQoOjjP3uN5JvFverVu3Lsq9R2xz9ISR1ZvjVn8dnz57xhnlSeMcY9DYCWTWsElMuROMobTa\nGEhW0jpP2pgqEGKvao1RlI15sfFZQ7qY4OLbN4tgFHY1AdbradtO9a83Xn99b/8MEX0QedKG0qnm\nmYO0YbU6c0z3fyFTvkhIg6BpDvT5z/tnXhcY9LwCuL1HjXIPPfRQb9+S7RbdHZ82NSZrMfAD59xv\nM8f+wTl30UYr2Arob5z3iPfGLbd8n6lTL6GtTRn/GlM1icBaVuJJltlvJc+V1Q+B+ldAGNHVpNan\nI/FYHZn9Gl+lRJdOU182ukDFWfPAVIRSaOXUH0fSbe7nv8NKhP6o0vEax/UMcDdClVQ2eDbSwcZg\nad9rvyv+eh/3+5427cjGgRX9NQ/wn1cgJJufmjoTCoU8N9xwHV/60t8BxLiFiK2KHozJWkwvjFv9\neXyaP3cuV8+YQREhE99KkFn/BpWJMmwMiaNSffB5f3w0If5Ee1IbIZpkzsvGaJHZvzchzgsCLQsC\nobxa5OuvCAmLjzzsMH73xBM87euZ6NvYHGOzIqoglyTkkBF1MGH2obMER2XsIshzp3rDy5DnTLV/\nFfps34aM/phztZ4aAvVQlQp/+dBDHH10tRCEiK2F7o5Pm2JkHemce+y99m1L9OdBLKISpVKJwYOH\n0tb2FBJTZYfrdqT7UaNkJkEQQ9nM7X7/OaTDnb+ChELXIgZENSMrIQz7un8slV2mXk8NouzwPR4R\n44D09CI7TdCphJ0CjCN0pdqeIpIP7Gd+f87Ur5EST/vv46g0MvX+2evaNqvAxzJfBwRhWv2OHanP\n+XyOXC5HQ8ONXHCBSu9HRPQsesjI6rVxq7+PT8d/6lP8+te/Li/n2N5RA/11kqeSPna5qwC0EkQr\nbB6sY5B4KxvtCqHXbkcmk3r3tFfXHrhIWrJHy80CTkMmsO3AaqT3/LM/fiLSk2odauzp5FeNO4Cm\n5maGDInhexFplEolhtTVlZc/24Enkef1AILxA/I8n0YwmPR5W0nIBPoikngF5JlcRtdZQoGUvBaE\nTJ8J8PCjj3LkkUdu+ZeMeE9sDeGLm6rs+4dNb1JERHeRQxLo/s7sO4+QIUWH407E07PK7x+PDL86\nPfguwQgbg3SFgwhh1hAMlJlmf7UJkoZXF3w7tKwKa7xICIF1yNrteEJod+LfqyKgokTwoum5y/33\n+hkixrGEtJ5WFvnM59+SFuxwwG6mzXlghi87wb+u8tfMesYmI0OJo6NjJW1tK5g69ZKYVyairyOO\nW5uJB371q3Igvk24CrLM04H0wB1VznUEgYsE6QG/ifR6RcTA0gD/alARDdVltdI81iCa59/bNmh+\nrDwiuHGzL5tHUthD6LnVGNQlr1XIspgDzv/CF7poXcT2jNraWq694QY2IM8/wOGEDJr6n+kA/g15\nRnUE1uXZcYTZyKcRLWT1hE2kMu9cwdShs4gOc6zdnzP5Yx+jmCQ89liv+T4iukCXnqwkSQ4HPgpc\nAnyH0NcOBj7jnDug6onbAP19pTCiEkoX7OhwONeJc2pUfAoheRQRosfPqE4gsbS9/ZHpgB4bjTCH\nJhOMLhACzHwCJU9JLSoPP5ewbjqPIL9+FaJsqGtJY5A1KuuZ0jVTSK/3qgy7esvsmnAJ6WqXE6Ta\ns+Uh7cGb7tupa7HaZasHENKisUmmDh0e7PrZEtKECC0n9eXz43jnnbfKlBo1uCLFJqInsCWerL4w\nbg2U8WlwoUBrRwc1hKSrkPZuYV6fRAwd7Ym0h7IeqzGk6YK2zt0RdRJbZzWPlvZIJwEPEJaf7DW0\njhrEq6Y9o7ZJl+gS0hL12nO/Eb1ZEV3gc2eeyX/cdVcqvYAuzTrSHqauqLUbCM+j/l8eQZY+HzfX\nKhJGZisXb6m1uvDQTlAm/M0TT3DooYf2zBeOSKEnPVk1yMCU9687+q0FCR6OiOgxXHDB+axf/wbv\nvvsmf/1rM9dco/mvricMjT9FupE/+E3XStU7A9LFPZepXYdbfJ0v+u1axFOkHh6b5+pvfNnfIo5/\n24XO8eX+gBhHK30bx5t6XkDinaqt90Kg613mP49FPG26prUfQq45mDA1WeLb24FMBaYjHj415pTe\n9xzBM2e9e78nGEz6fTqBKxBDTNt+OGJkQugicqiYsnMJLS0tlEol5s+/nvr6naLse0RfQRy3egjr\n29vLEanPI3mq2gi+//cRjJUTSEdyau/yxUydKgGfID3X477ONsTA0lX7gt9X5+uxHi2dUP4SWQ7b\nO3ONoinzNmFyu5KQ6EKXtzROTCXqtf3RmxXRFf79zju59957K/bXIc+2Gjr6XI0neEuVVwISpW1j\nrnYD/gl5Js8kLJXa2YmmLrAxjSf5V12uLSHxhnVJQmNjn0htu11jU2KyPuCc+/NGC21jDJSVwoiu\nccst3+fCCy/GOV231KTAWdEJTXWpMUmjSUcNQDqNoIpg6PnW2BgLvEQgmaiHCipDu/OmHuuVOgrx\nvGXju0CiBB40bbOO/6zwhnrlNMdVJ3AxknJzIpKuU3NnnIhMcbSchubuTyAY5MxxyyrvNGU6gceA\noYjBNwX4BXA5kktssTmWjfsaS6HwIm+//Wb0aEVsEXooJqvXxq2BNj7VJknK+6SyRCAGjmb0y/Ys\nSqnSVf1qcVy1SAJXPTe78q/UQr2bexC8XfjylwH3Eya4Gq/V6c97hpCeXq/bCewErPfvdxk2jKbX\nXivHa7UDr0dvVkQXWLt2LXuPGlV+3pUmu5hAzD8cCXjQkTzr9dIZhT7fWa+tzmQgjN7V4rZ0ZqRL\nxJ2E/xXI/+rR6NnqMfSYJytJkgX+7c1Jktyf2e7b4pZGRHSBUqnE1KmX4NxKYBmFQo4bbrAeLbu2\no6HQFtp1XUl6WqDrSOpx0mF4NhKr9SJibCjTeWXmvOmELrED6QZH+2tqTNOvfLuycV+diFKirk9p\n3bpWbL+D1c1S+l8eEfHQ7O+/RqYWDwI/J3SzOWRKocadruM6xJPlSCcvfgrp1jUN4tH+GgV/jQJi\nYIHQLfU7TCOsz80Enqe9vZ1Fi35ARERvIY5bPY+Sc7zPGxuNSA+jvdscZEW+RGXPonFPOpnMxnEV\nCVQ+7f3GID2qkp1f8Pu1V7beLocYeT/z5ZSGNRtZdqpFerVDkBgtbbMeW2/a8vJrrwFCSNdlrb/7\n/Oe7fa8itg+MHDmSXUaMKEtsTUeemStNmd8ho6nOMvT50yVhHf31v6EaxrMJcYMvAl8lLDhk47Z0\n8SJPMLD+jRDYoPUfedhh5JKERYsW9eRtiNgEbCwm62Dn3FNJkkyudtw5t3grtmujGGgrhRFpBLVB\nWa8pFiewfv0blEolzj778zzwwH0Euh4I0cOGhIIMqw8iXVI2KkANpax3SwVU9Vj2POsFyyoCWjXB\nyxDDpMbUO8sfVzpioynfCVyNxIepZ07Xe5XE0oHQBx/xZRKzOYR48wnEi6XxXPcDJyPeqSMQuuFH\nSK8lL0HW3FTi/iBfh+ar/zpC2fwNIguvURZ6v9Nra8XiBF577ZW4Ahyx2djCmKxeH7cG6vg0YsgQ\n3lovpskgJLOz9sD7kV6tVx+6LvFoT6vLQFmPUydwF3A66Tip2zJlsvshra26rz9f9WQhxHFpj549\nZiWFsh6H16I3K6ILNDU1sfuIEYA8cxOQaOoEWXacjYzUc5D/wSyqP3+6IHEC8DrwKOE/oKPrVUjk\ntRpPUJnuQCOv8WWWEjgnhyNLrNrWtevWMXz48B64C9sfuj0+dSepVl/ZpNkRAxkLFy5yxWK9Kxbr\n3cKFi1Kfp0w52VUmG85V2Vdwkqy31kly3lq/XxMN27KaEHip3+pcZQJfrb8xc606FxIN1/nraJLi\npf5zvd9snbZeTShccJXfo9G81+/1tcx313M1mbKWqzHX1fthkyxrEmKbTHmWOd+2seCv9VH/+WR/\nfiHV3kJhkFuw4ObefoQi+il8/97r48zmbgN5fNpvr71cAVwj6eSsc8B9mJD0t87vqzdl9JhumtS1\nJnNME78OIp1wGNJJhW3i1xwhsWsuc7yekAi5aI41+rqGEpLHZutds2ZNb9/yiD6MQyZOdDlwT/pn\nT5+vrxOSChf9/0H/C9n/jX1G8Z938+X0P2GTgNf6ctWe8zrzXNuk3fq/+Yl51vf90Ifi870Z6O74\ntDFP1oqqB8q2mZu4yZZcD2OgrhRGpGFlwq1nK58fR0eHavg40vmc7DqkKvNZTSul3mVjoNTZrs+V\nxi/NQDxMqq9ls6pk15A0rFud+zZmaSZBH2sJcCCynmtzXz1F8CDpelXWS2aVBXcHXjbXqCGsDx+F\nMMQfRuKoDkTWslT/y0Y6ZL+P0hw1IfQBpPOTabvs+fp6NSIaMpGGhgYuvvgrKKIKYcSmYAs9Wb0+\nbg308UlVB1UR7ZMEit0ShJ7nSEfPjkd6DvVsqT9fe2Tbu6gYgKqv2V7WyrtXy2JYR+gBIa1Jq9fT\nuvUXyiZ8tSPA3Guu4fIrLQksIiKNTx93HL/45S8rRtApCOFeR0wbNa45tXRfVn3wMeAwKHu5usop\nZ1MsJIheMoTnP0G8zr8jeLU0QEFnK7vtuiv//corm/39tzf0pLrgp/32gN8+C3wOCQB5YEsaGRGx\nKaitra0yIb/NG1ggggzatT1HWm2wgBhYIEPt0/74dIIRM5YQ2/UbSMUYaXd0DSEXlxonyxFmv7Ks\ntXt8hhCRcLmpbxUyhSj58+8hGHo/8vs7gf8gGGefN/VO8JsagtqelxGlahUEUVKBQ6Y/DomjOgDp\nVu/x9Sl5Zhmh687CZrJxvv0rCNpfGh5+HGlRkLmIQZdwySWX0dLSAoiQyeDBQ6MKYcTWRhy3tjLW\nt7dz5bRpOGQpx8q5Dyb0KNnYERtBmwc+RFi6sr2LxnLpEtUYpPe7yn9Wep/NVKh1bkB6712QXq6E\nGFg2jktJ5asy16sx9auhddW0aSy8qVrKtYgIwV33SahnIbNfo7NrCNq8EOKnoDIGcRXy/H0EGALU\nI9Rb/R/obCOPLCiowaSLE7MQA8s+2+8gsVwdyLKrtnVXX+9fXn2V+lyO1atXb9F9iOgC7+XqApZW\n2fdsd9xlPb1JsyO2JyxcuMgVCoOqUOnynpL3aUOJsxQ3pcJZit8sf17ewTRfVmlzjZ42l6XrNVYp\n0+hghrmOUvVqXKApZumL2j6l52UpiXMy5S2NMEslVEqifq4352QpgErrwwnlL++ENqjUQqVg6vs5\n5vP4zHX1Og9n2mlpkEI5LBQGuTlzrnHFYrinxWK9a25u7u1HKqKPgm7SMaptvTlubS/jU2trq3vf\noEEu7ylKlhY4CNyYzL46Q20qUBZUK1OqLO1JKU/vM/UpHUopV3lwSRWKH77cUCqphfVU0gL1ekVf\nX85TsvR4XT7vWltbe/t2R/Rh3LxgQYoGqFQ/+1zmCVRa3Z/LPI+WcpgHd4h/PpeC29WXz/s66qrU\nn322i+Bm+TqUelhrnnf9Dyb+/KH19b19K/s8ujs+bYqE+zLgK865x/znI4CFzrlJGz1xC5AkyRSg\nATHYf+Ccm5857t6r3REDD01NTYwYsQdpp7ylrc1Eclp9mKBHZVX7rMdF10NVIEOhxBebnlI9Z+pJ\nUkn0Zf5aedKhrNnrFZFcVHN92XZkfeu3pIUoJvjyTyPeoGcQL9Qj/vjHfF26ZqZrxfZ+XInQG1XI\ndQXpMHFtl3qiLOHAUioT3+YORPhCz4HgAD8GyVaj7bGCGkrMeZpAIPpD+XihUGDBggYuuOB8IiIs\nekjCfauNW3F8SmPPXXbh5XXryCHSOw+TTqCh0kPZ3shRvVeZ6V9tj6XcA0sf3I9K6Xcrj62eMO2t\nrdiGltHrnWPO7ahSZxTAiNgYSqUSO++wA3R08IzfNxHR4P0/yCxCR/NOgmqmirIoNyRLOdTZigYM\n7ONfs/8FnTmUSP/3IDz3lo77MYSSaDtZpdHmgRfXrGHkyJGbcScGPnpc+AKRG1sO/Nlvy4ADu2PJ\ndWdDfuOXgA8iz8dSYGymTE8ZpRH9CK2trS6XG+Q9KerVsl6nQcazVO9EHEK9LL9w8JhfuanmDatx\nwaOlHqOiqW91xrtjvUPZNlghiIITT1vWk1bjgmCGeq/UQ6TX/5rxOhW8R0mFK1RcQ4Ut1Cs2KONV\nanRpb9cg00b1zI0z17Xttvvsd5/l99WY+moy17Bl6/2r1ifft1isd62treUtIsK5HvNkbZVxK45P\n1XHisceWV9CXEoQmGs2KuhWtsKIYugKfy5TRlX0riGFX6a3nICskoGIYOXAf8a8qIDAncx3dTjWr\n+zW+bD24uiRx69at6+1bHNHHcXNDQ8WznX0uBxE8sHXmmVMvalceVvznA81/Rv8P9eaadeb/pJ6z\nrHCGPvs14KaQ9gB/yNT/wd126+1b2ifR3fGpO4PLTsBO3al8czZEbfIX5vM0YFqmTA/ftoj+AqUN\n5vN1LpdT1b4sJc9+tgbHqcawsMaEGjFZY2SGMXiyNMJB3gCqyxgV1dQB1bhQQ6SxinFUMPVkFQCL\nmXpmuGCg1bpAZ1QKY525nlVFVENOjbSsQVbrxCA8MXNdNZTsd1/axfcc5CqVG2e5tJEWjKzrr78x\npSIZEdETRpYLY0WPjltxfOoaZ512Wsp4qc0YM/sQqE466bP0qBpwexIoT40EmmC9Maow5ef4MtA1\nPWsPAl3KGn11BHrgUr8/b+rKGmHnnXVWb9/iiD6O6+fPTxlKg8xzOIhAdy0gioRZ48cqYNoFA8Dt\nkjHCipnntJa00ZYnLDR0RcfNIbTavKmnhkBL3P39748KhBl0d3zamLrgec65HyVJcpms/odD/iLf\n2aiLbDORJMkZwHHOuf/nP58LHOacu8iUcV21O2LgQ1Xq/umf/pWLLppKZ2c7+Xyek046iXvvvZdK\nqp9+1sTBJyHh0EpWcYRQa82DpWp/k0hnebEO+k6zOSSn1GcRUoBS6DoRJ/5XgH/05arlgH8EUQE8\nyO97zhxzhOTEqlyoQhff9PsdgfiibdNrzSStDOgI+eMPylxL2zYdUQm0mkSrqpRTBcKJhG4i+90q\nv28ul6OzU7/PbOCccj60qD64fWML1QW36rgVx6eNo6WlhdEf+ACvv/UWq4AbgFsQl98q4EJEcQ0q\nex+b50d75mo9idL/cqQVDC1R+0Skh8+Tziqo0J7S0guV3K2fq+nVRtpgxMagtMGVXpxrtDm2sRFU\n94HMHNrNee8D3iTMNJ5AEoDb/4MKaWh9lxEUNTUAois6rs4SRgM/Jah1aq6uTmCPESP48//+7ybf\nh4GM7o5PWUEUi3r/Opgqg9VmtG1TsUl1z5o1q/x+8uTJTJ48eSs1J6KvQSfhF1xwPl/84t+Wja5h\nw3ZDjAPtri4GFvj3txGG2V8QmNBqvGgXZru6g/17+0jqca3Liv/+H38dre9rSHxUDplaqJaW1RdS\nTCaoH86nElcRpgVPIX9LVRxUqfvZftMuVY3Dc5BYtYmkpxvnkO7O9Xsch8SPadvbkFgvVW2c6a8z\nDlFo1GmJRkGM9mWLvuwsskKmnZ02EmMOcBJtbRtYsOAfuPjii6KhtR1h8eLFLF68uKeq29rjVhyf\nNoIhQ4bwyptvstfuuzPGy0IXkX+59pxXAgsJvZFFkRA3Mgr4izlmJ5L4Mq3muCa2AJlgnoj09Nrj\nqaZqAen5tM4SlCNn7XKUJi+2+PzZZ3PPz3/+HnchYntFbW0t13/nO4y5+GIKpA0mm/S6iCwo6IxD\nn73Zfv+BSDoEEAPrREQeNQd81O/Pkf6PaBqD9QRFTQiKhDsiCcRnUWnw5YDVhCVVTZ+gUeivrFvH\nkNpa1jY1bXeLDFs8PnXH7bUtNkQJwNIxvg5cmSmzJd6+iAGI1tZWr2CnMUh7uhBrVY3Cpwl8bbyU\njVOyFDyNobLxW9P8e01wPMcFup9V9bOUPU1WnC1/tQuxV1mKoI3X0nba5MSTTNmJme+bfT2+yn24\n2rRjVuYaluJXk7l2vaukXmqsnN5bW7auSl3V4+Ly+bqYzHg7Bt2kY2zLLY5Pm441a9a4ofX1ZVqT\nxkUpnSlHOq5qEJXxUqpCaGl7li5llQv12CWGdlVDJS2xYK6n9KqEytiVQqb+Or/vrM98prdvbUQf\nRmtrq6vL5ysScleLoSr4Z09prPUExcFhSFLiPOl4wkGkaYJZ+mA2dtFeO8fGY7/02hdl6jzK/E+O\nmTy5t29xr6K749OmqAvuBVyEBPqq58s5507efNNuo9fTHG2fRBIBPQmc45x73pRx79XuiO0Pt9zy\nfaZOvYT29k6c68DHuhM0d7KOeUUBWedcimhgqXcGxLN0LcusE6AAACAASURBVEJKKRHog1kCijP7\nLYllNLJOpaQYTcuZmPJ5//oM8DYS9nEEoj4YFPnCGpN64S5HvE3ZpMpjEKU/m6xZ25fL1HklcAai\nAKhKjO3I3+5wRB1QEzor8aDG35dZpNfExhM8gtpOEAXHB/z+Fcha3SGZdi8heOeeAg6goeHGVDLj\niO0DPaQuuFXGrTg+dR+rV6/mIwcdxJvNzXQi/m/tnZYQ9Fkh9Ko2/breSdWKzSqqbSBQpqxqm/Z2\nyxBOworMMahO18p6AFSZUP307UTaYMTGcf211/L1K6+soLMq1VXJ/lcTRnUdZbW8QxQ09ZnW0Vk7\nRk3M/WKmfkh7YHNAo38/AfgrYcYBgTprZz2Jb087MgNQVUQ769le/wPdHZ82xchaDvwAmSVq3+Sc\nc/+12a18r0YlyfEEidx/cs59O3M8DmIRVVEqlSiVSgwbthttbVYw2LKFHJXxVRsINLyxhO5KySl2\n6N0FeAXpKv8LMYyOJqS1dKTjwKyRNY5gZBUJw7Y655VcoG20sF1gATGQ5lIZ23UUlVML7UJtvcch\n8vVqFD1vymqXqgKw3zTXVyQI+/v6zH773bUenfKsQLrv/UnHuum11cg6mELB8fbbb0bq4HaGHjKy\nttq4FcenzUN9krCBdE+nvZGNjrVxUNobTCQkYbVy7HNJE561l8kRlpa0fttLanRqjjBJ1Z5Ze3yb\nKCMhTSX81pw5XDl9+ubeiogBjlKpxJC6utRMQJ87NXDUaMd/1ufbllejDFOu2nNcRP4rdxIWEXS0\nt8vLdtS11+5qRuQISVjakATIv/efAc484wz+/c47N+2mDBBsDQn3J7vjGtsWmzQ7IqJrLFy4yNMH\nCw4u91S0xxw82QXNreApbXUuJAVWyp+q+uXN53pTppCp84AMNS6bcHhG5vqDTLmsXLomEM7786xU\netHBCS7Q/U723y+rhqgUwOx30vYkrlJZMSvnrnXOMm3T7TgX6IHV1B6zCokqX593cIFLJ0JW1cU5\nZYn3iO0LdJOOUW3rzXErjk9dY9rll6coe1bVbKmnSGUV1rIKhFYBMEuLUrpTktlvaYkjqKQOKt3w\nVFN3VkI+qwR3c0NDb9/OiD6MRQsXurokST27+p6NUPqy+/L+8+5VjhfMZhUNB5nr5DdS/wf9f6Ua\nhdBSfPV/Z/8vSlucM2tWb9/qbYrujk+b4sk6D9gbWfLWCHucc890edJWRlwpjNgU3HTTQqZOvQzn\n1JuSA2ZQ6dnSRYknkZALXftUT5hV8NPyVyFUvawOTyPyNxlHUCy0CoR5QgJg9TKNJ6y7ViO3ONMm\nR1hvGuvr13UwhV2b0nUwTYBsr6lEAC2r0O+53L9OJL3+vCpThyZ/Xg78GFlf1u9doFIpMUuVBHgW\nWTtTsZGEs846m9tvv5WI7Qs95MnqtXErjk8bR6lU4pCJE3nuhRcoID/QyZgfCVkx/6t/n11hL5n9\njkCnsv73BBgB3I0Qrw8DHvflLeVQ1d/018oB9wOfJvTETyE9XCdpL0ICtLS2Rk97RJdoampi9xEj\nWE6adN9J+jnM7gcRu7gBoQw6xOOapfR9A/Guqtep019npanXr9LSUeWa+n+xz7/WraOzQ0b9PRH+\njorCgMwo2oDR++zDcy+qT3hgY2vQBa8BzkMSMJYFUpxzR21uI7cUcRCLeC+USiUGDx7qKYNgY32C\n1hRIt/IJhPanBsB0xFDQmC5rdEHaWIDKHO0JEof0SwIV8FLEKFOywEzSsuqQNj5sncsIXbQSYpSW\nqN3p/v47abzVaIJhpN1ktl79nh2+fqhUG7RUv6WkDUB7Ty32JxhWRSTWDF/Ofhe9Vx2I0fpZX38n\n8HuKxY9GSfftED1kZPXauBXHp01DU1MTI0eMKE/wlEpleyxI053G+/0aRdvmy9YhP7IlHZcIdKsX\ngX9BdEy1PiWSQ7qHfAmRln+b0GPeRohAVaribOAv69YxfPjwLb8ZEQMSLS0tDNtpp4oZAqTpghOQ\nJUqlDIIsHlgpdpDnT5951Ua+ivRMohr5XmOq9L8FIc1BdgkYwvKoXYxwyMi9ghCvWE8w8PLAmu3g\n/9Dd8Sn33kU4E/iQc+4TzrmjdNv8JkZE9B6KxSLNzU00N7/B/Pnzke5BDSwQ42iuf6+RANXwFMEr\nVa6dsJ50I2JcqJGyAOkSE4JEuoq4qsFXQLpalaHX9dK7zTW0O/wv0t4nKxALwcNVIkwf8HWO89eY\nQzAgf4cYRo4QDr7Kv3+K0MVe5esY6+u1Bpaeo2G2HX47gGDcKgqIMBvIfbwWERU5lhAaHBGx2Yjj\nVh/H8OHDKTnHLx56iDZC79lG4AfkgWFIjzOa4EfXnkp74BIhxxaEZaGiLzMW6e1m+vKjESNJeyzl\nIhR92XeQlXvnrz2XsOL/FCIU4IB//ed/7tmbEjGgMGTIEE495ZTyaH6839+JPOPtyAj5HMGAV0Nn\nP4IU+ypz3ksEb9cGxMBaYcp0APv6612FjNrKndkA7OHr0TQHKjWv17aeLQjJb3LI/2wfwjLvBn/s\nJEI+rYMnTNiMOzWA8V58QuAeYJfucBC39ibNjojYOBYuXOTyeZUOF2nwhQsXlY+3tra6QmGQExn3\nWh9vNMjHCh3jrKx4ZVyVSsVrjJLGaNkYLpVYz7t0zFO9v2bBwT5OYqI0zsvGQS3NxDZpHR807dhY\n7Jf9PMfUe7VLS8wXfd1zzGcbV7U0U5d+H5W5z56jMVdafoavQ88tuhC3ZuPAan37ci5JalK/VcT2\nA7rJea+29ea4FcenzcMJxxxTjhuBtIR60kUcyyxCPJUtVy1eC3C7+NiSnavEoGRlrOvBTcrUdbKJ\nSdHr3rxgQW/fuog+jHXr1rk8uBmEWKkiuL0Ck69qrFU2TkrjqvY1z2u1OKucqVNjwTSuEf/5WH9u\nbRfX0Pgr++yfauosEGTn9X9n69hzl116+7ZvNXR3fNoUuuB/IUv6Swh0aOe2koT7piDSMSI2Fao2\nCJIoMEs9U9n3tjZdkykAxxDSWKqH6KfI+uZZBI9MVrGwAEwhOPhHI/S9Kb6+LGlACQN5ZO3pD6a+\nrJBxB0KKEeW9dGzV75AUharDNRURPysSJNi13MG8Nx3ReujazT7r1VNxZBByjQosO/Peqjvqd3rS\nvz8Y8VY95T9XEhrOOONM7rzz34nYvtBDdMFeG7fi+LT5aGlp4QO77cY7775b9vFrQtQC8HHgN6a8\nRnxq5Ky9620IwVn1Ym1PfRjwBJUy1tmo0f9CEmU8jfSYJYSCVUMgRE8oFnlj/fpIa47oEodOmsTS\nZcsq4qGgeqxUG0Ke/zHhGbVJUUYD91KpiKmR0JhX5aq8D0lsrPs+ivyXsoqGavlpXTmkE80mXekE\nvgJ8l/DfWoxoG3cA40aPZvkqPWPgYGvEZE2utt85t7hbLetBxEEsoifR0tLC0KG70NGhubVqEWe9\nilnosIvf/zxwBUIB1DDQBBmKP0owgPbz+2sQdvU1SHd6GUJAKRKodZo/yz7X2j3az9mYrSB5HtjX\nShXU7lsjCDoRssArdG1kOd+W5/z3n+bbDcF40vd6X9TYXEYQr1ADKivi8QlEXGQ+Qlb4qT820d+L\njlTbrr/+Wi688O8B4iRmO0EPGVmTq+3fFuNWHJ+2HKtXr+a4T36SP//5z0Bavl17ZO3lliHLPF1F\nzWpZu2Slk8dzgX8z1622tOWQ3kwnrTsDb5HuQbdHKeuITUdTUxN7jBhRYaToc2hjpXKk4xHbkOfP\nilnoPk1VoHVls4E6QlZNSMdYqRQW5tq62DAa2A14la5zyun/UNtm/3PLkJnIuLFjebZR5zgDAz1u\nZPVFxEEsoqdxyy3f56KLptLZqfFL6pm6Evg2Ia7Jrn2ehhgHur+aaIXtdiYREh5rCLeujx5gzsuu\nu1pDz6YZhLQRlvWq2W55CvAQ0j0fD/yadORDO5XruVlNJE1k/CPESNT7Mw8xOuebNulQkb0feo9O\nQBIUa/ffATyGaIGF8kmSkMvlSJKEBQsauOCC81OeyYiBh54wsnoTcXzqOTQ1NTH2Qx+i5Z13yj2h\n9s46qVRkE7/apaM24GHgA0jPC8FH32HqGETwUNnMgpCOnL0cyQ5YRHq+OcDr22ly1oj3RktLC8N3\n2imVe02NowLyjOpzdyqBC6PPedbbpP8DHaH3o7pHzD7bWofllqhxpsf/UOV4kTBT0E75RP+q7RwG\nNBO4NO8H3vDtn3Lssdz/4IMbv0H9CFsjT9bbwHq/lZD73tIdTmJPb9LsiIieRWtrq1u3bp3Pr5XN\nEaUxRTZWSeOLNIdUnYOTzD6NzZriy2p5jd/SWCYb09RY5Tp67eN82YKTOC5cyE+1NHONbB3ZPFhL\nXciHlfjzsnnDbGyZvs5wEjulbdUytb6OnH9N/GZjuU71dTf68tW+56mmvOYsG+Sg3uVyg1xDw80u\nn6+riK+LGDigm5z3altvjltxfOp5vPTSS27fD32oaswJhFw+Ng5FY0Tsfs2xpTmwbPkaU1ZjXeb4\n+BfdlyPk9CogMWF6vBB/94iN4LNnnFGOcdLnbFCSuBr/7EA6xqrR77f5qTSXm30ms7FS+v5A816v\nWS1WUeOrjuri+GD/vGvsVd58tuWGZv5TO5hjH9h1196+/T2G7o5P3fJkJUmSQ1JafMQ5N22TT+xh\nxJXCiK2FSun30cj6zeOkvSzjCOtEGmukVMHX/fsaAq1OYal8uob0dYSSp16lNGVOrv1RhFqnGVyU\nlmeFYPHH/hn4DkEDSEkvts4CojA4yx8r+uu3EyiC04DrCJERMxBvV460BP10/17boYs8jjT5Qc87\nDaE5ZgkIzpz3NBJNkV2TtqzzPM3N/1s11i6i/6KnPVnbetyK49PWQ1NTEx/cdVfe7ewsk7m1B7RJ\nOVQxzZHO7DfG1NUGrDb7tUe28S1Z75iFo7qfvj3+9hFd4Jp58/jG9OkVz8wHgf9BnrcNpEdXh3iY\n9vPnqIy6PV9zxU1A8svpTMJeZ1dgDWlvrUqzgzzvdUCrOU/5NhC4Oo7q1ESVkLf/qUXAl3z5ifvv\nzzMrlV3Tf7E1JNzLcM51OufuQbhHEREDDrW1tTQ03EixOIEk2R/5i5yIGDkJQUxYDaFVSLej+Z3G\nAof7slcQDAItq9Q8h0i5JwSDxiGy7yeSlnA/wrfj0/7zQUgYaoKIXKhxpPgcgVaoMvHO1KmEmW/6\nc2vN9TsReiQIIWYlQcp9DsFwmk0QjlUpfHs/lCJpCQn485RiWUCGhQmkyQg5xKAsYQ3IXE4NLL1O\nB+973wgGDx7KLbd8n4iIaojj1sDB8OHDeaejg5UrV7JDTQ0Fggx2HlkqUgrgBr/ZSU6RYHzlkN5w\nqT+WM8e1N2qrcq7WXy25RwdQSPot0zViK+OCCy8sv1+PPEs71tTw3/59qz9mR9cEOB8xpLLPpNIP\nP2b2ZQMKFH9BnuEOQhKWAjL666yk1bdDZwnZUV3/NzrC21lK0W9Hm2t+yZd/GljR2Mj8efO6ujUD\nFu9pZCVJcrrZzvRJHv/6XudFRPRXXHDB+axf/wZvvbWOYrGA5F1/ivRajkURYUdrXqinkb/WfL+/\nQCUc8CvCcP4dJE7pAOBBfzyPhGGv8nUsIR33tQrJx3UVsj51vD//EH+N6YSwWjV6liHrYpobbBXS\nnc9FutkT/fFO0tMIXRPOIbmsHEG0zXb7mH0/9u8T4Gum/bpPp0I6RXL+fq1CDEDNrTUJGMMpp5xa\ncZXOzidoa1vB1KmXlGO1IiLiuDWwsf/++/NWqcSzK1ey5x57pJITa4+nvZdOKicgPaX2uOr7Pgvp\nle5GOANqZKmkkT0XX79OnOxE833ISJADhu6wQ89/6Yh+jyFDhnD2WWcxFhmlc8CwESPIJ0k56jmb\n8RIknnAcYclSs12CPIP/i+SvUmkqHfH12ZyAeKlAhFuU27ISGf3VaHKIN20QYWS2OBcZxXW07iTN\nk1kFvIwsQ8/055QIS8LTp09n4YIFm3q7BgQ2RV3wXwizynbgv4F/dM6t26ot23ibIh0jYpsgSLzr\n8K3dXJ5KwQhd+1lJEIfIhprq2iuIwZNV33OIQXcXYqRZFcHfEpT7sufMQDxQjWZ/HvGMHUjwvJUQ\nT5Iafuq+V5XCgxD1w/mkJepVrGIe6QTEWkYJCtr1Ku1R1746M+UvRwxLFcfQNeLnqRQCGQNcTJLc\nDDics6G60v5icQLr178RaYMDAD2kLvgv9NK4FcenbY+mpiZOO+kkfvfkk6mJoQbta3IJm3xDVQQt\n8duqtGlPpZNfPS9L5dJzsqIDu++yC//96qs9+C0jBgLWrl3LXqNGpZ6Vb8yaxTdnzSon1la6qz5b\n6kXSpUmQZ3IWYXm0k3RqAaXwKQ2wGu3VSm3pbEbph59Flostx0Q9w1auqisJ+icRDo4GIzxHmK28\n3drab8fqqC4YEdHDKJVKfO97P+Dyy79Ge/sGZFh+nvSwDcFRb2O17HO6BOkGlS7XlZFV7f+rde2O\nSLCrp2sa0s1WixBQz9BBph418KYjXaUaf7ruZD+3IxTBoi8/x3y/bJSD9fJdDZxHiHSw7PAJSFcN\nQYD2aX9fNN9Wte9i6xFD8Ywz/oZ7770HgIaGG7nggvOr3LeI/oaoLhixuWhpaWH58uUc9TEhUKnf\n3/IPVAo+q+t6JqEnBumJHkWkrPcl9Lh2iWtfwvJRNWW3/7z3Xk4+uddSikb0QXRlZLW3t/OtOXPK\nxlIH8uz+wZTbByHS70swdrLS7jYmyi6RZp9NRzCWNN+cHtfYxBzBUNsRyRSqo7PKy6sUvL2WljkB\n4QGNQWYuTcjoP3qffXjuxRe7cdf6DnrMyEqS5B/Mx+zMzznnvrp5TdxyxEEsojegxtbXvnYFnZ2d\nzJ37LT73ubMZNWoUgbEP0u18CHgJ6Z6WI2STn1WpVeXOtTuDyu5Q6wChztlMMRphkBAEKLSe6YhH\nSrvUbN32b501bKxXTj9vQBIaH5Gppx1ZK7PX1/cq7Z41smYghpgN570M8cbZXFx6jy4GbsakAKVQ\ncLz++qtR+GKAYUuMrL4wbsXxqW/gvvvu4/RTTilT/7RXaSMYWvqAZGWNtFcrAEMROtY0JEo1O2Gt\nR6QsbeyF9ePXJAnvdFYjgUVsr9hn1Cj+Z+1aIPA8rrvhBi6/7LJyXqsfAv+XsBhwEPLs/hZ5VrPL\nl3YpEoLE1DiCZ0yjt3UZ+BgksUt25NcZhJXoKvo655IOELA0xwRQ00ll5RuRhYwORMrqHf/+umuu\n4bIrr+zGXesb6Ekj6wuEPmg28A3MjMw5969b1tTNRxzEInoTNk9TS0sLO+30Piq7O/XSQDqbBQTD\n6irEELHp/nIEw2Y00jXmkLXTajQ6m6PL0gHzSPdWQgwz7Qqz556AGH+dVY6rrpH9PINAJYSQ8aOa\nFpdSCK3xpSqF8/z90O+q3wGEBKEpEZ8iqAxaz+CJFIu/5LXXXom5aQYYttDI+gK9PG7F8alvYenS\npZx4zDGse/31clJjnWzqiny1CaudOOqv2YYowf3Ff9ZjjyNyRwpVe1OvwG+feIJDDz20x79bRP9E\nqVRicJ1ESZX1ivN5vnj++dzy3e+WBVx0dFcvqkZK63FFEZlNzCVESn+TMOra0TWHjPqzkFipLI32\nG/5c5Zs0IgZfA0GDGAK1ECoVBy8jnevL/uc6kJivdqClH9IGtwpdMEmSZ51zH96ilvUg4iAW0VdQ\nKpWoq9uJYORAGFptHneFlYDXbipBKHM/Rbo3K2WuVD1dP8oSBNQw6zDnZKcRDqEmHkTac/U7pJu1\nxJm8qWs3hJoI6UTFen4u86rhr9o23fcCwfizRlPWiMuZup7x7bHy7Z0EI+4AkiRPoZDjuuuu5ctf\n/rt+11lHVEdP0QV7a9yK41PfxNq1a/nbz36WRx99tLwSb3u7oimbI0S3arSqrsbngR2AFlOH9nr7\nZj6Pw+i7xmciwqDhhhu44vLLU0ujq156if332acsMXU08AjV453eTzoooJYgya4zj2oS63WIzKoa\nQaN9OV1mVWMOwuyhiAhmNFE5y7GLEToTyS7X7ooktmnz7Vzm959w/PHc8/Ofd/fW9Sq2qoR7RERE\nGrW1tSxceBNBEHgMotCnmj1Wut2qDFpRiCLiBZqHxHotIxhaHciCvF2P0ut8CjGknvbnaZhsuy8/\nlkC5q0WMNRU2nm7achsSG4Y/b4lvw2uEGKlzCJLqlyFqgfr9GgnrYeORaYkaenmkG5/ov+uhpOO4\nLL5KUDGc6O/jwYShpMZ/DzGmnPs9bW1XMHXqJWUZ91KpFFUGIyIiKjBy5Ege+s1veK25mdtuu60s\nZw3SS2l8ic1gaKG9GQg9UNEG7E3IPuj8+/0JE848UEwSTj/99J79UhH9Fn9/4YUUcjnGE3R0vzFt\nGmPHjCkbLQ9XOa8AfNy/V0GXA0hLskOl5m+OkPfqZ4SZyR8IMYe67Gtl29uQGcMbmfp0hM/qBWcV\nCUHycy0mLOcqpfDnDzxAS0tLlTMGEDYlYzHwbHcyHG/tTZodEdF30Nra6tasWeOSpMbBageNDor+\n/WoH9Q5m+X1FB1ebMjUOCpnyRX98tT+Wz2w1pq5BDub494nfavw16/x+rX+WaUfB1GGvO8ifq9eY\nZN7XOKj159Znziv4Ni/1n+f46xf8OXP8+yf9uaea6+tWb67d6LeCqa/ev681303akMvVuny+zhWL\n9W7hwkW9/UhEbCZ8/94T40SvjFtxfOo/uPfee91nzzrLFbzbPQ8u8a9Fv9WAK/jX1X6r8Vu2TAKu\n0b8Wwc0BV+/fF0w9ERHOOXfjDTe4onmuiuCeffbZ1DN4knnO5phyif9c9M+urSfv9yX++dNyeXDH\nZMrW++eyWj26r9afm33mT/XnTsuUr/H11pv/xnmmTM606eQpU3r7Z+gWujs+bSwm623Ccvog0jlG\nnHOu1wIhIh0joq9CJd8B2tp0PcpS+XSfpcm1A88C9yC0QKjU+1ni3x9EkI8PIhCyPmQZ3Bpt4Eiv\nLakTXxMqFzL7x5Cm6CnlsNZcbz+/bxZpoQ29rv43C4T4K9Uo6kDINx9FvH2v+/dQGVJu18mUxOA4\n5ZRTuffe+0x9Via/AEynWJwXJd37KbYwJqvXx604PvU/lEolli1bxhGHHVaRZFipV0oDXI/411WW\nGoKcj+3pC6SjVEcDwxF+QBuRPhghapjDdtopNeq91tzMPiNH8ub69eURUeXU7axBqXoJ8uypuqWN\nh4IwmltdX/x5GsulmsLZIIf3ETxYzl9vib/GYoJn1yHCMNeYurMR1pa/4oBhyH+hE3ijubnfxFb3\nGF3QObejc26w3wrm/eDeNLAiIvoyNJHx+vVvsHDhAgL5RF+VuTzBb0pCGYyo7TngKEIKTTU2BvtN\nGdDZRMHa3Z6IDO0AFxEMF6UsjvZ1HoUIFINQB8cTcmupYZL4umzkwm2E2CkbHns8Mq143LfnAt/G\neYTc9Z1InJeG2+6PGFgJwiq3URF6fe2SG4ElJEmOQw452O97xrd9NDJMrEKmPfPiBGY7RRy3IjYH\ntbW1HHroobQ5x6OPPsr7Bw9OHbdJYA+qVgFhWatAECZ4F1GDu80ff82XLQKFJOHwww+vUlPE9oLa\n2lpySVKeDeSShNraWlauXk0CfBJ55jRflSYWnknQI34ekW13yPKnpQJCIPBfRZgZnIs8nxuQEXq6\nP98h8V5tfnvLn6OzgE5kFvIPhIWH5/21vo0EMODr1RnKOeb7ajzZKuS/cORm3bX+hZgnKyJiK6Kp\nqYkRI3ZHvDcqMnEKoQtMEAPlAXOWeqB+4z8fQfA4tSFrSA8i60bqPcpmfYFKcYkJSDdpBVqtDHzW\ncLOepXEEb9RM0h6sJQTDCeAk0kmLs2IfahRCOleY9UZ1IMOC5ts6DhGbbSdJ8qQXklSgOXj+Ghpu\n5Mtf/juA6M3qZ4h5siL6AtauXcvLL79c9m5ZjoAuB2V/5Wz2QEy5xUiuoUPMPpWXj8/L9olSqcTQ\nwYN5qq2NtxGFyrPOOIN/v/NOJowezfMvvJASsoCQzGUiMpprfNPeBEM/m4ogQQQv1GvVRkhJMAO4\nljCa55CZhMYSqvf2IIKCIIh4xi9I80j0/PMRQ6zGlNdI8dGIIahiHEXgtNNO4/af/KSbd693EIUv\nIiL6EGSCbz1CAD8mDLsJ8CuCh+oTBGPm/X4DUQLU9azJSPdo819VQxHpQtUjpmGtKgs/zb9/ytft\nEOPtsip1KQHAkfZOWag37WeEUF78tcf5tqhhp+2uRbr+MYRuGkRI9lqCIO2DiBG1Cueyoek5ksQB\nY8jnx7FgwY0Ui0UGDx5aFsSIiIiI6A5GjhxZ9m498MADzJ03D5CeS+WDdMU/SzEsECaoqwi99sHm\nHOUHJEBtkrDbbrtt7a8U0cdQW1vLvGuuYRKylJoD7rrrLlpaWnhq+fLUBP0PSELfSYTRtYDwQfYn\nZOpUj5dKcOmzuAEZYXWJU5MEzyWM5uqBbSQYB5chCwMq0aU8kgbgEtI8Ep0RnEeY7eh/ZXckc+hq\n397E71sF3H333QNWACN6siIitjLOPvvz3HHH7UBCkuiq5XGIcaVxWpCWQrepMsm8t3o+VjhV9+l/\nYybirB/vz3kIGeqtZ+sKpJtVI0+hbO05hKmAA44FfkllRhmHEAfsmtZMxKt1oGmnXie7/qVwBEFa\npS/qWp6NbkjHb61b95dUUuLBg4fS1ibli8UJMT6rHyF6siL6Mh5++GFOnTKF9W1t5d5Mo2T1V7+S\ndAp2jao91JRREnm2B4/PzvaFtWvXsteoUaln5Y9r1jBy5EhmX30135ozpyyJvhQ4m0pPVZ4wqu+D\nPE9PI9S+8YR4QfXAauCC5tzS+jS6+6vAzVTPH9cGfAB4mTBjKJJOLKMzGA1sSBADS6Xq2wnUxYeR\n4IXX+klcVvRkRUT0Mdx++600N79Gc3MTb73VRKFQIj2ZcgAAIABJREFUABYATyDd2G8Rb1In119/\nLQsXLiQIVuSRrnUJ0mWpl0m9Usea9/sSogc0F+sEhHGdR8gqWZrdNeYcuxbVjuSL/z3BgFqFGGrH\nEdbKjvffwyFd6DxTzxzgIwT5+hzpNd9zCKSEZWb/Qb7dDvi5P36V36dGXSWGDBkSDamIiIitiqOP\nPpqWDRt46aWX+JdbbwWkp1bPVifSqyaEyFulTDmkZ9SYGvU+WGmiJElIkn67xhDRTVQzLHTfmeec\nU86XNQb4myrnq7GkUAPnEIQ/AmGUBfFu6dNVROKodDTv9PtuJi1eYVFAZhLtwKX+cyfynI8njM66\nXJz3dY4jeOA+icxqHBKXteOgQf3CwNosdEeKsK9s0uyIiP6JhQsXuWKx3hWL9e6ss84rv1+w4OZy\nmdbWVjd//vUpifIgk17jRKZdZdRnZeTMG53IsBeM/LlKsJ9qZNBVGv7rmevUmGPVpOVrHMwwx4oO\njumi7KDM5xkuyM0XfbsHuSBnn/fvrdy9tl2/+yCXlqivqZBtt/c4yrn3L9BNidy+tsXxafvDmjVr\n3L333qvzSoeXvLay7SqT3eilra1MdsG8Jn7TeiIGPs4766yyNPpZp51W3t/c3OyK4Gb4Z6MR3JCM\njLrKteu+WtIpA7Jy7Fl5dXy5HLi6TPmsbLuVkM+Z53kQuFn+Vdv1pG+LtqMIbqnfiv5aNf5ZrwG3\nZs2aXvwFNh3dHZ8iXTAiohegCXNra2tT77O46aaFXH75FQAce+yx/Oxn9yNUuiuAbxHivX5LENaA\nEHptHfdZGqKlFtr3edI54S2hJTH1XI0ItFox2SyKBJqflYcfj8SZqWBGQpoaCZUCHtqWZYi3yyHr\naUKUyNICN3ZfI/ouIl0woj/jJz/5Cffddx+33nprqlctErwDluxsSdsQekHlJyg++MEP8qc//Wmr\ntj2i93D2aafxk//8TxLg1FNO4cf33APAqSecwM8feIDjkMhktb7tiKmJYlYQiPZdUf3ywAtmn9II\nvwR8N1P+EWAoEkNVIC0hvwPwDuKV/SbBS6vHH0Q4LzsCzQR5LW3vk8jor+WefPZZJk2a1O37tq3R\n3fEpGlkREX0cpVKJUqnEsGG7leOMAtNau9plSOyT5r7SqICnCTFRqux3FBIPBqI55BDKH0i3p0aT\n7TI7EOEJ7cJziAS85p63GWK0e4c0GUbb2kmIF9OufEdEzv0pvJht5vrTkWlIghANDkYMy8NRVcEY\nezUwEI2siIGCxx57jJtuuok777wztV8FCkB6tmsJS1ETkMmwNdAgqL9BjNsaaKiWL2vSAQfw5NKl\n5WOPI6NdERmlf0/lCK1KgxOQBIF50suqLlNO9X47kEydh5LWMb4MuAloJaQngECP/QSStEX1hW17\nlHqoiwVZg+9xROzjfuDThDi0vo4YkxURMcBgBR0C2vnMZ84giEkcQFAbfBrR99E0hWogqc7Vw4hx\nVWPOOcRvqoOVhSYkDtcXo0i9WhqHVfDl1LOlYa9qXOla2lzEUEyQ3Fk2L00OOIaQFWQ6YjDqGt4B\nvt5D0Xxi+fw4GhpujAZWREREn8GRRx7Jj3/8Y5xXKDz22GOBIGftkMjVlAFF0IC1UbKafytPjNva\nHrB02TKampoYMmQIx0+ZgmZU6wC+YsqtJ3g89ybkxNJYqU5kCfZ5c84YZPSd4T87Qv43jS10iIbx\nFYhRpnm1rEaxRlIPRmK9rKqhesvUMMviUGT0PwEZ8YcPH77R+9FfEY2siIh+gNraWhoabqRYnECx\nOIEFC27k7rtv54YbriV4jqYTDC5d2zq4Sm01CB3QEdZUdY2rExF3tUKwmjDZJlD+OkIe0G5c0YGs\nsekU4Q++7g2I4GsNIh0P0pXvZK7TTgiN/aU/7wpknbfdf7dlflOv3PPAMpIk4dxzzy5TBCMiIiL6\nEqZMmcKDDz6Ic45zzjyTIuK3v5uQ6FgpXdXMp+VUCmaosRUNrv6NIUOGcOIJJ6SSDQNlWfPZ3/42\nCbL0mAB/61/HEuTVrbjKPH98MJXLoxo80IbQ/CDIUl00dWpZrVCTEM8DfuTL6ZKsGv9vE57dnxFm\nAzeY8n9PWHK1Mwq9rhpwA3XsjnTBiIh+hGpxRgsWLOTyy79GkiRcd921TJ16GZXxTWoIWZqexkeN\nQeiFcwmkgA5Cl5onrTWUI6yLabyUZYgrnW9FpozNjwVwMaKyqOthE4B/R/LRa8YOVT3UepYAP0Vi\nwUJkQz4/rjzZaGi4kQsuOL+rWxjRxxHpghHbAw6ZOJFlK1aUk2WoVyE7YdZ9z5JO2/5N0jEuKpcN\nsNdee7F69eqt+wUiehQtLS28f6edUglMVNa8qamJPUaMYCYy8gF8Efgh1eXci8iIPscf0870eESv\nV0f2bLLgfJKwwbkKsr6O3hsIku8qx94J/Adh1NblWgsNQHjcfz6CEIulr1HCPSIiotdRjTp48cVf\n4e2332T9+je4+OKvsGDBDQSa3tUUi3nWrPmjl44/p4uaryEts74U6TKVZqgkFocQDXRNSverKAaE\ndIVaZiayDmvXwBIknaFDhhSlGJ7tjz2HTCssEkQSfjbiIZtZvkZHB7S3P0db2wqmTr1kwK6KRURE\nDAwsWb6cU045pZwk9lSgnpA4dgNCpNYediLifSgRlsO0N9XYm6Lf1vzxj+SMl+vJJ5/cpt8tovsY\nMmQI55x1VpmHcuYZZ5SNjuHDh7PfvvsyG4lEToDPVKlDlzGvRPgfKojR6ff9yu/TfFkOMdpX+Pet\nzrGCtGGQN2X1vLGkEyI3E7xVuUz5mYRl2iP8VkRybYHI0596yin9wsDaHEQjKyJiAMAaX1/96ldo\naGigUIBicR4NDTcycuRIFixoKNMNTzvtNIrFg70HKEc+X+AznzmNIJwB0j2oQVdEaIAJcCchb5dq\nZRUQo+iTBFa30hCrGXZ2DXYsMqzsgcSKlb8VSjJIEs0Rb6MXzvHXXeLbHQ2riIiI/oM777mHl9et\nwyEE6RWI0VREet+7kJ7y84QeU40tC41WrRbDVQAOO+ywssH16U9/eit+o4gtwa233861N9xAoVDg\nnnvv5fu33FI+dtP3vgeIpm+CZLG0FLwTCRP6uYRnSUfz+aSXTLPQhNr/g3BMNG5Lyf0X+3M1Xkuf\nNQd8mWCwPeXL/8F/VuqiQ0bqJb4OHdEBfuDzzQ1ERLpgRMQARTVqYTXpeEVtbS1nnvk57rpLh3Yr\n3a40w7GEta1OxLDJI2ux8wjDvxIM9D0EY0wJBZZy2Ias4z6FhOBq99sBtJPLFXjzzXWUSiV++MNb\nmTbt6/64tCvSBQcOIl0wYnvD3NmzmT1rVoVaHEgvWoNMWF8nKMBZ8nVWD1ZTuT+NeByyZG1rpJ19\n9tncdNNNA1Z4oD+hVCoxdPBgVrTJLzShWOSN9eupra2lqamJ3UeMKCv1LQPeQPR91YuknWYnabn1\nNgLNT/fpcqpGZiu9sJ0QqZ0n/Rw+S3XtX23T88iM4IAujtuZwEcR+mAb0NxPqIIQJdwjIiK2EE1N\nTey22550dExD1r9sPnmVUAfpSrV7F5b3GWf8Dfl8njvu+A9C19qJCFjcSNpTttK/jkGMt+eRrvk2\nhHmu+kgJhUKOt99+s2wwLliwkEsuuRznOsjn89x00wK++MW/BWJerP6OaGRFbI/YZeedebO5GUhn\nIWwnPUGegCxF7W/OtUaXxnjNIyxZqbGlxhiECFsbP1NTU8NNN93Exz72Mfbf314hYltgY0YWwEHj\nx7Ni5UrGI6OnUkkTSMVyqVFl4/1s/FUbwdBWD5btsXYFXqZ6IheNllaciIheXAjc7I8fSzrLZkeV\nutp8e4488kgeefTR7t2oXkS3x6fuZC7uK5s0OyIiYmth4cJFrlisd4XCINfQcLNrbm52zc3NbsGC\nm10+X+eg6JKkzi1cuMi1tra6devWuebm5vL569at8+XqHZzqoOgg56DgoNHBHL9vkH9f7yDv9xUd\nzPLlig5qXUPDzRVtbG1tdc3Nza61tXVb3pqIrQzfv/f6OLO5WxyfIjYXJx57rEvANYKbA64IrgAu\n798X/f455nMxsAVdzpcvgqsx5Vf790v9+1pzbo3fcuASU5dul156qVu5cmVv35rtBosWLnT1xaKr\nLxbdooULU8fWrFlT/q2K/rd80rxv9L//h0aNcgX/ebX5nQukn5uiebYa/Vb0z0GdqVfreNK/L2Se\nS22TvWYB3CL/DCVV6tLnq7+hu+NT9GRFRERURTW6oe4vlUpd5O8KuOWW73PRRVPp7Gz3yofzWbLk\nGe6443ZT6krgs0ikAcja6z1o4uHTTvsM999/P0CkAW4niJ6siO0ZC77zHb5+5ZW0t7czE/FIlQgE\nbt2yHgYld/8Eiau5kCBUgD/+PJJXySaOnUAQR9By1WiFio985CPMnDmTfffdl7333nsLv21ENTQ1\nNQGVuaNWr17N2H32KSvy6W841r/q77b7rrvyyquvppQDbwNOp5I22EalymAb8BKSjNh6pJQOOI50\nnqwDgEeQvFq2/AZCJk9LV1Xv1i8feoijjz56025KH0GkC0ZERPQZZA2yUqnEDjvsTEfH75EsHmN8\nSc3ekUdCba8hl3Pk83na2kQKvlicwPr1b3QZYxYxMBCNrIjtHRp/U0OaegXV42usgaR/nOnAtxHK\n4WuIlqv2spa6tT/VE2UcQjqyVpPQZlFfX895553Hueeey5FHHrk5XzfC4PNnn83td9wBwNlnncWt\nt4dFyVKpxJA6EYfSHqYIXIAkQ8ka3mrY5JAExg1USrBn6ahjkd9Z6YdjCdLt+vxoZk57vWMQuuB+\nvsyewCv+3AT4FunE23mg1A/7ySjhHhER0WdQW1vLkCFDUkZQLpdDDCyQ9TBlha9CmOZzgU/5cl3j\nllu+z+DBQxk8eCi33PL9rdH8iIgUkiS5LkmS55MkWZYkyd1JkuzU222KGHgYPnw4J55wAiXEwLJK\nbvhXqypXQ5jMadTrXF/uGwQD60fIRNeebyNuLYrIRNuKINQQYn1U/ujdd99l0aJFfOxjHyuLD51w\nwgl861vf4kc/+lHVuiOqo6WlhdvvuKP8e99+xx3lhMQg4+k3587FIfmlHCLpfkKVuhzwKcJzsRDY\ni6DnqxLs+cx56tGagKgLTiEt+b4KSSCsyoaaPPnXiIGV83W+TBDVyAM/AJ4heLH6o4G1OYierIiI\niG2KW275PlOnXkJbWxuy3jof6Xo1efF4oI2GhgaKxSJTp14CpOmCpVKJwYOHbtTLFdE/0Zc9WUmS\nfAp4yDnXmSTJNQDOuWmZMnF8iugRDNtxR1reeacsBzTb77eCBzX+8wyCvqseLxCMqKzn4WDgd/6z\n1gGBLqh6suOQSfEyqqeYV+/Zho18j+HDh3PYYYfxhS98gbFjx0ZRjS7Q0tLCsJ12SnmaXs8o761d\nu5a9R40qe5WyvxvA+3femY6ODt5avz5Vl5Wdss9CFprcWr1gtuwyxMO1H5WCG52IQdYB7Ay8iTxb\nEGiIOaC9H/ePkS4YERHR51Eqlfje937A1752BR0dDuc6cU7pgjMoFufx2muvpIymLE0wGlkDE33Z\nyLJIkuQzwOnOuXMz++P4FNFj2Lm2lnc2bKiIw9JJsBo5KvOux1U1cD5CwM4qyEFay1WNMfVuWDnw\nHNWNLJ1wq8FllQu78pApdt99d4444gjOPfdcampq2HXXXZk0adJ7nDXw8fmzz+aOO+4o/1YfGDmS\nF9esKR/XuKxlwCTSsumPI8bupwoFXvjTn9hr1ChmEmh6+/vy2WdJrzUNuIHw21X7zdWz2Q7sC7zg\nj+mzqHrCWueJvk6N/1q5cmW/NrKjkRUREdFvYHN13Xzzd5k27SqSJOG0007n7rt/AnQteKEesY2V\nieh/6EdG1v3Abc65/8jsj+NTRI/ikx//OI8++mhKrKKVtCS79VSNJXgj9LWdILetlK5liMT7c6be\nDaQNpBwhn5L1lhQy5z2FTMi7EtFwvLfhlQBTjj+eCRMmsOuuu/Lqq69yxBFHcPLJJ7/HmQMHa9eu\nZa9Ro1JG0B/XrGHkyJFAMLKmI5RQ9VQdAGWhlDbgwA9/mI6ODpYvX57ydm2g0nO5Afk9s4b6EuCn\niAe1gPy22QQuGquntMNsjJeN8auvreWt1tYtuj+9jWhkRURE9FuoUMawYbttkpcqCl8MPPS2kZUk\nya+QVDFZXOWcu9+XmQ4c6Jw7vcr5cXyK6HEMGzyYlrffpohMXFeYY2pMqVGTI6R6H0+g8tUghtHd\nCFFbz8smMb4SmaxnVQbPAe4geLr0eJZaWI1eNpZKaps1yBSW4mhxzDHHcOihh/L666/z/ve/nwkT\nJnDIIYcMOIXD9zKyAHbZaSfebGnhckTRrwh8AomLetyXOQJ47IknOPKww1J1ad40qwxojfWst1SV\nAZ9AEmHb33B34C/+s3pOlTKYrWevPffkhT//udv3o68hGlkRERH9GpEKuH2jt42s90KSJF8A/h/w\nSedcxbJskiRu5syZ5c+TJ09m8uTJ26x9EQMXO9XU8HZbW0V8lU5wrZpctTiuDkTGez6BvpUnTLAT\nJHltNkpWKWUa62VnX+oV02tkqWh2Mm+NOTX8rHGon7PxXXnSSZMVKsAx7zvfob6+nnXr1rHvvvsy\nZswY9tprr1QsU3/CvqNG8ee1a4FKuiCI+uQeI0bwOPBRJC7qbeBI0vfx2ZUrmTRuXOo3qPYbqbdz\nCiKoocjlcrR3dqaopmpw62/2bcSjppyU8UAjld7MDf10zr548WIWL15c/jx79uxoZEVERPRvRCrg\n9ou+bGQlSTIFCTH4hHPutS7KxPEpYqvh8ksu4aaGhgqDRSfKKq9t82lZY0snvW3Aan9shj9mY7Gy\n1LEpwC9MHVlJ9w8iBtwCU4deS+mGKzNtXu4/WwOsmserWr6uIhunIBaAD+y5J1/88pcZOnQow4YN\nY4cdduCtt97ilVdeYc899+T00ysc0X0Ga72RZT1YFkPr62n+618pIN+1RKVIxWNPPMHHDzssZfA8\nCRxG2gjCfx4JrPWf1WC3915phurhUoM7a/RfBlxr6u/PQhdZRE9WRETEgECkAm6f6ONG1ovIXOMN\nv+t3zrkLMmXi+BSxVXHIxIksW7GCIuJ5mocYLTr5TehasMLGXaksu3qt1iNiCgXCJDsx9WXFEuyf\nVPN3qaF3HRI3NpPqyWhziNGl8USrqEyUrF66ajFhXRlYXdENLawk+VcvvZSRI0fS3t7OoEGDqK+v\n5/XXXwdgyJAhDBs2jEmTJvUpWqJ6sh4BjkJ+4+eBs0nfu1tvu43Pn3NOat9XEU/TL5H7MAMxwKvl\nX1NPpxpWIL/PM2Z/Nc+YGvrQfz1YXSEaWRERERER/RZ92cjaFMTxKWJb4NPHH88vfvELahBDazZi\nXFjDyNIAq1H1IHiaGs3xXyLUM5tHqRoN0CoLgkyubZJcfN2/QgyqL/l9mhkx67HKJkoeAzyC5Ht6\nmkqlOwutoys5eTUc8cf3IMQTVYO2X+st5vM8uHgxS5cu5a9//St77bUXzzzzDK2trXziE5+gpqaG\npqYm3n33Xd544w1aW1vZZ599GD58OEuWLKG1tZW9996bAw88cJNVFJuamrjjjjtoamri8MMPp6am\nhsbGRtra2rj00kv5FvBD0t6nTvNejaSscaxGkJVfvxm4MFNWnye9f9opfxJ4iK69jyquMRBzYUUj\nKyIiIiKi3yIaWRERm4aDJkxg+XPPlQ0q63Gwhk827uob/v03Scda5QkiFhOAKxB5d6hUpFNhDVUW\n1Hgf245q1z4B4duqX+iHvh3/TVrJUMsvJYg1WCNrvH/NKhzauCOtQ79jVx4uzeVkr9uBSJ6vqHpG\n5flZT5vtwLLGZB74xrx57LLLLgwbNkzqqKnhnXfeobm5mebmZq779rdZ19RUNpg3Vp/S9gpUGpiH\nAs/697sgBllCoFtqPe2Z8+v8PdB7kTV+Owny7er1+jjwmC/bNkD7wGhkRURERET0W0QjKyJi03Hm\nKadw1333UUAmzvrH0ZgpnTyrl6mAeDAOIghdqOw3BNrYdCSuRo0MS5YrmvfWKFMjRyW71bhR0YqE\nkAxXoTTBA4F/BZoRjwoEA816qfSflW2fvX6eyvivrNGF2WcNi3oCF9gia2RC2pDdA1gDfBjYEXjU\nnLsv8lusRoQqflul/o1hIiF+DeBGxOj8N2CUv+7hyPdX2DZa9cmEkLD6OsS4XYh4CxeT9oQuRQzb\n31JJ47SGbC3wV0wc1wDu/6KRFRERERHRbxGNrIiI7kFjdKAyNkYn2HlCHJb+udQoyyYx7iTQw6pN\nrNUgs8qCamxpXqTDESn4uaadVkSh1rdHKW5ZT4l6wR4BHjD12GTJWYPJAccjUubW+NJ7UI1yqB68\nbD1ZQ6oTGOxfW/y+4xBvzp9Io5pnTD9Xa3P2WtWMyvcqo/dLlQTH+7bejBhAXwPORQyzrMFo69E4\nv9mIHPxk5H5dhuRYU6hn8DFgN2A/v38giVxUQ3fHp9x7F9m2SJJkVpIka5MkedZvU3q7TRERERER\nERERfRHDhw9n5qxZqX1KISwSvEeWOqcUMWv4FEkbTm2IITIGyYGlRtccAt1Mz59NkAM/BDGw5vvy\nMwkUtSIyye8AjvHnq5dtjKlD27Ab8H8RL1MReAmRDW8DLkEojW0E78wD/ntpXe3ANNJ0Owul2q3y\nm0OMRDW+dH8OeAcR89Dv8QhCv6vxmyr9dRK8Z7v79xsQ9b4NCK1ujH9/ojl+InCWf3+0f/0souyo\nZS41Zc7wr+chioFtCMVxvG9vjS8/3bf3DsLvpt+r4L+v7ltByJF2pLmXP/P7hhFyceWR/FwaHzfQ\nDazNQZ/zZCVJMhNY75z7zkbKxJXCiIiIiAGI6MmKiNg87Lbzzrze3Ayk46a68mqp6p8aQFcRPEZK\nN1Sqn3q2smqF6uGy8U46kdfyB5JOUqwUPqsUeD4SMzQbkYL/Cel4rmoqdtkcXK8ghoGFtrsr71A2\nIbN64g7230NjvjSpcy2VFMWDCXFLeh825qXq6nN3PFd0UV7PsYqM1lupxrKNZatGB9R6bMxXDnjR\nlLHxfx3bSZ/X7z1ZHv12gI2IiIiIiIiI2NZ45a23eP6ll6grFslOeVVUwlLtQIyDDsSAmIVMmJ9D\nJtx5gtdGJ+wTqfR+LSftMWsjGBvZ8gpV+9N2/SPiIbOeNKUm7uzrS0h7uw7w9VuvVxFRSlxt2rbI\nf78286rvc1XqPYRgMI1BDJEr2fjEtAOhI6p3KE91j5h6uh4n3GOHGIwFUy57nnrYtMwyKj1SOXPO\nc6TVARWJ/y7W03dI5h50En5DpY7WIJ42e5/099teDKzNQV81si5KkmRZkiT/lCTJzr3dmIiIiIiI\niIiIvo69996blg0bGLLjjuUJ8UzgD5hYrCQpG01qoOiEXD1XJdKT+BwhvxaEyfZViHfHGlu66UQ9\na8ioB8QaEDppLwD/SaAuAjQhghTP++upgaSGVyfpyX82s+JHfH2r/TYIMcTqCTQ8a3jZVzVA55I2\nvNRAOcB8R71uX/ESqDKgbXMHwVuptMbs930BoTYqPVN/o5/6c9QIa2Pg5cHqaWSFXrYJkiT5FbBr\nlUPTge8iip4A30LUPr+YLTjL8I8nT57M5MmTe7qZERERERFbGYsXL2bx4sW93YyIiAGF19av54RP\nfYpf/frXnOP3FfEKfH5ivPdee7H6j38E0kl8xxC8MQqN7wLKuZAKCL1vNmLI1fp9mp/Jlj8V+DFp\noQuL5b7OLG1NKYNt/nz8vqd92dsRg+lqf6xAoLupt8vS9si8LwB3IxTFannARtO19LtFPnNdCB6x\njsyxHHCE+aztTEy5aucdkimTfa/QfZbumYX1bCp9dDoSR7cIeJVKY1GNcKUiRlr0e6PPxWRZJEny\nwf/P3p3HWVnW/x9/fWYlhcENUsGlNEUExbVMTcosXFLLJe2XWpZZmgtuiXy/IloomuKSVn7LSi1T\n03JJNDdU1ERNXFg0yA1xwY0BiVmv3x/Xdc19nXvODAMOzJnD+/l4zGPOct/3ue77zDDnw+dzfS7g\nDufc8NzjqnkXESlDmpMl0n0OOfBAbrvtNqCwA2CcRzWgro736uvbAp/YhjstKYyBUX6dpDhXJwZT\nlcD/4Mv+mvHZs7h9UzheDXAkfn2sdP2sWcB7+OAjfZ1HgXUpnCcUx9QI3I6fZ5S2cL8D3yyCZNsY\n3MTXSwOvqUVeN11sOd7Or82VLogcG4m08vGdj+9k+ONlbVjEdeH7EeF77CTYWQfHdK7cccBl4bEb\n8AE0ZHPX4nyvpavpv3G9fk6WmW2Q3P06XVsLTkREREQSN//tb1x48cVA1gFwHH4uUzXwYX09Vfgg\nIg0+YudBR/sFbqvxH87TtbliaeB4skVso7SzYCvw+/B4E36tq5owrs+HbYeHL8OvOQVZ2VXs5Bcf\nOwC/hteOwG/DGNbHlwRODdv0AU6geEmgwwdYxeZ7DQv758sP0+sQG0LEbn6fwJchxtLEOFethqyz\nYtplsSZ5LGb/DsW3os/vW2yf+Fgcz+fDVzU+AI1zuZ7u4BxSzUDace5wChe4bgXunDx5tQ2wVkTJ\nZbLM7FpgBP69fRk41jn3dm4b/U+hiEgZUiZLpPs1NDSw9ZAhvPrKKzxG+8xNK7D5pz7FSy+/3Jad\nimWBsbQsPn4qcAHtsyKt+Fbi08gCkLTLYLE1qsCvN3UXfk2nsfhW6ZBl1arxrchjS/i4f5pxSzsV\ntuBbi++Bn3MSA8jYCbDYumB5sUFIHAO510nXk0rLKvPd/GK3ws938Ppx8ed4XluTlfjthW8Tnx4v\ndjlMs1LDyUoa07HGDN2T+MzY0ORc039gY/OTmnAusVNinIMW9ynnRYa7qtdnspxzRzrntnHObeuc\nOzAfYImIiIhI19XW1jLn5ZdZp66OzxV5/mmL/e+WAAAgAElEQVTgPy+/zJpVVW0d79IMViNZE4gJ\nRfaPGZ1pyb7NdDyfKWbBKoF7w+2T8SVyzcDVwBiy5gwX5PaPn3LzXfks3H80jLMKvxjvEnymKz9H\nyfBzumaGMfwUn4mKc6LyTTFIxjSerPFG/Mo3moglkl0VA7tWfDZteTj8eT8abn+ObC5XDEpj04p4\nbjGgiiWfL+BLN5vxzU8UYH08JZfJ6gr9T6GISHlSJktk5Zo7dy5DN9+8LeuxL77DWFy/qhnYbOON\neeW11wrmZUEWNMXMFmRd7NJ5XLFb4U/IStDSxZDTTFE+uxWPezNwGD5YWkoW1EDHGbL8vKmtaJ+J\nyq/rNRdYFI5TkxtPOjcrtlVPF2Eu5phwPa7BB2xxPlpHa2HF84mPP5e8JsvYJ3UqMInsGnYU4E4L\n3z8bziedO5eebxNwxRVX8OMfr8jssPLU6zNZIiIiIrJybLbZZjQ4R01lJa3A3/EB1llkWY1XX3uN\n2oqKtrlQMaOTLk4bszfgP6zX4LNJw8kyVZfgA44mfFlg3L6jrnfxWJX4AMsB/wAG4QOMPwPrkDVi\niC3UY+YoXc8q34Y+zk9K54hVh/1GhOMswS9qXMzjZFmz2Ar+ExTOv6rGzzm7nqyNfbHW8PH2oeH7\nXuE1DNgB33SiItluf+Bgspbz6XFiEHdxcl0gm7cV53XFTo1n48sI49paNyTXfRuSJiPOKcD6mJTJ\nEhGRkqFMlsiqs/dee/GP++5r+x/3KnyHwAlk2ZqJl1zCLy65hNfmzWsrL4vNMSBbb6sGmELx+V5x\n++vwne9iIAUUZNTuCbfTDn6xFLEJ+DRZgOOAbwGLgVvC9nFs6XywdCxP4oOYfKe9tNtgR1mgmXSe\nNRse9n0aH/w9Gx7flsI5V3F9rzS7FTOBy8pi5TNacawx+Ivn8yDwFfw8sKHJPvG9SudzpWWhDlir\nXz/era8vcgVEmSwRERERWabJ997LJRdfTAvZB/gJ+EAifhA//ZRTmDdvHvPfeactGxI/2KcNLpqh\nw/leca7U0WTznU4nK0+MGbU0E0XY5zmy7NNr4XsjvoRwN+CccMwjKFyoOAYw6fyonfAZtbw04xVf\nK+3gV40Plpbguxluhp/r9V9gc7JM4LI+fbeE85kdzu3J8NpfCPvuSJZZaiYLiGIm7tlwO2YTZwMb\nFnmdl8LYtqUwo9XZh/5m4JXXX1eA1Y2UyRIRkZKhTJbIqtfQ0MC6a67J0paWdlmeJ/Ef/puByZMn\nM2fOHE4+4YS27FS6YDBkazNBNt8rzve5lWztpTRjtCMwnfbdAsfhMzK70D77FKWL7s4N34fhg4xU\n7JiXf429gcm5Y8c5Yy9QuF5UKt/VsLNFi+M1imuCgQ/MHqN4Zi2eVw2FWb04Z2rz8JpbAHPwJYAX\nkr0H6dgqgRm5Y+fPYe211uLtDz7o5AwElv/vk4IsEREpGQqyRHrO3nvtxX333deWkdkXHwClQUYr\n8OKcOWw/bBhLli5tVzYYy+FiUEP4/gztW5jHLFgLvuX4HfhW7ZXJvi3J8YqVuaWlcw74Er5jIfjA\nbaew33TgoOQ80kWK80FJPObTRcZcrAww31I+jieOLwZhHf3LEDN2aZONzuatxY6F6ZjPxHdH/Ac+\nW5cPlPuRta2P+61ZVcWsl19m8ODBnbyaRCoXFBEREZHlNvnee3lv4UJqq6poAe7EB1iz8Vkl8B8c\nh2y+ORVmzJ4zh8023rhgPamq8PVTsmYZDt9UIe3KV40PLGKzjS/h18oibP/NsH3s6gc+SEhL82Lp\nXVzItwI/LyyWx20XjvEQvtNgNVmjCsOXGsYSwxjUxACnpciYOxPHEscby/zi2IstLBy/xyYesRti\nZfJcsQWI40LK8TVa8GuCbYBfjDlvB7KSyfhe/XvOHBY1NSnAWomUyRIRkZKhTJZIaRhYV8eCRYuo\npvhiwuADiimPPMKWW27J4IEDAR8ApJmoNEipIsv0jAMOJ2sYEQOq2IHwPHzmaWhuf8gyRrPwXQTT\nrNIw4MvA3cl+MXvjgG8DuwOj8Y0hhpNlyWbgO/ml0nPprBFFLAPcEh8IvVBkbGnJ3zD8umCX0j7r\nFBcv3jZcj+pwDnG7z1DYwCJtMJIvh6wD3kvOp29VFYuauho6SkqZLBERERH5WN6pr2fOnDlUUDwL\nFT/Ej9x9dzYYOJD7H3mEm2+7rW2buOhtzL5Atnivw2fI0qxUFYUZnPPwQcYGYd9PAL8DDkmOPSSM\nLS/OsRpHVsYYM0k34oOb/+IDuNhiHnz3vzXwnQTXCK+5D77Ur1gL9pipg6zBRmzs0dHYIgdcHr43\nJI8v7mQfwjEr8KWcaVMPku/fT8a5kCy7OCdkr2TVUCZLRERKhjJZIqVnry9+kQenTGkr7TsLHyTF\neVfNZHOnPlq6lFmzZrHjdtu1NceoICubi+s6xfvxtsMHN9DxnKtDgJH4LFTsIgiFzTbShYp3CLfT\ntutpc4g04xPHNhifjbof6BNeIy7YOxwfEMXM15v4DoedSbN3+dfLL64M/jpW5h5LpU1B9gO2D49d\nC3wnnGs6t8uAX//2txx99NHLGKksizJZIiIiItJt7n3wQd5fuBCHD27GkwUpL+A/8Meyuro+fbjl\nxhv5aOlS7pg8uaD7YFxnqwqfUWomyxK10l5c/ylmpP4CnBC2j+tuzSVbMytdX6qj+VRxLlgMeOK8\npvh67wAPky0m3Az8DB/ELKGwIcUGYbvpYd90ceKYCWulffYrnq/DlxnGFu1xLli6ePH/AseE263J\neMfjSzjjmmM7AF/DZ/+GJMdrck4BVg9RkCUiIiIinaqrq6PJOa674Ya24KgFn9mZQOF6TudfcAF9\n+/Th0Ycfptk5HnzkkbZgK867OoysQcVNYb9Y/taML9OrKHL8OC+rGvguvo15Ez5LdSM+eLqErM15\nc3LcFmAsPtNTTCtZYDebLCC8HjgfnzGrDK8X18tqwpc2NuNLEM/FlytClo1agyz4qgaOJZtrlTom\nfD8UOCrcPhu4OmxrZOtoEV7zJ2GM2+DXGovlj8/OmIGy6j1L5YIiIlIyVC4o0jt898gjue6669oy\nWmkThlgi14zPwNxwww0cdthh3HLLLRx88MFtwRa0b5LxRXyHwHiM1tzxY8nfOfgMU0tyrBjATcIH\nU8/jG0kcFp5PyxbzrdaHhe1ryMoLh5M1oIhzrSpy++UbYMTn8mtnHY8vP7wi2X4QPnOWz7ilpYPx\n9WKjkLRdfNo2PmbBnnjiCXbeeWek+2mdLBER6bUUZIn0Hg0NDWy64Ya8//77RTvtxZbk8fEnnnmG\nESNGMHXqVPbbay/+u3RpW2dByDI7aYAS52zl/1GIGa3YMj1dWyoGeF/HB0/jw/YvAvfhM0lD8XPA\n4vyn9DXSeU8xsEnX7eqoe2DslPh0eNyRtUyP++a7AjYn5zIbWASMIAsI02M/hS8LjC3c0/H+/tpr\nOeKII5CVR3OyRERERGSlq62t5c333mPu668zeJNNChbcbaBwzpMDdthuO/qY0bdvX97+8ENmzpnD\nJVdc0RbgOHzA4SjsSrg+2fyomLVKW74/RtbiPL6W4Rc3/lnYPs6t+k+4/zK+fO+hcIxRwB651xhP\n1r3PAacv5/V5LLkGD1J83tnx4Zyb8SWCO5Gt+VWZbNeELwmM2a0YVF5/ww20OKcAqwQpkyUiIiVD\nmSyR3mvBggUccdhhPPDAA22BTpq1yXfR+8EPfsC5P/0pAwYM4IEHHmDvPfcsyGxB1sEwBk2P44Of\nGJgZviRwJ4qvN5V2KUz/YYnzwt4H7gKmAeuSdRBsAT6LLx98hCzoyWe7ipULxvE+Hsa1FVl2bzhZ\nOeJAYAy+pTxkQWVaGgm0Ba9p+eGECRMYM2YMsuqoXFBERHotBVkivV99fT2D11uPhqamtgCkAl+e\ndwM+SIIsKBk8eDB33HMPQ4cO5YEHHuDpp5/mzDPOaGsPD9ncrRio/Rr4K77JRL4d+77AxWSt4J8j\nWwA4SgOWOIeqBd8ifkp4/Iv4Bhxn4VvCvwV8KTx3UPh+S7g9g6xZRvyKxzTgpbD98HD8XcJzsf18\nHHs6Jyy2YY9lZ1UVFfzjoYfYbbdlNY6XlUHlgiIiIiLSY+rq6qhvbOSZGTPaGjK04jNEP6OwU2Ar\n8Nq8eWy79db0r61lk0024cQTT6TFOe6YPJk1KyvbyudiyaDh51XFAOsW/Nyp+PzfyeY7VdO+m2AM\naNL28BX4AOcxsgWRp+IDLIdvpT4xOcbmZOV8Q8Kxjg/n813gU2QBUgVwati2CZ9hMwozV7Gt/Fn4\nQCxtw/6jE0/kP6+/zpKWFgVYvYgyWSIiUjKUyRIpP3/+85854vDDgcISwphp+h/gQnwAEjNVp552\nGnvsuScbb7wxtbW1XHPNNVw6cSLNLS0FJYX5xX5b8cHVnmRztfLlfPH2M/i1pvKZo+eLPJ7fv1hH\nwWL308Wb0yYdcYHjIcCj+FLF2CjEAev2788Djz3G0KFDkdKgckEREem1FGSJlK9p06Zx4N578+77\n7wNZiV81WUCzNYVdAh1QU1nJtOeeo66ujoaGBu677z5O/OEP20rxYunfMcDvk9eL85iOBl4F7ieb\nVxWbR+TnjcUgawd8B0HIugZC1mwj7rNlcowGfEliBVkHwrh/XEw4NvZIXzN2HTSgpqqK/8yfz4AB\nAzq/mLLKKcgSEZFeS0GWSPmbN28eTzzxBIcefHBbyV0MUvIt0dPGFQD9+/fnt9dey+abb05dXR0v\nvfQSRx9xBPPnz287fsxy1ZLNiYrHaKRQPhMGWUAFWSZqQng8H2R9Jtw/AT9PLHYQLDa3KgZ36WvE\nNa7GnXsu3/rWt9hss82Q0qQgS0REei0FWSKrl7vvvpvjjzmG1+fNa9eRMAZZVfjGEqfi51sRtutT\nU8PjzzxDba2fdXXrrbeyePFiJp1/PkubfKiVtpWP+8XsWfyHJg28RuIbU+yOL+OLnQLz/yjFfSrI\nslPg53gBnEth9isuZpy2cf/GN77BgQceqPbrvYSCLBER6bUUZImsnhYsWMDlkyYx8fzz2x4z/PpV\n9+HnV+XbtOfbpzvgwAMO4KxzzmH27NksWbKEhQsXcv455/BefX1b1ixtEQ+FgVTaqbBY5guyjoDx\ndaGwRftT+DWtYvaqJdl33b59ueaPf2T//fdf1iWREqMgS0REei0FWSKrt4aGBhYsWMD8+fP50q67\n0tjcXFDGF4OsLfDBURp0PQrsRmEA1Ar85MwzOfib32T27Nk88sgjvPbaawwaNIjJd9zBa0mZYTGx\nC2A8ZrH1v1rJWrTHroCxM+Caffrw7aOO4tBDD2WLLbZg8ODBy39RpCQoyBIRkV5LQZaIpGbOnMlp\nJ53Evffd17b2FPjugfdTGOw8iF/bKj6WNtGAjhcSLragcEeZqmLBXbrI8vbbbcdBhx/OlltuyS67\n7KIGFmVEQZaIiPRaCrJEpJj6+nqmTJnCu+++ywnf/z5NzhUER3E9qmYKA6AqfJe/BnwpXz5AehJf\nhvhseGwbincGjAsax3bukeG7Hz7x3HMMHjyYurq67jplKTEKskREpNcq9SDLzE4FLgLWc869X+R5\n/X0SWQVmzpxJY2MjNTU17LPnnrzx1lsABdkuyNrDf9wgC7L5Wjtsvz3X3XQTM2bMYOONN2bEiBEr\n4xSlxCjIEhGRXquUgywz2wj4P/zSODsoyBIpHfPmzaO+vp4BAwbwxhtvsHjxYg7ad18+rK/vtBSw\nq+WCo/bem0uuuIK6ujqVAK6mFGSJiEivVeJB1s3AecBtKMgS6RXmzp3LokWLGDRoEA0NDcyfP5+3\n3nqLvn37sv7667dtt3jxYmpqaujXr1/bY++99x41NTV8+tOfVhmgKMgSEZHeq1SDLDM7ABjpnBtt\nZi+jIEtEZLWyvH+fqlbmYERERHoLM7sXWL/IU2OBMcBX0s07Os4555zTdnvkyJGMHDmyewYoIiKr\nzJQpU5gyZcoK769MloiIlIxSzGSZ2TB8t+gl4aHBwBvAzs65d3Lb6u+TiEgZUrmgiIj0WqUYZOWp\nXFBEZPWzvH+fKlbmYERERMqQoigREemUMlkiIlIyekMmqzP6+yQiUp6UyRIREREREelBCrJERERE\nRES6kYIsERERERGRbqQgS0REREREpBspyBIREREREelGCrJERERERES6kYIsERERERGRbqQgS0RE\nREREpBspyBIREREREelGCrJERERERES6kYIsERERERGRbqQgS0REREREpBspyBIREREREelGCrJE\nRERERES6UY8EWWZ2iJnNMLMWM9s+99wYM/u3mc02s6/0xPikuClTpvT0EFZLuu49Q9ddyol+nrtO\n16rrdK26Tteq68rlWvVUJut54OvAw+mDZjYU+CYwFBgFXGVmyraViHL5oe9tdN17hq67lBP9PHed\nrlXX6Vp1na5V15XLteqRAMY5N9s591KRpw4AbnDONTnnXgHmADuv0sGJiIiIiIh8DKWWJdoQmJfc\nnwcM6qGxiIiIiIiILDdzzq2cA5vdC6xf5KmznHN3hG0eBE51zv0r3L8C+Kdz7o/h/m+Au5xzt+aO\nvXIGLSIiPc45Zz09hhWlv08iIuVref4+Va3EQey1Aru9AWyU3B8cHssfu9f+ARYRkfKlv08iIgKl\nUS6Y/kG6HTjMzGrM7FPAZ4BpPTMsERERERGR5ddTLdy/bmavA58D/m5mkwGcczOBm4CZwGTgOLey\n6hlFRERERERWgpU2J0tERERERGR1VArlgl2mRYx7npmdY2bzzOyZ8DWqp8dUzsxsVPiZ/reZ/aSn\nx7O6MLNXzOy58DOukuWVwMyuMbO3zez55LF1zOxeM3vJzP5hZmv15BjLkZmdamatZrZOT4+llJnZ\nRWY2y8yeNbNbzax/T4+plOhvU9eZ2UZm9mD4/PqCmZ3Y02MqZWZWGf723tHTY/m4elWQhRYxLgUO\nuMQ5t134urunB1SuzKwS+AX+Z3oocLiZbdWzo1ptOGBk+BnXWn0rx+/wP9upM4F7nXNbAPeH+9JN\nzGwjYC/g1Z4eSy/wD2Br59y2wEvAmB4eT8nQ36bl1gSMds5tjZ8mc7yuV6dOwk8b6vWldr0qENEi\nxiVD3bNWjZ2BOc65V5xzTcCf8T/rsmro53wlcs49AnyQe3h/4A/h9h+AA1fpoMrfJcAZPT2I3sA5\nd69zrjXcfQLf7Vg8/W1aDs65t5xz08PtxcAs/LqwkmNmg4F9gN9QBn+De1WQ1QktYrxqnRBKKH6r\ncp6VahDwenJfP9erjgPuM7OnzOyYnh7MauSTzrm3w+23gU/25GDKiZkdAMxzzj3X02PphY4G7urp\nQZQQ/W1aQWa2KbAdPnCX9iYBpwOty9qwN1hp62StqK4sYtxFvT7N2FM6eQ/GAr8Ezg33zwMuBr63\nioa2utHPcM/Z1Tn3ppkNAO41s9kh8yKriHPOaWHf5bOMf7vHAOl85V7/v8QfV1c+b5jZWKDROfen\nVTq40qbfyxVgZn2BvwAnhYyWJMxsP+Ad59wzZjayp8fTHUouyFqZixhL13T1PTCz3wC9fmJiCcv/\nXG9EYcZWVhLn3Jvh+wIz+yu+PEZB1sr3tpmt75x7y8w2AN7p6QH1Jh39221mw4BPAc+aGfi/kU+b\n2c7OudX2Gi/rb52ZfQdfurTnKhlQ76G/TcvJzKqBW4DrnXN/6+nxlKjPA/ub2T5AH6DOzK51zh3Z\nw+NaYb25XFCLGPeA8MEn+jq+GYmsHE8BnzGzTc2sBt/c5fYeHlPZM7M1zKxfuL0m/n//9XO+atwO\nHBVuHwXow0g3cM694Jz7pHPuU865T+E/EG+/OgdYyxI6554OHOCcW9rT4ykx+tu0HMz/z8ZvgZnO\nuUt7ejylyjl3lnNuo/Bv1GHAA705wIISzGR1xsy+DlwOrIdfxPgZ59zezrmZZhYXMW5GixivTBPN\nbAS+XOBl4NgeHk/Zcs41m9mPgXuASuC3zrlZPTys1cEngb+G//GvAv7onPtHzw6p/JjZDcAewHph\ncfqzgQuAm8zse8ArwKE9N8Kypr+Py3YFUIMvFwZ43Dl3XM8OqTTob9Ny2xX4NvCcmT0THhuj7szL\n1Ov/ndJixCIiIiIiIt2oN5cLioiIiIiIlBwFWSIiIiIiIt1IQZaIiIiIiEg3UpAlIiIiIiLSjRRk\niYiIiIiIdCMFWSIiIiIiIt2oV62TJdJTzGxd4L5wd32gBViAX8dhZ+dcc0+NLc/M9gAanXOP9/RY\nRERk5dLfJ5HSpCBLpAucc+8B2wGY2ThgkXPukp4aj5lVOudaOnj6i8AioMt/xMysqpT+EIuISNfo\n75NIaVK5oMiKMTPbwcymmNlTZna3ma0fnphiZpeY2ZNmNsvMdjKzv5rZS2Z2XthmUzObbWbXm9lM\nM7vZzD4RnuvsuJPM7EngJDPbz8z+aWb/MrN7zWygmW0KHAuMDo/vZma/N7ODkoEvDt9HmtkjZnYb\n8IKZVZjZRWY2zcyeNbMfrMoLKiIi3UJ/n0RKgIIskRVjwOXAwc65HYHfAT8LzzmgwTm3E/BL4Dbg\nh8Aw4DtmtnbYbgvgSufcUKAeOM7MqoArgIM6OG61c26n8L+UU51zn3PObQ/cCJzhnHsF+BVwiXNu\ne+fc1LBfKr2/HXCic24I8H3gQ+fczsDOwDHhj6KIiPQe+vskUgJULiiyYmrxf5TuNTOASmB+8vzt\n4fsLwAvOubcBzOw/wEb4P1qvJ3Xp1wMnAncDWwP3dXDcG5PbG5nZTfga/BrgP8lz1sXzmOacezXc\n/gow3MwODvfrgM2BV7p4LBER6Xn6+yRSAhRkiawYA2Y45z7fwfMN4Xtrcjvej7936f/YWbi/rON+\nlNy+Avi5c+7OMJn4nA72aSZkrc2sAv8Hr9jxAH7snLu3g+OIiEjp098nkRKgckGRFdMADDCzzwGY\nWbWZDV3OY2wc9we+BTwCvLiM46b/A1hH9r+I30keXwT0S+6/AuwQbu8PVHcwnnvISkIwsy3MbI3l\nOSEREelx+vskUgIUZImsmBbgYGCimU0HngF2KbKdo33NefQicLyZzQT6A790zjUt47jpsc4Bbjaz\np8ja9QLcAXzdzJ4xs12B/wP2CMf7HLC4g+P9BpgJ/MvMnsfX6yvbLSLSu+jvk0gJMOc6+v0SkZUl\nTNi9wzk3vIeHIiIi0kZ/n0S6hzJZIj1H/8MhIiKlSH+fRD4mZbJERERERES6kTJZIiIiIiIi3UhB\nloiIiIiISDdSkCUiIiIiItKNFGSJiIiIiIh0IwVZIiIiIiIi3UhBloiIiIiISDdSkCUiIiIiItKN\nFGRJSTGzkWb2ejce7ztm9khyf1FYzb7bmNkUM/teF7ctOD8ze8HMvhBum5n9zszeN7N/hsd+ZGZv\nm1m9ma3dneMuBem1WxXvVe61/5+Z3dOVsYmIiIgsDwVZ0o6Z7WZmj5nZh2b2nplNNbMdw3MFH4R7\nG+dcP+fcK9192PC1/Ds6N8w593C4uxvwZWCQc+5zZlYNXAzs6Zyrc8590D3DLSkdXruV9F6lx/+j\nc+6rnW3CCr6vIiIisnqr6ukBSGkxszrgTuBY4CagFtgdaOjJcXWFmVU651p6ehwfwybAK865/4b7\n6wN9gFkrcjAzq3DOtXbX4ERERESka5TJkrwtAOecu9F5S51z9zrnnjezrYBfAruEUq73AcxsXzN7\nxswWmtlrZjYuHszMNjWzVjM70sxeNbMFZnZW8vwnzOz3oURuBrBTOhgzO9PM5oRyuRlmdmDy3HfM\n7FEzu8TM3gXGmdk6ZnZ7GMsTwGa547Wa2afNbMNwDvFriZm1JtsdbWYzw7juNrONk+f2MrPZIdN3\nBWDhq50unN8rZrZnKEv7v+Ta/oksuPrQzO4L2w8xs3tDhnG2mR2SHOv3ZvZLM7vLzBYDI8N53mJm\n75jZf8zshGT7c8zsJjP7Q7i+L5jZDsnzG5nZrWHfd8O5LvP6FLkGnwuZ0Q/MbLqZ7dHRtrn9Ws3s\n08m5/crM/hHGOiX3nkwyX1a50MyeM7Otw+P9zezacA6vmNlYM7PwXL48scP31cw2N7OHwnMLzOzP\nXTkHERERWT0pyJK8F4GW8KF2lCXzgJxzs4AfAo+HUq51wlOLgW875/oD+wI/MrMDcsfdFR/A7Qmc\nbWZbhsfHAZ8CPg18FTiKwhKtOcBuzrk6YDxwvZl9Mnl+Z2AuMBCYAFwFLMFngY4GvkuRki/n3Pxw\nDv2cc/2AW4EbAMLYxwBfB9YDHkmeWw+4BTgLWDe89q7FXqOL5+f8cNxvKby23wK2Dtv0d8592czW\nBO4FrgcGAIcBV5kPfqPDgfOcc32Bx4E7gGeADfHX/mQz+0qy/dfCufUHbgd+Ec6zEp/RfBmfYRsE\n/HlZ1yfPzAaF45zrnFsbOA24xczW7eB6deZbwLnhNacDfwyv8VV8tvUz4WfwEOC9sM8VQD/8e7AH\ncCT+ZyI/zmW9r+cBdzvn1grX4vIVGL+IiIisJhRkSQHn3CL83CCHz6y8Y2a3mdnAsEm7jI1z7iHn\n3Ixw+3n8h/F8tmK8c67BOfcc8CywbXj8EOBnzrkPnXPzgMvS13DO/cU591a4fRPwb+CzyXHnO+eu\nDGVxTcA3gLOdc/8NY/pDsTGnzOwnwJb4oAx8sHO+c+7FcNzzgREhc7IP8IJz7lbnXItz7lLgrU4O\n3+n55YeyjPv7AS875/7gnGt1zk3HB4eHJNv8zTn3eLi9DbCec+6nzrlm59zLwG/wwVn0iHPubuec\nwwdv8X3ZGdgAOD1cywbn3KPLuD4bFTmnbwN3OefuBnDO3Qc8hQ/Gl9edzrmpzrlGYCw+6zcIaMQH\nUluZL5F80Tn3VggUvwmMcc595Jx7FT/H7Ygix17W+9oIbGpmg5xzjc65x1Zg/CIiIrKaUJAl7Tjn\nZjvnvuuc2wgYhs+CXNrR9mb2WTN7MKyWwu4AACAASURBVJRkfYifz5XPVKQfWJcAfcPtDYG0m+Br\nuWMfab4U8QMz+yCMJz12uu8A/DzDDo9XZOx7AycCBzrn4ryzTYDLkteMWZFB+MBjXu4wnXVD7PT8\nltMmwGfjuMLYvgXEzJ7LjW0TYMPc9mPwWb/o7eT2EqCPmVUAGwGvdjCnq7PrU2zbQ3Jj2BWfaVwe\nBefmnPsIeB/Y0Dn3ID4DdyXwtpn92sz64TNe1cCryXFe62CcG9L5+3oGPuidFsoq22XDRERERCIF\nWdIp59yL+GzQsPhQkc3+BPwNGBzKqX5F13+23gTS+TzpPJtNgKuB44F1QrnZCxRmeNLxLACaOzpe\nXihZ/D1wiHPujeSp14AfOOfWTr7WDBmiN/EBSDyGpfeX5/xWwGvAQ7lx9XPOHZ9s43Lbv5zbvs45\nt1+RbfNeBzYO2aBi4yh2ff7ZwbbXFRnzhctx3uDf8/S69wXWAeYDOOeucM7tCAzFl6Wejv95aAI2\nTY6zMe2DKcJxOnxfnXNvO+d+4JwbhP9PhKvifDERERGRPAVZUsDMtjSzU0IZFqEE7HD8/B7wmY/B\n5tuLR32BD5xzjWa2Mz670tXW1zcBY8xsLTMbDJyQPLdmOM67QEXIHgwrcgwAQmfBW4FzzDecGIqf\nA1XsPOuA24CxRUq/fgWcFfaPzRNiSd5dwNZm9nUzq8JnwTrLynR2fsvrTmALM/u2mVWHr53MbEg8\nrdz204BFZnZGuB6VZjbMQjv+Itvn930TuMDM1jCzPmb2+fBcZ9cn73rga2b2lfD6fcyvFVYsm7Qs\n+5jZrmZWg58j9bhz7g0z2zFkU6vx2bilQEvIwt0E/MzM+oagfXQYU16n76uZHRLeP4AP8T+X6two\nIiIiRSnIkrxF+DlPT5jvUPc48Bxwanj+fmAG8JaZvRMeOw4418zqgf8Fbswds7OAazy+nOtl4G7g\n2ri9c24mfg7N4/hyw2HA1Nxx88f+MT7oewu4JnzlG00AbI/PeEyyrMNgfXjdvwETgT+b2ULgeXzT\nCpxz7+LnQF2AD/42z42py+dXRLHzabvvnFsMfAU/p+oNfBB0PlBTbP8QZOwHjAD+g8/sXA3ULev1\nQsD6tXB+r+EzW4eG5zq8Pu1OyM9DOwDfUOKdcKxTKR7g5ceTv/0nfCOR94Dt8PO9COdzNb588BX8\n+3JReO4E4KNw/o/gm2X8Lv96XXhfdwT+aWaL8MH5iW4lruElIiIivZv5+e4iIqXLzH4HzHPO/W9P\nj0VERERkWZTJEpHeoNMOkSIiIiKlREGWiPQGxUobRUREREqSygVFRERERES6UVVPD2BFmJkiQxGR\nMuWcU3moiIj0ar22XNA5V3Jf48aN6/Ex9JYvXStdK10rXatiXyIiIuWg1wZZIiIiIiIipUhBloiI\niIiISDdSkNWNRo4c2dND6DV0rbpO16rrdK26TtdKRERk5emV3QXNzPXGcYuISOfMDKfGFyIi0ssp\nkyUiIiIiItKNFGSJiIiIiIh0IwVZIiIiIiIi3UhBloiIiIiISDdSkCUiIiIiItKNFGSJiIiIiIh0\nIwVZIiIiIiIi3UhBloiIiIiISDdSkCUiIiIiItKNFGSJiIiIiIh0IwVZIiIiIiIi3UhBloiIiIiI\nSDdSkCUiIiIiItKNSjbIMrNKM3vGzO7o6bGIiIiIiIh0VckGWcBJwEzA9fRAREREREREuqqqpwdQ\njJkNBvYBfgac0sPDkTI1duxYHnvsMfr3788666zDggULaGxsZMmSJXz44YcMGzaMo446ilGjRvX0\nUEVERESkFzHnSi9RZGY3AxOAOuA059zXcs+7Uhy3lJ7p06dzwgknMG3aNBobG1f4OF/+8pdZe+21\nWbx4MQ0NDQwePJiDDjqI/fffvxtHKyJmhnPOenocIiIiH0fJZbLMbD/gHefcM2Y2sqPtzjnnnLbb\nI0eOZOTIDjeV1cg+++zD/fff/7ECqiqgNXxF9913X7vtrr32WiqBr+y9Nx999BGjRo1izJgxK/y6\nIqujKVOmMGXKlJ4ehoiISLcquUyWmU0AjgCagT74bNYtzrkjk22UyRKmTp3Kr371K/74xz8C2f8Y\npP8FHm+75L4rsl3++aYir1fdwePpaxkwbJttGDFiBD//+c8ZMGBAV05FRAJlskREpByUXJCVMrM9\nULmgBFOnTmX06NG8+OKLLFm0iAraB02V+Oh8dnhsWHK/Adg291xL2D8+NgSfwcof2yXbRtXhfj7r\nFVWF195vv/2YOHEiQ4cOXcEzF1l9KMgSEZFyUMrdBSNFU6ux6667jn79+mFm7L777jz31FMsDQHW\no2QB0uxw+yF88PNxpcHXbHzAVQXUhK8KfFarGR9g1YTXrUyO0Ry+T77zTrbdemvMjEMPPbQbRici\nIiIipaykM1kdUSarfN1+++2ceuqpzJkzZ5nbHgrcBByDrym9GDga3/f/n0W2r6Zr5YLgg6wKsgzX\n8GSbmLnKZ7r6AIvxAVe6bQs++Gohy3594UtfYvz48ey2227LPE+R1YkyWSIiUg4UZEmPmz59Ogce\neCCvvvoq4AOSYqWAjs7nUUHhHKx8ENTMslWSZaNiIFUNnIVvd9kSHn8W2BF4Pmw7JPeamwHfAc5O\nHs/P56oIx7rkkksYPXp0F0YnUv4UZImISDnoDeWCUoZ+8YtfUFdXh5mx03bbMf/VV9tK7iqA02hf\nCvhkeK6ig+fi7RgEVSXbVIRjV5OV/MXbqRagMXzFUsBGYHy439LJOT1HVlo4FxgX9tkzPF8VvtIg\nDuDMU06h0oyDDjpoWZdNRERERHoBBVmyysycOZO99toLM+OEE06gYdGithK+sRQGRZO68XUbKAzK\nYqDzbHi8iiwAq8zt24oPlJrwwVYMsrYNjw8JX1VAbXiuGh9wuXC8B8Jx1gj7VITt4y9fY3j+jltv\npcqMiy66qHtOXERERER6hMoFZaWqr6/nyCOP5LbbbgMK26wbMCvcHxa+vxC+D6H7ygVjIDUjPBfn\nVz2ND5Yqw3OnAn9PjhPnXsVjFFOstHEccHg4h2fxpYZ/p7B0sSWMychKEKPYuGP0GWcwceLEDl5Z\npDypXFBERMqBMlmyUkybNo1+ffqwTv/+3HXbbW3ZojjHaRw+2GgI2zdTmBkyYB18Bilmkc4O30/A\nN7tInzsROC7c/jZ+obXG8HwMmOKxY9nftuG5CmARPhBKSxDj/KyY5UpL/SBrZhHHEOd8jU/OoTEc\nd1xy/hVkZYqHJK+RrgzeBFx44YWYGb/+9a+XdblFREREpIQokyXdZsGCBTz88MMcdvDBbYFNC1n7\n83ynvtgIIv6XdRPwZ3xZ3YFkjSHSTn5VyfbFslpQuA5WEzAFP2drNLAP0B+4gcImF/lugjELVQts\njQ+gqsgyW/E1Y/lfPtsVSwLj+ccAKzbKiGOLGazTgUuS46QdCWvC94vUIENWA8pkiYhIOVCQJR/b\nggUL2GHECObNnw/4ICE2qEgDolgaOByf4Uk77tUCe5OV66Xlf2kpHvjAxgHr4QOQ+eHxGDTlfzLS\nwOlJoB+wBT5w2RmYFp5PW6+n440BFxQuZjyELDjrqHNhvAYWjp8GWek+sWHHCcBVFAZbUVv5o372\npYwpyBIRkXKgckFZYXPnzmWDAQMYOHAgb8yfX1DuFudEnURWNrcZsDmwFB8gxQDrOuA3wB3hsRrg\nTnwQck3YN3YPjFmxaqAeeJfCphWxfK8aGBiOn5Yg7hRufzUc5wV8J8C5ZOWFMcOU7hebWuTFzFrs\nVBh/oeI4YzYPCsshm8N408WOK4BfhNc/iSwbFq9rZbxvxi233NLBiERERESkpymTJculvr6e2267\njWOOPJJmijediIFGsWYUFNnHFfme7gc+KNkf+BtwCz6o2T88Nzd836rIvk3JY2sCH5E1q4jSMsal\nZMHPZODHZI0o4nFj0NNEFqhB4VpZaXCVz8TFgKqWwszWT4Cfhftx/9uBb4Tb6TGqwzZ3Tp7MqFGj\nECkXymSJiEg5UJAlXTJv3jz22Wsvnp89G8MHIjFYiPOKYlYnzqF6Ad9QYkcKS+XS+U7D8F3+dgQe\nw2ea8nO30rld+YCN8Njp+ABlbDj+sWQliel2cU5VWoZXnXvecmNoxWeWJlLYnCJmsIqdVwz44vhb\nwzWIa2/FFu7xPMaG47+Ab4YRjxnPPY4xdiKsTPZvAVr1+yBlQkGWiIiUA5ULSqdmzpzJun378umN\nNmL27NnUkAUIY/Ef+NOSt6don3X5uFrIFvqtTF5zXLLNRfhA5ELgaHxGKq5v9R182SFkix3HxYhj\nc4q0Q6BRWNb3P8BRYfsXw2vFYCnfEbGWbF2uceF1YkAU18OqDs/H8sRW4KfhWO/hA6x0EeUYvDYl\n9wn3Y9lhlRnTp09fnssqIiIiIiuJMllSVENDA2v16VOQ8RmLD2JilmVrfICSZn2ewjeHSHVHuWC6\nnlYTPujaMbzeDhR27utoja0WfIlhX+B64JxwPnFuGGRNNaKYQSq21tZTwNBk2xgMxblYlWFMN+Db\nuqfn1Jhs14oPnuKcsliumL7OtrlxVpE1zoj7xddv1O+G9GLKZImISDlQJksKLFiwgP1GjaJfnz5t\nH+JjVmUihQFILOFLsz7b4oOGJuBrZBmiI8gyL8eRZZk+Gb7/Fj/XqhGYhG+C0UiWFYuvEbv5bUNh\n0JGKHQbTNa9+Eh6/C7gx3D4H+BG+8Ub8RYhNNWrCV2yEEcv+4jjOCuOrxs8Ju4Us6InZqSZ8VmtC\nMpYYWBlZNiyWXsY1vci9Tmy6EcszY1ljbPgRxYCtyvT5VERERKQnKZMlgG9oscWmm7Lggw/aPsg/\ni88WpRmiVPyw/xg+4PgCcB8+U7Qr2dpS0WyyrE5HLdrT1umfwQcgd4QxnJ4cqxL4BD6IyWfKfoIP\nCNNW65XAv4DtgVH4YCtd7yoGc0fhW8kfTWEQF+dCQZZ1ihmofIv4EWFMcQ2u/Byv/Fyx/JyzdM5V\nVIHPHMb3Im43Fh/ExXOJ87dagFPPOIOJEyci0psokyUiIuVAQZbwhV124Z///GfBIrixUUVa6uaA\n/wccDuxHVqIWA4ityTI0aeASy9jS7VrxwUaqhizLA+2Dp/yCxM8D/8YHTWPxjS9icFKsXPBJstLC\nfCOOuF1aHtmCXxx5DoXlfi3JdunaWvsCF5MFUr/DB2upKrKMVRp0QhZsxcWH07HEwC6/Rlcc0+PA\n58kae6TXSeWD0psoyBIRkXKgIGs1Vl9fz9r9+7crQ6sAzsZnSGKpXAy+Xgz7DgnPbYUPQtKSt1ha\ndxJ+cd2twj7xHavCB0XjybJDI4Gr8Wtp/QLfOv328Fxs1b4mhdml9Hjpwsa/AJ4BfoUvtYut1luT\nffNBVsw65duux3MfGcYxhqw5BrnxpF0KIcvIbR6+5xdnLpYpTF8z3/q9msIgK85hg6RUkCxYS7OI\nTfp9kV5CQZaIiJQDBVmroYaGBr721a/ywEMPtZW9pZmmYeF7nFsU5//sC/w9PLcB8A5Z8PWv8Pg2\nZNmefwP/h8/uzMaX9sWW6GkAEAM76LgBRhVZA4hzw+NjgE8Dr4X76fpc8RizybJd38ZnjiqT7SCb\nwxW7FoIPYmJQFAOvGKR9KTz+YG6csaQwXUsr3q8B/oEP1tIMXb6U8AyytbIcWffAtI07+JLGybQP\nutLjxo6GNeH7/fffz5e+9CVESpmCLBERKQcKslYzV152GSedfHLb/RqydarSjEosO0vnB80mW/cq\nrhF1Fj7oqSQrE0znFjnaz1t6EB9s7AZMJWsY8Qkzbr3rLj766COampr44Xe+w+KGhoKgKA1qxuFL\nF7cma5sOUAf8l8JsVBrMbAbsHsb1KNlaX+k2W+buxyCmIjlebFwxE7iVwrlm8ZwqyFrGx+u7GTAA\neD+5VtC+e2P6PsTXTa9vsW6HaRfCGJzFICuu09Wi3x0pYQqyRESkHCjIWo1cefnlnHzSSe2aTcT1\npsaTNXSI2Zv4PZbkxedjKVycf1SJb0xxQXg8Nl9wFGbAhgF/IZtTtAZZgLR46VJqa2MvPW/u3LnM\nmDGDJUuWMHDgQBobG7nphhu4/tpr27ZJ26LHkro38UEcwDrAYgozY3H8Q/ClkdPJyhNT+VbqsW38\n9mRlgxZe+yv4oDHNAMbXTOdujQ3XyfDrecXrmg8G0zlu8T2JgVNcLysfcG5FYUYrnm8Tha3eVT4o\npUpBloiIlAMFWauJhoYG+vbp0+FcoCqyrnxNwMnAZRTO+4mlc/nMVCxNSwOzF8LtbckyMF8iy1wN\nCce4B/gqMGHiRE4744zlOp977rmHF198kbq6Ov739NN5b9GigsAjygddawEfJecUt/8KPhj8Kr60\nL84zgyyISTNGz+LnfMWAMV6fzwJPkC3a3Jp8xcwWZNmtWM4Ym1tEVfjrWKw5Riq2co/lhel7E8sN\n0/la8b1q1u+QlCAFWSIiUg4UZK0mNvnkJ5n/zjvUkGVk0iDrSaAfWae9arImFs+RBRPPAjeRzRsC\nOBMfgMT5WLG8DdoHPKPwc4niHCMHbLvNNjz57LMf+xznzZvHSy+9xCuvvMLChQs57ZRTCoKWmHWa\nSfGuhPH5GITeCTwE/JTic8bSbNhWyf20VDKdS9VZZ8JxYQxjyILWCjpujhHLOGOb/PSxYkFW3C6W\nMbY1yNDvkZQYBVkiIlIOFGStBubOncuWm29OBf7D/AQK12raF5+5aQI+B/wzPBcDorQb4Fh8titt\nv55mss4CvoMPOirwDTFqKcwAxazOM/gAYv477zBgwIDuP3Fg2rRp3Hjjjbz++uvcdvPNQOHcpmfx\nbd2vxwdf4ym+dtcN+HLC68JjacYsZuU6amXfDOyED2RjQ4w4hphhil0bhwNLKMx4FVtnKx4j7YYI\nPqCLrxHLDGPQly58HEscVToopUZBloiIlAMFWWXu6quu4oTjj2/LLsV5UmkA8RJ+XtQ2+IWFd8WX\n8e2ND4RiFiseI/0QH4OB5vD1L3xGLM4Nis0xJpAFWTG7EzMsCxYupK6ubqWcf97MmTOZNWsW7777\nLqf86Ec0OdcuoNodv6DwxWQlf2lgdh3wR/wiyXEuVT6DlJYS5lutp9mtGIQRHjP89boQ2Bl4mKzL\nYbyW48nKENOW75CtNUYY08xkTOk5KKMlpUpBloiIlAMFWWWsoaGBfmEe1iwK5/b0IWu6AIWd+2Lm\nI//B/iT8PK00mIjt22OGqpYskCi2plMM9GITh0MPPpg/hgxTT5g+fTrPP/88a6yxBt88+GCgMIMU\ns0ZpMBWlJX5pe/V8KWElWRfAWI7ZBOwJ3E/WVCS/vlU1fk7WZhRmoEYBd5NlJWOjjTi+pnAOfWjf\nqTANwNLW8wAzZsxg6NChHVwpkVVDQZaIiJQDBVllbO7cuWyx+eZUUnxuT8y2DMV/0J6C/+AfM1Rp\nkAS+3O2zZNmRWBb3ND7IiqWEDbTP7NwDfJnCcrkLf/5zTj711G473+4wbdo07r//fs4666y2OWMx\nkxVbo9eQNQCBLMD5JvBnCtcA2xu4l6wRyPDkOHE/A34A/CZ5PGa74jXciix4ip8+07bwW5JlKcFf\n/zSQ2hf/HjRR2DEyn9Vco7qahY1pMajIqqUgS0REykHFsjeR3ujqq65i+JAhbeV9O5B9uM9rBUbj\nFxiO83YqKwp/NEbh5xU5fNAUMyMtZB0ED8UHXBXhWHG7fYFNyMoDTwzHPPqYYz7+iXaznXfemTFj\nxuCc4/bJk/nWkUe2lddV4gOfWfguhE1k17QK35o+ZpK+ib8mk8P9IfgAK4aU+5J1E6zEB1hN+DLB\ntD37ZmTZsPMoLPeMr30D2bpZNeErZuFi9uqesG1l2C4GYLFsMPpvUxNrVOifBREREZGPQ5msMtTQ\n0MDaffvyUHMznwf+B59hSj9Qxw/lkDVIqKmuZsIFF/DD44/n6G9/m5v/8pe27dPSsr/gA6qYRdkm\nHOMTFLZ5j40fapLXacEHKF8DZs2Zw2abbdZt570yxbLC4773PRqamtpaoT+Jn791FPAHshLLGCT9\nN+yfZvCgfaYw36AiLkwcH28mm7NVRVbqGb/yjTHSNu8VudtpmWFaJhq/KoCB667LG+++u5xXSeTj\nUyZLRETKgf7Lugz95te/prm5mS/gP0D/jOzDcyv+Q0xlRQVNhIWEKyq49NJLeX/RIk465RQAbv3r\nX3H4ksKxZB/mq/Dt2ivwpYa1FC6mG1+nCV8OWBVeIxagVQD7h31WVbOL7jBixAiOOOIIFjU2MmvO\nHK7+7W+pwGf3aoA/4YOgb+OvcSP+GtSQtU6vpbAJRl7MalUDF4XjHEXh9Y3X8V/4QKq1/WHa3qeY\nsUoXRXb4AOt5fGCWrq8VSxFbgAXvvUddTQ0iIiIisvyUySozDQ0NrNOvH081NbWbgxXXhIorUm1f\nWclrb75JXV0dtbW1BcdYu29fXHMz/6L9XK6YVYlNIFrCYzX4NbN+Blx48cX86Pjj6b/GGjzR6kOB\nz+ODhGZgl+2357Gnn14JV2DVmjp1Ktdccw2//93v2ppTxG5/X8Cvs5U2rYgBTb5RxheBB2if3YrP\np+thxSxVnLO1Je0Dt3zTkbShRvp8zHzFphnxtyrO/6oEGvW7JquQMlkiIlIOlMlajUysqqKqooJb\n8YFTS0sLN91wQ0GABVBbW8ull10GZmxD4VyuOKfH4edfPU1WEliBz5JUAGv06cNvfv1rXGsrO+HX\n3zoLHwzMmDGjLAIsgN12241rrrmGVue45/772XXkyLbW9Y+F7y1kXRfjc7OBI8gaUdzbwfHjda0k\n68qYliM+iV9jq4nCOWJRDObiL3rsRBjny8XxPE8WAMZsWwyizfR5V0RERGR5KJNVhq6+6ipGn3wy\nrqWFVudodY5KM34+aRIAo08+OctkVFfz/qJF7QIt8Bmtow4/nFv/+te2x8bhM1KjKJzT9QBZs4u9\n8EFDdXU1TzU10YgP6sB/cL/8yiv5wXHHdfNZl5brrruOm266ibvvvLMtyxSbUVRS+L8bMWuULnBs\nwNn40sz8WluxTLCarPlIBfBvfBOSmJmK7fd/SuHiyHG+XMyunZO8Tmytn24bywiV0ZJVQZksEREp\nBwqyylRDQwMNDQ2sv+66PN3cTC0+oHrz3XfZYL31eL7J5zyWFWTF0sNG/OK46VpOsexwW+BBfJC1\nNVm2pNaMivA+xXlK/wRGdvKa5WifffbhH5Mnt60TlnYGjFmqfKe/KnyGCrJ2+7eSrXMG7UsPYzOO\n44ErKJxHF1vID8W32I/SssWYuYpdCdP5WtXA2mutxdsffLAcZy6y/BRkiYhIOVC5YJmqra2ltrYW\nM6M29/ikSy9leHU1w6urmXTppcsMdmqBfkBVdTXz33mHDxcuZJPBg9kWH2Ct078/XwSG4TNcbVkZ\n53iebD5XBfAW0NparF1D+brrrrtodo5f/OpXrL/xxjSRlV0a/hrGOVdp0BNL+uKnzQn4MsPZZFlE\nIysTjE0rPgBeIuvmGIO3U8mCp9iQIwbE8R2JLfyryDobxiDw3Q8/pFqlgyIiIiLLpCCrjHUUUP3g\nuON4f9Ei3l+0qNOyvWL7DxgwgLq6Ok4fM4aqqiqqqqo4d8IENh40iEZ8e/YYCLSSZU1a8B/YDwZs\nNc1CHnvssbz66qs45zjyu99tC36mk3UgjHOuIJuv5aDd3LgY6sTALAZFrcD1+PW1SB7bgsL3pirZ\nP21gMgtfEhqzbvG10jLG9ddee8UugIiIiMhqQuWCq4GGBh/q5DsI5h/rSH19PZC1XE/LCAF2rK6m\nqamprUV82tkuZmtiQDEN+PxqVi7YmenTpzNhwgRuvfnmtoxRzErFQCgGV+lcLsPPt7owfE/XvYqB\nWVxXazq+jLOKwq6CsXnJtmHfanxZYr6bZHwuDbROPe00zr/oom65BiIplQuKiEg5UCZrNXT1VVex\nTr9+rNOvH1dfddUyt91gvfXYYL31CrZ1LS3siP9A7lpacMBMfBZkCH6uV1VFBU8DT5Gt17RLVVWX\nShRXFyNGjOCmm26i2Tn2+8Y32ua7pWWAhMdiw4v4/dDwPV33Kpb31YTnmvABVmycEUsQm/Et/eO7\nEOeKDaN9h8L4j0QMlJuAiT//OZtvtFE3XAERERGR8qNMVpmLnQYBJl16KUd973us06/fcjW+yG8L\nsNaaazKjxa/YtHVlJa0tLcwK+20FLFi4kD9ffz0nnXgiLS0tVFVUcNGkSXz/2GMVYC3DpEmTOOWU\nU6ghy2yla201kQViMXhKM1StyXZpV8JW4AfAryic+zU87N9AYZv59Lk4dwuyroMAL7/+OoMHD+6O\n0xYBlMkSEZHyoCCrjBULkpanu2B9fT0brLdeW3fBXaqqeHX+fAA2HTSo4BgXXnQRp592GgCXXnZZ\n21yv2OUwNuKQrps6dSq77757WwfCdIHgYu3gY8v2CWTBWXX4HrNQNWSLGcfW732ArwB3kZUExmCr\nD4Wlg7ExRjwGQLN+F6UbKcgSEZFyUJLlgma2kZk9aGYzzOwFMzuxp8dULq77/e9xLS0MwWegOird\ni2WCzU1NbAvsBDQ3NzN44EAGDRzItsOHM6yqimGh/K+6uhoza7dwbW1tLXV1dQqwVsBuu+2Gc44W\n59hsyBAqyYKtxrBNLAmMLfLHkzXQOAf4Kj4gix0F44LGDtgkHK8BuJNsztZssvWx0tLBOMerNTlG\nC1CpjoMiIiIiBUoyk2Vm6wPrO+emm1lf/Pz8A51zs8LzymR1UdvCxM4x4YILGDtmDM83NdEA7FBV\nxQeLF7cLgGIG7MtNTdxFYTnaMOBx/JpZ8R3YePBg5r3xBjPDezLUjIX//a8Cq5XgvPPO4+yzzy54\nLC0rjKrwc+F2orARSb7kL2asKvFBVFxPazjZosYVZFmyGMQ5snlfoMWKpfsokyUiIuWgJIOsPDP7\nG3CFc+7+cF9BVhc1NDTwyyuvMxQ8NgAAIABJREFUZOyZZwK+ScULYZ2qYaH8L59pamhoYK0116Sl\npaVdt7mtyUrF0sWIm4E54f4Q4I133mHAgAEr8cxWb/PmzWOP3Xbj9VdfbVswOJYOxjLBuDhxGmQ9\niQ+8gIL94nwvKAyoYtYqPj4IeCPZP87/agX6mLFkNVsDTbqfgiwRESkHJVkumDKzTYHtgCd6diS9\nT+wieMapp3JWUxPPNzXhzHyZX0UFrS0tDBo4kLXXWIMrL7uM+vr6tvlT50+c2JapOoOsK10rcAf+\ng3XsLhg/DQ3FB2FG11rDy4obPHgwc195hXcXLuTcCRMK2r3H9yMGR/G92xe/qHRcVwuyro/NZFmt\nWHa4L9kcsNgI4w2yksIodib8r3P0q6pCREREZHVX0pmsUCo4Bfipc+5vyeNu3LhxbduNHDmSkSNH\nrvLxlbLYtKKtOQW+fGzH6mpeeeMNNt5gA/4VugOOIMtIVFVUcOkVV9DU3Mzok04CskxF7GYXS8jS\nTFbsYmfAoA035D9vxHyHrCrHHHMMv//Nb9qCpQqyRaBja/e0OUac1xWDspjZqiBbjHhffCA9nixz\n9W/ghvBY3C+WHDpg77335ra77lpp5ynlZcqUKUyZMqXt/vjx45XJEhGRXq9kgywzq8bPx5/snLs0\n95zKBTtx9VVXcfJJJ9Hc3FxQKuaAKjPOO/98xp55Zls2oxm/SHA/QgvwykoqKiraArRh+Elx2+A/\ntNeSdZkjPJbu3wCMGDaMp56PRYayKu2xxx489vDDbR0FY3CclgUavinG3RSWE8b5VoTtn8cHWWcB\nPyNrC58vQ4zrezXiA7l3Fy5sW7xaZHmoXFBERMpBSQZZ5lvU/QF4zzk3usjzCrI6kLZtT7MNhm/T\nfT/+g7RB27pWQ4BH8Y0MPkfWKjz9ED0K/4Ec4BjgauDF5Pl78N3qhpI1Qzj/ggs49Sc/6e5TlC7a\nY489ePjhh9vux0YXMTiOwVY+ECdsV0X2XsbOguADqRayOXjDgaXJtrERhxphyIpQkCUiIuWgVIOs\n3YCHgefIPveNcc7dHZ5XkNWBNMhqwGefngrP5TvNPYvPSg0Jj6UZjFhmBv7DdgswHbiVLHAbCxxB\nNlerBh/AtS2M28kaXLLqxMWNwb+XFfhAKbZ2ryJrx342vpQwtoWPa2lV4t/XNHAn7D+ErDEKZGt4\n9a2qYlFT2vNQZNkUZImISDkoySBrWRRkde7Kyy9n9EkntWUiYnODFtpnLWrwjS1+SpataMZ/yK7E\nR7kxEHsU+AIwIzlGzI4YMBXYlcIg681339VCxCVi0qRJnHbKKaT9/2LJqAu3Y4kgZMFz/JmYSWGn\nyVgmGAOw+FgsOazAdxz8SB0HZTkoyBIRkXJQ8t0FZfl9/9hjqaqq4nH8B+SzyJoZpF0CwQdYE8Pt\nkfgP0A54BP+hOw2NdiXrWBfFD9StwC7hdbYOr3HgAQewwXrrsU6/flx5+eXdeYqyAkaPHk2Lcxx7\n7LFAVjYY38MWCtfaqsQH4Yb/WRiWe57wXAvwZu6x+A9Lk3NMnz69G89CREREpPQpk1WmYvOLpuZm\navAlg43ADmRd52IjhHwDjJ3w6yn9Dd/soApfGnhO2DfNfoBvirEthes0HbD//tw1eTJPhXKxbYFJ\nl17K8aFjofS8z2yyCf957TVayVq0xy6R4N/nuDjxEAoDrGp858F/kM3HqiH72Up/O5sB/b5KVymT\nJSIi5UBBVhmrr69nvf792zILcZ7VT4DD8fO1YuODOH8rlhfGD9uOwpLBscD5ZHN1zg7HGgI8CKyD\nD6gqKip89iyUirUCVlXFB4sXq3SwhMSfkZjZjME3tG9+En/j4s9FDYXzsQz4ATAa2JKs1DD+/DXo\nd1a6QEGWiIiUAwVZZe7/HXIIN//lL9k8KXxG4kn8Cs+V+AxVbHYQPzxDVhoYP4DHjoQN+JLAymTb\nWHIWm2S04NvFzwzv05Cwf/3SpQqyStD06dPZbrvtgKwRRgyQCN/zTTFimejcsE2cj7UVfi0tctup\nEYZ0hYIsEREpBwqyylhDQwNr9+0Lzc1tZV/Dab8Ibb6de9p1MF2EOHami/N3IMtuxExZdfi+VThm\nDO62xn8Af/n11xk8eHA3nqV0p/r6etbt37/gPQb/3tfgs1b5hYjBt/OPQVYFvpX/38gyYLERxvQZ\nMxg6dOjKPg3pxRRkiYhIOVDji//f3r3HSV3W//9/XDM7u2iyqAlJQpmQIgdFJCvTRDQ/mqafBFM+\nZeeyr5qAB1QoQVM8gnj82CerT1qpqf08pmkqpfkpFQUBRcVO4gnMZDF1DzPX74/X+5r3NbOLAju7\nOzv7vN9ue9s5vGfm/Z4ZuL2f+7qu11XjnHNMo33DizBMcAV2AtwcPeaUaJvQMOMA0pPlfPTYsE2o\nfPwpuf2p5PqY5CeENalujY2NtHrPr2+9FShrYoF9T+aSfv5gwWoEsC3pfL3lwHdI53o57DswatSo\nLj4CERERkZ6nkFXDGhoauHjBAhbU1eGxuVjrCzq7YCfKdcC9WCUC7MS4kNzmsMXL6qLHhbbfS6Ln\nLgY253gMeJh0npf0Doceeijee67+8Y8pYEGqgH1PwoC/60jX2nLAS8AWpOtqPYB1nAyV0Dz2fRk6\naFA3HomIiIhI99NwwT5gzZo1DB40iAwWhlqwDoJBqDLFDS5uBw6htEoFpQ0xIA1cocNgMArrTBce\nV+xomMlw6WWX8e1jj63Y8UnX+9C22/LSq68Wh/1BWg2F0qGl4fZw2+bA21hQI3n83zVsVNZDwwVF\nRKQWqJLVBzQ2NhaH/e1OGrA8cDzpyXHcjuJg0qFipybbhjlWheT2JViQasOaaJyaPPZR0uGCALOj\n6zsVCkyfNo3m5niAolS7f7zyCq+vXVusarV1sM1M0kYoO2EVr/8D3sK+M6HqmQWGDh3a5fssIiIi\n0lNUyeoDQgOMtrY2cqQtt0OlwZO27YY0HC3GgtdOlFYtdsKGiMVrKIXg5YCHsIWLw/YjscWNJ2BV\ntAzqMtib3X333Rx80EHFzxvSIYLl3624Q2HgsZA2dNAg/vHqq92wx9KbqJIlIiK1QJWsPqChoYG5\n55+/3jlR8RyrJVi4KgDXYPOrssDJ2Inzjsl2edJmGg6rYJyaPG6PsucvAJ+Its0jvdmBBx5I3nu2\n2XrrYtv/AqWLFUM6D8sBf0y22Sm5zwEvr17NqlWrummvRURERLqPKll9yGEHHcTdd99drFy10b5C\ndRown3TNLJJtTgbmUdqyPVTB5pCun0T0mLDeUhvp+lkFoC6b5Y1//1uVrBrQ1NTEVslixlnSv9qM\nwapaddj3IgwvzJF2uMwk9+nfssRUyRIRkVqgSlYfcu0NNxSDDpQOEQyd4s7H5taE9uwPJ5fPxwJT\naN1dwLrH5YBzgMeS20OwymMn0K3J68wirXice/75Clg1orGxkbz3fO1rXwPSz34p9n2YRdqBMHw3\nQvOUMJxwxx126P4dFxEREelCCll9SGNjI4cefDBgJ7ffx058d8IWlw0Bai5pG/a9sABWX/5kyW37\nYVWK8cC1WKhyyfU6bJHa5clzhgra5COPrPixSc/6yU9+Qpv3xVbv0H5NrXj+Vlt0/bm//pU1a9Z0\n5+6KiIiIdCmFrD7kf668kt/ec09xmNZcrHnFY2XbtWLrIdVhX5A52DDCDKXzsPYEfoudQC/FKlrZ\n5L5HKe1A15o8nwNee+21yh+cVAXvPXfddVe7NbXAqllPJpcd9v0I3QY/qLWzREREpIZoTlYf0dzc\nzNb9+7O01U57d8RCU5iPtTPpMK7QrOAQ4M7k/tDOvQU7KV6BVSp2jZ5jDBbYdiXtNhhMByZjXQfz\nwMfHjePhRYsqfZhSRZxzxWAN1sofrGoKpXP+PLB5fT1r1dq/z9OcLBERqQUKWX1EecgaRemQLUhP\neuPGBM8kl0dg1al60mDVDIwjrUrMBg7HKhiQVirCa4R23uF1Xly9moEDB1bmAKUq3XbbbfznYYcV\n2713tIBxHO5XrlzJsGHDemRfpTooZImISC3QcME+oqGhgbnnnccILGDlSZsQzCJt4+6BvUmbYlwb\nPceM5HcmeY5dk+dpSR53VnJbqHplgJNIW7zPJm1+kcc600ltO/TQQykkfxAplN2XIw3doTvh8OHD\nu3X/RERERLqCKll9SHNzM439+hW7BDaTzr36HjZHqwU78Z1N2pY9m9x/JmlHuAzwdPK8I7Bg9iC2\nzhZY2GoF+mGNL9YBHycNdwCvr11LY2NjFx2tVJvddtuNZYsXF7sNzsSCefwvuQ344MCBrFq9uid2\nUaqAKlkiIlILFLL6mAXz5jHj5JNL1sYCqzQtxcLQ+Og6wEjgz8ntN2Dzt+K5WCOw8FRHWgELFa4c\ncDDp3K4tgTewsPbvd95RK/c+qM65kiGk5d+j0H1wtYaT9kkKWSIiUgs2ebigcy773ltJtZl20kkc\nMXlysUvgQVgwCl3g6rET37grXAHYPbl8BFaBCJ0Gx5CuheSxboXLkss57KT5TtI23m9QWs2SvqfN\n++J6WuUypN+NQYMGMXrHHbtvx0REREQqpDNzsp5zzl3onBtZsb2RbvGLG29k8fLlFIAFwOnYie0I\n0kYWYPOuRiSXD8ACWBb4DdYt0GPztC6gNDQ1kzYzWF+YygAXnndehY5IepsQtML3bgQ2RPUZ7LtR\nh4X05557DudU1BAREZHeZZOHCzrnGoGjgK9i594/Aa7z3nd5NwMNF+y85uZmBvTrV5xjFaoK9cAi\nYDfsZPdULES1YmtlfRU7IW7FToLBKlT/xBYuzmJDvUIzA5Ltn0suh4YY+eQ5pkyezC9uvLFLjlGq\nXyYJUFnSTpZhKYBRpCG9DnhTw0v7BA0XFBGRWrDJlSzvfZP3/n+893ti5+JnAK84537mnFOLsCrX\n0NDApVdcAdiJ7JmkAakBq261YgFrKRakzgN+mjzekYao64BPJ88TWrnnsC9XFngFuD25789YiPPJ\n/TfedJO6DPZhBe+LldNQ0ZoJfJa0mlWPfdf69evH5P/8zx7ZTxEREZGN0ZlKVh3W0+BrwPbANcAv\nsYLGXO99l02mUCWrcpqamvjA1luTyedZCnwTeAg7uR2OdRCMGxOEta9yyeUg7lYYt+bOky5uHE6m\n66Lb86jBgUDOuWIb9zbsO1L+vQsy2HBDqU2qZImISC3ozJysZ4HDgAu892O99/O99694728CfluZ\n3ZOu1tjYyNlz5xYbXVyMhaOHgZXYEMFQYXDYyW8G+AxpiAqnuw2kCxMvJW2AES9Cu4K0ChZaeauN\nu8w84wwgXbutI9nkx2OhrLm5uXt2TkRERGQjdaaStZf3/qH3uq0rqJJVeR8fO5YnliwhB+yIBaQQ\njH4EXETpnJmwAHEG6I+1fg8nwAXSKkTYtkA6L2tUclvY/tEnnmDs2LFdeXjSC+ScK1Y960jD1nbA\namye1q6kAb0AzDz9dH4wd24P7K10FVWyRESkFnQmZD3uvR9XdtsT3vvdKrJn7/7aClkV1tzczFZb\nbMGitjYasLWwIK0sxOsZjcZC0p3ARyld32gO6QKzYcHZM6PXiTsOuuR5RgwbxtMrV3bNgUmvknGu\nOBw1dKmsw+b5TcH+ABDCPcnlBuf4d6HQwbNJb6SQJSIitWCjhws65z7pnDsJGOScO9E5d1LyM2dT\nnk+qQ0NDAwsuuYRx2SwjsC4m07BqQR2wPxamdsaGA2awsaLXJY/PYqFpLjaP6yNYgJqLnSCDNdLw\npMMGQ9h65vnnueiCC7r0+KR3WLZ8OWDflSwWqsCC+kjSZiphPS0HvOU9zjmef/75bt9fERERkY5s\ndCXLObcPsC9wDHBVdNc64Hbv/XMdPrCCVMnqOs3NzUyZPJk77riDDBaywslsDjv5jRsSeGze1nzS\nIYTPAouBI4Ensblacdv3FdiXJSxwDJB1jqa331aLbilpgrECG2Z6EO2bYYTqaRiiWge8f8AAXn7j\njW7fZ6kcVbJERKQWdGa44Ie993+v8P5s6GsrZHWh5uZm3tevHxlgCdYxcCGWrOuw+VqQzreqw0JY\nqFSFcJZN7gOrfrVF1+Mhg2Fdrbe1DpJgHS+3HjAASBcm3hxoIg1ZO5N+h8IfAuqx4HX8d7/L/Esv\n7c5dlgpSyBIRkVqwKcMFL0kuXu6cu73s57YK75/0gIaGBs4++2y7jM2z+nRy32ewKsIYbL5VPfAH\n0kYWYGErQzrnqiW53EBpY4wV0XUPWi9LAOs2ufu4ccXOlS1Y5RPsu7cTpcNOQ6gPC2ovuOwytt58\n8+7daREREZHIpgwXHO+9f8w5N6Gj+733CyuwX++1D6pkdYPhQ4fyj1WrADgJmJfcPgtbmDiPha2l\nye2hKhWGbj0DnIMtoPYM6TpaYUghpMO+skDj+97Ha2++2aXHJL1DqGZlsZAVhpn+CFsgOwwlhHTY\n6geAV7HvYC65rVX/T/Q6qmSJiEgt2OThgj1JIav7PPTQQ+y79948A0wClmMnt9cCP8CqCPHJboG0\ninUGcAjwMaz5xVzSIYUk24RSah47OV65ciXDhg3r4qOS3uAT48fz6KJFFEhDFqSVrPDdCY1VQhfL\nuM9gFmjSMNReRSFLRERqwaZUspa+y93ee79L53Zpg/ZBIasbbbvllvxz7Voc8F3gUiwgPYoFqPKK\nwulYpasVq2iNwCpZ5U0LZmCLH4fhhQXgWYUsSaxZs4bBgwYVh6GGf/HhuxK+X08C47A/ADRj1dWw\nllZojHHJggUcN3VqN+69bCqFLBERqQWb0nL9c8nPXcnPfwFfBH6TXJca88obbzBhwgQAjgOGJ7f3\nB/4DC00jsIrCM9hwrtCRENJmF0EO++LNp7TylQGOOOywLjoK6W0GDhzIhz/0IdqwQBWqoE9hgT2H\nfW/GYKH9OixsZZL7QkOWDDBt2jQumT+/249BRERE+qbOdBdc7L0fW3abFiOuYdsPHsxLr7wCwGbA\n29jJ7PbYHKtnku1GkK6bFU6MZwAX0X6B4lOxsNVK2rxg9erVDBw4sMuPR3oH5xw5YDDwMu2Hp+ax\n7xXRfaHzZah6Beeedx4nn3pql++zbDpVskREpBZ0ZvFg55zbK7ryKdLiRac45w50zq1wzj3nnNMZ\nUZX428svs+Pw4XjgCeD/YSeyz2KhakzyExpghJPf0Ib7Q7RfoPhsrHFG6BIHcKkqDhK59dZbKWAB\ny5NWTrOkCxPnO3hc6EyYTS57YOZppzHpc5/rjt0WERGRPqwzlazdgZ8CA5Kb3gC+5r1/vFM75FwW\nK4rsD7yITf2Z4r1/OtpGlawe9JHBg3nxlVfIAXsB9wOnABcm988BpgCjsLD1JLArpXNowgLFbVgD\njSnJdbCT4TfVrEASzz//PMOHD6eOdF6Wx75Ds7CqaFiXLW6qUr4WG1gzlnOAHYcPZ9lzXb5uumwC\nVbJERKQWdLq7oHNuAID3fm1Fdsi5TwKzvfcHJtdPS57/vGgbhawedub3v8/ZZ5+Nw05i4yFZz2Dz\nY8KQwJ1Ih3HVkVYdtgNWJdf7kZ4wtwKfP/hgfn3HHV16DNJ7bOYcbdh37UBs8mcI62FoYAEYBLxC\naTfCEdh3KgwpDFWt/g0N/Oudd7rrEGQDKWSJiEgt2JTFiI9Ofp/knDsR+Abwjeh6Z20HvBBdX5Xc\nJlVk9g9+wBcmTy4uGHsPdgK8PxaqziRdLDbM1ZoOvINVFR4AvpncngW2wapZ4fqtd96pxYml6M77\n7itWoxZg351dSRfFDg0uXlvP4x22jtaK5PIBwLrmZvZLGrqIiIiIVNKmzMnaPPndfz0/naUSVS/x\nixtv5O8vvEABO2l1wH20nx9Tl/xcnPzOAROAs4D65OdVrOIQr521YsUKRAAmTpxYHAI4Avgx6Zyr\nM0k7W7roJ8zd2g773r0MXJVcvjfZ5sHf/57tt92W5ubmbj0eERERqW3l3bXfk/f+h8nvORXfG/Mi\nMDS6PhSrZpWYMyd9+QkTJhRbjEv3GjJkCEdOnsz1N90E2JCt0L49rJsVGl/ksCpWaNvusaYXkA7p\naoi2mXX66dx7333ddixS3ZYtX86uo0aRx74/DwOfxL5XU6LttsAqpu/HwvuLwMFYtfVi4GRsrbcW\n4I/Ap159lS369eOiefOYemIlivGyMRYuXMjChQt7ejdEREQqqjONL3bA1qbdnjSsee/9oZ3aIefq\nsD9K7we8BDyCGl9UvXkXXMDpSWvs0N79eOASbPjfbKyrYGjp3kb7eTMhkIVPtg14Ww0wJNHU1MSA\nAdZnJ3x3JmGLEIfbwvIAYQ5WmH/VEN1XwJqyPJXclwUeAvYEvjB5Mr+48cbuOSDpkOZkiYhILehM\nyHoSuBpYRtr3wHvvf9/pnXLuIGzqRRb4sff+3LL7FbKq0BWXXsrUqVOLiwuHMJXFhgTGVatweziT\nmk3aYfBTWIWhDfjTn//MHnvs0W3HINXtiMMO4+bbbiv+VacO2A37S0x518rQbTAEd4dVtH6LhTCX\nPD5sG4a5vrZ2LY2Njd1yPNKeQpaIiNSCzoSsR7z3PXL2q5BVvZqamthmwADqsGpWOJGF9ovIhoVi\nHWlzjJ2gOBysAAzeZhteXLOmm/Zeql2oZoUq1feAc0krVpCGqhOxZQUcFqLCfeEPAC1YufyB5P7l\n2Hdzi8024/W33uqW45H2FLJERKQWdGYx4succ3Occ590zo0LPxXbM+mVGhsbufyKK2glXSw2blgw\nAqsmhAGAof37CGBn0vlbIZytfu01Ljr//G49BqleYehoqEydgw37+3Ry25LkegFYCJyebPd9LLy3\nYRXVWdh37YHkdyvWGTMLrHv7bbbbZht1txQREZFN1plK1nnA0cBKomWSvPf7VmbX3vW1Vcmqcs3N\nzQwZNIi1TU3siFWx8thJbAOlQwfz2IlwPTb2NNw+ATtRzgNvaW6WJK645BKmT5tW/D6tAP6JDTNd\nga3RNifZNkO6rlbYfgkwjnQuV1xZ7Zds9w4W2r505JFcc/31XX9QUqRKloiI1ILOhKzngZ299y2V\n3aUNem2FrF5i82QR2XASuy22WGx5wwuS389Gt4fwVQD++6qrOOaYY7prt6WKhSGD8VDUHDAQ6ySY\niW5vA+4H9kpuC4ErQ+l38DvAtORyAxA3dNccre6lkCUiIrWgMyHrFuAY7/2rld2lDXpthaxe5IB9\n9+V3CxcWhw6GwAWlDS/CJxrWyiqQztkCaNVnLliVdPN+/YrfkzA36wLgLdp3rcwTtT+ldFkBSJcM\n2An4KxawpgP/L3n8qJEjeWJ5qHtJV1PIEhGRWtCZOVlbASucc/c4525Pfm6r1I5J7bjngQfYL1nH\nLDQgCOtpTSnb1mEnvU9hJ8oO2CH5ffnll3fD3kq1a2ho4NJLLil+lzw2N2sp1mWwIzsm27WSBveW\n5OcMrPHKs9jyAxls6YGrk8cufeopvn/66V1wJCIiIlKrOlPJmtDR7d77hZ3Ynw19bVWyeqH3ZTK0\neV+sWA0Dnk8uxxWtPDY/63vYukZgJ8gFIK/PXbBq1oDNNydfKBQrUyuwKtSu0XZxB8uZWBh7PzaH\naxq2OHHobDkGC10nA9/CvosfwBY09sDQwYP5y0svdfGRiSpZIiJSCza5kuW9X9jRTwX3TWrMvwsF\nHvzzn4sLEj+PBaq4opXB5sTkseC1grSilQE+ufvu3b3bUoUaGho4e+7c4ry9LDAaC1ihYuVJK6Ie\n+ETy2New4LWAtOvlGCyEOeAiLKx5bDX0wVgQW/Xyy0z63Oe64/BERESkl+tMJetN0mk09dhUiDe9\n910+Q1yVrN6vwTk8acc3sC9THaVd3/oDD2Enz23YSfC/1IhAgFWrVvHhoUPJQHHdrPDdGUbp3Kyd\nsO/P2Vig3zF6nnjZgDYoLj8QSike63J5AFbp+qe+f11KlSwREakFnalkbeG97++9749NZTgcuLJi\neyY1rdl76rMWrzx2cgsWuoIc0IRVGSBdSHbrAQO6aS+lmjU0NKRNUSj97oTQFNZfc9j36THSzoGh\nChbWyWope2yopDpsOYEDksuXXnwxzc1x/0ERERGRUp1pfFHkvS9472/BOiSLbJA329o443vfA9KS\naFiYOAzfqsdObPPYlzUEreu1dlGfN3DgQMbsvDNt2PcnC4zCvj/hP7YwHDUMO72TNLRD2u3yYeCe\nsm1/ALyMhbMscHvymDlz5tC/Xz+uuOSSrjs4ERER6dU6M1xwUnQ1A+wO7OO9/2Qlduw9XlvDBWtI\nc3Mz/fr1I0e6qnVYnHgmMBerPoQ2288nl9v0HRBg80ym2BClADyJzesbgVWoylu6T8TWzgL7nsXr\ntLlk2yNIF8zeCvhX9PgV0WPnX3IJx51wQsWPqS/TcEEREakFnQlZ/0t6ftIG/A34kfd+dUX27N1f\nWyGrBvVLFi4OJ7shaB2AVSAgnSdTHF6o70Gf1tzcTONmm1HwvjjMb1ly3wgsdNWRzvsL3684dI0D\n/pxsNwerYBVIuxXuglW63p9sPws4OrnsnKPp7bdpaGjowqPsWxSyRESkFnRmTtZXvfdfS36+5b0/\npzsCltSud7xn8DbbFNfQKmAnuXeSDuGqI12kOAvknM7F+rpMJlNsojKL0iGDWey70oJ9p85IHhPP\nqAprazmsKcZ9yfXrsPI8QBicmsOaZxTndXmv+VkiIiLSzkZXspxzl0VXQ9GheN173+VjZ1TJqm2r\nVq1ih6FDi90Es6SVh7CWUZ50DaPpJ57IvHnzemRfpectmDeP6SefTC657ikdMhiaWzwe3Rb+48pi\n36WdSVu9u+h3XfKc4bv4fWzttrbkuVwmw99feYWGhgZ1HKwQVbJERKQWbErI+irpOciZ2B+Hi92O\nvfc/q+QOrmcfFLL6gKxzZClN8mEYYQY70Q0d4jQ/q+9qampiwIABJY1R4uGAYbHieO5VGxawno22\nmwj8FqtWPQp8jPYt4Pu8hroRAAAgAElEQVRhlbHW5HW2qK/n7RbrS3jE5Mn84sYbu+Yg+xCFLBER\nqQUbPVzQe/+/3vufee//F3g9XA63V34Xpa/Ke88+n/40BSxM5UkrCsuwFttZ7Eucc07DtvqohoaG\nYtOU0Hp9DBactse+NwXgVNIQVkf6n19YePgPwPTktlui57+OtAV8IXp8FninpaU4lPXGm25iwfz5\nXXKMIiIi0rtscuMLAOfcE9773Sq4Pxv6uqpk9SFNTU1slayNFapYS4DxpB3gQqXhP/bfn7vvvbcn\ndlN60BWXXMLUadPIkDasGAP8CpiEhaI6LHDNxjpWhmpU+J/EYfOzxpOGtTOT+8orY89E15dgQwfH\nAL6ujn+9+aYaYXSCKlkiIlILKrJOlkhXamxsJO89OewLW8A6vrUm94dKQx1w3+9+R0bNMPqc46ZO\n5dBDDsEBo7GOgRngKKzi5LDvi8cC1lLSOViPRpfHk4auKaRrY8XaKG2csSvpum5tbW1cfdVVFT02\nERER6X02ZU7Wm6TnIZsBb0d3e+99l8/+ViWr77r//vvZb7/9iu26w3ytuDoRhhfqO9J3NDc3079f\nv+KcvdCCHSx0tQKnA+clt8WVqUeB/qRNVcIcrqCBNFRlSOcB5rBgNSd5vX7ADOB8VbM6RZUsERGp\nBZsyJ2sL733/5Kcuuty/OwKW9G0TJ05k99GjgXSOVnl1IoNVtepV0eozmpqait+FsOYVWDgKFaxz\nk9+fwcLVCKxD5cewgDUjeUwOeIB0HldodJEnWTYg2e7h5HfoUrg/cAFJNeuHP+yKwxQREZFeolNz\nsnqKKlnyvro63srnO+woNwZ4LPmdx4Ybrl27tmd2VLpFU1MT7086DMbdKMP/EvsAvydt2e6Tn3rS\nZhb5ZNsssBzYF3gZOBgbNhjme0G60HH5bcX5Wbkcr69bp2rWJlAlS0REaoHmZEmv9PLrrxebGYTF\ni0N1Ymbyk8GqDm83NZF1jqampp7aXelijY2NTDnySNpIW/t70kWsf09a+QzD/Z7FulQWktvDtnms\nkcqLyX13YlXS+D/LHKVNM4JfdcGxiYiISO+jkCW9UmNjI+PHj6cFOxGGdOjgbOzEOJw0g50Qv3/A\nAJyGENasa66/nhHDh7cLPqFF+4nRbeE/vnWk35/YKErX1pqZbDeCtMlFmP8VbpsNnIMFtAsuukhV\nLBERkT5MwwWlVwuhKQwDC79ztG9uMB4LYgAPPvgge+21V7fuq3StNWvWsO2gQcUhpKETZfifYjbw\nEHAflDTIgLQqFZpZnJlcfxLrZBmGo14LnE1pFSsHLMKGCe4M4BxNb7+tkLWJNFxQRERqgSpZ0qut\nXLmSHOkJcvhCx8MHDwbuIO0IlwM+vffeqmrVoCwwMrkc5l2FiuaZWMDyWLgqRPd5LJw/hrVuJ7m/\nATg5ev6jk99hyKEDZmEBPqyhhf4AJCIi0ucpZEmvNmzYMLbs379YkfCkneXCyfQd2An2CqyaAWmz\nDOccs2fPRnq/gQMHMn7cOJZjn/0pHWwTOg12FIMy2JpXI5LrDhsGeHFyPYT2uEpWIG3hPivZLo+1\nlBcREZG+SyFLer3VTU30r68vNjCI18/agnSIYDM21OtgrOJRh1W15p51Fs45nRjXgIcXLeLl1avZ\nbvBgzgemY+tkhSrTYux7kcG+ByE4ARyCfS+CsCZWHmvlno9ur0u2rSftTHgBaYjfcsAAFsyb1xWH\nKCIiIr2AQpbUhD/8+c/Fk2BImxa8lVwPVYlWrLJVRzpULAz72qxfP7bbdttu22fpGg0NDax6+WUy\nWBUqrl71B47BPu97SENVqHiGClf4bhSSbb4GfJo0oIUgv4x07t/D2HDDEMJOPflkvnjEEV12nCIi\nIlK9FLKkJowdO5bNnSuZk/UkdoIdqlZhHk1Hwonxq6++SsY5Lrzwwq7eZelCbVhAWgJ8j3TB4J2B\nK5L7WiitTgHctZ7nGgEsxL5XS7FGF+XGUdrV0gM33HSTlg4QERHpg9RdUGqKS4JWqDhAOnRwBTZ0\nLB/dDjZs7B7spLuNUqtXr2bgwIFdus9SWV8+6ih+fsMN5LBgFdbAAmuK0YwF6rAY8bLkvhHYdyOs\nv0by2EeAPbDAXlf2XPFcwDbad7VsA/7xwgsMGTKksgdZw9RdUEREaoEqWVJTXnjhhWLICo0JwoLF\nI5Lbv4EFqtbk9nuwtt1Z0u6DoVPhBwYNwjnHmjVruvlIZFM0NTVx/Q03MBsLPouwzzIoYKGpQMeL\nCT9OugxAc/L7ZtJhg5/Evkejge8nj2/F1saK180aEV0/8fjjK32YIiIiUuUUsqSmDBkyhA9ttx1t\n2AlyIfn9LHZC3AJcjTXA2Bs7CW4BfkBpS+8gg52kDxo0iIFbbtldhyGd4IHzsc+2ATiANPhkgfcD\nh5IG8THJj8MqW6cmzxG6CJ6fPC4L/DF5jVasY2UYivo0sH9yX9gW4A/ALbfeyoL587vkWEVERKQ6\nKWRJzXl+1Som7LUXWdJKxQjsBDoMB5xLOq+mgJ00r08YEvbPtWtxznHxxRe/y9bSkxobG/nC5MmE\nPpGjsXlSS5Kf+LbBH/gAHmtW8Rhp4AoLEcdzq25M7n8WC1MF7D/P75NWrMIsvnAdrLtlDph56qnq\nXikiItKHaE6W1KTnn3+e4cOHFxsehKFhYShYkMVOlltJOxKCnWw/nVwOTRTylLb4fnL5ckaOHIlU\nnxOOO46rrrySR7EhfvG8qwJppSpH+t1oSbbZFlhN6dyqbwP/U3ZbmOt3EHA36dDUEORDM5WZwNxc\njtfXraOhoaHix1prNCdLRERqgUKW1KxBjY38c906MtiJbwYbPrYM+Chp6KrHOsY9CvxX8thwgrw8\nuR6fVIdAFubp3HHXXRx44IHdcUiygZ566il2GzWq+JmF/y3CfL2W5HI91jVwb9KKpcPmWK0gqUJh\n1S1I53e1RtuGcN6GfY9agN2j++uyWS659FK+feyxlT3IGqWQJSIitUAhS2ra5pkMzd4XT64hrUZ8\nlPREeylwEjaMLISobLTtGGxI2a6kay6FylZoDf/4E08wduzYrj4k2UBbb745a99+mwLQWF/PWy0t\nPIkF7RGk4SifXI6rVGG+Vrw9pGHtQx/8IKteeqnYpbAN2BJ4I7nfYXO7pgC719XxrzffVBVrAylk\niYhILdCcLKlpbxUK9MtkivOuQpfBUdjJczhB3pF0jaPnSTsThoYJM5Ptc9iJd2iKEKphALvtthvO\nOS6//PLuOTh5V6+/9RaHHHggOeCdlhYcMB64Lrn/lNNOK1Yjg2bsM30I+6zHYwE7fNZh/tZfX3qp\nuGZWGIr4L+y7tAQbanoecA2gPwiJiIj0PQpZUvP+nc+XrGcU2ncvw4aBhflWsVy0Lcl2cdgKc7lC\nJ7kwLA3gxO9+l3rnWLVqVZccj2yYpqYm7rr7bpaQrm+1FPss88CTixcXq5IHYwsV74p9jr9JfsdN\nMRywZ/JTXmaJ28SHepUD5gH5fJ6vf+lLanwhIiLSh1TdcEHn3IXAIdjUhueBr3nv15Zto+GCslFW\nrVrFh4cOLVYkMljFYTx24r0jpX9xGIOdlLdSOnwQ0kYa5YvYZpNt60mbKNQBK1auZNiwYV1zYLJe\na9asYbtBg0o+Z0jn12WAD267LS+98kpxeGA8ZDB83nlKF7S+DphDWt0K87bOCgthe198zAqsOrYL\nmpu1oTRcUEREakE1VrLuAUZ573fFOiaf3sP7IzVgyJAhbDdwYHFulsdOfFuxuVihkUVYXytUPULz\nA0hPtltJO8gFfyKthoWA5ZLtdho+HOcct912WxccmaxPY2MjWaw61UY69HM28AwWgF965RXyyf11\nZY//E7Y4MVg1CywwnYN9J0LYLmSzzM3lmL9gAYdPmlQM5mCBbHyy3Qn5PNOnTVNFS0REpA+oukpW\nzDn3eWCS9/5LZberkiWbZHPneDu5nCVtux0qGMPouOlFOC0Ow8ZCw4NwP6SVErCT9lDlCPO+csnj\nb7jpJiZNmlS5g5L1+p8rr2TqCScAcPbcuZx26qk8k9w3GgvEDvts/gOblwfpcMBQwToA+J1ztCZN\nVOKK14urV/OrX/6SGaecQktrKw7rVPmxZJuw7WigkMmw9q231ATjXaiSJSIitaAaK1mxr2PTI0Qq\n4q3kJDkEqfKoHq+bNAILUAeQdiEM4aoFq1bkgcWkVa9wQp2l44CVB46cPBnnHOeee27XHKQUffvY\nY3nj3//mjX//m5NmzGDKkUcWK1p5IJfNsgv2GcWLFoeug6GJxW+BQz73uZImGUFzczOnnHwyj7W2\nFite/YHypv5tQL5Q4Ftf+UqlD1NERESqTI9Uspxz92Jrfpab6b2/PdlmFjDOe9/uT/7OOT979uzi\n9QkTJjBhwoQu2lupRfXO/lAe5uaEfwUO+CxwB2nVqrxyEYaChbAWQlS8zRLS1t9heygNW+HyT6+5\nhqOPPrqShyfvoqmpiaamJhobG7n2pz9l+rRpLMHWtorn2bUBfwbeT9rWHdJhggD55HtU8L54exg2\nWv4/60HAxclzvbZ2LY2NjRU/tt5o4cKFLFy4sHj9zDPPVCVLRER6vaocLuic+yrwLWA/7/07Hdyv\n4YLSKU899RS7jBpVstYVWFXqDuAs0vlXcYDamdJAFuZfxd3l6ig9WY87D4bHxnO6wutfd911HHXU\nUZ07MGlnzZo1AAwcOBCwIYTTp00D4IILL2TGKacws7WVc0g/l3gBYwdsBryZXP4ecD5pQ5Q60jlb\n44GHk9+PYZ0IZyTbtwGzsDldClnrp+GCIiJSC6ouZDnnDsQ6H+/jvX9tPdsoZEmnbdnQwFstLcWK\nlY9+h+rVOmAP0gWIQ4c5SKtUYQhhPrkcV8YOAn5H+852ofoVmmMUkuttwP879liuuOKKLjnmvmbP\n3XfnscetfcX4ceN44OGH2bp/f5a2Wn1xTC7HOeedx4yTTirpBAgU527Fn3M48w/jrF02i8vnS0L0\n/2HzsUJ1zFH6+R8xeTK/uPHGyh9sjVDIEhGRWlCNIes5bPrL68lN/+e9P7ZsG4UsqYicc7RBu6Fe\nddjaSaERQhjyVz4sME/amTAMLQzbZrGT63gY2his+hU6FYbtSJ4jNMsoAIMGD2bmzJkcf/zxlTjU\nPqWpqYk1a9aw8/DhJZ/XX154gZ122IHHkpA1Ppfj5ddeY/A22xSD12jsM4xDVhv2XXk6+X8nhOXd\nx47l8cWLS16jjnQx66DYRCWX4/V169T44l0oZImISC2ousYX3vuPeu8/7L3fLfnRojLSZVq9Ly4e\nGzoNZrAQdCdpM4tQdXKkrcAz2LDCetJFiecmzxFC267YCXtoojEzeVwu+gnhLjwuNNRY8/LLTPvu\nd8k4x6hRo7rsPag1Xz7qKLYZMIAdhw9vd19DQwOTDj+cXbHPZtLhh9PY2MjFCxYwJpdjBDakbxfS\nz9kBQ4H4Dzs54Elg0eLF5HK5ktdoxr5LoYkGWLgak8tx8YIFClgiIiJ9QNVVsjaEKllSaVnnisME\nQzUqrlqFCpRL7nNAP9oPBQvzdIJQzQhrMIUhh3XA8uhx4b4wjDBcJrrugX0mTuS+++7r3MHWsKam\nJrYZMIAVWAXxLdKK4bixY7nn978vqVrFlaXm5mauvuoqZpxyCgDfnzOH782axe+BwcDoTAaXzdLa\n2spsYAr22V04bx4zTzsNgAsuuogvTJnChwYPZnne6qKjslleff11GhoaFLA2gCpZIiJSC6qukiXS\nE/JJa/cwJyvMs4orUKGFex3p/KnWDp4rDBX7JWkr97bo9jB/q/wxIYCFxY7j12lL7vv9/ffjksrW\nQw89VIlDr0nPYY0qFgN/xN7bJ5ctY/A22+Dz5e++aWho4LipU3l93TpeX7eO02bO5MorruCApAq1\n4LLLeH3dOo6YPJkzse/GUUceydQTTyw+5rgTTmDgwIFccumljK6rY3RdHZdceqnClYiISB+jkCWS\naPO+WEEKFaiwJtZcLGiFP6+HgBWC2AhgKyyI5ZLfRwNXJttlo+cLww7HJD+hoUIc4OpJuxvWRddD\nN8TnnnqKiXvvTZ1zXHvttRV+J3qvxsZGjjrySA7G3tPdgF8ll5e1tbG0tRWPVZfKh+81NzfT3Nxc\nUnH69rHHFgPUt489loaGBn5x4428tnYtr61dyzXXXw/QYZXKOYdzjof+8Ae27t+frfv353+uvLK7\n3goRERHpQQpZIpG2pKIVQpHDAlcLcCYWdA6htELVmvyswxauXRE9/rjk8pnJ88QNNloobYJRIJ0D\nFjfFCEEP0gpbf+Bm7B/wV7/8ZZxzfP3rX6epqalyb0Yv9aOf/YyGXI4x2Ht7cdn9+UKBtnyetta0\nDnnFpZcWg9AVl15Kc3Pzu75GY2NjSQv2ENDAhixOPeEElra28lhrK9ffcANLW1tZ2trK9GnT3vO5\nRUREpPdTyBIpk/e+WMmK27sXsPbcd5OGoTDXKixKDNb4oA2YjVWgMsnl64FfkLaID8MAWyjtRBcL\nj88m24ROiOuAz2MhIrR///lPf8qWAwbgnOMrX/lKp96D3mzNmjXk83mWYe9fA/YZjsxkGIF9Fs9g\nn920qVNZMH8+06dOTYPQ1KlstcUWXHT++Xzv9NNp3GyzYhUqhKmwoDHYulshoH3xiCP4wNZbk8/n\nacaGjMZaW1v5+pe+1G3vhYiIiPQMNb4Q6cBDDz3EvnvvXdLeHUrX0LoOq1AR3RcvYltP2hRjJ9IO\ngpA2z8iRVqnqo8c64AzS5grxgsZxsAqvGzfJCNsVgKEf+QhXX301EydO3Lg3oJcK62KFYZWhcclO\npPPcQmv2MUAhm7VhfW1txc9qZ2AkaWMSB3wQeDVpfJFva8MnQ0uPmDyZW269tdhIY0TyuiOx7oMO\n61aoxYg3nBpfiIhILVAlS6QDe+21V7GlOqThKlS2RmMBK1S0IB062EY6nwosjIU5VyGETSMNWNno\nchh6WMACVvAkVoEh2t5j875Co45wWxiGCLDqr3/loP32I+McU6ZMqemhamvWrOGxxx/nUdKwCun7\nn8M+wzCHrg04/POfp62tjZlY6AphbDmlQzf/DrQVCixtbeUp76nD2rP/6qabKBTa1yGXYp9ZBgtY\nYJ/bFyp7yCIiIlKlFLJE1uNt79nyfe8rdh0sQPFySwfbh6ATt2vfidIwFu67DKtIPQ88S9r6PV5x\nKV6nCaz5RvnzXJPcnwV+SBrm6rGwcAZp+/dfX389m/Xrx+APfIDZs0Nkq02h8hfCcFizqg7rNlgA\nVq1ezS233spsrLoUWvTHlcvy54uvB4V8vqSJyZ+S+6ckr7Ms+clj628dMXmyqlgiIiI1TiFL5F28\n9uabPL1yZbHFOqTdB+POgmEY2grSalXcpbBc6BQ4DHgZC1cF0upXqISFqtgulLaLD5WZ75FW2I5J\nfi8gDQVnJbd9BgsRdcA/V6/mvLPOos45Jk2aVDPdCU/67ndxwMeS6x6bQ5cFxic/HtgCe89CVe8x\n0uGbIYyFgBxC7gBKP+82bDHjDPaePpb8OOAW7D1fTmlorgOymQw/+fnPK33oIiIiUmU0J0tkA9U5\nR4a0jXroCpjBmivEixKH6lGofoTfdaQBLXyDC9Hjx2AL6EK6MHKYb5Ul/auIw1rKn0/7BZFJnvsI\n4GzaL3Z8HHBV9DzhOL74xS+y9957c8wxx2z4m1IlmpqaGDhgAHWkc9Zc9DsM6RyBvYceWLN2Ld84\n+mh+fdttxbls4f0NDUkewhYiDsEqiwXb88J15zjde84hHVqaBx4A9sWGeM4lDXGXXXEF3z722K55\nE2qE5mSJiEgtUMgS2QjO2blfGK4XqlbhxB3sxDo0rCiQNrwoD13lzTNCCNoMOBWYQ2kr+RC2QrfB\njhpsjKa0ilaIHh/vcyvWBr6J0mpL6KI47cQT2WeffTj00EPf+02pAmvWrGG7QYO4HTgYe4+mYu3b\nQ6MSSAPw9kOGsGzlShr79QM6DmMee29nYp/RLqNH8+SyZSUt/kOgC/O4fokF3yXYGl0hUGewUKdh\ngu9NIUtERGqBQpbIRmpwrjj0LszTgjREhe51IWSFIJZPbg8VqSXYELbyChikJ/dnA++UPc4DXwR+\nltwWAleospyTbB+qJ+E5M8l9s6LbQngbjTVqiDschuP58TXX8JGPfISPfexj7RbcrRbNzc009uvH\nJ4EHSUMtlL4Hs4HDseGXp512Gueed17xs9gdmzsF9lk8ir0fuwD7Ab93jhbv23UtDK8RqpzfAy4g\nbdEPcNTkyfzixhsre9A1SiFLRERqgUKWyCbIOFccjhYaJYQW4aEyFLdsb4GSdvDhxD+unozB5vXs\nQjqE7/novrdIhxCSPPYE4FJKA0UdaatwT+kQuFBZ+Q4wETiKNCjmk8d/BfhPYFLZMReA/fbfn8Mn\nT+bwww9n4MCBG/hudb0vH3UUv7zhBrLYe52jtFIY3uswfC80Lgnvz8HAbyh9H0N4zQOnYUMEH8Xm\nfK3AwtpTyWuFaleYN/cNbE20PwGfBKir419vvlm1IbWaKGSJiEgtUMgS2UQumaMVxEP4QvhaAZwE\n3Ek6DyuuaIXABWmL9njtrTxwCtaNMG6GAaXD/MLJffycp2JD1+IhcCEkQDofK49Vsp6Jbg9D4MAW\nUV4Z7Vd43NChQzlt1ixGjRrFXnvtVf72dJumpia2GTCgOA/qt8B/0L46tTO230uB14EJpIs8g71P\nzVjIfTi5/7Hkvl2x9/9J7H29k9J1uMaQBrd4SOhngXsAr5C1wRSyRESkFtS99yYi0hHvPQ3OlQyv\ng9JGFeuwE/K4ghKaZoSmFqFqMoeOmzTMT7b/JvBT0nAVglW8Ble4LYdVXuIz1Sw2/K18QeQMVpF5\nH3Al8PXkWMLrHJ28/mRs2NzU5P4XX3iBE77znWIgmzFjBv369WOXXXZh0qTyOljX+cmPfgTAHVhg\nqge2xIJRLFSzxgP7kAbhWANpi/42YBxp236wAEYHj22ldKFqsM/vFux9vPySSxSwRERE+hBVskQ6\nKRMFrdDS20c/jnSOVeg0B2mDivA4KK2OjMCqMb8mrSLFnQj3A15Mbg/PGS94HIYnxsMLM9icoXjI\nXFx5iStY9wMfJp0rFrbLA3tjYWVB9Lzxv8hW4IgjjmDgwIF87nOfY9999+2SkNHc3MyAzTdnz0KB\nPya3xe973N0vVKIAxkbbxJ0iiY4zBM0wFJDkeh6reMXraWUoHaYI9r61Ai+88AJDhgyp0BHXPlWy\nRESkFihkiVRAXTJHK8xtCpWO0PgiBK24C2A89K+OdE5X3O59Ee2bYxSwYWh3U3pCH9bUKg9sdwHH\nUzqU0GFD6sqfI6y5FYTn/AnW+n3/5DGQhrIwBPJu4KOkoSwOXh448qij+NJXvsIWW2zB9ttvX5Hg\n8Ylx43j8iSeKizmHY15HOncqDAEMVa7vkA6/DNtfRzpcM7w/8VDAED4/i72fYbvyJiHhcwz377bb\nbvzp8cc7fZx9iUKWiIjUAoUskQoZNnQoL6xaxYnYXKh4WF8IT+VzeOKT9LjdeggM5a3F47k/YPOD\nvk4avkJICk034ipVHhgCvEBp2Io75eUo7bDno+3C654EHFv2miFwhAra5cCJwNPRc8X7ATBw6605\n8bTTeOONNxg2bBj77LMPw4YNY0OFtu1LkvclT1pJuharYIUgFTcoaY72Nx7etxM2B2sGts5VHD6/\nAfyItCtkC2mIC9uEZiOhqnju2Wdz2qxZG3w8YhSyRESkFihkiVRQ/7o6mvMWI0LYiTvVxUP3QlOE\nMJQtrGsVqiHxGlmO0qFr2eRxIZjFnQjjSlJL2XOQPHYu8EdsvlgsR2nVbAk2PHFE2Xbh2KYCh2Hd\n+U4lbR8fQkw/4CxgOulcsLBv8bC8YPN+/fjxz38OwFZbbcW//vUvhg4dyh577EG5VatWscPQoTyA\nzbEKxxYH01DFKr8eAmho/BE+l0eBPZLnCRWpsI+h0hg/NoTIMaSNSQrA3LPP5lQFrE2ikCUiIrVA\nIUukwhYvXsy43XYrzs2KmyTEc6XC3CpIg1HcfTAeehYvJHww1kEvnkcUQs93gGuwisx4SkNWKxai\n4mFuWSwond/BfXWUVrXC9XgBZUiHRwL8EBtSOIq0qUd5lWs28EHgmOQ5n4meM3798su33nUXf//7\n3xkwYACDBg3ipz/+MT//5S9L3p8n6bjK5JPXuRj4b9K27SFkxu99qIaFQOaB7YG/JY+Lw275gsUF\nYPzYsfzpiSeQTaOQJSIitUAhS6SL5JJ5WnF79QzrHz44g7QSFEJTeFw8tyucfYY5XnHoCfOkrsCq\nRy1Y8AjVqDgQhepYuJ4jXXcrBKT4X1mONLx19LohqISK3CRsva2vY/O/fhttG3gskC3GWsUfBdwG\nfAgLSuurpMVVsLgSVY81BLk72vYI4CWsLXsL6XDM8k6A4bnqKB1CGDf9mANMIR22GYZnOqChro6/\nvPRSVa0f1hspZImISC1QyBLpQlln54oF0s50cTe+cCY5C6smLcNCwdLoOUIFqjW6LSx6vIjStaDC\nyX8IaPEwwp0prQy1UlrRitf5+jRwX3I5dEwMx+Gw8FPekOM0YB5pa/jyKtusZLtvRa8fV/nioBaq\ndD/EmmlMTLb7VXLcn6f0vQwVpolYmMthofXs6D0rX8OsvF1+IXq+0NAjQ+lr5IEnsPbwB2DDPfPA\nVu97H6+9+SbSeQpZIiJSCxSyRLrYbbfdxuGHHVasYkF6kt9Gade/PwKfon3XwHCCX0dauYmDWlwR\ni8NYXFnqByxPbo8DF5SuuRWHnhXYPKWjom1zHbxuR00zytvPhxAVV+nAOhduj1W7ZgHnUlptW9/w\nwTCfCmyYZBMWwkLlLnQF/A0WiIIQzg7CQhKkoaoBC2rh9o7CZHj/w/6sWLlyoxp2yLtTyBIRkVqg\nkCXSTeqdK4aHPG62otsAABBCSURBVKXhKlwPv8uHsYWQFYcTKF0HK1b+eJLX+S9sGN8k0tblcQiC\ndB5X+XPnsCF3N2LDGuPuhR297qPAnqQBpXxIZHnjizBnyyX7BRbuFieXy+dZlXc2jPczXtsqVK7i\n9vShijcRWEj6OYSGIqF61VHICqH3nvvuY+LEiUhlKWSJiEgtUMgS6UbZZJ4WpB3swgl++eLBYE0i\nppCe3Ic5Vx0Jla14TlFobZ5JHh+HtNOxRhBxCIobZcSLJddFzx/ksMC0FKtGlS98XN5+fnTye1l0\nvRVrSAGlgZLotXLYfK1Dsdbw22Dh61zgA9icr+DCZF+nA98Ero7uC1XAeMHm+FjD/fcDE0gbgZTP\nY7v1rrs48MADka6hkCUiIrVAIUukm91///0csN9+JcMHwUJKDhvW9wZp5z2wADKCNLCEEBNCUKjS\nhPW1oLSisyS5fGfZ4wvA94HPYEPqQqOMjraNW5qXz+GanTy+vNF6jvbi0BWHrDFYY42xyfPGVasQ\njtY3dDDYkPvD+1Redftksj/3ACdjYTCuPP7smms4+uijOzgiqSSFLBERqQUKWSI9JONcSeOJuIJV\nHirK50DFjRogDUChQUaYsxWqZI9QOtyuvGrVFr3WYjpugR4P7ysPXHEFKzzPEmwdqUnheEkDYNgW\nSoPaFNL5YvHrh+2ewVqr7xrdH9rFdzQnLHQmDPd7LFCVH18cssLwwlD1u1fDAruVQpaIiNSCjqZz\niEg3KHjPypUri8GjldKT/EJ0W1sHjw+Vr7hZRaiMhcpTKxYWdu/g8TmsagVpt8I6YLfkcWdF24bQ\nM5u09Xs9aaUq7GcLafjbFRvWV49V5/oBNwMnRtueQxp+ziQNVI60ercdaXfDSuiPrZEVnt9hoStu\nKFKfybDoiSfIe6+AJSIiIhtNlSyRKpBzrmT4YJibFP4K0oaFlfCtPwi4i44bZMSt2csXNA7lAQec\nQTrfy2NrQJ1N2n0PSocJ3gwczbs3sihEP8Vjo33VqtiZD6tMjYxeoxULZ7nkteve5fGwccMF423i\nNvehUvfNb3yDaSeeyMiRI5GeoUqWiIjUAoUskSpx9913c9BBBxWvlw/9qyetdIVhgPHwv3g+E8n9\n5Z0CQ4grD1xhHa/y9bZC+Ajb5IGPA/sD85Ntw2N2prSZRzzEsAXYMnn8OjZ86OBHgf8GjiUNRdsA\nr2FNO5YA/xs9zx7Y0MjgU8lrPRi9XnkL/Dxw1llnMWPGDBoaGpCepZAlIiK1QCFLpMqce+65zJk5\nE0/pulqh0URHQWk2cAjt5xqFjoXxcMO4lXlYaLi8E2AcsnLAgVgjjPJ26a3A3sAOwC9pH/p2JW0/\nX941MMztGpj8/hfWLfA12s/xirsVBgdj62MdSNoOP1TzOpq7Vj7kcvNMhj8uWsTYsWOR6qGQJSIi\ntUAhS6RKOWfnmWHOVdxJMIu1NZ9EOi+qo655IVCFfy3lYSu0KIf21S2wAHNPsk1Ha0aV7C9WfdoM\nuApbWPgcrPlEqMjVR4/fmdKqXHnlKxZXob4BDMc6IMZrjdVh873Op33QDPO+PHDEkUdywUUXMWTI\nEKT6KGSJiEgtUMgSqWKPPPIIH//4x4tzq+I1ncJZaCtWSfoLpfO2MsBTyeUR0fZx6AoBK1TK4nAT\nryfl6DhkhY5/8fXyYYh5Sqtfs5NjOQcLYiSXZ2PNLxwW0p5Ifof9C2EqCNe/D8zFKmfjKV3XKhyj\nA8694AJOOOEEDQmscgpZIiJSCxSyRHqBa6+9lq99+cvFIBQ3tAjzrUKgCeEjS1rR2Sn5HapecUVr\nfS3Zw7DE0E0wBKjwL+8/gN/Sfmjes8n1nWlfSVtfA4sNaWQRqnnxAs0F0oWSF2HDE4nei7Fjx/Ll\nL3+Z6dOnI72DQpaIiNQChSyRXuSkk05iwfz5ZCgNRiGExNWt8vWrQgCLh+yFBYE96Zyv8tBVLgwz\nDL/X1zFwFywA5Vl/EBsBPADsW7ZN+XPF62LF873iuWUk1wvOMX36dObNm/cuRyHVSiFLRERqgdbJ\nEulF5s2bR957Lr7ssuI6WZB2yQvrVYXA1UoavN7tH/ui6HImed6wbla5UCUKa12FtbggXd9ql407\nrI3Smjx/+fpg3zr2WNq8p1AoKGCJiIhIj1IlS6QXu/DCC7n++utZ+vjjQDrED9rP2xoO/JW0YkVy\n/2exOU270n7e1c6sf6hfCFvrE+Z5xY/pzHDB8q6EAMcccwxXXXUVUjtUyRIRkVpQlZUs59xJzrmC\nc27rnt4XkWp2yimnsGjRIlq85wtf/GKxyx5YEAmVrTrg79g/+BYsSIU1t+6k48pTM+mQvRWkrd6X\nYPOiQsWrnrTyVR9d98lrhWpXK9bY4vTo+inYgsYtwFnA5dFj4sfFl2eecQbee7z3ClgiIiJSlaqu\nkuWcGwr8CJurv7v3/vUOtlElS2Q9br75ZubOncvjjz9esiZWUF7hAlv09y+UzrMKa049nWwT1s56\nDNgTq3ato3Rtrp1ov6jxO7Rv3x7mgj2JtXiPOxOG+WOhSnb44Ydz8803b8I7Ib2RKlkiIlILqrGS\nNR/747aIbIJJkyaxaNEivPd865hj2HHHHUvmb8UVriwWfv5G2lGwBYiX5x1But5UhrQKtjEctq7V\nmOS5wrpZu5I2uigADVtswfg992Thgw8Wq1UKWCIiItLbVFUlyzl3GDDBez/dOfdXVMkSqZgpU6bw\n5JNP8sxTT5W0aC+Xiy6Xb7Mzti5WNrqto/lU65tfFc+/CvOqBg8ezPz58znqqKM2+FikdqmSJSIi\ntaDbQ5Zz7l5g2w7umoX9sfsA731TErLGe+//2cFzKGSJdMK5557LLbfcAsBjjzxSHKL3buKW8Btb\nyYqNHDmSH/7wh+y1116deBapVQpZIiJSC6qmkuWcGw3cB7yV3DQEeBHYw3u/umxbP3v27OL1CRMm\nMGHChG7aU5Hac9ttt3H77bfT0tJCS0sLK1asoK2tjWXLlr33g8vU19fT0tICwAc/+EFOP/10jj/+\n+ErvstSIhQsXsnDhwuL1M888UyFLRER6vaoJWeU0XFCkOixevJipU6fy1ltvceihh/Liiy/yj3/8\ng2w2yw477MA222xDW1sb++yzDxMnTuzp3ZVeTpUsERGpBdUcsv6CDRdUyBIR6SMUskREpBZUbch6\nNwpZIiK1SSFLRERqQTW2cBcREREREem1FLJEREREREQqSCFLRERERESkghSyREREREREKkghS0RE\nREREpIIUskRERERERCpIIUtERERERKSCFLJEREREREQqSCFLRERERESkghSyREREREREKkghS0RE\nREREpIIUskRERERERCpIIUtERERERKSCFLJEREREREQqSCFLRERERESkghSyKmjhwoU9vQu9ht6r\nDaf3asPpvdpweq9ERES6jkJWBemkZcPpvdpweq82nN6rDaf3SkREpOsoZImIiIiIiFSQQpaIiIiI\niEgFOe99T+/DRnPO9b6dFhGRDeK9dz29DyIiIp3RK0OWiIiIiIhItdJwQRERERERkQpSyBIRERER\nEakghSwREREREZEKUsjqIs65k5xzBefc1j29L9XKOXehc+5p59wS59yvnXMDenqfqo1z7kDn3Arn\n3HPOuVN7en+qlXNuqHPuAefccufcMufcCT29T9XOOZd1zj3hnLu9p/dFRESk1ihkdQHn3FDgM8Df\ne3pfqtw9wCjv/a7As8DpPbw/VcU5lwUuBw4ERgJTnHM79+xeVa1WYLr3fhTwCeA4vVfvaSrwFKDu\nRyIiIhWmkNU15gMzenonqp33/l7vfSG5+mdgSE/uTxXaA1jpvf+b974VuB44rIf3qSp571/x3i9O\nLr8JPA18sGf3qno554YAnwWuBtQuXUREpMIUsirMOXcYsMp7/2RP70sv83XgNz29E1VmO+CF6Pqq\n5DZ5F8657YHdsOAuHbsYOAUovNeGIiIisvHqenoHeiPn3L3Ath3cNQsb8nZAvHm37FSVepf3aqb3\n/vZkm1lAi/f+l926c9VPw7g2knNuC+AmYGpS0ZIyzrlDgNXe+yeccxN6en9ERERqkULWJvDef6aj\n251zo4GPAEucc2DD3xY55/bw3q/uxl2sGut7rwLn3FexYUv7dcsO9S4vAkOj60OxapZ0wDmXA24G\nfu69v6Wn96eK7Qkc6pz7LNAPaHTOXeO9/3IP75eIiEjNcN7rj+VdxTn3V2B37/3rPb0v1cg5dyAw\nD9jHe/9aT+9PtXHO1QHPYAH0JeARYIr3/uke3bEq5OyvGj8D/um9n97T+9NbOOf2AU723n+up/dF\nRESklmhOVtdSgn13lwFbAPcmraSv7Okdqibe+zbgeOC3WBe4GxSw1utTwJeAfZPv0hNJiJf3pv+n\nREREKkyVLBERERERkQpSJUtERERERKSCFLJEREREREQqSCFLRERERESkghSyREREREREKkghS0RE\nREREpIIUskRERERERCqorqd3QKQ3cM69H/hdcnVbIA+swdYY2iNZ06oqJAvMtnjv/6+n90VERESk\nL1LIEtkA3vt/ArsBOOdmA+u89/N7an+cc1nvfX49d+8LrAM2OGQ55+qqKSiKiIiI9GYaLiiyaZxz\nbnfn3ELn3GPOubudc9smdyx0zs13zj3qnHvaOfcx59z/55x71jn3g2Sb7Z1zK5xzP3fOPeWcu9E5\nt1ly37s978XOuUeBqc65Q5xzf3LOPe6cu9c5N8g5tz1wDDA9uX0v59z/OucmRTv+ZvJ7gnPuQefc\nrcAy51zGOXehc+4R59wS59y3u/MNFREREakVClkim8YBlwKTvffjgZ8C5yT3eaDZe/8x4L+BW4Hv\nAKOBrzrntkq22xG4wns/EmgCjnXO1QGXAZPW87w57/3HkiraQ977T3jvxwE3ADO8938DrgLme+/H\nee8fSh4Xi6/vBpzgvR8BfBN4w3u/B7AH8K0ktImIiIjIRtBwQZFN04CFpnudcwBZ4KXo/tuS38uA\nZd77VwGcc38BhmKh6oVo3tTPgROAu4FRwO/W87w3RJeHOud+hc0Rqwf+Et3nNvA4HvHe/z25fAAw\nxjk3ObneCAwH/raBzyUiIiIiKGSJbCoHLPfe77me+5uT34Xocrge/t3FFSWXXH+v5/13dPky4CLv\n/R1Js4s563lMG0nV2jmXwQJZR88HcLz3/t71PI+IiIiIbAANFxTZNM3AQOfcJwCccznn3MiNfI4P\nhccD/wU8CDzzHs8bV6gaSatcX41uXwf0j67/Ddg9uXwokFvP/vyWdMgizrkdnXObb8wBiYiIiIhC\nlsimygOTgfOdc4uBJ4BPdrCdp/2cqOAZ4Djn3FPAAOC/vfet7/G88XPNAW50zj1G2k4e4Hbg8865\nJ5xznwJ+BOyTPN8ngDfX83xXA08BjzvnlmLzyVTtFhEREdlIzvv1nf+JSFdJGkrc7r0f08O7IiIi\nIiIVpkqWSM/RXzhEREREapAqWSIiIiIiIhWkSpaIiIiIiEgFKWSJiIiIiIhUkEKWiIiIiIhIBSlk\niYiIiIiIVJBCloiIiIiISAX9//VW+f3HbNFtAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x1094f5390>"
]
}
],
"prompt_number": 31
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Updates:\n",
"\n",
"Everything seems to be wokring fine except for the ellipsoid parameter generation. While it is creating ellipses (finally) it still isn't generating the tails and 'closing in' on the true data. In the bottom right figure we can see the ellipsoid generated for every sensor stacked on top of each other. \n",
"\n",
"**NOTE**: They all use the same 'a' and 'b' values (given by Dr. Shan) but the theta is changing. The subplot depicts this in way that we would expect. \n",
"\n",
"What's next? \n",
"* Calculating individual 'a' and 'b' values during ellipsoid generation? \n",
" * ** HE GAVE ME THE BASE SATION's a AMD b VALUE**\n",
"* Why aren't the tails forming?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"for sensor, readings in measurements.iteritems():\n",
" humidity_mean = helpers.calculate_humidity_mean(readings)\n",
" temp_mean = helpers.calculate_temp_mean(readings)\n",
" temp_sd, humidity_sd = helpers.calculate_std_dev(readings)\n",
" print \"Sensor %s\" % sensor\n",
" print \"\\tTemp. mean: %s\" % temp_mean\n",
" print \"\\tHumidity mean: %s\" % humidity_mean\n",
" print \"\\tTemp. Std. Dev.: %s\" % temp_sd\n",
" print \"\\tHumidity Std. Dev: %s\" % humidity_sd\n",
" "
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print sensor_18_humidity_mean"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"-1.128405868e-17\n"
]
}
],
"prompt_number": 15
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment