{ "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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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from examples.cfd import init_smooth, plot_field\n", "\n", "nt = 100 # Number of timesteps\n", "dt = 0.2 * 2. / 80 # Timestep size (sigma=0.2)\n", "c = 1 # Value for c\n", "\n", "# Then we create a grid and our function\n", "grid = Grid(shape=(81, 81), extent=(2., 2.))\n", "u = TimeFunction(name='u', grid=grid)\n", "\n", "# We can now set the initial condition and plot it\n", "init_smooth(field=u.data[0], dx=grid.spacing[0], dy=grid.spacing[1])\n", "init_smooth(field=u.data[1], dx=grid.spacing[0], dy=grid.spacing[1])\n", "\n", "plot_field(u.data[0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, we wish to discretise our governing equation so that a functional `Operator` can be created from it. We begin by simply writing out the equation as a symbolic expression, while using shorthand expressions for the derivatives provided by the `Function` object. This will create a symbolic object of the dicretised equation.\n", "\n", "Using the Devito shorthand notation, we can express the governing equations as:" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial}{\\partial x} u{\\left(t,x,y \\right)} + \\frac{\\partial}{\\partial y} u{\\left(t,x,y \\right)} + \\frac{\\partial}{\\partial t} u{\\left(t,x,y \\right)} = 0$" ], "text/plain": [ "Eq(Derivative(u(t, x, y), x) + Derivative(u(t, x, y), y) + Derivative(u(t, x, y), t), 0)" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "eq = Eq(u.dt + c * u.dxl + c * u.dyl)\n", "eq" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now need to rearrange our equation so that the term $u(t+dt, x, y)$ is on the left-hand side, since it represents the next point in time for our state variable $u$. Devito provides a utility called `solve`, built on top of SymPy's `solve`, to rearrange our equation so that it represents a valid state update for $u$. Here, we use `solve` to create a valid stencil for our update to `u(t+dt, x, y)`:" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle u{\\left(t + dt,x,y \\right)} = dt \\left(- \\frac{\\partial}{\\partial x} u{\\left(t,x,y \\right)} - \\frac{\\partial}{\\partial y} u{\\left(t,x,y \\right)} + \\frac{u{\\left(t,x,y \\right)}}{dt}\\right)$" ], "text/plain": [ "Eq(u(t + dt, x, y), dt*(-Derivative(u(t, x, y), x) - Derivative(u(t, x, y), y) + u(t, x, y)/dt))" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "stencil = solve(eq, u.forward)\n", "update = Eq(u.forward, stencil)\n", "update" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The right-hand side of the 'update' equation should be a stencil of the shape\n", "\n", "\n", "Once we have created this 'update' expression, we can create a Devito `Operator`. This `Operator` will basically behave like a Python function that we can call to apply the created stencil over our associated data, as long as we provide all necessary unknowns. In this case we need to provide the number of timesteps to compute via the keyword `time` and the timestep size via `dt` (both have been defined above):" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "tags": [ "nbval-ignore-output" ] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Operator `Kernel` ran in 0.01 s\n" ] }, { "data": { "image/png": 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2d3fB8zxkWUYqlWoZCZDJZBCPx/uyn34hDAtuEpr2sOu6SZJEISUE4QEk0AjiiON0sLRXpYaDFmgskXFrawuSJGFubg4LCwuOExm7oZs5aG4Pqx40g9z3SCSiuWXGfWg0Gk3CjTlujUYDiUTC1HUL8vvO8Fs8fbeEpQdNlmXPjsOO60YhJQTRX0igEcQRRV/GaCxraUfYHTRjImMmk8Ho6CguXbrU920zjGLLzu8l6ALND3Ach2QyiWQyadrnpi+X3N3dxcrKCqrVKqLRKFRVxVtvvdUk3NLpdKDEQhgW0FTi2D+6DSkpl8tQVRXj4+MUUkIQNiGBRhBHCKvB0k5ukF45aP0WhvpExlgspiUyvvvuuwMXPt2UOAZZoAVhcRaPxzE6OorR0dGm12VZxt7eHl5//XWk02lUKhVsbm5CEASoqmo5z81vQRZhKQ0My3H4UaBZ0alccnd3F7Is49ixYxRSQhA2IYFGEEeATsEfTghbSAhLZFxeXsbQ0FBLImO3/WC90I3YCrJAA4LbPxeNRrVEyLNnz2qvq6qqzXPT97kJggBJkpBKpVqEWzab9azPLajvv5EgCZt2hOU42PUzFos1PZSgkBKCaA8JNIIIMXaDP5wQiUTQaDTc3E3b23VTKBkTGW/dumWayBiJRCCKomvbtYNZDxqVOAYLjuPa9rnpyyWZ41av1xGPx1vCSbLZLJLJZF8XpGFynsJyHH5zWbtFlmUkEomm1yikhCDaQwKNIEKI0+APJ3jdg9brQnJvbw/5fB7b29s4depUx0RGL9IjzVw7O+IrqALtKIlLfZ+b8YGAJEmacON5Hnt7e1hdXUW1Wm0KNtELN7f63MIi0MISEhIWBw04FGhOxKbTkBL991BICREWSKARRIjQlzGyJ8lul4J4meIIdLeQVFUVW1tbyOVyqFQqOHPmjO1ERq9KHI9SD1oYcOMzFovFMDIygpGRkabXFUVpKpXkeb6pzy2dTjfNcWN/j8Xs3+LDItDC4qDJsuzo9+dn3HIDuw0pYX8y0UYhJUQQCMennyCOMFbBH/16YuilgwY4e7JsTGScn5/HrVu3HPX5OI28d4Oj2IMWZPr9vkciEQwNDbU4vaqqolarNQm3UqkEnuchSRKSyWRLOAnrczNb5IZhkUoOmv9w6qA5xW65JHuASSElRBAggUYQAcWsv6yfwozhtYNmRxxKkoTl5WUUCoWmRMZuFjxelDh2IwqDLNCCvO9ewnEc0uk00uk0xsfHtdeZi6Cf57a1tQWe51Gv1xGLxVrCSer1uodH4h5hcdBIoLmDnXJJCikh/AgJNIIIGMwtkyRJ+/9B3jD84KBZYUxkXFhYwMmTJ3t6X7wQD2bb7HQMXjh9hD/hOA6JRAKJRKJtn5sgCCiXyygWixAEAQDw8ssvt7humUwmMGKBHDT/4eXQbSu6DSmp1WrY39/HqVOnKKSE6Csk0AgiIOiDP4rFIpaXl/Hwww8P/MbnlYPGBKjZtiuVCgqFAorFIsbHxy0TGbvBLyEhdgiqQAvDgiYox2DV51YsFrG6uoq5uTlNwG1vb4Pnea3PTd/j1k2f2yAIk4MWphTHIB1LO9dNEASsrKxgcnKSQkqIvuKvKytBEC3oyxjZ4iMWi0GWZU8u+F45aECrWHKayOjGNgdBNw5a0MsEad+9JxaL4eTJk02vqaqKer3eVC7JHDdRFJFMJk0HcScSCU+uT+Sg+Y+gCTQr2ANCOzPdKKSE6BUSaAThQzoNlvZqWDTbB6+3vbm5iXw+j/39fczOztpOZOwGL4TPUetBI7zHKiSE4zikUimkUqmmPjcALfPctre3sbS0hFqthlgs1uK2ZTIZbah3vwiTgxYWgRY2N9DoGlNICdEPSKARhI+wO1jaS4HmlYPG3o/XXnsNiqJgbm4ON2/edJTI2A1+cdD68T1+gRYh3tNNiiPrcxsbG2t6XZbllj63tbU1CILQNMDbOM/NjUV8WBw0P/ZtdQO7p4VFoEmS5PpMNwopIcwggUYQPsDpYGmvywwHKQ71iYyyLGNmZgYXL14c2OLFL3PQ2I283fcEVaABwS8TDPpiyc2Y/Wg0iuHhYQwPDze9rigKqtVqi+smCAJkWdb63IwJk0763MhB8xfsXhEWgebWfLpuQ0rY9zChRiEl4YUEGkF4iL6M0fjkrB3RaFRLcRw0TBz2e25SvV5HoVDA8vIystksFhYW8O6772J8fHygCxe/zEELs0AL+oIiqO+7nkHMQYtEIprompiYaNp2vV5vEm7r6+sQBAGNRgOJRKKlXDKbzbb0ubHfQxiETVhcJybQwvA7AQbTT2fHdWNrBwopCS8k0AhiwFgNlnZSshCNRrWLtBcpjkD/FhBmiYxjY2PgOA7379/3ZCaZl3PQZFnG6uoq8vk8Go1G00KVLVZZX08YhALhHV4t4PR9bsePH2/6N1EUmwZx7+zsaH1u0Wi0SbCxPtQwLETD5KC1qwYJGpIkIZ1Oe7JtK9eNQkrCCQk0ghgQnYI/nMCEkRc3cf223RRopVIJ+XweW1tbOHXqFO7cudNSIuVFuaFXDpqiKMjlclhcXEQ8Hse5c+eQSqVQq9XA8zwODg40l4HdYBVFQa1W08RbOp0OzMKIxKW3+LU0MB6PY3R0FKOjo02vsz43Jt4ODg6wtrYGAPjpT3/aMseN/T0orlSYBFpQ3nM7SJLku9ESvYSUCIIARVFw7NgxCinxGf46ywgihNgN/nACu+G5VQ/vBLbvsiz3HNChqiq2tra0RMYzZ87g8ccft0xk9KL3btCisF6vY21tDfv7+4hEIrhy5QomJiYgyzJEUWxZqLK+njfffBOJRAKCIGBrawuCIEBV1ZbZVW4GMrhFGBYBdAyDxazPrdFo4Cc/+Qlu376tjQbgeR67u7vgeR6yLCOVSrX0uGUymb6HDTnBq+qIfhCWUk1G0ARnp3LJzc1NiKKIoaEhy5CSb37zm3j88cdx69atge77UYcEGkH0CafBH05gT7a8SHJk2+5FtCiKgrW1Na1sb35+3lYio1flhoPYZrVaRT6fx8rKCoaGhpBOp/Hwww+3fTrK9i+bzSKZTOL48eOYmZkBcHj+MbfNbKGaTqdbenq8HDwcZActyPvOCNMxDA0NYXh4GCdOnGj6t0aj0TTPbWNjAzzPo9FoIB6Pm34eksnkwIUru96EQaAFTdB0wo8OWjewc1qWZSQSiaZjMoaUfPvb38bs7CwJtAET/LOMIHyGvoyRlQ31o8Y7iLPQWCLj4uIiIpEIzp49i9OnT9u+gYdRoFUqFeRyOaytrWFychIPP/wwRFHE22+/7eicMfagcRyHdDqNdDrdslA1GzzM8zwkSUIqlTLtc/OTw0C4zyBCQvqN/nprhOM4JJNJ7UGGHn2fmyAI2N3dxcrKCqrVKqLRqOkg7n6WD4dNoIXhOBhhFJzGihX9Z0hVVZTLZRw7dsyL3TvSkEAjCBewCv7oZw13kGah1et1LC4uYmlpCdlsFpcvX8bJkycdvzdeziRzewFbKpWQy+Wwvb2N06dP49FHH0U2mwUA7OzstDganbZtNyTEavAway7XO256hyGRSLQ4DCxJr1eCLgzCQBgEWrfH0K7PrVqtasKtUqlgc3OzpXzYWC7Z6wI+bAItbIImDA4aw87xlEolEmgeEJ6zjCA8wBj8MQhhxgiCg8bzPPL5vJbIePPmTRw7dqzr98YrBw1wZwGrqip2dnaQy+VQLpcte+6sSkjbbb/XfeM4Ths8bLwZM+HGXIbt7W0sLi6iXq8jHo+3OG5mEeidCHqJ3VEVN37C7b6taDSKoaEhDA0NNb2uLx9mn4m9vT0IgtDiQuv/tPswgzmBJND8R9iOp5NAk2UZBwcHJNA8gAQaQXQB6y9jZYws+GOQcbV+dtD0iYxTU1OmiYzd4JWDBvS2+FNVFRsbG8jlcqhWq5ibm8ONGzcsF2zdROb3M8wkHo9jbGwMY2NjTa9LktQUgW4sDTOWSbIo9KALASNBF5dAOATaoI5BXz5s3H6j0Wgql2SOm9nDDOa+GT8TYQkIAcIlaNh9/yg5aOVyGQBIoHlAeM4yghgA+uAPtti+cuWKJzdTvzloqqpie3sbuVxOS2R87LHHXJ0Z023vW6/bBLpbhCuKgmKxiFwuB0VRMD8/j5mZmY43+G6i/b2YgxaLxTAyMoKRkZGm11kEOluklstlFItFVKtVcBzXUibJEk4J7wiDQPNa2Oj73IwLWv3DDEEQsLe3h9XVVdPPhH5sRtCFWpgEGrv3hOV4gMPqiHb3o1KphFgs1uIiE/2HBBpB2MAq+EOSJM8WNX5x0IyJjHNzc7YSGbvByxJHJ9uVJAkrKyvI5/OIxWI4d+4cTp8+bXux1a2D5hcnxywCHXh/JABz3FhPD8/zUFUVP//5z1tct0wmE/hFalAIg0Dz6zFYPcxQFKVpnhvP89jf34ckSXj++eeRTqdNyyWD4uKEKWaf3W+D8t7boZODViqVMDo6StdgDwjPWUYQLtMp+CMWi3kmkADvHbRGo4FCoYBCodBVImO325UkqW8/3wx9mlUnGo0GlpaWsLi4iHQ6jcuXL2NyctLxorGbckU/CTQr2EgAFobC2N3dxVtvvYVz585pDsP29rYm3NhIALfDGNwiDO5TWI4haAvJSCTS0ue2u7uL3/zmN/jABz7QJNxKpZKWtppMJls+D9lsFvF43Fe/xzClOEqSFKrhzYqiQFGUtg9TS6VSS2k7MRhIoBGEAavB0sb+slgsNnCxoMeLcj/gMJGxVqvhnXfewfDwMB588MGuREg3eNWD1kkw1Wo1FAoFLC8vY3R0FNevX8f4+HjX70m3DlpQYZ+viYkJTExMaK+zMAb9ItUYxmAMJwmSu+AnwiDQ/OygOUFRFMRiMa3PTZ+2CqBlntvW1hZ4nke9XkcsFmtx27zs/ZRlGclkcuDb7Qdh7D8D2juC5XIZY2NjofhcBY3wnGkE0SPGwdJMmFk9/fPSwfJi+zzPo1AoYHV1FbFYDNPT01hYWBjohdsLgdZuu/qUyhMnTuCDH/ygK08bg9KD1m/0YQzGkQBskcoWqmtra+B5HqIoIplMmo4EoFlu1oTh3Amig2ZGp94zq7RV1ufGhJux99OsVLLfJcRh6kGTJCk0xwK87wi2+/3v7e21jJ8gBgMJNOLIw2x+JswA2Io4PioCrVwuI5fLNSUy5vN5T57IeinQ9AvYcrmMfD6PjY0NnDp1Cnfv3nW1ibqb2WtBFmjdlIBaDR02ugusx43NcjMbwu10JEAYCYODFoZjALovC2zX56af58ZGZQiCAEVRNCfaWDLphlsUth60sDlonY6HhlR7R3jONIJwgL6/jAk0Vspm9wbvdYljPwUaS2TM5/Mol8uYmZlpSmT0qrzSK4HGcRxkWdZmmO3t7WFmZgaPP/64qymV+u0Bzhac/YzZHwRuict27oJ+CPfOzg6WlpZQq9W0sjDjIjWZTNp6/8MgDMJwDGFIPQTcPw6r3k9VVVGv15uEm96JNhtO7/SBBjlo/qVTgiPwfokjMXhIoBFHCuNgaUY3jb9+cNDq9bqrP1NRFKyvryOXy2mJjB/4wAdaSsM6zUHrF14INCbm33jjDdRqNczOzuLatWt97atwEkyi/56gOmiDIBaLYXR0tKVcR5blpgVqqVTS4s+j0aip45ZOpwMvZoyERaAF/RiAwQlNjuOQSqWQSqVa+tzYcHp9aI/+gYZZuaTZ5yJMAu0oOmh7e3s4ceLEgPaI0BOeM40g2mAV/AF0H67ABJpXCxs3RRKLhWeJjPPz85ienra8sXqRpggMVhjqxweIoojJyUk8+OCDA7lBdzN7LcgOmpeL6mg0ajnLTT8S4ODgAOvr6xAEoaWfh11fguzghEGgHZUetEFgNZzeOONwf3+/6XNhTFwVRdGjI3CfsDlokiR17Mvd39/H+fPnB7RHhB4SaESoMQZ/APb6y+wQi8W0hZkXF203HLx6vY6lpSUsLS0hk8nYTmSMRqNoNBo9bbsbBuGgybKsiVUAOHv2LAqFAqampgb29LRbBy3I+M39i0ajLfHnwPv9PMa5VfV6Hc8//7wWvKB33dLptO8XdmEQaOSg9Z92Mw5rtVqT67azs4NqtRPoUQMAACAASURBVIo33njDcp5bkIJ7jqKDRjH73hGeM40gdOjLGPXCzM2bN1tweVXC0YtA0ycyHj9+HDdu3MDx48dtvz9h7EETRVGbYZZMJnHhwgVMTU0hEolgeXl5oO7UUStxDNKiWt/Pw0YC7Ozs4N1338WNGzea+tx2d3fB8zxkWdacBWOfm5+EW5B+D2aEyUHz03lhh0gkoj2c0I/KeOGFF7CwsIBIJKIJN+a4mQX3sL/7MbgnjA6aHYFmDGIiBgMJNCI0WA2WdluYMVjfmiRJSCQSrv/8TnQj0Izpg3fu3Gl5Emp322HpQavX69oMs+HhYVy9ehUnTpxoOmcGLX7Ytp0ca5AFGuA/B80p+pEA+p4NsyCGYrGoDRy2StAbtLNADpp/8LOD5hT9oHnjQl8UxSYnWh/cE41GLee5efXehGmmG9BZoKmqiv39fYrZ9wgSaETgMQZ/sIVGN8EfTuA4ztOgELvbNktk7DV9MAwOmiAIyOfzWF1dxfj4OG7dumUZJzzocJKj5qCFGasgBlVVm4IYeJ5vcRaM4STMWegHYTh3wuSghaGUjrUYWLlO8XjcMrhHP89N3/8JoKmMWP9nv92tsDlooigilUq1/Rpy0Lwj+FcA4sjCLv6yLDcFf/TLMTMjGo16FrXfSaCxRMZ8Po96vY65uTncuHHDlQVekB20g4MD5HI5rK+vY2pqCo888khLQEQ/tusEdg6bLZqtnI4gC7QwuB7dzHKzGglgTNDb2toCz/Oo1+uIx+OmpZK9loSRg+YfZFn2pCrDbdg106mosepzU1W1pf9TX0ZsdKPZn2650UetB01VVZqD5iHhOdOIIwMTZuVyGcViEefPn3ct+MMpsVjMdw6a00TGbvDSQet2u3t7e8jlctjZ2cH09DQee+wxZDIZW9/rhfhxmsoYZIEGBNvBcXvfrRL0JElqWZwuLy+3RJ/rBZzdgfJhEGhhctDCcBzsWu3WsbD01Ewm01JGbBxQv7GxoQ2oZw81jMLN7pxDRtgctE4pjmweHgk0byCBRgQGfRmjoihoNBpYXV3FxYsXPdsnP5U46hMZ0+m07UTGbrcdBAeNlXfmcjns7+9jdnYWV65c6VjW0et23cCp4Aq6QCM6E4vFLEcC6IUbe3hVrVbBcZyp42acWRUGgRYWBy2IISFmuC3QrOA4DslkEslk0rLPjX0+9vb2sLKy0jLn0DjPzWyfj5qDViqVAIBSHD0iPGcaEUqsgj8ikQgSiYRn5YUMP5Q49prI2A1eOmjsnGh3fKqqagO3a7Ua5ufncfPmza5LXbwQaOxY7RJkgRaGRbWXtIs+1y9OK5UKNjY2WmZWZbNZNBoN1Ov1QLs3qqqGQtgE+Xegh/Wfefn5btfnxuYcCoKASqWCzc1NCILQFGyiF26iKIbi/GJ0EmjlchnDw8OhEqVBgt51wpdYDZbW95d5PSga8LbEked5AMBPfvIT271UbuGlgwZYP2FWFAWrq6vI5/NQFAVnz57FzMxMzzdVr0oc9dvsdI4HWaABwS5xBPwpMiORiOUsN+PMqnq9jlwuh1wu17I4HVQIQ6+EyUELg0DzsxNoNedQVVXts6F33QRBgCRJeP311zE0NNQi3oLYM9hJoO3t7WF0dDQUn6kgQgKN8BXGwdLtgj/YhcXLsoNBlziqqoqdnR3kcjmt/OCRRx4ZeAyuVw4au9kbb/ySJGF5eRmFQgGxWAwPPPAATp065doix6sSR+M2290ogy7QgkzQ3nezmVU8z2Nubg7Dw8NN5ZJ7e3tNIQwfu/6/2t4On/2Pfh2CKWHpQZNlmY7DI/TjMvQoioLnnnsOFy5c0MommePGwnvMyiXt9oAOGtYq0slBGxsb8+X+HwVIoBG+wCjMAHQM/mAXFjvDFvtFLBYbSImjPpGxVqthbm4O169fx7//+797NoPNawcNABqNBhYXF7G0tIRMJoOFhQWcPHnS9RsK9aD1F1oAeA8TN2xxahwJMCTchgIF7FMQQeeFd5a/BQAQ1cNrZGPoNdf3W0+YnKcwHEe7iP2gwa7/4+PjLesNfXiPIAgolUpNPaBG4cZ6QL38HbN1S6ceNOo/8w4SaISn6MsYWXmK3Zh8NofMyz60fjtokiRpJXscx+Hs2bNNiYxezyMbdHkp25YgCMjlclhZWcHY2Fjf++68ED9HqQcNCJ4LFTbMPsuJynUoUBHnotA/nrASZ4ruq/RfE+feW2pUrgMA6tlf9eWzGoagE4AEmh9h6wyz47EK7zH2gLKRGfo+NzPXbRAPnFkiZbvzjASat5BAIwaOcbA0o5vB0oNysKyIRqNoNBqu/1y9M5ROp3Hp0iVMTU21vD9epUhalRr2G9Z39/LLL+PkyZP40Ic+NJDyTnLQiE4EXRjoz51Y5RoAQAEQ55o/33bEmf7/TYUafwMA8OuV/7en2POWfQiJsPFz75YTwiTQugk8seoBZX1ueuFWLBYhCAJEUUQymWzp/2Tz3Ny6ztipPGIljoQ3kEAjBoZV8AfQ/eLGa4EWi8VQrVZd+3mCIKBQKGBlZcVWIqPXpYaDugGXy2XkcjlsbW2B4zjcuHEDk5OTfd8uwwun0qwHrd0CNMgCLUziJqgw94mJM+BQnImq7iEaOMgGIRbnYi3iTI8Cpeln6F9fmPkf8Kvc002x58ZSsGw2a7uPh0JC/EWYBJqbM9D0fW76UmIALfPc9EPqY7GY6Ty3bvrc7Ag0ctC8hQQa0Xe66S+zS1hKHMvlMvL5PDY2NhwlMnp1/HoHrV+oqord3V0tEGVmZgaPPfYYXnzxRcdzzHrF6xTHg4MD3L9/H+vr60gkEk2L16GhIWQymUALNCAcIifI3Hrof0KGOxxDIapyizizQlQlKDj83RndNgCoq6L2d72bFkEEChTcOPc/oqbKiGbe0GLPeZ7H/v4+1tfXtZEAZkO4jX08VOLoL8Ik0AYVRpZIJJBIJFqGQ7M+NybcjLMOWeiP/vORyWQszyNRFDsez/7+Pi5cuODasRHOIIFG9A19GaNemLl5A/XaQetFILFExnw+3yRAMpmMo+174aCx32M/XCVVVbG5uYlcLgdBEDA7O4vr169rYShezSTzYps8z+OVV17B9vY2pqen8aEPfUhLEON5Hpubm8jn82g0GojH45BlGe+++27TQrbb2W+DJAyL6iDTOLiMOCKaIDMTWhGY/46YOAPQ8v16cXb4tYqpSEtxUaB6HdGhN0xHAuiFGzvvWR+P3k2o1+toNBqBFzhB339GWI4DcNdB64Z2fW7VarUpeXV7exuCIECWZdN5btls1raDNuiEaOJ9SKARrmI1WNptYcbwWqB1MwfNKpGxmzRGr3rQ2LbdFC2KomBtbQ25XA6SJGF+fh5nzpxpuYn4JfK+n+zu7oLnedy7dw+zs7N4/PHHkUwmIYoiVFVteboqiiLW19dRKBQAAJubm+B5Ho1Go8Vx87NwC7IDEsT9bhxcBgDEOyQy2hFneto5b1YiDQAilYegDL3RvO1IRDtn9aiq2rIwrdfryOfzuH//ftMQbv3C1O+OjrH8P8iQg9Z/9J8PNjIDOPx81Ov1pnLJtbU18DyvDdyORqN45513mhzpZDKpnXulUqnlXkMMDv+dbUQgcTP4wwleDooGnAkklsjIFtHGRMZ+b99t3OrLkmVZm2EWiUS098VqgeKVm9XvEjxVVbG9vY1cLoeDgwPEYjGcO3cOs7Oz2r9bEY/HMTw8jGg0iosXL2qvi6LY4jz4UbgFUdwEncbBZYiqggzXvAwwc8+cUlfff2gW51o/x05Fmhn6sq4TJ04AACqVCs6ePYvh4eGmIdyrq6vgeR6SJCGVSpn2ufll8c2ubWERaH58ENQNXjtoTuE4DqlUCqlUqqXPTRRFvPPOO2g0GohEItjZ2cHS0hKef/55/OM//iPm5uZw7tw5VKtV3Lt3D/fv38f8/HzPx//UU0/hqaee0tZAV65cwec//3k88cQTpl//L//yL/ijP/qjpteSySRqtVpP+xEU/HFFIgJLP4I/nOAHB63T9o2JjBcvXsTk5KRrPXhBddBEUcTS0hIKhQLS6TQefPBBTE5OdjxvvAjs6KcoZCWd9+/fR7Vaxfz8PG7evIlXX33V0Tli1oMWj8cxNjbW0ugdFOEWFILWP8fEmRFBlRA3BH5ELdwzGarWs9YOUVXaijRBVwapOXIHDyI1/JuOP7vlZ76Xfmi2MFVVFY1Go8lxYz1uZuc9E3CDnjPJrjNBEgNWsOHmYcCvDlo3xONxxGIxZDIZnDt3Tnv92rVr+J3f+R288cYbePvtt/Haa6/h6aefxle+8hVEIhFcvHgRly9f1v77+Mc/7qgEcmZmBl/+8pdx4cIFqKqK73znO/j0pz+NV199FVeuXDH9npGREbzzzjva/x+lh3nhONuIgdPP4A8n+DkkhCUyrq6uYmxsDNevX8f4+LirF5ggOmi1Wg2FQgHLy8sYGRnBtWvXcOLECdvvSxAi7+3ASl1zuRxEUcTZs2cxMzOjLQL6OQfNr8ItyCWOQUEvzph7JrzneJkJKTPk94QUE1d6oaZ3zxhse/qfz7apL5+MgNNEWu3gQdRUBWMj79raJ6B9iiPHcUgmk0gmk6YlwnrHTZ+cF4/HW0QbE279OFfZtS0Mn4OwjAsAguegdUKSpJZ+96GhIdy5cwd37tyBqqr47ne/i5/+9KdYWFhALpfD22+/rf33b//2b47H3HzqU59q+v8vfvGLeOqpp/DSSy9ZCjSO4zA1NeX8AEMACTTCEfoyxjfffBPJZBLnz5/37GYSi8U8tbvNBOL+/j5yuZyWyPjwww/bSmTsdvtBcdDYcOlisYjx8XHcvn27q/r2oIeEKIqiDR9XVVUTZsaHG17MQfNKuIVhMRqEY1gvX8KwbjcFEzGlx8o9M8KEWqevZ26afrsKVEuR5pRue7esznuWnMfO+93dXSwvL6NWq2kOhNF16ybyXA8L1gjC+dQJ6kHzL51SHEVRRKVSwdjYGGKxGC5evIiLFy/i05/+tCvbl2UZzzzzDHiex507dyy/rlKpYG5uDoqi4ObNm/jbv/1bSzEXNsJzthF9wyr4IxKJQJIkT28kfihxZG7i3t6elsg4PT3tOJGxG4LgoOkF66lTp3Dnzh0MDw/3tN0gCjRZlrGysoJ8Po9oNIoHHngAp06dajvXzMk2+xmz3064CYKASqUCQRB6Fm5BKxVkBGG/9eJMUFVkDNdtp+6ZGbX3wkFSbfrYyoqIuGHbViItxUVQ2r9o20Vzew6aVXKeLMtNwk0feR6JRFoS87LZLNLptK19k2U5FP1nQLiORZIkJJNJr3fDNTqlOJbLZQDA8ePHXd3u66+/jjt37qBWq2FoaAjf//73sbCwYPq1ly5dwre//W1cu3YN5XIZf//3f4+7d+/izTffxMzMjKv75UdIoBGWGIM/9MKM4zjE43HPmzW9FmjshvvSSy/1nMjYDdFoFPV6fSDbMtt2OwHBZpjt7u52NULAiqAJNEmStF67ZDJpu9fOCwfNKfF4HKOjoy1lLmbCTRAE1Ot1U+FG/W39xSjO7GDXPWPoe9pqqtxWpImq2heRNqj0w2g0iuHh4ZYHTYqiNM2qqlQq2NjYaJrlZnTdjLPcwhRNTw6af+kk0EqlEhKJBNLptKvbvXTpEn71q1+hXC7je9/7Hj772c/i+eefNxVprNyScffuXVy+fBnf+MY38IUvfMHV/fIj4TnbCNdgjpA+kZGJMv2iMh6Po1KpeLWbALxLcWRuCEsjmpycxNmzZwd+M/Kbg6aqKra2tpDL5VCpVDA7O4urV6+6+uQxKD1ojUYDS0tLWFxcRCaTwUMPPYSJiQnbT/itttmuT8svTk4n4cach62tLRQKBe0hw2uvvYahoSESby6yXr4EoFmYdeueOcFMpAm6+H07Io1hV6S57aA5JRKJYGhoyHSWW61WayoT3t7eBs/zUFW1aSQA+wyHQdyE4RgYYexBa3dt3dvbw9jYmOsPCxKJBM6fPw8AuHXrFn7xi1/ga1/7Gr7xjW90/N54PI4PfOADuHfvnqv75FdIoBEaZsEf7WrhvXavvNgH/aKbJTK+/vrrmJqa8uTi7UWiIUPvoOkDLxqNBubn53Hr1q2+LK797qDV63UUCgUsLS1hdHQUN27cwPHjxx0vHPsZEuIVVsKtWq3ixRdfxMTEBGq1WpNwC0qqpB97hnbKFwFwiHbZ02XEqrzRLBESaC55FExmo5mJtLLS/HWyJti4jiLNr/PDWNljJpNpmVXFhBt7cFEul9FoNPD888+3DBlmfw+KkxMmgRYmB421rHQqcTSWtPcDRVFsVwHJsozXX38dn/jEJ/q8V/4gHGcb0RP6mHz2BNLOYOlYLAZRFNt+Tb8ZlEBrl8j4m9/8xjOR5OUcuEgkokXl5/N5AO7MdrOzXT8Oqq5Wq8jn81hZWekpBMXJNo1f73eBZgVbKJw6dapp0SBJUpPrYBRumUxGc9zY370Qbn5930VwEJQohiPvXyON7llNVTUhxYhaXPozXc5I21UkpGwI2AOT8z0KVSfSgELpMubH3m75OtYr7UehbAXHcUin001lZFtbW8jn87h+/XrTuV8sFiEIAkRRRDKZNB0J4LeHFpTi6E/YSKROJY6jo6Oufp4+97nP4YknnsDs7CwODg7w9NNP47nnnsOzzz4LAHjyyScxPT2NL33pSwCAv/mbv8EjjzyC8+fPo1Qq4Stf+QoWFxfxx3/8x67tk58hgXZEcWOwdDwe99xB63fM/v7+PvL5PNbX1zE5OWkaK+tl1L9XDhpbOG9sbCCdTuPChQuYmpoaWP+HnwZV8zyPfD6PYrGIkydP4pFHHnEltdOp4GLvfdAWqYC1+xSLxUwdNzPhZoxFHxoa0hauXgk3L1kvX2oRZ0YOVMDuuyKrwMF7Qm448v5C1co9M1JTVVORxlw0M3HGYCKtph5+f7F0CafH3mn6Gn3VR5BhrhMbCWAMaWg0Gk0jATY2NlqCeYx9bvF43JNrAjlo/oStVzo5aL08YDRjc3MTTz75JNbW1jA6Oopr167h2Wefxcc+9jEAwNLSUtPnd29vD3/yJ3+C9fV1HDt2DLdu3cLPfvYzy1CRsBGOs42wjZuDpf1S4sicP7duzKqqagEXe3t7HQMuvI66H+S26/W6NnQ7Go3i+PHjuHnz5kBv/n4ZVH1wcNA0TuHu3bstvSe9btNpiSMQTIHGsHu8doXb9vY2FhcXW+ZZ6f8b9CDiQcDEmRHmRB289zbHTUoWrdwzPQdKq1CzQt/7ZiXSdmUVcZunbIpTUFNNBl+HZH5Yp3tZIpFAIpEwneWm7+/c3t7G0tKSNhLAzHFLJpN9e7/Y+iIsAi1MDpooiohGo21/98xBc5Nvfetbbf/9ueeea/r/r371q/jqV7/q6j4ECRJoR4R+DJb2S4kjcHjx7HWhpSgKNjY2kM/nUa1WMTs7ayuR0UuhOiiBpi/fY6Jsa2vLkzELrLRykOjdrHK5jFwuh62tLUxPT+PRRx/tyziFbksW/VpuNwhIuAFv7V7TwjnM3LODLk4P2eJ7DhQZIrim2WpOOXjvuYeocohz1jvXqdQxLA5atw8brfo79bPcBEHA3t4eVlZWUK1WEY1GTR23Xme5AWgKGAs67MF2mBy0Tseyt7fnuoNGOCMcZxthiTEmH4Ct/jI7xONxTfh59WSJbbcXkSLLcsvg4OnpadsXY68dtH6W+x0cHCCfz2NtbQ2Tk5NN5Xu7u7ueRPx7FRIiyzJ++ctfaq7q448/jlQq1bdtGnvQOn1u9Q5a0Oi3yO+3cPOLa3kozswfFskOY/PtIOocOTORZhbpb+Wi2YGJNOai6UXaUXHQnNJullu1WtXO/f39fayvrzeNBDC6bsaRAO1g98QwuE7sAWwYjgXonOAIHLZ3TE5ODmiPCDNIoIUQq8HSbgkzht698urCxXFc1w6WPpExlUp13UfltUDrx7ZLpRJyuRy2t7dx+vRpPProo8hmsy3bHrRQAgYr0FRVxc7ODt59913IsoyRkRFcu3ZtIO5KN3PQgGAKNMag990t4eZ1qTeDVxOaQGPu2YFyeJ3ORJqvE92WN1rBnDk7bhoTaQeGj3EnF00PE2lv7V7DwvFfNz2ADDKDCtaIRqOWIwH0wo3neW2OoaqqpkO4M5lMy32TDakO+u8DCJfYBOw5aKVSCZcuXRrQHhFmkEALEW4EfzghEolo5WZuzrlyilOBJggCFhcXsbKy0pLIOIjtu4mbAo2JkVwuh3K5jDNnzrR1ibwKKBmEQGPz3O7fvw9BEHD69Gns7+/j4sWLfd2unl560IKG3xZx3Qg3juPwyiuveFYq+dbuNYzrShqZMOsVq/JG0cKRY25ap4HYW3IUKc4set9cpO0o799jlPfCQjIREZnIYbkzc578di45xetB1ZFIRDt39aiqimq12tTntrOzA0EQoCgK0ul0k2hjPysMsIfQQT+3GHYEWj9CQghnkEALAW4GfzjFD0mOdgWSnUTGbvDaQWO/825/16qqYmNjA7lcDtVqFXNzc7hx40bHhaWXDlq/3m9VVbG+vo779+9DFEXMz8/jzJkzkCQJi4uLAy1lO4oOmt+xEm7Ly8tYX1/H1NSUJz1ub+1ea3LPjBjdMzPKOkF3PNrbNf1ABex4DTXVXKTp0QszI4ISRyYi4pWdW7iUeiEUC2ivBZoVrOwxk8ngxIkT2uuqqqJerzc9uCiVSqhUKpBlGT/72c9awkmy2Wyg+rnClEYJHIaEkEDzP8H5hBAt9CP4wyl+SHJsF3PPEhnz+Tx2d3c7JjK6vf1+o+/Bc3rDUxQFxWIRuVwOiqJgfn4eMzMztn9OmBw043tx7ty5pnlu+oHcg7pRH0WBFtR9j0QiiMfjOH36dNPrLKChUqlojkM/hBuvJjAeEWx/vZm7ph9mvSu//+8yOByPOA/lOVBilhH/ndw95qJZibMIp2ou2q58eC1frN9BJPJ/ON5PvxE0McBxHFKpFFKpFMbHx7XXt7e38dvf/haXLl3SXLf19XXwPK9V3Rj73Pw4yw2w5zgFiU7Ho6oqSqUSCTSPCc8Zd4RQFAWiKGoJev3oL7OLHwSa2T4YXaHZ2dm+9Q7FYjFPwjKA7gSaJElYWVlBPp9HLBbDuXPncPr06a5674Leg8YCYnK5HCKRiOV74YX46WZQNRBMkRMG58MMq4AGvXATBKEn4faLndtN/7+vJDESef96VFNjyODwQcqufCh44h1cKwYLFtlVDhfNTKhZlTcyWMR/O5H2/v6Zu2jrchpxzvr8ZyItxYmoqXHUVG9mfbmNoii+FClOYamHx48fb5nlJoqiaY+b2fnPRFwikfDs9xs00dwJSZI6tqWUy2WMjY0NaI8IM0igBQRj8Mcbb7yhBVt4eVPyS9Q+c3LYgrtQKHTlCnWDlyWOrOfCzvb1oSjpdBqXL1/G5ORk1+dPkB00SZKwvLyMQqGARCKBS5cuYWpqyvK9YIJtkILUaQ8a0H00v18I8r47oZNw0/f4sFlWZsLtnnI44JW5Z0ZxxmDCzIqoSWCIGUyoiWoUx6P2HkoZRZqZe2YUaTuKs3RUJtKOL/wvAH7t6Hv9hl9LHJ3STtTE43GMjY21CAB9jyd7cGGc5WZ03fo5y02/X2Fz0NrN7FRVlUocfUB4zrgQw0I/9ImMiUTCkxlURvzSg1av13H//n0sLi4imUzi/PnzXSUydrt9L9+DTgKxVqtpM8xGR0d7DkXRbzdoDpooilhcXMTi4iIymQyuXLmCiYmJju+FFwKtG7EVdIEWZNy4FjsVbvH3Qtb22/RpGbHrnlkhqoeL7l05aSrSzAZkd+ukiWrElov2/s+I48fbd/DYiRfbbsvPDLKMup904zpZ9XjKstx0/pdKJRSLRVSrVUQikZZEyWw2i3Q67dr6KIwOWjvBeXBwAFmWW5xPYrCQQAsAzDVjbgnHcYjH4+B53utd81ycVKtV7O/vo1Kp4NixY7h69SpOnDgxUOHqpYPWbvs8zyOfz6NYLGJiYgIf/OAHXS1ZCJKD1mg0UCgUsLi42JVI9arE0bi9TvsbVIEW5PJMoP/7bSbcWGljHOafwR0lgyzX6HqbduamWYk0Mw6UmKXDp8fonnUSaQzmovVyzH4gLA6am0IzGo1ieHgYw8PDLdvQD+E+ODhomeVmdNyczHJjhNFBa3c8pVIJHMe5EqJGdE94zrgQY3YxicfjnpcWAt6VOOoHKGcyGUxMTODmzZsD3w/A25AQtn29UCqXy8jn89jc3MTU1BTu3r3btpyhl+363UHTu4fHjh3D7du3uy7bGPSAbKc9aOx7gipyCPv868bvYsLk7s3Ez45iPwTJbnmjFax80q5QayfSVuVhpDhn9xOjiwYg0C4aexgbdAZxHJFIxHKWW61WaxmJwfM8VFVFOp1ucdwymYyloAybg9YpxbFUKmFkZCRUxxxESKAFALOn5n7o/QIwUCfPmMg4PT2NRx99FJubmyiXywPZBzP0PXBewAQim2G2t7enpVWm0+m+bdcrB82OMBQEAblcTnMP3Rip4IVAOyoOGhDeoJB+MBHbN329kzBzq7zRjF05aRnzDzSXYdpx0pq369xFC6pIC4uD5qWoYWWP7OEtQ1VVTbgx5213dxc8z0OWZU24GUsmu0lJ9jOdHLRyuUzumQ8IzxkXYswWLn5y0PrtHrFExnw+D0EQMDs7i6tXr2opRH5zsAYJG7XwzjvvoNFoYG5uDtevXx/IcNxoNKqF1wxycd1OKFUqFeRyOW0mlZvu4aDFD4WEBItBfQb07pm+vFE0TB7rd3mjGSUljbFI1dbXGkUaE5c1NW7LRduSmz/XsnooakYiNbu760tIoPUPjuOQTqdbHlyqqopGo9HkuBWLRfA8D0mSEIlEkEwmoShKk3ALYtomC5vr5KCNjY3RQzOPIYEWUPwQakdrGQAAIABJREFUzgH018mzm8joFwdrkCiKgrW1NeTzeVSrVZw8eRJXr14d6FM+togY9NNFM4G2v7+P+/fvY2trC6dPn8ajjz7q6qw7q+32k25LHInBMyhheSjODt2zAyWN45EKAGBXGcKwTWHEYAInoitxPBmtdL1vNfVwsepEpLX7WUaRpnfRjOJMz76SwkikBl5JBtJFC5NAG8SDQjfgOA7JZBLJZLIpGENVVYiiiF//+tdIpVLaw2Ke59FoNJBIJEyHcMfj/h35wNZK7cQlzUDzByTQAopfHLR+CMVGo4Hl5WUsLi4ikUh0TGT0OqgkFotBUZSBOEmyLGNlZQWFQgEcx+Hs2bPY2NjA8ePHB16CYRziPCiYs8SGaeZyOezs7ODMmTN9LevsRjD1uj3jwp8dd7vv8aIv0A38uqDxI0ZxZoeS0vq5iBj6zzbfEz7Kew7ahE6wtStvNNuWXqRZpUwyF81Jz5yVOItyiuaibcrDpl8TBMKS4hiG42CJ2ZFIBOPj4zh16pT2b6IoNiVLbm9vN80yNBvC7eUsNwZbK7X73ZRKJSpx9AEk0AKAVYmjoiielxG4KY6q1SoKhYIWB283kdFrgdbNsGiniKKozTBLJpO4ePEiJicnEYlEsLOz41maIoCBb5udDy+//DL29/cxOzuLhx56qOPgzV7ppuRw0NujEsfw8q8bv4tURMSBTmgxcWZ0z3gliWz0sMSRiZVEm/4wPYquvJGJoYkunLVenTQzF60ojSFu4zhYL1oQXbQwOWhBF2gMs3t7PB43HQlgHImxt7eHlZUVVKtVRKNR0yHcqVRqYMKNlTe22x45aP6ABFpAYRcLURQ9F2i9Onn6RMaTJ086joP3i0DrRxRvvV5HoVDA8vIyhoeHTUWrVz1wHMcNtOxPVVVsbW3h3r17AICxsTHcvHlzYH0AXoeEqKqKnZ0dCIKA4eFhZLPZls9+0AVakOnnAutfN3635bVOzpmbLtKWPISGGsPJ6IHpv7PyRiMlJY0I2n9mCtK4rfLMLXmk49foXTQ9/7rxu/jE5H/v+P1+IEwCLQzHARze2+2us6xmGepnuQmCgHK5rM1y4zjOdAh3KpVy/T3slOAIHIaEuDmSh+gOEmgBwOzGH4lEEI1GIYoiUqmUyXcNBiaOnJb3qaqKvb095HK5pkTGbDY7sH1wi0gk4nqioSAIyOfzWF1dxfj4OG7dumX5RMuruHtgMEmOqqpifX0duVwO9Xodc3Nz2N/fx/z8/ECbtAftoLFyRSZM79+/D0EQkE6ncf/+fUiS1BQXnc1mNVc9iHhd+tMLgzgvUhF7D8K2pBFkDAmJZu6ZsbyxHQ31cKmwKQ9birReOFDSpiKNuWh6cSaqMccumpWA9CNhETZhd9Cc0m6WW7Va1Ry3SqWCzc1NCIIAVVVNh3BnMpmuzxE7D5JLpRKmp6e7+vmEe5BACzB+6ENjC2S7FzB9IiPP8y2JjN3A0gS9rHl3Kyjk4OCgKYXwzp07LRd0s217tSjvpzhkQSi5XA6yLOPs2bOYmZlBJBLBb3/7W09KKwcthCVJwosvvoharYazZ89ienpaW8DpU8cqlQr29vZQq9XwxhtvNN3Uh4aGuh7QOmjI/WvFzD3Toxc2W1Jnl6kdio30RubM2RVqJSWDsYhg+m96F9BKpDnFykX7/9Z/D/956tmef34/YT2mfv+c2iFMAs2Jg+aUSCSiXav1qKqqCTfmvG1vb0MQBCiKgnQ63eK4tZvlpj+WTmu1/f19KnH0ASTQAoDVk2U/JDnqSy3bfehlWUaxWEQ+n2+byNjLPnh5Q+g1SZK5iTs7O5iensZjjz1mO4UwGo2i0eg+UrsX+uGgsfTOfD4PjuNw7tw5nD59umnRMuhyw0Fukz3EYKMTzp07hzNnzmhCXJZly9Sxl19+GdPT00ilUqhUKuB5Hjs7O9qAVivhFmT3Ksx8e/U/YcpwiSzJGYxF3xc8RlFmdM/6BXPT2rlT+8phdUc7kdaJZXG8xT106qJlInUIFkElfoJdX8IgbMIi0BRFgaIoAw/h4jhOm+WmR1VV1Ov1ppEApVJJGwmQSqVMkyXZ/kuS1LHyhEJC/AEJtIBg1lvih2HVHMe1dY/04RaJRAIPPPAATp065eoTwkgkAo7jIEmSZ7G+3bhYqqpie3sbuVxOC7u4cuWK45LVsDhokiRheXkZhUIB8XgcFy5csEzvDKNAU1VVcwwlScLU1BSKxSLm5+cd7WM8Hsf4+DjGx8ebfra+jIbneWxtbYHneW0hoBdtg25cB4Jd4gj0Z/+nYmUA75c3GsVZtzgpb2zHpjxse+6YUaSZ9dAZXTQmPmtK3JFIa+ei/U7i//FNop4Rdn0Jg4MWhhRH4P0QLL8cC8dxSKVSSKVSLdd4VlXBHLf19XXwPA9RFJFMJrWh2xzHoVQqaSMBjFBIiD8ggRZg/FDiyPbDKNC6TWTsBo7jfBEUYnf7Zj1VvYRdeCnQ3HDQmIgvFApIp9NYWFjAyZMn254rXgi0fgVwsFLO+/fvQ1VVnDt3DtPT0zg4OECxWGzZh077aPa+6J/GTkxMNG1bL9wODg6wvr4OQRCaSm/0rls/F7ZBLXHsx34z94xXkkhFRJTkVkd9RxpCtoNjZje90QrWf2aFVV8ac8+8oCgewyQTtwYX7b9V/whnfvWniMVimsugfzDhpXALk0ALi4NmJ5beD1hVVQCHo4uYaFtdXYUoinjzzTe1kQD37t3DCy+8gAcffBBXrlxBvV6nkBAfQAItwPhFoOmdPJbIuL6+jomJCceJjL3sg9ez0DoJFUVRtNI9RVG0nqpeL/xBddAajQYKhQKWlpYwPDyM69evY3x83NbiKAwOmqIoKBaLyOVyANBSytlObFnhVERa9T8oitIUFV0qlbC6uopqtaotbM2EWy/4zc3wmuH3hi1HOcW2OOulvNFO/5kRVt5oNzzETqkjc9GMpZt2XLSi+P5T/w1pVHPRjsfeHxMwHK3hIx/5iGUUeiwWa3KUmYAbhHBj7kbQPwte94S7CROaQf6dJBIJJBIJjI2NoVwuI51O4+zZs5AkSRu6nclk8KMf/Qjf/OY3sbGxgU9+8pO4evUqFhYWsLCwgMuXL2NhYQFnzpxx9F489dRTeOqpp1AoFAAAV65cwec//3k88cQTlt/zzDPP4K//+q9RKBRw4cIF/N3f/R0+8YlP9Po2BA4SaAHBbOHlF4EWjUZRKpWwvLyMnZ0dnD59Gh/+8Ie7SmTsFq8FWjsHzVi653aZZ9ActFqthnw+j5WVFRw7dgw3b95seeJnZ7teOGhubJMJ9VwuB47jLM+HbueguUEkEsHQ0BCGhprL0FhUNOtv293dxfLyMmq1GuLxeItosyqhsSKoDprb/NPyf8Gkyd2ZlTfuSPaGU5uxLo0hAkUrn3QLJyJNgfsOkV6cGdmVhrRB28PRGv6v9f+Mz07/15YAJn0Uejvh1i9HOUwR+0B4nMBB95/1E31ISCwWw+joKD760Y/iox/9KIDD+/PJkyfxzDPPYGtrC2+99Raef/55fP3rX8e9e/eQyWSwsbFhu0d+ZmYGX/7yl3HhwgWoqorvfOc7+PSnP41XX30VV65cafn6n/3sZ/jDP/xDfOlLX8InP/lJPP300/iDP/gDvPLKK3jooYfceyMCQHjOuiNIPB4Hz/OebZ+FGbDSqPn5+YEMDDbDrRTFbjFz0BqNBhYXF7G0tIRMJmOrdK8bguKg6UcHnDhxAh/60Ie6bkT2ykHrRUCw8JNcLodYLIYLFy7g1KlTludDNyWV/Z6DZhUVzYazMuG2vb2NxcVF1Ot1JBKJlv42fdN6GHB7xMdkbN/0dafCbFdu/Xo2l2xdav7sKYhgKlZqeq1TeaMRJtI6lTfuyymMRK171wqNCdPSTTMXbbkxjihnfi2w6kUbtti21fltFG5GR9ko3LLZLJLJpONzImwCLQwOWj8THL2gU4pjqXR4DTALKqvX67h//75tcQYAn/rUp5r+/4tf/CKeeuopvPTSS6YC7Wtf+xo+/vGP4y/+4i8AAF/4whfwwx/+EP/0T/+Er3/967a3GwbCc4cMOWYXeq8cNGMiYzqdxsmTJ3HhwoWB7wvDDw4auynp++/GxsZw48YNHD9+vG8lEn530CqVijY6YHJy0tbogE54MfutW1EoyzKWl5eRz+cRj8fx4IMPYnJy0lY/md8EmhVWw1lFUWwKJtnY2EClUtGa1vWiTVXVwM5wcxO9e2YlPAC07T3beE98xTl77ydztNal98vRjWLNLpvyMFKc9X3JrFzTDF5Jduyvc0KckyGqURzIKQxHa/jO6qfx2en/aut7uxFu0Wi0RbR1Em5hEmgcx4XmWML0MKlTimOpVEI6nTYNK0smk1hYWOh627Is45lnngHP87hz547p17z44ov48z//86bXfu/3fg8/+MEPut5uUAnPWXcEGXSKo1Ui49tvv+3ZoGRGrzH3bmy/Wq3i9ddfx9raGiYmJnpyiJzgVwdtf38fuVwOm5ubrpe9BiEkhJW25vN5pFIpxw4q254Td8YrgWZFPB7H2NhYSx+qfoYbz/MoFouQJAmvvvoqUqlUi9uWzWZDsdjrxLdX/xMA814+MydIz4GSwoGLwRzr0hhkNYIJCzevXbz+rjyE49GK5b8D1i5aJ5dQ76Kti52vr2Yu2oaN77OD28ItLH1bYTkO4Gg6aKOjo64+UH799ddx584d1Go1DA0N4fvf/76l0GMPcvVMTk5ifX3dtf0JCiTQAoKXDlqtVkOhUMDy8jJGRkbw0EMPYWJiQtsnP/TCeemglctlbG5ugud5TE9P4+7duy29O/3Ebw5aqVTC/fv3sbOzg5mZGTz22GNIp9Oub9evDpokSVhaWkI+n0cmk2n5vNiFfX2QBZoVrGldH+X84x//GJcvX0YkEmkavs3zvObUB3H4thMEJaGVN5bljBZusSsNYbRNvP66NOqq26RnSxqxFGlmsHljdkRaJ9q5aHpxJquRtm4jg7loLNHRiYvmhG6FWzKZRKPRwNLSUk+lkl4jy3JoPpdhdNA6CbSxsTFXz7lLly7hV7/6FcrlMr73ve/hs5/9LJ5//vme3LijQHjOuiNIvwdV201kjMViEITeZ/P0wqAFmqqq2N3dRS6XQ6lUwsjICDKZDK5evTqwfWAwkeR2H4wdmINmfD9mZ2f72o/oR4GmHxeQzWZx7dq1nkZLsAWOE8EVFIFmBpvhNjo62hQaox/M6tfh22589v5p+b9ofzeKMyMHSkoTLsZeMoZZeSPrP7OD3nViiYpOhBrQKtKM5Y1GF81uj12hcaJtGaVdBj28upNwW1tbw+bmJkqlEorFIgRB6KpU0mvCErEPhMtBU1W1o0Arl8uuJ28nEgmcP38eAHDr1i384he/wNe+9jV84xvfaPnaqakpbGxsNL22sbGBqakpV/cpCJBACwiDctBUVcXe3h7y+byWyNjJEfK6/4vtQ7Va7fyFPaKqKjY3N5HL5SAIAmZnZ3H9+nVsbGy0XFQGBbvYelFWwnEcDg4O8POf/xyVSgVzc3O4fv163weG+ynFURRFFAoFLC4uYnh42LWeQ72D5uR7girQAPNjbTeY1e/Dt52S4iSUTXq0zNwzvTDrxT1zkqi4JY1gOOrudbZTYIjdXrR2Lpq+zHFQLpoTmHCrVCqoVCq4du0agFbHrVwuB0K4hUmghclBY+s0OyWO/URRFNTr5p/pO3fu4Ec/+hH+7M/+THvthz/8oWXPWpgJx1l3RInH41AUxZWLoV548DzvyAHpt5Nnh36nOLKZVfl8HpIkYX5+HmfOnNEudF6XGQKDvSmyBM9isQhRFHH+/Hncvn17YDcyrxw0/QMRNsdtcXERo6OjXY0LaAdbZDk5zqALNCcEZfi2HfTuGcPMOfMDB3LakUizW+po1z1jwrSmxgPporXDGBLSznGrVquoVCoQBMF3wi1MAq1TqEaQkCQJHMe1/d2USqWm0vNe+dznPocnnngCs7OzODg4wNNPP43nnnsOzz77LADgySefxPT0NL70pS8BAP70T/8UH/nIR/AP//AP+P3f/31897vfxS9/+Uv88z//s2v7FBRIoAUYthgWRbHri6F+eLIsyy3Cw+5+eC3Q+rUPLIGvUCggEom0DBPWb9/LoA4AA9m+oihYW1tDLpeDLMvak7Zz5871fdt6upm/5sY22ZM/NmD72LFjuH37tqs3NP32gKPjoLm1724O347H4567EUY2pBFkIo2+bqNTIAkL2ZiMN89SsxI7u/JQ2/LKfbl9uAlz0azKORl2XTQGc9H+98KT+N/m/8+2P3sQ2K2CiEajpnMK2TluFG7VatX04US/hFuYBJosy673UHsFK29s9/t2u8Rxc3MTTz75JNbW1jA6Oopr167h2Wefxcc+9jEAwNLSUtN66u7du3j66afxV3/1V/jLv/xLXLhwAT/4wQ+O3Aw0gARaYDD7QEUiEUSjUYiiaBqJ2g5RFLG8vIzFxcWehycPOk3Sah/cFGj6fqJ0Ot0xGt3LOWwszrifgkU/XBk4FGTT09NYWVnB1tZW37ZrhRcOmizLKJVKeOGFF3D8+HHLnky3OIoljv2kn8O3e+lBY+5ZijO/fujLG+2Ks177z9ohKO+XL2+Ioy0izYpOTlpZzrQNQjHDiYtWbByDgsPf0YlY54HaXtBrzL7VOW58ONFv4UYpjv6kU/8ZcOigzczMuLbNb33rW23//bnnnmt57TOf+Qw+85nPuLYPQYUEWsBxWl5oTGS8cuVKVwlzvexDP3DLwdK/P+xpj52gBy9LHPu5feMMrwsXLmBqakpbRHjhZLHtDkqg1Wo15PN5LC0tIZFIDGx8wlErcfTKqXJj+HatVuv7+74hjZi+Pqj+MyuciDQrti2OTU+uMWFLnOpdtGKj2dmOQIUCDtvScJNIG47WfOGi9WsOmlvCLZPJ2OrjpBRHf2JHoJXLZU/CzohWwnHWHQGsLoh2g0IqlQry+bw2o8vNsiwmjrwcstmrg8bzPPL5PIrFIk6cOOHYHfG6zNPtwc2SJGFxcRGLi4tIpVK4fPmyqYPoxcBo4HDB0e/3u1qtIp/PY2VlBRMTEzh79iwODg4GIs4YTgVXkAUa4Mwt7DdOhm+Xy2UoioJSqWQ6w83qCfxf3fufMZUEylIGqbh5QqKVMPMTG+IohtsEfbD0xkG6aEZxZmRbGoaoHP5eRmP9D5iyw6CFTS/CLZPJYGhoSAvj0Qu3MJU4hslBE0XRloPWz8oQwj4k0AKE2eKrU3nh3t4ecrmc7UTGbmAfeEmS+p7e124fulmws2HKGxsbOHXqFO7cudPyJN0OzMHyIupev/1eaTQamjAbGhrC1atX2zqIYXTQBEFALpdDsVjEyZMntXNieXkZ+/vOYsZ7JRKJHCmBFgTMhm/ncjlUq1WcPn26afg2z/OQJMl0+HYmk8FU8tB5mnxPnG2LQzgR7212GAAUxeYFVhTm54QMDqfjpebXOvSfWWHXSetmPhoTqYKSsOWirTSOI2JxzMxFM+IHF83Lh5x6uhVuTKxVq1XE43FUq1XfJ6d24ig6aP3oqSacE46z7ghj5qCxRMZ8Po9KpYIzZ87gypUrjvvU7BKNRsFxnKcCjfWA2RVIbGbX7u6uNkw5k2mNt3ayfcC7i3mvAq1eryOfz2N5eRljY2O4efMmjh07Zqu00ysHze3t8jyPXC6HtbU1TE1NtTzM8Cra36lA8+L34QZBXsQBh5+FY8eONS1uVFVFo9HQFrT64ds/nP6/m9yzbbH1wVlNbb6WtBMnzDGKR5w9qNKLOaNYM6LvP3MLY3ljry7ammj/6X88IkNUoihLaV+4aIqi+Dox0K5wK5VKEAQBL730UpNw0/8XFOEWJgetk0BTVZUEmo8ggRYgzBZreoFmFgU/iOhzjuM8L/Fjx9hOIKmqiq2tLeRyOVQqFczOzuLq1auuDFO2s/1+0q1A05fxdVPaGQYHrVKpIJf7/9l78yBJzvLc98nK2rt6memZnt6ml2lJI830rJqRZtEM8ol7MWDHOdhxuRGO6wvYF+NzjuCaA9dEQGDHCeOwzMUG7LCNLCuMAo5lhxcQN+Q42GBCyAKJkASIGYmRupbunt7Xqupac71/VH85WVm5Vy5VNfWLUMD09PSXVZWd+T35vO/zprG2toaRkRFcvXq1IQHQ6TXNoiXQtB5EtLuD1q7HrnXcFEUhEokgEonUjWD4TPLDiNEsclztoRARZ3L3bJ3tQ39QX6jkuDhysPdgiVdxkVbYAQhiACMGQk0JSW9Uc9GUw6kBay6assRTz0WzIs4a/i1TK13200VrFQfNKkrhVi6XkUgkcPTo0Trhls/nsbq62uC4tbJw6zQHzegBQLfEsXXojLPuLiYUCqFarSKdTmNhYQHBYBDT09OqUfBu4neSo7zMUnkxFQQBa2trSKfTYBgGU1NTePDBBx19UhkIBEBRlK9R+1bWlrtF8jI+O+v64dg4se7e3h5SqRQ2NjYwOjqKRx55RNdF9UP8WHXE2lmgtdKmzEtolXTFdda472yD6UPEoltmllV2wLJII1gpdRQ0yintuGhKBFCWyhzjAcYVh9AKnZJ+SHrQzDpurSrcBEHomM8EqO2P9O5xgiAgn887Os+zi326Aq2NqVQqyOVy0hMPJxIZ7eJ3kmMgEGgIjuB5XprxBgDT09MYGxtz7WLrp4toVqDJRYmeW2SWdnTQ8vk8UqkUNjc3MTY2hmvXrpmac+PXcOxuD1p7YPa6+5nkhzX/Ti7MlO5ZgYsiHmawwVgLDdHqP1NDLpiIG2VHqDmR7AhoB6SouWiZ6mFEA9YfEpIyR0KB928uWrs6aEqMwk7aRbiRe1snOWh6ryWXy0EUxW6JY4vQGWfdXQK5CMkTGXt6etDf34+HH37Y12Pzu8SRHAPP8+A4TpphFg6HG6Lh3cLPqH2jtbPZLNLpNLa2tqSeOyeGb7ZTD1oul0MqlZLeg+vXr1vqy/Sjv8uO4GpngdbOx26FGG2v2sBInFntPzPDKjtgy81aZ/sRMRBMOT6Gflq99yunUhqpxSqjXpJl1UUjbDLOBmmZpVPi6e2mOLaacCN7mk74TADjFMdsNotAINCQXNvFH7oCrY3I5XJ4++23sbW1JSUy5vN5LC4u+n1ovpc4AjWxMD8/j83NTSQSCczOznrqKPo5rFpLoO3s7CCVSiGbzeLo0aOWRYkRxOHx+smvFYGWzWaRSqWws7PT1Htg1c1yAqVAMzqX29lBa+cSR7PvudI9k5c38hZnkjVT3qjWf6ZHjo+jIoRUXTHSf2aVXc6+c19bt9FFqwihplw0eZnjb7/9X/H5+/6iqWO0Sic5aE5WqhgJNzKvMJ/PY21tDaVSCRRFqQ7gtiLcSP9ZO1+b5Jhx0Pr7+zviHOwEugKtjSiVSujp6cGJEyekDWa5XPZdGAH+Omgk6KJcLiMYDJpOIHQap4Zl20FeaiiKIra2tpBOp7G3t4fJyUmcOXPGlYRNchNuRYG2u7uLVCqF3d1dTExMYHZ2tqlAGL9CQpRr6p3XfohIJ2nnYzcLcc+ybAyDoaLh969Va+EVCdr+QGqnsFq6uMX24lBoT/d7tFw0EpySCGrPVwO03bNmiNEsyrz3aYpdgWYNuXAbGhqSvi4IAsrlspScure3Z0u4dVKCI2AcEtINCGktugKtjRgdHa27CAH+9375eRx7e3vIZDJYW1vD0NAQent7MTU15VuDq58ljsFgEJVKBevr60ilUiiXy5iamsL58+ddjW0mmwmvk670xJLcNZycnMTp06cdEaet4KA5/f1dnMPogZBe79k224OB0B2RQvrPvBRnWoEdQM2ZIpgVaXt87SFiMyLNiPnKoQYnUemiNRMW8pnkh/H79zxp+bjs0ikCze9gDTJMu6enR1O4FYtFQ+HGMEzHCTQjB21gYKBjHMN2pyvQ2gi1Xxq1OWh+EAwGUa1684RX3k81OjoqBV289tprvopVv0ocBUFAoVDA9vY2tra2MD09jfHxcU8EE9lM+BGeIV9TFEXs7OwgmUy65hr60YN2N4WE3E2bArl7phRnwB1hZgW1/jMrASFWICLNbHmjUqQZlTfKZ8IVuKihi2aHlf33mAjTw+F6EemHi+a3sHEKrxw0q8iFmxw94SaKIl555ZWWSJVsBkEQDB+k7u7udh20FqIr0NqcUCgk/eL5eUEMBoMoFMzNtbGDKIrY3t5GOp1GLpdT7SXys8TQj/UFQZBSKlmWRSwWw+XLlz19AktRlC9JjkSgkXLOVCqFYrHoqmvYSnPQ9GhXgQa077EbHfeH3/gEhiJAVQiiKty57W6z9vqwvOw/02Kd7Ucv7ZxwsuqikcCUqhA0fD/kLtqKQvwGKAGCGMAm0wtW5iIS0fyf3/w4njjxBdPH1Qyd4KCJoth2YSdawm15eRmrq6uYmJjQddzi8TgSiURLCzcziZTdEsfWoivQ2gi1X3ryy8ayrK8Cza0SR1EUsb6+jnQ6jXK5jMnJSZw9e1bVGfE7SdKrEkee57G0tIRMJgOapjEzMwOe57G+vu7LTdGPJEeKosBxHF5++WWUSiVMT09jYmLCVdfQrxRHpVNYLBYRiURURWg7O2idTE+QQZGPIEjduT5oibMtJoGeFug3M8MG24ehUN7U95opddTCqoumFRaiFGdKQpRQJ9Lspm3apd2EjRrketWKDppVeJ5HJBJpaC1ROm6FQgHr6+t1wo0kSyYSCcTjccRiMV+FG8uy0gNVLfL5fFegtRBdgdbmBAIB0DQNlmUdTeezitPiSBAErKysIJ1OQxAETE1NGZbttYJAc3N9+fiASCSC+++/H0eOHAFFUVhZWWmJgBK3EUURGxsbePvtt8HzPIaHh3H06FHPyjlFUYQoip7daIngEkURm5ubUgmnKIqIRqPSBoD8L9C+LlQrPnVPr0KlAAAgAElEQVS2gtbxf/iNT6DH5OmpJs7M9p+tVBpnFwWoxgcKghjAaHS34WtayPvP1FATaaT/TMkW2wta5ZgIOT5WN5NMc02Ls+BWKrVNp9r7ocVapQ/D0drr8spF6wQHjdwLOkWgqb0Os6WSesKN/OeVcCP9Z3pr7e7udmegtRBdgdYBtEJQiFMx+xzHSe5QMBjEsWPHMDo6auqm5WUfnJfrMwyDhYUFLC4uoqenR3V8gF/zyLxamzipqVQKDMNgfHwcqVQK09PTrq4rh5yDXgs0MkqDBL+cPXsWPM/XbQJ2d3dRLBalJ/A3b96sE29+P701S7uKSz16grUoeLl7JoeU0m3ZmL1FHKGQivDQEyNEzCmFmhXKwp0qBitOml30XDS1MkcrkfukzFFOlGaxVulDf6iMXhd64JT4Ma7EDYhAa/fXARiHaiixK9zU5rg5fc0281ry+TympqYcW7NLc3QFWhuh9cvaCkEhzYpEhmGwuLiIhYUFxGIxPPDAA5I7ZBY/55C5sX61WsX8/DwWFxfR39+Ps2fP4uDBg6rviZ+v3U0HTRRFrK6uIp1Og+M4KQCFZVmkUilPNzTkffdiTdJbl8/nkcvlcM899+Do0aOSW07TNCKRSF1iqSiKuH37NlZWVpBIJFAsFrGxsdHQLyF33MLhcFsIt1ZHS7SruWc5NoZ+WShIM8LMKkoRQoQaDwpjkaytn0kwK9K2mQQGw9r9ynkuhr6gei9agYtik+lFT9D8gzDinplFWeZIPi+3XTTycKLdnScSdNIJ1xWe5x3pZ24F4WYUsQ/UetC6Dlrr0BVobYZaj0krDIm2W15YqVSQyWSwtLSEgYEBnDlzBoODg7YuQH6XODoVEkLmui0tLWFwcBAXL140rAvvNAdNEARJmPE8j5mZGYyNjdXF+pPv80qgyR00tyDCLJlMolQqIRKJYHx8XHIK9damKArRaBTBYLDuKSjZBBQKBRSLRWSzWSwvL0tzA4lgk4s3N0cz6B1/JzpoAJBjYhiM1ERJf8h6nDxhpdrfVECIHsvV2jWmGaG2wfYhphgeLSfLxgFoi7RtG2KVoOaiZUr1MfyCGNB0FrVctMp+kmOJc36OpBxyDW1356kT+ugIHMchFou59vO9FG5mHLSuQGstugKtA2gFBy0YDFpKkywWi8hkMlhZWcHhw4dNiRAzx+BnimOzISHy92RoaAiXLl1CX5+5Xgs/Z7A56aDJew9FUcTMzIxqiasf8f5urqkUZiT05MaNG5YfVihFjtYmQFkmubW1hfn5eTAMg0gk0uC2xePxtn+67ybKz6nmntXEChFnSveME+vfT2X/WZ6LIkFXbTtmZlCmOi5XBySRZtR/5hZaLtom0wsAKHIRQxdttWL/PVNz0QB3e9E6SaB1ynXC6/meBDeEm5FAE0URuVwO/f3uXWu6WKMr0NoMtafMrSDQyBN3juN0L865XA7pdBqbm5sYHh7GlStXpHCDZvHbQbNbZri3t4d0Oo319XXb74mfAs0JB42MDEin06AoCjMzMxgZGdHcrPgh0MgG3EmXR0uYkRupm4OqaZpGX19fw0MAlmUlt61YLGJlZQXFYlF6miwXbWQD4MSmshNKotQg7hnZ5FvFTPKgEithGGosVwfACEGMRNQHUsv7z5RsMgkc1ilhJChdtGbcM4KpyH0dF81PyPW73X8POkmgGe1nvKYZ4SaKIgKBADY3NzUdt1wuV1c238VfugKtA2iFkJBAIIBAIACO4xCJ1A8vJUOE0+k0stksxsfHce3aNcdLB/wWaFYdPLlYHRsbwyOPPIJ4PG5rbSKSvAywIDTjoPE8LwkzmqZx7733YmRkxPA1BAIBz2PvKYpybE0jYSZf0+tB1aFQCAcOHKgrdRFFEdVqtW4DsL29jWKxCFEUG0ok7c4DatcSR+Vxf/iNT4ATaOSY2jWOiDO5e7ZdTaA/rF3uuFHtRVQR895MeaNeUqMWq9V+TZGmh1mRpodeLxqg76LJ3TMzoo2gV+YYpVmUuLBrLhop1+4KtNbBLwfNKkbCrVQqYX5+HjzPI5PJoFgsgqIo/PjHP8b3v/99HD9+HCdOnIAoiqardrq4T+ufeV3qULt4h0IhFItFH46mHqVAItHgZIjw5OQkzpw5ozrDzI31vcasi7W7u4tUKoXd3V2Mj483DNy2uzbgzw3FjoPG8zxu376NTCaDUChUNzLALH4Mjm52TTJwPZlMolgsGs5vsyoI3erjIv1t0WgUg4OD0tdFUazrb9vb28Pq6irK5bK0aVA6bm79/rcqwUDjNWG72ugWycsbN6q9rh6TEYxsmLYVkVaQ9WkpRRrpP5NjFBgih5Q3GrFQOoiwyntuFWWZo5xiseiYc0zohARHoLMEWqs5aFaRC7eNjQ309PRgamoKgiCgUqmApmlsbGzg1q1beO6557C9vY0LFy7g/vvvx8mTJ3HixAmcPHkSJ0+exLFjxyy9F48//ji+/vWv49atW4jFYrhy5Qo+97nP4fjx45r/5umnn8av/dqv1X0tEomgUnE/RbUV6Qq0DqAVQkLkx0ECHjKZDFiWxdTUlCezqoiD5YeLRNbXEohkY55KpbC3t4eJiQmcPn3asc2qnwLNioPGcZwkzKLRKE6cOIGhoSFbn5cfAs2uAFIKs6mpKVy4cMHwsyKz19w+PruQ8hml88vzPEqlkuS27ezs4Pbt26hUKgiHw6qOW7s7B4Rfff1TiGt8rHJhpuaeyYWZ0j1zA2X/mRZ2nTQz6JU2NuOiyVG6aFbLHJVhIR946w/xWO4/1PX8NDvSolMEGklx7ATaxUEzgzzFMRAIIB6P49q1a7h27RoAYHl5GQ888ABeeeUVJJNJvPHGG7h58yb+/u//Hrdu3cKhQ4ewvLxser3vfe97eOyxx3Dx4kVwHIdPf/rTeOc734k333yzwemT09fXh7feekv6c6fcF+zQGWfeXU4r9KABNYGyurqKmzdvIhAIYHp6GqOjo55drMmF1EycrBsQB00uEMlg5XQ6jVKphKmpKZw/f97x4yOlMX70oZlx0MiQ7Uwmg3g8rjrLzSrt4KDZFWYELcGl9RCiVZIQaZpGb28venvrXQ+O4yTRViwWsba2hmKxCJZlEQgEwLIsSqVSXTBJu2xa5Z8HZ2LYshI7rpkb/WdarO73wg1YSKF0qtSxKpj7fVmrNFeetVquvUZBrH2Wh6L1xy4XapcuXarr1dzc3JRKx9SEm1HJb6cIm05Kcew0N1DvvpPL5dDT04OTJ0/i1KlT+KVf+qW6f7u6umppvW9961t1f3766acxNDSE1157DdevX9f8dxRFYXh42NJanUpXoLUZWiWOfgo0lmWxuLiIvb09MAyD48eP48iRI55fpOUukh8CLRgMQhRFaYO8traGVCrlmYvoV1CInoNGzo35+XnE43GcPn0ahw4dcuSpWCsLtGaFGcGPHjQ3CQaD6O/vb0gKYxgGP/nJTxCPx8EwjDR4WxAER10KtyDv+a++/qm6r8vLG/VE22YlgXhQO54e8L7/TIv1Si+ORPcavl7QiKHfZBKqQlJOlo1ZEn5y1Fw0RqANyxzlLhoRZkq2KglwYgADCrczHmTxG2//Hv7Hmcdx+PDhOz9TJ6yBuBZy17inpweRSEQqZe4EYdMpokYQBAiC0FEOmt5r2d3dRX9/v+p1NRgM4ujRo02tn8vVHHijEJJCoYDJyUkIgoDz58/jD/7gD3Dy5Mmm1m5XOuPMu8vxKySEDFK+ffs2ent70d/fj6GhIYyMjHh+LEBtc+rnwGZyU1pcXMTi4iIEQcCxY8cwNjbmyQ3LL4Gm9p6zLIuFhQXMz8+jt7e3qfl2WvhV4qi3plPCzOx6at/fygJNi3A4jHA4jAMHDmBsbAxA7b2sVCp1jlsnDt42I868hDHhVmmJNC122DgOhkqqf5e1mW6pxMg90woLURNnAUqUXDQAyDIxSaQRF63CN75PemENpOS3WCwil8vVzSLs6emRQrZ2dnaQSCQQCoXa7lwGOkegkXtpJ7wWoHZPNnLQBgYGXDnnBEHAxz72MVy9ehWzs7Oa33f8+HH89V//NU6fPo1cLoc/+qM/wpUrV/DGG29gfHzc8eNqdboCrc1oBQetVCohk8lgeXkZg4ODePDBB3HgwAHcvHnT1zlkgH9BITzPY2lpCQCwsLCAe+65Rzcm3g1awUFjGAbz8/NYXFxEX18fzp8/71psr18OmlbJ4c7ODpLJJAqFQtPCjHC3CDQ1KIpCLBZDLBbDoUOHpK8rN7tag7flToUXjvpjm3+LQzFIzk2ejeBgpCZKdqpx9IXuuDyk/2yzot5/1Ur9Z1pYFWlGaLloW0xN7PSa6DWTY+SirZb7EKCMf1eClABODCDLxMDwtc16X7h2LL/6+qfwP848bvgzAoEAEolEw/gUea/m+vo6eJ7HrVu3UKlUEAqFGmZaEeHWyvhVweI0HMeBoqiOcDUBYwctm802PYtWi8ceeww3b97Eiy++qPt9ly9fxuXLl6U/X7lyBQ888AD+8i//Ep/97GddObZWpivQOoBQKGRpSLRdyLyutbU1DA8P4/Lly3U9Jq0QVuK1QCOhF/Pz8wiHwwgEAjh37pwvUbVODoy2AnHQ3nrrLSwuLmJgYEAS7W7SCiWOcmG2t7eH6elpR3sMrX6m7SzQzD651dvsyt22zc1NZDIZTwZvi6KIQ7E7Sbp64gzQFmZW2NToWQtA/fMfjuabXrOqcI3MiLQ9rpZQq+eiNct8cdCUqG0MC6FMiTQ14kEWJa6533N5ryYpqTt37hw4jkOpVJLO5a2tLSwsLKBarWqG7LRKKV6n9NKRBMd2dDGVmCnXdEugfeQjH8Fzzz2HF154wbILFgqFcO7cOSSTScePqx1ojd/oLqbRqg8Gaha2GxfG3d1dpNNpbG9vY2xsDNeuXVOd1xUMBlEquXMDNotXAo2U8C0sLCAej+PkyZM4fPgwnn/+ec9FA8EPB61arWJjYwM7OzsAgIsXL7r2FE6JH4KUCCC3hZlyPfmf9TYM7SzQgObmoPk5ePu/5f4Jh2JAhQ+qlr45QVUIYqd6p3QuGFAJCNEQZ0B9CaATYo2wXuk1laSohrK8UemiEfcMAPa4iGUXTYvVsvEDNHmZI3HRwjQPhqeRZyKSi/buH34W//Ph32n6mOTCJhgMap7L5DwmrluxWFR9CEH+81osdVKJYye8DgDSnshMiaNTiKKIj370o/jGN76B559/HtPT05Z/Bs/zuHHjBt7znvc4dlztRFegdQCBQAA0TYNl2abnaRHIIN10Oo18Po+JiQnMzs42DKGW4/ccMi+OgfTdLS4uor+/H2fPnsXBgwelTbPfPXBeCZZKpYJMJoPbt28jkUigr68PDz74oCdrE/zqQcvn85ifn8fe3p5rqZzy9e7WEkencGLwdiKRkMIc1IgGWRTYcJ1o2qmqD53fqcaQCN3pOTPTfyYXZk6wVumDAApHHBRqZjDjolkNDNncH11AhknLUStzNCPOTK1brn0mPSFn+gfNhISEQiEMDAw0bKQZhqkTbvKHENFotEG0OekeK+mUFEejksB2guM4aZ+ohdMO2mOPPYZnnnkG3/zmN9Hb24u1tTUAQH9/P2Kx2oOZ97///RgbG8Pjj9fKhH/v934Ply5dwj333INsNovPf/7zWFhYwIc+9CHHjqud6Iyzr4tjQSGiKGJtbQ3pdBrVahWTk5OmN6B+p0kC7gkkIkiWlpZw4MABXLhwQbWEj8xi8wMvBFq5XJbeh8OHD+PSpUsoFouYn593dV01vBZoZAO/t7eHY8eOuSrMCJ2W4qiHl6VEZgdv5/N5rK6uolQqgaZp1cHb//FH/y+iJu+kSnGmRp6JIhqrXUc3yrUyRjW3zAnW9101ItTMBISosVntxeGIuX60Zkodm3XRNvZLS4OyVEm9MkdlWAgAyUWL0JxU8umEi9aMsJGH7BBEUawTboVCQUpH5Xm+Lh1VLtyaFVed4jx1yusAzInNXC5ny+XS4stf/jIA4NFHH637+le+8hV88IMfBFALVJOfb7u7u/iN3/gNrK2t4cCBA3jwwQfxgx/8ACdOnHDsuNqJrkBrM7Q2Mc2KI0EQsLy8jEwmA0EQMD09jfHxcUsXqFZx0JwUKaVSCel0GisrKzh8+DAeeuihhohwOX4FdZC13RIs8vdhaGiorv+wUqn4UtbplUAjqYx7e3sIhUKYmprC5OSk6+sCrT+o2mn8PnYrg7cXFxdRrVYR7atdd7VElLL/zAxEmLmFoAgIIULtQFhbOCn7z5SoiTTSf2aVLBsDZ2I0wGa1vpdPz0XbaLLvj5Q5quGEi+Z0zD5FUYhEIohEInVBTUbucbNjLTpF2HSSg2aU4Ai4U+JoxPPPP1/35y9+8Yv44he/6NgxtDudcfbdZahtwuwGdMhDLkKhEGZmZmynD7aKQHPiGAqFQl0gypUrVxpCCdxc3w5uuIfFYhHpdBqrq6ua74Of4SRuCrSdnR3Mzc3VlTL+9Kc/9dzpsSrQAO1B1l3soTV4+10v/z7MSpCdqnGc/EY5gSht/Dtstf/MLOv7wvBIzHw6Y4m/M//MrJO2w8ZtH68TvWicGDDtohlRZMMtKdC00HOPK5VK08O3OyUkpFOEJmBObGazWdeDvbpYoyvQOgSrDhrDMFhYWMDi4iLi8ThOnDiBoaGhpjZ1fs1jk9NskmQ+n0cqlcLm5iZGR0fxyCOPqAaiaNEpDppcoI6MjODq1asNs33cWNcKbjloJPwjn8839Jh5XVZppwcNaE+B1m7Hq0W+GkVfpCL9WU+YFdiw1IO2UVZ/AORWeaMe6+VeSyJNjlmRJp8tpkaBjSCh4z4q3TOCmou2VOxHmLZ3XTZT5rhTijdd5ui3sJGPtbA6fFsu2ki/U7vTSQ6a2RJHrwK+upijM86+uwy1p+pmBVq5XMb8/DyWlpYwMDDQEHLRDMQ98nNzGAwGUS6bbzAnkKTKnZ0djI+P4/r167YCV9o9JISMUlhfXzctUP1y0JwWS3JhNjk5iXPnzjX0mHldQtiMg9aOtNNxv+vl30c02FjeKBdnStT6z7SEmdeQGV+EZkQaYL+8EaiJN/2frR1WpcTJ91erzDES4lBlm9tOCYLQkvPDrA7fZhgGr7/+ekMwSbsN376bHDRRFJHNZl2bWdrFHl2B1iEYuVeFQgGZTAarq6umeqnsEAwGIYoieJ737cmTlRJDEpWeSqWQy+VMJVWaWd9PB41h7JXa7O3tIZlMYnNzUxqlQJKWzKzbzg6aGWHm9JpmsdODBrSX0CG0y8ZND6V7xgnWnAQz5Y3Nouw/04OUPOo5XWpsVnt155LlmZp4a9ZFa4ZmyxydDgvx20GzitY8wu9+97s4ceIEeJ6X+jVv377ddsO3OY5rai/QSnAcZ/ge53K5bolji9EVaG2I2kYmFAqhWCw2fD2XyyGdTksle2Z7qexARJmfpQFmHCxRFLG5uYlUKoVSqWS4Kbe6vl9JlnYctFwuh1Qqha2tLdvOIXHQvHZOA4FAU++1FWEmX9PrEse7RaC1E+96+fel/19kIuiPlpGv1v/e5Cox9IS1xcVWuUdy4KzgVv+ZHhuVBIaihYavy/vPlOxU49KwbqchIwziGu8fKXOUu2cMT1suc9wo3fn3oqzM8UCs8XU166J51YPmJuTa2NfX1yBuzA7flpdL+llieDc5aDzPY29vr1vi2GJ0BVqHIO+9Is5QOp1GNpttqmTPCm7MY7OKnoOlHCEwPT2No0ePOnoToGnaVomlU2ubFWjZbBapVKrpkk6yLuB935NdsbS7u4tkMolsNoupqSmcPXsW4bD2RlOOHyWOytdoNKi6nWknYckLARSZCChKlMSZ2fLGrbK5uWZ+9J9poSXS9DAj0pQumrK80Q8XTS7M1Ngq1j6/vmjj5331+c/j+4/+tuVj6YT5YeT+oyZs9IZvy4XbxsYGMpmM78O3/awEchqjPVk2mwWAbolji9EZZ99dhpaDxjAM1tfXkU6nUSqVMDExgTNnzpjefDqB30mOausLgoDV1VWk02nwPG9rhICV9Vt5Dtru7i5SqRR2d3cdKekEIG0qvH4CbFWgKYWZnd+Nbomje7SLuHz0xT80nHum554RcWbHPXMLZf+ZFmZFWonTdqJJeaMco1JHOfIB4CUupOmi3S4MIKIoGTXjommJM4oS61w0AMhXooiE6teIBO3d/zrJQbNybw2FQujv729oufB7+DbHcXeNg5bL5RAMBjWDwLr4Q1egdQCCICCXyyGfz+PNN9+UBIgfT3/8TnKUCzSe56XZbhRF4dixYxgdHXX1Juh3iqPW2qTXLpvNYnJyEqdPn3ZMuJObmNdPHM2KJSeEGcFqqmKzqDl2Zhy0dhRoQPscd4ULIqTibuUq2n2bRq5Zq/WfERihfpNq1UlzotTRTRdNzmYpAcpEHxodEMELtfeyUI0gEakdGylztOOidYJAIy6gEw9b/B6+3UkOmpFA293dxcDAQNuff51GZ5x9dyk8z0szzIDaRvkd73iHr79kzcbcO7V+JpORZrvdd999GB4e9uQJvd9z0OQCjZS6kiHLk5OTrjiq5H31WpgaCTS5MHPqtXudWGm3B82P0Ja7gUvf/WNEw1AVZ16xruLwqIVbHIlZK0e0wkYloZpIqYXZUkc7qLlomyZLSIE7ZY6b+++rKFKmRJqcQrVWhUCEmh3aLSREDbfLNL0cvn23OWjd/rPWoyvQ2hCO45BKpTA/P49YLIb7778fPT09eOmll3x/AuKnQGFZFktLSxBFEaurq47MdrOKnw6aPKxja2sLqVQKxWIRk5OTdbO8nIaiKF+SHLUEmhvCzGhNt1Bz7IwEm9d9ck7RDiWO0XC9EJBv5JXlb3IqOiV/RsidNzXhoJU8uK6Il3dasG2X4xhUCctwiwIbaXDzjKjyQVNljpsGPWcEtTLHUIAHu39cuVJNZEZDrGUXrVMcND9EjRvDtzvNQdO7/2ezWfT397fFNfhuojPOvruMcrmM7e1tnDlzBoODg6AoCtVqFYIg+J485EeJI8MwmJ+fx+LiopRQ+eCDD/oSkev3HDSWZfHyyy+jVCphenoaExMTntxk/JiFplzTTWFGaIUSR0BfpLXzTbaVhaXSPSsxIfRE1F0kef9ZthJDVNGXZNR/tllKIGRzsLIW6+UEBJHCkXi9UDPbf6aGmkjT6j/bqcbrAjnUyDFR9Ie1g1bMYMU9A4DtUu37rUTsA/Vljk7QKSEhreQ6NTN8m2VZrK+vg2EY9PT0IBKJtO211WyJY5fWoivQ2pD+/n489NBDdV8jT0dYlvX1AulliWOlUkEmk8HS0hIOHDiA8+fP48CBA/iXf/kX31wsP0JCRFHExsYG3n77bXAch+HhYcfTKY3w00HzQpjJ1/RSRKitVywWUSqV0NfXp/pUtF0dtFZH6Z7JKVbDiKv8fVanJ00Ns05OM5ASSaVQU8OqY2XEbjWGAxH1MJCcSniI8t8CQI9KaaVeWIiei0bEmRKrZY7ERaNpATxfE1mRIIcL3/4iXv1f/5upn9F10LzDaPh2oVDAm2++KTlu5XJZCtFQ/hcOh1tauPE8D0EQdPcD+Xy+K9BakK5A6xBaIeIe8KbEsVQqIZPJYHl5WXXodqsnKTqFKIpYX19HKpUCwzAYGxtDOp3G1NSU5zcMPxw08gT01VdfdV2YEfycg1YoFJBMJrGxsYFQKCTNDyLDYkmZDtDaTpQWrSwsiXtWYUIIRat17pmaOLMqzPaqUew5drTqCIrSPCLUtASTHlXuztbB6VJHuy5aiQthtxxH2GaKolnkZY5aLlqFDYHl6IaERz26As1/yPBtch+ZnZ2V7umlUkly29pp+DbZj+kJtGw22x1S3YJ0BVoborX59jtBkRxDpdJciYoWhUIB6XQaa2trOHLkCC5fvoze3t6G7/M7qEMQBFdvtmSeWyqVAsdxUmonx3FIp9OezyMDvHXQstkskskkdnZ2EAgEcP36dc9GSfg1B+2nP/0p1tbWMDY2hitXrkjvN9kwkBjqQqEAnufx05/+FH19fdJmIZFISL0VXexDBwSUGGsbL2V5o5LdctzUvDMr/WdWID1uh2JF2z/DjEjbY2ol53oumhmKbFjVRdNDzUVTumdkBhrBTliIEoYNmnbROkGgdULQCVATmhRFSZ8HTdPo7e1t2G+0w/BtjuMQCAR0z61sNotDhw55eFRdzNAVaG2K2kYxFAr5mqAIuCOO8vk80uk0NjY2MDo6iqtXr+rO6/BToJGLrxv9BIIgSMKM53kcO3YM4+Pj0jrkfOA4ztPZd4A3zhIRZmSG28TEBN58801PX6uXDlqpVJLcUYqi8MgjjyAej4PneTAMg1AohIGBgbrSFFEU8eKLL2J8fFwScBsbG1JvhXyzQP5rlSe9rcql7/4xgJp7RsuEVLGqft6xgv7vfZkNIRpksVuOa36P0/1nZtgq9zQt0mIhc/cfpUhTljcqXTRS3qj7M/ffT4YLGrpo5HvtDgLXCwshZY6hIG/aRRNFEaIotr246YQ+OuBOgqPRA612GL5t1H8G1FIc77nnHlfW72KfrkDrIPyOuHf6GLLZLFKpFLa3tzE+Po5r164hFjO+UfvtoAG1G5VTG19BELCysiK5YzMzM6rz3MjafkSsu1naqRRmZIZbLpdrmeRIJymXy0in01heXsbg4CBomsapU6dM/Vvy1Fc5+FXeW0FKdBYXF+vKJOXCzemhr2aPvVVLHM2yV4no9qoR9MSZl/AKMSl30+z0n+2W4zjgULmjXqmjHRfNLcyEhRi5aOSa0u7ipt1LHAnNJji20vBtowRHoFvi2Kp0BVoH0QoOWrNllmR2VzqdRjabxcTEBGZnZy0lMvqZpEgi551YXxAELC8vI51Og6IozMzMYGRkRPMmTjbnfrx2N3rQiEDf2dmpE/kXVxIAACAASURBVGbyNb0WaG6mOFYqFaTTaSwtLWFoaAhXrlwBALz00ksNx2B0jEqhQ3orSI8agWVZ1TJJQRAQi8XqhJuZ2UGdxoP/+iWE9u+StIbbQvrP9irG16hsKdbgqNh1cayg7D8zYqvcg76IujiS95+pYVakNVvqaBVS5igXx5wQqHv/nSpzlIeFMGwQPKcvvLoCrbVwawaaH8O3WZY15aB1BVrr0RVobUqnlTgqZ3dNTEzYDn3w00EDmneTBEHA0tIS0uk0aJrGvffei5GREVMbYz/SFJ1eVynMTp06pXoe+CHQ3EhxrFaryGQyWFxcxOHDh+t6K4vFouXXaMWJ0iqTrFarkttmVCZJksyapZ2Fn1lx1k7slOI4GHfGDSP9Z0p2qzHdProcE9UUl3IXTelIapU5OuFcZot3PkdS5kiOMR6td/VImSOg76KR+0VXoLUGXs5Ac2L4Nrkeqz1AMypxFEWxO6i6RekKtA6iFUJCrJY4kiTCdDqNSqWCqamppmd3tYJAs7M+z/O4ffs2MpkMQqEQjh8/juHhYUsbV78GZTvhoOVyOSn8w4xzSgSal6EoTopChmEkYXbw4EE8/PDDDSUxWmJL7/U2WyooH/oqbxyXl0kWi0VXyiRbqcTxwX/9kurXK9UQopE71zi5OFOWN5KAECLOrKT6yXErIMQIKyJNPozbyVJHJ+H4AIK0/u+v0kUjyIWZkgAlQhAplCphiAKFnni17u+DQQGcjosmCAIoimrrhxRA7XV43f/sBm45aFZwavh2uVw2fC25XK5OHHZpDboCrU1Ru5CHQiEUi/abvJ0gFAqB53nDTbMgCFhdXUU6nQbP81ISoRMXRT9j9u2sz3GcJMwikQgeeOABHDlyxNbN2i+B1oyDJhdmR48eNV3SKg9H8Wpj40SJI8uymJ+fx/z8PAYGBnDx4kXNp5d2XqNbvVxWyiRJX0U8Hm/LMslTz/45wvGaAwLcKW9UijNlD5cSO66ZVwEhesfO8Xf+zq6TZlakFaoRJCJVzb8vMWHEw+r9ZkU2DEaj5FLpouXL6uNnlGWOSnYLcUtljlRARLEUkc4TMy5aJyQ4Al0HzQusDt8mwu2VV16pE22hUAhTU1MAalUrXQet9WjNM7CLLVolJATQbkxV9lVNT09jbGzM0ZtTMBhEtap9w3cbsyKJ4zgsLi5ifn4e0WgUs7OzOHz4cFOb13Zy0OwKM/magLebm2ZKHDmOw8LCAjKZDPr6+nDhwgXDun9yLrSCQNPCqTLJVhJt4fid6yjDBBGLWg+k2CtFJYGnhRf9Z06wU6qVBvZoCCUtdstxBJsQnIWq+euBG+i5ZkB9miNx0QiVaggCH0Bc5qZp9aJ1Ujx9JwjNVnDQrKI1fPtnP/sZAODgwYMoFovI5XL4m7/5GzzxxBOIRqOYmprC4OAg/umf/gkPP/wwZmdnMTQ0ZPt6/Pjjj+PrX/86bt26hVgshitXruBzn/scjh8/rvvv/uEf/gG/8zu/g/n5edx777343Oc+h/e85z22jqFT6Aq0NkXLQfNboJGLGsuydQJNWb537733Ynh42JWLeTAY9NVJNCqxJBv1+fl5xONxnDp1CocOHXJkg+qng2Z23WaFGUEu0LzCTokjEeKZTAY9PT04d+5cXcmKHuScsCJCWyEN0U6ZZCAQQCgUgiiKvqZJEvdMFCgwTO0WWak2PmwqV8IIh9V/z/dK6m6NE+wWa2IpQIk40GPsUFkNCNFduxzDgVhjsIe8vNEKJaZWDmfXRcuXo4jqlI0SF03unpktc8zLPkO7YSEBWkCpFEEozElljqe/+Wf46X/6SP16XQetpWhlB80qPM+jr68PR44ckb72h3/4h/jMZz6DGzdu4Ac/+AH+9E//FN///vfx1FNPIZPJYHBwELOzszh58iQeeughfOADHzC93ve+9z089thjuHjxIjiOw6c//Wm8853vxJtvvqk5HukHP/gBfuVXfgWPP/44fvEXfxHPPPMM3vve9+JHP/oRZmdnm34P2pXOOAO7AGiNHjSKouqOg4iRhYUFRKNRnDhxoqmnM2bwM8WRrK8mVliWlYRZb28vzpw5g8HBQUffCz8dNIbRf7pOhNn29ratdE61NQFvBZoV8UMeSqTTacRiMZw+fdqyEFfOuHP6GL1Gq0yS4zjcunULLMtKYyXkZZJKt83NMkk6VH8+yTfmpGytXGnssyH9Z0ScGblnRuzuuzdqL5P0SBGxpsSMcLN9XBoiTYu9SgS9UfcqGipsUFekmUFZ5pgrRWH27FKbiUYFRIiy6H2WCSKkIeaBznGeOkWgcRzX1L2pldBKcUwkErh8+TISiQS+8IUv4LnnngNFUSgUCvjZz36GN954Azdv3sSNGzcsrfetb32r7s9PP/00hoaG8Nprr+H69euq/+ZP/uRP8K53vQu//du/DQD47Gc/i29/+9v4sz/7MzzxxBOW1u8kugKtTWlVBw2oOUjlchnr6+tYWFhAb2+voy6RmfVbSaAxDCOJ1L6+Ppw7dw4HDx505b1oxR60XC6HVCqFra0tR4QZgTTVt5qDJgiCJMwikUhTpavyEkcr/6ZVBZoWwWBQSjK79957AdSXSZKeCq0ySfK/zQYUnHr2z0GHAJ6lETBwWZTumZFrZiYgpKAi/OwgF2798UYxZdQ75zRmRJrSRVOWN+r1oumxlU8grHjvzbhodlCWOcqplmouIx3mcfqbf4bvXP7fpYcNneKgdVKpZqc4aEYpjsr+s0QigYsXL+LixYuOrJ/L5QBAN4TkpZdewsc//vG6r/38z/88nn32WUeOoV3pjDOwC4DW6EGrVCrgOA6vv/46Dhw4gPPnz3ueDuS3QCPry1P6BgYGPHkv/HTQlMIln88jmUxia2sLR48exTve8Q7Hn0q6MX9NDz1BSPorU6kUgsFgU2Ev8vWAzhdoBPlx202TVLptPT09ljeNWuJMzTlrlpxM2GnNWmsGuVgz46zJA0LkMPyd99Csi1ZmtbcYpLxRjlGpoxx52aKTLhr5PESgzkWzWuZIXLQALUDgAwgERQjcnZ84Pz+PUqn2eYTDYfA8j4WFBen8jUQiLdWXaYZOctA64XUA5gRaf3+/K+eaIAj42Mc+hqtXr+qWKq6trdWVYALAkSNHsLa25vgxtRNdgdZBhEIhCILgy0WyXC4jk8lgaWkJNE1jenpaehLuNX6nOJKZbiQ+XS+lz2m8FiwEuTD0QpgRvJ6FphYSQkryUqkUAoGArfEIWsh70Kz8m3YUaGaPW69MUu62WS2TrLln2uWNyjI2OZVyGHTI2u9d0QWxp0Tp5hCx1hdTH0JtBSLSzPafOVHqaNVFy1vsBczZ7B1UK3PUgmdo0GEe/9fia3j9l38T5XIZS0tL2N7eRj6fx+rqKkqlEmiabkhAdWrmoFt0ikC7mxw0N4dUP/bYY7h58yZefPFFV35+p9MZZ+BdiFaJI1CrOfbqIlksFpFOp7G6uoqhoSFcvnwZc3Nzvt5E/HLQKpWKJFIjkQgeeuihhrlWbuOng1atVvGjH/1IEmbXr19HNOpeWAJZ1w+BRoTE6uoqkskkAOCee+7B6Oioo08i7Thodr6/VWjmuIPBoG6aJBFu8plBctFmFzVxptd/tles/U4YlVC6CUknHOgx30umxm45hpgF58psqaMd9Fw0hg0aljkWShFQgfrzT+mimUGtzJG4aHKoEC+V6iYSCVQqFZw6dQpATSDIXeLt7W0sLCw0uMTkf+PxeEsIik7ppesUB00URdMOmtN85CMfwXPPPYcXXngB4+Pjut87PDyM9fX1uq+tr69jeHjY8eNqJ/z/je7iGIFAADRNg2VZ1zfGe3t7SKVS2NjYwMjICK5evSol9LRKiaFX87Hk7uHhw4cxOTmJcrnsuTgDagLNKKzDafL5PBYXF7G3t4eDBw96IswIfgg0ANIMP47jJGHm1sbEarR/M6MAOg2zZZLvee3/k9wzIpy4Ko1QtHYdYytBBCN3RBfpP6uUzT2IYpiglAiphVp5o15AiBNki7GmRVq+HEFfzLuxJiUmrFmGKceqewbUkjuVIq3u722WORJImSO334926h+/jBv/239p6EGjaRq9vb3o7e2t+3kcx9XNHFxbW0OxWJTu+UrHLR6PeyaYRFHs9qC1GIIgQBRF1ZFHhGw266iDJooiPvrRj+Ib3/gGnn/+eUxPTxv+m8uXL+Pf/u3f8LGPfUz62re//W1cvnzZseNqR9r/DLxL0RIebic5ZrNZpNNpbG1tYXx8HNeuXUMsVj8rxu9euGAw6MnNolQqIZ1OY2VlRXIPe3t7cfv2bezt7bm2rh5eOmj5fB6pVAqbm5sYHBxEPB7HAw884MnahGYGZFuFlK4CwFtvvYWZmRmMj4+7vgGyWrLYziWOXtFQJqkIKuOq+tcNs8KsFRGE+vdZ7qaZ6T9TQ02kafWf7VUioHVEEACUqyHEItbvIXZdtELJidAi82WOVFCAyAVA7TuvZp2nYDCI/v7+uod/oiiCYZg64Xb79m0Ui0UIglBX3kv+NxqNOv77Ru47nSDQOsVBI3tBvdeSy+UcbcF47LHH8Mwzz+Cb3/wment7pT6y/v5+aa/4/ve/H2NjY3j88ccBAL/1W7+Fd7zjHfjjP/5j/MIv/AL+7u/+Dq+++iqefPJJx46rHekKtDZGbSPmljja2dlBKpVCNps1LF8LhUK+DoqWD8t24yJbKpWQSqWwurqKI0eO4MqVK3UlUn72wHkhWOTCjJwLxWIRb7zxhqvrquGFg0aE2dzcHCqVWu/OpUuXGh5MuMXdItAAf0ozTz3759L/55kAhEBt46rlnlmhXKoJOTpYf476Wd6oxU4hbrk3jeXuXF+tOGmlShhxjeHfZZWZc3JI755eKqYV90wpzpQumpWwkEpRJtxFCuGeO69RLSxE5AI49Y9fxjfP/7ztBz0URUkJqPIQKlEUUalU6sp719fXUSqV6sp75f8bDodtCzdyHW53YSOKYsc4aKTdRe/cyuVyuO+++xxb88tf/jIA4NFHH637+le+8hV88IMfBAAsLi7WHdOVK1fwzDPP4DOf+Qw+/elP495778Wzzz57V89AA7oCreNwMmqfbEzT6TT29vYwOTmJM2fOGPaX+T0oOhAIgKIox2eZFAoFpNNprK2tYXh4uK6sU45ffWBkbbcc1L29PSSTSWxubmJ8fLxOpJfL5ZZJj3QKURSxvb2Nubk5lEolHDt2DEePHsV3vvMdT90eq6ME2lmg+YZYE2fK8ja20niLVPYSKfvPOIZGKMhL4swv7AyozpejTQWIOFnu2IyL5iVyUaZ00RjydwIQ6ql/LcRFA0e5ErNPURRisRhisRgOHz4sfZ2U9xLRls1msbS0hEqlglAo1BBK0tPTo1siR+B5Xhp90s6QssB2F5qAcUAI4LyDZube8/zzzzd87X3vex/e9773OXYcnUBXoLUxahsxJwSaKIrY2NhAKpVCpVLB5OQkzp8/b+oiDfhf4kiOwSnBUCgUkEqlsL6+jtHRUTzyyCOIx9UHxAL+Dsp2w0HTE2ZurmsGtwTazs4O5ubmUCgUMD09jYmJibobnZcCyE5PWTsKND+E5al//LLmXVBNnJlFLs6U7plZ3O4/kyMXcyS+3q5Q04vWB4AqU7uP6LloZqiyQVOz5eQoyxyL++4ZbeBoqoWF1LllalAiIHtf2WIIdLR2TxKqNAIyV/aXfvJtfP3M/2L8AhxAXt4rjzbnOK6uL3NjYwPFYhEMwyASidSJNhJMIhcxpEyz3QUa2Td0goNmRqAp56B1aR3a/wzsUkczAk0QBKytrSGdToNlWUxPT+Po0aOWnyS53QdnBieCSuRBKGNjY6r9dlpr++mgObW2GWFG8Dqsw611d3d3kUwmkcvlMDU1hQcffLDhBuf1a72bShx9weCtkpc3suUg6LD2Z8+UQgjYEGRuzD9TQ9l/pgdx04z6z5SwHK2bYilHKdKU5Y1KF83MaIJyJWwouIwwCgspFyKWwkIQACAAfIWGyN/5DKigUDv92IDvjk0wGERfXx/6+vrqvk762+TjKwqFAniel/rbenp6EAgEpGtjOyc5chwHiqLa+jUQzAo0t2L2uzRHV6B1GHbEERmwm8lkIIoijh07hrGxMdsXKL9THJs9BnmPlVYQih5+lzg2u7YVYaZc16vkTIJTYimXy2Fubg67u7uYnJzE2bNnNR1jqyWHzaK1ntZ73RVo5jj1j1+u+7PehhyoiTM9mJK5CoNW7D/TIl+OIhpWf+An7z9TUq6EEWvCHav7WTqljlouGs8HNEUacdGKst4zve9XYuSc1ZU5Klw0Pf7Tj/4FN479F1Pf6yXhcBjhcLhuE0/GV8iDSXK5HFiWxQsvvIB4PN7guLXL4O1O6T8DagJNr/JJFEXkcrm63sUurUNnnIV3KVqz0Mz2f/E8j6WlJWQyGdA0jZmZGYyMjDT95KhVShytCrRcLodkMomdnR3TwkRrbT/ECtCcQJM7hlZfPzln2k2g5fN5zM3NYWdnBxMTEzh9+rRhj6XXMfZ3i4Pm5XGf+tsnAI19i7L8TC7MlO4Z6T8j4syOe+YGdvrPtCiWIuiJW+8rMyvSmi11VK5phqKJ1EY1F82wrNEEFC1C5Kn68ywkAGz7ODby8RWDg4MAgM3NTaTTaczOzkrCzWjwdiKRMN064RWdkuAI+NOD1sU5ugKtwzAjjjiOw+LiIubn5xGJRHD//ffjyJEjjm2s281B293dRSqVwu7uLiYmJjA7O9tUuAi5uPvxJM6OQFMKM6uOIVkX8H5QqV2BJncJjx49aukz92s4tlvff1fCBoAQD+y7JiJDg9pPbQxYSGw0cs3s9J+Vi7XzULWETuUS3dPjfmKuFZHGyZw1pUgj/WdKSpWwbslguRrSFJ12XDSBCzSIaSMXrVII173/VmeikTJHOWJp//6wL/xPfe0vceP//E3zP7OFIPc74poNDQ3V/Z2Vwds9PT2+iaROctBYltV9LSzLolgsdkscW5TOOAvvUrQcNC2BxjAMFhYWsLi4iJ6eHpw6dQqHDh1y3PEIhUIQBMHXWnQzQR3y0QGTk5Om3BOzawPmnl45jRWB5oQwI5DPmed5T5+IWhVL8sAXuy6pHyWOd0tIiBec+uqTQPzO74jI0AjsizOleybq9Gzx5SDggGPGlBt/X8yKMwAoFusfLFgVbHpuG8/duX7bddK8wqx7VlV5vw3/TcHafcGozJG4aCItgiI9aSEBNRXXnujd7/UGbxPRRgZvFwoFcBzn2+DtTnPQ9B48ZrNZAOgKtBalK9A6DLUetGq1ivn5eSwuLmJgYABnz57FwYMHXdsQEVHCsqyjMfdWj0FNqIiiiJ2dHSSTSUujA6xAmqX96EMjaYp6pYaFQgHJZNJy+IkeJL3L66AQs+9zqVRCMpnE2toaRkdHmxajXpc4yt9Xo9/bdi1xBLwVliJPAfsBGILKYGqhEgQVVj+3eIN+NCOq8mh2g943qxSLESn4JCabw2UlIETzZ5ciCIetVUeYLXVkqiGEdWL12WoQoYj62lWN5EgrvWVqiAJV75Iq4hydcNEAAEwtbh8hsW1dNJ7nLQubYDCIgYGBuhI7rcHbhUIBoii6Pni7kxw0juNURwERstksIpGIbip1F//ojLPwLsXIQSuXy8hkMlhaWsLg4CAuXrzoSa0xTdOuzCGzgrLEkcy0SiaTKBaLlkcHWMWvoBC98ko3hJkcP0SpkYNWLpeRSqWwsrKCkZERwxEJTqzpNGqCS28z0s4CzW1OffXJ/X4f6o5ZIdtgE/dMUInYJ/1nkjhTDp824aY1E91vh/K+EJQLtWZhmKAtkRZoQohWK85cp+XumZkyR6YYrjs/rKCciWYKtibSzvz1X+H1X/8NW+v6hR2BpoadwduBQKBublszg7c7zUHTE5skYr8dwlvuRroCrcMIBoNgGAY3b97EysoKhoaGcOnSpYboXLfxO2o/GAyiXC5Lw7aTySRKpRKmpqZw4cIF15+Q+TULTU2guS3M5Gv74aCpvc+VSgWpVArLy8s4cuSI5lBxu2u28hw0P5xMJ/BikxDgKAgm9/pK98yua8bKHRiH3TJVVJYoF8MQBQpRh4RapRRGNN74szidZEc9WKb23tp10UiZaFDF8WzWRYNI1Ys0taFoRpgpcwyKNRcNgBBqv99fpwSaFk4M3ib/q3f/d/t1eIlRimM2m0V/f7+HR9TFCl2B1sYoNzQk+EAURfA8jytXriCRSPhybH4nOdI0jUKhgJdeegmVSkWa6eZV6YJfs9AoigJFUeB5vq7fyk1hRvBjFppyzWq1inQ6jdu3b2NoaMiV34FW70FrZwfNzeM+9dUngdh+KIhGG4uac2YXgaEhMNY3elb6z6xCUgiJUGsm7VFLpGnBVIIIR/17aKfWe6bnojEmExsdK3MksBQonmo7F80vYWNl8HYmkzEcvO1H77hbGL0WkuDYddBak844C+9ycrkc0uk0Njc3MTo6CgA4fvy4rYh4p/AryVEURayvr0sJUcePH7c1bLtZ/CpxJALtzTffxM7OjifCjODHayauHcMwkjAbHBx01TX2o8SRrEdmFi4tLSEWi0kbk0QiIfVRtqtAc3uToOqe1TkjOutXaCAk+16Dcka+HARFG38GTvefaaEMOyFCLRzXfogmDwiRI8i+7oZIU7poyvJGvV40LXg+AJEPgDLppJkVZ83SSS4az/O+tTSoYXfwtiAIiEaj2NjYkIJJ2lXAGKU4khLHLq1JV6C1MSzL4tVXX8Xu7m5dIt3q6qrvMfdelziKooi1tTWkUimwLItDhw5hb28PU1NTnh2DHD8EKnHMSJqWV8KM4IeDJggC8vk8vve97+HgwYN46KGHXC/Z8GtQ9crKCpLJJABgbGwMLMsil8theXkZ5XIZoVAIiURCEsl7e3vSU+F2wS1heeqrTyKwb0NRTABi1MLnpxRnKohsAAgK+mWQHokxK1QLYUQSzZU9mhFpnMxJVIo0Ut4ox6jUse57Zc4Yx9CqZY6sTnKj0kXjS6HGz8qgzFHNRROLoTvfK/930sIUxKj2A612c9H8TG22gt7gbXIP5Xke8/PzKJVKAFA3eJv8b6sP3hZF0XQPWpfWpCvQ2phQKITDhw83xMPrRe17hVcljoIgSMKM53kcO3YM4+Pj2N7eRi6Xc319Lbx0k+SljKOjo4hEIpicnPRUnAHevmaWZTE/Py8NWb9w4YJnUcFe9qCJogiWZZFOp0FRFO655x6MjIxI4p9sEDiOk54Ir66uolwu48c//jF4nm9w2hKJRMtvLpzk7JN/hUCQghDbDwDZF2dUNSBtkKkKDTEiS8okm/yKeXHbbLKjI9g4LUmEfDNCrVIKqwojt7DjogEw76IJlG1BLQkzAgXNz4Wq0KAEQIjztfNx/xwkjlo7uWjt3LslH7y9tLSEw4cPY2xsDIIgoFwuqw7els98a8XB2+Re3BVo7UsL3FG62IWiKExNTTVsFv3u/yLH4KaDRByFdDoNURQxMzOD0dFR6Qme38OyvQgJUQozklD44osv+lJe6UWKI8dxWFhYQCaTQW9vL6amppDNZj2d4+KFU0hSR+fm5rC3t4dDhw7h7NmzmuIwGAyiv78f/f394DgOe3t7OHnypPRUmPy3trZWt7mQizaj5nm3cUswirKXRNwzuThTxYIwQ5mulabJMFPe6DfKssdm3TSmFNItmaz7XpOljnrPQdhqUHVOndJF03PPlPB6g8eNXDSlMFNDRayJASBQkp1vsjLHdnLR2lmgyZG7TvJ0yHYbvE32H0Y9aMPDw14dUheLdAVaB9IKDppbJY6kB4c4CjMzMxgZGWkorfBboLkZElIsFpFKpaSZXsroeD8j/t0SLjzPY3FxEel0Gj09PTh37hwOHjyItbU17OzsuLKmFm6XOO7u7uLtt99GoVDA9PQ0IpEIDhw4UHeO6/WZkb+TPxU+dOiQ9PfyzUWhUMDGxgbS6TRYlpXcNrl4i8VinrltTjuTZ5/8KyC470gwgdoeu1p/rVC6Zw0oyxtZ6s6ds2x/06XWf+ZGQIjesG0lxE0LaognQaMvjaAm0jiNoBSmEgTlQ0WcmoumFhZiyUUr2dhKBcTaGvIv7Z9PQkiQXDSKB8498Vf48X9ubZHWKQLNzOvQGrzNsmxdf5ufg7eJ0NS7dudyOTzwwAOurN+leboCrc1R26i1gkALBoNS/bYTCIKApaUlpNNp0DSNe++9F8PDw5oXNyLQ9AY2u4kbIslImLm5thnccNB4nsft27eRTqcRjUZx+vRpHDp0SPpM/UqOdKPEMZ/PY25uDjs7O5iampLm9L3++uuWXqNRSIjW5oJhmDq3bWtrC8ViERRFNThtrVTKo4eoc4ejNFwyysxbLRNmYtDEudCC/Wd6cOUQgjHz9xC5cLPipBn+XIZGwEbppFYvmh667pkeZsSZ3DnTcNEoARADIiiBQoANSOWNQkiU+idbGUEQOkKgNZPiGAqFTA3eXlxcRLFYdHXwtpnX0S1xbG26Aq0DaRWB5oSDxfO8JMxCoRCOHz+O4eFhw4sXuTCpDWz2ApqmUalUHPlZZoWZfG0/5mA5uS4R5KlUCuFwGLOzszh8+HDD594K0f7NUigUMDc3h83NTUxMTODUqVN1PaV25qDZEZDhcBgHDx6sGw5LZgyplfKQqGr5f7FYzPYTYacfpJz7i6eAaM09M0ugEoAYbp++nzoc1oBWRZod+CoNOqIupPjqvpukIdKE/b+nNPq0OIaGyKufi0oXTdjvHzQsTVWWORaDzTmcKi5a3V8zFIRwbb1zf/EUfvxfP9TEYu5yNzloVmh28LZ8HICVwdtGCY5ATaDJj6lLa9EVaG2O2i+r3+V9QPMljsQ5yWQyCIfDeOCBB3DkyBHTFydygfVrpokTJY5yYTYyMmIozAjtw034NwAAIABJREFU7KCREtZUKoVgMGj4ufsh0JyKsS+VSkgmk1hbW8PY2JiUwtrsek7G7MtnDMlhWbbObbt9+zYKhQJEUWzobZOPADDCqeM+++RfQVS8lVop+qS8MVAxISxLNGAQ3GC3/0wsBlWPUf41uscZwWS27NGuSLPioumJNN/RK3O0WtaoExYCqLto0mGERLR6PmInCDQyQ9aLPYPR4G0i3HZ3d3H79m3Lg7eN9j6iKCKfz3cdtBamK9A6kFAo5Gh5oR3sikSO47C4uIj5+XlEo1GcPHlS1TkxIhAIIBAI+CZUmxFJdoWZE2s3QzMOmiAIWF1dRTKZBEVRuO+++zAyMmL4ubejg1apVJBKpbC8vIzh4WHDz9dqz5sXc9BCoRAOHDjQEFVdLpcl0ZbNZrG0tIRKpVLXOE/+c3MEAMVR5koPYSDM2AAQ4mvCDDAUZ6Yp0417dQNxBgC8ShCFU6JNa1Ei0oz6z5QwpVBjX5cMgTX/2StdNOKeAbURB2oumlChQRmMRwDuuGcAIPKUOYEtF2eKsBBTyMVah7hoPM+3Rcy+HoIgQBRFX4Wm1kMxq4O3GYbplji2OV2B1oG0SomjlWMg6Xzz8/OIx+M4depUXa+R3WPwQ6iQta2Kw2aFGaGdHDRRFCVhJoqiFCNv9kbvl4NmZ00yTHtxcRGHDx/GlStXGm7CWuv55aBZgaIoxONxxOPxusQz+QgA+WBYQRDq+i+q1Sp4nm+6b/TcXzwFIVp7/aS8kWIpiGHj90S1vLGkvVkzKwJRVNxqHexJI6KNEoGAQqxZCQjRgyuHEAip/27rCTe+EgRtkNYINLpofNWZDbLIUpoizXbkfiEIt+0s4qKJQYDiALpUW1AMiS0ZGEKcp3Z30MxE0/uFncHbNE3jxo0bdUmS/f39CAaDEEURuVyuW+LYwrTeWdjFEmobmVYQaGZLHFmWlYRZIpHAmTNnMDg46Eg/ip+lnlZEUrFYRDqdxurqKkZGRnD16lX09PR4sraT0DQNhjEX0y2KItbX15FMJsFxHGZmZjA2Nmb5CawX0f7Nrklmts3Pz+PgwYN4+OGHLQ3TbheBpoV8BACB9F/IhVs2mwXDMPj3f//3hkCSRCJhavP34J88BeybTBQLiHRNnBEHIsBSEGQbdrXQRMco7h+vh6aCIHPYlGKtWfhyEHTM+vXUrkhTohcYonTRBJNjEgSrs+uKTQoQk2EhSsSgCGo/el/PbfML8sCq3QUax3FS9U27oDV4+9atW2BZFn19fSgUCtjc3MTXvvY1/O3f/i0mJiYwMzODoaEhvPbaa4hGoxgbG2tq3/XCCy/g85//PF577TWsrq7iG9/4Bt773vdqfv/zzz+Pn/u5n2v4+urqajf6f5+uQOtA3Iq4t4JRiiLDMFhYWMDCwgL6+vqk2HQngwL8FGhm1i6VSkilUo4JM4IVoeQkZoSLKIrY3NzE3NwcGIbBzMwMxsfHbd8Q/SpxNPMAhJTrZjIZJBIJ28O0td5Xrd+tVhNoasj7L8gIgJWVFayvr2NmZqaujEc5AkAu3pQjAITQfqS+TJwBNWFmlUCZhmDWIZPT7CbeBmpCUyiGABGg4s5dA8kwbjNCTdRx1qyUN9b9O4a2HIai56KplcKqljkKFFCWvR4B9cLbTpmjHIMyRwLFUjUXrcVKHTtFoHWCCwjceXDf29uLyclJ6etnz57Fhz70Ibz++ut45ZVX8PLLL+N3f/d3kUwm0dvbi9nZWZw6dQqzs7O4cOECHn74YdNrFotFnDlzBr/+67+OX/7lXzb979566606V1BefXG30xVobU6rOmjEQlc23DIMg0wmg8XFRQwMDOD8+fOuWeyt6qDJhdnw8LBjwszM2m6iJ5ZEUcTW1hbm5uZQqVRw7NgxHD16tOmbIUk49HKcgpEoFAQBt2/fRiqVQiwWa9oVbsUeNDdRlvGQmGp52tnm5iaKxaKUdpZIJPB//MuLCADgTZ5SAaa22SVQPAURsllUSnFm0H8WKNKWEiPrcPHUFff7pYhQ0y171EhSEbn6r1t106y4aHYhLppZ90yvdNUL6FKgTmzyUYVQVJQ5EheNLlMQgjW3+LXfag2RRu437eQ8qcFxXEcINKBWuaEsoQ+Hwzhz5oz037PPPotbt26hUqng1q1buHHjBm7evIl//ud/xg9/+ENLAu3d73433v3ud1s+zqGhoW4fnAZdgdaBWO3/cusYgDtJQtVqFZlMBrdv38aBAwdsuwlWj6GVBJrbwkxvbS9QW1cURezs7GBubg7FYlESZk7V+JMNgZczeLQEkyAIWFlZQTKZRDAYxMmTJzE0NNS0cGz3EsdmkcdUDw4OSl+Xp50VCgUIISCgdtmTvf2kvDHAaKSCWhg8TVUDEIM8AlYdM5P9Z1qpk6ZRls+RYIuoM9cGvhzUjLhX/X6TIs0QJgBojEIQWY1Y/SZdNKpIQ1R+bjZctMB+LxmlUuZIVyjp/1M8BT6u/hqFIBDgam5xq0ACQvyYOeokfo3lcQOjFEd5QEgsFsO5c+dw7tw5rw5P4uzZs6hWq5idncV//+//HVevXvX8GFqVzjgT72K0HDRBEHy16wOBAGiaRrFYlITZ4OAgHnroIUv9N81A07TvJY4k2c4LYUZolRRHIswKhQKmpqZw4cIFx29+5Pz2UqAp55KJooi1tTXMzc0BgOkESrvrGdGuAs1OUispd7z4hacQoO+4EKLGqSAXZqKJhD/DYzASZ61oKBCh5kTpYzkIWHTSDFMSqwEgoiH8qg69oRbcM2r/M6YEqlGkmYQIM7OItCgFgwhRscFFI7SKi9YppYGd5KAZCbRcLoeBgQHfRPXIyAieeOIJXLhwAdVqFU899RQeffRR/PCHP8T58+d9OaZWoyvQOpBQqPZojWVZ3y425XIZoiji1VdfxdDQEC5dutSQPuQ2fjtoAHDjxg2sra15Iszka/uZ4pjNZjE3N4dcLofJyUmcP39eOifdWBOAp31opMRR3k/HsqztoBMj7Dho7YodYfngnzwFaF3mTL4VgQoFUXaK6vWeEZdNuVm3Xd7YJLaDTpwUagr0+s90IQJMT6QB2i5aha6ZUirOniO9aEqULpoCLWFWN+/aIDiELtVOYkGWQkpcNEoALv7RU3jl//FXpHWKQLubHLTd3V1fSwuPHz+O48ePS3++cuUKUqkUvvjFL+JrX/uab8fVSnTGmdilDuJe+SFOSqUSMpkMlpeXEQgEcN9992FiYsLz4wD8i9knpYxA7YLvlTAj+JFsCEBK5XvllVcwOTmJM2fOmB5QbBciRrwUaBRFoVqt4uWXX0a5XHasn05vPfnroyhKV4S1q4NmlwAPCCruGV2l6vt6NN4SpThT/R6OArj234CqBlGUgjWRZrL/rAGLLhrKNBDzZ/yJyFIIlGnT4xEohUNq6KLJyhytumaaP3I/2ZHMQwuwd8obRbr298vLy7pDi92mUwRapzloeg9GW3EG2kMPPYQXX3zR78NoGboCrc3R2qh5HRRSKpWQTqexsrKCI0eO4MqVK7h586ZrzokZSO+bVyjfA6D2lMjOLLNm8NpBy+fzSCaT2NraQiAQwPXr110XZgSKojxNctzd3cX8/DxKpRLuueceTE5Our4hsuOgeZ1s6QR2nL+LX3gKAl0TaeJ+UiNPi6Cr9T+LrlDgI7KyVNKLVrHnNtotdVPtPzMxoNoyVg+vEAR6rF0zKLlL5oZIU7poyvJGpYsmCweh2ICqi6aH0kWjSwGINjSWWWGm6aKRv6dFULziPC7LEktlLtp//Mf/iS+dPw6WZRGNRhvGVMRiMVcDPLwsMXcTI9epXRBF0XSJYyvxk5/8BCMjI34fRsvQ/mdiF9UNnFdBIfLhysPDw3XDd/0OK/GqxFFNnCYSCWxubrZMWIcbFAoFzM3NYXNzE0ePHsXZs2fxxhtveCbOCF4ItHw+j7m5Oezs7GBwcBA0TWNmZsbVNQl3Sw8aYK3EkYgzAOBlpxwRZ8Q9o1VEmFlhRv6taOdO2Yr9Z3oQt8iiUJMwIdIoRi7qFCJNrb/MqNTRIqQ8Va2kUQ1KQINIa3DRZGWO0kDpZgS2znw0kQYovhaGQ/5MvvbxH76F7//f75dCcwqFAra3t1EsFgEA8Xi8QbiFw2FHSqJJSEi700lOIKA/cDubzToa1FYoFJBMJqU/ZzIZ/OQnP8HBgwcxMTGBT33qU1heXsZXv/pVAMCXvvQlTE9P4+TJk6hUKnjqqafw3e9+F//6r//q2DG1O12B1qG47aAVCgWkUimsr69jdHQUjzzySINT5GcPmBfrk/APpTDzan0t3BZoxWIRyWQS6+vrGBsbw/Xr1xGNRpHP531xbtwUaOSms7GxgYmJCZw6dQo7OzvIZDKurKfG3Z7iqMbDn3sKFAVg3z2TovVle025MJO7Z0qU5Y0UByCoLuw0f0a79Z/JUf7qFOmmRJpV56opdBId7bhoBNpGeaKdf2OEmosmh+LvlPRSYi1G/eDBg3Wja0hQFRFtuVwOy8vLKJfLCAaDDaLNTplkJwmbWCzm92E0Ddl36H0muVwOR48edWzNV199tW7w9Mc//nEAwAc+8AE8/fTTWF1dxeLiovT3DMPgE5/4BJaXlxGPx3H69Gl85zvfUR1efbfSFWgdgNqGzC2Btre3h1QqhY2NDYyNjakKM/kx+CnQ3OrDMxJm8vX9dNCcng0mHxMwOjqKa9eu1d3MWnH+ml1KpRKSySTW1tbqRKhb6+lxt4SEWHmdQghSaSNv0bClTJyicnFmyz3TQqAQqCgtGZXvUygvrch1q2ubZt9NE224V1SZhmi2x8xsqaMeTMDUa1OOUFBz0SiOahjBoOaiKaGLgbrPkRLNuWhWwkKULhr5M7Afux8EHvr8Uzj45p3381tf+U1QFIV4PI54PF43BJjneWmuoHIoPCmTJKLNqEyyUwRap7wOUt6ody9wusTx0Ucf1b1+P/3003V//uQnP4lPfvKTjq3fiXQFWofitDjK5/NIpVLY3NzE+Ph4w+ZcjU5z0MrlMtLpNJaXl3WFGcGvoBZyg3FKoMkF6fDwsKYol6cbeikSnBRMlUoF6XQaS0tLmq/V6x6vu21QtRGX/uApUEGVCkITpxxdoaRZaGoEKsalb1b6z+Suiuom34Q4U/4cgqZoc/CjD5RoCPFGAUUZpDSqibS68kY5Zdr0bDirNOOi6f5cWZkjXXa3tM+MiyYney+NgbnaF9/1a3/Z8P3f+spvAqjdJ5RD4QFIQ+GJcFtcXGwok5QLt3A43HHCpt0x8zpaMSSkSz3tfyZ2Ud0MO9X/lcvlkEwmsb29jaNHj9Y5CUYEg0FUKpWmj8EuTqU4WhVmTq9vFXKjbLYvQC5WzApSwPuGcScEGsMwSKfTWFxcxOHDh3H58mX09vZqruelALpbetDMiPpLf/AUhOAdV4u4Z7qDe+WDgHWwGxiihC4FPOk/o0sByaZRE1FOoSXSVJElPlpy0gygqgFNN4/ad9j05trRe0FTPWcBIrYUJataLpoT4swoLKTue024aMC+SEvu/4XiWqAm2oA7ws1MmWQ+n8fKyopUJvn/s/fmwXFc973vt7tnsBAAFxAkuIAgARIiKZEgKa6QZcW5VqzI8rtWfJNSUvVix46d5/vKfnF445Sd69j17Kq4HMWx4qWiJC6VXypx4qTqxlWx81xWZLu0VuVZtiXZkgjMYCWxcME6M8As3f3+mDmN06fP6T7d0zM9M5hvFYvkTG8DDAbn09/f7/vTNA2xWCzyNMly1Uig6RbQZppmTYaENGVX/f0ENSWleDyOTCYTeP+lpSUkk0ksLS3h0KFDOHXqFFpbW31fQz07aDSY7d27VxrMiKIscQSKv2yCpGhms1mMj49jZmbGE1ZoERis9i+5cgCtUChgYmICk5OT2LVrFy5fvuw5SL0eShzrEdAA75AQQ+I3Fh1DTkTgjHXPFF2xORCOWVgy58sqkB64ViGp1OBlww8USb6NfUEaJVlIkwEwt21cj50XQ5RsWIiUqIh9QL7MkZaWUbh9hV5lvCTRUS0Uwc2IA0tDKnaNGQDvxgfn58zNbfMqk0wkEtB1vawyyVpQo8xBk3XQaAhvqvZU/+/Eprh3noP2oC0uLiKZTGJ5eRn9/f0YHh4OnMpXCyWOQXqxygUzoqhKHEn0vF84zOVymJiYwPT0NHbv3u17uDjtoFVTQV6rruuYmprCxMQEOjs7cf78eelfVtV20LYSoLnpyp9+HaDcMzW/6WoQIGPhTM3LQV0QEfckcOR+uRKs/gms2YDKT/9ZSWxZHYE0r/JGx3HWNYcjZXu+NB4hKIDRx+G5aKTnzwvGVNoN0xVPFy2WDhbDzypWGkRNnDObo1aSltt0yoAisJH3OnHRCKRZ1+v2thT9PvTptpEyyba2NrS3t2NgYACAuEzSNE1bGAldJlkLvbONMgdNBtBWV1dDTXFsKnw1Aa1B5QfQTNO0wGx1dTW0IcO1ELMPeNv9RCyYyTpHbuePwkED/Ll3+XweExMTmJqawq5du3Dp0iVPF4knMkA5CkCTPadhGJiZmcH4+DhaW1sxPDyMnp4eX4uDWuhBa8RB1W6viZQ2KnoR0NQ8oFOGvsr5mPGCs2I/mr9rDOqWldN/FlQ2V60tnPermtFgtlTx5gQTEMJCHPt8oHMEcNHIPDJH6aMPF80CM0nR5YyaS+cAKX+EASwfUzdLHWVEfgY9Pj944PY3//fD1r+9yiTT6bSjTDKMNMly1SgOWj6fd30d2WwW6+vrTUCrcdX/O7EprmTKC03TxJ07d5BMJrG2toYjR47g3LlzoQ2XjrrEkdwJ8wI0utcqDDCjzx/V65cBtEKhgMnJSUxOTmLHjh24cOFC2R/YUZR1ygCaYRiYnZ1FIpFALBbD3Xffjb179wa6a1svJY7VDmsJQ7zXed9niqEgigIYrXwYY8XbRtEBxOlyR+bcLot0rbSYNmVurkdZwSV4CcQdMtrLf9+qGyof+Ari95qaVWFIuGMyLpprOSTjorGJmSIYU3m9ZAIXTc2W9zMlBDOq/4znotmkAjCK73O19HGrt9hdNDNWHBmxfEzFjiQFtV4fJQFv7vzeZ/5f7uO8MklaYaZJliMy3HkrOGhLS0sA0OxBq3E1Aa0B5DckxDRN3L59G4lEAplMBkeOHMH58+dDv3MUdYmjoiiukFQpMCOKxWLIZrOhHc+P3ECpUChgamoKk5OT6OzsxL333htaLXq14QUovlbROU3TxPz8PBKJBAzDwF133YX9+/eXBS7VdtB4JZVeDlqjaOSzxbJGgyprBOzuGSuyDc898zPbTM0pQM59m8jKGwNKXVc3Ia2Mt7AQ0tz24UAaKW+0PVZmqaNfkXAYKfjmyI+L5tc1Y0W7aKyIq2bGKBcNAAxgrV/F9inJr6lkz5qs3HrbAO80SQJvbJkkDW1hlEmSz/RGcNC85rmtrKygvb1dOvCtqWhU/+/EprjilTiapolbt24hkUhgY2MDR44cQX9/f8U+kAigRXknnweJlQYzoqhCQkTn1nUd09PTmJiYQHt7O86cOYPdu3eH+r2J4jXzgIm818fGxpDL5XDs2DEcPHgwlDuvBJiq9b4OErMPhDdmoVriXqtShDFFB9eZUnOAUV4lNlfauhJ4wV4V+UmfYNbWlpvmAkGiWHeF6mUj7pQXqKmUs+bHSQv6vKgXzXreT0kj46Kp62qgkQBBwEzWRSPzAMn/lcKme0b+hgmsHlbRNe3DSaMl2bMmK6/eNkC+THJubg6ZTMYqk6TBzU+ZpMxw53qRV9XQ0tISdu7cWVe/H7aimoDWABKFhBiGYUWtLywsIJlMIpfLYWBgAH19fRW/U0Q+IGR7wCohug+MBjM/6YRBVSsljrquY2ZmBhMTE2htbcXp06d9913JKkhgRxjnpAHmzp07GB0dxfr6OgYHB3Ho0KFQf+kSyKsmoNEOGilNzWaz6OrqQmdnJ7Zt22ZdFw1o9Sb6mu/7TNE9U/RShHgJxAib+IEzLVdcyBK59Z6R/iLHtQV8C0n3n1VZJOREL7PsUd1QYfjo4ZKFtHKk5BXX2WHWtVCOqqK7f4+tMkhD8YY0ykUj5bFS33OPmH3A3UWjIc3aPlY0S9UCkD6gomPOAAS9cb5bIKvgtgHByiQnJiaQy+UcZZIdHR22z0v6GKqq1nTKpKy8ShxJxH4T0GpbTUBrUBEgunHjBqanp5HP5zE4OIi+vr6q3SGS7QGrpGKxGDKZDF5//fWqgRl97igdtHw+j+npaYyPjyMej5fVd+XnvFGVOC4vL2N0dBSrq6sYGBjA4cOHK3ITgnz9DMOoyi9z4tiRgJNkMon29nZs27YN169fRzqdhmEY1gKELF5yuZznMPlaEv2+vO8zXy8uLGN2OFPygNlShDNaLKxZYQql7QyPjzw1D4BTbudb5bwdyg0ICbi7tq6WDWnahgK9LdwbAmpOgSEIJFFzpZ/BgIEl5bho3OOJ5qSVWdLoKdZFY6+rUHzc0DZLflMHVHTOcr7fYUNbiDeIqlEmaZpmQ8AZ4A1oy8vLgYLAmqqumoDWAGIX3IZhYH5+HgCQTCZx9OhR9PX1Vf3DR1EUqxcuioXixsYGstks3njjjYqWMooUVYmjYRjI5XIYGxtDa2srTpw4gd7e3qrcLYvCQSsUCrh9+zampqZw+PDhUINueKIdtGpJ13U899xz0DQNp06dwq5du6yGdnaI7MrKCgDgpZdeQmtrq61Pox5mERE4U3TYfkMpeb5jxsIakebRP0YU23ACnIxbVm/9Z7RYByYMN40HaaogOETNqq5fPwJgbpDm9rwoCMa2L6cfUeSiOUJEJFy0WFrxPQeteBHwDAvhuWhsqSPpQyOPk/e4YhYhrWOeKnc04HT4qGtwXGKFgkb8qNwySQJtdJkkAPzkJz8JXCZZK/JKcVxeXm4GhNSB6utd15RQiqJA13XMzc0hmUzCNE3EYjEMDw9j9+7dkV1XFEEhGxsbmJiYwMzMDOLxOA4fPowTJ05U9RqA6pc4mqaJ2dlZJJNJZLNZ9PT04OzZs1UtY6img5ZKpZBIJLCwsIDOzk5cuXLF9zD1ICJwU+nXaZombt68iWvXrkHXdRw7dgwHDhyAoii29xU7RNYwDPzoRz/ClStXbPOIZmZmkEqlAMDRYN/Z2RmZy03rD/79teLiTy/2nhH3TBEkNxI4C9KHFnOJKmdVTj8ar/+Iv3AvPqh3eLyvyug/81IspQkhTZGYpebHSVOzCozW6CBXLShSpZmxUsmrlwtLu2jcnjMmPCQsaTnvQdZAEdIUcxPY1neraF8UvNcEXxZpNy3k0kc/8nLb6M/LPXv2WI8vLCxgfHwc+/fvRyqVClQmWSuSLXFsqrbVBLQGkGmaVumToigYHBzEgQMH8OKLL0ZWYkdUzah9Gsz27NmDK1euYHJyMrK7X9UqcWSTCo8ePYqlpSW0trZWvca8GimO6+vrSCQSmJubw4EDB9Df3w9d16sCZ0B1erwWFxdx7do1rK+vo6+vDxMTEzh48KBtG8MwoGka3rPjA9Zj/2vlKev6NE3Dzp07bb+ITdNEJpNBOp3G2toaFhcXMT09jWw2a3Pburq6rEVItd5Dj37xX6HENhe5JC5cBGci8ZwFWqpuLwfzWnjLKrbOcUw46zcvvtLS/EWfJ7iFJL9umsJ8vIcNaaxLRtw10fN0Uic7uJy3DSuvXjRLAhet3KTG4kXABkm2uWfU4wSYtA1AbyuVAMchdNHIPoZW3GS9W4WqAy1rJhRj88AK+2tL4KaVFTRSxQoEGbfNNE20trZi//79tm3YMklyo4tXJtnR0RHJ711aJHvA7Ybb8vJycwZaHagJaA0gRVGwsrKCoaEh7Nu3z7qr42dYdaVUjWHVPDAjtehRRv1XusTRNE0sLCwgkUigUCjg6NGjVlLh2tpaJHBeyddMh7z09vbiLW95Czo6OpBMJpFOpytyTp4qOZB7ZWUFY2NjWF5etvrocrkcJiYmAMBKjzQMA4/1/B+O/WlY+yr+HkAR2uhrJ4uKvXv3Wo/n83nLaUulUpiamrK+pqzT1tnZGfpNj7f+cXEQNYEzskCmF4Qil8xapJYmWrgGgGSLoQluknXLYkyYSKByNh9iwU3fRi1wQ1jrsqEaYfSmCc9F/UpgIY0FMPJY0H4zN3m5aPT3mC4TFG7PwJljULUPF82Pwwt1E+JUarKLES+50KX3PCmNVEwUAa4UIJLrUhBPF69PMUzbjQU/5Y9SwFZD4UV8cPv/yiqTjMVijgqFapZJkt+/Xg7aoUOHqnI9TQVXE9AaRKdPn3YsGGsF0CoFSG5gRp8/qq9BpV47PS4hm81aSYV0uYWmacjlJJtwQlQlHDQCKNPT0+jp6XH0EkYxey3sc6bTaYyNjeHmzZvo7+/H8PAwWlqKRJLP5y0oMwwDj3b9jq9j09BGiwa3eDyOXbt22e6qGoZh6227c+cOJicnbSU/bG9bkDvHBM4UvbiAJICkFEpuACOeK6JJjBuU2cbzGGTRXAPhZ3QAhd7uY5C5j7dtUEjTNhRPEA5TroEizPtFZhaeogMaBxQdolw0PzP2RKKdMlv/Ge2oefSo0f1p9HueuGi2/jVj01HLdyhQCkAsWzwHcdRMDbYbAA53jTwetPyxhoCNKGiZJEmTJODGlknSJZJs+m5YKhQKUBTF9bjLy8s4ffp0qOdtKnw1Aa2BVc3ywmpeAw1mPT09XDAjisViWF9fD/X8siIBDmGl/dEDxr0i5KMKKAnzvCROfnJyEjt27MClS5e4yVNRABobfR9UGxsbSCQSmJ2dxYEDB/DAAw8Ih4f+1473ln0+Wjxwo6FNVVXLbevt7bUep/vaUqkUbt++jXQ6bW3Plkm63cml4cyIl/p4tCKc2SCMROsLStaI2OeUAqAxkeO27SXcsmLCo/d2UYp2bgrEWQtp3at4g6RdAAAgAElEQVStq8IyRLa8kZa6ocAIudTR63k/8GntJ9mLBohdNNeSSUkXTfNyzLwi+EtljbQIjKmFTSgjZY9kRhodIqICMEof32pesaCLLn9kHWYCbPRrLHvGWp1AGxAsTXJpaYlbJkn+LqdMkvSfue3fLHGsDzUBrUHE+2GM0j2qxDVks1mMj49LgRl9/ihLHIHiByZxQ4Lqzp07GBsbQzqdxsDAgOeA8Sji7oFwUhzJQO3x8XF0dnbi3nvvtZWXVOKcflUuFBJXcGpqCnv37rXKNWmZpgld1/Eb3R8q93KlJeO28Up+DMNAJpOxQRtx29rb2x1u28P/8x+KPTOGHc6MuH3RT/rQjHgJlBi5LQTVbPBwD5uTIZPoyFsLBeg/CyL2a0BgreDDVfMScetsZZUS4kGaMPAlq3g6k0FLHQnYi0CKhTRS2liNYeVuYCYcVi1y0UjvGSfl0SpvpD4qWUiDCeitSuln0ISik5smigVp9PU4yh/LSX60jlF7cOYmL7cNKL9MkvxbpkzSK8ERAFZXV5shIXWgJqA1sOLxuBUdG5VisVjZpXYsmF2+fFl6hkctAFo58LC0tISxsTFrtteFCxekPqSjGpJN5q8FkWEYuH79OpLJJFpbWzE8PCw1ULueShwLhQKmpqYwMTGBnTt3ct/LxHU1TdN3OWOlJOO2kcUELdZt+++fexrZHQr09qLbYUV/l76UCg1k1L8tldZuJL2RVwIJ2Ptw/EjKLauB8kYZWaAmAVUyQ52BIqjJQJpCxev7cdK0rAJd4KR5OWhalkTri0sdlYJ3DyItXmAI66LFMgp/GDl9HI6LFqjkVlDqyBMBMtFga0Wn3C+q95M8ZmgKVJjFckcdMFXyApwnVQz3a/GlCsxRq7Zk3Da3Mkn6ZtfNmzeRTqelyyS9EhxN08Ty8rLrTc+makNNQGsQ8RaxtdCDVg4kZrNZq5Rx9+7dvsCMKEpAUxQlcMnf8vKyFRZx5MgR37O96slBMwzDGg+gqipOnjzpa25bVCWOfs7JDpk+d+6cY/wFHQBSK2DmJr9u23/5v/4W5g4FhrYJZ6q+GRFOL2BVt9I50f0eww5m7MJatDCnwxiCzEOrddGgFqQEkO05koU0Wn4gzfNYQV20EsCJII24aGz4i5vIe0c0qNptP1k3VeiiibZxKXV0/F0CMvrn0eoB1TchjXbfTHXTTSM3K2iw2zyp/9dhU52UPvqRbJlkV1eXY2ZrLpez3DZSJplOp2EYBrZt22bdIMtms1BVFaZpCn+HNmP260NNQGtg1UIPWpASRxbMRL1HMorKSSLyC4grKytIJBJYXFxEf38/zpw5E6g8MsoeNFlwYccD0HO+/CgqB02mB43MpkskEtA0Dffccw/27t1re431BmZeYsEt9ZtXoLcUQyNMtfg3C2dqAdDJ/Qc6udHlnoTIPZOVmueXTTaEOG/NWKYIxjKOmpe0jH9IUjcUmJp4HxLK4eaiWcdio/WzdLS+InTRvMSDM5GL5ve9Q1w0C+pYV036QPDtovEe40GaBZomHdGvQNUZICNuGlX2SH+NFB2QKX30BWxAEdrqHNJ4ki2TbGlpsfWOsWWSa2trWFpaQj6fx3PPPWe5bMvLy1hZWcGFCxewY8cOrK6uNnvQ6kBNQGsQ1aqD5gdQaDDr7u4uC8zo80c5C04WlNbW1pBIJHDr1i309/fj1KlTZc31igrQZBw0kkI5NjaGXC6Ho0ePoq+vL3CQSi2WOJLXODo66hgyTW/TSGDGKvWbV2BoCvRWFBd8qlJc9Bmb7VnEKSNwpuqbkeC01Dz/cYAaVi3524z0/LCL7qDz0Gqp/0xGfkof3aStK9z0SLq80bGP5Iw0FtK8yhtZsZCmZu37i1w0v06Y3319RedT8uuiaXnqhgd5XlDqCIA7L41AmlownU4aOQ6vHNG0fx2sPjXO9ZcNbA2soGWS4+PjyGaz6Ovrs9y2Z599Fl/72tewuLiIPXv2oLu7G1/5yldw8eJFDA8P4/jx474qdGg9++yzePzxx/Hyyy9jbm4O//qv/4pHH33UdZ8f/ehHuHr1Kn7xi1/g0KFD+NSnPoXf+Z3fCXT+RlYT0BpYtRIS4gVolQAzP+evpLwAMZVKIZFI4ObNm+jr63NN8fOjWnXQ6LCTo0ePClMo/ajWUhwXFxcxOjqKTCZjvUYaPhsdzDL/7QoKbUUYM2IoLfSUzdlmqv1vYHNRKIIzVopZXO+J4MzheBQAhPExUCf9Zzyxi3MCanoZ891FkOa6T0BIYxX2bDS3njDWRbNKaX3AHG9EQ1AXTcvCDjx0cAfZJr/5OP29J/8mcwe50EbKJMn+pc86els7jJbKRw3T/vp0ZhPBtytw6WMDumle8nLbCoUC4vG4rUzy4x//OD7+8Y9jfn4eTz/9ND71qU9hbW0NX/7yl/Hzn/8cuVwOJ06cwOnTp/Erv/IrvmApnU7jzJkz+MAHPoD3vOc9nttPTEzgkUcewYc//GH8wz/8A5555hl88IMfxP79+/HQQw9Jn3crqAloDaxacNDcyiyz2SwmJycxPT0dOpgRxWIxa35U2PNGZCQqsUyn00gmk5ifn8fBgwfx1re+Fe3t7aGeNyoHjQdLpKduZWXFV9iJjKLot+O9ztXVVYyOjtqGTNOvkQCdYRh4d+f7qnq91dDGuy+XwKwYmmCQu/JxdzhjXQcrHCS2CWdccJPMHtI4aY5SyYzl3DcwOAv+0rqyEN6POV8+16zaBqAL7gkJZ15Rj2ulskAvUKNBm4U0qZljvGPmFOHi3qvUMaiL5hZAI9rXM0JfQqYCxAJOjOGBGB29b0GbRrloJUgjJY6+nUWRk0Y9b/3Tr5O2BcFMVvl83pEITLRv3z7cc889UBQFf/u3f2v1Uk9OTuK1117Da6+9htXVVV/ne/jhh/Hwww9Lb//kk09iYGAAX/ziFwEAJ0+exPPPP48vfelLTUBj1AS0BpGoxNEwDOi6XrZLEVQ8F68aYEafHwgn6j6IWEDLZDJIJpOYm5vD/v37cf/992Pbtm0VOW8tzEFbW1vD2NgY7ty5g8OHDwfuqXNT1CEhbkOmiUhkfiM6ZgCQeuwKgKJTZpScM9LfYmooRn+XftvQi1h6AWfE7HAmkpq3L6zZbYO4ZX7LG20LbnbuLo81qMfoRbbIPREBU6VEXk8559XWFdeeQec5vZ00LauUVRqq5hWoOfH7iUCaTKKiosM5982Ap4umrcMJJj5dNC6YiYZX04enH+ekOrKPqTo2A0ao52hI44aNWH9znDT2W+zBVlJuWh0Mu66W2F41rxRHNiBEVVUMDg5icHAQ7373uyt2nUQvvfQSHnzwQdtjDz30ED72sY9V/Nz1piagNbBITXE+n48U0IiDVSgUMDExURUwI1JVFYqiRAZopMRxfX0d4+PjuHHjBvbt28edexWmiKvkluRUCRFYoqHl0KFDeOCBB8rqqZM5ZzWlqipyuRx+/vOfuw6ZbnQwy/y3K8VSqRKYAfbwASOuWAs+urSKjfcG3JMbgU0Hxk9MOlCmE4bNxTHXQSjjR8ttUc46LorpdN5C6ddhjuHmpslIy5ZXMsmT23By2feEWpDvUQTC60XTAjpeRL4cMxGkceQWHmKVN1I/t3Rqo6mSNMfSzzHzHqKHWttcMnJ89sI4aY+Aj/f3FoUzFsyIvABteXkZO3bsqOq6gNb8/Dx6e3ttj/X29mJ1dRXr6+uhVhLVu5qA1iDi/bCpqhp5iiGBxDfffBM3btxAd3c3Ll68WLWIV0VRIu9Dm5+fx9jYGPbu3Yv77rvPMSuqEqJnsIVVSiijQqGA9fV1vPDCCzhw4EDopZs8VRvQcrkcMpkMRkdH0dvby/2ekh6zRixlBDbBDODAmbnpoNF34wE7nJFFt+fi2ZRLzCMuiBeQeT2vbcBXb1G1RC/W/ZZJ+onX1zaK2wcFLR6kib5/2obi+rUmjpUbpJHtuNH5EmWwsbRcqSN5fzncVoGLZoMzlpg8XDRpMPNIcWS3cXPPbM8zA6+taH1O35u1Dbl+notW2t5W8uhR4CEdy9+gyY4iicCMiPSgibS0tNSM2K8TNQGtgcQLLoiyDy2Xy2FiYgJAsdStmmBGK4pyPxJ8srCwgPb2doyMjDjmmlRS1Qa0bDaLZDKJmZkZKIpScYeQFom8r7RbSA+ZVlUVhw8fxokTJ2zb1OKQ6TC18e7LVgmjqRUXRoZWgjLNDmd6vFgWZcQ3vyfsooznmtGwphbsC2J2Ia3ogEYdM6hbFkaPUKXEW6TSC3ib4xXiOlXkhnktrN325ckLvsKSXxeNlt+h0rGMRPiHwOby3WcWsNTRdim8sBAOpAFF8OKVOBaf2wSrzcHWdldtMwGSvgDOywoSHNLgoOYFZ4D/Esdqa9++fVhYWLA9trCwgO3btzfdM0ZNQGtwRZHkSMBsenoau3btgqZpOHHiRMXLGUWqpoNGv/bu7m4cOHAAqqpWFc6AIqwrilJxMKVf7+7du3HmzBn8/Oc/rxqcAbDCXwzDqEgpL2/I9MzMjK1ks9GTGQEg857LMOIKNSvJhKkppcUYNv/mwJnCxucr/H4zsoi2nnP5dqp57zI0N2AjYQ9BS9l4i2uv/rNKiIbLMMoL6YU6AROZ47IL/LAhjd2GdeVYF43nnrGQRl6fn8AQVXd30TTRnDOPusOgASDliP56kKRKGtbI63d7zFRLvWtWYiQFYzQvlSDRERxCPUerGRyyKRkwI5IBtChnoI2MjODf//3fbY89/fTTGBkZieiKaldNQGsgRe2gsWBGHLNnn3028qj7Sp8/n89jcnISk5OT2Llzp/Xak8kk0ul0Rc/Nk6IoUjPJgqpQKFivd8eOHdbrTafTVXcrKwVopmlibm4OY2NjjiHTN27csJwy0mf2a9vfH9q5a0mZ91wGACud0VRL7hmoxRY1qLa4YCvFcvPi8zmLVFtyo2QvWhApBU7Qg+MEzocCQ5xAlZiJBvDDPoTljT7Ws0F7y7Ss+9dOpT4qWADjfZ+CljqKrk1mX557xoU0BHBiS9BWtoMrcNHUHAM2dBw/2aaw+TgZWE1vS/eg0ZDmACYLwCinje0nEwWHuL002W0bMDjED5gBsELhvHrQwgQ0MiqIaGJiAj/72c/Q3d2N/v5+fPKTn8SNGzfwd3/3dwCAD3/4w/jqV7+KP/qjP8IHPvAB/OAHP8A///M/47vf/W5o19QoagJag6sagJbL5TA5OYmpqSns2rULFy5csH0ARD2PrZKARoPK9u3bHa89yh7ASpR26rqO6elpjI+Po6OjA+fOncPu3btt56xGuSEtGtDCED1kulAoYGhoyDFkmriTjRwAQsoZLRizShiVTSAjZVOlf9OOFV3iBFDBILzURY7YBbBiAgr1McIu/HluGRuJXm5gSL2IXvAbIWUjxTIBIS0H6JLXIOukuUkpFM8pHGzuo9RRNNScu20GDriXcdHCLK/VaNeQ/GwqDCB5PU6HeViPKVZpI2AvZXTsUzo3F9TcSislIvi3UnCIXzgDYK01vBy0I0eOBL0sh3784x/jl3/5l63/X716FQDwvve9D9/4xjcwNzeH6elp6/mBgQF897vfxR/8wR/gL//yL9HX14evf/3rzYh9jpqA1uBym0NWrrzAjCjqkI5KnL9QKGB6ehoTExNcUKHPHUXcPRAuoBmGgevXryOZTKK1tRXDw8Po6elxQFilyw15ItcQxmulh0wPDg6iv7+fO2RaVVVcPfPZss9XiyJgBpA+s02oMsj/VdgWdDScKUYJ4koyFT6csY6FrdQxvwlomsssNJHUvJxLFaYzVglXzFcfjmDbMCL0rWMJSh69Qkh4kKYKflytZMYyv55uIBbL8KHLjwPnVeooFAVpvOHVfqTmigDuFYbiF9IscSCt+G8XSEPpMQaSFF5QCuz9a17Omq/gEDivoR4UBMyICoWCVT0jUtgO2tve9jZH5Ratb3zjG9x9fvrTn4Z2DY2qJqA1kHiORSXcKxrMdu7cKQQzokpCoozCBDRd1zEzM4Px8XG0t7fjzJkz2L17t9AtqncHzTRNzM7OIpFIQFVVnDx5Er29va6vF0BVZ++RX0jlOGj0kOkjR47gyJEjW2rINBFdzsg6Ykap34wsSul/m9rm4ozAmaKbNlAjIqVr3NQ9sjjXNsGseEz7djyw8nJWgrpnZcXry/apVUE2UBOsp0SgxQaDyJY80u6oHyfN62vkdizaRSorGIRytkh/lsy2rHhzzsJwzQiU0XDmCVyScjhbHpCmcuL2WUgSlTva3lseJZC+R0vUWcJjOXAGbPafuVWvRN2D1pS8moDW4IrH48hkMqEcyy+YEUVd4hgGJJGgiPHxcbS2tuLUqVPYs2ePZxlf1A5aUGgxTRMLCwsYGxuDYRg4duyYo8yPp7DLDWVFkhz9qjlkuijimhWhy+6aWaVKVFIjQIEaM9tI0cXfByGcSUbp86TmnYvnwBBUg/H65YgHXNoGALN8Ry1IX5ospMkAmB/go0WARgRdwsAQzvaqbi+7BeDponFdM48AEds5Q3bLPEsdUewpNTRSsmgHJS7I0TDGAbViX5vLi5Aod7SO76Y6gbNywYzIK2LfNM3IUxybklcT0BpIvMVzGD1ouVwOU1NTVgCGLJgR1UKJYzbrMye5JFLaNz4+jlgs5ukgsYoi4p8+t9+vu2mauH37NsbGxpDNZnH06FH09fW5lkzQqnQ4iUh+v84bGxtIJpO4ceOGcF7bVgMzU1VgorQ4NVFy0DYXVySxEdhcZAFMaSPtuJXcM3pxx8oCNrp3jVkEsw6IojsdnSCSLW/kuh3lOGPUdm7zzMIob3RTGKWPWrb4vfBzDC3n7kYRUJcBMHYbTSK5kZYI0nj9ZNxr9QhBsc5TctFcnTMJSJOZ6+Y8OXxBmlowbe8n63Hd5G5vK1FkHDCyHW94tW0/Vh7v50YJDgkLzIi8EhyBooPW3d0d6nmbqoyagNbgKqe8sFwwo69hfT2CDOGSYrGY7yRFwzAwOzuLZDIJVVVx/Phx7Nu3z3fwRdQljn6cLNJ/lU6nrf6rIGWK1R4cDRTBUOacJGl0ampKODi80WeZEW3810ubg6WpIBB7b1nprjd199xgYMoqbWTgTBU4aWYMtoQ+18U6G4uec/b9yJQuSoU85OBYIMvG5geBM0Acre53ELUvMd8WbcMdsKTmnnGO4ZbGqWYBQ8J9kwEwGVnjGyT2d9uGB3S8KH6eixbbYL70IbpmrNx6tWiHkE5wBACFAIwk1BX3Kf3fpQfNcQzAAWqA93vNd4kjrQaHM6CYJu0GaKZpYnl5uemg1YmagNZACstBI5HxU1NT2LFjR2AwI6oFB032/CRancTGDg0NYf/+/YETCaMucZQ598rKCkZHR610pwsXLpQ13DoK19ALCukh0zt27MDly5cdc/m2wiwzoARmVkw+Vb4Yo/vIqB0UxQFh9Mwz2+NUSRQR7Z6pugnDZVVKFr9kcW+q/hflMrCk5TiL6oh6w3hiwS2Iy+UV3EFL2yhuX5ab5gF6rIJCmt/nvSTsLxOUKpLt6YRQL0gTDrrmBWdQ/w/kmJFDccCKuJO2cmIbdClykAb+c6ZKgXkFetACaQuAGZGXg5bJZJDL5ZoOWp2oCWgNLj/9XyyY3XvvvaH8IEfdgyYDaKZpYn5+HolEArquWz1XsqV9IhEXyzCMso8V5NxuoLS2toaxsTHcuXMH/f39OHPmjKP/KoiiKnHkARpvyDSbtrkVwQzYhDO61MgaWmvatyHbsWVNQKkvjfrSs8EiIlhjt1UL3mspt8HVIml5wGTejmHPNau0rNK40tdHpx22ENeffsseHeEhEpBGu6cspIn6EL0gXctt9oKZghacWMa71NEBRAJIY8c3uF4bDXKQ/3aVA2dex3E4bH4hDXYopRMYnSDGJCoyXwDh4GretnXcg1ZJMCOSGVINoOmg1YmagNbgknHQaDDbvn17aGBGX0OtOmimaeLmzZtIJBLI5XK+e65kzg0UUw1rBdDS6TQSiQQWFhbQ19eHBx54AK2tAQYcuZw3ipAQ+pxuQ6bpbbYKmAFwuGbFf29uZ2ocMGNKHOl9rHImatFEA5eiA6rLctThlgWAL27/EPNxFxTGQi9vDFEa5bCFEZ/Pum1+3TB2X9moekDeSVPyYviS3a6cVEfrGCXgYd9XPBdN24C3Mxuia2Y7t58wEUAa0ujSVVtgCMdZAzg9aG7XpMqV1NZbD1o14AzwBrTl5WV0dna6Bok0VTtqAloDSVTiSKbLs/1ElQYzoqhLHHl9YGQYcSKRQDabxeDgIPr6+kKPhqdj56v9ocgC2vr6OpLJJGZnZ7F//35uMEYYiqIHjZxTZsj0VgEzgHLNBKEfRLaQDgX2/hHG9aIX845+NN3+f1q2UseCCdODbNjFrsg9oxeiMjBWVmx+OSr3HIK1JSmHpPvWhOWNPtanVtljgHs3xGGSAS9r+zLuXzmSFNnjS0TvCx02mdlm5Dp4pY7sNhB/G4ImmdJygJnLCV171ajST26MPnUMwFlOKYQygTsWKpjxFAGcVQvMiAqFAtraxHdWlpeXsWPHjsAtG01VV01Aa3ARKMjn8xYsVAvMiGqhxJGAimmauHPnDsbGxrC+vo6BgYHAYRgyIqmGUQCqpmnI5XLIZrMYHx/HzMwM9u7di7e85S3o6Oio6Hmj6EFbW1vD9PS065BpoPFnmQGUa6aWIvPJl8ECMwJqcAaD0KL6z0TAxIMBHpypBTH0ublnVkkctY2WL12Px9us3koZyxHdtxYEqkQSxenLLKhZd0xxCw4pDV3miQBYGC4aT6QMUeiwlSCNBj0vGLNAiRMG4mAm0z1URUaujpkspJFetdLPqqKLHTLeceifcfY5gOPYgXofCaL1y9YWADMiGQetCWj1oyagNZB4P3SqqloOUj6ft1IZqwFmRKTE0TTNSD4YiIN3584dJBIJpFIpC8zKCcPwc/6ogkKWl5fx7LPPYvfu3RgZGUFXV1fFz1ltB211dRVra2tYWlrC4OCgY8g0gC0RmQ8wYAbnApIAG+CEIrrHjD6G4zhMQAjvPERk8aX6XSSxc5JUZ+kiq8AwJlu2WCPljbREjoKfXjLhcGrqcQIwMuDHgptsCSPgDmnW8Rn4ErlnZDteyWCQUkfecUSQ5oAlj8RG8t4O8n6SDtFxgTQRWAHupZBAyV2znlNcgYi8Pk8YreMetKjgDPBOcVxeXm4Oqa4jNQGtwaQoimNgr6ZpmJiYwMLCArq6urhBCZVULBazSsoq5VS5KZ1OwzRN/PSnP8WRI0dw/vz5qoAZUbUdJZJYOD4+Dk3TcPHixao2BVfr9dJDptva2tDf349jx47ZttkqYJZ7+CKMuCLuL1Odt/DZYA8hnDELMif0UYc1nH0kju057pmat39mieamiY4pq8gctQqVN3qJnrsVRq8amXtW2OZvPzXr7pLSC3YW0ngA5tchE53TiDkTFkXwJlO+CBTj9AH5Ukf6xgOZlyajoCMHiNSCKQYcl6RG6/nS/w2NA2mAA454N3SCluLWYg9alGBGJBMSwqYXN1W7agJaA4s4ZrlcDisrK1UHMyLygUGXWVZDy8vLSCQSWFpaAgBcuXLFMfOqGqrWLDRd1zE9PY3x8XF0dHSgv78fq6urVU9sqrSDxhsyPTo66ihn3ApgBgDZ/83dNYOiMPBlf9q2cCblkPRCRhE4afB20kSLVFu5I/NWccBZhWGMG8pQjlvG2S7MkkNPiVy1UglkGKAWy/h/TX7i8GWdNAJ2IjdMyxT/9hNaAvDn7wF8SKMfc4UmjovGm73npbLAjClhdOtBo7fnbWsLCOHuW3xhimAeIsDc3KnTHrTv/O3vVvWGr5tkShybDlr9qDbeVU2FJkVRbAOmu7q60NnZiYGBgUjgDLCXWVZDq6urGBsbw+LiIvr7+zE8PIwf/vCHkdVdV7rE0TAMXL9+HclkEi0tLTh9+jT27NmDhYUFC06rqUo5aPl8HuPj45ienkZPT49tyDQdErIVhkwDm2BmcBIWATjuHm/2oZX+0pj/q3AsFlnnzc9sLVrkDrupAgoNZyE5WlK9QHBClmxgSDlwBojnYJUDbkEXqzLljzLfZ15vmtcimwdponI3Ky1R4msfNJ0xtu52E6HksEkAkWI4XwfXcaMgTRX0qLm5aGW7Znnnm8YPpFnvC1GkPr0bCQnx6F3zita3tgvKVxV0zT71u/fg2WefRVtbGzo7O9HR0YHOzk50dnaivb296snNMg5aM2K/ftQEtAbTxMQEEokEOjs7ce7cOXR3d+OnP/1ppCEdQHWSHNfW1pBIJHDr1i0cOnQIp06dsuLjo0ySrBSwmKaJ2dlZJBIJqKqKkydPore31wLRKOaRVeK87JDpS5cuOco0yDm3gmuWe/gizJgiBjPACWdsmSKn/8y2e2mRSCexsbDm5papunepI09upY1kcam3cnpt2YUr51xR94vxxAM3B7SFsb7kHEPbKK6J/Qx5dsw9k+xNo0vg/DhpSkFcyujVx0QnIioFsYsmW7rotr11LraSmBe9n/V+L7KQVgkwo+UFaSr7cc5+npT2d43TZwBMeBNAEBZSS/1ndDljLpdDOp1GKpVCKpXC9PQ00uk0ANiAjfw7jFmjPOm6DsMwXNOil5eXMTg4WJHzNxW+moDWYGptbcXZs2fR3d1tLdSjnkMGVDbJMZVKIZFI4ObNm9ZcLzZqNkpAC/vcpmliYWHBGqp99OhR7lDtKNIUgfBKHGlnsK2tzXXItKZp+B9nP1f2OWtZBMyATZBRSGAHO7+MkmMx6NF/xtvHDc4Uo3RMnzDm6nqVFpS8pEY2ijxU8KqBIBAutMmu6QKsScni3w+osYptALqf1EQf51TzgCFxbC8XjYU0G8AJIC22wX/cL9R5yiVEJCiceUGZ4xLYEkbdA4JszppkySQkXeUbUpUAACAASURBVPgwetAq0H/G6zNraWlBS0uLrXTQNE1kMhkL3JaWljAzM4ONjQ20tLRY0Eb+bNu2rWy3jfyu93LQmiWO9aMmoDWYDh486FiURx1zT64hbEDKZDJIJBKYn5+3epFEc72iTFIMC5RM08Tt27cxNjaGbDbrOVQ7ioHR5Ly5XPBbvvSQaVVVcffdd2/ZIdNEbJ8ZATMaHhzzyziw5ihh5LSEiuDMWoSpin2RJQEwXimP5Diax0Bb7mtiJemehR4YUkGQoxfpekuZvTglsZfrBU2e5YulXzF+QC22IYYqOpLfL6SJ5okRSOM9z0IXcehEMEYetx2LF6nP6VHjljFySh2DzkXzC2fWOZnvsfucNB+R+pxj83f2uL7qhzJa8hMCoigKOjo60NHRgb1791qPFwoFy2lLp9O4ceMGUqkUDMPAtm3bHODW0tIi3ZqRz+ehqqor6DVLHOtLTUDbAorH48hkMpFfQ1iAxg5cvv/++7Ftm3usWNQljuWee3FxEWNjY0ilUtaML6/AlWr2/bHnDQKGZMj02NgY8vk8jh07hoMHDzbBDBLlhR6OF9cZEgyWtgWKeJQ58sRdzLILP9UJZzLHcWxTg2WLlZaWg7WQ9QrSAOC56GVFUgilyxCZ42t5O6Q5yuMYyfaP0ZDmVt5Y7jwxnkSQxgUoXhhI1vmYV2KjVbbr4z0eFMwA8deNBS630A92P8WEvce1JIeLVkkwK9M5CzOdMRaLYefOnTZIMk0TGxsbFritrq5ibm4OmUwGsVjMAW0dHR3c3/1e/WdAMySk3tQEtAYT725LPB6vCQet3Gug0/t6e3t9DVyOusQxqIO2srKC0dFRLC8vY2BgwNeIAAJK1Z4/F6TEcXFxEaOjo0in0zh69OiWHjIN2MsZhfPIwCtf3HTYbNuwaxS2JNGHk8Yex/EQ862XCuZgz81zwWTcM96xZOGvBsob/YruvZOCNR/y0yvm2Dfv7aTR7xMW0kQDrQkQqboY6qxkR8H9K22D/34n12SqcpBHroX7XuKVLPLcNRbSStvYeio9ZqgVryV8MGPlNoialVcZoxWz7/FrsVHAzE2KoqC9vR3t7e3Ys2eP9biu67betvn5eaRSKRQKBWzbts3W39bZ2ek5A800TaysrFRl9m1T4agJaFtAtdKDFvQastksxsfHMTMzg71799rS+2QVlZtEzu235G9tbQ1jY2O4c+cO+vv7cebMGd/NxZqmWY5TNQHNT0knnbg5MDCACxcubNkh04A8mAFiOHPdBghU5qiYANjyQ0VxgJ8nQPIU8K1JH5ssHI2WiIiqmqcVxehTvWteYCW6XHZhXU5/GnHiZEoTAR9OGhl+7rG9qoshTdHFkKYJZrZ5lToKr8OjBFK4LS2X/YLCWSCnUTDjzHpa8r5cRSP1K9RrVm1pmobt27dj+/bt1mOmaSKXy1nQlkqlcPPmTWQyGSiKAkVRcO3aNQveOjo6bKEhy8vLzRLHOlIT0BpMteqgBYHEXC5ngdnu3bsxMjKCrq6uQOeP2kGTPXc6nUYikcDCwgL6+vrw1re+1RF4IitSBqHrelXjfmUcNPp19vf34/Tp0w4A3apgBgjgjFMqZEkA4A4njTpOcQNO+aFEaAgXBiXgTNY9YxePpuIsreKXnPFixOWcv3Kj9Ks664yRo8yQinAvJ/zDOp4AtmQW0bL9Y0Dx++5nec1CGvu+YSGNft4N0kTPcfvOIIA0Uw6CiIvm2W/GQFoQMAsCZdwSVUWxgZA0mNGR+mHH6QN145oFlaIoaG1tRWtrqy0wyzAMTExM4M6dO9A0Dbdv38bk5CS+//3v4x//8R8xNDSE48ePo7OzE4uLi9B1PZSZtF/72tfw+OOPY35+HmfOnMFXvvIVXLp0ibvtN77xDbz//e+3Pdba2oqNjY2yr6NR1QS0LaBaCQmR/UHM5XKYnJzE1NQUuru7ubHqQc5fyzH7QfrqZM4LFAHNLXo3bLm9XrpMdf/+/dxgl600ywxwcc04QOUVpy+SjJMGyLlpMnDGk2LyQwgc20ks9uRLFKsDZwAnfZHZNgxQiiqlkUgWttjvM7uf2/fYzRnjwUKYTpot2VEAaVpWzkkjX3e3WWj0tn7KaSOFMyKJQdTWprzvN1vaSf7Jc++9VCaY/dkfjGB4eLisY0QpMmu2o6MDx44dsx4/ceIELl26hFdeeQWvvvoqUqkUHnnkEQDAqVOnMDw8bPvjZ1but771LVy9ehVPPvkkLl++jCeeeAIPPfQQrl27ZgtGobV9+3Zcu3bN+n9Us2nrRU1AazDVqoMmA0j5fN4Csx07duDChQuhNbTGYrHIglLcyivDKN8USVGUSGah8Rw0tyHTRFstAMQCM5MTAuKAotJfjt4yTtkhR479AsDZ5t1v07GNo2RJUZwtODImbh32gXHFuWZRXHoo4MaTwFUTpjSKoIl5nECMrCtG76cYck6j38HTnjPRdIgdmxKIcZMdBQDnVdZIf689B1aTY3qEhpD9ZPvAiEIHM9iDg1zdsBAi9aVEf+75hLUnP/OQNbesnsULCenp6cG73vUuvOtd70IikcDly5extraGiYkJvPbaa3j11Vfxgx/8AE888QROnTqFf/u3f5M+31/8xV/gQx/6kOWKPfnkk/jud7+Lp556Cp/4xCe4+yiKgn379gV/kVtMTUDbAorH4zAMA4ZhVH2yPX0NIkihBxF3dXXh3nvvDb2RNcqYfd658/k8JiYmLJfwypUrtlrzsBTFLDT6nLquY2pqCuPj48Ih01sSzMhA5lJcPllUSEXjCxuIfJCMR2hI8Vo4d6+lesrkHLag4BWZe1YhseCmtxRdGtmSSb8lYTG6V62MskziGLLhJJ5x/Fkx3Nmi9UnYR2mVUk4apFdwSBDxwEsx+EDEHW6dg3doCL29TzAr7uNze5neMN4oDMbtDwvMApU7MuWXIpFyxmQyKR28VcsqFAqeQ6p37tyJlpYWnDhxAidOnMBv/MZv2PaXVS6Xw8svv4xPfvKT1mOqquLBBx/ESy+9JNwvlUrh8OHDMAwD9957L/70T/8U99xzj/R5t5rq/13ZlKfID20+n0drazSNErwyy0KhgJmZGYyPj6OjowPnzp2zDdgO+/y1UOJIw+j27dtx8eLFijbtRgFoqqqiUChgenpaasj0VgIzmLDgzNGzpSpyPWOctYdswqF0qWOIKYfScFaD8GRTla6FABsBIAJRWrZ8t83Rq8acwyGJhbaak0uQtKU2+uxLA+SSG4OWO5Kvg2hEhMhhcxyfbCMo3ZUpd+RBmpY3/ZVA+vhVJwNlRFw4s20gEQAScaQ+22dWKBRC6ceKWoVCQTgHFigCmluriB9IvX37NnRdR29vr+3x3t5evPnmm9x9jh8/jqeeegrDw8NYWVnBn//5n+O+++7DL37xC/T19UmfeyupCWgNJh7ckPrkqAGNAJKu6xaYtbW1YXh4GD09PRWtR446JISUb46Pj6O9vZ0LLJVQtQHNNE0sLi4im81iamqqOWS6pNyvUq4ZmIWaKBqflRvA0AsTl58jbvgHA4BlwVmZP8PsbDRHmaQieXdeAdiVoM5JeKwIAJZ7TAFEAT6i730ucq0QENnZZ2zZY87f/gCnL81ttplkciNvG1/BIYLSRdm+M0t+0ho9IE0r9ZvJlEBWZgacZLR+lIOoJcsaeSEguq5Hti4KU15z0IiDFlXf18jICEZGRqz/33fffTh58iT++q//Gp/73OciuaZaVxPQGlCKolhzo4iiDgohfXDEVWlpacGpU6ewZ8+eqnxgRBWzbxgGbt26hXw+jxs3blT1NQPVAzR6yHQ2m4WqqnjLW97imGVG/myFWWZACcxiAjADHEAjC2bibeXfV9z9OUEeIoeNW/7IfO5I96dV4ceBF6zAgzauasjJ05gZWWHOPwsCWrREaY/C8+Xt7w+pmH0PAONt43jeLTiEgS5yfK+YfYfDxgMvQwAyvOAQzvvVvQSS/7hIvvrM3LaLEsyAQK4ZrUZy0GRKHMNQT08PNE3DwsKC7fGFhQXpHrN4PI5z584hkUiEck2NqCagbRFFGRRCIEXXdUxPT+PkyZPo7e2t6p2cajtopmlibm4OiUTCguWRkZGq9wBWA9CWlpYwOjqKVCqFo0ePoqenBy+88IL1Wsnr3yqR+UARzADY4IwtT/QMBrGe4DzGKXV0hIa4/HyVk1oYtsMWermj9LXwF8E80fsbcZcLiQDkZKFKuAjmPK7mitvzhk3LOJh+Uhtt+3HAyi250Q1KygoO8TnzTOSwOaLxS31k3P5IOjjEpd+MhbSq9Zmx29Q5mBHput4wPWhur2NlZSU0QGtpacH58+fxzDPP4NFHHwVQXOc988wz+MhHPiJ1DF3X8dprr+Gd73xnKNfUiKr/d2VTDvEctCgAzTAMC1IIjF26dMn3wOUwVK2QENM0sbCwgEQigUKhgGPHjmHPnj344Q9/GElISyVTHNkh0+fPn7fGKRCnDNhaYAZsumaKWVpMcXrNWJUb8853w9wXeY7N2euShbMGF/u19Yo4Z4dlqzlTfoC2nwUrs61KOWt+ExZF0kq/MnigxspR9kilPYp6zniLfDYcRCS1AM9ZZoDL8wX357WcHKR5JjuWwIuGLsU0uZCm5k0pyLdmp9WqaxYxmAHyM80axUHL5/OeJY5hpWIDwNWrV/G+970PFy5cwKVLl/DEE08gnU5bqY7vfe97cfDgQXz+858HAHz2s5/FlStXcOzYMSwvL+Pxxx/H1NQUPvjBD4Z2TY2mJqBtEVUT0Fj36NixY9i3bx+efvrpSJMUC4UCTNOsiHNnmiZu375tlfgNDg7i0KFDtsj5KO7UVQJMM5kMxsbGsLCwgEOHDjmGTJNfdtlsFr++a+t8+BLXDNpm2Ad3yDQnGl9mwWLrF1OYx8sRpweueGDeRfD2Lz1FrXFq3j2roNSc84vEQpovaAtyDdRHvSusSQ4L9gNqrEgPnd94fi0LmC4flwQS3CCt3Of9ljWKtueBlwjSvPrXrGNKwllYjhlQv31mbmoEB800TSkHraenJ7RzPvbYY7h16xY+/elPY35+HmfPnsX3vvc9KzhkenradkN6aWkJH/rQhzA/P49du3bh/PnzePHFF3H33XeHdk2Npvp+VzbFFQ9AqlHix7pHR48excGDB60f0qiDOoDKfBgvLi5ibGwMqVQKAwMDOHz4sO2OnKqqUBQFhUKh6s3IYTposkOmgeJ7cCvBWf6hi8W72jEFKC12TE2xLVb4pYEB0xfpSkZBFL4UmJTbs0ZXcOrch4v7qoBj5cYJARGdl97OiIUANrKGVogMxYIbF9rcyieDnje/+R4p11mzovWZ48iWMJLrMeLui30LvgrukEZvT0MWe2zH8wX356WCQ3J8wHL2sJG7M3CFNFtZowekSYESmuWMMmoEB80wDJim6emgDQ0NhXrej3zkI8KSxh/96Ee2/3/pS1/Cl770pVDP3+hqAtoWUSUdNNM0cfPmTSQSCeRyORw9ehR9fX2Ocr4og0rIB7DXXSY/WllZwdjYGJaWlnDkyBHce++9wibdqOawhdGD5nfI9K9tf39Z56snFR68UAIxs/g3DWeUQoUzN9HAJOvKBb0G2X1DLotUC6avrx1vy7BKAMuVA9rykpAWcLEbdMh00OOIwI3sL/PesEoRqY9tHjDIOmWitEg/ThqBKZELZjlsbC+ZANJkg0PUgtzP7FYCMyA4nAGN4aCRG9/V6kFrqjqq73dlU9KKx+PIZDKhHpMu69vY2LDK+kR3o6J00MiogTDOv7a2hkQigVu3bqG/vx/Dw8OefXVRzCMr97zskGnezLatGJlPlH/oYnEBQeCMiDPPzLFQFSQe8uQWLOI4pk+xizTeNcgMz/Z/YrnNKhHlD3AS9wSHDFLSV67YHrdyXTXeAlnNw1pYO9ww0ZqYA1tq3vneloE/so9iOHvNRFAg46Z5AYWiu/SKkef9BocIIE04u8wRHEI9xXPKFft2XnH7DZHOWAUwK57GhK7rde+gERfQrcd9ZWUF3d3dVbyqpspVE9AaULwSxzAdNNM0cefOHSQSCaTTaQwODqK/v9/zQy4ej0cGaED5gJjJZJBIJDA/P4++vj488MADaGtrq8q5g0rTNORyOe8NKRmGgevXryOZTKK1tRVnz5511K5vZTArPHjB6iWzyhjJeoJ1zkLusVIMF/eIE0jiR0JAlFzQkeuir0E28bESCqM8UfP4yKwGwLHAVkxXDO+LGJarRh/PiMuXPcqGggDFIBQvl4yIt51VOinqFdNLDrjgRoiWM6UgjRxHCFMmH6R42/N6zaweV3Zbt7LRegAzoKLljKzIzctGcNDcXoNpmk0HrQ5V3+/KpqQVFhzR/VZHjhzBhQsXpD/cop7FFtRNonuv9u3bh/vvvx/btm2ryrnLlaZpVkiJl+hwF0VRuOMQtjKYAYD+9vPWDDCD6TGrNJwV93ff2GtRLAK4sIJG2GvgXQ97LpErUin3zHnM4LuKAK7S4EbGA3iBmq9o/XwRNACOayd4X7mVMCqmye0XFO7jUb5nuW4e6YzW9l59aWzZok6lLBqmENK8nDT6OMXHS9fLc8145jQFaV5uGJnnFoZrFjmYWQchTbT8g4UFZ8BmaWC9O2heCY5A+CmOTVVeTUBrQFXCQVtaWkIikcDKyopnv5VIUZY4Bjl/LpdDMpnEzMwM9u7dy+29klVUg7JlwJCUqo6OjiKfz+PYsWM4cOCAY8g0UHTXtsqQaVqFBy8UF2CqIHFRUwB6YcbrfVIVxwLHVMSLGq+h1kEkAibeOAD5g5YXNMLtCSqzd6zayY2sKgVuznRF+wNhOWvEtSOgphb4sCUSAT3SgyW7L4Ebg7nZwXvfegEYbxvH827ljgyk2WLyRcEheeLAcY7Hi8bnpLKSbb1utpDnq+KaSRwmFDizHZD6ophmqGBGRMobqzmTtRKSddCagFZfagLaFlFQ94oOwjh8+DDOnDkTeI5ZvZQ45vN5TE5OYnJyEt3d3bhy5Qq2b99e9rlrsQeNHTLN6yEkdfpb0TEDiq6ZWjBgxDdXXYamWIsfU2XgLCQ5F2ib52BDSIKKBplA7lu5KZA+xZb7CRfXkISCKq/LeOAWpttmAzbmLWm5YsJofc54gLxpbc/Clq/kxgL1syIQDRMiUHPs4+GmqboJ6O7HUQz+a6eviQuIjuAQ8XNEWl5c8ihKRHXAmy4XklNXrpmLPvHeuwAAP/7xj9HZ2Wn7U25pYiMkOALegJZKpVAoFJqAVmdqAloDKgwHbXV1FYlEAnfu3JEOwvBSLBbz3Q8VprwArVAoYGpqChMTE9i+fTsuXLgQ2gdarYWErK2tYXR0FIuLizhy5Ig1ZJrWVgczoAhnim5acKYYpg3OuOKtncoZTs07he6cqwR4hIiUeX7+glwOGoMmUZYjR4IeR5WItfcrFtpEwFbuQpjAbbk9bF6wJYIdel8WnkU/T6oumBVGPQ/AE8LcgI8uSeQ6X+Tjk+f+GqXnBc/xAI7XZ0Z+tkyNA00UvCnkWsnXWPC18YKzMMAMqDycfe+p34NhGMhkMkilUkilUrh9+zYmJyeRy+XQ1tbmgLb29nZpR6wREhwBb0BbXl4GgGYPWp2p/t+ZTUkpHo/DMAwYhuGa9EMnFB46dAgPPPBAaLO7YrFY6EmSfs/PAzRd1zEzM4Px8XG0t7fj7Nmz2L17d6hlD7VS4ug1ZBqA1WNmmuaWhjPjbfdC0YtBIGTBwy7wHIvUKsCZ8DzwXpj5ATi/EkEjsPmwlyPiB87Kju9X3CEulHlrARSKyyZ0ycg5NjfQ44oYqlwSDen3mszXigZ8PyWTsm4aux3bC0Yeo4/j6BdzKXl0nU0meG4zbp95nOpLs/VsisDJFPxsM6AmHejjphoBMyJVVS34opXL5SxoI+CWTqehqio6OjrQ1dVl7dfR0cEFmEZy0NxaTlZWVrB9+/aGgNGtpOZ3qwElctCAYvkeD7jS6TQSiQQWFhZw8OBBXwmFsqq1EkfDMHDjxg0kk0nEYjGcOnUKe/bsqUg9etQljhsbGxgfH8f169ddh0xv5QAQIvOt56x0RpNaRDr6YkzqjjbZl33rKIo1G43eRrjOq3BZHr2Aow/jCU4hibdopiW7aA97thpPtQRvLLTJJB7KH5sGrWDHsFw1H2vdTSdOvI0N6jzgyutx9nnRe56GNK6bBVCOFvMc55C8FMbNa/G+WSMFXabpCU31UM4IAP/+9Q963kgGgJaWFnR3d9ui41m37ebNmxgfH0c+n0d7e7vDbQtzLmqUEq3riJaWlrBjx44qXlFTYaj+35lNcaUoihXsAGzOAWN/kOno+AMHDnAX7mGpVlIc6bRCADh+/Dj27dtX0UZhTdOQzWYrdnyRTNPExsYGnnvuOakh01sZzADAvP+sEM7spVAVcMUAKC5QIAVvASVa1PoCtzIvz1ScwMvdLgyYLPMQInirFrhZi35TPjhFZnFti7x3cc+k9q/APl7wxe7LLVksPacZgsh8nept40bxl54T9ZIBmwDn8rqtVEpOyqMfcWcssg+VGQJSDTD7t79+P0zTtN1EVRTF9scL2tzctrW1NRu4ZTIZ65jXrl2zgVu9uWqFQgEdHR3C50nEfr2HoWw1NQFtC4kGpPX1dSSTSczOzgaOjg9y/igdNE3TsLy8jBdeeAGFQoGbVlgpxWIxpNPpip+HiAyZTiaTMAwDly9fbg6Z9lARzlQbnBFg8nqHyEbCl9V3VhD0nVUZ3OjXYIFqFX/vK7opXHBK9ZRV8Fp54FYxaCPhHRVw19TC5vFlj0cv4mVnm9nLHuXPJwNg5N/0NizMOJ73jOKnnuP0ktnO4fJt54aOMMez3RASljRzHqQgsR5cs6f/n/9u/ZuU1vP+tl1TCawIcMi4bbt378bu3btt5yIjg1RVtblt27Ztc7htra2tNQs4Mj1ozf6z+lMT0LaQ4vE40uk05ubmcP36dfT29pYVHR/k/FEAGhmsff36deRyORw/fhyHDh2qCpgRVSskhB0yffLkSbz++uu2D+cmmDllwVlJtJPFAlAl+7hcJVqkVdF1c4YbuJzbh9MVViy+LeWRs5gKszRQVlWFNthL6sjr9b3I5sAW4L+0lAY9tvzRbR6a27n8ABj9mOfxPBxD3teQdb9s52fcNIBxiDnvT3I89ufK9TwC1WR0PqMvf+JtuH79utUvRpwr2sFiYY38YX+fBnHbNE1DZ2cnhoaGABR/N5LetrW1NaTTaSwsLCCTyVjb0n86Ojpqwm1rAlpjqgloDSq2xDGbzSKfz+MXv/gF9u7di5GREXR1dVX1mqJw0OgY+e7ubuRyORw+fLiq1wBUPiRENGQ6m81av9jIdqZpbslZZkKNnLHgTNENG6jJAI5imA52KibPkb4cpfRYKFfrSyJ4q6TrZp3bpRyNhrdqfl1E/UCyZYLhXUeZ0Ca5cKaTA4vnkD8F93ilNbHBwpboemgekRwwTfbjbR8EwIjUgly/m6srJ7pJYkL8PSn1pjl+HjhJjJ7pi27nYa9VpBooZ/xfX/3fsba2hrW1NSwsLCCRSFjOFYG1rq4udHV1obW11YIpWjS40fDGum3EaeO5bWyKo6IoaG1tRWtrq81t03Ud6XTaKpGcn5+3outZt62rqwstLS1Vddu8AK05A60+1QS0Blcul8PExASmp6ehaRqOHDmC48ePR3ItJChDpgG4XNHz28hg7cXFRSSTyYqeV6RKhYR4DZkmfxcKBSiK0nTMWI2cgdGiQdGLv9RpOKNlgQ5nocU6RWwsONne69e16wI95N/1QcAtTJCiv4bsYUNxl3wujtgyQVrVgrdKOW280sPisQU7eCRAAvZSP7+umltsPe/8smDn5rxZLpgAwmi3yTPJEXBcOw1F3LJHt965Eqh5gpGM41XjcEaXM9I3iE3TRDabtZyrtbU1zM/PI51OIx6PW+BD/01+t8m4bbwSSUVRkM/npcYHaZqG7du32+ah0tdMg1smk0E8HucmSVZq3eOV4ri8vNwMCalDNQGtQVUoFJBIJDA1NYVdu3bh0qVLmJqaitSOJx8ghUKh7JlqIqVSKYyNjeHWrVuO+W1R9sBVosRRZsg0+f+vbX9/qOeudymXTttcM+F29KKZ1/8VYvqhKugxA6oXPiECt2rOC1NF/WURfXSJ4K0a4MZCmxFTpN0z72PTxw1+HCFAuVwn7QTZYMhlH/J94IEaW/ZIH9fLdeOVAtqeF/V5CcoNneWIEq6YhxRdPu2SqxpwzWg4c5xfUdDW1oa2tjb09PRYj+u6bsHP2toaZmdnkUqloOu65bbR4EYC0FhoI3/TwLa0tITl5WVs377dms/q5rb5uWbabZudnUU6nbaumS2TLNdtI8EqXg7aiRMnAp+jqWjUBLQG1djYGFZXV23Dlv0Oqw5b5MOvEoBGp1GKxgRENSyanDssOGwOmS5PBM4UY3MANVB0z2hYE7lpm8/zQkAqAzKRpwbmaxfcAAbeqlRaxAO3SkObWjBti22v77/swnszFZI/n8xPCSPg7naxx5IpUeTNCiPnEMGJTJ+WWnB3hr0SGxXDFL7fihAaDpwBjEvn0XfHXme511CO3MDMS5qmYceOHTb3hyQTk1TGlZUVXL9+Hevr62hpabGVR9LOFYGtXC6HRCKBmzdvYmBgAAcOHLBaQtzcNtneNpHbtrGxYUHb6uoqZmdnsb6+bjmEbG+brNtGkqm9AK3poNWfmoDWoDp58qTjgyYej0c6KFpRlNCj9jc2NpBMJnHjxg3PNMooHbQwShybQ6bLlwjOALjDWTXW/AHOUXPgVgpQCex2BYQrO7xxXKcqqeJuG/vl5jlsgY9tOo5pxJRAC3grkVG2V81lH5E8SyUh11cmirmnr5WX2Gg5Y5xeMtvznGPT5y/+h/O8y68LGfisKJjR4Cn4mS0HJhxRuAAAIABJREFUzNykKAra29vR3t6OvXv3Wo8XCgVbieTMzAxSqRQMw7DAR9d13L59G93d3bjvvvscN3Fpt43u3S4X2uhr3rNnj+2aWbeNXHNHRwfXbWNF1jReISHNHrT6UxPQGlSqqnIBLUoHjVxDGJCUy+UwPj6O6elp7NmzRyqNspo9cKzoGWx+yxmaQ6bDkXr+FExFsQ9rJsNyfS5sq+meBVG1kwOLJ6WHCIs3q3apYtQQC1TPbaNfaxjlt67H89mr5vZ9tw+ktu/jOktMVCrJHFOq7JECNbfERqEr5tJL5pnCyPS2BUpgVDyeZ64lkHivnX1MUSoGZ26KxWLYuXOnI7E4k8ng1q1bmJ6eRj6fh6ZpuH37Nv7zP//TEUiybds2LnD57W2TBbdYLCZ0CAlsLi8v4/r169jY2LAcQvqPYRjQNM11XUHmoDVVX2oCWoOK98MaVcw9rXJdrHw+j8nJSUxOTqK7uxuXL1+Wtu7JHSZd16sOaLFYzPpAl+0DzOfzmJiYwNTUVHPIdJlSz5+CGaPKGRVFCGese8brUVN0yRlnzM8h69ptbsd/OEzVAqgALj1m1b6OyN1HzrndoM3nwpoXTCGENo9SPPZ4QUZNkK83ew3uQ6xN4fncSiXLKnvUXc5Zrivmcf6yovErGZsv8f4AgKf/7v8MeILKSNd13LhxAzMzM+jv78fg4CA0TUM+n7dKJNfW1jA5OWnNKWUDSbq6uqy1g6i3zS1FMky3jQ4kuX79OtLptHW+119/neu2maaJ5eVldHd3l/nVbKraagLaFlLY5YXVvIZCoYDp6WlMTEygs7PT1lsnK/Lh6pV4VAmRc+u67gloZMj0xMQEurq6cPHixeaQ6TKknj8FGAbIuGk3p0vNGzA9UhqlB1BztlPz4hWa0VLdmwZEoYBKCLPhogamWrgOx9Bp8jEVVjAIVZJaTv8gPUTZoH4+xL1qlGtNg56by0fvY9ihyQ00rOPzfs45bo/tv4bLOf3OJmMTHyscj+967LBdM0a1BmYAcPPmTVy7dg1tbW24fPmy7eZmPB5Hd3e3DVoMw0Amk7HA7fbt25iYmEAul0N7e7ujt629vV3KbXMbtk3vL+O28RzC2dlZTE1Noa2tzXLbnn/+efzVX/0VhoaGcPLkSbS2tmJpackzTERWX/va1/D4449jfn4eZ86cwVe+8hVcunRJuP2//Mu/4E/+5E8wOTmJoaEhfOELX8A73/nOsq+j0dUEtC2keixxNAwD09PTGB8fR3t7O86cOYPdu3cHSj0iPXBRuIgyASnskGnea22CmT9pp47DNAyYLTEohVKUfnwTkIl7RsCJvWseZkqjl9Qcf4VWS+BWbVgSXQdQG+BW6WvgumwBf2uzAMD2D8oel13sq2U4a7YSSol9FcMs9oOJtqVhgu0NcyvPY0qf2XO6XhNVZsm/JrhH98MDziR7yURhJ1vNNVtfX8ebb76JlZUVDA0NWSEgXlJV1XKfaOVyOauvLZVK4ebNm0in01BV1eG0uQ3bBjYDPejf4zS4BXHbVFVFW1sbBgcHrcdPnjyJ4eFhvPLKK3jttdewuLiI3/zN3wQA3HPPPThz5oz1Z3h42NfN7m9961u4evUqnnzySVy+fBlPPPEEHnroIVy7ds3WE0j04osv4rd+67fw+c9/Hu9617vwzW9+E48++ih+8pOf4NSpU9Ln3YpSTMkfQoR2D6+pasg0TSs6liiVSuHFF1/EO97xjoiuCnjttdfQ3t6OY8eOuW5nGAZmZ2eRSCQQi8UwNDSEvXv3lj388Yc//CHOnj0bScPsf/zHf+Dy5cuOAeGmaWJ+fh5jY2NQFAVDQ0Po7e11gBlQ/Lo0h0zLSTt1HGZcs8GZQcGZmtdtZY+AJKAx70FZ9yxsRQVuPNXUtUQAkVFegzRYyQRLeBzTdbHPPGf97AjWGKJjmariax/rZ1Z+LeM8rltpIntYr+dFx6V3cemFkz024PI1FPTRSasOXTP6Zm5vby+GhoYqNs7HMAyk02kbuK2trbkO2+atXUQuG7suJyDGi/+fmZnB0tIShoeHude6sLCAoaEhrKysYHZ2Fq+88gpeffVVvPLKK3jllVdwzz334Hvf+570a798+TIuXryIr371q9ZrOHToED760Y/iE5/4hGP7xx57DOl0Gt/5znesx65cuYKzZ8/iySeflD5vA8rzl0TTQdtCisfj1h2bavdgEXmVOJqmibm5OSQSCQDAXXfdhf3795cNZvT5o5yFRp/ba8g0vV0zMt+fCJwpBQNQ7asgNV9s9AgDzqJULTluNXUtNeC4VdNtk5ln5gfO2GO6HdcSLxjD5qzJn9vvflYposhB4rx215h6ujSR91YK4Va1YpSO4/aWKCPoY6u5ZktLS3jzzTdhmibOnTtX8RuwxD2THbYdi8UcM9s6OjqEbhsvkIRNgaaHbbu1TaysrKC1tRWdnZ04ceIETpw4gccee8x6nr2R76ZcLoeXX34Zn/zkJ21fiwcffBAvvfQSd5+XXnoJV69etT320EMP4dvf/rb0ebeqmoDWoBKFhADF8Aky0LHaisVi2NjYcDxumiZu3bqF0dFRFAoFHD16FAcPHgwdJMOIuw/j3PSQ6cHBQfT39zs+ZJtgFkCKCu2eIQvOzBb7RxyBs0YWD5YiK5OkroVeQJuisJRKXkvUoSBVgDbevLpw0hyxmZbIrhpkwimYGV4yc9Xo/Vz3Ke1HP+8FdjLAas1bc4noF51P2hmjX5Nsr1olapnqFMxyuZw1emZgYACHDx+O7OZzJYdtA3ZwI/9OpVK4desWdu3aJRy2vbS0hJ07dwpvcvtxGW/fvg1d19Hb22t7vLe3F2+++SZ3n/n5ee728/Pz0ufdqmoCWgOLDF8kUlXVSjCKCtDi8ThSqZT1f9M0cefOHYyNjWF9fR2Dg4M4dOiQdNKhX0XtoKVSKUxNTXkOmW7OMvMppfhLWTtxzAFnSl639Z0B3u4Z/xzBw0GiVtTQ5pghJQhLqRVwq0toE5UFeoXe+JTCfHy6DaXmiXbnbPu6MIJwH8F+UgDmAlm8iH6yDTeiX9ahlIRMbkJkpZpM6rCckVTajI6OYseOHRgZGXGMnqkVhTlsmxxP13Ur4fngwYM4cuQIVFXlJkm+/vrroVUgNVVdNQFtiynqJEcakJaWljA2NobV1VXr7lcYCUOy56+mMpkMNjY2cO3aNfT39+PUqVMOSG6CWQApm6sq7USxr5H0mwFFOAsiehGr5krH4AIaE6NfQ71YXooa2niqFXCrJWiTOq+P/qtAwOaamkgfy+PczLfXtq9oAkWAfXj7uZY1Ch5zbEN/nMj0ogWcTWZzA8vtJxOpTl2zVCqFN954A+vr67j77ruxZ8+eugMQmWHbqVSKO2xb0zTcunUL8XgcFy9exPbt223HJnCWzWbx5S9/GV/4whdCC+Po6emBpmlYWFiwPb6wsIB9+/Zx99m3b5+v7ZvaVBPQGlisgwZEn+RIShxffvllLC4u4vDhwzh37lzVYu+rDWjZbBbJZBLXr19HPB7H0aNHHQEpzWTGAFLsKzPtxDEoBlXSqCgWnHm5Z0W3TdsEMXAWrRJwBoh7sWgZrVWe1ByxRL1BfsQDt1qANqAKSY4VhkVPYPMBB4q+CRO+0iZNPuh5zg1j3C3e447HvHq/XK7R9f8y+3BUsX4yN9Wha6brOsbHxzE9PY1Dhw7h3LlzFb+hW22JovTX19exvLyMqakppFIpxGIxZLNZ/OxnP0NXVxeef/55tLe348KFC7jnnnvwk5/8BB/96Edhmiaefvpp3H///aFAbEtLC86fP49nnnkGjz76KIAiED7zzDP4yEc+wt1nZGQEzzzzDD72sY9Zjz399NMYGRkp+3oaXY317m7KU1EOqyblfel0Gj09PVwXqdJigzoqJXrI9O7duzEyMoJkMmkr3WyCWUAxcBYbPAzQcFYwgDgfgpRcAWasxfo3AEBV3eEsZKlZnbtANFqiB7daCvvwUi1AGxBR/D7vnCG9fRzAFnDGHRs0InS7uAEj9H/kzucJYKbg3zLHrwAkVb1kURGnY9L6nx+4G/l8Hi+88AK3PyoKt+rWrVt488030draikuXLjmSkBtdKysrVjnn2bNn0d7ejnw+b7ltiUQCzz33HCYmJgAU1xanT5/Gb//2bwMAVldXbSWW5ejq1at43/vehwsXLuDSpUt44oknkE6n8f73vx8A8N73vhcHDx7E5z//eQDA7//+7+OXfumX8MUvfhGPPPII/umf/gk//vGP8Td/8zehXE8jqwloW0xROGiZTAaJRALz8/PYs2cP4vE4Tp48WdVrIIrFYr5Si/zKbcg0ce+aYBZQDJgpmgbtcB8Qo1amDJwR94zAmBlTN8EMAAI2lLsNuw4qGhJp1SS4KYARAQx5aSuXSKrU2yc0WDOdwGa43MBwHSDNc7uCuFAyyYcsgMmOB/ARoe8lxXRJlozCFZN0zciIHpJEuLa2hrm5OaTTacTjcW4aYaWCOUhbwOLiIoaGhnDw4MG6K2csR+vr63jjjTewtraGEydO2MbvxONx7Nq1C7t27cITTzyB73znO/jDP/xDHD9+HA8//DBu376N73//+3j88ccxOzuLgYEBnDlzBp/97Gdx+vTpwNf02GOP4datW/j0pz+N+fl5nD17Ft/73vesIJDp6Wnb++G+++7DN7/5TXzqU5/CH//xH2NoaAjf/va3mzPQJNScg9bAKhQKjsTCV199Fdu2bfOcQxaGNjY2kEwmcePGDezbtw/Hjh2DaZp4/vnn8Y53vCOSD9rx8XGsrq7i7NmzoR6XHTJ91113OYZMk2bdoaGhJpj5EQfMANjgzKQXCATQ8jrAhoEw/2cBTTZavyxAC+FtHym0eVw/DW5hlDdWUlE4bqyq1dvmF9pkIYIAm2/ooNYesi4dew6bKycyjph+rjDkdsyKzSZzUxkz4AC5ckaSRkiDG90fxYJbOW0LhmFgZmYGyWQSe/fuxV133VWxmWa1KHqm2759+zA0NCT8es7NzeHq1at47rnn8IUvfAG/+7u/6wDm27dvW3PPfv3Xfx39/f3VeBlNuas5B60pu6rhoOVyOatWfM+ePRgZGbFKEnK5nOUeVSqp0U1hx+zTQ6YB4OTJk8Ih05qm4X+c/Vxo5254CcAMCAnO6lgybpua0yMBOZXjYuk1WCIJ1EaZZKBQkCDn4bxlwnDa1BBKIsksM7f9eXBjc+Ukkg9lYY07EFvxPqabogz6cJNsr5kojXB9fd0Ctjt37mBqagobGxtoa2tzQFt7e7vnjdnl5WW88cYbMAwDZ8+eRXd3d1mvr960srKC119/3XOmm67reOqpp/CZz3wGv/qrv4rXX39dGLzR09ODt7/97Xj7299eyUtvKmQ1Aa2BJZqFlslkKnK+fD6PyclJTE5OYteuXbh8+bKj7pk09RYKhcgALYwetOaQ6QpKcS6QRXCGgg6QxX9cK4KZrCTKcpSsDrONGYNQwyU2LLixkFY2tAV86Zqgt60WwS3qMsnqDrnmw2E5MCEDW25gQe9PjiFzPX6v2eHGCQAs6PFDEe/rRD5/quCaeUlRFGzbtg3btm2zzbrK5XI2t+3mzZtIp9O2Ac8E2kgyYT6fx9jYGObm5jAwMGBFx28VFQoFJBIJ3LhxA0eOHMHAwIDw9b/++uv46Ec/irm5Ofz93/89HnnkkS1V+rlV1AS0LaZKhITQfVednZ04f/688K6XqqpQVTWyWWxhAFpzyHSF5AFmiqZB7dsP6NTw45Zi2YeSL9grnAK4Z0peh8KYy6aiQNmwv1/YyzRafZTyRPA71AvaohQP3GoR2oBo3baquWzMecoKzOH0r5maXFAFLRbYpOYMsueQ2Ecxmf2iXPC6fY1qAMy81NLSgu7ubts6wDAMpNNpC9pI5UmhUEBrayvy+Tza2tpw4sQJ9PT0bCk4u3nzJt58801s27YNV65cQUdHB3e7jY0N/Nmf/Rm+/OUv4/d+7/fwuc99bssFpmwlNQGtgSVy0MIqcSR14uPj42htbcXw8DB6eno87+REmSRZTorj2toaRkdHrSHT9957r6MuvDnLLKBcyhnJvy0404rb2uAs7u+jrBjBz7htARcEatb958kXwFVJtRxIUu9uWzWgLZTIf4mF/v/P3pnHNXHn//+VhEAgIMgtShDlEDw4VBB1a7u1dXe7bXfdo/a7bbXXPna/9apaW92ite1Wra2r1a7YYz36Xau1Vvvb2tuutYfbFRAvEiAcch9yJoGcM78/MNNMMgkBckzg83w88hCGOT6jODPPeb8/77e1YAHD65tmWyFy4F3Z7rt/HwLaToSO67wGEraBtrF3T3NUMdERjvbtgrRFe3izdL5l9MyMWq1GaWkpNBoNoqKiQNM0qqurUVpaCn9/f86CJCMpUmRZBCUlJQVxcXGc50fTNL755husXLkSUqkUZ8+exezZs0fU3wXBFiJoowxXNKqmKAqNjY1QKpXw8/NDeno6oqOjnb5YeKtZ9FCPbVmFMj4+3m6TaVKZcQg4IWYCsR8EY0JYcgb0i5nTh7GKgsH6IZNDzjhTGYfwQMkInHVT6wD+XX65xI2RNi8/C/hKtI1PkTbAjrQNQwKG1Oja3r4cNJN2uB1t3t5qLM4OZbDnzyV4g4lyOUpLdKOQmeFjTzNzG5rx48cjOzub1dPMsmGzSqVCbW0t1Go1ALAKkpjlzdf6odE0jfr6eiiVSkRGRmLu3Ll2M4o6OjqQn5+P48ePY9OmTXjyySc91jeW4F1867eaMGyGE0GzLIhB0zRSUlIwbty4Qb/FcYUkDpXBCJplk+nY2FjMnz8fQUFBrHWImA0RB2Jm+b0wNATw8wP8/QGjERDdrORlWYTFOnpmkc4o0BvZRUQAWznzEkId9+8h38SNU9p40mzbV6JtfJI2V6dHuqpvGuCcsDks5W9nXpnLGa7geRC+ydmNGzegUCggFosxe/ZsjBkzxmYdew2be3t7GWlra2tDVVUV9Ho9AgMDbaRNIpHwMsJkjhrqdDpMnz4dkZGRnOtRFIUTJ05g/fr1yMjIwKVLlzB58mQPj5bgTfj1JEBwKa5KcaRpGm1tbaioqIBer0dSUhLGjx8/5Bxxb0fQzEJlb/xcTaat87yJmA0RJ+aZATejZoGSfjkTCvvlLOCmpAEAxxtEgf7m77ULStO5Kno2FHxB3IQ6OymSPBY3Im39uLPJNcBd5GPo+7JeMMjthyhsHhM9N8I3MdNqtSgvL0d7ezuSkpIwYcKEQQmUQCCAVCqFVCplVSvU6XSsaFtzczN6e3shEolY0ubunm0DYRk1jI+Px+TJk+0WSrt+/TqefPJJFBcXY+fOnfif//mfUTUnj9APf+74BI8gFotBUZRDQbGkvb0d5eXl6Ovrw6RJkxAfHz/s6ovenINmWUXSuq+KyWRieo9YN5k2Q8RsiAxCzODn1/+nWPxj6qE9OaPpH8UMYDetBmyjZ1x44sbngje5XOLGJ2kDuMWNSJvzeE3arP7ZXC1s1sLjqNm1433ZLhvMPDZmHJbl9oV21hlgGV+ljW9iRtM009NsoHS+oRAQEICAgABEREQwy8w928zi1tDQALVaDZPJBKlUahNtc3ePtY6ODpSWlkIsFiMnJ8duYQ+j0Yh9+/bhxRdfxG9+8xuUlpbajbARRj78ursTXIq9CBqAAasodnZ2oqKiAj09PUhMTERCQoLL8ry9meIoFAohEAhYgkZRFBoaGqBUKhEQEICMjAybJtPmXmYUReHe4KVeGbtP4qSYARZyJhKx5cxk+lHOLDEY+iNsg4En6Y2uwlelDeCHuPlCiqQ3pM2VPdO45Ma6d5ozwma3/P1g57FZTw8bYpTOFdE5V0se3+Ssu7sbcrkcRqMRM2bMYEmUO7HXs02r1TKRts7OTtTW1kKr1SIgIMBG2oKCgoadIqnX61FeXo7W1lYkJSUhPj7ebhGQS5cuYfny5VCpVDh58iRuv/12XqZoEjwHv+7kBJcjEAgYuQAGLnPf09ODiooKdHR0ICEhAVlZWS6fkOrNFEeBQMAc35km0wApmT9knJxnZhYz0HT/Mj9Rv5QJhf1/+lv8/onF/WIG2MrZEKJnAoMJdIDVOPVGCMCuvijUGUAF+sbEbF+QNoBE24aDV6XtZgojJR66VNnu27GwDaYHmUNhc2Y/1usMUdgAWwFzpsn1UKSNb2JmMBhQWVnJ9PSaOHGiV/qeWiIQCBAYGIjAwEBER0czyw0GA1QqFRNtu3HjBtRqNYRCIWdBEmfOg6ZpNDU1oby8HKGhocjLy0NgYCDnuhqNBn/961/xxhtvYNWqVcjPz7eZ604YnfDvrk1wO1zz0NRqNZRKJVpbW+1WKnTl8TUajVv27QxCoRA3btzA1atXodPp7M6pI2I2RJwUMwD9VRlFon5Jo+gfJUsstpUz4Ec5G8qwjCbA2l2EAgisy+TfFHTr8vnCPvb3lvPUrJtZc+3Pmzgzr02oM3pd5Ii0DR2PSJvF/DKhgWMumxPS5gzWwgYMfS4bZ1rkYHbFJXXDkLahbONovHySM5qm0dLSgrKyMgQHBzvs6cUXxGKx3Z5tZmlraWmBUqmEwWBAUFCQjbQFBAQwL3Z7e3shl8uhVquRlpZmt8I1TdM4c+YMVq1ahejoaJw/fx4ZGRkeO28C/yGCNsKxjqABbEHr7e1FZWUlmpqaEBcXh5/85Cd23/S4Cm+mOHZ2djJv95KSkuw2mTbP0/v1mIe9Mk6fZBDpjOZy+QKxGAI/KzkzR87MmMvpW1ZrHCB6BoA9N828XzdhU8bfAprHkTdrcbOWNL5KG8APcSPSxoZL2mgXVY20LD4ynMIjgAuKgAxD2oYC13j5JGZA/7OEQqGASqVCSkoKYmNjfTZFz7Jn27hx4wD0PxfodDpWtK2xsRG9vb0Qi8UICQkBRVHo7u5GdHQ05syZY/cld2trKzZs2ICPP/4YL7zwAp544gmvRxgJ/IMI2ihELBajr68PpaWlqK+vR0xMDObNm+exN13eSHFUqVSoqKhAe3s7xGIxkpOTMWHCBNY6pMn0EBlAzPpXEQD0zYfFm3IlEIkg8PMDbTJBEHBzkralRPmLueXMEp3+5j5vvlQwR71EzhQH4Xh4cPKBgrPKox0EfdwvI/gqbgNJG1/ga7SN7/Pahixt1BDCQQAEVlUjXSFs1pUimX0PNcrmilRDD0obn+SMoijU1NSguroacXFxmD59+ojs0yUQCCCRSCCRSBAVFcUsN5lMaGpqQlVVFUwmE4KCgtDW1oa2tjZIpVIcO3YMkZGRyM7OxqxZs/Dpp59i48aNmD9/Pq5cuQKZTObFsyLwGf7ddQluRa/XQ6fTQaFQIDo6mrOEvLvxZBVHyybTEyZMwC233IIrV66wooqkMuMwsE5nND8g3ZQxlqhZiBkAQCT6Uc6MNx+2zQ+xRqN9WdIb+ptWW+7XOk3RGh6WKOYSN1+RNjN8Eze+ShvA72ibpbSZZYWyHNsQ5YzzWG4QNmbfHOMcadK24ZE0FBYW8qJ8fEdHB+RyOUQiEWbNmsUqyjEaMBqNUCqVaGhoQGJiIiZOnAihUMj0bFOr1fDz88PZs2exf/9+tLe3QyQSITs7G1lZWSguLgZFUUhISHBbtHHr1q344IMPoFAoEBgYiLlz52L79u1ITU11uN3x48eRn5+PmpoaJCcnY/v27fjFL37B/JymaWzevBlvvvkmurq6MG/ePOzbtw/JycluOY/RiMA6/c0B3uu0SBgyRqMRJpMJRqORecvl5+eHqKgoTJs2zStj6ujowOXLl3Hrrbe67RjWTaaTkpKYibclJSUIDQ3FxIkTiZgNFa6omdWDkI2c0XR/OiMAmAuEWK7jL+YupW+OnplTFq1TQazTHbmiZ1wPL9YPbm6InrkKvoobF3yTNi74Im1cWEqbSE95VOIGmjPl6ibXjnCluLH2O8z0SJv9uWJ3Tuzj83f+lykfb5lmp1KpQFGUTUGLkJAQl1Vetkan06GiooKpTjhhwoRR16ertbUVCoUCQUFBSEtLs5uBpNfrsXv3brz88stYsmQJ7r77blRWVuLSpUsoKSmBXC6HVCpFRkYGCgoKkJaW5tJx/uxnP8OSJUswe/ZsGI1GbNy4EVevXkVpaandMX///fe45ZZbsHXrVvzyl7/EkSNHsH37dhQXFzPPjdu3b8fWrVtx6NAhJCYmIj8/H1euXEFpaSkkEolLz2GEMuD/eiJoIxydTofq6mpUVVUhODgYycnJaGlpAQCXXwicpaenB//973+xcOFCl+/busl0cnKyTYTwypUrCAgIwKRJk4iYDZbBihnXHLSbsgbgR2Gz3Id1eoz1NWqwguaMnAG8FjQuiLS5Hr6Km6ckbbBFLUaCsAFDlDYHz04ukUCLXXz+jv2URstojVnYVCoVdDodAgMDbaTNsqDFYKFpGvX19VAqlQgPD0dqauqoexjXarVQKBTo6upCSkoKxo0bZ7cIyIULF7BixQqYTCYUFBTgJz/5ic26Op0OpaWluHTpEu6++263tyJoa2tDdHQ0vv76a9xyyy2c69x3333QaDT46KOPmGVz5sxBZmYmCgoKQNM04uLisHbtWqxbtw5Af0uFmJgYHDx4EEuWLHHrOYwQBvxP6Bt3TcKQuX79OpqamjBjxgxERkZCIBCgo6MDvb29XhuTZZl7V4X1LZtMBwcHO2wy7efnhzUZz7vkuKMGJ8TMvB59M81IYI58UfSPX1vJGX2zGIhAyHEp4upzNpTo2QjF11Mk+ShtfE2R9ER65FAqDgqt0hXdKWzWqZGAiwuQWBfiGEbPRJekWt7cxef/53i+mUAggFQqhVQqRUxMDLNcr9ezhK25uRkajYYpaGH5CQoKGjACplKpIJfLodfrMW3aNNY8rNGAWU4rKioQHR2NuXPn2m1w3dPTgy1btuDw4cPF5ZSTAAAgAElEQVRYv349nnnmGbsFQwICApCVlYWsrCx3Dp+hu7sbAFhVK605f/481qxZw1q2aNEinDp1CgBQXV2N5uZm1kv20NBQ5Obm4vz580TQXAT/7pAEl5KYmAiZTMYSIU/OAePCPIHYZDINOwXDusm0pYiaIU2mh4kzcsZVWt9C1GiKgkAs5pYz6wIgrqzwqdXZShvXSwGOc2QhuXkj1uqBQPaNVqDTgw7gvlF7Gl8qSELmtQ0PPs5psxY2wEekjUNOBVyl/s3S5nzm0Y/7G4K0DSRnjvD390dERAQrImOZIqlSqVBXVweVSgUAnD2/zC9TzdMFEhISkJiYOOoqDlrKaUZGht0oF03TOH36NNasWYPJkyejsLDQa5lKXFAUhdWrV2PevHkOp7g0NzezZB8AYmJi0NzczPzcvMzeOoThw687IcHliEQiUBT7Rs7VB82TmKXMYDAMWdCsm0xPmTKFs6wv6WU2DJwQM5qi7ZbSN4sZI2dAf/l8Djmjb1ZrFDgqpW/et4FjLpr+ZjVHa/lyVURNq2e+FPTp2D9z8ZwWd2Av2iboM/BO3nwh2jbSpG0o0TNn4b20DaYJNmd/Nue3t9mfA2kbjpzZQyQSITQ0lFXMw5wiaZa2trY2VFVVQa/Xw9/fH0ajEf7+/khJSUFUVNSommtmMplQVVWF2tpayGQyTJo0ya6cNjU1Yd26dfj666+xbds2PPbYY7z7u3riiSdw9epVfPvtt94eCsEJ+HXXI3gEb/YhA/pTMkQi0ZCieDRN48aNG6ioqCBNpt2Fg2gSbfFAIRCJILC4VwlEIlYpffrmiwGBuen0zeWs/Rl+/B2wiaRZojcAfhzly/U/itOQG0IPFD1zZhc6PedyvkTWuDBLm6W8EWkbOgP1axPqTF6ROF+JtAHuEze70uYCMeVshD1MafvsyBND38Fgj2eRIhkbGwsATBue7u5uJiOltrYWCoWCM0VSKpX6bM8ze7S3t0Mul0MsFiMnJ8dutWuTyYQDBw5g06ZNWLRoEa5du8b0TuMTy5cvx0cffYRz587ZtBiyJjY2lqlVYKalpYX5/TD/2dLSwjrXlpYWZGZmunjkoxd+3eEILofrountCJp5DIMVtK6uLpSXl0OlUmHSpEkOm0yTXmbDgOZ44uAqp2+xnrWcAQBMVL90maweXM3fW0XbWPj5/Vi1EbBtRO1Mig1X9MzVDxEDRM98TdyItLkeS3Ezf81HaaPc2MDaWTwZbeOUtmHMO2Ptm7sVnlPi5kk5s4aiKFy/fh3V1dWIjY3F9OnTWfOsTCYTa16bMymSvoZer0d5eTlToTI+Pt6ufJaWlmLlypVoaGjAO++8g1/+8pe8E1WaprFixQqcPHkSZ8+eRWJi4oDb5OXl4cyZM1i9ejWz7IsvvkBeXh6A/qkzsbGxOHPmDCNkPT09+OGHH/DnP//ZPScyCvG9/z2EYePtOWjA4KJ4lk2mJ06ciKysLJtGmKSXmRsYZMVGJt3RZI6cWV1eBAJOObOESXUcbN8lnt0UB4JL3Ii0DR9fnNfGF2kTcjSwHnXS5mjemSv2P0C0zZty1tnZCblcDoFAgOzsbJsiW0B/imRYWBjrZxRFMSmSarUabW1tqKyshMFgQFBQEGcVST5C0zSamppQXl6OsLAwzJ07126FSq1Wix07dmD37t344x//iBdeeMHj/WSd5YknnsCRI0fw4YcfIiQkhJkjFhoaisDAQADAQw89hPHjx2Pr1q0AgFWrVmHBggV49dVXcdddd+Ho0aMoLCzEG2+8AaD/xf/q1avx4osvIjk5mSmzHxcXh1/96lfeOdERCL/uWgSPIBaLYTKZQFGU13KkzZOPHcHVZNr64k7EzE04WRjEOuWR+do8t8w818zyTSqHnLFSHW0qNQ4hesbFUIqDeBBflzYzfJM2wDeibY6kzVvYSBtt1cAagPBmNM56uTsZidL26VHvyJler0dFRQVaWlqYzJTBPBcIhUIEBwcjODiYWUbTtE0VycbGRvT29sLf35+ziqQ3I08ajQYKhQIajQbp6emIjo7mXI+maXz77bdYuXIlAgMD8e9//xs5OTm8i5pZsm/fPgCw6Tt74MABLFu2DABQW1vL+jefO3cujhw5gmeffRYbN25EcnIyTp06xSossn79emg0Gvzxj39EV1cX5s+fj08//XTUtV1wJ6QP2ihAp2MXNaAoCp9//jluu+02r73NKioqQlRUFGQymc3PHDWZNkPEzE0Mopw+61uzNNGUjUAJHKW5WK/LJV+OBE2nByQcv8POpjcOR9C8WByEr+JmDz5KGxd8kzYuvCZtQ3gC8KS0cR7fk33ahiltnhY0mqbR2NiIiooKhIWFITU1lYmouAuj0WjTr02tVgOAjbQFBwe7vVokRVGoqalBdXU1xo8fj6SkJLtpmZ2dncjPz8d7772H/Px8rFmzxiaTh0AYBKQPGqE/HG0p4kKhEEKhEAaDwWuCxpXiaDAYUFNTg5qaGkRERCAvL88mbYCImZuwIypmOWN6m5mlxN78MztyRt+MljqUNS5uyhl9M7okEIkAo9WcNj3HPC9rGeOSM3tviXmagmOJL0XbABJpcyV8rSDJhZBrrtsoirQBzombp+VMpVJBoVBAq9U6jBi5Gj8/P4cpkiqVCi0tLVAqlTAYDJBKpTbiZq/32GDp6upCaWkpBAIBZs6cyZnSaR7fBx98gPXr12P69OkoKSlBUlKSS8ZAIDiCX3cegsfwdqEQyxRH6ybTs2bNwtixY1nrk15mbsTZqo0O5p8BYMuZyQSIRIyYARxyxhE9s1yfNWfNHpzRvWE+gFlFnFn7Mz8c6O1E7ryIr0sbH4UN8I15bW6XNhfmz4wmaQMGTpH0pJwNpmy8p7BMkTRXBKRpGjqdjpG27u5u1NfXo6+vj0mRHDNmDBNpG0yKpMFggFKpRGNjIyZNmoSEhAS7KZ21tbV48sknUVhYiFdffRUPPPAA70rnE0Yu/LnDENyGdQQN8L6gicVi6PV61NXVOWwyDZCS+W7H2aqNlt+LRLbyZilTA6U5mn9uIWQDpVtzpj96GstonVZn+3MibUPGV6JsZvgebSORtkEc30vS9snx5W47hjWtra0oKyuDRCJxWDaeDwgEAkgkEkgkEkRFRTHLjUYjKz3yxo0bUKvVjOQ5SpGkaRqtra1QKBQIDg5GXl6ezdQJy+MUFBTghRdewK9//WuUlpayxkEgeAL+3E0IHsWblRxpmkZfXx9aW1vR0dFBmkzzhUHMP3MUWeOCtvpdE1jLmLV8OfM21Nno2WDSG53Z1hHW0sYzYQN8q/Q/l7QB/BW3ESltXpp9PtqkzV309fWhrKwMXV1dSE5ORlxcHK+LWjjCz88PY8eOZWXYUBQFjUbDSpGsqKiAyWRiqkgGBgaio6MDGo0GqampGDduHOffAU3TuHz5MpYvX47u7m588MEHWLhwoc/+fRF8G1IkZBRgNBphskoVKyoqQmRkJBISEjw2Dssm0729vZBIJJg7dy5nk2mKokBRFH495mGPjW/UM0DUzJl1aIq23W6gQiBckTHBAOmUAD8FzVl4KG5c8FHa7GEtbXxsA2CGT9LGBUvaeH7n99VCJO6OnlEUxUwdiImJQXJyssvmb/Edmqah1WqhUqlQX1+P9vZ2iEQimEwmBAQEMOXmW1paMHv2bEyZMgVarRYvvfQS9u/fj5UrVyI/Px9SqdTbp0IYuZAiIQRuPJ3iaN1k2t/fH3V1dSw5I02mvYxlqqNVlKx/kcC5dSxxpkqjNVxvNq0LgXAJFsd2Ai7B4MMcAh9IjwR8P0WSax0+SJsvRtoAgPLnX4qkdaTN08LGFWkDvBtt6+rqglwuB03TyMzMRHh4uNfG4g0EAgGMRiOqq6thMBiQnZ2NiIgIGAwGporkt99+i7feegs1NTUQi8WQSqUQCoV46qmncM8993hsbt65c+ewY8cOFBUVoampCSdPnnTYS2zZsmU4dOiQzfL09HRcu3YNAPDcc89hy5YtrJ+npqZCoVC4dvAEt8KfOwLBo3hK0CybTCckJDBNptva2pgUS1KZkUcMscw+53oObnBM3zOREKDYD1gCa4EaRhSLqf44FKnwdFoLkTaXQ6TNtQj1HCmSPJM2b6dGMuNwkCLpruiZwWBARUUFmpqaBiyAMVIxmUyorKxEXV0dEhISkJiYyMiWWCxmUiRXrFiBJUuW4Omnn0ZhYSHy8vIQHh6Oc+fO4bXXXoNKpUJaWhqysrKwaNEi/OEPf3DLeDUaDTIyMvDII49g8eLFA66/e/dubNu2jfneaDQiIyMDv/vd71jrTZ06FV9++SXzvb32AQT+Qv7FRgFc+dNisRi9vb1uO+ZATabNZfYpioLJZCKpjHzATjXHASNpN7d1WDSEWcfiIZSjV5mNnHHhZPTMErOoDdS7TMC3EvtE2lyOM9LGF3xd2oR6Ey8Ejk/S9vyzc1FeXs5UInRFk2aaptHU1ITy8nKEhoZi7ty5bu9pxkdu3LgBhUIBf39/5ObmsppnW0JRFI4cOYINGzZg7ty5OHPmDGu6B03TqK2tRUlJCUpKStDR0eG2Mf/85z/Hz3/+c6fXDw0NRWhoKPP9qVOn0NnZiYcfZj9D+fn5ITY21mXjJHgefl3pCR7DXUVCdDodqqqqUFdXh9jYWMyfP5+zybRIJIJer8c90odcPgbCIBlEs+ahzEtz9hiccubhKBZ9s8S+wHq8Af79TbH5IB1E2lyOL1WQ9DVpM3/tC9IGuF/coqOjoVKpUFtb65ImzWq1GgqFAr29vUhLS0N0dPSoK2qh1+tRVlaGGzduICkpCRMmTLD7d6BUKrFq1SooFAoUFBTgt7/9rc26AoEACQkJSEhIwL333uuJUxgyb7/9NhYuXGhTT6CiogJxcXGQSCTIy8vD1q1bIZPJvDRKwlDg11Wd4BbsRdBcmeI42CbT/xPzvy47NmGYcETDuHCpnHFEz2y3c7K4h7MPI05Um7SLWTa4KiDyQTq4pA3gnbj5urQB/BQ3n+jV5kDa+IQ7xe30yRXsfVo0ae7p6bGpQGju9WX+iMU//u6ZTCZUV1fj+vXrmDBhAjIzM0ddGhtN02hsbER5eTnCw8ORl5cHiUTCua5er8eePXuwbds2PPDAA/jggw9s+q36Go2Njfjkk09w5MgR1vLc3FwcPHgQqampaGpqwpYtW/CTn/wEV69e5XV7BQKb0fW/mcBgTjEcLqTJ9AhjsE2rreSOts52EggBmKwWCQAjR4qkyWqZgyqNArH7HpJtomcD4Yy0eSv65gPRNl+SNoBE21yJL8xpM+OONEl7TZrNFQhVKhU6OztRW1sLrVYLiUSCkJAQiEQidHR0wN/fH7NmzWKlvI0WNBoN5HI5ent7MXXqVERHR3OuR9M0CgsLsWLFChiNRnz88ce45ZZbRkSU8dChQwgLC7MpKmKZMjljxgzk5uYiISEB7733Hh599FFPD5MwRPhzpSa4DXdE0CiKQkNDA5RKJfz9/UmT6VGEM33Pbq7o3LZcQjRACX3awe8uZ6qkv4cfoO30GuMFPiptAH/FjUib6xip0mYdPbOHQCBAYGAgAgMDWdKh1+vR3t6OmpoaaDQaiMViqNVqXLx40SZFUiqVjggB4YKiKFRXV6Ompgbjx493GDns6enB888/j4MHD2L9+vXYsGEDay68L0PTNP7xj3/gwQcfHLB9QlhYGFJSUqBUKj00OoIr4M9VmeBRhjoHjaZptLS0oLy8HABIk+mRhnW6oxVOlckH3CpnQ0I/wMuImwI36OjZYOBreiTgE9IG+Fa0jUib6xip0uYsFEWhubkZSqUSUVFRyM7ORkBAAEwmE1M2vqenB3V1dVCpVACGN6+Nr3R2dkIul0MgEDiMHNI0jdOnT2Pt2rVITExEYWEh0tPTPTxa9/L1119DqVQ6FRFTq9WorKzEgw8+6IGREVwFf67ABLdhL4JmMplAUZRTZXhpmkZ7ezvKy8uh0+mQlJSE8ePH220yTXqZjUA4+p5xr3azyqM7ZcfusYd4zJsCZ312bq/qSKRt2BBpcw9E2lyHs9EzLrq7uyGXy2EymZCRkYGIiAjmZyKRyKaqn+W8NpVKhZaWFiiVShgMBkilUpa0jRkzhjWvja9Ytg+YPHkyZDKZ3eeWpqYmrFu3Dl9//TW2bduGxx57jNetBtRqNSuyVV1djZKSEoSHh0Mmk2HDhg1oaGjA4cOHWdu9/fbbyM3NxbRp02z2uW7dOtx9991ISEhAY2MjNm/eDJFIhPvvv9/t50NwHfy52hI8ivmibDAYBgz5WzeZlslkNm/iSC+zEcxQqzwOYX4a0L9IILa4NDkZPRuynDnAXNXR5ljuFDd76ZF8kA4ibS6HSJvr4JI2gH8VJJ3BYDBAqVSisbERiYmJmDhxolOi4cy8tq6uLtTV1bHmtVl+JBIJL1IkzRk7ZWVlCAkJQV5enk1VaDMmkwkHDx7Epk2bcMcdd+DatWvM+fOZwsJC3Hbbbcz3a9asAQAsXboUBw8eRFNTE2pra1nbdHd348SJE9i9ezfnPuvr63H//fejvb0dUVFRmD9/Pv7zn/8gKirKfSdCcDkCcwEHJ3B6RQL/0Ov1sP63/vzzzzF37ly7vUKsm0wnJibavG0jYjaKcaaCo5Pb2l9tgH1azD1wh6BxYufBRTDAPAC3wFPp4KO0ccFXabMHX8XNGj5Jmz08JW3/Or1qUOvTNI3m5mamV9qUKVPsSslwMRgMjLSZ0yR7e3vh5+dnI21BQUEejUT19fVBoVCgu7sbqampnFMpzMjlcqxcuRJ1dXXYu3cv7r77bl4IJoHggAF/Qfl/FSW4DXuFQgZqMg0QMRu1OFnlsX9VO9cfV8kZAJjnUXJUgWRF4TwArbeN2rhd2viaIkkibW7BV6JtfI+0Afws+6/RaKBQKKBWq5GamoqYmBi3ioZYLEZ4eDjCw8OZZZbz2lQqFWteW3BwMCs90h3z2iiKQl1dHSorKxETE4O5c+faLYKh1WrxyiuvYNeuXXjsscfwySefYMyYMS4dD4HgLfh1xSS4DYFAYBNBsxY0Z5tMEzEbpQxyTpn9+Wr9D0NOFxwZCDvjog2Oi+AMSeAG+bDEJW2Am8XNl6QN6Bc3rY43AkekzT34Wq82M56QNpPJxPQRHT9+PGbMmOG1uWFc89pomoZGo2GkrbW1FZWVlZzz2kJCQgasKmiPnp4elJaWwmQyITMzkyWOltA0je+++w4rV65EQEAAvvrqK+Tm5pKoGWFEQVIcRwkGgwEUxY4w/PDDD4iPj0d0dDRTtjY8PBwpKSmcTaYB0suMwMEwioE4ipINp2LkcHAobm58APB4iiSPpYNv0mYPPoubNXyUNnvwSdq4cFbanElvbG9vh1wuh5+fH9LS0nympxlN09DpdExqpFqtRk9Pz5DmtZlMJlRWVqKuro6ZTmEvMtfZ2Yn8/Hy89957ePbZZ7F27VqfKHRCIFhBUhwJ/XBdGEUiEZqbmyGXy+02mQZIyXzCADgqze9AngZKYaRN3BP+me1FIrdUiuSKvAnEfm6VM8ALKZJ8jbQBP0bbLKNuPJQ2X4q2+UqkDeB/iuRAxUicQafToby8HDdu3MDkyZMRHx/vUxEggUAAiUQCiUTCKj5hPa+ttbUVGo0GIpHIpoJkUFAQ2tvboVAoIJFIkJuba3dOPEVROHnyJJ566ilMnz4dJSUlSEpK8tTpEggeh0TQRglGoxGmmw+8FEWhsbERpaWl8PPzw/Tp00mTaYJ7sCNQgyooMth9e7DXj8DTDbBBIm0seChtXPBV2rjgq7RxwSdps+bDL9ZwLqdpGvX19VAqlYiIiEBKSgokEomHR+dZrOe1mT/mrJ6wsDDExsYy/dqsG0/X1tZizZo1uHDhAl599VU88MADvC6dTyA4AYmgEfoxz0FraWlBRUUFaJpGeHg4goKCbEqvmsWMpmn8eszDXhoxwecZREER9mZOyJujfduJvLlD3GiOBtjuljYSabOARNpczkCRNkGfgTcS50ykTagz8kbkenp6IJfLYTAYmBejowHLeW00TaOhoQHl5eWIiIhAVFQUtFotM6/tyJEj+OabbzBlyhRMmzYNvb29eOedd/DrX/8apaWlpFQ8YdRAImijhBs3buDKlSvQ6XSYPHkyJkyYgKqqKvT29mLGjBkA2E2mKYrC4tBHvDxqwojARWmIjLi5es6ZByJuJNLmZXgobVzwVdrsYRY1PkkbF54WNOvomdFohFKpRENDw4BzrEYyarUacrkcWq0WU6ZM4Xw5XF9fj++++w7ffPMNLly4gOrqavT29mLChAnIyspCZmYmsrKykJWVhYSEBLemhZ47dw47duxAUVERmpqacPLkSfzqV7+yu/7Zs2dZPc3MNDU1ITY2lvn+9ddfx44dO9Dc3IyMjAzs2bMHOTk5bjkHAm8hETRCPwKBALGxsUhISGBuDH5+fjAajazKjBRFQSAQQCgU4kP1IZv9kAIhhEFjb47akKtCsiNkwxUsroibq6Vt1EbaAH6IG4m0uQXLaJv5az6KmrcqSNI0jdbWVigUCkilUsyZMwdSqdStx+QjFEUxhcjMomWdxgj0P6dERETg6tWrOHbsGFasWIFNmzbBYDDg0qVLuHjxIi5evIhTp06htLQUd911Fz788EO3jVuj0SAjIwOPPPIIFi9e7PR2ZWVlrHL/0dHRzNfHjh3DmjVrUFBQgNzcXOzatQuLFi1CWVkZaz0CgUTQRgkURdn0PGtoaEBdXR1mzZrFiJn5Y425eWZlZSWEQiGSkpIQFRUFgUBApI3gWlwQIXNHVIxE2lwIX6WDh9LGBZ+ljQs+Sps9XCFtH36xBr29vVAoFFCpVEhJSXHYaHkk09HRAblcDpFIhPT0dLt9ymiaxldffYVVq1YhMjISBQUFyM7OtrtfrVaLjo4OxMXFuWvoLAQCgdMRtM7OToSFhXGuk5ubi9mzZ2Pv3r0A+p/N4uPjsWLFCjzzzDNuGTuBl5AIGsEWc8QsICAAXV1d+OabbzBmzBjWx9zHhKZptLe3Q6lUQq/XY/LkyRg3bhxrgi6JtBFcClfEbbDRNjfMQ/NGpM0TwkZ6tVnAFWkDeCdsXJE2gL/iNpoqSJ78bDWqqqpQXV2NuLg4TJ8+fVSWgTcYDKioqEBzczMmTZoEmUxmt7BHW1sbNm7ciH/96194/vnnsXz5cs4ImyUSicRjcjZYMjMzodPpMG3aNDz33HOYN28eAECv16OoqAgbNmxg1hUKhVi4cCHOnz/vreESeAoRtFGCuUiI5Tyz0NBQ3HrrrUwfk56eHjQ2NqKvrw8SiQSBgYHQarXQ6/WYOHEiKz1yIIi0EVyKq9IkXSxZ7i5I4o3UyB+PzYMUSb4IB1eTbZ5JG+BbKZIjVdr+85//QCAQYObMmXajKCMZczGysrIyhISEIC8vD4GBgZzrUhSFd999Fxs2bMCcOXNw+fJlTJw40bMDdiHjxo1DQUEBZs2aBZ1Oh7feegu33norfvjhB2RnZ+PGjRswmUyIiYlhbRcTEwOFQuGlURP4ChG0UcLFixfR0tKCGTNmICQkBCKRiJlrFh4ejvDwcGbdzs5OVFRUoKurC0FBQRCLxaisrERjYyMryhYSEjKoN4NE2ggux03RNj7PayPSxhPhINLmcnxd2v43Pwv+/v6Ii4uDWCwGTdOjKq2xr68PcrkcKpUKqampiImJsXv+lZWVWLVqFeRyOf7+97/jt7/9rc+Xzk9NTUVqairz/dy5c1FZWYm//e1veOedd7w4MoIvQgRtlPDdd9/h5ZdfRkNDA5KSkpgqSNnZ2cjMzIRUKoVSqUR+fj4A4LnnnkNGRgYCAvofOPR6PRNp6+7uRl1dHbRaLYKCgmykbaDUBEuItBFcDpG2H/fvpRRJIm0WEGkbFr4kbUlJSejr60NdXR3kcjkEAgGCg4OZe6O5z5evi4g1FEWhtrYWVVVViI2NdZjWqdfrsWfPHmzbtg0PPPAATpw4gbFjx3p4xJ4jJycH3377LQAgMjISIpEILS0trHVaWlpYVR4JBIAUCRlV0DSNpqYmFBYWorCwEEVFRSgqKkJraytiYmLQ0dGBmTNn4k9/+hN+8YtfIDAw0OHbP71ez6RGmj86nQ5SqdRG2oZbUphIG8HljNJiJN4oRNJ/XFL2n4GH0saFWdoEOj1vBc4Sb5f9P3luPfM1RVHo7e1FT08PqzmzyWRCcHAwI2yuukd6i+7ubsjlcphMJqSnp9uVLZqmUVhYiBUrVkCv12P//v245ZZbfCbC6EyREC7uuOMOhISE4IMPPgDQXyQkJycHe/bsAdD/eyKTybB8+XJSJGR0MeAvPhG0UYxarcbOnTuxY8cOJCcnIycnBzU1NSgqKkJnZyfS09NZkbZp06YhICDA4QVVp9PZSJter2feIpo/wcHBRNoI/INIm0ch0mYBkTa34ClRs5Qze9A0jb6+PkbWzPKm1+uZbBSzuIWEhDDFuviI0WhEZWUl6uvrMXHiRCQmJtqNDKpUKjz//PM4cOAAnnrqKWzYsAESicTDIx48arUaSqUSAJCVlYWdO3fitttuQ3h4OGQyGTZs2ICGhgYcPnwYALBr1y4kJiZi6tSp0Gq1eOutt7Bnzx58/vnnuP322wH0l9lfunQp9u/fj5ycHOzatQvvvfceFAqFzdw0woiGVHEkcPP3v/8dW7ZsweTJk/HRRx9hwYIFzM/M6QoXLlxAYWEhPvroIzz//PNQq9WMtGVnZyM7OxtTp06FWCxmpC0gIABRUVFMA0qaplnS1tbWhsrKShiNRs5I22BSP0h6JMHljNIKkt5KkSTpkRb4YHqk+Ws+ixqfUiQFAgGCgoIQFBTEehg33yNVKhW6u7tRX1/PFOuyjrQN9JLUE7S1tUGhUEAikTjs7UbTND7++GOsXbsWCQkJKCwsRBssngIAACAASURBVHp6uodHO3QKCwtZjafXrOlvQL506VIcPHgQTU1NqK2tZX6u1+uxdu1aNDQ0ICgoCDNmzMCXX37J2sd9992HtrY2bNq0Cc3NzcjMzMSnn35K5IxgA4mgjVLy8/Mxa9Ys3HPPPU5d7CmKQlVVFSNtRUVFKCkpgVarxbRp01jSNmXKFPj5+dndL03T0Gq1NpE2c+qHdaRtOPn6RNgIbsEFkTbA9ZEx0qvNhfBVOngobVzwWdq4GI60ORM9GywGg8Em0qbRaCAWi20ibUFBQR6RNp1Oh7KyMrS3tyM5ORnjx4+3e9zm5masW7cO//73v7F161Y8/vjjPpvGSSC4AZLiSHAfJpMJFRUVjLQVFxejpKQEJpMJM2bMYKVHpqSkOCweYk79MN+IzNJGUZSNtEml0iFLW2dnJ5bFrx7qKRMIjuFhiiSRNhfCZ+kg4uZynJU2dwgaFyaTiTWfzfwRCoU2kbbh3CetoWka9fX1UCqViIiIQGpqKlNAjGuMhw4dQn5+PhYuXIjdu3fztl8ZgeBFiKARPIvRaIRCoWAKkZilTSQSISMjA5mZmYy0JSUlOXyjRtM0M8naUtxommZuRJbS5ugNojmXvKOjAxMnToRMJmMJI4m0EdwGkTaPQaTNCiJtLodL2jwlaFxQFAWNRsOKtKlUKtbLTcto22CjWGq1GqWlpdDpdEhLS0NkZKTddeVyOVatWoXa2lrs2bPH6QwdAmEUQgSN4F1omobBYEBpaSmKiopw4cIFFBcX4/LlywgICEBmZiYyMzOZ9EhHE43N+7OUNvMHAEvYxowZg6CgIOh0OlRVVaGpqQnjx4/HpEmTnJ54TaSN4DaItHkMIm1WEGlzKR9c+Iu3h2CDdUaKWd4MBgOkUqlNtI2rJL7JZEJ1dTWuX7+O+Ph4TJ482a7cabVavPrqq/jb3/6Gxx57DC+++CLGjBnj7tMkEHwZImgE/kHTNPR6Pa5cucIq93/16lVIpVJWamR2djbi4+MHlDaNRsMSNpVKBZqmQdM0goKCMGHCBERGRg47V59IG8FtEGnzGETaOPABceOjtPFR0LgwF+yyjrRptVpIJBJWpM1kMkGpVMLPzw/p6el2ZYumaXz33XdYuXIlAgICsH//fuTm5pKoGYEwMETQCL6BuXDIpUuXGGkrLi7GtWvXMHbsWGRlZbEibXFxcZzSptVqce3aNfT09CAwMBCRkZEwGAzMDUkkEtlE2iQSCZE2Aj8h0uZRSNl/K3xI2rxR9t9X5MwRer2ekbXu7m50dHTAaDRCJBIhLCyMibR1dHQgJSWFiaJ1dnZi06ZNOHbsGP7yl79g7dq1vG4LQCDwDCJoBN/FnM5YUlLCirQpFApERUWxIm0ZGRn4+OOPsW3bNsyaNQt79+5FZGQkS7woioJarWZF2tRqNfz8/GzmtBFpI/AWIm0ehUibFT4kbe5mJAga0H+vbW5uRllZGUJDQ5GcnAyj0chE25qbm7F48WL4+/sz1Ru/++47pKam4uDBg0hLS/PoeM+dO4cdO3agqKgITU1NAzaQ/uCDD7Bv3z6UlJRAp9Nh6tSpeO6557Bo0SJmneeeew5btmxhbZeamgqFQuG28yCMaoigEUYWNE1DrVajuLiYkbZvvvkGTU1NCAkJQU5ODmbPno1Zs2YhKyvLRtKsMZlMNtKm0Wjg5+dnE2kbbv8ZIm0Et0GkzaMQabNilErbSBC03t5eKBQKqFQqTJkyBdHR0Zz3Oa1Wiy+++AJvv/02amtrQVEUmpqaYDAYMH36dGRnZzMvTTMyMtzaiPqTTz7Bd999h5kzZ2Lx4sUDCtrq1asRFxeH2267DWFhYThw4ABeeeUV/PDDD8jKygLQL2jvv/8+vvzyS2Y7Pz8/h0VRCIRhQASNMHK5fPkynn76aZw/fx6rVq1Cbm4urly5wqRHVlZWIiEhgZUamZmZibFjxw4obZZ5+uZIm7+/P6e0DQcibQS3QaTNoxBps8AHhM3MUMXN1+WMoihcv34dVVVVGDduHJKTkzmLhQD91ZnfeOMNPP/887j33nvx6quvIjo6GhRFQalU4uLFiyguLsbFixdx8eJF/L//9/+Ql5fnkfMQCAQDChoXU6dOxX333YdNmzYB6Be0U6dOoaSkxB3DJBCsGVDQ7DemIhB4zKpVq/DGG2/gz3/+M/7v//4PERERAIBf/OIXAPojbZ2dnUzlyKKiIhw4cAA1NTVITExkFSHJzMzEmDFjGGkz596HhYUxx7OUtp6eHrS0tECj0SAgIMBG2gaTh/+h+pDNMiJtBJdAU7bLBilttMlku4thSJar98d5DL3B9hgekDZar+c4rhslSmd7PN5Im1Znu4yn0ibg+HvkYzESV9Ld3Y3S0lLQNI3s7GyMHTuWcz2apnH16lUsX74cHR0dOH78OO68807mXikUCpGSkoKUlBTcd999zDZ8h6IoqFQqhIeHs5ZXVFQgLi4OEokEeXl52Lp1K2QymZdGSRjtkAgawSf56KOPMG3aNEycONHpbWiaRltbG5Maae7T1tDQgKSkJJs5bcHBwQ4jbZY5+uZPb28vUxHL8mPvzaSzEGkjuA0SafMoXqkgCfBH3qzhqbhZYy1tvhhBMxqNUCqVaGhoQGJiIiZOnGi3QnJvby+2bt2Kffv2Yfny5di8eTOkUqmHRzwwQ4mgvfzyy9i2bRsUCgWio6MB9KdNqtVqpKamoqmpCVu2bEFDQwOuXr2KkJAQdw2fMHohKY4EgiNomkZTUxPTWNtciKStrQ2pqamMtJnz6gMDAx1Km8FgsJG2vr4+BAYGsoTNXu+Zgeju7kZFRQXUajX+9ssDwzl1AsE+RNo8CpE2K3gubScubxl4JZ7R2toKhUKBoKAgpKWl2ZUtmqbx73//GytXrkRERAT279+PrKws3pbOH6ygHTlyBI8//jg+/PBDLFy40O56XV1dSEhIwM6dO/Hoo4+6argEghkiaATCYKFpGvX19bhw4QITZSsqKkJnZyfS0tJYkbbp06cPWDzEXObf8qPVam2kbcyYMfDz48467uvrg1KpRGtrK2QyGSZOnMgpeCTSRnAbRNo8CpE2K3gkbb4kaFqtFmVlZUyZ/Li4OLv3qxs3bmDDhg3417/+hS1btmDFihV270l8YTCCdvToUTzyyCM4fvw47rrrrgHXnz17NhYuXIitW7e6YqgEgiVE0AgEV0BRFGpraxlpMxciUavVSE9PZ81pmzp1KsRisUNp0+v1NtKm0+kQFBRkU+6/vr4etbW1iImJQVJS0qCrYxFpI7gNIm0ehUgbBx4WN1+RM/OLRqVSicjISKSmptqdH01RFI4ePYpnnnkGubm5eP311wc1fcCbOCto7777Lh555BEcPXoU995774D7VavVkMlkeO6557By5UpXDZdAMEMEjUBwFxRFoaqqiiVtJSUl0Gq1mDZtGkvapkyZAj8/P4fSptPpWMLW2dkJk8kEoVCI8PBwREREMOmRomE+hBJpI7iNUSptgHfEzSvSxmdhA9wqbb4gaCqVCnK5HHq9HlOmTHFYKr6yshKrV6/GtWvXsHv3bvzud7+zOy+NL6jVaiiVSgBAVlYWdu7cidtuuw3h4eGQyWTYsGEDGhoacPjwYQD9aY1Lly7F7t27sXjxYmY/gYGBCA0NBQCsW7cOd999NxISEtDY2IjNmzejpKQEpaWliIqK8vxJEkY6RNAIBE9iMplQUVHBSo8sKSmByWTC9OnTmfTImTNnIiUlxSZ9hKIonDp1CtHR0RAKhZg4cSL8/PyYkv/d3d0wGo2QSqWsSFtwcDCRNgJ/IdLmUYi0WeFCYeOzoJlMJlRXV+P69euQyWSYNGmS3fuCwWDAnj17sG3bNtx///3Yvn27TVVDvnL27FncdtttNsuXLl2KgwcPYtmyZaipqcHZs2cBALfeeiu+/vpru+sDwJIlS3Du3Dm0t7cjKioK8+fPx1//+ldMnjzZnadCGL0QQSMQvI3RaIRCoWAKkZilTSgUIiMjg5E2ANi9ezfq6urw/vvvIzc31+ZNJk3TNpG2np4eGI1GBAcH20jbcN+EEmkjuA0ibR6FSJsVQ5C2P706n5k7HBISwvw5mNYq7qK9vR1yuRxisRjp6el2Kw/SNI2ioiIsX74cer0eBQUFWLBgAW+LgBAIIxQiaCON119/HTt27EBzczMyMjKwZ88e5OTk2F3/+PHjyM/PR01NDZKTk7F9+3amVxjQf7HevHkz3nzzTXR1dWHevHnYt28fkpOTPXE6oxKapmEwGFBaWoqioiKcOXMGn332Gbq7uzFt2jSEhYUhIyODSY9MTEx0KFo0TUOr1dpIm8lkYh4izB+pVEqkjcBfiLR5HNJg24IBpO3dwr8w2QzmP/v6+iCRSFjCNmbMGAQEeGZunF6vR3l5OVpbW5GUlIT4+Hi7sqVSqfDCCy/gH//4B9atW4eNGzcOek4zgUBwCUTQRhLHjh3DQw89hIKCAuTm5mLXrl04fvw4ysrKmF4elnz//fe45ZZbsHXrVvzyl7/EkSNHsH37dhQXF2PatGkAgO3bt2Pr1q04dOgQEhMTkZ+fjytXrqC0tJRcuN1MZ2cnXnrpJezduxdLlixBfn4+Ojo6WOX+r169CqlUyqocmZWVBZlMNqC09fX12UgbTdM20hYUFESkjcBfiLR5HCJtVkgC7KY2WrZWUalUUKlU0Gg08Pf3Z4TNfM2VSCQui1SZW8SUl5cjLCwMU6ZMsXvPpmkan3zyCdasWQOZTIb9+/dj6tSpLhkHgUAYEkTQRhK5ubmYPXs29u7dC6B/vlJ8fDxWrFiBZ555xmb9++67DxqNBh999BGzbM6cOcjMzERBQQFomkZcXBzWrl2LdevWAejvsxUTE4ODBw9iyZIlnjmxUYhCocC8efOQnZ2NV155BRkZGTbrmCNjly9fZknbtWvXEBYWxpK27OxsxMXFDShtvb29LGFTqVSc0iaVSof9IEGkjeA2iLR5HK9Im07PG3k7Ub7N6XWNRiPUajUr2qbRaCASiWzSI4OCggZ9re3t7YVcLodarcaUKVMQHR1tdx/Nzc146qmn8NVXX2Hr1q14/PHHhz1fmUAgDBsiaCMFvV6PoKAgvP/++6xyskuXLkVXVxc+/PBDm21kMhnWrFmD1atXM8s2b96MU6dO4dKlS6iqqsLkyZNx8eJFZGZmMussWLAAmZmZ2L17t3tPahRDURTOnTs36Nx/s2SVlJSwpE2hUCAqKspG2mJiYhzun6ZpaDQaG2kTCASckTYibQTeQqTN44ymsv+DETQuTCYT1Go1K9qmVqtZ11pztM1eKjpFUbh+/TqqqqoQFxeHpKQkzn6Y5nUPHTqEZ599Frfffjtee+01xMXFDescCASCyxjwYYrfHQgJDDdu3IDJZEJMTAxreUxMDBQKBec2zc3NnOs3NzczPzcvs7cOwT0IhULceuutg95OIBBAKpVi3rx5mDdvHoB+yVKr1SguLmak7cSJE6ioqEBcXBwjbWZxi4yMZERLIBAgODgYwcHBzM2boiiWtNXV1UGlUkEoFNpIW2Bg4KCk7ZTqINra2lBeXg6RSIRtdxQM+u+AQOCEpmyXDVLaaJPJdhfDkCyu/Q13n5zH0Rtsj+EBaaP1eo7jekCedLbHdae0DVfOAEAkEiE0NJQp6w78eK01S1tDQwOT1WAu+mS+5hqNRpSVlQEAZs6cibCwMLvHUigUWLVqFWpqanDgwAHce++9pAgIgeBjEEEjEHwc8xvYBQsWYMGCBQD6pa27uxvFxcW4cOECiouL8e6770KpVEImkyEzM5OJsmVlZWHs2LHMDdwsYiEhIRg/fjyAHx8kuru70dPTg5qaGqjVaiZlx7q5NtfDgEqlQllZGdRqNZKSkhAXF4cP1Xk265EoG8Fl8FDa3LVPm2OMdmnjSWqkIyyvteYXZJap6CqVCk1NTVAoFKBpGv7+/oiIiIBKpQLQL32W1Rp1Oh1effVV7Ny5E48++ihOnz6NMWPGeOXcCATC8CCC5iNERkZCJBKhpaWFtbylpQWxsbGc28TGxjpc3/xnS0sLxo0bx1rHMuWR4HsIBAKEhYXhpz/9KX76058C6L/xd3Z2oqioCBcuXEBRUREOHjyImpoaJCYmslIjMzMzMWbMGE5pM0NRFDPPoqenB9XV1VCr1fDz82MJW0BAAOrq6tDS0gKZTIaMjAy7aTkA8KH6kM0yIm0El+EmaQNcH20j0jYMXBRlc0X0bDCYsySkUilEIhGam5sRFhaGxMREGI1GqFQqtLW1oaioCA8++CDi4+ORlpaG+Ph4fPbZZwgODsaZM2cwZ84cj0bNzp07hx07dqCoqAhNTU04efIkazoGF2fPnsWaNWtw7do1xMfH49lnn8WyZctY6wy2cjWBMFIgguYj+Pv7Y+bMmThz5gxz0aMoCmfOnMHy5cs5t8nLy8OZM2dYc9C++OIL5OX1Ry0SExMRGxuLM2fOMELW09ODH374AX/+85/dfEYETyMQCBAeHo477rgDd9xxB4B+aWtra2NSI//73/+ioKAADQ0NSEpKYqVGZmRkIDg4mCVtZgkzY55n0dPTg+7ubjQ0NECv10MoFCI0NBRCoRBdXV0ICQkZVJVQIm0Et+ICaQM8kyJJpG0YeDg1cqhotVooFAp0dXUhJSUF48aNY6675ikJmZmZuHTpEr7++mucOnUKX3zxBbq7u1FbW4sHH3yQedlmzpKIiopy65g1Gg0yMjLwyCOPYPHixQOuX11djbvuugt/+tOf8M9//hNnzpzBY489hnHjxmHRokUA+itXr1mzhlW5etGiRXYrVxMIIwlSJMSHOHbsGJYuXYr9+/cjJycHu3btwnvvvQeFQoGYmBg89NBDGD9+PLZu3Qqgv8z+ggULsG3bNtx11104evQoXnrpJZsy+9u2bWOV2b98+TIpsz+KMZdvNjfWLioqQnFxMVpbW5GSksKSthkzZtgUD6EoCu+88w5kMhmCgoIwefJk+Pn5sQqRWJahto62DQcibQS34oJCJIBvFiMZVYVILKTNkxE0mqZRV1cHpVKJ6OhopKSk2G2CTVEUPvzwQ6xbtw7p6enYt28fUlJS0NbWhosXL6K4uJj5VFZW4ssvv8Ttt9/ukfMQCAQDRtCefvppnD59GlevXmWWLVmyBF1dXfj0008BDL5yNYHgQ5AiISOJ++67D21tbdi0aROam5uRmZmJTz/9lHmjVltby6r8NHfuXBw5cgTPPvssNm7ciOTkZJw6dYqRMwBYv349NBoN/vjHP6Krqwvz58/Hp59+6jY5G0y6wptvvonDhw8zF/CZM2fipZdeYq2/bNkyHDrEjq4sWrSIucATBo9AIEBcXBzuuece3HPPPQD6Hxzq6+sZaTtz5gxefvlldHZ2Ii0tjZE2Pz8/7Nu3D62trThy5AhycnIYebOc1G5O1TELW3NzM3p7exEQEGAjbfYeULggkTaCWyGRNvYxRnik7cT1ne49jgUqlQqlpaUwGAzIyMhARESE3XXr6uqwdu1a/Oc//8Err7yChx56iLn3R0VF4c4778Sdd97JrN/d3c27F67nz5/HwoULWcsWLVrEZPzo9XoUFRVhw4YNzM+FQiEWLlyI8+fPe3SsBII3IBE0gscYbKPtP/zhD5g3bx7mzp0LiUSC7du34+TJk7h27RpTvGLZsmVoaWnBgQMHmO0CAgIwduxYj53XaIWiKNTW1uLChQs4c+YMTp48ifb2dqSlpUEsFiMjI4NJsUlPT4e/v7/DORGWDV/Nn76+PkgkEhtpczSHzRmItBHcCom0eRx3SJsnBM1kMqGqqgq1tbWQyWSYNGmS3T5lRqMRb7zxBp5//nncc8892LlzJy9T/ZyJoKWkpODhhx9mCdjHH3+Mu+66C729vejs7MT48ePx/fffM9MygP6Xyl9//TV++OEHt54DgeBmSASNwB927tyJxx9/HA8//DAAoKCgAKdPn8Y//vEPznSFf/7zn6zv33rrLZw4cQJnzpzBQw89xCwPCAiwWyiF4D6EQiEiIiJw8eJFHD58GL///e/xwgsvQKfT4cKFCygsLMSJEyeQn58PrVaLadOmMamRWVlZSEtLg5+fHyNtYrEY4eHhCA8PZ45hMBhYwtbQ0IC+vj4EBgayhC0kJGRQ0kYibQS3QiJt7GP4YKTNE3LW3t4OuVwOf39/5OTksIowWXPlyhWsWLECN27cwHvvvYdFixaR0vkEwgiGCBrBI7giXaG3txcGg4H1AA/0V4KKjo7G2LFj8dOf/hQvvviiw/QQgmtobW3FjBkzkJKSgm+++QYzZ85kfpaUlIT7778fQP8b4oqKCkba3n33Xaxfvx4mkwnTp09n0iNnzpyJlJQU+Pn9eFkSi8WIiIhg/Xvq9Xom0tbd3Y26ujpotVoEBQXZSJvlvgaCSBvBrRBpsz2Om8WNS9r6j+vdwiB6vR7l5eVoa2tDUlISJkyYYFe2ent7sW3bNvz973/HE088gc2bNyM4ONjDI3Y99qpMm/trikSiQVeuJhBGEkTQCB5hKI22rXn66acRFxfHylv/2c9+hsWLFyMxMRGVlZXYuHEjfv7zn+P8+fN200QIriE6Ohrvv/8+5s2b5/BNrkgkwpQpUzBlyhQ8+OCDAPqlTaFQMNJ26NAhPPnkkxAKhcjIyGAVIklKSmL9W5p7AVlLmznK1tnZievXr0On00EqldpI22B+L4i0EdzKKJY2gL/RNndFz2iaRmNjIyoqKjB27Fjk5eXZnRtG0zTOnj2LlStXYuzYsfjmm2+QnZ09YqJmeXl5+Pjjj1nLLKtMD6VyNYEwkiCCRvAJtm3bhqNHj+Ls2bOsG9qSJUuYr6dPn44ZM2Zg8uTJOHv2rMcqVo1m5s+fP6TtRCIRpk6diqlTp2LZsmWgaRoGgwFyuRyFhYW4cOEC9u/fj8uXLyMgIACZmZnIzMxkpG3SpEmsgjj+/v6IjIxEZGQks0yn0zHS1t7ejurqauj1egQHB7OkLTg4eNDSptfrUVlZicbGRsTHx+Op7L8O6e+BQLDBh6RtuPvkPA6PpM2VaDQayOVy9Pb2Ij093eHcsRs3buAvf/kLTp06hS1btmDlypWDygbwBmq1Gkqlkvm+uroaJSUlCA8Ph0wmw4YNG9DQ0IDDhw8DAP70pz9h7969WL9+PR555BF89dVXeO+993D69GlmH2vWrMHSpUsxa9YspnK1RqNhpkkQCCMZfv+PJ4wYhtJo28wrr7yCbdu24csvv8SMGTMcrjtp0iRERkZCqVQSQfMhBAIB/P39kZGRgYyMDDz66KOgaRp6vR5Xrlxhyv2/9tpruHr1KqRSKbKyspCZmckUIpHJZCxpCwgIQFRUFNP/h6ZplrS1tbWhsrISRqORM9JmuS8zFEWhvr4elZWVCAsLw5w5cyCVSkmkjeBeuKQNcEmD7eEK1kib1/ZB016X7o+iKNTU1KC6uhrjx49HZmamXdmiKArHjh3DM888g9mzZ+Py5ctITEx06XjcRWFhIW677Tbm+zVr1gAAli5dioMHD6KpqQm1tbXMzxMTE3H69Gk8+eST2L17NyZMmIC33nqL6YEGDFy5mkAYyZAqjgSPkZubi5ycHOzZswdA/81IJpNh+fLldnuavPzyy/jrX/+Kzz77DHPmzBnwGPX19ZDJZDh16hRTIp4wcqBpGlqtFpcvX2akraioCNeuXUNYWBgrNTI7OxtxcXGcomW9P8tCJD09PTCZTDaRNp1Oh4qKCgD9Fcgso3XOQqSN4HZcUEHSHemMvlJB0pWC1tXVhdLSUggEAqSnpyM0NNTuulVVVVi9ejWuXr2KXbt24fe//73DaxeBQPBpBsxVJoJG8BiDbbS9fft2bNq0CUeOHMG8efOY/QQHByM4OBhqtRpbtmzBb37zG8TGxqKyshLr16+HSqXClStXht30mOAb0DSN3t5elJSUsKRNoVAgKiqKJW1ZWVmIjY11OI+Dpmn09fUxstbV1YWenh7QNA2JRIKIiAiEhoZizJgxkEqlw36IItJGcDtE2pzCVXJmMBigVCrR2NiISZMmISEhwe51wmAwYO/evdi6dSvuv/9+bN++3aYQFmFgJkyYgI0bN+J///d/mWXff/89Fi5cCLlcjoSEBC+OjkCwgZTZJ/CHwTba3rdvH/R6PX7729+y9rN582Y899xzEIlEuHz5Mg4dOoSuri7ExcXhzjvvxAsvvEDkbBQhEAgglUoxb948RuRpmoZarUZxcTEjbSdOnEBFRQXGjRtnI21RUVGMtAkEAgQFBaGvrw+XL1/G2LFjERcXh7i4OEbcGhsbUVZWBpqmERISwoq0SaXSQU3kJ+mRBLfjgnltJD3SiWPRNFpbW6FQKBAcHIy8vDwEBQXZXbe4uBjLly+HVqvFRx99hAULFoyYIiCeJjc3FxcuXGC+p2kaq1evxpNPPknkjOCTkAgagTAIXn/9dezYsQPNzc3IyMjAnj17kJOTw7nuwYMHbSYzBwQEQKvVMt/TNI3NmzfjzTffRFdXF+bNm4d9+/YhOTnZrecxGqFpGt3d3SguLsaFCxdQXFyM4uJiKJVKyGQyZj7bjBkzUFJSgtdeew2ZmZk4evQoZ38ic+TOOj1SIBDYSFtQUNCwH7yItBHcziiOtB1veX1YhTj6+vqgUCjQ3d2N1NRUh5F6lUqFF198EW+//TbWrl2Lv/zlL3arORKcY8eOHTh06BCuXr0KADh8+DCefvppVFRUjIi2BIQRB0lxJBBcxbFjx/DQQw+hoKAAubm52LVrF44fP46ysjLOilwHDx7EqlWrUFZWxiwTCASsCc7bt2/H/2/vzsOiuNI1gL9NQ9Nssgiybwo2yNbQKIKZiIaJS5KJ1xtHc2ciJMYYJy5IjEYHAeMadRxUNBKjQedmgksM3hkjYySDRkUi3SDIKpsK0gSVrdntLlXYiQAAIABJREFUrvsHDzWWzaqy+v2eh8dQnCpPKZJ665zznW3btuHo0aNwdHTEhg0bkJWVhZycHPof9gBgGAbV1dWQSqW4fv06/vWvf+HatWsQCoUYP348bG1tIZFI4OPjA7FYjFGjRnUbtFQqlVpoq6+vB4/H4wS2jr1+KLSRIe8FCW1/in8Lurq6nJcrBgYG0NLqfrSNYRjcuXMHRUVFMDc3h7OzMwRd7LPGMAwSExMRFhYGGxsbxMbGwt3d/bnex4vq559/RmBgIGpra8Hj8SASibBx40YsWrRosLtGSGcooBHyvPj5+WHixImIiWlfp6BSqWBra4vly5d3WuQkLi4OoaGhqKmp6fR6DMPAysoKH3/8MVavXg0AqK2thbm5OeLi4jhbCJD+defOHaxduxb//Oc/sW7dOvzxj39EdnY20tLSkJaWBplMhvLycjg5OXGqR4rFYujr6/cY2hoaGtRCG5/PVwttQqGQQhsZ+kZYaPv+QSxaWlpQX1/P/vusq6tDc3MzdHR02LDW8WtHAKurq0Nubi7a2towYcKEbteOyeVyrFmzBhcuXMDWrVuxZMkS2qvzOWpsbIShoSGSkpJw4cIF/OMf/4BUKqVCK2SoojVohDwPra2tkEqlWLduHXtMQ0MDQUFBSElJ6fI8hUIBe3t7qFQq+Pj4YOvWrXBzcwPQvk+MXC7nbLxtaGgIPz8/pKSkUEAbIKdOnUJwcDDeeust5Ofnw8rKCgBgZ2eHWbNmAWgP0xUVFWxgu3z5Mvbu3YvKykqIRCLOmjZPT0/OlEYNDQ0YGBjAwMAA1tbWANpDm0KhYANbSUkJFAoFNDU11aZH9jW00Zo20u9G0Jq27x/EAmiffq6trc2pztra2sqGtbq6OpSXl6OpqQlCoRAaGhpoamrCmDFj4OnpCR0dnU6vr1KpcOzYMfz5z3/G9OnTcfPmTdjY2DzDXZLO6OrqwsPDA9999x0OHTqEH374gcIZGdYooBHSC/fv34dSqVTbf8Xc3Bx5eXmdniMSiXDkyBF4enqitrYWu3btQkBAALKzs2FjYwO5XM5e48lrdnyN9L+JEyfip59+gp+fX5dteDwerKys8Lvf/Y7dvoFhGJSVlbGhLSkpCTt27EB1dTVcXV05oc3DwwPa2tqc0NYRwDoolUpOaCsuLkZDQwM0NTXVRtoev1ZvUGgj/W4EhbYOAoEAo0ePxujRo9ljcrmc/ZlvYmKC+vp6XL58Gdra2rh06RJqa2shkUjg7++P5uZmrFy5EiUlJThy5AjmzJkzKEVA+rJ2OjAwEBcvXlQ7Pnv2bHYT6ZCQEBw9yv2ZMmPGDCQmJj7/zvfB5MmTsW/fPrz55psIDAwc1L4Q8qwooBHST/z9/eHv789+HhAQAFdXV8TGxmLTpk2D2DPyOHt7+6eq8sXj8WBrawtbW1v813/9F4D2t+V37tzB9evXkZaWhrNnz2LTpk1QKBSYMGECJ7S5ublBIBCwD2x8Ph+GhoacvZKUSiXnDX5VVRUUCgUEAkGnoa0vziiOQqVS4e7duyguLoaJiQkipuzu858DIV0a4qEtoearXp/T0tKCgoIC3L9/H05OTrCxsWH/7ba1taG+vh65ubmQyWT4xz/+gbKyMmhpacHS0hL/8z//Aw0NDZSXl8Pa2npAQ9rx48cRFhbGWTs9Y8aMLtdOnz59Gq2treznDx48gJeXF+bNm8dpN3PmTHz99dfs50OhcrKXlxe0tLSwc+fOwe4KIc+M1qAR0gutra3Q1dXFqVOnMGfOHPZ4cHAwampqcObMmV5dZ968edDU1MS3336L4uJijBs3Dunp6RCLxWybqVOnQiwWY8+ePc/9PsjAU6lUKC4uZkObVCpFRkYGmpqa4O7uztlY29XVFZqamt0+wD0Z2urq6tDQ0ABtbW210NZVsQKg/cGro4CNSCTijBJ0oFE2MiAGYU1bb8MZwzC4d+8eCgoKYGJiApFI1GUBJ4ZhkJKSguXLl0NbWxsffPABWltbkZ6eDqlUitzcXIwePRoSiQSvvvoqVq1a1ac+P42+rp1+UnR0NCIiIlBRUQE9PT0A7SNoNTU1SEhI6Ne+99W0adPg4+ODv/zlL4PdFUJ6QmvQCHkeBAIBJBIJkpKS2ICmUqmQlJSEZcuW9eoaSqUSWVlZmD17NgDA0dERFhYWSEpKYgNaXV0dUlNTsXTp0v65ETLgNDQ04OTkBCcnJ7z99tsA2r8XCgsL2dAWHx+PtWvXQqlUwsPDgx1pk0gkGD9+PKf8N5/Ph5GREYyMjNhjjx494oS2iooKNDY2QigUqoW2R48eoaCgAA8fPsTYsWNha2vb5VoNmhpJBsQAj7T1Npw1NDQgJycHzc3NcHd3h5mZWZdta2pqEBERgW+//Rbr16/HJ598ovaCpLGxETdu3IBMJoNK1ck9P2dPu3b6cYcPH8aCBQvYcNYhOTkZY8aMgbGxMaZPn47Nmzd3+pKnv6lUKlRVVeHw4cO4detWr1+WEjLUUUAjpJfCwsIQHBwMX19fTJo0CdHR0WhoaGD3Olu4cCGsra2xbds2AMBnn32GyZMnw8nJCTU1Ndi5cydu376N999/H0D7FLnQ0FBs3rwZzs7ObJl9KysrzigdGXn4fD5EIhFEIhH++Mc/AmgPbXl5eWxoO3r0KFatWgUNDQ14eXlxpkc6OTlxKsBpamrC2NgYxsbG7LGOaVcdoa2srIzdg08oFMLW1hYGBgZQKpV9WkxPoY0MiEGcHqlSqVBSUoLS0lLY2NjA29u7yz3SGIbBmTNnsHr1ari4uCA9PR3jx4/vtK2urq7a1Pf+9DRrpx/3yy+/4ObNmzh8+DDn+MyZMzF37lw4OjqiqKgI69evx6xZs5CSkjLglSkvXbqE6dOnw8XFBd999x1nXS8hwxkFNEJ6af78+aiqqkJERATkcjnEYjESExPZ//nduXOH86BbXV2NxYsXQy6Xw9jYGBKJBFevXsWECRPYNmvWrEFDQwM++OAD1NTU4KWXXkJiYiLtgfYC4vP5cHNzg5ubG0JCQsAwDNra2pCbm4u0tDRcv34dsbGxyMzMhLa2Nry8vNhy/z4+Phg7dizn+09LSwsmJiYwMjJCRkYGAMDAwACWlpZQqVTsSNvjpcQf/+jLpr0U2siAeA6hrafRs+rqauTm5oLH48HX15ezJvRJZWVl+Pjjj3H16lXs2rULwcHBI6py4OHDh+Hh4aFWUOTxCsMeHh7w9PTEuHHjkJycjFdeeWVA+xgYGDggo5GEDDRag0bIC+ZFqeg1EjEMg9bWVmRlZbH7s0mlUmRlZUFPT4+zR5uPjw+qq6sRFhaGsrIyXLhwAXZ2dmrr21pbWznr2erq6tDS0gI9PT21kv/P+nacQhsZEF2EtjP1X3d6HGgfcb516xbkcjnGjh0LOzu7LsOWUqnEoUOHsHHjRrz++uvYvXu32ijVUPAsa6cbGhpgZWWFzz77DCtXruzx9zIzM8PmzZuxZMmS59J3QkY4WoNGCPmPF6mi10jE4/Ggra0NX19f+Pr6AmgPbc3NzcjMzGSLkGzfvh05OTng8/nw8fHB73//e9y4cQMaGhqwtrbmPHgKBAKYmppy9n9qaWlhw9rDhw9RWlqK1tZW6OnpcQKbgYFBn0IbjbSRAfHkSBtPo8twxjAMKisrkZ+fDwMDA/j7+3e5pxkA3Lx5E8uXL0dVVRXi4+Mxc+bMQSmd3xvPsnb65MmTaGlpYadgd6esrAwPHjyApaXlc+k3IYRG0Ah5obxIFb1eRAzD4JtvvsGaNWswduxYvP/++6itrYVUKoVUKkVeXh5MTU0569l8fHxgYWHR40Nmc3Oz2kjbo0eP1EKbvr4+jbSRIaWzFwMA0NTUhLy8PNTW1kIkEnX776CpqQnbt2/H/v378ac//QlRUVHQ19fvz24/F8ePH0dwcDBiY2PZtdMnTpxAXl4ezM3N1dZOd/jNb34Da2trxMfHc44rFAps3LgR//3f/w0LCwsUFRVhzZo1qK+vR1ZWFr2cI6R3aASNENLuRajo9SIrKipCcHAwSktLsXv3bsyfP5/zsMkwDBQKBWQyGTvSdvr0ady6dQuWlpac0Obt7Q0zMzPO+UKhEEKhkB1pZRiGM9JWVVWFoqIiPHr0CPr6+mqhjQqRkMHQ2fdSx/5/RUVFMDc3x5QpU6ClpdXp+QzD4OLFi1ixYgWMjIzw888/w8fHZ8iOmj2pr2unASA/Px+XL1/G+fPn1a7H5/ORmZmJo0ePoqamBlZWVnj11VexadMmCmeEPEc0gkbIC+LevXuwtrbG1atXOVXE1qxZg4sXLyI1NbXb83/55Rf4+fkhNTWVs2YtPj4eurq6nIpe+vr6g1LR60VWVVWFmJgYfPLJJ71+s88wDOrq6iCTyXD9+nVIpVLIZDIUFhbCzs6Os57N29sbxsbG3T6Ydky3fHKkTalUqq1n09PTe+aCChTaSFe6GjWrq6tDTk4OlEolXF1dYWJi0uU17t+/jz//+c9ISEhAVFQUVq5c2afiOYQQ0oUe3/BQQCPkBfGsAW3JkiVISUlBZmZmt+06NuC+cOHCgFf0Is+OYRhUV1dDKpVyQltpaSkcHR05I21isRiGhoY9hrampia10MYwjFpo09XVferQplKpcOfOHax0j3zaWycjRGfh7NGjRygqKkJZWRkcHBzg4ODQ5QsklUqFEydOYO3atfD19cWBAwfg6OjY390mhLw4aIojIaSdqakp+Hw+KisrOccrKythYWHR7bkNDQ2Ij4/HZ5991uPvM3bsWJiamqKwsJAC2jDE4/FgYmKC3/72t/jtb38LoD1kVVVVQSqVckr+l5WVwcnJSS206evrs6GNx+NBV1cXurq67PcZwzBobGxkw1p5eTny8vI6DW16eno9Tid7+PAhu6/T13f+qjYqQiNtL47OwllVVRXy8vIgFArh5+fX7QhzSUkJQkNDkZmZib1792L+/PkjqnQ+IWR4oBE0Ql4gfn5+mDRpEvbt2weg/U2xnZ0dli1b1m2RkLi4OHz44YcoLy/vcW1ZWVkZ7OzskJCQgN/97nfPtf9k6GAYBhUVFUhLS2NL/stkMsjlcohEIk5o8/T0hK6ubo8jbQ0NDZxRtvr6evB4vE5H2ng8HlpaWlBQUICqqqoeS6M/iULbyNJZMGtpaUF+fj4ePHgAZ2dnWFtbd/k92NbWhv3792Pr1q2YP38+duzYQetoCSH9haY4EkL+gyp6kf7EMAzKysrY0NZRPbK6uhqurq6c0Obu7g6hUNhtaFOpVGqhTaFQgMfjQSAQoLm5GaNGjYKzszOMjIyeuXADhbbh6clwxjAMysvLcevWLYwePRoikajLn0UMwyA9PR3Lli1DY2MjYmNjERgYOGyKgBBChiUKaIQQrpiYGHajarFYjL1798LPzw9A+8bUDg4OiIuLY9vn5+fDxcUF58+fZ6e8dWhqasKcOXOQnp6uVtFrKG7cSgZex9qw69evs6FNJpOhvr4eEyZM4JT7d3Nzg0Ag6Pbh+MGDB8jNzYVSqcSoUaPQ0tIChUIBPp/PGWUbNWpUjwGwNyi0DV2djZopFArk5uaiubkZLi4uMDMz6/J8hUKBTZs24fDhwwgLC0N4eDiEQmF/dpkQQgAKaIQQQoYalUqF4uJiTmjLyMhAU1MT3N3dOaHN1dUVmpqaKCsrw8cffwwdHR1ERUXB3t6enc6oUqmgUCjURto0NTXVQpu2tjaFthEg8tJKzt+rpqYmbt++jdLSUtjY2GDcuHFdVlxkGAaJiYkICwuDjY0NYmNj4e7uPsB3QAh5gVFAI4SMLJcuXcLOnTshlUpRUVGB77//HnPmzOn2nOTkZISFhSE7Oxu2trYIDw9HSEgIp83+/fvZkUUvLy/s27ePs50A6V9KpRKFhYVsaJPJZEhPT0dbWxtsbGxQUVEBd3d3rF+/HtOmTeux3LlSqew0tAkEgk5D27Oi0DYwTtceQX19PefvtaGhAUD7Hl3m5uYwMzPrMozL5XKsXbsWP/74I7Zu3YolS5bQdiCEkIFGAY0QMrKcO3cOV65cgUQiwdy5c3sMaCUlJXB3d8eHH36I999/H0lJSQgNDcXZs2cxY8YMAO1r8xYuXIiDBw/Cz88P0dHROHnyJPLz89mNmcnAu3z5MhYvXozq6mq8/PLLKCsrw40bN8Dj8eDp6clZ0+bs7Nzjg7ZSqez04V5bW1utEAmFtqHnySmNbW1tKCgogFwuh7W1NXR0dFBfX4/6+nooFAocOHAAdXV18PDwgEQiwf3797Fz505Mnz4de/fuhY2NzSDdSd9eCMXFxeHdd9/lHNPW1kZzczP7OcMwiIyMxKFDh1BTU4MpU6bgiy++gLOzc7/eByHkqVBAI4SMXDwer8eAtnbtWpw9exY3b95kjy1YsAA1NTVITEwE0F7dcuLEiYiJiQHQPmXO1tYWy5cv77a6JekfVVVV+PTTTxEfH4/169dj9erV0NbWBsMwaGtrQ25uLlvuXyaTITMzEwKBAGKxmLO59tixY3us6vjo0SO10NbY2AihUKgW2gQCwTPfG4W2vuusCIhcLkdBQQFGjRoFFxcX6OjocNoolUpcvXoVly9fRmpqKnJyclBeXg5DQ0MEBARAIpGwHzY2NgNaFKSvL4Ti4uKwcuVK5Ofns8d4PB5nne/nn3+Obdu24ejRo3B0dMSGDRuQlZWFnJwcWldHyNBD+6ARQl5sKSkpCAoK4hybMWMGQkNDAQCtra2QSqVYt24d+3UNDQ0EBQUhJSVlQPtK2v3v//4vHj58iOzsbDg4OLDHO6o3enl5wcvLC4sWLQLDMGhtbUVWVhY7NXLfvn3IysqCrq4uuzdbR2h7shS/pqYmjI2NYWxszB5ra2vjhLZ79+6hqakJQqFQbXqklpZWn+6ts8IWFNq69uSfV1NTE3Jzc1FfXw+RSARzc/NOwxWfz8ekSZNw5coVXLlyBSEhIQgPD0dpaSlbXfTMmTPIzs6Gqakp5s2bx76g6W+7d+/G4sWL2VGxgwcP4uzZszhy5EiXL4R4PF6X+1UyDIPo6GiEh4fjzTffBAAcO3YM5ubmSEhIwIIFC/rnRggh/YYCGiFkRJPL5WoVJc3NzVFXV4empiZUV1dDqVR22qZj82MysEJDQ7Fq1apeteXxeNDW1oavry98fX0BtD+wNjc3IzMzky1CsnPnTmRnZ8PIyAhisZhTiMTa2poT2rS0tGBiYsLZ8LqtrY0zylZWVobm5mbo6OhwApuBgQGFtufgyT+TjmqgRUVFsLS0hIeHR5d/zgzD4Nq1a1ixYgV4PB7Onz+PgIAA8Hg8WFpawt/fn23b2NiIGzduQKFQ9Ov9dHjaF0IKhQL29vZQqVTw8fHB1q1b4ebmBqB9GrdcLue8iDI0NISfnx9SUlIooBEyDFFAI4QQMqQ863QzHo8HHR0d+Pn5sVtIMAyDxsZGZGRksKFt8+bNyMvLg6mpKWc9m4+PDywsLDj90NLSwujRozmbF7e2trIjbbW1tbh79y6am5uhq6urFtp6KmrSoWMPr9B/hMDExAQikYidovYihLbOwmptbS1yc3PZcPL4aGdnbSMjI/HNN99g3bp1WLNmTbdTU3V1dTmBrb/dv3+/zy+ERCIRjhw5Ak9PT9TW1mLXrl0ICAhAdnY2bGxsIJfL2Ws8ec2OrxFChhcKaISQEc3CwgKVlZWcY5WVlRg1ahR0dHTA5/PB5/M7bdPVlCIy/PB4POjp6WHKlCmYMmUKgPYwpFAoIJPJ2NB2+vRp3Lp1C5aWlpzQ5u3tDTMzM05oEwgEnYa2jlG26upq3L59Gy0tLdDT01MLbU8WNamvr0dubi5aWlrg7u6utofXSB9pe/L+Hj16hMLCQpSXl8PBwQGOjo5drilkGAb/93//h9WrV2P8+PGQyWQQiUQD0e1+5+/vzwmRAQEBcHV1RWxsLDZt2jSIPSOE9BcKaISQEc3f3x8//PAD59iPP/7IPvAIBAJIJBIkJSWxxUZUKhWSkpKwbNmyAe8vGTg8Hg8GBgaYOnUqpk6dCqD9Qb+urg4ymQzXr1+HVCpFfHw8CgsLYWdnx1nP5u3tDWNjY7XQZmpqClNTU/ZYc3MzO9L24MEDlJSUoLW1Ffr6+hg1ahT09PRQV1eHX3/9lQ0ivS39/mSoGY6BrbPgWVVVhdzcXOjo6GDy5MnQ09Pr8vzy8nKEhYXh6tWr2LlzJ0JCQnosDjNYTE1Nn/mFkJaWFry9vVFYWAgA7HmVlZWwtLTkXFMsFj+nnhNCBhIFNELIsKJQKNgHE6B9/UVGRgZMTExgZ2eHdevWoby8HMeOHQMAfPjhh4iJicGaNWvw3nvv4aeffsKJEydw9uxZ9hphYWEIDg6Gr68vJk2ahOjoaDQ0NKiVtiYjH4/Hg6GhIaZNm4Zp06YBaA9t1dXVkEqlbGiLi4tDaWkpHBwcOFMjxWIxDA0NOaFNKBRCKBSyI2IMw6ClpQW1tbWQy+Wc7+eqqiq0tLRwRtr6EjaG2yjbk/1tbm5Gfn4+Hj58iPHjx8PKyqrLKa9KpRKHDh3Cxo0b8frrryMnJ0dtmt9Q8zxeCCmVSmRlZWH27NkAAEdHR1hYWCApKYkNZHV1dUhNTcXSpUv750YIIf2KyuwTQoaV5ORk9sH5ccHBwYiLi0NISAhKS0uRnJzMOWfVqlXIycmBjY0NNmzYoLZRdUxMDLsvkVgsxt69e9n1S4Q8iWEYVFVVQSqVIi0tja0gWVZWBicnJ870SLFYDH19fU7QKCgowMmTJzFlyhSMHz8eFhYWaGlp4RQiqaurg1KpZEfaOj709fWfeYRosENbZ6Xzy8rKUFhYCFNTU4wfP77bveiys7OxbNky/Prrr9i/fz9mzZo1oKXyn8Xx48cRHByM2NhY9oXQiRMnkJeXB3NzcyxcuBDW1tbYtm0bAOCzzz7D5MmT4eTkhJqaGuzcuRMJCQmQSqWYMGECgPYy+9u3b+eU2c/MzKQy+4QMTbQPGiGEDFWXLl3Czp07IZVKUVFR0eOebqdPn8YXX3yBjIwMtLS0wM3NDVFRUeyG2wAQFRWFjRs3cs4TiURUkXIAdOzP1RHYpFIpZDIZ5HI5RCIRvL294enpiYKCAnz77beYNWsWDh8+3GUQYRgGTU1NnMBWX18PlUqlFtr09PSGRWjrbIRPoVAgJycHLS0tcHV15UwPfVJTUxM+//xzxMTEYOnSpdi4cSP09fX7s8v9orsXQoGBgXBwcEBcXBwAYNWqVTh9+jTkcjmMjY0hkUiwefNmeHt7s9fr2Kj6yy+/RE1NDV566SUcOHAA48ePH4zbI4R0jwIaIYQMVefOncOVK1cgkUgwd+7cHgNaaGgorKysMG3aNBgZGeHrr7/Grl27kJqayj6sRUVF4dSpU7hw4QJ7nqamZrcPvaT/dIwMpaWl4fTp00hISACfz4exsTH09PQ4I20eHh4QCoXdjgR1VKN8MrQxDKO2sbaent4zjyo9z9D2ZDhTKpUoKSnB7du3YWtri3HjxnW59o5hGFy6dAnLly+HoaEhYmNjIZFIhs2oGSGEPIYCGiGEDAc8Hq/HgNYZNzc3zJ8/HxEREQDaA1pCQgIyMjL6o5vkKdy/fx9r167F8ePHERkZiRUrVqCiogLXr1/njLTV19djwoQJnDVtbm5uEAgEfQ5tdXV1bBGUx0Obrq7ugIe2zkbNHj58iJycHGhpaWHChAkwMDDo8vwHDx4gPDwcp0+fRmRkJEJDQ3u9bQEhhAxBPf4Qpp9whBAyTKlUKtTX13M2VAaAW7duwcrKCkKhEP7+/ti2bRvs7OwGqZcvtoKCAgQEBGDKlCnIzs6Gvb09AMDBwQEODg6YN28egPa/y+LiYrYIyffff4+IiAg0NTXB3d2dE9pcXV2hqanJBq2OLQT09PTYKn4qlYoT2u7evYv6+nrweDxOYOvYbqIvoa0vhUiebNva2opbt26hsrISTk5OsLW17fL3VqlUOHnyJNauXQuJRIIbN25g7Nixve4nIYQMVzSCRgghQ8DTjKDt2LED27dvR15eHsaMGQOgfdqkQqGASCRCRUUFNm7ciPLycty8ebPbUQrSP1QqFf7973/jlVde6fO5SqUShYWF7EibTCZDeno6Hj16BA8PD3Z6pEQigUgkAp/P7zZoqVQqNDQ0qE2P5PP5aqGtp6mWfdWxPi8/Px+GhoZwcXGBjo5Ol+1LSkqwatUq3LhxA3/961+xYMGCIVs6nxBC+oimOBJCRoZvv/0W7733HoqLi9lRgnfffRdSqRQ///wzDA0NB7mHz6avAe3vf/87Fi9ejDNnziAoKKjLdjU1NbC3t8fu3buxaNGi59VdMkiUSiXy8vI4oe3GjRvg8Xjw9PTkrGlzdnbucT81lUoFhULBCW0KhQKamppq0yOfNrQ1NjYiNzcXCoUCLi4uGDNmTJfXaWtrw4EDB7BlyxbMnz8fO3bs4GwETgghIwAFNELIyMAwDMRiMV5++WXs27cPkZGROHLkCK5duwZra+vB7t4z60tAi4+Px3vvvYeTJ0/itdde67H9xIkTERQUxJbtJiMHwzBoa2tDbm4u0tLScP36dchkMmRmZkIgEEAsFnM21x47dmyPI1FKpVIttDU0NEBTU1NtpE1bW7vbKYq3b99GcXExrKys4OTkBC0trS7vIz09HcuWLUNjYyNiY2MRGBhIRUAIISMRrUEjhIwMPB4PW7ZswVtvvQULCwvs27cPP//884gIZ33RMZIYHx/fq3CmUChQVFSEd955ZwB6RwYaj8eDQCCAl5cXvLy8sGjRIjAMg9bWVty8eZMtQrJv3z5kZWVBV1cXPj4+8PLyYkObvb09J7Tx+XwYGhpyRqWVSiXq6+vZwPbrr7+ioaEBAoGg09BWW1uLnJwcMAwDiUQCIyOjLu9BoVBg8+bN+Oqrr7Bq1SqEh4d3O/12ddVvAAAPNklEQVSREEJGOhpBI4QMKz4+PsjOzsb58+cxderUwe7OM1EoFCgsLAQAeHt7Y/fu3Zg2bRpMTExgZ2eHdevWoby8HMeOHQPQPq0xODgYe/bswdy5c9nr6OjosA/Tq1evxhtvvAF7e3vcu3cPkZGRyMjIQE5ODszMzAb+JsmQwDAMmpubkZmZyYY2qVSK7OxsGBoacqZG+vj4wNraulcjbY+Hto6RNj6fD6VSyX4fGxoaQiAQdNqn8+fPIzQ0FNbW1oiNjYWHh0d//REQQshQQVMcCSEjR2JiIubOncuODri4uAx2l55JcnIypk2bpnY8ODgYcXFxCAkJQWlpKZKTkwG0b2B78eLFLtsDwIIFC3Dp0iU8ePAAZmZmeOmll7BlyxaMGzeuP2+FDEMd5fkzMjI4oS0vLw+mpqZqoc3CwqLbKYd3795FcXExBAIBTE1N0dzcjLq6OjQ2NiIvLw/nzp2Dl5cXJk2aBGdnZ+zatQv/+te/sGXLFixdurTH9XL9af/+/ezG0V5eXti3bx8mTZrUadtDhw7h2LFjuHnzJgBAIpFg69atnPYhISE4epRbwXLGjBlITEzsv5sghAwXFNAIISODTCZDYGAgYmNjERcXh1GjRuHkyZOD3S0C4NKlS9i5cyekUikqKip6XEvXVTCtqKiAhYUF+3lfHprJ88EwDBQKBWQyGRvYpFIpCgoKYGlpyYa2juBmZmaGkpISLFu2DHw+H7GxsbC0tOQEuba2NmRlZbH78928eROVlZXQ1dXFtGnT8PLLL8PX1xc+Pj7dToXsL8ePH8fChQtx8OBB+Pn5ITo6GidPnkR+fj5bHfVxf/jDHzBlyhQEBARAKBTi888/x/fff4/s7Gx2ynVISAgqKyvx9ddfs+dpa2vD2Nh4wO6LEDJkUUAjhAx/paWl8Pf3x8qVK/Hpp58iNTUV/v7+SEtLg4+Pz2B374V37tw5XLlyBRKJBHPnzu11QMvPz8eoUaPY42PGjGGn1fX1oZn0H4ZhUFdXB5lMxu7TJpPJUFhYCBMTEzQ1NUEsFuPDDz9kp+h2NtJWUFCAFStWoKioCFu2bIG1tTWkUinS0tKQlpaG27dvw8nJCb6+vtiyZcuA7Xnm5+eHiRMnIiYmBkB7cRNbW1ssX74cn376aY/nK5VKGBsbIyYmBgsXLgTQHtBqamqQkJDQr30nhAxLFNAIIcPbw4cPERAQgMDAQBw8eJA9/tprr0GpVNKUoSGmN9UoOwJadXV1lyMmz/rQTPpXZmYmFi1ahPLycsyePRvV1dWQyWQoLS2Fg4OD2sbacXFx2LVrF4KDg7F169ZO/96rqqrYwLZkyZIBWTPZ2toKXV1dnDp1ivM9GxwcjJqaGpw5c6bHa9TX12PMmDE4efIkXn/9dQDtAS0hIQECgQDGxsaYPn06Nm/eTFsGEEIAquJICBnuTExMkJeXp3b87Nmzg9Ab8jyJxWK0tLTA3d0dUVFRmDJlCoD2h2apVIp169axbTU0NBAUFISUlJTB6i4B0NTUhE2bNiE6OhorV67Ehg0boKurC6B9pO3xkHX9+nXExsairKwMVlZWOH/+PAICArpcx2ZmZoaZM2di5syZA3Y/9+/fh1KphLm5Oee4ubl5pz93OrN27VpYWVlx9iOcOXMm5s6dC0dHRxQVFWH9+vWYNWsWUlJSBnWtHSFkeKCARgghZEBZWlri4MGD8PX1RUtLC7766isEBgYiNTUVPj4+z+WhmfSP9PR0/Pvf/8a1a9fg6enJ+RqPx8OYMWMwa9YszJo1C0B7aEtLS4OtrS1nfeFIsX37dsTHxyM5ORlCoZA9vmDBAva/PTw84OnpiXHjxiE5ORmvvPLKYHSVEDKMUEAjhBAyoEQiEUQiEft5QEAAioqK8Ne//hV/+9vfBrFnpCcBAQG4evVqrzeQ5vF4mDhxYj/36umZmpqCz+ejsrKSc7yysrLHQLlr1y5s374dFy5cUAurTxo7dixMTU1RWFhIAY0Q0qPuNzkhhBBCBsCkSZPYPeGe5aGZ9L/ehrPhQCAQQCKRICkpiT2mUqmQlJQEf3//Ls/bsWMHNm3ahMTERPj6+vb4+5SVleHBgwewtLR8Lv0mhIxsFNAIIYQMuoyMDPbh9Wkfmgl5GmFhYTh06BCOHj2K3NxcLF26FA0NDXj33XcBAAsXLuSsh/z888+xYcMGHDlyBA4ODpDL5ZDL5VAoFADaN6D/5JNPcO3aNZSWliIpKQlvvvkmnJycMGPGjEG5R0LI8EJTHAkhhDwThULBjn4BQElJCTIyMmBiYgI7OzusW7cO5eXlOHbsGAAgOjoajo6OcHNzQ3NzM7766iv89NNPOH/+PHuNsLAwBAcHw9fXF5MmTUJ0dDTnoZmQ52X+/PmoqqpCREQE5HI5xGIxEhMT2TWQd+7cYbd/AIAvvvgCra2teOuttzjXiYyMRFRUFPh8PjIzM3H06FHU1NTAysoKr776KjZt2gRtbe0BvTdCyPBEZfYJIYQ8k642ng4ODkZcXBxCQkJQWlqK5ORkAO3Tw7788kuUl5dDV1cXnp6eiIiIULtGTEwMu1G1WCzG3r174efnNxC3RAghhPQX2geNEEIIIYQQQoaIHgMarUEjhBBCHnPp0iW88cYbsLKyAo/HQ0JCQrftQ0JCwOPx1D7c3NzYNlFRUWpfd3Fx6e9bIYQQMgxRQCOEEEIe09DQAC8vL+zfv79X7ffs2YOKigr24+7duzAxMcG8efM47dzc3DjtLl++3B/dJ4QQMsxRkRBCCCHkMY9vtNwbhoaGMDQ0ZD9PSEhAdXW1WkETTU1N2iaAEEJIj2gEjRBCCHmODh8+jKCgINjb23OO37p1C1ZWVhg7diz+8Ic/4M6dO4PUQ0IIIUMZBTRCCCHkObl37x7OnTuH999/n3Pcz88PcXFxSExMxBdffIGSkhL85je/QX19/SD1lBBCyFBFUxwJIYSQ5+To0aMwMjLCnDlzOMcfnzLp6ekJPz8/2Nvb48SJE1i0aNFAd5MQQsgQRiNohBBCyHPAMAyOHDmCd955BwKBoNu2RkZGGD9+PGeDb9Ju//79cHBwgFAohJ+fH3755Zdu2588eRIuLi4QCoXw8PDADz/8wPk6wzCIiIiApaUldHR0EBQUhFu3bvXnLRBCyDOhgEYIIYQ8BxcvXkRhYWGvRsQUCgWKiopgaWk5AD0bPo4fP46wsDBERkZCJpPBy8sLM2bMwK+//tpp+6tXr+Ltt9/GokWLkJ6ejjlz5mDOnDm4efMm22bHjh3Yu3cvDh48iNTUVOjp6WHGjBlobm4eqNsihJA+oY2qCSGEkMcoFAp2ZMvb2xu7d+/GtGnTYGJiAjs7O6xbtw7l5eU4duwY57x33nkHt27dwrVr19SuuXr1arzxxhuwt7fHvXv3EBkZiYyMDOTk5MDMzGxA7ms48PPzw8SJExETEwMAUKlUsLW1xfLly/Hpp5+qtZ8/fz4aGhrwz3/+kz02efJkiMViHDx4EAzDwMrKCh9//DFWr14NAKitrYW5uTni4uKwYMGCgbkxQgj5D9qomhBCCOmLtLQ0eHt7w9vbGwAQFhYGb29vREREAAAqKirUKjDW1tbiu+++63L0rKysDG+//TZEIhF+//vfY/To0bh27RqFs8e0trZCKpUiKCiIPaahoYGgoCCkpKR0ek5KSgqnPQDMmDGDbV9SUgK5XM5pY2hoCD8/vy6vSQghg40CGiGEEPKYwMBAMAyj9hEXFwcAiIuLQ3JyMuccQ0NDNDY2YvHixZ1eMz4+Hvfu3UNLSwvKysoQHx+PcePG9fOdANu2bcPEiRNhYGCAMWPGYM6cOcjPz+/xvMFY13X//n0olUqYm5tzjpubm0Mul3d6jlwu77Z9x699uSYhhAw2CmiEEELICHXx4kV89NFHuHbtGn788Ue0tbXh1VdfRUNDQ5fn0LouQggZXBTQCCGEkBEqMTERISEhcHNzg5eXF+Li4nDnzh1IpdIuz9mzZw9mzpyJTz75BK6urti0aRN8fHzYdWEMwyA6Ohrh4eF488034enpiWPHjuHevXtISEh46r6ampqCz+ejsrKSc7yyshIWFhadnmNhYdFt+45f+3JNQggZbBTQCCGEkBdEbW0tAMDExKTLNoO1rksgEEAikSApKYk9plKpkJSUBH9//07P8ff357QHgB9//JFt7+joCAsLC06buro6pKamdnlNQggZbLRRNSGEEPICUKlUCA0NxZQpU+Du7t5lu8Fc1xUWFobg4GD4+vpi0qRJiI6ORkNDA959910AwMKFC2FtbY1t27YBAFauXImpU6fiL3/5C1577TXEx8cjLS0NX375JQCAx+MhNDQUmzdvhrOzMxwdHbFhwwZYWVmpbSZOCCFDBQU0Qggh5AXw0Ucf4ebNm7h8+fJgd6VL8+fPR1VVFSIiIiCXyyEWi5GYmMiGwTt37kBD4z+TfwICAvD3v/8d4eHhWL9+PZydnZGQkMAJoGvWrEFDQwM++OAD1NTU4KWXXkJiYiKEQuGA3x8hhPQG7YNGCCGEjHDLli3DmTNncOnSJTg6Onbb1s7ODmFhYQgNDWWPRUZGIiEhATdu3EBxcTHGjRuH9PR0iMVits3UqVMhFouxZ8+efrsPQggZAWgfNEIIIeRFxTAMli1bhu+//x4//fRTj+EMoHVdhBAy2PhRUVG9bdvrhoQQQggZfB999BG++eYbnDp1ClZWVlAoFFAoFODz+dDS0gLQvq7rl19+YYt+WFtbIzw8HHp6ejAxMUFMTAyOHz+Ow4cPY8yYMeDxeFAqldi6dSsmTJiA1tZWrFixAo2Njdi3bx80NWn1BCGEdGNjTw1oiiMhhBAyQvF4nc+k+frrrxESEgKgfWNuBwcHdiNuoH2j6vDwcJSWlsLZ2Rk7duzA7Nmz2a8zDIPIyEh8+eWX7LquAwcOYPz48f15O4QQMhL0OMWRAhohhBBCCCGEDAxag0YIIYQQQgghwwUFNEIIIYQQQggZIiigEUIIIYQQQsgQQQGNEEIIIYQQQoaIvtTC7XFBGyGEEEIIIYSQp0cjaIQQQgghhBAyRFBAI4QQQgghhJAhggIaIYQQQgghhAwRFNAIIYQQQgghZIiggEYIIYQQQgghQwQFNEIIIYQQQggZIiigEUIIIYQQQsgQQQGNEEIIIYQQQoYICmiEEEIIIYQQMkT8P2w+8Jv2QRjWAAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "op = Operator(update, opt='noop')\n", "op(time=nt+1, dt=dt)\n", "\n", "plot_field(u.data[0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note that the real power of Devito is hidden within `Operator`, it will automatically generate and compile the optimized C code. We can look at this code (noting that this is not a requirement of executing it) via:" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "tags": [ "nbval-ignore-output" ] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "#define _POSIX_C_SOURCE 200809L\n", "#define START_TIMER(S) struct timeval start_ ## S , end_ ## S ; gettimeofday(&start_ ## S , NULL);\n", "#define STOP_TIMER(S,T) gettimeofday(&end_ ## S, NULL); T->S += (double)(end_ ## S .tv_sec-start_ ## S.tv_sec)+(double)(end_ ## S .tv_usec-start_ ## S .tv_usec)/1000000;\n", "\n", "#include \"stdlib.h\"\n", "#include \"math.h\"\n", "#include \"sys/time.h\"\n", "\n", "struct dataobj\n", "{\n", " void *restrict data;\n", " unsigned long * size;\n", " unsigned long * npsize;\n", " unsigned long * dsize;\n", " int * hsize;\n", " int * hofs;\n", " int * oofs;\n", " void * dmap;\n", "} ;\n", "\n", "struct profiler\n", "{\n", " double section0;\n", "} ;\n", "\n", "\n", "int Kernel(const float dt, const float h_x, const float h_y, struct dataobj *restrict u_vec, const int time_M, const int time_m, const int x_M, const int x_m, const int y_M, const int y_m, struct profiler * timers)\n", "{\n", " float (*restrict u)[u_vec->size[1]][u_vec->size[2]] __attribute__ ((aligned (64))) = (float (*)[u_vec->size[1]][u_vec->size[2]]) u_vec->data;\n", "\n", " for (int time = time_m, t0 = (time)%(2), t1 = (time + 1)%(2); time <= time_M; time += 1, t0 = (time)%(2), t1 = (time + 1)%(2))\n", " {\n", " /* Begin section0 */\n", " START_TIMER(section0)\n", " for (int x = x_m; x <= x_M; x += 1)\n", " {\n", " for (int y = y_m; y <= y_M; y += 1)\n", " {\n", " u[t1][x + 1][y + 1] = dt*(-(-u[t0][x][y + 1]/h_x + u[t0][x + 1][y + 1]/h_x) - (-u[t0][x + 1][y]/h_y + u[t0][x + 1][y + 1]/h_y) + u[t0][x + 1][y + 1]/dt);\n", " }\n", " }\n", " STOP_TIMER(section0,timers)\n", " /* End section0 */\n", " }\n", "\n", " return 0;\n", "}\n", "\n" ] } ], "source": [ "print(op.ccode)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Second derivatives and high-order stencils\n", "\n", "In the above example only a combination of first derivatives was present in the governing equation. However, second (or higher) order derivatives are often present in scientific problems of interest, notably any PDE modeling diffusion. To generate second order derivatives we must give the `devito.Function` object another piece of information: the desired discretisation of the stencil(s).\n", "\n", "First, lets define a simple second derivative in `x`, for which we need to give $u$ a `space_order` of (at least) `2`. The shorthand for this second derivative is `u.dx2`. " ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial^{2}}{\\partial x^{2}} u{\\left(t,x,y \\right)}$" ], "text/plain": [ "Derivative(u(t, x, y), (x, 2))" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "u = TimeFunction(name='u', grid=grid, space_order=2)\n", "u.dx2" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle - \\frac{2.0 u{\\left(t,x,y \\right)}}{h_{x}^{2}} + \\frac{u{\\left(t,x - h_{x},y \\right)}}{h_{x}^{2}} + \\frac{u{\\left(t,x + h_{x},y \\right)}}{h_{x}^{2}}$" ], "text/plain": [ "-2.0*u(t, x, y)/h_x**2 + u(t, x - h_x, y)/h_x**2 + u(t, x + h_x, y)/h_x**2" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "u.dx2.evaluate" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can increase the discretisation arbitrarily if we wish to specify higher order FD stencils:" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial^{2}}{\\partial x^{2}} u{\\left(t,x,y \\right)}$" ], "text/plain": [ "Derivative(u(t, x, y), (x, 2))" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "u = TimeFunction(name='u', grid=grid, space_order=4)\n", "u.dx2" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle - \\frac{2.5 u{\\left(t,x,y \\right)}}{h_{x}^{2}} - \\frac{0.0833333333 u{\\left(t,x - 2 h_{x},y \\right)}}{h_{x}^{2}} + \\frac{1.33333333 u{\\left(t,x - h_{x},y \\right)}}{h_{x}^{2}} + \\frac{1.33333333 u{\\left(t,x + h_{x},y \\right)}}{h_{x}^{2}} - \\frac{0.0833333333 u{\\left(t,x + 2 h_{x},y \\right)}}{h_{x}^{2}}$" ], "text/plain": [ "-2.5*u(t, x, y)/h_x**2 - 0.0833333333*u(t, x - 2*h_x, y)/h_x**2 + 1.33333333*u(t, x - h_x, y)/h_x**2 + 1.33333333*u(t, x + h_x, y)/h_x**2 - 0.0833333333*u(t, x + 2*h_x, y)/h_x**2" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "u.dx2.evaluate" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To implement the diffusion or wave equations, we must take the Laplacian $\\nabla^2 u$, which is the sum of the second derivatives in all spatial dimensions. For this, Devito also provides a shorthand expression, which means we do not have to hard-code the problem dimension (2D or 3D) in the code. To change the problem dimension we can create another `Grid` object and use this to re-define our `Function`'s:" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle u{\\left(t,x,y,z \\right)}$" ], "text/plain": [ "u(t, x, y, z)" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grid_3d = Grid(shape=(5, 6, 7), extent=(1., 1., 1.))\n", "\n", "u = TimeFunction(name='u', grid=grid_3d, space_order=2)\n", "u" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can re-define our function `u` with a different `space_order` argument to change the discretisation order of the stencil expression created. For example, we can derive an expression of the 12th-order Laplacian $\\nabla^2 u$:" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial^{2}}{\\partial x^{2}} u{\\left(t,x,y,z \\right)} + \\frac{\\partial^{2}}{\\partial y^{2}} u{\\left(t,x,y,z \\right)} + \\frac{\\partial^{2}}{\\partial z^{2}} u{\\left(t,x,y,z \\right)}$" ], "text/plain": [ "Derivative(u(t, x, y, z), (x, 2)) + Derivative(u(t, x, y, z), (y, 2)) + Derivative(u(t, x, y, z), (z, 2))" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "u = TimeFunction(name='u', grid=grid_3d, space_order=12)\n", "u.laplace" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The same expression could also have been generated explicitly via:" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial^{2}}{\\partial x^{2}} u{\\left(t,x,y,z \\right)} + \\frac{\\partial^{2}}{\\partial y^{2}} u{\\left(t,x,y,z \\right)} + \\frac{\\partial^{2}}{\\partial z^{2}} u{\\left(t,x,y,z \\right)}$" ], "text/plain": [ "Derivative(u(t, x, y, z), (x, 2)) + Derivative(u(t, x, y, z), (y, 2)) + Derivative(u(t, x, y, z), (z, 2))" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "u.dx2 + u.dy2 + u.dz2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Derivatives of composite expressions\n", "\n", "Derivatives of any arbitrary expression can easily be generated:" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "u = TimeFunction(name='u', grid=grid, space_order=2)\n", "v = TimeFunction(name='v', grid=grid, space_order=2, time_order=2)" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial^{2}}{\\partial x^{2}} u{\\left(t,x,y \\right)} + \\frac{\\partial^{2}}{\\partial y^{2}} u{\\left(t,x,y \\right)} + \\frac{\\partial^{2}}{\\partial t^{2}} v{\\left(t,x,y \\right)}$" ], "text/plain": [ "Derivative(u(t, x, y), (x, 2)) + Derivative(u(t, x, y), (y, 2)) + Derivative(v(t, x, y), (t, 2))" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "v.dt2 + u.laplace" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial^{2}}{\\partial x^{2}} \\left(\\frac{\\partial^{2}}{\\partial x^{2}} u{\\left(t,x,y \\right)} + \\frac{\\partial^{2}}{\\partial y^{2}} u{\\left(t,x,y \\right)} + \\frac{\\partial^{2}}{\\partial t^{2}} v{\\left(t,x,y \\right)}\\right)$" ], "text/plain": [ "Derivative(Derivative(u(t, x, y), (x, 2)) + Derivative(u(t, x, y), (y, 2)) + Derivative(v(t, x, y), (t, 2)), (x, 2))" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(v.dt2 + u.laplace).dx2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Which can, depending on the chosen discretisation, lead to fairly complex stencils: " ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle - \\frac{2.0 \\left(\\left(- \\frac{2.0 v{\\left(t,x,y \\right)}}{dt^{2}} + \\frac{v{\\left(t - dt,x,y \\right)}}{dt^{2}} + \\frac{v{\\left(t + dt,x,y \\right)}}{dt^{2}}\\right) + \\left(- \\frac{2.0 u{\\left(t,x,y \\right)}}{h_{x}^{2}} + \\frac{u{\\left(t,x - h_{x},y \\right)}}{h_{x}^{2}} + \\frac{u{\\left(t,x + h_{x},y \\right)}}{h_{x}^{2}}\\right) + \\left(- \\frac{2.0 u{\\left(t,x,y \\right)}}{h_{y}^{2}} + \\frac{u{\\left(t,x,y - h_{y} \\right)}}{h_{y}^{2}} + \\frac{u{\\left(t,x,y + h_{y} \\right)}}{h_{y}^{2}}\\right)\\right)}{h_{x}^{2}} + \\frac{\\left(- \\frac{2.0 v{\\left(t,x - h_{x},y \\right)}}{dt^{2}} + \\frac{v{\\left(t - dt,x - h_{x},y \\right)}}{dt^{2}} + \\frac{v{\\left(t + dt,x - h_{x},y \\right)}}{dt^{2}}\\right) + \\left(\\frac{u{\\left(t,x,y \\right)}}{h_{x}^{2}} + \\frac{u{\\left(t,x - 2 h_{x},y \\right)}}{h_{x}^{2}} - \\frac{2.0 u{\\left(t,x - h_{x},y \\right)}}{h_{x}^{2}}\\right) + \\left(- \\frac{2.0 u{\\left(t,x - h_{x},y \\right)}}{h_{y}^{2}} + \\frac{u{\\left(t,x - h_{x},y - h_{y} \\right)}}{h_{y}^{2}} + \\frac{u{\\left(t,x - h_{x},y + h_{y} \\right)}}{h_{y}^{2}}\\right)}{h_{x}^{2}} + \\frac{\\left(- \\frac{2.0 v{\\left(t,x + h_{x},y \\right)}}{dt^{2}} + \\frac{v{\\left(t - dt,x + h_{x},y \\right)}}{dt^{2}} + \\frac{v{\\left(t + dt,x + h_{x},y \\right)}}{dt^{2}}\\right) + \\left(\\frac{u{\\left(t,x,y \\right)}}{h_{x}^{2}} - \\frac{2.0 u{\\left(t,x + h_{x},y \\right)}}{h_{x}^{2}} + \\frac{u{\\left(t,x + 2 h_{x},y \\right)}}{h_{x}^{2}}\\right) + \\left(- \\frac{2.0 u{\\left(t,x + h_{x},y \\right)}}{h_{y}^{2}} + \\frac{u{\\left(t,x + h_{x},y - h_{y} \\right)}}{h_{y}^{2}} + \\frac{u{\\left(t,x + h_{x},y + h_{y} \\right)}}{h_{y}^{2}}\\right)}{h_{x}^{2}}$" ], "text/plain": [ "-2.0*(-2.0*v(t, x, y)/dt**2 + v(t - dt, x, y)/dt**2 + v(t + dt, x, y)/dt**2 - 2.0*u(t, x, y)/h_x**2 + u(t, x - h_x, y)/h_x**2 + u(t, x + h_x, y)/h_x**2 - 2.0*u(t, x, y)/h_y**2 + u(t, x, y - h_y)/h_y**2 + u(t, x, y + h_y)/h_y**2)/h_x**2 + (-2.0*v(t, x - h_x, y)/dt**2 + v(t - dt, x - h_x, y)/dt**2 + v(t + dt, x - h_x, y)/dt**2 + u(t, x, y)/h_x**2 + u(t, x - 2*h_x, y)/h_x**2 - 2.0*u(t, x - h_x, y)/h_x**2 - 2.0*u(t, x - h_x, y)/h_y**2 + u(t, x - h_x, y - h_y)/h_y**2 + u(t, x - h_x, y + h_y)/h_y**2)/h_x**2 + (-2.0*v(t, x + h_x, y)/dt**2 + v(t - dt, x + h_x, y)/dt**2 + v(t + dt, x + h_x, y)/dt**2 + u(t, x, y)/h_x**2 - 2.0*u(t, x + h_x, y)/h_x**2 + u(t, x + 2*h_x, y)/h_x**2 - 2.0*u(t, x + h_x, y)/h_y**2 + u(t, x + h_x, y - h_y)/h_y**2 + u(t, x + h_x, y + h_y)/h_y**2)/h_x**2" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(v.dt2 + u.laplace).dx2.evaluate" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.8" }, "widgets": { "state": {}, "version": "1.1.2" } }, "nbformat": 4, "nbformat_minor": 4 }