agent-singlependulum.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "195b2d98",
   "metadata": {},
   "source": [
    "## Expected Free Energy for single pendulum with nonlinear observations\n",
    "\n",
    "Wouter Kouw, last update: 20-11-2022\n",
    "\n",
    "### System\n",
    "\n",
    "Consider a damped [pendulum](https://en.wikipedia.org/wiki/Pendulum_(mechanics)) with angle $\\theta(t)$, driving force $u(t)$ and noise $w(t)$. The continuous-time dynamics of the system are:\n",
    "\n",
    "$$\\begin{align*}\n",
    "m l^2 \\ddot{\\theta} + c l \\dot{\\theta} + m \\mathcal{g} l \\sin \\theta = u \\, ,\n",
    "\\end{align*}$$\n",
    "where $m = \\text{mass}$, $l  = \\text{length}$, $c = \\text{friction}$, and $\\mathcal{g} = \\text{gravity}$. \n",
    "\n",
    "#### Multivariate first-order system\n",
    "\n",
    "With the variable substitution $z = [\\theta \\ \\dot{\\theta}]$, I cast the above system into a multi-variate first-order form:\n",
    "\n",
    "$$ \\begin{bmatrix} \\dot{\\theta} \\\\ \\ddot{\\theta} \\end{bmatrix} = \\begin{bmatrix} \\dot{\\theta} \\\\ -\\frac{\\mathcal{g}}{l} \\sin \\theta - \\frac{c}{ml} \\dot{\\theta} \\end{bmatrix} + \\begin{bmatrix} 0 \\\\ \\frac{1}{ml^2} \\end{bmatrix} u \\, .$$\n",
    "\n",
    "#### Discretization\n",
    "\n",
    "A forward Euler discretization for the state transition yields:\n",
    "\n",
    "$$\\begin{align*}\n",
    "z_k =&\\ \\underbrace{z_{k-1} + \\Delta t\\begin{bmatrix} z_{2,k-1} \\\\ -\\frac{\\mathcal{g}}{l} \\sin (z_{1,k-1}) - \\frac{c}{ml} z_{2,k-1} \\end{bmatrix} + \\begin{bmatrix} 0 \\\\ \\frac{\\Delta t}{ml^2} \\end{bmatrix} u_k}_{f(z_{k-1}, u_k)} \\, .\n",
    "\\end{align*}$$\n",
    "\n",
    "We have noisy observations genereated by a nonlinear observation function $g$, \n",
    "\n",
    "$$ y_k = g(z_k) + r_k \\quad \\text{where} \\quad r_k \\sim \\mathcal{N}(0, R) \\, .$$\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b615d750",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m\u001b[1m  Activating\u001b[22m\u001b[39m project at `~/syndr/Wouter/Onderzoek/Projecten/tue/efe-planning/ECC2023-efe4ukf`\n"
     ]
    }
   ],
   "source": [
    "# using Pkg\n",
    "# Pkg.activate(\".\")\n",
    "# Pkg.instantiate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "336ca769",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "UT (generic function with 1 method)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using Revise\n",
    "using Optim\n",
    "using ForwardDiff\n",
    "using Zygote\n",
    "using Printf\n",
    "using ProgressMeter\n",
    "using LinearAlgebra\n",
    "using ControlSystems\n",
    "using Distributions\n",
    "using Plots\n",
    "default(label=\"\", grid=false, linewidth=3, markersize=3, margin=10Plots.pt)\n",
    "include(\"util.jl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "id": "cc0ceae8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "g (generic function with 1 method)"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# System parameters\n",
    "mass = 2.0\n",
    "leng = 1.0\n",
    "fric = 4.0\n",
    "const gravity = 9.81\n",
    "\n",
    "# Temporal variables\n",
    "Δt = 0.1\n",
    "len_time = 100\n",
    "time = range(0, step=Δt, length=len_time)\n",
    "\n",
    "# Matrices\n",
    "f(z::AbstractVector, u::Real) = [z[1] + Δt*z[2]; z[2] + Δt*(-gravity/leng*sin(z[1])-fric/(mass*leng^2)*z[2]) + Δt/(mass*leng^2)*u]\n",
    "Fz(z::AbstractVector) = [1 Δt; -Δt*gravity/leng*cos(z[1]) 1-Δt*fric/(mass*leng^2)]\n",
    "\n",
    "# Measurement noise\n",
    "R = 1e-3;\n",
    "\n",
    "# Nonlinear observation\n",
    "g(z) = -leng*cos([1.0,0.0]'*z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "6cc39986",
   "metadata": {},
   "outputs": [],
   "source": [
    "function update(z_kmin1, u_k)\n",
    "   \"Update environment\" \n",
    "    \n",
    "    # State transition\n",
    "    z_k = f(z_kmin1, u_k)\n",
    "    \n",
    "    # Emit noisy observation\n",
    "    y_k = rand(Normal(g(z_k), sqrt(R)))\n",
    "    \n",
    "    return y_k, z_k\n",
    "end;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "id": "450a6ffc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Control for checking dynamics simulation\n",
    "cutpoint = 100\n",
    "# u = [10*sin.((1:cutpoint)./ 2π); zeros(len_time-cutpoint)];\n",
    "u = zeros(len_time);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "id": "e8389f03",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initial state\n",
    "z_0 = [π+randn(), 0.0]\n",
    "\n",
    "# Preallocate\n",
    "z = zeros(2,len_time)\n",
    "y = zeros(len_time)\n",
    "\n",
    "# Start recursion\n",
    "z_kmin1 = z_0\n",
    "for k in 1:len_time\n",
    "    \n",
    "    # Update system\n",
    "    y[k], z[:,k] = update(z_kmin1, u[k])\n",
    "    \n",
    "    # Update recursion\n",
    "    z_kmin1 = z[:,k]\n",
    "    \n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "9e6227e4-5bda-4422-a8dd-c38758275294",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: Saved animation to /home/wmkouw/syndr/Wouter/Onderzoek/Projecten/tue/efe-planning/ECC2023-efe4ukf/figures/1pendulum-sim.gif\n",
      "└ @ Plots /home/wmkouw/.julia/packages/Plots/m8l21/src/animation.jl:156\n"
     ]
    },
    {
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      ],
      "text/plain": [
       "Plots.AnimatedGif(\"/home/wmkouw/syndr/Wouter/Onderzoek/Projecten/tue/efe-planning/ECC2023-efe4ukf/figures/1pendulum-sim.gif\")"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "anim = @animate for (i,t) in enumerate(time)\n",
    "   \n",
    "    # Cartesian positions\n",
    "    px,py = polar2cart(z[:,i], l=leng)\n",
    "    pen_k = [0 0; px py]\n",
    "    \n",
    "    # Plot line\n",
    "    plot(pen_k[:,1], pen_k[:,2], label=@sprintf(\"t = %.1f\", t), alpha=0.5, xlims=[-1.5,1.5], ylims=[-1.5,1.5], aspect_ratio=:equal, color=\"black\")\n",
    "    \n",
    "    # Point masses\n",
    "    scatter!([pen_k[2,1]], [pen_k[2,2]], color=\"black\")\n",
    "    \n",
    "end\n",
    "gif(anim, \"figures/1pendulum-sim.gif\", fps=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "127f956a",
   "metadata": {},
   "outputs": [
    {
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      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p1 = plot(time, z[1,:], xlabel=\"time (s)\", label=\"angle\")\n",
    "scatter!(time, y, color=\"black\", label=\"observations\")\n",
    "p2 = plot(time, z[2,:], xlabel=\"time (s)\", label=\"change in angle\")\n",
    "p3 = plot(time, u, color=\"red\", xlabel=\"time (s)\", label=\"control\")\n",
    "plot(p1, p2, p3, layout=(3,1), size=(900,800))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1901b1f1-9fcc-4209-a5ed-d4b462f155f2",
   "metadata": {},
   "source": [
    "## Generative model\n",
    "\n",
    "We have a deterministic nonlinear state transition:\n",
    "$$\\begin{align}\n",
    "p(z_k \\mid z_{k-1}, u_k) = \\delta(z_k - (z_{k-1}, u_k))\n",
    "\\end{align}$$\n",
    "which, under an extended Kalman filter, gives a state prediction of the form:\n",
    "$$\\begin{align}\n",
    "p(z_k \\mid u_k) = \\mathcal{N}(z_k \\mid f(m_{k-1}, u_k), J_z S_{k-1} J_z')\n",
    "\\end{align}$$\n",
    "where $m_{k-1}$ and $S_{k-1}$ are the mean and covariance of the previous state $p(z_{k-1}$.\n",
    "\n",
    "I will use an unscented transform the approximate the joint distribution of the nonlinear observation function:\n",
    "\n",
    "$$\\begin{align}\n",
    "p(y_k, z_k) = \\mathcal{N}\\left(\\begin{bmatrix} y_k \\\\ z_k \\end{bmatrix} \\mid \\begin{bmatrix} m_{UT} \\\\ f(m_{k-1}, u_k) \\end{bmatrix}, \\begin{bmatrix} S_{UT} & C_{UT}^{\\top} \\\\ C_{UT} & J_z S_{k-1} J_z^{\\top} \\end{bmatrix} \\right) \\, .\n",
    "\\end{align}$$\n",
    "\n",
    "where $m_{UT}$, $S_{UT}$, $C_{UT}$ are the mean, variance and covariance produced by the unscented transform. This produces a likelihood of the form:\n",
    "\n",
    "$$\\begin{align}\n",
    "p(y_k \\mid z_k) = \\mathcal{N}\\big(y_k \\mid m_{UT} + C_{UT}(J_z S_{k-1} J_z^{\\top})^{-1}(z_k - f(m_{k-1}, u_k)), S_UT -  C_{UT}(J_z S_{k-1} J_z^{\\top})^{-1}C_{UT}(J_z S_{k-1} J_z^{\\top})^{-1} C_{UT}^{\\top} \\big) \\, .\n",
    "\\end{align}$$\n",
    "\n",
    "Note that due to the approximation, the likelihood variance depends on the state and the action. This will ensure that the ambiguity term in the EFE function is not constant."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "id": "6bb3000c-852d-4b73-9471-360499a8e100",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Preallocate\n",
    "z_est = (zeros(2,len_time), zeros(2,2,len_time))\n",
    "\n",
    "# Initial belief\n",
    "m_0 = zeros(2)\n",
    "S_0 = diagm(ones(2))\n",
    "\n",
    "# Start recursion\n",
    "m_kmin1 = m_0\n",
    "S_kmin1 = S_0\n",
    "\n",
    "for k in 1:len_time\n",
    "    \n",
    "    # Prediction step\n",
    "    # Jz,Ju    = Fz(m_kmin1, u[k])\n",
    "    Jz       = Fz(m_kmin1)\n",
    "    m_k_pred = f(m_kmin1, u[k])\n",
    "    S_k_pred = Jz*S_kmin1*Jz'\n",
    "    \n",
    "    # Regularize approximation\n",
    "    S_k_pred += 1e-8*diagm(ones(2))\n",
    "    \n",
    "    # Correction step\n",
    "    mU, SU, CU = UT(m_k_pred, S_k_pred, g, Q=R)\n",
    "    K_t = CU*inv(SU)\n",
    "    m_k = m_k_pred .+ K_t*(y[k] - mU)\n",
    "    S_k = S_k_pred .- K_t*SU*K_t'\n",
    "    \n",
    "    # Store state estimates\n",
    "    z_est[1][:,k]   = m_k\n",
    "    z_est[2][:,:,k] = S_k\n",
    "   \n",
    "    # Update recursion\n",
    "    m_kmin1 = m_k\n",
    "    S_kmin1 = S_k\n",
    "    \n",
    "end"
   ]
  },
  {
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   "execution_count": 187,
   "id": "d5c44b33-fbc9-446b-b3a7-29ddb88bc11d",
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       "</svg>\n"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p1 = plot(time, z[1,:], xlabel=\"time (s)\", ylabel=\"angle\")\n",
    "plot!(time, z_est[1][1,:], ribbon=sqrt.(z_est[2][1,1,:]), color=\"purple\")\n",
    "p2 = plot(time, z[2,:], xlabel=\"time (s)\", ylabel=\"change in angle\")\n",
    "plot!(time, z_est[1][2,:], ribbon=sqrt.(z_est[2][2,2,:]), color=\"purple\")\n",
    "plot(p1, p2, layout=(2,1), size=(900,500))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe99f22e",
   "metadata": {},
   "source": [
    "## Expected Free Energy\n",
    "\n",
    "From the agent's viewpoint, the evolution of these future variables are constrained by its generative model, rolled out into the future:\n",
    "$$\\begin{align}\n",
    "p(y,z,u) &= \\underbrace{q(z_{k})}_{\\substack{\\text{current}\\\\ \\text{state}}} \\cdot \\underbrace{\\prod_{t=k+1}^{k+T} p(y_t|z_t) \\cdot p(z_t | z_{t-1}, u_t) p(u_t)}_{\\text{generative model roll-out to future}} \\, ,\n",
    "\\end{align}$$\n",
    "\n",
    "where $y = (y_t, \\dots, y_T)$, $z = (z_{t-1}, \\dots, z_T)$ and $u = (u_t, \\dots, u_T)$. \n",
    "\n",
    "Consider the varational free energy functional for estimating posterior beliefs $q(z,u)$ over future states and control signals, with an expectation over future observations $q(y \\mid z)$: \n",
    "\n",
    "$$\\begin{align}\n",
    "H[q] &= \\overbrace{\\iint q(y \\mid z)}^{\\text{marginalize }y} \\bigg( \\overbrace{\\int q(z,u) \\log \\frac{q(z,u)}{p(y,z,u)} }^{\\text{variational free energy}}\\bigg) \\mathrm{d}u \\, \\mathrm{d}y \\, \\mathrm{d}z \\\\\n",
    "&= \\int q(y,z,u) \\log \\frac{q(z,u)}{p(y,z,u)} \\mathrm{d}u \\, \\mathrm{d}y \\, \\mathrm{d}z \\\\\n",
    "&= \\int q(y,z|u) q(u) \\log \\frac{q(z|u) q(u)}{p(y,z|u) p(u)} \\mathrm{d}u \\, \\mathrm{d}y \\, \\mathrm{d}z \\\\\n",
    "&= \\int q(u) \\bigg(\\sum_{y,z} q(y,z|u) \\log \\frac{q(z|u) q(u)}{p(y,z|u) p(u)}\\bigg) \\mathrm{d}u \\, \\mathrm{d}y \\, \\mathrm{d}z \\\\\n",
    "&= \\int q(u) \\bigg( \\log q(u) + \\log \\frac{1}{p(u)}+ \\underbrace{q(y,z|u) \\log \\frac{q(z|u)}{p(y,z|u)}}_{G(u)}\\bigg) \\mathrm{d}u \\, \\mathrm{d}y \\, \\mathrm{d}z \\\\\n",
    "&= \\int q(u) \\log \\frac{q(u)}{p(u)\\exp\\left(- G(u)\\right) } \\mathrm{d}u  \\, .\n",
    "\\end{align}$$\n",
    "\n",
    "We can recognize a KL-divergence between $q(u)$ and the function $p(u)\\exp\\left(- G(u)\\right)$, which will be minimal when $q(u) = p(u)\\exp\\left(- G(u)\\right)$. The $G$ function is known as the _Expected Free Energy_. Let's look at it in detail for a future observation $t$,\n",
    "\n",
    "$$ G(u_t) = \\iint q(y_t, z_t \\mid u_t) \\log \\frac{q(z_t \\mid u_t)}{p(y_t, z_t \\mid u_t)} \\mathrm{d}y_t \\, \\mathrm{d}z_t \\, ,$$\n",
    "\n",
    "where \n",
    "\n",
    "$$\\begin{align}\n",
    "% q(y_t \\mid z_t) &= \\mathcal{N}(y_t \\mid Cz_t, R) \\\\\n",
    "% q(z_t \\mid u_t) &= \\int p(z_t \\mid z_{t-1}, u_t) q(z_{t-1}) \\mathrm{d}z_{t-1} \\\\\n",
    "% &= \\mathcal{N}(z_t \\mid A m_{t-1} + Bu_t, AS_{t-1}A^{\\top} + Q) \\\\\n",
    "p(y_t, z_t \\mid u_t) &= \\int p(y_t \\mid z_t) p(z_t \\mid z_{t-1}, u_t) q(z_{t-1}) \\mathrm{d}z_{t-1} \\\\\n",
    "&= \\mathcal{N}(\\begin{bmatrix} y_t \\\\ z_t \\end{bmatrix} \\mid \\begin{bmatrix} C(A m_{t-1} + Bu_t) \\\\ A m_{t-1} + Bu_t \\end{bmatrix}, \\begin{bmatrix} C(AS_{t-1}A^{\\top} + Q) C^{\\top} + R & C(AS_{t-1}A^{\\top} + Q) \\\\ (AS_{t-1}A^{\\top} + Q)C^{\\top} & AS_{t-1}A^{\\top} + Q \\end{bmatrix}) \\, ,\n",
    "\\end{align}$$\n",
    "\n",
    "with the approximate posterior for the previous state $q(z_{t-1}) = \\mathcal{N}(z_{t-1} \\mid m_{t-1}, S_{t-1})$. The distribution $q(z_t \\mid u_t)$ is constructed from the state transition:\n",
    "\n",
    "$$q(z_t \\mid u_t) = \\int p(z_t \\mid z_{t-1}, u_t) q(z_{t-1}) \\mathrm{d}z_{t-1} = \\mathcal{N}(z_t \\mid A m_{t-1} + Bu_t, AS_{t-1}A^{\\top} + Q) \\, ,$$\n",
    "\n",
    "and $q(y_t, z_t \\mid u) = p(y_t \\mid z_t) q(z_t \\mid u_t)$ which is equivalent to $p(y_t, z_t \\mid u_t)$ in this case. Note that - during planning and in linear Gaussian models - we can drive the KL-divergence between the approximate posteriors $q$ and the true posteriors $p$ to 0, thus allowing us to swap $q$ for $p$.\n",
    "\n",
    "We will decompose this EFE function into ambiguity plus risk terms (see [lecture slides](https://nbviewer.org/github/bertdv/BMLIP/blob/master/lessons/notebooks/Intelligent-Agents-and-Active-Inference.ipynb) for more detail). To do so, we will decompose $p(y_t,z_t \\mid u_t)$ into $p^\\prime(y_t)p(z_t|y_t,u_t)$ where $p\\prime(y_t)$ is a distribution over the goal state, a.k.a. a _goal prior_; $p^\\prime(y) = \\mathcal{N}(y \\mid m_*, s_*)$. The derivation goes as follows:\n",
    "\n",
    "$$\\begin{align}\n",
    "G(u_t) &= \\int  q(y_t,z_t|u_t) \\log \\frac{q(z_t|u_t)}{p^\\prime(y_t)p(z_t|y_t,u_t)} \\, \\mathrm{d}y_t \\, \\mathrm{d}z_t \\\\\n",
    "&= \\int  q(y_t, z_t \\mid u_t) \\log \\frac{q(z_t \\mid u_t)}{p^\\prime(y_t)} \\frac{1}{p(z_t \\mid y_t, u_t)} \\, \\mathrm{d}y_t \\, \\mathrm{d}z_t \\\\\n",
    "&= \\int  q(y_t, z_t \\mid u_t) \\log \\frac{q(z_t \\mid u_t)}{p^\\prime(y_t)} \\frac{p(y_t \\mid u_t)}{p(y_t \\mid z_t)p(z_t \\mid u_t)} \\, \\mathrm{d}y_t \\, \\mathrm{d}z_t \\\\\n",
    "&= \\int  q(y_t,z_t|u_t) \\log \\frac{q(z_t|u_t)}{p(y_t|z_t)p(z_t|u_t)} \\frac{p(y_t|u_t)}{p^\\prime(y_t)} \\, \\mathrm{d}y_t \\, \\mathrm{d}z_t \\\\\n",
    "&= \\int  q(y_t,z_t|u_t) \\log \\frac{q(z_t|u_t)}{p(y_t|z_t)p(z_t|u_t)} \\, \\mathrm{d}z_t \\, \\mathrm{d}y_t + \\int q(y_t,z_t|u_t) \\log \\frac{p(y_t|u_t)}{p^\\prime(y_t)} \\, \\mathrm{d}y_t \\, \\mathrm{d}z_t \\\\\n",
    "&= \\int  p(z_t|u_t) p(y_t|z_t) \\log \\frac{1}{p(y_t|z_t)} \\, \\mathrm{d}z_t \\, \\mathrm{d}y_t + \\int p(z|u) p(y|z) \\log \\frac{p(y_t|u_t)}{p^\\prime(y_t)} \\, \\mathrm{d}z_t \\, \\mathrm{d}y_t \\\\\n",
    "&= \\underbrace{\\int  p(z_t|u_t) \\int p(y_t|z_t) \\log \\frac{1}{p(y_t|z_t)} \\, \\mathrm{d}z_t \\, \\mathrm{d}y_t}_{\\text{ambiguity}} + \\underbrace{\\int p(y_t|u_t) \\log \\frac{p(y_t|u_t)}{p^\\prime(y_t)} \\, \\mathrm{d}y_t}_{\\text{risk}} \\ \\, ,\n",
    "\\end{align}$$\n",
    "\n",
    "Ambiguity is an expectation over an entropy, which - in the case of a Gaussian likelihood - is actually independent of the state,\n",
    "\n",
    "$$\\int p(y_t|z_t) \\log p(y_t|z_t) \\mathrm{d}y_t = \\frac{1}{2}\\big(\\log 2\\pi |R| - 1\\big) \\, ,$$\n",
    "\n",
    "so the expectation over $p(z_t|u_t)$ doesn't even apply. As you may have noticed, the control $u_t$ doesn't affect ambiguity which means there is no information-seeking behaviour in linear Gaussian state-space models.\n",
    "\n",
    "The risk term is a KL-divergence between the Gaussian,\n",
    "\n",
    "$$\\begin{align}\n",
    "    p(y_t|u_t) &= \\int p(y_t, z_t \\mid u_t) \\, \\mathrm{d}z_t  \\\\\n",
    "    &= \\int \\mathcal{N}(\\begin{bmatrix} y_t \\\\ z_t \\end{bmatrix} \\mid \\begin{bmatrix} C(A m_{t-1} + Bu_t) \\\\ A m_{t-1} + Bu_t \\end{bmatrix}, \\begin{bmatrix} C(AS_{t-1}A^{\\top} + Q) C^{\\top} + R & C(AS_{t-1}A^{\\top} + Q) \\\\ (AS_{t-1}A^{\\top} + Q)C^{\\top} & AS_{t-1}A^{\\top} + Q \\end{bmatrix}) \\, \\mathrm{d}z_t \\\\\n",
    "    &= \\mathcal{N}(y_t \\mid C(A m_{t-1} + Bu_t) , C(AS_{t-1}A^{\\top} + Q) C^{\\top} + R) \\, ,\n",
    "    \\end{align}$$\n",
    "    \n",
    "and the goal prior $p^\\prime(y_t)$. The formula for the KL-divergence between two Gaussians is (see [wiki](https://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence#Multivariate_normal_distributions)):\n",
    "\n",
    "$$\\begin{align}\n",
    "D_{\\text{KL}}( \\mathcal{N}(x \\mid m_1, \\sigma_1) || \\mathcal{N}(x \\mid m_2, \\sigma_2) ) = \\frac{1}{2} \\Big[\\log\\frac{|\\Sigma_2|}{|\\Sigma_1|} - d + \\text{tr}(\\Sigma_2^{-1}\\Sigma_1) + (\\mu_2 - \\mu_1)^{\\top}\\Sigma_2^{-1}(\\mu_2 - \\mu_1) \\Big] \\, .\n",
    "\\end{align}$$\n",
    "\n",
    "For our distribution, this becomes:\n",
    "\n",
    "$$\\int p(y_t|u_t) \\log \\frac{p(y_t|u_t)}{p^\\prime(y_t)} \\, \\mathrm{d}y_t = \\frac{1}{2} \\Big[\\log\\frac{s_*}{|C(AS_{t-1}A^{\\top} + Q) C^{\\top} + R|} - 1 + \\text{tr}(\\frac{(C(AS_{t-1}A^{\\top} + Q) C^{\\top} + R)}{s_*}) + \\frac{\\big(m_* - (C(A m_{t-1} + Bu_t))\\big)^2}{s_*}) \\Big]$$\n",
    "\n",
    "\n",
    "The decomposition is the same for any future state $t$. We may thus unroll the policy as $G(u) = \\sum_{t=k+1}^{TT} G(u_t)$.\n",
    "\n",
    "---\n",
    "\n",
    "The above equations can be written down to form an objective function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "id": "c0c535a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EFE (generic function with 1 method)"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "function EFE(u::AbstractVector, \n",
    "             state::Tuple{AbstractVector, AbstractMatrix}, \n",
    "             goal::Tuple{Float64,Float64}; \n",
    "             time_horizon::Int64=1)\n",
    "    \"Expected Free Energy\"\n",
    "    \n",
    "    # Unpack goal state\n",
    "    m_star, S_star = goal\n",
    "    iS = inv(S_star)\n",
    "    \n",
    "    # Unpack parameters of current state\n",
    "    m_tmin1, S_tmin1 = state\n",
    "    \n",
    "    # Start cumulative sum\n",
    "    cEFE = 0.0\n",
    "    for t in 1:time_horizon\n",
    "        \n",
    "        # State transition p(z_t | u_t)\n",
    "        Jz  = Fz(m_tmin1)\n",
    "        m_t = f(m_tmin1, u[t])\n",
    "        S_t = Jz*S_tmin1*Jz' + 1e-8*diagm(ones(2))\n",
    "\n",
    "        # Unscented transform moments\n",
    "        mU, SU, CU = UT(m_t, S_t, g, Q=R, D=1)\n",
    "        \n",
    "        # E_q(z_t | u_t)[H[q(y_t | z_t)]]\n",
    "        # ambiguity = 0.5(log(2π) + log(SU) - 1)\n",
    "        ambiguity = 0.5(log(2π) + log(SU-CU'*inv(S_t)*CU) - 1)\n",
    "\n",
    "        # D_KL[p(y_t | u_t) || p'(y_t)]\n",
    "        risk = 0.5(log(det(S_star)/det(SU)) + 1 + (mU-m_star)'*iS*(mU-m_star) + tr(iS*SU))\n",
    "        \n",
    "        # Cumulate EFE\n",
    "        cEFE += ambiguity + risk\n",
    "        \n",
    "        # Update state recursion\n",
    "        m_tmin1 = m_t\n",
    "        S_tmin1 = S_t\n",
    "                \n",
    "    end\n",
    "    return cEFE\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae93a271",
   "metadata": {},
   "source": [
    "We can use the Optim.jl library to auto-differentiate EFE and minimize it every time step."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "id": "598f0c08",
   "metadata": {},
   "outputs": [],
   "source": [
    "len_trial = 40\n",
    "time = range(0, step=Δt, length=len_trial)\n",
    "\n",
    "# Time horizon\n",
    "len_horizon = 20;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "id": "d14620f5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32mProgress: 100%|█████████████████████████████████████████| Time: 0:20:11\u001b[39m\n"
     ]
    }
   ],
   "source": [
    "# Distribution around goal state\n",
    "goal_state = [3.14, 0.0]\n",
    "goal_obs   = (g(goal_state), 1e-5)\n",
    "\n",
    "# Limits of controller\n",
    "u_lims = (-18.0, 18.0)\n",
    "\n",
    "# Preallocate\n",
    "z_est = (zeros(2,len_trial), zeros(2,2,len_trial))\n",
    "z_sim = zeros(2,len_trial)\n",
    "y_sim = zeros(len_trial)\n",
    "u_sim = zeros(len_trial)\n",
    "\n",
    "# Initial state\n",
    "z_0 = [0.1, 0.0]\n",
    "z_sim[:,1] = z_0\n",
    "\n",
    "# Initial belief\n",
    "m_0 = z_0\n",
    "S_0 = diagm(ones(2))\n",
    "\n",
    "# Start recursion\n",
    "m_kmin1 = m_0\n",
    "S_kmin1 = S_0\n",
    "\n",
    "@showprogress for k in 2:len_trial\n",
    "    \n",
    "    \"Interact with environment\"\n",
    "    \n",
    "    # Update system with selected control\n",
    "    y_sim[k], z_sim[:,k] = update(z_sim[:,k-1], u_sim[k-1])\n",
    "   \n",
    "    \"State estimation\"\n",
    "    \n",
    "    # Prediction step\n",
    "    Jz       = Fz(m_kmin1)\n",
    "    m_k_pred = f(m_kmin1, u_sim[k-1])\n",
    "    S_k_pred = Jz*S_kmin1*Jz' + 1e-12*diagm(ones(2))\n",
    "    \n",
    "    # Correction step\n",
    "    mU, SU, CU = UT(m_k_pred, S_k_pred, g, Q=R)\n",
    "    K_t = CU*inv(SU)\n",
    "    m_k = m_k_pred .+ K_t*(y_sim[k] - mU)\n",
    "    S_k = S_k_pred .- K_t*SU*K_t'\n",
    "    \n",
    "    # Store state estimates\n",
    "    z_est[1][:,k] = m_k\n",
    "    z_est[2][:,:,k] = S_k\n",
    "    \n",
    "    \"Planning\"\n",
    "    \n",
    "    # Single-argument objective\n",
    "    G(u::AbstractVector) = EFE(u, (m_k,S_k), goal_obs, time_horizon=len_horizon)\n",
    "    \n",
    "    # Call minimizer using constrained L-BFGS procedure\n",
    "    results = Optim.optimize(G, u_lims[1], u_lims[2], zeros(len_horizon), Fminbox(LBFGS()); autodiff=:forward)\n",
    "    \n",
    "    # Extract minimizing control\n",
    "    u_sim[k] = Optim.minimizer(results)[1]\n",
    "   \n",
    "    # Update recursion\n",
    "    m_kmin1 = m_k\n",
    "    S_kmin1 = S_k\n",
    "    \n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "id": "249a7873-ebe1-4fd6-b44a-eb888a6450e9",
   "metadata": {},
   "outputs": [
    {
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      "┌ Info: Saved animation to /home/wmkouw/syndr/Wouter/Onderzoek/Projecten/tue/efe-planning/ECC2023-efe4ukf/figures/1pendulum-trial1.gif\n",
      "└ @ Plots /home/wmkouw/.julia/packages/Plots/m8l21/src/animation.jl:156\n"
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/>"
      ],
      "text/plain": [
       "Plots.AnimatedGif(\"/home/wmkouw/syndr/Wouter/Onderzoek/Projecten/tue/efe-planning/ECC2023-efe4ukf/figures/1pendulum-trial1.gif\")"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "anim = @animate for (i,t) in enumerate(time)\n",
    "   \n",
    "    # Cartesian positions\n",
    "    px,py = polar2cart(z_sim[:,i], l=leng)\n",
    "    qx,qy = polar2cart(z_est[1][:,i], l=leng)\n",
    "    gx,gy = polar2cart(goal_state, l=leng)\n",
    "    \n",
    "    # Concatenate\n",
    "    pen_k = [0 0; px py]\n",
    "    pnq_k = [0 0; qx qy]\n",
    "    goalp = [0 0; gx gy]\n",
    "    \n",
    "    # Plot line\n",
    "    plot(pen_k[:,1], pen_k[:,2], label=@sprintf(\"t = %.1f\", t), alpha=0.5, xlims=[-1.5,1.5], ylims=[-1.5,1.5], aspect_ratio=:equal, color=\"black\")\n",
    "    plot!(pnq_k[:,1], pnq_k[:,2], color=\"purple\")\n",
    "    \n",
    "    # Point masses\n",
    "    scatter!([pen_k[2,1]], [pen_k[2,2]], color=\"black\", alpha=0.5)\n",
    "    scatter!([pnq_k[2,1]], [pnq_k[2,2]], color=\"purple\")\n",
    "    scatter!([goalp[2,1]], [goalp[2,2]], color=\"green\")\n",
    "    \n",
    "end\n",
    "gif(anim, \"figures/1pendulum-trial1.gif\", fps=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "id": "454c11de",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<defs>\n",
       "  <clipPath id=\"clip020\">\n",
       "    <rect x=\"0\" y=\"0\" width=\"3600\" height=\"2400\"/>\n",
       "  </clipPath>\n",
       "</defs>\n",
       "<path clip-path=\"url(#clip020)\" d=\"\n",
       "M0 2400 L3600 2400 L3600 0 L0 0  Z\n",
       "  \" fill=\"#ffffff\" fill-rule=\"evenodd\" fill-opacity=\"1\"/>\n",
       "<defs>\n",
       "  <clipPath id=\"clip021\">\n",
       "    <rect x=\"720\" y=\"0\" width=\"2521\" height=\"2400\"/>\n",
       "  </clipPath>\n",
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       "    <rect x=\"309\" y=\"87\" width=\"3205\" height=\"553\"/>\n",
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       "  \n",
       "  \"/>\n",
       "</svg>\n"
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p301 = scatter(time, y_sim, ylabel=\"observations\", color=\"black\")\n",
    "plot!(time, goal_obs[1]*ones(len_trial), color=\"green\", linestyle=:dash, label=\"goal obs\")\n",
    "p302 = plot(time, z_sim[1,:], ylabel=\"angle\", label=\"true\", color=\"blue\")\n",
    "plot!(time, z_est[1][1,:], ribbon=sqrt.(z_est[2][1,1,:]), label=\"inferred\", color=\"purple\")\n",
    "plot!(time, goal_state[1]*ones(len_trial), color=\"green\", linestyle=:dash, label=\"setpoint\")\n",
    "plot!(time, -goal_state[1]*ones(len_trial), color=\"green\", linestyle=:dash, label=\"\")\n",
    "p303 = plot(time, u_sim, color=\"red\", ylabel=\"Control\")\n",
    "plot(p301, p302, p303, layout=(3,1), size=(900,600))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "id": "d7e8ed3a-4d26-4495-b801-20928840d9c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"/home/wmkouw/syndr/Wouter/Onderzoek/Projecten/tue/efe-planning/ECC2023-efe4ukf/figures/1pendulum-trial1-timeplots.png\""
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "savefig(\"figures/1pendulum-trial1-timeplots.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0adbc45b",
   "metadata": {},
   "source": [
    "### Trajectory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "a13988c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "len_trial = 20\n",
    "time = range(0, step=Δt, length=len_trial)\n",
    "\n",
    "# Time horizon\n",
    "len_horizon = 10;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "fa758a37",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "planned_trajectory (generic function with 1 method)"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "function planned_trajectory(policy, current_state)\n",
    "    \"Generate future states and observations\"\n",
    "    \n",
    "    # Extract time horizon\n",
    "    time_horizon = length(policy)\n",
    "    \n",
    "    # Unpack parameters of current state\n",
    "    m_tmin1, S_tmin1 = current_state\n",
    "    \n",
    "    # Track predicted observations\n",
    "    z_m = zeros(2,time_horizon)\n",
    "    z_S = zeros(2,2,time_horizon)\n",
    "    y_m = zeros(time_horizon)\n",
    "    y_v = zeros(time_horizon)\n",
    "    \n",
    "    for t in 1:time_horizon\n",
    "        \n",
    "        # Prediction step\n",
    "        Jz         = Fz(m_tmin1)\n",
    "        z_m[:,t]   = f(m_tmin1, policy[t])\n",
    "        z_S[:,:,t] = Jz*S_tmin1*Jz' + 1e-8*diagm(ones(2))\n",
    "        \n",
    "        # Predicted observations\n",
    "        y_m[t],y_v[t],_ = UT(z_m[:,t],z_S[:,:,t],g, Q=R)\n",
    "        \n",
    "        # Update previous state\n",
    "        m_tmin1 = z_m[:,t]\n",
    "        S_tmin1 = z_S[:,:,t]\n",
    "        \n",
    "    end\n",
    "    return z_m, z_S, y_m, y_v\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "77f3bd7e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32mProgress: 100%|█████████████████████████████████████████| Time: 0:00:23\u001b[39m\n"
     ]
    }
   ],
   "source": [
    "# Distribution around goal state\n",
    "goal_state = (3.14, 1e-5)\n",
    "\n",
    "# Limits of controller\n",
    "u_lims = (-10.0, 10.0)\n",
    "\n",
    "# Preallocate\n",
    "z_est = (zeros(2,len_trial), zeros(2,2,len_trial))\n",
    "z_pln = (zeros(len_trial, 2,len_horizon), zeros(len_trial, 2,2,len_horizon))\n",
    "y_pln = (zeros(len_trial, len_horizon), zeros(len_trial,len_horizon))\n",
    "z_sim = zeros(2,len_trial)\n",
    "y_sim = zeros(len_trial)\n",
    "u_sim = zeros(len_trial)\n",
    "\n",
    "# Initial belief\n",
    "m_0 = ones(2)\n",
    "S_0 = 3.0*diagm(ones(2))\n",
    "\n",
    "# Start recursion\n",
    "m_kmin1 = m_0\n",
    "S_kmin1 = S_0\n",
    "z_kmin1 = [0.,0.]\n",
    "\n",
    "@showprogress for k in 2:len_trial\n",
    "    \n",
    "    \"Interact with environment\"\n",
    "    \n",
    "    # Update system with selected control\n",
    "    y_sim[k], z_sim[:,k] = update(z_sim[:,k-1], u_sim[k-1])\n",
    "   \n",
    "    \"State estimation\"\n",
    "    \n",
    "    # Prediction step\n",
    "    Jz       = Fz(m_kmin1)\n",
    "    m_k_pred = f(m_kmin1, u_sim[k-1])\n",
    "    S_k_pred = Jz*S_kmin1*Jz' + 1e-8*diagm(ones(2))\n",
    "\n",
    "    # Correction step\n",
    "    mU, SU, CU = UT(m_k_pred, S_k_pred, g, Q=R)\n",
    "    K_t = CU*inv(SU)\n",
    "    m_k = m_k_pred .+ K_t*(y_sim[k] - mU)\n",
    "    S_k = S_k_pred .- K_t*SU*K_t'\n",
    "    \n",
    "    # Store state estimates\n",
    "    z_est[1][:,k] = m_k\n",
    "    z_est[2][:,:,k] = S_k\n",
    "    \n",
    "    \"Planning\"\n",
    "    \n",
    "    # Single-argument objective\n",
    "    G(u_t::AbstractVector) = EFE(u_t, (m_k, S_k), goal_state, time_horizon=len_horizon)\n",
    "    \n",
    "    # Call minimizer using constrained L-BFGS procedure\n",
    "    results = Optim.optimize(G, u_lims[1], u_lims[2], zeros(len_horizon), Fminbox(LBFGS()); autodiff=:forward)\n",
    "    policy = Optim.minimizer(results)\n",
    "    \n",
    "    # Planning\n",
    "    z_pln[1][k,:,:], z_pln[2][k,:,:,:], y_pln[1][k,:], y_pln[2][k,:] = planned_trajectory(policy, (m_k,S_k))\n",
    "    \n",
    "    # Execute first planned action only\n",
    "    u_sim[k] = policy[1]\n",
    "   \n",
    "    # Update recursion\n",
    "    m_kmin1 = m_k\n",
    "    S_kmin1 = S_k\n",
    "    \n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "326b1f1b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: Saved animation to /home/wmkouw/syndr/Wouter/Onderzoek/Projecten/tue/efe-planning/ECC2023-efe4ukf/figures/planning.gif\n",
      "└ @ Plots /home/wmkouw/.julia/packages/Plots/m8l21/src/animation.jl:156\n"
     ]
    },
    {
     "data": {
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DWFkQAzR0AICVCSJBfDiD2EVyDCGUYFI+aMHMp1CA66ZAUVhgKMgxC0i/OGGF2iQ55VMZ8pPCYD9xsIAtYhkuhFyb7bkGyX7FmamZAKNKWndUhAmODeSsYyFiR01ZHfIHc4e6kFrBBcAAOEZYK4FVQvkAZUgBQJ48AdrpYIA21QDD9w3BSAMhNwRRUAGbaEFGYigAVtr/OMNvU6BiMIA0SC6/wYfkAm+n8ANAzZI59fy+ZOEXvQtZMnmAH56IqFDxpT1Rjk27fpOa+QTtPdnCxBxD+EKBNBubiAC/rBSAyEBjOAPpdAFGbAAnuAJBpB8avAH/jAFT6BBkaQKT7Ba/iACS5AJpPACXsB4jicQkFcBgyAQqnCAlSABDUgbuqAGL2AALwV1g8NT9dci9dISzfWDclJllpVlKvN6pxF7DoEBAbgEHRENXSIQPACFWsBWrmAA6XcDWtALCJAbq9aBA1EDXcBFAqGFtyUBKWgHKTAQkCcDyOYPdEAmM1iDBOEGHMB5UYdLU6c/ROgivaQSDfaHaSJnqmdnM+N/GlEJBHB2D/+gIh2hBg9ABkvQACCiBREQA2qQAasVZm5ABg3gJW7wAF2gBktAYhz4SINgAJzkDyXwAm6wAmroD8L3Uf4AeZywAFPgBQsQKXUoEBKACSdIBiIiV+q3h/fUhylEiC0CDzj1EcLQD/yAD53CjGhiaZimaU6jhKbBhA4xCKAWalEEEpWgBWpAXJlQCYgwBXZAHbPgBlXQBZ0wEJ4gBlUQByqCCYmmd2qwj7pABlNQCZIQP7QYB4aGCKQgEKkgBl1AkLHQcQJBB7MgDHygBVXwgnrYg91ijT+VEdCgH/hQD/MQD89getYYJ7pmWb1mNdxYGt7oELXQBScwc/a1VW2xfk//MQt2dRHtZxLvF1ge5hDD0Cf6cA/0QJKkcpKnMnAzdnBj05Kk8ZKHgZNMMQsZ0ACuZRB1gABc+YWS4oPWGA+68pH7EJIjWZL0p5SXwnVeB3ZpA5WjIZWGQZVLYQQ15woLsI8CEQcw9xA9WRI/6VykUj5q+WDkoHqstzdwKRpymRMZOBJ2gGR3hYxUEQ1p1EpGUBB8aZMJ8ZckEZiFGZpxcn/WpX/8VzeLGRqNiRNAYFsiUQVQOJlfwR64IBBm4D4EEQcGYAAe1W67IgGkEJyksJOyJprGiS5VdmVIaDipCRqr+RLCkArCIAnlJxCtKRCzEAmVkG6lEH6V0G6zkAux/4AIIDIQsRAJ9eYPrqAIrgCb9USZU9FwdiUiBaEKqvQJEmCMCcGIEdCfEiCZTXacAvorhlhnd9Y4zfkZxFN679CgDvqgEBqhEjqhFDqhZWMQooAAJVADFvACGHKdmFABN7ACEZA9BigDLwB0AmEEL5ABrIII1EEGD3ADFnBq/sAHC3ADQBebJQSfUjFPxIVOnMl4I7IQnjkSoDmgSgoj2Dhd2ng5CeoZxLMOE1alVnqlEnahBCEKAKCBvVAB8XWdvqkFq+UKXXpbZmgEGZBBagBzn9AAKiIMFfCdDbB4vRABPFpcPioVD6CB/iAD14EQYpCHRqqMc7SkiDonKclr6v+AOlHaGcSjDleGpZRaqdelpQMhCgSgQU8AhWJqBi8gAhbQhgbYbhwQKUYQqOCkBhUQUhhABhk6EEqQpwQGFl5gAZnAcsmhChiQC6E0CJ0QBwiwg7tiqLqUqMh6JkxZcE7pqIrIJ+9AVNI6rdRardZ6rdh6reyAqZnqTQIxBad2nV1QAprwjnlogAMhAvFlBCblD/HkD2KQARTzCZ6wAAMhXu8JFsOgBRlQAq3mCjEASmogAhoXX1+5kcmasDcCXZb1dacyDyKJlo7zrEDBpbnBAUt0nZooEENwrgSQruvaru8qCQ1AahuUNOpEqzmlkYWjsC4rIxBmWYl5KgtGEBT/sg9RAijQkyaPyhnP6RLfxwFdwKGTdJ1qEAFi0ANapJ4fKxDquigiy0lFUFtaoAKVMAxeoIYvUAEqaz97ymjGmk8vO7Yugg6TlX/75yvv8IwHcbP4cJTPQDVD0rOb8bMtIQoLEAvEeE3wJhCI0AV/oAqRsEEcBU8gkgleMwsYeUpkgGh7wgheIAmeQJA9yrKWQ7YuuwzicIRa5itXZxFDyQ/6ALdT8k90qxl2yxJ4KxV0eRZHKhJJirkBl3qVlQzpkCxQ9hFEKZKA8g7scLqZkborkQoKGBWtaxavGxKxK7uUZralmbbIEpQoIS4UOxnHWxbJCxLLy7wvprmcSy/A/1u9knG9ZJG9H7G93BtYtEtZtvstzQMwIyG8fkG+Y2G+HoG+6QtQzou2p5ksLAa/IiG/fUG/YmG/HYG/+QtD3ltZy+ktzgjA8VtkxfO1+Ba2e5XAJ7m+q3e76OI/EBy/JfAEIjzCJFzCJnzCKJzCKrzCLNzCLvzCMBzDC0DBnmfByYXBzLi/3GCa6hJpHywSmBBSQjzERFzERnzESJzESrzETNzETvzEQiwGxLlTCIvDp8ewDNy56cKtP9zF2GvDKdY5zTBYTZVYjjVZ4FAOjWrFchKztcvB6hKEXjzH5QvGajY2Y5wOh8VY4KB63IBd2ZUM5aDFbEwk5nC2O1wO/P+yI3TcyAVsx47GL+xwVE1VDuQwDpB1ZZNaqdglDubgloW8sF3HwKA8L7nryKjcFQbMEQgMI82wVOZgxsmAyJbKDd+QDOKQWE6VDuoAdulwmNc1DuhQyqH8Im7MvnCsL/CQysysypCsb8giZ9+gWYB8pbcsDuMAVejAy8Q8I+yQDuPgxzsszP0bymZbWTzML3bUzOyMFau8Ea3cDjG2yZblDeCAzThmDumwDM1QzmjSDOZgZZf1DeTQeoWMxZTVwPzyvu3c0FTxzhqBwOkQXbWry+bgY93sK+tgDhRtWWm8xvl7zBvcMDXr0CYNFRCdEeirDuPg0c1aMOpQDh1du4P/zL3nzL8N88AnvdNOkdIYsbwanM4xE9P4J7PlkNGJCl3KScgF48E8/dRL4dMXkaRydmlOytROswzkgMjU5clIfZypZ13tGzP2ANVmnRRSbRGgeX+qt5J8883AXM/C/NVqqcNC3TBcfNZ6DRRpXRE/OdGAPNaXA9ACbVkEncxK2QzoQA5FjWVYvTByvNeS/RN9TRGhx9IuDTwbPdOUlcYGTYjLUA6be1mCLTOMPNmo3ROVPRGPFtTQqzzrINPSJciPDWcbPQ603JT+3DD/m9q+nROrLREqxg6HjFnkUNvBQ9TSBQ7kgA67LVTfLNvS1Q2CnA7PzTAd+dvabRPBHRHK/0WajKpHv3y21PXH4qDGgRXahX1ZzD3MdePU2x3fM9HdEKFPSv3G0I0OuG1Z2AUO4/DJK3Tb0yxd3/Df65CWKsM78r3gMUHfD0FH6zAOVwYO5nDdehTayeDH/d3cFn450T3K11XdHV41Jc3gJr4SDu4Q+9MM5XBl+kfXQqXYjI1p2EXd6I06MS3h2eXf7u05gXjiQJ4SKd4Q3xNj33t6Ar7jBs43Mn5pm+wNnvzZqPO5QV7lJjHkDEE3TUpZ4iDlRIjh2tXeI64uH07Pq1cO1q08bWblbD4SWL4QKeO9Yn2gainjA/7H2AXl5gDS8zLJMS0O4tzZzQ3jnZPXbX7oG//x5gohL4vKrGP+h7cd6Nzg3+aA3Gji50n1VIrlWPhXzfkX5fwT2Yh+6H9rB/UjCmKgBrV5sC3L4i5+1Mj64dol4jeC6ZVsyYwFWdnl6YGM5o/uOgw96oeOiVqAASxFEKj0BDUQAd3Wmc8MesRNy8c9tuug342Nzv/NVJpODpye27xOqd0ADsnQ3JYuPb0t7GzOC27lD7ZgAKSAVSvgmmPF6hHBBzKgA3oZEu8w0+KA2GSb42Y+3QGfXfaMyzZWDrvsY+XOP9mN7myuCA2QrktEEAZAkGLQl8U6EbP3ZwRAudB4CkWNiDgM15ytXQWPz9qMDhjtz78uQPDt8GweBxj/MBDWsUAAMGgyzxCZsAAkHCsNsUaANk4hcQPIUPTIUOHF3A4bze0btmO8vA4tj2sKDvNtnvMCUQNxKBBAupczvxCZ0ABC/FYNEQOhlvUeMU8wgAyWIAULj8MIToiGTvUnvggR31ITPxAGIPaxRO8PMQiAZgDp2RG10IgNIAVSwOdJj6hrK/eH7oW0cXnJYQvx9gLIFg0YO6QD0WiSUARLQMMRcQIEAANS8AZvn/gnSeWMz+ZiIFsVUAQhMimYgABIsAIVYLIIoegHoQtPcASnsApRb/p/eMqpz+aVcAaLqwpeAoNqEAe2f/vPbhLD8GbAj6jSO/zW75fPXxLREM/T/y9U63z94M/3N7H93b+kwR7+6H8QuI8Q3F/+ejQPBJj+w7/+B9H+7r9P8p//BkH/BmH/ANFO4ECCBQ0eRJhQ4UKGDR0+hBhR4kSKFRW66+dP40aOHT1+BBlS5EiSJU2eRJlS5UqWLV2+hBlT5kyaNW3exCnzU4WcNOtZBBpU6FCiRY0eRerQXk+mTZ0+hRpV6lSqVa1eZboTq8mfSb1+BRtW7Nikz7aeRZtW7Vq2bd2+vakVrsauZO3exZtX79B30Ob+BRxY8GDChd3KnVt372LGjR2T3WdY8mTKlS1fNowYruLHnT1/Bs2QHmbSpU2fRp16pea3nEO/hh1b77Nhqv9t38adW/db1m5dywYeXDhfv7uNH0eeXHnL3m1/D4ceXTpCd/yWX8eeXXvu5myfTwcfPvi97eXNn0cPuPva7+Ldv38cL/18+vXtO12vtj18/v3JwivuPgEHJLBAkfJLaz//FmSwKIwMhDBCCelDEC0FGxwKnmfcwVA8fSYEMUQRkavwrAs7pOideKzzhx94UJRunhFnpLFG0krc6kQYHXLnGX1q42gYejjcETh4bEQySSX/whErHYtMCB57AvyoH3iIhBK0vpbksksvq2ryqiezHOideTIy6R53sCTTsci+hDNOOWkK06oxoVTxzZSgeabNx0abM1BBBy2pzqruRLH/R3yEeUmfd/xczCxCJ6V0UkOpQrRBKal8CZp4IM1ry0pHJfXLS6fKtD8z0bRpn0dBHau6UmelFclTpUrVvTybGmYeNmFNirxahyV2wlujynW6Hu/hlCkXgfVKvmKnpVbAY6FKFjp46Gn2KSF/hTYoeBittlxzzbv2qWyBW/UsK8ENd6IHz6W3XuXSdWrd19yJ58e11IQ33oc+tLdgg3HDtyl9P4Nn0bf4FJgiGQ+muOLSEmZq4cfeYfEvRyOG6EiLRyZZMox70rgxAAfzFOSGRC05ZpnhOjmnlBeTtjBXXVZIz5l/BpolYZ6QIIM/PEJEBKVFEIWkmnG6OS93hJWs/9eAQQY0aK23LqkLDEj5AwFSouEojgwQQVsXp3n6K+q7OL7sWZ4HkpRru+/u6IFBNLphio7iWAGlp29y+79uqx5ybpjxZnxrXQCIRSMxXiB7ozgayOAFPgplOzHxci7tXZDnbbx0izn5I3XVJfGHFAB60ciNDDrCxA5M3EAgDpIqIQAB3xFQwzfw3MHHNoAFptp05Q1W4wXnn1/CH1sAqEUjMgIHyQsRKg9pJ1twAZ9c76aD+zaIwwV9efVHjgYB1v0pQomQZOcepMFtKtyrZ6ABErePYYVH/9Y3wIot4QXDKMUCMOGPWSyBF/6QhNpIUYEqrA0w+UNKPASYm5ZBiv90BAShwXKhAt95QSOpaAAu/KEEA/huCbAbyf1qgkEHFU85OyOTOwgWQh4arBcb5MgDTSJDnwinfMuxWpYm1kMmKo+IM6GhUPa3HSsVSWRNxGLjniiTKAJFg+b5FooWl0Uybm2LMekiRYg3n370qUHu8FkZ5Qi0M8IkjRI54nzw8Sr/ZG2Of5xZHV9yR4hM8T4d5E/dALnIkgnSJYR0yBIH5KirDWeMjMTkwRzZEkguRIcRSmJ4PphJUhZskyzpZELewaoIyW06yStlLOl1ypWk8iCGBFEYo5M+WfayWrRUiS0LIkkRtVFbQPRlMocFzJQIUyCftNEw9hicUSrTmrT/YiZKnAkPVtrofLCB5jXFic3ObSZSh6vR/0JDzHG2k1LZPIkt2bkkaMwjNFd0Zz4tVc7WSG2HcXKlYy6pT4LGCZ5cwQs3ByWkxrgDHisqaEQDddCSEBKXgxIdWRwaj3rwA5kSBSmXKEqSO85zUMdLykY7+tGQtlSk/BSeWOBIq28KpUfzwEc/WOpSnr70gmPx46zUKZEexSOnPUUqoUY6kijis1b1fMg74IHTbibVqnNaqkho6A7+USugBJEqVXd6VbJ6KashoaENqxXGdzyDHvqoalnlOlGYOgcsiixXP9A5V77K6awgyd9A+zpYwm7lrx/JXxwLu1jGTuWwHimc/0kbO1nKxqWu40NKACu7Wc7a5LEdiVo1Ozta0grusuxBSj1Ku1rWDvG0+jkKbVo7W9p25LMcSdkqa7tb2t52Iyn7J2+FO1rf0qUovBxucvUpjFQI0SPCqIQmXPtTvoxVudf15QoMAAA6fEQVD+CABFYgvu69NkFDkRV21dtOScQCA931yA9+4I9eVMAOFmzbUIK6Xv4q870fQUAlNKKFGODXc+Kybn8VvMj/doQXAFCFRsxGEk88wA4XtkOE7QoU0S7Yw0w0wvOe5waONJgjswDALDRSBwvsDgExgHEMNrdhi8DywzfuISNUp7pPlBi+QSJA0/xxhhQY2JwWwSuOlf/8RxNzJAPB84cMKhhD81rIIoJdcpZ7aIcuNKAGXYgw/fyhhwXEoQsI0PCBqmwiiyhWy2/moRueMOcnkMIfmDDDRv6gAyN4gnPUnYhk4TxoZRbXH5kaF6EV3U5DI6rDi4Z0KRs9EdVG2tK+nHREZHtpTkt6zTmKCFc7PepMZnpgpEb1Ik3dEOSm2tVMXPVCsPxqWg8w1j2rda5h/WknOWS/ugb28m59EM0G29jqG3ZBHn1sZpuR12JiiI2bPW1nAxohm6Z2tqudX1XuVdvftliyBRJccJebZOKeR4LNvW5zJfsd6mZ3vKc17PTK296mfLadDvLre/ebWrd2qr8FPu//fB+qILodeMIJbu12qFXhDyentZMMcYq/s+CYKhN5K75xpV4cVQNxM8dFblCP40oggh55ypc06WKr3OWmKjmylv1yms+o0Uupec6VZOiO6dznNDL0z4UO9JgP3ejtLvrRlV6sW3kizQQkhZBB6ArphlAXAi6sK/jgBUTUTyOe6ELYu+AKI6dECWfgoRb8FkI38ICHg8AeYY3AgQoY4SNxkIAXwk52Krfk7GlfOwjbzsM/xL2wS7C7RwBnWr+jPYRqj7PbQ1j4xiL+7hV4ghdS8WeW/P3xgSfg4Cdv+J72whanR73aNmJ5jwxiCWLQQYBJwggCPKABDXhABmQQY973/z7GEsCA74U/fOIX3/jHR37ylb985jff+c+PgQUqAH3qV9/618d+9rWPgQho3/vfB3/4xY98DjRg/OdHf/rVL4a/LKEBC1jA+xdQAo6wPiQG9LpHetGDJfR/CWq4AwwTwAHEMDVwAwJEwARUwAVkwAZ0wAeEwAiUwAmkwAq0AzdQAwvUwA3kwA70wA8EQQwEwREkwRI0wRN0wDggAxRkwRZ0wRf0s8qwP5CIAwzIv6XDQWKxP16wA2GIBhXzB2FYgR7IwSIsFjWIAN+JADJonRTzBxWwABV4AAyIHCO0wlnJBVLQQlJQIWEohdoQBkxAhE+4wSs0wzNEwzRUwzVkw/82dMM3hMOoEAYkQIAG6AICUgQdsAAkAKFB4IA6LAIYUp9IsAADWAAZqEJIIwMMsAVSaABEGKA8IAMdiIEybJw4+ANdSAUMeAJLvBtSyIReiIUVsAFLswDd8YcpqAEQIjAmMgMOiLMM8MQlM4BOWDEMYMUC66EVeAIC6gVEcAMLuC9I6wUA2Dx/GIQHyMUeMoMIUL31cYUY4AALWKBIMwBO0Ag6wEUCakW2ewA7i7MIsDQMiAOymYJS5EZdJCA7aIAe66FOIAB487AzsIBY+IQGWIQBmgVMQAIRwISnUx49MIA4wARMiEH1+QNO0AVReAHSI7RhcL8HYMIB4gMMsEj/DLjD9amCi8SAFxigYESACDCC6onDkjTJk0TJlFTJlWTJlnTJl4TJmJTJmaTJmrTJm8TJnNTJneTJnvTJnwTKoBTKoSTKojTKo0TKpFTKpWTKpnTKp4TKqJTKqaTKqrTKq8TKrNTKreTKrvTKrwTLsBTLsSTLsjTLs0TLtFTLtWTLtnTLt4TLuJTLuaTLurTLu8TLvNTLveTLvvTLvwTMwBTMwSTM7YgFRqgEQSxMozwzEcCAB3DHxSxKToAhHlBHyTxKMRABzERKXpAAEhsJYfACASwFzpxJYXiBSiQJTHixGDualtgESriE2aTN2pxNWYAHqdLN3OTN3fTN3gRO/9/8ItOctmGQgfGaRX9IGF9whOZ0zud0TkiQhUoSl7gizlobhhsoAcVUM5l4BUiAzvBsTlkIi3cIuet0tSkggCWYMxPqu5gIBfEUT/IMC3fgN/REtUEQuy6Asu6MiUuQz/CkT7GIB43Dz2/Dl18IUAG1C4U60HLDl1dYUOgc0LFAuAfVNnyJzwl1zgq10J7DUMKQhAX4nRI10RNF0RRV0RVl0RZ10ReFURRtAL4juv/k0A6VmvMMUbiogxcAnx8F0iAV0iEl0iI10iNF0iRV0iUNUgmITJtLOgW90fHUi3Da0cCoAxmokQp40hFJFwmdUkfwULuw0iudiyzd0i4Vkf902dApHVMylTYzZQs0pREutZF0AdAwfdO7qDQ5fQs6nRE7rZFrkVI9dQyU89OrANQREdQadQkwNdRDlcdEfYpFFZFGhdKXaFM37YzhpFS0sNQQwVQvLbo8jdTHwLZPxYpQHYxcmEi0GNU1jblCPVVU9TZVdQpWFQxSQAC1iNUQORZIrdXHWBlctQpdDQwgMIAfAIJa4AM66AIOyAQyqMZKcLwGSoEhAEiZ+FUQOZZN5VTQKFZjnYpQvQUKUIB0Vdd1Zdd2ddd3hdd3ZYBG+IhBQICCFIYpQAAvwARXUAH4WrxekIAu8AQ1eADujIluNZaYM9Vh7QwHJdeosNRoWAP/AbDYi8XYjNXYjeXYjvXYHIgGr+PVjZgCFdiIf5WwwHEDk9UIEXhNmlBYCbkVWnXYzrjQiM1VLeWIaBgFBvDYnwXaoN3YA2iEYQhZjhhZjZiCJagclPWHxZuCBbjICijHmojZCLkVYa3Zx3CHm8XZntDVWxDbsSXbsjXbs0XbtEXbYTBaryuFXlXa6NGIFwDN6/EHMvDInrhaCLkVcA1X2Mijr8UJZE2LkL1BXgiyuCXZA4oFCwgcVUCAvbkzIIRZNQXWkmvYrfWMmRLcnCBcwDAD7lMFMdCCjZiFP8RIIvSHSsiA9xOBbYWJvTWQU6FZzd1ccutcmfhcA5HdAjkV/6213c11OFfrh3kAUWXa3QLpXQI5Fb/92+DoU1KDhnp4kXbAXV9KXgJZ3gE5lcwNXtBA1DcbBn3YEIK43l7KXsHABXDMCV2wXH/YXmu5uNr9XvCd1AXjh3jgI/Ntp/QNjMXrCUTYRo+I3/u4FOCtX9BotSXrB3rYX4M4X1nyX8AA4JwQYJAoYPu4FOd9Xujw1CWDhnu4EoaI4Fia4LXoAbjjADcgGwCeAg7IgCVQvSUYhBjIgC4gG0nogjPIHHcUBi3ggBSYsWjoggyIATUY4I7I4Pq4FO9N4NBIVQ8b3/J1iBIupVDdB3HoBm7g4i724i8G4zAW4zEOY3CYpwXIAP9OwIQIuC8AVgNRSAUe0AGNKJpKwAS9iYY4MIAuEIUp2MYbuAFSqIQIYB0xwIBPqATgw+D3XViVoN8nhuJbHa78feCGsGJSClV4IONN5uROHmN0+IgFmDE1KDIAjoZOQITLIRsJyAONWAK/iYMW8wfE7QVXMAAYOgMirADJNeRFvtOCQ2BIvidJpq0GfgfqTIhLziQsHgdPduZnFuNkOGNs9AdGqIA8DhxcwIAUUIIlAAA6xroqiJ44YFl/AABbkAQD4Ej5MQBwHIQk5oglppCC4+AOno5xTa4QHmGLUGZMOmG1WADJjQNYXLzm0YhMIABw1ghxftpyPmdSuOWOIGT/jUBiXx7UgnPiKZ2DOTAFZJYNr6WtKV4ToehnRvrntFgAEdCFWcCA4Fm8GuQFXXiBb/YHCQjncXZoW4gGESgCXoiGT8CEaJiCFOCFxoXnjZDn+aiTR75RP7ACK0iDZngPkF4tfpiHSgaKkl6kk0aLBSCDCmiAJ6gN1wvCG2iACnCDbXyBGFQDMYiGQZAfjcAAtbGFIYgAzFEE+uKBBrAANbgBi3bUkwjmGx2DpzYEj2aX412kYegHvSJmnDDmpNBqQOLqs1gAqTuLpE6POqnnCZ0DKnjqVWAH/uDcJhoGaOiHfcCHeqCHeHgGeMhNg+ha2H6GeJgHeqgHfNAHfmjs/8cmCX1GbIqY7D+q7K24bF9lZJnNt4zmUC546jmQ6v4oU7w5bX7QB3ywh3lwbdge6ZSSKg2xbdzWbd7uqo8Q6eCuiOGeo+LGCklwrsxObqx9NqaeUDgA7SyAhdH2j+keGdS27nugB+1+7WOmpu+ube3Gaq9Qbzli76tITJEQBUV4b5iohGck4Pjm22cb7AVNhCx4ajjYU/eYGouBBnsY8ITQ77lBiAUvowa3iuMGiSUIPthtCQmoxo/QbPQIk84O0DR46i9wBFjokOitl32IB/RW8YNgcTJy8aqIBZZqAMyWCRsPiRw/jzBh7gB16qfGAzFFkfCdFWNG8iRX8v7V2f+OGAZfUPM1Z/M2d/M3h/M4h/NfAIkYiDAtcAMbkAAdUJsVIAAO+OtZ6AEL4ABITMU4eAEJcAWXzYA5/gMRqIAiyAWNYIRpVAMqB+xMNQn6DtDCtgI0oFIUWeBZEQYRHnMyX3Ez9wha+IKndvVXh/VYl/VZp3VazwJQCOWmiYEHkARXKIEKKgUDkARVGAaMtIVKiHJ/WIEHiARVqAUAiAFSUAVEiABMsAUD8gfI/QNcQAICuPEL/2XBDlPnxANX9wPwDPH+uChayd/uRnWSVvWOuIRap/d6t3dan4Nc94cYmDJy1ggE2DxGkIAfLYI7XIHS9YfHEbIVIAPwiQUC6AX/MdBFXjCAb1diDJ9dXuPx8EyEVreCNsDRHYFYUoEGBz71d1eIJc+iUN2FNOCCl4f5mJf5maf5mrf5mh8DVND3I9YIPoBFfwB4f3CDlF4atFuBqn0cH/QHC8CApREBV2DPjWgAi49njPddXsty8YSDp86CRAj5HQnchSLfk0f5hVB5LGpyqjhunvcHn//3zUMECfC6o9eIpNcIFehPydHZXqj4Krd65v00Tud4D7cCOHiE5vSDU1gGKFkjQrHqBC97eB+ntJ+KtYcytwf6zRMGC5gCXOAFRbBFuk94ACCXQWiASmCuckwFBECEXlgCb/f7cC+JDRfPNABtIG/ORAgE/2RAhmQohxRHkfukJxGOfLA4+yaifKl4gTsfBLKpBLldgSp0hR6QAAl4gaaZgrymLxHoH5+fQoR/ZwmAPSmv+vtIhTsAzbILiY1/TkEAbSvo8twPhFPgfW7wBnJQhx0p0C8Zhn0AiGfu2hEsaPAgwoQKFzJs6PAhxIgSHerzZ/EixowaN3Ls6PEjyJAiR5IsafIkSpF1ZKRs6fIlzI4VPsWsaTPmIAQYEEQL+amCyEuOhhItatTRGCtWxhB9BCmRKWTIuFHlJg7dxKxaty6EB+0m2LBiOfab944r2rRq17JlWHEs3Lhy59L1uLIu3rwYZ+rt21JYNEw8fQIF+esoYv+ieJRS8WM0kaxm6MRVpQqu3Lq2mtnC6+f381xo9+AN3Gz6NGrTb0Gzbu1a7N3XslvynW37ouCeIH+GfJU48RelaSAZhSSr4DJy3Sp7I7csNfSH7/bdri5yX7zS0bdz706Q3TJz5cSBA/fMOvr0s2Orb3+xtnvQuUMKHgLkfiSOoX4fhaM0SyKIHWdQM+WAU5lV5ni3oDv4xIceNPS8o92CFVrIlTrolDMOON50s1xV5Tw4IolhsVdidfChWNd8IGnSgBoxqkHTRkLxR1QiWSgFR2IDHsTOZFV9eFlmF0I3z4qsDaPPM0Y6+SRD62hITjLeCAliZeYluSWXIZ3YZWv/KoIpVosf8fbRYTcS1QYVVnDxm48JqUOOlUKOkw6Upj0zzJhz8RPPO+zkOeiFzYRHjjjfcPMhgkKCM0455qyzWp+VbvmlpXqJmWlMZXp0pke+qemIIEpZgQecDjVjDjhYcpOMOYISqpZXnNo0DD7wzLprdM2oIx6HVDHaKDfgiBOpOrIWRKmtzapXxwqkSDsttdVaey222Wq7LbfdevsttRLQ6KxLsYiQAQEi6LBbYR7tN2pSS/EXZ0PpiOPqN+QUyatW73hGbkr6wKMsvwWjleGGySzqKoLfiEOOOcs00xCzAFv8miQRaLwxxx17/DHIIYs8Msklm3xyxxK4cnFK/70g8jIilbALko03LmZFY/NOtA45ii7cjTh4GiyRO9SxLJLABA+9dEPrpFMOlXUSS9U3yZBTTjoTS1Tx0V17/TXYKYHKkS+PjBqcFWmYnWpWq7ZaGaxKM52QO/aErVHSc+ud0DLlVLnw1N5YjfW+W3F9N+KJK3702BuJeqN/VmQhCHFsb2UvvpjtvdA8fN4t8Oaht6OOgQwLmQyk6Kiz2eGLu/467Fw2rtG7/CXCRZs83kivVuuU47OwV4l+0DNffQ368HOvYw5lw1p2bMRya9Z67NVbf/1ts2dU829tKMVFImtbntaqCsNtjtbD13o08skPXT7D+Wa9IPXY238//v9zaX9R2TcK0uapRsW7tCxjHPgix+qG9w5+XKx97uOXZMYBOKp4YxzokN526pe/DXKwgyjZn0Ue9xs0KOULo3LEANXiO+BRRXiic4cGubQPXT2QX+xIxzikRkELpu9CMfQgEIMoRIuA0B+1Swwe2pQzAaaGHeYwX1XAgT7R0cNWM6whr4BEJwQBLVaD+uEQwyhG7BWRe4j5QpvScEIUbqeAy2HUNzS3uXh4bkxXxOKs0tGzRolDUhSCEhjHKMhBJg6E/fvNHP5DuROm0DQFOpCdnrO34oHpjnjME+kgCTc58iqQhPwkKC8GQhEe5XY7WiMbveNEKLZQaHPrzJb48Qz/DF7SO5lkWDLKkUCDeTKUvvxlpUB4xKN4z00BWmMjoYNDBMVtbgtEkSxpWcvtLI+VlnGO3noJzG1ys0QgNGNRBKEjK8yhcox00pwQdJkeFqxBI4rmNC+0PMo0jBxY2Zw2u6nPfVpnf4dEDAnlhcpUOmmFlclX4QpGjzqiB57xXFAEGVbBdEiTl/y8KEa92a6MkLIofjCVYwaaTO+4rTLdGIckDRYPYTR0lg9VJToMiKAKooOdoctnRnOqU/1tFCPDLAra1DhQguYJSNZ0YcHWNxtZvrQ7QMohF69i0+HhdKdWvWpN9gfOoSRScoIYKlEJVUB1epFfsHwNU5tKzd81/wpWU3VfVbEq17mWRHv/LIoprdAGc6JypOhUDuDWya/ptCatam1ikJgpqZfGla6OfexGtNfRoRQTfGANK68MWpXmJDRP7vRLPwRy2NRoNoqcZCxkU6tasfXUIj8l1TjnID6Rzm2VJg0ar5BUk2FAAxr94Ac/9qEPfdzDHvSgxzzm0aTRomaZt73naBu72uleVXtbTUMJLzsUv+aRnlVJxgVntSd/9LYfv92HcPFxj3ogdx7xiMcz4gsPeLxjQn9k7oKWp0nLnDa61P0vBzOhhi4QmMB38Mvs7jqUjyoFD5CYbV9F58YsTRG/Fk4NDl0FNOheWLoA/rCzeAAAABgAAf8mRkANENzayaLRCmjg61C5yy+eKQpE+XrrhXO8M1aps78dBjGQY4cJADzBFq+Z3U/n0KbJaXe7D3zkG7tRwV3quMoQyfBzrWwQDwe5y11yw2CO3Foz5rUNEI4xFo2KIKRquc0FKZA1icQrOgqjt7717W+Bi17hDle991jvcdtLj/e+9xnwje8z5gsPBnq50WHLCUNZ0zgFs8mYTXYyHm94r/NV1M1qxaEON8wvd9zD0abWpzAwcAbZNI6U4mzTHC6N6VoWUIdy9jR+4dzjzg7qrKf+9S9VAYR0LeEJxn6CG1SckSM+ArtWMKGsMYtHGruqjzjGdQ316DyrhLdglAT/NrhDqYkTkxvFysYI9xh8qjODVcbDKylzLIjtS5avnlTmlTvqEe5981sjY7trvNAQ7Vk39ak6LFY5Ujrv0CWHYVfp9JOe2e+J83tsIlQyzr46cHfXcFXe/a6PFw7BJx7w3t42HsVTPsRYnEEJN6gCInTTl7EdkQtKacPACY7fWz732iI30pwO3kymuaOKKj96EBGBABI3YMQrAMzMN1ozOCz5mBvXsh4Pni+F/9xI9T4oAvcmcaSTfYO6QEAGMNETXoiBAFo4tz8OmSOcxTrn0r7wUxl26657Z3lQ5fTmvl32wd+PDwSYRUaWYAG4P87Z0LY7x9XqO2smyOd8J6Df/xqVL5MvreiRJjzoY+eGB2gkDguA+7vUjSq7313LydkvNyZ6+bZoEfaLsrboCBv63VsPEQAQRUZukAG42yjgrNc5tm/4dzhic/ZaWdXfmdNHXs9N8Ly/vuuEEYEHuIEUscCEiNVw7v7dzAoaZ33kc+zxtpbD8s4f3Xi2XSx7ut9gncM+/l/3kxGPmABTkHlenIlvlNnxIV/X8dzPSNX7/YgedQguJRzEDY3u5R8FKs4wLIIYdIEbqAJonMl+RA6AFGDrdV1ysBA3yM/7RdA3fAiWdBH1iY5SVaAMYtWZXMLcWQEcsFu0pZ+n5d2u/dw8mc438NA03d8MHiHL6MIsDP+DMMyCEz6hE+qCsvmCIzieCBrgArbD5PGROSSLm+kR5b1Kwj0UDCGhGV5MDABAJgwZ/7XhCijbK5RKg13hCGbhnNheNzxKOahOrqFDz2wb0IQcHnnF552hIVYKI7iBLdSCGzSiIzYiIigbKMQLU9AhD3adDwqLqwgOxMxPLQWh5tHfYdHRIZbiRfEGgy3RFV7i5UHf25gUvjxM9AxP34ThZeBJBCZPGZoiL9oKKaxLRtBBF6iYL7TYcNBhHWahQoCHeJAHsbCgZaQO1xXVOixDOqCDOQRLVAniQ/laL35jnwiGRkzBG0ZdIvyH1a2iMqpFM6SDOSCKCTZKN6DOHr7/IFuwQzW64zuSwzgkAziY4LYNYYVZ2EqBo0GGIwJohA4AI0yowQm8gCT4hAXYHA4iIxauI1c4zTuKw8FpIgXRYzrYY0LgY4ZgI9SMgzgkA0BGmelEkT3l4iWR2kHOJJdoQQyIAAHIQAzsZAygi/jBxOgpApiRwm7MwPdY5EVi5FogTD9OzUHJ4jKsgzosg0mSA6L4Y0s6ZeCAA+pYZcRomTfSpFiOCBJgQAUQAAakZVqugBiwFExgQBz0xA08wW74wBwiJSsq5USwA1O+olYKyV8Sizdw5cNcjTmgwzKog0jmWDyg3Fg+5oh4AgYA4K0QAPD5gxqUwG4QARUQAQ18/yZohqZojiZpliZoksEq6KWFGMpGxuNfVo04jINhmkM6KCZMtlm+QaZuvk4sAADi+YMdLN5HVAJntoAHdAByJqdyLidzNqdzdsAGBEET1J9qooZGUglhymakoENtNsNt8p2/7KZ4qocqdEIv9EInpKd6pmcqwEQvAAAH+oMbcABlaoQnEEELTMBz7id/OmcITAEhnEV1DmjgOeZ4HuhspOEatqEbxsQC5Ic/TIEN7MYFNMIoNMIlyIGGbiiHdqiHfiiIysEgECiJzk3RISiK3kYmDIIu6MIgvCiMvigmxMQSsIQuRMAffEQ0/EQ0DIOP7gIowBj6fWeJFul2jF2KJv8py8QCBkhAA/BAIWbEmUQDlcZdKDxYAcKCkW4poVifkn6pbUgCH9TCTZDCyhAG2VwpluZcXnKpm6LFiYKpnLZGLiyAIljEEoxYA5BCffKUR/wCKlAC5L0poXrHos0pooLGIBgAn7gCASwBJ2AAD/SpXBSRRQCqoO5goW4qdDRmon5qX7iBBFiEGxCAFLpBa9GFpV7EL7BCpjZZm3KqrB7ELoKqrdYFHZCeP7zA8PnDHTQApcbFqmLEMLiqkCLTrCZrWhDirTbrXHgCANBBJhjA2/mDF0xm1JnEMLzCVjGRsn7rRBihs44rXPSAnpKpP2TAD8CdSXDrseoMuMZrQyD/KbnWa1hgwh9IoT8Igxp4ArueBC1cwpqqSazKq5F6qb0mLKcMK0jswiack8FGLEHkpsJW7E1wwhKsQAbcgBpAXbbGhMMSbIm+Azw8wzzQgz7gg2hJLEOEpcW+bEqUqgFUQAY0HQbkwr++BJDCaxa6wzsY2jzcgz7wg1tqRIRMCMsiREHCLNOmxCwYwAqcaTTwgQEsQc7CBJAea8HGk8/G1zzYw9Aa6Ej8iTvcV7y+A5c1rcLagQHwQkZUwah+bFj4gpoWxdYmD8m+Vz0M7b/chDCMhtkm6zP0rdoWLkm4QQNoBOJerU3QLSRgKTOwl3vBl6IhLR6RrMnWAz7wAzRE/ylclIWAKmucGi7pjoQkAEBEXsQwrAAHMO5NYKojvMIwVOlG8JZvBVfKGldyHdp81Vdb+CzJzheivVdyHdef4YM+oBc/mFdvea5f4MpyySq9li71dsQw7MQUxAwdiAAA8IHrggWg0kKwpgRvmRd6EZfkHpc9CG3y7sPy9kPzAkw/SEjglqinVi/+foQrqEAbLoAbjC9cMCxM0O5OkS2XUmz+JrBHpAIf2IEk9EIHpurRiQYNkajLKrAC8wEPqAASZIKYXR/oDqi4YjAJq8GIGQCJqV1rCDDFLUn0KiPakrAMX0QDYAAHVsICsMQKS3DoHW39LhzCznD+4gIADMJFTP8BD+MFC5PdPqxs13meEM/wJwDAuICZayxx2VHwz01vFCfwFF+mfCbkDh/in4Sum5FiF0sxAGSACLTxWZZAG4vAFHxvBbowbqZtGo8rKYxMD9DxDILuD3ej2OYxIUtaEp/h/FruYY1wITdyBIslP5hFU02gI1fyZ2AxEkayGWNREFuyJ6vqIX/jMGhyDSHwJ5+yEoeyQS5JdoTOz9YD4aKyLFeqKs8kKweyk7gDPMTDPcTyLP+ysNayWN7yoLiDyerDIAOzMo8FJtsyk+CyafysPTDaMldzXTSzWEKDykIzV+jyPCCzNYdzAArzgWqzE6vFz9IDPzivOLdzWGDzbpr/81bocjzggy+7Mz7Tsr1CQz2QhkP87DzsAzvnM0G/MznLKT/7s0G8Ay/3w0AXNESDBTwr6fw+Az3sQ9FGtEan8kZ3ND5PtEeHtBCDtEiXtAKTtEmnNPWitEq3tNqytEvHtMXCtEzXNIqSghFggHDOjE33tMV6QheIQZiZyUH7tFGDqad0BE0fNVPTZFJzxFI3tVTLoCqcgVVf9RngAm4MtUdUAgG04apNtVg/JiksgVmf9RKcqT88dWQV9Vi/9Uyytb+5NVzXtSkKAybEgQFggr8StV3/tXi6glpiwAvwNGAfNqJGNWIvNhIqNmM/NgU6NmRPNu9JNmVf9uBZNmZv/7bKaTZnf3bF0TVojzboeTZpn3ajmTZqrzaIqTZrv/Z0uTZsz/ZjyTZt3zYNijZu7zaQ2TZv/zY/+TZwD/c2CTdxHzcoGTdyL/cYKTdzP3cQOTd0T/cGSTd1XzcZ6TZ2b7cvWTd3f7fieDd4jzfYiDd5nzfLmDd6r7ezqDd7v7eluDd8z3eXyDd93zeK2Dd+73d86Dd//zd6+DeAD/hsCDiBH7ghI7iCx46BL7iDg/KDR/jdNLiEV/hNULiFZ/hLYLiGd/hJcLiHh7hIgLiIl7hSa7eJp3iCqziLkwiJt3iKvziMl7iMz3iI17iN8zd6isJDL4IBfGMplCMvisILAP+wDH5CDBi5rZqBTjyABbTnR/yBASg5BWrCTpsiJmDAN1ZCr1psJSDeMMjAhEb5lPeilX9jlm95lzOtGIgAAEs5leffmfdimvcil6ttL1hAWHuE4XmBn3uBHcCMoA86oRe6oR86oie6oi86oze6oz86pEe6o6tBBEi6pV86pme6pm86p0u6GkhAp4e6qI86qZe6ppNBBZi6qq86q2s6GK+IK9SArM96DYzLMNyACgw0IxAAAixAr1tAHAe7sA87sRe7sR87sie7si87sze7sz87tDc7BzxAtFe7tV87tme7tm97tE87t387uIe7uI97tnNABJA7uqe7umd7tSaJLtj/AbzHux38ZjQAAQdAcI7n+2tEgxJkgL7qO8CDRhcYgBfEiB0EPMLrhR0c2xN4QcI/PMRHvMRPPMVXvMVfPPbxAhk8QY6WYjSIAh38710PQhVUASOYoi24wRRkLwlHQwasABlEgBiUIiMsALrwohtgwBRoQQO0+xlGgg54Ac9XAQYvQgMAhiQcfZyHHp90AgHwIr77Ax8Aay/mQQRgcBXcgEUMgwF0gik6vUFafS8OwxMUtgL/gNVaxAMYcSmC/TfyggT85CHmQgQgQAX8ZgIbwRLoRgMswtc/fS/2ggrowEPjXzTggifIQApgsE32RC8YwKufodubYi+sgA0UfgW6/wIAGFkCj5uR2YEELD3vTf4hCsMLvADmY1/U/wECpL7F6kAF8MACeO/cnwsAiECKHaIJc0AcR70ZLkEG6MAKIEActLwkxAFRliJeYwLze/0hfh/zM7/rg54wVEIcDALeY7z2bz/3d7/3fz/4h7/4jz/5l7/5nz/6p7/6r3/18oIXjAtY/IGf68FHDIKfHxj7f7cqGAD/9z9AGBD4wBWAONH8JVS4kGFDhwtjIHjR5aFCMS8WpKi4kWNHjx9BhhQ5kmRJkydRplS5kmVLly9hxpQ5k2ZNmzdx5tT5kJcaNz4NWPjpJk4vNaRkxsAAkoPGnU+hRpU6lWpVq1exZtW6lf9r16gLVnTk1WmWQluehCFcKMzTJ2EVlTa0xUlU2oVNvebVu5dvX79/AQcWPJhwQ7ALC8ZJqKOCGwQACEwRpoQAAAN/FEbr8hjAAjoP4yrUtaKyZTV3nRZWvZp1a9evYceWPfuwwsQIdRjAUEkVEgAvZHwSxWFBr4RaCHhRpcoIgUoOQydcsiASL1eDBqGevZ17d+/fwYcXv7p2wtv+dAAQlbAXgQh2GQGQ5E+XgSUKh1m4AX2pwhQqKsJrvAEJLNDAAxFMULzy/DlPhwYWekAGhVIB4DNFAHjCjg3t4AADtSDq77jf6iiLIQEVTFHFFVls0cUXU2LQwQoWigAIhVT/MSgaOwCoAIMffwSwoej8EUYMCyBTIRXtYGzSySehjFJK1mTUET0aFbIRRx0RAYAPj4i0zTEOmJzSzDPRTFPNNWMMyzYrGavxxoRyPIgXicAUsSEkFiiTzT8BDVTQQVWs8qAr5dzy0DMAuKESUiKZQgwQFSJSBzUyUWWQBl7wk9BPQQ1V1FH7qmA/hWJZII+EjMhgIQzuMw8BOxSKQwIAcMUAsyH1nA5XAm6wxVNSiS3W2GOR5coWVeyCzoJZdFkoF1WGWUiXWTIQMtltue3W229pigFXNyuqAdfUwE1X3XXZXbcXXXQxbqN3423X3nvxzVffffnt199/AQ5Y4IEJ/y7Y4IMRTljhhRlu2OGHIY5Y4okprtjiizHOWOONOe7Y449BDlnkkUku2eSTUU5Z5ZVZbtnll2GOWeaZaa7Z5ptxzlnnnXnu2eefgQ5a6KGJLtroo5FOWumlmW7a6aehjlrqqamu2uqrsc5a66257trrr8EOW+yxyS7b7LPRTlvttdlu2+234Y5b7rnprtvuu/HOW++9+e7b778BD1zwwQkv3PDDEU9c8cUZb9zxxyGPXPLJKa/c8ssxz1zzzTnv3PPPQQ9d9NFJL7mW0lG3WhQLUm9d6k+wdF12pmGf3Xala79d96Jz3913oHv/XfiQdVkigwhiUaiXGxBYQAyPgv8fXnqOa9GCR1UUqoIDXkRZ4DmOop9e/Ix1AQD7hB4YBKEleugo/PHhp7j884UBYEl/3CAT/ApswcV/moaBDWoYI34F3Nb8EhILAJjIDqzjSCUIgAAJIkANlHKJMqQhjWAYkIPGQmCRCIAUf6hBBO6LHQCxkcFidJCFo/qgPyTwJX8gwQgmvIk8MjgNebSQh4TKhCQAMAhMIMQLGHBFJRCQCRvWZBjFyCA2ehjFQHkISNUSxhIa0BjonVAmwKiGNKahDCmOEVzve8kxMniNapGRjdsyo0uCkcFttJGOyHojS5iRQWrko459JNYdV5INYkgjG340pKgAmZJ8UEMaxGD/xiEhSahEomQbGdxgJDEJqEme5BoZPEYmQbmmTZYEg9KoBjBCmcozjZIk2JiGNFaoSllGiZUikccrieGMWe7SSbUMSTEGCUVeDtNFvvyIMKyRQWWskZjNVJAxPRKODFqDmc60poGg2ZFgTIMY2rjmN7HJxZU4Y5DU2CE40SmebG4kG68sZDrh+Z11PsSLGTxHPPHJnXk6xBhpzOc/ZbPPhlyDmwQE6EFbI9CFnGOQ1eAjQiFaGIUqJBsqfEtEMRqYifrjloN8ZEZB6peNauOJ1QzpSbsyUWS+MhwodalXJhqOV1rjoi+1KVYmmkJY3pSnV1GoM16pw54OdSoKdSIh/2tKVKXmRKD1lIYYlxpVnAgUjdK4hlSxahOBxlEac8zqV2OyzzxKY49gNatL9llRQp6VrSuZ5yLB+NG2zrUk89TGIC9JV72KZJ6dlMYn9xrYj6yzlNZApWARu5F1YmOQsUzsYxuSTXkMUocmhexjs3lUYV6Ws/6AJjKVadnOEpUXpDAtKeSlWHF+5BgzHe1X44AAIHliiSMJBjG6+dqsxoFcWyQJM15pTt1iNQ4iyNRgV9uRdq51uFKNQwMysAAO4KIjnXgAh+xQCo/k44vSkGtzldqLavVCBDXkCCYQEAP1yiA7HemnBpMK3qjGQU8P8SVBpWFQ+WJ1CtqqSC3Pkf/BU+53qUvQghuWYIBI1PYjriRGMURL4Jcu4gk/qMJ6GNwReTBSGs6IsITPykqSSgMbHwaxWUeJzEG29MSBHaU0pUHTFrs4uQ7RqTZMPOOsbpKcYDynjum6yaNmI75ADnGNF8JdZRpZr5M0xiCvyuQgI1khXNWvlNmaSIaS9aFYzjKV/aHWd3r5yxyB6zS+S2awAnLEeVUzipE8jE4Sg8VvhvNGCntYO6+5xgFU4Z6PXBEc+jjHgB6fJ+iQaEUvmg67ssobNWtoKVYBV5W2NK4igNPkCqMauIWqpHmoC1WkYtSlJjWpXaHphxwDyoUGtU3NyFWvvpqMn7CDGfhwP1X/NwS4XHY1rcWHixRYmgA8aFZV3rfcMQO7hyswgBYwkYpKLCFDu04yNTzK7CjmqA4MqQICfq1VcVZSg+HWtvAqAQBeMAQTABDWo8XpV8Ceu4WiAMAQFxIHAhQ5KtEr5YDp3cJoVEAC8/HHMP6wgBhYOyGuhKW5A+67TDQAAAiIgAF6lGqfnnDDGdRlxHmYizPc4AU8cMOxkX3CYrxysyDn4CdEQAoLZqV3K5VGnV1uwHYnD6axC8cgrZFzFvZiATJMaey2mVuhd/APEaADz7eSO6D6eOkc7MWlK53pjSdkyBCvuuyE0QWxj13sp9n6Igd5z6/ztHbvjfLa49cLGVB3/yGSUIKqCUqMK8NdfFfXeK20Du8tl5Xv8PM7Q7yQgZn3uwJqLQa/C787N8TgBQBYgQzUGwNnx+rRFnildyMvviJiAAAWABIGOPCEXNAkEkqYggjBtwW8ht7wyNPJIBBwhicsAOr/BQRucU77a3LgDAmZiPt+L2Phj48tiHC+8yuxeJVEgwCfSAgZ/Gvf3zt2+dIbxAOwHviX1AIAPKfDh877+yOot73d910vZJsHTMx//rSNSfk0HgdXcYQTgAgGHTYE9txPdzJBPXQCAb6nCzoFfGDgFvxB+gZQdj6h/HRCB+5DGDDgUFQrAqcnA8hAJ0ShAVYA9VLrv8CMA1NnGP/IAAGAIA6wq/3ubxAkwdU2CgUt5+qwDgDEjypq0AYpJxpOKwhJ4XzgzQcxqgeNkHI8wQ7IINe0AgmTEHJsYdgqrdhQrqhOMApDx9m0IFOmjQCegOG0sHVyhFYW4tu8TiagcAwXJ93WbSHa7d1Sjg1lx96+p1b2bevosHUGruASYhj4QOHEcA9JRxMoDgEeAOMq4O/mkBBbJxfUQAliYAmKguay0BFlaQ0xUXBS4QnuUCEG4QnesAg3MXQYowQTAhcWQAsGsRQ1RxgMwA1EawokoBVdEXMm0PocYhAAABWlQhNvkW8KULscYhEAgO4aMRg3pyBgcCHUwADSMKwuURn/HacCUmDmesECeosHp5EaGScOGsVEEiIVVIAADI4UvVFzpoAACCAD1AsD2NHs9DAdNUcSYmABcKUBboATnrAb6bFxhOEK5/EfVQkYCVJ6DPIghSchFdJ3GLIhdechIdJ2JHIiJdAfLbKFKjIjU2cjObJ0PPIjRyckRTJ0SLIkP+ckUbJzVHIlN6clXTJzYDImL2cmaXJwEEEEdFIEMGwDb3J44oAD6G8UTfAngXIb98cohScOFgADVOAzMkwpRccVsItDjCMT/qATmNINOgKCJoiCIFAqLwcTaqAszbIGVm8hxEB/VKt/cCEtxfJ23GD/fDIubQcRysITJIAVk9Iu/21nCRCAABrgCQSSIWzSL/cmLA0TIxHzIhvz5RjzMTsyMiUTJCmzMkfyMjHTJDVzM1OyMz2TJUEzNF9yNElTJk3zNGsyNVWzcg6zNfvmNWFzb2RzNvOmNm3zbnAzN+tmN3lzbnzzN+MmOIXzbYizONvmOJFzbZRzOdOmOZ3zbKAzOstmOqlzbKzzOsMmO7Xza7izO7vmO8Fza8RzPLOmPM3zatAzPatmPdlzatzzPaMmPuXzaeizPpvmPvFzafRzP5OmP/3zaAA0QFtGGHChmobBE4gxKgmUbrAF44jQFSrAAhrABgptQBsUZXRhEOyNCJFgP3ghhhg0Q+fmhRbA4P+qoAZGlETj5oOu7nzmsiM84QGeTxFOh0XNRhduQAd2tEeVKCE+aBYWKCHqwIE2ohIMoAR2sttwtGx6gdESjQg/aBgIAMPUoARWtEnb5oUwgCv94QamIEu1VG3cgAwAwAsqyB/ooAH+QA0QQNeKckzlRgmAoE6BYI3i4AVuABN8S04VRxIQAGZcwbxcRhXu7mVKgfPQ5g8MQDFJRhOMtGUwob5WphLoclEb9WUgFWYmFWYsdW0Y1VFHZlNfplNf5lPV5g8IoBSEsFVd9VVhNVZldVZptVZt9VZxNVd1dVdddRAqgFeBNViFdViJtViNdVb5wAKOdVmZtVmd9Vl1NQ//MABaqbVarZVXifJAIsE9IqBbvfVbwTVcxXVcybVczfVc0TVd1XVd2bVd3ZVdE/Fd5XVe6bVe7fVe8fVdH8Di8rVf/fVfATZg6zVeBbZgDfZg6/VQ/XRhGbZhHfZhITZiJXZiKbZiZyIaEMENenJlhCETFAFR6yAO4DRlhKES4iAOFtRsasACjGABzFBlkLQBCMBl6GABZKAGEEADU2YQMoAHcNZLyyYTECBa+EACovFidMEWOmFmW8YV5MUNHgBm3KACRDVrtGDhisQAdHFlllZmNgVmyIAtyaYIOK8BFqFluhZmhCEDqqBldEEEMMACRlZsfoDzaLRqPSZtXSYawnhABHzxZIQBEfQgA4bgbKrABv7QADoBbZm2ZaIBCbYnZkoBAKKlbCKhAYyDERoA8kpGb1nmCTKgcj3VAArTa6KBA07ACx6g+FZGF4AgBggACMJwZcBRBuy0dEWmCnhAC7CIL82mF9xgCj6WZYxCDYwXKlWmE4x3eY/WYlQheMWATy12eqm3eq33erE3e7V3e7m3e733e8E3fMV3fMm3fM33fNE3fdV3fdm3fd33feE3fuV3fum3fu33fvE3f/U3nQICACH5BAUFAAMALF8AFQDAAWwCAAj/AAcIHEiwoMGDCBMO+MewocOHECNKdNhPocWLA6I9xMixo8ePIEOKJDix5L9oI1MS9BdtmMmGKkkyHOZPJb+bOHPq3MmzJ86aMYMufEm0aDyhCN/R0wgTqdOnUD8WjdhP3ruoId/BixcPmjx69/Lt68dSYkeG0frhowcN3lWV7uLKnUu3rt27cqFhDTm178SjewXCs0esaeDDiEf6dTgMH+DESLVy9QpWLFmmA4n521dPXry3T/GKHo1XL+SLi1M3fHw4HtN/p2PLlqnan1XQsw9rHWA6MenfwHvnLqhaNevD8F4PXx61+D9i+4Qznw4VuHXR0pk7X3wc+WvY1MNL/3Xujx488eidXl9fN/vy7X67I/dnOL194s75QcN9vz9I9gDG5d5w8PUl33z1+Seec9HU45aCEP4XIHsD5lbgVAcGphV9DEVInXP97MefhyQmNCGF6F1o1HDwcAheibKpFo1jMNZ40YnrVTibikRliFiLHdoIWWpVjSjkkQLheJ2OMfJoko8/9hMkks35RUw+UFJZo5LWMRmbk09OB4+UL2oplF/lnWfmmkly+ZuXp4FZUpZRTsmmYkVBB+edJbr5ZopySkQnYu+QyadIRTWo5qFs+knanokFKqh47/BjJ6MWFaWfkZgi6ehokCImaUSDJlbopZ0a9JKinKZ65KfYAf86qkOlmmppma4O9NI+i+baKKx3hXrYrA/Vauo+qKZqUjTy+MoosMHKSuw/xh6b7KEv8dOrs79CS5ewgU27Wn/vIIsrtiUN0yy3z3r7rbTEVgvZO/lca6ZJ/TzILpXOsMNMOueYU4456TjjroDwzirvvPWeq6VJxNDT6r7oObOOOgALTI4y4XzTzccfewNyN8qUUzC04O4lLkMLM2yvjfi2TLFT7bCzzr8Bl0POOB2P7PPPQIMcjsnsOJoyVitT62HDa5ZETD0Tz/wUOwNkXE454ygDTtDdeCNyNwqBo8w45Awc8Dgeh+z1xyWfjOPRVYor82n3OFxjSf7MLbVH4xD/5I1APxv08QDhjH21Oeeowww77eDVDjPmoB102wYDCDdUSesNWd1ImmRP1HsHRfVF3hReNuKJr+NM43K98w57j0ee9s+UL5nwqJpDZo/dEOJ9eegYtWMOOAN9M8Dp56TDjOq/fSRa7JIDXTuot0uaO2T18N5fSfmADnxK6oSznHXMnBP9z0OnU7RdvzuVuY3ZlzhRNO1/n9A644AtkDLMyAZg+efz2teGdo71IWxBK7veaeihvfCUhFf2i4ozyuExgYDjHO6YDY4AOLu1fYyA7KjfmRJ4JAYqaH7riiDNzvGNvw3gG+YwWG7cBL0Ofo1k23oPCUvYQAJJRFsqfEr4/1x4vNENB1Y1/Nk+HLhDHqZnIuoKolPwR0RlqCODzHFXEpWBkg818Ujy6OGQJJIv70nxIhOs4AAuiMXpHEwujQOKF+VmpjDO8SERM+MZLXKOcLjQG+WQYXjemJfqBUqBw7GjDiHSD0RGUB3K0N8AxrGONg6SkO4QYVDetyZ5EMNCEXmaHveIEHaQQ2T7S4clxYPJTBpSTo5M5CdFZZK8kTIlwkvbGs3RuP60UpMx4SSboCFGjBQHH6O8ZUHSAY4/BnKV6fnlK8EUS+1wBEz+AGYEmZE//Y2DGdC0jzQRSMdDCWdl+YBHO5QJEnaUA2SES0cvIzROJpYTU9DwylfqUf8PfIiFH2RhiUsYpM3v5XJwMJynh+p5x3ipUCtb6Yo+6VEPe/hzHwD1h0AhyM6PpMOPgyPH+mDE0OkIs6MoDQo34cm/uNiopNr5Ykpn2k4KDi4cGAznQjFZUDzdk6ZADd45tvaxb5SDdZ7i6TSdVM2ghu6jqCzi67QE00VOq6lOpdg6yNE1sLVUp8uBKDwiOpl8emWi9PgMIXuKKJlm1alpvGlOwRoTefQTH/jYh15v0o++ajQagB2o0ybyuTeylS9ufStN+zg4b8TQpV8a1QCyebDDguSkip3pSgdHSbkEJh6zRM2FBpJOb1l2PD/NbEfdCc9wqBKye0lOaBHrF4L/0A9lS+URVlV7JxaCLKGw3UulVDYRg/AKVqf1CGZ5e8YhgkyknkUMPoqJlGQx61PJPUtimWs/U7IUnMENjAnTc1w3Zfea2+Xu3g76MTaG97PUjQ2zXqek8xpTbubIb/IUxw5nqHdmjB3cM98b2y76p5Gsm5B9RUuseqgNaOAoHNkOlzzlrYNx/9XSZsHWWQILlz4RGobETrTgTE1rH7PjGsgECLRvFE4ZZRsY4tKhjgv7N8MVe6fQXkvXqJQrvsxppIJze6F8pCO/OtuY1m6o4pF5sGtP/mABcTwd3xaVl9GNTfxgJErLEflCGerXzQCWM51lrWdNDlnIyKEOKs8G/5LwhK6HD0PMI+UNReS8akzaYTFmYCxg5jje/lLcDZwa0c178e7grJhl2bgGyOjpcpe+XKBqBagd6RiHyL7mDTYjOirs7QY4zNFo2QDJTHmj76MoDR/5uIsdwxvAyJQRw08LxbkfG3CPNWSpOyHzT3mOFyYHMBdMa1pt3/C0rUWCv++Weja7OxRlqRdshTkKI3SBNfFmXetlcySuUp7LdMII6aXBI1bVxh17hFLsTP8Nyslus7cVwkxOH/XZswFtuUl022il23p2ic1ctA04tnV73gNhRiQ5a8DwJGffMCrvu/59SFbGxdh/9Ea8Ec5akCmDx7s2laF8dd2J21PP0f+MyzrKIb6CK+McN3az8IgqalLjezhMY5fEXUlxWPrn4uaT9W/LIW/1tkMd5aB5N8rBDvqmh4EQR9J8D3hyhypILitvpsthrlpMk0PpJAPvnHMDjcKETls8r7rCSAT0vg2kG0btX1CdcQ5yELrQcw15bB4edTNFrMQKWS6EVB7rt9M65sp0RjrszmTCmUPset87hyJo4IauXUjuaEfQBeK1uJOSHeYLHK0NePPpmAvh2k3tS9dReIKQYwCI3xvouwlPb4w+4P3J3stQTxuUm0nzynj34BI+M9YvvPbjKGBdIkTM3fNeV+nF/MpbXvCBpMNXkAMpPJMN8+V7KB4DfT7/elXPpnUcj4jvHgCti84mZrD8hgJJtttK3x8g9f3TgufTOguy/eQfukZH935EtEYmk2CRlx6VkiDilxD5lypogxBEt38REoAt9DUCkT7ipiXT5XwLKBANmCpHVxAC9ELJV0n3oXh2N3wXaA7qkGBsQm73Z2sf6Cuzp0YsFYHLUTMXYz5RNRC0JnaHEg8K2IEMOC2m8ARvcArJxChHZw7BZxDeMA7mYIJR4Wc5M0kcM3wqqH5TOHZUwncxKIPEsgoIQABSIAWnEHuhA3pf5zd/kz4KZSLu0C84IxDlkBDphxBRqHwHaCOnwoFE6IHEIgYAAABn+AZLmCtNGElQKIXr/6CD6nAO53A1G9MxbwdlHuFiMFYO3cct5hKGyzYthGiIUoCIygR6SSdJXuM3A+BBHSFhFKY8/eWFnQJ1gBiIaoAEZ+ALo1IKBkCKaZhSkKMMxnMR7TU2ZTMA5zAA8gZNfYhPDhGIHGEDhQgAKjArmqADb1AI5gdUipd0mng6BMNfEkhTj3aL0liNAKAKoyIN0hAPauhUz3hL7+Ai0tgRADAA1TgK7fiO9xhEnwiK3laNGOB7/wg8uzOEB3kQU6ACS2ALBrmQMwODAjlvSaM0Eik1+qaQGdl7EdmRviJbHAmSghh9JMknCTiSJzkU5LeSh7KBKnmSM+iSWmKL6JiRM/9Jk0dSdtGokwiRkz4JIxt5kx0JlEHpIWBYkQtolEepIPW4EU2pKiYZlRCSkjGpk0xJlekBk0RJklmpleFhk10Jkl8JlsxBkWNJllNpluIxlGmpli3JlumRlEopjWUpl6dhf1fZlHeJl4RyKz3plyX5kYJJHQ0TmIXZl/fxDl2RQoGoe4iZmGupIFtBD/jQDy4hENEgMUToSVBZmNAXl+TSFfWwDy5yKf9QHgvolnW5kIqZGPAADfSQD/1QGBAReLbBe+cYmaD5mlDBmPJgD/zwHbd5TdmUiE6ll3sJlr6pEloBDaV5msV1Wf8QIrb2h7wJmixJmMgRD5ZZm32hEgz/ESLl+F+HuZxm2ZwYAQ3CSZxFUV0MsQ+7JTWQmZ3aqZ4JoRTSORVIE5/zyS5o+ZZHiZ8GMRjuSRS0FJ/6oljQIFjoyZYEOhDxEJDhGScMcSULGlS7+aAQOpkc8Q7ysJ8ICkoXig85hFLKyaHp6aEWAQ9LsRgnNwwOQlPYaZ/aGZrc6RHxgA+2WaHSIqMnukcUKqBUqZjQAJj86R8PsZnIyS0J+Zk3WoSimZ/0IKIlIT8OwaSkFKCtSZNZCQ88CqMwAhHzJUU8WZxRGngeGg9ImqRCAhG5GUEbqqJ+OZMgaqUv8TBwuh/AI5JQmqZSmqMDAA/1cKDv2TSMBHjh8ZRo/wqoatqS8XCeqcEnZAQN5ZkrPxYRjspgEQmiZFIcnfJD/xkeXGmjm4qjVjeoVQofuSKqviKWdNqbJBQP9eCgoOorEyGfqXKmf3qqP7ky9NCm28EuEnEl8XCpWsKasSqrF1kgMzMRxoqsQkKXy8qszXqrewOtJmomKVqt1nqtYgo8TrOtR2KVveqrgQquPmo/6WIPQQohpeqt96mutSVFJgGkMAKr8vqt9Hqlt3SvMxohXEqkN9qvI8pOy8KZ/qGsBFuwBuuvKLUqCruo3rkPtrqvDvuwjTpTEtukMfEO0MkPPTqd6KpcGnuuKUUUqpmX0HAPn3qwJZt6J9ul3KKy9P8gXPEgD/mApxAbszKrscxVFMcpFCBLD/tgqIfqsyYLtP8ltHwaErFZD+DprEq7tAZLZVNhnRwBD/KADzyrGlWLWv2Kf0WhtQbBmEaLtKwatlarrt6WtZY6ACBbDyJLLGwrtteKen3BD1/rJHeLtxcpfjNrqn8rlXm7lINbuG27MnZ5tYoLuHZ7kM36uCkRuBIZuZQbTIwLl1SbuU+xuV6JrZ7bn+Likus6uuEyLT5JsqgbWbPClzTbuvf1urJbu/ghWbabu4MpJ7rbu7Tbu7aLu8AbvIEyvLorKcabu8WbvMTrt8zbvCryvMrrvNIru9Rbva3LI9gLvWu7vdk7Wt7/a72dG76oO77kO7rme76Z273qi77O0b7iK7rwu77yO7+UW7/2+7j4m7+FC7b86771+r+eG64CTL+nW8CKG8AIfL9uusAMnLQOrL8QHMEJDLMUXMF5esEP3LMa3L8m0cEGzLog/LcfPMISbBYmfMIbm8J3i8IsjMEo+8JKq6kyDMMNW8N4ucI4XLUxvMMxS7g+jK5AHMSnirFEvKJH3L9JvMRM3MRO/MRQHMVSPMVUXMVWfMVYnMVavMVc3MVe/MVgHMZiPMZkXMZmfMZonMZqvMZs3MZu/MZwHMdyPMd0XMd2fMd4nMd6vMd83Md+/MeAHMiCPMiEXMiGfMiInMiK/7zIjNzIjvzIkBzJkjzJlFzJlnzJmJzJmrzJnNzJnvzJoBzKojzKpFzKpnzKqJzKqrzKrNzKrvzKsBzLsjzLtFzLtnzLuJzLuhzKmNDLvvzLwBzMwjzMwVwLu5wYj5DMyrzMzNzMzvzMzlwLs3XMWAHN1nzN2AwL1IwY2NzN3pzMkCDN2xwY31zO16zN47wX5rzOzRzO05zOSMHO8qzMsBC71DzP8uzO9rzL+CzP9XzD8CwQ/bzO+gzQ8DzQ6/zPRpzOCF3OBb3Q29zQ5YwOvNjDAc0REv3NsRAP+3nRKZHR3hwLg/qyEJ3LIN3NsyAQmWrRHn0QJ43NKT0Q9VnStv/80tcc0wPhmSzd0gNh09aM0wPRoDrcysTQD/UgRzHh09AM1BLqnq9c1PfQFnGxREKh1M/M1APRrapc1PUg1XRB1UFh1c6M1QNhrgaNyFzt1XcB1kkt1sxM1mVdNzs9yWntOr/B1irh1m99EbC6yXXNHnj90XqtzHBdELx61nj81xMS2CMx2ITNEXMayYqtJIwtEo6dzIVdoNI5yAo42X5S2SFx2Y+Q2QXapn9cnJ4NK6ANEqJN2mcrqXscSvzAFq202h/R2iHR13ZMpvtgFa0kF7btEbgdEs1H01QMp1FNEL891fF82a6dEJHtxnjUD2l1EMvtDsHdEcMtEhw9113/vKS97Tpy+NvZjdHOrRLwYNpn7BD+kNzYttzljRHbPRL04t1V3BBcbSzXHd8XMd8pMdNg3BDD0NvvahH7jRRtMAeKMNjPzRE6jdgj3BD+kA9POxIHjhRWYAVfAAd/INYNzhHQ8B1ZPJ718BnsBt9OYQVUkOFWwAVpkAcL/tIfDtmnKb32jTnQIQ8FLhIXHhRUMAYsHuQ/DgeDANIzvrUv+728eybRQOEea+AoLhRt8AiKkAdpwAVBzuIungcNfeQfGpA8PLg0rCr+0NXz6DxRHhQxrsx/AAdfsOJZngVjQOSQMM9e/qFyDeGN26zEAFh+zhIsQRZ91Q85oVeGjld4/3UP/LToN6tBaZ4SVDAHzwwJijAHaJAFWZ7hX9AGXL7Od94R9NCjcikuw9AP+0APnjFWudLjbX3NedAGX5DpVpAFaKDg3/zpHRHixv22khIN/LAWbfHkmPfoeX3NkFDnjzAIczAGmJ7lVLDpHX7TiOEatgm7PKIZnOEZwr4mrF7s5lzlbYDlLE4FK77la77XP2KPXnohvg7sGRpE3S7Y8zwIcADkmS7ndL7MuP4R5iqTxYHtnWHiKRXvjY3QlZ4GzZ7lXMDpmH0a78CVOLkY7c4W705TBG/ZCH3syfzqsX7vaTAI/3cYob7rQIUmXS3wzHXxrA3SGp/scIAGsn4I2/+e6+regX0xDBQuraql8sLt1lV+5RlOBWig81iR3iT/r31RJJ/G89qt1xrf5nDQjbLxDvVpkX3BKsvG9PIt2o8ACbFA9HQmWGKYJ5uCcFpv3ufNHN2t5+LaF2nCezazOOzQX5XjLfytEFy/70T7iU07FTivqFLzOJPIMyr2DeAgNi82DoqvM1cjY4iDOulAY4qzPHPfX/nQ3I6t90ih07zlF0r/aexwZBszfESUZlDWVUHDYk32Dbnj32qPGVnlF9FgD6M6M85QPlijRkJXEGKjDByjNc1k+sIPNI5V1WkvHkbP9ozSF8RQ9v+1DkfGM8J3ELY3MOpAenbhDP1iMzf/ow4YE/mS+PhIRok7o/i+Xzhi45jyzuD2QfVHfy9u7yAzbz/9k/vVZxDgMA6cyAxxSGwA4U7gQIIFDR5EWHDfAIYNHT6ECPHRRIoVLV7EmPHirIgdPX4E+RHasH//Qp5EmVLlSpYlXb6E+Y/YPmgsbd7EmZNlO4fhBnTr1tGbsnLm1DlzBzLhUqZNF+psqFHqVKocoV6FGM9fSaxdveKMGbZkP3nweH5Fm9arN5Dhxpk7ty6pyqZ17Q58epXqXr4UrarV+W4fV8CF04qNGQ1fPMONHUNcxxAcSHDjBpxj5kznXc5M80LtG3rq38cs5REjXFo1SsQw+UF7t1o2WnYD/5QN8Ma247kBtb12Bn7ws07RxTGSnn0yXrTUyZ23dumvHrzYzq3fdJYO90+Hk8s5Dh4eb1fj5f1eRwmPX3P0jqHLzFez/fyT7dKRC+rw2wDtqsWLHy4n88xDjj6I3qkHNQMLey+a6RaE8CF3mCkHHKAa8macczST7b/wAsRpQOMUOSVCj6BhzsSu3iOrOhUNnLAcnxzqRsPrPAwOxJtEFE0RQVD5xhwOX2RIK5OIvAm6meJxEckb1zEnnG90+0kZc3y7EcfOdLSJx74g8TEZMb8pB8sX38mHPSc/gs5B6tZEj51zbsutoXDMkYs+Lbckz0u+IvkDFTF/8oYcZpw87f9IODuCzh953mly0dWcOceyh8Ap51AI9+SMS5b8DG2WdCxlqBtl0jlLxeWIkfQh6GhqNbl21CFnP/3IQVVFTu/ydCVQ+5qlnQnJobKbcM5JNUL1FF20tWHseTNW/yiczKEMN0RyV7t6VelXvv5yh50KcfPGWCFVRJBZJFvzhx5IpS3NHShnbMjUc9fUti5uU/J2L+TcccYccHTrhkwzF0RR3Qhbew3eeKG8jUYrD3YyX6f67FeqAgdwp51z6O2mUE0hNFJFxIZZzGHw5CS11HAyhddizzDOOKONGRJIHWWKHae/BdFUGD3EpINHZcMAvo/KnzD1OWaZE9oXpZo1Dsn/HXXGKfbUZOc7jT7EyDL6aFptbegbXMPG+WmEoj5pao1uhkjecsoNylhsDVz1OrGIyYcxtNMC+OMpMdRwa6PVXptmtyuCO6JwzSG7G3CuNFC958Jy82/AKdyPYA3ZiRRtxIVTfPGJGu8I4CgJJjOy+RD06r3WWtQcLUojLhVTdgzXfHSD2A7J9I1uesedOXluGr1oBpC9eedL4tvv2ruSe+B6lUF2esd9Jwh4kIS3CPWqmSFH4lxfhweeeOKBBhp55KGnHnvwyWcffvrxx59hSHr+pcy1x4p9sMY6mAGwIe9I3/q4Nx6sgI9xV5Ebd35yrCFJK4Hsax/86GGP+e3D/374o50BN8MOgUnsXq1CoPoyCL960O+D/ogGal7ij3tAg3ve+4gDz4OVcI3rJ5IrRwVFOESoCLBYZlNH6K6DwPVlMH7zqx/+osGc/sGkIdHYx6OKJzMcekSHp/tK4GaUm9YR0Yw2eRy9qnTC+Syvim98CUSIwQ96wMNiXezIFx8hPjR6DHe4MdQZBamU+9CoUOpYUNEgREMmcQqPEdEjH3HijlGZUIiDNKPqwlGsO1EMPfJRUTTiY0cPPVIiX5RkToaFodzgineYrJ3ValUnQCbvdfUIWoSGQUdS5qh0pkvlCH2Yu3K4Dpa9o9Qm69VJE2lFWv2oRzyAY8qHRNI/Rv9kSG7sdcljtkpuZKvS+SD0DnqwSmX+iM8WL9ZAVM4mXB/TTW4yJM5u4ut2xcKUMZXVj1xKC4taXAo1HWJN51SPRpgaWT11tY5ygNNU2XtR1wzYD3pIk3Ts1GEwAYPN67FRoe3pWCXrlU8kwWMwZ5SODbv3y8VptDBpjGcr6fnRDtlnmFWCKJESBktRQsOOAo1KOxcUI3AO4GX6pGlj3lkrGpEpoS+CR5r6acZh7MMfLHWbS0vDUW1aiZtJhaC8zNGyH3oVTjsFK1anplX/kFCZQZFpWiE4KxnRsqzmYIYSTYQgBckVow5ka4eodakC+jUlSLspod7iSSIZaaqG7Zb/UOEkwHoBxUqQ9YhAWFZUyeHqq0QiZ18xCxrJSkpOyiTXPF+ZVIEwwxzKuFCpzIVIeMGDn48dLb9K683BdqewrM1OYkM2MaMlCre5ldpupeUxstpmAE/F5Dux9pDOpuOzizKpmpAbIuU6TE7boVFDzsHY3on1jz98GW3RljDtbrdL3VWZ1RpaWXINoDIMga7DQircDFFOc/DAh0vcq9aaBRZJPCnHeX/YE3KYIx3smMuipMtZs92tdtDYynEHrNuMnhGp1qJbUL5BlHMcZagEaYdrzwuU9K5WZelq74Z3BF8ijqyodrXvOMqRDmZEWC0FccY6mKGOc5zDHOUgxziU/xGO2MrWSvnVnGM1LOPkdpim60iHOcjBZIiwRcQkPoqPT0IQdgg5HUY+8jjGEY7JNDk/ESkYOcZLxNDGmMoztrJcncGMcyS4Wh5xC1zWISyBBJkZZzbHkcmhDGX8mSVAgfQ3XjZTA9pWwHf2CkFzy44sb7lcXWaLN8IBsvqW2iOQLlg4lDEOchTlHOlQBzN2B0vjThnTKKFBrnW9a1732te/7jUZWCHjPfd5HBYCMUggLepVtxouJZa1i4+ZXTvf2iYdwHa2tb1tbnfb29zeQBCacF3kskMdR95ZpN3SalfzeB3kxSx7bW3tk3zb3vfGdwimUAhF0psh7WAHuakM4P84+tsrckB4whW+cIY33OEMJ4S0DU5veU/8K5q2eMYBLMN5Z/x7NPb4neXd8ZB7EeQldy/BL41yvZyc5aMd+cv/Cj4DyxyWUbXiy1PRcgdGouY2F2TMgc7zxVUiFK0ABmyGPlpqF3zpApoaJDCRCl4QQ4ZKf7pfR07yrFezX5XgBCyAERasd52mTa+22dsGqqnXguNk16vag86/lcsdz+aJRNh/0Tx/8GMf+cBHPepBD3m0b33pi7vdLbgepyv+7qLBhChqAcfmESMa+euH3/Fhj8ET3vDxSB9OUnhBDK7wffSIn+Dx4UIP+r0sjm+IPOiedtjnMDR5h8XeKb972Q3/4/KZ96D9+HG//MFwim+PCfLD0pE51jHxMl9Wzmv/eI1EfvK8x372KZ+klHZd9tKfPvUrkvdW6F7750c/+Ff0DxqC8uWWVn/4P3UR6ys//fevomxK0tN+e7zWtJe/j3sE8uMFV8G/A0SMBXGJqnq9iYsHxmu8ALyJtjMnrMg+InIJYqCo/ruz74s/CVSJkpAGaVC8GYomKouH24pAEGRB1pihe2AS5KqzD2zBGgwJmOip5+umFFw+G/TBlYgJBnwXmprBFfzBIzyJ5OMlhZIyI0TCJ7zBmIAm6TmjInRCKMRCNgkL6YjBIWrCusvCMEwJsdilOtIeGIsJMVTDlhga/3soO5XBsB5cwzkEQsTQwIrSwZ9xn32gojSkwz9kQ8T4Jw5MJHmwh36wvysExEXUwtmphzd0jneABnrgw+ZhxEtMEugoQ0I0jHeIB3nAhwx7HkwkRZvgu1ECDHiAhnqoxDcqxVfMxPdovi7MCU+Uh3wQxe2DxV00xeYZxJVQxXpAROzjxWLUieeBJkg8IPfJhz7cPWOERgt0HgakDlW8h2HkvWjURrTon9nTxW0Ex8NAQAAMx3LMCfQzx3RUjW9Ux3ZcR9lxx3i0Dj+Ux3q0x3vEx3zUx33kx370x38EyIAUyIEkyII0yINEyIRUyIVkyIZ0yIeEyIiUyImkyIq0yP+LxMiM1MiN5MiO9MiPBMmQFMmRJMmSNMmTRMmUVMmVZMmWdMmXhMmYlMmZpMmatMmbxMmc1Mmd5Mme9MmfBMqgFMqhJMqiNMqjRMqkVMqlZMqmdMqnhMqolMqppMqqtMqrxMqs1Mqt5Mqu9MqvBMuwFMuxJMuyNMuzRMu0VMu1ZMu2dMu3hMu4lMu5pMu6tMu7xMu81Mu95Mu+9Mu/BMzAFMzBJMzCNMzDRMzEVMzFZMzGdMzHhMzIlMzJpMzKtMzLxMzM1MzN5MzO9MzPBM3QFM3RJM3SNM3TRM3UVM3VZM3WdM3XhM3YlM3ZpM3atM3bxM3c1M3d5M3e9M3fBM514BTO4STO4jTO40TO5FTO5WTO5nTO54TO6JTO6aTO6rTO68TO7NTO7eTO7vTO70xNfRDP8STP8jTP80RP8xwG4qSGaXDP94TP+JTP+aTP+KyGYyDO+tTP/eRPYSDOarCGABXQASXQAjXQAx3QaxCH4qzA5wwIACH5BAUFAAMALGIAFQDoAWsCAAj/AAcIHEiwoMGDCBMqXMiw4L+HECNKnEixYsOLGDNq3Mixo0eEFUOKHEny38ePJR8S89fv5El+MGPK5OcvmsubOHNqTMkzpM6fQIMKPdizqFGeN0Wu7LcPXz160KDFgzc0o7urWLNifQcPmrx6+GhWHUvW4NGzJsuqXVsWrdu3PR1KjMZyn7168qTGY+tRq9+/W+HFk0cP375+w/gq5gi36OLHkHc2nkxZ4jB//JxClUo18k3AoENjFQyNnr19NT17rpxStWvVrGOfjcb0KWeE7V6fFM2799V38fjpZiub5PDjbYsrn7iSXz68Ut8hJ+u7uuh808kuF5m9O87tsmnb/6Unb6p3vtbT/8V+Pih4n+3jN3z/tvnzvPGky3+svj9W9vt9Rx9FARY40IBFRcMPXuYZ6Jp//gHooEcIEjjheRWWNEw/9pR34XEQ9ifhh5JlGBGJyJlY0YYd7oUiciGqN+KL86l4Io2R2RgRix7imF2M6c3oY0I63jjkWjry6OKR3QFpnZBMylXkQ1FWpaKSVcbnZHVQZjnAlEZ6mRSCWIop35a+dZklmGGaydh7ZboZIJq9qVklm23KyRB9/tSzpJ4G0smbnVHimSegRG0XDT75IXqhoNc5auihjn65HDH7QPOOfpU6CGlohDI5KaWALtcPPZ11+uGnoIV65Kikmv+pXDR+qkojq4C5OiSssa4ZWzT5QGOrR86www4z6qSTzjnmmFNOOeSMo8y045RjTjrMOCMUrutJyitEpbJGDD/ycDpsO8auk+yyzT4brbThgNPNvPTWS5A393pD7zfKVHttti5x65euPn7ba8GV+YOqreuYAy84+tY7rzcU60sxvTfRe/G8/PqLrbYYCawVwTgafDCKlUVjz5+OMmNOOBFLbC9C8w4ETjjUkvNss+coq8467KjLLDnKhFPzADJ3s3E3HVuLLTsIiZwVyTQOiJlbvsI1TLAMm6OMxAQxfXO/5Ohs7Tk9Yws0O1q9k1VCWqGrztDjwJy0xjF/E47O5pz/ow7bUl9F9YsDthRPP2gVClc/5arKTDl21wtOOT+z44x6BF21EWjtCG0O0UYnvfS+ypSTDuC4Do4yfS0JBI0/Z+36Vp+ptgx5xfROrg5vbPXW+dyfF3230hHvbU62kKpOYuEFQRPNUSWjtWijlT4eee6m+wVjdXLTfb3E3pR+DjNbKv8h8wW9Q88wRq1+FKaamqunOpArXW845ZCv/XnWEeSMOp+D2N3AQQ5zqONyEfLWe1pnEHjYgxiOudBZGLep6t1OYvhLB2AC5R92pKMc4/jG8PA3vnY8SYHgYeBB4IEPCCLFQEdRGcvk1A76wSxm3QiHAQcAmlVBqB3MOAc5/0I3sZiBo1rpQCCoULgdFSIkHvuIS4CKMi5NOaqG5fjG6HSojoFsEEcxYgcAx4FD4s1rbyXsFqLQx5DDvbA9RaGd/MyERRFicIde/EuWYtS5c1wwad9AIurMJ0HWZeR1rcFQSuB3xXSQQ14SU8bxCvJFN7mDhxDyoNfsiLczluMcwlqjITXivJJ0hyenqp2b2uFITtJLkus4SCXlhCYgCvF6S4NauBbIEfWxbyTTKcn0WkYOV84LllHTo6Mg5TZnpMNhriyHKHnZEXjUw4XceU1JKEhMmUlSl7JUZqWkFkRr1WOaKTwJC7FpEdiIhFbwmKOZ1kEOHCITbrNcZuDcQf/ICbHxI1DMZo4qgil5dIqeMfNGOWK5kHyOc5/9dNA/T+LGdi4mJApTpZ7YUY6EkgOc+NzfsDAZuIjCcJQ5QaRFkcScTKmKo64kB0MV0sORCmSf/GSiqYJSyrechCLc7BRM6zWOmYZUpDYlqdRMWqCJ5sSXYBrmS82Bw6I2xKE2xSlTp4jSoFiTnRXihxVV5QyqEpUZVxVnUjMHUZ0qx4lezUeFaDessrpyHF1kCFY/Iph4+DUqgM2LPAZLj8LSox6IBQs+FruPxu4jJv3oB0vo0o96hLIqWnVrceAqlHjkIx+LXWxiEVvYpwz2tF4BLGD9ylrBuBYeGnVUWSE5r3H/pCOtanUJPPIBVjjxgx4zxElm0dnEAuUmIce1VTteVi9l3Ba3SFXnNacUjX3II545Ge4u07lWEi33es69yF478g55PG9S/sjHdQPWVuLutLsTasc5wJuO5NI0ty7pKdYWkpZEkSS90IgtdEW21f04Fb7tkS8Ru6GMc4QMvx95XW8V0xNiVHas4m3vdouLYPko+H4OznB0KcoP+FC4KMP4LfXuW1LNyoazHUbOOb5Gr3CEeMBY0YlngfkY6VkXu+FssXvfGmPvzBjE9m0ohKs5XRMPFC0AVqV29XTgIqsmHTQ+ozmssuRe0qO3EtFNYyxsWelMWU5VtvJjsHy/LT94/8QeUd95BSrmyYwLuELe8HvV7Bk219jNItaKTvRL5+GwZgD+uEd+uFXg+CAIxnwui4KNaI4kKxnOHYEG4hKZHcoQRGXQYFWjFZnmSA9ltpIzB8gC/Tac7PiNp2zMQYClKTqN2jsVgrSpgbKOctxx1TjWHE7WKUVH+zQh1S2Xk26N68LleNdCUQc5InkOYAf7kjf5agQNvN+FFNRtEGJ2s8HDj2eiDto5kW+Wa6sOS19a0DeB6rabGjuM3BkeInIxa9TRjQF4gxwafDa6OVLWBSvUqKwWuEvMW2+JQm8jFkbVCYcsm3fYS4dKHHhGeu1KcJgDpAkX9k1U+vDzzZsjff+KR530zRpokLGI3yCH/kSu8YNIG4PncLdeu6yRijbcfaa8ScqXSPEXD4Ad852YQCSZ8ZoPhJXjiORzN8fzjAS021XjNE4SveiRsbwyDIR6xCgW890pfNfOSLrGyJFXqmN6I8TGOsJ4DJRF1VpwX6cMXNlhDtr2u8EmpLmaOer3yYGcy2/XyPpkrbhC1x0fmhJ3rKlpEKjba3LraHWMe700jPel6hh5Bz4mIybHCyUaNik6a0AhhlMcfiActxfgz25TdUS9uTn/fOI1Ao8SM770K3U6kcDTBwIgQApvsHZB0r7uAegQddhW7pGJ2naOjJcj8YDd791kIeEr5D0YML7/FKRwCuUbpNf28oZtNY+o2eZtobq/PinBXHIqh9n73wePBACwgPGjAsgLUVbrlkMfx35ign5t9nrXRnsnQQ+V0Skn43TvoQQE0H9S4AzypBDSFjMDUHYGyCQ3h3vmt3Oh8RPvEEWepirggn/Dtx2+sAQw8Aan4BF8t2AD0GBKFH004kHlMIB4pXMsVoI/AQ/aR3oj1V8saBZ8koEZYXkY8w3584EB8j8BZEYTA38a0RudNWfbl4QdVmobwXd+d4M5B2/tUU4DKDnlMIJHVVNCIQ+H5oVWBoYcoW44NDlPI4WesQ5+pAzGJDkF1G6IJ4RD8Q73EIdyWGR06BGPY0cU/zMQ/KIzPYNwfKFJ4wAxuFMvgWQ6ChiEblgVvRcbiTiHXRUUzCczA3E0esM36bAObHgStvRHSUNCzACEnih/OlaEKTiKMbaIN+Ey0SJAGCMQj9h5/jI+ncgQaDg8OVRAtdgRvsEX0PBLD8iLiliKatE9wQMxBjE84KAMBeQ3CihGDlNGkiNIH6GFi+GAomiN10h5nuEOzsAMzwQt4SBCSCMzoxOJn+QwCwY+pdOK7MU7i3GCsuGOpAiPrwFuV+EM61CPQ/SH+miOxvOM8UeQkAEPm4aICNlhRZAI0sBd09E2WNE9AxCMd2M8BzSI/uEa8cCF1diRCAYANBkHIukdvv/zkH50LZ2IK7oBh8Uhk0VGkxxwk+2BU+kxHO9QD8ohlEMJABwQkntWIEhphtMRikHplDFGk2pglJ4iKBeSfU2plTH2AnEglVNJIv1zJNO4HGSJYLn2lkHBjmMpl2sVl3aJE+8gV26Zl/Dli36pEES4HYH5l9hYmBjxkoSJmHd5mIy5EEC5mI95hI45mQaxlPRhmZSpkJrZQL4nmZ2pgpXZmWIJHqG5mV55moRWl6cpmpzZmUtJf+3Ymq4JHrSyYpopD7oImrRZKRmSYgvzmJqGIL05LDoSZX4ZHBVSnMY5JXeGmx0JRbKZlcxZm1EVLAKWhCxkItXZnKNCZpelnU3/tpzdaSsm8w/Jlp2mJm8ZUp7eeZ7/0CcYtp4MZyPuaZ7waRm/pZ5rtZrteZ/WmZ8RgZwIRnL2CaABKqAS8ZxMCCg+pyMIip8KShJ2x59ZopxgEqESOqEpcWENOiS7hScauqEc2n36CVxZEqKGMqIJqqD8NRG0ZqEBom0ryqIQOKEbQVAe+iHsKaI2eqMGIyAromIFUl4wySY/2qIQOhT/hZ3t4Z9ImqRAuqQsNRLg+aGLMZy8IqVK2perkRLAGVyK8aCjwqVdypF1xhP+AHky6hJcAVt/hYLfYqZnaoSTxxNXehBv+leBRRiIZQ/4kA+NxQ+R5Q81MZ1zSqe+yZqk/2YUdFET0YCoJVpsiqp6cicfkxqllZp3J3dSmaoimzqlcBE9n0qcobqox/Yqpfoepyqq7eMlq+qlrWqppncnsTqbs6pnxoGqtzqqucqpVPKevfpzv4pmQZdUw1p/xWp/TmaYyXqsy6qrwapmz0p30aqr6Fat3XetGyaB2rqC3BouLPitSBiu5kohz3qu6uoSw7qu7vpTq/qu8ooSmTqv9oquOHqv+vom+bmv/sqvJvOvAlsiWzqwBosRk3KwCpujB7qwDguwpvmwEkuv1DmxFkuxXXixGouxnbqxHsuuWvexIqsTzTqyJvsT03qyKruyLNuyLvuyMBuzMjuzNFuzNv97szibszq7szzbsz77s0AbtEI7tERbtEZ7tEibtEq7tEzbtE77tFAbtVI7tVRbtVZ7tVibtVq7tVzbtV77tWAbtmI7tmRbtmZ7tmibtmq7tmzbtm77tnAbt3I7t3Rbt3Z7t3ibt3q7t3zbt377t4AbuII7uIRbuIZ7uIibuIq7uIzbuI77uJAbuZI7uZRbuZZ7uZibuZq7uZzbuZ77uaAbuqI7uqRbuqZ7uqibuqq7uqzbuq77urAbu7I7u7Rbu7Z7u7ibu7q7u7zbu777u8AbvMI7vMRbvMZ7vMibvMq7vMzbvM77vNAbvdI7vdRbvdZ7vdibvdq7vdzbvd77veD/G77iO77kW77me77om77qu77s277u+77wG7/yO7/0W7/2e787iwn6u7/8u7+igL+K8QgCPMAETMC1QAwAvBYFvMADXAnAkMBlwcAS/AihAMERPMELXAsWXBUYzMAOvMFD0cELXMEgDBQizMAaXMI/ccIF/MEqjBMsvMD/+8IwHMMGTMMuYcMt/MA4/BE6TMAk3MMd8cM3LMQcQcQNzMNGnBFIPMAzvMQY0cQDnMJQ3BBSLMAuXMULccUC/MSiG4G2wsWPEAlU3LnB12Fi/AhZjLm7amVp/AhePLmUGmNvTMaSS6xo/MaYoMSK66tu/MZwnLgxWWSAPMZlDLgVS8eF/7zHfxuxf1zIcWy3pvrIgGzHdQuqalbIA8zIcVskfKbJTvy2mkrIoGzIalummVzKj4AJiVG2iUrJoBzJXXuen6zKkAAJh5y1LprKtszKWhtD/GAPUOFarFXMfKpaqiVYqXVazEwYpVVY9sAPrazIqtzFV4unmAEdGQiEudHN7AUc8mAPutYp1SzAt5zLTUuh/ZAP5CGmkfEX7+AV+5B6w1LO5uzL6RwSCtIhAXaUotEV9dAPCFwp9hzKSssc/rAPDIKl2+Mb4JwP/gAoBf0It8wLA020EEEb+DDMDM0//tEV9MAP9FwlEy3A+Cyx25HQC93Rc+Ikg4EP/nDRPlLSAv+cCtKwrxWyEuzcz2LCTF6RDyNNIjQtwLzwrr/ZDxsNnWYiMADNDzJtIEP9CAd8rSqiIJblzrQUOMBBDxEN1UMNC7lqI9VlWQA4UlUpHF5d0rj81D+qIzo9zEV21g4S1WBto0WyIezcIHwm1wYyBzSNyxFaJLTRIjXH190xBwOQBQbBBXlQ0rCQssUp1vsA1/hn2AFiBZiNBoMQCeW81pB9miaSbFhd2EiJ1gWSBZhNBVkAB/b82ODamRmSXuVhi95n2fLxCIqQBpiN2V/wB7Z8wPf3mAiyEmzK0sJn27f9CHnwBbttBWmgCKXs2sEdmPRhYffA06qCi7tR2nN9y4//AAeojdlZ4NeF7NkT4ZfvcaXGPSRV2d5+YdoBUsCDgAZWQAVUYAVj8Aec/cbSva1CuR0pVmad4t4E/hfwvR8E7N15wAXN3QbQLcbmfca8uBzVBRUPBRoOSY/MAi1nozY5WOBbcuDJvcCK0AbhbQWMncb9LeFJOCuTPdpREjfroOHOAjoSeTfegDPV8kl+wwzsEHggXh0iHh8SfMt/MAbNrdlXHOEli3+yIdswPiTo8pDP5CzSAg7dmInMiOOApOPPgjbq4OO2iNxE3sFzkAX3bQWrfcUrXqvZyhr+YA8Btt4Bgi7IsuEg5If30o3M+I3jUEDXwi7PcuVbDj6zSDYd/+7jHy4yQ94eIgwJJZ7mVtDbSMzk1jpwlRFxUT4hSNeDftdvCyExHcM3Pf7jGRE0ybLhoPPpzKjlx/RJM8ctjX4eMbzczf3cRNzmlx5pmf5jUeJMPQg2R2MQevPniW7qx0XnuDEQ+mHn7PI5oGOOw7OJp8Mqs+4dLOzd4L3b463Dlg6tCQkXtKbsCeYyUTc6/Zbj4Jjorngc8pThgh4tylBGG6OSiw4h194dPzzfzZ3f+33Cug7uzgoXXEfu58GHlwhI5DA+i+4jsfg9kfRJ6wDk/ZHv2eHtkKDcDL7bDn7C3x6yNqV3tXIkwH5DHBg+BkTxe5QV8/g5/1gvKH8Omf+XHhY/HU1c4iee4iIc8LBGomdxb0dSQ14j7Rn04UsNGjwYQt44DgZ07++d1kR8y4OA5Lut5BP88XMMrPpsXQbfHQ1TT0lzkufADgwpeF5SHXwY7CME6xSfFTU/HG985mmeBW2AwTyf9dw3O9d9JEj3SOgeSOMDekzSH1Q4RDCfN0g081fx9q8ByJDeBvdt35TOwLMADXx5qbDqFvI5JCVP9JTT9mavJ0CS9MZU74GIDwWiyba+27hewLMgEPCgm6maNUah6Q5PP/NuhZ6URGXPgIhCJ7Y0RNLeDeAADWxN62ms7Sfe7QT8+gQRD/dwpHifdbXv6zhi7lpURgQ09oT/OCy44kwO8+mAhuCaPAi6vdv+LsDOnz7Q8JkduzwxFCxdfxzO9EiAxPSKr92AEjhpPy0AIW/AQIIFDR5EmFDhQoaPHD6EGFHiRIeQID3Kw8XKRittFD2atTBevWj/TJ5EmfIkQ5YtXb5cqFKmSn/14r2DmVPnzoPpynnrFlRoN2Xm1LVzl1TpUnc8nT6FupPpVKpVrS59l5RfVK46KX4FO1FRmywcueSJ1RJavplt/3WFq9OtzGj75MHDGVevznXmwg0NGo7cOXZXk+5FnPilYcaNp24dkCeL4r1hLYe1+GcMx47O2rWEJ8/f3JSUFZNGOYwfvZumXR9kZ04ZYKLn/9YNYPxat2vHvRtDHkBlAJpIu51eRh52ThYqG9M4gxkP3zDUb41DrU6MXz1o13U7SzeOdjhzzHAb9p5er2/2ViELHwhJPczk9SdCUpRm46G8MN/J44cY1OZ7iTRi+uGuPwL3akcdcr4BDJxy0hkIvQUvdKo9DZkCDsOX7ANRoj/yYOepkUoizUODSPMnH2jgUXEvZsr5ayhvxkkHutxi5LGlDX90p8MeFQqxyIpm+Qyqd9aai0e36rpLwSGf6ms2oIRS5hzozrtqSi8TAnJDIb8syEgj04ILHnpGm8nDmaCMh8yonDlHPMDIK5FLq+Tkk6AwNRyTTzOLDGkvaKZrU/89mYbZh7U+n2onHXKuFEpC8yrs8tGC4OEUnng+hSZUaOQhlR566uEuTt3+bC9QOQcNsVDE3qGnn+qqcyol7WySUlOYZgQHsG/IoRDTPdWDZ1R5TD21nnvwwWcfafnpp1p/osGWultVIsaffVLttStW2XOVTFhBlFWxE7dl91Z/8HnRV6f6qlGoG7X0M1Pv/ttHwHb/XVGmbvm5Rx5owpVq3N7K/fJc+9KlbMkA2yUGW4svxjjjaPx5N155eWLnnNkAKypPPatKj19t/zWpKxa/lecmhBlSeOGPHa4P4o93Rgw8O4cKp5xLjUV537VQVGnBW6PhBx96PGapZscY9hL/5+R05jlrqBosB8KhhlXHIH2vkw7p0pzcNpp+nIZabKkZo3pKq5GbRSmt7+YJWEq78YbYJImmKr147jE7aS9ZVpttvE5+m6q4h5z7srqZwrtyhbgOZ2+izNky36LJtqdww/lk+aTEY268qsd7jNyyyaeyPHbwyAHHm73xdPtY40Zis8mPS7dumH7siTL1IG9uHazXP49dXjoftB3ocm7LnfnX1LQVV60BPqgu7uCRenUek1ce8MCb5zPkSccr7yALd8N+2+blX6jbfFjLKkzxYySfokNQGYdtzEc59A2pSprbnMkK8r7ryaNf7CogQVL0EuERLx5iQl7/IKIIQSTD/4PdCFo6kMLACKqHGbLhG6XupUDPWc80oXkgBEsYMJk4hWnfs5m8NCiR/33QXuMwxzp2NEPdqINGmhsWvtxHwoitZWUyJOJBRgeVuuDvKvtT0Q4hEolHxOIc5QiWvYAiGC2NLYpxwVz0hDKsHCFkiK5ZUj6eCMUzJmQleukWPlDHoQxq0SGxSFJfxoFAbxRFHWas40645rWhSEiEbnxjxMoGPOskkkDCwyEWPeRHiOgMPEekDTgG4wwXWpIhs0Ng0I6yxMboRk2i454pPXStPvoRawTpy/qCokZDjpCAskRIyAbJvqEtsJXwIwklWwZMZsaFkw+5pUEiBUphDYAw5/8DpiBpsznqVQ+RL6zHHEvXTHJ2hZNyYMIOvMAKmAiSkUPpJezqeMLM7W2FkGTi9e7hL2WW059R0aAcwLADEnjgAxsIQhM61xKcNAiFtPlGAIW4FPQ5Yx3pMAc5lBHGrwWQhYwr5WviwRZl3vGfJ91J6/wABiagwAMdgClMNzCFQsDIKcJ8Z1AGoIxyHOWXmmoHMzBajo3aaG+OXOgAsemdkfKznyiFqlcc5gd00uClMY2pC5gAhljYNCoOzRxEJUrKn8ZoHer44jjqtU3prdKbId1NPCZW0mVG1a4ugVVVX3rVmKJgq354BCQQgSa9qI+jOiXIN8IxDnKUoxznOEf/2NaR1NdY9BwZLSpbG6kMcpgjHcz4Wwu/Sbbs0bWSd0VtQ0Ik0B1soAN8hSkJdgAGOUwkmlwJ6kONOhBvHKQbih3HOBwL2c9OFioWxahGgxU9NQqLs+Y4BzMoa8xIqgcapTVtarWrWuSslAkkwGpMPUADJtS2fK8JGY3WiliCsHcACAyMMhhbDuhGlhns+Fs7LprWtTbXRot9rDo+is/qWrd32d1ughNiGe/SILxZ3WpguRiW21KGHesQ6mUzqtFwfKMg7tUsRMMR1hAHBRzC9ew6PiOlMKnoPwdGsIJlXCaKVJUELg2vC2brB0hEYsKSG5I72sEOZqgjHZctBznG/7HR9paYrd94bnR1lLoY0QqWJZ1xlgkSEda6FrYdkC1tH/Fj5ECCE6mARmiD7MulDPmiRzZHkne6VgCfYwCFMR5Fq5xM06JEy38ewCO8C94Hf4C85gVRJULRil8QgxgH81VvhozfPJdVRfDgc59NCugZu+DBMD20Inpsn0hwohW8cOo/IM2zSluaT/DYp6b9zGktP1irYBC1RS6CnEhgIhW1SDVKVl25H6EP1sHuM63/DFO/ggGwuq6PolsBDNQMG312s+RIZX02Zf8ZsCEqdSpQvS1rd/tC8Yjhtutq7iyDCBOigIU4q1NudguOH+rmdr1njBxp/0KZ9Na3bq6L7/9ZB7zdX+n1r5HNMoAbPDHxWBPBN+1wGU/k3bBYOCVb9DSvUjwuvMu4pj2u5YeUmtEST0niWNPxkUenHjCWeMu1fOZxo5w03ouZzEXycpvnW+cJ7jnLhHe/tnl8kkGf+M+BjnRKMs2CM9PyO47O9HUrXcFUN223vvUiqN91SaHDetKtvvSwa1rl8WA5VON4ZaSP/c9ll7jWU/VPlcFd7G4PuN0pObB6xKzrsYOhvMOOd8KzJJYIOS1M6MIP4jU8azAMOdULP3lNtUXlRdcU5PU+Rcp3Xk437wfRF/el+G2e855H/eerozbR/x2OnqqV6ROVeto/imLe6ntrXvKOToH/KlSlatY98jEta10r8qavffLlVTqt2wMfw98HtfrBsWGwXfbJVn72l3997k9Q+9/ffvfFf3fwl1/145e9+dXPM/Trff3vZ3/7mQ5/+m9P/jGvf/6zdn9Z69//d+O/p/q/AQTAAKQjAkTA/TNA30nABqycBSQ/B5RA+xu/CbTAKEK+C9RAS5K8DfRAYCK4DxTBf6KrETTBqDrAE1RBqHKLFXTBq3vBGJTBGaTBGrTBG8TBHNTBHeTBHvTBHwTCIBTCISTCIjTCI0TCJFTCJWTCJnTCJ4TCKJTCKaTCKrTCK8TCLNTCLeTCLvTCLwTDMBTDMSTDMjTDM0TDNFTDNWTD/zZ0wzeEwziUwzmkwzq0wzvEwzzUwz3kwz70wz8ExEAUxEEkxEI0xENExERUxEVkxEZ0xEeExEiUxEmkxEq0xEvExEzUxE3kxE70xE8ExVAUxVEkxVI0xVNExVRUxVVkxVZ0xVeExViUxVmkxVq0xVvExVzUxV3kxV70xV8ExmAUxmEkxmI0xmNExmRUxmVkxmZ0xmeExmiUxmmkxmq0xmvExmzUxm3kxm70xm8Ex3AUx3Ekx3I0x3NEx3RUx3Vkx3Z0x3eEx3iUx3mkx3q0x3vEx3zUx33kx370x38EyIAUyIEkyII0yINEyIRUyIVkyIZ0yIeEyIiUyImkyIq0yG+LxMiM1MiN5MiO9MiPBMmQFMmRJMmSNMmTRMmUVMmVZMmWdMmXhMmYlMmZpMmapEV9wMmc1Mmd5Mme9EmeHIaYnIahJMqiNMqjRMqkPMpqOAahVMqnhEqoFAaYtIaqtMqrxMqs1MqtzMprEId3DAgAIfkEBQUAAwAsXgAVABUCawIACP8ABwgcSLCgwYMIEypcyLChw4cQI0qcSLGixYsYM2rcCPGfR4/EOG4MKbKkyZMoU6pcybKly5cwCX6cSZNYv3rQ3sV0CA+aPHv8/HncSbSo0aNIkypdKpGm06ce/eWDBo8pz3jy6O3zR2ym1a9gw4odS1Yk1LNoo+2TB09nWYfvetLL12+Y07d48+rdyxcj2r9oh/GjF89t34jw4tGrt/Xj4ceQI0veCbjyX2KDC0+++E5xv82gQ4seLdOyabQ2cRomTdGdu3j4SLKeTbs20dO4K0ulatuia9fw5PnrTby48aa5k6dd2/Z469+/oeVzTr26beXYoQomvNo6ROjg4dH/i+a9vHm92dM/9QftfEXw8N/J4+e+vv2i6vM/zfeu+32G8AX4Wj3k/WfggX7ppyBN0ciD4HcCBijfZw9WaGFBC2boFD9VXQhghBHCJpuHJJan4Yk10eNfiQWB6KJ4w7Eo43Uo1jiTP/HMqJCLPLojnY5AbmbjkB/Zs2KQA/TYo3gFIulkWURGGU17TxqkpJLvQENflVwqFeWX+3TY5UBXlhkPgWOm+dKXUQ7joJpkllmmfDHCaedGbH7ZTzzt3JmknICK6OegEeX5JTEqtsQjO8ykY86j5gzw6DnmUGpppedkqumm56Tj6aegpqPOqMyw06dKgKbqjniEtpqQoWzi//iequ44s046lJYzTjjfDNDNAN4I1E03wXpD7LHGDqvsssw26+yw34QzDjnlVKoOM85oRCugR7rqJ6xs8veQqraqk+uuvRbkTbAODTvQs/DGS2yyzXoTjjLUVppOqac2tK2c3XqbJrhsTumQku2sY6455ZCjTLoErQuvvdNOWimkGGNczsYcd1zOAORQG7LII49jMq/yxvuNMtOWk6k667DT4r9XBjzwP3cSnCeHH8LXDqOONqwMOMauS2+891Lbaan+tuOO0073J/XU7yhJULmOMjzO0EdP7GzS1abjDM082jymV2frfCg9C0WYzjjfKCuxvODgG7Y6pnJENnQJ/f/MzMIN7wpOysx6o4w5Yu8dn7d3Oal2nnsmFCE75hDd9bIrj1PtOTBnS9TeDzkD9LnKhHM5s8qUk7jiZncJlY6P50lMPStG2M7bR1O8eTrreF7WthD1K1C5lI5TeLKpp8MOza1ziRaJsRvKnpWTV350OObILJDwkKU6azvMmENO3F+Tc87yqTZfJWAVRm9omP2C2Oc4uY+TDnHejwsfM+fA/Ww45lvHnBhXmf+4z1ANEsiiKscs7GnPOfnbEYj4Nw6ile8czCgbAQt4ngPCikM8uh39luUN+9knggS50jrOQY7Blc8cApTQBi3jHQ8aClFVAxHlXKgsBz4ogqlaITn/wnG8boBjHJyDjvqelJzj2BBWOJIf7jBHjvuxSHE9YgcLieisI3JuiY5TTm+eCCsjCWgA6ygHF5V1ON8BCYs8EuIamQWOdDTpW9lhDRlhNaUADaAd/TsWtMqhjjS5409wFNAK1disHBEqP6HZI6zCBB6BpJGHw1LG+VyVSAFpUY3eAMd0HqmfyEjyUFLBSTz49sdzKONo3yCkwFLYyQA5o06DWlBfTmkjYvhjH6rMISvRyEh6tXGWM6sleMCIJA3lhZcZGkY/gAkNR0Zoe66cWze+QY5CIpN6ylTiDHUpFmjmJxr9yAc9qNKdaw6AGeXAZDc06cZv0jKcv2FmkGz0/xVzKged+FhncxDiTnaUg1nc9KY9CYrPfI7zREnx52kAKtCDnfGP5iBfJs9Rz4WCs6H6BNKX8MNLYkTjpP5Apz/6wY+W7mMf+cCHPeQRDzHpz48CSYcyllUOZqikM/EIKjyGesWGuiaksBvpmvRz0mj4Y6UsfWlM71GPqtKDHvLIqk+gwdWg1rSmRGWJOwfADnIsSxk+zQhQobEYfOyjH1xJi1OfGlWYynQAbNNqV4U61LFOxqhHfWiNhvEKaaDIpCh1aj/qOlWrYlUeXN1rYsLavYtiVKPgOEdE4sJVedTDrXDtCgdRglK6uvSl+JCpYx8b2WoKFaxLAaw7kDqjL//FAQEGgIEk3Jpa1dZjMY/Va2S9OtmhtnOzB+EeX/yqDtMNyxvl6OgA4hIPttIDtHHN41GSI9p/IHauiz1tau3hWOES17gSkS1tZRQlWRgAADCQwhuUyyW/smOEmVwHQaQDV7tA1CoHROxTV+rSmOKjvF2FRzjXy6IoSQIA8JWCFOjrJBANxBnmoFc4NEuQeHT3v2OR6FAIYtJp5oOqkBUqrRhcoiitggARnu+Y/DqAdFiQWOXgnof5+UxzSkSxMP1tigsjIBZDL0piIEB8T0HhGdF4HcZT1jj0W5Adg/gwpyzJMAicD3tglUqtYhMtWCHdN+L0wuXQaDisWGX/Zkj/NE/06EnYJA22VYnGNk5WLOkbj2hceTTuk7NJ6PwmJFl2IMyI8rDG8cAq+/nNxHmcoEuSJ3kYuTqHHt5Be6hQg/QZ0tQB16TNwqZCyyjTAjmHRr9hjibHQygKqg+bRs2RSp+axu/cqbLI0WiDwOPRkDQQkWiNp1KXyMIFMehZO32QX5fSQjUitkZsfSFkEwSQq271Qpwd7COTU9oXofYPcT0Adeh6WOXodbNhnZ59PhvcFTGUqe/jooOU9axp3Ta7seO8dsM73uI+Ibkvq6zM8mTfTVQTv/9NEXnTe+Dldi6Oy+xrhOMmzKdhOMC/NG/vWNsg9zUmlRsCj34sXGA0/9T4RAKOaYgTU81sbsg7TJ7whf5F5Ss3tnU+bhDcJcsb5qB4s2meG1q/DueF0jkEIY5hiS965HAhesbhTROkJ53jS0f1QNQxvrl5gxz5fsjMi47zEVv9IXHwBZGiwafi8PzC53B6N7An9IS8gx9kP7veGwJhDKi9RsQ4aDh6Spu3IzrN2jQhRd6xj7zv/fEIgTCE72CjaFyvHFD/68ABqehhgQOGFmG84yFP+oJIXg1Dise5JYa9sB/G8GS13lnP0WS4NH7qpc89QSRvgFEQSR5plPvczeF6vMCe67DsJoNFj3vdO38AFchAIqJkaYHAU/iHU/dXeHSQpl+Poxp5R/8+Lv788rP8nYxEXfaYYrWDpNFoz1X8Rsbf/PLr/vzbU0eam3XMz10pua7UQOsnEvhQf/Z3f6X2GwjRDvqnUUaDRNpXEig0EOuQUahDeyZRgKZxgAdYafW2PekwPoWDRHWXXoDSN1NUcJiHEvdggByYex5YJs4Qgl3DTWIzKyeoEJQzR/OkbShRDy74gqUXg4Ayg2aFUFVUggqUgwzBdRq1Td20EkC4gUJof+KmKlr0SnSkOgcxgdcmOuvwN+rgKOc2LHTHElM4WlVofkrHUFkUSARhRKojP+zADmE4KpryKBsTMltTOigjLyUUcyqRhuyzhh3YhjtyTwFSgcpgEAD/ZDJ+CA6+Ui/0ok3PdToCGIEnQQ9UaIhWiIgRcUhLCB0VaDoGYYmEAy/gEA73YjIhozq1ZxKcmHKe+IlYhxKHZA7ChzmsyDItszGY0inXwgy9U2aXBhH08GFnUYsviH8m0SjXEjPOUHfHmBLyQIvMaIvUhyTXqIbZyIa3qCPdWIjfeIjhKCOzSI7lqI2/NyPMd3Pr2IygaCGv5o3xCI7bWCLQAGzPc4/yeI4Wko7w6I8cmCd2ZiHv2I8E+Y9RgkMVUo/quJDmyCY8cyD7aI8SiY8FA2b2IZAKmZEFSTDi4h4J+ZEgOZFQ5EjlAQ8Wd3QnyZDgMjvlAQ1uZpIvKYRq/9MPA3UcHumSN5mN4OImx1GST/GTBDlJNkUbLBmRRumPBaMZtHGRy9iUP/klRjIbPVl1VLmVQxI5okGUaLOVYjkQKDIMBzkZS+mTY7mWAnEiFRkZUtk4bDmXBrEgBgMZWYkzdLmXCKEg+FCNLQGWfDmYC6EesqIX8SB1ZkeYjKkQ2OGQbxGXi9mYlOmYyfGWYuGRlbmZHTFRHbcUJcmZotmZljGSTFFyYTmaqvkQugENsfgScbmastlwZzE7gDkR8iBas7mbG+cUOnmbcEF/vDmc4UYTQrkTS0mcypkRMxEmLVFdPnFHyzmdFuER5CGKyRQfiVFdWbUY9oAP+fBWAv8hndRZniJhD9CZFW0Vnot1UiMyEO9pnvI5n/RZn/Z5n/iZn/q5n/zZn/75nwAaoAI6oARaoAZ6oAiaoAq6oAzaoA76oBAaoRI6oRRaoRZ6oRiaoRq6oRzaoR76oSAaoiI6oiRaoiZ6oiiaoiq6oizaoi76ojAaozI6ozRaozZ6oziaozq6ozzaoz76o0AapEI6pERapEZ6pEiapEq6pEzapE76pFAapVI6pVRapVZ6pViapVq6pVzapV76pWAapmI6pmRapmZ6pmiapmq6pmzapm76pnAap3I6p3Rap3Z6p3iap3q6p3zap376p4AaqII6qIRaqIZ6qIiaqIq6qIz/2qiO+qiQGqmSOqmUWqmWeqmYmqmauqmc2qme+qmgGqqiOqqkWqqmeqqomqqquqqs2qqu+qqwGquyOqu0Wqu2equ4mqu6uqu82qu++qvAGqzCOqzEWqzGeqzImqzKuqzM2qzO+qzQGq3SOq3UWq3Weq3Ymq3auq3c2q3e+q3gGq7iOq7kWq7meq7omq7quq7s2q7u+q7wGq/yOq/0Wq/2eq/4mq/6uq/82q/++q8AG7ACO7AEW7AGe7AIm7AKu7AM27AO+7AQO5bDkFhw1VL8gFq+dVVYpRXD4K7+QFW/FVytdV59xTxn0g/xCa7etRbLlEPClE+1lCX1QCHa6hT+/0APSZkkkqOz2HkRAtIT+RANKaustbkPHBlb8CEe+dCxx6obOGt8SqQY/DC0tYobwzAVj7FM0DCztIod/VB9oAEdQEuepKoe0YAPKjkbv6G0TOupC/K1wDkWRyW1elcL9qkh0YCe7rEq0oFL8AYJkQAL5Vkj/JATB3JI80G1HgUJgNsKiluZQxIN9bCTPxQP9tC2o/YImvsIojCah1K4cUsaa4smtKa5jMsJj8uVeeIPkxu6rLFMwjFpm/sIp/sLcxmTRhskAqIlgja7mosJvyANTak2N5uztyYg8ZAPqWsnvru5lcALy8uMj0MMuXtnL2IPZEsozau5kWC3Rxk9+P9gvLq7JOMhMNu7uZHQCuVoQ9NjSDUDDX7rJ+e7uZ1riGRkm3CSKvEwtYMyv6YLCaGAuc93Sl6Zv6piuQKcJv67uZwADM4HTdFwlgZMK/BAugq8wJsLvJAnUWHiuh/FDo4CMg1TMq5YwsrAMieMwid8Lyzsh+EADjAcwzGcOoiTNylBNnSiJhjsvLxgdSL2D1MCnDrkKLsyEOxyivPyXHIDiJg4L16HL5XSOyKBRbzLJTs8u93LcD/8EX9JW2XCDuogPuEgEOsCEb9iEKmYxpfoeZpjDnjjs3CUvNFrIVdMu41LbFt8I0crObQCxmKMxgU3DpESKqNSyIXMDMSYyGH/uA4xU4eO7MjTGMmS/E7Fs4trbERtjDevqYhYBA/YiyR17LupMMdwksc1QTsShIVhPETxckSqk3ldaFR/dCsMMzTP4nUAVCnMUHsLNh6kfB+hPLuh8MvrY8o0UcDZKSfOwD8DUIbN4sq88x5kMopwNBBgfA66woNJvCzS4jJvHCcLBr8zEsy+28CuYsxOEcEfJYOrrM3LckSIA8sm0bPgDDwXZi4N487PrDmd4jQNtb/EXB7kPLuYAAzCayfo/BTOWc/cNwDLjM3OTEeaE81koSoFkTCO4jDyVC+How7+rEyvRiIDvbmM+7wKl9DpTCVl8kft3MTwvElZy4QFQcvl/8A1z/INgpxBtbQlHjLSs1sJ3htGKP0UXdx+t9NCRlODEy3PmicnCXHNulJE4BBAcMTTdOzTWCy4IjXUUIEjLztW+mc5CLXUWbfSXTiDNX06AHQ+ZGPVV43V3JsK7MXVUGGbPHd9/PfKm9wbKAQeaG3Jg6c8tOLWFQLXvisKAe0cdI0We/Jk5rBT1wN6FaI4IAxKX6M6Y1MmhP0ghl3ODixsi50W8pBpWdgsg1d81bY3WsTKl5gsgf3RILLZCNLZ5Wy7shbaf0FJCghygbSFgji+NCNEPAR/huPGsA0esn0gtO27wJvYoIHbgNFH9HxhNIiEHn0nZENBT6gsOO3G8P+R3Aay3L4L1NUB3ZXRxcnlhEh4g4QiijTDgI99Ol6k0+D9H+Ltu4FbHOZtGV5tELezfyRkP0qoJliE1hFthuXwDgmMIGgwB4Nw37QbCXI9G/ttGvhbEGHdLCToUbVU2Ty4LkxtIFRABVaQBWOQBnPwB4qw3PX73BV+GvyQtuiHfUE3aQ212mv02wLxCPbRBlQwAFYQ5EJuBVTwBWjQBnmw4iN9us7tJS+OGwlEgbpoiYcT4t8kW+6wQupAsxbSBmPABUMu5CMe5FwwBkj+4KFcu7v05KexZeErEFnYNacNb1juGvVtH7OrCHkAB2nwBWEe5GNe4icOB3lQx8B70GT/weZ/4VT8kA/1kGJi4gy9/c5cyHB17g53juf/O7t/MAdt8AVZ8OdDXuRHnuT++7xNnhKKziAsdWAp1i2Sjl8qeN0qd+mZXh8YDAmPMAh50AZoAOZ/Huhl3gYO3ryR0MNLwea+NE1eRlOrVEkK0YDJlw7tsNf+J9OiYeslMtB6zud+LupCbuJpQOh+wAQg4AjbBd1OtQ+uXk398YEJUYr1A34cQV3QeVVVle/18J34IBC9FZ4vFfD7YLEEv1hwtVgrNVdOtfArBVUsZbECb1e9RV76rrHBlVWQBVmS5cHaDuQXMtCMu7mK8AfeHurgPuJRgAMgcBv3S7H+APHsnrEi/8tVlMvQZ9Z92aRNmqSJB2HvPuFZnzXwcCW0amkUeTKxT3Wx7E5erOValOUvdU4fVtDTtB3yne7lJi/mJQ4FpEww35VSDg/zBnZg5WVeJCvE8I4QDbiFIzdU6emdbsUP/aVdie5BJmVa7E5VV6XxKgZYVs3jnH3fkaC5csAEI9ACREAEUUDiVjAH+U7x+h75+K6xIQtck3/5ln/xreVaXzVUNV8QSMXxae9+urjeAzEeQwIZEjUQW/by7C5kCfbVqXLr7gHhjyAHNEACIRACHrABJMAEfpDkPO9ko28Qkq6Fs+c7icljcLZHErHsMKX3Q9YWEUL75yHefgAGLtAB3P/P/TQABo8w+JAwC9ZuIQ29gOrNzSs4EO9QD8oYa/odaCahWBcr/fEb+IZd+CTQ/R3wAQDBRM4jgo8giYI2QOFChg0dPoQYUeJEihUtXnSXUeNGjRPXlQvXTaTIb+TUOYTm799Kli1dvoTJ8uJMmjVtUoyZU+dOmDd9/gQaVKjNgkWNHj0KZseHDk07uGDiB1LBSKF+/Us4VOtWrg45fs04kd05Zd68jeym7Fw7h/DsEeMZt2VXunVxysWr0+5evn1nIgV81A8YFx88OKUB5lEkqlZZZvUb2S/YrxPbpSN3Fm04c+wgQouWl6dk0ntFny6dWvXWwK3lMDnslIRAo1X/r7aEvFq3TcocKTIrBw5tN3DlTkKEt+90zt3NtS4f7Vz69IatASt12tQFGD+1Hb/MTV38gN4bKbIzp2y4t3FrJcobBv3lePo35busn7+0daODUTBFTDGjILEKLpjC00+18jqayJl0xjELLWU6myiefu6TKUENaZJvQw/r4u8ROZbKbjY5GCuKQF52QvDDvRYMiyJ1yvlmuOKYoeidegzs0EUfL8rrRyF9emSA1sCgoYPYnuJuqhQL5KnFIYOCMUaPzAlHM5HYS4ctilK6b0oxK4puTDMnQsoPJlzIroPEInGyIBXxkvJMjKqkyMFy1ItQJLWcsQiee3q0s9CIejI0/1GFjBqRBAA7mM2PSFCUM5QV86pTUa/wlEhP9YbrhrN1ZgJtOU1PPfQfVAslSBHCPFhyO6mOmvO0TE/lNCJPQSXJJC8DVQ61VYclVlE1XYC1KQ92kEOROCu9VDRizvlGmXLOGXXVXB/alddvxjGHmV8vgk/YYs9FV0wPHkUhKoKeNYiTaE/jB9Rvy0kn2zO3bahbe8EV9yYLzU23YIM3zC4xg5CKRF4M/0lHyy01AwfcdDzzsErzuE1nT167+TbccWvSkce4DkY5Zf06+IDZwBqeF0No1DnH44+JsxhQ6TQGi+NyxvnYmwnVGfkmMINUOWmlpWsN5oddgsadhZxhxv8cckK6ORxyzFFH58l4pswhPYHuc6SQidYKHnxMLnNpt9+ObFLAnH4a6t48sxociYfT+pyAhwJ7QbE7Jnvvs4sOqlS54Ga8cb+Qcrhu8DRmRx1zBqgxaGv9RhyiwMvTlfBuyiYJXLTpgocfvBxnvfWujIpc8skDb2edmpX5ZqF/8V1HaoU+/6odZ5xhhx1m1mFGHXXSSecc582pOUvSQQa486HeoYdt5lznvvufCopddvB+B96ddpi53SGzFKrYHOafP8ccc8qhvxxyyBlnHGXGCUeZcMARzs1ApRnShexvfBnYyby3QAZe5BHhE9/4KqIxqqVPIt5YiFn2dpbpCVD/gIeTjI4W10ASlhAiMYugBGniu4Z8xRmWu1o3GOJBGgIwHP1Txv7Gcb/6yQ96B5TM0XZiQiIWcQDSSCGLIsOOdFith/JznvOYpzxmHK94w7PeeNSmQCN2kYRJ1MmtSvgOeYRmiF5EYwPBmBMxMpCMKjljGuXovTXGpI3dw54ZtzdHPnavjgfqIjzqocc99tGQrPvjS/IBDyKqTXv4OWQkW5dImOzjjm6LRz7aJklOwo2SMfEHPRjpunjw45Fz6WQqGffJnBAjH/FwHDQuFEdV1rJxrHxJP+TxDrcJEVG2BCYdcRmNesCDlwd7YyGDuUwGspIfl7RTHmPCTGp68Y+h/xzlqgQZn/lU05tyBKMrYakpQWnvm+eMZAR1ecwzZbKb6IQnJyVHTGOKqZQmi2c+g/mwZwpJlqjUZ0CruRxsbiiZKxFoQvOJF2LsIx7sFI80VaVQiiaUJ+sUzyArulGOKiQm0bhHPVOjkXJ21KQnHYBLLDmTKr0DHi+NRzygMVN51JQe9ajHPoiBUp72VFX0iAc8YjpTaNj0pvWwBz7ysY998KMf/fCHP6IRjZ321KpXxWpWtbpVrnbVq18Fa1jFOlayltWsZ0VrWtW6Vra21a1vhWtc5TpXutbVrnfFa171ule+9tWvfwVsYAU7WMIW1rCHRWxiFbtYxjbWsY+FbP9kJTtZylbWspfFbGY1u1nOdtaznwVtaEU7WtKW1rSnRW1qVbta1rbWta+FbWxlO1va1ta2t8VtbnW7W9721re/BW5whTtc4hbXuMdFbnKVu1zmNte5z4VudKU7XepW17rXxW52tbtd7nbXu98Fb3jFO17ylte850VvetW7Xva2173vhW985Ttf+tbXvvfFb371u1/+9te//wVwgAU8YAIX2MAHRnCCFbxgBjfYwQ+GcIQlPGEKV9jCF8ZwhjW8YQ532MMfBnGIRTxiEpfYxCdGcYpVvGIWt9jFL4ZxjGU8YxrX2MY3xnGOdbxjHvfYxz8GcpCFPGQiF9nIR0ZykpWivGQmN9nJT4ZylKU8ZSpX2cpXxnKWtbxlLnfZy18Gc5jFPGYyl9nMZ0ZzmtW8Zja32c1vhnOc5TxnOtfZznfGc571vGc+99nPfwZ0oAU9aEIX2tCHRnSiFb1oRjfa0Y+GNJT1MWlKV9rSl8Z0pi89jEhPZBqfBnWoRT1qUpd61NU4RqclYmpWt7rVxRCGqiFiDVrX2ta3xnWudY3ra4iDxQEBACH5BAUFAAMALGEAFQA9AmsCAAj/AAcIHEiwoMGDCBMqXMiwocOHECNKnEixosWLGDNq3Cjxn8ePIEOKHEmypEmPHFOqXMmypcuXMGPKnEmzZsqTOHPq3InSps+fQIMKHUq0qNGYPJMqXTryqNOnUKNKnUp1KNOrWLP+q8q1q9evYMPW1Eq2LFaxaNOqXcsWqtm3cK+2nUu3rt27C+Pq3bsUr9+/gAM75Uu48E7BiBMrXmzRsOPHOBlLnkxZMOTLmE1W3sy5s9fMoEOH9Ey6tOmfolOrPs26teuLqmOvfk1bMrFo/vz127cPXz169ORBgxYPGr16+/hFI0ZbtvPZtaODvZ17d757v4MTjwcP3jt34MOL/x8//h28ePLo2dvXb1jn5/ChS59fVJ7weNzhkd/Pv79//ucZt14/0SgW34Gp0aegUP816OCDDpoHTXr48OMPc3UhqGGCC3Y403cQhijiiOFJCE099+xzoVgbtsihhzCyBCJ4zjjDzo3rMMOMOuqk4+M5QJpzjjnmlGNkOeQkOc44yjQZzpPKkCOkOuuQ+OA78djTz2cudilajGBm5I854IDjTTdopqnmmmie2aY3cLIJZ5xsduNNOOOUY046zDhjZX/w0JOPe1F5aeiLYSYKETxu1unoo5BG+maa4EQ5JTt/ivfOif4MduinXyoq6kL7KKPmN2WGowyeyiyZJzlHEv9JJJBA+sijOsyss86NNTKTTpHkhPONpG2GA+ue6/hpZaD7YAgUqNCGOuq0BPmyAgFSvJHpiDO6w446Q5KjDDh1xklnN+CMI+U5zGAa4qb1dGpTtPRmRu29AnkBALZSoKLftgDT6GuR44TTaKTftLqnsg4y6+xL9UYMGb733gAAAFJk+2/AHIvXzrfnIKnMsOWm6c045jAD4ab2FMiSxDA7RjG1XVwsBQyFnIffzjzvfN7P3AX9c3dEF91twM6s8yuSwjr6zTjnVPlgPPT08zBGMWdN2MzT+nLCvhz0crVFzJU9AIbR7FYPcRtnOmM7SpszjqPKlJNOO1dCg89yjWn/7bdeXFOrSinEjC1TNPzgE1w8HbvTTjrlGCynMuaoA2Gg/Bie19+cvxX450ER4w8/9gjnHcDsnEMOuWyme467DW66d0Od124W6LgTlXY+a8dztIjrmEPOwWmGYzfD/8Vzj8sH2e68VrlHf1TaisvD+IjOQC65neZSbnns0PBj0PPkyyX9+U6Jvk/p0PzuX+qr1+k67P3Fg4975effF/r8R+VPPtBoW4OYcY5xEA9NxksH8sjzDnn0Q38Q1En/JhgVYvRjbe7jT/Yi56Y52cl7/RmA/YYRwRI2hYIohIoFMQihdaiOZGsCh93EU5AG+sOEONxKCncIlWHwgx6+e1A7/5hhDmUcUIbMMMg7BGI/YuSwhDyM4lOisQ8gZpA8G9xenMKRsoGMBx7yuOET8yfFMk4xH/IQoH+Ct700UW6B4YFGs8b4vJdEIx/7MKMeIfK/NDZIIOuInMkEooxzMIwggRIjHf/GEmL8MIj00NweJ3mQ/wUwPAlxB+SGNZBufIMcd1MiNPKxSK2pxJIChAYlVzk+kqywfUv04ngeNw4YokmG6jhIoKJRSolphIppPFrwTHUOVu6RKRdsn3+cUUA2GW8dBxllL+lFtkf+bphq8gbzjDlBuAxjH37EZEHYUUSTnYly7DBIPOrBy2keSiKv5A82YxhLbkoPMhf0XULYSP88dNYwfO700kNQKc9yrumT6VClPcFkKEvW0yDMEGQ2oeaMgqyznQFF0EJ8CMT+zPNUoFQWPRYKGHcCEx4IaYc6ymFLT4ZUU/LIXEEyGpuDWNCK/SFiG285Q/HEI48kFQpN+XLT62ExHcOLYU/DA8ZmqWSoSiEIQTMYUYOdS4bpKE/4JBnUggAgApmQBlQ/NQB/3AMa/End3NZkPJWJp6lcFepAInjSK7qjqh7kaVbHo7xtdpUhF5PAWOPzkDtekjzkNNWkKCc1plZtMvGhYkf/s1Krqqmt5EnkXyVyMQD0YrDygWc/6KHGu5LJmZX74mPnUxbJxkOW+1FpOczE1nL/uHU8o4zrZhFysQeIFbSh2Yg/1rafiLKuUVjFm2O3lKiSAPO1BiGPbMOB2u+pVl67nQgAEJCI3wIXMysxrAAfN9vWhXRGmhVVH+Oh3P+Q10wH4+JtNSVH3WZXIZn47Hft5RKOqhGvazrZ63waLxj18XQOkm1Lu8FF6/KVnfeFzX5BQ5N8zug7HzUZOgmM3deIDh+HfRD8WHfZlLUXpuKLMNYmDF6f+APEwpRbnRjr0+WdxoL2CLGD4EddNtGYP/HIh31V7BAWT0wojpxseNS64AbX2K+MeWVp+7NBxfrYHI3NbBiJfBMjG8YpZkWreDZIMuTarb32g/JfXmlX6aqj/4gHZDA5BtyfUXJ5JV4ujFRO6rHKsgmhypKdmtkiuh+KOUTBI8eCPQm1+e4HHhC+M57zvJeuWFg8AJ4onTeVjw5/JW3rowfbSMRjOwXYeyfeTwNTLOmXUTouYQHmO76DYYNmc8MlClB6UtQPfwx6JqJT230E2OajlsPKtVWggy7aaoi92nNqeaR4grfWNVGOGalmIH6MgyL2rGgjoLaHqLlTbAipFM51Mp4hyw1GTzfb1c8mC10ICh74xblSekrHOrKdQfMUJz32yIeF+GaQYO+jHveZdeOmLbxFP41dEKKaTN+NlHhD7y7EqCKCmaloOXVQYedQB/3epetRLzytqv+jLvFOlrLLjfLXFIe3xZkiGIeCh7wjI1bC1tWnk//pYztKR8h26sZyqCPbgKLHxGM+lpnTXDHfDGe9wcW0OE8KXXlCFtIDxo4cCZ1ISVrVomtryJVBo2VMD4rT9zeZZLoPZOVgErGwnu99N+hj6+jRkIzEJKLPndEQj7jSh5x2l6w9KaT5HxCnnLSljetRdPKGpYLEd7F7/O9o+gae8lQOdm1d1Wd3d+GfdXgJskZ0+cAplV0ovMdH6lx/17y6jAQkXCXrTw4bvadKfxLpDKMfpTPq+6heMKurCRx4OtaU2gVHgMFL9Lq3Cu9736HfBz92joubkYSUDiqN3OdvFRT/oaL/lOlTP0xUXNuUNaVw8PcHS1oiP1XMXxJ8pV/H7m9QU2Eu/6PQXySfg3qqty3moTPDMSHpUQ8ogg+8YSH9Fxb/9xHnY0H3YD3bNhz2cRwL2IC95mv894BzEYE6BIIkWH7/V4IouHvTl4IsWBT014IwKFQrGIM06BMzWIM4OBO8l4M8KBOl14NA6GxOF4REKHPxVoRI2GUWl4RMqBFD2IRQWBFLGIVUOBFHWIVYCBHPloVcWGSU1oVguDleFoZkiBB5VoZoOFNGloZsKBAs1oZwOGFwGIffNYd2CFp2mIdQlYd86IYB1YeA6E6AOIi9NIiGOABjdIiKmEOK2IiI/xhBjuiIEBSJlEg+lHiJj1g7mIiJmriJm8hInuiJWROKpOiH9VKKqHiKqJiK0LKKrpiJXfKKsihQsliLLVKLuAiL8JGLuXggvPiLzvGLwqiLFDaMwygtxiiMX5aMzNg8hzE+zRiN0jiN1FiN1niN2JiN2riN3NiN3viN4BiO4jiO5FiO5niO6JiO6riO7NiO7viO8BiP8jiP9FiP9niP+JiP+riP/NiP/viPABmQAjmQBFmQBnmQCJmQCrmQDNmQDvmQEBmREjmRFFmRFnmRGJmRGrmRHNmRHvmRIBmSIjmSJFmSJnmSKJmSKrmSLNmSLvmSMBmTMjmTNFmTNnmTOP+Zkzq5kzzZkz75k0AZlEI5lERZlEZ5lEiZlEq5lEzZlE75lFAZlVI5lVRZlVZ5lViZlVq5lVzZlV75lWAZlmI5lmRZlmZ5lmiZlmq5lmzZlm75lnAZl3I5l3RZl3Z5l3iZl3q5l3zZl375l4AZmII5mIRZmIZ5mIiZmIq5mIzZmI75mJAZmZI5mZRZmZZ5mZiZmZq5mZzZmZ75maAZmqI5mqRZmqZ5mqiZmqq5mqzZmq75mrAZm7I5m7RZm7Z5m7iZm7q5m7zZm775m8AZnMI5nMRZnMZ5nMiZnMq5nMzZnM75nNAZndI5ndRZndZ5ndiZndq5ndzZnd75neAZnuL/OZ7kWZ7meZ7omZ7quZ7sGZ0XJ53ByJwagpzv9JuqmJumNJu285r6g5pPJJqFuJl7WJn79ZhnmJhTSJiHF5gvyJci2BN1+aAAOJcSShJwWaHnl5YY+ozriBu6QXAesqGIt43UYR328Bv3QW7lAQ8TQg8VAn2mIaJPx4slug/5cKLagR/rZyX+RiEOSBoyehakmHopimD5R3ITUg8CB6N+EaTy5omHdqQndx4Uwh6E9xVOCm2UGKWxVSM3kis70iNCFySyciRKwiQFsypZF3Ls8HkjQqUuaiFXqoJZejuOCA1IsiROMi60NXd5JSfcA3vFoy5TYncBgyWDxyV1yheH/9gPgIp5kPp6xJN8heqmsSNxc9p0i7o1gxgNyOYoqaIqTbIkSRIrskIrtoIruYIjBEQwTfN3qrIu+tZ8/7EpiWoUm3oZgCgLrNB9OXIj7OAMlrpw7NCqcWdEmFcpsnp7EXIiS4cauaqrcygNjpADAnAFajCsUuoOR1OsS8MkYweqloJt4FMPVqOp0XpkbIgLa0ABAvCuQdAE2rqtOzYwIhOu3PNBdpNl/AEvzCWE6aquZUgKOaAA73qwObAKvpYbuqEbvdYPvcYPEjuxEssbFmux+YAPGruxGnuiCEcc5fZ+Y6Y04TIuxpculUOrTKU338YRAVuMYUgMa2ACB3CwAv+gADlACsshDdLgE2mTOIuzoyLSeMc2dpK3r//BouaaES8bXNGTBlYwLzWBC1jgrjZLAWuAC7AACZDwCz1rFLgBtNYjtAlGQMHyKCirDirrDix6D/8aEU3rtFlIsDYrAAeQA46QCoqQBllgBVaQB5lqE4VWPdzxJ+wAObXkKEcbNf7Bop3mhXELsxPEBWzBrlZ7sAyABZzwB2WQBVTgt347B2kxDP7QG+NGtrNktj0mPyijtoAiD/nwa5GLjOeDBlKbEqTgBAZrsyAQBn+ABp77uaDLBX/AC3ZRaPcQHEb6H4cbd0ZbN4wLegU2V7NLu7nzCI+wFtRqAjZbABMQBHn/kAZcYAVUILxWwAVtEAm1kBi/pzhBdHeqi7Yoo2yZRQ9zVL1yS4RUe7kQMAEuAAVt0Leg67fo+wiw8LWTIYCw1CDNW22T03nf57gkhL8txnSQgBF0KwAF0L8dAAVjEAUCDLpf0AaP0ArAwBr3R7ZDNHSXZyyMSxDwp0gUrGc8aLkaPAETMAI48AXlW74i3AaKkApeKx1pc33Mi7hWp24jhzlONMOVhoO5ywD9uwEj0AIg3MM+PMKKEAq8ELik0b4DGFtEFD/pBsFvNUoT7MR2CoPbi8NUbMVU4LkD/AVwMAicAAv3YkGpV7gelXJoUhByFjUDsSn3IMNqPKN2RDpM/8pDVDsBGtABVUwEfmu+VjDCg4AJJhw4H5F+A6AfsAUeLkTGzgTBA0E1D3TIbJcS6rM25MUkI6VHwMAHQUACH1DFUUDJfmvJmCDE1JIUKew+ZktiZJdOnSwP94vKOSFc/NA753a2amIOZiQKYUADKGDLWPzDg1AJomC8MbIXRWw94FEQoSzMl0XKLINRyGyhFPF7qXdJSnNsf5om3wANXsw1JGDNPTzJY1DHkcAJtVDPkpEaiJNj0EUQwewo6lYl63Qh6TyhDaE+onY6zvBmomxeKQNUZSTJ5Cu8VLDPiqAInJDJicE51mc9AzBtfpxuc8YMTTV+i8E5CvHNygTKiP8LedDLDifytmU0wB09B4MQCbv8CwDtsvH2exUofKG8umw1Z+uQ0y7dGrc4EHoc0WNG0eQSZ8ZSOe2Q04ZzwTvkuQPQ0fyszV1MwRVBgdYDIuOM0FKiDszygazlGKXbO6k7dFZ3MnbDDojKD08dRR/wARtQEHmgCI/Qz7DQxPjLEQIYRGvN1li2TueqyTuxymmNWL9iQI/iwuT61guFCNk7AI8Q0sCgxi6x2O9QapktJexgzHBNLbuzODkVMp96a0LiLo7b2nsUCQPwC4dcEx8GRA28YHSSQO8wvdSiPsG3fhMdMg48yoHHtizLZb0tFOknD+0wJDlnTmpSN+kQZEP/XRmrDLIZ5AwEFHd9yropWyI53WxOrEKKBw+/4noIbXTwoNOnQT0RfWHdkjRDUjCSom7kCh57/d2rZNZdkTb3EA8r1dzmJHnm4AzygNt4UWgfa1fkzdwqBynp0nlq2y3osQ8Snl2JjRaoBw3UFq4s5w6Rdhe4YaLj9h/8LTySE8+UUjeV833u8OEhrmKze7z8YOJF1FJ08jTpAC8gThU1eqPaYXIOcuFMk6+CSnc33q/oEbsEvlmRKxjRQA/vUEDCfTCyty5UgiXyUA/2gA94xA8dCKIW0eI2ih1FalduGuPBciZRnnmWom+AQjX4ENko2LSTEQ3WLTfGZ3UJM3vL/9emBXiBLXocZ45H2JGj3WEl7WAjOqJ3Q1IkcWdVdn5ACaMnIvd+VGMPyoGDAUsaW65JMk7OkCeoCRMlenIOfNKmTf6lPDKmRGIk5MAkq8Lq5RLlnz7l9XMiKkKE6Vob/pBj78B6u/6qkDInnp58SLLrTVImkRqpwR7qe64eBNKEuQojg5tGyw0sBYOv+XrtkYJ8m1eqp+ojOF4ixYEciwyE0eraasM2eOcjYMckvv5nyNcqs6cnQiLrtncjuGcc+eDnWbipuANqH2ukcOMrBL+qwnqkZE7qO56EdTpBpLs+pvM7BdgdPXOACJiBwKGA9bCxeNSAag6xGV+FQWpGt/8RDdHQ19IooxGKoXdZoXkpoXopgg7aoEF/g0O/oIC5gwy6dgo6c4aZoIW5hYu5hpBZoJM5Vpr5h51ZSqPJiKYJiapZPrDZObXpN/h5n7vZisFpKMe5IctJWM9ZU9Oppe0593Rf93Z/93if93q/93zf937/94Af+II/+IRf+IZ/+Iif+Iq/+Izf+I7/+JAf+ZI/+ZRf+ZZ/+Zif+Zq/+Zzf+Z7/+aAf+qI/+qRf+qZ/+qif+qq/+qzf+q7/+rAf+7I/+7Rf+7Z/+7if+7q/+7zf+77/+8Af/MI//MRf/MZ//Mif/Mq//Mzf/M7//NAf/dI//dRf/dZ//dif/dq//dz/3/3e//3gH/7iP/7kX/7mf/7on/7qv/7s3/7u//7wH//yP//0X//2f//4n//6v//83/8AMUDgQIIFDR5EmFDhQoYNHT6EGFHiRIoVLV7EmFHjRo4dPX4EGVLkSJIlTZ5EmVLlSpYtXb6EGVPmTJo1bd7EmVPnTp49ff4EGlToUKJFjR5FmlTpUqZNnT6FGlXqVKpVrV7FmlXrVq5dvX4FG1bsWLJlzZ5Fm1btWrZt3b6FG1fuXLp17d7Fm1fvXr59/f4FHFjwYMKFDR9GnFjxYsaNHT+GHFnyZMqVLV/GnFnzZs6dPX8GHVr0aNKlTZ9GnVr1atatXb+GHVv2bNq1W23fxp1b927evX3/Bh5c+HDixY0fR55c+XLmzZ0/hx5d+nN91a1fx55d+/bsw6Z/XztN/Hjy5c2fR2++2jHw7c2mhx9ffjFh7u2LtZZf/37+/f3/7+8ace4TLSAAIfkEBQUAAwAsawAcAOkCZAIACP8ABwgcSLCgwYMIEypcyLChw4cQI0qcSLGixYsYM2rcyLGjx48gQ278R7KkyZMoU6pcybKly5cwY8qcaVKkzZs4c+rcybOnz59AgwqtSLOo0aNIkyplObSp06dQo0qdSrWq1YIkr2oVmXWr169Ao0UjBras2bNoL3ZNy5bh2rZw4zbM584dvHjQ5NnLx8+f3L+AA/t8K7gt4cKIz5oqdOpd3ceQ7+bd2zex5cuYDR7O7HUz5885XcZ5cOkSqnTrnEFezVqyXr5+QcuefdUzbam2b+s+uNRkg0vJgifr1g2cMnLlzqFWzbp5XdeUY++eTv1j7upBr2PH3JvlMAJvhhP/H9/NmzfyxpErT+3c+Tt40OxJ306/vkLt9nXizx+4O8sMBEhR2jjKfEPegeWdN156yS3XXmT05DMMfxTSt59sF4aUYYWG+aeSKiU88MYpzgjkzDrpnGMOOcqAoyCCCZL3TTjImZOOOuy4F489/XDoI20bmhWkZyXhFOSPQnqoEjH3tNMOZAc5w0yK5bAIDowxmjfeN8edk2Nr9OwzIZJkInYkVEUOlGZNJxFU0wBZtQnnmxr+U2ZhSrpEjD/84EOPPPE4tlqUKJ5TZYtYHqhMOcw8udo7O/Z456QdatbbQjQh1Gamc65pJ0qdnvmQqJROlWdR0fSzTz3yQCMolAe1/8OOOiqyGM6BWn4zjpfNwSPPPtGUKmxndmLV3X1FGVvsp3Eyq2azbDbb6ZzT3kTqsE/988orpyKV6qqtwvPqYwideA45BiKojDmNsgZpPZJiK2+2xbp5rKbJKtsVqGsVKSe10gJ8rUMDzysUAACo4Eu3ve3Z55+BsmYQM+YoA+M35PDaGjT5BGvwxz0R5iGyM/EWbUrPMptmqM6yXC9XL4MMFsIAaMHwqQ77CSg8gwrEzrlXqmuOOs29G6/MSFsX88oU5ZZhzJYyTa1A+24qbdV0wpy0WQjLcPPXJaV6j6vkCtSOOhXDCE7GzK3mK7Bbx41RwT/xa/VKLlPdsr9Se/9Et9w4IWwz2ISTRAw/9PBc9gA/ozuelt6sy0zR8dBzNOCYYwr1V6CyrDfKn1c9Nd9/45u5VgCIAOdIq38aeuEk+VNPxGWfXU44L44XTjnptB2ZPPycLryloJVuk/HDc2QK8gTDHk0+8ihe10DrrJg7cd6MY846zcWDz5jJY05MPx5zxjxI54cPGOHjzz6uiencTp6Wu6fj6GPvyDOf+h8Ts0/07ricRjo3qfTxz0wM80c+oCG96Q2AYuN4XK4y9iVBceyA8noe2X42jnHUoyN4M9LmrDVCopQQgz/K0zAQ10B3mOhct8IVOdKxmnjUo3wo/JHsoFGX6kVwPOngSEv/RBiaehnPgDksnn/8MTaJPTBtBwqHOXyXv/0lcTuHS1wPK3Y9cMhDiEzxW7/oREZPlfFzrxvdyd7St2ddMWlLicb/WujCxknQG+QgGmTisQ+yvHE6GlQcxXB3IIydYx9gHGIiScdIaDVSdEN0pCQlabo/wlEp46NHPCT2sxiOZ12+g4c9cGjJzMiOdoM0z4sw1jt3xMOKFnkJCPHWuTdBS2+4XNYtBZbLSVKtkqXc2lIUyMBBqWMcCjIPxvRYl3dAQ4DB/EsmpceM26lySzNUDTwsVzpZjgSSRrSb1dzIFE+p0ZYEJF40AaeUFWoRMuwwR9A+aY77uTIf65SLHOXx/w7H2A53uQMH755jOT920yWL5GUvy4m1hu4yYP/ypTrziTml9IOfr2pHOpCJPW8IlHuP2SYpKboVJvKwLrZLF3nq95xf+dGNiwTdN3U5Lab9C42hW+jUFBqwnfrUXiQdHlKGgY9NQmYd5XAReZRxjvs5M3hBdQrTMmlUdzgjfirV3dBa2kdgDjCMMVXZI/O2srLezVl2S9lNgRrV5B2lH++sizPOoYyAlgOkdfHeS9uqn5Tss59yTQc5rtcNKbbLmR3TnBhlOkuHijWcfLMXZM14Tpq+zjZI5CuFijKMfNCuh+XIajfGQcOQ0mOkmm3sSaJhj5MGlhwwWhdIEbtXZP8pLZ1IymxqN0sTf8TVqnSNojm+VBdoQHW3GVmJ/8hWFw7GdriP8R5qbRtN3SKXQzJZ7rjUMdj55XGP9gDfdUfFErhKr3p1xdWuiBuPe0zXLSdEoXXHi92YRKMe4npMiSy20iniT3/0JdlKZJdf4CJTS9hbb3TrAUuIzLeIx4vvVwP8xpjsg7nu0ChHt1QOdQDWHcalsFpVEo17VNUd1RxAITN2Pxs2WCIPJqLWSCjiP8LkvvG4XzznSRymtk2U7yXpS7SrXyhi036mhWYsJVyVWurSsY+VrGR1G+Map/AlF83oRnOHsck1E8BRjYl5IcPdb+RuXffbppLnBjXYycT/ZOMUpxnX+OQ2itHK1XVJNIp6VHkqqp7Rxec67YvfV3XyQAL1sl1cOuMpuxmhyqrp3lQm6ZORlcpMxjMGXZLlx7SDrsn0KKNCesMK25fPnt7ygUjLnKfWFn1tfjRMotbLS1+NpiH8Kaw1HdSWEPWz1RStj5sZYv7N5HD87LOLXiRFvG7zxUqLmqzBylZeplWnkzSrjHnda5b4VnpzTS82mek98cqtKGNO9YYTjOS8fi9kmTYVONW401vuEqeY5nZqlXvhoyb1z8x5tjBRNbvVINWTxJEicfO3ZhqjBWW+HKOkL8vYOukbuQOOa7hDvcwBFJcfr6bUUZ73WeDWdZUz/wRvkLedJHSmUeKiS6PnHH5xjKuEH8kGLThUTM8S2WWUIj8Ksj8MWmH79zHQ6OpQqvxNyzC95kjz6wI9fS6BJKjLAsnflZPy7dU4w8jEWSaEoA3vtDwdwlAXcUoILKjq7dzq3QDlQPIRb/NhEnEnrkuZz3wO3+kVN3V3a+DTLmSUZNmfWxaIKkkrEJEOfn3DXCAdD42eu0Kmik1+/OnOTnh2mqSzrnV7NwZS2OEO4Kmc50nD4FpylKp6qU3dY6mtkvoK1b7z5zYJjj2u4YJ4YwBEG0C5b7/YOEpeYv8ULnE/HnLAD1rzuNesSbLscbcXROF2oYc/7KwVnPXDfZw81/81sfddCK08KsTPT/qjX1HD9XsAGv79QLKHZI55EyiE2ycdBUIx/v55+fd0FtM2gASIFOzHfiSxe4wzAG83ENjnTL8SDfnyVW62Q83BOOciWj22VZenfWZXgCAYgpB2gAj4D+YFf6o2f9kUUtBQD8ByKdI2bcMwRz1zNmCHTRoje+dHgjzYgyOxXD5zDjFEEDRyDu3iDpCiF/1ADCLIdU0EKwMwV6EFI7ujDvZEbCDng1q4hTeBY+0wABulUgQBDtqjDm3jTBGyfU34EjMYPe8Df2jjfzJCQeOyYDvIhXiYhxQxZvE0Dho4egOwKOeAV3ZhQy+4hiZBTG+IgeTAY5//1GFXSGwMpoeUWIkdQWTusA6GIoeIpj2tFFJKyISPRgzRwCf7gA/2AChQOADoRVi6MojOUTlZaIm0WIsZsWduGFjWkyi7A4v4Uzn4oIZKUYqqkg/2wCqtEg/iUodQKIWOmHC8E4lICA3BaIvWeI23uA/04FqZaCiE1FEL4olUlBf5IIwmQYr+UIz28CfQEA/KyIzOkRCtiCCvyAzwuE2ziI36uI8VMYOzIz3skA4V84flsSiMY0/w0Y7v+CA9wxDOwA7ssA7MAENUCIm9wjF3yI8auZEIMT5j00ATaU24ch5kODS+05BmA5ESqQ60cg4qYg7lUCXkQCDKEA7PiGAJ/7Y990gP+ciRPvmTEqFAqvgYAVkO64YriwKTMkmTNoklOImTiRJFFuku1JiRQHmVWFkQcrSNkNEOFEMOCBeVYjmWjwMO4aAMyjAOGUOIe8STzZeVcBmXCjEM34dh7lCUfkiW3TAjZ9lByBGT5uCSyqEOzMAMqXGSzgEfiSWXjNmYEOGRxeRptBKY6XAjhgmRiPkoDPkgsuiYnvmZESGUebeZpLmZimmVoJmaqfk8fyIP8kAPsFkPsimb94APtpkP+5Cb+8APvNkPvukPwFmKYiEWb6maxnmcyJmcyrmczNmczvmc0Bmd0jmd1Fmd1nmd2Jmd2rmd3Nmd3vmd4Bme4v85nuRZnuZ5nuiZnuq5nuzZnu75nvAZn/I5n/RZn/Z5n/iZn/q5n/zZn/75nwAaoAI6oARaoAZ6oAiaoAq6oAzaoA76oBAaoRI6oRRaoRZ6oRiaoRq6oRzaoR76oSAaoiI6oiRaoiZ6oiiaoiq6oizaoi76ojAaozI6ozRaozZ6oziaozq6ozzaoz76o0AapEI6pERapEZ6pEiapEq6pEzapE76pFAapVI6pVRapVZ6pViapVq6pVzapV76pWAapmI6pmRapmZ6pmiapmq6pmzapm76pnAap3I6p3Rap3Z6p3iap3q6p3zap376p4AaqII6qIRaqIZ6qIiaqIq6qIz/2qgA6gUIEKmSOqmUWqmWeqmYmqmauqmc2qme+qmgigAN8AqOGlVK4AW5kKqquqqs2qqu+qqwGquyOqu0Wqu2equ4KgGgUKpBpQRnsE4VsKu8SlG+CqzCOqzrVKzRFKzImk/KGkzM2qzR9KylFK3SWkrUaknWeq1/lK3YsQq+MBTbyq1X5K2BsQpuIBEVMAkI4QteUJwbMa7kmkPmChiSYAES8Qm9gBC7AADmBhLyOq8YVK9ekQk1IAIxYAkCkQg1sAJkQAzDsAILAARAQAxu0AdLcAJVMAzSMACrAAQnsAS5IBBTUArSQAeAoAUisAS7MABTAAA9AASqYBMBK7D8/+OthuAACbCzPNuzPvuzO+sAn0AMHYsQbAC0SJsADqALRTsQw7AAeFAKi6CwfSABiaAJKjAFA6AGEpAJmSANOrAAcaAJKWAEA9ALDaAFnYAEGEAW6zoAStAAbpAJJbAEA5AJAOC1+yoSNWuz4eOtLBAAgju4hFu4hku4QvCWxJAAh9u4gssGtdULBjAJTZsBfSAQpdAAA3CvA6EDOiAQqkAAw+AGGSAQw9AA7Pq2SsADAkEIpduv//oRfeu3w4OzjOu4uDu4CWAIC9EEuVu4DqAKr+YGD9AARSALA4AAFoABzBsBw8C5AqEDXTAQBmAKVcADRcsB6aq6WiAQllAB0v8Auzgxu7R7OtkqDRDbC+q7vuzbvu7bC7rAsQzhC+9bv/KLEJ8QAzEwABWQCAUxCfgavXY7ALoAAL2gBiowEBVACPzLrkrQvQPwveHrr00bEuRbvpjjrdKAvsTQwR78wSAcwhvcEBwcwiKMELmgsAPQBS8gDV2QAcjrC5IwAKOwAKsQvQ1gCgPwBCcwAKqAAApLBw3QstzrveArDUAMrxlxwRgsNwSrFa+QAQvwABwwCgMwDFoQAQ3wAFo7AFVgARFADDrAtgvAATc8AIBQAQ2AASqsApngxb86AJpQAgIRBxgQAZ1As8faxH8bx5yhA2LwFUzMx0nzxIIByIK8x4T/LDyGXBHE8AmTUApQkQlW7BWDvMgg08gSMQxdsAA0UwGXmxOvcMY8UQojyxGXjMkGo8kQEbE088oQfBNagAQ5oQnpKhAqEAcdkcqqLC+s/BBV8MrC7L+yTMs44QYtLBCr0LKorMi97MR+nBG+YADC/Moc4BHDUAUcsAIMPABa8ANPgAE8QAsCoQYcgAE1QKrD4AUccAJ1IBB04AbhXAfGHMFPsLkxgAEr0AgD8AoY0AAxUAQrzK4DQAcnwAFiQBajsASAwAEiQNCTsAL6TNAGwcvPLCy/3BCLUM2vTADhyhEgOwqEAMTSoAUG4AaqoAQcIA2WEAGf8AqEQKpDEAOj/5AJEsDAU4AAajAKr7AAmyAQN9C9iTAJML0AqrDOIlAKN5zLA3AHDzAJn4ABVRDBBrAEo6AGDeALw4AAhEALXosQFn3RlJLRDEEHHP3KpJwR31HJU3AD3nzNA+ALCCDSEvDTArELBMDMblADLvsCA7EEdtsLCDCzAyALk5AI2jsAyFy0TC0CatCxktAALI0AY7IAoyC5gBC7CuzMYo00ZL0QjHDWCOPRHLEKAOBHcXDNWsC6AtG/xDAFW/wEvqAJBMC8zMu6UzDAcrwAo6s6A0AGEcADT2ABXqDYyTwATG21AvEK/moJEjAQXTsAdWABCGADaU0QYd3ZZfLZCiHXov8tAhWMEb5AAGfcBTLgzSsgEMSwAJ4wEJmAAWQgCwSwtwMxBU/QtBbQ0LqcvJVcAsUdB+mNy7qc2HeLABH83AIR3aB7A359ENmt3UjC3QqhBWdNADPcES/AA75QCg9wuSYtCcQgBhZADJuQx75QAr/6AjrQsqOgsPbdtGKQAQiwtw1wuYBAAMXdCBJgCi3L1GpgAa/QCytAy84N3ZlgC4kwDMRQBQ1e0ZwN4asczRlBDC/A0cXtEbZwAw8gAXHsBlPwAg1QxQPQCBmwxUjAsbugBFqcAQx8BoE8ELSAAV08AISgxTcwBXGAvk+QAemtBAxMDFogAQ9gBPvqCU3+AqD/IAslsMUrQNhODuVbI+EKQQxk0AA0gwHdfCcPDukVIukLIQ01Taqlsumczh+eDjikXur2cepSMQrX7RGlUMl6rOqZLOVwAQTTKxJVoNt8++S0Pta23ha4bhO7Pr6+/ut3Yq7C6Q/L3uzM/uzOHu3QPu3S7uwhtwox4AYWwAHdPOyrUAMVINUTcgsqAAjMu99k4AZAIAEyQM4eewMVkAIqnOUSoAOAbezIPi/eKg/PqJf+/u89hkgFMQoEwANIjgAmO+yqkAi5UAoc8KuvUPCrIAkGQKpG0ACJ8AoxQMu+8ABqoAuJMKrIjQS3QAhVje/5ji3emg4A3/Iu3w3wYBCj/wAAtxC9Uz3sA7ALi3AHS+DXzG0LAsHmA2AEStC6pUsHHHALqfoCbiDfHy0DvG7Bx57yP+Kt9UAgZ5n1Nbn1Wt/1XP/1Xh/2YP/15WBFo4AARasFPTAAw24JDQAEVXAD1xzxAyECeDD0XdCxALzCDSACfi8CY6u5AvEEUQ+wU0/1HMLqQDHzuiAQPHDz03sDZCAQYjD3BFD3d28EeT8Ae5/aFRzxH10DhS+7h4/4FKL4P0HwhE4Jc83204sENzAMmhABlo/5eK/3+LoLDyAGu7ALhCDJK+sLjIAAo+8RqW76t4H6PlHDXIsBoSwGdNDPK/AAJxAHdkvuA/EE7EoG0f8/AJ/A2qpgAxFQATVww7IQAw8QA2SgBiiP/Mke7F5Rw5Zx/O4vG8rfE/KfGPRf/59x/wAxQOBAggUNHkRY0NemhA0dPoQYEWIFUBItXsSYUeNGjh09fgQZUuRIkiVNnkSZUmVIJWdWvoQJk2JMmjVt3sSZU+dOnj191mz5U+jOmUONHkWaVOlSpk2dCgz6VGrHolOtXsWaVetWriSjdgUrsGpYsmXNnkWb1qSSKqXcvoUbV+5cunXt3sWbV+9evn0lVFQbWPBgwoW7iomQWPFixo0dP4YcWfJkypUtX8YcQcIrw509fwYdWvRo0qVNn0adWvVq1q1dv4YdW/Zs2rX/bd/GnVv3bt69ff8GHlz4cOLFjR9Hnlz5cubNnT+HHl36dOrVrV/Hnl37du7dvX8HH178ePLlzZ9Hn179evbt3b+HH1/+fPr17d/Hn1//fv79/f8HMEABBySwQAMPRDBBBRdksEEHH4QwQgknpLBCCy/EMEMNN+SwQw8/BDFEEUcksUQTT0QxRRVXZLFFF1+EMUYZZ6SxRhtvxDFHHXfksUcffwQySCGHJLJII49EMkkll2SySSefhDJKKaekskorr8QySy235LJLL78EM0wxxySzTDPPRDNNNddks00334QzTjnnpLNOO+/EM0899+SzTz//BDRQQQcltFBDD0U0/1FFF2W0UUcfhTRSSSeltFJLL8U0U0035bRTTz8FNVRRRyW1VFNPRTVVVVdltVVXX4U1VllnpbVWW2/FNVddd+W1V19/BTZYYYcltlhjj0U2WWWXZbZZZ5+FNlppp6W2WmuvxTZbbbfltltvvwU3XHHHJbdcc89FN11112W3XXffhTdeeeelt15778U3X3335bdff/8FeElp7qknH378ISbgMaUhZQ0TFLiiEHjcoRieeOSRx559+hlG4SsbzoEBAUb2AhVUzjmHGXYoZpnld+CBRp6CD/aYyH9uxhlkCkbmWQAIwAkHnG+6IdqbcMYpx5x0VG655ZehgYYegxGuGf+2LAZ4ZDect+aaa1zWcIKCAw7oeWQGQAhDEEGGJrobb7xpu+1vlEFaaWacabpli+WhR2OOqy7NCtu6Jrzwf3BxJOyxyxZAARPCQCSPNriIIotDzClnnHDi5rxouImeG+lzlsY774rjiZqfhAEv7JGsD4rENcMNR9wJE3gmG3cTsEBEDjjGoCJ44dFwZqB22FHnHMzHUabztt/m/JtwyEk6nXVWbvqdeOhRnXWN0MBKcCpgm31rYkjBwoTcyz6AAiz4qGSOMrgQngor7s9ijmfwqQeaeCY2SDvWkTxzkEMZm3Me9KBHNHAogxzmSJnToGEPf3gvMK/DSez+0ZTynS//fesrGwWcwAdRKKINY7hf8O5nBSp8oQ1/4AQviCEN8/mDH/ighzzi8Q53BBB5yjMgAp3HOXCMI4Isg1k9+mFBARWOYQ5TAONGRoEcOKIVnMhDGuhnvxVaIQtomEMkRAELYJSPa9Hoxz7qIQ9owIOHBnHGOtJxjnIYkG1DBAc5jlgxaOQjGkzsD9dAFkUpUtERpEiFIuDwhfqtsIVtGEQoWvELM1byZsSwIQ51yMMeFsQZzEgH5oRIRD0yQ29S+yMg8fO1HBCScVRcAy5qwYk5oCELwusiF9CQB0y0QoaWBKbh0KhGNrqRYgRhRzrKEY7PEdGIpmTZxfaRSlW+Z4MC/5EiA3KwBlL8ohWPaAMju5jCMcBhEKKoBQ2DuU5gDsMf+7AHGzkpkGQus5lxK+Ie3wGNenSvmu/hmTa5SQxeYNGW47wfF9KQB05Mkp0Phegl+3GPNh5zAPVkpvPyyYx2UGyfSvwne0wwUGB8M5wI9WI5I+FLYkTUpS/9hz/yIY+JHROj92zbRpHIzyWG1DzSKGgWs4BShf4hFLVYHUhg+tJo7IMe8WDZRZWZ0c7plI/5qKBPwQPOLY7zi3PgBBljslR2NvWpLbupRp8ZTe4lVavWiUQbBjJOhQ4iFTJ0a07IWslh8KN/aKXjKPFZyorJYx955VI06AENaqLoampJg/9BUsrQdDplr4Ujhl+hwUl3sCOweCzHOfD2DsN2LEv+gAY7yME2ZgRqfAOBQyTE2pXL4gyT+KApyzy7TM69zRvjMMc63LFPfDT2SfyIhzrG4dtmpuNPr+1MbWWqQ91+9nlwC0c51NEO7RV3ScTIBzzOEY5v4LQb3yiHM3r6rcuaFaoU8+w47gi9bxhxZfGoR1aFRAx7OMMcCFwgA9Mrj2ggdlxkdS8PnTHV6xItHOZQhzvwq18dRQMa6yjHHTn34HbQw7TxWuow9kFTHq7DHMr4XDPzmA5nwIMe650RcpU7xG6E4xzwwIeB6wVTmVbUs+QAR4O9oYzgwsOwLhpGPdz/cWLzEk0ZN94H4FxKjH707x3tUIc9Pedg7ZL2sB3aGkEwKQ8Mb863cfttOuJBYVVCtK9PfYeJyZFi+hrRGX38cIRmF43wpgPIeCSHOuJh3LcK5KHThUcy/9w5Iq+jj4Q20OyoTA//LrfJ2V0HgQstEXb646/MYHLnpqdme0CaP2acdDsK6I0BOC+7zND0pjkSzMw+Nb4aLpoR33EPNtfHkmatdHlxOmRzOIMeppZ1R4DZVHm8g8FoJjYzoLGPPLdn2U7175wTSGRn5DfZMLFkj9kRajTXt9gvRs86p+uMc4wDHE1uNLq/rdcOVjkefgZHq6P3ZHfgo9ra6TRu23EO/3IItm3ZVcej5z2U8jEb1CgWiNvkNg41wzg6EKUyRdlNjlYHmMuC9uPCOWi46Y4b4hGXW6AHvRyX9rUe8WjHVM8ct1HDw9six4rhhtEPefgXxUSL+NvyuA566Bg3IebHYhdcjua57Z7TK7ZhkY3znBPO0z4H+kAEzA573Gav7nWGOk6MRyM6OuRUFwzholEPVTPTIDU2xzvw0ZrLvrN/8MAyuaP3TPxaHO3R5Zo92k4QVgP9HPHgxzU/U9ud5+Op8PgkHccxRHMzw8jT/HtquIaPwR9EGemARj9udpbabq2pa4SqHAdgwC2jGbjMIC0+ep151uBsH/D4b0GAPg5pi/8+zEkpffka//jIZw7XvSVyOtqxPX/SHjfEuMeSg3wQPTqD+S196EeCr241trEdzFCe5mhcNGUkTR3Wlwc//u383fB3yWxDSOWN7Mft13/ZE91kMgvYvCYf/IHWaweLoYfiMjr28w1iwAfcw7WEmJ5zYIfrs7/twySn8j7wMwf5Gr9uaKDQOj/tyRh+mDoDNI5owIfNYgamO762KYgiMgfL455hiMB1ioZosKF7oK51CD+DQ74HUgd20B5+2ofZE8HqEDF6SLQLDLIM7IYBGLLQsr7iWipimEF/6Ad+2Id8IJh6yCGo+R93cAZ2YIZ1aK39mzlXA66lcQeYkZp+KMD/IfQOe/sxHWw9B3sgyzMsHFqseOhCAZKjOVKeASiHOiIHchgH5lGGAwqaFIQ2teLAFouafGBDN6SPHos5puu/zmGuS3Q6TVTCHYQwH7wYewBBSQQQEWs2sVOGJOzEVcxAcACaA2KecXigcxCui6mHICTFBukHengHUDPEQhxE6kkac4AglEmHdFAHdQhDdnCG0XoZi9FDqOFCaWQjmcHFXMyRNsTGbeTGbvTGbwTHcBTHcSTHcjTHc0THdFTHdWTHdnTHd4THeJTHeaTHerTHe8THfNTHfeTHfvTHfwTIgBTIgSTIgjTIg0TIhFTIhWTIhnTIh4TIiJTIiaTIirTI/4vEyIzUyI3kyI70yI8EyZAUyZEkyZI0yZNEyZRUyZVkyZZ0yZeEyZiUyZmkyZq0yZvEyZzUyZ3kyZ70yZ8EyqAUyqEkyqI0yqNEyqRUyqVkyqZ0yqeEyqiUyqmkyqq0yqvEyqzUyq3kyq70yq8Ey7AUy7Eky7I0y7NEy7RUy7Vky7Z0y7eEy7iUy7mky7q0y7vEy7zUy73ky770y78EzMAUzMEkzMI0zMNEzMRUzMVkzMZ0zMeEzMiUzMmkzMq0zMvEzMzUzM3kzM70zM8EzdAUzdEkzdI0zdNEzdRUzdVkzdZ0zdeEzdiUzdmkzdq0zdvEzdzUzd3kzd70zd8EznXgFM7hJM7iNM7jRM7kVM7lZM7mdM7nhM7olM7ppM7qtM7rxM7s1M7t5M7u9M7vBM/wDBR9IM/yNM/zRM/0VE/01MbSnIb3hM/4lM/5pM/6nM9qQIb2FE375M/+9M9pEAbYtIYBJdACNdADRdAEPdBrEAd9DAgAIfkEBQUAAwAsXQAfAJQCYQIACP8ABwgcSLCgwYMIEypcyLChw4cQI0qcSLHiw38YLWrcyLGjx48gQ4ocSbKkyZMoU6pcydIjxpcwM7acSbOmzZs4c+rcybOnz413MsUcSvSn0aNIkypdyrSpU5oEAAAoQrSqVZkH+1hooEPX069gw4odS7ZsWKlSQV1dy3ZUVKk6zMqdS7eu3bt4CaIFkEga279E3extkLew4cOIEyv2yAEtAlqAI8MEJLUBggzDXi7ezLmz589hTQ0wUCGR5NP/hjWWIuUUNHzRYIKeTbu27dshUevGSKzPqVPuBsajxy8m7uPIkyuvvfu0v3DJwJU758xd8AHwoOWLrXm59+/gw9P/bV41nzeB5weMM7fOunDixsXLn0+/vk/y/94p69atYLhy6VR3HTzybCebfQjSRow/+dRDT4IQ7nQaNMycM443/RHkzTjntHfdAMMVd2CEJNYVTT/50CNPPNa1GE2JMOZ0FTTtCORMOuWEw59/5ajTzofZGdhdjEQqFQ0/+NADDTwtOlOhOeQog6Ey/hRpJU4Y+WMPNAUxY844O3oj5gDfkHMOO+4JFE89/RAz4pVwrrRggyu+0yI76pxTzjg68uennw/GKehMqe0jDzwEOaMnODsKxJ8y5vgIpHbcYTXopRqdmOKKLbazTjrmlKMMo3+Wyp83yqxDDKasrvRPP/XE//MOQeuYI2WjAn3DIZofhuimpa0GW9CRSS7ZJDOgRsmomGKa2s034ZBjzjnMtBOPsNii9E8090Az60CKlvMNrgJBqk6a2BWYGbDZwslPPdDIeuw5UIaD4an3lgqOMuWYk46H7rwTDzT07NPuwSX9Qww/9CBKkJf7ZegoOGYKKNA79PQzJMIlDkOQO3iGOg6p+DobzjjTqcNrwAPXs0+bHMd80j/+dFsQOxaOi94A/a3noZr4/CozglUOVOsAGDLr7LPKSPvvj9bBM5zLRQ9tdUrbGuqwQO3gaK/EAv3XnkDw0OPPxlcn1w+IszIzgDJIO1rqySmv/E529ODTj8dp9/89EzGwykrrlxgWpMw5Pw7wjnZo+w2aoQOpk6NB3kQ7LTMCsixPPfn4s6rjoNtEcz5LJup1f2NKNzZ29VQaOmg3lsNoQeAMkA7U7khNj8vRfP7671gOo3WX4qJ+3ji3B/eOPBqzC/xcaw8QnKLkjIvrfz4KxDnMz3d/nz/wJnpOxBOXs3o89qzrvVn8EIQzOfkOFE6kNa5Z9fr43xcN6e98u07xBDlc4gh0tn/k7yn44FJwagUmckGqWgOAhj1ic8AKHmUY+GCRjc7xtfKhSU35aJwFdyK4AdRqP+lBD6TYAbQXjfCFRnmVPPonEHVUD18bSod7ytY7A8KQJ8zIUQr/c7UrxcUDNj78oRJ9gsFr2chW1zPHByMYQuct8STtkNw3kJbCMgWIZUi8ohh/IsOt2VBn6EFejUDUOiuOUSMlvBH8DPIfHSqOUkl8ox55IjwuCQRnOiLI/D64OBHtkSOzwtmF6Ei/OxrokJD8XsO4lo4LScwb5DgX0NQXyYiwA4pgext7lKedzHTylD4hxj6gcZ1PBlJ+Z1KePAqIymGBKDhds2SjNiRFUubDlLUMZk/8MckB5PJUueqRndwRj324CZWq9OMAgji7gZSJOrNa3C/zKMxu7oQY+VCcQGpVzXJRJzjwaCM3r/gPfsgDXFAkiBcHKA9nrtOb+NwJMR2W/8vC5SqT12HcPUcIPnEO4Iz+FGV10mXPfDoUKeCU5v/AMcTDLTSdFIThPZxoQnO8UiDSYUY2iSO0h5oUKfvkmoUa9aweBbSK+VvYDFXaQIKoMTjx2OZAT8pTnkTTaLID2yDRSY+M/o5mxTRhUBs1VMXN0o09jWpPolEPcI0voZi0IxWhyrFo2IOjgExomc6FU3xwUqpoXUr7/GcOihJEdUQ1qsyi+a2D3jCFkLroU3ea1r4apaqUhF+GHoW4OxryYGU0mkf9BNJyMOM6OS2pXyfblOglkoNgk44mMcrXK20rVte5UU3TiDh07rWzlE1tKg0WueoN5FHmcIZhUVuin/8CFY1h6+Umuara3i5FUftBjzfGitPWeTYaCaxrWBs11gGaTYS+jW5TmKTUavJnkLMt0avCN5AsCjaAsYVs0Hgr3fIihbXGXKmGyGHHNbmQPlk7VEH+16eBwNW0BaStefebFHjMqlbhoJ35sgsemsGrrsaUHAoHsqHSCkQ7v9IvfyfcX2NWcos2Lax7k6Ow4dEqZ/EbQFOx81zyUvjETEmkRwX82Fm1jzkM8hZBuibEUGo2YA+uooRRzGOnaNFwA5AtogDLmYXRg6N/PMddKxqpNJUtvz2O8l2AmyExbVEdBrkH9+4yutJ1V3IdfCt7eTUQgZpYymhmSjgXKLuH0KP/czs+ipGRPID3jWtM8mtymhZnj/zGOc2AZoo7FMWzg2wRQCwkyDu/El+DJlhU5BoAxc7p5Dev68yBzjRY1rEzDaXHcuqQbZmVsl1pJnkc1jOcOaq1Z2iwKT6ajrVd1vyQblgOgmq6yUuGcSIUyffLoASbrmLZK+JcGtOyTvZX7nHLgbhNxJQ7D6qmw+mChLMjqYmGP/ixj3zYox7ykEe84rE1g7yPVP6hX6vx4ec/K/vdYBkGrLAzkJCNgyC46gY41hMgizhI3CDy70SyaKt7yXNXLSJbwSKMbHg7nCyjO/K32lEhUSHkutPBNUfa4Qx2rIMZ6kjHOegVqnKQYxzK/1BGqsErqetos4fQfbjMD6OwftxjReBSR700VOhuTPtfiWIHO0CeDpGb4+gmP7kywvG1peFqTMw108oULqI3zfzqnskavBwGMhyh2tP3Akc4SFYqPCck0goxF9Qu9ppKNRzrcC+Mwhgkcem5o+Jw88g39qWMcYyDHP06+jmKro51rMNiaiIprOPOeNxgRN5b4jrF9WQva4q97+QAfL9Gfg51qIMZ62AH7lpE+g8VJEhud3fjV7+Yl9BdcNZhhzMyV/qFmB478JBaPAYGDWiEe3fNiznrh8/hmtvjULrnve9/X4962AMf+djHPvjRj374wx/RSP1fiM99++BHMt0Pv//4x0/+8pv//OhPv/rXz/72u//98I+//OdP//rb//74z7/+98///vv//wAYgAI4gARYgAZ4gAiYgAq4gAzYgA74gBAYgRI4gRRYgRZ4gRiYgRq4gRzYgR74gSAYgiI4giRYgiZ4giiYgiq4gizYgi74gjAYgzI4gzRYgzZ4gziYgzq4gzzYgz74g0AYhEI4hERYhEZ4hEiYhEq4hEzYhE74hFAYhVI4hVRYhVZ4hViYhVq4hVzYhV74hWAYhmI4hmRYhmZ4hmiYhmq4hmzYhm74hnAYh3I4h3RYh3Z4h3iYh3q4h3zYh374h4AYiII4iIRYiIZ4iIiYiIq4iIzYiI7/+IiQGImSOImUWImWeImYmImauImc2Ime+ImgGIqiOIqkWIqmeIqomIqquIqs2Iqu+IqwGIuyOIu0WIu2eIu4mIu6uIu82Iu++IvAGIzCOIzEWIzGeIzImIzKuIzM2IzO+IzQGI3SOI3UWI3WeI3YmI3auI3c2I3e+I3gGI7iOI7kWI7meI7omI7quI7s2I7u+I7wGI/yOI/0WI/2eI/4mI/6uI/82I/++I8AGZACOZAEWZAGeZAImZAKuZAM2ZAO+ZAQGZESOZEUWZEWeZEYmZEauZEc2ZEe+ZEgGZIiOZIkWZImeZIomZIquZIs2ZIu+ZIwGZMyOZM0WZM2eZM4/5mTOrmTPNmTPvmTQBmUQjmURFmURnmUSJmUSrmUTNmUTvmUUBmVUjmVVFmVVnmVWJmVWrmVXNmVXvmVYBmWYjmWZFmWZnmWaJmWahmF0oALuEAKcOkIcrkGjrAGa4AFdkkKTfmWpCCXc2mXd+kEgpkDhGkCJkABJsAAFKAACiAAjvmYj3kAkPmYOSAN0tCFvwAJJZIKlzkfkfmZoDmZojmapOmYldmZpkgFBREJK/EIj0AfpRmbjlkAtFkAEHCbtzkBIAACGhAEvhkEO8AEwgkFYYALr6iag/CafuOYEEABu7mbvxkEYSCdYRAGYHCdeQAGczAHcNCdbdAGaZAGaP8wBuTJBVFABVSQBVZgBVnQnoqQiq5pEKoJOnLAnd75nWlQBmUwBl/ABVmAnuuJnuh5ngJKBet5oAZ6oApqBXDgO62InqCToApaoAW6oBRaoQuKoFnABV/wBW3QCqoXk20wAFEwABl6ogvanhz6BWOABmiQBt/ZnXOQBzT6B4OgCI9QCZjACTwaCrwwFEBpBQIhpAMRnjG6nTVqo4qgCDq6o5wQCqEgCqmQCq3QCrBQC7XAC7zwC8DAcDAhbq+2eEFJpVaKpVr6C79wbN+HEezAL2eSHVoGpE+5pi82Jv/xptrRbiHqk6gxDOWQUPIzHewQJHp6lWtBDO+gZCTDI3j/CmdiWpUxAStcsg6KyliCJHVlIyRWV4P7cyiU6neBwn+80Q+RR6nkQFFhIm3R0iGZCnNvx4HDwDDxEDtNVyrnMIDGtySm2idg4w2TxgzDsQ+pR4Lg4y0QYz1O5yffQGcCmCX5cCjvw6u0YybMQCDC+qgS2KnwYGfJqi8csg4Esh0MiBHRYCjxgDM11qv7Ri2tiq0FuDDgBg9e0kDd6id15AwhgoHkmiLxQKk5skvoQTHs4Sub2n/+MEPzmi/1eq++MoLkug9Hhq71JVySJi3sAA3XKnzy1z7MsEg8k6yTBq4F8l4s+Hj7ECsSi1XngT3o42f0Rwz2AA/j8yevdSoP/7Q49XA/OJir4RJmjjJs7ZAxBWt+xOQMbYV278EPfFOEGGFz8hA76NYstrZqGHtp5scPFDJHHytI55BOwOSEucpAhXMe/DFsR+Q6w6dKMislCHE4R+SgVdi0DYMj6FZoIiZFJbanPEZVRhtgZpdGzAANxRGG8fVJ5EO2z8JegitZyeYPWYtbb1UO7CAPJFuGWXIP8JAOp8pS/QEp7mBWGstf/7APa4u4QtW19QC3bJgaDGO4nGtr5LAORRW6vSUP9GU8GoI88TC4eLgt+DAAOVNl0oY80BB80kUz8VBJBidg60C5equGgEMP7PCvoTQ/7ZAPjItWyKsOlnQQ8+MM9v/wTIfIurbTvbmrDs77vOzkuGdkqQPhufjwqnyIVNNbTo5yOPBgvN30KsmLaqGENLpLS5cIOMl7Kwx2PF3bPJ1EM9DQvv8LKfkrv4q4LUoFucyiu9whRgTMvZD7vl1bdabIvzMrMT6HNJkEDXKFPwrDD/07Ow50Du+wD7QbigtTwB0MwOkQD73zPCt8UMXjvncLvtkbiwbUv4BaaOOgDtBwNn1DvpLjVlsbNpJLDxH2i9BwYQeBSUqss9hCvsxwqkMUqLKLtsTouMobSsMVu0XFKjW3UZpbt4I0xVDWjNEgD1+MYXIDwIFbuRFCrgzzDjo3Kv8rYo5VvEPbjAf7xWH/LG3kwA5m430LwmwMZC/SZrdSrMT8UMXcWMfr4FoUO1ySS7nL4cdPqycRM8iX3EzHRo51zA6efBDpQBBLyxk1V1WS47+oTCb8cjv15HbsGA3SWw4LgSoH5Q6uFj128bDQ8Enk8DVhzGBNI0VHtDdyGo/AfHsLoSurRqiMVnP0AMiicmfPDFIoow7p1A/a54/2MBBfksvCJSariq8FM8u69hL701Ejg7S5ssvu0MteqpALAyI0VnnRhm8/Z8xsshG75g9rkyTiRm7w0HHr4Hkjd3TNrLCUE88Yq6fq64+d2q+KenFg8yzrYc7j5l8dhyygUnKZl3JMJ85LsxCRtm+r/9ayXtrRCtll8moreJwQw0Wz74xnQFwRP4cxbVLNLrnCsTLQ4zwR0BIOKed3mRd40zJ4nhd6xozOSL2T8QUPn3LVopc7UtN79JA3+MAP/HB9N60baykQON3WcB3Xcj3XdF3Xdn3XeJ3Xer3XfN3Xfv3XgB3Ygj3YhF3Yhn3YiJ3Yir3YjN3Yjv3YkB3Zkj3ZlF3Zln3ZmJ3Zmr3ZnN3Znv3ZoB3aoj3apF3apn3aqJ3aqr3arN3arv3asB3bsj3btF3btn3buJ3bur3bvN3bvv3bwB3cwj3cxF3cxn3cyJ3cyr3czN3czv3c0B3d0j3d1F3d1n3d2J3d2r3d3N3d3r393eAd3uI93uRd3uZ93uid3uq93uzd3u793vAd3/I93/Rd3/Z93/id3/q93/zd3/793wAe4AI+4ARe4AZ+4Aie4Aq+4Aze4A7+4BAe4RI+4RRe4RZ+4Rie4Rq+4Rze4R7+4SAe4iI+4iRe4iZ+4iie4iq+4ize4i7+4jCe2fow4zRe4zZ+4zie4zeuukg5DT7+40Ae5EI+5EQu5NWADE5Z5Eq+5EwuDE1pDVAe5VI+5VRe5VZO5dcgDl8YEAAAIfkEBQUAAwAsaQAkALICXAIACP8ABwgcSLCgwYMIEypcyLChw4cQI0qcSLGixYsYGZYy42ZXxo8gQ4ocSbKkyZMoU6pcybKly5cwBQIAgOGfyUkGZka4FbOnz59AgwodSrSo0aNFARggJO2fzZEvZs40g7Sq1atYs2rdyrWrS0JuVDkd6zQkB6kAqnhdy7at27dw48p9SLauXYxdpBKwNLev37+AAwseHNGu4boVh1WxkAEP4ceQ+w6LRrmyZX/RMGvOnLmfZ8yRQ4smebg02dGoU2eN1g8fPWjwYr9zR7u27du4c+u2p7q3b4emg5f9Tby4yWH98r2O504gO3XnzEmfTr269XLYs2vfnj0dPuPgfwv/Hz88vPnzB4n5Uw77nXPo5ZSB69ZtgDdv9PPr38+/v//85KAnIGTkFVjegAiits8A0AzQ3ADOwDfOfALdV9B/GGb4nzkJdhiYgQV6KKJc6u1TT4MDOcPMOeVM6M1C4YxTznTR1WiOjTjeeOM5PPbo4488vhPNiET2BSJ5RSaJFDHJDeSeQOsMFM6L+hkEjjIzqsMObe/E5uWXYIYp5phf3qPkmXAdGVw09PiD5psr/RMNe/A82c466Tx0ZZZbDtAlNPXk488wAxEzgKGIHqpooowu6mijcEbKlpqGufkONPlIqmlGctqDojt4mkPOlAt9g6U5Wj4ITzz04NMPMQdu/yorepT+00865TDjIDz1DDnrrwr948898bzTDq5T5mfhQeUMkKpAq9JjDz/RPAXstQkeyU5+ypzTjjuX8oPttcLWE88Ax5JD4UGmDsAhQavKM22149ZLZIHQvDgAfeCUs6U78dhDqL1oOtWPuRCmQ843F5o6YzrsDATPQAtaS/DFRQpXTznf0HdfN+Ok8+078riJsYf/MEkPPO44c87CFypjTpQCuYeiySfn/GZp/rzjsjL07dtNOOb8C80+huocXsr7yMOyMwp/o69A3cgcJTzy1LMPzkp3LWldxKxM2zrNUt2NNyHv2qvXqjk1TD6wtfzy1FTLHDHW/CTN9t6bkv9FzD7Q0MbOOeEMRB/RztB2NN+POTUnNLO5TA7d+9o9ANZIM675rGT5I7Y76kxu9jfkqONgPGtvLpfj+EDessL2Ge6N5ZirbvuvY/0duDvsmAOO0PTJnPil/dzu1VjDFsv7OeNciPY5W2Kut/HUfz1WP/K8Y2w64+h7X79RAozP9NUXhfyJgjMfNNXPb3lp5uXH37fb+DAHqjkMA9/tt/C0KX9Q57Pf4JpHkLONA3rgwhT5/sfAnY2FH/Kgzc/0dbiZKW5BDWwJ8j43QOcd0H3ygF8GR2g9Od2jTqDimNnQlid38MpXJCSNnOo3m3WYQxl06wbp0jE8TA0shkCMFFn/+OE6Z5iDVEILBwLDFUROGSx7PrthAXVIDpElMB8/bKIW4TQWNqFQYfXBjw5zdTp8ZHGLDOmiub4VuimCo4ojO9oZ0UjHM+UOcII7ouGqZo6R0aN4dUSIU4hBxNn0Thl73KEztOfDQDqyhJ5j2bEIaB9vgK+MC9ziBlnmDu7lT2ghiyMWH0lKTd0RGt+y4e8qWTVvudB/mhwkHnnnOwoOrWhXhGEpdwlJesymHedApNku6Q5MAZEs2INHOyY5NQO2EHW65KU0SziM+tGGGeVoJshc2b9olq+L1kzhKpNojh7mbZroxN0TIxdMgliyHFFiYvWGWETmJbKKp0tdOvfJ/znH2SMeqVSh2bp1Ont4k22dqwcnyTbO4JUTXPIQFz8nSq51yk2YVANfAgGJUFnu7mf3NB3A9EnRkgKLdfYL3SeD58p4mFFnnfsc2fLHrT4m8JwmzSm2rgdFI2J0X0SLXskIRpZohNOne+yXSKGp06bai37KUynwWHi6TJ0UmdmjjUqpxNI44tSpYK3XE1k2uMIZLqguJKkDz8fJsiYVngU9aFjnelXdOUiq7AtlMa2aJLDxgx72A53o9OdKedL1sBdzSiRpiUSg4pKpKOsc3Dh5P7PmJ6j5lCtiN7tT3WkVZgOhqmHNA7Z+AHY27miHOqS4wrTdNJOcje24FCu23v+ZlWqIE59mR1MXf7QOtcsbx0orGDGAGVS2yFUa0xrUye5V6D6l25U88MG1yJTWXKhVbXym2I03inS0yQ1vzspFVj0Cj2jMaAdB6iFRwdTlcZQd4HAdarrMive+Xlsuurj3ovu86BvjMAcPB9KgfeyWK6U9LW20+9P8vBF6DoJoe/FL4a7JSaHv6N04C1i4c+gKWtP1h8W08t6mxfdl872lOtRLm/6JsMIwzm8hj7Xd0O6LIB5W7+UA9aoRmw+Z6FswrhrML3KcwxkRvtRxY8xkxl24ThBa7WANMjsBJ85PrDJwrFxymGiYuDaDW5iF9EO0FUeYVV9tspqd3A9PTcz/QQM4B0KCFo5yePhB8ZCHoLZcEUr5A7sLXi2RdfjBCGMtHwdes6Lzux55nGsguLrxcwcCjgCvuDnwgMY9euzjARiIGJnxhz/4sY984MMe9aCHPOQBDWjEIx4nBi3wVMzid6COo4vOdfmiIS4URVlUlAutzHjIJWjQg1qgFnU/SG3qeqR61a1+dWwEoptqq5a1ZqMihFscwkTr+tu28+3lBNKOFakrh/UZAJbOsQ7aEKTat3EGO9ixDmaoQx3p6JF0skOOcYxDGcoIR4plll4H2boeuAa3wmMI2Aetg0VAS3e2w0GOHU0HO+ToN8DDEY6GSrySoV1WyIH3YCRz28AL/0/5FofBjxPN5teT+7h/RV4Qml9IQ/spc60DlnCV+1yL6sGH05pT7peBQ4x7zJAlOa4Mf2ccOzQ6RzrSoQ5mrGMd7GDxK/MB2597fYtebnhzHg516fBo6lW3OjucgWQnHQTexUb41+c+TZa7HLi56VJsXt3qVq9aHvSgh7PvgY987GMf/PBMP0RNGbo7fp9M+gxmGv/4ylv+8pjPvOY3z/nOe/7zoA+96EdP+tKb/vSoT73qV8/61rv+9bCPvexnT/va2/72uM+97nfP+977/vfAD77wh0/84hv/+MhPvvKXz/zmO//50I++9KdP/epb//rYz772t8/97nv/++APv//4x0/+8pv//OhPv/rXz/72u//98I+//OdP//rb//74z7/+98///vv//wAYgAI4gARYgAZ4gAiYgAq4gAzYgA74gBAYgRI4gRRYgRZ4gRiYgRq4gRzYgR74gSAYgiI4giRYgiZ4giiYgiq4gizYgi74gjAYgzI4gzRYgzZ4gziYgzq4gzzYgz74g0AYhEI4hERYhEZ4hEiYhEq4hEzYhE74hFAYhVI4hVRYhVZ4hViYhVq4hVzYhV74hWAYhmI4hmRYhmZ4hmiYhmq4hmzYhm74hnAYh3I4h3RYh3Z4h3iYh3q4h3zYh374h4AYiII4iIRYiIZ4iIiYiIq4iIzYiI7/+IiQGImSOImUWImWeImYmImauImc2Ime+ImgGIqiOIqkWIqmeIqomIqquIqs2Iqu+IqwGIuyOIu0WIu2eIu4mIu6uIu82Iu++IvAGIzCOIzEWIzGeIzImIzKuIzM2IzO+IzQGI3SOI3UWI3WeI3YmI3auI3c2I3e+I3gGI7iOI7kWI7meI7omI7quI7s2I7u+I7wGI/yOI/0WI/2eI/4mI/6uI/82I/++I8AGZACOZAEWZAGeZAImZAKuZAM2ZAO+ZAQGZESOZEUWZEWeZEYmZEauZEc2ZEe+ZEgGZIiOZIkWZImeZIomZIquZIs2ZIu+ZIwGZMyOZM0WZOC6ARr/0AKxCAN0mCTJXEAAhCUFGACOOkIuDCST5EDMRGUTBmUQKkAFJADa+AIpMCTPjkRYIADNDABXAkBEFAATtmUUCmVVLmTfvgHkYBGYVAQeTAHAgEHA9AGA5AGBZEFWUAQVmAFWaCXX/AFRAAFRIADI7ABXfmVYMmUBxCVTuAIjmCVbwgJkGAQd4lGViAQeckQVKAQeWkFVLCXWUAFm0kFURAFRBCYLdAChDkBXlkAh8kARDmVuOCYb3iZc/UFXACam5mbeQmae6mbo1maRHCaqWmYrkmWVdmT8UgBB6AQlfAHcPkTocAJmPAIf5AHcNAGaTAGX9CbuhmaVPCd3xmav/8ZnKjZlSbgCOvoCE4wAAKAECYgEJgwAGgwAJlJnz5xGsDAC7UAC62QCqGACZDwB3NwnWhgm92Zm+AZnglKmiDAhmlQmZGCnglxAO8pEIMwANs5EN85EM/JZYdxEMPwC7VQC/35n4rQltipndx5oHlZBmYJjhK6nAixngMQn2UwmfUpEFxAl5UQCgMwRyiBJA2Rn7zAn6KACSc6B21QoFywm4hAgnNQn4rwCHDxnVwgKa4wAH4glwgxBs8JC8DQE0dCESFapK0QCrBQgnu5WXlQBgSRo0hRKw/YGvhQp3Zap/YQeKmmp4EneH26p34KDaw2qIJaqICXRVQ6VxuKYLX/wmf8R0iAJTnzgSFidDbKcqkek6kaEjG416inYX8s52gDNKkHgXOmeqp5wnue6qjl52VOY0Pd83EJgSXckR3Wcau3CiRAwgwT5nurKn4sJxDMYA6UBHIIUWc8FDAi1mnq96vVJyxwMwA0MzU2RxB1pg6ZhmjMWn+14g+Ls3zEADc0JnDVWhAAxm4uNgzb+n8GEg1AQzrrUA9A2nvEYA/wQDjUGmwE4Qxo1nULKBzFsx/dAg3VdXsX5g7mVaoUl6wD0HMaWBrx4FwTZw7u0KuwJyfy4AzlsGGGowwiAygFa4Jgcw8a2zHp5jHjwAzy4K+jJywZK1Axkw7xgEEzaBf+/3Cv4SBxNRUP3oZ5T7QOU1ZA46AO8eCwN0gWw0AP6iBcIddd5eAMFuuz/0BES7s+skMOzECwRVgX+/AOvqOzBsQM9HB5TBMP6fBThvMNTysPPfuDRQUNZ3tz3cKzXpcy+ICzpQoOfUQPbbu1ZIEP7CBrQqO2UPttjlMP7rCxkmY2RPMOAsOFyAQPviM0QoM28dpkiiUP2NRf2jS3NBuGfiMPS3tzSkS34eU49DBTBhE8Mvu5aEgW+aCx6Ka2FbtZbkMP7JBNq4s2WRuybYg88XAORzdFQ8u2TTVI9aCxw7tH3kAO62C8epg79MAMlKQfzbsOfLtPg4QPCMux+8K70P8biA8kuR5HH/BKD/PaREMkuY01UOmgtYroOKIbIO7EL+bwDi9GQuuLr3Irs74bv/LLDPQ7RY37HQzUOWaLtuQED1FLiYoFtzgkt+dQtMZTVPO7uk7rDAYcigYDwRisDOoADUaLMRZMvZTDL097Dyz7iU7BD8F7Wx9DHykLDX27VqibuydMRWKbvqlot17LsfjhDeXQDtkrK3bRD9AAtJ80Os5bxLjow/hTQPtCuPSwwrTyXgqlDuVwW8x7QDxrxbQoJ/SgsXuUROcAD1yHIGBTP8OqwK3lv8roskCrsOWgDsVkD/9LIHWBxEbEtBhcZBM8wskoLNBAvQoxNOUgMgL/kcdpklDvgCtH519JR2gz863ZSMiG3BCrxA5otq5WATb5EA+9I7E3dziJDA9LJo62skbIghAi111Gxq9/BCtHURcQ1MdSk8OHU0XuwLdgrMrrARttLKtmA3IANjOZhg/08hF+lsVbzLmTfMzrAA0NfI/DAjlaDDQNca7r4GKcsWz8YGr4sKes5mrSZizzZm/QwSMzUg4Z928bR676qixWM7O/zI9GBTnDTMyTRjWlCjwOQTmS/MeIjK33UMMHOSdO08ZIlxGnuh9vlA69zMga6arwAKscFyNOV3Y3MnX2tg7yBi6r8mqDqqd1inj8wHj3fJIrfZUu/dIwHdMyPdM0/13TNn3TOJ3TOr3TPN3TPv3TQB3UQj3URF3URn3USJ3USr3UTN3UTv3UUB3VUj3VVF3VVn3VWJ3VWr3VXN3VXv3VYB3WYj3WZF3WZn3WaJ3War3WbN3Wbv3WcB3Xcj3XdF3Xdn3XeJ3Xer3XfN3Xfv3XgB3Ygj3YhF3Yhn3YiJ3Yir3YjN3Yjv3YkB3Zkj3ZlF3Zln3ZmJ3Zmr3ZnN3Znv3ZoB3aoj3apF3apn3aqJ3aqr3arN3arv3asB3bsj3btF3btn3buJ3bur3bvN3bvv3bwB3cwj3cxF3cxn3cyJ3cyr3czN3czv3c0B3d0j3d1F3d1n3d2J3d2r3d3N3d3mT93eAd3uI93uRd3uZ93uid3uq93uzd3u793vAd3/I93/Rd30ihD/id3/q93/zd3/7N3y39kdMw4ARe4AZ+4Aie4AdeDcgQkwr+4BAe4cIAk9ZQ4RZ+4Rie4Rq+4Rl+DeJAggEBACH5BAUFAAMALLcAKQCOAlcCAAj/AAcIHEiwoMGDCBMqXMiwocOHECNKnEixosWLGDNq3Mixo8ePIEMW/Eey5DCC0QakXKnSXzSXMEXKnEmzps2bOHPq3Mmzp0+cJ/MVhEf0XUh37+JBo2ePnz9iP6NKnUq1qtWrWLNqXUjM3756PsuZS8fMmbuz7uDFk1dvX7+TW+PKnUu3rt27eB9+HRDPnUBnA8cZ9Eazm+Fu4JSJPVcWbdq19PA5zUu5suXLmDNrNshMILlwAw3vPNzNm7fSp7t9C0eu3Dl17ByrlRd58ubbuHPr3s37oNGEphGCK2juXPHjxpMjLy7RODll4EgfNm368Ddl5IrDdvwOHjS2+572/x5Pvrz58x39Dez78bd7ge8HxCcYj6/9+vgHwHuH1tm6dOaU85l0BE7HmmtktYNWUtDAhd6DmpUE4YQT7iMQewIxc045AnXDkGDnFFQfPRZCJdA/A6CoYoosrrjiiS3G+GJX+9gjDzT78eeOM8wAWM440RFYHWneHHhOOuukROGSeZVEUkijrPDACqUwaSVOQhnVjoYDCCbQkAaBA6JB0Ayk5FRd8YMPPfL01d9/AY4TToFDHhYOPlfmuZWTfHZEjAQABFqBNHoWylE09hiE2gCiSdQPXmmu2aZj7cD5YzipTeeNX4Z2KhWfoG40SqCkquLpqRLdIx9G9PAWKZvx6P/oTqXpbDgOdvygqqtOoPaK4kW3kAoAAbvsaqxB6snXjjocDsaaQOsgdCZ6r7Yp67THZhuSr71etASpT2i766/1QQTPAPLcw080v3aapj0miitvR9xyW1EjZEwyr6f9tCpQiA01te/ABGdUb70FE0xMvwOl8+VCFiYs8cQSHWwvxbsSww895w7gsIcYhyyywRZ3O/KVxOwjj3zsnCMYyIERRE8/7Z5s880nlhwqzuelvDJEM9fM89A267wz0bhFk+VD8ASN9NM8G90n1JYpDc1vDTX9KNVcRy31k13ThWisA6xjzkHf/KWf02G3ffPXErpt1T/8/EwQYQhpLbTcfIv/DPfefecUTT3nspP1zPEGrvjIcA8D+OIgpQyNXw7jTVCza9MM+eZFG11PPPY4yDlH//jD8UCYEjScQGmxPfrrjB/cT7TyuQ47RZIP0E6Hd7OeeeK3B49xvV56yVc+wAuv0D/9yANPpeXMmbftylc/PKheBne2fvIka71B0eDDXoilEUSOOgJBs8/j37dfMJ/7mJN2QQ4fz/7rdMtjVGcHnWM4PPXwx/3cR0CClQQsBWmUQJrmvdsNbj8CUYblBsI/aGiugBg8WemuNpAJFkR9A2xb7gbyjeAYJB71wFYGVyiyBwpke9NTYdtKdzqGvEMe/EgeC3cYsvxhzSDjSIdf/6CRjxDibIToUwgK2cXDJvLMhQqJ1hKpxrzTtSx1BYnWDXPoxC4OLX+cUsg7oJGroYWvXF+CmYhSaEQvulFig5OPM87mwfUkSoN1+2FCbnjBN/rxi3lcCFIGUMaE/SMaKjtXO9JhvC8F8UIp/KMkoTY4NDLKIIAZAD5Ep63S1aNMqtsjGds4yVJiLFdYw5sJB9K9Yx0ykZdbSDw2SUpT2pJilXQI8jzFvM/9hnYDqOMAAPMO6t3ymERjnv4KUsekDEAoTPrHMGApEIdhsSCYi8cukcnNrp1xIKszSBgHcI+tlceTHCzb3erIjN3Bo3u17KY8e4jK0CAkiQOpBz84mf+ZVzqvYQO4Jv0GMsZ88HOeCKWa+MYZRfjUB5qWKd09QDmYCSpjKPQwaDwTytGRNe8iqrLLMDYGwUwKlCDpMJx8oBHAjXb0pTZbKEHGMT+HgPKgUZEoRQXysmAS5KID4FTT9kEMl8L0qDbzxz3sRhGjtEqGOZmm87CGuYKAgxwEGSM+oqFDpHqVbylplR4lsrIGWqQk0XiJP/rBj33kAx/2qAc92ASNnXbJpwUBKqfiQQ8ufvWvsDsJAg1SU4eAxXEqEQhb3QpXubJpAHWNRzyKIpGqhjKrROQqYDdrPaFY8iEqjcjuBvpC81U0IULtq1E5y1rFjfW0B7GsQwxDncP/JFCNA6iqVpnY2t5icGsdY4imhLkRoK6nr131rXIJ6FmNzM+4A4GhxwoSWv1kdrXLza71qpsQlY7WdwTNakG6QxQU9lG76HUjcBlKUKLwRSllkgdt6FGPetwDH/nYxz740Q9/uISrU0uvgP9YugGoJyVFHbCCF8zgBjv4wRCOsIQnTOEKW/jCGM6whjfM4Q57+MMgDrGIR0ziEpv4xChOsYpXzOIWu/jFMI6xjGdM4xrb+MY4zrGOd8zjHvv4x0AOspCHTOQiG/nISE6ykpfM5CY7+clQjrKUp0zlKlv5yljOspa3zOUue/nLYA6zmMdM5jKb+cxoTrOa18zmNrv5/81wjrOc50znOtv5znjOs573zOc++/nPgA60oAdN6EIb+tCITrSiF83oRjv60ZCOtKQnTelKW/rSmM60pjfN6U57+tOgDrWoR03qUpv61KhOtapXzepWu/rVsI61rGdN61rb+ta4zrWud83rXvv618AOtrCHTexiG/vYyE62spfN7GY7+9nQjra0p03talv72tjOtra3ze1ue/vb4A63uMdN7nKb+9zoTre6183udrv73fCOt7znTe962/ve+M63vvfN7377+98AD7jAB07wghv84AhPuMIXzvCGO/zhEI+4xCdO8Ypb/OIYz7jGN87xjnv84yAPuchHTvKSm/zkKP9PucpXzvKWu/zlMI+5zGdO85rb/OY4z7nOd87znvv850APutCHTvSiG/3oSE+60pfO9KY7/elQj7rUp071qlv96ljPuta3zvWue/3rYA+72MdO9rKb/exoT7va1872trv97XCPu9znTve62/3ueM+73vfO9777/e+AD7zgB0/4whv+8IhPvOIXz/jGO/7xkI+85CdP+cpb/vKYz7zmN8/5znv+86APvehHT/rSm/70qE+96lfP+tZD3gmOcH1DokAEFEwgB2vARXJ1TgqFCIACAglFnqhA/CxQgfYbAAHsiUEMQiWdEwNIAxcOkgU0DCASosDNI/4gkDSMYQBUGID/FcZP/PLT/gNBWEPvjz3+LAwAEiGzgkDkPyHgKQIOX8gC+cufhShEAQcuEASOgAvFVn4UM37jdyrA0AqRMAdjUH5UgID9R3s7gAW50Hxyhg94IhFzdSMe+B0gKA/5YFZCBgy1UAkOSHwSqH9WQHtMwAcE2GWlc0fpED0egRrE1SGIMQ7lkA7OwFf7AFU6RgwnmIIqSAVZYHzHBwVg4Ag41WQ1RA4lJBWaQlun4Q2K4T9rgQ8keGPSQISYMAdfEAUIWH7jFwVQIAeysHtFljarNBGy1RDmcDYOU4fTVSsDUiB6uIPmwAzuwFL75IVfyAthSAQsaAURaH5QgAi/IA3O/1do0bAxfcEM5jAOmbKH0sEajOEdAuNijigQn8gLlQAFX6CCiLh/XwAFnPALNKYq78AsyoBbwuQN42AO0cJUW7EwnwQP63AOeYiJ0iEm5qAOf8iGOGGMNDEIaYAQX9AGijAArCgvcTMRhOKIvIAIUEAECIiISIiIXzAHoYCBLZYawZSD46E09BAPzlCDyvANwHgY3KUQ07cboZAHZYAQ1icQyMhLJkONn+gKYZCN2wiBYLCPi6aLOEKJv3gY9UMeOVAQB2AQCahBCEMRjkgoxOAIYYADUWCGUAAMIwYO5hiHu4KO6sgO5vQQ7icTvGCQXLEGCDEHA4GABIEJLdlDFv9jEczHfLiwBkGAAy0Agy6pYKYjEIUlTr3lBAZBA24jNRXxhcw3DLgAkh32htz0CI8gSUYDY+WAWwSxDmSUXhrQAQPABVEwOlt5YvyDEOUQj+mljfQXPDojYidVYRP5PWm5YW8IGn7xhLI2lxAGD2fjlQOgDOcAQEMZa4ApYKGlQAOBT4lpa3nZWs6AVQgxDvgUbYt5VIMDGEc5EOTADrhYbfXiDm3pLxz1DvLjld9QDs6Amt4GKoU0AK3ZDoN1S+cCGgcRmrBZbiQRDZZpVebwDvcQmdVjIeRjleOwDqO5bvQQLZbTKKChTdgFOfHgMFNYEJhpV/RGD4ZjORN0DvH/EFLtAw2dQRhvaJif1W9rWY7tox6GU0J7aQ7nYpzyliuZWY6EMQ6d0YVt453BaRDDiQ/VmW8NySiLIhCtFDbtIF2qYw67Y58Bdw/BRRAekjbucJs3Qw/OUA4iGVu26ZcVdy7hZJUhgw/mWZiEOQDkAJYscnLm+KLZkg/QkEmqJEzMKYQzZxTkmScb4w6+GKPhUA7MAA3+WXMmCl4PEg/oMye2tZvnUEwpqXMfJUEPcQ6ZtBn7AA3ftRDK0IfQsIFM96GKsqJ48Q4AwxBEOp4ySnXANBEQ5RP2EA/REk54ZRDn0A7N6XXsxUzoGaMG0ZvtNUyAwQyd4TDb0yyNZKYz/5Wne8p3KwqoipJAl6QQX7oOsyR4n5kTQ6oOADQAEtp3VXUkA6AO61AWw+Re6fMdAxFShZQSBRp4sSp7tFqrtnqruJqrurqrvNqrvvqrwBqswjqsxFqsxnqsyJqsyrqszNqszvqs0Bqt0jqt1Fqt1nqt2Jqt2rqt3Nqt3vqt4Bqu4jqu5Fqu5nqu6Jqu6rqu7Nqu7vqu8Bqv8jqv9Fqv9nqv+Jqv+rqv/Nqv/vqvABuwAjuwBFuwBnuwCJuwCruwDNuwDvuwEBuxEjuxFFuxFnuxGJuxGruxHNuxHvuxIBuyIjuyJFuyJnuyKJuyKruyLNuyLvuyMBuzMjuzNFuzNqJ7szibszq7szzbsz77s0AbtEI7tERbtEZ7tEibtEq7tEzbtE77tFAbtVI7tVRbtVZ7tVibtVq7tVzbtV77tWAbtmI7tmRbtmZ7tmibtmq7tmzbtm77tnAbt3I7t3Rbt5ulD3ibt3q7t3zbt37Lt6HKd9MwuIRbuIZ7uIibuIdbDcgweYr7uJAbudkgooZnDZZ7uZibuZq7uZyrudcgDqoWEAAAOw==\" />"
      ],
      "text/plain": [
       "Plots.AnimatedGif(\"/home/wmkouw/syndr/Wouter/Onderzoek/Projecten/tue/efe-planning/ECC2023-efe4ukf/figures/planning.gif\")"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "anim = @animate for k = 2:(len_trial-len_horizon)\n",
    "    \n",
    "    p201 = plot(time, goal_state[1]*ones(len_trial), color=\"green\", linestyle=:dash, label=\"setpoint\", ylims=[-1.5, 1.0])\n",
    "    scatter!(time[1:k], y_sim[1:k], color=\"black\", label=\"observations\")\n",
    "    plot!(time[k:k+len_horizon-1], y_pln[1][k,:], ribbon=sqrt.(y_pln[2][k,:]), label=\"planned\", color=\"orange\")\n",
    "    \n",
    "    p202 = plot(time[1:k], z_sim[1,1:k], xlims=[time[1], time[end]], label=\"true\", ylabel=\"Position\", xlabel=\"Time [s]\")\n",
    "    plot!(time[k:k+len_horizon-1], z_pln[1][k,1,:], ribbon=sqrt.(z_pln[2][k,1,1,:]), label=\"planned\", color=\"orange\")\n",
    "    plot!(time[1:k], z_est[1][1,1:k], ribbon=sqrt.(z_est[2][1,1,1:k]), label=\"inferred\", color=\"purple\", ylims=[-2,2])\n",
    "    \n",
    "    p203 = plot(time[1:k], u_sim[1:k], xlims=[time[1], time[end]], color=\"red\", ylabel=\"Control\", ylims=u_lims.*1.1)\n",
    "    \n",
    "    plot(p201, p202, p203, layout=(3,1), size=(900,900))\n",
    "end\n",
    "gif(anim, \"figures/planning.gif\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b74da5e4",
   "metadata": {},
   "outputs": [
    {
     "ename": "LoadError",
     "evalue": "syntax: unexpected \"=\"",
     "output_type": "error",
     "traceback": [
      "syntax: unexpected \"=\"",
      "",
      "Stacktrace:",
      " [1] top-level scope",
      "   @ In[20]:34",
      " [2] eval",
      "   @ ./boot.jl:368 [inlined]",
      " [3] include_string(mapexpr::typeof(REPL.softscope), mod::Module, code::String, filename::String)",
      "   @ Base ./loading.jl:1428"
     ]
    }
   ],
   "source": [
    "function EFE(u::AbstractVector, \n",
    "             state::Tuple{Vector{Float64}, Matrix{Float64}}, \n",
    "             goal::Tuple{Float64,Float64}; \n",
    "             time_horizon::Int64=1)\n",
    "    \"Expected Free Energy\"\n",
    "    \n",
    "    # Unpack goal state\n",
    "    m_star, S_star = goal\n",
    "    iS = inv(S_star)\n",
    "    \n",
    "    # Unpack parameters of current state\n",
    "    m_tmin1, S_tmin1 = state\n",
    "    \n",
    "    # Start cumulative sum\n",
    "    cAmbiguity = 0.0\n",
    "    cRisk      = 0.0\n",
    "    for t in 1:time_horizon\n",
    "        \n",
    "        # State transition p(z_t | u_t)\n",
    "        Jz    = Fz(m_tmin1)\n",
    "        m_t   = f(m_tmin1, u[t])\n",
    "        S_t = Jz*S_tmin1*Jz' + 1e-8*diagm(ones(2))\n",
    "\n",
    "        # Unscented transform moments\n",
    "        mU, SU, CU = UT(m_t, S_t, g, Q=R, D=1)\n",
    "        \n",
    "        # E_q(z_t | u_t)[H[q(y_t | z_t)]]\n",
    "        ambiguity = 0.5(log(2π) + log(SU-CU'*inv(S_t)*CU) - 1)\n",
    "\n",
    "        # D_KL[p(y_t | u_t) || p'(y_t)]\n",
    "        risk = 0.5(log(det(S_star)/det(SU)) + 1 + (mU-m_star)'*iS*(mU-m_star) + tr(iS*SU))\n",
    "        \n",
    "        # Cumulate EFE terms\n",
    "        cAmbiguity += ambiguity\n",
    "        cRisk +    = risk\n",
    "        \n",
    "        # Update state recursion\n",
    "        m_tmin1 = m_t\n",
    "        S_tmin1 = S_t\n",
    "                \n",
    "    end\n",
    "    return cAmbiguity, cRisk\n",
    "end"
   ]
  }
 ],
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