KrusellSmith.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Replicating Maliar, Maliar, and Valli (2010, JEDC) to solve Krusell and Smith (1998, JPE) model using Julia\n",
    "\n",
    "By [Shunsuke Hori](https://github.com/Shunsuke-Hori)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Overview of the notebook\n",
    "This notebook solves the model of Krusell and Smith (1998, JPE) and succesfully replicating the result of Maliar, Maliar, and Valli (2010, JEDC)\n",
    "\n",
    "The solution strategy is as follows\n",
    "\n",
    "1. Solve individual problem by Euler equation method with 2D interpolation\n",
    "    - Agents are boundedly rational. In the code, they take into account the information about the mean of capital\n",
    "    - Aggregate law of motion is approximated by log-linear relation, i.e. $\\log(K_{t+1})=B1+B2\\log(K_{t})$ for good aggregate state and $\\log(K_{t+1})=B3+B4\\log(K_{t})$ for bad aggregate state \n",
    "    - If specified, Howard's policy iteration is used\n",
    "1. Compute the path of aggregate capital using the policy function obtained by VFI\n",
    "    - Simulation is based on Monte Carlo. That is, aggregate technology shocks and idiosyncratic employment shocks are drawn for many agents and many periods. Then, using the LLN, the aggregate capital is computed by aggregating all agents for all period.\n",
    "1. Update the coefficient of aggregate capital law of motion, $B1$, $B2$, $B3$ and $B4$, by regression\n",
    "1. Check convergence of $B1$, $B2$, $B3$ and $B4$\n",
    "\n",
    "Additionally, this notebook also includes the [result](http://localhost:8888/notebooks/KrusellSmith_Euler.ipynb#Implementation-with-value-function-iteration) with value function iteration as a solution method for individual utility maximization problem.\n",
    "\n",
    "NOTE: Regarding interpolation, Krusell and Smith uses various interpolation scheme depending on the purpose, including polynomial interpolation. Maliar, Maliar, and Valli uses spline interpolation in their paper. This notebook only uses linear interpolation because I could not find interpolation package for polynomial and spline 2D-interpolation.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Code to solve models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First thing to do is import some packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "using Interpolations # to use interpolation \n",
    "using QuantEcon  # to use a function, `gridmake`\n",
    "using Plots      # to plot the result\n",
    "pyplot()\n",
    "#plotlyjs()\n",
    "using Optim      # to use minimization routine to maximize RHS of bellman equation\n",
    "using GLM        # to regress\n",
    "using JLD        # to save the result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Setup\n",
    "\n",
    "Functions in this cell are prepared for model parameters and initial guess of the solutions \n",
    "\n",
    "- Types\n",
    "    - `TransitionMatrix`: collection of transition matrix\n",
    "    - `KSParameter`: collection of model parameters, functional forms, and grids\n",
    "    - `KSSolution`: collection of solution, which is guess at first\n",
    "- Methods\n",
    "    - `create_transition_matrix`: construct an instance of type TransitionMatrix\n",
    "    - `KSParameter`: construct an instance of type KSParameter \n",
    "    - `place_polynominal_grid`: create polynominal grid \n",
    "    - `r`: compute interest rate ( = marginal productivity of capital) \n",
    "    - `w`: compute wage rate ( = marginal productivity of labor)\n",
    "    - `KSSolution`: construct an instance of type KSSolution\n",
    "        - Guess can be the load of previous result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "code_folding": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KSSolution"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Collection of transition matrix\n",
    "\"\"\"\n",
    "immutable TransitionMatrix\n",
    "    P::Array{Float64,2}       # 4x4 \n",
    "    Pz::Array{Float64,2}      # 2x2 aggregate shock\n",
    "    Peps_gg::Array{Float64,2} # 2x2 idiosyncratic shock conditional on good to good\n",
    "    Peps_bb::Array{Float64,2} # 2x2 idiosyncratic shock conditional on bad to bad\n",
    "    Peps_gb::Array{Float64,2} # 2x2 idiosyncratic shock conditional on good to bad\n",
    "    Peps_bg::Array{Float64,2} # 2x2 idiosyncratic shock conditional on bad to good\n",
    "end\n",
    "\n",
    "\"\"\"\n",
    "Collection of model parameters\n",
    "\"\"\"\n",
    "immutable KSParameter\n",
    "    u::Function\n",
    "    beta::Float64\n",
    "    alpha::Float64\n",
    "    delta::Float64\n",
    "    theta::Float64\n",
    "    l_bar::Float64\n",
    "    k_grid::Vector{Float64}\n",
    "    K_grid::Vector{Float64}\n",
    "    z_grid::Vector{Float64}\n",
    "    eps_grid::Vector{Float64}\n",
    "    s_grid::Array{Float64,2}\n",
    "    k_size::Int64\n",
    "    K_size::Int64\n",
    "    z_size::Int64\n",
    "    eps_size::Int64\n",
    "    s_size::Int64\n",
    "    ug::Float64\n",
    "    ub::Float64\n",
    "    TransMat::TransitionMatrix # bunch of transition matrix\n",
    "    mu::Float64\n",
    "end\n",
    "\n",
    "\"\"\" \n",
    "Create transition matrices for aggregate shock,\n",
    "idiosyncratic shock, and shock state\n",
    "\n",
    "##### Arguments\n",
    "- `ug` : unemployment rate in good state\n",
    "- `ub` : unemployment rate in bad state\n",
    "- `zg_ave_dur` : average duration of good state\n",
    "- `zb_ave_dur` : average duration of bad state\n",
    "- `ug_ave_dur` : average duration of unemployment in good state\n",
    "- `ub_ave_dur` : average duration of unemployment in bad state\n",
    "- `puu_rel_gb2bb` : prob. of u to u cond. on g to b relative to that of b to b \n",
    "- `puu_rel_bg2gg` : prob. of u to u cond. on b to g relative to that of g to g\n",
    "\"\"\"\n",
    "function create_transition_matrix(ug::Float64,ub::Float64,\n",
    "        zg_ave_dur::Float64,zb_ave_dur::Float64,\n",
    "        ug_ave_dur::Float64,ub_ave_dur::Float64,\n",
    "        puu_rel_gb2bb::Float64,puu_rel_bg2gg::Float64)\n",
    "    \n",
    "    # probability of remaining in good state\n",
    "    pgg = 1-1/zg_ave_dur\n",
    "    # probability of remaining in bad state\n",
    "    pbb = 1-1/zb_ave_dur\n",
    "    # probability of changing from g to b\n",
    "    pgb = 1-pgg\n",
    "    # probability of changing from b to g\n",
    "    pbg = 1-pbb  \n",
    "    \n",
    "    # prob. of 0 to 0 cond. on g to g\n",
    "    p00_gg = 1-1/ug_ave_dur\n",
    "    # prob. of 0 to 0 cond. on b to b\n",
    "    p00_bb = 1-1/ub_ave_dur\n",
    "    # prob. of 0 to 1 cond. on g to g\n",
    "    p01_gg = 1-p00_gg\n",
    "    # prob. of 0 to 1 cond. on b to b\n",
    "    p01_bb = 1-p00_bb\n",
    "    \n",
    "    # prob. of 0 to 0 cond. on g to b\n",
    "    p00_gb=puu_rel_gb2bb*p00_bb\n",
    "    # prob. of 0 to 0 cond. on b to g\n",
    "    p00_bg=puu_rel_bg2gg*p00_gg\n",
    "    # prob. of 0 to 1 cond. on g to b\n",
    "    p01_gb=1-p00_gb\n",
    "    # prob. of 0 to 1 cond. on b to g\n",
    "    p01_bg=1-p00_bg\n",
    "    \n",
    "    # prob. of 1 to 0 cond. on  g to g\n",
    "    p10_gg=(ug - ug*p00_gg)/(1-ug)\n",
    "    # prob. of 1 to 0 cond. on b to b\n",
    "    p10_bb=(ub - ub*p00_bb)/(1-ub)\n",
    "    # prob. of 1 to 0 cond. on g to b\n",
    "    p10_gb=(ub - ug*p00_gb)/(1-ug)\n",
    "    # prob. of 1 to 0 cond on b to g\n",
    "    p10_bg=(ug - ub*p00_bg)/(1-ub)\n",
    "    # prob. of 1 to 1 cond. on  g to g\n",
    "    p11_gg= 1-p10_gg\n",
    "    # prob. of 1 to 1 cond. on b to b\n",
    "    p11_bb= 1-p10_bb\n",
    "    # prob. of 1 to 1 cond. on g to b\n",
    "    p11_gb= 1-p10_gb\n",
    "    # prob. of 1 to 1 cond on b to g\n",
    "    p11_bg= 1-p10_bg\n",
    "    \n",
    "    #   (g1)         (b1)        (g0)       (b0)\n",
    "    P=[pgg*p11_gg pgb*p11_gb pgg*p10_gg pgb*p10_gb;\n",
    "        pbg*p11_bg pbb*p11_bb pbg*p10_bg pbb*p10_bb;\n",
    "        pgg*p01_gg pgb*p01_gb pgg*p00_gg pgb*p00_gb;\n",
    "        pbg*p01_bg pbb*p01_bb pbg*p00_bg pbb*p00_bb\n",
    "        ]\n",
    "    Pz=[pgg pgb;\n",
    "        pbg pbb]\n",
    "    Peps_gg=[p11_gg p10_gg\n",
    "              p01_gg p00_gg]\n",
    "    Peps_bb=[p11_bb p10_bb\n",
    "              p01_bb p00_bb]\n",
    "    Peps_gb=[p11_gb p10_gb\n",
    "              p01_gb p00_gb]\n",
    "    Peps_bg=[p11_bg p10_bg\n",
    "              p01_bg p00_bg]\n",
    "    TransMat=TransitionMatrix(P,Pz,Peps_gg,Peps_bb,Peps_gb,Peps_bg)\n",
    "    return TransMat\n",
    "end\n",
    "\n",
    "\"\"\"\n",
    "Creates KSParameter instance\n",
    "\"\"\"\n",
    "function KSParameter(;\n",
    "            beta::Float64=0.99,\n",
    "            alpha::Float64=0.36,\n",
    "            delta::Float64=0.025,\n",
    "            theta::Float64=1.0,\n",
    "            k_min::Float64=1e-16,\n",
    "            k_max::Float64=1000.0,\n",
    "            k_size::Int64=100,\n",
    "            K_min::Float64=30.0,\n",
    "            K_max::Float64=50.0,\n",
    "            K_size::Int64=4,\n",
    "            z_min::Float64=0.99,\n",
    "            z_max::Float64=1.01,\n",
    "            z_size::Int64=2,\n",
    "            eps_min::Float64=0.0,\n",
    "            eps_max::Float64=1.0,\n",
    "            eps_size::Int64=2,\n",
    "            ug::Float64=0.04,\n",
    "            ub::Float64=0.1,\n",
    "            zg_ave_dur::Float64=8.0,\n",
    "            zb_ave_dur::Float64=8.0,\n",
    "            ug_ave_dur::Float64=1.5,\n",
    "            ub_ave_dur::Float64=2.5,\n",
    "            puu_rel_gb2bb::Float64=1.25,\n",
    "            puu_rel_bg2gg::Float64=0.75,\n",
    "            mu::Float64=0.0\n",
    "            )\n",
    "    if theta == 1.0\n",
    "        u = (c) -> log(c)\n",
    "    else\n",
    "        u = (c) -> (c^(1.0-theta)-1.0)/(1.0-theta)\n",
    "    end\n",
    "    l_bar=1/(1-ub)\n",
    "    k_grid=place_polynominal_grid(k_min,k_max,k_size,degree=7.0)   # individual capital grid\n",
    "    K_grid=collect(linspace(K_min,K_max,K_size))   # aggregate capital grid\n",
    "    z_grid=collect(linspace(z_max,z_min,z_size))   # aggregate technology shock\n",
    "    eps_grid=collect(linspace(eps_max,eps_min,eps_size))  # idiosyncratic employment shock\n",
    "    s_grid=gridmake(z_grid,eps_grid)               # shock grid\n",
    "    # collection of transition matrices\n",
    "    TransMat=create_transition_matrix(ug,ub,\n",
    "        zg_ave_dur,zb_ave_dur,\n",
    "        ug_ave_dur,ub_ave_dur,\n",
    "        puu_rel_gb2bb,puu_rel_bg2gg)\n",
    "\n",
    "    ksp=KSParameter(u,beta,alpha,delta,theta,l_bar,k_grid,K_grid,z_grid,eps_grid,s_grid,\n",
    "    k_size,K_size,z_size,eps_size,z_size*eps_size,ug,ub,TransMat,mu)\n",
    "\n",
    "    return ksp\n",
    "end\n",
    "\n",
    "function place_polynominal_grid(k_min::Float64,k_max::Float64,k_size::Int64;degree::Float64=0.7)\n",
    "    grid=Array{Float64}(k_size)\n",
    "    for (i, x) in enumerate(linspace(0,0.5,k_size))\n",
    "        grid[i]=(x/0.5)^degree*(k_max-k_min)+k_min\n",
    "    end\n",
    "    return grid\n",
    "end\n",
    "\"\"\"\n",
    "Compute interest rate given aggregate capital, labor, and productivity\n",
    "\n",
    "##### Arguments\n",
    "- `alpha` : capital share\n",
    "- `z` : aggregate shock\n",
    "- `K` : aggregate capital\n",
    "- `L` : aggregate labor\n",
    "\"\"\"\n",
    "r(alpha::Float64,z::Float64,K::Float64,L::Float64)=alpha*z*K^(alpha-1)*L^(1-alpha)\n",
    "\n",
    "\"\"\"\n",
    "Compute wage given aggregate capital, labor, and productivity\n",
    "\n",
    "##### Arguments\n",
    "- `alpha` : capital share\n",
    "- `z` : aggregate shock\n",
    "- `K` : aggregate capital\n",
    "- `L` : aggregate labor\n",
    "\"\"\"\n",
    "w(alpha::Float64,z::Float64,K::Float64,L::Float64)=(1-alpha)*z*K^(alpha)*L^(-alpha)    \n",
    "\n",
    "\"\"\"\n",
    "Collection of KS solution\n",
    "\"\"\"\n",
    "type KSSolution\n",
    "    k_opt::Array{Float64,3}\n",
    "    value::Array{Float64,3}\n",
    "    B::Vector{Float64}\n",
    "    R2::Vector{Float64}\n",
    "end\n",
    "\n",
    "\"\"\"\n",
    "Create KSSolution instance\n",
    "\"\"\"\n",
    "function KSSolution(\n",
    "        ksp::KSParameter;\n",
    "        load_value::Bool=false,\n",
    "        load_B::Bool=false,\n",
    "        filename::String=\"result.jld\")\n",
    "    if load_value || load_B\n",
    "        result=load(filename)\n",
    "        kss_temp=result[\"kss\"]\n",
    "    end\n",
    "    if load_value\n",
    "        k_opt=kss_temp.k_opt\n",
    "        value=kss_temp.value\n",
    "    else\n",
    "        k_opt=ksp.beta*repeat(ksp.k_grid,outer=[1,ksp.K_size,ksp.s_size])\n",
    "        k_opt=0.9*repeat(ksp.k_grid,outer=[1,ksp.K_size,ksp.s_size])\n",
    "        value=ksp.u.(0.1/0.9*k_opt)/(1-ksp.beta)\n",
    "    end\n",
    "    if load_B\n",
    "        B=kss_temp.B\n",
    "    else\n",
    "        B=[0.0, 1.0, 0.0, 1.0]\n",
    "    end\n",
    "    kss=KSSolution(k_opt,value,B,[0.0,0.0])\n",
    "    return kss\n",
    "end\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Shock Generation\n",
    "The functions in this cell are used to draw aggregate and idiosyncratic shocks\n",
    "- Methods\n",
    "    - `get_shock`: translate an index shock combination grid to shock value\n",
    "    - `generate_shocks`: draw aggregate and idiosyncratic shocks, which is the main function in this cell\n",
    "        - `draw_eps_shock` (local function inside `generate_shocks`): draw idiosyncratic shocks given aggregate shocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "generate_shocks"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "\"\"\" \n",
    "Translate shock index into shock value\n",
    "\n",
    "##### Arguments\n",
    "- `s_grid` : shock  grid\n",
    "- `s_i` : shock index\n",
    "\"\"\"\n",
    "get_shock(s_grid::Array{Float64,2},s_i::Integer) = \n",
    "    s_grid[s_i,1], s_grid[s_i,2] \n",
    "\n",
    "\"\"\"\n",
    "Generate aggregate and idiosyncratic shock\n",
    "\n",
    "##### Arguments\n",
    "- `ksp` : instance of KSParameter type\n",
    "- `z_shock_size` : size of aggregate shock\n",
    "- `population` : size idiosyncratic shock in one period\n",
    "\"\"\"\n",
    "function generate_shocks(ksp::KSParameter;\n",
    "        z_shock_size::Int64=11000,population::Int64=10000)\n",
    "    \n",
    "    \n",
    "    \"\"\" \n",
    "    Draw idiosyncratic shock given previous idiosyncratic shock and \n",
    "    transition matrix.\n",
    "    The transition matrix must be consistent with aggregate shock\n",
    "\n",
    "    ##### Arguments\n",
    "    - `eps_shock` : preallocated vector. current period shock is stored in it\n",
    "    - `eps_shock_before` : previous period idiosyncratic shock\n",
    "    - `Peps` : transition matrix of the current period\n",
    "    \"\"\"\n",
    "    function draw_eps_shock(eps_shock_before::Vector{Float64},\n",
    "                              Peps::Array{Float64,2})\n",
    "    \n",
    "        eps_shocks = similar(eps_shock_before)\n",
    "        # loop over entire population\n",
    "        for i=1:length(eps_shocks)\n",
    "            rand_draw=rand()\n",
    "            eps_shocks[i]=ifelse(eps_shock_before[i]==1.0,\n",
    "                Float64(Peps[1,1]>rand_draw),  # if employed before\n",
    "                Float64(Peps[2,1]>rand_draw))  # if unemployed before\n",
    "        end\n",
    "        return eps_shocks\n",
    "    end\n",
    "    \n",
    "    # unpack parameters\n",
    "    Peps_gg=ksp.TransMat.Peps_gg\n",
    "    Peps_bg=ksp.TransMat.Peps_bg\n",
    "    Peps_gb=ksp.TransMat.Peps_gb\n",
    "    Peps_bb=ksp.TransMat.Peps_bb\n",
    "    \n",
    "    # draw aggregate shock\n",
    "    z_shock=simulate(MarkovChain(ksp.TransMat.Pz,ksp.z_grid),z_shock_size)\n",
    "    \n",
    "    ### Let's draw individual shock ###\n",
    "    eps_shock=Array{Float64}(z_shock_size,population) # preallocation\n",
    "    \n",
    "    # first period\n",
    "    rand_draw=rand(population)\n",
    "    if z_shock[1]==ksp.z_grid[1] # if good\n",
    "        eps_shock[1,:].=Int64.(rand_draw.>ksp.ug) # if draw is higher, become employed\n",
    "    elseif z_shock[1]==ksp.z_grid[2] # if bad\n",
    "        eps_shock[1,:].=Int64.(rand_draw.>ksp.ub) # if draw is higher, become employed\n",
    "    else\n",
    "        error(\"the value of z_shock[1] (=$(z_shock[1])) is strange\")\n",
    "    end\n",
    "    \n",
    "    # from second period ...\n",
    "    for t=2:z_shock_size\n",
    "        if z_shock[t]==ksp.z_grid[1] && z_shock[t-1]==ksp.z_grid[1]  # if g to g\n",
    "            eps_shock[t,:]=draw_eps_shock(eps_shock[t-1,:],Peps_gg)\n",
    "        elseif z_shock[t]==ksp.z_grid[1] && z_shock[t-1]==ksp.z_grid[2]  # if b to g\n",
    "            eps_shock[t,:]=draw_eps_shock(eps_shock[t-1,:],Peps_bg)\n",
    "        elseif z_shock[t]==ksp.z_grid[2] && z_shock[t-1]==ksp.z_grid[1]  # if g to b\n",
    "            eps_shock[t,:]=draw_eps_shock(eps_shock[t-1,:],Peps_gb)\n",
    "        elseif z_shock[t]==ksp.z_grid[2] && z_shock[t-1]==ksp.z_grid[2]  # if b to b\n",
    "            eps_shock[t,:]=draw_eps_shock(eps_shock[t-1,:],Peps_bb)\n",
    "        else\n",
    "            error(\"the value of z_shock[t] (=$(z_shock[t])) is strange\")\n",
    "        end\n",
    "    end\n",
    "    \n",
    "    # adjustment\n",
    "    for t=1:z_shock_size\n",
    "        n_e=Int64(sum(eps_shock[t,:]))\n",
    "        er_ideal = ifelse(z_shock[t] == ksp.z_grid[1],\n",
    "                    1.0-ksp.ug, 1.0-ksp.ub)\n",
    "        gap = Int64(round(er_ideal*population)) - n_e\n",
    "        if gap > 0\n",
    "            for j=1:gap\n",
    "                become_employed_i = \n",
    "                    sample(find(x-> isapprox(x,ksp.eps_grid[2]), eps_shock[t,:]))\n",
    "                eps_shock[t,become_employed_i] = ksp.eps_grid[1]\n",
    "            end\n",
    "        elseif gap < 0\n",
    "            for j=1:(-gap)\n",
    "                become_unemployed_i = \n",
    "                    sample(find(x-> isapprox(x,ksp.eps_grid[1]), eps_shock[t,:]))\n",
    "                eps_shock[t,become_unemployed_i] = ksp.eps_grid[2]\n",
    "            end\n",
    "        end \n",
    "    end\n",
    "            \n",
    "    return z_shock, eps_shock    \n",
    "end\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Functions for Euler equation method\n",
    "\n",
    "Functions in this cell is used to solve individual problem by Euler equation method\n",
    "\n",
    "- Methods\n",
    "    - compute_Kp_L: compute approximated $K'$ and $L$, which depend on current aggregate shock\n",
    "    - compute_expectation_FOC: compute expectation term in Euler equation\n",
    "    - euler_method!: find optimal policy by Euler equation methods, namely, iteration of Euler equation\n",
    "    \n",
    "    $$ \\left(c\\right)^{-\\theta}=\\beta E\\left[\\left(c'\\right)^{-\\theta}(1-\\delta+r')\\right] $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "euler_method!"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Compute next period aggregate capital and labor\n",
    "\n",
    "##### Arguments\n",
    "- `K` : Current aggregate capital\n",
    "- `s_i` : current shock index\n",
    "- `B` : coefficient of ALM for capital\n",
    "\"\"\"\n",
    "function compute_Kp_L(K::AbstractFloat,s_i::Integer,B::Vector{Float64},ksp::KSParameter)\n",
    "    Kp,L=ifelse(ksp.s_grid[s_i,1]==ksp.z_grid[1],\n",
    "            (exp(B[1]+B[2]*log(K)),ksp.l_bar*(1-ksp.ug)),\n",
    "            (exp(B[3]+B[4]*log(K)),ksp.l_bar*(1-ksp.ub)))\n",
    "    Kp = ifelse(Kp<ksp.K_grid[1],ksp.K_grid[1],Kp)\n",
    "    Kp = ifelse(Kp>ksp.K_grid[end],ksp.K_grid[end],Kp)\n",
    "    return Kp, L\n",
    "end\n",
    "\n",
    "\"\"\"\n",
    "Compute expectation term in Euler equation\n",
    "\n",
    "##### Arguments\n",
    "- `kp` : next period individual capital holding\n",
    "- `Kp` : next period aggregate capital\n",
    "- `s_i` : current state of shock\n",
    "- `ksp` : KSParameter instance\n",
    "\"\"\"\n",
    "function compute_expectation_FOC(kp::Float64,\n",
    "                                  Kp::Float64,\n",
    "                                  s_i::Int64,\n",
    "                                  ksp::KSParameter)\n",
    "    alpha, theta, delta, l_bar, mu, P =\n",
    "        ksp.alpha, ksp.theta, ksp.delta, ksp.l_bar, ksp.mu, ksp.TransMat.P\n",
    "    expec = 0.0\n",
    "    for s_n_i = 1:ksp.s_size\n",
    "        zp, epsp = ksp.s_grid[s_n_i,1], ksp.s_grid[s_n_i,2]\n",
    "        Kpp, Lp = compute_Kp_L(Kp,s_n_i,kss.B,ksp)\n",
    "        rn=r(alpha,zp,Kp,Lp)\n",
    "        kpp=interpolate((ksp.k_grid,ksp.K_grid),\n",
    "                kss.k_opt[:,:,s_n_i],Gridded(Linear()))\n",
    "        cp = (rn+1-delta)*kp+\n",
    "                   w(alpha,zp,Kp,Lp)*(epsp*l_bar+mu*(1.0-epsp))-kpp[kp,Kp]\n",
    "        expec = expec + P[s_i,s_n_i]*(cp)^(-theta)*(1-delta+rn)\n",
    "    end \n",
    "    return expec\n",
    "end\n",
    "\n",
    "\"\"\"\n",
    "Solve individual problem by Euler equation method\n",
    "\n",
    "##### Arguments\n",
    "- `ksp` : KSParameter instance\n",
    "- `kss` : KSSolution instance\n",
    "- `n_iter` : maximum number of iteration of Euler equation method\n",
    "- `tol` : tolerance of policy function convergence\n",
    "- `update_k` : degree of update of policy function\n",
    "\"\"\"\n",
    "function euler_method!(ksp::KSParameter,\n",
    "                        kss::KSSolution;\n",
    "                        n_iter::Integer=30000,\n",
    "                        tol::AbstractFloat=1e-8,\n",
    "                        update_k::AbstractFloat=1e-8)\n",
    "    println(\"solving individual problem by Euler equation method\")\n",
    "    alpha, beta, delta, theta, l_bar, mu = \n",
    "        ksp.alpha, ksp.beta, ksp.delta, ksp.theta, ksp.l_bar, ksp.mu\n",
    "    k_grid, k_size = ksp.k_grid, ksp.k_size\n",
    "    K_grid, K_size = ksp.K_grid, ksp.K_size\n",
    "    s_grid, s_size = ksp.s_grid, ksp.s_size\n",
    "    k_min, k_max = minimum(k_grid), maximum(k_grid)\n",
    "    counter=0\n",
    "    k_opt_n=similar(kss.k_opt)\n",
    "    while true\n",
    "        counter += 1\n",
    "        dif_k=0.0\n",
    "        for s_i = 1:s_size\n",
    "            z, eps = s_grid[s_i,1], s_grid[s_i,2]\n",
    "            for K_i = 1:K_size\n",
    "                K = K_grid[K_i]\n",
    "                Kp, L = compute_Kp_L(K,s_i,kss.B,ksp)\n",
    "                for k_i = 1:k_size\n",
    "                    k=k_grid[k_i]\n",
    "                    wealth = (r(alpha,z,K,L)+1-delta)*k+\n",
    "                                w(alpha,z,K,L)*(eps*l_bar+mu*(1.0-eps))\n",
    "                    expec=compute_expectation_FOC(kss.k_opt[k_i,K_i,s_i],Kp,s_i,ksp)\n",
    "                    cn=(beta*expec)^(-1.0/theta)\n",
    "                    k_opt_n[k_i,K_i,s_i] = wealth-cn\n",
    "                    k_opt_n[k_i,K_i,s_i] = ifelse(k_opt_n[k_i,K_i,s_i]>k_max,k_max,k_opt_n[k_i,K_i,s_i])\n",
    "                    k_opt_n[k_i,K_i,s_i] = ifelse(k_opt_n[k_i,K_i,s_i]<k_min,k_min,k_opt_n[k_i,K_i,s_i])\n",
    "                    \n",
    "                end\n",
    "            end\n",
    "        end\n",
    "        dif_k=maxabs(k_opt_n-kss.k_opt)\n",
    "        kss.k_opt.=update_k.*k_opt_n.+(1-update_k).*kss.k_opt\n",
    "        if dif_k<tol\n",
    "            println(\"Euler method converged with $counter iterations\")\n",
    "            break\n",
    "        end\n",
    "        if counter >=n_iter\n",
    "            println(\"Euler method failed to converge with $counter iterations (dif = $dif_k)\")\n",
    "            break\n",
    "        end\n",
    "    end\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulate path of aggregate capital\n",
    "- Mathods\n",
    "    - simulate_aggregate_path!: simulating aggregate path of capital using shocks drawn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "code_folding": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "simulate_aggregate_path!"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Simulate aggregate capital's path using policy function \n",
    "and generated aggregate and idiosyncratic shock\n",
    "\n",
    "##### Arguments\n",
    "- `ksp` : KSParameter instance\n",
    "- `z_shocks` : aggregate shocks\n",
    "- `eps_shocks` : idiosyncratic shocks\n",
    "- `k_population` : initial capital holding of all agents\n",
    "\"\"\"\n",
    "function simulate_aggregate_path!(ksp::KSParameter,kss::KSSolution,\n",
    "        z_shocks::Vector{Float64},eps_shocks::Array{Float64,2},\n",
    "        k_population::Vector{Float64},K_ts::Vector{Float64})\n",
    "    \n",
    "    println(\"simulating aggregate path ... please wait ... \")\n",
    "    \n",
    "    T=length(z_shocks)   # simulated duration\n",
    "    N=size(eps_shocks,2) # number of agents\n",
    "    \n",
    "    \n",
    "    # loop over T periods\n",
    "    for (t,z) = enumerate(z_shocks)\n",
    "        K_ts[t]=mean(k_population) # current aggrgate capital\n",
    "        \n",
    "        # s_i_base takes 1 when good and 2 when bad \n",
    "        s_i_base=ifelse(z==ksp.z_grid[1],1,2)        \n",
    "        \n",
    "        # loop over individuals\n",
    "        for (i,k) in enumerate(k_population)\n",
    "            eps = eps_shocks[t,i]   # idiosyncratic shock\n",
    "            s_i=s_i_base+2*(1-Int64(eps))  # transform (z,eps) to s_i\n",
    "            # obtain next capital holding by interpolation\n",
    "            \n",
    "            itp_pol=interpolate((ksp.k_grid,ksp.K_grid),kss.k_opt[:,:,s_i],Gridded(Linear()))\n",
    "            k_population[i]=itp_pol[k,K_ts[t]]\n",
    "        end\n",
    "    end\n",
    "    \n",
    "    return nothing\n",
    "end\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Obtaining aggregate law of motion coefficient\n",
    "\n",
    "The functions in this cell are used to obtain the coefficient of approximate aggregate capital law of motion (ALM)\n",
    "\n",
    "- Methods\n",
    "    - regress_ALM: regress aggregate capital law of motion and obtain approximate ALM\n",
    "    - find_ALM_coef!: main iteration. update ALM coefficient until convergence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "find_ALM_coef! (generic function with 1 method)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Obtain new aggregate law of motion coefficients \n",
    "using the aggregate capital flaw\n",
    "\n",
    "##### Arguments\n",
    "- `ksp` : KSParameter instance\n",
    "- `z_shock` : aggregate shocks\n",
    "- `K_ts` : aggregate capital flaw\n",
    "- `n_discard` : number of discarded samples\n",
    "\"\"\"\n",
    "function regress_ALM!(ksp::KSParameter,kss::KSSolution,\n",
    "                        z_shock::Vector{Float64},K_ts::Vector{Float64};\n",
    "                        n_discard::Int64=100)\n",
    "    z_grid=ksp.z_grid\n",
    "    n_g=count(i->(i==z_grid[1]),z_shocks[n_discard+1:end-1])\n",
    "    n_b=count(i->(i==z_grid[2]),z_shocks[n_discard+1:end-1])\n",
    "    B_n=Vector{Float64}(4)\n",
    "    x_g=Vector{Float64}(n_g)\n",
    "    y_g=Vector{Float64}(n_g)\n",
    "    x_b=Vector{Float64}(n_b)\n",
    "    y_b=Vector{Float64}(n_b)\n",
    "    i_g=0\n",
    "    i_b=0\n",
    "    for t = n_discard+1:length(z_shocks)-1\n",
    "        if z_shocks[t]==z_grid[1]\n",
    "            i_g=i_g+1\n",
    "            x_g[i_g]=log(K_ts[t])\n",
    "            y_g[i_g]=log(K_ts[t+1])\n",
    "        else\n",
    "            i_b=i_b+1\n",
    "            x_b[i_b]=log(K_ts[t])\n",
    "            y_b[i_b]=log(K_ts[t+1])\n",
    "        end\n",
    "    end\n",
    "    resg=lm(hcat(ones(n_g,1),x_g),y_g)\n",
    "    resb=lm(hcat(ones(n_b,1),x_b),y_b)\n",
    "    kss.R2=[r2(resg),r2(resb)]\n",
    "    B_n[1],B_n[2]=coef(resg)\n",
    "    B_n[3],B_n[4]=coef(resb)\n",
    "    dif_B=maximum(abs(B_n-kss.B))\n",
    "    println(\"difference of ALM coefficient is $dif_B and B = $B_n\")\n",
    "    return B_n, dif_B\n",
    "end\n",
    "\n",
    "function find_ALM_coef!(\n",
    "                       ksp::KSParameter,\n",
    "                       kss::KSSolution,\n",
    "                       z_shocks::Vector{Float64},\n",
    "                       eps_shocks::Array{Float64,2};\n",
    "                       tol_ump::AbstractFloat=1e-8,\n",
    "                       max_iter_ump::Integer=100,\n",
    "                       Howard_on::Bool=true,\n",
    "                       Howard_n_iter::Integer=20,\n",
    "                       tol_B::AbstractFloat=1e-8,\n",
    "                       max_iter_B::Integer=20,\n",
    "                       update_B::AbstractFloat=0.3,\n",
    "                       T_discard::Integer=100,\n",
    "                       print_skip_VFI::Integer=10,\n",
    "                       method::Symbol=:Euler,\n",
    "                       update_k::AbstractFloat=0.3)\n",
    "\n",
    "    K_ts=similar(z_shocks)\n",
    "    # populate initial capital holdings\n",
    "    k_population=37.9893*ones(size(eps_shocks,2))\n",
    "    counter_B=0\n",
    "    while true\n",
    "        counter_B=counter_B+1\n",
    "        println(\" --- Iteration over ALM coefficient: $counter_B ---\")\n",
    "\n",
    "        # solve individual problem\n",
    "        if method == :VFI\n",
    "            solve_bellman!(ksp,kss,\n",
    "                           tol=tol_ump,\n",
    "                           max_iter=max_iter_ump,\n",
    "                           Howard=Howard_on,\n",
    "                           Howard_n_iter=Howard_n_iter,\n",
    "                           print_skip=print_skip_VFI)\n",
    "        elseif method == :Euler\n",
    "            euler_method!(ksp,kss,\n",
    "                        n_iter=max_iter_ump,\n",
    "                        tol=tol_ump,\n",
    "                        update_k=update_k)\n",
    "        end\n",
    "        \n",
    "\n",
    "        # compute aggregate path of capital\n",
    "        simulate_aggregate_path!(ksp,kss,z_shocks,eps_shocks,k_population,K_ts)\n",
    "        \n",
    "        # obtain new ALM coefficient by regression\n",
    "        B_n,dif_B = regress_ALM!(ksp,kss,z_shocks,K_ts,n_discard=T_discard)\n",
    "\n",
    "        # check convergence\n",
    "        if dif_B < tol_B\n",
    "            println(\"-----------------------------------------------------\")\n",
    "            println(\"ALM coefficient successfully converged : dif = $dif_B\")\n",
    "            println(\"-----------------------------------------------------\")\n",
    "            kss.B .= update_B .* B_n .+ (1-update_B) .* kss.B\n",
    "            break\n",
    "        elseif counter_B == max_iter_B\n",
    "            println(\"----------------------------------------------------------------\")\n",
    "            println(\"Iteration over ALM coefficient reached its maximum ($max_iter_B)\")\n",
    "            println(\"----------------------------------------------------------------\")\n",
    "            kss.B .= update_B .* B_n .+ (1-update_B) .* kss.B\n",
    "            break\n",
    "        end\n",
    "        \n",
    "        # Update B\n",
    "        kss.B .= update_B .* B_n .+ (1-update_B) .* kss.B\n",
    "    end\n",
    "    return K_ts\n",
    "end\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting\n",
    "The function is used to plot the path of true path of aggregate capital and approximated one\n",
    "- Methods\n",
    "    - plot_ALM: plot the path of true path of aggregate capital and approximated one"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "plot_ALM"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Plot true and approximated ALM of capital \n",
    "\n",
    "##### Arguments\n",
    "- `ksp.z_grid` : aggregate shock grid\n",
    "- `z_shocks` : aggregate shock\n",
    "- `kss.B` : ALM coefficient\n",
    "- `K_ts` : actual path of capital\n",
    "\"\"\"\n",
    "function plot_ALM(z_grid::Vector{Float64},\n",
    "                  z_shocks::Vector{Float64},\n",
    "                  B::Vector{Float64},\n",
    "                  K_ts::Vector{Float64};\n",
    "                  T_discard=1000)\n",
    "\n",
    "    K_ts_approx = similar(K_ts) # preallocation\n",
    "\n",
    "    # compute approximate ALM for capital\n",
    "    K_ts_approx[T_discard]=K_ts[T_discard]\n",
    "\n",
    "    for t=T_discard:length(z_shocks)-1\n",
    "        if z_shocks[t] == z_grid[1]\n",
    "            K_ts_approx[t+1]=exp(B[1]+B[2]*log(K_ts_approx[t]))\n",
    "        elseif z_shocks[t] == z_grid[2]\n",
    "            K_ts_approx[t+1]=exp(B[3]+B[4]*log(K_ts_approx[t]))\n",
    "        end\n",
    "    end\n",
    "\n",
    "    plot(T_discard+1:length(K_ts),K_ts[T_discard+1:end],lab=\"true\",color=:red,line=:solid)\n",
    "    plot!(T_discard+1:length(K_ts),K_ts_approx[T_discard+1:end],lab=\"approximation\",color=:blue,line=:dash)\n",
    "    title!(\"aggregate law of motion for capital\")\n",
    "    \n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementation by Euler method"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, construct model instance `ksp` and initial guess of the solution inside `kss` \n",
    "\n",
    "(Grid size inconsistency is also checked, which may return error when exiting result is loaded by `load_value=true`)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# instance of KSParameter\n",
    "ksp=KSParameter(k_size=100,\n",
    "                k_min=1e-16)\n",
    "# instance of KSSolution\n",
    "kss=KSSolution(ksp,load_value=false,load_B=false)\n",
    "if size(kss.k_opt,1) != length(ksp.k_grid)\n",
    "    error(\"loaded data is inconsistent with k_size\")\n",
    "end\n",
    "if size(kss.k_opt,2) != length(ksp.K_grid)\n",
    "    error(\"loaded data is inconsistent with K_size\")\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's draw the shock for stochastic simulation of aggregate law of motion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# generate shocks\n",
    "srand(123)\n",
    "z_shocks,eps_shocks =generate_shocks(ksp;\n",
    "        z_shock_size=11000,population=5000);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, the following cell solves the model with Euler equation method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " --- Iteration over ALM coefficient: 1 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 1868 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.4556643772779668 and B = [0.455664,0.877296,0.438162,0.880418]\n",
      " --- Iteration over ALM coefficient: 2 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 2005 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.01194706494540887 and B = [0.137682,0.963462,0.119502,0.96685]\n",
      " --- Iteration over ALM coefficient: 3 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 1479 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.012429438071340365 and B = [0.149423,0.960332,0.135204,0.962694]\n",
      " --- Iteration over ALM coefficient: 4 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 1516 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.007084614314802812 and B = [0.147807,0.960707,0.134031,0.962974]\n",
      " --- Iteration over ALM coefficient: 5 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 1159 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.004062551435912554 and B = [0.146911,0.960937,0.133124,0.963222]\n",
      " --- Iteration over ALM coefficient: 6 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 1044 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.002383876077763747 and B = [0.146451,0.961055,0.132628,0.963361]\n",
      " --- Iteration over ALM coefficient: 7 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 1065 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.0014303729909590501 and B = [0.146213,0.961116,0.132363,0.963436]\n",
      " --- Iteration over ALM coefficient: 8 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 1050 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.0008768443163971185 and B = [0.146088,0.961148,0.132222,0.963476]\n",
      " --- Iteration over ALM coefficient: 9 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 1017 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.0005485109058530613 and B = [0.146023,0.961164,0.132146,0.963498]\n",
      " --- Iteration over ALM coefficient: 10 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 974 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.00034954334404080356 and B = [0.145988,0.961172,0.132105,0.96351]\n",
      " --- Iteration over ALM coefficient: 11 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 926 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.0002264320715512913 and B = [0.14597,0.961177,0.132083,0.963517]\n",
      " --- Iteration over ALM coefficient: 12 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 874 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.00014875045461057446 and B = [0.14596,0.961179,0.132071,0.96352]\n",
      " --- Iteration over ALM coefficient: 13 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 820 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 9.885788332636425e-5 and B = [0.145955,0.96118,0.132065,0.963522]\n",
      " --- Iteration over ALM coefficient: 14 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 765 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 6.631382514887818e-5 and B = [0.145952,0.96118,0.132062,0.963524]\n",
      " --- Iteration over ALM coefficient: 15 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 708 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 4.48072540583655e-5 and B = [0.145951,0.961181,0.13206,0.963524]\n",
      " --- Iteration over ALM coefficient: 16 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 651 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 3.0443087124187862e-5 and B = [0.14595,0.961181,0.132059,0.963525]\n",
      " --- Iteration over ALM coefficient: 17 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 594 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 2.076821253785277e-5 and B = [0.145949,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 18 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 537 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.4209519261981773e-5 and B = [0.145949,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 19 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 480 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 9.741695670306694e-6 and B = [0.145949,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 20 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 424 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 6.687466508698003e-6 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 21 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 370 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 4.594411339209348e-6 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 22 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 317 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 3.1576579837266916e-6 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 23 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 266 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 2.1703967988118134e-6 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 24 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 219 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.4916336017467557e-6 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 25 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 176 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.024884198480569e-6 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 26 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 137 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 7.039676926667848e-7 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 27 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 103 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 4.834097304673435e-7 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 28 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 74 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 3.319196261453161e-7 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 29 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 50 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 2.2794120549396446e-7 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 30 ---\n",
      "solving individual problem by Euler equation method\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Euler method converged with 37 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.5634870192959838e-7 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 31 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 27 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.0716623247142287e-7 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 32 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 20 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 7.337721727451729e-8 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 33 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 18 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 5.00449526541491e-8 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 34 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 15 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 3.408943094473926e-8 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 35 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 13 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 2.3183727299036505e-8 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 36 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 10 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.5783928553059212e-8 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 37 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 8 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.0743600203921844e-8 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      " --- Iteration over ALM coefficient: 38 ---\n",
      "solving individual problem by Euler equation method\n",
      "Euler method converged with 7 iterations\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 7.295628601244886e-9 and B = [0.145948,0.961181,0.132058,0.963525]\n",
      "-----------------------------------------------------\n",
      "ALM coefficient successfully converged : dif = 7.295628601244886e-9\n",
      "-----------------------------------------------------\n",
      "16333.330134 seconds (20.04 G allocations: 9.153 TB, 27.86% gc time)\n"
     ]
    }
   ],
   "source": [
    "# find ALM coefficient\n",
    "@time K_ts = find_ALM_coef!(ksp,kss,z_shocks,eps_shocks,\n",
    "               tol_ump=1e-8,max_iter_ump=10000,\n",
    "               Howard_on=true,Howard_n_iter=20,\n",
    "               tol_B=1e-8, max_iter_B=50,update_B=0.3,\n",
    "               T_discard=1000,print_skip_VFI=10,\n",
    "               method=:Euler, update_k=0.7);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's compare the true aggreate law of motion for capital and approximated one with figure and regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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8km7bS+88ILLK+ps+3/sscdYvny5y/u5yq+//kpCQgKjR492WAG4ZMkS68o3W3r27MnHH39MfHw8Wq3WbjVcz549WbNmDdnZ2ezbt48ePXqg1WpLlcNynM7OJ8DVq1ft6lU2FSFvVT0nZZXL2fNYEhaH+uTk5FLrluU+huKPwVJeHgd0g8HAf/7zHyIjIzl48KDdR5oQgo8++qjMbctUX+QwDTIuc+7cOcLCwhyUq9zcXBISEhzqt2nThpycHOuUkC07d+50Wh9wuiR97969dlYFVwgKCqJ58+acOHHCpamS4OBgoqOjOXv2rFMly5nM586dA7CuFLQghHB6HCqVCnBuWWjevDnBwcHs37/fYerVExQnK8D27dud7tOtWzfUajWbN2+2rga1WBJ79epFamoqc+bMQa/XF7sytCiWablt27YhhLDbJoRg27ZtdvUqG0vIhH379jkNS2BZpm8rb0nX2RnBwcE0atSIs2fPOlUynPVREVim952FWEhKSuLcuXM0atTIznpVFpo2bUpwcDD79u2zC8fgjLLcxwCXLl3i4sWLxe7jzJXBlpKuaVpaGhkZGdxzzz0OFvD9+/e7FDJD5vZDVrBkXKZBgwakp6fbTV8ZjUYmTZrk1FI1YsQIAN555x1MJpO1/OTJk06/MgcNGkRgYCDz5s2zDqIgfR1Onjy5TDK//PLL5Obm8txzzzmdWrtw4YJdvJ8RI0ag0+mYMmWKXb0tW7awYcMGh/0tPh07duywK//vf//rEB8JICwsDJBeTkVRq9WMGzeOixcvMmnSJKdK1tGjR8scU6c4Wbdu3crcuXOd7mOJL7Rz5062b99unSKGQn8ri3+bK/5XIPnC9OzZk2PHjjnEIvvmm284ceIEvXr18oj/lSfQarUMGzaMtLQ0PvzwQ7tt69evZ8OGDTRp0oSuXbtay0u6zsUxcuRI9Ho9b775pp3iefjwYRYuXEhISEiJoQS8waBBgwgJCWHBggV2z70Qgtdffx2DweCR1DFqtZrnn3+ejIwMJkyY4KDEZGRkkJ2dDZTtPgZprHrrrbcczu2iRYuIiIigf//+JcpYo0YNFAqF02taq1Yt/Pz8SEhIsFPC09PTGT9+fIntyty+yFOEMi4zfvx4Nm7cyH333cfgwYPx9fVly5YtJCcn06NHD4ev3FGjRrFo0SLWrl1L27Zt6devHzdv3mTJkiX06dOH1atXo1QW6vihoaF8+umnjB07lvbt2zN06FBrHCwfHx+ioqLs6rvC888/z+7du/nuu+/4888/6d27N1FRUVy7do2TJ0+yZ88eFi9ebI1l8/rrr/Pzzz8ze/Zsjh49Srdu3bh8+TI//fQTAwcOdJD5hRdeYMGCBTz22GMMHjyYmjVrsnv3bhISEhgwYABr1661k6dZs2ZERUWxZMkSfHx8qFu3LgqFgvHjxxMSEsLUqVNJSEhg1qxZrF27lvvvv59atWqRnJzMkSNHOHToELt27SrWT6wkBg4cSHR0NB999BFHjx6lVatWnDp1ijVr1vDoo48WOy3Zs2dPdu/ebf1t4a677iImJoYzZ84QGBhoFwOtNL7++mvuu+8+nnvuOVavXk2LFi04duwYq1atIiIigq+//trt4/Mm06dPZ+vWrbz//vvs3LmTzp07k5iYyLJly/D392fBggV290WvXr345JNPGDt2LI899hgBAQE0aNDAwUHdltdee421a9eyaNEiTpw4wQMPPMD169dZunQpBoOBuXPnlttS5C7BwcHMnTuXYcOG0blzZ4YMGUJERASbNm3ir7/+olOnTvzrX//ySF/vvfceu3fvZtGiRezevZt+/frh4+PD+fPnWb9+PTt27CAuLq7M93Hr1q3ZsWMHHTt2pHfv3tY4WAaDgW+++cbqL1Uclnt827ZtPPXUU8TExKBUKnnqqado0KABL774IjNmzKBNmzYMHDiQzMxM1q1bR4MGDeQI+XcqlbeAUaY6snz5ctGuXTvh7+8vwsPDxeDBg8W5c+eKXeadnZ0tJk6cKKKiooSPj49o0aKF+Oabb8Ty5csFIGbOnOnQx7Jly0Tbtm2Fj4+PqFWrlhgzZoy4ceOGCAwMFG3atLGrW9pyeAtLly4VvXv3FjVq1BAajUbcddddokePHmLGjBkOy8mvX78uRo8eLcLDw4Wvr69o3769WLFihfjkk08EIH755Re7+vHx8aJr164iKChIhIaGiv79+4u//vqr2GXYu3fvFt27dxdBQUHW+Dy28hsMBjFnzhzRtWtXERwcLHx8fET9+vVF3759xddffy2ys7NLPFaLTBQTB+uxxx4TERERwt/fX3Ts2FEsWbKkxLAOGzdutC5zv3Xrlt02S7gN21AOrpKYmChGjRolIiMjhVqtFpGRkWLUqFFOl9KXJ0yDs2XwJd033bt3F86GxtTUVPHyyy+LBg0aCI1GI8LDw8Xjjz8ujhw54rT/jz76SMTExAiNRiMA0b17d+s2Z2EahJCel8mTJ4vY2Fhr7Kt+/fqJ7du3u3V87p6v0p6jbdu2iX79+onQ0FCh1WpFbGysmDx5stN7seixukN+fr745JNPRFxcnPDz8xOBgYGiRYsWYuLEiSI9Pd1az9372CJTUlKSGDJkiAgLCxO+vr7innvuERs3bnSQo7hze+rUKdG/f38RGhoqFAqFXR2dTiemTZsmYmJirM/sxIkTRVZWltPrLYdpuP1RCFHECUJGpgJ45513mDZtGr/99hv9+vUrtf7Zs2eJiYlh8ODBLF26tAIkdOTJJ5/khx9+4Pjx4zRv3rxSZJCRkXEfhUJB9+7dXUrXIyPjKWQfLBmvcuXKFYey48ePM2vWLEJDQx0co9PT0x2WM+fl5fHPf/4ToEJ8UJzJvHXrVpYsWULTpk1l5UpGRkZGplRkHywZrzJu3DgSExPp1KkTNWrU4Ny5c6xevRq9Xs+8efMc/B62bt3K6NGjefDBB6lfvz5paWls3ryZxMREevXqxZAhQ7wuc//+/fHz8yMuLo6AgACOHz/O+vXrUalUfPHFF17vX0ZGRkam+iNPEcp4lR9++IHZs2dz4sQJMjIyrI6iEydOdJo8+cyZM0yePJmdO3daVyY2adKEIUOGMGnSJIekst7gs88+44cffuDcuXNkZWURGhpK165defPNN+ncubPX+5eRkfEs8hShTGUgK1gyMjIyMjIyMh5G9sGSkZGRkZGRkfEwsoIlIyMjIyMjI+NhZAVLRkZGRkZGRsbDeHUVoclkIiUlhaCgILeTf8rIyMjIyMjIVAeEEGRlZdllHPGqgpWSklJl8onJyMjIyMjIyHiTpKQk6tatC3hZwbLkzUpKSiI4ONibXVUqmZmZ1KtX77Y/ztsd+TreHsjX8fZBvpbVG6HTExqhYUjwGpZmjritr6PlXrXNF+pVBcsyLRgcHHzbnlRb7pTjvN2Rr+PtgXwdbx/uyGup18PBg+BGEvWqRkFqJhBMvxonWJp5Z1xHW3co2cldRkZGRkamqvHWW9CpE2RkVLYkZSbvZh4Avj6mSpakcpBT5cjI3CHodDouXryI0WisbFG8SnZ2NgCnT58mMDCwkqXxPiqVigYNGqDVaitbFBkPojt0gv3cw73VOBZ4brqUVzZPdfs/h86QFSwZmTuAy5cvM3z4cHJzcytbFK9jMpkIDw9n7Nix1tU8tzv+/v78+OOP3HXXXZUtioyHeOPESGbyBLeyMgkJrWxpykZeej4AP6Y+CLxVucK4wZo1cPfd0KBB+dqRFSwZmdsck8nEe++9R2hoKLNmzaqQfI6VidFo5MSJEzRv3hyVSlXZ4nid/Px8Jk+ezNSpU5k9e/Ydo1Te7hzPNq/Ad9GClZEBf/+7YMkSBRERXhTMDXJv6QDw0RgqWRL3GDgQ3nzhJh98HVaudmQFS0bmNictLY2EhASmTZtGXFxcZYvjdYxGI3l5eTRr1uyOULAAXnrpJd5++21u3LhBRFV5u8qUiwKj9HpW4JqC9dvcZDZvvosfP0zk5U+jvSeYG7SKvEEA2bQLv8TqK5UtjesEk0HNH2bB1++Wqx35U0dG5jbn1q1bANbYLDK3H5Zrm56eXsmSyHiKWM0FAExG1xSsehlHAWiYe8xrMrlFXh6Kvz+KP7koNdXrQycPP/x0meVuR1awKgCDwWUrr4yMxzGZpBU8d4o1507Ecm0t11qm+jPEfw2d2INK4do1ranNAmDFkRhviuUyN5bHUyf9OKnUwqTWVLY4LmM0gh4txxUty92WrGBVABoNjBlT2VLIyFQd3n33XfLz8ytbDJmqiKwkAtBLtZU9dCEo0LWvc4Ve8ndauDPWm2K5zNkkH65RB4Ack18lS+M6+TnSKut1+t7lbktWsCqIhQsrW4JSyM2VzWwyFcbUqVOdKlgGQ/VyhpXxLMaDR/hKNR7Dzr2VLUohN25Iy8oqmPx8yMfH5XH5Spr7VqLurW7wy/ybbu/nChpTQeEfyupjPc+/JY1LPkp9uduSFSwvYTLB3LnS9CCAVlOFv8pMJggIgI8/rmxJZO4AXnjhBQC6detGXFwc/fv359lnn+X++++nVatWgBQN2eI7BhAeHk5iYiIAZ86cYcCAAXTs2JHWrVvz5ZdfVvgxyHiHFXPTeImv+H52TmWLYsX0+GAyBo5wKE9IgO7dpSklb/DGrTfoyD6XFaztp2u73ce2YzX5vwmn3d7PFQpyC09Mh6jLXunDG+TdkhRDH1X5FSx5FaGXWLUKxo4FtfkM++iygJBKlak4RH4B4/mCl1bsp9lrlS2NTIVw/jzYKDAeIzQUGjUqscrs2bOZM2cO27dvJzQ0lGeeeYa//vqLHTt22OXxcobRaGTYsGH873//o1mzZuTm5tKlSxc6d+5Mx2qcUkRGIjNL+uY3KKpO0NTXDwzlE/5wWMv3xhuwbRvk5IA3sr+s0j3EBRpy48Z1atYqvX6Ej+SU/SJfAf9wqY8wbvCAagvQpcxyFseNjEKr1SOxRz3evtcokBSsGurscjclK1he4ta5G0BNdJeu0pI0hil+At6rbLGcos8u4Cte4ujpw2ypbGFkvE9aGsTEeMfXRaWCq1chPNyt3Z544olSlSuAU6dOcezYMYYOHWoty8rK4vjx47KCdRugNEkm/5DAqpNtYGWOc1+cgqwCwAeVUgAKp3XKQ7qQoou6bCEzT5dE4mI8BCFQIBAq76gBSak2flfVyP2kbmg2jTlLx+BTQPnGFFnB8hK6Y2eAmmjPHOMovcEvgKqqYBVkShq7Vl11BjUZLxIeDmfOeM+C5aZyBTiktFGpVHYpfSz+WkIIwsLCOHjwYPnklKmS1AuS7snOzapO/j29yflrclTOV2zjVURGJgR6fnZCh2TFEybXlBOLS2MUKS7VN+XruEE4BUrvOKDrCgrlLtBXI2+k/HwU+HpE8bxzFKx166QJc3//CukuUC0luWwUKf2Pj0+F9FsW8jOl1SdadRX2E5PxLKVM43mboKAgMjIyCA11ngOkSZMm7Nmzh/79+7NixQpyciSfnKZNmxIcHMyCBQsYNWoUAGfPniUsLIywsPJFXZapfArypTHIx7/qOEW3UR3loqmeQ7mfQQqL4C0LUAHSO8NVBetalqQozeU5nnWhfsb1fMCHVTm9eLdsIpaITlco97SdvYHpXujFCxQUoMDHI9e1GqmV5eDmTejfH/71rwrrMq7ONV7kKxrXyeENPuSUsnmF9e0ufkhKYIvQahRqV6ZaM3HiRPr06UNcXBzXr1932D5z5kwmTJhAu3btOHDgADVr1gRArVazZs0aVqxYQevWrWnZsiWjR48mLy+vog9BxgvcUyeR7dyH+XJXCVopjtKARIdyhUFygnY1EKi7GM32D1cVrCtZkhX4FE1dql+QJcmvVXpn5mJQk+PW39VohpDdCVrOEEvHsHMO29LTpZRErnJHWLCuXMgnCsF7W5YwuYL6bBF2la/4J5dMS5jOG+zJ6k58BfXtLoHqfHbQlcatOwJ/q2xxZO4ApkyZwpQpU4rd3q9fP86cOWP9+z//+Y/1d+PGjVm9erVX5ZOpHDKzlYzlGxYlZ9ARfh/jAAAgAElEQVS+soUxM1ws5j42g/gNFIW+VhdyahFANr4+3tUeXFXg8nSS1S8d1yy5lpmL2j7eif7vayxcCepNBSvpcDr129Rg+6JE7nsyutztZWZIwnYJP+uwLSxMighQoHPNNnVHWLByMiUN/VROxaUK0ecZOE9DMnKl2CS5VMzUZJnIz6crO6lTo6D0ujIyMjJeQlcgOEELcvRVx6Ui0pDEXSQ7aAlpuiDqchkfrXe0h6acBFxXTu4LOuxW+wVZkoI1scHPbu3nKhYLH4CL6RTLxJGVkqUpfv4Fj7Sny5P0Ba2TW7AVR2iv3+1yW3eEgqXPl06YRl1xdsoTycE05jxbTkqRbLWqqhtAMTtdzz46VG0lUEZG5rbncIq0QEJ4YVVeWflFDKINhx2m6nQGFVp0Xos8/zXjiCQFJa61f5/fX261X5AtKUDessD9cb6h9bc337z6Aun8aDyUjUdn9gO8kB/lsK0ul11fpcmdomDlScqNpgKduH840AKAvALpFGtVVXeF3rGzPnRiHz9faFfZosjIyNzBbE+KBlz3O6oIdptjRBWV6ao+jCO0Rq/zjqw92UIKdxFVy7WP81r6ZLfaL8iR2vXW+qvTNwod6YQXX72WiOuBfp55xxaYLVjfXnjAYZsSEyY31KY7Q8GyWrAqrk9LBPcCnfQlplFW3RV6FgV0z/WGpdSUkZGR8R56gzReViWn6G95DnBUsP7IuxfwTrQTO1w8GYZ6DbmLywwM+MOl+hYF67uUPmUWrSQ0Qmf97c3L2byO5EMWWyfTI+3p8iVpnc14/cYA1jLA5bbuMAWr4p5avUXBMscC0aiqroJlMYlW5PmRkZGRKYpOb1awqpAFy0JRmfTCvVV+7hLLKT5hossK1tvHhpFMXca13O5S/RBNLgA5wjuuIQX6wmneRsGpXukDoLZ/Fr/Tm/YNPZNT0fI+VBfzPtTjepaB6qVgRURIOfNsVheVSMeO8MEHlaRgSTeXJdhaRU5Puoun57BlZGRkyoLOPG56ya2pXBRVpAxC5bTcU5whln/xCSlXXXtN6w1K+rCRfrVc88W6u2469bhE7YCs8ohZLFkF0txjV3bwXMsdXukDwFdRQG/+oGaIZ/ycVSazc76i/OpRtVKwgtLO83HuizDCMfGmA3v20G//e3zx9hVrrgGtl1Z7OMNgHijahScB0DjQMdZPVcGyakJ9RwTtkJEpnpSUFLp16+bRNhMTE5k9e7ZdWf/+/Tl16pRH+7kdMBilcVOlqHoaloMFC43Tck9jidBeGjqDUnK6d3V+VaeTUuUovRPU9VqulPpqHx29Ouf7x+EIGnGO1PzSU225wrOdjhLHgWJFboRjfKziqFYKVjZBvMbH7M1vXWrdzC59WE8/XuYLzu1P523e561u3tOii2LxwQpVZiJQ8HHcDxXWt7tYnDRlC5bM7YLBULav2aioKLZvd22KxVWcKVi//fYbTZu6FhDyTqK25ibNOU7PNp6Z7vEkReNRfaZ5DfCSgmVjwnNZXzIoOUVTDqRHu7aDXi8pWHkuanBuojOYF3h5caUlwJWbPlygEZezPJSuSKeTnNmF40rWWlxjNPNcbqpaKVhapDhNp/SlO2PfzzYAXuZzRn3fk2m8Q0CAV8WzQ6OQzIyRmjRzQdXVXqw+WHkZkOq9uXIZGVtGjBhBhw4daN26NQMGDODq1askJiYSGhrKpEmTrJHaN23aBODSttdff52OHTvy008/kZ2dzbPPPkurVq1o1aoVU6dOBSAvL482bdqwfPlyAHbt2kV0dDSpqanWdiwoFAqmTZtG586diY6OZuXKlXz44Yd06NCBmJgYtmzZAkgK3UMPPUSHDh1o2bIlw4cPt6b3eeGFFzh16hRxcXE8/PDDAERHR1vzKZ49e5bevXvTunVr4uLiWLlypV3/H3zwAZ06daJhw4YsWLDAi1ek8inQq/ChoEp5uauQlHWlwl6maCHFXfJKJHd9YQwpVxU4nVHFWWJ449Qol+ov2RrJRaLZerJ2mUQsXR5JvcgmiLd3P+qVPgBSM6WpyFPXa3imwYICSfF0ctp1aCWF0UWqlYKlM+dmyjSVbgo8j5RrzS6GSAUqOV3DT/EiX+FjyuUrXsSgqjqB84rSJEz6Wly5sxYbaz9VydLIVARXrkBCQvH/Mm0W5KSllVw3La1sMnz22Wfs37+fw4cP061bN959910AMjIyaN68OYcPH2bevHkMHz6crKwsl7a1bNmSffv2MXz4cN5//30KCgo4fPgwe/bsYeXKlSxduhQ/Pz+WLVvGP//5T/bt28eIESNYtGgRERERTuUMDAxkz549zJs3jyeffJLIyEj279/PBx98wL/M6bdUKhWLFy9m//79HD16lJCQEL744gsAZs+eTdOmTTl48CCrVq1yaH/EiBE88cQTHD58mGXLljF69GguXrxo3e7j48PevXtZt24dL7/8cpmtc9WB0XXW8l/eqFIKVhwHGcsctBp7mZRGSQnyhgXLVFAWBUt6nbsqTYF5tdwOPDslbmFa9LfW37l67717DXrzDIzWM7HT5u1qwV90oH+9Iw7bblGD69Ryua3qo2DZmBh/SSv9hniJLwH7gHWbL1ZcgtuR9bfwFS+x63J9XuIrZp7uX2F9u0uHyGSW8xh/0YGHxPrKFkemApgzB9q3L/7frl2FdVeuLLmujcHFLRYvXkyHDh1o1aoV3377rdWio1areeaZZwDo0qULUVFRHDhwoNRtGo2GJ5980tr+5s2bee6551AqlQQEBPD000/z+++/AxAbG8v06dO55557GDNmTIl+V0OGDAGgQ4cO5OTkMHToUAA6depkTecjhGDmzJm0bduW1q1bs3btWuvxlERWVhYJCQmMHj0agJiYGO677z67acoRZp/TZs2aoVaruXr1aqntVlcaqJOZwUT2ngyubFGsTGQGQ1jqoPRtEfcTw2mPxV+yRZ/rvoKlN0q+VM6mtpzWL/Cun1tDdZL1tzfVZYuCpdZ6Rp05nRpKDKd5uMEhp9s/5jWX26o2bs2SRi9ZgdQuxJRSmC/pbxQqNsdSa9PLK9I5IvQGsgnks50dAXht/xAqLtW0i9y4ISVX0ut5jBX0ZDN1uAoMr2zJZLzM88+DebbKKU2aFP5+5BFoV0IM2vr13e9/x44dzJo1i127dlGrVi1WrVrFv//972LrKxTFvzQs2/z9/VEqlRiNzl94RdtISEggIiKCpKQkp/Ut+Pr6ApKVqujfFmvS4sWL2bx5M1u3biU4OJhZs2axefPmEtst7XiK9l+0z9uRgnzB7zzIKxl7K1sUK4/xM9kEIkz28eU304uexBMa7HpcJFcx5tnEkHJRO3k0NJ7d2a1cru+tAKkWFMbC+9SbBknrbGoJY4Q7FOgUxS4WCCeVWlwHWrrUVrWxYNlq9Cpl6VfLMjV4hlgU5t8KZcWlX7ieE0AwWRymTYX16RYpKRAeDosWkZ0luEYtad65CqWokPEekZGS0lTcv2AbA0J4eMl1w8Pd7z89PZ2goCBq1qyJTqdjzpw51m0Gg4FFixYBsHfvXlJSUoiLiyt1W1F69erFvHnzEEKQk5PDokWLePDBBwFYs2YNGzZs4NixY+zZs4elS5e6fxBFjic8PJzg4GCysrJYuHChdVtwcDAZGRlO9wsKCqJdu3ZW36qzZ8+yY8cO7r///nLJU13ZeUvKgFGFZgj5hUepyU2yM+0/7HVo0aD3irD+Gj3bzFN3rlqwXqs5j+H8gEm4GNZB792TvCS10JxREQqWp/zodToFV4gkJbuIFdVopBebiSLF5bYcrsSCBQtQKBRWR8tRo0YRGxtLmzZt6Nq1K/v27Suf9GVEoS/U6F1RsN5nsvV3D7YAFZvfauT+lyqsrzJxxZxPad8+Zu9qQx2ucYYYWcGSqRD69u1L06ZNadq0Kd26dbNTkkJCQjh69Cht2rRh1KhRLF68mKCgoFK3FeWdd95Bo9Fw991307lzZx5++GEGDx7MpUuXGDduHEuXLiUsLIxly5YxadIk63RfWXj66afJzc2ladOm9OvXz27K0eKQ36pVK6uTuy0//PADS5cupU2bNjz++ON8++231C+LWfA24L9XRgLSlGtVYQ+dAUdFJ4sgrlPLOkXlUfR67mMHRpQ0beBqnAZz2AVXu3DdV7tMfJ9WOHvkzcvpq9R5tA+dXsFNavLO/keKbNC5bYSwmyJMTExk7ty5dOnSxVr26KOPMnfuXNRqNWvWrOGJJ54gMTGxXAdQFrSKQguW2s2o6PHmicGKfGgLjFV79tWkM/A2HzBJl4XO/KAlUZ+l1GdJ5Yomcweg0WgcrEbTpk2zji2ffPJJsfs62xYdHc2tIjlLAgMDmT9/vkPd+vXr200LNm7c2O5v23Zsx4zAwEC7v+vWrUt2djYgKX6WFY1FsYydttiOoU2aNCl236JjVlpZVxRUEwxm64s3c9e5y0xeBRyvxXkac57G/Dc5mUaedu/V61FgcXVx7b2VlhdAPr6uTxF62YKlonCqXrjoF1YWXmzzJ+9s7YPwkAnLmk2gyOnJy9CxlKE05qzLbVktWCaTiTFjxvDFF1/gY5P98eGHH0ZtjkDZpUsXkpOTK8cHQK+njjmLdVzYpVKr92WdQ1lFPrQGY9WefT18yof/8iZT9vS3XREsIyNzu/PXX/DOO5UthVOMFgWr6hiwrBT3/hBGz79YLicJWnKUPXRy+WTEJa3iFE15qtZGl+pH+GaXR8RS0ZsKA5jW9nU+Re4JAshhPqNo3zDdI+1Z4ncVPe230iS95xxNiu5SLFYzy6effkrXrl1p3759sZU///xz+vfvb1W4ilJQUEBBQYH170zzWu/MzPInYTRcvcFVsz+Tryqv1DZzccyvVKAzeESWojg7Tp0TBcsbfZeVnCwpRo+fJp/cfPsBoirJWZF48n6tSmRnZ2MymTAajcU6gFcV6tWrx40bN5zKWdI2Wyzbq/qxehKj0YjJZCI7O7vU+9fnwQFk3TSgfc311VAVhcEkjZv5eflkZmZW/jNpMgGhZhmyUGbaRj2XfHSysko/5+6Sei2L43TgEVay+cxl7oouvX2dScMwfuSZ8C1kZr5Qav0nY7czhr8B3jm/OpOkJ3zMJMa1SGbaYe/045ufySgWkhvQwyPt55tndAxGYdfezWvpQE3A+XE4K1MDHD16lJ9//plt27YV2+n//vc/fvrppxLrfPjhh9ZgfrbUq1ev2H1cJZqGwHkAUg8uIiRkZIn1O7LHoWzt2rW8HtK7zDK0IJjW1GMJx5xutz3OWPY7bA8J8VCkWQ/QiSbAGdL3v89F+gN9AZjCu4SEOF7DOwlP3K/u4k8MuZwmlK7cYqfH2w8PD+fEiRPk5eV5vO2qyuHDhytbhAojMTGRpKQkOnbsWGrdYSzgR56BkKrnb1kfyQ9uxsyZDJn5q7W8Mp5JsFggJFNGXFwc6dhaSaTyhx9+mCQ3po1coSUtgGNcJZJHHn+I0zjGZCpKMOlo0bF71y66ufCu+QCA6YB33k0NzOdkHf2osUR673rjOg7mJXxZSN4zz7DMHMKlPPyEmhT+5HxiIiEhhYtNoszvzL6sIyTEtbBLaoDt27eTmJhITEwMAFevXmXs2LFcuXLF6gw6depU/vjjD2rXLj7q65tvvsmrr75q/TszM5N69eqRlJREcHD54pqc+e08HYZJv18dHMPkuT+XWD8kxLG/ha83oOZbZTdV/j10P0tELzIy7DVVZ8fZrc5VKPIuK24lUWVw+vv9dBwPI4YPZsWBxmw6IZVr0FcpOSsST96v7rL67QM8+SW89uC7/GNZZ4+2ffr0acaOHUvz5s1p1qyZR9uuihiNRg4fPkzr1q2toRVud/z8/KhXrx7r1q0jNja2xLoNzUlxq+Jz3iP8Evfpf+D/5j+O4rHvK/WZBDBm5RJWV/qdsC+BsNgw67aPQt5nGu+wcsWvNHmgrkf7Pbb4GPeOk34vnL+Qlo+VPi1VJ0RNOjWIjBtExtbvS63v8/bbfPXlZbqwm/leuBeaheWBETQKA0Mff4Ixy5Z55TpO6riPuacf4OwMH74dU/54k35PPMFXG3OJahDN+sOF5+XUhst0Ggz/5j2WOjlflnvVFjXAuHHjGDdunLWwR48evPLKKzzyyCP89NNPvPPOO2zatKnUlS0+Pj52/lsWgoODy31StQqt9XeWIpzIMrTXMMJgv/7cTRqIC4Rxg+Dgmk632x6nENes5aGkE0UKwcGuxc6oCDRK6ToFBGgxmQqnfDXo7a7VyZNQsyYUE+T6tsQT96u7qFXS/e3np/Z438HBwSiVSkwm0x2jcIAUM+pOOV6TyYRSqXTp3jUgvRwqQ2EpDSNKwrhJSFCk3VhdGc8kgI3HCzVCA+xk6Mt6pvEO/n7+HpdNJQrfd36+fs7b/+or6N4dWrUCQIeBD3ibTWeOsccFeabsHUAydfGhwCvn1lchLRZJ8o1l2vFhwDKvXMdcgx8Aey/UZ5gn2jaZUCBQKJR2sqqRromP2ujyMZS61G3EiBHUqVOHQYMGWcv++OMPatZ0rmR4C11+oT+F3kbZcotyek7OZ7TLddv5HmdI/kL68xtj+JY8/MrVt6e5lSFND2y91JDWwRes5Z/yql2c2ubNISYGTp+uYAHvMO6+S0pX1CrKM46atkRFRaHVapk7dy7PPfccmiqcF9MTGI1GEhMT8fPzuyMULL1ez9y5c9FqtURFRZVa/++KlSwUJbtYVBYT/WdTN+MoiHGlV64ADPmSte9HhhIS9LndNkswa2+kytEX2KzAK6b9bS8tpUHQbBpkHsFoEBhRo8LgcpiGa9lSct7FjOCH8grshG9CXiNqSDeeW3Q/yblhpe9QRvQWp3QPXYd3Tw/nKnUYErEL6Got1+VK94LRjbR3ThUsSwJTkB7eqoDexhH7/45156tS6k/jLd42zzJb2HuxFp28IJszFtZ5A26d5Dm+IYH2NONEBfXsGm3qSy/y6JpZPBG0gRf2jQHgGnXs6rVqBQ88UOHi3XFoldJzptZ43i8mMDCQTz/9lFdffZWdOz3v31XVMJlMJCUlUa9ePZTKqr2a11NotVo+/fRTAgMDS63bhoP48zgQ4H3B3ORxza+8xBSCzoRSujeZ91GZ9LzGdJpzwu4D3WiE1QwkjgME+pWeG9ddbN93xdkFHmElb+pm8i9An2cANPhQ4HqgUXMwgF78AXh+kO+tioeou1EohMvpe8qC3ug8rEJZWZ12Dz2I54Um24FnreW6PEnp7av7lRsutlW1gzXZIN1AEmp16WfSkpDxATbxB5KD3eaz9b2qYF0+p+PP/25i2LcPEGgwkEo4qxkIgKmKBc23pDEQShXWQFhAf9YChakfFLduYkrRQRHFS8azaISeKJLRltE4WxpdunRh48aNpKSkYPJUyOMqSnZ2Nh07dmTdunUuKRzVHaVSSVRUlMvH2kdsJIwbQOl+OhWN3qBgAc/S9/rOKqFg+aoNTOcN6Q+bN3hBAUznDf7HCOrV8XzIC2Eo3YJlQG1NGycKdDzMb5xRNnU90KjZ8nNAUUIerPKg14NGgwL3lJ///Q/atIG77waDAa5elVxUnHgfAWD0sIKlN6mcpsqJrZOJGj11lNcB1yxy1UbB0tlo9CpV6dqwRcG6Rm3qcYkk6nvsAlzbdZ7a9zhGljvz0W+M/elp+g/ejbJARS1SrduExnWzYkVgq2AJnU1i0SJRahWXkxDLtgHjK1K8O478fHic5TS7q4bX+ggMDCzVAfp2wLJcOjY2tmL9drKzISDAYznRvIURFfWxjyV48yZoNFBMUPwKI0En+RNVmUjuBgPreYi/s4Lz1zKpEykVS4mSlcXmrCsvPZtd4QBxtOVgsc1nEcx24z38E/BT6fiVR3hRO4/d4l6X+tAbzIqJl7J3LMl9mDY3a6NUmNw6Rf940cTkt0zcfbeaI0ekdFzffguji/HQseifnrpnDEKJATV5OpWdY0/t4DxG8h1HlW1dbqtqmVVKoHZgjvW3SlX6ifzRnLD4KHezh85EcB2TyTM30j/uTXBafiRJ0mpT09V0ubLCbtuaulJckps3IT5eeqFWJgfOSS+e1NwAHtlf+AVW9GE7TBsW8VSFynYncuF6ALOYQK7BSyYsGe+SnS1pJ19/XdmSlMyqVXzDWP7JTLvimjUhNrqgmJ0qjoG5Uh6JqhLJXZ+r5yxNyMPfzpKky5E+SrXoPJcEz65jPS04zkXqc3ejnGKr/ak3rzg2z0IoVEpMLipMlliN3pq+G1PwJetPN5IsWG7sp8zKQCxbDkB6khQM9dyfV4utbzTHTjO5G/YuNRUOHXIoNggV/8c/eGpPkXR3BoPbqXKqjYLVKuqm9bfaTb/VnxgsnRgPOcFF2FimbLmeI5no840aLhrtl+3GaiRH8v/8B3r1glOnPCJKmbmWLr3IdUJtFxT1Dydz8RnmQHt3KhURr9KSz8wbPlgyFYBl2fbmzZUrR2l8+innaMxBHL/Cr96sfCu7EWlwryoGrOQUBeP5EgCTsVAofa6kYD3Crxw84YXzptejRU99kvBROw5AlneZSmG01gdQqpQup6XRm8d9b1mw9GjQaBUoFK6nyhECblGD62ek58l0PhEA1fHi44CtbPeedV93yGjfi3Nxf3coN5gj0Bdt7sp1FWv4G/n4utxHtVGw0OsJQVr2qVW798WQQQhK3DNTlkRx/lSWjAlKtRK9KDL7au48J1v6v7JnESzZjtRq0NnkTdSbl6Lu2oWcQgcpZYVaDWtXevdkJKdLxui/kmp5tR8ZL2HRwqv4qsUTWXVZT7/KFqNYDJbQnjovZyJ2EX2+c18oiwWraLmn2HyoJn1ZRz4+TjUHk16SS6mQtp09bUJLAQVKXwYGb3GpjyCFZBnzioJlMpkVLPBXFdjlEi4Jy2O0Ol/ymzYazIpkCY+V2qTjPSYTV89V13OJ+5IW04RzDuXWfJhFlMLdx4K4SiRZwnW/zmqjYOlz9dRGii2lcMvgCFN4j6tEeswUerMYBzeLs51KXThQWPj8pjTNZjolRSpWXbnsEVnKisVi4qMFvcn+Nrh+He69F96TPgzMq0zuTM6vk0yNWz/Z59V+cvKlESRbL08RVkfyc0205ChrrnaobFFKZOetFpUtQolYLVhzv61kSSQMtuESUgsTbdspWF6wtiWl+bGBvrzGRySmOI4Jhjypf0tCZUOBET1anq75G+/X/tKlPn5o+QEzecUrC7CMBQYESjRaJWvbvsO37V2TSa8zW/LNljmjXrJalLQYWGkyMJn33Vaw1DjPqWwwG0eKXlfLO1OF6waeaqNgLdlZn9M0BSCmRtkyynvqQVjOE05Ko0jPl6wQKrXSagmyMDNjFADGVOkmUGXd8owwZcTyYD517zlrziiAhYxEmSvNe3fI244aPY+zvFJkrAoYcyW/FJXBu/4p5jUHqNTyFGF1JDUVjtOSFcmejcJvx65dkJxcriYMJudD/j/4kneZUq62PYEwv5KOUTWCMttZsOYvsP62xMcCL8XBMisaX/AyKamOcessi5RaaaUPdoNOeumrtUrXfcL0erd9ilzFMoWq0Sqk6RoXZLp1C+ZOl1yBVAqpvisWrHfPPslsnnf7Bd+f32hAokP5jrCH6cxuJwqWJFMXP0e/reKoNgqWwXyiG3KeEa1cP0AL/+BLnmh+1NNiweHDBIeEEMpafjonBYFQqu1PawDZVnOjwTzvrdJU7qm3aOMapdEu63kUVzBcMyuB+/dgQFOspn8nYNRJA6y3Z36MRosPVrV5JGVssKxyLhDeC+La595sZreYVa42/spu6rT8S8YzhffK1XZ5sVVUqkpYG4viAnAmO9L6u05oPi8gLWiw9c3yFLqCwjad6Q1apYGGnKe1rxQB2jJOmVQa8owuWsH1ep5gGX9oy59exqFpi4LlY1awXFB+kv44zYT3pADm7ihYG292YB6juZHp3rNXnHLZiPOEk+YwT2YwK73zIl0Py1E17mIXMJgtsjeoWSZT1COspGXE9TL3L4zONfDclRs5Rgsi8KcGkvYtlPZ3QwgZ1pUdVkW+kp2w9BanaqUJgyiUV6MyWQcVy2HcoGKj9lcl6ofnEkA2/WM9m8y1KAbzkmmlCyFIZKoeVguC0nve2Zvow7jM6eVq42BuTOEfVcWT3IxFSQA4SqtKlKQQ2ynCG/rCkB9hAQW8wGzASxYsG5clp+1bVrQppFe4wXzu/n15LHHnS87Tq1DAyIfTGXP6NX5kGPco93hMbguWuJUarZLJ50by4anHS93nyrHChWyDQrYAEB4oLbcP9i3eJ89gUrKfjvz8V7RbMqYSwWWc5JA0GMw+2/ZjsXUhkgtRDCxUGwXLaJAGMA36Mg0MKozlGlBsTcK2xJ+tRyuOcYZYWnBcktWkIJIUfmQoR2hFP9ZZNWWjOVREUSWsotHpJDl+PxpJC80Za/k34jmrI/62680BmMx/Kl7AKkJsZBbZBHFvdIpX+3mkadWK9C/jHlZLpxcVLF/y+BcflasNo22Ub5vx8FFWsIBnytV2udHr+SefArCV7pUrixkp3pVE/SCbNFbmlzB4R0+1TBEW174+z8BbfMCw0HWSOGY5NSpHxcAZ36+uwb7sZlygoVfCTPipdHzFi8TF5rIvI5aDGY5xI4uSkVV4b3YKlMbDTo1v8CsP82irM8XtZuOU7p6M3/A8Jhzfw5Nz3iAfX7sUciApWApMDjNUJVFtFCzLqrcbhPPvraWE9TeZ+JyX7Yo28BCHr5Z9hZbSWPhJ8TGTrL//Si6McB5BKilEcnejHFK4i6EsZTA/MY8xVgWrabD0oq7hvXiSLjGqnTTNejk9gB9rFgYRXWEaZDVP39AF0ZG9DOPHSpGxSmBZ1uLllCu1/LKAKmdUkHERizOuN6eSQ8ggxJyouazYLvSxtYys5FGeZYGzXSoMtdDziXlszcbNiMwK9nMAACAASURBVKdGI+QUHy+qrNT0zyMQ6dn840rhAoFbt2AX99CKIwT4ej6OS2kWrGtXBWOYxxVRGyi0oGpUJtcjuZvUnFQ0Z5bhxfKK64CfxsCLfE3jejqUCtf8vGynWi1WIq3SwMOsJjI0r9j9rGEVPDR2/lf/Ko/yC+83/Z9duV4v+Qh2Pfedy21VHwXL5oazjdvkFKPR6iTZgmOAlNZgybGym51VwiZVj41Pkm2MpJU8yjFaSlY24DoRnEB6KE1CQWoqTGr+GwIFERFlFsUj+Cklp22TCbuDaK86VDjvrTDiQwFKN1dt3k7k55qYx7NczPSuRmyNrH/nnupqjVFv8dXz3gXUe8Af0mLBmsTHVe9mMxjK7nA9fjy4kxbp4kW4cqXUas2iMvmepwFQqwotPYdPaHieb1jO47Rq6HnFzk7BcjZDaJ66tExJ+6n1tCWBAI3O9VyEQsU+0YFXTR+XW17Hxs0HYE6V48osquW9A2BQSn5kwmhWGEv4crFYsNw1xD3JIrqzxa5MCAr9jos02Lm+dL/cMrqu/FcbBcv25Jc6Luj17ERKF2AbLqFc44nBwKvMAOwVrKIXdShLrDdXbQp9vgQK7r8f3j34iFRQmg9WWpq0NMlbmE2CwiQKzYNmsWqHSspXw4BUFAhMiqod28ebrN1XizHMY9lx765qOncjlFmM55GO5VslJlM5GM3+Gb5OgkJ6ipvU5FcGlauNRwJ+B+BJ/ud2uBu3yclxK5ieMV9PMneVra+ffnKr+qzoGXwf9XrpFfV6dnEPAJc1Da3FFoulGoNXFNU3OmziL7W0aMqZBcvi47Q/XxqX2jW6RQLtaRiYWupVbcYJXuILdCYNWoXeK6sIczMNxNODjAJflwON2r7jd+W0BmDZjkiUCP66ElncblYfYnd94QyoravpLVisaM6ua/uoK7zCTJeDpkIFKViT2m4qdxt1gwpN46UdYEGOgaPcDcBpmmJCQSPOles5KMgxSPPVSJHhLRSN8n2DcI6e0tCVHXbli0P/gcEg5X86S2MKSln1PzBiF71qFR+9trysOykdixDQOW2NtVwoFIQHScL5qXVs534SnER9LivXrsHBgx5rzuuYzA+tQuld5/PNF6L5D5OrnlVBxiWUJgMRXGdsG887DNuyt5zp6lurJd+Wt5nm/XstMBD6u75C7WqKiQbmHIn/6rjFvb7cNF9MYBYjXUh2bSwwEIgUtiYkqtBCZl3U4CUFSysKaK45xw660rZxpsN2iwXrl1s9zYJKf2+70YILhvolZp84Rktm8TJ6ofKagpV4UUEv4jl6KRiFQrikyttOEVqc93PypP/3J0cVu19ZpwgNqB0swpbrOoZveSzhrSI7mJ3f3eijQhSsued7l7uNIS0KlY3SniVdrnTSmpudzn/msXJHcr9x3cgvSGH161IYJNSZLBdT1Oykq/XvOlyhl3YHZ8/CF2f7EcNZzlwoOc/2TcJIxXvziPuTpS8Ckwm7tD7XTLWszpvZeikFRIoo/uvBXdo1vkVbz+lrXsdUMS5Y6A1Krw3WHmfvXsnUefp0ZUtSZWjbOJPr1KZFhBetzkBfxcZy7a8w39DHaeGV8AK2xNOD85scI2UXR3ELiVwh36QlA88n9l69t7Y1fEXnmMJVbpYVZQ25wJ6jAR7vF6MRP42BruwkxN/RCmhRBFTmSO6WWYizaVJaM6Wh+FV3SrNKZRBqs4Ll+cHNogBqfFUuW7BaRBXGhtQppClCV8I0bIscArg/dC7nCTbykF2Z5R40oSLL4Ge37cpNH47R8vbMRWg7jVXaibScJMuJOEdjaaqrHMmebZfr2sZoMTkxS+ry7ct2cJ+DJlbaMUSRQhTeW7lm+cIRJmGNngyQhy/Z0gcbmTop55InfbBScqpuXkNFqmReV54oXNHnygPuCTLztVwhil2nKnn1gwvk/L6TSXyMLsELceWqK5bxyVuauBC04giNVYnlaibUnG7sAo3sVsh5g17E0xTXk67ayuPuyzIq4wShbiwACCeVHsSXWs82DtaafbVQKKRZT4vPnUBJfoHnLUA/nmzLu/q3pT+cnAzL+0illOTbtD+UxpzFD7MzeAkmrFHMZx19MaJEozQW10W5sARoVfuopGTPLrRfNyTL+vtIjrTq0BIfsKTwNXW5zD/4kha13Yvk7gy7ALJFlMJvd7diA32r3hShRzAauYedQOkXy3Jxc5C+LN5gOteoXa6byDair61CEqKVbujaFGb71uvsB65c/Plf3mN2ZcXF1bKgQHg12J7lfSAEdnGwVJg4clqyXJ3NlFao3K/e6bF+NejsBahCqPbvB0C9pnDK1LqI0FvxqbKyQAjyDdI1SEr1K2WHymfn+TrMYBKHLlV9ZdCrmEyFg5HRyADWsOa8l1LRGI0e8YdcnVu4Atsb8ZuKYsD14I8Wv6L3eZtnW7o31Wp0c6xsyAViKH7pv1Umm3AJ32yU3Cpyb+RZg06Cd87jnykN+V43hM+YwMWrjsmki1qwMrOVnKcxvkhxo3Jzi297IaN4nelcDYplUpi0ctTTx2B5X2p8VfzQ8TN+aDWt1H0iAnKZj5TxxJJj0TKDUGKGC4OBLxnPA7FJbslYE8eMMBbFVUuBg1lBb45VWOWmCO/G/cjrRfnPtu7sMjuuR/qX/KViOUlJ1LeW5eNbLgXL1oJlmyqnX/3jvM37xFI4XaIvsO9o3YOfMT77A7uy0qY5lzGYTfQpu8ClYDRCDW4yussxO4VxYZ03rFab4fUlP7IJvnM81u8YpBxjiYNf81ibHsNyUWysEJZpFK8YJm7cgOBgWLjQqsh5ISSNxwnSSIO4r+tJ5W9LPlf9k9+7TAZg3/EAfmMA+67W80pfxgIDR2hNomhQrnYMNivMrC9VIXia7xjJwnK1XZSWHGUCn7kum3mM7c0mmoddc6svdz9GnfnfOK1nngrswD6ikeIiKY16azl4R8EymiBLBPJPPuNUkr/D9jB/6RkM00pWH4vCZVm4UJpMR2iNxlSARm2uX8oHv7tYrJEaXxWBmgICVcWHWbBwI1PDJfM72+LyanRh/P13xkS20c3twfM1PrIGB7cQ5KtnMz3ppvjTMVWO+XZpoHZ9ZqlCFKxWlH8qIStf+hJqx1/8q13JyYedzeW/o57OoMZll8PWgqWwSfbYLiKJ95ksTQNa6hYxvSvVSod524r4eiwJo1GK2+Wj1GNATTe2AdDO/yS/7/1/8s46TI4qfdt3VXePTzKZ2CQTdyLEDQmwuC4OIfiyuITFZdFFFpfFZdGgS7AAgQCBhHgI0UlCXCY67jNdVd8fp05VdXd1d3VPT5b9fc91cZGprjplp855zyvP0xoQKuiQGHNtCOrrI6qIZFXnB1+2QN5Cc+FmYEVuShnK1pUwgZ+Y83GxJRT+v5CCpRgmweJ/uQ//tzGZpzlqwT8AKCkXixSnrmcq0VAjxrTZ2rhmtbMuaFfCWe9P13mTC3nD9B6kConq3FleD5oSniwTNbA6U+zpGKk/N5+xPMytYqOqMqBTBROZArTMNxsMKpbgsVv7vQtqGMYSOmeUmtdpFuN4NLAA0DQOabWE9zg75RWlVg5Wpl8Mnh4e0s9rOnIP9wK2B0tqtMYi5n6q9lJmcAR1jYl5d936Z5oa5DBm0sG3N5LJPWjQl7V81/kCz+fYJwbWizSfyEyu8HOpivuynMaQxMUZU5hQ6D3hMhxOD5aztFNr0qmgFQYqgxGJ+E4DqwO7hNZlGDfJf3tyCmqKuA9dJ4jf6mgBn84D75irZPM5Jx2WyMyEgw8O2TTBNOS2E70q5L+Fn1a0R8HgjV/tLPyCXMFxc2Df5GWWoqG+HmYxgfKmbIJmfmBLJx6nAlu2imuteuGdOHv+/wM5wbVUrp6Vc0P03Bov+DU4xPq3NQa1ULheVFx5N7DkPX7FcSzYkZgn0NVYWrMmZjHGTgpctzvR1CgW1GKJLMNWBoMLy3gAkSOV8FiuaXEpeDRdIaA4qHTCYUrlyPuWUYdVJv+jHnQ3UKXd6iPIefWvsFHvztl8YBk0qYLTg/XShiN5ZsspcY+prLUXJ0d3FKXmHbLF+BvLGA7i437u4rnZQxO7RgI0hYewzW9BUSNNzmBQwU+QoK5SWeltDbBPDKy/8Eqz2wia40oG9XENLKcxJJGQyrhbm488Yf3bOcg98eNwK7nyBETujozbz2MsuygQVRTAWOZZx/23PRWaBkUMZEZRIR3ZRWZA3NP7Vcdb+8zaMwCAcyufT+ocR/MNN8w/I2TbDkRF4ttNE5NqsyVRUSM+tj11djn2sYO2YKAwpGt5tMOSRl2t6ATb6/K5rK9IuP1v9wsvKNohChUqtkaWj///Cinl1VISo5J36c6sJ5vXjiMdQE7cddUaZ/Mec2medywcyxjKy1zqef+8zAZO5yMe5wbeXTMyoXO5TsAzZ4r/z54d8ZOK7s2DFTSsUKIljaPploEDSXyzt9wCHWKrigT12B6sYH2Qm3mEc7v8JP42DfyLeU0cE8Xok/1IReddYyLrm8w0mhQPPD3aVXMrD5GXrzJj9/58UzI27jHV9XbfPK7TEgDOGraG57iScX2jJ7DLqEjMWygrgxWhEaw7eJAaQslpK0o1nucKFEWhS1qoERzUBC3Hzxu70Lo1bFpSRjzsEwOrlsgYcqKQYrjTOYZ75h8bc9/eBTUU04lj+NratoLBbCjPT/r8Bb99beUoTPXbPFg3F9lu9baUMJ8xnDtqNUF8jGYhAIoqKhqdNnGbnNgEfINZzrm8nfT1xsPNg78CYHlxPlvpxthjRMLyUyXnhuzXjzUMDnivBHKinDwqw0qnq80OrSotnGxUVQWnnio+LI+Q3qMQL0QLxgirzKKZRSU9GN56Q8jp/siw8tIS0ORqcVx9NVxxxT4/7VDESlsqTbRUEaHWICb5HoHmEdE6tQjle2yoCfIBZ3MGHzWr7RCYsjWn8onnQ/p1quIjzqSrsj3h+d7NWCqr9nMU0ymri0wWXMb+7kK/YSjIqmQ4v9GJYiab+WRpfp3ySpWN9KQz20nzJeZVfOzdTnFDcpqmEJAG1qxIA/HbBXlM5H165ggjQBpYx7dbAEQfR2T6jAiPqRRrHfmY0yzDK1Xo17GCh7idVm18QirHU8TSXp1ITU8VnSt5gQGdouddezGw5o65jjeGPBb3Gnbtgqt4nstyp/D2gNDE/GBQYTn7czg/ALBjxsq47e2TEfIrTmh2G84cvN21sSUR/ATpxE67ZBX4S8XjPLnkkKTP/zMTbMkE1b0z3sRjtGcPrfy1+NCpI5MaslAVYWDdxX38wgGC+LQwNtNogCYRDm0hFKbvJZdKdPPDuv20NYzqsDnEO5ehNtKb9aSp3tmYnVjAWF7n4pBtVabGmEoLWxJTp4r/3vOuo+hmS+lBnekcxfbKBLXRvJxPGnSqzU/03w4de0FJnVgwfRiM7/bfZ3juOXjxxX16ysWMsJjVW1qL0GIOV5oXIpQerOOYRsCUfpFtb/dgcHjGRReRSyWjWOT9GBmeUUI1E71Aph448dGiXnzHUUxd0iPit830YAkj4rZ76oAivss4kZ10oiO7yKeErEyDD+d04QhmsJ0uTBjifREHsKOpbdx9NF0hoJohwu8jc46lQeU3o2ppShMF7EC56EJxTJSkdWmoy9DtnKrBnMHHNNSneNyROT0+H4pioHvRInSMfdV6Vmg7USxGXcfi8Yo1dn65rj/3cnfItr6s5WSmhmyzJIgCSoTFdnDHtXYVPFDdEL9C9g+0BI2NoEN/MG5XCNpWuoRf8aYyHg2X8ZL1ImPFq//Ca1Zidw415FAjBgxUTuQLVjNAdLU4Jr2Gr9m6Y7FPIMq+DbPjZmYpjC/YFLISzFAazDyK5LtJuFr5k/wNiM2ttWEDpKfpXqTCoiMJkWY3A+vNuf04hunMKEp9zpjMk/CpBgv39uQNLuD0UZtSfp6oMAx48MGEJZnUdcKjubDpj8MYu4iRLGTUPj3nCJZYzOMtTYMlB/7pjYc1q51JqlhwPMn1ZGaIb7A5BJ/RsH3JbqpoldAYZjQ2CR461cBIcP31PUdE5HulxPkcDKKkiYnUklbRdYJNhr0YTdDd1t1fTBax9QsfG/g6r/Z6CIA3iUyqllWDRTUixHfB6FXsSO9Jh7xGDmdG1MKkrHSNQrZxDNMBCKgtU7BSVa3wO33QFe9Eo7pj7fDiRkEA+tTMoSgYFJe6lyw7ecpivQa3+TSDeroSSu1g8Xe5GFgTe87jNh6y/vZC3fM/Y2C1T3NK5cTed8NmH9fwDGv6HM8QlrGVLuT4ajGaEWd2qru/okWvtvmRP/HNii6cje05+VP/7TyTdhOa6cqsJz1uMvMyhvIs1yZ9vfHw+eahVNKa2nofB/AL36/qJEKZjsvaVt+WaZzAHiP+iitR+GKsxD97YDmNTSo/v7w6+RNY2ZwJuBT0yJLgqjrT/dwCDjcrH8IHz649mrc5j+y05LyFSWHbNsrveARj8vUJHdYRUULfO7ClJa4qKYxmEWPMkPy+wnp6sc3UzpPv8tqDfm2Rc8n2P60/Os6esXGKIVbsz3INfCRCgm45q83F/XsuB2Ax3nOpvpzbFhWDPXq7lKQEtckUVAatspthQDY1oaaJMaCcPPbQgWCTQbDJzs1K9GKDullgFOO4LoFdDGstaCEWuSwcZJ7vcxuPhepqqKsDn48DB5YxgyNpneP+TlU9yGJG8i+uBmwB61QbWNMWF9CP36mpN4lGPRzj5EaVxnJZjeAA+3Kpe9GD5E6D2K/hVS5hHX1DtsWSyrmv9GrOW3NHaCOOvDvwJp/2P2NgPTRkCg2HHMWwrDVx+/P2nT7+xTW88eheDmYWixmJqtAsJncn9hrtYv4+e30nPuBs6+/BnUs5XxUVV3/hdTKpZ96y2Hlpg1nuSoSWKny0RSQdNjQqzOUAyuoyzA/BfkYbqgXRaKWegEq9RwwNrIr627B0YVh1922Luk88aEGDarITKt92c3pJQ7glQndWLpMiQgJydbyvUFGq0YZyXlj7p4SOa0AMeum+Px5Z7L5EH9ZzPNMAmDR6LfWkk5seXaKkOcjLEu32C2xsVjuKITr5v7iGjSuEFyXV+TcAw/wiofgtF+9LNMjJLaAGkycNcEwO+3UQidGFbeuTbY1HfxnP8DKRc7MFUV29d68YK+rI4gB+Yc6KxCR6fm/oThWtYo8pmkZGmk4eZVzBCxE/W1Wr6NTntkO7+VYRL5RVFtEmyWCQjuymtcnoH/C1DA+WpYCR5t2DNbrQ5peSWoQ2Ibb7/WT4g8wyKZJiDZ0lRM7ZRQy0IioSwUbxfezS27G+LlR4vLw2LSSn+P+UBwtNIy0NAkowrqEkrfs2bVW+5AQWMlok2qXqUhy0BaNcVs0RAvKKEsKWDvEn7LHMpzfJ00rEQ9BMKGwMii7g8yuoqhFCJ9FkimimuoQXYGhaUdTfcv0idy49ksA4Elu2iEFlfeiz+uX3DuRSzZwN8UuxJaTL30m5IsedlkiNGtpbaBIN71iMZih8y9HMWxfbeE8lrO8kPT4JoBNPyEGppUrm/oewDFEarupB0mlMOZ+QRKusIAcym67+5sTNIc2RQ/L6UuFdagkPVjLUD9Jo8DLGhyOXSjPlwX7+ASVIPiX4okyEp/Gx6/Z3lUnsfuQNACrq0qgwQvMvDU23rnUuB1BWlRj32YzaA6x2ouGdrYfw4d7DonKJWUSn1VVkUo8fjT/XvW+vDqMYJOWlOjfyKCtNOgeZh5dqehhpYPnTfZ7FnscV2uE6qQNosadHeVQ+NA7iFyYyhd75ieXCuSEo6SVULSJv7NK5F4UYZF6CI/87BlYwCH6/J3ejU2hyC915gDvFS05RH3J6RRYxGhCCzhJNYWPLtopcvtFCWdnjGViJcsgkCs0cwOS1+tNUi05Cosk0CodlJFdFGAsTMqOHcywiSyV+99z12Tye4jr2fDIrZPvvO8WgWLTTu5zLGcPXYKBw2QS7nFfmBbREiFA1vQmKT7Hex/Lt+05+Rg6q2YHEvC4yXL48Y9/mPMVCR3aSR/MH2KShaUzmSb5e3TP+vkm2Lyu/moP7uMv6t7SPNXPVrjaTY8uJiibhoU8jdjGPE3JSvrPdS0zqk5hUjuyTznF1v/Z7KaEdo/ra6SXa8lXUPPg02VRzEJHVeRgG5/IuDz4uVnfBJiy9PgldM0Lsx0SdznLijjUHvL3jCN7ZdSRl5LOVyPCY9PatbehubZuvjeS739qTR1nU/NWKMp3HuZEXuIIN9OSYwuVxryUZBB0erIdGfMwrveJL5WT6Gq3KeVlFKB0BP6zuFO1EAExhEmcPbj6hue1FjczZDmqhf8eU7zGxTwys7jTPrQ0w+bcLuaboCvL81WT7Yn+0cmXuz7BXFgqpCxGu1vpGbBvt8GQ1NYWe58uVPTk9+H7ItjemtY95jje5gIWMacZVxkZQV+jOJi7sKapv/AGF8wYt4cn2dhLfWR0Fx8pjnZ9wbSMe8inhYW4J2XYQsxjOrxycuTjqcRtLhBtWsvfHwsbd2VzPU2wpC11lulIuxINLVqyWXB6rJ/gJ8jTXMrpzMUFdVsKk/jzRIAeTaFWx8TCoW8tVuSaKC3mD81qQ1iQevl1ZyNNMZumO2N91sqip0pnLeCqN5lWzOokVu7QSPGY9Cuo5gF9SmsP2Up2ouD5H/cDzMdLAOqPtD0zomNyizukV+qaoO36a2F5mp2NcO24BOXdcF72ISNPwEaR/plm8oCmkK010Y7O1i64ZaEHDMkgTze3dz7/OaicagrpKjSYSu//FNRG/F+QI77ez2tKPRlBXqSDPepbhkOHgGRxBTzaRk2FWFaa6iND0sKk+ha655fRKj08vUlaTRnfzOcuoiTRkP1rc2/WY6nIxhm6mW8I38SKXRSwq+neu4i3Oo1NGaSTRaJj94CXCsk8MrAKHEHKyWF/Tkc31HZk++AaeHvNuzH2tiSPNvr1J7aZzZGH0vJ9E4JbX8zMTrH9Lt6aEWyTltS9iE8014iU+ljw0XWUIy8n3idWdL6AyrOMOjsmyy53bqUKGIdkJ2G0Q20N7ljCCHxoOjHrcmj2Cr6yqIS3uOVZtE8bYr9tCJza5IHONkx9wAPSNNJKtD9RhYMkPvCVSo9ZuTmc+Y8nLbLA8WPuSB6vOjAwuLkvO63LMoORz5FKNh7mNZ7juv3b+1TuEvJTeAtE2gPWbfGj4Wdno0m8TgJO9XIZUAkqQXziIuWnJ09iEw7D+r3ju1Fbejj+ygsvzeR2emGAQNPwhnoaP6wSR8v4sYw8uxrCmieiBIwcoy1fPZnownaOscwzpsIuJZiFToouiMzO/EMfFCBFqhoLiiz49H7/fBibwE5pu7+NTNGu8i+aRktEdSZMzpP1OHuVGMtNS23E1TXhEFQXMJKyY+zc0wBO/jOUB7hTXZ95WMM5lle7VmczTrKVfzHOc7sLxZoVfHccVtK7jPN6hVaDexYOlcir/oZ50fqcPQ3rHUNQ2sU8MrG85ptltaLqCXzU8vSyLIyTddl9c1+lDzuyZ/ArtUH60/p2tRD7YCvIYjSB5c4YI27K3xUq3m4OgbtL+O43RsGcrjQt/WIrBfffBjBnxz7GOPlxOKDeR9PRVGMIwmjkjyLWX2R7JXct2ceeMQwEY2iu+h8ROTA/9GKSGlauBNXcurFsXsXn6ym4oGPywxnbJZ/vFtY3slnqpnJ0lAaYwiRotwxoo9yWTe6MZGVxf1TGp4xNVr29JzOBwFpjh+n2CsBfVkp5OcFScNpOg11lJle43LzoJSpN4kJ4VTQdyvXndpIG1pHEQq8pESOi559LwVoNmntfhFdpcJsaYFVtb27+b4bnerA9ZFFu/N2k0kUaNbucAyQWmNEr0oM728mwu5vWIc3qBF847TVdR0sQCM82tmMSsaOvst0Wx/YpmLeajXZM0sCpozc38E9WvciOPk5Ge+hwsmdP6xdZhvLH7+Jj7778/PPSL/T7GF4ioVyt/7PxQSatwFN/xwE8HRd1vLPNpRShZqRVyd360saRydBU/IteyD+vJyPyDhAif5apmtxHUVFFSmqSB5eW4WDift6x/pynupfSSI0N6sH6nD5vpjkwlOpJvkz5/qqHpKp9yCj8UCzkcX0Bl+d4Cvqq2O/msssEAnL3poZBj774bPrw3epK6xF3cF5LzAbbw90NllwFw3DEaz75se+temmy3m50V/33JxXF4yawV7fNQ6SGxtVRUS26vsCeE68fOwUBhVLfEuKK8QBqwe+tzuLLwMyDxcENzIAf4ZIsYerT944QI7+QfCcmyNBfhWm/SOGip1yfHtJvbvp6yNgtbizDT1m0KN/EIxUphnCO8YwCiEvgnDqGx1hv1SLvsOsYyj+u3XM+jywUdxZQp8dMEnHB6harrxcrQ6QnPUsSEHS3HtbZSfJSflYlxMKi7GFiawfVfHcFsVXj8En3nspIzloEVNFQy/OJarhjl4hgIBrmY15mU87m1ya9o1jgYTyqnhhwe5Wa21ZtFNSnuuP3alXKuX6TFTN08gtf2nBxz/3C5yAsGiBy8hw/4nPZEX9w6ebAagtHzQdyKBS41Jfycz2rHbh9fcAI+H2Qoobmp35WMYDpH828uJJ8STwuSfWJg7SZ2OMwLgoaKT4XrN1zNQ8tiW8NHDtzOAkaT3cp+4Lua8impzUz6/L1Zb73o9/PcJTnaUsJ/OJW79/+UjfSgFxvIphbFXFYkWmF0Dc8kfb3xcG/XVwHYXpuHhsrBI2uZUjSca/baBpFfb6QTxdTpoSRv3dhMx9nuFTiAKKOsqmIdfdhAr5Cftpu8QT7Foesl8fHH6D/OtP70kj8lDZLwvm4tyl0MrKt5lstdSp+lq1/RHCtGu044/sUkCDlpTt/Ql1PyfyKd+hYLMbkhK12crE1GfFe3K/5Auj7zGcdrXBL5Q0NDi7w7mRh+EKK4XCWrPQAAIABJREFUogW7iTifOTGOyY4vz+EVs6uHAVC8U+UxbuLyptSNN5LAcSvdSMdbEcWJgzcyTz3QLEgS3+2F5ydGseCcLGXY3TmO3J72OAXsYAedqCE74nityQyhmeNTfqCarul7GMN8/oxYBGVn6jRqfisnJ9F3fmPVPUBsz5emq3TKqeTrdufx8J++i/j9yZnDuZ+/c272VI5FyJ75Fd1ziFCiSstiPmOsvOVU4cg+G3k9S+SOhRdPueGs08KMcPlQg0Hu5+9RCzCc9xPrPRzEbL7GXWLPmPaVuMimJuasaMVJfMEDQz9kdr+LI/atII+L+Tdl5LNppzv5qRP7xMB6hsnNbkPTFfw+gyXV/VhVEXullZ9Zx2gW4UvzcQ4iX+v0tQ/yt4VnxzwuFkoHTaCbydrczuderXQM33AsX9M7s5gebLbYylWzIuIC3uQlLuVhbolbsZNBHX35PenrjYexWcvpwlYMzUDFQE3zmx+CbZC0V0s4hJ8icsi20J2fiJ6vse64a5na6ny+4yh+ITTXSuavyWcTsqq49lpyqLb+LC6LbxDLwoXwgsN2WcJoSE+L/Oqe42pe4vLItsxdM955096oaRQxgJLKxFbSXiAFgn0+7CqxfRgi7NJehD8H5ydX+v/7rsT4f/Y5Ghr4KONcKh97OeVNq3qQDzmDtzkPiKvo0Wy0hBRPoJ0InUlDf7Y2PmVtNySTQ6pp4AvVrsv+ShCjxvsu2iDyRZ07unm3L/O/xjr68AOHWxXgTsgyfTnmPbT/e3yy/z0sZAy1ZDGKhXRoI4yB+7kLHYVTxyamDznUJ7z4kiLBDZqh4vPBQRmLXG++pt5HFbnsaMjna44DwKfq8UOEjaHnnLu7F+OYT0l0LeXkoGlWbomg/4kdSQh+OT3k7/pGmYQVZBcdIxRBrOM8GliPcWNENAXgfN5k3UMfcTGvoVfV2NGvNDVup9u26/+SVI7uw+/Tha5RPNIyB4t3H9bRlS0hq6Jk8EHlsSw2GXXV/DxruzOuW0cWN/GoRYSlYDCcXy0P1k08ygh+ZQ39o3YYCUuWoaVgxvCtUIffL8hYw8RgVXR0F7qEWS75CxLDZzzCqabG0w5CJWaeMxmEZVhqjGK7v2fXj2Iu9iC/vST+CsFwYV8HOKbPOq7nCfbvURm3DQnpPXLqJD49fxwDKWLKon6e2/EKWWnz228GSyp78wp/5fShLWdUh8Omw0juu/iuKIXadS2Aqt11nMlHXPVU8xLD3eBD4ww+podZ9bSvcrBm1zZPnkh6OwDa5grPkpx0U6kP6kYtEBemgaVgP0f/76KaMN5zLaUtBgoZafY9uErl6LolDux6CaZncnyrVSHXBEL2y4cWYrwo2N+RV/RWNzKcXwn4o9/Uvzrez9XDfmHgjhk8OOvgyOvUYBcF/Fo/EBCi4wv7n0d2lkF/VkeVyhnQtYZcKumEIPX0++NTRiSDpgadBlUskMMJrN33D53rrvzlHABun3cid3MfOVF0eSUxKMSXygmZTw1RBXoAc7j+9yv4NxdTUaWGphc5GzQM0qmnh4MRwcti6n/GwArQRIZfC/n4omHZ5tY8wk0YKPyVV/iMP3s6LhaCusph+b9xeb8f+KLJTtoP7zYfcBYfbRzFTTwCwG8MZ2i3Mk7hE4opJIifbmyhkNgVWEECvOjwsrxz0fes/XJtjCMSw1el49hKN9bVduIs3mfzzvQIV+7S2r5MYVLCfFxOWaFokCHCL9U/U4xIaH2o5ho+4TRrHy85t0M7i9yoNjmhiaBtM2t5ghvo28U7iaYUG32Pida2DWWCl6olcqPkx/zx3sO4bP1N/MwEOuVWxzkqdZA8XIlyKx2OqHDYl962ZCDDdqVNSVAbPP20EMWM0XgNWVaYSZ7rylELEj+XB8i+8sLeM5vVzkX82/q3NBRsHqzUGVgyFSARvPrLAPo3LA3hLPymMj5LdwgcnbJthmCqd97Xvxov5WzejzhMQj6Lg/MEPxS6bhp9oo0mApHhtAQ/BM1Q40rljE9bzKCOe6POW9Kgv6xM5McuZRjpaQZjB1axmv3o3sk9LJub3sh8xlpkwdLIS7WB9chPY+lWugQwvYFxnBufm6LpEtIZsrpMFOBEm1Okx1EcE739LznB8vSBKGaQBvOkdiI3Oi1dsRYbr204lCu33mafp1GngQw2YVdce3lm/zMG1sw+l/DCYR+GuI+jYf76dtzCIyiqwjSOZzcdvHm+YiCoKWT6mqjV0piy5whrezjb617a8/KGw3kSW99teI8y7uI+AE7ic+7lnpjK9Yam057dFLGfte28Nw5n/Imp0wS8Z4dICN7dkMeHnEVVQ1pEiHBmneDhSnQCnsyTMRMTAToEhEu/lVFBJ5PGY4EpHjyDwwFv4ZA+7co5jml0aRtmSLlQLsSD9GB9b54fbHK5FtEidHDVBHVf3EE31Vi2RoRxfitJzNswnrnAHyoFyxXynSWVxD95Mpx0UtSfG2o1cqjhCNPYvH7ET2yiOx0yWybxv2tbEfJu7W+eAe703sgJwpJdaWaFohOTsKl0zsQbF1ZFTYCdRkdUx1i9sqFPyLXGheP7ObG38EI53//T2lV8EyUXB2xvnhx7bl06kauKrraMtF8ZycrV9sB0Jh/wS1G+t2szsVPvwCJGR4TrQmCG2FRFj2lgaU6FEI9SOfux2lIJCZhRrlQbWJpmK2MoipwnFc9jhlzQBrXY43fvTrVMYSJt2Rtz6GwilPJHaxAroie5PkQOTX4La6s6M6tmhH18fWQ06f+UgUUwKFYSCnENJVEiKh7gs1zDVxzXbA+WZij4VCPk4wd4PePKiH2btDD+J1VFM0OCezwk/Cu6xnm8HSGVU0ts/cJEoJmhwCaTHsCX5kNVQw2sRkN8feFGZDwoGKTHYXDumSHyfsr1Vqw3E+FlftYRfC928mAcFeRUM40TGNYztAR3ym8DUTAoq/GeOyU//nrs3K+WzK05bohNc6AZKi9xGYu3tAxRpRsaG8QHcXLv5eLjKIpfGQrwKaIiqCX0GVMJGbqZWPhznD0jUU96TLWX8lLR9mLEINwmUE13trSYgdy3YyXH8hV5zTSwnFI5sk9bFBAp9GDJ8a415SG6rDGP0YSR5xyrz8qdRgE7YuYrAXRgFwoG1VXO8F2kd2aLYS8mLnR486xrMJ9FhSYqitdVF7C+rlNIgZJzsv2IM9myN7Hiqe81kb9aFcMW/6DiGBbu6iYIsl26lPS2NzqIY/+x/aK4Ujlbiv08wzWUITzz/kDLhAjluwRZwK8AdzNokLuu7VFMD9HelR4sJ7mn2/fYLqeeibzPWObTMcv74kZ6KlcxyOYg1ISB5SOI6lNC5j2tMdLA+j8VIrSkcjzoGgmSM3H3KxnMm1zgyfMVs01dGFiKooTkch2nfMNAVobIdDTqwsA6h3f5kDOoqEtjGfu73pIrzPyo8NBcKnXOgqbOoNQblFI5TuOxyRCr3c5piYlOa3HyywBG5ohw55/5lD6mIenM/xJ/xzfstpZm8zGnWfchsbFUJPDOXul9dXnl6HkR2ywPVgvMmzl+u0JKM1QMVGaua6G8ptpamBUqJyQnk47Z1fDuuzBwIKyILzexgiFAy+gzJgvFxTgwzJVpVsAbTYATbSjj+fJzov4eEVYLCkbp7zf2inpMsyAJMJspn3U6/7H+3ZIeLDkGJDJmSa/HuQUzOLlQ5GZ6CaeBvXC1NPqAwqwyasnkyKG2N905Np3JhxHtZAbEoPzl3nGAGSFUjZD7CKfpSdS7La8hllFza/ktTF07SHiwXNrXpJaswzPzQ+VIfluXwxCWsX6T+xhctCGd63iGxYzkZw6mdwdhlKRMi7CpCaqrQwysq/afxZOdHuJwfPiL3bnzerGB7mymM6JgQI79Tg+W6zWak+g0TmDyyFmRv0eB3mhPvtM2ikiRoRs0NRn4CUYIVLsJov9hPFh5ssKjGbis+G5eWzXekyfKSXIGorTSq+Bk1DZ1FVU1IkKNWUYNKxnMcY7k0aAmBoV3OZczLsjmq2VduNhltRTNAm6qC/IFJ0bkMRzvm+5+QBIIGj6GsYRzcwWPij/dx1F9NnBn9lPWPqcHPqcde/hgwD0JtT2VU9hmJrl+7MipAqHZ+Dce56KO4nn97KhGDPeUeTFqftnQiTP4mPpgaOKqfEduE280pKmRFq+WZCm2J2h2H9WMFmZyv+oqmDDBZhfFwZytGuxdvJmpnEz15jjlRI4HsS9lfeJhMk9xPF+GbGuT28Qe2nFswZLEGtP1EDZvN4QzYn++biCTebrFDKyaGpE47mXx4gVd2UJBaxFWP6DvHgaykjZqRZyjvONZU96lnDZ8zomejgkGxaR8VrvvGZP2G+AwsDx+GM5J783lIxjBr5auHYSqcLgVEXVs00g79jAod4t5fgVVCd3Xb4QaWIl+s3JBaSxbHnUfzVBFxA/31JZ2GcKT6fRI+lWDukYfKxhCfRR2Cyvvk9M5mNnkZJmFLqlaLZ1+OuTmhhhYg9vt5KCsX5nD39hCd9fDVHRqyeIsM5xssTQ4PFhuzPc7d6t8winUqdkJDdJZaUGmmLm2HyHyGg3dYFy3Hdzvvy8iH1lvcvFgeTBK94mBlQrPyw+141hb0YHPR97LOyOfirmvM/4rcWibZYzLT75CSzMUfIoIETrv5oOmU/mRQ5nPWGtbk+nBoqkJXn89ggRTIlqnrq7UWUt/arDdqXdxL9emvei6fzLQDJXD+Z4+PlEV4U/3Mb57MX8J2ISqfVmbVF7QZbxk/Tv8PeykE09wQ4hIqUT46txLB95WLp7RjBUFIdvls3XrexfzGmOJ9Fa5jZR2DlbqLaz5v9vCzjJk22IpWC7M9dLA+m1PIS/9OopTmcrSDXESwh3P6I+U5P4EN/Bl2ESuGhp3cy8LyxOsIrSElaN7i8INrO+29Ada7plMX9yOZQylLJgaaoy3OY+RvcsBaJtVx2wO4rtOF6SkbQj97v7M5zH2tCHH7ZNm30TPn94A4Oe60WyhO/V13h6s8zstr89gG11C+6w55Q1ihfgtHLK62jSuZeSiLrMtC80qcqf3I/ycXnC/IugC9NNOj7pPED8+H1EdCjePmMHxfGkZX4NZjl/V4xKNSgNL9ttu7eu4jqfIzU7Raulz8a6DQfDJxa1J8l0XI8XlTS5gNfvxpJl8L+9ZcxpYLvf06+osTuMTygIdYn58h/FD6IZgMCIk7lN0RnUu5qb0Z8xojkOT1vRg9WUt2+nMDxzGyL7xK9T3iYG1ieav6oKGit8n5B3S1dguf/Ghhj68O3tNYXLfaUmf//4er3PzwC8jQoQXay/zT25hPX2sSbtJ9+FXTB4QVbV4sMIRlW23IdKTci/3cHDAxShIEkFDGIFWeCDNZ5GtWdehCTmdRJdoKjp5lLGYERzKzJDf/JgUFi46W+Eaj8N7x+/AlhMojGpADjxuXpaXuZQ5HBCxfdqa/pHtm8cPLkg9k/uSTXb4Mmgmq7YYk7ts19G+HDQW7O5usV3H85A4V3KH9tyc4otMHvMZw7bwyjVd5wWuYFVVYkn8epNGDTm8Xxk9GdripTIXENIQb6mwqeRMS5Z1PxzFdHYkYYl7WNo0MCVtg7teazxIr8cPjiKTbUFRYewM/cWC08tRWpdJNbn8ui7SKD2QX/iXSRkTcnwwtLJW01V8qi7GcXNOqa0xOJJv+ZAzxL4JvhLJ5B6N+BJMD1YADs5aTN/WLgVDZsh4uLqUxYygM8UilOmRyX0rXXmGa+jcrpGnuJ78VjESDhPAa1zM5bwgDFPTgzV/Vw8+q/xTzOOczgSAwa1FKFF3GFjh6glg389JTR/z8PzDorZ/DlNCN5iGtBO5OYZNFRLmwZIpAa2opDM7OIyZ5OfEJ9DdJwbWdxwR9bftW3Xa5tSzfWvsSTxoCIvei+SN+FDDXHpqfOKwWBiXs4JRHQSfljOU1UA6002txSmInI1G3Y/f4bmRPFjhUjnRPDRu8d5FjGSj0SPp6484ByqfcxJz9ogqHX+6j+1VrVjaaFcuLtKHs50unLf27/Y1e7C1FESIdgZH8FQYyewNPA7Alb9fH3Hcpb7XQv5umxM7Ud55PeFeQjnAuL1yH7pFdOrE0p0FEdveHfssGirH9NsY91oShczBS6eeS3OEcKyuR/eaNAtuBpbpwVIVJ2Fr7PM7B7kRnZsv4p4qnMgXvMX5IdtK9oqJclW1RwNrwwY44QS0GhFfqdWj87BJD5Z8WnJebw7XXiwEzXXP1V0+bVY7bZQy+rfdwxl8ZH0jRZuzyKeMo3a8GefolkVuoJ5Ch7Ye2AslrzlCzv1qG8RiYese9/fo5qH8bVUae+jAwgrh9ZTFTSiKNSHvLVP5jqPIQPSTRKcVaajdzoNR99Hw4fMpvNblbv46eK7LDhpHM51TmcoIluAniN+nWznu0cZpaajuooDreIbKoOlVStHC7hJe4yUup3fubsZmixDolDUjuXv3NQm1c9sg4QmbNXKykKXB3WiU73uL0ZVdNe4J9BBZ8LBrF5wVnoOn6+wsz2A5gyMq6uWcXMR+PMqNnMAXnp7ZPjGwtoeRTTox7d5FlNZkMP2BRTHb0BAx6Sc3nsxT606Iue8pA4p4q1XoCzUSKBF1hcmHcuPQGbzc7QHHddm5PxnU8xTX8VzH+5iad5G1PWqIMIqaupzEbsXWABzNIh5rTKyTxsJ9Wf+kiIGU0JZNdKdtBx9v/TaEYxumMhSR/6Cj0oFdrK7rZh3nZvyF4wWuoIR2LCKUOBSEADTg6tW7SX2CYTjyZTx04GhSObYHK7KNS3mJ54mUO3LrH4quCWOsBTxLcnBoIINbc5+jPbtbLMSk61BGXshNZvrFrJ3m1zyzWoRU0/yBeBr20IE7eBCqqlB2ixV/hZlSVFznsdDhvvtg2jS01SKVIJa3SH4Ho/2iv2otGEoG2xg+qd2cZrVjGHDKgNUECPLJPDEuL3CEqlP1SvMoT/iYm8fMZG6XUJ6vm1uLtIhoY2U4nN+PvnSZ+L/j0Nexx2U3A8sW1RZ/+9BI82mcW/8qB5uySBlmBEVWiifqdZZcZFJOyA1Bw4ffb5gcB5H3ft/CY5jNQVytP8MNPMZXHI9fNazIQLTnFe4J1BQ/2+ns2UPoFVcNmskbPe4FvEnljCaMP84hlfM8olLfzciW30VACcYcOwezgtkcaD3LhjqX52MYvLZgMIdXfco9B81gUZdTrJ/athLvvJZsbuZRpnECm3ekRbYRhn1iYF3Hs67bK+cXUbZKMMqqTdG9Fas+X0edno7fDz+W7M+PewfHPF+/Nns4IUvEXLuwlQ7s4vhf7+e0uTcmeQfw1d4xzNnTl775JYzIWOW6zyTe5Tqe4ciMWYzJtBMYZfTqKL7lQv7N42acOZ4H6xB+AuxB+/3GU5O+/nCc53+Pgawkg3q6swVfupDK0fDxHUdSyDaGsJyT+TRkVR6uZeUGmcj4EWdGaBHKEJTPZfLqZBRbvEIAW3bG78B6lCT0NumCN8htwnuFS7mK513acjlBMEg12TQ0pt4zoWmhfygYLWazPLDtfPIpCxlID+y/l2yqKcipsUJbShxxbKeBtbUs+orxvwV9wECy+opQry49dFFC9BEwO5Hl2YsxLXTMa+AJruetViLMZIcIW8aDZRUkNDPHXcMXUZrv7BMzp8f3GntBI/G/3ciL0yJusKMqQvNePVjO712GKZ3bzuUd5jGWl7mMpQyLvATLwBLHfL3fDbxzyKt8ETyGGnI4kw/o20FY7sfxNZvpxhmjNnm8QYFsBAFqJtFJkKUHK1rEZktlGzbQi9/pwxPcAGAqnZj3HseDJbFoSwe6sJ2NW6Oz2ycFx7sUPFgqXWIYlBGpCfIGdF2Es3E3Gi25Mdz5wiQu4yXe52zLkyW/pwt4w9pn9x4F3QxTZ6UFaa3atA/pAZ0FjOZBbPLRFZvij3//VZqGvHH9uXWu4NRRowwcDZUNDPpzH8ppg8+vmFV88ZbZ9ssdxzyG8VsIO3AyuG/rRby27pCQDh8eE57JYTzFdSKPyW93WOkVeJ2LeZLrLQLRaKuM8PyOlmBalhN6EwE0VFMDTFT9dGAP2+mCjmqWhjsOc8kPi4X19A75+1PEqkAxBzAp2QBCC60Tti7e8k3xGbjl4Bk+oPx1//mcwYd0yvPO5C5Xor0c/GMPrT6ZXKp57OcxntvxCqeBtbmxE49xI6fu542LKlF8VyGuP2SikkadoViGqhorRNjQgPbDT9afb/82pPkXZhgwdiz88kvz2wKOK37FCs/L78irybOtOo8pTKTW1L7ukR5do7F9qwau5yk6+YUB0KLVptgT44ra5uWzHqtOp18H4V0ywgxKgOBv8Wk6vEDyLCUEc9wezQKGILxPlpxTHM+gIFJQ6NjWHp+e4TogdGwIELRCe66XYPaZEW02hlyT7EM+NEsQGqAbW8lOS4wGpD9C/mc2B0Xd51/KtRw5qJgD1r/NLb9EEt7qBtSRyUJTT3Ewy3lq1Lv4AwpZ1ESV7zm4b2hY358W2+OVNJxahKZM3Q08TpZpXEbsHmZgXTBPRBhuWn85f+NJDmIWrXLdPFji//44HixLes7sDHLuPpVPrH30oG5TPIV7DjWN0Swif4hdGPGH58FyMoR3b1fruk9jtaMM1R+9qsKJpcXt+axB5EXdwOPcyT9MPaTkoRkqPtXg5+I+TCkVbbuRj/3EIXxYcTRv19kVIt071NGGUooYiIaPBtKjdhiwX/77JkGfPE8qebB+bhjLNrrwHFfjRyNo+CJCmb8xjJ84JDQW7XLPsRDtmmWLPzOBFQwC4GbjYW7gCWsfL+GWA7pudd03N62BDzmLMb29q5jKMM9h/Ght+2mPuLaWmDh1xzWPKPmWYjozsH3qk+nBzg0KGUglt5Ki2rptsTxYt91G+iSbdiMl4bCGBrYuKEa7/e/x9/UAmQ8JoEsDy6OF9WtJdyYxhdJKMTFMavtN9J1lAp3ZuKYrpNHApYNSYyiGQxrjN/9+SfKNnHMOH+hncvJQYTxI5YKfimzy4w5t4ifuekGQxMXRH184gXOLH6GRNMtr8VWdSI42vPI0uXyozn76BNfzkMMLEQ5pYJ3Wdb65QSY9mx5ENLRwBvZEpXJMYyKcXdzZ3gXGGwzuVkm1nkltU+Sz1DSF5ezPJDN5uzPFdMypYWj/emrIYXh/9/m0Z5ty5jCey3kBcBhYKQ5tXzfnTI5bI8ZyGSJsQ1kEebZEuDexOijy5r4tFwbkbA52tWjkgtGn6DG9xysZzNNMthYqch7LdWgcGrphFVp8+vtAbi25yfqtvMzgWa5mp9ExZP94+K8aWOOYyyBWYKBwyED3iUXexCgWcuWEFZ7iuR+uGsR1ZXcDUEJbFAxUtXlizzLZ8eMNw3l498WAe7jsU07hkvJHeaTiUmvbiD6VvIz4+1Ye5m3OFx0myoeZlxMkgzpe5y/i3NLASmH04aSGD6nAFq1GUSLan8GRFDEwpONKeYf/ED1c+SfJxE50A8uvinvqw3oGsQoMg7lmZd8nppfLS1hgdKdt7M9SWmWGrSLlx5jA4Cd3nWEWZYzsX8X0vSMTbcYznB4szWhZqZwhmYKmwckJ9N2SdlTSmvKGTHrkCkO0sGN0D+Xnc9qRTiMnmmX3qQiHBRt1urGVOzf9JflGoiwl9QQr72RftSprY4QWK6sU+rOaI8o+AuCuvu+xgDEMaLMr6jHNQa986XVKvo1d733PTjqiBPwhbU1ZbFfPdsxPTTXZZV3tim3pjYqHDeX5rGjoy1KGUUI7AL6qNw2sJKRyDubn8E08yk0xmeUtsV/ToXLTlmt4rugwK3rwDucxp8j2zt3Io8xb187btZmQ+pVRIfuzzxeVIFsLK4ZR0T1L5YxnnpVPFkhvGXqYioZMqjRxnzJh/ALeYhlDPR1v0TQ4o1UuFzmsWymPcBPpapOnXDj5fuXc8jG2I0TXDIuBYPHOLrxXY9O+7NwJ1/IsG2v/hwysLmyj0GRujWY9yBX3ZbxEZpbiiZFdxlEB/sGdvM7FzfZg6YaCz2dWXJn+F7+i8axLqW+T4cfvZEVWFCsf4FX+6mjUfWJok9PE7Txohc9aIkQYrijv80U34EIYbc1rcSPpk8ilip5sAKJfc5ZP5HpoqNSREeJZkStMLx99q7R6ljKMIwaHur5fWTqGCfyU0MpMerAs3bG1doiyJeyeSUPsPD0NlekczcqdqdObdGJQxnoCNOL32TdSXi1mkZMHrOb6oT9goFBYEP29vrFFlEFP52ggNaveJlOsdW7loOQaMAzo0cP1Jxn6mtTLpQrLBUXlghKgoVGhC1vJ9kUPJS1dk8Fa+rM6KIo29svazFCWtZiBfETfzZzNe81aJBawi07sRA2I9+62gPH5U7OKu7/XG4AQBvc6qWp6JJv84Wmz6MFG2ubF9pz34XcUDPY6RCfkGOW8z52msDzElsqRXqaZVSNZWtKVUsMulKhvsJ/RE/yNZVvzSATzGRfzdyOo8TXHsL0yN6pUTriB9Q3H8snmkcQrI1y3I5vPOMka/6WBpWsGW7eG5YU2A0FNEfQWgKKK+fM6nuJkprruP47Qb1R+Rs5FXGV55D0N7FTGTTxGW18Fmb74oVq56JLv+Xmuss+pixxYVdGjVhE6x88/fIhQwaCeDNbSl7qgu0tZDpJtKHNoEca+bE1XLB6seYxnDgc0OwdLM1RUlZAHH1CCXM1z5FNi8TuBUFyXnQsgqKtU0DqizarKKBckc2MkF4uVS5KiwdswIgwsRYmeDBxQ7FVtuk9IAMWsgHG07TSwnM+/b7YwHk/nY7KoC0m+XIhLvlAUbK/IEXpwYS93bWk7ZjGBj+Z5l565YcjXAGx04W1rieTzbrm2vFIQPzM4kg9Wxi7gSBbHt5olNAQdNyLzF/q1L/N0gzJPq7Np+KfCljDMSi+1Mcnkak2DraF9cQAij01XmymzAAAgAElEQVSOHQVZ8fnUAJaVi2rZVplN5FHO0rp+UfeVfVOGjtA0pnIyc3f0SOTqvcMkRkxUF9QNbywUfFdu7y9miDgBtPeVciYfJCiVo4SMmwABpYnOFMf1Qq43q5PrHCmXMxELguOHbnM95kYei9jWKkOESB8u+rO4JkPB5ws9d4dsO49IwUi5ooHWqHEcX/NdUZeo81a4gQXwbfFgNu9I41i+omhDumvb05Z14WQ+I4ifdzmHQIYwJBsboVs3+HszI/XPcjUjWGzyYIkLP63/Su7Ne4JS8qPm5smCLglpWDk9WK7s9KZF+FPvi3ls/H9cdgiFRd8ThfJBGvkyMd86jYuB9Yf3YH3EmfzMIfRnLdOXu1M5ZKUFeYVLeJlLmb2hsydDKZwHaw0DrES7ZKEZPnw+I7Sow3y5JbTjEl6198UfshKb/ltHLuWViDYboswpdbUGvzGMapN8TXqNjkz3rrUUE7qOho8j+C5k84iue60VxuW8QB9+ZzxzWNR3orVP6xyNUSyK4Ldy4hcOtIyULwN2KFFOSvdzJ/f1exewk97dkiy9TOBvLh3GMXwTYSBYtE8JDH7tA9FLy1vEMeE0dqQ+WQslSbdRK+jK1pCEZpsHy6C20c8iRlLjnoMKwJg8oR+5iZ5AaoxO/VMRbgzUJl7W77yIyTwJiGTftzkPgP26VrGEYfRv40LU6AL57BVDp5R8avToIr5yJSwNiM93jOZUpvLumpFJ3UY8SILX5vSPU8yEXp9fZTxzaJctrJEDmW3ts22P+8ScKCYuv50POYsZHMlKvBGYOskprW2GTyzSPHY2t91yM9w9G25e+DF9SunNOjpkVprnVwnnRG6bYX8kKronctn1S6v5+FlRNJGNkLkJl3aSkIVEPr+Civt8F66HCMJ5VVPv4xuOpazSvWpM5t29zsWcw3tWDpZU0FrlXiDvGVfzHIsZZTLgi5cxtst2zs76nA84K0QazYlwQ9yaYh0Gltscsbs8TTDs+3yePg753Q7uWcM0jgs9p24wvmATk1p9EalFGJSh4/8hD5YTQd39UjICGhvpybcczdrdeTw9/E1e2y9y5eGEsEJDH/aA3GIGZEf3usSDbij4VEIs28Y6jZkcwgoGsZzQiirnQBGNB8uNmRZg7QY//+F0i902oGqcw7tc0ypFRICaRpBAhNjpIX2LeYA7ADiPtzmQX8Tg5uy4msYmerCE4VGbv8ZBy9FWtb000lDsylaU3NASVzdvlRcPVnVjgL2054tFnUK2WylY770XccxlvGiFMEMQwz/eEobP3M32osKLAGxz8E3FePZnOTXVkQZWUUkHnlh6OKNZxMr10ck1w7+fVDwTNdhIDzZyhZl0myiMoEZf1nIsX3Mc0+jJRkaxGBAizz/wJ5aVeSMalbejak1xtQhlV5ETw3NbRL5GSxGNPjZzJFOY1Kz25biVkQFzOJCjB4v0jHEO2Sg3z0gy2NVoh80Gs9LTMW7j9spgf2ZzMOUV3q7L9ftxmQnzKWE3HSL3NQs/rOiBoeLzGRyAXbzgHLe9erDGjQpyxrVijPocURUYLX3CSsPwCw+pG/nwOyOf5Bzetf7uyQZvTO5mvzUQFBD5eTqn8h9ys8QPZ56eGneclBgCrNyTqEn9hOZCgf0dOQ0st/ngk4VdRf/1+2MOSP3Myk3ruZjv2YmAT+fU3ku5u8OLgpfceT+mB+uUPstZyCje5HxG946vsbxPDKzvcafJd66cotE0oGk8aE76qk+hc3YFXdJjV1ppWuhKqCCrggcHT+HxAZFeJK+4u80znNp/ZYgnrGSPzmHM5FYeZi7jQ5I5nTZV1NymKB9BeEdqlRXkXc5lVHp0cdBEILW0IlZwikI2NRzLV+RTioYvwsDSgzpNBKgmh8r/hHrAJAoQ+VCfcRK91E32sU0a7dgj+F/CPga31cnIXvE7sMybqqwLDTFbRKMlkW08yO3M4uCI7Z9vDq1kMVAYYU7WvfKaL1geji/W2iEo3TSwWopHaWW9oMtw9jk52E5b25ct1cJ1H6tcu31aBT0QFWiH8QMHFm5q9nUt3lnIJnoygNVJHa81aqyjL3M4gK84ni84iWOl8LqmcT9/Z9au6KE+J+SzL97tZxtdWVg9IPq+YR4sS6y7hTyQ8l1tqWxNxR2PJNWGNBqsPCvzG3yMmzgfsXgLpibHHS3KgjnmMS4hwk2aMI5rqmMc6NQatCn1rW1LNkWGpU7nYy7m9ci2TAkVw2lgqYI/S6KqRuXPfMr7nCX29fDOzw/aKhWyz9Th7iGVxVP+gEqvjGIKMl1EuE1BcoDxzCGLWlTVDvFGnVvMx/M7fflc+TN9uzfyH06nS554wOrHH7oe5xUv81ee4RqCuoLffJfry/KZXRfbs7uOUL3QwgyRTOccD6OF9XxoXL31Fp5YenjE7xLScWD1D12P8Jp17mDKwqlqZA6W+b23z6ljFIs5n7fp3i6Gu9/EPjGwKmjlal06uS+i8e/U1dgfj2epHN2uHCorg993tY7KiOsVE7M+44Du20XCnvngZUXdNE5Ax8cyhlq5WE4DT3b6CeFx5igerAi2dE2jmE7sNVKTAC0/4F8ZEbK9uikdHxpfcTy1ZLGG/sxiAldsv8PaZ9NmhRe4kk305LDT3RmyFQz8NFFNDi9rdnVYRkBjDx2YyilcsuDSkGN0zeAvjjArQM/28Tuw/ObCPz4rSdKli+dTRqGDf0vi662OZFyzr3zFcZSQz4X7/xr3WhKFNA4BJprl1i0VIvymSlRohhhYpgfLOUnE8hr2yijmLu4D4E7+wdE91zb7uhQzEcxQkyM6lKv9e7nH2vaNqfG2ZUca5bShpNEbIWrfbBHCSVdEvKRKiy5Oaz87AemBT3U+jn0+8f9N9GTsg5G8SF7whek58QVCE6Ev4A3e4gIAGoOpmRK0eFyFLjCMSA+WnORi9UunPqY1xDvG+uUuSeiSNyscXy7owFr6U94k3r1uqPh8cCFvMI+xACzd1pbPOJnBrPBMDpxPKR0QFaZyYp/Bka772h4shQ/63819wz5x2UljKEsBOJlP0RGeNunBikpibW7fQwfO1t+1aUbqzXlr3Zr4NxMDl/Ey1/EMBWmlFGaK6MW/l43kvNJnrH28jHEvDhFE0PO7noHPZMx3ZXI3eaum7D6cG+afGfG7hHzm8l2t3pDGSeEi5IZBZV2AMiMvwsCSpMW+gIqCIZwpHl78PjGwdlLgejG7sEseo4XRdjmqnlWfwodbxvHq9ugimQBn9ljILZ3fBiAvD3Jy8GSYxYQplTNx4DKeaCs0pNw4oW7gcZ7geu7uZleoRK/Oi3Iq0/C6mX+K/YIax/ANt5ff5H5AglC0ILfzAK84KxqBN+cPoJcZOruEV9lBJwrZxg81YyOuDeBX3Fclz3MlQQLM5FA+Dp7suDFxbBltKGsMLVU2dIO/cz+Z1EbsHwvSfR6+q3y25zrc6BKX84KrPmbQbOvA3N9A16kjgzaUkU9Zi1g+8poHpa1lCpPozboWE3uWhSHO9yc9mIbh8PjFOP1nO8dysVl5lSpKie+3Cu/SNCW2/FU0RFukAGwoFh6CsoY4ZfEmCjNL8REkJyCSI2P5EuVg3zuwGbA9Ni1kHxMMQmez4noN0T1rXqD6FDqznffmiVw6aVwBZOY0kyrehJaEJ/bdsc/w/cibQ7bdmSHSQWJ5Vp10OVYSs2N/59jwApfb212mv5o6uc00PBDFTQ9zq0VKKfOffGiePVjOsOMFprewAHciW7lw9wXUqBq6f199Dg2k05Gd3MvdFDEQVXF4sKLNLY5n4SdoTU6yP3+yJ9Kznwxe2u9pXhwlFszhxorbtbVlb+gGc6cCZRfTOF5scukD0oNVRmw5rP0o4juOIDdbtFFSptJIWL6hrnPL7BM5cuPLXDp6CT/m2fnDfTrV8A6TKA+KxdoKhrBtb/R0Col9YmDdxkMhybUSzmqtaBpoTiPG54fPto/i3V3RxaMBDu2wirM7/BCy7colf+WsZbcncNWhmF07go0V+Qwv2MGJWYLnKRhGOHcBb/Awt3E9T/Gntkut7dJ4HMlierCRF7kMiLHKMJ/V+bwFwMZNglTu+7oDk75+JwI+nQe4kxEIr0xhmkgCdn4IKjrHM41zmBJStelFi3CFmY/2DucK76V1sE2YGn7nelCnO1uYiJ0ztb0kfge2cq3CPFgBNXqs4yUutwY5J2w2boX6Go0s6uz8lBYoIwyPZqjoLSb2LJ+O8zldNGYlndmOYdg5D7E8BU6vxE4KKK1JIiH67rvh6aetP2Vo8i7trsTbIjbxrUU06nGU03RJJCn6TqzKtZ7tq/kbjzM1cxIoClq1Kc3UgiFCqX2XLAYhWNr9AYUddKamIdKYMnypkUzRDJVLXAp7Yh+kofh97H74dYpNOoWhqkiLiPX5OT1YchI2gpFGFwg5s+e5gle4VCz8w9uyqkPF3/PbncCdh8ziPu6mmEKu5DnGF24BxPf6Q+AYTh+2Lu6tfc2x7KU9ANsQlc1ZuJOByiR3f0CJGnmZX9af3xjGLgqoNXm1VB9xPVi643PxobNkTRYKBktWi8VIMFyyJlmESeUYhoJihjTdri1CWskiwtIs3jC3PiB4q+JzS4xjHsvY3wpbymtwRpU2bvWj6YIKqkNuHfv5bA99+1YNTGIKm6rsKNJPq9rHPe8+ChG2ibnShOgeLKdhpvpUkQMV74Smt8mJsqZs9jRGUiV4xZmlL/DW8uHCEjTfdPjg/hYX8I3JEeS0GOU/FzGKjfRis6nVF0/s2Rcu+eGRMDEudDt/5CzeZ8UR15vtCwbmbKpZSz8MlAhjyKsmGEAdWezUbS9lRZnOofzIHA6ImIhUxWAxIziLD6xtM1fG78DR+EQfHu3iVndgh4sAuTSw+mVstlbFSxiBgsFdP8c26pOBJbdlqDTh5xb+yQm9mlnGEwWGm4fKoX8o56BY7/fbEjukfDYf8PD8wxK/kPvug8l2BWqTGZJy8yZ4QSyDXz5frybrQflFTOYpqmvEtbRPc8l9MTGwsILHuZHcsi1UkWNRk7SUgazpUGqu0kexMKk25OIpv7XpuXR5dIl837Gg6aqniS/0IDEpt28TpJMSGk6LdV3pAZ0dFLCNQnp1EeFdZ79w9vlcqumCoG1w63My161/njh/W0qsBHAQeVPSoPNdeD7jfQvo3CpWgpjALCZY/+6HmLhLcE/5yE4Pcg93069bPeevvYPbfj0j8joNJeT5dmQnl49YEDfJ/fCednGPT9EscejWGQ2k0cChbbyRwsZFuIEF/NsU2na7tqYw5v/Llgl+qjtKb+A0PuFYvqKwQ2TlpK4bnvqZlH2z9EbN/nEtduiysdFRyRoe8TI7hup3VDX+kWga4n24ndu6cxY4PxRJhhkvEbiotCNLa0OT5hSaV+EjaBpg1d4OTK8VblS3eypiP77haH6p2t/a1ra1WJHIj2wGR3AE39G5o3vHkEalZBS3GKlTRDSqNemspS+1ZPEBZ3PtCpEPJd3LtWTjQ2MN/VlP77Bkv8QGYNWRi9ZQq/ETh1JJa+sdfs+fWMBocrJ0LuQNjuZba38v3oBDCsXqMfxdBNQoH12MpXBQUzmcGbza/b6QVTFAfTBFKzsHZA5WuZ5LGk20poIJXVyqG1MAy4PlNOqLiqwQh2WAxRg06nWxyryS58iiJilvze08wDNcY/3dpIkhKNm+HcvAkompXhUQKhozeYRb2LRTeE5v6Rkj4dfsR9sopBVVLGQMndnO+b1bRionGFSoRhDfjmFBcm3g50Q+57Dh5ahoEZ/CX3iVdq0T09WLhva+UsFdmAAeWn0Kj2w8g6rGdNYbPTEMmN4Un8ldMXQK2EUhxVblmmq45GUBz3CNVbHm1ufkOHLNIDMCEiZAraLbWrHnneM5tzfdoX8oDbsQJQ0HcjOD3M199OvRyKb6ArbVRibpa7oawkg/ikX0altJ9y4apbTh4CHutCcHdNnCdxxBf1bjR7OJ34PmYsuruzcO/lJ0I3cuEzlRoiJPIUATGdS5zpv1YQn/G+vEwvz5akG58jXHhVAkSGjB2KLsEjXk8DTXUVNlOkfMeUwauyDGRk1XUFWDOVu78mitTUK6u8THVE62xkD4g9E0uH0gg1hBHmXoKAzv674KkJ25P6s5fFiJyYMVe8R8YPlJXLfh2pBtXhjgY0FHEM69t2ool5aIHCy3jvI3nuRYvuHBzedY24b1reFJJuOniSlMZCFjWM2AqFIcndqIj/Ea/gWQsGhtPJSWGPRnraX/VBEUCZ3OicivCGPoP5weYtCGGx5u6IjNqu4cxOz70K13+Cd+ZDSLwDCs0OI/EXkYXlbTp/RaShtKSfOFXZeusx+rIhLnY+VyCIJakVsUPnF7Ms7nz4dx4zyHEzVd5MJ81up8gBAx0lSjq1+8k/SA3f5/XilhG13Rdcj1C06kTvnRCT/l93MbD9GVrUlVzD3E7VznWDUGTSMzYW+HiViecd0kr42WfhAO2VebGs2EViV62zU1cDGvMd5koO7HGqZyChM6Ni9JOBq65wgpozaUcgcPJNXGWvqLRHefzzV36FX+Su/O3sXRY+GbLpdYNAgBvOkbzirZj7nlA/hocU/6sB5DN3i2UaZTxPgunPQqhv3uZM6aM6/x79xv5Zy5kaDKMUf2mduqbuebdX2s31/jEn7YJHLXfAGV57XLWLwlvqf9Ul5mMCLcGS5sHAFZymmKTLuNPeE5bjoiX8vnV2hDOQFflOelaRzB90zkPeHBkh4vTVQlGikyCdbUdmFrnZAQktRG5/AedWSFjEHRYOWMOq/HZWwc0Xknl6Z7oy/aRE+qqkNDqMuwHSH6qiIR/FJ0Zm/uwkN111m/LVmTxalMpdSRz/mH8mC5TWzjmUs/1qIQPURYUyY+zge4g7xWOqoSP5HUySIr4UXDMGab+PD5lJA8pba5jdzCw677h5xfUdDwESRgiXNupzDqZNq3UzVPc62V8C0nezXGgJ8IwiclGZd2GlhO9vZEPVgFDgPLOYhZbLi4KJ87nsUahDaaF4NY0TVKacu5Y38P2f7s8kM5ghmh0kTEnpCNXXtEnouuR+zniZ/qjjuEkVXnbZK6qO9sXuUSeujCa7WSQWwsd2c6bi4Gp6+lF+tplW1PRhvMHMgT+xTx+Kj3qCSXfoXRKzetPC3UlDFYt/aJhVV71bsotxPZ6dHzkmRfPaf/Yk9trawUlACWFmGMefDLxQX8m4vZhjjmCl5gDAtbLAnrqiE/cxkvUkY+9cTPTYxAsaNq1ifoV2SfPiRtjs2plKrrN8PPY5kXmUwchg8+gO3bzbCialgV5YZuMFRdQS/W07VjdCOtpkrnKKYznjns2GVXSNrhRXvfSoeixun+TyPakgLscvH7WsMkft0RyrFXVieev+pXua3xHn78Pb5ahI4dMpWs89HQUKezgkHUNgVQFcM1YhNepfk1x7FwZ9e4Ujlby3NZxhCC+PE7DKytu9KoI4vZ5UlKVoVfn65aHieZg3U5L3AX97r2sd6E5rHJPTTD/gj37I18Dkf23sBD2f/wfF2WVI45NjiLoG67RbdsB0VRXOc9vyOS+Yf3YKkIRvFaMqNO3FdfK26yI7ssfgpPUjlhfCrhzKyJQjPLdVXVPn9BfiMPcxvtiWSKDpGdUdWIeL+Byt6SKNdjDg7yBYeXhDcX4c9a2rbOlX6IgeV4btnpwQi6iYj2HSs05zVLA6szO6z8lsk8GaEhJqtGvHTg0pp09tAu4qNdXlrIs1zLFCZCkx32iBVSupe7ATh5w5MRBpYnfiqLCtzbmxrddgPH8o11TX/nHzy1ZEKco5LDyVnf8Q/uDHlOX5lMxmMLNpOuNpFLdcwJVj6DJQyngfSUVMwVZokwUu+05EiAM9Oie76kY2O/tt6Y3L/aLapiRxXu4DQ+toS+Xds2Pw/pnRnKUhYwmuUl7ooUzYZpsAC8y6TEj7/dLvCZU9QmhF5Az8iG/HzKaR1RuJM0wsawWDj7bDhhQoXIK1IN6/PRgzpZ1DKGBWSmRb+uulqD7ziKeYyntFwMYsEGjUOZyWSe5IRBG12Pey7jxohtmX7xYm+cdxpgp4Y48eLyg7iAN8jJVYSh6uFDsDgFPWDDZh9DWMGS9a2iKpe45fpNX9+Hskofl/ISKza4U4w8u2AMo1hEATu5vfXzloFVXydOUqc1j8n/Lu4FJH+YaPPgntuYnPkCKxnEJnq4DuwX83rIPGrT7Nj3We4W9TRDuBl4W9RKO8QtOvI5f7aS3MOVX+ScGQjEroYMx77LwXLxHLzHRBYzimxq+XqRu5tVls2+wl9ZvyvHm1SOk0XWRHM9WDoqquXBkhvFPa2nN/+PufMOk6LK/v6nqntyZsgMOWcFJClRUEHWiGDOAXRdBRXD4qJrzmldxZxFUcwBMyKSc855yAM9eaan6r5/3MpV3dOg7u89zzPQXX3r5nDuCd8zmumu9E4J1tw1OUziMV+egRMGeYM5SF3LcNY8gPtnLPsDLbDJVPONMQzKzb5qWb+MdKQE47JMGddpBF+zpLHtQt+uaYWF1D6KLwLzX0tH6/P0XFuCZLbj1dQbeK3b0wA8Y4TccTI++wzvnkSkRpPmnsXf+MK3aE2D9U85yw2UGkfF2Y2VNGUnhdX1/RKsBCZPpZbE7/SrPaFVGZ0fOJnHq2ybpL8KR+n45NWM4Bt7Y9F1K1YbQkaR30sDqipjN/TEbKniOIvP2EqrP0WbGW0r50qoid+jKyHSNDIoJQd7MTVDQif0abWXLxhFZkpidkWWHVqNxjo6sKsqturHxBMyL04/MZSRfM2jq08/pmbUSg4Gy7yAHA1VOWwIq7QwzZSdZKZI5nB6h7u5seFH5HGEOSul129VFcyI7ycSl0bvfY5XuIYF9GFfEGK6hw5vL7b2bSdYpo5SKySIc+8w52RpieBdLuZE5tAkJ9j8JEgFfEHPDfRkEWXV0tZGQyXIsfJUZpKTpxoqvFqbx4eMYakHd/ASw0vcS5YENaxIjU1A/kE4Y2pIobxS5WWuZef+YEZJ1xWiJPMi47gu9wOrr80yw7FsVxOke7kHgWLEcJTPBrfeyaTUZ/mNAbzNpZSXBahmUTlAfdoaNlEWkjshxjLNqLu/vOLyMPupL8OlxSBn/5lnyrAue/mUM13p2rCRnnmb6Z+7xlBrBkmwFF9e8ej/VIJV4nDhj4X/c23oNUB66G3am8mtXb/juebxQ+XIiNju/OqmllAvfIzxzjBVhMIVKqeyQrCZVpSR4Qu74JRgxQo/EcvG6Icldfg3U6gxPCsykqMMZBZ31HvtmOsfVO7VoTcYyo9WXYd22sv7yLiDf897j2F8TxYlrnA3aBprjNhigUjIuD0zuiTZNimWcWgI364RNPwJ3Qx1hfn05bNlzT3P5f/TGQO33mpJlZLDOufzvhtvy6COrGEq4+StO0Zsw3g0YeP1nMjvLnDceLRoX1P+zb94Ure96v4qN/8fy/uRxxF27zHwmhxu7JsP1+HZdafQiL38sjy2inJojq1qCxM9JolwMm4br7tHLaMRhZzVyQFaGonA7be7bWtiUGW5ThmZXMLbDOZnQAIvAjTKLiNKEquLGsXLwiKz6/WoVqv0xQQe1IxL0P3czSHq/mU4WLfNOYsXuB6A+fQ96venLDvb+hwKK2xMP47LekmP1Qahg9RLLQFsU4577oFzz4XNmz0Z/fe/MHVqreUtrrKDljfEBjP86CNYGOAE2S9lqaUidEqwdooC3uViDhyKfVQ5L0Nm/bUHJYZgvDiGNUqS/6Fu2iIZX5FI7l4thYIwNCoioYO2yOExuJBedh5B7dFsBkuJoSL8se04zscdBswF0xDbBAswzD5CIdLTBL2ZT1pYXkImtvqs1rYkQk4JltcjL0hK+h7SZnkj7Yz6SdJRLXiSIDOjR2f3o0/R17Rlo8WceUnowhIcmH2bHNKohzsiTAG7uK3tZ9zX7m0UNVhFOKD9fgbzM91ZRs/mHuyuAPofhcoZQnqqv3OassP6LGIwGw10G4xNDat0zN9Pr/T4ruyuwTXoiRM+YEaHY8fBmqQ+wQktDloeEQDL16XQhs1czhvM4UQriCd4QuXEsC+LGS/Ko8Lr0LSMWQymTdruY66/K3/Tpks1RNdm9RSFTErpygqSk4RkKr2G18YG1IC9nI3fhgEk3pdJGaoturXcm0P4doAgCefxBfFDIoHtiberyC0Sd4rQa577r/VZRecRbucXBvvyWmdI3nQUGuTXIFCoayzCZ5YN4q7b4ktCNpY3ke8n6Or+zNrhLvdtSFAVeQy0oboFEAzE+OLSPiw81Mr1exClK/ZYnh6eyfF1d8RMG4sW05P59JYn9zffkBaOUkgTxvVeaid66CF49FH4/fda8yvcK7ewPsy3JHLPIo1TFU1jAk/x0cbuMd93kskwLt+Vzyq6src6NniheVBlUezJI6GijpqKKmOjyidCeyps26NQkuo+9Az8KbCX5QknyP/zvPz2DTfAuHHURrFgN847D3r3hsLt9loKUcOg1PmGitAd7mWbkBenA4di43M515ulWnpDGj6/zhWs3O0fx2t4idYlS33PTdWmuX9ohFBDCpfzhivZXhqiK9JZIBHzzH9gY7+ZqkIVHUpKAtpj/B5SyAhVkqr67c+yKbZwtIbzHbkc9vVdEJnju40WrKrpQIuCGubTl84NpQ1kLMerROkNLuMrRlomNQCHKtLZGG3paJ//cr3WExA81YimoBEiyYiOEgsHS0XwGJMkcxawAFWhSU0Gjn4JiEXYzURnD4X8SO5GnZvkV/IzQ1nG8RxX8P8Jg9WLJYED51yEsTjuct026Ew8VI7fyD0WIm6idA/30K/tQZctl9npMzkNjTClZFmItM72mpPeDKNjUqKxCNE0NNTavU8SJJOZ2a02pYYw9dMNxlBVGcrPrKA7FaFM9tKQmZzKnQrLf+AAACAASURBVEdsdOW5y9O5m/vZR0O6sTwoe9fN7K1KO3xBu+ZVVJDKlzWnceOa8a53hC44h49dz3o0q30C2+Cgwc9Bjp0ZbgFdpxk7pUFyDBJCsU7QrxnJTgMYcM3b8Y2lrQWZoO7M3MQVdE5idmA7/ix6vvhimf/0jwAPThCOG2OcqrdJ2cmbSI/HxzPu4Yp2tTNAXrqaV3iam6FLFxg50nGldjTciqRcO7NptuMSR6w4kzbvyWA7LRIO21I/WUpqzfVRHscexVyjmbjVT38VgxzPiS4RcnavGlZdeH5PFY7lk8ODZTpjT9Jmy7FVDx+b80Ftff7RWNukQkfiG5oXY6cEywqVE9db1A8qap4tX/K3mEboQRLKDxa2YgF9rHHUCBEKK9zM0/zqiF86gacpqwwlbIPVnvWWvZ65P77BFTB4sC+tZnq/hhQ+7fUAb/V8xpcGTbOcia7gdduExcC10mNd3o1uLCOT8wufsAxvLezFP8hgXcEbjOIrVKFZ3oKvLOxOv7IfrDReSVTQnjPzcG+mXrOIuUmDOKuLFKMGhsrRJZ6XlXeMYN9ePLUlm7K5geddyWZwjsGxBcUiNMYkKcQ/uV9KIRMY+P+ZijCoMk701ljMxsvCjmWnhhR+3dOWjw4NiVvU6Pq/ck5TD1bMnxEqR1UZ2mYHk9OfBII96s7lYy7iHS5sbuPhmBtGY0/8u9okWBN40nggQ+VcsD3YY/FoKTO1hkt5k8nV/6IxhTzZXx66b89phYKgkhQu3PUIa+lEPod4o8wGuqtyaHhWOlxcnWQCygE8UWrHHFR0jVSq2Cqas66sqesdoQsex2N0mgCjkgiD9QCTrWDKFaUa/+Je1jjsxLwkHGWfwCIK2E0uhznxyJdx63J+/R9R0MlISxymAaAJu5nNQI5nyV/GYJmbhZj6kizbZbeiJISD9djuC7nMsBsJhY9tPc2nL+9zIVRKKJLZv2iM57/usT4KZ4F4B++cjdKuS0twm2uYfJiWbLGC68ZDcjd5wGyfBOuvYbBqNLVW55J45KxXKEnl5LLPeW+J9NZ9+9AIfj4iIVvMA0hfKi9PoSK3FHk00332pkGkiRC5cXCwVEfMu7P4lIKkfXze5hYe6/sxLeqXcyHvoiqCycoDRv3jlOXYh836v8LV1jPnu4859pggBqswkm6/Iwwpfghmciq3Ik1T+mEwn2H1qELlmOVd7YCOmbfEr6a0oCLCakycrSl7x9OFVdRjPw9yF8XkSJxIywMzuB5Oyb6KsGMRGvvBx3v6196YBGhxg9N5dKi0i/I6mHmb4/3eFQl2+tmnOn2YT8Mmcu8O2ps0TXGt00DtgabRlZV8wBjq5cmL9sbCDF+ot1005ax5d3Dekjs5s+sWZiRfYP3WraCIh7md/RWZPMg/mcp1HCiu3SHAt/O8/vrrKIrCp59K9c+DDz5I+/btUVXVena09Aw3BtqlHHDYLcU6SzOw3cbVsMr7m07gwX1Xxi3vigZfc0kr9+36oRUjuXLTsakIhSaBOYurU+nXvJAbU2UICO/m/g+eYSrjeIdLGNXUHyrnOKSRuhkPK6ae3Ngw7uEeEILZSzP5geFsq/5zPJQa1InyJpfTMbxBLnrjFmOBziEn7fm8z2W86ZI0JgLT4AxiWiMcon0zVI6i+DYlXRO0ZJvLruBQiSd8QgCZTIpv0caoZnmZ4D7+xS08ETNPXSjs2i1R7EfwtSyHEKFavIA03Y0WnHDdscE2jwVb6mjILMt16xcO1UqcCrikEqHQUYPOOulhbqczq1g9bQUvMp7n5/eyfquMhthJgYWRFY/iAo2agrAE66QLI1SOFTkhdtpWdY4wlml8iTuG4l8WKkf/Y6FyHj/OlvCFwgqLtOMpPCIxfTShEjYkF+YhtuhgCwAOF7ul5lGSqKoFdgEkUzvRvCAG0O4aw6lB15nDiSyt7kR99SB1Mqro176Id7mYtBSdMxTpSBM32LPTBkuXk3myAyvMuTdcxatcz/O8zLWB3ugmpIMuAE1jPn0Y3XsHN/M0C+jDw9zO9UiTg1ByiJcyb+HsjrVjn33PcMum1nmwP8WEmO2JF4twWmQES+hBlCQLP1AN2Z7gseahU3gUUnS2FybRjO3M3yRtxLZX1I7plQiJGj+Su/WbR4LlNLWcwdkWIxvVw1J9bUrlAuaAiVtlfQ+4cJUW65ZwIzNNc5XZBhvepxGFVGpJ6IpKi7qlnKp+b/3WqdFhbudRS938KlczfZGt9oxFrhm2bds2Xn75Zfr2tY0ohw0bxjfffMPAgcfuPv4v7qcsNrwOEHtCpDoQcENhxZhvtWyZHvRdgG2ldVlZ3jqR6vqzq9ZozwZmLG3pulF4B/w5/sF6w0jPiXlgMlgZlLmDXsYKlWNscuZhbVz2jzmciI9M2H9FWAB1znq2YwNVIsURKsdx+6gl5JGXaghBcTG8+SZbd4S4hLfYoTXxmXeGFJ3NtOIOB67YtEXx8WLA3jC88+d1w0vRS2b9v8UTMNwhmqsTOmJ5unzLCNqygRKyKRTxjaUHZi/jBcYnriI06mz274W8x8mN1ib07tGSN1SOcxx1YW+AsWwhAZaWtbM+n3joM66fcwxwAQbdycOsoTNTjbicB8psG6PZu1vRjJ1s31c73lM8Js/8LVGmZ2T+Ai7jTcqNGH3JodgMzfD2O5jGBeygmev5X6ciVK150tIIyH401CDFdvBJTlFQFVu1pQnVAqY0p+5ew2arKurecz7nTL7kb7XXVwSbM5ht+LBMQoTYRuWqvW87uATFEMXEk6w2qVfN7/TjVwbQsUVFXAeVPI7QiTVGXQLqbRy8DVIjoGn0YCn18mos/Kw9NLLw49SkEGemfUenerXbis7gXOuz01a3ueHx6qR6OdVczcvUydW5Z/0F3LPufF8azcDVOoJtJHdqp11xmRGAIY3WW+YSqiLQdIWdNKNtfhEN2UPX7KO3qwwiPeplsBQ+4wyrbrrD98B5SapXkGpJyX8o6sFD+iTUsMo8+tCmoBIvyViEHgbbW5caHR1pL2dOBnP/82pNZh7sKc2LvIytMTGcZ3AsxzwnWal1Xefqq6/mueeeIyXFvqH07t2bVq1aBb58NFTbwVwvKxjHwhmjSA2rCcEtFJbnciDqDkPwR2AarBtFWGFvWRZLovLGEOTkFCGHFXRla7kdgy89TZb8vuEpcTuPMJKvrLhZXjIxdtbSUcL3m/rfPxFotJw0hKIyg3N5aOlpMn9jNuyiKaoqOEA9SshyHRoJOHa5SAEWXfw04y8vZ/eaCO9wCRGRZR34L3Id8+hDkwY1DOFnl148Ee+cvrny9uiVvGQotpfgtdheTzElHg8+aH38uclFrg1qEzLs0qvRS+LWpVjL4BtGUFqSqARLdvgeGtOAvQxTf2ZMq0UJvXu0ZLoce7HVQKoTLLvCOFOsRJNM0EBmkaUeW6gck0zX62Ucb9TBzmzmNsnI7S2qXYIZb18JMu+KR3XCxdzN/SzeIyXFL/R4JXZiI3Pn5aMDazmvydHbpSVCuoCfkWFj+jD/6DMQgsbs5h6m0LVjjaHaMg4boZKRVM2pfEt+ZpWZHIjtoFNrfWuRG5q/6lGNvTSiRM/g4b2X8+m249CFQjVJCE3nNyED3MeblylhjX7MYwC/kZ6iBdj42BPgFa5iPn2MOgZIsHTI5yCPHDfNLtRxWf6MM5nCv4EAZ4FESAiXaUxQHVo3LONlrqVxI8GS4tYsjvgFA5pQeYQ7rO8n8hvtG5eQkwPL6cbJXYOx385vtcAy+FYV3WLI/uxQOZdFnuW91dK5RDEcw0w7KKHphEJwoRHsxClND905yZXPXTzEprJG9GFBoOmF5kEMCNoPLPUn51JsaPTNvcHUKoEdn7YsmsS6fXm8UXOx9dv+w0ksoqdL6qkncBZa+psnn3ySE088kZ49Y4Pr1UZVVVVUOSQBxcW2fUJJSSmpxe4baSNK2UNjdtGEvOYPuNKbZELZ53KYgvpF6LqGEEpgWpPOW3cvrYpKeN6RRtfljS3ee7Go4lA50JCoFuW1Be14tPRzdhQXU17qd/XvY8QJu3LlTzxllNWi4UEm8gQfMJbfOJFicignHT0a8dVnxQqVzxdJ1WlvFnKo6BDlZZL5VNCPqf5eWr1Moz/l1ItKI/KtkRyKi4upjtoMX0jR+ImT+YmTqUORVa63zcH1seE3FARrdqXzIuP5W+RHAJIUDU2X716HtAkqKS5mJ93YSTNO5DfmcBJV1TW1tndC8w+4f83ZVHvSphvzsAeLmco4pjKO4uIIxZESoJGv7km7bfR5XdMoLfZj59Q273ZW5PEJ53Do0Bb0/NrVKDWaoDOruJw3uI3H0UNhqquqqPwTxthLuUi7olQqKC4uJnKkGIzbb42mEzIMcHNTD8dso8loP88NXKW+g6Ydy3yUc6MxhXRgreW5WV2jWXnVGJtkRWVlrfmXFscWjVdXSqeSaE1i9dRrZB9UVpnSnGjM95LKynmXq6Qa36DXuJJe9etSXHxN4Dt/hPJCduDpO3iY4uKjw8L6fEtvCmnCPdzLLRVLUdGpqpZ9rgmF/OQIb3AW5U2mU1xczPAGS3h3a38qKss9fSDHr7b+PJTciH9WT7G+m+mzjO8KguLiYsoOVgAN+LRsGGq54JRd26n8PcQFVLN1+05uNrzvysu89bBJLS4m0/hcVlJCddERoB6dWUUhjV17wzUO+yeBfz1XVdUQQiNaXU3JgcNM5Q6Gbbbj5G3DVguVVpTxa9UwmuzMpk0t/XEWP1JOOpEjfYg6YhDOpZ+vDqGSEjKAkvJyhNDRdX9/e50IBAoVVVXUVJbSjZWUiyOB/ZVaUcEovuJqXmYFfSkrl+unqqISFZ2odmxnpE1yfnwbHUq7g4vl/NKkR/YpfMcB6pKUvADI59tvdIqLSzlSVA3IsDrpqf59VzfiSpYWF6N76tYpZzvJmZtZXtUBgCOHI6R7vC4jhyNADh9wPrdtXUXbtsVUVNheil4Sus7MNQ24VXuBc4zyPpjbkJtYwNtVs6101VH3/hDYb0IIsXLlStG3b19RXV0thBBi0KBB4pNPPhFOCnrmpSlTppgOSZ6/iKhHA9/zW3lUtGOdECDGBr5nyvSEeJcLxPEgBvCMaMOKGGkR99JOtGaj6M+rrucDeF60Z3HM9+L9ZZAhQIi+jBUDmSiyOSIA0Zcu4kLesero/BvIC9b7PUDcxFOu3+uyX3SM0943uFSAEGHC4gRGCRCiM78fU/29f504ToAQ9SgUIMSJPGe0Z4xVfg++sz7ncsjRltM9bfXnn0aZ9XsTtoqbuEiAECcxRIAQHVgkuvOLwJFRK0fbJ/NvkU6pGMg/am3LFyDKSBMTCLueX8+NojUbRQ6HrTIA0ZgmgXU/i9us5xtBtKZL4LjGq8uN3CRAiPrUSWgc7uIc8RHniLn0ESDEVwwWT5P3p4yx928Mb4rOrBTFpApA5JNltek6zhBTaSg201KcHScPuX6EWEEX0Z3fxQBeOYa6yDJv4inRmZXW98HcZ6UZxBMChOhIv1rz60XjwHG6D8RAYzz+Tv+E6nYfZwgQ4mSeFiDEK2TFTDuIia7y8jkgBIhPQLT5C8bvUxC38YgAIY6QfdTv92OaVdeWIOqwXwzmDgGI5mwQp/OQECBGGunvMNZqM1oGjl9t5VWDmMATogNrrLXnfL8F6wUg0o152JK1ojnrxUAeFX2MccglXzSkULRhg+gWZ110pJ64iafEeJ4XPWkiUgkLEKILK0QdDoohTAqovxDD+TpgXCeLhhSK90BkkSpAiN5cGDjHVBCN2CEGcG+t/XEmn4jT+UKonjoE9eUQwuII2aIZiujNDHECX/rSNGSnL58xNBO5xpdzYtTjOXLFQeqIK3lFdGGOaEIzAUIM5RYBQgz2nJvHur7l/n2nAMRJ3CTSKRXX8YJ4lwtEfSNdJkUCEKmkijwOCRCiX0D/jGaceJRbRacAHuI/IJY63kkj3ZemDvUcc7+DAMQArgocUznen4kBXCdCRK08TmS8CFMt+jDaSjcgxvkUiUQsnkgFmD17Ntu2baNt27a0aNGCefPmce211/LCCy9wNHTnnXcSiUSsv5077fAXv836zfVbJBKRRr2GiPS1V18lEomwbcUOWrCFT++aRSQS4bp20r1zDB/y6+zZdO/WhZTkVF9e5t8U1rOZNnRo08r1vFPHDqSmpsd8L+ZfURHrVqwG4IYbxjNy5AgECpFIhB8+vpd3uZh2+I0cO7Zva+Uxa9Ysnyj4IPX48qtFvvJMMsWphTt2c+sEqSfOysygeNOmo2+D5+/F56XKLMVg3rt360okEuH666+3yq9XxwECq4Ssd+/95620wkYfDMrfaTenhpKoaCZlwTfceDcAOelJ5GRnEYlEeJ7racBePv9ypfXOh4xBQTDq9L/V2pbThg0jnQoevPdu1/NNeRexmTZEyOUXBvEWlxCJRPjum+8D696ww6nW88npn/L2G2/7xjRWe82/ZVmXATBvzryExuHekyOcywwLsf8S5WOWtPr0D49v0N/o1O9ZTRfu5x4ikQhbNyxmILMoYCfPXpHPFWf0phVbeefNN2PmkZYqb/IHqEdqWjqtWrY+6nqY9BsnsRobjPKEE/pYabp1laqF5557rtb8fvnq5cBxKuUhThl2CpmU8Pj47gnV7aecfwEwcUg5F/EORd1ilz98uNuG70w+YwdN6d72ZDYC5U899aeO38jTTrPK+phzj/r9xo2bWO9/88NawioMHjSUSCSCGk6hc2eJQzR92jQikQhDBw0C4LPPvgwcv9rKCyuKy3MuOnSo6/3uGduIRCLMnyv3zpSkJELhFHr36sEtt9wCwOIFi8mgjHP5mO++eCtmWa+9/i3PcDMvcD2PPPkxO7ZIu6btNOdJJvLYNU189QeYmebvxwEnDWIvjVjcbgbrVq0D4Prr/bhfKhqHjxwhHFI5sf9JtfaHGYvw8AG/vZY37cR7fiaXCF9+u45GjRpSp049/zpS/d6HQy9+nY0bt/Nv7ubOB4L3kTnNv+AUvqMTa7is2QK+++47AHr0l3Z19Zq0+0PzdBySZ6ghzLBhJxOJRLj9mhO5WH2PbxjBWjqyaYMEBE1SZNv37d7MfdxNMlV8/+OPvnZ16P03JvEY/33xa19511x5JV272zh3G9dt9KWZ/7utUv/gvQ+IRCKcN9pv12ZSwwb1OG/0aHRUK49zzhpNCI0brr/BSjfq9DNc5Tj5HZPCAOPHj2f8eBuXaPDgwdx8882cddZZMSsRRCkpKS77LSdlpKWTnZ3tejaTU9lEWxQEHy6fzXlXZlN8cB/baMu2H+eR/cBACpqGUTdovMPFnCHyCIcOIlB8eXlJ2bSJ7OzBdkNDoYTec1F1NaSkoBV0AVaSlp5KcpLUm2dnZ4LR1i8ZxflMc3mHJCWpVlkbiuryHP/wZX+4JJtWnvq0ZQMbaWcxWFmZWYTDspy6pdtp2+YEFk1fQ8Hoo0dzNiklWapqT82cw6uR0SQlhcjOzqZJPdtuYmjdlcws6sMFvMftmS+QnS1Fo6N6F5PHpZzEHMbxAtnZ4335O52zX8mbxH+rZSgYRZXlvtPuPtpk7IHs3/i7YXMVDtmqxw1GsOdQKFzreA1f8gh12MgHyVtJdaTVHUa2pzKTalIQ2ZCeUmQ9d+Z9XL4EcT2FmSysPo7UFL9BZRdWkp3dNXZlDLez9LQMslNTYft2aNs2bvoVdOUNLgekl5iiqEc3RxOk0XwMvM23nMYj2dlQUsKvyEM0ORyGcNioexrEKL9v+rcsq+zIyfxEVzaCUnzMdV1ML9d3VbHHOmTYhWSkp9Wef2qwIfwj3MH8tlNp8MMEUpIySEmgniIiRfyZoRq20YJwiR6z/JDqVi1kUspoPqLRjiI+40fStmwh7c8cR9U2cv+ZIVx5lHkrDtua5LQcVHRrfU2vdxFq2xPIWl3M+6vWMGpsNutKmwOQkZEZ2Adxx0UIzhfvsYZOFNKYjzgX8ZPCeY53eqauJTv7FEadl27UT6DpIVKSVdLS5H6XkZaORikqOhkZGWTGKDM1xVbhpSankJEqvSNLyKYtG+lZ0DpwTiu6f3zvGzqbub/Bror6Vj5p6f45NoNzyM75DIUSQmqo1nk6i0EUk0Nast/W2PtuSljaaGXnZBFWi0Dxn1ua8NvvpqUlk5qWwxT+Tbt9c+kVUCdBiCX05AD12NHsInZmS5xCxdgvw6GjPCM99B/+zjPcRAP2kZoi59eo7vs5PTwRtbqK+7mbCdUSPFxByLIMG7YoSaRn+ctOTQ0Z/wfsB6EQJCVxHEtZxvHk52W6zgGAkhS7z9OMPC7otZ3cjy7hUtwX6WwidM3dTWpqfQSqY08KE0IjP8teR+Fw7edTrRZt999/PwUFBcydO5err76agoICDgRw4bVRkFfDco6zPldVy6ocKZb/rzwsb1zndlxDH+ZzBW+w+2AKF3ZcyoN1Y7v/mvQ7bjwP9VgA1O6WEhdtl5wQpoOLZSgc1akmiZZsJR83IJ8TsM0ZBwzgJaSNRhBWiRnmwxx4oQvSk6K0YjPD+IF9NOSrTxOLrRaLzLG4ud67dGCtVdeh3Q7yItehojGp9Qw6sJZG7KF7aJX9sqaxHHljGMpPgflf5kA9PiVlFl5gVjUAQynITjSRuHy6UPiQsXyxprXnuf252uFW3qBONDCGYn0j+HRLtiKEctTekmC3QWg6TJgA7drFTb++pDEvMJ5XDcyekJIYaOGx0LyoZP7XIW0VnFbD+8szeWv7IBQEH/zWJOh1AK6uYwenCys6iXjReOkWHqc967iDh0hxSDpTQs7g4vL/RAysKxznVVs20I3lPMffSaGSbvUK6c5yNhTVTahuFlaYLgzIjNjlax4IiWe5iYX0ZmtNMxQEb67tnVCZidLNq6/hcW4D4B3iO1sEkXOoQkkqexr1ZPIAiavVM7ycZnkllJJlxUWfvV/OE69xeR/mcTXBUkOLNI0PGcNKulFCNufxEWM82FlmX59aIsGFe6SulZ5xnnAvR8jlA8Zy4FBskGUXptu8Ba61Gy9UTuBiM2I+CqGgVRuRJ8L+eWBegBMFGjW9ELXKKB9i4wr2Z44vrRMHS1GCPVN/yT6DQfzieqaGFImdRewmmzhYJjxPOCzhCUzPwrs7/4EAlEiPvmSiCBTbN8ABagtQWmYCLBuMVaXGW1yKQGXN9gwr3cXGGRg2+j/Iw/myny9j8PqptGc9J/MDqQFBwcMOIFKzb+umldGDJa50I/mKCLnc32WaD6JFq5Fj3a2giBcYxzW8RLeGtfNBgQzWL7/8YkmvJk+ezK5du6iqquLgwYPs2rWLevWODivjLS4mP9dvch8masWEMzdr25tItrBj/n7mGsxSKKxwQuPdnJnpFyN6KcmDmv7soBksbzP6qOq9bW0Fp/ENxWRzKW/SrEGV5REB8MX8+qRQzTB+4HtOcb2rOg4H72CZzFggrodnSPRbbuO07VPZTBuykGEVYsWwSpTMDUgNqxIB2CxSUUgiKuunKJZY27WDGG7VYaKcx0eB+Z/KTFd68+2oFcTUj+0SBFnRpUHtE9jcfFbucR+isZCk01M0nuAWPmCM67k5FmFq0FHo0a6USg/ej4k3U2udNGEHXIuz+163bgIvYksAw4r2lzFY2zQJ7GrOr91f2d4zkxedyaeFkiGI560Vwl7Dx2dupG3m3tiJg0gIxvAhD/BPMiklhwgt2ArAvf3sYK25xi0/N7N23Kf5qzOtzxtpxwq6s572sp26ztW8wnPLE4OYKUNu7nP3t2Y2A+OikZvzRfFgo+3T5TxccqCp750/QutKg9HIEyUX0GhyyBcqxzqYjXb1zt8EwB33prny0VF9IUZ8ZdVoiFru7senGnAkEQkfMTbnWyu8ioXSoOkcIY8ttOaDmfXISati7Wp/2a5QOV986fr+E0PZcNAfKud6nqdx9VZ/xYz9TReKKyagF1zV3IMVaofm2LnIjsUoojUUsMv6fg5+hsZcg6EkNaaTYid1nRVL70zjUh4KKzbQaIx9xMTeK6IORVoOjRoKCmnCoCZyvLOSq4JfTJCmM5pldLeQ5QGieohS3YZh8V5e9+6FBYZnp/kO2BcJQ7geuDfV6Coo8AHn8yPDAhveIL9GhufCwV8Y4+ykgfwqPxhI7s70Eg5Co6BOOeOYyktcx7C2fogNL/1PkNzP5IvAWITOxWp1ntFBimIvfpMsZNs4p5AZ8NHLYB0LkvvP+zszk9O4lpd4k8vp0b5MRjc3wzcYC3CWEdeulAyasw1wS7C8N3EreGUADMFNPMNVTk+XN9+Ed9+NW8+Pr/mWnb94o7LGJtNFv1pNpYoUGzJMVbmS19lPA2pEiCpSWEIPHqv8u/Xut0vqMZ4XqSGJvswNzN88qAA+qhhpbe79W+xhA235tGggd2x32zXouo2QbNKp7QI2QA+Zm5t3kzMhEHykabRjo+9GvatUevYspicCBUXoJBHlA8bwmgOZPh655oUlzoo955zD34KtJCvRvwxH6Qb+Y9dx/37WjbdxwkwrZIjPYHVK3mR9fqH900zudJS3XU0jn0OcwneWfc65fCxtGB391L/hFgbzc0wYEycFXVL+w41ESWbrwWxW0D3hZb8IGYBvf4Xh6xbnRfOg8kZnMBnYBEDoj4q0PzgvvBIsp1RhaulFLDrU0pUubDDT6+e4LzkzOZXHDElazLrGAX81yQQrNdeMqtio6ZYEyzG2B35dT3FlCsXfzfPl5Uy3Q2vicvv/Jw8ybWXnwPIP4BcUvLOyG99xKkLgkmDdxYP87IhfeoYhBVeU2pHcD35rQ6/o1TVWDEFwX1pMsmB5Qgqv93uJTzrf7c9U0yxb12sMiaKqYsMuxArDZjwuJ4Oxa6fYSO7GXUb9gxzBGKZzPMsoIdvK6+XfOlJHt8OembAZLVSJuWX2M8i56YyyMZ3R9CiQcvbWWAAAIABJREFUkBNBl3AJNGq3NSiQtDPuoNkv87fU40kmupLdwSMykomeTHmpTF92oNzIQhBSdEorQvyX8eygaUL8xP8uVI535xbCBv8iSB0kB37FXnsRhJJU1hY14KfS2OL3d5Hgh/U90c+PhcHKSyo1amK8p6p0KzjEONUIN+LZ3DMopw8LaMoOBhTYzIGTKwcHgxVQn3e5yFIZXcB7ZFGKguA6XuRepgDQoq7blXX0K6dx5il+yIhYlJMeZQg/MW77nbRnPQ8PlxLB75fXp4CdHCSf0UvuYjstKCaHKVU2Av6hiG1cuchjR2PSDM6xPv+9+EHGNpI3gzS1irZsYlV5K36J9HANh9B0K6K6/bD28dJjhHiJxagUHVZ4iWvY54giANAiTd4y59FPYp1oGiqCMUynCdI+6xoDUiIWDchchoJOo7pRvj7SnwJ2xuZYjhyxDqJMSthKK5qG9/5lEizTHVkjzKHdlQzDlgLrIrFQOZfvttGx1QApZG2kRzXasJnpnMe7XMQB6jOLQdLmztFPpzRbx88MtcAv47YrDtDouyuM8C9Hqe3tmCE3/niti4UH91cxWLquMJKvjvl9Z1tCySHGFT3ItFXSyWByySR+2i3V2VaoHPPi4jkiHuJOrnPgygWRViX3txxscFPVw0iYB977yHAk9UJFfJ19Ppf3WkWd7BoG8CvJYd0yml51SErw9u73H1lOhm5C2X3kZmnukDiOxt/uADIOCpWzfK9EmNeFYuUbCitsowXTsA2jzbY58cRikTNsV1W5xhTutb4fxK++dqoIM5KqyVT9e/tDFTczhg+pzz6eMYKbq2HFOmtqUxGCgR9lcEFmWz/bHbynHy2tpQPXnCSllE6tD4BeI3iJa3gnc7yrbJBnvHPOncyPNM6rMOruL0fTFUKqzsvXy8Ddh4OiM+k6TdnJE0ykcV15aZu9pQmvEAynMmnFRWQtlOYvW1+V//dotJdrUt5my950buC/fM9wyiprjw38P2GwpnMupR54C3MSlRrIKObGbtlfGFzpe6vseHdqWOWNVT259sADxKJVhmdSL9yAjW+u7c1Ne+4IeiUmmYzVDwynnDR0JcTAdvt4Sr3VaIM7/RTu4YOUS9lBc85ot87Ox7iRdTQQhHMvMRBtAw4Hc+PJophHsUHXXuI6GlPIGjpyUhu3aiabCBclB6vrgqhb8wg/cTJNUw9YuniQIUp2U4CGjCY+gq+5JPyee3E4mEqN4Aj33zDS+iyEQv1kuRmZN0tFVdBRXIe5rkMLtrvirVVU1T49Y0qwYjBYu/eGuI6XfLeXkC4lnmGiCGDtlhQUBFfxijUmPqbdQ8lKlAJ2EVIF9xRey24KYqL1U6cOeoUUx1uhchK4DR8rOQF7S0rdfSP0xCRYzj4OhWpJHPS+oRqYzQDLg9CUGr2w3GEzKYT0d04gwnG8ECoWyv9R1dK+YTsPIy8VZB5hJF/xi0OqAXYf/VE1vq9Of1CCNaXNe9ZnNazyTcVgVu+Xl1cdlbBxVphDuqVUXkDWmzZ7AH37so8G7CS++lN7/0MAJvGo9Wy6w+4IoEiXEmNz/59WPJKeylKa1Kmgd4difmUQ9fM1K2yK1a8B3eCcAx1CG0HTuM14z9kmhOA2HmM43/EqVwcyWFZ0BQF5mVE+5Ux6dijjIt5lKuP4DzdwN/+2NCR35r7I6a3W+fJx0prdOdbnynKdz7Cdx7zzh4oK9Idlv/lUuQ66N3on22lOXQ5a5imhsOqIRRg8/5z7oqoIDkdU+jOHWbskmPj8g8cW7cRLdSiytFaKorj6WuiCa3iFDmEpEXeOnxpWWUIPRz6HUZJixyLUdRnWrUGeZJyC9owt21T6MJ8BzKZ+brWvTC8drMqmecpeV5mntN7Mw1kPsHS7xA68mld55rceMfOw2lNrij+BruY19h3w2BZ59LDevTotLCewk4kJhRVjsGLTlbwO+De4lYcaM7PsxKOq95qIbfCbQTm/rMx3TXjvLfbfTKFYNUDkAkLlnMpMBAp5PeVkDjpMvzMXC5ov9lgy1XRknU/dmohdhPsFY+KbNwtHSAOAM/hcHvbI/nbFIvROzMWL4xflQPBduSOHO3mQl3ecysKyzu45oOuUkOliKp+cfULtTYkheXm36Z0k47cnMBfWo9zuem6+b0KH7C+SzONrXMVwJFRIOenEo4FZS7mJZ2DoUPLLDSlIDCbhv2Ic8+gn0xibz6CMRfSusykw/R8lJ6BebrYnlIj1T7BU1aRtUTsW5vkr/8l1i48OUNO8qb4RoHJdW2RLFJcdLEBFsGh1mi+dL884aMqm2iMeo+SljqyhpsY0BI5N13Wfx1eMsoCQTbLWyp8twRIKKcZ8rlcLox9E3dM2WJ9DySEURVhrRxMhy87FXAd7KvN8ecyan8JbXMYcTopb1rZ1UnW1Dzuaxdl8AsACg6F+ushtqC9Q/KFydN3aO2zTXH/HdmpWyn+Q7vOXp7zvO0ysKS0E+RRxPFLaoQeATJpzJUmpIS2phjP5nAb1dCqMtR9BemCa9boq5yMGNo1vyuBcUzWGdK9HhmTK2uBe76Vf/sIYPqArK0hOUXh182Ae3XkBXpKxUTXWYKs/uzQvsUPlxDgO+uWuI8sIUB5SBDWawlz60zA1Qku2kJeSuCYkHrli3Kruvrb2alM96VERej37kpJVpjOajs38oMKarhBSBKaTbBDjVFUp2E4Lecl0nN11ORBo/qEosKJSSnRX7TLOc2NuOvmRRJyw/mcqQp8Kx8NgZadKztJUC4xpJQ9up3hVDauoqgi8efjK86SJ5Y0Rj1ZE3HHG1LBKeTSJPVr9wDYAVIfS2ENDimvsw9i0cXrBMGguaBDlI86lfTO/y+6PDJN5o3KIfNdvhTTmJa4hUu7GQLGM0T20axeWV5D7BcPIXZHSuQ9WyUVqMoIL6GPFj1JDikeC5c5q5uTZ7gde43UUUpRq7uAhSitCPMydrnpM5AkWcALd2lbQgH2um24i0pxOaVsC07YOb2c0HzGEn2xbMSHQa5wrxH5p9gF5U5/IQ2yt0yNwbJ/ySL281Cx5LztoxsGd5YziS1KodIVxcNLPDLE+V5BOLxZyQ70Pubnd13HLOFZKxrZn8qredN2+jsQL/1Cs2QblRTVZHK7OjJ04gJyqgN5GuJe/1Zc2NU4j7LfXGwapCYx/3CDAMeJUxqO1dOKbA1JN8srx/41TsMzcybiewAKGq1Kl8KerCFH4xFC9e72fEnrfmM8vch05earL+01HISkJOrGarFS5YQT12WCHdDkefbxarqUfOdl6tsAwMm6KxArydo+OyrOV17KksKHVeUWHFQYbnnLxJFh1MqsZbTjc1K8HRTYSCyFqLOZMj2rM4Gy2OtDYvQ3VNOjKCj7s8bDNvTvi2n7DCO7lHg6YJgYJmJ44D+IaI0pA2Ah75lXB/rIynyjJnMd0snJUZu3rwJdF/Xx56qgWvAtICJl2zSoJhRW+YiTDOxf63gH4Z+tp1nuqKqw9f9L8c0kjOFydqy0JrqXxvMBvm2XEDMUzaDVRgYJgXKkhnXTutQFGYLtLshnNx9TL8dtk6kIhpArLqSxoPzDNCObTh5J7noCyMjRNXqZ7spjxuNe5oggKo3Vd7S0pD3GQum6zlgT64n/GYHkbrgrNctNeRnfO6ykPyoZ1a3iFq2iTI40rzU0yhUrq5CsouDfjWHQ/k13fTYYhHk2cCFdeaX/3lhMKK7yzoJ1l2Bp0ex5S8RWN2cNTC+1bXpuWGmP4gB4sYRvNSU+Hc5lB3ezYRrzF5NCF1a5nm2jLdbzEwu1u+6FyMniryu0VB9C0KUwctcH3/IfFeeRzkL1R6V2z4ZBk5JxzW1UEMzmNh6snuPrNa/MyY5tbTOqTTKIy/0h7pnKdjLDuoLCq8wS3cgKLQJe3xCdi2E7Eoldb3E9TdviZZ03jTD7jAt5nLv1lG4Rwq2UdBawvldKZEFGSRHVc255YtLuqLs9yE0fIRSMU10XclDgO5mfO4hMW0ws9lHT0BkMJUg42yKKX6ZO4xLL/8jP8+F9WOsfnY1FnOudGazYzmJ9tFa+j2VWaPNDiMU9WnjHS1GefxSwmVE+nlEFXSaOcrFCc27ym8SWncyPPWY+e5R9MDMnQLqnh2j0gLTp8GCZPjj/2jvrdZISPORr69oCE6RjHVJRwyBmzHo0QGakaq+nCqOOkh9tZTRb48uidYAzEzJA8qCPYqrFLjQC+JkOqKIL5jux+LevJHdX38tu2An5fm0t99nHD3XXYaQTT1uN4dKJpVr4Vp5xJWYlsWC8WUsAuq+tqqjTOZQbTHR7EfttNY20KQXExvM3F7IvYOFi/McCVfnm0I9sO55AoZYSlFDJJlfPDDBxtkukclUTU8mbz7m1CSImQ6XkHtsRIURVG8g0Fuf6QMwBoGufwCafzJaoiLIkX2NL7WLRggTwjVq2KmcSiTziHdfukFNTJX93C4zTMk33wabUE63Xutckp/jM6lGQH//ZSm/RC2mXutlWjQYbwxr4zkadY8/VWeOwxaRyPRifWcIfDLs+s748l8kJQbexFD/16Ir0PfOWSRiayVf+fSbDCqs7d3Ed99tGdFVZt87JquIrXaJAuIQnM/vqcM8jMUhIO2ny8I4gjkJDk6+MX9vPRm7Fjm4WSFHuyCEH9rAqXzRDAESEXm8uw3VCzzaU/LdlGSTTVyiMWfUJskNcdRX7JwU49GL9oz3x/dPSqaoUi8q22mIyVEgAt4V10uu42WFU8h7WXwRJCQRPyxuyTCjlnqKMvHucWGlGYGK+h6/zCYG7q5caTeaFoLFO4l2edAK+67nbpdixGU1KqGLAUQQf3YH6OW5UDNVKcvJeG7KSplCrOmAGZ/vH6kLGAvOmZh48aOnpHjESpLRs5mxkcoo7PHrJf3Y38u+3bLOF4zuheu+vxEH46Jomwc/xNqavZ7+6bYezbqJea5MVmgsyNe0TByphpHIVaH2t01WaO9wZDUdwzZzh/40v2IY2i19KBvsoCOoi1vMUlTOw1O/C9QLr7bnjgAVgZu56zO17HfUwmnTJO4bvE8zboqZ0OiJpQyCPBsl3qzYdds/37RqJmCIohssmgjDykOMkEDy4wHEYUBGX7HBNRwYKMiWohDlCfFAemUZd06SUd5I2+e38S/0F6Or88u4MDQkOgYl8EvN6NrdnkO5c0TZHrVtcp3CvVVRt2xlZVX7jnCZ5ZHF9latkVo1u38pAhwfKqWzs0kefeCSwE1dDYeNZZkHR9NV2IVKY4MC5irB3dlpyFFOE6p1bRlUrdjxBvkskQL18eM4mLzLydF/c0KkhSJHNpys1zM6LWmZKX429bpUhmGmPZe9Bv8/tEp1d5vPMbcY37nf31DDdRWSHQNBncOYkafjC0Rla9nd0tTHtMOWZ6sAIkJv2fSbBMHAqL6XE0ZAC/8uX2rtb37izjFL6XG4PqF6sGkVeUnMiB0LPyN07SbYaptQfnRw3ZmFFCF4zovINZDHbd7ExQMydMA4riUiVU6Cm8z/nsOxRsJA6Jb2axyNw4RmTHBrILG3U0QandDJaRRtFcjKkidFcoHK+w3y/BUthQ1oRD1GVPJN2XdhYDGcqPbNhqL+z3uSBhAD90nVZspW6amzF+7vDFrKMjq+jKLAbyLacidDfj5PxcY8A6fMcorit9IvBwD9WJf1N9bO+lAAzgNx7nNkrJouK+x6GsLOZqPIGF1nwetelpzpl7a2C6P0pDsxbxCefwOLdSVmGvnxF8zfjW33F89mZ5KYnT6eY8MJXGRy3BcvTpOjrwI8McTgr+cuJ5NJrUs8WhwOf7aUC0RqELKzmn2aLANO7K2fN2bJ3vOY/pvPB5YzY0Ggj79vmSH650H7rN2U6FmkGKXsElvEN+eu3qFotqDGlXPL2irlNIY8rJcKneEi7CAVuio0r8JocEK5SkWOWAffilOSAFEjXc71JHSvgL2GXZjXmpQbiI+tsXuvLWDaBR87Dsnye90CbwJENypMnIca38AXVXbsngIaSn85ndt1l7kEaIW5KfY3hTGY7HCd8AUiPg3Wd1HZbQk39tuNj2Ikzynzcm/lki66BXCwlR0Jzt6FE51ilqsITTPF+G8SMV1aFAnC2nzRJAxxTJfM5fnwuKwhtcxrrCYITxIQsf5TLeoB9z6ZO/0QchFFcIYYS4UbbEhgQ6jw99bWmSV245eK2iC3q1m8FqWr+KN7nMKj/TwHs06XBlOhcwjRWbM/CRrlt8AQQzn04J2ftcyOPzTnJpn5xG9eARGpg2Wzqoiu5i4P6/lmDVVOuspCsHqC8RpBdKUWlJqcJvDGBDRBpI6rrCQeryAydTXaMmpOoDvxokkfcstY5BLdOlMakpuQglebw0jB5+hpssw0GTwXLeDPYVJVn2EwAHS1O5kPdZvdkfgiEDDzREAAXtw+eluNHJLVffABsgc3J1z90m22XMgrQUu+0ds+UmOSJtFp+qdt2vPXE1SzneURePBMuziT2eMpndVVIFebBUtncWA5nGWEqOaAxmFj8zlMPFNgOqpKejhNSEJvApG59nCvf4ZrtzUxrMLEbwLXqN7rrFOudk93RpbNqMLcyInhHIYDVKLvI9c5L5Rjo2s/dt6UkSmy1GYzbQjq8Nr8ug2+qfRVc0kVKPh7jLdSJ8w0j53ZwUcTq9W4o8qH7i5GNSEToRlc0oDiZemSsv87KVgAQrXn0H1l/DtbyUoDGXnU999SAHqcv1vEB7NlC0NeJL7tVE7Kc+F4u3GaV/VntZHlpd1Ijx/NeKYhGrfub+tdgRkitRcuICKoqB32R8f1e9hGEdC+nIGmYslB6C64qlyty5D831RMeIRV3zdnEWn1CHIrf3mGMYuqZtdA2dgilJc0g8liy16tApdTOPMIn0FL9dhnOepCfXWGt8CT05PeUHhjSVa9vLmPgqBTxywkecxGwWRNqhrZfvBSG5f2poGBLBwTLt2rbRkiMGjMDfmwbPE2d/W0CjnjReSZz5TihJ4kRexav8sq5hYP6aUHiLy3icW5nU8UvrLGnIHiu3WNRRlyYrjSq38u5/DlNZIcstLIQdhsDzDS5nnSGtNM/A047ba9nWfsrZ7NmnutvqcGYQiuqC+QEIJ8W5cGkaqCoF9au5lqlkpMVWEZpUqSVxcaclvBa+FoDn+bvr94L0w7RKkZLWtGTNKEYhpOg0y7OZv/+vJFjezik+ovO+A/foQIk8fDftkHGYNhVLO6PRLReTx2GG8wOllWFObrWVSRlxjE8NahRy3zqlLWL8w+s3TnLdDr03h1DYhv/XNYPBUhR69VXoiLxtmcaLoZDd3spqdzeHU6XkKmiATGTfMzzhXDIp4UWus9pikRC0YCu5qvtmZ92+lNgT7q5On5HDEUuCNbB7hCncQxN2MaXrDDIpoVXyLs4Qnzte1lnmCHHk7dGQonM6X1rfrwm/bvWjaXB/InMYy4dudZ1L4CcMfBlf1X1UGK3Hv5nCt5vdMf+0gKmta4LWjcothtmpImyWtIckqmnPSnShBh7uyTFunV5q7wj+/c+DN7OJtvb8nzPH3o2Al7iW17gKkF49fxVMw8YKGwncy5NU16h8vb8XCoJ35rWJmcdD+U9Yn51eaIlSZrrOA9xFPfZzK4/Julg2WP68EmGwtBpBE3bRnzm0YSNN2cE7BhbeafUWcTafsLcsq/bKOTpFaHqt0hpvfVuwnS/0kRygnoytur57jDf9tKO0Di8yntKK2Lg6t+y8manG+r+LhxLO26SQwyNZUeDXFpdx9wky4sJ5YjptGpayjo4cLpWS5Gm7pOoqqB8mc1/csqqqFT7lbL5hhKVCBfcZoKO6pAgdU7caKkIbjdxcDLMZQL56mEk8Rlqqvz5eqbTL7V/FdkgIsqv0LLjcpDIasleaNjws52goKiX2ztBOFt4ZtWtGTI948/Mc+tMrVzJvfXADp+4psqNHWE5dnvyTQxpfM4KurABgTK68PFkqOWKHsTKjE1g2W8btujtS7/fP42JjrdXNkFLZnZuquPjGPO47T5bfpAk0by7TpFNBc7a76oOiuKA9du817PCMuaVVa3xgmExESkMoJ7nVpknJsU0Gzl96OzevvIqOLSqYyjjq5vr3aO8ZqCDokLeP4clu856xTEOgcH/PT+iaJqV0WSnSTlrTZD5dGh3in9zPKL6gff4xhsr5s+lhJtGgjtudzTzkc43QwMJmZl00tOEaK0RJKKwwsOVObkx/tdYyG6gHXd8n9Z3NvEZnx32niHwqsUX/kWr5+U4eYgg/kZ1tMzdC03n9tzYUiB2Uz5zJcQZDFFYNCVacUDlJKe6wFE7SAlyHQQYuDSQztIM3xI4hSXp6/4UBrxjSLStUjr0QLMgH87OKexMyYnXFbFtI5woDKsOsn0mmjfvs7jcyhXvcNjmu+GGCIanzaJvnHsPA5hss3k/b3fgtQWFOhKbTILeK//B3HuU2l3TPNG4VyJv9yV33M9tjH1GbajqIgW+ftMUqG4CTToIuXazfZ3Cu9Tmsan8yepJNh2tsJsMrZbx4/o08vk3a6BSXx1ZbO8e9QWqEusl+yU5c0nUGMJvbeIxWbCFMlNNy5/EkE3iuzztWMjMuYVZa7Qzt9HlN2U0Bl/MGm2jLTprZ4I01GhfyHrctHptQ3UyaV9qFLzjD+h6Ebq0H3KZDaBa+1+J90iaypgafzZuXvt3ZCcAlxfXSjyUn1Bp+Jh6JEnclGiQfJie5wvRwQEkyLn1Gu1qlS/OIbPwquSCPZSftKpZ7lRfWxLnGe6SvZ+s++/eJDd9FGPuN2d+zD0pvxIX0ZtrB4XRmFQs35vrKczJOuu6W8GxQ2rO7RNbHKcG6hLc4niVUVXgOHAP1W0ehskb2SSisMIKvOd0B9Goj0Ncek7O00l5TSWtX0J+5ZCdJZuVmnnalTQo7mMOQtPnVPdfYEBoj+JZGhtSpd8Yaq55gqFtjAeGasDYGg5WVrVBII4bzPQDNso8EvwjUSa/kAt4jrVyq5Y9s96//HxlqMVNOBmsEdigsE23dbNX8FWnWektJgX4nhTif96304eQAKbdBhVV1KIpmuaA9vNSjbQnrsePC9my8xxUeyqRhBhwPikJ2SGoh6mRIFbdm2GA1zS3hfu7mC87goi4r/BXy0P+EwRrPVOrmBDNYNpK7Wy1gqZ4cHaYmmdGWY09o85aRpLpnWE56lIbq0eHH1EuRm8sNPM9PnEyblpol7RG6oKwybEEpjOU51tLB4padm7LTUwMgnBIbOO0WnuBEfgusjyVud3A1WlRnC61ZWtPFldbq3yAVoRkWwWSwzIWgqkzmftbS0bIb26Y35S0uscblk2UtuRj7MPTlr2nswIa3+FWz1Qojmq7mJ4awqOAsnlVucm24WrVGU3ZYeb5Z71Yu7VK7O3qQF5p8HizBQtPozBpu43HXzaawMp8qUtlJC3RU0sJRurGCJ5jITwwhjXI6ZOyMWxezJ5Y6dPqDkuUN1WzrF4xiUYk/CLSKRkg9eqlQonTu7metz15VicCx8cY5K5qHd1ufX+35Aq92etIdbbkWEppOH+ZzC09Yl4JJjd5mAk+TGrL3h855hfRgMT1a187AmfMyE5uBMBG3C8ty2EVBQmpXZ4iNpRXtXb/tXXmAd6762fXMNM7PopjOSLcqJ26dWeJFF0FWLQK0yhopNYo39nG96BKgCjyG2oYboV6jM53R7IjkGOXIn1OM8fBe+NqyQapd49DMHUagaM+7zvXeKmU3aUn+/lJDirVfmtEVAPZU57OGzpRU+C8ALgmWx85ydOQVnlg82Fd+MtUs43ifVOvtTX35kLEIAZOqpKSuSk9iHC9yVZYdXusi3jXqXbtaf8M+23bz2n9J05fPD8p9McgGzCRVhSm9vmZacw9AtiH685q8uCVYwXUxVfKlZHH5/PEoqkJj9nArUjodzwwwOaRxBp/TIkcKRUxPfycN40c6G97v5hn44fzm7joYDHC+etj1/T0uIC8PMpKqaYYt5W9U18TEDJBe6gqqKohqKoeoEyyldMQdVNFok3eIhYVN+EIb6Uo2kSfpwzwq9BTqhOXZ36GR3INMFSHHH+/Ktzb634XK8eKNGB1hGbSa/JTFYMnvG4rsUAJqWGVfWSarqv0HlEmfG5ywy8gceGdld5QdtXtIOallulzgNSZiuarSLL+cs/hEeprpwoW83oH1NEmSk65dfUeYCE+onFCy4YYeMD6r6Wx5lrRzqJom8YgVEiEz1d6YzINhebSTK5/0VJ1cDnN+nt/jKCOpmrZsYOLSi2nNZq4+SYLeLdmYxUB+5TB5/GPxZVSRyoZoSy7jLWu8Nu7PodoRBPn8tm4mqKZaZx59re+nVH/JpYpkyBqmHGZIaDZqSB4mLt24pjHXAN6smxSplZE2KRZjoKFyRhM3CKpeo3PwcIivGUEFqa6XmoWlzdkPnCHnpK6TTQkTeYpSMqkgncubfB+3Lh1StvkfmvZEE26BaJQz+IJ/4o9EUEUK6eHqv0xFmKvazIp+yB1PQojYjKqTxuxxwAMoCnO+K2VoenA8yiDaswdSqOZbTuNDxsgD2DTwdhR8dcc5LKZXQhuYmWQcL1rPTADXyasvZiutEurTaJW9AQ9IXej6re/VnbnktSGeco3+QrX2MBOVHLA4hg8/JGGKd7hpqJziDKJ+lOS123r04JV8vLoDbydfyRimM2tjY1Q0C7MpKFROazaxh0bcXYuKcG9ay+A2OCRLKjpdm9vSsSyllOmMZnDHfaSmCFqyhZCwLwIzI5IhqYrGuDiZn3WFdgVlTOBJwHTSkZSRqlmhd0zyXnK/3W04VwmFZUKCyOqonFHyHiP3vmala2fEvE3EyN05jb/mdJ5kAnOPyHh7XgZW86iem2SX0DrZfbGrLNN4jSsYx4ucwkx21Ug1rGmMH8+8wsXEK/gm3Vc7Yge0X7UnnwuYRlnohWi+AAAgAElEQVRUmvF0y5cXrm4spyNrrL6Mksx0RnPq8VKgEdXcY5YWjnI3/+bDOjIerTkvTmChrE///i4g6Lp5BkMZZIIlVEIqzF2bS10OsWlrgBRY18nlCBN4kvW0p0uDA7y7tgeTy+9yJSshmwX04fFVp9I6Yy+ZlFg2WN3r7GRI1mLo1w/Ky6FFi4TOp/8Jg/U7ff2hcgw1xREkVoY5CW3JlqT7ltui+lCSyiuLjmPokY9jlmUGGm4UdnPXV382CoADB2B/DEHWaKZbt1Gw5942E5guFGJQpwN8wjkkh3W0GvsGYoa9/arNTQgUTu+6w5ePaQehhGNLsCqRtmidWM2HDryWx5hEElG+YziDOtg3O7MfH8l+0J2RJer2D/Go7jul27SikkYFmemyDSUVYebTlwrSKI6m0Z85jM373lVXr2rksh/diMyRI8KCIACoIpXdhyRDptdoNrYLbjsnoek0oZCWbKFL+lbrhl0bme3zMVgiRFLYAxmh6SzdmMnpfM2XjHJt+HkNko38pNfksi1ZKAgmc58FzOdl2r2UplT6bCqqI9ILS3/lVfhRxv/7jlN970rU/MQw3o6Fmods6VPN+Btdv+lCsUJoxFN3HNYdampVZQJP8TNDE/L2A/sgfJ0r+MmwdSytDHMv/+KVDQP9LyTCYBt5FuP38KwxmaAE+tTcd5KIJuRc8f+YO+8wKaqs/3+quicnmIEZ0pBhyCDRBCiComJWMGdZw7przgrmuCprFnNGMK2i4iICigJLkJxzGAZmmMDk7q76/XHrVtWtqm7G/b2P73ueh4fp7sp1w7nnfM/32yyphpHMZRYnKWza0v4I0WhTnp5har6IxR+xWtQKrA/LT2Hahv5czruA4NLUMO17L20Q77rUJYhsoFNNlrKACrLkHJH6G5HlLL4u4T27egzEotWdon9u/4Wcy2d0Kqilf1E9W+lCr/Ttzrkl0ajufwYSyzWOr+mSW06SbtikwGEtZjvDGSlRHuduiljPvxkD+HmTDJs2RKMT2wBokx8VVCvp6ayiD2fxuZ0mvbD5dxzf1s816LZ9lWr08FaeZX9EpDof4CHlt5LyZHXngHGwssLkKt4iiQizGMvXlaLvKBGsuFI5Lt4rTeAv3fb5tiO8uzj7evqTjFAVsovubFSgB/1YSfNsRxrNbZnJjTzEJLoniecr+3Bo3ClQUABjxyrb68kyfe08h507obJSgPZ1zUzITrF0bRpn8iU38BLzGcHOyhxiBqTpwZx/u2tyOfqtqzlENqldRKr/2p7zeKaDxXmXlkbvPbO456fRgfsr137YLf4H7GRmsWF7ivKdN9z31le5gd8rIdOkkE840mtnW5IM3peah8gbX3WV+BdkOVQqqYZ1VQ63VC5lbN2j8oxIsjKAJ4Cq0lIXgZRfKuceHqOOVJHqJNjBmsdIsbubwsKyJCKMYTYts53SZ+kkSG4R26zKDDNQvEumD1GlcqzrvIsnHKkcKb1gvRcvuWq7qrXK59jmbb7T3W0RuS0vactU82p0XeC7FAyW1Tmf4TbOazmXI3b9i3vnn+i/do/JAcP7KD9Mv4bLuqvOjhEz7UjceKZTW+PaqYvAcNURw0Bn/S7BXfU8NzGTU4HDU2cck/E74/hGiDxbJsGbadSzvcQZaHNR6QUMdIqyiumesTvhOZpsM2fC5ZfbH92g/381qM9ViWAlgNeUxRz8y92rLuQ/Fjt3kx0s633PcLH1H795KpN5kPklTlR6b3U27djF3N/9eBvfMRO8ksAKxcNc23B+9j2D85lmVwlL+8fAD5nL8T6pHK/dyyMKONpn27dj7vPTQPiuz9TIssrXs/mD2LcA0zRTac962OKqs97l/ga/w7rNIsUMcijddkIfcT9/afmF/d37XEqyFuFhiwD61t03K5i+6piFx9J1ewxdW+UUZsRMVc7LbQPbl/IK1/IZ53JS0XalUYS1mPP+DYNmVHIEy9mJSFv5eLBcTsR5iJRg23wnfd2HNbTkgP3sbmv1Aed1TiwX5o1KAWRahKNeqRyvfbejF6+Wnat8J9uqvIYWSSJb0irfgd3E6xe9U7fQge1ifw8kIZ+SuIuRSATmbBLYqhX7WzOafwsMHzCZydzPw2qFtksqx9v/bEdMSuVYY7L+9xsDX3ByWojnuInehU4F36BB8Mor4j2FQg6fVxBNQ3lViAUcSxl5XMVb/L6vFbGYRotQOY9wLwXs4+qi+fb2mmayM9IaDZNZ/xF+iaxWtJ8HSb7IXJD9n5HKkYy2ciK/sZ9A+CsCs0kCBNmklZzHwZKOkN5Qi1nr4EZ27IDZFrbNG/H5Yb9TCVROrrXMcypcDMNDg5CU5ApXuWgHLCflJW4glQZyckM8z9/pWehHv37IxYAgq/RGn/bQlm85mWjMuTdvZ5NWVWFQRgsWVgeEfC0vSddMFjOMX7cIXIB0sL7gLNuRldcuV3reyWczatWZMe40QHRWt01iMnuqc7g1+oTNZZaabHAOM5jNCQxof9BWqB+YtYlaM42GaHzAtTRZzODtxMfr8zity1p7QAcBwFeiZq42ue2gmFCGMIk14f4YX4rKyRoyabCiipesuj3htYzLmkcKDTS3CjcK2cl4Fy/M+p0OqFdGKjtaq+Qz+Ion+n7Ic0WvHfaem2Rnngnvvmt/dPejp1HvwzC1QD4qr1UbThRkc41THRY0qAVZYFGH7SA71/fauhHsoV3TxL4TXHCKZgnA1h5eX01e22zGMKP2ZPU3NL9z7SJsDDI5DGRQYztGilVUwOrVfN/tRt6oOE/ZJ/D60PmPpeNXlID243D22jhRjKNjkqo5ShKhMDSjgiRdHPf/J1Mt+5UXB6sZMU5BSEFpmsnybY4D3WiEmcZ4QaJsTWRVjQ6NTaLr6ZpfxbW8RnKSCYbBzj3O2JuiOWn3htoYixlCBc55fQt6U+MYfuHrnnfYIHJZxQZCS/F1/mKLlDdJKifgZ/lsfEVNViN4zJIU+25nb14pU4s0JIZyNqO5jpdpl3KAQnbSoa1YZL+QdCsndA/Gi37Q/h6e0YXeqwcaLKJQcW7lppvgqTlCQiozqYHZjGFTpaj030crVtFXiWA9zP1sLBYpc+/cX18Px/ALd1WKe7Qr3pODizyqGlK4iSl0KXDmS6OuHr20xE4R2lqEAd1Cjk+zrMzB7yWt7bl7EEu5grcVOR9dc6KB9rVbfFv2NhhNyjb8rxGNZqSqne9mngOgQ34dk5lkE0d6tQhleulw9nH1acpn6WBV/bCQyjkO8WD//jBGRIuZykR7VQ74enUorDF9USFhIlRVGLaekduu3PEAGiZv/Oas8vJbmvRiDSfznbj3TI2/8086FcQf+EtpySCP5lgJrTiVb1lX7B8gPqhTuUNkdYzUVHLbl8sK6c/v9u2tLRZpWpvRHZOYqbOQo/i8XGBPnBShQ7IHsBeVQd5O2Xmc4E8ZTwoNhIih6SLdkZcTZQbncQJz0GJRqsjhHD5nTsXAJlXnACxsdSZ9Wekv8zcM4fBa9h6XkJoSn2hU3l83PqIj24ntclJqjsXpUHV1sHs3+yJ53MHTbKcjINrGXTxpb+ZOMcqy6KEspg17mMVY4eD+T4GwvJhHM2RHPv6C48T1TNlqs+2DWlLuO6Trb/eTaLKD5dnufD52VQ87R9xXm21915QUofP3qQUOdqqQnY6DVZaYv8x7bTVGOh3Zxg9WGgkCopcxMVlP4kH7q5GWbp7b2rOTIz1pY4C7enyJ1rcPJ0cdOpZOhfGrJg1T4yBiNX0VbxAJpQgsyB+0tHEiNatpptJGQiGN/cmFTDxaQCTOaOWXxTnJVQmWyOR7m39ITTeZkagydtfUO3+vb+jI+Uzj1835bNqVyiCWML/SiQ4q1W/+E4r/QkkYMZPiA2JhNpK5ZIVqbadh916dYSzmexwH2rfwN0QmIztUwwjm8yR3KDQ7o5ijbL8/msvBusSi5O5x7EwrwyKfg1dv1ns9QVWEctx6npt5lesoizYTx7McgCuSPqBvqzgUArEY5yb9i4EsRddNwi46oUTYrXnz1GsS9yD++JyzeZ2JSgTrQy52yE5dB32by0kPN/Irx/BJ7WnykoBgQldwOV6u4xysSeXV5+rIC1XQLKUO3RMI8NwyAA9Y2MGYqVsi0QZjmcXj3INe6eBSNZeDJZ/1FfOv4PjVjiyWRtPWOH9eBMvz4lrkRHiRG0i2mH7nMAqAjgV1TOIhctNElEm2t7e53CLI0+J6ju7GmVOgNnqJo/qJUYqeVKUn2u5mLvaanhTCRCdGGNMwyUmuo5OuSkqsqRORODewXQ+J8L7Nanw4OQPgKH6N+9vv9zpREbmaWRZRI1Uy7Nou2d/RSqtSWEl/dGvKlNcqI1juyph6U6R25bONxQRDczy7h8cCv9cR0SNNs0LT6EoLda9+NtS3txpwEyKVhsFUruGvfeYqX7/fOJ41FW3tATmXg2AYSopT4eWprqWVXiKmUcPwKbontPPOg8JCGkzh0ElKDe+kXNTWWYFJ0sYJTON+Hhb4vCYC+/8bi6EzgWn8Tn87egZwRMZGemfu4P6CqfzCMVx31OF1MMbxNbpu0pq9/INbmqw64NMjxcBotMSFA7Y3m8CD1SrLIXUNua5Dw7QB2y05PF+N28GKEqKONKEeAczgXMrJVa7/nhUTOJZfKLMoIZYwyI7CT2YSdx4lpHKSiASKMz9ZcrnyuR27bEBtkP3W6mzu4TFSqEfDJJkItQfiy3rFsy3FIoqq4cHjhDSl/Y1u4W8Hynve5ocCSJNjT4skdXA9VBETuqPW+cOuBUfEDFvXAXWNIZYxiNqYAyspShZ0J0GUGXtLk5nD8eTU7+O5+YOUSjI3Ia7XwU+mwZ8iNDVbJulnhnMnT7Frn7NQq0GVvTpjyz+4faFY3FZVCTmZek9GWI6l3dhoF7iUR8VxlnmKD0b0FtCBLggepiBcpk+ODI19tCJqpVETjiOGAeGwqB7XIJyRQnc2MIDl/MyIuGNuuzb+Ph41xPlmcRK/cbSP/iUUEJC6mA/IThYPSJ4pL6OeE5hNSmqceV0P8QvHUFqhZjT2Gy2Y3eVaHj3qG59DpNxyzO+0xgyNQ2YmrdnLN5xKZUOK8rukcJBTVNTUFbiNCAAEXq5if56D5fUsPVI5NkuwYXA1U5m5TVTFxQydU5hpgzETaRG6O8uNk3KbdF292jmDwFH8yvl8Yn9ukaziLmSKUp7ruqFL+U+eCsiz+VHcT1bXhRyFFUWLRDV+5lhKy+Pz3iSatJ7jZvtvL92F9/urW/oZg42YcBNlAwl0sKxtw1bKQB5PaBH6r+3TT2HuXGy8kq02b9ka+rCrJhcdgzMH7GCOPgYzZlBKHtfxMqu3OwPXpweObxJDsrygYSymqJmakrwu8k/eWX+kvWpZSy+ijaoeoqJFuHgJuhGlhKHcZQQ7iUGUF4ANXr9yt1pdtc0j5BqUAmrLHpt77IZlV3HByrv8G/0XFjM0al2l+UeF/sNUJjKTU9mCwJu9zHV82G0yj3d/mzOy5nAMvyZclrkHeg3owXpu4TllFZzIvAPdbxxFBIuiIIhotAl+27heW+2/JXcTwE460GCIAXkdPf/QtZ0f/owT+NH+fCZfAmp72VDVmggCkJzJIQaxzBYmnsRD5KSISeQ3juIzF9eZ11KxyBtpH0gKLC1fO8BGutNAKs9Ygug1tU0HvV9sLRhutoYOXTM40OgULYTCloNlBEMOQB1jql75MO65BrYv4yWuJyOkehpVFc4xM0J1ZKc50VJn3NTs8Whdveg/k5jMCWm/kkI9Jx7hd5ZnrWrDCcwRV+iiadAwOS93DsPzBQjdy4D+OwNonq5K+RimxjecxpN7LmZxkqjmrtNUPi+3uR24ZcvgyCNhjyf4PbKbqFDeRHfu4ClxbXFenexLEyxogViMBkewpC2v7U6MMBt3ioXT3Nhwtpf69U8BRmx7hyeit9GLtXTMPgi6zmktFtJgVYbHCxqPPeSCOhwUhQ9L9ov2LrMYSSGD0TiV1vI9FmQ7kJwKmtmOmBxPjywqZzZjyM0Lfij1sSSG8wtzVvqzMTJ1Z0fVArqQl7pBYtR0zWQfrdlDW6oN5x1rmjMXnvbgYN54Q4xPbjjQ/7kIlvdioo0G5TS3Bylphw7Bm1zNyjLx0gxTqLJvRDB1J8Jgufl9zjtLDbdPZlLgPmN3v0EPi4XdJtm0rH2a6MzDEQA4IZUjfrOlcjxLKslX45ZXqKnVWMIQViAwXVU1IUbwMz+vbh54TUDCSh03z1JOWKxihyWr4tY2NivAKZBOUstUgQ0JcrByk8VxhzbfyEtcT0qyOM7dR821qTDcNmECnHtWVKk6AriTJzjeCqtvr2mJjkGb3HqO5Rc2bQ3RklJe5Tp2lDhRFQ2BEYnX2TduFO0E4NSyd3mXS30NzEAngrPiuYOnKS9X005KuhAhPlxKf3sCk9beYiYOx5kATVNEPQ6HXJFt62QLhwJQQoHdLg5GMtnfeHhgd1PscvNtMlzR2PfSRUn0vTxmi5uOZJ5YZhqG8/wSeLVtQwKT8g2noesmPzGKW/hHk/FAqUnqCncbnVlHL99pXZjkw5trozYpauFAzxThfP1kRccTWXa6M170Zg1VLmLfjhYoWCnKcF1vosWQd0zx2lW8ST4lPMo9lBxIMBzHYjZdjKxuy0hverRzCYNpRjk5FnbdDR1KpoHeHWs4q+ETZiwXzveOWtGP3cUY31qLJ4Dpa+MD3bvmV3E9r5Ciq+nmaIPz/jum7FP1J2VlWkgLrBTsk7Se63k5sFHIqHRYi2KYzoQ6l+O5re3HXNBZpDu9E20v1rH6pXnKd88UvcGx/MwXB0ewJN9KJbZv7zvnO5Z2noaTvjxg+X5VHm7WNjlOpFG2xfPbB9ObSKFs+3NAxsYbwZJjvIy6nF3/IdN+V7ncpO2OtOL1yOXMZwS3DRTj8jNtn+NK3gLiVzEb25xMTWooOJWdmmzwGefwvoUjlvPKmD7F9javci17rapyt1QOoIS8+uFEUG3lE2/6FNMGnzfLMTmFmbYskXLt3qiWpnFpp5+5rUDQB13LawzLdIq1CtIPKRmolctEu1IcLJfUVCL7XwO5b9iaxL0B6aSfV4oRYH+dAMidkb+QYloLYCfQv20pV4Q/8O0HasOrrVdvbdJttYGOmXsA3Eh3hS/Gi/USESxXKNJTWQDO5OD+WpbC7tA6Qmmpo2cY8IbkCiCGGg4tZCcveDSTAGaeKLiJWugqzsTWIgwY3CV27L7+XyvXOqxPDX/hVfprK3mo3wwAumft43peEQBSICPcwG7a+Y45nPmcWuFf1Z7Md7aYZlSuAqyVspKWiaiNV9OcFI/XiorgFIsjbnHjAF7gRubtUcH2MUIkeTDypmHSq00lAxFVP+6IxENMsiIQpo8g0Q7Xx+lSf409TxJRu30Nwi8unEYtlbVJTOFvTGay/f33jOV1/kKEZItTp+lRiUS2kGHqF66JSYL2dUS6ANPk50MDKGI97y+JH+35LMcpv5Urxue4RSHpTGTtCxp4hWsDf1Oql6zHbDbFwzIM2rODo1mAhkk2lXxrYWyuzZ3WpOsCSElyRTYNUxkrghwsNza0ihw0TI7OFQu1QSzhq43iOb7KtaxKUGmYTCMVNOM+HmXfgfgR7fsrb+N7RLRc0ny4IIaHtfX0tClxAN7s8jh3F4r++jWn0aVtPT/FhrO9TIy7T2wWlWvx2ny33GCRbcBua/+uHKJ8rcWciVnQtDi/tbJodfSQ5uMN3EYnBiat5lluDRw0jZiJhkGIGEZMfU96SLOvxxvBAv+8VJS+ix6sxzB1lu0J1vMDV8RNM+3o68b14vh7dqvH9EYmpzGejlni+fVhlfLb2t2qYoeu+SNYLZtHeY2JdjXgiBzhjEgMU0KpHHTqSWU3hZgyWqDr9lx3W89gqRz3PSSHZBWg9+AxsjnEcER63GZKd13L/TzC2l1Zvv3kdUib7qo0lsTc3uFAw2T8zmd4dfWxdG3fyEzG0bXQLy7uSxFiMqrlKs5p6VQOntR8MQATeY27Bs9WWN77rfwAw9CUqGOvlK20zTh8Ne+f4mDdyBTa5HlCsVaYUFaOnZ8jAODyYXy1VWCKrmw7i604Miiji3bxfPIdwSdyy7KYnsFqwACCrA+rOdZiTi8nl99dQsaNVo75fD6hGxsJp4Qc5yhm8PLiQYw7+J5yPDlBuiNYshJPw4S8PHsAWb7FT/EcTyrHq/gtbcV2CxDseZXSeXim+CLfPpJewgYXSokF3ZHKkROIvaiQzzYWI5lGvBaPc+saplJpVe1EDXHstftymcLflAEv6sFNdEveSev0+A14y9oG+76XMpgPNw1VfjfQCXscLCNm0rN1Be9wOX9jCqkp/kEoaF1yN4/Tk7VxiyveiV5s7RvfOaojnZo6nb/xAkNxwNivcL39dxMKkppsV2jvqJWcLvDZEMRgMoxFnL3uEcavuJeJxZPZSBE7K+JIMqFORiHXaq7mUBMr2gyDXqwN/On5vo78lUwdpITiY5Kkvf5rH3bSgUe5l4pIBlXk2OmOIMBromtrtNKVS2MD+M4FhP7ZwmwqmL0AR7h5sogYLmMQi/aKknY3Ka+02d86/edZbuVWi0U7kfbi1LqLbLyXtMPpJSayPlk76JgsUlc6Is2iu0DOzZMEXjBem04UlSsuS+YnjnOoFyxzVxUWpe2kqs7xEJ9vKRbbuu6n2HmPy/jg0BmM5TsWrPbTR8iIvHB2VCqZQ2YmhxolD5//msuqPe/H4g80gRuPFguxHj389yixVLpbk3OJtbBapTpNXh6s8UwnM0VEWl7iBvV6DqkZHU1zsiLScjJjTGSqXeU4IkdItkinIBFNg2Fqtui6/W4tB6sFBxiUG4ytaxESIPCj+JVmKTLlp76naKPBBrpzyCLclfOcV35LLqbl3p/9nE8zyhVJIXcWIZ7ySRd9G/+p68PO6lzHOQu48bOG7GYvre3PQ9vuAcOw+SjdzyKZRsIhk6QUnaGIyKexvxTDVFOE09rfzp0DPcTTzz7rO/ef4mA9wgN0aqVKangHk+w2ImcsUzjbqqzqCu8DSwDgc69CvTpDddEk9tCGYSzkSpzBfB+tbGV0r3WwUoQPMomNFNGsmYulwTDZXZnN2qgqMmyvbFyrMLnP6UmiCkc6XI986g/jerWppLWgLHCwk3pfO2Nt+fRT59HIx1YZ8+fiBQbLcAjjXFI5D/EA05IusX87GMvhJ44j0igOPGNdbx7jHt8xd9KeYlcjHsMPjOU7Nrk0oM7IW8A/s+9n0daW3MQUNfIRM2xnWwM+63w79wwKZq5uxy6uLrfEgoOIRk0z0MEyY2L07ctqpnATWRlBo5D63U08RwY11JFG14zigO3dJxD/LWVw4M+GqbGcAawjYMQmeLX635rX4S2qdYDWkkaiihwORrMpj2Q6IrAJKvcyY47D++7It2xHrSmizGJDgxH8zN+Yonx9BMtol+roTuam1NCHVZzSP6iSU7XahhAZVHMc81hWKRZimyw4QW00OdGuitVUm3zEhaRQz2fmWUoUUxbgxItgdbYinOGQCrKPZ9Pvc9Ifj3E3j1v9KdFzDHLo6ur/P9qK5igp/MZRVNYnCwFv6xZkeq8ygMAVoDYSP3w2a1UbRvGTHzvkIhot2vmDUlUr210o7I9gAZTHcpjFWPYd9L9TGZGXjoX7PZ285mluWiz0WINkVOoa1QXtp8XD+Y6TMUydDs0qydaqSA5oRhJ3pLuemV3VWa/OdT9vbo3XFpWKttrogch4p7urBizlzRZ3ErSR3b91FZaSSCpHQCHE/o8vFVWyR65/m7t5wgb3B5lc+D/CfQwuEBQQXXJUrdgD+016sIGzLdpt+R5nr1YjgVK8YUu0A3v2QH2DRiXNlDnbPXalZlgOluueiljP6NBcYugiCJDAwdJMgySc1GHP/DJWHWzLqnpn7t4bESnxF7mRhliY7Gz41cKFH4xk+VKEQX7I4w/6o2d/WorQh5HxDCbyWmOe9G5JrRrlqY+GFcJD7zn+iWCp9jpYXy9rSzv2UEW2svoqIy9u1GhoM5GW3I/giULXaZ4VZRBLhG6cYSqVSwBJmniRednOC5UrslHJvyifgywDJ18fdjWKR7mHt7jSt70s3Z5VP5IJE2Dm62JSKixoJINqjs7yC1LqGKRrdby0/gTasIcxR4iOsnVPCjfyAgY6z6wVObillV0YxU82ruDnXR0DMS3b6MyPOMy2UcJKOTRAn7QtnJvxnd3x3A5WQUa1zanVPKk6IZO723lw+Jtcz9QwMAj5I1gGlB8Ks4o+YvD/0J/SdEewmlHOc9zCSvqxk/b8o/dbgdcjJ9OWocR0AIdqQxzDgkAneg29/keZ3HVTdbDKTRe1h+v7sG5YWoR+PiqvXRBxRWtd8fKmOlirNyaTTwn/tCSfpOVRprzrxwd/LtJqTWFyN0Rl1ydM4KLWAlNyB8L5Hr/rOXu7LYtFSmbKlGAlh9Iyjct5l685jXOZofwmI+gqBst1/9bzdFfFJSS1cuk3LnE54wkdLHROkGK0lv1RloY2GY581yelo/mmTOA8H+Bhlm3OUVJLQVI5bpu3s2Pc89gRJM/tuDFYd/AUYwc4RQk5VPIcN9GrQ02gg/XyoUvFIQMekREzCRGzHYuhXQ9yjvUO3VHhltkNXIQKL3HrBAK8snscu2gv+oRhJozUgQpyj2feNct0zmVlhcB1RT1QEBuOZKl+FLUoY0SKSplRfcjk34zmEt4nm0rKIiLqLOkMElVgx0zdjmBVNDgVpSDmubn7ghd/cow7gTk0RMV5Tmi/CYB0aujGRkdOje48wIP07SIaaFW96kQ2S6njMt4B4PXXISaZ3F00DW9ytf13arpKdg1inhSYO41QCNZuTSWdGhatCihIiMVIoYFzmc4ihtKhWSWT15zH3dv/Ym/yzJ4L7L9fX4ulGXEAACAASURBVHMM6LodvPi+fBid00vonrHX9UD889M/LPUAt/0pDtYOCn2rLfkyZPrIlsrxDDIXrr5b+Tz1tz60bdxKoMVi9urc62DJTns0v9LXynvv2SMwJDL0fjpfKTQNvlWorjOibzlLGEJuTsyqRFAf8uLul2CicUJ/x7uX1yLLPKWz3bvQnwIrd+EkJOYC4D4eVQjypEmn61gr731otQXI1g3asJckzZ9mufGoJezP68X+uiyyqSI3R2xTWRNmBudRruXynzJRwXNSWyHcKdMtQazEQSaB224zYgJ/JQWz3Q6WGY3RgjKSaWBk7qqEkUp39WlQBEteq7dM2IwZfL2sLf1Yxf08TNUPKj/RJCbjjmBV0JxnuJUfOFFENA4zkqbp9TbPTZDV1uvUkR4oldOSAwkrZFmyBFYeXr1d2sPcx0EXx457ETHbxe8U1k2MSIw9UVH1mSiCtS3iwt658BJNTcVFIv7qUhDp6g93jfDv8Ae0CG/naZqHVUJPyeQO8M6V86mqEoSJV1+Nz9yEvfGcCqUC1RR97gvOtKM8SaGmPYejCrbYf3+Bw193OAfLa38kBTowdS2nd3JkwF7ZewYflDrjSyhJtyJAol9JigQzzrNItBCQ7+SilqoO6oFSZ5/NdFMiAk+U/4WbmEKnNg107RjlVL5RzyePHSj4K97b0OQVtM2qpFl6I58hMGTutGf7/HpeZ6LnPjzHsiWjNIwAnsM5HK98Htl8BUPzBBt7vKhlvSdKNp7ptgN+iYcOJhIV38dc+rfei9y2K8yJ/Juh951E5d8e4K1i8R7tYiXNjNuPDXTCHgJY93uYsnGsdxcAPq10jVnW9ci5rxdrOZ6fFJqGU/iWFrnid++1dMipsN/D7NnYWDypcOI1WypHYjNNWMxQHkt+kJgZEkORLsbWWED7+HltHhN5nQ+4mAqasfdQlkiV6q6Is+sZ7DiUq+DSAJ7u/Q5T+ky1P5+1/VnuWzhOOU8kAA7wpzhY/VjNb2tUbId7sGrLbv7aS6w+veSC7kESsFnAg6yi3OQSa4XiZYWVUaMDtLTlS7wr2Z6sow2Ol7qtxpkM+vO7YJZ2MbnHYpq/Ss/mPnCuUZ57pyFwGTJFmJ/tl9BwY62896lh0oY9ynnkACjz8e7KDIkl8JkFzteko+KRynkjdjk/lvQRx7e8ITmweec8L/mgxP0c9BDoAaytac+PDcfarLnuFa1hTRYPMolhzTcyfuvj3L94nO8YIDjN3jCFY+lEsqwfTRMWLOB1rmF4t33KfkbM4cF6jHu5erUTSTHRmMyDPgzWK1zHt1iI+jgTvnzmA1LWMYDfA7eR55CWZOHY0q2IpYlGXmo1LcIVgfu2H5LPoP7xSUC9VuPRnovXZ0K6wU/VQ6m3KB0SRbDcKZ+X1x5nk/I2lWg0UOkemMVYPt7jOFj10TBH8hs/rCg47DHlK9lNocLrBCrPU5+sHXbX7VDg73fuohDvsxrFj3RlE9lZzvX/0P8O5jOCFfQXKg/AVT1/tauVZZu4L0AYOSPsxzBCYocpZupKdBua/txBvDvdFWHTNJNMzVlM6iFNOCNWR6qKOrih4HVFAmcwZhIiSupRKtFo62Z1Chmr2yHZEim0LkQPJLuy+3mA4zCkXTF3pEzhq4KJXNlvqdJPNTdGKhYjHTV9Z6aq+Cgncqf5lTqA4z1ksvd3/oibu4uq4E7NRd9NS1HfSyygT7XPEoEAtzQb+J/qsn1tmFZ9qvKd3Va7doYpUyhIEsdKz3SD3H2nBCBfKyUnJM4p+4OmmYxkLrmUxe3/WxoL7b9/K+7IGH6w2/E9PMbFfKD074RSOVGnj2nVh5z7CccZo1KTuJVn6NVa3GcsBmFivBu9yGrXLvLTANjm1pIMPuECYoQ4iR/495bOxAyN9HAj1/MSR7CMrmnOvK9pUFun2XyP/TO3iDblikrvieSzvy6YCsNt/2tVhO6VyAjmM6D5Dut7dT/vC5cs4EHmjojEi2CBM9F5U0he/b83djqabSvpLxwjnxahZ5CTrcktlWM5Lq/UXS7OmyQ+99z+ne8eHnfhm7wD/X7yaYVwGrzPU07sR3QUjXBficYGerCl3l/xJ7lD6mLJbKAHm/dlKtf5fvQCW3styQIa20SjngiWu5x9GAs5A8G7teDtjbx9rRPanswkVlR34S8HH7MfYVo4whAW8wkT6JBVTm9WcxKzGNRsCzsaW1NcE4z/AGhlOXJOBMu6rg8/RBt1PNfwBiOKSrjNShcBpKeoUjl1MSd0vYCjmcE5tGIW83Am+610savuLl5+a9zrAbiv+csUscF2MgewXN3ANdJIepJTNNEG7uIJnh06jS+K1IittF2095ESJrJrmEozK5qLacZNg4c9AtaJIljuvri8zCldb2qKMHGExjn2q+tHsogjOVDlXxH69nN1v4UVKqYxw+VAGGho1SLCdczKV+Je2yh+YhoTbAcYLGFiLz4lFhOpGFcfbZFeS2dEdF2OI+1xytulxUs7JQrYGei+d9hk7Bvi3bn9Fg2ncg8glKQpzoh7HAw6T5dm8dPhEhMVO+FE3w+SUwzg140OaL/eSGEBR1NZJ+TGjkLQGEgdR9m/gyqLjy7cxaS0p+3q5M17HKfJncJrqDMoRsUDDTtedbBips6JzOLTdrcGcv5t8kiDuVNF/QpEv89I8UxiAa9J4vV8/dLa9ilLzuqLDb24o1LFvNo8X9Z4PThrPVlU0TxXfL4pYyrD2+/wnxRY3Xw4d+a/A7joHTSTDuzgWH6J65i5v+6WU8JcjuPrbYKqo5BdlNJCiWC9y2UcqBRjnPeYkQjcaSlcrF7jLCziRrCSQjzD7QzuVKbcv1wMhUKuLFHA+CW3X2RVVu87lEHM1AjpJn1ZxUjmkR12Fi+aJoIg1RZY//hmy8VNuDpQU1LD4hr/JPN20px0ZzV+Pp/YjbRTSzXM73WwdN2M62D5ynOV/VzbWbed06CGsF7lWqVi0Vvqqod15q3KpSPbKC7GD3wDrt99Dxomc9c4fFCpaeJaTksVIfOkZI0MqulZ4y/nd9tYVJB3DZksYxBhIj6+lI8ROWR5PWXl4h73NvrJ2T5Z0ZOLK16kOiImsPW7hYPlfmaSjXxZWUdAjWBJfAA4BLE9WcvR/MpEXgcgPR2FmXoOo8jTy4XyuXWe7m2qWcwwJvApKTSwlt4MZDnfHRicsAFnUM0V+rsA1CY351h+dianXY4Gl5YUJtUaoKdyNS2aRZVJ7LQWTopwJPM4jxmksp/h/Ez/gEhUSRyOqla6aEfl0Swu4BMbs+cGVnpNcq910sRA+AnnJ0yL/lFLp9aJxlqg/24W1YmbDDC0f6+y38qSAqZPDz6m7DcT+ESBGP23Ujluc9/26nKLA69pLA22La508CNd2EyeXmZzjlVH05w0YL0fvOSuaC0nlyNYzgyLIDTQwTIMNoeKeA0Hx5GRGvONTdlU0Ymtyv0NytseeC89CuMzsxvo7KWN+t0fiGBdm/MJJ3feaH/WPTQo+3fUszHvaO44ZgEAY1s4AsZBDlZmsh/Qa29vYZcqPMHYS+7rwM0u/GFJheNAHzByOZYFLNucw4HyMP/kbwCkUo+GYTvggW1C6sRZgKtVO8TEOJbvFJ6q31Zn0YZiXuQGtoS6Y6JxdB/PfGNotGcnRcnbOLfHat7KVXU7j/PKIbn6bKvsWp7n73RoqbavQNyY5VjVoTp40kGQ0b0g3kfbwZApQdNUMhG3Z77KqE7b/CcFiMU4K28+bdhDRrIYn3TE+KBhJoxgOxdg4tbi+5Tx3MmTSgTrVa5ja3Ga7/5f5joqa8I2DrMylmW/U3dVn9s0ybcj8YHW/b8auRLD1Cx1EOvSAtqHe/EEEJk9F8MQItHX8hrPcQtpuhpVdgdoQprBFctv5LqV1znXRHycm3Kcw27xP2Rez7Jn+xo+wKEQ+GWfWBkM7azyq8gX/iAPAKBbVAJB5n7BXoypfAH/4gwWcSSmCUaJygosQ/32uT0PUNM16iMhdtCRSER40MkeMr25NQK02mg44TE9rNOGPeTqlfbnNOqoJn6I0YtBcFuUJLuxSamhXRTyLSfTprkIgcvnnRP2C0pvKm3OnIZjfJQSdod1rVfKI5nK8WKGRlvU6q4ZM2Advagn1c6t62FdAfPrGIJLBNPGYLlXPO4Jbld9S2VgBIELLrFYB9zcZZppcC+PMrHrHOdY6PzAGIqrs+zBqQM7hKPhmizcmooS82AAU7mGFfhpPeINPs+m3MNT3K7w/Mh7dtvofo5DL4sTju+2m8lMElI+CYD9x/GTD6CbyCRxqvggVnrj+ZSRzFVIbFvHdttt6CMu4KuNPRk/Ps4xTY27enzBJyt6oWsmGVRzM8+SntpEB+sPVsk1JULTLEVMZl98oa6ypdyTxDTO2d/bfrTuvmmfy+OsFNOaSxGg/l85RvBIlTtnuGfb1VxuvEWJFRH5F6dxMJrNh1zEKczk5mFC6iqJCJOZrIxH2w75Fz0tOEBuZnDqEGBe0hhbZUKm5RNFG712Xc5HnNLVcbA0DSKGM6GlNlaRFa4jxSKRvKKtg58yoobPS/BCN9wmsUvXXgs3D/nF/v7QlpK4+0R1Ee3QQxr1jTr7KeB45qBjcCEf0SW03Tq2/57LqlPYanbiqD0zePzXEUoXUqRyrH3/ykucaXxmfekpvsKRyinKPcCpGXOV373aq6cvf5DTfxFOWHpShHOZQUEzj/NpXcAT3GljZVcdFMfxEjOP7ScWPDIdLGgaEjtYduZFTnJNkMqJEbIX45omKua+4sy4u2XpjvNvGmoV+kKOZBPd/VJYAcUK1/EqhZnlynfZKQ30ZG0CevswOynkUI2VJrb66tpYD/bn9eKOkYts2E2goHw8kXlNYwiL+YrT2R9xsM+aZtrHA6gzUiiub05pJFvZ5v9UBMt3MRbfCIjSz1c2HG9/Ly5M/G+gcTVTbckT4dEHNyCvFpLbvC/7pZf8c1kntnKPxW8C2GKx9jFcToNpmDx3zGcs6a7yTDUaSf7zacIptMnaNC0hmBYI5JqSNpz5tkMiQ+nVZPI8N7GjNAO2bcOoEY7WI+1e8+0fMzShpSTvK4DJ3d4WlYMkaEyXE88cRtmK5aGwmpKYy/HsbChA10yO7F7OR1xAqt5IA8k8yj2s3udMOt/sH+JrwO++GaFtW+sa3OzYsRhjmcXwFiIitG5/HmP5npP4gW/XdOBR7gNEuXksomoR2rfpOlEVXW1eIq/F61CnJc/idp5hXMkbyveLPGz8uumcXEa5Tn52jH0/T648mau23ht4jsMxgnttHiOdSjzDoCubeZnrmcdxduj7aW6jJQdsrqYT+SHRIQWgNC8X+vVD06GIDTzLrTTLOjxfFSR2mNygaTsd1IQB7PqBizA7duLMM6FHuhO93E8+jY1qW5YTwvvFJyS8tlP5hgH8Tq2FYxuHIORtqHe2mVMxiN9NQSBawD5O4xuWlnZgLscxk3G0yBD9bzrn8S6XKTcTpK6wn/yEIbvBLGE1Ahcp0/J/JILlVZ3QNYMVDU7ELxzGTrF5rzEpJByO3jgg+bK6+PIxg9vt4/aUF0hNhZPOdCI0OThFPW6GeHB4C/WQZkcPaklnGQN5j0s4MTyHbCqZMGy773yvLhzAURXfcsDIpao+RYGZHNV8HQNyttmPQJqPRdyymKkzh1G8cnCC75kFmbtK8ZsNXWnHHoXPCeCE7rt4ietJpd7WwdX14MadmSzG/et5xdouQQTLek6flY6khkwqq8Uz3BLryP5DwQLUo6q/YkbFaFpygCwrCtk7Y7tTKRtnETkmw2Gen7OniDrSbSqlny1IRXZahCNxtpML924t1VCmF4s5YchW1tJbgdW0wkWJEw7TgZ18vEgUXrnbfciMood1ew4LwjF6YUe/cCyGKeARSxjCAVqyt9GNGVapQl7Ze7rFg+VsoQcyJvrtz0sReu775FH1XMjHAGynox0tarCcfxlCNUyNCEnUWTgYW6om8EHGv+XWeY2czWf25+JiITit7O+ZxAqSBM5ASr24ZRxMwwxkct8SEdgUN9GoYWrsozUrIw5L9uEcrN8DIijSfmYEjfXiOmUaqCUH+IGTKK9NoW3nZJ6cKCqV4knlhDTDrjC0V0IuojppXZuVchePk5kmtp3c7wtFCxGg2W8CR7SBHuykg32s9vn1XMQHDLaINZfW90LHpH1BAxfwCb9vTKclB7iPR/l9nwNo1jR/jnvpC78Ri1lthFRuM57ENGG88bGo7LE2rqhLsavkbKZi4DxmsHl7WAHJ/lzex3kglpVzhO2ASJPM7IcLn7v1rALN6umjXDp3US3JjmZtPdSSlbVdA3etoJmCdzuc2RE4SwZnpQuMLe1S3uNDVxTZWzLutSQtQlJY4jYEoeYrXNu0XB6QEo7viKlM7k46+rDmmgT7Z2y2v64ih2UMdDRO0chIEwccnL3Jd5jWuQ28jEgBjGa2TVYK2GLNXqLRMOr96GFXdF3egxxTXDfz4161FP5IfuN9LqH4QILnbxh2FbHEdeXnBkuWBNmmhvYK5Y2mqUUArXIbuKPyXj5fI3BsFY2iLbdhj+B6ihqssRw8wI50BdnRhbt4MF1gbMIDnH3cnE+Pt3hWhbRZ16KHHMbsRRyJaY1GPfUNTGCawyLuMomVkikuOQ98z8k8WvQ+t3fza0kW05rj+InlG9Q++2TrKRSyiynll7KiOJ+v6jw4MsskRtVNNFrbKBbXXmLNvq1LuZgPuMnF/zay7RYCzdPoNc2PxfVGsGT6VNIcjDnwEc8vDJZaWxA7kk/KxpBJNVf1F+Pai0UvcLulkRhXKsf1fWPMz0sF0KZFI7M4iZsRhJtyPhlZJHDDadTyI6MoOeQZJ+0coXMOBbsYCqETc7IoVnBB00y7/6ekQF9Wku7Fv6ESz4Ioqrkgfw5nthP3fw1vcES28z4KMqqVFOHWujZ2KlKa5mLwl9bfi7nlfzFF+L3hlH0eIN9+gR8u6KhsNzprMf/idPohStTbt6jlVL4JBrMlWNEN7F5tl+4C9O8V8UUky8hjh+UggBNClysITXeiMrYWYZBkOJ4IlrXTimgv5ysMGklmxgy1ocpVolcouAfruAmH18ddVg7O4HWoLkyEJBprrfx6oIMlQrwP9P5MudYuHaIMZCnDQktpjnAui5rv53HuISdLnKdjhl9sVVstaC/cq5fsbBjavYI7edKeGKJmSJT2Wg++vs60sV7RqPO8cjrl+lKEv2734E/QMWIm0xnPp4xnaZl4bwt3Odu5nVwQ76xXfhmFVudtnyJSFu6BN2hdIqOE8RysqY2XoWFSZ4pFQJBUDsDKbdn8jSkKUetPK/N4kRvZTbvAdIC9L/2dasYmmM3ibvjTO9IMdGV1LAsU4tnG/OFMHjUfcMbCm3muyVI5Q7pXMg1//jGVOuW+vSmdhOZysCQu8TcrclhDJhOstNr49r+RkmSQRCNtU/0yL3nZEa7jVbKo8j2XYZLR2U00auqErAVKCa3QMNlxKI8oSdzOU3y/SUQEvmEcsxlDQ52z754aJx2RSh1l5HEZ77F2h1r56banY7cQKxLjxzTOJ5tKMlKbFjkEOHnfWzy35Fj7831dp3FL5uv258x0k+l141haLPrPlasFp4+GGOe8Y+uIwjgYH1DeyZHDnHdY6mKin9h8uj2vFrHeTmfrYc1HONlAmPHhz3mdvwR63bGYWDBK0k9lbnCl3d27NpjJzOM4yqvU8Xt0xm8MYikGGp+u68tNpcER5bCFQ9V1Z6LdXSkc2N+3eRZChsEeT2oxL02ktgs9RRDLtqo4T5HtU8eEtnn13M9DtMwTN9QjVeA4JUg8kU6egU6FkcVCjnLUTlyUBDd0CIammGi0tarqorE4C01LKkemsu050DTpwTomMI3R/Mj8HR3U/QIcLLeSApqmsNPLtqhhcln1S3y7vjNt25ispD9H9vBXYQeNI1e1msn5nRfbn09rKfr46XzFXwYsUlKEbbU9Pib35uFqMsNqNfL9POI7z5/iYJ3NDFo1Uy+mBepEbZfHeh7GY21epJxcNlvszGP6lgix2YB0iRf4rZhXlPmTafZXHS3x1GqyeJ9L7W1CpuhER/OrXU6vubQIX1h1HHfuuTH4dG4mdy+xqCnWZdM5j/POU5UV4lV7fc7ZtHQ9M9nIJKeXpEU4WJ3MAfLtDv3UXr9UjqSXsJncrQEtKVmjDXtJ0+o5SQLsdXVFTiwm8Ewu+72yE4Cy6m/bxgRN4wy+st9dzNTRNZPiijQ+5yyFGy1qzRU3XXSAf87sSla4lrSQH0j7H0tlJplG+xm8xrU8uf4MAOpcDNOhJH9ofVSXHXzBWYCDT1MdLH8buoT3KWRn3NXd7XUPiXswxco1Hh/O3tJkpnATw3A6tl0qjWlRkASf4xxmcIIr8nU4e5j7BcZswQIYOjRwm0t4ny2uqqhFHEkepdzKM8EHdTsz1mU2kMqOXU0cRgzDphNx270p/+Cpzq/an20Hy/0Yi4sdCmiXvbRkGKcWC36a6nNE3w0qgskK1yOpSwKdWMNZsKynB2twxIwlZs09NrkJG22zns0z3M68HR0B7DRjkA4eCB67C6xIfjyH0jRM7uApxg0u4Zyea+3rbGrkEMAwdSXFMTxvLUNDDpC9LpokYAPWw5f3FiVMQ53fwUqUrj5YncxWa4Eox5Zj+MUeBwABm7AOMYkH+abZJWL7kIrdvJ2nyaOKlxuv4hpeZ/46FbMETgRLl0zu1nGzqVTwSO7nK+EavmduGDZ+L4imwWvuRZHjH6jta3tppi23JC2pQESTf0RNV6/aKSqne7HGOb7neO3z63mISeS3FNd2XJZ4j5KaSOBdg683Rsjmf7L7geVg9WINp+U7ld933QVHWwHgken/oZ5UsqkkVWvw3K917IhBLWl2JFy++z3l6URIYpSVCXp1xVHKfh8s7GqrQki7lPcYy3dstlKXOobtOEuoRa5WzvTIGWw6mKvQJ3ntsiFr2aA5UeO27Palf+VeXdhCRnJEaYNmfYNVhesc+1+97+alYe8p5xkz2O/c/SkO1ttcxcBO5Qm38Uq8+H6QZhNe+FtQ+9YJeIKsh9kSATRuKKth737RELbTKXCXfmkilfASN1ATFisLd4pw2YFCFlT7CTUBxQOW+wxMFp2G9HR0DHKzxYSR5cpIXeWS8XFbT9YroWI54EUIlqyQqZFt9W18v8kUoQzL25EeXecR7uOh1MfoblWc1RvJbKIrkQZxvi92DFSEOAFWVokVSb2VxpXHMtCVSNypKT9yY97HLNmayzl8zsFKlzNpmGRyiGsmVNGsucbMfvfw+lD/s5C+wqX6Bx7iR/+kGU5Sm7dM6/axooStrBSwOnmo7e1cptNrSCZn8zm54SrfOQB7PI1Z7yeIZFWeZx8F7KU12VTyzOnzlMICXY9fxaNZlT5NNQF81THvuBNj9Rr64icpdROOSruMd3mG233fixtwBqVHjv2e9paj3eR53jAYzi9cwEfK1wOS1zI4c71ymmP5mYlHr3E2atMGbvEzJe85lM26RjEIFxtqCX6Gi2NI10zqak0aSGVvg5+jreqQxhyOp4EUpjJRATO/y2WA6ogbOClCufhy0754A+zuidztAM5mNA9Z3FlxHSzrvCnJJv1bi/Grgua+Kr1EJvmCbNN15XxRM6QQjbqjc/V1ps/BSpQuf23RAI4sF9WbQbhOgHUNne0J8wAtFeoB9+L0C84WDo8Bb3IV6/f60+RyPJO4Tdkew0Q54z/3cf6SW+G++zAmTXZun2AH69vKY1hJP4vJPb6D1R8hd+ReqMbDDH68rIi/8Lry3eb+okK1qpVKLSKfiYyQndJjK/9Iu99/w2DPhXZ6NewsfoKuxTQFfllSs0xbL8apS1ffwXPc4nPaaw/WUXPQ0nw1Ncpowb8ZwxltRYS+babaAJevTSGDWo5BFHjI9/jL5lZsoastPeO10kMprEMVmTcQhWBdLNoTzUUYm5NlcDQLGB5eiImGrrsA/gGDUXZyPR3Du+3PQ1nMrroWlDQ40cKaqJi7fuBE+NvfQNN41wq2tKDUh8EKLEgKeOh/WorQe3IfEWKctIBv0PFGVNwWi3EDLwae/qcVuejEbCbp2ft6U1UTX70e4LTseYDFNm+dNyXZpIB96JppgcWDe5XEqgAWqD3G8WlWCi0UQtc1otm58mfbRjIv8HgvcoNNkApOR9zo0vpzWwr16MTonOrXczNMMcDMLelJOjX06iI6UVllmHe4nDTqbGzOwpJOdGcTO/eIZ/Xh9mPsCcdr63BSoIRCzFyqTnijk+dxdcuvHKmciPOMBudt4xDZ9OpuRSk8DdgH9DR1j3SJtZ3rsYc9vqcRM6lr0O1ntrVOaIQpjppnZT6d8WR+9SHPj57JVz3vCrxvOXnIwoSIR19MWjRichZfcCEfiaIH3ZmApusTCOn4yDKl/c4ANuDXroxncgIxDeGYraYv/Vvs9m03EbUIYgX9me5Kpbvt4soXmb5GDIQ5qQ12RLWpYOuFa7MZyFK+QSWQ1XWUd/3iwLf4mtP8A9jcub5jiuiFeP6PPgozX9jK0VZKt4ZMpnE+AIvKunLQom5aWuXHua3flsIJzGERwziPT5XfJK7QH8ESbdWWynE7WB58hpcFXpo7ohfPwZL7hsLqhL+3JPH4pRzD1BUH6+eDvZnX6OB0tpdmKrp6boFhI+qPYL29Kj4nm5s/Si7eBvA7Z1kadQBn7X2JC48Uk+dq+tDC2M8t/INWLWO+iL+OwZ2ND4sFQ8C4H7PagI6JYcLwrsX0ZC2p1BMxQzTGwrz96B7u52FOt9Lg8SJYN++7k1mMFRAEM36k7qfmwkHStUSUq87z8JrES0kaGe+20sEa0K6US5KnKdvU1GqsoweNUXGM+liSckwNk+0VzZk5EzZsCDi2FcHaWy2c1bKo+H89PWw9T4AXpqaxwvReGAAAIABJREFUckOKfUyAYSy2Hf5LejhQiEJ2+sDrrQvEduU1Yjx8lesIMqmN67bvOIUvOJsvEZkJJSpnRRkNBOZR12H/wTDd2cDcFc3xmWGgh3UbwvIFZ3P+hsnctdQJFDy1Q0AX1tBHLOZwskmb6Ebz0CFykl0ktQFe7ILKPnjtT3Gwoui+hlyHCnSTA5K3MfbfoA520xZ1JI1aaqsDWq1h0IEdDsGiywRBqW5XJ4ovnT9NE5/WV9RdimyNTkf3q2YfrencrhHDdDqqtG85mQv4iEFFLnoEq2rQLTvxZs4tXNBntX1uaVJ24zUm8rE1OQDcyIsKD458nu6UptsyqGEYi3z8HgAPDpnJwq6XsK++GdlU0SJPHOtQjc7z3MxOs5BdCObeIwoEiN5N07APVbzUR7YK7CxO8g2UpiWVI793O1h2dEDOAvGWYfL+0Q8bwQp5KkdNw2TKL4PoZ6VVixuEgyuPcydP4B0uX+cayMiAwsLDhmp0jLgOPkB1rc5CjmIexwneGdfCq4+2lpBuxnWwNtONHXRMeH63TWYyIC5ZOgCDCvzOtndg+5HR3MgLgcec1Xg8Ww5aQHnXbN1UwsvKQzrLGWjj7qT9EjuKr8uc1W1WqJZmVCrvfwPdaTD9jqvgohP3EA5Dm4JgXFJJQ44Lu+G3REzu3m3EeTWGpK7mTa60S+rdDpYXIzqk/T6qdokqum7ZjsLAU9wRdx/7XBJvqWtKn/rjTO7O56e3nMWTdY6SQTisRgnc7dCImb4UZyKpHEk0CpCUFmbBVW/xJlcpYvCaZpJkSbZMZSLP1V3LP7iN9m2i5OZpDMRJX2qYdqQ+iKlbRLBitEk+QE5SHR1yD7GOXuylre0AXcnbLGcgX3ImAONSZtv7ep+TvD8jYAH9GWeLohprVdwtax9FrurVeM/DaxdeEuKmIxdye7mHRNRqAzapcECkZNGaTHqxjt37RX/4rOW1YlNXtHD6hn6MGwc9XPUUsv1KklMHniAsShI3r1OlhKR9esjBRNl9xXo2hezkct6x1TikNbd8He8w3il1r00gK3+PB6uYxIP2PdnHMQy+5RRezrjDdrAMU2MT3amu9ffdORvb8nDsHlfBi3i/Sooz4PRHW5G4duzmq15388KRjnbtrVtvYPKKs5Tt79z9V98x/hQHK49yvlzYKuE2EzsIzI9XCsF734apUU9aYBXh1h0h7uBpKvB7sTJqIgHL57RfohzcMOAkZinO2eYUB4dxTkTgJNwpyqAOGCZKASU2W7u0KEkcMh3eqxPSfqWiTqwO3KuMnbQXv4+I+qtH0GltVQ3GG1yVSgfLy/daeqiBZsm1olLPxZ8iQ8w/REfZpfs5acJBs4lGPS/kAj7ixHw/KaeXpgGElt2Gho729+5B2568rB/v2nIND612dNraJqkcOrPMMYERLGlHsIyeHVTCPyOm8mCtqRWp4ZQkgyghHuMeXwTrRf6KrcUQx+GTg0MhuwMxRtLcDuXL4b8zutdeB9NnMRLHc7D+qO2y2pERc1KLoZD/+te6o46WlRDcV+VgBvDl5t4stYSKm6qJF88/XRbtyxO7L1I2vIgP+G6NuAcBkt3AdXvuCzymuw/Gq6ovyi62333nNP87SuRgNecgvVhD+1bOYmVeu4t5o9V9rKKvrWV6cp9ddoREpo3u5jEANkY6M3+q6Og5Sc5K2B3tjPd8bAcrpPapP8LkbnocLF0zydaclHdhl2QbwwQqR5YRNXyTJwiHcMPna3zfewHB5uAh1JFOVzZ7NnSOuSA2zLowUXJfgNPfxTsJeXexbWDL3ZyZ+SM/dPsrDw7+Wumnkp3+FGaKz9azeLS/WLh7n6Hsf/Gkcs7mCyGXYw20D/ebzktFYkHSsblwoH1zVsA1h5M0clIbWBVRK0q9DuT2imb8GBnh2cZqq9Z4/cHM5rzzjjP2x8uqSBqjkGsNK7cvYB/NORg3GvdbnVPVPntfH3qz2o6E/Y1/chxziXkhklaDy8tXI63b6tvY6hgAB2uS40YKtVQxD52rf0HXPEulpNikiA0sjAyy27WE5JgBD3vR9la8HFEFSCWm6gy+5BRm0jdzq2+/QZaT3y4As7WypjNrK9XCBSNg7P7zqggTjAV9Wckp+VYpvE8qR71EN8jca4nU5aWDJSvacpL8k693cL1rm8PSPCs22jqQk6IUKUL1PL8zgHe4PJA0bW3EBfLUdVhulXVudgaeq3hLXE/LAt9AX0OGXb4ar4JodB+xOjbQ+ZVjKI0EsI9bjaWyMY0SWlFWpXJ3vdF4iS0VInlZ3BGscUnf8xS305VNFFBiTyZHsMxmKNfDuvII7uNhZkbGcNn2yfZ5kvQo7djFVK4mL6mKsXxHcam4luXVXW3FeYARaUtoRTHPWhQRyTQqvGdyRV3UUuSBZnKqz8HKTI0qUj9Sh0wzDVbQn6UMIptl9jkAVtGP+kiIZ1aP5arNwTI20sGaHr6Akcyzn11P1pJDhY3Ribgggpdp79G7Tbndnt8yr+DJ479nQ/vgsvA/amP5jjRqWVzTmyEWTUYooLfPZ2STj+lOMy3Y09H5/tMZznI10f5xHIK24f0KpmfqllF8xEVs2m9JJVmDx5I6vzNoGJqdIgQV++i9dukInlPwi/9369qu4k2+4GyFp0lDSA2tn+IoK+TrpTRLqVMLO/LqkUzfcpwf6gLvts0Tq/Z4hQzxno9ciLg119znaIr5pHI06KWtoyX7OZ+P6XXREapun+e6DE8EKyeljncun0uPc3qz8TuVckASUdrnstq4W2fVRGPuOoeapd5IYSeFRGI66LrtjBWwT+UyC7jnCd2W8VTr52xA+9YSB36ia2Js6Mh2jrDoNvjyS7Qpz9v3pj4nnfP4lLeb3yIiY56Jfx8FlJAPd1iRRxd32Oiu2/0XF3DNZoeOtuSity3IbaWm5WerunF2nUowbIO9rXG0oAAuc6E2zs50lBoGD3buLzlsEEPn4k6Crd/tYA1mCafzr7jYOjdEo2/mNpJp5O21AhB7HtMJE/VnqSyR6/OeC8ZeSZv6Wx+fg/U61yif30udyCm9tgNiobqP1kRIEpkAV3V/UIRTRlR/ZJT9ncRUdWYr3dhk6zm6rcYiAh/KYp+DFbTeDurX/2s0DW6tryNYbresh78frGznvehEhGLxxGTB6eQyr+r18o2YycdcQBWO/l37jFJnf6uTr9mewXDms3VHCMPUCOnqdcgI2qbdKtHbFjrzav4D9uev6k9iSZVwuMxyP1r1+739bOFqaRGSWcSRdGSbT1BUWnJYZKZPtVZsB6J+B+vjDQN5dN9V7KwVK+/txWKScPNgyZX13lqxv1xFG6ZGUl4Ot2+cyGa68RI32J1yAtN4kjvtY7nBquvoSRe2KlI5x3XexS7aczVvkqbVM4ux1EesUmPUBjw++3ve5gquRVSbPRh6mKwMg50UcgKz7W3TkyK04AApNCiT7SPcS9d29cpgd8loK5JhGBzLL5zELJLZyzU4qukgsA1bDuXze203gixNExNnJKYznF/sZ9eZraRSb+Msou72aXXY3BwrTWJcKTiAgkaI/8LyKGMYi7i3+K+spq+4j6ZDdgLNQLNZ+DXXTP/qh5kMqpgdZy/X/gEORFt2K0BhgFklYrVsmia8+6594cmav4hFRBmcl+qNYF3Hy+jERETCk9oIuraFiAqnY1hg/xYjxAZ60Ofl65UT7zdbKniyUJJD72BLkrogCclhcZ3ndgim8ehbGIxalwsJPaTRKc+JOgVFleLZ+cmfM6CtU4UseeYOkM8nXICma3xdeAN3DRbv8dhmTmmzGTPITIsp/G1poQhr14l73b/NI0LtiWDJ/r7WVZlpmhrrXID15RxBB3aycVca9Q0aMywcYHPK4TAOlj35Wem0OetEKvJkvrWcRrHgXM5AQkQp738c+Z0yqCOVUweq0cwYOj1Zx6jkBZzdcRl3tX5X+X0wS0TqKMDBygg3cBtP07nAs3g3RBR0OPPRibEu0tXZNQ7HVZolSq0HaO8eThz5kQInxd9r89f235oRQ8dkXKEA6LfJFjJBkmsrboWtx4yYyX7yqWoQUahpTOBMvvRlVfYftKqqXVEIN5G3tEhM9/XJc5kh9pXv3k23YZ1nasOlAvajO88ikL7JKoIY7Wq/JoJi41lu5Xluts8TpJZxkFyu3nIXz6x2qKWCpNyCMvx/YgRLPbss2QRIoYEVFQJIWlrt0WayXvgVVmTH8VQDHmQCTILs5OutaoX/lHVWMRVRw055SMsKOaF86WFX14f5heHU1CYu4y2tUhHWndmmkPPdXXmnXVWRmuy/7pXlASLNlm2nU9zla1qKVT0WZ5UMMH9vVz6vGGUPWzY40tUR/oGo2DrYIFaDjhahlbvuJpyNCMksqRADxgGcCSeU5JfKMU1TcbAUDJUsk5ekp54GXJSynbHMYruFQxI1igaF7GYir3NRm58AOKVoC3tpQwkFVDc476A7G620rigAGKot5tz+okq0usqgjnTKycUEPwg7rFvXE/xM706bwmQm0cpQdf0k+aHUJDyraJ392/fGieyqyKJ3l3qu42U6ajuEIxEE2EDwo/3dpeN2OJMD5pXNHWBxt9wyCtgXd58PufDwx7Teqa6baBicy3R2NlGIOqjP7qEdZUZzzJpaqLciPDZlC/Dpp3Y7vS73U9/+IS1GikuuyjvprKUXBiEWlXZ1Um0JHCxp7uKRSivqHXZpSz508AYm77/eTsW+yA1UNKQxi5PowHZu7DfP2ifKE9aiQ97XgXqVyBbE++3U0i9rBWJ8+IyzObpnOeMHbHTSkAkWlF57LuVuxvXZbn8O4lzrkrKbgjThwD3c+R37eyNmkhQy7EkPRCqta3MR5cvL9hA2GyqmRvZpt4apSXC0QQ9pRA2dYtrQmr3oGAxjgR1RDJpAGxo16knlim0P8NiysQ5Q38I5mqZm0yQYhMRCJqSTSoMPQ2tYVDIYBiNbbeDClv9Wft9DO0Wv9rblF3LmKkHTkpkS4WnuoHcH9T0aBjSjgvmM5E6e5NT91lwW8r+DM/pssa8dEhONxlOWcf+gV7g432yUu0Wj4IpgLecIFnBM3DFOFnTIw4hsj9h2E90oJ9cX4AhyAKWyhtuSQzEyUJ1S/corlM+GFrLvW84Lc6LD2U5HJgzZ6kjlBEyLbkwgiHYoaUsu4gP+xWnsaxQReHdEWtoY/s3ymu5sPZRvf6fhf3dBzumf5mB5b9wN2P6esdy+/krl905WeaaBxh08yVtcBSROESbCJHilclaUF6pOiGmSRi1TLJFRUB+YrTzucg7eGvgiHw6IwxkUZO6Gj2mX+mal+fl9Eq0jTmSWTVzo5RNbsyubG/knvRB8OR93fcC3v139KGFPVkdwUwaUSV6telGM4GCw/FG7/8fce8dZTW3v/+/kTO+VoTM0kSK9WEG9ol4bKgrYe++Kir1eu1iuioqCIlYEuXZF7ALSpHcYeh1gej0n+f2xs5O9k5wBv7/X697P+gfOmZxkJ9ll7bWe9TxD8gVYfy4Dme1EAPxahL8whG1WS0zDplOrWp7hTnKTxM53EhexqryF3gbfAjCt4gQSaeAEpxBBLSkeYU5lZHOxoO2pTmM4U+nGSmat8KJ3FiJ9EItBUWQvfyYPIT9NONCqBEotzXiQR7X7MxMjTXJU3ZA2kYd4lNP5XPv+C87gA853MU1ppgfsPMX+km9XtEXSWUSIMW1ND67a+2ToNf6uVM5KuvIj/3A14wws2mRXaPiq63jNHWeAq6wQz1QMlmEYtKeEKYxgvroxOfRQOPvs8N/HAXGvrGsv3o8TFXArip3bdYl+QxAizw+awoIel7qf4y46eH342ZJglaQ6d7Rmi6a3KQHX6vOfUDmCP2tFZLANm7mB11i4rYjvOYkl9KRTlqBTeJY7udfBYZVVJcRt4/ecGHfTlBixOJvPaNOs/v+puEAc7EtxAD9zrH6MqmGn7G5ys2JgWRoPW+26bbTOFJij3Ex9/upduI2z0j3HxMseeFUAFmbo7RoKD1YLdvAWV/IhpzOKj0iingv7rwr85vbfzuKI9e+xoq49JZX5Wr/pkL6b9ik7NBZ6M+LhTv2NsDBYSk8+qj0j8MzCrKwhnV3O4vzan/1IoTZwzLFt1nNj5HXe4gq+4Z+akLPfeWrlRJXcTIBpByNYsh4oTgSrxvaCFOpmsbrSYiQfMWev2BzLNS0/WRRuraGLNsc9zEO0dMbB0ale0cFXewawhbZUNogI1ltOOi8nrYEeeJHPeO3z2yldNrAxW6e2MR6QjphoT37VJp77SWziVKLRdmwiMy3mrctNRLCkxUgQzOymeD5r6cyiKhEkCFPLGB+5LsDkboaQuf5vMVi+wbQUoeM1ig/pykp3Mc1HpOUkf5Jlm5h9esFOsfNuWnMo/oSTmWEzEI9ELSepll6dPa85NdlyFzr3fDYcy088yRh3cnWvb9lkR6rITQ4Hfhn+WfTCC2HiRPejmtYI9XybeDPfcxK7S03YtIn2DkmqtE170lhNF5fALnS3busdJFQqZ5AAnTbLrOFC3iM7XUyiD3d8jzu7iLCz5DNqlyacvN8Y7KajzASTvKwoQ/iZzqxhN0XMYCimYdO2RSN38hx/bc5nEHO4hEn8uEtMgHJy9XfgRXWHEiXR5Se6PfYMFeU2t/M8KyI93AWhoi6JLzhDOxfAKD5m3vI0t+LopuhYflwlnHy131TSi7U+6gvDNJpkWZcjbx3B8v8lTj8HsB021YH8ie3srqVOpYnFqn3xpTn+roMlubgaHLByJZmcdagXQcukgte4QZu8YweYDixMzQHeQEe+4WT9oNWrhfJy6AnCx2cCjWKh2bQJ0Nf4xZUdeIDHuIR36JJUEvyxbxFMTNLf0S+OE2EYNgU5og+3TinFb+0Ka9z0RW8WaYS/YRqNFkYg+iHHj4WXNooRcQHaZdUiovrDdh1Ldg5TWMWh7NofTu/hYjQd4I4spGhXVBd+vGp1dWDbVMTSdQF6w3YLWaSN2zeSL9c7fETOS+jAelKTLaoqbZ5jtHtszvblIQSbws7tsoSxRU971woR/R2e9m1oNErVIlxIPxJpxAbasIVzmUJBWnC+lfOZjDJLB+R7TuL5fh/wyiEvM4zp3jUSTGrqTC5iEn+u1iEUj6Q/S52Ryq0Vj7G2rJBFtU1TowjuOpP16+GH9e2pJ4XqWn0cnVi8hhuT3uQq3mIRfVzMoGkaQWJpp/GyUMswjLgRrHgOzFEl77n/H6SsefV1Np8wku+29eBspnLqISKC/2a/N7iEdwAdlpFCHWlOZEl1HvY3ZgSOBejXqZw/GeQ9m5D2rSEIs5i6oF1gwfPmGZnWtwIKD+7c5RRG5LKPRDPEL7AIzJ2nZf7CoKJNVJDNaJ6nfYoYU7khDARWh44BmpMwqZywrNH/DIMl7Rv+yfec5A7WvehK832TltGuqF4g+YCc9EZ6sSh0sWkqRditY70mvtsuvZTkJB0T00iiRtxpWYYnieBzsCwplXOAHY5r770HR3gMtqbhlR6HZYW65etVc31YyDH86rUtajGleDR7fGrs0ShspbUQjyV8129ZIgp1XXsB2pUpwhxnrhmcOIdEpwqyU0E573GxW0F1ZNYyBuSLqMeRnfYIvi2HWVetwExMNunXpYqPGUkmle73BrjPbG9lEnOdASnB5x5Zno7L+bRSdzx204yqSpsXuJ1fOJb1VaJ//Lih2D3GP7FHo9A5Zw/Hps1lQvRilm3XaRognMkdwwjdSUqbF+1DP+a71BZSe9Fv87cUcRbTRGWi074FK1IZz9XMtQc2SdOwmkN5XlngDmSSk+v76qMAseiXN3rUKBkOCaed6e3YLgzBH6i2xSzmiqNFJZzs9o/xgPZcJnAZn/iIaKWd1X8LMzgh8H0jifxFX/7cJyZfN0VowdKKdjzBfeyhkG3RIv2HK1fC22/DBi8K17E4xmrFQT6HKQC0juwkLytKS7bRMjkoldOxqMpNX3zJ6Xq7EQ6j6pAI8XYxtrbQlrZsos4Rev+Ykfy0VdzLAiV12qG5iNgu9aX/6xEcXD8vD7KUA8w+5i66sZxt+9N4Y9ZhvMG1dGA9RTlBpQPNKipYn9oda/zbtK5dw6t/eJVgl3T4jat85Jfj9w/n603C+Ttq4csArlROebmgU5B2LlMoqxeRkroGX5/1zYtpqcE56PGc53hrlriWyuLtx25azsw7hqeZzEWhUb5YzHBAEfGlcnoqRLtGxCRmGUzmIjbu0iEpVye/yxEJ87CBZ5aczDXr79L+fhkTXK099/S2wSOPwGcrRUXgV/Oaab/Bstgb8b5rdBQfEiK2u75IW7RFJ8E1jODC3Sa/hkuZSGpa+HwUL4jrErvWZzKN4dRGRX9dV9OCd7kUgEsKv3GPv5tn3M2mGtmS9EWBSKxtk0YtnzvjR32PR/IHF/MuXRwCa+1nSiW7tKQUky6sYkyzic492W775b9RO8JonmXB5kKysg32kS9IUP+jS37FQqA8jxW9wsXdvajcsHyBuWzrky7CubqgOVGKaYxgtej1We/jt/+KgzWI2RRkhO+2JL4hXu53SuH1XNvfA4UOKZ3K7Ywle9Y3gWObDJn7XuCqihYeOJEqgc8hwm0KzsWyDbeyULbOdbCq63h1/cmM33wSYRaQx/E3B5s/ENpgYRWWKYn6wBvHdaIYQLYtZjOCKQEW+voGg10UUekIFr+wcxR+EwR6tgsadqv6kk36M48Ccy93Hv4bj/IAgzs45JRu3N12n6XZpxcWJksriwFdLDg9U+y2O7NWw+eYhk1VXQJzGaDt9OSgVSMkTXHtgOcY3d34GNetFKnd3VWeE+F3sKyYzWXd5zKhxf2OMKx+HucGQ69lNhHBOmX/+yykH1HHYVadWlXgdcPebKYx3BUPNk1Y+MM+9++RhPhSSdfwelyNwzD70BC0B2saigGxUK3e621eTCye5i42VXoT+kecB8D1vBp6zgJ7D6kpOv5jNkdqvGhXMIGRBLFSohGW62yrRS7npgj9s1VVwvFQHSzLEez+lcFsbPCpEvz8M69wA3fsVhZB0wzdVDy17hw4CKkcaSXOuDqBGSx1orKq2TZaqnwLbd3NwbW8wYdrRdpUViIB5GeK8aYumPfzGP2lmHic+evIhp9ZSTcWbshxo1AHI5Wzb1MlnVjPUy+nOdVW3t9Oab3EdRylqUzukqYhRoSqyiAPVkt20CxNOOnlVXqfbWxE4yzr2qlR5x8EfqoZxNIdoj/+yPFMc+SrJD5K2iM8xBAW8zy38yyj+X29zsEHYj6LmJZbLCEfSx8WumlPNTNhJphetNH/CC0LwzQcotEgDc+Evq8y9kSvmlTOC0WK7+9/j7sq09hk6vM0wO3HL2J3mv79D2sEpu8kvnWfh9/B6l1cxkQuJys7fD7SsiPKEu8S1jr3ZDsd4r6lYo1ozwZuaD7VPf5unuJyR1lkZMbX7vchWWTnApZ2TTWCNZrnuJhJoe2tIpNLqnT+wKRkg1V0ZUSuSDWLcYvTfsv97nlGs2qnRwT++i0raHtmH+1c1/aaw8dFt2jf+TcBbjQ2bP533rG6pE/t9yRT+z+lHXZV5keBn/5XHKzvOZmh3T0A8KYl5YFj/JOeFBsWiEkFi/NnKy5hEh9/GRRGPaJbOfPoz/hHQ7iIfA6WbRus3ywWxGoy2L83OFkNzltGI4kspherCgVIUi7aU6/5js93DeL70j6B3x2MmYblAjd7FHugyFMRi42/2nwQc0MHi9/qG4SkgWSfnl0ZZJeVWoQx/0AwTR7kUS5J+YT0vGQhXpmaSh3J7vW+L+3LH6VdnMMFx9L3e8Qz0JyDSAQMQyOVPJzZDCucxdKSDAYxl0unn+m1SXZwpxd/1P95pvR5wv27f5I51fjGI84zYqFOqt/BklI5mE7FTEz53r2O/lwHO8z6YqcaPlwM3yS8Mw6PVCwGUSKupJDhw2BEIkbcCFZTBJjxjgc4NFGAZs9kOnO2epGTbbRmDE/zxnW6AvxlTOBVgoR5QmfDc66vGbBQaB3+HbMsBjGXf/ADxWx0v+6dLFKXU7Y70Tbb4AhmccPAefzlMEtXkUmdHQSgLqI3f3CU94VD6uu3NKqpqbbZShsqY2mBv1dVG1r6Qo4fA9slbdVuBTOQIlSlmcJ8H69dXn/ZSmsecjB/B6JdUHmw1tGZsoqD6w8Rw9IKFMTJzEB/UgtLLNvkEFazkfbsLg0SRQNsWtcoT6XZ3b+dRu8SxXkzTTdNKq2x2nOwM9rmu463P4L1NaeyjwKqyOAZ7uL3DWHSX4abIrQUvzNCjNvmX8Alq8ZoWoCqE+d/5nMa+rKT5tgYbupRswUL4DvFwXKwmTp9hv6bJ+Ycz5mV7xEwpQLR+63zJ6evDCjew308QfhBceYKw3ajk98oAvFyDo86c8zvm4Uzt2ircHQznECDtM20ZZMzDjJNEX0dwcfcWCg2ULkpOt7s+/l5ZFPGmU4RhupgHcNvdCfImSbtlwYflYNKOI2MYImv2rdq4HQ+p7/5l3eoc9wqDnULT6QVZ+6lf8oy9/M/8+dSF01wI4ng+R/qZsot+rEJaBEmRWIkGj7s9P8VqZztc4JhuAAi34h4v1M6UmVUhHTVCjHvRxb9WcCVIysDf1q1McXVTgNYuLMFW3Z651BJIKXdVPwFZ/A5X3Gqq0MnB+ZT3OOIFwebcTBmGrYniqm8hTEIr3hHbbZ2/GQu4CtOdT9bMTs0FeWfMHIiwcokCVTf4tA0FBaIe69vNFlLZ/LN/UL3bdw4lrUYSip1zF8mnILHN17AG+tPcNqt4wM0dn7TZM5K/R4u5R1ubvef0OjeyblzKSObwmbib6mJUVLN+CkQE4svPhftjhA7KBybtWyFg3iM6IuJliL0+sEIPnYxPM8O+ZLlHfTUkTT/rsc/wN1zxyyu5zWXIdg0DRIc8s9EGohE7LjPJyjxAAAgAElEQVQRrK20dgsPDsbkBN05QeCWfuY4dtdkBI67+uQtvMeF2nV+4tiArrJt2VzPq8zaIJzH1jlV9GZR4Jim7OcVzRjGdFbTJYBzU+2Vzi/zPheQmVjH+hrPWZ1SrqeJ1+zO4W2udBcBgJ2lCXTC42X6VElXrikR4315lXe827al+aHpixmcyFYn9QsizSzZ8SO+xVclFw7rj/uqdIzV4cz2RNU58PPzk/cuXht0FFVLcbgc26SWagUKAGsrm2v4QJCVUV77ZdQnTCoH4JpFQvokQA5t61GUMFT/aTVikf6SU2HYMB7mYRJoJD09yGVmYvEwj1BKYagTKkHMErc5uL1gVjfbF7OzLoct9c2Y6aSm+zNPj2D5HMehVdP4pGGYA8KPL4Xmts3RD12+zDsuwA5v6VV4KnYonoMln/2A9qWBopvGBpsq0t0IVKBN2NSSGvhe9i+5UdxcLubnbQ6udS/5vLRjBGucYfAJI/jRwfIajnfzCSPdZ3b/QA+bmMs+6htNjeZITWHezdOcxWdxN2X+TaqNwTPcycIakXZVZZywBc+aDBAYpkFD1OQf/MBL3Bo8uW1DJOJpp9rQu+QzxvzmraevbRebfdUh1fjXMHVctVoQ4tjKumCU8r/nYFnqIhby5zglj313fc0Lczzs0q4GkVJMiYQIO7u9M7hIRS1TW/jS7WptQrMaY67DolLyC4kbL0fcvbO385KhadU+YiSdWMshbZsGoN5dOJFRiJCiuuOW/z+85Rb+hSejcDMvuxQFICa9UByac0957OU0viA5RCrnie7vM777S5Q3ppFIAzl54t4aGg3uYCyLoj0gORmuvdbjF5GK9E71BTh9LE4XilqmJjUUIeo+R39kySRGxI6STYX3tzAxTfU+MZk39jdxbsMK7VN+R856czx3/nY6g9Z/ICJCcsJxJoxbz1itOVifMNLV5TMjhos1a8oedKQdwqykLJfxXM0SB4BuRgzyM4QT+SgPighWHAfrC85woyoHY/+yBSlqVGHkDt3wmqbmuM/gRI7nJxITYeI9nsNhxyzGcT2rdzlAPWWykRQqB6pq27I3lc8ZpjksAKujHbXPHZO30p6NBwzpzFwlFgY1RVkfDX9+NaQ32b6DrchLTIRzzxVzRKf0HTzCg+6ioWpfhkVU124XUffCFLHpuZ/HmcDlXhvi3O6tvAA4kRc1UnKANkvnwLKdQgrl0Ty2dBj3IipWz+d953gFSIyHP/UrIPittl5/5n76mvVbvcjjGjprlaut2MaUdX34g6O5jIkUFor71Kuj4zsv4FVFR5z292khCqLmlhRi1tVgl3vcYfMYSEKSGZc3KUbEiYjHiWD5LDelloJIGV9/470Y/zktW0TZpZ2TLuAtXy0vZniDXrkr78/FAYZo7342pwWZVFFZFS9FaAu8ms/89A7yX/met9OKWzffTi+noE+NOmpSOZLo1Hk2SdRzH/+iukTHDadleBPOAvqxkq4Y2HT0M/oTBKFHLZO7eYZrttwn2uqTynmRW3kpcof4bcTANkzXGfTbr5uLmVxxBpsoZgQfY9mGw4PlHdOgRLOkncdH9GEhqQkNLC8+jaeHeGnSlzecxjNrdamcs0rf9J/iv+NgdWY1H87xvLtmuUFaggsLv9U+y8jIjlgzqqPeAE2OiI6aZAbPsWRtKsP51CU4U00OqF7OrvueZm/rCvfRGNfzmvi/04HqoxGiJFBDOvdUCKFfdXcVUNhGKG/fzlhys5teHIbn/kgbxE7r9xV57vfSa85JrXcrOACHo8l0eYzCKiMATa5A5K2Dr7hd6m46Ze7ynEdDB5gvi3ryDW41s8NxYiu4hDP7bmKB0Z9+2cEBE0nUmdxNLPaTS3ksI+BgJRD1Jk7nguNKTub5Eq/cP8vUI3GL7J7YDm9SArEAXquAPRQV6A7Rm1xNXWMC9XYSqnhoy4IGSijmvktLwPdM7+B58Z+DkMoBwekWz6Ixr40P8xA925ZpjkokEh+D9XdtHgMA2B/zUrShFAYhqSJpX7/ngcE9PTzxefbvMf5ymLm7s5y7ePqADlE8DtXP64b6DrR4mIf4dm1HmiIsyUgJbrL8fSsLD44gK49bJO/DbwfjYMkijmnT4JusUTx0yIeUUuBuMvp2rqKNA5KVa6x0jkQDxJcZiXW0YDun8jUz8KJy8dog5wkzYugA8AO0uTEm2rW9NlerAAXdcXALeJTKKMtWHKyohfVeEMArraExuDlWx4Qqu9O5oIwrW3tRu820Zc6uYkBwRWGaGBHTlSkBXyQhpIt1zdpGv8y1zOw/hskD/w2W5WL8jJ3bsTHceV98acTFYFmYJEhi2oOIYD066GtmdtT1+/z9PBYzNAfr/hyBN9q0P4sv7VO0Y/3tKatNZgVdtbnnQDQNcaVyJL2Bb0hJHLS000MC9VOqPQfrim2PkUyde56LmcRonue8930/VDyYxfSmnBxMLNaHVFv726xVtAMDExfROkuM5XUlEc5lClWWiOCakeC4V23a2sN4ar94RxKDKSO6bdnEKD6kX8bqwO+u51VW0I3W6ftJsBtd4XIQYuk/lPbWjg/DDP9XHKzdNKemLv6ljmAW1xV9pq1fctK3bH2hlvpH6mIlbde+RFEd0RBcpOQLkJVe7ZJ2BBws+TJlRzxr4f3c4VSMfFDt4IVMkzSq6cg6Ypap5WVBcHq9GBamDDTIW9jUeznS0Uq0zUjowidLtPMyG13WadVO6SpSQmXk8DnDqA3BrUgcUlljGlESqW/UsVhv1nm7H38o3cJzKguyGulrL3DDu13wOGoMQ+/0tzOWF7mVC5bcjaF8b2DxUsJosoxKrmS8209+3tOd70o9cPygFK8KCIRskMyXRwwvRZibKpyutXSmc7G+AH/I+e7u2sR2J8IE06KYTaSmQiIlPM1dnOikbmTU86PVfbhp133BZ4k3Ccynn1aJ10FJVQFElYn3IR7lsOJKigsFtqGWVC48fB0bE+Onzv6OyfTd0kavzDwzORjN/Gp+EZ8wMvQcas9W9fAApiz3qAb6spCnGRPAJPktHg9WoblXu97knSfwCA8zZ2trX+pA/32nQhGZKGS3+50/aqnRrjh9+LZ20/Cbv20t2M5IdNCqqnHaL7KIVhnlGp9f66JGLuI953yiHcPxQMNSfcGyBRBfEoZ6bQg0CxD4OXAiWMqUcCAHq6JStGHuvk4BDJZhiHm3J4uFY4NOnmjZBpEUkdK0bRj6XjAiEs8kobA0dR6YnHY1ZjdvA/csd7rzSYyISHsZBvmKVJG6kQx7Rvd2/Yyxh7zupm22lmUwPesSNm/2sIuHsop/OBx6moPle4Y2Biem/c4LSWNCQe4BC0kVBeV39AiWfMZmJISCwbm/C51+NHVhe7qzQseJyghSHAdrQIZHx9LT4VoEaF4YYyPtGNJCRKb9GcbhDpFssbEJv/nbeTw/8tz8YwF4njvoFoKvClu/4lHN+L/3xrH4d3r+FVzeR8xp1dUwnwFU2SIibCjvM8xkMGIGJ7CfXJ4rftWVjjqUVbRiG4emBO/5c87gbp7mnl7f4AfFh/Jg/e9oGrwKAICUZL1pHdgAlqUzq0sHyydSWh4VD7W6IYjBkh0vDOMjB3mNgxOK2TpwM9pg8RPHiWsqsjDu753FY9e+RBpI4jrGOVgm/V6+4yTW0AXym8bLLKzr6grthgVG1uwvdJ071RbRhxOYQVGe5zyoIffMBAE8lOnHqlgwFz9l6xF8vGMwf+4Xi/neMkeeRlFjd+9bVk0qRKOuw+v8J2aL39/N07zB1W7FkBrtKyOHQfyJadraRG8R4drkiWQY1bzNla6z6eedOidL5Pslmef7kUvcCEqf5JUeK71hYRIjh/JATiybMjed8FP+OVzRx9EmU0CjSWxjBkP5Hr06dGlpC76oPj7wLFWzMeiCtxMazK8k0Og6AIFNgenhYh7lITJSY7S2tzR5jYO1ZuzhbKaSZnhAVCnVolpTxJz9crx+5Y9g/VXl7ULHcR0XMelvR7Dk5O9OxM5LfHOn4DGzLDitKH7lpOwfWoWYbyd7E55siJvaCEut+9rWl4W8F5JmSaFWOF6WRQ1pLt+YOLG3aZJjWh1LcnN4Weff6ckSl69NWs+WQX4ugA+d6k4zYpCbrkAUDlRj4E4sNkOZQet8RZnCEP11Cb14hZsAGNv+34zuLtJX3VPWU5wsNnNW1Ppb6emAPqQy3l8qPV8blr9zjPt5LHewZ58ojtFJUBXnIhRfYrlFNVgWkxd24+LKV2jTxnOwLExmcoI7VxqmKGo4p+8G/VSY9E5dzeUJkzitaB4jW/7W9M36cFQj+YjiAj+Tu0GqWe/qtFZYGd5PMUOjU5LoVo5PlffxQBGsFzp4fV4SM4Pof+3YzBHNxSa8S4EeyZWFBtYnUwLn9EN4VtCNjeViwzGV4ZoMkrSGaLB9FxjBSGgO+wOOrFw7eqQ6m1QFMiIf12RLgNDNSHDNV/uJbdsYBpzIDL7jZHqnrREi0YbNd5zMc9zpzgk3K1Xf22jNozxEzDK4ec/9TFntYRb98l4Qz6H8L5hIx3iNkcy/vR3agV4sZnNtoebw9DCER+wHZ8YiYlfVJiukErEJAjY58dY54L8Py/6pTVC1VTEmcQkAi98R7VLbLCeMqtoIURLpy0LH2dAfsiRQpaOOK/HbbVvv4GMcCoWQWWPVvmaB76T9wFCwLHeykKSsgCaAHM8mbx3C5G3HeUzuRvzn5mfOtxVcwvIdeTzJGNZWCSDyFtowl4Fu7l59b3KiU6VyXItEAu/O72ANTp1HDak87nAVqQvXmZkzOSNXCPheOWAxFWRRSYYm7AzQnhIHV2HRPXmdW2a+u9TkTp5h4640LJzn67OmpHLOS/0P9/E4/VmgLd4GospSglrPb+vp2y2jO+U1iXQ4Sik7b0Iqp4idPE54BC3MJDHp9WnvuN81ywiSNKrv4i1HLUFat0zP2fNHsNQJcQMd+IhRWFGLNKo5jS8IM79DIIG4mYaI4g12FAFUmoa2aR4W5/5CHeMgj1O5hPwAaVlh2JPFbpo7bAPmjzos5TBuU9N7jh3CGgrZw7/rruTtLUNZ51Qe3sTLlFYkubxX13UWC1uUBN5x5hW3vUaMb/ln4Nz92+0JfAeww8GYdWpTzzkDNntSOQeJGzulYB7fcTKn9PGqqw3DDiwIg7JW0iNbvPOP297F6BaTD+o6LfL1yKhl66Blf2rSjwXUoAQJIoIlefwAWircRHG1CA2DxzecxzOrz9AKzyvJZBG93c2szGAYBnQ21pOVrKf0bbmhtywuaPUzVxcHSWZVe3XJMYzY/CyX8zaHM5uPOI/jDtWr2C0b0sx6VtKNq3iTkXtecZ6Lg3NS5v+zDvHWPQjOv+r/40ZttNScsgFwHl5iRPybnOBshJ05q8xJFUp4gWp+6EIWFVi2CGpUE6zoBzATg5mktyPXaJJJ0vyFQoZpsIhevNbuae+eJA7YmYumM4zfOYrB3fcFxr2Gr7Z1hx/LcrDEBo/wIF9yKrsbhbMYBvEwTZhePZSle5or34U4WP+rFKEoifduUObs19GJMrJZS2fOXPusuzgNYzrzE0XZpu0rgc07Wbz89EFB+gHXsw/Jx/q/29LYPJAiBCF7MfDGgVRuqwiNYMlOPYOhvNPxMR7srcujHKyZ2BzLT0B4FGFwcbDS0v0bv1BfF058uXRbHmcxjeYOVuuDTg8FjpGhb1eCxDmNP++tfqdWoMjxu2hLPvfyJIMyxc5sKYfp5dBK7yqhPfvIwzRsCvL0CqPfrKPYWNdcu55/hzCnthdp1NLLIQxUF/hL8z5ndAuxM4paJpcxkSwqWbTWG/gZVHIxkzxchbLz3Lvf5DnuZMf+VKLolVnNnZRsU1I5Y7Mf4XEeYCQfUaNMNhO5nP8wjFKHDLZVshehOIxlzFjWHPMwb+e3cGszbrefo6E+uKD9XSb3nTTnU84lwfYinRnJesq0P/O0cXGFA1YHuIun6ZLpUat4Dpb4nJMgnKJ3uZhdFBElkepKi2oyApEZ9xy+hVpyte23BE6se4bEL4k22TbaxJhi6JOfFAZ/ljvd7/yLtyTz/bToRvf6T24IpkTDsDiSrkJGIJOpow9/0Z4S7qt7gD/2CdbzYkp4mVtYUpLJDE5kPR04Kl+ky2/kFcY6up71Dfp4O2AjHJuGwCK2bh7Vfnwgx0eO2VZJjuOmpThwSX69L5VoimVRnLaHV7iBFgUhBUWKFRfp5fqHZO3S0lSqI2ASdLC0jZhzrOSUK2InH3IsI/iYBBq5qOdi/HbpvBsYseQ+Zu3vxpy9hzj9RjzLaQynmgxXKkcbQ2HpPUy2xZrzY3RwIC0UZluqcllY2xULkzkcwSDmBM55VOFaTsn+g084l0X09tjJHedJjU71KhRjbopT/Rqm2yojsX6nQrsvx2ZyAqudoPrefQajeZY15UXaYRJDON3hIvuVIYDQ10x2hOq7RvQK26X0xLIMYlGbm/A4rIoVZZFQB9A0A/xrV/IWs1uPCBzXiyVuMdvhu6bz5G+CN9Kl5yHKUcwiPzsq1DawKGIn7diorQ+25a3fANNKB7uBm3e4lNkcwV+5xwXb6thdc88JBHrCeBH/Z0zuKkkYeC+2ikyy772RpNZFWIh0WxdW0Yl17mTjp6i//spG3ud8FqzNCmz27SY6XmKS4eoqAbRP2sYRhwrQai77aFUgJm+JuamvasSyDU7jC0bykQcEdU79JPfSJXkjxdk6tf4/+ZqDMbUD+F/Um1zFEYPiL6a/MoTla5MCJKMA6/Zk0YYtQtsMKEoKUv/bto+J1gdyVx2stDQ4lp/IThMd/a7mkxjVUVRbysHfO00Mvk85V6RHHUtJsujAekzEjn02R2Ia0KqFxbWMA4RU0pnVk/lgv9jRu1I5pp7jXlKvS1bcGfM0+3bZzdz+Uh+NMIURWvtA9LVKMt0U4ctVl/NziUh7yAnOMKHGF+re8fgEpz3hIWDVfghhKV+vCMPKSVLyn5mmTqq4alcuL3A7jfUhKSzCCTTj2XJnx747Jqg4FtCXvu08XMsg5jCPgXo0Z/Bg978n8AO5CR7diZciFMdnJYpomFoO3pSSAgT9B1n9l2VUUUwJpxWJfiUdWcuC9IR6zuMDjmcmRQk6A3ubPOHkSRA4BMe+XCzWNDuaFnlijEdDCj+K8yq4mHfdz6WKosSlUkYEgx4sow9/CTC0Aw9wteXkYqikfWQaDrwKx593hMuvSK1Cv7kCtJEImCbpiPvu6DDDB6yyEmpqvHcmnQpVizCkK3+17wh+3O7goyyLopRybuA1CrKbdrD8Psjt3b/j9Q7PBv7ehs2Yhk27/CqtkkzFsfoX5QgxLCCbcs5mGofkBqN8FY2pVMVS3aiCWgAkBdKlk6yOofvtx5i9TmfPv50XKIm25pTof9hVm+XqDDZ17zIFCYLmxD8Oruj0C/e2epeRfMI8BnpribNZ0Y53Bomc210nSE0ROutePGD32Sse0z7vczKBZWXwPKPZWFXA2UylU75YG17wYYZlBaeMwEM4gNu27YBknSoXFta+WlIDgsqvcgPZCb6+LDcSxwnHZ4+VT0W9yF4F9iGGAYYorBjCL9zCS9pBoujCs+d2XMCRifPpkFfGRtrzErfw9s+i3YVnHh1o8566DBezJS0SEsH63zpYijO0ZnOK9+Ff/8LMzRbzkWV5kiDOA2plbicr1RvgpWUJXMAH3P5GF/7zju48uKHTkBfbprXNVnSJirx0MeHuJy8wKGxbvJhsymnNVm8SVScAH0cXwJfNryJ6EJVgpmF7oHrLOx2AOXAA5nlil30CM0ijmoH86e4m1N/4zYraLKYXyx1HIRRv4kSwzjhNXDAxxwELOovn8UleKqtFkcVPHE+fTmKxHZHzPce2FpOjfM5qWDWdKl4461cAenSoYT2d6Iq3mzUMNKzKdHuY4DSxdaC9f4fw/L7LtHtYavdwgZWrY50oaxCRpxnrvXSpGRFO9TW8DkA/FtAqdR+dUrfxfMVVzCwRx+r9xnteu3YB94m0nNjshk9o22NFnM1U9jk8VarmpWqL9rVlAHP5VFI/mL7dvVygQ9K8eyngHhTm4P37CZBVhdiMBuE0ZVOO1dcTZXYloJxr3skzfF4+xP37iczgy53e8empFgvpwwm9RRROan79i/u8fhyz+YF/8IUiMKvapQOWB7ULgQo7g420Z52TalZThPPLOjGdMxnEn2wuiWr37Fa4KtNYYSFsV2gbznR2y89tGUGHFrX0ZDGFSUF4weEddrtyIeBBCdbSyWWgbiCZF7iNXxE74IjDYVZCB87nffdZzuJI5paKBVKlVjm0lRhDP+zQtQilvT83qNMGuCmYypoIXy5uw4ecTy8WcWjLitDjy7NaU9Wuu9uvF5Z3JItyPp7j4aiGtlnt0tJI/dex20Yyft2xAAwueZdndzj8aL7J5mUHsyVNRub49VdB4+6bF6UU1xbaYhg2w3uv10SIVZhF2NxtA29yjYBUhMApJGxBAo9VmgjZN6WepDofPmvdzsJNOlb2OUZzZMZSLEyuXnojVy26IXA91WQQTKY0t9OKcT/6HGjLot70NiJ7YnnOb4PRqRW7dam4sAhWi6xqTmBG3AhWjZUS+r3sD2UNqUxjOBX1wtGZ7SuWGs1zAFzB264UW6jkmm0EoqgRLMZzpfiNsnk7jS8YxnSaN2zmC85wq20BGkgKjxTu2gVPPOFeXxKNSqeuigxe5BY27hHjo8LI4X0uEGosKi2Ur+jCsg0+yrmWS/uKbEg1GeTkGjQ0wB1TfYSnCKhQIIIV4mBdkBTErv1XHKy2bNHSE35sjNwFRBu8h3KItZJYDJanDeTqo7wKBVl6DGCsWKadRz7TUJka09Q9zI4ddS/Xt6ilp9kuDYONl8NVJ4CJu0/lu616xMNctoTI+rXB6/ubY9j8hABNpyXH9PYf2sXNX1/Cu0ziYp5iDMOUqiO1Yw9ijvv/a784lV841g37jtvlUR1Isx2gevZJQpsxIcNhFjegNVvomLBJaahcxRQvUErlODvPVZWtvHMrRQl19QYJNOpK9oZNNGa4eX4TCwM76GD5OnDY7kAKc965/VZOXCOAnWtKPcoLM0Gk1ewkcX+P8BCP9/yESV2fwjQ8mgbVwVIZtZopMDjDiJ8iHLr3Qz7De85qW1WpnFXlLZjLIJfR2DD1snu30nVlkBz2AR7ViHLJy4Obbw5tD8B/TNGePxoHinvEZNMeL/25mF58ynD3XV3DG7y+TSx6Uh6jIuotChHDog+LyM0SfbVzhkhlbKGtG/W1ohZD+YEz4mCwUhMaaYn4nUy9AvRMF1jCzbViMldThLLkfyrDRZ8pK3N/V10vIj5q1a4RMV0dRs2clTcedUk87FsLdmgErzJVa2Noagsfcr77/i5hEk+vHCbaqEjlyIiT6qireLV4m6Z6h/l/RUkq5bUKWWmcH+RQTnHpPHdR/mlfTyrJ0lQCzjlkidjp4xUJqAK2mxubs62xGT8zhAqfH3ezUjgAMGd5JtVrt2MMGcxPl00KpNZat7JJdShnZHpe1Wi8vp+3IQlLK93EJ4zlNj5lOHO3hjC5OxtGA7EYqilC97wyauTjHNQeoe3NAzYG1u5SzGhIX1LP62DZjuVn7zS+itS6xgj1huf0NNoi/XnuEVvZTaFb/ADwzlLxXM5imtMW5x4VB+vkHluZwYlxI1iB5a9a9Ds5z/mlcqTz1Ju/yGWf+/kRHnJ1U+9MfjlwHcsyAhEskNF2S0uFn8sUhjPVff69lOrGGAk8tvf64I00a+ZyWgrIiPja1SIkkdt4kVXbBcQg3azlB06gF4uorRbXmT0bRrSfz+OtxintM0KDI4mJ4X6eZevrGsCTfT/lky4Pasc9kfp44Lf/FQdrXuoQLhuolHH6QAgSb1NT5b2stRwiHqRPKkcdgMUFeljxxJ472Uqr8AI+n4NlmxHWbvUWkJuf1DWukpNs+qStptZIYzstmdJc7NrUXcO/d4/k8806Fwb5+dChAwcy6VEn0uBGBUCk41rk1HplxJgMZxrH8bO2U1cdLD+jtmqf7g3mluWEFKa4MJrnOD5lltJQ3cGaW9WNdRWOkLQzkifuVuQY8Gg1LNsgpugTJtJAv7wS1m9NdisATSxNtkee81/9p/vwY/qk1dtY7DLhJ5jKoqkCZk0wWxTBWYJiYw+F7sAyDRtrXxnccw+Wg7/zR7BUaypFuM/KCf3eb3Iukv3QjOjlxabDs9L9mLzAb0Olcr6On47ONYQjUmSKcP9onmPdVm+SryKTc/mU7EyLAcwlkUYMRMRHSsP8WqpEWnyd5chcj5LDPeQAKUIsi54s5TCWuPp7IITYAZf3zLJNDmc2N6y9lc3Lyqkhnf3kBu5/7kbRD6cx3PvSDMeqWRjU19nspDmNdggRcaNNTQj7tYmlaajtpAUP8phIEUb0PqlxVIVEO8OiALmKQHocmrXQa6ylM5XV8afvvRS4xURtk3cF2qdGkd1oplJ6bmGysb4Fx/Ezq0q8lM6ZA7YGrmXFbLZvFI7IhD+6cNOcCzhtxdPataTKg3SwUhG4rXxKaZHtFV+EOVjr6MYW2nA/j/PJimC1mqxsFtJdIkUo7/RlxCZkEWKebsrBsmMWm2hLDWlu2s+sCkY7VTNNCaIOYqSkXTrras5Y9Uzgt6kpNoWUuizp4l7Ev7JfdGxew+W8rVOgyDUxDpjPX5F3mLHMvT+A/U60f12pmLdqFNypivWcxwCX7b8zwaCBbQdxgD1ZTD3JgTF4Me9xEZMxsOnLAv6JriX8WVUQXqHdk1Iod3iPKi5jAq0VfjjxH5PVdGEJvVztzCOPhOeXDOXEXE/1xLINdxMwcKAbJAvYGIeI17IMjWAboCi9ilaJu/UfhGx4/isOVpgkQODPIeFGK2YHPE11APonsdSkGK3Y7oakVdtbFuFwJdJj2ejDT6YAACAASURBVAaLN3i7y/e+8ha13zkK07B5qe3znJHwNR9xHp2SNode30/xf7DmAh2VjhgxRVTrnz23udf5ieN4hAf5ilP4HS8/bMcsTuVLNwVyoOuoJjFYWVlCTiNRYbxoxTZaRXa6n3eWJlDAHn6YLwbj5Zsf5pVlIpUkQ9xlUe85qozRa7fooepHeIi7un/lA72Kqez0lB9YSg/33bXMqKBd4nbiWQp1bjQkwbRCNfyMiMnmHUm8+bFo+0bau5OTiYW1eg089RRWrVgcxM41/H3ecPgCFuYFqwvDbB4DQ7+3YvAE97ii3WqKcAQfa/QVfosR0cS0gSZXZNmv2psi6vU5w0In5L5da/mUcyilANOwqSST1QQxQtVVNk9wD2t3iHetAuDd+zuAgzVzdWvu4DlKKfCYqhHEm+BFCF9s/hRvcA3tKpa6ost7aMZY7tAKAMIclppagzzFaZHAXcs2+HVRFjtpwZa6wsDv3p3VmXSCVZa3Gy+GUhSIFKH+nbpRCXOwyqodMXBnTB7GEkYowtjxeMKkGaZX8FNDOt/9FbwP1XKzYmRQSctEsYFT27u/Id2VSNnu/BsgGnWqzdR5+fFRIXxHMVvLGlQ0plCuzAlqv3uw3SQmzOnGcCdCM4HLQ9OJ0nolr8TE4kVuYzWHapXd0rwUoVgMj2y1iauyPhZtc+Aasrq7hemxjatqDgCN9YIP77N9Q7CIuFXPTZnceJUoeFg/5YdfGFz7MeiZFOf+5Pgd2KWct7mSlCSfg9UE+N7f5oxUPUNS0Sg2ElvKReRHVqlGSaCcHFeu7QeG8gkjiUYJVbGYcNTbgQjWUnryFGO0jTVA/S238JzTthF8Ehi7Zpx5V70n9zE5kWi/1NzVsXFuxkCdi8oqTTAMl3zWsk267J3Fi38M4M8/4Z57wq8pOSdVYlKvQWYg6r03Ftxo/59wsET6xQy8LCtqcXTdD3y62MMmaLtE/yndHFtwEEYtk/lK+alw6PRjJKZnCT2pqxXRMzcH7kyYhcqcppJu/l0bWfQLg5gjBpJfntw0iSQYDOdTPmIUD/MId/KsJglixYQe0+ecIUQ6Q0xiK/z2WPsJ3N39C046CUpKhCqOtPP5gO/rPSwOpsleClychRA29SIwAA2WN5hs5ZnU1XsPpxm7xI7ZJ5VjOkQG2ZTTg+XeRH2APmNhukz3CablLs7q65DXyVFY9W//60IuW3mXG9oHtLJnv9iztOy0Rlob20L/pk4WT3NX3DYvqujAfTzBDoec0jBFqbCNwceMapIs73Ee0N7/3TzFL3WD4h4/1hLq8VFFAqJL+5B0h2nyJldzNtMwDFF1NFThzpFWUW5zH0+wZoeo/Ftd48ndSHD4garaFm0r5G2ucO9fWvPkMu3z4NR59GRp6DniyYNIU+WZNLObjhDFc27G21eEfm9jUJhWzVW8Sd8kESFQ31/YtX5dLkLrUoXidsZqWKR4TPcXOOS1fvLeeMe7tmePWIicZ6L+9tE/T3KlcuT51QhWjIgL4ldTXmFpKStmk54qxk3HjF0BBvSySs+zy6vYqEUQ+/CXKzo8lO9JTtXf35VpH3AgHiwJYjacTMjJxat4oGBc8EBgdYaHK/Rjg+V9ypRdjMgBHSzDNLBsk3F4KS5/V/LzJR6eIjZYCzfmcT2vuuks8Ka8aZmXOI0MOmFv/daFZrH4m08/+bV7bmd8piaKm05LEv1QpoiXOcTNfufojz/gnYbzQ05ohY75I5nFCczQvqt/9FHuxAPOz/TJ2hzoOUewKKtLYcIE2Lknwi28xHOMBrysx/vWKK9pjoOVSQXtypfwS2Vf6knmRv6NhcFeO5d6K7yoRNoVvM1hLMGyYWHWcVxzuEd2/fnWvry84xzt+G41cwPn+K84WMNqPuDduV3dz7KzHYXgLurXYhtnpP8YeFkXXGTyh30ke6q9EKY6iUlwm7RFG7K4hReprQ+PZgBM5FJe5XpGdl0SWL+fRLiy1zNOQD0UB2t8pQCdq3T5ti9s+HfsklY/cCbTqSWNb+Y7XpviIBoGdGE1BY6TtNKpCnO9cMfBsoi4O1G/JdEQijcZlLmCfvmbME1o3lz/WyNJ7LI8L9IvKaHyYA3qUsZ0htE1aYN7vIUZioFzK1IMH+7IsD08lOIYf7mlJ6/t8lI/KhMywBbbK1hINC0lYuD1ofR0WLIE5n7vhfm31eSxtb5QS7l1aVXFbxxN+zYNhKsaohHdNWVhWDFptTEPP3Ml42lT1KCnv53nMphfDnidZ7ibi/cGiWilTbcFBqhOYfIPxWw4qSKZqlVNxQrJCUv2/yWV3o69HZs4n/ddXp14Zll2QJbjyMwlvL5+qHM958tYjElcxKcMp4Is7Xh1sfen6MLucQBi0suI1LjzS3okqBNqxcAk2P5QPBfwMaO4tMd80qnmjPSZ7Njh0CjI8znP7io87i6p55lsRunOMi7lXd7gWu83cbpXWwcQbBg6vjSeOPTR/MZlTKD2mKFUkE1Zo5gntXEXMm9JDJNsv4xgyXQLQGVhEP5gxWyyMkVbumTt0OYI8OFmy/Zrm9J5DODXzcWAQ67pNGyoA0oPpt+C7W6ZvJeWqft5c8BbfND9X1qEJ9H3/tTxqQq+g9fHXbUQEg4YWbl/yG9sb95X+y4sgqU+j8dzxbjdsDuDcVxPfZ0CwHbu7/iTxFwRtSNUkKlFZOoazMC4UM0/jjfuEHOADGCcclE+44ZO4+qJAty+EL39KqZXtump6B3BC9lC/9HvTInKz/CF0cSihPZaxE+0uem5tWXibmqjiVxxBXz2Sy4P8ijtHEyq7NdqhN/FmxHjI87jga1XYzjXlxEpP4el317nWtbSmayEGtoZm8lJ93DkM7Z1Y8IeXRrof1ZFuCTWne3lQeV3mWce1W0pz+Y/FUgxTJvu4HJU6IDiYHVtpaMv12xP52VuCZXRkS8hl/1czzj6Fm0LOHRqJCLWaHH82te5s+ZhAF4tu8A5kbh+C7b//4pgqRgIucOrqbbJp5SpC4oBJw3hm/RliXZBVgP/QWCLVM3CiUol1A5ahqYqwgB+qk2o9jhJ3A2UK5XjhUpb5NUzjM9JddjCi9hJK7aRkRJ1LyPtXKbwII9x5ZwrAxGsGzMnkWrX8CgeaPDbLT0YX3qm+3llg65ftZ2WLgVCYkRJETrX3Eg72rS2OewwKMjXd8Cy4mgZPXiFG8hIrOdo/iAjA8w4Ub9fNrbjvup7Q/8m7UNGcbnCJZWNHplRoyvjuZrDOoh3uZierOYQju4uxsOgOFWIfmvKmWuNwMrsshVnOcTBWrQ2nSe5lxI6NJnu9jO5z9jtERj2ZAnvcyF52QdysILfdUkNMtdPrzieS5jEuXwaEHBVIwFFWaLfHY3Htu2vrJLjJ2p5ZLYPdQyySYdpe17SZXZg/EkbzlQ65JezgH5saGxD8+bQsijmOlRy3KlkpXLhFUUzltBv9LUhzE7jSwDSUiw9DRnn+N8YzJtcTZqDc/qrWmQA/FVQh7Ca4/jRwwQqDoeKMVMdLLttSLo0ZpMQsTmemTRLqQhAJ9Q5e2msm9YPp3G2Xg3qfJCObeeEEpcIE4LRIYC3uo3llb4TyEutJT+hnP01yeyICXzetbxOc3ZwPDNFGl7FYNkxrK++RhJFSYe1d3YJo/iQnzie/XZ28IKKGRFTw1CB50h7bdYjeqpUDujpLMuGXqmrmeIUpH21oDnZVLBXYSixLDsUZyitdarO0L5tj3DWOrSq53eOonuXKNd+f7ZbPd6I+Ps5iIuqahQArZo1uht9aWfyGWOXn0RaisW3nCyUHGT7MOOSjxrYjOdqFipFDnDgCNZ37a7hxmIxDn6YaTCds9xruJkUhf7BT1FiADM5nioyeLzgxQDtQphN4mKu5C3e6v9GIC0rYE36Cf6nTO73fjvELXpKSnRClc4EINNBY+7QdxtJTvm/NjEog9NPnOgGgELKV1XQuDzYnxZYi5eKtGI2ZdFM6tBxRDI6di2v67Ixf9O2NxS4tBGu8xK12Ee+K476FPewiWLtd2XkcgVv0bWtB/DfoaSOjmSWdnxYt/12b39+3x1f8051NOWzDJXKcV6MrAp9myvYRDEXHulEtJSJRjIoW5ja+1maO4S7cseTY+/nUft+9/uwMljw9P3+SDjW1WJsmbbf7ey2ZVPAHtqx2fXMM0VWiwwq3cl/XKt/UUYON/EKjXWSWMbEZCdhtmB7C/5dd2W8RyauQ6XgcHNMyhVJ3qsA/5Lz/HqzmKP5nbwci3qSeIKmHTlpTTlYBcZermQ8zfB4g8IcLDW64N8sqCLefvZoNQ3xJlfzMA8dMMLn39n/i3uZcMhTgT46Zu/ouOfIylAWe+f+VSZ3/z2elf0jTzKGy1p+595Dz1mvs3mzr22+Ratj8hbeWXVEYCEzsFwajpiZyF7yPZZrZdMkpxYt+uJc/+ouv3Aks3jWl07u1izEua+sVEgndbxkUylZdbI3bJtuLNeencQO/cTxfIDYPN7c/gtuaC8KJwrNvWQliUif6mD16RuSIrSEOsM4ruPw/LWOWoL3d/WdPFFzizafv8+FbhZgEpe471RWGb5TO1J3sEIwWO6G0VlHnvjzHxy7WaStk2ggm3IMbD5hJKfXePqSL3ELP3I8W6YLYWm5KPfLK6GYjQDkR/RNUsB8UIZEGmiZqUM25KZOVs7KdyOfiwqNicWRGZLOX+OeMhZOLXGLBsLs5V5v69d3fpueEuMoZrnzod+kJqXfUUhaMp+u6EUtSzmMuaUdwLb5ilN5j4vdv01hBH9yeOg1jk6cE/guwSmwadJMk9oVJQDsXC8CCv9hmPxTwGSfldQ5pmFzAjOZwBWckTYziKkKMVdGyrK4r/Z+/tjoZYpkQYVq/zsHy/FO/+1U9/bqJJyDKqeEOWpHqN+wlZIvPQBlHnvdiUsdoDl5Jt85JJqBlIYsdGqCyf0C3udp7mLJzmaBCV/V/rOiIiqS4KP1l/pKXVnplG7+v4Hcb151nZu3d9NvTWgpqjadM8GyyEKkvr7Bq+J7jAe0Y8NShE9suYjx646Le/7+R3tOpV8UVb3n7ftTmcwFbG4UDp4b9nUcGzWFIxneTVOXymmRsEcsTL4FLmyHALis2Cr31oD8DQxJFYvetf3n86dkqHZGkJUgdmjN2O1OdoOzFrkO/qaVNbzEzeyrTIi7LxQDKny49ExcxRW8xT+YqX3vB3JemPOV+/8ysokqWJRSCsE0+YLTNTZ89/rEeJ1rtO/i8XIBbtrvhoQ3vPY0odEJcGunL7W/DSnwaFD8UjkRZewtpC9fcLq7UBzuCJYH2hTn4XZMF8DjQ9IFxi2URgHoyDoMKwZ79sDEiaFahP7NVebJRzOmz/ec3/FPzSGp1cnHsebMw8RyHficiOCs8s8xJ/ADbdjCR4zkx62HsILuzK7rI87ZEHGJFi9rJdImDSQx1aHwkPffMXO3lhoEQddw2iEeW3ZqYiP/6Lqd6MgL3P6QlxXjjIE7PamcOM/zQt7jPD50P1+W/x+W04Pjenvgf9MMOuhDmy1maIHAB63IH8wt3Ry5H4U+Jwwn2CK7lp17InRhDb/v6eIU0QSdBOdTYH5WFzp5rJz7DcQCLC2uFqFhMLnkKF7ecpbGg9VAEnsodPmc5sQ8HK6B0KL7cZWYv1wR5YjhKgBcn/MhTdkXqzpzadmLHOYoTHzDP7mg70rtGIkR20FLRvEh9+4f7VzH+bsSwRrWdhE3Fnl8Sv4oV+nyXRpfW6jF8xyawCgDbpTKn74T8A79Nx3YIDYRDuDcvXSciK+0KVlXeKLbjmVRcWBRbcNwX37MGfdvcA0fMopDi4Mpf9vS079adN4SNCsHWmfV48c23sjC7UXuV//nmNw1c1601El69I9/kEK9ywt1NL+xV2FS9qP3JS/Nlr26F9+UCKbsqLWkMYanGb94YOgOMMVZdK2oAE4nGlKvST/3XAbyarNHubTHgqZuPa6ZBhzHj+JaSgRL3GL8ztYuYSuL6eW0L3ifk30CtW+3ezRwTFORt5UrYfLXHs+Fh8GSESzP81+6OZuLmMyAREflXIaFnQMKcjzn1NtJQFq6ur012WS1YVe0QJfoMQjlnTrTWVzUPnVZx994I09EfXJTanmKMRjYbN4hJkkrTTjyjxwz0wvXmx4z+tqnpnIrL1FalhDQ3JJmGEZcB+vbwot4i6u4mZepwEspvMslvM/57COfTCronbTC/VsuZfy2VMcjbdqTxjlM5XXf4gtgEWkyLeC3KjuDPziKQjWC5RsXBpbmkBzTzEsNDOV7DXzuJ/FNjIhxMZFLyaSShfRjw0aTWlL4lcGhbfI7BAY2GIYrUN5FOljKez9ESVe8w6XiGVx+OVx+OVkJYier8sMFFu8EE4qLxaSqRKxTyndpx1nbtmNikZgh0gwdkrd5bXQsmTpasIMcyjiPj/htq74QrduSzC8cy58MZGTRzwD8k29cqRv3GcZbTJQH1C26hOJV33DT7yNYgABmpyRZWr+NF8F6nws16opeyc4zVFMcBqxHT7u7rJlOW3LT6hnDk7TK9SAIYYtS/477vTQjFkXJZbRK8XJaar9rIDGw/jdVPVttp/I2R3I8M0mmjvM7zwscc+XK2xmz5Hy+29GTqaWDNYmlf3Mz+8h32fQbbC8E2OCkxuoaxJiX82+VlcYaRITfPgDIds2+Aj5rOMVNyb/DpYGO3jNrI72zS2DOHOpIcXmwXKJR5T2e3Goplxd5GzE3feq0raziIJZs3wNeuCadKVNgV2mEF7mFPeVJoT97ysEg/+FUq5/sUCnsLzfdOVTaDE5kypYj2L21gdPxNmYSwtJU2/zz6O2M5Z2Oj8X5gbArtj3CE/vEBlM6NplUMoqPKcwLOnXNC6Lac1XH3Mzqww8qgiXt7qUXaMVbzm0EKtf/hylC30Tg24b4b1SmWWK+Mkz5QTpYJbv1PK98oGEpQv93lg1DuuzkQ0Yxltvc7+Vu2IqJFNVxaX/ShVVkmSLsKyfw57iTf6TOokehPlEfrGk5eUtvf1MTTgIxWrONGfNzqSJOrFexXimrA9/ZPkyAaoceKuRxpEUSDDqyjrQk8VyuzfqAIW1EqFY+iztSxzGU73mQRzmc2Xy1uLX79ySfeKZp2uTlwblOefrDVaM5edtbPBm7MySCFf853BfzHMcqO115iBbjuRrwFgNXa9H0nMsvKwa7DMZ7GoVTFEmM0BBSki9/21RKDnCvK62WNFdypZKswILodwYkBcIn6Fp57s5aPh9XhiW+baA9y+nByphYKN7kKrp08CIBo3kW66dfA9xI0h7mYU1myR/BSnIcrPaK9pgVs0mhnkSimuyO+3efg3UvTzJy5cOYhk02ZdzQTkzUmgYogo4E4Bh+Z+dOkMyXh7UQO+6mpHJME7bUFVJSVUjzbC9sFdump4KbsZsjmUVm5+YM51M+6XCPe30VK3UsP3M9rwEe7YF0eNx0Ol7ayMYQEWe8Tcrs3UEh+NZspVFBPJhYJBDlu1rvOUZjhisJAtChIJzJ3W9uib0PQ+K3v8o7MH+fA2K3LPLS6niSe2lf4EkmhRZKWJYLE5i88WhePuwt3un1Yuhv2ka2k5MRddPmEB5Qkc7PV3UnYCGe6dlM4+gW6wPHrqtpxZbafIdP0XQCWuIZ3eiQomYSfFaTlLQWCHD7CD5meWVbV08zZjRdaSYj7ZJLajIXBTr6Y10m83jX98HZpLm6tiEYrADWJ6I7YQeagwDuWXaB9vmWlzoyYgRs2pbAbbzIjr26gzWaZ7XPUoxZKnDU1BpYkXCn7I83ddqOiqSmqUMwjMA9PM79dEzbEecHwlbWdaCkwYHU+NcFX2duyTb8FY5qH7um9HE6GCXkpjdNIittWUVbjX5IXjIYaf+fpQhFB7rZ4ahYuFLwcEjskH+wv8Nl2md119QYMzVxSdXUEK/fMrJMduO9fMsyaF8gPOBEJQQtF7FYoyCvLEws4whmk2SIYw4klXOwZihiyzE5eFxNPK/9nRyCNwnklamLeBVEAQvJI/wd7FhGlsk6OnNqH1EWfFf2G5zUSUxy7u6qbTGnOBqMf3I4pdXi/bY9vRf1XfvQDM8J9UvlTKgdJdjdSTioFKG0b+0T3f9XxDwHa+YGL6og31VyMpQNOonzimeTHqklI6GOR3Zc5TJkj6l9yGtbnChRU0SjtXYKN+ExHfurcKQtq+1AC7a7cjGBaEscZmb5rq90GNbD2JPj2S+WSC91ZzmpaYrjcvNNcOyx7jWH8ynzy7yIxlHM4tWNp7qfW+Q38Dmn072jCMfL/nM/HnuxFbVYTjee4w5+/C24MF3de66Lm5C2vaGA0vpMyslhb71wMNXnXE42i+jtphViUdvTznQWUcv0rpWQaLCGztzEk5jEuOioDdy17GKuWn6LKzIPOoUICDD6XAYy/68EpnKOe42ZOee4hQv1pHANb/CjE2lPcIIhKnEsCP3J1ZWCimI/uS6b+6FFIiI4aV1QjuN1ruOJXz2euzBx74aoybx1uUznLA5nNsd0anpRkvZrVV+6sZxZK7zo6mHNvcimnGP+tXYE968REfCh5Z/y6SaRTlMdAMOACb752Ypabp9ssCIBJ0F1eiNGjNP7bde41sKmUK/aVCCwfuAE3gtxXkBsNEzDdnGbovJQ9A0JlpfvUF3cf0aHSaSn2XzMKI5s7lVFX7Pz4WDjFBMbL7TI93M/99cPctaJ9dtT+ZxhbGp0eMd8zhPApopc1ta39c4f5oQdwLbVBYmKQcnw+OaZzbTVPo/jOgB3Tk9JjIVmEwAK033ccabJ49ynzfmq9d07k585jiIF61pH6gHXUUGr46yXzrpQTg5TOZt9lWIg3ufMRQ/yKMRiOr2Ish21bJOlCX25+HBdwDqeeVI5yvxp6pF224aTfOSp4rr/BUswYlzKRHHjCE0tEErzEP5sj3fwLGlUc8lgb5esDVzfO28K5B6IYFm4kQCV5qDSKX8tzGkUVYKmPtmp5/ms8gQW7Q5KNxyMmYY3wOW5vQiWOCaDSq7nNZ7mLh7gMY7lJ7IdB0sdlD3icAYBTNp3auA7m6bTkHpDvaIA919TB2luSexACe2DmDnThIceCjompkmlE30zsDGxsdHFjMNAhH6TVXpPLT+dTjt+BeC3TcHJCeCmktt46K9hfND7WT4c8II24OptsTsTDln4czHM+CnCs/aOF2DIEHtGATIvru3Cdlq5AFp//40rfYHFy9zkpq+xbfLYy63p40OPB5iSIHhrptlO9MSp0MrAwRalpWjXvJNnGbtG9JUrGU8a1TQqVY8ZqTFO50vyc0U/OLaFiIz+zjGuMK0Vs+nBcu7kOR7iEfHD8nLYIRyBFukV9IoIXFf3FBGlNrDJTBT3td1ZGFTHeh95GNjMdIS0rajF5F1DMbBpcDagn9tnuMcbpkFR+QKWsZ8cykhJtl2liGc+8vpGRbWeCt5Fcy29K19Or+RVLvgXRMWVC673E406z/JC3uea1SIqroKRBxQLp0YOqdbGVlrg8Rmpgf2F9ON1ruOoFA+CsL00idIq8d4aSDpgUYG0ifvPZCXdqGnw0mMjeq7iRQRXmrw/UUUo7uH36CC21Bawjo40NuhjYlqiHmGdMquVu5jZthHYeKZleP9PMMT8IcXok6njjB4biGcGNuN4nH9zE/Ppz7LS5oFjxIZRypo5U5ThRRDleeKZ+9wtPbIkfte0yXnhGKWStbIuUT/IwYiVV4uNQJkl1pgjulewgL4U5ngb/If+OpPL13nMly4Q3rehvkypVvZbvATIgTC+vSUBMhaxmEdbZNgWY1pNbvKc3sXN0M2BtDJb3PtJfKdhSifvOSm80Y5FjBitE4RTpjKon8NUNuwQG3qZ+bqWN9i5U3dKr2z9rfv/eFI58cyldVCe21W95/F+kaCukL7EJ4wK/DZwhYkTJ2IYBtOnTwdg9+7dnHzyyXTu3JkePXrw66+/HlSjVFvc6lQmcLlbVh9IlYSkq37ieLIoF+H4OEzuBRk6uO3UwzYzh0EaV5X3Q10qx7Jhw840XuEGN/esWl5WlHaRbVSThoHNA3mvBq5/2977+HRNz6ZuPa5JB6c5O7j8GEc82bDpxFoy0rwSUwuTu3iWE5khyP8MnZUX+P+Ie+8wqYrs//91b/fkoScBQ2YYck4qUUDMGUVQUdecMKw5rauuriKYc84K5hwBEVRAQCRJkJzTzDDTPXmm+9bvj7q3buyB3ef72895nnmmu2/VrVx16oT3YQTzSUZT91/s+80Q+iFLsOy4N7LArQ1tOFBnhr0wF/+96yfxNH9XKl3nuxesby4NuE1qm1VBWUWImcgF5RKZOxblpf2X8kaL5KCdbdhj455oGrUi3VlN+bNjQWyua8uOqny12TnnXNxR72TdousiqXj+z0Y/8rlFuxwBxi01ipJ4eOZpMgZLxdAzl6smDMpozq2Zzyctt5cmxfsWhMczXEfJgRBnRWZxBIt48EGZLjVVQo6EiaNrMJq5XMuz1JDFkgqHp6knVM5hLbb7q+kUyVsHWr9+0KaNekf78B6yqOK4HBuK4uiWkumaslke3AYao5hHEVuoJ52d2KCmiYYEr6yTkp5Plsv95C3hVvUAFLCWcXwOuq4kG1+vstW/yUBH1/0h+2vCximqvV7YjNtMlYq1zzzWXMbaaCrKhNV+q+xh2SvJFpU4Y9gF8UsjHQwWaWlqK6wjncb4oS3iHF0y1a4175Aiqzh9mu25a6BTUt+Mrmzkt7U5ZFGl1P3/vDNBW+yQOUZCOFRY8PdVl3HDn7bHrfNSujXeDnTbjX8wS+lU0LSqcxUjWMpgbuJxHlvhD6mioFeUBMtu62cmkr8z6HZQfpDMgoEXp69pJta6gFc48N284zh+6V1c+Mf1PhvInIhgEMtI/XWOvIiA6YFpT86C3IQEYA1b8SKbrI5ZJ/fk7p4tx8qr5rfIcohwzodNeUh4eQAAIABJREFUm1AQKUbc4Iy8uYx2zFWLvAzW+PrpgfBCqm4YhIi75j3A2/v9QeBd+TRBgS4vAhNzZipwXGd7WmIzXtXVdns7spUJrX9Vzwyh+6SsQWTFg0wIKQZwJi/Or2Bo6h8sXChNBY5Pwh+6Sti6dSuvvPIKQ4faLpZ33HEHQ4cOZcOGDbzxxhtMmjSJxsZG34uaJF2nCxsZwmKWLfMPSlPW/AlCgWCM4J/ILZrVMYTFgRKshKExAds7wzA0fljVJlDd+AJXQSLBzMILODVvPm9xEb3TTCbIFyonadWbJAVYjqEakp+TYAPdOKa/vOnGyGEzxbzNBcxnOH8wiFRN6seNhOBiXmcYC5rUywdt9MJR/sGoMaEzgGV89btU5w7f9xnP/i7nhzUWvuDdjjHaXeF2RLi1/yzfAg9pBifyLZ9kX6R+69q8nJGptkHregeEBkCGVqvwWoTDAN15cLpC8mhC1tNcWM6Ns5jNvnp76fT+25gXOjrpcyclc1E2BLzHJIaZXna6Y54OZeEhM1iHErTOOjRbmaL4DzmbsmgY7fTT0A8frDaLbp0T/Ekf2rFTGm4ScsUms6i8QuNtLqA0JqV9PXL86innjfEX09Dd2L6DuCnZnLu1iFfEZWRRTZqJZo5mz9EDjVKq+VDmgzzKLfRjJV4yGuIK/kLdyANuy8V8T5g4iza3CPT4aZUfbH/Ruo1Mt6VeMoXP11zkg0qxKGzy9ylWLD/H+AUNUVWNaaNl2kA+yD/Yh+2ZFMRgnZZpe1y1HdlJ7ZVr6M2rvyRn7J1UGCr110/TlafcYtPrVnP0kzMUkBE36MUaLuJNAFqM7eu6OBiGg7kWsKm6FVtrPZHSTTo3+ytm/dmKK5DS1zt4uElby7ahvWgYvMsFLGBEIA6WdWGU9dcZlL9NMfCWdNUKmdTUXrl/nyCEwbe77Etzj/RtSdODzWCVk2fXxzOOlfF0ahLpqv+VR5u5CIsvHcPnxzxr5nVf/gZ2r2Emx9OqwDxzNfclLbBOnkfTqibzHJPtQCGefaZXc3neWPvLbUyz4kMDplreMJjHGF9ZK3fkub7PTIzlXc53zQ933QQ38xgX86bam6zfmyJdg0ytht20ZkLOTAlKa5J13n/r8KY3EkKprdOpA11X3qgGGgON3/lkWXGTZfZBXvwSKhKCs0KSSRtuavtnzU6mfbAqZBhcdtllPPPMM6Q5Yqd8+OGHXHWV9Go6/PDDadOmDfPmzWuyYv5SdDab0quyUvu2Y8VsS8ZI1pHOE9zE/A32YnUyY96DvSk3VKHp/MxoV1LvQuhkHrTp1MkJtnOnbedhuYQ7YmV5I2z/JzSyxV/oJORN3wmTDqpDurKeD5nIhbzN7UylmmzubSXd7i0k94UMpxmVQUXQjFigWuuOlm8wqfvvATn8pIV0VjCAspjcjIVdPRtB13DrSpzd72Wew1rCb3ukCTqwnWNTHfMqFHINkFfEL4RGN6QOvVGk2AdDEwyWITTuXH8xD6ybgK4JTuIbHuZ2rjMNYeVCDV7orfPqmpQUWjSFO5I+W9gwmPN5T9mXWP20j5bM5pikDFZNlcFkXiBuHohG3OATzmRDY1HSsl5JXAK40Y31sE5FVZi9JQ77KF3nLh7iZL5B06TKb7jJADr7fPvuMBfyNlv2SEnhigO2VOlUvpT1CvBqO4bZigH5fnM3Ho3/XR7ejthsdYY1t2T7/5b6Pofzu4yf6CEjbpBjwpOo5RLAYBmEeZkr2VQSCcRUax4JZrC8UoYpldcEpgMJ/HkC39E8JJ0BnHM9yH7wvd86w5tvYmzchKbBZbzqAlINYrDCusHXnMyyQZdSWOjeKw/VDtOyWXHWb8q84dyODEB8EtJrzRvs2VKBNjYINtBVoYd756mREESypMSieVolAvce4NyDTsme61KhHcss1pfIQ7o3NiyIRZdkTncx0CKgj5QNlqkivKz7L0ztmCRUTuYg32+WBM2aT1a7W7CfNqnBwMMWWQzW+5yrfvOOo+VUZI1d+5C8nGwvyWAKd7CFYu5eJcGdjbJy9LhjbnpMNHIj8r/XTtldJ/e8OI2vmMwLSZ3A9FclOK4VKqeUFpQssIM7N+S2RFsUbFfqvUjoGBzHTKVu9NUNQ61zZ4i3g5ms6JogajRjFX2Jx+FMPuVmHjXzyjTvODzojbhBVqYE0+3BOjbUtmMH7bmBJzDQWc5AymvSgopSdAUv05M1CAE/cyQn9bfV+Uv2tueNmO2p2zyngRYBdmdqp3388ccZMWIEgwfbCKtlZWU0NjbSyhFPpaioiO1elD6T6uvrqa+3vcZiprfPraW2qqd28RKEKQF75IlGYrEYrbPLCCILmXXzvjB9Y04xslzopVGhygBYuyGTX7mJy2N+kbPREAfyuYMpdGQbhe26s6VugCvNO1zASOZzMW/S9c+ljEgk0NZLgLVvq4/kHPVeWb4hdBJGQtUhFlBuMrqoaBY7ft/LA9zDh78VcsL4GFo0SjOgpraWeCzGaOaxkn6U0kK5zibMGV1bU6fEsCUEe25kUIsQ/nqNy/6BRIvhh1Rfo64BSKeuXo6Vgd3mVnnlPMs1/BB2654b4w3q3Y1x90GWiNdTVVsNDnsXzZTOGJpGlZlv9Y4WbKg8nXHmdyMtA6dDYpQIQ1jE+5xLdrgaA51YLEZjoy2arqmrshzO0DCIJwx+r+5MTmMDGoICyridaeymNdM5l5TQ7S72ytk/KXV1pBsGlQfps6ZulqWGbXx6PN+TEs4jFospMND6Bqny7sxGYjH7UlFVXg2mVCkWi1FbVsNZfEKL8hI2JqnPk4a0CXMa31bXVNO2bT0lJSFiMakK06qrbZsJT0BXQ9jrq6pSXmnrGmqJxWIsK7H3hC5sZBTzEHG3V28sFlPQK7FYjMa6BqpEFqW0YFW1eXsUghc3jjU/GsRiMZolEsxzXIZc76yoVB5m9fVyHwkTV+2xyhJmuxvijSD8l7Ga2hqEo++y0Kkmm6qaKiANDVmXZLYkT3ADQ4sGsJm9bGxoR89YjFDIPjAS5rqbwPd8hDw86+ob4OKLMXgbTRi+dzc22nvJ8Swgmypeik7kGS5gd91YYrEYdQ32IrDWpJe6s5vD+J33OF+mMxnY+oY6lT5h2BAqAs3sM4OEgbnOI2BKy/eUCirI433O5aVYjJo6t2FzXVUNBS/cQxavUJyxk03leRA2VFnyYJfrPQ40Ntp7wqecSdk6KcUrYiuxmLSTG8NS5nIUCaG5GKx4QvjanEIDIa2RG/vOor5xHQ312ehCUBOLUUgN+7DnapZWrfJ3ZS9n8Bmji1OIxWLEKmJACzD31UZS1DxIRmf2W8VJn19OxwYblDcej7vySEFKgtp6ub4fzptCLPYma7dpKh6kEHIMZlSdSgGlKn+otpYsoKqyEiMWIzvDDvuVrF6Gh8ObxTFkUU1NtRy32roaV95az12gHTuoLSkFU2uw/0ByjZURr6MHa1mHDIWnI5S03VmG9VnHoIJcashwzX9NNN3POgnWNXTmeGbyZsXtLKUtZ/AZj3ELdfVyT8ohquwoKyuriVVUoGPwBeNIrCnkK16hgDJ14WhMxJss8zeGso9Cmhs7OJJfqU0/T6X/en0xL1WcqdIeF/2I6Zzqf4kQQqxatUoMHTpUNDQ0CCGEGD16tPjss89EaWmpSE1NFU6aMGGCeO2110QQ3XvvvQJ5iXD9FbFISF5XiCH0EoM4ToAQrWgnAHELqOdBf0M4y/NO+ftpdHP9PpIrRYjGwDpY+V7hUiFAvAJiONe7ylnAUPW5F4MECHEsPwgQooh1rvdkUiUK2SXG8M8mykv+9w6If/CA2b7rBSAKaCn6s0wMZ7gAxCW8KoaywFXHdxkgRjFXjGK0+u1WpqrP1/OkK30HNvjKXgHiyUOsp262dxiXCkDks1+M4Q6zv2UhJ/CmACH6ssJszwSV/3BOc9VnHLeLDLLU9zRqxaXcK67jKfE856p8o7hHFLJTfb+Yl1zvSaVOlFAgltNPHM9tIpcyAYgxTBEgxO8MElmOdgxglhjODDGImWIoM0R/5ojDWSSeZbKoJEsIEM1BtKWVoxw7/3h6iif4uwDN10et2S5AiJt4VCyjf9J5LOsoPwsQA83822knSskXA8kXIMQ93Od6fzbNXHXKJEOAEM3Zl3TcmrNfgBBdWK/yNqfYl64dbQQIkUK9GMGrrvoezlcqXU9zPXShvzn2dtrnucrRHuGqq/PzzTwi8ikVIEQPc09oyZdiGDMECDGIHwQgvuFIUczGwD7sR2f1+VgmCxDiQl72tWs0dwgQYigTxZG8LHqx0PWeQRS60ndikwAhNNIECNGLRWb/bBaY692ZX4C4BER31opLmSYA0RbEOD418/8mALGf5irPkUwWl5vzeABzRDtz3lh/Y3hY1edEvhFn8rE4jXcECBFHN+fxGJV+FNcFjv0+WogNjn4q4i+zTiNVmjO5VWRSJY7lB3E835lj+pbox1w1bkdzmwAhhnO5axwLae2q901MFjfziOjNKnE1F4nBfCeG8KGnXjLto5wjjuBU9f16nhRjuUKAECfxtUo/irkChHifo1xlDeE9X3sXg3gJxFNmogSaWGI+u5d7Vd4reUHEHPm6s1bcwjRxtfm9JW3NetwiTuYrAUIcw/SkawwQV4Go98z74Ux1penPHDGc90QneggQ4gNzf+/FCJWnmNW+9SLTHCEiVIiudDfrjLib+0UHtiat01E87aqPtZaG0ELM4GzRmWxX+g50FCDU3D2e78QAjlf5B9DStw6tv/GMEgLMPUvucdfzpHkW+OvWmdUChDiHF8QXjnkwhC+b7Oe5ID5muLmOvhEgxLecIECI7vTy9J0QneglmoHozSrz/Z+KXxgh7uZ+8SA3muN0UZNlHsWPYgIfiDmEhABxvuvZnaKAfaIHawQIMZH3BUQFIKLRqOKJEEKI559/XrRq1Up07NhRdOzYUaSlpYkWLVqI559/XmRmZoo9e/aoDIcffriYNWtWIINVV1cnotGo+tuxY4cARI+UP1TD17/6nfj87l9EKnVi3dwNIhqNitoHHhA5lCcdxPeum+t6r/X7vidfc/3+xPjZIkyD6zf1V1EhNBLiJS4XAkT9+eeLqafNcZUzm7Hq85ynFrmedU/Z6Cr/Xu4Vhfo+cc+oWaqdO3bsCC474K9ywnniRh4TIMTUcfNENBoVa+bJzfzzO2V7U6gXadS66nFNixlCgKh85TX127WOBfWrOQnVRAtv85X9a9HZYtW59x5aXcvLhUZCPDtpjohGo6JAKxX3H/WDiEajouqHH4QAcV7B12IUc1WhVW+/o/J/dOvPAoS4gcdlXXvNFHs273XVsfGII8SD3ClaavtVvntGzxat9L3qezfzkLD+FoRHitMKF4gTIz+Lh06YLXIoF9FoVNw0cJboyl9CgIju2aPyH1Pwuxjf+hdxVM7vYmL7X8Rnve8QESoESIZGgNi1YoVoR6Yqw9kPL58/S4AQZaUVvj5qq+8WIMSrXKIOahBiMs+am84BAUJkE1PPBIjKn39W86kXf4rKOXPEZopEOTmu929btUPlO1ByQOz6a5cAIZprJUnHrTMbxe1MESeamxEIsXLOFl+6ld+tU88v6TbX1ce3FU0XlfPk3Jz33GIBQix8Z4WIRqPib0P+VOmGMV+8zkWi8qefXPmj0agYwxyRRq2IRqNiBL+oZ08UP6HqcFbbXwUIcUzeEhGNRkWegxH1/lV8O1N9fvS4rwUIcWXKK759ZzS3CxDinWvmiteGvyjub/Oc6z2znlgcuKeU7JP70GGZq0Q0GhXF4a2+OrRhpxAgap5/XnTlL3FLzosiGo2K2Lp14jQ+FyDE4MzVIhqNilKTaQYhHjt9lvr8aa87fO99ZswMVZ+T+UqczmeiS3iLACFmcLaIRqPi24fsC9e0k2cF7nNWAitd1/Am0Yyo+PFpu81TW0x1lR2NRsWHIx4Rr3R5UBw4IPtjytHfyrEa/6Mr3YZf3czvhXmyzQsZIupOGyeOyVssxredH9i/3VM2io9vnefK/9Rp3/nWnHUePNnsTlfaiR3m+9ocHzBA1F98sai7+mohQFzE62JY2u8iGo2Kf527XOVtRlTcGH5K5XuMG8XpfCb2/vtpuf/+KC8jX53xonjYZC4nFAT0seOv5oknhBEKuep438jvXGlG5fwhzu0wTyz9WB72cwvPEtFoVMx+eonK82TLB1z9ZOWdc5+84C87/S4RjUZF+YLF4kpeEG1JftZUnn9J4Nqp+vprIUDE/vjDlX7D7D/FcH4VF/G6AClU+PTu+Spf+fdy/Aso8b1z3tVvikUcrr4XaKWB+6d1Rp6YIc/cK7rNFm+c/61Ke2pz/7g6/xqPPFLMLRgnQIiOYbkf3smDAoRY8t4frr4DIX57d4XY/qe9b55eaLenIT1bgBAvXzSnyTKlsEaImsFDxVNcJ5bf/4F6dv9RP4gCrVS8x7kChBjOryKIwQoDXH311Vx9tcS+ABgzZgw33HAD48aNY9GiRbz44ovcd999LFmyhF27djF69GiCKC0tzWW/ZZHTgO3vLx3GOzctkxhEXXdBJAKZmQ7cE7iPe7nPcvMGMjLSiETs6OGPcRM38zhZGWlkOX5PCaWgY7jSOkkgjSo7so2uNa0I6W532mMcoU5SdC+wmqbeG6aRQvYh0EhNCanfI5FI0rK9dNWKS3nJhGkIhcJEIhHKM6QIOTMrg0gkotC5Tj0V+uTtZMrb7firXqpW0lPtcDYvOdxdp3K7p82ar05X7bmfsWv38tSh1FVY3nNyDAzKSUuT9a3Uc5jLaCrj2S57nazsLDmuQIYJB/CD6TXYKFLJzbPVg8OZTzg1VbrBakLVNTUlhCF09V2wl5P5miEs4h4eoEjfgabp6GlptM2vobe+lkhkGJP7/8aEZTKmYSQ3F9Jl+ZnhRlJ16UEYDmmMa7OUzNU1xMjhE8bTj5WMSotQ5rAXcfZbepqcK9mZ2aRmuG3OdCo5ma85jS+5gSdJRudoH/KquFR9z45EVD+toTfZkTrW0pz9tGSIo+y46VX6HpPIjbxFuC64jk4yKEPH4EpeUqGUmkWa+dI3i9hqrYldV/L6enttX7D1QbJHr4ZffyU1RebLbpZFJBIhc0AvLOe6hQwnlwouznQbx0ciETqxhTrSiUSGKTU3QMeMMlWXvrm7+HgXNE+tNOdYcPy3ZsTITLX3l4IMS0WYfM1nZKRxfu+l0Lice3ZPVr9nZaYF5snJlXNT0+S60bRy1/Mz+YQ9tGY+w2lT24oNdOPLmjCPRCIYVTVKXT8x/0cikes4gOBDJjCRjwg78LrOKFwENrA/p/Il1w5YBBGpbv+GUwDoom0FYDLPcyAS4dghjQzmd5ZyGCE97GtDdNpLDGKpK2DvTc1e5aryKTBkkZpvc2uHufJFIhEmFK8EbQsi9y4aSSE67BHu/PFEdC3Fla4ux+293SZF2ikN4zcWVd4ByDUW1L8CXe0J6jfd/m7lacU6ouRSo3nBlHX/ezWNUHo6P+3vzUYuYymDiWgNRCIR0rvYoK6VRPgmcQKPm/nbsosvGMfZG2dybiRCebq0ZU3LSFNegZPbfU0k4vdctGhJSUdmJNxAnfeO+gUitlecQCek6/TtmcZRzOGz2pMYHYmQlSXXy8PczhnNlhCJyH2rJfuIRKTaNDMh53how0YikQh/7s9XYZaSbd91KcG2RVkZEs6gmWPfAYh0zmK+Gfj+TS7mAPmkpdl7TEaDVBU7Dfn7sYKV9CclnOqysXOq/YLG/6t2V3LYhg9ICesc1kn2dwGlhELJ9zIAUlMVtI5V3hTu4hFuoVOHS31509MySE+10efDTgcP0xknLS21yTItgwlDpPB3nmb6vvn0N9OnpYYx0JnEDM5juoq166WDmmhPnTqVBQsW0LVrVy666CLeffddUlJSDpbNXYjDY+u7Jc1550fTbdu0TnttcV9X+klMp9rhyeQ1qiwwUYC3lXqQ3I2m8U4AysnnJL7lzqVnBRqVFpnI1Im4+z1O25o4KWykC1OyHuT4bluaLC8Z6bpgAMvI44CKiRgENArw5Zdwykipe7eMR0WjbUNhRUMHFAKxRc/m3eMrWxxCJHFFZoHXTpfuEk7AtQ27MjiKubRL2cspjnAJLqwyr0uLcDsKpNJAA6nUke4GGg1BwjE991HIN5zCPciQCtJYUjLvfxu6nvmp0o6nc04p33IS2VRS42BEvhgyhemDHlVxwZwhR1bTh7P4hMrqELVJloTVjiBD7u0tD+NjzuJ5JrvQ9ecwlqe5jgry6MZfnCK+Us+yqWTVxgzXeyqqUziCJdzIE+4uM+dFBrVowjgkVOdGUthGR5cnXmCMTodR9/FF9qGcTxlVZDONW9m/7oAvVM5DU+T/zxhHD9byHSex5M8M1tOVy3lZgVcOYLkLI8gi56bcJkMyMa3TynzPnKCtixhi2lJKapsp83UKBduEgjkVPQF5QQZADkxvti+7uxmNwDEn06gjQowD5DOS+SzYJA9By85tX1mYhQznU87gtsK3AInQvpresl3OKngWoEBzJWhGjIt4Q83RcqT9XjhVV04tQU2486lWLGOQy+j6hLSfzEY7vHvjto3faQO223UyDDQEYeJkpAvO413aRdx2Kl5HgJOb2dA9uiYIawlSQ+4YrvZz45D2HoUN6HBOiBBlfPvFvrTX77iVF1aP4sstfbiCV1hFP4U19csi90V5p7AxDy0vyrJqN8SL0EMKRuJgoXLW7MnnCW6kuzMYsmeudUjbR5vMClLSpOdmhSH3CGuunch3dAhLA+qW7ON6B2ixDUZq1u0QQIaT7Qt7y1L4mPHU1HsB3HS6s45bTKPxpRxGbpZk7HKo4K9N8mJgOOw5rdBD6/blMcyxRjUN5s2Dp+0m+MqSl2l7bO/jPu7u8kGTbZq2/WwerJS4bVa+CFFu4TGFzeek3p1qXH3lFPIsS/Qzq3JorvR375ACDB+SOzqr6QXIMQyiwNkzd+5cxo2TAIWFhYXMnDmTDRs2sHr1ao466qhDqpSTvM3olGveCs0FX5dwM2xdH75MBeK1GuOkOhOBe/Hm5q7fhXAHDE5GYeIYQmN08Q6e4AYe4Ra7LAtQNOHeINqE97u+P87NXJL2Hoe1c4fcOFTSTSR3DWFjeKpYhAHpzU2tTqTSkn18+FsHf6IAOjljju83g+Shcg5GE1M+o1ehPAgtmIFLcj+lE1vIppJT+ZIlG+2bztiBcqzXmhMRICVNV3EY53IUJ/z5CA9yt6tOId190LpAIIEpiVtNmAzhPkANgwe4h2qy3d4yZhqLuVxe1YU9uEFiZR9XEUQK8C9ogzMMaslwSV0B1tGTA+bBuJ7uLuDUarJ93q7b9sqb50LcSN9qXpiQHgrUsSmDegqYznkKdfxKXqRFgC9EslA533EiALczjT0H0nwMVl4e1JDByXyjGIyGBujKRgooU2M3kGX0copqTFpRZUsWLCbi0WLp+eUc93wOcIQpKuvHSv7cZDOlx3Zcj4ZBREtuqKrpGnVGKpWNbqlJMmgAXZeBoGctlvNNupXLgydBiIl8yHvIUCThVPc7rOFMoVFxPwKNp7lelumYOsuq3LAjfVnlStCCElqx139hdOBXeRmfurJqXtjt97zULYN2x/j2ybBDznyxTO4lu+vy2VjTRtU9M0PwLhdweFvbewpkLNF/mqDRALsa7In12paxfNfnNt4e6QbBtTC0hqUvJyUFspzrLIBTtPbhF6ttjLMLeYuJ7f2BxOdVDWJ1eRsXPEGDCR78zNQaX3qLrJiZVvFp4QTDWMCaskKeMcfsYKFprPVg4c0BPgbr3e7/ZuphH9mhcswxtXDwbmMa31XJiAv7KVTzC+y1EItLgUOy+JNOemldsIZp+YYsJvAxB6J+BqueNNe669NBzq0ouaze5o5D6KS6Bvdhtbb5KEaNguuCcZchFEKY549V3s08xuC85GCzAL9Fe/FLg4QTSQh//Z2UTSVh3fBFILBohPiFdGoVzMrB6NvoCLMYB1yULr1zH3XwDkH0X4IM/GfkPczXf7aaU/lSoSn7GApzECzySkHu4OHAcoxE0xKsH83DJkQCQ8AR7fdwA0+54qkpBs1ksLqynlP4SoH1uUiIg4KVJSMZzFh6bzlB0sHdXisuVJuW8n9hagUltKTa6/qRjJyLvaGBZeP+RSIuDj2SONKr7YZMCQ/xcsYNnNRrq6ueRlxQRzrVZPM1p7Knwj4E09PdOEUCDS/oqzU/3Ejuwa7uFr2QuEIySxouBuuXXTa2iY95MAzFlN21/iL/SzWgiVA5sq1BfuLCtdBaYWNEOTctKzzItybzYjGA/275NPMmf5AUpkEzfdOv5CXq68Shh0kCliK9gk/gezKy/P1plXk4i9lRbXs5DmeBupmu29WMzq1reJ6raVVol92TtfyLe+22JgT7aEkLSniAfwLwFafyEHf5yp1b0V99Lm2Q0obauAlD4eizHzieGjJ5kLuIk0Jjvd3/B2IyvFLQPEnnAACje5dyx6IzGL7+DdfzhCkRMAz3+a5pcs5aGFDPtnpQ4T/FSeEkvuMnS7XvkeRYl6AoOapNDaQq6VOX/AMq7V0bL3HlncJd3LHA9kISaC6Xdos27cnkZ0ZzDLM4u6+bcS3ZGCWIfq4fwvF8z/rtNpPZKtXvuX3/itM4Z/391NUYnMt0Fu6QUjzvpSIzW+d+x7iXxu3Lz/4DYSwwXydZHuE6BkcPrjhoHNXV9JEfHK+5l38FYllYB3bQnpaVnXyfs2KHWq9s0zLOAkZwREfb3f7RHWcHZVVk7QuWNAzgkd+OdCcy++NALMwCRrC+UWJzWRfUHziBDyttlaLzMrphv+zb63fd5qprU7S2wo9278zrhWkoKQ+zjSKlCfmEM0lPSag4jvFgYSQA/Qrd0AT54aa9rC/YNY1V9EPXYdl2GVP49bcPAAAgAElEQVS4gbSDnqO6JpRGw7qoxshhEUdQ1ygX69VmjNAp3Cn3esOd36J06qglk3NG2DFMm6K4sHCwHOdySO5TFlzGZorpE4Db9z9isNyzYmdtAV9zKo0Js+KeWmwob84FvKO+Hz3wgOt5hakL9l58hAjGxLHIingeJo5hgU6CCtsCsNF0TW2TU0Mu5VzOKy60cSf92nA4O2I5vt8PhXQdVpkQDFYQWGsjs/qjE5u5zcSq6dA2QRc20D5duvTHHSpMSx0TRF/W2Dg7q6evYNAX97Le6PofSbBSaUCrMZHnAkLlxOIZLnBKL+Ci8E4zTXPBB9igqw4GKwRNhcrRECZis2DG0q70iq8A4KMNNvSGcyN56K/x3Lt+EjN7/p2Xhr8d2H6v6sNVXhMqwotiT/MQ/1Df95oxNgGmM0l9XsBw4oSImIFnrX76x77rGfXc2UkZrOZ5Cd7nbPbRisZ6Q6E6n53yWdL6vhm+HIAXkHZHBnogPpzV5iEs4vHlknG4iwexwvmAlAy3zqvjal4kN8duv4HOg9zNBiTiu5EQtGIfN/M4M0wVlY7hGusg2lsn7V0ONLhjEYaIYxBCx+AfmGjpRlzFMaup00kQZmligO+dITMGXbOMeGDgcGvzDYXggTuCpZYAx0QW0wd3QFsVKifFg+dm9uX5vMdRG18222K3/bSe9joNAiiuarDVWVso5hUuZ3DcjSJfEpVpKsj1qz2TXJpuq7ybmRxPrMa+so/Pn+tLZ93KG+sSvM+5bI/lUkcaaVqDL6FzFbxWbrurz4/2bvLiqSP3j8/MANgpNLgYGi9NzPhSfa4hk+1V/jh7htDQdPchqqJDNLGmLVLAn4Y/T60RHORYlWMm3eYIEr816gbftPqjqlbOhR1xuT8Ut2/kAxPCY36tH58LIGQOmXWJsC54f+Ot5O1J8nvSWL3mZGyPVBXrGKSGEhKgE/syMpnn6Oaw7VNtC3hXMtrY0EEly0y1Obe5ZX2TZZF10qGdLiWpEc1er0NZxJ5SydwOZwEA1/Esm3ekuC4GJ7ReoT6rC9whCkfiwhMCDji+xzZeTbtWfZ/NscznSF/e/wmD9XGXO5WYHWzEZoVs66nF3M0dmM556CQ4i4/IcJuqkGGKY72H5Ck9N/FO+hVJ62F1rFQRwq7yTH5lBBebN1QndcyvpII81nY6mUL2cU6zb31pTq58nw9X9khaXlNkAau1ZSc3jTLDYQhBOrUqBIcLvVvXZagcE6Ax7oAmGYtfDWjRFRXT1Oe4I7bcQUwL3HV11KMukaJwRKyN6II90xQyM7jX2F873IbPGeEG0DSF9A32ODqZ2ON67OC51JvU9wju23ka9UqCFatPl9IhIdxAo44F8Ue0mMUV3cnQ6khPSQQC2zUl1bPSB6kIv2lIbgS70YFAL9AIOaQShxrsGYfq24gbZGZI9fLzmcnF08eFfnR9/5izqK33D7rV5me5Dl2DXMoZzgI2YQd+Fgb2Ye7YlHZ4gsQmGh02D2Z9p3KHAhl20ikFtt3G0YUSYHLqdsmUGegcxw90MDd8y94DwEgYCtfopZXSUPuDxjN8789kHyP41TzbhE/K5eRNpj8TjMMnG6LTy8NgWaFywqnynZMj78mkjoNZBKkgHYUGMfiGB6urhJaMFx+7q+OcI14GK8n0sQIeO+f31gZ/DNWQGf/TOsQbSSGDOmat7+BS6RnorHFIWWoMWzK2j1bctuUqnlxrB2MHW4q9sqE76LqS5p7Et3Rt7nYksGgU85gaeVB9v4bnuHbZJb501j7gPC+zdfOMaCI6g1039SKZxwNQ3GRes0+dlwivgHnSX/fyr+Wnq/daDF1uLsp2NZkqMj1Vpk3TpIr1UMwDslNk2ht4gpe5XKlnvWp+i6x6OUPlzF5WwKPcKttmMlgn8D3347bp9UZRuDPmDzvnKsvc43sW7Gfi4E0UIB0kXt52XFPZCOkGHbUdZFLNuemfMR57XVhjYNlmA+wtCal53IZdXNjZESrnEBmsvqZEyprfzuQ92sQ4N/Rhk/nhf8RgNU+N8T22CHRDrTuauNfYLGTeDHOISnsGz85hcdZecWnX5uWMSws2NgO4y7wFSxWhxmuL+3I0P/rS3cjj1NbIyZjfIsQbXEKPVFtH/Pjpc8mmUtpQ/QeqNidZ2fI5QEZIboBdOzZQSyYj+0kJRz1pSjLUkAixhWK1kDPDDUzmOXXrgOCQIc6DpXmOzZX9J9VeTR+e4gYAcmt28cJCeeBZEy7hObycC3hnqdv25aa+s/GSrgvas50p+TYT3qdtOReEpqvvWynifIdUM0SCEbmrGZq/3hTXhqTHo1Ms7DTBsowqzdukc+O0NiBrLCfxHmP4yVXHod3KmcE5pKcGoYYf2jIy0PmJMWpT9c6dpHPJsEEpjYQ4JD2BlT7FPFxnMEmFanFSy0JZ5lAWousynpfT/tGiA9EQcziK2obk0igng+VDYd9srx8Ng9xU22bFki6tq+0AQnA7U7mfe2QsQQ811Nnj5rX/cFI75nMC37O9JMNUx7v7tkNL2xOuQCRnsL6tPNKlsnGS5ayRH5LMvyuMV9ABaBicZYbrCmLwg4Z1oAcR27Lb+Z3DeeTnIa5nyWxKIlqlr36ZKX4ke12Ta1lJ0pXdoWA08xiHlJjWx0MuqZ7Vfot+jfVjxQE3821JsQemrWHVlmzuNM08zuH9QHu4BDpzGYNxih3+5DtO9DGhIPta0+SlsZhN3M0DjMhcLtvgkWAFMyZyLDZuCdGGXfy+y5ZA92/WtBOT1Uc12A5X3jpuqGvH7tpcP7PnMJVIxjB1ays1B31T15vvbrI6AKTqcVqwnye5kWZU8jg3MZXbkqoIlSG9OUb/4EHqGuz6xBttE47ObHLlnbvJPc7Ta/w2gE4KaQYX8QaX9/0NTYOJSCblYOeRFYnjZ0ZxTfpr1GN7SlprohTbJttI2LbNllmKRfWkcwpfsWC924bbS1bkjlJDqjKDTE4ORv8TBgtdt3XqwKBMKWa0BtrLSIbNDisnnxlM4q9dbiO7FCumkHdhBuj+nfQZUpQd0gyEgNd+76dsA8A2vBzKb9TUyveoeFyOsnQzgrr0qPvvjMW75knOPYEjJIwlbjU7ZCfted+M0P3XNsmonF4ob/7CMMilgh10UCEHwriV5ZlUuzZ6q5+PZjZHFf133o8yPJBbAuNVATmHICXs7p/8tGrX9885HV0TDOIPzslxMMeeCZyXHXcZksYJc3fxdG7p/pVql0gYrnFy1sOKRfjAzot5c8NwdE3QlfWczufcV/iiTGNuxolmua44gQDtW9RxDh+QGg62ATkU+plRjOUnBUni3fyTMVh79sio8SAlWPEGg810ckkOvPRRQs51Z6icoPdba/A3hqHrsIGuHO2RiApDsPSvbI5mDvtK/QzWMFM07/W8dVFnW4ol0AldeqHju+OD6aQwhMU8wU14KVpllx9PmBLwgOLqyeGf/JtN+7KU6stVndamhIMEf4t8zhFZqwPeAv/Ye23g7yAZmj6sUvaZBwv2/MCcEXzERE7mazSkp6aTgkzrHuNm13fnvKxpcHNULVuIwIC8llGwc/xX1nb1pQuFZL2tm3/YNCuKx6GWDGVn5J23/VLdaiMrNEwQnZE1i4oaW+12Dh9Q3Si/52GbgugN9WgVFdQ9/DB/mSroOCmBFrYqFI0mmYQHuIenWj8cWNfP0+yoE+2QNjgZYblvNtQL9tAG4XAXa5vRhHQT3PHpTAoKlaNh75cZmmTuo9Vh3sJcB8mWjtrcZIKcTHn2vcPfkmSQWax1r2NwDc9zG48kVRFafWQ5/fxJX+odlxdLgjWdSTzsCQVWH/dA1hw0pqBp3G6ZmWCZxRwsH8RENhnUkm+UsoTD7WfmmnDWzYgbdGjdyEh+oR8rqWjMYs1zP3FjZ6ly/oZT2FuRfP8EGSqnD6vU90FdbTvsbRU5fBE/2ZV+IH/4691kCf+P6MX9Z7q+F4Qkzo010JFMN2PgtW3YWebWEe43A6R6J/Kavfl8Fg+AqzcphQaO53tuTnuWk1ouZXuF235qkRn09Gw+ZM5Kyd1aDNafDd1UOj3kZLD+OwnWlf2kN8waevP5KvPw8cRSPI0vOILFqkyAFD2BTgIjbquNyihgLD+qGG0WZVDrkq5YB9JVvMhxXZr22vBSM9NuyMlUFuQL7mAKbXS3J6U7Gr174WSH3Rg6AwZohDThC+q9vSLCd/Fj7YS5ua589aTZ0ijrBtaY8Bksq3qYdjhfVRzJwv2d0TUZ5PlzzmBcZA7TuJVUc98/+dkxXPSaR5+uOO0gKeGhzQGnYW8nNpOWFrypeCWRjuhTGHGDklKNzmymbWxt0rKujz8GuO3fDmaPEgoJv70cNnwfuMf2PakZYxB/0InNpGqHHgR+xXbblubjOrlmK8lWBXmDe1tk3abBns9BZLXDUh35DOHNcbSMyef1uJKKC//ue0+yA+MmHqOodT1n84Haz1IcXoVWeWMdEnKnekfXhMswGkDst+PenYg0SbBs6G5jqqyPU0rmmXearil38RMcbuNWsG1n3noRgFeoCynBMptsGfGvL83nJ8YqbC5rHr3JhS6mSNWriRithtBc9XiGa1myXe7nzuC/pKRATg6EQqSzgc5sDGyzVZ6ma0zqu4oRzJfQN2Y675zvrq1Xn9uzg3OZzsVDpLOA3W67jNBBDv6j+pQy3+v1a2aJxeQetLSmJ7pu9/+0fMn87SlN4RrTMDvZJU07QjISoqs8f7p38EuXvVSXCCvHiut4hsUczkY6J1cRBqhRhWMjTddtKbgvhJUQLvXxwbz4kzFYBzHdQtfhDzGI3qxhZsMYV/gja4wtVTjIy54mDFJo5AdO4Mal59Nz8lH0GFFg5zuI+rieNNIc8dnaNrc/z1zXgXFxW03Zn+WBphD/Ewbr9m2TXd+FR9c9/rBtrudeUXeyjhhe7D7Yv1jdmSuqH09ajwgxxjCXW7NeYHKR36bKxYyYG7lVl3+X2UCsPVpVcLb+kVQR/nf8lQtfZfEOOVm27ghxCl/x104Tg8Xc/MGtJ+/MJjAM/m16avVkLT9yDFPC93AkP6v3JnB7Y1qBehdzxCEb+FlkefhJDBP5zuYFgincRUd9B+kOtZLzpuw9oGZsOsL1/ac1hfTL2UYqDfxad5j6/ds1RZyW+FR9v7X8LtfiVkGyNXvDNuK258hX5mGg6mEG/DVMew1Ngx20ZwX96BbezK08Smq67JPTxyW44EJ3/+yuyORjxlNXk1yCNYp5vmfJaCX96NDO3TcWnovXzsHpuWjEDaXCacoJwIpT2QIbXiSIwapxeJcnuyz0alOhDh+nemHSJGil76OQfWymMyOLdiatzy8OkFGATp3sz81HSHuccFhDJAzW05VreTb4RQk7XqLFYF3dZZYv2QZTRVldFzIxa9xtqzLPBIGOJgy+rRjOsgMdva9RjhcneHBuHuMWunao53Fu4jczpmlGls5IE/PLKm82tn2eYUiQ5G85GV0XrmC3AEZ5BfwoGTIXswFcbto4OjHkgjQUC8zD3ukkVGLIy6JzXVq2nE9j+9OHTEZUwYKYjEbC49ihJL2mA4LmicCs4FMCqMzIc+3nWylS9qBOaauT/s1IZRMYxGAtbnsm942cTe9WZWjIuIk7GyXTlp5p99ddPEhH3fYcC5EglQZCmm3fCJCTFWcE0manpMF9sfNSQaRRBUe3yFIRljmEX5pmrx3DY8MKyQVYuyvlpWx5aVvr5VzFCwxiadI6VTfazPN+CrmG5+jKRvq0j/IIt5CZFSzBslTAndnoMrUY21X2WT5llHri3g4s3E0VzXjMlDYflFHSJPTHfQuOg4kTKWaz+XvT+Z4c9DZvm8Gcn65z21lbR9lyBqrfLFMKdX6a87FXu5iy3zoYg/UYNyPQlBTL5flu3rdzkfaDyebu/0ZF6KFt9ZKhsBa8l3t3biLOdF7q3dp9ezIMrUmYBmWsHQ4HSyICGKxQgAj42N67eVO/1JTmJC2uSXKKoa2qRGMa33AK0Rp5s/2ZUay1gmiak+GrkiGsT+nDGd1slYY1iS5LeYubeUz9XkFeoMpsC50oq3UbnzdFPVjL4+YCEs7bqflBCGkA2UiYHbTjyP62q259o0zzENL48a+KQte7L254iQf6fEARW7l87/12m3T3eLxVO4G/6EEP1rKDdvzI0Yxd+gjnLbrOxWAJ4AgWcQrfuMqx7HAse43x7RdTQS4DWMHjJRe4OyiAlm7OYwIfEy1PPm+OY6brd8vN2Wugr/J4Jk9+ToK5jOYyXnWndRxwPtuCJJRCI9O4VXnWgN/2AqAx7lchO2kIv9E2r8a+/XrS6Bh8ypnM4hiM8y/w5e+BlLKNcoCN1tfDDTfYaaY8LOtQmFZOIi7oznpmEWz0OrLYxmSyeK3s8/x2H3FsqXe3gjJGpbsBKn9algtC0Io9lCVymbrnb7y34QjvaxSj8L0JreF5aEKtmBVxYFQJ095Pw5ZIGoZtBzq+7W8+HLbXuZS6bdKjLkTC9Ww5kolzSbA8U/FAmVC2b2OZQ3+kHZLF7Dn30Z+jEmzROYeOaLOTCc2+c6iSTEYqEXwgWzAzKxqko880buVqnrfhUxy0c6ls130HrnO14XFuJm56k1veqF7a4GJS/XM+V4+RlRYHXVcH3QW7ZBDlUIrOJKSo9SMm8Hzj5SrfWOYQI6IYK6s/u7SpUdAcG2tse6xAClo0QhCPQ2pNhSOZUP0W5ORyY+T1wNePHiPT3HvKH+rdKjh7Erp1gPvC8bupTuvaqpJbeMzFdILsow5sIwtpvhEnjOXL04L9FOX59y/LtnPbR4vYRgduRgo2DibByjClYXFCkJfHDVfUMowFB1Ut5qXXkm9KS39MuKVoQfuakRDs2afzozl3rK19ZI9SnkWq/Q9mP72YI/iDwWpNl8RsxtXiCyxw1mqyfPnh/4jB6pKynf20UAPtZ7CaFmFeZnmseXYYYYgmB6qMAp7jGjaLTpTX+xmMAdiunJY9SaDhqAVa2YQo/GA0ZbENn2BtGmpjM98ZJVd5oVl9sLKyE2gaIm5vwNOZRAoN1OsZCtRQvdsxxHkRmedjJvDMYreBbFM0iD/YTLGCXLB4w8a4xkY6U2VkmujPCdqxi3SH6suSMsxCqvt21QTcCB3ovuqnkKYM10HeXMfzMVO4k3bsYkT2SoXKnp5qkE8ZRtzgks4/cx/3+YswGjFiVYjaOnRdcE6nRVxoujrvb8xjMYc3aayuDpUAmAaBxrHMZLxpJ5WMnLfOINgEXZdqywrcfWQdAK9xCc1z40qC1RSDZW3Cf+Nt+/2BqgD785D2u33PFzKMls1q1dz0bko6guUM5HJe8asPgB5OhGuTUlPdTU9Ph5NbLsEwtINifDmlecWZUsqjpzUdWeJv/VfwdoHbnstI2HrPBiFte4L4a+9+cj7v0InNbKMD9fEQUXJ5v8qUlppGy6nUc0zGfLU/PWNKiQzDxoOa1HEBQfTxEilFe5XLXb9fhbQT7FyUUAyd8LjIVzvMGy/gHa4zGfx/pDxCBTn07OJ3cnHO+fE9VvNQ3qMU5Ekbv2MGlKJhOIWGgD0HLudVSmhJjmlEfxuP8AqXB6oInepT7zzcVxV8ONnkkOAmcR5A11ld0pLPTfiHsoS5hjRNMasb6MaMxASVrSPb+Iwzmf2XDHOiImmEdAW7MKmtrREIoi0l2TzBDZzDDAAu5nXeGPMWxcVw1z0O+0cNcnI1erGaNY3mnm7uKRP5gJMzbacaSx0KUlMq9BCn95WSngUrs3mZK9no8PL1UpqJon847kuFWjtep7FMnW0UcRrSPqmWDAsGkhAJEg2y/5xo5SeZKuwbeMptcH4QRunLPrfTnu1KC2Lt/Qe1ZXY4BDjn7DnM8EnkQK7vSgd0pXq/ptkM7kHO7u3mHFhjRmJYucU28bCk/RaM0lY6EUT/JwxWGvW0oFRxnt+ubOd63r+4ikXYt0nvguxvMkJe26yDhcoxCLGbtpxa/hZnLvWDHzqp0dyLFIPlqEKCEPVGmFv1xxnYoWkjyGRUk7ANPa1DxTq8tSZCmmggJ6XjoF/OQOKkMMs4mjkc7cr3YKotFXIb6h96XbfRkV20tdVE5uLYU5ZKVzZSK9IZpC93VNb/cu+N3EXm4nHhYFm2nVbfoNON9ZzB5/za4zJzocgFfdbw3ZTRnIw0g2EtNrKFTkrEb9HUds8yn5EsZ6DcXxzShi+rxzKExSQCbseqPg4pmZc2pvXhLS5kPiMYbnqegAQW/Rf3ECOHY5jFZNPeAiTjsbfUzb03NGqcylec7JG+WfeIbqyXCMWHIMEykLAep/OF3YYgGywHBsrJPTb5Hr/POewpTw9UEQIsankqHdnKNoo4gR/4kbHczsNkm+FcnCC+TZFS4Xr69yiHwf1+WrguFm1Spc3ScU14eCsPIs9lzKlCkKrjYGm088BIo4427GYLxRSxjd/XSzDRaKFUcTYmdBYynCncyUv5d1JfJ8ihglwqaM92txG7pzDLk7VLS1v6axlhA5SZHlLpGRo9Tamgz5jaUcBsjlUqyKtCr5BDzGVbZLXrOa6xXxCSDjchzaATW8nKFIxhLoUZHvBIxwH9IRO4JvKO67FUEbqzOOeez3v2IOHNLAarFXs4oeB339O7DtzClxt68tnaHtSZkksLJkOgudQ3S4zB6rPlnLO+RDJjCokkbIfRMgqblmCt3RXhJp5QEv53OR8Mg8y0BMLBmaaFEoRT5Z5zIGFGCQhZjOorFIe3A3Ie3DRyibuQkO0IZWlWKvBgbTnI2tcssF+L9kfTWMQRPocPdJ2+rFSmCfspJGLG+cymioWbZFgl52XtC5ORBb/kvkkyGRy1rnSdO3iYCzr7Efqd9NGOoUxDgq067UTf4zyaRfz74LAe5a4z0pqPdQ06bUwg6EOB8HCSC2fNzLvHxDy8gpeC8/xHJfw/onzdHSqnvMbmgHvzJ53a1NPFwcV7F6Q1gT5Z5uYaDwY0alFYS5AwJNbOTTzGFI9nBEBmqJ7HuImx3XcBUBTepZ69tbAb6dTzgLiboZ1LDlpeIDl2IGtftCVYAQyWYzIc2TCbd1b086W5sO5F1/citnB92D7UXej4/8Hc0ptlYXTuBkJ6KbXOlfZW1rj8K3Q/x4Tm0onNnMe7bNptH9o928tNfjbH+l9s0pVLr+ApbnDhYHkZGgNdeYlM3XchzzdciiF0ab+h8CISYEivmQWMcJXh9GbUNdhbn6duqUFAcr4+aCJUTiv2UkMml/GautkBzOI4Ffx3Nse6bl77aOWTmO0pCbOCAT5jSV+onEOIR5YgxO1M400uAuAwlpCa5m9farYDSNFx6Fu2RJOYwfJteUlVhG1SSlzenWP5iTbsVoeXk6lsij4Z8gifDnzAJ8EayDJaIyVrJ/A9v22ybUD+1mY2okVLBg8mOVmglx5uJJGQUurdtOX3+r6mBMt/0Oua4EKF5B7mdL7gS6RRviXJ7dYn1fwu+zefA2DIUB0xcriG59hBB1cV9tS5D8jRpv2edbDlU8bgIDsbx8UgP62GxIef0HCd9DT0SlfPQcZ304WtwrSotRn/cStF6rd6I4VoPMvlzTxHP5ZTOvgRqi24CQ1BtWGv9zgpzO10CVNHfuVKn1+g0ZwSTs6cq2y7LLL2oqeHzfC3F7DC7l7NC9zawR+z7r3q0/l9bzs3wLHj+QwH2K+T1lsAuWF5/qToCdqznV3RbB4wmQ3jPL/a20leiINGUuXYb9yEmCkhaV7nYh4Z9ZVSKVvzzDKFeY1L+aHmSPUerV1bTyG60ocnCaHpou+2S1gR3bxmWfT9skKGsoj6Bi/3q7OJzi7A7VMH7kTDYCNdmb1OCkC8XuoWbXPMoU/a+h1FvGU5TWse+uMEHuFWRrVODpYNMHd/Txd2oos8h1mYRiIZja6+so5US0IMB1cRWvZVFlmI8WCP+xsmknsy+j9hsNbUdWYyz9nAn7q986ymD4TDboMyTy1f41IAFQDTIinBSk7PmLrXkGawoaYNMzmex7k5MBhtZqiem3iCw4vLGMpC2oVto1O1qJLpFQ6BQo7NXIXKsSRYAQOf3Uz+1jr9ACuMvuwNEKt7pURh4q6DxelSG+Re3FRdE6Yr9FyO4sT+8sBTNgUJQUzPZSudmM557D5gu79mpDYhuTKpJiE3OGervaFpBJq6ucyuOIwb6qcqCZbTw++PMr+hMoAIucX1d/wxUQXEtRispoZSQVI0BjA3QvCFafsymKX8aYqUrXpbZDFbb5qu2d5xbmgMroDFdPyDBzlwgEMK9mw9swAdL+NVgmK0Zzo05dUJe9x+daASl8TS6NKqijt5yB96xLM460mliK08aeKmfYN0ZV5n1qNvy+DYnSlhGWBYqSLNi9Lj3Ewxm/mMcfzBYFcA7x2VuUlFsc1MfLhubap4bOFwivZ4DJETEu4CYFVDd+X84KUb237E+bwLQIIwI1ig+lQP6SxYADNMvsB12CYSihG2YDnaZdk2ObescB/cls2ZdUGUoLT+tVNeGWYtvTiDT7ntsDmMPztE2rOmx2gS9erSxAAu5VX2ldlrICssJWYW5A3AtN9G0WPXbKIVgluZJuFxdD2QoX+JK1V9vXAhuVqU7HT3YayHdXKpIF2rp1+3esrxmwo0Hxy8di0J1oW8FchhWOYFQVOhqTVtAWlaW2TfLrVspyO9O9kXhm9mNq1+tsZ8LT35mSO5kDd5bOWxCDSyauXlew29QNNoTOispzt/NRa78r7PubxWNVG1xXvRa1G/g5d/lUzTocQiXFEqGSK5Y9pjZ4W88UqyDaFRS6ZSiT3DtZBIKEcTK2rIoQgvuqVubfL5g9v/xm7aqr2vsjGdvbQ66DmajBfaQ2vFR0w0LxTTuE1dcCyyXu8sZuwgez0G0TY6Mpnn7B8cc8+aa1b82QPkk4dfm/V/wmCtru/CC0xWnezFFvFhNRgAACAASURBVDpQm8GdTFHf+3Rxu/ZbyM5+vBECQ9pYZN0IQ5pBo7A3m6CJ0zbbNOwLhfCGyrE6dz3diNX73Z0PhaxwJxBgg2UusCNYpOzNWrSAdGrpH9mKjuFyUe9keWJ42lFKc35L2HghyTCiDka6ZhpWe9C81YFiCNem4Hy3z+snYH+w+rNJCZbjPbmiXMJkmKqIX9c1Zyw/Eq0QPLH2+MA2vLdnLABPcAN3Dpnj2ozj5lw4FAYraIO7qXGqMvK8nakuZP15jFZgsO9xHlsoUojD3o002e20d3EtPzKWuRxFRQVkpcu5M0JPLla3GJxHTLF6U/Zl7dnOPfyL536ToqDHPPhTCUOjZ9sYD/EPxehb9FDsWhcQ5wjmczpf8qvpNRgiQRp1dGc9HUI7GdfDE2rDIitWpDneIRJkmka3KTRyhgk6mh2uU9K1PTU5SRmsNNOxIDerkUYRJircse+MhJNRJalH8PjCXzmGH3m0/zu+Z5quMWwYRCLmdzP/pbxOh72LfHPl2gG22jqZrcr+mGRWysnnU8b7nker5VzdShEI4TKuDYyTCRwT/47XuZTKGvtWdXJrCWCai8MQ24SfqayUzMfWkiwIhcjS/AGTrfk0nk95ofI8z8MAPEJLcoFBOFVXgZYBiptLFWSzND/4qVVaHgcoZB/VDX6GxzADuDsvLMkuH0G/Ky9JK1ROit1PB5MYWWUey2yWM4A9tGZRSTEb6cpLXAVAd/4CXVeh4VbUS8el3Fz4B/8G4Ld66QEXIUZaipuxriJbOQtZZ8RJHjMCd6XkP33KQy4mXQGGetT81ncrQsoAloNhqD0kbjrCaJMnK0/DZNSUmQXA0krpEKGid+iwmc6si/kjCzgpmY1WO3YpAOUT+B6Af3M367ZluMZuQAvp4ez8LdUhvA+iyM61NO/VMvBZ/6Ioadh8ycdMYCvF/no3XcT/P1RjmBILC7DSs9ms2dlMBeI8nMU088QFtYLpehmsEzuv596cp5KWqyRmmkFZo42B5XWzBTis1U4WMpR9Nc3oyVpGZtggYtbB2Js1fPyHv1MPhZwT5vYjpIGj4TEk1jPSMIo6WxlIECKkGRI007EGj0GKor17WgV5jGy0D/uCHPtW+Z/YYIV0g4ThULOYBVn9cArfcFndM/a7HYzDvnL3LA7a4OxQOXaf9C+K8i/usRHMHVM1hxgGugTw06CsKo2fGEtDnRHoxg3wY5n0wtpKEYXZ1a6y4oSkf+GhMFiNfqnCM8K2YwkTpwG7zX/Sl92mt1gW1RSxzQ5J4bWJSlYBh7uxMASFBXEEGjPTTgtOLwRX8IoKFA7SIzXZYWF511pzojmlrudCgMMAz/XszSo3E7CUw1zfr+NZ6pFMgyH0pE18dtOJPLT5bPsASftRHf7OOG+JuFDStee3n8KI0i/8LwNSqKED2+QtXreZaIuMhHDAXejqkPaRpnEYS6gI2bhd/+QBoOk11CBS/QyPM1ROkgNjy363ZPphbnd9d80Zw6Avq1Qon2Tja605JwNSfYIcN6cnY0gXJETIJUkvaviL2Tu6u2BYwB2/dVfCHVz4XyWT+WRjf9dv9Y06m+nM7/V9QdMUA34pr9Klhc0MB5Ocn1fzAsetmOZ7atn0OKXyvviJTZDShAQwWE8lP05kWsdw6BgqRqr9W4LLeZXX/zzCt96zmunKeUGggRCUk89FI922kDqGGhNrCnkhPpzUKlMyrH2Ka1wqLM1sqPdiZzFYyvgbg08Xt6OvCU+gJF9dO3MJwd6OFr0RPbPJ55o571tmm0C/Zpc8t3Zsk/l0XaM3f1LMJs7iI67ENoex+tWKQHGAAtZsz1brL48DXNHHPOO94IhNUdu26AX+2JcgTV8O5tQE/yMG62Tc+vgd8dZSBWA21rvpWgB3LdgvJ5KnI6wDwMtgDWu7nUsjHyWtx+tcIt+vJ5dyAUzgQ/aUpzOchXy+ohNvcRHtUxwqQuei+i970HnAt8mSG8zg7tWU0JyexVJ8rw8cgDFGTjyh6TSSKkXhGLRKr+ByZEBZyyAzSBLnZEw6t7c3nf8EH9WSYNVUC1qwn0+WFsnfHRuG05DUuYD3lLvVB5d1c3vltGKP6sMrWtihUfoWVXIPD5ASkm36LfNoFeRX1wwEOr0zNtM5UuJS3yW9cZpV2kNr0HVXLMZ22q6DGtp26dDAI9xCfsRvh+Ds43X08BmgWrdIA53V9FKbqldFWDxcHlQpeA4HZyxCZ6icpCeqfz68z7mHxGA1I+ayqbJeV1Wjs4Eu/rBISdQGHzHBVb8wjVKlm2S9zC/tzo9lAwlpBhfwNndGnucGngRk4GOLrJs8wP6GHDYlgtVKLVjFv7iX1BRBKCRDrzgZzqLmVerQytDq+Hfzpzivpx+JeUV1F5ZyGBWNdjQJy5Daa0vkJIMAj0jHhpWM0czNdI+9dXmyyJrryxjE1CVjpXrMMshOIsFSWECOdZndp8ifLuSut6ZBmcinpiHMObzvchwpdjgvWKF4LHo/dhIL97jfb62RDK2OPWWpSrJ6JL+oS1GyNVjMF4ziZ5YxMAnQqI6mywgTOVRwzv/H3FvG2VGk79/f7j7jlmQycZm4CyQhAgQJ7u5kkV1k8cUJu8uiy+KysLj74m4JECVCSEKEuOskk8xMRk93Py+qq7uqu885E3774fnfb+bMOS3V1VV33XXLdfGGtiHOJPK1LFiWy0hmsKYiMHKldzKVaJ57LySnQklIsu+lO9tEN1RKZRy2E9nASrGUSs7mcBEWZ9VTQA1tWjucab7NtdzPHdxKjiUM2LiN3fk8zzNe5eod/JUdNdksYoBWRaoC2aaSp3edlvZ303A5gs+5aB9RFCWBXDOto6YpwKif4M/8nX9wJkG+nnwHElMLvA2UzG3GiLU1lm7IVL0aehVaUpepQeCkbHfGI/4H0kXhywMYnf2Tppir63W3r0z+20YbJnEwW3bov/uLTZwCS+OGeN7L3UqkCCPmUM8m2vEWp+M88qhoi6dEtb5VFOtv5SJMqDtYb2JlmTat2e6TyObnBzky27aL7wqseuFmJ8lABElugR9K0Rd/wZdoBguu97azaGRghygCcyopStSTazby4ksGFZT5rm712S3lfarft2+lwJADnQv0+37MsZimy0hmcHE7xRvhJ2GJ6w4yfqETws1bYIidytPld3PL0M9DQKPx70NO5Lc5na9W98Y0XIYzCxeDP5nPZcwv6Nyuiet4gJZFUQNLVXa1MXgosjR/DsMZz8u+1yCs6BKFuVw/fBLlWTpcwoo1CU7iPf8ZXcelkazUVFiOwyQOFAm3iqSaGqvozt1MwDShmmJORScYdhz4Ym4berOMqhr9IqbhUh5TKVhPnhYis0mkBeaVVYR5uS4v8wdG5c/3SZVVWbsjMHSSjpVymdlFOefzouAiNIWRm1SQ08f03Op7sO4ouo/jCicysmMUKPW65SLMY1nRxd9Isyo4mBGD56/TjlQ2CfifF/ztHbp7HG8t8vT58j46kbU6ZtZXl7CQAT4NWeP8KCQGBJsfdV5KfCXt2pICTCloMHBxbDfAEIyRcTl6xW7SNSNRCeklObXwcz/MCfAHXiY32+FQvqJ1oZ4KIqWE5UxhP+YxNHaT4HreRxnifIOzeLzN7dEDgX9ZQfV4V1YDYnxv3AgfT27BTEbS6Ij2vcI5sddQJdbAijECTTNIo5D6osk2udULEdagFxdo5xpB5bDMbXuH1IaMj5buJabdz/Xcyl0aDIUmhuGvjSAw3yQEiIUdeLBMMNvGh8zE8zsZ9aikM/LTTEy/CWnFMl0ayGEM0xjAQu0+ck78jeCdO7ZLv271jGK68MTFzNVNOzKn96indSwNxueuumxmh7z1YSYV+J0MLKdMdyH3tFbpHRQ27LP0DOxwR8gcrFu+OED7fnVlCT81DUrZjhJ20pbNHNFyRuzv9eSxim6YuNznJUBKmIbNdlC9pFb5/VYP1oVDgwqhT5aLuHR4gn39Nfzby7GTCqskqxbTtXFmB0bqVtrQi6W0sbbTl8V+yais+vChDjyF/yhXclT/1c1u6ztD7+LVEY9w2TViwZaKOjff5GxeJYd6EkYQOlOVTiLkLezoJfq2YxN/5XaGt1olSGaxtM7cVZtgAQNJ1jX5fSNDbSWGR9vjip2JNIId203ph1KLCiau64lpBIpuoLOAy63/pDhTPpRSqaiKG08vs2ZOReQ7gJ8ISt7iqhZHd1zLmUWfaN/trLb8Mn3Hdlm8PIscGunWGL+g4jixJOYZUZZTFj4EJNrhClcTN+WuNhxO3VA6hL+Nmxp7rEbGDVQa8a55FVU86Rgpcy4DqhzX88yE3pEThF1kdWZcB8l5FwYcPo23aFmSejFxXJFvJIFWASrr83yKD9Nw/c9Tl7cN+FW9Sx7qlb7fxa2AIKAHfcw4jl6dO+iGGDBUAi+KurCGwZzlM9quGXiwLGEozdlezvNcyHSFEqYFldzKHfRgOUbI6km6luYhhmARDFPlPMBfWFdZyNcclpKWxiF4fxGIAYTXzTDgwD6b6M8iwY2Zwl072vzR/zyEefRnIZeMmMPo0TDhaeENlRvcuAUzLP3K63jLM3bM00+F1q35cINYeNV3bxiG3/+3tBSVtdW1Fi97BS915GE3CUPz64V6PpKF7TsTRvdLn5gNInG8jnwqqrL5lKP5ld7Uk4Mtc7BSOAUauwT0VK4TGEz5iQaO5wNaFScxlqeu9nM9aJh0ohl/KPm3zeAiXEV3iqlmFiP8oiIIxpZqUziOS7Zl041VTGYs102JghE3B6ZBXd/btQw2Pz/82pYXM1QQijb9DjJuhO5Cdl3dHXzk4A3a76nYvjPJEz+N5IwtD6f8vT2bOIdXuanz6xp/kioyH+s/CGqchAeQd4dCldOmRSMjEUbab6XKURX+h8tF1dmyNdlcwpNatY8U36GDSQ4NbKfUB9Q80PiBpfTh3IJ3uYx/RxjP5UL34y/Cu7KAQXuYhKUQUhO8j8JCeJVzGcYczcBSJ3C4f77fJIlbE9zB35iRHE67gmpMHFY3BJgz3z6zisEsoOo5EfK9u/FaUW0CHJb9nXguW5Tgx3mwwtAbHfKDkltZcbSTFuygJfs5P/BQThSqQ5Wa+gRn8Rovva1jr6lhoHx2+5ACZsJkOALPZvWPW7hyqB4aXUU5LVpGB8+JfRfzj5b6GA4juct7bkbfuAQHObFGXyaxUsyzvTtXBNGLcIKs4ZJFE1PYl885Qm9GXA5SinFnmq4IT9kOdeRyS+X1scfZigMx6Vgpd8ybvd3lhh15vmcGBFAoQFOjG+QauQ6Tdu/Dou1tI9eRJfWJkAfrLc6gvFPUm9nHA1a1MSkpdrUCANXjaBj4SbLtS2r9vL16j2S3A7oX86LzhAGmUeU0o2RfFS21wVuULlVgNKQhqgIemzgRQl8Qm7d8aj3+t6iBFV7DfXod19S8cOvo7BuxqfInd9DTr8SMO+a7ouO4YMQC9uq2k72YywxGM7+hT+S4B/gL+5gBjpaJQzmraZlTy1olyJKTZ9KHJZFQeZy0KbU5TUJWGAbLawOIBTWX0TQCJPcs1wvVKfPNxsJOunzDoWyq0r3gJm6Apu84HMTECM6fKhtrRX7xso0FnJt8not4mjzqKcvfzZU8Eot8juvS/Zj+yr+ibvtv3M7JPebxASfSt1sDRoEO0D2GqVTSgrsQnsEaJz1DiGmIZ3zhJ+EkkR7bTIGgy/aaxo0IDseRzOQBrvN/k8/zOUf53zk2WmqFxG5UjaTm2BXnDAnInrX500yb5HcxsMZ2Xqn9vzbZQVOM4c1GOLehuQ/jujpYZVgMPOs5kWAiIrcpT5lEdkx3yHwwV5nYBw7ewSQO2qO2RdqqaEepNDZuy+IpLqG6LmpgycXgp109mMk+dGSD79UwRwivyBX9J3I5/2Zvj9Vb5gJJA0v2cw2FNDl7gNOg4LDIf+WHFziPaezLvnlzqKGAaYymb/cgj2RHtQjLPORVpCyoFCXEktPq/JrH+MfIz+jPIs5edpt/3sqdwoOxdI3wXv41+XffaDgkZzKvcjbHLH+IW2cdr1X4ucDhfMFNHjmulBwzWAwNw2BU+zWsoCel7OCv3J7RUl68rpA3OIvzbteLGtT3eAHP0wZRmm1aBnd63gfTMiI7tDiqHHGwSTj2p42VpJMRpkEe/ywXMi6Uw5NOUtncfdtWpkVyn8jBFFPlAwBLsZscWqPgxLluyn6WHqwdOyCfOj7dfWDkmG205qSeASZT0jVThggbEckzDU0mpYUNdGMVJ/C+7wV94YfuFOY79GMR85L9uWTb7bzwy4jIdQIPVsydYjrMxSBBk3i/3nuUfJCqQTSm3Uo/+T83y/bzzDZUigUqjDlUkyfmi+rddxyDvWh+rpG6sMrFfh8F7bu8tJpDrO+0JHcLm2RM2N3E8bkIP2sQ4MZ3MoExTI0FbZXtvmPn5ZrOfISr/cozNb9OlbUKVU6cB2uAtYS2xXVgWdR7fXpTRbAAXzdKVJ1+wjF8Ygdevj78ShHV4Djs2yEIc7cudbmf6/gqBV2T/mDBimOaUJwVrCdqXqphGv7ciStyuZqH/RBeuO/6Zi2nVa53XdelJZWi3Snk1B6iQtS0BJftDx7DwsiO63mEq9PMQUXPOOLcCda97FPm9Y3hRQxI+oVml/M4FjYTPAqoTCL14M4GsVG9fJ+Z9GJpxv1+55IqP+k+cs2YuenYLus2JXjNC/PKRx7Zc3va88LSpVXgiCnIVpgQ/l8ysMLu+WKqmJZzcPB7aFeSEyqfDD/MgUyKv48TDxYopYLWfMjx1Bn5fsWBNJQAEjG4M9KDpV1VAfv7rQbW6wuDKpvm4GDZHhjeArs/n3AM1ymcg+agAWLxKi3lRf7gJyv615dYUt4Efpk/8MTUKFBpKrlrxRncvPAc3+Xtc0gaJhfwgmiDAQXUMpoZFBYEvdVQLnaSP7E3AHO3d9Guvdlt4yd7qhO8yha7OMnL6Ciu551WKWfzOlubWrKzKV/zYJ3V4XufR0wVDYXXcDm3/xwu4UkANtAxtTdInpPiPcu+PYSvOZl36Wms8I9XFengMh3/KZWBVWvnUKFUuEJgMD3KFXTr0JAx0VUFJj2BD2KPUWUU07mQZ+lWFvXqVtKCguwAtC+cN2YaDr8wiJv4J3MVslXZjn5KmOT8mkf5YFE835zMwZLPZsWE/lqwk4QTGO97ZS9KGSJcjQgj5/ftwlkjlvEjI/mQE3yvhGNDluWQTy3b7FIvjycmz8r7W5LXyDm8wnm8QDG7vHqx+ITrDmxkiDHf39FcicjnVPMDz+sznc6e8jYNl+e8AhypC57jj/p1PR1ZXKKECF04nbdoFYO/I+X+ro9xOY/xCwNo2yZ4Pj+srujm4wev5sPsU+nUtokf2J+hPWuwDMfnCnztX0GkoZKW/JU7BVSNI/LibuUuDIRHMzy0NQL40BhatEVspuatiSdWdpXNeJyBJT2jm6vymeoBDC9vCvSMtCsncTDP2ef53+dTy1ucwVfLujF2Y5A0bSQsZjOc1wjBT8TIjpps3uFUTuQ9erer4pleQd6gxEuDQP+0ZyN1rjAC1X44lK9T6v/JbU7h4r2EITxxbkve42S2U5qyTS1zvAo9y9DmkY/h1wwDy3WEBwvLQkvCQlQkn+jBNXzACRpVjpvCCynl33s9rTdBwndkoNjRCgIU6cbKeC5CBzZtVXAfvbldmBfjKMhwXynLNhXEfZ3+9OYd9n+TLbsLtf9bG9vZywp2oj+v1fMt2ra2eVZJugsPuINSGFiu66b1YG2jDSvpwXlLbmKwZw1nqh7Lyo73MljYnM2rlJftjv7eDKmoU/BrvCb4MFMxi3luW7HoDjy1H7PQd9ryZdc6udzNLVpi7NU85CM5xyHbNkfmV5cza2fPoFrRa19dQ9A3nbK3RhsEHHhCCx57DK65V6ecmDGpzmuTEYs1trZO7Nh/2VIWIAR4inaJ3ct/HtOAA/auppY8yts3cFL76WTRxF8UAxRgfLcATNYwDc1IfoEL6LFb976ExUpRMWaZLj+yD//hEhrJ5qSE4PMyLJNurOI67qOwEM4f8pOPeQOiOqy+IXrN+34cy5BNek6THBcHM5HC3GRGsEHVwLpcBcpLdbyHT3T4ID0s1ZXVLGAQm3fmplT+L3X9OwXU8BlHczSf8SJ/8HG0nCZbw1n6sOkollbE51aZJpqBlTDFmFX5Gw3T1Khy2ptbKDHjQ/1reIYnn6zjsPM6aMp5PC+TRaPPRWhhE5CAp54UHUp28wrjGcx8qijBwmHJ6tzIccvpxdm8xhTzACq2uQxkAWP5gVFM1zxYjgOvXizCPJW1OX4/De0Un7tXUSs8W1k5pp8c7ziG134xjiXQopQLeI5ru/6Xx7iSASwiKyeYl/JRP+GY4AQvFSAvx2F/plBS5NA9sZZiS/Tx0H5BeEUWUHzOkTyUNyFoJ639nChVtLSBCFWOkNSjWrzz/ixkdN7PkV/vq7+CH9e258N55bGE0RcND7x837rBhlr22/eruujA1glTq85MJ8s35HE6b3MbtzG292ZargvWtWOV6nn5zI1k+8j3qoHVhbUpPVhqikZNnTAaZilUcmGRz2WYhhYpqtptsdHomOo0flofJLBnmTbFVLGI/ny9uhcJmvhpqVjHs2jyGQDe5nQO58uU1wxLUU4jedRqUZDLeZxxXZenPW/apm46rROwiXb8Sp9YCrCD+27U1ru4uR0bKg3Jz5uCtAF12KZaD8LyuxhYz/4ySvs/x63XRtG26kBRHceHlLZ0OJDv/O/CBkeqahYnTdKrKq6SgWnixFLlABRQQ8/OQqn0yAqC9N/ML6Mz63iAaxnVpzL23D0RubP1k25jDKySEpg/H267w/IB7KTIsXPez1exjN6+8juUr3iIv5DlLVZaDsgeWFiW513I8fjSZCWLOrDHl37CGKZyGY+zrVJHTb/8csjp2w0IlOiI/YJdzwNzD+IVxmtKuc7DSquszVHKbcX95jQN5gOOp9HNwjBcrCyTPOr9ZOVTeJeHQmCZuQmV6Nal0c3SQBozVr94z9qGLdr3huuwD7PYTimH8xUrPdJPM2FyJY+yjs6UtBAGnUxYBkEv4YYzgQkMDVUCdHNX5Fdl8GDJ38/jJZ+9IAL9oIiDidmqpXa91mwjhwbGMplPFnQNPFihsTm4YAXlXjUWiKowWTXsJB2fqgcC1po4uXvkR7zX/Xp/DsicvnMJAD7/5D7N9+sDGqFbSx5jXrcTiBebs85qivBOGnhGlQO1NQ4zGcmKZHnEgyoly0xyNJ9w7rBF2Jgcyefcz7WxfQEi+bsllWDbNDa4LGQg5/AqMxitebDq7SxWbRMLVkVNLrlePlbnlvEG488bvcVPeRbLsKmmyE8FuMnLUZHyPBey3VUM2tAisw8/shbFoyzD00qxzbR2J3NZ+/cjz7sPIlncwtYM/l/pyxdZx3HpPjE0P8Cp+Z9pemMOezPuNOGN2e/41rHnSA/WpebTPN3u75Hfb2+4gWlrO2qFCOpY7t66ig4I71sdQQ6lJFV3HHzwX4C6ZBZ38DfW0zm2Papo6P2mGSFqB3iDM7hh36l+u3zYDKUfJnGQsokJ3yRI0chEhg4wd1sn/zxVrz0/ezDd3dSGTO82wWboT/stpsJqx/6N3/Dc4jHYJPzxczP3aPlOauHOvaVRnDJV3BBVzn/mDOcaHmZI23iGBynfrO3NDEZr37Vji6icj1EqnVrUaONSerC+WaAYTM2IPk1aVe5/3rA9sFPC5x6NXpjkH5fxDv8DCRuPC+x+PNh0hf9/TlYwCF7lHE2JQPRhvlFi8qo4LilzMgCuRKDGJazgfiOYzalEsbPK2MoPjGVgrwZ6sozB2QECdZNtUUGZqJj4jVnu2ZaC5C4NCKV6J04GDVLIpxWROQyRXaM0Zxw9RAjNd3GCsNxtx6SBHK7hQQ7Zy0MiVxTELlownTE8wWURcNHYa/oly7Bpt0d+qixwsqLIcdwIHMH0xmGcyAfU2PliZ6JAOqyoiSYqgx5iNEyDW6Yc5cfnIf24gWDHckx4InmLkQyPHZr4jlWU06pUV7xxHR638zLN6AZCjosn+DNbtpkZc7DU5PLVlJNLnQ+OGSezGcHi/idrBl8FZSz1QhyNSZNuras5h1ei1Wee91GVwcznfq4lJ8vxcx2f4iIfryhOygpq6WhtVkKE4u81BAn/L7jnsakmALhcWd+hWQP53Z970NdLPjfLu4r8IRuqqkVb5if7CVaAmLad1G46J/MurpVgNsPpx5IAkDGOlF2BM5DzbZ1nxJQo+TnXTFfK7F2Xe7gZEAZ7nLjDRNJ+0jHZRhsu5FmeHvUCtxMYHOtiDIJqt5Al9OHv3MbuOr2vurFK8zC+MqsPhU07qKgQ4ehNO3LAsnyvodo/r3pzx8SJLPrtkutpXxJNEG9BJWXWDtq1CZ5x7zYb6H3SQFzHpduRfWOfHc9IGJf4PlrFi4eDpVQTQyhUZZrMJ5oS8YiXF+o44jmK2YWLQdcuza8ekGNgFyU02Sav1J3i/yarED/hGPJyxDPsoJTlTaJaUZ3/93Cz4sHSx9Vhm1/m4Zlj/LZmkp+2iXEQ3jTYtpt2I3lEvzVMYV9mMsKvqjVx/Rw8+azfplh/AUblRj2Mqry+diwN5PpG5AtzBQD060v2TnteXIXpdlqxg5b+wjcGYcTeyh3aRhQCD9bO2mBt6t9Dh0SJE7WyuklhTwnr7k9VT7B6fsY7/A8k39J3z98l9+eOhhv8/8uKgwctoobGvBKe4M/+d+3b6oNiqocCHJZMVDmH8jUQwqAi3nsxjDliV5NIRNzFcqDVkp/Sm5ZJ2hQEocWIB2sPL9m2WITbwutDAzmspyN2YzREGOM8SSnSg+XvviSGiTfIHuAv2oBrls1pSAMrQNDWDCyvastWKE2k9M8RuzDbi90v35DHeF5iVcSb4gAAIABJREFU/UaTqxZdFHu7H7YK5X0Ht3Lu0AXRJNwMnk/5zsNIxk2NLv/iei7xoDGeTP6RcXyLlWVSTy4r6IHtmvxtcpTsOm6Bln2tyoi+1XzNIfyby1m9IcvPIwjjy/nXMBxu9pJOH+RagUmVZpzu3g1ff2vy8rSeADwdzuFzYN+eW3iF8WRl6217Y8fhWqXcn/k3fVjKbIaTm+34IKsn8672riMSospJmDYJdGRvE5t2OZU+0fD8+t7NGmxVDTk+JIJxyskeGKQb4rmMx+ga32ki5/MiW+uKGOV5baRuitsI7aCUm7iXbqz0552Uh3Zd4H92XSjwPMEleY3M9EI+m3fpVapSzr5EGJYSg26WtwiqIdR/cUPkvCt+vZx+LOF2/q6F9OVzq7rPxmI3hWzYkuAqHmXN1jywLPLcWnrzKzkKWo4cT7dwN/9O6nPOdoh9L1KPqqFKFniJy2neo/Rg9bBWx1oYclyl8kjM2thR86RG2uUgKvW8TZiZHbOLTSGyIOtAvufN2T35sn6s/9tjXElH1tOT5drzfeVBa6iblS20TenBWpHswhaPe1YaDUNIbcioecjq+21KGmkNLIB9mcYIZvsFKaaSg9ccvZ7JwTZ5m6AJkkZkh2LhsS3OSW/sxOmN1mynlB1+wyRW4Aucz5INRZqB1alY5GSqFHP56QsetXYCZCmQQx3LohGBCTGb2N/FwMrL1itimkjEcvsB0NhIY24xD3MNAB3YEOE/65xiYTm446+c2zI1R5PvWg8ZWCoqsZQvOJKPOI4GJ4uR/Ei/7MC1KidyL5bz4ezUMe10oj7zDYNEzo0/wZoRG1blwL4SvFCcPwxRivw9B9KZ9VRuF31dnKeEyfYoROjguAIFfSttAgwTrzLoWh7krs3B4hHnmUk3OaVrXz2kS6EIveaZjf5EkdAYZ5eIdyzxdrbXZPMK46ncaaREK5+4WRgBteTTo/WuaBJuhnwLqQxf5yzt+8Z6hxsJ3OKOYQkaEcNgMmP5iWHsrDJjOyDuPZsWESyZbMumvaSHsl36dK7FxWCV0SNyPgji5LuZ4Ff6gECYTyX5+YKXS0IR1KJrHknjIRqtP8djW3TAwyc948PFANvmMi8HTCDqpKbK+Wj1YB7ceo5/myFFK/2wmRRJGfJfThX3qjmXCzbeGb5URNTQkayscmyorg6eL5XxV+9kcxSf8sOarv53suIvXYhhNd1INugG1jUbr+MNzvDv2aVUeHkGtt/ug9FOW9FWWxiG8DM1FFBe7j1LtuWfj+MwlJ8Z5UHLxG08HWW1Dnvo3uZ0PykcAp0gSbANA07Y9CRTdg3iV/pS3kXBGfJ06VT2Y7Y7DFUe5C9MXRf1plVRwqyGwbrya5MauFKKNLBuT97CwDXRUIz0jGrvWVlfvljWw/fgxnIROgaWEeSyxWGEpRLTUvsXyrN0yCELm39wG58vDzCmCjqLkKiVMPxc0TzqKC50qKKIE0ZuDl3DqxyuqvLHRlfWpGxT1yKhO9uVNnFTweP+99lGU3o9N3Cg//H9n7txov2O8PbK3OA0eUfT/vo5o5jOtPphKY+BIFQno1at8oVh9f6ygSnPEedBK7bTA7EOx9kA8v1toBPfLWkXMDVQyyXDxZqoGa/N8GSohxx2XBAi7NWlwYfhkfIt46LnZ7zD/0CsUG5DJS11j5Daiqwsf4FuxybhZg11RC/iwc5O7DaPa9u9lrIdMlwRxrRR5X6u9ZORr+QxZi0t4Q3O0lDSVVf0b60iVBXAXi1XA7DfgErmMpQ2Zc1zUQ/0EvWlx0MaWPv316uK5EDbu2eVj9O0R2TPpqje2UULXmE8034VCkI1ELYng9yDuFBLcaF43sM7/OJ/V0ANF2a94r/eI8qC3fiAVsI4aJWzm4Tp8DHHMI5vyaIRq59IZC0zt9Mip95Xco7t4sRVGSnP+zNDxc4s7MHKsLNr6bHfzEPnWAt7136x+7ONNj6eEXiLelytRFyIScFs8iVMleMnpaUYJ94ufzNBYcEnKVzYqoRBYf3bOy7JJNSRG8kbSwUQOJ3RNNY7Pmr9QH4RZf0pNM7E9b15vvIEshMC5+eyzh9rXmwQ70jJcWdxshfT64aQSVQ3v2HAgdZkOpdU0fcAEU52Mbgu/0nGdY9utDY2lPI5R0UKdcR100+isIH1MNdwOm/Rl8UUZ9Vp+E8yjy3L0kMb1/AQBQqUjNSNCxjMvxYeLTxvaRZN1Vsf116VeUDqNdluwzRY0tSd9Q1ebpSiNIZ5njMTOwIp8U9u5vvVXQnLOL7hvPZfUlu/Z8tOvmdMzHKHscspivwuQ2Gy/T1ZxmG5QVGLZbnUkdpd4Thwq3sHdeRzMv/VkOYzidqnpgEFZjwa/fwtYqw99xx89nlwjtxMGZ6ZX0QNWSE+a9NwsOfMhZKSAHInTVJDh0IRmmxVYnNp4SsczSfcyQQ6FVSm13OHHMLP5z7Aw7k3saqiiG+dg7Qq0nRFIL061lLOap6pOj319YFnlwkj5IJ9f/WeW7THiqngV0VWZV/lpfn8xQPeVeUM3vQ/R6hyYhTP1soocXjkvt5pq/c+CXPvodoP+4WwyNT8Pv+wjHf4H0h4wdiPKdqLXrcjBKzmKZHNtGcx/SMTUp47npdCN4pHY5YiY+7pDKxL+I9fVg0Bqq8attnjcFiMbKlRFLYTeJiGMi8ShkklMh/Irz6UvE65OezHZL982w9VeFVTAB1b6eSt6SQctqqp96g3VGToDIq8qMDhTzxN35LAq1JDEQ/l3IRpQhfWcG2PAFJgX29j3b1zE5bhcAyf0p5Ngo9xiMinmFhyEn8d862Og5XBNv2co/h5cztMU1TJuRjcw00ZPVhlrcXvYS+BmtcGsNwRSe5JRzGwElFcIIg3RONChEvX5gal/kknYyKG3eSwjJ7ad1mkItINRLbxanSGW8eBl6b0IJ+6yICPg1MAWEtXtikQWFtpSxNZKXOwZHJ/WcskExnHPq2WM15JcAehhOduDxbuJFbaquHg2uKeK+nGYXtX8GHemZw2JMipfKngMq7If44Duq+LnHvNIgGXEJf7GPcskyfDA+cIHKKwgQXCSytDc1YrkXvolLRkpCV2w/lZTZrR/gVHaO9SnVs/7ShnM+2YwaiUxraab5qpsEW+/2RTUGwjiOW985R3Lw2WBEmNF86/VsytvnlzO0d8fzN1jXuAwQdUelRAXyXHxW6gfC5Cz8CawzAeb32b/7s6ZC81n/I/Sw+v4+ADvb7HyTQlxQnXxVA1hUWjyjENv6BIylqPqFzq5gsuwPdGQgBfs5OWqiLX7yHRz4FsV3h8PiYF0Tv4c8JxxLU+4VgmcDdOMn0OFsC03UO4of4fYin1qH9syRUZ8rir4Wkzy2p25aW4mLhmwyrxDqrXpIYaAW+Tj+UTLIeNeghR5TgwpEcNI5gpQHt9LsLgfW3d2bxcYRObrn30iuEmx9JwzgDmhWBq4HcysHY16I3bl6k6qFloQQmHmHZU6Q8i8xUkzYCU7XX5GqVNWCToYa+SrbG/uxjsooTOBIo2kSOUQb0bJCBou5bf6ME6feBC//M3G/p5DQiqd9JJiZeYKjkIP/ipi3baeQNmYWH7g93HP/E8IRO4k6OH6q7sdPLwqLeY1C8okfUVtRlvYMV6sIpcnuZihrQKLWKuGyR2K4M/5zRBbWB0K/f7xQ/Peaudk/QSMSXZczJqnASNCj5+say7lkzem6Uck5MBkDPMlSKbH0o6iKsQMqwUBlZMU3uUVXFEQqe5Wb8126dEcWyXmQsLMHAZoYBEqlJVBb1DXt5MihVSYAyhG67hNpuGy9m8Gn+9Jv2ev9KH80b/GnusMLBM/13HVlgq4QqQiOGZn0uOjzK2kZvjRpgJcqlPWeIoHzeRFX1ZuXnR7/bbD9q3El4Mu9GOMEacxlv8Sl9Mw2V7X7GLWNfnEJ8f1bbFcx7gVVG/yZnau1T733ENPucosQymIHrWNj4xoXvtWE/N+iFCUxjQU2uHMph5bNwW7Pi7s4LD+YIhxgIcTB1QlhTG3OmnQ8eOGdsRlt7K5I0Dg5ZVaX0719KWzfyJZ/S2KJ12kPG9//loPsXE5orB32uGgQwR9iF+rKrStrXNbV6hgWnCTjeeHTqV92cyQc5WdTWcz/PMXaXj4FmGwxucSSkVHDlwHT1YzkFMTNmm6iax3tbUmiy0+7IOUVXo2On8XvjP4GCK6SA+kWs0MIzZ5OXquk4F/mx0s1hBD5IZqHK0GwFbmkSV68/J1BR3IKZsNcV09CIwYcgGEO0dxXTyqMW2oSS/if2ZzEp68NjMkamakL6ZllcgFXp/P68o4nGuSHGW2qbfQfq1jho06oDeq5swGGQJfJiLMDxZq9AHoJQbZ5zA8cvvT90OFnMOr/CXIVGeNimjmOHnQ0DgwbprZxCuyM9Lb0w0R9Sh/tgSsXj+ujaPu7glowu9K2s4jbf4yNvFyB3XoJYbuJqHGNR2K6YHhQhBVdmkuS1YS1dRbbQHmfR52bZvzIFiVCqDTvUKxhqdPXrAuHFw883+V3dxC1Ps0WQnHJIkqHUCQ7xNW4NqCjliyCYa6x1e5A/+jkEqQGlg+aCJyYBo9fgQwGb3wmABME1DAwI9ifd5sZUO6xCWlMZHaF1rZe70+0CSycaFCN/28ojCctzg1bydc65+jxBVTqOXXzmbKPI4RL1qgI/6n07iKFEAhnXYlLI83DREcvCjXMGjIYUTDp+2YzNF+fGhAEmVIw2sf66Khho0bwpiR9scD7JKM+VXdDoOYxGLrenaLGzs5ScSqyIThsO4N+fxggbcqYo8tmtZLTXoIS1J0lvVmMshhxp89x0cd3yQYC/4Fd2UqNWGIcJyoI+9VAZWphChulDLULv0eJumAKrcaRexgMF6gjC19OFXCsxaH0dNlXTqJV0uT5x0UVDLbTc6Rj/ieI4ctJ4hvWo5nbd4m9OZXheEc6QefIHzOMkM9IKJw3Bm06t4i25gJQwKqGnWpqS0lcvVXqWrYRpU2C1jj2uOuq2rdXmR81m/Qw9nmobLZtqzg1IaGwXW2sQDbk9xFViwXaQGrN2czanbn+R8XqA122hImhyXFc8bKsVS6JIMXM7M/4DzO37NbEbQvUvgNRrBTI7gC07jLRYwkGVbS5jDcFY1ZYa2APhqsThu78KlAPSxUnMcAhzdbyWHKXhbS+gXOeY9TmIGo70iFrTUCml0FuQEz9Ac58hBfTdzGF/6/JJ7ci78TgbW2C6rATgLkR+1hbba4JW7rHe8RSeCFt3MHY/rxmPZ+PfBFjFvy2KKktypyjoVF4bAwFJleH8lJ+I39qDqaZFr16I1BdzKXZFqn7C8y8kMZ7YPNieNm78M/kbgPxkGkzjYp6ORngQJbLnH8BJhLsKY5vUo3MJchvIqZ8cvPNnZ8M030DsAAryVu7i04WEmHDSNEczi9J9uDO6RZVHIbixs6nY7nM+LXMxTfMpR9C2v45/cyPl1/+Y/80YHRLIeVc6ZvM4HCtgqQHF2kBthGNC9dBcb6ISBy03ck7E/NlfE52WoxsypvE2rUtEW0zK42+PnigsRqmSlmsRR5Sjd6SSdjGHQTECkqSSVe/+A8jU4brCwq2KZLvMZzCn8N0Iw7SQdjYoq7KVURXqwVq81KaWCKZUDIsfMbHUk4zsG90iSaFaIMCdbHHM5j7N4fREDqqZx78ThtPU2dN8kD+DgXe/x7Jyoiz+VB+tFzk85+SWtjjRUBvBL5JiOHjfmAQeILvm4SfA4VtXngBuEhOJEQo7YjuEXtIQrFqWU5gYbo3CIpzXb/MpqgBaFSQbwiz+mBVCl628uNKodD47CNFw+5Hi20lYLqaUj7zX3sIjnV4LFLc6DdTSf0rX1bjBNmhBetnt3XRI57gfGMscN3vEQ5ok8GsehlxEUMRmmwXucFAkBxYoCYmukHt4pq7ZzqaMny3h/wK1KFbl+kSJLmUOSQP3T1MVco9uvFufl25i4fMshbKc1R7X/mRcLL0//OJbAG3S8tfSeFv/ixNZePpv3cB3YwDF8wk5acCLvM5CFfmVoczWP5Fu8oqOo/MtJg9MH0KvNLo7jo7THSDw4SY69dnM2j3Kl2nQGda0KnrUZdkXP9rupJZ/314UMrGbaJP+/5GDtoBUvtLzW/9/HlfGMLiOh71LC1mL3EJmxfx83PZ5RFcXMYRi2kfDbtEShM4hbYORuVHOuKor1t3qw1CRQaWz5hLoZrvkNh3CDosxaFnglrpbFhxzHz9v0ykZpYMmF+TXO4a2Z3Zrd1rdWjuDW9Rf7vGdx7ctOOAxlHmfzOoXRfOCUssLt5ispzTiWITkn4N5r0bOMo/ic7p2auJF/sdTpybrqFpqBdVyrqRwSw79nhapWx49YzOleUuQyemW0lMNeVSmybUfxKcfyMaX9hFFrGAqismXSoURH/JecadEbxRhYngV+JxPo36kqM5L7bzSwWuTrSq4Hy1lKLw9TJn5+mIbLIgZwLzfqoJWIkK1akHIVjzBtZTwlkQhNGCSTAuogzsDom72SllagIMcwrVkhwuP32cRaOvMK41m3PZ8qt4jahgSjvKrUX+x+XhVh9PmkYs4OpWtcxcMpV9O8XJc2bPHxo1REbykX9PxB+/++fBFmcl0Xu0mEhFLJUUdBSaIG2zX8ZN9UHqzy4h2MYjpfcHgkpCn5BKUcMmQbvzCIod128Rpn0bVDE5bp0OR6OZfK6RvpwONcwVa3zPfSLaafv4lOlxC9pyFCVffGFYCIi5rUJbNY4+U8zWsMPByyKS9wAU/aF/vfXzb/EsYwjUnrerCvOUNr36cczeOkN0ZAeH1nMYIRzKRti0Zu7BhfZJVKpdeTx3J6cUKrH3AqRXJ6WL9O6X+x77356pcOHMREGhpT92/bPOHxy81xtfkhPf7pRBp3tpzvphlQ5XjnPsGfOYn3eIMz+ZDjcTD2+J1Kdeuvr5k2/DF4eymv7VUJ/7om149Gyft1bl3ng+Q2a+0241H9/5/yYNXbunbqzVIOywuqPKRLdM0ZAlHdsEwfFBSiHRGnsABch7QK9yeGsZQ+PPzLIYxF3L+55fnafZQJ36o4mmzXHNlYE8TqJQ6Wz2KfYbAuDdFB+K2xLK7mYd5ZOphtw49katERnMI75HswGWqYpzHZ/Fc/c1s33t05LkKVo0peltIPe+DWkxUeYT6q+kaT83iBGUtaBAB8xx8LTU2+8SWxi3p0TbKUXuzVo4qrOrxDOzbzFDo2z75t1R0q/j1BJLZ23jiDdJKKGqEo3+ZdTuIhrmEYczjlmAa/C8pZzRm8QSLbZPw+S7hegXN4l1Nir/fcjAHkNuzUvpPvbTwv075FXUYDSvZXR3NjhDIonezfV8+jWU4vcqmncne2n/Qalgk93wZEAcmRfMGdTOB1zzhwmmxtrrzABSzclIIqxxAbDf9de2Oht5oHE6LKKWd1xpwSeZ5v7BoiCVhNbHZcCSERvZoMEeaG7OFHuJqKynij+6iR29lCO6qrXI7gcw2NXko4V7DAEF6KfTptoqHepZL4fgLhvDiwbKHHXCG+sxtterFUO+5cXubavScxnTEczlcRXbaVtjp/pDevSgvqOYs3aNnCJddsxHCj8156xx8rvpU7PIaCTzmGTV7lavoQ4Z4tO61ZD4iq496mjkTuOi4v8geWbyvhuwWlfMbR4ntlZBzaZ63/+RM3QCBn0CDuL7iNV5aO1OAsZPpAcxK2t+zI4jC+5k5uZWz/Cspz4xHJMy7mto190Dj//ppYlu982LAjj+84KG0H+xyohqsDjSbj8wxVkT/btqhOraKYiRWDKWcVazaJ+TKAhbRiByvowZucyaF8jW0o8CFppCU7gKA/1jWK6soyI32S+4odLdNuOlR5MHcCh/ZarVPDeZsnwwwYSZpjJK3bWcQ09o3mif+/ZGC98YtIYHvdI88Ml01mtxbGRk5br9TfMDSlFJ6QKaly3HiwwLBUJYMYt4nDw1yV8tgiL4WieyKYpAtXBefv0y81q3k6kZM3n92KB8sbBBlc6GEaGDmJrp1+CqvphgG0nvU5Y77+B+9wGh1aN3rXV87Zg+R8yxRhAknqGZfv/ZcBX3I6b3Ibf9+jMuxyYw3vLerDZxytvTsbi5c4j5Wb8xUKISCRoKYxm9kMo448TBNy8kx6sZy8RBM4DkfzmQ/86T+vRvYsHiJzyqdyfopFISfb5STeZyXdGcAiNm3zwApNeJ+TaCJLVIWaJvfFAEGGxcWggVw9LCg9m7hg2xnpMmR/bXA68CDXpj1WO09RIhKqZBQzeGzaMD/pNSz7lvyiJThP4O6AKsd2mcYY7fhUoZIL957LW63+rDgkXO96d/nHPFBzMd/vELqklAoe5momD7w084MpYRxRGedgOwZfcRgAW93WKYFG2+RU0ZXVHDkspjAm1WLlfV9d5fIlR3BOTBFAOHdPJvUP67g5NocuLJbp+vhNIAys/4QotN7nRI2IN/yARVSx3kuAlu1+jxOZuyTPP37y4Mt5ouB68a+ilzp6Rk9Z1k4fsRzwKwqPGxSFvPBvs4cGlgz7jeNbZuYdqP1mN4n0gSnL24X0UjBH+rSppNDL49qKjrtlmQ6OY0SYHh7nCuaTGQJEGq0y7SJubXqDMzhrWPqE+TlVvejiFVdFxqEZGHuywjOdwba2WoTK6uoNLGXO3rbgZDrtSM+5KteFq/adxbKS4YzZ9C7XLL+MNZT7oeJT+C93cwsbvLEzkXG4noF1SWFqmCQIDDD5981twqgclFiU9ryJy7swPaRLUsn5uW8wtP0WnRrO69RF64r8woLmjMPJy8WGodFOH1U7QKH2045rVov/rxIaMfMYwgd1h/v/73/V3sx6cjYnPxjkRWlUOaGOWByT4AZeIVCaXccJHgO4WnLdh18jVSdSPuB42rdzaUElR+QG1SfSgGjL5t+M05DllU9n0xihytnTvC6J/ixd+SqRJhDLY7VHVDlefkwlLbmNv7PvkChfWq1RwNuczj+4jcqq5lWSTDLHMenGL1lVKRSChuTuASraSVdBOBaNnruimBHMZhttRPcr4cTKpvj4pDqeDNPg0Sl7+4CVkD60rLanGyv1HzyLYAtiJ3bs4U388IMYFjto5e/oU1UhhsWnEFKGsfz8MceyuSKRkS4j7OEaws9czmMZ760anIXU8Cans5GO2I5Bx5IaDjAnR8554MsBvjdDSgc2cjUP0bIoyS9eib2ce6nWhW6lVYzM+slvu8TO+wMvB/equYifqgS46nZas5EO5Gdlhp/4cXmpHzY2DA+40cEPaS5y+oqck5g5MbJ0OWfxOtl50feXcpGTHlbP27ZIQbqXcveCY7X/32kUBSsGbrNCvC+MfIq3Bt3J2Y7YiDq2q3Fr/ovrqaGIBnJYRk+e5cJIocZIfkTlkZzyaxkn8x57X7Ev73EiVbtFvmoc0fdbiCIEM2Fo4+YiT5eWtwyMrrBoSO7NkFyvwGYACyOWqYp+rq4Tapvyc2yqia/uMw0Xx4VBpqjqPpwvIsDW6cTXU1hgmkysGh455nkuoHVx+hyjS1ddH7QptHhfs/pKn/tv5zphKKYzsOZViBSRqt2WplOTTubnGttnC+9wCoWJBkqs3WIz4gabE4B5DGUheo6kNDQPV9bJOPnMew65Bm9oFMU30ohOJWYz1GdPmY7gpVnErXdqAUGqIhVVghShUHtCNsn3HBh7/u9iYJXk6uBrX3MY11ZO0L4bfslwbdB8ppBJhiHtZcl6WDJ5sE70lLylGFgOVuzO/BC+Ziw/BPlBnTsEP3o3OY23f3OWe9+yCgCGMzuag7WHSaAyPCeb4veBZeESKHqNm2lPkNwt4cHyQQ1DnXwx/9HCD8299oH2t7S75yp/8qg5MKqBFWaZV+9lmlBZZTGBO1m+PpdjFsdj1yzZJQyd6/kXh/ZdR6OjJ7A2lyrnXm7Uvq/b7fAGZ3Ceh8nWvp3L/vsHvzcgyKpfnBldZNPdR11k9+27nU85ij/zJLOWlpCbSB+Wzsu2OVcxTOYxtFn5C98vEUbiXdzCibzPmV6OmmO7nDBwOV/lRhPzP0AnW36Zc+nOKurIo12rRn9uSYyalJ7TkFLMS0QNJxOHvjmr/dy5LziiWRuc7TU5rPCwpAzLxDQEVY78zsULCcV00R/Kv+duJuAYUQ2fagc8e1kJY/nehzVo8PLtyhXGiDpbX1CmNomClYqa3IgHK5sojUhxTgPFRrXPQpFtJnlMqeKUOZqPzD+I3izjTzwb8diGq/9qG4M5cTLvsaFCcBGadhN51GrvTo6nZ3efxVMEeU3+72mm0556sGq8qvE2bI1wEaq6IVUYf01lMR94RSVuaB7IcHFOo8jtO4X/7lH7pC46lk/44ud2fLwj6mXpwtqM41T1HocPnV0TsDDcOU8Y5unaeO3ekziSzxjSq5bZ9QFCetI2M24ku5bVcgrvYrlJAYFjuCS9yk1Vr3/HQdp5cXiRcTIAYchKKrQ8S8zzcjOKQaeK1YyIy6m8QzdWMsUezcqKYm29K8wV96lpXe5/l1+Q+ZpyX+yGnquoMGqcHcJXke9+FwOrrEDkF3RS8KUyPdo/uA0QlUu5+XozZfn7XIZq348qXcbBLeemvKZUConQRIwzsL7hUIH6bZqMPShBlxuC+K+cAI9xJVMXRtnTmyNyh34+L3BNtw8BxYO1h9hao3uI8IUctNIQ+WlpISYucxcLBZ+frZaoNv/6Al3cIEnC36lJacMWnuISXl0ZKJY9T3gUz6sqFt/AsonsoDVjzoDqugR3M4FVG3NSVthN2iSUVGsq6N9xV0QZZ8q3kM80KaRYKncanKUALarG8YucxxyGYxhQ05gZ1A6CrlWTlkvym9jHw7yyky77DagkiZUSc6ZVcTKCEVdD5sqD7IS4505aaKE52zFS4kRNC1XjSo/TNsrAtrmZewD8iqxU68zsTR15bvcZ/hz41wHJAAAgAElEQVToWFAZOcY0RFjsLY9u5hn+xF3rx2d8Lg23zhSLqgr3INB+jFjvWmWyiIt4ikUbotAwqebprvocJjOW2hDfsWNl8am3cQwrbPnfqz/1jxgnO4nRMZYFts1AYyGH8SUFeQ5feyFP7dymwKsV7vuJjBMgpfKS3pwo85KkDQP+uuoCFib7UEuBxmojdenndQewiGjF5+LN8XAFftv3QBKegflfTmFgw2ztNzlPTDNE9qysMN8s7cKJIdgWvyleiFDO/1So36lE1XVJ16J33vrIMc/xR+asjyehl+kpqmEyeqCedmIZTuCd8STdJrZz0U4+42iB+aZIltGUuSjEezcfLezB9btvQ5A9B8U6qaRVS5d+LGKDHV/EIsXPhfT+lxupaU3xkDNS5HrVl8UA9CMaUpR5c6dXP8Mrc/pra8FFYzzcyY7CuzeI+c3anElIkfC60qmD49P2SNkRkzf5uxhY8jnWK2zvmV50EVW0YUssVc4YpnEQExmKHk++oveX/K17POghBMnh4cXVXLPa/3wj/+RCngXgYCaxfnOCjyYWcuo5QS6DOrhVxO49EflIB/Idx7QWCdZj+27jI44lJ69512yLSKiUClmOf9nfPgCnV0V46JCtftJwuiqfsMgcrG204Xb+zrINeg4bwJrdAc7SnlZWSn07uEVggKuenOICmye5hIHlIjSpvj/D0I91MDiqywKWLNHvIZOVP+EYgZ0V0vHp4D0AsnNF54bD0xGgURVgVIUiaS7+XuidiZsECPx20gXHwcLR8is08QZEjhF4Pt4PwVbEieSq3EkLLQnfccjIklCMHhJaTycaG1wmevxc5/OC9nxh+WpFd26uuYUsSywmZ3Wbwdccoh0jSZpnevhfc9mbz3aMirucfl4Ibbs8awNP/xwodBeDC6yXGdxpR+TcnU0FPMNFbKiMUq2kRKX37pcMAa22Mnb6UBY9Crdov3W0BKK167ramLqZu8kjSr/y0qqx3LfmNFzDI/C142EaNH6+GLWymm6Rdtt1jf7/M6r6M9vxEuGV9z/eM6QTKfT4d8s7xX4fvk5z5ABvA5NNIwsZqIfPZd6qoc+9s/Pf9z/XNqWGWzANF9s1fK7CK3jMxxVsjoS96a2y4nNy56yLB8CWhqAavi3ID+kUA0aEeO/SRjn28t5XWRl/bi2KUMbzEvsUL8mI7bV+ZyFvcyrT13bkzYYTvP7xkuaVW4ZTJbp0tOnMOl6v1T3aYVmz17Fcx30cOVgAXcs5lHGD6x0n2Useicmbvpl7mMJ+vldSC7V7Y66dZ/91Yn2zcoUtb0xd3P3r0A9WBKtuVww+5+9iYIV3ax1ZnxG/xsJmG2VU0iqSOyAxWCgOxdUzLAL3eLhEYQPLalPqf/4nN3ODUu0V641R7vFbkdxXVopd6WL6+Qtip5a7OZZPUrq6w3IBzwOKgeWH2rz/ZQKmVPSO41MMpAJ8jBMVlBPQuLok352a17anfWKakEUjEwbr1aEmNnbSpSDP4RKeomtbsdDI/pnFcG49cIqOg+UadCzYSZ8+hEScM5mxrKksxkoYZNOAi8GN/DPjBM/JF50bdo2H82VSPXtzN8V+OpniwVq2Po/7uQ7wDKwMQFjO+o3UkcvJLQIQSYn5lE5kG58JVWA6DjwxZTDlNfHglwAH5Oqo8jMZybwlwaZkoZeLlZoqR4yxXp3rWUZv+rfazMUxhQpTqodwJJ9r32USOV7e5lT26r2ba1s+T01j0LbXE3/g4cR1HNI36n2YsMDLNYp5f6k8tfJ+TQ2ibTcn7uNrDmFuq3Hk0EgZW8kx9RDokdniXbmOjq22gEE+Ercq323tx/vbx1JLAevppNHySKYH0AGAM9k1cuzuwOMaNQ0s0wn0r9IJkgImYdqMi4FFyUmk0S9eQ8JkuankVW/hmoyIvV99VfBMvgfLCjxYX3MINxcGJMe2sgk+NoSlZBqiilvqsQaFb/NIPsvYNulpBw83LAX+V6oNrSxCcFwzqJgNDTbLdAIiak9/p93Ejh8Pa9ZAt25+xf2d3Ipruxnny48ryzidt6muz8JAeM/CIcLl9GDO4RMYrDg4zOyE50FKb8AtHHQa93O9vx+Q8Ay73SiPnyrSgyWLKOKockpmfUv7Z+7wUgBg7+47GcLP5LPb79MxY+C2bi/xOUdRVZsZ50zq4/5FoRCmadI9ZGSuoBdh+V0MrFW7dHfxBjr5HoVUsosSP17e2KQPpgUM4nsO5Ka6v2nf2zaxuRJSZIiyIFef/IZlUkcuFZTC/fdrVT+xkAQ5TtrfmyPDOwrv08ascmZWei+mmVQ5EsdDTrqZq8q00w7vJV68j3gujQDXpSWV/IEXOWKYXpKfTi4dPovvWgcJ4XHPnJVQFPke5pD5BlxYsWCLiRjiaVErdwzL1AwsByNtuT3A5wu7YFqGjwHUifUMyclAi5HinYQ9WKri0wjNmzlOWhU1MZS5WhLLwrVF3I3IWbSTLpMXtMDAjaDVS1n5x7vJp46p1QH9RHNQqZtSeGNtR+TnVLqpwz6XlbwaCWOEjc9XOIfDh8SXsZuWIRZy7103uNmspIf/+1lnCWVf72RrqPTNMbBk3w9jDkWFLrahK9aurEkZApWGeSwxdyoDyxufsuLr9FeO4ZC7x4FtczH/8Yoz9HZbClVOXo7Dfh6MzCcc61eXacebwvPyg7MvvzCIjZuC9qngodLoyLTwqcdKMUwDy3D5gbEcxafU7A5+H8LPlFJBh+ztWAiICG3BzXA/F8MHSs4kW1jCMXzMraYINz/6mBIKVAqDJF/om5xBsRkU4qjq4CAmade+vvwdLu/xOaVUaM/djk2MYVrGtuXkmZzMf/377EimSKZPoRIlEKbtmgzx+m/NFh0TxDRcJnIwADfxT2pjSIU1MQzoIgo4qiqEF9vBTAm1ot1LejFtEWUyDeE9b8tmf3z0aFxCy89eYy+UdBzL0itWUzbN9a8PQerA+03pyeglOO1opovj4zzyw4fDH//oI7l3bFXHWbxOLQW8vyDg82yd5eGNNUMl+ywhoeG8bnOWX6F9LanZY34XA6td4e7Id5k8WGoyYnjBluWz9zVdrX1/2vSrOWruXaSSsfzAgUzigjGh+JFpkksDpeyAa68VuVfypxjFqoIO/lagUVlF+Ih9GVcsETQ8yzfm8xLjM8IHlLKdMUxllefe390gBmm7ot2M4xtGdNmitd1Oir7+el4bprIfVRTvUZ5BWXEDva0A3NVQ+kTilf1fPVhxKN/zc/bhrL2XULfb4VsOZketUDzh0mi50Nm2t07GLLp9WgRl9qblpbB4k/ty/s27Xa7J3MgYCRsRObnBM6jl6/L04aXC+JXYQWE5fOgW5rI3BXnBjFaNODvpsrNGtPujFGjw0gOSMIKNxFIiLr2IbNkVr7iHznkOd3dt2rD+4UXT/CKSoK368SOYRVmL+Ko/SdEhDax31gSL72Gls3ntNbx8kBCNVurH8cUPIXtjzNywVv8dm+12C+qT0R2tXJDi5nmqJFl5vyG7p1FJCwb2avDZEJ72EsI31urGqqksPHk5TsQQCItlikVZGjJqSPkuggIiOS9TLaxdlSrCOAYN03SpoIzPOUqLJJSxjXF8S0GiAQeTAnbTWjVSMhl0s2bBlsxeVYAGmviY4+hRLDaFCYW4PCfL4UkuYViPnfTsZnMZj/Mcf+S7htGR67zGWT6tjZRD2szngNJf/BC8/9w4NKcwJDvP4kEPNsc0YWVdh9jjUnpuvX5yMHwapXXbwgYWbPPgJU7jbfLM9BWJqpzF6wDsxVzuXX82K5LlaY+XHhvbFmNmTOF8rip+kc20p11bbwxlZYFpMogF7MdkPuNIVm3OYzJjmdyQ3miubRKL50+rRb7SqNZiXSk1ouF5VfbutoMytvrAoY95hmmcmIbrU+XI97q5Ogjxv7dNeEKbkyvcp0sdo5nGkir9vao2SU5MEYrflox3+B/IyM4i3ipRfiFzDpYq4Y549MjPKaQaBytUzp6eKkdOGith8DGKxRxmL1eUQ9xL6NUl6NDfTJXjdX0WSd+F/cOSNqIaLcNF/8UNHMQk3vZKpbMsMYiuGD1bVFh654dDhDuqhbbdY6oc09RyPFQqB9lXudkOr3AON3N3s6ozVDl3zAqGMYdLZ+gJy30Ty2mZU8umzQaH8C0/rxS7w9JWLpfxODdzDx8u7q156hw3vhqsQ34QNjEN4SkCmk2V46aoCpDGTwc2MJbvKSgKbv6PxB3kUifu6S26A1oIstK5MczrgK7hPHFUA8t2M+NgeSH5LOO3geCG5Wxew/3uu7S738Vr8iM4X07SJUfJH1INqLBIL+biFdkM4Wdmby/3f8sxxLt6tvM/uKD4Hf28PfBg3cPNbNyew5U8CgTcpx/ax9LBXstz06OVnuF8Rv3C6T1Y+792MS0QBRVvzOvPkVVv+cfYobSJl+tEzptcGGqJ5nxp97BcbMf0gTflJgq86mZPsj2aoDiP0iDma/QjWaFKecMIinFANxJ8qhxLFgTtxRF84f9eWZuCqUDK8OFoWfNpZDlQ+8ILWKeeBEBSKenPznK5hKfo0aEOFVD2kZoLtOcAEflYHw63etWrqnFoWgb/4ZKUfJCaKAjjhmWmjMykhEzDYRiz+VNx8M7CxphlBu9uPZ32SHfLzboErlXzMmPbIzflXuL/A10e4ZrCZ2IfYiC/8Bce5Ei+8JkuMjkHGmyxBq2pEMUXZ3YX0Zi7sm9Pe17vDrv9eZtJZA7W+m05vMdJXtPVvF1vTjTDwOresYEqivl4kw6/oeUBj0mNz/X75GDFdPqEsnjsqTgJd8QVnx3JI+eKahLpuquvh/c3jkw79hrJFkBzRoDdspm2YIjBJBWuFtqJeQn1jam9a82VpdtFnsN2WvnK1q+Wy3DNrziMuxQPSO+2nqfEspjKGNbtEoaIzA+Q13W9vvqI4/l+YWbyXynT1nfh7uor/LCFqgCsvQbLW3MOr3E3EyKUHJkkL9clm0YanJCG9yqlwhRC7dq6HhDgYJZuLw08FNW7GVv/JYNbb4rcQ82NMEyDU8Zs9OknvueAjEZtqh2o9Bbty1QOZqJ2HccNAAJlWHpEV+FJS7k79ssIVQ+W+HsD97JXx20ZuQgbXdGPWUbz8+wgqCKUMpIZnMD7WDi8zWlpDaxnnAsi3zm2S3uCd/EvbmDpe1FePgi8mLV1BvMZoo2Fe3o+B8D+JfPpbYod79U8RFdWY9ZFveNhGT2wminsy/NcyPqKXKo9ahe5u//YPSYl0KhqYI1AzzNLaWB5XiMfe8k02VhTxDQ72N2fV/69ds74/HcBYVc3NrhMYb+0z2SZwuvxUK7IK/U56sB/PoBCzxP6VJZOxA0eZ5sZ9POIAbUczLeMYjr3cgOtWro+TyzoRuY6OvNfTtXCQpto7+dVZRqjeyrJk07CzI2pxPWVg4FrWj6e0iwj6Gv5Dv/JzRH6m1lVfZhR0VPLpzEsk7c5jYfRIySxYllsoS0dWU9Brs3JbabEHpZKvaylK3MYzrUlzwbHhoz5t/d5gMM94/UW7uZCp/lrpxOqND7NfSvFkfq9k7bnrLCsCFWOlBc5z4cGaW7UQl5CDo+8HAcXg/OsKNuB3jCzWR5FwM/BmrGkhV/lrPa/bGmz1m4PkDpClePZBeP4Ji0W3+9iYMVhY5zRKooZocpxfOh/js1/MPXY6D/+If4uq4130QK8zeksoR9fLunKcV7yn7qzk27YNqjhpOi9VTLmcClsc2VzjSibr3YLfde76wpEnkw7lHDZth9utSyO5lPenC924nn5BiOZQVFOo3f94JzqumYQmXry44ZO3FN7VUCVoxidfuWiaoDsqVvP2wWGB/E9jdfyw7L2AdaNfBeel0fQm0BhicW3HMx+/zmbh7mGS4ZMj9yie5GyQzXRkNxnMJrDVj0VOUeTFO+kVYnNw1zFvdzINTykbSY6mJvZl6kAnDZ6HS4GF+0lFqAwGbWUb39pS0+Wsb0i6Av53iZwF4Pbb8NZtSZtU/+2U4Q7W2ft5JwYmpZUMqRcrwScwWj294zqOQyP9YIc4SWcv+0ID0w7NvlE6nbS1frjRc5nXkX8/JQeLD8N0TutmF20SHj5NKbpj4WrrccZyY8Y9bUxV9MlkS1CWCDGaWfWcSHP0o1VFFGFjUfVFFvPEoQIwzlDSTt+TOzVPwjh/JFn2FSRhWkaGu9fWCe2sQRVyIh266iogB8V+ISvPopWEVqWCBH6uVuKB0vmrp3A+1xx4AJRJZkdra5eXTyYDYedr130FwZi4HID91FSgmZgqQvSYg889boeH3C2l7P6IueR53ls3f+1hUVA2q1KY4PLN4xjW3Uui1bk8Cx/EvdvEZTMD2gfhJ/CuTv3LD+V2389XTNKJSJ7c6hyME1GM52/cTtjBlbRpyBaKAGkZDDwRdlQhTdz+T98Qb5Hmj6PobzmNo8yJk66kl53qNjUkotwct1w9ucHdlbrxloTWUziYI7lo2ZD8/hqVHatjGFnQE/eUZfnFzmoEtn0AJe2eJODOy3V1ru4/m/OMlXdkM0iBvieN/9cz2N3JY9yYt/FKc//XQysb1Z2BwKqHADmz097zuUEVSBxlqZ00UnF0rpmtfjezRwWWVMZJCLGTaL2RpCIKwHUVNlaGez6hvSJKr/myAkDlpFFI2OzpitAo0ZAsJlGPgzl3siF77k5Q9lFC//09u3FIjmip8AUUvOF9iRPyrQEi70MW6i2hmkJuIi/7DeTW7iLJ7hU4CbtgcxcVcYMRmvVPgAPNvyZqas7KCzz4nsbi820pZ5cUYGYY3Iwk2gjKVti+q86GeQXGaYRIQ/dlGy+R0+VFkU2V/Eo0xhDCVWa8b2DVrSQFV2eUZhlpvcq1TUlWEFPmhoCheN7NnFh5Urct1LsQr/+GmprfaLbq9u8zitkxony76PoOLljvtYjExb3j4oMC0kj/99cRgc2+u3+ngO04ydt7EucHDZwI89zAe4yEfKSr/DfXEbHHGEcv7/zIKbUC1e9kRC5L89xYeYHU4xp0xSJta9wLncxgWqK2U2B2KXGTLseRWJM7d0n6ilLtQM2E0E11XP8karaBFZCN7DCc8TFIId6ju++IBIC3m/fqI6S0CnSwHKSDv/lZO2YrbQJQs4xG4RL/mxx4plKKM802UrbgJLEMHhmn2f4NyJHVNUZWQgjslfJVvp41W+VtOJG7gWCIp7/pZwwarNP0SNl106XQ/mGab+WaoTsbdsFbe3VNiAIXxbicZXFArkqFIZh8Dpnp0Tn1i9giWIcSZUTU2T1FBdxcP/0+WarGoKNR0Q379I3Ps0y/FLInfw17e/y3lf2/4ZP217IsUvu4+idrzKF/SNjVkK5fMKx/nnH5ITgDELie7DkIygsHOlk6tKyCMD4QBb4Se+qXF32Gkd2WagZ+WqIUCqy5hhY81YJW2FtnQ6z4YdSsehXVsEbHjZfWH4XAysMswBwKU+kPSdMbRIWP1WlUSxYA5eLiqq8ZGpuwNGyKkS5XDbRhEFpsDzINRQWx4QIG9SX9duS3HuU7qSRHDqamwMPluOKe2e4Zpgja4ktqhAr64UR4S8UoXwe3aJvfrstL3yzgEHcwl306R64RNsW7GYAC8nOFjAYl/GEFkJtjizfJsqwwwnjluFg24Zfii0XtE3bs2nPZhrJ8YmbQXB+lbMqtv904k/4cl47vlVwljIVXaQUTzHIxVPdya11OzPLw2zCNKmkBXWN6QGx/KoVO+rBmscQtq5v5FOP0BaAmd4OrqoKDjsMrlGS9b1Y1eF84Vc6pZP/j7jzDpOaWv/4J8ls351ttKUtvUgVBFSKiliwK3Ys6L0qdsV+r1jRq+K1X3vvooK9YgVFQaT33tsusLN9d2by++PkpEySKQv6+z4Pj27mJDlJTnnPe973+7V7m7qyiq84xvF7p4B79dvxoiMAy9Ozi+bkUM0YPqB5sN71XiWJZSy6t6niHN5Fv08kqUjPyThe5YUtgpzz3q3/YGrtsXRmNSuUHijonhl2sVi/M9vk4VI0sVBoIIOdhrzRGroIRQePPtEtuJ0T+JScHNdP/qt2TeMUW4anqikiZspmYL25wbkan1VyqmB8j0Zd/cDLkJsweCbTWl3BxTViIRppdAZln8tbYntE01hPKdOjI13X+M9/REa/xLrt1iJkNoNoCKvkZzWQZ+j42ethSuWkORcqkhagS7GbKHafoaqkGQHusk/Yvdt2TqovbAwLbQqq2evBUSQuqRPVFYunjdS21aUQsyRgXl7dzlXkQ8bQpjj+Qnz4Diu2MNbAepbLmGbEEok6Jh+/nCq6t6vhEa6nR+5mumVsoF5Pp1rP9qyXHdK4PSXjK98yAH3aCk9tizzD8yw9WMcf73MGvvfWUbzfhQwtsX1KuzE1KChE0TMSJz1aUjkx04Ps+xtpD4rC5TzjXe/Et9h3FGa5G9ezxBdplYSOc695zfN304NlGFgmpX2cILszeJ9cKh1p/EHcA34D6RzMLPHSPMxcaZxcynNNj3KXlAM2nhkzjTYFo23koEpO/JdIx5exH+Y8EbM6cIg9p1BtSWkQIEwLdhJIs+p33ZBZwlDZB24wWRd9/XrncaIGt5Xzug5yP0WQvT7DeM7lHTbQgZt/dqf87qgVK5FxvEL/DnuprHfGcySiDQEhzB0rDF5TAzMYZjKY259dO/YoogHRi39Y2pIi9nDPLCd5ZizMeDJbBt6wbjuZxikcyXfcu+AkXrZ7beTeuAyK37iRXEV4W/LS6hjCb3zNsY7J3Q8by8RA+m8mcQsPMtoWtHwXd/JbsxNd55x00FYCNJor94e5kZbspBNr6dshZAahjzMmsIL0Wu+b27Z9AVrlim3BCAGWVYuUc02NMlT7ndV05Z/1/3OJG/uhvDKdBUZmsKpa21ux8Op253SezaecBKrK7QYZpVneZ5GytSwdHYUHDFklRVVQNcVMSQfYVe9M559RJZIeqmo1N3mtR39qU1BND22VGXMUzA7zNucC8Mq9m83dgo8WdqIj6zmlJr4IL1jZyABDmE3Z3oDD+2d/Xvmdvtvdn9dsqgEy+9u+ZbnfoGlcyGu0YbP5reSYFiuV08pGKF5Zn85qQxbprJOdc5GqiO1a2T8eJUE2cSwUhQYyuJqnmLsqyBdlbkZylWjCAdchlRNTVH5X8/d98GAlQmlJA9fzmKC5MKRyZBxXvJglkyongVROUbZ4/7kZxk5Tx47iv/ffH/c8rz6whN6swO0R3xBpy/bKHIcHy952uxUKr3Qy5M/yuWLfuJwDr+NxftrQgb0UongY53+LgdW5WGyTxLp34+EmQ0ury3jvCWlk7538xAiyM0UPq4mIiaxTYKNnebAsXsdA+vvvrnLPpl/LbxwiRFo9Okb7A0T81PNcxsqNCbJl/GBUYlTGTK4oEls+pgcrBXwxPZ1CI+Nbtn9Z5T0hjbZs4qs/xPaXPXU6leB8mUJvapfZ34mmcTlP882qjk26NlidZ42N9wikB8suh2GUt7Olq4I/6QrbCsIrGPLXneLaPVlG31IvqZzEqCGHRfRxHFu/OcAILBFke0d+etaBbAoLAsPyatFOwpH478bLwGpbWM0pfEw6DVQ2inZ+Lm9xBf9jR7UhgbNuHc9zCbvrc3i72bXcxEP8WDmA2QwBSMrAGnXzAB7s9hJD+cUVq9KCnd6ThDEB56nCqFttkO0toRdEIqaR0YAwaP3a98Y9eUzjFPPbFdj0S+dXim8nhHmNrT4lyr3cYXml48C+za9oqiPN3w4vA2tHXT73crtpNCWDqroAH3EqdYYGofBgKeiofIIwUmMH7MceE9f+96/HubQI7QsK66BYpXfUNnAGU+jQstaM6xs12gph2BoS7SOZccWlcKHCG+uGsol2lFNkqhmA1cc+3jqIdXRyXWt7pYfLbx/xx9oi7uYuyim2Fo3Su60qZlLPMzGG969rW3EQc1n90FTe+tDNMeWSymkiahsD9Mx1z3FfMZp1ZXkeZ4iFCzj7Z9dSZ/ucwQjH33+lgSU9Sl9tPICnQ2MdyUGxRs66+y2JsPQsjfZsoFGPH9srF2LmM1x/Pfz8M/TwDh2QkG2zlZE00wmR7BLrZQcYs/5h7po92kwOApGpLtF/8ljuOHY2Sr43Z5njvmnehmNevsqlPMcgZjNvuxjj7ZmoEn+LgSVXsVs8GIn90J0VXMejBPO9G3zzwjAjmGFy/Xy7RXi8bsn3D1beQyEh8p0DaZcu7oJGgYH8SX2j+xUVHNCa34yJq64xNV2t2Hsck/Uz1xUJ78dhXbfyhJJE5ooNDm+OJlea8keVLbSlulYcP/+QNQxgriibwpfXAiIbpY4sruFJdu21ZfupKq9zAct22cgfU9UiNOptxn7I+yIMrGb5jfyL+2jTQgw8sVqE8u9eiAw1zwFokAhQfozrQFVdg0UytCFdWeniJ3J5G2yPbtei83M1x8LLwJInaUSIGnEQjaTxNFcyYfmlEIlQMfAILuN5blhxCb3TVvAQtzgU6mcVjE74fFphkJtX/IOfOMwkQJQ4hFneFoiR3dM2zRljoqNANMozupjspEcl1OjNtfX98tacxjQmcTuZ1HJ0x1UsNjTu5CuT6ddgEXP+hpvvyPVcMXImMuA9Fu2bu71r22vzuYN72Vqe4XifydzvXSMuQ1EtaaZRBuv5QQVrHOecdhr0zVwptsRtn/6fvOCp7PDz5k48XjGOKJpo79Eo3dPX0iltE827WwHemrHSTmZSju23iqby446efMqJFLHHsXiYZGQx2wmG7fh1Y5uE90sV5VVicVFHlhX2YCMale+9o01UG6DMWNys3Znr8lpoxhahfJ6kMgd9oChQmrXT87c/1hV7HpeGqn0CD+YlIANNYRF+HY8CcDEvJVU+VJfOrxzCtI0D+V/FeWY/A7fHtsNtVrB9QZFKC3byTYMz5jIWaYEoNzKZ7iG6FfUAACAASURBVC2MLWRNg+Hu4PVYyHGxP/MBKw45VrwbbKEl9tdkG5j7jyzi7i8HJ+XBkrtCJzaPccQY456CTqhBtK9y3N/4bzGwNB/5gHhYQm8e43r/7TJ7ugPQLEvMZn6DJ1gBfvaGYmcnloiqlhXuZyxcqLi3hFLCaGPCO+QQczXWu6ScS7XEHUFyK4FzdS4HYhlLohn74hEZ969bHrJk5Xjs15OorLFa5ssLBlJDjsOwSPWdyLr0MzqPeR0lSiSq0KpZmPu4nXYl4kHkSvVRrmPcwcsdAYfgPQBN+JfoBPVksLcm3Zx4ltOdMXyQ1K7sbQf/yH8N9l4Jl1SO7T0cY1tcpWpg2Ykj1+7I4S3ORVEgWxM8NofzIwAnFs40tAlFPzimyBLDtXMYdeqWnHEA8AoXmZ4oieHM4Ngyd0biG793Q0elQ9pWx/EvOY5PZjV3TewbqrwnGvl+5jKQWrJpnV9tTnoSqqLzQ2QE/ZnHXt07psbz2sbEeyOTad86zFfKca4yg5jNUX3cgdkvrhLeA0VTeMjwxiV7v+VGmIMaUBl32DoaCZBJHSoRCtOq3OcZ6eV2o91L4QDghw2deLDyctPjoocjZKoNjO6x1hHsrWnJG1ieTO6qzSNs6yQyDjRN001NVDtK8ytcx/YV9vrVVIr2bheCN7epYqa1yjrhPd26x23cq6owbqRgtV2bUXpJkoWqxZHK8aN5Mb5fFJWDZcB2IsqYFDxYMrZsLIm3iAEWbwwylF9ZW9UCFd0hgB53XFcNwXQ9vvG3ZU8uD3MTe6o9KDfiQN5bqqzEeweaIQo/oLSc3gaXWTIefM9rGW1qUDBG6cN4XgXd2q7G7b37Wwyshdu9lcSTgZ+Y8obdeTzJVVRXig/ao0isHNoHtnqWB0ug0j6Zyu2s7bQ0V8z3NlgDqV+j2qyLFVpTmdzp1Qt0nbKWvVhVa3j2fOU6nHB0Flt5aZEPaC9clSbDuYyHiEbpzBqOZDpHDEh+ADym9xa+trli7c9cVpdrHMPz92QgH+FkGzUHWFuEdq4bsCawEraRlxU2v6dMtfbqfF26wLHN5rCbYr5eVGJ2nByq6cRamgf2us6JRUWLrqZguIRLKsf26O++C1uN5mgGryeIUcjIhGbsQrFFaM5Y0ZzzjG8un+1KI0kkHAZ0iw5B0aPc1+01FHQW5Vqp/ql4LGXwtx1V5LG00a21JV3+Z+d97v4toru+xcEt1rrKgfV+5L331mfxLmKFbFE36Oym0IynShayvZzIp+QHdc8t7G6s9HxJtWFjazOFNu3yBKkiAFtH4S7usrxOsfVUxYIiPyfMjUwmjQZBSOth/QuaBo2lkW5M4Sx+nZ8ttvAV6112KSwzY0WS4RByMbmrIgh8DoO5lOcc22dDEAL12RlhCtlDf+Y5DK2/IhDbbmA11IjFlunB0hQys41ty5gs63gUCad3mMOlrT6hNVscx/szz0GcGg+SKkBRFfY25nqW8et/3xli6BFdMyWOdof8t9mO5zP+yHMnLPhBJnGl+WyLx0L2lcaoIE1VfYhm3SdKqp34313yNSdIGvQ4T9x7HK8CmMlDeYTcZVWdV1YPp0ervSY56cxVTbNBzDk0JoOyMarxEv900Kl4nt+ku6aIiw5axCSbfEMqiOXekFi6JZ9reJK9e4y9c6MXXb37Lt9rncH7dGEVx/ez9snlh2vJTnqxFICfw9ZWlV/HMDmhmurBMvDsoqEM3yQmz41l2fzswfURC8fgZRt8M9Oj5LOXIR3Edk0s0ei3S1rzHmebGS/Jok1xHUdj8ZbZB2IzLirZlY4H5DVit2BeK7mNS3rPoq5WZwXdzO1Y87mM1b2iiPgyuQXtRxMhj6qqJQwbQeMhbuHLXjcmrKeQ13G2x3is6hkZgioDnB6sFXRjhg+R5KF9q9lFCzq1qadv6zKeu2urGUsQUCK0ztzNK4wzy0utRjmBqnqEF+cNAGB7jRVj8NtvCR8vIbzeqvROtw64t0aiEXdMYa9C7wVQrPdk9o5S8/+lWLyqWpl4WgpKEA5pJVX1jG49ku88DRl5SFGVpD0asc/SqoWIW2wkjXuMmJt11W4WcxWdSBSKCyJM5mYaSWceA7zvoQmiUTkOSZkoRbH63433FZlbHE0xsBRNNeM6X+BSx+vpwmpG8BMZaeKbtGYrvVhie5a/wMCybfVKD28wJ8K/mUTHkjqKmymM5U1WxMhCyWp7eY9PaL+I85t96aRpgKSlcgBe5J/iHBXmVLgXIZB40RlG416Etu62cn/vztm8S5fA+qTqBZZBcjzuBZAXZNsNR1UUoEPOTi7jWRpIIyvH/T7m04/XuIDaBo15DGBaQ/xsQMnw7xeT5od2LYWhKFn8L+JVWrKdm3nIVfaXkCC/fverAjOxZMOu+MoIfmhWrNOfeWaMt4QjDjieY69Jd00Rmf8Yy7/PXM09TDSD1JKF32RtDppGFqFcXVVE/T+c7DQt8ut5g/MA74BsezyO38uLp1GWCiSfDcCUPztzYsOHCc+5wofi4oLh69hLoWmwSENEerDWl4nVlZfuX/xKOiekmBh3QLyHidzDaL5ImbliRG9BBPg8lzqOH5q7kK7BHSxelUEPVrB8o+gkaRkqJ/MRjzCBWetEupBK1Ax49iM5tEgjIS1dVPJwfuRO7krqfWgBxTXoSuN1FN+6xI4d58pgySh0YxXDDAJSd0GLWmPjtgCVk58zV3tphGmMarxqM7A+2j2caESnwNA9/KhsaKw29n6DV5yaHJDrdfekEIlYWmDmMQ/KFvt1AE7gU1bstnhn5Ne8udOH5paHlsIELt/9m5xHqFrj7rBY7LW1UTxczCu8+1up61zTwFKgLwtN9v+490t39pf0TJVZa1pwDlZQ8KrqEvd5alTE2Bkf/Dku9aUNkMZ+M1X0nWg46iBL1XW47HLV8pwmMdS7gtw1xTSgYz0TkvtJCwhuqQX04zB+Mn9fstPJG7Q/YJ8L5LhfkBdhEhPp0q7el7DYxb3kuKgKkYjLwLqVBxwyQvHgkMoxjsUmdPmtZzUiNGcnZ6hTXfX1QhqNKXVsmT1pqgokgAw5aYxoqEqUR3u/zLNcThphz7muHwu5gDfMbek6PX7S124jHm7T7tSSIDq3rWcC/3UcS2QEr/llG78bsdLutJLk0Kqlzi6aM2N3L+e9bdvw8b7H32JgUVQE773n4K0oojypU33J/OQ8ZKxk5pcJ78WfDb19r2USwtlo92Wj6chay9WbxMfYXx4sU+QWY4cwiYnjM3yUxzWNtXQ0WdrtIshgadr9zGEs3ZB8A19bFuQF/skRfA84v4lJDaHCPdzJF8RfwXhBZoKWE0P2qWno4Qj/eUms9uW7Ts/S+IhT+YNBLN4mYno0IuY3aeHDtWT3YB0xuJpBzGY9HYXBkoRHT9JV2CGNuc4IPcV45wKU5iZo95IXJhKhggKqIlnmPS7K+4AB+WscBIhbGpoT/cLaytjeYAU476Pt74qt8eoX0lv4asjNTB+N4Jq4tvbw3t6wT+6fcwK1YcubeUtrEXdxfMmfjOBnAMamxZf8sKN1ic4zjOdl/sH28jRW6SIr8VKed9bXw/iTRnlshm8Q/y1215igKGz6fatDnPv8tj+6ztOMmMOGep11dKCWLN+xSDK5f1wsKDsiYd3wYMVwyRljwA3Ko771lWjTBs7mHTTCXM0TZGRawfmx49I2SviFYajGWLCFthTbxvTGBNmyTYG9jZgxivbwAR9Zk3hbhJtqm7Gsuj2dY7yTr3EhzxnC3ImgoJNNNZoGg4vEIis2octvIT6DEeyiBc8r1r3iDUV3cA/3101Iql7gHlPl1q4f5GIkLGW+7IvrOBWzdhXiDzoBzZg3k6DFccCIeXIckvxjPvi4fBivGYvRBKFh/jDaVGz7VwLivnbKEC/8PQaWgSgqdWTSk6UOxfd48NHYNQcOM01XrjTjGEcPcCsb6MDSrQUWb5FxnfV05A9jX7dETazyLrco9tXAUjXF4sGKkBThpV3/yw5d1ejMWqbMFROIlqbSmi1kagY5n62N7K1KXirnj43NuZQXqCXLrLNZf2PgSCgFEQcyjifWuzk1NIrXlw1i6vcFzvtqmvmW5H1fyr7G3MYc39vbO2Tf7rHz+2yklMtX3+B5jh3Ca+B8by3yG7iRyUzkXjNmyAtHHFRJGI0JfacL/SqfZIwVm3M4nB9YvVY82CP1V5jfbVLzxxmSv9xRvjGqoZ9xhvl3VFcY2VV4ZoZ23Ul3lrP+ntdZujTh47mwnRLh3TPgNSjKd/pDzRDz2Cpj1RyN6K5BcfoOJ82FRKz3xD6ut04vMw/K6/27Lj4jtR3pWRo9EO9N1RR6a8s4js9pz0YOM5IFxG/uc+3ejwX04xsjFjHkQ1wJUNzc2RmqajVmrnF6rLy2sYfmL6Ff/npWrw/QiXXMYVB8AwvN/CbSgxU72I8ZvpMasrjH2H6KBzWgUksWXVjNE1xLdo5izqmx9ZCxQ+f2X2pm7z6CNfH/BUo5ji3CcL1YNTbUi/CBmoYA1bUq73IO3xt1k2gZFElBkoPJjlvnjOGAxVOoiPmeJiVNEjiVaVzHYwzoWUv3XO8t8ETrN90m7h77rk9PtzxpK+nO47VOT38q6MbKuL9bMViaaEuaxk+M4Bze9myzXVjFRbxsnpeI5uKkAeuZyD1cfHBqA1JDRGOdLQEBoBXbHbJ2ElIzN8smbJ2TnlwMWiwiaGylDQ3RmPlSVUmjgX9xP4d32uh7/t9qYP2H29hNMWU0YzwJtN8MKL6Cqs5sq65FYvUUz0C53khZXbrV0vLzWln0CKxOWK8jAjM4li/p0jFF5t8Y2ON6oh4rUC/MZaDn8R+XiUA+GaukKLBFK+WcgSvN60ukYhjKTCQZI+UQezYmpTMGruNdzuKzJniw1u0U3rRQjBv7/l3/5NN1lkfSvK9d+sQ4dF72VKYbzOx+JIcXtv1OnKPi8GICLK7p6HmOHV4s621bNDCZm/mMEzyzqSTUNA2NKIoe5XuOpBbvmIDq+gA/cTghwwmno5geLCWgUVXn7OjHZ37veI6R+XMZ1G4HaTTw0FlzWU5PSgtD9OyZ8PFMlLKe5sbAdbfNwPKa7OU3kVuEr3EBbccJSYtIWOfTrLMc5a++xJvR+oCOTooEed3nuJQDs0UGz9zKbmbbl3W5iicTP5CdLFNTURFiylfzpMMbqHgsRXsViW/atkUDawzDsR3+AyqI1bzdQ19TpxLMqHeU8draeKDby0zo/rlpnLzFeWbMiesehvSO3MKLRGB2u9O5d5hT4zWQrpJFXdK6eh9zikXeqChcP2gmV/Gk2ytk/N2rZDfHGNumdm9Cx8L9z+Q+oEcNHQwKBjnur9uo0YMV/LEyaHoVYlE6XGz9tj64veu3NVvEYnVtDJfXlxzHx6q3XmgsTE+KopixwHb8lwn06ejOGrWjxjYexBp27z+9i3NtiU3JzBF+SCSdJbcIr2j2Pk+2eZBbllzA4fwkFo8ec/EauvAqF5n9daA631XGjrSAzj3cSWZaavPmog15Dv3WVXThDwaZyT52fMqJPMN4jsqzvHXpWtPm6S07Rf+bUeFeGModsUFttvJvJnme/7caWDLQbhctHCvjePCNwYoxsIa12yCOK/4vcjI3o6PQGLU6oqcMj+GduiRmC8GOoFIlBDj3MdBFuvpBeJiSWTV9iTvNHGB7SHRShwitppludLsHKyWpHON1zeUgruYJmtm8zhnpOnmEKMxt5Bze5UQ+S/q6Emu3i3rX4Ny2VBWdSL218jDbgqqSQb3zOTSNKkSMmV+Q+/Bmy4zrwIpN2fxpM1STeRtZGVGKKHdQKMjZsD6vuXl/T5hSA/EHRznAhRsMzwSqQYQYZbdeSEWd03vZGHG6zjOUBksRIEmdr1j0ZjGHMIsfbMYHQKbilpXKzxbfJ2DEClWQT+DeOxnCbxRl1nCI6uSPadXS+/m7tKtnFN+ahonWW0zyV/Mkn+8WXFd3LjuLB7iNDOpMwfN+LEj4PDX1GhMNFnZVFf07RL4rLsVrLVeat5tOrCE3w2qHfYmvo4qqciDzrD81heY5TlHq6bv6ep4nJD4ST6An9N3IVPUMrtojnisS1gmumUd2NGYi1zR20pyVugffXwzsxvs2Wgl+s4IqerDcNS49rN5iXl+2vw10MH/vWphcCEgqCGRopran7IP2LEJPQlag+0ndWbQgSq/Turt+21IrttSf4BrasZG+tvYUTVJT1a5FuKvB7dn8haGUtowvlVOIlcUcjpXT1TTa24z6v5JotKgIJvBfjsr+hUNzF7KjPr4zwlFNwpwVSBBD3ETlE81mB5SwlS5yS7dzZ1fZAioYz3O01HZZt21i0oWMtdI9sr+jqNSTQXqazgeGLqPr/CbdtYmwB7zKbJpE8OOhMoPcDW9FMlI5jBekh3abyLtTKgzht7hSHK/kXSPELpsqlSPvH4jxYO1D55GLJ8ccbgzaECOVk4rYs237ZgB/mgHiABcPXSG2S/bhPfga0UqUxrqIu5xixULJb/lNeKQZ0PnEQm+yu8xAmEt4ntKW9YRqnZ6BZIhGzzl0A+U0cwg219WKeJnJWRNdBqIdq7dmo6Bz2+xT4t7DTEwwJpAoKkM7CgLa4evf4I7ZTg9hfTTNYdhFoqqIxTEMrCOZzofz3YNQPNzBPdzOJEbaSFWf5nIWdXbXfUQvMZE2D4hg6/9yA4GsNH7jEI7rvRHFsOqPMxZXvu1O03iOy3jQ4Jrq2Fm8hwYyWFwjvAuaKtLU68hipBEPKFPb46E+EuAXI2tT0VRmhQ/yLOc1gZzUaTFr6EJWps5VPElfFvA98dPkGyIarWzeTEVTSU9z9uu6iEemmLEYipeZKtGxZQ2j9S9Y1ijafJ4e4n1OZ/2TzsDsheuDtGSnw+Dzgz1uqjXbqK1TfAPHM6kjQCPLyprzPmfEXorIvjn2vaFpDOUXWrGNDiVigWXyYCn+bSsrC3r3Vcn2cBrvRMR3VpPDRkpTpgABEUj+MDexblumabDZsZJuKY2PsQZWVNHM8Az4azI0JZo1g/9yI53VdaCqDg7LxAZWxDeJRSJ80klw001w8cUp1cvO97iN1tSQJVRYfnGHg9STTh0ZDodCTX0TebBkcpKHXdFABjfxMCgKLfEOK/pbDaymNAy77p0dXdrV8yZjadtcdDTdaMD5ir/YM888A7rudDp5eKBOz/qc3zmY9bYVWSzmhftwEh8Lva59QM+We7gg7V0geQ/WQ/d467mZGUS2AXpkw1e894eYYJss9mwbuBScXF0RNCZyD/M3N/M6NSn41UVTdOqi1kRkD66PTTK4YM9jVBk8WNWN3mnO2+qLGMer9O1U5TKsk3JExohnA/y5IodOrGPzzvjKoXuqhEFXVpvLVVdBb59cDDPItEG0g0zq6N16N1dpz6ApUcK6qIPcplrb2E5QDBhYUtOB8wYsZVHOIXw8rz3fcyTb9nqzp/uhkTS24YwZ2k2R50uSC5oMg29nAx1EfJ+iQDjMC43jAGsR4Ze0Ulmfzm6KaI5YdeYHrcb6yR5BXRLQrKDWtYasUgc2JHweB/O/6s4ENX/zaAPbavJ5hXGEKhXPAGovRHSVt4wsZRBttCYq2sdRfMMTXM0Tz7rb6KnzJnLWb9clZWChaaDrFKgh/sGLHFy6jTN5n+t4zFFse4X49vGMf7OeHvxdMzZ3pJxiZmcd7vgtqgiR40//KGEzboHjyoGHu47tK7aWpfM/rmIvBWi6mwdLds/xPsK7XghgXCdmAn3zTZg2LblrSK2+6jqN23u5T1pMH8orvcckybRuR1GeM17ondmdedzGMJ/Knonk90qnPkFJA8ZLnBHqx2cVw82gdPDvu9a9tpKhx/fUkZ4ODz2Ep7Ubr1ox43XZhz/D4MHQ0s1vVcoGsqjj12rLSzyg3S5XuVTu68VfeAZTGMW3cPbZHMBS+nksYv5WA2sKZyUuFAO7/pUdzYp1xvI2BTmiMb61WKw87s9/MOE1HSsdj5VFUUCQl9m5n2KxgxZ8yknUNezbKxzZfQsvZFwFwNDSzVyT9WLCc26a6D1hyhgSe2OYEx3A1grRmP85ZBHdbcG+yaKsykq9HcdrVNc6DaxJTGTRFvfKLVnIulw7yLkaEVlV1r2CuZbxKQ1ROSnaeZGK073jHZ5eN5rLDIFuLcZwTyqrxcPAitWN8z1VBoHq8OSTsGiRdzm5UouEdXqziAu1N00CWk2JsgchPNnOoBjYFS0yWbUB1tS1pSCjlq6BdeyszEr+2Wx4jQtdLOoH85unBSLbWq8MK25RURDZkJEIExofAOAnDrN+88Cfq4MM4g/uNjzbA/uF2b1VDNZy9aipTWNkttMmqJriO0EV5LndLsv3tuJiXqFsb8DMJrq9uX/oQOz9QBguW2pE/2jLZq7+aBTB4918d2EC1EXSTK9MKes5xofscnVZAa9xAVGjTrL9W2npRl18ts086x1TVg2ofL+hMy9wCX00Z1DylOgYGsigusb7bWb38+aD2hdU1AojxS6VY3qwNIuiIl42bywkEedkbuJKnjK1IseOhVPiO5tdUDSVgKabQf92/Lm2wOMMp2H3jiGtlJMVQ4lh7CCMNBZSyXjbJW7kYXKoYgvJSRdF0NhIO57ecw73b78YTbPRdCRYhapEWaN3ilumqZBts72xoFJL/IlDy4zMyZk1Fodchha775rafYfkuoPyzezCDh2sbeIY/K0GVpPg51qVx419r4yA6HBSdDYeEnmwZKCiDGr1wuQaYRTtaxahPUZqZMd13JabRNAucDRfM4YPHMekJ8juqdKImlI52WmNpiszFQ/Wul3O2KKaOuubfLKwAwDlValJH9gh32FhhtMzp6nWQHIm7znidzKp4zQ+5Ji+IvMwoPhn4ZjHFdH5GiOqKSP0PqfTlZVJrQpnrGzJSL6jKmTVS267TntqC4895nMi9pVQ/HvYtwg1IoSjGlt2ZzFTH4qmRs1MV6lpN1H7DyfzkXn+3a2fNRknTdmOFFO6fuRw5jDYcWwU33HVNnfm75y1giajxsZ/owZUOoVX8PqvXcwJpM7Y4vD1VhqTyDwGsItmlJTYUr+NbYeAFmU6oziRTygg+SBqeZ3B/E5Bvs5TBbe7ynRiDUf2d8cN/bBZGAp7QipPcyXzGMC/Fp6N/t33vvdzeYIUOLzDesAwjH0mKinxIb0yAcK+BuUva1oxjtdo1AOmFiFgGuDmNVMwsLw8WKo0amPG4d90Ycjt9mEuP+KIpG+bNOyZpps2G2OdTYsQQPWZ6PyQpojBcRF9eZorOTlJ7isvqCpw0EHm4m8oM52/ecDLmxqbpOMWpk++P4/jVeZxIEXsTqp8eWU6pWzkm9phqIpu0SoQTbjNKaRy/oq9Yasdn8kUIL43TbLW90pbxYH8CTR9y1rGYA3Ndcd62rfO19GRxbjjKv/fDKy7Or0W9/cbmUwxZb4xVaHaNKZxCruNdtMsR0zOh2YkXr04Ej2MwW4WB/MFQh/wvZoTE15jWaSrca19M7DCBKgKZ4o5MJp4lSDhZTHLOI+2QUs+QJVyMwC6zgD+pAU76NMtSZcxcGAX57arfb5+9mOxlTT1B+fAngoK88Qgd2Jn5ypBU3Vapu1GIyxibmwdPI1GhvA7LQrECtTuwfLbZt1aV8R2SvhhYbFDbqc/85PKzCmryuQHRtJQZ11fvoueXRq59lr/cy0PVoI4BrlF2Kgziun0ZSFT53fiqMbPHc8oaU4qwjmOFbuqR/llXWvuqb/Z3NpNJM8Ti1UxckASP9e4s1dlmxuVPcs8pqgKW/USQjUB1wTiN+HbjzejHC2gmIaR/DKaqqOj8hknpjTJyOt0YTV5QYUczdrGkMZpZ9Z4TiAVhjh1OKxwHY8KrrxWrWCkfxyWlwerbZEIct9FczaWeW+PqKpONKpQkBvmbN4hlypzNe66hzHpVkTzeJ7LeOdXkSlXT6ZnuWTgVW9Ngx20YnKDU/x7qCq+d15m09LfmwJ7G9lVLqltnKECUTSXFy8eDg3M3ud6SYJhRVNhwgSKVBGwLuME7fWLhYwBA8vzEusVlN9wJd3ozGreaeb8FvFQyF66sjohfYJ5L0nToAdQFN1k8lfQE85NXrF6+wuyXg9zExDf1pMG1tD0OdzJ3QAs2+btQUx4X5lM5xFbNpUxfM2xAL78j/9vBlawj5s12Y531bGU08w3XmJTWRanMY3la0Rsi/Q6TQ4l5gjp0UZsIX1qI+w8mN8Zbbjjp9cNTXgNMwbIJwg/Wbwzrwd5DeU0NIgJfF00/nuRaCTNtVrNzhCW1MHtLF0tjYjpZfluRVse43qChBxBg4nQp8ip02U3sBqqhYFTXdX0jmU24pisnRs7fMj4FoLhOETQ0RbsmTvg9GCtCXmzSEsjSlVtSRJovMvZfDU4cdKFSdza4N4iTOTJTNaD1bYt1JLJUX13MJvBtNS3mUHrUrw5jQaTj2tn1CmerBLltw0lPFx3lRmgmlRMTxLwGjzlcx8wqrV1LKCK7xPDg/UqF5IX9PHexBpeiuKKf7Bn4afipZCGw9uMdaTSF1NmxiyN51nPCUTJFR4aPTOLR2cMYvZbiSlcYhddmdmqKSD/DFewcIM3h5ZQdVDo1LqOdziXBfRnPgd6lo0VOK+q8e7PqfRzTw1F4zXfV++UkjpEnU17NlCcIxZqOVSZRM1/Fez1kzGKhbmNXMBrFBeIPnkcn7vGxXg4P3tq4kIJ8BKC7FXSv5Tm7WYoM+nAerNMIkUQgKt5CoCyPCdljPyGm2nHe5zFoVmJExYkHuYGDuNH/pWZmGgWrL4iPaO5GQ30YBkrcWdgAnzDUTzC9YCIv3wlGp8GoqmIHTfierAMr2Q0ipkAtHZXatI8EulZGgewhCwlQWyZD/5WA+tKnqIzq8mmOiHLtDkZJqJpMNypctDcEG7rWd6Onm0rqSWT0Xzp+Xsy7X28ygAAIABJREFUZJ+yzL56sOoNArOyMnj01yGM3P1+UufVkO3g8AE4vE85IfJob1Oy12werHlbxGopVakcfd16x98FQZu3yPhO4ajGWN5MyBHkhY5tGviUE+ha4AxEPKbFPA7Pm0uEADczmc07rISC3spS3mIsK7aLyUpTogxGUAL47YjJuiqaaum18TCPMMEl6eKFWGoQsBFJJ8qwsWkRxoOappFJPaoeYSbD2EFLokbyg6x/I9Z27Otc4Fixv1k+2lQEkPETqQqrtvf5hl5NxrxHkeVpUVSFgBIhHFYcBla8dmePiRvPM1RWq1ZmcI4YHE/pvIjhBpO7JPocmLWERLDLWjSEVd6uFozq9/FvM+1/DFP5cVGx69zTJ4nYzi7HdIZhw+DccxPeLxaBNIUNlTaGfb+oB0VkgcpG8gC3+CpeSAUF6RF1pfab5VLwYMXGYNkCx2ONa7nASTeaYjW5SVFm7Au8tAhX/rSNWrLo2M4KVk/Fi5KXJibOZHUmvWCXygH4b8vJfMgYR7ap7zxmjDv9EPxRfUsr6D/Mue0qv2ExZQzkz5QyEj/hJH7mMN5sEJmeryXJgxUmgKLAvcO+YRkH0FH1TiY5iulcb0us2OEhFL8/UNxM4WJeMv+ON96mK8KDVRHJZTtCSq2pxLeZORrr6cDautaJC3vgbzWw0mgkg3rRCRL0ezOI2cdSNVe3BpN7qF5k6XxRl3jzXw2oZFLv0DM7k/fM7YJkgggTGYDJ4uulIgPn+ed0Y2JMriUcy1cuYktNQ/BD2VqTRtQmlSP+u5bObC1LPmZqd4Po8J9yAjoKGenW9QNGnFRUV3iT89lIch44O3QUHuM6lu6K8TxpmkOwWLW1hY8zzmQJvVm4SaxWA7ZvlqF6b1vINqeq0LEjNGMXS+jFLTyYlBViGlh2D1Y0uXYgJ6qCtAQxgjapHN1wueu6joLO8EJ3ZPyfDKTOti00v7a7SfchtwhTHVyWbcyhYvk2lw6eV9vcY8TeTV/dgRYyvk8THqxwo9ODFU9kXLN5J55jPPWNloF1zo0iQPfk7stN8doR6YJE8Ojjk2jHtnvurdSY33iAuB4f8y1Hmb/VNLgzgocdpqHrOLjfUoaqsqnXseafvnFoqk5UV4iGozQSiLvlItvinCLBLO9rYBkeiWN9FpN2KAGNCxChG6cwzViIGL/F1GM3hWyhrdlcAV5YeXjCe+wLvAys8yf34X3ONDt3KgzsAL2z1jCNU8zs1abAJLE1PmthoJJcqhyZpH7fXBphkhn/rnNWuLqIXU/yN4bwdtVJSddtthFLmW5sm/UnPhGobC9h0kR/Ny3s5Oa5sw7012PdJxh0IRLxxlvpwXq25nxuNPQLm6wsYErlxF+A/5tJqLg74d9qYMkBI4fqhMyq5uvzXfHKbCuDcM4oV6MnkZIurznJYl99nzNNrbAWgcQBgftL7Dk3U7yHgKYbIVjJtQQvfaQ91elk0MBHS6wMHk2xiAvtIsgVVclvsWytEfvXMhOMHCvl25TqSCl52In6sMZ3jKKs1plK/mdlV36qsHhp7FsEcstFfsprWk0xxVkv7WrxN9kha6ioIr4nnwqyqCWKxkNrxySsZ6zXFKBFfr2Il8mJ/93at42yjg481O/tuOVq6jXO4w3unyISLC7lBYNoVOc/3V71PKc1ljxHFAXdIBqVA/UF/RMQY8Ygu10xwe4lRAjwqD093KNtykGvqj6Nl/gH/ZiPqgkPViTiDOK9hBepq09ui1BmhR14IHTuZrRVu1ROoWBw1poltx2UhYiBUjWFI7J+5wCWMIdBJt0D7DOlnS8iUYV/XGHRePjdp0NuGZ0yt/Db4hzSaWQJvXyNBWmQSg9IuNG7/fXqHmYlXfmIxClxiqbSm8UUsIdpnGZsEYr3HVuPV42toM7NbJqMXbumlHyQKhxiz5JoFMv4APiaYwU/YZJ4vfZ0TuUjB89UqniKqxjLm6YXbW5dL3JjpLD8DIJtCM9IrJFmh9z+3EMRF/Iad+1JPgZLzlPpSiM38DB9n7sqbnl7HJ6iCANrBsOYqN/jWf58XudmROZ+VRW8NjsFyYgUoKuaqSQCjinIhcEZwpNqXxSUFob8iseHofiheFho3VjBjUwGIJsaCj3avtnVjz76aPr27Uv//v0ZPnw48+aJfd45c+YwdOhQ+vXrR//+/fn+e//smURYygEsoTchgpw3IL4WUbEWv6OaBpYxsLQvFHFVyajGO1wZHhiaxB73CVnfU0wZhUX7ZmD1aisGqAN6RJIWewZYTG+zc0qs3i48TVtDlot5Q7vh3D1cZJw1lQcrP0cMHCpReOstR+vOD4iJ6+CsBSymF8t99urjobJOdJztVU7X+KRVZ3HHjivMv+2fS24Jy+e4pPXnJtGoX8bIYS2XWdcxVkQyIPLH3R7M2jHw2iLs3aGKdziXFi38zhJIS1fowAYyVTcbuh0RNN7iPP79jkWUJYSGbatJG/qywBGP1CttJfq336LqEcYM3U4YjcJMb960ZPAQN5v/79ViZFeKRuEEPmc+B5KeqaIRJRwWlA+eJ8Qg1kMki/35J5xqKGRsr80XpI1ARBEGdrJbYCYPl6qgKVE20p6xvMXnNlWEfV0s2SEDn0G01dyg1Xj97nP/QVN5sfMD6MaC6C3OYxfeDcvccjZiACPGOc/GCBRnZqt0ZbXJUxYXqupMnlFVTuyznqHMdHmwZn5dw8OXrOCAVs7F6Aq6swG3JM3+QPMWiqlXKg3KncaW1NK1mb7nxUOtIsYyO9VJqqggnzABc06aWjnK8fvt3Eu7VvGTAUzpL48paVCvGq7gf4DQIkx2lwOgL8LrHVCMjNSs+IakNLDO401uaDuFt5YPZAQzeCx6tWf5NzmfycYYkZODw6O5PxGqTXN4BP3omwDeL7mWfzOJ0QGLhLipY6CuatSTySvl7sQ3e1/RfTynZi2nTJnCwoULmT9/PhMmTGDcuHHous6pp57K3XffzYIFC5gyZQrjxo2jtrZplX2D85nIPTSQ4asXJ/HP4BQC+DfKWCb3U/uKPfREWVoAjBoFRx/tyyYr6QHiBW1mq7UUU77PQe4yhqGhzvBgJXne+5zpOrarUgwye2ut1bKiqabFYTewUtnalJliD3ELn8x3Dp7ZATFwF6t76cNierLcdX4i7KoVhtWyKmf8nKbqJrEmOD1YR9QazODykKaxySA89JPKOayFqJuiqYSqNdbRie0GoWYymXamq77RZsGZQVgJgwrFfxNJ5WSI57Vv/wrWBW8DS8nMZIFtcsgJh0xPsaoppv5hU/A7gx1GvJcHSw6o9gxHFIU2gR3kaHWMxemx89vyLymBy226Yl5GyENzDuchg+m9UREdZ8uO5Eb0BkMgXQ2oaGqUKvKoJOik99iPBlaJTbhc0ZwizPHY7IlGk9rO6Nu5mqe5nLurhUh52BgqWxXGGFKaRi2ZVCVBNOoysBSFTi2rGc2XLi61fqOac8Pz3V3aey3YRXuDo21/I5Ch0ccwGOQipxtCp7Kp4/DWiDDQ7jCyzZqC2ISb76qcWYxbaU37Vt4G7po18Mjlq2hhbFF6SBlCIODYak9Fi/CrtBOZywAU4E8GOOYGL6jpAc5gChfxMsc3+531IRE7+FfK8ySD2AzXeOO1kp7GJCZyoG07NFUuQPNamky0cX8Ylajp0JnOkezyiD8zzyoosNIYKyoqUBSF8vJydu3axahRwiLv1q0bBQUFfPll4v18L7RihxkImYiXIooW96PKDiW3v2TGVFJbVbm58PXXniywICaLDqxj9lz/wXtS4SPMp39KweJeSN8pBqOGuYuEBysFErlY2L0JJjTNRspnHU7FwKq1cRzFpqueXiLIQUdkzUmtsjYoXYXnST/Iyb2kqTqNNhVz++S8WRdxOXJSXNVQahpYH24c5HmfnLQGRvMFRcEw9eHkO6zE8P6VVJNNx9YWxUU0ohNG8xR5taO8QmTl3L/k5LjltAzxvPYBdXC7bVyb8RynznXzUDVk5LIEy9sVUTQz0LcxqnE27zBzfeLEDy8cjKUjuIwefNvTzUNxQKnYChlYspUj+F7E8Kgqf7Q/jRsGiK3a6mde5yXEYiaecXEl/+NaI2DWa8LUVEE0uDO9LdeX/QuAq86vcJWLB1VTmFHrLZWzz5x2Ntj1CmOv6ztkpKBF2KF1A5fzLD80CsLSwowaLuNZOtzhDGIuD6WRTa2vlEcsmvdtTQ05ZFIrKuojlSOxq8ZpuK2ka5O82ElBVWnJDnKo4pAeYodD0pU01The1ShiRoOEhLB6E0IdltODDziD3SEjbME4noPYVZnKab67JZ06Qb9ulsNC8Spn2xq3Xz8ZFKoVDGAeDaTxM4fx1aL4hKNKQGMKZwmZLEUxebD+3w2smBCChngOWU3qB1qHKmq8RdMTwuis44vdyWdL6G0y7D+lXssTuLdfHRbEBRdcwA8/iEHxiy++oFmzZpSUlDBlyhTOPPNM5syZw4oVK1i/fr1nXerr66mvtyafUCjk+K/6669Eb/sdfoJpC9pxRsh/X7S1tpWj+JZQyM14DKBqVTzALbQrOJJQKERa2JDMQTHvlxqCZl1LAjtZT0c2pAUo9LnWivquvMK13FVWRUOm83lTwd7N4pz183bR2JiJSjTJ61j1lWhoFO+gMRwxj0/cdRt95mucGQrRGLYsrOramqTru3GvteppaGxwnHdss1noKEQyrFiWVN9D8+YKkMfIo+sJhSxRXIWIw4NVXVNFRsggrDQ6fGNjPaFQiIuW32SmEpfXZXnWIUANjzCBdiX/Y1d9DTg0/NztNRZaYx051FJVWUHUKDN9Zi5jCLN87RpKgv7PvbNMPNfc3aVx30+0IQxkmFsfAENarWB49pOcFD3cPKYSIYpGx6ztLKuwBs3NkVZM5DZG8DO/LLmH9xjNkI2f0Hcf+gRAD1YQVvNdda+uFVlY4XADPyISTJ4MhchVFBqrqvmKk+lZZsULVlZVEvCIw4pW1lBMOQMMYsDK6iqUkHMVpisRAoRppu0m0mgQskbd7dj7OwbN61ZFLR6q3boVw1VXX9fEscON92yqFZXVVcYEG6Qf8yltUe55nwfnnMiS9ecwvsa5Q+BVVqurIwexoJzAf/lHz21kfPFfalq/5yi/eYcYE2rISerZThtTz/8WXsF1PEYoFGLj5kwaSOf1gqsJhV5wlf96ueXhDIVCdGclABX76T3av2VDdZg3OZ8gFajhPYRCIVPzsbZOtoMgw/mZUCg5TcGAoStqDy1JtQ1IlvSd5bUEQiF0Y2zKp4JqctlLIWV76kj3uW5jxJozIxF3G1y4MMCzXG7+raAnXcc8VUXBSlCJHb9d0HWCwHz6UV/RhWiRFR7ifZ57HvJCorE1ERrqqsHGCbdzZxXRIu8ElzHrnmM6hzIu8hr57OUqnuLQNoEm3zvcYwj1kya5zj+cuRSyh1BoFJ3vGEPbRx7hmthb6B549dVX9dGjR+u6ruvz58/XjznmGL1///762LFj9ZEjR+qPP/6412n6nXfeqSN4AX3/DeEEHXR9OLfHLfeqMEB9f29r/H608ffhjNdB1x/m0oR18P6nG//QH2KMDrqeR4Fv+Uc5SwddzyG7ifcT/+5moA66fhX99bM5R7+U+5M6T6PRrK/8N5CjddD1EdxlHuvMYv0wHtEB/Tpa6a3ZrIOut6ZD0nU8gYPN93MwJzp++9j4YXXMO9wf/4byml7MDvO6xeSZvzUzjg/mBB3Q+/K9We5ixnte7yxu0IPs1QeBHiBoq6+uD+C7hPU5xCjc03bsII7TQdebUxL33Ba00UHXh/BBCm1R14/hS/1W0HeCPpip5vER/Kj35id9OK87yndiuflHf07WQddHcXMTv4F1XR30mR5lhtFBB10/nyMc338R6E+g6qDrh3CRPpkbjN8Uz3s1p50Out6KrTroega5rjKHcq9eyjq9CvQDmaGDrrejRUrPkkeO3oM/zb8LKTP/vw/D9lvbLaTc8T4APY8K/RGu0w/zOWc4/9O7M1fvy+E66PqJfKz3ZIln2UMp0KczUm/HBv1GHtIfNG52XEy5ZrR31SPevwmgP8UVega1uuiDF+mg6xt9vttwro+5/v4dA+z/8sk2rz/aOPYGY3XQ9Y501wG9HRv0idyd9DUH87kOut6J1fojXKfPo1/K9UqjXgddb0NrHdB7M0sHXS9lnVnfAxjoe35PDtFB15fSQz/G4/fuxhxxuDHGdWFh0nW7CPSFoL/PIB10/VBOT3hOGPRT+VAfxBf6SK7VQdcLKPcp/9d9b/u/HBQddP1xrtbfYKzeIk7Zrsw369WcHQ47YX/+G8U3+pm86zpeUVFh2kSee2AXXngh48ePp7y8nH79+vHVV5YeVs+ePenVq5fXadx2221MmDDB/DsUCtGuXTs2bdpEMCgs3en3z2fMg3DYiCP47NObPK8DQH09lVu2UNGpk+fPyrZt0KMH095/n/DRR/PMuX/w4+dQnK1SsS21bQOAfIP7r6Kigi/73AMbYcnSJeS38ZaC+GfrGVANq1evJpwRcT1nslh85mTu/BrOP+ss+rXYSuCrV5j8R+L635z/InMYxA8VVtkf/7uIk++BoYcO49MvxfFhLbbTq0tfPvm1goz//IeVD8xnK234+ptvaD8kOc6StHfeIXu8+P8bbriBo+940/wt84Yb4MUXaXv55UiN1YqK1N+/F67qP59l6wOgC9mJL9cuQC8WXEWDCnegRnXe/t8/aH7eW5zacQ1SDWJAv348+rO7Ds8d/jGfz1P5/vvvCXXuR5tSEYA6iYm0Lgjw8aJNcb/jpk8WceH5q/ngw960HSUyNb+9bwGnPwS//voLLXq5eZQktm0M06MPtBg6jIov4r+f4vxGwkbGTBSVa268j6qX3qckoxUyNOt4Puec4RsIZAW4+RsRbArwcN4kiirLeYFLuO3WGznrAThsxOF8+Kl7ezER8m18mEOZycmlf1Kx8EJHmfUfzKffP+C08y/hjTfEsYqKCi5v/zO9u1TDXLjwggsY//rhAOzdu9dbVHnRbnoMg+2UMI/+lG5bi5btjBd58KR53P9TB25Ne5oDc3aQsXcW3yycjl5a6ijnNe7IZ1m7dgXvDn2Fq7cJAs8DAqv5JSy+26yvbidyyCEpvycv5Odb7Uf2h9L8CGECfP7550SGDXOdc+uhc/llTQ73//s+TphoSeV49adfnl3OqFsGo4i8Ua6+/ErKn3mHt95+HvV4i3pi66I99BzmrEc8pD/9NC/ctgUFnYqKCt67+g9+eR1atGxDxUo359izY/9gxmfW9e3j6P6A/Vum1UIrQ2Tg3oe/4N1LhnJw/mYA3n1rCj1O6EC//HLfd+aFczstgXJBXTPBEF6uqEjRA5+vA/DD99/RcmBrji5ZBzXQg+VsoAMAzz37DH3P8d46nfvWakZeIbinPpw6lciRRzp+X/ThWobZwoWzMjKo2Jna+y3pfwSsgyuuuIIv//NS3LKF+VBJkGOLfuOoQ47l+8+FjFPFXvc9k/3eXn0yJdTUkF8CWdRyHm9x8sqV6D4hPoe13AJ1QsvziPRfqFy2hvf3iWfFG6flzzb7CVjPaEcAxKBXU1ND69bC3fvRRx9RXFxMUVER27Zto6REBAK/8MIL5OTkMNJHJiIjI4OMDHcQXTAYNF9qTo7YT1PVQOIX3dybkRsgUlXLHA6iU30uxcEgAS1AHiHGpb0DweTV1CVe5UL2UEgw+Bhz6kXQcH5+kGDQ28Ba2CDSUQsK82kICDeq/TmTRSBDvI9MTSEjLQ00LalryMHXXrYgKFymzXIazeOauhUw3nV6OofyK19wPN06Z5GebF1zc8mgjnoyyczMcNbvwgvhxRfJuO0208BqUgfyQFpAoYu6js2RWgYyl7xgT5DtSFnPSKbTuV1bCAYdLN9pqncdVlS1p4o8VmxpRc/BYmuoB8s5im/IVK136fcd66IFvM6FXFu/wvw9LSDeeV5ebtznzuwmFFZufqAliV6PRp1pYHVlFS/NO5QnKy5heInFIr6BUtoFl0IgwGi+NA2sZuxmD0U8yC1MzBLXSKqvJcCvDEXdk8vNMdfpe9Fwlm2fSvcbxoBhYAWDQRY3dCOvUigAZGZarny74WFHTaHFIdOfBVCUb2WAGMjMEuvBFxvHcYH6OWEC5OXn4/dCvb5js+b5tErfa/7dLW0tv4SH0IVV5OTl+V5rXyDrsJQSZjOYev00ijzuk5amEdFVWhUHGMYMcqh29XGJ3FyxVa6jMpmbKZr3EbfxFF+smsNoW/nqQmubNZk28PGa3lzDraTRQDCYRZZh5E6pPZnzPc4vNIbHEfxEMHhYSvdKBcFgkMwcq5Ov2V7MwGCQZQhOs6yMTILBIOsJsoReSd+/NKecWC7XVOtezFa20docA4rThLRYPxaYUio5uTm+1w3mizi2CBo5ubmuNih/DxnbcZNaPUUw+ERKddwdEGOBa/z2gGbQDWiqQlamOE9Bj3tesu+sKXMkAIZd8ToXcAkvkte6tS9Xg6qIcedUpvFo/n+g087U75cEvkPEpr8b53FUENbnKaecQp8+fejXrx9PPfUUn332GYqi8Pzzz9OtWze6du3Kp59+yrRp01D2IbA7mCtiMSQZWFNR26AxmDl8O09YpnpUp5Ig7zSc1qTrXcjrXMfjAPxQKYJg4wVOmkSj+5hF+MNO4Q18/M/hNIRVB2lkPHhpEbYqFqlEA0ssXiRV0TEyuZmxoT1vcy4Z1MVNc3WhbVvWIjyJrncybJjwxsZY7vsDp3acz2WBlyx+EVsAqKZEHMSVAZsw9Iwyby4WXcZZKDbKBTTe4Hz+1/6hhPWxqEHcWoSJ2kF6OmzbJl5XIixJH8AAQ1/waa7k3YU9DSZ3q8xbjBUpfOGwk4XeyHCYw2CTJLLJJHsx8Oz2ikKPf52GkuE0hjQlSmNENc9rxTbuYaLvtWOzhLxuJjmZFHSiisp2WvlmjPpCVR0JCcdkzQDgWcbvc8JKIlSQzyl8zJL13hODpolki4FdQ8xgBFs6H+YrOB9LT7ElJEb52CxN13tNgJARUCqDquV9JlTe5Vm+baFIcuhhZA9//DG8+mpKt0waTqJRZ6OWmc6H8osnH5EfRjZ3k/emimc1Edws3/3AnOW0ZZMZHwbxEyjkNxrFdP5c7Z6t5XP/yUDe53ROKvg55Tq+Uylk4RLk4oj7SZJvRTe//yc53goGj3Id1/NIyvVJGUbg+kyGC1bdOERYFjdjaoolfwVUgNLSUmbPns2iRYtYsGAB06dPp39/ESR45513snLlSlatWsUnn3zicoGlikE9hHXfNm/fXMixNA1yElka3vcMFvlJ4k2a+4toVDdmwZ01OVz7wykcuv6tpM7LuehM9LbOb1Haso4lHMBBLa00aSGVI+r4zepOLKWXI6U4KRx2GAHC9GYRwRz/9E+7evz+wAkdl3Cx8gpL6M0TXEt1rfU9cpRavuA4tu8RKxtN1U2jpDbiHfxoSuWoFkv4W4zlO44kmxrPc+yINbAemVTD+Y8caFxz/3XkzmkbzQkLYMmuliK/yai/RpgKCnhl0yhe3nAkM7Gstpfrx5r/LxdCqUrlxOLKPmJAT4V/J6BEaQxb5IkaYnvMD/bJ8z7+RTjq7nsHti836hHll+r+bKYdG7emRryjozCrRnio7+YODsgQ9C6j+I7Fa71FmPcF52L153hcRyDkbyK6an6wzz6DrVt9ysZkVdnfdbxyiWBnDQdrDPTLrpP9SLbBk04STu2/AnbJIznuH4DYtpSi76kyuUvC4n2RypEGuzSi/tnsY6ZxqsnLB8Qdb7OyFQI0Uk4zdle6s93s3/B0PmwSI+7Le4XjQU1inNIM6hIFGHfoSqrI4eC0uZ5lr+NxHuGGlOuTMjSNU5kqFAk86GrsUP4mA2si9/AUV8Yt87cyuYPVGJvKzSMhrf5YA+udcPIsvg588QW8KWKLrIk4jgfL+O++erCuGCAkP45rvcAQ9U0O979cwuJNToXwjEyFA1hGToblHdQU3Zxg5TsKk0ZlZWr1bMEuFtGX4b39V4czGe47EDcJzz3Hpjpr79y+Cny94Bq20NYUzg1oFieJn8dGrt5U1eqjuyliLG+zoyExI3isUX/DxGwq64UxF098NGUEAi7vpAJ0yCkT9zcMlY+3D2Ha9kP4hqPNctPCloC5bL/76sGy1DLiXyjLZqQG1IjpwVI1xdzS9r2HzdNyO/d5tqPRfbfwCNejoNM+3ZLlSQXhqMrsGuE1nsAjzGm0ss1CtU1M5Y4De3baLQbjteLjzVBVRXCsnS+2e7NzFIzoDBdkW/yUE8iklnDE23gLZIq20srGyxUP0sDqpyx03MfXwDLKL8U7Lnd/QkmzjGnZB6UxZc4D6ZkoXbu6T/bBkKJVvM05ZFHLQP7gAxIrOsQiqlgktgDtM3dyEHN52jb5xvNgde8aZYWRAe3Vnu2C3Qvpw4xqbwHweMjRRGZqh5aJOSwDhuSLquqkZyjkULNfF5BNgiIoNJIxnuVC8Cmupv0ub8Nwf+CeD3px5fT4O2b/fwZWCqsML8gB2ZKBEce36E0TZWT0aBgrVv/5AcFfEteDZRMO3hcE83QUogT0RnRd3yceLEaMgFtugZus5AFVtbYI7VxP1Qkk8WJxJu/xMhf9dXoiHniKKx2khfZ3HesNOLbNYk7mYwDGtvnR83pyMSO8QVBEOS0Q+/Nvlo9OWB9zdR/DUzSUmaTtx7n5voabeI+zzb8zqENVotzVd6qzPqpOOKrQhi3mMbsRUxQUA+Wo0qbpg1WSSzXZpqBzosXgY1xHGzabdWuMWF6VDXTgPm73PdfFFeU1oBuEiwowoeQdcV6KzVHVFM4q/o4M6lhEH6oVK8byr2ja0XZWAP6nnGTcx/tF5mWFCRLiu529acU2tu2MY5Aahk8J22jOLhrCTmUDiZygxneMdJB5hSLLAAAgAElEQVTRxoMUkf4ubbTjPn4EznXh1LYg9wm2D+RnYP3ecCAvrRqR9CXb5+5mNF/SQDoH8xtjmJr4pBj8pg/hYGYhqSS/DQ2hUGbcGJA8jZ6w8Vx59bGMbOsdn8ZUJmxO3WNUoFVxIp/Qv1PiAH5JGqwYdfudwQ7PuB1PchWPcH3K9WkK4vGx2dHcFmO5P9f7LowZAzEJCbH42w2sZZtyKaaM/i2SW1H5QRo/UiJCUuHvDw/KqcUzCNBIZpb/tU4Lfgfsh62h9HRTGDeqK01mnAWEq+GBBxxBklP73s0jfV8DcGgRpupBnM1gEYcVZ5Ytp4hthnr5/sDVPOX421OL0Hj/l/b4mUwEJ5Pf/nzXgjLjZEvHLK2dcBF8UnGY5zle97fHYIHw3AXz919Pfqr+n46/G0kTos+qczLTVJ1IVHUYVa1shJL9u9WwnlLHlnEqyL36YrIvu8D0YCVqm5fyApsNsteAEkXVo/yHW+nfMXE4QFq200L16lcNehp7KERVoua7SLX/KZpKQInQQDrH8hXf1x5i+23/fcMDDT4vL++hX51vP3IWz3Mpl/MMO2gVl7zWHkMYIGwZszHXDmRojOQHkyk8EWScm4xt69elmjxC5CjeK7IOzcTxfPZ6/r6/Ie8jx/3FBsnu7oomGnqXXEJ3VrCKbiidO8Gq1Bcj5RSho5iepllVfdiL5REfxysU5MaRyrExtXsZ+W3bwljE7soaujRpER5QjS36JFYRGlHas4EzW89k9sZWHMzv3Fx9h2fZa3iSG/6OGCzgE07mc05IWO7TnrdwMw/SjRX/7wSpf7uB1RhRKadZUmzF8aAENBSiRIzdsEsHz2ck3/Fy4LL4JyaBQIC42xkgBKHTqd93AystjQBhwo26IdK7f9Eyp4oiTUxwDi3CFA2s7bTiPm5n1rIC3zLNKKd1klsRTYHdy3F9xV3OY4GAYNYHIhf9w/P8oa3XAdYKbQ9FzAuLAToZBYDYLcKe2PQ096P7QyMimLQNRNFQ0d3bP5pORFfYZsj95LOXPKwVasaAXpSykfSxZzStIk88Ac8+a2ZoptI2NVVH1cPcyoMc0L4qYfmMnAA3DLFi+Lxe50szuzOJiSLIPSZGKFkoqoKm6uiohMh3JEckE5+SLNIN7b+SDPeWuu+YEQhwBu+zytBbjLet1LKFzr+4j5e5mHV0osHwJLneW4rtMpAm7ikJfju1a2Q8z/rGKEoj0JFo8RfiKIS+nJQGur7fDwD0HHOAWcYnyd0bxxxDQIlyLF9y5eA/oIt3UkE8aFIyxVh8fh8a6Pi9kD0U5vgbWNvL00yFE88dkX1gcjfPUWAXzU1PZzwclL6QW3mAc9rNZOOePAAa9f2/ff6XQVV5kFs5nQ9Sisf7S6ryf+2dd5wTZfrAv5NMku2wBXZZlt6XDiIgItgVFXvvDcupp97ZzlPAhmfDO+XO7tl/2D0Vz4roqYgoRar0Ir3tsj3l/f0xmUmym2wmycwmYef7+ewHkkzeeTLvzPs+7/M+paVPqK28En0eZVmJpPMEHIy+5CjO+/cxzX9PB/bLL0FgQ8iRb6rz82exmEGJO9H166coWDlt8YnY6kzpwh9pBuALiriK5AgeCXVCq3WbVM1TB8GDzxJ/MIN6+at8WexESevxv1/CW7AyHYqjfoYc8FHbuFW5DnpK5XQqE6ykN6P7KOb/ZfQPDHwGOlPKkjdkQLXj4eSsz/nb0tDVm7JFaNMm5ArakkvAuW6/o4A//0mwPHNYQvJcNnQBr3I+/yp/otnj/szDnMY7AHw28i7+r+9U5QNJ4u/cEKI0NkaS4OIjN3MI32mvG6NO/nOyJvD4ViVTejwWrDn7Az4swUYiI/1MRvrLDI3IX93ks4g6jywzkf/okqe4GO7nr3zkX9G7qOcEPqKwTWh0tuLXKejERl1yq1l2hnp/0mTyYUOK4MhX71XGgwrahP3caNTnYkL/DQBcetCv/LfkEu2iejzw+eeRvh0eu+RlBD/Rt1Cfla8xy0UffuJg6t2q+4uCasWczs3U1kXuS59NpsZfKzLsMNJIwYpnl2OnJ5/5jODLxZFTH6m81e5aruEpkKQgS2mLqwrxYwv4DSbZc6zlr5q6Mpr7e4Jh/TYb1/EkA0r8SUyEgKIizY8qEXocXEh5efPH5Jdla2UhEuLUU2lDBbYunRBCiilSSw/Pbj6eF9eNB0ItWKK9viSjKupKIJnOjsHWCk0ev9J1ww/n8hXKfnikKKYB7bbzHWPoURqY6E85SrGu6FGwHBl2erOKLEdgNfo+J1PCVmrqDLRgST7qg9J1zOAP/L3oXvY0hOZks9tFk9qQFbTheGZxNf9i7Vp49FH48svE5OnVvoLzeZ2eOduaPe4pruY9/NFKDjueBh8/M4y91U5dDqoDO1dwMS9F9M9UB/v+LGWfV7kWMRsOpdB6c2s9AR8pI2sRfoViRsmXAwqvWsC7tDj86nLmor5abTOI8qz592192JjCZF7vdy8fcRKDeoVXYtWt22gcM3SnEsXpD6TYV+uikN3cLv0t7PGLq5USWd5mIkSN5B3OoANb6NJG2SrsX7iNY3O+0z6322O/J2TJv30W5yJpma8vEBzJqQy0nYOUWndD5HE92Ik9XJ9X1Dh4g0CahHgW4ZpflZ7xW5bZQGc21xUhO0OjShuTRYzOvAlyAh9FPeaPa65HQrCXfOMNFjHS4gqWOiGs2ptgZlVJYrp8K2O7Kw6+T/84hKMq3klUPADGj4elS6M8b6+/Du/G7hDZBElis60Lfzx8Mf3abmV4zoro34mBD7aP4j/blOLHl5TP47F20xg2DEpjjAXQFJokLgmCBwctitN/B6tOpKNylzAsgsHmg3WDaEMl+yoC0XX33qxs4XiFDh8O1RkpKO9BDVlsp8RwC1YwEgJsthBH2X4sU7YIfbYQhWQLpcziBP7Ftezx+9n+/juJoTlhNT9cVAfVdsRuZ3+9k4P4mS9/ba/PQVVzYg9/nGrB8nqhg1P5ca4Mfdf9IH7iRD4E4Kne0zUn5EOHBBQgIxcPOVRxGc9zwqhAFssyNjOJpyltHz4H4Jaq0BxIzSl8bq+NlfSmihzl2XT7lf5G92HMt6XfWqI+74vW5fEXpjFGfBv28OyDzY8ebMxWSgNbIEIk/OzZJR9vcC5zt3WN6/uNF5+qNGo0HsDqjZF3DNQC7y9yCaMHNt1OV7dhx/JNSPuxcFPpmyEyNovdzuU8z5+XXoLdv6iNpGD9Tke20z4OiWKnC+u1rdTm+NWv9D/FNa3PB0sdNBLNzQOEbH9t25/Ncq/+8NyEKSyEU081pi3/77h14Cf8o+t0Y9pUm7b7tJxC/Qu3cVPRK/z8c5Mk2VFRfSyaG/QXL4b//CfixwmRS2XIBF8iK+b87h2VQqmy7I8qambFoiooqg8VBBTNbnJ0R/DqOjt3ch/L1gUKTp/P68p5DbR+2Bs5se4lHzcO9nsCVq3j+C+3HfQVT5dOZVL3gInqb9zGYBbyDWO1y5Xos7ZwRykn8R9mbtUfnfXY2pO5f/NFgDKo38z0UAUsDL9X5mLDxwe28KHPqgXrMff1jGqznEJ2kV+g77rPZwSz/cWo85x1nOaPFutSUMX1Hd6iB6sZ3Le+uSZi4lcGKj6BDz6ovSeryYEjKASNPRKai1D+faeTvqxkP3nKJNLQ4P9SgvehX8FSJybZpSjXkXKYne7PapBNdD87I1m8SXEi/2VbKR9VH55QW7LkZT3deHtN7OkPoKk1Xe2C7CDrTnM+x6oFK5tqbRER8rkrdPEXj5P7kLy1ynd1zPjHbXmBLzkKiaZ50RrT9vnHaD/t5rCfGU245NrhCL4+Q1zLzRQpKknzwfIZoFjusJWwvypgjUi2tho3qqJowGqsSdM2gdsbZHmJs309W4QDB8JJJ8XVfFQ6szFE9iL7Xo7jEzq2V1bu6lzU3D3w805lm2TN5kA5p4IiGyOYR6l9e6SvadR7ZR7gTlZsyGzymZF5sBpbsG7nb/TfOCskk3tfVtCraC+DnCu4rOtXIe8vZjCvcT4Zfn2smaTHuvh0dQ8+4iRe+V2/9/DcPX2YXalURNC7ZfP58o5M4lmO930c9nN17LjXewey3RdzwlxNwZs2TVswSBJk2RvIozLhnHaNz/ULwwNOTcDz8lWcxZvUucNPEnJQdvYStjbJ1h5McN6wu7mH69feRCY1/LAssRI1Sza35S7uU6yyBCb/4GS2IXLYYTTfcxZvJnTeWPl4ibK1+9qyofx5120JtaUuaOKN4Nas6f5FVhuHoli1C4rcLMpriHx+vwUr0v3cOBv/lSXRt8kao+Xq0vG47PYpyqvNJjSFL5KCxWWXwe23xyxPPKylB1/4y9M0h9qPp/M2b3e4wWyxmpelpU8o+xdCjSeReBhUO5d/zBkEEFOSzlTjUvfTvPh9H+VHGJyMR7YruZIA5m8r46Oq8XG1M8epBA+05BbhEQQsMzZClUO7FDrBBpJhRm6v3qU44tbbghQku51nuZJbc6PXr9RW856mA7GR20vPd5wckrQTlHs7+NaYxh3Kj66uRv7q06DjFNme4SoOPhiefhpuvTUxefQmGg1Gtvlw+wKpFEbxA8czK8p5/BFsEVap6mTvw4bdFtmqEgk1RxcjR2LvqwQGDO+0gwd7PKsoQybf3FW2PI7lM1ZtbFqvFQixXqymp5ZXKRzB2b0FNn6oHkgdmQmnqamoDTVtq9d8Es9G/I6MJ+a+iBcZZUEVskOY4MJ6XJbi0B9v9z+Yfa/yff8i68QiJcAhk1rK2MQy+tGvc2RfJTUZ7CX8m7VbmpZKU8edbzmMqdzNBcUxevED86rKQ2RsjuA8WOp99pD9LzGf0wx+5qCox9x/pBJZ6qI+uT4tJEHB6tRB2dI7rCS+5IfByJJXC9cVIj7TaSrwrfcQVm5vw1XfXcgpK6YZ2raiYCnd/PLyEdyx/cYo3whPpq2etuzF4Wy5G/bxIIffXxkU8lkdGXzHGPbXKoOTLAvasYN3BkyJ2J7rECV8WvQN1Cqs98pU0IZCaU+kr2moA6EnjMOqkdaPEbkrGMFPIe9JktCUuGK2IZD4dksPXtowTssCDfASFwd9ByZNQrNkxYtqSYllrLLbwS0CClYOVeTRfJJDdTB/mYvCft6hyG+txMvHuw6milz27NY3uVaRzSoCLgS92+7gUl5gbK9trK4r4yJeYvN240LR75/cwBOPhlottCTLESa5YAUrWs6ixttGmjKbqD9So9I6jc8Tjo10Zh3dEjqvXrqyHmisYCXGjI7T6MFqXXX6wuK/5qoFa3zhr8zkLPaTyy6K6MeKZtM/qNe4ngx2V4YpleMKKK93c29cOsPL25UFsp71u90W8Lc9uN9+VtCH6xrlJEwG45nNuX6XjOYY8coNHC7NTolahC0ec6+aKo3ITyHj1Xw7fb703SKUJS8eD1Q2ZLLfa2y+EUXBUq55IkpoH8da9tYVQP/wzq5m0InIflFT2v2TD6uOYNmGbEaibBG2oYL2rshJLW+7w4bshLFjA+/trpAZxzd8XHdhhE2QAI5M5XEJFxFkaHRlmFI5NgQ5LmXCVrdvPlgzgA85nEEs1o57imuMkyMgjiZDczhowI1iAZHtPi1iWE8tQgj4IE3iWa4M8/mYwVVMZgrPcQUZNuXB1/vMZz89HfIDyR9vHPI1zH0KpH+ww1PAK1zE7TXrdbWlh79Maerk+IpPiQSLNMk1UbCamRzkTOVi3cJDfMhJuH1ys23rRVWmbXgBuy4FawNd2UDXxE6sE3VrN1jBSnhhrfqdxfkIa9tvfsW5W/YOuvEpZ6vbplFqVclOGwsYwlAWhh1Hghdv6+iKt7pDhBLgkcmVlSTMjdN4hEOzYElKuaY+/AaixW0xTWguACYElwt7mxz+b9+57NrchdjtfcaRvFI5CdYiBHDYPKqPe1r7YCkKluR3wTL2N8iy0Fa3vgRWe39z38Q/uL5FVwRLL3kk4mdaYJt/1di/ZDfj+bpZ+XJyYPLk0ElItUp9URdNvQqyYLlD+6gL6w1VsN6rOILvGql7kiT40/A5ofLYhS6nz0TRa8G6k/sp9ZftsdvALQKT/hccxTs0XyfUHs0KGOSAfckFyoMvZess0DxpEpwZlHDVbmc9Xaisc/La9qM0Oc3kVXfzubvkIOvwEBZSWx/dgnUQ8+nGOhrc/j4KYx2byVn86s94Hg3VgjWPg/0yRb8oixbB8hbyJV6JkhJBHfcTGdM0/NGr8T7C+8mlI5sDPnNxjJFaqZwol/tEPmLSqluaPygMZZm76M1KBvXUUdReCgoYkmUWM5AvfIkFEhiB3lqEgJZAeJs3wWwFCdLiClZ+sZNfGcDh/Xck3JYsefF4A//PlIyLAmpJZMmL10vipXLCcMfBX/Fch7sApZ5YvArc156xzGFci9YirO41JOJnjQusXnzQUg7jG/71+8SYzqFOKG/WRffOlxwydn/W/WDW0t3QKMLp289r8p6EQNhDLUB2WcKDMjn0YLXmn2I0ekvl3Nn1dVb719ayXeDAzbXMoGtJna48Sc05dSuNKkkvbfjwjToEACkzzv1Pu51erOLVn/uyuraj0paRBbvDYItSv/TMsdsZhlKcdjOdmvWn0qypKJUg1vive7i5/SzeYgBLdcmoVSvwK+5F7ZXXBeyO+J1Bg6BvX13NG0ZolobExsxjV89gHd3j3iKsIpsGnAHF2Z+I7y3O4HKe09VGQMEKL4SaYmQZ/an1hffhaw7ZJnTn+lKVk7HtV7J1bwaDWdziQQzh+IZxvMqFuo4dlrcGSL5fdss7ufftyYA3J5P3QOKRB6rlB2DqYV+yrCzxLO7JwC75AkGEBrfdo6iCgbKyvBQifhfY9aIz73I6Kzc2jaAzi+AJN4/Qrb8X9ikpMrTxSJb5mBN4e8dYYkG1SkWMkglGkrSyRgC9/IlmjXbwlW1NA0BsktC26gD+98l+ZLtgKx14hzPozEZu58Em3zOCqIqPH/mHb8n83xfKd+yQLaqZwXUM6B591QyEDVEPZs6ittzHXWyki7brEq++P+3nY/DgQJICixqz1w7RcsnJLntISZrmFD5HloOLeIn/chy/MjDwnQQtqY0VrMJ2Nq7kGbqzNqF2jeJoPgOCFSyd20bNoCipbk7tvSz6wWHQEpWqN9A554AQnME7PBd2s7spZ/A2EPkeDB65o+w4hsVu0x91W+Law1U8xeW9v2XnfmUBs5eC2E+aRO7v8zJ/4MnWl2gUUEz1iXreohSUXbS9hJuva1CcnZPs0BYvsuTD4zVnizA4V1gi/go1QlGsqurM35JSsQedqvEgOr9GSXCoWY7UBIkxXj81BLpxRvRIfOI4mZP7K+VPfqMPAgmnwZaj4ISiKsMzl/P15oDnRXk/H3Y7NKCsZmdzBPdxl6FyqBzWbydX8RS3946SWLekBMaMAeDeMf/l04yTlfcliXv5q5bJPBK9O9eRTVXETO5qged/cg2f+gMnPdFdSsKiWgFsNhFw6jXZghU1l5wsUx5U37I5q6jstPGSdCnvcwrrgxzMszKb3jvlLOVwvmryflgZ/cr0mbylyRTL1ozZqIrGGb0Vv8Mzeizgtvb/TqhNu83HabzL8NL46qiu9nRTFJDG88/zz8MJJ+hqYx3dgcgKcrCCpaduahMZa0rZQFd+WBa9pNEr5Q8qvpyS1CToIZn8wCiW0S/6gZAy923qXL04ODJ3Ht9s7sb0GU5+W538iIF4kW3KVqdPxO9oGYlvt/Tg+X1KNkCfiL82U6DUQsvdMsETTAWhMevadot/QHr0mxG8ydkx/77g0H89HO78jrKcfdrrdziN0Xwf41mbx95ISXyN83ixyxS21gRyHEk2W5PElMEM0pHxWC+9O1bzFNcwoo3+0lAFOQ0UubeynfY0eGy6HFR7d6lnClMiRhuqfXU4s+mtZFnAEWdMSCD1ROCZM3KbNxwd7YqCmRchVdXijW15hkCx+qjWKIcDHzbuZirX8QQd2Ux5z6b5lpZTztfo86Hp3c3NNfxTK1btlWR681tA4UoyPzKScpYyqlgp3D6+w0rOK/hvQm3KNl9CpXK+bVD81ZqYny67DD6KLWdVpD6fRUBR01PWq0m7/q/o2sOw26kmizqfM6UUrFH8qERk6iHBwAWjSJ2rFwePdPo71/JPAJ5dOIKrdt2XZIni479dr+Gf49+iQ8ZeOroi+zrEw6y1fbm/4g8AnNvtR27p8Gpc7agRZHGHMsdBbk5zWdn9yQHVygBaIr3YLFhaIj29UTJBFkGAtziTuYyO6ZxRT2ELXXUJJGV7MtiiZ5O0vFHhWERk/7XYBfLvTcaSEt5uZ7O7mBK2M+fXAn2rySAfq7BN+gd7DzK33gpbtiiBC/EQXP2nsbJuFv3l3xjH1xS3C//7tleGbr9HS/1RY8+lASeF7CafvYoCm2iaBqedHKq0Mi8V1TK38jA9WJNQu0axnzyW0b9RGGFig5JdEnzO0azeF59DdKHdv+BK4NpnUc15vEbvbuGt4UXsZAz/A/Rb24M5rkRZcOktlTOer/njvPN1BTmkIlct/gP/4tqkB76l59VTkWVtIFhS2Zk5tSOTLFB85LoayKSWGUOf47kBjxvatkMWWrj84R1WcFaRvq2CxqhbizaTt1GCaZsXmIjKGznpdnTuAqAoXxloVf/vmLcI/RPtQJs+J+BXvOcxf70yEPdnCTM5J6bz6ZKpkYKl5nPZXpOrvWezS0wcvIEreSZsG0swrkbc1sps/sjjzN6hv81Z68u5l78CyqA+mXvYQsdmv1PjdtCJTTxA+KSG6mD/Dqdjs0GHDrrFaUJwZOShhcqquKzU3O0ELTluBIWg8WQWbTIsrl2n+JEhWMBQpaBzokt2hyO0VI4aOdvyGX2aZdkO5Rlcta8dC2oT87CX7T72k8frSwZFPzgMb3e4gVe4IKFrn8t++rIioueMHa/WJyIOC9awgvWAPl30zjWXMZ8RSnqVFLJg8cUX8PPPug6tFYoLQHt5r5kSRSWFrl4cyLLm1+D22dM20aippXIckqZgJbLasyeh2HOwc3XjAb5H1la6sJ4OxYpcapmRWMWTJMVZfYRtvq7j/1JzJx8uU4qJro45G40+GuuwF/EKx65+UktxAoq/UL+OlZzC+4BSWiUYNczeCL5f1Y5/8EceXhu+RmA4ftjShee5QpFVZ6f8sjqP83hDSbcRBnWwn8JU3XJEQn0MbDbIddZjwxv3dqNe/pj3Indxb8QtniYKVpTFjFoN423O4COUKNiV62OPMAumss7JI9zCb/7ktaqCtdbvI5RsqshmEIuY/ss4AB5eeDSTNtyZUJuqxTheQ1iJcw8X8FpiMuBpvk4lHk3BOjrnh5jbbxx13RxrapWViyQ1LdOTVI48EoYN03WobBMcwnd80vuPJgvVPGmtYE1Y8RiP8mdAUbCSbQ6Mlyd2ncOMxWOVLRijS+XIAeVkxd5iFtb0jqudBwsfBszfRgmmU6mXx7gJoEm+p8Z+E5pFIo57YDo3cb70hq5j1aSwEHBaNpo/9mxai2+vN0+zto3ja5wuCRwO7fdupzjk+Mt5wTB5tPqhPv19HxzxaLNLnMJ7Tcr/NPmOMzSCrcnnGcZZUVT5uhdXcUm3OeyiyKAK9JHZJQo5ls/YvC3872isYEXzCZP99983jNPeq08wU02DCNUy1Xxbt/O3xBo2iOw9m8nJ9OH2R48bERjULVupGRj34tGAMXsLpUxlCjv3hdfyf6eMbzmMK3mGPxfE/mxvrlMsfnrGb9mmRtUK7Z48m/+L+ZzJxB5DWgozSWsFK/jaKQpWevJ5xUg+3VTOdQuv4Obl+sJ69SI7AgkfH/x1Atetja/yeXtZKSXTkgqW1DtQ2mRNI2uRV7LzO2XaQKsqAY/01Zd3Jpj+LKWrWKfrWIfk1WoRmqVgjStewQQ+ZjyztfckhLYNejOP4XRJrN2bz3x/bS5h4qNs9/upxTKN2Rv5i5Wxmd407yRv90/mXzM+7OdZOcb9xsLcevqxjHF9d7Cxrj0PcwuVFeYu0KKVynG4Gr0fZXJwSIqmH5z/zOtOTEl0ZDRayERJndHi5OfjcIDHG1CwolUYiMbDg16hiJ3x60k6rSrNoT6/u/c1bzF6hqsoJnph+sa89/sIQN/4rUYxS0BhIdzFPdzJ/TGfM5loSZgtBSt+ZHtgMPEIW9JzXsSLbPfh8dlYU13M+rri6F+IAYcjYMFKJNHowVlLqCI7bJSSaRQUcDPTw340oq2SKkEtjqpaJPpmrI/5NAP5lRe94evfNUa2eXH7s2abpWCpIcbB2CShObVvowQkiS9WlnE395ojQ7A4am4kn/7hItiCJUlg79s7qh+P3al8fh0zwn7es5fEjUxv4o8XD5eMXKE4S0sSq6s7MI2/UB25Hq8h/NCg1MJsLg9WLMiSh178xnFyoCh6ogpWYythCwYN68Zh9+L2GmfBUp+3uOfiZ5+FxYujH9cM73EKEN1qWUku+92xpzjKcSjjdrg0Ho2R7X4FSwJXlp17uZu3ODPKt1ILu13wMwdx9YbE820mQgo+PvqRbULLMFxi35W2Fiy7TfjzYMWfRiESsj/bN/h3IOMcjGbVHs4zTDI9lD0S6gCk0sahbDepg2K7fA9DWIDPG/vvqyKXxUJfKRGleoBfwTLJ529hZXfmMI71dNXek4BTBitWtqt4Bh827I6W8Y9QJ35vDM61wRYsm13im8xjWRqlXEtUBcOflsAIVwBhs+NGiVqct1exlDbUmbtF+EbViUDkSTRWa5Es+Tidd+jnWKW9F+7+//e/4cMPdbbpV7Be4NKYZGlJHDYfbq8ydQkMSM6shvTHOxtmZsLAgdGPa4Z8FGfsaH53x/AZF257OOb2BxQoJaz6dY++h6wqWDYb2krpXu6O+ZzJRP0NS2p7JFWO9Faw7D6G8QsCif7OVelrwbIJvINFvgkAACAASURBVD5l2jC6VM5xg7fyKheAz5fQYPRV7Wie44qkLWlP4YOQ12rSSTWU/eRDdnI39/Dx9oPiav9Vm04LlhTw/1AtWNdGsLjEy5OrjqWGbLYSCJOTJBEyMXu8TZMA5mYGtor+8eeNhsnj8NfIi8eCNZEPKGzrZefO6N+xu6L4WDWKcEuEWp8LJ27emNuNNWWHAeAuSiAsUQfRSuX06uFjKL/obs9h8+BB1nxmALyepkrixRfDiSfqbNNfgif+mg/mI9t9uD3+/HU+KeHgpruWnM0eCuOuRWgEWqmcCDKUs5TerORHRvFzg77FYDDqLacnh5ZDVu6nvvnbtTq26UZJdhWQ/PrEaa1gOeyKo7MXG1ML/s6c7pclW6S4ULcITQgipFfHGk7nXfB4/IlM47vh1jR0Yhn92barZcO1R/M9l/F8k/e/31cOBPkUOBw8y5W8uPW4uM7j01k02WHzaPUvi2yKX9o7nB7XOSPK4l9Kl7JFe0+SQqMqbXapiVP0v64ObFOMHKivPI0e4rFgyQ6JTGr4gFMo717H/PnRI6yjObFv2+3gCW5gCYlZCwA+WaFkP69vkLAVFQIgXIlXl2iOQC658NfRlS3Ti1VhPwvHIVmLWMRgNotA+guvO7EJxeZyIOEL2c49i5kcxecJtWskDrsPty/IgpXgmLmzQcluPqbr7wlKFj9qapJI1s0C9mhWrnjyYKkWHS2ivBkcsqA/S7hm4P/SVsG6fcSXXMjLyXbBSm8FS7YL1tKdbKopWvMjbR0mO1GYhGwTeHySKcWeNVOC2+0vlRNf+7u8+QBU1bbsAyfjwY0Dfgld2S+sVMLGNYOa37phi9MvSq+f6t0dX+DSnkrCv6UFiuVjOyVxnTMSatj4IAIKU0fnLup8Tu21ZLc1UbBUSxPA0L61hsnTtZOXISzgj+31RxKdMWIDs9Xs4ZJEcXH0a9y2sPl7S/hT11/ES7rliMS+eiWpp8cDZ5+tvNe+fcLNNou6pRzRCCzL5FClu73nO0/lc45hTsMo7b2C7ATDCGUZgY1bCGxDpULJkWDO6jSXc4uVAJAJpYs4r90XCbUn2wWDWcgh3eIrlWMEn6PU0W2uVI6WXV/nYjCYJXsVJXz5uuiLiMfGvqcsYmw2bM7Uyn+mGy1psWXBipseuTvZSBfq8d80yVZX40SxYNn9TujGtr1xXx4zOQtPnSchH69o2xtmIaNsgzB0aKg8fjFUeb5c3I7/cjz73LGn9l66FD7XuUA/od08DilcqZxbNkfZVJtVrQiPcRMzy6eyszpLO8Zmaxp1FuzD0yQiLQHKymABwzir7We6v9OhyM1I5ikvdN7UxaV2/sq9dGZD2M9VC9dpRKmJqAPVR8zrEUyYoDhLt4lepi0hShyKv6gzI3zfVNY6eIHLdbenKpxXtH2Hw/mKviynvHecxRlVHA7G8TVF7NLeGsXciLnJksHZ3eZxcftPlP93mcs1pR9E+Ubz2FMk4gwiK1hL7YPYnKFEUsdjwWrwR5LX6lh3SU5/qghJwpWVnhashAMXDCKtFay7hn7Ek/xBez1te3puEU4e8C5vDLgfp82N057gANmI79e05xxmUlflYWLpT5xdMieudjQFq4Vv2NkcwRuc1+R9Ndu56lOgWncafLGvuMrLoW3b6McBoaVy7OYMPmqzH6M4zviwgc2mGSOXT5mJJIWG1I/hf6GJMo3sKPXEsVRWdjhYSjlO6pm3PDf68f7vNFcqR7XQuUk8I6i63eqNIygiXg7NXUQJWyPeazUNsd27wp+3o1PGDoawUPE3GZ1g2Sa7nT6spIA92luP8idDrrlhOBzg9vsbGlAqR7bDEgayuyYz+sEm0ZflFLON4vbh78efVuTx1rvxZ9XvV7ADAKddh4VflhnOfO6aO8G0RaTZPL1kDK9zftL9stNawQrO5A7wXoW+gqapRlleJd2dm/lk6J28dPA/DW1bDbH31Hs5r+xbruwUX2HUlqrXppfSLKX+l9OhyKVabDxxrO5iYV5Nf37a3hmA8/c8Yco5VH8JFXV1vSlLya69GKWkx4A+bkahZHUewkL6dw8sTzdtd2IU9cLJ81zGL1X6k9Qu31nIw9yCG/1yCNnBcH5mUoTyP6qeN5dRYT+PBU3BMnY90yxactxIpXJiTKQ64TelrJZN9kfBuZyJK9aS1GRLULMipwjbPYWsrVL2c3fU5rK1oTCh9tTn7dUFxpWXipVitnMUX5AZQcfr2RM6K8NOXBas/kVK7qxsV/Qb/r21g/mF4dR7HaH5VtKI3fXKTkayZ6u0V7DUWoSQEhbe+AgulWN0Jnf/tpGn3ptQKR7NfyRKAVqjuYe7KGZbk/cPKlwPQJssZSWrOmJ7THbKvHf9Rdy/5GQAfmoYbMo5GitYt/EQ1/x2I3VlyhbBvg79AOje1cdN/jxhD/AXunf2cArvAbC7wriBceOODK7geS7c9IDu7/yysR0vcQmgXynfX+fgdN6NWFhYtdCp1RsSIWDBSrgp3UwomMvj3Bi5HEqMebCqfcpsvKi+D49zk2GTybNMYh6Buq5uHFQRZ1VtE7hn8cmctuIBZBmK3/0XFyxPsFSOnBzrfIgMqhLbzPjvyFIeAL11U4Px2ZTxQPJFv+FXVSjKq80GuBIrvZQsHE7Io4LPh96aVDnSWsGatmgCVxLI3J1sh7Z4+WL7QJ7cdLKSqMrgp1yz7NR52FbbJu7V3rntlWSGLT0IRQrL16Ji/FFT6nZZLJFu8SAHRTCZVfvyqO5rm7y3qrZMK27crp3/TYeD9iim/wUMRdhl9qIEIxjZT2rovp4IJO07rtCIR13f8fdhpO0oI2sFqkV12zqNi7aMxnp3R67mKSoqIyhYQRYsJ9Gd1dVt8h+qBiHhY36vc40RtBFbKWU68VWAMAOHLHD77JpynOg2UK5LWaQlM6nqVjowk3Ooro0shCvLznF8woPyX2Nuv8an3PCehuhjlkNzwVKu6wtcGuKKkw44HEr+x2Qnyk1P+5+fSk9WyOtk77fGyxfb+vPO1v5s9Hakw163v/qeMaiRZu46LzcsmESD107TSnfRKctQnF5beoswUgSTpmD5Bwx1cr4m9zVAv6UlVmS7oKZBuaZmJRo9umfTsj0ScOyxMHs2jPOXnqt2O8mgDoAlDGBgtZM5HALoV2r0EFBe9Y9WziAne733jLobEamItpGDZWEbDw4aGNN5k3GNRqFBclFFLpJ9f9jPVQWrF79RTTbQMexxKnb/eOe0e5EQZNhasMpCEnHIArewk00V1eQkvJi4fcy33P3tUUl1f1iOYpWu2G8jO8IxmXkOPmECiNhXGr/sLANg+26ZaBuhqq+j5L+wl/Jv/yfG5vszE4fDv1CzSuXET+PtYW8MK+xUQrYr1oHvKgawuKKLsW37FSxPgz/RaJxK6NiCpSynLyXFLavETmEqW8JMNP0KtjOKH8jNUFafqhIwXF5kqjxqSg0wT8GyhcnQbpN8SBKMHx8YM1ZsymY0cwG4ieks3RDYxtGzFaAXdeKPRcEKdsDXO8apz/MUpkY85lJeYDTf65YjEocO2EcDLvoU7op+sEFsalDKYEWayIO3CPU4lWfaFYXqoLar8WHHFybJ6IGIQwa3L1BOKuEpVE1gm8S5eLpTKenS7MJIfUDi2Ne+adRcHuFPjB+4O+qxqgXLZktPgwUoSqIbJ9PWm2PV1UtaK1hqxlkVtahxuiHLioKVSCLQiG07A07uieTZWu/uyJccGZJrKZn07iPxA4eQkaP0eUa2nUJ2me5UoyQ5VCZCsxSsnfV52v/v9isb4Qb/YCXGjTMks7skjJNN9f3wxjBcBKci0GsZ0DPBGVUqJ5CnoeWcsD7Zq/g1Reob1S/sep5gO9FrkmbKbo7jEwa1VbL2/2XbDYbI2Z7tnMMbhrRlBg4HuIWdGr+tJ+ExMwUUrG52pQ+bfVZkmXF8zdW+2C1JGS7Bn3gMmy+6k7vDH5eSytn8o6HOU1/vNcdPVi9prWA1tmB54kjAlgrIsvCvyIwvldOzi5vHuInC7LqE8mz9UNmf65iROg/d3XfDW29BHyWyrn9/eIsztTqBZiHbBR6fukWo9NVjhm7qwsuLA4NCN5TtQhHGt0z1jdJkC0o8KhkYHqdasGLywfIrf3lUkJUV5eAYMCrp5c6qTErYyue/GWsxbg5bhuIw7PWFv0clCfqwgmncgTRvXtT2ZJsPNw4tkOWD/UcYImcJ20LyYKUayhZh4N5PdMz8z6p+eJPsr6Om3GhWwZIkvmEcT3N17Ce49lqYOBEOPTTqoQ7//dQ2I8GktUlE9bGMJ+LSSA4oBevpLtOSI0iCqFuEigXLWAWhY6ngJh6nILteCSKMs521daUAVFS1rBJ7FU+Fr8/mcsEZZwReOxzcxb3MqL7EVHlkOVjBUib6wnbGXhO1bM8xfIo8SUk8Gc55v7GCZXcGbcsZuEWonicmHyy/BWsuo+jdzR3laP28zMX8j7EJt7N+ZzbbKWHRlnbRDzaIP0xXfMuyiiPnBRvHHKVE0ogRUdvrkLmXzZRRiWLx9Bm0+GmcluEYPuV03jakbSNQLFgB+RL91VtrlAyzfUv2JdhS/HzkUUp8meYHVlwMH3yAntWOav25ephfyR86FLp2NUcukzj30E1M5AMybXVJlSO9FaxG1ec725NXSyoRnA5lRSbMKJWjbqh7PPgSMIOvrVNC2FpawXLgVhJtRj3Qb+YX5m75nNJtEVe3UzKJf19+BdfxREhSRiPwJ+jmcp4nO8tf2T7MtlITBStoi7Cs0LhSOc5sRaCrXPpL1PTp5eNNzlSUBaMXDWxOuI1qt7IPsqva3PqDwZx8lgshmo+GjKWY9eTyt1lJX77ZpdTlNGq1/gvDeYprQmRKpVI5g8t2c67rPe31+MJfE2rP6d8SG9Nze0LtJMJ79ROAlk+DE46Jw3/nd0rJdvoXRr/8AuuaBt6kNA4HO2mHSLIbWXo6LfnJywpdGbuNWyi3KE6HoAGHXwEy9o6ocTtYwCEM3OdDCHvcCpzd7/Do9bTsHavVIozC7koH3zOGPZ4iU+WZ0G0F7JwH/BW7w8Z7nEphndufc90Y7H5HVw8yZ43ehnhcgsHjgdkhx6m+Udr3gixYRvoW2WUl+STOPOAWXd8pbGfjTNXqEcPey/X8g68ZD/5kqo3pwnou4FUg9lD1YFRl1EBDnyE8z+W6lRnh9yMbXbqBz9b1jKmOYXN0Yy21ZALKomro1aPIyU0R1wDguPKNHOe6n/l1/RnEYm7t8T4QfxUPrUKAkJM2IcqSB0RqJHLOypbIYivo8NdKWWSZHzgEovv0m0ry1eUEuGL0spDXM/ccnSRJEuOkfqv5oOAyv4+UsQ/Y+u2ZHMp3LFnlZHz+YsYWLY+rnQkdFgKQn9OyWuxbnMmyqIHF4LMrysYuX4G5AslyiCZvhtVMtcx6Tz49xALZGNWyBErqhowegWhLd0F0J+mYiUVpcziYz3C6s4bVG2PI5h7FWuLAbUjZlpIi5Xr2yU+e1SIcPux4dP4+4U8eWda2ilN5D5eO3Fl6GMFP9CeQzPJv/8rjrod0ljtqCfylchy4acCZcP4ONVdgdUPyygGNzFCin7Mj5WhoSfz1KJ/+Jfo2daryy0ZzF9p6SWsFq7Gt/fOqBOtwJYkuRdUcY/+Sr/pey8MjjfV1UK0cnjovt3WdyY19PomrnfN7zKUBR4srWI/yJy7j+ajHackwTV6Dbq0vYGl1VwDu2nglW+jInPrES7cEo2XfLyoJ7F+EMc9m50jkUQHA8OFQXCJpc83ONuFzScXLAoawyV2i+/iqBicvcTHr6B5T4MEIfuIkPoz4+W4K2UDijum9jujEcvpy2S2pMRDHw7QVpwAgOf2FbQ2KHE21LcHGeGxOKt2ZCCSqyVZKSSWAui338vfGPjOx0Mu5gd6sxJWZ/Cl51c62fMM4Vu5OrARRMtlbl7y6ksEkvzcTwRm6MjYyNL1FcTjA46GtfT85LmMVGDnTr2DVexPLFJ+VhQOP0kYLcnb2xzzPFVGPU6PWzFawnvz1ME7YqNSL/GzfwQD84g6/nRUvDkcgS/28NYVICG5ed32T4zIz4TF/hu1HHoG8PLjJH9C4c6ehIjGMBfRs0F+iY3eViydRZI5l2+NJrmvW524vBczkHN3tRaS4mL5iBdKRxkTeJYPt9UrV6N3uNrzOeez3GWP++C/H8TnHGNKWGbz2Sz/auHfxPWN4hzM4ff7tCbWnLWha2P0hGKfdqzsxpg1z97W3VCr59PbVtpx/otGo88FhzEmqHGmtYH2+qmvIa7NvPLNYX1XEc9XnUu+xG+4QHKxgub22mELtQ3j4YXjwQeje3UDpdPDrr/D551EPU42Zia5mo55HDqQrUIfjAslYJ/cu7RQH9Ux7A/vdyiD39f5hYY9tQwV9WKHdNkamRGhMLNc22AFfsusfZmrJTKm6d6mM6he5prIdtWTxiO02Q9rdT170g5JI41x8iY6Yqj+ex5M8/6fdvgJd1t4JfMyj/MlUWbTyaianvDET9Td0JLmBb2nt5K5WzFb5qd5YS0JLsWh7CVfWP8nizf/H2KL9nGlg26qC5a7zcuzCv1HSpobX42koPx9uM2YAj4lu3ZS/KKgK1sl8AJiXvVeWAyHiPiFRzDZmf1ht6DkO7beb7xlN3/IrWJKppBFQU0M0ZjQ/8BMjAKX8ym23KUrWIYcYKhIA3hiGi2AH/FhcZARSq1aw+rKcE/gYdBS0VvVWNedPsXeLITJ0Y62/VI8JfnwGEJzvDRJfkx45RPGE7pSXvDQN39UOBaC+QWr2KftYC6d53DRZVOUkUr62dED9DcG+hMkgrS1YjR+0WpGeJk2nvzDuK3sm8P32Hsa2naNsozbU+RLKg5XqSBLY8TDOZJOw7JCCLFgSp/RbSZcTBhh6DmeGjdHMJd9ZjTNLGW4bfOEdcLuynle4UHudnQ23325O4dpOxfqdqFW5IbYtwqUM4AUuj/j5sUc0cPihaRourAPNcVsHeS6lP/qUKsq126D18ip6sYVSQ9oygyYWrAQjr1UfLFsSQ0rPzP8S0GntPfhgU2XR3C3S2IKlWiU/S/JWd1pbsFwZyg3Qk1Wsppfp/jdmod7Q9T6H4eUanJlK2w11ai1CY9tPJfSmdEgEp0uiwV9sNZHM+M3hxsFuiims92n954mQ48ioqLpozJ4NvXq5dB/vyA4oCZKBhaez2jhJcu5AU4mlPwszayhmG0O7K4EOM/gDIw2QwZ7CDu4QsE6oJPoMqhHIZufQa46eWYr1MWqR9j17AiZLkzgQLFhqPddvGJdcOZJ69gRRJ5+bmA6gO7w51VCzXtcLp+ETdkamxM32x+lVsFtJZJrGBTyjMYdxTGCWqedwugKFeBWF1fhB6LvVxXRgGx8t6apZgiLV2awlixv5u+EyNGb8eOjYtOZ2RNRnE0CWjbtGicRppAM7aM+7nKbrWFlW7kX1Wr/CRWaKljIY7YO1freSgmLD7uSlovDZdJTKAcVVI9PcCDl1wZ+2QWOEFk5PJumtYPkVkz+gRHXdYX8omeLEjTpA+rAbPnk4HPBo1t0MK/5dSWRqbPMpxZU8y+PcaOo5XBk26slACNWCZbzCWu1WFLilW/I1X6Z0K2Su1lJ+hivpXGbcQP3BBzDLXB06qYzlW91+I06HYA+FCKd+y6IuPvgA3k6d0jiNaWzBSrT6RVW98ozJJC+x5m8+xTUkFRYP6vW9uucXSZYkfrqWpUaS1LRWsFxZoVrqEBYmSZLECF7tm2JhcjqhoQFRuR9pqzGOsKlILGVG4qV/5/1cywx8bi+zul/HPSONn+1lv/+A10tUC1aqIkkwnRsZxVxDZ4133knpuT9hYrmHT++nJFqeu15/fjJdTJwIp59ubJsG0q7Qx+F8pb3um5fYmJbnD5ocXbohoXYSYU6Rv66qU39SXrMoLYUfOZiD2qxKtihxIzlSY7xMDSniJFgxAXCnqVOeaokDc5zQN+/OIPeOaQhmYas1ppxGKrKEgezNLuMfJp7jkPJ9HMJ14LucUnkHZNYYfg41eMPjgS7dbOykCDknC9ho+LnMRNu6jMHj/qL2n7B2bz4QPnnrafp2z9KWHxnJTvQVoBb+opWqgtCF9UBXU+RKJQb2rucrjuQWHuI/TGTqwLeBM6J+LxKqxcbdkDz3iX8+5+Shh5qvU9lSuLJlDuYnsHVOtihxI2zWFmHCDBvoZgz/015/jwmx6S1AWamPZ7mCHPabUouqP0t5nBtZRS8cHLgRWAC/V+ebewJ1hVlfb5pD0MhBtYxgHlcctBDJ5aSI3bT1JrmoVhz8yMEcxhx27tY/zIhjj0caZWxm/HRiHd2pQp8vkKpgZTh9nM3/0ZPVZoqWOriULVEnDUrEZYLPoKZgJXFoHDAAXn45NbYIkWUm8gEfbB6ebEnipsbvZnE5zyVVjrRWsGwZzpCSDqkcWtwcbQtsXMHz/MhIbhj2v+hfiJFK2jCFqeyiiGH8Ynj7rQm3zcUO2uGtbeDRnRfxn3UDDT9HzrFjmPfAl3S594qAQhemFmGq8ynH8i2H4fbqH2b69VPK/lhE5+uNStLfhoaW2R5PGfwKllG1CKsalGfs3d+MTbeSrrhx8CET+XTb4GSLEjc5bRQL1nH8N6lypLWChdOJQGI488lhf0rXz2oW/yRaznJK88zbwhPYeJhbTGs/2bz0EsybZ+455vzWgWJ2sGm9lxf2ncrszb2MP4nNBnfcAdnZuCUnEoIrG2aEPXQ6N5KFsYlOjWIy9wCxZXK/4w6YPt0siVKfZctgoU5X0u21iqWrvtbHd4xhKx1MlCx1WPl7Dk7qmcoUttCR6+ZfnFB7+X6jd6+81Cr8nSy8kuI5tLAieoLnVCUzx45A4owTjSmAHi9prWDtrc3gf4ylASeH8H3aruDckpNPOYZtFJtuI64jPZOx6uGii2CEyQXgtbxi1W4litDkJ8jmVAa75yLUY5TxkENq+9WlxLZHmtCvHwzWaThQa+i5GwS/U8ZIfjRRstTBnunEHZSMtdKdWH2o0hIfy+jHTQOil+RqDaiRy5GqR6QFHTrAlVfC381PYdMcaXwFlarqAJsp4zOO5Z0EHB2TSY3XxXF8ytnM5JvN5tb6+50yU9s/0FEjV+urPQjABJe5EOxRckhdxwy2YXAUmcFETZ5oEReqQ7SnwUceFZSzLLkCtRCunFBP8IQVeFmmHyuw+dJvG94MbBnKvFokJ690UMLYbPDMMy1fO7exGEk9e4KoD9o/uCHJkiSGM1v5Hd8wji839EyyNBbNoVmwajz4hC3p1plxfM1FvJxcIaJgRuCGBeTnKgpBrqMu4PDdCsjIbaxgJbhzUeJfoIxLbtbvVEFyOfmAibza+55ki5L2pHeaBr9igisDkrvVmhDxFsa1aHlc2cojM3NWLh4akq5gtUR5oESJxQfLQj/dS2oB6Fm4l1204z1O5Y4ky9QSuHJDFcmEn8HCQqipMT1DetrgdDKRD4mUKsVCP2mtYKmKSYM3NXJexIs904mED4H5FpFJY5YC/c09yQGMmvjz4VeUVa8krUmmOHzFkQD8X1KlaB7LgmUOaoCpu14J7vkJc4sApwoZeaEKlttnwDRmKVcB1L3nZOatOEBI66WlPVN50J72XAbA4DTN5C45HThpUP5vwlz0f5wNwGSmcMOEVpIrxyQ0q6mfZFuwUpnRfM85vEFBQbIlOTBxlivuBA3d+iRZkpbFkRNaGsidzs7YqYjNpqRzv/vuZEuS9qT3nSkrK5d5jGQAv3IY3yRZoDhxOjUFy4wtwgzqALiWf9K/rML4E7QicvPtFKAk/TyMOVw91OS8EGnMBbzKSXxobRGaRO+T+nDphR56nzUk2aK0KJJDpivrtNdt5NRMU5LW/P67UjLJIiHSe+QLMh+ktZNnkIJlhkXEiz/yDZfl5JUg+e0cfMNhANzMY3TNN19h/YyjWcQg089jNNdKT3Eeb1hmPpPIyoIXXpbJ1Zf4/YBiHd35kBMBuKdfKm+QW7Rm0n62LWIn5/MqleSxneJkixMfDge38TfAnLnodN4FYDaHs3P/gZsHq0VwOrHjBaCQ3S2iPBzNFwwyPmG86cx1jOV8XqWu3lKwzGYCH3My7ydbjBZFLfuVzBqCFhbNkfYKVhmbyaOSZ5jEXdybbHHiw27nFvt0PuUYzhyw3LTTXMzLfLYkPcsJpQwuF31YST1OVtKHuVs6mX/OXbtg7tywH7VpY/7p4+UX20G8zvl4fZaCZTatqlQOgN2uWf3r0ziC3OLAJu0VLHVgOZyvGcaCZIsTPw4Hx/A5PduZu+Vk7dYkiNNJLvsZxVyu4HlmrW4BB+PCQmU/KAx//jMUp6jh9sa6aYCVpqEl2N5tNDv6tp48TmPEtxzBbACmrjg7ydJYWIQnrdM0ACxiCLspZMbLeVBUlGxx4mat3BsnuykzWQOyFKwEkWV8uFnAMCD511OI5MsQCZfUgFs4rTQNLcDEi/Mj6eAHJKtFD+3/G2raJVESC4vIpP3SsjMbmMh/4MIL4fjjky1O3JxT9yL9WM6yHcYriUu+2MY7nAZgeu28Ax5Jopas4JdJ5ZZbYLl5u8oJ4ZQUHxlLwTKfyZOVe6G1oN5bAIMyViZREguLyGjT7THHHMOgQYMYMmQIY8eOZcECZbtt3rx5jBo1iqFDh9KvXz8eeuihpAkbjg10ZQbXJVuMhMm01VNFLv9dbXypnP6D7BzFFwBIydYIDjCSfTkzMqBt2+TKEAl1ErTJllZvYSzBCpbk9SZREguLyGhbhG+++SZt/SP1e++9xyWXXMKiRYuYNGkS99xzDxMnTmTPnj307duXE088kfLy8qQJHcK118KIEcmWImEybP7JKNG6WmFw21x8yElA8hWCAw3LOhMZp80DXusaWRiPy+bGH8yL5LWKNFukJpqC1TZoGVxRUaFZh24fEQAADGdJREFUOiRJYt8+pap2dXU1TqeTglRKzTxjRrIlMIRMuz8PlgmL/XpcXMBrprXfmrEU1si4bNYWoYU5OG0BpWp2dfovsC0OTEKc3C+66CJmz1YiM2bNmgXAiy++yMknn8xf//pXdu7cydNPP02JWn28EfX19dQHxcxWVlaG/HugYsTvzJAVBcvr9Rh+vTwIwEVb9lKWv/uA74940d+Pedr/zOivA4UzjtzJtFldqK7Z36KKaGsZd1oDkfoyeItwm6ed1dcpTmt4JsP+NhGGf//73+L4448XQghx9tlni9dee00IIcSaNWtEWVmZWLp0abivicmTJwvA+ovj7wSeFyDE4fzBlPZteMS/uEqcmgK/Nd3/+rBcgBAgxBX0T7o8qft3vIB/p4Ac1t+B9jeSTwX+ZzCPvUmXx/qz/tS/iooKTSeShBCCMGRmZrJ+/Xo6d+4cYpU688wzOeaYY7jyyiubfCecBatTp05s2rSJvLy8JscfKBjxO2/t8yVPbzuV6RM/47JXRhksIZS0kZnGHVz56sF4TjrJ8PYPBPT2429tjmAE83mSP3D5XYU0/PnPLSilRTRay7jTGojUl1lHHok8fz4u6njUeQcX7ZySPCEtotIankn1N1ZUVGi/UQbYt28fNTU1lJYqWb7ff/99CgsLKSoqIjs7m6+++oojjjiCXbt28eOPP3LzzTeHPYHL5cLlcjV5Py8v74C9qMEk8jvHF6/k6W3gcsqmXCsHFaymJ5Kc2yr6IhGi9qMrA+phDN+RkXk2Gdb1TElay7jTGmjSlxlKya8M6qh3261+ThNa2zMpg+LUfuaZZ1JbW4vNZqNdu3Z89NFH2O123nzzTW655RY8Hg9ut5sbb7yR0aNHJ1vuA45zus+jYtFVHNpzrCnt15DFk1zPUYt+5GQr8XFCDMxey5r67ixgKFm7CuidbIEsLFob/oV8BnXUCWeShbGwCI8M0KVLF+bNmxf2gKOOOoqff/65RYVqlWRkcBXPQEdzqvo6acCDw4roMoC/NEzhYw5jJX352/KvuTXZAllYtDKm/X4hf/Hn9nuGSdyZZHksLMJhBe2nCA3OHHZTYFrc/625/wKsNA1GUGHLZyV9AStNg4VFMlhW0w2AtuxlcodnkyyNhUV4rOk2RXh+/REUsZstFdmmtH9VwduAlcndCHYSKGdkXU4Li5Yn0+UD4L2bvuWypX9KsjQWFuGxFKwUwZWhdMWHS7uZ0r7IVOrnWQpB4uwVgaS81vW0sGh5MvwKltS5E+TnJ1kaC4vwWApWiuDKUGbqeo8c5cj4WGtTahxaPliJkykHskjbrCfIwqLFyXQp2YUE1nhmkbpY00OKkJGldEW9x25K+7dsvgGwLC5GkOkIKjRrXU8LixYnM1P5t7bOegAtUhdLwUoRXFmKYlXvNceCVZRRDUBJQYMp7bcmMh3ewAtLw7KwaHGyMhULVs1+b5QjLSySh6VgpQiqglVn0hZh59y9DGIRQ3tVmdJ+a6JNZqBawbCyHUmUxMKidZKZpSxsaqs8UY60sEgeloKVImRmK11RW29Ol2RneKgm27K4GMC5vZS8cNcygxHFG5MsjYVF6+PK8atYSzfOGrYm2aJYWETEUrBShKJCxeSdZa8zpf3sTJ+lYBmEcCllOm5iOpkNFUmWxsKi9ZGR66Ab63G6q5MtioVFRCwFK0Xo3snNX7ifM8qXm9L+Lk8+2+jAlwsKTGm/NTGkbBdfM44tlLJ9h6WwWli0OO3bK//6axJaWKQiloKVIjhznNzPXxlcsMmU9rMy/XljEKa035poe+KhjORHxvENLywYkmxxLCxaHyeeCDNnwnnnJVsSC4uIWApWquAvXkqdOVuEAzvuBcBba0URJsyxx7JjluKHNX9rWZKFsbBohUgSnHWWlYjOIqWx7s5UIUvJtE5trSnNj+yzDwCHu8aU9lsb2aVtAKiuNyfq08LCwsIivbEUrFQh21+DsMqcNAoiOwcAqcZyCjWCnHZKpsPqBkeSJbGwsLCwSEUsBStVyFEUIKrNUYDcuYpzu7vB8sEyAmdRHgP4lSm9Xku2KBYWFhYWKYip+xtCKJN5ZWWlmadJOurvS+h3qgrWKaeACddrSeFQoJJfOx3KwQd4f8RLrP343WNfwIRLDvj7O90w5Hm0SAmsvjwwaA39qP42Ve8BkETwK4PZvHkznTp1Mqt5CwsLCwsLC4uUYdOmTZSVKcFPpipYPp+PLVu2kJubi3QAJ7isrKykU6dObNq0iby8vGSLYxEnVj8eGFj9eOBg9eWBQWvoRyEE+/fvp7S0FJs/utXULUKbzaZpcq2BvLy8A/bmaU1Y/XhgYPXjgYPVlwcGB3o/tmnTJuS15eRuYWFhYWFhYWEwloJlYWFhYWFhYWEw9ilTpkxJthAHAna7nfHjxyPLVuLJdMbqxwMDqx8PHKy+PDBojf1oqpO7hYWFhYWFhUVrxNoitLCwsLCwsLAwGEvBsrCwsLCwsLAwGEvBsrCwsLCwsLAwGEvBakRdXR2nnHIKvXv3ZvDgwRx99NGsXr0agB07dnDcccfRq1cvBgwYwDfffKN9r6amhnPPPZeePXvSu3dv3n77be0zn8/H9ddfT48ePejZsydPPvlki/+u1syLL76IJEm8//77gNWP6Uh9fT3XXXcdvXr1YuDAgVxwwQWA1ZfpxqxZsxg2bBhDhgxhwIABvPTSS4DVj6nODTfcQNeuXZEkiYULF2rvm9Vv9913Hz169KBHjx7ceeed5v9AsxAWIdTW1oqPP/5Y+Hw+IYQQTzzxhBg3bpwQQohLL71UTJ48WQghxLx580THjh1FQ0ODEEKIqVOniosvvlgIIcTatWtFu3btxK5du4QQQrz00kviiCOOEB6PR+zevVt07txZLFmypEV/V2tl3bp1YvTo0WLUqFHivffeE0JY/ZiO3HjjjeK6667TnsutW7cKIay+TCd8Pp/Iz88XixYtEkIoz6bL5RKVlZVWP6Y4c+bMEZs2bRJdunQRCxYs0N43o9/mzJkjysvLRVVVlairqxPDhw8XH330Ucv9WAOxFKwo/PTTT6JLly5CCCGys7O1gV0IIUaMGCE+//xzIYQQ5eXl4ocfftA+O/PMM8Wzzz4rhBBiwoQJ4o033tA+u+WWW8Sdd97ZAtK3brxerzjyyCPF/Pnzxbhx4zQFy+rH9KKqqkrk5uaKioqKJp9ZfZk++Hw+UVBQIObMmSOEEGLRokWitLRU1NfXW/2YJjRWsMzot2uvvVZMmzZN+2zGjBni/PPPN+cHmYy1RRiFv//975x88sns3r0bt9tNSUmJ9lnXrl3ZuHEjABs3bqRLly4xf2ZhHo899hhjxoxh+PDh2ntWP6Yfa9asoaCggAceeICDDjqIsWPH8uWXX1p9mWZIksTMmTM57bTT6NKlC4ceeigvvfQS+/fvt/oxDTHr+TuQ+rT1ZPyKgwceeIDVq1fz5ZdfUltbm2xxLGJgyZIlvPPOOyE+ARbpicfjYcOGDZSXl/Pggw+yYMECjj76aJYuXZps0SxiwOPxcN999/Huu+9y2GGH8dNPPzFx4sQQnx4LiwMJy4IVgUceeYR3332XTz75hKysLAoLC5FlmW3btmnHrF+/ns6dOwPQuXNnNmzYEPNnFubw7bffsn79enr16kXXrl2ZO3cukyZN4s0337T6Mc3o3LkzNpuN888/H4ChQ4fSrVs3fv31V6sv04iFCxeyZcsWDjvsMABGjBhBWVkZixcvtvoxDTFrTjyg+jTZe5SpyKOPPiqGDRsm9uzZE/L+xRdfHOLQV1paqjn0TZ48uYlD386dO4UQQrz44otNHPoWL17cYr/HQoT4YFn9mH4cffTR4uOPPxZCKP1SWFgoNm/ebPVlGrFt2zaRk5Mjli1bJoQQYtWqVSI/P19s2LDB6sc0obEPlhn9Nnv27CZO7h9++GHL/UgDsRSsRmzatEkAonv37mLw4MFi8ODB4uCDDxZCKAPE0UcfLXr27CnKy8vFV199pX2vqqpKnHXWWaJ79+6iV69eYubMmdpnHo9HXHvttaJbt26ie/fu4vHHH2/x39XaCVawrH5MP9asWSPGjx8vBgwYIAYNGiTefvttIYTVl+nG66+/rvXhgAEDxGuvvSaEsPox1Zk0aZLo2LGjsNvton379qJHjx5CCPP6berUqaJbt26iW7du4vbbb2+ZH2kCVi1CCwsLCwsLCwuDsXywLCwsLCwsLCwM5v8BRkdLKZg8HRcAAAAASUVORK5CYII=\" />"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_ALM(ksp.z_grid,z_shocks,\n",
    "         kss.B,K_ts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Approximated aggregate capital law of motion\n",
      "log(K_{t+1})=0.14594821741362846+0.9611811624862514log(K_{t}) in good time (R2 = 0.9999988558436316)\n",
      "log(K_{t+1})=0.13205800455894173+0.9635249205659238log(K_{t}) in bad time (R2 = 0.9999972131809477)\n"
     ]
    }
   ],
   "source": [
    "#kss.B  # Regression coefficient\n",
    "println(\"Approximated aggregate capital law of motion\")\n",
    "println(\"log(K_{t+1})=$(kss.B[1])+$(kss.B[2])log(K_{t}) in good time (R2 = $(kss.R2[1]))\")\n",
    "println(\"log(K_{t+1})=$(kss.B[3])+$(kss.B[4])log(K_{t}) in bad time (R2 = $(kss.R2[2]))\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The approximated law of motion of capital is very close to the true one, which implies that assuming agents are partially rational is not bad idea since the difference of their actions are negligible.\n",
    "\n",
    "Note: The mean of capital, about 40, is  sufficiently close to Maliar, Maliar, Valli but higher than Krusell-Smith."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "save(\"result_Euler.jld\",\"kss\",kss)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean of capital implied by regression is 40.049373762168585\n",
      "mean of capital implied by simulation is 40.160799927814296\n"
     ]
    }
   ],
   "source": [
    "# Compute mean of capital implied by regression\n",
    "mc=MarkovChain(ksp.TransMat.Pz)\n",
    "sd=stationary_distributions(mc)[1]\n",
    "logKg=kss.B[1]/(1-kss.B[2])\n",
    "logKb=kss.B[3]/(1-kss.B[4])\n",
    "meanK_reg=exp(sd[1]*logKg+sd[2]*logKb)\n",
    "meanK_sim=mean(K_ts[1001:end])\n",
    "println(\"mean of capital implied by regression is $meanK_reg\")\n",
    "println(\"mean of capital implied by simulation is $meanK_sim\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figures in Krusell-Smith"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's prepare some functions for figures in Krusell-Smith"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "plot_Fig2 (generic function with 1 method)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "function plot_Fig1(ksp,kss,K_ts)\n",
    "    B=kss.B\n",
    "    K_min, K_max = minimum(K_ts), maximum(K_ts)\n",
    "    K_lim=collect(linspace(K_min,K_max,100))\n",
    "    Kp_g=exp(B[1]+B[2]*log(K_lim))\n",
    "    Kp_b=exp(B[3]+B[4]*log(K_lim))\n",
    "    \n",
    "    p=plot(K_lim,Kp_g,linestyle=:solid,lab=\"Good\")\n",
    "    plot!(p,K_lim,Kp_b,linestyle=:solid,lab=\"Bad\")\n",
    "    plot!(p,K_lim,K_lim,color=:black,linestyle=:dash,lab=\"45 degree\",width=0.5)\n",
    "    title!(p,\"FIG1: Tomorrow's vs. today's aggregate capital\")\n",
    "    p\n",
    "end\n",
    "\n",
    "function plot_Fig2(ksp,kss,K_eval_point)\n",
    "    k_lim=collect(linspace(0,80,1000))\n",
    "    itp_e=interpolate((ksp.k_grid,ksp.K_grid),kss.k_opt[:,:,1],Gridded(Linear()))\n",
    "    itp_u=interpolate((ksp.k_grid,ksp.K_grid),kss.k_opt[:,:,3],Gridded(Linear()))\n",
    "    \n",
    "    kp_e(k)=itp_e[k,K_eval_point]\n",
    "    kp_u(k)=itp_u[k,K_eval_point]\n",
    "    \n",
    "    p=plot(k_lim,kp_e.(k_lim),linestyle=:solid,lab=\"employed\")\n",
    "    plot!(p,k_lim,kp_u.(k_lim),linestyle=:solid,lab=\"unemployed\")\n",
    "    plot!(p,k_lim,k_lim,color=:black,linestyle=:dash,lab=\"45 degree\",width=0.5)\n",
    "    title!(p,\"FIG2: Individual policy function \\n at K=$K_eval_point when good state\")\n",
    "    p\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, plot the replication figure:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figure 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img 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\" />"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_Fig1(ksp,kss,K_ts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figure 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img 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tePFixf4+/vj5eWVaSxjx45l6NChNG7cmO7du6NWq9m/f3+miYG7uzvu7u78/vvvPHr0iEaNGnHv3j127dpFhw4d8m3xx+bNm7NkyRLCwsJo1KgRERERbN26FVNTU50xTgBLliyhWbNmDBkyhN27d1OzZk0uX77Mrl27KF26NEuWLMlzHIsXL+bSpUvMmDGDffv20apVK4QQ3Lhxgz///JMnT55kWKfqP//5D4MHDwbyr/cKwM7Ojt69e+Pn50e9evVo27YtUVFRbN++nXbt2uXLudfneFu1asXvv/9Oly5dcHNzw8DAgE6dOlG7du1M21YqlaxduxZvb2/at29P9+7dcXBwIDQ0lODgYKpUqcLs2bPf+hgkKU8KZe6i9K+kmbae23VmMlum4XVBQUGiX79+onLlysLU1FQYGRkJOzs70a5dO7F48WKdqe1C/G8qfXY/b05Xz+91sIKCgjLUz2qqfHp6upg1a5aoXLmyMDIyEpUrVxYzZ84Ut27dyvUyDa9r06aNAISJiUmGc5NTGwkJCWL8+PGifPnywtjYWNSsWVMsX748y6n8QrxaM6pq1aqiWLFiomLFimLSpEkiNTU106n4UVFRYtCgQcLOzk6YmJgIFxcXsWjRIhEeHp6nY33d68slXLp0SbRv315YWloKMzMz0aZNG+3yDG+KiIgQAwcOFLa2tsLQ0FDY2tqKgQMHioiIiAx19VkHSwghYmJixMSJE0WNGjWEsbGxsLKyEq6urtpz9KaEhARhbGwsTE1NxcuXL3N13K/LapkGIV6txTZq1ChRtmxZYWxsLGrXri02bdqU7TINWS2lkNV+cnu8jx49Ej169BA2NjZCqVTq/F5kd6/9888/olu3bsLGxkYUK1ZMODg4iNGjR4unT5/qdS70ua8kKScKId4YZCBJkvQBiYiIoFKlSu+8FzI/nT59mgYNGtCvXz/Wr19f2OFIkpQLcgyWJElSEffTTz8BMHz48EKORJKk3JJjsCRJkoqge/fu4efnx+XLl/n999/x9vamcePGhR2WJEm5JBMsSZKkIig8PJzvv/8ec3NzPv74Y5YvX17YIUmSpAc5BkuSJEmSJCmfyTFYkiRJkiRJ+UwmWJIkSZIkSflMJliSJBW6iIgIFAoFAwYMKOxQPjiOjo44OjoWdhiS9K8jEyxJykZev/g1n2vbtm2m2+fPn49SqaRixYpcv349HyLN3JYtW1AoFNrXoWQmJSWFqVOnUrVqVUxMTLCzs2Po0KFERUUVWFzS+y04OBiFQsHkyZPzpb2WLVuiUCjypS1JKipkgiVJ79ikSZMYM2YM1atX5/jx4wX2ItrHjx/z1VdfYWZmlmUdtVpN586d8fX1xcbGhjFjxtC4cWNWrlxJ48aNefr0aYHEJkmS9KGTCZYkvSNCCEaMGMG0adOoX78+R48ezdMLg3Nr6NChWFhY8J///CfLOuvWrSMwMJDevXsTEhLC7NmzCQgIYPHixYSHh+Pj41Ng8UmSJH3IZIIl/ets376d3r174+TkRPHixbGysqJ58+YEBATo1Fu7di2VKlUCXiUimkdtCoWC4OBgvfaZlpZG3759WbRoEa1ateLvv//GxsYmvw4pg7Vr17J7925WrlyJubl5lvVWrFgBwKxZs3Qe0QwbNozKlSuzadMmkpKSst2XWq2mVKlSODs765S/ePECpVKJQqHg4MGDOtsGDBiAQqHg7t27Gdq7desWn3zyCSVKlMDMzIw2bdpw4cKFTPcdFRXF119/jZOTE8bGxtjY2NC1a1cuXbqUoa5mLFJ8fDyjR4/Gzs4OY2NjateurfdLjRMTExk/fjz29vaYmJjg7OzMihUrsn10dvz4cTp06EDJkiUxMTGhRo0a+Pr6kpiYmOk+9K2/c+dOGjRogKmpKWXLlmXIkCG8fPlSr+NSq9WsXLkSd3d3SpYsiampKRUqVODjjz/W3vOTJ0/G09MTgClTpuj8XkRERABw48YNxo8fT926dSlVqhQmJiZUq1aNCRMmEB8fr7NPhULB4cOHtX/W/Lz5WP6ff/6hV69e2NraYmRkhIODAyNHjuT58+d6HaMkvStyoVHpX+f777/HyMiIZs2aYWtry9OnT9m1axfdunVjwYIFjBw5EgBXV1dGjx7N/PnzqVOnDl26dNG2oc+g4aSkJLp168a+ffv45JNP8Pf3x9jYOL8PS+v+/fuMGTOGoUOH0rp1a44ePZppveTkZMLCwqhevToODg462xQKBR999BHLli3j9OnTNG/ePMv9KZVKPDw82L59O1FRUZQpUwaAw4cPo1lmLygoiDZt2mg/ExQURKVKlTLsNyIigkaNGlGrVi0GDRrE7du32blzJ56enly9epWyZctq696+fZuWLVvy4MEDvLy86NKlC1FRUQQEBBAYGMihQ4do2LChTvtpaWl4eXnx8uVLunbtSmJiIps3b6ZHjx4cOHAALy+vHM+vSqWiY8eOBAUF4eLiQp8+fXjx4gVjx46lZcuWmX5m69at9O7dG2NjY3r27EmZMmX4888/mTp1KoGBgQQHB2NiYpLn+uvXr6d///5YWlrSr18/rK2t2bNnD23atCE1NRUjI6Mcjwte/W7897//pUqVKvTp0wcLCwsePnzIsWPHOHjwIC1btqRly5ZERESwbt06PDw8dI7Z2toagG3btrFq1So8PT1p2bIlarWaEydOMGfOHA4fPsyRI0coVqwYAL6+vqxdu5a7d+/i6+urbcvV1VX75127dtGjRw+USiWdO3fG3t6eK1eusHDhQgIDAwkLC6NEiRK5OkZJemcK803TklQYbt++naEsLi5OuLi4CCsrK5GQkKAtv3PnjgBE//799dqH5nONGzcWzZo1E4AYNGiQSE9Pz/Yzvr6+ev28Sa1Wi48++kjY29uL2NhYIYQQvr6+AhD+/v46dS9duiQA0bFjx0zj+fnnnwUgVq1alePxLliwQABiy5Yt2rKRI0cKMzMz0ahRI9G4cWNt+e3bt7Xn483zBYjZs2frtO3j4yMAMWvWLJ3yJk2aCAMDA3HgwAGd8uvXrwsLCwvh4uKiU+7g4CAA0blzZ5GSkqItP3jwoACEt7d3jscphBArV64UgGjXrp3O9bx8+bIwMTERgM61iYmJEVZWVsLY2FhcuHBBW65SqUTPnj0FIKZOnfpW9S0tLYWZmZm4fv26tjw1NVW0aNFCAMLBwSFXx1ayZElhZ2en8zug8fz5c+2fg4KCMhzn6x48eKBzjjWmTJkiALFx40adcg8PD5HV19GzZ8+EpaWlKF++vIiIiNDZ5u/vLwAxYsSInA5Nkt45mWBJ0v/3yy+/CEAEBwdry942wdL8vJ5gZEXzpaXPz5sWL14sAJ2kI6sE6/jx4wIQn332WabxLF++XABi7ty5OcZ+8eJFAYhhw4Zpy5ydnYW3t7eYNGmSMDQ0FHFxcUKI/yUo69ev19bVnK9KlSoJlUql07Zm26effqotO3v2bIYk7XXffPONAMTFixe1ZZoEKzw8PEN9BwcHUbJkyRyPUwghWrZsKQBx9uzZDNuGDh2aIfFYv369AMTw4cMz1L97964wNDQUlStXznP9devWCUCMHDkyQ/2jR4/qnWA5OjqK5OTkbOvllGBl5fnz5wIQAwYM0CnPLsGaO3duhvvldXXr1hU2NjZ6xSFJ74J8RCj960RFRTF79mz279/P3bt3M4wxioyMzLd91axZk+joaEJDQ5k6dSqTJk3Ksm7Lli21j9TyIjw8nG+//ZZBgwbh7e2d53byolatWpQuXZqgoCAAnj59yuXLl+nXrx/u7u5MnTqVo0eP0q5dO20dzTie17m6uqJU6g4NrVChAgDR0dHashMnTgDw5MmTTMc7Xbt2Tfvf18eGWVtba8fVvbmP0NDQXB3rhQsXMDMzw83NLcO2pk2bZnhn4Llz5wAyfXxYsWJFKleuzI0bN4iLi8PCwkLv+prxaZk9xm3cuDGGhrn/33yvXr1YvHgxzs7O9OrVC09PTxo3boypqWmu24BXEzrWrFnD2rVruXTpEjExMajVau12fX7HNNc6LCyM27dvZ9ienJzMs2fPePbsWYGOa5QkfckES/pXefHiBQ0aNODevXs0bdqUNm3aYG1tjYGBAefPn2fnzp2kpKTk2/7s7e21Y4h8fX1RqVRMmTIl39p/3eDBg7G2tmbu3Lm5qm9lZQVATExMpttjY2N16mVHoVDQsmVLtm7dSmRkJMePH0cIQatWrXBxccHExISgoCDatWtHcHAwTk5O2sTpdZaWlhnKNAmCSqXSlr148QKAvXv3snfv3izjSkhI0Pl7VsdiaGiokwBkJzY2NsvZn6+PEXu9flbbAGxtbblx4waxsbFYWFjoXV9z/TRj315nYGBAqVKlcj6o/2/+/PlUqlSJNWvWMH36dKZPn46JiQk9evTgl19+yXUCM2rUKBYuXIi9vT2dOnXC1tZWO+5wypQpev2Oaa71okWLsq2XkJAgEyypSJEJlvSvsmrVKu7du8e0adMyLEEwe/Zsdu7cme/7dHJy4vDhw3h6ejJ16lRUKhXTp0/PUC8iIoK1a9fq1fbrvTfnzp0jJiZGO9D4Tb1796Z3797MmzePMWPGULlyZZRKJTdv3sy0vqa8atWquYrF09OTrVu3EhQUREhICFZWVri5uWFgYEDjxo0JCgri5s2bPHz4kCFDhuh1nG/SJGK//fYbI0aMeKu28rLvrNYHe/LkSab1s9oGr9Yre72evvU1SWNmC8OqVCqeP39O+fLlMz+YNxgaGjJu3DjGjRtHZGQkhw8fZs2aNaxfv57Hjx8TGBiYYxtRUVEsWrSI2rVrExoaSvHixXVi1/cfGJrjvHjxYoaZqpJUlMkES/pX0Txi6Ny5c4Ztmc22MzAwAHR7T/KicuXKBAcH4+npyYwZM1CpVMyaNUunTkREhN5fPq8nWJ9//nmmU/jPnj3LuXPn8PT0pHLlytovKVNTU9zd3Tlx4gR3797VmdEnhOCvv/7CzMyM+vXr5yoWzSO/v//+m9DQUDw8PLTnr1WrVkyePJnt27cDmT/+0odmdmBoaOg7T7Dq1KlDcHAw58+f15npBhASEpKhvuZRYnBwMD169NDZdv/+fW7fvk3lypWxsLDIU/06deoAr+7f7t2769QPDQ0lPT09T8dpZ2dH79696dmzJ9WrV+fgwYMkJSVhamqa7e9FeHg4QgjatGmjk1xpYszM6+1p/qzRsGFDtm3bRmhoqEywpPdLoY4Ak6R3bObMmQIQixcv1inftGmTduD4mjVrtOVxcXFCoVAIDw8PvfajGZj95sy0iIgIUalSJQGIb7/9Nq+HoZesBrkLIcTq1asFIHr37i3UarW2fMmSJQIQQ4cO1Wtf5cqVE6VLlxaA+PXXX7Xlx44dE4B2W2RkpM7ncppMAGS4Bg0bNhQKhUJs3rw5Q32VSqUzWUGIVwPZsxrsnd0g6zetWLFCAKJDhw46A/KvXr2a7SxCExMTcenSJW25Wq0WvXv3znIWYW7rR0dHZzmLUHNcuRnknpycLI4fP56hPDY2VpQrV04YGxtrB79rZqBmdr0iIyMFIBo1aqRzfu7fvy+qVKmS6bXs1q2bAMSdO3cytBcVFSUsLCxE6dKldc6HRkJCgggNDc3x+CTpXZM9WNK/Sr9+/ZgzZw4jR44kKCgIBwcHLly4wKFDh/j000/Ztm2bTn1zc3MaNGjAkSNH6NevH1WrVkWpVNKvX78MazjlhoODg/Zx4U8//YRKpeKXX37Jr8PTW//+/dmyZQv+/v7cuXMHDw8Pbt26xbZt26hUqVKmjzKz4+npib+/v/bPGu7u7piZmfH06VOqV6+Ora3tW8fu7++Pp6cnvXr14tdff6Vu3bqYmppy7949QkNDefr0KcnJyW+9nzcNHDiQDRs2sHfvXtzc3GjXrh0vXrxg8+bNfPTRR+zevVtnoL6lpSUrVqygd+/eNGzYkJ49e1K6dGkOHjzImTNncHd359tvv81zfSsrKxYsWMCAAQNo0KABvXr1wsrKij179mBqaprrc52UlETTpk2pVq0rqe6GAAAgAElEQVQa9erVo2LFisTHx7Nnzx4eP37MuHHjtOOoatSogZ2dHZs3b8bY2JgKFSqgUCgYOXIktra2dO3alYCAAOrXr0/r1q158uQJe/bsoXXr1pkOVG/VqhV//PEHXbt2pV27dpiYmFCnTh0+/vhjSpcujb+/P927d6dOnTq0bduWGjVqkJKSQkREBIcPH6ZJkyYcOHAgr5dUkgpGYWd4kvSunT9/Xnh5eYkSJUoICwsL4eHhIQ4ePCjWrFmToQdLiFfrKrVv315YW1sLhUIhABEUFJTtPrLqwdJ48OCBqFq1qgDE6NGj8+nIMpddD5YQr3ouJk+eLKpUqSKMjIxEuXLlxBdffCEeP36s9740SzvY2Njo9IgJIYSXl1eGpRw08tKDJYQQL168ED4+PsLZ2VmYmpoKc3NzUbVqVdGnTx+xbds2nbr51YMlhBDx8fFi7Nixws7OThgbG4uaNWuK5cuXiz/++EMAYt68eRk+c+TIEdGuXTthbW0tjIyMRLVq1cTEiRNFfHx8pvvQt/727dtFvXr1hLGxsShTpoz44osvxIsXL7I97telpqaKOXPmCC8vL1GhQgVhZGQkypYtK1q0aCH8/PwyXM8TJ04IDw8PYWFhoe391fRAxcXFibFjxwpHR0dhbGwsqlatKqZNmyZSU1MzvZZpaWli/PjxomLFisLQ0DDTe+HatWti8ODBwsHBQRgZGYkSJUoIFxcXMWrUKHHy5Mkcj0+S3jWFEG8xL1ySJEnS8vHxYcaMGezbt4927doVdjiSJBUimWBJkiTp6dGjRxkevV25coVGjRphYGBAZGSk3mtHSZL0YZFjsCRJkvQ0fPhwIiIicHd3p0SJEty+fZvdu3eTlpbGqlWrZHIlSZLswZIkSdLXpk2bWLp0KVevXiUmJkY7GWLs2LHvfBV9SZKKJplgSZIkSZIk5TNlzlUkSZIkSZIkfcgES5IkSZIkKZ/JBEuSJEmSJCmfFegsQrVaTWRkJBYWFigUioLclSRJkiRJ0jshhCAuLg47OzudNze8rkATrMjISOzt7QtyF5IkSZIkSYXi/v37VKhQIdNtBZpgad72fuXKFcqXL1+Qu5I+ILGxsdjb23P//n0sLS0LOxzpPSHvGykv5H0j5cb1l4IJp1T8fe0JZfZ9T/MqpQjYuFqb52SmQBMszWNBCwsLeeNKerO0tJT3jaQ3ed9IeSHvGykzMamCqWfVLLikpqI5bPnUkDrd52BmZkbAxtXZDn+SK7lLkiRJkiS9Ri0E628KvgtLJ+ZsIJP7tWVsbUNMDC0BSx48eJBjG4WaYKWmpnL37l1UKlVhhiHlwMDAAAcHB4yMjAo7FEmSJEkqUCej1IwMUXPy3AXsAifxdbtmjHdpSzFD/SbrFVqC9eDBA/r06UNiYmJhhSDpoXjx4vj7+8uxdJIkSdIH6Umi4IdTKlafe06pwCl4W8SzKmB5nr/3CiXBUqvVTJ06FWtraxYsWICJiUlhhCHlUnJyMhMnTmTKlCksXbo0yympkiRJkvS+SVMLFl1WM+lUGqqjq6lxYztLZ03Co0Xzt2q3UBKsZ8+ecfbsWWbMmIGrq2thhCDpacSIEfz44488f/6c0qVLF3Y4kiRJkvTWDj5UMypExfUYqLFnDIPauDJm5QEMDAzeuu1CSbCio6MBslw7Qip6NNfq5cuXMsGSJEmS3msRcYKxJ1RsixA0L6fAr5UBdQYvyddF0QvlWY9arQbIlwxRejc010pz7SRJkiTpfZOYLvA9o6KGXwIHV81hrHovhzsa4FpKke9vnJGDad6R4ODgd/o4tH79+gQHB7+z/UmSJElSUSWE4I9wNTV+T2Pmut2UW/Exv3Vy4qehnfVOrFQxz0nevTzHenIdLEmSJEmSPliXXwhGhar4++w1yh2YyLCmzsw5vAczMzO92hHpacQf2UFsoB/p6SLH+rIH6zWnTp2iVatW1K9fHzc3N7Zu3UpERATW1tZMnDiRunXrUrVqVY4fP87XX3+Nq6srzs7OXLp0CXjVS+Xs7Mznn3+Os7Mz9erV4/z585nua8OGDdSuXZvatWvToUMHHj58CICLiwshISHaesuXL6dnz54APH78mB49euDu7o6Liws+Pj7aeiEhIdp4Bg4cSHp6ekGdJkmSJEkq8qJTBKNDVNTe9IJzy76j+cmphGycy8L/TtM7uUq+eponc/5DzJ41mDX0wmz4nBw/U2R6sMJjBdGpBdO2tRFUtsy+CzA6OpqhQ4eyb98+bG1tefbsGXXr1sXf35+YmBjq1avHtGnTWLVqFd7e3uzevZt58+bx008/MWXKFLZu3QrA5cuXmT9/PuvXr+f333+nV69eXL16VWdfly5d4ttvv+XMmTOUL1+eGTNm8MUXX7B//35GjRrFwoULadKkCQCLFi1i4cKFAPTv358ffvgBDw8P0tPT6dixI1u3bqVz58707NmTNWvW0KZNG/7880/Wrl2b/ydSkiRJkoo4lVqw5obg+1MqklXwH+trtB/uRYd23nq3lf40kugdy0i+HIZx1TqUGjSRYraOxBf1ldw1niULqv6ejjrnHrc8MVDA476G2JhknWSFhIQQHh5Ou3btdMqvX7+OiYkJXbp0AV6NbTI3N8fT0xMAd3d3Nm3apK3v6OhI69atAejRowdDhw7l/v37Om0GBQXRtm1b7eJlX375JVOnTkWlUtG3b18mTZrEkydPuHnzJgqFgubNm5OQkMChQ4d48uSJtp34+HiuX7/OtWvXMDQ0pE2bNgB4eXlRuXLlvJ4uSZIkSXovhT55tQr7mTtP6edWmtnuBtiZNdW7HXVKEnEHtxD3dwAGliUoOeBHTOs002u8VpFIsGxMFNzsYVigPVjZJVfwagBcrVq1dB7PAURERGBsbKz9u4GBgc7CqAYGBtk+jlMocp6Z8Pp2U1NTBgwYwLJly7h69SpfffWVNj6AEydOZFiY9Z9//sm2TUmSJEn6kD1OFHx3UsX6M08oFehLt4rFWf/NAr3bEUKQdDaYmF2rUCXEYNGmBxatu6M00n9B9CKRYEHOj/AKWpMmTbhz5w4HDx7U9gSdP3+e4sWL69VOREQEQUFBeHp68scff1C2bFkqVKjA7du3tXU8PT2ZMWMGkZGR2NnZsXTpUlq3bq1dCuGrr76iUaNGpKWlsWrVKgBtr9ns2bOZPHkyAJGRkajVamrUqEF6erp2vwcPHtTZnyRJkiR9iFJVggWX1Uw5mYI6eBk1I/az8udpNG7UUP+2HoYTHbCY1PBLmNZuilXnIRiWKpfn2AwBnj9/rn2sBZCYmEh4eDhRUVF8+umn3L17FysrK+DVOKCvv/46zzssqkqUKMHevXsZN24cY8eOJS0tjYoVK/Lrr7/q1U6tWrVYu3Yto0aNwsjICH9//wy9Sc7Ozvz000+0bdsWAHt7e1asWKHdXqFCBdzc3KhWrZpOgrdp0ya++eYbnJ2dUSgUmJmZsWzZMipUqMCWLVv48ssvUalUNGjQgDp16rzF2ZAkSZKkoi3wvprRoSpuhAVR/sgcJgzty/D1B/R+nZsqIZbY/etJOL4PwzIVsBk+E5Pqdd86PkOAUqVK6cx2+/nnnzl8+DAlS5YEYN68edoxSB+yunXr8vfff2co16w8D6+So4iICO3fmzVrpp1FCGBoaMi6desytNGyZUudc9yvXz/69euXaRwJCQmcO3eOBQt0uzfLlCnDxo0bM/1MkyZNspyxKEmSJEkfivBYwdcnVOy6k04Z/4H0q2XLgoPbtB1BuSXUKhJC9hO7bx1CrcKq8xeYN++EwiB/Hu5l2sqqVauYNWtWvuxA0s/SpUuZMWMGX375JZUqVSrscCRJkiSpSEhIE8w6r+bni2rKmMDvHxnRvPM8ypXT/zFeyu1LRAcsJi0ynOLuXlh9PBADixL5Gm+GBCskJISXL1/SsWNHbdn48eOZOHEiNWvWZNasWVnOUEtJSSElJUX799jYWADi4uK0f4ZXs9/UajUqlQqVSpVvB1PYmjdvzpkzZ97qmIYMGcKQIUMAitS5UalUqNVq4uPjda5lQdC0X9D7kT4s8r6R8kLeN0WfELDtvgE+5wyICt3JQI+aTPnIATNDgOJ6XTt17AuSAzeQfvE4yvJOmA2diUEFJxIEoEc7cXFxOdZRCM30tP9v8ODBlCpViv/+978A3L9/H3t7e4QQLFq0iMWLF3PlypVMG5s8eTJTpkzJVXA2NjYsWbIER0fHXNWXCldERATDhw/n2bNnhR2KJEmS9G9R3gV6zQULG1jzBTy9DYnROX/uDUYGCoa4OTKyQWUS01XMPn6DrVciedvVoWJiYrC0tMx0m06CFR8fj62tLadOnaJGjRqZfsDExISHDx9SqlSpDNsy68Gyt7fnypUr2jWfAG7cuMHQoUPZsGFDlvuRipZr167Rr18/li9fTrVq1Qp0X5r75v79+1neuJL0JnnfSHkh75ui6UUKzLxUjJUX47DaP43axZ6yZPYkKlSooHdbadfPkLx/LSL6GUaN2mHcshsKE/1WCHjTw4cPqVmzZrYJls4jwi1btlCnTh1t0pOens7z588pW7YsAAEBAZQtWzbT5ArA2NhYZ80oDQsLC50AzM3NUSqVGBgYaJcmkIo2AwMDlEol5ubm7+x/QpaWlvJ/eJLe5H0j5YW8b4oGlVqw8rqaH8LSSDi8Dqerv7N45kTatGqpd1tpUQ+I2bGM5CunMK7mhvXQaRQrVzFf4szNY0mdBGvVqlXa8T/wqkeqQ4cOpKSkoFQqsbGxYdeuXfkSnCRJkiRJksaxx2pGhqg4/xya3FhLx9rpfLsiEEND/Wb1qZMTif3Tn/jD2zGwKkWpQRMxcWnyzhfg1on6zVXMzczMOH369DsNSMqcQqHg5cuXWFtbF/i+xo0bh7m5uXZBU0mSJEkqKA8TXq3CvummmgZllJzorKRhmf/o3Y4QgsQzfxOzaxUiKQFLr95YeHZDYZTxydq7UGRWcpckSZIk6d8jRSX49aKaqaeSURz6jY9LJbJj4RSUeehpSr1/k+htS0i9cwVT1+ZYdfoCw5JlCyDq3NNvudMPnEKh0FlU1MbGRruoqKOjI5MmTaJx48ZUqlSJ6dOna+s9fvyYHj164O7ujouLCz4+Ptptjo6O+Pj40KRJE+zt7Vm6dClr1qyhcePGODo6snnzZp39+/j4aFdxf/0l0q87ffo0TZo0oXbt2ri7u3P8+HEARowYwcyZM7X1rl+/jr29Penp6aSlpTFhwgTc3d1xdXWlR48evHz5EoBHjx7h7e1NzZo1adOmDQ9y8ZZwSZIkScqrvffUOP+Rzg9r91Nq2cf82r4iO/OQXKniY3i5ZT5Rc0ehTk7E5qs5lBrwY6EnV1CEerDSnz1CnRRfIG0rTc0xtLF963aio6MJDQ3l2bNnVKlShYEDB1K+fHn69+/PDz/8gIeHB+np6XTs2JGtW7fSvXt34NXK7CEhIdy6dQsXFxd+/PFHQkNDOXXqFO3bt6dXr17afSgUCs6dO0d4eDj169enadOmOktZpKam8umnn7JixQq8vb05duwYXbt25datW4wcORJvb2++++47DAwMWLx4MUOHDsXQ0JCZM2diZmbGyZMnAZg2bRo+Pj4sWrSIUaNG4e7uTmBgIA8fPsTV1VXO7pQkSZLy3c0YwdehKvaeuUmZ/RMZ7F6VucG7MDc316sdoVKRELKXmH3rAbD+5D+YNe2IoghNnCsSCZYqPobHMwaDUBfMDpRKbKf6Y2Cu3zL6b+rTpw/wqmercuXK3LlzB2traw4dOsSTJ0+09eLj47l+/br27z179gTAyckJExMTunXrBkD9+vV58eIF0dHR2rFVX3zxBQCVK1emRYsWHDlyRCfBun79OkqlEm9vb+DVq3rKli3L+fPnadasGTVr1mTnzp14e3vj7+/PxYsXAdixYwcxMTEEBAQArxI1TbuHDh3i559/BqB8+fJ06tTprc6TJEmSJL0uPk0w/ZyaX07HUzxwJo3TbrNuzSyqVq2qd1vJNy8Qs20JaY/vYtaoLZYd+mNgXvDjk/VVJBIsA3Mryv24qkB7sHKTXBkYGOisnp6cnKyz3cTERKdueno6mmXETpw4obM9u89p/q5QKFAoFKSnp2cZU25mPbxeZ/To0cyZM4enT5/y0UcfaZfYEELw22+/4eXlpVd7kiRJkpRXQgj8bgvGh6l4kQLf1VHi7uhJp/Zz9G4r/WUUMTtXknT+CEaO/0eZbxZgZK9/gvauFJkxWIY2thjZVy2Qn9w+HnRyciIsLAyAbdu2kZCQkONnzM3N8fT0ZPbs2dqyyMjIPI9jWrNmDfBq5fSjR4/SvHlzne3Vq1dHrVbz119/Aa9mfj5+/BhXV1cAvLy8ePz4MdOnT2fEiBHaz3Xp0oV58+aRmJgIQGJiIpcvXwagTZs2rF69Gng1HksuxSFJkiS9rXPPBM13q+i76R8alRZc627I9KYWdGrfVq92RFoqsYGbeDJzCCnhFynx2ThKj/qlSCdXUER6sIqKefPmMWrUKHx8fOjQoUOWC6q+adOmTXzzzTc4OzujUCgwMzNj2bJleVpxVqVS4ebmRkJCAgsWLMjwKiEjIyO2bdvGqFGjGDt2LCYmJvzxxx/a59cKhYLBgwfj5+dH48aNtZ/77rvvSElJoWHDhtoequ+++45atWoxf/58BgwYQM2aNSlfvjytWrXSO25JkiRJAniWLPA5pWbZqShKHJiMd4kU1o1diLm5kV7tCCFIvhhK9M7lqKKfYe7RBUuvPijfchX2dyXDuwjzU2xsLFZWVty/f18n2bh27Rp9+/Zl48aNcjD1a/JrrauOHTvSs2dP+vXrl0+RvdtrprlvsnsFgSS9Sd43Ul7I+yb/pKsFy66q8TmZSvLfK3C4vZsVP02hedMmereV9uQ+0duWkHL9LMY16mP9yTCKlbUvgKjz5sGDB9jb2+f+VTnS++306dP06tWLmjVragfkS5IkSVJBO/xIzagQFf+EHsEueBYTB/Vk9NoDer8OT52cQGygH/GHd2BQogylvpiMSa2G7+XYYJlgFSFv25lYv359bt26lU/RSJIkSVL27scLvg1TsSVcUP6vyfQqEc+Sg3/o/SRGqNUknjpIzJ41iJRELNv1w6LlpyiK6fdYsSiRCZYkSZIkSXpJThf8clHNzPNqLIrBWg8DevSbiGkWs+mzk3rvOtEBS0i9ew3Tui2x6jQYQ+vSBRD1uyUTLEmSJEmSckUIwe57gjEh6dw9vpv2tmls+rYnlkYKQL/kShX3kpg9a0gM+5NidpUoPfInjKu4FEzghUAmWJIkSZIk5ehatGBMqIrAU1cpvd+HL1u6Mefr8RQ30m98lFClE390N7EHNqBQGmDdbQRmjdsVqVXY84NMsCRJkiRJylJsqmDaOTXzwl5iHjiDFoaPWec/P8MyQrmRfOMc0duWkP7kAWZN2mPZ/nMMzD7M2ZsywZIkSZIkKQO1EGy4KRh/Io2XwRtxuLSJhdN/oJ1XG73bSn/+mJidK0j65zhGlWtRZuwCjCo4FUDURUeRWcm9KFmzZg0KhYIdO3Zoy1q2bEmlSpVwdXXF1dWVefPm5aqtS5cu5SnLlyRJkqTCcvqpmqa7VAw4rKJO4gV+qBHHteOBeidX6tRkYvZv4PHsoaTcvUbJft9ReuTPH3xyBbIHK4OIiAhWrFhBo0aNMmybN28eXbp0KYSodKWnp2NoKC+dJEmSlL+ikgQ/nlKx8lIyLmWNCe5ogIetO+CuVztCCJL+OU7MjuWoYl9i4fkpFh/1QmlsWjCBF0GyB+s1arWaL774gt9++w1jY+M8tzN58mSqVq1KvXr12Lx5s862wMBAmjVrRr169XB3dycoKEi7zdfXFycnJxo0aICPj4+25ysiIgJra2u+++476taty8KFC0lLS2PChAm4u7vj6upKjx49ePnyJQBxcXEMGTIEd3d3ateuzdChQ0lNTc3z8UiSJEkftjS1YMElFVX9kti09FfqbP+cM10M8LDVP01IexTBs8Xf82LNdIrZVaLchGVYdRz4r0quQCZYOubOnUvTpk2pV69eptvHjx+Pi4sLPXv2JDw8PNM6e/fuZevWrZw5c4bTp08TERGh3RYeHs7kyZPZt28fZ86cwc/Pjz59+pCSksLevXsJCAjg3LlznDx5kocPH+q0GxMTQ61atTh79ixjxozhp59+wszMjJMnT3L+/HlcXFzw8fEBYOzYsTRv3pyTJ09y4cIF1Go18+fPz5+TJEmSJH1Q/n6oxm1bOqNX/Yn54o783KYMZwP/oJiBfimCOjGe6G1LefLTl6iin1Jq6FRshkzBsLRdAUVetBWZ50z+/v74+/tnuX3y5MnUrVsXgD///JOFCxdmWXfEiBF4eXkBcPbsWa5fv07v3r2z3f+lS5cICAjgyJEjmW7fsGED9vb2CCFYtGgRHTt25MqVKxnqHTp0iB49emjfTTRs2DCOHTsGwIEDB7h16xYtWrTQ1lcqldy7d49Dhw7RvXt3LCwsABg8eLBO71axYsXo27ev9u87duwgJiaGgIAAAFJTU7U9Xjt27CA0NJS5c+cCkJSUpPfrCiRJkqQP2904wdgwFQEnb1Nq30T613Xkt+Cd2u+h3BJqNYkn/3y1CntaKlYdBmLu0RmF4fu7Cnt+KDIJVu/evXNMgjS8vLy0CVRO6tatq03MsnP06FEiIiKoWrUqAI8fP2bo0KE8evSI4cOHY2//6iWTCoWCESNGMG7cOJ4/f06pUqWybff19ycJIfjoo4/w8/PLMZ4337tUvHhxlMr//WtCCMFvv/2W6XkQQhAQEEC1atVy3I8kSZL075KULvjvBTWzzqsotncaDRIus2HVLKpXr653WykRV4kOWEza/ZsUr98Kq48HY2CV/ffiv4V8RPj/DR8+nEePHhEREUFERASNGjVi+fLlDB8+nPT0dJ48eaKtGxAQQNmyZTNNrtq0acPWrVuJi4tDCMHy5cu127y9vTl48CD//POPtuzkyZMAtGrVioCAAOLj4xFCsHr16mzj7dKlC/PmzSMxMRGAxMRELl++rN02Z84c0tPTAXj58qV8R6EkSdK/nBCCbXfU/N/WdGacVzPGxYC/fLoTdiBA7+RKFfuCF5t+5umvX4NQU3rUL5TsO14mV68pMj1YRVlKSgodOnQgJSUFpVKJjY0Nu3btyrRu+/btOXnyJHXr1sXS0pJ27dpptzk5OeHn58ewYcNITEwkNTUVNzc3/Pz86NixI2FhYbi6umJtbY2Hh0e2L8v87rvvSElJoWHD/71l/LvvvqNWrVrMmzePCRMm4OrqilKpxNDQkP/+9784OX3402IlSZKkjK68FIwOVXEw7B88HMz4q1s1qlopgNp6tSPS04g/spPYQD8UhoZY9xiFWSNvFEo5DOVNCiGEKKjGY2NjsbKy4v79+1SoUEFbfu3aNfr27cvGjRupUaNGQe3+vRMXF4eFhQVCCMaOHUtSUhJLliwp7LCAd3vNNPdNTEyMdiybJOVE3jdSXnzo901MqmDyGTULTj7DYv9U6prFsvG3OdjZ6T/wPPnqaaK3LyX9aSRmzTpi1a4fyuL6jdf6UDx48AB7e/ts7xvZg1WEfP7550RERJCcnEytWrVYunRpYYckSZIkvYfUQrD2hmBCWCoxh1ZT+fo2ls3xpZVHc73bSn/2iOgdy0i+dAKjKi6UGfADRnaVCyDqD4tMsIqQ7du3F3YIkiRJ0nsuLErNyBA1p0KPU+7QdKZ+3pVxqwP1nk2uTkkm7uBm4oICMDC3omT/HzB1bZ5hEpaUOZlgSZIkSdIH4EmiYMIpFWtvCByubeXT6BBW/LmFkiVL6tWOEIKkc0eI2bUCVXwMFq26YdG6J0pjkwKK/MNUKAmWZrmBtLS0wti9lAeaa/X6UhGSJElS4UtTC367pGbKWTWGSljSVMkXg3phaNBH77ZSI8OJDlhC6u2LmLg0oXTnIRja2BZA1B++Qkmw7OzsMDIyYsWKFQwZMoRixYoVRhhSLqWlpbFixQqMjIzyNDBSkiRJKhh/PVAzKlTF9aP7cHtxnL9WzqGkif6P8NQJccTsX0/C8b0YlrbD5j8zMKmR+VtNpNwplATL3NycuXPn8s033xASElIYIUh6MjIyYu7cuZibmxd2KJIkSf964bGCsSdU7Dh5nVJ7ffiiaS3mLfPFTM/kSqhVJIQeIHbfOkR6OladBmPevBMKQ9nx8bYKbQxWo0aN+PPPP4mMjEStVhdWGFIuKJVK7OzsZHIlSZJUyBLTBbPPq5kTFoPRgZk0Ut9j48afqVKlit5tpYRfIjpgCWkPb1Pc/SOsOg7EwFK/8VpS1gp1kLu5ubl8nYskSZIk5UAIwdZwwdjQNB4F+2F/YQPzp3xHp/beerelin5GzO5VJJ4Joph9VUqPmYex4/8VQNT/bnIWoSRJkiQVYRdfCEaFqAh+JOhQLpUhNZP4fkmg3uOXRXoqccE7iPvTD4WRMSV6fU1x949QyMlLBUImWJIkSZJUBL1MEfieUbMoLIoqtiXY39aItvYWwJd6t5V0OYyY7ctIf/EY8+adsfT+DGVxOeyjIMkES5IkSZKKEJVasOq64PvQZOIPLcPpzn7+2rqOiuX1Xy4h7elDYrYvI/nKSYyruVLqC1+KlXMogKilN8kES5IkSZKKiJAnakaGqDh7LIhyQbOZPbQvozcc0HsNQnVKEnF/+hMXvA0Dy5KUGuiDSe2mchX2d0gmWJIkSZJUyB4lCsaHqdgYFkGJvT70qmXH0qDtWFlZ6dWOEIKkM0FE716FOjEOy496Yd6qG0ojuQr7uyYTLEmSJEkqJKkqwfxLaqaeU8ORVbje28+GpbNwrlVT/7Ye3CI6YDGpd65gWqcZVp2HYFiybAFELeWGTLAkSZIkqRDsv69mTKiK27HwVU0lIwsyCtEAACAASURBVD/qShW7YXo/xlPFxxC7bx0JofsxLGuPzZezMKnmVkBRS7klEyxJkiRJeoduxQi+PqFiz4nL1Eq+zvlvu+NcUgGU1qsdoVKRELKXmP3rQS2w6jIM82YdURjIr/aiQF4FSZIkSXoH4tMEM8+r+fnEC0z2T6e50TM2zJ+JQ0n9B56n3PqH6G1LSHsUQfGGXlh1GIiBhXX+By3lmUywJEmSJKkACSHYfFsw7kQaUYfWYX9lC4tn+tC2tafebaW/fErMrpUknTuMkUMNynz9K0YVqxdA1NLbkgmWJEmSJBWQC88FI0NUHD0eSpmD0/Dp3YkfVwRiaKjf169ISyUuKIC4g5tRGBenRJ+xFK/fWq7CXoTJBEuSJEmS8tnzZMHE02qWXVNTKTmcjg83seaAHzY2Nnq1I4Qg+fIJorcvR/UyCnOPLlh690FpYlZAkUv5RSZYkiRJkpRPVGrB8mtqfjylQiUU/NxQyYha1Sg2YqnebaU9uU/09qWkXDuDcfW62AydSrGy9gUQtVQQZIIlSZIkSfngyCM1o0JUXDgSSIWTiwnZvx17a/1eyAygTk4gNtCP+MM7MChRmlKDfTFxbiRXYX/PyARLkiRJkt7Cg3jB+JMq/ENvUXLfRPrXd2LhX79jbm6sVztCrSbx9CFidq9GJCdi2fYzLDy7oShmVECRSwVJJliSJEmSlAcpKsHci2qmh8bCgTn/j737jJKiTt8+/u3uyREmkJEkIAiCIiiCIAaUoGDOmNBdXQEVFAOIKElFzBIUQUQRlZyGjMAMYcgZJEdJ0j09ebrq97xg/z4bcKWUhgnX55w6B5C5z9VaO3NtV/VdXJm3k29GD6RWzZqOZ+Xv33F6C/u+bURe3pL42zoTUtrZXiwpXFSwREREHDDGMGO/4bnlFnsWfE/F1SN5r3d37u4wyPEsy+/FN2MU2SvmEFquCsnPvkP4xZcFIbWcbypYIiIiZ2mH93SxmnXAcGNFF6/cnMzDH6cQFubsMp6xAmQunU7GrK/B7aLUHU8TfU07XB5PkJLL+aaCJSIi8gf8+YZ+a22GLD9OOVcmE2+tTseqLlyu1o5n5e5Yh3fiUAJH9xPdtA1xbR/BExMfhNRyIalgiYiI/A5jDGN3Gl5My+PXuV9QZedUvvn0Xa6q5nzBZ+DXo/imfE7O+qWEVatLmRc+Iqyy8/u1pGhQwRIRETmDNSdOb2FPW/wTZRYO5K3H7qXHVyl4HF7GM/l5+Bf8QMb873FHxlD6oReJanS91i4UcypYIiIi/+J4jqHXKpsRafuIn9GbO2ol8cW8HyhdurSjOcYYcjek4p08AivjV2Kvu4PYm+7DHREVpORSmKhgiYiIAAHbMHSLzeurbQq2LqLeio/4+pMBNLysvuNZBUf2nt7CvmMdEXWbkPTMQEKTK5770FJoqWCJiEiJt/iom1fmBNh8Cjpf4uKN21tSPvZGx5fx7OxMMlLGkrl0KiEJ5Uh8si+Rl14VpNRSmKlgiYhIiXUgywVPfcut4/ZQcdM40j/tT6Nk5/dGGdsme+UcfNNHYfLziGv7KLHXdcQVoi3sJZUKloiIlDg5AcPgDTYDluXBtoU03j+R7z57h+p/olzl7d2Kd8JnFBz4magrryf+1ifwxCcGIbUUJSpYIiJSYhhjmLzX8HxaAQfnj6X8+q85uHEF804cJS4uztEsy3cS3/RRZKfPI7RSDZK7vkd49UuDlFyKGhUsEREpEbaeMnRbZjE3NZ2k2W/Q8642vPDuBJKSkhzNMYECMhdPIWP2t7hCQih1T1eir74Zl1tb2OX/U8ESEZFizZdv6Lva5uPNNhdFW9x1agqfzBhD2bJlycjIcDQrd+uq01vYTxwhpnl74to8jDsqNkjJpShTwRIRkWLJNobROwwvL8slM+DizSvDeKF+COH3O38oc+DEYbyTR5C7aTnhF19G4mO9CK1QLQippbhQwRIRkWJnxTGbLmk26T/No+zid5k54hOua1jH8Rw7Lxf/vO/wL5iAJ7YUCY++SmSDa7WFXf6QCpaIiBQbR7MNL6dbjE7bTanpvbi/YVWGL5pMbKyzy3jGGHLW/oRvyhdYWT5ib7ib2BvuwR0eEaTkUtyoYImISJGXbxk+2WzzxrJMCma9Q8OsrXw7ciB1LqntfNah3XgnfEb+7k1EXHYNyR2eIiSxXBBSS3GmgiUiIkXanIM23ZZZbE+bS4Ulg3n31ee57/Z+ji/jWVkZZMwcQ1baTELKVCLp6QFE1L4iSKmluFPBEhGRIml3huGF5RZT9hlalHMx+KHa3DBwJhERzi7juV2Qv3IOmQvGY2yL+A6dibn2Nlwe/YiUP09nj4iIFClZBYZB623eSTtB3OHVfPfkLdxT3YXLVcPxrMDeLcy8vym5078g6qrWxLd/DE9s6SCklpJGBUtERIoEYwzf7zZ0X5bP0TlfUnn7RIa/3Yebargdzwp4j+Ob8gU5a38i37KJfmoApevqcqCcOypYIiJS6G04aei6zOKnJakkz+tHn4fu4JVRs/F4nG1PNwX5+BdNxD93HK6wSCJuf4YO13XAO+LiICWXkkoFS0RECq1fcw2vr7b5LO0AsdN7c2u1OEbPHU9CQoKjOcYYcjcvxztpBNapY8S06EDczQ+SWWBhgpRdSjYVLBERKXQs2/DFdpvX0m1yfSeoM6MLYz7oR6PLGzieVXD0AN5Jw8nbtorw2leQ9GRfQstd9M9/6OxROSJnSwVLREQKlaW/2HRJs1h3Eh6t5WJg43KU6zLN8Rw7N4uM2d+S+dNkPKWTSXyiDxH1rtYWdjkvVLBERKRQOJRleGmFxbdpO0iY/SbzRw/j+hqlHM8xtk32qvn4pn2Jyc0m7pYHiW11F67QsCCkFjkzFSwREbmg8izD+xtt3krzYWYOpLG9j29HD+TiP1Gu8vfvOL2Ffd82Ii9vSfxtnQkpnRyE1CL/mwqWiIhcMNP32XRbFmDvvG+puG4MH7zRkzva3+x4juX34psxiuwVcwgtV4XkZ98h/OLLgpBY5OyoYImIyHm3w2t4brnFrKWrSUzpQ/eON9HvsxTCwpxdxjNWgMyl08mY9TW4XZS642mir2mHy+H6BpFzTQVLRETOG3++od9am/c32VSMghfK7KLHtFGUL1/e8azcHWvxThxK4OgBopu2Ja5tJzwx8UFILeKcCpaIiASdbQzf7DS8mJaH79Sv9G5Rjh6XuYkMecDxrMDJX/BN+ZycDamEVb+UMt0/JqySFoVK4aKCJSIiQbX6uKFLmsWyxQsos/BthvXqziNXVHQ8x87PxT//B/wLfsAdFUvCwz2JvOI6rV2QQkkFS0REguJ4juG1VRafp+4lfnov7qpbni8WTiQ+3tllPGMMOeuX4pvyOVbGKWJb3UHsTffhDo8MUnKRv04FS0REzqmAbfhsi03vZVnkz3qP+r51jB02gMvqXep4VsGRvXgnDiPv53VEXHoVyc8MIiS5wrkPLXKOqWCJiMg5s+CQTddlFps3baLC1BcY0LMrne55w/FlPDvbT0bKWDKXTiMksTyJT71JZN0mQUotcu6pYImIyF+2z2/oscLixz2Ga8q6SH2iNpf3nElkpLPLeMa2yF4xB9/00ZhAPvHtHiOmZUdcIaFBSi4SHCpYIiLyp+UEDO9usBmY9iuhaV/ydd8ePHixG5cryvGsvD1b8E4cSsGBn4m68gbib30cT3xiEFKLBJ8KloiIOGaMYdJew/NpBRya+xWVtozns/69aFvT+YJPy3cS37QvyV41n9BKF5PcbQjh1eoGIbXI+aOCJSIijmz+1dBtmcX8pctJmvMmr91/G72/mE1IiLMfKSZQQObiyWTM/hZXSBil7u1G9FWtcbm1hV2KPhUsERE5K948Q981Nh+lHSZ6em/aVIpgzOxvSUpKcjwrZ0s6vknDCJw8QkzzW4m75SHcUbFBSC1yYahgiYjI/2Qbw6jthlfSLbIKDFelD+L9d7ty1ZVXOJ4VOH4Y7+Th5G5eQXjNBiQ+3pvQ8lXPfWiRC0wFS0REftfyozZd0mxWHbd5qKabt5uEUOHxTx3PsfNy8M/9Dv/CiXjiSpPw6GtENmiuLexSbKlgiYjIf/kl2/DySouvUndSakYvPu3ZlWdatXA8xxhDzppFeKd+gZ3tJ/bGe4i94W7cYRFBSC1SeKhgiYjIb/Itw0ebbfou82PNGMQVeT/zzaiBXFK7lvNZB3fhnfgZ+bs3E3lZM+I7PElIYrkgpBYpfFSwREQEgJQDNt3SAvw8/3sqrvmS93p3554OgxzPsbIyyJjxFVnLZhFSphJJTw8gorbz+7VEijIVLBGREm5XhuGF5RZTl20iYfqrdGvXkrc/SSEsLMzRHGNZZC2biW/mV2Ab4js+RUzz9rg8+lEjJY/OehGREiqrwDBgnc3gDTZlI2FwEzf3df6cihUrOp6Vt3PD6S3sR/YSdVVr4ts9hie21LkPLVJEqGCJiJQwxhjG7zZ0T8vj+M/reaVDY3o2cBMVcpnjWYFTx/FN/YKctT8RVuUSyjz/AWEX1Q5CapGixf1/v6hatSq1a9emYcOGNGzYkPHjxwNw7NgxbrnlFmrWrEm9evVYvHjxBQsrIiJ/zfqThpbTLe4fupCC99szoMI2+jbyEBXibF2CKcgnY844jg7sTN7ODZR+oDvJ3YaoXIn807+9gzV+/HgaNmz4b3/h5Zdf5uqrryYlJYX09HRuv/129uzZQ2ionmwuIlJUnMw19F5lMyxtH7HTe9OxZiJfzv+R0qVLO5pjjCF303K8k4djnTpOTMuOxN38AO6I6CAlFyma/vAS4ffff8/OnTsBaNy4MRUqVOCnn37ixhtvDHo4ERH5ayzbMGKbzWtp2WTPep+6J9P5+pMBXH5ZfcezCo4ewDtpGHnbVhN+SSOSnnqL0LKVg5BapOj7t4L18MMPA9CkSRMGDRqE2+2moKCAcuX+/96SqlWrsn///jMOy8vLIy8v77ffZ2RkAOD3+3/7tcgf+b9zReeMOKHz5r+lHnPTc20oG4/mUm7UHfR95hE63dUNl8vl6N+Tyc0mb9GP5C+fhSs+icgHXiKkdiNyXC5yivi/b5038mf4/f4//kvmn/bt22eMMSY/P9+89NJLpk2bNubEiRMmLCzM/Ku7777bjBw50pxJnz59DKBDhw4dOi7kUaqi4YkxhhH5hleWGqpe+afmuMDcXaeCWd35OrP9mRvMs42rmXCP+8K/Ph06Csnh8/nO2IeMMcZljDH8hyNHjlCrVi38fj/R0dHs2rXrt3exmjRpwoABA854ifBM72BVrlyZLVu2/KmP/UrJ9H/nzYEDB4iLi7vQcaSI0HkDuRZ8sj2EwauzYeZAenf7O09fVRb3n3jcn3VoJ7kzRmEd/JmQ+s2IaP0Q7vjEcx/6AtN5I3/GoUOHqFu3Lj6f73fPmxCArKwsCgoKKFXq9M6ScePGcfnllwNw9913M2zYMN544w3S09M5dOgQLVu2POOw8PBwwsPD/+vPY2NjdeKKY3FxcTpvxLGSeN4YY5i23/BcagH75o2l0oZv+OitV+jQuqbjWZb/FL7po8heMYfQCtVI6PIu4TWc369V1JTE80b+vLO5pBwCcPToUe68804sy8IYQ/Xq1RkzZgwAb7/9Ng8//DA1a9YkLCyMsWPH6hOEIiKFxHav4bllFilL00lMeYOed7eh7/DZjr9PGytA5pJpZKR8jcvtodRdzxLdtA0ujydIyUWKtxCA6tWrs3bt2jP+hbJlyzJnzpzzGkpERP63jHzDW2tt3k89QuT0PtxU1s3XM8dQtmxZx7Nyt6/BO3EYgWMHib6mLXFtO+GJ1rs5In+FNrmLiBQhtjF8/bOh50qLjHxof2omPfr/jeZNmzieFTj5C94pI8jdkEZY9XqU6f4xYZVqBCG1SMmjgiUiUkSsOm7TJc1m+YEs7q0TzbtXeagc85TjOXZ+Lv75P+Bf8AOeqDgSOr1M5OUtcbn+xN3wInJGKlgiIoXcsRzDq+kWI1N3Ez+9Fz1uv4F3b/ib4znGGHLWL8E3+XMsv5fY6+8k9sZ7cYdHBiG1SMmmgiUiUkgV2IbPtti8npZJ/sx3aJC5hW++GMildS5xPuvwHrwTh5K3cwMRl15F8u1/IySpQhBSiwioYImIFErzD9l0SQ2wdf4EKqwawTuvPs8Dd/RzfBnPzvaTMetrMlOnE5JYnsSn3iKybuMgpRaR/6OCJSJSiOz1G7ovt5i49iClf3yWZ1tfw7ups4iIiHA0x9gWWctnkzFjNCZQQHz7x4lp0QFXiNbsiJwPKlgiIoVAdsDwznqbt9fbJITD6LbJXH//UCpXdv4w5bw9W/BO+IyCgzuJanwj8e0fw1MMt7CLFGYqWCIiF5Axhgl7DC8sy+fw4h/p8dg99GoUSkxoKBDtaJblO4lv2kiyVy0gtHJNkrsNIbxa3eAEF5H/SQVLROQC2fSrodsyiwWLU0ma14/XH7qD1xp78Hic3WdlAvn4F03GP+dbXGHhlL7vOaKatMbldgcpuYj8ERUsEZHz7FSe4Y3VNp+kHiBmem/aV4vjq7njSUhIcDwrZ8tKfJOGEzh5hJjmtxF3y0O4o2KCkFpEnFDBEhE5TyzbMGqH4eW0bPyzPqLW0VS+/qA/V17R0PGswPHDeCcNI3fLSsJrNiTx8d6Elq967kOLyJ+igiUich6kHbXpmmaz+oSh1owX6XdHS/728CvO1y7k5eCfMw7/okl44kqT+FgvIi5rpi3sIoWMCpaISBAdyTb0XGHx9U5DoyQXqbd5uObJoY7nGGPIWb0Q77SR2Nl+4m66l5jr78Id5mx9g4icHypYIiJBkG8ZPtxk0zfNhz1jIP9o24wPO3TA43b+TlP+wZ14J3xG/p4tRDZoTnyHJwlJKBuE1CJyrqhgiYicY7MO2HRLC7Bz7rdUXDeG9994ibva3+J4jpXpI2PmV2Qtm0VI2YtIemYQEbWc368lIuefCpaIyDmy02d4frnF9CVrSJj1Ot073kj/z1IICwtzNMdYFllpM/DNHAPGEN/xb8Q0b4/Lo2/ZIkWF/tcqIvIXZRYY+q+1eS/tKOHT3+D6hABjp4+ifPnyjmfl/rwe38ShFPyyj+irbiau/aN4YkoFIbWIBJMKlojIn2SMYdwuw4srLH7Ng8eSD/FA38dp2exqx7MCp47hm/IFOesWE1a1DmWe/5Cwi2oFIbWInA8qWCIif8K6k4YuqRZLt+zjziurMPgqD1VjGzueYwry8S/4Af+873FFRlH6wR5ENbpeW9hFijgVLBERB07kGnqvshmeuofY6b25v2FVvn15oOM5xhhyNy7DO2UElvcEMS07Etf6AdwRUUFILSLnmwqWiMhZCNiG4Vttei3LImfme1x6ai1jhw6kQb1LHc8q+GU/3knDyNu+hvBLriTpqbcILVs5CKlF5EJRwRIR+QM/HbHpkhpg4/zJlF8xlPd7duWRe95wvoU9J4uMlLFkLpmKp3QZEju/QcSlV2kLu0gxpIIlIvI7DmSevoF9/M4ACaMf4G8tG/J+6kwiIyMdzTG2TXb6PHzTvsTk5xDX5mFir7sDV6iz9Q0iUnSoYImI/IfcgGHwBpuB623iQuGrVmHcdt8oSsXHO56Vv287pyZ8RsH+7UQ2akX8rY8TUio5CKlFpDBRwRIR+SdjDFP3GZ5LK+DA3DE82qYZQzrWIS7MBTgrV5b/FL5po8heOYfQCtVJ7jKY8Br1ghNcRAodFSwREWCb19AtzWLOkuUkznmTV+69lT531CIkxNn9UcYKkLl4Chmzv8Hl9lDq7i5EN70Fl9sTpOQiUhipYIlIiZaRb3hzjc0HqYeJmv46t1QMZ0zKNyQnO7+Ml7t9Dd4JQwkcP0R0s3bEt+mEOzo2CKlFpLBTwRKREsk2hjE/G3qm5XBq1qfUOLSQ0UP60bRJI8ezAieO4J3yObkb0wirUZ8yj7xCWMXqQUgtIkWFCpaIlDgrj9l0SbNZedzQZMe39GpdgWcfn+l87UJ+Lv553+Nf8AOemHgSOr1C5OUttHZBRFSwRKTkOJpteDXd4sttFg2S3Cxu7+Ha8k86nmOMIWfdEnxTPsfye4m9/k5ib7wPd3hEEFKLSFGkgiUixV6Bbfhks02fND8FM96m3UVhTPnoDTxu5+805R/ejXfCUPJ3bSSiXlOSOz5JSFKFIKQWkaJMBUtEirW5B226pgXYPu97KqweyeDePbivYzvHc+wsP76Ur8laOp2Q5Aok/a0fEXWuDEJiESkOVLBEpFjak2HovsJi0pJ1JMx6na5tW/J2Wgrh4eGO5hjbImtZChkzv8IEAsTf9gQx196GKyQ0SMlFpDhQwRKRYiU7AINXWby9wkvo5F60jM/hm8mfU7FiRcez8nZvxjvxMwoO7iKqyU3Et38MT1xCEFKLSHGjgiUixYIxQKM7aTwrnGO5Ns83iODmBp1o1byp41mW9wS+aSPJXr2Q0ItqkfzcB4RXveTchxaRYksFS0SKvI2/Gv6xJAxueo76cQV8fGs0NeJCAWflygTy8S+ahH/OOFxh4ZS+73mimtyEy+0OTnARKbZUsESkyPo119Bntc2nqfuJmfYabEllZNfllI+LcTwrZ/MKfJOGE/j1F2Ku7UDczQ/ijnI+R0QEVLBEpAiybMPI7YZXUrPITPmAS46vYNig12jZfBzR0dGOZhUcO4hv8nByt6QTXqshiZ37EFquSpCSi0hJoYIlIkVK6i82z6YGWLdgOuWWfcyn3Z/hiQd64ff7Hc2xc7Pxz/0O/6KJeOITSXy8NxH1r9EWdhE5J1SwRKRIOJxl6LnSYuxOQ7lZvXiieiQfLZ1BVFSUoznGGLJXL8A3dSQmJ4u41vcT2+ouXGHO1jeIiPwvKlgiUqjlWYYPNtq8tdYmKgRGtvDw8GMDCA1x/u0rf/8OvBOHkr93K5ENryX+ts6EJJQNQmoRKelUsESk0Jqx36ZbagG7537DzVXCGPfyg5QKdwHOPtVn+b1kzBhN1orZhJarQtI/3iaiZoPghBYRQQVLRAqhn32G55dZzFiSTuLsvvS88xbe7PEPQkOd3R9lrACZS6aRkTIW3C5K3fE00de0w+XxBCm5iMhpKlgiUmj48w3919m8l/oLEdP6cFNZF1/P+IqyZZ1fxsvdvgbvxGEEjh0gumlb4tp2whMTH4TUIiL/TQVLRC44Ywzf7DS8mJbLiZShVN03hy/fe4trmzZxPMs+dYwTP35A7oY0wqrXo0z3TwirVCMIqUVEfp8KlohcUGtOGLqkWaQdNdxgbaZNy0Sef2oWbofb001+Lj2uvpjMj5/HEx1PQqeXiby8pdYuiMgFoYIlIhfEiVzDa+k2I9b5uLR8LPPberi+YmOgsaM5xhhy1i4mc/II/taoKmHX3EpSu064wyOCE1xE5CyoYInIeRWwDcO22vRKzSR35rtckb+T5dO+JdTj/Hl/+Yd2n167sGsjIXUac8OHk9g4YILKlYhccHqCqYicNwsP2zScUECXj74nelhHvnioCatmjHNcrqysDE798AnHBj+L7feS9Pf+RN3/IvszcoKUXETEGb2DJSJBtz/T0GO5xQ9LN1J65uv8o3VTBqfNIiLC2TtNxrLIWjYT38yvwLaJ79CZmGtvw+UJIT8jI0jpRUScU8ESkaDJCRgGb7AZsNbCM6EnzcJOMG7CZ1SuXNnxrLydG/BOHErBkb1EXdWa+HaP4oktfe5Di4icAypYInLOGWOYvNfwwnKLQ9nwQn0PDzbvQv3a1R3PCpw6hm/KF+SsW0xYlUso8/wHhF1UOwipRUTOHRUsETmntp4ydF1mMe+nVJpXL83se+tTq5QLcFauTH4e/oU/4p/3Pa7IKEo/0IOoK6/H5XB9g4jIhaCCJSLnhC/f0He1zUepB4ma1pt2VWP56qU3SSzl8PE2xpC7MQ3v5BFYvpPEtLyduNb3446IClJyEZFzTwVLRP4S2xhG7zC8nJaNd+ZH1DyaypgP+tP4ioaOZxUc2Yt30jDydqwjom5jkv7en9Aylc59aBGRIFPBEpE/bcUxmy5pNukLZlJ2yft80O0pnn7kFcfb0+3sTDJSxpK5dCohCeVIfLIvkZdeFaTUIiLBp4IlIo79km14Jd1i9A5DlW3f08m9hc+WTic6OtrRHGNbZK2YQ8b00ZhAPvHtHiOmZQdcIWFBSi4icn6oYInIWcu3DB9vtnlzjU2oG4Y1d9P5iQfwuJ0/7y9vzxa8Ez6j4OBOoq68gfhbH8cTnxiE1CIi558KloiclZQDNt3SAvw8dxyXZa5jweghJEQ4L1aW7yS+aSPJXrWA0Mo1Se42hPBqdYOQWETkwlHBEpH/aVfG6X1WUxevISGlDy90uIEBPd8mLMzhpwMD+fgXTcY/51tcYeGUvu85opq01toFESmWVLBE5IwyCwwD1tkMTj1K+PQ3aJUQ4JtpX1K+fHlHc4wx5G5ZiW/ScAK//kLMtR2Iu/lB3FExQUouInLhqWCJyL8xxjBul6FHWh7HZw+nyu6ZfPFuX65r3tTxrIKjB/BNHkHu1nTCa11OYuc+hJarEoTUIiKFiwqWiPxm7QlDlzSL1KOGjhVtrrs+mS5fp+B2eBnPzs0iY/a3ZC6egic+kcTHXyeiflPH6xtERIoqFSwR4XiOodcqmxFp+6hbpRzz20ZwfcVo4EFHc4xtk71qPr5pX2Jys4m7+QFir7sTV1h4cIKLiBRSKlgiJVjANgzdYtN7WRZ5s96j3qm1zB73ORXKOX8sTf7+7XgnDCV/3zYiL29J/G2dCSmdHITUIiKFnwqWSAk1/5BN17QAWxZOocKKoXz4Uhc63fOG48t4lv8UvmmjyF45h9AK1Uh+9h3CL74sSKlFRIoGFSyREmav39BjhcWEtC0kzOzN31s1YsjSGURGRjqaY6wAmYunkDH7G1xuQ2O0KgAAIABJREFUD6Xuepbopm1weTxBSi4iUnSoYImUENkBw9vrbd5ZbxO26BOa+VbxzfiPqFLF+af6cretxjtxGIHjh4hu1pa4Np3wRMed+9AiIkWUCpZIMWeM4cc9hu7LLY7mQPfL3HS9vTPlSj/veFbgxBG8k0eQu2kZYTXqU+bRVwirUD0IqUVEijYVLJFibOOvhq5pFotSl3O5vYuFr3WiRpwLiHU0x87LwT9vPP6FE/DElCLhkVeJbHit1i6IiPwOFSyRYujXXMPrq20+W36YuBmv07ZCGKPf70dynMPH2xhDzppF+KaOxMryEXv93cTecA/u8IggJRcRKR5UsESKEcs2fL7N5rXluWTN+ZTahxYyekg/rmrcyPGs/IM78U4cSv7uzURe1oz4Dk8SklguCKlFRIofFSyRYmLxEZuuaRbrl8yh/JL3ePMfj/PMYzOdr13I9JEx8yuyls0ipGxlkp4eQETtK4KUWkSkeFLBEiniDmQaXlpp8d0uQwNrN52sxXyyaAqxsc7uszKWRVbaDHwzx4AxxHf8GzHN2+Py6NuEiIhT+s4pUkTlBgzvbbTpv6aAuHAPo1t6eLhmLdyut53P+nk93olDCfyyj+irbyGu3SN4YkoFIbWISMmggiVSxBhjmLLP8PyyAAcWfU/lDWNZNW8qidHOHsgMEPj1KL4pn5OzfilhVetQ5oWPCKtcMwipRURKFhUskSJk6ylDt2UWc5evIzmlD8+3a0G/j6YQHh7maI7Jz8O/4Acy5n+POzKGhIdeIrJRK61dEBE5R1SwRIoAX76h72qbj1YcJ3rWm1wfm8WYSSOoWLGioznGGHLWL8U35XOsjFPEXnc7sTfdhzvC+cOdRUTk96lgiRRitjGM2m54Jd3CN38k1bZPYMTbfWjVornjWQVH9uKdOJS8n9cTcelVJD0zkNBkZwVNRETOjgqWSCG17KhN1zSbVScMD13s4u5HGtCuxZN4HD5M2c72kzHrazJTpxOSWJ7Ep94ism7jIKUWERFQwRIpdI5kG3qusPg6/QB1o7NZemcdmpVzA00dzTG2Rdby2WTMGI0JFBDf/nFiWnTAFRIanOAiIvIbFSyRQiLPMny4yebNldmYOR9Q//hyxn02mEvLOf90YN7uTXgnDqXg4C6iGt9IfPvH8MQnBiG1iIiciQqWSCEwc79Nt7QAu5dOp8Kyj3mrxzM8cl8v51vYvSfwThtJzuqFhF5Ui+TnPiC86iVBSi0iIr9HBUvkAtrhNTy/3GJm+jaSZ/Xmqeb1eW/JDKKinH2qzxTk4180Ef/c73CFRVD6/heIanwjLrfzd79EROSvU8ESuQD8+YZ+a23e32STsGsezTaOZszY96hevbqjOcYYcjcvxztpBNapY8S06EDczQ/ijowOUnIRETkbKlgi55FtDGN/NvRcaeHLh96Xu3nh4dZEh7VxPKvg6AG8k4aRt2014bWvIOnJvoSWuygIqUVExCkVLJHzZNVxmy5pNstXrqLWjvGsGDWEi2Kcb063c7LImP0NmYun4CldhsQn+hBR72ptYRcRKURUsESC7FiO4dV0i5HpRymd0od2ZV18+Wl/yjgsV8a2yU6fh2/al5j8HOLaPEzsdXfgCnX2mBwREQk+FSyRICmwDZ9stumzIo/AwqHU2TeHke+9RdOrmjielbd3G96Jn1GwfweRV1xH/G1PEFIqOQipRUTkXFDBEgmCuQdtui2z2LZsPhV+eodXnu7E04/Pwu3wU31Wxq/4pn1Jdvo8QivWILnLYMJr1AtSahEROVdUsETOod0Zhu7LLSbvM1ybbPNs9Br6LZxMXFycozkmUEDm4ilkzP4WV0gIpe7uQnTTW3C5nT0mR0RELgwVLJFzIKvAMHCdzburMkmODuG76yO5p3oIro6vOp6VsyUd36RhBE4cIbp5e+JveRh3dGwQUouISLCoYIn8BcYYxu829Fge4OjSCVRcNYIpXw2nQY1ajmcFjh/GO3k4uZtXEF6zAYmP9SK0QrUgpBYRkWBTwRL5k9adNHRNs1iyeiPlUnrTrXVT+i2ZRUREhKM5dl4O/jnj8C+ahCeuNAmPvkZkg+ZauyAiUoSpYIk4dCLX0HuVzfDVJyk1+y1ujPIy6sdhVKpUydEcYww5qxfinTYSO9tP7I33EHvD3bjDnBU0EREpfEIAcnNzue+++9iyZQuRkZGUKVOGoUOHcvHFF3Pdddexb98+4uPjAXjkkUd4/vnnL2hokQshYBuGb7Xpvdomb/VUaq4cytCBvbn+upaOZ+Uf+BnvxKHk79lCZIPmxHd4kpCEskFILSIiF8Jv72A99dRTtGnTBpfLxSeffELnzp1ZtGgRAO+//z4dO3a8UBlFLrhFh226LrPY9Cs8UdtFl2ZXU7dKB0JCnL0JbGV6yZjxFVnLUwgpexFJzwwiolbDIKUWEZELJQQgIiKCtm3b/vaHV199NYMHD75goUQKi31+w4srLH5Ye4hav6az8oU7uDLZDVR0NMdYATKXTidj1tfgclHqjqeJvqYdLo/WLoiIFEdn/L/fH374IR06dPjt9y+99BK9e/embt26DBw4kOrVq59xWF5eHnl5eb/9PiMjAwC/3//br0X+yP+dKxfynMkJwEfbQxiywSJkwcfUO7KYz/r3olZ4Jk5jBXZtJHfmKOwThwhtdAPhN9yHHR2HPysrOOFLqMJw3kjRo/NG/gy/3//Hf8n8h/79+5urr77aZGVlGWOM2b9/vzHGGNu2zccff2zq1Knzn1/ymz59+hhAh46ifVxxu2HADsMzEwxJ1Q0h4X9qTuW4SDO8XUNzoNvNZsLdTcylybEX/rXp0KFDh45zdvh8vt/tRC5jjOGfBg8ezHfffce8efMoVaoUZxIREcGhQ4dITEz8r392pnewKleuzJYtW6hY0dklFSm5/u+8OXDggOMN6H/FFq+LnmtDWbxpD2Vnvkr7Ky/mzZ7PExMT42iOyc8lb/Fk8tOm4YqKJaL1Q4TUb6a1C0F2oc4bKdp03sifcejQIerWrYvP5/vd8+a3S4RDhgxh3Lhx/1auAoEAJ0+epGzZ059umjBhAmXLlj1juQIIDw8nPDz8v/48NjZWJ644FhcXd17Om1N5hj6rbT7bYnOROU6LFW/w5ZjB1KhRw9EcYww5axbhmzoSK8tHbKs7ib3xXtzhkUFKLmdyvs4bKV503ogTZ3NJOQTg4MGDdO/enerVq9OqVSvgdFlasGAB7dq1Iy8vD7fbTVJSElOnTg1uapHzxLINI7cbXk23yLNhYGM33eqVJ+zJ8Y5n/evahYjLriH5ticJSSofhNQiIlIUhABUqlSJf7lS+G9WrVp1XgOJnA+pv9h0SbNYu3YtlRb0I23C19QqF+94juX3kjFjNFkrZv9z7cJAImpdHoTEIiJSlGiTu5QoBzMNL620GLfuOMlz3qBd6Xw+/3E45R2WK2MFyFwylYyUb06vXbj970Q3a6+1CyIiAqhgSQmRGzAM3mAzYE0+niUjuHTXDEa825drmjZ1PmvrKryThhM4fojopm2Ia9sJT4zzd79ERKT4UsGSYs0Yw+S9hheWW+xf8xOVFg2kR+f7+ceoFNxut6NZgeOH8U4eTu7mFYTVqE+ZR14hrOKZd8KJiEjJpoIlxdbmXw3dllnMP2xoU9lFz0Y53PfahN9dQfJ77Nxs/HO/w79oEp7YUiQ88iqRDa/V2gUREfldKlhS7Pzf2oVP12VxkTnB9Fur0u4iN3CroznGtsletQDf9C+xczKJvfEeYm+4G3dYRHCCi4hIsaGCJcWGZRs+32bzWrpF9qopVFvxGZ8O6M3NFzm/jJe/b/vptQv7thHZ8Frib+tMSELZIKQWEZHiSAVLioXFR2y6plms37yVynN688T1jej700wiI50t+bQyfsU3fRTZK+cSWqEaSf94m4iaDYKUWkREiisVLCnS9mcaXlxh8f0mL2Xn96N16DFGfPMRVapUcTTHBArIXDyZjNnjcHk8lLrrWaKbttHaBRER+VNUsKRIygkY3llv8/Z6m6gj66k742U+6vcqN1x/vfNZm1fgmzyCwMkjRDdrT/wtD+OOjg1CahERKSlUsKRIMcYwYY+h+wqLI9nwfD03L95Tn1I9UwgJcXY6Fxw9gG/yCHK3phNesyGJj/cmtHzV4AQXEZESRQVLiowNJ0+vXVi07Qg11w5n06dvUquUG3B2Gc/OySJjzrdk/jQZT6kkEh/vTUT9a7R2QUREzhkVLCn0TuYaXl9tM3RjLkmpn3LlwQUMf2/AP8vV2TO2TfbKufimj8Lk5xB3y0PEtroTV2hYkJKLiEhJpYIlhVbAhk83W/RebZO3fg41lr5Hr2cfp9NDsxy/25S3ZwveiUMpOPAzkVdcR/xtTxBSKjlIyUVEpKRTwZLCqXZLWswJZ/POnVSd24tbG9Wg/7wpxMY6u/nc8p3EN20k2asWEFqpBsldBxNevV6QQouIiJymgiWFyl6/oVtqGHSfS5QnwIMHR9BnxABq1qzpaI4pyMe/aCL+ud/hCg2n1L3diL6qNS631i6IiEjwqWBJoZAdMAxaZ/POeotSHhtGPsHc2UOJv/M9R3OMMeRuWo538gisU8eIufY24m5+EHdUTJCSi4iI/DcVLLmgjDF8v/v0stAjO9ZTZV4f3u/9Aret+BaXa6ijWQW/7MM7aTh529cQfkkjkp7sS2i5i4KUXERE5PepYMkFs+6koVuaxeKdJ6i28E1ui83m4+8/JybG2btNdnYmGSljyVw6FU9CWRI7v0HEpVdp7YKIiFwwKlhy3p3INfRKtxmxtYCy6V9wxfYpfDTwDZo1awZARkbGWc0xtkXW8tlkzPgKE8gnru2jxF7XEVeI1i6IiMiFpYIl502BbRi6xabPapuCPaupObsXzz1yN08NS8Hj8Jl/ebs24Z00lIKDu4hqfCPx7R/DE58YpOQiIiLOqGDJeTHvkE23NIutXuh8iYsnGiVSq9sPlC5d2tGcwKnj+KZ+Qc7anwi9qBbJz71PeNU6QUotIiLy56hgSVDtzjB0X24xeWcO9bzprHqqFVckuQCHaxfy8/Av/BH/vO9xRURR+v4XiGp8Iy63s23uIiIi54MKlgRFZsHptQvvbrCI2TqDuqkf06f7M/8sV2fPGEPO+qX4pn6B5TtJTMuOxLW+H3dEdJCSi4iI/HUqWHJOGWP4dpeh50qLY3u3U31ub25vVp/e86cTFRXlaJb1y16Of/U1+bs2ElG3CUl/709omUpBSi4iInLuqGDJObPmhKFrmkXqXh8XLxnAzfYhPvpyCNWqVXM0x87KYMD1dcka2pOQ5Eok/a0fEXWuDFJqERGRc08FS/6yYzmG19ItRm43XBKVzZUTH2DAaz246aabHM0xgQIyl04jM2Ust9YsR/gtj5B04124PDpNRUSkaNFPLvnTCmzDJ5tt+q6xcQEfNnXzdN04PA+kOF7ymbMlHd/k4QSOHyb0yhtp0fll9r4zSeVKRESKJP30kj9l9gGb55ZbbD9wjDqL32T8kNepV72i4zkFRw/gmzKC3C3phNdsQMKjr5Ibk8Sp3O5BSC0iInJ+qGCJIzt9hheWW0zbnU+NNcNounsOHwx6y3G5srMzyZj9DZlLpuIplUTiY72IuKwZLpeL3LPc5C4iIlJYqWDJWfHnGwassxmy0SZ+1wLq/fQu3Z98iE7DZ+J2sIvq3x5vU5BHXJuHib3uDlyheryNiIgUHypY8j/ZxvDNztNrF04e2kvNeb24sX5l3pw1kbi4OEez8nZuwDtxGAWHd+vxNiIiUqypYMnvWnnMptsym+XHDHdVc3Ft7kpaf9SXSy65xNGcwMlfTj/eZv1SwqpcQvJzHxBe1dkMERGRokQFS/7L4SzDK+kWY3bY1A07xcJ2yVxXwQ086GiOnZeLf/54/At+xB0dR+mHXiTqilZ6vI2IiBR7Kljym9yA4f1NNv3X2oQc2cRl817nhUfu5roKnRzNMcaQs3ohvmlfYmX5iG11J7E33os7PDJIyUVERAoXFSzBGMPkvYbuKyz2Hz1F/dR+1A71MnjMUCpVcvZomvx92/FOHEr+vm1ENmhO/G2dCUksF6TkIiIihZMKVgm36VfDc8ss5h8MUHfLaJqsn8CgN3vTokULR3Ms30l800eRnT6P0ArVSPrH20TUbBCk1CIiIoWbClYJdTLX0Ge1zdCtNhfl7efy8X+n832389R7swgJOfvTwhTk4180Ef+88bhCwih1T1eir74Zl9sTxPQiIiKFmwpWCVNgG4Ztsemzxsay4Z0mbp66uCL5931HYuLZr0wwxpC7MQ3vlM+xTh0n5trbiLv5QdxRMUFMLyIiUjSoYJUgcw/aPLfMYsvxPJrt+orvXn+SSvEewANREWc9p+DwHryThpP38zoi6jQm6am3CC1bOXjBRUREihgVrBJgp+/0DexT9xnqHpxN44Xv84+nO1MxLtTRHCvTR0bK12SlziQkuQKJT71JZN0mQUotIiJSdKlgFWP+fEP/dTbvb7RJ8O2kyZxe3HBFbV6dOYWYmLO/lGesAJlLp5ORMhaMIb5DZ2Ka34orxFlBExERKSlUsIoh2xjG/Gx4ZaWFNyOTJumDKJO5h3c+fYcaNWo4mpW7dRXeySMIHDtAdNM2xLXthCemVJCSi4iIFA8qWMVM2lGbbmk2q04Y7qvhImrZG9x9bxtuueVtR3MKjh/CN3kEuZtXEFajPmUe7klYJWflTEREpKRSwSomDmaefiDzt7sMlyfC4vYeri3vhus/dDTHzskiY863ZC6egicugYRHXyOyQXNcLleQkouIiBQ/KlhFXE7A8N4Gm4HrbaJyT9Dyp748d39bri1/m6M5xrLIWp5CxswxmII84m5+gNjr7sQVFh6k5CIiIsWXClYRZYxhwh5DjxUWh/wBWuz4HLNuOv3f6kvTpk0dzcrdvub0fVZH9hLV5Cbi2z2KJ/7sd2KJiIjIv1PBKoLWnTz9eJufjhiuPrWYCjMH8sDD9/PYOym43e6znlNw7CC+KZ+fvs+q+qWU6f4xYZVrBjG5iIhIyaCCVYQczzH0WmXzxXabagUHuG5OLxpUKcMbk3+kVKmz/2Sfne0nY/a3ZC6ZiqdUku6zEhEROcdUsIqAAtvw6WabN9bYAAy52k1Lk01oi9e49NJLz3qOsSyy0maQMetrjBUgrm0nYlvejis0LFjRRURESiQVrEIu5YDN88sttnsNd0ds55O76pEc6QLqOZqTu3UV3ikjCBw9QNRVrYlv+wieuITghBYRESnhVLAKqR1ewwvLLWYcMDQObKPltN40vPYqkiPrO5pT8Mv+0/dZbU0/vc+q+0uEVbo4SKlFREQEVLAKHV++4a01Nh9usqng8tF+eX/ico8xYOiHVKlS5aznWFkZ+FPGkpk6HU/psiQ+1ouIy5rpPisREZHzQAWrkLBsw5c7DK+lW2Tm29x6cCzeJeN4oddrtGrV6qzn/PbcwNljwbKJb/8YMS064ArRfVYiIiLniwpWIbDwsM1zyyw2/AoPVLM5NuQuWrVpzdOzUwgJObv/RMYYcresxDflcwLHDxN99c2nnxsYWzrI6UVEROQ/qWBdQDt9hhdXWEzeZ2haxsWKDm6alAklt/kPREREnPWcgiN78U4eQd72NYTXbEjCo68SVqF68IKLiIjI/6SCdQH48g3919p8sMmmbGg+D+4ZxqvN2lC3TF2Asy5XVqaPjJSvyUqdSUhiORI79yHi0qt1n5WIiMgFpoJ1Hlm2YeR2Q69VFlkBuD93Hvu+Gcwtjz9GnTp1znqOCRSQuXQaGSnfABB/2xPEXHsbrpDQYEUXERERB1SwzpN/vc+qY9QeAtN6Ub5WdT6ZMpnY2NizmmGMIXfzcnxTviBw4gjRzdoSd8tDeGLOfou7iIiIBJ8KVpD9631WTeKyeWzLO/j2b2PI24OoWfPsn/uXf3g3vskjyNuxjvDaV5D4eG9Cy1cNXnARERH501SwguRf77MqFwnjrveQu2QSyTdeQ7t2/c96juU/RcbMMWQtn01IUnkSn+xLRN0mus9KRESkEFPBOsf+8z6rV+tZvNQonKgQF9R49Kzn2Pm5ZC6ahH/+9+DxEN/hSWKuvRWXR//JRERECjv9tD6H/vU+q3vLniJiRl9CD1cg6qrXznqGsW2yVy0gY+ZoLL+XmOa3Etf6AdzRZ3efloiIiFx4KljnwL/eZ3V1ok1P70jW/DCZPn360KxZs7Oek/vzenxTRlBwcBeRDZoTf+vjhCRVCGJyERERCQYVrL/Al2/ot/b0cwPLRUKf2DRSh/aj+t1303/WLDwez1nNKTh6AN/UL8jdvIKwKpeQ3PU9wqtfGuT0IiIiEiwqWH/Cf95n1ePiDPZ+/jwnS8czfvx4EhISzm5OppeMlLFkpc3EUyqZhE6vEHl5C93ALiIiUsSpYDm04JDN88tP32fVqaaLAY09JIfGsiPxJerVq3dWM0x+Hv7Fk/HPHQ8uF/HtHz+9KDRUD2QWEREpDlSwztK/PzcQPoybx9+vuYGwsBAg7KzKlbFtctYswjdjNJbvJDHN2xPb+gE8MfHBfwEiIiJy3qhg/YH/vM/qvao7WTr0NU7Wr4/dodVZz8nbtRHvlM8p2L+DiMuuIenpAYSWqRTE5CIiInKhqGD9jv+8z+qlmplkTx3AyoMHeO+996hWrdpZzSk4dhDftC/J3ZhGaOWaJHd5l/Aa9YOcXkRERC4kFawz+Nf7rB6uYWi0+zumvTmGnj17ctNNN53VDCvTh3/Ot2QunY4nPpGEh3sSeXlLXG53kNOLiIjIhaaC9S+2ew0vrbSYus9wTVkXKzu6+XHwK5jy5Zk1axahoaF/OMMU5JO5ZCoZc8aBMcS17URsi464wsLPwysQERGRwkAFCziRa3hzjc3QLTYVo08/N/De6i5cLhdXDhp0VmsTfruBfeZXWN7jRF/TlribH8ITW+o8vAIREREpTEp0wcqzDB9vtum31sYYeLOhRdiS4QSWJeKq8RDAH5YrYwy5W1eRMX0UBYd3E1GvKUlPvUVouYvOx0sQERGRQqhEFixjDD/uMfRcabE/E/5Wx831voUMfXkQDz30EA888MBZzcnbuw3ftJHk79pIWPV6JHcbQni1ukFOLyIiIoVdiStYK47ZvLDcJu2ooV1lFyPqHGDkoFdZVrEiEyZMID7+j3dSFRw9QMaM0eRsSCWkfFUSn+xLRN0m2sAuIiIiQAkqWHv9hlfSLb7bZWiQANNb5ZE+djCfrl/PwIEDueSSS/5whuU9Qcbsb8haMRtPfBKlH+hB1JWtcLnP7pmDIiIiUjIU+4LlyzcMXGfzwSabhHAY2cLDIzVdbN2yHeuKK+jTp88fvvNkZ/vxz/8B/+LJuMMiiL+tMzHN2uvRNiIiInJGxbZgBWzDiG02fVbbZBVAzwZuHi1/kmoVygBQr169P3y8jcnPI3PpVDLmjYdAAbGt7iS21V24I6PPx0sQERGRIqrYFSxjDDMPnH5u4DYvPFLLRY8aGYx4ty9v+f2MHDnyjz8ZaFlkp88jI+VrrIxTRDdtQ1zr+/HEJ56nVyEiIiJFWbEqWOtPGnqssJh3yNCqvIsxLWDt1FE81+97evfuTYsWLf7n1xvbJmfdEjJSxhI4doDIhi2Ia/cIockVz9MrEBERkeKgWBSsI9mG3qssvtxuqBkPU1t7SDi4jFcf7kvHjh2ZNWsWISG//1KNbZOzMe10sTqyl4g6jUl46EXCLqp1/l6EiIiIFBtFumBl5Bve3WAzZKNNpAc+usbNU5e46PLM03g8HsaNG0di4u9f1jPGkLt5ORmzxlJwaBfhta+g9D1dtctKRERE/pIiWbDyLcPwrTZvrbXxF0C3em5ebuCmVPjpe6veeustypQp87tf/9v29VljKDjwM2E16pPc5V3Ca9Q/Xy9BREREirEiVbCMMfyw2/DqKos9fnikpos3G3nYuCSFvVvL07BhQ4DfLVfGGPJ2rCVj5hjy920jrFpdkp4ZRESthufzZYiIiEgxV2QK1qLDNi+ttEk/fnoD++SbPET8uovnHn2ZWrVq8eqrr/7Pr8/9eT0Zs74mf/cmQi+qTdLf+xNe+wptXxcREZFzrtAXrI2/Gl5eaTHzgKFxsotF7T00is2mf//+7Ny5k0GDBnHxxRef8WuNMeRtW03GvPHk79pIaKWL9VgbERERCbpCW7AOZBpeX23x1Q5DjTj4/gYPd1aF7777jjdHjqRHjx4MHDjwjF9rbIucDan4531PwcGdhFauSeLjrxNRv6mKlYiIiARdoStY3jzDoPU2H26yiQ39v08GugnzuBg/fjyHDh1i1qxZhIX992NqTKCA7FXz8c//gcDxQ4TXbEjS0wMIr3W5ipWIiIicN4WmYGUWGD7ebPPuBps8C168zE2Py9zEhvJbObr33nvP+LV2Xi5Zy2aSuXAilu8EEfWvIeGhlwirUvt8vgQRERERoBAUrNyAYdhWm4HrbU7lwd8ucfPq5W6SwyyGD/+MXbt2MWTIkDN+reU9QWbqdLLSZmLnZBLV6Hpib7ib0HJVzvOrEBEREfn/LljByrcMX2636bfO5pdseLSWi96Xe6gS+//au7eYqPI7DuDfMwPMCnIRXRCF4bJcKkKVW8Qbl6VstA9KJSbWSx1jiyXhgYd9qIlV6OrgJsTE6oNus0ESNkQRJE3UKiHrhUR06ApeoiyDMw7igAvqAO44MMy/D7TTuu4MOGW45ft5m3PJ/3eSb05+Oec//yPh2rVr+N2RI9i2bRvKy8vfO9eif4Sh6/UwtzVB8lTAZ1Uu5mdtgUdg8DRcCREREdG7przBstoEvtEKlH43Cv0g8NtPJJSkyBHjL8FgMGDHH/cjKCgINTU1CAgIsJ8nrCMwtzVh8Ho9RgztkC8Kgf/mP8BnVS5kH/lM9WUQEREROTThUSlYAAAHVUlEQVRlDZZlVKDye4Ev20bxZBDYEiHh75/JkRAoYXh4GF988SU0Gg3KysqwfPly+3nWH57jTfM/8Ob2VdiGXkMRuxILf1+Cj+LTIMnkU1U+ERER0YRNSYP1tVaOv92w4vkbID9SwvlfyZG06L//6pMkCcnJyThw4AAkSYIYtsD8oBlvmi/D8n0rpHnz4ZOWA5/VG+EZEjEVJRMRERG5bEoarL/c98TORAl/WiHHsgVjjdXjx48RGRkJhUIBT09P/HrjRli09/BjSyPMbU0Qb3+EV9RyLNjxObxXrIfkpZiKUomIiIj+bxNqsDo6OrB792709fXB398fZ86ceec13nhufmbBmrixoUwmE0pLS9HT04O/Hj8OvOmH+V4TzN9dw+jrPsgXhmB+5m/gnZINz6BQ166KiIiIaBpNqMHat28fCgoKoFKpcP78eahUKmg0mgkPovQRsNlsqKysxDdVVfh811asWh0F88li/GDqh8zHH/OS1sM75VN4RSzjoqBEREQ0q43bYL148QItLS24evUqACA/Px9FRUXQarUOvwH4U//89gpUJ04iJyoYXyf5QN5aj7eBwfBemYF5v1wDr4h4SHJOWCciIqK5YdwGq6urCyEhIfDwGDtUkiQolUoYDIb3GiyLxQKLxWL/bTKZAACVR/6M0nW/wMexsRiNXA58kgjxcRiGJAlDAGA0Tt4V0aw3ODgIAOju7sbAwMA0V0OzBXNDrmBuyBXGf/ctQgiHx0zqJPeysjKUlpa+t/1CuxEX2o0Avp3M4WiOi4+Pn+4SaBZibsgVzA25or+/H/7+/j+7TxLO2i+MvSKMjo7Gy5cv4eHhASEEQkJC0NTUNO4TrNevXyM8PBwGg8FhAUQ/NTAwgLCwMHR1dcHPz2+6y6FZgrkhVzA35AqTyQSlUolXr169syj6/xr3CVZQUBCSk5NRVVUFlUqF2tpahIaG/uz8K4VCAYXi/eUU/P39GVz6YH5+fswNfTDmhlzB3JArZDKZw30TekV4+vRpqFQqqNVq+Pn5oaKiYtKKIyIiIpprJtRgxcXF4datW+6uhYiIiGhOkJeUlJS4dQC5HFlZWfZ/IRJNBHNDrmBuyBXMDblivNyMO8mdiIiIiD6M49lZREREROQSNlhEREREk4wNFhEREdEkc2uD1dHRgTVr1iA2NhZpaWl4+PChO4ejWejt27fIy8tDbGwsVqxYgdzcXGi1WgBji9xu2LABMTExSEhIwI0bN6a5WpqJKioqIEkS6uvrATA35JzFYkFRURFiYmKQmJiInTt3AmBuyLlLly4hOTkZK1euREJCAiorKwGMkxvhRtnZ2aKiokIIIURNTY1ITU1153A0C5nNZnHx4kVhs9mEEEKcOHFCZGZmCiGE2LNnjzh06JAQQog7d+6IpUuXiuHh4WmqlGYinU4nVq9eLdLT08WFCxeEEMwNOVdcXCyKiors9xyj0SiEYG7IMZvNJhYsWCDa2tqEEGP3HYVCIQYGBpzmxm0NVm9vr/D19RUjIyP2AoODg0VHR4e7hqQ5QKPRiPDwcCGEED4+PvabnxBCpKWliYaGhmmqjGaa0dFRkZOTI1paWkRmZqa9wWJuyJGhoSHh6+srTCbTe/uYG3LEZrOJwMBAcf36dSGEEG1tbWLJkiXCYrE4zY3bXhF2dXUhJCTEvj6EJElQKpUwGAzuGpLmgOPHj2Pz5s3o7+/HyMgIFi9ebN8XERHB/JDdsWPHsHbtWqSkpNi3MTfkTGdnJwIDA6FWq5Gamor169ejsbGRuSGnJEnC2bNnsWXLFoSHh2PdunWorKzE4OCg09xwVTWaMdRqNbRaLRobG2E2m6e7HJrBHjx4gNraWs6ToQ9itVrx9OlTxMfH4+jRo7h79y5yc3M5P5icslqtOHz4MOrq6pCRkQGNRoNNmzahtbXV6Xlue4IVFhYGo9EIq9UKABBCwGAwQKlUumtImsXKy8tRV1eHy5cvw9vbGwsXLoSHhwd6enrsx+j1euaHAAA3b96EXq9HTEwMIiIi0NzcjIKCApw7d465IYeUSiVkMhl27NgBAEhKSkJkZCTu37/P3JBDra2teP78OTIyMgAAaWlpCA0Nxb1795zmxm0NVlBQEJKTk1FVVQUAqK2tRWhoKKKjo901JM1Sx44dQ3V1NRoaGhAQEGDfvnXrVpw6dQoAoNFo0N3djczMzOkqk2aQwsJCGI1G6PV66PV6pKen46uvvkJhYSFzQw4tWrQIOTk5uHLlCgBAp9NBp9Nh2bJlzA059J8HRo8ePQIAaLVadHZ2Ii4uzmlu3PqpnPb2dqhUKvT398PPzw8VFRVITEx013A0Cz179gxhYWGIioqCr68vAEChUOD27dvo7e3Frl27oNPp4OXlhZMnTyI7O3uaK6aZKCsrC8XFxcjLy2NuyKknT55g79696Ovrg0wmw8GDB5Gfn8/ckFPV1dVQq9WQyWSw2WzYv38/tm/f7jQ3/BYhERER0STjSu5EREREk+xfsqQVJpLf1LEAAAAASUVORK5CYII=\" />"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_Fig2(ksp,kss,40)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Both figures are replicated well. \n",
    "\n",
    "Note that the mean of capital is approximately 40 in this replication, which is different from Krusell-Smith but same as Maliar, Maliar, Valli. Therefore, Figure 1 is plotted around 40 and policy function for Figure 2 is evaluated at K=40"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Solution with value function iteration\n",
    "In this section, each agent's utility maximization problem is solved by value function iteration."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's prepare functions for value function iteration\n",
    "## Bellman equation and VFI\n",
    "The functions in this cell are used to solve individual household problem by VFI\n",
    "- Methods\n",
    "    - rhs_bellman: evaluate RHS of bellman equation given the guess of value function\n",
    "    - compute_expectation_VFI: compute expectation term of Bellman equation given current shock state\n",
    "    - solve_bellman_once!: maximize RHS of Bellman equation for an agent of state (k_i,K_i,s_i)\n",
    "    - solve_bellman!: maximize RHS of Bellman equation for all state until convergence\n",
    "    - iterate_policy!: iterating policy and compute values under the policy. used for Howard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "code_folding": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "iterate_policy!"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Compute right hand side of bellman equation\n",
    "\n",
    "##### Arguments\n",
    "- `kp` : next period capital\n",
    "- `ksm` : KSModel instance\n",
    "- `k` : current individual capital\n",
    "- `K` : current aggregate capital\n",
    "- `L` : current labor\n",
    "- `zeps_i` : \n",
    "\"\"\"\n",
    "function rhs_bellman(ksp::KSParameter,\n",
    "            kp::AbstractFloat,value::Array{Float64,3},\n",
    "            k::AbstractFloat,K::AbstractFloat,s_i::Integer)\n",
    "    u,s_grid,beta,alpha,l_bar,delta, mu =\n",
    "        ksp.u, ksp.s_grid, ksp.beta, ksp.alpha, ksp.l_bar, ksp.delta, ksp.mu\n",
    "    z, eps = get_shock(s_grid,s_i)\n",
    "    Kp,L = compute_Kp_L(K,s_i,kss.B,ksp) # Next period aggregate capital and current aggregate labor\n",
    "    c = (r(alpha,z,K,L)+1-delta)*k+\n",
    "          w(alpha,z,K,L)*(eps*l_bar+(1.0-eps)*mu)-kp # current consumption \n",
    "    expec = compute_expectation(kp,Kp,value,s_i,ksp)\n",
    "    return u(c)+beta*expec\n",
    "end\n",
    "\n",
    "\"\"\"\n",
    "Compute expectation of next period value\n",
    "\n",
    "##### Arguments\n",
    "- `kp` : next period individual capital\n",
    "- `Kp` : next period aggregate capital\n",
    "- `value` : given value \n",
    "- `s_i` : current shock state\n",
    "- `ksp` : KSParameter instance\n",
    "\"\"\"\n",
    "function compute_expectation(\n",
    "              kp::AbstractFloat,  # next period indicidual capital\n",
    "              Kp::AbstractFloat,  # next period aggragte capital\n",
    "              value::Array{Float64,3}, # next period value\n",
    "              s_i::Integer, # index of current state,\n",
    "              ksp::KSParameter \n",
    "              )\n",
    "    k_grid, K_grid = ksp.k_grid, ksp.K_grid # unpack grid\n",
    "    beta, P = ksp.beta, ksp.TransMat.P      # unpack parameters\n",
    "    \n",
    "    # compute expectations by summing up\n",
    "    expec=0.0\n",
    "    for s_n_i=1:ksp.s_size\n",
    "        value_itp=interpolate((k_grid,K_grid),value[:,:,s_n_i],Gridded(Linear()))\n",
    "        expec = expec + P[s_i,s_n_i]*value_itp[kp,Kp]\n",
    "    end\n",
    "    return expec\n",
    "end\n",
    "\"\"\"\n",
    "Solve bellman equation for all states once\n",
    "\n",
    "##### Arguments\n",
    "- `k` : individual capital\n",
    "- `K` : aggregate capital\n",
    "- `s_i` : shock state index\n",
    "- `ksp` : KSParameter\n",
    "- `kss` : KSSolution\n",
    "\"\"\"\n",
    "function solve_bellman_once!(\n",
    "            k_i::Integer,\n",
    "            K_i::Integer,\n",
    "            s_i::Integer,\n",
    "            ksp::KSParameter,\n",
    "            kss::KSSolution,\n",
    "            )\n",
    "    # obtain minimum and maximum of grid\n",
    "    k_min, k_max = ksp.k_grid[1], ksp.k_grid[end]\n",
    "    \n",
    "    # unpack parameters\n",
    "    alpha,delta,l_bar, mu = \n",
    "        ksp.alpha, ksp.delta, ksp.l_bar, ksp.mu\n",
    "    \n",
    "    # obtain state value\n",
    "    k=ksp.k_grid[k_i]   # obtain individual capital value\n",
    "    K=ksp.K_grid[K_i]   # obtain aggregate capital value\n",
    "    z, eps = get_shock(ksp.s_grid,s_i) # obtain shock value\n",
    "    \n",
    "    Kp,L=compute_Kp_L(K,s_i,kss.B,ksp) # next aggregate capital and current aggregate labor\n",
    "    # if kp>k_c_pos, consumption is negative \n",
    "    k_c_pos=(r(alpha,z,K,L)+1-delta)*k+\n",
    "        w(alpha,z,K,L)*(eps*l_bar+(1-eps)*mu)\n",
    "    obj(kp)=-rhs_bellman(ksp,kp,kss.value,k,K,s_i) # objective function\n",
    "    res=optimize(obj,k_min,min(k_c_pos,k_max)) # maximize value\n",
    "    # obtain result\n",
    "    kss.k_opt[k_i,K_i,s_i]=Optim.minimizer(res) \n",
    "    kss.value[k_i,K_i,s_i]=-Optim.minimum(res)\n",
    "    return nothing\n",
    "end\n",
    "\n",
    "\"\"\"\n",
    "Solve bellman equation for all states until convergence\n",
    "\n",
    "##### Arguments\n",
    "- `ksp` : KSParameter\n",
    "- `kss` : KSSolution\n",
    "- `tol` : tolerance of value function difference\n",
    "- `max_iter` : maximum number of iteration\n",
    "\"\"\"\n",
    "function solve_bellman!(\n",
    "            ksp::KSParameter,\n",
    "            kss::KSSolution;\n",
    "            tol::AbstractFloat=1e-8,\n",
    "            max_iter::Integer=100,\n",
    "            Howard::Bool=false,\n",
    "            Howard_n_iter::Integer=20,\n",
    "            print_skip::Integer=10)\n",
    "    counter_VFI=0  # counter\n",
    "    while true\n",
    "        counter_VFI += 1\n",
    "        value_old=copy(kss.value) # guessed value\n",
    "        # maximize value for all state\n",
    "        [solve_bellman_once!(k_i,K_i,s_i,ksp,kss)\n",
    "          for k_i in 1:ksp.k_size, K_i in 1:ksp.K_size, s_i in 1:ksp.s_size]\n",
    "        # Howard's policy iteration\n",
    "        !Howard || iterate_policy!(ksp,kss,n_iter=Howard_n_iter)\n",
    "        # difference of guessed and new value\n",
    "        dif=maxabs(value_old-kss.value)\n",
    "        # print covergence process\n",
    "        !(counter_VFI % print_skip ==0) ||\n",
    "            println(\"VFI iteration $counter_VFI : dif = $dif\")\n",
    "        # if difference is sufficiently small\n",
    "        if dif<tol\n",
    "            println(\" ** VFI converged successfully!! dif = $dif\")\n",
    "            break\n",
    "        elseif counter_VFI >= max_iter\n",
    "            println(\"VFI reached its maximum iteration : $max_iter\")\n",
    "            break\n",
    "        end\n",
    "    end\n",
    "end\n",
    "\n",
    "\"\"\"\n",
    "Iterate the value function fixing the policy function\n",
    "\n",
    "##### Arguments\n",
    "- `ksp` : KSParameter instance\n",
    "- `kss` : KSSolution instance\n",
    "- `n_iter` : number of iterations\n",
    "\"\"\"\n",
    "function iterate_policy!(ksp::KSParameter,\n",
    "            kss::KSSolution;n_iter::Int64=20)\n",
    "    value=similar(kss.value)\n",
    "    for i=1:n_iter\n",
    "        # update value using policy\n",
    "        value .= \n",
    "            [rhs_bellman(ksp,\n",
    "                kss.k_opt[k_i,K_i,s_i],kss.value,\n",
    "                ksp.k_grid[k_i],ksp.K_grid[K_i],s_i)\n",
    "                for k_i in 1:ksp.k_size,\n",
    "                    K_i in 1:ksp.K_size,\n",
    "                    s_i in 1:ksp.s_size]\n",
    "        kss.value.=copy(value)\n",
    "    end\n",
    "    return nothing\n",
    "end\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's skip the following steps in this section to save computational time.\n",
    "- consturuction of `ksp` instance since it is same\n",
    "- consturuction of `kss` instance to use the previous result as initial guess of the solution\n",
    "- draws of the shocks to use same ones"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, instead of constructing `kss` again, obtain value from the policy function derived by Euler method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "iterate_policy!(ksp,kss,n_iter=30);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, the model is solved by VFI in the next cell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " --- Iteration over ALM coefficient: 1 ---\n",
      "VFI iteration 10 : dif = 4.364130337367499\n",
      "VFI iteration 20 : dif = 0.5155086466810985\n",
      "VFI iteration 30 : dif = 0.06101406344856741\n",
      "VFI iteration 40 : dif = 0.007215234574232454\n",
      "VFI iteration 50 : dif = 0.000852061281875649\n",
      "VFI iteration 60 : dif = 0.00010046707080846318\n",
      "VFI iteration 70 : dif = 1.1826375214241125e-5\n",
      "VFI iteration 80 : dif = 1.3896425912207633e-6\n",
      "VFI iteration 90 : dif = 1.6298264426950482e-7\n",
      "VFI iteration 100 : dif = 1.9079607227467932e-8\n",
      " ** VFI converged successfully!! dif = 8.085862646112218e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.02551266404864358 and B = [0.130832,0.964894,0.106545,0.970074]\n",
      " --- Iteration over ALM coefficient: 2 ---\n",
      "VFI iteration 10 : dif = 0.04110720950990299\n",
      "VFI iteration 20 : dif = 0.004799456575142358\n",
      "VFI iteration 30 : dif = 0.0005606688813486471\n",
      "VFI iteration 40 : dif = 6.551400201715296e-5\n",
      "VFI iteration 50 : dif = 7.655140279894113e-6\n",
      "VFI iteration 60 : dif = 8.94252366379078e-7\n",
      "VFI iteration 70 : dif = 1.0442380471431534e-7\n",
      "VFI iteration 80 : dif = 1.2187229003757238e-8\n",
      " ** VFI converged successfully!! dif = 9.830898761720164e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.010571478106761914 and B = [0.138905,0.962971,0.113833,0.968363]\n",
      " --- Iteration over ALM coefficient: 3 ---\n",
      "VFI iteration 10 : dif = 0.0004685646893847206\n",
      "VFI iteration 20 : dif = 5.4314097894803126e-5\n",
      "VFI iteration 30 : dif = 6.4477072214685904e-6\n",
      "VFI iteration 40 : dif = 7.622459747835819e-7\n",
      "VFI iteration 50 : dif = 8.993168876259006e-8\n",
      "VFI iteration 60 : dif = 1.0597830168990185e-8\n",
      " ** VFI converged successfully!! dif = 8.557094588468317e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.006449099771311431 and B = [0.140108,0.962642,0.114784,0.968106]\n",
      " --- Iteration over ALM coefficient: 4 ---\n",
      "VFI iteration 10 : dif = 0.0004316023300816596\n",
      "VFI iteration 20 : dif = 5.057148842979586e-5\n",
      "VFI iteration 30 : dif = 6.002880127198296e-6\n",
      "VFI iteration 40 : dif = 7.094776037774864e-7\n",
      "VFI iteration 50 : dif = 8.366657766600838e-8\n",
      "VFI iteration 60 : dif = 1.0639979564075475e-8\n",
      " ** VFI converged successfully!! dif = 7.953985914355144e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.0037177793034470913 and B = [0.140774,0.962464,0.11558,0.967893]\n",
      " --- Iteration over ALM coefficient: 5 ---\n",
      "VFI iteration 10 : dif = 0.0001699352112325414\n",
      "VFI iteration 20 : dif = 1.9677074277524298e-5\n",
      "VFI iteration 30 : dif = 2.2995970141437283e-6\n",
      "VFI iteration 40 : dif = 2.691489555672888e-7\n",
      "VFI iteration 50 : dif = 3.161997597089794e-8\n",
      " ** VFI converged successfully!! dif = 8.755819180805702e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.0021012252914709983 and B = [0.141146,0.962364,0.116081,0.967759]\n",
      " --- Iteration over ALM coefficient: 6 ---\n",
      "VFI iteration 10 : dif = 0.00016965897827958543\n",
      "VFI iteration 20 : dif = 1.848068291110394e-5\n",
      "VFI iteration 30 : dif = 2.05708909106761e-6\n",
      "VFI iteration 40 : dif = 2.325381274204119e-7\n",
      "VFI iteration 50 : dif = 2.647169594638399e-8\n",
      " ** VFI converged successfully!! dif = 8.945391982706496e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.0012679245607524897 and B = [0.141284,0.962326,0.116284,0.967703]\n",
      " --- Iteration over ALM coefficient: 7 ---\n",
      "VFI iteration 10 : dif = 4.9276457787073014e-5\n",
      "VFI iteration 20 : dif = 4.933374896154419e-6\n",
      "VFI iteration 30 : dif = 5.170394956621749e-7\n",
      "VFI iteration 40 : dif = 5.5685518418613356e-8\n",
      " ** VFI converged successfully!! dif = 9.463576589041622e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.0007726858753848709 and B = [0.141347,0.962309,0.116399,0.967672]\n",
      " --- Iteration over ALM coefficient: 8 ---\n",
      "VFI iteration 10 : dif = 3.44231706321807e-5\n",
      "VFI iteration 20 : dif = 3.568709871615283e-6\n",
      "VFI iteration 30 : dif = 3.8495443277497543e-7\n",
      "VFI iteration 40 : dif = 4.244049023327534e-8\n",
      " ** VFI converged successfully!! dif = 9.12990572032868e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.00048209680162884794 and B = [0.141369,0.962302,0.116458,0.967656]\n",
      " --- Iteration over ALM coefficient: 9 ---\n",
      "VFI iteration 10 : dif = 1.758010006369659e-5\n",
      "VFI iteration 20 : dif = 1.7869241446533124e-6\n",
      "VFI iteration 30 : dif = 1.9031887177334283e-7\n",
      "VFI iteration 40 : dif = 2.07742800739652e-8\n",
      " ** VFI converged successfully!! dif = 8.598362910561264e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.0003055378304484685 and B = [0.141377,0.9623,0.11649,0.967647]\n",
      " --- Iteration over ALM coefficient: 10 ---\n",
      "VFI iteration 10 : dif = 1.023216435669383e-5\n",
      "VFI iteration 20 : dif = 1.03666968698235e-6\n",
      "VFI iteration 30 : dif = 1.102799274121935e-7\n",
      "VFI iteration 40 : dif = 1.2026134754705708e-8\n",
      " ** VFI converged successfully!! dif = 9.64348600973608e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.00019619175347125595 and B = [0.141377,0.9623,0.116508,0.967642]\n",
      " --- Iteration over ALM coefficient: 11 ---\n",
      "VFI iteration 10 : dif = 6.056440042812028e-6\n",
      "VFI iteration 20 : dif = 6.10131223766075e-7\n",
      "VFI iteration 30 : dif = 6.479382363977493e-8\n",
      " ** VFI converged successfully!! dif = 8.801350759313209e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 0.00012730360336368762 and B = [0.141376,0.962301,0.116518,0.96764]\n",
      " --- Iteration over ALM coefficient: 12 ---\n",
      "VFI iteration 10 : dif = 3.566279190181376e-6\n",
      "VFI iteration 20 : dif = 3.556169758667238e-7\n",
      "VFI iteration 30 : dif = 3.754672661671066e-8\n",
      " ** VFI converged successfully!! dif = 9.877851425699191e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 8.313458897782344e-5 and B = [0.141374,0.962301,0.116524,0.967638]\n",
      " --- Iteration over ALM coefficient: 13 ---\n",
      "VFI iteration 10 : dif = 2.2697702775076323e-6\n",
      "VFI iteration 20 : dif = 2.2698196744386223e-7\n",
      "VFI iteration 30 : dif = 2.4034420675889123e-8\n",
      " ** VFI converged successfully!! dif = 9.869268069451209e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 5.463237199027082e-5 and B = [0.141373,0.962302,0.116527,0.967637]\n",
      " --- Iteration over ALM coefficient: 14 ---\n",
      "VFI iteration 10 : dif = 1.2852221971115796e-6\n",
      "VFI iteration 20 : dif = 1.2533530480141053e-7\n",
      "VFI iteration 30 : dif = 1.3040221347182523e-8\n",
      " ** VFI converged successfully!! dif = 8.32721980259521e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 3.63293125280606e-5 and B = [0.141371,0.962302,0.116529,0.967636]\n",
      " --- Iteration over ALM coefficient: 15 ---\n",
      "VFI iteration 10 : dif = 9.561501315147325e-7\n",
      "VFI iteration 20 : dif = 9.57708721216477e-8\n",
      "VFI iteration 30 : dif = 1.017394879454514e-8\n",
      " ** VFI converged successfully!! dif = 8.143899776769103e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 2.4483813326064974e-5 and B = [0.14137,0.962302,0.116531,0.967636]\n",
      " --- Iteration over ALM coefficient: 16 ---\n",
      "VFI iteration 10 : dif = 5.508533149622963e-7\n",
      "VFI iteration 20 : dif = 5.388682211560081e-8\n",
      " ** VFI converged successfully!! dif = 8.823121788736898e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.636877019500771e-5 and B = [0.14137,0.962302,0.116532,0.967636]\n",
      " --- Iteration over ALM coefficient: 17 ---\n",
      "VFI iteration 10 : dif = 4.021055701741716e-7\n",
      "VFI iteration 20 : dif = 4.010468046544702e-8\n",
      " ** VFI converged successfully!! dif = 8.30476665214519e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.0984150278420257e-5 and B = [0.141369,0.962302,0.116532,0.967636]\n",
      " --- Iteration over ALM coefficient: 18 ---\n",
      "VFI iteration 10 : dif = 2.3281569383470924e-7\n",
      "VFI iteration 20 : dif = 2.2501069452118827e-8\n",
      " ** VFI converged successfully!! dif = 9.03918362382683e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 7.2048826815218625e-6 and B = [0.141369,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 19 ---\n",
      "VFI iteration 10 : dif = 1.230218344971945e-7\n",
      "VFI iteration 20 : dif = 1.0416044915473321e-8\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " ** VFI converged successfully!! dif = 8.250196970038814e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 4.988788248755371e-6 and B = [0.141369,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 20 ---\n",
      "VFI iteration 10 : dif = 1.0984092568833148e-7\n",
      "VFI iteration 20 : dif = 1.089637180484715e-8\n",
      " ** VFI converged successfully!! dif = 8.687948138685897e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 3.290747322109988e-6 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 21 ---\n",
      "VFI iteration 10 : dif = 8.936746098697768e-8\n",
      "VFI iteration 20 : dif = 9.178563686873531e-9\n",
      " ** VFI converged successfully!! dif = 9.178563686873531e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 2.158295437842961e-6 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 22 ---\n",
      "VFI iteration 10 : dif = 3.8132498048071284e-8\n",
      " ** VFI converged successfully!! dif = 9.028951808431884e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.5509704746619057e-6 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 23 ---\n",
      "VFI iteration 10 : dif = 1.3471407100951183e-8\n",
      " ** VFI converged successfully!! dif = 8.787935712462058e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.0163098228543888e-6 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 24 ---\n",
      "VFI iteration 10 : dif = 4.011184273622348e-8\n",
      " ** VFI converged successfully!! dif = 8.319318567373557e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 6.248587137436257e-7 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 25 ---\n",
      "VFI iteration 10 : dif = 2.6097382033185568e-8\n",
      " ** VFI converged successfully!! dif = 8.564882136852248e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 3.880477443818364e-7 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 26 ---\n",
      "VFI iteration 10 : dif = 2.0421111912583e-8\n",
      " ** VFI converged successfully!! dif = 8.35751734484802e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 2.843728103413268e-7 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 27 ---\n",
      "VFI iteration 10 : dif = 3.812928639490565e-8\n",
      " ** VFI converged successfully!! dif = 8.57767190609593e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 2.919172302912054e-7 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 28 ---\n",
      "VFI iteration 10 : dif = 1.3114174635120435e-8\n",
      " ** VFI converged successfully!! dif = 8.181245902960654e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.6344598458006843e-7 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 29 ---\n",
      "VFI iteration 10 : dif = 5.4228507906373125e-8\n",
      " ** VFI converged successfully!! dif = 9.760071861819597e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 9.524729271959131e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 30 ---\n",
      "VFI iteration 10 : dif = 3.021312977580237e-8\n",
      " ** VFI converged successfully!! dif = 8.285155672638211e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 7.177423369530977e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 31 ---\n",
      "VFI iteration 10 : dif = 2.392872033851745e-8\n",
      " ** VFI converged successfully!! dif = 8.194376732717501e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.0872591149624355e-7 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 32 ---\n",
      "VFI iteration 10 : dif = 5.144397619005758e-8\n",
      " ** VFI converged successfully!! dif = 9.24671894608764e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.570228442410171e-7 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 33 ---\n",
      "VFI iteration 10 : dif = 2.3067457277647918e-8\n",
      " ** VFI converged successfully!! dif = 9.729632211019634e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 7.874108731709129e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 34 ---\n",
      "VFI iteration 10 : dif = 7.674799462620285e-8\n",
      "VFI iteration 20 : dif = 8.989559319161344e-9\n",
      " ** VFI converged successfully!! dif = 8.989559319161344e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 3.674765916561462e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 35 ---\n",
      "VFI iteration 10 : dif = 3.5518326058081584e-8\n",
      " ** VFI converged successfully!! dif = 9.848633908404736e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.1407666089535695e-7 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 36 ---\n",
      "VFI iteration 10 : dif = 5.78716878862906e-8\n",
      " ** VFI converged successfully!! dif = 8.39969516164274e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 3.834874243158204e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 37 ---\n",
      "VFI iteration 10 : dif = 8.088653657978284e-8\n",
      "VFI iteration 20 : dif = 9.574307568982476e-9\n",
      " ** VFI converged successfully!! dif = 9.574307568982476e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 4.068997078165992e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 38 ---\n",
      "VFI iteration 10 : dif = 6.087861947889905e-8\n",
      " ** VFI converged successfully!! dif = 8.969834652816644e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 4.422016042227028e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 39 ---\n",
      " ** VFI converged successfully!! dif = 9.783235555005376e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.2206419956750647e-7 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 40 ---\n",
      "VFI iteration 10 : dif = 7.822649195077247e-8\n",
      "VFI iteration 20 : dif = 9.270820555684622e-9\n",
      " ** VFI converged successfully!! dif = 9.270820555684622e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.8181412958506726e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 41 ---\n",
      "VFI iteration 10 : dif = 1.760491841196199e-8\n",
      " ** VFI converged successfully!! dif = 9.28258714338881e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 5.6862735645091256e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 42 ---\n",
      "VFI iteration 10 : dif = 5.217941634327872e-8\n",
      " ** VFI converged successfully!! dif = 9.463349215366179e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 9.779224406647469e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 43 ---\n",
      "VFI iteration 10 : dif = 2.28354224418581e-8\n",
      " ** VFI converged successfully!! dif = 9.649710364101338e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 4.013947332848211e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 44 ---\n",
      " ** VFI converged successfully!! dif = 7.641517640877282e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 8.247222312018909e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 45 ---\n",
      "VFI iteration 10 : dif = 5.345765430320171e-8\n",
      " ** VFI converged successfully!! dif = 9.702773695607902e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 5.5271162438530475e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 46 ---\n",
      "VFI iteration 10 : dif = 6.705204214085825e-8\n",
      " ** VFI converged successfully!! dif = 9.735970252222614e-9\n",
      "simulating aggregate path ... please wait ... \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "difference of ALM coefficient is 5.700652201678924e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 47 ---\n",
      "VFI iteration 10 : dif = 2.999195203301497e-8\n",
      " ** VFI converged successfully!! dif = 8.3674080997298e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.5016738530437834e-7 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 48 ---\n",
      "VFI iteration 10 : dif = 1.08337872006814e-8\n",
      " ** VFI converged successfully!! dif = 8.718018307263264e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 1.779748049768326e-7 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 49 ---\n",
      "VFI iteration 10 : dif = 1.6313094874931267e-8\n",
      " ** VFI converged successfully!! dif = 8.512699878338026e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 6.603349556044691e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      " --- Iteration over ALM coefficient: 50 ---\n",
      "VFI iteration 10 : dif = 7.444867833328317e-8\n",
      "VFI iteration 20 : dif = 8.854442512529204e-9\n",
      " ** VFI converged successfully!! dif = 8.854442512529204e-9\n",
      "simulating aggregate path ... please wait ... \n",
      "difference of ALM coefficient is 7.825109485382065e-8 and B = [0.141368,0.962303,0.116533,0.967635]\n",
      "----------------------------------------------------------------\n",
      "Iteration over ALM coefficient reached its maximum (50)\n",
      "----------------------------------------------------------------\n",
      "26895.406260 seconds (27.08 G allocations: 12.690 TB, 25.15% gc time)\n"
     ]
    }
   ],
   "source": [
    "# find ALM coefficient\n",
    "@time K_ts = find_ALM_coef!(ksp,kss,z_shocks,eps_shocks,\n",
    "               tol_ump=1e-8,max_iter_ump=10000,\n",
    "               Howard_on=true,Howard_n_iter=20,\n",
    "               tol_B=1e-8, max_iter_B=50,update_B=0.3,\n",
    "               T_discard=1000,print_skip_VFI=10,\n",
    "               method=:VFI, update_k=0.7);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following same exercises show that the main result is same as before"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\" />"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_ALM(ksp.z_grid,z_shocks,\n",
    "         kss.B,K_ts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Approximated aggregate capital law of motion\n",
      "log(K_{t+1})=0.14136817405539825+0.9623027152453734log(K_{t}) in good time (R2 = 0.9999992137407112)\n",
      "log(K_{t+1})=0.11653324573318116+0.9676352636916012log(K_{t}) in bad time (R2 = 0.9999982189177621)\n"
     ]
    }
   ],
   "source": [
    "#kss.B  # Regression coefficient\n",
    "println(\"Approximated aggregate capital law of motion\")\n",
    "println(\"log(K_{t+1})=$(kss.B[1])+$(kss.B[2])log(K_{t}) in good time (R2 = $(kss.R2[1]))\")\n",
    "println(\"log(K_{t+1})=$(kss.B[3])+$(kss.B[4])log(K_{t}) in bad time (R2 = $(kss.R2[2]))\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "save(\"result_VFI.jld\",\"kss\",kss)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean of capital implied by regression is 39.46272307237643\n",
      "mean of capital implied by simulation is 39.70193508699299\n"
     ]
    }
   ],
   "source": [
    "# Compute mean of capital implied by regression\n",
    "mc=MarkovChain(ksp.TransMat.Pz)\n",
    "sd=stationary_distributions(mc)[1]\n",
    "logKg=kss.B[1]/(1-kss.B[2])\n",
    "logKb=kss.B[3]/(1-kss.B[4])\n",
    "meanK_reg=exp(sd[1]*logKg+sd[2]*logKb)\n",
    "meanK_sim=mean(K_ts[1001:end])\n",
    "println(\"mean of capital implied by regression is $meanK_reg\")\n",
    "println(\"mean of capital implied by simulation is $meanK_sim\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figures in Krusell-Smith"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figure 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img 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\" />"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_Fig1(ksp,kss,K_ts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figure 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img 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\" />"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_Fig2(ksp,kss,40)"
   ]
  },
  {
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