{
"cells": [
{
"cell_type": "markdown",
"id": "49bcb5b0-f19d-4b96-a5f1-e0ae30f66d8f",
"metadata": {},
"source": [
"## Comparing the dynamics of the reaction `A <-> B` , with and without an enzyme \n",
"\n",
"### Here, we'll explore a HYPOTHETICAL kinetics scenario where the catalyzed reaction `A` + `E` <-> `B` + `E` follows the kinetics of a 2nd-order *elementary* reaction \n",
"\n",
"LAST REVISED: June 23, 2024 (using v. 1.0 beta36)"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "cbb1af2e-3564-460e-a4ae-41e4ec4f719f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Added 'D:\\Docs\\- MY CODE\\BioSimulations\\life123-Win7' to sys.path\n"
]
}
],
"source": [
"import set_path # Importing this module will add the project's home directory to sys.path"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "087c0d08",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"from life123 import ChemData\n",
"from life123 import UniformCompartment"
]
},
{
"cell_type": "markdown",
"id": "d6d3ca49-589d-49b7-8424-37c7b01bcacf",
"metadata": {},
"source": [
"# 1. WITHOUT ENZYME\n",
"### `A` <-> `B`"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "23c15e66-52e4-495b-aa3d-ecddd8d16942",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of reactions: 1 (at temp. 25 C)\n",
"0: A <-> B (kF = 1 / kR = 0.2 / delta_G = -3,989.7 / K = 5) | 1st order in all reactants & products\n",
"Set of chemicals involved in the above reactions: {'A', 'B'}\n"
]
}
],
"source": [
"# Initialize the system\n",
"chem_data = ChemData(names=[\"A\", \"B\"])\n",
"\n",
"# Reaction A <-> B , with 1st-order kinetics, favorable thermodynamics in the forward direction, \n",
"# and a forward rate that is much slower than it would be with the enzyme - as seen in part 2, below\n",
"chem_data.add_reaction(reactants=\"A\", products=\"B\",\n",
" forward_rate=1., delta_G=-3989.73)\n",
"\n",
"chem_data.describe_reactions()"
]
},
{
"cell_type": "markdown",
"id": "0e771dda-1c0f-4fc0-ab21-049740643897",
"metadata": {},
"source": [
"### Set the initial concentrations of all the chemicals"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "5563e467-a637-44fa-9ba1-d35ddd82c887",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0:\n",
"2 species:\n",
" Species 0 (A). Conc: 20.0\n",
" Species 1 (B). Conc: 0.0\n",
"Set of chemicals involved in reactions: {'A', 'B'}\n"
]
}
],
"source": [
"dynamics = UniformCompartment(chem_data=chem_data, preset=\"fast\")\n",
"dynamics.set_conc(conc={\"A\": 20.},\n",
" snapshot=True)\n",
"dynamics.describe_state()"
]
},
{
"cell_type": "markdown",
"id": "651941bb-7098-4065-a598-e50c0b641ab3",
"metadata": {
"tags": []
},
"source": [
"### Take the initial system to equilibrium"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "76f24d9a-a788-41d8-90a4-db87386f91aa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"16 total step(s) taken\n",
"Number of step re-do's because of negative concentrations: 0\n",
"Number of step re-do's because of elective soft aborts: 1\n",
"Norm usage: {'norm_A': 10, 'norm_B': 9, 'norm_C': 8, 'norm_D': 8}\n"
]
}
],
"source": [
"dynamics.enable_diagnostics() # To save diagnostic information about the call to single_compartment_react()\n",
"\n",
"dynamics.single_compartment_react(duration=3.0,\n",
" initial_step=0.1, variable_steps=True)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "e58db01b-b932-4f60-91c2-a578353a3702",
"metadata": {},
"outputs": [],
"source": [
"#dynamics.explain_time_advance()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "4a19ad2a-fbd2-420a-b958-2daf88bcc841",
"metadata": {},
"outputs": [
{
"data": {
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ttWqXyiAPQwww1+unDjtRwO5zlT5HkcatPYw3BcbJvZXKzW1/KvMuMAb3kWPQmNdNmVYii/ziNU9iOHursW5MZ1WeqlBiJwrwuAx+zjGr+nkf+Q2wvGaEcc6r1stvKs22N17PjDdCViKA8Ya01JMr47gw36Byu/FJmHH3Eytbxn0ttfuu4MG+nIQnuwk1H1/GibKZodVNsJOnALep8bwoFSfAfF0qlbZUH6zqMwoK/G+7sq2WZbm5lvG0HzrkAMvdc0qNSbsJHG+r0Z7GCYPV58bxbHX9UvHgknawOm/N19lS9rdaBmV1LpW6fzDa0uq+R1UcV7keG9kaOVrdG5W6JhivQ1Z5pehttJ+Zo5u22H2flxpTTtfPUvcIVvcednzHjx1ZiD/Cy1QZUzyd+Zzz8l1udX5YfUeo3Edb8XAjCqheB+W5YB5//NosvxvdXvt1DogYxb0o6kgGgcyIAqUm8FZPIOXF1Sngn/nmQ0UNdHMja3cDY3Uz5eRl4NQXt0PWqg2qNwfGuuSXs+qTBrftLCUOON24y7ylAg1G1W4v/XYrWtjdXKqMa94+q8CKqmWWmnyYRQm7Ms31l1pXfPhhB9HMA6faYi3lKWB+eqHqVqlyYxDGOa9Sr52NpV3kuVLKTmYBUkUUcHNd4uUbz7e4r6WlmL36xj9KRsO2sok8X41Rt83fRV5EATsvG5Xo3l5EAaty7dxnzZ+rjkOnCZPdddmLKGAuy+58svrcKbaBkxeXHTfOySnQZCnbmQMJO7XTKe4M7zt/lYp6r3I9trO/ld3sHniY6zGXKe3ExY6J40YXxCMzEzdtcSsKWI1P1Qc4Tp4wTmvXzdd03na7ulXGmZmTm3GnakM7vm5EAZXrYKnrg/H7x8u13/z95eWeDnlAIEwCqRUFzLsPlHL9sbo4ywuD+QvbanJoVNFV1kG5uZF1egJkvMhFLQpY9cPNExDzhNvN5NrKDk5fhLI+o8eAG1HAyt3W7il2mCetm7LDFgVUltWoigKlvozNN8Z2N8rmmx1Zt4qrtJlrGKKAirgSxjmvUm+pa5fxZiYqUcDOdd34FD3ua6lx/LsRN+RYM4rKvKxfsV+5/Etez7hdjBOXpIoCduPL/LnqOLS7DlpNeIxpgxAF7M4Bq8/tJj1WAqpVn+RTy1JLUrxMEnmev7+5puCdZMfd3Cd5znlZlqhyPVadiJcSOu0mqfL7nreDvw6dPk1s4SfPXW4rJ88Pnq/UGDLbsNTyASnqGO+FVJYe2X3/2bXLyo2f12m855LeOaXuw4L4LjeOu1I2VLmX5n0IWhRw+v6VHkherv0QBdzcvSJtHARSKwpwmPJpnvyCMF9s7S6URkOY1XFzGaqTFWOZbm5kS10Yza5dUYsC5vVs5gHs5ibZj2u/6onjp45Sk2sv3hGqbfabzsrFvlSZql/6vAwpzFitXS3lkinrN58Hpc4L83lWynPDfLNjtU5SRYAKQxRQ8SgI45xXqdfpfJbXvihEATkRMtvJPMHS4VpqJYypilDGG2Te59kz9xdPf41CgHmiknZRQHUcJkEUsBO2jG1XEabl+WCXz+m6XeqaL7+nVUUBXpY874zlqkxmeXqn67GqKFBqYm71nWwU4Pg5Jb+35PnFRQ4eA8P4IEi1LaX4hiEK2AlNVkzk+WQcZ07LdqzugY22M9/b2X2XO407NwKdXVlBiwJW55qxbqulNHbHzW2GKOD3jhb5wyaQCVHAeDEz3mQ6PVEwwre7CJsnKyrqppsbWSfVMi5PgVIKr91SDZXB7Gfi7vSlwY+r3rhYXcztbvT99FeFiZ80VmsHS5XndHMpb5icnkiELQqUWjPsxEveJDl5loQhCqg8sQ/jnFep1+w66zTpUnF/9bJ8wI3ooOO1VNrPjfDEzyseHFaOSd6vx5a+LJ5amicqaRcFVMdhqfO81M23m4mIG48A3h47TwGVseB03TLfj/D/5fXYyVPAaYkCL8vu3kVl6ZGcSKkIHOZ+mq/HqhNxN54C8h6Qe0bIc8oohnBPHL7unp9zxqVhqm0pZbs4RQE7RioxRYyClmTl9v7Aady5ORed7u+cPDzsvCvM9jF70Lg5L52u/RAF3NBE2jgIZEYU4HCtJgN2FwqjMdysdS51kyrXZtktTbD6Yg5jfXEQA81psunWbd3cpiDEAWMZXsUA2a6kegoY104ag2QaefMxxsWlUlsSqj7VdzNhMZdZ6iZPNaaAeRzxcWoMVsePq9zk8nRhiAJON7L8KXEY57xKvSrCgd3Ex3ieGM+1Ui7STnEhrCYYdjELrG4+zTd7YXC1Gl+cheraYOPyI+M6fLvP7cavtJ2Vd5bqzXCp7wW7m1mrMaO6TEDW57T+28v3VSnRsNSYVJ3AuRELVB4UlOqj1Rgzj2U7+6tM/uzsID8329iqPar1qFyP3UzE3axHl8zMcQTsPuf9d9MWOxuqjik31w27MWUeF6rXPG6/R/78YlEwQqv+q4oCquPBKfaASsyToD0FVJeGuL32q953eLneIQ8IBEUgU6KAvOjyd3kTKU9Uq0kj/8KRN1lWkY+lyKASFd14k+L2QijrKRURnPcpyuUDTpN+J9FAdQDLC7TbSX0pu6rWbUxn11+v7VNpg3SRd7MMw6pc2UarNaBmoUz1S1/yNT4BM4owXjwF5Bg2Rvjln9mtQ7VbGsHPA779Ghc5rM4d1bEZhihg7KN5qyfj+t4wznn5NM9tvdIGfP0t32nCzZP8Uje6pTwirM43eT4YrwVxX0tlH1Siadud83Zree3WklvdXLoR1JwmgVbttPtuCUMU4PVbjX/zOCx1DXVaLqM6mXQz+eftsUpfKu4M7yePIVEq4KnVdU6ODXMkdCshTdrIfIyPGR7DQorF5jJ5f6yu81bXEdUldCrXYzcTcau+2bXF+OTb7CUmry1mRm7aYjcewxAFnL5/Zf9kn62umby98vvbboya73tV7w942arjzur7WH6mErciaFHA7jta9om/c/He7bVfVXRXuTdEGhAIi0DmRAHjF4PxC8BqjbJV/ABjAEN+c823EVPZP90sHJjXocq2OE3s5UCwcmV3yut3cinrVnGXt/rSCmsQR1FuqTXsXlwmVdoclCgg67Jaq2seR26+9I0iAK+DlyX3QvcqChi/kGW7eVn85tVqizGr9X9W2wWaeaucC2GJAsYbJmO7zG0yr70N4py3WgvsVK9so0znVhQwjxN5I6oycTPzsZrMxX0ttRqDTktTjP2yE6nsrrN2AoDZtrINQXgK8PYar4FyLIYlCvD6zOPfPA5LXUOdnsrZjUnVCZxbsYC3VeX6a9Unq7gEVpMlO/vzMs39NV5b5Zaysu/mIM1W329WfXFyFZd1Wn2XGq9BbifiVn2za4vVwx3jWLPaGnXR4seK4gzw9KpPk+X3mZUXkMryK5UxLtPwc5JvEcwDJxqvP+bxw8eODGZqJ+obyzR6GLq5P1Add1bnOh9zfAvwODwFZN+tviv5MattCo12srv2q3gll7I3joFAFARSKQpEAQ51gAAIREcAa/GiY42aQCANBPy67aeBgZs+gJcbWkgLAuoEVD1p1EtEShAIhwBEgXC4olQQAAEPBPiXJ38Zt2pyeqLsoRpkAQEQSDkBK9fplHfZV/cgCvjCh8wgYEkA1yEMjCQRgCiQJGuhrSCQcgJWLnsq6wpTjgXdAwEQ8EBAXk9Ut4j0UEVqskAUSI0p0RFNCJSK56RJE9EMECgiAFEAAwIEQAAEQAAEQAAEQAAEQAAEQAAEMkoAokBGDY9ugwAIgAAIgAAIgAAIgAAIgAAIgABEAYwBEAABEAABEAABEAABEAABEAABEMgoAYgCGTU8ug0CIAACIAACIAACIAACIAACIAACEAUwBkAABEAABEAABEAABEAABEAABEAgowQgCmTU8Og2CIAACIAACIAACIAACIAACIAACEAUwBgAARAAARAAARAAARAAARAAARAAgYwSgCiQUcOj2yAAAiAAAiAAAiAAAiAAAiAAAiAAUQBjAARAAARAAARAAARAAARAAARAAAQySgCiQEYNj26DAAiAAAiAAAiAAAiAAAiAAAiAAEQBjAEQAAEQAAEQAAEQAAEQAAEQAAEQyCgBiAIZNTy6DQIgAAIgAAIgAAIgAAIgAAIgAAIQBTAGQAAEQAAEQAAEQAAEQAAEQAAEQCCjBCAKZNTw6DYIgAAIgAAIgAAIgAAIgAAIgAAIQBTAGAABEAABEAABEAABEAABEAABEACBjBKAKJBRw6PbIAACIAACIAACIAACIAACIAACIABRAGMABEAABEAABEAABEAABEAABEAABDJKAKJARg2PboMACIAACIAACIAACIAACIAACIAARAGMARAAARAAARAAARAAARAAARAAARDIKAGIAhk1PLoNAiAAAiAAAiAAAiAAAiAAAiAAAhAFMAZAAARAAARAAARAAARAAARAAARAIKMEIApk1PDoNgiAAAiAAAiAAAiAAAiAAAiAAAhAFMAYAAEQAAEQAAEQAAEQAAEQAAEQAIGMEoAokFHDo9sgAAIgAAIgAAIgAAIgAAIgAAIgAFEAYwAEQAAEQAAEQAAEQAAEQAAEQAAEMkoAokAAhm9t76HWjt4ASkIRuhCoqiinEY1VtG13ly5NQjsCIlBXU0G1VRW0q607oBJRjC4EmoZVUf/AALXheqyLSQJrx6jGamrv6qPO7r7AykRBehAYP7KWtjd3UV//gB4NQisCIVBWRjRhZB1t2tkRSHkoRB8C1ZXl1FRfJc5bL69Jo+u8ZEOekAlAFAgAMESBACBqVgREAc0MEmBzIAoECFOzoiAKaGaQAJsDUSBAmJoVBVFAM4ME1ByIAgGB1LAYiAIaGiWAJkEUCAAiRIEAIGpWBEQBzQwSYHMgCgQIU7OiIApoZpAAmwNRIECYmhUFUUAzgwTUHIgCAYHUsBiIAhoaJYAmQRTwCfHb3/42XXnVda6XDzz5yB/ogIMPoanTDvDZgsHs69etoTWr3qSTT/+k5zJ3bN9Kf3nqETp7/gLPZbS2NNOfltxH8z//Rc9l8Iz/87P/oku/crWvMu6753Y6Y958amwa7qocN6JAEMxUGvfic09TfUMTzZr9YZXkkaXp7uqi392zkC649F8jq1O1IitmaRQFHrxvEX30pNNp9JhxqmgSl05lnEEU8GbW5a+/QnvaWuioY0/0VkAEuZIqCmTh3PRr/iyIAl7vRfyyjTM/RIE46Ydbtx9RgN/b33jjjeE2EKV7IpB5UeCiK39AL722sgBv/6mT6aFFNxXBPGvB9bR2/Ubxmfk4RIGh4w6igKdz0TETRAFHREMSQBRwz0zXHBAFwrMMRIHw2EIUcGYLUcCZURJTQBRIotXU2gxRQI1T0lJlXhQ4bt4V9OySWwt24/8fe8Qs+t51XxCfcdFgx86WglDABYLRo5rorluuEcchCkAUgKcAPAXivvBnYeIBUSC8UQZRIDy2WTg3/dKDKOCXoJ75IQroaZcgWgVRIAiK+pWReVHAbJJv3HwHvbV6Q0EE4CLB1y47j+bNPVYkXfLYc/TjhYuLhATEFNBvYPttkZvlA37rQv5oCaRx+UC0BPWtDcsH9LWN35YldfmA335nIX8WRIEs2NHcR4gC6bW6H1GAU8HuA3qODYgCJrtwT4AZB04RngLLV66j+Zd/h+677QaaNX2aSGn1GUQBPQe3n1ZBFPBDT++8EAX0to+f1kEU8ENP77wQBfS2j5/WQRTwQ0/fvBAF9LWN35YlVRQwe3v75RBlfqv5Z9D1QxQwEOVeAg8/8TyteGaRrQAwxCibXqS+1Q9R+0e+E7RtUF6MBMrLy6i2uoLaO3tjbAWqDoNAJdtft5LZF/udh0E33jJrqipogP109/TH2xDUHjgBLub19A5Qbx9sGzjcmAusr6tk37V9NDAwEHNLUH2gBMqIGmqrqK2jJ9BiUVj8BCrYPVSNj3vkxmFVoXTCHCeOVzJqRKWNr/AAACAASURBVGPBuzsOUYB7mF///TvppmsvKXide+k8RAEv1DzmufWXD9LCXz/s6BVgNgqPKXBjw7eob9xHqOuffkx9E45SasHDS35PM2YeSvsfcKBSepVEa9esprdWLKMz531KJbllmq1bt9ATj/4/+uwFF3suo6W5me5f/Bu65Atf9lwGz3jLD28WOzv4ed15x8/p3PM+S03D3e0+4EYUCIKZSh+fWfoUNTU20ZwPH6GSPLI0XV2ddOftv6Avf/XKyOpUrciKWRpFgd/86pd0ymkfp3HjxquiSVw6lXEGUcCbWV975WVqaW2h4084yVsBEeRKqiiQhXPTr/mzIAp4vRfxyzbW/BAFYsUfZuV+RAF+bx/G7gMzj19QJADI/nOhYPyYkcIDPA5RICg7QBQIiqRDOWYPAWNyp5gCXBT4j31+T+U73xTZWj90A7Uedq1jy7EloSMibEloQoTdB5zHjDkFdh9wz0zXHAg0GJ5lEGgwPLYINOjMNgvLB7AlofM4QIrkEPCzfCCMLQn5xH/NuveL4r1Z0ZSiAD8md54zehIYhQTjznTGZeQyIP1zLy+nnbtbRZbLPncm7T15nPAIkC+Zx2oyb/Zo4PmvuPhsEdzeWC8vq5T3etAjJvPLB/gA4S/zNoTGgaGy+0D5X6+k+hU/E9m6JvwztRz5Q+oZOcvWXhAFnIcyv3Bc+pWrnROWSOH1i9hNTAHsPoDdB3wN0gAyZ2HiAVEggIFiUwREgfDYZuHc9EsPooBfgnrmR0wBPe0SRKt0EwW4l8CZpxxT2DnOro9yi3k5Cefp+CT/gGl7FXaVM+86Jz3J5eScp+digJz0y+PmZQpybmkWBcwCBj/+k/95QNTPj/37pecU4tgZ56jwFAhi5JYoQwK2SmJc+yEHEU+3/9TJQwQEGWiw9v1Hqemlq6iydZ0osuUj36e2mV8NuRcoPgwCbkSBMOpHmeERQKDB8NjGXTICDcZtgfDqR6DB8NjGXXIWRIG4GcdRP0SBOKhHU6cfUYC3MMjdB+RcTmXNvtXyAeOuc3YTby4EnPuJE8TTfPPW9VZ5eJnck4BveW88zvvOA9irtJWn5YLD/X9cOqQcGfw+aGtn3lMgCKDG3QfK+jpoOBMGhq2+SxTdtdcp1HzED6m36YAgqkIZERGAKBAR6BiqgSgQA/SIqoQoEBHoGKqBKBAD9IiqhCgQEeiIq4EoEDHwCKtLqygggwJaoZTeBXaigHGibzeZf3vDB2KJgfQ6sKpHeiIYj/H08BSIcID7qcpqS8K69Q9S08tXUUX7JhqoqKYWJgzsOehSP9Ugb4QEIApECDviqiAKRAw8wuogCkQIO+KqIApEDDzC6iAKRAg7wqogCkQIO+KqdBIFeNfdLB8YPaqpsFSA5zV6CkhRwGnSfuwRswpLFaw8FbyKArwfR86ZXmifcekCRIGIB7mX6nigQR4hv7Vj6NZ15V27aDgTBurevlcU3TllHvMa+C/qq9+LEFPAmTZiChQzQqBB5zFjToFAg+6Z6ZoDMQXCswxiCoTHFjEFnNlmQRTwGt/ImZ6+KSAK6Gsbvy3zIwrEEWiQT/ztdh+wWj5Qyr3fj6cA5263fMBKkIAo4HekRpy/lCggmzJs7W+E10B5dzP1Vw9nsQb+ix5a00AHHHwITZ0W3LKC9evW0JpVb9LJp3/SM4Uggua1tjTTn5bcR/M//0XP7eAZIQpAFPA1gFhmiAJ+CeqTH6JAeLaAKBAeW4gCzmwhCjgzSmIKiAJJtJpam3UTBXirrbYklBNtGYTQKaYAL0fuAGD0FuDCwZFzZtC8ucfaxhRQWT7AYwHwNuzc3VLYKUEGGuQBBs2CAe8Tf2H5gNq4jD2ViijAG1mxZ6PwGqjdsES0+d6Kr9O0I+bRPgfNCawPEAWGovSqzrtZPhCEkKIyCOApoELJWUhJ4/KBLEw8IAq4H/+qOSAKqJJyny4L56Z7KsU5IAr4JahnfogCetoliFbpKAoYJ/TGPpoDx5daPiDzldoa0I+ngAwQaAxgz+uUbeTiw8NPPF9oPo9jsPDXD0MUCGLQRlWGVUwBu7rrV/0P8xq4msr6u6i/dgy1HP6f1H7ABVE1FfUoEnAjCigWiWSaEEijKKAJ2tibgZgCsZsgtAYgpkBoaGMvOAuiQOyQY2gARIEYoEdUpR9RgDcxyN0HIupyJqrB7gMBmNmNKMCrq2xZw4SBa4lvYchfnXufIcSB3hEHB9AaFBEEAYgCQVDUswyIAnraJYhWQRQIgqKeZUAU0NMuQbQKokAQFPUrA6KAfjYJqkUQBYIiqVc5EAUCsIdbUUBWOWz1Imp69ZtU3rVTfNRy+HeobdbXA2gRivBLAKKAX4L65ocooK9t/LYMooBfgvrmhyigr238tgyigF+CeuaHKKCnXYJoFUSBICjqVwZEAZ82UY0pYK5G7j4wbdJIJgz8Bw1b8yuRpHvsEcJroHvCca5bhpgCQ5EhpoDrYeQ6g8pab9eFBpQBgQYDAqlBMSrjDKKAN0MhpoA3biq5EFPAmVIWRAGv9yLO9PRNAVFAX9v4bZkfUSCM3Qf89gf5cwQgCvgcCX5FAbn7QO17f6KmV/6DKptXiRa1zbyCWuf8Jw1UVCu3EKIARAHlwRJgQpXJWoDVuSoKooArXFonVhlnEAW8mRCigDduKrkgCjhTgijgzCiJKSAKJNFqam2GKKDGKWmpIAr4tFhQooBsRtOrN1DD8h+Jf/sa9qWWD/8ndUw9W6mVEAUgCigNlIATqUzWAq5SuTiIAsqotE+oMs4gCngzI0QBb9xUckEUcKYEUcCZURJTQBRIotXU2gxRQI1T0lJBFAjAYl5jCthVXb3tZeE1UL3lWZGkY9p8saSgr35yAK1FESoEEFNAhVIy0yCmQDLtptJqiAIqlJKZBjEFkmk3lVZnQRRQ4ZC2NBAF0mbRwf74EQV4Kdh9QM+xAVEgALsELQrIJjWsuJUaX/sPKuvrpoGqBiEM7Dn4iwG0GEU4EYAo4EQoucchCiTXdk4thyjgRCi5xyEKJNd2Ti2HKOBEKJnHIQok024qrYYooEIpeWkgCgRgs7BEAd60irZ3hNdA3foHRUu7Jn1MiAM9o2cH0HIUYUcAokB6xwZEgfTaFqJAem0LUSC9toUokE7bQhRIp115ryAKpNO2EAV82jXomAJ2zalbd5/YpaBiz0aRpHX2dez3m0XJEVNgKD2vEX/diAI7tm+lvzz1CJ09f4HP0VQ6u9X6+FArVCxcZa23YlGBJ0NMgcCRxlagyjiDKODNPIgp4I2bSi7EFHCmlAVRwOu9iDM9fVNAFNDXNn5b5kcUwO4DfumHlx+igE+2UYkCvJllPW1CGKhfdbtodc/IWSwQ4Xepa/LJ4n+IAhAFfA5nT9lVJmueCg4gE0SBACBqUoTKOIMo4M1YEAW8cVPJBVHAmRJEAWdGSUwBUSCJVlNrM0QBNU4y1XHzrhB/PrvkVncZI04NUcAn8ChFAdnUmg/+LJYUVO18XXy056BLqPXw79K697fQmlVv0smnf9Jzr4J46t3a0kx/WnIfzf+8v/gHXE289CtXe+4Lz+hVnYengDp2lcmaemnBpoQoECzPOEtTGWcQBbxZCKKAN24quSAKOFOCKODMKIkpIAok0WpqbYYooMaJp1ry2HN0932P0s7dLfS1y86jeXOPVc8ccUqIAgEADzOmQKnmNb5+MzW+/l2RpK9uArWy7Qvb9/tMAD1CEW5EAdBKFgHEFEiWvdy0FqKAG1rJSouYAsmyl5vWZkEUcMMjLWkhCqTFkkP74UcU4KVlafeBi678AX1o5gH09xVrBMi7brlG24EBUSAA08QlCvCmV+1azrwGvkk1G58UPemccha1Hno1C0T4oQB6lt0iIAqk1/YQBdJrW4gC6bUtRIH02haiQDptC1EgnXblvdJSFOjrYuuon4geemUt0ZTcMm6r18zjF9B9t91Ab2/4gH68cLHWSwggCgQwfOIUBWTz6/9xJzW++k0q724RH7UfeCG1zrqK+hqnBtDD7BUBUSC9NocokF7bQhRIr20hCqTXthAF0mlbiALptKu2okBXM9HPRkQPvWY40Vd2W9Yrlw48tOgmcZwLBDdde4m2SwggCvgcPnHEFLBr8rurXqF1rz5G5/fcXEjSNutr1MbEgf7qJqWeIqZADpMbUSAIZirGwe4DKpSK0yCmgHtmuuZATIHwLIOYAuGxRUwBZ7ZZEAW8xjdypqdvCogC+trGb8v8eAqEtvsA9xT44zl+u+Y+f0UN0ScesMwnlw5ccfHZ4jj/n790XUIAUcC9+Yty6CQKyN0HTvun6dS47EdU9/a9oq391cOp7dCrqO2QKx17G8QEF4EGHTF7SgBRwD02iALumemaA6JAeJaBKBAeW4gCzmwhCjgzSmIKiAJJtJpam7UUBdSaHmkq7hlg9VrxzKJI26FaGUQBVVI26XQUBeTuA9VbX6CGZT+k2vcfE63va9xXLCloP9B6kPI0EAVyhoangPqJoTJZUy8t2JQQBYLlGWdpKuMMywe8WQiigDduKrkgCjhTgijgzCiJKZIkCvQP9FN/fx/xH/53H/tbfMb/5j/s/wH+90Dub3aEHcv93dffTwPs/6Jj4nOWrixfbj4PTytKzJfP8/B6xafyb1lPvk3imEifT8fLZn+L9og259op2m/Rvlw/+DHR6lxZ+bTiE/m37LdgMJArW9Yj8g+2lZfJHjlST3+v6L+ZSaFcA9N+no6VcU3v1XTjjTcmcUi7ajNfOmAVQ0DnJQQQBVyZ2DqxDjEFSnWj9r1HqGH5D6l660siWc+YOUIc4EEJ8bIm4EYUAMNkEUBMgWTZy01rIQq4oZWstIgpkCx7uWltFkQBFR4DfCImJ2Fy4igmkfnJHz8m/zZPTPmEjeU3TjjlpFVObMXkU0w4Bye0xkminJiaJ5yFyWd+win+N0xsCxNOQ7miDNaa2uoyaunoGpxoGyacYpJbmADnJ5z5/wcnwLm+Gyfdxe2Tk+P8pLowATZO7vMTWjEBHpzAGie5nD1e0RC48ojr6cen5XZOS/PrrAXX0+hRTUOWCui8hACiQAAjUndRQHZx2NrfMHHgR1TZvFp81DX5JBZv4OvUNeGfA6CQriIgCqTLnsbeQBRIr20hCqTXthAF0mvbqEWBXvZ0s6uvk7p6u3Lv7LeT/d3dz/7vzf3fxdYnd/K/2W83+5v/z//uzB/LfZY73mn4W5TRw/Lmj4l87G+evnegd+hTaDG5H3wqnV4r692z8rJyKi+vIP7D/65gf4vP+N/8h/1fxv8uy/3NjrBjub8rysupjP1fdIx/zo6LdPm/c2WKlIXyRZp8eYW/ZT35NvEycnlz5Yk62d+iPaLNuXYW1WNo32AbxF+5sizaV+i3YFBWXA/vq6GttVWV1FRfQ82tfaL/ZiaFOg1My3k6VkZd5bBMbUmo98gvbh1EgQCslRRRQHa1YcWtwnOgvHO7+Khj33NEMMKeUYcEQCMdRUAUSIcdrXoBUSC9toUokF7bQhRIh235E9nChDw/CW+oH6DNu1upo6cjPyHvLky4ZVo+QR+ctA9Ourv7Wdr8RF5M4g2TcDHZZxN0OfHnIgAvg4sCOr7K2NSyMPmUE0c2kSqaCMpJoXliyidspgmnnLTKia2YfIoJ5+CEtmjCWZiMFk84C5PP/CRY/G+Y2Ip68hPowkRZtKecRtTX0p6O/sGJtmHCKSa5hjoH22ecAOcmnMZJd/GEWLY1N+EUk2OLSffgBH1wAmuc5JbxtQ54KRPwE1OAVzJpdJ1yXUgYHQGIAj5Z6xxToFTXynrbhddAIxMHiCnV/LXnoEtp/V6X0tL/e4XOnr/AMxkEGvSMrmRGBBp0zxUxBdwz0zUHYgqEZxnEFAiPrW4xBXr7e/JPsXNPvvkkmT8ll0+95VNyObnOTbiNxwcn4fIYfyo+9Gl67km8nMjnnrrn/o/7VVleSTUVtVRTWSPeq8trqDb/dw3bc3zwWO547jP2N3uvFemr85/ljtWyY7yMmqrBvDwdPybSsr//+uCf6KNnnEENjU3FT6HFRHbwqXTcbIKsP0kxBYLsdxbK8iMKhLb7QBbAh9xHiAI+ASdVFJDdrtizUXgN1K+6Q3y0uX8S/aGM7aH5+a/SQMUwT3QgCnjC5pgJooAjoiEJIAq4Z6ZrDogC4VkGokB4bI2iAF8/nZsk5ybZ0j2dT7qlO3phgp53P+dPwnNPwHOu6oMT9EGXdmsX+EF3d2OdfH12nC/+NFxMsvkknE+k2d/11XVUWVZN1XwiLX5zE+nCBF1MyIsn6EWT7vxEvjY/eRcTdFEHm7DLfHwyny+XiwJRv7AlYdTEUV+YBCAKhEk3vrIhCvhkn3RRQHa/auebQhxofvtZeqhzHl066gG2hSHfxvCrrglBFHCNTCkDRAElTEWJIAq4Z6ZrDogC4VkGooA92w7mVdfa3Upt3S3F7z38s1b2WcuQd5m+raeNzmiZS49WPErv9r9HPX3d4RlRseTK8irxtFs++TZP0HOTcsNTcf63+DU8FXeYoOfKz0385QRdfFaV+9/8ijqmgCKqQJNBFAgUJwqLmQBEgZgNEFL1kYsCx827gnaytWNWL133bXRin7SYAqX6U7P5r2JZQc3Gp0Sy3qYDRDDC9gM+54QhVccRUyBV5izqDGIKpNe2iCmQXtu6iSnA1623KU7a5WRfTO5ZnqJJPpvU9/b1BAaVr3c2uq0XJtv5Sbh8si0m0ga39dwTcP6ke3CCXngqLvOy40YXeOnibp6g8/XZur2yIAroxjyK9mD5QBSU46nDjyjAW4yYAvHYzanWSEUBu+0ZnBqp+/E0iQKSde2Gh0S8gartr4mPusceQW2Hsm0M9z5Dd3ME0j6IAoFg1LIQiAJamiWQRkEUCARjbIXwCTh/yi4n6PxJvJyo95e10472ZtrV0Vz01J4/jbd6Wh9UJ3ik7MbqRqqvahTvDdVN4r2RvTcY3hvY8Yaa3OfGdDw9n5jz3yrmvo7XUAIQBdI5KiAKpNOuvFcQBdJp20hFgZnHL6CbrmXr1ecemyqaaRQFpIGGrV5Ejct+SBVt74iPOiefKsSB7vHHpMqG5s5AFEiveSEKpNe2EAXisW1nX0exa31XztWeT9b32EzajS728mk9d9UP6mWetIv/qxoKk3o5uTdO8uvZ8Vy6wcl9ZUVVUE1COTYEIAqkc2hAFEinXSEKpNeuEAXytr31lw/S/X9cSs8uubXI2t+4+Q56+Innh4wAudQhLTEFZAd3bN9Kf3nqkSG7DzS8eQs1MHGgvLtZJO2Y9mlqPewq6h1+8BA2iCkQzgUDMQXcc0VMAffMdM2BmALhWIZP2l955Tm23/QuGjF93JD1823d1k/i5RN8PrnnEe2DePEAcMan78YJ+piGEVRbXk91FYMTe+uJP3+a38j28NZjizHddh8Iwk5Bl5EFUQAxBYIeNSgvTgJ+PAWw+0Cclitdd6SiAF8+cNJxh9MVF5+tDZEljz1H13//TtGeUSMaLUWBt1ZvoIcW3WTZ5qyIArzz5eypDw9G2LD8xwUWe2Z8iVoPvZr6a8cVPoMoEM7whijgnitEAffMdM0BUcCdZXZ27KCt7VvY7ybaumdz/m/2vod9xv7f0r6ZtrHj/Gn+UexnBPt5jP14edVW1im52Ds9reeu+nYvNzEFvPQhrDwQBZzJQhRwZpTEFPAUSKLV1NoMUUCNU9JSRSoK8An4jxcuHjLx1gFaKU8BiALFFqpoXS+WFAxbc7c4MMCCIrUd+nX2ezX7u4ogCoQzoiEKuOcKUcA9M11zQBQg4tvJbevYQlv4JJ//sr+3trFJP3/nE332K4+rRrqvraijE6pOpLEVY2j96PctXewt18/z9fRVufXzUayVhyig65npv10QBfwz1LEEiAI6WiWYNkEUUONoFVxf56D6kYoCPKZAqVecoFSXD1h5E6Q5pkApe1Xt+LsQB2o3LBHJ+uomiHgDe6Zfrna2aJwKMQU0No7PpiGmgE+AGmdPakwBvpZ+K3tyv6Ut9/RePsUXk3/xpD836d/WsVWZ/vCaETS+fiKNHTaexg+bQOPq+e94Gsf/Zp/x/8cPm0hNNcOVy4wzYVJFgTiZJaXuLIgCSbFFkO2EKBAkTb3K8iMK8J5kZfcBLgqc+4kTCh7yF135A9qxs8XW+zxuK0cqCsTd2VL124kC5jx8CQR/2S0n0LmPobVtw5NEL32P6L2luSrGzCQ64htE0z8TWpUoGARAAAR0J7CzYydtat1Em9mEXryzSf8m9mTf+Bn/u7krF6tF5TWxYSJNaJhAExsnkt3fE9iEv66qTqU4pAEBEAABEAABEAiBgFkUUJ1rhtAUpSIhCuQxqRpKxiAwejVk1VPAPMLq3vm9CEZYtWu5ONQz8lDaM+Nyaj/gAqXBqFMieAroZI1g2wJPgWB56lRaFJ4CAwMD4ql+br1+3o3fsEY/93Q/99S/u79LCQ/fg348m+iPrWNP9dmEvvjpPn+yn3+6z951CaCn1LEAE8FTIECYmhUFTwHNDBJQc+ApEBBIDYvR0VOgq6+Lnlj7ROS0aqtq6eRpJ1vWaxYF+IPlGQdOoe9d94XI26lSYeSigDGwn2ygDtsUehUFshRoUGVA8TR9f7+d/vfFjfRvdT8SWXobp9Gegy8TAgGVVagWQzxC6aVfuVo5vVVCrxF/3YgCdjs2+Gq4RWbEFHBPFDEF3DPTNUfYMQU6eztyE31DUD45wRef5Sf7PI3qi7vm5yb0zFWfT/aZ+z535ReTfu7Onz82onakapGhpFv++iu0p40FHDz2xFDKD6LQpIoCCDTobP0siAJe70Wc6embAqKAvrbx2zI/okBYuw80dzbTiB+M8Ns11/mHs+/53dfuthUFdu5uLTp25inHQBTgRPjEe+GvH6b7bruBZk2fJiAtX7mO5l/+Hbrsc2fGuiuBnSjAVR7jNoX8/wOm7UV33XKNaD9EgaHngQw0eNHRdVS/8jaq2vmGSNRfO5bFG2DiwPQvUX+18zpWiALFbCEKuL5WE0QB98x0zeFVFGhhrvlb9rB1+Yan+8a1+7mAfZupudP6S92Kx9i6cbk1+eLpfn7Cn3/KL9bu59fsl4qmrxNniALhWQOigDNbiALOjJKYAqJAEq2m1mYdRQHuKXDO/eeodSDAVDWVNfTAOQ/YigLGmAI8EY+vF/ec1677kXoKmN0oZKNUn9IHaMNCUVaeC0YVh7t6rF2/sZD+yDnTC4IARAFri5h3H6hb/wchDlRveU5kGCivFV4D3Hugr2FvW7NCFIAo4Pechyjgl6A++c2iQNFT/fykf3f3NrFm/wO2Tn8bC87HA/ZxDwCVV3VFTWEyLyb1haf7PCBf8dP98rJylSITkwaiQHimgijgzBaigDOjJKaAKJBEq6m1WUdRQK3l0aaymvfqvIQgUlGAqyNWSwWs1ulHazZ/tSGmgBq/mg+eovq3bqPa9x8tZNhz4MVMIPgS9Y6YrlZIRKncLB+IqEmoJiACiCkQEMiQi3m3ZT1taF5HGwrv79B77G+5Hd8ADSi1gG+nJ9z0DU/w5ZP8cezp/jgWoZ+78o+sHaVUHhLFQyCpywfioZWsWrMgCiTLIsG0FqJAMBx1LMWPKMD7k9XdB3TxjrcbU5GKAjp6CgRxskEUcEexeutLwnOg7p37Cxk7pp0ntjLsHnuEu8JCSg1RICSwGhQLUUADI7Am8Cf465vfoXdb3slP/uV7Tgzo7e8t2dAxdWMNE/2J4in/PiMmiwl+Y9WYwtP9+qoGPTqMVvgiAFHAFz6tM0MU0No8nhsHUcAzOu0zQhRQMxGf95pjCui6dID3KFJRQOeYAmrmtU4FUcAbvcpdb1HDyl/QsNV3FQro3Pt0IQ50TfqYt0IDygVRICCQGhYDUSA6o+zq3Fk04RciAPtd37KOufkPLsuyatHEhsk0dfg02qdpX/a+L01hf09hf8un/pXllUOyRbH7QHT0UJORAESB9I4HiALptC1EgXTalfcKokA6bRupKMAR6rr7gFfzItDgUHLmmAJObCva3mWeAwuF90BZfguv7vHH0ffe/hh2HzDAQ6BBp5E09DhiCrhn5jbHxtb3xNP+9ezpPnf55+85t/93aHfnLtvi+KTePOEXE38x+Z9KtZV1RXm9Bhp0258spkdMgfCsjpgCzmyzIApg9wHncYAUySHgRxQIa/eB5NDTt6WRiwL6ovDWMogC/kUBWUJ5124mDPyC6lctpPLO7fTttm/R9XvfT3sOuJDaD1xAA5X1ro3k9YvYjacAtiTsot/ds5AuuPRfXdsn7AwQBfwT7unrFhP8DewJf+49N+EX/7Pfrr5O20r4ev4p/Ck/e8JvnPBPaWIeAMOnumocRAFXuFwlhijgCperxBAFnHFBFHBmlMQU8BRIotXU2gxRQI1T0lJBFPBpMYgCwYkChZLYWmIuDPx/T7fTjQ3fEh9zQYALA3sOvMhVUEKIAj4HuEJ2lcmaQjGhJIEooIaVb9uXe9Kff+IvXPxz6/3fa9lQshC+lr9ows+e9HO3f/4ZX/cf1EtlnGH5gDfaEAW8cVPJBVHAmRJEAWdGSUwBUSCJVlNrM0QBNU5JSxWJKCD3ZFz464dL8lnxzKKk8RPtRUyB8MxWt/5BFnPgbqr54M+FSjr3+TgTCC6kzr1OC61iN54CoTUCBYdCIKsxBbawbfv4Wv4Nu4sj+vP/dzDPnFIvPsHPre+fWpjw557+70s6BfKDKBDKKaNFoYgpoIUZQmlEFkSBUMBpXihEAc0N5KN5fkQBXm1Wdh/wgTiWrJGIArH0LMJKIQqED7tqx2tU/4+7hEDA/AZEhT2jDqF2sbTgQhqoqA20ERAFAsWpVWFpFQX6B/qLt/AT7v7rCmv923v22NphWFX94ISfufYLl38hBOwr1v2Xl5VrZUO7xkAUDN+TyAAAIABJREFUSISZPDUSooAnbInIBFEgEWZy3UiIAq6RJSYDRIHEmMpVQyMVBbjHwE3XXkLz5h5b1Ei+K8H9f1xKzy651VXjdUkMUSA6S5R37RS7FdT/426qaHtHVDxQ1Uh7DmLiABMIeocfFEhjIAoEglHLQtIgCmxt30xvbnsj97v9DVqxbRmb/L9dkvfo2jE0ZUQugr9xws89AMbXT9TSVm4bBVHALbHkpIcokBxbuW0pRAG3xJKRHqJAMuzkpZUQBbxQ0z+PFqKA3JEgicsHEFNg6CB3u/uA3WnCI5Re+pWrbc+iund+n1tasGlpIU3nlDNZYMKLqGuvU8RniCkQ/kVIZa13+K2wriENMQV4UD8+6c9N/tnv9mVDtvO7jC6jJeynsrE6N+HnE/8iAWAa8aB/SX6pjDOIAt4sjJgC3rip5EJMAWdKWRAFvN6LONPTNwVEAX1t47dlfkQB7D7gl354+bUQBb5x8x303MvLE+kpAFEgPlFA1ly97W80bM3dTCBYVGhMz8hDqf2gi+iXL/XTGZ/8NDU2DXd1FrnxFMDuA9h9wNXgKpF49c6V4uk/n/jn3t+gXZ07h+QYXjuCZo4+jGaOPZQOGXMo9bzaSh876UwaN35SUE3RrhyIAuGZBKJAeGwhCjizhSjgzCiJKSAKJNFqam2GKKDGKWmpQhcFpBeAExirZQVOeXQ4DlEgflFAtqC8c1su7gATCCra3hUf/7T9SjpnVi9VzZzPYhDMVh4yEAWUUZHKZE29tGBT6uopwNf/y0n/oACwjKzW/Y8bNoEO4ZP/sbNpJhMA+O++I/YvApWFiYfKOIOngLfzB6KAN24qubJwbqpwKJUGooBfgnrmhyigp12CaBVEgSAo6ldG6KKAsct2MQX0w+KuRYgp4I5XFKnr1i3OLS3Y/NdCdd3j/4na9zufOvb7tGNgQjeiQBT9QR3BEYg6pgCf6Bsn/vzpPxcEuDBgfvHo/oeMZR4AYvJ/mPh7YsPk4Dqf8pIgCqTXwIgpkF7bZkEUSK/17HsGUSC9VvcjCnAq2H1Az7ERqSigJwL/rYIo4J9hWCVUb3+F6t6+l4atvZfKelpENQOVw6h92qepY//PUPe4oyyrhigQlkXiLzdMUYC7+stJvxQC+JIAq9eBo6YXnvznhIDDaFTd6PgBJbgFEAUSbDyHpkMUSK9tIQqk07YQBdJpV94riALptC1EgQDsClEgAIhhFzHQR8OYOFDHxIGazX8p1NYzeg61M3Ggg3kQ9FcPxh2AKBC2QeIrPyhRYFPbRuEBwIP/yR0AeFBA84tv58ef/B8yjrn/j865//NYAPVVDfFBSGnNEAVSaljWLYgC6bUtRIF02haiQDrtClEgvXaNVBRYvnIdzb/8O7Y0sfuAv4G2ft0aWrPqTTr59E96LiiIoHlR7T6g0kmriL9VO9/MeQ+su5fKO7bmimETN7m0oGviCeRGFAiCmUpfrNbHq+QLO43KWu+w22BXflAxBfh2f3IHALkVIN8W0PyqY14oRe7/43JLASrKKkJFkIV1yyrjDKKAt2GGmALeuKnkysK5qcKhVJosiALYfcDvKEF+nQj48RTA7gM6WbK4LZGKAsfNu4KOPWIWHTlnBv144eLCbgNnLbieTjrucLri4rP1JWXTMgQaHApGd1HA2OK6dx5gHgS/pZr3nyh83DtyBnXt/1mqnn0BbesZ6TgmIQqka/eBVTveYk/+X8/FAdjKdgDY8QY1d+4eMg5G1o4SLv85L4Cc+/9BbElAHK8sTDwgCoQ3siAKhMc2C+emX3oQBfwS1DM/PAX0tEsQrYIoEARF/cqIVBSQgQb3mzKJvvSNnxREAb5DgVEk0A+TfYsgCiRbFJCtr2xdK5YW8CUGcucCfqxj30+JpQWde821HQQQBZIpCmxrac+5/YvJPxMBduREgK6+ziG2nlA/KecBkA8CyLcBnDJ8mjaXqixMPCAKhDfcIAqExzYL56ZfehAF/BLUMz9EAT3tEkSrIAoEQVG/MmIRBebNPZa4QCCXC8htC5O4fICbFDEF9BvYflpU++4fqX7d76hm/ZJCMb2N+4ldC3j8gb6GKX6KR94YCLR1txYm/f/YuZyWM0+AZVvesGzJ1OH7iTX/fOIvtwEcXz8xhlajSrcEsHzALbHkpEdMgeTYym1LsyAKuGWShvQQBdJgRes++BEFeInYfUDPsRGpKMCXCcw4cAp977ovkPHvb9x8Bz338vKC54CeqOxbBVEgaRZzbi+PKTCSNlPHa3dTHRMIKptXFzJ17vNxEX+gc8o854KQIhYCq3asoJc3PU9/++AFWrbt77R21z8s23Hw6Bm5iT8PAMiEAL4EYESt85KRWDqFSh0JQBRwRJTYBBAFEms6x4ZDFHBElMgEEAUSaTalRkMUUMKUuESRigJmOtxbQL7uu+0GmjVdH3dcN5aEKOCGVjLSmgMN1rz/pAhMWLducaEDffWTqWPa+cx74HzqHX5QMjqW0la+tvll+tvmF+hvm16glzc+Tzs6txf1tLK8Muf+zyb/syfOpsMnzaEpDTOotqIupUSy2S2IAum1O0SB9NoWokA6bQtRIJ125b2CKJBO28YqCqQBKWIKDLVikgIN2o1Bu90Hyru20zAWe6Bu7W+patdykX1z/wRa0vc5mv/RKcJ7oL9mVChDG7sP5LD29HXnvAC4AMB+uTdAe++eIuZ7Ne5DR0w8hj7UPpv2HjuVTjrmE1TG71DYK6gtCUMxssdCs7BuGTEFPA4OhWyIKaAAyWOSLJybHtEUsmVBFMDuA35HCfLrRMCPKIDdB3SyZHFbIhUFZKBBHlMgLS+IAtkSBYy9rdn8V7a14e+oefWf6eGOj9MXhy0Uhzv3Pl2IAx1TzqKBqsbAhnpWRYGWrmaDCJATAwYGBoq4Hsii/n9kwlH0kYlH0xGTj6EpTTmvo6C2JAzMiCEVlIWJB0SBkAYPKxaiQHhss3Bu+qUHUcAvQT3zw1NAT7sE0SqIAkFQ1K8MiAI+bQJRILuigOz5zs3v0F8f/wNdNOlZqt34+CAQ9o3Yuc9Z1DF1HnufRwMV1b5GW1ZEgc1tH4iJP18O8PIHz9Pyba8P4XbYuDk5AYB5A3xk0tE0btgES7YQBXwNOa0yQxQIzxwQBcJjC1HAmS1EAWdGSUwBUSCJVlNrM0QBNU5JSxWpKMCDC5503OF0xcVnJ41TyfYipkCqzCk6Y7d8wKmn5Z3bqG7DEqplOxfUbFpaSD5QXkOdTBzoYB4EncyDAK9BAu/sXju4FICJAeaggOVl5bnJPxcBJrH3CUdTY02TZ4RpXD7gGUbKMiKmQMoMaugOYgqk17ZZEAXSaz37nkEUSK/V/YgCnAp2H9BzbEQqCixfuY6+9I2fJHaXATsTQhTQc3D7aZVXUcBYZ8We96l2w0NUxwSC6q3/NygQVDWJpQVcJOjc6zQ/zUxk3rd2LBdxALgXAPcG2Nj6XlE/GqobmQDAlgKwyb8UASorqgLrK0SBwFBqVxBEAe1MEliDIAoEhlK7giAKaGeSQBoEUSAQjFoWAlFAS7P4blSkooBxtwGrlq94ZpHvDsVRAESBOKiHW2cQooCxhZWt65hAwDwImEhQve1vhUP9taNz3gNsmUHX5JPC7VRMpb+6+aWcAJBfErCzY0dRS8YOGze4FIB5A8we/+FQWwpRIFS8sRYOUSBW/KFWDlEgVLyxFg5RIFb8oVUOUSA0tLEXDFEgdhOE0oBIRYFQehBzoYgpMNQAad59wGq47di+lf7y1CN09vwFSqOxsnmV8B7gSwyqdi0r5OkbNkksLeAxCLrHHzekrCTEFOjq68wtBRAiwIvivbOvo6gv+zRNLSwF+DDzBjh49Awlbl4SIaaAF2p65kFMgfDsgpgC4bFFTAFntlkQBbD7gPM4QIrkEPAjCmD3AX3tHKkoYLf7wK2/fJDu/+PSRC4rgCgAUcCtKGAkVrVzWW6JAfMiqNy9clAgaJxa8CDoHnek+FxXUeCZdU/S6sdfo0fGPSEEAfPrIL4zAI8FwLwA+O+Upn0juyJCFIgMdegVQRQIDzFEgfDYQhRwZgtRwJlRElPAUyCJVlNrM0QBNU5JS6WFKLDksefo+u/fSUlcPgBRAKKAH1HASK96+yvCe4CLBJWtbxcO9TYdKOIPPLVzOtWN2Y9mzQ7Xvd7pIrajczstXf84Pb3hCXr63cepp6ub/o39fJ/98NfscYcXRAAeE2Bs3TinIkM7DlEgNLSRFwxRIDzkEAXCYwtRwJktRAFnRklMAVEgiVZTazNEATVOSUulhSjwjZvvoOdeXp5ITwFucMQUSNqwd25v0DEFnGssTlG95fncLgbvPkQVbYOB+HpHTKfOySez+AOnUNekE90W6zk9Dw74NBMCljIh4MUPnisqZ+aYQ+mEKafQkROPpSMmH00NVY2e64kiI2IKREE5njoQUyAe7lHUipgCUVCOp44siALxkI23VogC8fIPs3Y/ogBvF3YfCNM63ssOXRSQXgBOTbzp2kto3txjnZKFdrzUEga+leLa9RtF3ftPnUwPLbqpqB0QBUIzS2wFxy0KGDvOtzaUuxiUd24tHOqvHs6EASYO7HUK28XgVOqvHRMYr4GBAVr67pNMBMh5BKxvHvRcKGPf9CfsczITAk6lE5kYMHX4foHVG0VBEAWioBxPHRAF4uEeRa0QBaKgHE8dEAXi4R52rRAFwiYcX/kQBeJjH2bNoYsCxsbbxRQIs4NOZRtFi1EjGod4K1x05Q9ox86WghDABYLRo5rorluuKRQNUcCJcvKO6yQKGOlVb3mWat9/gmo2Pk5VO98sAts94bicFwETCHpGznINfXPbB0wIeEL8Pr3+CerobS+UMaFhEhMCThEeAVwIqKsc5rp8XTJAFNDFEsG3A6JA8Ex1KRGigC6WCL4dEAWCZ6pDiRAFdLBCOG2AKBAO17hLjVQUiLuzpeq38xQ4bt4V9LXLzit4MXAR4ccLFxfEA8QUGEoVuw+EM9LN6+MrW9ZSDRMIaplAULPxyaJKe5v2z3kQ5D0J7Fr0+pZXhTfA0veepFc3vVSU7LBxcwreAIdPyAU7tHqprPUOh4hzqYgp4MwoKSlUxhlEAW/WREwBb9xUciGmgDOlLIgC2H3AeRwgRXII+BEFsPuAvnaGKJC3jZUosHzlOpp/+XfovttuoFnTp4mU5s8gCkAUCCrQoNNlotTuA2W9e/IeBMyL4P3HqaJjc6G4gcp6tryAxyA4mdpYHIInty5jSwIep2eYEPB+y7uFdFUV1WJZwIlsWQD3CNircR+nJonjKpM1pYJCSARRIASoMRWpMs4gCngzDkQBb9xUckEUcKYEUcCZURJTwFMgiVZTazNEATVOSUsVuSjAn7zv3N1qySnO3Qf8iALXXvdN6u7pd2X7h5f8nmbMPJT2P+BAV/lKJV67ZjW9tWIZnTnvU57L3Lp1Cz3x6P+jz15wsecyWpqb6f7Fv6FLvvBlz2XwjLf88Ga68qrrfJVx5x0/p3PP+yw1DR/uqpzy8jKqra6g9s5ex3xBMHOshCV4ZulT1NTYRHM+fIRj8orNL1Al2xmg4t3H6L0tr9GjrBuP9hE9xoZpz8Bg9n2GT6GT9z2V/c6lk6edSlXlVY5lmxN0dXXSnbf/gr781Std5w07gxWzyspyqmT27exmQFLy+s2vfkmnnPZxGjdufEp6NLQbKuOspqqCBtiP2+txaqEpduy1V16mltYWOv6EkxRzRJ+ML/vp6R2g3j5337XRt7S4xiycm34Z19dVsu/aPuKxbNL68novkmgeZUQNtVXU1tGT6G6g8UMJVLB7qBrFe2Rzbn5vf+ONNwKrhgQiFQWs1uPrwsSrKMDb39XTh5tQXQwZUDvciAIBVRloMS9tfIGefOdxemLdY/Q6EwWMr6PLiU6rZL8VRHNGTqG+feZS796nUu8+pxJ5EAUCbXgEhaVRFIgAWyKqgCiQCDN5amRSRQFPnc1YpiyIAhkzaa67EAVSa3Y/ogCH0jjM/QOo1MLUqGORigI6BhqUtvAaU4DnR6BBjUZ0QE3RNdCgXffae/aI7QKfFkECH6et7YPLB4ZV1ed3CziFPrbXibTP7mViiUHtB0+y7Q4Hlw8MsOUDYqtD9tvJfvsa1JYPBIQ8smIQaDAy1JFXhOUDkSOPrEIEGowMdeQVZWH5QORQNagQywc0MEJITfCzfIA3CVsShmQYn8VCFMgDtBMFsPuAzxGW0OxJEAXe2b1WbBe4lC0TWLqhONAg3yaQ7xIgtw20M0PV9ldZLAIWqJAJBNVbiwMN9ow5XIgDXCToHmcfaDBpJoYokDSLqbcXooA6q6SlhCiQNIuptxeigDqrJKWEKJAka7lrK0QBd7ySkjpSUYAvHzjpuMPpiovP1oaPcUtC2agzTzmGvnfdFwpt5O1eu36j+H//qZML2xPy/xFocKgpsftAOMObB83b1r+dllcuZx4Bj9PK7cVbEh416djcloFTT6UZo91vSVjR/gHbxYDvZsCDFT5BZYYtCfuGTcp5EPCAhex3oGJwS0KVAHDhEHEuFYEGnRklJYXKOIMo4M2aCDTojZtKLgQadKaUBVEAuw84jwOkSA4BP6IAdh/Q186RigLm7fz0xaLeMogCEAXC3n3gufeW0iPrHqKWldtpU+8H9CL74a+mmuFsWQATAfIeAaPrxqgPXKeULOAT3+ZQbHfIBILK1rcHczD5X3oQcIGgvXov+t09C+mCS//VqdTIj0MUiBx5aBVCFAgNLUEUCI8tRAFnthAFnBklMQU8BZJoNbU2QxRQ45S0VJGKAjymQKlXnLsPeDUcRAGIAmGIAi9/8DwTApbQI28/RBtb3xOQ57KfqrpqmnjwVDqRiQHH7X2i12HrOl/VruW5OARMIKje8lxR/tYRh9PPN3+cLv34h6h7/NE0UNXouvywMkAUCIts9OVCFAiPOUSB8NhCFHBmC1HAmVESU0AUSKLV1NoMUUCNU9JSRSoKJA2OansRaFCVVHLSxRFT4PUtr9Cf3s4JAeubB5/M7zfiQDpj/3l0+n7zaNbY2bFDLO/anotDwASCGuZJUN7dUtQmHouga/wxLA7B0UwkOIb6a8fF3mZjAxBTQCtzBNoYLB8IFKdWhSGmgFbmCLQxWRAFAgWWkMIgCiTEUB6a6UcU4NUh0KAH6BFkgSgQAGSIAgFA1KyIqESBFduXCRHgESYGrN65skBhn6apQgQ4fdpZdPhEvYP81XzwNAtU+DRVb3uBeRG8MMSSvSOmD4oETCjoa9w3VmtDFIgVf6iVQxQIFW+shUMUiBV/qJVDFAgVb2yFQxSIDX3oFUMUCB1xLBVELgoYg/bddO0lNG/uscSXFRw5Zzrddcs1sUDwWylEAb8E9csfpiiwZtcqemTtEuEVwEUB+ZrQMEmIAKczr4CjJx2nHxSFFpX1dbJdDLg48Dx7f1G8l/V1FOXsa5xK3WOZF8GEY6iLvfeOnKFQcnBJIAoEx1K3kiAK6GaR4NoDUSA4lrqVBFFAN4sE0x6IAsFw1LEUiAI6WsV/myIVBbggMHpUk5j8HzfvCvraZecJUcBuO0D/3Qu/BMQUGMoYuw8MZbKhZR39iQkB3Cvg71v+Vkgwqm40EwL40oCz6KP7nFRywFqtjw9/hDvX4LTWm291WL2ViwRMLGC/5Z07igrlywt4LILucWzJAX8f82HnShVTIKaAIqgEJHMaZ7wLEAW8GRIxBbxxU8mFmALOlLIgCmD3AedxgBTJIeBHFMDuA/raOVJRgHsE3HfbDTRr+rQiUUBuC4hAg/4Gyvp1a2jNqjfp5NM/6bmgIILmQRTI4f+g9X2xawD3Cnhp0/8VbNJY3USnMRHgDLY84KSppynbKqmigLmDPGghX2YgvAnYkoOKtlwgRfnigQq7xx1ViEnAYxMMlFcpczImhCjgCZuWmSAKhGcWiALhsYUo4MwWooAzoySmgKdAEq2m1maIAmqckpYqUlGAewf84nv/PkQUgKdAMMMGosBQjl7VeTfLB4xCyvaObSI+APcKeO79pYUGVZfXFIIFcq8AL6+0iALmvle2rM0vOch5ElQ2/6M4SVl5zouABy5kSw740oN+JqyovCAKqFBKRhqIAuHZCaJAeGwhCjizhSjgzCiJKSAKJNFqam2GKKDGKWmpIhUFvnHzHfTcy8vp2SW3FjwF9psyieZf/h0685Rj6HvXfSFp/ER7EVMgkWYr2Wg3okBbdyv9cc3/Cq+Apzc8Xii3jH0jyhgBZ7AlAlUV1ekDFUKPKto/yHkS8MCFm5+nqp2vD6mlZ8ycnEiQX3LQVzdBuSWIKaCMKnEJsXwgcSZTbjBiCiijSlzCLIgCiTNKAA2GKBAARE2L8CMK8C5h9wE9DRupKMARyKUCRhyXfe5MuuLis/UkpNAqiAIKkBKWREUUeGHjX+n3//gd+72Xevt6Cj08eerpwivgNBY0sKG6MWE916+55d3NuZgEXCjIxyaggYGihvIdDoxLDnobp9l2BKKAfjYOqkUQBYIiqV85EAX0s0lQLYIoEBRJvcqBKKCXPYJsDUSBIGnqU1bkooA+XQ+uJRAFgmOpS0l2osCOzu30vyvvpQdW/Zbe2rG80FweJJBvIcjjBIysHaVLN1LZjrK+7sHAhUIoeIHKevcU9bWvYZ/BwIVjj6CekYcS8TsU9oIokMphIToFUSC9toUokF7bQhRIp20hCqTTrrxXEAXSadtIRYGLrvwBvfTaSjIHFEzyloTYfWDoiZHGQINLNzxJ/8s8Av6wenGhwxMbJtOnDjqf5o4/g9a9/BadPX9BqFeJtMYUCAJa9baXC7sb8CUH5V3bRbGPd82l4eW76aiaV6hn1GHsl4kD42ZTxYQ5tLNuBg1U1AVRfexlZGHdMmIKhDfMEFMgPLZZODf90suCKOA1vpFftnHmhygQJ/1w6/YjCmD3gXBt46f0SEUBHmjw3E+cMGSpAAIN+jHhYF4EGhzK0esXMfcUaBvYTLe/vIh+v+peenv36kLhp077OP0LEwO4VwB/BbFjg8oIgCigQimXpmrXCuFN8Nzf19HInnfomL6HLTP3jpzBhILZQizI/R5G/TUj1SvSJGUWJh4QBcIbbBAFwmObhXPTLz2IAn4J6pkfooCedgmiVRAFgqCoXxmRigLcI+Cmay+heXOPLSKBLQmDGRgQBYIRBR5b90d6cPXvxA4C8jV1+H7MK+DT9KmDP0N7N00pqgiiQBf97p6FdMGl/xrMQA6wFCmkHDrzICYULKOq7W9QXfNyqtzxOpWzv61evY37Uc/oQ6mXLTnoGcMEA/beN2xigK0KvqgsTDwgCgQ/bmSJEAXCY5uFc9MvPYgCfgnqmR+igJ52CaJVEAWCoKhfGZGKAmn0FOAmRUwB/Qa22xa907yWxQm4l/6X/b7f+m4h+5kHfIoJAefTx6bMdVsk0mtKoBBToKWd7WzwRl4seL0gGpT1dw5ped+wSbnlB6PZLxMJerloUCKYoaZdT32zEFMgvSZGTIH02jYLokB6rWffM4gC6bW6H1GAU8HuA3qOjUhFAb5MYOGvH6b7bruBZk3PRQdfvnKd2JIwyTsQQBTQc3CrtOqhNQ+w5QG/ZVsJPlFIfvDoGXTe9M/SxR++gCp6k+dKrtLvLKdxCjRYuestsQ2i9Cyo2vUGi1GwewiyfhZQsmdkLk6BEAuYaMB3QcArPgIQBeJjH3bNEAXCJhxf+RAF4mMfZs0QBcKkG2/ZEAXi5R9W7ZGKArwTVlsSWi0pCKvDYZQLUSAMquGVuXL7m2IbQR44cFv7VlFReVm5iBPAlwgcu/cJpLIlYXgtRMlhEnASBazqrmx9m6p2sOUHzLOgknsX7HiDKjo2D0k6UDGMLTnIeRMUPAt4cMOyijC7hLLzBCAKpHcoQBRIr20hCqTTthAF0mlX3iuIAum0beSiQNowYveBoRbVcfeBYQ0NQgTgSwSe3/iXQqMPGzdHxAnguwg01QwvfO5GFEBMAf1jCsya/eGCbb2IAlbXrYo9G3PeBEwgEMsQdi6jitZ3hiZlgpMQCfLxCWRQw4GqhsAuh1lYt4yYAoENlyEFIaZAeGyzcG76pZcFUcBr0GO/bOPMD1EgTvrh1u1HFMDuA+Haxk/pEAX80GN5IQroLQrcc/d/07q936P71v2aWrtbRGPrKocxr4BP0zlMDPjwxKMsRwBEAfUTQ2Wypl5asCmtdmwIShSwaml5504mFORFAulZsHulZaf4UgMhFrD4BLntEtnOB7WjPQHIwsRDZZzBU8DT8CGIAt64qeTKwrmpwqFUGogCfgnqmR+igJ52CaJVEAWCoKhfGZGLAjzY4M7drZYkVjyzSD9CDi2CKKCnKPCH1YvptyvupiM3zqFF7Gc3+zly0j/Rv7CggXyJQE1FbUnLQhRQPxVVJmvqpQWbMmpRwKr1Zb17CksPjJ4FNNA/JHlf49S8QDC4/KBv2GRHKFmYeKiMM4gCjkPFMgFEAW/cVHJl4dxU4QBR4HY6Y958amwa9Ej0y033/BAFdLeQ9/ZBFPDOTueckYoCZy24nkaPaqK7brlGZyau24aYAq6RhZJhe8c2unfFXUIMkDsI8CUB5x78WbFEYNbY2cr1uhEFlAtFQi0IhOkpoNxBJgiIJQd86QFfgiD+XkZcQDC/+uomiN0Oekax7RF5UEP229u0v3JVWUoIUSC91kZMgfTaNgueAum1nn3PIAqk1+p+RAFOBbsP6Dk2IhUFZh6/gJIeVNDKjBAF4h3cf9/8N7p35d1MEFhUaMghYw+j82dcSJ9hv5UVVa4bCFHANbLEZNBCFLChVcmWGkiBILddItv5gC1JML/6a0bkdj7gWyOKJQizqXf4gTRQ7n6sJ8ZwCg2FKKAAKaFJIAok1HAKzYYooAApgUkgCiTQaIpNhiigCCphySAKBGAwiAIBQPQzeISgAAAgAElEQVRQxMNrfi+8Ap57f2kh92nTzqTzZ15EJ045xUOJg1kgCvjCp3VmnUUBK3A8eCEPYmj0LOBBDq1efQ37UG/jNOpr3Jd5E7D3Bvk+jfqrm7S2SxCNgygQBEU9y4AooKddgmgVRIEgKOpXBkQB/WwSVIsgCgRFUq9yIhUF+PKBk447nK64+Gy9KPhoDWIKDIUX5u4Du9hT09+yJQL3MjFgQ0su0ntDVSOdf0jOK2D/kQcVNchrxF83ogB2H8jm7gM+Lhu+s/LtEPnSA7E9Ivv91T/2oXlVi2lC+dBtEmVl/TVjioUCLhyw3z4uIgyb6LtNYReAmALhEUZMgfDYIqaAM9ssiAJe70Wc6embAqKAvrbx2zI/ogB2H/BLP7z8kYoCSx57jn68cDE9u+TW8HoUcckQBaIRBd7Y+lohXsAADYhKp485hAkBFzHPgAW2gQO9fhFDFFA/kVQma+qlBZtSh0CDwfbIujQx8fjYXBpf08a2RVxPla3rxPaIufd17H29ZbwCWdpAZT0TCKYKgaDgacDFgiYmHDBvA2LbKsb9Uhln8BTwZiWIAt64qeSCKOBMCaKAM6MkpoAokESrqbUZooAap6SlilQU4DEFSr2w+4C/4bN+3Rpas+pNOvn0T3ouKIin3kF6Ckycu79YIvDX9/5c6NOp+36cCQEX0klTT3PsJ0QBR0S+E6hM1nxX4rGATIkCJ51Oo8eMsyVV0bGJKlqYQMB+K9qYcCDemXDA3su7tpckLIQCthyht4EJB/xdLlFgngYDlQ0ereMum8o4gyjgjqlMDVHAGzeVXBAFnClBFHBmlMQUEAWSaDW1NkMUUOOUtFSRigJJg6PaXsQUUCWllq63v5fuXraQfvXmHfTO7rUi07CqevoMEwI+zZYIHDRqulpBPlK58RTwUQ2yxkAgaTEFokBU3t2c9yh4x/DOBAMmGlS0bijZhP668WJZQm8Dj2EwNbdEgXscsPf+2rFRNL9QB0SBSHFHWhliCkSKO9LKsiAKRApUk8ogCmhiiBCa4UcU4M3B7gMhGCWAIiEKBAARokAAEFkRzV276a43fkF3L19IOzpyTy4PHj1DCAHnz1gghIGoXhAFoiIdfT0QBdwxL+vrznkUsOUIg0sSBv8v6+u0LXCgqikft4DHL8gJBUI4EJ4GU901RCE1RAEFSAlNAlEgoYZTaDZEAQVICUwCUSCBRlNsMkQBRVAJSxa5KMDjClz//TuLMCV9m0KIAv5G/cbW9+iuZbcxQeA26u7vEoUdPek4uvCwy+mM/eb5K9xjbogCHsElIBtEgWCNVNH2Xs6jgC9NYMsSRAyD/NKE8q5d9pWVV4p4BSJuARcJ8jslSMFgoKLOdUMhCrhGlpgMEAUSYyrXDYUo4BpZIjJAFEiEmTw1EqKAJ2zaZ4pUFLj1lw/Swl8/TPfddgPNmj5NwFm+ch3Nv/w7dNnnzkzkrgQINDh0jKvGFFi14y22TOA2+s2KXxYKOXnq6XQREwP+ee+PEY9QeulXrvZ1EiGmgC98SplV1norFRRCIsQUCAGqiyLLu3bmgh3mYxdUsB1Dch4H7LN2620VZfF99ZPzgQ/5Dgn70p66qbRo6Ua68DPnUl/dBCImKphfEAVcGMeQFDEFvHFTyYWYAs6UsiAKeL0XcaanbwqIAvraxm/L/IgC2H3AL/3w8kcqChw37wo69xMnDJn8c7Hg/j8uTeSuBBAF3IsCr25+SXgFLFlzfyHzJw88jy469HKaM+GIwmcQBYrZWk1ww7s0qJcMUUCdVVgpkzjxKOvrYN4FubgFhaCHYreE3O4JxGKLGF+dA7X00/Z/o2vqvy8+5vEKuDjQP2w8e59IPLZB1fDJ7P8JtKdijHjvqx1PA1XRBEIMy7ZRlAtRIDzKSTw3w6NhXTJEgaiJR1MfRIFoOMdRC0SBOKiHX2ekogDffcBqqYBcUoDdB/wZXPfdB/7y7lNimcBT6x8tdPRzh1xCF866nA4aPTR4IEQBiAL+zggieAr4JRhf/sLWivmdEnqb36Xb/3EQfX3MXczLYDNrWG5rUqcXj2vQxwUCLiAw4YD/Ld7l/1xQ4J/VjHIqKrXHIQqEZ1qIAs5sIQo4M0piCogCSbSaWpshCqhxSlqqSEWBJHoKfOPmO+jhJ54fYlejgIGYAqWH/Z/W/kEED3xh47MiYU1FrfAK4MsEJjXspeU5g5gCWpolkEYhpkAgGGMvpLxjC1V0bKbydv7OtltkQkFt7zai9k000Mr+zx/jHgkqr4HymrzXgUE0kGJC3utAeB/wpQtl5SpFIk2ABBBTIECYmhWVBVFAM+SRNAeiQCSYY6nEjyjAG4zdB2Ixm2OlkYoCSYwpwEWBt1ZvoIcW3WQLE6KANZrFK+8RywTe3P6GSDCmbixdeOhlTBD4EjXVDHccnHEmgCgQJ/1w64YoEC7fOEu3iinAt1ssZ0KBEAk6mYDAxINy9lvBRIVy9pn4v5P9st1PVF/9teNyHgcFDwQuFoxnHgjsXXoisPeBimGqRSKdAwGIAukdIhAF0mlbiALptCvvFUSBdNo2UlGAI0za7gMQBdwP/HuW/w/d/vp/0/rmt0XmKWwbMu4VcOGsy6iivMJ9gTHkgCgQA/SIqoQoEBHoGKrxE2iQexTkvA7yogETEAqiQV48EMeYmKD66q8enhMKROyDvHBg9DqozX3eXzNStcjMpoMokF7TQxRIp20hCqTTrhAF0mvXyEWBpKE0Lx8YNaKxKCAiAg0OWvTh1b+nW1/9IX2w4z1awH6eHPO0WCYwf8YFnsyOmALF2BBo0P0wQkwB98x0zaES0NKPKKDe74G8d4HB64B5IhS8EAzeCGX5LVadyh5gS6oKooEQEYxeB3nvAxY0kXshsLULTsW5Po6YAq6RKWdATAFnVFkQBbD7gPM4QIrkEPDjKYDdB/S1M0QBl7Y5a8H1IodcTsBFgRtvvNFlKUSLFy+mww47jA4++GDXee0yrFq1it544w0677zzPJe5efNmeuihh+iLX/yichlPvv0kfe+579HS9UtFniNGH0FndZxF1111nXIZVgm9sjWW9dOf/pQuuOACGjFihK+2lMrshZmXxjz++OM0fPhwOuqoo7xkDy1PZ2cncc7XXHNNaHV4LVhXZl77Y5fv9ttvp7POOosmTOCTxnS+dB5ntsQ7dxK1bWJxDlhgxD3sXf7N3/n/e/KfdzWrG61+IlE9szN/b2C/XCjg78bP+fHKOuUyX3zxRWpubqZTTz1VOQ8SqhHIwrmpRiLbqaK4F8k2YfQ+KQSCuLdPSl+T1s5IRAEZS+Cyz51puR3hwl8/TFbHdIRp3ikhy54Cy7b+nX7GPAP+9PYSYapx7Eb0isOvonOmnk9/WnIfzf+8urBgZWt4ChRTgaeA+ysCPAXcM9M1hz6eAsETKutrH4x1IGIc5L0QxDvzQuBBFcXnW5Ur768ZwZYuTBwa66BoFwa28wJb4gBPAWWsrhPCU8AZGTwFnBklMQWWDyTRampthqeAGqekpYpEFOBP10ePaqK7brF+knjRlT+gHTtbSgbz0wWs1faJWQs0+G7zeiEG/Patu4VZqitqmBjwdfrqh6+myvIqXUzlqx2IKeALn9aZEVNAa/P4alw0ywd8NdFf5oG+4qULXDRgHgci9oEMnJh/L+vrVqproKIuH/dgDPHtGweqGqhfvDcywSD3PsDe+/k7+7y/mr1XsmP5/8XximqluvwkQkwBP/T0zpsFUUBvC4TTOogC4XDVoVQ/ogBvP3Yf0MGKQ9sQiSgw8/gFdNO1l9C8ucdaUrCaaOuCi2+j+OySWwvN4f8fMG2vIoEjK6JAa1eLiBnw89d+XOBx8WFfoiuYGDC2bpwuJgukHRAFAsGoZSEQBbQ0SyCNSr0o4IJSeeeOws4KOS+DvLeB9DrICwllPS0uSrVOyoWFASYW9DOxoEhMkCKC4X2gkokOebFBiA88X/691G4NEAV8m0nbAiAKaGsaXw2DKOALn9aZIQpobR7PjYMo4ICOezmsXb+xkOrIOdOHeDxkQRT4xWu3CEGgJb/29V8O+jQTA66iA0YGFxPB8ygOISNEgRCgalIkRAFNDBFCMyAKuIda1tuWEw+6dhEXCMp6Wqm82/DOjvPPy7tbc+/seBk7Xt6be+fpy/p73FdslaO8stgjgYsJXGhgIkJ1/QjqKa9nv3lPBu6xwI8bPRm42JD3YiA+I8ErEQQgCiTCTK4bCVHANbLEZIAokBhTuWpoJKIAf7r+tcvOK+kp8OOFi4ueyLvqRYyJ0x5T4N4Vi8RSgQ0t7wjKJ045VSwT+MjEo22pt7Y0I6ZACGMSMQXcQ0VMAffMdM2R5pgCcTP3G1OAb+dYJCZwcaEgIuRFBSkm5N9FeiFCtOXfmbjQ2x4YisJSB4NwYOulIIUF5sUglkoIj4ecF8OAzyVxiCngbNIsiALYfcB5HCBFcgj4EQWw+4C+do5EFODb+r21eoNtzACnmAP64iNKqyhQ+5GRQgx4Y+trAv+cCUcIMeDkqac7mgOigCMiTwkgCrjHBlHAPTNdc0AUCM8yfkWBoFrGPQ4KYoLwRGDCQd4joaG8nXo6mqmP/ebEhLxHA/dk4J4LXGwweDQE1aaBymG5JRHCY8Gw1MHspcA9FPLeC4V0LN/9f3qGjj/+RBo9bq9IYi8E1e8oy4EoECXt6OqCp0B0rKOuCaJA1MSjqS8SUYB3hXsL8Jdxfb78fOfuVlrxzKJoehxwLWkTBZa+9Si9/tyL9KPuHwpS00YcwMQAtqPAwZ9VJgdRQBmVq4QQBVzhEokhCrhnpmsOiALhWUYXUaBUD13FFBgYYF4H3BMhv9TB+J73YhDCAhMU5FKJwpIIg7DAj5f1+VsacXv7ZXRW7RKaUM62nywrZ54HtWyJQw0TCGqJWJBe8T9/r2Tv7G/ix8pzx3O/Newz9l6WT8PTirz5fIUyZF5ePi+rWryTKD9fJyuDyivCG0geS4Yo4BGc5tkgCmhuIB/NgyjgA57GWSMTBTgD7jHw8BPPF+GwWqOvMS/LpqUhpsDK7W+KmAEPrXlA9HFU3Wj66uFX06Wzc2JO1l6IKZBeiyOmQHpti5gC6bWtK1EgQAx8u0jhsWAUE4RXQl50MMZbyC+ZMHoxCNGhr5OI/Zb1q+0IEWDzhxQllkNwkYALD1w8kMKD8f/834V0eSEiJzJwUcIkWkiBoihfXojICxyirLzgYW5UFkSBMG2qa9kQBXS1jP92+REFeO3YfcC/DcIoIVJRIIwO6FBmkkWBTW0bhRjwq+V3CJTl7EkG302AbzFYx9wms/qCKJBey0MUSK9tIQqk17ZxiQKBEh3oZ8JAFxMJ+C8TCnqZUCDEAsNn+WPic358gAkJMh3/TOaVeQpl8PJYOeLzfDp2jPrz5fNjvE62rWW8r7KC50JOYKiliuo66i2rpv68VwP7wOApkfeWkN4TwguCeTwIkSHvEZH3qhAeFTydQeAQ3hjS64J7T3AvCxbQEq/wCUAUCJ9xXDVAFIiLfLj1QhQIgG8SRYEOFtDp1ld/JOIG9PXnbhIumPUFJgZcRRMbJgdAJdlFQBRItv1KtR6iQHptC1EgvbZNhSiggXnEThEGcYGLCDkxIS9C5EUKkuIEFx2k0MBFBiZSCLFCihY8vyyPp+NpRBm8vLxIIcWJ/P+xY2CigHEZB1+aIZZtFISGvBAhl2YIj4qcZ4VYjpFfmpErQy4DMYgPrCyRTooWMl0ZEyPYgxcqq2BlsHdiv2w5xwCxJR3ic/5Zel4QBdJjS3NPIAqk07YQBXzaNYkxBf7n9VuFd8COju2i92cdcI4QA6aPOYR2bN9Kf3nqETp7/gLPZBBTwDO6khkRU8A9V8QUcM9M1xyIKRCeZVIXUyA8VK5Lxu4DJmQ83kNeMKC82DCmfoB2s9hSA71sFwux1IIJD0JokL954SEvOgghoyBKDKYVHhVGTwlRlvScyHtP8Lz9va7t6DfDT9v/jS6oXUQjyneXKIptoylEgpxwYBYPxP95ISF3nMWo4IICjxMh/mdeGPJ/lm6g8DkXG7gQweNJcCHCkE8KE/KYrDcvXuTqyIkXog5T+8TxfFt42YU68+U11tdSS2e/SQBh/RTCSL49hb7K9pmEEnOd8n+Rn6WVgopoo0Xf8uXn2ifZmphgC1NXQ9yPKIDdB1yhjjQxRAGfuJMkCjyw6jfCO+DtXatFrz+6z0limcDRk/+5QAGiQA6FG0+BIJipDEOIAiqUitNAFHDPTNccEAXCswxEgfDYQhRwZht5TAEmChQ8GfJeDYWlF0JYyAkIOZFBLtnIL78oeFkMelcI4UF6WuSXdRREi/yxn207hz7X9GBOFGBLOMr6+USZ/TJPzTJi3ppsaYn4xSseAgVxwyBMFLw38mKIFEq4+DBgFEDywokUH2RZQ9LxsplwY0hXEEdYeUJwKQg3uXYY/xf5pGBUJIzkvEzEcSne8Lzyf2M5vA88rzxm7If0YhH15AQq0T7hwSIZ5ISXqspKqq+voV2tbOwahJZBkcpYf16sydd9x20/oxtvvDEeO6PWkgQgCvgcIEkQBZ5c/4jwDHh100uit4eNm0NfYZ4Bp+931pDeBzHBhaeAz0Flkx2igHuuEAXcM9M1B0SB8CwDUSA8thAFnNlGLgo4NynwFPfdczudMW8+NTYNL1H2QF4k4AIBm2xxwUCKBfx/LibkhQRxnMeo4IICXwIq/mdeGPJ/lq6s8DkXG7gQwZeKciHCkE8KE/KYrEfUK+vIiReFNvE8+XSiDfl0vOxCnbztZf1UX11Ge9qZwFIkgLB+CmEk3x5ZZ6F9JqFECCeGOuX/+TblmBjbm2ci65RtFe0bTFfEhLHDKxoC3277FkSBaFC7rgWigGtkQzPoGlPgb5teEGLAn9c/Jho9pWlfIQacP3NBAL1OdxFuPAXSTSJ9vUNMgfTZVPYIMQXSa1vEFEivbbMgCqTXevY9S1RMgYK4IYUTgyCTF1pyAk1ecGCCx6AAwkUWC6GEixbGdHmBJyeiSO+QYnFkULjJtcP4v8gn6zEKI+KzvDgjxRueV7a1INYYvFOs+pHvX66enEAlxBvhwSJFqkGhqIKV28eX4hgFGbNYJISefB5eDvu/dfY3qOn4b2bxlNC+zxAFAjCRbqLAml2rWADBH9HvV90retdUM1zEDPjSnCsD6G02ioAokF47QxRIr20hCqTXthAF0mtbiALptG2iRIF0miC0XvmJKcAbhS0JQzONr4IhCvjCl8usiyiwrWOr2E3gztd/XujVl+d8TQgCjTVNAfQ0O0VAFEivrSEKpNe2EAXSa1uIAum1LUSBdNoWokA67cp7BVEgnbaFKODTrrrEFPj1m3fS4ucW0UG9B9J97OczMy4USwX2GT7VVQ8RUyCHy40oEAQzFSMhpoAKpeI0iCngnpmuORBTIDzLIKZAeGwRU8CZbRZEAbWYAs6skpQCokCSrOWurX5EAew+4I51lKkhCvikHbco8NaO5XTz89+kpRuepIPZz6n1p9HcMz5Fh477kKeeBTHBRaBBT+gdM0EUcEQ0JAFEAffMdM0BUSA8y0AUCI8tRAFnthAFnBklMQVEgSRaTa3NEAXUOCUtFUQBnxaLUxT4ycs3049e/q7owbj6CXT1/tfRmNbRdPLpn/TcK4gCOXTwFFAfQiqTNfXSgk0JUSBYnnGWpjLOsHzAm4UgCnjjppILooAzJYgCzoySmAKiQBKtptZmiAJqnJKWCqJAABaLOqbAX9/7M/MO+A9avu110frPHXIJXX/Md6mxGnEDAjCna1EgqDpRTjQEEFMgGs5x1AJRIA7q0dSJmALRcI6jliyIAnFwjbtOiAJxWyC8+v2IArxVCDQYnm38lAxRwA+9fN6oRIE9PW1CDFi0/HZR84wxs+i6o79LJ0w5OYBeoAgjATeeAiCXLAIQBZJlLzethSjghlay0kIUSJa93LQWooAbWslJC1EgObZy21KIAm6JJSM9RIEA7BSFKPDg6vuEILCpbaNo8f/f3v3H+lXWdwB/EgNbNim1uIxZMmpXGEU7CMsKJcUsMwESF9t1yej+UDomAomsGSi/mpUJKQibTFITQISAGge6YMuE8StOVyJoIpEA0o1aSiIDCYVStlE2Tdbzdd+722/vvec55znnnvN87wv/svd5nvP5vj7ntN/zvuf7fP9y+RXhk8t9z2cD7ZtyCaFAW7LdrysU6L4HbVUgFGhLtvt1hQLd96CtCoQCbcl2u65QoFv/No8uFGhTt7u1hQKJ9m3vKfDC3ucHYcA3d9wzqPQDv/nB/U8HXB2W/dqJB1W+a+dz4bntT9tTYJJM3R1/q4QCTezDEHMa2mgwRunAMfYUqG7W1xn2FGivM/YUaM/WngLltnMhFKj7XqRcr78jhAL97U1qZSmhgG8fSNVvb75QING2zVDg1h9uDpse+6vwPz//7/Crh7wzXHHq1WHdsvOmrVgocDBN3X+IhQLxF0bMzVr8as2OFAo069nlajHnmScF6nVIKFDPLWaWUKBcSShQbpTjCKFAjl2Lq1koEOeU2yihQGLH2ggFnnj5+4OnAx77922D6tYcu3YQCPzGOxfOWK1QQCiQeDrXmh5zs1Zr4QYmCQUaQOzJEjHnmVCgXrOEAvXcYmYJBcqVhALlRjmOEArk2LW4moUCcU65jRIKNNCxJvcUuPaxjeHzP/jbQVVHz3vvIAz4wyVrGqjSElUEqjwpUGVdY7sXsKdA9z1oqwKhQFuy3a9rT4Hue9BWBXMhFGjLrs/rCgX63J202lJCgeLIvn0gzb+t2UKBBmSbCAUeev6+wdMBz72+fVDRuSdeGDbs3zvgkHcc2kCFlqgqIBSoKpbPeKFAPr2qWqlQoKpYPuOFAvn0qmqlQoGqYnmMFwrk0ac6VQoF6qj1f45QoIEepYQCu996NVyzf9+Au35056CSk45cPng6YMV7TmugMkvUFRAK1JXr/zyhQP97VLdCoUBduf7PEwr0v0d1KxQK1JXr9zyhQL/7k1KdUCBFr79zhQKJvUnZU+ClX3klXL/j6vD6vtcGVVy+4qrwid/9ZO2K7ClwMJ2NBmufTtETYz7rHb1YwwPtKdAwaIfLxZxnQoF6DbKnQD23mFn2FChXmguhQN33IuV6/R0hFOhvb1IrSwkFfPtAqn5784UCibZ1QoGde54LX7vn9vDwfz0Ytu//3+nv/dDgawaPWXBcUjVCAaFA0glUc3LMzVrNpZOnCQWSCXuzQMx5JhSo1y6hQD23mFlCgXIloUC5UY4jhAI5di2uZqFAnFNuo4QCiR2rGgp86albw5WPXhLW/PyPwo8P3RnWrvyzsPb4sxOr+MV0oYBQoJETqeIiMTdrFZdsbLhQoDHKzheKOc+EAvXaJBSo5xYzSyhQriQUKDfKcYRQIMeuxdUsFIhzym2UUKCBjsXsKfDSf7wYrtz2qXDfj7cMjvjHv/2n4dOn/U141y8vaKACSzQtYE+BpkX7s549BfrTi6YrEQo0Ldqf9ewp0J9eNF3JXAgFmjbLYT2hQA5dqldjSihQHNG3D9Rzb3uWUKAB4bJQ4OvbvxI27g8E9r79Rpj3S4eHT6+8PvzJ0o80cGRLtCUgFGhLtvt1hQLd96CtCoQCbcl2v65QoPsetFWBUKAt2W7XFQp069/m0YUCbep2t7ZQoAH76UKBPfteHzwd8A//+tXBUT70W6vDX+8PBN5z2FENHNUSbQoIBdrU7XZtoUC3/m0eXSjQpm63awsFuvVv8+hCgTZ1u1tbKNCdfdtHFgq0LdzN+kKBRPfp9hT45o57Bk8H/PQ/XwqHvOPQcNX+jwp89P3nThzt4fu/EY457v1h0eJjEiv4/+n2FDiYsu6Ov1VCgd2vvhK+88j9Yc3adY31cqqFpvp8fKsHjFw85rPekUs1PsyeAo2TdrZgzHkmFKjXHnsK1HOLmWVPgXKluRAK1H0vUq7X3xFCgf72JrWylFDAtw+k6rc3XygQYbtq3YawY9eLg5FLFi0MW+/YNDFrNBTY97O3BhsJfuXp2wZj/uDo0wd7Byyef+DNv1CgHL74i+PcT1xSPnCGEXX/IRYKxLPH3KzFr9bsSKFAs55drhZzngkF6nVIKFDPLWaWUKBcSShQbpTjCKFAjl2Lq1koEOeU2yihQEnHzrnourD7tb0TQUAREByxYF64/YZLBzMnhwKP7PqnsPFfPhVe2Ltz8LONK68N5524fsojCAXKLxWhwIFGnhQoP2dGRwgFqpv1dYZQoL3OCAXasxUKlNsKBcqNchwhFMixa3E1CwXinHIbJRQo6dhpqy8MF59/Vlh95srByC0PPBo+e/PdYduWzRMziz0FLn74onDrDz8/+LMVCz+w/+mA68P73v07uZ0P6v0/gSpPCkDLS8CeAnn1q0q1nhSoopXXWHsK5NWvKtXOhVCgise4jBUKjEsnD34dKaFAsZpvH+jnuSEUmKEvTz27M6y94Kpw100bw7KliwcjR//sW89/K/zF/evDM68+Pfj5JSdvDOt/77J+dltV0QJCgWiq7AYKBbJrWXTBQoFoquwGCgWya1l0wUKBaKqsBgoFsmpXpWKFApW4shksFEgMBVbctiI8/pPHw/KFy8PnzvxcWHHUimyar1ACBAgQIECAAAECBAgQmNsCQoHEUKDYU+DtlW+Haz54TaUz6e677w4nnHBCOO644yrNm2nw9u3bw5NPPhnOOuus2mu+/PLLYevWreG8886rvcaePXvCnXfeGdavn3o/hdiFC9srr7wydviU42688cZw9tlnh/nz5yetM9PkJsxiinvwwQfD4YcfHk455ZSY4bM2Zt++faFwvvTSX+yz0af/+mrWtNEtt9wSVq1aFY488siml+7Nen0+z3qDVLOQxx9/PLzxxhvhjDPOqLmCadMJzIVrU/fLBWbjvUh5FUYQ6DljK9MAAA6MSURBVF6giff23b+K8axAKFDS17I9Bab7SsKy08VGg2VCIdho8EAjGw2WnzOjI2w0WN2srzNsNNheZ2w02J6tjQbLbefCxwfqfhNSuV5/R/j4QH97k1pZyscHfCVhqn5784UCJbZVvn2gSpuEAuVaQgGhQPlZMvMIoUCqYH/mCwXa64VQoD1boUC5rVCg3CjHEUKBHLsWV7NQIM4pt1FCgYiOFV9DuGPXi4ORSxYtnPh6wuHU4tsH3nzrZxErGZKLgI0Gc+lU9TptNFjdLJcZNhrMpVPV67TRYHWzXGbMhVAgl140WadQoEnNfq2VEgoUr8S3D/Srn8NqhAIN9EUo0ABiz5YQCvSsIQ2WIxRoELNnSwkFetaQBssRCjSI2bOlhAI9a0hD5QgFGoLs4TJCgR42pYGShAINIAoFGkDs2RJCgZ41pMFyhAINYvZsKaFAzxrSYDlCgQYxe7aUUKBnDWmoHKFAQ5A9XEYo0MOmNFCSUCAR0UaDBwO+ufeNcN+Wu8Laj9b/BoNiVXsKHGhro8HqF6s9Baqb9XWGPQXa64w9BdqztadAue1cCAVsNFh+HhiRj0BKKGCjwf72WSiQ2BuhgFBg96uvhO88cn9Ys3Zd4tk083ShQHVeoUB1s77OEAq01xmhQHu2QoFyW6FAuVGOIzwpkGPX4moWCsQ55TZKKJDYMaGAUEAo8Hb4+y/dHM4+d33i1dT8dKFA86ZdrSgUaE9eKNCerVCg3FYoUG6U4wihQI5di6tZKBDnlNsooUBuHVMvAQIECBAgQIAAAQIECBBoSEAo0BCkZQgQIECAAAECBAgQIECAQG4CQoHcOqZeAgQIECBAgAABAgQIECDQkIBQoCFIyxAgQIAAAQIECBAgQIAAgdwEhAIJHVu1bkPYsevFwQpLFi0MW+/YlLCaqbMtUKV/l1/zhXDvQ989qMRnvn3HbJfteIkCm2+7J3ztH/85bNuyOXEl07sSiO2h67arDjV33HMuui5874lnJxb0b21ztrO1UtUeum5nqzPtHGe0f67ZdpzbXLVqD12zbXZj9tYWCtS0Lv6R2/3a3okgoLjBPGLBvHD7DZfWXNG02RSo2r/iL7wf/dsLgp/ZbFLDx9rywKNhw2e+OFh1wfzDhAIN+87GclV76Lqdja60e4zTVl94wLVa/P+Vy5eFa6/4eLsHtnpjAlV76LptjL6ThYr3w5N/Seb9cSdtSDpo1R66ZpO4ezNZKFCzFcU/cheff1ZYfebKwQrFm9XP3ny3G42anrM9rWr//IU32x1q73ixv2VurwIrpwrE9tB1myrdv/l62r+eVK2orIdlP696POO7FdDPbv2bOHpZD8t+3kQN1mhfQChQw/ipZ3eGtRdcFe66aWNYtnTxYIWp/qzG0qbMgkCd/o0+GuU3zbPQqJYOEXtD2dLhLduAQGwPXbcNYPdsieI3WMcfe7QnBXrWlyrllPXQdVtFs/9ji1/CHLP4KE/S9r9V01ZY1kPXbMbNnVS6UKBGH+vcVNY4jCktCTTRv+JNTfGffSRaalKLy8beULZYgqUTBer20HWbCN/x9OEbT3u5dNyIhMPX6aHrNgG8w6nFjeRre96051aHPUg9dN0eumZT5buZLxSo4d7ETWWNw5rSkEAT/Rt+ttmb04aaMovL1L2hnMUSHapEoG4PXbf5nlpFz2/+8r0HPKGX76uZm5XX7aHrNu/zZXQPp7xfzdysvmoPXbN5nidCgZp9q/qZ9JqHMa0lgdT++QuvpcbMwrJ1byhnoTSHiBSo20PXbSRwz4bV+e1yz17CnC8npYeu27xPH/3Lu39F9VV7WHV8/kLj8QqEAjX7WHX3+pqHMa0lgbL+jT76NNXuyT4j11JzWl627g1ly2VZvoLAdD103VZAzGSox1AzadQMZZb10HWbf48nv4LR90tl/R+vVz8er6ash67Z8ejz6KsQCiT0tcr33CccxtSWBGbq3+hfeJPHFuWcfNJSm+a01Je2lp38dXbDY3z49FNtWNYWeAvrlvXQddsCeodLDj/qNVUJmy772MS3/3RYokOXCMT00HU7XqfR6PulJYsW2n8psxaX9dA1m1lDI8sVCkRCGUaAAAECBAgQIECAAAECBMZNQCgwbh31eggQIECAAAECBAgQIECAQKSAUCASyjACBAgQIECAAAECBAgQIDBuAkKBceuo10OAAAECBAgQIECAAAECBCIFhAKRUIYRIECAAAECBAgQIECAAIFxExAKjFtHvR4CBAgQIECAAAECBAgQIBApIBSIhDKMAAECBAgQIECAAAECBAiMm4BQYNw66vUQIECAAAECBAgQIECAAIFIAaFAJJRhBAgQIECAAAECBAgQIEBg3ASEAuPWUa+HAAECBAgQIECAAAECBAhECggFIqEMI0CAAAECBAgQIECAAAEC4yYgFBi3jno9BAgQIECAAAECBAgQIEAgUkAoEAllGAECBAgQIECAAAECBAgQGDcBocC4ddTrIUCAAAECBAgQIECAAAECkQJCgUgowwgQIECAAAECBAgQIECAwLgJCAXGraNeDwECBAgQIECAAAECBAgQiBQQCkRCGUaAAAECBAgQIECAAAECBMZNQCgwbh31eggQIECAAAECBAgQIECAQKSAUCASyjACBAgQIECAAAECBAgQIDBuAkKBceuo10OAAAECjQlsvu2ecPOX7z1ovfM/8uFw4Z+vCaetvnDws21bNh80pvjZgvnzwtY7Ng1+VrbW+35/3Yx1L5h/2OA451x0XfjeE89OOXbTZR8Lq89cGVat2xB27HoxDP//cPCWBx4NGz7zxbBk0cKJukYXiqlj5fJl4d6Hvjsx9cOnnxquveLjlY4b8zoaa6SFCBAgQIAAgWkFhAJODgIECBAgMIXA8Kb1rps2hmVLF0+MKG7uH9n2g4mb6uIm+uSTlobbb7h0Yszl13whPPr9pybCgti1Rm/eR2/qi58Xa+1+be+0N/XFmGEoMFrX8M9nCgUmUwxDhKnqmOpnVY4b8zqcmAQIECBAgED7AkKB9o0dgQABAgQyFChu9oe/AZ+p/NGb46ee3RnWXnDVAb+lj12ryVDgiAXzBk8UDEONYV1FUFAWKsTUMV0oEHtcoUCGF4WSCRAgQGAsBYQCY9lWL4oAAQIEUgVGH/+fab3iBve5nT8ZPBlQ/La8uDGe/ORAlbWK48z0G/qYm+mihuOPPTr89NXXw6+/+12DR/uLpxeK/4o/azMUiD1uzOtI7aH5BAgQIECAQLmAUKDcyAgCBAgQmIMCwxvzyS99qsfohz+f/Fn8Z759xwFiVdcqCwVi9hQobs5PPun4wR4CRT1FfcVTA39369dbDwVijmtPgTl4UXnJBAgQINBLAaFAL9uiKAIECBDok8DoDexUHysY3sgPNyGcrv4qa6XsKVCEAsPN/4pahk8vVPkNfZ09BWKPW6WOPp0LaiFAgAABAuMmIBQYt456PQQIECDQqkDxGH6x8/7o0wBT7SVQVsh0a5U9KVD2+P/w4wNFKDD81oNhwFDlZjwlFCg7bpU6yhz9nAABAgQIEKgvIBSob2cmAQIECIypQHGD/9VvPDL4Tfvof8Ob3dFvJZguFKizVpOhQFF/safB8GsTq9yMp4QCZcetUseYnmZeFgECBAgQ6IWAUKAXbVAEAQIECPRJYHiDX9Q0+kTAVF9BWIybKRQovo2gylpNhwKTbavcjKeGAjMdt0odfTo31EKAAAECBMZNQCgwbh31eggQIECgMYHJmwcOF51uz4Cyjw9UWassFIjdaHCqJx2q3IxPV8fwYw9Dk+EeC5M/tjDahNHj2miwsdPUQgQIECBAIElAKJDEZzIBAgQIECBAgAABAgQIEMhXQCiQb+9UToAAAQIECBAgQIAAAQIEkgSEAkl8JhMgQIAAAQIECBAgQIAAgXwFhAL59k7lBAgQIECAAAECBAgQIEAgSUAokMRnMgECBAgQIECAAAECBAgQyFdAKJBv71ROgAABAgQIECBAgAABAgSSBIQCSXwmEyBAgAABAgQIECBAgACBfAWEAvn2TuUECBAgQIAAAQIECBAgQCBJQCiQxGcyAQIECBAgQIAAAQIECBDIV0AokG/vVE6AAAECBAgQIECAAAECBJIEhAJJfCYTIECAAAECBAgQIECAAIF8BYQC+fZO5QQIECBAgAABAgQIECBAIElAKJDEZzIBAgQIECBAgAABAgQIEMhXQCiQb+9UToAAAQIECBAgQIAAAQIEkgSEAkl8JhMgQIAAAQIECBAgQIAAgXwFhAL59k7lBAgQIECAAAECBAgQIEAgSUAokMRnMgECBAgQIECAAAECBAgQyFdAKJBv71ROgAABAgQIECBAgAABAgSSBIQCSXwmEyBAgAABAgQIECBAgACBfAWEAvn2TuUECBAgQIAAAQIECBAgQCBJQCiQxGcyAQIECBAgQIAAAQIECBDIV0AokG/vVE6AAAECBAgQIECAAAECBJIEhAJJfCYTIECAAAECBAgQIECAAIF8BYQC+fZO5QQIECBAgAABAgQIECBAIElAKJDEZzIBAgQIECBAgAABAgQIEMhXQCiQb+9UToAAAQIECBAgQIAAAQIEkgSEAkl8JhMgQIAAAQIECBAgQIAAgXwFhAL59k7lBAgQIECAAAECBAgQIEAgSUAokMRnMgECBAgQIECAAAECBAgQyFdAKJBv71ROgAABAgQIECBAgAABAgSSBIQCSXwmEyBAgAABAgQIECBAgACBfAWEAvn2TuUECBAgQIAAAQIECBAgQCBJQCiQxGcyAQIECBAgQIAAAQIECBDIV0AokG/vVE6AAAECBAgQIECAAAECBJIEhAJJfCYTIECAAAECBAgQIECAAIF8BYQC+fZO5QQIECBAgAABAgQIECBAIElAKJDEZzIBAgQIECBAgAABAgQIEMhXQCiQb+9UToAAAQIECBAgQIAAAQIEkgT+F5MrtJUYbZXuAAAAAElFTkSuQmCC",
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| \n", " | SYSTEM TIME | \n", "A | \n", "B | \n", "E | \n", "caption | \n", "
|---|---|---|---|---|---|
| 0 | \n", "0.000000 | \n", "20.000000 | \n", "0.000000 | \n", "30.0 | \n", "Initialized state | \n", "
| 1 | \n", "0.000250 | \n", "18.500000 | \n", "1.500000 | \n", "30.0 | \n", "\n", " |
| 2 | \n", "0.000375 | \n", "17.817500 | \n", "2.182500 | \n", "30.0 | \n", "\n", " |
| 3 | \n", "0.000500 | \n", "17.165712 | \n", "2.834288 | \n", "30.0 | \n", "\n", " |
| 4 | \n", "0.000625 | \n", "16.543255 | \n", "3.456745 | \n", "30.0 | \n", "\n", " |
| 5 | \n", "0.000750 | \n", "15.948809 | \n", "4.051191 | \n", "30.0 | \n", "\n", " |
| 6 | \n", "0.000875 | \n", "15.381112 | \n", "4.618888 | \n", "30.0 | \n", "\n", " |
| 7 | \n", "0.001000 | \n", "14.838962 | \n", "5.161038 | \n", "30.0 | \n", "\n", " |
| 8 | \n", "0.001125 | \n", "14.321209 | \n", "5.678791 | \n", "30.0 | \n", "\n", " |
| 9 | \n", "0.001250 | \n", "13.826755 | \n", "6.173245 | \n", "30.0 | \n", "\n", " |
| 10 | \n", "0.001375 | \n", "13.354551 | \n", "6.645449 | \n", "30.0 | \n", "\n", " |
| 11 | \n", "0.001525 | \n", "12.813405 | \n", "7.186595 | \n", "30.0 | \n", "\n", " |
| 12 | \n", "0.001675 | \n", "12.301481 | \n", "7.698519 | \n", "30.0 | \n", "\n", " |
| 13 | \n", "0.001855 | \n", "11.720345 | \n", "8.279655 | \n", "30.0 | \n", "\n", " |
| 14 | \n", "0.002071 | \n", "11.068171 | \n", "8.931829 | \n", "30.0 | \n", "\n", " |
| 15 | \n", "0.002330 | \n", "10.346417 | \n", "9.653583 | \n", "30.0 | \n", "\n", " |
| 16 | \n", "0.002589 | \n", "9.692012 | \n", "10.307988 | \n", "30.0 | \n", "\n", " |
| 17 | \n", "0.002900 | \n", "8.980003 | \n", "11.019997 | \n", "30.0 | \n", "\n", " |
| 18 | \n", "0.003274 | \n", "8.221264 | \n", "11.778736 | \n", "30.0 | \n", "\n", " |
| 19 | \n", "0.003647 | \n", "7.564476 | \n", "12.435524 | \n", "30.0 | \n", "\n", " |
| 20 | \n", "0.004095 | \n", "6.882233 | \n", "13.117767 | \n", "30.0 | \n", "\n", " |
| 21 | \n", "0.004543 | \n", "6.309997 | \n", "13.690003 | \n", "30.0 | \n", "\n", " |
| 22 | \n", "0.004991 | \n", "5.830030 | \n", "14.169970 | \n", "30.0 | \n", "\n", " |
| 23 | \n", "0.005528 | \n", "5.346939 | \n", "14.653061 | \n", "30.0 | \n", "\n", " |
| 24 | \n", "0.006066 | \n", "4.957322 | \n", "15.042678 | \n", "30.0 | \n", "\n", " |
| 25 | \n", "0.006711 | \n", "4.580248 | \n", "15.419752 | \n", "30.0 | \n", "\n", " |
| 26 | \n", "0.007485 | \n", "4.232821 | \n", "15.767179 | \n", "30.0 | \n", "\n", " |
| 27 | \n", "0.008413 | \n", "3.932073 | \n", "16.067927 | \n", "30.0 | \n", "\n", " |
| 28 | \n", "0.009528 | \n", "3.691843 | \n", "16.308157 | \n", "30.0 | \n", "\n", " |
| 29 | \n", "0.010865 | \n", "3.519230 | \n", "16.480770 | \n", "30.0 | \n", "\n", " |
| 30 | \n", "0.012470 | \n", "3.411824 | \n", "16.588176 | \n", "30.0 | \n", "\n", " |
| 31 | \n", "0.014396 | \n", "3.357403 | \n", "16.642597 | \n", "30.0 | \n", "\n", " |
| 32 | \n", "0.016707 | \n", "3.337375 | \n", "16.662625 | \n", "30.0 | \n", "\n", " |
| 33 | \n", "0.019480 | \n", "3.333337 | \n", "16.666663 | \n", "30.0 | \n", "\n", " |
| 34 | \n", "0.022808 | \n", "3.333329 | \n", "16.666671 | \n", "30.0 | \n", "\n", " |
| 35 | \n", "0.026802 | \n", "3.333331 | \n", "16.666669 | \n", "30.0 | \n", "\n", " |
| 36 | \n", "0.031594 | \n", "3.333330 | \n", "16.666670 | \n", "30.0 | \n", "\n", " |
| 37 | \n", "0.037345 | \n", "3.333331 | \n", "16.666669 | \n", "30.0 | \n", "\n", " |
| 38 | \n", "0.044245 | \n", "3.333330 | \n", "16.666670 | \n", "30.0 | \n", "\n", " |
| 39 | \n", "0.052526 | \n", "3.333332 | \n", "16.666668 | \n", "30.0 | \n", "\n", " |
| 40 | \n", "0.062463 | \n", "3.333327 | \n", "16.666673 | \n", "30.0 | \n", "\n", " |
| 41 | \n", "0.074388 | \n", "3.333341 | \n", "16.666659 | \n", "30.0 | \n", "\n", " |
| 42 | \n", "0.088697 | \n", "3.333285 | \n", "16.666715 | \n", "30.0 | \n", "\n", " |
| 43 | \n", "0.105869 | \n", "3.333568 | \n", "16.666432 | \n", "30.0 | \n", "\n", " |