{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# The Devito domain specific language: an overview\n",
"\n",
"This notebook presents an overview of the Devito symbolic language, used to express and discretise operators, in particular partial differential equations (PDEs).\n",
"\n",
"For convenience, we import all Devito modules:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from devito import *"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## From equations to code in a few lines of Python\n",
"\n",
"The main objective of this tutorial is to demonstrate how Devito and its [SymPy](http://www.sympy.org/en/index.html)-powered symbolic API can be used to solve partial differential equations using the finite difference method with highly optimized stencils in a few lines of Python. We demonstrate how computational stencils can be derived directly from the equation in an automated fashion and how Devito can be used to generate and execute, at runtime, the desired numerical scheme in the form of optimized C code.\n",
"\n",
"\n",
"## Defining the physical domain\n",
"\n",
"Before we can begin creating finite-difference (FD) stencils we will need to give Devito a few details regarding the computational domain within which we wish to solve our problem. For this purpose we create a `Grid` object that stores the physical `extent` (the size) of our domain and knows how many points we want to use in each dimension to discretise our data.\n",
"\n",
""
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Grid[extent=(1.0, 1.0), shape=(5, 6), dimensions=(x, y)]"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"grid = Grid(shape=(5, 6), extent=(1., 1.))\n",
"grid"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Functions and data\n",
"\n",
"To express our equation in symbolic form and discretise it using finite differences, Devito provides a set of `Function` types. A `Function` object:\n",
"\n",
"1. Behaves like a `sympy.Function` symbol\n",
"2. Manages data associated with the symbol\n",
"\n",
"To get more information on how to create and use a `Function` object, or any type provided by Devito, we can take a look at the documentation."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
" Tensor symbol representing a discrete function in symbolic equations.\n",
"\n",
" A Function carries multi-dimensional data and provides operations to create\n",
" finite-differences approximations.\n",
"\n",
" A Function encapsulates space-varying data; for data that also varies in time,\n",
" use TimeFunction instead.\n",
"\n",
" Parameters\n",
" ----------\n",
" name : str\n",
" Name of the symbol.\n",
" grid : Grid, optional\n",
" Carries shape, dimensions, and dtype of the Function. When grid is not\n",
" provided, shape and dimensions must be given. For MPI execution, a\n",
" Grid is compulsory.\n",
" space_order : int or 3-tuple of ints, optional\n",
" Discretisation order for space derivatives. Defaults to 1. ``space_order`` also\n",
" impacts the number of points available around a generic point of interest. By\n",
" default, ``space_order`` points are available on both sides of a generic point of\n",
" interest, including those nearby the grid boundary. Sometimes, fewer points\n",
" suffice; in other scenarios, more points are necessary. In such cases, instead of\n",
" an integer, one can pass a 3-tuple ``(o, lp, rp)`` indicating the discretization\n",
" order (``o``) as well as the number of points on the left (``lp``) and right\n",
" (``rp``) sides of a generic point of interest.\n",
" shape : tuple of ints, optional\n",
" Shape of the domain region in grid points. Only necessary if ``grid`` isn't given.\n",
" dimensions : tuple of Dimension, optional\n",
" Dimensions associated with the object. Only necessary if ``grid`` isn't given.\n",
" dtype : data-type, optional\n",
" Any object that can be interpreted as a numpy data type. Defaults\n",
" to ``np.float32``.\n",
" staggered : Dimension or tuple of Dimension or Stagger, optional\n",
" Define how the Function is staggered.\n",
" initializer : callable or any object exposing the buffer interface, optional\n",
" Data initializer. If a callable is provided, data is allocated lazily.\n",
" allocator : MemoryAllocator, optional\n",
" Controller for memory allocation. To be used, for example, when one wants\n",
" to take advantage of the memory hierarchy in a NUMA architecture. Refer to\n",
" `default_allocator.__doc__` for more information.\n",
" padding : int or tuple of ints, optional\n",
" .. deprecated:: shouldn't be used; padding is now automatically inserted.\n",
"\n",
" Allocate extra grid points to maximize data access alignment. When a tuple\n",
" of ints, one int per Dimension should be provided.\n",
"\n",
" Examples\n",
" --------\n",
" Creation\n",
"\n",
" >>> from devito import Grid, Function\n",
" >>> grid = Grid(shape=(4, 4))\n",
" >>> f = Function(name='f', grid=grid)\n",
" >>> f\n",
" f(x, y)\n",
" >>> g = Function(name='g', grid=grid, space_order=2)\n",
" >>> g\n",
" g(x, y)\n",
"\n",
" First-order derivatives through centered finite-difference approximations\n",
"\n",
" >>> f.dx\n",
" Derivative(f(x, y), x)\n",
" >>> f.dy\n",
" Derivative(f(x, y), y)\n",
" >>> g.dx\n",
" Derivative(g(x, y), x)\n",
" >>> (f + g).dx\n",
" Derivative(f(x, y) + g(x, y), x)\n",
"\n",
" First-order derivatives through left/right finite-difference approximations\n",
"\n",
" >>> f.dxl\n",
" Derivative(f(x, y), x)\n",
"\n",
" Note that the fact that it's a left-derivative isn't captured in the representation.\n",
" However, upon derivative expansion, this becomes clear\n",
"\n",
" >>> f.dxl.evaluate\n",
" f(x, y)/h_x - f(x - h_x, y)/h_x\n",
" >>> f.dxr\n",
" Derivative(f(x, y), x)\n",
"\n",
" Second-order derivative through centered finite-difference approximation\n",
"\n",
" >>> g.dx2\n",
" Derivative(g(x, y), (x, 2))\n",
"\n",
" Notes\n",
" -----\n",
" The parameters must always be given as keyword arguments, since SymPy\n",
" uses ``*args`` to (re-)create the dimension arguments of the symbolic object.\n",
" \n"
]
}
],
"source": [
"print(Function.__doc__)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ok, let's create a function $f(x, y)$ and look at the data Devito has associated with it. Please note that it is important to use explicit keywords, such as `name` or `grid` when creating `Function` objects."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle f{\\left(x,y \\right)}$"
],
"text/plain": [
"f(x, y)"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"f = Function(name='f', grid=grid)\n",
"f"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Data([[0., 0., 0., 0., 0., 0.],\n",
" [0., 0., 0., 0., 0., 0.],\n",
" [0., 0., 0., 0., 0., 0.],\n",
" [0., 0., 0., 0., 0., 0.],\n",
" [0., 0., 0., 0., 0., 0.]], dtype=float32)"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"f.data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"By default, Devito `Function` objects use the spatial dimensions `(x, y)` for 2D grids and `(x, y, z)` for 3D grids. To solve a PDE over several timesteps a time dimension is also required by our symbolic function. For this Devito provides an additional function type, the `TimeFunction`, which incorporates the correct dimension along with some other intricacies needed to create a time stepping scheme."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle g{\\left(t,x,y \\right)}$"
],
"text/plain": [
"g(t, x, y)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g = TimeFunction(name='g', grid=grid)\n",
"g"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Since the default time order of a `TimeFunction` is `1`, the shape of `f` is `(2, 5, 6)`, i.e. Devito has allocated two buffers to represent `g(t, x, y)` and `g(t + dt, x, y)`:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(2, 5, 6)"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g.shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Derivatives of symbolic functions\n",
"\n",
"The functions we have created so far all act as `sympy.Function` objects, which means that we can form symbolic derivative expressions from them. Devito provides a set of shorthand expressions (implemented as Python properties) that allow us to generate finite differences in symbolic form. For example, the property `f.dx` denotes $\\frac{\\partial}{\\partial x} f(x, y)$ - only that Devito has already discretised it with a finite difference expression. There are also a set of shorthand expressions for left (backward) and right (forward) derivatives:\n",
"\n",
"| Derivative | Shorthand | Discretised | Stencil |\n",
"| ---------- |:---------:|:-----------:|:-------:|\n",
"| $\\frac{\\partial}{\\partial x}f(x, y)$ (right) | `f.dxr` | $\\frac{f(x+h_x,y)}{h_x} - \\frac{f(x,y)}{h_x}$ | |\n",
"| $\\frac{\\partial}{\\partial x}f(x, y)$ (left) | `f.dxl` | $\\frac{f(x,y)}{h_x} - \\frac{f(x-h_x,y)}{h_x}$ | |\n",
"\n",
"A similar set of expressions exist for each spatial dimension defined on our grid, for example `f.dy` and `f.dyl`. Obviously, one can also take derivatives in time of `TimeFunction` objects. For example, to take the first derivative in time of `g` you can simply write:"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle \\frac{\\partial}{\\partial t} g{\\left(t,x,y \\right)}$"
],
"text/plain": [
"Derivative(g(t, x, y), t)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g.dt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We may also want to take a look at the stencil Devito will generate based on the chosen discretisation:"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle - \\frac{g{\\left(t,x,y \\right)}}{dt} + \\frac{g{\\left(t + dt,x,y \\right)}}{dt}$"
],
"text/plain": [
"-g(t, x, y)/dt + g(t + dt, x, y)/dt"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g.dt.evaluate"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"There also exist convenient shortcuts to express the forward and backward stencil points, `g(t+dt, x, y)` and `g(t-dt, x, y)`."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle g{\\left(t + dt,x,y \\right)}$"
],
"text/plain": [
"g(t + dt, x, y)"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g.forward"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle g{\\left(t - dt,x,y \\right)}$"
],
"text/plain": [
"g(t - dt, x, y)"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g.backward"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And of course, there's nothing to stop us taking derivatives on these objects:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle \\frac{\\partial}{\\partial t} g{\\left(t + dt,x,y \\right)}$"
],
"text/plain": [
"Derivative(g(t + dt, x, y), t)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g.forward.dt"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/latex": [
"$\\displaystyle \\frac{\\partial}{\\partial y} g{\\left(t + dt,x,y \\right)}$"
],
"text/plain": [
"Derivative(g(t + dt, x, y), y)"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"g.forward.dy"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## A linear convection operator\n",
"\n",
"**Note:** The following example is derived from [step 5](http://nbviewer.ipython.org/github/barbagroup/CFDPython/blob/master/lessons/07_Step_5.ipynb) in the excellent tutorial series [CFD Python: 12 steps to Navier-Stokes](http://lorenabarba.com/blog/cfd-python-12-steps-to-navier-stokes/).\n",
"\n",
"In this simple example we will show how to derive a very simple convection operator from a high-level description of the governing equation. We will go through the process of deriving a discretised finite difference formulation of the state update for the field variable $u$, before creating a callable `Operator` object. Luckily, the automation provided by SymPy makes the derivation very nice and easy.\n",
"\n",
"The governing equation we want to implement is the linear convection equation:\n",
"$$\\frac{\\partial u}{\\partial t}+c\\frac{\\partial u}{\\partial x} + c\\frac{\\partial u}{\\partial y} = 0.$$\n",
"\n",
"Before we begin, we must define some parameters including the grid, the number of timesteps and the timestep size. We will also initialize our velocity `u` with a smooth field:"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"tags": [
"nbval-ignore-output"
]
},
"outputs": [
{
"data": {
"image/png": 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jiBHH7WDpsEoNwxBo7XYbx8fH2NzcRKFQwJUrV1wnMnrByxw0v4ZVh0UQ+27sc5udne34miRJHcmSxj63ZDJpO8+NB7cGiF48vVd46UFTFCW043DiulFICUEMFxJoBDGiGMsYzWUtvRgFB82YyJhKpTA3N4dHHnkksAWGWWw5+b3EXaCFTTqdxtTUVFfAC+tzY+Lt+PhYd90AIJ/PI5vNQtM0bG1t6QIujn1QPCygqcRxeHgNKalWq9A0DSdOnKCQEoJwCAk0ghgh7AZLu7lAhuWgBSEMj4+P9UTGU6dO4cknn8Tm5mbgZVNeShzjLNCivDiz63PTNE2f51apVHBwcIC1tTXU63UoimI7zy2dTod0JL3hpTSQl+OIokCzo1+55MHBARRFwczMDIWUEIRDSKARxAjQL/jDDbyFhJgTGRcWFvDMM8+gUCgAALa2tgJ3DL2IrTgLNCB+/XPGlMhcLoe1tTU8/vjj0DQN7Xa7Y57b9vY26vU62u020um05Ty3bDYb6mI0bq+/HXESNr3g5TjYzaZUKtXhKlNICUH0hgQaQXCM0+APNyQSCbTbbT930/F2/RRKLJGxVCpBFEXbRMZEIgFJknzbrhOsetCoxDEeCIKAbDaLbDbbs89NFEUcHh5ibW0NjUYDyWTSdp5bEAt1npwnXo4jjmWyViiKgkwm0/EYhZQQRG9IoBEEh7gN/nBD2D1ogy4kFUXB+vq640TGMMJJ7Gav9SOuAm1UxGWvPrdGo6ELt1qthp2dHYiiCE3TdKfOXC7p5wKeF4HGS0gILw4acP/8dnOuug0pMX4PhZQQvEACjSA4wljGyO4k+10KEmaKI+B9ISlJElZWVrC8vIxMJoMHHngAZ86c6bsI8hp5Pwij1oPGA4O8x5LJJMbHxzE+Pt7xuKZp+jw35rwdHh5CFEXIsoyxsTFL183sVjiBF4HGi4OmKMrQxngEjV9uoNeQEvY3E20UUkLEAT7e/QQxwtgFfwzrjmGYDhrg/s6yMZFxamoKd+7cwcmTJ12FogQtfEaxBy3ODOt1FwQBuVwOuVyua3vtdrujXJI5bq1WC+l02nKeW68+N14EGjlo0cOtg+YWp+WS7AYmhZQQcYAEGkHEFKv+smEKM0bYDppTcWhMZJybm8MTTzyB6elpT9sNWpB6EYVxFmhx3vcwMPa5zczMdHxNluWuPrf19XU0Go2OAd5G4ZbL5bgRaLw4aCTQ/MFJuSSFlBBRhAQaQcQM5pbJsqz/P8gLRhQcNDs0TcPh4SFKpRL29/e7Ehm9EIZ4sNpmv99tGE4fET1SqRQmJycxOTnZ8biqqh3z3Or1ekefWzqdhqZpWFpa6hBwcSuzIwcteoQ5dNsOryElzWYTR0dHenk8hZQQwyJen7wEMcIYgz82NjawurqK97znPYFf+MJy0JgAtdq2MZGxXq/jwoULuH37dlcioxeiEhLihLgKNB4WNFE/hkQi0bPPbW1tDbu7u2i326hUKqjX65BlGdlstqvHrVAoIJ1OR/KYeXLQeEpxjNOx9HLdRFHE2toaTp8+TSElxFAhgUYQEcdYxsgWH6lUCoqihPKBH5aDBnSLJUVRsLGxgVKp5CiR0Y9tBoEXBy3uZYK07+HA+twKhQJqtRoefPBBANDLvowBJbu7u6jX62i1WkilUpaDuMfGxkKf5xY1t8YLvDlocRJodrAbhE5mulFICTEoJNAIIoL0Gywd1rBotg9hbltVVc+JjF4IQ/iMWg8aET7mHjRBEJDJZJDJZPr2uVWrVWxsbKDRaOgDvM2uWz6fD0Rw8OSg8SLQeHMDzTcAKaSEGAYk0AgiQjgdLB2mQAvTQRMEAaVSCbu7u5icnMTt27cxNzc39FCUKDhow/ieqECLkPBxExLSq8/NOM+tXq9jb28PoihCVVXkcjnLeW5+Ot68OGhR7NvyArum8SLQZFn2faYbhZQQVpBAI4gI4HawdNhlhkGLQ5bI2G630Wq1PCcyeiEqc9DYhbzX98RVoAHxLhME4i8y/UhxTCQSuvAy/+xWq9Uh3DY2NiCKIiRJQjabtZ3n5nafyEGLFuxawYtA82s+ndeQEvY9TKhRSAm/kEAjiBAxljGa75z1IplM6imOQcPE4bBjuc2JjGfPnkU+n8fly5cDE2cAzUELgrgvKOL6uhsZ5vtZEASMjY1hbGwMJ06c6PiaeZ7b3t4eVlZW0Gw2kUqluty2fD6PXC7X05XgQdjw4joxgcbD7wQIpp/OievG1g4UUsIvJNAIImDsBku7KVlIJpP6h3QYKY7A8BYQmqZhZ2cHpVIJtVqtI5HxxRdfDGUmGc1BI0aBMBZwrM/NfNNFUZSuPrfNzU2Ioqj3uZldN5bayoMY4MlB61UNEjdkWe4aHB8Udq4bhZTwCQk0ggiIfsEfbmDCKIyLuHHbfgo0VVWxvr6OcrkMWZaxuLiIxx9/vKOcJIxyQ3LQgiHO+84DUSsNTCaTmJiYwMTERMfjrM/N7LqJoqh/rr7++usYHx/vcN/iNs+NJ4HGgxPIkGU5cufSICElrD90ZmaGQkoiRrTOMoLgEKfBH25gFzy/6uHdwPZdURSk0+mBf54kSVhdXcXy8jLS6TQuX75sm8gYRu9dWD1ooyTQeFgE0DEEg7HPbW5uTn9c0zTUajW89NJLmJmZQbPZxNbWFkRRRLvdRiaTsZzn5qXPbdiEVR0xDHgp1WTETXD2K5fc2dmBJEkYHx+3DSn5u7/7O7zvfe/DY489Fui+jzok0AhiSLgN/nADu7MVRpIj2/agoqXZbKJcLmN1dRWTk5O4detW30TGsMoNoyAKaQ5adInzvjPifgxsLAAAXLhwoeP9IkmS7rjV63Xs7+/rfW7JZNJSuNn1uQUBe+/zINDiJmj6EUUHzQvs3FYUBZlMpuOYzCElX/3qV3HhwgUSaAET/7OMICKGsYyRlQ0No8Y7rrPQarUaSqUSNjc3cfLkSTz++ONdc5Z6bXcUBBr1oBFBM+zQnyAwft4aSafTmJqawtTUVMfjrM+Nibfj42PddQNgO89t2IKDN4HGw3EweBScY2NjHY8Z30OapqFarTq+RhP+QQKNIHzALvhjmDXccZuFdnh4iGKxqCcyPv300xgfH3f1M8KcSRbkAtYsthRFwdraGo6PjzE+Pq4vFo0lpnEWaHEXBjzAg0Bzewy9+tyazWbHWICDgwPU63UoioKxsbEO4Wb1fhwE3gQab4KGBweN4eR4KpUKCbQQ4OcsI4gQMAd/BCHMGHFw0MyJjOfPn8etW7e67ti52W4YbhYQ7AKWlTjKsoyVlRWUy2VkMhlMTk5a9tUUCgU0m01kMhn98bgRV3HJGDVxE0X86ttKJBK6W2ZE0zS02+0O4WZ8P6bT6Q7Bxv7OZrOuXlvmBJJAix68HU8/gaYoCo6Pj0mghQAJNILwAOsvY2WMLPgjyLjaKDtoqqpiY2MDpVLJNpHRC2E5aECwqWpsOOkLL7yA8fFx3L59GydOnIAkSfo+SJKk99SIoohWq4WtrS2sr693LBSjHojAA3EXlwAfAm3YxyAIArLZLLLZLGZnZzu+ZuxzE0URBwcHWFtbQ6PRQDKZtCyXzOVylp8pvASEAHwJGnbdHyUHrVqtAgAJtBDg5ywjiAAwBn8Ui0U0Gg3cunUrlItpFB00YyJjKpXCpUuXcPbsWd9en0F63wbZJhDMIrzRaKBUKmFtbQ2apuGJJ57QF4JmYZpOpzE9Pa3Pj5IkCblcDufPn+8QbsZAhFQq1SXa2PyoMBfncS7P5AUeBFqYwqZXn1uj0dDfj7VaDTs7OxBFEZqmWc5z46lviyeBxq49vBwPcP+60UugVSoVpFIp1+0IxOCQQCMIB9gFf8iyHNqiJkoOWrPZxPLyMlZXVzE+Pu4okdELYZY4DnO7tVoNxWIRW1tbOHXqFG7fvo0333yz6y59L5jISaVSPQMRmHirVCpYX1/X7/CbRVuhUMDY2FjsF+2Ec+L+u47aLDfg/mfl+Ph41wJX07SueW4HBwcQRRGyLAMAfvzjH3e9L/3qcwsKnmL22fV2lBy0SqWCqakpbm4YxAl+zjKC8Jl+wR+pVCo0gQREw0EzJzI+9thjQy2FSCQS+uIlKIxpVn5TrVZRLBaxu7uLs2fP4plnnkGhUMDx8bFrQdjPhbILRDDe4a/X6zg6OtL7agRBsBVudMF+Fx7cJ16OIS7npSAIunt28uRJ/XHWt/vOO+/g5MmTEEVRd9xarRbS6XRXOEkUXHA7eHIDZVnmanizqqpQVbWn6K9UKnqVBhEsJNAIwoTdYGlzf1kqlQpcLBgJo9yPoaoqlpeX8cYbb+DMmTOeEhm9EFYPmp/DqjVNw8HBAYrFIiqVCs6dO4f3ve99HcEpXgdVe8HuDr+qqh3Czao0y9znls/nPS3GqMQxfHgQaFF00NzChgNnMhmcO3eu42uyLHe44IeHh119blbz3MIUSIqiIJvNhrZ9P+Gx/wzo7QhWq1VMT0/H/n0VR/g50whiQMyDpZkws7u4helghbF9TdOwu7uLYrGoz0UxC4thE4ZA82u77M54sViEKIq4cOECHn74YcvExSjMQUskErr4MsJKs4x9bnt7e6jX69A0DblczjLJjpcyJ17hQSDHyUHrhV0vXSqVwuTkJCYnJ7ueb5znVq/XO26msPekWcAFITZ46kGTZZmbYwHedQR7vWcODw+7yuWJYCCBRow8zOZnwgyAo4jjURFo5kTGixcvYmxsDBMTE4GKMyBcgeZ1AauqKjY3N1EqlSBJEhYXF3H+/PmeiyMvs9eCcqGMpVlzc3P645qm9ZwdZVwkGgVcKpWiu7MRgAcHjYdjANyXBSYSCds+N/N7slKpoF6vQ5ZlZLPZrhsprM/Nr9eRtx403hy0fsdDQ6rDg58zjSBcYOwvYwKNlbI5vTCFXeI4bIEmyzJWV1dRLpe7Ehlfe+21UMRpWALNS4mjoihYX19HqVSCIAi4dOkSFhYWHC28jH1vbgRaGK+Ncfu5XA65XK7jcePsKPZnY2NDXySOjY0hk8lAkiRsbGzo4i1OCyEehAEPx8BLPL1fx9HrPcnGdDDhZuxzY2mv5pspXkKDyEGLLv0SHIF3SxyJ4InPFZAgfMA8WJrhpfE3Cg5aq9Xy/eeaExlv3ryJU6dOdbw+/eagDYs4lDiyUQPlchnZbBbXrl3D6dOnXS24vASTRLWPy252lHGRuLe3h1qtZjuE2/gnbil2cYEXgRb3YwCGLzQFQUAmk0Emk+lyR4x9bqIoolKpYGNjA41GQ3fPza5br95TngTaKDpoh4eHHSE2RHDwc6YRRA/sgj+AwcIVjOmOQeO3SKrVaiiXy9jY2MCJEyd6JjKGkaYIhCcMnbhTrVYLy8vLWFlZ0YdLex014GX2WtgOmluMi8RkMont7W3cvXsXQOcQbvPdfRrCPRx4EGi896AFQa8+N+M8N3Zjxdh7aiXeeEtx5EVsAvePp98Nr6OjI1y5ciWgPSKMkEAjuMYc/AE46y9zQiqV0oVfGB/afjl4h4eHKJVK2Nvbc5zImEwm0W63B962W6LYg2YcLj07O4u7d++6ml9mhVcHLc4Yj9U8hJshy7KjIdxhxI/z8PrH/RjIQRsevUKDms1mR0jJxsYGRFGEJEkAgFKphIODgw7hFscbKqPooFHMfnjwc6YRhAFjGaNRmPl5QWCiLKwSjkEEGktkLJVKODo6wvnz510lMoYV8R+lEkfzcOmnnnqq666zV3gqcXSCm75PuyHcRuFmjh8f9hDuuL7uZuK2YDbDk4MWF6fG2Od24sSJjq+1221873vfw+zsLFRVxd7eXscNFat5bn6+L/2GRwfNiUAb9IYj4Q0SaAQ32A2W9luYMVjfmizLllHpw8aLQDMnCl68eBF379513dczaj1oRvFjN1za7+0BcHWscRZowGAiJ5lMWpZlWQ3h3tzc1PtpaAj3u5CDFh2i6KB5gV0X5+fnOz4jFUXpGAlQrVa7+tysyiXDfk14mukG9Bdomqbh6OiIYvZDggQaEXvMwR9soeEl+MMNbKBoWEEhbrZtTGRMJpN6IqPXu4Gj5qAJgoBqtYqVlRXb4dJ+bw8YHQdtWLgdwl2v1wGgS7RFYeDvsOHh3KRAMAoAACAASURBVOHJQeOhlI61GJivM8lkEhMTE5iYmOh4nL0vjSEle3t7EEWxa1SH8T0a1GvFm4MmSVLfaxg5aOER/08AYmRhH/6KonQEfwzLMbMimUyGFrXvRKAZgysKhYJlIqPXbY+Cg8aGS9dqNdRqNSwuLtoOl/YTdg5bLZrtnI44C7SgXQ+7fhpVVfW5UeyPkyHcYRyD35CDFh0URQmlKsNv2Ge1U1FjfF+aZyy2Wi1dtImiiK2tLdTrdUiSpCe+ml03v/vcRq0HTdM0moMWIvycacTIwIQZK4u4cuWKb8EfbkmlUpF00Or1Okqlkp7IePfuXczMzPh2sQrTQQtqOLexFDSbzeLixYu4ePHi0LfNcJvKGGeBBkTDwUkkEp6GcGcyGSiKgqWlpY47+3G6286DQOPJQePhONhn9aDHIggCxsbGMDY21tXnZp7nZg4OMrtt+XweuVzO07nOm4PWL8WRCWASaOFAAo2IDcYyRlVV0W63sb6+jmvXroW2T1ErcaxUKiiVStjd3cX8/Dzu3bvXVUbi17Z5dNDshkv/6Ec/Cnzx6lZwxV2gRZleA39brRY2Nzexvr6uD9s2DuG26nOL4l14HgQaLw5anEJCeuGXQOuFXeKrsc9NFEUcHR3pcxYBWPa45fP5nq/7qDlolUoFACjFMST4OdMILrEL/kgkEshkMqGVFzKiUOLI0rG8JjJ6IUwHjZ0Tfi7E+g2XDqP3rVe0vxVxFmhxXVSzO/sTExNIp9O4ceMGgM4h3OyPcQh3Npu17HMLcwg3DwJN0zQuhA1PDloymQxtTqhdn1svN9zqpko+n0c6nebSQesl0KrVKiYmJrgSpXGCXnUiktgNljb2l4U9KBoIt8SRHfOLL76IdrvtOZHRC2E6aIB/d5idDpcOQ/yYt9nvHI+zQAOiUeI4CMbfj3EIt7k8yM0QbqNwG/ZnHA8CjScHjQeBFkUn0FjGbETTNLTb7Q7hZrypkslk0G63sbq6iqOjI124BTVncRj0E2iHh4eYmpqK7fHFHRJoRKQwD5buFfzBPljCLDsIo8RRlmWsra2hVCoBABYWFnDhwoVAL4RhOWjsGAe98LsdLh2Gg2bVg9brQhl3gRZn3LzuUR7CHfeFGC89aIqi0HEEjCAIyGazyGazXdcCdlPllVdeQSqVwsHBQcecRXO5ZBzGdbDqm34O2vT0dOw/F+IKCTQiEpiFGYC+wR/sg8XJsMVhkUqlAitxNCcyPvjgg/jxj3+M+fn5wO9SRsFB84LX4dJhCTQqcRwdBhnC7cewX14ctCgvip3Cy3FYRezHkXQ6rY/quHLlSsfNYatxHaIoQtM023luUXhN2LqlXw8a9Z+FBwk0IlSMZYysPMVpTD6bQxZmH1oQDlq9Xke5XMb6+npXImPY88iCXtR5GeAMDD5cOgzxM0o9aED8SxyHRa8h3Cxy3GrYr1U4Sa/0Oh4EGg/HAJBAiyJsnWE8Hrs5i5qmdc1zOzg4gCiKeniQlesWZA8q66frdZ6RQAsXEmhE4JgHSzO8DJYO0sGyIplMot1uD+VnG0WFXSJjWCmSfpUauoWJUicCTdM0HBwcoFgsDjxcmhw0oh9BC4N+w36Nd/W3t7chiiIEQeiKHWfCjYdzhxdhE8XeLS/wJNDcBJ4Y32cnT57UH2d9bkbhtrOzg3q9jna7rfegmsXbMPrcnFQesRJHIhxIoBGBYRf8AXhf3IQt0FKpFBqNhm8/T9M0PZGxWq3i3LlzePbZZ7vivRlhlxqGcQHuJ5bYcOlisQhRFHHhwoWBh0uH4VSO0hy0uLseUXrdvQ7hBoByuYxqtdoh3OK0wKaQkGjBk0DzI8HR2OdmDg9iPahMvJlLma3KJXO5nOfzxIlAIwctXEigEUPHS3+ZU3gpcTQORmaJjI8++mjfkoewjt/ooAWNnUAzD5deXFzE+fPnfelPjEKKo9/Pjxpx3vc40G8I98svv4xCoYBWq9URO57L5bp63KI6hJtKHKMFTwJt2GFkdj2oqqp2lDKb+9zY+9M8z63fvkqS1Pc5R0dHuHr16sDHRniDBBoxNIxljEZh5ucFNGwHbVCBxBIZy+UyEokEFhcXsbCw4PiiFpaDxn6PYfa/MRRF0VMtE4mEPlzazwUOzUEbLjwsquMKG8KdSCQwPz+v3zFnQ7iNd/WthnCbhVuYM5N4ETZ0HNEjrBloiUTCts/NPM+tUqno789sNmtZLskqSZw6aGbBSAQHCTTCV+wGS/stzBhhCzSvc9BarRZWVlawsrKCfD6PGzdu4PTp065fo7B60Ni2w3TQzMOlr1+/3jFc2k/clhv6tU2z4OolwuIs0BhxdkDiut8M82vPhnCPjY3hxIkTHc+zGsJdr9chSVKoQ7h5iNk3l//HGXLQhge7sWJufzC+P5lwM89azOfz+nm2v7+PfD5vmfxaqVS6SjGJ4IjO2UbEGj+DP9wQ5qBowL1AMiYyzs7O4pFHHsHs7Kzn1yhMgRZWgiQArK6uYm9vDxMTE7hz5w5Onjw51PPMrZvlB6NU4hh3ccMDTsVxryHcxgAE88Iwk8nYCje/fv9xFvgMdiOIF4EWZDLhMAnLQXNLr/enLMv6+3N9fR2SJOGdd97Rk19LpRL+6Z/+CVevXsWDDz6IVqvlKu2Y8BcSaMRADCP4ww1RcNCcbL9araJUKmF7extnzpyxTGT0wig5aGy4tCiKSCaTfYdL+0lUBlX3e35cBVrc4eV1H/Qzmy0Mew3hrtfrPYdws3IsL8l1PJTUsfd8HMRAPxRF8ZSaG0Wi5qB5IZVK6SM7qtUqMpkMLl++rCe/5nI5vP3223jnnXfw3HPPoVwu4yMf+Qg+9alP4cEHH9T/3LhxAzdu3HA0Q9SOz372s/jkJz+Jj3/84/ibv/kb2+d94xvfwKc+9SmUy2VcvXoVf/EXf4EPfvCDnrcbJ+J9thGhMczgDzdEOSTEKpHxfe97n20io9/bHzZBOWjm4dLj4+O4dOlSYOIMoDloQcGDAxJXhvna2wUgGO/o+zGEm4cURybQ4n4cAD/jAoD4OGhOkWUZ+XwewLvJr+95z3vwnve8B8D9z4OzZ8/im9/8JgDgzTffxJtvvokvf/nLePPNN7G/v4+33noL165dc73tl156CV/60pfw0EMP9Xzeiy++iI985CP4zGc+g1/+5V/G1772Nfz6r/86XnnlFdy+fdv1duMGCTTCFcYyxtdffx3ZbBZXrlwJ7WKSSqXQbDZD2TZgLRBVVcXW1hZKpRJarRYuXryIRx55ZKCY917b59VBsxsu/YMf/CCUwI4o9KD5+fwowcNiNO7HEIY4Nt7RN8KGcDPhZjWE2xxOwma58eCgDbs1ICioBy269EtxZH1sN2/exIULF/D+97+/4+t7e3ue+tNqtRp+4zd+A1/+8pfxp3/6pz2f+/nPfx7vf//78fu///sAgE9/+tN4/vnn8YUvfAH/7b/9N9fbjhv8nG3E0LAL/kgkEpBlOdQLSRRKHFmZp6qqAyUyeoE3B808XPr8+fNdw6XDSlSkEsfhE9f9j+t+G4nSMXgdwq2qKkqlEqampjqEW5xEm6IosdrfXvB0LCwZkRf6pThWq1UAsK1UMQ7gdsPv/M7v4EMf+hB+4Rd+oa9A+973voff/d3f7Xjsl37pl/Ctb33L07bjBgk0whZz8IdRmAmCgHQ6Hap7BYQv0Jj4evvtt7G+vo5cLuc5kdHr9lut1tC3Y7dtv0SLm+HSoyTQzIvmQv0x2+fXhe9GapFNxIs4lJf2G8L9gx/8APl8HqIodgzhNg75jfoQbh766BjkoEWXfgKtUqkgk8n42pLx9a9/Ha+88gpeeuklR8/f2trC6dOnOx47ffo0tra2fNunKMPP2Ub4BusvMyYyMlFmvICn02nUarWwdhNAuCmOoiiiVCoBuH+3adBERi/E3UHzMlw6KmIpiG1em/5V4NDZ80/hffjg4wDqQL3ww6Hum99EXRiMAnEQaHawIdwAsLCwoAs446wo9sduCLexbDJMUUECLZrw2IPWK2Hz8PAQ09PTvp2Lq6ur+PjHP47nn3+em+CYYUMCjdCxCv7oVQsftnsV1j4YExnn5+eRSCRw69atrkGSQRBm1P0gDtogw6VHwkE7eBBPXHT38Sxp774PMrWHAQDt8Z/4ulvDJs4OYFzFDfDu6x7nYwC656AZZ0UZS7KshnCvr69HYgg3T8EaPAk0nhw01rLSr8TRnMY6CD/84Q+xs7ODu3fv6o8pioLvfve7+MIXvoBWq9V1rszPz2N7e7vjMbbuGgX4ONuIgTDG5LMULCeDpVOpFCRJCmgv7fchCIHGBjqWSiVUKpWORMZ/+Zd/CU0khekgehGHVsOl5+fnXS0M49AP5pmDB/V/GgWXkbTQ/bFt99xM7WHIUKCOv+bP/hGWxFlYAnwINNYr7XSWm90Q7na73SHcgh7CzZODxpPY5MlBYyOR+pU4Tk1N+faZ8PM///N49dVXOx772Mc+hhs3buAP/uAPLF/be/fu4dvf/jY+8YlP6I89//zzuHfvni/7FHVIoI0ofgyWTqfToTtow47ZNyYyNptNXLx4sas3Ksyo/7g4aK1WC8vLy1hZWRl4uHTQ89eAgAZVHzwIGQpS6L0IMIqxtJCyFWeMFJKQa7dRS/wAuVwukovwKO7TKMGLQAMGG/AsCAKy2Syy2WxXOILVEO56vY52u+3rEG6egjXIQYsmbL3Sz0HzktJox8TERFc0fqFQwIkTJ/THP/rRj2JhYQGf+cxnAAAf//jH8XM/93P467/+a3zoQx/C17/+dbz88sv427/9W9/2K8rwcbYRjvFzsHRUShyZ8+fnRU2WZayvr6NcLgOAXoJndbEJO+o+yg4aGy69traG2dlZX4ZLhyFKh+3ayQfuZ8kAQEO7HxDTT9SlkMS4+iT+v+98wXIhGRXhFncnKu5E4RzwyrDnh9kN4ZYkqUO49RvCXSgUkMlkes5y40GgsfUFLwKNJwdNkiQkk8me7xXmoAXJyspKx7n/9NNP42tf+xr+6I/+CH/4h3+Iq1ev4lvf+tZIzEADSKCNDMMYLB2VEkfg/oenH3PG2u227vTkcjlcu3YNp0+f7vk6hSlUwxaHdr9/83Dpp556qmvWkVcSiUTg590wQ0KM4qyf0Or4Pigd/3Yi0v6Hxz+O9cZ/R61W63ABBEGItHAjhgs5aN5Jp9N9h3DX63XHQ7h5EWjGgLG4w25s8+Sg9TuWw8NDXx00K1544YWe/weAD3/4w/jwhz881P2IKnycbYQt5ph8AI76y5yQTqd14RfWnSW23UFFiiiKKJfLWFtbw8zMjKtExrBFUtDlfgwrJ8tuuLTf2+UlJMSrc2b5s2xEWkOTkBPS+r9P5/4LTueg96X1my1lFG7j4+P6QtLPxXychQEQ7wREgA+BNmwHzS1eh3CzfrZyuRzrGyXs2sCD68RuwPJwLED/BEcAODo66oq4J4KFBBqH2A2W9kuYMYzuVVgfXIIgDORgmRMZvTg9YQu0sMWhk+HSfsKDQNM0DccHDyBvCPyQNBUSrLfBBBbD6J6ZH7cTacbtpIUEErXbUMdf6zlbqpdwsyrdGlS4UYljOPDwusdFZPYaws1uFIqiaHmjxGqWW1QdKtZLF/XfhxN4EpuAMwetUqng+vXrAe0RYQUJNI7wI/jDDYlEQi83y2azvv98p7gVaOZExoWFBTz77LP6HJ1hb99PwhRogiBAFEV8//vf7ztc2k/iPAeNCTMAujgTfxbykYb9QssosMxizYwMBaImY1LIdnyfEV0MHt/A2MR/Wj7HiXCr1Wo4OjrC5uYmGo2GPo/KrXDjYREXZ+IibnrBSgPjegyJRALj4+PI5/NIpVK4ceMGgHeHcBtnue3u7kIUxUgP4eYxwTGu55YZJwLN75AQwj0k0DjAz+APt0QhydGpQFJVFdvb2yiVSmg0GpaJjF6IiosV1MXDOFy63W7j2rVrfYdL+0lYISFuYrzNqKqKjY0NTObeB+C+OBONaYw9xJmZo58Fg+Qt4vaN2Ikz4zbtHLteGIXbqVOn9MeZA8AWkWbhxnptWJlkoVBANpvlZtETZ3gQaHEvM2WYe9DYTY98Po+5uTn98agP4aY0yugiSRIJtBhAAi3GDCP4wy1RSHLsF3PPhiKzRMbFxUWcO3fOtw/cMGP2jT14wxZI5uHSJ0+eRK1Ww6VLl4a6XTNhlTgC7u8KK4qC9fV1FItFJBIJPHILOFZVIDH4+SJqck+RJkHtK/zSSKDZw0VzA3MAzAPbzcKN9dyIoqiHJTD3+uDgANPT07ETbnEXBzwINJ7CNZx8xjgZws3+VCqVwIdw8yRqnDhOcaLf8WiahkqlQgItZPg540YIVVUhSRJkWe7oLQvj4hoFgWa3D+12GysrK1heXnacyOh1+61Wy9ef6ZQgBJokSfrraBwuvbOzg+Pj46FssxdhlTgCznt1FEXB6uoqSqUS0uk0rl+/jkLmGRyrKiZM558b98zseFmJNKMz50SkAfBNpFnRT7ixREkAKBaLaDabXSl3LKCkVzw54Z24C0yAj2MA7r8vBhl8PcgQbivh5nVfeBJoPB0LcF+g9WtLqVarXSMliGAhgRYTzMEfr732GsbGxnD16tVQL0pRido3lryxRuv19XVMT0/j4YcfxokTJ4b2OoU9i0wQhKFsv99w6bCGZIftoPVClmWsrKygXC5jbGwMN2/exKlTp3B88MB952wIMEFm56b1E2ms1HGYIs0Ko3DTNA3Ly8u4e/cu0ul0h+NWqVSwvr6ORqPhaa4U4Yy4v36qqsb+GIDhOYH9hnAbhZsfQ7h5EjU8OmjmG2ZGNE2jEscIwM8ZxzEs9MOYyJjJZHQHLUyi1IN2dHSEUqmEra0tnD59Gk8++WQggxbDdhH9FojG4dInTpzAY489ZvlBHVbEfxQFmiRJWF5exvLyMgqFQpeY9UOcOekXM7pn5u81irQDtft5Ewn/yh0HwS7lzhhPzuZKra6ueh4I7DdhfxYPAg/uk7H3Os6EEa7BhnCbP+fNQ7j39vawvLyMVquFdDptKdzYe44ngcbTsQD9Befx8TEURekS8kSwkECLAcw1Y24Jm5XCyoLCJGxxomkaJEnC/v4+isUizp07N1AioxfCdND83L7b4dKj5KDZlTi2222USiWsrKxgamrKcn7e+u6i/u9Byhv7sa20u36+FVbiLGyclJD2Em7moASzcGPpeOzf/e7+uyXuMfU8CDReetCidByDDOFmVT/7+/vI5/O+z04MEh4dtF7HU6lUIAhCIDe4CXv4OeM4xurDOp1Oh15aCIRX4mhMZKzVaigUCnj66aeHHvFuRZghIWz7gwilSqWCYrGIvb09V8OlR8lBM2+32WzqLuPMzAwef/xxS5exvHMJ6R5rEjuxNJvw9tFs1ePGkKD2dPKOVRWSJgCV6zg7/Zan7YdBMpm0HQhsJ9zS6bSt4zaKxF1gAnyITCAe6YdOhnCvr6+j2WzinXfe6RrBYXTe4jCEmzcHrV+KY6VSweTkJFfHHEdIoMUAqw+vKPR+AQjcyWOpeKVSCZqm4dKlS5BlGcfHx6Etrsw9cEHjRaD5MVw6LActTGFo7G+cm5vrWUZ7X5y9u/A1C6cDRbMVb0bhNptIuYrDtxNpB4oGQOjYJzt2q9cwN/W24236gd+LNDvhZr77v7+/31G2NYrCjQdxEyXnaRDifBxGl7tWq2F8fBzXr1/XA4HY+85qCLeVcIvK6xBESnKQ9HPQqtUquWcRgJ8zjmOsLpxRctCCcI+MiYwsHGV+fh6JRAIrKyuxdrAGxY1Q0jQNOzs7KBaLEEVxoFlwyWRyoNlgXgnDQWOzhV555RXMz8/j3r17XaV2Xd+jpTAtdL9H7wslOBJKwH2xJmkCZpP2r7HZGevlpPUiLWiQNAGSJuCdw1u4OvO6658xCEE4OXZ3/2VZ7nDczP02rDzSHJTAiLPA4UWgxf0YgHgLNCNG16lXkmuj0ei4YdJvCHc+nw/89XGSehgXWNhcPwdtenqai/dTnCGBFlOiEM4BDN/JE0URy8vLWFtbs01kjIKDFebvwsnxG4dLS5KExcXFgYdLs4tk0HcXgxRox8fHKBaL2N7ehiAIuHPnDs6cOdP3+17fvtr1GBNmXjlQtJ4izYxRpBm3LWm9XTQm0gpC+J8vQZJKpWz7bYzCbXd3F+VyGa1WC5lMBoVCAaqqQpZlVCqVgaLJw4IHgcZTSAgPx6EoSt8bf8ah9/2GcO/v70MURSiKYivchlWSx5ODxtYKvT6jaAZaNODjjBtBouKgDUsouklkDDuoJJVKQVXV0BY5vRw083DpS5cuYWFhwZcFALsYhpGoOGznrlqtolgsYnd3FwsLC3jve9+LH/zgB47uopZ3LgFIYTrx7vtT0rzvp/F7rURav4TIQYRhkC5aVAWCnXBjCXesXKvdbuO1117To8mtSiWjKtx4EGg8OWg89P4Mchx+DOE2CrdBxZUsy1z8TgDoa6Vex1OpVKjEMQKQQIsBdiWOqqqG3rzqpzhifVGlUgkHBweOExnDFmhBDIvut32zQLMbLu3nAsbooAWJMfLe73P/8PAQxWIR+/v7XX15TBj2o651ngMVNd3lRjktb7TCjZN2X7x1P9eNixakSItTWIUx4U5VVaRSKTz00EOQJKljAWmeKWVVKhn23XkeBBo5aNFiGGsTJ0O42Ty3zc1N34Zw8+SgsfLGXu93ctCiAR9n3AjCPiwkSQpdoA3q5Gmahu3tbRSLRTQaDVy4cAEPPfSQ476oqAi0sKJ4jQKt1WqhXC5jdXXVcri0nwiCEPpMMj/OfXNgyoULF3D79u0ut8zJsbLSRuaeVdThOCZO+9jY9q3KFfuJNMId7D2WTqcxPT2N6enpjq+bhdv29rYu3IwLyLCEW9wFGk8OGi8CLajjGGQIt51wM55LPDlo/RIcgfsVJObPLyJ4SKDFAKuLTiKRQDKZhCRJrpL3/IaJIy93YFkiY7lchqqqWFxcxLlz51wvSgbZBz9IJBKhJRoC9wVaq9XCG2+80Xe4tN+Ecdz9hkY7RdM07O3toVgs4vj4uG9gilMHjdFLHDllkNJIt2wpua7HTiSagblocV5cOzkvegm3Wq2mC7etrS3LO//GeW5+Czdy0KJDHGL2nRB2dQ/DjyHckiSF2sbgJ05uJFcqFSwsLAS0R4QdJNBiTBT60FiJgJsSgHa7jdXVVb387sqVK3oioxdYmmCYtfthBYXUajUcHBygVqthfn6+73Bpvwkj8p5dIL0KQ5ZkubS0hEajgcXFRdy9e7dvuYsgCD2P1RgM0ss589O1qqjpjl4389cYdS3V00WzEmcAsKWMWz4+LOJU4ugX6XQaMzMzXQtIY8mWWbj53WvDw8KTBweN9daSQBs+TodwHxwcQJZl/Md//AdSqZRlOEmchnA7EWhHR0dU4hgBSKDFALs3fhSSHI2llv3e9I1GA+VyGWtra5iamvKt/I5tN8wLQtBJksbh0uPj4zh9+jQeeeSRwLbPCMNB81paqWkatra2sLS0BEmScOnSJVeObVgDsvvRS6QZsRNpduIMANKCDOlnPXVhxO6PMnZ3/s3CbWNjo2dIQqFQ6Pu5yIMw5kHYsM+XKAsbp0RdoNlhHsOhqipeeOEFPPXUU1AURX/fVatVbGxsdA3hNgq3KA7hlmW5781ICgmJBiTQYoIgCF0X0SgMqxYEoa97dHx8jFKphM3Nzb6JjF5IJBIQBAGyLIc2UDaIWWisV2ppaQnValUPsdjc3ES1Wh3qtu0Ic2i00+2yEQPFYhGKouDy5ctYWFhwvXjotU2rWH3AuryxlyACgPlkA0D/8kZjGIlTkda9L/cdsrTDMsxhirSoLWTcEtT+Wwk3TdO6SiV7CTdWKsneA+SgRQP2+RJ3oQnwk0bJruuZTAapVKpr/qV5CPfx8TG2trYiO4TbaYkjOWjhQwItxkShxJHth1mgmRMZWVR5oVDwffuCIEQiKGRY27caLv3II4/oYjTMQdlh9d45EWiqqmJ9fR3FYhGCIODy5cs4e/as5wuj1U0SAPj2xmOY/9k6ZF8p4ESybvn9TsUQE3AnEk1X+2cUaXYllnYuWi+Yi3asjmHC5T65Ja5OTtj7LQgCMpkMZmdnO0ISzOl2ZuGWy+X0z2RZlnF8fDzUeVLDhCcHLe7HAcTXQTPTL5Z+kCHcZuEWxBDufgJN0zRUq1USaBGABFqMiYpAMzp5LJGxVCpBFEVcuHABd+7ccTQ/atB9CHsWmt9Cxej8yLJsO1w6TIEWRQfNOPstlUrh6tWrA/U4OtkmwyzOzD1cTp0q4/fOJ2uOv8eNk2bcN0lLOdq3LWUSW3v38OzJ7zneJ6fE3f2IInbpdmbhtru7i3a7jVdeeQWKoujCLahBwH7Ag2OjKAoEQYj9eyHsnnA/YULT7e/EyxBuVVWRy+WGOoRbkiTkcr2rOEigRQMSaDHB6u59lARau93GysrKwImMg+wDLw6a2+HS5KDdR5ZlrK6uolQqYWxsDDdu3MDp06d9W+xYhYTcd8+OAPR2zwZhSxnvEmnmWWtG+kX713/mhrmBuWgFoY26Nrwy4rCdqFHBLNzY5/Sjjz7aNQj48PAQ9XodiqJ03fVnpZJRcHx4cdDifgzAu2WBvByLn+uYsIdw93PQWq0WGo1G17gCInhIoMWYdDqNet3/BaEbJElCu93Gm2++iVwuN3Aio1fCSlFk+OGgeR0uPeoOmiRJWF5exvLyMvL5PG7fvo25uTnf70LbxezvK9Zlu25FkBHJJMCsRJodXoWiUxcNAP51SC5aXIl7Dxfb/16DgO2EG7vrb7V4DPI6wEsPGi+iBuAj7CSoGWh+DOE2vvfsgkD6CbRKpQIANActApBAiwlWF54wHTRjImMymcTp06dx586d0C6QUXDQvIqkQYdLj6KDvF2VrQAAIABJREFUlkwm0W638fbbb2NlZQUTExN45JFHMDs7O7Rz0OzafXvjsY6vM1G0pdxP/yoIbV+370ak9f453vZv2C5a3BfXcafX699r8cjKtURRRK1W6yrXCkq4kYMWHVipJi/HEuTAeDNuhnBvb2/3HcLdL8WxUqkgl8uFOl+XuA8JtBgTRoojS2Tc2trC3NwcnnjiCayvryOVSoW6wAo65t5q+24FoiiKusgdZLj0qDlozWYTzWYTb7zxBmZnZ3H37t1AyjEsy4zR+boz8WOFm/4zO7aU8Z5BHczNi6uLRiWO4eDVATSWa5l/nlWfTb1e7whIMP4ZNNmOB3HDS98WL8cBBOegecHLEG4A+oge9t7TNA0zMzNIJBJ6xD7dMAsfEmgxIUwHTdM0HB4eolQqYX9/HwsLC3jmmWf09K+dnZ3Qe+Gi4KC1284ciVqthmKxiK2tLZw6dWrg4dKj4qA1Gg2USiXdtV1cXMS1a9cC2TbQ6aCZ3TOgtzjzky1lUu9764WVSDPuY13LuHLRjGWXw+5FI4LF7xLNXn02ZuG2t7fni3CLe5kpwIfIBO67TjwcBxC+g+aFXkO4//3f/x1zc3NQFAUHBwdYXV3F7/3e76FcLmNxcRHz8/PI5XJ47rnncPPmTZw/f36g99UXv/hFfPGLX0S5XAYA3Lp1C3/8x3+MD3zgA5bP//u//3t87GMf63gsm82i2RxugnAUiddZR3Qw7EHVxkTGer2OCxcu4Pbt212JjKlUCqIoDm0/nBAFgdZPqBiHS589e7ZD5A4CE0lhLFCCcNBEUUSxWMTGxgZOnTqFe/fu4e233w68BMPN7LVByhvN/WdWOBVpXrfPXLR1udvRPZU81v/tp4sW58V13MVBUM5lL+HWaDQ6hJtVJHkv4UY9aNGBl4h9INoOmlvYOuXMmTMd18/nn38er776Kl577TV897vfRb1exyc+8Qn89Kc/RS6Xw4MPPoibN2/i5s2beOaZZ/DMM8843ua5c+fw2c9+FlevXoWmafiHf/gH/Nqv/Rp+9KMf4datW5bfMzk5ibfeekv/f9zf114hgRYTgnTQFEXBxsYGSqWSo0TGsMUR24dGoxHq9q1eA03TsL+/j2Kx2DFc2k9xwX4vYZSVJBIJx86hW4xO4/z8PJ5++ml91owbseQX5hRHY3mjhOAv4E5EWr9Sx14umpU4Mz8+7XNqJZU4hkPYApMN9M3n812R5HbCDUCHcGu1WpBlOfRjGQRenCeeBFocHTQ72BrFfDzj4+O4d+8e7t27B1VV0Ww28c///M9otVp455138MYbb+CNN97Ayy+/jHq97kqg/cqv/ErH///sz/4MX/ziF/H973/fVqAJgoD5+XmXR8cffJx1I0o6nYaqqr59GBpTBDOZDB544AGcOXOm7wVj2E6eE8JOcTQ7aP2GS/sJ+/2EcVEchoN2dHSEYrGInZ0dnD17Fu9973uRz+c7nhOGQEskEpAkqau8cVeZ7CtU/Og/A9BVVmgUaXZpkkykuSnBLEtztvvMwkIYlOgYf6IqauyEG1tE1ut11Go11Ot1NBoNFItFlEolW8ctisdohBy06NEvVCNOyLIMQRB6/m4qlYre05bNZnH79m3cvn3bl+0rioJvfOMbqNfruHfvnu3zarUaLl68CFVVcffuXfz5n/+5rZjjGRJoMYbdBZEkaaAPw2azqacITk5Ouk4RjIqDFoWYffNw6UuXLg19Hhz73Yc1j8yv7VYqFSwtLWF/fx/nzp3Ds88+aztQM4z0SKMorCgFzLkoMZS0FHaUCcuvLaQOB9ovp06aHWYXzc45s6KiFHxz0axCWIhgiKpAsyORSHQJt5dffhnnz5/H+Pi47rbVajVsb29DFEVd7DHBNj4+jkKhgLGxscgcOy/hGjwJNDa4nQdYxH6v871arfoesf/qq6/i3r17aDabGB8fxz/+4z/i5s2bls+9fv06vvrVr+Khhx5CtVrFX/3VX+Hpp5/G66+/jnPnzvm6X1GHBFpMsHpDJRIJJJNJSJLkqWTOKpHRyxszjDRJq30IU6AJgoBGo4Hvfve7joZL+73tMOPuB3WyDg4OsLS0hEqlYtvnaCasEsfdk/ebl5k427VwpazETi8HzSiIvIq1XgIMcObyucHoom1IM/i/Nz+I/+nM/+vbz48bcRM4ZuK+/8C74oYJMPPXjKWSZuFmdtvCEm68OGi8CE2Arx60fjPQgPs3Sv0WQtevX8ePf/xjVKtVfPOb38Rv/uZv4jvf+Y6lSGOlloynn34aDz74IL70pS/h05/+tK/7FXVIoMUct+WF5kRGP8IqolDiGFbMPisLLZVKUBQFN2/edDRc2m/CSnL0KgxZb97S0hKOj49x8eJFPPzww45LQMMqcaxYCCGz8HHjQJkpS3OeRNquMunK0TPDXDTjvruJ3PeDuAuEuBP317+XyEwkEn2FW61Ww9HRETY3N9FoNHSXLkjhxotA46WXDuCvB63fsVSrVdy5c8fX7WYyGVy5cgUA8Nhjj+Gll17C5z//eXzpS1/q+73pdBqPPvoofvrTn/q6T3GAj7NuBLC7IDgNCjH2RPVKZPSCsbwvrA/loB0083Dpa9eu4T//8z9x5syZwPbBSBjzyLxsV9M07O7uYmlpCaIoYnFxEXfv3nVd459IJAK/KfCvwm8h3/9pXbgVOUwkmYVav1j7fiKtXzmiV2GZT7Qhqhn8P9u/gF85/d89/QwGlTiGAy8Omtvrj1G4nTp1quNnGedI2Qk3ViZZKBSQzWYHfg15ETY8lTjy5KBJkuTIQfO7xNGMqqr6TLZ+KIqCV199FR/84AeHuk9RhARajLDq0ehXXmhMZFQUBYuLizh//ryvd4TYz5JleSghGE73IYgFu91w6UajgTfeeCO0hU7UHTQ2smFpaQmtVguXLl0a6DwMw0HLJ/qnVW5IM46e54R1eWbg/jTAugzTClHNdO17LxfNHBbil0gjgocXgebXMSQSCYyPj+upscZtGIVbtVrFxsYGRFHsKK80/nEj3Hhy0HgRNaPooJkHXw/CJz/5SXzgAx/AhQsXcHx8jK997Wt44YUX8NxzzwEAPvrRj2JhYQGf+cxnAAB/8id/gqeeegpXrlxBpVLBX/7lX2J5eRm/9Vu/5ds+xQU+zroRxs5BkyQJq6urWF5eRjqddpzI6IVkMglBEEIVaCzFcVgLjX7DpY1BHWF8mIcl0Po5aKqqYmtrC0tLS1AURQ9NGfTiHbRA+7+WfwF5i7eO0ZHakPy7qDHcijSvLtqg+85ctEGIu0CI8/7z4FxqmjZ0cdNPuLFEyUqlgvX1dTQaDUvhNj4+jkwm03XOqKrKRWKgoii+VOdEAZ4ctH4CTdM03wXazs4OPvrRj2JzcxNTU1N46KGH8Nxzz+EXf/EXAQArKysd79vDw0P89m//Nra2tjAzM4PHHnsML774om2oCM+QQIsRVg6aWaCZExlv3bqFubm5oS4eBEEIPaSDfej4LZCcDpce1vadEjUHTVVVbGxsoFgsQtM0XL582dfQlDAcNCvMwmYQ98xuQPW6PNOzNNGqL84rVi5aL6xctC+t/Y/4385909P24yoU4rrfDHLQBsNOuCmK0uG4GYVbKpVCoVBAPp/XSyUlSQrtJqef8BQSwpuD1u8GgN8ljl/5yld6fv2FF17o+P/nPvc5fO5zn/Nt+3GGj7NuhGECrVaroVQqYXNzE3Nzc3j88cd9vQvSj7CTHI1lloN+mHoZLp1IJCAIQigiCYiOg6YoCtbW1lAqlZBMJnHlyhXMz8/7fmc7yJ67++7ZfdGyK09gLnUcyHaNbEgzOJt25qQZXTSr8kazi9bPPXMaFmJ00drttuuFZtwFQpzhQaAF4aC5JZlMYmJiAhMTnSM2zMLt8PAQq6uraDab2N/fx+HhYZfrZuW4RRVeShxVVeVKbMqy3DVT1Iiqqjg6OsLs7GyAe0XYQQIt5siyjN3dXaytreHs2bN4+umnu+7iBUHYSY6JRGLg4IhBh0uH6SKG7aDJsozV1VWUy2VkMhncuHEDp0+fHtqCIiwHza048zMF0atIC5rppIh/+7d/Qzqd7ghRYP/m5W60mbgsnq2IorhxS5xEpp1w+8lPfqK/X+r1Og4ODnThxhw3c6lkOp2O3HHzFHYCgJvPrH43sKvVKjRNC/TmPmEPH2fdiMA+hJmQKJVKODo6Qjab7evwDJuwSxzZPngRKX4Nlw5LJIW5bU3ToCgKvvOd7yCfzwdSUgsEJ9D+a/FXMf2zm6dm92xDmsZ0Uhz6Phgxi7Re5Y29wkF6JTo6CQsptU51fP1c5qDj/+9c+z/xP098RXcI2OdVu91GNpvtEm7srm7cSwXjTNQW+W7QNI2LgA1VVZHP57vSgBVF0d9LZuGWTqctw0nCLJXkxUFja5q4n1eMfimOlUoFiUSio7+eCA8SaDHCWD4myzIWFxexsLCA9fX1UMUZEH6JI9sHNyLR+HomEglcvnwZZ8+e9fxhzIJKwiBogdZut7G8vIxyuQwAuHPnTiDCjBGUQJtOiqirWdTVzoZ3K3HmV3pjP9w4ab2oKAVPwR5mcXb/sTkAwOl0VX9samoKU1NTHc9rt9sdC82NjQ3U63XIsgxBEFAul3F0dKQvMvP5fCwWR3EXlmH2b/kBe/3jfAyAfYpjMpnE5ORk18JZluWOUsn9/X0sLy+j1WqFKtx4EWis/yzu5xXDiYM2NTUVi8/cUYAEWoxYXl7GysoKLl26pAuJ3d3d0IUREB0Hzck+sOHSy8vLyGazuH79ui/DpcMalg14HxjtFjb/bWVlBdPT03j44YfxyiuvYHZ2NtCLWFACraLkkRY6X9cNyf8ZMXYBIQAsRZQTkTZIv5xdWIiVOAOAtKBA0t5dkE0nRcuwkEwmg0wm01FCo2ka2u02fvjDHyKfz6PVamF/fx/1eh2aplnOnMrlctwsmqJCnF9PJtDivrB06wKmUilb4Wa8EbK3t9cl3Nj7iYWU+JkeyYtA4ynBEegfEhLEDDTCOSTQYsTi4iIuXLjQcSENu/crSvvRz8EyD5e+c+cOTp486dvCJMwSx1Qq5XjwoxeazSZKpRJWV1dx4sQJPPHEE5ientaPN+ikqyAE2n8t/mrH/40CJAo4SW/sJdLclmi+3TzTJVbNbEtTHS6aEwRBQDabRSqVwtzcHObm7rtxmqah2Wzq0eWsVLJer0MQhK7eNr+GBXuFB4ETV9hnQZx/B4B/c9BSqZSlg20Wbru7u6jX62i1WshkMpaOmxfhxkuwBk8JjoAzB216ejr27yNe4OfMGwGsygjt5qAFzbAFgtN9sBJodsOl/SbMEsdhOWiiKKJYLGJjYwNzc3Nd89/YYiLowI6gHLRB3TMrx+lSdmegfTLuy9l0xZefZYXRRWMljE7YlqYgKvddPzeR++ZFgSAIyOVyyOVyumgD7p9rjUYD9XodtVqtY1iwMUjBKNx4iC4fJnEK2LCCJwdtmMLGTrhJktQxx43dCGFprG6FGzlo0UNV1b6C8/DwkBy0CEECLeak02n9jRfmB0kqlUKtVgtt+2wfjCLl+PgYpVLJdrj0sLcfJH67d8bB3PPz87bpoIIgBFZeaWTYAs3snpnp5zyVWnO2bpNRtA0q1uxE2q480fFvOxetouRduWiSlrQ9LnOZoxecODmJREJfJJ469e5raYwur9Vq2N/fx8rKih6kMMxEybg7UHEXaOSgDUY6nbYVbkbHzUq4Gd9XhUJBvxbFXSwD/AhNwFkiJZU4RgsSaDHC6uLD3mySJIX6QRKFEkfmoDkdLu03PKQ4Hh8fY2lpCTs7O45fuyBnkjGiMqjaiBuX6d3vOQVJS+JSdncIe2SPGyfQy3Hlk23dRQsKu+hyY1lXrVZzlCjJy6LMKXEXaGz/43wMQPTi6dPpNKanp7sW7Wbhtr29rQu3bPZ+oNLy8jImJyf191YcSwX9mKsaFSRJ0m+o2nF0dEQCLULwceaNMIlEAslkEpIkjXTMvqZpkCQJOzs7WF5edjRc2m/inOJYrVaxtLSEvb09nDt3Ds8++yxyuZyj7+XRQTPTzxnalqZ6fr0fTASZhZqTlEUnpY5eXbTXxQXkk97TKQ+lguMyx2Etru3KunolSuZyuS7hlsvlei5u4iwO4i7Q4p5CyYjLqIBewq1SqeDVV18FAGxtbaFer0OSJGSzWctSySgLIJ4cNCY2e71PDg8PaQZahIjuO4NwTFTcqzB64dhMuKWlJdRqNRQKBTzzzDOh9JyE2Yfn1cU6PDzE0tISDg8PPYvasBy0YYlCVt7YLxCDUWrODSRiOn5Wa86TmzbsfjQjwyxzDLJUsFeiJOvFYaWS/RIl407cBRovg7bjItDsYKXEAHD9+nX9nDLfDDELN3OZZD6fj4Rw48lBc3IsR0dHWFxcDGaHiL7wceaNCHYX0CgEhQQtEq2GS6uqikqlElogQNgOmtNta5qGg4MDLC0toVqt4uLFi3jooYc8v25hOWhAMHecN9vTOJm2dp9KTevyP6fizvJnOhBpFSVv+zVj/5n58bnUsWV5o5WLxo5NVDKeBCgrczyUCvijn/6v+NMrf+v6ZwQNS5TMZrM4ceKE/rhVouT29jZEUYQgCEgmk0in0x0uQZiJkl6I076a4cFBYzcn4u7YsKAT4+/D6mYI0NvFHhsbs3Tcgnx9FEXxdfxAmPSL2Afu96CRgxYdSKDFDEEQuu4yx3FItFd6DZdeW1sL1UkMOySkn4ulaRr29vawtLSEer2Oixcv4tFHHx34AhSWgwb4L9D+5K2PYCYN7EkTOJOpYLPdLWYOpQIOpeH2NJZac67j6p2WOg4bry6a1WdbVOiXKPnOO+9AluXYJkrGXeDw4KCxz9C4H4ebPjo7F1uSpI6bIb2E2zD7Rlm5Mw84cdBIoEULEmgcEAUHLZVKDTVN0slw6TAFEhDdkBBN07C9vY1isYhms6nP0/OrdCNsB81PFCSwJ90XMVbizAq/yhvNeJkptiFND+TeMeycQUavMkc74uKiuYElSubzeSQSCVy5cgXAu4mSbJG5v7+vDwo2x5b7nSjplTgLtLgLTIAvgTbIGkAQBGQyGczOzmJ2dlZ/nJUf9+obNbttgwo3nuag9RNomqahWq129eoS4cHHmTdCWN1ljoJAYy6M33ND3AyXDjuoJOwSR7NI0jRNLwOVJAmXLl3C+fPnfRfQYTtofiBJEsrlsuXX7MobfdluD6dJVDIoKXO4NOZfwmOvcs1eYSGDljmOJ1uoKdmez437AttI3BIlo+pcOoUHB419fsf9fTCsm7TG8uNewq1Wq+Hw8BD1eh2Kogwk3HiagyZJUl+xWa1WO15bIlxIoHFAFEJCEokEEokEZFnWY3YHwctw6bAFWhRKHDVNg6Zp2NjYQLFYhKZpuHz5MhYWFoa2gAnLQRMEYWCB1m63sby8jOXlZbx4/isAer9Gq81ZjCeDDYIpNTtFWq/+M+b+ncnYlzruSRM9RWc/94zhxUX739/8BL7w4N/Yfj2uQsHpfjtJlKzVagMnSnrZ/zgLg7iHawDvHkOcfw9A8MmHvYRbq9XqcNx6CTd2Q8R4Ho2SgwbcF2hU4hgd+DjzRgirD+90Oo16vR7C3nTih0AyDpc+ffo07t2713UXepjbH4SwSxyB+7NnyuUyEokEHnjgAZw5c2boC5cwHDRgsKj9druNcrmM5eVlTE9P4+7du3hx9ys9v2e1Gd6dRbNIGxa9xJ8Tio2T+r/Pjx12fX067Xwo9ijhNVHSnH6Xy+U8LfDjLtDivv8AHyITiE40vSAIGBsbw9jYWFfgj51wU1W1Q7i1Wi20220ufjf9bp6LoohWq0UCLUKQQOOAKISEDLoffgyXZg5WWBfrsAQiC04BgNXVVcv+vGEShoPGtutWoJmF2eOPP46ZmRn8H2/8L8gl7S/ATJw5cc/86AGzwo1I22xPD+SiWdGvzNEozgCg9LP/n84cAUDfMse4L7D9pleiZKPR6BoUzBIlzb1t4+PjyGQyPV/fuAscHhbQPBwD8G6KY1TpJdyazSbq9brePyrLMt5++2289dZbtqWScfmd9UtxrFTuXy9IoEUHEmgcEIUeNLYfbgSKpmnY399HsVhEtVodeLg0s++dxMkOA+agBbXYkWUZKysrKJfL+mt29+5d18J2UOLgoLXbbZRKJaysrHQIs340lDRWlejU5Jeac5hJe3PLnYSeuC3hlLQkVpvWr2NKUCBrSWy3J3WRBvQuc4xriSMQnMAUBAH5fB75fN4yUZI5btVqFevr62g0Gn0TJXkQaHHefyD6wsYpblIco4QxqZWxs7ODJ554AolEouOGiNVsRKOj7XcJsh/0K3GsVqsoFArcjBXgARJoMcOuxDEKAs2pg2RMFWw0Grh48SIeeeSRgeOn2cUtrNklqVRK7wEb5mLB2Dc1Pj6uB6d8+9vfDk0oRdVBMwqzmZkZPPHEE5iedpbO6IRBEhz7BYS4hfWfMby6aDUl61iklRonkXLgGBpFGo9ljlEQlixR0nyDxkmiZLPZxMHBgf7/uPXdxF1gAvw4aFEpcRwUVVWhqirS6TQymQxyuRxOnny3SsDouPUSbuYS5LB+x/0E2uHhIaampmL/PuKJeH0KE5ZEISQE6F/iqKoqNjY2UCqV9OHS586d820xwAbGhpmkCNz/IBzGrCOWaLmysoKpqSk8+uijmJ2d1T9Qw+qBC+s17yXQWq0WSqUSVldXMTs721OY3S9vvH/e7rXHcTJTG9o+D0pNyaKmZHF+7CCU7XtNcwSAlcYsZjP33T8rFy3Kc9DiTL9EyVqthuPjY1SrVezu7oaeKOkFHsRNXJ0nM7wINHYttTsWo+NmFm7mEuTd3V2IohiqcOuX4litVjE9PU0CLUKQQIsZUXbQ7IRir+HSfhNmUAg7Hr9FUrPZRKlUwtraGmZnZ23L88ISaFFy0MzC7Mknn/Q812WzOeXJ7TH3YjEu5/Y87YcVq81ZRyKNuWhOyxsZTlw01mMma0lbF42VOZrh0UWLG8ZEydXVVVy5cgWzs7M9EyXNi8thJEp6gYeYfR5EJhBeBYvfyLIMQRBc/07sSpB7CTcAtsLNL8HUz0GrVCq+VpcQg0MCjQPS6fRQh0Q7xeygORkuPYx9CEugCYLg6/ZFUUSpVML6+jrm5ub6io2whFIUetCYiF1dXcXJkyc9CbN+7lkvwcLESq9yPybc/BRqTuglzryGhWy3J13vRzYp46Bd0F00M3G+cxv3Ejvj/tslShqT7/olSo6Pj2NsbCyw1+T/Z+9dYyS3z3PPhyyybn2/90x3z6VHo9GM5qIZjWTNSBo5H+KrghjBagGfPZCdXQcHiORYMeAg0doBNnYiK7Hh43MEy/Y6toINdAw4kOXAOLBX8EIXYxTFluxYI1nyVFXfu6uvdb+zyP3Q+nNIFskii6ziZfgDxvLUdBdZVSzy//B53+f1+vsP+Eeg+aWXjsxAs+u40usdJaWSpAx5a2sLpVJJ/B2rwo2UawYCzVsEAs1jaA1oBvYFkdMCjUS1klK8wcFB3eHS3dgHr0ftl0olpFIpbGxsmBo1cDM6aNVqFb/97W9FYXbPPfdgcNC4ePiLtz8JYF+cSTHqni1ouGV6pCTO01ELYs2oi2Y3y5VRREKdf8eISFMrcwxKHJ2h3fuul3wndQWKxaLlRMlO8IO48YuwcfpGsV306nXQNK0b+qP13TIj3MiayEiJY4B7CASaD6BpGqFQCI1Go+MERDvgeR6ZTAYvvfQSxsbGDCfl2YkbBFqn2y8UCkilUtjc3MSBAwdMjxpwsget1w5atVpFpVLBu+++i8nJSdPCTEpJEf2+UTXmvHXiIilZqIy3iDQzASFEpCkDQsyw0xhApdlakmQmLCQoc/Q2nZYIWkmUVM5ws9K365cUR6+LTMA/vXRGBjt3E63Qn3bCTSna+vr6xGNLT3AGDpr7CASaT3AyKIQMl97Y2ADDMKaGS9uNkyEhwI1ZbGbI5XJIpVLY3t7GzMwM7rvvPsTj5gcG3wwOWrVaRSqVwurqKhiGwZEjR3DixImOnuvBV/8SB+NxsPSNfTcizpYr+71aVlwkqWBRE2lqaM0QMyLO7Ao/Ia+91mQ6ev2REIdak8FevQ/lZljmonl9ge1l7HYurSRKKsWbkUWyH3rQ/CJsAgetuxgRbsViEfl8HhsbG6hUKmIA09tvvy2b4RaNRsVjLpfL4ejRo068pAANAoHmMbQWMU4EhUiHS8/MzODkyZNYWVlxTJwBnQkkOzEjkjKZDFKpFPb29jA7O2tpBhzZthO9YL3YbqVSQSqVwtraGiYnJ3Hp0iUkEglLd90PxvOyvzf49hdjIlDshpRKdlLyWGmyYgqlGsryTTWyjbiqo2XGRbMDr5Y4er0Hqlf7byRRkgzeLhaLYlWIMphEmSgZOGjuwa3CxixOO2hmkQq3yclJ8XGSnk3mpRLhtry8jE9/+tM4fPgwjh07hmKxiFgshuXlZczNzVn6Pj399NN4+umnsbi4CAC4/fbb8dd//df48Ic/rPk7P/jBD/CFL3wBi4uLOH78OJ588kl85CMf6Xgf/IB3jr4AEbU46nYR93ahN1x6d3fX8bh/p0sc221fEATs7e0hlUohm83i0KFDOH36NCIRdXfEDE7G3XdLFKsJM7K467Ug7ZY4k7JQGZcNdTbKRnUIB6I53Z/RctGMlnS2o5MyxyIX0R1cHdAbnBaY0kRJKUYTJUulEiKRiKdFjpf3XUrQS+cuaJoGy7KIRqOYn58XH79w4QLm5+fxm9/8Bm+//TZeeuklvPvuu3jmmWcQj8dx6tQp3H777eKfe++9F/397W/2AcDs7Cy+/OUv4/jx4xAEAf/0T/+EP/zDP8SvfvUr3H777S0/f/XqVXz84x/HE088gQcffBDPPvssPvaxj+GNN97A6dOnbXsvvEaJ3U0yAAAgAElEQVQg0HxCtx00I8Ol3TCPrVdCVQstB00QBOzs7CCZTKJYLOLw4cM4d+6crfPS/OSglctlpFIprK+vY2pqCpcvX265OBgZVK3Ff3r9z9HPQFbeKEXpJu3V2/cCGhnYbITlyigOxZyZc6aHUqBaLXOMh+qyfjuvOyBex43vv9FEyUKhgEwmg3Q67XiiZKcEwsZdeM1B00PttYTDYVy8eBEXL14EAFy+fBlPPfUUHnzwQbz77rt466238NZbb+HnP/85vvWtb+G5555TFVdq/MEf/IHs73/7t3+Lp59+Gv/2b/+m+hxf//rX8aEPfQif+9znAABf/OIX8cILL+Cpp57CN7/5zU5esi/wx9F3k6HmoHVLoJkZLk3cIyfvxjIMg0ql4si2gVYXSxAEbG1tIZlMolKp4OjRo7h48WJXTvx+6EEzIsyk2+1UoPUzxsv2VisjHQ9n7hQzIi3b2O9XtOKikefRKnPsJkXuxvN7tcTR6zjtoJlBLVHyt7/9LSKRCKanp3XDE5TCrRuJkp3C87wv5of5RaD55XUA7cWmIAjIZrMYHR1FJBLB2bNncfbsWVu23Ww28YMf/AClUgmXLl1S/ZlXX30Vn/3sZ2WPffCDH8Tzzz9vyz54lUCg+QS73atOhkszDANBENBsNh278+SGEsdmswlBEJBOp5FMJtFoNHSFrV2EQiHU670VEmS7Vh20crmMZDKJjY0NTE9P6wozghWBpmSzMoDRSKs4Wa2op5BaCQjRo9a8cXxIRVqnIqld/5nR8kYjDiLQWZkjAPzR63+Nv4n8r4a24Ua8JHDU8Pr+k/JArUTJcrksCrdsNqubKNnf3++IUPKTg+aHUk2O42xpPXADHMe1PaZzuZytqdtvvvkmLl26hGq1iv7+fvzwhz/EqVOnVH82nU5jampK9tjU1BTS6bRt++NFAoHmQdQupCzLolRSHwBrBulw6Wg0ittuuw1TU1OGLt5EfDhZGuB0iiNN08jlcnjllVfA8zzm5+cxMzPTkwuv0w5aJ4s86cy36elpU6MFaJruyDUm5Y17tTimYvtDms2IM6toiRQ1zJY7WnXRzGJ3mWOAM3hdoOmlONI0jf7+/pYbPt1KlOwUP/Sg8TwPQRB8IzT98DqA9muyZrOJQqFga8z+iRMn8Otf/xq5XA7/8i//gk984hN46aWXNEVaQCuBQPMJVnuv7Bgu7YZ5bE6lOPI8j7W1NaysrEAQBJw8ebKt42g3Ts5BA8wt8kqlEpLJJNLpdEcz34DOHTRS3kjEmZp71i1x1gnLlVGMhq3ffDGCWpkjeS86LfNcKN4YbMwLFA73Z1p+ZjBcw5/n/xXfGfjfOtpGgDW8XlraSYqj1URJItyUiZKd4gfniVx//CBsnKwEspt2a7JsNgsAGB21LwgrHA7jlltuAQDceeed+MUvfoGvf/3r+Na3vtXys9PT09jc3JQ9trm5ienpadv2x4v44+i7ydBy0DoRaOVyGQsLC1hbW7NluLQbSgx7uf1ms4mVlRUsLCyAZVlMTk6i0Whgdna2Z/tAcNJBA4zdAS4Wi0ilUqIw63TmG9lupyWOUvfMy5D+Mym9dtGUkDJHqTAj0JSApeL++WVa8f4PRKpd2Z8AfYg486uDZpZ2iZJEuK2traFYLKLZbMoSJYlwi8VipvbJLw4a4A+BxnGcL14H0N5By+VyYrlvt+B5HrWaeu/3pUuX8LOf/QyPPfaY+NgLL7yg2bN2sxAINJ9gtgeNDJcmtb92DZd2OsmxVwKN4zhRmEWjUZw8eRJTU1NYW1vDxsZG17evhtMOmt4dx2KxiGQyic3NTRw8eNCSMCN0ItD+0+t/jnpzf7ubFfXjXRpaARhzjuxKcNRitTKC2Vir86TFRnVIM6FS+jNqaIWFaKFW5qgmzpSkKwOYjhVkZY5edXK8XCLoB4HWizloRhMld3d3USqVIAiCbH5bu0RJPwg04gJ6+Vgi+MlBayfQMpkMhoeHbTv+/uqv/gof/vCHcejQIRQKBTz77LN48cUX8dOf/hQA8PDDD2NmZgZPPPEEAOAzn/kMHnjgAXz1q1/FRz/6UXz/+9/HL3/5S3z729+2ZX+8ij+OvgDDDppyuLQdC2UpTsfcd1ugNRoNLC0tYWlpCfF4vKUU1EkH0SmBRl672raLxSISiQS2trZsE2YEO0NCCOvlQQyGezeY2QxmRZpd2ySUm2FDYnWpOAKaMia0VorDGIvti8HBcA2f3f0unjvyN53tbEBH+EGg2emgmUEtUZLsT6VSEUWbkURJP/Q8+aFMk3CzOWh29p9tbW3h4YcfxsbGBoaGhnD27Fn89Kc/xe///u8DAJaXl2XHyeXLl/Hss8/i85//PB5//HEcP34czz///E09Aw0IBJonUbuQ6gkjveHSduOGEkee522/G1mv12U9enfccQdGR0dbPgunRBLQ3YHRelAU1ZLkWCgUkEwmsbW1hZmZGdx///2IxWK2btesQHvw1b9EVOWCqxYQokcvEhylSEM0zIi0zcqAbhnnXi1u+rW3g5Qv8gJlWKTtVuKiSAvoPX4QaG5znyiKMp0oCQDJZBK7u7uOJ0p2ih9EJsFvDprecZTNZjE0NGTbOeAf//Efdf/9xRdfbHnsoYcewkMPPWTL9v2CP46+ALAsC57nZSdII8Olu7EfTgo08to5jrPldVarVSwuLmJlZQUjIyO48847dXv0nEyRdCogBbghDnshzJTbtIv18qBtz6WFmQRHJ1HrbdPDTJojTQngBe+KAS28LHAAb++/V0pM9RIlr169ivHxcfGGqjJRUuq4dTtRslP8JNBuJgeNlDgGuAv3fcMD2qIVEgLsl+BRFGV4uLTdOF3iaJdAq1QqWFhYwOrqKsbHx3H33Xe3NI2r4QaR5AQUReGdd95BLpfD7OxsV4UZwc4Sx07FGXGM2rlFR/t3O3p+NYiLZkREablopP9Oz0VT9uIB+mWO5L0wAxtqotEMiS7aYLiGP3r9r/HdY59FX1+fZ9wDr/bOAYGD5gbIdWtiYgKDgzfORcpEyXQ6jVKp1PVEyU7xi0Aj4wLcKILN0mw2wfO87mvJ5/OBQHMh3j/6AgDsL1ZpmsbS0hI2NjYMD5e2G6dLHCmKsiSSyuUyUqkU1tfXMTk5aTo8xckSR7LtXt5NzufzSCaTqNfrGB4e7lrprBpmBNqDr/6l5r9JxZmR/rNak0FaI2BECxKaMdeXNfV7WqxWRsRxAWrs1az3+eXrEcP9eCvFYbAha8f9WmFITHK8du0a6vU6IpGIuPiUOgheXoy7DT8INK84aHqoiUynEiU7xS8Cjaxh/PRa9ARaNpu1dUh1gD0EAs2DKC9EZLg0z/PY3Nw0NVzabliWRbXqbFx2JyJRGv8+PT2Ny5cvt5ShGIH0YjlxR7eTeWSdks/nkUgksLOzg7m5OfT19WF2dran8+/MOmjR90rw9qpxjEaN9Twp3SI1IWK01wq44TKpzQLzOo1mSPbe6PWhqZU5Rpkbzvv/Rb+M/3n/58QFaLFYxOrqKkqlEnieRywWkwk3vXS8AH287P4RepHi2G3MXDPaJUpKh2+rJUqS747d3xme530haprNJiiK8sWNII7jxBv4WmSzWYyPj/dwrwKMEAg0j0JRlNgfRYIrYrEYTpw4gampKcf2y2kHzew+EAdoe3vblpRBcpfKiTQru/vv1Mjlckgmk6IwI47Zq6++anuiYjuUwSRGkYqzqkYwhxorRftKQJaKI5ZF2np5EAfj+bY/pyxzVI4XUCtz1Cv5VJY5Wn1fSJkjABRqUQxEqhiIVMGyLEZGRloWodVqVbYI3draQrlcBk3TLQvQ/v7+rvbcSvGqQPCLg+blxbQgCBAEwZK46SRRkqZpxOPxlkTJcDjc0fHglxRH0n/m5e8EoV3/GbB/XSdDpQPcQyDQPIggCHj77bexsrIiGy792muvuUIcOdmDRvah3fuQzWbFxCw7Uy2lM8F63T9Dtt0NoZTL5ZBIJLC3t4e5uTk88MADiERu9Cg5Udpp1EGTljeacc+AfTGyW7kh2K2W8UmRumlGEhydwEyZYy+gKAqxWAyxWEx2x5ek4xHRtre3h5WVFVSr1ZaQBfJfO+/0e9mF8oNA83oPGjmPdeM1dJIoSYYWK4Vbu2uaX0ocb6YERyAocXQr/jgCbzLIHBVlf5TRWWjdxOkUR0A/SXFvbw/JZBLZbBaHDh3C6dOnZULDKiRy3on3gJRk2LltImSJMNN6v5wIKDFT4hhVSRjcLveLPU9aSMWZVbSSC5eKI5jWicPXQ81FU+s/61bkvtI9s6PMkbhov3/17/DC5ccN7YdWOp40ZKFYLCKdTqNYLILjuJYyyV726rgJP/Rvef01dFOgaaGXKElEW6lUws7OjuFESb8IND8lODYaDUMOWiDQ3Ecg0DzKkSNHWhanbhBobixxJLHFyWQShUIBhw8fxrlz57pW+uR0UIgdDlo2m0UikUAmkzEkZO3arhnM9qDtVc2JrbXCkKwvqpusFIcx1288QCRfv/FZGC11NIqRREu7nT1pmSOhnXg2glrIgiAIqNfrsv62nZ0dlMv7ApWUfCnLJL0sAPTwurgBvO+gkeuFG15DKBTC4OCgLE0S2F/oS4WbWqJkrVZDJBJBoVBwPFHSCn5z0PReiyAItg+qDrAHfxyBAQDc4V65qcRREARsb28jmUyiXC7jyJEjuHDhQtdLD52chWZVHGYyGSQSCdFhPHv2rCEh66SDprfAPPPjv8fhsVZxtl1uDYCRlvKtFdqPVLAbsyLNLMreM6NolTl2U8AWalFUGowpF80oFEUhEokgEonIenV4npf16uRyOVnJlzKURDmLyqsixw8CzeuvgYScuPk1sCyL4eHhloW89GbH6uoqisUi3njjDccTJa3gJwfNaA/a6Ohoj/YowCiBQPMoWrPQSqWSA3sj34deR70rCYVCyOfzuHr1Kur1Oo4cOYK5ubme3RFzchZapwJNKsw6cRidctAA/cXZaH8ZhVoUIXp/34z0nxFx1iv3TEqnIs0OF62TaP4qx7Z9nzopc6xyvZ9/Jg0ZmZycFB8nJV/SUJKFhQXU63XROSiXy2AYBsViEfF43PULUCVuFgbtIAEbXnvPpXjZAQyHwxgdHcXo6ChyuRwGBwcxNzfneKKkFW42By2bzQYOmgvxxxEYAMA97hVgrDHVbnieRzqdxsbGBniex6233orZ2dme3wlzusTRzLalPXlWSj+dctAAc4sbqXOmLKHL1yMo1MwFxZiJ2DcKEWlmywiNiLR2ISlmUi21UPahGUVZ5hhjOVQazl+itEq+lGWS2WwWW1tbEARBloznxgWoFD+4T4C3Raaf4ulpmu44UVIq3JwsL/abg6a3FiM9uYGD5j6cv/oFdISWg+a0QCMntUaj0TOBxvM81tbWkEqlAEA80Rw+fLgn21fiZB+eUYG2t7eHRCKBfD5vS0+eUymOgHZq5Zkf/z1G+yG6Z+0wK87sQtl7BeyLtLGY+dAOqwOqSUCHEmWZYy9LQLtR5mgHUudgb28PY2NjmJmZaVmAptNpVCoVcQGq7G/r9Y0sJV4XaCSF0qsOFOBtB01Ku5AQI4mS5GaH1URJq6/DTw6a3uigXC4HAIGD5kL8cQQGAHBHDxpFUT3bj2azidXVVSwsLCAUCuH48eOYnp7G6uoqtra2ur59LdzqoAmCIAozEpZy/vx5Wy50NE2jXq+3/0EbaSfQRvuNC5ytYj9irP4xayViXyvBUY+1whBmBnItj0sDQpRsl/sxES/qPq/ZUQPt6KTMcSN/w41q8vuf40S/+n67wUUzAukhUluANptN2RiA3d1dWTKeUrT1MmDByyMCAH84aH6ZH9ZpiqM0UVI6x9VKoqQVOI6zNd3ZSdqlOGazWQwMDPhGkPqJ4BPxKG510IDuO0gcx2FlZQWLi4sIh8O47bbbMDU1Jb4nTidJuk2gKYVZN8JSnOhBIwviXm+3l2iJtE4wm2KphRH3TKvMUSrMCCGaR5OnsV3sR7NJY3ooL/ahuaXM0SqhUAgDAwOysSjAjWQ8ItzW19dRKpXEu95Kxy0Wi9kuRAIHzXn84qDZXappJVFSKtzM3vDwm4PWTqAF7pk78ccRGADAHT1oZD+6IZAajQaWl5exuLiIeDyO22+/HRMTEy2LC6cFmltKHKXjBYrFIg4fPty1FEuzkfd2bldNDN/9wpcQU7xM4tQoMeKeeQkjLprW7wHGyxzNoibOlIRCPNK5QQz3VWSPu7XMkdCpC6WWjCcIAmq1mqy/bXt7G6VSSZyBqUyUtFKe7HWB5gcHzS8CrVdz0IwkSpJUyVKpZDpR0m89aO0E2tDQkKe/P34lEGg+gmVZ8Dzv+LBIu4VivV7H0tISlpaWMDAwgHPnzmFsbEzzhOJkiiLgrINGBlXv7OwgkUigVCrhyJEjuPPOO7t6R9Cp19xOGGr1nxEBslVsjdsHnElw1MJOF43QaZmjVnlluzLH9dyQ4V5AAMiWYjKR5gcXzSjSgIXx8XHxcbU+ndXVVVSrVbAs2xJKYrTcy+sCzesJjkAg0OxC2hdKUN7wMJIoaSSa3iu0ey3BkGr34o8j8CZEq8QR2HeanDxJ2tWDVqvVsLi4iOXlZQwPD+PChQuGkobc4KDVap07DZ1CBvBubW1hdXUVR44cwcWLF3tyoXEixZFsV02gKR2xTCmGwdiNz0RLmJnadhcSHAnKmHkjIk0actKpi9YOM0EqpMxxPbdfEtnkaU2RRsocpRCRRsoc7/x//yte/8Bjne98l+m2yNHq0+E4TlYmqSz3Uva3KV0Drws0MkPMy/gtxdFNaN3w0EuUFAQBqVQKe3t7MuHmtYH1giAYdtAC3Ecg0HwETdMIhULihdkprAqkarWKVCqF1dVVjI2N4a677jJVIy0dVO3EybTXbpIgCKJjVigU0N/fj7vvvrundwCd6EED1AUaKW/MVyIYUZTKuQ21BEct1gpDqqWHRlDrP9Nz0bTKHCsNpuvloKEQj2bTXYu8djgZtMEwDIaGhmSLLHKzRrr4VHMN+vv7xWHvXhVqgYPmDgRB8JTQ1EuUvHr1KqampsQZYU4mSlqBfLf19i+bzQYOmksJBJpH0bqQuiHJsdMSx3K5jFQqhfX1dUxOTuKee+5paQ42un0nLxahUKgnn4EgCNje3kYymUSlUsGRI0cwPj4uDs3tJU45aEaEYaYUs7wdo4EXAHBg0NrAaLsw46JJ58N1ilqZI3HPOmU334f4e85nLNLblFAvQ1EUIpEIIpFIS7lXpVIR3bZ8Po9cLod6vY5XXnmlpb+tr6/PtYtPgh8cNDc6T2Yh53+vCDQtyE2/iYkJWaiPNFGyWCz2LFHSCmQdoveZ5HK5ICTEpQQCzcNQFNVy59YNQSEsy5oq8SsWi0ilUkin05iensbly5fR39/5glE6LNuJi0W3e+CIMEskEqhWqzh69Cjm5ubAMAwWFxcdcbLc5KA1uBAanPxzl5Y37hXjphf7jWYI24qySK1yPalwOzCY7yhiX4utYj8mNeLoO8GMi2a2LDSd238fQqEb75NemaMaoRCPciUiijS3lzm6HalrQNje3sbCwgJuu+022eJzcXER9XodkUhEtb/NLYIicNDcATkPe12gCYKgmuLoVKKkFUi7i96xlcvlcOutt/ZkfwLMEQg0n+GGqH2GYVAqldr+XKFQQDKZxNbWFg4ePIj77rtPd6CiUWiaBkVRjs0y6VaJoyAI2NraQjKZFIXZoUOHZCf7Xrl3StzSg3b3C18CcOP9MOKeGSnZU4ozo2zkB9HkaRwcsi/kw4xIMzoXzQzdKnOU9qF5sczRqy4OEThqi09pmaQ0FY/nedkYAPLfaDTa8/fBL+LG66+h2WyKo0+8DCkLNCqitJJYG42GaqIkz/OIxWKGEyWtYCTsJHDQ3Esg0DyMmoPmFoGmtw+5XA7JZBI7OzuYnZ3F/fffj1jMehmach+cnEVmp0giwiyRSKBer4uOmdoFxCkny2kHrVQqIZlMtv15I+6ZtExPzQXqBFLqZ6dQk6IX3rFd7jflWlmBlDmS980uiIvm1jJHLw971tv3cDiMcDgs61ERBAHValU1XIGmadnCUxqu0M3994Mo8INAIzdHvQxZN1gpT6QoynCi5M7OjhhMopYoaeWmhxGBFsxBcy+BQPMZbhBoWn1wmUwGyWQSmUwGc3NzuHLlStfCTJxMcrRLHAqCgM3NTSSTybbCjODWuPtuIQgCVlZW8NZbb+HgwYOo1MJgVPrFzFDlWGRt6FtTwy6hZsZFaxeWoky4lELKHO1IvSR0UuYoddOCMkd7MStwKIpCLBZDLBZTHQNAFp97e3tYXl5W7dEh/7Wj1MsP4obn+a6K2F7gdMS+XXAcB4qiunJMtUuUlM4+VLvpYTZR0qhAC0JC3Ekg0HyGW0JCyD4IgoC9vT0kk0nk83kcOnQIZ8+e7frFyC3DojuBCLNEIoFGo4H5+XnMzs4auvg5JdDIdnt1N5sEymQyGQwNDeG+++7D+/6/p3TF2V7RWCmfEXFm1ZFazw1hQkNgKSP2tbC7H00LNXdOr8xR6Z41m7RhB1Itbp9QrkRA0d51qtyKXd9Z6RgAKRzHyRaeGxsbKJVK4DgOsVisRbTF43FT+xM4aO7ALwJNrf+s26j1hgKtNz2ksw8ZhmkJJVEmSnIcpxvyIwgCcrmcofFFAb0nEGgeRmsWmpH+r27CMIw4jyuZTKJcLuPw4cM4f/58zxLB3OCgmV04CIKAdDqNZDIJjuNw9OhRw8KM4KSDBnR/sVSpVJBKpbC2toapqSmMj49jbGxMt3eRa4YMi7PdfJ/lckajpHODmB4ynvjYzWHN+UpE00UzixlBpodeH9rZHz2F3/zho5a3YSdeFQnd/s4yDKPao1Ov18USSWmpF4AWt6C/v1/TMQhSHN2BXwSaU+Fiamjd9DCaKFmpVMDzvK6TFvSguZdAoPkMp1McydyQRqOBa9euyRIGe4nTDhpg/E4cEWaJRALNZlN0zDq5YDvpoAHdW2hIZ+NNTk6KSZ+/+c1vbCut3M33qT5uRWxouUEEsyJNyVax31BgR6YU63gmnJnUS6330C4aVQZslAMbc7ZKQInXe9B6LXCkYwDGxsbEx3melw0Pls6gYllWtUwySHF0B34RaE44aGYxkihZLBZRKBTQaDTw8ssvi4mSKysr2NjYwJkzZ3Dy5EmUSqWgxNGluPsoDNBFy0FzQqDxPI90Oo1UKiVu//7773dsho5TaYZk20D7+m9BELCxsYFkMmlZmEm37aSD1mw2bf3Ma7UaUqkUVlZWMDExgUuXLslm05DetzM//ntL2+m2sNDDqkizgpUZcWbSHJWuml4fmlqZI3HTmLAzwT9+xy0OlLTfZnJyUnycOAbEcdva2hKvNeR8k0wmReEWj8c9JXj8IND88BoAdzloZlEmSpLexrm5OdGpfuWVV/DP//zPWFhYQK1WQ39/P/7sz/4Md9xxB06fPo3Tp0/j2LFjHYnUJ554As899xzeeecdxGIxXL58GU8++SROnDih+TvPPPMM/viP/1j2WCQSQbVa1fiNm4dAoPmMXveg8TyP9fV1pFIpCIKA+fl5TE9P42c/+5kjoREEJ1McaZrWjZ0nYjaZTILneczPz2NmZsaWixtJU+z1XXGS3mXXZ16r1bCwsICVlRWMjY1pDi2Xvs+k/6xaDiMaV3d81JwgJ8UZwYpI2yvGMdqvPsssX7kxZqKdi2a1zLEb76NamSNx0dxY5uhFvNDDpeUY1Ot1LC4uIpPJoF6vY29vD6VSCYIgIB6Pt7htTowBMIIfxE3goLkPjuPEQBGSKPnoo4/i0UcfBc/zePHFF/GJT3wC99xzD95++23867/+K95++20IgoCTJ0/igx/8IL785S8b3t5LL72ERx55BHfddRc4jsPjjz+OD3zgA3j77bfR16d9fRgcHMS7774r/t2N31En8MdReJPipIPWbDaxtraGVCqFUCiEY8eO4cCBA+JFxsk5ZICzJY6AupPF87zomAmCgGPHjuHgwYO2XpjNllfaiR2z0Or1OhYWFrC8vIzR0VHcfffdGBoa0t2mniisFCO65XDlivz47FX/mRrp3CCGOyxD7Bakd69SC5uKuLerD00Pt5U5enVR4QWBpkU4HBZLt06ePAngRiKe1HFLp9Mol8sIhUItok0ZrOAEPM97Xtz4RaB52UFTolfFQ/rbotEo/uIv/kI8BzSbTaRSKVy7ds30WvInP/mJ7O/PPPMMJicn8frrr+PKlSuav0dRFKanp01t62YgEGg+o9s9aBzHYXV1FQsLC2BZFidOnMD09HTLBd7pNEmGYVCpOLfYlZZYKl3Gbggz6XYBZwSalVlo5E740tISRkZGcNdddxlqXKZpGh+79j/Bvhc0qOeeKcnn4q4rmdvN92Fs0HzIj56LJsVuF42UORpxz4yWOeYzcQAU+obk+yktc2xUGQgN9zgOXu9B8zLKkBBpIt7ExIT4eLPZlCXiKYMVpHPbSJlkrxbqgYPmHvzyOoD2KY7ZbLblBmgoFMLx48dx/Phxy9vP5fbHybRLiSwWizh8+DB4nseFCxfwd3/3d7j99tstb9/rBALNw2g5aDzP236S4TgOy8vLWFxcRDQaxalTpzA5Oal559XpsBKnHTSy/dXVVSSTSVAUhfn5+a4JMwJFUaAoyjOz0BqNhijMhoaGcPHiRVMNyzRNg43uf87Vsnx0g557ls8ZS3VUw46hz1rphIC6SDOS4GhUpBGs9J9JsSNdcl+USRFQyu3vX7RfWzAGZY7W8bKDBsBwSEgoFMLAwICshxXYPwdJxwCsr6+jWCyC53nVMQCxWMz29ytIcXQPRmaHeYV2r4UkOHbj+8/zPB577DHce++9OH36tObPnThxAt/97ndx9uxZ5HI5fOUrX8Hly2V+qk8AACAASURBVJfx1ltvYXZ21vb98hL+OAoDRMjdkkajYcvJsl6vY2lpCUtLS+jv78eZM2cwPj7e9gvtFoHkBEQgX7t2DQzD4JZbbpGVf3YTMmDTyVloRuA4DktLS1hYWMDAwAAuXLjQ0SwWcow3KozhGVlWxFmv6NRJM0KniY7dKnNsFWdyqsUI0KTA9su3TbG8q1w0r4ocrws0qzH7LMtiZGREdmNIEATUajXZGICtrS2Uy2VQFCUKNuUYACuvwQ8CzamWBjvxy+sA9teBegItm812LWL/kUcewbVr1/Dzn/9c9+cuXbqES5cuiX+/fPkyTp48iW9961v44he/2JV98wqBQPMZNE3bkmBYq9WwuLiI5eVlDA8P4/z58xgdHTV8IXRDiWOvt8/zvNiXV6vVcPDgQZw6darnF16nAlKMOGjEiV1YWEBfXx/Onz8vi9k2y4df/yEgtIqzSlH9AmtWnHUzYr8dRkRapSZfFEpdtHxFe5Gh556RMkejs+OslIq2E2dSGsWwKNKYcBNcfV+cBy6aNbwu0LoRs09RFKLRKKLRKMbHx8XHyeBg4rZlMhmsrKygWq2CZVmZYCP/38iNUj8IND+8BuBGsIbXEQShrYPWLYH26KOP4sc//jFefvll0y4Yy7I4f/48EomE7fvlNQKB5mG0LqpWgkKq1SoWFhawurqK0dFR0yVnBKdLHHsZN8/zPFZXV8XAlOPHj2NjYwMDAwOOXLDc6KA1m00sLy8jlUohHo/j3LlzGBsbs74wVDHNtMSZErf1n6nRTSdNDz1xZwWpq0ZKGFU/RA2kIs1NeLmPy+sCrZeDqqWDg6empsTHOY4TRVupVEI6nUapVEKj0UAsFmsJJYnFYrJrgx/EjV9KHP30OgD0VKAJgoBPf/rT+OEPf4gXX3wRR48eNf0czWYTb775Jj7ykY/Ytl9eJRBoHoeiqJbFQSfiqFwuY2FhAWtra5iYmMD73vc+1Vhzo9wMJY5KYSYNTNne3nZ0DptTDppyu81mEysrK0ilUohGozh79qyhEtlOEXjt521UvXm6M9vjZaQXzUyYimxfbCpzvCHO9BAAvPd5hgSguf//67kI6Pd6C91W5uhFvC7QBEFwfEHNMAyGhoZkgQuCIKBer8v623Z3d1Eq7d9wkY4B4HkeHMd5+rPwi7DxSw8aWX+060GzMz3xkUcewbPPPosf/ehHGBgYQDqdBgAMDQ0hFts/5z/88MOYmZnBE088AQD4m7/5G9xzzz245ZZbkM1m8Q//8A9YWlrCpz71Kdv2y6t4/ygMaMGMg1YqlZBKpbCxsYGpqamWQcBW9sGvAq3ZbIpJlgzDqCZZOjmHzSmBJk1xJO9RKpVCOBzG6dOnMTExYevi48T/+K+gdM5g0oCQeiEMitUvV3QyYh/QDg4pVyKIm5xP1i0HrGU775WMcvWQYUfSmDjTh68wokgDgjJHq3hVFAC9ddDMQFEUIpEIIpGIrIybjAEg/W0k6e71118HwzCq/W1eEAx+EWh+eR1EaOp9N3K5nDiewg6efvppAMD73/9+2ePf+9738MlPfhIAsLy8LHOLM5kM/uRP/gTpdBojIyO48847cfXqVZw6dcq2/fIq7v/WB+ii5qAZEWiFQgGpVAqbm5s4cOAA7r33XlvrrhmGQblsPFHObohAs/OOpFR0sCyL2267DVNTU6rP75RIcnLbNE2j0WhgeXkZyWQSLMu2Tfu0A6PhIHaRz8QxONK7Y5urh5CvxzE4ZHybXDMkDu7WQs9Fazc/zhJNat8RE6FgpsyRCgkQmvLjSeCcd9HcKBKM4GXXBuhOD1o3kY4BmJycRKPRwCuvvIJ7770XtVpNdNu2trZQKpVQr9cRiURa+tvi8birXrcfZrkB/nLQ2r2ObpQ4tuPFF1+U/f1rX/savva1r9m2D37C+0dhQAt6Ai2XyyGVSmF7exuzs7O4//77RevZTtxQ4gjYMw+MlOktLCwgHA7j5MmTmsKMEAqFUK1WLW23U6zMI+sUnudRrVaxu7uLaDRq6D2yCsUYe431QufpaoDS8dm/AGmFWxgRbnoR+3bRqDBg+q2J9EaFURVpVsocq7moyb2QlDkqIC6aG8ocgx4053Crg2YUcq5mWRaRSKSltaBer8uGbq+urqJUKoHnecTj8Zb+tmg06sj74RfnyS+vo12CI7Av0DpJTw7oDYFA8zhqJ2I1cZTJZJBKpbC3t4fZ2VlcuXIF0ajZxZJxnC5xJCdYK3fDlMLMjBt0s5Q4kiHcyWQSjUYDo6OjOH/+fNcXCGrljXyJBaUQFFbEWdVg2IgUqXDrG7JXoOdzchdNmeCopFKMIKYzQwyw1oum7OkzU+bYEZI+NIKQY0EN7d+MOvPP38Iv/pdPIBKJeHrB3mu8LtC85qApIQJN6zMIh8MIh8MtYwCq1aqsv21zcxPlchk0TbeItr6+PktjAIzgB2EjCIItN3XdQLu1jyAIyOfzXYvZD7CO94/CgBZYlkW5XIYgCNjb20MymUQul8Phw4dx+vTpnsz4cNpBo2kaNE13tA8kcXBhYcHQUG41/F7iKAiCKMwA4Pjx48hms6BpuqeLPaHCgOrbX6DriTNl/5mekBBdnpAVV4QSnbe+IfMzx7RQirROUA707hXm3TNtSJmjEBYA4p7Fmrh69WpLHw9ZoPph0dUN/CBwvCwwSWmgmddAURRisRhisRgmJiZkz1Uul0W3bW9vD8vLy6jVagiHwy39bUbHABjBD8O2eZ53ReiMHThR4hhgL8EVy4cwDINSqYTXXnsNpVIJhw8fxvnz58Uh1r3aBydj9sk+mBEqHMeJjlk0GrUUbOGkQO2mQBMEARsbG0gmk+B5HseOHcPBgwdB0zQKhYJjolTNPTOLnQJCit1CzYxIM+Kiqf0OQavM0Swt763FPjQZ5RAQ3z/uHnjgAdkCdWtrC6lUSow7V/bxxGIx2xb3XhUJgYPmLHZG7EvHAEhpNBqyMQDr6+solUrgOE4sk7TyvSDOk9eFjZFoeq9gxEHL5XJBiaOL8f5ReJMjPYkKgoCtrS0sLS2hWq3i+PHjOHTokCMnG6dLHAHjIokMT15cXLQszAh+c9AEQcDm5iYSiQQ4jsOxY8cwMzMjW1iEQiHU692fUbVf3rjviNF96jcBzIZGNIrdd5VKuRiiJsWSFu3KG83QSZmjViqmVpmj0KRAdexIqsftq3HH//gO3vzP/0WWREvizqV9PDs7OyiVSqAoqkW09ff3m76ZFfSgOYcfHLRuC0yWZTE8PCxzSwRBkIWSKL8XUtFG/hsOh1Xfa1Km6XWBxnGcWH3jdTiO0z2P5fN58Dzf0ZzbgN4QCDQfIAgC0um02Ac0MTGBTCaD+fl5x/apGymKne6DFkSYLSwsIB6P48yZM7bN6HLaQbNLKBHRf/36dTQaDRw7dgyzs7OqF7BeDsgWKvunLjuWxfVcxIJ4MEc1F0VUpTdNKziEq6sveBpVBmxU/fhqVOSn9U5cNDup57pbUi2EBVDERYu1Hn/SuHPp3WJSDkYWqNJyMC+k5tmF1wWa1x00p0oDKYpCNBpFNBqVjQHgeV4cA1AqlZDNZrG6uopqtQqWZVX728gNCq8LND+4gASO43RzBrLZLCiKks3uC3AXgUDzOLlcDq+//jp4nsf8/DxmZmZQKBSwvb3t6H4xDON4w62WSOI4DktLS1hcXEQ8Hu/K8GSvO2iCIGB7exuJRAK1Wg3z8/OYnZ3VvXjRNN3z9Eg1hAKrulBX0m3h0MJ7zg8p91MTak5BXLSKSjCKVpmj0KDbzpbTpQtx+8B+WMib//m/tP19aTnY1NSU+Hij0ZCFL0hT85SlYMRV8DpeFmiBg2YvJGREOXaH4zjN8mHS1764uCiKNi/e0OA4zjcCrdFotJS6SsnlchgcHPTN6/UjgUDzOLFYDPPz82IfEOCe/i/A2ZkiSoEmFWZ9fX04d+4cxsbGunJx96pAEwQBOzs7uH79OqrVKubn5zE3N2foJN6L13ziu/8dQAhgrDlenYkze102LTfN0J40aNQbYYQHjDmlxEWzIyCkXTKmtMxR+j7bVuaoRTkEukGDD1u7ScCyLEZGRlpS8yqViija8vk81tfXUalUwLIsms0m1tfXUa/XxQWqVxY+gYPmLG4TaFowDIPBwUHVMQA7Ozt49913Ua/Xsby8jFKpBEEQRKEnvanh5pRVvyQ4Au3XXkFAiPvxx5F4ExONRjE7Oyt7jGVZ8DzvqF1P0zRCoZDjUfscx6HRaGBpaQlLS0tdF2YEJ0s8OxFKgiBgd3cX169fR7lcFoWZmYtVz+avqYgzEhAiFFpr7pUuj5BjgbA7eoaquSjY/s7LUesFcyJNb6i3U+mOpmnTh0bX7V/sSocLS1Pzms0mSqUSfvOb3wAA0uk0isWiLHxB6rY5NaNKD68LtMBBc5ZwOIz+/n4wDIOTJ08CaL2hUSgUkE6nUS6XZSmrUvHWyxAzLfzkoLUTaLlcDsPDw57+7vidQKD5EHKiazQajp5snHbyaJrG9vY2FhYWMDAwgDvuuAOjo6M9OSGR951EKPcSswKNCLNSqYSjR492HCzTyx40NdTEWcvP5Nj9aPZ2WIzYN0OjGLYk0npB18ocLSKN26fqFHiWB92gDZc5WiUUCmFwcBAMw2BmZgZjY2NiKAkpBSPlYMoZVdI/Tt6197pA84OD5nVRoLwZrHdDg5RJlkol7OzsYHFxEfV6HZFIRLW/rZef7c3koGUymcBBczn+OBIDZLjBvQKcS3JsNBpYXFzExsYGWJbF+fPneybMCNISz15ffI0Kpb29PSQSCeTzeRw9ehQXL160dHHqtoN2+9e/AQyo/5tMnGn0nwk55+/QalHPRRAe6izIw4yLZhWjg7+5egh8xcCxZKIPjc6w4EecLd02gjSURBm+IO3hUS5OlaItFov1ZHHq5QRKwPsOlNf3HzAerhEKhTAwMCBLWQVa+z7X19dRLBbB83zLeIy+vj5bx2NI8ZuDpudKBiWO7icQaB5H6yTFsqwr+tB6KdDq9bpYyjg4OIgDBw5AEATZIqlXUBQFiqIccZTaOWiZTAaJREIcXm7XjLxuh4RwA52/l3rirFcJjlqQoAulSNNKcNRDmeCohC+xmqMJ+NL+e6Q1T67dcxvBbB8anZV8bpQAOnPj7/ygszeglLRbMGrNqFKOACA9PAAQj8dbhJvdoSR+cNC8vP9+EGhWXUCtvs9qtSqb36Z0otXGAFjByZ55OxEEwXCJY4B78f6RGACKolrugjpdXtjLfajX61hcXMTS0hKGhoZw4cIFjI6OYmlpCbu7u13fvhoURTkWFKK13Ww2i0QigUwmg8OHD+PcuXO2LvZ68nrf6z+jyyHwcWPbcrNzpqRTJ82IiybYILBUn1elzNGOPj+ZOFP99/3X03xPuJMyR2C/D61XZY6ANRcqHA4jHA6rhpIQ0SaNOg+Hwy1lkvF4vOMFciBwnMWpmH076cZroCgKsVgMsVgM4+Pj4uNSJ7pUKmFvbw8rKyviGADynZCKN6PfDb/E7JMb4+1CQoIZaO4mEGg+5WZw0KTCbHh4GBcvXpSdcJycRebk9pVCKZfLIZFIYG9vD4cOHcLZs2e7Eg3eTQdNWd4oE2ecBxaXOqEWStqJNKGhvhCqF8LiAG9PoShzpDNhgDIueEKFkCjSAIh9aEzBuwstaQ/P5OSk+DjHcTK3TVoKphZKYiQxz+sCzev773WBCfRW2Gg50dLvRqlUkgX2xGIx2XeDlEkq33fys16HrDv0PpNcLoe5uble7VJABwQCzQeoOWhuEGjd6kGr1+tYWFjA8vKyqjAjON2H57SDlsvlkEwmsbOzg0OHDuH06dPivJpubrcbSMsbzbhndI4Fb0uIRW/LIDspbzSKXpkjsO+0qZU5in1+bWbMEceSqlOqgSx6ZY7SEkZVKAEQWhfjTDaEZrz1cz73nf8b//GpP9F/Tg/BMAyGhoZkw2UFQUCtVpOFkqgl5kkXp9I764HAcRY/hoQ4gdZ3gwT2EPG2u7vbUkJMviP1er1l/psXIeWNet/roMTR/QQCzac4FdAhxW4HSSrMRkZGNIVZt7ZvFqcEYqVSAQC89tprmJubw5UrVxCNRru+XeKg9XLBRxdD4KPqAsw+cdZ7+AoDWqMXTA+hwIIaMH9jhvSfdYodaY5txVnLLwCQbDJUpmUijY8IoGu9OQ6dFDkURSEajSIajcpKwaSJecrBwtFoVBRs9Xod9Xrdk0JNEARP7rcUnuc93/fkBoGmhlZgjyAIKJfLqnMNs9ksdnd3W/rbvPQZGemlC0JC3I93jrgATdQuTm7pQatWOxvEK6VWq2FhYQErKysYHR3FXXfdZejEwjCMo7Hvvd5+sVhEIpHA1tYWAODSpUstaVndpFujBUh5I12ngXZhhe+5O7RG35nbIvb1EHIsqCET3+GK8fe8UxfNrQghgGreEGmkzPFmRisxTzkCoFqtIpVKYWFhQXUEgBvmU2lBKke87KA1m82ulJz3ErcKNC0oihJDRqQlxL/4xS8wMTGBcDgshpKUSqWWpFXyPYnH46489tolOAqCEDhoHiAQaD6FZVmUy2XH98GKg6QUZnfffbesfKEdbnDQeiHQSqUSEokENjc3MTMzg/vuuw8vv/xyzxdW5EJl98Wajwigq/S+YyLdXlF9G1rizIuYFmlQd9GsBoTIxhhUQqpljkKDBsryz8RomSO9y8o/X4Ey1Yemh9/KHK0SDocxOjqK0dFRAEC5XMbc3Bz6+/tF0ba3t4fl5WXUajVxELEylMQNC1Mi0LzuoLnhvbSCH1xAYP91DAwMtCQ/K8skM5kMSqWSau9nX1+f4wPpjTpo5BwQ4E68/40KUD0RuKEHrVOBVK1WRWE2NjZmWphJt99sNh0rgel2iWO5XEYikUA6ncbBgwdx3333IR6PA3BmaLTUQbMV5dPpPL1ZcWY08p0kCvLD9n6nBI3wEJJGCHQm0ozQzkXrFSSN0TDSPjRFmSMAsLkQmvH9z7WXZY5ehQx6Jo7C1NSU+G+NRkMWSrK6uipbmKqNAOjluZaca7wscPwg0PzgAgLac9CUNzWAG2MAlL2flUpFNpBeKt56ddPUiEDL5/NBiqPLCQSaT3GLQDOzD1JhNj4+jve9730dCTPp9oH2dn+36FaJY7lcRiqVwvr6Og4cOCATZgQnAkrI7Dc7BdrtX/8GoPLREfdMq//MCqq9UO+5OVrR73YLNy20Ehxbfs5EL5pW/5nXyhwJPCsgVKZEkQb0xkXzqoujNyKAZVkMDw/LSqGUC9N8Po+NjQ0xlEQp2szEnHe671597wH/CDQvlThq0Ww2DTuB0jEAExMT4uM8z6NUKok3NtTcaKl468b3o9Fo6L6OWq2GSqUSCDSXEwg0n+KGkBCj+0B6IFZXVzExMYF77rkHg4ODlrdPTnpOCTS7HbRKpYJUKoW1tTVMT0/j3nvv1UyccjpB0i74iLDvkBhYvzCF0P7Pd4jo5HSwVhKFm0CBH1EIIxMR+1p000XrCJUyx05CWWTumcHPWQvSh6YGW+zuAt7KHDSnMVthoLUwbTabMrdNGXOuFG52lIGRm0GBQHMWPwg0MtzZ6uugaVq191PqRpdKJayvr6NUKoHjOFmZJPlvLBbr+Lhu56BlMhkACHrQXE4g0HyAm0NC9ARKt4QZgQyLdkqoMgyDWs380GEl0vdpcnISly9fbpkBo8QpgWb7LDQLT2VELAhNCiGb52URB65FqFlEyLGAwfECQOeJjrLnqDCm5szRDbrlfdfqQwvtMhD03nqLfWjERdsX7d5dwHcbu0rAQ6EQBgcHZedwacw5+bO9vY1SqSQrA5O6bWZupvE8Lzr3XiWI2XcH5LrVrV46LTeajMgg4o18P6RBJtLvh5Ey4nbz3HK5HGKxWE/SnQM6JxBoPsUtJY4cx7UsAKRO0OTkZFfTBp0MCrEqkqQlnxMTE6beJ784aEYx4p4pRQKTDekLBEKHIoHOsLaLNE10EhytBoS4kjZ9aDwrgG5QCJUp8TO++F+/g18+9qnu7ZKHRUK39l0r5pznedkIgJ2dHSwuLrak5ZE/akOFgRv9c17GDw6aH0SmkeHOdqM1IoPneVQqFfH7kc1msbq6imq1CpZlW9w25WzDdlVDmUwGw8PDnj5n3Qz48Mp986EVEsLzvKN3tsgJgpwseinMCE5G7Xfq3pH0yuXlZYyPj3fkLDrpoNm1XdX+MxVTjOnAAWOyGr9j8zqJzrAAD/DD9twkoHMseBOljkKBBRh9gWlm8LcMSZmj2XAWzfffInpljgHqEBeql9A0LYovKY1GQ+a2LS8vtwwVlv5xYt/txg8CzQ8OWrPZBE3TrvgstEJ7OI6T9bdtbm62zDbs6+tDuVzG0NCQ5rFFIva9/t3xO4FA8ylEHDUaDcdOnGS7xWIRa2trWF9fN1yiZxdOOmhmxaF0EPfo6KilkBQnHTS7UxyZMgWuv1Vk0A0KvIkKDapOIVTu4sVX0L7Y0VnGsEiTJjiqPpdJkab7XOX25wa6SpsKYzFT5kg1IXcxlX1oNsTth2pAM7L/p1t4uQcNcI/7x7IsRkZGZOEFgiBougnkHHv9+nXZCAAviQUiDLyMHwSaHf1n3YZhGAwNDcnWBaSMWNrfRtoiUqmUKPRee+01DA4O4sKFC8hkMpYC2AJ6QyDQfIDaxZWmaUf7r4D9UkaKovDv//7vmJ6e7qkwI3ihxLFer2NxcRFLS0sYGRkxPIjbjm3bjZ0OGs/uL3qJOGOKFLi4okzRhHumFGeGyhtthARiEKGmFbGv+fsdDl6miyHw/fqfiZaLpjVrzgq2uWdtyhzV6HaZoxdxagyJUSiKQjweRzwelw0V5jgOm5ubSCaT4HleDF1oNpstoSRumE2lhV8cND+8Bi/OcpOWEZMxAHt7ezh16hQikYgo2q5evYqrV69ifX1dDPn50z/9U5w5cwZnzpzB6dOnO1p3PPHEE3juuefwzjvvIBaL4fLly3jyySdx4sQJ3d/7wQ9+gC984QtYXFzE8ePH8eSTT+IjH/lIR++BX/He0RigCkVRLXdxnepDK5fLSCaT2NjYAEVRuP322zEzM9Pz/QCcF2h62240GlhcXMTi4iKGh4dx8eJF22JvveygNZtNnH3qW6rx+p3C5kKi4HMaM26a5nPY6KJZohICXXfnwoz0ofFMb1w0Ny7+jeB2gaYFwzCIx+NgWVZcDEpDF8ifzc1NlMtlhEIh1VASpxflfhFobnef2uEFB80opK2E3NgAgO985zsA9iuavvSlL+H1119HPB7Hj370I3zpS1/C+vo6ZmdncebMGXzuc5/D7/3e7xna1ksvvYRHHnkEd911FziOw+OPP44PfOADePvttzVTpq9evYqPf/zjeOKJJ/Dggw/i2Wefxcc+9jG88cYbOH36tD1vgg8IBJqP6XWSY6lUQiqVwsbGhhgD/+tf/9qRiHuC0ymOaiKJ4zhRmA0ODuLOO++UDcC0AycGVZPtdirQeJ7HysoKUqkUgP3SRmDfQWMsxKSzOQcvuhpvBZ1l0Byw9vkYEWl0dX/hZ8RFa/c8dpQ5GhLKXYzbBwIXTYmXyzOVPWhaoQvNZlMWSrK1tYWFhQXU63Wxd0cq2uLxeM9Eq9cDNniehyAInn4NgHcdNCUke0Br3dXf3w+KonDhwgV85StfER/f3d3FtWvX8Oabb8oCfdrxk5/8RPb3Z555BpOTk3j99ddx5coV1d/5+te/jg996EP43Oc+BwD44he/iBdeeAFPPfUUvvnNbxrett/x/tEYoEmvHLRSqYRkMol0Oo0DBw7I5nM5HffvtIMmFUkcx2FpaQmLi4vo7+/H+fPnTZ0IrWy7V3SyXVKelEgkwDAMTp06Bfzmt+K/E3EmLW9ki5TMDdFKcHRUnLWByYbADdvwGekkOJqh47AQi7T0oSmxoQ8N2HfRiJNmN14WOV510ADjKY6hUEh1NpVyBMDu7q4YSqLmtoXDYVv3n4gbLzto5Iac1wWaXxw0cv3VE5u5XA5zc3Oyx8bGxvDAAw/ggQcesLT9XC4HALo3nV999VV89rOflT32wQ9+EM8//7ylbfuNQKD5BCdKHIvFIlKplCjM7rvvPtFOJzgpkMj2nRKI5LVzHCc6Q/F4HOfOncPY2FhXF0WhUAj1er1rz6+FGQdNEARsbGwgkUgAAG699VYcOHAAp//b06Bt+Mik4qzj8kYbhIEeVkUanWPBh42930oXrV1AiJH+M9IDaGRAuJ1iOZyRLGglm6Z4oDZy4wFpmSP93mkoZH00oa/wskCzmuIYDocxOjoqW0wqI84zmQxWVlZQrVYRDodbkiTj8XjHAoucK70s0Igg8PJrAPzjoHEcB4qidD+PbDaLM2fO2L5tnufx2GOP4d5779UtVUyn07J0SgCYmppCOp22fZ+8jPePxgBNWJbtijgqFotIJpPY3NzEwYMHVYVZt/fBKAzDoFKpOLZ9QRDw8ssvIxaL4ezZsxgfH+/JYsjNDpogCNja2sL169fBcRxuueUWHDx4ULyghGqAoHOtV7pnqvtR7uA9dmh9YZuTZgN6LpodZY77j1MdC2aZMNMgkqFQH1R//mZk//jqRpmjV0UO4N1974b7pBVx3mg0ZEl5a2trKBaL4HledQSAkYHCfhFo7QSBF/CLg8ZxHBiG0T32stmsbf3uUh555BFcu3YNP//5z21/7puRQKD5BLUvo93uUbFYRCKRwNbWVlth1q19MIsTDl6z2cTq6iqSySQA4LbbbsOBAwd6ugjqRty9EfR63wRBwO7uLq5fv45KpYJjx45hbm5OdmG/8/PfAHRGvrEGetHY/L5j0lN0IvaNQESaVsS+XoIjUwiBM9jPZrUXrVu0jduHMXEm/myeAtWUu2kB6tzMDpoZWJbF8PCwLOlOEARUq1XRbcvn89jY2EC5bn6ZwQAAIABJREFUXAbDMC2ira+vTyYC/CLQ/CBs/OKgNRqNtq8jn89bTopW8uijj+LHP/4xXn75ZczOzur+7PT0NDY3N2WPbW5uYnp62tZ98jrePxoDNGFZFuVy2fLzFAoFJJNJbG1tYWZmBvfffz9isZih32UYxpFSO+n2eyXQeJ4XhVk4HMapU6fw61//GiMjIz1fADkVjhIKhVQFeSaTwe9+9zsUi0UcPXoUhw4dUr2INGwQZ15ALcSCyYbQjHcmqtVEGgkIsROpiyYdcUDXKN0yR6vljeE9GtD6aCnIyhylRDIUGu9N9lCWOb7vie/gtb+yx0ULetCcwen+LYqixMjyiYkJ8fFmsym6bcViEel0GqVSCY1GQzYCgGVZz773BL8INI7jDK9r3Axx0LQQBAHZbNa2YDJBEPDpT38aP/zhD/Hiiy/i6NGjbX/n0qVL+NnPfobHHntMfOyFF17ApUuXbNknvxAINJ+gdpK32oNmRZhJ98EOkdgpvRBoPM9jbW0NyWQSDMPg5MmTmJqaAkVRno677wSlg5bL5XD9+nVkMhkcOXIEFy5caJvqqVfeqIcZcdbrGWhGYXMhNIa6e7zQxZBuOSddDhmaKWZpH0yUOYYzJj5Xer8PTQpbhCjSgBtljnb0OfoBLws0t0bUh0IhDA4OYnDwxh0nMlBYGkqSz+fFMnhpKAn5/04mIBvFLwLNLw5aO4EG7F+X7XLQHnnkETz77LP40Y9+hIGBAbGPbGhoSFwvPvzww5iZmcETTzwBAPjMZz6DBx54AF/96lfx0Y9+FN///vfxy1/+Et/+9rdt2Se/4P2jMUCTTvu/CoUCEokEtre3MTs725EwIzhd4thNJ4mkDyaTSdA0jRMnTmB6elq22HEqJMVpYUiOoZ2dHRw6dAhnz55tm4B2/ovfADR6y5SLbiVScdbz8kYtOhQ5ZkQaXZMcayZKHXsF3aA76wd8DzPiTIk0bj+cAzj1kTy24UWRQ5w/L+474C1xKR0oTNJ78/k8/uM//gPnz5+XJUkuLS2hVqshEom0iDYroSTdwOtjAgh+6kHTE/Y8zyOfz9vWg/b0008DAN7//vfLHv/e976HT37ykwCA5eVl2TF7+fJlPPvss/j85z+Pxx9/HMePH8fzzz8fzEBT4JalTIBF7HDQ8vk8ksmkKMyuXLmCaDRqab/ckOJot1DheR4bGxtij9nx48c1e8zcHNbRDTiOQyaTwauvviqKe6PHUKfx535M5euFk6YHU6ZkYw2kaJVOtitzbIeyDy2yS8ndVAHaZY4GYEpykcZH7C1z9CJeF2huddCMQtwnIsKkNBoNmduWyWRQLBYhCIKq22YklKRbr8HLnwHhZnHQcrkcBEGwtcSxHS+++GLLYw899BAeeughW/bBr3j/aAzQxKh7lc/nRbdjbm7OFmEm3QenBZpd25fGwguCgGPHjsnSB7W2fzMItEqlgmQyibW1NYTDYUuuKwAwFYDT+HWzQs6tEfvdwKiLxhQpcP2dvz66YWwhqBfYolfmGDHrnEn60NTKHImbRkSa3WWOXu1B8+p+E3oZEtIN9AQmy7IYGRmROR2CIMhGAORyOaytraFSqYBl2ZZAEmUoSTfwS4mjnxw0PYGWzWbFuYAB7iYQaD6mnYOWy+WQSCSwu7truzCT7oPTAo3neUt3WgVBQDqdRiKRQLPZxLFjxzAzM2N4QKqfSxxrtRpSqRRWVlYwNTWFW2+9FVtbW6bFGSlvVOs/Y0pAU+PpwvnuDB4GYNuAZKMoRU+nLhpTCHUuSnFjMLhd0JxzZafSMkctbmYXzesOmpdKHNUwe12iKArxeBzxeByTk5Pi4xzHyUYAbGxsoFgsguO4lhEAfX19iEajtr1vfhFofnHQGo0G+vq067mz2SyGhoZ84Xr6He8fjQEAtEsceZ5vOYESYba3t4e5uTmcPn0akUh3VrlO96CREy7HcW17oJQIgoDNzU0kEglwHIf5+XnMzs6aOrH5VaDV63UsLCxgeXkZY2NjuHTpEgYGBrC5uWlpu4yJkXXhfMebaX2unMpihRL/R5X6yHs2jcWIfT3YXAhNjVLDTmHe6wlr56LplTmGaurC2I4yx7Ckn5DiOw+N0SKcvSH4+QhA14CNjQ1x8drpwsWLQsEPAs3LC027SjQZhsHQ0BCGhobExwRBQK1WE922UqmEzc1NlMtl0DStOgKgE4HiF4F2szhodgaEBHSXQKD5GNIo2mg0EAqFkM1mkUwmeyLMCHY4WFagaRoURZkSaIIgYHt7G9evX0e9XheFWScnbydLHHmet/0OM8dxWFxcxOLiIoaGhnDXXXfJTvY0TXeWHskDoQrEdEFS3qjlntkhzqRldJ2IAHEulwDUTczbaufoKGHzFBoqg5elASEtv1Ok0LBQwqi7PwYdtk5GHkQylH7CpoU+NOKm8ez+sSY9rtbX11uGDg8MDMiGDvsZrwo0r/egdTNgg6IoRKNRRKNRjI+Py7Ypddu2t7exsLCAer2OaDTaItri8bju8eEHgSYIgi9eB2CsxHFoaMiz3/mbiUCg+QS1LxtN0wiFQtjb28P6+joymQwOHTrUE2FGICKxEwfLDiiKMtyHJggCdnZ2cP36dVSrVczPz2Nubs7SSdvJkBDAvrKNZrOJ5eVlpFIp9Pf348KFC6pNxp283vNf/Ibq40xJ/eel4qyT8sZwF2alkbRBM0LNDVhx0cygVeZoJm6/LW360PT4zHO/witf+j9kQ4el/T3hcLjFcZCm6Xm1lytw0JzFCYFJ0zQGBgZaepCkIwBKpRJ2d3dRKu2fhLVCSchr8LqwIdcsP5Q4tktxzGQygYPmEbx/NAaIUBQlWyhkMhkIgoBr167h8OHDhqLO7YY4WI1Gw7G70O1EgyAI2N3dxfXr11EulzE/P49Dhw7ZctFxssQRsC7QeJ7HysoKUqkUIpEIzp49i/Hxcc0FXccOGiCbzaUlztqh1+tEHLNuzkDrllDTctF0f6cDF81M/5lemWMnaAWDWC1z1OpDIy4a/95r0Bo6LO3vKRaLWF1dRalUAs/z4mJVEATkcjmwLOspt83rAo3neU8vqt2UgBgOhzE6Oiq78cbzvCyUJJPJYGVlBdVqVbxpUavVEIvFUCgULJUIOwlZH3hdaAJBiaOf8O6ZLUCTTCaDRCIhpvWcPHkSBw8edGRfzDhY3UJr+4IgYG9vD9evX0epVMLRo0dx6NAhWy/4TvXgURQFiqI6du/IjLdEIgGGYXDq1ClMTk62Xch15Bia0HOdROqbTgS0gcju/jZrNgq1TkSaEawmOqphZfSBMm6/BYtx+8B+mSPdANgC0HxPT933f34Hk09dBQA8l/uu+LNa/T3ShasgCFhYWMA777yDcDiMgYEBUbwNDAwgFou5cuHqVeeP4OcURzdA07SYBjk1NSU+znGceOyvrKygWCzijTfekJUIS123SCTi6s+J4zjQNO3qz8IoRgSaXTPQArpLINB8RCaTwfXr15HNZnH48GGcO3cOv/rVrxy/CLshyVG5fSLMCoUCjh49iosXL3blTmwoFEK1WrX9edtBURRomjYtlkhi5fXr1wEAt956q+aMNzXMbvPOz38D0K7GkMHmb7gdRmGL5n7ebiIZquciTSqOlC4a08HQaGmZo9H+MzX0yhxt+5wMxu0TtBzXPxr631sek4o2ZZre8vIyzp8/j3A4LJtdtbq6imJx/8VJF6zkj14pUi8gPapuXjzrEZQ4OgPDMBgeHsbw8DB2d3cxNjaGmZkZWYlwsVhEOp1GuVwGwzAtJZL9/f2ucaz8kuBIQuHa9aAFAs0beP+IDBBZWVnB8PAwzp07J5bZmB1W3Q3ckORIBBpxF3O5HI4cOYILFy50dZHkVIkj2bZRsSQNRmk0GqZGCSi3KQiCtXASyaJaK17fCOGchXJGG9erRkSa1lwxukeHTqcumlaZo9bjalj6nAyiF7cfqu+7aO32V020AfvCjdwEky5cxW1L3LZCoYC9vT0sLy+jVqshEomo9rb1SjD5Iabe6/vvFpHSKSRcQ6tEuNlsykJJtra2kEql0Gg0EIvFWkRbLBbr+WfqpwRHQL+Xjqx9AtxPINB8xLlz51r6f5x2rwB3DKsuFAr4xS9+gWw2iyNHjuCOO+7oyd1rp1IcAWMCTdp/V6lULAejEEFneuHRRgeyJlIbwznjPwtYjHE3qGlImWXdhhJFNk+ZCkcx2oum139mJizEjoRNZZljN+L2SZmjlK1HL4tljkYhwu2/4/8RH9Nz2wiNRkPmNiwvL7eEMpAkyb6+vq6cr5yurrBK4KA5T7tzfSgUwuDgIAYHB8XHBEEQQ0mIeNvZ2UGpVBLLKpXCrZvXa784aBzHidUzWgQOmnfw/hEZIKJ218lp9wpwViTmcjlks1nUajUcOXJE5i72Ajc7aJlMBr/73e9QLBZt67+ThpO0E2h3fv4b4BXXXKYMcIpZ6d0UZ73GrpLHcB6oD7b/OTuxUt5I0CpzbNt3psSGuH0Cz9xw0exCz20jsCyLkZER2WJJGcqwu7uLpaUl1Gq1lgh0O9yGwEFzFj8Ig07i6SmKQiQSQSQSwdjYmPg4z/Mol8uicNNym4lwkyapWsFPDhrDMLrfiaAHzTt4+8wQ0BaWZVEulx3dBydEYj6fRyKRwO7uLvr6+jA+Po4TJ070dB8A5x00tUTFXC6H69evI5PJ2F7mKXXQjMJUAS6u/m964kzpIoWzaBF8SrpdSmcEu/vSjMAWqbYOFFO5MX/ODFbKHO0W1OHs/n8p6dv73qHYGGj5cRmh+v6fTlw0o7TrbdMKZZC6DYVCQdVtkP4xuuj3ukALHDTnsTOJUjpAWwpxm4nbRno7BUHQHAFg5rj2g1AG2kfsk7TZIMXRG3j/iAwQUTshuaUHrVcuUqFQQCKRwPb2Nubm5nDlyhXxDpwTODUHjWxb+r5L35tDhw51ZexCp+EkwL57podeQIgRcdYrjMzfskOkqbloVtIT26Ec7qy1T3ZhpsyRCDM92ML+c9SH2v9sLzHitmlFoBO3gZSILS4uigOHSZIkKZOMRqOq1wgvCzSvO2h+EWjddp/U3GbS20lEm3RuIcuyLaKtr69Pcz/95qDpkcvlVGeYBriPQKD5HDf0oLEsi0ql0tVtFItFJBIJbG1tYXZ2FleuXEE0ul8rxzCM2NvRa5wucSSLuEQigXQ63fLedAMjs9Du/Pw3QDcBWqHjpOWNbNFY0ISRxbkb6ZZI04IpAVxfm5+x2UXTww73rJPPPpwDGu/doCd9aDxzI5AlVLe+X3ZgxG1TcxukA4eVvT1Kp83rAidw0JynFwJNDWlvp9rcQiLc0uk0isUiOI5THQEQjUZ946A1Gg3d1yEIArLZbOCgeQTvH5EBIjejg1YsFpFMJrG5uYmZmRncf//9iMXkK0wnQ0qcLHEEgLW1Nbzzzjs4cOAA7rvvPsTjGrWENtKJa6jmnrVb8Idq+66OFm4oZ2xHJEOJYkFJrxIcgX1hpvvvBu5vqLl3asJN63WZ7UOLZABBQ1sIlKTMkUbLrD22uL8fNcU6pRnZ3+duljlawarbVigUUCwWZUl6FEXhzTfflAk3LbfNbXhdYHpdoAmC4LokSq25hbVaTbxpQdIky+UyaJpGKBRCOBzG6uqq6TJhN9HOQSuXy6jX64GD5hG8dwQGmMINISHd2IdSqYRkMol0Oo2DBw+qCjPp9p12sXp5Ia7VakilUtje3kZ/fz8uX77ccpe9mxgpcQzVAEHn7GPEPdMTZ5bo8XovnDNXdqcUQr100fTKHM2UV1otSY106JoqZ6NFskCjzfvhBTpx2wRBwM7ODt555x0MDg6Kwq1cLiMUCsnKI9uViDmFHxw0t72nZiCVEm5/DRRFIRqNIhqNYnx8XHyc53mUSiX87ne/A4CWMmG1EQBuPt6MDKkGEDhoHiEQaD7HDQ6anWWW5XIZyWQSGxsbhl0hpx00wN5Gai3q9ToWFhawvLyMsbExTE9Pi3NmeolWOAnh7s99w/I22IL2kGEz2B3d3ilmRVrL7zuQ6qiErpkbJE432os0tT40O/vcAIAt7Ys0ZZnj3qcuY/Q77nPRjNLObaMoCgzDIBQK4fDhw+K/k0UrcRs2NzeRTCbRaDTEEjHpn0gk4piLFThozkJuxHn1NdA0jYGBAbHHbW5uDgBaRgAoR2Aog3l6mQytRzuBls1muz6yIMA+AoHmI7RKHMl0eafuctkhkCqVCpLJJNbX1zE9PY17770XfX3Gbn073QcG7F/IunVS5DgOi4uLWFxcxNDQEO666y4MDw/j3XffdaS80kgPWjv3TIl04W+XOLOMyfYxrUHJBKsiTc/BkrqNRlw03e0YCAtR7pfUDdXrG2tX5hjOQjYzjxK0yxzbIRVk4fyNJFFS5khz3p4RpoW623ZZ/P9k0TowcCP2ksytIiWSpLenXC6DYZgW0dYrt83rDlovbtx1E68LNIJyfaRWJiwIAsrlsijastksVldXUa1WEQ6HW9y2vr6+nr8vHMfp9pdns1kMDQ15+qbGzYQbljkBXYSIgkaj4ahA69TFq1arSKVSWF1dxdTUVEflek72gZFUw24IxGazieXlZaRSKfT19eHChQuyC0ooFEK93vvEA70etEuf+QagcbOR4tTFmRS2oP64kXI5L/SkWRFpbB5odOCiqfWfScscjfSfmZlV1ylmA0G0+tCUZY4Eptw67sHrLppR2pVISudWSUvEms2mzG0jgQzNZlPVbTMbf94OrztQXt9/Imy8vuA3kn5IUZTonkkHzpNQEvIdWF9fR7FYBM/zqqEk3XScjThogUDzDoFA8xFqXzrSAOtkkiMpcTQzc0cqzCYnJ3Hp0iXZHV0zEAfPqZk/dgtEnuexurqKZDKJSCSCs2fPYnx8vOW1ORXxr+egGR0G3BIsUXNPup4eRiL22xHOWXO4jGDVRdOiXZmjUmR1UuYIHjIXzQ6Uw6sBoBmmEKr700UzgpFAklAohMHBQQwO3rgzoAxkKBQK2Pj/2Xvz6DjuMv33qapetFqWvMmbZHmJ7cRr4sSWMSYZMiQ5DIPJzBxgBiYQchi4IZsTPL9wSQYIDIGQgQQ4ZDgBTBhyZ8JAmHtJ4CQkk8SBsDjgbF7UrcWyLMmbtl7U3bV87x+tKlVVf2vrrl7U/f2c42Opu7aWSt311PO+zzsygmQyaYg/98NpmOtz3KpFoM11CnkdVqEkqVQq5+aF2XHWjwDwI5TEKcVxYmKCDameQzCBVmVwHAdCjBcV5Q4KCQQCrtOe1ICLU6dOYdGiRQUJs3z2Xwz8EkqKomB4eBi9vb0QBAEbN27EkiVLLC9QyiXQ3O6X5lhYbrOE4iw0AWTK3EOdr4DK10WjHkOeYSHU5T3E8NPKHG3LIn0qcwRmz0m1zJGRixu3jRbIoLptapkkzWlQ/zU3N7vq65nrAmeuh4RUi0Bz46B5geM41NfXo76+PudvQD+7UJ+mqvaLm0NJvNyAcBMSoheSjMqGCbQaoNxBIeobhl2ZpT7goq2tDTt37vTtjUTdf7mGURbqYBJCMDo6img0CkVRsG7dOixdutTxjTvfgdGFYuWgqeWNdv1nNEIx7zO2nMoZtQt+yrUd4awFgd/CzaovjRfpQtGNaHAr0twmOrrZnxvyFTyhyfzDXJzi9mmEJwmkuuzflhziaqbMsRAKcdtSqZR2wTo1NYXh4WFMT08jFArlJEk2NDQYBBlz0MrLXBeYKqUSmoIgWPZ36t02dXYhx3E5os0u5MNNiSNz0OYOTKBVGTQHrdwCza7MMpPJYGBgACdPnkRrayuuuOIK3+/w8DwPjuMgSRLCYY9X+j6Qb4kjIQTnzp1DJBKBKIpYs2YNli9f7voDvVy9d1YOml15YzBuHFJdDNz0MDk5MfptFBLo4RY/3Dy7cQSBBOzLBW0EjZWLZlXmaHUcbsoc/YbWh6aWOcpBDoHUrEir1rCQUuDGbVOdBtqwYfWCdWhoCIlEAoqiGC5WFUUpa/l+IahVHXNZoM31kBMg+3so56BqfX8nbXah+ncwNjaGwcFBpNNphMPhHOHW0NDgykFjEftzBybQaoByCzQgN8lRFEUteXD+/PnYsWNHUe/slHsWmhehRAjBhQsXEIlEMD09jdWrV2PlypWe7/CV00Ez73fPJ78NNHEIpGbdELW80U6c0dwzLwmOocnZr3NcmAKvK/SzuMwDj804JTj6jWsXLWVfZhpI2QtnL7PoeMl7+qb6++MU0+/Pxz40c5kjjdgHd6H5//mdPzuscdy4bVZ9PdPT05pom5jI/gEePnxYS9HT/zO7bZWGWmVQycfoRDWUOKqfVZX2OvSzC5csWaI9LoqiYQSA/uYFIQR9fX2YN28eNZhnYmICq1evLtdLYniECbQqwypqv9x3GdU+OFEUcfLkSQwMDGDevHm47LLLSjLVvtyz0Nzue3x8HJFIBFNTU+jq6kJnZ2fed/YqKSREDmXFmRdCFomNrtaddF6mEDiTqaKKtWLMInPjovEV3i9llb5pBSc7J3oali+gD80K1UUT0gRyeO6W0c0V3LhtDQ0NaGhowOLFiyHLMl588UV0d3cbQkmGhoYQj2dPHnNpWCXNgGICrTJQPyPL5aB5RZ3Zpr+hTQjB1NQUXn31VTQ2NmqlwmNjY/jEJz6B1atXY8OGDTh79iwWLVqEZDLpOD/WiZdeegkPPPAAXn31VYyMjODJJ5/Evn37LJd/4YUXcNVVV+U8PjIygvb29oKOpVqZG2ckoyDKHRICZMXC6dOn8frrr6OpqQnbt2/HggULSrb/ckbtuxFKk5OTiEajGBsbw6pVq7B9+/aCLyScBkYXC1q8P6eLONdDuwgXMt5CQczlceGJXKemVAOpixUwEprwFsoBZF00N6WDTmEtdi5aME7vD/Q6tLqYeInb15c5CiJBIDWrxJmLVnrs3Da1lD8YDKK+vt5QumV228bHx3PKw8xuW6l72ZhAqwwkSdLaIOYq6tB5nucNDlk6ncaPf/xjHDlyBG+++SZ6e3vxu9/9Dt/85jexbt06bNmyxfBv1apVrn8OiUQCW7duxY033ojrr7/e9bGeOHHC0IeqH1nAMMIEWg0QDAaRTCbLsm9JkjA4OIhYLAZRFLF161YsWLCg5G+G5S5xtNp3PB5HJBLBuXPn0NHRgc2bN7tKLyt0v8XELAz3fPLbQIDi7HpwSNwQ9jgny3dmXrLap+a3UPOanFgogSK8ZViVOZr70Ggiu5hljoy5hV64fQv/AcDebVNRy8PUf4ODg0gksoP+Su22KYqizcmcq1SDQCtn/5mf0PrPwuEw9u7di7179wIAuru78bWvfQ3d3d14/fXXtX8/+clPcOLECVy4cMH1nNnrrrsO1113nefjXLx4MeuDc8ncPysZBqxKHEvtoKlDlPv7+7W7mwsXLjREzpaScpc4mh20ZDKJaDSK0dFRLF++HHv37kVdnb8pGapQKnXSmd0cNBU/5oWpmIWZ1z6nYpGvUOMt/lR5CfDqAQfjgOji87YQF83xGPIsVfXas+Zn3L4ZtcyRuWiVi5veNlp5mKIoBrdNH8ZQV1eXI9q8Rp9bMdcDQoDqSHEsV7qz3zgFhBBCMDk5iQULFmDZsmVYtmwZrr32Wu15URRLUv67bds2pNNpbNq0CZ/73Ofwtre9rej7nKtUyKUMo5iUsgdNlmWcOnUK/f39CIfD2LRpExYtWoS33nqrbCWGQPncJHXfaslfKpVCNBrF8PAwli5dij179hRcC263X0JIyQWa1943/YV/KE4gh9wfa2jKOVK/3ITH6ImP+QSHBGOA6HEsoJVI89oTSNsuYD3jLN8yx2I4oeFxY9OgeoMg3ZJ7rpnLHJUgB15kSY5zFafeNp7n0djYiMbGRmoYgzps2xx9bv7n1YWpBoEmy3LF9PTlSzU7aGYmJiYs3ati/x6XLl2KRx55BDt27EA6ncajjz6KK6+8Er///e9x6aWXFnXfc5W5f1YyDJTLQVMUBUNDQ+jt7UUoFMLFF1+MxYsXa8dT7qCScjtomUwGx44dw6lTp7B48WLs3r3bdSlBvqh3BUsdhax30PZ88ttQZsobnfrAQvHci2C7+Wchl/O33OJ3yAQwKwRCk/7F8ptFml8BIV4Gh7uFdmx2ZY7BhP32csocHagbsxdW4UkCTskuk2m233BoKvvLnN63E/U//737g2BUHIW4bfpBw+fPn8fAwAAymYzBbWtubkZjY6Ot21YNEfWyLPte+VFqqslBsxNZkiQhHo+XbQ7a+vXrsX79eu373bt3o7e3F1//+tfxox/9qCzHVOkwgVYDFDMkRBVmfX19CAQC2LhxI5YsWZLzoRQIBJBKFXjLvgDKJdBEUcT58+dx/vx5LFq0CLt27TI0yBYTvUAr5V1OJwctmCCQ6o3nhyrO3LhnvgizMlwXqcmSfgg1r06a21JHFVr/mV2Zo5WL5iXshYZjmaNFH5qTMKMRiingFCDTRD855HA20dF87jKqBzdumyrC9GQyGUNvm+q26ZdX/zU2NiIQCFSNgzbXxU21OGiiKDrOQANQUYOqr7jiCrz88svlPoyKZe6flQwDpXLQFEXB8PAwotEoBEHA+vXr0d7ebnm3sJwOlrr/UgalSJKEkydPor+/X7uzetlll5Vs/wC0BvRSl5aqDtqeT35beywwTSA20s8NmnNmhVk4lKO80Ryx75XQpDexVIm4DXixEm40/CpXdSPOaAmO2nHEFU2k0cochTRhLloN4STaACAUCqGtrY06aDgWiyGRSODs2bPo6+uDKIqor69HKBSCJEk4d+4cmpqaUFdXN+eSBKtBoFWTg2Yn0CYmJhAMBtHY2FjCo7LnyJEjWLp0abkPo2JhAq0GCAaDUBTFlzt2iqJgZGQEvb29AICLLroIS5cudfxgqYQSx1IIFTUcpa+vD42Njdi+fTtSf2yYAAAgAElEQVRkWUYkEin6vmmUYxaafp+8aHRAzO4ZL7lXO+FJAjno/QKmVBH7XvDqaFG3EQNkm8BPwVReqN+nVf9ZMcNC3MDJhYm0fJwzwnNamaNKKK6Al5BzU4G5aAzAXYmkldumzmwbHR1FMplEX18fkskkBEEwJEmqZZKVLB6qISSkWhw0pxJHtf/ML9c2Ho8jGo1q3/f39+PIkSNoa2tDR0cH7r77bpw+fRqPPfYYAOAb3/gGurq6cMkllyCVSuHRRx/F888/j2eeecaX46lG5v5ZyXBE/aMVRRHhcH7DiQghGBkZQTQaBSEEa9euxdKlS13/sZd7FluxHTx9D144HMaWLVuwcOFCcByHCxcuVPQMNr/hed7ws7Zzz9wSnqzwkIY8UinDE0Da1K9tl+BIQ8jYi7R8cIrXtxJ3ZrdMHTROc9HMpYt2ZavmZa3i9s1BIPlgdtaCCetzl7loDDNu3LZwOIxwOAxRFJFOp3HppZdCURQkEgmtRFLvtjU0NOSUSYbD4Ypw25iDVjlIkoT6eus5LBMTE2hp8akRGsDhw4cNg6f3798PALjhhhtw8OBBjIyMYHBwUHs+k8ngzjvvxOnTp9HQ0IAtW7bg17/+NXV4NSMLE2hVBu1Nm+d5CIKQl0AjhGB0dBTRaBSyLGPt2rVYtmyZ57swlVDiWIz9E0K0Uk+e56k9eOWewVZKgUYIwdjYGD73o7cgIOtOANkL3XwQ0jAMC3aiUiL2nVAFF02kFRM3zl0xwkKKjR/izApVpJnLHL24v4zaxcpt++bR+7TPUZ7n0dzcjObm2cZSQojW2xaLxQyuWyAQoPa2lVpoVEvQSb43risJNyWO8+fP903YX3nlldqweBoHDx40fH/gwAEcOHDAl33XCnPkcobhBY7jcv5wvDpYhBCcOXMG0WgUkiRh9erVWLFiRd5vxuUucfQ7Zl8vXBVF0YQr7c2vHC5WqfdNCMG5c+cQiUSQTruLFQwmFMhh+w8LL+JsrlKISBPS2X8ZD4EhfsTr+1nmaHbPvJY51o2TvMpY9W4ZrcxRPxstPKlAbMieq2qZI8BcNEb+3HLxPTmPmYdtq27bggULtMdlWTa4baOjo4jH45BlGfX19YYSyaamJoRCoaK5bcxBqxzcljgy5g5MoNUIboNCCCE4e/YsotEoMpkMVq9ejZUrVxZ8l0x1kUo9k8u8/0LRC5FMJoO1a9di+fLltj8fVSSV47WXQqCNj4+jp6cH8Xgca9aswQ1f+AWAWfdMj9q7E0zk1gSaExzN4iyf/jO3FDNi3w3hCUAsoHc7FHMv0jgJIA7v/Pm6aGo5YyhGf1yP10HUetQyx7oZ58xr/L4dVgEiwSTRRBqQPV+FTPXfQGCUDje9bYIgYN68eYY0YEKI1tumF27JZBLBYJDqtvnhfFWDQKumHjSnFEcm0OYWc/+sZORAc9CcBJoqPKLRKFKplCbM/HrzVd84nO7yFAs/QkIuXLiAnp4eTE9Pe/r5qK+9HB8ExUxxnJqaQiQSwdjYGLq6unDZZZd5en127lkopkApliCr0IqcYKIwkeaWQKrwgBKnyH23WPXW0ZYzi7m6IpY1mlECHHiJaCItkCaQZs5f5qIxio1TbxvHcairq0NdXR0WLlyoPa66bWqJ5PDwMOLxOBRFsextcwshpCpCQqrFQXOK2Z+YmKioiH2GM0yg1QhWAo0QgvPnzyMajWJ6ehpdXV3o6Ojw/Q2rEgRavg7e+Pg4IpEIpqam0NXVhc7OTk9CRD+PrNQCrRjplclkEpFIBGfOnMHKlSuxefNmhELukipozpmZUMyd9eSmDM7vBMdCI/adCE0BmTzH5OldNCeRVCm9aGr4i9kddSpzrBtXqA6tV7yUOWrHPJVHIgyD4TOFuG2pVEpz2qampjA8PIzp6ekct625uRkNDQ1Ut40QAkLInBc31eCgEUJcOWh68c6ofOb2WcmgQhMg5hI/NcwhEokgkUhowqxYb1Qcx5U1LCMfF0vvEK1atQrbt2/PS1zyPA+O4yBJUsmbkf100FKpFHp7e3H69GksXboUb3/723NSo/7iH74JhLnZcJCkArHBnUpyK8zyRXVcvIi2VFvpSlK5mV+TWaS5dZkAb6WONJwSHN3MPwvFCXXguJeZaHbUjWfPE04hvog0GnZz0lQ3DZgtcyRv3w7u0J+LciwMhhfcuG319fWor6/HokWLtMclSTL0tundNn38v/pPvc6Y6yEh1eCgKYoCQoijg7Zu3boSHhWjUJhAqxH0DpoqzOLxOFatWoUdO3aU5A5SOaP21Tdgp7tMQHa+RyQSwblz59DR0eHJIbKiVHPYzPjRgyaKIvr6+jA4OIiFCxdi9+7dObN91LupdmWLZnei2PjhspjnaqVbKdsrgq5046RZuWRuSwwLddEKnYnmdXSCU8+an31oNPTCDIChzFGuE9iHKaNiceO2BQIBtLS0GKLYCSGYnp7WyiQnJiYwNDSEVCql3awcGBjQRJuV21bJVIODpt74Zj1o1cXcPisZrgkGgxgfH8cf/vAHTE1NYdWqVbj00ktLWm5YTgdNHTVgt/9kMoloNIrR0VEsX74ce/fuRV2dP3F15UpyLGS/sizj5MmT6OvrQ0tLCy6//PKcN3hVmCmKgnfd8B0gzGlzz7y4Z2oqnkq+/Wequ1Is1Dh3qlBziVtHLN9yRy+z0fwYmE0/BrqLZrm8mDuEnFbmWIzfr51bBtDLHFVCsezflhzmgb/cgcCzh30/PgajWLhx2xoaGtDQ0JDjtp0/fx7Hjh2DJEkYGhpCPJ6119XeNjVFsqmpqSxtDW4ghFRF0InqAtqJ48nJSbS1tZXwqBiFwgRaFWIucZyYmMDIyAiSySRWr16dd6leoZQ7at9KIOpL99rb27Fnzx40NPjbfFMucSoIAjKZjKd1zEO3t23bllO7rhdm+5o/kn3w+p0ITBOAy5Y26gkmFC3BETAGhISmnOP2nRIcw5NKUd2TnP3pAirSLcUrgwxN5dcHFooTZJoopc4FROzTyhvNLloobu+KqWWO+QweL8XvWN+H5rbMkcGoJty6bQ0NDQgEAtiwYQOAWbdNLZEcHx/HqVOnkEqlEA6Hc0okGxoayj5sW715WQ0Omt1rIIQwB20OMrfPSoYtk5OTiEQiGB8fR1tbGwKBQFlrkMtZ4gjkuknpdBp9fX04deoUFi9eTC3dK9a+S4UgCFAUl6EbhGBkZATRaBQcx1GHblOFGYDk9Ts9xcqrhAoIXAhPVkZYg9rbltK5avn8LKwITxJPItBr9Lvqoln1n/kdFmJZmklx0cyYyxjNfWilLnNUQjz4TPaXzVw0RjVDE253/fIm7Wu927Z48WLtcVEUDfH/g4ODSCQSAEDtbSvlzWP1pulcd9CcEhwBluI4F2ECrQpJJpN44403MDY2ho6ODmzZsgWTk5M4ceJEWY+rnCWO+v2Looj+/n6cPHkSbW1t2LVrlyHlqhj4PSjby36dhKGa5NnT0wNRFLWh2/pyCXVsg6IoeG/TDbn7yRAoAfrFNS25sRBhBgCheH7rF/PinSbU/MKrSAOsXbR8cAoPoeG1zJGGWuZYbDEenpRnEzplgnSr8YLNrswRAIS0khVoDEYN8bXrHgXwqOExvdMGZCtnWltbDeKAEIJkMqmJtrGxMQwODiKdTiMcDqO5uRmNjY1amWR9fX1R3Da1vLHcTl6huHXQmECbWzCBVoWod7I2bdqkpQaW270Cyl/iKAgChoeH8cYbb6ClpQU7duwo2RtWpYaEmIdM02a7qXX6esdMj/SXO+gbJ7PiTF/eWAh1E9ntuRlwXKyEPyfqxr2LKc7iVySIhZXRuRVpwXj+4lUtc3Qqb9SOqZgz7jxQN271Q+cQ1j3HKQRi8+wJp7po2v8zLlowln1vk5iLxqhh3JRIchyHxsZGNDY2YsmSJdrjZrft5MmTmttmdtqampoKLk2shgRHwFmgxeNxSJLEBNocgwm0KqSxsREbN240POY0qLoUBAIBz/1QfiDLMk6dOoWJiQnU1dVh+/btWLBgQUmPodJCQmKxGHp6erQRArQh007CTEUO87PumYvr7lBMMTgr5v4z2sW7KswqDatSRjXMItXqn6uid9G8DINWKaj/LEFsRbbVtv0ICzG7Z4WUOVqKMgdU8aUXamb05Y4MBsOIUyAJQHfbFEUxuG3nz5/HwMAAMpkM6urqckSbF7etGhIcAWeBNjExAQCsB22OMffPTIYrgsEgFEWBoihli8ENBAJIJvOolcoTfdhFKBRCa2sr2traSi7OgMopcXQzZFrtMSOEOIoz5R2Xej4mr2Vv4UnFsnxSpZQBIV6oG1cMIs3LTDMaxSp1DExn3S+x0UaETduLNFfH4nHWnRfH1HFbeYozPaHJGZes0fquO59RmIvGYLjAjdvG87wmvvRkMhmD23b+/HkkEgnwPG8oj2xqakJjYyNVwFSTg2bXuzc5OYl58+ZVhRitJdhvqwqh3T1S/3hFUSz5sGT9MZRCpBBCMDw8jGg0Cp7ntbCLY8eOlcXFAspf4phKpdDX14ehoSHLIdNWASB26B2FwLQCaSZWP5BUINXnqiaze2aH6pw4ibNKx283LTxJINXRfyZWASGFuGduCCackzj18CIpWZmjW2FGOMz2oQkcIKtpjlzODL9AQgYvKZAas+e/6p7pXTQ2vJrByA83blsoFEJbW5shOt7stp09exZ9fX0QRRH19fU5bpubuahzAafruvHxccN8O8bcYO6fmQwqHMdpwQ7A7Bywcgq0YvfBEUJw5swZRCIRKIqihV2ogrVcZYbqvtPpPOrSCoQQglQqhUOHDjkOmfYizPSoAkrSzTzTi7Ns6h3n2j3hRYJgcu5GmFsN5K6/oCDd4o9IC8UUZJrdb0vtmXIimCB5u2hCmj6oPN8yR7uyVqcyRxU/XDM95uj9QELSRJoePqOAk1i5I4PhF4W6bbFYzCDckskkOI4Dz/M4ceKEQbjNNVdNkiQ0NjZaPq9G7M/1MJRagwm0GqLcQSHFSnEkhODcuXOIRqNIp9NYs2YNVqxYkVPKGQgEyiKS1H2rzc6lQB0y3dvbC0VRsHPnTtsh0/kIMzUcJDA9EwRi4555KW1zEmf5lrtVQhlkeNI/keaVYEKB2Oh938GEP2LZfA54cdF4ydvvnVOyyYylIJCQoATpP1fmojEYxcWt27ZgwQJDe4OiKIhEIojH4+B53uC2qcO29f/C4XDFChw3PWis/2zuwQRaDVHuoJBilDheuHABkUhEG8JNSyFUKWfMf6ncO/OQ6Y0bN+Lo0aOGN+dChZkeIa0YnItA0ptroHdcwlP+lTSWK8HRDWrpppNQs0pw5Gce9+KiCWlrkaX2n6l4ddFoYxRy9u9xNluhoTB1EzJIHqeAlzJHJcCDn3HJhGkJcr2x3BEAc9EYjDLg1m0TBAFNTU3afFhCiNbbFovFkEgkcObMGSSTSW1Z/b/GxsaKcNuYQKtOmECrUswljkD5Y+79FEgTExOIRCKYnJxEV1cXOjs7HWvJyy3QirlvqyHT6XRaC/xQlyOEUGeZeUF1z2jiTO+eBROyYT6UVambn+KsEqGlPapumlXEvhu8ljrm66K5xarMMTTlsUfNRUmmVZlj3URxb4SYyxxVhOns3/esUBPAZ2TmojEYFQJNuD3wp/9b+5rjOITDYYTDYYPbJssyEomEViI5OjqqRdeb3bbm5maEQqGSum1OAo3NQJubMIFWQ5TbQVODMgpJkpyamkIkEsHY2Bg6Ozuxbds22/Qi8/7LJdCKFRLiNGRa/V+SJHAcV7Bj5jdhh4HVbgRbuUoXrSL2vRCeVJBpKuwFqCLNq0tlh5OL5he0MkerodRuyhz14owjyMtF84LqopEAr7llgVj2PVYJZ++sc5IC7orNIH94o7gHw2AwPPPpS79EfVzvtgmCgHnz5mHevHnaY4QQpNNpQ5Lk6OgokskkgsEgNUmyWAnaTimOExMTLCRkDsIEWpVCu3tT7h409Q1EkqScaHcn4vE4otEozp49i5UrVxqGcLul3A6a3wLNzZBp9fv3zfuob/t1G61vds8YdOomFKTmF/Zz8iLOvLhoVv1napkjrbzRMizE4nG/CI/L2bLEAvFS5uiE6qJxMsHcjb1hMGoPp942juNQV1eHuro6LFy4UHvc7LYNDw8jkUhAlmVqb1uhbhshxJWDtmHDhrz3wSgPTKDVEOV20HieB8dxngRaMplENBrF6Ogoli9fjr1796Kuri6v/Zc7xdEvcejnkOl8UELZi3u7Pq9gwvnnHIrJ2raqBa8X8CqFijSv4seNSHMKBzH3rlkRcnBJ9ejdMy9ljmE1rVEmvog0J2hljqqLRgIcOImAT8vgRRlKSMgKtcs2QXn1zaIfG4PBKA5uAkms3LZUKqWJtqmpKQwPD2N6ehrBYJDa2+bWbZNlGYQQR4HGHLS5BxNoVYrVLLRSDoo2w3GcaxcvlUqht7cXp0+fRnt7O/bs2YOGhoaC9j/XSxz9HjKdD07uGacQR3EWimWfz0eceU1w1Je82ZW7pVrL3+hdqEgLTSnIzMtd30tASDkoappjCcscreAzWZEGAMKm9ZDfPFHcA2IwGCXDTSAJx3Gor69HfX09Fi1apD0uSVKO2xaPx6EoChobG6lumxn1msYpJIT1oM09mECrIcrtoKnHYCeSMpkM+vr6MDg4iMWLF1PnduWLHz1w+aK6d4QQz+UMxRoyXQhCSobUEDCk1zmuk1Yg2Ew5KCQgJGyed2VyUZwu0mnzskoh2njTn0LdhGLb+8VbJDuqWIk0GsGEYu+CzoS+iA3e/1byKXO06j1zIud37wOFljmqLpoSFMCL6g0JATyAwLo1kCK9vh8zg8GoHNy4bYFAAC0tLQZ3S++2xWIxTExMYGhoCKlUCqFQKEe0KYoCQRBsryvUOWiMuQUTaFWKlYNWzhRHwNrFEkURAwMDGBgYQFtbG3bt2mUoEfBr30C2JKDUAi0QCGgCym0sryiK6O/vx8mTJ4s2ZNoLyjsuBacQCCl3EebF7j8Lj2fPoxyR4VOJm1m0lcplyyegw84lKxZq/5nV4GrAfXkjLxJqSaNTmSP1HKiAMkczfEYGJ8ogQQEkzD52GYxapFC3TR9IMjQ0hEQiAUXJvt8cPXqU6rYRQjAxMYG2trYivjJGMWCfFDVEuUNCaMcgSRJOnjyJ/v5+zJs3Dzt27CiaFa8KI6fEo2LuW5ZlR4GmDpnu7+9Hc3MzLr/8ct+HTPuBGiuuEkhKkOvory0YkzyXNNIuzNULcpVSzjtTBZtXoZZP2mMhA629umiOvWhJJW8XzS1OaZ561DJH87lgRSFljqHxzOw3M6Mq9A6a2Jy9CKKVOdJcNE6UQcJBVurIYDA03Lpt8+fPz5lpOjw8jJMnT6Kurk5z215++WV85zvfwbp167Bx40aEw2GMj487hom44aWXXsIDDzyAV199FSMjI3jyySexb98+23VeeOEF7N+/H2+99RZWrlyJz372s/jIRz5S0HHUAkyg1RCVVOIoyzJOnTqFvr4+1NfXY/v27Ya5I8VA7YErh4voJiDFPGR669atWLBggcENLZsw696anekUMF6oq+WNTuKsUEKTqlNS8KYKpm5c1srfUvOL56oVW6T51X9mHlytHUNMoc69sytzdBMMUkxCExnHZfRljsFYRit/5BQF0jzrZFkSFMCJWScNMmEijcFgWOLWbeN5HnV1dVi9erX2+MaNG7Flyxa89tpreOONNzA2NoYPfOADAIBLLrkEW7du1f5t2bLF003xRCKBrVu34sYbb8T111/vuHx/fz/e/e534xOf+AR+/OMf47nnnsNNN92EpUuX4pprrnG931qECbQqxarEsdwCTRAEXLhwAQMDAwgGg9i0aRMWLVpUsqGOxR4YbQXHcZYpkoQQjI6OIhKJGIZMm4UZkBVxhQ6ZzhdVnOndiEDS+mepF2Zm98yNm6aKskpGDSEpllArVKS5SXakuWhq/5n+e72LRovXzxcn94wm2szumTqkWsNjmaMbYeYE4XkEprJNlnKD0aHXu2h6WD8ag8HwgircVKFGc8VaW1tx7bXX4tprr8WZM2ewbt06TE5OYnh4GK+99hpef/11PPPMM3jggQdwySWX4Fe/+pXr/V933XW47rrrXC//yCOPoKurCw8++CCArHh8+eWX8fWvf50JNAeYQKshgsEgFEUpS0iGasWfPXsWQPYuTnt7e8mEmUq5Z6Hp9+00ZFq/XLEi813RvdXzKnwm/wv40OTMoF+TW1cJ7pkVdRNZVyTtQ58aLxmdLVWkOQWEFIKX2WheEDLEs4vmRD5uql2Zo504M/SZcZxW5ugUFiIkRa0XTW6YdcxVFw1BARBl1o/GYDA885/nHoEoiuA4DqIo2rZNTE5OIhwOo6mpCRs2bMCGDRvw/ve/X3s+kyn85pQdr7zyCq6++mrDY9dccw1uv/32ou63GmCfDlWKlYMGZMMnvA55zhdCCM6cOYNoNApZltHa2opgMIilS5eWZP9m/Ii792Pf+iHTq1evRkdHR86bbNmFGQBhy0bImHXP+LQEuS77tsH5rBdUYeY3xY5Z16MmCroRauYER9vtTioQG+gvxK7XKxRTkGn2R3jZ9aKZyxxDMXcCneaelarM0Q/XDIAh5ZH6dDylfU3Cpt5XmSCwpgtSb78/x8JgMKqWn01+X7vJTghBPB7HuXPn0NraqgkttZ1CvQYcHx/H/PnzLW+Gu51Jmy+jo6NYsmSJ4bElS5ZgamoK09PTOYnUjFmYQKtiOI7TSuOA7B+uIAglEWiqOxSJRJBOp7FmzRqsWLECg4ODGB8fL+q+7Si3gxaPx3Hy5EnHIdPFnGXmBbnR+OatirOc5XT9Z4G4qM19cksgYfydmN0z15Qgvc8N4XHZFzfNsM0pBWmX4R96aCKN1n/m1kXzWt5o56LxGcVVuasq2uzKXr2UOfomzkwQngenmH4+PA/oHjO7aAArdWQwGNY8OfUDrbJGbZVQE56XL1+OVatWged5Q4+6ytGjR0teqcTwBybQaoxSJDleuHABkUgEiUQixx0qp0Aq5/6TySRSqRROnDiBjo4ObNq0KUckV5IwA2bdMz4jQw7wBvdMSElQKOVZgbi3cys4mb1QNoePuKGUCY563DqH4XEZnEKQbvXvbdaLSBMy+Vmc5v4zt89ZhYX4hVmccYr3Mkf1fPOCqzJHiotGi9zn0rOljyQUmPk/CC4jMpHGYDByuO3/vQHPP/+8Fp8vCALOnTuHYDCIyy+/PGcckSrO0uk0Hn74YXzlK1/Bpk2bynHoAID29nacOXPG8NiZM2cwb9485p45wARaFWN20IDiBoVMTEwgEolgcnISXV1d2LFjR447VO6o/1ILtHQ6jd7eXgwNDSEYDGLNmjVYu3atYZlKiMynQYJCNrlR4MCnZ39mQir356cXZmb3jOaQ5HOhPFdRAy38Emr5OGluSx2DCQUoUGPRyhtpLloolnWPaC4afSaakr+zimxkfin6GN24aBpqL5oq0jpWQBocKv5BMhiMiuZ/4j8EkL0+mJ6exsTEBE6ePIl4PI5AIIB0Oo0jR46gubkZL7/8Murr67Fjxw5ccskl+NOf/oRbbrkFhBA8++yz2LNnT9lctO7ubjz99NOGx5599ll0d3eX5XjmEkyg1RjFGFY9NTWFSCSCsbExdHZ2Ytu2bZZzxso9LLtUKY76IdMLFixAd3c3ent7DX1mlSrMAEDYeBFo/osqzmjumettm+anuXHPKjkgBIBtD5JKeFzKW6TlBIcUUaQFkgokm7lngWkFUr11L1oxcNufaFXmqM4z8+q60XfiPiyE5qKpj3EZCZCyIpUEZ86LYJCJNAajxlHFmcrk5CR6enrQ0tKCbdu2ob6+HqIoIh6PIxaLIRqN4tChQ+jvz/ayEkKwefNmfPjDHwaQvUZraWnx5dji8Tii0aj2fX9/P44cOYK2tjZ0dHTg7rvvxunTp/HYY48BAD7xiU/gW9/6Fg4cOIAbb7wRzz//PJ544gk89dRTvhxPNcMEWo3hp4Om/qGePXsWK1eupJbtmamEEsdiphbZDZlWX3slCzMgW9pIglkhSVz0dJkvQK0IxLLnHSnjnKty4yTSzELMdltTCqQ8kxDzJWBT4ugF1T2zw01YiBvBZRg2nSeGMkcrdGWOnlw0FUkCZioOAh0rAFGCNDJawFEzGIy5hFmYTU9P49ixY4jFYtiwYYNh/E4wGERraytaW1vxjW98A7/4xS9w1113Yf369bjuuutw/vx5LUp/eHgYXV1d2Lp1K77whS9g8+bNeR/j4cOHcdVVV2nf79+/HwBwww034ODBgxgZGcHg4KD2fFdXF5566inccccdeOihh7BixQo8+uijLGLfBUygVTE0S9uPEsNkMone3l6MjIxg2bJl2Lt3L+rq6lytq+6fEFIWyz0QCCCZTPq+XTdDpnme14Z0V6Iw01ADDFwgJJ0DQVRhVg5KmeDolroL2RsUmZbC335DMRmZZvdhJKGYYit6AtNZAZGvixZMZIWXHM59ziosBKCXOWrHrHPPvJY5hiYzWcerjNi5aAgIgCSDE2duWkkSEAwCM+/RgaXtkEbP6lb0b/4cg8GoDMzCTFEUDA4Ooq+vD+3t7di8ebNlVdLIyAj279+PQ4cO4Stf+Qo+9rGP5YzqOX/+PF577TW89tprBTtpV155ZU7rjJ6DBw9S1/nzn/9c0H5rESbQaoxCHLRUKoW+vj4MDQ2hvb0de/bsQUNDg+f9q+6R3eyOYuF3zL5+yDQA2yHTgiDgzm33+bbvYiBsvEj7mkuLIA25EbzcjEsgJJ3PIz7t/Wc91xMcVexK34Bs6IUfIo2GXUBIMCFDbCz9356KG/fMC2YXTS1zDKl9joQYRFpRyxwdIvcdXTQASGWHXSMYAEQJgcKvf4AAACAASURBVIVtkMcns/sy/+iYYGMw5jS0csajR4+CEILt27ejtbWVup4sy/j+97+Pf/mXf8G1116Lo0ePor29nbrswoUL8c53vhPvfOc7fT9+RvFgAq2KsZqF5tVBymQy6Ovrw+DgIBYtWoTdu3ejqakpr2NSQ0MkSSqbQPOjxHLODJn2QGDtahBAE2XKzP/8tAil3nj3zkqc6d20QDwDxeTE+VXeWOkJjm7xQ6R5ddHcYnbRzOWNdr1oQlqxdNGsoLlo4QvpvBI+Q0UIoXFV5uhleyYXTXPO1O9lJSvSAAitLYBCoMQTINLs3x5RKD8bJtoYjIrHLMwkSUI0GsXp06exatUqdHV15VxPqBw9ehS33HILRkZG8B//8R9497vfzaL0qxAm0GoMLyEdoihiYGAAAwMDaGtrw86dOwu2x3meB8/zJR2WrccPgTZXhkx7hQQD4DKi5kSRhhD4aXuXjFbeGIi7vzjO5+LbjHYxTvmAsnJKMvOLO5zTC2p8vGTharnpS/Mq0orhoqnljb5tz0JkOZU5hiYzuQLe5KIVijBJucml00Va/5neRdXPQqs3nX92Ik1Rsr1pkgR+XhOURDL7emQZwOzPnKj74phoYzAqGbM4O3v2LI4fP46Ghgbs2rULjY2N1PVSqRS++tWv4uGHH8bHP/5x3HfffWhubi7FITPKABNoVYyVg+ZU4ihJEk6ePImBgQE0Nzdjx44dljZ7PpQzybGQFMdYLIaenh5tyPSll16aUxdeabPM3BLoXAlkxNkLR47TxJnePeMc0gq9iDOv6F2RQh00q0HFeQk3FwmOKnYOTGhSRKaF3mdAg88YN+ZGpAnp2XXMIk3tP9NTSKIjjWBsJgXUxXBqL1iVObpd3g2BiensFzb9Fznw3KxI05U3cvHU7DJ1Ls45VaRlRPCNDSAZEUQUwXG8TnyZxBoTZQxGRWEWZups1LGxMVx00UVYtmwZ9bqNEIJDhw7h1ltvRWNjI1544QVcfvnlzDWrcphAqzHsQkJkWcapU6fQ19eH+vp6bNu2DW1tbb6/CZQzyTGffSeTSUSjUYyOjlqmVVZ6MqMlHI9Ax3ItPc4OPpkBCVsLCD7js4MyMdOLk2dvWT59RmbhVmqnzatIy1k/JlNLCwsln/RGqzJHO9QyR717xklKjtNq5aIVo7RRE2Z+IvBZdwwAkrrth0KAKGVLG1UXbcY9g8mV43h+ZhRGdltcgAeZ6a/lBNavxmBUEnpxRgjB0NAQotEoFi5ciN27d1tWFI2NjeGee+7BT37yE9x777244447LANDGNUFE2g1Bs1BUxQFp0+fRm9vL4LBIDZt2oRFixYV7e5MOYdVexFo+iHTVqEoc1mYAUBgzSqttDGn7GoGPkm/6OVEGQgJEBLZ54mp3yyf/jMhLiKvwrsinat6wVYqsVaoSAvGJIjN7t7a3ZQ6OomzwLTiGIiiHlcxMYuzHBfNY5mjZ2HGQytzNMTsW7hos+sJgDKjplSxJkozJYzICjRVpKmpj4EACABOEABZBpFnt8kJAogkgtO9dqKQ3NJHJtgYjKJjds3i8TiOHj2KdDqNzZs3Y+HChdT1FEXBT3/6Uxw4cABbt27Fa6+9hjVr1pTikBkVAhNoVYxTiSMhBCMjI9rQwfXr16O9vb3otnm5HTRVUFk14NKGTJvrvOesMANmxdnSJYAogjOXbHGmi1r1S4p7poqzQghMpWf3YfE70VOugJDQRAacAmRanYWaG8Fiu68CRZoXggnZ8WcqTEuQ671/XFi5aLax+hfSOWKe5qLpycdttSpzdBRmugTHgtC7aKpIU10zAJgRXwb3jOeNIk2SAEFAzqvWizGi5Io18zK6ZRkMRuGYhZksy9p1xcqVK7FmzRrLoLSTJ0/ijjvuwJ/+9Cf827/9G/7+7//e8nqFUb0wgVZjBINBKIqCkZER9Pb2QpZlrFmzhppAWMxjKKdAA7J9dqGQ8UJblmVt9oh5yLRKNQgzjWBgtrRx5nfPpSWQutIIAzcx/ZWE2j+mH3zsRqzlS2hShNSY31s0zUXT95/5jZCSIddZO3HFcM+8zkRzQ8HljPm6aIaD0Ik0bbsz6ygKyMzMNE4Qso/xPCAIIKk0uKDxd05MI0WI3Y0DJs4YDF8wi7OxsTEcPXoUwWAQV1xxhWWwhyRJ+M53voMvfvGL+Ju/+RscPXrU0mFjVD9MoFUxZieMEIKJiQkAwLFjx7B27VqsWLGi5HdmylniyPM8OI4zCDS1xDMajVoOmVZnmSmKgvc23VCWY88bkzDjBAHC8vbZ/hZRBMLhXHFm4RJwasmjroTRXN5IQ++UAS4THCtstpmZ0HgGIASZlsKEGi/RL47VXizRtH1zQAh1XQ+ljoGkBKmBvqwwLWn/01y0QNJefFkJQ5qLpg415yTi2kXT3DMgG9iiO2ecyhxVF82zMCumi2Z4XpgtdVR3HQyAiNKs+FLFnsCDKMrs9oAZ5yz7t0lkme6kzS7MRBqDUQBmYZbJZNDT04OzZ89i7dq1WLlypWUIyGuvvYZPfepTiMViePLJJ/HOd76ThYDUOEygVTkcx4EQgrGxMUQiEcTjcXAch8suu6zgyPx8KWeJI8dx2v7dDJkG5mZkPgCqMAMAYUFrVpzVhTVxlrNqSgQJ57490MQZDXP/mRBPaS6dFW7KGyuOmYt0tf/JTqgVMkMrOJnJEWk0zMLNL5HmBicXrRiExqYLPm98DwHx6qLpRZp2UJRSR30K5IxI0ws4ThCyok2/PZ3oUv/+FdHmvddUGslgMNxhDgEZGRlBT08PWlpa0N3djfr6eup6iUQCX/rSl/Dd734Xt912G+65556cXndGbcIEWpUzMTGBnp4eTE5OYtWqVbjssstw6NAhKHYlNkUmGAwikUiUbf88z+P8+fN48803kU6nsXbtWixfvnxOD5nOQXehxenq3IUFrbNljRQXk0tZOJsymRVnHhDUOPFiii8P88+KjSrUxGb/y0TdirSc9WKSbay9kHKfvplPL1ogPjOugTIzT++iqe6Z6+2aHFkr7Fw0YTKZf8CMXy6aHr2LJorZuWiG572JNEOJoyrU7Fw03XIMBsOZ/zr/74YExmQyiWPHjiEej2Pjxo1YvHixpWv23HPP4bbbbsPixYvxyiuvYOvWraU8dEaFwwRalROJRNDS0oKtW7dqJX1uZqEVk3KWOI6Pj0MURfT29mLt2rWWQ6YVRYGiKHjfvI+W5TjzxsI144IB8POaZ8WZMLOcRbSv3j3jpjMgIQ/zuRJpcD73BqmUKyDEC5xCXDlq+RCczOQV1uEWs4umljfaLa/HTxfNS5mjAVOZIw3DoGmfh1gDMLhoBpLTQEM9kEjO7lvFIKZmHhdFXSnj7LJar5ksZwWaIGTDREyiUf37J7JMdcdUsWYQaiztkcFw5L7f3olYLIZDhw4hGAyiubkZiqJgcnISixcvxq5duyyj88+ePYu7774bTz/9NO677z7cfPPNloEhjNqFCbQq5/LLL9f6p1TKGdIBlKfEMRaLIRKJ4MKFCwgGg1i3bh1WrFhhWGauDpkGYCvMOEEA19hgLKkyk8lkZzCZNztNcc1M5YtcRgIJCuAT7hwNwGX/WQWRb3liIUKNs+hLC8RESB4dukBchNTkbh2nUkcvLprqngHZOXlWLlognskpi7Xdrs494xTFU5mjMFWEuWYWcLGZSgH9e3AiSV/YCV2JJNHH8Mvy7Pb1+9EtbxBqOmxDQ7IL5HesDEYVoy9nlGUZIyMj6OvrgyzLaGhowLlz53Du3Dk0Njbiv/7rv7Bw4UJceuml2LFjB371q1/hM5/5DPbs2YM33ngDHR0dZXwljEpmbl0lMTzjFLVfDkopEJPJJF5//XW88sorqKurw969e9Hc3GwQraowk2UZ7226YW6JM47PKWfUxNnM15o4C4Wyd9m1hWfODYo446Yzmjhz457pxZlv4qvCA0K8YDdA2SogxA5aOaBTcIheLBWKMC1ZumteSiad4KRcAREccyGwZON66tgDS3GWb6mi6f2ViyVn/+mFmH45q6/1d9D1QSb6x/k8llddMjn398LxnKHkkcFgWPM/8R8axJkkSYhEIjhx4gRWrFiBd7zjHdi9ezf+4i/+Art27UJXVxcCgQBeeOEF/NM//RNWrVqFm2++GWvWrMH27dvxpz/9CQMDAzk30f3ky1/+Mi6//HI0Nzdj8eLF2LdvH06cOOG43k9+8hNs2LABdXV12Lx5M55++mnD84QQ3HvvvVi6dCnq6+tx9dVXa/38DH9gAq3KoQm0cpYYlmr/6XQaR48excsvvwwA2LNnDy6++GKEw2FDSIgqzP668R+rT5ipMfp6cRaeEWJqUECGIhw89CdySReumavZZnPwrcjLh6pMEJxIGxMHC8RrzxaQK9KsxFQgKTmmM3J5XFPwmdz9BeLZc5AX8xd2nItztpjOmSrK3K9QApGmkKy7Jsu5Tpj5/cNKpKnLmZZnMGoNc0Lj2bNn8dvf/hbxeBy7du3C6tWrtT52juPQ2NiIJUuW4Etf+hLe9a53YXp6GjfeeCP++7//G+9///vR19eHe++9F+vWrUNrayve8Y534NixY74f94svvoibb74Zv/vd7/Dss89CFEW8613vss0B+O1vf4sPfvCD+NjHPoY///nP2LdvH/bt24c333xTW+arX/0qHn74YTzyyCP4/e9/j8bGRlxzzTVIpVK+v4ZahfOg3Isn8RlFQ5IkyKY7p+qbwMaNG8txSJiamsIf/vAHXH311b5v2zxket26dTkzR9544w2Ew2GsXr16bokyFXM5o+7iigsEZ/tTAoHs13rnTBVCeldM756l0znBBHoHjTMnwAVyy9JyHDSK+DIvQxVoFAeN2oNmTt0swnUktcTRagwBrWzM5OiI82d7E6wcNKsSR7OrpJY7WjloNFGkljvauV3EwVgRUhIUStLn7HHSj8dc5qgKNCA3/VM7lpleNLW0kebS5pxDuvOHn1LDaiwPN4uHXjSDILP7HNWfD8TF12anS+/2659TLNYhujJIIEecmcsaac6aaQX75xmMKsYszFKpFI4fP46JiQlcdNFFWLp0qWUIyB//+EfccsstkGUZjzzyCN7+9rfnLKveTH7ttdfwnve8BwsWLCjq6zl37hwWL16MF198EXv37qUu8/73vx+JRAK/+MUvtMd27dqFbdu24ZFHHgEhBMuWLcOdd96Ju+66CwAwOTmJJUuW4ODBg/jABz5Q1NdQJTh+2LAetCrHqsQxmcyzD8IH9A6WX3M+9EOmm5qabIdMBwIB7N/6BV/2WzIod6/NwgzArGsmy1rKG6deuNJEUEY0XhzaiDM3uClvzLcEko+7vDM3c05J8+mxxsWEKs4oqE6a7LIvzI5ATIQS9r/BXEhJkOv8/4jQ96LpxRmQddGsRJqh74wSFpLTizYTFqKJM5/w5JTZbkgX6KH/mjL7jIokAYEAiOqCW4lE9b3DFAxiG7evW57BqEXMwowQgqGhIUQiESxevBi7d+/WgtfMTE1N4fOf/zwee+wxHDhwAP/n//wfy8CQcDiM7du3Y/v27b6/BhqTk5MAgLa2NstlXnnlFezfv9/w2DXXXIOf//znAID+/n6Mjo4abrK3tLRg586deOWVV5hA8wkm0GqQcoeEBGdEgCzLCAQKOwXNQ6a3bNmChQsXVs+QacDWMQNmypmIkhVmqjirC2fFmVrSqL9wDQWzwszLISRnysPMsd8+wSmKsY+NJiY96jqn+VblEHB6OEVBYCoNaR5lDp1L90wlEM9AanIfRBKIi66EspVIE1LZ9w8+TXfRhKR1tH4pKZk4s4vc188/s1vOSqTpHzf/3Zp7Si1CQrLP8yCSqPuWkuCYfYB+fAxGjWAWZ7FYDMeOHUMmk8HWrVstXS5CCJ566ins378fa9asweHDh8tWqURDURTcfvvteNvb3oZNmzZZLjc6OoolS5YYHluyZAlGR0e159XHrJZhFA4TaFVOJYaEqKJMFMW8BZp5yPSGDRvQ3t5ePUOmAWfXTO05C4VAFCX7/UzstibO1GG3+jlY+ou8oM3PX5LA6S8A8xFnFKHFSYoxHbJMIQVmAWcl2AoZMO3qOGacIZpQ87QdjyJNSIqQG+i/Uz5d3Bs4fEaGkMiAUNwymosWmJjOOZecIveFWPb3axD7CuyFvkXkvm+uGWDtnJkPJZ0x9oNaldTyPIi6nHrsapmjKvJsRJdhLpob547BqFLMwkyWZfT19WFwcBAdHR1YvXq1ZRz+yMgI7rrrLrz44ou4//77cdNNN+XMVi03N998M958802tN59R2TCBVoOUOySE4zgIgpCXi0cIwfnz5xGJRKp3yLSK7qKKM30oaN8HAiCyDE6bb6ZbThNnMxfhMyVRlugFWCpN7S8z4PS8/ngTOiejwj60VNwKNgCeA0Jc7d/CTfOCWaTR+s/02Ik0bRmTi6a6Z9o+LFw0df92LhonylSRZti/29JWeI/cd9ye1+APNy6aCZJKgaurA1FdajcOm/kpvUibWZbob8RwvKVIo85AYy4ao8Ywi7MLFy7g2LFjCAaDuOKKK3J62VVkWcYPfvAD3Hvvvbjmmmvw1ltvYenSpaU4ZE986lOfwi9+8Qu89NJLOSOGzLS3t+PMmTOGx86cOYP29nbtefUx/Ws9c+YMtm3b5vOR1y5MoFU5leigqcfgVaBNTEygp6cHsVgMq1evth0yPSdnmVHgBAFEIdpFFK93vAQBICQrzgiZFV+yDM5cG0/7WZvds1SBCYOpDNBUlz1u9aLaPHOt2OLMx4HDmmAjBHJLg2/btd3nVBqcpBQk1Lw6aW5w6kfTizS1vFF7jiLShIT12AHAohdNUVy7aKp7BlBEm0sXzVfXzLyL6Wlw9fUg0zMuX1J3c0AvxHje6KJ5EGkcz9mKL9sZaEyoMWoEszDLZDLo6enB2bNnsXbtWqxcudKyV/7o0aO49dZbcfr0afzoRz/CX/3VX/nWV+8XhBDccsstePLJJ/HCCy+gq6vLcZ3u7m4899xzuP3227XHnn32WXR3dwMAurq60N7ejueee04TZFNTU/j973+PT37yk8V5ITUIE2g1SLl70ABvLp5+yPSqVauwfft2rY9NRQ0AURSlKoQZgGzPiO4iig8GtO/VpEZuRqQB0HpWDOKM52bFmZ17JpsuxMzumMvyRs6D22GFH/1nfiNMzl6sW4k1twEhdqi9ZzQ3zar/jIaTSNM7a2YXrdjljWbsXDQv7pm2zmSyoLJZLpbMX+i7cNHITECTKs70z1G340GkmW/E0PrMHIdTZxdyXobBmOPoxRkhBCMjI+jp6cH8+fOxe/du1NXVUddLpVJ44IEH8NBDD+HjH/847rvvPkuHrdzcfPPNePzxx/E///M/aG5u1nrEWlpaUF+frRL5x3/8Ryxfvhxf/vKXAQC33XYb3vGOd+DBBx/Eu9/9bvznf/4nDh8+jO9+97sAsjf+b7/9dnzxi1/EunXr0NXVhXvuuQfLli3Dvn37yvNCqxAm0GqQYDAIWZahKErZaqTVJEc7kskkotEoRkdHsWLFCuzduzcnCalahZnh2xmXkCgkK8wUAqhfA4YSR1WcEUkCZ5XAmBFnBVh6xsnw2guYyQBmE4Q3XWSb3TMalT4kl3IhrIo1eV7+ISNu5na5LXm0mh8WiGdch3S4LXW0PY60BM6inFPvojm5Z7Y4uGh8jC7o3Lpommtm0YuWNwkXM9hsyiDNIo2I0uzfv0Wcvh6W3MhgzGJ2zRKJBI4fP45EIoGLL74Yixcvpq5HCMHLL7+MW2+9FfX19fjf//1fXHHFFRXnmun5zne+AwC48sorDY//4Ac/wEc+8hEAwODgoOFacPfu3Xj88cfx2c9+Fp/5zGewbt06/PznPzcEixw4cACJRAIf//jHMTExgT179uBXv/qVpahleIfNQasB0mlj6ZqiKHjmmWdw1VVXWUa/FptXX30VixYtQkdHR85z6XQavb29GBoaQnt7O9auXYuGBqNrUQvCDND1mhFFi9IHsg6a2tDP6cWV7k3WINACAWM4iNkhMws0KwdNLcUyP28WZwBdoJlvCFAEWkEOmt8flC7fH+V59dYOGkW0WAk0q/RGaV7Y0kGzEmicKENupLtoVr1pckPQ1kHjp0Uo9dZCzkqgAXAUaGYXjU+k6SEgFnP1csSZ6dzKOa9M3+aUNBZyLqnnDUWYEScRZDU3DdBEGrFKYaVs21GUWazHYFQbZmGmKAoGBgbQ39+P5cuXY+3atZbBZePj47jnnnvwxBNP4J577sH+/ftzKnkYDA+wOWiMrB2tF+I8z4PneYiiWDaBRitxFEURAwMDGBgYwIIFC9Dd3Z1TNlCVwgywjtJXZxep4owo2ZRGkzgjsgxO92GhF2ckIxrFg1dxJkrZf4Uyh/rPvCJMTQMKoMwz3T10GRBii6IgMDENucn7nUkhkbEUaTQKLW/k0iJI2CIZMiODS2YAh1AQANrIBWqPGcVF4yeTjueXnYtG7TcrxEWzccw4jncWabMLzyYyqvPOnHrHiGJIY8zpRdPDhBmjRjCLs4mJCRw9ehQcx+Gyyy7LmZuqoigKfvazn+HAgQPYvHkzjhw5grVr15bikBk1DhNoNUq5g0L0JY7mIdM7duxAa2urYfk5P8vMCpdR+tqFlD4UheNmhZpJnOnvsHNeyxfNYSHmWGE36Y1uyhvdUpmhj1TUuVs5Qs0FVu6ZihBP+SLS7JId+WQGSoOF6zYtav/TXDQ+mRUQdiINACDKVJHmJtHREwpxLKH1PQgk7m57tiLNVOqoCTOL5/Xo55wZ9mfuRWPCjFEjmIWZKIqIRqMYHh7G6tWr0dnZadnqMTg4iDvuuAOHDx/Ggw8+iA996EMVF53PqF6YQKsBzA4aUH6BFgwGkclkcOrUKdsh00CVROabcRBmQG60PgRh9sJMJ4A0cTYj1ojuei5HnOnEFUlntD4WANm+sjJ/+PgZkV5STNe7mlBrpAyhdtF/ZoVZpNmVNxrW8+Ck2Yk0bRmHUsdC0A8sB5xdNG2EA8VZs4OLJWZ2aCPi3LpoSRc9Zh4gaYdEVYpIsxJnxoWYMGPUDuYQkLNnz+L48eNoampCd3d3TuuEiiRJeOSRR3Dffffhfe97H44ePYpFixaV6rAZDABMoNUs5UxyJIRgenoaZ8+exdjYWHUOmbbChTADZuP11a8BUMUZAE2YZZ+zdyBImtL/Y75Dr8dhewDo/WdumIMBIV5R497l5vwDRXK2WYCT5tahciPSzMvroblonH4ZGxfNC4b5ejRMLppa5qiJs0IxCzO7oA8TZheNpNLezjkP+wLYEGpG7XD7//cRyLKM3/72t2hubkZ9fT3GxsaQSCSwfv16LF26lBrsQQjB66+/jk996lOYnJzEz372M1x99dUVHQLCqF6YQKsBaG8u5RhWrR8ynUwmUV9fj927d1OHTCuKAkVR8L55Hy3pMRYd8x1sU5S+PrFR/72GwBsi8TnzXDT9ptX+NFWAmZ83z0Fzg4fh1AbMzkaCHmVO/SC0EXKkuTTzyfJB75TlLdQs3DY1ft62lJB2TMkMiIXw4tKm+WU6kaaWNxqeL9RFo4g0LkkfkE5z0bipZO7NChcuWo44cyqFpLloPjlmJJUGVxfOijPAPkKfBs9lUxxtnDHt/YXNNmNUOapjRghBKpVCLBbD0NAQRkdHIQgCZFlGNBrFmTNnMDo6ijNnzuDyyy/Hhg0bkEql8K//+q/493//d9x6662455570NjYWOZXxKhlmECrUUpd4mgeMh0KhXDq1CmDOKu2IdO22CU26r43NPsLgrU400HU36vXUjq/ygtp5Vlu7kB6FGeArofIYvuVJuCE2DSgECjNRgfMqf+MBicp4KQ0tYzSdj0bkeYVmnDT9qNz0bikh2h9Sc7/RgANvQCL258vrog7zFnz6myZez5diDRiDu2hiC/LYBD9ew8Ta4wqQV/OyHEcJElCf38/RFHEpZdeigULFkAURcTjccRiMbz88st49NFHMTAwgGAwiMbGRvA8j09/+tP467/+awhuqkd84KWXXsIDDzyAV199FSMjI3jyySdtZ4l95CMfwQ9/+MOcxy+++GK89dZbAIDPfe5z+PznP294fv369Th+/Li/B88oKkyg1SilEmj6IdOdnZ3akOlz585pJZZVm8xohVWZo/5iieNzxZl+efMMJME4J4nav0ZZ3xa7D6jpmdIy2oWumw+2EpWMWIVA+CrcvFzjzlw0q5HwZqGWD3zCKNLclAm6FWla6aLN74tLiSBh+vlkduVy0LloXFInVCgiTe+iaQPRZcW9i6YP8DC7Ym5cNH0yo9PyNiJNmXbhvtmItBxxZliPdy5lZKKMUUWYQ0BkWUZvby9OnTqFzs5OdHV1aWIrGAyitbUVra2tuOWWW/CBD3wA//zP/4zDhw+ju7sbbW1teOmll/Dwww8jFoth48aN2L59O6655hr8wz/8Q1GOP5FIYOvWrbjxxhtx/fXXOy7/0EMP4f7779e+lyQJW7duxd/93d8Zlrvkkkvw61//WvveanwAo3Jhv7EagFY2FgwGkUz6nGCmw2nItFpiqSgKZFmuvlJGGi77z6wGVWsXVhxvvEgTLJZ3CUmlwTXklt6RlLG/hxMEIB9RX4H1+2bhliPYfOg/cwMfSxVFpLlBL9LshBSXlkDq8i9l5KazIo9YDU6HSZw5bS/u0HdGI5Yo7Dykxea7SInMWcWNOFMxiTRbYQaXPWZMnDGqCLM4O3/+PI4fP45QKISdO3eiqamJup6iKHj88cdx9913Y/fu3XjuuefQ2dmpPU8IweDgII4cOYIjR45gbGysaK/huuuuw3XXXed6+ZaWFrS0tGjf//znP8f4+Dg++lHjNVQgEEB7e7tvx8koPUyg1SjFCglJp9Po6+vDqVOn0N7eVTQjsgAAIABJREFUjj179lCHTAuCgEwmg79u/Effj6EioYgzILcMyeykcYKQ46wZcBNnrwo29feti+fXjsMcHuLmwjNf96wCyRFsTYWFenhJauRjKUBRQBpNQs1jiSqfSIOEbN7SKc6aWyeNS4lUkcalssKOS0uWLpq2bEakizQrx4/mok0lckNpnFy0hMWNKDcums08M0d0LponYabDSZQBTJgxag+zMMtkMjhx4gTOnz+PtWvXYsWKFZbBHtFoFLfddhuOHz+ORx55BH/7t3+bsyzHcejs7ERnZyfe+973Fu11+MH3vvc9XH311QaBCQCRSATLli1DXV0duru78eUvfxkdHR1lOkpGPjCBVgNYOWh+ljh6HTL990v+L9/2XdFYCLPcxehJjp63RQiITnhzgjArzKxwIaq8unL2G6O5ht77z2zXLRC9YCt6H9uMEFMTCXOEGgWrnjUuIwGSDNLg3k3jkhlAKPxnSBNpqntmv/8Z8RJ06dIpsjuRBhjFmdfB027EmYOLlo8wIxkxZ5ah5bKsnJFRQ5iFGSEEw8PD6OnpQVtbG7q7u1FXR3//zGQy+OY3v4n7778fH/rQh/Czn/0sZ97qXGN4eBi//OUv8fjjjxse37lzJw4ePIj169djZGQEn//85/H2t78db775Zs51GaNyYQKtRvErxbGmh0y7gZLaSF+M5Ig0w8UXxwMwXoyZQ0Pydr3M5Bt/TxNxFVje6BVbsZZH/5nj/hIpVyKNijQzuDyZdi3SuBkhQOpznTQurRP7Fi6aFyxdNCv0LprX5MS4i7JGKxfNi3NmEmmKlWPnASdxxoQZo9Ywi7NEIoFjx44hmUzikksuweLFi6nrEUJw+PBh3HLLLZAkCU8//TT27t1bFdH5P/zhDzF//vycUBF9yeSWLVuwc+dOdHZ24oknnsDHPvaxUh8mI0+YQKsBiuGgKYqC06dPIxqNIhQK1daQ6Xxw4X5p0fpmgeQi8ZG6SzeuV77OWBV8uFli039WKmeNS6QAWQHJY96Ztg29SHMTHDKdoYo0wzI6kaaWNxqe17loVu6ZXqRxetElitYumlmcObloVmLOwUUjM325nEvn20wh4swXxwxg4oxRVZiFmaIo6O/vx8DAAJYvX45t27ZZBmBMTU3hC1/4Ag4ePIgDBw7g7rvvNvTCz2UIIfj+97+PD3/4wwiF7N+358+fj4suugjRaLRER8fwAybQapR8e9AIIThz5gx6enoAoLaGTBeCXR8Z9E/lKc5M61GXydM987W8kUaFlTe6hYslNVeMNM/Oy/HSf2bJjDPKxVP+iTQ3y+tEmt49Myzj4KS56UfzhORxwLJenNEEmfmxme9JAaFJTJgxGP5jFmfj4+M4duwYOI7Djh07DGEZeggheOqpp3DnnXeiq6sLhw8fxsUXX1yKQy4ZL774IqLRqCtHLB6Po7e3Fx/+8IdLcGQMv2ACrQawctBkWYaiKDmDomkQQnDhwgX09PQgnU5j7dq1WL58ueWQ6ZqYZVYEDEOrzdH72QdzLtY4njNXP9JnIOWIPw7I2RblXKg3CjQyncq96KWtZyG8uPrCAjgqEXX4sV6oucKFmFNTC1WhZjkzzULIcMk0iMVYBc6FOKCuN5UAbO7aclMzw6AtHDEuI9J7I2kumiq4zLPRaC5aLJ7rCrvoPTOLM0IU1y5a3gEgfgkzgIkzRlVhFmaiKCISiWBkZARr1qxBR0eH5XXLyMgI7rrrLrz44ou4//77cdNNN7m6xikX8Xjc4Gz19/fjyJEjaGtrQ0dHB+6++26cPn0ajz32mGG9733ve9i5cyc2bdqUs8277roL73nPe9DZ2Ynh4WH8y7/8CwRBwAc/+MGivx6GfzCBVqMEZy6CRFF0tPzNQ6Y7OjpyhjjW3CyzfCkgNCTfmH4ArhwpqjjDjCAzLFiYa0VcXNBSL44bK0zYUUQwF0vMlkg2Ndgu6xUunsqKEspIBFtEEZwogrhcTytN9OOixq5s0WogtX4dp74zaqmj7Fy6qxNtVuejk0gruzBjooxRhejFmVqxc+LECTQ3N6O7uzsnFVpFlmUcPHgQ9957L/7yL/8Sb731FpYuXVqqw86bw4cP46qrrtK+379/PwDghhtuwMGDBzEyMoLBwUHDOpOTk/jpT3+Khx56iLrNoaEhfPCDH8SFCxewaNEi7NmzB7/73e+waNGi4r0Qhu9wxP28n9IMBmIUhUwmA/Pv+plnnsHu3bstZ4WYh0x3dXVpwk6FCbMCKUB0FSTOKCLLSqA5ruvBPXO3+TyEQZNP/WBe5p9ZiS7zNpoarJe1ctBkyuOK7qKdJrasSgF1vaZmkWbpoIkiYHfjJjMj4mguWpoy08ws0lIzy9AEmn55s0CjLa8KNL0L5qbEl+PyvlnAxBmD4S9m12x6ehrHjx/H5OQk1q9fT22lUDl27BhuvfVWnDp1Ct/61rfwnve8pypCQBhVjeMJyhy0GsYqKMRpyDTAhFnB2IgQankiZEMvGFWc0Si2OKsU4jMX5+bX69VtKhSawIsns483uhSRNHFmJjltfG0u+7S45LQm0hzLG9NpukjLZIxfOzSo55DSCTg7F402A8xqeXP/GM1F07tmqvAr5qBp/a6ZMGMwqNBCQE6dOoXe3l4sWbIEu3fvtgzBSKVS+NrXvoZvfOMbuOmmm/DLX/4S8+bNK8VhMxhFhwm0GoHjuBwHzSzQ3A6ZZsKsQPJMiFMv4DieA7G8ljM9MbMvzqIHqeqhlciVWrSp6IMkGhs8D6LOQX1tdq+HcgNGS060SD4zYCXS9OhFGs09U4/DS6mjKuLcBNQkZvrdzDcPLEodif6ccJhjBsyWOnoVZ2yeGYNhj1mcTU1N4ejRo5BlGdu2bUNbWxt1PUIIfvOb3+DWW29FOBzG888/j507dzLXjFFV1OhVGwOYTXKUJEmLrVWHPdKGTAM1OsvMb+wuthzEm2vnzLQtMuNGWK2f4/vQSipp86sqobzRK8np3JJDryWSXnrKaK5aYsZVcysWFYsLeEkGpuLeRackZ//VUcSXWdTpRVrGYvC0KtJECbC6GSCK1u6glTNGE1n6Zc39kQ6QRDL3/HQh0orlnDHXjFGLmIWZLMvo7e3FqVOntHYKc5+7yvj4OO655x488cQT+OxnP4s777wzp/WCwagGmECrEWh3lgRBwOjoKI4dO2Y5ZBpgkfklxeZizFPcvdueNQ9QLzZpsfzlmjNTyOuLm0rk8gkk8dK/pmJ2wdyUN7rZjltSabpIM6M6Y6IEWA2ajidml7ESaZLk7NylLFw4w3bkXCFJS2vUCTzNOaMtZyHSiJtj0S/vMhWTCTNGrfLVVz+D4eFhzJs3Dw0NDbhw4QKOHz+Ouro67Ny507InXlEUPPnkk/j0pz+NzZs348iRI1i7dm2Jj57BKB1MoNUgiqJgeHgYY2NjCAQCbMj0XIDjLXrT1Kc5w7K2z7vYlyus3Lh02iDSSDoNrt44y4uk0uDcCINykdA5JsVIjzSLOVU8FCpu9b1pbgfR60Wa3TpqT1hGtBZpdqRn3DcrkSbJ9Oh9iotGUlnnLOemBUV8kXgi1+l1E71PGydRIEyYMWqVx04/jFgshlgshqGhIcRiMSgzZd7z589He3u7VtFjHjw9ODiI/fv3449//CMefPBBfOhDH6ro6HwGww+YQKsR1B60M2fOIBKJgBCCtrY2NDQ05ESvqsKMEIL3zftomY6YoeFCMBnFW+5FIMe7/FP3qcSQmHqRaFH9ZpFWkvJGwHvkfcJU3uZFsHl11dSwC4soaQNWwSDJ6ayosRLAtPVSaUDw8PM3izSzc2Tnollu0ybeX++EpRzKGqkOmeI8NmDGRTOcqy6EHOBTKSPAxBmj6tCXM7a0tIAQgtOnT6OnpwcLFizAokWLkEqlcPbsWfT29uLxxx/HoUOHsGHDBmzatAnJZBI/+tGP8L73vQ9Hjx5lUfGMmoHF7NcI58+fxxtvvIF0Oo01a9ZgxYoV6OvrQzKZxJYtWwAYh0wrioLrW24s81EzcvBJxJgdNc2JKNA9c7dzd+vyXgZaezmeAmeSEd1FNKcXUrT3Uqv3V9rjtIv4hgb7/jMa+u3QRJpd4qOdSKOlKqoizUqgqCItTeldM7to+v42KzElCDkCjVr6q8040y3rol/SfGPBajlteZbOyGBYYu41i8fjOHbsGFKpFDZs2EC9OTw0NITf/OY3OHToEP74xz+iv78fyWQSK1aswPbt27Ft2zZs374d27dvR2dnZ1GDQV566SU88MADePXVVzEyMoInn3wS+/bts1z+hRdeMMw0UxkZGUF7e7v2/be//W088MADGB0dxdatW/HNb34TV1xxRVFeA6NiYTH7jCwcx6G9vR2dnZ1a820gEIAkSYZkRkVRwHEceJ7PeXMFwAJCyg3tQs6jaKOVO85eRNIvJrmAzi0psJfNLXbBDJ7Em2Gj/t5nIrp4d87tMXlx1ZIzYSKmElHXuO0xA7LlhRKAMCXSmibOgP+fvTOPa+rM9/8nBAgQdkFki4DIvgRQUOmvLrV12s5te53paO+dK9bWaTvXFa1W664VXGpVcKFWRWem4lKL09raVlqrVeuFBASBIKsIEkRkSYAsJOf3B80pJxsgiyzP+/Xi1XJynpPnkJic9/k+z+cxLGad2xlKq+w81FE7fMRAxUtf9YxSqXQkjWpt614VrXP0viE509qP3kQCQAgEveiLztcEkWlES3sYI9BxnTJq1CjcuXMHp0+fxuLFi7FhwwYolUrcvn0b2dnZyM7ORnp6OgoKCvDyyy/jwoUL/XYeLS0tCA8Px4IFCzB79uxutysqKmLE/Y8ePZr+/9OnTyM+Ph6HDx9GTEwM9u7di1mzZqGoqIixH4FAKmgjBLVarbPmWXV1Ne7fv48JEybQYqb50YaiKIjFYpSWlsLExAS+vr5wdnYGi8Ui0jZY6YegEH3H7VGEfz/HIJt0tdZYH1bPjMGytOxZ9QzQX0HT3lcjat2pnmljwTFePdOe/9VZ1AwJmqadseAPhdLwgtSAYYHTkilKU4Uz8B7uLGl05UxvoqjWcQ0lU+p9EhaJzScQjKAtZ48fP0ZhYSHYbDaCgoIMrlNGURR+/PFHLF26FE5OTjh8+DAiIyMNPo9MJsPjx4/h5ubWp/03BIvF6nYFraGhAfb29nr3iYmJwcSJE5GcnAyg49rM09MTixcvxgcffNAvfScMSkgFjaCLpmLG4XDQ2NiIa9euwdbWlvGjWRiSoijU19ejpKQECoUC48aNg6urK2OCLqm0DVL0XARSqh6mQWqjR/ooIxfvA73+mrqlVWdbl9LWD1BtHVH+rO6mKnZ3jlKb7MmqaWp1x9w0Q4tK6wvnkCs6JK2lzXAoiKadIUnTyIyhGH10vH/0vk86VbyozkMku4jF73IOWefj9kTOQKpmBIIhtK8DlEoliouLIRaL4ePjAx6PZzDYo66uDmvXrsVXX32FLVu2YNGiRXorbJ2xsLAYMDnrKXw+H3K5HCEhIdi0aRNiY2MBAAqFAgKBAGvWrKH3NTExwcyZM3Hz5s2n1V3CIIUI2ghBExLSeZ6ZnZ0dpk2bBolEgubmZjQ3N+PBgwdoa2uDhYUFLC0tIZPJoFAo4OXlxRge2RVE2gYvjIvITsLVZXXtCea/GZW3J0kCfAK0pe2Jh0c+AZ0XRWZZGamq9YQ2WcewPosnEDWNkBgSNW00YtSd5MauKml6JE0jXsYkTe97SI+kUSqV/iGX+oYnyuQ9Gqpr7H1MP3eXByFiRhh+aH/Xa8LIioqKYGNjg8mTJ8PSwGeuWq3GqVOnsGbNGkyaNAm5ubnw8vIagF73D66urjh8+DAmTJgAuVyOzz77DNOmTcOtW7cQGRmJR48eQaVSwcXFhdHOxcUFIpHoKfWaMFghgjZCyM7ORm1tLcLCwmBjYwM2m03PNXN0dISjoyO9b0NDA4qLi9HY2AgrKyuYmZmhtLSUXrtE82NjY9OjBSKJtA0ytITLUIw/y4TVZ+EkjOczUI3ob3HTN7etO9LW3eGNHU+i+7ekWttoQetWZc2AzGlkgI6a14had6twwO8LS6Nj8WaWvnlnAHNIpLak6au6MeaV6Xl9O0kapRUcok/S6HXI9N0Y0pY0Y9WtHqx9ptO0t3JGxIwwTNH+Tm9ra0NhYSEkEgn8/f3h4uJiMMSjtLQUS5cuRWFhIQ4ePIg///nPQz4639/fH/7+/vTvU6ZMQWlpKT755BP84x//eIo9IwxFiKCNEK5fv46dO3eiuroavr6+dApSZGQk+Hw+uFwuSkpKsH79egDApk2bEB4eDs5v6zIpFAq60tbU1IT79+9DJpPByspKR9q6GprQGSJtT4keCFeHuOmJ7u/NUEljz6fnQnugpa1fqmydhEtTWWNZWfZMrPQdViNqhm6WGJrjpVDQ8kHJFYYljdHmt9fG2OvR3m58rt+TDHfUsxYagN8lqzvzwvTtY0TS+qRqRiAMQ/SFgFRWVqKsrAxjxoxBaGiowZu3CoUCSUlJSExMxF//+ld88cUXcHBwGIhuPxWio6Pxyy+/AACcnJzAZrNRW1vL2Ke2tpaR8kggACQkZERBURRqamqQlZWFrKwsCAQCCAQCPHz4EC4uLnj8+DGioqLw7rvv4qWXXoKlpaXRCFuFQkEPjdT8yOVycLlcHWnr7tBIQxBp62f6Kr6/n6RN73MN0BBJ+vm6m4ZoSE4Mfdb+JlDai3nr29+gFHR6Th3RMiBo+gSE0dZIoAjV3m7076+RIZaBmzWUQqFfuDT9MDP9vXrWGT1tKIUCrG7ceTcqXNrDJUnVjEDQi7acNTU1obCwECqVCkFBQQZli6IoZGVlYfHixVAoFEhJScGzzz7brzH5fUl3QkL08fzzz8PGxgbnz58H0BESEh0djaSkJAAdcsvj8bBo0SISEjKy6PKNTwRtBCOVSrFnzx7s2rUL48ePR3R0NCoqKiAQCNDQ0ICgoCBGpS0kJAQcDsfoB6pcLteRNoVCAWtra4a0WVtbE2kbChBx0/8cFhxQbTJdqQJ6Jmh65IlladHl8MbuPCeLYw6qtc2gWBqdH8gx71LQAP1/a+1KlbakMYI5DL0v2tsNJ352TmvsdCxjktaVcAEA1a4Ey9zc6L5EzAgjFW0xa29vR2lpKaqqquDl5QVvb2+DQxQlEgm2bNmC48eP4/3338eaNWtg8SRzaAcYqVSKkpISAEBERAT27NmD6dOnw9HRETweD2vWrEF1dTVOnjwJANi7dy+8vb0RHBwMmUyGzz77DElJSfj+++/x3HPPAeiI2Y+Li0NKSgqio6Oxd+9enDlzBiKRSGduGmFYQ1IcCfo5ePAgNm/ejHHjxuHrr7/G1KlT6cc0wxUyMzORlZWFr7/+Glu2bIFUKqWlLTIyEpGRkQgODoaZmRktbRwOB87OzvQClBRFMaStrq4OpaWlaG9v11tp68kYdDI8cgDog3XXAMMXtv0hbgMxRFJT3TEoaToNun9/i2qT/T5X7UnXP0OnAI7f+tpZ1IwKi0rVIXYGgkSoTnPPKIWyy78t1d5usJKmd+ii5vj65o11aqOdwEip1XoljVIouv2eNbYvkTPCSETf92xdXR1EIhEsLCwwadIkcLlcvW0pisI333yDFStWYOzYscjKykJQUFB/d7nPyMrKYiw8HR8fDwCIi4tDamoqampqUFlZST+uUCiwYsUKVFdXw8rKCmFhYbh8+TLjGHPmzEFdXR02bNgAsVgMPp+PS5cuETkj6EAqaCOU9evXY8KECXjllVe6NcRArVajrKyMljaBQICcnBzIZDKEhIQwpC0gIACmpqYGj0tRFGQymU6lTaVS6a209WbiMBG2AaIPQ0QGotrWa2Ez8rnJ4uipWHWzemZoX5alxe/x8dp9N1SxMyTFFhzDgqanjbaoUfrCQdDxNzUWQ88yNTUca695zfUdW9+6jEYqbCxDEfraoTjtmmGYZvT/69ufiBlhpKItZ3K5HEVFRaivr8f48ePh7u5u8HteLBZj5cqV+Omnn5CQkICFCxf2etQMgTCMIEMcCf2HSqVCcXExLW1CoRA5OTlQqVQICwtjDI/08/MzGh5CURTa2trQ3NzMiP1Xq9U60sblcp9Y2hoaGjDfc9mTnjKhJwxnaevm5yaLwwEl/30uFUN2eiBoBjE367Gg0cfX9+/RkNRpEh8NyBndzsjrRCmVRl9Hqr3d8OOdLgIZfTB0c8lQPzXSpU/ItPvTnUXNiZwRhiH6ovOrqqpQUlKCUaNGwd/fnw4Q00alUuHEiRNYv349Zs6ciX379g3a9coIhKcIETTCwNLe3g6RSEQHkWikjc1mIzw8HHw+n5Y2X19fo3fUKIpCa2srLWsacaMoCjY2NjrSZqwSqBlL/vjxY3h5eYHH4zGEkVTaBog+juvvb3HTK219sZYZDARo9PDYlCZgRHs4orGqj/ZzaPphpI2miqQ3KVK7nb4gD6XWvDR9+2jmtRl4TY1Wsjr/2zckZ10do/N+XckZETPCMEVbzqRSKQoKCiCXyxEYGAgnJyeDbQsLC7F06VJUVlYiKSmp2yN0CIQRCBE0wtOFoigolUoUFBRAIBAgMzMTQqEQubm54HA44PP54PP59PBIYxONNcfrLG2aHwAMYbO1tYWVlRXkcjnKyspQU1MDd3d3+Pj4wLybi/QSaRtAhki1jWVu1jeCpiUAtAg+oaD9fpzf3ttdVc+0MTU12Eaf1NCiZkx4Ood5KPXMC+z8uJZUab+GjCGZemLxKeVvqZK9lDMiZoSRiraYqVQqlJeX4969e/D09MS4ceMM3lCVyWT4+OOP8cknn+Dtt9/Gtm3bYGtrOxDdJhCGKkTQCIMPiqKgUCiQl5fHiPu/c+cOuFwuY2hkZGQkPD09u5S2lpYWhrBJJBJQFAWKomBlZQUPDw84OTnBysqqV3f0iLQNIENA2vSu2dUV3Rg6153jasvZ7w/8FjCiXaEz8llPV8j0VPUMBryYmRmvuinbf5vvZmA4oUrdMW/N0Jy2314zvfPlfpM0vUsF6BE4tbJd73a6r2Q4I2EEs/Lbt+mgLhsbG6hUKpSUlMDU1BRBQUEGZYuiKFy/fh1LliwBh8NBSkoKYmJiSNWMQOgaImiEoYEmOOT27du0tAmFQuTn58PBwQERERGMSpubm5teaZPJZMjPz0dzczMsLS3h5OQEpVJJSxubzdaptFlYWBBpGyoM8tj/bglbd2SgG8fsStDo9hrp6kF0v6aN0aqTSm2wfzrixNZ63VRafdeWp87Pa+Q1NyiPvx1P3Q2Bo7p6LiJmhGHKBekJKBQKSCQSSCQSNDU14fHjx2hvbwebzYa9vT09neDx48fw8/Ojq2gNDQ3YsGEDTp8+jQ8//BArVqzo9ugUAoFABI0whNEMZ8zJyWFU2kQiEZydnRmVtvDwcHzzzTdITEzEhAkTkJycDCcnJ4Z4qdVqSKVSRqVNKpXC1NRUZ04bkbYhxCCWNh156aGcacsBHdbR04ARNWVY9Lo7t6sz2oKF38/VYEKkRtL0tAXwu6Tp64+BBEZ9jzH2MzoXz4h4sUyImBGGLfpCQMRiMYqKimBnZ4fx48ejvb2dnvctFosxe/ZsmJub0+mN169fh7+/P1JTUxEYGDig/b969Sp27doFgUCAmpqaLheQPn/+PA4dOoScnBzI5XIEBwdj06ZNmDVrFr3Ppk2bsHnzZkY7f39/iESifjsPwoiGCBpheEFRFKRSKYRCIS1t165dQ01NDWxsbBAdHY2JEydiwoQJiIiI0JE0bVQqlY60tbS0wNTUVKfS1tUi3V1BpG0AGaTS1qPjdSUIPRjCqDPnzawbFbLObTpXwAwJ1m/H7c6i0EbpQpwMJjB2Nxa/q+cgEIYx2nLW2toKkUgEiUSCgIAAjB49Wu/3nEwmww8//ICjR4+isrISarUaNTU1UCqVCA0NRWRkJH3TNDw8vF8Xov72229x/fp1REVFYfbs2V0K2rJly+Dm5obp06fD3t4ex48fx+7du3Hr1i1EREQA6BC0c+fO4fLly3Q7U1NTo6EoBEIvIIJGGL7k5uZi9erVuHnzJpYuXYqYmBjk5eXRwyNLS0sxduxYxtBIPp8PBweHLqVNc+dQ81+pVApzc3O90tYbiLQNIH0gbb0SNj1SwDI1Eu3fE4kwNTVaPTOIoXlZhtqwTYwKGt1nPX9rbXHSCQLp9Lih+WK9DvogYkYYoWiLmVqtxr1791BWVgZXV1eMHz8eZvpSWtGRzvzpp59iy5YtePXVV/Hxxx9j9OjRUKvVKCkpQXZ2NoRCIbKzs5GdnY1///vfmDx58kCcFlgsVpeCpo/g4GDMmTMHGzZsANAhaOnp6cjJyemPbhII2nQpaE8ww51AePosXboUn376Kd577z3885//xKhRowAAL730EoCOSltDQwOdHCkQCHD8+HFUVFTA29ubEULC5/Nha2tLS5tm7L29vT39fJ2lrbm5GbW1tWhpaQGHw9GRtp6Mw9f+0gSItPUb+i7OeyhteudrdUfaDIhB52oQQ9Z6KBKdF4hmDGXsSlY6n47mPIy00TyP3nPu3GctUdP3d6NUqt+DQLQe10iWRtRIAiOB8ORof880NTWhoKAAFEUhMjISDg4OettRFIU7d+5g0aJFePz4Mc6ePYsXXniB/q40MTGBn58f/Pz8MGfOHLrNYEetVkMikcDR0ZGxvbi4GG5ubrCwsMDkyZORkJAAHo/3lHpJGOmQChphSPL1118jJCQEXl5e3W5DURTq6urooZGaddqqq6vh6+urM6fN2traaKWt8xh9zU9rayssLCx0pM3QncnuQqRtgOiPKtsTikF3q3WGxIRlZmpYtrqaf6WviTE57eIcu6xqdTGPzFgCY7eOTyCMQLTFrL29HSUlJaiuroa3tze8vLwMJiS3trYiISEBhw4dwqJFi7Bx40Zwudyjc37HAAAgAElEQVSB6HaPeJIK2s6dO5GYmAiRSITRo0cD6Bg2KZVK4e/vj5qaGmzevBnV1dW4c+cObGxs+qv7hJELGeJIIBiDoijU1NTQC2trgkjq6urg7+9PS5tmXL2lpaVRaVMqlTrS1tbWBktLS4aw2djYPJG0NTU1obi4GFKpFJ/88XhvTp3QXfpC2roQjG4dw9ACzt2QsO5W57SPZajCpf083V5cWvtvqd0X7TAQ7WGR2gmMpGpGIOigb2TGw4cPIRKJYGVlhcDAQIOyRVEUfvrpJyxZsgSjRo1CSkoKIiIiBm10fk8F7fPPP8fChQtx4cIFzJw50+B+jY2NGDt2LPbs2YO33nqrr7pLIGgggkYg9BSKolBVVYXMzEy6yiYQCNDQ0IDAwEBGpS00NLTL8BBNzH/nH5lMpiNttra2MNWzDhUAtLW1oaSkBA8fPgSPx4OXl5dewSOVtgGil9LWU2HTJyImZqbdkjOd5+6p6BnvmMHjG0+H7Dol8Yn6wzxA79oTCEMQbTmTyWQoKiqiY/Ld3NwMfl89evQIa9aswVdffYXNmzdj8eLFBr+TBgs9EbS0tDQsWLAAZ8+excsvv9zl/hMnTsTMmTORkJDQF10lEDpDBI1A6AvUajUqKytpadMEkUilUgQFBTHmtAUHB8PMzMyotCkUCh1pk8vlsLKy0on7r6qqQmVlJVxcXODr69vjdCwibQNEL6Stt4soM6Srh2LCYrN7Jnqa8+yFAGnPMdP3mJHG+vtj6HECYQSgLzq/qqoKJSUlcHJygr+/v8H50Wq1Gmlpafjggw8QExODAwcO9Gj6wNOku4J26tQpLFiwAGlpaXj11Ve7PK5UKgWPx8OmTZuwZMmSvuougaCBCBqB0F+o1WqUlZUxpC0nJwcymQwhISEMaQsICICpqalRaZPL5Qxha2hogEqlgomJCRwdHTFq1Ch6eCS7l/HvRNoGiO5Km4FK1JNWkXpSoev8HN2dP0epKcNJi3r6TId9GDkflgmLDFkkEJ4AbTmTSCQoLCyEQqFAQECA0aj40tJSLFu2DPn5+di3bx9ef/11g/PSBgtSqRQlJSUAgIiICOzZswfTp0+Ho6MjeDwe1qxZg+rqapw8eRJAx7DGuLg47Nu3D7Nnz6aPY2lpCTs7OwDAypUr8R//8R8YO3YsHjx4gI0bNyInJwcFBQVwdnYe+JMkDHeIoBEIA4lKpUJxcTFjeGROTg5UKhVCQ0Pp4ZFRUVHw8/PTGT6iVquRnp6O0aNHw8TEBF5eXjA1NaUj/5uamtDe3g4ul8uotFlbWxNpGwroE7buSkc/VOi6EqbutumOgPUKImYEgg7aYqZSqVBeXo579+6Bx+PBx8fH4PeCUqlEUlISEhMT8cYbb2DHjh06qYaDlStXrmD69Ok62+Pi4pCamor58+ejoqICV65cAQBMmzYNP//8s8H9AWDu3Lm4evUq6uvr4ezsjGeeeQYfffQRxo0b15+nQhi5EEEjEJ427e3tEIlEdBCJRtpMTEwQHh5OSxsA7Nu3D/fv38e5c+cQExOjcyeToiidSltzczPa29thbW2tI229vRNKpG0Q84TC9iQy1e8CZgwiZwQCA30hIPX19SgsLISZmRmCgoIMJg9SFAWBQIBFixZBoVDg8OHDmDp16qANASEQhilE0IYbBw4cwK5duyAWixEeHo6kpCRER0cb3P/s2bNYv349KioqMH78eOzYsYNeKwzo+LDeuHEjjhw5gsbGRsTGxuLQoUMYP378QJzOiISiKCiVShQUFEAgECAjIwPfffcdmpqaEBISAnt7e4SHh9PDI729vY2KFkVRkMlkOtKmUqlgY2PDkDYul0ukbTjzJEMq+yCl8okxsrA1ETMCQRdtOVMoFLh79y4ePnwIX19feHp6GpQtiUSCrVu34tixY1i5ciXWrl3b4znNBAKhTyCCNpw4ffo05s2bh8OHDyMmJgZ79+7F2bNnUVRURK/l0ZkbN27g2WefRUJCAv74xz/i888/x44dOyAUChESEgIA2LFjBxISEnDixAl4e3tj/fr1yMvLQ0FBAfng7mcaGhqwfft2JCcnY+7cuVi/fj0eP37MiPu/c+cOuFwuIzkyIiICPB6vS2lra2vTkTaKonSkzcrKikjbcOVJxKevhK2fAkYIhJGIvhCQmpoa3L17F/b29ggICDD4nU1RFL799lvEx8eDx+MhJSUFwcHBA9FtAoGgHyJow4mYmBhMnDgRycnJADrmK3l6emLx4sX44IMPdPafM2cOWlpa8PXXX9PbJk2aBD6fj8OHD4OiKLi5uWHFihVYuXIlgI51tlxcXJCamoq5c+cOzImNQEQiEWJjYxEZGYndu3cjPDxcZx9NZSw3N5chbfn5+bC3t2dIW2RkJNzc3LqUttbWVoawSSQSvdLG5XJ7PeSFSNswwZCwGZKsbkToEwiE7qMtZ62trSgsLIRUKkVAQABGjx5t8PNaLBbj/fffx48//oiEhAQsXLiw1/OVCQRCryGCNlxQKBSwsrLCuXPnGHGycXFxaGxsxIULF3Ta8Hg8xMfHY9myZfS2jRs3Ij09Hbdv30ZZWRnGjRuH7Oxs8Pl8ep+pU6eCz+dj3759/XtSIxi1Wo2rV6/2eOy/RrJycnIY0iYSieDs7KwjbS4uLkaPT1EUWlpadKSNxWLprbQRaSMQASMQBgZtMVOr1bh37x7Kysrg5uYGX19fvethavY9ceIE1q1bh+eeew779++Hm5vbQHSbQCB0TZcXU4N7BUICzaNHj6BSqeDi4sLY7uLiApFIpLeNWCzWu79YLKYf12wztA+hfzAxMcG0adN63I7FYoHL5SI2NhaxsbEAOiRLKpVCKBTS0vbFF1+guLgYbm5utLRpxM3JyYkWLRaLBWtra1hbW9Nf3mq1miFt9+/fh0QigYmJiY60WVpa9kja0iWpqKurw927d8Fms5H4/OEe/w0ITxkiZwRCv7M24+8oLCykP3Pb29tRVFQEAIiKioK9vb3BtiKRCEuXLkVFRQWOHz+OV199lYSAEAhDDCJoBMIQR1Ptmjp1KqZOnQqgQ9qampogFAqRmZkJoVCIU6dOoaSkBDweD3w+n66yRUREwMHBgf4C14iYjY0N3N3dAfwubU1NTWhubkZFRQWkUinYbDZD2DSLa+u7GJBIJCgqKoJUKoWvry/c3NxwQTpZZz9SZSMQCCOVdEkqPRRdIpGgpqYGIpEIFEXB3Nwco0aNgkQiAQCw2WxGWqNcLsfHH3+MPXv24K233sLFixdha2v7tE6FQCD0AiJoQwQnJyew2WzU1tYyttfW1mLMmDF624wZM8bo/pr/1tbWwtXVlbFP5yGPhKEHi8WCvb09ZsyYgRkzZgDokLaGhgYIBAJkZmZCIBAgNTUVFRUV8Pb2ZgyN5PP5sLW11SttGtRqNaRSKV1pKy8vh1QqhampKUPYOBwO7t+/j9raWvB4PISHhxsclgPoj5Am0kYgEIYznT/3uFwuuFwu2Gw2xGIx7O3t4e3tjfb2dkgkEtTV1UEgEOB//ud/4OnpicDAQHh6euK7776DtbU1MjIyMGnSpAGtml29ehW7du2CQCBATU0NvvzyS8Z0DH1cuXIF8fHxyM/Ph6enJ9atW4f58+cz9ulpcjWBMFwgc9CGEDExMYiOjkZSUhKAjgtkHo+HRYsWGQwJaW1txVdffUVvmzJlCsLCwhghIStXrsSKFSsAAM3NzRg9ejQJCRkhUBSFuro6emikZp226upq+Pr6MoZGhoeHw9ra2uiXvkqloqWtqakJ9fX1UCgUMDExgZ2dHRwcHGBrawsbG5tep4QSaSMQCMMB7ZtSMpkMIpEIjY2N8PPzg6urq87nrlqtRkVFBX7++Wekp6ejpKQEDQ0NaGpqwrhx4+ibbZpREs7Ozv16Dt9++y2uX7+OqKgozJ49u0tBKy8vR0hICN599128/fbbyMjIwLJly3Dx4kXMmjULQM+TqwmEIQQJCRlOnD59GnFxcUhJSUF0dDT27t2LM2fOQCQSwcXFBfPmzYO7uzsSEhIAdMTsT506FYmJiXj55ZeRlpaG7du368TsJyYmMmL2c3NzScz+CEYT36xZWFsgEEAoFOLhw4fw8/NjSFtYWJhOeIharcY//vEP8Hg8WFlZYdy4cTA1NWUEkbS0tMDc3FxneCSHw+lV34m0EQiEoYK+6Pz79++jpKQEo0ePhp+fH8zNzfW2VavVuHDhAlauXImgoCAcOnQIfn5+qKurQ3Z2NoRCIf1TWlqKy5cv47nnnhuI0wKLxepS0FavXo2LFy/izp079La5c+eisbERly5dAtDz5GoCYQhBQkKGE3PmzEFdXR02bNgAsVgMPp+PS5cu0SEflZWVjJj1KVOm4PPPP8e6deuwdu1ajB8/Hunp6bScAcCqVavQ0tKCv/3tb2hsbMQzzzyDS5cu9Zuc9WS4wpEjR3Dy5En6AzwqKgrbt29n7D9//nycOMH8kps1axb9AU/oOSwWC25ubnjllVfwyiuvAOi4cKiqqqKlLSMjAzt37kRDQwMCAwNpaTM1NcWhQ4fw8OFDfP7554iOjqblrfOkds1QHY2wicVitLa2gsPh6EiboQsUfZDhkQQCYSig/VklkUhQUFAApVKJ8PBwjBo1ymDb+/fvY8WKFfj111+xe/duzJs3j/7ud3Z2xgsvvIAXXniB3r+pqWnQ3XC9efMmZs6cydg2a9YsOnVaoVBAIBBgzZo19OMmJiaYOXMmbt68OaB9JRCeBqSCRhgwejpc4b//+78RGxuLKVOmwMLCAjt27MCXX36J/Px8Orxi/vz5qK2txfHjx+l2HA4HDg4OA3ZeIxW1Wo3KykpkZmYiIyMDX375Jerr6xEYGAgzMzOEh4fTQ2yCgoJgbm5udHikUqlkSFtzczPa2tpgYWGhI23G5rB1ByJtBALhaaAtZiqVCmVlZaisrASPx4OPj4/Bdcra29vx6aefYsuWLXjllVewZ8+eQTnUrzsVND8/P7z55psMAfvmm2/w8ssvo7W1FQ0NDXB3d8eNGzcwefLvYVKrVq3Czz//jFu3bvXrORAI/QypoBEGD3v27MHChQvx5ptvAgAOHz6Mixcv4tixY3qHK/zrX/9i/P7ZZ5/hiy++QEZGBubNm0dv53A4BoNSCP2HiYkJRo0ahezsbJw8eRJ/+ctfsHXrVsjlcmRmZiIrKwtffPEF1q9fD5lMhpCQEHpoZEREBAIDA2FqakpLm5mZGRwdHeHo6Eg/h1KpZAhbdXU12traYGlpyRA2GxubHkkbqbQRCISBRN9nTn19PQoLC2Fubo7o6GhGCJM2eXl5WLx4MR49eoQzZ85g1qxZJDqfQBjGEEEjDAh9MVyhtbUVSqWScQEPdCRBjR49Gg4ODpgxYwa2bdtmdHgIoW94+PAhwsLC4Ofnh2vXriEqKop+zNfXF2+88QaAjjvExcXFtLSdOnUKq1atgkqlQmhoKD08MioqCn5+fjA1/f1jyczMDKNGjWK8ngqFgq60NTU14f79+5DJZLCystKRts7H6goibQQCoT/Q/mxRKBS4e/cu6urq4OvrCw8PD4Oy1draisTERBw8eBD/+7//i40bN8La2nogut2vGEqZ1qyvyWaze5xcTSAMJ4igEQaEJ1loW5vVq1fDzc2NMW79D3/4A2bPng1vb2+UlpZi7dq1ePHFF3Hz5k2Dw0QIfcPo0aNx7tw5xMbGGr2Ty2azERAQgICAAPzP//wPgA5pE4lEtLSdOHECy5cvh4mJCcLDwxlBJL6+vozXUrMWkLa0aapsDQ0NuHfvHuRyObhcro609eR9QaSNQCA8KfpCQB48eIDi4mI4ODhg8uTJBueGURSFK1euYMmSJXBwcMC1a9cQGRk5bKpmkydPxjfffMPY9sMPP9DDGc3NzREVFYWMjAx6qKRarUZGRgYWLVo04P0lEAYaImiEIUFiYiLS0tJw5coVxhda56UAQkNDERYWhnHjxuHKlSsDllg1knnmmWeeqB2bzUZwcDCCg4Mxf/58UBQFpVKJwsJCZGVlITMzEykpKcjNzQWHwwGfzwefz6elzcfHhxGIY25uDicnJzg5OdHb5HI5LW319fUoLy+HQqGAtbU1Q9qsra17LG0KhQKlpaV48OABPD098X7kR0/0dyAQCMMTbTlraWlBYWEhWltbERQUZHTu2KNHj/Dhhx8iPT0dmzdvxpIlS3o0GuBpIJVKUVJSQv9eXl6OnJwcODo6gsfjYc2aNaiursbJkycBAO+++y6Sk5OxatUqLFiwAD/++CPOnDmDixcv0seIj49HXFwcJkyYQCdXt7S00NMkCIThzOD+F08YNjzJQtsadu/ejcTERFy+fBlhYWFG9/Xx8YGTkxNKSkqIoA0hWCwWzM3NER4ejvDwcLz11lugKAoKhQJ5eXl03P/+/ftx584dcLlcREREgM/n00EkPB6PIW0cDgfOzs70+j8URTGkra6uDqWlpWhvb9dbaet8LA1qtRpVVVUoLS2Fvb09Jk2aBC6XSyptBAIBgK6YadYrKy8vh7u7O/h8vkHZUqvVOH36ND744ANMnDgRubm58Pb2Hohu95qsrCxMnz6d/j0+Ph4AEBcXh9TUVNTU1KCyspJ+3NvbGxcvXsTy5cuxb98+eHh44LPPPqPXQAO6Tq4mEIYzJMWRMGD0dKFtANi5cyc++ugjfPfdd5g0aVKXz1FVVQUej4f09HQ6Ip4wfKAoCjKZDLm5ubS0CQQC5Ofnw97enjE0MjIyEm5ubnpFS/t4nYNImpuboVKpdCptcrkcxcXFADoSyDpX67oLkTYCYXii7yZNY2MjCgoKwGKxEBQUBDs7O4Pty8rKsGzZMty5cwd79+7FX/7yF6OfXQQCYUhDFqomDB56utD2jh07sGHDBnz++eeIjY2lj2NtbQ1ra2tIpVJs3rwZf/rTnzBmzBiUlpZi1apVkEgkyMvL6/Wix4ShAUVRaG1tRU5ODkPaRCIRnJ2dGdIWERGBMWPGGJ3HQVEU2traaFlrbGxEc3MzKIqChYUFRo0aBTs7O9ja2oLL5fb6IopIG4EwtNGWM6VSiZKSEjx48AA+Pj4YO3aswc8JpVKJ5ORkJCQk4I033sCOHTt0grAIXePh4YG1a9fi73//O73txo0bmDlzJgoLCzF27Nin2DsCQQciaITBRXJyMr1QNZ/Px/79+xETEwMAmDZtGry8vJCamgoA8PLywr1793SOsXHjRmzatAltbW147bXXkJ2djcbGRri5ueGFF17A1q1byRCIEQ5FUZBKpRAKhQxpKy4uhqurq460OTs760hbfX09fvrpJzg4OMDV1RVubm4McZNIJKAoCjY2NoxKG5fL7fVEfiJtBMLgR18IyMOHDyESiWBtbY3AwEBYWVnpbUtRFIRCIRYtWgSZTIaUlBRMnTp12ISADDR/+tOfYGtrS6+JSlEUYmJi8Pzzz+Ojj8gcYcKggwgagdCXHDhwgBbM8PBwJCUlITo6Wu++qampOpOZORwOZDIZ/TtFUdi4cSOOHDmCxsZGxMbG4tChQxg/fny/nsdIhKIoNDU1QSgUIjMzE0KhEEKhECUlJeDxePR8trCwMOTk5GD//v3g8/lIS0vTuz6RpnKnPTySxWLpSJuVlRWRNgJhGKEtZ21tbRCJRGhqaoK/v7/RSr1EIsG2bdtw9OhRrFixAh9++KHBNEdC99i1axdOnDiBO3fuAABOnjyJ1atXo7i4eFgsS0AYdhBBIxD6itOnT2PevHk4fPgwYmJisHfvXpw9exZFRUV6E7lSU1OxdOlSFBUV0dtYLBajurdjxw4kJCTgxIkT8Pb2xvr165GXl4eCggLyhT0AUBSFhoYGCAQCZGZm4rvvvsOvv/4KCwsL+Pn5wdPTE1FRUYiMjASfz4etra1R0VKr1TrSJpFIwGKxGMKmWeuHSBuBMLTQVzWrrKxEaWkpXFxcMH78eJibm+ttS1EULl26hPj4eHh4eCAlJQUhISED0e1hz7Vr1zBt2jQ0NTWBxWLB398fmzdvxltvvfW0u0Yg6IMIGoHQV8TExGDixIlITk4G0HEx7unpicWLF+sNOUlNTcWyZcvQ2Nio93gURcHNzQ0rVqzAypUrAQBNTU1wcXFBamoqYwkBQv9SWVmJ1atX4+uvv8aaNWvw17/+Ffn5+cjKykJWVhaEQiGqq6vh6+vLSI/k8/mwtrbuUtpaWlp0pI3NZutIm4WFBZE2AmGQcuzeHtjY2NAC1tzcjMLCQiiVSgQFBRmdOyYWi7Fq1SpcvnwZ27dvxzvvvEPW6uxDWltbYWdnh4yMDFy+fBlfffUVBAIBCVohDFa6/KInMfsEQjdQKBQQCARYs2YNvc3ExAQzZ87EzZs3DbaTSqUYO3Ys1Go1IiMjsX37dgQHBwPoWCdGLBYzFt62s7NDTEwMbt68SQRtgDh37hzi4uLw5z//GUVFRXBzcwMA8Hg8vPjiiwA6ZLqmpoYWtl9++QX79+9HbW0t/P39GXPawsLCGEMaTUxMYGNjAxsbG7i7uwPokDapVEoLW3l5OaRSKUxNTXWGR/ZU2kjkP4HQt+zN20TLWFtbGywsLGBiYoK2tjaMHj0aYWFhsLS01NtWrVbj5MmT+PDDDzFjxgzcuXMHHh4eA3wGwx8rKyuEhobiiy++wJEjR/DNN98QOSMMaYigEQjd4NGjR1CpVDrhIy4uLhCJRHrb+Pv749ixYwgLC0NTUxN2796NKVOmID8/Hx4eHhCLxfQxtI+peYzQ/0ycOBE//vgjHVajDxaLBTc3N7zyyiv08g0URaGqqoqWtoyMDOzcuRMNDQ0IDAxkSFtoaCg4HA5D2jQCpkGlUjGkraysDC0tLTA1NdWptHU+Vncg0kYg9Bx9/27EYjH9me/o6AiJRIJffvkFHA4HV69eRVNTE6KiojB58mTIZDIsXboU5eXlOHbsGF577bWnEgLSk7nT06ZNw88//6yz/aWXXqIXkZ4/fz5OnGD+bWbNmoVLly71fed7wKRJk5CUlIRXX30V06ZNe6p9IRB6CxE0AqGfmDx5MiZPnkz/PmXKFAQGBiIlJQVbt259ij0jdGbs2LFPFMHMYrHg6ekJT09P/Od//ieAjrvllZWVyMzMRFZWFi5evIitW7dCKpUiKCiIIW3BwcEwNzenL9jYbDbs7OwYayWpVCpIJBLG4tpSqRTm5uZ6pa0nXJCegFqtxv3791FWVgZHR0dsiN3T478DgTAc0ZYzuVyOu3fv4tGjR/D19YWHhwf9b1epVEIikaCwsBBCoRBfffUVqqqqYGZmBldXV/zXf/0XTExMUF1dDXd39wGVtNOnTyM+Pp4xd3rWrFkG506fP38eCoWC/r2+vh7h4eF4/fXXGfv94Q9/oBMTAQyKZW3Cw8NhZmaGXbt2Pe2uEAi9hsxBIxC6gUKhgJWVFc6dO4fXXnuN3h4XF4fGxkZcuHChW8d5/fXXYWpqilOnTqGsrAzjxo1DdnY2+Hw+vc/UqVPB5/Oxb9++Pj8PwsCjVqtRVlZGS5tAIEBOTg7a2toQEhLCWFg7MDAQpqamRi/gtKWtubkZLS0t4HA4OtJmKKwA6Ljw0gTY+Pv7Y9SoUTr7kCobYaShLwTkwYMHuHv3LhwdHeHv728wwImiKNy8eROLFy8Gh8PB3/72NygUCmRnZ0MgEKCwsBCjRo1CVFQUXnjhBSxfvrzfz6enc6e12bt3LzZs2ICamhpwuVwAHRW0xsZGpKen92vfe8r06dMRGRmJjz/++Gl3hUDoCjIHjUDoC8zNzREVFYWMjAxa0NRqNTIyMrBo0aJuHUOlUiEvLw8vvfQSAMDb2xtjxoxBRkYGLWjNzc24desW3nvvvf45EcKAY2JiAl9fX/j6+uKNN94A0PFeKCkpoaUtLS0Nq1evhkqlQmhoKF1pi4qKgp+fH0xNf/+oZrPZsLe3h729Pb2tvb2dIW01NTVobW2FhYWFjrS1t7fj7t27ePz4MXx8fODp6WlwrgYZGkkYSWi/31taWlBQUACZTIaQkBA4OzsbbNvY2IgNGzbg1KlTWLt2Ld5//32dGyStra24ffs2hEIh1Gp1v5xDZ5507nRnjh49irlz59JypuHKlSsYPXo0HBwcMGPGDGzbtk3vTZ7+Rq1Wo66uDkePHkVxcXG3b5YSCIMdUkEjELrJ6dOnERcXh5SUFERHR2Pv3r04c+YMRCIRXFxcMG/ePLi7uyMhIQEAsGXLFkyaNAm+vr5obGzErl27kJ6eDoFAgKCgIAAdMfuJiYmMmP3c3FwSsz8CUalUEIlEtLQJhULk5OTAxMQE4eHhjOGRvr6+XSbAaYZdaaStqamJXoPPwsICrq6ucHR0hI2NDczMzHrVdyJthKGMtpip1WqUl5ejoqICHh4eGDduHOMmSWcoisKFCxewcuVKBAQE4PDhw/Dz8xuIbnfJgwcP4O7ujhs3bjCG269atQo///wzbt26ZbT9//3f/yEmJga3bt1izFlLS0uDlZUVvL29UVpairVr18La2ho3b94c8GTKK1euYMaMGQgICMDx48eNziUmEAYRpIJGIPQVc+bMQV1dHTZs2ACxWAw+n49Lly7RIR+VlZWMSkRDQwMWLlwIsVgMBwcHREVF4caNG7ScAR1flC0tLfjb3/6GxsZGPPPMM7h06RKRsxEIm81GcHAwgoODMX/+fFAUBaVSicLCQmRlZSEzMxMpKSnIzc0Fh8NBeHg4HfcfGRkJHx8fxvvPzMwMjo6OsLe3R05ODgDAxsYGrq6uUKvVdKVNJpPB0tJSp9Jm6IJUH6TSRhiK6HvfNjQ0oLCwECwWCxMmTGDMCdWmqqoKK1aswI0bN7B7927ExcUNq+TAo0ePIjQ0VCdQpHPCcGhoKMLCwjBu3DhcuXIFzz333ID2cdq0aQNSjSQQBhpSQSMQRhgjJdFrOA+RHUYAACAASURBVEJRFBQKBfLy8ugqm0AgQF5eHrhcLmONtsjISDQ0NCA+Ph5VVVW4fPkyeDyezvw2hULBmM/W3NwMuVwOLperE/nf27vjRNoIgwVtOVMqlSguLoZYLIaPjw94PJ5B2VKpVDhy5Ag2b96MP/7xj9izZ49OGu9goDdzp1taWuDm5oYtW7Zg6dKlXT6Xs7Mztm3bhnfeeadP+k4gDHNIBY1AIPzOSEr0Go6wWCxwOBxMmDABEyZMANAhbTKZDLm5uXQISWJiIgoKCsBmsxEZGYm//OUvuH37NkxMTODu7s648DQ3N4eTkxOcnJzobXK5nJa1x48fo6KiAgqFAlwulyFsNjY2PZI2UmkjPG30hYDU1taiqKgINjY2mDx5ssE1zQDgzp07WLx4Merq6pCWloY//OEPTyU6vzv0Zu702bNnIZfL8de//rXL56mqqkJ9fT1cXV37pN8EAoFU0AiEEcVISvQaiVAUhX/9619YtWoVfHx88Pbbb6OpqQkCgQACgQAikQhOTk6M+WyRkZEYM2ZMlxeZMplMp9LW3t6uI23W1tak0kYYlGjLWVtbG0QiEZqamuDv72/030FbWxsSExNx4MAB/P3vf8emTZtgbW09EN3uFT2dO63h//2//wd3d3ekpaUxtkulUmzevBl/+tOfMGbMGJSWlmLVqlWQSCTIy8sjN+cIhO5BKmgEAqGDkZDoNZIpLS1FXFwcKioqsGfPHsyZM4dxsUlRFKRSKYRCIV1pO3/+PIqLi+Hq6sqQtoiICDg7OzPaW1hYwMLCgq60UhTFqLTV1dWhtLQU7e3tsLa21pG2nszNIZU2Ql+iLwTk/v37KC0thYuLC2JjYw0G5VAUhZ9//hlLliyBvb09rl27hsjIyEFbNdOmp3OnAaCoqAi//PILvv/+e53jsdls5Obm4sSJE2hsbISbmxteeOEFbN26lcgZgdCHkAoagTBCGAmJXiOZuro6JCcn4/333+/2nX2KotDc3AyhUIjMzEwIBAIIhUKUlJSAx+Mx5rNFRETAwcHB6IWpZrildqVNpVLpzGfjcrm9DlQg0kYwhj7Rb25uRkFBAVQqFQIDA+Ho6Giw/aNHj/Dhhx8iPT0dmzZtwtKlS3sUnkMgEAgG6PIODxE0AmGE0FtBe+edd3Dz5k3k5uYa3U+zAPfly5cHPNGL0HsoikJDQwMEAgFD2ioqKuDt7c2otPH5fNjZ2XUpbW1tbTrSRlGUjrRZWVk9sbSp1WpUVlZiacjGJz11wjBCW87a29tRWlqKqqoqeHl5wcvLy+ANJLVajTNnzmD16tWYMGECDh48CG9v74HoNoFAGBmQIY4EAqEDJycnsNls1NbWMrbX1tZizJgxRtu2tLQgLS0NW7Zs6fJ5fHx84OTkhJKSEiJoQxAWiwVHR0c8//zzeP755wF0SFZdXR0EAgEj8r+qqgq+vr460mZtbU1LG4vFgpWVFaysrOj3GUVRaG1tpWWturoaIpFIr7Rxudwuh5M9fvwYIpEIAHC88hOdqgiptI0c9FXN6urqIBKJYGFhgZiYGKMV5vLycixbtgy5ubnYv38/5syZM6yi8wkEwtCAVNAIhBFETEwMoqOjkZSUBKDjTjGPx8OiRYuMhoSkpqbi3XffRXV1dZdzy6qqqsDj8ZCeno5XXnmlT/tPGDxQFIWamhpkZWXRkf9CoRBisRj+/v4MaQsLC4OVlVWXlbaWlhZGlU0ikYDFYumttLFYLMjlcty9exd1dXVdRqNrQ6Rt+KEtZ3K5HEVFRaivr8f48ePh7u5u8D2oVCpx4MABbN++HXPmzMHOnTvJPFoCgdBfkCGOBALhd0iiF6E/oSgKVVVVtLRp0iMbGhoQGBjIkLaQkBBYWFgYlTa1Wq0jbVKpFCwWC+bm5pDJZLC1tcX48eNhb2/f6+AGIm1DE33R+dXV1SguLsaoUaPg7+9v8LOIoihkZ2dj0aJFaG1tRUpKCqZNmzZkQkAIBMKQhAgagUBgkpycTC9UzefzsX//fsTExADoWJjay8sLqamp9P5FRUUICAjA999/Tw9509DW1obXXnsN2dnZOoleg3HhVsLAo5kblpmZSUubUCiERCJBUFAQI+4/ODgY5ubmRi+O6+vrUVhYCJVKBVtbW8jlckilUrDZbEaVzdbWtksB7A5E2gY32nImlUpRWFgImUyGgIAAODs7G2wrlUqxdetWHD16FPHx8Vi3bh0sLCz6u8sEAoFABI1AIBAIgwu1Wo2ysjKGtOXk5KCtrQ0hISEMaQsMDISpqSmqqqqwYsUKWFpaYtOmTRg7diw9nFGtVkMqlepU2kxNTXWkjcPhEGkbBmy8upTxupqamuLevXuoqKiAh4cHxo0bZzBxkaIoXLp0CfHx8fDw8EBKSgpCQkIG+AwIBMIIhggagUAYXly9ehW7du2CQCBATU0NvvzyS7z22mtG21y5cgXx8fHIz8+Hp6cn1q1bh/nz5zP2OXDgAF1ZDA8PR1JSEmM5AUL/olKpUFJSQkubUChEdnY2lEolPDw8UFNTg5CQEKxduxbTp0/vMu5cpVLplTZzc3O90tZbiLQNDOebjkEikTBe15aWFgAda3S5uLjA2dnZoIyLxWKsXr0aP/zwA7Zv34533nmHLAdCIBAGGiJoBAJhePHtt9/i+vXriIqKwuzZs7sUtPLycoSEhODdd9/F22+/jYyMDCxbtgwXL17ErFmzAHTMzZs3bx4OHz6MmJgY7N27F2fPnkVRURG9MDNh4Pnll1+wcOFCNDQ04Nlnn0VVVRVu374NFouFsLAwxpy28ePHd3mhrVKp9F7cczgcnSASIm2DD+3hjEqlEnfv3oVYLIa7uzssLS0hkUggkUgglUpx8OBBNDc3IzQ0FFFRUXj06BF27dqFGTNmYP/+/fDw8HhKZ9KzG0Kpqal48803Gds4HA5kMhn9O0VR2LhxI44cOYLGxkbExsbi0KFDGD9+fL+eB4FAeCKIoBEIhOELi8XqUtBWr16Nixcv4s6dO/S2uXPnorGxEZcuXQLQkW45ceJEJCcnA+gYMufp6YnFixcbTbck9A91dXX44IMPkJaWhrVr12LlypXgcDigKApKpRKFhYV03L9QKERubi7Mzc3B5/MZi2v7+Ph0merY3t6uI22tra2wsLDQkTZzc/NenxuRtp6jLwRELBbj7t27sLW1RUBAACwtLRn7qFQq3LhxA7/88gtu3bqFgoICVFdXw87ODlOmTEFUVBT94+HhMaChID29IZSamoqlS5eiqKiI3sZisRjzfHfs2IGEhAScOHEC3t7eWL9+PfLy8lBQUEDm1REIgw+yDhqBQBjZ3Lx5EzNnzmRsmzVrFpYtWwYAUCgUEAgEWLNmDf24iYkJZs6ciZs3bw5oXwkd/POf/8Tjx4+Rn58PLy8versmvTE8PBzh4eF46623QFEUFAoF8vLy6KGRSUlJyMvLg5WVFb02m0batKP4TU1N4eDgAAcHB3qbUqlkSNuDBw/Q1tYGCwsLneGRZmZmPTo3fet0EWkzjPbfq62tDYWFhZBIJPD394eLi4teuWKz2YiOjsb169dx/fp1zJ8/H+vWrUNFRQWdLnrhwgXk5+fDyckJr7/+On2Dpr/Zs2cPFi5cSFfFDh8+jIsXL+LYsWMGbwixWCyD61VSFIW9e/di3bp1ePXVVwEAJ0+ehIuLC9LT0zF37tz+ORECgdBvEEEjEAjDGrFYrJMo6eLigubmZrS1taGhoQEqlUrvPprFjwkDy7Jly7B8+fJu7ctiscDhcDBhwgRMmDABQMcFq0wmQ25uLh1CsmvXLuTn58Pe3h58Pp8RROLu7s6QNjMzMzg6OjIWvFYqlYwqW1VVFWQyGSwtLRnCZmNjQ6StD9D+m2jSQEtLS+Hq6orQ0FCDf2eKovDrr79iyZIlYLFY+P777zFlyhSwWCy4urpi8uTJ9L6tra24ffs2pFJpv56Phie9ISSVSjF27Fio1WpERkZi+/btCA4OBtAxjFssFjNuRNnZ2SEmJgY3b94kgkYgDEGIoBEIBAJhUNHb4WYsFguWlpaIiYmhl5CgKAqtra3IycmhpW3btm0QiURwcnJizGeLjIzEmDFjGP0wMzPDqFGjGIsXKxQKutLW1NSE+/fvQyaTwcrKSkfaugo10aBZw2vZV/Ph6OgIf39/eojaSJA2fbLa1NSEwsJCWk46Vzv17btx40b861//wpo1a7Bq1SqjQ1OtrKwYwtbfPHr0qMc3hPz9/XHs2DGEhYWhqakJu3fvxpQpU5Cfnw8PDw+IxWL6GNrH1DxGIBCGFkTQCATCsGbMmDGora1lbKutrYWtrS0sLS3BZrPBZrP17mNoSBFh6MFiscDlchEbG4vY2FgAHTIklUohFAppaTt//jyKi4vh6urKkLaIiAg4OzszpM3c3FyvtGmqbA0NDbh37x7kcjm4XK6OtGmHmkgkEhQWFkIulyMkJERnDa/hXmnTPr/29naUlJSguroaXl5e8Pb2NjinkKIo/Pvf/8bKlSvh5+cHoVAIf3//geh2vzN58mSGRE6ZMgWBgYFISUnB1q1bn2LPCARCf0EEjUAgDGsmT56Mb775hrHthx9+oC94zM3NERUVhYyMDDpsRK1WIyMjA4sWLRrw/hIGDhaLBRsbG0ydOhVTp04F0HGh39zcDKFQiMzMTAgEAqSlpaGkpAQ8Ho8xny0iIgIODg460ubk5AQnJyd6m0wmoytt9fX1KC8vh0KhgLW1NWxtbcHlctHc3IyHDx/SItLd6HdtqRmKwqZPPOvq6lBYWAhLS0tMmjQJXC7XYPvq6mrEx8fjxo0b2LVrF+bPn99lOMzTwsnJqdc3hMzMzBAREYGSkhIAoNvV1tbC1dWVcUw+n99HPScQCAMJETQCgTCkkEql9IUJ0DH/IicnB46OjuDxeFizZg2qq6tx8uRJAMC7776L5ORkrFq1CgsWLMCPP/6IM2fO4OLFi/Qx4uPjERcXhwkTJiA6Ohp79+5FS0uLTrQ1YfjDYrFgZ2eH6dOnY/r06QA6pK2hoQECgYCWttTUVFRUVMDLy4sxNJLP58POzo4hbRYWFrCwsKArYhRFQS6Xo6mpCWKxmPF+rqurg1wuZ1TaeiIbQ63Kpt1fmUyGoqIiPH78GH5+fnBzczM45FWlUuHIkSPYvHkz/vjHP6KgoEBnmN9goy9uCKlUKuTl5eGll14CAHh7e2PMmDHIyMighay5uRm3bt3Ce++91z8nQiAQ+hUSs08gEIYUV65coS+cOxMXF4fU1FTMnz8fFRUVuHLlCqPN8uXLUVBQAA8PD6xfv15noerk5GR6XSI+n4/9+/fT85cIBG0oikJdXR0EAgGysrLoBMmqqir4+voyhkfy+XxYW1szROPu3bs4e/YsYmNj4efnhzFjxkAulzOCSJqbm6FSqehKm+bH2tq61xWipy1t+qLzq6qqUFJSAicnJ/j5+Rldiy4/Px+LFi3Cw4cPceDAAbz44osDGpXfG06fPo24uDikpKTQN4TOnDkDkUgEFxcXzJs3D+7u7khISAAAbNmyBZMmTYKvry8aGxuxa9cupKenQyAQICgoCEBHzH5iYiIjZj83N5fE7BMIgxOyDhqBQCAMVq5evYpdu3ZBIBCgpqamyzXdzp8/j0OHDiEnJwdyuRzBwcHYtGkTveA2AGzatAmbN29mtPP39yeJlAOAZn0ujbAJBAIIhUKIxWL4+/sjIiICYWFhuHv3Lk6dOoUXX3wRR48eNSgiFEWhra2NIWwSiQRqtVpH2rhc7pCQNn0VPqlUioKCAsjlcgQGBjKGh2rT1taGHTt2IDk5Ge+99x42b94Ma2vr/uxyv2DshtC0adPg5eWF1NRUAMDy5ctx/vx5iMViODg4ICoqCtu2bUNERAR9PM1C1Z9++ikaGxvxzDPP4ODBg/Dz83sap0cgEIxDBI1AIBAGK99++y2uX7+OqKgozJ49u0tBW7ZsGdzc3DB9+nTY29vj+PHj2L17N27dukVfrG3atAnnzp3D5cuX6XampqZGL3oJ/YemMpSVlYXz588jPT0dbDYbDg4O4HK5jEpbaGgoLCwsjFaCNGmU2tJGUZTOwtpcLrfXVaW+lDZtOVOpVCgvL8e9e/fg6emJcePGGZx7R1EUrl69isWLF8POzg4pKSmIiooaMlUzAoFA6AQRNAKBQBgKsFisLgVNH8HBwZgzZw42bNgAoEPQ0tPTkZOT0x/dJDwBjx49wurVq3H69Gls3LgRS5YsQU1NDTIzMxmVNolEgqCgIMactuDgYJibm/dY2pqbm+kQlM7SZmVlNeDSpq9q9vjxYxQUFMDMzAxBQUGwsbEx2L6+vh7r1q3D+fPnsXHjRixbtqzbyxYQCATCIKTLD2HyCUcgEAhDFLVaDYlEwlhQGQCKi4vh5uYGCwsLTJ48GQkJCeDxeE+plyObu3fvYsqUKYiNjUV+fj7Gjh0LAPDy8oKXlxdef/11AB2vZVlZGR1C8uWXX2LDhg1oa2tDSEgIQ9oCAwNhampKi5ZmCQEul0un+KnVaoa03b9/HxKJBCwWiyFsmuUmeiJtPQki0d5XoVCguLgYtbW18PX1haenp8HnVqvVOHv2LFavXo2oqCjcvn0bPj4+3e4ngUAgDFVIBY1AIBAGAU9SQdu5cycSExMhEokwevRoAB3DJqVSKfz9/VFTU4PNmzejuroad+7cMVqlIPQParUaP/30E5577rket1WpVCgpKaErbUKhENnZ2Whvb0doaCg9PDIqKgr+/v5gs9lGRUutVqOlpUVneCSbzdaRtq6GWvYUzfy8oqIi2NnZISAgAJaWlgb3Ly8vx/Lly3H79m188sknmDt37qCNzicQCIQeQoY4EgiE4cGpU6ewYMEClJWV0VWCN998EwKBANeuXYOdnd1T7mHv6Kmgff7551i4cCEuXLiAmTNnGtyvsbERY8eOxZ49e/DWW2/1VXcJTwmVSgWRSMSQttu3b4PFYiEsLIwxp238+PFdrqemVqshlUoZ0iaVSmFqaqozPPJJpa21tRWFhYWQSqUICAjA6NGjDR5HqVTi4MGD+OijjzBnzhzs3LmTsRA4gUAgDAOIoBEIhOEBRVHg8/l49tlnkZSUhI0bN+LYsWP49ddf4e7u/rS712t6ImhpaWlYsGABzp49i5dffrnL/SdOnIiZM2fSsd2E4QNFUVAqlSgsLERWVhYyMzMhFAqRm5sLc3Nz8Pl8xuLaPj4+XVaiVCqVjrS1tLTA1NRUp9LG4XCMDlG8d+8eysrK4ObmBl9fX5iZmRk8j+zsbCxatAitra1ISUnBtGnTSAgIgUAYjpA5aAQCYXjAYrHw0Ucf4c9//jPGjBmDpKQkXLt2bVjIWU/QVBLT/n97dx4T1dW/AfwZpx0RU9Ep6xBZRNQWZYZ1CtpXaImg1khIWzVGGEM340aptmIQ+AVxq7WgWMF1oGmDxUZM2jrFYpFYAQtIFa0LCEVWlwo6KGJg3j+I92V+rFZhgD6fhChnvvd6jhJzn5xz7klL61M402q1KCsrw5IlSwagdzTQRCIRJBIJ5HI55HI5QkNDodPp0NLSgpKSEuElJLt27cKFCxdgbGwMV1dXyOVyIbTZ2trqhTaxWAwTExO9WenW1lbcv39fCGw3b95EU1MTJBJJl6GtsbERly5dgk6ng5ubG8aOHdvtGLRaLTZu3Ij9+/fj448/RmRkZI/LH4mIhjvOoBHRkOLq6oqLFy8iMzMTM2fONHR3nolWq0VpaSkAwMXFBTt27ICvry+kUilsbGwQERGB6upqpKamAmhf1hgSEoKEhAQEBQUJ9xk1apTwML1mzRrMmzcPtra2qKmpQXR0NIqLi3Hp0iWYmZkN/CBpUNDpdGhubsb58+eF0FZYWIiLFy/CxMREb2mkq6srrK2t+zTT1jG0PZlpE4vFaG1tFX6OTUxMIJFIuuxTZmYmwsLCYG1tjeTkZEybNq2//gqIiAYLLnEkouFDo9EgKChImB2YMmWKobv0TLKzs+Hr69upPSQkBGq1GiqVChUVFcjOzgbQfoDtqVOnuq0HgIULFyInJwd37tyBmZkZZsyYgbi4ODg4OPTnUGgIevJ6/uLiYr3QdvnyZZiamnYKbZaWlj0uObxx4wauX78OiUQCU1NTNDc34969e3jw4AEuX76M48ePQy6Xw9PTE46Ojti+fTt+/vlnxMXFYdmyZb3ul+tPu3fvFg6Olsvl2LVrFzw9Pbus3bdvH1JTU1FSUgIAcHNzw6ZNm/TqVSoVUlL032Dp7+8PjUbTf4MgoqGCAY2IhoeioiL4+PggOTkZarUaY8aMQXp6uqG7RQBycnLw+eefo7CwELW1tb3upesumNbW1sLS0lL4/mkemun50Ol00Gq1KCoqEgJbYWEhrl69CisrKyG0PQluZmZmKC8vx4oVKyAWi5GcnAwrKyu9IPf48WNcuHBBOJ+vpKQE9fX1MDY2hq+vL/7zn//A3d0drq6uPS6F7C+HDx9GcHAwkpKSoFQqER8fj/T0dFy5ckV4O2pHixcvxvTp0+Ht7Q0jIyNs3boVR48excWLF4Ul1yqVCvX19Th06JBw3ciRIzFu3LgBGxcRDVoMaEQ09FVUVMDLywurV6/GunXrkJ+fDy8vLxQUFMDV1dXQ3fvXO378OH777Te4ubkhKCiozwHtypUrGDNmjNBubm4uLKt72odm6j86nQ737t1DUVGRcE5bUVERSktLIZVK8fDhQygUCnz00UfCEt2uZtquXr2KVatWoaysDHFxcbC2tkZhYSEKCgpQUFCAv/76CxMnToS7uzvi4uIG7MwzpVIJDw8PJCYmAmh/ucn48eOxcuVKrFu3rtfrW1tbMW7cOCQmJiI4OBhAe0BraGhARkZGv/adiIYkBjQiGtr+/vtveHt7w8fHB0lJSUL73Llz0drayiVDg0xf3kb5JKDdvXu32xmTZ31opv51/vx5hIaGorq6GnPmzMHdu3dRVFSEiooK2NnZdTpYW61WY/v27QgJCcGmTZu6/He/deuWENg+/PDDAdkz2dLSAmNjYxw5ckTvZzYkJAQNDQ04duxYr/e4f/8+zM3NkZ6ejrfeegtAe0DLyMiARCLBuHHj8MYbb2Djxo08MoCIAL7FkYiGOqlUisuXL3dq//HHHw3QG3qeFAoFHj16hKlTpyImJgbTp08H0P7QXFhYiIiICKF2xIgR8PPzQ25urqG6SwAePnyI2NhYxMfHY/Xq1diwYQOMjY0BtM+0dQxZv//+O5KTk1FVVQWZTIbMzEx4e3t3u4/NzMwMAQEBCAgIGLDx3L59G62trbCwsNBrt7Cw6PL/na589tlnkMlkeucRBgQEICgoCPb29igrK8P69esxe/Zs5ObmGnSvHRENDQxoREQ0oKysrJCUlAR3d3c8evQI+/fvh4+PD/Lz8+Hq6vpcHpqpf5w7dw6//vor8vLy4OzsrPeZSCSCubk5Zs+ejdmzZwNoD20FBQUYP3683v7C4WLLli1IS0tDdnY2jIyMhPaFCxcKv582bRqcnZ3h4OCA7OxsvPnmm4boKhENIQxoREQ0oCZPnozJkycL33t7e6OsrAxffvklvv76awP2jHrj7e2NM2fO9PkAaZFIBA8Pj37u1T9namoKsViM+vp6vfb6+vpeA+X27duxZcsW/PLLL53C6v83YcIEmJqaorS0lAGNiHrV8yEnREREA8DT01M4E+5ZHpqp//U1nA0FEokEbm5uyMrKEtra2tqQlZUFLy+vbq/btm0bYmNjodFo4O7u3uufU1VVhTt37sDKyuq59JuIhjcGNCIiMrji4mLh4fWfPjQT/RPh4eHYt28fUlJS8Oeff2LZsmVoamrC0qVLAQDBwcF6+yG3bt2KDRs24ODBg7Czs0NdXR3q6uqg1WoBtB9Av3btWuTl5aGiogJZWVmYP38+Jk6cCH9/f4OMkYiGFi5xJCKiZ6LVaoXZLwAoLy9HcXExpFIpbGxsEBERgerqaqSmpgIA4uPjYW9vDycnJzQ3N2P//v04efIkMjMzhXuEh4cjJCQE7u7u8PT0RHx8vN5DM9HzsmDBAty6dQtRUVGoq6uDQqGARqMR9kBWVlYKxz8AwJ49e9DS0oK3335b7z7R0dGIiYmBWCzG+fPnkZKSgoaGBshkMsyaNQuxsbEYOXLkgI6NiIYmvmafiIieSXcHT4eEhECtVkOlUqGiogLZ2dkA2peH7d27F9XV1TA2NoazszOioqI63SMxMVE4qFqhUGDnzp1QKpUDMSQiIqL+wnPQiIiIiIiIBoleAxr3oBEREXWQk5ODefPmQSaTQSQSISMjo8d6lUoFkUjU6cvJyUmoiYmJ6fT5lClT+nsoREQ0BDGgERERddDU1AS5XI7du3f3qT4hIQG1tbXC140bNyCVSvHOO+/o1Tk5OenVnT59uj+6T0REQxxfEkJERNRBx4OW+8LExAQmJibC9xkZGbh7926nF5q88MILPCaAiIh6xRk0IiKi5+jAgQPw8/ODra2tXvu1a9cgk8kwYcIELF68GJWVlQbqIRERDWYMaERERM9JTU0Njh8/jvfee0+vXalUQq1WQ6PRYM+ePSgvL8frr7+O+/fvG6inREQ0WHGJIxER0XOSkpKCsWPHIjAwUK+945JJZ2dnKJVK2Nra4rvvvkNoaOhAd5OIiAYxzqARERE9BzqdDgcPHsSSJUsgkUh6rB07diwmTZqkd8A3tdu9ezfs7OxgZGQEpVKJs2fP9lifnp6OKVOmwMjICNOmTcNPP/2k97lOp0NUVBSsrKwwatQo+Pn54dq1a/05BCKiZ8KARkRE9BycOnUKpaWlfZoR02q1KCsrg5WV1QD0bOg4fPgwwsPDER0djaKiIsjlcvj7++PmzZtd1p85cwaLFi1CaGgozp07h8DAQAQGBqKkpESo2bZtG3bu3ImkpCTk91oolAAABWdJREFU5+dj9OjR8Pf3R3Nz80ANi4joqfCgaiIiog60Wq0ws+Xi4oIdO3bA19cXUqkUNjY2iIiIQHV1NVJTU/WuW7JkCa5du4a8vLxO91yzZg3mzZsHW1tb1NTUIDo6GsXFxbh06RLMzMwGZFxDgVKphIeHBxITEwEAbW1tGD9+PFauXIl169Z1ql+wYAGamprwww8/CG2vvfYaFAoFkpKSoNPpIJPJ8Mknn2DNmjUAgMbGRlhYWECtVmPhwoUDMzAiov/hQdVERERPo6CgAC4uLnBxcQEAhIeHw8XFBVFRUQCA2traTm9gbGxsxPfff9/t7FlVVRUWLVqEyZMn491338XLL7+MvLw8hrMOWlpaUFhYCD8/P6FtxIgR8PPzQ25ubpfX5Obm6tUDgL+/v1BfXl6Ouro6vRoTExMolcpu70lEZGgMaERERB34+PhAp9N1+lKr1QAAtVqN7OxsvWtMTEzw4MEDvP/++13eMy0tDTU1NXj06BGqqqqQlpYGBweHfh4JsHnzZnh4eOCll16Cubk5AgMDceXKlV6vM8S+rtu3b6O1tRUWFhZ67RYWFqirq+vymrq6uh7rn/z6NPckIjI0BjQiIqJh6tSpU1i+fDny8vJw4sQJPH78GLNmzUJTU1O313BfFxGRYTGgERERDVMajQYqlQpOTk6Qy+VQq9WorKxEYWFht9ckJCQgICAAa9euxSuvvILY2Fi4uroK+8J0Oh3i4+MRGRmJ+fPnw9nZGampqaipqUFGRsY/7qupqSnEYjHq6+v12uvr62FpadnlNZaWlj3WP/n1ae5JRGRoDGhERET/Eo2NjQAAqVTabY2h9nVJJBK4ubkhKytLaGtra0NWVha8vLy6vMbLy0uvHgBOnDgh1Nvb28PS0lKv5t69e8jPz+/2nkREhsaDqomIiP4F2traEBYWhunTp2Pq1Knd1hlyX1d4eDhCQkLg7u4OT09PxMfHo6mpCUuXLgUABAcHw9raGps3bwYArF69GjNnzsQXX3yBuXPnIi0tDQUFBdi7dy8AQCQSISwsDBs3boSjoyPs7e2xYcMGyGSyToeJExENFgxoRERE/wLLly9HSUkJTp8+beiudGvBggW4desWoqKiUFdXB4VCAY1GI4TByspKjBjxv8U/3t7e+PbbbxEZGYn169fD0dERGRkZegH0008/RVNTEz744AM0NDRgxowZ0Gg0MDIyGvDxERH1Bc9BIyIiGuZWrFiBY8eOIScnB/b29j3W2tjYIDw8HGFhYUJbdHQ0MjIy8Mcff+D69etwcHDAuXPnoFAohJqZM2dCoVAgISGh38ZBRDQM8Bw0IiKifyudTocVK1bg6NGjOHnyZK/hDOC+LiIiQxPHxMT0tbbPhURERGR4y5cvxzfffIMjR45AJpNBq9VCq9VCLBbjxRdfBNC+r+vs2bPCSz+sra0RGRmJ0aNHQyqVIjExEYcPH8aBAwdgbm4OkUiE1tZWbNq0Ca+++ipaWlqwatUqPHjwALt27cILL3D3BBFRD/6vtwIucSQiIhqmRKKuV9IcOnQIKpUKQPvB3HZ2dsJB3ED7QdWRkZGoqKiAo6Mjtm3bhjlz5gif63Q6REdHY+/evcK+rq+++gqTJk3qz+EQEQ0HvS5xZEAjIiIiIiIaGNyDRkRERERENFQwoBEREREREQ0SDGhERERERESDBAMaERERERHRIPE078LtdUMbERERERER/XOcQSMiIiIiIhokGNCIiIiIiIgGCQY0IiIiIiKiQYIBjYiIiIiIaJBgQCMiIiIiIhokGNCIiIiIiIgGCQY0IiIiIiKiQYIBjYiIiIiIaJBgQCMiIiIiIhok/gt8CT7K71G3DQAAAABJRU5ErkJggg==\n",
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