From 9e59b31404e43e7965c24d7961b463fb8d5a02cc Mon Sep 17 00:00:00 2001 From: SylvainEstebe Date: Thu, 16 Jan 2025 11:47:35 +0100 Subject: [PATCH] add prediction function --- examples/test_prediction.ipynb | 490 +++++++++++++++++++++++++++++++++ pyhgf/model/network.py | 132 ++++++++- pyhgf/utils/__init__.py | 4 + pyhgf/utils/prediction.py | 228 +++++++++++++++ 4 files changed, 843 insertions(+), 11 deletions(-) create mode 100644 examples/test_prediction.ipynb create mode 100644 pyhgf/utils/prediction.py diff --git a/examples/test_prediction.ipynb b/examples/test_prediction.ipynb new file mode 100644 index 000000000..bb156d393 --- /dev/null +++ b/examples/test_prediction.ipynb @@ -0,0 +1,490 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 92, + "metadata": {}, + "outputs": [], + "source": [ + "from typing import Dict, Tuple\n", + "import jax\n", + "import time\n", + "import jax.numpy as jnp\n", + "from jax import random\n", + "from jax.typing import ArrayLike # Import ArrayLike\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import sys\n", + "# Import the Network class\n", + "from pyhgf.model import Network\n", + "from pyhgf import load_data\n", + "from pyhgf.utils import sample_node_distribution,scan_sampling" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Predictive Agent\n", + "In this notebook, we first create two agents: one with a binary child node (where the inputs are observed) and one with a continuous child node.\n", + "Rather than merely observing data, we want our agents to think and simulate the future by sampling from their own distributions and then inserting the samples as observations." + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [], + "source": [ + "#rng_key = random.PRNGKey(0)\n", + "rng_key = random.PRNGKey(int(time.time()))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Continuous Agent\n", + "We create an agent with two nodes, including a child continuous node as the input." + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "hgf-nodes\n", + "\n", + "\n", + "\n", + "x_0\n", + "\n", + "0\n", + "\n", + "\n", + "\n", + "x_1\n", + "\n", + "1\n", + "\n", + "\n", + "\n", + "x_1->x_0\n", + "\n", + "\n", + "\n", + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 94, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Define an agent with a continuous node and display the network\n", + "agent_1 = (\n", + " Network() # Create a new network\n", + " .add_nodes(precision=1e2) # Add Node 1: Continuous node with a specified precision\n", + " .add_nodes(value_children=[0]) # Add Node 2: Child node linked to Node 1\n", + ")\n", + "\n", + "# Plot the network structure\n", + "agent_1.plot_network()" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Sampled node with mean of 0.0 and a precision of 1.0: (Array(-0.26410845, dtype=float32), Array([3398566719, 1030377080], dtype=uint32))\n" + ] + } + ], + "source": [ + "# Sample from the continuous node\n", + "sample = sample_node_distribution(\n", + " agent_1.attributes, # Attributes of the network\n", + " 0, # Node index to sample from\n", + " rng_key, # Random number generator key\n", + " agent_1.edges[0].node_type # Node type for the specified node\n", + ")\n", + "\n", + "# Print the sampled value along with the node's mean and precision\n", + "mean = agent_1.attributes[0]['expected_mean']\n", + "precision = agent_1.attributes[0]['expected_precision']\n", + "print(f\"Sampled node with mean of {mean} and a precision of {precision}: {sample}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Run the scan to generate multiple samples\n", + "num_samples = 100 # Number of samples to generate\n", + "samples = scan_sampling(\n", + " agent_1.attributes, # Network attributes\n", + " 0, # Node index to sample from\n", + " rng_key, # Random number generator key\n", + " agent_1.edges[0].node_type, # Node type for the specified node\n", + " num_samples # Number of samples to generate\n", + ")\n", + "\n", + "# Plot the sampled distribution\n", + "plt.hist(samples, bins=20, alpha=0.75, edgecolor='k') # Histogram of samples\n", + "plt.title(\"Sampled Node Distribution (Continuous)\") # Title of the plot\n", + "plt.xlabel(\"Value\") # X-axis label\n", + "plt.ylabel(\"Frequency\") # Y-axis label\n", + "plt.show() # Display the plot" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Binary agent" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "hgf-nodes\n", + "\n", + "\n", + "\n", + "x_0\n", + "\n", + "0\n", + "\n", + "\n", + "\n", + "x_1\n", + "\n", + "1\n", + "\n", + "\n", + "\n", + "x_1->x_0\n", + "\n", + "\n", + "\n", + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 97, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Define an agent with a binary node and display the network\n", + "agent_2 = (\n", + " Network() # Create a new network\n", + " .add_nodes(kind=\"binary-state\", precision=1e2) # Add Node 1: Binary state node with a specified precision\n", + " .add_nodes(value_children=[0]) # Add Node 2: Child node linked to Node 1\n", + ")\n", + "\n", + "# Plot the network structure\n", + "agent_2.plot_network()" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Sampled node with mean of 0.5 and a precision of 1.0: (Array(1., dtype=float32), Array([3398566719, 1030377080], dtype=uint32))\n" + ] + } + ], + "source": [ + "# Sample from the binary node\n", + "sample = sample_node_distribution(\n", + " agent_2.attributes, # Attributes of the network\n", + " 0, # Node index to sample from (Node 1)\n", + " rng_key, # Random number generator key\n", + " agent_2.edges[0].node_type # Node type for the specified node\n", + ")\n", + "\n", + "# Print the sampled value along with the node's mean and precision\n", + "mean = agent_2.attributes[0]['expected_mean']\n", + "precision = agent_2.attributes[0]['expected_precision']\n", + "print(f\"Sampled node with mean of {mean} and a precision of {precision}: {sample}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "samples = scan_sampling(agent_2.attributes, 0, rng_key, agent_2.edges[0].node_type, num_samples)\n", + "\n", + "# Plot the results\n", + "true_count = jnp.sum(samples)\n", + "false_count = num_samples - true_count\n", + "plt.bar([\"False (0)\", \"True (1)\"], [false_count, true_count], alpha=0.75, edgecolor='k')\n", + "plt.title(\"Sampled Node Distribution (Discrete)\")\n", + "plt.xlabel(\"Outcome\")\n", + "plt.ylabel(\"Count\")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Observing his own sampling\n", + "Now, we want the agent to observe its own sampling. This means the agent will sample from its own distribution, treat the sample as an observation, and potentially update its internal state or parameters based on this observation.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([,\n", + " ],\n", + " dtype=object)" + ] + }, + "execution_count": 100, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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5BC0tLTj66KMBmL+JRiIRLF++vOzbeh577LF2r+GUU07B119/jYcffrjdWjKZDFKpVJdfAxERERERERERVa7Odjufz4dwOIzXX3+97L7777+/W5+37fx5wzBw7733wul04vDDD+/ys9LpNLLZbNm1YcOGwev1QlVVAF1rg/l8Hp988knZZuWO1NXVYfr06WU/tvaHP/wBzc3NOP300zt8xmGHHYZgMIgHHnig7PoDDzwARVGshggAjY2N+OSTT5BOp61rI0aMwAcffGB94aTk//2//webzYbx48db9wHmaKC23n//faxfvx4TJ07c7mulzquoHf+XXHIJ0uk0vv/972PUqFHI5XJ488038cwzz2Dw4MFl3xIzadIkvPrqq7jzzjtRX1+PIUOGYOrUqTjmmGPw5JNPwu/3Y8yYMVi7di1effVVhEKhss81YcIE2O123HrrrWhpaYEoijjssMNQXV2NBx54AD/84Q+x//77Y/bs2YhEIti4cSNeeuklHHzwwe0OvOiM0qz/jz76yPqiAwBEIhEsWLAA1157LY444ggcd9xxWL9+Pe6//34ccMAB+MEPfgDAnOV/ww034Pzzz8dhhx2GU089FRs2bMCKFSvazTr74Q9/iGeffRYXXHABVq9ejYMPPhiapuGTTz7Bs88+iz/+8Y/WV2M70tLSYs3wKn37zr333ouqqipUVVWVHapCRERERERERER7v650u3POOQe33HILzjnnHEyePBmvv/56u+DcGZIkYeXKlZgzZw6mTp2Kl19+GS+99BKuuuqqHR7k25FPP/0Uhx9+OE455RSMGTMGDocDzz//PDZv3ozZs2cDML9w0dk2+PXXX2P06NGYM2fOTh/w+9RTT0EURZx44okdvl+WZVx//fW46KKLcPLJJ2PmzJn4y1/+gl/+8pe48cYbEQwGrXvvvfdeXHvttVi9ejWmTZsGALjsssvw8ssv4zvf+Q4uvvhihEIhvPjii3j55ZdxzjnnWN9lMGnSJHzve9/D448/jng8jhkzZuCbb77BsmXLIMsy5s2bt1Ovk9owKsjLL79snHXWWcaoUaMMj8djuFwuY5999jEuueQSY/PmzWX3fvLJJ8Z3v/tdQ5ZlA4AxZ84cwzAMo6mpyZg7d64RDocNj8djzJw50/jkk0+MQYMGWfeUPPzww8bQoUMNu91uADBWr15tvW/16tXGzJkzDb/fb0iSZAwbNsw488wzjXfffXe7r2H16tUGAOO5555r975FixYZAAy3293ufffee68xatQow+l0GjU1NcaPfvQjo6mpqd19999/vzFkyBBDFEVj8uTJxuuvv24ccsghxiGHHFJ2Xy6XM2699VZj7NixhiiKRiAQMCZNmmRce+21RktLy3Zfw4YNGwwAHf4YNGjQdj+WiIiIiIiIiIj2Pl3pdul02jj77LMNv99veL1e45RTTjG2bNliADAWLVpk3VdqZQ0NDe0+35w5cwy32218/vnnxowZMwxFUYyamhpj0aJFhqZp1n2ljrVkyZJ2zyi9b8WKFYZhGEZjY6Nx0UUXGaNGjTLcbrfh9/uNqVOnGs8++2y7j+1MGyw9f+vm2FUtLS2GJEnGCSecsMN7H3roIWPkyJGGy+Uyhg0bZtx1112Grutl95R+Xdu2TsMwjLfeess48sgjjdraWsPpdBojRowwbrzxRiOfz5fdl06njeuuu84YM2aMIcuy4ff7jWOOOcb44IMPdup1UjnBMDr4HhoiIiIiIiIiIiKivdSZZ56JX//610gmk729FKJdoqJm/BMRERERERERERER7e0Y/omIiIiIiIiIiIiI9iIM/0REREREREREREREexHO+CciIiIiIiIiIiIi2otwxz8RERERERERERER0V6E4Z+IiIiIiIiIiIiIaC/i6O0F7A6FQgEffPABampqYLPxax1EREREREREREREfZGu69i8eTMmTpwIh2PH+fr111/HkiVL8N577+Gbb77B888/j1mzZm33Y9asWYP58+fjn//8JwYMGICrr74aZ555Ztk99913H5YsWYJNmzZhv/32w7JlyzBlypSdeGW7V0WE/w8++GCP+pdCREREREREREREVMnefvttHHDAATu8L5VKYb/99sNZZ52FE044YYf3b9iwAUcffTQuuOACPPXUU1i1ahXOOecc1NXVYebMmQCAZ555BvPnz8fy5csxdepULF26FDNnzsT69etRXV29069td6iIw303btyIQYMG4e2330ZdXV1vL4eIiIiIiIiIiIiIOvDNN99gypQp+O9//4uBAwd26WMFQdjhjv8rrrgCL730Ev7xj39Y12bPno3m5masXLkSADB16lQccMABuPfeewGY34UwYMAAXHLJJbjyyiu7/qJ6QUXs+C+N96mrq0P//v17eTVEREREREREREREtD2pVArxeNx6WxRFiKK4089du3Ytpk+fXnZt5syZmDdvHgAgl8vhvffew4IFC6z322w2TJ8+HWvXrt3pz7+7cOA9EREREREREREREfUpY8aMgd/vt37cfPPNPfLcTZs2oaampuxaTU0N4vE4MpkMGhsboWlah/ds2rSpR9awO1TEjn8iIiIiIiIiIiIi2nOsW7cO/fr1s97uid3+lYThn4iIiIiIiIiIiIj6FK/XC5/P1+PPra2txebNm8uubd68GT6fD7Isw263w263d3hPbW1tj69nV2H4LzIMA4VCAZqm9fZSqAI4nU7Y7fbeXgYRERERERER0V5H0zTk8/neXgZtg91uh8PhgCAIvfL5DzzwQPzhD38ou/bKK6/gwAMPBAC4XC5MmjQJq1atsg4J1nUdq1atwsUXX7y7l9ttDP8wD2z45ptvkE6ne3spVCEEQUD//v3h8Xh6eylERERERERERHuNZDKJr776CoZh9PZSaDsURUFdXR1cLtdOPyuZTOKzzz6z3t6wYQM+/PBDBINBDBw4EAsWLMDXX3+NJ554AgBwwQUX4N5778Xll1+Os846C3/+85/x7LPP4qWXXrKeMX/+fMyZMweTJ0/GlClTsHTpUqRSKcydO3en17u7VHz413UdGzZsgN1uR319PVwuV699tYkqg2EYaGhowFdffYXhw4dz5z8RERERERERUQ/QNA1fffUVFEVBJBJh4+uDDMNALpdDQ0MDNmzYgOHDh8Nms+3UM999910ceuih1tvz588HAMyZMwePPfYYvvnmG2zcuNF6/5AhQ/DSSy/hJz/5Ce6++270798fv/jFLzBz5kzrnlNPPRUNDQ245pprsGnTJkyYMAErV65sd+BvXyYYvfzlr9dffx1LlizBe++9h2+++QbPP/+89S0UgPkfw6JFi/Dwww+jubkZBx98MB544AEMHz6805/jq6++woABA/Dll1+if//+Ze/LZrPYsGEDBg0aBEVReuplEW1XJpPBF198gSFDhkCSpN5eDhERERERERHRHq/U+QYPHgxZlnt7ObQd6XQa//3vfztsY9trudR5O/fllB6QSqWw33774b777uvw/bfddhvuueceLF++HG+99RbcbjdmzpyJbDbbo+vY2a8sEXUFv+JMRERERERERLRrsLv0fWyxu16vj/o58sgjceSRR3b4PsMwsHTpUlx99dU4/vjjAQBPPPEEampq8MILL2D27NkdfpyqqlBV1Xo7kUj0/MKJiIiIiIiIiIiIiPqgPv2llQ0bNmDTpk2YPn26dc3v92Pq1KlYu3btNj/u5ptvht/vt36MGTNmdyyXiIiIiIiIiIiI+hhd16Fp2m77oet6b79kot7f8b89mzZtAoB2hybU1NRY7+vIggULrEMcAODrr7+u2PhfKBTwr3/9C+PGjevtpey0adOmYcKECVi6dGlvL4WIiIiIiIiIiPYAuq6jpaUFmqbtts9pt9vh9/t3apyNbugQIPTq2KLBgwdj3rx5mDdvXq+tgbqvT+/47y5RFOHz+awfXq+3t5fU484880wIgtDuxxFHHFF2n2EYWL58OXK5XK+sc9q0afzNgYiIiIiIiIiIeoVhGNA0DYIgwG637/IfgiBA0zQYhtHpNeqGjm82fYPzzj8PAwYOgCiKqKutw4yZM/DGG2/swl+d7XvnnXdw3nnn9drnp53Tp3f819bWAgA2b96Muro66/rmzZsxYcKEXlpV33HEEUdgxYoVZddEUSx72+l0Ip/P81uMiIiIiIiIiIioYtlsNtjt9t3yubb33QW6oZujhwwdmqGhoBWgGTpOOOlE5HM5LFt+LwYPHYLNmzfjb39Zi2g02q01lL7g4XB0Pf/mcjm4XC5EIpFufW7qG/r0jv8hQ4agtrYWq1atsq7F43G89dZbOPDAA3txZX2DKIqora0t+xEIBAAAa9asgcvlwl/+8hfr/ttuuw3V1dXYvHkzAHM3/sUXX4yLL74Yfr8f4XAYCxcuLPuKpKqq+NnPfoZ+/frB7XZj6tSpWLNmTdk63njjDUybNg2KoiAQCGDmzJloamrCmWeeiddeew1333239R0JX3zxBQDgH//4B4488kh4PB7U1NTghz/8IRobG61nplIpnHHGGfB4PKirq8Mdd9yxw1+PxYsXY8KECXj00UcxcOBAeDweXHjhhdA0Dbfddhtqa2tRXV2NG2+8sezjmpubcc455yASicDn8+Gwww7DRx99ZL3/888/x/HHH4+amhp4PB4ccMABePXVV8ueMXjwYNx0000466yz4PV6MXDgQDz00EM7XDMREREREREREe2ddENHQStALeSQzmcQV5NoySbQoiaQUJNI5zLI6wW0NDfjb2+sxXU3Xo/DDjsMQwcPwaTJk3DZFZfhuOOOwxdffAFBEPDhhx9az25uboYgCFanW7NmDQRBwMsvv4xJkyZBFEX89a9/tXrZgw8+iAEDBkBRFJxyyiloaWmxnnXmmWdi1qxZuPHGG1FfX4+RI0cCMHtXaeS2YRhYvHgxBg4cCFEUUV9fj0svvdR6RmcaIu1evb7jP5lM4rPPPrPe3rBhAz788EMEg0EMHDgQ8+bNww033IDhw4djyJAhWLhwIerr6zFr1qxdtia1kMPX8W2fIbCr9PPVQnS4euRZpRE7P/zhD62QvXDhQjz33HNlZyY8/vjjOPvss/H222/j3XffxXnnnYeBAwfi3HPPBQBcfPHFWLduHZ5++mnU19fj+eefxxFHHIGPP/4Yw4cPx4cffojDDz8cZ511Fu6++244HA6sXr0amqbh7rvvxqeffop9990X1113HQAgEomgubkZhx12GM455xzcddddyGQyuOKKK3DKKafgz3/+MwDgsssuw2uvvYb//d//RXV1Na666iq8//77O/xOj88//xwvv/wyVq5cic8//xwnnXQS/vOf/2DEiBF47bXX8Oabb+Kss87C9OnTMXXqVADAySefDFmW8fLLL8Pv9+PBBx/E4Ycfjk8//RTBYBDJZBJHHXUUbrzxRoiiiCeeeALHHnss1q9fj4EDB1qf+4477sD111+Pq666Cr/+9a/xox/9CIcccoj1myUREREREREREe29NENDTssjV8jBriYBwYz/pU22giDAJthgt9lhQ+vsfp/XB4/Hg5d+9yImHTAJNqcDakGF7JS6vIYrr7wSt99+O4YOHYpAIIA1a9bgs88+w7PPPovf//73iMfjOPvss3HhhRfiqaeesj5u1apV8Pl8eOWVVzp87m9+8xvcddddePrppzF27Fhs2rSpbOPsjhoi7X69Hv7fffddHHroodbbpUN558yZg8ceewyXX345UqkUzjvvPDQ3N+Pb3/42Vq5cCUnq+n/4nfV1fBOufOXmXfb8bbnlewswNDhwxzcWvfjii/B4PGXXrrrqKlx11VUAgBtuuAGvvPIK/vWvf+H888/HnDlzcNxxx5XdP2DAANx1110QBAEjR47Exx9/jLvuugvnnnsuNm7ciBUrVmDjxo2or68HAPzsZz/DypUrsWLFCtx000247bbbMHnyZNx///3WM8eOHWv9s8vlgqIo1tgmALj33nsxceJE3HTTTda1Rx99FAMGDMCnn36K+vp6PPLII/jlL3+Jww8/HID5BYr+/fvv8NdE13U8+uij8Hq9GDNmDA499FCsX78ef/jDH2Cz2TBy5EjceuutWL16NaZOnYq//vWvePvtt7FlyxZrTNLtt9+OF154Ab/+9a9x3nnnYb/99sN+++1nfY7rr78ezz//PH73u9/h4osvtq4fddRRuPDCCwEAV1xxBe666y6sXr2a4Z+IiIiIiIiIaC+jGRo0XW/9WdegGzo0TYOmaRA1CU6Ho13kb0s3DBT0AvJGAbffdyeu+PFleOQXj2Ds+H0x9aBv4fT/OR0HH9C1qSfXXXcdvve975Vdy2azeOKJJ9CvXz8AwLJly3D00UfjjjvusJqd2+3GL37xC7hcHW9K3rhxI2prazF9+nQ4nU4MHDgQU6ZMsd63o4ZIu1+vh/9p06Zt97ALQRBw3XXXWTvGd4d+vlrc8r0Fu+3ztf28XXHooYfigQceKLsWDAatf3a5XHjqqadw7LHHwuVy4a677mr3jG9961tlp4MfeOCBuOOOO6BpGj7++GNomoYRI0aUfYyqqgiFQgCADz/8ECeffHKX1v3RRx9h9erV7b5oAZg79jOZDHK5nLUjv/S6OhPQBw8eXHaYc01NDex2e9kp6jU1NdiyZYu1lmQyab2ekkwmg88//xyA+V0pixcvxksvvYRvvvkGhUIBmUwGGzduLPuY8ePHW/8sCAJqa2utz0NERERERERERHumUtzXDQ2FNpHfQHEnPwTYBAF2mx12Q0DBEOC0OWAXWs8UKEX+gl5AXtdQ0AvQDd36+KOOPxozjpyBd//2Lj545328+qdX8NCy5fjFL36BadOmdXqtkydPbndt4MCBVvQHzP6n6zrWr19vhf9x48ZtM/oD5sSMpUuXYujQoTjiiCNw1FFH4dhjj4XD4ehUQ6Tdr9fDf18kOlxd2nnfW9xuN/bZZ5/t3vPmm28CMOd+xWIxuN3uTj8/mUzCbrfjvffea3f4SSnay7LcxVWbzz322GNx6623tntfXV1d2einrnI6nWVvC4LQ4bXSYcfJZBJ1dXUdzhyrqqoCYH6F8pVXXsHtt9+OffbZB7Is46STTkIul9vh5+ahykREREREREREe47ORH6hGPk72smvw5yHn9PyMPRch5HfaXdAcrjgsDngsDlgF4obVkVg5vdmYOb3ZmD+FT/Fzy6Zj0WLFllneLbdPJ3P5ztcf1faX1c+bsCAAVi/fj1effVVvPLKK7jwwguxZMkSvPbaa51qiLT7MfzvxT7//HP85Cc/wbRp06DrOubMmYNXX321bPf7W2+9VfYxf/vb3zB8+HDY7XZMnDgRmqZhy5Yt+M53vtPh5xg/fjxWrVqFa6+9tsP3u1yudieZ77///vjNb36DwYMHd3iy+LBhw+B0OvHWW29ZM/Sbmprw6aef4pBDDunSr8GO7L///ti0aRMcDgcGDx7c4T1vvPEGzjzzTHz/+98HYH6xoHRIMRERERERERER7ZnaRn5N11HoYuQHAB3mTn5N11DQNeQLOeQLBRRUA3a7HU67A6LDBefWkb8TRo0ejRd/9yIikQgA4JtvvsHEiRMBoOyg3x3ZuHEj/u///s8aw/O3v/3NGondFbIs49hjj8Wxxx6Liy66CKNGjcLHH3/cqYZIux/D/x5MVVVs2lR+CLHD4UA4HIamafjBD36AmTNnon///pg7dy4OP/xw3HHHHbjsssus+zdu3Ij58+fj/PPPx/vvv49ly5bhjjvuAACMGDECp59+Os444wzccccdmDhxIhoaGrBq1SqMHz8eRx99NBYsWIBx48bhwgsvxAUXXACXy4XVq1fj5JNPRjgcxuDBg/HWW2/hiy++gMfjQTAYxEUXXYSHH34Yp512Gi6//HIEg0F89tlnePrpp/GLX/wCHo8HZ599Ni677DKEQiFUV1fj5z//edkXLHrK9OnTceCBB2LWrFm47bbbMGLECPzf//0fXnrpJXz/+9/H5MmTMXz4cPz2t7/FscceC0EQsHDhQu7kJyIiIiIiIiLaQxjFMTs5LW/O4ddLwb995LcJNtjbRn4DAHToMHfzW5Hf0KDpBWhG68c77HbYbQ64XC4EZD9cDufWS+lQLBrFGafPwQ/m/ABjxo6B4nHj/ffex1133Injjz8esizjW9/6Fm655RYMGTIEW7ZswdVXX93p1y9JEubMmYPbb78d8Xgcl156KU455ZSyMzl35LHHHoOmaZg6dSoURcEvf/lLyLKMQYMGIRQK7bAh0u7H8L8HW7lyJerq6squjRw5Ep988gluvPFG/Pe//8WLL76IJUuWwOPx4KGHHsJpp52GGTNmWIfVnnHGGchkMpgyZQrsdjt+/OMf47zzzrOet2LFCtxwww346U9/iq+//hrhcBjf+ta3cMwxxwAwvzjwpz/9CVdddRWmTJkCWZYxdepUnHbaaQDMMTlz5szBmDFjkMlksGHDBgwePBhvvPEGrrjiCsyYMQOqqmLQoEE44ogjrLi/ZMkSaySQ1+vFT3/6U7S0tPT4r6EgCPjDH/6An//855g7dy4aGhpQW1uL7373u6ipqQEA3HnnnTjrrLNw0EEHIRwO44orrkA8Hu/xtRARERERERER0c4pRX61kINu6MgVckgVMigUCh1EfqF8J79hQIdmjuuBgYKulUV+3Rq1I8Bht8Eu2OGyO+AQHLC1OUPTbrfDYSsfedNunTCgGwZ0Q4dTFjFx8kTcd899+GLDBhTyBfTr3x9nn30OFhYD/6OPPoqzzz4bkyZNwsiRI3HbbbdhxowZnfo12WeffXDCCSfgqKOOQiwWwzHHHIP777+/07+mgDkS+5ZbbsH8+fOhaRrGjRuH3//+99YM/x01RNr9BGN7J+vuJb766isMGDAAX375Jfr371/2vmw2iw0bNmDIkCGQJKmXVrhrXXfddfj+97+PcePGlV2fNm0aJkyYgKVLl/bOwipYJfx3R0RERERERES0K2m6hkQuhXg2gUQuhVg8BiXtQv2AfnC6zN32giDAMAzzAN7tjevRCsXQX/y5zUx+h81u7eZ32hywCdt6EqzP2XZyRdvIX0qxglAcIySYXySw2+ywC3bYbTbYujAOaEcWL16MF154oUujgXaH7bWx7bVc6jzu+K8AsiwjnU739jKIiIiIiIiIiIi6pRT5E2oScTWJaDqGaLoZmXwWqpYDDAOKTcY+tv7Fnfgdj9kpzeQvaOahuwW90C7ySw4JDrvDDPKCfbuRf2ulyJ/XC62H8Ra/u8A8zHfXRX6ithj+K4Asy8hkMuZXN4Wu/FZFRERERERERES0e2m6hmQuhbgV+ZsQTTchW1CRLagAAIfNDtkhwie6ITqC5i57TYAtK1hjd6zIr2vFHf3tI7/L7trpyK8bBozic7cZ+QXbLjm/kmhbGP4rwLbC/5o1a3pvUUREREREREREVPF0XUcil0RCTSGuJtCYbkIs3YRMQYVaUGEAxV34IrwuBSGlqsNd8rlCHi2pBNw2F5K5FKCntxH57XDYHD0c+e1w2Fx9MvIvXrwYixcv7u1lUC9g+K8ApVE/FXCcAxERERERERER9VG6rpft5I9lmtCYbjLH9WwV+T3bi/xaHo3pGBpSMTSmY2hMxdCiJhB0+tF/4LHQDQOSXdzpyG8U5/IDAATAJtjgsNnaRH7zgN++EvmJ2mL4L9qbo7gsy0ilUr29DGpjb/7vjYiIiIiIiIjIivy5JOLZJGKZZkTTMaTzWaiFHHTocNocnYz8TWhMRa3Y36ImAAB2wY6QEkB/fx0mKvuiTo7ADQVelxuiS+zUOrcX+e02G0RG/l2CbWzXq/jw73SaB32k02nIstzLq9k1FEVBY2Mj/x+qD8nlcgAAu93eyyshIiIiIiIiIto5uqEjmUsjriYQzybRlGlGYzHyZwsqDBjFmfzSdiN/vhj52+7kb1bjANpEfl8dJrjHIqIEUSX7yp4j6ICRMVAoFCCiffg3imtl5O996XQaQGubpZ5X8eHfbrejqqoKW7ZsAWBG8r3tAFy73Y5EIoFsNguHo+L/lfc6XdfR0NAARVH474OIiIiIiIiI9iilyJ9Qk4irCcTS5ZEfBmC32zoV+aPpZjSkY2go7uZvzraN/FWo99VgP/eYDiN/RwwByAl5NEVjsNvtMARzZ7nRJvILMCO/XTAP3rWZV2AXbIAOQDegFf+Pep5hGEin09iyZQuqqqq4KXYXYnUEUFtbCwBW/N/btLS0YMuWLdiwYQNDcx9hs9kwcODAve6LTERERERERES092gb+RNqEtFMMxpTUXNcj6bC0AG7zQbJuf1xPXmtgGi6CQ3FXfwN6Riasy0AALtgQ0gOoN5bg/E1oxFxB1El+80Q30kFXUO2oCJbULEpV8DgfC1SG9MQIMAm2Nr8ECAUf6beVVVVZTVZ2jVYgQEIgoC6ujpUV1cjn8/39nJ6XCaTwQcffIDBgwfz22f6CJfLxW8XIyIiIiIiIqI+Qzd0pHJpxNtG/nQMmXwW2UIWhmFGeskpwu2SEXJsK/JriGZaA39jKoamYuS3CTaE5CrUeSMYXzMKYXcQgS5Gfk3XkClG/mxBhW4YsAs2yA4RPpcbkUAIPtELt12G26lAcojceNnHOJ1O7vTfDRj+27Db7Xvlf3R+vx/5fB6iKMLlcvX2coiIiIiIiIiIqBeVIr85rieJWKalOK4nY87kN3TYBTskpwjFKSEo+7cZ+WOZprJxPU2Z8shf441g35qRiLhDCEh+2LuwEVIr7uTPlEV+oThGyI2hgYGoknzwSV74XB7ITomRn6iI4b8CyLKMTCbDw32JiIiIiIiIiCqMbuhI5zLmwbtqCk0Zc65+Op9BNq9Chw5HJyJ/QdMQzbSO6ylFfgMGBEFASA6gxh3BvtUjEVaCCMpV3Yr8pdBvGDpsgg2SQ4TH5caQwEAEJB98ogc+0cvIT7QDDP8VQJIkZDKZ3l4GERERERERERHtQlbkzyURzybRlGlGY7oJqXy6PPI7ipFf8nc4iriga4ilm9GQjloje9pG/qBchWp3GGOrRxQjvx92W+enaLSN/OZO/tbIr7gUDK4agIDsh1f0wCd6oDhlRn6iLmL4rwB2ux26rnPHPxERERERERHRXsIwDKTyrTP5mzItaEjHkMqZkd+AGdNlh9SpyN+YjqJh68gPM/JH3CGMiYxAxL1rIn+V7INP9DLyE/Ughv8KIQgCwz8RERERERER0R6oFPkTagpxNbHNyC85RCgOCQHJ12Gc13QNsUxLMfCbu/ljmeY2kd+PiBLEmMg+CCshBJUqOHog8osOEe42kb+0k9/tVBj5iXYRhv8KwehPRERERERERNT3GYaBdD6DuJpEXE2gORPHlnQUqVwa6lY75mWHuJ3IryOWaUZjOmaF/limGYZhRv5AMfKPigxDpJuRXy3kkClkrcgvwAbJKcLtVDCoqn/ZuB5GfqLdi+G/gjD+ExERERERERH1HaXIn1CTiBfH9WxJR5HOpduNxel05E/HEE3FEM00F2O8GfnDShAjw8MQUYIIyQE47J2P/LquI6upyOZVZApZaIYOmxX5ZQz090NAroJP8sDn8kBxyR0eEExEuw/DfwVh+CciIiIiIiIi6h3tIn82joZUFKlcqnXHvGCD7BAhOURUbSvyG7o56icVRWM6hsY2kR8AgnIVwkoQw8NDdzryZwsqCoZmRX7FKWOAv96M/KIbPtHLyE/URzH8VxBd13t7CUREREREREREez3DMJDJZxFXE1bkb0yZ43rMHfMGbIJg7eTfUeRvTMWKI3vMcT1aMfKXdvIPDw1BxB1CUA7A2ZXIb+itM/nzKjRDs8b1KE4Z/f31CMp++EQPIz/1effddx+WLFmCTZs2Yb/99sOyZcswZcqUDu+dNm0aXnvttXbXjzrqKLz00ksAgDPPPBOPP/542ftnzpyJlStX9vzidwGG/wphs9mQz+d7exlERERERERERHsVK/LnkohnE2gp7uRP5tLIFNTiWBwBktPcye+TvB3O0tetnfyxNjv5m6zIXyX5EXEHsU9oCCJucye/0975tNdh5BcESA4JskNEP18dQnJV60x+l8LIT3uMZ555BvPnz8fy5csxdepULF26FDNnzsT69etRXV3d7v7f/va3yOVy1tvRaBT77bcfTj755LL7jjjiCKxYscJ6WxTFXfciehjDf4WQZRmZTKa3l0FEREREREREtEezDt7tKPLrmjmTvxORvzljfmxD2gz90XQzNEMDAFRJPoSVIIaFBpvjepSdjfw6BAEQ7SIUp1QW+b2iBx5GftrD3XnnnTj33HMxd+5cAMDy5cvx0ksv4dFHH8WVV17Z7v5gMFj29tNPPw1FUdqFf1EUUVtbu+sWvgsx/FcISZKQTqd7exlERERERERERHuMtjP5mzMtaEjHkFRTyGpm5C+NxelU5C/u4m9IR8sjv+hD2B3EsMAghN1BhJUAnHZnp9eoGzrUQg6ZQhbZggpN0yHY2kR+by2CShV8opeRn/YoiUQC8XjcelsUxQ533OdyObz33ntYsGCBdc1ms2H69OlYu3Ztpz7XI488gtmzZ8PtdpddX7NmDaqrqxEIBHDYYYfhhhtuQCgU6uYr2r0Y/iuEoigM/0RERERERERE21CK/Ak1haasOXInmUshW8hC03UIECA5XTuI/Aaai98FYM7kjyGabrIiv1/0IuIOYmibyO/qRuTPFlTzrABNBwRAcrRG/oBcBZ9kzuT3OBXYbIz8tGcaM2ZM2duLFi3C4sWL293X2NgITdNQU1NTdr2mpgaffPLJDj/P22+/jX/84x945JFHyq4fccQROOGEEzBkyBB8/vnnuOqqq3DkkUdi7dq1sHfhLI3ewvBfIUo7/g3DgCAIvb0cIiIiIiIiIqJeUzp4N6GmrFCf2DryO1yQnCJ8YggOW/uEphtGcdRPrHVcTyqGQpvIH3YHMSQwABF3EGEl2O3Iny2oyOsF2GCD6HBBcUqo89YgWIr8Lg88LjcjP+1V1q1bh379+llv76r5+o888gjGjRvX7iDg2bNnW/88btw4jB8/HsOGDcOaNWtw+OGH75K19CSG/wohyzLDPxERERERERFVnGw+a87kV5NoycaxJRVFMpcyd8zrOgSYO+YlhwifeweRvziupzEdQ2O6CQW9AADwiR6E3SEMrupvRn45CJej+5G/oGsQAIgOEbJTQp23GkE5AF/x4F1GfqoEXq8XPp9vh/eFw2HY7XZs3ry57PrmzZt3OJ8/lUrh6aefxnXXXbfDzzN06FCEw2F89tlnDP/Ud/BwXyIiIiIiIiLa22XzWcRzKevg3dbIr6KgF2CDYMZ0hwivEoKjgwNzzcifKI7qibaL/F7Rg4gSxKT6fggrIYSVAESHq9NrNAwDakFFpqPI7xBRF6g2d/KLXnhFN7wuDyM/0Xa4XC5MmjQJq1atwqxZswAAuq5j1apVuPjii7f7sc899xxUVcUPfvCDHX6er776CtFoFHV1dT2x7F2O4b9ClMK/YRi9vRQiIiIiIiIiop1WHvkTxXE9SSvym+N6SpHfvc3IH1cT5qG7xZE90XQM+VLkd3kQcQexf10/RNxBhJQgpG5E/mwx9Bd0cwxQ6TsMBlVFEFYCVuT3uNywd3B2ABFt3/z58zFnzhxMnjwZU6ZMwdKlS5FKpTB37lwAwBlnnIF+/frh5ptvLvu4Rx55BLNmzWp3YG8ymcS1116LE088EbW1tfj8889x+eWXY5999sHMmTN32+vaGQz/FUKSJO74JyIiIiIiIqI9UragIq4mkVCTaM7G0ZiKIq6akV/TC0BpJr9DQvV2In9CTaIhFW0d2ZOJIa+VIr8bYSWEiXX7IqwEEXZ3P/JnC6r5XEGAaHdBdkoYVBVGSAmWjeth5CfqGaeeeioaGhpwzTXXYNOmTZgwYQJWrlxpHfi7cePGdt85s379evz1r3/Fn/70p3bPs9vt+Pvf/47HH38czc3NqK+vx4wZM3D99dfvsrMGeppgVMAW8K+++goDBgzAl19+if79+/f2cna7lpYW/PWvf8VXX32Fs88+Gw4Hv95DRERERERERH2TWsghriasmfwNqRjiaqI4FseM9KUd85JDgrODyG8YQFxNoCEdNXfzFw/fLUV+j8uNiBJExB0qRv4AJEfnY55hGFC1HLL5bIeRP6RUIaQE4XW54ZO88DLyE3VapbfcnsICXCHaHu5LRERERERERNQXlCJ/aSd/QzqGeDaJbCFbHItjWJE/rATgtLc/MNcwgHguica2O/nTMeS0PADA41IQVoKYUDsWYSWIiDvYvchfUJHNZ5ErjhEqRf6B/jBCbkZ+IupbGP4rhKIoyGazvb0MIiIiIiIiIqpQaiGHhJpEXE2Y43rSMbRkk1ALqjVTX3S4IO8g8idyydZ5/MXYv3XkH187GhElhLA7CLnbkV9FTs9bkV9yiujvr0e4zbger+hh5CeiPonhv0JIksQd/0RERERERES0W7RG/iRa1DgaUtHiTv7yyC85RISUqu1GfmtUT/HnnJYDALjLIn8QYSUI2Sl1eo07jvx1ZZHfI3rgYOQnoj0Ew3+F4I5/IiIiIiIiItoVcoUc4m0if2OqCS3ZOLKFtjHdCckpIahUwbXNyJ9CYyqKxnQMDcVxPWop8jsVhN1BjKsZhYg7iMjORP6CiryWByDAZXdCdkrFyB+AT/Qy8hPRXoHhv0LIsoxMJsMd/0RERERERETUbblCDvFcEvGsObKnIRVDixrfasf8jiN/MpcqBv7W0F+K/IpTRkQJYt+akda4HqWLkT+n5ZEpZNtFfskpoZ+vFhElCK/ogU80Z/I7OjggmIhoT8bf1SqEKIpQVZXhn4iIiIiIiIg6JafliwfvptCSjaMxFUNzMfLndTOmdybyp3Ipc1RPMfA3pGNQCyoAM/KHlSD2rR6JiNsc16O45E6vsRT5s4UsMgUVec0cI9RR5PeKHvhcHkZ+IqoI/J2uQthsNkZ/IiIiIiIiIupQTstbM/nj2QQa0lE0F8f1lHbMdyry51PWmJ7Sz9lS5HfICLuD2DcyAuFi5Hd3K/KryBayUAvmgb6lswLqvbWIuIPWobuM/ERUyfi7XwUxDIPxn4iIiIiIiKjC5bU84moSCTWJlmwCjekYmrNxZArZ8tn3DhFBuQpOmwOCIJQ9wzCAdD6DhnS0GPijaEzFkClGftkhIeIOYkwx8kd2MvLn2o7rcYio89YUD971wicx8hMRba3P/46oaRoWL16MX/7yl9i0aRPq6+tx5pln4uqrr273Pzq0fTabrbeXQERERERERES7UV7LI6GmEFcTaFGTaEy17uTPFWfqu+zmjvmg5IfT7uywt6RyZuRvbLObP1PIAgBkh4iwO4RRkeHFg3dDUJwyOpttDMNAXssjUzx4d+t11XqqEXaH4C/N5BfdcHbwHQdERNSqz4f/W2+9FQ888AAef/xxjB07Fu+++y7mzp0Lv9+PSy+9tLeXt0fhjn8iIiIiIiKivVdBK5QdvNuYjqEp09JhTA9Ivh1E/lgx8kfLIr/kEBFWghgVGYaIO2SO63EqXY782YKKTEEt7uQ34LQ7ITsk1HoiVuQvzeXvaKwQERFtX58P/2+++SaOP/54HH300QCAwYMH4//9v/+Ht99+u5dXtmfSdb23l0BEREREREREO6lt5E/kkmhIxdCUaS5G/jwEAE67A5JDQpXkg2sbkT/dJvKXfk4XMgAA0SEiUoz8YSWIiDsIt9Pd6cgPmGcHZPNZZAsq1K0if40njIgSgl/yMvITEfWwPh/+DzroIDz00EP49NNPMWLECHz00Uf461//ijvvvHObH6OqKlRVtd5OJBK7Y6l7BO74JyIiIiIiItqzlCJ/6fDdhlQMTdkWZPOl2feAy+6A5BB3GPkb02bgLx28m84XI7/dhYg7iBHhocVxPUG4Xd2I/AUV2Xy2LPJLDhHVnjDCShB+yWcdvsvIT0S06/T58H/llVciHo9j1KhRsNvt0DQNN954I04//fRtfszNN9+Ma6+9djeucs/gdDqRy+V6exlEREREREREtA0FrYBEzpzJn1CTaEjHEMuUR36n3QF5R5E/n22ziz+Khq0if1gJYkRoCMJKEGF3CN6djvyA0+aA5BRR7Q4j7DYjv1d0wyd6GfmJiHazPh/+n332WTz11FP41a9+hbFjx+LDDz/EvHnzUF9fjzlz5nT4MQsWLMD8+fOtt7/++muMGTNmdy25z5JlGel0GqFQqLeXQkRERERERFTxCrpW3MXfGvmbMi3IWJG/dcf89iJ/Jp+1DtwtjetJ5dMAzJn+ESWI4aEhiChBhN1BeF2enYr8Bgy4bOa6Iu4wIu4gfKIXPskDn8sDl8PVQ79CRETUXX0+/F922WW48sorMXv2bADAuHHj8N///hc333zzNsO/KIoQRdF6Ox6P75a19nWSJCGdTvf2MoiIiIiIiIgqTkHXkCyO6jEP3m1CLNPc9chfUIs7+aPWjv5UrhT5nQgrQQwLDUakOJO/q5E/r+WR6WgnfzHyh90B+EVzXI9PZOQnIuqr+nz4T6fTsNlsZdfsdjsPqe0GRVGQSqV6exlEREREREREe7XyyJ9EYzqGWKYZ2bwKVVNhAOaOeacIv+SFaHd1GPmzBdWaxd+QiqIxHUOyTeQPKQEMCw5CRAkh7A7C143Iny2oyBRUqAVzNLDT5oDoEBF2BxFxh6zI7xU9EBn5iYj2GH0+/B977LG48cYbMXDgQIwdOxYffPAB7rzzTpx11lm9vbQ9jizLyGazMAyjwz9QEBEREREREVHXaNa4HvNHNN2EaKapGPlzxbE4DkhOCT7JA9Ee3Ebkz6HRivzmjv5kzty857Q7EFaCGBoYaAZ5JQSv6IGtC3+3L0X+0g9AgMNmh+SQEFICiChBVEk++EQvIz8R0V6gz4f/ZcuWYeHChbjwwguxZcsW1NfX4/zzz8c111zT20vb45Rm/DP8ExEREREREXWdpmvmwbvZBBK5FKKpGKLFcT2qVtoxb28T+be1k79N5C8evpsoRX6bGfmHBAYUx/V0J/IXkC1k20R+wGFzQHJICMoBRIoH75rjeryM/EREe6E+H/69Xi+WLl2KpUuX9vZS9niyLCOTyfT2MoiIiIiIiIj6vFLkT1g7+WOIpttEfsOA027Ovt9e5FcLOWsXf+nnRC4JwIzxYSWIwVUDEHGbB+/6RG+XIn9BK5gz+QtZZAs5AAbsNgdkh9gu8ntFDySHuMNnEhHRnq/Ph3/qOYqiWDv+iYiIiIiIiMik6RqSuVT5uJ5001Y75u2QHSJ8ohuio+NxPblC3tzBn44Wx/XEkFDbRv4ABlf1R9gdRFgJwi91N/K3rsteXFdAqkLEHUKV7IO3ePAuIz8RUeVi+K8gsiyjqamJ4Z+IiIiIiIgqlq7rSOSSSKgpxNUEGtNNiKWbigfcmgfvliK/16UgrAQ6jvxavs08fnNcT3yryD/I3684k9/cdd/VyN968K4KHQYcxZ38AclvHrwreeGTvPC53JCcUk/9EhER0V6A4b+CKIqCr7/+ureXQURERERERLRb6LreZid/ArFMMxrTTea4njaRXypG/pBSBZtga/ectpG/MR1DYyqGFjUBAHAIdoTcQQzcmcivF5DNt+7kNyO/HbJDQpXkQ7U71GYmv4eRn4iIdojhv4KUZvxzxz8RERERERHtbcojfxKxTDOi6RjSxcivw4DTZs7k93Qi8je2mclfivx2wY6wEkB/fx0mKvsi7A6iaqcifw4GDNhtNkgOCX7Jh+FtIr9X9EBm5Cciom5g+K8gPNyXiIiIiIiI9ga6oSOZSyOuJhDPJtGUaUZjMfJnCyqMLkX+pmLkj3Yc+X11mOAei4gSRJXs6/A521LQNfPQ3XzHkX+YO4iA5IdXdMMnehn5iYioxzD8VxC3280d/0RERERERLRHKUX+RGlcT7o88sMA7HYbZIe03cifbxP5G4o7+pvVOAAz8oeUqh6I/Gox9OdgQIfdZodkF+GTvBjmDqGqzU5+xSn32K8RERHR1hj+K4gkSQz/RERERERE1Ge1i/yZFjSmoua4Hk2FocPcMe/c/k7+vFZANN1kBf6GdBTN2TaRX65Cva8G+ymjEXYHEZD9Ox35bYJ5ILDP5cGwQAhVsh/e4kx+Rn4iItrdGP4rCEf9EBERERERUV+hGzpSuTTiahIJNYlocVxPJp9FtpCFYQB2wYz8bpeMkGNbkV9DNNN68G5DKobmbAsA8+ODcgD13hqMr2mN/PYuRH5N15ApHrqbzZtnBdgFW1nk90s++CQvfKIHskOC0IWZ/0RERLsCw38FEUURqqpyxz8RERERERHtVqXIn7AO3m0pjuvJmDP5DR12wQ7JKUJxSghuYwd+XtMQy5g7+RtSUTSmY2jKmJHfJtgQkqtQ541gfM2obkf+bEG1Qr9uGLALAmSHBK/LjSGBgQgUx/WUZvIz8hMRUV/E8F9BBEGAzdb5P/AQERERERERdZVu6EjnMubBu2oKTZlmNJQif141Z993IvIXNA3RTOu4nlLkN2BAEASE5ABqPBHsWz0SEXcIAckPexf+zrt15DcMA7Zi5Pcw8hMR0R6O4b/C6LrOHf9ERERERETUI6zIn0sink2iKdOMxnQTUvl0cSyODodgh+QoRn7J3+GGtIKuIZpuskb1bB35g3IVqt1hjK0egbASRFCu6lbkL4V+w9BhE2yQHGIx8g9AQPKXHbzLyE9ERHsyhv8Kwz+4EBERERERUXcYhoFUvnUmf1OmBQ2pmBX5zQNubZAd0g4jfyzdjMZ0FA2pGBraRn6YkT/iDmFMZAQi7iCCsh92m73T62wb+c1xPa2RX3EpGFw1AIGtDt7l35WJiGhvw/BfYQzDgK7rvb0MIiIiIiIi6sNKkT+hphBXE2jOxLElHUUqVx75JYcIxbHtyK/pGmKZFjSkotbInlimuU3k9yOiBDEmMtzcya9UwdEDkV90iHAXI3+V7INP9DLyExFRRWH4rzA2m42jfoiIiIiIiMhiGAbS+QziarJd5Fe32jEvO0QEJF+HO/A1XUcs02yN62lIR83Ib5iRP1CM/KMjwxBWQl2O/LquF0f1ZK3IL8AGyWlG/kFV/ct28rudCiM/EVEFue+++7BkyRJs2rQJ++23H5YtW4YpU6Z0eO9jjz2GuXPnll0TRRHZbNZ62zAMLFq0CA8//DCam5tx8MEH44EHHsDw4cN36evoKQz/FYY7/omIiIiIiCpXKfIn1CTipXE9pZ38OxH5G9MxRDNNZZE/rAQxKjwMYSWIkByAw97FyK+pyObN0K8ZOmylyO+UMbCqHwJSFXySBz6XB4pL7vCAYCIiqgzPPPMM5s+fj+XLl2Pq1KlYunQpZs6cifXr16O6urrDj/H5fFi/fr319tZfLL7ttttwzz334PHHH8eQIUOwcOFCzJw5E+vWrYMkSbv09fQEhv8K43K5oKpqby+DiIiIiIiIdrF2kT8bR0MqilQu1bpjXrBBdoiQHCKqthP5m7Kt43qiqRiimWbohrmpLChXIawEMSI8FJGdjPzZgoqCoVmRX3HKGOCvR0Cugk90wyd6GfmJiKidO++8E+eee661i3/58uV46aWX8Oijj+LKK6/s8GMEQUBtbW2H7zMMA0uXLsXVV1+N448/HgDwxBNPoKamBi+88AJmz569a15ID2L4rzCyLCOdTvf2MoiIiIiIiKgHGYaBTD6LuJooi/zpXBqZQha6YUAQBGsn/zYjv6EXD+2NorE4k79t5C/t5B9ejPxBOQBnVyK/obfO5M+r0AzNGtejOGX099cjKPvhEz2M/EREFS6RSCAej1tvi6IIURTb3ZfL5fDee+9hwYIF1jWbzYbp06dj7dq123x+MpnEoEGDoOs69t9/f9x0000YO3YsAGDDhg3YtGkTpk+fbt3v9/sxdepUrF27luGf+h6GfyIiIiIioj3b1pG/pRj5k7k0MgXVHIvTJvL7Je92I39jcVRPQyqGWKYJWinyS36E3UHsExqCiNvcye+0dz4jdBj5BQGSQzIjv6818ntFD9wuhZGfiIgsY8aMKXt70aJFWLx4cbv7GhsboWkaampqyq7X1NTgk08+6fDZI0eOxKOPPorx48ejpaUFt99+Ow466CD885//RP/+/bFp0ybrGVs/s/S+vo7hv8Iw/BMREREREe1ZrIN3s4n2kV/XzJn8TnNcj0/ydnhgrt4m8jdYO/lbI3+V5ENECWGf0GBzXI+ys5FfhyAAol2E4pTQz1eHkFzVevAuIz8REe3AunXr0K9fP+vtjnb7d9eBBx6IAw880Hr7oIMOwujRo/Hggw/i+uuv77HP05sY/itMKfwbxW/zJCIiIiIior6j7Uz+5kwLGtIxJNUUspoZ+c2xOC5IDmm7kb85E0dDOmaN7Immm6EZGgCgSvQh7A5iWHAQIu4QQkoVnHZnp9eoGzrUQg6ZQtaM/LoOwdYm8ntrEVSq4BO98IoeeBj5iYioG7xeL3w+3w7vC4fDsNvt2Lx5c9n1zZs3b3OG/9acTicmTpyIzz77DACsj9u8eTPq6urKnjlhwoROvoLexfBfYRRFQSaTYfgnIiIiIiLqZWWRv7ST34r8OgQInYj8hvUFgtK4nmi6yYr8ftGLiDuIoYFBCLuDCCsBuLoR+bMFFZlCFpqmAwIgOcojv7c4k5+Rn4iIdjeXy4VJkyZh1apVmDVrFgDz4PhVq1bh4osv7tQzNE3Dxx9/jKOOOgoAMGTIENTW1mLVqlVW6I/H43jrrbfwox/9aFe8jB7H8F9hZFlGJpPp7WUQERERERFVlNJM/oSasiJ/IpdCtpBtjfwOFySnCJ/kgcPW/q/rumEUR/2UxvVEEU03odAm8ofdQQwJDEDEHURYCe5U5C/oGmywQXS4oDgl1HlrEJSr4JM88Lk88LjcsNkY+YmIqPfNnz8fc+bMweTJkzFlyhQsXboUqVQKc+fOBQCcccYZ6NevH26++WYAwHXXXYdvfetb2GeffdDc3IwlS5bgv//9L8455xwAgCAImDdvHm644QYMHz4cQ4YMwcKFC1FfX299caGvY/ivMG1H/RAREREREVHPy+az5kz+4sG7W1JRJHMpc8d828jvEOFzh7Yf+Yvz+BvS5k7+gl4AYEb+kDuIwaXILwfhcnQv8mcLKvJ6ATYIEIs7+eu81QjKAfiKM/kZ+YmIqC879dRT0dDQgGuuuQabNm3ChAkTsHLlSutw3o0bN5b971hTUxPOPfdcbNq0CYFAAJMmTcKbb75ZdqDw5ZdfjlQqhfPOOw/Nzc349re/jZUrV0KSpN3++rpDMCqgAH/11VcYMGAAvvzyS/Tv37+3l7PbtbS0IJ/Pw+Vy4fXXX8eWLVtwxhlnwOHg132IiIiIiIh2RjafRTyXsg7ebRv5zR3zAiSHaP1wdHBgrhn5E2hIR9GYMkf2NLaJ/D7Rg7A7hIhi7uKPKF2P/LlCDpli5C/oGgQAokOE7BARdgfNnfyil5GfiIh6XaW33J7C8lthOOqHiIiIiIioe8ojf6I4rieJTEFFQS8Ud/KbMd2rhLYZ+ePZRNlO/sZ0zIr8XtGDiBLEpPp+CBdDv+hwdXqNhmFALahlkR+A9YWHQVURhJVA8eBdNzwuN+wdnB1AREREezaG/wrT9nBfIiIiIiIi6li2oCKuJpEoHbybbI38ml4ArHE9EqoV97Yjv5owA7+1kz+GfCnyuzwIu4PYv25fRNxBhJQgpG5E/mwx9Be0AiAIEO0uyE4Jg6rCCCnBsnE9jPxERESVgeG/wnDHPxERERERUblsQUWizUz+hlQMcTXRYeSPKG44txH5E2oSDeloeeTXSpHfjbASwsS6fc2d/O5uRH4th2w+a87k307k94oeeBn5iYiIKhrDf4Xhjn8iIiIiIqpkaiGHuJrYKvInkS1kkdcLENA6FieiBDuM/IYBcyd/OoaGVNQa11OK/B6XgogSwoTasYgoIYTdAUgOsdNrtCJ/QUU2n0W+OK6nFPkH+sMIuYPwutzwSV5GfiIiImqH4b/ClHb8M/wTEREREdHeTi3kijv5E2hRzZn8Ldkk1IJqRX6Xw2UecKsE4LS3PzDXMIB4Llmcx996+G5OywMwI39YCWK/2jHFyB+E3O3IryKn5yHA3MkvOUUM8NeXjevxih5GfiIiItohhv8KoygKstlsby+DiIiIiIioR+UKOcRL43rUOBpSUcSzSXMsTnGmvliM/B6lapuRP5FLto7qSUXRkG5CTssBANzFyD++djQixYN3ZafU6TXuKPL399dZB+/6RA88ogcORn4iIiLqBob/CuN0OpHL5bjjn4iIiIiI9ljlkd88PLclG0e20DamOyE5JYS2G/lTaExFiyN7YmhIx1ojv1NB2B3E+JpRCLuDiOxk5M/reQACXHYnZKdUFvm9xZ38jPxERETUUxj+K5AgCL29BCIiIiIiok7JaXlzJn/WHNnTkIqhRY232TFvg2h3QHJKCCpVcG0j8idzKTQUI38p9KvFyK84ZUSUIMbVjLTG9ShdjPw5LY9MoXTwbnnk7+evRUQJwit6zNDvcsPRwdkBRERERD2Ff9KoQIZhcMc/ERERERH1OTktX5zJbx6825iKobkY+Us75ks7+bcX+VO5FBqKcb90AG/byB9Wgti3eiQibnNcj+KSO73GUuTPFrLIFFTrQF9XcV39fLUIF2fye0UPfC4PIz8RERHtdvzTRwUSBIHhn4iIiIiIelXbyB/PJtCQjqK5OK6ntGO+U5E/n2oT+M2fswUVACA7JETcIYxtE/nd3Yz82YIKtWAe6Cs6XJAcIuq9tYi4g/C6PPBJjPxERETUd/BPJBWK4Z+IiIiIiHaXUuRPqEm0FCN/SzaBTCFbHvkdIoLy9iJ/2trBXwr95ZE/iDGR4Qi7Q4h0O/KryBayyLUZ1yM5RNR5a4o7+b2M/ERERNTn8U8pFYrhn4iIiIiIdoW8lkdCTSGuJtCiJtGYat3Jbx6cW5x97xARlPxw2p3tziEzDCCdz6AhHbV28TemoshYkV9E2B3C6MhwRNxBRJQQFKeMzh5nZhgG8loemYLaZl2Ay+6yIn9ICcJfmskvujs8IJiIiIior2L4r0CCIEDX9d5eBhERERER7eHaRv64mkRDu8jfGtMDkq/DyA8AqVwGDcW4X9rJnylkAQCSQ0TEHcSoyD4IK0FE3CG4nUqXI3+2oCJTUIs7+Q047U7IDgm1ngjC7hAjPxEREe1VGP4rkCiKyGQy8Pl8vb0UIiIiIiLaQxS0AuK5JOLZJOJqAo3pJjRlmouR34zp5lgcCVWSD67tRP628/gbUzGkCxkAgOgQEVGCGBUZVoz8Qbid7k5HfsAcK5TNZzuM/DWeMCJKCH7JC2/x8N2OxgoRERER7ekY/iuQLMtIp9O9vQwiIiIiIuqjSpG/dPhuQyqGpmwLsvnS7HvAZXdAcojbjfzpUuRvE/rT+WLkt7sQcYcwIjy0OK4nCLerG5G/oCKbz0JtE/klh2hFfp/khY+Rn4iIiCoMw38FkmUZqVSqt5dBRERERER9QEErIJEzx/Uk1CQa0jHEMuWR32l3QN5R5M9n0ZiKWSN7GraK/GEliBGhIda4Hs9OR37AaXNAcoqodocRdgfhl3zwim74RC8jPxEREVU0hv8KpCgKd/wTEREREVWggq4Vd/G3Rv6mTAsyVuRv3TG/vcifyWetcT0NxXE9qbz5dwyX3YVIm8gfdofg3anIn4MBwGVzFuf9hxFxB+ETvfBJHvhcHrgcrp75BSIiIiLaS+wR4f/rr7/GFVdcgZdffhnpdBr77LMPVqxYgcmTJ/f20vZIsiwjm83CMIwO/xBPRERERER7voKuIVkc1VOayR/LNHc98hfU4k7+KBqL43qSuVLkdyKihLBPaLA1k9/r8nQp8ue1PDJtdvIbMMoif9gdgF/0wSd64BMZ+YmIiIg6o8+H/6amJhx88ME49NBD8fLLLyMSieDf//43AoFAby9tj1Wa8c/wT0RERES0dyiP/Ek0pmOIZZqRzatQNbV1x7xThF/yQrS7Ovy7QLagFnfxbyvyBzE0OBgRJYiwOwhfdyN/QYVayAEwx/WIDhFhtzkCqBT5vaIHIiM/ERERUbf0+fB/6623YsCAAVixYoV1bciQIb24oj1f2/BPRERERER7Fs0a12P+iKabEM00FSN/rrhj3gHJKcEneSDag9uI/Dkr7jcUZ/Inc+ZZYC67EyElgKHBQcXIH+pW5M8WVGQKKnIFc1xPKfKHlAAiShBVkg8+0cvIT0RERNTD+nz4/93vfoeZM2fi5JNPxmuvvYZ+/frhwgsvxLnnnrvNj1FVFaqqWm8nEondsdQ9hizLyGQyvb0MIiIiIiLaAU3XzIN3swkkcilEUzFEi+N6VK20Y97eJvJvayd/28gfQ2M6ikQx8jvtDoSVIIYEBiDiDiKihOAVPbB1ofLntQKyhaw5l7+gWpFfckgIyQFE3Gbk94oe+EQvIz8RERHRLtbnw/9//vMfPPDAA5g/fz6uuuoqvPPOO7j00kvhcrkwZ86cDj/m5ptvxrXXXrubV7rnUBQFzc3N3PFPRERERNSHtIv86Rii6TaR3zDgtDsgOcQdRv7oVgfvJnJJAGaMDytBDK4yI3+4eEhu1yO/Wgz9OQAGHDZzXcFi5PdLreN6JIfYU79ERERERNRJfT7867qOyZMn46abbgIATJw4Ef/4xz+wfPnybYb/BQsWYP78+dbbX3/9NcaMGbNb1rsn4I5/IiIiIqLepekakrlU+biedFPrjvli5JcdInyiG6Kj43E9aiGHxnTrTv6GdAwJ1Yz8Divy9zcjvxKET+pa5C9oheJM/lLkB+w2O2SHiIBchYg71GYnPyM/ERERUV/R58N/XV1du2g/evRo/OY3v9nmx4iiCFFs/QNnPB7fZevbEymKgkwmwx3/RERERES7ga7rSOSSSKgpxNUEGttEfrU4Fsdhs0NyiPC6FISVQIeRP1fImzv4izP5G9MxxMsifwCD/P3MQ3IVc9d9VyN/aSa/Oa7H3MkvO0QEJDPy+yUvfJIXPpcbklPqqV8iIiIiIuphfT78H3zwwVi/fn3ZtU8//RSDBg3qpRXt+Xi4LxERERHRrrF15I9lmtGYbjLH9WwV+T0uBSGlCjbB1u45OS1ftos/moqhRTXPLnMIdoTcQQzsgchf+qHDgMNmh+yQUCX5UO0OWeN6fKKHkZ+IiIhoD9Pnw/9PfvITHHTQQbjppptwyimn4O2338ZDDz2Ehx56qLeXtsdSFKXs8GMiIiIiIuo6XdfLxvXEMk1lkV+HUTzgtnORv+3hu6XIbxfsCCkB9PfXYaKyL8LFQ3K7FPn1ArJ5tezgXbvNBtkhwS/5MJyRn4iIiGiv0+fD/wEHHIDnn38eCxYswHXXXYchQ4Zg6dKlOP3003t7aXss7vgnIiIiIuoa3dCRzKURVxOIZ5OIZZoRTceQzmehFnLQoXcq8ue1PBrTTWhItY7saRf5fXWY4B6LiBJElezr8DnbUtCLO/nzKrKFHAwYsNtskIqRf5/iTP7SwbsyIz8RERHRXqnPh38AOOaYY3DMMcf09jL2GrIsI5vN9vYyiIiIiIj6pFLkT6hJc1xPuhmNxchfOnjXYTfH4uwo8kfTzWhIRc3Z/KkYmlXz/DEz8lftZOTXiofuqsjmczCgw26zQ7KL8EleDHOHEJD88Ipu+EQvIz8RERFRBdkjwj/1LIfDgUKhwB3/RERERFTx2kb+hJpENN1kRX5VU2HogN1u68RO/gKi6SYr8Deko2jOton8chXqfTXYTxmNsDuIgOzvRuRXzdC/deQXvRgWLN/JrzjlHvs1IiIiIqI9D8N/hRIEgeGfiIiIiCqKbuhI5dKIlyJ/xtzJn8lnkS1kYRgG7IIdklOE2yUj5OhE5C/O5G/OtgAA7IINQTmAem8Nxte0Rn57FyK/pmvIlA7ezavQDTPyyw4RPpcHwwIhVMl+eIsz+Rn5iYiIiGhrDP9ERERERLTXKUX+hHXwbktxJ3+mXeRXnBKC29iBn9c0xDJNZeN6moqR3ybYEJKrUOeNYHzNqG5H/mxBtUK/bhiwC7Zi5HdjaGCguZNf8sIneiA7JAhdONiXiIiIiCoTw3+FMgyDO/6JiIiIaK+gGzrSuYx58K6aQlOmGQ2lyJ9XzbE4nYj8BU1DNFM+rqcpUx75a7wR7FszEpHi/Hy7reuRvxT6DcOATRCKZwW4MSQwEIHiuJ7STH5GfiIiIiLqDob/CsVRP0RERES0J7Iify6JeDaJpuK4nlQx8uvQ4RDskBzFyC/5Yesgzpcif2lUT2M6hqZMCwwYEAQBITmAGncE+1aPRFgJIihX7WTk12ETzLMC3C43BreJ/KWZ/Iz8RERERN133333YcmSJdi0aRP2228/LFu2DFOmTOnw3ocffhhPPPEE/vGPfwAAJk2ahJtuuqns/jPPPBOPP/542cfNnDkTK1eu3HUvogcx/Fcohn8iIiIi6uu2jvzN2RY0pGJI5dNW5DfH4kjbj/y6hli6GY3pKBpSMTRsFfmDchWq3WGMiYxAxB1EUPbDbrN3ep1tI785rqc18isuBYOrBiAg+xn5iYiIiHaRZ555BvPnz8fy5csxdepULF26FDNnzsT69etRXV3d7v41a9bgtNNOw0EHHQRJknDrrbdixowZ+Oc//4l+/fpZ9x1xxBFYsWKF9bYoirvl9fQEhv8KJQgCCoVCby+DiIiIiAiAOYoylW89eLcp04KGdAypXBrq1jHdse3Ir+kaomnzuwDMkT1RxEqRHwKCsh8RdwhjIsMRcYd2SeSvkn3wiV7r4F1GfiIiIqJd684778S5556LuXPnAgCWL1+Ol156CY8++iiuvPLKdvc/9dRTZW//4he/wG9+8xusWrUKZ5xxhnVdFEXU1tbu2sXvIgz/FUqSJKTTaVRVVfX2UoiIiIiowpQif0JNIa4m0JyJY0s62mHklx0iApKvwziv6RpimRZrVE9DKopYthmGYUb+gOxHRAlidGQfhJUQgkoVHF2M/Gohh0wha0V+ATZIThFul4JBVf0RkP3wih74RA/cToWRn4iIiKiHJBIJxONx621RFDvccZ/L5fDee+9hwYIF1jWbzYbp06dj7dq1nfpc6XQa+XwewWCw7PqaNWtQXV2NQCCAww47DDfccANCoVA3X9HuxfBfoWRZRjqd7u1lEBEREdFezjAMpPMZxNVkWeRP59LtdsxvP/LriBXn+TcUD96NZdpH/lGRYQgrQYTkABz2zkd+XdeR1VRk8yoyhSw0Q4etFPmdCgZW9UNAqoJP8sDn8kBxyR0eEExEREREPWPMmDFlby9atAiLFy9ud19jYyM0TUNNTU3Z9ZqaGnzyySed+lxXXHEF6uvrMX36dOvaEUccgRNOOAFDhgzB559/jquuugpHHnkk1q5dC3sX/pzZWZ9//jlWrFiBzz//HHfffTeqq6vx8ssvY+DAgRg7dmyXn8fwX6EURUEmk+ntZRARERHRXqQU+RNqEnE1iabSTP5cqnXHvGCD7BAhOURUbSfymx8bLY7riSGWaYZu6ACAoFyFsBLEyPAwRHYy8mcLKgqGZkV+xSljgL8eAZmRn4iIiKg3rVu3rmze/q6ar3/LLbfg6aefxpo1ayBJknV99uzZ1j+PGzcO48ePx7Bhw7BmzRocfvjhPbqG1157DUceeSQOPvhgvP7667jxxhtRXV2Njz76CI888gh+/etfd/mZDP8VqjTqh4iIiIioO9pH/jgaUtE2kd88OHeHkd/QzXn+qSgai5E/2ibyB2Q/wkoQI8JDEVGCCMoBOLsS+Q29dSZ/vn3k7++vR7DNwbtul8LIT0RERNQHeL1e+Hy+Hd4XDodht9uxefPmsuubN2/e4Xz+22+/HbfccgteffVVjB8/frv3Dh06FOFwGJ999lmPh/8rr7wSN9xwA+bPnw+v12tdP+yww3Dvvfd265kM/xVKlmVkMhnzW6M5h5SIiIiItsMwDGTyWcTVBOJqEs1W5E8Xx+IYsAmCNa5nR5G/0ZrJH0Ms0wStFPklP8LuIIaHhiDsDiIkB3cq8muGBqF08K5TRn+fGfmtmfyM/ERERER7PJfLhUmTJmHVqlWYNWsWAPM7PFetWoWLL754mx9322234cYbb8Qf//hHTJ48eYef56uvvkI0GkVdXV1PLd3y8ccf41e/+lW769XV1WhsbOzWMxn+K5SiKEin0wz/RERERNSONZM/m0BLMfInc2lkCio0XTNn8jvNnfw+ydvhgbl6m8jf0GYnv2ZoAIAqyZzJv09osDmuRwnAae/8X0/aR34dggBIDgmyQ0I/Xx1CchUjPxEREVEFmD9/PubMmYPJkydjypQpWLp0KVKpFObOnQsAOOOMM9CvXz/cfPPNAIBbb70V11xzDX71q19h8ODB2LRpEwDA4/HA4/EgmUzi2muvxYknnoja2lp8/vnnuPzyy7HPPvtg5syZPb7+qqoqfPPNNxgyZEjZ9Q8++KBs3FFXMPxXqNKMf8MwenspRERERNSLSpE/oSbRnGlBQzqGpJpCVjMjvwAbJKcLkkPabuRvzsTRkI5ZI3ui6baR34ewEsSw4CCE3UGElQCcdmen16gbOtRCDplC1oz8ug7BBoh2EYrTjPzmuB4vvKIHHkZ+IiIioopy6qmnoqGhAddccw02bdqECRMmYOXKldaBvxs3boTN1vrnwwceeAC5XA4nnXRS2XNKBwjb7Xb8/e9/x+OPP47m5mbU19djxowZuP7663fJWQOzZ8/GFVdcgeeeew6CIEDXdbzxxhv42c9+hjPOOKNbzxSMCii/X331FQYMGIAvv/wS/fv37+3l7HYtLS3I5/NwuVzWtVdffRXpdBqnnXbaLjmFmoiIiIj6nrYz+Uvjelojvw4BghX5JYe4jchvWF8gKI3riaabWiO/6CvG/SAibnMnv6sbkT9bUM0xQpoOCCiO65EQVoIIKqWd/F54nErZX+KIiIiIaM9WiS03l8vhoosuwmOPPQZN0+BwOKBpGv7nf/4Hjz32WLf6LXf8VyhFUdDY2Mgd/0RERER7qdJM/oSaQlO2BQ2pGJK5FLKFbGvkd7ggObc3rscojvopjeuJIppuQqEY+f2iFxF3EEMDAxB2hxDeychf0M2Dd0WHC4pTQr23BgG5Cr7iuB6Py83IT0RERER7HZfLhYcffhjXXHMNPv74YySTSUycOBHDhw/v9jMZ/itU6XBfIiIiItrzZfNZcya/mkRLNo4tqSgS24r8YggOW/u/BliRvziPvyFt7uQv6AUAZuQPu4MYHBiASHFHf3cjf7agIq8XYIMAsbiTv85bjaAcYOQnIiIiooo1YMAADBgwAJqm4eOPP0ZTUxMCgUC3nsXwX6E445+IiIhoz9RR5E/mUm12zAuQHMWDd5UQHB0cmGtG/gQa0lE0psyRPY1tIr9P9CDsDmFwVX8z8stBuBzdj/wFXYMAQHSIkB0i6gLVCMpVxZn8bnhdHkZ+IiIiIqpY8+bNw7hx43D22WdD0zQccsghePPNN6EoCl588UVMmzaty89k+K9QDP9EREREfV82n0U8l0I8mzBDfSqKRC6JTEFFQS8Ud/KbMd27g8jfaO3kj5ZFfq/oQUQJYlJ9P4QVc1yP6HC1e862GIYBtaAi00HklxwiBlVFEFYCVuT3uNywdzBWiIiIiIioUv3617/GD37wAwDA73//e/znP//BJ598gieffBI///nP8cYbb3T5mQz/FYqjfoiIiIj6lmxBRVxNIlE6eDfZGvk1vQC02clfrbi3GfnjxcjfYI3riSFfivwuDyLuIPav62eN6+lO5M8WQ39eK0AQWtc1qCqCkFI+roeRn4iIiIho+xobG1FbWwsA+MMf/oBTTjkFI0aMwFlnnYW77767W89k+K9QpfDPHf9EREREu1/byF86PDeuJraK/C5IDgkRxQ3nNiJ/Qk2iIRW15vI3lkV+N8LuECbW7YuIO4iQEoTUzcifLUZ+CAJEuwuyU8KgqjBCShBelxs+yQsvIz8RERERUbfU1NRg3bp1qKurw8qVK/HAAw8AANLpNOz27v0Zm+G/QkmSBFVVe3sZRERERHs9tZBDXE1YM/nNyJ9EtpBFXi9AAKwd8xEl2GHkNwwgrpZ28hdDfzpmxngAHpcbESWIiXX7IqwEEXYHIDnETq/RMAyoWg7ZfLbDyD/QH0bIzchPRERERLQrzJ07F6eccgrq6uogCAKmT58OAHjrrbcwatSobj2T4b9C2e12aJrGHf9EREREPUgt5JBQk4irCTRn42hMx9CSTUItqFbkdzlckB0iwkoATnv7A3MNA4jnkq3z+Is7+XNaHgDgcSkIK0HsVzsGESWEiDvYvchfUJHNZ5HXNQCAaHdBcooY6O+HYJtxPV7Rw8hPRERERLQLLV68GPvuuy++/PJLnHzyyRBF88/3drsdV155ZbeeyfBf4Rj+iYiIiLqnbeRvUc2Dd9tGfgAQHS5IDhEhpWqbkT+RS7bO409F0ZBuQk7LAQDcLgURJYjxtaMRKR68KzulTq+xPPKryOl5CBCsyN/fX4+wEmydyS964GDkJyIiIiLa7U466aR21+bMmdPt5zH8VzBBEHp7CURERER7hFwhh7iaNMf1qHE0pprQko0jW2gb052QnNIOI39jMfKXfrYiv1NB2B3E+JpRCLuDiCjBnYr8eT0PlEX+OoSVAHyil5GfiIiIiKiX3XPPPTjvvPMgSRLuueee7d576aWXdvn5DP8Vjjv+iYiIiMrlCjnEc0nEs+Zu/oZUbKvIb4Nod0BySggqVXBtM/Kn0JiKFufym+N61GLkV5wyIkoQ42pGIaIEEXYHoXQx8ue0PDKF0kx+M/K77E7ITgn9/LWIKEF4RQ98ohdeRn4iIiIioj7lrrvuwumnnw5JknDXXXdt8z5BEBj+qesY/omIiKiS5bQ84moCCTWFlmwcjakYmtW4ORZHy0MQWnfyby/yJ3Mp6+DdUuhvG/nDShD71ow0I78ShOKSO73GUuTPFrLIlA7eBeAqrqufb6vI73LD0cEBwURERERE1Hds2LChw3/uKT3+N4K33noLU6dO7enH0i6i63pvL4GIiIhot8hp+eJM/qQZ+dMxNBd38pd2zHcm8qdyKXNUTzHwN6RjUAsqAEBxyAi7g9i3eiTCbjPyu7sZ+bMFFbm2kd8hot5bi4g7aB2663N5GPmJiIiIiPZg+Xweo0aNwosvvojRo0f32HN7/G8JJ598MjZu3NjTj6VdwG63I5/P9/YyiIiIiHpcKfIn1CRasgk0pKMdR36HiKC8ncifT1ljeko/Z4uRX3ZIiLiDGBsZYc3k717kV5EtZJFrM65HcoioK0Z+r8sDn8TIT0RERES0N3I6nchmsz3+3G79zeGUU07p8LphGIjFYju1INp9ZFlGJpPp7WUQERER7ZS8lke8FPnVJBpTrZHfPDi3OPveISIo+eG0OyEIQtkzDANI5zNoSEeLgT+KxlQMmTaRP+wOYkxkeDHyh7oc+fNaHpmC2mZdgMvuKkb+GoSVoHnwLiM/EREREVFFueiii3DrrbfiF7/4BRyOnvl7QLee8uqrr+LJJ5+Ex+Mpu24YBl5//fUeWRjterIsI51O9/YyiIiIiDotr+WRUFOIqwnE1SQa2kX+1pgekHwdRn4ASOXMyN9YHNVjRn5zl43kEBFxBzEqMhyR0rgep4IOHtOh9pE/D8Cw1lXriSDsDsFvHbzrhrOD7zggIiIiIqLK8M4772DVqlX405/+hHHjxsHtdpe9/7e//W2Xn9mt8D9t2jR4vV5897vfbfe+8ePHd+eR1AsY/omIiKgvK2gFxHNJxLNJxNUEGtNNaMo0bxXTnZAcEqokH1zbjfxm3C8dwFuK/KJDREQJYlRkGMJKEBF3EG6nu9ORHzDHCmXz5sG7pXU57U7IDgk1nggiShB+yQtvcS5/R2OFiIiIiIioclVVVeHEE0/s0Wd2K/xv7ysMr7zySrcXQ7tXKfwbhtHhX5KJiIiIdpe2kT+RS6IhFdsq8gMuu2OHkT+dy5QdutuYiiFdMEcbinYXIu4QRoaHIWLN5O9e5M8WVKhtIr/kEFHjCSOihBj5iYiIiIioS1asWNHjz+xS+P/yyy8xYMCAHl8E9Q5FURj+iYiIaLcrRf6EmkRcTaIxHUMs04JsPmtFfqfdAdkhbj/y57NtRvVE0ZCOIZ1vjfxhJYgR4SHFnfwheLoT+Qsqsvlsu8hf7QkjrAThl3zwim74RC8jPxERERER7ZQtW7Zg/fr1AICRI0eiurq628/qUvgfNGgQgsEg9ttvP0yYMMH6kcvlcM899+Dxxx/v9kJo95MkiYf7EhER0S5V0ApI5MyZ/Ak1iYZ0DE2ZFmS6GPkz+ay1g7/0cypvjix02V2IKEGMCJmRP+wOwbuTkd+AAZfNCckpIuIOI+IuP3jX5XD1yK8PERERERFRPB7HRRddhKeffhqapgEA7HY7Tj31VNx3333w+/1dfmaXwv+GDRvwwQcf4MMPP8QHH3yAZ599Fv/3f/8HAPD5fF3+5NS72u74JyIiItpZBV1DQi3t5Ddn8scyzW0if+uO+e1G/oJaDPyth++mcqXI70RECWGf0GBrJr/X5emZyO8wI3/YHYRf9MIneuATGfmJiIiIiGjXOvfcc/HBBx/gxRdfxIEHHggAWLt2LX784x/j/PPPx9NPP93lZ3Z5x/+gQYMwa9Ys69ratWsxZ84cXHfddV3+5NS7ZFlGS0tLby+DiIiI9kAFXUOyOKqnbeTP5lWomgoAcBZ3zPslL0S7q8PIny2oxXn8Uevw3WRZ5A9iWHAwIt2M/Hktj0xBNWfyF3LFdTkgOUSE3eYIIL/og684k19k5CciIiIiot3sxRdfxB//+Ed8+9vftq7NnDkTDz/8MI444ohuPbNbh/u2deCBB+Luu+/GwoULMXv27J19HO1GiqJg8+bN3PFPRERE26UVd/LHy2bylyJ/rmwsjk/yQLQHtxH5c1bcbyjO5E/mUgDMyB9WghgaHIRIcVyPrxuRP1tQkSmoyBVyMGBGftEhIqwEipHfC5/oZeQnIiIiIqI+IxQKdTjOx+/3IxAIdOuZXQr/uVwOLlf7vyANHz4c//znP7u1AOo9HPVDREREW9N0zZzJn00gkUshmoohWhzXo2qlHfN2SE6pGPm3tZO/beQ3d/SXIr/T7jAjf2CAueteCcEremDrQuXPawVkC1lzZE9BBSDAYbNDckgIKQFElCCqJB+8ogc+0cvIT0REREREfdbVV1+N+fPn48knn0RtbS0AYNOmTbjsssuwcOHCbj2zS+Hf4/FgzJgxmDhxIiZMmICJEyeivr4ey5Ytw/Tp07u1AOo9sizzcF8iIqIK1i7yp2OIpttEfsOA026OxdlR5I9agT+GxlQUiVLkt5mRf0hgQHEnv3lIbtcjv1oM/TkABhzFcT1BOYCIOwi/5CvO5GfkJyIiIiKiPcsDDzyAzz77DAMHDsTAgQMBABs3boQoimhoaMCDDz5o3fv+++936pldCv9//vOf8dFHH+Gjjz7CU089hQULFiCbzQIAjjjiCFxzzTUYN24cxo0bh1GjRnXl0dQLFEVBJpPhjn8iIqIKoOkakrmUNa4nmm5CNN3UumPeMOCwOyA7RPhEN0RHx+N61ELO2sVf+jmRSwIAHMXIP7hqACLuIMJKED6pa5G/oBWKM/lLkR+w2+yQi5E/7G67k98DySH2zC8QERERERFRL2l7pm5P6VL4//a3v112wICu61i/fj0+/PBDfPjhh3j77bfx8MMPY8uWLdA0rccXCwC33HILFixYgB//+MdYunTpLvkclUKWZesLN0RERLT3aBv5E2oSjVtHfgCOYkz3uhSElUCHkT9XyJs7+NNRazd/Qm0b+QMYVNUPEXcIYSUIfzcif2kmf7agwiju5JcdIgJSFSLuEKrkYuR3uSE5pZ75BSIiIiIiIuojNE3DoYceivHjx6OqqqrHnrtTh/vabDaMHj0ao0ePxmmnnWZd37x5804vrCPvvPMOHnzwQYwfP36XPL/SlEb9cMc/ERHRnkvXdSRySSTUFOJqAtF0M6LpGDIFFWpBhQEUZ9+bkT+kVMEm2No9J6fl28zjjyGaiqFFTQAAHIIdIXcQg/z9ijP5zdE63Y38akGFXhb5/a3jeiQvIz8REREREVUMu92OGTNm4F//+lffCf/bUlNT0+PPTCaTOP300/Hwww/jhhtu6PHnVyJRFJHNZhn+iYiI9hC6rpeN64llmtCYbjJn8m8V+T2diPyN1kz+1shvF+wIKwH099djYnEmf1VXI79eQDavWt9hYACw22yQHRKqJB+q3aE2M/k9jPxERERERFTR9t13X/znP//BkCFDeuyZuyT87woXXXQRjj76aEyfPn2H4V9VVaiqar2dSCR29fL2SDZb+xBAREREfYMV+XNJxLNJxDLmTv50PmuNxXEWD7jdXuTPa3k0ppvazOSPlkX+kBJAf18dJrjHIqIEUSX7OnzOthR0zZzHn1eRLeRgwIDdZoPkkOCXfBjmDiIg+eEV3fCJXsiM/ERERERERGVuuOEG/OxnP8P111+PSZMmwe12l73f5/N1+Zl7RPh/+umn8f777+Odd97p1P0333wzrr322l28qr0Hd/wTERH1Lt3QkcylEVcTSKhJxNLNaGwb+Q0DDrsdskPaYeSPppvRkIpaO/mb1TiAUuSv6pnIX1CRzbeJ/HYRPsmLYe4QIz8REREREVEXHXXUUQCA4447ruz8NcMwIAhCt87T7fPh/8svv8SPf/xjvPLKK5Ckzv3lccGCBZg/f7719tdff40xY8bsqiUSERERdVop8ifUJOJqoizyq5oKQwfsdlsndvIXEE03WYG/IR1Fc7Y88tf7arCfMto6JLfrkV8t7ubPwYAOu81uRn7Ri2GBIKpkP3yiB17RA8Up99ivERERERERUSVZvXp1jz+zz4f/9957D1u2bMH+++9vXdM0Da+//jruvfdeqKoKu91e9jGiKEIURevteDy+29a7pzEMgzv+iYiIdhHd0JHKpRFXk0ioSUQzzWhMRZEpBnVDN2ffS85i5HdsK/JriGZi1riexlQMTdkWAIBdsCEkB1DvrcF+NaMRdgcRkP3djPwqsnkVumFGftkhwufyYFgghCrZD29xJj8jPxERERERUc855JBDevyZfT78H3744fj444/Lrs2dOxejRo3CFVdc0S76U9cIggBd13t7GURERHu8rSN/LNNS3MmfMSO/YcAu2CE5RShOCcFtxPm8piGWaWod15OOoSnTGvmDchXqvNUYVzPKivz2LkR+TdeKX3goRn4YsAsCZIcEr8uNIYGBCEg++CQvfC4PZKdU9q2mREREREREfdF9992HJUuWYNOmTdhvv/2wbNkyTJkyZZv3P/fcc1i4cCG++OILDB8+HLfeeqs1cgcwN0wvWrQIDz/8MJqbm3HwwQfjgQcewPDhw3t87a+//vp23//d7363y8/s8+Hf6/Vi3333LbvmdrsRCoXaXaeuEwSBO/6JiIi6SDd0pHMZxNUE4u0ivwrD0DsV+QuahmimdVxPKfIbMGATbAjJVaj1RLBv9UhE3KFuRf5sQbVCv260Rn5P28gveqyZ/Iz8RERERES0p3nmmWcwf/58LF++HFOnTsXSpUsxc+ZMrF+/HtXV1e3uf/PNN3Haaafh5ptvxjHHHINf/epXmDVrFt5//32rOd92222455578Pjjj2PIkCFYuHAhZs6ciXXr1nV6JH1nTZs2rd21tn832ytn/NOu5XA4kMvlensZREREfVZ55E+hKdOMhlLkz6vQocOxk5FfEASE5ACq3WGMrR6BsBJEUK6C3db1yF8K/YZhwCYIxbMCyiN/aSY/Iz8REREREfVViUSibIT71uPd27rzzjtx7rnnYu7cuQCA5cuX46WXXsKjjz6KK6+8st39d999N4444ghcdtllAIDrr78er7zyCu69914sX74chmFg6dKluPrqq3H88ccDAJ544gnU1NTghRdewOzZs3v0tTY1NZW9nc/n8cEHH2DhwoW48cYbu/XMPTL8r1mzpreXsNeQZRnpdBqhUKi3l0JERNTrrMifSyKeTaI524KGVAypfNqK/HbBBtkhmZFf8sPWQZwv6Bpi6WY0pKPFg3fbRH4ICCpVqHaHMSYyAhF3EEHZD7ut8+ML20Z+cye/DptgHgjsdikYXDUAga1m8jPyExERERHRnmTMmDFlby9atAiLFy9ud18ul8N7772HBQsWWNdsNhumT5+OtWvXdvjstWvXYv78+WXXZs6ciRdeeAEAsGHDBmzatAnTp0+33u/3+zF16lSsXbu2x8O/3+9vd+173/seXC4X5s+fj/fee6/Lz9wjwz/1HFmWkUqlensZREREu51hGEjlW2fyN2Va0JCOIZUzI7+B1piuOLYd+TVdQzTdjMZ0DA2pKBrTMcTaRn7Zj4g7hDGR4eZOfqUKjh6K/Eox8lfJPvhELyM/ERERERHtNdatW4d+/fpZb29rt39jYyM0TUNNTU3Z9ZqaGnzyyScdfsymTZs6vH/Tpk3W+0vXtnXP7lBTU4P169d362MZ/itcacc/ERHR3qwU+RNqCnE1geZMHFvSUaRyaahbxXTZISIg+Trcga/pGmIZ87sASrv5Y9lmGIYZ+QOyHxEliNGRfRBWQt2K/Gohh0wha0V+ATZITnMn/6Cq/mU7+d1OhZGfiIiIiIj2Sl6vFz6fr7eXsVv8/e9/L3vbMAx88803uOWWWzBhwoRuPZPhv8LJsoxMJmMGC4YDIiLaCxiGgXQ+U7aTf0s6inQujWxBhWaY43p2HPl1xDKlnfxm6I9l2kf+UZFhiHQj8uu63mYmf7Y88jsVDKzqh6BcZUZ+lweKS+7w7AAiIiIiIqJKFg6HYbfbsXnz5rLrmzdvRm1tbYcfU1tbu937Sz9v3rwZdXV1Zfd0N8Rvz4QJEyAIAgzDKLv+rW99C48++mi3nsnwX+FKO/4Z/omIaE9UivwJNYm4mkRTaSZ/LtW6Y16wQXaIkBwiqjoZ+RvTMUQzTWWRP6wEMTI8DBEliJAcgMPexcivqcjmzdBfMDTYrMgvY0BVPQJSFXwSIz8REREREVFXuFwuTJo0CatWrcKsWbMAmH8HW7VqFS6++OIOP+bAAw/EqlWrMG/ePOvaK6+8ggMPPBAAMGTIENTW1mLVqlVW6I/H43jrrbfwox/9qMdfw4YNG8rettlsiEQikCSp289k+K9wiqIgk8n09jKIiIh2qH3kj6MhFe165Dd0c55/KoqGdAzRVAzRTDN0QweA4k7+EEaEhyKiBBGUA3B2J/IXzNDfNvIrThn9/fUIylXwiW74RC8jPxERERER0U6aP38+5syZg8mTJ2PKlClYunQpUqkU5s6dCwA444wz0K9fP9x8880AgB//+Mc45JBDcMcdd+Doo4/G008/jXfffRcPPfQQAEAQBMybNw833HADhg8fjiFDhmDhwoWor6+3vrjQE9auXYtoNIpjjjnGuvbEE09g0aJFSKVSmDVrFpYtW7bN8w22h+G/wrUd9UNERNRXGIaBTD6LuJqwIn9jypzJnylkoRkGbIJgjevZUeRvLO7ib0iZ43q0UuSX/Ai7gxgeGoKIO9T1yG+0juvJ5lVohgahdPCuU0Z/Xz2Csh8+0cPIT0REREREtIuceuqpaGhowDXXXINNmzZhwoQJWLlypXU478aNG2Gztf5d7KCDDsKvfvUrXH311bjqqqswfPhwvPDCC9h3332tey6//HKkUimcd955aG5uxre//W2sXLlyp3bhb+26667DtGnTrPD/8ccf4+yzz8aZZ56J0aNHY8mSJaivr8fixYu7/GzBqIDi+9VXX2HAgAH48ssv0b9//95ezm7X0tKCfD4Pl8vV7n1r1qxBNBrFD3/4Qzgc/DoQERH1jtJM/ng2gZbiTv5kLo1McSa/DQIkp7mTX3KIHc7S162d/Gbkb0yZ43pKkb9K8iPiDiKsBBFxm+N6nPbO/29fx5FfgOSQIDskhN1BhEoz+UUP3C6FkZ+IiIiIiKiLKqnl1tXV4fe//z0mT54MAPj5z3+O1157DX/9618BAM899xwWLVqEdevWdfnZLL0VTlEUfPXVV729DCIiqiBtx/U0F0fulCK/bmjWAbeSQ4RP8m4z8jdn4ta4nsZ0DNF0MzRDAwBUST6ElSCGhQabM/mVrkd+tZBDppAtRn4dggCIdhGKU0I/X11xJ78XXtEDDyM/ERERERERdVFTU5P1XQkA8Nprr+HII4+03j7ggAPw5ZdfduvZDP8VrjTjvwK+8YOIiHpBWeTPxtGQiiGpJpHVVGh6KfK7IDmkHUf+4i7+hnQM0XRTa+QXfQi7gxgWGISwO4iwEoDT7uz0GkuRP1tQzTFCmg7B1ibye2sRVKoY+YmIiIiIiKhH1dTUYMOGDRgwYAByuRzef/99XHvttdb7E4kEnM7O//22LYb/CidJErLZbG8vg4iI9gKlmfwJNYWmrDlyJ5lLIVvIQtN1CBCKkX97O/mN4hcIota4nsY2kd8vehFxBzE0MNCK/K6diPwF3Tx4V3S4oDgl1HtrEJCr4JPMmfwep1I2B5KIiIiIiIiopxx11FG48sorceutt+KFF16Aoij4zne+Y73/73//O4YNG9atZzP8Vzi32410Os0d/0RE1CWZfNbayd+SjWNLKorE1pHf4YLkFOETQ3DY2v+RQzcMc55/OmbN5Y+mYii0ifxhdxCDAwPM2fxyEC5H9yJ/tqAirxdggwDRYe7kr/PWIFiK/C4PPC43Iz8RERERERHtNtdffz1OOOEEHHLIIfB4PHj88cfLzml99NFHMWPGjG49m+G/wsmyzFE/RES0Xdl81jx4t03kT+ZS5lgcXYcAWIfu+tw7jvyNpcN3000o6AUAgE/0IOwOYXBV/25H/lwhh0wx8hd0DQIA0SFCdkqo81YjKAfgKx68y8hPREREREREvS0cDuP1119HS0sLPB4P7Pby74x/7rnn4PF4uvVshv8KJ8syR/0QEZElm88inkshnk2gJZtAQyqKRC6JTEFFobhjvhT5vUoIjg4OzDUjfwKN6VjryJ42kd8rehBRgphU3w9hJYSwEoDocLV7zrYYhgG1oHYc+R0iaqoiCCuB4kx+N7wuDyM/ERERERER9Vl+v7/D68FgsNvPZPivcC6XC6qqcsc/EVEFyhZUxNUkEqWDd5PlkV8oRn7ZIcKruLcZ+eNW5C8dvBtDvhT5XR5E3EHsX9fP3MmvBLsV+bPF0J/XChCE1i8+DCpGfm+bnfz2Ds4OICIiIiIiIqokDP8VThAECILQ28sgIqJdrG3kb8nG0ZCKIa4mkCmo0PQCUJrJ75BQvb3IrybQWAz8pZE9rZHfjbA7hIl1+yKsBBF2ByF1M/Jni5EfggDR7oLslDCoKoyQEoRP9MAreuBl5CciIiIiIiLqEMM/wTAM7vgnItqLqIUc4mrCmslvRv4ksv+fvfuOr7I+/z/+OnsnJyc5WewhCi5QBBUHFlRErVrUal2gYh1oXa2jDtwynLRabRVHtXVinXxFK1rr5idWi2LFgTKTnISMs8+5f3+c5MAhAZKQEEjez8fjPODc5z73fZ1DTkje5zrXJxltHLezPuQPuj3YWgj5DQNqY3VUhKvWB/3hUCaMB7x2D0F3YIOQvwCn1dHqGg3DIJaKE01EWwz5++YXUegJ4LN7yHP6FPKLiIiIiIiItIGCf8FkMin4FxHZQcWScepi9dTG6jLjesIhaqP1xJIxEulk4+x7O06rgyJ3YNMhf7yeyoaqnE7+eCoBgNfupsgdYHjprtlOfld7Qv5kjGgiSiKdAsBhseO0Oeib34uAe/3Cuz6HVyG/iIiIiIiIyFZQ8C/q+BcR2UFsGPKvi2UW3l23Uchvt9pxWR143X5sFluzYxgG1MXr18/jbwz7m0J+j91N0B1gj9KhBN2FWxnyx4inE5gwZUP+3vnlFDWO68lzePE6vFgV8ouIiIiIiIh0KAX/oo5/EZHtUDwZpzZWnxnXE6ulsqGaddHazFicxpn6TZ38hVsI+TecyZ8J+eNAJuQvcgfYo2RoduFdl83Z6hq3HPKXUeQuIM/hU8gvIiIiIiIisg0p+BcA0ul0V5cgItJjxZNxauP11EYz3fwVDaFsyJ8J0804LFacNicBtx/7JkP+BiobqqgMh6hoHNcTawr5bW6KPAH2KNmFIk+AYDtC/ngqQSTZNJM/AZiwW2y4bE565ZcSdAfwObzkOXz4FPKLiIiIiIiIdBkF/4LD4SAajZKXl9fVpYiIdHvxVILaWB11sQbWRWupbAhRE6vdqGPetsWQvyHeQEU24K+iomF9yO+2uQi6A+xWsnN2XI+7HSF/NBkl0rTwLmBvrKtX3vqQ3+fwkmf3Ym1h7QARERERERER6Rr6LV1wOp1EIpGuLkNEpNuJpxKNM/nrc0P+DTrmWxXyJxqyHfxNs/ljyRiQCfmL3AF2K945O67HbXe1usYNQ/5oMkZ8o5C/3FdK0BPILrqrkF9ERERERERk+6ff3AWXy0VDQ0NXlyEiskNrCvnrYvWsi9ZREa6iJrqJkN+1uZA/TEXjuJ6moD/aGPK7rE6CnkJ2DQ7JhvyedoX8MaLJKLFkApMpM67HaXVQ5itdP5PfqZBfREREREREZEel3+YFt9tNOBzu6jJERHYYiVSC2g1C/spwiJpoLZFkNHf2vdVBwOXHZrZiMplyjtEU8lduMK6nsiFEJCfkDzAsuFPjTP7CNof8iVSCSDLW2Mkfz9aVCflLKHIHsgvv+hyeFhcIFhEREREREZEdj4J/weVyEYlEMAyjWTAlItLTJVIJ6mIN1MbqqI3VU9GwvpN/4zA94MzHZrG1+L20IR6hojHcrwiHGkP+KAAuq4MiT4BdgjsRbAz53TYXrf2W3BTyR5MxIskY8VQCMLBb7DitDkq9QYo8heRnF95VyC8iIiIiIiLSnSn4FwX/IiKN1of89dTGMp381ZF1jSF/bphe4MzbQsifCfebFt5tCvmdVgdF7gC7BAdR5A4Q9ATw2DytDvkhM1YomojmhPw2iw2X1ZkJ+d0B8p2+7OK7LY0VEhEREREREZHuS8G/4HK5NOpHRHqcZCpJbbye2mhTyF9NdaRmg5Af7BYrTqsTvzMP+yZC/nA8krPobmVDiHAys2C6w+og6A6wc9Ggxk7+AB57O0L+ZIxoIkpso5C/xFtE0F2okF9EREREREREcij4F9xud7bjX0SkO2oK+eti9Y3jekJUR9cRTUQ3Cvkdmw/5E9HGUT3rR/aEE40hv8VO0BNgSNEAgp5CitwBvB0U8jutDoq9RY2d/HmNM/kV8ouIiIiIiIhIyxT8C263m9WrVyv4F5FuIZlKUhfPzOSvi9VTEQ4RiuSG/DaLFdcWQv5IIkpFduHdTCd/QyLz6Si7xU7QHWBI4QCK3AGKPAF8du9WhfwGBnazDafNQbGniCJP48K7zsxcfoX8IiIiIiIiItJaCv4Fp9NJNBrt6jJERNosmU5RF2vq5M+M6wlFaohkQ/71HfNbCvkrw6GcoL8h3hTy2wi6Cxlc2J9gO0P+RCpBpKWQ3+og2Bjy5zeF/HYvdqu9g54hEREREREREemJFPwLbrebcDisjn8R2a4l0ynqG0f11MbqqQyHCEVqiCZixFIxAGyNHfP5Th8Oi73lkD8ZyxnXUxkOUb9ByF/kDjAokAn5gx0Q8mfqyowRKvIECHoKyXdkxvXkORTyi4iIiIiIiEjHU/Av2Rn/IiLbi1RjJ/+mQn4DsmNx8pxeHJZAiyF/NBnLGdVTEa5qFvIPDPQj6C7MjNZpR8gfTcaIJGPEknEgE/I7ckJ+H3mOzOK7DoX8IiIiIiIiIrINKPgXLe4rIl0qlU5lZvJH66iLN1DVEKKqcVxPLNUUpltw2pxbCPnj2Q7+imzI35C5v8WaCfkL+mYCeXchPocXcxtS/qaQv+kCJqxmC06rk0J3AcENFt7Nc/gU8ouIiIiIiIhIl1HwL9kZ/wr+RaSztTrktzZ18rc8rieajFOVDfhDVDZUUdcU8putFHkCDCjo0ziupz0hf5JoMrpByA/WxnE9AVcBQY9CfhERERERERHZfin4F436EZFOkUqnqI83ZMf1VIVDVIVr1ofphoHVYsW1hZA/loxnu/ib/qyL1wOZML7IHaC/vw9BT2bh3TyHr00hfzKVzMzkT0aJJuOAgcWcqSvgKqDIE8DvzMPXOJPfaXV01FMkIiIiIiIiItIpFPwLNpuNRCKhjn8RabcNQ/66WD2V4WqqwtUbdcxbcFkd+OxuitwFLYb88WQi08EfrsoG/bWxDUP+Avr7ezeO6wmQ52xvyL++LktjXQVOP0FPIX5XY8hv9+C0OTvg2RERERERERER2bYU/AtAiwGciEhL0uk0dfF66mIN1MbqCEVqqGwINS5wm1l419o4rsdnd1Po9mM2mZsdJ55KbDCPP0RVQ4h1sTpgfcjfN79XNuTPd+a1OeRfv/BujDQG1sZO/gJn/vpxPU6fQn4RERERERER6VYU/AsAhmGo419Emkmn0znjekKRairD1ZmZ/BuF/N5WhPyV2Zn8G4T8JguFngB98ssZ0d6QP50kmljfyW8AFrMZl9WJ35lHsadwg5n8XoX8IiIiIiIiItKtKfiXLAX/Ij1bSyF/VbiacGPIn8bA1rjA7ZZD/moqG6qyHf1NIb/FZKHIXUDv/DJGuHfLzs9vc8ifjDUG/XEMDCxmM06rk3xnHoM9hY0z+T3kOXy4FPKLiIiIiIiISA+j4F+AzKgfBf8iPUfaSFMfD1Mbq6M2Wk91pIbKcIhwIprpmDcMrBYLLqtzsyF/Ihvyr+/kr4nVApmQv9BdQO+8MoZ7diXoDuB35bV4nE1JplOZRXdbCPnznD4GeQopcOYr5BcRERERERGRLQqFQlx44YW89NJLmM1mJk2axD333IPX693k/tdffz2vv/46y5cvJxgMcuyxx3LTTTeRn5+f3a+lMep/+9vfOOmkkzrtsWyJgn/JUvAv0j01hfx1sfrMTP5wbsiPARaLeYud/IlUkqpwdTbgrwhXURPdMOT3U55Xwp6eYVsR8scag/44BmksZgtOiyMT8rsD+F355Dm8+Bxe3DZXhz1HIiIiIiIiItL9nXLKKaxatYoFCxaQSCSYMmUK55xzDk8++WSL+69cuZKVK1cye/Zshg0bxg8//MC5557LypUrefbZZ3P2nTt3LhMmTMhe9/v9nflQtkjBvwCZd6VSqVRXlyEiW2nDkL8uVk9VpIbKhqrMuJ5UDCOdmX3vtG0p5E9RFcmM6Wka11MTXQeAxWQm4Cqg3FfCHiVDCXoygbxlK0N+s8mCy+ogz+5lUEEhflc+vsaZ/Ar5RURERERERHqWuro6amtrs9cdDgcOh6Pdx/vyyy+ZP38+H3/8MSNHjgRgzpw5TJw4kdmzZ1NeXt7sPrvtthvPPfdc9vqgQYO45ZZbOPXUU0kmk1it6+N1v99PaWlpu+vraNt98H/bbbfx/PPP89VXX+Fyudh///2ZMWMGO++8c1eX1q04HA4ikUjOR1REZPuWNtI0xMPUbhDyZ2byR4gmoxhGJqR32hx47C4KrZsO+UORaioaqrLd/NWNIb/ZZKbQ5afcV8weJbtQ5AlQ0MaQP5VOEWlcdDeayKwVYDGZc0L+fGceeU4feQ4vLquzxY/IiYiIiIiIiEjPMWzYsJzr119/PdOnT2/38d5//338fn829AcYP348ZrOZDz/8kOOOO65Vx1m3bh15eXk5oT/ABRdcwNlnn83AgQM599xzmTJlSpfmG9t98P/2229zwQUXsM8++5BMJrn66qs57LDDWLJkCR6Pp6vL6zbcbjfhcLiryxCRTWgK+euyC++uaxzXE2mcyZ/GYrLgtDlw25wEXPkthvzJVIqqSO64nupIbshf6guyW8nOBBvn51vMbQv5o8lYNuhPGwYWkwmX1YnP7mFAQV8KnHnkObzZmfwK+UVERERERERkY0uWLKFXr17Z61vT7Q+wevVqiouLc7ZZrVYCgQCrV69u1TEqKyu56aabOOecc3K233jjjfzsZz/D7Xbz+uuvc/7551NfX89FF120VTVvje0++J8/f37O9UceeYTi4mIWLVrEQQcd1EVVdT8ul0vBv8h2Im2kCccjmYV3Y/VUR9ZR0RTyJ2KkSWNtR8hfGQ5RHVmHgYHJZKLQVUCJJ8huxTtT5A4QcPnbFfI3Bf2GYWBuDPm9CvlFREREREREZCv4fD7y8vK2uN+VV17JjBkzNrvPl19+udX11NbWcuSRRzJs2LBmnzy49tprs38fMWIEDQ0NzJo1S8F/W6xbl+lMDQQCm9wnFosRi8Wy1+vq6jq9rh2dgn+RrpEN+eP11EbrqY7UUBmupiERzob8mbE4zkzI78zH3EI4n0ynGhftraKiIUTFRiF/wOWn2FPErsVDGkP+fCxmS6vr3DDkz3TypzGbMgsCe+we+vv7ULDRwrsK+UVERERERESks1122WVMnjx5s/sMHDiQ0tJS1q5dm7M9mUwSCoW2OJu/rq6OCRMm4PP5mDdvHjabbbP7jx49mptuuolYLLbVn1Rorx0q+E+n01x88cWMGTOG3XbbbZP73Xbbbdxwww3bsLIdn8vlIhKJYBiGwjqRTmIYBg2J9TP5qyPrqGgIZUP+zAK3mTDdbd10yJ9Kp6gK1zQuultFZThEqCnkJxPyBz2FDAvuRJE7QKHb32Ehv9vuzob8Gy68q+8bIiIiIiIiItIVgsEgwWBwi/vtt99+1NTUsGjRIvbee28A/vnPf5JOpxk9evQm71dbW8vhhx+Ow+HgxRdfxOl0bvFcixcvpqCgoMtCf9jBgv8LLriAL774gnfffXez+1111VVceuml2esrVqxothiE5Grq+FfwL9IxmkL+ulgDtbE6aiK1rA1X0RBvOeQvcOa1GM6n0ilCjW8QVISrqGwIEYrUbBDy51PkDjA0OJgidyEBtx9rG0P+WDJOJBnNhvwmmhYEzoT8flceeQ4fPocHj82t7xEiIiIiIiIissMZOnQoEyZMYOrUqfzpT38ikUgwbdo0TjrpJMrLy4FMjjxu3Dgee+wxRo0aRW1tLYcddhjhcJi//vWv1NbWUltbC2TecLBYLLz00kusWbOGfffdF6fTyYIFC7j11lu5/PLLu/Lh7jjB/7Rp03j55Zd555136N2792b3dTgcOe+mNP1jyKZt2PEvIm1jGAbhRITaWH1OyB+Oh4kmY6SMzLgep9WBy+rYTMifJhRp6uTPBP2hSE3mDTlMFLjyCboDDA0OalfIn06nG+fxtxDy29z08/fO6eRXyC8iIiIiIiIi3ckTTzzBtGnTGDduHGazmUmTJnHvvfdmb08kEixdujQ7Ev3//b//x4cffgjA4MGDc4713Xff0b9/f2w2G3/84x+55JJLMAyDwYMHc+eddzJ16tRt98BasN0H/4ZhcOGFFzJv3jwWLlzIgAEDurqkbqkp+BeRzWsK+eti9ZmFd6PrqGho7OTfaCyO0+rAv5mQv+m+TYvvhiI1jWF8JuQvcgfYpWhQZlyPqwCrpY0hfypGNJEJ+lNGGnM25HfR19+LAqefPKeXPLsXt93V4gLBIiIiIiIiIiLdRSAQ4Mknn9zk7f37989pjB47duwWG6UnTJjAhAkTOqzGjrLdB/8XXHABTz75JP/4xz/w+XysXr0agPz8fFwuVxdX13243W5qamrU8S+ygeYhf21jyN+wvmPeZMa1pZDfSDfO88/M469sCFHVGPIDjZ38hQwpGkhwa0L+ZCboTxqpbMjvtrnonV9OwOUnz+Ehz+FTyC8iIiIiIiIi0s1t98H//fffD2TeXdnQ3Llzt7has7Se2+1Wx7/0aIZhEElEqY3VZUP+ysZO/kgySrpx/YumcT1bCvkrG0LZxXdDkRpSTSG/M58iT4CdCgdQ5AlQ6Apga0vIb6TXL7ybiJEyUtlxPW6bi9555QRc+eQ5vAr5RURERERERER6qO0++FcH+rbhdruzi/uK9ATZmfzROtY1dvLXx8NEGmfymzcI+fOdvlaG/CFCkepsyO93ZmbyDy4ckOnkdxdgs7T+226LIb/JhNPqxGV10iuvjEKXf/1MfrtbIb+IiIiIiIiIiGz/wb9sG06nU4v7SrfVFPLXxeqpaRy50xTypzfomHdaHeQ5fS0umJs20tREanNm8ldFakgZKQD8jjyKPAEGF/ZvDPn92Cy2VtfYPORPYzLRGPI76JVX1tjJ78Pn8OJVyC8iIiIiIiIiIpug4F+ATMd/NBrt6jJEttqGM/lrmjr5Yw1EUzFS6aaQ347T6txyyN8Y8FeEQ1SFq5uF/IMC/TLjetwF2NsY8seScSLJKNFkjFQqjckMDosDt81JL18pAbdfIb+IiIiIiIiIiLSLgn8B1s/4V8e/7EiaZvLXxRqojq6joiFEfbyBaDJKKp3GhAmn1Y7TtrlOfoOaaG1jwF+V6eQPV5NsDPnzHT6CngADC/pS5AlQ1M6QP5qMEUlGSaZS2bUCmkL+ApefPGdmJr/X5sZsVsgvIiIiIiIiIiLtp+BfgPWjfkS2V5FEtFknf92mQn5HIVZz829vacPIzPNvnMdfGQ5R1RDKCfmLPAH6F/Qh6AlQ5A60O+SPJmMk0knMmHA0hvxlvhICTSG/3YvX7lHILyIiIiIiIiIiHU7BvwBgtVpJpVLq+JftQjQRzSy8G6tnXbSWtQ1V1McbMh3z6RRmMh3zTquDPHch1hYWzN0w5G9afLcyXE0ynQQyIX+hJ0B/f+9MyO8KYLd2TMjvsjkp8xUTcBWQ17jwrkJ+ERERERERERHZVhT8Sw4F/7KtRRNRauMN1EbrNhnyO6wOXFYHvs2G/HWZcL9pZM8GIX+ew0uRO8De5b0pcmfG9Tis9lbXmDbSxJNxIo0hfzKdwgTZukoLiil0Nc3k9+CzexXyi4iIiIiIiIhIl1HwL1kmk6mrS5Burinkr2sa11NfRV28nkgyRjKdbBzXs+WQv7Yx5K/ILrwbItEY8vscXoLuAHuV9cqO62lLyG8YBrHGgD/SGPID2U8Y9PMHKXIX4Nugk9/SwtoBIiIiIiIiIiIiXUXBv2QZhqGOf+kw0WSM2lh9NuSvbAhRG6sjkoyRSiehaSa/1Umx27PJkL8uVk9FQ1XOyJ5syG/3UOQpZETZbgQ9AQrdAZxbE/KnkmAy5YT8he7ccT0K+UVEREREREREZHun4F+yTCaTgn9pl2gyll14d120loqGELWxeqLJaOO4nfUhf9DtwdZCyG8YUBury4zpaezkrwyHSKQyIb/X7iHoDjCibLfMuB5PAU6ro9U1GoZBLBUnmohmZvI3hvwOix2XzUm//CIKPQF8dg95Th8+hfwiIiIiIiIiIrKDUvAvORT8y5bEknFqY3XrQ/5wiNpoPbHGBW4zs+/tOK0OityBTYf88XoqN+rkj6cSAHjtborcAYaX7kqRO0DQE2hfyJ+MEU1ESTSO62kK+fsq5BcRERERERERkW5Mwb9kmc1mkslkV5ch25FYMt7YyV+XGdcTDrFuo5DfbrXjsjrwuv3YLLZmxzAMqIvXr5/H3xj2bxzy71E6lKC7kCJPAFe7Q/4Y8XQCE5lOfqfNQe/8corcgey4Hp/Dq5BfRERERERERES6NQX/kuVyuQiHw/j9/q4uRbpAPBmntmlcT6yWioaqnJAf1nfyF24h5M+O6mn8M56KA+BpCvlLhlLkCRB0B3DZnK2uceOQP5FOQE7IX5YT8nsdXqwK+UVEREREREREpIdR8C9ZTqeTcDjc1WXINhBPxqmN11MbrWddrI7KhhDrorVEkxt2zNtw2pxbCPkbqGyoojIcoqJxXE+sKeS3uSnyBNi9ZBeC7Qz546kEkWTTTP5MyG+32HDZnI0hfwF5Dp9CfhERERERERERkQ0o+Jcst9ut4L8biqcSmZn80czInoqGEOtitRuMxTHjsFhx2pwE3H7smwj56+MNjQH/+qC/KeR321wE3QF2K9k5O67HvVUhf+YTBvbGNx965ZUSdAfwObzkOTIz+a0trB0gIiIiIiIiIiIiCv5lA02jfmTHFU8lGmfyZxberWwIUdMY8q8fi2PbYsjfEG+gYoMu/oqGqvUhv9VFkSfAbsU7E/QEKHIHcNtdra6xKeSPJqNEWgr5faUUeQLZefx5dq9CfhERERERERERkTZQmiZZLpeLSCRCOp3GbDZ3dTmyBU0hf12snnXROirCVdQ0jutpGovTqpA/0bBBwJ+ZyR9LxgBwWZ0EPYXsWrxzdia/p10hf4xoMkosmVnQt2mtgHJfKUFPAJ/dS55TIb+IiIiIiIiIiEhHUMImWU3Bv2x/EqkEtU0hf6yeyoZMyB9JRnNn31sdBFybC/nDzcb1RDcI+Ys8AXYN7tQY8hduVcgf36Aup9VBma+kceFdn0J+ERERERERERGRTqTUTbKaZvwbhtHVpfRoiVSCulgDtbG6nJA/mowRbxy3Y7fYMyG/Mx+bxYbJZMo5hmFAOBGhIlxFZWMXf2VDiEgyCoDL6qDIE2BocKfGhXcLcdtcbHSYTTIMg0QqQSQZa1aX0+qg1FtM0FNIXtNMfoenxQWCRUREREREREREpOMp+O8B1tRX4jDZsNvtm93P5XJRX1+/jaoS2DDkzyy8WxkOUR1Z1ximJwAjG6YXOPNaDPkBGuKRbLhfGa6iYoOQ32F1EHQH2CU4iCJ3gKAngMfmaXXID5mxQtFEZib/xnWVeoMUeQrJb5rJ7/Aq5BcREREREREREelCCv57gP+FvsNIphjjHoXFbNnkfm63m4qKCnX8d5JkKkltvJ7aaFPIX011dB3RRGYsjgmwWaw4rU78zjzsmwj5wxuE/E1/hpOZEU3NQn53AI+9HSF/MkY0ESXWGPLbLDZcVicl3iKC7kLynT58jUF/S2OFREREREREREREpOso+O8B0mmDn2pX803oe3YuGrTJ/ZxOJ5FIRMF/B2gK+eti9dTG6qloCOWE/AB2ixWn1bH5kD8RbQz414/sCScaQ36LnaCnkCFFAxvH9XRcyO+0OihuDPnznD7yFPKLiIiIiIiIiIjsMBT89xCpdIqvKpdR5AlQ6CpocR+3263Ffdth45C/MhwiFMkN+W0WK64thPyRRJSKxgV3mxbgzQ35AwwpHNA4rqcQ71aG/AYGdrMNp81BsaeIIk+AfGcePoeHPIdPIb+IiIiIiIiIiMgOSsF/D+Gzu4kl43yx+iv26zuyxVBXi/tuWTKVpC6eWXi3LlZPReNM/kg25F/fMb+lkL+yMeSvCGeC/oZ4GMgskBt0rw/5izyF+LYq5I9jQCbktzoIeooIegLkOXzkOb3k2b3YrZtf/0FERERERERERER2HAr+e5BiTyGr6iv4unIZu5Xs0ux2t9tNNBrtgsq2T8l0irpYUyd/ZiZ/KFLTYsif7/ThsNhbDvmTsZxxPZXhEPXZkN9G0B1gcKB/duFdn93bppA/kUoQaamT3+og6CnMdPI78shrXHhXIb+IiIiIiIiIiEj3puC/B7GYLRQ48/hf1fcUeQop9QZzbu/JM/6T6RT1jaN61o/rqSGaiBFLxdZ3zNs2H/JHk7GcUT0bh/xF7gADA/0IujOBfF57Q/5kjFgyDoDNbMVhdVDkyYwAynf4yHNkFt91KOQXERERERERERHpcRT89zBuu5v6eJjP13xFvtOHy+rM3uZ0OolGo90++E81dvI3hfxV4RBV2ZC/KUy34LQ5yXN6cVgCmwj549kO/oqGKirCIerjDZn7W6yZkL+gb6br3h3A5/BibkPKn2gc1xNJxognM+N6siG/u4AidwC/M08hv4iIiIiIiIiIiORQ8N8DBd0BVtav4cu13zCifFdMZMJoi8VCOp3u4uo6Viqdyszkj9ZRF2+gqiET8kcaZ9/DxiH/pjr5Nwz5Q1SGq6hrCvnNVoo8AQYU9CHYuPBu20P+JNFkNDOXPxnLhvxOq5NCVwHBxoV38xxefA4vTqujQ54fERERERERERER6X4U/PdAJrOZgLuAb0M/EPQE6JNfvv42k2mH7fhvCvnrNuzkD9dkw3QMA5vFitPq2GLIX7XhwrsNIeri9QBYzZlO/v7+PgQ9gcy4HoevHSF/rDHojwMGFrMVl9VBwFVAkSfTye9rnMmvkF9ERERERERERETaQsF/D+WyOglbIixZ+zUFLj9eu7urS2qTVDpFfbxhg3E91VSFq9eH/IDVbMFldeCzuylyF7QY8seTiUy4H67KBv11sQ1D/gL6+3tT5AlQ5A6Q72xbyJ9MJRtn8jeF/Jm1FlxWBwVOP0FPIX5XY8hv9+C0ObdwRBEREREREREREZHNU/DfgwVcflbWreG/a5eyT689MZvMGIax3XX8p9Np6uL11MUaqI3VUblByB9rHItjNVtwNob8hW4/ZpO52XHiqUR2VE+mk7+K2o1C/n75vTKL5Lozo3XaGvI3zeTPjOsxsDZ28mdC/sZxPU6fQn4REREREREREZFtLBQKceGFF/LSSy9hNpuZNGkS99xzD16vd5P3GTt2LG+//XbOtl//+tf86U9/yl5fvnw55513Hm+99RZer5czzjiD2267Dau16+J3Bf89mMlkIugO8EPNTwTdhQwM9O3yUT/pdDqnkz8UqaYyXJ2Zyb9RyO9tZchf2TiuZ12sDgCryUKhJ0DfDgj5my5pjMZPGDjxO/Mo9hRmZ/LnObwK+UVERERERERERLrYKaecwqpVq1iwYAGJRIIpU6Zwzjnn8OSTT272flOnTuXGG2/MXne7109PSaVSHHnkkZSWlvLee++xatUqTj/9dGw2G7feemunPZYtUfDfw9mtdlxWJ0sqvibg8mMymbbZAr/NQ/4aqsIhwo0hfxqjcYHb1oT81VQ2VGXD/pyQ311A7/xyRrgD2fn5bQr500miiVi2mx/AYjbjtDrJd+ax0wYhv8/hxaWQX0REREREREREZLvy5ZdfMn/+fD7++GNGjhwJwJw5c5g4cSKzZ8+mvLx8k/d1u92Ulpa2eNvrr7/OkiVLeOONNygpKWH48OHcdNNNXHHFFUyfPh273d4pj2dLFPwL+c48VtWv5fO1SzGZTCQSiQ4/Rzbkj9dTG9045I+TJt3GkD/UGPJXZUN+SzbkL2O4e1eC7gB+V16Lx9mUZLqxkz8RI5qMY2BkQ/48Zx6DPAEKnPn4HB7yHD6F/CIiIiIiIiIiIp2grq6O2tra7HWHw4HD4Wj38d5//338fn829AcYP348ZrOZDz/8kOOOO26T933iiSf461//SmlpKUcffTTXXntttuv//fffZ/fdd6ekpCS7/+GHH855553Hf//7X0aMGNHumreGgn/BZDJR7A6wonYVKUuacDhMIBBo9/E2F/Kvn32fGYuzuZA/kUpQFa6hoqGqcSZ/iJpY5sWeCfn99MorZbinvSF/qnFUT5RoIo5BGovZgtPiIM/pY5CnEP8Gnfxum6vdz4mIiIiIiIiIiIi03rBhw3KuX3/99UyfPr3dx1u9ejXFxcU526xWK4FAgNWrV2/yfr/61a/o168f5eXl/Oc//+GKK65g6dKlPP/889njbhj6A9nrmztuZ1PwLwBYLTbyHF6ipjg/Vq2kd+/erbpfKp2iPt7QuPBuCyG/YWC1tCbkT1IVrs4G/BXhKmqiTSG/mUJXAeV5JezhHkrQE6DAld9xIb/dy6CCQvyufIX8IiIiIiIiIiIi24ElS5bQq1ev7PVNdftfeeWVzJgxY7PH+vLLL9tdxznnnJP9++67705ZWRnjxo1j2bJlDBo0qN3H7WwK/iXL5/BisVn5/KcvGbHrnjituS+meCpBfWPAXx+vpzJcTXVkHdFkLLPwrgEWi3mL43oSqRRVkaaAP/NndXQdkAn5Ay4/5b4S9igZSlFjyG9pQ8ifSqeINC28m8isFWAxmXFZ14f8+c488pw+8hxeXFYnpjbM/BcREREREREREZHO5fP5yMvL2+J+l112GZMnT97sPgMHDqS0tJS1a9fmbE8mk4RCoU3O72/J6NGjAfjmm28YNGgQpaWlfPTRRzn7rFmzBqBNx+1oCv4lR743j9WhNXy++iv6FfSmPlbPulgdVQ3V1MRqiSXjxFMJwMBmtuG02vFtJuRPplJURXI7+asjmZDfbDJT6PJT6guyW8nOBD2F7Qr5mxbdjSZjpA0Di8mEy+rEZ/cwoKAvBY3jeppm8ivkFxERERERERER6R6CwSDBYHCL++23337U1NSwaNEi9t57bwD++c9/kk6ns2F+ayxevBiAsrKy7HFvueUW1q5dmx0ltGDBAvLy8pqNK9qWFPxLDqfbhcOw8fmar/iy8htS6RQADosNp9WB35mH3WJrMTxPplOEwjVUhKuy3fzVkXUYGJhMJgpdBZR4guxWvDNF7gABlx+Lue0hf1PQbxgG5saQ37tRyN80rkchv4iIiIiIiIiIiAwdOpQJEyYwdepU/vSnP5FIJJg2bRonnXQS5eXlAKxYsYJx48bx2GOPMWrUKJYtW8aTTz7JxIkTKSws5D//+Q+XXHIJBx10EHvssQcAhx12GMOGDeO0005j5syZrF69mmuuuYYLLrhgqxYj3loK/iWH3WHHnISgO4DVYsVmaflLJGWkqY6syyy82xCioqGKUKQmE/JjIuDyU+wpYlhwCEFPgIArH4vZ0uo6Ngz5M538acymzBghj91Df38fCjaaya+QX0RERERERERERDbliSeeYNq0aYwbNw6z2cykSZO49957s7cnEgmWLl1KOBwGwG6388Ybb3D33XfT0NBAnz59mDRpEtdcc032PhaLhZdffpnzzjuP/fbbD4/HwxlnnMGNN964zR/fhhT8Sw6Hy0E8FsNptWNq7MZPGwbronVUhKuyQX9VuJqUkfk0QMDlJ+gOMDQ4iCJ3IQG3H2sHhfxuuzsb8vscXvIU8ouIiIiIiIiIiEg7BAIBnnzyyU3e3r9/fwzDyF7v06cPb7/99haP269fP1599dUOqbGjKPiXHDaHndqadSwL/UhltJqKhkoqwyESqSQA+Q4fQU+AQQV9CXoKKXQXbPJTAS1Jp9MbjOuJkjbSmDDjtDnwNIb8flceeQ6fQn4RERERERERERGRdthhgv8//vGPzJo1i9WrV7PnnnsyZ84cRo0a1dVldQvpdIq1DVWsrF/Lfyu/JLSyim+/rcTtcBP0BBheuitBdyFFngBOq731xzXWh/zRRIykkcLcFPLb3PTxlxNw+bOd/B6bWyG/iIiIiIiIiIiIyFbaIYL/p556iksvvZQ//elPjB49mrvvvpvDDz+cpUuXZldKltYzDKiL1bGybi2r6tewpq6SlJHCaXVQ4MvH6bJwzO7H4HN5Wn3MtJEmlowTSUaJJmKkjDQmEzitTtw2F73zMiF/nsNDnsOH2+7CbGr9wr4iIiIiIiIiIiIi0jo7RPB/5513MnXqVKZMmQLAn/70J1555RUefvhhrrzyyi6ubscQTyVZXrOCVY1hf0M8gtlkJugpZPfSXSjzFVPg9LNq+QoW/7gIt8252eMlUgkiyRiRRIRYKoEJU2Ymv81JL18pAbc/O67HY3cr5BcRERERERERERHZRrb74D8ej7No0SKuuuqq7Daz2cz48eN5//33W7xPLBYjFotlr9fV1XV6ndur/6z+kgXfvENVQzWG2cDn8NIrr4xyXzElniDWjebzO5yOnOcO1o/siSSiRJIxDMPAYrbgtjop9RZT4i0iz+HD78zDa/dgNivkFxEREREREREREekq233wX1lZSSqVoqSkJGd7SUkJX331VYv3ue2227jhhhu2RXnbPYvZgsNmZ2hwMDsVD8Rrd292f4fTQTwapz4eJhqN5nTzexsX3w24/eQ788h3+HC0Yea/iIiIiIiIiIiIiHS+7T74b4+rrrqKSy+9NHt9xYoVDBs2rAsr6jq7Fg/hoH77Eqqv2mLoD2B3OohEItRG6uhT2IvSDbv5HR6N7BERERERERERERHZzm33wX9RUREWi4U1a9bkbF+zZg2lpaUt3sfhcOBwOLLXa2trO7XG7sRmtxGJRhjg783BA/fHZDJ1dUkiIiIiIiIiIiIi0gbbffu23W5n77335s0338xuS6fTvPnmm+y3335dWFn3FE3FMAGDCvsr9BcRERERERERERHZAW33Hf8Al156KWeccQYjR45k1KhR3H333TQ0NDBlypSuLq3bqY6sw2l1UOQOdHUpIiIiIiIiIiIiItIOO0Tw/8tf/pKKigquu+46Vq9ezfDhw5k/f36zBX9l60SSUexmGy6bq6tLEREREREREREREZF22iGCf4Bp06Yxbdq0ri6jW6uOrGNgQV/sFhvpdLqryxERERERERERERGRdtjuZ/zLthFJZLr9Bwb6AmAYRhdXJCIiIiIiIiIiIiLtoeBfAKiOrqN3fhmFrgIAdfyLiIiIiIiIiIiI7KAU/Euzbn+bzUY8Hu/iqkRERERERERERESkPRT8S7Nuf5fLRSQS6eKqRERERERERERERKQ9FPz3cJFEFIfZnu32h0zwX19f34VViYiIiIiIiIiIiEh7Kfjv4aqj6+iVX5rt9odM8B8Oh7uwKhERERERERERERFpLwX/PVgkEWnW7Q/gdruJRCIYhtFFlYmIiIiIiIiIiIhIeyn478Gqo+vo5S/L6fYHcDqdCv5FREREREREREREdlAK/nuoTLe/g0EFfZrd1tTxLyIiIiIiIiIiIiI7HgX/PVRTt39go25/WD/jXx3/IiIiIiIiIiIiIjseBf890Oa6/UEz/kVERERERERERER2ZAr+e6DNdfvD+o5/EREREREREREREdnxKPjvYbbU7Q8wePBg/t//+3/cddddVFdXb8PqRERERERERERERGRrKfjvYUKRdfTeTLc/QCAQYMaMGQwbNoxLLrmEP/7xj9TX12/DKkVERERERERERESkvRT89yCRRASnxcHAgr5b3Ndut3PAAQcwe/ZsSktLOf/885k7dy7RaHQbVCoiIiIiIiIiIiIi7aXgvwepjtY2dvv7W7W/yWTCbrczfvx4Zs2ahd1uZ+rUqfz9738nHo93brEiIiIiIiIiIiIi0i4K/nuIcDKGw2xvVbf/xkwmEy6Xi6OOOopZs2bR0NDAWWedxYsvvkgqleqEakVERERERERERESkvRT89xDxZLxN3f4tMZlMuN1ujj/+eG677TZ+/PFHzjrrLF5//XXS6XTHFSsiIiIiIiIiIiIi7Wbt6gJk2/A789rV7d8Sk8lEXl4ep5xyCkcddRTPPPMMf//739lrr71wu904nU5cLhculwun04nb7c5eb7q96WI2670nERERERERERERkY6k4L8HsJhNlHqKcOEgEol06LGdTiennnoq9fX1rFixglgsRjweJxKJUFlZSSwWIxqNEovFiEQi2etN2zbFZDIBYBhGs21tteEx2qK95xNpjfZ+XbaHvpZFeqZt+X1GREREdmz6nUFk+xMMBrnqqqtwu91dXYrsoBT89wC79doFt8WFx9553yjy8/Pp1atXNmTY0p8iIiIiIiIiIiKyaRaLpatL6HZCoRAXXnghL730EmazmUmTJnHPPffg9Xpb3P/7779nwIABLd729NNPc8IJJwAtv4H6t7/9jZNOOqnjim8jBf89QN9A764uQURERERERERERKRLnXLKKaxatYoFCxaQSCSYMmUK55xzDk8++WSL+/fp04dVq1blbHvwwQeZNWsWRxxxRM72uXPnMmHChOx1v9/f4fW3hYJ/EREREREREREREenWvvzyS+bPn8/HH3/MyJEjAZgzZw4TJ05k9uzZlJeXN7uPxWKhtLQ0Z9u8efM48cQTm31KwO/3N9u3K2llVRERERERERERERHZrtTV1VFbW5u9bG690NZ4//338fv92dAfYPz48ZjNZj788MNWHWPRokUsXryYs846q9ltF1xwAUVFRYwaNYqHH364y0eeK/gXERERERERERERke3KsGHDyM/Pz15uu+22rTre6tWrKS4uztlmtVoJBAKsXr26Vcd46KGHGDp0KPvvv3/O9htvvJGnn36aBQsWMGnSJM4//3zmzJmzVfVuLY36EREREREREREREZHtypIlS+jVq1f2usPhaHG/K6+8khkzZmz2WF9++eVW1xOJRHjyySe59tprm9224bYRI0bQ0NDArFmzuOiii7b6vO2l4F9EREREREREREREtis+n4+8vLwt7nfZZZcxefLkze4zcOBASktLWbt2bc72ZDJJKBRq1Wz+Z599lnA4zOmnn77FfUePHs1NN91ELBbb5BsWnU3Bv4iIiIiIiIiIiIjskILBIMFgcIv77bffftTU1LBo0SL23ntvAP75z3+STqcZPXr0Fu//0EMP8fOf/7xV51q8eDEFBQVdFvqDgn8RERERERERERER6eaGDh3KhAkTmDp1Kn/6059IJBJMmzaNk046ifLycgBWrFjBuHHjeOyxxxg1alT2vt988w3vvPMOr776arPjvvTSS6xZs4Z9990Xp9PJggULuPXWW7n88su32WNriYJ/EREREREREREREen2nnjiCaZNm8a4ceMwm81MmjSJe++9N3t7IpFg6dKlhMPhnPs9/PDD9O7dm8MOO6zZMW02G3/84x+55JJLMAyDwYMHc+eddzJ16tROfzybYzIMw+jSCraBn376iT59+vDjjz/Su3fvri5HRERERERERERERFqgLLdjmLu6ABERERERERERERER6TgK/kVEREREREREREREupEeMeM/nU4DsGrVqi6uREREREREREREREQ2pSnDbcp0pX16RPC/Zs0agJyVmEVERERERERERERk+7RmzRr69u3b1WXssHrE4r7JZJJPP/2UkpISzOYde7pRXV0dw4YNY8mSJfh8vq4uR0S2Ib3+RXouvf5Fei69/kV6Lr3+RXqunv76T6fTrFmzhhEjRmC19oi+9U7RI4L/7qS2tpb8/HzWrVtHXl5eV5cjItuQXv8iPZde/yI9l17/Ij2XXv8iPZde/9IRduz2dxERERERERERERERyaHgX0RERERERERERESkG1Hwv4NxOBxcf/31OByOri5FRLYxvf5Fei69/kV6Lr3+RXouvf5Fei69/qUjaMa/iIiIiIiIiIiIiEg3oo5/EREREREREREREZFuRMG/iIiIiIiIiIiIiEg3ouBfRERERERERERERKQbUfAvIiIiIiIiIiIiItKNKPgXEREREREREREREelGFPyLiIiIiIiIiIiIiHQjCv5FRERERERERERERLoRBf8iIiIiIiIiIiIiIt2Ign8RERERERERERERkW5Ewb+IiIiIiIiIiIiISDei4F9EREREREREREREpBtR8C8iIiIiIiIiIiIi0o0o+BcRERERERERERER6UYU/IuIiIiIiIiIiIiIdCMK/kVEREREREREREREuhEF/yIiIiIiIiIiIiIi3YiCfxERERERERERERGRbkTBv4iIiIiIiIiIiIhIN6LgX0RERERERERERESkG1HwLyIiIiIiIiIiItJG33//PSaTiUceeaSrSxFpRsG/iIiIiIiIiIiIdLnPP/+c448/nn79+uF0OunVqxeHHnooc+bM6erSuo1DDz0Uk8nEtGnTNrvfu+++i8lkwmQyUVlZucXjLly4MLv/xpcPPvggZ99EIsENN9zAwIEDcTgcDBw4kJtvvplkMrlVj01yWbu6ABEREREREREREenZ3nvvPQ455BD69u3L1KlTKS0t5ccff+SDDz7gnnvu4cILL+zqEpvp168fkUgEm83W1aW0yvPPP8/777+/xf3S6TQXXnghHo+HhoaGNp3joosuYp999snZNnjw4Jzrp556Ks888wxnnnkmI0eO5IMPPuDaa69l+fLlPPjgg206n2yagn8RERERERERERHpUrfccgv5+fl8/PHH+P3+nNvWrl3bYedpaGjA4/Fs1TGSySTpdBq73Y7T6eygyjpXNBrlsssu44orruC6667b7L4PPvggP/74I2effTb33HNPm85z4IEHcvzxx2/y9o8//pinn36aa6+9lhtvvBGAc889l6KiIu68806mTZvGHnvs0aZzSss06kdERERERERERES61LJly9h1112bhf4AxcXF2b9vbq6+yWRi+vTp2evTp0/HZDKxZMkSfvWrX1FQUMABBxwAwOTJk/F6vXz77bccfvjheDweysvLufHGGzEMo9n5Zs+ezd13382gQYNwOBwsWbKkxVpWr17NlClT6N27Nw6Hg7KyMo455hi+//77nFpfe+01DjzwQDweDz6fjyOPPJL//ve/OfskEgm++uorVq1a1fonchNmzpxJOp3m8ssv3+x+oVCIa665hhtvvLHFf4vWqKur2+TYnn/9618AnHTSSTnbTzrpJAzD4KmnnmrXOaU5Bf8iIiIiIiIiIiLSpfr168eiRYv44osvOvzYJ5xwAuFwmFtvvZWpU6dmt6dSKSZMmEBJSQkzZ85k77335vrrr+f6669vdoy5c+cyZ84czjnnHO644w4CgUCL55o0aRLz5s1jypQp3HfffVx00UXU1dWxfPny7D6PP/44Rx55JF6vlxkzZnDttdeyZMkSDjjggJw3CFasWMHQoUO56qqrturxL1++nNtvv50ZM2bgcrk2u++1115LaWkpv/71r9t1rilTppCXl4fT6eSQQw7hk08+ybk9FosBNKvD7XYDsGjRonadV5rTqB8RERERERERERHpUpdffjlHHHEEw4cPZ9SoURx44IGMGzeOQw45ZKtn6O+55548+eSTzbZHo1EmTJjAvffeC8D555/P0UcfzYwZM7jooosoKirK7vvTTz/xzTffEAwGs9s27uKvqanhvffeY9asWTmd9RsG9/X19Vx00UWcffbZOfPszzjjDHbeeWduvfXWDp9zf9lllzFixIhmXfYb+89//sMDDzzAq6++isViadM57HY7kyZNYuLEiRQVFbFkyRJmz57NgQceyHvvvceIESMA2HnnnQH497//zYABA7L3b/okwIoVK9p0Xtk0dfyLiIiIiIiIiIhIlzr00EN5//33+fnPf85nn33GzJkzOfzww+nVqxcvvvjiVh373HPP3eRt06ZNy/7dZDIxbdo04vE4b7zxRs5+kyZNygn9W+JyubDb7SxcuJDq6uoW91mwYAE1NTWcfPLJVFZWZi8Wi4XRo0fz1ltvZfft378/hmG0ONaotd566y2ee+457r777i3ue9FFF3HEEUdw2GGHtfk8+++/P88++yxnnnkmP//5z7nyyiv54IMPMJlMOW98TJw4kX79+nH55Zfz/PPP88MPP/D000/z+9//HqvVSiQSafO5pWXq+BcREREREREREZEut88++/D8888Tj8f57LPPmDdvHnfddRfHH388ixcvZtiwYe067oad5Rsym80MHDgwZ9uQIUOA5t38mzrGhhwOBzNmzOCyyy6jpKSEfffdl6OOOorTTz+d0tJSAP73v/8B8LOf/azFY+Tl5W3xPBuLRCKsW7cuZ1tpaSnJZJKLLrqI0047jX322Wezx3jqqad47733OnTU0uDBgznmmGN4/vnnSaVSWCwWnE4nr7zyCieeeCKTJk0CMs/bzJkzueWWW/B6vR12/p5Owb+IiIiIiIiIiIhsN+x2O/vssw/77LMPQ4YMYcqUKTzzzDNcf/31mEymFu+TSqU2ebwtzbVvjdYe4+KLL+boo4/mhRde4P/+7/+49tprue222/jnP//JiBEjSKfTQGbOf9ObARuyWtse1z711FNMmTIlZ5thGDz22GMsXbqUBx54oNkbGXV1dXz//fcUFxfjdrv57W9/ywknnIDdbs/uW1NTA8CPP/5IPB6nvLy8zbX16dOHeDxOQ0ND9k2NXXfdlS+++IIlS5ZQXV3NsGHDcLlcXHLJJRx88MFtPoe0TMG/iIiIiIiIiIiIbJdGjhwJwKpVqwAoKCgA1ofSTX744Yc2HzudTvPtt99mu/wBvv76ayAzZqe9Bg0axGWXXcZll13G//73P4YPH84dd9zBX//6VwYNGgRAcXEx48ePb/c5NnT44YezYMGCZtuXL19OIpFgzJgxzW577LHHeOyxx5g3bx7HHnssP/74I08++WSLayHstdde7LnnnixevLjNtX377bc4nc5mnfwmk4ldd901e/3VV18lnU532HMiCv5FRERERERERESki7311luMHTu2WUf/q6++CqxfFDYvL4+ioiLeeecdLr744ux+9913X7vO+4c//CG7uK9hGPzhD3/AZrMxbty4Nh8rHA5jNptxOp3ZbYMGDcLn8xGLxYBMSJ+Xl8ett97a4sLFFRUV2bUEEokEy5YtIz8/n7Kysk2et6ysrMXbTzrpJIYPH95s+3HHHcfEiROZOnUqo0ePBmDevHnN9vv73//OU089xWOPPUbv3r2z25vWJejbty9ut7tZ3U0+++wzXnzxRY444gjM5k0vNRuJRLj22mspKyvj5JNP3uR+0jYK/kVERERERERERKRLXXjhhYTDYY477jh22WUX4vE47733Hk899RT9+/fPGWVz9tlnc/vtt3P22WczcuRI3nnnnWynfls4nU7mz5/PGWecwejRo3nttdd45ZVXuPrqq7e4kG9Lvv76a8aNG8eJJ57IsGHDsFqtzJs3jzVr1nDSSScBmTcu7r//fk477TT22msvTjrpJILBIMuXL+eVV15hzJgx/OEPfwBgxYoVDB06lDPOOKNdC/zusssu7LLLLi3eNmDAAI499tjs9Q3/3qSpw/+II46gqKgou/0Pf/gDN9xwQ/bNGoBf/vKXuFwu9t9/f4qLi1myZAkPPvggbreb22+/Pee4J554IuXl5QwbNoza2loefvhhvv32W1555RV8Pl+bH6e0TMG/iIiIiIiIiIiIdKnZs2fzzDPP8Oqrr/Lggw8Sj8fp27cv559/Ptdccw1+vz+773XXXUdFRQXPPvssTz/9NEcccQSvvfYaxcXFbTqnxWJh/vz5nHfeefz2t7/F5/Nx/fXXc91117XrMfTp04eTTz6ZN998k8cffxyr1couu+zC008/nV3IFuBXv/oV5eXl3H777cyaNYtYLEavXr048MADm83q31Ece+yxPPHEE9x5553U1tYSDAb5xS9+wfXXX8/gwYNz9h05ciRz587lgQcewOVyceCBB/Lkk0+2+OkEaT+TYRhGVxchIiIiIiIiIiIisq1MnjyZZ599lvr6+q4uRaRTbHq4kmxTY8eOzX40RqQl/fv3Z/LkyV1dhoiIiIiIiIiIiGznemTwv2zZMn79618zcOBAnE4neXl5jBkzhnvuuYdIJNJp512yZAnTp0/n+++/77Rz7CimT5+OyWSisrKyq0sBYOXKlUyfPr3Vq5M/8sgjmEwmnE4nK1asaHb72LFj2W233Tq4yo735ZdfMmHCBLxeL4FAgNNOO42KioquLktERERERERERES2Qo+b8f/KK69wwgkn4HA4OP3009ltt92Ix+O8++67/Pa3v+W///0vDz74YKece8mSJdxwww2MHTuW/v3759z2+uuvd8o5pXVWrlzJDTfcQP/+/ds0TywWi3H77bczZ86cziuuk/z0008cdNBB5Ofnc+utt1JfX8/s2bP5/PPP+eijj7Db7V1dooiIiIiIiIiIiLRDjwr+v/vuO0466ST69evHP//5T8rKyrK3XXDBBXzzzTe88sorXVKbQtYd0/Dhw/nzn//MVVddRXl5eVeX0ya33norDQ0NLFq0iL59+wIwatQoDj30UB555BHOOeecLq5QRERERERERKRzPPLIIzzyyCNdXYZIp+lRo35mzpxJfX09Dz30UE7o32Tw4MH85je/yV5PJpPcdNNNDBo0CIfDQf/+/bn66quJxWI59+vfvz9HHXUU7777LqNGjcLpdDJw4EAee+yx7D6PPPIIJ5xwAgCHHHIIJpMJk8nEwoULgeYz/hcuXIjJZOLpp5/mlltuoXfv3jidTsaNG8c333zT7PwtzX5vad2AtWvXctZZZ1FSUoLT6WTPPffk0Ucfzdmn6dxNtTX5/vvvMZlMOd8UV69ezZQpU+jduzcOh4OysjKOOeaYdo0zahqPs2TJEg455BDcbje9evVi5syZLdb31FNPcfXVV1NaWorH4+HnP/85P/74Y86+rXluFi5cyD777APAlClTsv82rfnmf/XVV5NKpbj99tu3uG9rv54Mw+Dmm2+md+/euN1uDjnkEP773/+2eMyamhouvvhi+vTpg8PhYPDgwcyYMYN0Or3Fep577jmOOuqobOgPMH78eIYMGcLTTz+9xfuLiIiIiIiIiIjI9qlHBf8vvfQSAwcOZP/992/V/meffTbXXXcde+21F3fddRcHH3wwt912GyeddFKzfb/55huOP/54Dj30UO644w4KCgqYPHlyNrA96KCDuOiii4BMWPz444/z+OOPM3To0M3WcPvttzNv3jwuv/xyrrrqKj744ANOOeWUNj7yjEgkwtixY3n88cc55ZRTmDVrFvn5+UyePJl77rmnXcecNGkS8+bNY8qUKdx3331cdNFF1NXVsXz58nYdr7q6mgkTJrDnnntyxx13sMsuu3DFFVfw2muvNdv3lltu4ZVXXuGKK67goosuYsGCBYwfP77N6zQMHTqUG2+8EYBzzjkn+29z0EEHbfG+AwYM4PTTT+fPf/4zK1eu3Oy+rf16uu6667j22mvZc889mTVrFgMHDuSwww6joaEhZ79wOMzBBx/MX//6V04//XTuvfdexowZw1VXXcWll1662VpWrFjB2rVrGTlyZLPbRo0axaeffrrFxy4iIiIiIiIiIiLbpx4z6qe2tpYVK1ZwzDHHtGr/zz77jEcffZSzzz6bP//5zwCcf/75FBcXM3v2bN566y0OOeSQ7P5Lly7lnXfe4cADDwTgxBNPpE+fPsydO5fZs2czcOBADjzwQO69914OPfTQZp34mxKNRlm8eHF2FFBBQQG/+c1v+OKLL9q8eOyDDz7Il19+yV//+tfsmwfnnnsuBx98MNdccw1nnnkmPp+v1cerqanhvffeY9asWVx++eXZ7VdddVWb6trQypUreeyxxzjttNMAOOuss+jXrx8PPfQQRxxxRM6+oVCIL7/8MlvzXnvtxYknnsif//zn7JssrVFSUsIRRxzBddddx3777cepp57appp///vf89hjjzFjxoxNvoHS2q+niooKZs6cyZFHHslLL72EyWTKnuPWW2/NOeadd97JsmXL+PTTT9lpp50A+PWvf015eTmzZs3isssuo0+fPi3Ws2rVKoAWP/lSVlZGKBQiFovhcDja9FyIiIiIiIiIiIhI1+sxHf+1tbUArQ62X331VYBmndOXXXYZQLO1AIYNG5YN/QGCwSA777wz3377bbtrhszomQ3n/zedoz3HffXVVyktLeXkk0/ObrPZbFx00UXU19fz9ttvt+l4LpcLu93OwoULqa6ubnM9LfF6vTnBu91uZ9SoUS0+3tNPPz3n3/P444+nrKws+2+3rQwcOJDTTjuNBx98MBuob6y1X09vvPEG8XicCy+8MBv6A1x88cXNjvnMM89w4IEHUlBQQGVlZfYyfvx4UqkU77zzziZrbvpUREvBvtPpzNlHREREREREREREdiw9JvjPy8sDoK6urlX7//DDD5jNZgYPHpyzvbS0FL/fzw8//JCzfcM56U0KCgq2OhDf+LgFBQUA7TruDz/8wE477YTZnPvP3jRuaOPHtCUOh4MZM2bw2muvUVJSwkEHHcTMmTNZvXp1m2tr0rt375zAGzb9PDZ1uTcxmUwMHjy4XesLbK1rrrmGZDK5yVn/rf16avpz48cWDAaz//ZN/ve//zF//nyCwWDOZfz48UBmPYdNcblcAM3WF4DMp0w23EdEREREREREpCu98847HH300ZSXl2MymXjhhRc6/ZwrVqzg1FNPpbCwEJfLxe67784nn3yy1cetqqrK5l81NTWtuk8sFmP48OGYTCYWL16c3d60HufGlw8++CC7TyKR4MYbb2TQoEHZ9T7nz5+fc/zbbruNffbZB5/PR3FxMcceeyxLly7d6se6Oc8//zyHHXYYhYWFzR6XdIweFfyXl5fzxRdftOl+G4fQm2KxWFrcbhhGm87XnuNuqsZUKtWuc7bleBdffDFff/01t912G06nk2uvvZahQ4e2e0Z8Rz+PHf3cbMrAgQM59dRTN9v1v7l62iOdTnPooYeyYMGCFi+TJk3a5H2bRvy0VOuqVasIBAIa8yMiIiIiIiIi24WGhgb23HNP/vjHP26T81VXVzNmzBhsNhuvvfYaS5Ysya7pubXOOuss9thjjzbd53e/+x3l5eWbvP2NN95g1apV2cvee++dve2aa67hgQceYM6cOSxZsoRzzz2X4447Lie7e/vtt7ngggv44IMPWLBgAYlEosX1JjtSQ0MDBxxwADNmzOi0c/R0PSb4BzjqqKNYtmwZ77///hb37devH+l0mv/9738529esWUNNTQ39+vVr8/k7MvTdUEFBQYvvEG7cwd+vXz/+97//kU6nc7Z/9dVX2dubjgc0O+amPhEwaNAgLrvsMl5//XW++OIL4vE4d9xxR3seSpts/G9jGAbffPMN/fv3z25r7XPTEf82TV3/LX3Dau3XU9OfG+9XUVHR7FMPgwYNor6+nvHjx7d4aelTKE169epFMBhs8Z3qjz76iOHDh7fqMYuIiIiIiIiIdLYjjjiCm2++meOOO67F22OxGJdffjm9evXC4/EwevRoFi5c2O7zzZgxI7t256hRoxgwYACHHXYYgwYNavcxAe6//35qampy1srcktdee43XX3+d2bNnb3KfwsJCSktLsxebzZa97fHHH+fqq69m4sSJDBw4kPPOO4+JEyfmZHfz589n8uTJ7Lrrruy555488sgjLF++nEWLFmX3qamp4eyzzyYYDJKXl8fPfvYzPvvsszY+A+uddtppXHfdddnJFdLxelTw/7vf/Q6Px8PZZ5/NmjVrmt2+bNmy7OKsEydOBODuu+/O2efOO+8E4Mgjj2zz+T0eD9A8UN9agwYN4oMPPiAej2e3vfzyy/z44485+02cOJHVq1fz1FNPZbclk0nmzJmD1+vl4IMPBjLhs8ViaTYj/r777su5Hg6Hs2NhNqzF5/O1OEKmoz322GM5o5ueffZZVq1albMIcGufm474txk0aBCnnnoqDzzwQLNxR639eho/fjw2m405c+bkfMph4/tBZgHp999/n//7v/9rdltNTQ3JZHKz9U6aNKnZc/Hmm2/y9ddfc8IJJ2z2viIiIiIiIiIi24tp06bx/vvv8/e//53//Oc/nHDCCUyYMKFZY2Vrvfjii4wcOZITTjiB4uJiRowYwZ///OetqnHJkiXceOONPPbYY83GcG/KmjVrmDp1Ko8//jhut3uT+/385z+nuLiYAw44gBdffDHntlgsll3PsYnL5eLdd9/d5PHWrVsHQCAQyG474YQTWLt2La+99hqLFi1ir732Yty4cYRCoVY9Ftn2rF1dwLY0aNAgnnzySX75y18ydOhQTj/9dHbbbTfi8TjvvfcezzzzDJMnTwZgzz335IwzzuDBBx+kpqaGgw8+mI8++ohHH32UY489lkMOOaTN5x8+fDgWi4UZM2awbt06HA4HP/vZzyguLt6qx3X22Wfz7LPPMmHCBE488USWLVvGX//612bvQp5zzjk88MADTJ48mUWLFtG/f3+effZZ/v3vf3P33XdnF8rNz8/nhBNOYM6cOZhMJgYNGsTLL7/cbGb8119/zbhx4zjxxBMZNmwYVquVefPmsWbNGk466aStekytEQgEOOCAA5gyZQpr1qzh7rvvZvDgwUydOrXNz82gQYPw+/386U9/wufzZd8dHjBgQJtq+v3vf8/jjz/O0qVL2XXXXbPbW/v1FAwGufzyy7nttts46qijmDhxIp9++imvvfYaRUVFOef67W9/y4svvshRRx3F5MmT2XvvvWloaODzzz/n2Wef5fvvv292nw1dffXVPPPMMxxyyCH85je/ob6+nlmzZrH77rszZcqUNj1uEREREREREZGusHz5cubOncvy5cuz43Auv/xy5s+fz9y5c7n11lvbfMxvv/2W+++/n0svvZSrr76ajz/+mIsuugi73c4ZZ5zR5uPFYjFOPvlkZs2aRd++ffn222+3eB/DMJg8eTLnnnsuI0eObHFNS6/Xyx133MGYMWMwm80899xzHHvssbzwwgv8/Oc/B+Dwww/nzjvv5KCDDmLQoEG8+eabPP/885scg51Op7n44osZM2YMu+22GwDvvvsuH330EWvXrs2Ohp49ezYvvPACzz77LOecc06bnxPZBowe6OuvvzamTp1q9O/f37Db7YbP5zPGjBljzJkzx4hGo9n9EomEccMNNxgDBgwwbDab0adPH+Oqq67K2ccwDKNfv37GkUce2ew8Bx98sHHwwQfnbPvzn/9sDBw40LBYLAZgvPXWWy3u+9ZbbxmA8cwzz+Tc/7vvvjMAY+7cuTnb77jjDqNXr16Gw+EwxowZY3zyySctnn/NmjXGlClTjKKiIsNutxu77757s2MZhmFUVFQYkyZNMtxut1FQUGD8+te/Nr744oucc1dWVhoXXHCBscsuuxgej8fIz883Ro8ebTz99NPNn/SNXH/99QZgVFRU5Dxfu+66a7N9zzjjDKNfv37Nnpu//e1vxlVXXWUUFxcbLpfLOPLII40ffvih2f1b+9z84x//MIYNG2ZYrdYWn+MNzZ071wCMjz/+uMV6gWaPpbVfT6lUyrjhhhuMsrIyw+VyGWPHjjW++OILo1+/fsYZZ5yRs29dXZ1x1VVXGYMHDzbsdrtRVFRk7L///sbs2bONeDy+yfqbfPHFF8Zhhx1muN1uw+/3G6eccoqxevXqLd5PRERERERERKQrAMa8efOy119++WUDMDweT87FarUaJ554omEYhvHll18awGYvV1xxRfaYNpvN2G+//XLOe+GFFxr77rtv9vovf/nLLR4zEokYhmEYl1xyifHLX/4ye9+mbKu6unqTj/Oee+4xxowZYySTScMw1meCn3766Wafn9NOO8044IADstfXrl1rHHPMMYbZbDYsFosxZMgQ4/zzzzecTmeL9z/33HONfv36GT/++GN22x/+8AfDbDY3e47NZrPxu9/9zjAMw3jttde2+Hzcf//9zc7X2sclbWcyjK1cfVZkG1u4cCGHHHIIzzzzDMcff3xXlyMiIiIiIiIiItuIyWRi3rx5HHvssQA89dRTnHLKKfz3v//FYrHk7Ov1eiktLSUej2+xy76wsJBgMAhkxmAfeuih/OUvf8nefv/993PzzTezYsUKAFauXEltbe1mj7nzzjtjMpkYPnw4n3/+eXaNScMwSKfTWCwWfv/733PDDTc0u++xxx7LSy+9lLMuZSqVwmKxcMopp/Doo4+2eM4//vGP3HzzzaxatSpnezQapaqqivLycq688kpefvll/vvf/+bsM23aNP7xj3/wzjvv5EzBmDFjBnPmzGlx3QS/309RURENDQ3NRmtvrLS0FL/fn7Pt+++/Z8CAAXz66adac7KD9ahRPyIiIiIiIiIiItJ9jBgxglQqxdq1aznwwANb3Mdut7PLLru0+phjxoxh6dKlOdu+/vpr+vXrl71eXl6eHS20Jc899xyRSCR7/eOPP+bMM8/kX//61yYXDL733nu5+eabs9dXrlzJ4YcfzlNPPcXo0aM3ea7FixdTVlbWbLvT6aRXr14kEgmee+45TjzxxOxthmFw4YUXMm/ePBYuXNhs9PVee+3F6tWrsVqt9O/fv8XzejyeNj3H0vkU/IuIiIiIiIiIiMh2q76+nm+++SZ7/bvvvmPx4sUEAgGGDBnCKaecwumnn84dd9zBiBEjqKio4M0332SPPfbgyCOPbPP5LrnkEvbff39uvfVWTjzxRD766CMefPBBHnzwwXbVv3G4X1lZCcDQoUOzHfAfffQRp59+Om+++Sa9evWib9++Offxer3ZY/Xu3RuARx99FLvdzogRIwB4/vnnefjhh3M+qfDhhx+yYsUKhg8fzooVK5g+fTrpdJrf/e532X0uuOACnnzySf7xj3/g8/lYvXo1kFkH1OVyMX78ePbbbz+OPfZYZs6cyZAhQ1i5ciWvvPIKxx13HCNHjmzzcxIKhVi+fDkrV64EyL7RUlpaSmlpaZuPJ80p+BcREREREREREZHt1ieffMIhhxySvX7ppZcCcMYZZ/DII48wd+5cbr75Zi677DJWrFhBUVER++67L0cddVS7zrfPPvswb948rrrqKm688UYGDBjA3XffzSmnnNIhj6cl4XCYpUuXkkgk2nS/m266iR9++AGr1couu+zCU089lTMaOxqNcs011/Dtt9/i9XqZOHEijz/+eM7Infvvvx+AsWPH5hx77ty5TJ48GZPJxKuvvsrvf/97pkyZQkVFBaWlpRx00EGUlJS06/G++OKLTJkyJXv9pJNOAuD6669n+vTp7Tqm5NKMfxERERERERERERGRbsTc1QWIiIiIiIiIiIiIiEjHUfAvIiIiIiIiIiIiItKN9IgZ/8lkkk8//ZSSkhLMZr3XISIiIiIiIiIiIrI9SqfTrFmzhhEjRmC19oj4ulP0iGfu008/ZdSoUV1dhoiIiIiIiIiIiIi0wkcffcQ+++zT1WXssHpE8N+0uvRHH31EWVlZF1cjIiIiIiIiIiIiIi1ZtWoVo0aNyma60j49IvhvGu9TVlZG7969u7gaEREREREREREREdkcjWzfOnr2RERERERERERERES6EQX/IiIiIiIiIiIiIiLdiIJ/EREREREREREREZFupEfM+G8NwzBIJpOkUqmuLkV6AJvNhsVi6eoyRERERERERES6nVQqRSKR6OoyZBMsFgtWqxWTydTVpXRrCv6BeDzOqlWrCIfDXV2K9BAmk4nevXvj9Xq7uhQRERERERERkW6jvr6en376CcMwuroU2Qy3201ZWRl2u72rS+m2ujz4f+edd5g1axaLFi1i1apVzJs3j2OPPTZ7u2EYXH/99fz5z3+mpqaGMWPGcP/997PTTjt1yPnT6TTfffcdFouF8vJy7Ha73m2STmUYBhUVFfz000/stNNO6vwXEREREREREekAqVSKn376CbfbTTAYVMa3HTIMg3g8TkVFBd999x077bQTZrOm0XeGLg/+Gxoa2HPPPTnzzDP5xS9+0ez2mTNncu+99/Loo48yYMAArr32Wg4//HCWLFmC0+nc6vPH43HS6TR9+vTB7XZv9fFEWiMYDPL999+TSCQU/IuIiIiIiIiIdIBEIoFhGASDQVwuV1eXI5vgcrmw2Wz88MMPxOPxDsl4pbkuD/6POOIIjjjiiBZvMwyDu+++m2uuuYZjjjkGgMcee4ySkhJeeOEFTjrppA6rQ+8sybakd5xFRERERERERDqHcpftn7LYzrddP8Pfffcdq1evZvz48dlt+fn5jB49mvfff3+T94vFYtTW1mYvdXV126JcEREREREREREREZEut10H/6tXrwagpKQkZ3tJSUn2tpbcdttt5OfnZy/Dhg3r1DpFREREREREREREOkI8Hqe6upp4PN7VpcgOrMtH/XSGq666iksvvTR7fcWKFQr/u4GxY8cyfPhw7r777q4uRUREZJsKhUJ4PB4cDkennufzzz9nzZo1nXoOERER6Vy77rorZWVlXV2GyHYlnU5jGMY2O5/JZGr3KJt4PM4333xDOp3GbDYzePBg7HZ7B1fYOv379+fiiy/m4osv7pLzy9bZroP/0tJSANasWZPzn9aaNWsYPnz4Ju/ncDhyfjGura3ttBq7yuTJk3n00UebbT/88MOZP39+F1TUMoX1IiIiW+/JJ59k8ODBHHbYYZ06C3PGjBkceuihnXZ8ERER6VwrV67kv//9LxdccAFW63Yd+YhsM+l0mnXr1pFKpbbZOS0WC/n5+W362b2iooLrrruOl156ibVr15KXl8fOO+/MNddcs8n1UTvbxx9/jMfj6ZJzy9bbrv8XGDBgAKWlpbz55pvZoL+2tpYPP/yQ8847r2uL2w5MmDCBuXPn5mzr7E5AERER2faqqqooKCjo1C4lwzDweDxMmDChyzqKREREZOv873//44033timnc0i2zvDMEilUlvVhd8W6XSaVCqV8zqMx+M0NDTg8Xg2+bP2LyZNIh6L8cCDf8Hp8lBZFeKD9/5FOBxuVx1Nj7s9bwLG43HsdjvBYLBd55btQ5fP+K+vr2fx4sUsXrwYyCzou3jxYpYvX47JZOLiiy/m5ptv5sUXX+Tzzz/n9NNPp7y8nGOPPbZL694eOBwOSktLcy4FBQUALFy4ELvdzr/+9a/s/jNnzqS4uDj7Ef6xY8cybdo0pk2bRn5+PkVFRVx77bU535hisRiXX345vXr1wuPxMHr0aBYuXJhTx7///W/Gjh2L2+2moKCAww8/nOrqaiZPnszbb7/NPffcg8lkwmQy8f333wPwxRdfcMQRR+D1eikpKeG0006jsrIye8yGhgZOP/10vF4vZWVl3HHHHVt8PqZPn87w4cN5+OGH6du3L16vl/PPP59UKsXMmTMpLS2luLiYW265Jed+NTU1nH322QSDQfLy8vjZz37GZ599lr192bJlHHPMMZSUlOD1etlnn3144403co7Rv39/br31Vs4880x8Ph99+/blwQcf3GLNIiIirVFZWUllZWWn/hJfX1+P2+3GbDZjsVh00UUXXXTRRZcd8OL1eolEIgr+RVqwrX7O3fjNhabRPStWrOCbb74hHo9jGAbJZJpYPElDJMEPP63h3X/9i6uvu5FR+x3EbnuMYP8DDmL6DTcxadIkvv/+e0wmUzY/hUyeZTKZWNiY0y1cuBCTycRrr73G3nvvjcPh4N13383mZQ888AB9+vTB7XZz4oknsm7duuyxJk+ezLHHHsstt9xCeXk5O++8M5DJu5qmeBiGwfTp0+nbty8Oh4Py8nIuuuii7DFakyHKttXlHf+ffPIJhxxySPZ602z+M844g0ceeYTf/e53NDQ0cM4551BTU8MBBxzA/PnzcTqdnVZTNJ7kp7X1nXb8Teld7MVp75h/krFjx3LxxRdz2mmn8dlnn/Htt99y7bXX8swzz+Qslvzoo49y1lln8dFHH/HJJ59wzjnn0LdvX6ZOnQrAtGnTWLJkCX//+98pLy9n3rx5TJgwgc8//5yddtqJxYsXM27cOM4880zuuecerFYrb731FqlUinvuuYevv/6a3XbbjRtvvBGAYDBITU0NP/vZzzj77LO56667iEQiXHHFFZx44on885//BOC3v/0tb7/9Nv/4xz8oLi7m6quv5v/9v/+32RFPkAnpX3vtNebPn8+yZcs4/vjj+fbbbxkyZAhvv/027733HmeeeSbjx49n9OjRAJxwwgm4XC5ee+018vPzeeCBBxg3bhxff/01gUCA+vp6Jk6cyC233ILD4eCxxx7j6KOPZunSpfTt2zd77jvuuIObbrqJq6++mmeffZbzzjuPgw8+OPvNUkREpL22Rcd/0zlMJlOnnUNEREQ6l9vtJhqNdnUZIrKBhoYGDANMZiuYLYTWNWB3uEinjezP9w6nG4/Xy/xXX2avvUZhttpIps2YzZY2n+/KK69k9uzZDBw4kIKCAhYuXMg333zD008/zUsvvURtbS1nnXUW559/Pk888UT2fm+++SZ5eXksWLCgxeM+99xz3HXXXfz9739n1113ZfXq1TmNs1vKEGXb6/Lgf+zYsZv9JdZkMnHjjTdmg+Nt4ae19Vxy19vb7HxN7rrkYAb39rd6/5dffhmv15uz7eqrr+bqq68G4Oabb2bBggWcc845fPHFF5xxxhn8/Oc/z9m/T58+3HXXXZhMJnbeeWc+//xz7rrrLqZOncry5cuZO3cuy5cvp7y8HIDLL7+c+fPnM3fuXG699VZmzpzJyJEjue+++7LH3HXXXbN/t9vtuN3u7HoNAH/4wx8YMWIEt956a3bbww8/TJ8+ffj6668pLy/noYce4q9//Svjxo0DMm9Q9O7de4vPSTqd5uGHH8bn8zFs2DAOOeQQli5dyquvvorZbGbnnXdmxowZvPXWW4wePZp3332Xjz76iLVr12bHJM2ePZsXXniBZ599lnPOOYc999yTPffcM3uOm266iXnz5vHiiy8ybdq07PaJEydy/vnnA3DFFVdw11138dZbbyn4FxGRrWa1WgmFQqTT6U47R2VlpYJ/ERGRHZzT6VTHv0gnSyQShMNh3G43Nput2e0GkEylicaTQJqUyY7V4cMgk3OazDYMw8BiNpFKQyKZJpmCmXf8kat/9xvmPvQXdt19T/bdbwynnHIy+48e2ab6brzxxmbrdkWjUR577DF69eoFwJw5czjyyCO54447spmdx+PhL3/5yyZHES1fvpzS0lLGjx+PzWajb9++jBo1KnvbljJE2fa6PPjfHvUu9nLXJQd3yXnb4pBDDuH+++/P2RYIBLJ/t9vtPPHEE+yxxx7069ePu+66q9kx9t1335xf8Pfbbz/uuOMOUqkUn3/+OalUiiFDhuTcJxaLUVhYCMDixYs54YQT2lT3Z599xltvvdXsTQvIdOxHIhHi8Xi2I7/pcbUmQO/fvz8+ny97vaSkpNnHrEpKSli7dm22lvr6+uzjaRKJRFi2bBmQGX0wffp0XnnlFVatWkUymSQSibB8+fKc++yxxx7Zv5tMJkpLS7PnERER2Roul6vTf4lX8C8iIrLjczqdxGIxBf8inSSRSPD999+TTqcxm83069cPq9VGKm2QTKVJpdPEE0kSiSRY4tlMKlAYIB6PYTbbSKYgEo+TTBqZNwMAq9XMMcf9gqOOOopPPnqfRYs+4vX/+z8euO8e/vKXvzB27NhW1zhyZPM3Cvr27ZsN/SGT/6XTaZYuXZoN/nfffffNrvV1wgkncPfddzNw4EAmTJjAxIkTOfroo7Fara3KEGXbU/DfAqfd2qbO+67i8XgYPHjwZvd57733AAiFQoRCoTatxF1fX4/FYmHRokVYLLkfLWoK7V0uVxurzhz36KOPZsaMGc1uKysr45tvvmnzMZts/E6ryWRqcVtTx2R9fT1lZWUtzhzz+/1A5h3KBQsWMHv2bAYPHozL5eL4448nHo9v8dyd2ZkpIiI9QzQaxW63k0wmOz349/v9Cv5FRER2YGazWaG/SBtsqXt/Yw3hMAZmzBYLmCxU10Ww29MY6cbXnckEBlhMJjCZSKYMErEkiWSatGEGUljMJmxWM063GavVjM2ywZoALhvjxo/nZ+PG85tLr+B3l07j+uuvp2kNzw1f34lEosUa25L9teV+ffr0YenSpbzxxhssWLCA888/n1mzZvH222+3KkOUbU/Bfze2bNkyLrnkEv785z/z1FNPccYZZ/DGG2/kdL9/+OGHOff54IMP2GmnnbBYLIwYMYJUKsXatWs58MADWzzHHnvswZtvvskNN9zQ4u12u51UKpWzba+99uK5556jf//+La4sPmjQIGw2Gx9++GF2hn51dTVff/01Bx/csZ/E2GuvvVi9ejVWq5X+/fu3uM+///1vJk+ezHHHHQdk3ixoWqRYRESkszXN3g+Hw536hnJVVRX9+/dvthiZiIiI7HgU/ots2cbd+/37928W/qfSRuaSSpNKpUkbdix2N02t+laLLdM4Y4ZUyiCRTBGPJ4nHkyRMMSwWCzaLGZfDmgn5rWbMLTTapA2DdNogbUBmQQCwmE0MHTqUl196kWAwCMCqVasYMWIEQM5Cv1uyfPlyVq5cmR3D88EHH2RHYreFy+Xi6KOP5uijj+aCCy5gl1124fPPP29Vhijbnn6z24HFYjFWr16dc6msrAQglUpx6qmncvjhhzNlyhTmzp3Lf/7zH+64446cYyxfvpxLL72UpUuX8re//Y05c+bwm9/8BoAhQ4ZwyimncPrpp/P888/z3Xff8dFHH3HbbbfxyiuvAHDVVVfx8ccfc/755/Of//yHr776ivvvvz9bR//+/fnwww/5/vvvqaysJJ1Oc8EFFxAKhTj55JP5+OOPWbZsGf/3f//HlClTSKVSeL1ezjrrLH7729/yz3/+ky+++ILJkyd3ShAxfvx49ttvP4499lhef/11vv/+e9577z1+//vf88knnwCw00478fzzz7N48WI+++wzfvWrX6mTX0REtpmmETwWi6XZp806khb3FRER6R70f7lIy9LpNKlUKnupr68nmUySTqdJJpPU1dcTiydoiMSpq49SXRumui5MbV2YhnCUaDwBZoP8PB8Opx2ny004lqR6XYTQuijr6mPE40nMJvC4rBT4HAT9Lvw+Bx6XDYfNgtlkwjAybygkkmniiRTxRIqKikqOPfoIXnjuKb5b9hWhtSt5Y/6L3HXnHRxzzDG4XC723Xdfbr/9dr788kvefvttrrnmmlY/dqfTyRlnnMFnn33Gv/71Ly666CJOPPHEnDU5t+SRRx7hoYce4osvvuDbb7/lr3/9Ky6Xi379+rUqQ5RtTx3/O7D58+dTVlaWs23nnXfmq6++4pZbbuGHH37g5ZdfBjIjdB588EFOPvlkDjvssOxitaeffjqRSIRRo0ZhsVj4zW9+wznnnJM93ty5c7n55pu57LLLWLFiBUVFRey7774cddRRQObNgddff52rr76aUaNG4XK5GD16NCeffDKQGZNzxhlnMGzYMCKRCN999x39+/fn3//+N1dccQWHHXYYsViMfv36MWHChGy4P2vWrOxIIJ/Px2WXXca6des6/Dk0mUy8+uqr/P73v2fKlClUVFRQWlrKQQcdRElJCQB33nknZ555Jvvvvz9FRUVcccUV1NbWdngtIiIiLWkK/v1+fzac7wyhUCg75k5ERER2XIZhqONfeqQff/yRzz77jH79+uVsN5lMWCyWbOAPmdeJxWIDkxUDMFusxJJmEnWN62qZwGwyYcKEgUEyaZBMpkmmDVKpzOvLbEpisZqwWcxYG/9seuPNbLFgs2ZG3mQ6+TMd/Y0FYTaBrfETABazCbejkDH778uf7pvDsmXLSCQS9OnTh6lTp3L11VcD8PDDD3PWWWex9957s/POOzNz5kwOO+ywVj03gwcP5he/+AUTJ04kFApx1FFHcd9997Xp+fX7/dx+++1ceumlpFIpdt99d1566aXsDP8tZYiy7ZmMHvC/wU8//USfPn348ccf6d27d85t0WiU7777jgEDBuB0Oruowq4xduxYhg8fzt13393VpfQ4PfnrTkRE2uapp57C6XTy1VdfcfDBB7Pvvvt2ynnOPfdcbrzxRv2/JCIisoO77LLLuPvuu9s951tkR/Tjjz9y3HHH4ff7ufrqqxk5ciR5eXnZ2xPJJMlkOrsIb2bmvkEymSKVSGC12bDZMv3RyVSaVDKzTyKdpik5tVoaQ35LZja/1dJ8MoVhZMb1GMb6T9+YzCYspsxcf4vFjNViwmI2YzZvm0/nTJ8+nRdeeKFNo4G2hc1lY5vLcqX11PEvIiIish2rrKxk9913JxAIUFVVlZ1B2tF6QC+IiIhIj2AYhsbTSo+zaNEiIpEIfr8fwzBoCEdwON2ZxXWz8/mNxtn8JsxmM1aTCYvZQtJiJZFMEw0nSaWbuvnBZrXgtNqwWi2N3fzNz7txN7/JZMZiMWUX8LWY11/XGC7Z1hT8i4iIiGzHqqqqyM/Pp7CwkFAo1CkBvUYCiIiIdB9ms5lkMtnVZYhslR9//JFFixax995706dPn03uZxgGDdEkvQfuSl7pEFxF5ZitTlKGldqGzPpYJpMJc2PXfTKZJpFMkUimSabSTevoYrWacNgs2QV4LS1042feVMssxNv0s7PZnDm2w2bBamkK+bddN7/I5ij478EWLlzY1SWIiIjIFlRVVREIBKiurubHH3/slIA+HA7jdrvVhSQiItINuFwuIpFIp60LJNLZmsb2RCIRXC4X8+bNy4b/iWSadfUxaupjVNdGWV0VprYhTjia4PjJvyVWH8Lj8WCzWTGZTI0Bfybob+rmt5hNWK1mPDYbtsaRPRv/GGyQ6eY3crr5MyG/vfE+VkvmDQLzdt7NP336dKZPn97VZUgXUPAvIiIish2Lx+PY7fZO7fivrKzE7/dv17+wiIiISOu4XC4aGhq6ugyRdmsa2wMQS8Kb/1rE3qNdrA2FqayJEI4miSdTmE0mnHYLTocFi9lONO4ingwQT6apqYththqN3fxmHPbMuB6bteVu/KZxPYZBTje/xWzCYbdm5/JbLCbM+plZdhAK/kVERES2Y4ZhYDKZKCwspLq6ulNm9lZWVlJQUKDgX0REpBto6vgX2Z60ZnRPPJGipj5GYa9d8Pfag7TVi8OVRyhVzPufr8RqMeN22Mjz2Kmpj7EmFGZ1VQNrqsKEY5nxVn2LXZiGuXA7rbjcDmwtLsC7YdCf281v22DUT1PIr5+RO4dGjXY+Bf8iIiIiOwCPx0NDQ0On/IDcNE5Iv9SIiIjs+BT8y/ampdE9vXr1pi4cp6Y+Rk1djLWhMFW1UcLRJIlkiuNPv5CqyrUM6NsLl8fH2uowq6vCrAmFqVoXwTDAZjVRXOBh6IAApYUeSgJu3A4zTns9FnM6G/o3hfxpA5qG+ptNJqyNnwCwWExYG7v59fPwthMOhwGw2WxdXEn3peBfREREZDsVi8WwWjPzSZt+CemsUT/q+BcREekenE4nkUiEdDqN2dy821lkW1u0aBHRWBKrq4C03cuz8xfRb3CU+kiCaDwFGNgsFtxOK3keG9W1aerjFmoSebz28Rpi8ZUAFPgclAQ87DaokNKAh4I8R7OxO/Fkiroo2CsrMQxz9udok9mEzWLCYjFjNpmwWMBiNoAUpCGZBq2JvW0YhkE4HGbt2rX4/X4sFktXl9RtKfgXERER2U5VVVU1C+Q7a9RPnz59FA6IiIh0A263Wx3/0qm2NLYnlTaobch08tfUxYjY+1K40yGkDTNWuwNcJURiSdxOGyaTibXVYdZUrWNNqIFQbQwAu81CacDNnoOLKGns5nfYcgPitGEQjiaIxJKEo0nShoHVYibqsuKyx0mtXZlZfNdkwmRCTS7bGb/fT2lpaVeX0a0p+BcRERHZTm3ciW+1WonH43g8nk49j4iIiOy4XC4X4XBY87OlU7Q0tqcwWEpNfYx1dXEq10VYE2ogHE0SjSfBMGG3OTj1lF+x4qflePKD1Ebg689WsiYUJpFMYwIC+U7KiryMGFJMSaEbv9fR7GfTeDJFJJokEksSS6QwYcLpsOB12ehflk+h34nf68DvdWC3mYnH413zJMkW2Ww2dfpvAwr+RURERLZTGwfy+fn5hEIhCgoKOvQ8oVAIv9/foccUERGRrtEU/It0ho8/XkQ8bcXuKwO7l8dfWkT/QbsQjiVIp8BsNuFyWPE4bRiGwdrqCGuqGlgdCrOu3gpU43JYKQ242XuXYkoLPRQXuLFZcz95mk4bhGOJbNCfNgxs1sw4oLIiL6WNbw74fQ58bjtmc/MGFqfTuY2eFdmR3HLLLbzyyissXrwYu91OTU1NV5fUaRT878AmT55MTU0NL7zwwjY75yOPPMLFF1/crV8UIiIi24uNg/9AIEBlZSWDBg3q0PMkk0nsdnuHHlNERES6hsvloqqqSh3/0ipbGttTH0mwrnEB3oqaMCGjnMDAA0kbJixWC3mBUmxWMz6LnaqaCKsrMovwrq0Ok0oZmEwQ9LvoW+qjNOChtNCNz2PHxEbd/IkU4WiScCyR+RSAyYTbYcXjsjGot5/C/Ew3f77P0Wzkj0hbxONxTjjhBPbbbz8eeuihri6nUyn4FxEREdlOVVVVMXTo0JzgPxQKabE+ERER2SSXy0U0Gu3qMmQHsPHYnmeefQ6fv5ia+hjVtVFWV4WpbYgTiSZIGWC1mPB48zjtlBP53zffYncXsWxVjH//9xvqwwkAvC4rJYUe9t21lJKAh2CBC6sl9+fWVDpNJJYkEk0QiaegsZvf5bTSrzSP4gI3fp+DfK8Dr8vWYje/SHvdcMMNQKa5ubtT8N9NjB07lj322AOn08lf/vIX7HY75557LtOnT8/uYzKZuO+++3jxxRdZuHAhZWVlzJw5k+OPPx6AhQsXcsghh1BdXZ39uP/ixYsZMWIE3333Hd9//z1TpkzJHgvg+uuvzzmHiIiIdJzKykr8fn9O8N8ZHXzqCBQREek+3G63Zvz3UFvq3t+QYRi898EikmYvzoJSLC4/j774Kf0H7pSZn28y4bJbcDosWMx2KmoiLF/TwJqqMBXVEdKGE4u5geICF4N7+yktdFMS8OB12ZqdJxpPZkf2JFOZbn6X00q+18GQQg+FeU7yvQ78Pjs2q7r5Zb26ujpqa2uz1x0OBw6Howsr2rEo+O9GHn30US699FI+/PBD3n//fSZPnsyYMWM49NBDs/tce+213H777dxzzz08/vjjnHTSSXz++ecMHTp0i8fff//9ufvuu7nuuutYunQpAF6vt9Mej4iISE9XVVWVM+qnsLCQL774okN/kQ+HwzgczRdPExERkR2T0+kkEoko+O9hWlp0d8PwP55IUdM4sie0LsrqUJiqdBkFA/YjlUxhNkNZeTk+t510fYzVoTBrQmFWVzYQjiUByPfYKSl0M6RvAaWFbgrzXVg26sZPpdKEY5mgP5rIdPPb7RbcDhsDyvMpDrjJ99rx+5x4nFb9DCqbNWzYsJzrakBuGwX/Hagt76x2hj322IPrr78egJ122ok//OEPvPnmmznB/wknnMDZZ58NwE033cSCBQuYM2cO99133xaPb7fbyc/Px2QyUVpa2jkPQkRERLJisVjOomRNo3468hf5qqoqAoGAfukSERHpJtxuN7FYrKvLkG1s0aJFRCIRACKRKP/+YBH72fKpqYuxNhSmqjZKOJokkUxhNplwOqwUBws48RfH8NX/lmFyFPDBlzVUrVuFYYDNaqK4wMPQAQFKAx6KA27cztwY0TAMorFkNuhPpdONi/vaCOQ7KS30UOBzZMf2bDzyR2RLlixZQq9evbLXN9Xtf+WVVzJjxozNHuvLL79kl1126dD6tncK/jvIlt5Z3Rb22GOPnOtlZWWsXbs2Z9t+++3X7PrixYs7uzQRERFph40D/sLCQqqrqzs0+N94nJCIiIjs2Fwul0b9dANtaS6NxpP0G7wbecWDSOLElV9MVbqM//vgB8DAZrHgdlrxuW3U1KUznfxVDawOhYnFU4CXAp+ZkoCL3QYWUlLoJpDnxLzRz4eJZONs/liSWDwJJnDYrHicVnr39VPkd+H3OfB7HbidthZrFWkLn89HXl7eFve77LLLmDx58mb3GThwYAdVteNQ8N9Bct9ZjbBo0aJtHvzbbLnfVE0mE+l0utX3b1okcMMfDhKJRMcUJyIiIm1mGEZOIO/z+aivr2/T/+9bUllZmTNOSERERHZsLpdLHf87uM01l6bSBrUNMdbVx6mpi7KmKkyoNkokluT4KVdSUbGWfn3KKC4qIBxPsTYUZk3VOtaEGgjVZr4u7DYLpYVu9hxcREnAQ0nAhcPevJs/HE0QiSUJR5OkDQOrxYzbYSVY4KK00E2Bz4nf6yDPY8eibn7pQsFgkGAw2NVlbHcU/HeQvffeG5fLlf2mvPfee3d1SS364IMPOP3003OujxgxAiD7Alm1ahUFBQUAzT4NYLfbSaVS26ZYERGRHiwej2Oz2XIC+aa/d3THv4J/ERGR7sNqtZJMJtXxvwPbsLk0Gk/x1ruL2GdfD1W1EVZXNRCOJonGk2CYsNvMmW5+j51Eykt9zMR/vqtn7aK1xJNpTEAg30lZkZfhQ4opDbjx+5qv7xRPprIL8DYt7uu0W/A4bfQvy6PQ78LvzYzscTkUJ8qOa/ny5YRCIZYvX04qlcpmn4MHD+52a5nqldpB+vTpw7x587p0xn9rPPPMM4wcOZIDDjiAJ554go8++oiHHnoIyHyB9+nTh+nTp3PLLbfw9ddfc8cdd+Tcv3///tTX1/Pmm2+y55574na7cbvdXfFQREREurWqqqoWR/AYhtHhHf+9evVS8C8iItKNmEwmBf/bmdaM7kml0qxriFPcZyj55buStnhwevxUpUr41+IVjfPzrXicNgzDYG11hDWNI3vW1ccBcDkslAY87LVLMSWFbkoKPNisud346bRBOJbIBP3xJOm0gc1qweWwUFbkpbTQjd+bmc3vc9sxm/VzonQf1113HY8++mj2elND9FtvvcXYsWO7qKrOoeC/A/Xp02e7Dfyb3HDDDfz973/n/PPPp6ysjL/97W/ZFbJtNht/+9vfOO+889hjjz3YZ599uPnmmznhhBOy999///0599xz+eUvf0lVVZVW0xYREekkVVVVLXbim83mDh3Ft6k3GERERGTHpdB/+7Kp0T0NkQQ19TFq6mJU1ISpqI4QjiaIxdNMOv1iQpVrGdC3F778PKpqIqyuCLO6Ksza6jCplIHJBEG/i76lPkoDHkoL3fg8dkxs1M2fSBFu7OaPNy3ua7fgddsZ1NtPYb6T/Mag32GzdNGzJLJtPPLIIzzyyCNdXcY2oeB/B7bhF+nChQub3f7CCy8021ZeXs7rr7++yWOOGTOG//znPznbNv6B4f777+f+++9vU60iIiLSNpsaweP3+6mursbv93fIeUKhkEb9iIiIdDOGYSj8344sWrSISDSOxZFHyuZl3uuLGDAkQW1DnEg0QcoAq8WE22HF67aRNuIkDRthCvjn4grqwisB8LqslAQ8jN61lNKAh2CBC+tGs/VT6cYFeKMJIvEUGI3d/E4rfUt9FBe4yffa8fuceF02dfOLdGMK/kVERES2Q5WVlS124gcCASorKxkwYECHnCcej2O32zvkWCIiIrJ90KifzrWlsT2GYVAfSVBTF6OmPkbC1Z+inX5GChM2u4uEvZiauihOhwWL2U5FTYTlaxpYU5Xp+k8bBhaziWCBi0G9/JQWuSkJePC6bM3OE40nG4P+JMlUGpPJhMtpJd/rYEihh0CeA7/Xid9nx2ZVN79IT6LgX0RERGQ7VFVVxZAhQ5oF/wUFBVRVVZFOpzGbzZu4d9uo219ERKT7UfDfOVoa21NSWp4d2VNdG2VVVZj6SJxwNLPIss1q5Ven/IrVK1eQHwgSTlr55Ku12YV6AfI8dkoCbob0LaC00E1hvgvLRt34qVSacGPIH02kMAwDh92C22FlQHk+wQIXfp8Dv8+Jx2nVz3giPZyC/x5E/+mLiIjsOCorK9lnn32a/cJWWFhIKBTqsP/X9fOBiIhI92MymUin011dRrf0ySeLiCVN2LzFGHYvT76yiH6DwoSjSRJN8/MdVlwOC2aTibXVEb5fWcuaUJjKdWaMH6qwWkyUBDwM7R+gNOChOODG7cyN6AzDIBpLZoP+ZDqNxWzC5bARyHdSGvBQkJeZy5/ncTRbwFdERMG/iIiIyHaosrKSQCDQ4qifL7/8skMC+0gkgt1uVzeYiIhIN+NwOIhEIuTl5XV1Kdu9LY3ticaT1NTFWFcfo2pdlBpTbwoHH0zKMGGz2nDllQKQ57ZRXZdmTSjM6qoGVofCxOIpAPw+B6UBN7sOLKSk0E0gz4l5o5+/kql0dgHeWCLzKQCHzYrHaaVXXz9Bf2M3v9eB25k78kdEpCUK/hup2022JX29iYjIljR9fHxjRUVFHdbxX1VVpYV9RUREuiGXy0U4HO7qMrZ7G4/tee6558kLFLOuPk5NXZQ1VWFCtVEisSTJlIHZDE6Hh9NO+SXfffsddm8RK0IJFv3vO0K1MQDsNgulATd7Di6iJOChJODCYW/ezR+OJjKz+WNJUmkDq8WM22ElWOCitNBNgc+J3+sgz2PHYlE3v4i0XY8P/m22zLuk4XC4xV+uRTpDPB4HwGLRwjoiItI2gUCA6urqDgn+KysrFfyLiIh0Qz01+N9S9/7G3v9wEQlcOPxBTI48Hnnx/zFg0BCi8RQYYLeZcTut+Dx2QrVRVlQ0sLoqzNpQmHjSgYk6AvlOyoq8DB9STGnAjd/naPazVTyZIpLt5k9hMplw2i14nDb6l+VR6Hfh9zrI9zpwOXp8VCciHaTHfzexWCz4/X7Wrl0LgNvt1i+/0qnS6TQVFRW43W6s1h7/EhQRkc1o6WeSvLw86urqOmRur4J/ERGR7snlchGJRLq6jG2qpUV3Nwz/U6k06xri1NTFqKnLLMAbSpcRGDiGZCqN1WKmuKQMj9MGhsHa6kh2ZM+6+kzznsthoSTgYcTOxZQWuSn2u7Hbchv60mmDcCyRCfrjSdJpA5vVgsthoazIQ2nAg9+XCfl9HnuzBXxFRDqKUkegtDQzj60p/BfpbGazmb59+ypoERGRFiUSCcxmc4v/T5hMJgzD0KgfERER2SSn00kkbcU3qgAAshZJREFUEsEwjB7z//yiRYuyb3ZEIhHe/3ARZmcBNXUxKtdFWBvKLMCbmbtv4LBbKSws4Fe/PI4vl36LxVnAp8vqqPhkDcmUgckERX4XfUt8lA7zUFroxuexY2Kjbv5EKrsAb7xpcV+7Ba/bzqDefgrzneR7HeR77TjtiuFEZNvRdxwyv0CXlZVRXFxMIpHo6nKkB7Db7ZjNmtEnIiItC4VC+P3+/8/en0fJddd3/v/z1t1v7Wu3WmtrteQdbMBmdQKGsDiAgZDAGUz48mUS8iXEmGATjMFAiBOGkJA5TCAMh8w38yUJIfnNOLGBgYQ9YLw2sSTjFUm21FXVVV3dVXepu/z+qFZbLclau9Xb+3GOz3G1uqo+lrurbr3u+74+J/ygPl9VPxdccMGqCQSEEEKI1cJxnGUf/J9ObU8/jNm8/UKy1VHCRMfJD9GM13DHDx4jSp7uz884GkkSc2jC42CzxaGJLlO9PuDgWBHDZYvn7BpmuJymWrTRjurWj+IEz+8P+vmDCJKZaX5LY8NwllrRIZ8xKGQtMrZOSqb5hRCLSIL/I6iqKp3rQgghhFh0J5vET6VS8zKs0Gw2T3qCQQghhBDLj2VZy7rj/0S1PUmSMO32aU/5TE77jLdcGu3BNP8bfvOD1OvjbFi7hkq5QBRDveXyi0NTHGr2qLdc4iRBTSlUizZb1hYYKjsMldJkHX3OGpIkwQ+i2dqeMIpRFAXb0shnTLaXHEp5i0LGIp8xjqn8EUKIxSbBvxBCCCHEElOv108Y/OdyOVqtFvl8/qyeR6p+hBBCiJXpcMf/fFwhuBiOrO3x/D7f+cHdPPf5GSYmPQ42e0y5AT0vJEkSdC2FY+pkHIMoztGPNR56ssd3xxr0vBCArGMwXHbYvqHIUMmhUrCP6daPoni2ssfrRyRJgmmoOKbG6EieatGmkDUpZEzSti7HT0KIJU+CfyGEEEKIJeZkm+6WSiWazSabNm06q+fxfR/TNM/qMYQQQgix9DiOw/j4+JIK/k+luieOE6Z6ASObdpFfcx6R4mBlyzTjIb79032D/nxTwzZVUopCve3yxFMdDjZ7NCZdkgQ0VWGolGbnphJDJYehkoNjHTvN7/nhbNAfxjFqSsE2dUo5i+FymmLOpJA1yaVNdE2qeoUQy48E/0IIIYQQS0yj0WDbtm0nDf7jOD7rPWNkWk0IIYRYeWzbxvO8xV7GrGeq7vGCkMnpgPaUR3PS49BEj6legBdEXPu299Gsj7NpwwilYoH2lM/BiR4Hm10OTvRmNumFQtZkuOSwa3OZ4bJDKWsd060fRjE9L8T1Q/wgBAVMXcOxNNZuKFDJ2xSzg6D/6JMEQgixXEnwL4QQQgixxDSbTZ7znOc8YyhfLpdpNptnPcW3lKYAhRBCCDF/jtzcdykYVPd4pIw0oZrhf/2fu9l6XsREx8P1Q8IoIZUCy9BIWxopRWG6ZxIZZX7wHxNMdJ4CwNBSDJfTXLS1MjvNbxlzo60kSQab7/qDoD+KB5v72qZGtWgzXHYoZi0KGZNc2kBVZZpfCLEySfAvhBBCCLHEnGzT3XK5zN69e8/qw7zv++i69NMKIYQQK5FlWbMd+QvhVGp7XD+kPeXTnvIhO0pl21VEqOimg6fWeKrZxbE0smmDiY7HgXqXg80e4xM9gjBGAUr5Qe3OJdurDJfSFLLmMccuQRjhHp7m70coioJlqKQtnU1rcpTzg27+fMbENiUGE0KsHvKKJ4QQQgixxPR6PWzbfsY/L5VKTExMnFXwLxv7CiGEECvXQk78H6+2Z2RkLZPdYCbo9zg40aM95Q8m7qOEVCrFm3/jrdQPPUmpXMOLDX72aJNDzS7t6QAAy1AZLqe5dEeN4bJDrehg6Oqc547jhJ7fHwT9QUgSDzr9bUtjTSU9e3IgnzHJpo1jNvAVQojVRIJ/IYQQQoglJkmSEwby5XL5rIP/RqNxwqsKhBBCCLF82ba9YMH/3XffjdeP0Z0ysZHh7+64mw1bXHpeONO7n2AaGrapkXV0Gm2Pg/UuhyZ6jE+ohI83UBSoFGzWD2W5fFea4bJDNm2gcNQ0fz+a3YC3H0agKNiGSsYx2LIuTzlvk8+Y5DPGMZU/Qgix2smrohBCCCHEMpPL5Ziamjrr4F8m/oUQQoiV6XQ29z1ZbU8/jJmc9mlP+7Q7PlPqeipbX0KUpNB0AzU9RD+MyTgaSRJzaMLjULPFwZmNegEcS2O4nOY5u4YZLqepFm20o7r1ozjB8/uDfv4gIkkSDE3FtjTWD2UYKqXJZwwKWYuMrR+zga8QQoi5JPgXQgghhFhC+v0+qVSKVOqZN5pLpVLEcUwcx2f8PBL8CyGEECuXYRgEQXDSIYGja3u+9rWvUaoM05rymZz2GW+5NNq9wTT/bH++zVt/4838Yt8vsLNVGlMJ//H4PuptlyhOUFMK1aLNlrV5hssOQ+U0GVuf87xJkuAH0WxtTz+KSSmDyp58xmR7yaGUtyhkLPIZ45jKHyGEECe35IP/KIr4yEc+wv/7//6/HDx4kJGREa677jo+9KEPyQdVIYQQQqw4rVaLfD5/Ssc5Z9vxv3PnTjmeEkIIIVaQJ598krGxMS688MJT+v4f33U3QWJg5EpgZvnr/30Pm7bswPVC4iRBV1M4lk7GMYimfcYnehyc6HGw2aXn6UCbrGMwXHbYtqHIUMmhUrCP6daPonhQ2eOHeDPT/Kah4pgaoyN5qsXBBryFjEna1uX4RAgh5sGSD/5vu+02Pve5z/HlL3+Z888/n5/+9Ke8/e1vJ5/P8573vGexlyeEEEIIMa9OddPdVCpFGIZn/DzS8S+EEEKsLE8++STveMc78DwPy7LYvHnznCGBOE6Y6gWztT3jEz2a8QilzS8gShS0VIpSZQ2WoZJSFOptlyeaHQ42ezQmXZJksJHuUCnNeRtLg2n+koNjHTvN7/nhbDd/GMeoioJt6ZSyFsPlNMWcSSFrkkub6NozX+UohBDizC354P+HP/whv/qrv8qrXvUqADZt2sT/9//9f/zkJz9Z5JUJIYQQQsy/er1+SsF/Npul3W6Ty+XO6HlO9QSDEEIIIZaHsbGx2V5/z/PodKaot1zccZeJjsfBZo/pXoAbRJAk6JpKPp/nrb/+Bn7+80dR7RIP7uvyr/fV8YIIgELGZLjssGtzmeGyQylrHdOtH0YxPW8wze8Hg6EE09BwLI21GwpUCzaFzCDoP/okgRBCiIWz5IP/K6+8ks9//vM89NBDbN++nfvvv5/vf//7fPrTn37G+/i+j+/7s7enpqbOxVKFEEIIIc7aqXbvl0olGo0GGzZsOKPnOTwNKIQQQoil6cjanpGRkRN+b5zA5q07yZTW0Y817FyFftTizh89CimTVAqsmTBeURTqrR4HJyY5NNGjOekBNobmM1zWuHBrhaHSYJrfMubGRkmS4PrhYANePySKEjQthW1qVIs2w2WHYtaikDHJpQ1UVab5hRBisSz54P/GG2+k0+lw3nnnoaoqURTxiU98gre85S3PeJ9PfvKTfPSjHz2HqxRCCCGEmB/NZpPNmzefUvA/MTFBHMcn3AhYCCGEEMvP0bU9X/ziF+eE/14Q0ZkOmOr5THQ86i2Xnh/y6t/4XRqNJiPDVb79T18g4xhMeQkH6j0ONbscmugRhDEA5bzFUMnh4m0VhkppilnzmOOPfhg9Pc0/u7mvStrS2bgmRyU/6ObPZ0xsc8lHTEIIsaos+Vflv/u7v+Nv/uZv+J//839y/vnnc9999/He976XkZER3va2tx33PjfddBPXX3/97O0DBw6wa9euc7VkIYQQQogz1mw2edaznnVKwX+z2TzjDX6TJJGaHyGEEGKJmlPb4wf85O4xnq1mmZz2GW+5dLoBnh8SxcnMNL+OY2ooxTyJYrC/6dKY9Pj7bz1EmOhYhspQ2eHSHTWGyw61ooOhq3OeM44Ten4f1wtxg5AkHnT625bGmnKa4XJ6NuTPpo1jNvAVQgixtCz54P/9738/N954I29+85sBuPDCC3niiSf45Cc/+YzBv2mamKY5e7vT6ZyTtQohhBBCnK1Trfopl8v8/Oc/P6PgPwgCNE2T4F8IIYQ4R06ntsf1QkY2bCdb3UykmFiZMq24ynfv2w8JGLo2mLq3NSamfBpNl3rbpd7uEUWgKFDKWtimzvMvrLF+ZIhcxkBh7vt+0I9mN+Dth4M72oZKxjHYsi5POW+Tz5jkM8YxlT9CCCGWviX/yt3r9Y65fF1VVeI4XqQVCSGEEEIsnOnpaRzHOen3lctlfvKTn5xR8N9sNikUChL8CyGEEOfAiWp7wihhquczOR3QmQ4Yb/WY6vXxgj6vetNvMdFssm7tEOVSnulen8akS701yXjLpev2AbBNlWrR4dJtNSpFh3LBQk+l+NtHC6wrDyb0ozjB8/uDbv4gIkkSDE3FtjTWD2WolRwKmZlpfsc4ZgNfIYQQy8+SD/5f85rX8IlPfIINGzZw/vnnc++99/LpT3+a3/zN31zspQkhhBBCLIhTCeQPd/yfafB/KlcVCCGEEOLsHVnbE4QJ3//JGBdfatGc9GhOurhBRDDTn2/qKrahkkrpeIGN5pR54LEOzfvGiePBNH8lb7FpOEulaFMtOKRtbc40f5IkBP0IUjoHDk4w2bdJKYPKnnzGZHvJoZS3yGdMChnzmMofIYQQK8OSD/4/+9nPcvPNN/Pbv/3bjI+PMzIywrve9S4+/OEPL/bShBBCCCHm3akG+fl8nk6nc0bBf6PRoFQqSfAvhBBCnKFTqe7phzGdrk9pzVbywzuJVQfDztGOyvx09yHUVArb0shYOp0oodF2GW+7NNo9el4EQNrWqBUcRkfyVAsOpZyJelQrQhTHuH4fL4jw+09P85umSSmrcflFI+QzJsWsSdrW5f1fCCFWiSUf/GezWT7zmc/wmc98ZrGXIoQQQgixoMIwJJVKHVNzeDyHqw/PpP6w0WhI1Y8QQghxho5X3bNmzQjTbsBUN2CyG9Bou0x0PDw/oh9FvPKNv0l7osn6tcM4TobmpMt4a5r6zPclCagqVAo2W9YWqBRtagUb29TnPHeSJPj9ENeP8PyQMI5RFQXL1MlnTIaKDrmMQT5jMPHIMDvWpzl/c1ne84UQYhVa8sG/EEIIIcRq0Wq1yOfzp/zhXFGUM57437Fjh4QAQgghxBkYGxvDDyI0K09sOPzLd8ZYtymg6/bx+hEkCZqqYpkqGVuj04txA5VOmOU799fxgkMA5NI61aLDtvUFasVBx/7R3fphHON6IV4QEfRDQMHQVWxTZdNIllJusAFvzjGwrbkRT9qxcV2XJEnkPV8IIVYhCf6FEEIIIZaI0+3eVxSFKIpO+3kajQbPec5zJAQQQgghOHltT5zAdG9mmn86wNPXUhy9kjhJoRsmsVGm54XYpkpKUWh0XMYnpmi0XdpTPgmgqwqVos32jSVqRZtqwcbU50YySZLgBTPT/EGfOAY1pWCZGqWcxVBpEPJn0wa5U9iA17YHwb8QQojVSYJ/IYQQQoglotFonFbwn8lkaLfbZLPZ03qeZrMpHf9CCCEEx6/tKVWGmOoGdLo+Ex2Pesul54dH9OcbXPv613Hw4AGcbIVuP8Xjuw9Sb7n0o8GVeIWMQbXosGu0RLXokE8bx7zv9qNBXY/rR/TDGBQGm/uaKutqBUo5i6xjkssYWMbpb8Br2za9Xu+Mrg4UQoiV6PHHH+djH/sY3/72tzl48CAjIyO89a1v5Q/+4A8wDGOxlzfvJPgXQgghhFgiTrd7v1Qq0Ww2Wb9+/Wk9j+u62LZ9JksUQgghVpT7HxijH6sYmRroDl/75hjrNrlP9+enFCxDwzE1FAXqbY9Gq8N4y6XT1YA2pp6iWrS5YEuFWtGmXLAxtLlBfZwkeH4f14/w++HsNL9tagwVHaoz3fy5tEHGMTjJMP8psW2bTqdz9g8khBArxJ49e4jjmL/8y79k69at/OxnP+Od73wn3W6XT33qU4u9vHknwb8QQgghxBLRbDbZsGHDKQf/xWKRZrMp3b1CCCHEjJPV9rh+SKcbMDk9mOZvx0MUNj6POFFQVZV0oYqaUkjbGq0pn0PNHvW2S73dI4pAUaCUtVhTTnPxtgqVgk0ubaAw9304CCNcP8TzI8KZO5q6SsbW2bgmSyFrkk8PantM/fSn+U+FbdscOnRIJv6FEGLGK17xCl7xilfM3t68eTN79+7lc5/7nAT/QgghhBBi4TQaDS6++OLTnviP4xhVPfXQQE4UCCGEWImOru35/Bf+iky+zOR0QGc6YLzVY6rXxwv6RHGClkphp7O84fWv5rHH9qE7RX5RD/jpQ0/QdfsA2KZKtehw6bYalaJDuWChp1JznjeKE/ygjxtEeEFIMrO5r22qjFTTVAo2+bRBNm2QsQ3O1Vuw4zizm/sKIcRyNDU1NefKJdM0MU1zXp9jcnKSUqk0r4+5VEjwL4QQQgixRJzu5r7lcpnHHnvstD7Q9/t9VFWV4F8IIcSSd7Lp/aP99J4xopSDma+SsnL8/Td+xrqNowT9CGVm4t4yVNSUTrPj8VSry3i7R3PSI45NFKVHJW+xcThLtWhTLTikbW3ONH+SJAT9CDcIcb1BHZCiDCp7srbO5pEchaxJLm2QS5voWuoEK15YsrmvEGK527Vr15zbt9xyCx/5yEfm7fEffvhhPvvZz67IaX+Q4F8IIYQQYsnodDqk0+lT/v5yuczdd999WsH/xMTEae0jIIQQQiyG4226e2T4H0YxnemAya5Pezqg3urRimvkN1xGFMakVKjVhshYOp0oodF2GW+7NNo9el4EQNrWqRVsRtfkqRZtSjkL9Zhp/njQzR9ER2zuO5jmXz+cpZK3yKZN8mmDtK2f07+jk5GJfyHEcvfggw+ydu3a2dvPNO1/4403ctttt53wsXbv3s155503e/vAgQO84hWv4I1vfCPvfOc752fBS4wE/0IIIYQQS8jpBPKVSoVWq3VaH+hP96oCIYQQYjGMjY3heR4Anudz1z1jXK7n6HQD6m2XiY43pz/fMjQq5TyveeXLeeTRJ1CMAvc+0mGiM06SgKpCpWCzeW2eatGhVrCxzblBfZIk+P0Q14+e3txXUbBMnXzGZGhmA958xiDrmGjq0n4vtW179u9QCCGWo2w2Sy6XO+n3ve997+O666474fds3rx59t+ffPJJrrrqKq688ko+//nPn+0ylywJ/oUQQgghlql8Ps/k5ORpBf/j4+MS/AshhDjnTqe2x+9HrNu0g2xlEyE6VqZKK67xb/fsJ0lAU1NYpkrG1uj0YsYnXOoz0/xeEANpcmmoFk22rS9QKzoUMiap1Nz3vjCOcb0QL4gI+iGgYOiDaf5NI1lKOZt8xiTnGNjW8otPLMuSiX8hxKpQrVapVqun9L0HDhzgqquu4tnPfjZf+tKXSKUWr5JtoS2/dy4hhBBCiBUoigb9w6cTyKuqSpIkMvEvhBBiSTtRbU+SwFQvYKobMDk9mOZvT3u4fsQrf+3dTDSbrF1To1rO4wcxjY7L+IRLo+3SnvJJAF1VqBRttm8sUis6VAs2pj437kiSBC+YmeYP+sQxqCkFy9Qo5SxqRZtC1iSbNsg5xjEnCZYjy7LwPE+CfyGEmHHgwAFe8pKXsHHjRj71qU9Rr9dn/2x4eHgRV7YwJPgXQohl4m/+5m949atfTT6fX+ylCCEWQLvdJpfLnfbESZIkxHF8yt/faDTYunWrBP9CCCHOmSNre/x+zA/vGuPSZztMdDzqLZeeH87pz7eMwTR/GKVxwxR793f5/liDfjQIsAsZg2rRYddoiWrRIZ82jnlf60eDuh7Xj+iHMShgzkzzr60WKOctso5JLmNgGeo5/zs5F1RVPa1jBCGEWOm++c1v8vDDD/Pwww+zbt26OX+2Ek+SSvAvhBDLxN/+7d+yceNGXvCCFyz2UoQQC+BsJvGjKDqt57n88ssl+BdCCHFWTqW6J44TpnoBlbVbyQ1vJ06lMZ0c7ajCj3721GDi3tBwTA1FgXrbo97qUG+5dLoBAIaeolawuWBLhVrRplywMbS5QX2cJIMNeP0Ivx/OTvPbpsZQ0aFSnKnsSRtkHIMVMMx/WlZimCWEEGfiuuuuO+leACuJBP9CCLEM+L7P+Pg4e/bs4YorrkBVV+ZUkhCrWb1ep1AonPb90uk0k5OTZLPZU/r+ZrNJoVCQ4F8IIcQZe6bqHtcP6XQDOl2f5qRHo+3i+hFBGPKqN7yT1kSTDWuHyWQztKZ8DjV71Nsu9XaPmT16KWUtRippLt5WoVKwyaUNFOa+ZwVhhOuHczb3NXWVjK2zYThLMWeSTw9qe0x9dR83r+TuaiGEECcmwb8QQiwDDz/8MC984Qv5+c9/ThzHEvwLsQI1Gg2KxeJpf0AvlUo0m81jLlV9Jt1uF8dxzmSJQgghBDBT3eP3UY0ssebw9e+OsX5LyFS3jxf0ieIELZXCMjXSlkbiJoQYeEqe7//HBF33EAC2oVItOVy6rUal6FAuWOhHvQ9GcYIf9HGDCC8ISZIETR1U9qyppqkWbPJpg2zaIGMbyHntuU53LyAhhBArhwT/QgixDDz44IM873nP4/bbbyeKInRdX+wlCSHmWaPRYP369ac9iX84+E+S5JTvK9P+QgghjnQqtT09t89kL6Az7RPa6yiNXkmUpNBNi0Av0+74WKaKmtKZ6Hg81eoy3u7RnPSI48E0fzlvsWE4Q63gUC3apG19zjR/kiQE/Qg3CHG9kDCOUZRBZU/G1tk8kqOQHVT25NImuibT7CejKIoE/0IIsUpJ8C+EEMvAnj17eM1rXkMqlcL3fSzLWuwlCSHmWbPZ5KKLLjrtUL5cLjMxMXHKwb98+BdCCHGk49X21IaG6UwHTHZ92tMB9VaPabeP5w8m7tWUxute93rq4wfJFsp4kcbYIw3q7R49b7DvTNrWqBYcRtfkqRZtSjkL9Zhp/njQzR9Ex2zuu344SyVvkU2b5NMGaVsGX86UbPArhBCrkwT/QgixDOzfv5/h4WE2bNjAY489xiWXXLLYSxJCzLMz3dy3XC7z+OOPE8fxSWuC+v0+qqpK368QQohZDzwwRhCB7lRIDId/+tYYaze6c/rzLV2dneZvtl3G29PUWy4TnRTJ/hYpFSp5m81r81Rnpvkdc25QnyQJfj/E9SM8fzDNryoKlqmTz5jUig75jDE7za+pcnXafFAUhTAMF3sZQgghFoEE/0IIscQdntBRFIVt27axd+9eLrroIgnuhFhhOp0OmUzmtO9XKpW49957T2mSv9Vqkc/npepHCCFWsJPV9gRhTGfap9MLaHU8JpU1FDddSZQo6JqGla0CkHV0Jrsx9ZbLeMul0e7hBYPj0mxap1aw2ba+QLVgU8xapFJz31vCOMb1QrwgIuiHgIKhp7BNjU0jWUo5m1zGJO8Y2JZEEwvFtm1c16VYLC72UoQQQpxj8u4qhBBL3OFpf1VV2bFjB3fccQdRFEnwL8QKczod/Uc6surnZM70qgIhhBDLw9G1PX/1xS+SzVeY6gZMTgfU2y7taQ93Zpo/lVKwDIdrX3cN+/btw0iXeKoVMvbYftpTPgmgqwqVos32jUVqRYdqwcbU50YJSZLgBTPT/EGfOIZUCmxTp5QzqRWL5DMmuYxBzjGOOUkgFo5lWfR6vcVehhBCiEUgwb8QQixxu3fvZsuWLSiKwujo6GylhxBCABQKBdrt9ikF//V6nUKhIMG/EEIsE6ey6e6R7rlvjBATI1dCMbL83dfHWL9xM34/giRBn+nPz9oq7emY8Yke9QmX8bZLPzSAaQoZg2rRYedoiWrRIZ82SB31vtGPZrr5/Yh+GAMJpqFhmyprqwVKOYtc2iSb1rFNiR0W0+GJfyGEEKuPvAMLIcQSt3v3bi6//PLZXu4oioiiaLGXJYSYR0dWep0uTdOI4/iUgv9GoyET/0IIsUwcb9PdI8P/OE6Y6gV0ugGT0z71lksrrlHY+ByiKEFVFcqVGrapoSjQaHvUWx3G2y6d6QAAQ09RK9icv7lMrWhTKdgYmjpnHXGS4M6E/H4/JI4T1NSgsmeo6FAu2BSyg5A/65jIMP/SYtu2TPwLIcQqJcG/EEIscQ8//DDXXnvtbLVPpVLh4MGDbN68eZFXJoSYL+12m2w2e1YVXqdyJVCz2WR0dFSCfyGEWAbGxsbwPA8Az/O4+94xVKtAp+szMenRaLv0/IhgZuNWQ9Mo5PO87jWv5JHHniBlFnjwF10aD9QJB3v0UsparCmluWhLhWrRJpc2UJj7nhCEEa4fDjb3jSNAwdRVMrbO+uEspZxJzhnU9pi6evSyxRJjWRau655xpaAQQojlS4J/IYRY4oIgwDCM2dvbtm1jz549Et4JsYLMR/f+qVwJ1Gw2ufTSS+W1QwghFsHp1PZEccLGLeeRKW8gTDTsXJVWXOPbP/0FcZKgKiksUyNtaeAl1Nse9dYk9bbLdK8P2NhGSLVkcPG2GtWCTblgo6upY57HD/q4QYQfhMRJgqaq2KbKmkp69uRALm2QsQ3k7WP5cRxHgn8hhFilJPgXQoglrNVqkcvl5kwBb9++nfvuu4+rr74aTZOXcSFWgnq9TrFYPOP7O47D9PQ02Wz2hN/XaDQolUrywV8IIc6xk9X29LyQya5PZ9qnOenRnHRxg4hX//r/Q7PRZM1wlVIxTxwnTHQ8nmx1GW/3aE56xPFgmr+ct1g/lKFWcKgUbDKOPmeaP0kSgn6EG4S4fkgYxSiKgm1qZGyd0TU5CjmTfNoglzbRtTO/Ck0sHYc7/k+lElAIIcTKIomREEIsYXv27GHz5s1zgv9t27bx1a9+VTb4FWIFOdy9f6ZVP6VSiXq9zpo1a074fdPT0ziOc0bPIYQQ4szNqe3x+/z7T8e49LI07emAeqvHtNvH80OSZKY/39LIWDpxNks/1nj8kMtdex+j5w2u7krbGtWCw+iaPJWiTTlnoaaOnuYfbMDrBRFeEJGQYMxs7rt+KEs5P9iAN582SNv6Of87EeeGbO4rhBCrlwT/QgixhO3evZutW7fOCQOz2Sy9Xk82+BViBWk2m4yMjJzxJH6pVGJiYuKULuOXaX8hhJgfp1LdkyTQ9foMrdtGrraVKGVhOiXacYUfPvAkKAqWrmKaKmpKp9l2GW9PU2+5THQ8kgRSKlTyNpvX5qkWHKpFG8fUj3qeBL8/6OV3/ZAwjkkpCrapk8uYbCnaFDLmTG2PiabKe8FqYds2rVZLJv6FEGIVkuBfCCGWsD179vCCF7zgmClgy7LodDrYtr1IKxNCzKdms8muXbvOKvhvNpsnDf7lQ78QQsyPZ6ruCcKYzrRPpxfQ7viMt3r0vBA3CHnlm95Fq9lk3dohSoU8k12fessd/NN28YLBUEc2rVMr2GxbX6BasClmLVKpua/tYRzj+SGuHxH0Q0DB0FPYpsbGkSzlnE0uY5JzDBxLPvavZoc7/oUQQqw+cgQghBBLWLvdJp/PHxPkbd26lYceeoihoaFFWpkQYj41m82z6t4vlUocOHCAOI6fsS4oDENSqdQZ1wkJIYR42qC6xydlOERqmm9+f4xNWxPa0x6uHxFGEamUgqVrWEYKBY2eZhEbJe5+aJL21DgJoKkK1aLN9o0FakWHSt7GMuZ+TE+SBC8YhPxeEBLFMWpqMM1fypnUikXyGZNcxiDrGKgpmeYXT5OOfyGEWL0k+BdCiCXK9310XT9uELht2zb27t3LlVdeiaqqi7A6IcR8arfbJ92Y90QqlQpjY2Mn/FDfarWOeyJRCCHEqdX2eEHEVDeg0/NRMhsojl5JjIph2nhqmUMTXSxDJWurtKdjxid6sxP9QTjYm6mQMagWHXaOlqgWHfJpg9RRr8v9aNDN7/oR/TAGJcHUNWxTZW01Tyk36ObPpnVsUz7SixOzLEuCfyGEWKXkKEEIIZaohx9+mE2bNh13OnfHjh18//vfJ45jCf6FWAFOpZv/REql0kn7e5vNJoVCQYJ/IYQ4yvFqe4aH1zDVC+h0AyanB5U8nW4wpz//ta+7lkZjnFKpjB+bPPSLNvV2j8npAABDT1Er2Jy/uUy1aFMp2Bja3OO2OElwZzbgdY/c3NfUBlcAFGzyGWNmmt9EhvnF6Uqn01L1I4QQq5QE/0IIsUQ9+OCDbNmy5bjB/9DQEOPj40RRhK7rx7m3EGI5OdspvFMJ/huNBsViUYJ/IYQ4ytjYGH4/RrMLxEaa//1vY6zb4NHzI4IwhAQMXcMyVNK2TnvK52C7y3jLpdFWCPdNoChQzFoMldJcuKVCtWiTSxsozH3NDcJotps/jCNAwdRV0pbGuqEspZxJzhlswmsaMtwhzp5lWXieJxP/QgixCknwL4QQS9SePXt4zWtec9yJfkVRSKVS+L6PZVmLsDohxHyJ4xhFUc4qkNc0jSiKJPgXQghOXtsTxQmdrk9nOmCyGzCdGqE0eiVRkkLTdVS7Qj9KSFsaeAn1tkejPcl4y2W61wfAMlSqRZuLt9WoFmzKBRtdnTusEccJbtDHDSL8ICROEjRVxTZV1lTSsycHcmmDjG0gL89iIdi2jed5i70MIYQQi0CCfyGEWKL279/P8PDwM4Z0GzZs4LHHHuOSSy45twsTQsyrTqdDJpOZl0D+ZFU/GzZskOBfCLGiHa+2p1CqMdn1meoGNCZdmm0PNwjp9yMURcHQLK59/Wt58skDWOkSremEvfsP0Jz0iGNQFCjnLdbXMtSKNtWCQ9rRj53m70e4QTioA4oGJ3VtQyNj62weyZHPmuTTBrm0ia7JRuvi3NB1nTAMZeJfCCFWIQn+hRBiCYrjwQZwJwroDm/we9FFFx23DkgIsTwcnsSfj9/jKIpO+DwXX3yxBP9CiGXlVDbdPdJ994/Rj3WMbAH0NF/9xhjrNm3BO7I/39LIWDqdKKExOdh8t97u0fM0oINja9QKNpuG81RLNqWchXbUa3QUDzbg9YIIL4hISNBnpvnXD2Up5wcb8ObTBmlbahnF4pL3fiGEWJ0k+BdCiCXo8LT/iTbu3bFjB3fccQdRFEnwL8Qydjj4P1u2bTM9PU0mkznunzebTan6EUIsK8eb3j86/J92+3S6AZ1pn8akx0Q8RGHTc4li0NQUuVINQ0+hpnSabZfx9jT1lstExyNJIKVCJW8zOpKnWrSpFRwca25QnyQJfj/E86M5m/vapk42Y7Cl6FDImDO1PSaaKq+zYmlJkkQm/oUQYhWS4F8IIZag3bt3s2XLlhMGdKOjozz++OOzVwcIIZan+ereL5VKNBoNhoeHj/vnnU6HdDp9Vs8hhBDn0tjY2Gw3ued53HvfGKZTZLIX0O74jLd69LwQNxhM8+uqSjab5Q2vfTWPPPYEql3gkSdd/v3BCbxgcEVUNq1TLdhsXVegWrQpZS1Sqbmvv2Ecz27AG/RDEsDUVSxDY+NIlnLOJpcxyTsGtiUfqcXyIMG/EEKsPnKUIoQQS9Du3bu5/PLLTzjxf3gzzxNVewghlr5ms0mtVjvrK3dKpRLNZpMkSZ7xJIJM+wshFtPp1PYkCWzeupNMcS39RMPOlmklQ3zzrn2EUURKUbAMDctIoaDR6Hj8ojVNvdWjPeWTYKGpPtViiu0bClSLDtWCjWVoRz1PghcMQn4vCIniGDWlYJk6pZxJrVgknzHJZQyyjoGaktdRsfwoiiLBvxBCrEIS/AshxBL08MMPc+211540CKxUKhw8eJDNmzefo5UJIeZbo9Fgx44d8zLxPzEx8YzBv3zgF0IsppPV9vhBNKjs6flMTPo02j26Xshr3vJe6o0ma4ar5LJZ1BS0p2PGW71BN3/LJQgHVz8WMgbVosN5oyVqBYd8xiB11OthPxp087t+RD+MQUkwNA3HUllbyVHK2+TSJtm0jm3Kx2WxcshxgBBCrD5yJCOEEEtQEAQYhnHS79u2bRt79uxhdHRUJnmFWKbmq3u/VCpx8OBB4jg+5qRhFEUoiiKvE0KIRTOntscP+MndYzxbzTI5HVBv9+hMB0f152vYpkaplCdJmTzZdLn/kX1MTgcAGHqKWsFm1+YytaJNpWBjaHOvlIyTBHdmA173yM19TY1a0aFSsClkByF/1jGRYX6xkkk9qBBCrD4S/AshxBLTarXI5XKnVPuxfft27rvvPq6++mo0TV7ShViO2u02uVzurB+nVCrx4IMPHnei7/BzyEbgQoj5dKrVPa4fMrJxO9nqKJFiYaXLtOIq371vPyRg6BqWoZKxdVpTPgfbXcZbLo12jzACRYFi1mKolObCLRWqRZtc2kBhblIfhNFsN38/ilBQMA2VtKWxbihLKWeScwab8JrGM9cpCrHSGIaB53nzcrwhhBBi+ZCUSAghlpg9e/awefPmUwrotm3bxle/+lWZ4BFiGTvehP6ZqFQqsx3/R5uvqwqEEOKwZ6ruieKETtdnqtunPT3YgHeq18fz+7zq136bZqPJ+pEhyqU8Xa9Pve3RaE9Sb7lM9foAWIZKtWhz8bYa1YJNuWCjq3NfJ+M4wQ36uEGEH4TESYKmqtimyppKmkrBJp8xyKUNMraBvPyJ1cy2bbrd7mIvQwghxDkmwb8QR4njmJ/97GdLcsPUdDrN9u3bF3sZYoHt3r2brVu3nlIQmM1m6fV6S/LnVQhxauarc7dYLNJut4/7ePV6nWKxOC/PI4QQ8HR1T0oziRSbb/1gjC3nQbPt4QYhQT9CAUxdwzJVVEvH79vo6TJjj3do3D9OHA+m+ct5i3VDGWoFm0rBIePox53md/1wUAcUxSiKgm1oZGyd0TU5CjmTvGOQy5jomlzdJMSRLMvCdd3FXoYQQohzTIJ/IY7yzW9+kzvuuINNmzYt9lKO8eMf/5hPfOITspHrCrdnzx5e+MIXnvIEsGVZdDodbNte4JUJIebb4Y1452MS3zAMwjA8bvDfaDQoFotS9SOEeEanUtsTRvFgA97pAD2/keKm5xGjoZsOvVSZXzw1hW1qZCydTpTQnHQZb7ept3r0vMGQgmNr1AoOl63JUynalHIW2tH7ksSDDXi9IMLrRyRJgj4zzb+ulqVSsMilTfJpg7StL/jfjRDLneM4EvwLIcQqJMG/EEe58847+e3f/m3K5fKSq0TYsmULd955J+9617tQVeklXakmJyfJ5XKn/PO3detWHnroIYaGhhZ4ZUKI+dbpdEin0/P2fqMoyjMG/+vXr19y72tCiKXhmWp7um6fyW5AZ9qnMenRnHTxDvfnKwrXvPZNTEyMU61U6ScGjx/sUG+5THQ8kgRSKlTyNpvX5qkWbKoFB8eaG9QnSYLfD/H8aGZz34SUArapk80YbCk6FNImuYxBLm2iqfI6JsTpsiyLXq83O3AghBBidZDgX4gjTE1NEQQB+XweXV9600NXXHEF//AP/8A73vEOCf5XKN/30TTttA7It2/fzt69e7nyyivl50KIZeZw9/58TuIfb8+PZrPJhRdeKB/2hRDHNTY2hh+EaGae2HC447tjrN0Y0PNC3GBwJZGmprBNjayj0+kmjLd61Fsu9bbGA/saAGTTOrWCzdb1BaoFm1LWIpWa+7oTxjGePwj6/X5IApi6imVobBzJUs7Z5DImOcfAseTjqhDz4fDEvwT/QgixuiyLI6kDBw7wgQ98gDvuuINer8fWrVv50pe+xGWXXbbYSxMrzDe/+U2e//zno2lL81fDMAyGh4d5+OGHOf/88xd7OWIBPPzww4yOjp5WCLhjxw6+973vEcexBP9CLDOHK3jmi2madLtd0un0nK/L5r5CrC4nq+1JEph2B5U9k90Az1hLcfRKokTFMAwivUzPCzH1FIqi0Zz0GG9NU2/1aE/5JICmKlSLNts3FKgWHaoFG8vQjnqeBC8I8YLBNH8Ux6gpBcvUKeZMasUi+YxJNq2TS5uoKXmNEmIhSMe/EEI87ZprruG+++5jfHycYrHIS1/6Um677bZnrDpczpZmunmEVqvF85//fK666iruuOMOqtUqP//5z2WDOrEgvvWtb3HDDTcs2eAf4GUvexl33HEH5513noS8K9CDDz7I5s2bTyv4r9Vq1Ot1oihakleqCCGeWb1ep1AozFsgXywWaTQa1Gq1OV/vdDpkMpl5eQ4hxNJ2vNqecmVo0M3f85no+DRaPbpeiB9EJCQYmsHrX/c6Dh16inS2TK+f4u49h6i3XIJwcBVRPmNQKzqcN1qiVnDIZwxSR7129aPBNL/rh/TDCBQwNA3HUhmp5CnlLLJpg1zawDaX7vG2ECvNkRP/Qgix2l111VV88IMfZM2aNRw4cIAbbriBN7zhDfzwhz9c7KXNuyV/tHXbbbexfv16vvSlL81+bXR0dBFXJFaqZrOJruvz2rW8EJ71rGfx5S9/mSAIZDPXFWjPnj1cc801p3VS5/DGoL7vY1nWAq5OCDHfGo0G1Wp13qp+SqUSzWbzmEv5kySRjX2FWCXuf2CMfqxipGtgOPzj/xlj3UZ3pj8/JqUo2KaGbQ6qBRttl8dbU9TbPSanVaCNoaeoFWx2bS5TK9pUCjaGNvfYJE4S3JkNeF1/UAekpgZ1QLWiQ6Vgk88Y5DIGWcdEhvmFWDy2bdNoNCT4F0II4Pd+7/dm/33jxo3ceOONvPa1r6Xf76+4YcolH/z/r//1v3j5y1/OG9/4Rr7zne+wdu1afvu3f5t3vvOdz3gf3/fxfX/29tTU1LlYqljm7rzzTl70ohct+Sl6VVXZsmULP/vZz7j88ssXezlinu3fv5/h4eHTPvm0ceNGHnvsMS655JKFWZgQYkE0m022bds2byecTxT8CyGWp5PV9rh+SKcbMNUNmJh0mUyGKWx8LlGSQtNUnHyVVEohY+u0pnwOtruMt1wa7R4zQ/kUsxZDpTQXbqlQLdrk0gYKc1+XgijC80Lcw5v7omAaKmlLY91QllLOJOeY5NIGprG0j6eFWG1s25aqHyHEsjQ1NUWn05m9bZompmnO2+NPTEzwN3/zN1x55ZUrLvSHZRD8P/roo3zuc5/j+uuv54Mf/CB33XUX73nPezAMg7e97W3Hvc8nP/lJPvrRj57jla4cnU6HVqvFxo0bF3sp59R3v/tdbr755iVd83PY1Vdfzde//nUuvfTSZbFecWqOtyHnqdq2bRt79+7loosukqleIZaR+e7eL5VK1Ov1OUH/4deWpXw1mxDi+I6u7fnCF75IOl9iqtunPe0z3uox1evj+X3ieHBlj+1keMPrX8Pjj+1DTxfZ1wi45+dPMNXrA2AZKtWizcXbalQLNuWCja7OPXaI4wQ36OMGEX4QEicJmqpimyprKumnp/nTBhnbQF5ehFjapOpHCLFc7dq1a87tW265hY985CNn/bgf+MAH+Iu/+At6vR7Pe97zuP3228/6MZeiJZ8YxnHMZZddxh/+4R8CcOmll/Kzn/2M//bf/tszBv833XQT119//eztAwcOHPODIo5vamqK66+/Htd1uemmm7jgggsWe0nnxJNPPkmhUMAwjGURjOzatYvPfe5zBEEgwf8Ksn//ftasWXNGV53s2LGDf/mXfyGKIgn+hVhG2u02hUJh3h6vUqmwZ8+eOZt9t9ttcrmcvDYIsQScbHr/aD+9d4xIsTHzVVJWlr/75hjrNowS9CMUwNQ1LFNFtXQmpjzqjS71Vo/GpEccmyiNHqW8xbpaZqayxyHj6MdO84eDuh7XDwmjGEVRsA2NjK0xuiZHIWeSdwxyGRNdk9cSIZYby7LwPG+xlyGEEKftwQcfZO3atbO3n2na/8Ybb+S222474WPt3r2b8847D4D3v//9vOMd7+CJJ57gox/9KP/pP/0nbr/99mWRCZ6OJZ8Yrlmz5pjQfufOnfzDP/zDM97n6Ms+jrwkRDyzbrfL+973Pq677joqlQqf+MQn+OAHP8jOnTsXe2kL7p//+Z95yUtesmxCdEVROP/887n77rt54QtfuNjLEfNk9+7dbNmy5YzeaDZt2sQTTzxxVlcNCCHOvSMD+vlQKpVotVpzJvrm+6oCIcSZOd6mu0eG/2EUDzbgnQ5oTfvUWz1aUY38hssJoxhVhWp1iIyl04kSmpMu4+029ZZLzwsBcCyNatHm2cN5qkWbUt5CO+qkXxTHeDPd/F4/IkkSdFXFMlXW1bJUCha5tEk+bZC2V94l70KsRul0Wib+hRDLUjabJZfLnfT7DueZJ7J58+bZf69UKlQqFbZv387OnTtZv349//7v/84VV1xxtkteUpZ8yvn85z+fvXv3zvnaQw89tOpqaBZar9fjfe97H295y1vYvn07lmVx8803c+utt/LhD3+Y7du3L/YSF9S///u/87GPfWzJ9/sf6eqrr+arX/0qV1xxxbI5YSFObPfu3TznOc85o59DTdOIoogoihZgZUKIhZIkybx+CD9e8F+v1ykWi/P2HEKIMzM2NjY7cet5Hj+9Z4zLjDydaZ/GpEdz0sU73J+vKFi6Srmc55pXvZxHHvsFipHnvkc7TEyOkySQSkElbzE6kqNatKkVHBxrblCfJAl+P8Tzo5nNfRNSClimRjZtsKXkUEib5GZqezRVpvmFWIksy5LgXwixolWrVarV6hnd9/AA5ZH7xa4USz4t/L3f+z2uvPJK/vAP/5A3velN/OQnP+Hzn/88n//85xd7aSuG53nccMMNvOlNb2Lnzp1YlgXA8PAwH/rQh7j11lu59dZb55wZW0keeeQR1q1bh6Zpy2oacsuWLezfvx/Xdclms4u9HDEPHn74Ya699tozruMol8scPHhwxf6uCrHSHA795/O9xzRN+v3+nA/2jUaDQqEgVT9CzLPTqe0Jwph1ozvIVjYRomNlqkzENf717n1AgppKYZsaWUen000Yb/Wot1zqbRcviACHrAPVosHWtYXBNH/WIpWa+/oRxjGePwj6/X5IAhi6im1obBzJUs7Z5DImOcfAsZb8R0EhxDyxbVuqfoQQAvjxj3/MXXfdxQte8AKKxSKPPPIIN998M1u2bFlx0/6wDIL/yy+/nH/8x3/kpptu4tZbb2V0dJTPfOYzvOUtb1nspa0Ivu9zww038NrXvpYLLrjgmK6skZERbrrpJm6++WY+8YlPsGnTpsVZ6AJabjU/R3r2s5/ND37wA17+8pcvq5MW4vj6/T6GYZzx/bdt28aePXsYHR2VnwchloGpqSkcx5n331dFUY6p+lmzZo28Lggxj05U25MkMO0OKnsmuwGNtktrysP1I171a++m0Wyybk2NSjlP0I9pTnqMt6ZptAbflwCaCtWiw/YNBaoFh2rRxjLmHqsmSYIXhHjBYJo/jmNSKQXL1CnkTGrFIoWMSTatk0ubqCl5DRBitTJNE9/3ZeJfCLHqOY7D1772NW655Ra63S5r1qzhFa94BR/60Ieecf+A5WxZJJ2vfvWrefWrX73Yy1hxgiDg93//93nVq17FJZdcgmmaxw0F1q9fz4033siHPvQhPvnJT7J+/fpFWO3CSJKEe++9lze+8Y3LMvi/+uqr+cIXvsAv//Ivo+vSwbqctVqts958c/v27dx3331cffXVy/LnWYjVZiG794/c76PZbLJr1y4J/oWYR0fW9vj9iB/dNcYllzlMdHwarR5dL8QPIhISDE3FMlSyjkYUZ3BDlYcO9PjBz5oE4eB3NZ8xqBYcdmwqUis65DMGqaN+Z/vRYJrf9UP6YQQKGJqGY6mMlHOU8jbZ9KCyxzblOEAI8TRFUeQ4QAghgAsvvJBvf/vb8/JYjzzyCF/60pd45JFH+LM/+zNqtRp33HEHGzZs4Pzzz5+X5zhbckS4SvX7fT7wgQ/w0pe+lGc/+9nPGPoftnHjRm644QZuuukm/viP//iklzMvFz/72c/Yvn37sg1JR0ZGaLVaTE9PS3/zMrdnzx42b9581sH/V7/6VdngV4hlotFoLEjwr+s6vV6PdDoNyOa+QpyqU6nuiROY6vlU1m4lN7SdOOVgOHlacYV/H3sKRVGwTQ3bHFRINiZdnmhNMd7qMTkdAGBoKapFm12bS1SLDtWCjaGpRz1PgjuzAa/rh8RJgjZTB1Qt2lQLg5MDuYxB1jaOqfwRQoijzfe+QkIIsZp95zvf4Vd+5Vd4/vOfz3e/+10+8YlPUKvVuP/++/niF7/IV7/61cVeIiDB/6oUhiEf/OAHefGLX8xzn/vck4b+h23evJn3vve9fOADH+BP/uRPGB4ePgerXVi33347V1111bIN/gGuuOIKvvOd7/Crv/qrEuosYw8++CBbtmw5q+A/k8nQ6/Vkg18hlomFCv5LpRLNZnN2c6t2u00ul5vX5xBipXmm6h7XD+l0A6a6AROTLvVJl54XEYQhr3zDO2m3mqxfO0wum6U17VOf6FJvu9RbLmGUoADFrMVQKc2FWypUiza5tIHC3N/7IIrwvEFtTxBGKCiYhkra0lg3lKWUM8k5Jrm0gWmox/+PEEIIIYQQ58SNN97Ixz/+ca6//vo5+27+0i/9En/xF3+xiCuba/mmneKMRFHEzTffzHOf+1yuuOKKUw79D9u+fTu/8zu/w+///u/zqU99ilqttoCrXVhRFPHzn/+ct7/97ajq8v0A9dKXvpRPf/rTvPKVrzyrfnixuPbu3cuLXvSis95807IsOp0Otm3P08qEEAul0WhQKpUWJPiv1+vs2LFjtu9fTgwLcWJjY2N4foBqZIi1NF//7hgbtoR0en08v08UP70Bb9rSwEuIFQM/ledHuyeY6h4CwDJUqgWbi7ZWqBUdygUbXZ373h7HCW4wmOb3gplpflXFNlWGy2kqBXswzZ82yNgG8usrhJgPMvEvhBDzZ2xsjP/5P//nMV+v1Wo0Go1FWNHxSfC/isRxzC233MIll1zCC1/4QizLOqMgYOfOnfzWb/0W73//+/n0pz9NuVxegNUuvJ/+9KdcdNFFyzr0ByiXy/i+T6vVYmhoaLGXI87Q5OQkuVzurMO5rVu38tBDD8nPghDLQLPZPOsrfY6nVCoxMTExG/jLh3yxGp1KbU/PC+n0AjrTPrG9ntLo84mSFLppE+hlWh0fy1RRLZ2JKY+DjS7jbZfGpEscgaJAKW+xrpqhus2mWrTJOMeZ5g8HdT2uHxJG8aAOyNBwLI1Na3IUciZ5xyCbMTG0+X09EEKIwxRFkUpQIYSYJ4VCgaeeeorR0dE5X7/33ntZu3btIq3qWBL8rxJJknDrrbeyc+dOXvKSl5xx6H/Y+eefz//1f/1f3HDDDXz6059elv3y//zP/8zrXve6ZV3zc9iLXvQivvWtb/HmN7953gMksfB830fTtHmZyN2+fTt79+7lyiuvXPYntYRY6ZrNJoVCYd6n8cvlMo1GgyRJiONYNvQTq87xantqQ8N0ugGd6YB212e81aPbC3H9PnECWkrlta97PfXxg+QLZbxI52ePNhhvufS8EADHGvTrP3t7jUrBoVyw0I467oriGC8I8fwQrx9BApqawjJV1tWyVPIWuYxJPm2QtvXF+OsRQqxiMgwghBDz481vfjMf+MAH+Pu///vZE6s/+MEPuOGGG/hP/+k/LfbyZi3/xFOcVJIk/OEf/iGjo6O89KUvPevQ/7CLL76Yt73tbbPhfz6fn4fVnhtBEPDkk08yMjKyIsLRX/qlX+KjH/0ob3jDG6TuZxl6+OGHGR0dnZeTNjt27OB73/secRyviJ9tIVayVqtFoVCY98ctlUo89NBDJEnC1NQUmUxGgn+xqjzwwBhBBLpTJtHT/NO3xli30cX1I/pRhKIoWLqKaaRIpXQmJl0OtFzG2y4TkymS/S1SKajkLUZHclSLNrWCg2PNDeqTJMHvh3j+YKI/jBNSClimRjZtsLnoUMyY5GZqezRVhjOEEItH0zT6/f5iL0MIIVaEP/zDP+Td734369evJ4oidu3aRRRF/MZv/AYf+tCHFnt5syT4X+GSJOGP//iPGRoa4hWveMW8hf6HPetZzyKKIt73vvfx7ne/+7Sm51VVZefOnYsSRvzgBz/gsssuWzHBaCaTQdd1xsfHWbdu3WIvR5ymBx98kM2bN89L8F+r1ajX60RRhK7LJKEQS1kYhgty1Vm5XGZiYoI4jmc3EJarwcRydrLann4Y05n2mewFtDs+ndQaihuvGNT26BpmtkICZB2dTjeh3nYZb/Wot1y8IIKZP6sUbLasLVAr2pSyFqnU3GPUMI4Hk/x+hN8fXAWg6yq2obFhOEulYJPLmOQcA8eSj1lCiKXFtm16vR6lUmmxlyKEEMueYRh84Qtf4MMf/jBjY2NMT09z6aWXsm3btsVe2hxyRLrC+b7Pli1bzqrT/2Quv/xyVFXlW9/61mk9/vj4OGvXruV3fud3znkgceedd/K2t71tRdT8HHbVVVfx9a9/nbe//e0S8Cwze/bs4ZprrpmXE1GHKz1838eyrHlYnRBioSzU5falUolWq0WSJLPBvxDL1dG1PX/1xS+SK1TodAMmpwMabZfWlIfrR4RRREpRMA2HN7z+V9m3bz9Gpsihdsx/PHaA1rRHkoCmQqXgsH1DgWrBoVq0sYy5x4RJkgwqe4LBNH8cx6RSCpapU8iZ1IpFChmTbFonlzZRU3JVjRBiabMsi16vt9jLEEKIFWX9+vWzU/9jY2O0Wq0l9flr5aSe4rgsy+JlL3sZ/X5/QSfrL730Ui666KLTCjGSJOFP/uRPuPPOO/mVX/mVczb577ou7Xabcrm8ogLyF77whdx000289a1vxTTNxV6OOA379+9neHh43n4HNm7cyGOPPcYll1wyL48nhJh/C9mxa1kWQRDMBv8LsY+AEGfqVDbdPdI9940RYmLkSihGlr/7+hjrN27GDyJQErSUim2qZB2NyemY8ZZLo9VjvO0S9HVgmnzGoFpw2DFapFZwyGcMUkf9TvSjwTS/64f0wwgUMDQNx1QZGclRyttk04PKHtuUj1BCiOXHcRxc113sZQghxIrw3ve+lwsvvJB3vOMdRFHEi1/8Yn74wx/iOA633347L3nJSxZ7iYAE/2KeKIpyRtPz119/PTfddBObNm1i165dC7CyY/3rv/4rV1xxxYqa9odB0JPP59m3bx9bt25d7OWIUxTH8bw/5rZt29i7dy8XXXTRijq5JcRK0u12sW17QQP5JEloNpvUajV5LRBLwvE23T0y/I8TmOr5dKYH0/z1do9WPERh4+VEEahqinKlhm1qKIpCY9Kl0ZpivNVjcjoAwNBSVIs2u0ZLVIsO1YKNoc29oi5OEly///Q0f5KgpVLYpka1YFMt2uQzJrm0QdYxjqn8EUKI5ejwxH+SJDIQIIQQZ+mrX/0qb33rWwH43//7f/Poo4+yZ88e/sf/+B/8wR/8AT/4wQ8WeYUDKyv5FMuObdvceOON3Hrrrfzpn/4p1Wp1wZ/zG9/4Bu9+97tXTL//kV72spdx55138lu/9Vsr8r9vJdq/fz9r1qyZ1/9fO3bs4F/+5V+IokjCPiGWqGazSbFYXNAP3oc7/rdv3y4f8MWSMDY2hud5AHiex933jqFaBaa6ARMdj3q7R8+LCMIQEgVdS1HI53jdNa/kkcd+Qcossntfl/oDDcIoQQEKWZOhUpoLt1SoFm1yjnHMz3sQRXjeoLYnCCMUFExDJW1prKtlKeVNcs4g6DcNOX4SQqxMjuNI8C+EEPOk0WgwPDwMwL/8y7/wpje9ie3bt/Obv/mb/Nmf/dkir+5pEvyLRTc8PMy73vUubr75Zv7sz/5sQWtqJicniaKIfD6/IgPR5zznOfzt3/4tYRhK8L9M7N69my1btszrwfemTZt44oknFuRqAiHE/Gg0GpRKpQX74K3rOq7r0mw2F/R5xOp2OrU9UZywcct5ZErrCRMNK1elHdf49k9/QRQnqKkUlqGRtjTwEhrtwYmAettlqtsHbCyjT7Vgc9HWCrWiQ7lgo6tzj+fi+Olpfi+YmeZXB3VAQ6X0YJo/bZDLGGRsA/nVEEKsFpZlSdWPEELMk6GhIR588EHWrFnDnXfeyec+9zkAer3eksrjJPgXS8LFF1/ML37xCz71qU9x4403LtgvyTe/+U1e8IIXLKlfwvmk6zpr1qzh5z//ORdccMFiL0ecgt27d/Oc5zxnXn8mNU0jiiKiKJq3xxRCzK/Dm+4uVCBfKpVoNBq0221yudyCPIdY3U5W29PzQjq9gM60T7Pj0mh5eEHIq3/9PTQaTUbWVCkW88RJwkTH42Cjy3jbpTHpEkegKFDKWaytZqhtG9TvZBwDhaOm+cNBXY/rh4RRjKIo2IaGY2lsWpOjkDPJOwbZjImhrbyhDyGEOFW2beO67oLuMySEEKvF29/+dt70pjexZs0aFEXhpS99KQA//vGPOe+88xZ5dU+T4F8sGa9+9av5zGc+w9e+9jWuvfbaBZnI//a3v80HPvCBFdfvf6Srr76aO+64g507d67YExwrycMPP7wgP+/lcpmDBw+yefPmeX1cIcT8WOhNd0ulEs1mkziOV+QVbmLxzant8fv8+KdjXHp5hva0z3irR7cX4vp94gS0lIJtaqRtjTjOEiY6T4z3uOuhx+m5IQCOpVItODxre41qwaFcsNCO+tmN4hgvCPH8EK8fwcw0v2WqrKtlqeQtcjPd/GlLl2l+IYQ4guM4dDqdxV6GEEKsCB/5yEe44IIL2LdvH2984xtn20tUVeXGG29c5NU9beWmn2LZURSF3/md3+Gmm25idHSUyy67bF4fv16vY1nWgm+muNguueQSvvSlLxEEAbZtL/ZyxEn0+30Mw5j3x922bRt79uxhdHR0Rf+8C7FcNRoNNm7cuGChfKlUYmJiQqb6xGk51eqerttneP12crUtRCkb0ynRiit8//4DKChYhopppEildCYmXQ60XOptl+akR5JAKgXlvMXocI5qyaZacEhb+pznSJIEvz/o5Xe9kCgeTPNbpkY2bbC56FCcCflzGQNNlRNcQghxIrZtc+jQITk2EEKIefKGN7zhmK+97W1vW4SVPDMJ/sWSous6f/AHf8Af/MEf8Ed/9EesW7du3h77zjvv5EUvetGKn4JXVZWtW7cyNjbGc57znMVejjiBVqtFLpdbkOBv+/bt3HfffVx99dUr+goXIZarZrN5Tib+ZQM/caqeqbqnH8Z0uj6T3YB2x6fedum6fdwg5JVvfBetiQnWrR2iVMjT6QbU2y7jrR6NlosbDCrnso5OpWCzeW2BWtGmmLVQU3N/LqM4xvVDPD/CDwfT/LquYhsaG4azVAo22bRBPm3iWPK+JoQQp8u2bTzPk+BfCCHO0J//+Z/zf//f/zeWZfHnf/7nJ/ze97znPedoVScmR81iySkWi7z3ve/lwx/+MJ/97GdJp9Pz8rjf+973+PCHP7wqQtCXv/zlfP3rX+dZz3rWqvjvXa727NnD5s2bFyz4/+pXvyob/AqxRE1MTFAsFhfs8cvlMg888ACZTEaCf3FKBtU9PindJlLTfPP7Y4xuS2hNebh+RBhFpBQF09CwZqb5Xc8mNkrc8/MOralxkgRUFaoFh20bClQLDpWCjW3OPRZJkgQ/CHGDCM8fTPOnUgqWqVPImdSKzuwGvLm0ecxJAiGEEKfvcMe/EEKIM/Onf/qnvOUtb8GyLP70T//0Gb9PURQJ/oU4ke3bt3PNNdfw8Y9/nI997GNnHV7v27ePUqmEYRirIgA577zz+K//9b8SBIEE/0vYgw8+yJYtWxYk+M9kMvR6PdngV4glKgxDdF0/+TeeoVKpxCOPPLJgrzFi6TuV2h6/H9GZDuj0fJTMBoqjVxKjYpg2nlrmqUYX21TJ2Bqdbsx4y6XR6jHedgn6gxPLuYxBrWCzY2ORatGmkDFJHXWs1Y/iQS9/EBH0Q1DA0DQcU2VkJEcxb5FLD2p7jj5JIIQQYn44jiOb+wohxFl47LHHjvvvS9kZH1m3Wi2+8Y1vcODAAQBGRkZ4+ctfvqDTa2J1ueqqq3jkkUf467/+a6677rqzCi7++Z//mV/6pV9aNSG4oihceOGF/OQnP+HFL37xqjjZsRzt3buXF73oRQsWylmWRafTkb0ehFiCFvpDd7lc5tFHH533/XLE8nC82p7hNSNM9Xw60wGT0wGNtsvktI97xMT9a193LY3GOKVSGT8xeXh/m3qrR3s6AEDXUtQKNrtGS1QLDtWChaHPPbaKkwTX7w+6+f2QOEnQUilsU6OSt6gWbfIz3fxZxyAl0/xCCHFOyMS/EELMj36/z3nnncftt9/Ozp07F3s5J3RGKegXv/hF/uRP/oRXvvKVsxNEP/7xj/noRz/KDTfcwDve8Y55XaRYnRRF4Td/8ze55ZZb+P73v88LX/jCMw6w77rrLq655poV3+9/pKuvvpqvfOUrvOAFL1g1JzyWm8nJSXK53IKdmNm6dSsPPfQQQ0NDC/L4Qoily7Zter0exWJRTv6uQmNjY/j9GM0uEBtpbv+3MdZuHFT2+EEIKOhaCttUSds67WmfQ40u9bZLvZUi3DeBAhSyJrVSmvO3VKgVbHLpY6+cDKIIzxtM8/fDCBQFU1dJWxrrallKeZOcMwj6TWP1HIcJIcRSIx3/QggxP3Rdx/O8xV7GKTmjNPCP//iPueeee47pXv/Yxz7Gs571LAn+xbxRVZUbb7yRG2+8kXXr1rF58+bTfoyf//znbNiwAU3TVlX4MTo6ylNPPYXrumSz2cVejjiK7/sL/jO5fft29u7dy5VXXrmqTnoJsdR1u11s217w96RisUixWJSqnxXgZLU9UZzQ6fpMdftMTvt01bWURq8gSlQ0XSdlVQj6CY6pkSQJjUlvtrJnqtsHwDJSVAsOF22tUC3alPM2hjb3vSOOE9ygj+dHeP2QOE7QVBXbVBkqpQfT/DPd/BnbYBUddgkhxJJnWdayCaqEEGKpe/e7381tt93GX/3VXy3pYdszWpmiKExNTR0T/E9NTa2qYFWcG5lMht///d/nIx/5CJ/97GfJ5/Ondf/bb7+dl7zkJUv6F3GhXHbZZXzve9/jV37lV+R3c4l5+OGHGR0dXdBAbseOHXzve98jjmMJ/oVYQprNJoVC4ZwE/+fiecTCOl5tT7FUY7IX0Jn2aXZcmm0P1w9nevcTDN3k2te/jiefPICdLtF2Ex762ZM0Jl3iwVA+pZzF2mqG2jabatEm4xgoHDXNHw7qelw/JIxiUoqCZWg4lsbGNTmKOZO8Y5DNmBianGASQoilTFVVoiiSiX8hhJgHd911F9/61rf4xje+wYUXXnhMRv61r31tkVY21xkloZ/61Kd48YtfzAUXXMDatWsB2L9/P//xH//Bf/kv/2VeFygEwIYNG3jrW9/K+9//fq644orTCjHuuecefv3Xf31VBv8ve9nLuPXWWzl48KBMfC4xDz74IM973vMW9P9LrVbj0Ucf5a//+q8l+BdiCXnqqafOSQVPuVyW4H8JOpVNd4903/1j9GMdI1sAPc1XvzHG+k1bcf3+nP78tK0RJ32abZ/xVpvxtkvP1YAOjqVSLTg8a3uNasGhXLDQjnr/ieIYLwgHm/D2I0gG0/yWqbKulqWSt8jNdPOnLV2m+YUQYpmS4F8IIc5eoVDg2muvXexlnJSSnOGrfhRF/OQnP+HJJ58EBpv7Puc5z1mS4dL+/ftZv349+/btY926dYu9nHNucnKSfr+PYRiLvZSzkiQJu3fvptPpnNb9qtUq69atwzTNBVrZ0nb//ffLJk5L1K5du8hmswsayu3Zs4d2u71gjy+EODNbtmyhVCot6HFTo9HAcRwcx1mw5xCn53jT+0eH/123z2Q3oNP1aU56PL5vnH/8X/9MHIOqqbzqFS+nUs4RxTAx6THe6lFvuzQnPZIEUiko5y1qBYdq0aZadEhb+pznSJKEIIwGG/B6g819FUXBMjUytk616FCcCflzGQNNleEBIYRYCa6//no++9nPYtv2Yi9FCCFOaLVnufPltEag9+3bx/r164HBZWJXXHHFgixKiONRFIVdu3YRx/Fp33c1T7tfdNFFMtWxRCmKsuCTuOedd94Z/c4IIRbWufj9r1QqC/r44vSNjY3N9it7nse9949hpotMdgMmp3zGWy5dt48bhCRJgqamyGSzXPvaV/PoY0+g2QUeOejy490TuEEEQMbRqRZsNq8tUCvaFLMWamruz1YUx7h+iOdH+OFgml/XVWxDY8NwlkrBJps2yKdNHGv1XSEphBCrRZIk8tlQCCHm0fj4OHv37gUGdcu1Wm2RVzTXaR3Zb9y4kVKpxMUXX8wll1wy+08QBPz5n/85X/7ylxdqnULMWs0h/pk4F+GSWNrkd0YIIRbG6dT2JAls2baLTHEt/UTDzpZpxUN88yf7CKOIlKJgGhqWkSKV0mm0XcZb0zTaLq0pjySxUFWPasFh24YC1YJDpWBjm9pRz5PgByFuEOH5g2n+VErBMnQKOZNa0ZndgDeXNo85SSCEEGLlSqVSEvwLIcQ86HQ6vPvd7+YrX/kKUTQYyFFVlV/7tV/jv/7X/3ra+5MulNMK/h977DHuvfde7rvvPu69917+7u/+brbqJ5fLLcgChRBCCCGEWGpOVtvj9yM60wGdns9Ex6fZdpl2+7zmLe+lXm+yZrhKNptFTSl0ujHjLZdGq8d4253ZpBdyGYNawWHHxiLVok0hY5I66mR+P4oHvfxBRNAPQQFD03BMleGRHOW8RS49qO05+iSBEEKI1UeCfyGEOHvvfOc7uffee7n99ttnG3F+9KMf8bu/+7u8613v4itf+coir3DgtCf+N27cyGtf+9rZr/3oRz/ibW97G7feeut8r00IIYQQQoglaW5tj89dd4/xbC3H5LRPo+XSnvZxj5i4N/VBGK+UCiSqyVMtlwce3Ud7OgBA11LUCjY7R0tUCzbVgo2pHzvN7/r9QTe/H87Z3Lect6gVbfIz3fxZxyAl0/xCCCGOoCjK7GSqEEKIM3f77bfz9a9/nRe84AWzX3v5y1/OF77wBV7xilcs4srmOuuxnyuuuII/+7M/4+abb+bNb37zfKxJCCGEEEKIc+5Uq3tcP2Ttxh1kq6OEmNiZMhNxle/csw9Q0LUUtqmScXRaUz6HGl3qbZdGy6UfJShAIWtSLTqcv6VMreCQSxvHVPMFUYTnzUzzhxGKomDqKmlLY10tSylvknMGQb9pLNxG0UIIIVYGy7Lo9XpLpoJCCCGWq3K5fNzX0nw+T7FYXIQVHd9pBf9BEGAYxjFf37ZtG//xH/8xb4sSQgghhBDiXHqm6p44Tuj0gkFtT9fn0ESPqV4f1+/zqjf9Fs3mBOtGalRKBbpen8akN1vZM9XtA2AZKSoFhwu2VKiVbMp5G0ObG9THcYIb9PH8CK8fEscJmqpimypDpTTVoj3bzZ+xDWT7HiGEEKfrcPAvhBDi7HzoQx/i+uuv53/8j//B8PAwAAcPHuT9738/N9988yKv7mmnFfxnMhl27drFpZdeyiWXXMKll17KyMgIn/3sZ3npS1+6UGsUQgghhBBiQR2u7lE0g0ix+dYPxti6E5ptD9cPZ3r3EwxdwzZV0rZO0HcwMgo/e2Ka5gN1oggUBUo5i7WVDLVtNtWiTcYxUDhqmj8c1PV4fkR/ZnNfy9BwLI2Na3IUcyY5xyCXMTE02aRdCCHE2XMcB9d1F3sZQgix7H3uc5/j4YcfZsOGDWzYsAGAX/ziF5imSb1e5y//8i9nv/eee+5ZrGWeXvD/7W9/m/vvv5/777+fv/mbv+Gmm26a7TZ9xStewYc//GEuvPBCLrzwQs4777wFWbAQQgghhBAncyq1PWGU0On6dLoBemEjxU3PJUZHNx16SpknnpzCNjXStkac9Gm2fcZbk9TbPbpuCIBtqlSLDpduq1EtOpQLFlpqblAfxTFeEA424e1HkAym+S1TZW0tQyVvkUsPQv60pcs0vxBCiAUhE/9CCDE/jtz/dik7reD/BS94wZxNC+I4Zu/evdx3333cd999/OQnP+ELX/gC4+PjsmGMEEIIIYRYFM9U29N1+0x2B5U9zUmPZtsd9Of3I5SUwjWv/TUmJsapVav0E5MnDnWot1yakx5JAqkUlPMWm4ZzVIs21aJD2tLnPHeSJPj9QS+/6w0291UUBcvUyKYNNhcdChmDfNoklzHQVJnmF0IIcW7Yto3ruiRJcsy+MkIIIU5NFEVcddVVXHTRRRQKhcVezgmd1ea+qVSKnTt3snPnTn7913999uuHDh0664UJIYQQQghxJsbGxvCDENXMEesOd3x3jHWb+nS9Pq4fkiQJmpoaTPNbOnEcU297g39aGg/sawCQtnVqRZvNawtUCzalnIWamhuURHE8W9njhxFJkmDoKrahsmE4SzlvkcuY5B0Dx9aPt1whhBDinLBtm16vJ8G/EEIAvu/z3Oc+l/vvv597772XSy655JTup6oqV199Nbt3717Zwf8zGRoaWoiHFUIIIYQQq9DJanuSBKbdgE538I9vrKU4eiVRksIwTGKjzLTbxzJSpBSdRtul3pqm0XaZmBpM86sqVAo2W9cVBtP8BRvbPM40fxDiBhGeHxJGMaqqYBk6hZxJreCQzww24M06JpoqoYoQQoil48iJfyGEWO1+//d/n5GREe6///7Tvu8FF1zAo48+yujo6AKsbP4sSPAvhBBCCCHEfDhebU+5OkRnOqDT82l1fBptl2m3j9+PgAQtZfD6172OQ4eeIpMr0wtUnthziPG2O7NJL+TSBtWizbaNRWpFm0LaJHXUNH8Yx7heOFMHFIIChqbhmCrDI7nBNH/aJJc2sE05rBZCCLG02bY9u0+jEEKsZnfccQff+MY3+Id/+AfuuOOO077/xz/+cW644QY+9rGP8exnP5t0Oj3nz3O53Hwt9azIJxQhhBBCCLFk3f/AGEGcQk9XwUjzj/9njHUbXVw/JIoTUikw9UEYrygKzUmXemuKeqtHe1oF2uiqQrVos3O0RLVgUyvYGPrcw+AkSfCCcFDbEwweW0sN6oDKeYta0SafGYT8Wcc45iSBEEIIsdQ5jkO73ZaJfyHEsjE1NUWn05m9bZompmme1WMeOnSId77znfzTP/0TjuOc0WO88pWvBOCaa66ZU512uEptqex9K8G/EEIIIYQ4Z05W2+MF0WCav+vTmvKYTIYpbnweUZJC01ScfJVUCjKOTnva56lmj3rLpdFy6UeDIKOYNakWHc7fUqZWcMiljWO6jIMowjs8zR9GKIqCqas4psa6WoZS3iLnmGTTBpahnpO/GyGEEGIhycS/EGK52bVr15zbt9xyCx/5yEfO+PGSJOG6667jP//n/8xll13G448/fkaP86//+q9nvIZzSYJ/IYQQQghxThxd2/OFv/oimXx5Nug/NOEy1Qvwjpjmt+w0b3j9a3j88X0Y6RL7m33uefgXTHX7AJh6imrR5oItFWolm3LextDmBvVxnOAGfTw/wuuHJDGoagrbVBkqpakWbfJpg2zaIOMYyDC/EEKIlUg6/oUQy82DDz7I2rVrZ28/07T/jTfeyG233XbCx9q9ezff+MY3mJqa4qabbjqrdb34xS8+q/ufKxL8CyGEEEKIM3Ky6f2j3X3vGJFiY+QrpMwsf/eNMdZv2DzozwcMXcMyVNK2xkTHp97sUW+7NNouUWSiKF1KOYu1lQy1bTaVgk02baBw1DR/GA0qe/yIMHp6mj9t62xck6WYs8g5g6Df1GWaXwghxOogwb8QYrnJZrOn1Jf/vve9j+uuu+6E37N582a+/e1v86Mf/eiYEwiXXXYZb3nLW/jyl798Suv67ne/e8I/f9GLXnRKj7PQJPgXQgghhBCn7Xib7h4Z/odRQqfr0+kGdKYDDrV6tOIa+Q2XE0YxmqpQrQ6RtlWSJKbR9hhvTVJv9+i6gxMBtqlSLTpcuq1GpehQLljoqdScdURxgh/0B0F/P4IkQVNVLFNlpJqmWrDJpQ1yGZO0paPINL8QQohVynEcXNdd7GUIIcS8q1arVKvVk37fn//5n/Pxj3989vaTTz7Jy1/+cv72b/+W5z73uaf8fC95yUuO+dqR1aLS8S+EEEIIIZatsbGx2Z5gz/P46T1jXGbkmer6NCY9JiZdXD8i6EcoqcHEfamY45pXv5xHHv0Fipnn/kc7NO8dJ0kglYJy3mLTcI5K0aZacMjY+pznTJKEoB/hBiGuFxLFMYqiYJka2bTB5oJNIWuSTw+6+XUtdbylCyGEEKuSZVl4nicT/0KIVWvDhg1zbmcyGQC2bNnCunXrTvlxWq3WnNv9fp97772Xm2++mU984hNnv9B5IsG/EEIIIYQATr26px/GrB89j2x5I3107GyVVlzjX+/eR5IkaKkUtqWRtnXiOKHedgf/tHq4fgQ4pG2oFQ02r81TLTiUchbqUeX6URzPVvb4YUSSJBi6im2obBjOUs5b5DImecfAOeokgRBCCCHmkol/IYSYH/l8/pivvexlL8MwDK6//nruvvvuRVjVsST4F0IIIYQQz1jdkyQw7QZMdQMmuwH1tkur4+H6Ea/89Xcz0Zhg7ZoalXKefpjQnHTZNzFNo+0yMeWRJKCqUC04bF1XoFK0qRVsbPPYaX4/CHGDCM8PCeMYNaVgGTqFrEmt6JDLGOQzBlnHRFOls0cIIYQ4Hbqu0+/3ZeJfCCFmbNq0aV5fE4eGhti7d++8Pd7ZkuBfCCGEEELMVvcoKZ0Qk3/94Rg7zldptF2m3T7+Uf35WVsjibP4fY2fH+jxg/9oEvRjAHJpg2rRZtuGArWiQyFjkjpqmj+MY1wvxAuiwea+Chiahm2qbBrJDab50ya5tIFtyiGrEEIIMR8U2exGCCHO2gMPPDDndpIkPPXUU/zRH/0Rl1xyyeIs6jjkU5QQQgghxAp0KrU9cQLTvYBON8AujVLYcBlJykQ3baaVMj/f18LUNRxTJaUoNCZd6q0p6q0e7ekAAF1VqBZtzttUola0qRZsTH3uIWaSJHhBOKjtCUKieFAHZJka5bxFrWiTzwxC/qxjHHOSQAghhBDzRyb+hRDi7FxyySUoinLM6+nznvc8/vt//++LtKpjLbvg/4/+6I+46aab+N3f/V0+85nPLPZyhBBCCCGWnGeq7fGCiM50QKfr05ryGJ/p3B9M88M1r/91Ws06a4aHiFImTzW71FsujZZLPxoc1BazJtWiw/mby1SLDvm0ccz0YD+Knp7mDyMUZbC5r2NqrKtlKOUG0/zZtIFlqIvxVySEEEKsWhL8CyHE2Xnsscfm3E6lUlSrVSzLWqQVHd+yCv7vuusu/vIv/5KLLrposZcihBBCCLFkjY2N4fkBqpEh1tJ8/btjbNwa0ekGeP5g4j6VAsvQcEwNBWY24O1Tbxk8sH8cAFNPUS3aXLClQq1oUy7YGNrcoD6OE9ygj+dHeP2QJAY1pWBbGkOlNNWCPejlTxtkHAMZ5hdCCCEWz/EmVIUQQpyaH/3oRzSbTV796lfPfu2v//qvueWWW+h2u7z2ta/ls5/9LKZpLuIqn7Zsgv/p6Wne8pa38IUvfIGPf/zji70cIYQQQohz5lRqe1wvZLIX0Jn2iZ31lEavJEpUdNMi0Ms0Jz0sQyVta0x0fOrNHvW2S6PtEkWgKFDKWoxUMly8bVDZk00bKMxN6oMwGlT2+BHhzB0tXSVt62xck6WYs8g5g6Df1GWaXwghhFhqJPgXQogzc+utt/KSl7xkNvgfGxvjHe94B9dddx07d+7kT/7kTxgZGeEjH/nI4i50xrIJ/t/97nfzqle9ipe+9KUnDf5938f3/dnbU1NTC708IYQQQogFcbzantrQGjpdn043oDMdcKjVY7rXx/P7REmCllJ57euupV4/SKFQxot1Hny0yXjbpev2AbBNlWrR4dJtNSpFh3LBQk+l5jx3FCf4QX8Q9PcjkiRBn9ncd6Q6mObPpWem+W0D2S9QCCGEWPriOF7sJQghxLJ033338bGPfWz29le+8hWe+9zn8oUvfAGA9evXc8stt0jwfzq+8pWvcM8993DXXXed0vd/8pOf5KMf/egCr0oIIYQQYuE98MAYQZigO2US3eH/9+0x1m10cf25/fmmkcJJ6Ux0PJ5qdRlv9Wh2UsT7WqRSUM5bbBrOUinaVAsOaVubM82fJAlBP8INQlwvJIxjUoqCZWpk0wabCzaF7GAD3lzaRNdSJ1i1EEIIIZYiwzDmDEoKIYQ4da1Wi6Ghodnb3/nOd/iVX/mV2duXX345+/btW4ylHdeSD/737dvH7/7u7/LNb37zlDdIuOmmm7j++utnbx84cIBdu3Yt1BKFEEIIIU7ZyWp7+mE8O83fnvKZSo1Q3HQlUZJC13WMdIU4gbStE3cTGm2X8bZLfWajXhj8Wa1gM7o2T7XgUMqZqMdM88e4fh8vGGzumyQJhqZimyrrh7NU8hbZtEkhbeDY+jn5uxFCCCHEwrIsi16vt9jLEEKIZWloaIjHHnuM9evXEwQB99xzz5zh86mpKXR96Xx2WvLB/9133834+DjPetazZr8WRRHf/e53+Yu/+At830dV5/bHmqY5ZxOFTqdzztYrhBBCCPFMjq7t+asvfpFcocJUN2CyG9Bou0x0PDw/oh8Npvktw+ba1/8q+/fvx0yXqHdiHnziABNTHkkCqgrVgsPWdQUqRZtawcY25x5sJkmCH4S4QYTnD6b51ZSCZegUMia1okMuYww24XVMNFU6e4QQQoiVyLZtCf6FEOIMvfKVr+TGG2/ktttu45/+6Z9wHIcXvvCFs3/+wAMPsGXLlkVc4VxLPvj/5V/+ZcbGxuZ87e1vfzvnnXceH/jAB44J/YUQQgghzpVT2XT3SPfeN0aIiZErohgZ/v7rY6zfuBmvH0GSoM3052dsjU43ZrzlUm/3qLdc/L4OTJFLG1SLNts2FKiVHAppk1RqblAfxjGuF+IFEUE/BMDQNWxTZdNIjlLOIp8xyTkGtrXkDweFEEIIMU8k+BdCiDP3sY99jNe//vW8+MUvJpPJ8OUvfxnDMGb//L//9//O1VdfvYgrnGvJf9LLZrNccMEFc76WTqcpl8vHfF0IIYQQ4lw53qa7R4b/cQLTvWB2A956q0crHqKw8XKiCFQ1RbFcwzZVFEWhOeky3pqi0XZpTQ26d3VVoVq02bGpRK1oUy3YmPrcw7ckSfCCcLABbxASxwym+U2Nct6iVrTJZ0yyaYOcYxxzkkAIIYQQq4dt27iuS5IkKIocEwghxOmoVCp897vfZXJykkwmc8xA+t///d+TyWQWaXXHWvLBvxBCCCHEUjQ2NobneQB4nsc9942hWUWmej4THY96y6Xnh/j9CBLQtRS5XJbXX/MqHnnsCRSryN79Xb4/1qAfJQAUsyaVgs2uzSVqBYdc2jjmQ3k/iman+fthDAqYuopjaqyrZSjlLHLpQdBvGXJlpBBCCCGeJsG/EEKcvXw+f9yvl0qlc7ySE1uWwf+//du/LfYShBBCCLHCnE5tTxwnbNq6k0xpPWGiYuWqtKIa3/7pL4jihFQKLEPDMTUUoN52B/+0XDrdALAx9YBq0eaCLRVqRZtywcbQ1GOexw36eH6E1w9JZqb5bUtjqOhQLTqDXv60QcYxkGF+IYQQQpzI4eBfCCHEyrcsg38hhBBCiPl0stoe1w/pdAMmpwfT/I22i+tHvPo3/h8a9QlG1lQpFPJAwsSUT6M5E/S3e0QRKAqUshYjlTQXb6tQKdiDaX7mJvVBGA0qe/yIcOaOlq6StnU2rslSzFnknEHQb+oyzS+EEEKI03PkxL8QQoiVTYJ/IYQQQqx6c2p7/D4//ukYl16eoTMdMN7qMdXr4/l9oiRBS6WwTI20rZEkeSIMflF3+elDT9B1+wDYpkq16HDpthqVokO5YKGnUnOeM4oT/KCPG0R4QUiSJOgzm/uOVNNUZ04OZNMGGdtArsYXQgghxNmybZtmsynBvxBCrAIS/AshhBBiRTrV6p6e22d4/XZytS2EiomVLtNOqnz//gMoioKpq1hGilRKZ6Lj8VSry3irR7PjEceDaf5K3mLjcJZq0aZacEjb2pxp/iRJCPoRbhDieiFhHJNSBhvwZh2dzSM5ClmTXNoglzbRtdQzrlcIIYQQ4kw5jsOBAwcWexlCCCHOAQn+hRBCCLHiPFN1Tz+M6XR9Ot2A9pRPve0y7fbx/JBXvuk/M9Fssn5kiFIxT6cb0Gi7jLdd6q0erh8BkLZ1agWb0bV5qgWHUs5EPWaaP8bzB9P8fj8iSRIMTcU2VdYPZ6nkLbJpk0LawLH1xfgrEkIIIcQqJFU/QgixekjwL4QQQogVZ1Dd45PSbaJUmv/z/TFGtydMdDw8P6IfRSiKgmVoWEYKVdHxfAvFLHHvwx0mpsZJElBVqBRstq4rUCna1Ao2tjk3qE+SBL8f4voRnj+Y5lcVBcvUyWdMhooOuYwx2ITXMdFU6ewRQgghxOKQzX2FEGL1kOBfCCGEEEveqdT2+P2IqW5ApxeQym6kuOkKYlQMy8FNlXmy3sUyVTK2RqcXMz4x2Hy33nLx+zEAubROteiwbUOBWtGhkDFJpeYG9WEc43ohXhAR9ENAwdAH0/ybRrKUcjb5jEnOMbAtOdQSQgghxNLhOI5M/AshxCohn0aFEEIIsaQdr7ZneM0I072AqW7A5HRAvd2jPe0/3Z+fUvjV172BZnOccrlCkBg8vL9No+3SmvIB0FWFStFmx6YitaJDtWBj6nMPjZIkwQtCXD/EC0LiGNTUoJu/nLeoFQchfzZtkHOMY04SCCGEEEIsJZZl4XneYi9DCCHEOSDBvxBCCCGWtLGxMfx+jGblic00t//bGOs2+vT8cE5/vmWoZByN9nTAoYke9Yke9VaK/r4mAIWMQbXosHO0RK3okE8bKMrcoL4fRbPT/P0wBgVMXcUxNdbVMpRyFlnHJJcxsAx1Mf46hBBCCCHOmEz8CyHE6iHBvxBCCCHOqZPV9sRxwlQvoNMNmJz26alrKY1eQZSoaLqOYlXw+xG2oaEoUG+51Nsd6i2XTjcAwNBT1Ao2F2ypUCvalAs2hqYe8zxu0MfzI/z+09P8tqUxVHSoznTz59IGGcdAhvmFEEIIsdyZponv+xL8CyHEKiDBvxBCCCHOmePV9hTLtdmQf6Lj0Wi7uH5EEIYAGJrJ61/3Og4+eQArW6LjwiP/cZB6u0cUgaJAKWuxppzm4m0VKgWbXNpAYW5SH4TRoLLHjwhn7mjpKmlbZ+OaLIWsSW5mmt/UZZpfCCGEECuPoijHXPEohBBiZZLgXwghhBBn7FQ23T3SffeP0Y91jGwBdIevfmOM9Zu24gV9ojhBS6WwTI20pZG4CY1Jl3prkvGWS9fVgA62oVItOVy6rUal6FAuWOip1JznieIEP+jjBhFeEJIkCbqqYpkqa6ppqgWbfNogmzbI2Aby+VcIIYQQq0WSJDLxL4QQq4AE/0IIIYQ4I8eb3j86/O+5fdrdgKmuT3PSo50MUdj4XOIEVE0lV6yhawpqSqfZ8Xiq1WW83aM56RHHg2n+ct5iw3CGWsGhWrRJ2/qcaf4kSQj6EW4Qzm7uqygKtqmRtXU2j+QG0/xpg1zaRNdSR/+nCCGEEEKsGjLxL4QQq4ME/0IIIYQ4I2NjY3ieB4Dnedx7/xhmukinG9CeDqi3eky7fTx/MHGvplKkM1ne8LpX88hjT6DbRR495PGTvRP0vAiAtK1RKziMrslTLdqUchbqMdP8MZ4/mOY/cnNf21RZP5ylkrfIpk3yaYO0rZ/zvxchhBBCiKVMJv6FEGJ1kOBfCCGEEMDp1fYkCWzZtotMcYR+omFnK7TiIf7PT/bN6c+3TJWUojMx6TLemqbedpnoeCSJhaq6VAo2m9fmqc5M8zumftTzJPj9ENeP8PzBNL+qKFimTj5jMnTEBry5tImmygSbEEIIIcSJKIoiwb8QQqwCEvwLIYQQ4qS1PX4/Yqob0OkFtDoe9ZZL1+3zmrf8HvV6kzXDVbLZLFpKodOLGZ9wqbddGu0eXhADkE3r1IoO29YXqBZsilmLVGpuUB/GMa4X4gURQT8EFAx9MM2/cSRLOWeTy5jkHQPbksMYIYQQQogzEcfxYi9BCCHEApNPzEIIIYQ4qrbH5667x7hMyzE5HVBvu7SnPVw/IowiUikFS9ewTZVqqYCimTw14TL22H7aUz4JoKsKlaLN9o1FakWHasHG1OcediRJghfMTPMHfeIY1JSCZWqUciZDpSK5tDmY6HeMY04SCCGEEEKI05dKpej3+4u9DCGEEAtMgn8hhBBihTrV6h4viFi7aQfZ6iZCLOxMmVZc49/u2U/CoD/fMlQytkp7OuLQRI/6RI96y6UfDS4TL2QMqkWHnaMlqkWHfNogddTGcf1oUNfj+hH9MAYFzJlp/nW1AsWsNRv0W4a6oH83QgghhBCrlW3b9Ho9SqXSYi9FCCHEApLgXwghhFiBnqm6J44TpnoBnW7A5LTPeMtlqhvg+iGv+rV302w0WTdSo1ws4PZDGm2PeqtDveXS6QYAGHqKWsHmgi0VqkWbSsHG0OYG9XGS4Pp9XD/C74ez0/y2qTFUdCgXbApZk1zaIOMYyDC/EEIIIcS5Yds2rusu9jKEEEIsMAn+hRBCiBXocHWPohqEis23fzDG1p0KjbaL60cEYQiAoWlYhkra1ghCBzOj8OAvutQfqDOzRy+lrMWacpqLtg6C/lzaQGFuUh+EEa4f4s3UAaEomLpKxtbZMJylmDPJp02yaQNTl2l+IYQQQojFcnjiXwghxMomwb8QQgixDJxKbU8YJUz1fDrTAUZhE8VNzyVGRzcdppUyjz/ZwTI1HEsjcRMakx711iTjMxv1AtiGSrXkcMm2GtWCTblgo6upOc8TxQl+0McNIrwgJEkSNHVQ2bOmmqZasMmnDbJpg4xtoMg0vxBCCCHEknE4+E+SBEUO1IQQYsWS4F8IIYRY4p6ptqfn9pnsBXSmfZqTHs1JFzeICPoRiqLwmte+iVazTq1WI8Rg36Epxts9mpMecTyY5i/nLTYMZ6gVBhvwph19zjR/kiQE/Qg3CHG9kDCOUZRBZU/G1tk8kput7MmlTXQtdYL/EiGEEEIIsdgOV/1I8C+EWI02bdrEE088Medrn/zkJ7nxxhsXaUULR4J/IYQQYokbGxvD8/uoZo5Yd7jju2OsH+0z7fbx/MHEvZpKYVsaGUunEyU0Jl3GWz6NtsYD++sApG2NasFh03CeasmmnLNQU0dP88d4/mCa3+9HJMnTm/uuH85SyVtk0yb5tEHa1hfjr0MIIYQQQpwF6fgXQqx2t956K+985ztnb2ez2UVczcKR4F8IIYQ4x05W25Mk0PX6dKZ9Ot0A31xLafT5RKTQDZNILzPVDTBNFTWl02y7jLemqbddJjoeSQIpFSp5m81r81QLNtWig2PqRz1Pgt8Pcf0Izx9M86uKgmXq5DMmQ0WHXMaYnebXVJkIE0IIIYRY7o6c+BdCiNUom80yPDy82MtYcBL8CyGEEOfQ8Wp7ytUhproBnV5Aq+NRn+nc92Ym7nXV4HWvfx3jh54ik6/g9lXufahOo93DC2IAsmmdWsFm6/oCtYJNMWuRSs0N6sM4xvVCvCAi6IeAgqGnsE2NTSNZSjmbXMYk7xjYlhwiCCGEEEKsRLZtMz09vdjLEEKIk5qamqLT6czeNk0T0zTP+nH/6I/+iI997GNs2LCB3/iN3+D3fu/30LSV9xl45f0XCSGEEEvYAw+MEcQp9HSVRE/zj98aY91GF9ePCKOIVErB0jVsUyWlKDQ6Lk9MTNFou7SnVJL9LTRVoVq02b6hSK3kUMnbWMbct/QkSfCCmWn+oE8cQyoFtqlTypnUikXyGXMw0e8Yx5wkEEIIIYQQK5Nt29TrdZn4F0Isebt27Zpz+5ZbbuEjH/nIWT3me97zHp71rGdRKpX44Q9/yE033cRTTz3Fpz/96bN63KVIgn8hhBDiLJystscLosE0f9dnouPTZpjixucRJSk0TcXOVVGArK3Smo44NNGjMeEy3nbph4Np/kLGoFp0OG+0RK3okE8bpI7aiK0fDep6XD+auV+CaQxOIKytFijlLHJpk2xaxzbl7V8IIYQQYrWSqh8hxHLx4IMPsnbt2tnbzzTtf+ONN3Lbbbed8LF2797Neeedx/XXXz/7tYsuugjDMHjXu97FJz/5yXm5mmApkU/+QgghxBk6urbnC3/1RbL5Mp1uwOS0z3jLZaob4M7056cUBdtK84bXv4YnntiH7pR4stnnvkf20ZkOADD0FLWCzfmby9SKNpWCjaGpc543ThJcv4/rR/j9kChO0FKDyp6hokO5YFPIDkL+rGMiw/xCCCGEEOIw2dxXCLFcZLNZcrncSb/vfe97H9ddd90Jv2fz5s3H/fpzn/tcwjDk8ccfZ8eOHWeyzCVLgn8hhBBixsmm9492971jhIqNkS+TMnP83TfGWL9hM0EYQgKGrmEZKmlbpzXlMd7uMd5yqbd7RJGJonQpZi2GS2ku2lKhWrTJpQ0U5ib1QRjh+iGeHxHGEaBg6ioZW2f9cJZSziTnmOTSBqahHn+xQgghhBBCAOl0Wib+hRArSrVapVqtntF977vvPlKpFLVabZ5Xtfgk+BdCCCE4/qa7R4b/UZzQ6fp0pgMmpwPG2z1acY3ChssJo3jQu18ZIm1pJG7C/7+9O4+Sq77vvP++S92t9u6uaqm1i8Ug9t2GnIydcIw9NgkYO7GHEEwcZjmCMcgz50BmDM4kMUNIfBivxBnHnnMmJI4fj/cneBwwEPvBGAtjGrN5wUbISL2oqqu76t5a7r3PH9V0aCGwEiRVd+nzOkfnqG7drvpWSb+q7k99+/ubmYuYrs0xXQ9ZaHUB8ByLStnn9OOqVEo+oyWfjGUuqyNOUtqdLmEnpt3pkaQptmXhuxZrx7JLHw4Usg4538FQN7+IiIiI/DN4nkcURYMuQ0TkiHvggQd48MEHecMb3kA+n+eBBx7g+uuv53d+53col8uDLu+QU/AvIiICTE5OLv0AFEUR33t4knPcIo2FNrNzEbNzIWEnptuNwTBwbYuRcpHffOub+MkzP8dwSzz6swazP5giScAwYLTosWE8R7UUUCn5ZIPMsm7+NE3pdGPCTq8/DihOMAwD37XJ+Rm2ThQo5l2KWYdC1iVjmy9XvoiIiIjIQQmCgCiK1PEvIkcd13X527/9Wz7wgQ/QbrfZsmUL119//bK5/8NEwb+IiAytgx3d04sTNmw9gfzoJrqpjV+oUEuqfPN7u0jTFMs08T2bnJehEafMzIVML47saUUxEBD4CdWSx5a1RcbKPiMFD9vcv5s/IWp3iToxUScmJcWxLTzHYsN4ntFifwPeYtYh62cO87MjIiIiIkcjz/M0419Ejkpnnnkm3/nOdwZdxhGj4F9ERIbSy43uSVNoRl0aC20azQ4zi938UTvmLe+6htmZWSbWVBkdLRLHKbP1kKn6AtO1kH2NiDQF04Kxos/WdUUqJZ9KKSDwlgf1aZrS7vbn8r+wua9lGHhuhkLO5ZiyTynnLo7tcbEtzewRERERkcPPsiySJFHHv4jIkFPwLyIiQ+mF0T2GadPD5d4HJnnNSTbTtRatqEfY6ZGmKRnLwnMt8kGGJM3R7ln8+PmQ7zwxS9RJAMhnM1RLPsduKFEp+YzkPUxzeVDfSxKido+wHdPp9gADJ2PiuzabJvKMFnwKOZdi4OB7evsVERERkcFS8C8iMtyUPIiIyKpwMGN70hTmWx3mmx2C0a2UNpxFarrYXkAjHeWpZ/fhZWw8x8TAZqYR8fN988zUQ+rzbVLob9Jb9jl+Y5lKuT+b33Ps/e4nJer0Q/6o0yVJwDTBdzOMFFyq5TLFnEsh55APHCxT3fwiIiIisnIYhr4/FREZdgr+RURkxXu5sT1RJ2a+2aHRarNvrs1MvUUz6tFenJ9/8WX/htrsNOvWjBObHnv3tZjZFzJVD+n2+t38pZxDpRxwwpYRqqWAYs7B3O8HoW7cn80ftuPFr0txHRvftVhXKTFS6M/mz2cz+K7eWkVERERkZUvTVB3/IiJDTumEiIiseJOTk0TtDpaTJbGyfP3+STYfG9Nodpbm55uGge/a/eDdgNl6xHSty1TdZfK5KQCcjEm15HPS1lGqZZ+xko9jW8vuK0lTwsWQP1ocB2SZ/ZE91XLAWMmnlO+H/PnARc38IiIiIrIaKfgXERluCv5FROSIO5ixPWG7R6PZodFskwYbGNl8PjEmGdenkxllZi7Ccyyyfob6fJs99SZTtZCZeoteDIYB5ZzHmpEspx4zRqXsU8g6GCxP6ju9/ua7UTuml8SAgZuxyHo2G9bkGSm4FIL+JryuYx2wVhERERGR1UbBv4jIcFPwLyIiR9SBxvaMr1lLo9mmsdBhbqHDVL3FfKtL1O6SJCmWaXHJpZcxPbOHUnmUKHZ4/JlZpushC60uAJ5jUSn7nHZclUrJZ7Tkk7HMZfedJClhp0vYiWl3eiRpim1Z+K7F2rEsYyWfYs6hkHXI+Q4afSoiIiIiw8g0TeI4HnQZIiJyGCn4FxGRI+rRRyfp9FIywQhpJsuX75lk3aaQsBPT7cYYhoFjW3iuheVl2NeI+EWtyVS9xeycSbKrhmHAaNFjQzVHtexTKQVkg8xLu/m7MWGn1x8HFCcYhoHv2OT8DFvWFigVXIpZh0LWJWObL1OxiIiIiMhwcV2XMAwpFouDLkVERA4TBf8iIvKq/LKxPb046XfyN9vUFzrMmxOUF8f22LZNJjtGkkDOy9CIU2bmQqZrIdP1Fq2o34UU+DaVks/mNUUqZZ+RoodtLg/q46S/AW/UiYkWN/fNLHbzr6/mGSv1N+AtZh2yfuaIPDciIiIiIiuR7/u0Wq1BlyEiIoeRgn8REfkX239sz//81Kcolis0Fto0mh1m5iJm58L+/Py4P3jfy3hc9rbf4LnnduPlRpieT3j82d3sa0SkKZgWjBV9tk70Q/5KKSDwlgf1aZrS7vbn8vc3900xDfDdDPmswzEbAkpZl8Li2B7bUje/iIiIiMgLFPyLiAw/Bf8iIrLkYDbdfbHvPzJJDxenUMZwcnzu65Ns3HwMYadHmqbYlonv2uSDDHPNpN/JXwuZrodEnQwwTz6boVLyOXZ9qd/Nn/cwzeUje3pJQtTuEbZjOt0eKeBmLHzXZtNEntGCTyHnUggcAk9vbSIiIiIir0TBv4jI8FM6IiIiwIE33X1x+J+mMN/qMN/sMNfsMF0LqaXjFDedQxKDZZmUR6u4GRMDm5lGxHRtgelai/p8mxSwLYNK2ef4jSUq5YBKycdzlr8VpWlK1OmH/FGnR5wkWKaB52YYKbhUymVKOZd8NkMh62KZ2oFXREREROSfw/d9oigiTVMMQ99Pi4gMIwX/IiICwOTkJFEUARBFEQ8/MknGL9Notdk312am3qIZ9Wgvzs93bItCPs/bf/Mt/PinP8f0yjy9u8W3H5ul00sAKOYcquWAE7aMUC0FFHMO5n4/WHTj/mz+sB3T7SVgpDi2TeBZrBsrMFL0yWf7I3t8V29bIiIiIiKv1gsd/wr+RUSGlxIUEZEhdrCje5IkZfOxJ5IbWU8vtfEKY9SSKnc/9Cy9JME0DHzX7gfvBszWI35Wm2e63mJuoQP4OHaHStln29ZRqmWfsZKPY1vL7ydNCRc34A3b/XFAltkfB/TCPP9izqGQc8j7zktG/oiIiIiIyKvneR5hGJKm6aBLERGRw0TBv4jIkHql0T1hu0ej2aHRbFObi5iuh7TaMW/9N+9lZnqWibUVSsUiAPX5NnvqTaZqITP1Fr0YDKCc9xgfyXLKMWNUyj6FrIPB8qC+04uXZvN34xgDA9exyHo268fzjBRcCoFLIevgOtb+D0FERERERA6DIAgIw3DQZYiIyGG04oP/W265hf/zf/4PTz75JL7vc/7553Prrbfymte8ZtCliYisaEujewyTbmJz33cmOelUh6lai/lWl6jdJUlSzMWO+6xnQ6lAjMOumRY7f/RzFlpdADzHolL2Oe24KpWSz2jJJ2OZy+4vSVLCTpewE9Pu9EjSFNuy8F2LtWNZxkp+v5s/65DzHfQbxSIiIiIig+H7PnNzc+r4FxEZYis++L/vvvvYvn0755xzDr1ejz/4gz/gjW98I48//jjZbHbQ5YmIHDEHO7anFfWYa7bJV46huP40UjMg42ZpJKNM/ngaN2PjuRaWl2HffMT0TJOpWovZuYgkAcOA0aLHhmpucWRPQC7IHLCbP2z3CNs9enGCYRj4jk3Oz7BlbYFSwaUYOORzLo5tvky1IiIiIiJypPm+r45/EZEht+KD/7vuumvZ5c985jNUq1V27tzJr/7qrw6oKhGRI+vlxvb04oTGQodGs0Ntoc10rcVC2CVq9zvuL37bFdT2zbB+Yg1YHrNzIVO1OtP1Fq0oBiDwbKpln81rilTKPiNFD9tcHtTHSX8D3qgTEy1u7ptZ7OZfX80zVvIoZF2KWYesnxnEUyQiIiIiIgfpheBfHf8iIsNrxQf/+5ubmwNgZGTkZc9pt9u02+2ly/Pz84e9LhGRw6k/tqeNmfGIzSz/8K1Jtr4GZudCohfm5xsGXsbCdS0sM8NsPWR6PmF6weeH39tLmoJpwljRY+tEkbGyT7UUEHjLg/o0TWl3e0Ttfkd/L0kxDfDdDPmswzEbAkpZl8Li2B7bUje/iIiIiMhqEgRBfyyoiIgMrVUV/CdJwnXXXccFF1zAySef/LLn3XLLLfzhH/7hEaxMROSf52DG9nR6CfMLbeZaHazCJsqbX0eCRcbzCa1Rnpuax3dt8kGGRjNlqtZiuhYyXQ+JOv1u/nyQoVL2OXZ9qd/Nn/cwzeUje3pJsrQBb6fbIwXcjIXn2GyayDNa8CnkXAqBQ+CtqrcNERERERE5AHX8i4gMv1WV4Gzfvp3HHnuMb33rW6943o033siOHTuWLu/evZtt27Yd7vJERA7Kgcb2rF07wULYobHQYa7ZYboWUl+ICNsxvTjGNAx+89K3Mzs7xejoGN3U5ae7G0zXWtTn26SAbUGlHHD8xhKVckCl5OM5y1/m0zQl6vSIOv1u/jhJsEwDz81QLrhUy2WKWWexm9/FMrUDr4iIiIjIsPF9nyiKFPyLiAyxVRP8X3PNNXz1q1/l/vvvZ/369a94ruu6uK67dLnRaBzu8kREDtrk5CTtboztFUmcLF+7d5L1m9s0ox7txfn5jm3hORb5wKa+kPxTN3/NorNrFoBizqFaDjhhywjVUkAx52Aay4P6bvxCN3+Pbi8GAxzbJvAsJkYLjBR98tn+yB7fXTVvCSIiIiIi8ipoc18RkeG34lOeNE259tpr+cIXvsC9997Lli1bBl2SiMgyv2xsT5KkzLf6G/DOLXQI7XWUN59PklrYjgPeGFEnxndtDMNgZi7kZ/vmma63mFvoAODYJpWyz7ato1TKPpWSj2Nby+8nTQkXN+AN2z3SNMUyTXzXXvya/ocDhZxD3ndeMvJHRERERESODplMhm63q45/EZEhtuKD/+3bt3PnnXfypS99iXw+z549ewAoFov4vj/g6kTkaHegsT3l0SqNZof5Zod9cyHTcyGtKKbT60EKGdvhsrddyp7nd+PlR5mP4Cc/3MNMvcViUz7lvMf4SJZTjhmjUvYpZB0Mlgf1nTgmivqz+btxjIGB61hkPZv143lGCi6FwKWQdXAd68APQEREREREjjqGYWAYagQSERlmKz74/8QnPgHA61//+mXHP/3pT/Pud7/7yBckIkPtYDbdfbEf/GCSbmLj5MbBCfj8NyZZv/lYonaXJEkxFzvus54NUcpMPWK6Psd0LWS+ZQNzeI5Fpexz2nFVKiWf0ZJPxjKX3U+SpISdLmEnpt3pkaQptmXhuxZrx7KMlfx+N3/WIec76Ht4ERERERF5JUmSqONfRGSIrfjgX29CInKkHKh7f//wvxX1aLQ6NBbazDZCauk4pU2vJUnBsk1ypQoZy8DyMuybj5iZaTJVazEzF5EkYBgwWvRYX81RKflUygG5IPPSbv5ef1xP2O7RixMMw8B3+h8gbFlboFRwKQYO+ZyLYy//kEBERERERORgKHMRERleKz74FxE5UiYnJ4miCIAoinjkB5N4uREaCx3qzTZTtRYLrS5Ru0eSgm0aZLN53n7pW/npMz8nE4zws6k2Dz31M1pRD4DAs6mWfc5aU6RS9hkpetjm8qA+ThKixdn8UTcmTVMyloXnWqyv5hkreRSyLsWsQ9bPHPHnRUREREREho9hGAr+RUSGmIJ/ERla/9yxPccev41ceYJuYuMXxtiXjPONB5/tz883DLyMhetaWGaGfXMhu2shU/WQfXMRaephWi3Gij5bJwqMlX2qpYDAWx7Up2lKu9sjavc7+ntJimmA59rksw7HjASUsi6FxbE9tqVufhEREREROfQU/IuIDDcF/yIylH7Z2J5OL2F+oc1cq0O90Wa63qIZ9rj48uuZnpllzfgY+XyejGXSaKZM10Om9rWYrodEnRiAfDZDpeRz7LpSv5s/72Gay0f29JKEqN0P+tvd/m8BZDIWvmOzcW2esaJPIedSCBwCTy/JIiIiIiJy5CRJMugSRETkMFHKJCJDafnYnjYP7Zzk7EyBuYUOM/WQ2nxE2I7pxTGmYeA6Np5jUh0rY9oee2shP3xmN7WFiDQF24JKOeD4jSUq5YBKycdzlr+EpmlK1OkRdfrd/EmSYJoGnpuhVHCplsuUci75bIZC1sUytQOviIiIiIgMRiaTodPpDLoMERE5TBT8i8iqcbCje9qdmHWbX0N+bDM9XLz8GLW0yr07nyOlPz/fdy3ygc3cQsJULWS61u/m73T7HS/FnEO1HPCaLWWqpYBizsE0lgf13bjfzR+2e3R7MRjg2DaBZzExWmCk6JPP9kf2+K5ebkVEREREZOXwfZ9WqzXoMkRE5DBREiUiq8LLje5JUphvtWksdJhb6DBdb9FY6BC2e7zlt7czOzvL+okqoyMlok7MzFzITG2eqVqLuYV+d4tjm1TKPtu2jFIp+1RKPo5tLbv/JE0JFzfgDds9kjTFNk181176mmLOpZB1yAfOS0b+iIiIiIiIrCS+79NsNgddhoiIHCYK/kVkVXhhdI9hOfQMj3v+v0mOP8Fgei6kFcV0ej1IIWNb+K5Nzs/QjbM0OwZP7Goy/egMvTjFAEp5l/GRLKccM0al7FMIHIz9uvk7cUwU9cf2dHoxBgauY5H1bNaP5xkpuBSCftDvOtaBixYREREREVmhPM9Tx7+IyBBT8C8iA3EwY3viJKXRbDPf7OKUN1PadC6pkSHjBjSNUX7yiwa+a5P1bIhSZuoR0/U5push880uAJ5jUSn5nHrsGNVywGjJJ2OZy+4nSf6pmz/qLHbzL44DWjOaZazkU8w6FHIOOd/BUDO/iIiIiIiscr7vE0URaZq+pBFKRGSYfe1rX+O//bf/xqOPPornefyrf/Wv+OIXvzjosg45Bf8icsS93NieVtSj0erQWGgz2wiZqUVEnR7tbowB/Malv01tdprx8SpdHHZPzTNVD5mZC0liMAwYKXisr+SoHOdTKfvkAgeD/br5e/1xPWG7Ry9OMAwD37EJPJvNawuUCi7FwCGfc3Fs88APQkREREREZBV7Yca/gn8ROZp8/vOf5+qrr+aDH/wgv/Zrv0av1+Oxxx4bdFmHhYJ/ETniJicnidpdLCdPksly1/2TrN/apdnqEba7JCnYpoHv9sP4JHmhm7/NVD3Do89NAxB4FpVywFnHVxkrBYyWPGxzeVAfJwlRp0fU7hF1Y0jBtkw812J9Nc9Y0aOQcylmHbJ+ZhBPh4iIiIiIyBH3Qse/iMjRotfr8d73vpfbbruN97znPUvHt23bNsCqDh8F/yLyqh3M2J5m2GWu2aHRbNP11jOy5QJiTDKOSy8zyvxCB9cxMc0M++ZCdtdCpuoh++Yi0hRME0aLHlvWFhY30w3IesuD+jRNaXd7RO1+R3+c9mf6e65NPuuwtRxQzrkUcg6FrINtqZtfRERERESOTkEQEIYhaZoOuhQRkQOan5+n0WgsXXZdF9d1/8W39/DDD7N7925M0+SMM85gz549nH766dx2222cfPLJh6LkFUXBv4i8Kgca2zNWXcP8Qpu5Vod6o810PaQZdgk7PSDFMm0ufdulTE3tIV8cJerZPPL0NNP1kKgTA5APMlTKPsesK1Et+5TzHpa5/NdPe0nS7+Rv9zfgTdOUTMbCd2w2rskzVvIp5FwKgUPg6eVORERERETkBZ7nUa/XFfyLyIq1fyf+zTffzAc+8IF/8e399Kc/BeADH/gAH/rQh9i8eTN//ud/zutf/3qefvppRkZGXk25K46SMBF5VR59dJJObJLJjpFmsnzx7knWbQoJ2zG9OMY0DFzHxlvs5p+ph0zVFpiphdQWTNJdNWwLxkoBx28sUSkFjJV8fHf5y1Oapv2RPZ2YqN0jThJM08BzM5QKLtVyQCnnks9mKGTdl3xIICIiIiIiIv8kCAKef/75QZchIvKyHn/8cdatW7d0+eW6/W+44QZuvfXWV7ytJ554giRJAPgv/+W/cNlllwHw6U9/mvXr1/O5z32Of/fv/t0hqnxlUPAvIsv8srE97U5Mo9mh0Wqzr9GmzhrKm19LnBpkbBsvX8EA8oHN3ELCVC1kutZiuh7S6fZfYIs5h0op4DWby1TLAcWcg7nfZlLdeLGbvxPT6fbAAMe2CVyLiYkCI0WffLY/smf/DwlERERERETklb14c18RkZUon89TKBR+6Xnve9/7ePe73/2K52zdunXpw84X/yaB67ps3bqVZ5999lXVuhIpLRORJfuP7fmf//NT5EqjNBY6zC10mK63aCx0+vPzX+i497K8/W2/wbM/f5ZMdoTnaz1+8NNdzC10AMjYJtWyz7YtI1RKAZWyj2Nby+43SVPCdpeo05/Nn6QptmniuzZjJY9Kqf/hQCHrkA8cTHXzi4iIiIiIvCpBEGhzXxEZCpVKhUql8kvPO+uss3Bdl6eeeopf+ZVfAaDb7fKzn/2MTZs2He4yjzgF/yJD7GA23X2xnd+fpGd4OMVRTLfAZ//vJBs2bqXT60FqkLH7YXzOz1BbaLN3psl0PWS6FtKLXQyalPIu4yNZTj5mjGrZpxA4GPt183fimCha7ObvxRgYuI5F1rNZX80zUnQpBC6FrIPrWC9TrYiIiIiIiPxL+b6vzX1F5KhSKBT49//+33PzzTezYcMGNm3axG233QbAO97xjgFXd+gp+BcZUgfadPfF4X+cpDSabeabXeoLbaZrLWpJldLGc+jFKbZlUBkbJ+vZEKXM1COm6/2RPfPNLgCeY1Ep+Zx67BjVcsBoySdjmcvqSJKUsNMlasdEncVufsvCdy3GR7JUyj7FrEMh55DzHQw184uIiIiIiBx2vu+r419Ejjq33XYbtm1zxRVXEIYh5513Hvfccw/lcnnQpR1yCv5FhtTk5OTSN3FRFPG9709yrleisdBmthEyU4uIOj3a3RgDcDM2I+Uil1z8Zn78059juiUmfz7PzKNTJDEYBowUPNZVclSP86mUfXKBg8F+3fy9/riesN2jFycYhoHv2ASezea1BUoFl2LgkM+5OLZ5gMpFRERERETkcFPHv4gcjTKZDH/2Z3/Gn/3Znw26lMNOwb/IKnKwo3t6ccrGrSeQG91IL83gFyrUkir3PPQsSQq2aeC7/TA+SV7o5q8zVQ9phT0gIPBiKmWXs46vMlYKGC152ObyoD5OEqJOr78JbzeGxW5+z7VYX80zVvQo5Poje7JeRt38IiIiIiIiK4TrukRRpOBfRGRIKfgXWSVeaXRPM+wy1+zQaLaZqUfsmwsJ2zFvfee1zMzOsm5NldFygTiBfXMhu2sh0/WQ2bmINAXThNGix5a1BSpln0opIOtllt1/mqa0uz2idry0ua9hGHiuTT7rsLUcUF4M+Qs5B9tSN7+IiIiIiMhKZZr6mU1EZJgp+BdZJV4Y3WOYNr3U5d4HJjnhJJvpekgz7BJ2eqRpim31N+DNBxnSNE8nsfnJnhYPPrGPsBMDkAsyVMs+W9eVqJZ9ynkPy1zejt9Lkn4nfzum3et382cyFr5js3FNnrGSTz7rUMy6BJ5eSkRERERERFYjdfyLiAwnpXUiA3IwY3vSFBbCDo1mh2B0K6UNZ5KYHhk3YJ4Rnvz5PlzHxnNMTDPDTD1kqrbATC2kttDv5rcsqJQCjttYolIKGCv5+K693/2k/ZE9nZhosZvfNA08N0Op4FItB0sb8Bay7ks+JBAREREREZHVx9A8VhGRoaXgX2QAXm5sT7sT02h2aLTa7Gu0mam1aEb9DXgh5eK3XU5tdpqJteOklsdULWSm1mKqHtLpJgAUcg7VUsBrNpeplH1KORdzv2/muvFiN38nptPtgQGObRO4FhMTBcpFj0K2P7Zn/w8JREREREREZDikaaqOfxGRIaVET2QA+mN72lhOlsTK8vV/nGTzsTGNhc7S/HzTNHAzNr5rYRgGM3MhM7Ue03Muk7unAMjYJtWSz7YtI1RKAZWSh5NZvqyTNCVsd4k6/dn8SZpim/1xQGNFj0rZp7g4mz8fOJjq5hcRERERETkqGIah4F9EZEgp+Bc5BA5mbE/Y7tFodphvdiC7gZEt5xNjkXF9OtYo07UQ37XI+hnqC232zjSZrodM10J6cYoBlPIu1ZEsJx0zRrXkU8g6L/nVzE4cE0WL3fy9GAMD17HIejbrq3lGii6FoB/0u451BJ4dERERERERWamSJBl0CSIichgo+Bd5lQ40tmd8zVoazTbzzS5zC22mai3mW13Cdpc4SbFMk9+89DJmZ/ZSKo8SJQ5P/XwfU/WQ+WYXAM8xqZQCTj12jErZZ7To49jLg/okSQk7XaJ2TNRZ7Oa3LHzXYnwk2+/mzzrkF7v5Nb5RREREREREXmCaJt1ud9BliIjIYaDgX+RVevTRSTq9lIxfJnGyfOWbk6zbFBG2+7P5DcBZHNmT9TPUGhF7ZsP+fP45k2RXDcOAkYLHukqO6nE+lbJPLnAw2K+bv9cf1xO2e/TiBMMw8B2bwLPZtLZAueBSCBwKORfHNgfzhIiIiIiIiMiq4Ps+YRgOugwRETkMFPyL7OeXje3pxSmNZptGs8PcQpumNUF58/nEqYmdyWAFY8RxSta3SdKU2XrEVK3OVD2kFfYACDyLSingzOOrVEoBoyUP21we1MdJQtTp9Tfh7caw2M3vuRbrq3nGih6FbD/kz3oZdfOLiIiIiIjIP4vnebRarUGXISIih4GCf5EXOdDYnmK5wlyzQ6PZZqYesW8uJGzHdOMYwzDwMh6XXfob7P7FbrzcKLPzCU/u2s3sXESagmnCaNFjy5oClbJPpRyQ9TLL7jdNU9rdHlE7Xtrc1zAMPNcmn3XYWg4o5RyKWZd81iGjbn4RERERERF5lXzfV/AvIjKkFPzLUDuYTXdf7Ps/mKSbOjj5Eoab53P/d5INm44h7PRI0xTbMvFdm5yfYb6VMF2PmKq1mKmFhJ0M0CAXZKiUfLauK1Ep+YwUPCxzeTt+nCSE7X7Q3+71u/kzGQvfsdi4Js9o0aOQcykGDoGfOXCxIiIiIiIiIq/CC6N+0jTF0K+Ri4gMFQX/MrQO1L3/4vA/TWEh7CyO7OkwUw+pJeOUNp1LnIBtmZRGqriOiWlmmKmHTNUW+ufN97v5LQsqpYDjNpYYK/lUSj6+e4Bu/k6PsBMTLXbzm6aB52QoFVyqpYBizqGQc8gHLralb7ZERERERETk8FPwLyIyvBT8y9CanJwkiiIAoiji+49MkvHLNFpt9jXazNRbNMP+BryQYpsW+Xyey37zLfz0Zz/H9Mr8aHeLb/9wlk43AaCQc6iWfI7fVKZa9illXcz9uvm7cdKfy9+J6XR7YIBj2wSuxZqJQr+bP+tSyDr4rpagiIiIiIiIDIY29xURGV5KHWVVOdjRPUkKW449kdzIenqpjZcfY18yzt0PPbvUce9m+mG8YRjMzIXM1OaZrrWoL3QAn4zdoVryOXHLCJWST7Xk42SWL5k0TQnbXaJOfzZ/kqbYZn8c0FjRo1L2Keb6IX8+cF7yIYGIiIiIiIjIoARBsNTxLyIiw0XBv6warzS6J2z3aDQ7zDc77GtETNdbhO2Yt/6b9zIzM8vEmgqlYh4wqC+02TvTZLoeMlML6cYpBlDKu1TKAScdM0q1FFDIOi/5VcdOHBNF/W7+bi8Gw8DNWASezfpqnpGCS2FxA17PsY78kyQiIiIiIiJykDzP0+a+IiJDSsG/rBpLo3sMk25ic/93JjnpVIepWov5Vpew3SVJwDTBczIErk1aKpAYDs/NtHj4x88y3+wC4DkmY6WAk48ZozriM1r0cezlQX2SpISdLlE7Jur2SJIU27LwXYvxkSyVkk8x55DPOuQCBzXzi4iIiIiIyGoSBAGzs7Pq+BcRGUIK/mVgDnZsTxj1mGt1yFeOobjuNFLLJ+NmmUtHefTH0zgZG8+xyPoZao2I6dmQqVrIzFxI0m/KZ6TgsW4sR/U4n0rZJxc4GOzXzd/rj+uJ2jHdOMZc7ObP+hk2rc1TLngUgn7Q72bUzS8iIiIiIiKrm+d5mvEvIjKkFPzLQLzc2J5enNJotmk0O8wttJmqhSy0ukTtLnGa8tbLrqC+b4b169Zg2B6z9Yip2hxT9RatsAeA71pUygFnHlelUg4YLXnYprns/uMkIer0+pvwdmNI+938nmsxUel38xeyDoWcS9bLYKibX0RERERERIaMZvyLiAwvBf8yEC+M7TEzHrGZ5R++Pckxr4HZekjUiel0Ywyz33HvOSammWHfXMTsQsJ00+eHD+0lTftjfUaLHlvWFKiUfSrlgKyXWXZfaZrS7vbn8odRjzhJMAwDz7XJZx22lgNKOYfi4mz+jG2+TNUiIiIiIiIiw0PBv4jI8FLwL4fEwYzt6faSpW5+q7CJ8ubXkWCR8QJCY4Rde+bxPZusnyFJEqbrEdP1kOlaf6NegKyfoVr22bquRKXkM1LwsPYbrh8nydLInnYvJk1TnIyF71hsXJNntOhRyLkUA4fAzxyoVBEREREREZGh53lefy89EREZOgr+5VU70NietWsnWAg7zDc7zDU7zNRD9jWipfn5hmHwm5e+g9nZKcbGKnRTh2d+0eifNx+RpmBZUCkFHLehxFjJp1Ly8d0DdPN3eoSdmKjdoxcnWJaB52QoFVyqpYBizqGQc8gHLralmT0iIiIiIiIioI5/EZFhpuBfXrXJyUnanR62VyRxAv7f+yZZv7lDM+y+ZH5+zrdpNBOmaiHT9RbTNYtHd80AUMg6VMs+x20qUy37lLIu5n7d/L0kIYx6i+OAemCAY9v4rsXmiUK/mz/rUsg6+K7+e4uIiIiIiIi8HHX8i4gMLyWj8hIHM7ZnIezSWGgz1+zQdtZR3nI+SWqRcVwSZ5RW1MN3LQzDYHYuZKo2z0w9pDbfBiBjGVTKPidsGaGy2M3vZpb/d0zTlLDd7c/mb/dI0hTbNPFdm9GiR7XsU8z1Q/584LzkQwIREREREREReXm2bRPHsTr+RUSGkIJ/WeZAY3uq42sXQ/429fk2U7Ww383f6ZGmKbblcNnb3saePbsJ8mMsdEx+9sQepmsh3bj/zUM57zJW8tm2dYRqKaCQdTCM5UF9J46JXujm7/XHAbkZi8C1WV/NMVLod/Pnsw6eYw3i6REREREREREZOgr+RUSGj4J/WeaFsT0Zv0zq5PjSPZOs2xgStmN6cQyGgefY+I4J2EzPhUzvm2eq3qKxYAN13IxJpexz8jFjVMs+oyUfx14e1CdJStjpErVjom6PJOmPA/Jdi/GRLJWSTzHnkM865AIHNfOLiIiIiIiIHHr7N+WJiMhwUPAvADTDLjP1ELIbKG8+n8SwsTMZnOwYKSzN5t9bC5mutZiqhXR7CQZQznusHcly6jFjVMp+v5uf/br5e/1xPS/e3NfLWGT9DJvW5ikXPApBP+h3M+rmFxERERERETkS0jRVx7+IyBBS8D/kdu3axQMPPMCJJ57Ipk2blo6nKdQXImbrEb+YaTIzFxK2uxiGxSWXXsKe53+Blx1hai7hhz/bTW0+IgUytkm17HPy1tGX7eaPk5R2p9sP+rv9WYGZxc19Jyr9bv5CdrGb33dQc4GIiIiIiIjIYBiGoeBfRGQIKfgfYrt27eLSSy8lTVOy2Swf/8Rf4GbLTNdCfjGzwNxCm3Y3xrZMAteGFJ7d22DX3gWaYQaYp5BzqJYCXrOlzHg5oHig2fyL3fxh1KOXJBiGge/a5AOHrWWfUr6/AW8h65KxzcE8GSIiIiIiIiJyQAr+RUSGz6oJ/j/2sY9x2223sWfPHk477TQ+8pGPcO655w66rBVt586dhGFIrrwGIzvO//MPjzGxbjNxkuA5Nk7GotHs8OO9dXZPLdCNUwLPZkM1z/pqjuqIj5tZ/l8kSVLCdpewEy9t7ptZnM2/YU2esaJHPutSyjoEfmZAj1xEREREREREDlYcx4MuQUREDrFVEfx/9rOfZceOHdxxxx2cd9553H777Vx00UU89dRTVKvVQZe3Yp111ln4vo9X2ki2vJ5KZRzHsfjFdMize2eYroWkKYwWPU46ZoyN43nKBXfZfP5uHBNGvWWb+/qOTc7PsHWiQCnvUsy6FHIOtqVufhEREREREZHVxHVdwjCkWCwOuhQRETmEVkXw/6EPfYirr76aq666CoA77riDr33ta/zVX/0VN9xww4CrW7k2bNjA5z//eT7+N/cTJgEPPVWj0ZzCNGFiLMtrT1nLhkqOwPunzvxektAMOzTDLkmaYpsmvmezdixLpexTzDoUci45dfOLiIiIiIiIrHq+7xOG4aDLEBGRQ2zFB/+dToedO3dy4403Lh0zTZMLL7yQBx544IBf0263abfbS5fn5+cPe50r1WO7Yp6e8fDthA1rs5x9Yo61lRwZ85+68zvdmIWwvxmvaULgZTh2XZHRsr/Yze/iaDa/iIiIiIiIyNDxfZ9WqzXoMkRE5BBb8cH/zMwMcRwzPj6+7Pj4+DhPPvnkAb/mlltu4Q//8A+PRHkr3gWnrWPP1CxJEjM+WgD6m/a0oi4LYZd2N8axLQrZDMduKDFW8hktergZa8CVi4iIiIiIiMjhpuBfRI4W9957L294wxsOeN13v/tdzjnnnCNc0eG14oP/f4kbb7yRHTt2LF3evXs327ZtG2BFg1PKu4yWAvbOzNNotmlGPeIkwXdsKiWfiUqWsaJPueBhmsYvv0ERERERERERGRq+7xNFEWmaYhjKBURkeJ1//vk8//zzy469//3v5+677+bss88eUFWHz4oP/sfGxrAsi7179y47vnfvXtasWXPAr3FdF9d1ly43Go3DWuNKZxrQ7fXodWDdqM/4SEC54JMP/mlOf7sdDbBCERERERERERmETZs28ZnPfIa//uu/HnQpIvIilUqFG2+8kSAIBl3K0HAcZ1me3O12+dKXvsS11147lB98rvjg33EczjrrLO6++24uueQSAJIk4e677+aaa64ZbHGrxOmvmeCErRUqpQDP0QgfEREREREREel705vexK//+q8PugwROQDLOrpzvPn5+WUN3fs3e79aX/7yl5mdneWqq646ZLe5kqz44B9gx44dXHnllZx99tmce+653H777TSbzaH9RznUNk6UB12CiIiIiIiIiKxQvu8PugQRkZfYf3T7zTffzAc+8IFDdvuf+tSnuOiii1i/fv0hu82VZFUE/7/927/N9PQ0N910E3v27OH000/nrrvuesmGvyIiIiIiIiIiIiKy+j3++OOsW7du6fLLdfvfcMMN3Hrrra94W0888QQnnHDC0uXnnnuOr3/96/zd3/3doSl2BTLSNE0HXcTh9txzz7FhwwZ27do1tJ/giIiIiIiIiIiIiKx2/9wsd3p6mtnZ2Vc8Z+vWrTiOs3T5j/7oj/jIRz7C7t27yWQyr/CVq9eq6PgXEREREREREREREdlfpVKhUqkc9PlpmvLpT3+a3/3d3x3a0B/AHHQBIiIiIiIiIiIiIiJHwj333MMzzzzD7//+7w+6lMNKwb+IiIiIiIiIiIiIHBU+9alPcf755y+b+T+MNOpHRERERERERERERI4Kd95556BLOCLU8S8iIiIiIiIiIiIiMkQU/IuIiIiIiIiIiIiIDBEF/yIiIiIiIiIiIiIiQ0TBv4iIiIiIiIiIiIjIEFHwLyIiIiIiIiIiIiIyROxBF3AkJEkCwPPPPz/gSkRERERERERERETk5byQ4b6Q6cq/zFER/O/duxeAc889d8CViIiIiIiIiIiIiMgvs3fvXjZu3DjoMlYtI03TdNBFHG69Xo/vf//7jI+PY5qre7rR/Pw827Zt4/HHHyefzw+6HBE5grT+RY5eWv8iRy+tf5Gjl9a/yNHraF//SZKwd+9ezjjjDGz7qOhbPyyOiuB/mDQaDYrFInNzcxQKhUGXIyJHkNa/yNFL61/k6KX1L3L00voXOXpp/cuhsLrb30VEREREREREREREZBkF/yIiIiIiIiIiIiIiQ0TB/yrjui4333wzrusOuhQROcK0/kWOXlr/IkcvrX+Ro5fWv8jRS+tfDgXN+BcRERERERERERERGSLq+BcRERERERERERERGSIK/kVEREREREREREREhoiCfxERERERERERERGRIaLgX0RERERERERERERkiCj4X0U+9rGPsXnzZjzP47zzzuO73/3uoEsSkUPslltu4ZxzziGfz1OtVrnkkkt46qmnlp0TRRHbt29ndHSUXC7HZZddxt69ewdUsYgcLv/9v/93DMPguuuuWzqm9S8yvHbv3s3v/M7vMDo6iu/7nHLKKXzve99buj5NU2666SbWrl2L7/tceOGF/OhHPxpgxSJyKMRxzPvf/362bNmC7/scc8wx/NEf/RFpmi6do/UvMjzuv/9+Lr74YiYmJjAMgy9+8YvLrj+Y9b5v3z4uv/xyCoUCpVKJ97znPSwsLBzBRyGrhYL/VeKzn/0sO3bs4Oabb+bhhx/mtNNO46KLLmJqamrQpYnIIXTfffexfft2vvOd7/CNb3yDbrfLG9/4RprN5tI5119/PV/5ylf43Oc+x3333ccvfvEL3va2tw2wahE51B566CH+4i/+glNPPXXZca1/keFUq9W44IILyGQy/P3f/z2PP/44f/7nf065XF4650//9E/58Ic/zB133MGDDz5INpvloosuIoqiAVYuIq/Wrbfeyic+8Qk++tGP8sQTT3Drrbfyp3/6p3zkIx9ZOkfrX2R4NJtNTjvtND72sY8d8PqDWe+XX345P/zhD/nGN77BV7/6Ve6//37+7b/9t0fqIcgqYqQv/hhZVqzzzjuPc845h49+9KMAJEnChg0buPbaa7nhhhsGXJ2IHC7T09NUq1Xuu+8+fvVXf5W5uTkqlQp33nknb3/72wF48sknOfHEE3nggQd47WtfO+CKReTVWlhY4Mwzz+TjH/84f/zHf8zpp5/O7bffrvUvMsRuuOEGvv3tb/OP//iPB7w+TVMmJiZ43/vex3/6T/8JgLm5OcbHx/nMZz7DO9/5ziNZrogcQm9961sZHx/nU5/61NKxyy67DN/3+d//+39r/YsMMcMw+MIXvsAll1wCHNz7/RNPPMG2bdt46KGHOPvsswG46667+Nf/+l/z3HPPMTExMaiHIyuQOv5XgU6nw86dO7nwwguXjpmmyYUXXsgDDzwwwMpE5HCbm5sDYGRkBICdO3fS7XaXvR6ccMIJbNy4Ua8HIkNi+/btvOUtb1m2zkHrX2SYffnLX+bss8/mHe94B9VqlTPOOIO//Mu/XLr+mWeeYc+ePcvWf7FY5LzzztP6F1nlzj//fO6++26efvppAH7wgx/wrW99ize/+c2A1r/I0eRg1vsDDzxAqVRaCv0BLrzwQkzT5MEHHzziNcvKZg+6APnlZmZmiOOY8fHxZcfHx8d58sknB1SViBxuSZJw3XXXccEFF3DyyScDsGfPHhzHoVQqLTt3fHycPXv2DKBKETmU/vZv/5aHH36Yhx566CXXaf2LDK+f/vSnfOITn2DHjh38wR/8AQ899BD/8T/+RxzH4corr1xa4wf6eUDrX2R1u+GGG2g0GpxwwglYlkUcx/zJn/wJl19+OYDWv8hR5GDW+549e6hWq8uut22bkZERvSbISyj4FxFZobZv385jjz3Gt771rUGXIiJHwK5du3jve9/LN77xDTzPG3Q5InIEJUnC2WefzQc/+EEAzjjjDB577DHuuOMOrrzyygFXJyKH09/93d/x13/919x5552cdNJJPPLII1x33XVMTExo/YuIyKuiUT+rwNjYGJZlsXfv3mXH9+7dy5o1awZUlYgcTtdccw1f/epX+eY3v8n69euXjq9Zs4ZOp0O9Xl92vl4PRFa/nTt3MjU1xZlnnolt29i2zX333ceHP/xhbNtmfHxc619kSK1du5Zt27YtO3biiSfy7LPPAiytcf08IDJ8/vN//s/ccMMNvPOd7+SUU07hiiuu4Prrr+eWW24BtP5FjiYHs97XrFnD1NTUsut7vR779u3Ta4K8hIL/VcBxHM466yzuvvvupWNJknD33Xfzute9boCVicihlqYp11xzDV/4whe455572LJly7LrzzrrLDKZzLLXg6eeeopnn31Wrwciq9yv//qvMzk5ySOPPLL05+yzz+byyy9f+rvWv8hwuuCCC3jqqaeWHXv66afZtGkTAFu2bGHNmjXL1n+j0eDBBx/U+hdZ5VqtFqa5PJqxLIskSQCtf5GjycGs99e97nXU63V27ty5dM4999xDkiScd955R7xmWdk06meV2LFjB1deeSVnn3025557LrfffjvNZpOrrrpq0KWJyCG0fft27rzzTr70pS+Rz+eXZvQVi0V836dYLPKe97yHHTt2MDIyQqFQ4Nprr+V1r3sdr33tawdcvYi8Gvl8fmk/jxdks1lGR0eXjmv9iwyn66+/nvPPP58PfvCD/NZv/Rbf/e53+eQnP8knP/lJAAzD4LrrruOP//iPOe6449iyZQvvf//7mZiY4JJLLhls8SLyqlx88cX8yZ/8CRs3buSkk07i+9//Ph/60If4vd/7PUDrX2TYLCws8OMf/3jp8jPPPMMjjzzCyMgIGzdu/KXr/cQTT+RNb3oTV199NXfccQfdbpdrrrmGd77znUxMTAzoUclKZaRpmg66CDk4H/3oR7ntttvYs2cPp59+Oh/+8If1aZ7IkDEM44DHP/3pT/Pud78bgCiKeN/73sff/M3f0G63ueiii/j4xz+uX+sTGUKvf/3rOf3007n99tsBrX+RYfbVr36VG2+8kR/96Eds2bKFHTt2cPXVVy9dn6YpN998M5/85Cep1+v8yq/8Ch//+Mc5/vjjB1i1iLxa8/PzvP/97+cLX/gCU1NTTExM8K53vYubbroJx3EArX+RYXLvvffyhje84SXHr7zySj7zmc8c1Hrft28f11xzDV/5ylcwTZPLLruMD3/4w+RyuSP5UGQVUPAvIiIiIiIiIiIiIjJENONfRERERERERERERGSIKPgXERERERERERERERkiCv5FRERERERERERERIaIgn8RERERERERERERkSGi4F9EREREREREREREZIgo+BcRERERERERERERGSIK/kVEREREREREREREhoiCfxERERERERERERGRIaLgX0RERERkhXr3u9/NJZdcMugyRERERERklbEHXYCIiIiIyNHIMIxXvP7mm2/mf/yP/0GapkeoIhERERERGRYK/kVEREREBuD5559f+vtnP/tZbrrpJp566qmlY7lcjlwuN4jSRERERERkldOoHxERERGRAVizZs3Sn2KxiGEYy47lcrmXjPp5/etfz7XXXst1111HuVxmfHycv/zLv6TZbHLVVVeRz+c59thj+fu///tl9/XYY4/x5je/mVwux/j4OFdccQUzMzNH+BGLiIiIiMiRouBfRERERGQV+V//638xNjbGd7/7Xa699lr+w3/4D7zjHe/g/PPP5+GHH+aNb3wjV1xxBa1WC4B6vc6v/dqvccYZZ/C9732Pu+66i7179/Jbv/VbA34kIiIiIiJyuCj4FxERERFZRU477TT+63/9rxx33HHceOONeJ7H2NgYV199Nccddxw33XQTs7OzPProowB89KMf5YwzzuCDH/wgJ5xwAmeccQZ/9Vd/xTe/+U2efvrpAT8aERERERE5HDTjX0RERERkFTn11FOX/m5ZFqOjo5xyyilLx8bHxwGYmpoC4Ac/+AHf/OY3D7hfwE9+8hOOP/74w1yxiIiIiIgcaQr+RURERERWkUwms+yyYRjLjhmGAUCSJAAsLCxw8cUXc+utt77kttauXXsYKxURERERkUFR8C8iIiIiMsTOPPNMPv/5z7N582ZsW9/+i4iIiIgcDTTjX0RERERkiG3fvp19+/bxrne9i4ceeoif/OQnfP3rX+eqq64ijuNBlyciIiIiIoeBgn8RERERkSE2MTHBt7/9beI45o1vfCOnnHIK1113HaVSCdPUjwMiIiIiIsPISNM0HXQRIiIiIiIiIiIiIiJyaKjFR0RERERERERERERkiCj4FxEREREREREREREZIgr+RURERERERERERESGiIJ/EREREREREREREZEhouBfRERERERERERERGSIKPgXERERERERERERERkiCv5FRERERERERERERIaIgn8RERERERERERERkSGi4F9EREREREREREREZIgo+BcRERERERERERERGSIK/kVEREREREREREREhsj/DwpEbFu9V2kKAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Generate predictions based on the agent's internal model and inputs\n", + "agent_1.input_data_prediction()\n", + "# Plot the predicted trajectories to visualize the agent's future states\n", + "agent_1.plot_trajectories()" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([,\n", + " ],\n", + " dtype=object)" + ] + }, + "execution_count": 101, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "agent_1.attributes[0][\"expected_mean\"] = 3\n", + "agent_1.attributes[0][\"expected_precision\"] = 1e-2\n", + "\n", + "# Generate predictions with the updated parameters\n", + "agent_1.input_data_prediction()\n", + "\n", + "# Plot new trajectories\n", + "agent_1.plot_trajectories()" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{-1: {'time_step': 0.0},\n", + " 0: {'observed': 1,\n", + " 'mean': 0,\n", + " 'expected_mean': 0.5,\n", + " 'precision': 100.0,\n", + " 'expected_precision': 1.0,\n", + " 'value_coupling_parents': (1.0,),\n", + " 'temp': {'value_prediction_error': 0.0}},\n", + " 1: {'mean': 0.0,\n", + " 'expected_mean': 0.0,\n", + " 'precision': 1.0,\n", + " 'expected_precision': 1.0,\n", + " 'volatility_coupling_children': None,\n", + " 'volatility_coupling_parents': None,\n", + " 'value_coupling_children': (1.0,),\n", + " 'value_coupling_parents': None,\n", + " 'tonic_volatility': -4.0,\n", + " 'tonic_drift': 0.0,\n", + " 'autoconnection_strength': 1.0,\n", + " 'observed': 1,\n", + " 'temp': {'effective_precision': 0.0,\n", + " 'value_prediction_error': 0.0,\n", + " 'volatility_prediction_error': 0.0}}}" + ] + }, + "execution_count": 102, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "agent_2.attributes" + ] + }, + { + "cell_type": "code", + "execution_count": 113, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{-1: {'time_step': 0.0},\n", + " 0: {'observed': 1,\n", + " 'mean': 0,\n", + " 'expected_mean': 0.5,\n", + " 'precision': 100.0,\n", + " 'expected_precision': 1.0,\n", + " 'value_coupling_parents': (1.0,),\n", + " 'temp': {'value_prediction_error': 0.0}},\n", + " 1: {'mean': 0.0,\n", + " 'expected_mean': 0.0,\n", + " 'precision': 1.0,\n", + " 'expected_precision': 1.0,\n", + " 'volatility_coupling_children': None,\n", + " 'volatility_coupling_parents': None,\n", + " 'value_coupling_children': (1.0,),\n", + " 'value_coupling_parents': None,\n", + " 'tonic_volatility': -4.0,\n", + " 'tonic_drift': 0.0,\n", + " 'autoconnection_strength': 1.0,\n", + " 'observed': 1,\n", + " 'temp': {'effective_precision': 0.0,\n", + " 'value_prediction_error': 0.0,\n", + " 'volatility_prediction_error': 0.0}}}" + ] + }, + "execution_count": 113, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Generate predictions for agent_2 based on its internal model and inputs\n", + "agent_2.input_data_prediction()\n", + "agent_2.attributes" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/pyhgf/model/network.py b/pyhgf/model/network.py index 391aae227..fc3a2ac02 100644 --- a/pyhgf/model/network.py +++ b/pyhgf/model/network.py @@ -24,6 +24,7 @@ beliefs_propagation, get_input_idxs, get_update_sequence, + inference_prediction, to_pandas, ) @@ -88,21 +89,24 @@ def create_belief_propagation_fn( ) -> "Network": """Create the belief propagation function. - .. note: - This step is called by default when using py:meth:`input_data`. - Parameters ---------- - overwrite : - If `True` (default), create a new belief propagation function and ignore + overwrite : bool, optional + If ``True`` (default), create a new belief propagation function and ignore preexisting values. Otherwise, do not create a new function if the attribute - `scan_fn` is already defined. - update_type : - The type of update to perform for volatility coupling. Can be `"eHGF"` - (defaults) or `"standard"`. The eHGF update step was proposed as an + ``scan_fn`` is already defined. + update_type : str, optional + The type of update to perform for volatility coupling. Can be ``"eHGF"`` + (default) or ``"standard"``. The eHGF update step was proposed as an alternative to the original definition in that it starts by updating the - mean and then the precision of the parent node, which generally reduces the - errors associated with impossible parameter space and improves sampling. + mean and then the precision of the parent node, which generally reduces + the errors associated with impossible parameter space and improves sampling. + + Returns + ------- + Network + Returns the current instance of the network with the (potentially new) + belief propagation function bound to the ``scan_fn`` attribute. """ # get the dimension of the input nodes @@ -127,6 +131,112 @@ def create_belief_propagation_fn( return self + def create_inference_fn( + self, overwrite: bool = True, update_type: str = "eHGF" + ) -> "Network": + """Create the prediction function (``scan_fn``). + + Parameters + ---------- + overwrite : bool, optional + If ``True`` (default), create a new belief propagation function and ignore + any preexisting values. If ``False``, a new function is not created if + ``scan_fn`` is already defined. + update_type : str, optional + The type of update to perform for volatility coupling. Can be ``"eHGF"`` + (default) or ``"standard"``. The eHGF update step starts by updating + the mean and then the precision of the parent node, which can reduce + parameter-space errors and improve sampling stability. + + Returns + ------- + Network + Returns the current instance of the network with the (potentially new) + ``scan_fn`` attribute defined, allowing for method chaining. + + """ + # Ensure that an update sequence exists; if not, create one. + if self.update_sequence is None: + self.update_sequence = get_update_sequence( + network=self, update_type=update_type + ) + + # Create or overwrite the belief propagation function (scan_fn). + # This function will be used by lax.scan (or a similar mechanism) to loop + # over observations. + if (self.scan_fn is None) or overwrite: + self.scan_fn = Partial( + inference_prediction, + update_sequence=self.update_sequence, + edges=self.edges, + input_idxs=self.input_idxs, + sophisticated=True, + ) + + return self + + def input_data_prediction( + self, + time_steps: Optional[np.ndarray] = None, + input_idxs: Optional[Tuple[int]] = None, + ) -> "Network": + """Add new observations to the model and perform predictions over time. + + This method sets up default or user-defined time steps, optionally updates + which nodes receive observations, and then applies the scanning mechanism + (via ``scan_fn``) to perform belief updates across these time steps. + If no scanning function is defined, it is created by calling + :meth:`create_inference_fn`. + + Parameters + ---------- + time_steps : np.ndarray, optional + An array specifying the time points at which observations occur. + If ``None`` (default), it defaults to ``np.ones(100)``. + input_idxs : tuple of int, optional + The indexes of the state nodes that receive observations. If not + provided, the existing values for ``self.input_idxs`` are used. + + Returns + ------- + Network + Returns the current instance of the network with updated + ``last_attributes`` and ``node_trajectories`` for method chaining. + + Notes + ----- + - The arrays ``dummy_values`` and ``dummy_observed`` are placeholders for + demonstration. In practice, you should replace them with real observed + data and indicators of whether each observation is valid or missing. + - The scanning process, driven by ``self.scan_fn``, traverses each time step + to update the network's node attributes based on the specified + inference algorithm, effectively performing precision-weighted + prediction-error corrections. + + """ + # If input node indexes are provided, set them + if input_idxs is not None: + self.input_idxs = input_idxs + + # If a scan function hasn't been created, initialize it + if self.scan_fn is None: + self = self.create_inference_fn() + + # Use default time steps if none are provided + if time_steps is None: + time_steps = np.ones(100) + + # Perform the scanning operation over the time steps + last_attributes, node_trajectories = scan( + self.scan_fn, self.attributes, time_steps + ) + + # Store the final attributes and full trajectory of node updates + self.node_trajectories = node_trajectories + self.last_attributes = last_attributes + + return self + def input_data( self, input_data: np.ndarray, diff --git a/pyhgf/utils/__init__.py b/pyhgf/utils/__init__.py index f5cd566be..6b4a89c06 100644 --- a/pyhgf/utils/__init__.py +++ b/pyhgf/utils/__init__.py @@ -5,6 +5,7 @@ from .get_input_idxs import get_input_idxs from .get_update_sequence import get_update_sequence from .list_branches import list_branches +from .prediction import inference_prediction, sample_node_distribution, scan_sampling from .remove_node import remove_node from .to_pandas import to_pandas @@ -18,4 +19,7 @@ "list_branches", "to_pandas", "remove_node", + "sample_node_distribution", + "inference_prediction", + "scan_sampling", ] diff --git a/pyhgf/utils/prediction.py b/pyhgf/utils/prediction.py new file mode 100644 index 000000000..3aea58c55 --- /dev/null +++ b/pyhgf/utils/prediction.py @@ -0,0 +1,228 @@ +from functools import partial +from typing import Dict, Tuple + +import jax +import jax.numpy as jnp +from jax import jit, lax, random +from jax.typing import ArrayLike + +from pyhgf.typing import Attributes, Edges, UpdateSequence +from pyhgf.updates.observation import set_observation + + +def scan_sampling( + attributes: Attributes, + node_idx: int, + rng_key: random.PRNGKey, + model_type: int, + num_samples: int, +) -> ArrayLike: + """Generate multiple samples from a node's distribution using JAX's `scan` function. + + Parameters + ---------- + attributes : Attributes + The dictionary of nodes' parameters. + node_idx : int + The index of the node to sample from. + rng_key : random.PRNGKey + A PRNG key used for random number generation. + model_type : int + Specifies how to generate samples (e.g., 1 for discrete, 2 for continuous). + num_samples : int + The number of samples to generate. + + Returns + ------- + samples : ArrayLike + An array of shape (num_samples,) containing the generated samples for the + specified node's distribution. + + """ + + def scan_fn(carry, _): + rng_key = carry + sample, new_rng_key = sample_node_distribution( + attributes, node_idx, rng_key, model_type + ) + return new_rng_key, sample + + rng_key, samples = jax.lax.scan(scan_fn, rng_key, None, length=num_samples) + return samples + + +def sample_node_distribution( + attributes: Dict[int, dict], + node_idx: int, + rng_key: random.PRNGKey, + model_type: int, +) -> Tuple[float, random.PRNGKey]: + """Sample a value from the distribution of the specified node. + + Parameters + ---------- + attributes : Dict[int, dict] + The dictionary of node parameters, keyed by node index. + node_idx : int + The index of the node whose distribution is to be sampled. + rng_key : random.PRNGKey + A PRNG key for random number generation. + model_type : int + Specifies the distribution type (e.g., discrete: 1, continuous: 2). + + Returns + ------- + sample : float + The sampled value from the node's distribution. + rng_key : random.PRNGKey + Updated PRNG key. + + """ + node_attr = attributes.get(node_idx, {}) + mu = node_attr.get("expected_mean", 0.0) + precision = node_attr.get("expected_precision", 1.0) + + # Ensure precision is positive + precision = jnp.where(precision > 0, precision, 1e-12) + sigma = 1.0 / jnp.sqrt(precision) + + rng_key, subkey = random.split(rng_key) + p = jnp.clip(mu, 0.0, 1.0) + + # Sample based on model type + sample = jnp.where( + model_type == 2, # continuous + random.normal(subkey) * sigma + mu, + random.bernoulli(subkey, p), # discrete + ) + + return sample, rng_key + + +def handle_observation( + attributes: Attributes, + node_idx: int, + rng_key: random.PRNGKey, + sophisticated: bool, + edges: Edges, +) -> Tuple[Attributes, random.PRNGKey]: + """Handle the observation for a specific node based on the sophistication flag. + + Parameters + ---------- + attributes : Attributes + The dictionaries of nodes' parameters. + node_idx : int + Index of the node to handle. + rng_key : random.PRNGKey + Random number generator key. + sophisticated : bool + Determines whether to use sophisticated sampling or default. + edges : Edges + Information on the network's edges. + + Returns + ------- + updated_attributes : Attributes + Updated attributes after observation. + rng_key : random.PRNGKey + Updated RNG key. + + """ + + def sophisticated_branch(_): + sampled_value, new_rng_key = sample_node_distribution( + attributes, node_idx, rng_key, edges[node_idx].node_type + ) + return sampled_value, 1, new_rng_key + + def non_sophisticated_branch(_): + return jnp.nan, 0, rng_key + + # Use lax.cond to branch on sophisticated or not + sampled_value, observed, rng_key = lax.cond( + sophisticated, + sophisticated_branch, + non_sophisticated_branch, + operand=None, + ) + + # Assign observation to the node + updated_attributes = set_observation( + attributes=attributes, + node_idx=node_idx, + values=sampled_value, + observed=observed, + ) + return updated_attributes, rng_key + + +@partial(jit, static_argnames=("update_sequence", "edges", "input_idxs")) +def inference_prediction( + attributes: Attributes, + inputs: Tuple[ArrayLike, ...], + update_sequence: UpdateSequence, + edges: Edges, + input_idxs: Tuple[int], + sophisticated: bool = True, + rng_seed: int = 42, +) -> Tuple[Dict, Dict]: + """Perform inference and prediction steps in a network. + + This function updates the network's parameters based on new observations and a + specified update sequence. It integrates prediction, observation handling, + and update steps in three main stages: + + Parameters + ---------- + attributes : Attributes + The dictionaries of nodes' parameters. This variable is updated and returned + after the inference and prediction steps. + inputs : tuple of ArrayLike + A tuple of arrays containing the new observation(s), the time steps, and + additional input data. + update_sequence : UpdateSequence + The sequence of updates that will be applied to the node structure. + Typically, this is a tuple of two lists: + ([(node_idx, update_fn), ...], # prediction steps + [(node_idx, update_fn), ...]) # update steps + edges : Edges + Information on the network's edges, which may be used by update functions. + input_idxs : tuple of int + List of input node indexes that will receive new observations. + sophisticated : bool, optional + Determines whether to use sophisticated sampling during observations + (default: True). + rng_seed : int, optional + Seed for the random number generator (default: 42). + + Returns + ------- + attributes, attributes : tuple of Dict + A tuple of parameter structures after the prediction and inference cycles + have completed. Both entries are the same here (carryover vs. accumulated + structures) but can be differentiated if needed in future extensions. + + """ + rng_key = random.PRNGKey(rng_seed) + prediction_steps, update_steps = update_sequence + + time_step = inputs + attributes[-1]["time_step"] = time_step + + # Prediction Sequence + for node_idx, update_fn in prediction_steps: + attributes = update_fn(attributes=attributes, node_idx=node_idx, edges=edges) + + # Observations + for node_idx in input_idxs: + attributes, rng_key = handle_observation( + attributes, node_idx, rng_key, sophisticated, edges + ) + + # Update Sequence + for node_idx, update_fn in update_steps: + attributes = update_fn(attributes=attributes, node_idx=node_idx, edges=edges) + + # Return updated attributes + return attributes, attributes